Now using py files, for automation

author Neil Smith <neil.git@njae.me.uk>

Mon, 15 Feb 2021 09:28:17 +0000 (09:28 +0000)

committer Neil Smith <neil.git@njae.me.uk>

Mon, 15 Feb 2021 09:28:17 +0000 (09:28 +0000)
author Neil Smith <neil.git@njae.me.uk>
Mon, 15 Feb 2021 09:28:17 +0000 (09:28 +0000)
committer Neil Smith <neil.git@njae.me.uk>
Mon, 15 Feb 2021 09:28:17 +0000 (09:28 +0000)
diff --git a/.gitignore b/.gitignore

index 11da1617af4ffd18f33d94ac1ae176fc906cb90b..d20439c8980fc6e75b5ad0763da1321fc729ac88 100644 (file)
--- a/.gitignore
+++ b/.gitignore
@@ -12,4 +12,8 @@
  *xlsx
  *ods
  *csv
  *xlsx
  *ods
  *csv
+*png
+*mp4
+*js
+*json
  
  
diff --git a/cases_excess_deaths.ipynb b/cases_excess_deaths.ipynb

new file mode 100644 (file)

index 0000000..cf1b291
--- /dev/null
+++ b/cases_excess_deaths.ipynb
@@ -0,0 +1,906 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "import itertools\n",
+    "import collections\n",
+    "import json\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "from scipy.stats import gmean\n",
+    "import datetime\n",
+    "\n",
+    "import matplotlib as mpl\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline\n",
+    "%load_ext sql"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Connected: covid@covid'"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql $connection_string"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 144,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# res = %sql select report_date, deaths_weekly as deaths_covid from weekly_cases where geo_id = 'UK' order by report_date\n",
+    "# deaths_cases = res.DataFrame()\n",
+    "# deaths_cases.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 165,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "53 rows affected.\n",
+      "Returning data to local variable res\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%sql res << select sum(new_deaths) as covid_deaths, extract(week from (date_trunc('day', date) + interval '2 day')) as eweek\n",
+    "from uk_data \n",
+    "where extract(year from date) = 2020 \n",
+    "group by eweek\n",
+    "order by eweek"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 166,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>covid_deaths</th>\n",
+       "      <th>eweek</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>3068</td>\n",
+       "      <td>49.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>2906</td>\n",
+       "      <td>50.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>3035</td>\n",
+       "      <td>51.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>3708</td>\n",
+       "      <td>52.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>3263</td>\n",
+       "      <td>53.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    covid_deaths  eweek\n",
+       "48          3068   49.0\n",
+       "49          2906   50.0\n",
+       "50          3035   51.0\n",
+       "51          3708   52.0\n",
+       "52          3263   53.0"
+      ]
+     },
+     "execution_count": 166,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_covid = res.DataFrame()\n",
+    "deaths_covid.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 167,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "53 rows affected.\n",
+      "Returning data to local variable res\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%sql res << select week, avg(ydd) as deaths_mean\n",
+    "from (select week, year, sum(deaths) as ydd\n",
+    "     from all_causes_deaths\n",
+    "     group by year, week) as year_deaths\n",
+    "where year < 2020\n",
+    "group by week\n",
+    "order by week"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 168,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>deaths_mean</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>13870.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>15783.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>14985.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>14457.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>13841.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week  deaths_mean\n",
+       "0     1      13870.2\n",
+       "1     2      15783.4\n",
+       "2     3      14985.8\n",
+       "3     4      14457.2\n",
+       "4     5      13841.0"
+      ]
+     },
+     "execution_count": 168,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "mean_deaths = res.DataFrame()\n",
+    "mean_deaths['deaths_mean'] = pd.to_numeric(mean_deaths.deaths_mean)\n",
+    "mean_deaths.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 169,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "week             int64\n",
+       "deaths_mean    float64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 169,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "mean_deaths.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 170,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "53 rows affected.\n",
+      "Returning data to local variable res\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%sql res << select ac.week, wk.date_up_to, sum(ac.deaths) as deaths_2020\n",
+    "from all_causes_deaths ac, \n",
+    "    (select week, date_up_to \n",
+    "     from all_causes_deaths\n",
+    "     where year = 2020 and nation = 'England') as wk\n",
+    "where year = 2020 and ac.week = wk.week\n",
+    "group by ac.week, wk.date_up_to\n",
+    "order by ac.week"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 171,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths_2020</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-01-03</td>\n",
+       "      <td>13768</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2020-01-10</td>\n",
+       "      <td>16020</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2020-01-17</td>\n",
+       "      <td>14723</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2020-01-24</td>\n",
+       "      <td>13429</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2020-01-31</td>\n",
+       "      <td>13123</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week  date_up_to  deaths_2020\n",
+       "0     1  2020-01-03        13768\n",
+       "1     2  2020-01-10        16020\n",
+       "2     3  2020-01-17        14723\n",
+       "3     4  2020-01-24        13429\n",
+       "4     5  2020-01-31        13123"
+      ]
+     },
+     "execution_count": 171,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_2020 = res.DataFrame()\n",
+    "deaths_2020.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 172,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths_2020</th>\n",
+       "      <th>deaths_mean</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-01-03</td>\n",
+       "      <td>13768</td>\n",
+       "      <td>13870.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2020-01-10</td>\n",
+       "      <td>16020</td>\n",
+       "      <td>15783.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2020-01-17</td>\n",
+       "      <td>14723</td>\n",
+       "      <td>14985.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2020-01-24</td>\n",
+       "      <td>13429</td>\n",
+       "      <td>14457.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2020-01-31</td>\n",
+       "      <td>13123</td>\n",
+       "      <td>13841.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week  date_up_to  deaths_2020  deaths_mean\n",
+       "0     1  2020-01-03        13768      13870.2\n",
+       "1     2  2020-01-10        16020      15783.4\n",
+       "2     3  2020-01-17        14723      14985.8\n",
+       "3     4  2020-01-24        13429      14457.2\n",
+       "4     5  2020-01-31        13123      13841.0"
+      ]
+     },
+     "execution_count": 172,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_2020 = deaths_2020.merge(mean_deaths, how='outer', on='week')\n",
+    "deaths_2020.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 173,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths_2020</th>\n",
+       "      <th>deaths_mean</th>\n",
+       "      <th>deaths_covid</th>\n",
+       "      <th>excess</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>week</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2020-01-03</td>\n",
+       "      <td>13768</td>\n",
+       "      <td>13870.2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-102.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2020-01-10</td>\n",
+       "      <td>16020</td>\n",
+       "      <td>15783.4</td>\n",
+       "      <td>0</td>\n",
+       "      <td>236.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2020-01-17</td>\n",
+       "      <td>14723</td>\n",
+       "      <td>14985.8</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-262.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2020-01-24</td>\n",
+       "      <td>13429</td>\n",
+       "      <td>14457.2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-1028.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2020-01-31</td>\n",
+       "      <td>13123</td>\n",
+       "      <td>13841.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>-718.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      date_up_to  deaths_2020  deaths_mean  deaths_covid  excess\n",
+       "week                                                            \n",
+       "1     2020-01-03        13768      13870.2             0  -102.2\n",
+       "2     2020-01-10        16020      15783.4             0   236.6\n",
+       "3     2020-01-17        14723      14985.8             0  -262.8\n",
+       "4     2020-01-24        13429      14457.2             0 -1028.2\n",
+       "5     2020-01-31        13123      13841.0             0  -718.0"
+      ]
+     },
+     "execution_count": 173,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_2020['deaths_covid'] = deaths_covid.covid_deaths\n",
+    "deaths_2020['excess'] = deaths_2020.deaths_2020 - deaths_2020.deaths_mean\n",
+    "deaths_2020.set_index('week', inplace=True)\n",
+    "deaths_2020.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 174,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths_2020</th>\n",
+       "      <th>deaths_mean</th>\n",
+       "      <th>deaths_covid</th>\n",
+       "      <th>excess</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>week</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>2020-12-04</td>\n",
+       "      <td>13986</td>\n",
+       "      <td>12157.0</td>\n",
+       "      <td>3068</td>\n",
+       "      <td>1829.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>2020-12-11</td>\n",
+       "      <td>13942</td>\n",
+       "      <td>12328.8</td>\n",
+       "      <td>2906</td>\n",
+       "      <td>1613.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>2020-12-18</td>\n",
+       "      <td>14658</td>\n",
+       "      <td>13159.2</td>\n",
+       "      <td>3035</td>\n",
+       "      <td>1498.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>2020-12-25</td>\n",
+       "      <td>13035</td>\n",
+       "      <td>9231.2</td>\n",
+       "      <td>3708</td>\n",
+       "      <td>3803.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>2021-01-01</td>\n",
+       "      <td>11580</td>\n",
+       "      <td>8774.0</td>\n",
+       "      <td>3263</td>\n",
+       "      <td>2806.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      date_up_to  deaths_2020  deaths_mean  deaths_covid  excess\n",
+       "week                                                            \n",
+       "49    2020-12-04        13986      12157.0          3068  1829.0\n",
+       "50    2020-12-11        13942      12328.8          2906  1613.2\n",
+       "51    2020-12-18        14658      13159.2          3035  1498.8\n",
+       "52    2020-12-25        13035       9231.2          3708  3803.8\n",
+       "53    2021-01-01        11580       8774.0          3263  2806.0"
+      ]
+     },
+     "execution_count": 174,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_2020.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 175,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "date_up_to       object\n",
+       "deaths_2020       int64\n",
+       "deaths_mean     float64\n",
+       "deaths_covid      int64\n",
+       "excess          float64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 175,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_2020.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 176,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='week'>"
+      ]
+     },
+     "execution_count": 176,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "deaths_2020[['deaths_covid', 'excess']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 177,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths_2020</th>\n",
+       "      <th>deaths_mean</th>\n",
+       "      <th>deaths_covid</th>\n",
+       "      <th>excess</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>week</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>2020-12-04</td>\n",
+       "      <td>13986</td>\n",
+       "      <td>12157.0</td>\n",
+       "      <td>3068</td>\n",
+       "      <td>1829.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>2020-12-11</td>\n",
+       "      <td>13942</td>\n",
+       "      <td>12328.8</td>\n",
+       "      <td>2906</td>\n",
+       "      <td>1613.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>2020-12-18</td>\n",
+       "      <td>14658</td>\n",
+       "      <td>13159.2</td>\n",
+       "      <td>3035</td>\n",
+       "      <td>1498.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>2020-12-25</td>\n",
+       "      <td>13035</td>\n",
+       "      <td>9231.2</td>\n",
+       "      <td>3708</td>\n",
+       "      <td>3803.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>2021-01-01</td>\n",
+       "      <td>11580</td>\n",
+       "      <td>8774.0</td>\n",
+       "      <td>3263</td>\n",
+       "      <td>2806.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      date_up_to  deaths_2020  deaths_mean  deaths_covid  excess\n",
+       "week                                                            \n",
+       "49    2020-12-04        13986      12157.0          3068  1829.0\n",
+       "50    2020-12-11        13942      12328.8          2906  1613.2\n",
+       "51    2020-12-18        14658      13159.2          3035  1498.8\n",
+       "52    2020-12-25        13035       9231.2          3708  3803.8\n",
+       "53    2021-01-01        11580       8774.0          3263  2806.0"
+      ]
+     },
+     "execution_count": 177,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_2020.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/cases_per_day_with_lockdown.png b/cases_per_day_with_lockdown.png

deleted file mode 100644 (file)

index 8842d43..0000000

Binary files a/cases_per_day_with_lockdown.png and /dev/null differ
diff --git a/covid-old.ipynb b/covid-old.ipynb

new file mode 100644 (file)

index 0000000..954e0ea
--- /dev/null
+++ b/covid-old.ipynb
@@ -0,0 +1,3562 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "source": [
+    "Data from [European Centre for Disease Prevention and Control](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "import itertools\n",
+    "import collections\n",
+    "import json\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "from scipy.stats import gmean\n",
+    "import datetime\n",
+    "\n",
+    "import matplotlib as mpl\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "DEATH_COUNT_THRESHOLD = 10\n",
+    "COUNTRIES_CORE = 'IT DE UK ES IE FR BE'.split()\n",
+    "COUNTRIES_NORDIC = 'SE NO DK FI UK'.split()\n",
+    "COUNTRIES_FRIENDS = 'IT UK ES BE SI MX'.split()\n",
+    "# COUNTRIES_FRIENDS = 'IT UK ES BE SI PT'.split()\n",
+    "\n",
+    "COUNTRIES_AMERICAS = ['AG', 'AR', 'AW', 'BS', 'BB', 'BZ', 'BM', 'BO', 'BR', 'VG', 'KY', # excluding Canada and USA\n",
+    "       'CL', 'CO', 'CR', 'CU', 'CW', 'DM', 'DO', 'EC', 'SV', 'GL', 'GD', 'GT',\n",
+    "       'GY', 'HT', 'HN', 'JM', 'MX', 'MS', 'NI', 'PA', 'PY', 'PE', 'PR', 'KN',\n",
+    "       'LC', 'VC', 'SX', 'SR', 'TT', 'TC', 'VI', 'UY', 'VE']\n",
+    "COUNTRIES_OF_INTEREST = list(set(COUNTRIES_CORE + COUNTRIES_FRIENDS))\n",
+    "COUNTRIES_ALL = list(set(COUNTRIES_CORE + COUNTRIES_FRIENDS + COUNTRIES_NORDIC + COUNTRIES_AMERICAS))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4843,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
+      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
+      "100  553k  100  553k    0     0   564k      0 --:--:-- --:--:-- --:--:--  564k\n"
+     ]
+    }
+   ],
+   "source": [
+    "!curl https://opendata.ecdc.europa.eu/covid19/casedistribution/csv/ > covid.csv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4844,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# First col is a date, treat geoId of NA as 'Namibia', not \"NA\" value\n",
+    "raw_data = pd.read_csv('covid.csv', \n",
+    "                       parse_dates=[0], dayfirst=True,\n",
+    "                       keep_default_na=False, na_values = [''],\n",
+    "#                        dtype = {'day': np.int64, \n",
+    "#                                 'month': np.int64, \n",
+    "#                                 'year': np.int64, \n",
+    "#                                 'cases': np.int64, \n",
+    "#                                 'deaths': np.int64, \n",
+    "#                                 'countriesAndTerritories': str, \n",
+    "#                                 'geoId': str, \n",
+    "#                                 'countryterritoryCode': str, \n",
+    "#                                 'popData2019': np.int64, \n",
+    "#                                 'continentExp': str, \n",
+    "#                                 }\n",
+    "                      )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4845,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "89150"
+      ]
+     },
+     "execution_count": 4845,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data.size"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4846,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "raw_data.fillna(0, inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4847,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>dateRep</th>\n",
+       "      <th>year_week</th>\n",
+       "      <th>cases_weekly</th>\n",
+       "      <th>deaths_weekly</th>\n",
+       "      <th>countriesAndTerritories</th>\n",
+       "      <th>geoId</th>\n",
+       "      <th>countryterritoryCode</th>\n",
+       "      <th>popData2019</th>\n",
+       "      <th>continentExp</th>\n",
+       "      <th>notification_rate_per_100000_population_14-days</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>2020-12-14</td>\n",
+       "      <td>2020-50</td>\n",
+       "      <td>1757</td>\n",
+       "      <td>71</td>\n",
+       "      <td>Afghanistan</td>\n",
+       "      <td>AF</td>\n",
+       "      <td>AFG</td>\n",
+       "      <td>38041757.0</td>\n",
+       "      <td>Asia</td>\n",
+       "      <td>9.01</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-12-07</td>\n",
+       "      <td>2020-49</td>\n",
+       "      <td>1672</td>\n",
+       "      <td>137</td>\n",
+       "      <td>Afghanistan</td>\n",
+       "      <td>AF</td>\n",
+       "      <td>AFG</td>\n",
+       "      <td>38041757.0</td>\n",
+       "      <td>Asia</td>\n",
+       "      <td>7.22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>2020-11-30</td>\n",
+       "      <td>2020-48</td>\n",
+       "      <td>1073</td>\n",
+       "      <td>68</td>\n",
+       "      <td>Afghanistan</td>\n",
+       "      <td>AF</td>\n",
+       "      <td>AFG</td>\n",
+       "      <td>38041757.0</td>\n",
+       "      <td>Asia</td>\n",
+       "      <td>6.42</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>2020-11-23</td>\n",
+       "      <td>2020-47</td>\n",
+       "      <td>1368</td>\n",
+       "      <td>69</td>\n",
+       "      <td>Afghanistan</td>\n",
+       "      <td>AF</td>\n",
+       "      <td>AFG</td>\n",
+       "      <td>38041757.0</td>\n",
+       "      <td>Asia</td>\n",
+       "      <td>6.66</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>2020-11-16</td>\n",
+       "      <td>2020-46</td>\n",
+       "      <td>1164</td>\n",
+       "      <td>61</td>\n",
+       "      <td>Afghanistan</td>\n",
+       "      <td>AF</td>\n",
+       "      <td>AFG</td>\n",
+       "      <td>38041757.0</td>\n",
+       "      <td>Asia</td>\n",
+       "      <td>4.65</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     dateRep year_week  cases_weekly  deaths_weekly countriesAndTerritories  \\\n",
+       "0 2020-12-14   2020-50          1757             71             Afghanistan   \n",
+       "1 2020-12-07   2020-49          1672            137             Afghanistan   \n",
+       "2 2020-11-30   2020-48          1073             68             Afghanistan   \n",
+       "3 2020-11-23   2020-47          1368             69             Afghanistan   \n",
+       "4 2020-11-16   2020-46          1164             61             Afghanistan   \n",
+       "\n",
+       "  geoId countryterritoryCode  popData2019 continentExp  \\\n",
+       "0    AF                  AFG   38041757.0         Asia   \n",
+       "1    AF                  AFG   38041757.0         Asia   \n",
+       "2    AF                  AFG   38041757.0         Asia   \n",
+       "3    AF                  AFG   38041757.0         Asia   \n",
+       "4    AF                  AFG   38041757.0         Asia   \n",
+       "\n",
+       "   notification_rate_per_100000_population_14-days  \n",
+       "0                                             9.01  \n",
+       "1                                             7.22  \n",
+       "2                                             6.42  \n",
+       "3                                             6.66  \n",
+       "4                                             4.65  "
+      ]
+     },
+     "execution_count": 4847,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4848,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "dateRep                                            datetime64[ns]\n",
+       "year_week                                                  object\n",
+       "cases_weekly                                                int64\n",
+       "deaths_weekly                                               int64\n",
+       "countriesAndTerritories                                    object\n",
+       "geoId                                                      object\n",
+       "countryterritoryCode                                       object\n",
+       "popData2019                                               float64\n",
+       "continentExp                                               object\n",
+       "notification_rate_per_100000_population_14-days           float64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 4848,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4849,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "ename": "KeyError",
+     "evalue": "'Only a column name can be used for the key in a dtype mappings argument.'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-4849-4ccdef75f4f0>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      9\u001b[0m     \u001b[0;34m'countryterritoryCode'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     10\u001b[0m     \u001b[0;34m'popData2019'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mint64\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 11\u001b[0;31m     'continentExp': str })\n\u001b[0m",
+      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36mastype\u001b[0;34m(self, dtype, copy, errors, **kwargs)\u001b[0m\n\u001b[1;32m   5855\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0mcol_name\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5856\u001b[0m                     raise KeyError(\n\u001b[0;32m-> 5857\u001b[0;31m                         \u001b[0;34m\"Only a column name can be used for the \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   5858\u001b[0m                         \u001b[0;34m\"key in a dtype mappings argument.\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5859\u001b[0m                     )\n",
+      "\u001b[0;31mKeyError\u001b[0m: 'Only a column name can be used for the key in a dtype mappings argument.'"
+     ]
+    }
+   ],
+   "source": [
+    "# raw_data = raw_data.astype({'dateRep': np.datetime64, \n",
+    "#     'day': np.int64, \n",
+    "#     'month': np.int64, \n",
+    "#     'year': np.int64, \n",
+    "#     'cases': np.int64, \n",
+    "#     'deaths': np.int64, \n",
+    "#     'countriesAndTerritories': str, \n",
+    "#     'geoId': str, \n",
+    "#     'countryterritoryCode': str, \n",
+    "#     'popData2019': np.int64, \n",
+    "#     'continentExp': str })\n",
+    "raw_data = raw_data.astype({'dateRep': np.datetime64, \n",
+    "    'day': np.int64, \n",
+    "    'month': np.int64, \n",
+    "    'year': np.int64, \n",
+    "    'cases': np.int64, \n",
+    "    'deaths': np.int64, \n",
+    "    'countriesAndTerritories': str, \n",
+    "    'geoId': str, \n",
+    "    'countryterritoryCode': str, \n",
+    "    'popData2019': np.int64, \n",
+    "    'continentExp': str })"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "raw_data.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "raw_data[((raw_data.geoId == 'UK') & (raw_data.dateRep >= '2020-07-10'))]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# raw_data = raw_data[~ ((raw_data.geoId == 'ES') & (raw_data.dateRep >= '2020-05-22'))]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "base_data = raw_data.set_index(['geoId', 'dateRep'])\n",
+    "base_data.sort_index(inplace=True)\n",
+    "base_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "base_data.loc['ES'].loc['2020-05-10':]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "countries = raw_data[['geoId', 'countriesAndTerritories', 'popData2019', 'continentExp']]\n",
+    "countries = countries[countries['popData2019'] != '']\n",
+    "countries = countries.drop_duplicates()\n",
+    "countries.set_index('geoId', inplace=True)\n",
+    "countries = countries.astype({'popData2019': 'int64'})\n",
+    "countries.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "countries.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "countries[countries.countriesAndTerritories == 'Finland']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "countries.loc[COUNTRIES_OF_INTEREST]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "countries[countries.continentExp == 'America'].index"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_date = base_data[['cases', 'deaths']]\n",
+    "data_by_date.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_date.loc['UK']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# data_by_date.deaths.drop_duplicates().sort_values().to_csv('dth.csv', header=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_date.groupby(level=0).cumsum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_date = data_by_date.merge(\n",
+    "    data_by_date.groupby(level=0).cumsum(), \n",
+    "    suffixes=('', '_culm'), \n",
+    "    left_index=True, right_index=True)\n",
+    "data_by_date"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_date = data_by_date.merge(\n",
+    "    data_by_date[['cases', 'deaths']].groupby(level=0).diff(), \n",
+    "    suffixes=('', '_diff'), \n",
+    "    left_index=True, right_index=True)\n",
+    "data_by_date"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_date.loc['UK', '2020-04-17']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_date.loc['UK']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# data_by_date[data_by_date.deaths_culm > DEATH_COUNT_THRESHOLD]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# days_since_threshold = data_by_date[data_by_date.deaths_culm > DEATH_COUNT_THRESHOLD].groupby(level=0).cumcount()\n",
+    "# days_since_threshold.rename('since_threshold', inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "dbd = data_by_date[data_by_date.deaths_culm > DEATH_COUNT_THRESHOLD].reset_index(level=1)\n",
+    "dbd['since_threshold'] = dbd.dateRep\n",
+    "dbd.set_index('dateRep', append=True, inplace=True)\n",
+    "dbd.sort_index(inplace=True)\n",
+    "days_since_threshold = dbd.groupby(level=0).diff().since_threshold.dt.days.fillna(0).astype(int).groupby(level=0).cumsum()\n",
+    "# days_since_threshold.groupby(level=0).cumsum()\n",
+    "\n",
+    "# days_since_threshold = dbd.rename('since_threshold')\n",
+    "days_since_threshold"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# days_since_threshold = (data_by_date[data_by_date.deaths_culm > DEATH_COUNT_THRESHOLD]\n",
+    "#                         .reset_index(level=1).groupby(level=0)\n",
+    "#                         .diff().dateRep.dt.days\n",
+    "#                         .groupby(level=0).cumcount()\n",
+    "#                        )\n",
+    "# days_since_threshold.rename('since_threshold', inplace=True)\n",
+    "# days_since_threshold"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_since_threshold = data_by_date.merge(days_since_threshold, \n",
+    "    left_index=True, right_index=True)\n",
+    "data_since_threshold"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_since_threshold = data_since_threshold.set_index('since_threshold', append=True\n",
+    "                              ).reorder_levels(['since_threshold', 'geoId', 'dateRep']\n",
+    "                                              ).reset_index('dateRep')\n",
+    "data_since_threshold.sort_index(inplace=True)\n",
+    "data_since_threshold"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT']), :]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_since_threshold.loc[(slice(None), ['ES']), :].tail(8)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT']), ['deaths_culm']].unstack().plot(logy=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# deaths = data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT', 'IE']), ['deaths_culm']].unstack().xs('deaths_culm', axis=1, drop_level=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "deaths = data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['deaths_culm']].unstack().sort_index().xs('deaths_culm', axis=1, drop_level=True)\n",
+    "deaths_by_date = data_by_date.loc[COUNTRIES_ALL, ['deaths_culm']].unstack().sort_index().xs('deaths_culm', axis=1, drop_level=True).T"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "cases = data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['cases_culm']].unstack().sort_index().xs('cases_culm', axis=1, drop_level=True)\n",
+    "cases_by_date = data_by_date.loc[ COUNTRIES_ALL, ['cases_culm']].unstack().sort_index().xs('cases_culm', axis=1, drop_level=True).T"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "COUNTRIES_AMERICAS_DEAD = list(set(deaths.columns) & set(COUNTRIES_AMERICAS))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_since_threshold.reset_index().merge(countries, on='geoId').set_index(['since_threshold', 'geoId'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_since_threshold.reset_index().merge(countries, on='geoId').set_index(['since_threshold', 'geoId']).sort_index(inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_since_threshold_per_capita = data_since_threshold.reset_index().merge(countries, on='geoId').set_index(['since_threshold', 'geoId'])\n",
+    "data_since_threshold_per_capita['cases_culm_pc'] = data_since_threshold_per_capita.cases_culm / data_since_threshold_per_capita.popData2019\n",
+    "data_since_threshold_per_capita['deaths_culm_pc'] = data_since_threshold_per_capita.deaths_culm / data_since_threshold_per_capita.popData2019\n",
+    "data_since_threshold_per_capita"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "deaths_pc = data_since_threshold_per_capita.loc[(slice(None), ['UK', 'DE', 'IT', 'IE']), ['deaths_culm_pc']].unstack().sort_index().xs('deaths_culm_pc', axis=1, drop_level=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "deaths_pc.index"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "deaths_pc = data_since_threshold_per_capita.loc[(slice(None), COUNTRIES_ALL), ['deaths_culm_pc']].unstack().xs('deaths_culm_pc', axis=1, drop_level=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "deaths[COUNTRIES_CORE].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "deaths[COUNTRIES_FRIENDS].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths[COUNTRIES_FRIENDS].plot(figsize=(10, 6), title=\"Total deaths, linear\")\n",
+    "ax.set_xlabel(f\"Days since {DEATH_COUNT_THRESHOLD} deaths\")\n",
+    "for c in COUNTRIES_FRIENDS:\n",
+    "    lvi = deaths[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = deaths[c][lvi], s = f\"{c}: {deaths[c][lvi]:.0f}\")\n",
+    "# plt.savefig('covid_deaths_total_linear.png')    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths[COUNTRIES_CORE].plot(figsize=(10, 6), title=\"Total deaths, linear\")\n",
+    "ax.set_xlabel(f\"Days since {DEATH_COUNT_THRESHOLD} deaths\")\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = deaths[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = deaths[c][lvi], s = f\"{c}: {deaths[c][lvi]:.0f}\")\n",
+    "# plt.savefig('covid_deaths_total_linear.png')    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths_by_date.loc['2020-03-15':, COUNTRIES_CORE].plot(figsize=(10, 6), title=\"Total deaths, linear\")\n",
+    "# data_by_date.loc[COUNTRIES_CORE]\n",
+    "# deaths_by_date = data_by_date.loc[COUNTRIES_ALL, ['deaths_culm']].unstack().sort_index().xs('deaths_culm', axis=1, drop_level=True)\n",
+    "ax.set_xlabel(f\"Date\")\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = deaths_by_date[c].last_valid_index()\n",
+    "    ax.text(x = lvi + pd.Timedelta(days=1), y = deaths_by_date[c][lvi], s = f\"{c}: {deaths_by_date[c][lvi]:.0f}\")\n",
+    "plt.savefig('covid_deaths_total_linear.png')    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "deaths_prime = deaths[COUNTRIES_CORE].copy()\n",
+    "deaths_prime.loc[73:, 'ES'] = np.NaN\n",
+    "# deaths_prime['ES'][70:]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths_prime[COUNTRIES_CORE].plot(figsize=(10, 6), title=\"Total deaths, linear\")\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = deaths_prime[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = deaths_prime[c][lvi], s = f\"{c}: {deaths_prime[c][lvi]:.0f}\")\n",
+    "# plt.savefig('covid_deaths_total_linear.png')    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = cases[COUNTRIES_CORE].plot(figsize=(10, 6), title=\"Total cases, linear\")\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = cases[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = cases[c][lvi], s = c)\n",
+    "plt.savefig('covid_cases_total_linear.png')    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths[COUNTRIES_AMERICAS_DEAD].plot(figsize=(10, 6), title=\"Total deaths, linear\")\n",
+    "for c in COUNTRIES_AMERICAS_DEAD:\n",
+    "    lvi = deaths[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)\n",
+    "# plt.savefig('covid_deaths_total_linear.png')    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths[COUNTRIES_CORE + ['BR', 'MX']].plot(figsize=(10, 6), title=\"Total deaths, linear\")\n",
+    "for c in COUNTRIES_CORE + ['BR', 'MX']:\n",
+    "    lvi = deaths[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)\n",
+    "# plt.savefig('covid_deaths_total_linear.png')    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths[COUNTRIES_NORDIC].plot(figsize=(10, 6), title=\"Total deaths, linear\")\n",
+    "for c in COUNTRIES_NORDIC:\n",
+    "    lvi = deaths[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)\n",
+    "# plt.savefig('covid_deaths_total_linear.png')    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths[COUNTRIES_OF_INTEREST].plot(figsize=(10, 6), title=\"Total deaths, linear\")\n",
+    "for c in COUNTRIES_OF_INTEREST:\n",
+    "    lvi = deaths[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)\n",
+    "plt.savefig('covid_deaths_total_linear_of_interest.png') "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths[COUNTRIES_CORE].plot(logy=True, figsize=(10, 6), title=\"Total deaths, log\")\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = deaths[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)\n",
+    "\n",
+    "plt.savefig('covid_deaths_total_log.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ylim = (5*10**3, 5*10**4)\n",
+    "ax = deaths[COUNTRIES_CORE].plot(logy=True, figsize=(10, 6), ylim=ylim, title=\"Total deaths, log\")\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = deaths[c].last_valid_index()\n",
+    "    if ylim[0] < deaths[c][lvi] < ylim[1]:\n",
+    "        ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)\n",
+    "\n",
+    "# plt.savefig('covid_deaths_total_log.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths[COUNTRIES_FRIENDS].plot(logy=True, figsize=(10, 6), title=\"Total deaths, log\")\n",
+    "for c in COUNTRIES_FRIENDS:\n",
+    "    lvi = deaths[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)\n",
+    "\n",
+    "# plt.savefig('covid_deaths_total_log.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths[COUNTRIES_NORDIC].plot(logy=True, figsize=(10, 6), title=\"Total deaths, log\")\n",
+    "for c in COUNTRIES_NORDIC:\n",
+    "    lvi = deaths[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)\n",
+    "\n",
+    "# plt.savefig('covid_deaths_total_log.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths[COUNTRIES_OF_INTEREST].plot(logy=True, figsize=(10, 6), title=\"Total deaths, log\")\n",
+    "for c in COUNTRIES_OF_INTEREST:\n",
+    "    lvi = deaths[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)\n",
+    "\n",
+    "plt.savefig('covid_deaths_total_log.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths_pc.plot(figsize=(10, 6), title=\"Deaths per capita, linear\")\n",
+    "for c in deaths_pc.columns:\n",
+    "    lvi = deaths_pc[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = deaths_pc[c][lvi], s = c)\n",
+    "plt.savefig('covid_deaths_per_capita_linear.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths_pc.plot(logy=True, figsize=(10, 6), title=\"Deaths per capita, log\")\n",
+    "for c in deaths_pc.columns:\n",
+    "    lvi = deaths_pc[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = deaths_pc[c][lvi], s = c)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "deaths_pc[['UK', 'IE']].plot( figsize=(10, 6), title=\"Deaths per capita, linear\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "deaths_pc[['UK', 'IE']].plot(logy=True, figsize=(10, 6), title=\"Deaths per capita, log\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "deaths[['UK', 'ES', 'IT']].plot(logy=True, figsize=(10, 6), title=\"Deaths, log\")\n",
+    "plt.savefig('covid_deaths_selected_log.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "deaths[['UK', 'ES', 'IT', 'MX']].plot(logy=True, figsize=(10, 6), title=\"Deaths, log\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT']), :]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_since_threshold['deaths_m4'] = data_since_threshold.groupby(level=1)['deaths'].transform(lambda x: x.rolling(4, 1).mean())\n",
+    "data_since_threshold['deaths_m7'] = data_since_threshold.groupby(level=1)['deaths'].transform(lambda x: x.rolling(7, 1).mean())\n",
+    "data_since_threshold['cases_m7'] = data_since_threshold.groupby(level=1)['cases'].transform(lambda x: x.rolling(7, 1).mean())\n",
+    "# data_since_threshold['deaths_diff_m4'] = data_since_threshold.groupby(level=1)['deaths_diff'].transform(lambda x: x.rolling(4, 1).mean())\n",
+    "# data_since_threshold['deaths_diff_m7'] = data_since_threshold.groupby(level=1)['deaths_diff'].transform(lambda x: x.rolling(7, 1).mean())\n",
+    "data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT']), :]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "deaths_m4 = (data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['deaths_m4']]\n",
+    "             .unstack().sort_index().xs('deaths_m4', axis=1, drop_level=True))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "deaths_m7 = (data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['deaths_m7']]\n",
+    "             .unstack().sort_index().xs('deaths_m7', axis=1, drop_level=True))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "cases_m7 = (data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['cases_m7']]\n",
+    "             .unstack().sort_index().xs('cases_m7', axis=1, drop_level=True))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_date['cases_m7'] = data_by_date.groupby(level=0)['cases'].transform(lambda x: x.rolling(7, 1).mean())\n",
+    "data_by_date['deaths_m7'] = data_by_date.groupby(level=0)['deaths'].transform(lambda x: x.rolling(7, 1).mean())\n",
+    "data_by_date"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_date.loc[('UK', '2020-07-15'):'UK', 'cases'].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "cases_by_date_m7 = data_by_date.loc[COUNTRIES_ALL, 'cases_m7'].unstack(level=0).sort_index()\n",
+    "cases_by_date_m7[COUNTRIES_CORE].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "deaths_by_date_m7 = data_by_date.loc[COUNTRIES_ALL, 'deaths_m7'].unstack(level=0).sort_index()\n",
+    "deaths_by_date_m7[COUNTRIES_CORE].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths_m4.plot(figsize=(10, 6), title=\"Deaths per day, 4 day moving average\")\n",
+    "for c in deaths_m4.columns:\n",
+    "    lvi = deaths_m4[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = deaths_m4[c][lvi], s = c)\n",
+    "plt.savefig('covid_deaths_per_day.png') "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths_m4[COUNTRIES_CORE].plot(figsize=(10, 6), title=\"Deaths per day, 4 day moving average\")\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = deaths_m4[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = deaths_m4[c][lvi], s = c)\n",
+    "plt.savefig('covid_deaths_per_day-core.png') "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths_m4[COUNTRIES_FRIENDS].plot(figsize=(10, 6), title=\"Deaths per day, 4 day moving average\")\n",
+    "for c in COUNTRIES_FRIENDS:\n",
+    "    lvi = deaths_m4[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = deaths_m4[c][lvi], s = c)\n",
+    "# plt.savefig('covid_deaths_per_day-friends.png') "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "C7s = 'ES FR IT UK'.split()\n",
+    "ax = deaths_m7[C7s].plot(figsize=(10, 6), title=\"Deaths per day, 7 day moving average\")\n",
+    "for c in C7s:\n",
+    "    lvi = deaths_m7[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = c)\n",
+    "# plt.savefig('covid_deaths_per_day-friends.png') "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths_m7[COUNTRIES_CORE].plot(figsize=(10, 6), title=\"Deaths per day, 7 day moving average\")\n",
+    "ax.set_xlabel(f\"Days since {DEATH_COUNT_THRESHOLD} deaths\")\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = deaths_m7[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = c)\n",
+    "# plt.axhline(0, color='0.7')\n",
+    "plt.savefig('covid_deaths_per_day_7.png') "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths_m7[COUNTRIES_FRIENDS].plot(figsize=(10, 6), title=\"Deaths per day, 7 day moving average\")\n",
+    "ax.set_xlabel(f\"Days since {DEATH_COUNT_THRESHOLD} deaths\")\n",
+    "for c in COUNTRIES_FRIENDS:\n",
+    "    lvi = deaths_m7[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = c)\n",
+    "# plt.axhline(0, color='0.7')\n",
+    "plt.savefig('covid_deaths_per_day-friends.png') "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "deaths_m7_prime = deaths_m7[COUNTRIES_CORE].copy()\n",
+    "deaths_m7_prime.loc[73:, 'ES'] = np.NaN\n",
+    "deaths_m7_prime['ES'][70:]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths_m7_prime[COUNTRIES_CORE].plot(figsize=(10, 6), title=\"Deaths per day, 7 day moving average\")\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = deaths_m7_prime[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = deaths_m7_prime[c][lvi], s = c)\n",
+    "plt.savefig('covid_deaths_per_day_7.png') # see below for where this is written, with the projection"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths_by_date_m7.loc['2020-03-01':, COUNTRIES_CORE].plot(figsize=(10, 6), title=\"Deaths per day, 7 day moving average\")\n",
+    "ax.set_xlabel('Date')\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = deaths_by_date_m7[c].last_valid_index()\n",
+    "    ax.text(x = lvi + pd.Timedelta(days=1), y = deaths_by_date_m7[c][lvi], s = c)\n",
+    "plt.savefig('covid_deaths_per_day_7.png') "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths_m7[COUNTRIES_FRIENDS].plot(figsize=(10, 6), title=\"Deaths per day, 7 day moving average\")\n",
+    "for c in COUNTRIES_FRIENDS:\n",
+    "    lvi = deaths_m7[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = c)\n",
+    "plt.savefig('covid_deaths_per_day_friends_7.png') "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths_m7[COUNTRIES_CORE + ['BR', 'MX']].plot(figsize=(10, 6), title=\"Deaths per day, 7 day moving average\")\n",
+    "for c in COUNTRIES_CORE + ['BR', 'MX']:\n",
+    "    lvi = deaths_m7[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = c)\n",
+    "# plt.savefig('covid_deaths_per_day_7.png') "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths_by_date_m7.iloc[-30:][COUNTRIES_CORE].plot(figsize=(10, 6), title=\"Deaths per day, 7 day moving average\")#, ylim=(-10, 100))\n",
+    "ax.set_xlabel(\"Date\")\n",
+    "\n",
+    "text_x_pos = deaths_by_date_m7.last_valid_index() + pd.Timedelta(days=1)\n",
+    "\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = deaths_by_date_m7[c].last_valid_index()\n",
+    "#     if c != 'ES':\n",
+    "    ax.text(x = text_x_pos, y = deaths_by_date_m7[c][lvi], s = f\"{c}: {deaths_by_date_m7[c][lvi]:.0f}\")\n",
+    "plt.savefig('deaths_by_date_last_30_days.png') "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths_by_date_m7.iloc[-30:][COUNTRIES_FRIENDS].plot(figsize=(10, 6), title=\"Deaths per day, 7 day moving average\")#, ylim=(-10, 100))\n",
+    "ax.set_xlabel(\"Date\")\n",
+    "\n",
+    "text_x_pos = deaths_by_date_m7.last_valid_index() + pd.Timedelta(days=1)\n",
+    "\n",
+    "for c in COUNTRIES_FRIENDS:\n",
+    "    lvi = deaths_by_date_m7[c].last_valid_index()\n",
+    "#     if c != 'ES':\n",
+    "    ax.text(x = text_x_pos, y = deaths_by_date_m7[c][lvi], s = f\"{c}: {deaths_by_date_m7[c][lvi]:.0f}\")\n",
+    "plt.savefig('deaths_by_date_last_30_days_friends.png') "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = cases_m7[COUNTRIES_CORE].plot(figsize=(10, 6), title=\"Cases per day, 7 day moving average\")\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = cases_m7[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = cases_m7[c][lvi], s = c)\n",
+    "plt.savefig('covid_cases_per_day-core.png') "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = cases_m7[COUNTRIES_FRIENDS].plot(figsize=(10, 6), title=\"Cases per day, 7 day moving average\")\n",
+    "for c in COUNTRIES_FRIENDS:\n",
+    "    lvi = cases_m7[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = cases_m7[c][lvi], s = c)\n",
+    "plt.savefig('covid_cases_per_day-core.png') "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = cases_by_date_m7.iloc[-30:][COUNTRIES_FRIENDS].plot(figsize=(10, 6), title=\"Cases per day, 7 day moving average\")#, ylim=(-10, 100))\n",
+    "ax.set_xlabel(\"Date\")\n",
+    "\n",
+    "text_x_pos = cases_by_date_m7.last_valid_index() + pd.Timedelta(days=1)\n",
+    "\n",
+    "for c in COUNTRIES_FRIENDS:\n",
+    "    lvi = cases_by_date_m7[c].last_valid_index()\n",
+    "#     if c != 'ES':\n",
+    "    ax.text(x = text_x_pos, y = cases_by_date_m7[c][lvi], s = f\"{c}: {cases_by_date_m7[c][lvi]:.0f}\")\n",
+    "plt.savefig('cases_by_date_last_30_days_friends.png') "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "def gmean_scale(items):\n",
+    "    return gmean(items) / items[-1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "def doubling_time(df):\n",
+    "    return np.log(2) / np.log((df.deaths_culm + df.deaths_g4) / df.deaths_culm)\n",
+    "\n",
+    "def doubling_time_7(df):\n",
+    "    return np.log(2) / np.log((df.deaths_culm + df.deaths_g7) / df.deaths_culm)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# data_since_threshold['deaths_g4'] = data_since_threshold.groupby(level=1)['deaths'].transform(lambda x: x.rolling(4, 1).apply(gmean_scale, raw=True))\n",
+    "# data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT']), :]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_since_threshold['deaths_g4'] = data_since_threshold.groupby(level=1)['deaths'].transform(lambda x: x.rolling(4, 1).apply(gmean, raw=True))\n",
+    "data_since_threshold['deaths_g7'] = data_since_threshold.groupby(level=1)['deaths'].transform(lambda x: x.rolling(7, 1).apply(gmean, raw=True))\n",
+    "data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT']), :]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_since_threshold['doubling_time'] = data_since_threshold.groupby(level=1).apply(doubling_time).reset_index(level=0, drop=True).sort_index()\n",
+    "data_since_threshold['doubling_time_7'] = data_since_threshold.groupby(level=1).apply(doubling_time_7).reset_index(level=0, drop=True).sort_index()\n",
+    "# data_since_threshold.loc[(slice(None), 'UK'), :]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_date['deaths_g4'] = data_by_date.groupby(level=0)['deaths'].transform(lambda x: x.rolling(4, 1).apply(gmean, raw=True))\n",
+    "data_by_date['deaths_g7'] = data_by_date.groupby(level=0)['deaths'].transform(lambda x: x.rolling(7, 1).apply(gmean, raw=True))\n",
+    "data_by_date['doubling_time'] = data_by_date.groupby(level=0).apply(doubling_time).reset_index(level=0, drop=True).sort_index()\n",
+    "data_by_date['doubling_time_7'] = data_by_date.groupby(level=0).apply(doubling_time_7).reset_index(level=0, drop=True).sort_index()\n",
+    "data_by_date.loc['UK']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "doubling_times = (data_since_threshold.loc[(slice(None), COUNTRIES_OF_INTEREST), ['doubling_time']]\n",
+    "             .unstack().sort_index().xs('doubling_time', axis=1, drop_level=True))\n",
+    "doubling_times.replace([np.inf, -np.inf], np.nan, inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "doubling_times_7 = (data_since_threshold.loc[(slice(None), COUNTRIES_OF_INTEREST), ['doubling_time_7']]\n",
+    "             .unstack().sort_index().xs('doubling_time_7', axis=1, drop_level=True))\n",
+    "doubling_times_7.replace([np.inf, -np.inf], np.nan, inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = doubling_times.plot(figsize=(10, 6), title=\"Doubling times, 4 day average\")\n",
+    "for c in doubling_times.columns:\n",
+    "    lvi = doubling_times[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = doubling_times[c][lvi], s = c)\n",
+    "# plt.savefig('covid_deaths_per_day.png') "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = doubling_times_7[COUNTRIES_CORE].plot(figsize=(10, 6), title=\"Doubling times, 7 day average\")\n",
+    "ax.legend(loc=\"upper left\")\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = doubling_times_7[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = doubling_times_7[c][lvi], s = c)\n",
+    "plt.savefig('covid_doubling_times_7.png') "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = doubling_times[COUNTRIES_CORE].plot(figsize=(10, 6), title=\"Doubling times, 4 day average\")\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = doubling_times[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = doubling_times[c][lvi], s = c)\n",
+    "plt.savefig('covid_doubling_times.png') "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = doubling_times[COUNTRIES_FRIENDS].plot(figsize=(10, 6), title=\"Doubling times\")\n",
+    "for c in COUNTRIES_FRIENDS:\n",
+    "    lvi = doubling_times[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = doubling_times[c][lvi], s = c)\n",
+    "plt.savefig('covid_doubling_times_friends.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = doubling_times[C7s].plot(figsize=(10, 6), title=\"Doubling times\")\n",
+    "for c in C7s:\n",
+    "    lvi = doubling_times[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = doubling_times[c][lvi], s = c)\n",
+    "# plt.savefig('covid_doubling_times_friends.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# deaths_diff_m4 = (data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['deaths_diff_m4']]\n",
+    "#              .unstack().sort_index().xs('deaths_diff_m4', axis=1, drop_level=True))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# deaths_diff_m7 = (data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['deaths_diff_m7']]\n",
+    "#              .unstack().sort_index().xs('deaths_diff_m7', axis=1, drop_level=True))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# deaths_diff_m7"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# data_since_threshold.replace([np.inf, -np.inf], np.nan).groupby(level=1).last().loc[COUNTRIES_ALL]#, [doubling_time]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "dstl = data_since_threshold.replace([np.inf, -np.inf], np.nan).groupby(level=1).last()\n",
+    "dstl.loc[dstl.index.intersection(COUNTRIES_ALL)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# data_since_threshold.replace([np.inf, -np.inf], np.nan).groupby(level=1).last().loc[['UK', 'DE', 'IT']]#, [doubling_time]]\n",
+    "dstl.loc[['UK', 'DE', 'IT', 'FR', 'ES']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_since_threshold.loc[(slice(None), ['UK']), :].tail(20)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_since_threshold.loc[(slice(None), ['ES']), :].tail(20)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "source": [
+    "## Death projections"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_since_threshold.loc[(slice(None), ['UK']), :].tail(15)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "it_since_threshold = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['IT']), :]\n",
+    "s_end = it_since_threshold.index.max()[0]\n",
+    "s_end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "uk_projection = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), :]\n",
+    "uk_current_end = uk_projection.index.max()[0] + 1\n",
+    "# s_start = uk_projection.index.max()[0] + 1\n",
+    "uk_current_end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "current_uk_deaths_m7 = uk_projection[uk_projection.deaths_m7 >= 0].iloc[-1].deaths_m7\n",
+    "current_uk_deaths_m7"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "it_since_threshold[it_since_threshold.deaths_m7 <= current_uk_deaths_m7].loc[60:].first_valid_index()[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "s_start = it_since_threshold[it_since_threshold.deaths_m7 <= current_uk_deaths_m7].loc[60:].first_valid_index()[0]\n",
+    "s_start"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "s_start_date = data_since_threshold.loc[(89, 'IT'), 'dateRep']# .iloc[0]\n",
+    "s_start_date"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "s_end - s_start"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "uk_end = s_end - s_start + uk_current_end\n",
+    "uk_end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "proj = it_since_threshold.loc[(slice(s_start, s_end), slice(None)), ['cases', 'deaths', 'deaths_m7']]\n",
+    "ndiff = uk_current_end - s_start\n",
+    "proj.index = pd.MultiIndex.from_tuples([(n + ndiff, 'UK') for n, _ in proj.index], names=proj.index.names)\n",
+    "proj"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "it_since_threshold.loc[(slice(s_start - 8, s_start + 2), slice(None)), ['cases', 'deaths', 'deaths_m7']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "uk_projection[['cases', 'deaths', 'deaths_m7']].tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# proj['deaths_m7'] = proj['deaths_m7'] + 20\n",
+    "# proj"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "source": [
+    "Projected deaths, UK following IT trend from now."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "uk_projection = uk_projection.append(proj, sort=True)\n",
+    "uk_projection.deaths.sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "uk_projection = uk_projection.droplevel(1)\n",
+    "uk_projection"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "uk_projection.loc[152, 'deaths']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "source": [
+    "## Correction for cumulative deaths correction on 14 August"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# uk_projection.loc[152, 'deaths'] = 50"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "uk_projection['deaths_m7'] = uk_projection['deaths'].transform(lambda x: x.rolling(7, 1).mean())\n",
+    "uk_projection.loc[(uk_current_end - 20):(uk_current_end + 5)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "uk_projection.loc[(uk_current_end - 5):]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "uk_projection.deaths_m7.plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "proj.droplevel(level=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths_m7[COUNTRIES_CORE].plot()\n",
+    "# uk_projection['deaths_m7'].plot(figsize=(10, 6), title=\"Deaths per day, 7 day moving average\", label=\"Projection\", style='--', ax=ax)\n",
+    "proj.droplevel(level=1)['deaths_m7'].plot(figsize=(10, 6), title=\"Deaths per day, 7 day moving average\", label=\"Projection\", style='--', ax=ax)\n",
+    "ax.set_xlabel(f\"Days since {DEATH_COUNT_THRESHOLD} deaths\")\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = deaths_m7[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = c)\n",
+    "# plt.savefig('covid_deaths_per_day_7.png') "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "it_since_threshold.deaths.sum()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "source": [
+    "# Excess deaths calculation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "with open('excess_deaths.json') as f:\n",
+    "    excess_deaths_data = json.load(f)\n",
+    "    \n",
+    "# with open('excess_death_accuracy.json') as f:\n",
+    "#     excess_death_accuracy = json.load(f)\n",
+    "    \n",
+    "excess_deaths_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "additional_deaths = data_by_date.loc[('UK', excess_deaths_data['end_date']):('UK')].iloc[1:].deaths.sum()\n",
+    "additional_deaths"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "uk_covid_deaths = data_by_date.loc['UK'].deaths.sum()\n",
+    "uk_covid_deaths"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "uk_deaths_to_date = int(excess_deaths_data['excess_deaths']) + additional_deaths\n",
+    "uk_deaths_to_date"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# excess_deaths_upto = '2020-05-08'\n",
+    "# excess_deaths = 54500"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# excess_deaths_upto = excess_deaths_data['end_date']\n",
+    "# excess_deaths = excess_deaths_data['excess_deaths']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "source": [
+    "Recorded deaths in period where ONS has reported total deaths"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# ons_reported_deaths = base_data.loc['UK'][:excess_deaths_upto]['deaths'].sum()\n",
+    "# ons_reported_deaths"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# excess_deaths_upto"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "source": [
+    "## Correction for deaths total correction on 14 August"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# ons_unreported_deaths_data = base_data.loc['UK'][excess_deaths_upto:].iloc[1:]['deaths']\n",
+    "# ons_unreported_deaths_data['2020-08-14'] = 50"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# ons_unreported_deaths = ons_unreported_deaths_data.sum()\n",
+    "# ons_unreported_deaths"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# scaled_ons_unreported_deaths = ons_unreported_deaths * excess_death_accuracy\n",
+    "# scaled_ons_unreported_deaths"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# uk_deaths_to_date = excess_deaths + scaled_ons_unreported_deaths\n",
+    "# uk_deaths_to_date"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# data_since_threshold.loc[(slice(None), 'UK'), :][data_since_threshold.dateRep == excess_deaths_data['end_date']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# data_since_threshold[data_since_threshold.dateRep == excess_deaths_data['end_date']].loc[(slice(None), 'UK'), :]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# ons_unreported_start = data_since_threshold[data_since_threshold.dateRep == excess_deaths_data['end_date']].loc[(slice(None), 'UK'), :].first_valid_index()[0] + 1\n",
+    "# ons_unreported_start"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# unreported_projected_deaths = uk_projection.loc[ons_unreported_start:].deaths.sum()\n",
+    "# unreported_projected_deaths"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# unreported_projected_deaths_scaled = unreported_projected_deaths * excess_death_accuracy\n",
+    "# unreported_projected_deaths_scaled"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# uk_projection.loc[(s_start):].deaths.sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# deaths_actual_projected_scaled = uk_deaths_to_date + uk_projection.loc[(s_start):].deaths.sum() * excess_death_accuracy\n",
+    "# deaths_actual_projected_scaled"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# excess_deaths / reported_deaths"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "source": [
+    "True deaths to date, if we follow the scaling of excess deaths over reported deaths so far."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# uk_covid_deaths = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), 'deaths_culm'].iloc[-1]\n",
+    "# uk_covid_deaths"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# uk_covid_deaths_scaled = excess_deaths + unreported_deaths * excess_death_accuracy\n",
+    "# uk_covid_deaths_scaled"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['IT']), 'dateRep'].iloc[-1] + pd.Timedelta(s_end - s_start, unit='days')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), 'dateRep'].iloc[-1].strftime(\"%Y-%m-%d\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# uk_covid_deaths * excess_deaths / reported_deaths"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# uk_projection.deaths.sum() * excess_deaths / reported_deaths"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# data_since_threshold.loc[(slice(None), 'FR'), :]\n",
+    "# data_since_threshold[data_since_threshold.dateRep == '2020-05-18'].loc[(slice(None), 'FR'), :]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "source": [
+    "## School reopenings"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "school_reopenings = {\n",
+    "    'ES': {'date': '2020-05-18'},\n",
+    "    'FR': {'date': '2020-05-18'}, # some areas only\n",
+    "#     'IT': {'date': '2020-09-01'},\n",
+    "    # 'IE': {'date': '2020-09-01'},\n",
+    "    'DE': {'date': '2020-05-04'},\n",
+    "    'UK': {'date': '2020-06-01'}\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_since_threshold[data_since_threshold.dateRep == '2020-05-04'].loc[(slice(None), ['DE']), :].first_valid_index()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_since_threshold[data_since_threshold.dateRep == '2020-05-04'].loc[(slice(None), ['DE']), :].iloc[0].deaths_m7"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "for cID in school_reopenings:\n",
+    "    dst_in = data_since_threshold[data_since_threshold.dateRep == (school_reopenings[cID]['date'])].loc[(slice(None), [cID]), :]\n",
+    "    dst_i = dst_in.first_valid_index()\n",
+    "    dst_n = dst_in.iloc[0].deaths_m7\n",
+    "    school_reopenings[cID]['since_threshold'] = dst_i[0]\n",
+    "    school_reopenings[cID]['deaths_m7'] = dst_n\n",
+    "school_reopenings"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths_m7[COUNTRIES_CORE].plot(figsize=(15, 9), title=\"Deaths per day, 7 day moving average\")\n",
+    "# uk_projection.deaths_m7.plot(ax=ax)\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = deaths_m7[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = f\"{c}: {deaths_m7[c][lvi]:.0f}\")\n",
+    "    if c in school_reopenings:\n",
+    "        marker_col = [l for l in ax.lines if l.get_label() == c][0].get_color()\n",
+    "        ax.plot(school_reopenings[c]['since_threshold'], school_reopenings[c]['deaths_m7'], '*', \n",
+    "                markersize=18, markerfacecolor=marker_col, markeredgecolor=marker_col)\n",
+    "        ax.text(x = school_reopenings[c]['since_threshold'] + 1, y = school_reopenings[c]['deaths_m7'], \n",
+    "                s = f\"{school_reopenings[c]['date']}: {school_reopenings[c]['deaths_m7']:.0f}\")\n",
+    "plt.savefig('school_reopenings.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# ax = deaths_m7[COUNTRIES_CORE].plot(figsize=(15, 9), title=\"Deaths per day, 7 day moving average\",\n",
+    "#                                    xlim=(46, 91), ylim=(0, 400))\n",
+    "# # uk_projection.deaths_m7.plot(ax=ax)\n",
+    "# for c in COUNTRIES_CORE:\n",
+    "#     lvi = deaths_m7[c].last_valid_index()\n",
+    "#     ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = f\"{c}: {deaths_m7[c][lvi]:.0f}\", fontsize=14)\n",
+    "#     if c in school_reopenings:\n",
+    "#         marker_col = [l for l in ax.lines if l.get_label() == c][0].get_color()\n",
+    "#         ax.plot(school_reopenings[c]['since_threshold'], school_reopenings[c]['deaths_m7'], '*', \n",
+    "#                 markersize=18, markerfacecolor=marker_col, markeredgecolor=marker_col)\n",
+    "#         ax.text(x = school_reopenings[c]['since_threshold'] + 1, y = school_reopenings[c]['deaths_m7'], \n",
+    "#                 s = f\"{school_reopenings[c]['date']}: {school_reopenings[c]['deaths_m7']:.0f}\",\n",
+    "#                 fontsize=14)\n",
+    "# plt.savefig('school_reopenings_detail.png')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "source": [
+    "# Lockdown graphs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "lockdown_dates = {\n",
+    "    'ES': { 'part_start': {'date': '2020-03-14'}\n",
+    "          , 'full_start': {'date': '2020-03-15'}\n",
+    "          , 'part_finish': {'date': '2020-05-18'}\n",
+    "          },\n",
+    "    'FR': { 'part_start': {'date': '2020-03-13'}\n",
+    "          , 'full_start': {'date': '2020-03-17'}\n",
+    "          , 'part_finish': {'date': '2020-05-11'}\n",
+    "          },\n",
+    "    'IT': { 'part_start': {'date': '2020-03-08'}\n",
+    "          , 'full_start': {'date': '2020-03-10'}\n",
+    "          , 'part_finish': {'date': '2020-05-04'}\n",
+    "          },\n",
+    "    'DE': { #'part_start': {'date': '2020-03-13'}\n",
+    "          'full_start': {'date': '2020-03-22'}\n",
+    "          , 'part_finish': {'date': '2020-05-06'}\n",
+    "          },\n",
+    "    'UK': { 'part_start': {'date': '2020-03-23'}\n",
+    "          , 'full_start': {'date': '2020-03-23'}\n",
+    "          , 'part_finish': {'date': '2020-05-31'}\n",
+    "          },\n",
+    "    'IE': { #'part_start': {'date': '2020-03-12'}\n",
+    "          'full_start': {'date': '2020-03-27'}\n",
+    "          , 'part_finish': {'date': '2020-05-18'}\n",
+    "          },\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "for cID in lockdown_dates:\n",
+    "    for phase in lockdown_dates[cID]:\n",
+    "        dst_in = data_since_threshold[data_since_threshold.dateRep == (lockdown_dates[cID][phase]['date'])].loc[(slice(None), [cID]), :]\n",
+    "        dst_i = dst_in.first_valid_index()\n",
+    "        dst_n = dst_in.iloc[0].deaths_m7\n",
+    "        dst_c = dst_in.iloc[0].cases_m7\n",
+    "        lockdown_dates[cID][phase]['since_threshold'] = dst_i[0]\n",
+    "        lockdown_dates[cID][phase]['deaths_m7'] = dst_n\n",
+    "        lockdown_dates[cID][phase]['cases_m7'] = dst_c\n",
+    "\n",
+    "lockdown_dates"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths_m7[COUNTRIES_CORE].plot(figsize=(15, 9), title=\"Deaths per day, 7 day moving averagee, with lockdown dates\")\n",
+    "ax.set_xlabel(f\"Days since {DEATH_COUNT_THRESHOLD} deaths\")\n",
+    "# uk_projection.deaths_m7.plot(ax=ax)\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = deaths_m7[c].last_valid_index()\n",
+    "    if c != 'UK':\n",
+    "        ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = f\"{c}: {deaths_m7[c][lvi]:.0f}\")\n",
+    "    if c in lockdown_dates:\n",
+    "        for phase in lockdown_dates[c]:\n",
+    "            marker_col = [l for l in ax.lines if l.get_label() == c][0].get_color()\n",
+    "            ax.plot(lockdown_dates[c][phase]['since_threshold'], lockdown_dates[c][phase]['deaths_m7'], '*',\n",
+    "                    markersize=18, markerfacecolor=marker_col, markeredgecolor=marker_col)\n",
+    "            if 'start' not in phase:\n",
+    "                ax.text(x = lockdown_dates[c][phase]['since_threshold'] + 1, y = lockdown_dates[c][phase]['deaths_m7'], \n",
+    "                        s = f\"{lockdown_dates[c][phase]['date']}: {lockdown_dates[c][phase]['deaths_m7']:.0f}\")\n",
+    "# plt.savefig('school_reopenings.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = cases_m7.iloc[-50:][COUNTRIES_CORE].plot(figsize=(15, 9), title=\"Cases per day, 7 day moving average, with lockdown dates\") #, ylim=(-10, 1500))\n",
+    "ax.set_xlabel(f\"Days since {DEATH_COUNT_THRESHOLD} deaths\")\n",
+    "# uk_projection.deaths_m7.plot(ax=ax)\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = cases_m7[c].last_valid_index()\n",
+    "#     if c != 'UK':\n",
+    "    ax.text(x = lvi + 1, y = cases_m7[c][lvi], s = f\"{c}: {cases_m7[c][lvi]:.0f}\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = cases_m7[COUNTRIES_CORE].plot(figsize=(15, 9), title=\"Cases per day, 7 day moving average, with lockdown dates\")\n",
+    "ax.set_xlabel(f\"Days since {DEATH_COUNT_THRESHOLD} deaths\")\n",
+    "# uk_projection.deaths_m7.plot(ax=ax)\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = cases_m7[c].last_valid_index()\n",
+    "#     if c != 'UK':\n",
+    "    ax.text(x = lvi + 1, y = cases_m7[c][lvi], s = f\"{c}: {cases_m7[c][lvi]:.0f}\")\n",
+    "    if c in lockdown_dates:\n",
+    "        for phase in lockdown_dates[c]:\n",
+    "            marker_col = [l for l in ax.lines if l.get_label() == c][0].get_color()\n",
+    "            if 'start' in phase:\n",
+    "                marker_shape = '^'\n",
+    "            else:\n",
+    "                marker_shape = 'v'\n",
+    "            ax.plot(lockdown_dates[c][phase]['since_threshold'], lockdown_dates[c][phase]['cases_m7'], \n",
+    "                    marker_shape,\n",
+    "                    markersize=18, markerfacecolor=marker_col, markeredgecolor=marker_col)\n",
+    "            if 'start' not in phase:\n",
+    "                ax.text(x = lockdown_dates[c][phase]['since_threshold'] + 1, y = lockdown_dates[c][phase]['cases_m7'], \n",
+    "                        s = f\"{lockdown_dates[c][phase]['date']}: {lockdown_dates[c][phase]['cases_m7']:.0f}\")\n",
+    "# plt.savefig('cases_per_day_with_lockdown.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "plot_start_date = '2020-03-01'\n",
+    "ax = cases_by_date_m7.loc[plot_start_date:, COUNTRIES_CORE].plot(figsize=(15, 9), title=\"Cases per day, 7 day moving average, with lockdown dates\")\n",
+    "ax.set_xlabel(f\"Date\")\n",
+    "ax.set_ylabel(\"Number of cases\")\n",
+    "# uk_projection.deaths_m7.plot(ax=ax)\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = cases_by_date_m7[c].last_valid_index()\n",
+    "#     if c != 'UK':\n",
+    "    ax.text(x = lvi + pd.Timedelta(days=1), y = cases_by_date_m7[c][lvi], s = f\"{c}: {cases_by_date_m7[c][lvi]:.0f}\")\n",
+    "    if c in lockdown_dates:\n",
+    "        for phase in lockdown_dates[c]:\n",
+    "            marker_col = [l for l in ax.lines if l.get_label() == c][0].get_color()\n",
+    "            if 'start' in phase:\n",
+    "                marker_shape = '^'\n",
+    "            else:\n",
+    "                marker_shape = 'v'\n",
+    "            marker_x_pos = ax.get_xlim()[0] + mpl.dates.date2num(pd.to_datetime(lockdown_dates[c][phase]['date'])) - mpl.dates.date2num(pd.to_datetime(plot_start_date))\n",
+    "            ax.plot(marker_x_pos, lockdown_dates[c][phase]['cases_m7'], \n",
+    "                    marker_shape,\n",
+    "                    markersize=18, markerfacecolor=marker_col, markeredgecolor=marker_col)\n",
+    "            if 'start' not in phase:\n",
+    "                ax.text(x = marker_x_pos + 3, y = lockdown_dates[c][phase]['cases_m7'], \n",
+    "                        s = f\"{lockdown_dates[c][phase]['date']}: {lockdown_dates[c][phase]['cases_m7']:.0f}\")\n",
+    "plt.savefig('cases_per_day_with_lockdown.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = cases_m7[COUNTRIES_CORE].plot(figsize=(10, 6), title=\"Cases per day, 7 day moving average\")\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = cases_m7[c].last_valid_index()\n",
+    "    ax.text(x = lvi + 1, y = cases_m7[c][lvi], s = c)\n",
+    "plt.savefig('covid_cases_per_day-core.png') "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths_m7[COUNTRIES_CORE].plot(figsize=(15, 9), title=\"Deaths per day, 7 day moving average\",\n",
+    "                                   xlim=(0, 15), \n",
+    "                                    ylim=(0, 66)\n",
+    "                                   )\n",
+    "# uk_projection.deaths_m7.plot(ax=ax)\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = deaths_m7[c].last_valid_index()\n",
+    "    if c in lockdown_dates:\n",
+    "        for phase in lockdown_dates[c]:\n",
+    "            if 'start' in phase:\n",
+    "                print(c, phase)\n",
+    "                marker_col = [l for l in ax.lines if l.get_label() == c][0].get_color()\n",
+    "                ax.plot(lockdown_dates[c][phase]['since_threshold'], lockdown_dates[c][phase]['deaths_m7'], '*', \n",
+    "                        markersize=18, markerfacecolor=marker_col, markeredgecolor=marker_col)\n",
+    "                ax.text(x = lockdown_dates[c][phase]['since_threshold'] + 0.3, y = lockdown_dates[c][phase]['deaths_m7'], \n",
+    "                        s = f\"{lockdown_dates[c][phase]['date']}: {lockdown_dates[c][phase]['deaths_m7']:.0f}\")\n",
+    "# plt.savefig('school_reopenings.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "source": [
+    "# Write results to summary file"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "with open('covid_summary.md', 'w') as f:\n",
+    "    f.write('% Covid death data summary\\n')\n",
+    "    f.write('% Neil Smith\\n')\n",
+    "    f.write(f'% Created on {datetime.datetime.now().strftime(\"%Y-%m-%d\")}\\n')\n",
+    "    f.write('\\n')\n",
+    "        \n",
+    "    last_uk_date = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), 'dateRep'].iloc[-1]\n",
+    "    f.write(f'> Last UK data from {last_uk_date.strftime(\"%Y-%m-%d\")}\\n')\n",
+    "    f.write('\\n')    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "with open('covid_summary.md', 'a') as f:\n",
+    "    f.write('## Headlines\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('| []() | |\\n')\n",
+    "    f.write('|:---|---:|\\n')\n",
+    "    f.write(f'| Deaths reported so far | {uk_covid_deaths} | \\n')\n",
+    "    f.write(f'| Total Covid deaths to date (estimated) | {uk_deaths_to_date:.0f} |\\n')\n",
+    "    projection_date = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['IT']), 'dateRep'].iloc[-1] + pd.Timedelta(s_end - s_start, unit='days')\n",
+    "#     f.write(f'| Projected total deaths up to {projection_date.strftime(\"%Y-%m-%d\")} | {deaths_actual_projected_scaled:.0f} | \\n')\n",
+    "    f.write('\\n')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "with open('covid_summary.md', 'a') as f:\n",
+    "    f.write('## Total deaths\\n')\n",
+    "#     f.write(f'Time based on days since {DEATH_COUNT_THRESHOLD} deaths\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('![Total deaths](covid_deaths_total_linear.png)\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('| Country ID | Country name | Total deaths |\\n')\n",
+    "    f.write('|:-----------|:-------------|-------------:|\\n')\n",
+    "    for c in sorted(COUNTRIES_CORE):\n",
+    "        lvi = deaths_by_date[c].last_valid_index()\n",
+    "        f.write(f'| {c} | {countries.loc[c].countriesAndTerritories} | {int(deaths_by_date[c][lvi])} |\\n')\n",
+    "    f.write('\\n')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "with open('covid_summary.md', 'a') as f:\n",
+    "    f.write('## All-causes deaths, UK\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('![All-causes deaths](deaths-radar.png)\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('### True deaths\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write(f'The number of deaths reported in official statistics, {uk_covid_deaths}, is an underestimate '\n",
+    "            'of the true number of Covid deaths.\\n'\n",
+    "            'This is especially true early in the pandemic, approximately March to May 2020.\\n')\n",
+    "    f.write('We can get a better understanding of the impact of Covid by looking at the number of deaths, '\n",
+    "            'over and above what would be expected at each week of the year.\\n')\n",
+    "    f.write(f'The ONS (and other bodies in Scotland and Northern Ireland) have released data on the number of deaths '\n",
+    "            f'up to {pd.to_datetime(excess_deaths_data[\"end_date\"]).strftime(\"%d %B %Y\")}.\\n\\n')\n",
+    "    f.write('If, for each of those weeks, I take the largest of the excess deaths or the reported Covid deaths, ')\n",
+    "    f.write(f'I estimate there have been **{uk_deaths_to_date}** total deaths so far.\\n')\n",
+    "    f.write('\\n')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# with open('covid_summary.md', 'a') as f:\n",
+    "#     f.write(f'In that period, the UK reported {ons_reported_deaths} Covid deaths.\\n')\n",
+    "#     f.write(f'In the last three weeks for which excess deaths have been reported, the excess deaths have been {excess_death_accuracy:.3f} higher than the Covid-reported deaths.\\n')\n",
+    "# #     f.write(f'That means the actual number of Covid death is about {excess_deaths / reported_deaths:.2f} times higher than the reported figures.\\n')\n",
+    "#     f.write('\\n')\n",
+    "#     f.write(f'The UK has reported {uk_covid_deaths} deaths so far.\\n')\n",
+    "#     f.write(f'Using the scaling factor above (for Covid-19 deaths after the ONS figures), I infer that there have been **{uk_deaths_to_date:.0f}** total deaths so far.\\n')\n",
+    "#     f.write('\\n')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "with open('covid_summary.md', 'a') as f:\n",
+    "    f.write('## Deaths per day\\n')\n",
+    "    f.write(f'Based on a 7-day moving average\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('![Deaths per day](covid_deaths_per_day_7.png)\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('![Deaths per day, last 30 days](deaths_by_date_last_30_days.png)\\n')\n",
+    "    f.write('\\n')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "s_end - s_start - 1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "with open('covid_summary.md', 'a') as f:\n",
+    "    f.write('## Projected deaths\\n')\n",
+    "    f.write(\"Previously, I was using Italy's deaths data to predict the UK's deaths data. \"\n",
+    "            \"This worked when both countries' trends of deaths were falling or constant, \"\n",
+    "            \"as they were until September.\\n\")\n",
+    "    f.write(\"\\n\")\n",
+    "    f.write(\"As of mid-September, with cases rising in both countries at around the same time, \"\n",
+    "            \"I can't use Italian data to predict the UK's future deaths.\\n\")\n",
+    "    f.write(\"\\n\")\n",
+    "#     f.write(f\"The UK's daily deaths data is very similar to Italy's.\\n\")\n",
+    "#     f.write(f'If I use the Italian data for the next {s_end - s_start - 1} days (from {s_start_date.strftime(\"%d %B %Y\")} onwards),')\n",
+    "#     f.write(f' the UK will report {uk_projection.deaths.sum()} deaths on day {uk_end} of the epidemic.\\n')\n",
+    "#     f.write('\\n')\n",
+    "#     f.write('Using the excess deaths scaling from above, that will translate into ')\n",
+    "#     f.write(f'**{deaths_actual_projected_scaled:.0f}** Covid deaths total.\\n')\n",
+    "#     f.write('\\n')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "with open('covid_summary.md', 'a') as f:\n",
+    "    f.write('## Deaths doubling times\\n')\n",
+    "    f.write(f'Based on a 7-day moving average\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('![Deaths doubling times](covid_doubling_times_7.png)\\n')\n",
+    "    f.write('\\n')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "with open('covid_summary.md', 'a') as f:\n",
+    "    f.write('\\n')\n",
+    "    f.write('## Cases per day and lockdown dates\\n')\n",
+    "    f.write(f'Based on a 7-day moving average\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('![Cases per day](cases_per_day_with_lockdown.png)\\n')\n",
+    "    f.write('\\n')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "with open('covid_summary.md', 'a') as f:\n",
+    "    f.write('| Country ID | Country name | Most recent daily cases | Most recent daily deaths |\\n')\n",
+    "    f.write('|:-----------|:-------------|------------------------:|-------------------------:|\\n')\n",
+    "    for c in sorted(COUNTRIES_CORE):\n",
+    "        lvic = cases_m7[c].last_valid_index()\n",
+    "        lvid = deaths_m7[c].last_valid_index()\n",
+    "        f.write(f'| {c} | {countries.loc[c].countriesAndTerritories} | {cases_m7[c][lvic]:.0f} | {deaths_m7[c][lvid]:.0f} | \\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('(Figures are 7-day averages)\\n')\n",
+    "    f.write('\\n')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "with open('hospital_normalisation_date.json') as f:\n",
+    "    hospital_normalisation_date_data = json.load(f)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "with open('covid_summary.md', 'a') as f:\n",
+    "    f.write('## Hospital care\\n')\n",
+    "    f.write(f'Based on a 7-day moving average\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('![Cases, admissions, deaths](cases_admissions_deaths.png)\\n')\n",
+    "    f.write('\\n')\n",
+    "#     f.write('Admissions are shifted by 10 days, deaths by 25 days. '\n",
+    "#             'This reflects the typical timescales of infection: '\n",
+    "#             'patients are admitted 10 days after onset of symptoms, '\n",
+    "#             'and die 15 days after admission.\\n')\n",
+    "#     f.write('\\n')\n",
+    "#     f.write('Plotting this data with offsets shows more clearly '\n",
+    "#             'the relative changes in these three metrics.\\n')\n",
+    "    f.write('Due to the large scale differences between the three '\n",
+    "            'measures, they are all normalised to show changes ')\n",
+    "    f.write(f'since {pd.to_datetime(hospital_normalisation_date_data[\"hospital_normalisation_date\"]).strftime(\"%d %B %Y\")}.\\n')\n",
+    "    f.write('\\n')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "with open('covid_summary.md', 'a') as f:\n",
+    "    f.write('## Testing effectiveness\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('A question about testing is whether more detected cases is a result of more tests being '\n",
+    "            'done or is because the number of cases is increasing. One way of telling the differeence '\n",
+    "            'is by looking at the fraction of tests that are positive.\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('![Positive tests and cases](tests_and_cases.png)\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('Numbers of positive tests and cases, '\n",
+    "            '7-day moving average.\\n'\n",
+    "            'Note the different y-axes\\n')\n",
+    "    f.write('\\n')    \n",
+    "    f.write('![Fraction of tests with positive result](fraction_positive_tests.png)\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('Fraction of tests with a positive result, both daily figures and '\n",
+    "            '7-day moving average.\\n')\n",
+    "    f.write('\\n')    \n",
+    "    f.write('\\n')\n",
+    "    f.write('![Tests against fraction positive, trajectory](fraction_positive_tests_vs_tests.png)\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('The trajectory of tests done vs fraction positive tests.\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('Points higher indicate more tests; points to the right indicate more positive tests.'\n",
+    "            'More tests being done with the same infection prevelance will move the point up '\n",
+    "            'and to the left.\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('![Tests against fraction positive, trajectory](tests_vs_fraction_positive_animation.png)\\n')\n",
+    "    f.write('\\n')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "with open('covid_summary.md', 'a') as f:\n",
+    "    f.write('# Data sources\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('> Covid data from [European Centre for Disease Prevention and Control](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide)\\n')\n",
+    "    f.write('\\n')    \n",
+    "    f.write(\"\"\"> Population data from:\n",
+    "\n",
+    "* [Office of National Statistics](https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/weeklyprovisionalfiguresondeathsregisteredinenglandandwales) (Endland and Wales) Weeks start on a Saturday.\n",
+    "* [Northern Ireland Statistics and Research Agency](https://www.nisra.gov.uk/publications/weekly-deaths) (Northern Ireland). Weeks start on a Saturday. Note that the week numbers don't match the England and Wales data.\n",
+    "* [National Records of Scotland](https://www.nrscotland.gov.uk/statistics-and-data/statistics/statistics-by-theme/vital-events/general-publications/weekly-and-monthly-data-on-births-and-deaths/weekly-data-on-births-and-deaths) (Scotland). Note that Scotland uses ISO8601 week numbers, which start on a Monday.\"\"\")\n",
+    "    \n",
+    "    f.write('\\n\\n')\n",
+    "    f.write('> [Source code available](https://git.njae.me.uk/?p=covid19.git;a=tree)\\n')\n",
+    "    f.write('\\n') \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "!pandoc --toc -s covid_summary.md > covid_summary.html"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "!scp covid_summary.html neil@ogedei:/var/www/scripts.njae.me.uk/covid/index.html\n",
+    "!scp covid_deaths_total_linear.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp deaths-radar.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp covid_deaths_per_day_7.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp covid_doubling_times_7.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp cases_per_day_with_lockdown.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp cases_admissions_deaths.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp fraction_positive_tests.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/    \n",
+    "!scp tests_and_cases.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp deaths_by_date_last_30_days.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp fraction_positive_tests_vs_tests.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp tests_vs_fraction_positive_animation.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/   "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "with open('uk_covid_deaths.js', 'w') as f:\n",
+    "    f.write(f\"document.write('{uk_covid_deaths}');\")\n",
+    "    \n",
+    "with open('estimated_total_deaths.js', 'w') as f:\n",
+    "    f.write(f\"document.write('{uk_deaths_to_date:.0f}');\")\n",
+    "\n",
+    "# with open('projection_date.js', 'w') as f:\n",
+    "#     f.write(f\"document.write(\\'{projection_date.strftime('%d %B %Y')}\\');\")\n",
+    "\n",
+    "# with open('projected_deaths.js', 'w') as f:\n",
+    "#     f.write(f\"document.write('{uk_projection.deaths.sum():.0f}');\")\n",
+    "\n",
+    "# with open('projected_excess_deaths.js', 'w') as f:\n",
+    "#     f.write(f\"document.write('{deaths_actual_projected_scaled:.0f}');\")\n",
+    "\n",
+    "edut = pd.to_datetime(excess_deaths_data[\"end_date\"]).strftime('%d %B %Y')\n",
+    "with open('excess_deaths_upto.js', 'w') as f:\n",
+    "    f.write(f\"document.write('{edut}');\")\n",
+    "\n",
+    "# with open('excess_deaths.js', 'w') as f:\n",
+    "#     f.write(f\"document.write('{excess_deaths:.0f}');\")\n",
+    "    \n",
+    "# with open('reported_deaths.js', 'w') as f:\n",
+    "#     f.write(f\"document.write('{ons_reported_deaths:.0f}');\")\n",
+    "    \n",
+    "# with open('scaling_factor.js', 'w') as f:\n",
+    "#     f.write(f\"document.write('{excess_death_accuracy:.2f}');\")  \n",
+    "\n",
+    "# with open('projection_length.js', 'w') as f:\n",
+    "#     f.write(f\"document.write('{s_end - s_start - 1}');\")\n",
+    "    \n",
+    "# with open('s_end.js', 'w') as f:\n",
+    "#     f.write(f\"document.write('{s_end}');\")\n",
+    "    \n",
+    "# s_start_date_str = s_start_date.strftime(\"%d %B %Y\")\n",
+    "# with open('s_start_date.js', 'w') as f:\n",
+    "#     f.write(f\"document.write('{s_start_date_str}');\")\n",
+    "    \n",
+    "# with open('uk_end.js', 'w') as f:\n",
+    "#     f.write(f\"document.write('{uk_end}');\")\n",
+    "    \n",
+    "with open('last_uk_date.js', 'w') as f:\n",
+    "    f.write(f\"document.write('{pd.to_datetime(last_uk_date).strftime('%d %B %Y')}');\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# pd.to_datetime(excess_deaths_upto).strftime('%d %B %Y')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "!scp uk_covid_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp estimated_total_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "# !scp projection_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "# !scp projected_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "# !scp projected_excess_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp excess_deaths_upto.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "# !scp excess_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "# !scp reported_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "# !scp scaling_factor.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "# !scp projection_length.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "# !scp s_end.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "# !scp s_start_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "# !scp uk_end.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp last_uk_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp hospital_normalisation_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_date.loc['UK'].to_csv('data_by_day_uk.csv', header=True, index=True)\n",
+    "data_by_date.loc['BE'].to_csv('data_by_day_be.csv', header=True, index=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ukd = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), ['deaths', 'deaths_m7']].droplevel(1)\n",
+    "ax = ukd.deaths.plot.bar(figsize=(12, 8))\n",
+    "ukd.deaths_m7.plot.line(ax=ax, color='red')\n",
+    "# ax = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), 'deaths_m7'].plot.line(figsize=(12, 8), color='red')\n",
+    "# ax = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), 'deaths'].plot.bar(ax=ax)\n",
+    "ax.set_xticks(range(0, 120, 20))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ukdd = data_by_date.loc['UK'].iloc[-30:]\n",
+    "ax = ukdd.deaths_m7.plot.line(figsize=(12, 8), color='red')\n",
+    "# ukdd.deaths.plot.bar(ax=ax)\n",
+    "ax.bar(ukdd.index, ukdd.deaths)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ukdd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "np.arange(0, 130, 20)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_date.loc['UK']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_date.loc['UK'].plot(x='deaths_culm', y='deaths', logx=True, logy=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_date.loc['UK'].plot(x='cases_culm', y='cases')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ukdbd = data_by_date.loc['UK'].copy()\n",
+    "ukdbd['deaths_m7'] = ukdbd.deaths.transform(lambda x: x.rolling(7, 1).mean())\n",
+    "ukdbd['cases_m7'] = ukdbd.cases.transform(lambda x: x.rolling(7, 1).mean())\n",
+    "ukdbd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ukdbd.plot(x='deaths_culm', y='deaths_m7', logx=True, logy=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "fig, ax = plt.subplots(figsize=(12, 8))\n",
+    "xmax = 10\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    if data_since_threshold.loc[(slice(None), c), 'deaths_culm'].max() > xmax:\n",
+    "        xmax = data_since_threshold.loc[(slice(None), c), 'deaths_culm'].max()\n",
+    "    data_since_threshold.loc[(slice(None), c), :].plot(x='deaths_culm', y='deaths_m7', logx=True, logy=True, xlim=(10, xmax * 1.1), label=c, ax=ax)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_since_threshold.loc[(slice(None), 'UK'), 'deaths_culm'].max()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "countries.continentExp.unique()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "countries.loc['KW']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_date.groupby(level=0)['deaths'].shift(-25)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "offset_data = data_by_date.loc[:, ['cases']]\n",
+    "offset_data['deaths'] = data_by_date.groupby(level=0)['deaths'].shift(-25)\n",
+    "offset_data['cases_m7'] = offset_data.groupby(level=0)['cases'].transform(lambda x: x.rolling(7, 1).mean())\n",
+    "offset_data['deaths_m7'] = offset_data['deaths'].dropna().groupby(level=0).transform(lambda x: x.rolling(7, 1).mean())\n",
+    "offset_data['deaths_per_case'] = offset_data.deaths_m7 / offset_data.cases_m7\n",
+    "offset_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "deaths_m7"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "offset_deaths_m7 = (offset_data.loc[COUNTRIES_ALL, ['deaths_m7']]\n",
+    "             .unstack().sort_index().xs('deaths_m7', axis=1, drop_level=True)).T.sort_index()\n",
+    "offset_deaths_m7"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "offset_deaths_m7['UK']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_since_threshold.loc[(slice(None), 'UK'), :].tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "countries.loc['PT']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = cases_by_date_m7.iloc[-50:][COUNTRIES_FRIENDS].plot(figsize=(15, 9), title=\"Cases per day, 7 day moving average\")#, ylim=(-10, 1500))\n",
+    "# ax.set_xlabel(f\"Days since {DEATH_COUNT_THRESHOLD} deaths\")\n",
+    "# uk_projection.deaths_m7.plot(ax=ax)\n",
+    "for c in COUNTRIES_FRIENDS:\n",
+    "    lvi = cases_by_date_m7[c].last_valid_index()\n",
+    "    ax.text(x = lvi + pd.Timedelta(days=1), y = cases_by_date_m7[c][lvi], s = f\"{c}: {cases_by_date_m7[c][lvi]:.0f}\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "ax = deaths_by_date_m7.iloc[-50:][COUNTRIES_FRIENDS].plot(figsize=(15, 9), title=\"Deaths per day, 7 day moving average\")#, ylim=(-10, 100))\n",
+    "# ax.set_xlabel(f\"Days since {DEATH_COUNT_THRESHOLD} deaths\")\n",
+    "# uk_projection.deaths_m7.plot(ax=ax)\n",
+    "for c in COUNTRIES_FRIENDS:\n",
+    "    lvi = deaths_by_date_m7[c].last_valid_index()\n",
+    "#     if c != 'ES':\n",
+    "    ax.text(x = lvi + pd.Timedelta(days=1), y = deaths_by_date_m7[c][lvi], s = f\"{c}: {deaths_by_date_m7[c][lvi]:.0f}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "jupytext": {
+   "formats": "ipynb,md"
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/covid-old.md b/covid-old.md

new file mode 100644 (file)

index 0000000..cc80d79
--- /dev/null
+++ b/covid-old.md
@@ -0,0 +1,1736 @@
+---
+jupyter:
+  jupytext:
+    formats: ipynb,md
+    text_representation:
+      extension: .md
+      format_name: markdown
+      format_version: '1.2'
+      jupytext_version: 1.3.4
+  kernelspec:
+    display_name: Python 3
+    language: python
+    name: python3
+---
+
+<!-- #region Collapsed="false" -->
+Data from [European Centre for Disease Prevention and Control](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide)
+<!-- #endregion -->
+
+```python Collapsed="false"
+import itertools
+import collections
+import json
+import pandas as pd
+import numpy as np
+from scipy.stats import gmean
+import datetime
+
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+%matplotlib inline
+```
+
+```python Collapsed="false"
+DEATH_COUNT_THRESHOLD = 10
+COUNTRIES_CORE = 'IT DE UK ES IE FR BE'.split()
+COUNTRIES_NORDIC = 'SE NO DK FI UK'.split()
+COUNTRIES_FRIENDS = 'IT UK ES BE SI MX'.split()
+# COUNTRIES_FRIENDS = 'IT UK ES BE SI PT'.split()
+
+COUNTRIES_AMERICAS = ['AG', 'AR', 'AW', 'BS', 'BB', 'BZ', 'BM', 'BO', 'BR', 'VG', 'KY', # excluding Canada and USA
+       'CL', 'CO', 'CR', 'CU', 'CW', 'DM', 'DO', 'EC', 'SV', 'GL', 'GD', 'GT',
+       'GY', 'HT', 'HN', 'JM', 'MX', 'MS', 'NI', 'PA', 'PY', 'PE', 'PR', 'KN',
+       'LC', 'VC', 'SX', 'SR', 'TT', 'TC', 'VI', 'UY', 'VE']
+COUNTRIES_OF_INTEREST = list(set(COUNTRIES_CORE + COUNTRIES_FRIENDS))
+COUNTRIES_ALL = list(set(COUNTRIES_CORE + COUNTRIES_FRIENDS + COUNTRIES_NORDIC + COUNTRIES_AMERICAS))
+```
+
+```python Collapsed="false"
+!curl https://opendata.ecdc.europa.eu/covid19/casedistribution/csv/ > covid.csv
+```
+
+```python Collapsed="false"
+# First col is a date, treat geoId of NA as 'Namibia', not "NA" value
+raw_data = pd.read_csv('covid.csv', 
+                       parse_dates=[0], dayfirst=True,
+                       keep_default_na=False, na_values = [''],
+#                        dtype = {'day': np.int64, 
+#                                 'month': np.int64, 
+#                                 'year': np.int64, 
+#                                 'cases': np.int64, 
+#                                 'deaths': np.int64, 
+#                                 'countriesAndTerritories': str, 
+#                                 'geoId': str, 
+#                                 'countryterritoryCode': str, 
+#                                 'popData2019': np.int64, 
+#                                 'continentExp': str, 
+#                                 }
+                      )
+```
+
+```python Collapsed="false"
+raw_data.size
+```
+
+```python Collapsed="false"
+raw_data.fillna(0, inplace=True)
+```
+
+```python Collapsed="false"
+raw_data.head()
+```
+
+```python Collapsed="false"
+raw_data.dtypes
+```
+
+```python Collapsed="false"
+# raw_data = raw_data.astype({'dateRep': np.datetime64, 
+#     'day': np.int64, 
+#     'month': np.int64, 
+#     'year': np.int64, 
+#     'cases': np.int64, 
+#     'deaths': np.int64, 
+#     'countriesAndTerritories': str, 
+#     'geoId': str, 
+#     'countryterritoryCode': str, 
+#     'popData2019': np.int64, 
+#     'continentExp': str })
+raw_data = raw_data.astype({'dateRep': np.datetime64, 
+    'day': np.int64, 
+    'month': np.int64, 
+    'year': np.int64, 
+    'cases': np.int64, 
+    'deaths': np.int64, 
+    'countriesAndTerritories': str, 
+    'geoId': str, 
+    'countryterritoryCode': str, 
+    'popData2019': np.int64, 
+    'continentExp': str })
+```
+
+```python Collapsed="false"
+raw_data.dtypes
+```
+
+```python Collapsed="false"
+raw_data[((raw_data.geoId == 'UK') & (raw_data.dateRep >= '2020-07-10'))]
+```
+
+```python Collapsed="false"
+# raw_data = raw_data[~ ((raw_data.geoId == 'ES') & (raw_data.dateRep >= '2020-05-22'))]
+```
+
+```python Collapsed="false"
+base_data = raw_data.set_index(['geoId', 'dateRep'])
+base_data.sort_index(inplace=True)
+base_data
+```
+
+```python Collapsed="false"
+base_data.loc['ES'].loc['2020-05-10':]
+```
+
+```python Collapsed="false"
+countries = raw_data[['geoId', 'countriesAndTerritories', 'popData2019', 'continentExp']]
+countries = countries[countries['popData2019'] != '']
+countries = countries.drop_duplicates()
+countries.set_index('geoId', inplace=True)
+countries = countries.astype({'popData2019': 'int64'})
+countries.head()
+```
+
+```python Collapsed="false"
+countries.shape
+```
+
+```python Collapsed="false"
+countries[countries.countriesAndTerritories == 'Finland']
+```
+
+```python Collapsed="false"
+countries.loc[COUNTRIES_OF_INTEREST]
+```
+
+```python Collapsed="false"
+countries[countries.continentExp == 'America'].index
+```
+
+```python Collapsed="false"
+data_by_date = base_data[['cases', 'deaths']]
+data_by_date.head()
+```
+
+```python Collapsed="false"
+data_by_date.loc['UK']
+```
+
+```python Collapsed="false"
+# data_by_date.deaths.drop_duplicates().sort_values().to_csv('dth.csv', header=True)
+```
+
+```python Collapsed="false"
+data_by_date.groupby(level=0).cumsum()
+```
+
+```python Collapsed="false"
+data_by_date = data_by_date.merge(
+    data_by_date.groupby(level=0).cumsum(), 
+    suffixes=('', '_culm'), 
+    left_index=True, right_index=True)
+data_by_date
+```
+
+```python Collapsed="false"
+data_by_date = data_by_date.merge(
+    data_by_date[['cases', 'deaths']].groupby(level=0).diff(), 
+    suffixes=('', '_diff'), 
+    left_index=True, right_index=True)
+data_by_date
+```
+
+```python Collapsed="false"
+data_by_date.loc['UK', '2020-04-17']
+```
+
+```python Collapsed="false"
+data_by_date.loc['UK']
+```
+
+```python Collapsed="false"
+# data_by_date[data_by_date.deaths_culm > DEATH_COUNT_THRESHOLD]
+```
+
+```python Collapsed="false"
+# days_since_threshold = data_by_date[data_by_date.deaths_culm > DEATH_COUNT_THRESHOLD].groupby(level=0).cumcount()
+# days_since_threshold.rename('since_threshold', inplace=True)
+```
+
+```python Collapsed="false"
+dbd = data_by_date[data_by_date.deaths_culm > DEATH_COUNT_THRESHOLD].reset_index(level=1)
+dbd['since_threshold'] = dbd.dateRep
+dbd.set_index('dateRep', append=True, inplace=True)
+dbd.sort_index(inplace=True)
+days_since_threshold = dbd.groupby(level=0).diff().since_threshold.dt.days.fillna(0).astype(int).groupby(level=0).cumsum()
+# days_since_threshold.groupby(level=0).cumsum()
+
+# days_since_threshold = dbd.rename('since_threshold')
+days_since_threshold
+```
+
+```python Collapsed="false"
+# days_since_threshold = (data_by_date[data_by_date.deaths_culm > DEATH_COUNT_THRESHOLD]
+#                         .reset_index(level=1).groupby(level=0)
+#                         .diff().dateRep.dt.days
+#                         .groupby(level=0).cumcount()
+#                        )
+# days_since_threshold.rename('since_threshold', inplace=True)
+# days_since_threshold
+```
+
+```python Collapsed="false"
+data_since_threshold = data_by_date.merge(days_since_threshold, 
+    left_index=True, right_index=True)
+data_since_threshold
+```
+
+```python Collapsed="false"
+data_since_threshold = data_since_threshold.set_index('since_threshold', append=True
+                              ).reorder_levels(['since_threshold', 'geoId', 'dateRep']
+                                              ).reset_index('dateRep')
+data_since_threshold.sort_index(inplace=True)
+data_since_threshold
+```
+
+```python Collapsed="false"
+data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT']), :]
+```
+
+```python Collapsed="false"
+data_since_threshold.loc[(slice(None), ['ES']), :].tail(8)
+```
+
+```python Collapsed="false"
+data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT']), ['deaths_culm']].unstack().plot(logy=True)
+```
+
+```python Collapsed="false"
+# deaths = data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT', 'IE']), ['deaths_culm']].unstack().xs('deaths_culm', axis=1, drop_level=True)
+```
+
+```python Collapsed="false"
+deaths = data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['deaths_culm']].unstack().sort_index().xs('deaths_culm', axis=1, drop_level=True)
+deaths_by_date = data_by_date.loc[COUNTRIES_ALL, ['deaths_culm']].unstack().sort_index().xs('deaths_culm', axis=1, drop_level=True).T
+```
+
+```python Collapsed="false"
+cases = data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['cases_culm']].unstack().sort_index().xs('cases_culm', axis=1, drop_level=True)
+cases_by_date = data_by_date.loc[ COUNTRIES_ALL, ['cases_culm']].unstack().sort_index().xs('cases_culm', axis=1, drop_level=True).T
+```
+
+```python Collapsed="false"
+COUNTRIES_AMERICAS_DEAD = list(set(deaths.columns) & set(COUNTRIES_AMERICAS))
+```
+
+```python Collapsed="false"
+data_since_threshold.reset_index().merge(countries, on='geoId').set_index(['since_threshold', 'geoId'])
+```
+
+```python Collapsed="false"
+data_since_threshold.reset_index().merge(countries, on='geoId').set_index(['since_threshold', 'geoId']).sort_index(inplace=True)
+```
+
+```python Collapsed="false"
+data_since_threshold_per_capita = data_since_threshold.reset_index().merge(countries, on='geoId').set_index(['since_threshold', 'geoId'])
+data_since_threshold_per_capita['cases_culm_pc'] = data_since_threshold_per_capita.cases_culm / data_since_threshold_per_capita.popData2019
+data_since_threshold_per_capita['deaths_culm_pc'] = data_since_threshold_per_capita.deaths_culm / data_since_threshold_per_capita.popData2019
+data_since_threshold_per_capita
+```
+
+```python Collapsed="false"
+deaths_pc = data_since_threshold_per_capita.loc[(slice(None), ['UK', 'DE', 'IT', 'IE']), ['deaths_culm_pc']].unstack().sort_index().xs('deaths_culm_pc', axis=1, drop_level=True)
+```
+
+```python Collapsed="false"
+deaths_pc.index
+```
+
+```python Collapsed="false"
+deaths_pc = data_since_threshold_per_capita.loc[(slice(None), COUNTRIES_ALL), ['deaths_culm_pc']].unstack().xs('deaths_culm_pc', axis=1, drop_level=True)
+```
+
+```python Collapsed="false"
+deaths[COUNTRIES_CORE].plot()
+```
+
+```python Collapsed="false"
+deaths[COUNTRIES_FRIENDS].plot()
+```
+
+```python Collapsed="false"
+ax = deaths[COUNTRIES_FRIENDS].plot(figsize=(10, 6), title="Total deaths, linear")
+ax.set_xlabel(f"Days since {DEATH_COUNT_THRESHOLD} deaths")
+for c in COUNTRIES_FRIENDS:
+    lvi = deaths[c].last_valid_index()
+    ax.text(x = lvi + 1, y = deaths[c][lvi], s = f"{c}: {deaths[c][lvi]:.0f}")
+# plt.savefig('covid_deaths_total_linear.png')    
+```
+
+```python Collapsed="false"
+ax = deaths[COUNTRIES_CORE].plot(figsize=(10, 6), title="Total deaths, linear")
+ax.set_xlabel(f"Days since {DEATH_COUNT_THRESHOLD} deaths")
+for c in COUNTRIES_CORE:
+    lvi = deaths[c].last_valid_index()
+    ax.text(x = lvi + 1, y = deaths[c][lvi], s = f"{c}: {deaths[c][lvi]:.0f}")
+# plt.savefig('covid_deaths_total_linear.png')    
+```
+
+```python Collapsed="false"
+ax = deaths_by_date.loc['2020-03-15':, COUNTRIES_CORE].plot(figsize=(10, 6), title="Total deaths, linear")
+# data_by_date.loc[COUNTRIES_CORE]
+# deaths_by_date = data_by_date.loc[COUNTRIES_ALL, ['deaths_culm']].unstack().sort_index().xs('deaths_culm', axis=1, drop_level=True)
+ax.set_xlabel(f"Date")
+for c in COUNTRIES_CORE:
+    lvi = deaths_by_date[c].last_valid_index()
+    ax.text(x = lvi + pd.Timedelta(days=1), y = deaths_by_date[c][lvi], s = f"{c}: {deaths_by_date[c][lvi]:.0f}")
+plt.savefig('covid_deaths_total_linear.png')    
+```
+
+```python Collapsed="false"
+deaths_prime = deaths[COUNTRIES_CORE].copy()
+deaths_prime.loc[73:, 'ES'] = np.NaN
+# deaths_prime['ES'][70:]
+```
+
+```python Collapsed="false"
+ax = deaths_prime[COUNTRIES_CORE].plot(figsize=(10, 6), title="Total deaths, linear")
+for c in COUNTRIES_CORE:
+    lvi = deaths_prime[c].last_valid_index()
+    ax.text(x = lvi + 1, y = deaths_prime[c][lvi], s = f"{c}: {deaths_prime[c][lvi]:.0f}")
+# plt.savefig('covid_deaths_total_linear.png')    
+```
+
+```python Collapsed="false"
+ax = cases[COUNTRIES_CORE].plot(figsize=(10, 6), title="Total cases, linear")
+for c in COUNTRIES_CORE:
+    lvi = cases[c].last_valid_index()
+    ax.text(x = lvi + 1, y = cases[c][lvi], s = c)
+plt.savefig('covid_cases_total_linear.png')    
+```
+
+```python Collapsed="false"
+ax = deaths[COUNTRIES_AMERICAS_DEAD].plot(figsize=(10, 6), title="Total deaths, linear")
+for c in COUNTRIES_AMERICAS_DEAD:
+    lvi = deaths[c].last_valid_index()
+    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)
+# plt.savefig('covid_deaths_total_linear.png')    
+```
+
+```python Collapsed="false"
+ax = deaths[COUNTRIES_CORE + ['BR', 'MX']].plot(figsize=(10, 6), title="Total deaths, linear")
+for c in COUNTRIES_CORE + ['BR', 'MX']:
+    lvi = deaths[c].last_valid_index()
+    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)
+# plt.savefig('covid_deaths_total_linear.png')    
+```
+
+```python Collapsed="false"
+ax = deaths[COUNTRIES_NORDIC].plot(figsize=(10, 6), title="Total deaths, linear")
+for c in COUNTRIES_NORDIC:
+    lvi = deaths[c].last_valid_index()
+    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)
+# plt.savefig('covid_deaths_total_linear.png')    
+```
+
+```python Collapsed="false"
+ax = deaths[COUNTRIES_OF_INTEREST].plot(figsize=(10, 6), title="Total deaths, linear")
+for c in COUNTRIES_OF_INTEREST:
+    lvi = deaths[c].last_valid_index()
+    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)
+plt.savefig('covid_deaths_total_linear_of_interest.png') 
+```
+
+```python Collapsed="false"
+ax = deaths[COUNTRIES_CORE].plot(logy=True, figsize=(10, 6), title="Total deaths, log")
+for c in COUNTRIES_CORE:
+    lvi = deaths[c].last_valid_index()
+    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)
+
+plt.savefig('covid_deaths_total_log.png')
+```
+
+```python Collapsed="false"
+ylim = (5*10**3, 5*10**4)
+ax = deaths[COUNTRIES_CORE].plot(logy=True, figsize=(10, 6), ylim=ylim, title="Total deaths, log")
+for c in COUNTRIES_CORE:
+    lvi = deaths[c].last_valid_index()
+    if ylim[0] < deaths[c][lvi] < ylim[1]:
+        ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)
+
+# plt.savefig('covid_deaths_total_log.png')
+```
+
+```python Collapsed="false"
+ax = deaths[COUNTRIES_FRIENDS].plot(logy=True, figsize=(10, 6), title="Total deaths, log")
+for c in COUNTRIES_FRIENDS:
+    lvi = deaths[c].last_valid_index()
+    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)
+
+# plt.savefig('covid_deaths_total_log.png')
+```
+
+```python Collapsed="false"
+ax = deaths[COUNTRIES_NORDIC].plot(logy=True, figsize=(10, 6), title="Total deaths, log")
+for c in COUNTRIES_NORDIC:
+    lvi = deaths[c].last_valid_index()
+    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)
+
+# plt.savefig('covid_deaths_total_log.png')
+```
+
+```python Collapsed="false"
+ax = deaths[COUNTRIES_OF_INTEREST].plot(logy=True, figsize=(10, 6), title="Total deaths, log")
+for c in COUNTRIES_OF_INTEREST:
+    lvi = deaths[c].last_valid_index()
+    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)
+
+plt.savefig('covid_deaths_total_log.png')
+```
+
+```python Collapsed="false"
+ax = deaths_pc.plot(figsize=(10, 6), title="Deaths per capita, linear")
+for c in deaths_pc.columns:
+    lvi = deaths_pc[c].last_valid_index()
+    ax.text(x = lvi + 1, y = deaths_pc[c][lvi], s = c)
+plt.savefig('covid_deaths_per_capita_linear.png')
+```
+
+```python Collapsed="false"
+ax = deaths_pc.plot(logy=True, figsize=(10, 6), title="Deaths per capita, log")
+for c in deaths_pc.columns:
+    lvi = deaths_pc[c].last_valid_index()
+    ax.text(x = lvi + 1, y = deaths_pc[c][lvi], s = c)
+```
+
+```python Collapsed="false"
+deaths_pc[['UK', 'IE']].plot( figsize=(10, 6), title="Deaths per capita, linear")
+```
+
+```python Collapsed="false"
+deaths_pc[['UK', 'IE']].plot(logy=True, figsize=(10, 6), title="Deaths per capita, log")
+```
+
+```python Collapsed="false"
+deaths[['UK', 'ES', 'IT']].plot(logy=True, figsize=(10, 6), title="Deaths, log")
+plt.savefig('covid_deaths_selected_log.png')
+```
+
+```python Collapsed="false"
+deaths[['UK', 'ES', 'IT', 'MX']].plot(logy=True, figsize=(10, 6), title="Deaths, log")
+```
+
+```python Collapsed="false"
+data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT']), :]
+```
+
+```python Collapsed="false"
+data_since_threshold['deaths_m4'] = data_since_threshold.groupby(level=1)['deaths'].transform(lambda x: x.rolling(4, 1).mean())
+data_since_threshold['deaths_m7'] = data_since_threshold.groupby(level=1)['deaths'].transform(lambda x: x.rolling(7, 1).mean())
+data_since_threshold['cases_m7'] = data_since_threshold.groupby(level=1)['cases'].transform(lambda x: x.rolling(7, 1).mean())
+# data_since_threshold['deaths_diff_m4'] = data_since_threshold.groupby(level=1)['deaths_diff'].transform(lambda x: x.rolling(4, 1).mean())
+# data_since_threshold['deaths_diff_m7'] = data_since_threshold.groupby(level=1)['deaths_diff'].transform(lambda x: x.rolling(7, 1).mean())
+data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT']), :]
+```
+
+```python Collapsed="false"
+deaths_m4 = (data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['deaths_m4']]
+             .unstack().sort_index().xs('deaths_m4', axis=1, drop_level=True))
+```
+
+```python Collapsed="false"
+deaths_m7 = (data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['deaths_m7']]
+             .unstack().sort_index().xs('deaths_m7', axis=1, drop_level=True))
+```
+
+```python Collapsed="false"
+cases_m7 = (data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['cases_m7']]
+             .unstack().sort_index().xs('cases_m7', axis=1, drop_level=True))
+```
+
+```python Collapsed="false"
+data_by_date['cases_m7'] = data_by_date.groupby(level=0)['cases'].transform(lambda x: x.rolling(7, 1).mean())
+data_by_date['deaths_m7'] = data_by_date.groupby(level=0)['deaths'].transform(lambda x: x.rolling(7, 1).mean())
+data_by_date
+```
+
+```python Collapsed="false"
+data_by_date.loc[('UK', '2020-07-15'):'UK', 'cases'].plot()
+```
+
+```python Collapsed="false"
+cases_by_date_m7 = data_by_date.loc[COUNTRIES_ALL, 'cases_m7'].unstack(level=0).sort_index()
+cases_by_date_m7[COUNTRIES_CORE].plot()
+```
+
+```python Collapsed="false"
+deaths_by_date_m7 = data_by_date.loc[COUNTRIES_ALL, 'deaths_m7'].unstack(level=0).sort_index()
+deaths_by_date_m7[COUNTRIES_CORE].plot()
+```
+
+```python Collapsed="false"
+ax = deaths_m4.plot(figsize=(10, 6), title="Deaths per day, 4 day moving average")
+for c in deaths_m4.columns:
+    lvi = deaths_m4[c].last_valid_index()
+    ax.text(x = lvi + 1, y = deaths_m4[c][lvi], s = c)
+plt.savefig('covid_deaths_per_day.png') 
+```
+
+```python Collapsed="false"
+ax = deaths_m4[COUNTRIES_CORE].plot(figsize=(10, 6), title="Deaths per day, 4 day moving average")
+for c in COUNTRIES_CORE:
+    lvi = deaths_m4[c].last_valid_index()
+    ax.text(x = lvi + 1, y = deaths_m4[c][lvi], s = c)
+plt.savefig('covid_deaths_per_day-core.png') 
+```
+
+```python Collapsed="false"
+ax = deaths_m4[COUNTRIES_FRIENDS].plot(figsize=(10, 6), title="Deaths per day, 4 day moving average")
+for c in COUNTRIES_FRIENDS:
+    lvi = deaths_m4[c].last_valid_index()
+    ax.text(x = lvi + 1, y = deaths_m4[c][lvi], s = c)
+# plt.savefig('covid_deaths_per_day-friends.png') 
+```
+
+```python Collapsed="false"
+C7s = 'ES FR IT UK'.split()
+ax = deaths_m7[C7s].plot(figsize=(10, 6), title="Deaths per day, 7 day moving average")
+for c in C7s:
+    lvi = deaths_m7[c].last_valid_index()
+    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = c)
+# plt.savefig('covid_deaths_per_day-friends.png') 
+```
+
+```python Collapsed="false"
+ax = deaths_m7[COUNTRIES_CORE].plot(figsize=(10, 6), title="Deaths per day, 7 day moving average")
+ax.set_xlabel(f"Days since {DEATH_COUNT_THRESHOLD} deaths")
+for c in COUNTRIES_CORE:
+    lvi = deaths_m7[c].last_valid_index()
+    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = c)
+# plt.axhline(0, color='0.7')
+plt.savefig('covid_deaths_per_day_7.png') 
+```
+
+```python Collapsed="false"
+ax = deaths_m7[COUNTRIES_FRIENDS].plot(figsize=(10, 6), title="Deaths per day, 7 day moving average")
+ax.set_xlabel(f"Days since {DEATH_COUNT_THRESHOLD} deaths")
+for c in COUNTRIES_FRIENDS:
+    lvi = deaths_m7[c].last_valid_index()
+    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = c)
+# plt.axhline(0, color='0.7')
+plt.savefig('covid_deaths_per_day-friends.png') 
+```
+
+```python Collapsed="false"
+deaths_m7_prime = deaths_m7[COUNTRIES_CORE].copy()
+deaths_m7_prime.loc[73:, 'ES'] = np.NaN
+deaths_m7_prime['ES'][70:]
+```
+
+```python Collapsed="false"
+ax = deaths_m7_prime[COUNTRIES_CORE].plot(figsize=(10, 6), title="Deaths per day, 7 day moving average")
+for c in COUNTRIES_CORE:
+    lvi = deaths_m7_prime[c].last_valid_index()
+    ax.text(x = lvi + 1, y = deaths_m7_prime[c][lvi], s = c)
+plt.savefig('covid_deaths_per_day_7.png') # see below for where this is written, with the projection
+```
+
+```python Collapsed="false"
+ax = deaths_by_date_m7.loc['2020-03-01':, COUNTRIES_CORE].plot(figsize=(10, 6), title="Deaths per day, 7 day moving average")
+ax.set_xlabel('Date')
+for c in COUNTRIES_CORE:
+    lvi = deaths_by_date_m7[c].last_valid_index()
+    ax.text(x = lvi + pd.Timedelta(days=1), y = deaths_by_date_m7[c][lvi], s = c)
+plt.savefig('covid_deaths_per_day_7.png') 
+```
+
+```python Collapsed="false"
+ax = deaths_m7[COUNTRIES_FRIENDS].plot(figsize=(10, 6), title="Deaths per day, 7 day moving average")
+for c in COUNTRIES_FRIENDS:
+    lvi = deaths_m7[c].last_valid_index()
+    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = c)
+plt.savefig('covid_deaths_per_day_friends_7.png') 
+```
+
+```python Collapsed="false"
+ax = deaths_m7[COUNTRIES_CORE + ['BR', 'MX']].plot(figsize=(10, 6), title="Deaths per day, 7 day moving average")
+for c in COUNTRIES_CORE + ['BR', 'MX']:
+    lvi = deaths_m7[c].last_valid_index()
+    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = c)
+# plt.savefig('covid_deaths_per_day_7.png') 
+```
+
+```python Collapsed="false"
+ax = deaths_by_date_m7.iloc[-30:][COUNTRIES_CORE].plot(figsize=(10, 6), title="Deaths per day, 7 day moving average")#, ylim=(-10, 100))
+ax.set_xlabel("Date")
+
+text_x_pos = deaths_by_date_m7.last_valid_index() + pd.Timedelta(days=1)
+
+for c in COUNTRIES_CORE:
+    lvi = deaths_by_date_m7[c].last_valid_index()
+#     if c != 'ES':
+    ax.text(x = text_x_pos, y = deaths_by_date_m7[c][lvi], s = f"{c}: {deaths_by_date_m7[c][lvi]:.0f}")
+plt.savefig('deaths_by_date_last_30_days.png') 
+```
+
+```python Collapsed="false"
+ax = deaths_by_date_m7.iloc[-30:][COUNTRIES_FRIENDS].plot(figsize=(10, 6), title="Deaths per day, 7 day moving average")#, ylim=(-10, 100))
+ax.set_xlabel("Date")
+
+text_x_pos = deaths_by_date_m7.last_valid_index() + pd.Timedelta(days=1)
+
+for c in COUNTRIES_FRIENDS:
+    lvi = deaths_by_date_m7[c].last_valid_index()
+#     if c != 'ES':
+    ax.text(x = text_x_pos, y = deaths_by_date_m7[c][lvi], s = f"{c}: {deaths_by_date_m7[c][lvi]:.0f}")
+plt.savefig('deaths_by_date_last_30_days_friends.png') 
+```
+
+```python Collapsed="false"
+ax = cases_m7[COUNTRIES_CORE].plot(figsize=(10, 6), title="Cases per day, 7 day moving average")
+for c in COUNTRIES_CORE:
+    lvi = cases_m7[c].last_valid_index()
+    ax.text(x = lvi + 1, y = cases_m7[c][lvi], s = c)
+plt.savefig('covid_cases_per_day-core.png') 
+```
+
+```python Collapsed="false"
+ax = cases_m7[COUNTRIES_FRIENDS].plot(figsize=(10, 6), title="Cases per day, 7 day moving average")
+for c in COUNTRIES_FRIENDS:
+    lvi = cases_m7[c].last_valid_index()
+    ax.text(x = lvi + 1, y = cases_m7[c][lvi], s = c)
+plt.savefig('covid_cases_per_day-core.png') 
+```
+
+```python Collapsed="false"
+ax = cases_by_date_m7.iloc[-30:][COUNTRIES_FRIENDS].plot(figsize=(10, 6), title="Cases per day, 7 day moving average")#, ylim=(-10, 100))
+ax.set_xlabel("Date")
+
+text_x_pos = cases_by_date_m7.last_valid_index() + pd.Timedelta(days=1)
+
+for c in COUNTRIES_FRIENDS:
+    lvi = cases_by_date_m7[c].last_valid_index()
+#     if c != 'ES':
+    ax.text(x = text_x_pos, y = cases_by_date_m7[c][lvi], s = f"{c}: {cases_by_date_m7[c][lvi]:.0f}")
+plt.savefig('cases_by_date_last_30_days_friends.png') 
+```
+
+```python Collapsed="false"
+def gmean_scale(items):
+    return gmean(items) / items[-1]
+```
+
+```python Collapsed="false"
+def doubling_time(df):
+    return np.log(2) / np.log((df.deaths_culm + df.deaths_g4) / df.deaths_culm)
+
+def doubling_time_7(df):
+    return np.log(2) / np.log((df.deaths_culm + df.deaths_g7) / df.deaths_culm)
+```
+
+```python Collapsed="false"
+# data_since_threshold['deaths_g4'] = data_since_threshold.groupby(level=1)['deaths'].transform(lambda x: x.rolling(4, 1).apply(gmean_scale, raw=True))
+# data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT']), :]
+```
+
+```python Collapsed="false"
+data_since_threshold['deaths_g4'] = data_since_threshold.groupby(level=1)['deaths'].transform(lambda x: x.rolling(4, 1).apply(gmean, raw=True))
+data_since_threshold['deaths_g7'] = data_since_threshold.groupby(level=1)['deaths'].transform(lambda x: x.rolling(7, 1).apply(gmean, raw=True))
+data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT']), :]
+```
+
+```python Collapsed="false"
+data_since_threshold['doubling_time'] = data_since_threshold.groupby(level=1).apply(doubling_time).reset_index(level=0, drop=True).sort_index()
+data_since_threshold['doubling_time_7'] = data_since_threshold.groupby(level=1).apply(doubling_time_7).reset_index(level=0, drop=True).sort_index()
+# data_since_threshold.loc[(slice(None), 'UK'), :]
+```
+
+```python Collapsed="false"
+data_by_date['deaths_g4'] = data_by_date.groupby(level=0)['deaths'].transform(lambda x: x.rolling(4, 1).apply(gmean, raw=True))
+data_by_date['deaths_g7'] = data_by_date.groupby(level=0)['deaths'].transform(lambda x: x.rolling(7, 1).apply(gmean, raw=True))
+data_by_date['doubling_time'] = data_by_date.groupby(level=0).apply(doubling_time).reset_index(level=0, drop=True).sort_index()
+data_by_date['doubling_time_7'] = data_by_date.groupby(level=0).apply(doubling_time_7).reset_index(level=0, drop=True).sort_index()
+data_by_date.loc['UK']
+```
+
+```python Collapsed="false"
+doubling_times = (data_since_threshold.loc[(slice(None), COUNTRIES_OF_INTEREST), ['doubling_time']]
+             .unstack().sort_index().xs('doubling_time', axis=1, drop_level=True))
+doubling_times.replace([np.inf, -np.inf], np.nan, inplace=True)
+```
+
+```python Collapsed="false"
+doubling_times_7 = (data_since_threshold.loc[(slice(None), COUNTRIES_OF_INTEREST), ['doubling_time_7']]
+             .unstack().sort_index().xs('doubling_time_7', axis=1, drop_level=True))
+doubling_times_7.replace([np.inf, -np.inf], np.nan, inplace=True)
+```
+
+```python Collapsed="false"
+ax = doubling_times.plot(figsize=(10, 6), title="Doubling times, 4 day average")
+for c in doubling_times.columns:
+    lvi = doubling_times[c].last_valid_index()
+    ax.text(x = lvi + 1, y = doubling_times[c][lvi], s = c)
+# plt.savefig('covid_deaths_per_day.png') 
+```
+
+```python Collapsed="false"
+ax = doubling_times_7[COUNTRIES_CORE].plot(figsize=(10, 6), title="Doubling times, 7 day average")
+ax.legend(loc="upper left")
+for c in COUNTRIES_CORE:
+    lvi = doubling_times_7[c].last_valid_index()
+    ax.text(x = lvi + 1, y = doubling_times_7[c][lvi], s = c)
+plt.savefig('covid_doubling_times_7.png') 
+```
+
+```python Collapsed="false"
+ax = doubling_times[COUNTRIES_CORE].plot(figsize=(10, 6), title="Doubling times, 4 day average")
+for c in COUNTRIES_CORE:
+    lvi = doubling_times[c].last_valid_index()
+    ax.text(x = lvi + 1, y = doubling_times[c][lvi], s = c)
+plt.savefig('covid_doubling_times.png') 
+```
+
+```python Collapsed="false"
+ax = doubling_times[COUNTRIES_FRIENDS].plot(figsize=(10, 6), title="Doubling times")
+for c in COUNTRIES_FRIENDS:
+    lvi = doubling_times[c].last_valid_index()
+    ax.text(x = lvi + 1, y = doubling_times[c][lvi], s = c)
+plt.savefig('covid_doubling_times_friends.png')
+```
+
+```python Collapsed="false"
+ax = doubling_times[C7s].plot(figsize=(10, 6), title="Doubling times")
+for c in C7s:
+    lvi = doubling_times[c].last_valid_index()
+    ax.text(x = lvi + 1, y = doubling_times[c][lvi], s = c)
+# plt.savefig('covid_doubling_times_friends.png')
+```
+
+```python Collapsed="false"
+# deaths_diff_m4 = (data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['deaths_diff_m4']]
+#              .unstack().sort_index().xs('deaths_diff_m4', axis=1, drop_level=True))
+```
+
+```python Collapsed="false"
+# deaths_diff_m7 = (data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['deaths_diff_m7']]
+#              .unstack().sort_index().xs('deaths_diff_m7', axis=1, drop_level=True))
+```
+
+```python Collapsed="false"
+# deaths_diff_m7
+```
+
+```python Collapsed="false"
+# data_since_threshold.replace([np.inf, -np.inf], np.nan).groupby(level=1).last().loc[COUNTRIES_ALL]#, [doubling_time]]
+```
+
+```python Collapsed="false"
+dstl = data_since_threshold.replace([np.inf, -np.inf], np.nan).groupby(level=1).last()
+dstl.loc[dstl.index.intersection(COUNTRIES_ALL)]
+```
+
+```python Collapsed="false"
+# data_since_threshold.replace([np.inf, -np.inf], np.nan).groupby(level=1).last().loc[['UK', 'DE', 'IT']]#, [doubling_time]]
+dstl.loc[['UK', 'DE', 'IT', 'FR', 'ES']]
+```
+
+```python Collapsed="false"
+data_since_threshold.loc[(slice(None), ['UK']), :].tail(20)
+```
+
+```python Collapsed="false"
+data_since_threshold.loc[(slice(None), ['ES']), :].tail(20)
+```
+
+<!-- #region Collapsed="false" -->
+## Death projections
+<!-- #endregion -->
+
+```python Collapsed="false"
+data_since_threshold.loc[(slice(None), ['UK']), :].tail(15)
+```
+
+```python Collapsed="false"
+it_since_threshold = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['IT']), :]
+s_end = it_since_threshold.index.max()[0]
+s_end
+```
+
+```python Collapsed="false"
+uk_projection = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), :]
+uk_current_end = uk_projection.index.max()[0] + 1
+# s_start = uk_projection.index.max()[0] + 1
+uk_current_end
+```
+
+```python Collapsed="false"
+current_uk_deaths_m7 = uk_projection[uk_projection.deaths_m7 >= 0].iloc[-1].deaths_m7
+current_uk_deaths_m7
+```
+
+```python Collapsed="false"
+it_since_threshold[it_since_threshold.deaths_m7 <= current_uk_deaths_m7].loc[60:].first_valid_index()[0]
+```
+
+```python Collapsed="false"
+s_start = it_since_threshold[it_since_threshold.deaths_m7 <= current_uk_deaths_m7].loc[60:].first_valid_index()[0]
+s_start
+```
+
+```python Collapsed="false"
+s_start_date = data_since_threshold.loc[(89, 'IT'), 'dateRep']# .iloc[0]
+s_start_date
+```
+
+```python Collapsed="false"
+s_end - s_start
+```
+
+```python Collapsed="false"
+uk_end = s_end - s_start + uk_current_end
+uk_end
+```
+
+```python Collapsed="false"
+proj = it_since_threshold.loc[(slice(s_start, s_end), slice(None)), ['cases', 'deaths', 'deaths_m7']]
+ndiff = uk_current_end - s_start
+proj.index = pd.MultiIndex.from_tuples([(n + ndiff, 'UK') for n, _ in proj.index], names=proj.index.names)
+proj
+```
+
+```python Collapsed="false"
+it_since_threshold.loc[(slice(s_start - 8, s_start + 2), slice(None)), ['cases', 'deaths', 'deaths_m7']]
+```
+
+```python Collapsed="false"
+uk_projection[['cases', 'deaths', 'deaths_m7']].tail()
+```
+
+```python Collapsed="false"
+# proj['deaths_m7'] = proj['deaths_m7'] + 20
+# proj
+```
+
+<!-- #region Collapsed="false" -->
+Projected deaths, UK following IT trend from now.
+<!-- #endregion -->
+
+```python Collapsed="false"
+uk_projection = uk_projection.append(proj, sort=True)
+uk_projection.deaths.sum()
+```
+
+```python Collapsed="false"
+uk_projection = uk_projection.droplevel(1)
+uk_projection
+```
+
+```python Collapsed="false"
+uk_projection.loc[152, 'deaths']
+```
+
+<!-- #region Collapsed="false" -->
+## Correction for cumulative deaths correction on 14 August
+<!-- #endregion -->
+
+```python Collapsed="false"
+# uk_projection.loc[152, 'deaths'] = 50
+```
+
+```python Collapsed="false"
+uk_projection['deaths_m7'] = uk_projection['deaths'].transform(lambda x: x.rolling(7, 1).mean())
+uk_projection.loc[(uk_current_end - 20):(uk_current_end + 5)]
+```
+
+```python Collapsed="false"
+uk_projection.loc[(uk_current_end - 5):]
+```
+
+```python Collapsed="false"
+uk_projection.deaths_m7.plot()
+```
+
+```python Collapsed="false"
+proj.droplevel(level=1)
+```
+
+```python Collapsed="false"
+ax = deaths_m7[COUNTRIES_CORE].plot()
+# uk_projection['deaths_m7'].plot(figsize=(10, 6), title="Deaths per day, 7 day moving average", label="Projection", style='--', ax=ax)
+proj.droplevel(level=1)['deaths_m7'].plot(figsize=(10, 6), title="Deaths per day, 7 day moving average", label="Projection", style='--', ax=ax)
+ax.set_xlabel(f"Days since {DEATH_COUNT_THRESHOLD} deaths")
+for c in COUNTRIES_CORE:
+    lvi = deaths_m7[c].last_valid_index()
+    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = c)
+# plt.savefig('covid_deaths_per_day_7.png') 
+```
+
+```python Collapsed="false"
+it_since_threshold.deaths.sum()
+```
+
+<!-- #region Collapsed="false" -->
+# Excess deaths calculation
+<!-- #endregion -->
+
+```python Collapsed="false"
+with open('excess_deaths.json') as f:
+    excess_deaths_data = json.load(f)
+    
+# with open('excess_death_accuracy.json') as f:
+#     excess_death_accuracy = json.load(f)
+    
+excess_deaths_data
+```
+
+```python Collapsed="false"
+additional_deaths = data_by_date.loc[('UK', excess_deaths_data['end_date']):('UK')].iloc[1:].deaths.sum()
+additional_deaths
+```
+
+```python Collapsed="false"
+uk_covid_deaths = data_by_date.loc['UK'].deaths.sum()
+uk_covid_deaths
+```
+
+```python Collapsed="false"
+uk_deaths_to_date = int(excess_deaths_data['excess_deaths']) + additional_deaths
+uk_deaths_to_date
+```
+
+```python Collapsed="false"
+# excess_deaths_upto = '2020-05-08'
+# excess_deaths = 54500
+```
+
+```python Collapsed="false"
+# excess_deaths_upto = excess_deaths_data['end_date']
+# excess_deaths = excess_deaths_data['excess_deaths']
+```
+
+<!-- #region Collapsed="false" -->
+Recorded deaths in period where ONS has reported total deaths
+<!-- #endregion -->
+
+```python Collapsed="false"
+# ons_reported_deaths = base_data.loc['UK'][:excess_deaths_upto]['deaths'].sum()
+# ons_reported_deaths
+```
+
+```python Collapsed="false"
+# excess_deaths_upto
+```
+
+<!-- #region Collapsed="false" -->
+## Correction for deaths total correction on 14 August
+<!-- #endregion -->
+
+```python Collapsed="false"
+# ons_unreported_deaths_data = base_data.loc['UK'][excess_deaths_upto:].iloc[1:]['deaths']
+# ons_unreported_deaths_data['2020-08-14'] = 50
+```
+
+```python Collapsed="false"
+# ons_unreported_deaths = ons_unreported_deaths_data.sum()
+# ons_unreported_deaths
+```
+
+```python Collapsed="false"
+# scaled_ons_unreported_deaths = ons_unreported_deaths * excess_death_accuracy
+# scaled_ons_unreported_deaths
+```
+
+```python Collapsed="false"
+# uk_deaths_to_date = excess_deaths + scaled_ons_unreported_deaths
+# uk_deaths_to_date
+```
+
+```python Collapsed="false"
+# data_since_threshold.loc[(slice(None), 'UK'), :][data_since_threshold.dateRep == excess_deaths_data['end_date']]
+```
+
+```python Collapsed="false"
+# data_since_threshold[data_since_threshold.dateRep == excess_deaths_data['end_date']].loc[(slice(None), 'UK'), :]
+```
+
+```python Collapsed="false"
+# ons_unreported_start = data_since_threshold[data_since_threshold.dateRep == excess_deaths_data['end_date']].loc[(slice(None), 'UK'), :].first_valid_index()[0] + 1
+# ons_unreported_start
+```
+
+```python Collapsed="false"
+# unreported_projected_deaths = uk_projection.loc[ons_unreported_start:].deaths.sum()
+# unreported_projected_deaths
+```
+
+```python Collapsed="false"
+# unreported_projected_deaths_scaled = unreported_projected_deaths * excess_death_accuracy
+# unreported_projected_deaths_scaled
+```
+
+```python Collapsed="false"
+# uk_projection.loc[(s_start):].deaths.sum()
+```
+
+```python Collapsed="false"
+# deaths_actual_projected_scaled = uk_deaths_to_date + uk_projection.loc[(s_start):].deaths.sum() * excess_death_accuracy
+# deaths_actual_projected_scaled
+```
+
+```python Collapsed="false"
+# excess_deaths / reported_deaths
+```
+
+<!-- #region Collapsed="false" -->
+True deaths to date, if we follow the scaling of excess deaths over reported deaths so far.
+<!-- #endregion -->
+
+```python Collapsed="false"
+# uk_covid_deaths = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), 'deaths_culm'].iloc[-1]
+# uk_covid_deaths
+```
+
+```python Collapsed="false"
+# uk_covid_deaths_scaled = excess_deaths + unreported_deaths * excess_death_accuracy
+# uk_covid_deaths_scaled
+```
+
+```python Collapsed="false"
+# data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['IT']), 'dateRep'].iloc[-1] + pd.Timedelta(s_end - s_start, unit='days')
+```
+
+```python Collapsed="false"
+# data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), 'dateRep'].iloc[-1].strftime("%Y-%m-%d")
+```
+
+```python Collapsed="false"
+# uk_covid_deaths * excess_deaths / reported_deaths
+```
+
+```python Collapsed="false"
+# uk_projection.deaths.sum() * excess_deaths / reported_deaths
+```
+
+```python Collapsed="false"
+# data_since_threshold.loc[(slice(None), 'FR'), :]
+# data_since_threshold[data_since_threshold.dateRep == '2020-05-18'].loc[(slice(None), 'FR'), :]
+```
+
+<!-- #region Collapsed="false" -->
+## School reopenings
+<!-- #endregion -->
+
+```python Collapsed="false"
+school_reopenings = {
+    'ES': {'date': '2020-05-18'},
+    'FR': {'date': '2020-05-18'}, # some areas only
+#     'IT': {'date': '2020-09-01'},
+    # 'IE': {'date': '2020-09-01'},
+    'DE': {'date': '2020-05-04'},
+    'UK': {'date': '2020-06-01'}
+}
+```
+
+```python Collapsed="false"
+data_since_threshold[data_since_threshold.dateRep == '2020-05-04'].loc[(slice(None), ['DE']), :].first_valid_index()
+```
+
+```python Collapsed="false"
+data_since_threshold[data_since_threshold.dateRep == '2020-05-04'].loc[(slice(None), ['DE']), :].iloc[0].deaths_m7
+```
+
+```python Collapsed="false"
+for cID in school_reopenings:
+    dst_in = data_since_threshold[data_since_threshold.dateRep == (school_reopenings[cID]['date'])].loc[(slice(None), [cID]), :]
+    dst_i = dst_in.first_valid_index()
+    dst_n = dst_in.iloc[0].deaths_m7
+    school_reopenings[cID]['since_threshold'] = dst_i[0]
+    school_reopenings[cID]['deaths_m7'] = dst_n
+school_reopenings
+```
+
+```python Collapsed="false"
+ax = deaths_m7[COUNTRIES_CORE].plot(figsize=(15, 9), title="Deaths per day, 7 day moving average")
+# uk_projection.deaths_m7.plot(ax=ax)
+for c in COUNTRIES_CORE:
+    lvi = deaths_m7[c].last_valid_index()
+    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = f"{c}: {deaths_m7[c][lvi]:.0f}")
+    if c in school_reopenings:
+        marker_col = [l for l in ax.lines if l.get_label() == c][0].get_color()
+        ax.plot(school_reopenings[c]['since_threshold'], school_reopenings[c]['deaths_m7'], '*', 
+                markersize=18, markerfacecolor=marker_col, markeredgecolor=marker_col)
+        ax.text(x = school_reopenings[c]['since_threshold'] + 1, y = school_reopenings[c]['deaths_m7'], 
+                s = f"{school_reopenings[c]['date']}: {school_reopenings[c]['deaths_m7']:.0f}")
+plt.savefig('school_reopenings.png')
+```
+
+```python Collapsed="false"
+# ax = deaths_m7[COUNTRIES_CORE].plot(figsize=(15, 9), title="Deaths per day, 7 day moving average",
+#                                    xlim=(46, 91), ylim=(0, 400))
+# # uk_projection.deaths_m7.plot(ax=ax)
+# for c in COUNTRIES_CORE:
+#     lvi = deaths_m7[c].last_valid_index()
+#     ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = f"{c}: {deaths_m7[c][lvi]:.0f}", fontsize=14)
+#     if c in school_reopenings:
+#         marker_col = [l for l in ax.lines if l.get_label() == c][0].get_color()
+#         ax.plot(school_reopenings[c]['since_threshold'], school_reopenings[c]['deaths_m7'], '*', 
+#                 markersize=18, markerfacecolor=marker_col, markeredgecolor=marker_col)
+#         ax.text(x = school_reopenings[c]['since_threshold'] + 1, y = school_reopenings[c]['deaths_m7'], 
+#                 s = f"{school_reopenings[c]['date']}: {school_reopenings[c]['deaths_m7']:.0f}",
+#                 fontsize=14)
+# plt.savefig('school_reopenings_detail.png')
+```
+
+<!-- #region Collapsed="false" -->
+# Lockdown graphs
+<!-- #endregion -->
+
+```python Collapsed="false"
+lockdown_dates = {
+    'ES': { 'part_start': {'date': '2020-03-14'}
+          , 'full_start': {'date': '2020-03-15'}
+          , 'part_finish': {'date': '2020-05-18'}
+          },
+    'FR': { 'part_start': {'date': '2020-03-13'}
+          , 'full_start': {'date': '2020-03-17'}
+          , 'part_finish': {'date': '2020-05-11'}
+          },
+    'IT': { 'part_start': {'date': '2020-03-08'}
+          , 'full_start': {'date': '2020-03-10'}
+          , 'part_finish': {'date': '2020-05-04'}
+          },
+    'DE': { #'part_start': {'date': '2020-03-13'}
+          'full_start': {'date': '2020-03-22'}
+          , 'part_finish': {'date': '2020-05-06'}
+          },
+    'UK': { 'part_start': {'date': '2020-03-23'}
+          , 'full_start': {'date': '2020-03-23'}
+          , 'part_finish': {'date': '2020-05-31'}
+          },
+    'IE': { #'part_start': {'date': '2020-03-12'}
+          'full_start': {'date': '2020-03-27'}
+          , 'part_finish': {'date': '2020-05-18'}
+          },
+}
+```
+
+```python Collapsed="false"
+for cID in lockdown_dates:
+    for phase in lockdown_dates[cID]:
+        dst_in = data_since_threshold[data_since_threshold.dateRep == (lockdown_dates[cID][phase]['date'])].loc[(slice(None), [cID]), :]
+        dst_i = dst_in.first_valid_index()
+        dst_n = dst_in.iloc[0].deaths_m7
+        dst_c = dst_in.iloc[0].cases_m7
+        lockdown_dates[cID][phase]['since_threshold'] = dst_i[0]
+        lockdown_dates[cID][phase]['deaths_m7'] = dst_n
+        lockdown_dates[cID][phase]['cases_m7'] = dst_c
+
+lockdown_dates
+```
+
+```python Collapsed="false"
+ax = deaths_m7[COUNTRIES_CORE].plot(figsize=(15, 9), title="Deaths per day, 7 day moving averagee, with lockdown dates")
+ax.set_xlabel(f"Days since {DEATH_COUNT_THRESHOLD} deaths")
+# uk_projection.deaths_m7.plot(ax=ax)
+for c in COUNTRIES_CORE:
+    lvi = deaths_m7[c].last_valid_index()
+    if c != 'UK':
+        ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = f"{c}: {deaths_m7[c][lvi]:.0f}")
+    if c in lockdown_dates:
+        for phase in lockdown_dates[c]:
+            marker_col = [l for l in ax.lines if l.get_label() == c][0].get_color()
+            ax.plot(lockdown_dates[c][phase]['since_threshold'], lockdown_dates[c][phase]['deaths_m7'], '*',
+                    markersize=18, markerfacecolor=marker_col, markeredgecolor=marker_col)
+            if 'start' not in phase:
+                ax.text(x = lockdown_dates[c][phase]['since_threshold'] + 1, y = lockdown_dates[c][phase]['deaths_m7'], 
+                        s = f"{lockdown_dates[c][phase]['date']}: {lockdown_dates[c][phase]['deaths_m7']:.0f}")
+# plt.savefig('school_reopenings.png')
+```
+
+```python Collapsed="false"
+ax = cases_m7.iloc[-50:][COUNTRIES_CORE].plot(figsize=(15, 9), title="Cases per day, 7 day moving average, with lockdown dates") #, ylim=(-10, 1500))
+ax.set_xlabel(f"Days since {DEATH_COUNT_THRESHOLD} deaths")
+# uk_projection.deaths_m7.plot(ax=ax)
+for c in COUNTRIES_CORE:
+    lvi = cases_m7[c].last_valid_index()
+#     if c != 'UK':
+    ax.text(x = lvi + 1, y = cases_m7[c][lvi], s = f"{c}: {cases_m7[c][lvi]:.0f}")
+
+```
+
+```python Collapsed="false"
+ax = cases_m7[COUNTRIES_CORE].plot(figsize=(15, 9), title="Cases per day, 7 day moving average, with lockdown dates")
+ax.set_xlabel(f"Days since {DEATH_COUNT_THRESHOLD} deaths")
+# uk_projection.deaths_m7.plot(ax=ax)
+for c in COUNTRIES_CORE:
+    lvi = cases_m7[c].last_valid_index()
+#     if c != 'UK':
+    ax.text(x = lvi + 1, y = cases_m7[c][lvi], s = f"{c}: {cases_m7[c][lvi]:.0f}")
+    if c in lockdown_dates:
+        for phase in lockdown_dates[c]:
+            marker_col = [l for l in ax.lines if l.get_label() == c][0].get_color()
+            if 'start' in phase:
+                marker_shape = '^'
+            else:
+                marker_shape = 'v'
+            ax.plot(lockdown_dates[c][phase]['since_threshold'], lockdown_dates[c][phase]['cases_m7'], 
+                    marker_shape,
+                    markersize=18, markerfacecolor=marker_col, markeredgecolor=marker_col)
+            if 'start' not in phase:
+                ax.text(x = lockdown_dates[c][phase]['since_threshold'] + 1, y = lockdown_dates[c][phase]['cases_m7'], 
+                        s = f"{lockdown_dates[c][phase]['date']}: {lockdown_dates[c][phase]['cases_m7']:.0f}")
+# plt.savefig('cases_per_day_with_lockdown.png')
+```
+
+```python Collapsed="false"
+plot_start_date = '2020-03-01'
+ax = cases_by_date_m7.loc[plot_start_date:, COUNTRIES_CORE].plot(figsize=(15, 9), title="Cases per day, 7 day moving average, with lockdown dates")
+ax.set_xlabel(f"Date")
+ax.set_ylabel("Number of cases")
+# uk_projection.deaths_m7.plot(ax=ax)
+for c in COUNTRIES_CORE:
+    lvi = cases_by_date_m7[c].last_valid_index()
+#     if c != 'UK':
+    ax.text(x = lvi + pd.Timedelta(days=1), y = cases_by_date_m7[c][lvi], s = f"{c}: {cases_by_date_m7[c][lvi]:.0f}")
+    if c in lockdown_dates:
+        for phase in lockdown_dates[c]:
+            marker_col = [l for l in ax.lines if l.get_label() == c][0].get_color()
+            if 'start' in phase:
+                marker_shape = '^'
+            else:
+                marker_shape = 'v'
+            marker_x_pos = ax.get_xlim()[0] + mpl.dates.date2num(pd.to_datetime(lockdown_dates[c][phase]['date'])) - mpl.dates.date2num(pd.to_datetime(plot_start_date))
+            ax.plot(marker_x_pos, lockdown_dates[c][phase]['cases_m7'], 
+                    marker_shape,
+                    markersize=18, markerfacecolor=marker_col, markeredgecolor=marker_col)
+            if 'start' not in phase:
+                ax.text(x = marker_x_pos + 3, y = lockdown_dates[c][phase]['cases_m7'], 
+                        s = f"{lockdown_dates[c][phase]['date']}: {lockdown_dates[c][phase]['cases_m7']:.0f}")
+plt.savefig('cases_per_day_with_lockdown.png')
+```
+
+```python Collapsed="false"
+ax = cases_m7[COUNTRIES_CORE].plot(figsize=(10, 6), title="Cases per day, 7 day moving average")
+for c in COUNTRIES_CORE:
+    lvi = cases_m7[c].last_valid_index()
+    ax.text(x = lvi + 1, y = cases_m7[c][lvi], s = c)
+plt.savefig('covid_cases_per_day-core.png') 
+```
+
+```python Collapsed="false"
+ax = deaths_m7[COUNTRIES_CORE].plot(figsize=(15, 9), title="Deaths per day, 7 day moving average",
+                                   xlim=(0, 15), 
+                                    ylim=(0, 66)
+                                   )
+# uk_projection.deaths_m7.plot(ax=ax)
+for c in COUNTRIES_CORE:
+    lvi = deaths_m7[c].last_valid_index()
+    if c in lockdown_dates:
+        for phase in lockdown_dates[c]:
+            if 'start' in phase:
+                print(c, phase)
+                marker_col = [l for l in ax.lines if l.get_label() == c][0].get_color()
+                ax.plot(lockdown_dates[c][phase]['since_threshold'], lockdown_dates[c][phase]['deaths_m7'], '*', 
+                        markersize=18, markerfacecolor=marker_col, markeredgecolor=marker_col)
+                ax.text(x = lockdown_dates[c][phase]['since_threshold'] + 0.3, y = lockdown_dates[c][phase]['deaths_m7'], 
+                        s = f"{lockdown_dates[c][phase]['date']}: {lockdown_dates[c][phase]['deaths_m7']:.0f}")
+# plt.savefig('school_reopenings.png')
+```
+
+```python Collapsed="false"
+
+```
+
+```python Collapsed="false"
+
+```
+
+<!-- #region Collapsed="false" -->
+# Write results to summary file
+<!-- #endregion -->
+
+```python Collapsed="false"
+with open('covid_summary.md', 'w') as f:
+    f.write('% Covid death data summary\n')
+    f.write('% Neil Smith\n')
+    f.write(f'% Created on {datetime.datetime.now().strftime("%Y-%m-%d")}\n')
+    f.write('\n')
+        
+    last_uk_date = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), 'dateRep'].iloc[-1]
+    f.write(f'> Last UK data from {last_uk_date.strftime("%Y-%m-%d")}\n')
+    f.write('\n')    
+```
+
+```python Collapsed="false"
+with open('covid_summary.md', 'a') as f:
+    f.write('## Headlines\n')
+    f.write('\n')
+    f.write('| []() | |\n')
+    f.write('|:---|---:|\n')
+    f.write(f'| Deaths reported so far | {uk_covid_deaths} | \n')
+    f.write(f'| Total Covid deaths to date (estimated) | {uk_deaths_to_date:.0f} |\n')
+    projection_date = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['IT']), 'dateRep'].iloc[-1] + pd.Timedelta(s_end - s_start, unit='days')
+#     f.write(f'| Projected total deaths up to {projection_date.strftime("%Y-%m-%d")} | {deaths_actual_projected_scaled:.0f} | \n')
+    f.write('\n')
+```
+
+```python Collapsed="false"
+with open('covid_summary.md', 'a') as f:
+    f.write('## Total deaths\n')
+#     f.write(f'Time based on days since {DEATH_COUNT_THRESHOLD} deaths\n')
+    f.write('\n')
+    f.write('![Total deaths](covid_deaths_total_linear.png)\n')
+    f.write('\n')
+    f.write('| Country ID | Country name | Total deaths |\n')
+    f.write('|:-----------|:-------------|-------------:|\n')
+    for c in sorted(COUNTRIES_CORE):
+        lvi = deaths_by_date[c].last_valid_index()
+        f.write(f'| {c} | {countries.loc[c].countriesAndTerritories} | {int(deaths_by_date[c][lvi])} |\n')
+    f.write('\n')
+```
+
+```python Collapsed="false"
+with open('covid_summary.md', 'a') as f:
+    f.write('## All-causes deaths, UK\n')
+    f.write('\n')
+    f.write('![All-causes deaths](deaths-radar.png)\n')
+    f.write('\n')
+    f.write('### True deaths\n')
+    f.write('\n')
+    f.write(f'The number of deaths reported in official statistics, {uk_covid_deaths}, is an underestimate '
+            'of the true number of Covid deaths.\n'
+            'This is especially true early in the pandemic, approximately March to May 2020.\n')
+    f.write('We can get a better understanding of the impact of Covid by looking at the number of deaths, '
+            'over and above what would be expected at each week of the year.\n')
+    f.write(f'The ONS (and other bodies in Scotland and Northern Ireland) have released data on the number of deaths '
+            f'up to {pd.to_datetime(excess_deaths_data["end_date"]).strftime("%d %B %Y")}.\n\n')
+    f.write('If, for each of those weeks, I take the largest of the excess deaths or the reported Covid deaths, ')
+    f.write(f'I estimate there have been **{uk_deaths_to_date}** total deaths so far.\n')
+    f.write('\n')
+```
+
+```python Collapsed="false"
+# with open('covid_summary.md', 'a') as f:
+#     f.write(f'In that period, the UK reported {ons_reported_deaths} Covid deaths.\n')
+#     f.write(f'In the last three weeks for which excess deaths have been reported, the excess deaths have been {excess_death_accuracy:.3f} higher than the Covid-reported deaths.\n')
+# #     f.write(f'That means the actual number of Covid death is about {excess_deaths / reported_deaths:.2f} times higher than the reported figures.\n')
+#     f.write('\n')
+#     f.write(f'The UK has reported {uk_covid_deaths} deaths so far.\n')
+#     f.write(f'Using the scaling factor above (for Covid-19 deaths after the ONS figures), I infer that there have been **{uk_deaths_to_date:.0f}** total deaths so far.\n')
+#     f.write('\n')
+```
+
+```python Collapsed="false"
+with open('covid_summary.md', 'a') as f:
+    f.write('## Deaths per day\n')
+    f.write(f'Based on a 7-day moving average\n')
+    f.write('\n')
+    f.write('![Deaths per day](covid_deaths_per_day_7.png)\n')
+    f.write('\n')
+    f.write('![Deaths per day, last 30 days](deaths_by_date_last_30_days.png)\n')
+    f.write('\n')
+```
+
+```python Collapsed="false"
+s_end - s_start - 1
+```
+
+```python Collapsed="false"
+with open('covid_summary.md', 'a') as f:
+    f.write('## Projected deaths\n')
+    f.write("Previously, I was using Italy's deaths data to predict the UK's deaths data. "
+            "This worked when both countries' trends of deaths were falling or constant, "
+            "as they were until September.\n")
+    f.write("\n")
+    f.write("As of mid-September, with cases rising in both countries at around the same time, "
+            "I can't use Italian data to predict the UK's future deaths.\n")
+    f.write("\n")
+#     f.write(f"The UK's daily deaths data is very similar to Italy's.\n")
+#     f.write(f'If I use the Italian data for the next {s_end - s_start - 1} days (from {s_start_date.strftime("%d %B %Y")} onwards),')
+#     f.write(f' the UK will report {uk_projection.deaths.sum()} deaths on day {uk_end} of the epidemic.\n')
+#     f.write('\n')
+#     f.write('Using the excess deaths scaling from above, that will translate into ')
+#     f.write(f'**{deaths_actual_projected_scaled:.0f}** Covid deaths total.\n')
+#     f.write('\n')
+```
+
+```python Collapsed="false"
+with open('covid_summary.md', 'a') as f:
+    f.write('## Deaths doubling times\n')
+    f.write(f'Based on a 7-day moving average\n')
+    f.write('\n')
+    f.write('![Deaths doubling times](covid_doubling_times_7.png)\n')
+    f.write('\n')
+```
+
+```python Collapsed="false"
+with open('covid_summary.md', 'a') as f:
+    f.write('\n')
+    f.write('## Cases per day and lockdown dates\n')
+    f.write(f'Based on a 7-day moving average\n')
+    f.write('\n')
+    f.write('![Cases per day](cases_per_day_with_lockdown.png)\n')
+    f.write('\n')
+```
+
+```python Collapsed="false"
+with open('covid_summary.md', 'a') as f:
+    f.write('| Country ID | Country name | Most recent daily cases | Most recent daily deaths |\n')
+    f.write('|:-----------|:-------------|------------------------:|-------------------------:|\n')
+    for c in sorted(COUNTRIES_CORE):
+        lvic = cases_m7[c].last_valid_index()
+        lvid = deaths_m7[c].last_valid_index()
+        f.write(f'| {c} | {countries.loc[c].countriesAndTerritories} | {cases_m7[c][lvic]:.0f} | {deaths_m7[c][lvid]:.0f} | \n')
+    f.write('\n')
+    f.write('(Figures are 7-day averages)\n')
+    f.write('\n')
+```
+
+```python Collapsed="false"
+with open('hospital_normalisation_date.json') as f:
+    hospital_normalisation_date_data = json.load(f)
+```
+
+```python Collapsed="false"
+with open('covid_summary.md', 'a') as f:
+    f.write('## Hospital care\n')
+    f.write(f'Based on a 7-day moving average\n')
+    f.write('\n')
+    f.write('![Cases, admissions, deaths](cases_admissions_deaths.png)\n')
+    f.write('\n')
+#     f.write('Admissions are shifted by 10 days, deaths by 25 days. '
+#             'This reflects the typical timescales of infection: '
+#             'patients are admitted 10 days after onset of symptoms, '
+#             'and die 15 days after admission.\n')
+#     f.write('\n')
+#     f.write('Plotting this data with offsets shows more clearly '
+#             'the relative changes in these three metrics.\n')
+    f.write('Due to the large scale differences between the three '
+            'measures, they are all normalised to show changes ')
+    f.write(f'since {pd.to_datetime(hospital_normalisation_date_data["hospital_normalisation_date"]).strftime("%d %B %Y")}.\n')
+    f.write('\n')
+```
+
+```python Collapsed="false"
+with open('covid_summary.md', 'a') as f:
+    f.write('## Testing effectiveness\n')
+    f.write('\n')
+    f.write('A question about testing is whether more detected cases is a result of more tests being '
+            'done or is because the number of cases is increasing. One way of telling the differeence '
+            'is by looking at the fraction of tests that are positive.\n')
+    f.write('\n')
+    f.write('![Positive tests and cases](tests_and_cases.png)\n')
+    f.write('\n')
+    f.write('Numbers of positive tests and cases, '
+            '7-day moving average.\n'
+            'Note the different y-axes\n')
+    f.write('\n')    
+    f.write('![Fraction of tests with positive result](fraction_positive_tests.png)\n')
+    f.write('\n')
+    f.write('Fraction of tests with a positive result, both daily figures and '
+            '7-day moving average.\n')
+    f.write('\n')    
+    f.write('\n')
+    f.write('![Tests against fraction positive, trajectory](fraction_positive_tests_vs_tests.png)\n')
+    f.write('\n')
+    f.write('The trajectory of tests done vs fraction positive tests.\n')
+    f.write('\n')
+    f.write('Points higher indicate more tests; points to the right indicate more positive tests.'
+            'More tests being done with the same infection prevelance will move the point up '
+            'and to the left.\n')
+    f.write('\n')
+    f.write('\n')
+    f.write('![Tests against fraction positive, trajectory](tests_vs_fraction_positive_animation.png)\n')
+    f.write('\n')
+```
+
+```python Collapsed="false"
+
+```
+
+```python Collapsed="false"
+with open('covid_summary.md', 'a') as f:
+    f.write('# Data sources\n')
+    f.write('\n')
+    f.write('> Covid data from [European Centre for Disease Prevention and Control](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide)\n')
+    f.write('\n')    
+    f.write("""> Population data from:
+
+* [Office of National Statistics](https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/weeklyprovisionalfiguresondeathsregisteredinenglandandwales) (Endland and Wales) Weeks start on a Saturday.
+* [Northern Ireland Statistics and Research Agency](https://www.nisra.gov.uk/publications/weekly-deaths) (Northern Ireland). Weeks start on a Saturday. Note that the week numbers don't match the England and Wales data.
+* [National Records of Scotland](https://www.nrscotland.gov.uk/statistics-and-data/statistics/statistics-by-theme/vital-events/general-publications/weekly-and-monthly-data-on-births-and-deaths/weekly-data-on-births-and-deaths) (Scotland). Note that Scotland uses ISO8601 week numbers, which start on a Monday.""")
+    
+    f.write('\n\n')
+    f.write('> [Source code available](https://git.njae.me.uk/?p=covid19.git;a=tree)\n')
+    f.write('\n') 
+
+```
+
+```python Collapsed="false"
+!pandoc --toc -s covid_summary.md > covid_summary.html
+```
+
+```python Collapsed="false"
+!scp covid_summary.html neil@ogedei:/var/www/scripts.njae.me.uk/covid/index.html
+!scp covid_deaths_total_linear.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp deaths-radar.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp covid_deaths_per_day_7.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp covid_doubling_times_7.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp cases_per_day_with_lockdown.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp cases_admissions_deaths.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp fraction_positive_tests.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/    
+!scp tests_and_cases.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp deaths_by_date_last_30_days.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp fraction_positive_tests_vs_tests.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp tests_vs_fraction_positive_animation.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/   
+```
+
+```python Collapsed="false"
+with open('uk_covid_deaths.js', 'w') as f:
+    f.write(f"document.write('{uk_covid_deaths}');")
+    
+with open('estimated_total_deaths.js', 'w') as f:
+    f.write(f"document.write('{uk_deaths_to_date:.0f}');")
+
+# with open('projection_date.js', 'w') as f:
+#     f.write(f"document.write(\'{projection_date.strftime('%d %B %Y')}\');")
+
+# with open('projected_deaths.js', 'w') as f:
+#     f.write(f"document.write('{uk_projection.deaths.sum():.0f}');")
+
+# with open('projected_excess_deaths.js', 'w') as f:
+#     f.write(f"document.write('{deaths_actual_projected_scaled:.0f}');")
+
+edut = pd.to_datetime(excess_deaths_data["end_date"]).strftime('%d %B %Y')
+with open('excess_deaths_upto.js', 'w') as f:
+    f.write(f"document.write('{edut}');")
+
+# with open('excess_deaths.js', 'w') as f:
+#     f.write(f"document.write('{excess_deaths:.0f}');")
+    
+# with open('reported_deaths.js', 'w') as f:
+#     f.write(f"document.write('{ons_reported_deaths:.0f}');")
+    
+# with open('scaling_factor.js', 'w') as f:
+#     f.write(f"document.write('{excess_death_accuracy:.2f}');")  
+
+# with open('projection_length.js', 'w') as f:
+#     f.write(f"document.write('{s_end - s_start - 1}');")
+    
+# with open('s_end.js', 'w') as f:
+#     f.write(f"document.write('{s_end}');")
+    
+# s_start_date_str = s_start_date.strftime("%d %B %Y")
+# with open('s_start_date.js', 'w') as f:
+#     f.write(f"document.write('{s_start_date_str}');")
+    
+# with open('uk_end.js', 'w') as f:
+#     f.write(f"document.write('{uk_end}');")
+    
+with open('last_uk_date.js', 'w') as f:
+    f.write(f"document.write('{pd.to_datetime(last_uk_date).strftime('%d %B %Y')}');")
+```
+
+```python Collapsed="false"
+# pd.to_datetime(excess_deaths_upto).strftime('%d %B %Y')
+```
+
+```python Collapsed="false"
+!scp uk_covid_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp estimated_total_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+# !scp projection_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+# !scp projected_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+# !scp projected_excess_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp excess_deaths_upto.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+# !scp excess_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+# !scp reported_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+# !scp scaling_factor.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+# !scp projection_length.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+# !scp s_end.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+# !scp s_start_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+# !scp uk_end.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp last_uk_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp hospital_normalisation_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+```
+
+```python Collapsed="false"
+data_by_date.loc['UK'].to_csv('data_by_day_uk.csv', header=True, index=True)
+data_by_date.loc['BE'].to_csv('data_by_day_be.csv', header=True, index=True)
+```
+
+```python Collapsed="false"
+ukd = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), ['deaths', 'deaths_m7']].droplevel(1)
+ax = ukd.deaths.plot.bar(figsize=(12, 8))
+ukd.deaths_m7.plot.line(ax=ax, color='red')
+# ax = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), 'deaths_m7'].plot.line(figsize=(12, 8), color='red')
+# ax = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), 'deaths'].plot.bar(ax=ax)
+ax.set_xticks(range(0, 120, 20))
+```
+
+```python Collapsed="false"
+ukdd = data_by_date.loc['UK'].iloc[-30:]
+ax = ukdd.deaths_m7.plot.line(figsize=(12, 8), color='red')
+# ukdd.deaths.plot.bar(ax=ax)
+ax.bar(ukdd.index, ukdd.deaths)
+```
+
+```python Collapsed="false"
+ukdd
+```
+
+```python Collapsed="false"
+np.arange(0, 130, 20)
+```
+
+```python Collapsed="false"
+data_by_date.loc['UK']
+```
+
+```python Collapsed="false"
+data_by_date.loc['UK'].plot(x='deaths_culm', y='deaths', logx=True, logy=True)
+```
+
+```python Collapsed="false"
+data_by_date.loc['UK'].plot(x='cases_culm', y='cases')
+```
+
+```python Collapsed="false"
+ukdbd = data_by_date.loc['UK'].copy()
+ukdbd['deaths_m7'] = ukdbd.deaths.transform(lambda x: x.rolling(7, 1).mean())
+ukdbd['cases_m7'] = ukdbd.cases.transform(lambda x: x.rolling(7, 1).mean())
+ukdbd
+```
+
+```python Collapsed="false"
+ukdbd.plot(x='deaths_culm', y='deaths_m7', logx=True, logy=True)
+```
+
+```python Collapsed="false"
+fig, ax = plt.subplots(figsize=(12, 8))
+xmax = 10
+for c in COUNTRIES_CORE:
+    if data_since_threshold.loc[(slice(None), c), 'deaths_culm'].max() > xmax:
+        xmax = data_since_threshold.loc[(slice(None), c), 'deaths_culm'].max()
+    data_since_threshold.loc[(slice(None), c), :].plot(x='deaths_culm', y='deaths_m7', logx=True, logy=True, xlim=(10, xmax * 1.1), label=c, ax=ax)
+```
+
+```python Collapsed="false"
+data_since_threshold.loc[(slice(None), 'UK'), 'deaths_culm'].max()
+```
+
+```python Collapsed="false"
+countries.continentExp.unique()
+```
+
+```python Collapsed="false"
+countries.loc['KW']
+```
+
+```python Collapsed="false"
+data_by_date.groupby(level=0)['deaths'].shift(-25)
+```
+
+```python Collapsed="false"
+offset_data = data_by_date.loc[:, ['cases']]
+offset_data['deaths'] = data_by_date.groupby(level=0)['deaths'].shift(-25)
+offset_data['cases_m7'] = offset_data.groupby(level=0)['cases'].transform(lambda x: x.rolling(7, 1).mean())
+offset_data['deaths_m7'] = offset_data['deaths'].dropna().groupby(level=0).transform(lambda x: x.rolling(7, 1).mean())
+offset_data['deaths_per_case'] = offset_data.deaths_m7 / offset_data.cases_m7
+offset_data
+```
+
+```python Collapsed="false"
+deaths_m7
+```
+
+```python Collapsed="false"
+offset_deaths_m7 = (offset_data.loc[COUNTRIES_ALL, ['deaths_m7']]
+             .unstack().sort_index().xs('deaths_m7', axis=1, drop_level=True)).T.sort_index()
+offset_deaths_m7
+```
+
+```python Collapsed="false"
+offset_deaths_m7['UK']
+```
+
+```python Collapsed="false"
+data_since_threshold.loc[(slice(None), 'UK'), :].tail()
+```
+
+```python Collapsed="false"
+countries.loc['PT']
+```
+
+```python Collapsed="false"
+ax = cases_by_date_m7.iloc[-50:][COUNTRIES_FRIENDS].plot(figsize=(15, 9), title="Cases per day, 7 day moving average")#, ylim=(-10, 1500))
+# ax.set_xlabel(f"Days since {DEATH_COUNT_THRESHOLD} deaths")
+# uk_projection.deaths_m7.plot(ax=ax)
+for c in COUNTRIES_FRIENDS:
+    lvi = cases_by_date_m7[c].last_valid_index()
+    ax.text(x = lvi + pd.Timedelta(days=1), y = cases_by_date_m7[c][lvi], s = f"{c}: {cases_by_date_m7[c][lvi]:.0f}")
+
+```
+
+```python Collapsed="false"
+ax = deaths_by_date_m7.iloc[-50:][COUNTRIES_FRIENDS].plot(figsize=(15, 9), title="Deaths per day, 7 day moving average")#, ylim=(-10, 100))
+# ax.set_xlabel(f"Days since {DEATH_COUNT_THRESHOLD} deaths")
+# uk_projection.deaths_m7.plot(ax=ax)
+for c in COUNTRIES_FRIENDS:
+    lvi = deaths_by_date_m7[c].last_valid_index()
+#     if c != 'ES':
+    ax.text(x = lvi + pd.Timedelta(days=1), y = deaths_by_date_m7[c][lvi], s = f"{c}: {deaths_by_date_m7[c][lvi]:.0f}")
+```
+
+```python Collapsed="false"
+
+```
diff --git a/covid.csv b/covid.csv

deleted file mode 100644 (file)

index 32e0f07..0000000
--- a/covid.csv
+++ /dev/null
@@ -1,37239 +0,0 @@
-dateRep,day,month,year,cases,deaths,countriesAndTerritories,geoId,countryterritoryCode,popData2019,continentExp,Cumulative_number_for_14_days_of_COVID-19_cases_per_100000\r
-19/08/2020,19,8,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,2.02409158\r
-18/08/2020,18,8,2020,3,0,Afghanistan,AF,AFG,38041757,Asia,2.23964419\r
-17/08/2020,17,8,2020,45,5,Afghanistan,AF,AFG,38041757,Asia,2.32901966\r
-16/08/2020,16,8,2020,120,7,Afghanistan,AF,AFG,38041757,Asia,2.21072859\r
-15/08/2020,15,8,2020,7,0,Afghanistan,AF,AFG,38041757,Asia,1.89528575\r
-14/08/2020,14,8,2020,79,9,Afghanistan,AF,AFG,38041757,Asia,2.3185049\r
-13/08/2020,13,8,2020,76,10,Afghanistan,AF,AFG,38041757,Asia,2.29747538\r
-12/08/2020,12,8,2020,215,32,Afghanistan,AF,AFG,38041757,Asia,2.09769491\r
-11/08/2020,11,8,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,1.80328159\r
-10/08/2020,10,8,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,2.07929408\r
-09/08/2020,9,8,2020,39,5,Afghanistan,AF,AFG,38041757,Asia,2.35793526\r
-08/08/2020,8,8,2020,78,9,Afghanistan,AF,AFG,38041757,Asia,2.57348786\r
-07/08/2020,7,8,2020,41,0,Afghanistan,AF,AFG,38041757,Asia,2.65234858\r
-06/08/2020,6,8,2020,67,4,Afghanistan,AF,AFG,38041757,Asia,2.57874525\r
-05/08/2020,5,8,2020,82,6,Afghanistan,AF,AFG,38041757,Asia,2.89681678\r
-04/08/2020,4,8,2020,37,4,Afghanistan,AF,AFG,38041757,Asia,2.97567749\r
-03/08/2020,3,8,2020,0,1,Afghanistan,AF,AFG,38041757,Asia,3.2464326\r
-02/08/2020,2,8,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,3.70382472\r
-01/08/2020,1,8,2020,168,12,Afghanistan,AF,AFG,38041757,Asia,3.73536901\r
-31/07/2020,31,7,2020,71,0,Afghanistan,AF,AFG,38041757,Asia,3.86943221\r
-30/07/2020,30,7,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,3.88257567\r
-29/07/2020,29,7,2020,103,1,Afghanistan,AF,AFG,38041757,Asia,4.55026302\r
-28/07/2020,28,7,2020,105,1,Afghanistan,AF,AFG,38041757,Asia,5.02868466\r
-27/07/2020,27,7,2020,106,10,Afghanistan,AF,AFG,38041757,Asia,4.76318694\r
-26/07/2020,26,7,2020,121,13,Afghanistan,AF,AFG,38041757,Asia,4.48454576\r
-25/07/2020,25,7,2020,108,35,Afghanistan,AF,AFG,38041757,Asia,4.38991291\r
-24/07/2020,24,7,2020,13,0,Afghanistan,AF,AFG,38041757,Asia,5.30995453\r
-23/07/2020,23,7,2020,188,21,Afghanistan,AF,AFG,38041757,Asia,5.9460976\r
-22/07/2020,22,7,2020,112,4,Afghanistan,AF,AFG,38041757,Asia,5.60699654\r
-21/07/2020,21,7,2020,140,5,Afghanistan,AF,AFG,38041757,Asia,5.8646082\r
-20/07/2020,20,7,2020,174,17,Afghanistan,AF,AFG,38041757,Asia,6.63481448\r
-19/07/2020,19,7,2020,12,17,Afghanistan,AF,AFG,38041757,Asia,6.91082696\r
-18/07/2020,18,7,2020,219,32,Afghanistan,AF,AFG,38041757,Asia,7.79406692\r
-17/07/2020,17,7,2020,76,21,Afghanistan,AF,AFG,38041757,Asia,8.01224823\r
-16/07/2020,16,7,2020,254,49,Afghanistan,AF,AFG,38041757,Asia,8.30140416\r
-15/07/2020,15,7,2020,285,33,Afghanistan,AF,AFG,38041757,Asia,8.47226904\r
-14/07/2020,14,7,2020,4,2,Afghanistan,AF,AFG,38041757,Asia,8.4564969\r
-13/07/2020,13,7,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,9.15835722\r
-12/07/2020,12,7,2020,85,16,Afghanistan,AF,AFG,38041757,Asia,10.08102754\r
-11/07/2020,11,7,2020,458,37,Afghanistan,AF,AFG,38041757,Asia,10.29132277\r
-10/07/2020,10,7,2020,255,20,Afghanistan,AF,AFG,38041757,Asia,9.81290112\r
-09/07/2020,9,7,2020,59,1,Afghanistan,AF,AFG,38041757,Asia,10.35178265\r
-08/07/2020,8,7,2020,210,16,Afghanistan,AF,AFG,38041757,Asia,10.81180346\r
-07/07/2020,7,7,2020,433,56,Afghanistan,AF,AFG,38041757,Asia,11.14827583\r
-06/07/2020,6,7,2020,279,38,Afghanistan,AF,AFG,38041757,Asia,10.82494691\r
-05/07/2020,5,7,2020,348,7,Afghanistan,AF,AFG,38041757,Asia,11.16667666\r
-04/07/2020,4,7,2020,302,12,Afghanistan,AF,AFG,38041757,Asia,11.68715735\r
-03/07/2020,3,7,2020,186,33,Afghanistan,AF,AFG,38041757,Asia,11.80281973\r
-02/07/2020,2,7,2020,319,28,Afghanistan,AF,AFG,38041757,Asia,13.04356158\r
-01/07/2020,1,7,2020,279,13,Afghanistan,AF,AFG,38041757,Asia,13.68759072\r
-30/06/2020,30,6,2020,271,12,Afghanistan,AF,AFG,38041757,Asia,15.01245066\r
-29/06/2020,29,6,2020,351,18,Afghanistan,AF,AFG,38041757,Asia,16.30050894\r
-28/06/2020,28,6,2020,165,20,Afghanistan,AF,AFG,38041757,Asia,17.12328902\r
-27/06/2020,27,6,2020,276,8,Afghanistan,AF,AFG,38041757,Asia,18.15110695\r
-26/06/2020,26,6,2020,460,36,Afghanistan,AF,AFG,38041757,Asia,19.15000929\r
-25/06/2020,25,6,2020,234,21,Afghanistan,AF,AFG,38041757,Asia,19.90444343\r
-24/06/2020,24,6,2020,338,20,Afghanistan,AF,AFG,38041757,Asia,21.08735409\r
-23/06/2020,23,6,2020,310,17,Afghanistan,AF,AFG,38041757,Asia,21.62360692\r
-22/06/2020,22,6,2020,409,12,Afghanistan,AF,AFG,38041757,Asia,22.32020987\r
-21/06/2020,21,6,2020,546,21,Afghanistan,AF,AFG,38041757,Asia,23.32436959\r
-20/06/2020,20,6,2020,346,2,Afghanistan,AF,AFG,38041757,Asia,23.41900244\r
-19/06/2020,19,6,2020,658,42,Afghanistan,AF,AFG,38041757,Asia,24.91472726\r
-18/06/2020,18,6,2020,564,13,Afghanistan,AF,AFG,38041757,Asia,25.25382831\r
-17/06/2020,17,6,2020,783,13,Afghanistan,AF,AFG,38041757,Asia,25.76379424\r
-16/06/2020,16,6,2020,761,7,Afghanistan,AF,AFG,38041757,Asia,25.70070567\r
-15/06/2020,15,6,2020,664,20,Afghanistan,AF,AFG,38041757,Asia,25.13290856\r
-14/06/2020,14,6,2020,556,5,Afghanistan,AF,AFG,38041757,Asia,25.1749676\r
-13/06/2020,13,6,2020,656,20,Afghanistan,AF,AFG,38041757,Asia,25.98986161\r
-12/06/2020,12,6,2020,747,21,Afghanistan,AF,AFG,38041757,Asia,25.90311483\r
-11/06/2020,11,6,2020,684,21,Afghanistan,AF,AFG,38041757,Asia,25.46412354\r
-10/06/2020,10,6,2020,542,15,Afghanistan,AF,AFG,38041757,Asia,25.30903081\r
-09/06/2020,9,6,2020,575,12,Afghanistan,AF,AFG,38041757,Asia,25.61395889\r
-08/06/2020,8,6,2020,791,30,Afghanistan,AF,AFG,38041757,Asia,25.65601794\r
-07/06/2020,7,6,2020,582,18,Afghanistan,AF,AFG,38041757,Asia,25.11187903\r
-06/06/2020,6,6,2020,915,9,Afghanistan,AF,AFG,38041757,Asia,25.63761711\r
-05/06/2020,5,6,2020,787,6,Afghanistan,AF,AFG,38041757,Asia,24.65185822\r
-04/06/2020,4,6,2020,758,24,Afghanistan,AF,AFG,38041757,Asia,23.97891349\r
-03/06/2020,3,6,2020,759,5,Afghanistan,AF,AFG,38041757,Asia,23.27968185\r
-02/06/2020,2,6,2020,545,8,Afghanistan,AF,AFG,38041757,Asia,22.81177497\r
-01/06/2020,1,6,2020,680,8,Afghanistan,AF,AFG,38041757,Asia,22.45164439\r
-31/05/2020,31,5,2020,866,3,Afghanistan,AF,AFG,38041757,Asia,21.35285181\r
-30/05/2020,30,5,2020,623,11,Afghanistan,AF,AFG,38041757,Asia,19.07640596\r
-29/05/2020,29,5,2020,580,8,Afghanistan,AF,AFG,38041757,Asia,20.23302972\r
-28/05/2020,28,5,2020,625,7,Afghanistan,AF,AFG,38041757,Asia,19.00543132\r
-27/05/2020,27,5,2020,658,1,Afghanistan,AF,AFG,38041757,Asia,18.04333065\r
-26/05/2020,26,5,2020,591,1,Afghanistan,AF,AFG,38041757,Asia,17.04968569\r
-25/05/2020,25,5,2020,584,2,Afghanistan,AF,AFG,38041757,Asia,16.24530644\r
-24/05/2020,24,5,2020,782,11,Afghanistan,AF,AFG,38041757,Asia,15.68013801\r
-23/05/2020,23,5,2020,540,12,Afghanistan,AF,AFG,38041757,Asia,14.29481819\r
-22/05/2020,22,5,2020,531,6,Afghanistan,AF,AFG,38041757,Asia,13.44049382\r
-21/05/2020,21,5,2020,492,9,Afghanistan,AF,AFG,38041757,Asia,12.49416529\r
-20/05/2020,20,5,2020,581,5,Afghanistan,AF,AFG,38041757,Asia,11.64246962\r
-19/05/2020,19,5,2020,408,4,Afghanistan,AF,AFG,38041757,Asia,10.98266833\r
-18/05/2020,18,5,2020,262,1,Afghanistan,AF,AFG,38041757,Asia,10.40961384\r
-17/05/2020,17,5,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,10.3386392\r
-16/05/2020,16,5,2020,1063,32,Afghanistan,AF,AFG,38041757,Asia,10.6908837\r
-15/05/2020,15,5,2020,113,6,Afghanistan,AF,AFG,38041757,Asia,8.32769107\r
-14/05/2020,14,5,2020,259,3,Afghanistan,AF,AFG,38041757,Asia,8.61421832\r
-13/05/2020,13,5,2020,280,5,Afghanistan,AF,AFG,38041757,Asia,8.25408774\r
-12/05/2020,12,5,2020,285,2,Afghanistan,AF,AFG,38041757,Asia,7.84401204\r
-11/05/2020,11,5,2020,369,5,Afghanistan,AF,AFG,38041757,Asia,7.54697003\r
-10/05/2020,10,5,2020,255,6,Afghanistan,AF,AFG,38041757,Asia,6.75573423\r
-09/05/2020,9,5,2020,215,3,Afghanistan,AF,AFG,38041757,Asia,6.37983151\r
-08/05/2020,8,5,2020,171,2,Afghanistan,AF,AFG,38041757,Asia,5.99867141\r
-07/05/2020,7,5,2020,168,9,Afghanistan,AF,AFG,38041757,Asia,5.82517784\r
-06/05/2020,6,5,2020,330,5,Afghanistan,AF,AFG,38041757,Asia,5.60436785\r
-05/05/2020,5,5,2020,190,5,Afghanistan,AF,AFG,38041757,Asia,4.89725015\r
-04/05/2020,4,5,2020,235,13,Afghanistan,AF,AFG,38041757,Asia,4.48980314\r
-03/05/2020,3,5,2020,134,4,Afghanistan,AF,AFG,38041757,Asia,4.10338566\r
-02/05/2020,2,5,2020,164,4,Afghanistan,AF,AFG,38041757,Asia,3.91674864\r
-01/05/2020,1,5,2020,222,4,Afghanistan,AF,AFG,38041757,Asia,3.61970663\r
-30/04/2020,30,4,2020,122,0,Afghanistan,AF,AFG,38041757,Asia,3.06242427\r
-29/04/2020,29,4,2020,124,3,Afghanistan,AF,AFG,38041757,Asia,2.92573237\r
-28/04/2020,28,4,2020,172,0,Afghanistan,AF,AFG,38041757,Asia,2.7285806\r
-27/04/2020,27,4,2020,68,10,Afghanistan,AF,AFG,38041757,Asia,2.42890989\r
-26/04/2020,26,4,2020,112,4,Afghanistan,AF,AFG,38041757,Asia,2.38685085\r
-25/04/2020,25,4,2020,70,1,Afghanistan,AF,AFG,38041757,Asia,2.181813\r
-24/04/2020,24,4,2020,105,2,Afghanistan,AF,AFG,38041757,Asia,2.09506622\r
-23/04/2020,23,4,2020,84,4,Afghanistan,AF,AFG,38041757,Asia,1.97940384\r
-22/04/2020,22,4,2020,61,1,Afghanistan,AF,AFG,38041757,Asia,1.90580051\r
-21/04/2020,21,4,2020,35,2,Afghanistan,AF,AFG,38041757,Asia,1.82431111\r
-20/04/2020,20,4,2020,88,3,Afghanistan,AF,AFG,38041757,Asia,1.83219718\r
-19/04/2020,19,4,2020,63,0,Afghanistan,AF,AFG,38041757,Asia,1.67710445\r
-18/04/2020,18,4,2020,51,1,Afghanistan,AF,AFG,38041757,Asia,1.60350112\r
-17/04/2020,17,4,2020,10,4,Afghanistan,AF,AFG,38041757,Asia,1.46943791\r
-16/04/2020,16,4,2020,70,2,Afghanistan,AF,AFG,38041757,Asia,1.55618469\r
-15/04/2020,15,4,2020,49,2,Afghanistan,AF,AFG,38041757,Asia,1.44052232\r
-14/04/2020,14,4,2020,58,3,Afghanistan,AF,AFG,38041757,Asia,1.37743375\r
-13/04/2020,13,4,2020,52,0,Afghanistan,AF,AFG,38041757,Asia,1.29594435\r
-12/04/2020,12,4,2020,34,3,Afghanistan,AF,AFG,38041757,Asia,1.18028197\r
-11/04/2020,11,4,2020,37,0,Afghanistan,AF,AFG,38041757,Asia,1.13033686\r
-10/04/2020,10,4,2020,61,1,Afghanistan,AF,AFG,38041757,Asia,1.07513436\r
-09/04/2020,9,4,2020,56,3,Afghanistan,AF,AFG,38041757,Asia,0.91478425\r
-08/04/2020,8,4,2020,30,4,Afghanistan,AF,AFG,38041757,Asia,0.85432437\r
-07/04/2020,7,4,2020,38,0,Afghanistan,AF,AFG,38041757,Asia,0.78072104\r
-06/04/2020,6,4,2020,29,2,Afghanistan,AF,AFG,38041757,Asia,0.69660295\r
-05/04/2020,5,4,2020,35,1,Afghanistan,AF,AFG,38041757,Asia,0.64665783\r
-04/04/2020,4,4,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0.55465367\r
-03/04/2020,3,4,2020,43,0,Afghanistan,AF,AFG,38041757,Asia,0.55991105\r
-02/04/2020,2,4,2020,26,0,Afghanistan,AF,AFG,38041757,Asia,0.44687736\r
-01/04/2020,1,4,2020,25,0,Afghanistan,AF,AFG,38041757,Asia,0.37853141\r
-31/03/2020,31,3,2020,27,0,Afghanistan,AF,AFG,38041757,Asia,0.31544284\r
-30/03/2020,30,3,2020,8,1,Afghanistan,AF,AFG,38041757,Asia,0.25761166\r
-29/03/2020,29,3,2020,15,1,Afghanistan,AF,AFG,38041757,Asia,0.25235427\r
-28/03/2020,28,3,2020,16,1,Afghanistan,AF,AFG,38041757,Asia,0.22080999\r
-27/03/2020,27,3,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0.18663702\r
-26/03/2020,26,3,2020,33,0,Afghanistan,AF,AFG,38041757,Asia,0.19452309\r
-25/03/2020,25,3,2020,2,0,Afghanistan,AF,AFG,38041757,Asia,0.1077763\r
-24/03/2020,24,3,2020,6,1,Afghanistan,AF,AFG,38041757,Asia,0.10251892\r
-23/03/2020,23,3,2020,10,0,Afghanistan,AF,AFG,38041757,Asia,0.08674678\r
-22/03/2020,22,3,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0.06045988\r
-21/03/2020,21,3,2020,2,0,Afghanistan,AF,AFG,38041757,Asia,0.06045988\r
-20/03/2020,20,3,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0.0552025\r
-19/03/2020,19,3,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0.05783119\r
-18/03/2020,18,3,2020,1,0,Afghanistan,AF,AFG,38041757,Asia,0.05783119\r
-17/03/2020,17,3,2020,5,0,Afghanistan,AF,AFG,38041757,Asia,0.0552025\r
-16/03/2020,16,3,2020,6,0,Afghanistan,AF,AFG,38041757,Asia,0.04205905\r
-15/03/2020,15,3,2020,3,0,Afghanistan,AF,AFG,38041757,Asia,0.0262869\r
-11/03/2020,11,3,2020,3,0,Afghanistan,AF,AFG,38041757,Asia,0.01840083\r
-08/03/2020,8,3,2020,3,0,Afghanistan,AF,AFG,38041757,Asia,0.01051476\r
-02/03/2020,2,3,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0.00262869\r
-01/03/2020,1,3,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0.00262869\r
-29/02/2020,29,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0.00262869\r
-28/02/2020,28,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0.00262869\r
-27/02/2020,27,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0.00262869\r
-26/02/2020,26,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0.00262869\r
-25/02/2020,25,2,2020,1,0,Afghanistan,AF,AFG,38041757,Asia,0.00262869\r
-24/02/2020,24,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-23/02/2020,23,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-22/02/2020,22,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-21/02/2020,21,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-20/02/2020,20,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-19/02/2020,19,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-18/02/2020,18,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-17/02/2020,17,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-16/02/2020,16,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-15/02/2020,15,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-14/02/2020,14,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-13/02/2020,13,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-12/02/2020,12,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-11/02/2020,11,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-10/02/2020,10,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-09/02/2020,9,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-08/02/2020,8,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-07/02/2020,7,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-06/02/2020,6,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-05/02/2020,5,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-04/02/2020,4,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-03/02/2020,3,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-02/02/2020,2,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-01/02/2020,1,2,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-31/01/2020,31,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-30/01/2020,30,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-29/01/2020,29,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-28/01/2020,28,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-27/01/2020,27,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-26/01/2020,26,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-25/01/2020,25,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-24/01/2020,24,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-23/01/2020,23,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-22/01/2020,22,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-21/01/2020,21,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-20/01/2020,20,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-19/01/2020,19,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-18/01/2020,18,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-17/01/2020,17,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-16/01/2020,16,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-15/01/2020,15,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-14/01/2020,14,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-13/01/2020,13,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,0\r
-12/01/2020,12,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,\r
-11/01/2020,11,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,\r
-10/01/2020,10,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,\r
-09/01/2020,9,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,\r
-08/01/2020,8,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,\r
-07/01/2020,7,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,\r
-06/01/2020,6,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,\r
-05/01/2020,5,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,\r
-04/01/2020,4,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,\r
-03/01/2020,3,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,\r
-02/01/2020,2,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,\r
-01/01/2020,1,1,2020,0,0,Afghanistan,AF,AFG,38041757,Asia,\r
-31/12/2019,31,12,2019,0,0,Afghanistan,AF,AFG,38041757,Asia,\r
-19/08/2020,19,8,2020,155,2,Albania,AL,ALB,2862427,Europe,66.51698017\r
-18/08/2020,18,8,2020,119,2,Albania,AL,ALB,2862427,Europe,65.64359545\r
-17/08/2020,17,8,2020,120,3,Albania,AL,ALB,2862427,Europe,65.01475845\r
-16/08/2020,16,8,2020,143,6,Albania,AL,ALB,2862427,Europe,65.11956462\r
-15/08/2020,15,8,2020,146,6,Albania,AL,ALB,2862427,Europe,64.31605068\r
-14/08/2020,14,8,2020,154,5,Albania,AL,ALB,2862427,Europe,61.97537963\r
-13/08/2020,13,8,2020,141,3,Albania,AL,ALB,2862427,Europe,59.80938553\r
-12/08/2020,12,8,2020,140,5,Albania,AL,ALB,2862427,Europe,58.6565177\r
-11/08/2020,11,8,2020,125,1,Albania,AL,ALB,2862427,Europe,57.85300376\r
-10/08/2020,10,8,2020,136,6,Albania,AL,ALB,2862427,Europe,57.57352065\r
-09/08/2020,9,8,2020,124,4,Albania,AL,ALB,2862427,Europe,57.22416676\r
-08/08/2020,8,8,2020,135,1,Albania,AL,ALB,2862427,Europe,55.23284961\r
-07/08/2020,7,8,2020,127,6,Albania,AL,ALB,2862427,Europe,54.14985256\r
-06/08/2020,6,8,2020,139,6,Albania,AL,ALB,2862427,Europe,53.48608017\r
-05/08/2020,5,8,2020,130,4,Albania,AL,ALB,2862427,Europe,51.00566757\r
-04/08/2020,4,8,2020,101,6,Albania,AL,ALB,2862427,Europe,50.62137829\r
-03/08/2020,3,8,2020,123,5,Albania,AL,ALB,2862427,Europe,49.92267052\r
-02/08/2020,2,8,2020,120,4,Albania,AL,ALB,2862427,Europe,48.49031958\r
-01/08/2020,1,8,2020,79,3,Albania,AL,ALB,2862427,Europe,47.86148258\r
-31/07/2020,31,7,2020,92,4,Albania,AL,ALB,2862427,Europe,47.02303325\r
-30/07/2020,30,7,2020,108,2,Albania,AL,ALB,2862427,Europe,47.26758097\r
-29/07/2020,29,7,2020,117,4,Albania,AL,ALB,2862427,Europe,46.46406703\r
-28/07/2020,28,7,2020,117,6,Albania,AL,ALB,2862427,Europe,45.73042387\r
-27/07/2020,27,7,2020,126,4,Albania,AL,ALB,2862427,Europe,45.73042387\r
-26/07/2020,26,7,2020,67,6,Albania,AL,ALB,2862427,Europe,44.22820215\r
-25/07/2020,25,7,2020,104,5,Albania,AL,ALB,2862427,Europe,45.13652226\r
-24/07/2020,24,7,2020,108,3,Albania,AL,ALB,2862427,Europe,44.64742682\r
-23/07/2020,23,7,2020,68,3,Albania,AL,ALB,2862427,Europe,43.73910671\r
-22/07/2020,22,7,2020,119,4,Albania,AL,ALB,2862427,Europe,43.73910671\r
-21/07/2020,21,7,2020,81,1,Albania,AL,ALB,2862427,Europe,42.16701422\r
-20/07/2020,20,7,2020,82,1,Albania,AL,ALB,2862427,Europe,41.81766033\r
-19/07/2020,19,7,2020,102,4,Albania,AL,ALB,2862427,Europe,41.53817722\r
-18/07/2020,18,7,2020,55,3,Albania,AL,ALB,2862427,Europe,40.31543861\r
-17/07/2020,17,7,2020,99,3,Albania,AL,ALB,2862427,Europe,41.53817722\r
-16/07/2020,16,7,2020,85,4,Albania,AL,ALB,2862427,Europe,40.94427561\r
-15/07/2020,15,7,2020,96,2,Albania,AL,ALB,2862427,Europe,39.54686006\r
-14/07/2020,14,7,2020,117,2,Albania,AL,ALB,2862427,Europe,38.60360456\r
-13/07/2020,13,7,2020,83,4,Albania,AL,ALB,2862427,Europe,36.75202896\r
-12/07/2020,12,7,2020,93,4,Albania,AL,ALB,2862427,Europe,36.36773968\r
-11/07/2020,11,7,2020,90,2,Albania,AL,ALB,2862427,Europe,35.24980724\r
-10/07/2020,10,7,2020,82,0,Albania,AL,ALB,2862427,Europe,34.79564719\r
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-29/07/2020,29,7,2020,18,1,Angola,AO,AGO,31825299,Africa,1.33541558\r
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-27/07/2020,27,7,2020,50,5,Angola,AO,AGO,31825299,Africa,1.33227342\r
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-29/06/2020,29,6,2020,23,1,Angola,AO,AGO,31825299,Africa,0.3990536\r
-28/06/2020,28,6,2020,32,0,Angola,AO,AGO,31825299,Africa,0.33306836\r
-27/06/2020,27,6,2020,15,0,Angola,AO,AGO,31825299,Africa,0.25765665\r
-26/06/2020,26,6,2020,8,0,Angola,AO,AGO,31825299,Africa,0.24823019\r
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-24/06/2020,24,6,2020,3,1,Angola,AO,AGO,31825299,Africa,0.28279389\r
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-17/08/2020,17,8,2020,253,17,Australia,AU,AUS,25203200,Oceania,21.28697943\r
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-13/08/2020,13,8,2020,414,21,Australia,AU,AUS,25203200,Oceania,25.96892458\r
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-31/07/2020,31,7,2020,721,13,Australia,AU,AUS,25203200,Oceania,21.79485145\r
-30/07/2020,30,7,2020,278,9,Australia,AU,AUS,25203200,Oceania,20.1839449\r
-29/07/2020,29,7,2020,369,6,Australia,AU,AUS,25203200,Oceania,20.04904139\r
-28/07/2020,28,7,2020,532,6,Australia,AU,AUS,25203200,Oceania,19.66020188\r
-27/07/2020,27,7,2020,453,10,Australia,AU,AUS,25203200,Oceania,18.27545708\r
-26/07/2020,26,7,2020,355,6,Australia,AU,AUS,25203200,Oceania,17.44619731\r
-25/07/2020,25,7,2020,289,6,Australia,AU,AUS,25203200,Oceania,16.80738954\r
-24/07/2020,24,7,2020,410,5,Australia,AU,AUS,25203200,Oceania,16.85103479\r
-23/07/2020,23,7,2020,468,2,Australia,AU,AUS,25203200,Oceania,15.91067801\r
-22/07/2020,22,7,2020,359,3,Australia,AU,AUS,25203200,Oceania,14.57354622\r
-21/07/2020,21,7,2020,267,1,Australia,AU,AUS,25203200,Oceania,13.81967369\r
-20/07/2020,20,7,2020,361,4,Australia,AU,AUS,25203200,Oceania,13.30386618\r
-19/07/2020,19,7,2020,206,2,Australia,AU,AUS,25203200,Oceania,12.21670264\r
-18/07/2020,18,7,2020,425,3,Australia,AU,AUS,25203200,Oceania,11.82389538\r
-17/07/2020,17,7,2020,315,2,Australia,AU,AUS,25203200,Oceania,11.14541011\r
-16/07/2020,16,7,2020,244,3,Australia,AU,AUS,25203200,Oceania,10.21695658\r
-15/07/2020,15,7,2020,271,0,Australia,AU,AUS,25203200,Oceania,9.59005206\r
-14/07/2020,14,7,2020,183,0,Australia,AU,AUS,25203200,Oceania,8.78063103\r
-13/07/2020,13,7,2020,244,1,Australia,AU,AUS,25203200,Oceania,8.37592052\r
-12/07/2020,12,7,2020,194,1,Australia,AU,AUS,25203200,Oceania,7.58633824\r
-11/07/2020,11,7,2020,300,0,Australia,AU,AUS,25203200,Oceania,6.99911122\r
-10/07/2020,10,7,2020,173,0,Australia,AU,AUS,25203200,Oceania,5.95559294\r
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-30/06/2020,30,6,2020,81,0,Australia,AU,AUS,25203200,Oceania,1.71406805\r
-29/06/2020,29,6,2020,45,0,Australia,AU,AUS,25203200,Oceania,1.45219655\r
-28/06/2020,28,6,2020,46,0,Australia,AU,AUS,25203200,Oceania,1.34506729\r
-27/06/2020,27,6,2020,37,0,Australia,AU,AUS,25203200,Oceania,1.21016379\r
-26/06/2020,26,6,2020,37,1,Australia,AU,AUS,25203200,Oceania,1.08319578\r
-25/06/2020,25,6,2020,29,1,Australia,AU,AUS,25203200,Oceania,0.97209878\r
-24/06/2020,24,6,2020,18,0,Australia,AU,AUS,25203200,Oceania,0.89274378\r
-23/06/2020,23,6,2020,13,0,Australia,AU,AUS,25203200,Oceania,0.82925978\r
-22/06/2020,22,6,2020,25,0,Australia,AU,AUS,25203200,Oceania,0.79751778\r
-21/06/2020,21,6,2020,27,0,Australia,AU,AUS,25203200,Oceania,0.71816277\r
-20/06/2020,20,6,2020,18,0,Australia,AU,AUS,25203200,Oceania,0.62690452\r
-19/06/2020,19,6,2020,21,0,Australia,AU,AUS,25203200,Oceania,0.59913027\r
-18/06/2020,18,6,2020,23,0,Australia,AU,AUS,25203200,Oceania,0.55945277\r
-17/06/2020,17,6,2020,12,0,Australia,AU,AUS,25203200,Oceania,0.49993652\r
-16/06/2020,16,6,2020,15,0,Australia,AU,AUS,25203200,Oceania,0.51977527\r
-15/06/2020,15,6,2020,18,0,Australia,AU,AUS,25203200,Oceania,0.49596877\r
-14/06/2020,14,6,2020,12,0,Australia,AU,AUS,25203200,Oceania,0.46422676\r
-13/06/2020,13,6,2020,5,0,Australia,AU,AUS,25203200,Oceania,0.46422676\r
-12/06/2020,12,6,2020,9,0,Australia,AU,AUS,25203200,Oceania,0.53564627\r
-11/06/2020,11,6,2020,9,0,Australia,AU,AUS,25203200,Oceania,0.54358177\r
-10/06/2020,10,6,2020,2,0,Australia,AU,AUS,25203200,Oceania,0.53167852\r
-09/06/2020,9,6,2020,5,0,Australia,AU,AUS,25203200,Oceania,0.58325927\r
-08/06/2020,8,6,2020,5,0,Australia,AU,AUS,25203200,Oceania,0.59913027\r
-07/06/2020,7,6,2020,4,0,Australia,AU,AUS,25203200,Oceania,0.59119477\r
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-05/06/2020,5,6,2020,11,0,Australia,AU,AUS,25203200,Oceania,0.63087227\r
-04/06/2020,4,6,2020,8,0,Australia,AU,AUS,25203200,Oceania,0.59516252\r
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-02/06/2020,2,6,2020,9,0,Australia,AU,AUS,25203200,Oceania,0.57135602\r
-01/06/2020,1,6,2020,10,0,Australia,AU,AUS,25203200,Oceania,0.59516252\r
-31/05/2020,31,5,2020,12,0,Australia,AU,AUS,25203200,Oceania,0.59119477\r
-30/05/2020,30,5,2020,23,0,Australia,AU,AUS,25203200,Oceania,0.61103352\r
-29/05/2020,29,5,2020,11,0,Australia,AU,AUS,25203200,Oceania,0.63880777\r
-28/05/2020,28,5,2020,6,0,Australia,AU,AUS,25203200,Oceania,0.65071102\r
-27/05/2020,27,5,2020,15,0,Australia,AU,AUS,25203200,Oceania,0.67054977\r
-26/05/2020,26,5,2020,9,0,Australia,AU,AUS,25203200,Oceania,0.67451752\r
-25/05/2020,25,5,2020,3,0,Australia,AU,AUS,25203200,Oceania,0.66658202\r
-24/05/2020,24,5,2020,11,1,Australia,AU,AUS,25203200,Oceania,0.70229177\r
-23/05/2020,23,5,2020,14,1,Australia,AU,AUS,25203200,Oceania,0.71816277\r
-22/05/2020,22,5,2020,2,0,Australia,AU,AUS,25203200,Oceania,0.73403377\r
-21/05/2020,21,5,2020,11,1,Australia,AU,AUS,25203200,Oceania,0.80942103\r
-20/05/2020,20,5,2020,8,0,Australia,AU,AUS,25203200,Oceania,0.86893728\r
-19/05/2020,19,5,2020,15,1,Australia,AU,AUS,25203200,Oceania,0.93242128\r
-18/05/2020,18,5,2020,9,0,Australia,AU,AUS,25203200,Oceania,0.96813103\r
-17/05/2020,17,5,2020,17,0,Australia,AU,AUS,25203200,Oceania,1.00384078\r
-16/05/2020,16,5,2020,30,0,Australia,AU,AUS,25203200,Oceania,0.99987303\r
-15/05/2020,15,5,2020,14,0,Australia,AU,AUS,25203200,Oceania,0.90067928\r
-14/05/2020,14,5,2020,11,1,Australia,AU,AUS,25203200,Oceania,0.90861478\r
-13/05/2020,13,5,2020,16,0,Australia,AU,AUS,25203200,Oceania,0.89671153\r
-12/05/2020,12,5,2020,7,0,Australia,AU,AUS,25203200,Oceania,0.88480828\r
-11/05/2020,11,5,2020,12,0,Australia,AU,AUS,25203200,Oceania,0.90464703\r
-10/05/2020,10,5,2020,15,0,Australia,AU,AUS,25203200,Oceania,0.89671153\r
-09/05/2020,9,5,2020,18,0,Australia,AU,AUS,25203200,Oceania,0.90067928\r
-08/05/2020,8,5,2020,21,0,Australia,AU,AUS,25203200,Oceania,0.90861478\r
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-01/05/2020,1,5,2020,16,2,Australia,AU,AUS,25203200,Oceania,1.05145378\r
-30/04/2020,30,4,2020,8,2,Australia,AU,AUS,25203200,Oceania,1.14271204\r
-29/04/2020,29,4,2020,13,4,Australia,AU,AUS,25203200,Oceania,1.27761554\r
-28/04/2020,28,4,2020,12,1,Australia,AU,AUS,25203200,Oceania,1.4244223\r
-27/04/2020,27,4,2020,10,2,Australia,AU,AUS,25203200,Oceania,1.5513903\r
-26/04/2020,26,4,2020,16,2,Australia,AU,AUS,25203200,Oceania,1.64264855\r
-25/04/2020,25,4,2020,20,4,Australia,AU,AUS,25203200,Oceania,1.78151981\r
-24/04/2020,24,4,2020,13,1,Australia,AU,AUS,25203200,Oceania,2.04339132\r
-23/04/2020,23,4,2020,7,0,Australia,AU,AUS,25203200,Oceania,2.38858558\r
-22/04/2020,22,4,2020,22,3,Australia,AU,AUS,25203200,Oceania,2.74171534\r
-21/04/2020,21,4,2020,13,1,Australia,AU,AUS,25203200,Oceania,3.09881285\r
-20/04/2020,20,4,2020,26,1,Australia,AU,AUS,25203200,Oceania,3.44400711\r
-19/04/2020,19,4,2020,53,2,Australia,AU,AUS,25203200,Oceania,3.56700736\r
-18/04/2020,18,4,2020,36,4,Australia,AU,AUS,25203200,Oceania,3.90823388\r
-17/04/2020,17,4,2020,39,0,Australia,AU,AUS,25203200,Oceania,5.05094591\r
-16/04/2020,16,4,2020,42,2,Australia,AU,AUS,25203200,Oceania,5.88020569\r
-15/04/2020,15,4,2020,50,0,Australia,AU,AUS,25203200,Oceania,6.78088497\r
-14/04/2020,14,4,2020,44,0,Australia,AU,AUS,25203200,Oceania,7.17765998\r
-13/04/2020,13,4,2020,33,4,Australia,AU,AUS,25203200,Oceania,8.84411503\r
-12/04/2020,12,4,2020,51,3,Australia,AU,AUS,25203200,Oceania,9.84002031\r
-11/04/2020,11,4,2020,86,2,Australia,AU,AUS,25203200,Oceania,11.34776536\r
-10/04/2020,10,4,2020,100,2,Australia,AU,AUS,25203200,Oceania,11.84770188\r
-09/04/2020,9,4,2020,96,5,Australia,AU,AUS,25203200,Oceania,12.90709116\r
-08/04/2020,8,4,2020,112,3,Australia,AU,AUS,25203200,Oceania,14.0180612\r
-07/04/2020,7,4,2020,100,6,Australia,AU,AUS,25203200,Oceania,15.95432326\r
-06/04/2020,6,4,2020,57,2,Australia,AU,AUS,25203200,Oceania,16.00987176\r
-05/04/2020,5,4,2020,139,4,Australia,AU,AUS,25203200,Oceania,18.20800533\r
-04/04/2020,4,4,2020,324,7,Australia,AU,AUS,25203200,Oceania,18.54526409\r
-03/04/2020,3,4,2020,248,2,Australia,AU,AUS,25203200,Oceania,17.91439182\r
-02/04/2020,2,4,2020,269,1,Australia,AU,AUS,25203200,Oceania,17.50174581\r
-01/04/2020,1,4,2020,150,1,Australia,AU,AUS,25203200,Oceania,16.87484129\r
-31/03/2020,31,3,2020,464,3,Australia,AU,AUS,25203200,Oceania,16.59313103\r
-30/03/2020,30,3,2020,284,2,Australia,AU,AUS,25203200,Oceania,15.05761173\r
-29/03/2020,29,3,2020,431,1,Australia,AU,AUS,25203200,Oceania,14.12519045\r
-28/03/2020,28,3,2020,212,0,Australia,AU,AUS,25203200,Oceania,12.62141315\r
-27/03/2020,27,3,2020,367,2,Australia,AU,AUS,25203200,Oceania,11.94292788\r
-26/03/2020,26,3,2020,376,3,Australia,AU,AUS,25203200,Oceania,10.60579609\r
-25/03/2020,25,3,2020,600,1,Australia,AU,AUS,25203200,Oceania,9.16947054\r
-24/03/2020,24,3,2020,114,0,Australia,AU,AUS,25203200,Oceania,6.83643347\r
-23/03/2020,23,3,2020,611,0,Australia,AU,AUS,25203200,Oceania,6.46346496\r
-22/03/2020,22,3,2020,224,0,Australia,AU,AUS,25203200,Oceania,4.06297613\r
-21/03/2020,21,3,2020,165,1,Australia,AU,AUS,25203200,Oceania,3.21784535\r
-20/03/2020,20,3,2020,144,0,Australia,AU,AUS,25203200,Oceania,2.57903758\r
-19/03/2020,19,3,2020,111,1,Australia,AU,AUS,25203200,Oceania,2.03545582\r
-18/03/2020,18,3,2020,79,0,Australia,AU,AUS,25203200,Oceania,1.6386808\r
-17/03/2020,17,3,2020,77,0,Australia,AU,AUS,25203200,Oceania,1.35697054\r
-16/03/2020,16,3,2020,49,2,Australia,AU,AUS,25203200,Oceania,1.06732478\r
-15/03/2020,15,3,2020,52,0,Australia,AU,AUS,25203200,Oceania,0.88480828\r
-14/03/2020,14,3,2020,41,0,Australia,AU,AUS,25203200,Oceania,0.68245302\r
-13/03/2020,13,3,2020,30,0,Australia,AU,AUS,25203200,Oceania,0.52771077\r
-12/03/2020,12,3,2020,14,0,Australia,AU,AUS,25203200,Oceania,0.40867826\r
-11/03/2020,11,3,2020,12,0,Australia,AU,AUS,25203200,Oceania,0.35709751\r
-10/03/2020,10,3,2020,20,0,Australia,AU,AUS,25203200,Oceania,0.30948451\r
-09/03/2020,9,3,2020,6,0,Australia,AU,AUS,25203200,Oceania,0.23012951\r
-08/03/2020,8,3,2020,11,1,Australia,AU,AUS,25203200,Oceania,0.20632301\r
-07/03/2020,7,3,2020,4,0,Australia,AU,AUS,25203200,Oceania,0.16664551\r
-06/03/2020,6,3,2020,7,0,Australia,AU,AUS,25203200,Oceania,0.16664551\r
-05/03/2020,5,3,2020,11,1,Australia,AU,AUS,25203200,Oceania,0.14680675\r
-04/03/2020,4,3,2020,8,0,Australia,AU,AUS,25203200,Oceania,0.1031615\r
-03/03/2020,3,3,2020,4,0,Australia,AU,AUS,25203200,Oceania,0.0714195\r
-02/03/2020,2,3,2020,3,0,Australia,AU,AUS,25203200,Oceania,0.0555485\r
-01/03/2020,1,3,2020,1,1,Australia,AU,AUS,25203200,Oceania,0.04364525\r
-29/02/2020,29,2,2020,2,0,Australia,AU,AUS,25203200,Oceania,0.0396775\r
-28/02/2020,28,2,2020,0,0,Australia,AU,AUS,25203200,Oceania,0.031742\r
-27/02/2020,27,2,2020,1,0,Australia,AU,AUS,25203200,Oceania,0.03570975\r
-26/02/2020,26,2,2020,0,0,Australia,AU,AUS,25203200,Oceania,0.031742\r
-25/02/2020,25,2,2020,0,0,Australia,AU,AUS,25203200,Oceania,0.031742\r
-24/02/2020,24,2,2020,0,0,Australia,AU,AUS,25203200,Oceania,0.031742\r
-23/02/2020,23,2,2020,1,0,Australia,AU,AUS,25203200,Oceania,0.031742\r
-22/02/2020,22,2,2020,4,0,Australia,AU,AUS,25203200,Oceania,0.02777425\r
-21/02/2020,21,2,2020,2,0,Australia,AU,AUS,25203200,Oceania,0.01190325\r
-20/02/2020,20,2,2020,0,0,Australia,AU,AUS,25203200,Oceania,0.0079355\r
-19/02/2020,19,2,2020,0,0,Australia,AU,AUS,25203200,Oceania,0.01190325\r
-18/02/2020,18,2,2020,0,0,Australia,AU,AUS,25203200,Oceania,0.015871\r
-17/02/2020,17,2,2020,0,0,Australia,AU,AUS,25203200,Oceania,0.015871\r
-16/02/2020,16,2,2020,0,0,Australia,AU,AUS,25203200,Oceania,0.015871\r
-15/02/2020,15,2,2020,0,0,Australia,AU,AUS,25203200,Oceania,0.0238065\r
-14/02/2020,14,2,2020,1,0,Australia,AU,AUS,25203200,Oceania,0.031742\r
-13/02/2020,13,2,2020,0,0,Australia,AU,AUS,25203200,Oceania,0.031742\r
-12/02/2020,12,2,2020,0,0,Australia,AU,AUS,25203200,Oceania,0.0396775\r
-11/02/2020,11,2,2020,0,0,Australia,AU,AUS,25203200,Oceania,0.0396775\r
-10/02/2020,10,2,2020,0,0,Australia,AU,AUS,25203200,Oceania,0.0396775\r
-09/02/2020,9,2,2020,0,0,Australia,AU,AUS,25203200,Oceania,0.0396775\r
-08/02/2020,8,2,2020,0,0,Australia,AU,AUS,25203200,Oceania,0.05158075\r
-07/02/2020,7,2,2020,1,0,Australia,AU,AUS,25203200,Oceania,0.0555485\r
-06/02/2020,6,2,2020,1,0,Australia,AU,AUS,25203200,Oceania,0.05158075\r
-05/02/2020,5,2,2020,1,0,Australia,AU,AUS,25203200,Oceania,0.047613\r
-04/02/2020,4,2,2020,0,0,Australia,AU,AUS,25203200,Oceania,0.04364525\r
-03/02/2020,3,2,2020,0,0,Australia,AU,AUS,25203200,Oceania,0.04364525\r
-02/02/2020,2,2,2020,2,0,Australia,AU,AUS,25203200,Oceania,0.04364525\r
-01/02/2020,1,2,2020,2,0,Australia,AU,AUS,25203200,Oceania,0.03570975\r
-31/01/2020,31,1,2020,1,0,Australia,AU,AUS,25203200,Oceania,0.02777425\r
-30/01/2020,30,1,2020,2,0,Australia,AU,AUS,25203200,Oceania,0.0238065\r
-29/01/2020,29,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,0.015871\r
-28/01/2020,28,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,0.015871\r
-27/01/2020,27,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,0.015871\r
-26/01/2020,26,1,2020,3,0,Australia,AU,AUS,25203200,Oceania,0.015871\r
-25/01/2020,25,1,2020,1,0,Australia,AU,AUS,25203200,Oceania,0.00396775\r
-24/01/2020,24,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,0\r
-23/01/2020,23,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,0\r
-22/01/2020,22,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,0\r
-21/01/2020,21,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,0\r
-20/01/2020,20,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,0\r
-19/01/2020,19,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,0\r
-18/01/2020,18,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,0\r
-17/01/2020,17,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,0\r
-16/01/2020,16,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,0\r
-15/01/2020,15,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,0\r
-14/01/2020,14,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,0\r
-13/01/2020,13,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,0\r
-12/01/2020,12,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,\r
-11/01/2020,11,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,\r
-10/01/2020,10,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,\r
-09/01/2020,9,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,\r
-08/01/2020,8,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,\r
-07/01/2020,7,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,\r
-06/01/2020,6,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,\r
-05/01/2020,5,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,\r
-04/01/2020,4,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,\r
-03/01/2020,3,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,\r
-02/01/2020,2,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,\r
-01/01/2020,1,1,2020,0,0,Australia,AU,AUS,25203200,Oceania,\r
-31/12/2019,31,12,2019,0,0,Australia,AU,AUS,25203200,Oceania,\r
-19/08/2020,19,8,2020,158,0,Austria,AT,AUT,8858775,Europe,27.1256466\r
-18/08/2020,18,8,2020,344,1,Austria,AT,AUT,8858775,Europe,26.82086406\r
-17/08/2020,17,8,2020,162,0,Austria,AT,AUT,8858775,Europe,23.29893241\r
-16/08/2020,16,8,2020,260,3,Austria,AT,AUT,8858775,Europe,22.42973775\r
-15/08/2020,15,8,2020,221,0,Austria,AT,AUT,8858775,Europe,20.91711326\r
-14/08/2020,14,8,2020,229,1,Austria,AT,AUT,8858775,Europe,19.42706525\r
-13/08/2020,13,8,2020,241,1,Austria,AT,AUT,8858775,Europe,18.68204125\r
-12/08/2020,12,8,2020,138,0,Austria,AT,AUT,8858775,Europe,17.81284658\r
-11/08/2020,11,8,2020,111,2,Austria,AT,AUT,8858775,Europe,17.74511713\r
-10/08/2020,10,8,2020,76,0,Austria,AT,AUT,8858775,Europe,17.21456973\r
-09/08/2020,9,8,2020,116,1,Austria,AT,AUT,8858775,Europe,17.90315252\r
-08/08/2020,8,8,2020,130,1,Austria,AT,AUT,8858775,Europe,17.94830549\r
-07/08/2020,7,8,2020,114,0,Austria,AT,AUT,8858775,Europe,17.68867592\r
-06/08/2020,6,8,2020,103,0,Austria,AT,AUT,8858775,Europe,18.25308804\r
-05/08/2020,5,8,2020,131,1,Austria,AT,AUT,8858775,Europe,18.67075301\r
-04/08/2020,4,8,2020,32,0,Austria,AT,AUT,8858775,Europe,18.76105895\r
-03/08/2020,3,8,2020,85,0,Austria,AT,AUT,8858775,Europe,19.61896538\r
-02/08/2020,2,8,2020,126,0,Austria,AT,AUT,8858775,Europe,19.37062404\r
-01/08/2020,1,8,2020,89,0,Austria,AT,AUT,8858775,Europe,19.09970622\r
-31/07/2020,31,7,2020,163,2,Austria,AT,AUT,8858775,Europe,19.6528301\r
-30/07/2020,30,7,2020,164,3,Austria,AT,AUT,8858775,Europe,19.53994768\r
-29/07/2020,29,7,2020,132,0,Austria,AT,AUT,8858775,Europe,18.30952925\r
-28/07/2020,28,7,2020,64,1,Austria,AT,AUT,8858775,Europe,19.08841798\r
-27/07/2020,27,7,2020,137,0,Austria,AT,AUT,8858775,Europe,18.50142937\r
-26/07/2020,26,7,2020,120,1,Austria,AT,AUT,8858775,Europe,17.54192877\r
-25/07/2020,25,7,2020,107,0,Austria,AT,AUT,8858775,Europe,17.40646986\r
-24/07/2020,24,7,2020,164,0,Austria,AT,AUT,8858775,Europe,17.03395786\r
-23/07/2020,23,7,2020,140,1,Austria,AT,AUT,8858775,Europe,16.27764561\r
-22/07/2020,22,7,2020,139,0,Austria,AT,AUT,8858775,Europe,15.83740416\r
-21/07/2020,21,7,2020,108,0,Austria,AT,AUT,8858775,Europe,15.27299203\r
-20/07/2020,20,7,2020,63,0,Austria,AT,AUT,8858775,Europe,14.69729167\r
-19/07/2020,19,7,2020,102,0,Austria,AT,AUT,8858775,Europe,14.81017409\r
-18/07/2020,18,7,2020,138,0,Austria,AT,AUT,8858775,Europe,15.04722718\r
-17/07/2020,17,7,2020,153,0,Austria,AT,AUT,8858775,Europe,14.85532706\r
-16/07/2020,16,7,2020,55,1,Austria,AT,AUT,8858775,Europe,14.68600343\r
-15/07/2020,15,7,2020,201,1,Austria,AT,AUT,8858775,Europe,14.48281506\r
-14/07/2020,14,7,2020,12,0,Austria,AT,AUT,8858775,Europe,13.46687324\r
-13/07/2020,13,7,2020,52,2,Austria,AT,AUT,8858775,Europe,13.79423227\r
-12/07/2020,12,7,2020,108,0,Austria,AT,AUT,8858775,Europe,13.91840294\r
-11/07/2020,11,7,2020,74,0,Austria,AT,AUT,8858775,Europe,13.42172027\r
-10/07/2020,10,7,2020,97,0,Austria,AT,AUT,8858775,Europe,13.34270257\r
-09/07/2020,9,7,2020,101,0,Austria,AT,AUT,8858775,Europe,12.77829045\r
-08/07/2020,8,7,2020,89,0,Austria,AT,AUT,8858775,Europe,12.01068997\r
-07/07/2020,7,7,2020,57,0,Austria,AT,AUT,8858775,Europe,11.3559719\r
-06/07/2020,6,7,2020,73,1,Austria,AT,AUT,8858775,Europe,11.10763057\r
-05/07/2020,5,7,2020,123,0,Austria,AT,AUT,8858775,Europe,10.71254208\r
-04/07/2020,4,7,2020,121,0,Austria,AT,AUT,8858775,Europe,10.02395929\r
-03/07/2020,3,7,2020,138,0,Austria,AT,AUT,8858775,Europe,8.99672923\r
-02/07/2020,2,7,2020,37,0,Austria,AT,AUT,8858775,Europe,7.89048147\r
-01/07/2020,1,7,2020,111,2,Austria,AT,AUT,8858775,Europe,7.66471662\r
-30/06/2020,30,6,2020,41,1,Austria,AT,AUT,8858775,Europe,6.78423371\r
-29/06/2020,29,6,2020,63,2,Austria,AT,AUT,8858775,Europe,6.62619832\r
-28/06/2020,28,6,2020,64,2,Austria,AT,AUT,8858775,Europe,6.18595686\r
-27/06/2020,27,6,2020,67,0,Austria,AT,AUT,8858775,Europe,5.68927419\r
-26/06/2020,26,6,2020,47,5,Austria,AT,AUT,8858775,Europe,5.27160922\r
-25/06/2020,25,6,2020,33,0,Austria,AT,AUT,8858775,Europe,5.05713262\r
-24/06/2020,24,6,2020,31,3,Austria,AT,AUT,8858775,Europe,5.06842086\r
-23/06/2020,23,6,2020,35,0,Austria,AT,AUT,8858775,Europe,4.8652325\r
-22/06/2020,22,6,2020,38,2,Austria,AT,AUT,8858775,Europe,4.7071971\r
-21/06/2020,21,6,2020,62,0,Austria,AT,AUT,8858775,Europe,4.79750304\r
-20/06/2020,20,6,2020,30,0,Austria,AT,AUT,8858775,Europe,4.31210862\r
-19/06/2020,19,6,2020,40,1,Austria,AT,AUT,8858775,Europe,4.67333237\r
-18/06/2020,18,6,2020,17,6,Austria,AT,AUT,8858775,Europe,4.6281794\r
-17/06/2020,17,6,2020,33,3,Austria,AT,AUT,8858775,Europe,4.7862148\r
-16/06/2020,16,6,2020,27,1,Austria,AT,AUT,8858775,Europe,4.53787346\r
-15/06/2020,15,6,2020,24,0,Austria,AT,AUT,8858775,Europe,4.47014401\r
-14/06/2020,14,6,2020,20,2,Austria,AT,AUT,8858775,Europe,4.24437916\r
-13/06/2020,13,6,2020,30,1,Austria,AT,AUT,8858775,Europe,4.51529698\r
-12/06/2020,12,6,2020,28,1,Austria,AT,AUT,8858775,Europe,4.75235007\r
-11/06/2020,11,6,2020,34,1,Austria,AT,AUT,8858775,Europe,4.75235007\r
-10/06/2020,10,6,2020,13,0,Austria,AT,AUT,8858775,Europe,4.57173819\r
-09/06/2020,9,6,2020,21,0,Austria,AT,AUT,8858775,Europe,4.85394425\r
-08/06/2020,8,6,2020,46,0,Austria,AT,AUT,8858775,Europe,4.84265601\r
-07/06/2020,7,6,2020,19,0,Austria,AT,AUT,8858775,Europe,4.68462062\r
-06/06/2020,6,6,2020,62,2,Austria,AT,AUT,8858775,Europe,4.98940316\r
-05/06/2020,5,6,2020,36,0,Austria,AT,AUT,8858775,Europe,4.61689116\r
-04/06/2020,4,6,2020,31,1,Austria,AT,AUT,8858775,Europe,4.85394425\r
-03/06/2020,3,6,2020,11,1,Austria,AT,AUT,8858775,Europe,4.7071971\r
-02/06/2020,2,6,2020,21,0,Austria,AT,AUT,8858775,Europe,5.46350935\r
-01/06/2020,1,6,2020,4,0,Austria,AT,AUT,8858775,Europe,5.50866232\r
-31/05/2020,31,5,2020,44,0,Austria,AT,AUT,8858775,Europe,5.62154474\r
-30/05/2020,30,5,2020,51,0,Austria,AT,AUT,8858775,Europe,5.93761553\r
-29/05/2020,29,5,2020,28,23,Austria,AT,AUT,8858775,Europe,6.07307444\r
-28/05/2020,28,5,2020,18,2,Austria,AT,AUT,8858775,Europe,6.21982159\r
-27/05/2020,27,5,2020,38,2,Austria,AT,AUT,8858775,Europe,6.62619832\r
-26/05/2020,26,5,2020,20,1,Austria,AT,AUT,8858775,Europe,6.60362183\r
-25/05/2020,25,5,2020,32,1,Austria,AT,AUT,8858775,Europe,7.35993408\r
-24/05/2020,24,5,2020,46,4,Austria,AT,AUT,8858775,Europe,7.11159274\r
-23/05/2020,23,5,2020,29,2,Austria,AT,AUT,8858775,Europe,7.06643977\r
-22/05/2020,22,5,2020,57,0,Austria,AT,AUT,8858775,Europe,7.43895177\r
-21/05/2020,21,5,2020,18,1,Austria,AT,AUT,8858775,Europe,7.04386329\r
-20/05/2020,20,5,2020,78,3,Austria,AT,AUT,8858775,Europe,7.57441068\r
-19/05/2020,19,5,2020,25,0,Austria,AT,AUT,8858775,Europe,6.88582789\r
-18/05/2020,18,5,2020,14,1,Austria,AT,AUT,8858775,Europe,6.95355735\r
-17/05/2020,17,5,2020,72,0,Austria,AT,AUT,8858775,Europe,7.56312244\r
-16/05/2020,16,5,2020,63,2,Austria,AT,AUT,8858775,Europe,6.88582789\r
-15/05/2020,15,5,2020,41,2,Austria,AT,AUT,8858775,Europe,6.55846886\r
-14/05/2020,14,5,2020,54,1,Austria,AT,AUT,8858775,Europe,6.77294547\r
-13/05/2020,13,5,2020,36,3,Austria,AT,AUT,8858775,Europe,6.7277925\r
-12/05/2020,12,5,2020,87,2,Austria,AT,AUT,8858775,Europe,6.97613383\r
-11/05/2020,11,5,2020,10,3,Austria,AT,AUT,8858775,Europe,6.75036898\r
-10/05/2020,10,5,2020,42,1,Austria,AT,AUT,8858775,Europe,7.25833989\r
-09/05/2020,9,5,2020,62,5,Austria,AT,AUT,8858775,Europe,7.52925771\r
-08/05/2020,8,5,2020,22,1,Austria,AT,AUT,8858775,Europe,7.7663108\r
-07/05/2020,7,5,2020,65,2,Austria,AT,AUT,8858775,Europe,8.20655226\r
-06/05/2020,6,5,2020,17,6,Austria,AT,AUT,8858775,Europe,8.50004656\r
-05/05/2020,5,5,2020,31,2,Austria,AT,AUT,8858775,Europe,8.87255856\r
-04/05/2020,4,5,2020,68,2,Austria,AT,AUT,8858775,Europe,9.34666475\r
-03/05/2020,3,5,2020,12,7,Austria,AT,AUT,8858775,Europe,9.1208999\r
-02/05/2020,2,5,2020,34,5,Austria,AT,AUT,8858775,Europe,9.65144729\r
-01/05/2020,1,5,2020,60,4,Austria,AT,AUT,8858775,Europe,11.01732463\r
-30/04/2020,30,4,2020,50,11,Austria,AT,AUT,8858775,Europe,11.22051299\r
-29/04/2020,29,4,2020,58,20,Austria,AT,AUT,8858775,Europe,12.19130184\r
-28/04/2020,28,4,2020,67,7,Austria,AT,AUT,8858775,Europe,13.69263809\r
-27/04/2020,27,4,2020,55,6,Austria,AT,AUT,8858775,Europe,14.13287955\r
-26/04/2020,26,4,2020,66,23,Austria,AT,AUT,8858775,Europe,14.97949773\r
-25/04/2020,25,4,2020,83,5,Austria,AT,AUT,8858775,Europe,17.02266961\r
-24/04/2020,24,4,2020,61,14,Austria,AT,AUT,8858775,Europe,19.60767713\r
-23/04/2020,23,4,2020,91,31,Austria,AT,AUT,8858775,Europe,22.06851399\r
-22/04/2020,22,4,2020,50,1,Austria,AT,AUT,8858775,Europe,24.75511569\r
-21/04/2020,21,4,2020,73,10,Austria,AT,AUT,8858775,Europe,28.06257073\r
-20/04/2020,20,4,2020,48,9,Austria,AT,AUT,8858775,Europe,30.78303716\r
-19/04/2020,19,4,2020,59,12,Austria,AT,AUT,8858775,Europe,32.69075013\r
-18/04/2020,18,4,2020,155,21,Austria,AT,AUT,8858775,Europe,34.74521026\r
-17/04/2020,17,4,2020,78,17,Austria,AT,AUT,8858775,Europe,37.46567669\r
-16/04/2020,16,4,2020,136,9,Austria,AT,AUT,8858775,Europe,41.30367912\r
-15/04/2020,15,4,2020,191,16,Austria,AT,AUT,8858775,Europe,45.7399584\r
-14/04/2020,14,4,2020,106,18,Austria,AT,AUT,8858775,Europe,49.95047284\r
-13/04/2020,13,4,2020,130,13,Austria,AT,AUT,8858775,Europe,57.84095431\r
-12/04/2020,12,4,2020,247,18,Austria,AT,AUT,8858775,Europe,62.26594535\r
-11/04/2020,11,4,2020,312,24,Austria,AT,AUT,8858775,Europe,66.18296548\r
-10/04/2020,10,4,2020,279,22,Austria,AT,AUT,8858775,Europe,70.20157979\r
-09/04/2020,9,4,2020,329,30,Austria,AT,AUT,8858775,Europe,79.93204478\r
-08/04/2020,8,4,2020,343,23,Austria,AT,AUT,8858775,Europe,83.05888794\r
-07/04/2020,7,4,2020,314,16,Austria,AT,AUT,8858775,Europe,88.17246177\r
-06/04/2020,6,4,2020,217,18,Austria,AT,AUT,8858775,Europe,94.27940093\r
-05/04/2020,5,4,2020,241,18,Austria,AT,AUT,8858775,Europe,98.68181549\r
-04/04/2020,4,4,2020,396,10,Austria,AT,AUT,8858775,Europe,100.19443998\r
-03/04/2020,3,4,2020,418,12,Austria,AT,AUT,8858775,Europe,100.8378698\r
-02/04/2020,2,4,2020,529,18,Austria,AT,AUT,8858775,Europe,102.3279178\r
-01/04/2020,1,4,2020,564,20,Austria,AT,AUT,8858775,Europe,99.90094567\r
-31/03/2020,31,3,2020,805,22,Austria,AT,AUT,8858775,Europe,97.10146155\r
-30/03/2020,30,3,2020,522,18,Austria,AT,AUT,8858775,Europe,89.7753922\r
-29/03/2020,29,3,2020,594,0,Austria,AT,AUT,8858775,Europe,86.19701934\r
-28/03/2020,28,3,2020,668,16,Austria,AT,AUT,8858775,Europe,81.19632793\r
-27/03/2020,27,3,2020,1141,18,Austria,AT,AUT,8858775,Europe,75.27000065\r
-26/03/2020,26,3,2020,606,4,Austria,AT,AUT,8858775,Europe,63.6882639\r
-25/03/2020,25,3,2020,796,5,Austria,AT,AUT,8858775,Europe,57.57003649\r
-24/03/2020,24,3,2020,855,9,Austria,AT,AUT,8858775,Europe,49.16029586\r
-23/03/2020,23,3,2020,607,8,Austria,AT,AUT,8858775,Europe,39.8362076\r
-22/03/2020,22,3,2020,375,2,Austria,AT,AUT,8858775,Europe,33.01810916\r
-21/03/2020,21,3,2020,453,0,Austria,AT,AUT,8858775,Europe,29.06722431\r
-20/03/2020,20,3,2020,550,2,Austria,AT,AUT,8858775,Europe,24.32616248\r
-19/03/2020,19,3,2020,314,1,Austria,AT,AUT,8858775,Europe,18.25308804\r
-18/03/2020,18,3,2020,316,0,Austria,AT,AUT,8858775,Europe,14.76502112\r
-17/03/2020,17,3,2020,156,2,Austria,AT,AUT,8858775,Europe,11.26566596\r
-16/03/2020,16,3,2020,205,0,Austria,AT,AUT,8858775,Europe,9.54985311\r
-15/03/2020,15,3,2020,151,0,Austria,AT,AUT,8858775,Europe,7.28091638\r
-14/03/2020,14,3,2020,143,0,Austria,AT,AUT,8858775,Europe,5.6102565\r
-13/03/2020,13,3,2020,115,1,Austria,AT,AUT,8858775,Europe,4.01861431\r
-12/03/2020,12,3,2020,64,0,Austria,AT,AUT,8858775,Europe,2.75433116\r
-11/03/2020,11,3,2020,51,0,Austria,AT,AUT,8858775,Europe,2.03188364\r
-10/03/2020,10,3,2020,29,0,Austria,AT,AUT,8858775,Europe,1.47875976\r
-09/03/2020,9,3,2020,3,0,Austria,AT,AUT,8858775,Europe,1.15140073\r
-08/03/2020,8,3,2020,25,0,Austria,AT,AUT,8858775,Europe,1.117536\r
-07/03/2020,7,3,2020,33,0,Austria,AT,AUT,8858775,Europe,0.83532994\r
-06/03/2020,6,3,2020,12,0,Austria,AT,AUT,8858775,Europe,0.46281794\r
-05/03/2020,5,3,2020,5,0,Austria,AT,AUT,8858775,Europe,0.32735903\r
-04/03/2020,4,3,2020,6,0,Austria,AT,AUT,8858775,Europe,0.27091782\r
-03/03/2020,3,3,2020,4,0,Austria,AT,AUT,8858775,Europe,0.20318836\r
-02/03/2020,2,3,2020,4,0,Austria,AT,AUT,8858775,Europe,0.15803539\r
-01/03/2020,1,3,2020,3,0,Austria,AT,AUT,8858775,Europe,0.11288242\r
-29/02/2020,29,2,2020,2,0,Austria,AT,AUT,8858775,Europe,0.0790177\r
-28/02/2020,28,2,2020,3,0,Austria,AT,AUT,8858775,Europe,0.05644121\r
-27/02/2020,27,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0.02257648\r
-26/02/2020,26,2,2020,2,0,Austria,AT,AUT,8858775,Europe,0.02257648\r
-25/02/2020,25,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-24/02/2020,24,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-23/02/2020,23,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-22/02/2020,22,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-21/02/2020,21,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-20/02/2020,20,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-19/02/2020,19,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-18/02/2020,18,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-17/02/2020,17,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-16/02/2020,16,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-15/02/2020,15,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-14/02/2020,14,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-13/02/2020,13,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-12/02/2020,12,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-11/02/2020,11,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-10/02/2020,10,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-09/02/2020,9,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-08/02/2020,8,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-07/02/2020,7,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-06/02/2020,6,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-05/02/2020,5,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-04/02/2020,4,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-03/02/2020,3,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-02/02/2020,2,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-01/02/2020,1,2,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-31/01/2020,31,1,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-30/01/2020,30,1,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-29/01/2020,29,1,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-28/01/2020,28,1,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-27/01/2020,27,1,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-26/01/2020,26,1,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-25/01/2020,25,1,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-24/01/2020,24,1,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-23/01/2020,23,1,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-22/01/2020,22,1,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-21/01/2020,21,1,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-20/01/2020,20,1,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-19/01/2020,19,1,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-18/01/2020,18,1,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-17/01/2020,17,1,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-16/01/2020,16,1,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-15/01/2020,15,1,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-14/01/2020,14,1,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-13/01/2020,13,1,2020,0,0,Austria,AT,AUT,8858775,Europe,0\r
-12/01/2020,12,1,2020,0,0,Austria,AT,AUT,8858775,Europe,\r
-11/01/2020,11,1,2020,0,0,Austria,AT,AUT,8858775,Europe,\r
-10/01/2020,10,1,2020,0,0,Austria,AT,AUT,8858775,Europe,\r
-09/01/2020,9,1,2020,0,0,Austria,AT,AUT,8858775,Europe,\r
-08/01/2020,8,1,2020,0,0,Austria,AT,AUT,8858775,Europe,\r
-07/01/2020,7,1,2020,0,0,Austria,AT,AUT,8858775,Europe,\r
-06/01/2020,6,1,2020,0,0,Austria,AT,AUT,8858775,Europe,\r
-05/01/2020,5,1,2020,0,0,Austria,AT,AUT,8858775,Europe,\r
-04/01/2020,4,1,2020,0,0,Austria,AT,AUT,8858775,Europe,\r
-03/01/2020,3,1,2020,0,0,Austria,AT,AUT,8858775,Europe,\r
-02/01/2020,2,1,2020,0,0,Austria,AT,AUT,8858775,Europe,\r
-01/01/2020,1,1,2020,0,0,Austria,AT,AUT,8858775,Europe,\r
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-18/08/2020,18,8,2020,124,2,Azerbaijan,AZ,AZE,10047719,Europe,16.51121016\r
-17/08/2020,17,8,2020,112,0,Azerbaijan,AZ,AZE,10047719,Europe,17.67565355\r
-16/08/2020,16,8,2020,89,2,Azerbaijan,AZ,AZE,10047719,Europe,19.40738988\r
-15/08/2020,15,8,2020,103,4,Azerbaijan,AZ,AZE,10047719,Europe,21.29836633\r
-14/08/2020,14,8,2020,91,3,Azerbaijan,AZ,AZE,10047719,Europe,23.43815547\r
-13/08/2020,13,8,2020,93,2,Azerbaijan,AZ,AZE,10047719,Europe,25.90637736\r
-12/08/2020,12,8,2020,84,3,Azerbaijan,AZ,AZE,10047719,Europe,28.59355442\r
-11/08/2020,11,8,2020,79,2,Azerbaijan,AZ,AZE,10047719,Europe,31.85797692\r
-10/08/2020,10,8,2020,87,2,Azerbaijan,AZ,AZE,10047719,Europe,35.01292184\r
-09/08/2020,9,8,2020,105,5,Azerbaijan,AZ,AZE,10047719,Europe,38.29724936\r
-08/08/2020,8,8,2020,129,4,Azerbaijan,AZ,AZE,10047719,Europe,40.446991\r
-07/08/2020,7,8,2020,144,3,Azerbaijan,AZ,AZE,10047719,Europe,42.46735005\r
-06/08/2020,6,8,2020,193,3,Azerbaijan,AZ,AZE,10047719,Europe,44.4877091\r
-05/08/2020,5,8,2020,226,5,Azerbaijan,AZ,AZE,10047719,Europe,46.45830561\r
-04/08/2020,4,8,2020,241,6,Azerbaijan,AZ,AZE,10047719,Europe,47.71232157\r
-03/08/2020,3,8,2020,286,8,Azerbaijan,AZ,AZE,10047719,Europe,48.98624255\r
-02/08/2020,2,8,2020,279,6,Azerbaijan,AZ,AZE,10047719,Europe,50.00139833\r
-01/08/2020,1,8,2020,318,7,Azerbaijan,AZ,AZE,10047719,Europe,52.17104499\r
-31/07/2020,31,7,2020,339,3,Azerbaijan,AZ,AZE,10047719,Europe,53.69377866\r
-30/07/2020,30,7,2020,363,8,Azerbaijan,AZ,AZE,10047719,Europe,55.22646483\r
-29/07/2020,29,7,2020,412,7,Azerbaijan,AZ,AZE,10047719,Europe,57.17715633\r
-28/07/2020,28,7,2020,396,6,Azerbaijan,AZ,AZE,10047719,Europe,58.48093483\r
-27/07/2020,27,7,2020,417,9,Azerbaijan,AZ,AZE,10047719,Europe,59.80461834\r
-26/07/2020,26,7,2020,321,8,Azerbaijan,AZ,AZE,10047719,Europe,60.82972663\r
-25/07/2020,25,7,2020,332,9,Azerbaijan,AZ,AZE,10047719,Europe,62.91975323\r
-24/07/2020,24,7,2020,347,6,Azerbaijan,AZ,AZE,10047719,Europe,64.85053971\r
-23/07/2020,23,7,2020,391,9,Azerbaijan,AZ,AZE,10047719,Europe,66.85099374\r
-22/07/2020,22,7,2020,352,13,Azerbaijan,AZ,AZE,10047719,Europe,68.35382239\r
-21/07/2020,21,7,2020,369,9,Azerbaijan,AZ,AZE,10047719,Europe,70.19503631\r
-20/07/2020,20,7,2020,388,5,Azerbaijan,AZ,AZE,10047719,Europe,71.6281974\r
-19/07/2020,19,7,2020,497,8,Azerbaijan,AZ,AZE,10047719,Europe,72.97178593\r
-18/07/2020,18,7,2020,471,7,Azerbaijan,AZ,AZE,10047719,Europe,73.34002872\r
-17/07/2020,17,7,2020,493,8,Azerbaijan,AZ,AZE,10047719,Europe,74.45470957\r
-16/07/2020,16,7,2020,559,7,Azerbaijan,AZ,AZE,10047719,Europe,75.24095767\r
-15/07/2020,15,7,2020,543,6,Azerbaijan,AZ,AZE,10047719,Europe,75.5295804\r
-14/07/2020,14,7,2020,529,7,Azerbaijan,AZ,AZE,10047719,Europe,75.65896299\r
-13/07/2020,13,7,2020,520,8,Azerbaijan,AZ,AZE,10047719,Europe,75.80825061\r
-12/07/2020,12,7,2020,531,6,Azerbaijan,AZ,AZE,10047719,Europe,75.94758572\r
-11/07/2020,11,7,2020,526,8,Azerbaijan,AZ,AZE,10047719,Europe,75.84806064\r
-10/07/2020,10,7,2020,548,10,Azerbaijan,AZ,AZE,10047719,Europe,75.75848807\r
-09/07/2020,9,7,2020,542,9,Azerbaijan,AZ,AZE,10047719,Europe,75.74853556\r
-08/07/2020,8,7,2020,537,7,Azerbaijan,AZ,AZE,10047719,Europe,76.22625593\r
-07/07/2020,7,7,2020,513,8,Azerbaijan,AZ,AZE,10047719,Europe,75.93763321\r
-06/07/2020,6,7,2020,523,9,Azerbaijan,AZ,AZE,10047719,Europe,75.58929544\r
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-29/06/2020,29,6,2020,0,0,Bahamas,BS,BHS,389486,America,0.25674864\r
-28/06/2020,28,6,2020,0,0,Bahamas,BS,BHS,389486,America,0.25674864\r
-27/06/2020,27,6,2020,0,0,Bahamas,BS,BHS,389486,America,0.25674864\r
-26/06/2020,26,6,2020,0,0,Bahamas,BS,BHS,389486,America,0.25674864\r
-25/06/2020,25,6,2020,0,0,Bahamas,BS,BHS,389486,America,0.25674864\r
-24/06/2020,24,6,2020,0,0,Bahamas,BS,BHS,389486,America,0.25674864\r
-23/06/2020,23,6,2020,0,0,Bahamas,BS,BHS,389486,America,0.25674864\r
-22/06/2020,22,6,2020,0,0,Bahamas,BS,BHS,389486,America,0.25674864\r
-21/06/2020,21,6,2020,0,0,Bahamas,BS,BHS,389486,America,0.25674864\r
-20/06/2020,20,6,2020,0,0,Bahamas,BS,BHS,389486,America,0.51349728\r
-19/06/2020,19,6,2020,0,0,Bahamas,BS,BHS,389486,America,0.51349728\r
-18/06/2020,18,6,2020,0,0,Bahamas,BS,BHS,389486,America,0.51349728\r
-17/06/2020,17,6,2020,0,0,Bahamas,BS,BHS,389486,America,0.51349728\r
-16/06/2020,16,6,2020,1,0,Bahamas,BS,BHS,389486,America,0.51349728\r
-15/06/2020,15,6,2020,0,0,Bahamas,BS,BHS,389486,America,0.25674864\r
-14/06/2020,14,6,2020,0,0,Bahamas,BS,BHS,389486,America,0.25674864\r
-13/06/2020,13,6,2020,0,0,Bahamas,BS,BHS,389486,America,0.25674864\r
-12/06/2020,12,6,2020,0,0,Bahamas,BS,BHS,389486,America,0.51349728\r
-11/06/2020,11,6,2020,0,0,Bahamas,BS,BHS,389486,America,0.77024591\r
-10/06/2020,10,6,2020,0,0,Bahamas,BS,BHS,389486,America,0.77024591\r
-09/06/2020,9,6,2020,0,0,Bahamas,BS,BHS,389486,America,0.77024591\r
-08/06/2020,8,6,2020,0,0,Bahamas,BS,BHS,389486,America,0.77024591\r
-07/06/2020,7,6,2020,1,0,Bahamas,BS,BHS,389486,America,0.77024591\r
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-05/06/2020,5,6,2020,0,0,Bahamas,BS,BHS,389486,America,1.28374319\r
-04/06/2020,4,6,2020,0,0,Bahamas,BS,BHS,389486,America,1.28374319\r
-03/06/2020,3,6,2020,0,0,Bahamas,BS,BHS,389486,America,1.54049183\r
-02/06/2020,2,6,2020,0,0,Bahamas,BS,BHS,389486,America,1.54049183\r
-01/06/2020,1,6,2020,0,0,Bahamas,BS,BHS,389486,America,1.54049183\r
-31/05/2020,31,5,2020,0,0,Bahamas,BS,BHS,389486,America,1.54049183\r
-30/05/2020,30,5,2020,1,0,Bahamas,BS,BHS,389486,America,1.54049183\r
-29/05/2020,29,5,2020,1,0,Bahamas,BS,BHS,389486,America,1.28374319\r
-28/05/2020,28,5,2020,0,0,Bahamas,BS,BHS,389486,America,1.54049183\r
-27/05/2020,27,5,2020,0,0,Bahamas,BS,BHS,389486,America,1.79724047\r
-26/05/2020,26,5,2020,0,0,Bahamas,BS,BHS,389486,America,1.79724047\r
-25/05/2020,25,5,2020,0,0,Bahamas,BS,BHS,389486,America,2.0539891\r
-24/05/2020,24,5,2020,3,0,Bahamas,BS,BHS,389486,America,2.0539891\r
-23/05/2020,23,5,2020,0,0,Bahamas,BS,BHS,389486,America,1.28374319\r
-22/05/2020,22,5,2020,0,0,Bahamas,BS,BHS,389486,America,1.28374319\r
-21/05/2020,21,5,2020,1,0,Bahamas,BS,BHS,389486,America,1.28374319\r
-20/05/2020,20,5,2020,0,0,Bahamas,BS,BHS,389486,America,1.79724047\r
-19/05/2020,19,5,2020,0,0,Bahamas,BS,BHS,389486,America,3.33773229\r
-18/05/2020,18,5,2020,0,0,Bahamas,BS,BHS,389486,America,3.33773229\r
-17/05/2020,17,5,2020,0,0,Bahamas,BS,BHS,389486,America,3.33773229\r
-16/05/2020,16,5,2020,0,0,Bahamas,BS,BHS,389486,America,3.59448093\r
-15/05/2020,15,5,2020,2,0,Bahamas,BS,BHS,389486,America,3.85122957\r
-14/05/2020,14,5,2020,1,0,Bahamas,BS,BHS,389486,America,3.59448093\r
-13/05/2020,13,5,2020,0,0,Bahamas,BS,BHS,389486,America,3.33773229\r
-12/05/2020,12,5,2020,1,0,Bahamas,BS,BHS,389486,America,3.33773229\r
-11/05/2020,11,5,2020,0,0,Bahamas,BS,BHS,389486,America,3.08098366\r
-10/05/2020,10,5,2020,0,0,Bahamas,BS,BHS,389486,America,3.59448093\r
-09/05/2020,9,5,2020,0,0,Bahamas,BS,BHS,389486,America,4.87822412\r
-08/05/2020,8,5,2020,0,0,Bahamas,BS,BHS,389486,America,5.13497276\r
-07/05/2020,7,5,2020,3,0,Bahamas,BS,BHS,389486,America,5.64847003\r
-06/05/2020,6,5,2020,6,0,Bahamas,BS,BHS,389486,America,6.16196731\r
-05/05/2020,5,5,2020,0,0,Bahamas,BS,BHS,389486,America,4.87822412\r
-04/05/2020,4,5,2020,0,0,Bahamas,BS,BHS,389486,America,5.90521867\r
-03/05/2020,3,5,2020,1,0,Bahamas,BS,BHS,389486,America,6.41871595\r
-02/05/2020,2,5,2020,1,0,Bahamas,BS,BHS,389486,America,6.93221322\r
-01/05/2020,1,5,2020,1,0,Bahamas,BS,BHS,389486,America,6.93221322\r
-30/04/2020,30,4,2020,0,0,Bahamas,BS,BHS,389486,America,6.93221322\r
-29/04/2020,29,4,2020,0,0,Bahamas,BS,BHS,389486,America,7.95920778\r
-28/04/2020,28,4,2020,0,0,Bahamas,BS,BHS,389486,America,7.95920778\r
-27/04/2020,27,4,2020,2,0,Bahamas,BS,BHS,389486,America,8.47270505\r
-26/04/2020,26,4,2020,5,0,Bahamas,BS,BHS,389486,America,8.21595641\r
-25/04/2020,25,4,2020,1,0,Bahamas,BS,BHS,389486,America,7.95920778\r
-24/04/2020,24,4,2020,2,2,Bahamas,BS,BHS,389486,America,7.95920778\r
-23/04/2020,23,4,2020,5,0,Bahamas,BS,BHS,389486,America,7.70245914\r
-22/04/2020,22,4,2020,1,0,Bahamas,BS,BHS,389486,America,7.4457105\r
-21/04/2020,21,4,2020,4,0,Bahamas,BS,BHS,389486,America,7.95920778\r
-20/04/2020,20,4,2020,2,0,Bahamas,BS,BHS,389486,America,7.95920778\r
-19/04/2020,19,4,2020,3,0,Bahamas,BS,BHS,389486,America,7.70245914\r
-18/04/2020,18,4,2020,1,0,Bahamas,BS,BHS,389486,America,7.95920778\r
-17/04/2020,17,4,2020,1,1,Bahamas,BS,BHS,389486,America,7.70245914\r
-16/04/2020,16,4,2020,4,0,Bahamas,BS,BHS,389486,America,8.21595641\r
-15/04/2020,15,4,2020,0,0,Bahamas,BS,BHS,389486,America,8.72945369\r
-14/04/2020,14,4,2020,2,0,Bahamas,BS,BHS,389486,America,8.98620233\r
-13/04/2020,13,4,2020,1,0,Bahamas,BS,BHS,389486,America,8.47270505\r
-12/04/2020,12,4,2020,4,0,Bahamas,BS,BHS,389486,America,8.98620233\r
-11/04/2020,11,4,2020,1,0,Bahamas,BS,BHS,389486,America,8.47270505\r
-10/04/2020,10,4,2020,1,1,Bahamas,BS,BHS,389486,America,8.21595641\r
-09/04/2020,9,4,2020,4,1,Bahamas,BS,BHS,389486,America,8.98620233\r
-08/04/2020,8,4,2020,3,1,Bahamas,BS,BHS,389486,America,8.21595641\r
-07/04/2020,7,4,2020,4,0,Bahamas,BS,BHS,389486,America,7.4457105\r
-06/04/2020,6,4,2020,1,1,Bahamas,BS,BHS,389486,America,6.41871595\r
-05/04/2020,5,4,2020,4,1,Bahamas,BS,BHS,389486,America,6.16196731\r
-04/04/2020,4,4,2020,0,2,Bahamas,BS,BHS,389486,America,5.13497276\r
-03/04/2020,3,4,2020,3,0,Bahamas,BS,BHS,389486,America,5.3917214\r
-02/04/2020,2,4,2020,6,1,Bahamas,BS,BHS,389486,America,5.13497276\r
-01/04/2020,1,4,2020,1,0,Bahamas,BS,BHS,389486,America,3.59448093\r
-31/03/2020,31,3,2020,0,0,Bahamas,BS,BHS,389486,America,3.59448093\r
-30/03/2020,30,3,2020,3,0,Bahamas,BS,BHS,389486,America,\r
-29/03/2020,29,3,2020,2,0,Bahamas,BS,BHS,389486,America,\r
-28/03/2020,28,3,2020,0,0,Bahamas,BS,BHS,389486,America,\r
-27/03/2020,27,3,2020,4,0,Bahamas,BS,BHS,389486,America,\r
-26/03/2020,26,3,2020,1,0,Bahamas,BS,BHS,389486,America,\r
-25/03/2020,25,3,2020,0,0,Bahamas,BS,BHS,389486,America,\r
-24/03/2020,24,3,2020,0,0,Bahamas,BS,BHS,389486,America,\r
-23/03/2020,23,3,2020,0,0,Bahamas,BS,BHS,389486,America,\r
-22/03/2020,22,3,2020,0,0,Bahamas,BS,BHS,389486,America,\r
-21/03/2020,21,3,2020,1,0,Bahamas,BS,BHS,389486,America,\r
-20/03/2020,20,3,2020,2,0,Bahamas,BS,BHS,389486,America,\r
-17/03/2020,17,3,2020,0,0,Bahamas,BS,BHS,389486,America,\r
-16/03/2020,16,3,2020,1,0,Bahamas,BS,BHS,389486,America,\r
-19/08/2020,19,8,2020,0,2,Bahrain,BH,BHR,1641164,Asia,307.89122842\r
-18/08/2020,18,8,2020,755,3,Bahrain,BH,BHR,1641164,Asia,325.98814012\r
-17/08/2020,17,8,2020,0,0,Bahrain,BH,BHR,1641164,Asia,298.20298276\r
-16/08/2020,16,8,2020,378,2,Bahrain,BH,BHR,1641164,Asia,319.28558023\r
-15/08/2020,15,8,2020,326,1,Bahrain,BH,BHR,1641164,Asia,308.92707859\r
-14/08/2020,14,8,2020,462,1,Bahrain,BH,BHR,1641164,Asia,302.89477468\r
-13/08/2020,13,8,2020,460,1,Bahrain,BH,BHR,1641164,Asia,301.79799216\r
-12/08/2020,12,8,2020,407,2,Bahrain,BH,BHR,1641164,Asia,297.53272677\r
-11/08/2020,11,8,2020,386,1,Bahrain,BH,BHR,1641164,Asia,299.48256238\r
-10/08/2020,10,8,2020,382,1,Bahrain,BH,BHR,1641164,Asia,297.34992968\r
-09/08/2020,9,8,2020,322,2,Bahrain,BH,BHR,1641164,Asia,297.47179441\r
-08/08/2020,8,8,2020,418,3,Bahrain,BH,BHR,1641164,Asia,295.46102644\r
-07/08/2020,7,8,2020,375,2,Bahrain,BH,BHR,1641164,Asia,298.1420504\r
-06/08/2020,6,8,2020,382,3,Bahrain,BH,BHR,1641164,Asia,297.1671326\r
-05/08/2020,5,8,2020,297,1,Bahrain,BH,BHR,1641164,Asia,293.45025848\r
-04/08/2020,4,8,2020,299,3,Bahrain,BH,BHR,1641164,Asia,298.50764457\r
-03/08/2020,3,8,2020,346,0,Bahrain,BH,BHR,1641164,Asia,311.60810254\r
-02/08/2020,2,8,2020,208,0,Bahrain,BH,BHR,1641164,Asia,315.99523265\r
-01/08/2020,1,8,2020,227,1,Bahrain,BH,BHR,1641164,Asia,335.67638578\r
-31/07/2020,31,7,2020,444,2,Bahrain,BH,BHR,1641164,Asia,345.54742853\r
-30/07/2020,30,7,2020,390,3,Bahrain,BH,BHR,1641164,Asia,350.42201754\r
-29/07/2020,29,7,2020,439,0,Bahrain,BH,BHR,1641164,Asia,356.02779491\r
-28/07/2020,28,7,2020,351,1,Bahrain,BH,BHR,1641164,Asia,365.95977002\r
-27/07/2020,27,7,2020,384,3,Bahrain,BH,BHR,1641164,Asia,377.17132474\r
-26/07/2020,26,7,2020,289,1,Bahrain,BH,BHR,1641164,Asia,382.47244029\r
-25/07/2020,25,7,2020,462,2,Bahrain,BH,BHR,1641164,Asia,391.12483579\r
-24/07/2020,24,7,2020,359,4,Bahrain,BH,BHR,1641164,Asia,394.11052156\r
-23/07/2020,23,7,2020,321,1,Bahrain,BH,BHR,1641164,Asia,408.61242387\r
-22/07/2020,22,7,2020,380,1,Bahrain,BH,BHR,1641164,Asia,426.22187667\r
-21/07/2020,21,7,2020,514,2,Bahrain,BH,BHR,1641164,Asia,433.53376018\r
-20/07/2020,20,7,2020,418,2,Bahrain,BH,BHR,1641164,Asia,429.87781843\r
-19/07/2020,19,7,2020,531,0,Bahrain,BH,BHR,1641164,Asia,435.48359579\r
-18/07/2020,18,7,2020,389,3,Bahrain,BH,BHR,1641164,Asia,430.36527733\r
-17/07/2020,17,7,2020,524,4,Bahrain,BH,BHR,1641164,Asia,441.57683205\r
-16/07/2020,16,7,2020,482,6,Bahrain,BH,BHR,1641164,Asia,435.42266343\r
-15/07/2020,15,7,2020,602,2,Bahrain,BH,BHR,1641164,Asia,446.02489453\r
-14/07/2020,14,7,2020,535,0,Bahrain,BH,BHR,1641164,Asia,440.96750843\r
-13/07/2020,13,7,2020,471,5,Bahrain,BH,BHR,1641164,Asia,440.90657606\r
-12/07/2020,12,7,2020,431,0,Bahrain,BH,BHR,1641164,Asia,438.8958081\r
-11/07/2020,11,7,2020,511,1,Bahrain,BH,BHR,1641164,Asia,440.78471134\r
-10/07/2020,10,7,2020,597,3,Bahrain,BH,BHR,1641164,Asia,453.76330458\r
-09/07/2020,9,7,2020,610,2,Bahrain,BH,BHR,1641164,Asia,448.52312139\r
-08/07/2020,8,7,2020,500,0,Bahrain,BH,BHR,1641164,Asia,442.30802041\r
-07/07/2020,7,7,2020,454,1,Bahrain,BH,BHR,1641164,Asia,451.75253661\r
-06/07/2020,6,7,2020,510,0,Bahrain,BH,BHR,1641164,Asia,463.26875315\r
-05/07/2020,5,7,2020,447,2,Bahrain,BH,BHR,1641164,Asia,458.57696123\r
-04/07/2020,4,7,2020,573,1,Bahrain,BH,BHR,1641164,Asia,456.62712563\r
-03/07/2020,3,7,2020,423,2,Bahrain,BH,BHR,1641164,Asia,451.32601008\r
-02/07/2020,2,7,2020,656,5,Bahrain,BH,BHR,1641164,Asia,454.12889876\r
-01/07/2020,1,7,2020,519,3,Bahrain,BH,BHR,1641164,Asia,439.01767282\r
-30/06/2020,30,6,2020,534,1,Bahrain,BH,BHR,1641164,Asia,440.29725244\r
-29/06/2020,29,6,2020,438,5,Bahrain,BH,BHR,1641164,Asia,436.33664887\r
-28/06/2020,28,6,2020,462,0,Bahrain,BH,BHR,1641164,Asia,428.96383299\r
-27/06/2020,27,6,2020,724,7,Bahrain,BH,BHR,1641164,Asia,432.13231584\r
-26/06/2020,26,6,2020,511,2,Bahrain,BH,BHR,1641164,Asia,451.75253661\r
-25/06/2020,25,6,2020,508,2,Bahrain,BH,BHR,1641164,Asia,420.61609931\r
-24/06/2020,24,6,2020,655,2,Bahrain,BH,BHR,1641164,Asia,418.11787244\r
-23/06/2020,23,6,2020,643,2,Bahrain,BH,BHR,1641164,Asia,425.91721485\r
-22/06/2020,22,6,2020,433,3,Bahrain,BH,BHR,1641164,Asia,426.58747084\r
-21/06/2020,21,6,2020,415,3,Bahrain,BH,BHR,1641164,Asia,423.35805562\r
-20/06/2020,20,6,2020,486,2,Bahrain,BH,BHR,1641164,Asia,431.46205986\r
-19/06/2020,19,6,2020,469,6,Bahrain,BH,BHR,1641164,Asia,434.69147508\r
-18/06/2020,18,6,2020,408,2,Bahrain,BH,BHR,1641164,Asia,435.42266343\r
-17/06/2020,17,6,2020,540,1,Bahrain,BH,BHR,1641164,Asia,441.27217024\r
-16/06/2020,16,6,2020,469,3,Bahrain,BH,BHR,1641164,Asia,439.26140227\r
-15/06/2020,15,6,2020,317,4,Bahrain,BH,BHR,1641164,Asia,435.42266343\r
-14/06/2020,14,6,2020,514,3,Bahrain,BH,BHR,1641164,Asia,452.97118387\r
-13/06/2020,13,6,2020,1046,2,Bahrain,BH,BHR,1641164,Asia,442.61268222\r
-12/06/2020,12,6,2020,0,2,Bahrain,BH,BHR,1641164,Asia,403.06757886\r
-11/06/2020,11,6,2020,467,3,Bahrain,BH,BHR,1641164,Asia,428.59823881\r
-10/06/2020,10,6,2020,783,2,Bahrain,BH,BHR,1641164,Asia,416.41176628\r
-09/06/2020,9,6,2020,654,1,Bahrain,BH,BHR,1641164,Asia,380.58353705\r
-08/06/2020,8,6,2020,380,2,Bahrain,BH,BHR,1641164,Asia,342.74453985\r
-07/06/2020,7,6,2020,548,1,Bahrain,BH,BHR,1641164,Asia,340.06351589\r
-06/06/2020,6,6,2020,539,2,Bahrain,BH,BHR,1641164,Asia,330.31433787\r
-05/06/2020,5,6,2020,481,1,Bahrain,BH,BHR,1641164,Asia,312.09556144\r
-04/06/2020,4,6,2020,504,1,Bahrain,BH,BHR,1641164,Asia,300.21375073\r
-03/06/2020,3,6,2020,507,0,Bahrain,BH,BHR,1641164,Asia,291.19576106\r
-02/06/2020,2,6,2020,406,0,Bahrain,BH,BHR,1641164,Asia,281.5075154\r
-01/06/2020,1,6,2020,605,2,Bahrain,BH,BHR,1641164,Asia,270.66155485\r
-31/05/2020,31,5,2020,344,2,Bahrain,BH,BHR,1641164,Asia,246.53233924\r
-30/05/2020,30,5,2020,397,0,Bahrain,BH,BHR,1641164,Asia,235.56451397\r
-29/05/2020,29,5,2020,419,0,Bahrain,BH,BHR,1641164,Asia,234.83332562\r
-28/05/2020,28,5,2020,267,1,Bahrain,BH,BHR,1641164,Asia,232.5788282\r
-27/05/2020,27,5,2020,195,0,Bahrain,BH,BHR,1641164,Asia,233.67561073\r
-26/05/2020,26,5,2020,33,0,Bahrain,BH,BHR,1641164,Asia,239.76884699\r
-25/05/2020,25,5,2020,336,1,Bahrain,BH,BHR,1641164,Asia,255.733126\r
-24/05/2020,24,5,2020,388,1,Bahrain,BH,BHR,1641164,Asia,245.43555671\r
-23/05/2020,23,5,2020,240,0,Bahrain,BH,BHR,1641164,Asia,241.90147968\r
-22/05/2020,22,5,2020,286,0,Bahrain,BH,BHR,1641164,Asia,242.20614149\r
-21/05/2020,21,5,2020,356,0,Bahrain,BH,BHR,1641164,Asia,240.92656188\r
-20/05/2020,20,5,2020,348,0,Bahrain,BH,BHR,1641164,Asia,232.27416638\r
-19/05/2020,19,5,2020,228,0,Bahrain,BH,BHR,1641164,Asia,222.464056\r
-18/05/2020,18,5,2020,209,0,Bahrain,BH,BHR,1641164,Asia,217.71133171\r
-17/05/2020,17,5,2020,164,0,Bahrain,BH,BHR,1641164,Asia,211.00877182\r
-16/05/2020,16,5,2020,385,2,Bahrain,BH,BHR,1641164,Asia,207.96215369\r
-15/05/2020,15,5,2020,382,0,Bahrain,BH,BHR,1641164,Asia,192.42440122\r
-14/05/2020,14,5,2020,285,1,Bahrain,BH,BHR,1641164,Asia,176.39918984\r
-13/05/2020,13,5,2020,295,1,Bahrain,BH,BHR,1641164,Asia,165.73602638\r
-12/05/2020,12,5,2020,295,0,Bahrain,BH,BHR,1641164,Asia,153.12302731\r
-11/05/2020,11,5,2020,167,0,Bahrain,BH,BHR,1641164,Asia,139.7788399\r
-10/05/2020,10,5,2020,330,0,Bahrain,BH,BHR,1641164,Asia,133.13721237\r
-09/05/2020,9,5,2020,245,0,Bahrain,BH,BHR,1641164,Asia,117.35573044\r
-08/05/2020,8,5,2020,265,0,Bahrain,BH,BHR,1641164,Asia,120.76794275\r
-07/05/2020,7,5,2020,214,0,Bahrain,BH,BHR,1641164,Asia,117.41666281\r
-06/05/2020,6,5,2020,187,0,Bahrain,BH,BHR,1641164,Asia,106.44883753\r
-05/05/2020,5,5,2020,150,0,Bahrain,BH,BHR,1641164,Asia,99.07602165\r
-04/05/2020,4,5,2020,99,0,Bahrain,BH,BHR,1641164,Asia,92.00786759\r
-03/05/2020,3,5,2020,114,0,Bahrain,BH,BHR,1641164,Asia,92.06879995\r
-02/05/2020,2,5,2020,130,0,Bahrain,BH,BHR,1641164,Asia,86.88954912\r
-01/05/2020,1,5,2020,119,0,Bahrain,BH,BHR,1641164,Asia,81.64936594\r
-30/04/2020,30,4,2020,110,0,Bahrain,BH,BHR,1641164,Asia,76.04358857\r
-29/04/2020,29,4,2020,88,0,Bahrain,BH,BHR,1641164,Asia,78.17622127\r
-28/04/2020,28,4,2020,76,0,Bahrain,BH,BHR,1641164,Asia,82.98987792\r
-27/04/2020,27,4,2020,58,0,Bahrain,BH,BHR,1641164,Asia,92.06879995\r
-26/04/2020,26,4,2020,71,0,Bahrain,BH,BHR,1641164,Asia,94.38422973\r
-25/04/2020,25,4,2020,301,0,Bahrain,BH,BHR,1641164,Asia,92.61719121\r
-24/04/2020,24,4,2020,210,1,Bahrain,BH,BHR,1641164,Asia,81.04004231\r
-23/04/2020,23,4,2020,34,0,Bahrain,BH,BHR,1641164,Asia,72.14391737\r
-22/04/2020,22,4,2020,66,0,Bahrain,BH,BHR,1641164,Asia,70.80340539\r
-21/04/2020,21,4,2020,34,0,Bahrain,BH,BHR,1641164,Asia,70.1331494\r
-20/04/2020,20,4,2020,100,0,Bahrain,BH,BHR,1641164,Asia,71.47366138\r
-19/04/2020,19,4,2020,29,0,Bahrain,BH,BHR,1641164,Asia,66.11161346\r
-18/04/2020,18,4,2020,44,0,Bahrain,BH,BHR,1641164,Asia,67.08653127\r
-17/04/2020,17,4,2020,27,0,Bahrain,BH,BHR,1641164,Asia,64.40550731\r
-16/04/2020,16,4,2020,145,0,Bahrain,BH,BHR,1641164,Asia,67.26932835\r
-15/04/2020,15,4,2020,167,0,Bahrain,BH,BHR,1641164,Asia,58.5560005\r
-14/04/2020,14,4,2020,225,1,Bahrain,BH,BHR,1641164,Asia,51.54877879\r
-13/04/2020,13,4,2020,96,0,Bahrain,BH,BHR,1641164,Asia,38.75298264\r
-12/04/2020,12,4,2020,42,0,Bahrain,BH,BHR,1641164,Asia,34.54864962\r
-11/04/2020,11,4,2020,111,1,Bahrain,BH,BHR,1641164,Asia,32.41601692\r
-10/04/2020,10,4,2020,64,0,Bahrain,BH,BHR,1641164,Asia,26.13998357\r
-09/04/2020,9,4,2020,12,0,Bahrain,BH,BHR,1641164,Asia,24.61667451\r
-08/04/2020,8,4,2020,55,1,Bahrain,BH,BHR,1641164,Asia,25.65252467\r
-07/04/2020,7,4,2020,56,0,Bahrain,BH,BHR,1641164,Asia,25.40879522\r
-06/04/2020,6,4,2020,12,0,Bahrain,BH,BHR,1641164,Asia,22.30124473\r
-05/04/2020,5,4,2020,45,0,Bahrain,BH,BHR,1641164,Asia,23.27616253\r
-04/04/2020,4,4,2020,0,0,Bahrain,BH,BHR,1641164,Asia,21.81378583\r
-03/04/2020,3,4,2020,74,0,Bahrain,BH,BHR,1641164,Asia,22.78870363\r
-02/04/2020,2,4,2020,2,0,Bahrain,BH,BHR,1641164,Asia,19.07182951\r
-01/04/2020,1,4,2020,52,0,Bahrain,BH,BHR,1641164,Asia,20.10767967\r
-31/03/2020,31,3,2020,15,0,Bahrain,BH,BHR,1641164,Asia,17.91411462\r
-30/03/2020,30,3,2020,27,0,Bahrain,BH,BHR,1641164,Asia,17.42665572\r
-29/03/2020,29,3,2020,7,0,Bahrain,BH,BHR,1641164,Asia,15.96427901\r
-28/03/2020,28,3,2020,8,0,Bahrain,BH,BHR,1641164,Asia,15.59868484\r
-27/03/2020,27,3,2020,39,1,Bahrain,BH,BHR,1641164,Asia,18.03597934\r
-26/03/2020,26,3,2020,29,0,Bahrain,BH,BHR,1641164,Asia,15.6596172\r
-25/03/2020,25,3,2020,51,1,Bahrain,BH,BHR,1641164,Asia,17.06106154\r
-24/03/2020,24,3,2020,5,0,Bahrain,BH,BHR,1641164,Asia,14.01444341\r
-23/03/2020,23,3,2020,28,1,Bahrain,BH,BHR,1641164,Asia,15.53775247\r
-22/03/2020,22,3,2020,21,0,Bahrain,BH,BHR,1641164,Asia,14.80656412\r
-21/03/2020,21,3,2020,16,0,Bahrain,BH,BHR,1641164,Asia,13.95351104\r
-20/03/2020,20,3,2020,13,0,Bahrain,BH,BHR,1641164,Asia,13.22232269\r
-19/03/2020,19,3,2020,19,0,Bahrain,BH,BHR,1641164,Asia,12.43020198\r
-18/03/2020,18,3,2020,16,0,Bahrain,BH,BHR,1641164,Asia,11.45528418\r
-17/03/2020,17,3,2020,7,1,Bahrain,BH,BHR,1641164,Asia,10.6022311\r
-16/03/2020,16,3,2020,3,0,Bahrain,BH,BHR,1641164,Asia,10.54129874\r
-15/03/2020,15,3,2020,1,0,Bahrain,BH,BHR,1641164,Asia,10.54129874\r
-14/03/2020,14,3,2020,48,0,Bahrain,BH,BHR,1641164,Asia,10.78502819\r
-13/03/2020,13,3,2020,0,0,Bahrain,BH,BHR,1641164,Asia,7.86027478\r
-12/03/2020,12,3,2020,52,0,Bahrain,BH,BHR,1641164,Asia,8.46959841\r
-11/03/2020,11,3,2020,1,0,Bahrain,BH,BHR,1641164,Asia,6.58069517\r
-10/03/2020,10,3,2020,30,0,Bahrain,BH,BHR,1641164,Asia,6.58069517\r
-09/03/2020,9,3,2020,16,0,Bahrain,BH,BHR,1641164,Asia,4.81365665\r
-08/03/2020,8,3,2020,7,0,Bahrain,BH,BHR,1641164,Asia,3.83873885\r
-07/03/2020,7,3,2020,4,0,Bahrain,BH,BHR,1641164,Asia,3.41221231\r
-06/03/2020,6,3,2020,0,0,Bahrain,BH,BHR,1641164,Asia,3.16848286\r
-05/03/2020,5,3,2020,3,0,Bahrain,BH,BHR,1641164,Asia,3.16848286\r
-04/03/2020,4,3,2020,2,0,Bahrain,BH,BHR,1641164,Asia,2.98568577\r
-02/03/2020,2,3,2020,6,0,Bahrain,BH,BHR,1641164,Asia,2.86382104\r
-01/03/2020,1,3,2020,3,0,Bahrain,BH,BHR,1641164,Asia,2.49822687\r
-29/02/2020,29,2,2020,5,0,Bahrain,BH,BHR,1641164,Asia,2.31542978\r
-28/02/2020,28,2,2020,0,0,Bahrain,BH,BHR,1641164,Asia,2.01076797\r
-27/02/2020,27,2,2020,10,0,Bahrain,BH,BHR,1641164,Asia,2.01076797\r
-26/02/2020,26,2,2020,21,0,Bahrain,BH,BHR,1641164,Asia,1.40144434\r
-25/02/2020,25,2,2020,1,0,Bahrain,BH,BHR,1641164,Asia,0.12186473\r
-24/02/2020,24,2,2020,1,0,Bahrain,BH,BHR,1641164,Asia,0.06093236\r
-23/02/2020,23,2,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-22/02/2020,22,2,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-21/02/2020,21,2,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-20/02/2020,20,2,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-19/02/2020,19,2,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-18/02/2020,18,2,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-17/02/2020,17,2,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-16/02/2020,16,2,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-15/02/2020,15,2,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-14/02/2020,14,2,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-13/02/2020,13,2,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-12/02/2020,12,2,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-11/02/2020,11,2,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-10/02/2020,10,2,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-09/02/2020,9,2,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-08/02/2020,8,2,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-07/02/2020,7,2,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-06/02/2020,6,2,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-05/02/2020,5,2,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-04/02/2020,4,2,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-03/02/2020,3,2,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-02/02/2020,2,2,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-01/02/2020,1,2,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-31/01/2020,31,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-30/01/2020,30,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-29/01/2020,29,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-28/01/2020,28,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-27/01/2020,27,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-26/01/2020,26,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-25/01/2020,25,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-24/01/2020,24,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-23/01/2020,23,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-22/01/2020,22,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-21/01/2020,21,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-20/01/2020,20,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-19/01/2020,19,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-18/01/2020,18,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-17/01/2020,17,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-16/01/2020,16,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-15/01/2020,15,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-14/01/2020,14,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-13/01/2020,13,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,0\r
-12/01/2020,12,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,\r
-11/01/2020,11,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,\r
-10/01/2020,10,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,\r
-09/01/2020,9,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,\r
-08/01/2020,8,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,\r
-07/01/2020,7,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,\r
-06/01/2020,6,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,\r
-05/01/2020,5,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,\r
-04/01/2020,4,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,\r
-03/01/2020,3,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,\r
-02/01/2020,2,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,\r
-01/01/2020,1,1,2020,0,0,Bahrain,BH,BHR,1641164,Asia,\r
-31/12/2019,31,12,2019,0,0,Bahrain,BH,BHR,1641164,Asia,\r
-19/08/2020,19,8,2020,3200,46,Bangladesh,BD,BGD,163046173,Asia,23.50499818\r
-18/08/2020,18,8,2020,2595,37,Bangladesh,BD,BGD,163046173,Asia,22.71871784\r
-17/08/2020,17,8,2020,2024,32,Bangladesh,BD,BGD,163046173,Asia,21.9588104\r
-16/08/2020,16,8,2020,2644,34,Bangladesh,BD,BGD,163046173,Asia,21.26084861\r
-15/08/2020,15,8,2020,2766,34,Bangladesh,BD,BGD,163046173,Asia,20.98791978\r
-14/08/2020,14,8,2020,2617,44,Bangladesh,BD,BGD,163046173,Asia,20.99159972\r
-13/08/2020,13,8,2020,2995,42,Bangladesh,BD,BGD,163046173,Asia,21.03943893\r
-12/08/2020,12,8,2020,2996,33,Bangladesh,BD,BGD,163046173,Asia,21.04802546\r
-11/08/2020,11,8,2020,2907,39,Bangladesh,BD,BGD,163046173,Asia,21.02594582\r
-10/08/2020,10,8,2020,2487,34,Bangladesh,BD,BGD,163046173,Asia,20.94314719\r
-09/08/2020,9,8,2020,2611,32,Bangladesh,BD,BGD,163046173,Asia,20.81312267\r
-08/08/2020,8,8,2020,2851,27,Bangladesh,BD,BGD,163046173,Asia,20.75731026\r
-07/08/2020,7,8,2020,2977,39,Bangladesh,BD,BGD,163046173,Asia,20.57147333\r
-06/08/2020,6,8,2020,2654,33,Bangladesh,BD,BGD,163046173,Asia,20.49726123\r
-05/08/2020,5,8,2020,1918,50,Bangladesh,BD,BGD,163046173,Asia,20.55246031\r
-04/08/2020,4,8,2020,1356,30,Bangladesh,BD,BGD,163046173,Asia,21.25103544\r
-03/08/2020,3,8,2020,886,22,Bangladesh,BD,BGD,163046173,Asia,22.2151795\r
-02/08/2020,2,8,2020,2199,21,Bangladesh,BD,BGD,163046173,Asia,23.17993689\r
-01/08/2020,1,8,2020,2772,28,Bangladesh,BD,BGD,163046173,Asia,23.49273172\r
-31/07/2020,31,7,2020,2695,48,Bangladesh,BD,BGD,163046173,Asia,23.6534224\r
-30/07/2020,30,7,2020,3009,35,Bangladesh,BD,BGD,163046173,Asia,23.67672868\r
-29/07/2020,29,7,2020,2960,35,Bangladesh,BD,BGD,163046173,Asia,23.99811003\r
-28/07/2020,28,7,2020,2772,37,Bangladesh,BD,BGD,163046173,Asia,24.12261464\r
-27/07/2020,27,7,2020,2275,54,Bangladesh,BD,BGD,163046173,Asia,24.32317133\r
-26/07/2020,26,7,2020,2520,38,Bangladesh,BD,BGD,163046173,Asia,24.5629807\r
-25/07/2020,25,7,2020,2548,35,Bangladesh,BD,BGD,163046173,Asia,24.66479235\r
-24/07/2020,24,7,2020,2856,50,Bangladesh,BD,BGD,163046173,Asia,24.91073495\r
-23/07/2020,23,7,2020,2744,42,Bangladesh,BD,BGD,163046173,Asia,25.21984984\r
-22/07/2020,22,7,2020,3057,41,Bangladesh,BD,BGD,163046173,Asia,25.67677562\r
-21/07/2020,21,7,2020,2928,50,Bangladesh,BD,BGD,163046173,Asia,25.65837593\r
-20/07/2020,20,7,2020,2459,37,Bangladesh,BD,BGD,163046173,Asia,25.82581316\r
-19/07/2020,19,7,2020,2709,34,Bangladesh,BD,BGD,163046173,Asia,25.99693033\r
-18/07/2020,18,7,2020,3034,51,Bangladesh,BD,BGD,163046173,Asia,26.35204446\r
-17/07/2020,17,7,2020,2733,39,Bangladesh,BD,BGD,163046173,Asia,26.40111032\r
-16/07/2020,16,7,2020,3533,33,Bangladesh,BD,BGD,163046173,Asia,27.18984395\r
-15/07/2020,15,7,2020,3163,33,Bangladesh,BD,BGD,163046173,Asia,27.33826816\r
-14/07/2020,14,7,2020,3099,39,Bangladesh,BD,BGD,163046173,Asia,27.6565829\r
-13/07/2020,13,7,2020,2666,47,Bangladesh,BD,BGD,163046173,Asia,28.21777362\r
-12/07/2020,12,7,2020,2686,30,Bangladesh,BD,BGD,163046173,Asia,28.91880204\r
-11/07/2020,11,7,2020,2949,37,Bangladesh,BD,BGD,163046173,Asia,29.42050041\r
-10/07/2020,10,7,2020,3360,41,Bangladesh,BD,BGD,163046173,Asia,29.98414443\r
-09/07/2020,9,7,2020,3489,46,Bangladesh,BD,BGD,163046173,Asia,30.34355182\r
-08/07/2020,8,7,2020,3027,55,Bangladesh,BD,BGD,163046173,Asia,30.3269921\r
-07/07/2020,7,7,2020,3201,44,Bangladesh,BD,BGD,163046173,Asia,30.56312153\r
-06/07/2020,6,7,2020,2738,55,Bangladesh,BD,BGD,163046173,Asia,30.7342387\r
-05/07/2020,5,7,2020,3288,29,Bangladesh,BD,BGD,163046173,Asia,31.22060399\r
-04/07/2020,4,7,2020,3114,42,Bangladesh,BD,BGD,163046173,Asia,31.19116448\r
-03/07/2020,3,7,2020,4019,38,Bangladesh,BD,BGD,163046173,Asia,31.27028317\r
-02/07/2020,2,7,2020,3775,41,Bangladesh,BD,BGD,163046173,Asia,31.13780536\r
-01/07/2020,1,7,2020,3682,64,Bangladesh,BD,BGD,163046173,Asia,31.28070967\r
-30/06/2020,30,6,2020,4014,45,Bangladesh,BD,BGD,163046173,Asia,31.39110784\r
-29/06/2020,29,6,2020,3809,43,Bangladesh,BD,BGD,163046173,Asia,30.82991712\r
-28/06/2020,28,6,2020,3504,34,Bangladesh,BD,BGD,163046173,Asia,30.42021722\r
-27/06/2020,27,6,2020,3868,40,Bangladesh,BD,BGD,163046173,Asia,30.02278379\r
-26/06/2020,26,6,2020,3946,39,Bangladesh,BD,BGD,163046173,Asia,29.77929448\r
-25/06/2020,25,6,2020,3462,37,Bangladesh,BD,BGD,163046173,Asia,29.31378218\r
-24/06/2020,24,6,2020,3412,43,Bangladesh,BD,BGD,163046173,Asia,29.14695827\r
-23/06/2020,23,6,2020,3480,38,Bangladesh,BD,BGD,163046173,Asia,28.99914738\r
-22/06/2020,22,6,2020,3531,39,Bangladesh,BD,BGD,163046173,Asia,28.5422216\r
-21/06/2020,21,6,2020,3240,37,Bangladesh,BD,BGD,163046173,Asia,28.05892292\r
-20/06/2020,20,6,2020,3243,45,Bangladesh,BD,BGD,163046173,Asia,27.68786238\r
-19/06/2020,19,6,2020,3803,38,Bangladesh,BD,BGD,163046173,Asia,27.43333326\r
-18/06/2020,18,6,2020,4008,43,Bangladesh,BD,BGD,163046173,Asia,26.58694724\r
-17/06/2020,17,6,2020,3862,53,Bangladesh,BD,BGD,163046173,Asia,25.78165389\r
-16/06/2020,16,6,2020,3099,38,Bangladesh,BD,BGD,163046173,Asia,25.19838353\r
-15/06/2020,15,6,2020,3141,32,Bangladesh,BD,BGD,163046173,Asia,24.75801747\r
-14/06/2020,14,6,2020,2856,44,Bangladesh,BD,BGD,163046173,Asia,24.39247685\r
-13/06/2020,13,6,2020,3471,46,Bangladesh,BD,BGD,163046173,Asia,23.72272792\r
-12/06/2020,12,6,2020,3187,37,Bangladesh,BD,BGD,163046173,Asia,23.14129753\r
-11/06/2020,11,6,2020,3190,37,Bangladesh,BD,BGD,163046173,Asia,22.43106927\r
-10/06/2020,10,6,2020,3171,45,Bangladesh,BD,BGD,163046173,Asia,21.41969931\r
-09/06/2020,9,6,2020,2735,42,Bangladesh,BD,BGD,163046173,Asia,20.18998631\r
-08/06/2020,8,6,2020,2743,42,Bangladesh,BD,BGD,163046173,Asia,19.72386068\r
-07/06/2020,7,6,2020,2635,35,Bangladesh,BD,BGD,163046173,Asia,18.98112629\r
-06/06/2020,6,6,2020,2828,30,Bangladesh,BD,BGD,163046173,Asia,18.51377401\r
-05/06/2020,5,6,2020,2423,35,Bangladesh,BD,BGD,163046173,Asia,17.8182655\r
-04/06/2020,4,6,2020,2695,37,Bangladesh,BD,BGD,163046173,Asia,17.41960543\r
-03/06/2020,3,6,2020,2911,37,Bangladesh,BD,BGD,163046173,Asia,16.75844302\r
-02/06/2020,2,6,2020,2381,22,Bangladesh,BD,BGD,163046173,Asia,15.74032651\r
-01/06/2020,1,6,2020,2545,40,Bangladesh,BD,BGD,163046173,Asia,15.26254774\r
-31/05/2020,31,5,2020,1764,28,Bangladesh,BD,BGD,163046173,Asia,14.48240064\r
-30/05/2020,30,5,2020,2523,23,Bangladesh,BD,BGD,163046173,Asia,13.97088909\r
-29/05/2020,29,5,2020,2029,15,Bangladesh,BD,BGD,163046173,Asia,13.16068915\r
-28/05/2020,28,5,2020,1541,22,Bangladesh,BD,BGD,163046173,Asia,12.55472583\r
-27/05/2020,27,5,2020,1166,21,Bangladesh,BD,BGD,163046173,Asia,12.32227634\r
-26/05/2020,26,5,2020,1975,21,Bangladesh,BD,BGD,163046173,Asia,12.20145167\r
-25/05/2020,25,5,2020,1532,28,Bangladesh,BD,BGD,163046173,Asia,11.62431454\r
-24/05/2020,24,5,2020,1873,20,Bangladesh,BD,BGD,163046173,Asia,11.22872108\r
-23/05/2020,23,5,2020,1694,24,Bangladesh,BD,BGD,163046173,Asia,10.47004029\r
-22/05/2020,22,5,2020,1773,22,Bangladesh,BD,BGD,163046173,Asia,9.86591694\r
-21/05/2020,21,5,2020,1617,16,Bangladesh,BD,BGD,163046173,Asia,9.21150109\r
-20/05/2020,20,5,2020,1251,21,Bangladesh,BD,BGD,163046173,Asia,8.7042828\r
-19/05/2020,19,5,2020,1602,21,Bangladesh,BD,BGD,163046173,Asia,8.41908752\r
-18/05/2020,18,5,2020,1273,14,Bangladesh,BD,BGD,163046173,Asia,7.85851012\r
-17/05/2020,17,5,2020,930,16,Bangladesh,BD,BGD,163046173,Asia,7.48560961\r
-16/05/2020,16,5,2020,1202,15,Bangladesh,BD,BGD,163046173,Asia,7.25377344\r
-15/05/2020,15,5,2020,1041,14,Bangladesh,BD,BGD,163046173,Asia,6.86676651\r
-14/05/2020,14,5,2020,1162,19,Bangladesh,BD,BGD,163046173,Asia,6.57421134\r
-13/05/2020,13,5,2020,969,11,Bangladesh,BD,BGD,163046173,Asia,6.25466996\r
-12/05/2020,12,5,2020,1034,11,Bangladesh,BD,BGD,163046173,Asia,5.99707422\r
-11/05/2020,11,5,2020,887,14,Bangladesh,BD,BGD,163046173,Asia,5.66771966\r
-10/05/2020,10,5,2020,636,8,Bangladesh,BD,BGD,163046173,Asia,5.38007108\r
-09/05/2020,9,5,2020,709,7,Bangladesh,BD,BGD,163046173,Asia,5.17951439\r
-08/05/2020,8,5,2020,706,13,Bangladesh,BD,BGD,163046173,Asia,5.05316982\r
-07/05/2020,7,5,2020,790,3,Bangladesh,BD,BGD,163046173,Asia,4.87407944\r
-06/05/2020,6,5,2020,786,1,Bangladesh,BD,BGD,163046173,Asia,4.62875016\r
-05/05/2020,5,5,2020,688,5,Bangladesh,BD,BGD,163046173,Asia,4.4128604\r
-04/05/2020,4,5,2020,665,2,Bangladesh,BD,BGD,163046173,Asia,4.29264905\r
-03/05/2020,3,5,2020,552,5,Bangladesh,BD,BGD,163046173,Asia,4.07614596\r
-02/05/2020,2,5,2020,571,2,Bangladesh,BD,BGD,163046173,Asia,3.92526846\r
-01/05/2020,1,5,2020,564,5,Bangladesh,BD,BGD,163046173,Asia,3.73820488\r
-30/04/2020,30,4,2020,641,8,Bangladesh,BD,BGD,163046173,Asia,3.60143381\r
-29/04/2020,29,4,2020,549,3,Bangladesh,BD,BGD,163046173,Asia,3.34261142\r
-28/04/2020,28,4,2020,497,7,Bangladesh,BD,BGD,163046173,Asia,3.13408153\r
-27/04/2020,27,4,2020,418,5,Bangladesh,BD,BGD,163046173,Asia,2.94088473\r
-26/04/2020,26,4,2020,309,9,Bangladesh,BD,BGD,163046173,Asia,2.76976756\r
-25/04/2020,25,4,2020,503,4,Bangladesh,BD,BGD,163046173,Asia,2.61582343\r
-24/04/2020,24,4,2020,414,7,Bangladesh,BD,BGD,163046173,Asia,2.36497425\r
-23/04/2020,23,4,2020,390,10,Bangladesh,BD,BGD,163046173,Asia,2.17975064\r
-22/04/2020,22,4,2020,434,9,Bangladesh,BD,BGD,163046173,Asia,1.97367405\r
-21/04/2020,21,4,2020,492,10,Bangladesh,BD,BGD,163046173,Asia,1.73263803\r
-20/04/2020,20,4,2020,312,7,Bangladesh,BD,BGD,163046173,Asia,1.45234933\r
-19/04/2020,19,4,2020,306,9,Bangladesh,BD,BGD,163046173,Asia,1.27203231\r
-18/04/2020,18,4,2020,266,15,Bangladesh,BD,BGD,163046173,Asia,1.08987532\r
-17/04/2020,17,4,2020,341,10,Bangladesh,BD,BGD,163046173,Asia,0.92979797\r
-16/04/2020,16,4,2020,219,4,Bangladesh,BD,BGD,163046173,Asia,0.7218814\r
-15/04/2020,15,4,2020,209,7,Bangladesh,BD,BGD,163046173,Asia,0.58940359\r
-14/04/2020,14,4,2020,182,5,Bangladesh,BD,BGD,163046173,Asia,0.46244569\r
-13/04/2020,13,4,2020,139,4,Bangladesh,BD,BGD,163046173,Asia,0.35082087\r
-12/04/2020,12,4,2020,58,3,Bangladesh,BD,BGD,163046173,Asia,0.26618227\r
-11/04/2020,11,4,2020,94,6,Bangladesh,BD,BGD,163046173,Asia,0.23060952\r
-10/04/2020,10,4,2020,112,1,Bangladesh,BD,BGD,163046173,Asia,0.17295714\r
-09/04/2020,9,4,2020,54,3,Bangladesh,BD,BGD,163046173,Asia,0.10978485\r
-08/04/2020,8,4,2020,41,5,Bangladesh,BD,BGD,163046173,Asia,0.0766654\r
-07/04/2020,7,4,2020,35,3,Bangladesh,BD,BGD,163046173,Asia,0.05519909\r
-06/04/2020,6,4,2020,18,1,Bangladesh,BD,BGD,163046173,Asia,0.03741271\r
-05/04/2020,5,4,2020,9,2,Bangladesh,BD,BGD,163046173,Asia,0.02821287\r
-04/04/2020,4,4,2020,5,0,Bangladesh,BD,BGD,163046173,Asia,0.02698622\r
-03/04/2020,3,4,2020,2,0,Bangladesh,BD,BGD,163046173,Asia,0.02821287\r
-02/04/2020,2,4,2020,3,1,Bangladesh,BD,BGD,163046173,Asia,0.02698622\r
-01/04/2020,1,4,2020,2,0,Bangladesh,BD,BGD,163046173,Asia,0.0263729\r
-31/03/2020,31,3,2020,0,0,Bangladesh,BD,BGD,163046173,Asia,0.02698622\r
-30/03/2020,30,3,2020,1,0,Bangladesh,BD,BGD,163046173,Asia,0.02821287\r
-29/03/2020,29,3,2020,0,0,Bangladesh,BD,BGD,163046173,Asia,0.02759954\r
-28/03/2020,28,3,2020,0,0,Bangladesh,BD,BGD,163046173,Asia,0.02943951\r
-27/03/2020,27,3,2020,9,0,Bangladesh,BD,BGD,163046173,Asia,\r
-26/03/2020,26,3,2020,0,1,Bangladesh,BD,BGD,163046173,Asia,\r
-25/03/2020,25,3,2020,6,1,Bangladesh,BD,BGD,163046173,Asia,\r
-24/03/2020,24,3,2020,6,0,Bangladesh,BD,BGD,163046173,Asia,\r
-23/03/2020,23,3,2020,3,1,Bangladesh,BD,BGD,163046173,Asia,\r
-22/03/2020,22,3,2020,7,2,Bangladesh,BD,BGD,163046173,Asia,\r
-21/03/2020,21,3,2020,7,0,Bangladesh,BD,BGD,163046173,Asia,\r
-20/03/2020,20,3,2020,0,0,Bangladesh,BD,BGD,163046173,Asia,\r
-19/03/2020,19,3,2020,2,0,Bangladesh,BD,BGD,163046173,Asia,\r
-18/03/2020,18,3,2020,3,0,Bangladesh,BD,BGD,163046173,Asia,\r
-17/03/2020,17,3,2020,2,0,Bangladesh,BD,BGD,163046173,Asia,\r
-15/03/2020,15,3,2020,0,0,Bangladesh,BD,BGD,163046173,Asia,\r
-09/03/2020,9,3,2020,3,0,Bangladesh,BD,BGD,163046173,Asia,\r
-19/08/2020,19,8,2020,1,0,Barbados,BB,BRB,287021,America,7.31653781\r
-18/08/2020,18,8,2020,1,0,Barbados,BB,BRB,287021,America,6.96813125\r
-17/08/2020,17,8,2020,1,0,Barbados,BB,BRB,287021,America,6.61972469\r
-16/08/2020,16,8,2020,2,0,Barbados,BB,BRB,287021,America,9.75538375\r
-15/08/2020,15,8,2020,4,0,Barbados,BB,BRB,287021,America,13.23944938\r
-14/08/2020,14,8,2020,1,0,Barbados,BB,BRB,287021,America,11.84582313\r
-13/08/2020,13,8,2020,0,0,Barbados,BB,BRB,287021,America,11.49741657\r
-12/08/2020,12,8,2020,0,0,Barbados,BB,BRB,287021,America,11.49741657\r
-11/08/2020,11,8,2020,1,0,Barbados,BB,BRB,287021,America,11.49741657\r
-10/08/2020,10,8,2020,4,0,Barbados,BB,BRB,287021,America,11.14901\r
-09/08/2020,9,8,2020,0,0,Barbados,BB,BRB,287021,America,10.45219688\r
-08/08/2020,8,8,2020,5,0,Barbados,BB,BRB,287021,America,10.45219688\r
-07/08/2020,7,8,2020,0,0,Barbados,BB,BRB,287021,America,9.40697719\r
-06/08/2020,6,8,2020,1,0,Barbados,BB,BRB,287021,America,9.40697719\r
-05/08/2020,5,8,2020,0,0,Barbados,BB,BRB,287021,America,9.05857063\r
-04/08/2020,4,8,2020,0,0,Barbados,BB,BRB,287021,America,9.05857063\r
-03/08/2020,3,8,2020,10,0,Barbados,BB,BRB,287021,America,9.40697719\r
-02/08/2020,2,8,2020,12,0,Barbados,BB,BRB,287021,America,6.27131813\r
-01/08/2020,1,8,2020,0,0,Barbados,BB,BRB,287021,America,2.09043938\r
-31/07/2020,31,7,2020,0,0,Barbados,BB,BRB,287021,America,2.09043938\r
-30/07/2020,30,7,2020,0,0,Barbados,BB,BRB,287021,America,2.09043938\r
-29/07/2020,29,7,2020,0,0,Barbados,BB,BRB,287021,America,2.43884594\r
-28/07/2020,28,7,2020,0,0,Barbados,BB,BRB,287021,America,2.43884594\r
-27/07/2020,27,7,2020,2,0,Barbados,BB,BRB,287021,America,2.43884594\r
-26/07/2020,26,7,2020,0,0,Barbados,BB,BRB,287021,America,1.74203281\r
-25/07/2020,25,7,2020,2,0,Barbados,BB,BRB,287021,America,3.48406563\r
-24/07/2020,24,7,2020,0,0,Barbados,BB,BRB,287021,America,2.7872525\r
-23/07/2020,23,7,2020,0,0,Barbados,BB,BRB,287021,America,2.7872525\r
-22/07/2020,22,7,2020,0,0,Barbados,BB,BRB,287021,America,2.7872525\r
-21/07/2020,21,7,2020,1,0,Barbados,BB,BRB,287021,America,2.7872525\r
-20/07/2020,20,7,2020,1,0,Barbados,BB,BRB,287021,America,2.43884594\r
-19/07/2020,19,7,2020,0,0,Barbados,BB,BRB,287021,America,2.43884594\r
-18/07/2020,18,7,2020,0,0,Barbados,BB,BRB,287021,America,2.43884594\r
-17/07/2020,17,7,2020,0,0,Barbados,BB,BRB,287021,America,2.43884594\r
-16/07/2020,16,7,2020,1,0,Barbados,BB,BRB,287021,America,2.43884594\r
-15/07/2020,15,7,2020,0,0,Barbados,BB,BRB,287021,America,2.09043938\r
-14/07/2020,14,7,2020,0,0,Barbados,BB,BRB,287021,America,2.09043938\r
-13/07/2020,13,7,2020,0,0,Barbados,BB,BRB,287021,America,2.09043938\r
-12/07/2020,12,7,2020,5,0,Barbados,BB,BRB,287021,America,2.09043938\r
-11/07/2020,11,7,2020,0,0,Barbados,BB,BRB,287021,America,0.34840656\r
-10/07/2020,10,7,2020,0,0,Barbados,BB,BRB,287021,America,0.34840656\r
-09/07/2020,9,7,2020,0,0,Barbados,BB,BRB,287021,America,0.34840656\r
-08/07/2020,8,7,2020,0,0,Barbados,BB,BRB,287021,America,0.34840656\r
-07/07/2020,7,7,2020,0,0,Barbados,BB,BRB,287021,America,0.34840656\r
-06/07/2020,6,7,2020,1,0,Barbados,BB,BRB,287021,America,0.34840656\r
-05/07/2020,5,7,2020,0,0,Barbados,BB,BRB,287021,America,0\r
-04/07/2020,4,7,2020,0,0,Barbados,BB,BRB,287021,America,0\r
-03/07/2020,3,7,2020,0,0,Barbados,BB,BRB,287021,America,0\r
-02/07/2020,2,7,2020,0,0,Barbados,BB,BRB,287021,America,0\r
-01/07/2020,1,7,2020,0,0,Barbados,BB,BRB,287021,America,0\r
-30/06/2020,30,6,2020,0,0,Barbados,BB,BRB,287021,America,0\r
-29/06/2020,29,6,2020,0,0,Barbados,BB,BRB,287021,America,0.34840656\r
-28/06/2020,28,6,2020,0,0,Barbados,BB,BRB,287021,America,0.34840656\r
-27/06/2020,27,6,2020,0,0,Barbados,BB,BRB,287021,America,0.34840656\r
-26/06/2020,26,6,2020,0,0,Barbados,BB,BRB,287021,America,0.34840656\r
-25/06/2020,25,6,2020,0,0,Barbados,BB,BRB,287021,America,0.34840656\r
-24/06/2020,24,6,2020,0,0,Barbados,BB,BRB,287021,America,1.74203281\r
-23/06/2020,23,6,2020,0,0,Barbados,BB,BRB,287021,America,1.74203281\r
-22/06/2020,22,6,2020,0,0,Barbados,BB,BRB,287021,America,1.74203281\r
-21/06/2020,21,6,2020,0,0,Barbados,BB,BRB,287021,America,1.74203281\r
-20/06/2020,20,6,2020,0,0,Barbados,BB,BRB,287021,America,1.74203281\r
-19/06/2020,19,6,2020,0,0,Barbados,BB,BRB,287021,America,1.74203281\r
-18/06/2020,18,6,2020,0,0,Barbados,BB,BRB,287021,America,1.74203281\r
-17/06/2020,17,6,2020,0,0,Barbados,BB,BRB,287021,America,1.74203281\r
-16/06/2020,16,6,2020,1,0,Barbados,BB,BRB,287021,America,1.74203281\r
-15/06/2020,15,6,2020,0,0,Barbados,BB,BRB,287021,America,1.39362625\r
-14/06/2020,14,6,2020,0,0,Barbados,BB,BRB,287021,America,1.39362625\r
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-12/06/2020,12,6,2020,0,0,Barbados,BB,BRB,287021,America,1.39362625\r
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-23/03/2020,23,3,2020,4,0,Bermuda,BM,BMU,62508,America,\r
-22/03/2020,22,3,2020,0,0,Bermuda,BM,BMU,62508,America,\r
-21/03/2020,21,3,2020,0,0,Bermuda,BM,BMU,62508,America,\r
-20/03/2020,20,3,2020,2,0,Bermuda,BM,BMU,62508,America,\r
-19/08/2020,19,8,2020,1,0,Bhutan,BT,BTN,763094,Asia,5.50390909\r
-18/08/2020,18,8,2020,5,0,Bhutan,BT,BTN,763094,Asia,5.63495454\r
-17/08/2020,17,8,2020,8,0,Bhutan,BT,BTN,763094,Asia,4.97972727\r
-16/08/2020,16,8,2020,0,0,Bhutan,BT,BTN,763094,Asia,4.06240909\r
-15/08/2020,15,8,2020,2,0,Bhutan,BT,BTN,763094,Asia,4.19345454\r
-14/08/2020,14,8,2020,3,0,Bhutan,BT,BTN,763094,Asia,3.93136363\r
-13/08/2020,13,8,2020,15,0,Bhutan,BT,BTN,763094,Asia,3.53822727\r
-12/08/2020,12,8,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.83463636\r
-11/08/2020,11,8,2020,3,0,Bhutan,BT,BTN,763094,Asia,1.83463636\r
-10/08/2020,10,8,2020,2,0,Bhutan,BT,BTN,763094,Asia,1.96568182\r
-09/08/2020,9,8,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.96568182\r
-08/08/2020,8,8,2020,0,0,Bhutan,BT,BTN,763094,Asia,2.09672727\r
-07/08/2020,7,8,2020,3,0,Bhutan,BT,BTN,763094,Asia,2.09672727\r
-06/08/2020,6,8,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.70359091\r
-05/08/2020,5,8,2020,2,0,Bhutan,BT,BTN,763094,Asia,1.70359091\r
-04/08/2020,4,8,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.70359091\r
-03/08/2020,3,8,2020,1,0,Bhutan,BT,BTN,763094,Asia,1.83463636\r
-02/08/2020,2,8,2020,1,0,Bhutan,BT,BTN,763094,Asia,1.96568182\r
-01/08/2020,1,8,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.83463636\r
-31/07/2020,31,7,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.96568182\r
-30/07/2020,30,7,2020,2,0,Bhutan,BT,BTN,763094,Asia,2.22777273\r
-29/07/2020,29,7,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.96568182\r
-28/07/2020,28,7,2020,4,0,Bhutan,BT,BTN,763094,Asia,1.96568182\r
-27/07/2020,27,7,2020,2,0,Bhutan,BT,BTN,763094,Asia,1.4415\r
-26/07/2020,26,7,2020,1,0,Bhutan,BT,BTN,763094,Asia,1.4415\r
-25/07/2020,25,7,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.31045454\r
-24/07/2020,24,7,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.57254545\r
-23/07/2020,23,7,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.57254545\r
-22/07/2020,22,7,2020,2,0,Bhutan,BT,BTN,763094,Asia,1.57254545\r
-21/07/2020,21,7,2020,1,0,Bhutan,BT,BTN,763094,Asia,1.31045454\r
-20/07/2020,20,7,2020,2,0,Bhutan,BT,BTN,763094,Asia,1.17940909\r
-19/07/2020,19,7,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.17940909\r
-18/07/2020,18,7,2020,1,0,Bhutan,BT,BTN,763094,Asia,1.17940909\r
-17/07/2020,17,7,2020,2,0,Bhutan,BT,BTN,763094,Asia,1.17940909\r
-16/07/2020,16,7,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.91731818\r
-15/07/2020,15,7,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.91731818\r
-14/07/2020,14,7,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.91731818\r
-13/07/2020,13,7,2020,2,0,Bhutan,BT,BTN,763094,Asia,1.04836364\r
-12/07/2020,12,7,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.78627273\r
-11/07/2020,11,7,2020,2,0,Bhutan,BT,BTN,763094,Asia,0.91731818\r
-10/07/2020,10,7,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.31045454\r
-09/07/2020,9,7,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.31045454\r
-08/07/2020,8,7,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.31045454\r
-07/07/2020,7,7,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.4415\r
-06/07/2020,6,7,2020,2,0,Bhutan,BT,BTN,763094,Asia,1.57254545\r
-05/07/2020,5,7,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.31045454\r
-04/07/2020,4,7,2020,1,0,Bhutan,BT,BTN,763094,Asia,1.31045454\r
-03/07/2020,3,7,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.31045454\r
-02/07/2020,2,7,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.31045454\r
-01/07/2020,1,7,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.31045454\r
-30/06/2020,30,6,2020,1,0,Bhutan,BT,BTN,763094,Asia,1.31045454\r
-29/06/2020,29,6,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.31045454\r
-28/06/2020,28,6,2020,1,0,Bhutan,BT,BTN,763094,Asia,1.31045454\r
-27/06/2020,27,6,2020,5,0,Bhutan,BT,BTN,763094,Asia,1.70359091\r
-26/06/2020,26,6,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.04836364\r
-25/06/2020,25,6,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.04836364\r
-24/06/2020,24,6,2020,1,0,Bhutan,BT,BTN,763094,Asia,1.4415\r
-23/06/2020,23,6,2020,1,0,Bhutan,BT,BTN,763094,Asia,1.31045454\r
-22/06/2020,22,6,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.17940909\r
-21/06/2020,21,6,2020,0,0,Bhutan,BT,BTN,763094,Asia,2.62090909\r
-20/06/2020,20,6,2020,1,0,Bhutan,BT,BTN,763094,Asia,2.62090909\r
-19/06/2020,19,6,2020,0,0,Bhutan,BT,BTN,763094,Asia,2.48986363\r
-18/06/2020,18,6,2020,0,0,Bhutan,BT,BTN,763094,Asia,2.62090909\r
-17/06/2020,17,6,2020,0,0,Bhutan,BT,BTN,763094,Asia,2.62090909\r
-16/06/2020,16,6,2020,1,0,Bhutan,BT,BTN,763094,Asia,2.62090909\r
-15/06/2020,15,6,2020,0,0,Bhutan,BT,BTN,763094,Asia,3.01404545\r
-14/06/2020,14,6,2020,4,0,Bhutan,BT,BTN,763094,Asia,3.01404545\r
-13/06/2020,13,6,2020,0,0,Bhutan,BT,BTN,763094,Asia,3.80031818\r
-12/06/2020,12,6,2020,0,0,Bhutan,BT,BTN,763094,Asia,4.06240909\r
-11/06/2020,11,6,2020,3,0,Bhutan,BT,BTN,763094,Asia,4.45554545\r
-10/06/2020,10,6,2020,0,0,Bhutan,BT,BTN,763094,Asia,4.19345454\r
-09/06/2020,9,6,2020,0,0,Bhutan,BT,BTN,763094,Asia,4.19345454\r
-08/06/2020,8,6,2020,11,0,Bhutan,BT,BTN,763094,Asia,4.19345454\r
-07/06/2020,7,6,2020,0,0,Bhutan,BT,BTN,763094,Asia,3.14509091\r
-06/06/2020,6,6,2020,0,0,Bhutan,BT,BTN,763094,Asia,3.14509091\r
-05/06/2020,5,6,2020,1,0,Bhutan,BT,BTN,763094,Asia,3.53822727\r
-04/06/2020,4,6,2020,0,0,Bhutan,BT,BTN,763094,Asia,3.40718182\r
-03/06/2020,3,6,2020,0,0,Bhutan,BT,BTN,763094,Asia,3.40718182\r
-02/06/2020,2,6,2020,4,0,Bhutan,BT,BTN,763094,Asia,3.40718182\r
-01/06/2020,1,6,2020,0,0,Bhutan,BT,BTN,763094,Asia,2.883\r
-31/05/2020,31,5,2020,10,0,Bhutan,BT,BTN,763094,Asia,2.883\r
-30/05/2020,30,5,2020,2,0,Bhutan,BT,BTN,763094,Asia,1.57254545\r
-29/05/2020,29,5,2020,3,0,Bhutan,BT,BTN,763094,Asia,1.4415\r
-28/05/2020,28,5,2020,1,0,Bhutan,BT,BTN,763094,Asia,1.70359091\r
-27/05/2020,27,5,2020,0,0,Bhutan,BT,BTN,763094,Asia,2.09672727\r
-26/05/2020,26,5,2020,0,0,Bhutan,BT,BTN,763094,Asia,2.09672727\r
-25/05/2020,25,5,2020,3,0,Bhutan,BT,BTN,763094,Asia,2.35881818\r
-24/05/2020,24,5,2020,0,0,Bhutan,BT,BTN,763094,Asia,2.22777273\r
-23/05/2020,23,5,2020,3,0,Bhutan,BT,BTN,763094,Asia,2.22777273\r
-22/05/2020,22,5,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.83463636\r
-21/05/2020,21,5,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.83463636\r
-20/05/2020,20,5,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.83463636\r
-19/05/2020,19,5,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.83463636\r
-18/05/2020,18,5,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.83463636\r
-17/05/2020,17,5,2020,0,0,Bhutan,BT,BTN,763094,Asia,1.83463636\r
-16/05/2020,16,5,2020,1,0,Bhutan,BT,BTN,763094,Asia,1.83463636\r
-15/05/2020,15,5,2020,5,0,Bhutan,BT,BTN,763094,Asia,1.70359091\r
-14/05/2020,14,5,2020,4,0,Bhutan,BT,BTN,763094,Asia,1.04836364\r
-13/05/2020,13,5,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.52418182\r
-12/05/2020,12,5,2020,2,0,Bhutan,BT,BTN,763094,Asia,0.52418182\r
-11/05/2020,11,5,2020,2,0,Bhutan,BT,BTN,763094,Asia,0.26209091\r
-10/05/2020,10,5,2020,0,0,Bhutan,BT,BTN,763094,Asia,0\r
-09/05/2020,9,5,2020,0,0,Bhutan,BT,BTN,763094,Asia,0\r
-08/05/2020,8,5,2020,0,0,Bhutan,BT,BTN,763094,Asia,0\r
-07/05/2020,7,5,2020,0,0,Bhutan,BT,BTN,763094,Asia,0\r
-06/05/2020,6,5,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.13104545\r
-05/05/2020,5,5,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.13104545\r
-04/05/2020,4,5,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.26209091\r
-03/05/2020,3,5,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.26209091\r
-02/05/2020,2,5,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.26209091\r
-01/05/2020,1,5,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.26209091\r
-30/04/2020,30,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.26209091\r
-29/04/2020,29,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.26209091\r
-28/04/2020,28,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.26209091\r
-27/04/2020,27,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.26209091\r
-26/04/2020,26,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.26209091\r
-25/04/2020,25,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.26209091\r
-24/04/2020,24,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.26209091\r
-23/04/2020,23,4,2020,1,0,Bhutan,BT,BTN,763094,Asia,0.26209091\r
-22/04/2020,22,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.13104545\r
-21/04/2020,21,4,2020,1,0,Bhutan,BT,BTN,763094,Asia,0.13104545\r
-20/04/2020,20,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0\r
-19/04/2020,19,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0\r
-18/04/2020,18,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0\r
-17/04/2020,17,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0\r
-16/04/2020,16,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0\r
-15/04/2020,15,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.13104545\r
-14/04/2020,14,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.13104545\r
-13/04/2020,13,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.13104545\r
-12/04/2020,12,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.13104545\r
-11/04/2020,11,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.26209091\r
-10/04/2020,10,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.26209091\r
-09/04/2020,9,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.26209091\r
-08/04/2020,8,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.39313636\r
-07/04/2020,7,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.39313636\r
-06/04/2020,6,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.39313636\r
-05/04/2020,5,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.39313636\r
-04/04/2020,4,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.39313636\r
-03/04/2020,3,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.52418182\r
-02/04/2020,2,4,2020,1,0,Bhutan,BT,BTN,763094,Asia,0.52418182\r
-01/04/2020,1,4,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.39313636\r
-31/03/2020,31,3,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.39313636\r
-30/03/2020,30,3,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.39313636\r
-29/03/2020,29,3,2020,1,0,Bhutan,BT,BTN,763094,Asia,0.39313636\r
-28/03/2020,28,3,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.26209091\r
-27/03/2020,27,3,2020,0,0,Bhutan,BT,BTN,763094,Asia,0.39313636\r
-26/03/2020,26,3,2020,1,0,Bhutan,BT,BTN,763094,Asia,\r
-25/03/2020,25,3,2020,0,0,Bhutan,BT,BTN,763094,Asia,\r
-24/03/2020,24,3,2020,0,0,Bhutan,BT,BTN,763094,Asia,\r
-23/03/2020,23,3,2020,0,0,Bhutan,BT,BTN,763094,Asia,\r
-22/03/2020,22,3,2020,0,0,Bhutan,BT,BTN,763094,Asia,\r
-21/03/2020,21,3,2020,1,0,Bhutan,BT,BTN,763094,Asia,\r
-20/03/2020,20,3,2020,0,0,Bhutan,BT,BTN,763094,Asia,\r
-19/03/2020,19,3,2020,0,0,Bhutan,BT,BTN,763094,Asia,\r
-18/03/2020,18,3,2020,0,0,Bhutan,BT,BTN,763094,Asia,\r
-17/03/2020,17,3,2020,0,0,Bhutan,BT,BTN,763094,Asia,\r
-15/03/2020,15,3,2020,0,0,Bhutan,BT,BTN,763094,Asia,\r
-13/03/2020,13,3,2020,0,0,Bhutan,BT,BTN,763094,Asia,\r
-06/03/2020,6,3,2020,1,0,Bhutan,BT,BTN,763094,Asia,\r
-19/08/2020,19,8,2020,1796,49,Bolivia,BO,BOL,11513102,America,170.74460037\r
-18/08/2020,18,8,2020,879,75,Bolivia,BO,BOL,11513102,America,168.30390281\r
-17/08/2020,17,8,2020,1198,45,Bolivia,BO,BOL,11513102,America,175.37410856\r
-16/08/2020,16,8,2020,2687,119,Bolivia,BO,BOL,11513102,America,176.7812011\r
-15/08/2020,15,8,2020,1388,57,Bolivia,BO,BOL,11513102,America,170.84882945\r
-14/08/2020,14,8,2020,0,0,Bolivia,BO,BOL,11513102,America,172.29935077\r
-13/08/2020,13,8,2020,1743,66,Bolivia,BO,BOL,11513102,America,187.06513675\r
-12/08/2020,12,8,2020,1693,49,Bolivia,BO,BOL,11513102,America,182.40957129\r
-11/08/2020,11,8,2020,1636,72,Bolivia,BO,BOL,11513102,America,172.18643594\r
-10/08/2020,10,8,2020,944,53,Bolivia,BO,BOL,11513102,America,178.66601026\r
-09/08/2020,9,8,2020,1164,63,Bolivia,BO,BOL,11513102,America,180.43790457\r
-08/08/2020,8,8,2020,1468,59,Bolivia,BO,BOL,11513102,America,186.17918959\r
-07/08/2020,7,8,2020,1282,80,Bolivia,BO,BOL,11513102,America,183.88614988\r
-06/08/2020,6,8,2020,1780,65,Bolivia,BO,BOL,11513102,America,182.45300007\r
-05/08/2020,5,8,2020,1515,92,Bolivia,BO,BOL,11513102,America,182.43562856\r
-04/08/2020,4,8,2020,1693,75,Bolivia,BO,BOL,11513102,America,181.14145084\r
-03/08/2020,3,8,2020,1360,89,Bolivia,BO,BOL,11513102,America,178.67469601\r
-02/08/2020,2,8,2020,2004,87,Bolivia,BO,BOL,11513102,America,179.40429955\r
-01/08/2020,1,8,2020,1555,83,Bolivia,BO,BOL,11513102,America,179.68224376\r
-31/07/2020,31,7,2020,1700,86,Bolivia,BO,BOL,11513102,America,183.07837453\r
-30/07/2020,30,7,2020,1207,88,Bolivia,BO,BOL,11513102,America,185.14558457\r
-29/07/2020,29,7,2020,516,73,Bolivia,BO,BOL,11513102,America,186.3963335\r
-28/07/2020,28,7,2020,2382,64,Bolivia,BO,BOL,11513102,America,195.95935135\r
-27/07/2020,27,7,2020,1148,48,Bolivia,BO,BOL,11513102,America,184.50283859\r
-26/07/2020,26,7,2020,1825,62,Bolivia,BO,BOL,11513102,America,183.1044318\r
-25/07/2020,25,7,2020,1204,66,Bolivia,BO,BOL,11513102,America,181.45413808\r
-24/07/2020,24,7,2020,1117,79,Bolivia,BO,BOL,11513102,America,183.60820568\r
-23/07/2020,23,7,2020,1778,55,Bolivia,BO,BOL,11513102,America,183.71243475\r
-22/07/2020,22,7,2020,1366,55,Bolivia,BO,BOL,11513102,America,180.76796332\r
-21/07/2020,21,7,2020,1409,67,Bolivia,BO,BOL,11513102,America,177.90166369\r
-20/07/2020,20,7,2020,1444,45,Bolivia,BO,BOL,11513102,America,176.19056967\r
-19/07/2020,19,7,2020,2036,57,Bolivia,BO,BOL,11513102,America,174.29707476\r
-18/07/2020,18,7,2020,1946,65,Bolivia,BO,BOL,11513102,America,167.49612746\r
-17/07/2020,17,7,2020,1938,42,Bolivia,BO,BOL,11513102,America,161.79827122\r
-16/07/2020,16,7,2020,1351,44,Bolivia,BO,BOL,11513102,America,156.26544436\r
-15/07/2020,15,7,2020,1617,32,Bolivia,BO,BOL,11513102,America,153.2862299\r
-14/07/2020,14,7,2020,1063,59,Bolivia,BO,BOL,11513102,America,148.74357927\r
-13/07/2020,13,7,2020,987,53,Bolivia,BO,BOL,11513102,America,144.73075979\r
-12/07/2020,12,7,2020,1635,52,Bolivia,BO,BOL,11513102,America,143.52343964\r
-11/07/2020,11,7,2020,1452,64,Bolivia,BO,BOL,11513102,America,140.20548068\r
-10/07/2020,10,7,2020,1129,61,Bolivia,BO,BOL,11513102,America,135.58465824\r
-09/07/2020,9,7,2020,1439,47,Bolivia,BO,BOL,11513102,America,134.60316776\r
-08/07/2020,8,7,2020,1036,54,Bolivia,BO,BOL,11513102,America,131.64132481\r
-07/07/2020,7,7,2020,1212,42,Bolivia,BO,BOL,11513102,America,130.42531891\r
-06/07/2020,6,7,2020,1226,56,Bolivia,BO,BOL,11513102,America,129.49594297\r
-05/07/2020,5,7,2020,1253,58,Bolivia,BO,BOL,11513102,America,126.45592821\r
-04/07/2020,4,7,2020,1290,49,Bolivia,BO,BOL,11513102,America,124.57111906\r
-03/07/2020,3,7,2020,1301,70,Bolivia,BO,BOL,11513102,America,121.85247729\r
-02/07/2020,2,7,2020,1008,78,Bolivia,BO,BOL,11513102,America,117.6225139\r
-01/07/2020,1,7,2020,1094,52,Bolivia,BO,BOL,11513102,America,115.83324807\r
-30/06/2020,30,6,2020,601,57,Bolivia,BO,BOL,11513102,America,113.36649324\r
-29/06/2020,29,6,2020,848,44,Bolivia,BO,BOL,11513102,America,113.47940807\r
-28/06/2020,28,6,2020,1253,36,Bolivia,BO,BOL,11513102,America,111.47299833\r
-27/06/2020,27,6,2020,920,21,Bolivia,BO,BOL,11513102,America,108.51984113\r
-26/06/2020,26,6,2020,1016,37,Bolivia,BO,BOL,11513102,America,107.16486313\r
-25/06/2020,25,6,2020,1098,30,Bolivia,BO,BOL,11513102,America,106.01834328\r
-24/06/2020,24,6,2020,896,26,Bolivia,BO,BOL,11513102,America,102.01420955\r
-23/06/2020,23,6,2020,1105,47,Bolivia,BO,BOL,11513102,America,100.2683725\r
-22/06/2020,22,6,2020,876,33,Bolivia,BO,BOL,11513102,America,93.3284531\r
-21/06/2020,21,6,2020,1036,25,Bolivia,BO,BOL,11513102,America,88.19517103\r
-20/06/2020,20,6,2020,977,18,Bolivia,BO,BOL,11513102,America,84.66875391\r
-19/06/2020,19,6,2020,814,18,Bolivia,BO,BOL,11513102,America,80.37799022\r
-18/06/2020,18,6,2020,802,20,Bolivia,BO,BOL,11513102,America,78.58003864\r
-17/06/2020,17,6,2020,810,27,Bolivia,BO,BOL,11513102,America,77.23374639\r
-16/06/2020,16,6,2020,614,21,Bolivia,BO,BOL,11513102,America,74.19373163\r
-15/06/2020,15,6,2020,617,26,Bolivia,BO,BOL,11513102,America,73.62915746\r
-14/06/2020,14,6,2020,913,26,Bolivia,BO,BOL,11513102,America,71.65749074\r
-13/06/2020,13,6,2020,764,26,Bolivia,BO,BOL,11513102,America,71.20583141\r
-12/06/2020,12,6,2020,884,21,Bolivia,BO,BOL,11513102,America,67.5578137\r
-11/06/2020,11,6,2020,637,25,Bolivia,BO,BOL,11513102,America,65.25608824\r
-10/06/2020,10,6,2020,695,12,Bolivia,BO,BOL,11513102,America,65.21265946\r
-09/06/2020,9,6,2020,306,10,Bolivia,BO,BOL,11513102,America,63.31047879\r
-08/06/2020,8,6,2020,285,11,Bolivia,BO,BOL,11513102,America,64.10088263\r
-07/06/2020,7,6,2020,630,27,Bolivia,BO,BOL,11513102,America,64.64808529\r
-06/06/2020,6,6,2020,483,12,Bolivia,BO,BOL,11513102,America,62.09447289\r
-05/06/2020,5,6,2020,607,15,Bolivia,BO,BOL,11513102,America,61.30406905\r
-04/06/2020,4,6,2020,647,24,Bolivia,BO,BOL,11513102,America,58.35959761\r
-03/06/2020,3,6,2020,460,33,Bolivia,BO,BOL,11513102,America,56.54427451\r
-02/06/2020,2,6,2020,549,30,Bolivia,BO,BOL,11513102,America,54.44232145\r
-01/06/2020,1,6,2020,390,3,Bolivia,BO,BOL,11513102,America,51.19384854\r
-31/05/2020,31,5,2020,861,10,Bolivia,BO,BOL,11513102,America,50.08207171\r
-30/05/2020,30,5,2020,344,7,Bolivia,BO,BOL,11513102,America,44.76638876\r
-29/05/2020,29,5,2020,619,13,Bolivia,BO,BOL,11513102,America,43.55906862\r
-28/05/2020,28,5,2020,632,6,Bolivia,BO,BOL,11513102,America,40.12819482\r
-27/05/2020,27,5,2020,476,13,Bolivia,BO,BOL,11513102,America,36.23697593\r
-26/05/2020,26,5,2020,397,11,Bolivia,BO,BOL,11513102,America,33.25776146\r
-25/05/2020,25,5,2020,348,10,Bolivia,BO,BOL,11513102,America,32.19809917\r
-24/05/2020,24,5,2020,336,10,Bolivia,BO,BOL,11513102,America,30.20906095\r
-23/05/2020,23,5,2020,392,15,Bolivia,BO,BOL,11513102,America,28.77591113\r
-22/05/2020,22,5,2020,268,16,Bolivia,BO,BOL,11513102,America,26.97795955\r
-21/05/2020,21,5,2020,438,10,Bolivia,BO,BOL,11513102,America,26.34389932\r
-20/05/2020,20,5,2020,218,15,Bolivia,BO,BOL,11513102,America,23.26914154\r
-19/05/2020,19,5,2020,175,5,Bolivia,BO,BOL,11513102,America,22.42662316\r
-18/05/2020,18,5,2020,262,4,Bolivia,BO,BOL,11513102,America,21.6622766\r
-17/05/2020,17,5,2020,249,1,Bolivia,BO,BOL,11513102,America,20.46364221\r
-16/05/2020,16,5,2020,205,12,Bolivia,BO,BOL,11513102,America,20.39415615\r
-15/05/2020,15,5,2020,224,10,Bolivia,BO,BOL,11513102,America,19.15209298\r
-14/05/2020,14,5,2020,184,14,Bolivia,BO,BOL,11513102,America,17.70157165\r
-13/05/2020,13,5,2020,133,6,Bolivia,BO,BOL,11513102,America,16.59848058\r
-12/05/2020,12,5,2020,275,4,Bolivia,BO,BOL,11513102,America,15.78201948\r
-11/05/2020,11,5,2020,119,4,Bolivia,BO,BOL,11513102,America,13.94932486\r
-10/05/2020,10,5,2020,171,8,Bolivia,BO,BOL,11513102,America,13.64532339\r
-09/05/2020,9,5,2020,185,4,Bolivia,BO,BOL,11513102,America,12.67251867\r
-08/05/2020,8,5,2020,195,11,Bolivia,BO,BOL,11513102,America,11.96897239\r
-07/05/2020,7,5,2020,84,5,Bolivia,BO,BOL,11513102,America,10.54450833\r
-06/05/2020,6,5,2020,121,4,Bolivia,BO,BOL,11513102,America,10.36210745\r
-05/05/2020,5,5,2020,87,6,Bolivia,BO,BOL,11513102,America,9.40667424\r
-04/05/2020,4,5,2020,124,5,Bolivia,BO,BOL,11513102,America,8.94632915\r
-03/05/2020,3,5,2020,241,5,Bolivia,BO,BOL,11513102,America,8.25146863\r
-02/05/2020,2,5,2020,62,4,Bolivia,BO,BOL,11513102,America,6.39271675\r
-01/05/2020,1,5,2020,57,3,Bolivia,BO,BOL,11513102,America,6.09740103\r
-30/04/2020,30,4,2020,57,4,Bolivia,BO,BOL,11513102,America,5.81077107\r
-29/04/2020,29,4,2020,39,2,Bolivia,BO,BOL,11513102,America,5.69785623\r
-28/04/2020,28,4,2020,64,3,Bolivia,BO,BOL,11513102,America,5.73259926\r
-27/04/2020,27,4,2020,84,4,Bolivia,BO,BOL,11513102,America,5.385169\r
-26/04/2020,26,4,2020,59,2,Bolivia,BO,BOL,11513102,America,4.91613815\r
-25/04/2020,25,4,2020,104,1,Bolivia,BO,BOL,11513102,America,4.61213668\r
-24/04/2020,24,4,2020,31,3,Bolivia,BO,BOL,11513102,America,3.77830406\r
-23/04/2020,23,4,2020,63,3,Bolivia,BO,BOL,11513102,America,3.54378863\r
-22/04/2020,22,4,2020,11,3,Bolivia,BO,BOL,11513102,America,3.46561683\r
-21/04/2020,21,4,2020,34,1,Bolivia,BO,BOL,11513102,America,3.50904561\r
-20/04/2020,20,4,2020,44,1,Bolivia,BO,BOL,11513102,America,3.30927321\r
-19/04/2020,19,4,2020,27,1,Bolivia,BO,BOL,11513102,America,3.15292959\r
-18/04/2020,18,4,2020,28,0,Bolivia,BO,BOL,11513102,America,3.07475778\r
-17/04/2020,17,4,2020,24,2,Bolivia,BO,BOL,11513102,America,2.8923569\r
-16/04/2020,16,4,2020,44,1,Bolivia,BO,BOL,11513102,America,2.76207055\r
-15/04/2020,15,4,2020,43,0,Bolivia,BO,BOL,11513102,America,2.44938332\r
-14/04/2020,14,4,2020,24,1,Bolivia,BO,BOL,11513102,America,2.14538184\r
-13/04/2020,13,4,2020,30,3,Bolivia,BO,BOL,11513102,America,2.03246701\r
-12/04/2020,12,4,2020,24,4,Bolivia,BO,BOL,11513102,America,1.90218066\r
-11/04/2020,11,4,2020,8,1,Bolivia,BO,BOL,11513102,America,1.7545228\r
-10/04/2020,10,4,2020,4,1,Bolivia,BO,BOL,11513102,America,1.79795159\r
-09/04/2020,9,4,2020,54,3,Bolivia,BO,BOL,11513102,America,1.9542952\r
-08/04/2020,8,4,2020,16,1,Bolivia,BO,BOL,11513102,America,1.54606465\r
-07/04/2020,7,4,2020,11,3,Bolivia,BO,BOL,11513102,America,1.44183557\r
-06/04/2020,6,4,2020,26,1,Bolivia,BO,BOL,11513102,America,1.35497801\r
-05/04/2020,5,4,2020,18,0,Bolivia,BO,BOL,11513102,America,1.18994863\r
-04/04/2020,4,4,2020,7,1,Bolivia,BO,BOL,11513102,America,1.04229077\r
-03/04/2020,3,4,2020,9,1,Bolivia,BO,BOL,11513102,America,1.01623351\r
-02/04/2020,2,4,2020,8,1,Bolivia,BO,BOL,11513102,America,0.96411897\r
-01/04/2020,1,4,2020,8,1,Bolivia,BO,BOL,11513102,America,0.89463291\r
-31/03/2020,31,3,2020,11,3,Bolivia,BO,BOL,11513102,America,0.83383262\r
-30/03/2020,30,3,2020,15,3,Bolivia,BO,BOL,11513102,America,0.74697506\r
-29/03/2020,29,3,2020,7,0,Bolivia,BO,BOL,11513102,America,0.61668871\r
-28/03/2020,28,3,2020,13,0,Bolivia,BO,BOL,11513102,America,0.61668871\r
-27/03/2020,27,3,2020,22,0,Bolivia,BO,BOL,11513102,America,0.51245963\r
-26/03/2020,26,3,2020,7,0,Bolivia,BO,BOL,11513102,America,0.3387445\r
-25/03/2020,25,3,2020,4,0,Bolivia,BO,BOL,11513102,America,\r
-24/03/2020,24,3,2020,1,0,Bolivia,BO,BOL,11513102,America,\r
-23/03/2020,23,3,2020,7,0,Bolivia,BO,BOL,11513102,America,\r
-22/03/2020,22,3,2020,1,0,Bolivia,BO,BOL,11513102,America,\r
-21/03/2020,21,3,2020,4,0,Bolivia,BO,BOL,11513102,America,\r
-20/03/2020,20,3,2020,3,0,Bolivia,BO,BOL,11513102,America,\r
-19/03/2020,19,3,2020,0,0,Bolivia,BO,BOL,11513102,America,\r
-18/03/2020,18,3,2020,1,0,Bolivia,BO,BOL,11513102,America,\r
-17/03/2020,17,3,2020,1,0,Bolivia,BO,BOL,11513102,America,\r
-15/03/2020,15,3,2020,0,0,Bolivia,BO,BOL,11513102,America,\r
-14/03/2020,14,3,2020,7,0,Bolivia,BO,BOL,11513102,America,\r
-13/03/2020,13,3,2020,1,0,Bolivia,BO,BOL,11513102,America,\r
-12/03/2020,12,3,2020,2,0,Bolivia,BO,BOL,11513102,America,\r
-19/08/2020,19,8,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-18/08/2020,18,8,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-17/08/2020,17,8,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-16/08/2020,16,8,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-15/08/2020,15,8,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-14/08/2020,14,8,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-13/08/2020,13,8,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-12/08/2020,12,8,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-11/08/2020,11,8,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-10/08/2020,10,8,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-09/08/2020,9,8,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-08/08/2020,8,8,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-07/08/2020,7,8,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-06/08/2020,6,8,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,11.54601085\r
-05/08/2020,5,8,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,11.54601085\r
-04/08/2020,4,8,2020,2,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,11.54601085\r
-03/08/2020,3,8,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,3.84867028\r
-02/08/2020,2,8,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,3.84867028\r
-01/08/2020,1,8,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,3.84867028\r
-31/07/2020,31,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,3.84867028\r
-30/07/2020,30,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-29/07/2020,29,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-28/07/2020,28,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,15.39468114\r
-27/07/2020,27,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,15.39468114\r
-26/07/2020,26,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,15.39468114\r
-25/07/2020,25,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,15.39468114\r
-24/07/2020,24,7,2020,1,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,15.39468114\r
-23/07/2020,23,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,11.54601085\r
-22/07/2020,22,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,11.54601085\r
-21/07/2020,21,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,11.54601085\r
-20/07/2020,20,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,11.54601085\r
-19/07/2020,19,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,11.54601085\r
-18/07/2020,18,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,11.54601085\r
-17/07/2020,17,7,2020,1,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,11.54601085\r
-16/07/2020,16,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-15/07/2020,15,7,2020,2,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-14/07/2020,14,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-13/07/2020,13,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-12/07/2020,12,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-11/07/2020,11,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-10/07/2020,10,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-09/07/2020,9,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-08/07/2020,8,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-07/07/2020,7,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-06/07/2020,6,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-05/07/2020,5,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-04/07/2020,4,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-03/07/2020,3,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-02/07/2020,2,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-01/07/2020,1,7,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-30/06/2020,30,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-29/06/2020,29,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-28/06/2020,28,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-27/06/2020,27,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-26/06/2020,26,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-25/06/2020,25,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-24/06/2020,24,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-23/06/2020,23,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-22/06/2020,22,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-21/06/2020,21,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-20/06/2020,20,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-19/06/2020,19,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-18/06/2020,18,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-17/06/2020,17,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-16/06/2020,16,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-15/06/2020,15,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-14/06/2020,14,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-13/06/2020,13,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-12/06/2020,12,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-11/06/2020,11,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-10/06/2020,10,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-09/06/2020,9,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-08/06/2020,8,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-07/06/2020,7,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,3.84867028\r
-06/06/2020,6,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,3.84867028\r
-05/06/2020,5,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,3.84867028\r
-04/06/2020,4,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,3.84867028\r
-03/06/2020,3,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,3.84867028\r
-02/06/2020,2,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,3.84867028\r
-01/06/2020,1,6,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,3.84867028\r
-31/05/2020,31,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,3.84867028\r
-30/05/2020,30,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,3.84867028\r
-29/05/2020,29,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,3.84867028\r
-28/05/2020,28,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,3.84867028\r
-27/05/2020,27,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,3.84867028\r
-26/05/2020,26,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,3.84867028\r
-25/05/2020,25,5,2020,1,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,3.84867028\r
-24/05/2020,24,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-23/05/2020,23,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-22/05/2020,22,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-21/05/2020,21,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-20/05/2020,20,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-19/05/2020,19,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-18/05/2020,18,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-17/05/2020,17,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-16/05/2020,16,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-15/05/2020,15,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-14/05/2020,14,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-13/05/2020,13,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-12/05/2020,12,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-11/05/2020,11,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-10/05/2020,10,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-09/05/2020,9,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-08/05/2020,8,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-07/05/2020,7,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-06/05/2020,6,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,0\r
-05/05/2020,5,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,3.84867028\r
-04/05/2020,4,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,3.84867028\r
-03/05/2020,3,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-02/05/2020,2,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-01/05/2020,1,5,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-30/04/2020,30,4,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-29/04/2020,29,4,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-28/04/2020,28,4,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-27/04/2020,27,4,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,11.54601085\r
-26/04/2020,26,4,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,15.39468114\r
-25/04/2020,25,4,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,15.39468114\r
-24/04/2020,24,4,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,15.39468114\r
-23/04/2020,23,4,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,15.39468114\r
-22/04/2020,22,4,2020,1,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,15.39468114\r
-21/04/2020,21,4,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,11.54601085\r
-20/04/2020,20,4,2020,1,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,11.54601085\r
-19/04/2020,19,4,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-18/04/2020,18,4,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-17/04/2020,17,4,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-16/04/2020,16,4,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,7.69734057\r
-15/04/2020,15,4,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,15.39468114\r
-14/04/2020,14,4,2020,1,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,\r
-13/04/2020,13,4,2020,1,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,\r
-12/04/2020,12,4,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,\r
-11/04/2020,11,4,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,\r
-10/04/2020,10,4,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,\r
-09/04/2020,9,4,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,\r
-08/04/2020,8,4,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,\r
-07/04/2020,7,4,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,\r
-06/04/2020,6,4,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,\r
-05/04/2020,5,4,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,\r
-04/04/2020,4,4,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,\r
-03/04/2020,3,4,2020,0,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,\r
-02/04/2020,2,4,2020,2,0,"Bonaire, Saint Eustatius and Saba",BQ,BES,25983,America,\r
-19/08/2020,19,8,2020,316,20,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,105.81648338\r
-18/08/2020,18,8,2020,500,6,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,113.26877508\r
-17/08/2020,17,8,2020,0,0,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,103.81708804\r
-16/08/2020,16,8,2020,1,5,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,110.87555945\r
-15/08/2020,15,8,2020,350,6,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,123.90192299\r
-14/08/2020,14,8,2020,223,5,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,113.29906895\r
-13/08/2020,13,8,2020,253,6,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,127.08277921\r
-12/08/2020,12,8,2020,210,22,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,119.41843043\r
-11/08/2020,11,8,2020,173,23,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,121.17547481\r
-10/08/2020,10,8,2020,236,6,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,128.9307052\r
-09/08/2020,9,8,2020,402,2,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,131.02098214\r
-08/08/2020,8,8,2020,290,15,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,127.99159527\r
-07/08/2020,7,8,2020,251,5,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,119.26696108\r
-06/08/2020,6,8,2020,288,6,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,122.08429087\r
-05/08/2020,5,8,2020,562,21,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,123.35663336\r
-04/08/2020,4,8,2020,188,4,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,112.23878354\r
-03/08/2020,3,8,2020,233,8,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,110.75438398\r
-02/08/2020,2,8,2020,431,7,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,112.42054676\r
-01/08/2020,1,8,2020,0,0,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,107.11911973\r
-31/07/2020,31,7,2020,678,31,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,113.99582793\r
-30/07/2020,30,7,2020,0,0,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,101.75710497\r
-29/07/2020,29,7,2020,268,3,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,108.75498864\r
-28/07/2020,28,7,2020,429,11,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,106.60412396\r
-27/07/2020,27,7,2020,305,5,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,96.48597182\r
-26/07/2020,26,7,2020,302,4,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,92.21453633\r
-25/07/2020,25,7,2020,2,2,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,92.69923823\r
-24/07/2020,24,7,2020,344,5,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,102.18121913\r
-23/07/2020,23,7,2020,330,6,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,98.39448555\r
-22/07/2020,22,7,2020,195,5,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,95.97097605\r
-21/07/2020,21,7,2020,139,6,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,94.94098451\r
-20/07/2020,20,7,2020,288,5,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,92.66894436\r
-19/07/2020,19,7,2020,256,2,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,88.30662727\r
-18/07/2020,18,7,2020,227,4,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,89.30632494\r
-17/07/2020,17,7,2020,274,6,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,87.64016216\r
-16/07/2020,16,7,2020,231,8,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,84.85312624\r
-15/07/2020,15,7,2020,197,1,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,82.49020448\r
-14/07/2020,14,7,2020,95,4,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,79.8546379\r
-13/07/2020,13,7,2020,164,2,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,80.85433557\r
-12/07/2020,12,7,2020,318,3,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,79.15787892\r
-11/07/2020,11,7,2020,315,2,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,74.76526796\r
-10/07/2020,10,7,2020,219,6,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,69.46384094\r
-09/07/2020,9,7,2020,250,1,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,66.43445407\r
-08/07/2020,8,7,2020,161,10,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,61.52684734\r
-07/07/2020,7,7,2020,64,3,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,58.5580482\r
-06/07/2020,6,7,2020,144,3,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,59.43657039\r
-05/07/2020,5,7,2020,289,0,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,57.40688119\r
-04/07/2020,4,7,2020,172,2,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,50.65134847\r
-03/07/2020,3,7,2020,182,1,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,48.04607576\r
-02/07/2020,2,7,2020,153,2,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,44.28963604\r
-01/07/2020,1,7,2020,110,2,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,41.47230625\r
-30/06/2020,30,6,2020,128,1,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,39.50320479\r
-29/06/2020,29,6,2020,108,3,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,36.77675661\r
-28/06/2020,28,6,2020,173,2,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,35.35294478\r
-27/06/2020,27,6,2020,140,3,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,31.56621119\r
-26/06/2020,26,6,2020,119,2,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,29.17299556\r
-25/06/2020,25,6,2020,88,1,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,27.23418796\r
-24/06/2020,24,6,2020,63,1,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,26.05272708\r
-23/06/2020,23,6,2020,93,1,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,24.8712662\r
-22/06/2020,22,6,2020,77,0,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,22.96275248\r
-21/06/2020,21,6,2020,66,1,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,21.75099773\r
-20/06/2020,20,6,2020,86,1,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,20.69071232\r
-19/06/2020,19,6,2020,58,0,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,18.44896604\r
-18/06/2020,18,6,2020,60,0,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,17.99455801\r
-17/06/2020,17,6,2020,45,3,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,16.66162779\r
-16/06/2020,16,6,2020,38,1,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,15.63163625\r
-15/06/2020,15,6,2020,61,0,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,14.9045834\r
-14/06/2020,14,6,2020,48,1,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,13.54135931\r
-13/06/2020,13,6,2020,61,2,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,12.35989843\r
-12/06/2020,12,6,2020,55,0,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,11.17843755\r
-11/06/2020,11,6,2020,49,1,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,10.3605031\r
-10/06/2020,10,6,2020,24,0,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,9.45168704\r
-09/06/2020,9,6,2020,30,0,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,9.02757287\r
-08/06/2020,8,6,2020,37,1,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,8.27022616\r
-07/06/2020,7,6,2020,31,0,Bosnia_and_Herzegovina,BA,BIH,3300998,Europe,7.42199783\r
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-23/05/2020,23,5,2020,1,0,Botswana,BW,BWA,2303703,Africa,0.30385861\r
-22/05/2020,22,5,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.26045024\r
-21/05/2020,21,5,2020,4,0,Botswana,BW,BWA,2303703,Africa,0.26045024\r
-20/05/2020,20,5,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.08681675\r
-19/05/2020,19,5,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.08681675\r
-18/05/2020,18,5,2020,1,0,Botswana,BW,BWA,2303703,Africa,0.08681675\r
-17/05/2020,17,5,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.04340837\r
-16/05/2020,16,5,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.04340837\r
-15/05/2020,15,5,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.04340837\r
-14/05/2020,14,5,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.04340837\r
-13/05/2020,13,5,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.04340837\r
-12/05/2020,12,5,2020,1,0,Botswana,BW,BWA,2303703,Africa,0.08681675\r
-11/05/2020,11,5,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.04340837\r
-10/05/2020,10,5,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.04340837\r
-09/05/2020,9,5,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.04340837\r
-08/05/2020,8,5,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.04340837\r
-07/05/2020,7,5,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.04340837\r
-06/05/2020,6,5,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.13022512\r
-05/05/2020,5,5,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.13022512\r
-04/05/2020,4,5,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.13022512\r
-03/05/2020,3,5,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.34726699\r
-02/05/2020,2,5,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.34726699\r
-01/05/2020,1,5,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.34726699\r
-30/04/2020,30,4,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.43408373\r
-29/04/2020,29,4,2020,1,0,Botswana,BW,BWA,2303703,Africa,0.43408373\r
-28/04/2020,28,4,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.39067536\r
-27/04/2020,27,4,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.39067536\r
-26/04/2020,26,4,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.39067536\r
-25/04/2020,25,4,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.39067536\r
-24/04/2020,24,4,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.39067536\r
-23/04/2020,23,4,2020,2,0,Botswana,BW,BWA,2303703,Africa,0.6511256\r
-22/04/2020,22,4,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.60771723\r
-21/04/2020,21,4,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.60771723\r
-20/04/2020,20,4,2020,5,0,Botswana,BW,BWA,2303703,Africa,0.60771723\r
-19/04/2020,19,4,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.47749211\r
-18/04/2020,18,4,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.47749211\r
-17/04/2020,17,4,2020,2,0,Botswana,BW,BWA,2303703,Africa,0.47749211\r
-16/04/2020,16,4,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.39067536\r
-15/04/2020,15,4,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.43408373\r
-14/04/2020,14,4,2020,0,0,Botswana,BW,BWA,2303703,Africa,0.56430885\r
-13/04/2020,13,4,2020,0,0,Botswana,BW,BWA,2303703,Africa,\r
-12/04/2020,12,4,2020,0,0,Botswana,BW,BWA,2303703,Africa,\r
-11/04/2020,11,4,2020,0,0,Botswana,BW,BWA,2303703,Africa,\r
-10/04/2020,10,4,2020,6,0,Botswana,BW,BWA,2303703,Africa,\r
-09/04/2020,9,4,2020,1,0,Botswana,BW,BWA,2303703,Africa,\r
-08/04/2020,8,4,2020,0,0,Botswana,BW,BWA,2303703,Africa,\r
-07/04/2020,7,4,2020,0,0,Botswana,BW,BWA,2303703,Africa,\r
-06/04/2020,6,4,2020,2,0,Botswana,BW,BWA,2303703,Africa,\r
-05/04/2020,5,4,2020,0,0,Botswana,BW,BWA,2303703,Africa,\r
-04/04/2020,4,4,2020,0,0,Botswana,BW,BWA,2303703,Africa,\r
-03/04/2020,3,4,2020,0,0,Botswana,BW,BWA,2303703,Africa,\r
-02/04/2020,2,4,2020,1,1,Botswana,BW,BWA,2303703,Africa,\r
-01/04/2020,1,4,2020,3,0,Botswana,BW,BWA,2303703,Africa,\r
-19/08/2020,19,8,2020,47784,1352,Brazil,BR,BRA,211049519,America,286.8677469\r
-18/08/2020,18,8,2020,19373,684,Brazil,BR,BRA,211049519,America,288.67727483\r
-17/08/2020,17,8,2020,23101,620,Brazil,BR,BRA,211049519,America,287.3827919\r
-16/08/2020,16,8,2020,41576,709,Brazil,BR,BRA,211049519,America,288.66163869\r
-15/08/2020,15,8,2020,50644,1060,Brazil,BR,BRA,211049519,America,290.46974516\r
-14/08/2020,14,8,2020,60091,1262,Brazil,BR,BRA,211049519,America,291.2937224\r
-13/08/2020,13,8,2020,55155,1175,Brazil,BR,BRA,211049519,America,290.2257266\r
-12/08/2020,12,8,2020,52160,1274,Brazil,BR,BRA,211049519,America,296.82086127\r
-11/08/2020,11,8,2020,22048,703,Brazil,BR,BRA,211049519,America,291.44581941\r
-10/08/2020,10,8,2020,23010,572,Brazil,BR,BRA,211049519,America,292.03146395\r
-09/08/2020,9,8,2020,49970,905,Brazil,BR,BRA,211049519,America,292.77441755\r
-08/08/2020,8,8,2020,50230,1079,Brazil,BR,BRA,211049519,America,293.33210658\r
-07/08/2020,7,8,2020,53139,1237,Brazil,BR,BRA,211049519,America,296.01441546\r
-06/08/2020,6,8,2020,57152,1437,Brazil,BR,BRA,211049519,America,299.24683221\r
-05/08/2020,5,8,2020,51603,1154,Brazil,BR,BRA,211049519,America,304.320523\r
-04/08/2020,4,8,2020,16641,561,Brazil,BR,BRA,211049519,America,299.30037415\r
-03/08/2020,3,8,2020,25800,541,Brazil,BR,BRA,211049519,America,301.01371612\r
-02/08/2020,2,8,2020,45392,1088,Brazil,BR,BRA,211049519,America,299.93766534\r
-01/08/2020,1,8,2020,52383,1212,Brazil,BR,BRA,211049519,America,291.94901885\r
-31/07/2020,31,7,2020,57837,1129,Brazil,BR,BRA,211049519,America,283.32260734\r
-30/07/2020,30,7,2020,69074,1595,Brazil,BR,BRA,211049519,America,277.431099\r
-29/07/2020,29,7,2020,40816,921,Brazil,BR,BRA,211049519,America,263.61917461\r
-28/07/2020,28,7,2020,23284,614,Brazil,BR,BRA,211049519,America,264.11242378\r
-27/07/2020,27,7,2020,24578,555,Brazil,BR,BRA,211049519,America,262.69190407\r
-26/07/2020,26,7,2020,51147,1211,Brazil,BR,BRA,211049519,America,262.81178115\r
-25/07/2020,25,7,2020,55891,1156,Brazil,BR,BRA,211049519,America,257.06715778\r
-24/07/2020,24,7,2020,59961,1311,Brazil,BR,BRA,211049519,America,251.92950096\r
-23/07/2020,23,7,2020,67860,1284,Brazil,BR,BRA,211049519,America,243.71247205\r
-22/07/2020,22,7,2020,41008,1367,Brazil,BR,BRA,211049519,America,232.67762103\r
-21/07/2020,21,7,2020,20257,632,Brazil,BR,BRA,211049519,America,234.71363609\r
-20/07/2020,20,7,2020,23529,716,Brazil,BR,BRA,211049519,America,234.70036906\r
-19/07/2020,19,7,2020,28532,921,Brazil,BR,BRA,211049519,America,235.89534928\r
-18/07/2020,18,7,2020,34177,1163,Brazil,BR,BRA,211049519,America,240.3450159\r
-17/07/2020,17,7,2020,45403,1322,Brazil,BR,BRA,211049519,America,244.15739133\r
-16/07/2020,16,7,2020,39924,1233,Brazil,BR,BRA,211049519,America,245.43765959\r
-15/07/2020,15,7,2020,41857,1300,Brazil,BR,BRA,211049519,America,248.65396637\r
-14/07/2020,14,7,2020,20286,733,Brazil,BR,BRA,211049519,America,244.85817473\r
-13/07/2020,13,7,2020,24831,631,Brazil,BR,BRA,211049519,America,246.64259007\r
-12/07/2020,12,7,2020,39023,1071,Brazil,BR,BRA,211049519,America,249.3173178\r
-11/07/2020,11,7,2020,45048,1214,Brazil,BR,BRA,211049519,America,249.16095639\r
-10/07/2020,10,7,2020,42619,1220,Brazil,BR,BRA,211049519,America,250.01952267\r
-09/07/2020,9,7,2020,44571,1223,Brazil,BR,BRA,211049519,America,248.53361547\r
-08/07/2020,8,7,2020,45305,1254,Brazil,BR,BRA,211049519,America,247.65893923\r
-07/07/2020,7,7,2020,20229,620,Brazil,BR,BRA,211049519,America,244.87807527\r
-06/07/2020,6,7,2020,26051,602,Brazil,BR,BRA,211049519,America,245.44808368\r
-05/07/2020,5,7,2020,37923,1091,Brazil,BR,BRA,211049519,America,241.3770012\r
-04/07/2020,4,7,2020,42223,1290,Brazil,BR,BRA,211049519,America,239.83376148\r
-03/07/2020,3,7,2020,48105,1252,Brazil,BR,BRA,211049519,America,245.77928557\r
-02/07/2020,2,7,2020,46712,1038,Brazil,BR,BRA,211049519,America,233.77262471\r
-01/07/2020,1,7,2020,33846,1280,Brazil,BR,BRA,211049519,America,226.89082746\r
-30/06/2020,30,6,2020,24052,692,Brazil,BR,BRA,211049519,America,227.39876512\r
-29/06/2020,29,6,2020,30476,552,Brazil,BR,BRA,211049519,America,225.78539968\r
-28/06/2020,28,6,2020,38693,1109,Brazil,BR,BRA,211049519,America,219.45228883\r
-27/06/2020,27,6,2020,46860,990,Brazil,BR,BRA,211049519,America,211.40251924\r
-26/06/2020,26,6,2020,39483,1141,Brazil,BR,BRA,211049519,America,201.51005414\r
-25/06/2020,25,6,2020,42725,1185,Brazil,BR,BRA,211049519,America,197.2120107\r
-24/06/2020,24,6,2020,39436,1374,Brazil,BR,BRA,211049519,America,192.56286483\r
-23/06/2020,23,6,2020,21432,654,Brazil,BR,BRA,211049519,America,189.08263894\r
-22/06/2020,22,6,2020,17459,641,Brazil,BR,BRA,211049519,America,186.34489283\r
-21/06/2020,21,6,2020,34666,1022,Brazil,BR,BRA,211049519,America,187.03762125\r
-20/06/2020,20,6,2020,54771,1206,Brazil,BR,BRA,211049519,America,183.44083504\r
-19/06/2020,19,6,2020,22765,1238,Brazil,BR,BRA,211049519,America,172.09705178\r
-18/06/2020,18,6,2020,32188,1269,Brazil,BR,BRA,211049519,America,175.95917857\r
-17/06/2020,17,6,2020,34918,1282,Brazil,BR,BRA,211049519,America,174.27473976\r
-16/06/2020,16,6,2020,20647,627,Brazil,BR,BRA,211049519,America,171.44033387\r
-15/06/2020,15,6,2020,17110,612,Brazil,BR,BRA,211049519,America,167.15271452\r
-14/06/2020,14,6,2020,21704,892,Brazil,BR,BRA,211049519,America,166.82056499\r
-13/06/2020,13,6,2020,25982,909,Brazil,BR,BRA,211049519,America,172.30269073\r
-12/06/2020,12,6,2020,30412,1239,Brazil,BR,BRA,211049519,America,172.75092676\r
-11/06/2020,11,6,2020,32913,1274,Brazil,BR,BRA,211049519,America,170.85800608\r
-10/06/2020,10,6,2020,32091,1272,Brazil,BR,BRA,211049519,America,165.02335644\r
-09/06/2020,9,6,2020,15654,679,Brazil,BR,BRA,211049519,America,157.55259788\r
-08/06/2020,8,6,2020,18921,525,Brazil,BR,BRA,211049519,America,155.67294422\r
-07/06/2020,7,6,2020,27075,904,Brazil,BR,BRA,211049519,America,154.20030405\r
-06/06/2020,6,6,2020,30830,1005,Brazil,BR,BRA,211049519,America,149.19342223\r
-05/06/2020,5,6,2020,30916,1473,Brazil,BR,BRA,211049519,America,144.44240453\r
-04/06/2020,4,6,2020,28633,1349,Brazil,BR,BRA,211049519,America,138.56321558\r
-03/06/2020,3,6,2020,28936,1262,Brazil,BR,BRA,211049519,America,134.44948908\r
-02/06/2020,2,6,2020,11598,623,Brazil,BR,BRA,211049519,America,128.98726388\r
-01/06/2020,1,6,2020,16409,480,Brazil,BR,BRA,211049519,America,129.7178981\r
-31/05/2020,31,5,2020,33274,956,Brazil,BR,BRA,211049519,America,125.70414813\r
-30/05/2020,30,5,2020,26928,1124,Brazil,BR,BRA,211049519,America,117.00713708\r
-29/05/2020,29,5,2020,26417,1156,Brazil,BR,BRA,211049519,America,111.49989875\r
-28/05/2020,28,5,2020,20599,1086,Brazil,BR,BRA,211049519,America,105.58991134\r
-27/05/2020,27,5,2020,16324,1039,Brazil,BR,BRA,211049519,America,101.22411129\r
-26/05/2020,26,5,2020,11687,807,Brazil,BR,BRA,211049519,America,97.87608187\r
-25/05/2020,25,5,2020,15813,653,Brazil,BR,BRA,211049519,America,95.00708694\r
-24/05/2020,24,5,2020,16508,965,Brazil,BR,BRA,211049519,America,90.71757231\r
-23/05/2020,23,5,2020,20803,1001,Brazil,BR,BRA,211049519,America,87.92344132\r
-22/05/2020,22,5,2020,18508,1188,Brazil,BR,BRA,211049519,America,82.90992599\r
-21/05/2020,21,5,2020,19951,888,Brazil,BR,BRA,211049519,America,78.82557648\r
-20/05/2020,20,5,2020,17408,1179,Brazil,BR,BRA,211049519,America,74.34890197\r
-19/05/2020,19,5,2020,13140,674,Brazil,BR,BRA,211049519,America,69.38655946\r
-18/05/2020,18,5,2020,7938,485,Brazil,BR,BRA,211049519,America,66.30339679\r
-17/05/2020,17,5,2020,14919,816,Brazil,BR,BRA,211049519,America,64.71609158\r
-16/05/2020,16,5,2020,15305,824,Brazil,BR,BRA,211049519,America,60.00203203\r
-15/05/2020,15,5,2020,13944,844,Brazil,BR,BRA,211049519,America,55.69214304\r
-14/05/2020,14,5,2020,11385,749,Brazil,BR,BRA,211049519,America,52.50521324\r
-13/05/2020,13,5,2020,9258,881,Brazil,BR,BRA,211049519,America,50.08445435\r
-12/05/2020,12,5,2020,5632,396,Brazil,BR,BRA,211049519,America,48.24934\r
-11/05/2020,11,5,2020,6760,496,Brazil,BR,BRA,211049519,America,47.76651493\r
-10/05/2020,10,5,2020,10611,730,Brazil,BR,BRA,211049519,America,46.16452123\r
-09/05/2020,9,5,2020,10222,751,Brazil,BR,BRA,211049519,America,43.7494482\r
-08/05/2020,8,5,2020,9888,610,Brazil,BR,BRA,211049519,America,40.56583517\r
-07/05/2020,7,5,2020,10503,615,Brazil,BR,BRA,211049519,America,37.65040564\r
-06/05/2020,6,5,2020,6935,600,Brazil,BR,BRA,211049519,America,33.94274497\r
-05/05/2020,5,5,2020,6633,296,Brazil,BR,BRA,211049519,America,31.84039477\r
-04/05/2020,4,5,2020,4588,275,Brazil,BR,BRA,211049519,America,29.61058632\r
-03/05/2020,3,5,2020,4970,421,Brazil,BR,BRA,211049519,America,28.41039406\r
-02/05/2020,2,5,2020,6209,428,Brazil,BR,BRA,211049519,America,27.43763657\r
-01/05/2020,1,5,2020,7218,435,Brazil,BR,BRA,211049519,America,26.0389127\r
-30/04/2020,30,4,2020,6276,449,Brazil,BR,BRA,211049519,America,23.61625851\r
-29/04/2020,29,4,2020,5385,474,Brazil,BR,BRA,211049519,America,22.09149787\r
-28/04/2020,28,4,2020,4613,338,Brazil,BR,BRA,211049519,America,20.40800671\r
-27/04/2020,27,4,2020,3379,189,Brazil,BR,BRA,211049519,America,18.81975386\r
-26/04/2020,26,4,2020,5514,346,Brazil,BR,BRA,211049519,America,17.90195978\r
-25/04/2020,25,4,2020,3503,357,Brazil,BR,BRA,211049519,America,15.80529544\r
-24/04/2020,24,4,2020,3735,407,Brazil,BR,BRA,211049519,America,14.98937318\r
-23/04/2020,23,4,2020,2678,165,Brazil,BR,BRA,211049519,America,14.13412366\r
-22/04/2020,22,4,2020,2498,166,Brazil,BR,BRA,211049519,America,13.91237475\r
-21/04/2020,21,4,2020,1927,113,Brazil,BR,BRA,211049519,America,13.51578536\r
-20/04/2020,20,4,2020,2055,115,Brazil,BR,BRA,211049519,America,13.04148909\r
-19/04/2020,19,4,2020,2917,206,Brazil,BR,BRA,211049519,America,12.47148069\r
-18/04/2020,18,4,2020,3257,217,Brazil,BR,BRA,211049519,America,11.66835163\r
-17/04/2020,17,4,2020,2105,188,Brazil,BR,BRA,211049519,America,10.66811244\r
-16/04/2020,16,4,2020,3058,204,Brazil,BR,BRA,211049519,America,10.1796015\r
-15/04/2020,15,4,2020,1832,204,Brazil,BR,BRA,211049519,America,9.26085977\r
-14/04/2020,14,4,2020,1261,105,Brazil,BR,BRA,211049519,America,8.93202699\r
-13/04/2020,13,4,2020,1442,99,Brazil,BR,BRA,211049519,America,8.48758153\r
-12/04/2020,12,4,2020,1089,68,Brazil,BR,BRA,211049519,America,7.97111506\r
-11/04/2020,11,4,2020,1781,115,Brazil,BR,BRA,211049519,America,7.68587395\r
-10/04/2020,10,4,2020,1930,141,Brazil,BR,BRA,211049519,America,7.07985504\r
-09/04/2020,9,4,2020,2210,133,Brazil,BR,BRA,211049519,America,6.39376013\r
-08/04/2020,8,4,2020,1661,114,Brazil,BR,BRA,211049519,America,5.45653933\r
-07/04/2020,7,4,2020,926,67,Brazil,BR,BRA,211049519,America,4.8164052\r
-06/04/2020,6,4,2020,852,54,Brazil,BR,BRA,211049519,America,4.54111435\r
-05/04/2020,5,4,2020,1222,73,Brazil,BR,BRA,211049519,America,4.33547541\r
-04/04/2020,4,4,2020,1146,60,Brazil,BR,BRA,211049519,America,3.86260061\r
-03/04/2020,3,4,2020,1074,58,Brazil,BR,BRA,211049519,America,3.45369183\r
-02/04/2020,2,4,2020,1119,40,Brazil,BR,BRA,211049519,America,3.03625425\r
-01/04/2020,1,4,2020,1138,42,Brazil,BR,BRA,211049519,America,2.57096061\r
-31/03/2020,31,3,2020,323,23,Brazil,BR,BRA,211049519,America,2.05875854\r
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-30/06/2020,30,6,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.57239113\r
-29/06/2020,29,6,2020,26,0,Burundi,BI,BDI,11530577,Africa,0.65911706\r
-28/06/2020,28,6,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.43362964\r
-27/06/2020,27,6,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.43362964\r
-26/06/2020,26,6,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.43362964\r
-25/06/2020,25,6,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.52902817\r
-24/06/2020,24,6,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.52902817\r
-23/06/2020,23,6,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.52902817\r
-22/06/2020,22,6,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.52902817\r
-21/06/2020,21,6,2020,40,0,Burundi,BI,BDI,11530577,Africa,0.52902817\r
-20/06/2020,20,6,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.35557631\r
-19/06/2020,19,6,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.35557631\r
-18/06/2020,18,6,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.35557631\r
-17/06/2020,17,6,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.35557631\r
-16/06/2020,16,6,2020,10,0,Burundi,BI,BDI,11530577,Africa,0.35557631\r
-15/06/2020,15,6,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.26885038\r
-14/06/2020,14,6,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.45097483\r
-13/06/2020,13,6,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.45097483\r
-12/06/2020,12,6,2020,11,0,Burundi,BI,BDI,11530577,Africa,0.45097483\r
-11/06/2020,11,6,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.35557631\r
-10/06/2020,10,6,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.35557631\r
-09/06/2020,9,6,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.35557631\r
-08/06/2020,8,6,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.35557631\r
-07/06/2020,7,6,2020,20,0,Burundi,BI,BDI,11530577,Africa,0.35557631\r
-06/06/2020,6,6,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.18212445\r
-05/06/2020,5,6,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.18212445\r
-04/06/2020,4,6,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.18212445\r
-03/06/2020,3,6,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.18212445\r
-02/06/2020,2,6,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.18212445\r
-01/06/2020,1,6,2020,21,0,Burundi,BI,BDI,11530577,Africa,0.18212445\r
-31/05/2020,31,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.13008889\r
-30/05/2020,30,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.13008889\r
-29/05/2020,29,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.13008889\r
-28/05/2020,28,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.13008889\r
-27/05/2020,27,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.13008889\r
-26/05/2020,26,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.19946964\r
-25/05/2020,25,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.19946964\r
-24/05/2020,24,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.19946964\r
-23/05/2020,23,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.19946964\r
-22/05/2020,22,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.19946964\r
-21/05/2020,21,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.19946964\r
-20/05/2020,20,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.19946964\r
-19/05/2020,19,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.19946964\r
-18/05/2020,18,5,2020,15,0,Burundi,BI,BDI,11530577,Africa,0.19946964\r
-17/05/2020,17,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.06938074\r
-16/05/2020,16,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.10407111\r
-15/05/2020,15,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.10407111\r
-14/05/2020,14,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.10407111\r
-13/05/2020,13,5,2020,8,0,Burundi,BI,BDI,11530577,Africa,0.10407111\r
-12/05/2020,12,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.03469037\r
-11/05/2020,11,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.03469037\r
-10/05/2020,10,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.03469037\r
-09/05/2020,9,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.06070815\r
-08/05/2020,8,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.06938074\r
-07/05/2020,7,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.06938074\r
-06/05/2020,6,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.11274371\r
-05/05/2020,5,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.11274371\r
-04/05/2020,4,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.11274371\r
-03/05/2020,3,5,2020,4,0,Burundi,BI,BDI,11530577,Africa,0.11274371\r
-02/05/2020,2,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.07805334\r
-01/05/2020,1,5,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.08672593\r
-30/04/2020,30,4,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.08672593\r
-29/04/2020,29,4,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.08672593\r
-28/04/2020,28,4,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.08672593\r
-27/04/2020,27,4,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.08672593\r
-26/04/2020,26,4,2020,3,0,Burundi,BI,BDI,11530577,Africa,0.08672593\r
-25/04/2020,25,4,2020,1,0,Burundi,BI,BDI,11530577,Africa,0.07805334\r
-24/04/2020,24,4,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.06938074\r
-23/04/2020,23,4,2020,5,0,Burundi,BI,BDI,11530577,Africa,0.06938074\r
-22/04/2020,22,4,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.02601778\r
-21/04/2020,21,4,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.02601778\r
-20/04/2020,20,4,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.02601778\r
-19/04/2020,19,4,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.02601778\r
-18/04/2020,18,4,2020,1,0,Burundi,BI,BDI,11530577,Africa,0.02601778\r
-17/04/2020,17,4,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.01734519\r
-16/04/2020,16,4,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.02601778\r
-15/04/2020,15,4,2020,0,1,Burundi,BI,BDI,11530577,Africa,0.02601778\r
-14/04/2020,14,4,2020,0,0,Burundi,BI,BDI,11530577,Africa,0.04336296\r
-13/04/2020,13,4,2020,0,0,Burundi,BI,BDI,11530577,Africa,\r
-12/04/2020,12,4,2020,2,0,Burundi,BI,BDI,11530577,Africa,\r
-11/04/2020,11,4,2020,0,0,Burundi,BI,BDI,11530577,Africa,\r
-10/04/2020,10,4,2020,0,0,Burundi,BI,BDI,11530577,Africa,\r
-09/04/2020,9,4,2020,0,0,Burundi,BI,BDI,11530577,Africa,\r
-08/04/2020,8,4,2020,0,0,Burundi,BI,BDI,11530577,Africa,\r
-07/04/2020,7,4,2020,0,0,Burundi,BI,BDI,11530577,Africa,\r
-06/04/2020,6,4,2020,0,0,Burundi,BI,BDI,11530577,Africa,\r
-05/04/2020,5,4,2020,0,0,Burundi,BI,BDI,11530577,Africa,\r
-04/04/2020,4,4,2020,0,0,Burundi,BI,BDI,11530577,Africa,\r
-03/04/2020,3,4,2020,1,0,Burundi,BI,BDI,11530577,Africa,\r
-02/04/2020,2,4,2020,0,0,Burundi,BI,BDI,11530577,Africa,\r
-01/04/2020,1,4,2020,2,0,Burundi,BI,BDI,11530577,Africa,\r
-19/08/2020,19,8,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.1819666\r
-18/08/2020,18,8,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.20016326\r
-17/08/2020,17,8,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.20016326\r
-16/08/2020,16,8,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.20016326\r
-15/08/2020,15,8,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.20622881\r
-14/08/2020,14,8,2020,1,0,Cambodia,KH,KHM,16486542,Asia,0.23655658\r
-13/08/2020,13,8,2020,4,0,Cambodia,KH,KHM,16486542,Asia,0.23049103\r
-12/08/2020,12,8,2020,2,0,Cambodia,KH,KHM,16486542,Asia,0.25475324\r
-11/08/2020,11,8,2020,15,0,Cambodia,KH,KHM,16486542,Asia,0.24868769\r
-10/08/2020,10,8,2020,5,0,Cambodia,KH,KHM,16486542,Asia,0.15770439\r
-09/08/2020,9,8,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.12737662\r
-08/08/2020,8,8,2020,3,0,Cambodia,KH,KHM,16486542,Asia,0.26688435\r
-07/08/2020,7,8,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.24868769\r
-06/08/2020,6,8,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.2729499\r
-05/08/2020,5,8,2020,3,0,Cambodia,KH,KHM,16486542,Asia,0.27901545\r
-04/08/2020,4,8,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.26081879\r
-03/08/2020,3,8,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.41852318\r
-02/08/2020,2,8,2020,1,0,Cambodia,KH,KHM,16486542,Asia,0.41852318\r
-01/08/2020,1,8,2020,5,0,Cambodia,KH,KHM,16486542,Asia,0.41245763\r
-31/07/2020,31,7,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.38212986\r
-30/07/2020,30,7,2020,8,0,Cambodia,KH,KHM,16486542,Asia,0.41245763\r
-29/07/2020,29,7,2020,1,0,Cambodia,KH,KHM,16486542,Asia,0.36999875\r
-28/07/2020,28,7,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.3639332\r
-27/07/2020,27,7,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.41852318\r
-26/07/2020,26,7,2020,23,0,Cambodia,KH,KHM,16486542,Asia,0.41852318\r
-25/07/2020,25,7,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.36999875\r
-24/07/2020,24,7,2020,4,0,Cambodia,KH,KHM,16486542,Asia,0.36999875\r
-23/07/2020,23,7,2020,1,0,Cambodia,KH,KHM,16486542,Asia,0.34573654\r
-22/07/2020,22,7,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.33967099\r
-21/07/2020,21,7,2020,26,0,Cambodia,KH,KHM,16486542,Asia,0.33967099\r
-20/07/2020,20,7,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.1819666\r
-19/07/2020,19,7,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.1819666\r
-18/07/2020,18,7,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.1819666\r
-17/07/2020,17,7,2020,5,0,Cambodia,KH,KHM,16486542,Asia,0.1819666\r
-16/07/2020,16,7,2020,1,0,Cambodia,KH,KHM,16486542,Asia,0.15163883\r
-15/07/2020,15,7,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.14557328\r
-14/07/2020,14,7,2020,9,0,Cambodia,KH,KHM,16486542,Asia,0.14557328\r
-13/07/2020,13,7,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.0909833\r
-12/07/2020,12,7,2020,15,0,Cambodia,KH,KHM,16486542,Asia,0.0909833\r
-11/07/2020,11,7,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.01213111\r
-10/07/2020,10,7,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.06672109\r
-09/07/2020,9,7,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.06672109\r
-08/07/2020,8,7,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.06672109\r
-07/07/2020,7,7,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.06672109\r
-06/07/2020,6,7,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.07278664\r
-05/07/2020,5,7,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.07278664\r
-04/07/2020,4,7,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.07278664\r
-03/07/2020,3,7,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.07278664\r
-02/07/2020,2,7,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.07278664\r
-01/07/2020,1,7,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.07885219\r
-30/06/2020,30,6,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.07885219\r
-29/06/2020,29,6,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.07885219\r
-28/06/2020,28,6,2020,2,0,Cambodia,KH,KHM,16486542,Asia,0.07885219\r
-27/06/2020,27,6,2020,9,0,Cambodia,KH,KHM,16486542,Asia,0.07885219\r
-26/06/2020,26,6,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.02426221\r
-25/06/2020,25,6,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.02426221\r
-24/06/2020,24,6,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.02426221\r
-23/06/2020,23,6,2020,1,0,Cambodia,KH,KHM,16486542,Asia,0.02426221\r
-22/06/2020,22,6,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.01819666\r
-21/06/2020,21,6,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.02426221\r
-20/06/2020,20,6,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.02426221\r
-19/06/2020,19,6,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.02426221\r
-18/06/2020,18,6,2020,1,0,Cambodia,KH,KHM,16486542,Asia,0.02426221\r
-17/06/2020,17,6,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.01819666\r
-16/06/2020,16,6,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.01819666\r
-15/06/2020,15,6,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.01819666\r
-14/06/2020,14,6,2020,2,0,Cambodia,KH,KHM,16486542,Asia,0.01819666\r
-13/06/2020,13,6,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.00606555\r
-12/06/2020,12,6,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.01213111\r
-11/06/2020,11,6,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.01213111\r
-10/06/2020,10,6,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.01213111\r
-09/06/2020,9,6,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.01213111\r
-08/06/2020,8,6,2020,1,0,Cambodia,KH,KHM,16486542,Asia,0.01213111\r
-07/06/2020,7,6,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.00606555\r
-06/06/2020,6,6,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.00606555\r
-05/06/2020,5,6,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.01213111\r
-04/06/2020,4,6,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.01819666\r
-03/06/2020,3,6,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.01819666\r
-02/06/2020,2,6,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.01819666\r
-01/06/2020,1,6,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.01819666\r
-31/05/2020,31,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.01819666\r
-30/05/2020,30,5,2020,1,0,Cambodia,KH,KHM,16486542,Asia,0.01819666\r
-29/05/2020,29,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.01213111\r
-28/05/2020,28,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.01213111\r
-27/05/2020,27,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.01213111\r
-26/05/2020,26,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.01213111\r
-25/05/2020,25,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.01213111\r
-24/05/2020,24,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.01213111\r
-23/05/2020,23,5,2020,1,0,Cambodia,KH,KHM,16486542,Asia,0.01213111\r
-22/05/2020,22,5,2020,1,0,Cambodia,KH,KHM,16486542,Asia,0.00606555\r
-21/05/2020,21,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-20/05/2020,20,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-19/05/2020,19,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-18/05/2020,18,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-17/05/2020,17,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-16/05/2020,16,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-15/05/2020,15,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-14/05/2020,14,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-13/05/2020,13,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-12/05/2020,12,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-11/05/2020,11,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-10/05/2020,10,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-09/05/2020,9,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-08/05/2020,8,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-07/05/2020,7,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-06/05/2020,6,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-05/05/2020,5,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-04/05/2020,4,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-03/05/2020,3,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-02/05/2020,2,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-01/05/2020,1,5,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-30/04/2020,30,4,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-29/04/2020,29,4,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-28/04/2020,28,4,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-27/04/2020,27,4,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-26/04/2020,26,4,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-25/04/2020,25,4,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.01213111\r
-24/04/2020,24,4,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.01819666\r
-23/04/2020,23,4,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.02426221\r
-22/04/2020,22,4,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.03032777\r
-21/04/2020,21,4,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.04245887\r
-20/04/2020,20,4,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.04852443\r
-19/04/2020,19,4,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.04852443\r
-18/04/2020,18,4,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.04852443\r
-17/04/2020,17,4,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.04852443\r
-16/04/2020,16,4,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.07278664\r
-15/04/2020,15,4,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.07885219\r
-14/04/2020,14,4,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.07885219\r
-13/04/2020,13,4,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.0909833\r
-12/04/2020,12,4,2020,2,0,Cambodia,KH,KHM,16486542,Asia,0.11524551\r
-11/04/2020,11,4,2020,1,0,Cambodia,KH,KHM,16486542,Asia,0.10917996\r
-10/04/2020,10,4,2020,1,0,Cambodia,KH,KHM,16486542,Asia,0.12737662\r
-09/04/2020,9,4,2020,1,0,Cambodia,KH,KHM,16486542,Asia,0.13344217\r
-08/04/2020,8,4,2020,2,0,Cambodia,KH,KHM,16486542,Asia,0.15770439\r
-07/04/2020,7,4,2020,1,0,Cambodia,KH,KHM,16486542,Asia,0.16983549\r
-06/04/2020,6,4,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.16983549\r
-05/04/2020,5,4,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.38212986\r
-04/04/2020,4,4,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.40639207\r
-03/04/2020,3,4,2020,4,0,Cambodia,KH,KHM,16486542,Asia,0.5458998\r
-02/04/2020,2,4,2020,1,0,Cambodia,KH,KHM,16486542,Asia,0.52163759\r
-01/04/2020,1,4,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.51557203\r
-31/03/2020,31,3,2020,2,0,Cambodia,KH,KHM,16486542,Asia,0.51557203\r
-30/03/2020,30,3,2020,4,0,Cambodia,KH,KHM,16486542,Asia,0.57622757\r
-29/03/2020,29,3,2020,1,0,Cambodia,KH,KHM,16486542,Asia,0.58229312\r
-28/03/2020,28,3,2020,4,0,Cambodia,KH,KHM,16486542,Asia,0.58835867\r
-27/03/2020,27,3,2020,2,0,Cambodia,KH,KHM,16486542,Asia,0.57622757\r
-26/03/2020,26,3,2020,5,0,Cambodia,KH,KHM,16486542,Asia,0.57016201\r
-25/03/2020,25,3,2020,4,0,Cambodia,KH,KHM,16486542,Asia,0.5458998\r
-24/03/2020,24,3,2020,1,0,Cambodia,KH,KHM,16486542,Asia,0.52163759\r
-23/03/2020,23,3,2020,35,0,Cambodia,KH,KHM,16486542,Asia,0.51557203\r
-22/03/2020,22,3,2020,4,0,Cambodia,KH,KHM,16486542,Asia,0.30327767\r
-21/03/2020,21,3,2020,23,0,Cambodia,KH,KHM,16486542,Asia,0.27901545\r
-20/03/2020,20,3,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.13950773\r
-19/03/2020,19,3,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.13950773\r
-18/03/2020,18,3,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.13950773\r
-17/03/2020,17,3,2020,12,0,Cambodia,KH,KHM,16486542,Asia,0.13950773\r
-16/03/2020,16,3,2020,5,0,Cambodia,KH,KHM,16486542,Asia,0.06672109\r
-15/03/2020,15,3,2020,2,0,Cambodia,KH,KHM,16486542,Asia,0.03639332\r
-13/03/2020,13,3,2020,2,0,Cambodia,KH,KHM,16486542,Asia,0.02426221\r
-12/03/2020,12,3,2020,1,0,Cambodia,KH,KHM,16486542,Asia,0.01213111\r
-08/03/2020,8,3,2020,1,0,Cambodia,KH,KHM,16486542,Asia,0.00606555\r
-02/03/2020,2,3,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-01/03/2020,1,3,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-29/02/2020,29,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-28/02/2020,28,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-27/02/2020,27,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-26/02/2020,26,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-25/02/2020,25,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-24/02/2020,24,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-23/02/2020,23,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-22/02/2020,22,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-21/02/2020,21,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-20/02/2020,20,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-19/02/2020,19,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-18/02/2020,18,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-17/02/2020,17,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-16/02/2020,16,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-15/02/2020,15,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-14/02/2020,14,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-13/02/2020,13,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-12/02/2020,12,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-11/02/2020,11,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-10/02/2020,10,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.00606555\r
-09/02/2020,9,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.00606555\r
-08/02/2020,8,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.00606555\r
-07/02/2020,7,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.00606555\r
-06/02/2020,6,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.00606555\r
-05/02/2020,5,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.00606555\r
-04/02/2020,4,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.00606555\r
-03/02/2020,3,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.00606555\r
-02/02/2020,2,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.00606555\r
-01/02/2020,1,2,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.00606555\r
-31/01/2020,31,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.00606555\r
-30/01/2020,30,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.00606555\r
-29/01/2020,29,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0.00606555\r
-28/01/2020,28,1,2020,1,0,Cambodia,KH,KHM,16486542,Asia,0.00606555\r
-27/01/2020,27,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-26/01/2020,26,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-25/01/2020,25,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-24/01/2020,24,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-23/01/2020,23,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-22/01/2020,22,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-21/01/2020,21,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-20/01/2020,20,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-19/01/2020,19,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-18/01/2020,18,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-17/01/2020,17,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-16/01/2020,16,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-15/01/2020,15,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-14/01/2020,14,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-13/01/2020,13,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,0\r
-12/01/2020,12,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,\r
-11/01/2020,11,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,\r
-10/01/2020,10,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,\r
-09/01/2020,9,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,\r
-08/01/2020,8,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,\r
-07/01/2020,7,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,\r
-06/01/2020,6,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,\r
-05/01/2020,5,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,\r
-04/01/2020,4,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,\r
-03/01/2020,3,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,\r
-02/01/2020,2,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,\r
-01/01/2020,1,1,2020,0,0,Cambodia,KH,KHM,16486542,Asia,\r
-31/12/2019,31,12,2019,0,0,Cambodia,KH,KHM,16486542,Asia,\r
-19/08/2020,19,8,2020,17,3,Cameroon,CM,CMR,25876387,Africa,3.40464842\r
-18/08/2020,18,8,2020,113,2,Cameroon,CM,CMR,25876387,Africa,5.12822752\r
-17/08/2020,17,8,2020,0,0,Cameroon,CM,CMR,25876387,Africa,4.69153596\r
-16/08/2020,16,8,2020,0,0,Cameroon,CM,CMR,25876387,Africa,4.69153596\r
-15/08/2020,15,8,2020,161,0,Cameroon,CM,CMR,25876387,Africa,4.69153596\r
-14/08/2020,14,8,2020,45,0,Cameroon,CM,CMR,25876387,Africa,4.06934708\r
-13/08/2020,13,8,2020,50,3,Cameroon,CM,CMR,25876387,Africa,3.89544336\r
-12/08/2020,12,8,2020,171,3,Cameroon,CM,CMR,25876387,Africa,5.81611335\r
-11/08/2020,11,8,2020,0,0,Cameroon,CM,CMR,25876387,Africa,5.15527921\r
-10/08/2020,10,8,2020,324,4,Cameroon,CM,CMR,25876387,Africa,5.15527921\r
-09/08/2020,9,8,2020,0,0,Cameroon,CM,CMR,25876387,Africa,3.90317242\r
-08/08/2020,8,8,2020,0,0,Cameroon,CM,CMR,25876387,Africa,3.90317242\r
-07/08/2020,7,8,2020,0,0,Cameroon,CM,CMR,25876387,Africa,3.90317242\r
-06/08/2020,6,8,2020,0,0,Cameroon,CM,CMR,25876387,Africa,4.62197447\r
-05/08/2020,5,8,2020,463,4,Cameroon,CM,CMR,25876387,Africa,6.03252687\r
-04/08/2020,4,8,2020,0,0,Cameroon,CM,CMR,25876387,Africa,4.24325081\r
-03/08/2020,3,8,2020,0,0,Cameroon,CM,CMR,25876387,Africa,4.24325081\r
-02/08/2020,2,8,2020,0,0,Cameroon,CM,CMR,25876387,Africa,4.24325081\r
-01/08/2020,1,8,2020,0,0,Cameroon,CM,CMR,25876387,Africa,4.24325081\r
-31/07/2020,31,7,2020,0,0,Cameroon,CM,CMR,25876387,Africa,4.24325081\r
-30/07/2020,30,7,2020,547,2,Cameroon,CM,CMR,25876387,Africa,8.04594552\r
-29/07/2020,29,7,2020,0,0,Cameroon,CM,CMR,25876387,Africa,5.93204917\r
-28/07/2020,28,7,2020,0,0,Cameroon,CM,CMR,25876387,Africa,5.93204917\r
-27/07/2020,27,7,2020,0,0,Cameroon,CM,CMR,25876387,Africa,5.93204917\r
-26/07/2020,26,7,2020,0,0,Cameroon,CM,CMR,25876387,Africa,6.92523265\r
-25/07/2020,25,7,2020,0,0,Cameroon,CM,CMR,25876387,Africa,6.92523265\r
-24/07/2020,24,7,2020,186,3,Cameroon,CM,CMR,25876387,Africa,6.92523265\r
-23/07/2020,23,7,2020,365,9,Cameroon,CM,CMR,25876387,Africa,6.2064306\r
-22/07/2020,22,7,2020,0,0,Cameroon,CM,CMR,25876387,Africa,4.79587819\r
-21/07/2020,21,7,2020,0,0,Cameroon,CM,CMR,25876387,Africa,8.19279755\r
-20/07/2020,20,7,2020,0,0,Cameroon,CM,CMR,25876387,Africa,9.4526334\r
-19/07/2020,19,7,2020,0,0,Cameroon,CM,CMR,25876387,Africa,13.77703928\r
-18/07/2020,18,7,2020,0,0,Cameroon,CM,CMR,25876387,Africa,13.77703928\r
-17/07/2020,17,7,2020,984,14,Cameroon,CM,CMR,25876387,Africa,13.77703928\r
-16/07/2020,16,7,2020,0,0,Cameroon,CM,CMR,25876387,Africa,9.97434456\r
-15/07/2020,15,7,2020,0,0,Cameroon,CM,CMR,25876387,Africa,9.97434456\r
-14/07/2020,14,7,2020,0,0,Cameroon,CM,CMR,25876387,Africa,9.97434456\r
-13/07/2020,13,7,2020,257,0,Cameroon,CM,CMR,25876387,Africa,9.97434456\r
-12/07/2020,12,7,2020,0,0,Cameroon,CM,CMR,25876387,Africa,8.98116109\r
-11/07/2020,11,7,2020,0,0,Cameroon,CM,CMR,25876387,Africa,8.98116109\r
-10/07/2020,10,7,2020,0,0,Cameroon,CM,CMR,25876387,Africa,8.98116109\r
-09/07/2020,9,7,2020,0,0,Cameroon,CM,CMR,25876387,Africa,10.22553883\r
-08/07/2020,8,7,2020,879,29,Cameroon,CM,CMR,25876387,Africa,11.11051554\r
-07/07/2020,7,7,2020,326,2,Cameroon,CM,CMR,25876387,Africa,8.28941073\r
-06/07/2020,6,7,2020,1119,15,Cameroon,CM,CMR,25876387,Africa,8.11937153\r
-05/07/2020,5,7,2020,0,0,Cameroon,CM,CMR,25876387,Africa,5.06639509\r
-04/07/2020,4,7,2020,0,0,Cameroon,CM,CMR,25876387,Africa,5.06639509\r
-03/07/2020,3,7,2020,0,0,Cameroon,CM,CMR,25876387,Africa,7.55128604\r
-02/07/2020,2,7,2020,0,0,Cameroon,CM,CMR,25876387,Africa,10.54243005\r
-01/07/2020,1,7,2020,0,0,Cameroon,CM,CMR,25876387,Africa,10.54243005\r
-30/06/2020,30,6,2020,0,0,Cameroon,CM,CMR,25876387,Africa,10.54243005\r
-29/06/2020,29,6,2020,0,0,Cameroon,CM,CMR,25876387,Africa,10.54243005\r
-28/06/2020,28,6,2020,0,0,Cameroon,CM,CMR,25876387,Africa,11.67087198\r
-27/06/2020,27,6,2020,0,0,Cameroon,CM,CMR,25876387,Africa,13.12393419\r
-26/06/2020,26,6,2020,322,0,Cameroon,CM,CMR,25876387,Africa,14.15576294\r
-25/06/2020,25,6,2020,229,5,Cameroon,CM,CMR,25876387,Africa,12.91138519\r
-24/06/2020,24,6,2020,149,5,Cameroon,CM,CMR,25876387,Africa,12.98481121\r
-23/06/2020,23,6,2020,282,2,Cameroon,CM,CMR,25876387,Africa,13.83500718\r
-22/06/2020,22,6,2020,329,1,Cameroon,CM,CMR,25876387,Africa,14.30647949\r
-21/06/2020,21,6,2020,0,0,Cameroon,CM,CMR,25876387,Africa,14.22918895\r
-20/06/2020,20,6,2020,643,18,Cameroon,CM,CMR,25876387,Africa,14.22918895\r
-19/06/2020,19,6,2020,774,6,Cameroon,CM,CMR,25876387,Africa,14.87456498\r
-18/06/2020,18,6,2020,0,0,Cameroon,CM,CMR,25876387,Africa,12.02640848\r
-17/06/2020,17,6,2020,0,0,Cameroon,CM,CMR,25876387,Africa,12.67178451\r
-16/06/2020,16,6,2020,0,0,Cameroon,CM,CMR,25876387,Africa,13.39831561\r
-15/06/2020,15,6,2020,292,1,Cameroon,CM,CMR,25876387,Africa,15.3035275\r
-14/06/2020,14,6,2020,376,2,Cameroon,CM,CMR,25876387,Africa,14.17508557\r
-13/06/2020,13,6,2020,267,59,Cameroon,CM,CMR,25876387,Africa,14.53062207\r
-12/06/2020,12,6,2020,0,0,Cameroon,CM,CMR,25876387,Africa,13.80795549\r
-11/06/2020,11,6,2020,248,6,Cameroon,CM,CMR,25876387,Africa,13.80795549\r
-10/06/2020,10,6,2020,369,0,Cameroon,CM,CMR,25876387,Africa,12.84955276\r
-09/06/2020,9,6,2020,404,5,Cameroon,CM,CMR,25876387,Africa,12.62927471\r
-08/06/2020,8,6,2020,309,0,Cameroon,CM,CMR,25876387,Africa,11.66314293\r
-07/06/2020,7,6,2020,0,0,Cameroon,CM,CMR,25876387,Africa,11.60131049\r
-06/06/2020,6,6,2020,810,0,Cameroon,CM,CMR,25876387,Africa,12.36262234\r
-05/06/2020,5,6,2020,37,3,Cameroon,CM,CMR,25876387,Africa,9.66518239\r
-04/06/2020,4,6,2020,167,0,Cameroon,CM,CMR,25876387,Africa,11.66700745\r
-03/06/2020,3,6,2020,188,1,Cameroon,CM,CMR,25876387,Africa,11.80999496\r
-02/06/2020,2,6,2020,493,8,Cameroon,CM,CMR,25876387,Africa,11.99935679\r
-01/06/2020,1,6,2020,0,0,Cameroon,CM,CMR,25876387,Africa,10.09414491\r
-31/05/2020,31,5,2020,468,14,Cameroon,CM,CMR,25876387,Africa,10.09414491\r
-30/05/2020,30,5,2020,80,0,Cameroon,CM,CMR,25876387,Africa,9.00821278\r
-29/05/2020,29,5,2020,0,0,Cameroon,CM,CMR,25876387,Africa,9.2825942\r
-28/05/2020,28,5,2020,0,2,Cameroon,CM,CMR,25876387,Africa,9.87773138\r
-27/05/2020,27,5,2020,312,4,Cameroon,CM,CMR,25876387,Africa,10.3066939\r
-26/05/2020,26,5,2020,154,6,Cameroon,CM,CMR,25876387,Africa,9.10096143\r
-25/05/2020,25,5,2020,293,6,Cameroon,CM,CMR,25876387,Africa,8.93092223\r
-24/05/2020,24,5,2020,197,0,Cameroon,CM,CMR,25876387,Africa,8.97729656\r
-23/05/2020,23,5,2020,112,3,Cameroon,CM,CMR,25876387,Africa,8.25076546\r
-22/05/2020,22,5,2020,555,10,Cameroon,CM,CMR,25876387,Africa,7.81793842\r
-21/05/2020,21,5,2020,204,6,Cameroon,CM,CMR,25876387,Africa,5.67312585\r
-20/05/2020,20,5,2020,237,0,Cameroon,CM,CMR,25876387,Africa,5.50695118\r
-19/05/2020,19,5,2020,0,0,Cameroon,CM,CMR,25876387,Africa,4.59105825\r
-18/05/2020,18,5,2020,0,0,Cameroon,CM,CMR,25876387,Africa,4.69540048\r
-17/05/2020,17,5,2020,187,0,Cameroon,CM,CMR,25876387,Africa,4.69540048\r
-16/05/2020,16,5,2020,151,1,Cameroon,CM,CMR,25876387,Africa,4.00365012\r
-15/05/2020,15,5,2020,154,3,Cameroon,CM,CMR,25876387,Africa,4.33599946\r
-14/05/2020,14,5,2020,111,11,Cameroon,CM,CMR,25876387,Africa,3.74086228\r
-13/05/2020,13,5,2020,0,0,Cameroon,CM,CMR,25876387,Africa,3.41237747\r
-12/05/2020,12,5,2020,110,11,Cameroon,CM,CMR,25876387,Africa,4.12731499\r
-11/05/2020,11,5,2020,305,6,Cameroon,CM,CMR,25876387,Africa,3.70221701\r
-10/05/2020,10,5,2020,9,0,Cameroon,CM,CMR,25876387,Africa,2.92158252\r
-09/05/2020,9,5,2020,0,0,Cameroon,CM,CMR,25876387,Africa,3.3312224\r
-08/05/2020,8,5,2020,0,0,Cameroon,CM,CMR,25876387,Africa,3.33895145\r
-07/05/2020,7,5,2020,161,44,Cameroon,CM,CMR,25876387,Africa,4.25870891\r
-06/05/2020,6,5,2020,0,0,Cameroon,CM,CMR,25876387,Africa,3.63652004\r
-05/05/2020,5,5,2020,27,0,Cameroon,CM,CMR,25876387,Africa,4.20074101\r
-04/05/2020,4,5,2020,0,0,Cameroon,CM,CMR,25876387,Africa,4.1002633\r
-03/05/2020,3,5,2020,8,3,Cameroon,CM,CMR,25876387,Africa,4.1002633\r
-02/05/2020,2,5,2020,237,0,Cameroon,CM,CMR,25876387,Africa,4.06934708\r
-01/05/2020,1,5,2020,0,0,Cameroon,CM,CMR,25876387,Africa,3.77564302\r
-30/04/2020,30,4,2020,26,2,Cameroon,CM,CMR,25876387,Africa,3.77564302\r
-29/04/2020,29,4,2020,185,1,Cameroon,CM,CMR,25876387,Africa,3.67516532\r
-28/04/2020,28,4,2020,0,2,Cameroon,CM,CMR,25876387,Africa,3.09548624\r
-27/04/2020,27,4,2020,103,3,Cameroon,CM,CMR,25876387,Africa,3.09548624\r
-26/04/2020,26,4,2020,115,4,Cameroon,CM,CMR,25876387,Africa,2.69743995\r
-25/04/2020,25,4,2020,2,0,Cameroon,CM,CMR,25876387,Africa,2.31871629\r
-24/04/2020,24,4,2020,238,6,Cameroon,CM,CMR,25876387,Africa,2.59309771\r
-23/04/2020,23,4,2020,0,1,Cameroon,CM,CMR,25876387,Africa,1.67334025\r
-22/04/2020,22,4,2020,146,0,Cameroon,CM,CMR,25876387,Africa,1.84724398\r
-21/04/2020,21,4,2020,1,0,Cameroon,CM,CMR,25876387,Africa,1.38736525\r
-20/04/2020,20,4,2020,0,21,Cameroon,CM,CMR,25876387,Africa,1.41441694\r
-19/04/2020,19,4,2020,0,0,Cameroon,CM,CMR,25876387,Africa,1.78154701\r
-18/04/2020,18,4,2020,161,0,Cameroon,CM,CMR,25876387,Africa,1.95931526\r
-17/04/2020,17,4,2020,0,4,Cameroon,CM,CMR,25876387,Africa,2.25688385\r
-16/04/2020,16,4,2020,0,0,Cameroon,CM,CMR,25876387,Africa,2.40373588\r
-15/04/2020,15,4,2020,35,5,Cameroon,CM,CMR,25876387,Africa,2.55831697\r
-14/04/2020,14,4,2020,0,0,Cameroon,CM,CMR,25876387,Africa,2.6201494\r
-13/04/2020,13,4,2020,0,1,Cameroon,CM,CMR,25876387,Africa,2.78632407\r
-12/04/2020,12,4,2020,17,1,Cameroon,CM,CMR,25876387,Africa,2.78632407\r
-11/04/2020,11,4,2020,73,0,Cameroon,CM,CMR,25876387,Africa,2.76313691\r
-10/04/2020,10,4,2020,0,0,Cameroon,CM,CMR,25876387,Africa,2.48102643\r
-09/04/2020,9,4,2020,45,1,Cameroon,CM,CMR,25876387,Africa,2.54285886\r
-08/04/2020,8,4,2020,27,0,Cameroon,CM,CMR,25876387,Africa,2.36895514\r
-07/04/2020,7,4,2020,8,0,Cameroon,CM,CMR,25876387,Africa,2.32644534\r
-06/04/2020,6,4,2020,95,0,Cameroon,CM,CMR,25876387,Africa,2.40760041\r
-05/04/2020,5,4,2020,46,1,Cameroon,CM,CMR,25876387,Africa,2.04047033\r
-04/04/2020,4,4,2020,238,1,Cameroon,CM,CMR,25876387,Africa,1.86270208\r
-03/04/2020,3,4,2020,38,1,Cameroon,CM,CMR,25876387,Africa,0.99318348\r
-02/04/2020,2,4,2020,40,0,Cameroon,CM,CMR,25876387,Africa,0.86178955\r
-01/04/2020,1,4,2020,51,4,Cameroon,CM,CMR,25876387,Africa,0.70720847\r
-31/03/2020,31,3,2020,43,0,Cameroon,CM,CMR,25876387,Africa,0.53330475\r
-30/03/2020,30,3,2020,0,0,Cameroon,CM,CMR,25876387,Africa,0.36713008\r
-29/03/2020,29,3,2020,11,1,Cameroon,CM,CMR,25876387,Africa,0.37099461\r
-28/03/2020,28,3,2020,0,0,Cameroon,CM,CMR,25876387,Africa,0.33234933\r
-27/03/2020,27,3,2020,16,0,Cameroon,CM,CMR,25876387,Africa,0.33621386\r
-26/03/2020,26,3,2020,0,0,Cameroon,CM,CMR,25876387,Africa,0.27824595\r
-25/03/2020,25,3,2020,16,1,Cameroon,CM,CMR,25876387,Africa,\r
-24/03/2020,24,3,2020,29,0,Cameroon,CM,CMR,25876387,Africa,\r
-23/03/2020,23,3,2020,0,0,Cameroon,CM,CMR,25876387,Africa,\r
-22/03/2020,22,3,2020,0,0,Cameroon,CM,CMR,25876387,Africa,\r
-21/03/2020,21,3,2020,13,0,Cameroon,CM,CMR,25876387,Africa,\r
-20/03/2020,20,3,2020,4,0,Cameroon,CM,CMR,25876387,Africa,\r
-19/03/2020,19,3,2020,0,0,Cameroon,CM,CMR,25876387,Africa,\r
-18/03/2020,18,3,2020,6,0,Cameroon,CM,CMR,25876387,Africa,\r
-17/03/2020,17,3,2020,0,0,Cameroon,CM,CMR,25876387,Africa,\r
-16/03/2020,16,3,2020,1,0,Cameroon,CM,CMR,25876387,Africa,\r
-15/03/2020,15,3,2020,1,0,Cameroon,CM,CMR,25876387,Africa,\r
-09/03/2020,9,3,2020,1,0,Cameroon,CM,CMR,25876387,Africa,\r
-07/03/2020,7,3,2020,1,0,Cameroon,CM,CMR,25876387,Africa,\r
-19/08/2020,19,8,2020,282,13,Canada,CA,CAN,37411038,America,14.37276346\r
-18/08/2020,18,8,2020,785,6,Canada,CA,CAN,37411038,America,15.65046124\r
-17/08/2020,17,8,2020,198,2,Canada,CA,CAN,37411038,America,13.9450822\r
-16/08/2020,16,8,2020,237,4,Canada,CA,CAN,37411038,America,14.17763388\r
-15/08/2020,15,8,2020,418,5,Canada,CA,CAN,37411038,America,14.31128428\r
-14/08/2020,14,8,2020,405,9,Canada,CA,CAN,37411038,America,14.56522003\r
-13/08/2020,13,8,2020,423,15,Canada,CA,CAN,37411038,America,14.36207143\r
-12/08/2020,12,8,2020,289,4,Canada,CA,CAN,37411038,America,14.50374085\r
-11/08/2020,11,8,2020,666,6,Canada,CA,CAN,37411038,America,14.75500359\r
-10/08/2020,10,8,2020,245,5,Canada,CA,CAN,37411038,America,14.84321285\r
-09/08/2020,9,8,2020,236,6,Canada,CA,CAN,37411038,America,15.13724372\r
-08/08/2020,8,8,2020,424,4,Canada,CA,CAN,37411038,America,15.44196662\r
-07/08/2020,7,8,2020,374,4,Canada,CA,CAN,37411038,America,15.73599749\r
-06/08/2020,6,8,2020,395,4,Canada,CA,CAN,37411038,America,15.89103195\r
-05/08/2020,5,8,2020,760,11,Canada,CA,CAN,37411038,America,16.28663711\r
-04/08/2020,4,8,2020,147,2,Canada,CA,CAN,37411038,America,15.78143862\r
-03/08/2020,3,8,2020,285,4,Canada,CA,CAN,37411038,America,17.46008758\r
-02/08/2020,2,8,2020,287,6,Canada,CA,CAN,37411038,America,18.5159257\r
-01/08/2020,1,8,2020,513,6,Canada,CA,CAN,37411038,America,17.74877243\r
-31/07/2020,31,7,2020,329,12,Canada,CA,CAN,37411038,America,17.46008758\r
-30/07/2020,30,7,2020,476,5,Canada,CA,CAN,37411038,America,17.74877243\r
-29/07/2020,29,7,2020,383,11,Canada,CA,CAN,37411038,America,17.38791637\r
-28/07/2020,28,7,2020,699,11,Canada,CA,CAN,37411038,America,17.24891996\r
-27/07/2020,27,7,2020,355,5,Canada,CA,CAN,37411038,America,16.8907369\r
-26/07/2020,26,7,2020,350,4,Canada,CA,CAN,37411038,America,16.59403302\r
-25/07/2020,25,7,2020,534,7,Canada,CA,CAN,37411038,America,16.249215\r
-24/07/2020,24,7,2020,432,4,Canada,CA,CAN,37411038,America,15.67986432\r
-23/07/2020,23,7,2020,543,8,Canada,CA,CAN,37411038,America,15.51681084\r
-22/07/2020,22,7,2020,571,4,Canada,CA,CAN,37411038,America,14.77906066\r
-21/07/2020,21,7,2020,775,6,Canada,CA,CAN,37411038,America,13.87291098\r
-20/07/2020,20,7,2020,680,13,Canada,CA,CAN,37411038,America,12.86786002\r
-19/07/2020,19,7,2020,0,0,Canada,CA,CAN,37411038,America,11.63560337\r
-18/07/2020,18,7,2020,405,12,Canada,CA,CAN,37411038,America,12.23970316\r
-17/07/2020,17,7,2020,437,17,Canada,CA,CAN,37411038,America,12.00982448\r
-16/07/2020,16,7,2020,341,12,Canada,CA,CAN,37411038,America,12.35731551\r
-15/07/2020,15,7,2020,331,8,Canada,CA,CAN,37411038,America,11.44581981\r
-14/07/2020,14,7,2020,565,7,Canada,CA,CAN,37411038,America,11.32553446\r
-13/07/2020,13,7,2020,244,10,Canada,CA,CAN,37411038,America,11.60085427\r
-12/07/2020,12,7,2020,221,14,Canada,CA,CAN,37411038,America,11.53135607\r
-11/07/2020,11,7,2020,321,10,Canada,CA,CAN,37411038,America,11.5767972\r
-10/07/2020,10,7,2020,371,12,Canada,CA,CAN,37411038,America,11.17851902\r
-09/07/2020,9,7,2020,267,26,Canada,CA,CAN,37411038,America,11.17317301\r
-08/07/2020,8,7,2020,232,18,Canada,CA,CAN,37411038,America,11.2052491\r
-07/07/2020,7,7,2020,399,9,Canada,CA,CAN,37411038,America,11.45651185\r
-06/07/2020,6,7,2020,219,10,Canada,CA,CAN,37411038,America,11.22128715\r
-05/07/2020,5,7,2020,226,11,Canada,CA,CAN,37411038,America,11.48591493\r
-04/07/2020,4,7,2020,319,21,Canada,CA,CAN,37411038,America,11.92428823\r
-03/07/2020,3,7,2020,567,51,Canada,CA,CAN,37411038,America,12.16485894\r
-02/07/2020,2,7,2020,0,0,Canada,CA,CAN,37411038,America,11.63025736\r
-01/07/2020,1,7,2020,286,25,Canada,CA,CAN,37411038,America,12.66203841\r
-30/06/2020,30,6,2020,668,44,Canada,CA,CAN,37411038,America,12.75292068\r
-29/06/2020,29,6,2020,218,6,Canada,CA,CAN,37411038,America,11.92963424\r
-28/06/2020,28,6,2020,238,8,Canada,CA,CAN,37411038,America,12.3546425\r
-27/06/2020,27,6,2020,172,4,Canada,CA,CAN,37411038,America,12.96676131\r
-26/06/2020,26,6,2020,369,20,Canada,CA,CAN,37411038,America,13.61095621\r
-25/06/2020,25,6,2020,279,30,Canada,CA,CAN,37411038,America,13.70718449\r
-24/06/2020,24,6,2020,326,18,Canada,CA,CAN,37411038,America,14.22307502\r
-23/06/2020,23,6,2020,311,6,Canada,CA,CAN,37411038,America,14.44493467\r
-22/06/2020,22,6,2020,318,20,Canada,CA,CAN,37411038,America,15.07041852\r
-21/06/2020,21,6,2020,390,64,Canada,CA,CAN,37411038,America,15.93647308\r
-20/06/2020,20,6,2020,409,46,Canada,CA,CAN,37411038,America,16.8239117\r
-19/06/2020,19,6,2020,367,46,Canada,CA,CAN,37411038,America,17.35851328\r
-18/06/2020,18,6,2020,386,41,Canada,CA,CAN,37411038,America,18.09091745\r
-17/06/2020,17,6,2020,320,38,Canada,CA,CAN,37411038,America,18.86341673\r
-16/06/2020,16,6,2020,360,29,Canada,CA,CAN,37411038,America,19.89252477\r
-15/06/2020,15,6,2020,377,39,Canada,CA,CAN,37411038,America,20.95638191\r
-14/06/2020,14,6,2020,467,58,Canada,CA,CAN,37411038,America,21.97212491\r
-13/06/2020,13,6,2020,413,55,Canada,CA,CAN,37411038,America,22.78739232\r
-12/06/2020,12,6,2020,405,34,Canada,CA,CAN,37411038,America,24.10518521\r
-11/06/2020,11,6,2020,472,63,Canada,CA,CAN,37411038,America,25.67691386\r
-10/06/2020,10,6,2020,409,62,Canada,CA,CAN,37411038,America,26.74611701\r
-09/06/2020,9,6,2020,545,35,Canada,CA,CAN,37411038,America,28.15479218\r
-08/06/2020,8,6,2020,642,27,Canada,CA,CAN,37411038,America,29.40308686\r
-07/06/2020,7,6,2020,722,70,Canada,CA,CAN,37411038,America,30.56851831\r
-06/06/2020,6,6,2020,609,66,Canada,CA,CAN,37411038,America,31.68850862\r
-05/06/2020,5,6,2020,641,139,Canada,CA,CAN,37411038,America,33.15064394\r
-04/06/2020,4,6,2020,675,103,Canada,CA,CAN,37411038,America,34.70366152\r
-03/06/2020,3,6,2020,705,69,Canada,CA,CAN,37411038,America,35.54565901\r
-02/06/2020,2,6,2020,758,31,Canada,CA,CAN,37411038,America,36.44111666\r
-01/06/2020,1,6,2020,757,222,Canada,CA,CAN,37411038,America,37.27509512\r
-31/05/2020,31,5,2020,772,94,Canada,CA,CAN,37411038,America,38.29351113\r
-30/05/2020,30,5,2020,906,102,Canada,CA,CAN,37411038,America,39.57388191\r
-29/05/2020,29,5,2020,993,112,Canada,CA,CAN,37411038,America,40.36241924\r
-28/05/2020,28,5,2020,872,126,Canada,CA,CAN,37411038,America,40.70991027\r
-27/05/2020,27,5,2020,936,94,Canada,CA,CAN,37411038,America,41.37548923\r
-26/05/2020,26,5,2020,1012,121,Canada,CA,CAN,37411038,America,42.01701113\r
-25/05/2020,25,5,2020,1078,69,Canada,CA,CAN,37411038,America,42.34044508\r
-24/05/2020,24,5,2020,1141,105,Canada,CA,CAN,37411038,America,42.52220962\r
-23/05/2020,23,5,2020,1156,98,Canada,CA,CAN,37411038,America,42.86168162\r
-22/05/2020,22,5,2020,1222,122,Canada,CA,CAN,37411038,America,43.81327244\r
-21/05/2020,21,5,2020,990,118,Canada,CA,CAN,37411038,America,44.35856605\r
-20/05/2020,20,5,2020,1040,70,Canada,CA,CAN,37411038,America,45.58814968\r
-19/05/2020,19,5,2020,1070,60,Canada,CA,CAN,37411038,America,46.21363353\r
-18/05/2020,18,5,2020,1138,103,Canada,CA,CAN,37411038,America,46.82307933\r
-17/05/2020,17,5,2020,1251,117,Canada,CA,CAN,37411038,America,51.15869814\r
-16/05/2020,16,5,2020,1201,90,Canada,CA,CAN,37411038,America,52.23324731\r
-15/05/2020,15,5,2020,1123,168,Canada,CA,CAN,37411038,America,53.90120424\r
-14/05/2020,14,5,2020,1121,135,Canada,CA,CAN,37411038,America,55.30720639\r
-13/05/2020,13,5,2020,1176,176,Canada,CA,CAN,37411038,America,56.51273295\r
-12/05/2020,12,5,2020,1133,122,Canada,CA,CAN,37411038,America,57.44828572\r
-11/05/2020,11,5,2020,1146,178,Canada,CA,CAN,37411038,America,58.70994544\r
-10/05/2020,10,5,2020,1268,124,Canada,CA,CAN,37411038,America,59.77112958\r
-09/05/2020,9,5,2020,1512,161,Canada,CA,CAN,37411038,America,60.29503913\r
-08/05/2020,8,5,2020,1426,176,Canada,CA,CAN,37411038,America,61.00605923\r
-07/05/2020,7,5,2020,1450,189,Canada,CA,CAN,37411038,America,62.32652513\r
-06/05/2020,6,5,2020,1274,189,Canada,CA,CAN,37411038,America,63.17119562\r
-05/05/2020,5,5,2020,1298,172,Canada,CA,CAN,37411038,America,64.01586612\r
-04/05/2020,4,5,2020,2760,116,Canada,CA,CAN,37411038,America,66.01527603\r
-03/05/2020,3,5,2020,1653,175,Canada,CA,CAN,37411038,America,62.47621357\r
-02/05/2020,2,5,2020,1825,207,Canada,CA,CAN,37411038,America,61.98438012\r
-01/05/2020,1,5,2020,1649,188,Canada,CA,CAN,37411038,America,61.89349785\r
-30/04/2020,30,4,2020,1572,137,Canada,CA,CAN,37411038,America,62.07526239\r
-29/04/2020,29,4,2020,1526,152,Canada,CA,CAN,37411038,America,61.39631838\r
-28/04/2020,28,4,2020,1605,147,Canada,CA,CAN,37411038,America,61.01407825\r
-27/04/2020,27,4,2020,1543,95,Canada,CA,CAN,37411038,America,60.19346483\r
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-25/04/2020,25,4,2020,1778,156,Canada,CA,CAN,37411038,America,58.12188371\r
-24/04/2020,24,4,2020,1920,172,Canada,CA,CAN,37411038,America,57.0713916\r
-23/04/2020,23,4,2020,1766,140,Canada,CA,CAN,37411038,America,55.87923008\r
-22/04/2020,22,4,2020,1590,144,Canada,CA,CAN,37411038,America,54.87685212\r
-21/04/2020,21,4,2020,2046,110,Canada,CA,CAN,37411038,America,53.91456928\r
-20/04/2020,20,4,2020,1436,113,Canada,CA,CAN,37411038,America,51.53826526\r
-19/04/2020,19,4,2020,1469,158,Canada,CA,CAN,37411038,America,52.01406066\r
-18/04/2020,18,4,2020,1791,116,Canada,CA,CAN,37411038,America,51.73072183\r
-17/04/2020,17,4,2020,1717,183,Canada,CA,CAN,37411038,America,50.28729756\r
-16/04/2020,16,4,2020,1318,107,Canada,CA,CAN,37411038,America,50.16968521\r
-15/04/2020,15,4,2020,1383,123,Canada,CA,CAN,37411038,America,49.47737617\r
-14/04/2020,14,4,2020,1298,63,Canada,CA,CAN,37411038,America,48.75299103\r
-13/04/2020,13,4,2020,1064,64,Canada,CA,CAN,37411038,America,48.40817301\r
-12/04/2020,12,4,2020,1168,84,Canada,CA,CAN,37411038,America,47.88693647\r
-11/04/2020,11,4,2020,1385,60,Canada,CA,CAN,37411038,America,46.66537186\r
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-25/03/2020,25,3,2020,313,3,Canada,CA,CAN,37411038,America,4.98783274\r
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-25/02/2020,25,2,2020,2,0,Canada,CA,CAN,37411038,America,0.01069203\r
-24/02/2020,24,2,2020,0,0,Canada,CA,CAN,37411038,America,0.00534602\r
-23/02/2020,23,2,2020,0,0,Canada,CA,CAN,37411038,America,0.00534602\r
-22/02/2020,22,2,2020,0,0,Canada,CA,CAN,37411038,America,0.00534602\r
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-31/05/2020,31,5,2020,16,0,Cape_Verde,CV,CPV,549936,Africa,16.91105874\r
-30/05/2020,30,5,2020,15,0,Cape_Verde,CV,CPV,549936,Africa,14.36530796\r
-29/05/2020,29,5,2020,0,0,Cape_Verde,CV,CPV,549936,Africa,13.6379506\r
-28/05/2020,28,5,2020,0,0,Cape_Verde,CV,CPV,549936,Africa,18.36577347\r
-27/05/2020,27,5,2020,0,1,Cape_Verde,CV,CPV,549936,Africa,21.82072096\r
-26/05/2020,26,5,2020,10,0,Cape_Verde,CV,CPV,549936,Africa,23.63911437\r
-25/05/2020,25,5,2020,9,0,Cape_Verde,CV,CPV,549936,Africa,24.36647173\r
-24/05/2020,24,5,2020,9,0,Cape_Verde,CV,CPV,549936,Africa,24.54831108\r
-23/05/2020,23,5,2020,6,0,Cape_Verde,CV,CPV,549936,Africa,24.00279305\r
-22/05/2020,22,5,2020,7,0,Cape_Verde,CV,CPV,549936,Africa,25.0938291\r
-21/05/2020,21,5,2020,14,0,Cape_Verde,CV,CPV,549936,Africa,28.73061593\r
-20/05/2020,20,5,2020,7,0,Cape_Verde,CV,CPV,549936,Africa,27.09406185\r
-19/05/2020,19,5,2020,0,0,Cape_Verde,CV,CPV,549936,Africa,27.82141922\r
-18/05/2020,18,5,2020,0,0,Cape_Verde,CV,CPV,549936,Africa,29.63981263\r
-17/05/2020,17,5,2020,2,1,Cape_Verde,CV,CPV,549936,Africa,32.00372407\r
-16/05/2020,16,5,2020,11,0,Cape_Verde,CV,CPV,549936,Africa,36.91338628\r
-15/05/2020,15,5,2020,26,0,Cape_Verde,CV,CPV,549936,Africa,35.27683221\r
-14/05/2020,14,5,2020,19,0,Cape_Verde,CV,CPV,549936,Africa,32.00372407\r
-13/05/2020,13,5,2020,10,0,Cape_Verde,CV,CPV,549936,Africa,28.54877658\r
-12/05/2020,12,5,2020,14,0,Cape_Verde,CV,CPV,549936,Africa,27.45774054\r
-11/05/2020,11,5,2020,10,0,Cape_Verde,CV,CPV,549936,Africa,25.45750778\r
-10/05/2020,10,5,2020,6,0,Cape_Verde,CV,CPV,549936,Africa,26.54854383\r
-09/05/2020,9,5,2020,12,0,Cape_Verde,CV,CPV,549936,Africa,25.82118647\r
-08/05/2020,8,5,2020,27,0,Cape_Verde,CV,CPV,549936,Africa,24.73015042\r
-07/05/2020,7,5,2020,5,0,Cape_Verde,CV,CPV,549936,Africa,21.45704227\r
-06/05/2020,6,5,2020,11,0,Cape_Verde,CV,CPV,549936,Africa,21.63888162\r
-05/05/2020,5,5,2020,10,0,Cape_Verde,CV,CPV,549936,Africa,19.63864886\r
-04/05/2020,4,5,2020,13,0,Cape_Verde,CV,CPV,549936,Africa,18.9112915\r
-03/05/2020,3,5,2020,29,0,Cape_Verde,CV,CPV,549936,Africa,17.09289808\r
-02/05/2020,2,5,2020,2,1,Cape_Verde,CV,CPV,549936,Africa,12.18323587\r
-01/05/2020,1,5,2020,8,0,Cape_Verde,CV,CPV,549936,Africa,12.00139653\r
-30/04/2020,30,4,2020,0,0,Cape_Verde,CV,CPV,549936,Africa,10.5466818\r
-29/04/2020,29,4,2020,4,0,Cape_Verde,CV,CPV,549936,Africa,18.54761281\r
-28/04/2020,28,4,2020,3,0,Cape_Verde,CV,CPV,549936,Africa,18.00209479\r
-27/04/2020,27,4,2020,16,0,Cape_Verde,CV,CPV,549936,Africa,17.45657677\r
-26/04/2020,26,4,2020,2,0,Cape_Verde,CV,CPV,549936,Africa,14.91082599\r
-25/04/2020,25,4,2020,6,0,Cape_Verde,CV,CPV,549936,Africa,14.72898665\r
-24/04/2020,24,4,2020,9,0,Cape_Verde,CV,CPV,549936,Africa,13.6379506\r
-23/04/2020,23,4,2020,6,0,Cape_Verde,CV,CPV,549936,Africa,12.00139653\r
-22/04/2020,22,4,2020,0,0,Cape_Verde,CV,CPV,549936,Africa,10.91036048\r
-21/04/2020,21,4,2020,6,0,Cape_Verde,CV,CPV,549936,Africa,10.91036048\r
-20/04/2020,20,4,2020,3,0,Cape_Verde,CV,CPV,549936,Africa,9.81932443\r
-19/04/2020,19,4,2020,2,0,Cape_Verde,CV,CPV,549936,Africa,9.27380641\r
-18/04/2020,18,4,2020,1,0,Cape_Verde,CV,CPV,549936,Africa,9.09196707\r
-17/04/2020,17,4,2020,0,0,Cape_Verde,CV,CPV,549936,Africa,8.91012772\r
-16/04/2020,16,4,2020,44,0,Cape_Verde,CV,CPV,549936,Africa,8.91012772\r
-15/04/2020,15,4,2020,1,0,Cape_Verde,CV,CPV,549936,Africa,0.90919671\r
-14/04/2020,14,4,2020,0,0,Cape_Verde,CV,CPV,549936,Africa,0.90919671\r
-13/04/2020,13,4,2020,2,0,Cape_Verde,CV,CPV,549936,Africa,0.90919671\r
-12/04/2020,12,4,2020,1,0,Cape_Verde,CV,CPV,549936,Africa,0.54551802\r
-11/04/2020,11,4,2020,0,0,Cape_Verde,CV,CPV,549936,Africa,0.36367868\r
-10/04/2020,10,4,2020,0,0,Cape_Verde,CV,CPV,549936,Africa,0.36367868\r
-09/04/2020,9,4,2020,0,0,Cape_Verde,CV,CPV,549936,Africa,0.54551802\r
-08/04/2020,8,4,2020,0,0,Cape_Verde,CV,CPV,549936,Africa,0.72735737\r
-07/04/2020,7,4,2020,0,0,Cape_Verde,CV,CPV,549936,Africa,0.72735737\r
-06/04/2020,6,4,2020,0,0,Cape_Verde,CV,CPV,549936,Africa,0.72735737\r
-05/04/2020,5,4,2020,1,0,Cape_Verde,CV,CPV,549936,Africa,0.72735737\r
-04/04/2020,4,4,2020,0,0,Cape_Verde,CV,CPV,549936,Africa,0.72735737\r
-03/04/2020,3,4,2020,0,0,Cape_Verde,CV,CPV,549936,Africa,1.09103605\r
-02/04/2020,2,4,2020,0,0,Cape_Verde,CV,CPV,549936,Africa,\r
-01/04/2020,1,4,2020,1,0,Cape_Verde,CV,CPV,549936,Africa,\r
-31/03/2020,31,3,2020,0,0,Cape_Verde,CV,CPV,549936,Africa,\r
-30/03/2020,30,3,2020,0,0,Cape_Verde,CV,CPV,549936,Africa,\r
-29/03/2020,29,3,2020,0,0,Cape_Verde,CV,CPV,549936,Africa,\r
-28/03/2020,28,3,2020,0,0,Cape_Verde,CV,CPV,549936,Africa,\r
-27/03/2020,27,3,2020,1,0,Cape_Verde,CV,CPV,549936,Africa,\r
-26/03/2020,26,3,2020,1,0,Cape_Verde,CV,CPV,549936,Africa,\r
-25/03/2020,25,3,2020,0,1,Cape_Verde,CV,CPV,549936,Africa,\r
-24/03/2020,24,3,2020,0,0,Cape_Verde,CV,CPV,549936,Africa,\r
-23/03/2020,23,3,2020,0,0,Cape_Verde,CV,CPV,549936,Africa,\r
-22/03/2020,22,3,2020,1,0,Cape_Verde,CV,CPV,549936,Africa,\r
-21/03/2020,21,3,2020,2,0,Cape_Verde,CV,CPV,549936,Africa,\r
-10/03/2020,10,3,2020,-9,1,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-02/03/2020,2,3,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-01/03/2020,1,3,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-29/02/2020,29,2,2020,0,2,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-28/02/2020,28,2,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-27/02/2020,27,2,2020,14,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-26/02/2020,26,2,2020,0,1,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-25/02/2020,25,2,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-24/02/2020,24,2,2020,57,1,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-23/02/2020,23,2,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-22/02/2020,22,2,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-21/02/2020,21,2,2020,13,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-20/02/2020,20,2,2020,79,2,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-19/02/2020,19,2,2020,88,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-18/02/2020,18,2,2020,99,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-17/02/2020,17,2,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-16/02/2020,16,2,2020,134,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-15/02/2020,15,2,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-14/02/2020,14,2,2020,47,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-13/02/2020,13,2,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-12/02/2020,12,2,2020,39,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-11/02/2020,11,2,2020,65,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-10/02/2020,10,2,2020,6,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-09/02/2020,9,2,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-08/02/2020,8,2,2020,3,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-07/02/2020,7,2,2020,41,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-06/02/2020,6,2,2020,10,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-05/02/2020,5,2,2020,10,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-04/02/2020,4,2,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-03/02/2020,3,2,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-02/02/2020,2,2,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-01/02/2020,1,2,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-31/01/2020,31,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-30/01/2020,30,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-29/01/2020,29,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-28/01/2020,28,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-27/01/2020,27,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-26/01/2020,26,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-25/01/2020,25,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-24/01/2020,24,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-23/01/2020,23,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-22/01/2020,22,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-21/01/2020,21,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-20/01/2020,20,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-19/01/2020,19,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-18/01/2020,18,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-17/01/2020,17,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-16/01/2020,16,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-15/01/2020,15,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-14/01/2020,14,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-13/01/2020,13,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-12/01/2020,12,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-11/01/2020,11,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-10/01/2020,10,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-09/01/2020,9,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-08/01/2020,8,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-07/01/2020,7,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-06/01/2020,6,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-05/01/2020,5,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-04/01/2020,4,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-03/01/2020,3,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-02/01/2020,2,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-01/01/2020,1,1,2020,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-31/12/2019,31,12,2019,0,0,Cases_on_an_international_conveyance_Japan,JPG11668,,,Other,\r
-19/08/2020,19,8,2020,0,0,Cayman_Islands,KY,CYM,64948,America,0\r
-18/08/2020,18,8,2020,0,0,Cayman_Islands,KY,CYM,64948,America,0\r
-17/08/2020,17,8,2020,0,0,Cayman_Islands,KY,CYM,64948,America,0\r
-16/08/2020,16,8,2020,0,0,Cayman_Islands,KY,CYM,64948,America,0\r
-15/08/2020,15,8,2020,0,0,Cayman_Islands,KY,CYM,64948,America,0\r
-14/08/2020,14,8,2020,0,0,Cayman_Islands,KY,CYM,64948,America,0\r
-13/08/2020,13,8,2020,0,0,Cayman_Islands,KY,CYM,64948,America,0\r
-12/08/2020,12,8,2020,0,0,Cayman_Islands,KY,CYM,64948,America,0\r
-11/08/2020,11,8,2020,0,0,Cayman_Islands,KY,CYM,64948,America,0\r
-10/08/2020,10,8,2020,0,0,Cayman_Islands,KY,CYM,64948,America,0\r
-09/08/2020,9,8,2020,0,0,Cayman_Islands,KY,CYM,64948,America,0\r
-08/08/2020,8,8,2020,0,0,Cayman_Islands,KY,CYM,64948,America,0\r
-07/08/2020,7,8,2020,0,0,Cayman_Islands,KY,CYM,64948,America,0\r
-06/08/2020,6,8,2020,0,0,Cayman_Islands,KY,CYM,64948,America,0\r
-05/08/2020,5,8,2020,0,0,Cayman_Islands,KY,CYM,64948,America,0\r
-04/08/2020,4,8,2020,0,0,Cayman_Islands,KY,CYM,64948,America,0\r
-03/08/2020,3,8,2020,0,0,Cayman_Islands,KY,CYM,64948,America,0\r
-02/08/2020,2,8,2020,0,0,Cayman_Islands,KY,CYM,64948,America,0\r
-01/08/2020,1,8,2020,0,0,Cayman_Islands,KY,CYM,64948,America,0\r
-31/07/2020,31,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,0\r
-30/07/2020,30,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,0\r
-29/07/2020,29,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,0\r
-28/07/2020,28,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,3.07938659\r
-27/07/2020,27,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,3.07938659\r
-26/07/2020,26,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,3.07938659\r
-25/07/2020,25,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,3.07938659\r
-24/07/2020,24,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,3.07938659\r
-23/07/2020,23,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,3.07938659\r
-22/07/2020,22,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,3.07938659\r
-21/07/2020,21,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,3.07938659\r
-20/07/2020,20,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,3.07938659\r
-19/07/2020,19,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,3.07938659\r
-18/07/2020,18,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,3.07938659\r
-17/07/2020,17,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,3.07938659\r
-16/07/2020,16,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,3.07938659\r
-15/07/2020,15,7,2020,2,0,Cayman_Islands,KY,CYM,64948,America,4.61907988\r
-14/07/2020,14,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,3.07938659\r
-13/07/2020,13,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,7.69846647\r
-12/07/2020,12,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,7.69846647\r
-11/07/2020,11,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,7.69846647\r
-10/07/2020,10,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,7.69846647\r
-09/07/2020,9,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,7.69846647\r
-08/07/2020,8,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,9.23815976\r
-07/07/2020,7,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,9.23815976\r
-06/07/2020,6,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,9.23815976\r
-05/07/2020,5,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,9.23815976\r
-04/07/2020,4,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,9.23815976\r
-03/07/2020,3,7,2020,0,0,Cayman_Islands,KY,CYM,64948,America,12.31754634\r
-02/07/2020,2,7,2020,1,0,Cayman_Islands,KY,CYM,64948,America,12.31754634\r
-01/07/2020,1,7,2020,1,0,Cayman_Islands,KY,CYM,64948,America,10.77785305\r
-30/06/2020,30,6,2020,3,0,Cayman_Islands,KY,CYM,64948,America,18.47631952\r
-29/06/2020,29,6,2020,0,0,Cayman_Islands,KY,CYM,64948,America,13.85723964\r
-28/06/2020,28,6,2020,0,0,Cayman_Islands,KY,CYM,64948,America,13.85723964\r
-27/06/2020,27,6,2020,0,0,Cayman_Islands,KY,CYM,64948,America,13.85723964\r
-26/06/2020,26,6,2020,0,0,Cayman_Islands,KY,CYM,64948,America,24.63509269\r
-25/06/2020,25,6,2020,1,0,Cayman_Islands,KY,CYM,64948,America,24.63509269\r
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-29/04/2020,29,4,2020,0,0,Central_African_Republic,CF,CAF,4745179,Africa,0.8218868\r
-28/04/2020,28,4,2020,31,0,Central_African_Republic,CF,CAF,4745179,Africa,0.8218868\r
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-23/04/2020,23,4,2020,2,0,Central_African_Republic,CF,CAF,4745179,Africa,0.12644412\r
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-19/04/2020,19,4,2020,0,0,Central_African_Republic,CF,CAF,4745179,Africa,0.06322206\r
-18/04/2020,18,4,2020,0,0,Central_African_Republic,CF,CAF,4745179,Africa,0.08429608\r
-17/04/2020,17,4,2020,1,0,Central_African_Republic,CF,CAF,4745179,Africa,0.08429608\r
-16/04/2020,16,4,2020,0,0,Central_African_Republic,CF,CAF,4745179,Africa,0.06322206\r
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-12/04/2020,12,4,2020,0,0,Central_African_Republic,CF,CAF,4745179,Africa,0.1053701\r
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-24/03/2020,24,3,2020,0,0,Central_African_Republic,CF,CAF,4745179,Africa,\r
-23/03/2020,23,3,2020,1,0,Central_African_Republic,CF,CAF,4745179,Africa,\r
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-18/08/2020,18,8,2020,3,0,Chad,TD,TCD,15946882,Africa,0.14422882\r
-17/08/2020,17,8,2020,4,0,Chad,TD,TCD,15946882,Africa,0.12541637\r
-16/08/2020,16,8,2020,1,0,Chad,TD,TCD,15946882,Africa,0.10033309\r
-15/08/2020,15,8,2020,2,0,Chad,TD,TCD,15946882,Africa,0.09406227\r
-14/08/2020,14,8,2020,0,0,Chad,TD,TCD,15946882,Africa,0.08779146\r
-13/08/2020,13,8,2020,3,0,Chad,TD,TCD,15946882,Africa,0.14422882\r
-12/08/2020,12,8,2020,1,0,Chad,TD,TCD,15946882,Africa,0.12541637\r
-11/08/2020,11,8,2020,1,0,Chad,TD,TCD,15946882,Africa,0.14422882\r
-10/08/2020,10,8,2020,2,0,Chad,TD,TCD,15946882,Africa,0.18185373\r
-09/08/2020,9,8,2020,0,0,Chad,TD,TCD,15946882,Africa,0.16931209\r
-08/08/2020,8,8,2020,0,0,Chad,TD,TCD,15946882,Africa,0.16931209\r
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-06/08/2020,6,8,2020,1,0,Chad,TD,TCD,15946882,Africa,0.31354092\r
-05/08/2020,5,8,2020,2,0,Chad,TD,TCD,15946882,Africa,0.3072701\r
-04/08/2020,4,8,2020,0,0,Chad,TD,TCD,15946882,Africa,0.29472846\r
-03/08/2020,3,8,2020,0,0,Chad,TD,TCD,15946882,Africa,0.29472846\r
-02/08/2020,2,8,2020,0,0,Chad,TD,TCD,15946882,Africa,0.29472846\r
-01/08/2020,1,8,2020,1,0,Chad,TD,TCD,15946882,Africa,0.3072701\r
-31/07/2020,31,7,2020,9,0,Chad,TD,TCD,15946882,Africa,0.3072701\r
-30/07/2020,30,7,2020,0,0,Chad,TD,TCD,15946882,Africa,0.25710355\r
-29/07/2020,29,7,2020,4,0,Chad,TD,TCD,15946882,Africa,0.26337437\r
-28/07/2020,28,7,2020,7,0,Chad,TD,TCD,15946882,Africa,0.26337437\r
-27/07/2020,27,7,2020,0,0,Chad,TD,TCD,15946882,Africa,0.21947864\r
-26/07/2020,26,7,2020,0,0,Chad,TD,TCD,15946882,Africa,0.25710355\r
-25/07/2020,25,7,2020,0,0,Chad,TD,TCD,15946882,Africa,0.25710355\r
-24/07/2020,24,7,2020,26,0,Chad,TD,TCD,15946882,Africa,0.26337437\r
-23/07/2020,23,7,2020,0,0,Chad,TD,TCD,15946882,Africa,0.10033309\r
-22/07/2020,22,7,2020,0,0,Chad,TD,TCD,15946882,Africa,0.10033309\r
-21/07/2020,21,7,2020,0,0,Chad,TD,TCD,15946882,Africa,0.10660391\r
-20/07/2020,20,7,2020,0,0,Chad,TD,TCD,15946882,Africa,0.10660391\r
-19/07/2020,19,7,2020,2,0,Chad,TD,TCD,15946882,Africa,0.11287473\r
-18/07/2020,18,7,2020,1,0,Chad,TD,TCD,15946882,Africa,0.10033309\r
-17/07/2020,17,7,2020,1,0,Chad,TD,TCD,15946882,Africa,0.11287473\r
-16/07/2020,16,7,2020,1,0,Chad,TD,TCD,15946882,Africa,0.11914555\r
-15/07/2020,15,7,2020,4,0,Chad,TD,TCD,15946882,Africa,0.11287473\r
-14/07/2020,14,7,2020,0,0,Chad,TD,TCD,15946882,Africa,0.08779146\r
-13/07/2020,13,7,2020,6,1,Chad,TD,TCD,15946882,Africa,0.08779146\r
-12/07/2020,12,7,2020,0,0,Chad,TD,TCD,15946882,Africa,0.05643736\r
-11/07/2020,11,7,2020,1,0,Chad,TD,TCD,15946882,Africa,0.05643736\r
-10/07/2020,10,7,2020,0,0,Chad,TD,TCD,15946882,Africa,0.06270818\r
-09/07/2020,9,7,2020,0,0,Chad,TD,TCD,15946882,Africa,0.08152064\r
-08/07/2020,8,7,2020,1,0,Chad,TD,TCD,15946882,Africa,0.08152064\r
-07/07/2020,7,7,2020,0,0,Chad,TD,TCD,15946882,Africa,0.08779146\r
-06/07/2020,6,7,2020,1,0,Chad,TD,TCD,15946882,Africa,0.08779146\r
-05/07/2020,5,7,2020,0,0,Chad,TD,TCD,15946882,Africa,0.08152064\r
-04/07/2020,4,7,2020,3,0,Chad,TD,TCD,15946882,Africa,0.08152064\r
-03/07/2020,3,7,2020,2,0,Chad,TD,TCD,15946882,Africa,0.08779146\r
-02/07/2020,2,7,2020,0,0,Chad,TD,TCD,15946882,Africa,0.07524982\r
-01/07/2020,1,7,2020,0,0,Chad,TD,TCD,15946882,Africa,0.08152064\r
-30/06/2020,30,6,2020,0,0,Chad,TD,TCD,15946882,Africa,0.10033309\r
-29/06/2020,29,6,2020,1,0,Chad,TD,TCD,15946882,Africa,0.10033309\r
-28/06/2020,28,6,2020,0,0,Chad,TD,TCD,15946882,Africa,0.10660391\r
-27/06/2020,27,6,2020,2,0,Chad,TD,TCD,15946882,Africa,0.10660391\r
-26/06/2020,26,6,2020,3,0,Chad,TD,TCD,15946882,Africa,0.09406227\r
-25/06/2020,25,6,2020,0,0,Chad,TD,TCD,15946882,Africa,0.08779146\r
-24/06/2020,24,6,2020,2,0,Chad,TD,TCD,15946882,Africa,0.10033309\r
-23/06/2020,23,6,2020,0,0,Chad,TD,TCD,15946882,Africa,0.11914555\r
-22/06/2020,22,6,2020,0,0,Chad,TD,TCD,15946882,Africa,0.13168718\r
-21/06/2020,21,6,2020,0,0,Chad,TD,TCD,15946882,Africa,0.137958\r
-20/06/2020,20,6,2020,4,0,Chad,TD,TCD,15946882,Africa,0.137958\r
-19/06/2020,19,6,2020,0,0,Chad,TD,TCD,15946882,Africa,0.16304128\r
-18/06/2020,18,6,2020,1,0,Chad,TD,TCD,15946882,Africa,0.21320782\r
-17/06/2020,17,6,2020,3,1,Chad,TD,TCD,15946882,Africa,0.31354092\r
-16/06/2020,16,6,2020,0,0,Chad,TD,TCD,15946882,Africa,0.3762491\r
-15/06/2020,15,6,2020,2,1,Chad,TD,TCD,15946882,Africa,0.45149892\r
-14/06/2020,14,6,2020,0,0,Chad,TD,TCD,15946882,Africa,0.55810283\r
-13/06/2020,13,6,2020,0,0,Chad,TD,TCD,15946882,Africa,0.55810283\r
-12/06/2020,12,6,2020,2,0,Chad,TD,TCD,15946882,Africa,0.76503984\r
-11/06/2020,11,6,2020,2,1,Chad,TD,TCD,15946882,Africa,0.8214772\r
-10/06/2020,10,6,2020,5,1,Chad,TD,TCD,15946882,Africa,0.90299784\r
-09/06/2020,9,6,2020,2,1,Chad,TD,TCD,15946882,Africa,0.95316439\r
-08/06/2020,8,6,2020,1,0,Chad,TD,TCD,15946882,Africa,1.01587257\r
-07/06/2020,7,6,2020,0,1,Chad,TD,TCD,15946882,Africa,1.17891385\r
-06/06/2020,6,6,2020,8,2,Chad,TD,TCD,15946882,Africa,1.41093412\r
-05/06/2020,5,6,2020,8,0,Chad,TD,TCD,15946882,Africa,1.5049964\r
-04/06/2020,4,6,2020,17,0,Chad,TD,TCD,15946882,Africa,1.59905867\r
-03/06/2020,3,6,2020,13,0,Chad,TD,TCD,15946882,Africa,1.61787113\r
-02/06/2020,2,6,2020,12,1,Chad,TD,TCD,15946882,Africa,1.69939177\r
-01/06/2020,1,6,2020,19,0,Chad,TD,TCD,15946882,Africa,1.72447504\r
-31/05/2020,31,5,2020,0,0,Chad,TD,TCD,15946882,Africa,1.78718322\r
-30/05/2020,30,5,2020,33,0,Chad,TD,TCD,15946882,Africa,2.07564087\r
-29/05/2020,29,5,2020,11,1,Chad,TD,TCD,15946882,Africa,2.05055759\r
-28/05/2020,28,5,2020,15,2,Chad,TD,TCD,15946882,Africa,2.15089069\r
-27/05/2020,27,5,2020,13,1,Chad,TD,TCD,15946882,Africa,2.15089069\r
-26/05/2020,26,5,2020,12,1,Chad,TD,TCD,15946882,Africa,2.28884869\r
-25/05/2020,25,5,2020,27,0,Chad,TD,TCD,15946882,Africa,2.21359887\r
-24/05/2020,24,5,2020,37,1,Chad,TD,TCD,15946882,Africa,2.04428678\r
-23/05/2020,23,5,2020,23,1,Chad,TD,TCD,15946882,Africa,2.20105723\r
-22/05/2020,22,5,2020,23,1,Chad,TD,TCD,15946882,Africa,2.10072414\r
-21/05/2020,21,5,2020,20,1,Chad,TD,TCD,15946882,Africa,2.47697324\r
-20/05/2020,20,5,2020,26,3,Chad,TD,TCD,15946882,Africa,2.35155687\r
-19/05/2020,19,5,2020,16,0,Chad,TD,TCD,15946882,Africa,2.52086897\r
-18/05/2020,18,5,2020,29,3,Chad,TD,TCD,15946882,Africa,2.42053588\r
-17/05/2020,17,5,2020,46,2,Chad,TD,TCD,15946882,Africa,2.23868214\r
-16/05/2020,16,5,2020,29,2,Chad,TD,TCD,15946882,Africa,2.22614051\r
-15/05/2020,15,5,2020,27,4,Chad,TD,TCD,15946882,Africa,2.04428678\r
-14/05/2020,14,5,2020,15,2,Chad,TD,TCD,15946882,Africa,2.00666187\r
-13/05/2020,13,5,2020,35,9,Chad,TD,TCD,15946882,Africa,1.91259959\r
-12/05/2020,12,5,2020,0,0,Chad,TD,TCD,15946882,Africa,1.73074586\r
-11/05/2020,11,5,2020,0,0,Chad,TD,TCD,15946882,Africa,1.73074586\r
-10/05/2020,10,5,2020,62,3,Chad,TD,TCD,15946882,Africa,1.76837077\r
-09/05/2020,9,5,2020,7,1,Chad,TD,TCD,15946882,Africa,1.37958003\r
-08/05/2020,8,5,2020,83,10,Chad,TD,TCD,15946882,Africa,1.3356843\r
-07/05/2020,7,5,2020,0,0,Chad,TD,TCD,15946882,Africa,0.85283129\r
-06/05/2020,6,5,2020,53,7,Chad,TD,TCD,15946882,Africa,0.85283129\r
-05/05/2020,5,5,2020,0,0,Chad,TD,TCD,15946882,Africa,0.52674874\r
-04/05/2020,4,5,2020,0,0,Chad,TD,TCD,15946882,Africa,0.52674874\r
-03/05/2020,3,5,2020,44,5,Chad,TD,TCD,15946882,Africa,0.52674874\r
-02/05/2020,2,5,2020,0,0,Chad,TD,TCD,15946882,Africa,0.25083273\r
-01/05/2020,1,5,2020,21,3,Chad,TD,TCD,15946882,Africa,0.28845764\r
-30/04/2020,30,4,2020,0,0,Chad,TD,TCD,15946882,Africa,0.15677046\r
-29/04/2020,29,4,2020,6,2,Chad,TD,TCD,15946882,Africa,0.18185373\r
-28/04/2020,28,4,2020,0,0,Chad,TD,TCD,15946882,Africa,0.14422882\r
-27/04/2020,27,4,2020,6,0,Chad,TD,TCD,15946882,Africa,0.19439537\r
-26/04/2020,26,4,2020,0,0,Chad,TD,TCD,15946882,Africa,0.18185373\r
-25/04/2020,25,4,2020,0,0,Chad,TD,TCD,15946882,Africa,0.18185373\r
-24/04/2020,24,4,2020,6,0,Chad,TD,TCD,15946882,Africa,0.18185373\r
-23/04/2020,23,4,2020,0,0,Chad,TD,TCD,15946882,Africa,0.15049964\r
-22/04/2020,22,4,2020,1,0,Chad,TD,TCD,15946882,Africa,0.15677046\r
-21/04/2020,21,4,2020,0,0,Chad,TD,TCD,15946882,Africa,0.15049964\r
-20/04/2020,20,4,2020,0,0,Chad,TD,TCD,15946882,Africa,0.15049964\r
-19/04/2020,19,4,2020,0,0,Chad,TD,TCD,15946882,Africa,0.15677046\r
-18/04/2020,18,4,2020,6,0,Chad,TD,TCD,15946882,Africa,0.16304128\r
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-31/07/2020,31,7,2020,1961,99,Chile,CL,CHL,18952035,America,157.43955728\r
-30/07/2020,30,7,2020,1775,38,Chile,CL,CHL,18952035,America,160.2466437\r
-29/07/2020,29,7,2020,1877,53,Chile,CL,CHL,18952035,America,159.91422557\r
-28/07/2020,28,7,2020,2133,75,Chile,CL,CHL,18952035,America,159.69788996\r
-27/07/2020,27,7,2020,2198,92,Chile,CL,CHL,18952035,America,162.24642895\r
-26/07/2020,26,7,2020,2288,106,Chile,CL,CHL,18952035,America,166.54148222\r
-25/07/2020,25,7,2020,2545,76,Chile,CL,CHL,18952035,America,169.00559755\r
-24/07/2020,24,7,2020,2357,116,Chile,CL,CHL,18952035,America,171.71243088\r
-23/07/2020,23,7,2020,1719,45,Chile,CL,CHL,18952035,America,175.80697798\r
-22/07/2020,22,7,2020,1654,44,Chile,CL,CHL,18952035,America,177.62736297\r
-21/07/2020,21,7,2020,2099,130,Chile,CL,CHL,18952035,America,181.89075738\r
-20/07/2020,20,7,2020,2084,58,Chile,CL,CHL,18952035,America,186.77677621\r
-19/07/2020,19,7,2020,2307,98,Chile,CL,CHL,18952035,America,195.22441785\r
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-29/06/2020,29,6,2020,4216,162,Chile,CL,CHL,18952035,America,515.45388134\r
-28/06/2020,28,6,2020,4406,279,Chile,CL,CHL,18952035,America,529.81645507\r
-27/06/2020,27,6,2020,4296,165,Chile,CL,CHL,18952035,America,540.91288877\r
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-25/06/2020,25,6,2020,3649,226,Chile,CL,CHL,18952035,America,558.88457361\r
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-04/03/2020,4,3,2020,1,0,Chile,CL,CHL,18952035,America,\r
-19/08/2020,19,8,2020,53,2,China,CN,CHN,1433783692,Asia,0.08983224\r
-18/08/2020,18,8,2020,66,0,China,CN,CHN,1433783692,Asia,0.0935985\r
-17/08/2020,17,8,2020,96,0,China,CN,CHN,1433783692,Asia,0.09694628\r
-16/08/2020,16,8,2020,65,2,China,CN,CHN,1433783692,Asia,0.10127051\r
-15/08/2020,15,8,2020,70,1,China,CN,CHN,1433783692,Asia,0.10873328\r
-14/08/2020,14,8,2020,99,3,China,CN,CHN,1433783692,Asia,0.11542885\r
-13/08/2020,13,8,2020,81,4,China,CN,CHN,1433783692,Asia,0.12777381\r
-12/08/2020,12,8,2020,58,3,China,CN,CHN,1433783692,Asia,0.13767767\r
-11/08/2020,11,8,2020,113,4,China,CN,CHN,1433783692,Asia,0.14806976\r
-10/08/2020,10,8,2020,121,5,China,CN,CHN,1433783692,Asia,0.15504431\r
-09/08/2020,9,8,2020,92,0,China,CN,CHN,1433783692,Asia,0.159787\r
-08/08/2020,8,8,2020,120,1,China,CN,CHN,1433783692,Asia,0.16585486\r
-07/08/2020,7,8,2020,132,3,China,CN,CHN,1433783692,Asia,0.16843545\r
-06/08/2020,6,8,2020,122,1,China,CN,CHN,1433783692,Asia,0.16892367\r
-05/08/2020,5,8,2020,107,4,China,CN,CHN,1433783692,Asia,0.16983036\r
-04/08/2020,4,8,2020,114,3,China,CN,CHN,1433783692,Asia,0.16752876\r
-03/08/2020,3,8,2020,158,2,China,CN,CHN,1433783692,Asia,0.16543639\r
-02/08/2020,2,8,2020,172,6,China,CN,CHN,1433783692,Asia,0.16348352\r
-01/08/2020,1,8,2020,166,2,China,CN,CHN,1433783692,Asia,0.15706693\r
-31/07/2020,31,7,2020,276,0,China,CN,CHN,1433783692,Asia,0.15106881\r
-30/07/2020,30,7,2020,223,2,China,CN,CHN,1433783692,Asia,0.13718945\r
-29/07/2020,29,7,2020,207,1,China,CN,CHN,1433783692,Asia,0.12303111\r
-28/07/2020,28,7,2020,213,4,China,CN,CHN,1433783692,Asia,0.11236004\r
-27/07/2020,27,7,2020,189,0,China,CN,CHN,1433783692,Asia,0.10134025\r
-26/07/2020,26,7,2020,179,2,China,CN,CHN,1433783692,Asia,0.09136664\r
-25/07/2020,25,7,2020,157,1,China,CN,CHN,1433783692,Asia,0.08132329\r
-24/07/2020,24,7,2020,139,1,China,CN,CHN,1433783692,Asia,0.07316306\r
-23/07/2020,23,7,2020,135,0,China,CN,CHN,1433783692,Asia,0.06667672\r
-22/07/2020,22,7,2020,74,2,China,CN,CHN,1433783692,Asia,0.05956268\r
-21/07/2020,21,7,2020,84,0,China,CN,CHN,1433783692,Asia,0.05586617\r
-20/07/2020,20,7,2020,130,0,China,CN,CHN,1433783692,Asia,0.05175118\r
-19/07/2020,19,7,2020,80,1,China,CN,CHN,1433783692,Asia,0.0436607\r
-18/07/2020,18,7,2020,80,1,China,CN,CHN,1433783692,Asia,0.03933648\r
-17/07/2020,17,7,2020,77,0,China,CN,CHN,1433783692,Asia,0.03438455\r
-16/07/2020,16,7,2020,20,2,China,CN,CHN,1433783692,Asia,0.02999058\r
-15/07/2020,15,7,2020,54,0,China,CN,CHN,1433783692,Asia,0.03075778\r
-14/07/2020,14,7,2020,55,1,China,CN,CHN,1433783692,Asia,0.02734025\r
-13/07/2020,13,7,2020,46,0,China,CN,CHN,1433783692,Asia,0.02510839\r
-12/07/2020,12,7,2020,35,0,China,CN,CHN,1433783692,Asia,0.02287653\r
-11/07/2020,11,7,2020,40,0,China,CN,CHN,1433783692,Asia,0.02169086\r
-10/07/2020,10,7,2020,46,0,China,CN,CHN,1433783692,Asia,0.02057493\r
-09/07/2020,9,7,2020,33,0,China,CN,CHN,1433783692,Asia,0.01931951\r
-08/07/2020,8,7,2020,21,0,China,CN,CHN,1433783692,Asia,0.01841282\r
-07/07/2020,7,7,2020,25,0,China,CN,CHN,1433783692,Asia,0.01897078\r
-06/07/2020,6,7,2020,14,0,China,CN,CHN,1433783692,Asia,0.02085391\r
-05/07/2020,5,7,2020,18,0,China,CN,CHN,1433783692,Asia,0.02120264\r
-04/07/2020,4,7,2020,9,0,China,CN,CHN,1433783692,Asia,0.02196984\r
-03/07/2020,3,7,2020,14,0,China,CN,CHN,1433783692,Asia,0.0234345\r
-02/07/2020,2,7,2020,31,0,China,CN,CHN,1433783692,Asia,0.0249689\r
-01/07/2020,1,7,2020,5,0,China,CN,CHN,1433783692,Asia,0.02531763\r
-30/06/2020,30,6,2020,23,0,China,CN,CHN,1433783692,Asia,0.0280377\r
-29/06/2020,29,6,2020,14,0,China,CN,CHN,1433783692,Asia,0.02943261\r
-28/06/2020,28,6,2020,18,0,China,CN,CHN,1433783692,Asia,0.03173422\r
-27/06/2020,27,6,2020,24,0,China,CN,CHN,1433783692,Asia,0.03466353\r
-26/06/2020,26,6,2020,28,1,China,CN,CHN,1433783692,Asia,0.03382658\r
-25/06/2020,25,6,2020,20,0,China,CN,CHN,1433783692,Asia,0.03236192\r
-24/06/2020,24,6,2020,29,1,China,CN,CHN,1433783692,Asia,0.03173422\r
-23/06/2020,23,6,2020,52,0,China,CN,CHN,1433783692,Asia,0.02999058\r
-22/06/2020,22,6,2020,19,0,China,CN,CHN,1433783692,Asia,0.02657305\r
-21/06/2020,21,6,2020,29,1,China,CN,CHN,1433783692,Asia,0.02559661\r
-20/06/2020,20,6,2020,30,0,China,CN,CHN,1433783692,Asia,0.0242017\r
-19/06/2020,19,6,2020,36,0,China,CN,CHN,1433783692,Asia,0.02252781\r
-18/06/2020,18,6,2020,36,0,China,CN,CHN,1433783692,Asia,0.02078417\r
-17/06/2020,17,6,2020,44,0,China,CN,CHN,1433783692,Asia,0.01834307\r
-16/06/2020,16,6,2020,43,0,China,CN,CHN,1433783692,Asia,0.015623\r
-15/06/2020,15,6,2020,47,0,China,CN,CHN,1433783692,Asia,0.01311216\r
-14/06/2020,14,6,2020,60,0,China,CN,CHN,1433783692,Asia,0.01115928\r
-13/06/2020,13,6,2020,12,0,China,CN,CHN,1433783692,Asia,0.00732328\r
-12/06/2020,12,6,2020,7,0,China,CN,CHN,1433783692,Asia,0.00767201\r
-11/06/2020,11,6,2020,11,0,China,CN,CHN,1433783692,Asia,0.00718379\r
-10/06/2020,10,6,2020,4,0,China,CN,CHN,1433783692,Asia,0.00662583\r
-09/06/2020,9,6,2020,3,0,China,CN,CHN,1433783692,Asia,0.00641659\r
-08/06/2020,8,6,2020,5,0,China,CN,CHN,1433783692,Asia,0.00669557\r
-07/06/2020,7,6,2020,9,0,China,CN,CHN,1433783692,Asia,0.00711404\r
-06/06/2020,6,6,2020,6,0,China,CN,CHN,1433783692,Asia,0.00669557\r
-05/06/2020,5,6,2020,11,0,China,CN,CHN,1433783692,Asia,0.00641659\r
-04/06/2020,4,6,2020,1,0,China,CN,CHN,1433783692,Asia,0.00648633\r
-03/06/2020,3,6,2020,5,0,China,CN,CHN,1433783692,Asia,0.00655608\r
-02/06/2020,2,6,2020,7,0,China,CN,CHN,1433783692,Asia,0.00634684\r
-01/06/2020,1,6,2020,19,0,China,CN,CHN,1433783692,Asia,0.00648633\r
-31/05/2020,31,5,2020,5,0,China,CN,CHN,1433783692,Asia,0.00585862\r
-30/05/2020,30,5,2020,17,0,China,CN,CHN,1433783692,Asia,0.00592837\r
-29/05/2020,29,5,2020,0,0,China,CN,CHN,1433783692,Asia,0.00537041\r
-28/05/2020,28,5,2020,3,0,China,CN,CHN,1433783692,Asia,0.00571913\r
-27/05/2020,27,5,2020,1,0,China,CN,CHN,1433783692,Asia,0.00592837\r
-26/05/2020,26,5,2020,7,0,China,CN,CHN,1433783692,Asia,0.00634684\r
-25/05/2020,25,5,2020,11,0,China,CN,CHN,1433783692,Asia,0.00592837\r
-24/05/2020,24,5,2020,3,0,China,CN,CHN,1433783692,Asia,0.00648633\r
-23/05/2020,23,5,2020,2,0,China,CN,CHN,1433783692,Asia,0.00732328\r
-22/05/2020,22,5,2020,12,0,China,CN,CHN,1433783692,Asia,0.00718379\r
-21/05/2020,21,5,2020,2,0,China,CN,CHN,1433783692,Asia,0.00676532\r
-20/05/2020,20,5,2020,2,0,China,CN,CHN,1433783692,Asia,0.00676532\r
-19/05/2020,19,5,2020,9,0,China,CN,CHN,1433783692,Asia,0.00676532\r
-18/05/2020,18,5,2020,10,0,China,CN,CHN,1433783692,Asia,0.0062771\r
-17/05/2020,17,5,2020,6,1,China,CN,CHN,1433783692,Asia,0.00578888\r
-16/05/2020,16,5,2020,9,0,China,CN,CHN,1433783692,Asia,0.0055099\r
-15/05/2020,15,5,2020,5,0,China,CN,CHN,1433783692,Asia,0.00509142\r
-14/05/2020,14,5,2020,6,0,China,CN,CHN,1433783692,Asia,0.00557964\r
-13/05/2020,13,5,2020,7,0,China,CN,CHN,1433783692,Asia,0.00544015\r
-12/05/2020,12,5,2020,1,0,China,CN,CHN,1433783692,Asia,0.00509142\r
-11/05/2020,11,5,2020,19,0,China,CN,CHN,1433783692,Asia,0.00683506\r
-10/05/2020,10,5,2020,15,0,China,CN,CHN,1433783692,Asia,0.00571913\r
-09/05/2020,9,5,2020,0,0,China,CN,CHN,1433783692,Asia,0.00537041\r
-08/05/2020,8,5,2020,6,0,China,CN,CHN,1433783692,Asia,0.00641659\r
-07/05/2020,7,5,2020,2,0,China,CN,CHN,1433783692,Asia,0.00655608\r
-06/05/2020,6,5,2020,2,0,China,CN,CHN,1433783692,Asia,0.00725353\r
-05/05/2020,5,5,2020,2,0,China,CN,CHN,1433783692,Asia,0.00816023\r
-04/05/2020,4,5,2020,3,0,China,CN,CHN,1433783692,Asia,0.01025259\r
-03/05/2020,3,5,2020,2,0,China,CN,CHN,1433783692,Asia,0.01101979\r
-02/05/2020,2,5,2020,3,0,China,CN,CHN,1433783692,Asia,0.01213572\r
-01/05/2020,1,5,2020,12,0,China,CN,CHN,1433783692,Asia,0.0140886\r
-30/04/2020,30,4,2020,4,0,China,CN,CHN,1433783692,Asia,0.03780208\r
-29/04/2020,29,4,2020,2,0,China,CN,CHN,1433783692,Asia,0.04101037\r
-28/04/2020,28,4,2020,26,0,China,CN,CHN,1433783692,Asia,0.04428841\r
-27/04/2020,27,4,2020,3,1,China,CN,CHN,1433783692,Asia,0.04903111\r
-26/04/2020,26,4,2020,10,0,China,CN,CHN,1433783692,Asia,0.05663337\r
-25/04/2020,25,4,2020,15,0,China,CN,CHN,1433783692,Asia,0.06242225\r
-24/04/2020,24,4,2020,8,0,China,CN,CHN,1433783692,Asia,0.06688596\r
-23/04/2020,23,4,2020,12,0,China,CN,CHN,1433783692,Asia,0.070164\r
-22/04/2020,22,4,2020,15,0,China,CN,CHN,1433783692,Asia,0.07532517\r
-21/04/2020,21,4,2020,32,0,China,CN,CHN,1433783692,Asia,0.0802771\r
-20/04/2020,20,4,2020,14,0,China,CN,CHN,1433783692,Asia,0.08195099\r
-19/04/2020,19,4,2020,18,0,China,CN,CHN,1433783692,Asia,0.08564751\r
-18/04/2020,18,4,2020,31,0,China,CN,CHN,1433783692,Asia,0.08773987\r
-17/04/2020,17,4,2020,352,1290,China,CN,CHN,1433783692,Asia,0.08990199\r
-16/04/2020,16,4,2020,50,0,China,CN,CHN,1433783692,Asia,0.07023375\r
-15/04/2020,15,4,2020,49,1,China,CN,CHN,1433783692,Asia,0.07372102\r
-14/04/2020,14,4,2020,94,0,China,CN,CHN,1433783692,Asia,0.07406975\r
-13/04/2020,13,4,2020,112,2,China,CN,CHN,1433783692,Asia,0.07337229\r
-12/04/2020,12,4,2020,93,0,China,CN,CHN,1433783692,Asia,0.07239586\r
-11/04/2020,11,4,2020,79,3,China,CN,CHN,1433783692,Asia,0.07379077\r
-10/04/2020,10,4,2020,55,1,China,CN,CHN,1433783692,Asia,0.07658059\r
-09/04/2020,9,4,2020,86,2,China,CN,CHN,1433783692,Asia,0.07930066\r
-08/04/2020,8,4,2020,86,2,China,CN,CHN,1433783692,Asia,0.08041659\r
-07/04/2020,7,4,2020,56,0,China,CN,CHN,1433783692,Asia,0.07985863\r
-06/04/2020,6,4,2020,67,2,China,CN,CHN,1433783692,Asia,0.08076532\r
-05/04/2020,5,4,2020,48,3,China,CN,CHN,1433783692,Asia,0.08571725\r
-04/04/2020,4,4,2020,62,4,China,CN,CHN,1433783692,Asia,0.08690293\r
-03/04/2020,3,4,2020,70,10,China,CN,CHN,1433783692,Asia,0.08620547\r
-02/04/2020,2,4,2020,100,6,China,CN,CHN,1433783692,Asia,0.08822809\r
-01/04/2020,1,4,2020,54,1,China,CN,CHN,1433783692,Asia,0.08432234\r
-31/03/2020,31,3,2020,84,3,China,CN,CHN,1433783692,Asia,0.08216023\r
-30/03/2020,30,3,2020,98,2,China,CN,CHN,1433783692,Asia,0.07930066\r
-29/03/2020,29,3,2020,113,5,China,CN,CHN,1433783692,Asia,0.07420924\r
-28/03/2020,28,3,2020,119,3,China,CN,CHN,1433783692,Asia,0.0678624\r
-27/03/2020,27,3,2020,94,5,China,CN,CHN,1433783692,Asia,0.06088785\r
-26/03/2020,26,3,2020,102,6,China,CN,CHN,1433783692,Asia,0.05586617\r
-25/03/2020,25,3,2020,78,4,China,CN,CHN,1433783692,Asia,0.05042602\r
-24/03/2020,24,3,2020,69,7,China,CN,CHN,1433783692,Asia,0.04700849\r
-23/03/2020,23,3,2020,138,9,China,CN,CHN,1433783692,Asia,0.04359095\r
-22/03/2020,22,3,2020,65,6,China,CN,CHN,1433783692,Asia,0.03710462\r
-21/03/2020,21,3,2020,52,6,China,CN,CHN,1433783692,Asia,0.03577946\r
-20/03/2020,20,3,2020,99,4,China,CN,CHN,1433783692,Asia,0.03919699\r
-19/03/2020,19,3,2020,44,8,China,CN,CHN,1433783692,Asia,0.04414892\r
-18/03/2020,18,3,2020,23,16,China,CN,CHN,1433783692,Asia,0.04924034\r
-17/03/2020,17,3,2020,43,9,China,CN,CHN,1433783692,Asia,0.05593591\r
-16/03/2020,16,3,2020,25,13,China,CN,CHN,1433783692,Asia,0.06179454\r
-15/03/2020,15,3,2020,22,9,China,CN,CHN,1433783692,Asia,0.07434873\r
-14/03/2020,14,3,2020,19,15,China,CN,CHN,1433783692,Asia,0.11284826\r
-13/03/2020,13,3,2020,22,7,China,CN,CHN,1433783692,Asia,0.14137418\r
-12/03/2020,12,3,2020,24,11,China,CN,CHN,1433783692,Asia,0.16278606\r
-11/03/2020,11,3,2020,29,22,China,CN,CHN,1433783692,Asia,0.19173046\r
-10/03/2020,10,3,2020,20,17,China,CN,CHN,1433783692,Asia,0.2183035\r
-09/03/2020,9,3,2020,45,23,China,CN,CHN,1433783692,Asia,0.25282754\r
-08/03/2020,8,3,2020,46,27,China,CN,CHN,1433783692,Asia,0.26489351\r
-07/03/2020,7,3,2020,101,28,China,CN,CHN,1433783692,Asia,0.30681058\r
-06/03/2020,6,3,2020,170,30,China,CN,CHN,1433783692,Asia,0.35737608\r
-05/03/2020,5,3,2020,117,31,China,CN,CHN,1433783692,Asia,0.40766261\r
-04/03/2020,4,3,2020,119,37,China,CN,CHN,1433783692,Asia,0.42698212\r
-03/03/2020,3,3,2020,127,32,China,CN,CHN,1433783692,Asia,0.54073708\r
-02/03/2020,2,3,2020,205,42,China,CN,CHN,1433783692,Asia,0.66369844\r
-01/03/2020,1,3,2020,574,35,China,CN,CHN,1433783692,Asia,0.79251843\r
-29/02/2020,29,2,2020,428,47,China,CN,CHN,1433783692,Asia,0.89246377\r
-28/02/2020,28,2,2020,329,44,China,CN,CHN,1433783692,Asia,1.03962683\r
-27/02/2020,27,2,2020,439,29,China,CN,CHN,1433783692,Asia,1.30654297\r
-26/02/2020,26,2,2020,410,52,China,CN,CHN,1433783692,Asia,2.33194171\r
-25/02/2020,25,2,2020,515,70,China,CN,CHN,1433783692,Asia,2.44478998\r
-24/02/2020,24,2,2020,218,150,China,CN,CHN,1433783692,Asia,2.58253739\r
-23/02/2020,23,2,2020,647,98,China,CN,CHN,1433783692,Asia,2.77475607\r
-22/02/2020,22,2,2020,826,109,China,CN,CHN,1433783692,Asia,2.9114573\r
-21/02/2020,21,2,2020,891,118,China,CN,CHN,1433783692,Asia,3.09223771\r
-20/02/2020,20,2,2020,394,112,China,CN,CHN,1433783692,Asia,3.25049031\r
-19/02/2020,19,2,2020,1750,139,China,CN,CHN,1433783692,Asia,3.48295216\r
-18/02/2020,18,2,2020,1890,98,China,CN,CHN,1433783692,Asia,3.63095216\r
-17/02/2020,17,2,2020,2052,105,China,CN,CHN,1433783692,Asia,3.72489939\r
-16/02/2020,16,2,2020,2007,142,China,CN,CHN,1433783692,Asia,3.77790599\r
-15/02/2020,15,2,2020,2538,143,China,CN,CHN,1433783692,Asia,3.81856763\r
-14/02/2020,14,2,2020,4156,13,China,CN,CHN,1433783692,Asia,3.78767036\r
-13/02/2020,13,2,2020,15141,254,China,CN,CHN,1433783692,Asia,3.6359041\r
-12/02/2020,12,2,2020,2028,97,China,CN,CHN,1433783692,Asia,2.70124428\r
-11/02/2020,11,2,2020,2490,108,China,CN,CHN,1433783692,Asia,2.6620473\r
-10/02/2020,10,2,2020,2974,97,China,CN,CHN,1433783692,Asia,2.61064484\r
-09/02/2020,9,2,2020,2607,89,China,CN,CHN,1433783692,Asia,2.45811137\r
-08/02/2020,8,2,2020,3418,86,China,CN,CHN,1433783692,Asia,2.32266556\r
-07/02/2020,7,2,2020,3160,73,China,CN,CHN,1433783692,Asia,2.11503312\r
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-01/04/2020,1,4,2020,0,0,Cote_dIvoire,CI,CIV,25716554,Africa,0.63383298\r
-31/03/2020,31,3,2020,3,0,Cote_dIvoire,CI,CIV,25716554,Africa,0.63383298\r
-30/03/2020,30,3,2020,25,1,Cote_dIvoire,CI,CIV,25716554,Africa,0.62605589\r
-29/03/2020,29,3,2020,39,0,Cote_dIvoire,CI,CIV,25716554,Africa,0.52884224\r
-28/03/2020,28,3,2020,5,0,Cote_dIvoire,CI,CIV,25716554,Africa,0.38885459\r
-27/03/2020,27,3,2020,16,0,Cote_dIvoire,CI,CIV,25716554,Africa,0.3733004\r
-26/03/2020,26,3,2020,7,0,Cote_dIvoire,CI,CIV,25716554,Africa,\r
-25/03/2020,25,3,2020,48,0,Cote_dIvoire,CI,CIV,25716554,Africa,\r
-24/03/2020,24,3,2020,0,0,Cote_dIvoire,CI,CIV,25716554,Africa,\r
-23/03/2020,23,3,2020,8,0,Cote_dIvoire,CI,CIV,25716554,Africa,\r
-22/03/2020,22,3,2020,3,0,Cote_dIvoire,CI,CIV,25716554,Africa,\r
-21/03/2020,21,3,2020,5,0,Cote_dIvoire,CI,CIV,25716554,Africa,\r
-20/03/2020,20,3,2020,3,0,Cote_dIvoire,CI,CIV,25716554,Africa,\r
-19/03/2020,19,3,2020,1,0,Cote_dIvoire,CI,CIV,25716554,Africa,\r
-18/03/2020,18,3,2020,0,0,Cote_dIvoire,CI,CIV,25716554,Africa,\r
-17/03/2020,17,3,2020,1,0,Cote_dIvoire,CI,CIV,25716554,Africa,\r
-16/03/2020,16,3,2020,0,0,Cote_dIvoire,CI,CIV,25716554,Africa,\r
-15/03/2020,15,3,2020,3,0,Cote_dIvoire,CI,CIV,25716554,Africa,\r
-12/03/2020,12,3,2020,1,0,Cote_dIvoire,CI,CIV,25716554,Africa,\r
-19/08/2020,19,8,2020,199,0,Croatia,HR,HRV,4076246,Europe,37.70626209\r
-18/08/2020,18,8,2020,85,0,Croatia,HR,HRV,4076246,Europe,33.36403151\r
-17/08/2020,17,8,2020,151,1,Croatia,HR,HRV,4076246,Europe,32.16194508\r
-16/08/2020,16,8,2020,162,2,Croatia,HR,HRV,4076246,Europe,29.34072183\r
-15/08/2020,15,8,2020,208,2,Croatia,HR,HRV,4076246,Europe,27.47626125\r
-14/08/2020,14,8,2020,180,1,Croatia,HR,HRV,4076246,Europe,24.01719621\r
-13/08/2020,13,8,2020,130,0,Croatia,HR,HRV,4076246,Europe,21.51489385\r
-12/08/2020,12,8,2020,91,2,Croatia,HR,HRV,4076246,Europe,20.04295128\r
-11/08/2020,11,8,2020,45,1,Croatia,HR,HRV,4076246,Europe,18.84086485\r
-10/08/2020,10,8,2020,61,0,Croatia,HR,HRV,4076246,Europe,18.32568496\r
-09/08/2020,9,8,2020,77,2,Croatia,HR,HRV,4076246,Europe,18.42381446\r
-08/08/2020,8,8,2020,62,0,Croatia,HR,HRV,4076246,Europe,18.42381446\r
-07/08/2020,7,8,2020,28,1,Croatia,HR,HRV,4076246,Europe,18.88992961\r
-06/08/2020,6,8,2020,58,0,Croatia,HR,HRV,4076246,Europe,20.75439019\r
-05/08/2020,5,8,2020,22,1,Croatia,HR,HRV,4076246,Europe,21.981009\r
-04/08/2020,4,8,2020,36,4,Croatia,HR,HRV,4076246,Europe,22.71698028\r
-03/08/2020,3,8,2020,36,4,Croatia,HR,HRV,4076246,Europe,22.22633276\r
-02/08/2020,2,8,2020,86,0,Croatia,HR,HRV,4076246,Europe,24.26251998\r
-01/08/2020,1,8,2020,67,1,Croatia,HR,HRV,4076246,Europe,24.55690849\r
-31/07/2020,31,7,2020,78,3,Croatia,HR,HRV,4076246,Europe,25.31741215\r
-30/07/2020,30,7,2020,70,1,Croatia,HR,HRV,4076246,Europe,25.51367116\r
-29/07/2020,29,7,2020,42,1,Croatia,HR,HRV,4076246,Europe,26.88748422\r
-28/07/2020,28,7,2020,24,3,Croatia,HR,HRV,4076246,Europe,27.13280798\r
-27/07/2020,27,7,2020,65,3,Croatia,HR,HRV,4076246,Europe,27.84424689\r
-26/07/2020,26,7,2020,77,5,Croatia,HR,HRV,4076246,Europe,27.47626125\r
-25/07/2020,25,7,2020,81,0,Croatia,HR,HRV,4076246,Europe,29.02180094\r
-24/07/2020,24,7,2020,104,3,Croatia,HR,HRV,4076246,Europe,29.88043411\r
-23/07/2020,23,7,2020,108,3,Croatia,HR,HRV,4076246,Europe,29.56151322\r
-22/07/2020,22,7,2020,52,0,Croatia,HR,HRV,4076246,Europe,28.21223253\r
-21/07/2020,21,7,2020,16,2,Croatia,HR,HRV,4076246,Europe,28.21223253\r
-20/07/2020,20,7,2020,119,0,Croatia,HR,HRV,4076246,Europe,29.51244846\r
-19/07/2020,19,7,2020,98,0,Croatia,HR,HRV,4076246,Europe,27.99144114\r
-18/07/2020,18,7,2020,98,1,Croatia,HR,HRV,4076246,Europe,27.69705263\r
-17/07/2020,17,7,2020,86,0,Croatia,HR,HRV,4076246,Europe,27.64798788\r
-16/07/2020,16,7,2020,126,0,Croatia,HR,HRV,4076246,Europe,27.525326\r
-15/07/2020,15,7,2020,52,0,Croatia,HR,HRV,4076246,Europe,25.75899492\r
-14/07/2020,14,7,2020,53,0,Croatia,HR,HRV,4076246,Europe,25.75899492\r
-13/07/2020,13,7,2020,50,1,Croatia,HR,HRV,4076246,Europe,25.29287977\r
-12/07/2020,12,7,2020,140,1,Croatia,HR,HRV,4076246,Europe,25.70993017\r
-11/07/2020,11,7,2020,116,2,Croatia,HR,HRV,4076246,Europe,24.36064948\r
-10/07/2020,10,7,2020,91,1,Croatia,HR,HRV,4076246,Europe,22.88870691\r
-09/07/2020,9,7,2020,53,1,Croatia,HR,HRV,4076246,Europe,22.98683642\r
-08/07/2020,8,7,2020,52,0,Croatia,HR,HRV,4076246,Europe,22.22633276\r
-07/07/2020,7,7,2020,69,0,Croatia,HR,HRV,4076246,Europe,21.68662048\r
-06/07/2020,6,7,2020,57,0,Croatia,HR,HRV,4076246,Europe,20.46000168\r
-05/07/2020,5,7,2020,86,1,Croatia,HR,HRV,4076246,Europe,19.50323901\r
-04/07/2020,4,7,2020,96,2,Croatia,HR,HRV,4076246,Europe,17.85956981\r
-03/07/2020,3,7,2020,81,2,Croatia,HR,HRV,4076246,Europe,15.77431784\r
-02/07/2020,2,7,2020,54,1,Croatia,HR,HRV,4076246,Europe,14.05705151\r
-01/07/2020,1,7,2020,52,0,Croatia,HR,HRV,4076246,Europe,12.80590033\r
-30/06/2020,30,6,2020,34,0,Croatia,HR,HRV,4076246,Europe,11.55474915\r
-29/06/2020,29,6,2020,67,0,Croatia,HR,HRV,4076246,Europe,10.76971311\r
-28/06/2020,28,6,2020,85,0,Croatia,HR,HRV,4076246,Europe,9.15057629\r
-27/06/2020,27,6,2020,56,0,Croatia,HR,HRV,4076246,Europe,7.11438907\r
-26/06/2020,26,6,2020,95,0,Croatia,HR,HRV,4076246,Europe,5.74057601\r
-25/06/2020,25,6,2020,22,0,Croatia,HR,HRV,4076246,Europe,3.41000028\r
-24/06/2020,24,6,2020,30,0,Croatia,HR,HRV,4076246,Europe,2.91935276\r
-23/06/2020,23,6,2020,19,0,Croatia,HR,HRV,4076246,Europe,2.18338147\r
-22/06/2020,22,6,2020,18,0,Croatia,HR,HRV,4076246,Europe,1.71726633\r
-21/06/2020,21,6,2020,19,0,Croatia,HR,HRV,4076246,Europe,1.27568356\r
-20/06/2020,20,6,2020,11,0,Croatia,HR,HRV,4076246,Europe,0.80956841\r
-19/06/2020,19,6,2020,11,0,Croatia,HR,HRV,4076246,Europe,0.53971227\r
-18/06/2020,18,6,2020,3,0,Croatia,HR,HRV,4076246,Europe,0.29438851\r
-17/06/2020,17,6,2020,1,0,Croatia,HR,HRV,4076246,Europe,0.22079139\r
-16/06/2020,16,6,2020,2,0,Croatia,HR,HRV,4076246,Europe,0.19625901\r
-15/06/2020,15,6,2020,1,0,Croatia,HR,HRV,4076246,Europe,0.14719426\r
-14/06/2020,14,6,2020,2,0,Croatia,HR,HRV,4076246,Europe,0.12266188\r
-13/06/2020,13,6,2020,0,1,Croatia,HR,HRV,4076246,Europe,0.0981295\r
-12/06/2020,12,6,2020,0,0,Croatia,HR,HRV,4076246,Europe,0.0981295\r
-11/06/2020,11,6,2020,2,0,Croatia,HR,HRV,4076246,Europe,0.12266188\r
-10/06/2020,10,6,2020,0,2,Croatia,HR,HRV,4076246,Europe,0.07359713\r
-09/06/2020,9,6,2020,0,0,Croatia,HR,HRV,4076246,Europe,0.07359713\r
-08/06/2020,8,6,2020,0,0,Croatia,HR,HRV,4076246,Europe,0.07359713\r
-07/06/2020,7,6,2020,0,1,Croatia,HR,HRV,4076246,Europe,0.0981295\r
-06/06/2020,6,6,2020,0,0,Croatia,HR,HRV,4076246,Europe,0.0981295\r
-05/06/2020,5,6,2020,1,0,Croatia,HR,HRV,4076246,Europe,0.24532376\r
-04/06/2020,4,6,2020,0,0,Croatia,HR,HRV,4076246,Europe,0.29438851\r
-03/06/2020,3,6,2020,0,0,Croatia,HR,HRV,4076246,Europe,0.34345327\r
-02/06/2020,2,6,2020,0,0,Croatia,HR,HRV,4076246,Europe,0.44158277\r
-01/06/2020,1,6,2020,0,0,Croatia,HR,HRV,4076246,Europe,0.49064752\r
-31/05/2020,31,5,2020,1,0,Croatia,HR,HRV,4076246,Europe,0.53971227\r
-30/05/2020,30,5,2020,0,1,Croatia,HR,HRV,4076246,Europe,0.56424465\r
-29/05/2020,29,5,2020,1,1,Croatia,HR,HRV,4076246,Europe,0.58877703\r
-28/05/2020,28,5,2020,0,0,Croatia,HR,HRV,4076246,Europe,0.76050366\r
-27/05/2020,27,5,2020,0,1,Croatia,HR,HRV,4076246,Europe,0.90769792\r
-26/05/2020,26,5,2020,0,1,Croatia,HR,HRV,4076246,Europe,1.17755405\r
-25/05/2020,25,5,2020,1,0,Croatia,HR,HRV,4076246,Europe,1.39834544\r
-24/05/2020,24,5,2020,0,0,Croatia,HR,HRV,4076246,Europe,1.6436692\r
-23/05/2020,23,5,2020,6,2,Croatia,HR,HRV,4076246,Europe,2.01165484\r
-22/05/2020,22,5,2020,3,1,Croatia,HR,HRV,4076246,Europe,2.74762612\r
-21/05/2020,21,5,2020,2,0,Croatia,HR,HRV,4076246,Europe,2.82122325\r
-20/05/2020,20,5,2020,4,1,Croatia,HR,HRV,4076246,Europe,2.94388513\r
-19/05/2020,19,5,2020,2,0,Croatia,HR,HRV,4076246,Europe,3.11561177\r
-18/05/2020,18,5,2020,2,0,Croatia,HR,HRV,4076246,Europe,3.18920889\r
-17/05/2020,17,5,2020,2,0,Croatia,HR,HRV,4076246,Europe,3.33640315\r
-16/05/2020,16,5,2020,1,1,Croatia,HR,HRV,4076246,Europe,3.36093553\r
-15/05/2020,15,5,2020,8,0,Croatia,HR,HRV,4076246,Europe,3.55719454\r
-14/05/2020,14,5,2020,6,3,Croatia,HR,HRV,4076246,Europe,3.70438879\r
-13/05/2020,13,5,2020,11,0,Croatia,HR,HRV,4076246,Europe,3.92518018\r
-12/05/2020,12,5,2020,9,1,Croatia,HR,HRV,4076246,Europe,3.85158305\r
-11/05/2020,11,5,2020,11,3,Croatia,HR,HRV,4076246,Europe,3.85158305\r
-10/05/2020,10,5,2020,15,1,Croatia,HR,HRV,4076246,Europe,3.92518018\r
-09/05/2020,9,5,2020,36,0,Croatia,HR,HRV,4076246,Europe,3.72892117\r
-08/05/2020,8,5,2020,6,1,Croatia,HR,HRV,4076246,Europe,3.53266216\r
-07/05/2020,7,5,2020,7,2,Croatia,HR,HRV,4076246,Europe,4.14597156\r
-06/05/2020,6,5,2020,11,3,Croatia,HR,HRV,4076246,Europe,5.00460473\r
-05/05/2020,5,5,2020,5,1,Croatia,HR,HRV,4076246,Europe,5.39712274\r
-04/05/2020,4,5,2020,8,2,Croatia,HR,HRV,4076246,Europe,5.51978463\r
-03/05/2020,3,5,2020,3,2,Croatia,HR,HRV,4076246,Europe,6.28028828\r
-02/05/2020,2,5,2020,9,6,Croatia,HR,HRV,4076246,Europe,6.64827393\r
-01/05/2020,1,5,2020,14,2,Croatia,HR,HRV,4076246,Europe,6.99172719\r
-30/04/2020,30,4,2020,15,4,Croatia,HR,HRV,4076246,Europe,7.87489273\r
-29/04/2020,29,4,2020,8,4,Croatia,HR,HRV,4076246,Europe,8.41460501\r
-28/04/2020,28,4,2020,9,4,Croatia,HR,HRV,4076246,Europe,9.54309431\r
-27/04/2020,27,4,2020,14,1,Croatia,HR,HRV,4076246,Europe,10.54892173\r
-26/04/2020,26,4,2020,7,3,Croatia,HR,HRV,4076246,Europe,11.82460529\r
-25/04/2020,25,4,2020,28,1,Croatia,HR,HRV,4076246,Europe,12.60964132\r
-24/04/2020,24,4,2020,31,2,Croatia,HR,HRV,4076246,Europe,14.08158389\r
-23/04/2020,23,4,2020,42,0,Croatia,HR,HRV,4076246,Europe,14.8911523\r
-22/04/2020,22,4,2020,27,1,Croatia,HR,HRV,4076246,Europe,15.35726745\r
-21/04/2020,21,4,2020,10,0,Croatia,HR,HRV,4076246,Europe,16.16683586\r
-20/04/2020,20,4,2020,39,8,Croatia,HR,HRV,4076246,Europe,16.90280714\r
-19/04/2020,19,4,2020,18,3,Croatia,HR,HRV,4076246,Europe,17.31985754\r
-18/04/2020,18,4,2020,23,1,Croatia,HR,HRV,4076246,Europe,18.03129644\r
-17/04/2020,17,4,2020,50,1,Croatia,HR,HRV,4076246,Europe,19.13525337\r
-16/04/2020,16,4,2020,37,3,Croatia,HR,HRV,4076246,Europe,19.08618862\r
-15/04/2020,15,4,2020,54,6,Croatia,HR,HRV,4076246,Europe,20.53359881\r
-14/04/2020,14,4,2020,50,2,Croatia,HR,HRV,4076246,Europe,21.09784346\r
-13/04/2020,13,4,2020,66,2,Croatia,HR,HRV,4076246,Europe,21.76021761\r
-12/04/2020,12,4,2020,39,0,Croatia,HR,HRV,4076246,Europe,21.51489385\r
-11/04/2020,11,4,2020,88,1,Croatia,HR,HRV,4076246,Europe,22.29992989\r
-10/04/2020,10,4,2020,64,1,Croatia,HR,HRV,4076246,Europe,22.37352701\r
-09/04/2020,9,4,2020,61,1,Croatia,HR,HRV,4076246,Europe,22.6924479\r
-08/04/2020,8,4,2020,60,2,Croatia,HR,HRV,4076246,Europe,22.0791385\r
-07/04/2020,7,4,2020,40,1,Croatia,HR,HRV,4076246,Europe,22.47165652\r
-06/04/2020,6,4,2020,56,3,Croatia,HR,HRV,4076246,Europe,23.23216018\r
-05/04/2020,5,4,2020,47,4,Croatia,HR,HRV,4076246,Europe,22.56978602\r
-04/04/2020,4,4,2020,68,1,Croatia,HR,HRV,4076246,Europe,23.37935444\r
-03/04/2020,3,4,2020,48,1,Croatia,HR,HRV,4076246,Europe,22.25086513\r
-02/04/2020,2,4,2020,96,0,Croatia,HR,HRV,4076246,Europe,21.63755573\r
-01/04/2020,1,4,2020,77,0,Croatia,HR,HRV,4076246,Europe,19.57683614\r
-31/03/2020,31,3,2020,77,0,Croatia,HR,HRV,4076246,Europe,18.00676407\r
-30/03/2020,30,3,2020,56,1,Croatia,HR,HRV,4076246,Europe,16.31403011\r
-29/03/2020,29,3,2020,71,2,Croatia,HR,HRV,4076246,Europe,15.21007319\r
-28/03/2020,28,3,2020,91,1,Croatia,HR,HRV,4076246,Europe,13.61546874\r
-27/03/2020,27,3,2020,77,1,Croatia,HR,HRV,4076246,Europe,11.53021677\r
-26/03/2020,26,3,2020,36,0,Croatia,HR,HRV,4076246,Europe,9.8620152\r
-25/03/2020,25,3,2020,76,1,Croatia,HR,HRV,4076246,Europe,9.05244679\r
-24/03/2020,24,3,2020,71,0,Croatia,HR,HRV,4076246,Europe,7.21251858\r
-23/03/2020,23,3,2020,29,0,Croatia,HR,HRV,4076246,Europe,5.49525225\r
-22/03/2020,22,3,2020,80,0,Croatia,HR,HRV,4076246,Europe,4.80834572\r
-21/03/2020,21,3,2020,22,0,Croatia,HR,HRV,4076246,Europe,2.87028801\r
-20/03/2020,20,3,2020,23,0,Croatia,HR,HRV,4076246,Europe,2.35510811\r
-19/03/2020,19,3,2020,12,0,Croatia,HR,HRV,4076246,Europe,1.81539583\r
-18/03/2020,18,3,2020,13,0,Croatia,HR,HRV,4076246,Europe,1.57007207\r
-17/03/2020,17,3,2020,8,0,Croatia,HR,HRV,4076246,Europe,1.25115118\r
-16/03/2020,16,3,2020,11,0,Croatia,HR,HRV,4076246,Europe,1.10395693\r
-15/03/2020,15,3,2020,6,0,Croatia,HR,HRV,4076246,Europe,0.85863316\r
-14/03/2020,14,3,2020,6,0,Croatia,HR,HRV,4076246,Europe,0.73597128\r
-13/03/2020,13,3,2020,9,0,Croatia,HR,HRV,4076246,Europe,0.6133094\r
-12/03/2020,12,3,2020,3,0,Croatia,HR,HRV,4076246,Europe,0.39251802\r
-11/03/2020,11,3,2020,1,0,Croatia,HR,HRV,4076246,Europe,0.31892089\r
-08/03/2020,8,3,2020,1,0,Croatia,HR,HRV,4076246,Europe,0.29438851\r
-07/03/2020,7,3,2020,1,0,Croatia,HR,HRV,4076246,Europe,0.26985614\r
-06/03/2020,6,3,2020,1,0,Croatia,HR,HRV,4076246,Europe,0.24532376\r
-04/03/2020,4,3,2020,1,0,Croatia,HR,HRV,4076246,Europe,0.22079139\r
-03/03/2020,3,3,2020,1,0,Croatia,HR,HRV,4076246,Europe,0.19625901\r
-02/03/2020,2,3,2020,2,0,Croatia,HR,HRV,4076246,Europe,0.17172663\r
-01/03/2020,1,3,2020,0,0,Croatia,HR,HRV,4076246,Europe,0.12266188\r
-29/02/2020,29,2,2020,2,0,Croatia,HR,HRV,4076246,Europe,0.12266188\r
-28/02/2020,28,2,2020,1,0,Croatia,HR,HRV,4076246,Europe,0.07359713\r
-27/02/2020,27,2,2020,1,0,Croatia,HR,HRV,4076246,Europe,0.04906475\r
-26/02/2020,26,2,2020,1,0,Croatia,HR,HRV,4076246,Europe,0.02453238\r
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-30/07/2020,30,7,2020,294,1,Czechia,CZ,CZE,10649800,Europe,24.58262127\r
-29/07/2020,29,7,2020,283,0,Czechia,CZ,CZE,10649800,Europe,23.08024564\r
-28/07/2020,28,7,2020,192,2,Czechia,CZ,CZE,10649800,Europe,21.39007305\r
-27/07/2020,27,7,2020,112,3,Czechia,CZ,CZE,10649800,Europe,20.18817255\r
-26/07/2020,26,7,2020,131,0,Czechia,CZ,CZE,10649800,Europe,19.69051062\r
-25/07/2020,25,7,2020,281,3,Czechia,CZ,CZE,10649800,Europe,18.9581025\r
-24/07/2020,24,7,2020,230,1,Czechia,CZ,CZE,10649800,Europe,17.66230352\r
-23/07/2020,23,7,2020,246,4,Czechia,CZ,CZE,10649800,Europe,16.48857256\r
-22/07/2020,22,7,2020,226,1,Czechia,CZ,CZE,10649800,Europe,15.38996037\r
-21/07/2020,21,7,2020,153,0,Czechia,CZ,CZE,10649800,Europe,14.38524667\r
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-18/07/2020,18,7,2020,130,3,Czechia,CZ,CZE,10649800,Europe,13.36175327\r
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-29/06/2020,29,6,2020,305,1,Czechia,CZ,CZE,10649800,Europe,14.82656951\r
-28/06/2020,28,6,2020,260,2,Czechia,CZ,CZE,10649800,Europe,12.27253094\r
-27/06/2020,27,6,2020,168,0,Czechia,CZ,CZE,10649800,Europe,10.32883247\r
-26/06/2020,26,6,2020,93,2,Czechia,CZ,CZE,10649800,Europe,9.23961013\r
-25/06/2020,25,6,2020,127,4,Czechia,CZ,CZE,10649800,Europe,8.94852485\r
-24/06/2020,24,6,2020,89,3,Czechia,CZ,CZE,10649800,Europe,8.44147308\r
-23/06/2020,23,6,2020,63,0,Czechia,CZ,CZE,10649800,Europe,8.11282841\r
-22/06/2020,22,6,2020,50,0,Czechia,CZ,CZE,10649800,Europe,8.1691675\r
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-18/06/2020,18,6,2020,51,2,Czechia,CZ,CZE,10649800,Europe,6.79824973\r
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-16/06/2020,16,6,2020,40,1,Czechia,CZ,CZE,10649800,Europe,7.15506394\r
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-14/06/2020,14,6,2020,53,0,Czechia,CZ,CZE,10649800,Europe,7.1456741\r
-13/06/2020,13,6,2020,52,0,Czechia,CZ,CZE,10649800,Europe,6.96726699\r
-12/06/2020,12,6,2020,62,1,Czechia,CZ,CZE,10649800,Europe,7.00482638\r
-11/06/2020,11,6,2020,73,0,Czechia,CZ,CZE,10649800,Europe,6.9297076\r
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-22/07/2020,22,7,2020,91,1,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.00586967\r
-21/07/2020,21,7,2020,40,1,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.16372092\r
-20/07/2020,20,7,2020,79,1,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.14298134\r
-19/07/2020,19,7,2020,75,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.08882799\r
-18/07/2020,18,7,2020,50,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.22133087\r
-17/07/2020,17,7,2020,36,1,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.16372092\r
-16/07/2020,16,7,2020,27,2,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.19943909\r
-15/07/2020,15,7,2020,61,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.26396223\r
-14/07/2020,14,7,2020,42,1,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.30774579\r
-13/07/2020,13,7,2020,62,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.38955192\r
-12/07/2020,12,7,2020,66,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.63381809\r
-11/07/2020,11,7,2020,59,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.55777296\r
-10/07/2020,10,7,2020,108,4,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.65225327\r
-09/07/2020,9,7,2020,77,2,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.97026018\r
-08/07/2020,8,7,2020,228,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.88154086\r
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-01/07/2020,1,7,2020,99,2,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,2.3781386\r
-30/06/2020,30,6,2020,113,10,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,2.42192216\r
-29/06/2020,29,6,2020,274,8,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,2.36085562\r
-28/06/2020,28,6,2020,0,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,2.10737185\r
-27/06/2020,27,6,2020,141,7,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,2.20761316\r
-26/06/2020,26,6,2020,384,7,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,2.18572138\r
-25/06/2020,25,6,2020,0,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.88730186\r
-24/06/2020,24,6,2020,102,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,2.03823992\r
-23/06/2020,23,6,2020,99,5,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,2.09700206\r
-22/06/2020,22,6,2020,155,6,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,2.08548007\r
-21/06/2020,21,6,2020,195,3,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,2.06589269\r
-20/06/2020,20,6,2020,194,4,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.97256458\r
-19/06/2020,19,6,2020,183,2,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.88845405\r
-18/06/2020,18,6,2020,125,3,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.84927929\r
-17/06/2020,17,6,2020,137,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.89997604\r
-16/06/2020,16,6,2020,60,6,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.89306285\r
-15/06/2020,15,6,2020,54,1,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.99099976\r
-14/06/2020,14,6,2020,87,5,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,2.02441353\r
-13/06/2020,13,6,2020,122,3,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,2.07741468\r
-12/06/2020,12,6,2020,125,2,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.93799861\r
-11/06/2020,11,6,2020,131,6,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.99330416\r
-10/06/2020,10,6,2020,153,2,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.97371678\r
-09/06/2020,9,6,2020,89,2,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,2.08317567\r
-08/06/2020,8,6,2020,138,4,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.98062997\r
-07/06/2020,7,6,2020,114,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,2.00136955\r
-06/06/2020,6,6,2020,121,3,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,2.00367395\r
-05/06/2020,5,6,2020,149,3,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.95643379\r
-04/06/2020,4,6,2020,169,3,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.91149803\r
-03/06/2020,3,6,2020,131,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.8366051\r
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-01/06/2020,1,6,2020,83,2,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.8377573\r
-31/05/2020,31,5,2020,133,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.74212479\r
-30/05/2020,30,5,2020,1,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.68681924\r
-29/05/2020,29,5,2020,173,1,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.76747317\r
-28/05/2020,28,5,2020,114,1,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.63266589\r
-27/05/2020,27,5,2020,248,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.58542573\r
-26/05/2020,26,5,2020,0,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.37687773\r
-25/05/2020,25,5,2020,156,4,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.46674924\r
-24/05/2020,24,5,2020,116,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.32502878\r
-23/05/2020,23,5,2020,80,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.25359244\r
-22/05/2020,22,5,2020,110,2,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.20750448\r
-21/05/2020,21,5,2020,104,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.11993736\r
-20/05/2020,20,5,2020,102,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.18215611\r
-19/05/2020,19,5,2020,175,1,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,1.08882799\r
-18/05/2020,18,5,2020,0,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.88719318\r
-17/05/2020,17,5,2020,85,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.89871517\r
-16/05/2020,16,5,2020,71,10,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.88143219\r
-15/05/2020,15,5,2020,56,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.83649643\r
-14/05/2020,14,5,2020,73,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.85493161\r
-13/05/2020,13,5,2020,67,6,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.78119088\r
-12/05/2020,12,5,2020,78,3,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.72703753\r
-11/05/2020,11,5,2020,33,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.6509924\r
-10/05/2020,10,5,2020,54,2,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.63255722\r
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-01/05/2020,1,5,2020,72,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.3283767\r
-30/04/2020,30,4,2020,9,1,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.26846235\r
-29/04/2020,29,4,2020,20,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.27307115\r
-28/04/2020,28,4,2020,12,2,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.27191895\r
-27/04/2020,27,4,2020,17,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.25924476\r
-26/04/2020,26,4,2020,26,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.23965738\r
-25/04/2020,25,4,2020,22,3,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.22237439\r
-24/04/2020,24,4,2020,17,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.20624361\r
-23/04/2020,23,4,2020,18,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.22352659\r
-22/04/2020,22,4,2020,9,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.20624361\r
-21/04/2020,21,4,2020,18,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.2177656\r
-20/04/2020,20,4,2020,5,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.20509141\r
-19/04/2020,19,4,2020,20,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.19933042\r
-18/04/2020,18,4,2020,20,2,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.19933042\r
-17/04/2020,17,4,2020,20,1,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.18896063\r
-16/04/2020,16,4,2020,13,1,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.16591665\r
-15/04/2020,15,4,2020,19,1,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.17974303\r
-14/04/2020,14,4,2020,1,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.15785125\r
-13/04/2020,13,4,2020,0,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.17628644\r
-12/04/2020,12,4,2020,11,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.20278701\r
-11/04/2020,11,4,2020,8,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.19011282\r
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-31/03/2020,31,3,2020,17,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.1094589\r
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-29/03/2020,29,3,2020,0,2,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.06452314\r
-28/03/2020,28,3,2020,4,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.06452314\r
-27/03/2020,27,3,2020,9,1,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,0.06106654\r
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-24/03/2020,24,3,2020,0,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,\r
-23/03/2020,23,3,2020,3,1,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,\r
-22/03/2020,22,3,2020,9,1,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,\r
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-19/03/2020,19,3,2020,11,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,\r
-18/03/2020,18,3,2020,0,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,\r
-17/03/2020,17,3,2020,1,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,\r
-16/03/2020,16,3,2020,0,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,\r
-15/03/2020,15,3,2020,0,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,\r
-14/03/2020,14,3,2020,1,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,\r
-11/03/2020,11,3,2020,1,0,Democratic_Republic_of_the_Congo,CD,COD,86790568,Africa,\r
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-16/08/2020,16,8,2020,104,0,Denmark,DK,DNK,5806081,Europe,29.1763067\r
-15/08/2020,15,8,2020,165,0,Denmark,DK,DNK,5806081,Europe,27.38508126\r
-14/08/2020,14,8,2020,144,0,Denmark,DK,DNK,5806081,Europe,25.64552579\r
-13/08/2020,13,8,2020,111,0,Denmark,DK,DNK,5806081,Europe,24.73268974\r
-12/08/2020,12,8,2020,144,1,Denmark,DK,DNK,5806081,Europe,23.80263038\r
-11/08/2020,11,8,2020,373,3,Denmark,DK,DNK,5806081,Europe,21.83917172\r
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-01/08/2020,1,8,2020,64,0,Denmark,DK,DNK,5806081,Europe,10.60956607\r
-31/07/2020,31,7,2020,91,1,Denmark,DK,DNK,5806081,Europe,10.35121625\r
-30/07/2020,30,7,2020,57,1,Denmark,DK,DNK,5806081,Europe,9.33504028\r
-29/07/2020,29,7,2020,30,0,Denmark,DK,DNK,5806081,Europe,8.88723392\r
-28/07/2020,28,7,2020,109,0,Denmark,DK,DNK,5806081,Europe,8.78389399\r
-27/07/2020,27,7,2020,0,0,Denmark,DK,DNK,5806081,Europe,8.4738742\r
-26/07/2020,26,7,2020,0,0,Denmark,DK,DNK,5806081,Europe,8.4738742\r
-25/07/2020,25,7,2020,48,1,Denmark,DK,DNK,5806081,Europe,8.4738742\r
-24/07/2020,24,7,2020,40,1,Denmark,DK,DNK,5806081,Europe,8.16385441\r
-23/07/2020,23,7,2020,48,0,Denmark,DK,DNK,5806081,Europe,7.7504947\r
-22/07/2020,22,7,2020,40,0,Denmark,DK,DNK,5806081,Europe,7.13045512\r
-21/07/2020,21,7,2020,89,0,Denmark,DK,DNK,5806081,Europe,6.61375547\r
-20/07/2020,20,7,2020,0,0,Denmark,DK,DNK,5806081,Europe,5.87315265\r
-19/07/2020,19,7,2020,0,0,Denmark,DK,DNK,5806081,Europe,5.87315265\r
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-13/05/2020,13,5,2020,9,0,Eswatini,SZ,SWZ,1148133,Africa,9.84206534\r
-12/05/2020,12,5,2020,3,0,Eswatini,SZ,SWZ,1148133,Africa,9.58077157\r
-11/05/2020,11,5,2020,9,0,Eswatini,SZ,SWZ,1148133,Africa,9.84206534\r
-10/05/2020,10,5,2020,4,0,Eswatini,SZ,SWZ,1148133,Africa,10.71304457\r
-09/05/2020,9,5,2020,6,0,Eswatini,SZ,SWZ,1148133,Africa,10.36465288\r
-08/05/2020,8,5,2020,30,0,Eswatini,SZ,SWZ,1148133,Africa,10.53884872\r
-07/05/2020,7,5,2020,7,1,Eswatini,SZ,SWZ,1148133,Africa,8.01300895\r
-06/05/2020,6,5,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,8.01300895\r
-05/05/2020,5,5,2020,4,0,Eswatini,SZ,SWZ,1148133,Africa,8.01300895\r
-04/05/2020,4,5,2020,4,0,Eswatini,SZ,SWZ,1148133,Africa,7.8388131\r
-03/05/2020,3,5,2020,2,0,Eswatini,SZ,SWZ,1148133,Africa,7.75171518\r
-02/05/2020,2,5,2020,6,0,Eswatini,SZ,SWZ,1148133,Africa,7.57751933\r
-01/05/2020,1,5,2020,9,0,Eswatini,SZ,SWZ,1148133,Africa,7.31622556\r
-30/04/2020,30,4,2020,20,0,Eswatini,SZ,SWZ,1148133,Africa,6.53234425\r
-29/04/2020,29,4,2020,6,0,Eswatini,SZ,SWZ,1148133,Africa,4.87748371\r
-28/04/2020,28,4,2020,6,0,Eswatini,SZ,SWZ,1148133,Africa,4.35489617\r
-27/04/2020,27,4,2020,19,0,Eswatini,SZ,SWZ,1148133,Africa,3.91940655\r
-26/04/2020,26,4,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,2.26454601\r
-25/04/2020,25,4,2020,8,0,Eswatini,SZ,SWZ,1148133,Africa,2.43874185\r
-24/04/2020,24,4,2020,1,0,Eswatini,SZ,SWZ,1148133,Africa,1.74195847\r
-23/04/2020,23,4,2020,7,0,Eswatini,SZ,SWZ,1148133,Africa,1.65486054\r
-22/04/2020,22,4,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,1.21937093\r
-21/04/2020,21,4,2020,2,0,Eswatini,SZ,SWZ,1148133,Africa,1.21937093\r
-20/04/2020,20,4,2020,3,0,Eswatini,SZ,SWZ,1148133,Africa,1.132273\r
-19/04/2020,19,4,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,0.87097923\r
-18/04/2020,18,4,2020,3,1,Eswatini,SZ,SWZ,1148133,Africa,0.87097923\r
-17/04/2020,17,4,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,0.60968546\r
-16/04/2020,16,4,2020,1,0,Eswatini,SZ,SWZ,1148133,Africa,0.60968546\r
-15/04/2020,15,4,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,0.52258754\r
-14/04/2020,14,4,2020,1,0,Eswatini,SZ,SWZ,1148133,Africa,0.52258754\r
-13/04/2020,13,4,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,0.43548962\r
-12/04/2020,12,4,2020,2,0,Eswatini,SZ,SWZ,1148133,Africa,0.43548962\r
-11/04/2020,11,4,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,0.26129377\r
-10/04/2020,10,4,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,0.52258754\r
-09/04/2020,9,4,2020,2,0,Eswatini,SZ,SWZ,1148133,Africa,0.69678339\r
-08/04/2020,8,4,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,0.52258754\r
-07/04/2020,7,4,2020,1,0,Eswatini,SZ,SWZ,1148133,Africa,0.52258754\r
-06/04/2020,6,4,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,0.43548962\r
-05/04/2020,5,4,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,0.69678339\r
-04/04/2020,4,4,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,0.69678339\r
-03/04/2020,3,4,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,0.69678339\r
-02/04/2020,2,4,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,0.69678339\r
-01/04/2020,1,4,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,0.69678339\r
-31/03/2020,31,3,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,0.69678339\r
-30/03/2020,30,3,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,0.69678339\r
-29/03/2020,29,3,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,0.69678339\r
-28/03/2020,28,3,2020,3,0,Eswatini,SZ,SWZ,1148133,Africa,0.78388131\r
-27/03/2020,27,3,2020,2,0,Eswatini,SZ,SWZ,1148133,Africa,\r
-26/03/2020,26,3,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,\r
-25/03/2020,25,3,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,\r
-24/03/2020,24,3,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,\r
-23/03/2020,23,3,2020,3,0,Eswatini,SZ,SWZ,1148133,Africa,\r
-22/03/2020,22,3,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,\r
-21/03/2020,21,3,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,\r
-20/03/2020,20,3,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,\r
-19/03/2020,19,3,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,\r
-18/03/2020,18,3,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,\r
-17/03/2020,17,3,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,\r
-16/03/2020,16,3,2020,0,0,Eswatini,SZ,SWZ,1148133,Africa,\r
-15/03/2020,15,3,2020,1,0,Eswatini,SZ,SWZ,1148133,Africa,\r
-19/08/2020,19,8,2020,1386,28,Ethiopia,ET,ETH,112078727,Africa,11.46069405\r
-18/08/2020,18,8,2020,1460,16,Ethiopia,ET,ETH,112078727,Africa,10.74869453\r
-17/08/2020,17,8,2020,982,19,Ethiopia,ET,ETH,112078727,Africa,10.59701544\r
-16/08/2020,16,8,2020,1652,17,Ethiopia,ET,ETH,112078727,Africa,9.7208456\r
-15/08/2020,15,8,2020,1038,13,Ethiopia,ET,ETH,112078727,Africa,8.66533754\r
-14/08/2020,14,8,2020,1086,16,Ethiopia,ET,ETH,112078727,Africa,8.55559325\r
-13/08/2020,13,8,2020,943,23,Ethiopia,ET,ETH,112078727,Africa,8.30487662\r
-12/08/2020,12,8,2020,584,20,Ethiopia,ET,ETH,112078727,Africa,8.00776404\r
-11/08/2020,11,8,2020,773,13,Ethiopia,ET,ETH,112078727,Africa,8.06932791\r
-10/08/2020,10,8,2020,565,17,Ethiopia,ET,ETH,112078727,Africa,7.8962353\r
-09/08/2020,9,8,2020,801,10,Ethiopia,ET,ETH,112078727,Africa,8.52971858\r
-08/08/2020,8,8,2020,552,15,Ethiopia,ET,ETH,112078727,Africa,8.49313715\r
-07/08/2020,7,8,2020,564,9,Ethiopia,ET,ETH,112078727,Africa,8.36554826\r
-06/08/2020,6,8,2020,459,13,Ethiopia,ET,ETH,112078727,Africa,8.26561851\r
-05/08/2020,5,8,2020,588,7,Ethiopia,ET,ETH,112078727,Africa,8.35662596\r
-04/08/2020,4,8,2020,1290,52,Ethiopia,ET,ETH,112078727,Africa,8.10323265\r
-03/08/2020,3,8,2020,0,0,Ethiopia,ET,ETH,112078727,Africa,7.58038588\r
-02/08/2020,2,8,2020,469,10,Ethiopia,ET,ETH,112078727,Africa,7.89801976\r
-01/08/2020,1,8,2020,915,11,Ethiopia,ET,ETH,112078727,Africa,7.78649101\r
-31/07/2020,31,7,2020,805,10,Ethiopia,ET,ETH,112078727,Africa,7.26275201\r
-30/07/2020,30,7,2020,610,14,Ethiopia,ET,ETH,112078727,Africa,6.80682249\r
-29/07/2020,29,7,2020,653,11,Ethiopia,ET,ETH,112078727,Africa,6.45171496\r
-28/07/2020,28,7,2020,579,5,Ethiopia,ET,ETH,112078727,Africa,6.05021147\r
-27/07/2020,27,7,2020,1275,23,Ethiopia,ET,ETH,112078727,Africa,5.71740969\r
-26/07/2020,26,7,2020,760,3,Ethiopia,ET,ETH,112078727,Africa,4.72078881\r
-25/07/2020,25,7,2020,409,9,Ethiopia,ET,ETH,112078727,Africa,4.29430288\r
-24/07/2020,24,7,2020,452,8,Ethiopia,ET,ETH,112078727,Africa,4.06053862\r
-23/07/2020,23,7,2020,561,7,Ethiopia,ET,ETH,112078727,Africa,3.83480444\r
-22/07/2020,22,7,2020,304,3,Ethiopia,ET,ETH,112078727,Africa,3.43062426\r
-21/07/2020,21,7,2020,704,3,Ethiopia,ET,ETH,112078727,Africa,3.40921074\r
-20/07/2020,20,7,2020,356,4,Ethiopia,ET,ETH,112078727,Africa,3.26288503\r
-19/07/2020,19,7,2020,344,13,Ethiopia,ET,ETH,112078727,Africa,2.94525115\r
-18/07/2020,18,7,2020,328,2,Ethiopia,ET,ETH,112078727,Africa,2.63832404\r
-17/07/2020,17,7,2020,294,2,Ethiopia,ET,ETH,112078727,Africa,2.34567261\r
-16/07/2020,16,7,2020,212,7,Ethiopia,ET,ETH,112078727,Africa,2.083357\r
-15/07/2020,15,7,2020,203,11,Ethiopia,ET,ETH,112078727,Africa,1.89420424\r
-14/07/2020,14,7,2020,206,1,Ethiopia,ET,ETH,112078727,Africa,1.71308156\r
-13/07/2020,13,7,2020,158,3,Ethiopia,ET,ETH,112078727,Africa,1.66936229\r
-12/07/2020,12,7,2020,282,0,Ethiopia,ET,ETH,112078727,Africa,1.63456532\r
-11/07/2020,11,7,2020,147,4,Ethiopia,ET,ETH,112078727,Africa,1.51232981\r
-10/07/2020,10,7,2020,199,0,Ethiopia,ET,ETH,112078727,Africa,1.6042295\r
-09/07/2020,9,7,2020,108,1,Ethiopia,ET,ETH,112078727,Africa,1.55248016\r
-08/07/2020,8,7,2020,280,3,Ethiopia,ET,ETH,112078727,Africa,1.6220741\r
-07/07/2020,7,7,2020,540,13,Ethiopia,ET,ETH,112078727,Africa,1.53731225\r
-06/07/2020,6,7,2020,0,0,Ethiopia,ET,ETH,112078727,Africa,1.17239019\r
-05/07/2020,5,7,2020,0,0,Ethiopia,ET,ETH,112078727,Africa,1.22860068\r
-04/07/2020,4,7,2020,0,0,Ethiopia,ET,ETH,112078727,Africa,1.58460044\r
-03/07/2020,3,7,2020,0,0,Ethiopia,ET,ETH,112078727,Africa,1.68809912\r
-02/07/2020,2,7,2020,0,0,Ethiopia,ET,ETH,112078727,Africa,1.86208396\r
-01/07/2020,1,7,2020,0,0,Ethiopia,ET,ETH,112078727,Africa,1.97718163\r
-30/06/2020,30,6,2020,157,5,Ethiopia,ET,ETH,112078727,Africa,2.0744347\r
-29/06/2020,29,6,2020,119,4,Ethiopia,ET,ETH,112078727,Africa,2.09138707\r
-28/06/2020,28,6,2020,145,5,Ethiopia,ET,ETH,112078727,Africa,2.14492086\r
-27/06/2020,27,6,2020,250,8,Ethiopia,ET,ETH,112078727,Africa,2.23949724\r
-26/06/2020,26,6,2020,141,3,Ethiopia,ET,ETH,112078727,Africa,2.23503609\r
-25/06/2020,25,6,2020,186,3,Ethiopia,ET,ETH,112078727,Africa,2.25555738\r
-24/06/2020,24,6,2020,185,0,Ethiopia,ET,ETH,112078727,Africa,2.2412817\r
-23/06/2020,23,6,2020,131,1,Ethiopia,ET,ETH,112078727,Africa,2.23682055\r
-22/06/2020,22,6,2020,63,2,Ethiopia,ET,ETH,112078727,Africa,2.2412817\r
-21/06/2020,21,6,2020,399,0,Ethiopia,ET,ETH,112078727,Africa,2.26180299\r
-20/06/2020,20,6,2020,116,7,Ethiopia,ET,ETH,112078727,Africa,2.0209009\r
-19/06/2020,19,6,2020,195,2,Ethiopia,ET,ETH,112078727,Africa,2.06818909\r
-18/06/2020,18,6,2020,129,2,Ethiopia,ET,ETH,112078727,Africa,2.02803874\r
-17/06/2020,17,6,2020,109,1,Ethiopia,ET,ETH,112078727,Africa,2.03963773\r
-16/06/2020,16,6,2020,176,3,Ethiopia,ET,ETH,112078727,Africa,2.02000867\r
-15/06/2020,15,6,2020,179,2,Ethiopia,ET,ETH,112078727,Africa,1.93881574\r
-14/06/2020,14,6,2020,251,8,Ethiopia,ET,ETH,112078727,Africa,1.87635964\r
-13/06/2020,13,6,2020,245,7,Ethiopia,ET,ETH,112078727,Africa,1.73717176\r
-12/06/2020,12,6,2020,164,5,Ethiopia,ET,ETH,112078727,Africa,1.64081093\r
-11/06/2020,11,6,2020,170,3,Ethiopia,ET,ETH,112078727,Africa,1.58370821\r
-10/06/2020,10,6,2020,180,5,Ethiopia,ET,ETH,112078727,Africa,1.45879601\r
-09/06/2020,9,6,2020,136,0,Ethiopia,ET,ETH,112078727,Africa,1.3392372\r
-08/06/2020,8,6,2020,86,7,Ethiopia,ET,ETH,112078727,Africa,1.28302671\r
-07/06/2020,7,6,2020,129,1,Ethiopia,ET,ETH,112078727,Africa,1.28481117\r
-06/06/2020,6,6,2020,169,1,Ethiopia,ET,ETH,112078727,Africa,1.22413953\r
-05/06/2020,5,6,2020,150,1,Ethiopia,ET,ETH,112078727,Africa,1.10368848\r
-04/06/2020,4,6,2020,142,3,Ethiopia,ET,ETH,112078727,Africa,0.97877628\r
-03/06/2020,3,6,2020,87,2,Ethiopia,ET,ETH,112078727,Africa,0.87349315\r
-02/06/2020,2,6,2020,85,1,Ethiopia,ET,ETH,112078727,Africa,0.80746813\r
-01/06/2020,1,6,2020,109,3,Ethiopia,ET,ETH,112078727,Africa,0.76285663\r
-31/05/2020,31,5,2020,95,0,Ethiopia,ET,ETH,112078727,Africa,0.67541809\r
-30/05/2020,30,5,2020,137,1,Ethiopia,ET,ETH,112078727,Africa,0.60760861\r
-29/05/2020,29,5,2020,100,1,Ethiopia,ET,ETH,112078727,Africa,0.49875656\r
-28/05/2020,28,5,2020,30,0,Ethiopia,ET,ETH,112078727,Africa,0.41756363\r
-27/05/2020,27,5,2020,46,1,Ethiopia,ET,ETH,112078727,Africa,0.39258119\r
-26/05/2020,26,5,2020,73,0,Ethiopia,ET,ETH,112078727,Africa,0.36135314\r
-25/05/2020,25,5,2020,88,0,Ethiopia,ET,ETH,112078727,Africa,0.30603488\r
-24/05/2020,24,5,2020,61,0,Ethiopia,ET,ETH,112078727,Africa,0.25339331\r
-23/05/2020,23,5,2020,34,0,Ethiopia,ET,ETH,112078727,Africa,0.21324296\r
-22/05/2020,22,5,2020,10,0,Ethiopia,ET,ETH,112078727,Africa,0.18558384\r
-21/05/2020,21,5,2020,24,0,Ethiopia,ET,ETH,112078727,Africa,0.2025362\r
-20/05/2020,20,5,2020,13,0,Ethiopia,ET,ETH,112078727,Africa,0.19629059\r
-19/05/2020,19,5,2020,35,0,Ethiopia,ET,ETH,112078727,Africa,0.18915276\r
-18/05/2020,18,5,2020,11,0,Ethiopia,ET,ETH,112078727,Africa,0.16238586\r
-17/05/2020,17,5,2020,19,0,Ethiopia,ET,ETH,112078727,Africa,0.15435579\r
-16/05/2020,16,5,2020,15,0,Ethiopia,ET,ETH,112078727,Africa,0.13740342\r
-15/05/2020,15,5,2020,9,0,Ethiopia,ET,ETH,112078727,Africa,0.12580443\r
-14/05/2020,14,5,2020,2,0,Ethiopia,ET,ETH,112078727,Africa,0.11866659\r
-13/05/2020,13,5,2020,11,0,Ethiopia,ET,ETH,112078727,Africa,0.12045105\r
-12/05/2020,12,5,2020,11,0,Ethiopia,ET,ETH,112078727,Africa,0.11242098\r
-11/05/2020,11,5,2020,29,0,Ethiopia,ET,ETH,112078727,Africa,0.10349868\r
-10/05/2020,10,5,2020,16,1,Ethiopia,ET,ETH,112078727,Africa,0.07851624\r
-09/05/2020,9,5,2020,3,0,Ethiopia,ET,ETH,112078727,Africa,0.06870171\r
-08/05/2020,8,5,2020,29,0,Ethiopia,ET,ETH,112078727,Africa,0.06691725\r
-07/05/2020,7,5,2020,17,0,Ethiopia,ET,ETH,112078727,Africa,0.04104258\r
-06/05/2020,6,5,2020,5,1,Ethiopia,ET,ETH,112078727,Africa,0.02765913\r
-05/05/2020,5,5,2020,5,0,Ethiopia,ET,ETH,112078727,Africa,0.02587467\r
-04/05/2020,4,5,2020,2,0,Ethiopia,ET,ETH,112078727,Africa,0.02409021\r
-03/05/2020,3,5,2020,0,0,Ethiopia,ET,ETH,112078727,Africa,0.02498244\r
-02/05/2020,2,5,2020,2,0,Ethiopia,ET,ETH,112078727,Africa,0.03301251\r
-01/05/2020,1,5,2020,1,0,Ethiopia,ET,ETH,112078727,Africa,0.03479697\r
-30/04/2020,30,4,2020,4,0,Ethiopia,ET,ETH,112078727,Africa,0.04015035\r
-29/04/2020,29,4,2020,2,0,Ethiopia,ET,ETH,112078727,Africa,0.03925812\r
-28/04/2020,28,4,2020,1,0,Ethiopia,ET,ETH,112078727,Africa,0.0446115\r
-27/04/2020,27,4,2020,1,0,Ethiopia,ET,ETH,112078727,Africa,0.04639596\r
-26/04/2020,26,4,2020,5,0,Ethiopia,ET,ETH,112078727,Africa,0.04728819\r
-25/04/2020,25,4,2020,1,0,Ethiopia,ET,ETH,112078727,Africa,0.04639596\r
-24/04/2020,24,4,2020,0,0,Ethiopia,ET,ETH,112078727,Africa,0.0535338\r
-23/04/2020,23,4,2020,2,0,Ethiopia,ET,ETH,112078727,Africa,0.05442603\r
-22/04/2020,22,4,2020,3,0,Ethiopia,ET,ETH,112078727,Africa,0.05531826\r
-21/04/2020,21,4,2020,3,0,Ethiopia,ET,ETH,112078727,Africa,0.05977941\r
-20/04/2020,20,4,2020,3,0,Ethiopia,ET,ETH,112078727,Africa,0.05799495\r
-19/04/2020,19,4,2020,9,0,Ethiopia,ET,ETH,112078727,Africa,0.05977941\r
-18/04/2020,18,4,2020,4,0,Ethiopia,ET,ETH,112078727,Africa,0.05442603\r
-17/04/2020,17,4,2020,7,0,Ethiopia,ET,ETH,112078727,Africa,0.05621049\r
-16/04/2020,16,4,2020,3,0,Ethiopia,ET,ETH,112078727,Africa,0.04996488\r
-15/04/2020,15,4,2020,8,0,Ethiopia,ET,ETH,112078727,Africa,0.05085711\r
-14/04/2020,14,4,2020,3,0,Ethiopia,ET,ETH,112078727,Africa,0.04550373\r
-13/04/2020,13,4,2020,2,0,Ethiopia,ET,ETH,112078727,Africa,0.04907265\r
-12/04/2020,12,4,2020,4,1,Ethiopia,ET,ETH,112078727,Africa,0.04728819\r
-11/04/2020,11,4,2020,9,0,Ethiopia,ET,ETH,112078727,Africa,0.04371927\r
-10/04/2020,10,4,2020,1,0,Ethiopia,ET,ETH,112078727,Africa,0.03925812\r
-09/04/2020,9,4,2020,3,0,Ethiopia,ET,ETH,112078727,Africa,0.03836589\r
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-30/07/2020,30,7,2020,10,0,Finland,FI,FIN,5517919,Europe,2.19285568\r
-29/07/2020,29,7,2020,6,0,Finland,FI,FIN,5517919,Europe,2.01162793\r
-28/07/2020,28,7,2020,5,0,Finland,FI,FIN,5517919,Europe,1.90289129\r
-27/07/2020,27,7,2020,5,0,Finland,FI,FIN,5517919,Europe,1.83040019\r
-26/07/2020,26,7,2020,8,0,Finland,FI,FIN,5517919,Europe,1.77603187\r
-25/07/2020,25,7,2020,8,1,Finland,FI,FIN,5517919,Europe,1.63104968\r
-24/07/2020,24,7,2020,10,0,Finland,FI,FIN,5517919,Europe,1.54043581\r
-23/07/2020,23,7,2020,11,0,Finland,FI,FIN,5517919,Europe,1.43169916\r
-22/07/2020,22,7,2020,11,0,Finland,FI,FIN,5517919,Europe,1.35920806\r
-21/07/2020,21,7,2020,2,0,Finland,FI,FIN,5517919,Europe,1.17798032\r
-20/07/2020,20,7,2020,20,0,Finland,FI,FIN,5517919,Europe,1.1961031\r
-19/07/2020,19,7,2020,17,0,Finland,FI,FIN,5517919,Europe,0.86989316\r
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-29/06/2020,29,6,2020,0,0,Finland,FI,FIN,5517919,Europe,1.57668135\r
-28/06/2020,28,6,2020,0,0,Finland,FI,FIN,5517919,Europe,1.88476852\r
-27/06/2020,27,6,2020,19,1,Finland,FI,FIN,5517919,Europe,2.13848735\r
-26/06/2020,26,6,2020,5,0,Finland,FI,FIN,5517919,Europe,1.95725961\r
-25/06/2020,25,6,2020,12,0,Finland,FI,FIN,5517919,Europe,2.30159232\r
-24/06/2020,24,6,2020,11,0,Finland,FI,FIN,5517919,Europe,2.35596064\r
-23/06/2020,23,6,2020,1,1,Finland,FI,FIN,5517919,Europe,2.59155671\r
-22/06/2020,22,6,2020,1,0,Finland,FI,FIN,5517919,Europe,2.93588942\r
-21/06/2020,21,6,2020,9,0,Finland,FI,FIN,5517919,Europe,3.2258538\r
-20/06/2020,20,6,2020,16,0,Finland,FI,FIN,5517919,Europe,3.47957264\r
-19/06/2020,19,6,2020,0,0,Finland,FI,FIN,5517919,Europe,3.73329148\r
-18/06/2020,18,6,2020,5,0,Finland,FI,FIN,5517919,Europe,3.73329148\r
-17/06/2020,17,6,2020,4,0,Finland,FI,FIN,5517919,Europe,4.07762419\r
-16/06/2020,16,6,2020,4,0,Finland,FI,FIN,5517919,Europe,4.04137864\r
-15/06/2020,15,6,2020,17,1,Finland,FI,FIN,5517919,Europe,4.44007967\r
-14/06/2020,14,6,2020,14,0,Finland,FI,FIN,5517919,Europe,4.73004406\r
-13/06/2020,13,6,2020,9,0,Finland,FI,FIN,5517919,Europe,5.38246393\r
-12/06/2020,12,6,2020,24,1,Finland,FI,FIN,5517919,Europe,5.81741051\r
-11/06/2020,11,6,2020,15,0,Finland,FI,FIN,5517919,Europe,6.30672542\r
-10/06/2020,10,6,2020,24,1,Finland,FI,FIN,5517919,Europe,7.19474135\r
-09/06/2020,9,6,2020,20,0,Finland,FI,FIN,5517919,Europe,7.28535522\r
-08/06/2020,8,6,2020,17,1,Finland,FI,FIN,5517919,Europe,7.28535522\r
-07/06/2020,7,6,2020,23,0,Finland,FI,FIN,5517919,Europe,7.17661858\r
-06/06/2020,6,6,2020,30,0,Finland,FI,FIN,5517919,Europe,7.32160077\r
-05/06/2020,5,6,2020,0,1,Finland,FI,FIN,5517919,Europe,7.57531961\r
-04/06/2020,4,6,2020,24,1,Finland,FI,FIN,5517919,Europe,8.48145832\r
-03/06/2020,3,6,2020,2,0,Finland,FI,FIN,5517919,Europe,8.8439138\r
-02/06/2020,2,6,2020,26,0,Finland,FI,FIN,5517919,Europe,9.15200096\r
-01/06/2020,1,6,2020,33,4,Finland,FI,FIN,5517919,Europe,9.27886038\r
-31/05/2020,31,5,2020,50,2,Finland,FI,FIN,5517919,Europe,9.78629806\r
-30/05/2020,30,5,2020,33,1,Finland,FI,FIN,5517919,Europe,9.93128025\r
-29/05/2020,29,5,2020,51,0,Finland,FI,FIN,5517919,Europe,10.83741896\r
-28/05/2020,28,5,2020,64,1,Finland,FI,FIN,5517919,Europe,11.56232993\r
-27/05/2020,27,5,2020,29,4,Finland,FI,FIN,5517919,Europe,11.32673386\r
-26/05/2020,26,5,2020,20,1,Finland,FI,FIN,5517919,Europe,11.14550612\r
-25/05/2020,25,5,2020,11,1,Finland,FI,FIN,5517919,Europe,11.18175167\r
-24/05/2020,24,5,2020,31,0,Finland,FI,FIN,5517919,Europe,12.46846864\r
-23/05/2020,23,5,2020,44,0,Finland,FI,FIN,5517919,Europe,14.48009657\r
-22/05/2020,22,5,2020,50,2,Finland,FI,FIN,5517919,Europe,14.86067483\r
-21/05/2020,21,5,2020,44,3,Finland,FI,FIN,5517919,Europe,15.76681354\r
-20/05/2020,20,5,2020,19,1,Finland,FI,FIN,5517919,Europe,17.88717812\r
-19/05/2020,19,5,2020,33,2,Finland,FI,FIN,5517919,Europe,19.08328122\r
-18/05/2020,18,5,2020,61,1,Finland,FI,FIN,5517919,Europe,19.80819218\r
-17/05/2020,17,5,2020,58,4,Finland,FI,FIN,5517919,Europe,20.06191102\r
-16/05/2020,16,5,2020,83,6,Finland,FI,FIN,5517919,Europe,21.33050521\r
-15/05/2020,15,5,2020,91,3,Finland,FI,FIN,5517919,Europe,20.84119031\r
-14/05/2020,14,5,2020,51,9,Finland,FI,FIN,5517919,Europe,20.80494476\r
-13/05/2020,13,5,2020,19,4,Finland,FI,FIN,5517919,Europe,22.88906379\r
-12/05/2020,12,5,2020,22,4,Finland,FI,FIN,5517919,Europe,23.36025592\r
-11/05/2020,11,5,2020,82,2,Finland,FI,FIN,5517919,Europe,25.11816502\r
-10/05/2020,10,5,2020,142,5,Finland,FI,FIN,5517919,Europe,25.46249773\r
-09/05/2020,9,5,2020,65,5,Finland,FI,FIN,5517919,Europe,24.33888573\r
-08/05/2020,8,5,2020,100,3,Finland,FI,FIN,5517919,Europe,25.17253334\r
-07/05/2020,7,5,2020,161,6,Finland,FI,FIN,5517919,Europe,26.16928592\r
-06/05/2020,6,5,2020,85,6,Finland,FI,FIN,5517919,Europe,25.33563831\r
-05/05/2020,5,5,2020,73,10,Finland,FI,FIN,5517919,Europe,26.44112753\r
-04/05/2020,4,5,2020,75,10,Finland,FI,FIN,5517919,Europe,26.65860082\r
-03/05/2020,3,5,2020,128,2,Finland,FI,FIN,5517919,Europe,27.14791573\r
-02/05/2020,2,5,2020,56,7,Finland,FI,FIN,5517919,Europe,28.30777327\r
-01/05/2020,1,5,2020,89,5,Finland,FI,FIN,5517919,Europe,29.46763082\r
-30/04/2020,30,4,2020,166,7,Finland,FI,FIN,5517919,Europe,30.24691011\r
-29/04/2020,29,4,2020,45,6,Finland,FI,FIN,5517919,Europe,28.61586044\r
-28/04/2020,28,4,2020,119,3,Finland,FI,FIN,5517919,Europe,29.55824469\r
-27/04/2020,27,4,2020,101,4,Finland,FI,FIN,5517919,Europe,29.03268424\r
-26/04/2020,26,4,2020,80,9,Finland,FI,FIN,5517919,Europe,28.45275547\r
-25/04/2020,25,4,2020,111,5,Finland,FI,FIN,5517919,Europe,29.46763082\r
-24/04/2020,24,4,2020,155,23,Finland,FI,FIN,5517919,Europe,30.42813785\r
-23/04/2020,23,4,2020,115,8,Finland,FI,FIN,5517919,Europe,29.75759521\r
-22/04/2020,22,4,2020,146,43,Finland,FI,FIN,5517919,Europe,30.91745276\r
-21/04/2020,21,4,2020,85,4,Finland,FI,FIN,5517919,Europe,30.66373392\r
-20/04/2020,20,4,2020,102,4,Finland,FI,FIN,5517919,Europe,33.63586888\r
-19/04/2020,19,4,2020,192,8,Finland,FI,FIN,5517919,Europe,32.60287076\r
-18/04/2020,18,4,2020,120,7,Finland,FI,FIN,5517919,Europe,33.96207882\r
-17/04/2020,17,4,2020,132,3,Finland,FI,FIN,5517919,Europe,33.54525501\r
-16/04/2020,16,4,2020,76,8,Finland,FI,FIN,5517919,Europe,32.45788856\r
-15/04/2020,15,4,2020,97,5,Finland,FI,FIN,5517919,Europe,32.20416972\r
-14/04/2020,14,4,2020,90,3,Finland,FI,FIN,5517919,Europe,31.7329776\r
-13/04/2020,13,4,2020,69,7,Finland,FI,FIN,5517919,Europe,31.82359147\r
-12/04/2020,12,4,2020,136,1,Finland,FI,FIN,5517919,Europe,30.57312005\r
-11/04/2020,11,4,2020,164,6,Finland,FI,FIN,5517919,Europe,31.60611818\r
-10/04/2020,10,4,2020,118,2,Finland,FI,FIN,5517919,Europe,29.84820908\r
-09/04/2020,9,4,2020,179,6,Finland,FI,FIN,5517919,Europe,29.12329811\r
-08/04/2020,8,4,2020,132,7,Finland,FI,FIN,5517919,Europe,27.47412566\r
-07/04/2020,7,4,2020,249,0,Finland,FI,FIN,5517919,Europe,26.74921469\r
-06/04/2020,6,4,2020,45,2,Finland,FI,FIN,5517919,Europe,23.57772921\r
-05/04/2020,5,4,2020,267,5,Finland,FI,FIN,5517919,Europe,24.66509566\r
-04/04/2020,4,4,2020,97,1,Finland,FI,FIN,5517919,Europe,21.11303192\r
-03/04/2020,3,4,2020,72,2,Finland,FI,FIN,5517919,Europe,20.26126154\r
-02/04/2020,2,4,2020,62,0,Finland,FI,FIN,5517919,Europe,19.5182278\r
-01/04/2020,1,4,2020,71,4,Finland,FI,FIN,5517919,Europe,19.30075451\r
-31/03/2020,31,3,2020,95,2,Finland,FI,FIN,5517919,Europe,18.86580793\r
-30/03/2020,30,3,2020,0,2,Finland,FI,FIN,5517919,Europe,17.23475825\r
-29/03/2020,29,3,2020,193,2,Finland,FI,FIN,5517919,Europe,18.26775638\r
-28/03/2020,28,3,2020,67,3,Finland,FI,FIN,5517919,Europe,15.25937586\r
-27/03/2020,27,3,2020,78,1,Finland,FI,FIN,5517919,Europe,14.55258767\r
-26/03/2020,26,3,2020,88,2,Finland,FI,FIN,5517919,Europe,14.8787976\r
-25/03/2020,25,3,2020,92,0,Finland,FI,FIN,5517919,Europe,13.62832619\r
-24/03/2020,24,3,2020,74,0,Finland,FI,FIN,5517919,Europe,12.1422587\r
-23/03/2020,23,3,2020,105,0,Finland,FI,FIN,5517919,Europe,11.00052393\r
-22/03/2020,22,3,2020,71,1,Finland,FI,FIN,5517919,Europe,9.22449206\r
-21/03/2020,21,3,2020,50,0,Finland,FI,FIN,5517919,Europe,8.02838896\r
-20/03/2020,20,3,2020,31,0,Finland,FI,FIN,5517919,Europe,7.14037303\r
-19/03/2020,19,3,2020,50,0,Finland,FI,FIN,5517919,Europe,6.63293535\r
-18/03/2020,18,3,2020,47,0,Finland,FI,FIN,5517919,Europe,5.72679664\r
-17/03/2020,17,3,2020,5,0,Finland,FI,FIN,5517919,Europe,4.89314903\r
-16/03/2020,16,3,2020,57,0,Finland,FI,FIN,5517919,Europe,4.80253516\r
-15/03/2020,15,3,2020,27,0,Finland,FI,FIN,5517919,Europe,3.7876598\r
-14/03/2020,14,3,2020,28,0,Finland,FI,FIN,5517919,Europe,3.2983449\r
-13/03/2020,13,3,2020,96,0,Finland,FI,FIN,5517919,Europe,2.79090722\r
-12/03/2020,12,3,2020,19,0,Finland,FI,FIN,5517919,Europe,1.0511209\r
-10/03/2020,10,3,2020,10,0,Finland,FI,FIN,5517919,Europe,0.70678819\r
-09/03/2020,9,3,2020,11,0,Finland,FI,FIN,5517919,Europe,0.52556045\r
-07/03/2020,7,3,2020,7,0,Finland,FI,FIN,5517919,Europe,0.32620994\r
-06/03/2020,6,3,2020,5,0,Finland,FI,FIN,5517919,Europe,0.19935052\r
-04/03/2020,4,3,2020,1,0,Finland,FI,FIN,5517919,Europe,0.10873665\r
-02/03/2020,2,3,2020,3,0,Finland,FI,FIN,5517919,Europe,0.09061387\r
-01/03/2020,1,3,2020,0,0,Finland,FI,FIN,5517919,Europe,0.03624555\r
-29/02/2020,29,2,2020,1,0,Finland,FI,FIN,5517919,Europe,0.03624555\r
-28/02/2020,28,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0.01812277\r
-27/02/2020,27,2,2020,1,0,Finland,FI,FIN,5517919,Europe,0.01812277\r
-26/02/2020,26,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-25/02/2020,25,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-24/02/2020,24,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-23/02/2020,23,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-22/02/2020,22,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-21/02/2020,21,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-20/02/2020,20,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-19/02/2020,19,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-18/02/2020,18,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-17/02/2020,17,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-16/02/2020,16,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-15/02/2020,15,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-14/02/2020,14,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-13/02/2020,13,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-12/02/2020,12,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0.01812277\r
-11/02/2020,11,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0.01812277\r
-10/02/2020,10,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0.01812277\r
-09/02/2020,9,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0.01812277\r
-08/02/2020,8,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0.01812277\r
-07/02/2020,7,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0.01812277\r
-06/02/2020,6,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0.01812277\r
-05/02/2020,5,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0.01812277\r
-04/02/2020,4,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0.01812277\r
-03/02/2020,3,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0.01812277\r
-02/02/2020,2,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0.01812277\r
-01/02/2020,1,2,2020,0,0,Finland,FI,FIN,5517919,Europe,0.01812277\r
-31/01/2020,31,1,2020,0,0,Finland,FI,FIN,5517919,Europe,0.01812277\r
-30/01/2020,30,1,2020,1,0,Finland,FI,FIN,5517919,Europe,0.01812277\r
-29/01/2020,29,1,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-28/01/2020,28,1,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-27/01/2020,27,1,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-26/01/2020,26,1,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-25/01/2020,25,1,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-24/01/2020,24,1,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-23/01/2020,23,1,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-22/01/2020,22,1,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-21/01/2020,21,1,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-20/01/2020,20,1,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-19/01/2020,19,1,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-18/01/2020,18,1,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-17/01/2020,17,1,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-16/01/2020,16,1,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-15/01/2020,15,1,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-14/01/2020,14,1,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-13/01/2020,13,1,2020,0,0,Finland,FI,FIN,5517919,Europe,0\r
-12/01/2020,12,1,2020,0,0,Finland,FI,FIN,5517919,Europe,\r
-11/01/2020,11,1,2020,0,0,Finland,FI,FIN,5517919,Europe,\r
-10/01/2020,10,1,2020,0,0,Finland,FI,FIN,5517919,Europe,\r
-09/01/2020,9,1,2020,0,0,Finland,FI,FIN,5517919,Europe,\r
-08/01/2020,8,1,2020,0,0,Finland,FI,FIN,5517919,Europe,\r
-07/01/2020,7,1,2020,0,0,Finland,FI,FIN,5517919,Europe,\r
-06/01/2020,6,1,2020,0,0,Finland,FI,FIN,5517919,Europe,\r
-05/01/2020,5,1,2020,0,0,Finland,FI,FIN,5517919,Europe,\r
-04/01/2020,4,1,2020,0,0,Finland,FI,FIN,5517919,Europe,\r
-03/01/2020,3,1,2020,0,0,Finland,FI,FIN,5517919,Europe,\r
-02/01/2020,2,1,2020,0,0,Finland,FI,FIN,5517919,Europe,\r
-01/01/2020,1,1,2020,0,0,Finland,FI,FIN,5517919,Europe,\r
-31/12/2019,31,12,2019,0,0,Finland,FI,FIN,5517919,Europe,\r
-19/08/2020,19,8,2020,2238,22,France,FR,FRA,67012883,Europe,43.17528019\r
-18/08/2020,18,8,2020,493,19,France,FR,FRA,67012883,Europe,41.38607199\r
-17/08/2020,17,8,2020,3015,1,France,FR,FRA,67012883,Europe,45.68822983\r
-16/08/2020,16,8,2020,3310,3,France,FR,FRA,67012883,Europe,41.18909494\r
-15/08/2020,15,8,2020,2846,18,France,FR,FRA,67012883,Europe,36.24974619\r
-14/08/2020,14,8,2020,2669,17,France,FR,FRA,67012883,Europe,34.01137062\r
-13/08/2020,13,8,2020,2524,17,France,FR,FRA,67012883,Europe,32.08338313\r
-12/08/2020,12,8,2020,1397,14,France,FR,FRA,67012883,Europe,30.3941557\r
-11/08/2020,11,8,2020,4854,16,France,FR,FRA,67012883,Europe,29.39136345\r
-10/08/2020,10,8,2020,0,0,France,FR,FRA,67012883,Europe,25.95471083\r
-09/08/2020,9,8,2020,0,0,France,FR,FRA,67012883,Europe,25.95471083\r
-08/08/2020,8,8,2020,2288,12,France,FR,FRA,67012883,Europe,25.95471083\r
-07/08/2020,7,8,2020,1604,7,France,FR,FRA,67012883,Europe,24.22668489\r
-06/08/2020,6,8,2020,1695,9,France,FR,FRA,67012883,Europe,23.41788518\r
-05/08/2020,5,8,2020,1039,2,France,FR,FRA,67012883,Europe,22.37778667\r
-04/08/2020,4,8,2020,3376,29,France,FR,FRA,67012883,Europe,21.69881275\r
-03/08/2020,3,8,2020,0,0,France,FR,FRA,67012883,Europe,19.76485626\r
-02/08/2020,2,8,2020,0,0,France,FR,FRA,67012883,Europe,19.76485626\r
-01/08/2020,1,8,2020,1346,11,France,FR,FRA,67012883,Europe,19.76485626\r
-31/07/2020,31,7,2020,1377,16,France,FR,FRA,67012883,Europe,19.00380857\r
-30/07/2020,30,7,2020,1392,15,France,FR,FRA,67012883,Europe,17.7458415\r
-29/07/2020,29,7,2020,725,14,France,FR,FRA,67012883,Europe,17.05194507\r
-28/07/2020,28,7,2020,2551,17,France,FR,FRA,67012883,Europe,15.97006355\r
-27/07/2020,27,7,2020,0,0,France,FR,FRA,67012883,Europe,14.5882397\r
-26/07/2020,26,7,2020,0,0,France,FR,FRA,67012883,Europe,14.5882397\r
-25/07/2020,25,7,2020,1130,10,France,FR,FRA,67012883,Europe,14.5882397\r
-24/07/2020,24,7,2020,1062,10,France,FR,FRA,67012883,Europe,13.88389752\r
-23/07/2020,23,7,2020,998,7,France,FR,FRA,67012883,Europe,13.2258151\r
-22/07/2020,22,7,2020,584,0,France,FR,FRA,67012883,Europe,12.72591123\r
-21/07/2020,21,7,2020,2080,13,France,FR,FRA,67012883,Europe,12.56325593\r
-20/07/2020,20,7,2020,0,0,France,FR,FRA,67012883,Europe,11.51121942\r
-19/07/2020,19,7,2020,0,0,France,FR,FRA,67012883,Europe,11.51121942\r
-18/07/2020,18,7,2020,836,14,France,FR,FRA,67012883,Europe,11.51121942\r
-17/07/2020,17,7,2020,534,18,France,FR,FRA,67012883,Europe,11.13218782\r
-16/07/2020,16,7,2020,927,91,France,FR,FRA,67012883,Europe,11.31871912\r
-15/07/2020,15,7,2020,0,0,France,FR,FRA,67012883,Europe,11.30528887\r
-14/07/2020,14,7,2020,1625,25,France,FR,FRA,67012883,Europe,12.11259632\r
-13/07/2020,13,7,2020,0,0,France,FR,FRA,67012883,Europe,11.66342896\r
-12/07/2020,12,7,2020,0,0,France,FR,FRA,67012883,Europe,11.66342896\r
-11/07/2020,11,7,2020,658,25,France,FR,FRA,67012883,Europe,11.66342896\r
-10/07/2020,10,7,2020,621,14,France,FR,FRA,67012883,Europe,13.05122181\r
-09/07/2020,9,7,2020,663,32,France,FR,FRA,67012883,Europe,12.12453432\r
-08/07/2020,8,7,2020,475,13,France,FR,FRA,67012883,Europe,11.2560446\r
-07/07/2020,7,7,2020,1375,27,France,FR,FRA,67012883,Europe,11.31871912\r
-06/07/2020,6,7,2020,0,0,France,FR,FRA,67012883,Europe,9.82348424\r
-05/07/2020,5,7,2020,0,0,France,FR,FRA,67012883,Europe,10.24728335\r
-04/07/2020,4,7,2020,582,18,France,FR,FRA,67012883,Europe,11.20381584\r
-03/07/2020,3,7,2020,659,14,France,FR,FRA,67012883,Europe,11.54554118\r
-02/07/2020,2,7,2020,918,18,France,FR,FRA,67012883,Europe,11.2590291\r
-01/07/2020,1,7,2020,541,30,France,FR,FRA,67012883,Europe,10.57259393\r
-30/06/2020,30,6,2020,1324,35,France,FR,FRA,67012883,Europe,10.2786206\r
-29/06/2020,29,6,2020,0,0,France,FR,FRA,67012883,Europe,8.52970316\r
-28/06/2020,28,6,2020,0,0,France,FR,FRA,67012883,Europe,9.13704907\r
-27/06/2020,27,6,2020,1588,26,France,FR,FRA,67012883,Europe,9.92197276\r
-26/06/2020,26,6,2020,0,21,France,FR,FRA,67012883,Europe,8.63565294\r
-25/06/2020,25,6,2020,81,11,France,FR,FRA,67012883,Europe,9.26985935\r
-24/06/2020,24,6,2020,517,57,France,FR,FRA,67012883,Europe,9.96226352\r
-23/06/2020,23,6,2020,373,23,France,FR,FRA,67012883,Europe,9.79214698\r
-22/06/2020,22,6,2020,284,7,France,FR,FRA,67012883,Europe,9.55040242\r
-21/06/2020,21,6,2020,641,16,France,FR,FRA,67012883,Europe,9.63844519\r
-20/06/2020,20,6,2020,811,14,France,FR,FRA,67012883,Europe,9.54592567\r
-19/06/2020,19,6,2020,467,28,France,FR,FRA,67012883,Europe,9.24747559\r
-18/06/2020,18,6,2020,458,28,France,FR,FRA,67012883,Europe,9.69515071\r
-17/06/2020,17,6,2020,344,111,France,FR,FRA,67012883,Europe,9.53697217\r
-16/06/2020,16,6,2020,152,29,France,FR,FRA,67012883,Europe,7.88057425\r
-15/06/2020,15,6,2020,407,9,France,FR,FRA,67012883,Europe,8.15813282\r
-14/06/2020,14,6,2020,526,24,France,FR,FRA,67012883,Europe,7.93429526\r
-13/06/2020,13,6,2020,726,28,France,FR,FRA,67012883,Europe,9.87720525\r
-12/06/2020,12,6,2020,425,27,France,FR,FRA,67012883,Europe,9.68470495\r
-11/06/2020,11,6,2020,545,23,France,FR,FRA,67012883,Europe,14.01223105\r
-10/06/2020,10,6,2020,403,87,France,FR,FRA,67012883,Europe,13.48397442\r
-09/06/2020,9,6,2020,211,54,France,FR,FRA,67012883,Europe,13.29445862\r
-08/06/2020,8,6,2020,343,13,France,FR,FRA,67012883,Europe,13.51381942\r
-07/06/2020,7,6,2020,579,31,France,FR,FRA,67012883,Europe,13.17358634\r
-06/06/2020,6,6,2020,611,46,France,FR,FRA,67012883,Europe,12.66771346\r
-05/06/2020,5,6,2020,767,44,France,FR,FRA,67012883,Europe,12.35732538\r
-04/06/2020,4,6,2020,352,81,France,FR,FRA,67012883,Europe,11.68730496\r
-03/06/2020,3,6,2020,-766,107,France,FR,FRA,67012883,Europe,11.78579349\r
-02/06/2020,2,6,2020,338,31,France,FR,FRA,67012883,Europe,13.71079647\r
-01/06/2020,1,6,2020,257,31,France,FR,FRA,67012883,Europe,13.94060303\r
-31/05/2020,31,5,2020,1828,57,France,FR,FRA,67012883,Europe,13.73616473\r
-30/05/2020,30,5,2020,597,52,France,FR,FRA,67012883,Europe,11.56344818\r
-29/05/2020,29,5,2020,3325,66,France,FR,FRA,67012883,Europe,11.51271167\r
-28/05/2020,28,5,2020,191,66,France,FR,FRA,67012883,Europe,7.4791589\r
-27/05/2020,27,5,2020,276,98,France,FR,FRA,67012883,Europe,7.95071001\r
-26/05/2020,26,5,2020,358,65,France,FR,FRA,67012883,Europe,8.59536218\r
-25/05/2020,25,5,2020,115,35,France,FR,FRA,67012883,Europe,8.74160272\r
-24/05/2020,24,5,2020,240,43,France,FR,FRA,67012883,Europe,8.88187425\r
-23/05/2020,23,5,2020,403,74,France,FR,FRA,67012883,Europe,9.16987857\r
-22/05/2020,22,5,2020,318,83,France,FR,FRA,67012883,Europe,9.52652641\r
-21/05/2020,21,5,2020,418,110,France,FR,FRA,67012883,Europe,9.99061628\r
-20/05/2020,20,5,2020,524,125,France,FR,FRA,67012883,Europe,15.60893896\r
-19/05/2020,19,5,2020,492,186,France,FR,FRA,67012883,Europe,16.47444418\r
-18/05/2020,18,5,2020,120,68,France,FR,FRA,67012883,Europe,16.59979321\r
-17/05/2020,17,5,2020,372,88,France,FR,FRA,67012883,Europe,16.88033628\r
-16/05/2020,16,5,2020,563,130,France,FR,FRA,67012883,Europe,17.51006594\r
-15/05/2020,15,5,2020,622,351,France,FR,FRA,67012883,Europe,17.5712482\r
-14/05/2020,14,5,2020,507,83,France,FR,FRA,67012883,Europe,18.34274165\r
-13/05/2020,13,5,2020,708,348,France,FR,FRA,67012883,Europe,19.98421706\r
-12/05/2020,12,5,2020,456,263,France,FR,FRA,67012883,Europe,20.51695045\r
-11/05/2020,11,5,2020,209,70,France,FR,FRA,67012883,Europe,21.61972348\r
-10/05/2020,10,5,2020,433,80,France,FR,FRA,67012883,Europe,21.99577057\r
-09/05/2020,9,5,2020,642,243,France,FR,FRA,67012883,Europe,23.64321499\r
-08/05/2020,8,5,2020,629,178,France,FR,FRA,67012883,Europe,25.33095017\r
-07/05/2020,7,5,2020,4183,278,France,FR,FRA,67012883,Europe,26.85901456\r
-06/05/2020,6,5,2020,1104,330,France,FR,FRA,67012883,Europe,23.34327267\r
-05/05/2020,5,5,2020,576,306,France,FR,FRA,67012883,Europe,25.67566001\r
-04/05/2020,4,5,2020,308,135,France,FR,FRA,67012883,Europe,27.87672931\r
-03/05/2020,3,5,2020,794,166,France,FR,FRA,67012883,Europe,28.58853275\r
-02/05/2020,2,5,2020,604,218,France,FR,FRA,67012883,Europe,31.23727717\r
-01/05/2020,1,5,2020,1139,289,France,FR,FRA,67012883,Europe,30.94031934\r
-30/04/2020,30,4,2020,1607,427,France,FR,FRA,67012883,Europe,33.18167941\r
-29/04/2020,29,4,2020,1065,367,France,FR,FRA,67012883,Europe,34.7127283\r
-28/04/2020,28,4,2020,1195,437,France,FR,FRA,67012883,Europe,41.32638197\r
-27/04/2020,27,4,2020,461,242,France,FR,FRA,67012883,Europe,43.53192803\r
-26/04/2020,26,4,2020,1537,369,France,FR,FRA,67012883,Europe,45.25100047\r
-25/04/2020,25,4,2020,1773,389,France,FR,FRA,67012883,Europe,47.60427931\r
-24/04/2020,24,4,2020,1653,516,France,FR,FRA,67012883,Europe,51.43787054\r
-23/04/2020,23,4,2020,1827,544,France,FR,FRA,67012883,Europe,55.36696578\r
-22/04/2020,22,4,2020,2667,531,France,FR,FRA,67012883,Europe,58.43204806\r
-21/04/2020,21,4,2020,2051,547,France,FR,FRA,67012883,Europe,60.08844598\r
-20/04/2020,20,4,2020,785,395,France,FR,FRA,67012883,Europe,62.86552393\r
-19/04/2020,19,4,2020,2569,642,France,FR,FRA,67012883,Europe,64.48909234\r
-18/04/2020,18,4,2020,405,761,France,FR,FRA,67012883,Europe,67.02293349\r
-17/04/2020,17,4,2020,2641,753,France,FR,FRA,67012883,Europe,74.22751831\r
-16/04/2020,16,4,2020,2633,1438,France,FR,FRA,67012883,Europe,73.44408686\r
-15/04/2020,15,4,2020,5497,762,France,FR,FRA,67012883,Europe,76.76882071\r
-14/04/2020,14,4,2020,2673,574,France,FR,FRA,67012883,Europe,79.87419374\r
-13/04/2020,13,4,2020,1613,561,France,FR,FRA,67012883,Europe,82.41549614\r
-12/04/2020,12,4,2020,3114,635,France,FR,FRA,67012883,Europe,83.88685501\r
-11/04/2020,11,4,2020,4342,987,France,FR,FRA,67012883,Europe,86.12075383\r
-10/04/2020,10,4,2020,4286,1341,France,FR,FRA,67012883,Europe,85.32538437\r
-09/04/2020,9,4,2020,3881,541,France,FR,FRA,67012883,Europe,84.78220524\r
-08/04/2020,8,4,2020,3777,1417,France,FR,FRA,67012883,Europe,83.36456738\r
-07/04/2020,7,4,2020,3912,833,France,FR,FRA,67012883,Europe,81.37838212\r
-06/04/2020,6,4,2020,1873,518,France,FR,FRA,67012883,Europe,81.2679556\r
-05/04/2020,5,4,2020,4267,1053,France,FR,FRA,67012883,Europe,80.79938898\r
-04/04/2020,4,4,2020,5233,2004,France,FR,FRA,67012883,Europe,77.18814306\r
-03/04/2020,3,4,2020,2116,471,France,FR,FRA,67012883,Europe,71.79216569\r
-02/04/2020,2,4,2020,4861,509,France,FR,FRA,67012883,Europe,71.41164185\r
-01/04/2020,1,4,2020,7578,499,France,FR,FRA,67012883,Europe,66.25293229\r
-31/03/2020,31,3,2020,4376,418,France,FR,FRA,67012883,Europe,56.58165759\r
-30/03/2020,30,3,2020,2599,292,France,FR,FRA,67012883,Europe,51.85719289\r
-29/03/2020,29,3,2020,4611,319,France,FR,FRA,67012883,Europe,49.35767351\r
-28/03/2020,28,3,2020,3809,299,France,FR,FRA,67012883,Europe,43.72741283\r
-27/03/2020,27,3,2020,3922,365,France,FR,FRA,67012883,Europe,39.21484769\r
-26/03/2020,26,3,2020,2931,231,France,FR,FRA,67012883,Europe,34.25013068\r
-25/03/2020,25,3,2020,2446,240,France,FR,FRA,67012883,Europe,30.61799326\r
-24/03/2020,24,3,2020,3838,186,France,FR,FRA,67012883,Europe,27.52306598\r
-23/03/2020,23,3,2020,1559,112,France,FR,FRA,67012883,Europe,22.22259263\r
-22/03/2020,22,3,2020,1847,112,France,FR,FRA,67012883,Europe,20.50799695\r
-21/03/2020,21,3,2020,1617,78,France,FR,FRA,67012883,Europe,17.90551229\r
-20/03/2020,20,3,2020,1861,128,France,FR,FRA,67012883,Europe,15.776071\r
-19/03/2020,19,3,2020,1404,69,France,FR,FRA,67012883,Europe,13.2049236\r
-18/03/2020,18,3,2020,1097,27,France,FR,FRA,67012883,Europe,11.21873834\r
-17/03/2020,17,3,2020,1210,21,France,FR,FRA,67012883,Europe,9.63247619\r
-16/03/2020,16,3,2020,924,36,France,FR,FRA,67012883,Europe,7.89848125\r
-15/03/2020,15,3,2020,838,12,France,FR,FRA,67012883,Europe,6.56440941\r
-14/03/2020,14,3,2020,785,18,France,FR,FRA,67012883,Europe,5.37807036\r
-13/03/2020,13,3,2020,595,13,France,FR,FRA,67012883,Europe,4.23500657\r
-12/03/2020,12,3,2020,497,15,France,FR,FRA,67012883,Europe,3.37845486\r
-11/03/2020,11,3,2020,372,3,France,FR,FRA,67012883,Europe,2.64128317\r
-10/03/2020,10,3,2020,286,11,France,FR,FRA,67012883,Europe,2.08915053\r
-09/03/2020,9,3,2020,410,9,France,FR,FRA,67012883,Europe,1.66236692\r
-08/03/2020,8,3,2020,103,1,France,FR,FRA,67012883,Europe,1.05054427\r
-07/03/2020,7,3,2020,190,2,France,FR,FRA,67012883,Europe,0.89684248\r
-06/03/2020,6,3,2020,138,3,France,FR,FRA,67012883,Europe,0.61331491\r
-05/03/2020,5,3,2020,73,0,France,FR,FRA,67012883,Europe,0.40738435\r
-04/03/2020,4,3,2020,34,1,France,FR,FRA,67012883,Europe,0.29845008\r
-03/03/2020,3,3,2020,48,1,France,FR,FRA,67012883,Europe,0.24771356\r
-02/03/2020,2,3,2020,30,0,France,FR,FRA,67012883,Europe,0.17608554\r
-01/03/2020,1,3,2020,43,0,France,FR,FRA,67012883,Europe,0.13281028\r
-29/02/2020,29,2,2020,19,0,France,FR,FRA,67012883,Europe,0.06864352\r
-28/02/2020,28,2,2020,21,0,France,FR,FRA,67012883,Europe,0.04029076\r
-27/02/2020,27,2,2020,3,1,France,FR,FRA,67012883,Europe,0.0089535\r
-26/02/2020,26,2,2020,2,0,France,FR,FRA,67012883,Europe,0.00447675\r
-25/02/2020,25,2,2020,0,0,France,FR,FRA,67012883,Europe,0.00149225\r
-24/02/2020,24,2,2020,0,0,France,FR,FRA,67012883,Europe,0.00149225\r
-23/02/2020,23,2,2020,0,0,France,FR,FRA,67012883,Europe,0.00149225\r
-22/02/2020,22,2,2020,0,0,France,FR,FRA,67012883,Europe,0.00149225\r
-21/02/2020,21,2,2020,0,0,France,FR,FRA,67012883,Europe,0.0089535\r
-20/02/2020,20,2,2020,0,0,France,FR,FRA,67012883,Europe,0.0089535\r
-19/02/2020,19,2,2020,0,0,France,FR,FRA,67012883,Europe,0.0089535\r
-18/02/2020,18,2,2020,0,0,France,FR,FRA,67012883,Europe,0.0089535\r
-17/02/2020,17,2,2020,1,0,France,FR,FRA,67012883,Europe,0.0089535\r
-16/02/2020,16,2,2020,0,0,France,FR,FRA,67012883,Europe,0.00746125\r
-15/02/2020,15,2,2020,0,1,France,FR,FRA,67012883,Europe,0.00746125\r
-14/02/2020,14,2,2020,0,0,France,FR,FRA,67012883,Europe,0.00746125\r
-13/02/2020,13,2,2020,0,0,France,FR,FRA,67012883,Europe,0.0089535\r
-12/02/2020,12,2,2020,0,0,France,FR,FRA,67012883,Europe,0.01044575\r
-11/02/2020,11,2,2020,0,0,France,FR,FRA,67012883,Europe,0.011938\r
-10/02/2020,10,2,2020,0,0,France,FR,FRA,67012883,Europe,0.011938\r
-09/02/2020,9,2,2020,0,0,France,FR,FRA,67012883,Europe,0.011938\r
-08/02/2020,8,2,2020,5,0,France,FR,FRA,67012883,Europe,0.011938\r
-07/02/2020,7,2,2020,0,0,France,FR,FRA,67012883,Europe,0.0089535\r
-06/02/2020,6,2,2020,0,0,France,FR,FRA,67012883,Europe,0.0089535\r
-05/02/2020,5,2,2020,0,0,France,FR,FRA,67012883,Europe,0.0089535\r
-04/02/2020,4,2,2020,0,0,France,FR,FRA,67012883,Europe,0.0089535\r
-03/02/2020,3,2,2020,0,0,France,FR,FRA,67012883,Europe,0.0089535\r
-02/02/2020,2,2,2020,0,0,France,FR,FRA,67012883,Europe,0.0089535\r
-01/02/2020,1,2,2020,0,0,France,FR,FRA,67012883,Europe,0.0089535\r
-31/01/2020,31,1,2020,1,0,France,FR,FRA,67012883,Europe,0.0089535\r
-30/01/2020,30,1,2020,1,0,France,FR,FRA,67012883,Europe,0.00746125\r
-29/01/2020,29,1,2020,1,0,France,FR,FRA,67012883,Europe,0.005969\r
-28/01/2020,28,1,2020,0,0,France,FR,FRA,67012883,Europe,0.00447675\r
-27/01/2020,27,1,2020,0,0,France,FR,FRA,67012883,Europe,0.00447675\r
-26/01/2020,26,1,2020,0,0,France,FR,FRA,67012883,Europe,0.00447675\r
-25/01/2020,25,1,2020,3,0,France,FR,FRA,67012883,Europe,0.00447675\r
-24/01/2020,24,1,2020,0,0,France,FR,FRA,67012883,Europe,0\r
-23/01/2020,23,1,2020,0,0,France,FR,FRA,67012883,Europe,0\r
-22/01/2020,22,1,2020,0,0,France,FR,FRA,67012883,Europe,0\r
-21/01/2020,21,1,2020,0,0,France,FR,FRA,67012883,Europe,0\r
-20/01/2020,20,1,2020,0,0,France,FR,FRA,67012883,Europe,0\r
-19/01/2020,19,1,2020,0,0,France,FR,FRA,67012883,Europe,0\r
-18/01/2020,18,1,2020,0,0,France,FR,FRA,67012883,Europe,0\r
-17/01/2020,17,1,2020,0,0,France,FR,FRA,67012883,Europe,0\r
-16/01/2020,16,1,2020,0,0,France,FR,FRA,67012883,Europe,0\r
-15/01/2020,15,1,2020,0,0,France,FR,FRA,67012883,Europe,0\r
-14/01/2020,14,1,2020,0,0,France,FR,FRA,67012883,Europe,0\r
-13/01/2020,13,1,2020,0,0,France,FR,FRA,67012883,Europe,0\r
-12/01/2020,12,1,2020,0,0,France,FR,FRA,67012883,Europe,\r
-11/01/2020,11,1,2020,0,0,France,FR,FRA,67012883,Europe,\r
-10/01/2020,10,1,2020,0,0,France,FR,FRA,67012883,Europe,\r
-09/01/2020,9,1,2020,0,0,France,FR,FRA,67012883,Europe,\r
-08/01/2020,8,1,2020,0,0,France,FR,FRA,67012883,Europe,\r
-07/01/2020,7,1,2020,0,0,France,FR,FRA,67012883,Europe,\r
-06/01/2020,6,1,2020,0,0,France,FR,FRA,67012883,Europe,\r
-05/01/2020,5,1,2020,0,0,France,FR,FRA,67012883,Europe,\r
-04/01/2020,4,1,2020,0,0,France,FR,FRA,67012883,Europe,\r
-03/01/2020,3,1,2020,0,0,France,FR,FRA,67012883,Europe,\r
-02/01/2020,2,1,2020,0,0,France,FR,FRA,67012883,Europe,\r
-01/01/2020,1,1,2020,0,0,France,FR,FRA,67012883,Europe,\r
-31/12/2019,31,12,2019,0,0,France,FR,FRA,67012883,Europe,\r
-19/08/2020,19,8,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,53.35052008\r
-18/08/2020,18,8,2020,19,0,French_Polynesia,PF,PYF,279285,Oceania,53.35052008\r
-17/08/2020,17,8,2020,26,0,French_Polynesia,PF,PYF,279285,Oceania,46.54743363\r
-16/08/2020,16,8,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,37.2379469\r
-15/08/2020,15,8,2020,16,0,French_Polynesia,PF,PYF,279285,Oceania,37.2379469\r
-14/08/2020,14,8,2020,11,0,French_Polynesia,PF,PYF,279285,Oceania,31.50903199\r
-13/08/2020,13,8,2020,6,0,French_Polynesia,PF,PYF,279285,Oceania,27.57040299\r
-12/08/2020,12,8,2020,71,0,French_Polynesia,PF,PYF,279285,Oceania,25.4220599\r
-11/08/2020,11,8,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-10/08/2020,10,8,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-09/08/2020,9,8,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-08/08/2020,8,8,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-07/08/2020,7,8,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-06/08/2020,6,8,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-05/08/2020,5,8,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-04/08/2020,4,8,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-03/08/2020,3,8,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-02/08/2020,2,8,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-01/08/2020,1,8,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-31/07/2020,31,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-30/07/2020,30,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-29/07/2020,29,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-28/07/2020,28,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-27/07/2020,27,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-26/07/2020,26,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-25/07/2020,25,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-24/07/2020,24,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-23/07/2020,23,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-22/07/2020,22,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-21/07/2020,21,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-20/07/2020,20,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-19/07/2020,19,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-18/07/2020,18,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-17/07/2020,17,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-16/07/2020,16,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-15/07/2020,15,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-14/07/2020,14,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-13/07/2020,13,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-12/07/2020,12,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-11/07/2020,11,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0\r
-10/07/2020,10,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0.71611436\r
-09/07/2020,9,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0.71611436\r
-08/07/2020,8,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0.71611436\r
-07/07/2020,7,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0.71611436\r
-06/07/2020,6,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0.71611436\r
-05/07/2020,5,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0.71611436\r
-04/07/2020,4,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0.71611436\r
-03/07/2020,3,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0.71611436\r
-02/07/2020,2,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0.71611436\r
-01/07/2020,1,7,2020,0,0,French_Polynesia,PF,PYF,279285,Oceania,0.71611436\r
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-22/04/2020,22,4,2020,36,0,Gabon,GA,GAB,2172578,Africa,5.79956163\r
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-29/07/2020,29,7,2020,0,0,Gambia,GM,GMB,2347696,Africa,11.1598776\r
-28/07/2020,28,7,2020,49,2,Gambia,GM,GMB,2347696,Africa,11.1598776\r
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-26/07/2020,26,7,2020,61,0,Gambia,GM,GMB,2347696,Africa,9.07272492\r
-25/07/2020,25,7,2020,46,1,Gambia,GM,GMB,2347696,Africa,6.47443281\r
-24/07/2020,24,7,2020,24,0,Gambia,GM,GMB,2347696,Africa,4.51506498\r
-23/07/2020,23,7,2020,34,1,Gambia,GM,GMB,2347696,Africa,3.53538107\r
-22/07/2020,22,7,2020,0,0,Gambia,GM,GMB,2347696,Africa,2.17234259\r
-21/07/2020,21,7,2020,19,0,Gambia,GM,GMB,2347696,Africa,2.17234259\r
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-19/07/2020,19,7,2020,15,1,Gambia,GM,GMB,2347696,Africa,1.5334183\r
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-14/07/2020,14,7,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.7241142\r
-13/07/2020,13,7,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.8093041\r
-12/07/2020,12,7,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.8093041\r
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-27/06/2020,27,6,2020,1,0,Gambia,GM,GMB,2347696,Africa,0.68151924\r
-26/06/2020,26,6,2020,1,0,Gambia,GM,GMB,2347696,Africa,0.63892429\r
-25/06/2020,25,6,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.59632934\r
-24/06/2020,24,6,2020,1,0,Gambia,GM,GMB,2347696,Africa,0.59632934\r
-23/06/2020,23,6,2020,4,0,Gambia,GM,GMB,2347696,Africa,0.55373438\r
-22/06/2020,22,6,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.46854448\r
-21/06/2020,21,6,2020,1,1,Gambia,GM,GMB,2347696,Africa,0.46854448\r
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-19/06/2020,19,6,2020,2,0,Gambia,GM,GMB,2347696,Africa,0.42594953\r
-18/06/2020,18,6,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.34075962\r
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-13/06/2020,13,6,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.12778486\r
-12/06/2020,12,6,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.12778486\r
-11/06/2020,11,6,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.12778486\r
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-29/05/2020,29,5,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.08518991\r
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-25/05/2020,25,5,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.21297476\r
-24/05/2020,24,5,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.21297476\r
-23/05/2020,23,5,2020,1,0,Gambia,GM,GMB,2347696,Africa,0.21297476\r
-22/05/2020,22,5,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.25556972\r
-21/05/2020,21,5,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.29816467\r
-20/05/2020,20,5,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.29816467\r
-19/05/2020,19,5,2020,1,0,Gambia,GM,GMB,2347696,Africa,0.29816467\r
-18/05/2020,18,5,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.25556972\r
-17/05/2020,17,5,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.25556972\r
-16/05/2020,16,5,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.46854448\r
-15/05/2020,15,5,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.46854448\r
-14/05/2020,14,5,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.51113943\r
-13/05/2020,13,5,2020,1,0,Gambia,GM,GMB,2347696,Africa,0.55373438\r
-12/05/2020,12,5,2020,2,0,Gambia,GM,GMB,2347696,Africa,0.51113943\r
-11/05/2020,11,5,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.42594953\r
-10/05/2020,10,5,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.42594953\r
-09/05/2020,9,5,2020,2,0,Gambia,GM,GMB,2347696,Africa,0.42594953\r
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-29/04/2020,29,4,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.04259495\r
-28/04/2020,28,4,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.04259495\r
-27/04/2020,27,4,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.04259495\r
-26/04/2020,26,4,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.04259495\r
-25/04/2020,25,4,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.25556972\r
-24/04/2020,24,4,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.25556972\r
-23/04/2020,23,4,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.25556972\r
-22/04/2020,22,4,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.25556972\r
-21/04/2020,21,4,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.25556972\r
-20/04/2020,20,4,2020,1,0,Gambia,GM,GMB,2347696,Africa,0.25556972\r
-19/04/2020,19,4,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.21297476\r
-18/04/2020,18,4,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.21297476\r
-17/04/2020,17,4,2020,0,0,Gambia,GM,GMB,2347696,Africa,0.21297476\r
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-27/02/2020,27,2,2020,1,0,Georgia,GE,GEO,3996762,Europe,0.02502025\r
-26/02/2020,26,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-25/02/2020,25,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-24/02/2020,24,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-23/02/2020,23,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-22/02/2020,22,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-21/02/2020,21,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-20/02/2020,20,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-19/02/2020,19,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-18/02/2020,18,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-17/02/2020,17,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-16/02/2020,16,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-15/02/2020,15,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-14/02/2020,14,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-13/02/2020,13,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-12/02/2020,12,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-11/02/2020,11,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-10/02/2020,10,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-09/02/2020,9,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-08/02/2020,8,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-07/02/2020,7,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-06/02/2020,6,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-05/02/2020,5,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-04/02/2020,4,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-03/02/2020,3,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-02/02/2020,2,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-01/02/2020,1,2,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-31/01/2020,31,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-30/01/2020,30,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-29/01/2020,29,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-28/01/2020,28,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-27/01/2020,27,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-26/01/2020,26,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-25/01/2020,25,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-24/01/2020,24,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-23/01/2020,23,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-22/01/2020,22,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-21/01/2020,21,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-20/01/2020,20,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-19/01/2020,19,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-18/01/2020,18,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-17/01/2020,17,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-16/01/2020,16,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-15/01/2020,15,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-14/01/2020,14,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-13/01/2020,13,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,0\r
-12/01/2020,12,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,\r
-11/01/2020,11,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,\r
-10/01/2020,10,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,\r
-09/01/2020,9,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,\r
-08/01/2020,8,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,\r
-07/01/2020,7,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,\r
-06/01/2020,6,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,\r
-05/01/2020,5,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,\r
-04/01/2020,4,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,\r
-03/01/2020,3,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,\r
-02/01/2020,2,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,\r
-01/01/2020,1,1,2020,0,0,Georgia,GE,GEO,3996762,Europe,\r
-31/12/2019,31,12,2019,0,0,Georgia,GE,GEO,3996762,Europe,\r
-19/08/2020,19,8,2020,2900,11,Germany,DE,DEU,83019213,Europe,17.93801635\r
-18/08/2020,18,8,2020,0,0,Germany,DE,DEU,83019213,Europe,15.33741352\r
-17/08/2020,17,8,2020,561,1,Germany,DE,DEU,83019213,Europe,16.39620457\r
-16/08/2020,16,8,2020,625,0,Germany,DE,DEU,83019213,Europe,16.33356847\r
-15/08/2020,15,8,2020,1415,6,Germany,DE,DEU,83019213,Europe,15.8698204\r
-14/08/2020,14,8,2020,1449,14,Germany,DE,DEU,83019213,Europe,15.31573179\r
-13/08/2020,13,8,2020,1445,4,Germany,DE,DEU,83019213,Europe,14.61830287\r
-12/08/2020,12,8,2020,1226,6,Germany,DE,DEU,83019213,Europe,13.96423741\r
-11/08/2020,11,8,2020,966,4,Germany,DE,DEU,83019213,Europe,13.31137649\r
-10/08/2020,10,8,2020,436,1,Germany,DE,DEU,83019213,Europe,12.91026452\r
-09/08/2020,9,8,2020,555,1,Germany,DE,DEU,83019213,Europe,12.79462864\r
-08/08/2020,8,8,2020,1122,12,Germany,DE,DEU,83019213,Europe,12.49349352\r
-07/08/2020,7,8,2020,1147,8,Germany,DE,DEU,83019213,Europe,12.08274523\r
-06/08/2020,6,8,2020,1045,7,Germany,DE,DEU,83019213,Europe,11.6828378\r
-05/08/2020,5,8,2020,741,12,Germany,DE,DEU,83019213,Europe,11.10947655\r
-04/08/2020,4,8,2020,879,8,Germany,DE,DEU,83019213,Europe,10.76377344\r
-03/08/2020,3,8,2020,509,7,Germany,DE,DEU,83019213,Europe,10.3337525\r
-02/08/2020,2,8,2020,240,0,Germany,DE,DEU,83019213,Europe,10.02057198\r
-01/08/2020,1,8,2020,955,0,Germany,DE,DEU,83019213,Europe,9.97479945\r
-31/07/2020,31,7,2020,870,7,Germany,DE,DEU,83019213,Europe,9.46166522\r
-30/07/2020,30,7,2020,902,6,Germany,DE,DEU,83019213,Europe,9.11596211\r
-29/07/2020,29,7,2020,684,6,Germany,DE,DEU,83019213,Europe,8.67269122\r
-28/07/2020,28,7,2020,633,4,Germany,DE,DEU,83019213,Europe,8.27157925\r
-27/07/2020,27,7,2020,340,0,Germany,DE,DEU,83019213,Europe,8.00537582\r
-26/07/2020,26,7,2020,305,0,Germany,DE,DEU,83019213,Europe,7.78735399\r
-25/07/2020,25,7,2020,781,7,Germany,DE,DEU,83019213,Europe,7.71869519\r
-24/07/2020,24,7,2020,815,10,Germany,DE,DEU,83019213,Europe,7.23326539\r
-23/07/2020,23,7,2020,569,6,Germany,DE,DEU,83019213,Europe,6.7273584\r
-22/07/2020,22,7,2020,454,5,Germany,DE,DEU,83019213,Europe,6.57438176\r
-21/07/2020,21,7,2020,522,4,Germany,DE,DEU,83019213,Europe,6.50572296\r
-20/07/2020,20,7,2020,249,2,Germany,DE,DEU,83019213,Europe,6.34672362\r
-19/07/2020,19,7,2020,202,1,Germany,DE,DEU,83019213,Europe,6.31058741\r
-18/07/2020,18,7,2020,529,1,Germany,DE,DEU,83019213,Europe,6.3551554\r
-17/07/2020,17,7,2020,583,4,Germany,DE,DEU,83019213,Europe,6.22626957\r
-16/07/2020,16,7,2020,534,7,Germany,DE,DEU,83019213,Europe,6.06124753\r
-15/07/2020,15,7,2020,351,3,Germany,DE,DEU,83019213,Europe,6.02390678\r
-14/07/2020,14,7,2020,412,4,Germany,DE,DEU,83019213,Europe,6.16242893\r
-13/07/2020,13,7,2020,159,1,Germany,DE,DEU,83019213,Europe,6.26601941\r
-12/07/2020,12,7,2020,248,3,Germany,DE,DEU,83019213,Europe,6.39008708\r
-11/07/2020,11,7,2020,378,6,Germany,DE,DEU,83019213,Europe,6.3997234\r
-10/07/2020,10,7,2020,395,6,Germany,DE,DEU,83019213,Europe,6.7719264\r
-09/07/2020,9,7,2020,442,12,Germany,DE,DEU,83019213,Europe,6.87069871\r
-08/07/2020,8,7,2020,397,12,Germany,DE,DEU,83019213,Europe,7.09715232\r
-07/07/2020,7,7,2020,390,8,Germany,DE,DEU,83019213,Europe,7.326015\r
-06/07/2020,6,7,2020,219,4,Germany,DE,DEU,83019213,Europe,7.46212807\r
-05/07/2020,5,7,2020,239,2,Germany,DE,DEU,83019213,Europe,7.84517194\r
-04/07/2020,4,7,2020,422,7,Germany,DE,DEU,83019213,Europe,8.38480606\r
-03/07/2020,3,7,2020,446,9,Germany,DE,DEU,83019213,Europe,8.6004188\r
-02/07/2020,2,7,2020,503,9,Germany,DE,DEU,83019213,Europe,8.9906899\r
-01/07/2020,1,7,2020,466,12,Germany,DE,DEU,83019213,Europe,9.08343952\r
-30/06/2020,30,6,2020,498,12,Germany,DE,DEU,83019213,Europe,8.93769012\r
-29/06/2020,29,6,2020,262,4,Germany,DE,DEU,83019213,Europe,8.79314527\r
-28/06/2020,28,6,2020,256,3,Germany,DE,DEU,83019213,Europe,8.70882744\r
-27/06/2020,27,6,2020,687,6,Germany,DE,DEU,83019213,Europe,8.69798657\r
-26/06/2020,26,6,2020,477,21,Germany,DE,DEU,83019213,Europe,8.28964736\r
-25/06/2020,25,6,2020,630,13,Germany,DE,DEU,83019213,Europe,8.025853\r
-24/06/2020,24,6,2020,587,19,Germany,DE,DEU,83019213,Europe,7.93551247\r
-23/06/2020,23,6,2020,503,10,Germany,DE,DEU,83019213,Europe,7.61149109\r
-22/06/2020,22,6,2020,537,3,Germany,DE,DEU,83019213,Europe,7.4271964\r
-21/06/2020,21,6,2020,687,0,Germany,DE,DEU,83019213,Europe,7.03812984\r
-20/06/2020,20,6,2020,601,10,Germany,DE,DEU,83019213,Europe,6.57317722\r
-19/06/2020,19,6,2020,770,16,Germany,DE,DEU,83019213,Europe,6.33949638\r
-18/06/2020,18,6,2020,580,26,Germany,DE,DEU,83019213,Europe,6.02270224\r
-17/06/2020,17,6,2020,345,30,Germany,DE,DEU,83019213,Europe,5.79865772\r
-16/06/2020,16,6,2020,378,9,Germany,DE,DEU,83019213,Europe,5.79504409\r
-15/06/2020,15,6,2020,192,4,Germany,DE,DEU,83019213,Europe,5.59629492\r
-14/06/2020,14,6,2020,247,6,Germany,DE,DEU,83019213,Europe,5.76613512\r
-13/06/2020,13,6,2020,348,18,Germany,DE,DEU,83019213,Europe,5.8131122\r
-12/06/2020,12,6,2020,258,8,Germany,DE,DEU,83019213,Europe,6.28288298\r
-11/06/2020,11,6,2020,555,26,Germany,DE,DEU,83019213,Europe,6.86467601\r
-10/06/2020,10,6,2020,318,18,Germany,DE,DEU,83019213,Europe,6.62135884\r
-09/06/2020,9,6,2020,350,37,Germany,DE,DEU,83019213,Europe,6.67435862\r
-08/06/2020,8,6,2020,214,6,Germany,DE,DEU,83019213,Europe,6.77313094\r
-07/06/2020,7,6,2020,301,22,Germany,DE,DEU,83019213,Europe,6.86347147\r
-06/06/2020,6,6,2020,407,33,Germany,DE,DEU,83019213,Europe,7.02006173\r
-05/06/2020,5,6,2020,507,32,Germany,DE,DEU,83019213,Europe,7.29831057\r
-04/06/2020,4,6,2020,394,30,Germany,DE,DEU,83019213,Europe,7.24169717\r
-03/06/2020,3,6,2020,342,29,Germany,DE,DEU,83019213,Europe,7.66449087\r
-02/06/2020,2,6,2020,213,11,Germany,DE,DEU,83019213,Europe,8.21255677\r
-01/06/2020,1,6,2020,333,11,Germany,DE,DEU,83019213,Europe,8.57391891\r
-31/05/2020,31,5,2020,286,11,Germany,DE,DEU,83019213,Europe,8.58475977\r
-30/05/2020,30,5,2020,738,39,Germany,DE,DEU,83019213,Europe,8.94250828\r
-29/05/2020,29,5,2020,741,39,Germany,DE,DEU,83019213,Europe,8.80037251\r
-28/05/2020,28,5,2020,353,62,Germany,DE,DEU,83019213,Europe,9.00755347\r
-27/05/2020,27,5,2020,362,47,Germany,DE,DEU,83019213,Europe,9.70618693\r
-26/05/2020,26,5,2020,432,45,Germany,DE,DEU,83019213,Europe,10.23136656\r
-25/05/2020,25,5,2020,289,10,Germany,DE,DEU,83019213,Europe,10.83484133\r
-24/05/2020,24,5,2020,431,31,Germany,DE,DEU,83019213,Europe,10.91675008\r
-23/05/2020,23,5,2020,638,42,Germany,DE,DEU,83019213,Europe,11.20102162\r
-22/05/2020,22,5,2020,460,27,Germany,DE,DEU,83019213,Europe,11.93940492\r
-21/05/2020,21,5,2020,745,57,Germany,DE,DEU,83019213,Europe,12.84160571\r
-20/05/2020,20,5,2020,797,83,Germany,DE,DEU,83019213,Europe,13.38244437\r
-19/05/2020,19,5,2020,513,72,Germany,DE,DEU,83019213,Europe,13.67153408\r
-18/05/2020,18,5,2020,342,21,Germany,DE,DEU,83019213,Europe,13.87871504\r
-17/05/2020,17,5,2020,583,33,Germany,DE,DEU,83019213,Europe,14.28464517\r
-16/05/2020,16,5,2020,620,57,Germany,DE,DEU,83019213,Europe,14.53759866\r
-15/05/2020,15,5,2020,913,101,Germany,DE,DEU,83019213,Europe,14.92907431\r
-14/05/2020,14,5,2020,933,89,Germany,DE,DEU,83019213,Europe,15.80357067\r
-13/05/2020,13,5,2020,798,101,Germany,DE,DEU,83019213,Europe,16.46004522\r
-12/05/2020,12,5,2020,933,116,Germany,DE,DEU,83019213,Europe,17.06954269\r
-11/05/2020,11,5,2020,357,22,Germany,DE,DEU,83019213,Europe,17.32370072\r
-10/05/2020,10,5,2020,667,26,Germany,DE,DEU,83019213,Europe,18.11990196\r
-09/05/2020,9,5,2020,1251,103,Germany,DE,DEU,83019213,Europe,19.40876023\r
-08/05/2020,8,5,2020,1209,147,Germany,DE,DEU,83019213,Europe,20.37721075\r
-07/05/2020,7,5,2020,1194,123,Germany,DE,DEU,83019213,Europe,21.73593238\r
-06/05/2020,6,5,2020,1037,165,Germany,DE,DEU,83019213,Europe,23.13079022\r
-05/05/2020,5,5,2020,685,139,Germany,DE,DEU,83019213,Europe,24.57623876\r
-04/05/2020,4,5,2020,679,43,Germany,DE,DEU,83019213,Europe,25.90123325\r
-03/05/2020,3,5,2020,793,74,Germany,DE,DEU,83019213,Europe,27.22140958\r
-02/05/2020,2,5,2020,945,94,Germany,DE,DEU,83019213,Europe,29.22696942\r
-01/05/2020,1,5,2020,1639,193,Germany,DE,DEU,83019213,Europe,32.43586518\r
-30/04/2020,30,4,2020,1478,173,Germany,DE,DEU,83019213,Europe,34.5329701\r
-29/04/2020,29,4,2020,1304,202,Germany,DE,DEU,83019213,Europe,36.20487224\r
-28/04/2020,28,4,2020,1144,163,Germany,DE,DEU,83019213,Europe,37.62863905\r
-27/04/2020,27,4,2020,1018,110,Germany,DE,DEU,83019213,Europe,38.75849799\r
-26/04/2020,26,4,2020,1737,140,Germany,DE,DEU,83019213,Europe,40.58819493\r
-25/04/2020,25,4,2020,2055,179,Germany,DE,DEU,83019213,Europe,41.89391677\r
-24/04/2020,24,4,2020,2337,227,Germany,DE,DEU,83019213,Europe,44.39695182\r
-23/04/2020,23,4,2020,2352,215,Germany,DE,DEU,83019213,Europe,47.9937096\r
-22/04/2020,22,4,2020,2237,281,Germany,DE,DEU,83019213,Europe,51.15201465\r
-21/04/2020,21,4,2020,1785,194,Germany,DE,DEU,83019213,Europe,53.27923309\r
-20/04/2020,20,4,2020,1775,110,Germany,DE,DEU,83019213,Europe,55.74733646\r
-19/04/2020,19,4,2020,2458,184,Germany,DE,DEU,83019213,Europe,58.03837239\r
-18/04/2020,18,4,2020,3609,242,Germany,DE,DEU,83019213,Europe,62.22776407\r
-17/04/2020,17,4,2020,3380,299,Germany,DE,DEU,83019213,Europe,65.2065926\r
-16/04/2020,16,4,2020,2866,315,Germany,DE,DEU,83019213,Europe,68.57207861\r
-15/04/2020,15,4,2020,2486,285,Germany,DE,DEU,83019213,Europe,72.53501668\r
-14/04/2020,14,4,2020,2082,170,Germany,DE,DEU,83019213,Europe,76.10888819\r
-13/04/2020,13,4,2020,2537,126,Germany,DE,DEU,83019213,Europe,79.15998915\r
-12/04/2020,12,4,2020,2821,129,Germany,DE,DEU,83019213,Europe,81.8268417\r
-11/04/2020,11,4,2020,4133,171,Germany,DE,DEU,83019213,Europe,83.20483597\r
-10/04/2020,10,4,2020,5323,266,Germany,DE,DEU,83019213,Europe,85.80784788\r
-09/04/2020,9,4,2020,4974,246,Germany,DE,DEU,83019213,Europe,86.35832286\r
-08/04/2020,8,4,2020,4003,254,Germany,DE,DEU,83019213,Europe,86.33423205\r
-07/04/2020,7,4,2020,3834,173,Germany,DE,DEU,83019213,Europe,84.33349037\r
-06/04/2020,6,4,2020,3677,92,Germany,DE,DEU,83019213,Europe,85.0610328\r
-05/04/2020,5,4,2020,5936,184,Germany,DE,DEU,83019213,Europe,84.620171\r
-04/04/2020,4,4,2020,6082,141,Germany,DE,DEU,83019213,Europe,81.4160934\r
-03/04/2020,3,4,2020,6174,145,Germany,DE,DEU,83019213,Europe,78.96726267\r
-02/04/2020,2,4,2020,6156,140,Germany,DE,DEU,83019213,Europe,78.68540021\r
-01/04/2020,1,4,2020,5453,149,Germany,DE,DEU,83019213,Europe,72.52538036\r
-31/03/2020,31,3,2020,4615,128,Germany,DE,DEU,83019213,Europe,67.33501557\r
-30/03/2020,30,3,2020,4751,66,Germany,DE,DEU,83019213,Europe,63.19019189\r
-29/03/2020,29,3,2020,3965,64,Germany,DE,DEU,83019213,Europe,58.72375591\r
-28/03/2020,28,3,2020,6294,72,Germany,DE,DEU,83019213,Europe,54.83068118\r
-27/03/2020,27,3,2020,5780,55,Germany,DE,DEU,83019213,Europe,48.08405013\r
-26/03/2020,26,3,2020,4954,49,Germany,DE,DEU,83019213,Europe,42.08784779\r
-25/03/2020,25,3,2020,2342,23,Germany,DE,DEU,83019213,Europe,36.44698487\r
-24/03/2020,24,3,2020,4438,32,Germany,DE,DEU,83019213,Europe,33.81506399\r
-23/03/2020,23,3,2020,3311,27,Germany,DE,DEU,83019213,Europe,28.75478957\r
-22/03/2020,22,3,2020,3276,22,Germany,DE,DEU,83019213,Europe,24.83280587\r
-21/03/2020,21,3,2020,4049,2,Germany,DE,DEU,83019213,Europe,21.08307146\r
-20/03/2020,20,3,2020,5940,30,Germany,DE,DEU,83019213,Europe,16.54797667\r
-19/03/2020,19,3,2020,1042,0,Germany,DE,DEU,83019213,Europe,9.55923299\r
-18/03/2020,18,3,2020,1144,0,Germany,DE,DEU,83019213,Europe,8.38360152\r
-17/03/2020,17,3,2020,1174,1,Germany,DE,DEU,83019213,Europe,7.05258432\r
-16/03/2020,16,3,2020,1043,4,Germany,DE,DEU,83019213,Europe,5.67218097\r
-15/03/2020,15,3,2020,733,3,Germany,DE,DEU,83019213,Europe,4.43752701\r
-14/03/2020,14,3,2020,693,0,Germany,DE,DEU,83019213,Europe,3.61964405\r
-13/03/2020,13,3,2020,802,2,Germany,DE,DEU,83019213,Europe,2.79694292\r
-12/03/2020,12,3,2020,271,1,Germany,DE,DEU,83019213,Europe,1.86221953\r
-11/03/2020,11,3,2020,157,0,Germany,DE,DEU,83019213,Europe,1.54060723\r
-10/03/2020,10,3,2020,237,2,Germany,DE,DEU,83019213,Europe,1.35390346\r
-09/03/2020,9,3,2020,55,0,Germany,DE,DEU,83019213,Europe,1.06842738\r
-08/03/2020,8,3,2020,163,0,Germany,DE,DEU,83019213,Europe,1.00217765\r
-07/03/2020,7,3,2020,284,0,Germany,DE,DEU,83019213,Europe,0.80583756\r
-06/03/2020,6,3,2020,138,0,Germany,DE,DEU,83019213,Europe,0.46374807\r
-05/03/2020,5,3,2020,66,0,Germany,DE,DEU,83019213,Europe,0.29752149\r
-04/03/2020,4,3,2020,39,0,Germany,DE,DEU,83019213,Europe,0.21802182\r
-03/03/2020,3,3,2020,28,0,Germany,DE,DEU,83019213,Europe,0.17104474\r
-02/03/2020,2,3,2020,18,0,Germany,DE,DEU,83019213,Europe,0.13731761\r
-01/03/2020,1,3,2020,54,0,Germany,DE,DEU,83019213,Europe,0.11563588\r
-29/02/2020,29,2,2020,10,0,Germany,DE,DEU,83019213,Europe,0.0505907\r
-28/02/2020,28,2,2020,26,0,Germany,DE,DEU,83019213,Europe,0.03854529\r
-27/02/2020,27,2,2020,4,0,Germany,DE,DEU,83019213,Europe,0.00722724\r
-26/02/2020,26,2,2020,2,0,Germany,DE,DEU,83019213,Europe,0.00240908\r
-25/02/2020,25,2,2020,0,0,Germany,DE,DEU,83019213,Europe,0.00240908\r
-24/02/2020,24,2,2020,0,0,Germany,DE,DEU,83019213,Europe,0.00240908\r
-23/02/2020,23,2,2020,0,0,Germany,DE,DEU,83019213,Europe,0.00240908\r
-22/02/2020,22,2,2020,0,0,Germany,DE,DEU,83019213,Europe,0.00240908\r
-21/02/2020,21,2,2020,0,0,Germany,DE,DEU,83019213,Europe,0.00361362\r
-20/02/2020,20,2,2020,0,0,Germany,DE,DEU,83019213,Europe,0.00481816\r
-19/02/2020,19,2,2020,0,0,Germany,DE,DEU,83019213,Europe,0.00481816\r
-18/02/2020,18,2,2020,0,0,Germany,DE,DEU,83019213,Europe,0.00481816\r
-17/02/2020,17,2,2020,0,0,Germany,DE,DEU,83019213,Europe,0.00722724\r
-16/02/2020,16,2,2020,0,0,Germany,DE,DEU,83019213,Europe,0.00843178\r
-15/02/2020,15,2,2020,0,0,Germany,DE,DEU,83019213,Europe,0.00963632\r
-14/02/2020,14,2,2020,0,0,Germany,DE,DEU,83019213,Europe,0.0120454\r
-13/02/2020,13,2,2020,0,0,Germany,DE,DEU,83019213,Europe,0.01324994\r
-12/02/2020,12,2,2020,2,0,Germany,DE,DEU,83019213,Europe,0.01324994\r
-11/02/2020,11,2,2020,0,0,Germany,DE,DEU,83019213,Europe,0.01445449\r
-10/02/2020,10,2,2020,0,0,Germany,DE,DEU,83019213,Europe,0.01565903\r
-09/02/2020,9,2,2020,0,0,Germany,DE,DEU,83019213,Europe,0.01565903\r
-08/02/2020,8,2,2020,1,0,Germany,DE,DEU,83019213,Europe,0.01565903\r
-07/02/2020,7,2,2020,1,0,Germany,DE,DEU,83019213,Europe,0.01445449\r
-06/02/2020,6,2,2020,0,0,Germany,DE,DEU,83019213,Europe,0.01324994\r
-05/02/2020,5,2,2020,0,0,Germany,DE,DEU,83019213,Europe,0.01324994\r
-04/02/2020,4,2,2020,2,0,Germany,DE,DEU,83019213,Europe,0.01324994\r
-03/02/2020,3,2,2020,1,0,Germany,DE,DEU,83019213,Europe,0.01084086\r
-02/02/2020,2,2,2020,1,0,Germany,DE,DEU,83019213,Europe,0.00963632\r
-01/02/2020,1,2,2020,2,0,Germany,DE,DEU,83019213,Europe,0.00843178\r
-31/01/2020,31,1,2020,1,0,Germany,DE,DEU,83019213,Europe,0.0060227\r
-30/01/2020,30,1,2020,0,0,Germany,DE,DEU,83019213,Europe,0.00481816\r
-29/01/2020,29,1,2020,3,0,Germany,DE,DEU,83019213,Europe,0.00481816\r
-28/01/2020,28,1,2020,1,0,Germany,DE,DEU,83019213,Europe,0.00120454\r
-27/01/2020,27,1,2020,0,0,Germany,DE,DEU,83019213,Europe,0\r
-26/01/2020,26,1,2020,0,0,Germany,DE,DEU,83019213,Europe,0\r
-25/01/2020,25,1,2020,0,0,Germany,DE,DEU,83019213,Europe,0\r
-24/01/2020,24,1,2020,0,0,Germany,DE,DEU,83019213,Europe,0\r
-23/01/2020,23,1,2020,0,0,Germany,DE,DEU,83019213,Europe,0\r
-22/01/2020,22,1,2020,0,0,Germany,DE,DEU,83019213,Europe,0\r
-21/01/2020,21,1,2020,0,0,Germany,DE,DEU,83019213,Europe,0\r
-20/01/2020,20,1,2020,0,0,Germany,DE,DEU,83019213,Europe,0\r
-19/01/2020,19,1,2020,0,0,Germany,DE,DEU,83019213,Europe,0\r
-18/01/2020,18,1,2020,0,0,Germany,DE,DEU,83019213,Europe,0\r
-17/01/2020,17,1,2020,0,0,Germany,DE,DEU,83019213,Europe,0\r
-16/01/2020,16,1,2020,0,0,Germany,DE,DEU,83019213,Europe,0\r
-15/01/2020,15,1,2020,0,0,Germany,DE,DEU,83019213,Europe,0\r
-14/01/2020,14,1,2020,0,0,Germany,DE,DEU,83019213,Europe,0\r
-13/01/2020,13,1,2020,0,0,Germany,DE,DEU,83019213,Europe,0\r
-12/01/2020,12,1,2020,0,0,Germany,DE,DEU,83019213,Europe,\r
-11/01/2020,11,1,2020,0,0,Germany,DE,DEU,83019213,Europe,\r
-10/01/2020,10,1,2020,0,0,Germany,DE,DEU,83019213,Europe,\r
-09/01/2020,9,1,2020,0,0,Germany,DE,DEU,83019213,Europe,\r
-08/01/2020,8,1,2020,0,0,Germany,DE,DEU,83019213,Europe,\r
-07/01/2020,7,1,2020,0,0,Germany,DE,DEU,83019213,Europe,\r
-06/01/2020,6,1,2020,0,0,Germany,DE,DEU,83019213,Europe,\r
-05/01/2020,5,1,2020,0,0,Germany,DE,DEU,83019213,Europe,\r
-04/01/2020,4,1,2020,0,0,Germany,DE,DEU,83019213,Europe,\r
-03/01/2020,3,1,2020,0,0,Germany,DE,DEU,83019213,Europe,\r
-02/01/2020,2,1,2020,0,0,Germany,DE,DEU,83019213,Europe,\r
-01/01/2020,1,1,2020,0,0,Germany,DE,DEU,83019213,Europe,\r
-31/12/2019,31,12,2019,0,0,Germany,DE,DEU,83019213,Europe,\r
-19/08/2020,19,8,2020,340,9,Ghana,GH,GHA,30417858,Africa,17.03275753\r
-18/08/2020,18,8,2020,121,8,Ghana,GH,GHA,30417858,Africa,15.91499309\r
-17/08/2020,17,8,2020,322,0,Ghana,GH,GHA,30417858,Africa,18.14065935\r
-16/08/2020,16,8,2020,147,0,Ghana,GH,GHA,30417858,Africa,17.08207067\r
-15/08/2020,15,8,2020,216,8,Ghana,GH,GHA,30417858,Africa,21.57285368\r
-14/08/2020,14,8,2020,122,0,Ghana,GH,GHA,30417858,Africa,22.04297226\r
-13/08/2020,13,8,2020,321,8,Ghana,GH,GHA,30417858,Africa,21.64189208\r
-12/08/2020,12,8,2020,192,0,Ghana,GH,GHA,30417858,Africa,23.0062222\r
-11/08/2020,11,8,2020,209,0,Ghana,GH,GHA,30417858,Africa,24.94587226\r
-10/08/2020,10,8,2020,470,9,Ghana,GH,GHA,30417858,Africa,26.4121162\r
-09/08/2020,9,8,2020,436,0,Ghana,GH,GHA,30417858,Africa,28.54244372\r
-08/08/2020,8,8,2020,0,0,Ghana,GH,GHA,30417858,Africa,29.71938392\r
-07/08/2020,7,8,2020,1022,7,Ghana,GH,GHA,30417858,Africa,31.99107577\r
-06/08/2020,6,8,2020,1263,8,Ghana,GH,GHA,30417858,Africa,30.91276184\r
-05/08/2020,5,8,2020,0,0,Ghana,GH,GHA,30417858,Africa,29.00598721\r
-04/08/2020,4,8,2020,798,9,Ghana,GH,GHA,30417858,Africa,30.84372345\r
-03/08/2020,3,8,2020,0,0,Ghana,GH,GHA,30417858,Africa,30.72865946\r
-02/08/2020,2,8,2020,1513,0,Ghana,GH,GHA,30417858,Africa,32.72419774\r
-01/08/2020,1,8,2020,359,7,Ghana,GH,GHA,30417858,Africa,29.35446671\r
-31/07/2020,31,7,2020,0,0,Ghana,GH,GHA,30417858,Africa,29.64377045\r
-30/07/2020,30,7,2020,736,7,Ghana,GH,GHA,30417858,Africa,31.92861246\r
-29/07/2020,29,7,2020,782,0,Ghana,GH,GHA,30417858,Africa,30.96207498\r
-28/07/2020,28,7,2020,655,0,Ghana,GH,GHA,30417858,Africa,28.39121676\r
-27/07/2020,27,7,2020,1118,7,Ghana,GH,GHA,30417858,Africa,27.78302141\r
-26/07/2020,26,7,2020,794,0,Ghana,GH,GHA,30417858,Africa,24.99518539\r
-25/07/2020,25,7,2020,691,8,Ghana,GH,GHA,30417858,Africa,23.74591926\r
-24/07/2020,24,7,2020,694,0,Ghana,GH,GHA,30417858,Africa,22.69390567\r
-23/07/2020,23,7,2020,683,0,Ghana,GH,GHA,30417858,Africa,22.51966591\r
-22/07/2020,22,7,2020,559,0,Ghana,GH,GHA,30417858,Africa,23.08183568\r
-21/07/2020,21,7,2020,763,5,Ghana,GH,GHA,30417858,Africa,24.17329978\r
-20/07/2020,20,7,2020,607,3,Ghana,GH,GHA,30417858,Africa,24.926147\r
-19/07/2020,19,7,2020,488,1,Ghana,GH,GHA,30417858,Africa,25.22202582\r
-18/07/2020,18,7,2020,447,5,Ghana,GH,GHA,30417858,Africa,23.6177051\r
-17/07/2020,17,7,2020,695,0,Ghana,GH,GHA,30417858,Africa,26.27075187\r
-16/07/2020,16,7,2020,442,0,Ghana,GH,GHA,30417858,Africa,23.98590986\r
-15/07/2020,15,7,2020,0,0,Ghana,GH,GHA,30417858,Africa,23.82482027\r
-14/07/2020,14,7,2020,470,0,Ghana,GH,GHA,30417858,Africa,25.10696184\r
-13/07/2020,13,7,2020,270,4,Ghana,GH,GHA,30417858,Africa,23.56181688\r
-12/07/2020,12,7,2020,414,0,Ghana,GH,GHA,30417858,Africa,25.69871948\r
-11/07/2020,11,7,2020,371,6,Ghana,GH,GHA,30417858,Africa,26.30033975\r
-10/07/2020,10,7,2020,641,0,Ghana,GH,GHA,30417858,Africa,26.26746433\r
-09/07/2020,9,7,2020,854,0,Ghana,GH,GHA,30417858,Africa,25.67241914\r
-08/07/2020,8,7,2020,891,0,Ghana,GH,GHA,30417858,Africa,24.32781427\r
-07/07/2020,7,7,2020,992,7,Ghana,GH,GHA,30417858,Africa,22.75965651\r
-06/07/2020,6,7,2020,697,5,Ghana,GH,GHA,30417858,Africa,19.49841439\r
-05/07/2020,5,7,2020,0,0,Ghana,GH,GHA,30417858,Africa,18.6633786\r
-04/07/2020,4,7,2020,1254,0,Ghana,GH,GHA,30417858,Africa,20.33345017\r
-03/07/2020,3,7,2020,0,0,Ghana,GH,GHA,30417858,Africa,17.11165855\r
-02/07/2020,2,7,2020,393,5,Ghana,GH,GHA,30417858,Africa,18.22613545\r
-01/07/2020,1,7,2020,390,0,Ghana,GH,GHA,30417858,Africa,18.23928562\r
-30/06/2020,30,6,2020,0,0,Ghana,GH,GHA,30417858,Africa,17.70999128\r
-29/06/2020,29,6,2020,920,9,Ghana,GH,GHA,30417858,Africa,17.70999128\r
-28/06/2020,28,6,2020,597,0,Ghana,GH,GHA,30417858,Africa,16.46730023\r
-27/06/2020,27,6,2020,361,8,Ghana,GH,GHA,30417858,Africa,15.50405029\r
-26/06/2020,26,6,2020,460,0,Ghana,GH,GHA,30417858,Africa,16.81577973\r
-25/06/2020,25,6,2020,445,0,Ghana,GH,GHA,30417858,Africa,15.30351019\r
-24/06/2020,24,6,2020,414,10,Ghana,GH,GHA,30417858,Africa,14.35669796\r
-23/06/2020,23,6,2020,0,0,Ghana,GH,GHA,30417858,Africa,13.95233024\r
-22/06/2020,22,6,2020,443,0,Ghana,GH,GHA,30417858,Africa,14.84654179\r
-21/06/2020,21,6,2020,508,15,Ghana,GH,GHA,30417858,Africa,13.96876795\r
-20/06/2020,20,6,2020,274,4,Ghana,GH,GHA,30417858,Africa,13.26523386\r
-19/06/2020,19,6,2020,339,0,Ghana,GH,GHA,30417858,Africa,13.29482175\r
-18/06/2020,18,6,2020,397,8,Ghana,GH,GHA,30417858,Africa,13.28824666\r
-17/06/2020,17,6,2020,229,4,Ghana,GH,GHA,30417858,Africa,12.80826546\r
-16/06/2020,16,6,2020,0,0,Ghana,GH,GHA,30417858,Africa,12.80169038\r
-15/06/2020,15,6,2020,542,3,Ghana,GH,GHA,30417858,Africa,12.80169038\r
-14/06/2020,14,6,2020,304,3,Ghana,GH,GHA,30417858,Africa,12.01268018\r
-13/06/2020,13,6,2020,760,0,Ghana,GH,GHA,30417858,Africa,11.51297373\r
-12/06/2020,12,6,2020,0,0,Ghana,GH,GHA,30417858,Africa,10.04344224\r
-11/06/2020,11,6,2020,157,0,Ghana,GH,GHA,30417858,Africa,10.04344224\r
-10/06/2020,10,6,2020,291,0,Ghana,GH,GHA,30417858,Africa,10.13878098\r
-09/06/2020,9,6,2020,272,4,Ghana,GH,GHA,30417858,Africa,10.19795674\r
-08/06/2020,8,6,2020,176,0,Ghana,GH,GHA,30417858,Africa,9.714688\r
-07/06/2020,7,6,2020,294,2,Ghana,GH,GHA,30417858,Africa,9.35305833\r
-06/06/2020,6,6,2020,283,4,Ghana,GH,GHA,30417858,Africa,8.38652084\r
-05/06/2020,5,6,2020,337,0,Ghana,GH,GHA,30417858,Africa,7.88681438\r
-04/06/2020,4,6,2020,251,0,Ghana,GH,GHA,30417858,Africa,7.49230929\r
-03/06/2020,3,6,2020,227,2,Ghana,GH,GHA,30417858,Africa,7.23588097\r
-02/06/2020,2,6,2020,0,0,Ghana,GH,GHA,30417858,Africa,7.67641167\r
-01/06/2020,1,6,2020,302,1,Ghana,GH,GHA,30417858,Africa,7.67641167\r
-31/05/2020,31,5,2020,152,1,Ghana,GH,GHA,30417858,Africa,6.68357384\r
-30/05/2020,30,5,2020,313,0,Ghana,GH,GHA,30417858,Africa,6.502759\r
-29/05/2020,29,5,2020,0,0,Ghana,GH,GHA,30417858,Africa,5.8288128\r
-28/05/2020,28,5,2020,186,0,Ghana,GH,GHA,30417858,Africa,6.22989298\r
-27/05/2020,27,5,2020,309,2,Ghana,GH,GHA,30417858,Africa,6.54220951\r
-26/05/2020,26,5,2020,125,0,Ghana,GH,GHA,30417858,Africa,6.93013953\r
-25/05/2020,25,5,2020,66,1,Ghana,GH,GHA,30417858,Africa,7.95585278\r
-24/05/2020,24,5,2020,0,0,Ghana,GH,GHA,30417858,Africa,7.73887497\r
-23/05/2020,23,5,2020,131,0,Ghana,GH,GHA,30417858,Africa,8.56404813\r
-22/05/2020,22,5,2020,217,0,Ghana,GH,GHA,30417858,Africa,11.16120668\r
-21/05/2020,21,5,2020,173,0,Ghana,GH,GHA,30417858,Africa,10.44780997\r
-20/05/2020,20,5,2020,361,2,Ghana,GH,GHA,30417858,Africa,11.10203092\r
-19/05/2020,19,5,2020,0,0,Ghana,GH,GHA,30417858,Africa,9.91522809\r
-18/05/2020,18,5,2020,0,0,Ghana,GH,GHA,30417858,Africa,11.72337645\r
-17/05/2020,17,5,2020,97,1,Ghana,GH,GHA,30417858,Africa,11.72337645\r
-16/05/2020,16,5,2020,108,4,Ghana,GH,GHA,30417858,Africa,11.71680136\r
-15/05/2020,15,5,2020,122,0,Ghana,GH,GHA,30417858,Africa,11.36174677\r
-14/05/2020,14,5,2020,281,2,Ghana,GH,GHA,30417858,Africa,12.28554621\r
-13/05/2020,13,5,2020,427,0,Ghana,GH,GHA,30417858,Africa,11.36174677\r
-12/05/2020,12,5,2020,437,0,Ghana,GH,GHA,30417858,Africa,10.35575878\r
-11/05/2020,11,5,2020,0,0,Ghana,GH,GHA,30417858,Africa,8.91910272\r
-10/05/2020,10,5,2020,251,4,Ghana,GH,GHA,30417858,Africa,9.81002673\r
-09/05/2020,9,5,2020,921,0,Ghana,GH,GHA,30417858,Africa,8.98485357\r
-08/05/2020,8,5,2020,0,0,Ghana,GH,GHA,30417858,Africa,6.36796976\r
-07/05/2020,7,5,2020,372,0,Ghana,GH,GHA,30417858,Africa,6.36796976\r
-06/05/2020,6,5,2020,0,0,Ghana,GH,GHA,30417858,Africa,5.51320872\r
-05/05/2020,5,5,2020,550,0,Ghana,GH,GHA,30417858,Africa,5.51320872\r
-04/05/2020,4,5,2020,0,0,Ghana,GH,GHA,30417858,Africa,3.70506036\r
-03/05/2020,3,5,2020,95,1,Ghana,GH,GHA,30417858,Africa,4.3888692\r
-02/05/2020,2,5,2020,0,0,Ghana,GH,GHA,30417858,Africa,4.71104836\r
-01/05/2020,1,5,2020,403,1,Ghana,GH,GHA,30417858,Africa,4.71104836\r
-30/04/2020,30,4,2020,0,0,Ghana,GH,GHA,30417858,Africa,3.38616874\r
-29/04/2020,29,4,2020,121,5,Ghana,GH,GHA,30417858,Africa,3.40260646\r
-28/04/2020,28,4,2020,0,0,Ghana,GH,GHA,30417858,Africa,3.23494179\r
-27/04/2020,27,4,2020,271,1,Ghana,GH,GHA,30417858,Africa,3.23494179\r
-26/04/2020,26,4,2020,0,0,Ghana,GH,GHA,30417858,Africa,2.86344949\r
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-25/05/2020,25,5,2020,370,3,Guatemala,GT,GTM,17581476,America,13.4914725\r
-24/05/2020,24,5,2020,311,4,Guatemala,GT,GTM,17581476,America,11.87044819\r
-23/05/2020,23,5,2020,231,3,Guatemala,GT,GTM,17581476,America,10.48262387\r
-22/05/2020,22,5,2020,247,3,Guatemala,GT,GTM,17581476,America,9.55551172\r
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-14/05/2020,14,5,2020,143,2,Guatemala,GT,GTM,17581476,America,4.30566808\r
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-25/04/2020,25,4,2020,46,0,Guatemala,GT,GTM,17581476,America,1.66652675\r
-24/04/2020,24,4,2020,42,1,Guatemala,GT,GTM,17581476,America,1.46745359\r
-23/04/2020,23,4,2020,26,2,Guatemala,GT,GTM,17581476,America,1.45039017\r
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-19/04/2020,19,4,2020,22,0,Guatemala,GT,GTM,17581476,America,1.1148097\r
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-15/04/2020,15,4,2020,13,0,Guatemala,GT,GTM,17581476,America,0.80766825\r
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-12/04/2020,12,4,2020,16,0,Guatemala,GT,GTM,17581476,America,0.67684875\r
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-15/07/2020,15,7,2020,0,0,Guinea,GN,GIN,12771246,Africa,5.87256717\r
-14/07/2020,14,7,2020,0,0,Guinea,GN,GIN,12771246,Africa,6.18577075\r
-13/07/2020,13,7,2020,97,0,Guinea,GN,GIN,12771246,Africa,6.25624156\r
-12/07/2020,12,7,2020,75,0,Guinea,GN,GIN,12771246,Africa,5.89605744\r
-11/07/2020,11,7,2020,88,1,Guinea,GN,GIN,12771246,Africa,5.5515335\r
-10/07/2020,10,7,2020,184,2,Guinea,GN,GIN,12771246,Africa,5.24616001\r
-09/07/2020,9,7,2020,0,0,Guinea,GN,GIN,12771246,Africa,4.09513684\r
-08/07/2020,8,7,2020,61,0,Guinea,GN,GIN,12771246,Africa,4.64324311\r
-07/07/2020,7,7,2020,26,0,Guinea,GN,GIN,12771246,Africa,5.07389804\r
-06/07/2020,6,7,2020,40,0,Guinea,GN,GIN,12771246,Africa,4.87031571\r
-05/07/2020,5,7,2020,49,1,Guinea,GN,GIN,12771246,Africa,4.77635463\r
-04/07/2020,4,7,2020,71,0,Guinea,GN,GIN,12771246,Africa,4.83116526\r
-03/07/2020,3,7,2020,46,0,Guinea,GN,GIN,12771246,Africa,4.76852454\r
-02/07/2020,2,7,2020,13,0,Guinea,GN,GIN,12771246,Africa,5.76294592\r
-01/07/2020,1,7,2020,40,2,Guinea,GN,GIN,12771246,Africa,5.88822735\r
-30/06/2020,30,6,2020,9,0,Guinea,GN,GIN,12771246,Africa,6.09963977\r
-29/06/2020,29,6,2020,51,1,Guinea,GN,GIN,12771246,Africa,6.34237255\r
-28/06/2020,28,6,2020,31,1,Guinea,GN,GIN,12771246,Africa,6.31888228\r
-27/06/2020,27,6,2020,49,0,Guinea,GN,GIN,12771246,Africa,6.53029469\r
-26/06/2020,26,6,2020,37,0,Guinea,GN,GIN,12771246,Africa,6.56944514\r
-25/06/2020,25,6,2020,70,0,Guinea,GN,GIN,12771246,Africa,7.17236204\r
-24/06/2020,24,6,2020,116,2,Guinea,GN,GIN,12771246,Africa,6.62425577\r
-23/06/2020,23,6,2020,0,0,Guinea,GN,GIN,12771246,Africa,6.04482914\r
-22/06/2020,22,6,2020,28,0,Guinea,GN,GIN,12771246,Africa,6.44416371\r
-21/06/2020,21,6,2020,56,0,Guinea,GN,GIN,12771246,Africa,6.6007655\r
-20/06/2020,20,6,2020,63,1,Guinea,GN,GIN,12771246,Africa,6.60859559\r
-19/06/2020,19,6,2020,173,0,Guinea,GN,GIN,12771246,Africa,6.65557613\r
-18/06/2020,18,6,2020,29,0,Guinea,GN,GIN,12771246,Africa,6.12313004\r
-17/06/2020,17,6,2020,67,0,Guinea,GN,GIN,12771246,Africa,6.2249212\r
-16/06/2020,16,6,2020,40,1,Guinea,GN,GIN,12771246,Africa,5.7003052\r
-15/06/2020,15,6,2020,48,0,Guinea,GN,GIN,12771246,Africa,5.95869816\r
-14/06/2020,14,6,2020,58,1,Guinea,GN,GIN,12771246,Africa,6.09180968\r
-13/06/2020,13,6,2020,54,1,Guinea,GN,GIN,12771246,Africa,6.02916896\r
-12/06/2020,12,6,2020,114,0,Guinea,GN,GIN,12771246,Africa,6.41284335\r
-11/06/2020,11,6,2020,0,0,Guinea,GN,GIN,12771246,Africa,6.35803272\r
-10/06/2020,10,6,2020,42,0,Guinea,GN,GIN,12771246,Africa,7.04708061\r
-09/06/2020,9,6,2020,51,0,Guinea,GN,GIN,12771246,Africa,7.36811428\r
-08/06/2020,8,6,2020,48,0,Guinea,GN,GIN,12771246,Africa,6.96877971\r
-07/06/2020,7,6,2020,57,0,Guinea,GN,GIN,12771246,Africa,7.36811428\r
-06/06/2020,6,6,2020,69,0,Guinea,GN,GIN,12771246,Africa,7.77527894\r
-05/06/2020,5,6,2020,105,0,Guinea,GN,GIN,12771246,Africa,7.23500276\r
-04/06/2020,4,6,2020,42,0,Guinea,GN,GIN,12771246,Africa,8.01018162\r
-03/06/2020,3,6,2020,0,0,Guinea,GN,GIN,12771246,Africa,7.68131786\r
-02/06/2020,2,6,2020,73,0,Guinea,GN,GIN,12771246,Africa,8.20593386\r
-01/06/2020,1,6,2020,65,0,Guinea,GN,GIN,12771246,Africa,8.71488968\r
-31/05/2020,31,5,2020,50,1,Guinea,GN,GIN,12771246,Africa,8.20593386\r
-30/05/2020,30,5,2020,103,0,Guinea,GN,GIN,12771246,Africa,8.80885076\r
-29/05/2020,29,5,2020,107,1,Guinea,GN,GIN,12771246,Africa,8.45649673\r
-28/05/2020,28,5,2020,88,1,Guinea,GN,GIN,12771246,Africa,8.39385601\r
-27/05/2020,27,5,2020,83,0,Guinea,GN,GIN,12771246,Africa,8.96545255\r
-26/05/2020,26,5,2020,0,0,Guinea,GN,GIN,12771246,Africa,8.31555511\r
-25/05/2020,25,5,2020,99,0,Guinea,GN,GIN,12771246,Africa,8.84017112\r
-24/05/2020,24,5,2020,109,1,Guinea,GN,GIN,12771246,Africa,8.87932156\r
-23/05/2020,23,5,2020,0,0,Guinea,GN,GIN,12771246,Africa,8.28423476\r
-22/05/2020,22,5,2020,204,1,Guinea,GN,GIN,12771246,Africa,8.9263021\r
-21/05/2020,21,5,2020,0,0,Guinea,GN,GIN,12771246,Africa,7.88490019\r
-20/05/2020,20,5,2020,67,2,Guinea,GN,GIN,12771246,Africa,8.23725422\r
-19/05/2020,19,5,2020,138,0,Guinea,GN,GIN,12771246,Africa,8.50347726\r
-18/05/2020,18,5,2020,0,0,Guinea,GN,GIN,12771246,Africa,8.39385601\r
-17/05/2020,17,5,2020,127,1,Guinea,GN,GIN,12771246,Africa,8.39385601\r
-16/05/2020,16,5,2020,58,1,Guinea,GN,GIN,12771246,Africa,7.78310902\r
-15/05/2020,15,5,2020,99,0,Guinea,GN,GIN,12771246,Africa,7.65782759\r
-14/05/2020,14,5,2020,161,3,Guinea,GN,GIN,12771246,Africa,8.01018162\r
-13/05/2020,13,5,2020,0,0,Guinea,GN,GIN,12771246,Africa,7.61867714\r
-12/05/2020,12,5,2020,67,0,Guinea,GN,GIN,12771246,Africa,8.22159404\r
-11/05/2020,11,5,2020,104,0,Guinea,GN,GIN,12771246,Africa,8.23725422\r
-10/05/2020,10,5,2020,33,0,Guinea,GN,GIN,12771246,Africa,8.19027368\r
-09/05/2020,9,5,2020,82,0,Guinea,GN,GIN,12771246,Africa,8.26074449\r
-08/05/2020,8,5,2020,71,0,Guinea,GN,GIN,12771246,Africa,8.33904538\r
-07/05/2020,7,5,2020,45,1,Guinea,GN,GIN,12771246,Africa,8.57394807\r
-06/05/2020,6,5,2020,101,1,Guinea,GN,GIN,12771246,Africa,8.79319058\r
-05/05/2020,5,5,2020,124,2,Guinea,GN,GIN,12771246,Africa,8.51913744\r
-04/05/2020,4,5,2020,0,0,Guinea,GN,GIN,12771246,Africa,7.88490019\r
-03/05/2020,3,5,2020,49,0,Guinea,GN,GIN,12771246,Africa,8.68356932\r
-02/05/2020,2,5,2020,42,0,Guinea,GN,GIN,12771246,Africa,8.29989494\r
-01/05/2020,1,5,2020,144,0,Guinea,GN,GIN,12771246,Africa,8.27640467\r
-30/04/2020,30,4,2020,111,0,Guinea,GN,GIN,12771246,Africa,7.41509482\r
-29/04/2020,29,4,2020,77,0,Guinea,GN,GIN,12771246,Africa,6.86698855\r
-28/04/2020,28,4,2020,69,0,Guinea,GN,GIN,12771246,Africa,6.60859559\r
-27/04/2020,27,4,2020,98,0,Guinea,GN,GIN,12771246,Africa,6.60859559\r
-26/04/2020,26,4,2020,42,1,Guinea,GN,GIN,12771246,Africa,5.84124681\r
-25/04/2020,25,4,2020,92,0,Guinea,GN,GIN,12771246,Africa,5.80992646\r
-24/04/2020,24,4,2020,101,0,Guinea,GN,GIN,12771246,Africa,5.23049983\r
-23/04/2020,23,4,2020,73,0,Guinea,GN,GIN,12771246,Africa,4.67456347\r
-22/04/2020,22,4,2020,66,1,Guinea,GN,GIN,12771246,Africa,4.25956872\r
-21/04/2020,21,4,2020,43,0,Guinea,GN,GIN,12771246,Africa,3.86806424\r
-20/04/2020,20,4,2020,102,2,Guinea,GN,GIN,12771246,Africa,3.58618102\r
-19/04/2020,19,4,2020,0,0,Guinea,GN,GIN,12771246,Africa,2.86581278\r
-18/04/2020,18,4,2020,39,2,Guinea,GN,GIN,12771246,Africa,3.32778806\r
-17/04/2020,17,4,2020,34,0,Guinea,GN,GIN,12771246,Africa,3.02241457\r
-16/04/2020,16,4,2020,41,1,Guinea,GN,GIN,12771246,Africa,2.9284535\r
-15/04/2020,15,4,2020,44,0,Guinea,GN,GIN,12771246,Africa,2.71704108\r
-14/04/2020,14,4,2020,69,0,Guinea,GN,GIN,12771246,Africa,2.37251714\r
-13/04/2020,13,4,2020,0,0,Guinea,GN,GIN,12771246,Africa,1.89488167\r
-12/04/2020,12,4,2020,38,0,Guinea,GN,GIN,12771246,Africa,1.89488167\r
-11/04/2020,11,4,2020,18,0,Guinea,GN,GIN,12771246,Africa,1.62082854\r
-10/04/2020,10,4,2020,30,0,Guinea,GN,GIN,12771246,Africa,1.47988693\r
-09/04/2020,9,4,2020,20,0,Guinea,GN,GIN,12771246,Africa,1.25281433\r
-08/04/2020,8,4,2020,16,0,Guinea,GN,GIN,12771246,Africa,1.09621254\r
-07/04/2020,7,4,2020,7,0,Guinea,GN,GIN,12771246,Africa,0.98659128\r
-06/04/2020,6,4,2020,10,0,Guinea,GN,GIN,12771246,Africa,0.93178066\r
-05/04/2020,5,4,2020,59,0,Guinea,GN,GIN,12771246,Africa,0.85347976\r
-04/04/2020,4,4,2020,0,0,Guinea,GN,GIN,12771246,Africa,0.39150448\r
-03/04/2020,3,4,2020,22,0,Guinea,GN,GIN,12771246,Africa,0.39933457\r
-02/04/2020,2,4,2020,14,0,Guinea,GN,GIN,12771246,Africa,0.2270726\r
-01/04/2020,1,4,2020,0,0,Guinea,GN,GIN,12771246,Africa,0.11745134\r
-31/03/2020,31,3,2020,8,0,Guinea,GN,GIN,12771246,Africa,0.11745134\r
-30/03/2020,30,3,2020,0,0,Guinea,GN,GIN,12771246,Africa,0.05481063\r
-29/03/2020,29,3,2020,3,0,Guinea,GN,GIN,12771246,Africa,0.05481063\r
-28/03/2020,28,3,2020,0,0,Guinea,GN,GIN,12771246,Africa,0.03915045\r
-27/03/2020,27,3,2020,1,0,Guinea,GN,GIN,12771246,Africa,\r
-26/03/2020,26,3,2020,0,0,Guinea,GN,GIN,12771246,Africa,\r
-25/03/2020,25,3,2020,2,0,Guinea,GN,GIN,12771246,Africa,\r
-24/03/2020,24,3,2020,0,0,Guinea,GN,GIN,12771246,Africa,\r
-23/03/2020,23,3,2020,0,0,Guinea,GN,GIN,12771246,Africa,\r
-22/03/2020,22,3,2020,0,0,Guinea,GN,GIN,12771246,Africa,\r
-21/03/2020,21,3,2020,1,0,Guinea,GN,GIN,12771246,Africa,\r
-20/03/2020,20,3,2020,0,0,Guinea,GN,GIN,12771246,Africa,\r
-19/03/2020,19,3,2020,0,0,Guinea,GN,GIN,12771246,Africa,\r
-18/03/2020,18,3,2020,0,0,Guinea,GN,GIN,12771246,Africa,\r
-17/03/2020,17,3,2020,0,0,Guinea,GN,GIN,12771246,Africa,\r
-15/03/2020,15,3,2020,0,0,Guinea,GN,GIN,12771246,Africa,\r
-14/03/2020,14,3,2020,1,0,Guinea,GN,GIN,12771246,Africa,\r
-19/08/2020,19,8,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,4.42496995\r
-18/08/2020,18,8,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,7.07995192\r
-17/08/2020,17,8,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,7.07995192\r
-16/08/2020,16,8,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,7.07995192\r
-15/08/2020,15,8,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,7.07995192\r
-14/08/2020,14,8,2020,65,4,Guinea_Bissau,GW,GNB,1920917,Africa,7.07995192\r
-13/08/2020,13,8,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,5.10173006\r
-12/08/2020,12,8,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,5.10173006\r
-11/08/2020,11,8,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,5.10173006\r
-10/08/2020,10,8,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,5.10173006\r
-09/08/2020,9,8,2020,20,2,Guinea_Bissau,GW,GNB,1920917,Africa,5.10173006\r
-08/08/2020,8,8,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,4.06056066\r
-07/08/2020,7,8,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,4.06056066\r
-06/08/2020,6,8,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,4.06056066\r
-05/08/2020,5,8,2020,51,0,Guinea_Bissau,GW,GNB,1920917,Africa,4.06056066\r
-04/08/2020,4,8,2020,0,1,Guinea_Bissau,GW,GNB,1920917,Africa,1.61381257\r
-03/08/2020,3,8,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,2.81115738\r
-02/08/2020,2,8,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,2.81115738\r
-01/08/2020,1,8,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,2.81115738\r
-31/07/2020,31,7,2020,27,0,Guinea_Bissau,GW,GNB,1920917,Africa,2.81115738\r
-30/07/2020,30,7,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,2.70704044\r
-29/07/2020,29,7,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,2.70704044\r
-28/07/2020,28,7,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,5.83054864\r
-27/07/2020,27,7,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,5.83054864\r
-26/07/2020,26,7,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,5.83054864\r
-25/07/2020,25,7,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,8.53758908\r
-24/07/2020,24,7,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,8.53758908\r
-23/07/2020,23,7,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,8.53758908\r
-22/07/2020,22,7,2020,4,0,Guinea_Bissau,GW,GNB,1920917,Africa,8.53758908\r
-21/07/2020,21,7,2020,23,0,Guinea_Bissau,GW,GNB,1920917,Africa,9.63081695\r
-20/07/2020,20,7,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,8.43347214\r
-19/07/2020,19,7,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,8.43347214\r
-18/07/2020,18,7,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,11.29668799\r
-17/07/2020,17,7,2020,25,0,Guinea_Bissau,GW,GNB,1920917,Africa,14.21196231\r
-16/07/2020,16,7,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,12.91050056\r
-15/07/2020,15,7,2020,60,1,Guinea_Bissau,GW,GNB,1920917,Africa,12.91050056\r
-14/07/2020,14,7,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,11.86933116\r
-13/07/2020,13,7,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,11.86933116\r
-12/07/2020,12,7,2020,52,0,Guinea_Bissau,GW,GNB,1920917,Africa,11.86933116\r
-11/07/2020,11,7,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,12.18168198\r
-10/07/2020,10,7,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,12.18168198\r
-09/07/2020,9,7,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,12.18168198\r
-08/07/2020,8,7,2020,25,0,Guinea_Bissau,GW,GNB,1920917,Africa,12.18168198\r
-07/07/2020,7,7,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,10.88022023\r
-06/07/2020,6,7,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,11.66109728\r
-05/07/2020,5,7,2020,55,1,Guinea_Bissau,GW,GNB,1920917,Africa,11.66109728\r
-04/07/2020,4,7,2020,56,0,Guinea_Bissau,GW,GNB,1920917,Africa,10.30757706\r
-03/07/2020,3,7,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,7.39230274\r
-02/07/2020,2,7,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,8.43347214\r
-01/07/2020,1,7,2020,40,3,Guinea_Bissau,GW,GNB,1920917,Africa,8.43347214\r
-30/06/2020,30,6,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,8.01700438\r
-29/06/2020,29,6,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,8.01700438\r
-28/06/2020,28,6,2020,58,2,Guinea_Bissau,GW,GNB,1920917,Africa,8.01700438\r
-27/06/2020,27,6,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,8.69376449\r
-26/06/2020,26,6,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,8.69376449\r
-25/06/2020,25,6,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,8.69376449\r
-24/06/2020,24,6,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,8.69376449\r
-23/06/2020,23,6,2020,15,2,Guinea_Bissau,GW,GNB,1920917,Africa,8.69376449\r
-22/06/2020,22,6,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,9.00611531\r
-21/06/2020,21,6,2020,29,2,Guinea_Bissau,GW,GNB,1920917,Africa,9.00611531\r
-20/06/2020,20,6,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,7.49641968\r
-19/06/2020,19,6,2020,20,0,Guinea_Bissau,GW,GNB,1920917,Africa,8.64170602\r
-18/06/2020,18,6,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,7.96494591\r
-17/06/2020,17,6,2020,32,0,Guinea_Bissau,GW,GNB,1920917,Africa,7.96494591\r
-16/06/2020,16,6,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,6.29907487\r
-15/06/2020,15,6,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,7.18406886\r
-14/06/2020,14,6,2020,71,3,Guinea_Bissau,GW,GNB,1920917,Africa,10.61992788\r
-13/06/2020,13,6,2020,0,0,Guinea_Bissau,GW,GNB,1920917,Africa,6.92377651\r
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-29/04/2020,29,4,2020,45,5,Honduras,HN,HND,9746115,America,3.27309908\r
-28/04/2020,28,4,2020,32,0,Honduras,HN,HND,9746115,America,2.93450262\r
-27/04/2020,27,4,2020,34,2,Honduras,HN,HND,9746115,America,2.70877165\r
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-24/04/2020,24,4,2020,0,0,Honduras,HN,HND,9746115,America,1.40568832\r
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-30/07/2020,30,7,2020,19,0,Hungary,HU,HUN,9772756,Europe,2.2613887\r
-29/07/2020,29,7,2020,9,0,Hungary,HU,HUN,9772756,Europe,2.06697067\r
-28/07/2020,28,7,2020,8,0,Hungary,HU,HUN,9772756,Europe,2.13859836\r
-27/07/2020,27,7,2020,13,0,Hungary,HU,HUN,9772756,Europe,2.189761\r
-26/07/2020,26,7,2020,11,0,Hungary,HU,HUN,9772756,Europe,2.10790078\r
-25/07/2020,25,7,2020,26,0,Hungary,HU,HUN,9772756,Europe,2.05673814\r
-24/07/2020,24,7,2020,18,0,Hungary,HU,HUN,9772756,Europe,1.82138999\r
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-22/07/2020,22,7,2020,19,0,Hungary,HU,HUN,9772756,Europe,1.64743702\r
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-29/06/2020,29,6,2020,4,3,Hungary,HU,HUN,9772756,Europe,0.67534685\r
-28/06/2020,28,6,2020,11,0,Hungary,HU,HUN,9772756,Europe,0.75720708\r
-27/06/2020,27,6,2020,4,1,Hungary,HU,HUN,9772756,Europe,0.75720708\r
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-22/06/2020,22,6,2020,8,2,Hungary,HU,HUN,9772756,Europe,1.3506937\r
-21/06/2020,21,6,2020,8,0,Hungary,HU,HUN,9772756,Europe,1.26883348\r
-20/06/2020,20,6,2020,5,2,Hungary,HU,HUN,9772756,Europe,1.18697326\r
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-12/06/2020,12,6,2020,12,2,Hungary,HU,HUN,9772756,Europe,2.02604056\r
-11/06/2020,11,6,2020,10,1,Hungary,HU,HUN,9772756,Europe,2.15906342\r
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-30/05/2020,30,5,2020,0,0,Hungary,HU,HUN,9772756,Europe,3.76557033\r
-29/05/2020,29,5,2020,25,8,Hungary,HU,HUN,9772756,Europe,4.3385919\r
-28/05/2020,28,5,2020,23,4,Hungary,HU,HUN,9772756,Europe,4.46138223\r
-27/05/2020,27,5,2020,22,6,Hungary,HU,HUN,9772756,Europe,4.62510268\r
-26/05/2020,26,5,2020,15,8,Hungary,HU,HUN,9772756,Europe,4.68649785\r
-25/05/2020,25,5,2020,15,5,Hungary,HU,HUN,9772756,Europe,4.82975324\r
-24/05/2020,24,5,2020,28,4,Hungary,HU,HUN,9772756,Europe,4.89114841\r
-23/05/2020,23,5,2020,35,6,Hungary,HU,HUN,9772756,Europe,5.11626403\r
-22/05/2020,22,5,2020,37,3,Hungary,HU,HUN,9772756,Europe,5.11626403\r
-21/05/2020,21,5,2020,43,3,Hungary,HU,HUN,9772756,Europe,5.02417128\r
-20/05/2020,20,5,2020,42,3,Hungary,HU,HUN,9772756,Europe,4.98324117\r
-19/05/2020,19,5,2020,21,5,Hungary,HU,HUN,9772756,Europe,5.02417128\r
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-11/04/2020,11,4,2020,27,1,Iceland,IS,ISL,356991,Europe,219.89349872\r
-10/04/2020,10,4,2020,32,0,Iceland,IS,ISL,356991,Europe,236.98076422\r
-09/04/2020,9,4,2020,30,0,Iceland,IS,ISL,356991,Europe,246.22469474\r
-08/04/2020,8,4,2020,24,0,Iceland,IS,ISL,356991,Europe,262.75172203\r
-07/04/2020,7,4,2020,76,2,Iceland,IS,ISL,356991,Europe,272.83600987\r
-06/04/2020,6,4,2020,69,0,Iceland,IS,ISL,356991,Europe,257.1493399\r
-05/04/2020,5,4,2020,53,0,Iceland,IS,ISL,356991,Europe,264.43243667\r
-04/04/2020,4,4,2020,45,0,Iceland,IS,ISL,356991,Europe,267.51374685\r
-03/04/2020,3,4,2020,99,2,Iceland,IS,ISL,356991,Europe,277.03779647\r
-02/04/2020,2,4,2020,85,0,Iceland,IS,ISL,356991,Europe,271.71553344\r
-01/04/2020,1,4,2020,49,0,Iceland,IS,ISL,356991,Europe,248.7457667\r
-31/03/2020,31,3,2020,66,0,Iceland,IS,ISL,356991,Europe,248.46564759\r
-30/03/2020,30,3,2020,57,0,Iceland,IS,ISL,356991,Europe,235.86028779\r
-29/03/2020,29,3,2020,73,0,Iceland,IS,ISL,356991,Europe,231.09826298\r
-28/03/2020,28,3,2020,88,0,Iceland,IS,ISL,356991,Europe,216.53206944\r
-27/03/2020,27,3,2020,65,0,Iceland,IS,ISL,356991,Europe,191.88158805\r
-26/03/2020,26,3,2020,89,0,Iceland,IS,ISL,356991,Europe,182.63765753\r
-25/03/2020,25,3,2020,60,0,Iceland,IS,ISL,356991,Europe,161.90884364\r
-24/03/2020,24,3,2020,20,1,Iceland,IS,ISL,356991,Europe,146.50229277\r
-23/03/2020,23,3,2020,95,0,Iceland,IS,ISL,356991,Europe,143.70110171\r
-22/03/2020,22,3,2020,64,0,Iceland,IS,ISL,356991,Europe,117.65002479\r
-21/03/2020,21,3,2020,79,0,Iceland,IS,ISL,356991,Europe,102.52359303\r
-20/03/2020,20,3,2020,80,1,Iceland,IS,ISL,356991,Europe,82.63513646\r
-19/03/2020,19,3,2020,3,0,Iceland,IS,ISL,356991,Europe,62.74667989\r
-18/03/2020,18,3,2020,48,0,Iceland,IS,ISL,356991,Europe,64.70751363\r
-17/03/2020,17,3,2020,21,0,Iceland,IS,ISL,356991,Europe,54.06298758\r
-16/03/2020,16,3,2020,40,0,Iceland,IS,ISL,356991,Europe,49.02084366\r
-15/03/2020,15,3,2020,21,0,Iceland,IS,ISL,356991,Europe,38.37631761\r
-14/03/2020,14,3,2020,0,0,Iceland,IS,ISL,356991,Europe,32.49381637\r
-13/03/2020,13,3,2020,32,0,Iceland,IS,ISL,356991,Europe,32.77393548\r
-12/03/2020,12,3,2020,15,0,Iceland,IS,ISL,356991,Europe,23.81012406\r
-11/03/2020,11,3,2020,5,0,Iceland,IS,ISL,356991,Europe,19.60833747\r
-10/03/2020,10,3,2020,10,0,Iceland,IS,ISL,356991,Europe,18.20774193\r
-09/03/2020,9,3,2020,2,0,Iceland,IS,ISL,356991,Europe,15.40655087\r
-08/03/2020,8,3,2020,10,0,Iceland,IS,ISL,356991,Europe,14.84631265\r
-07/03/2020,7,3,2020,8,0,Iceland,IS,ISL,356991,Europe,12.04512159\r
-06/03/2020,6,3,2020,9,0,Iceland,IS,ISL,356991,Europe,9.80416873\r
-05/03/2020,5,3,2020,10,0,Iceland,IS,ISL,356991,Europe,7.28309677\r
-04/03/2020,4,3,2020,10,0,Iceland,IS,ISL,356991,Europe,4.48190571\r
-03/03/2020,3,3,2020,3,0,Iceland,IS,ISL,356991,Europe,1.68071464\r
-02/03/2020,2,3,2020,2,0,Iceland,IS,ISL,356991,Europe,0.84035732\r
-01/03/2020,1,3,2020,0,0,Iceland,IS,ISL,356991,Europe,0.28011911\r
-29/02/2020,29,2,2020,1,0,Iceland,IS,ISL,356991,Europe,0.28011911\r
-28/02/2020,28,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-27/02/2020,27,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-26/02/2020,26,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-25/02/2020,25,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-24/02/2020,24,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-23/02/2020,23,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-22/02/2020,22,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-21/02/2020,21,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-20/02/2020,20,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-19/02/2020,19,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-18/02/2020,18,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-17/02/2020,17,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-16/02/2020,16,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-15/02/2020,15,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-14/02/2020,14,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-13/02/2020,13,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-12/02/2020,12,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-11/02/2020,11,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-10/02/2020,10,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-09/02/2020,9,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-08/02/2020,8,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-07/02/2020,7,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-06/02/2020,6,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-05/02/2020,5,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-04/02/2020,4,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-03/02/2020,3,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-02/02/2020,2,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-01/02/2020,1,2,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-31/01/2020,31,1,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-30/01/2020,30,1,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-29/01/2020,29,1,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-28/01/2020,28,1,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-27/01/2020,27,1,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-26/01/2020,26,1,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-25/01/2020,25,1,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-24/01/2020,24,1,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-23/01/2020,23,1,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-22/01/2020,22,1,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-21/01/2020,21,1,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-20/01/2020,20,1,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-19/01/2020,19,1,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-18/01/2020,18,1,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-17/01/2020,17,1,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-16/01/2020,16,1,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-15/01/2020,15,1,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-14/01/2020,14,1,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-13/01/2020,13,1,2020,0,0,Iceland,IS,ISL,356991,Europe,0\r
-12/01/2020,12,1,2020,0,0,Iceland,IS,ISL,356991,Europe,\r
-11/01/2020,11,1,2020,0,0,Iceland,IS,ISL,356991,Europe,\r
-10/01/2020,10,1,2020,0,0,Iceland,IS,ISL,356991,Europe,\r
-09/01/2020,9,1,2020,0,0,Iceland,IS,ISL,356991,Europe,\r
-08/01/2020,8,1,2020,0,0,Iceland,IS,ISL,356991,Europe,\r
-07/01/2020,7,1,2020,0,0,Iceland,IS,ISL,356991,Europe,\r
-06/01/2020,6,1,2020,0,0,Iceland,IS,ISL,356991,Europe,\r
-05/01/2020,5,1,2020,0,0,Iceland,IS,ISL,356991,Europe,\r
-04/01/2020,4,1,2020,0,0,Iceland,IS,ISL,356991,Europe,\r
-03/01/2020,3,1,2020,0,0,Iceland,IS,ISL,356991,Europe,\r
-02/01/2020,2,1,2020,0,0,Iceland,IS,ISL,356991,Europe,\r
-01/01/2020,1,1,2020,0,0,Iceland,IS,ISL,356991,Europe,\r
-31/12/2019,31,12,2019,0,0,Iceland,IS,ISL,356991,Europe,\r
-19/08/2020,19,8,2020,64531,1092,India,IN,IND,1366417756,Asia,62.86649864\r
-18/08/2020,18,8,2020,55079,876,India,IN,IND,1366417756,Asia,61.98667986\r
-17/08/2020,17,8,2020,57981,941,India,IN,IND,1366417756,Asia,61.76500534\r
-16/08/2020,16,8,2020,63490,944,India,IN,IND,1366417756,Asia,61.39842638\r
-15/08/2020,15,8,2020,65002,996,India,IN,IND,1366417756,Asia,60.75769993\r
-14/08/2020,14,8,2020,64553,1007,India,IN,IND,1366417756,Asia,60.1807168\r
-13/08/2020,13,8,2020,66999,942,India,IN,IND,1366417756,Asia,59.48729782\r
-12/08/2020,12,8,2020,60963,834,India,IN,IND,1366417756,Asia,58.39861173\r
-11/08/2020,11,8,2020,53601,871,India,IN,IND,1366417756,Asia,57.48747018\r
-10/08/2020,10,8,2020,62064,1007,India,IN,IND,1366417756,Asia,57.05583059\r
-09/08/2020,9,8,2020,64399,861,India,IN,IND,1366417756,Asia,56.16788838\r
-08/08/2020,8,8,2020,61537,933,India,IN,IND,1366417756,Asia,55.01611763\r
-07/08/2020,7,8,2020,62538,886,India,IN,IND,1366417756,Asia,54.0924616\r
-06/08/2020,6,8,2020,56282,904,India,IN,IND,1366417756,Asia,53.12438285\r
-05/08/2020,5,8,2020,52509,857,India,IN,IND,1366417756,Asia,52.3514128\r
-04/08/2020,4,8,2020,52050,803,India,IN,IND,1366417756,Asia,51.26938646\r
-03/08/2020,3,8,2020,52972,771,India,IN,IND,1366417756,Asia,50.17879759\r
-02/08/2020,2,8,2020,54735,853,India,IN,IND,1366417756,Asia,49.26055718\r
-01/08/2020,1,8,2020,57118,764,India,IN,IND,1366417756,Asia,48.10183395\r
-31/07/2020,31,7,2020,55078,779,India,IN,IND,1366417756,Asia,46.47465954\r
-30/07/2020,30,7,2020,52123,775,India,IN,IND,1366417756,Asia,45.00204987\r
-29/07/2020,29,7,2020,48513,768,India,IN,IND,1366417756,Asia,43.58022994\r
-28/07/2020,28,7,2020,47703,654,India,IN,IND,1366417756,Asia,42.18358533\r
-27/07/2020,27,7,2020,49931,708,India,IN,IND,1366417756,Asia,40.77808544\r
-26/07/2020,26,7,2020,48661,705,India,IN,IND,1366417756,Asia,39.22438783\r
-25/07/2020,25,7,2020,48916,757,India,IN,IND,1366417756,Asia,37.7589502\r
-24/07/2020,24,7,2020,49310,740,India,IN,IND,1366417756,Asia,36.16339131\r
-23/07/2020,23,7,2020,45720,1129,India,IN,IND,1366417756,Asia,34.49450199\r
-22/07/2020,22,7,2020,37724,648,India,IN,IND,1366417756,Asia,32.96927298\r
-21/07/2020,21,7,2020,37148,587,India,IN,IND,1366417756,Asia,31.87356122\r
-20/07/2020,20,7,2020,40425,681,India,IN,IND,1366417756,Asia,30.78341145\r
-19/07/2020,19,7,2020,38902,543,India,IN,IND,1366417756,Asia,29.5995129\r
-18/07/2020,18,7,2020,34884,671,India,IN,IND,1366417756,Asia,28.57113048\r
-17/07/2020,17,7,2020,34956,687,India,IN,IND,1366417756,Asia,27.68465196\r
-16/07/2020,16,7,2020,32695,606,India,IN,IND,1366417756,Asia,26.65619635\r
-15/07/2020,15,7,2020,29429,582,India,IN,IND,1366417756,Asia,25.66477188\r
-14/07/2020,14,7,2020,28498,553,India,IN,IND,1366417756,Asia,24.87614044\r
-13/07/2020,13,7,2020,28701,500,India,IN,IND,1366417756,Asia,24.14605625\r
-12/07/2020,12,7,2020,28637,551,India,IN,IND,1366417756,Asia,23.46968916\r
-11/07/2020,11,7,2020,27114,519,India,IN,IND,1366417756,Asia,22.83071913\r
-10/07/2020,10,7,2020,26506,475,India,IN,IND,1366417756,Asia,22.2041172\r
-09/07/2020,9,7,2020,24879,487,India,IN,IND,1366417756,Asia,21.530092\r
-08/07/2020,8,7,2020,22752,482,India,IN,IND,1366417756,Asia,20.94776643\r
-07/07/2020,7,7,2020,22252,467,India,IN,IND,1366417756,Asia,20.45128576\r
-06/07/2020,6,7,2020,24248,425,India,IN,IND,1366417756,Asia,19.91565162\r
-05/07/2020,5,7,2020,24850,613,India,IN,IND,1366417756,Asia,19.22574548\r
-04/07/2020,4,7,2020,22771,442,India,IN,IND,1366417756,Asia,18.5351075\r
-03/07/2020,3,7,2020,20903,379,India,IN,IND,1366417756,Asia,17.93097308\r
-02/07/2020,2,7,2020,19148,434,India,IN,IND,1366417756,Asia,17.39548531\r
-01/07/2020,1,7,2020,18653,507,India,IN,IND,1366417756,Asia,16.9368408\r
-30/06/2020,30,6,2020,18522,418,India,IN,IND,1366417756,Asia,16.3748604\r
-29/06/2020,29,6,2020,19459,380,India,IN,IND,1366417756,Asia,15.7999996\r
-28/06/2020,28,6,2020,19906,410,India,IN,IND,1366417756,Asia,15.21767403\r
-27/06/2020,27,6,2020,18552,384,India,IN,IND,1366417756,Asia,14.63388478\r
-26/06/2020,26,6,2020,17296,407,India,IN,IND,1366417756,Asia,14.11471705\r
-25/06/2020,25,6,2020,16922,418,India,IN,IND,1366417756,Asia,13.65073011\r
-24/06/2020,24,6,2020,15968,465,India,IN,IND,1366417756,Asia,13.1438573\r
-23/06/2020,23,6,2020,14933,312,India,IN,IND,1366417756,Asia,12.70599707\r
-22/06/2020,22,6,2020,14821,445,India,IN,IND,1366417756,Asia,12.3440287\r
-21/06/2020,21,6,2020,15413,306,India,IN,IND,1366417756,Asia,11.98996422\r
-20/06/2020,20,6,2020,14516,375,India,IN,IND,1366417756,Asia,11.59169656\r
-19/06/2020,19,6,2020,13586,336,India,IN,IND,1366417756,Asia,11.25292754\r
-18/06/2020,18,6,2020,12881,334,India,IN,IND,1366417756,Asia,10.97958508\r
-17/06/2020,17,6,2020,10974,2003,India,IN,IND,1366417756,Asia,10.71780569\r
-16/06/2020,16,6,2020,10667,380,India,IN,IND,1366417756,Asia,10.5666806\r
-15/06/2020,15,6,2020,11502,325,India,IN,IND,1366417756,Asia,10.38401319\r
-14/06/2020,14,6,2020,11929,311,India,IN,IND,1366417756,Asia,10.15641076\r
-13/06/2020,13,6,2020,11458,386,India,IN,IND,1366417756,Asia,9.89668053\r
-12/06/2020,12,6,2020,10956,396,India,IN,IND,1366417756,Asia,9.64097542\r
-11/06/2020,11,6,2020,9996,357,India,IN,IND,1366417756,Asia,9.38556305\r
-10/06/2020,10,6,2020,9985,279,India,IN,IND,1366417756,Asia,9.13454172\r
-09/06/2020,9,6,2020,9987,331,India,IN,IND,1366417756,Asia,8.87122547\r
-08/06/2020,8,6,2020,9983,206,India,IN,IND,1366417756,Asia,8.61859409\r
-07/06/2020,7,6,2020,9971,287,India,IN,IND,1366417756,Asia,8.39860281\r
-06/06/2020,6,6,2020,9887,294,India,IN,IND,1366417756,Asia,8.16412108\r
-05/06/2020,5,6,2020,9851,273,India,IN,IND,1366417756,Asia,7.92751701\r
-04/06/2020,4,6,2020,9304,260,India,IN,IND,1366417756,Asia,7.65212539\r
-03/06/2020,3,6,2020,8909,217,India,IN,IND,1366417756,Asia,7.38171028\r
-02/06/2020,2,6,2020,8171,204,India,IN,IND,1366417756,Asia,7.14034925\r
-01/06/2020,1,6,2020,8392,230,India,IN,IND,1366417756,Asia,6.90608707\r
-31/05/2020,31,5,2020,8380,193,India,IN,IND,1366417756,Asia,6.67555728\r
-30/05/2020,30,5,2020,7964,265,India,IN,IND,1366417756,Asia,6.42724376\r
-29/05/2020,29,5,2020,7466,175,India,IN,IND,1366417756,Asia,6.13494662\r
-28/05/2020,28,5,2020,6566,194,India,IN,IND,1366417756,Asia,5.8788756\r
-27/05/2020,27,5,2020,6387,170,India,IN,IND,1366417756,Asia,5.67074013\r
-26/05/2020,26,5,2020,6535,146,India,IN,IND,1366417756,Asia,5.46128735\r
-25/05/2020,25,5,2020,6977,154,India,IN,IND,1366417756,Asia,5.24678486\r
-24/05/2020,24,5,2020,6767,147,India,IN,IND,1366417756,Asia,5.04450412\r
-23/05/2020,23,5,2020,6654,137,India,IN,IND,1366417756,Asia,4.78909175\r
-22/05/2020,22,5,2020,6088,148,India,IN,IND,1366417756,Asia,4.54509609\r
-21/05/2020,21,5,2020,5609,132,India,IN,IND,1366417756,Asia,4.34764549\r
-20/05/2020,20,5,2020,5611,140,India,IN,IND,1366417756,Asia,4.19776454\r
-19/05/2020,19,5,2020,4970,134,India,IN,IND,1366417756,Asia,4.00360722\r
-18/05/2020,18,5,2020,5242,157,India,IN,IND,1366417756,Asia,3.92530028\r
-17/05/2020,17,5,2020,4987,120,India,IN,IND,1366417756,Asia,3.72850834\r
-16/05/2020,16,5,2020,3970,103,India,IN,IND,1366417756,Asia,3.55703809\r
-15/05/2020,15,5,2020,3967,100,India,IN,IND,1366417756,Asia,3.43430842\r
-14/05/2020,14,5,2020,3722,134,India,IN,IND,1366417756,Asia,3.28984308\r
-13/05/2020,13,5,2020,3525,122,India,IN,IND,1366417756,Asia,3.14318222\r
-12/05/2020,12,5,2020,3604,87,India,IN,IND,1366417756,Asia,3.02403857\r
-11/05/2020,11,5,2020,4213,97,India,IN,IND,1366417756,Asia,2.87320622\r
-10/05/2020,10,5,2020,3277,128,India,IN,IND,1366417756,Asia,2.66704672\r
-09/05/2020,9,5,2020,3320,95,India,IN,IND,1366417756,Asia,2.57285884\r
-08/05/2020,8,5,2020,3390,103,India,IN,IND,1366417756,Asia,2.43446778\r
-07/05/2020,7,5,2020,3561,89,India,IN,IND,1366417756,Asia,2.30961577\r
-06/05/2020,6,5,2020,2958,126,India,IN,IND,1366417756,Asia,2.15212367\r
-05/05/2020,5,5,2020,3900,195,India,IN,IND,1366417756,Asia,2.03693196\r
-04/05/2020,4,5,2020,2553,72,India,IN,IND,1366417756,Asia,1.84921485\r
-03/05/2020,3,5,2020,2644,83,India,IN,IND,1366417756,Asia,1.77603079\r
-02/05/2020,2,5,2020,2293,71,India,IN,IND,1366417756,Asia,1.68015967\r
-01/05/2020,1,5,2020,1993,73,India,IN,IND,1366417756,Asia,1.58487402\r
-30/04/2020,30,4,2020,1718,67,India,IN,IND,1366417756,Asia,1.51271453\r
-29/04/2020,29,4,2020,1897,73,India,IN,IND,1366417756,Asia,1.4559237\r
-28/04/2020,28,4,2020,1543,62,India,IN,IND,1366417756,Asia,1.39576641\r
-27/04/2020,27,4,2020,1396,48,India,IN,IND,1366417756,Asia,1.3714693\r
-26/04/2020,26,4,2020,1990,49,India,IN,IND,1366417756,Asia,1.32755886\r
-25/04/2020,25,4,2020,1429,57,India,IN,IND,1366417756,Asia,1.24844689\r
-24/04/2020,24,4,2020,1684,37,India,IN,IND,1366417756,Asia,1.21961237\r
-23/04/2020,23,4,2020,1409,41,India,IN,IND,1366417756,Asia,1.14598921\r
-22/04/2020,22,4,2020,1384,50,India,IN,IND,1366417756,Asia,1.08239226\r
-21/04/2020,21,4,2020,1335,47,India,IN,IND,1366417756,Asia,1.0376768\r
-20/04/2020,20,4,2020,1553,36,India,IN,IND,1366417756,Asia,0.96588323\r
-19/04/2020,19,4,2020,1334,27,India,IN,IND,1366417756,Asia,0.90294494\r
-18/04/2020,18,4,2020,991,43,India,IN,IND,1366417756,Asia,0.83986028\r
-17/04/2020,17,4,2020,1007,23,India,IN,IND,1366417756,Asia,0.8113185\r
-16/04/2020,16,4,2020,942,37,India,IN,IND,1366417756,Asia,0.76221199\r
-15/04/2020,15,4,2020,1075,38,India,IN,IND,1366417756,Asia,0.73484115\r
-14/04/2020,14,4,2020,1211,31,India,IN,IND,1366417756,Asia,0.66685316\r
-13/04/2020,13,4,2020,796,35,India,IN,IND,1366417756,Asia,0.59140039\r
-12/04/2020,12,4,2020,909,34,India,IN,IND,1366417756,Asia,0.53987882\r
-11/04/2020,11,4,2020,1035,40,India,IN,IND,1366417756,Asia,0.48111202\r
-10/04/2020,10,4,2020,678,33,India,IN,IND,1366417756,Asia,0.41627094\r
-09/04/2020,9,4,2020,540,17,India,IN,IND,1366417756,Asia,0.37214095\r
-08/04/2020,8,4,2020,773,35,India,IN,IND,1366417756,Asia,0.33898857\r
-07/04/2020,7,4,2020,354,5,India,IN,IND,1366417756,Asia,0.28754017\r
-06/04/2020,6,4,2020,693,32,India,IN,IND,1366417756,Asia,0.26551177\r
-05/04/2020,5,4,2020,472,9,India,IN,IND,1366417756,Asia,0.22350412\r
-04/04/2020,4,4,2020,601,12,India,IN,IND,1366417756,Asia,0.19547463\r
-03/04/2020,3,4,2020,336,6,India,IN,IND,1366417756,Asia,0.15441837\r
-02/04/2020,2,4,2020,568,15,India,IN,IND,1366417756,Asia,0.13173131\r
-01/04/2020,1,4,2020,146,3,India,IN,IND,1366417756,Asia,0.09221192\r
-31/03/2020,31,3,2020,180,3,India,IN,IND,1366417756,Asia,0.08240525\r
-30/03/2020,30,3,2020,92,4,India,IN,IND,1366417756,Asia,0.07157401\r
-29/03/2020,29,3,2020,106,6,India,IN,IND,1366417756,Asia,0.06506063\r
-28/03/2020,28,3,2020,149,2,India,IN,IND,1366417756,Asia,0.05781541\r
-27/03/2020,27,3,2020,75,4,India,IN,IND,1366417756,Asia,0.04749646\r
-26/03/2020,26,3,2020,87,4,India,IN,IND,1366417756,Asia,0.04215402\r
-25/03/2020,25,3,2020,70,0,India,IN,IND,1366417756,Asia,0.03747024\r
-24/03/2020,24,3,2020,53,2,India,IN,IND,1366417756,Asia,0.03278646\r
-23/03/2020,23,3,2020,119,3,India,IN,IND,1366417756,Asia,0.02963954\r
-22/03/2020,22,3,2020,89,0,India,IN,IND,1366417756,Asia,0.02115019\r
-21/03/2020,21,3,2020,40,0,India,IN,IND,1366417756,Asia,0.01478318\r
-20/03/2020,20,3,2020,26,1,India,IN,IND,1366417756,Asia,0.011929\r
-19/03/2020,19,3,2020,28,0,India,IN,IND,1366417756,Asia,0.01163627\r
-18/03/2020,18,3,2020,12,0,India,IN,IND,1366417756,Asia,0.0096603\r
-17/03/2020,17,3,2020,32,1,India,IN,IND,1366417756,Asia,0.00892846\r
-16/03/2020,16,3,2020,3,0,India,IN,IND,1366417756,Asia,0.00658657\r
-15/03/2020,15,3,2020,7,0,India,IN,IND,1366417756,Asia,0.00636701\r
-14/03/2020,14,3,2020,8,1,India,IN,IND,1366417756,Asia,0.00585472\r
-13/03/2020,13,3,2020,2,1,India,IN,IND,1366417756,Asia,0.00526925\r
-12/03/2020,12,3,2020,23,0,India,IN,IND,1366417756,Asia,0.00512288\r
-11/03/2020,11,3,2020,6,0,India,IN,IND,1366417756,Asia,0.00343965\r
-10/03/2020,10,3,2020,10,0,India,IN,IND,1366417756,Asia,0.00300055\r
-08/03/2020,8,3,2020,3,0,India,IN,IND,1366417756,Asia,0.00226871\r
-07/03/2020,7,3,2020,2,0,India,IN,IND,1366417756,Asia,0.00204915\r
-06/03/2020,6,3,2020,1,0,India,IN,IND,1366417756,Asia,0.00190279\r
-05/03/2020,5,3,2020,22,0,India,IN,IND,1366417756,Asia,0.0018296\r
-04/03/2020,4,3,2020,1,0,India,IN,IND,1366417756,Asia,0.00021955\r
-03/03/2020,3,3,2020,2,0,India,IN,IND,1366417756,Asia,0.00014637\r
-02/03/2020,2,3,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-01/03/2020,1,3,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-29/02/2020,29,2,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-28/02/2020,28,2,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-27/02/2020,27,2,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-26/02/2020,26,2,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-25/02/2020,25,2,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-24/02/2020,24,2,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-23/02/2020,23,2,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-22/02/2020,22,2,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-21/02/2020,21,2,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-20/02/2020,20,2,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-19/02/2020,19,2,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-18/02/2020,18,2,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-17/02/2020,17,2,2020,0,0,India,IN,IND,1366417756,Asia,7.318e-5\r
-16/02/2020,16,2,2020,0,0,India,IN,IND,1366417756,Asia,7.318e-5\r
-15/02/2020,15,2,2020,0,0,India,IN,IND,1366417756,Asia,0.00014637\r
-14/02/2020,14,2,2020,0,0,India,IN,IND,1366417756,Asia,0.00014637\r
-13/02/2020,13,2,2020,0,0,India,IN,IND,1366417756,Asia,0.00014637\r
-12/02/2020,12,2,2020,0,0,India,IN,IND,1366417756,Asia,0.00021955\r
-11/02/2020,11,2,2020,0,0,India,IN,IND,1366417756,Asia,0.00021955\r
-10/02/2020,10,2,2020,0,0,India,IN,IND,1366417756,Asia,0.00021955\r
-09/02/2020,9,2,2020,0,0,India,IN,IND,1366417756,Asia,0.00021955\r
-08/02/2020,8,2,2020,0,0,India,IN,IND,1366417756,Asia,0.00021955\r
-07/02/2020,7,2,2020,0,0,India,IN,IND,1366417756,Asia,0.00021955\r
-06/02/2020,6,2,2020,0,0,India,IN,IND,1366417756,Asia,0.00021955\r
-05/02/2020,5,2,2020,0,0,India,IN,IND,1366417756,Asia,0.00021955\r
-04/02/2020,4,2,2020,1,0,India,IN,IND,1366417756,Asia,0.00021955\r
-03/02/2020,3,2,2020,0,0,India,IN,IND,1366417756,Asia,0.00014637\r
-02/02/2020,2,2,2020,1,0,India,IN,IND,1366417756,Asia,0.00014637\r
-01/02/2020,1,2,2020,0,0,India,IN,IND,1366417756,Asia,7.318e-5\r
-31/01/2020,31,1,2020,0,0,India,IN,IND,1366417756,Asia,7.318e-5\r
-30/01/2020,30,1,2020,1,0,India,IN,IND,1366417756,Asia,7.318e-5\r
-29/01/2020,29,1,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-28/01/2020,28,1,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-27/01/2020,27,1,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-26/01/2020,26,1,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-25/01/2020,25,1,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-24/01/2020,24,1,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-23/01/2020,23,1,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-22/01/2020,22,1,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-21/01/2020,21,1,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-20/01/2020,20,1,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-19/01/2020,19,1,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-18/01/2020,18,1,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-17/01/2020,17,1,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-16/01/2020,16,1,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-15/01/2020,15,1,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-14/01/2020,14,1,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-13/01/2020,13,1,2020,0,0,India,IN,IND,1366417756,Asia,0\r
-12/01/2020,12,1,2020,0,0,India,IN,IND,1366417756,Asia,\r
-11/01/2020,11,1,2020,0,0,India,IN,IND,1366417756,Asia,\r
-10/01/2020,10,1,2020,0,0,India,IN,IND,1366417756,Asia,\r
-09/01/2020,9,1,2020,0,0,India,IN,IND,1366417756,Asia,\r
-08/01/2020,8,1,2020,0,0,India,IN,IND,1366417756,Asia,\r
-07/01/2020,7,1,2020,0,0,India,IN,IND,1366417756,Asia,\r
-06/01/2020,6,1,2020,0,0,India,IN,IND,1366417756,Asia,\r
-05/01/2020,5,1,2020,0,0,India,IN,IND,1366417756,Asia,\r
-04/01/2020,4,1,2020,0,0,India,IN,IND,1366417756,Asia,\r
-03/01/2020,3,1,2020,0,0,India,IN,IND,1366417756,Asia,\r
-02/01/2020,2,1,2020,0,0,India,IN,IND,1366417756,Asia,\r
-01/01/2020,1,1,2020,0,0,India,IN,IND,1366417756,Asia,\r
-31/12/2019,31,12,2019,0,0,India,IN,IND,1366417756,Asia,\r
-19/08/2020,19,8,2020,1673,70,Indonesia,ID,IDN,270625567,Asia,10.34159496\r
-18/08/2020,18,8,2020,1821,57,Indonesia,ID,IDN,270625567,Asia,10.43360401\r
-17/08/2020,17,8,2020,2081,79,Indonesia,ID,IDN,270625567,Asia,10.38113298\r
-16/08/2020,16,8,2020,2345,50,Indonesia,ID,IDN,270625567,Asia,10.17346598\r
-15/08/2020,15,8,2020,2307,53,Indonesia,ID,IDN,270625567,Asia,9.88339731\r
-14/08/2020,14,8,2020,2098,65,Indonesia,ID,IDN,270625567,Asia,9.78473701\r
-13/08/2020,13,8,2020,1942,79,Indonesia,ID,IDN,270625567,Asia,9.71305124\r
-12/08/2020,12,8,2020,1693,59,Indonesia,ID,IDN,270625567,Asia,9.87526799\r
-11/08/2020,11,8,2020,1687,42,Indonesia,ID,IDN,270625567,Asia,9.89559128\r
-10/08/2020,10,8,2020,1893,65,Indonesia,ID,IDN,270625567,Asia,9.83572997\r
-09/08/2020,9,8,2020,2277,65,Indonesia,ID,IDN,270625567,Asia,9.68755476\r
-08/08/2020,8,8,2020,2473,72,Indonesia,ID,IDN,270625567,Asia,9.53642344\r
-07/08/2020,7,8,2020,1882,69,Indonesia,ID,IDN,270625567,Asia,9.2733293\r
-06/08/2020,6,8,2020,1815,64,Indonesia,ID,IDN,270625567,Asia,9.28219764\r
-05/08/2020,5,8,2020,1922,86,Indonesia,ID,IDN,270625567,Asia,9.3069551\r
-04/08/2020,4,8,2020,1679,66,Indonesia,ID,IDN,270625567,Asia,9.20829479\r
-03/08/2020,3,8,2020,1519,43,Indonesia,ID,IDN,270625567,Asia,9.21346799\r
-02/08/2020,2,8,2020,1560,62,Indonesia,ID,IDN,270625567,Asia,9.2578097\r
-01/08/2020,1,8,2020,2040,73,Indonesia,ID,IDN,270625567,Asia,9.32875644\r
-31/07/2020,31,7,2020,1904,83,Indonesia,ID,IDN,270625567,Asia,9.11517721\r
-30/07/2020,30,7,2020,2381,74,Indonesia,ID,IDN,270625567,Asia,8.99323751\r
-29/07/2020,29,7,2020,1748,63,Indonesia,ID,IDN,270625567,Asia,8.67582478\r
-28/07/2020,28,7,2020,1525,57,Indonesia,ID,IDN,270625567,Asia,8.61781104\r
-27/07/2020,27,7,2020,1492,67,Indonesia,ID,IDN,270625567,Asia,8.52801908\r
-26/07/2020,26,7,2020,1868,49,Indonesia,ID,IDN,270625567,Asia,8.59785727\r
-25/07/2020,25,7,2020,1761,89,Indonesia,ID,IDN,270625567,Asia,8.52506297\r
-24/07/2020,24,7,2020,1906,117,Indonesia,ID,IDN,270625567,Asia,8.46963583\r
-23/07/2020,23,7,2020,1882,139,Indonesia,ID,IDN,270625567,Asia,8.74714103\r
-22/07/2020,22,7,2020,1655,81,Indonesia,ID,IDN,270625567,Asia,8.73642511\r
-21/07/2020,21,7,2020,1693,96,Indonesia,ID,IDN,270625567,Asia,8.5934231\r
-20/07/2020,20,7,2020,1639,127,Indonesia,ID,IDN,270625567,Asia,8.41457821\r
-19/07/2020,19,7,2020,1752,59,Indonesia,ID,IDN,270625567,Asia,8.40275376\r
-18/07/2020,18,7,2020,1462,84,Indonesia,ID,IDN,270625567,Asia,8.29005192\r
-17/07/2020,17,7,2020,1574,76,Indonesia,ID,IDN,270625567,Asia,8.23056012\r
-16/07/2020,16,7,2020,1522,87,Indonesia,ID,IDN,270625567,Asia,8.24903583\r
-15/07/2020,15,7,2020,1591,54,Indonesia,ID,IDN,270625567,Asia,8.19841238\r
-14/07/2020,14,7,2020,1282,50,Indonesia,ID,IDN,270625567,Asia,8.08829714\r
-13/07/2020,13,7,2020,1681,71,Indonesia,ID,IDN,270625567,Asia,8.01439429\r
-12/07/2020,12,7,2020,1671,66,Indonesia,ID,IDN,270625567,Asia,7.83591892\r
-11/07/2020,11,7,2020,1611,52,Indonesia,ID,IDN,270625567,Asia,7.73023785\r
-10/07/2020,10,7,2020,2657,58,Indonesia,ID,IDN,270625567,Asia,7.59314806\r
-09/07/2020,9,7,2020,1853,50,Indonesia,ID,IDN,270625567,Asia,7.04663651\r
-08/07/2020,8,7,2020,1268,68,Indonesia,ID,IDN,270625567,Asia,6.77319597\r
-07/07/2020,7,7,2020,1209,70,Indonesia,ID,IDN,270625567,Asia,6.69301138\r
-06/07/2020,6,7,2020,1607,82,Indonesia,ID,IDN,270625567,Asia,6.59878525\r
-05/07/2020,5,7,2020,1447,53,Indonesia,ID,IDN,270625567,Asia,6.32349714\r
-04/07/2020,4,7,2020,1301,49,Indonesia,ID,IDN,270625567,Asia,6.2418345\r
-03/07/2020,3,7,2020,1624,53,Indonesia,ID,IDN,270625567,Asia,6.1457608\r
-02/07/2020,2,7,2020,1385,58,Indonesia,ID,IDN,270625567,Asia,6.03749312\r
-01/07/2020,1,7,2020,1293,71,Indonesia,ID,IDN,270625567,Asia,5.90668508\r
-30/06/2020,30,6,2020,1082,51,Indonesia,ID,IDN,270625567,Asia,5.83758592\r
-29/06/2020,29,6,2020,1198,34,Indonesia,ID,IDN,270625567,Asia,5.8135675\r
-28/06/2020,28,6,2020,1385,37,Indonesia,ID,IDN,270625567,Asia,5.68756314\r
-27/06/2020,27,6,2020,1240,63,Indonesia,ID,IDN,270625567,Asia,5.55047336\r
-26/06/2020,26,6,2020,1178,47,Indonesia,ID,IDN,270625567,Asia,5.50280602\r
-25/06/2020,25,6,2020,1113,38,Indonesia,ID,IDN,270625567,Asia,5.42927269\r
-24/06/2020,24,6,2020,1051,35,Indonesia,ID,IDN,270625567,Asia,5.476201\r
-23/06/2020,23,6,2020,954,35,Indonesia,ID,IDN,270625567,Asia,5.47324488\r
-22/06/2020,22,6,2020,862,36,Indonesia,ID,IDN,270625567,Asia,5.43370686\r
-21/06/2020,21,6,2020,1226,56,Indonesia,ID,IDN,270625567,Asia,5.36349916\r
-20/06/2020,20,6,2020,1041,34,Indonesia,ID,IDN,270625567,Asia,5.27740234\r
-19/06/2020,19,6,2020,1331,63,Indonesia,ID,IDN,270625567,Asia,5.15250653\r
-18/06/2020,18,6,2020,1031,45,Indonesia,ID,IDN,270625567,Asia,4.8768489\r
-17/06/2020,17,6,2020,1106,33,Indonesia,ID,IDN,270625567,Asia,4.74862746\r
-16/06/2020,16,6,2020,1017,64,Indonesia,ID,IDN,270625567,Asia,4.56497889\r
-15/06/2020,15,6,2020,857,43,Indonesia,ID,IDN,270625567,Asia,4.36174606\r
-14/06/2020,14,6,2020,1014,43,Indonesia,ID,IDN,270625567,Asia,4.30373232\r
-13/06/2020,13,6,2020,1111,48,Indonesia,ID,IDN,270625567,Asia,4.13486432\r
-12/06/2020,12,6,2020,979,41,Indonesia,ID,IDN,270625567,Asia,3.97486465\r
-11/06/2020,11,6,2020,1240,36,Indonesia,ID,IDN,270625567,Asia,3.86696649\r
-10/06/2020,10,6,2020,1043,40,Indonesia,ID,IDN,270625567,Asia,3.66225561\r
-09/06/2020,9,6,2020,847,32,Indonesia,ID,IDN,270625567,Asia,3.43020067\r
-08/06/2020,8,6,2020,672,50,Indonesia,ID,IDN,270625567,Asia,3.29421943\r
-07/06/2020,7,6,2020,993,31,Indonesia,ID,IDN,270625567,Asia,3.24027035\r
-06/06/2020,6,6,2020,703,49,Indonesia,ID,IDN,270625567,Asia,3.22401172\r
-05/06/2020,5,6,2020,585,23,Indonesia,ID,IDN,270625567,Asia,3.19851524\r
-04/06/2020,4,6,2020,684,35,Indonesia,ID,IDN,270625567,Asia,3.34188676\r
-03/06/2020,3,6,2020,609,22,Indonesia,ID,IDN,270625567,Asia,3.34521239\r
-02/06/2020,2,6,2020,467,28,Indonesia,ID,IDN,270625567,Asia,3.29976214\r
-01/06/2020,1,6,2020,700,40,Indonesia,ID,IDN,270625567,Asia,3.31047805\r
-31/05/2020,31,5,2020,557,53,Indonesia,ID,IDN,270625567,Asia,3.23251055\r
-30/05/2020,30,5,2020,678,24,Indonesia,ID,IDN,270625567,Asia,3.22216415\r
-29/05/2020,29,5,2020,687,23,Indonesia,ID,IDN,270625567,Asia,3.15269547\r
-28/05/2020,28,5,2020,686,55,Indonesia,ID,IDN,270625567,Asia,3.10872328\r
-27/05/2020,27,5,2020,415,27,Indonesia,ID,IDN,270625567,Asia,3.10983182\r
-26/05/2020,26,5,2020,479,19,Indonesia,ID,IDN,270625567,Asia,3.1353283\r
-25/05/2020,25,5,2020,526,21,Indonesia,ID,IDN,270625567,Asia,3.0444278\r
-24/05/2020,24,5,2020,949,25,Indonesia,ID,IDN,270625567,Asia,2.99306532\r
-23/05/2020,23,5,2020,634,48,Indonesia,ID,IDN,270625567,Asia,2.8393474\r
-22/05/2020,22,5,2020,973,36,Indonesia,ID,IDN,270625567,Asia,2.72923216\r
-21/05/2020,21,5,2020,693,21,Indonesia,ID,IDN,270625567,Asia,2.49459062\r
-20/05/2020,20,5,2020,486,30,Indonesia,ID,IDN,270625567,Asia,2.37412898\r
-19/05/2020,19,5,2020,496,43,Indonesia,ID,IDN,270625567,Asia,2.37338995\r
-18/05/2020,18,5,2020,489,59,Indonesia,ID,IDN,270625567,Asia,2.33606901\r
-17/05/2020,17,5,2020,529,13,Indonesia,ID,IDN,270625567,Asia,2.28433702\r
-16/05/2020,16,5,2020,490,33,Indonesia,ID,IDN,270625567,Asia,2.19676214\r
-15/05/2020,15,5,2020,568,15,Indonesia,ID,IDN,270625567,Asia,2.17569983\r
-14/05/2020,14,5,2020,689,21,Indonesia,ID,IDN,270625567,Asia,2.09403718\r
-13/05/2020,13,5,2020,484,16,Indonesia,ID,IDN,270625567,Asia,1.93551558\r
-12/05/2020,12,5,2020,233,18,Indonesia,ID,IDN,270625567,Asia,1.91001909\r
-11/05/2020,11,5,2020,387,14,Indonesia,ID,IDN,270625567,Asia,1.90299832\r
-10/05/2020,10,5,2020,533,16,Indonesia,ID,IDN,270625567,Asia,1.86161273\r
-09/05/2020,9,5,2020,336,13,Indonesia,ID,IDN,270625567,Asia,1.81098928\r
-08/05/2020,8,5,2020,338,35,Indonesia,ID,IDN,270625567,Asia,1.8479407\r
-07/05/2020,7,5,2020,367,23,Indonesia,ID,IDN,270625567,Asia,1.85496147\r
-06/05/2020,6,5,2020,484,8,Indonesia,ID,IDN,270625567,Asia,1.82392228\r
-05/05/2020,5,5,2020,395,19,Indonesia,ID,IDN,270625567,Asia,1.78364522\r
-04/05/2020,4,5,2020,349,14,Indonesia,ID,IDN,270625567,Asia,1.70604723\r
-03/05/2020,3,5,2020,292,31,Indonesia,ID,IDN,270625567,Asia,1.69791792\r
-02/05/2020,2,5,2020,433,8,Indonesia,ID,IDN,270625567,Asia,1.71011189\r
-01/05/2020,1,5,2020,347,8,Indonesia,ID,IDN,270625567,Asia,1.70050452\r
-30/04/2020,30,4,2020,260,11,Indonesia,ID,IDN,270625567,Asia,1.71269849\r
-29/04/2020,29,4,2020,415,8,Indonesia,ID,IDN,270625567,Asia,1.72637052\r
-28/04/2020,28,4,2020,214,22,Indonesia,ID,IDN,270625567,Asia,1.67722512\r
-27/04/2020,27,4,2020,275,23,Indonesia,ID,IDN,270625567,Asia,1.71491558\r
-26/04/2020,26,4,2020,396,31,Indonesia,ID,IDN,270625567,Asia,1.76073534\r
-25/04/2020,25,4,2020,436,42,Indonesia,ID,IDN,270625567,Asia,1.7363474\r
-24/04/2020,24,4,2020,357,12,Indonesia,ID,IDN,270625567,Asia,1.65616281\r
-23/04/2020,23,4,2020,283,19,Indonesia,ID,IDN,270625567,Asia,1.64877253\r
-22/04/2020,22,4,2020,375,26,Indonesia,ID,IDN,270625567,Asia,1.6247541\r
-21/04/2020,21,4,2020,185,8,Indonesia,ID,IDN,270625567,Asia,1.57745628\r
-20/04/2020,20,4,2020,327,47,Indonesia,ID,IDN,270625567,Asia,1.58965025\r
-19/04/2020,19,4,2020,325,15,Indonesia,ID,IDN,270625567,Asia,1.53570117\r
-18/04/2020,18,4,2020,407,24,Indonesia,ID,IDN,270625567,Asia,1.45477755\r
-17/04/2020,17,4,2020,380,27,Indonesia,ID,IDN,270625567,Asia,1.37681005\r
-16/04/2020,16,4,2020,297,10,Indonesia,ID,IDN,270625567,Asia,1.27814975\r
-15/04/2020,15,4,2020,282,60,Indonesia,ID,IDN,270625567,Asia,1.22346164\r
-14/04/2020,14,4,2020,316,26,Indonesia,ID,IDN,270625567,Asia,1.16138325\r
-13/04/2020,13,4,2020,399,46,Indonesia,ID,IDN,270625567,Asia,1.09228409\r
-12/04/2020,12,4,2020,330,21,Indonesia,ID,IDN,270625567,Asia,0.99288476\r
-11/04/2020,11,4,2020,219,26,Indonesia,ID,IDN,270625567,Asia,0.91122211\r
-10/04/2020,10,4,2020,337,40,Indonesia,ID,IDN,270625567,Asia,0.88683417\r
-09/04/2020,9,4,2020,218,19,Indonesia,ID,IDN,270625567,Asia,0.80036784\r
-08/04/2020,8,4,2020,247,12,Indonesia,ID,IDN,270625567,Asia,0.75824322\r
-07/04/2020,7,4,2020,218,11,Indonesia,ID,IDN,270625567,Asia,0.70651122\r
-06/04/2020,6,4,2020,181,7,Indonesia,ID,IDN,270625567,Asia,0.64997554\r
-05/04/2020,5,4,2020,106,10,Indonesia,ID,IDN,270625567,Asia,0.60674238\r
-04/04/2020,4,4,2020,196,11,Indonesia,ID,IDN,270625567,Asia,0.61967538\r
-03/04/2020,3,4,2020,113,13,Indonesia,ID,IDN,270625567,Asia,0.57755075\r
-02/04/2020,2,4,2020,149,21,Indonesia,ID,IDN,270625567,Asia,0.55611893\r
-01/04/2020,1,4,2020,114,14,Indonesia,ID,IDN,270625567,Asia,0.50106131\r
-31/03/2020,31,3,2020,129,8,Indonesia,ID,IDN,270625567,Asia,0.47297822\r
-30/03/2020,30,3,2020,130,12,Indonesia,ID,IDN,270625567,Asia,0.43159263\r
-29/03/2020,29,3,2020,109,15,Indonesia,ID,IDN,270625567,Asia,0.39131558\r
-28/03/2020,28,3,2020,153,9,Indonesia,ID,IDN,270625567,Asia,0.36101541\r
-27/03/2020,27,3,2020,103,20,Indonesia,ID,IDN,270625567,Asia,0.31741273\r
-26/03/2020,26,3,2020,104,3,Indonesia,ID,IDN,270625567,Asia,0.28489548\r
-25/03/2020,25,3,2020,107,6,Indonesia,ID,IDN,270625567,Asia,0.25126968\r
-24/03/2020,24,3,2020,65,1,Indonesia,ID,IDN,270625567,Asia,0.21247069\r
-23/03/2020,23,3,2020,64,10,Indonesia,ID,IDN,270625567,Asia,0.18919129\r
-22/03/2020,22,3,2020,141,13,Indonesia,ID,IDN,270625567,Asia,0.16628141\r
-21/03/2020,21,3,2020,82,6,Indonesia,ID,IDN,270625567,Asia,0.1141799\r
-20/03/2020,20,3,2020,55,14,Indonesia,ID,IDN,270625567,Asia,0.08387973\r
-19/03/2020,19,3,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0.06355645\r
-18/03/2020,18,3,2020,38,0,Indonesia,ID,IDN,270625567,Asia,0.06355645\r
-17/03/2020,17,3,2020,17,0,Indonesia,ID,IDN,270625567,Asia,0.04951491\r
-16/03/2020,16,3,2020,21,1,Indonesia,ID,IDN,270625567,Asia,0.04323317\r
-15/03/2020,15,3,2020,27,0,Indonesia,ID,IDN,270625567,Asia,0.03547337\r
-14/03/2020,14,3,2020,35,3,Indonesia,ID,IDN,270625567,Asia,0.02549648\r
-12/03/2020,12,3,2020,15,1,Indonesia,ID,IDN,270625567,Asia,0.01256348\r
-11/03/2020,11,3,2020,13,0,Indonesia,ID,IDN,270625567,Asia,0.00702077\r
-09/03/2020,9,3,2020,2,0,Indonesia,ID,IDN,270625567,Asia,0.00221709\r
-07/03/2020,7,3,2020,2,0,Indonesia,ID,IDN,270625567,Asia,0.00147806\r
-02/03/2020,2,3,2020,2,0,Indonesia,ID,IDN,270625567,Asia,0.00073903\r
-01/03/2020,1,3,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-29/02/2020,29,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-28/02/2020,28,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-27/02/2020,27,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-26/02/2020,26,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-25/02/2020,25,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-24/02/2020,24,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-23/02/2020,23,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-22/02/2020,22,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-21/02/2020,21,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-20/02/2020,20,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-19/02/2020,19,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-18/02/2020,18,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-17/02/2020,17,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-16/02/2020,16,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-15/02/2020,15,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-14/02/2020,14,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-13/02/2020,13,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-12/02/2020,12,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-11/02/2020,11,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-10/02/2020,10,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-09/02/2020,9,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-08/02/2020,8,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-07/02/2020,7,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-06/02/2020,6,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-05/02/2020,5,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-04/02/2020,4,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-03/02/2020,3,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-02/02/2020,2,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-01/02/2020,1,2,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-31/01/2020,31,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-30/01/2020,30,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-29/01/2020,29,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-28/01/2020,28,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-27/01/2020,27,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-26/01/2020,26,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-25/01/2020,25,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-24/01/2020,24,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-23/01/2020,23,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-22/01/2020,22,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-21/01/2020,21,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-20/01/2020,20,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-19/01/2020,19,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-18/01/2020,18,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-17/01/2020,17,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-16/01/2020,16,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-15/01/2020,15,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-14/01/2020,14,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-13/01/2020,13,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,0\r
-12/01/2020,12,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,\r
-11/01/2020,11,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,\r
-10/01/2020,10,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,\r
-09/01/2020,9,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,\r
-08/01/2020,8,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,\r
-07/01/2020,7,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,\r
-06/01/2020,6,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,\r
-05/01/2020,5,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,\r
-04/01/2020,4,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,\r
-03/01/2020,3,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,\r
-02/01/2020,2,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,\r
-01/01/2020,1,1,2020,0,0,Indonesia,ID,IDN,270625567,Asia,\r
-31/12/2019,31,12,2019,0,0,Indonesia,ID,IDN,270625567,Asia,\r
-19/08/2020,19,8,2020,2385,168,Iran,IR,IRN,82913893,Asia,39.8594238\r
-18/08/2020,18,8,2020,2247,165,Iran,IR,IRN,82913893,Asia,40.3008456\r
-17/08/2020,17,8,2020,2133,147,Iran,IR,IRN,82913893,Asia,40.72417635\r
-16/08/2020,16,8,2020,2245,161,Iran,IR,IRN,82913893,Asia,41.38992726\r
-15/08/2020,15,8,2020,2501,169,Iran,IR,IRN,82913893,Asia,41.75536662\r
-14/08/2020,14,8,2020,2625,174,Iran,IR,IRN,82913893,Asia,41.96401681\r
-13/08/2020,13,8,2020,2510,188,Iran,IR,IRN,82913893,Asia,41.95919253\r
-12/08/2020,12,8,2020,2345,184,Iran,IR,IRN,82913893,Asia,42.11115741\r
-11/08/2020,11,8,2020,2132,189,Iran,IR,IRN,82913893,Asia,42.49951211\r
-10/08/2020,10,8,2020,2020,163,Iran,IR,IRN,82913893,Asia,42.8637454\r
-09/08/2020,9,8,2020,2125,132,Iran,IR,IRN,82913893,Asia,43.24124547\r
-08/08/2020,8,8,2020,2450,316,Iran,IR,IRN,82913893,Asia,43.47160493\r
-07/08/2020,7,8,2020,2634,14,Iran,IR,IRN,82913893,Asia,43.51864168\r
-06/08/2020,6,8,2020,2697,185,Iran,IR,IRN,82913893,Asia,43.50296277\r
-05/08/2020,5,8,2020,2751,212,Iran,IR,IRN,82913893,Asia,43.36908894\r
-04/08/2020,4,8,2020,2598,215,Iran,IR,IRN,82913893,Asia,43.21712406\r
-03/08/2020,3,8,2020,2685,208,Iran,IR,IRN,82913893,Asia,42.99520709\r
-02/08/2020,2,8,2020,2548,216,Iran,IR,IRN,82913893,Asia,42.38855363\r
-01/08/2020,1,8,2020,2674,197,Iran,IR,IRN,82913893,Asia,41.9278347\r
-31/07/2020,31,7,2020,2621,226,Iran,IR,IRN,82913893,Asia,41.5720439\r
-30/07/2020,30,7,2020,2636,196,Iran,IR,IRN,82913893,Asia,41.42610937\r
-29/07/2020,29,7,2020,2667,235,Iran,IR,IRN,82913893,Asia,41.12700389\r
-28/07/2020,28,7,2020,2434,212,Iran,IR,IRN,82913893,Asia,40.9509176\r
-27/07/2020,27,7,2020,2333,216,Iran,IR,IRN,82913893,Asia,40.84840161\r
-26/07/2020,26,7,2020,2316,195,Iran,IR,IRN,82913893,Asia,40.67110924\r
-25/07/2020,25,7,2020,2489,215,Iran,IR,IRN,82913893,Asia,40.76880095\r
-24/07/2020,24,7,2020,2621,221,Iran,IR,IRN,82913893,Asia,40.49502295\r
-23/07/2020,23,7,2020,2586,219,Iran,IR,IRN,82913893,Asia,39.84133274\r
-22/07/2020,22,7,2020,2625,229,Iran,IR,IRN,82913893,Asia,39.96797014\r
-21/07/2020,21,7,2020,2414,217,Iran,IR,IRN,82913893,Asia,39.98244299\r
-20/07/2020,20,7,2020,2182,209,Iran,IR,IRN,82913893,Asia,40.22245102\r
-19/07/2020,19,7,2020,2166,188,Iran,IR,IRN,82913893,Asia,40.67834567\r
-18/07/2020,18,7,2020,2379,183,Iran,IR,IRN,82913893,Asia,41.01966362\r
-17/07/2020,17,7,2020,2500,198,Iran,IR,IRN,82913893,Asia,41.2451988\r
-16/07/2020,16,7,2020,2388,199,Iran,IR,IRN,82913893,Asia,41.42852151\r
-15/07/2020,15,7,2020,2521,179,Iran,IR,IRN,82913893,Asia,41.62269886\r
-14/07/2020,14,7,2020,2349,203,Iran,IR,IRN,82913893,Asia,41.54551035\r
-13/07/2020,13,7,2020,2186,194,Iran,IR,IRN,82913893,Asia,41.77104554\r
-12/07/2020,12,7,2020,2397,188,Iran,IR,IRN,82913893,Asia,42.1364849\r
-11/07/2020,11,7,2020,2262,142,Iran,IR,IRN,82913893,Asia,42.20764305\r
-10/07/2020,10,7,2020,2079,221,Iran,IR,IRN,82913893,Asia,42.64906486\r
-09/07/2020,9,7,2020,2691,153,Iran,IR,IRN,82913893,Asia,43.27139723\r
-08/07/2020,8,7,2020,2637,200,Iran,IR,IRN,82913893,Asia,43.07842595\r
-07/07/2020,7,7,2020,2613,160,Iran,IR,IRN,82913893,Asia,42.84686042\r
-06/07/2020,6,7,2020,2560,163,Iran,IR,IRN,82913893,Asia,42.7986176\r
-05/07/2020,5,7,2020,2449,148,Iran,IR,IRN,82913893,Asia,42.56705206\r
-04/07/2020,4,7,2020,2566,154,Iran,IR,IRN,82913893,Asia,42.41388111\r
-03/07/2020,3,7,2020,2652,148,Iran,IR,IRN,82913893,Asia,42.47297856\r
-02/07/2020,2,7,2020,2549,141,Iran,IR,IRN,82913893,Asia,42.40543862\r
-01/07/2020,1,7,2020,2457,147,Iran,IR,IRN,82913893,Asia,42.48142106\r
-30/06/2020,30,6,2020,2536,162,Iran,IR,IRN,82913893,Asia,42.60926453\r
-29/06/2020,29,6,2020,2489,144,Iran,IR,IRN,82913893,Asia,42.5043364\r
-28/06/2020,28,6,2020,2456,234,Iran,IR,IRN,82913893,Asia,42.4838332\r
-27/06/2020,27,6,2020,2628,0,Iran,IR,IRN,82913893,Asia,42.42835396\r
-26/06/2020,26,6,2020,2595,134,Iran,IR,IRN,82913893,Asia,42.1159817\r
-25/06/2020,25,6,2020,2531,133,Iran,IR,IRN,82913893,Asia,41.68541453\r
-24/06/2020,24,6,2020,2445,121,Iran,IR,IRN,82913893,Asia,41.05825787\r
-23/06/2020,23,6,2020,2573,119,Iran,IR,IRN,82913893,Asia,40.6361332\r
-22/06/2020,22,6,2020,2368,116,Iran,IR,IRN,82913893,Asia,39.99691584\r
-21/06/2020,21,6,2020,2322,115,Iran,IR,IRN,82913893,Asia,39.99209155\r
-20/06/2020,20,6,2020,2615,120,Iran,IR,IRN,82913893,Asia,39.92816982\r
-19/06/2020,19,6,2020,2596,87,Iran,IR,IRN,82913893,Asia,40.25501492\r
-18/06/2020,18,6,2020,2612,120,Iran,IR,IRN,82913893,Asia,41.43455187\r
-17/06/2020,17,6,2020,2563,115,Iran,IR,IRN,82913893,Asia,42.06412067\r
-16/06/2020,16,6,2020,2449,113,Iran,IR,IRN,82913893,Asia,42.73228372\r
-15/06/2020,15,6,2020,2472,107,Iran,IR,IRN,82913893,Asia,43.37150108\r
-14/06/2020,14,6,2020,2410,71,Iran,IR,IRN,82913893,Asia,43.42456818\r
-13/06/2020,13,6,2020,2369,75,Iran,IR,IRN,82913893,Asia,43.27019116\r
-12/06/2020,12,6,2020,2238,78,Iran,IR,IRN,82913893,Asia,43.81292288\r
-11/06/2020,11,6,2020,2011,81,Iran,IR,IRN,82913893,Asia,43.83704429\r
-10/06/2020,10,6,2020,2095,74,Iran,IR,IRN,82913893,Asia,43.92026316\r
-09/06/2020,9,6,2020,2043,70,Iran,IR,IRN,82913893,Asia,43.54879345\r
-08/06/2020,8,6,2020,2364,72,Iran,IR,IRN,82913893,Asia,43.52467204\r
-07/06/2020,7,6,2020,2269,75,Iran,IR,IRN,82913893,Asia,43.30275506\r
-06/06/2020,6,6,2020,2886,63,Iran,IR,IRN,82913893,Asia,42.82032687\r
-05/06/2020,5,6,2020,3574,59,Iran,IR,IRN,82913893,Asia,42.12683633\r
-04/06/2020,4,6,2020,3134,70,Iran,IR,IRN,82913893,Asia,40.70126101\r
-03/06/2020,3,6,2020,3117,64,Iran,IR,IRN,82913893,Asia,39.75087746\r
-02/06/2020,2,6,2020,2979,81,Iran,IR,IRN,82913893,Asia,38.53757054\r
-01/06/2020,1,6,2020,2516,63,Iran,IR,IRN,82913893,Asia,37.71141225\r
-31/05/2020,31,5,2020,2282,57,Iran,IR,IRN,82913893,Asia,36.8551022\r
-30/05/2020,30,5,2020,2819,50,Iran,IR,IRN,82913893,Asia,36.22191519\r
-29/05/2020,29,5,2020,2258,63,Iran,IR,IRN,82913893,Asia,35.35716264\r
-28/05/2020,28,5,2020,2080,56,Iran,IR,IRN,82913893,Asia,34.81443092\r
-27/05/2020,27,5,2020,1787,57,Iran,IR,IRN,82913893,Asia,34.66729032\r
-26/05/2020,26,5,2020,2023,34,Iran,IR,IRN,82913893,Asia,34.29823275\r
-25/05/2020,25,5,2020,2180,58,Iran,IR,IRN,82913893,Asia,33.88816878\r
-24/05/2020,24,5,2020,1869,59,Iran,IR,IRN,82913893,Asia,32.92693059\r
-23/05/2020,23,5,2020,2311,51,Iran,IR,IRN,82913893,Asia,32.51686662\r
-22/05/2020,22,5,2020,2392,66,Iran,IR,IRN,82913893,Asia,31.6062834\r
-21/05/2020,21,5,2020,2346,64,Iran,IR,IRN,82913893,Asia,30.51237746\r
-20/05/2020,20,5,2020,2111,62,Iran,IR,IRN,82913893,Asia,29.70913451\r
-19/05/2020,19,5,2020,2294,69,Iran,IR,IRN,82913893,Asia,28.75875096\r
-18/05/2020,18,5,2020,1806,51,Iran,IR,IRN,82913893,Asia,27.46704946\r
-17/05/2020,17,5,2020,1757,35,Iran,IR,IRN,82913893,Asia,26.46601095\r
-16/05/2020,16,5,2020,2102,48,Iran,IR,IRN,82913893,Asia,25.31421363\r
-15/05/2020,15,5,2020,1808,71,Iran,IR,IRN,82913893,Asia,23.99236036\r
-14/05/2020,14,5,2020,1958,50,Iran,IR,IRN,82913893,Asia,22.9973522\r
-13/05/2020,13,5,2020,1481,48,Iran,IR,IRN,82913893,Asia,21.92997982\r
-12/05/2020,12,5,2020,1683,45,Iran,IR,IRN,82913893,Asia,21.4849398\r
-11/05/2020,11,5,2020,1383,51,Iran,IR,IRN,82913893,Asia,20.65033902\r
-10/05/2020,10,5,2020,1529,48,Iran,IR,IRN,82913893,Asia,20.37294281\r
-09/05/2020,9,5,2020,1556,55,Iran,IR,IRN,82913893,Asia,19.89654496\r
-08/05/2020,8,5,2020,1485,68,Iran,IR,IRN,82913893,Asia,19.42858961\r
-07/05/2020,7,5,2020,1680,78,Iran,IR,IRN,82913893,Asia,18.87982753\r
-06/05/2020,6,5,2020,1323,63,Iran,IR,IRN,82913893,Asia,18.29367727\r
-05/05/2020,5,5,2020,1223,74,Iran,IR,IRN,82913893,Asia,18.26231944\r
-04/05/2020,4,5,2020,976,47,Iran,IR,IRN,82913893,Asia,18.34795045\r
-03/05/2020,3,5,2020,802,65,Iran,IR,IRN,82913893,Asia,18.79057832\r
-02/05/2020,2,5,2020,1006,63,Iran,IR,IRN,82913893,Asia,19.48045064\r
-01/05/2020,1,5,2020,983,71,Iran,IR,IRN,82913893,Asia,20.07504339\r
-30/04/2020,30,4,2020,1073,80,Iran,IR,IRN,82913893,Asia,20.82642531\r
-29/04/2020,29,4,2020,1112,71,Iran,IR,IRN,82913893,Asia,21.35589026\r
-28/04/2020,28,4,2020,991,96,Iran,IR,IRN,82913893,Asia,21.91309483\r
-27/04/2020,27,4,2020,1153,60,Iran,IR,IRN,82913893,Asia,22.66809496\r
-26/04/2020,26,4,2020,1134,76,Iran,IR,IRN,82913893,Asia,23.27595449\r
-25/04/2020,25,4,2020,1168,93,Iran,IR,IRN,82913893,Asia,24.12382205\r
-24/04/2020,24,4,2020,1030,90,Iran,IR,IRN,82913893,Asia,25.09350273\r
-23/04/2020,23,4,2020,1194,94,Iran,IR,IRN,82913893,Asia,25.8219693\r
-22/04/2020,22,4,2020,1297,88,Iran,IR,IRN,82913893,Asia,26.79044391\r
-21/04/2020,21,4,2020,1294,91,Iran,IR,IRN,82913893,Asia,27.74565174\r
-20/04/2020,20,4,2020,1343,87,Iran,IR,IRN,82913893,Asia,28.92760083\r
-19/04/2020,19,4,2020,1374,73,Iran,IR,IRN,82913893,Asia,30.3025212\r
-18/04/2020,18,4,2020,1499,89,Iran,IR,IRN,82913893,Asia,35.0074022\r
-17/04/2020,17,4,2020,1606,92,Iran,IR,IRN,82913893,Asia,33.19950252\r
-16/04/2020,16,4,2020,1512,94,Iran,IR,IRN,82913893,Asia,34.73000598\r
-15/04/2020,15,4,2020,1574,98,Iran,IR,IRN,82913893,Asia,36.50895996\r
-14/04/2020,14,4,2020,1617,111,Iran,IR,IRN,82913893,Asia,38.36269032\r
-13/04/2020,13,4,2020,1657,117,Iran,IR,IRN,82913893,Asia,40.25501492\r
-12/04/2020,12,4,2020,1837,125,Iran,IR,IRN,82913893,Asia,41.75536662\r
-11/04/2020,11,4,2020,1972,122,Iran,IR,IRN,82913893,Asia,43.24968796\r
-10/04/2020,10,4,2020,1634,117,Iran,IR,IRN,82913893,Asia,44.40027921\r
-09/04/2020,9,4,2020,1997,121,Iran,IR,IRN,82913893,Asia,45.31086244\r
-08/04/2020,8,4,2020,2089,133,Iran,IR,IRN,82913893,Asia,45.56293117\r
-07/04/2020,7,4,2020,2274,136,Iran,IR,IRN,82913893,Asia,45.16854612\r
-06/04/2020,6,4,2020,2483,151,Iran,IR,IRN,82913893,Asia,44.12770728\r
-05/04/2020,5,4,2020,5275,292,Iran,IR,IRN,82913893,Asia,42.37287471\r
-04/04/2020,4,4,2020,0,0,Iran,IR,IRN,82913893,Asia,37.17591695\r
-03/04/2020,3,4,2020,2875,124,Iran,IR,IRN,82913893,Asia,38.66782615\r
-02/04/2020,2,4,2020,2987,138,Iran,IR,IRN,82913893,Asia,36.46192321\r
-01/04/2020,1,4,2020,3111,141,Iran,IR,IRN,82913893,Asia,34.29702668\r
-31/03/2020,31,3,2020,3186,117,Iran,IR,IRN,82913893,Asia,31.96569241\r
-30/03/2020,30,3,2020,2901,123,Iran,IR,IRN,82913893,Asia,29.39314404\r
-29/03/2020,29,3,2020,3076,139,Iran,IR,IRN,82913893,Asia,27.35247276\r
-28/03/2020,28,3,2020,2926,144,Iran,IR,IRN,82913893,Asia,25.28888615\r
-27/03/2020,27,3,2020,2389,157,Iran,IR,IRN,82913893,Asia,23.31454875\r
-26/03/2020,26,3,2020,2206,143,Iran,IR,IRN,82913893,Asia,21.72977211\r
-25/03/2020,25,3,2020,1762,122,Iran,IR,IRN,82913893,Asia,20.22459614\r
-24/03/2020,24,3,2020,1411,127,Iran,IR,IRN,82913893,Asia,19.16204803\r
-23/03/2020,23,3,2020,1028,129,Iran,IR,IRN,82913893,Asia,18.17789451\r
-22/03/2020,22,3,2020,966,123,Iran,IR,IRN,82913893,Asia,17.83416441\r
-21/03/2020,21,3,2020,1237,149,Iran,IR,IRN,82913893,Asia,17.96683217\r
-20/03/2020,20,3,2020,1046,149,Iran,IR,IRN,82913893,Asia,17.96321396\r
-19/03/2020,19,3,2020,1192,147,Iran,IR,IRN,82913893,Asia,17.41445188\r
-18/03/2020,18,3,2020,1178,135,Iran,IR,IRN,82913893,Asia,16.68357316\r
-17/03/2020,17,3,2020,1053,129,Iran,IR,IRN,82913893,Asia,16.26989098\r
-16/03/2020,16,3,2020,1209,113,Iran,IR,IRN,82913893,Asia,15.63067362\r
-15/03/2020,15,3,2020,1365,97,Iran,IR,IRN,82913893,Asia,14.63687153\r
-14/03/2020,14,3,2020,1289,85,Iran,IR,IRN,82913893,Asia,13.23782976\r
-13/03/2020,13,3,2020,1075,75,Iran,IR,IRN,82913893,Asia,11.85567297\r
-12/03/2020,12,3,2020,958,63,Iran,IR,IRN,82913893,Asia,10.68699066\r
-11/03/2020,11,3,2020,881,54,Iran,IR,IRN,82913893,Asia,9.58464223\r
-10/03/2020,10,3,2020,595,43,Iran,IR,IRN,82913893,Asia,8.56310052\r
-09/03/2020,9,3,2020,743,49,Iran,IR,IRN,82913893,Asia,7.86719784\r
-08/03/2020,8,3,2020,1076,21,Iran,IR,IRN,82913893,Asia,6.98917852\r
-07/03/2020,7,3,2020,1234,17,Iran,IR,IRN,82913893,Asia,5.70350737\r
-06/03/2020,6,3,2020,591,15,Iran,IR,IRN,82913893,Asia,4.2308953\r
-05/03/2020,5,3,2020,586,15,Iran,IR,IRN,82913893,Asia,3.52172585\r
-04/03/2020,4,3,2020,835,11,Iran,IR,IRN,82913893,Asia,2.81738068\r
-03/03/2020,3,3,2020,523,12,Iran,IR,IRN,82913893,Asia,1.81031181\r
-02/03/2020,2,3,2020,385,11,Iran,IR,IRN,82913893,Asia,1.17953694\r
-01/03/2020,1,3,2020,205,9,Iran,IR,IRN,82913893,Asia,0.7151998\r
-29/02/2020,29,2,2020,143,8,Iran,IR,IRN,82913893,Asia,0.46795535\r
-28/02/2020,28,2,2020,106,7,Iran,IR,IRN,82913893,Asia,0.29548727\r
-27/02/2020,27,2,2020,44,4,Iran,IR,IRN,82913893,Asia,0.1676438\r
-26/02/2020,26,2,2020,34,3,Iran,IR,IRN,82913893,Asia,0.1145767\r
-25/02/2020,25,2,2020,18,4,Iran,IR,IRN,82913893,Asia,0.0735703\r
-24/02/2020,24,2,2020,15,3,Iran,IR,IRN,82913893,Asia,0.05186103\r
-23/02/2020,23,2,2020,10,1,Iran,IR,IRN,82913893,Asia,0.03376997\r
-22/02/2020,22,2,2020,13,2,Iran,IR,IRN,82913893,Asia,0.02170927\r
-21/02/2020,21,2,2020,3,0,Iran,IR,IRN,82913893,Asia,0.00603035\r
-20/02/2020,20,2,2020,2,2,Iran,IR,IRN,82913893,Asia,0.00241214\r
-19/02/2020,19,2,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-18/02/2020,18,2,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-17/02/2020,17,2,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-16/02/2020,16,2,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-15/02/2020,15,2,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-14/02/2020,14,2,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-13/02/2020,13,2,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-12/02/2020,12,2,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-11/02/2020,11,2,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-10/02/2020,10,2,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-09/02/2020,9,2,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-08/02/2020,8,2,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-07/02/2020,7,2,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-06/02/2020,6,2,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-05/02/2020,5,2,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-04/02/2020,4,2,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-03/02/2020,3,2,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-02/02/2020,2,2,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-01/02/2020,1,2,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-31/01/2020,31,1,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-30/01/2020,30,1,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-29/01/2020,29,1,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-28/01/2020,28,1,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-27/01/2020,27,1,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-26/01/2020,26,1,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-25/01/2020,25,1,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-24/01/2020,24,1,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-23/01/2020,23,1,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-22/01/2020,22,1,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-21/01/2020,21,1,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-20/01/2020,20,1,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-19/01/2020,19,1,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-18/01/2020,18,1,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-17/01/2020,17,1,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-16/01/2020,16,1,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-15/01/2020,15,1,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-14/01/2020,14,1,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-13/01/2020,13,1,2020,0,0,Iran,IR,IRN,82913893,Asia,0\r
-12/01/2020,12,1,2020,0,0,Iran,IR,IRN,82913893,Asia,\r
-11/01/2020,11,1,2020,0,0,Iran,IR,IRN,82913893,Asia,\r
-10/01/2020,10,1,2020,0,0,Iran,IR,IRN,82913893,Asia,\r
-09/01/2020,9,1,2020,0,0,Iran,IR,IRN,82913893,Asia,\r
-08/01/2020,8,1,2020,0,0,Iran,IR,IRN,82913893,Asia,\r
-07/01/2020,7,1,2020,0,0,Iran,IR,IRN,82913893,Asia,\r
-06/01/2020,6,1,2020,0,0,Iran,IR,IRN,82913893,Asia,\r
-05/01/2020,5,1,2020,0,0,Iran,IR,IRN,82913893,Asia,\r
-04/01/2020,4,1,2020,0,0,Iran,IR,IRN,82913893,Asia,\r
-03/01/2020,3,1,2020,0,0,Iran,IR,IRN,82913893,Asia,\r
-02/01/2020,2,1,2020,0,0,Iran,IR,IRN,82913893,Asia,\r
-01/01/2020,1,1,2020,0,0,Iran,IR,IRN,82913893,Asia,\r
-31/12/2019,31,12,2019,0,0,Iran,IR,IRN,82913893,Asia,\r
-19/08/2020,19,8,2020,4576,82,Iraq,IQ,IRQ,39309789,Asia,127.16171028\r
-18/08/2020,18,8,2020,3202,94,Iraq,IQ,IRQ,39309789,Asia,122.7353319\r
-17/08/2020,17,8,2020,4348,75,Iraq,IQ,IRQ,39309789,Asia,121.54733265\r
-16/08/2020,16,8,2020,4293,76,Iraq,IQ,IRQ,39309789,Asia,116.71138708\r
-15/08/2020,15,8,2020,4013,68,Iraq,IQ,IRQ,39309789,Asia,111.11990451\r
-14/08/2020,14,8,2020,3841,53,Iraq,IQ,IRQ,39309789,Asia,109.42312613\r
-13/08/2020,13,8,2020,3441,57,Iraq,IQ,IRQ,39309789,Asia,107.18958578\r
-12/08/2020,12,8,2020,3396,67,Iraq,IQ,IRQ,39309789,Asia,105.98632315\r
-11/08/2020,11,8,2020,3484,72,Iraq,IQ,IRQ,39309789,Asia,104.3353349\r
-10/08/2020,10,8,2020,2726,82,Iraq,IQ,IRQ,39309789,Asia,101.96696808\r
-09/08/2020,9,8,2020,3325,74,Iraq,IQ,IRQ,39309789,Asia,101.28774794\r
-08/08/2020,8,8,2020,3461,75,Iraq,IQ,IRQ,39309789,Asia,100.10992427\r
-07/08/2020,7,8,2020,3047,67,Iraq,IQ,IRQ,39309789,Asia,97.62708215\r
-06/08/2020,6,8,2020,2834,77,Iraq,IQ,IRQ,39309789,Asia,95.88196976\r
-05/08/2020,5,8,2020,2836,83,Iraq,IQ,IRQ,39309789,Asia,95.55635112\r
-04/08/2020,4,8,2020,2735,66,Iraq,IQ,IRQ,39309789,Asia,94.61510974\r
-03/08/2020,3,8,2020,2447,63,Iraq,IQ,IRQ,39309789,Asia,93.16000144\r
-02/08/2020,2,8,2020,2095,64,Iraq,IQ,IRQ,39309789,Asia,92.81148774\r
-01/08/2020,1,8,2020,3346,70,Iraq,IQ,IRQ,39309789,Asia,92.69446855\r
-31/07/2020,31,7,2020,2963,68,Iraq,IQ,IRQ,39309789,Asia,89.32889464\r
-30/07/2020,30,7,2020,2968,68,Iraq,IQ,IRQ,39309789,Asia,87.59395783\r
-29/07/2020,29,7,2020,2747,77,Iraq,IQ,IRQ,39309789,Asia,85.41129539\r
-28/07/2020,28,7,2020,2553,96,Iraq,IQ,IRQ,39309789,Asia,83.56697107\r
-27/07/2020,27,7,2020,2459,78,Iraq,IQ,IRQ,39309789,Asia,82.74274889\r
-26/07/2020,26,7,2020,2862,72,Iraq,IQ,IRQ,39309789,Asia,82.36879623\r
-25/07/2020,25,7,2020,2485,90,Iraq,IQ,IRQ,39309789,Asia,82.04317759\r
-24/07/2020,24,7,2020,2361,80,Iraq,IQ,IRQ,39309789,Asia,82.9666117\r
-23/07/2020,23,7,2020,2706,92,Iraq,IQ,IRQ,39309789,Asia,82.48072764\r
-22/07/2020,22,7,2020,2466,81,Iraq,IQ,IRQ,39309789,Asia,82.56976398\r
-21/07/2020,21,7,2020,2163,88,Iraq,IQ,IRQ,39309789,Asia,82.46800816\r
-20/07/2020,20,7,2020,2310,90,Iraq,IQ,IRQ,39309789,Asia,81.53439847\r
-19/07/2020,19,7,2020,2049,75,Iraq,IQ,IRQ,39309789,Asia,81.06377778\r
-18/07/2020,18,7,2020,2023,94,Iraq,IQ,IRQ,39309789,Asia,81.78878803\r
-17/07/2020,17,7,2020,2281,90,Iraq,IQ,IRQ,39309789,Asia,82.52397386\r
-16/07/2020,16,7,2020,2110,87,Iraq,IQ,IRQ,39309789,Asia,82.27721599\r
-15/07/2020,15,7,2020,2022,95,Iraq,IQ,IRQ,39309789,Asia,83.05310415\r
-14/07/2020,14,7,2020,2229,100,Iraq,IQ,IRQ,39309789,Asia,82.89029483\r
-13/07/2020,13,7,2020,2312,95,Iraq,IQ,IRQ,39309789,Asia,81.66922494\r
-12/07/2020,12,7,2020,2734,95,Iraq,IQ,IRQ,39309789,Asia,81.23167489\r
-11/07/2020,11,7,2020,2848,78,Iraq,IQ,IRQ,39309789,Asia,79.5399843\r
-10/07/2020,10,7,2020,2170,103,Iraq,IQ,IRQ,39309789,Asia,77.52013118\r
-09/07/2020,9,7,2020,2741,94,Iraq,IQ,IRQ,39309789,Asia,78.19935131\r
-08/07/2020,8,7,2020,2426,118,Iraq,IQ,IRQ,39309789,Asia,76.82310378\r
-07/07/2020,7,7,2020,1796,94,Iraq,IQ,IRQ,39309789,Asia,75.29676641\r
-06/07/2020,6,7,2020,2125,105,Iraq,IQ,IRQ,39309789,Asia,75.32729316\r
-05/07/2020,5,7,2020,2334,106,Iraq,IQ,IRQ,39309789,Asia,74.10876716\r
-04/07/2020,4,7,2020,2312,102,Iraq,IQ,IRQ,39309789,Asia,72.92839959\r
-03/07/2020,3,7,2020,2184,110,Iraq,IQ,IRQ,39309789,Asia,71.20618226\r
-02/07/2020,2,7,2020,2415,107,Iraq,IQ,IRQ,39309789,Asia,69.37203352\r
-01/07/2020,1,7,2020,1958,104,Iraq,IQ,IRQ,39309789,Asia,67.18173939\r
-30/06/2020,30,6,2020,1749,83,Iraq,IQ,IRQ,39309789,Asia,65.7240872\r
-29/06/2020,29,6,2020,2140,96,Iraq,IQ,IRQ,39309789,Asia,64.08836232\r
-28/06/2020,28,6,2020,2069,101,Iraq,IQ,IRQ,39309789,Asia,61.84719028\r
-27/06/2020,27,6,2020,2054,122,Iraq,IQ,IRQ,39309789,Asia,59.58566707\r
-26/06/2020,26,6,2020,2437,107,Iraq,IQ,IRQ,39309789,Asia,57.14607117\r
-25/06/2020,25,6,2020,2200,79,Iraq,IQ,IRQ,39309789,Asia,54.15444993\r
-24/06/2020,24,6,2020,1826,84,Iraq,IQ,IRQ,39309789,Asia,51.47318394\r
-23/06/2020,23,6,2020,1808,67,Iraq,IQ,IRQ,39309789,Asia,48.8300764\r
-22/06/2020,22,6,2020,1646,87,Iraq,IQ,IRQ,39309789,Asia,47.06715673\r
-21/06/2020,21,6,2020,1870,88,Iraq,IQ,IRQ,39309789,Asia,46.10556419\r
-20/06/2020,20,6,2020,1635,69,Iraq,IQ,IRQ,39309789,Asia,44.5334367\r
-19/06/2020,19,6,2020,1463,83,Iraq,IQ,IRQ,39309789,Asia,42.93332635\r
-18/06/2020,18,6,2020,1554,61,Iraq,IQ,IRQ,39309789,Asia,40.92110492\r
-17/06/2020,17,6,2020,1385,60,Iraq,IQ,IRQ,39309789,Asia,38.95467361\r
-16/06/2020,16,6,2020,1106,45,Iraq,IQ,IRQ,39309789,Asia,36.75166\r
-15/06/2020,15,6,2020,1259,58,Iraq,IQ,IRQ,39309789,Asia,35.02944267\r
-14/06/2020,14,6,2020,1180,53,Iraq,IQ,IRQ,39309789,Asia,32.48809094\r
-13/06/2020,13,6,2020,1095,39,Iraq,IQ,IRQ,39309789,Asia,30.26472617\r
-12/06/2020,12,6,2020,1261,31,Iraq,IQ,IRQ,39309789,Asia,28.53742105\r
-11/06/2020,11,6,2020,1146,34,Iraq,IQ,IRQ,39309789,Asia,26.14870306\r
-10/06/2020,10,6,2020,787,22,Iraq,IQ,IRQ,39309789,Asia,23.96349673\r
-09/06/2020,9,6,2020,1115,24,Iraq,IQ,IRQ,39309789,Asia,22.51093233\r
-08/06/2020,8,6,2020,1268,28,Iraq,IQ,IRQ,39309789,Asia,20.0891437\r
-07/06/2020,7,6,2020,1252,33,Iraq,IQ,IRQ,39309789,Asia,17.36463149\r
-06/06/2020,6,6,2020,1006,14,Iraq,IQ,IRQ,39309789,Asia,14.96319403\r
-05/06/2020,5,6,2020,672,15,Iraq,IQ,IRQ,39309789,Asia,12.62535395\r
-04/06/2020,4,6,2020,781,21,Iraq,IQ,IRQ,39309789,Asia,11.30507213\r
-03/06/2020,3,6,2020,519,20,Iraq,IQ,IRQ,39309789,Asia,9.60574986\r
-02/06/2020,2,6,2020,429,10,Iraq,IQ,IRQ,39309789,Asia,8.43047008\r
-01/06/2020,1,6,2020,260,10,Iraq,IQ,IRQ,39309789,Asia,7.7207232\r
-31/05/2020,31,5,2020,306,10,Iraq,IQ,IRQ,39309789,Asia,7.42563131\r
-30/05/2020,30,5,2020,416,6,Iraq,IQ,IRQ,39309789,Asia,6.81764026\r
-29/05/2020,29,5,2020,322,4,Iraq,IQ,IRQ,39309789,Asia,5.88657446\r
-28/05/2020,28,5,2020,287,6,Iraq,IQ,IRQ,39309789,Asia,5.34981249\r
-27/05/2020,27,5,2020,216,6,Iraq,IQ,IRQ,39309789,Asia,4.92243802\r
-26/05/2020,26,5,2020,163,3,Iraq,IQ,IRQ,39309789,Asia,4.61462665\r
-25/05/2020,25,5,2020,197,8,Iraq,IQ,IRQ,39309789,Asia,4.32971034\r
-24/05/2020,24,5,2020,308,5,Iraq,IQ,IRQ,39309789,Asia,4.05242572\r
-23/05/2020,23,5,2020,87,7,Iraq,IQ,IRQ,39309789,Asia,3.46224194\r
-22/05/2020,22,5,2020,153,6,Iraq,IQ,IRQ,39309789,Asia,3.39355676\r
-21/05/2020,21,5,2020,113,3,Iraq,IQ,IRQ,39309789,Asia,3.16460615\r
-20/05/2020,20,5,2020,57,4,Iraq,IQ,IRQ,39309789,Asia,3.00179683\r
-19/05/2020,19,5,2020,150,4,Iraq,IQ,IRQ,39309789,Asia,3.07302591\r
-18/05/2020,18,5,2020,144,2,Iraq,IQ,IRQ,39309789,Asia,2.81863635\r
-17/05/2020,17,5,2020,67,4,Iraq,IQ,IRQ,39309789,Asia,2.64819534\r
-16/05/2020,16,5,2020,50,2,Iraq,IQ,IRQ,39309789,Asia,2.64565144\r
-15/05/2020,15,5,2020,111,0,Iraq,IQ,IRQ,39309789,Asia,2.69144156\r
-14/05/2020,14,5,2020,119,3,Iraq,IQ,IRQ,39309789,Asia,2.61766859\r
-13/05/2020,13,5,2020,95,2,Iraq,IQ,IRQ,39309789,Asia,2.71179273\r
-12/05/2020,12,5,2020,51,1,Iraq,IQ,IRQ,39309789,Asia,2.47012265\r
-11/05/2020,11,5,2020,88,2,Iraq,IQ,IRQ,39309789,Asia,2.40906915\r
-10/05/2020,10,5,2020,76,3,Iraq,IQ,IRQ,39309789,Asia,2.33020839\r
-09/05/2020,9,5,2020,60,2,Iraq,IQ,IRQ,39309789,Asia,2.27678658\r
-08/05/2020,8,5,2020,63,0,Iraq,IQ,IRQ,39309789,Asia,2.20301361\r
-07/05/2020,7,5,2020,49,0,Iraq,IQ,IRQ,39309789,Asia,2.23354035\r
-06/05/2020,6,5,2020,85,4,Iraq,IQ,IRQ,39309789,Asia,2.10888947\r
-05/05/2020,5,5,2020,50,1,Iraq,IQ,IRQ,39309789,Asia,1.96388742\r
-04/05/2020,4,5,2020,77,2,Iraq,IQ,IRQ,39309789,Asia,1.92572898\r
-03/05/2020,3,5,2020,66,1,Iraq,IQ,IRQ,39309789,Asia,1.87485107\r
-02/05/2020,2,5,2020,68,1,Iraq,IQ,IRQ,39309789,Asia,1.70695396\r
-01/05/2020,1,5,2020,82,1,Iraq,IQ,IRQ,39309789,Asia,1.65607605\r
-30/04/2020,30,4,2020,156,4,Iraq,IQ,IRQ,39309789,Asia,1.49581062\r
-29/04/2020,29,4,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,1.13712134\r
-28/04/2020,28,4,2020,27,1,Iraq,IQ,IRQ,39309789,Asia,1.19308705\r
-27/04/2020,27,4,2020,57,1,Iraq,IQ,IRQ,39309789,Asia,1.19054315\r
-26/04/2020,26,4,2020,55,0,Iraq,IQ,IRQ,39309789,Asia,1.13203355\r
-25/04/2020,25,4,2020,31,3,Iraq,IQ,IRQ,39309789,Asia,1.09133122\r
-24/04/2020,24,4,2020,75,0,Iraq,IQ,IRQ,39309789,Asia,1.13203355\r
-23/04/2020,23,4,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,1.01755825\r
-22/04/2020,22,4,2020,28,1,Iraq,IQ,IRQ,39309789,Asia,1.4525644\r
-21/04/2020,21,4,2020,35,0,Iraq,IQ,IRQ,39309789,Asia,1.38133532\r
-20/04/2020,20,4,2020,57,1,Iraq,IQ,IRQ,39309789,Asia,1.47037167\r
-19/04/2020,19,4,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,1.53651295\r
-18/04/2020,18,4,2020,48,1,Iraq,IQ,IRQ,39309789,Asia,1.80616589\r
-17/04/2020,17,4,2020,19,1,Iraq,IQ,IRQ,39309789,Asia,1.6840589\r
-16/04/2020,16,4,2020,15,1,Iraq,IQ,IRQ,39309789,Asia,1.83414874\r
-15/04/2020,15,4,2020,22,0,Iraq,IQ,IRQ,39309789,Asia,1.79599031\r
-14/04/2020,14,4,2020,26,2,Iraq,IQ,IRQ,39309789,Asia,1.90283392\r
-13/04/2020,13,4,2020,34,4,Iraq,IQ,IRQ,39309789,Asia,2.04783597\r
-12/04/2020,12,4,2020,39,2,Iraq,IQ,IRQ,39309789,Asia,2.06564324\r
-11/04/2020,11,4,2020,47,1,Iraq,IQ,IRQ,39309789,Asia,2.0885383\r
-10/04/2020,10,4,2020,30,0,Iraq,IQ,IRQ,39309789,Asia,2.16231128\r
-09/04/2020,9,4,2020,171,5,Iraq,IQ,IRQ,39309789,Asia,2.17757465\r
-08/04/2020,8,4,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,1.81888537\r
-07/04/2020,7,4,2020,70,3,Iraq,IQ,IRQ,39309789,Asia,1.94608015\r
-06/04/2020,6,4,2020,83,5,Iraq,IQ,IRQ,39309789,Asia,1.85195601\r
-05/04/2020,5,4,2020,106,2,Iraq,IQ,IRQ,39309789,Asia,1.68914669\r
-04/04/2020,4,4,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,1.47291556\r
-03/04/2020,3,4,2020,78,4,Iraq,IQ,IRQ,39309789,Asia,1.51361789\r
-02/04/2020,2,4,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,1.34826468\r
-01/04/2020,1,4,2020,64,4,Iraq,IQ,IRQ,39309789,Asia,1.37370363\r
-31/03/2020,31,3,2020,83,4,Iraq,IQ,IRQ,39309789,Asia,1.28721118\r
-30/03/2020,30,3,2020,41,0,Iraq,IQ,IRQ,39309789,Asia,1.07606785\r
-29/03/2020,29,3,2020,48,2,Iraq,IQ,IRQ,39309789,Asia,1.07098006\r
-28/03/2020,28,3,2020,76,4,Iraq,IQ,IRQ,39309789,Asia,0.94887307\r
-27/03/2020,27,3,2020,36,7,Iraq,IQ,IRQ,39309789,Asia,0.78351985\r
-26/03/2020,26,3,2020,30,2,Iraq,IQ,IRQ,39309789,Asia,0.70211519\r
-25/03/2020,25,3,2020,50,4,Iraq,IQ,IRQ,39309789,Asia,0.64869338\r
-24/03/2020,24,3,2020,33,3,Iraq,IQ,IRQ,39309789,Asia,0.5214986\r
-23/03/2020,23,3,2020,19,3,Iraq,IQ,IRQ,39309789,Asia,0.45535732\r
-22/03/2020,22,3,2020,21,3,Iraq,IQ,IRQ,39309789,Asia,0.44772563\r
-21/03/2020,21,3,2020,16,2,Iraq,IQ,IRQ,39309789,Asia,0.41211109\r
-20/03/2020,20,3,2020,13,0,Iraq,IQ,IRQ,39309789,Asia,0.38412824\r
-19/03/2020,19,3,2020,10,1,Iraq,IQ,IRQ,39309789,Asia,0.36377707\r
-18/03/2020,18,3,2020,30,2,Iraq,IQ,IRQ,39309789,Asia,0.34342591\r
-17/03/2020,17,3,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0.28237241\r
-16/03/2020,16,3,2020,39,0,Iraq,IQ,IRQ,39309789,Asia,0.29763579\r
-15/03/2020,15,3,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0.20096775\r
-14/03/2020,14,3,2020,11,1,Iraq,IQ,IRQ,39309789,Asia,0.20351165\r
-13/03/2020,13,3,2020,4,0,Iraq,IQ,IRQ,39309789,Asia,0.1755288\r
-12/03/2020,12,3,2020,9,2,Iraq,IQ,IRQ,39309789,Asia,0.1755288\r
-11/03/2020,11,3,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0.15517763\r
-09/03/2020,9,3,2020,7,4,Iraq,IQ,IRQ,39309789,Asia,0.15517763\r
-08/03/2020,8,3,2020,16,0,Iraq,IQ,IRQ,39309789,Asia,0.13737036\r
-06/03/2020,6,3,2020,7,2,Iraq,IQ,IRQ,39309789,Asia,0.09666803\r
-05/03/2020,5,3,2020,5,0,Iraq,IQ,IRQ,39309789,Asia,0.07886076\r
-04/03/2020,4,3,2020,5,0,Iraq,IQ,IRQ,39309789,Asia,0.06614129\r
-03/03/2020,3,3,2020,2,0,Iraq,IQ,IRQ,39309789,Asia,0.05342181\r
-02/03/2020,2,3,2020,6,0,Iraq,IQ,IRQ,39309789,Asia,0.04833402\r
-01/03/2020,1,3,2020,6,0,Iraq,IQ,IRQ,39309789,Asia,0.03307064\r
-29/02/2020,29,2,2020,1,0,Iraq,IQ,IRQ,39309789,Asia,0.01780727\r
-28/02/2020,28,2,2020,1,0,Iraq,IQ,IRQ,39309789,Asia,0.01526337\r
-27/02/2020,27,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0.01271948\r
-26/02/2020,26,2,2020,4,0,Iraq,IQ,IRQ,39309789,Asia,0.01271948\r
-25/02/2020,25,2,2020,1,0,Iraq,IQ,IRQ,39309789,Asia,0.0025439\r
-24/02/2020,24,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-23/02/2020,23,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-22/02/2020,22,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-21/02/2020,21,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-20/02/2020,20,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-19/02/2020,19,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-18/02/2020,18,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-17/02/2020,17,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-16/02/2020,16,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-15/02/2020,15,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-14/02/2020,14,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-13/02/2020,13,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-12/02/2020,12,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-11/02/2020,11,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-10/02/2020,10,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-09/02/2020,9,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-08/02/2020,8,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-07/02/2020,7,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-06/02/2020,6,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-05/02/2020,5,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-04/02/2020,4,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-03/02/2020,3,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-02/02/2020,2,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-01/02/2020,1,2,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-31/01/2020,31,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-30/01/2020,30,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-29/01/2020,29,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-28/01/2020,28,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-27/01/2020,27,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-26/01/2020,26,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-25/01/2020,25,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-24/01/2020,24,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-23/01/2020,23,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-22/01/2020,22,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-21/01/2020,21,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-20/01/2020,20,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-19/01/2020,19,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-18/01/2020,18,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-17/01/2020,17,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-16/01/2020,16,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-15/01/2020,15,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-14/01/2020,14,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-13/01/2020,13,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,0\r
-12/01/2020,12,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,\r
-11/01/2020,11,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,\r
-10/01/2020,10,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,\r
-09/01/2020,9,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,\r
-08/01/2020,8,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,\r
-07/01/2020,7,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,\r
-06/01/2020,6,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,\r
-05/01/2020,5,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,\r
-04/01/2020,4,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,\r
-03/01/2020,3,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,\r
-02/01/2020,2,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,\r
-01/01/2020,1,1,2020,0,0,Iraq,IQ,IRQ,39309789,Asia,\r
-31/12/2019,31,12,2019,0,0,Iraq,IQ,IRQ,39309789,Asia,\r
-19/08/2020,19,8,2020,186,1,Ireland,IE,IRL,4904240,Europe,25.40658695\r
-18/08/2020,18,8,2020,56,0,Ireland,IE,IRL,4904240,Europe,22.53152374\r
-17/08/2020,17,8,2020,66,0,Ireland,IE,IRL,4904240,Europe,22.32761855\r
-16/08/2020,16,8,2020,196,0,Ireland,IE,IRL,4904240,Europe,22.0625418\r
-15/08/2020,15,8,2020,66,0,Ireland,IE,IRL,4904240,Europe,18.96318288\r
-14/08/2020,14,8,2020,91,0,Ireland,IE,IRL,4904240,Europe,18.39224834\r
-13/08/2020,13,8,2020,37,1,Ireland,IE,IRL,4904240,Europe,18.26990522\r
-12/08/2020,12,8,2020,33,1,Ireland,IE,IRL,4904240,Europe,17.78053276\r
-11/08/2020,11,8,2020,56,0,Ireland,IE,IRL,4904240,Europe,17.86209484\r
-10/08/2020,10,8,2020,68,0,Ireland,IE,IRL,4904240,Europe,16.94452148\r
-09/08/2020,9,8,2020,174,0,Ireland,IE,IRL,4904240,Europe,15.8026524\r
-08/08/2020,8,8,2020,98,4,Ireland,IE,IRL,4904240,Europe,12.74407452\r
-07/08/2020,7,8,2020,69,5,Ireland,IE,IRL,4904240,Europe,11.1332235\r
-06/08/2020,6,8,2020,50,0,Ireland,IE,IRL,4904240,Europe,9.8690113\r
-05/08/2020,5,8,2020,45,0,Ireland,IE,IRL,4904240,Europe,9.19612417\r
-04/08/2020,4,8,2020,46,0,Ireland,IE,IRL,4904240,Europe,9.0126095\r
-03/08/2020,3,8,2020,53,0,Ireland,IE,IRL,4904240,Europe,8.19698873\r
-02/08/2020,2,8,2020,44,0,Ireland,IE,IRL,4904240,Europe,7.3201964\r
-01/08/2020,1,8,2020,38,0,Ireland,IE,IRL,4904240,Europe,6.83082394\r
-31/07/2020,31,7,2020,85,0,Ireland,IE,IRL,4904240,Europe,6.70848082\r
-30/07/2020,30,7,2020,13,0,Ireland,IE,IRL,4904240,Europe,5.28114448\r
-29/07/2020,29,7,2020,37,0,Ireland,IE,IRL,4904240,Europe,5.28114448\r
-28/07/2020,28,7,2020,11,0,Ireland,IE,IRL,4904240,Europe,5.17919188\r
-27/07/2020,27,7,2020,12,0,Ireland,IE,IRL,4904240,Europe,5.15880136\r
-26/07/2020,26,7,2020,24,0,Ireland,IE,IRL,4904240,Europe,5.26075396\r
-25/07/2020,25,7,2020,19,0,Ireland,IE,IRL,4904240,Europe,5.21997292\r
-24/07/2020,24,7,2020,7,9,Ireland,IE,IRL,4904240,Europe,5.32192552\r
-23/07/2020,23,7,2020,17,1,Ireland,IE,IRL,4904240,Europe,5.64817383\r
-22/07/2020,22,7,2020,36,0,Ireland,IE,IRL,4904240,Europe,5.38309708\r
-21/07/2020,21,7,2020,6,0,Ireland,IE,IRL,4904240,Europe,4.79177202\r
-20/07/2020,20,7,2020,10,0,Ireland,IE,IRL,4904240,Europe,4.75099098\r
-19/07/2020,19,7,2020,20,1,Ireland,IE,IRL,4904240,Europe,4.91411513\r
-18/07/2020,18,7,2020,32,3,Ireland,IE,IRL,4904240,Europe,4.73060046\r
-17/07/2020,17,7,2020,15,1,Ireland,IE,IRL,4904240,Europe,4.26161852\r
-16/07/2020,16,7,2020,13,2,Ireland,IE,IRL,4904240,Europe,4.20044696\r
-15/07/2020,15,7,2020,32,0,Ireland,IE,IRL,4904240,Europe,4.01693229\r
-14/07/2020,14,7,2020,10,0,Ireland,IE,IRL,4904240,Europe,3.58873138\r
-13/07/2020,13,7,2020,17,0,Ireland,IE,IRL,4904240,Europe,3.85380813\r
-12/07/2020,12,7,2020,22,2,Ireland,IE,IRL,4904240,Europe,3.54795035\r
-11/07/2020,11,7,2020,24,1,Ireland,IE,IRL,4904240,Europe,3.56834086\r
-10/07/2020,10,7,2020,23,0,Ireland,IE,IRL,4904240,Europe,3.26248308\r
-09/07/2020,9,7,2020,4,0,Ireland,IE,IRL,4904240,Europe,2.97701581\r
-08/07/2020,8,7,2020,7,2,Ireland,IE,IRL,4904240,Europe,2.99740633\r
-07/07/2020,7,7,2020,4,0,Ireland,IE,IRL,4904240,Europe,3.01779685\r
-06/07/2020,6,7,2020,18,0,Ireland,IE,IRL,4904240,Europe,3.01779685\r
-05/07/2020,5,7,2020,11,1,Ireland,IE,IRL,4904240,Europe,2.7527201\r
-04/07/2020,4,7,2020,9,2,Ireland,IE,IRL,4904240,Europe,2.6507675\r
-03/07/2020,3,7,2020,12,0,Ireland,IE,IRL,4904240,Europe,2.73232958\r
-02/07/2020,2,7,2020,4,2,Ireland,IE,IRL,4904240,Europe,2.77311061\r
-01/07/2020,1,7,2020,11,1,Ireland,IE,IRL,4904240,Europe,2.83428217\r
-30/06/2020,30,6,2020,23,0,Ireland,IE,IRL,4904240,Europe,2.87506321\r
-29/06/2020,29,6,2020,2,1,Ireland,IE,IRL,4904240,Europe,2.77311061\r
-28/06/2020,28,6,2020,23,4,Ireland,IE,IRL,4904240,Europe,2.89545373\r
-27/06/2020,27,6,2020,9,3,Ireland,IE,IRL,4904240,Europe,3.34404515\r
-26/06/2020,26,6,2020,9,1,Ireland,IE,IRL,4904240,Europe,3.40521671\r
-25/06/2020,25,6,2020,5,6,Ireland,IE,IRL,4904240,Europe,3.36443567\r
-24/06/2020,24,6,2020,8,3,Ireland,IE,IRL,4904240,Europe,3.58873138\r
-23/06/2020,23,6,2020,4,2,Ireland,IE,IRL,4904240,Europe,3.58873138\r
-22/06/2020,22,6,2020,5,0,Ireland,IE,IRL,4904240,Europe,3.62951242\r
-21/06/2020,21,6,2020,6,1,Ireland,IE,IRL,4904240,Europe,3.89458917\r
-20/06/2020,20,6,2020,13,0,Ireland,IE,IRL,4904240,Europe,4.18005644\r
-19/06/2020,19,6,2020,14,4,Ireland,IE,IRL,4904240,Europe,4.34318059\r
-18/06/2020,18,6,2020,7,1,Ireland,IE,IRL,4904240,Europe,4.68981942\r
-17/06/2020,17,6,2020,13,3,Ireland,IE,IRL,4904240,Europe,5.46465915\r
-16/06/2020,16,6,2020,18,0,Ireland,IE,IRL,4904240,Europe,5.28114448\r
-15/06/2020,15,6,2020,8,1,Ireland,IE,IRL,4904240,Europe,6.38223252\r
-14/06/2020,14,6,2020,45,0,Ireland,IE,IRL,4904240,Europe,7.46293004\r
-13/06/2020,13,6,2020,12,2,Ireland,IE,IRL,4904240,Europe,7.62605419\r
-12/06/2020,12,6,2020,7,8,Ireland,IE,IRL,4904240,Europe,8.09503613\r
-11/06/2020,11,6,2020,16,4,Ireland,IE,IRL,4904240,Europe,8.72714223\r
-10/06/2020,10,6,2020,8,8,Ireland,IE,IRL,4904240,Europe,9.78744923\r
-09/06/2020,9,6,2020,6,4,Ireland,IE,IRL,4904240,Europe,10.37877429\r
-08/06/2020,8,6,2020,18,9,Ireland,IE,IRL,4904240,Europe,11.4594718\r
-07/06/2020,7,6,2020,20,0,Ireland,IE,IRL,4904240,Europe,12.25470205\r
-06/06/2020,6,6,2020,21,6,Ireland,IE,IRL,4904240,Europe,13.39657113\r
-05/06/2020,5,6,2020,31,5,Ireland,IE,IRL,4904240,Europe,15.31327994\r
-04/06/2020,4,6,2020,45,1,Ireland,IE,IRL,4904240,Europe,16.2308533\r
-03/06/2020,3,6,2020,4,8,Ireland,IE,IRL,4904240,Europe,16.61827317\r
-02/06/2020,2,6,2020,72,0,Ireland,IE,IRL,4904240,Europe,17.57662757\r
-01/06/2020,1,6,2020,61,0,Ireland,IE,IRL,4904240,Europe,17.90287588\r
-31/05/2020,31,5,2020,53,5,Ireland,IE,IRL,4904240,Europe,17.96404744\r
-30/05/2020,30,5,2020,35,6,Ireland,IE,IRL,4904240,Europe,18.75927769\r
-29/05/2020,29,5,2020,38,8,Ireland,IE,IRL,4904240,Europe,20.67598649\r
-28/05/2020,28,5,2020,68,16,Ireland,IE,IRL,4904240,Europe,28.58750795\r
-27/05/2020,27,5,2020,37,9,Ireland,IE,IRL,4904240,Europe,30.4430452\r
-26/05/2020,26,5,2020,59,0,Ireland,IE,IRL,4904240,Europe,31.87038155\r
-25/05/2020,25,5,2020,57,2,Ireland,IE,IRL,4904240,Europe,33.50162309\r
-24/05/2020,24,5,2020,76,12,Ireland,IE,IRL,4904240,Europe,37.15152603\r
-23/05/2020,23,5,2020,115,9,Ireland,IE,IRL,4904240,Europe,40.06737028\r
-22/05/2020,22,5,2020,76,12,Ireland,IE,IRL,4904240,Europe,40.90338156\r
-21/05/2020,21,5,2020,64,10,Ireland,IE,IRL,4904240,Europe,42.14720324\r
-20/05/2020,20,5,2020,51,14,Ireland,IE,IRL,4904240,Europe,46.2456976\r
-19/05/2020,19,5,2020,88,4,Ireland,IE,IRL,4904240,Europe,50.52770664\r
-18/05/2020,18,5,2020,64,10,Ireland,IE,IRL,4904240,Europe,53.1376931\r
-17/05/2020,17,5,2020,92,15,Ireland,IE,IRL,4904240,Europe,58.56157121\r
-16/05/2020,16,5,2020,129,12,Ireland,IE,IRL,4904240,Europe,63.67959154\r
-15/05/2020,15,5,2020,426,9,Ireland,IE,IRL,4904240,Europe,65.55551931\r
-14/05/2020,14,5,2020,159,9,Ireland,IE,IRL,4904240,Europe,64.18935452\r
-13/05/2020,13,5,2020,107,21,Ireland,IE,IRL,4904240,Europe,68.61409719\r
-12/05/2020,12,5,2020,139,9,Ireland,IE,IRL,4904240,Europe,71.10174053\r
-11/05/2020,11,5,2020,236,12,Ireland,IE,IRL,4904240,Europe,76.13819878\r
-10/05/2020,10,5,2020,219,17,Ireland,IE,IRL,4904240,Europe,85.61979022\r
-09/05/2020,9,5,2020,156,26,Ireland,IE,IRL,4904240,Europe,88.84149226\r
-08/05/2020,8,5,2020,137,28,Ireland,IE,IRL,4904240,Europe,97.42590085\r
-07/05/2020,7,5,2020,265,36,Ireland,IE,IRL,4904240,Europe,113.71792571\r
-06/05/2020,6,5,2020,261,20,Ireland,IE,IRL,4904240,Europe,121.18085575\r
-05/05/2020,5,5,2020,216,16,Ireland,IE,IRL,4904240,Europe,123.77045169\r
-04/05/2020,4,5,2020,330,38,Ireland,IE,IRL,4904240,Europe,127.54269775\r
-03/05/2020,3,5,2020,343,0,Ireland,IE,IRL,4904240,Europe,130.86635238\r
-02/05/2020,2,5,2020,221,33,Ireland,IE,IRL,4904240,Europe,139.73622824\r
-01/05/2020,1,5,2020,359,42,Ireland,IE,IRL,4904240,Europe,149.68680162\r
-30/04/2020,30,4,2020,376,31,Ireland,IE,IRL,4904240,Europe,157.12934114\r
-29/04/2020,29,4,2020,229,57,Ireland,IE,IRL,4904240,Europe,171.23958044\r
-28/04/2020,28,4,2020,386,15,Ireland,IE,IRL,4904240,Europe,183.53506354\r
-27/04/2020,27,4,2020,701,24,Ireland,IE,IRL,4904240,Europe,195.89171819\r
-26/04/2020,26,4,2020,377,234,Ireland,IE,IRL,4904240,Europe,196.42187169\r
-25/04/2020,25,4,2020,577,35,Ireland,IE,IRL,4904240,Europe,205.84229157\r
-24/04/2020,24,4,2020,936,25,Ireland,IE,IRL,4904240,Europe,208.26876336\r
-23/04/2020,23,4,2020,631,39,Ireland,IE,IRL,4904240,Europe,213.01975434\r
-22/04/2020,22,4,2020,388,43,Ireland,IE,IRL,4904240,Europe,210.65445411\r
-21/04/2020,21,4,2020,401,77,Ireland,IE,IRL,4904240,Europe,209.77766178\r
-20/04/2020,20,4,2020,493,39,Ireland,IE,IRL,4904240,Europe,206.75986493\r
-19/04/2020,19,4,2020,778,41,Ireland,IE,IRL,4904240,Europe,207.0453322\r
-18/04/2020,18,4,2020,709,44,Ireland,IE,IRL,4904240,Europe,197.93077011\r
-17/04/2020,17,4,2020,724,42,Ireland,IE,IRL,4904240,Europe,192.11947213\r
-16/04/2020,16,4,2020,1068,38,Ireland,IE,IRL,4904240,Europe,185.55372494\r
-15/04/2020,15,4,2020,832,41,Ireland,IE,IRL,4904240,Europe,168.09944048\r
-14/04/2020,14,4,2020,992,31,Ireland,IE,IRL,4904240,Europe,157.76144724\r
-13/04/2020,13,4,2020,727,14,Ireland,IE,IRL,4904240,Europe,143.54925534\r
-12/04/2020,12,4,2020,839,33,Ireland,IE,IRL,4904240,Europe,132.80345171\r
-11/04/2020,11,4,2020,696,24,Ireland,IE,IRL,4904240,Europe,121.69061873\r
-10/04/2020,10,4,2020,1169,28,Ireland,IE,IRL,4904240,Europe,113.65675416\r
-09/04/2020,9,4,2020,515,25,Ireland,IE,IRL,4904240,Europe,95.01981958\r
-08/04/2020,8,4,2020,345,36,Ireland,IE,IRL,4904240,Europe,89.3104742\r
-07/04/2020,7,4,2020,253,16,Ireland,IE,IRL,4904240,Europe,86.43541099\r
-06/04/2020,6,4,2020,507,21,Ireland,IE,IRL,4904240,Europe,85.74213334\r
-05/04/2020,5,4,2020,331,17,Ireland,IE,IRL,4904240,Europe,77.87139292\r
-04/04/2020,4,4,2020,424,22,Ireland,IE,IRL,4904240,Europe,73.20196401\r
-03/04/2020,3,4,2020,402,13,Ireland,IE,IRL,4904240,Europe,67.12558929\r
-02/04/2020,2,4,2020,212,14,Ireland,IE,IRL,4904240,Europe,62.82318973\r
-01/04/2020,1,4,2020,325,17,Ireland,IE,IRL,4904240,Europe,60.00929808\r
-31/03/2020,31,3,2020,295,8,Ireland,IE,IRL,4904240,Europe,54.78932516\r
-30/03/2020,30,3,2020,200,10,Ireland,IE,IRL,4904240,Europe,49.87521002\r
-29/03/2020,29,3,2020,294,14,Ireland,IE,IRL,4904240,Europe,46.61272695\r
-28/03/2020,28,3,2020,302,3,Ireland,IE,IRL,4904240,Europe,41.39275403\r
-27/03/2020,27,3,2020,255,10,Ireland,IE,IRL,4904240,Europe,35.66301812\r
-26/03/2020,26,3,2020,235,2,Ireland,IE,IRL,4904240,Europe,31.01397974\r
-25/03/2020,25,3,2020,204,1,Ireland,IE,IRL,4904240,Europe,26.38533188\r
-24/03/2020,24,3,2020,219,2,Ireland,IE,IRL,4904240,Europe,22.51113322\r
-23/03/2020,23,3,2020,121,1,Ireland,IE,IRL,4904240,Europe,18.08639055\r
-22/03/2020,22,3,2020,102,0,Ireland,IE,IRL,4904240,Europe,15.63952824\r
-21/03/2020,21,3,2020,126,0,Ireland,IE,IRL,4904240,Europe,13.66164788\r
-20/03/2020,20,3,2020,191,1,Ireland,IE,IRL,4904240,Europe,11.23517609\r
-19/03/2020,19,3,2020,74,0,Ireland,IE,IRL,4904240,Europe,7.422149\r
-18/03/2020,18,3,2020,69,0,Ireland,IE,IRL,4904240,Europe,5.93364109\r
-17/03/2020,17,3,2020,54,0,Ireland,IE,IRL,4904240,Europe,4.52669527\r
-16/03/2020,16,3,2020,40,0,Ireland,IE,IRL,4904240,Europe,3.44599775\r
-15/03/2020,15,3,2020,38,1,Ireland,IE,IRL,4904240,Europe,2.63037698\r
-14/03/2020,14,3,2020,21,0,Ireland,IE,IRL,4904240,Europe,1.85553725\r
-13/03/2020,13,3,2020,27,0,Ireland,IE,IRL,4904240,Europe,1.42733635\r
-12/03/2020,12,3,2020,8,1,Ireland,IE,IRL,4904240,Europe,0.87679233\r
-11/03/2020,11,3,2020,14,0,Ireland,IE,IRL,4904240,Europe,0.71366817\r
-09/03/2020,9,3,2020,2,0,Ireland,IE,IRL,4904240,Europe,0.4282009\r
-08/03/2020,8,3,2020,1,0,Ireland,IE,IRL,4904240,Europe,0.38741987\r
-07/03/2020,7,3,2020,5,0,Ireland,IE,IRL,4904240,Europe,0.36702935\r
-06/03/2020,6,3,2020,7,0,Ireland,IE,IRL,4904240,Europe,0.26507675\r
-05/03/2020,5,3,2020,4,0,Ireland,IE,IRL,4904240,Europe,0.12234312\r
-04/03/2020,4,3,2020,1,0,Ireland,IE,IRL,4904240,Europe,0.04078104\r
-02/03/2020,2,3,2020,0,0,Ireland,IE,IRL,4904240,Europe,0.02039052\r
-01/03/2020,1,3,2020,1,0,Ireland,IE,IRL,4904240,Europe,0.02039052\r
-29/02/2020,29,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
-28/02/2020,28,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
-27/02/2020,27,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
-26/02/2020,26,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
-25/02/2020,25,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
-24/02/2020,24,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
-23/02/2020,23,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
-22/02/2020,22,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
-21/02/2020,21,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
-20/02/2020,20,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
-19/02/2020,19,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
-18/02/2020,18,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
-17/02/2020,17,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
-16/02/2020,16,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
-15/02/2020,15,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
-14/02/2020,14,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
-13/02/2020,13,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
-12/02/2020,12,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
-11/02/2020,11,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
-10/02/2020,10,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
-09/02/2020,9,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
-08/02/2020,8,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
-07/02/2020,7,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
-06/02/2020,6,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
-05/02/2020,5,2,2020,0,0,Ireland,IE,IRL,4904240,Europe,0\r
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-05/08/2020,5,8,2020,1739,15,Israel,IL,ISR,8519373,Asia,265.27773816\r
-04/08/2020,4,8,2020,1878,10,Israel,IL,ISR,8519373,Asia,272.6374347\r
-03/08/2020,3,8,2020,742,9,Israel,IL,ISR,8519373,Asia,266.87409977\r
-02/08/2020,2,8,2020,1313,15,Israel,IL,ISR,8519373,Asia,269.01040722\r
-01/08/2020,1,8,2020,591,9,Israel,IL,ISR,8519373,Asia,275.97101336\r
-31/07/2020,31,7,2020,1823,12,Israel,IL,ISR,8519373,Asia,285.46701735\r
-30/07/2020,30,7,2020,2001,5,Israel,IL,ISR,8519373,Asia,279.85627581\r
-29/07/2020,29,7,2020,2097,12,Israel,IL,ISR,8519373,Asia,283.99977322\r
-28/07/2020,28,7,2020,2502,4,Israel,IL,ISR,8519373,Asia,279.66846856\r
-27/07/2020,27,7,2020,1278,13,Israel,IL,ISR,8519373,Asia,273.32997393\r
-26/07/2020,26,7,2020,1203,9,Israel,IL,ISR,8519373,Asia,272.49657927\r
-25/07/2020,25,7,2020,1493,6,Israel,IL,ISR,8519373,Asia,272.42615155\r
-24/07/2020,24,7,2020,1897,12,Israel,IL,ISR,8519373,Asia,271.81577799\r
-23/07/2020,23,7,2020,2043,5,Israel,IL,ISR,8519373,Asia,264.43260555\r
-22/07/2020,22,7,2020,2366,10,Israel,IL,ISR,8519373,Asia,256.12213481\r
-21/07/2020,21,7,2020,1387,6,Israel,IL,ISR,8519373,Asia,240.5106573\r
-20/07/2020,20,7,2020,924,8,Israel,IL,ISR,8519373,Asia,238.64432277\r
-19/07/2020,19,7,2020,1906,9,Israel,IL,ISR,8519373,Asia,237.04796116\r
-18/07/2020,18,7,2020,1400,8,Israel,IL,ISR,8519373,Asia,227.76324032\r
-17/07/2020,17,7,2020,1345,4,Israel,IL,ISR,8519373,Asia,217.351676\r
-16/07/2020,16,7,2020,2354,9,Israel,IL,ISR,8519373,Asia,216.64739882\r
-15/07/2020,15,7,2020,1728,6,Israel,IL,ISR,8519373,Asia,200.90680382\r
-14/07/2020,14,7,2020,1962,3,Israel,IL,ISR,8519373,Asia,190.04919728\r
-13/07/2020,13,7,2020,1207,8,Israel,IL,ISR,8519373,Asia,175.07156923\r
-12/07/2020,12,7,2020,1197,3,Israel,IL,ISR,8519373,Asia,164.82433625\r
-11/07/2020,11,7,2020,1441,3,Israel,IL,ISR,8519373,Asia,158.06327531\r
-10/07/2020,10,7,2020,1268,4,Israel,IL,ISR,8519373,Asia,145.84406622\r
-09/07/2020,9,7,2020,1335,2,Israel,IL,ISR,8519373,Asia,135.13905307\r
-08/07/2020,8,7,2020,1036,4,Israel,IL,ISR,8519373,Asia,125.7134768\r
-07/07/2020,7,7,2020,1228,7,Israel,IL,ISR,8519373,Asia,118.60027727\r
-06/07/2020,6,7,2020,788,1,Israel,IL,ISR,8519373,Asia,107.75440869\r
-05/07/2020,5,7,2020,1115,4,Israel,IL,ISR,8519373,Asia,100.2069049\r
-04/07/2020,4,7,2020,513,1,Israel,IL,ISR,8519373,Asia,90.57004547\r
-03/07/2020,3,7,2020,1285,3,Israel,IL,ISR,8519373,Asia,88.10507534\r
-02/07/2020,2,7,2020,1013,2,Israel,IL,ISR,8519373,Asia,74.68859504\r
-01/07/2020,1,7,2020,803,1,Israel,IL,ISR,8519373,Asia,65.81470256\r
-30/06/2020,30,6,2020,686,1,Israel,IL,ISR,8519373,Asia,59.89877424\r
-29/06/2020,29,6,2020,334,1,Israel,IL,ISR,8519373,Asia,54.39367428\r
-28/06/2020,28,6,2020,621,3,Israel,IL,ISR,8519373,Asia,51.79958666\r
-27/06/2020,27,6,2020,400,5,Israel,IL,ISR,8519373,Asia,46.05972763\r
-26/06/2020,26,6,2020,356,1,Israel,IL,ISR,8519373,Asia,43.41868821\r
-25/06/2020,25,6,2020,532,0,Israel,IL,ISR,8519373,Asia,43.30130868\r
-24/06/2020,24,6,2020,430,1,Israel,IL,ISR,8519373,Asia,38.07791958\r
-23/06/2020,23,6,2020,304,1,Israel,IL,ISR,8519373,Asia,35.13169338\r
-22/06/2020,22,6,2020,145,1,Israel,IL,ISR,8519373,Asia,33.60575948\r
-21/06/2020,21,6,2020,294,1,Israel,IL,ISR,8519373,Asia,33.4531661\r
-20/06/2020,20,6,2020,303,1,Israel,IL,ISR,8519373,Asia,30.90603029\r
-19/06/2020,19,6,2020,142,0,Israel,IL,ISR,8519373,Asia,29.03969576\r
-18/06/2020,18,6,2020,257,0,Israel,IL,ISR,8519373,Asia,28.93405418\r
-17/06/2020,17,6,2020,299,1,Israel,IL,ISR,8519373,Asia,26.93860217\r
-16/06/2020,16,6,2020,217,0,Israel,IL,ISR,8519373,Asia,24.87272244\r
-15/06/2020,15,6,2020,113,2,Israel,IL,ISR,8519373,Asia,24.06280368\r
-14/06/2020,14,6,2020,132,0,Israel,IL,ISR,8519373,Asia,23.42895422\r
-13/06/2020,13,6,2020,175,0,Israel,IL,ISR,8519373,Asia,22.17299325\r
-12/06/2020,12,6,2020,346,1,Israel,IL,ISR,8519373,Asia,21.46871607\r
-11/06/2020,11,6,2020,87,0,Israel,IL,ISR,8519373,Asia,18.33468261\r
-10/06/2020,10,6,2020,179,1,Israel,IL,ISR,8519373,Asia,17.73604701\r
-09/06/2020,9,6,2020,174,0,Israel,IL,ISR,8519373,Asia,15.90492634\r
-08/06/2020,8,6,2020,132,1,Israel,IL,ISR,8519373,Asia,14.02685385\r
-07/06/2020,7,6,2020,77,5,Israel,IL,ISR,8519373,Asia,12.82958265\r
-06/06/2020,6,6,2020,144,1,Israel,IL,ISR,8519373,Asia,11.92576026\r
-05/06/2020,5,6,2020,133,0,Israel,IL,ISR,8519373,Asia,10.23549503\r
-04/06/2020,4,6,2020,87,1,Israel,IL,ISR,8519373,Asia,8.90910634\r
-03/06/2020,3,6,2020,123,3,Israel,IL,ISR,8519373,Asia,8.12266349\r
-02/06/2020,2,6,2020,148,2,Israel,IL,ISR,8519373,Asia,7.0192959\r
-01/06/2020,1,6,2020,59,1,Israel,IL,ISR,8519373,Asia,5.32903067\r
-31/05/2020,31,5,2020,25,0,Israel,IL,ISR,8519373,Asia,4.74213302\r
-30/05/2020,30,5,2020,115,0,Israel,IL,ISR,8519373,Asia,4.6717053\r
-29/05/2020,29,5,2020,79,3,Israel,IL,ISR,8519373,Asia,3.43922023\r
-28/05/2020,28,5,2020,36,0,Israel,IL,ISR,8519373,Asia,2.87579849\r
-27/05/2020,27,5,2020,23,0,Israel,IL,ISR,8519373,Asia,2.67625329\r
-26/05/2020,26,5,2020,14,1,Israel,IL,ISR,8519373,Asia,2.67625329\r
-25/05/2020,25,5,2020,30,1,Israel,IL,ISR,8519373,Asia,2.85232258\r
-24/05/2020,24,5,2020,0,0,Israel,IL,ISR,8519373,Asia,2.77015691\r
-23/05/2020,23,5,2020,0,0,Israel,IL,ISR,8519373,Asia,2.98144007\r
-22/05/2020,22,5,2020,20,0,Israel,IL,ISR,8519373,Asia,3.62702748\r
-21/05/2020,21,5,2020,20,2,Israel,IL,ISR,8519373,Asia,4.22566309\r
-20/05/2020,20,5,2020,29,5,Israel,IL,ISR,8519373,Asia,4.23740104\r
-19/05/2020,19,5,2020,4,0,Israel,IL,ISR,8519373,Asia,4.40173238\r
-18/05/2020,18,5,2020,9,4,Israel,IL,ISR,8519373,Asia,4.80082278\r
-17/05/2020,17,5,2020,19,2,Israel,IL,ISR,8519373,Asia,4.96515413\r
-16/05/2020,16,5,2020,10,1,Israel,IL,ISR,8519373,Asia,5.72812107\r
-15/05/2020,15,5,2020,31,1,Israel,IL,ISR,8519373,Asia,7.43012426\r
-14/05/2020,14,5,2020,19,4,Israel,IL,ISR,8519373,Asia,8.38089845\r
-13/05/2020,13,5,2020,23,2,Israel,IL,ISR,8519373,Asia,11.03367584\r
-12/05/2020,12,5,2020,29,6,Israel,IL,ISR,8519373,Asia,12.20747114\r
-11/05/2020,11,5,2020,23,5,Israel,IL,ISR,8519373,Asia,12.6652513\r
-10/05/2020,10,5,2020,18,2,Israel,IL,ISR,8519373,Asia,13.56907369\r
-09/05/2020,9,5,2020,55,5,Israel,IL,ISR,8519373,Asia,16.17489926\r
-08/05/2020,8,5,2020,71,1,Israel,IL,ISR,8519373,Asia,17.59519157\r
-07/05/2020,7,5,2020,21,1,Israel,IL,ISR,8519373,Asia,20.16580328\r
-06/05/2020,6,5,2020,43,3,Israel,IL,ISR,8519373,Asia,27.54897573\r
-05/05/2020,5,5,2020,38,3,Israel,IL,ISR,8519373,Asia,29.73223499\r
-04/05/2020,4,5,2020,23,3,Israel,IL,ISR,8519373,Asia,31.89201834\r
-03/05/2020,3,5,2020,84,4,Israel,IL,ISR,8519373,Asia,34.27482281\r
-02/05/2020,2,5,2020,155,3,Israel,IL,ISR,8519373,Asia,36.61067546\r
-01/05/2020,1,5,2020,112,7,Israel,IL,ISR,8519373,Asia,37.42059422\r
-30/04/2020,30,4,2020,245,7,Israel,IL,ISR,8519373,Asia,39.1225974\r
-29/04/2020,29,4,2020,123,6,Israel,IL,ISR,8519373,Asia,41.58756754\r
-28/04/2020,28,4,2020,68,3,Israel,IL,ISR,8519373,Asia,45.5432577\r
-27/04/2020,27,4,2020,100,0,Israel,IL,ISR,8519373,Asia,49.92151418\r
-26/04/2020,26,4,2020,240,5,Israel,IL,ISR,8519373,Asia,53.46637599\r
-25/04/2020,25,4,2020,176,1,Israel,IL,ISR,8519373,Asia,54.58148152\r
-24/04/2020,24,4,2020,290,2,Israel,IL,ISR,8519373,Asia,57.68030112\r
-23/04/2020,23,4,2020,650,7,Israel,IL,ISR,8519373,Asia,60.89650025\r
-22/04/2020,22,4,2020,229,7,Israel,IL,ISR,8519373,Asia,55.09795146\r
-21/04/2020,21,4,2020,222,5,Israel,IL,ISR,8519373,Asia,56.44781605\r
-20/04/2020,20,4,2020,226,8,Israel,IL,ISR,8519373,Asia,59.40578021\r
-19/04/2020,19,4,2020,283,13,Israel,IL,ISR,8519373,Asia,61.58903948\r
-18/04/2020,18,4,2020,224,9,Israel,IL,ISR,8519373,Asia,65.19259105\r
-17/04/2020,17,4,2020,257,12,Israel,IL,ISR,8519373,Asia,76.36712232\r
-16/04/2020,16,4,2020,455,7,Israel,IL,ISR,8519373,Asia,81.10925534\r
-15/04/2020,15,4,2020,460,7,Israel,IL,ISR,8519373,Asia,83.691605\r
-14/04/2020,14,4,2020,441,13,Israel,IL,ISR,8519373,Asia,83.4920598\r
-13/04/2020,13,4,2020,402,2,Israel,IL,ISR,8519373,Asia,80.9683999\r
-12/04/2020,12,4,2020,335,6,Israel,IL,ISR,8519373,Asia,83.62117729\r
-11/04/2020,11,4,2020,440,9,Israel,IL,ISR,8519373,Asia,86.54392759\r
-10/04/2020,10,4,2020,564,15,Israel,IL,ISR,8519373,Asia,85.71053292\r
-09/04/2020,9,4,2020,156,6,Israel,IL,ISR,8519373,Asia,82.57649947\r
-08/04/2020,8,4,2020,344,8,Israel,IL,ISR,8519373,Asia,85.89834017\r
-07/04/2020,7,4,2020,474,8,Israel,IL,ISR,8519373,Asia,87.58860541\r
-06/04/2020,6,4,2020,412,3,Israel,IL,ISR,8519373,Asia,86.37959624\r
-05/04/2020,5,4,2020,590,7,Israel,IL,ISR,8519373,Asia,83.75029477\r
-04/04/2020,4,4,2020,1176,5,Israel,IL,ISR,8519373,Asia,78.83209246\r
-03/04/2020,3,4,2020,661,13,Israel,IL,ISR,8519373,Asia,65.43908806\r
-02/04/2020,2,4,2020,675,1,Israel,IL,ISR,8519373,Asia,60.54436166\r
-01/04/2020,1,4,2020,443,3,Israel,IL,ISR,8519373,Asia,52.69167109\r
-31/03/2020,31,3,2020,226,2,Israel,IL,ISR,8519373,Asia,49.45199606\r
-30/03/2020,30,3,2020,628,3,Israel,IL,ISR,8519373,Asia,46.91659821\r
-29/03/2020,29,3,2020,584,2,Israel,IL,ISR,8519373,Asia,40.39029633\r
-28/03/2020,28,3,2020,369,2,Israel,IL,ISR,8519373,Asia,34.26308485\r
-27/03/2020,27,3,2020,297,3,Israel,IL,ISR,8519373,Asia,30.16653925\r
-26/03/2020,26,3,2020,439,2,Israel,IL,ISR,8519373,Asia,26.84469855\r
-25/03/2020,25,3,2020,488,2,Israel,IL,ISR,8519373,Asia,21.83259261\r
-24/03/2020,24,3,2020,371,0,Israel,IL,ISR,8519373,Asia,16.46834808\r
-23/03/2020,23,3,2020,188,0,Israel,IL,ISR,8519373,Asia,12.27789885\r
-22/03/2020,22,3,2020,171,0,Israel,IL,ISR,8519373,Asia,10.14159141\r
-21/03/2020,21,3,2020,35,1,Israel,IL,ISR,8519373,Asia,8.15787735\r
-20/03/2020,20,3,2020,244,0,Israel,IL,ISR,8519373,Asia,7.7705249\r
-19/03/2020,19,3,2020,6,0,Israel,IL,ISR,8519373,Asia,4.96515413\r
-18/03/2020,18,3,2020,167,0,Israel,IL,ISR,8519373,Asia,4.92994027\r
-17/03/2020,17,3,2020,10,0,Israel,IL,ISR,8519373,Asia,2.96970211\r
-16/03/2020,16,3,2020,72,0,Israel,IL,ISR,8519373,Asia,2.89927439\r
-15/03/2020,15,3,2020,62,0,Israel,IL,ISR,8519373,Asia,2.06587973\r
-14/03/2020,14,3,2020,20,0,Israel,IL,ISR,8519373,Asia,1.33812664\r
-13/03/2020,13,3,2020,14,0,Israel,IL,ISR,8519373,Asia,1.10336758\r
-12/03/2020,12,3,2020,12,0,Israel,IL,ISR,8519373,Asia,0.93903624\r
-11/03/2020,11,3,2020,31,0,Israel,IL,ISR,8519373,Asia,0.80991876\r
-09/03/2020,9,3,2020,14,0,Israel,IL,ISR,8519373,Asia,0.44604221\r
-08/03/2020,8,3,2020,6,0,Israel,IL,ISR,8519373,Asia,0.29344883\r
-07/03/2020,7,3,2020,2,0,Israel,IL,ISR,8519373,Asia,0.22302111\r
-06/03/2020,6,3,2020,2,0,Israel,IL,ISR,8519373,Asia,0.1995452\r
-05/03/2020,5,3,2020,5,0,Israel,IL,ISR,8519373,Asia,0.1760693\r
-02/03/2020,2,3,2020,3,0,Israel,IL,ISR,8519373,Asia,0.11737953\r
-01/03/2020,1,3,2020,0,0,Israel,IL,ISR,8519373,Asia,0.08216567\r
-29/02/2020,29,2,2020,4,0,Israel,IL,ISR,8519373,Asia,0.08216567\r
-28/02/2020,28,2,2020,1,0,Israel,IL,ISR,8519373,Asia,0.03521386\r
-27/02/2020,27,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0.02347591\r
-26/02/2020,26,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0.02347591\r
-25/02/2020,25,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0.02347591\r
-24/02/2020,24,2,2020,1,0,Israel,IL,ISR,8519373,Asia,0.02347591\r
-23/02/2020,23,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0.01173795\r
-22/02/2020,22,2,2020,1,0,Israel,IL,ISR,8519373,Asia,0.01173795\r
-21/02/2020,21,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-20/02/2020,20,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-19/02/2020,19,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-18/02/2020,18,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-17/02/2020,17,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-16/02/2020,16,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-15/02/2020,15,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-14/02/2020,14,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-13/02/2020,13,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-12/02/2020,12,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-11/02/2020,11,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-10/02/2020,10,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-09/02/2020,9,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-08/02/2020,8,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-07/02/2020,7,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-06/02/2020,6,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-05/02/2020,5,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-04/02/2020,4,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-03/02/2020,3,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-02/02/2020,2,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-01/02/2020,1,2,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-31/01/2020,31,1,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-30/01/2020,30,1,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-29/01/2020,29,1,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-28/01/2020,28,1,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-27/01/2020,27,1,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-26/01/2020,26,1,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-25/01/2020,25,1,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-24/01/2020,24,1,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-23/01/2020,23,1,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-22/01/2020,22,1,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-21/01/2020,21,1,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-20/01/2020,20,1,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-19/01/2020,19,1,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-18/01/2020,18,1,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-17/01/2020,17,1,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-16/01/2020,16,1,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-15/01/2020,15,1,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-14/01/2020,14,1,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-13/01/2020,13,1,2020,0,0,Israel,IL,ISR,8519373,Asia,0\r
-12/01/2020,12,1,2020,0,0,Israel,IL,ISR,8519373,Asia,\r
-11/01/2020,11,1,2020,0,0,Israel,IL,ISR,8519373,Asia,\r
-10/01/2020,10,1,2020,0,0,Israel,IL,ISR,8519373,Asia,\r
-09/01/2020,9,1,2020,0,0,Israel,IL,ISR,8519373,Asia,\r
-08/01/2020,8,1,2020,0,0,Israel,IL,ISR,8519373,Asia,\r
-07/01/2020,7,1,2020,0,0,Israel,IL,ISR,8519373,Asia,\r
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-17/08/2020,17,8,2020,238,10,Japan,JP,JPN,126860299,Asia,13.30597526\r
-16/08/2020,16,8,2020,1137,3,Japan,JP,JPN,126860299,Asia,14.68781025\r
-15/08/2020,15,8,2020,2064,13,Japan,JP,JPN,126860299,Asia,15.13869993\r
-14/08/2020,14,8,2020,1069,10,Japan,JP,JPN,126860299,Asia,13.98309805\r
-13/08/2020,13,8,2020,932,4,Japan,JP,JPN,126860299,Asia,14.17701215\r
-12/08/2020,12,8,2020,1274,7,Japan,JP,JPN,126860299,Asia,14.32993627\r
-11/08/2020,11,8,2020,248,4,Japan,JP,JPN,126860299,Asia,14.38511508\r
-10/08/2020,10,8,2020,1207,7,Japan,JP,JPN,126860299,Asia,14.18962445\r
-09/08/2020,9,8,2020,1344,1,Japan,JP,JPN,126860299,Asia,13.71666324\r
-08/08/2020,8,8,2020,1624,6,Japan,JP,JPN,126860299,Asia,13.12703827\r
-07/08/2020,7,8,2020,1552,7,Japan,JP,JPN,126860299,Asia,12.50115294\r
-06/08/2020,6,8,2020,1134,4,Japan,JP,JPN,126860299,Asia,12.00848502\r
-05/08/2020,5,8,2020,1271,6,Japan,JP,JPN,126860299,Asia,11.6868714\r
-04/08/2020,4,8,2020,1786,5,Japan,JP,JPN,126860299,Asia,11.13193025\r
-03/08/2020,3,8,2020,1991,1,Japan,JP,JPN,126860299,Asia,10.22857435\r
-02/08/2020,2,8,2020,1709,4,Japan,JP,JPN,126860299,Asia,9.01700539\r
-01/08/2020,1,8,2020,598,1,Japan,JP,JPN,126860299,Asia,8.07187125\r
-31/07/2020,31,7,2020,1315,2,Japan,JP,JPN,126860299,Asia,8.11995564\r
-30/07/2020,30,7,2020,1126,3,Japan,JP,JPN,126860299,Asia,7.54294297\r
-29/07/2020,29,7,2020,1344,4,Japan,JP,JPN,126860299,Asia,6.95647107\r
-28/07/2020,28,7,2020,0,0,Japan,JP,JPN,126860299,Asia,6.12405935\r
-27/07/2020,27,7,2020,607,0,Japan,JP,JPN,126860299,Asia,6.40152992\r
-26/07/2020,26,7,2020,596,3,Japan,JP,JPN,126860299,Asia,6.21155717\r
-25/07/2020,25,7,2020,830,1,Japan,JP,JPN,126860299,Asia,6.03577326\r
-24/07/2020,24,7,2020,927,2,Japan,JP,JPN,126860299,Asia,5.70470041\r
-23/07/2020,23,7,2020,726,1,Japan,JP,JPN,126860299,Asia,5.24829285\r
-22/07/2020,22,7,2020,567,1,Japan,JP,JPN,126860299,Asia,4.83129872\r
-21/07/2020,21,7,2020,640,3,Japan,JP,JPN,126860299,Asia,4.53648623\r
-20/07/2020,20,7,2020,454,0,Japan,JP,JPN,126860299,Asia,4.19437763\r
-19/07/2020,19,7,2020,510,0,Japan,JP,JPN,126860299,Asia,4.03593562\r
-18/07/2020,18,7,2020,659,0,Japan,JP,JPN,126860299,Asia,3.82310308\r
-17/07/2020,17,7,2020,583,0,Japan,JP,JPN,126860299,Asia,3.47232352\r
-16/07/2020,16,7,2020,382,1,Japan,JP,JPN,126860299,Asia,3.16568701\r
-15/07/2020,15,7,2020,288,2,Japan,JP,JPN,126860299,Asia,2.98359694\r
-14/07/2020,14,7,2020,352,0,Japan,JP,JPN,126860299,Asia,2.85905049\r
-13/07/2020,13,7,2020,366,0,Japan,JP,JPN,126860299,Asia,2.67380735\r
-12/07/2020,12,7,2020,373,0,Japan,JP,JPN,126860299,Asia,2.45309212\r
-11/07/2020,11,7,2020,410,0,Japan,JP,JPN,126860299,Asia,2.23237689\r
-10/07/2020,10,7,2020,348,1,Japan,JP,JPN,126860299,Asia,1.9880136\r
-09/07/2020,9,7,2020,197,1,Japan,JP,JPN,126860299,Asia,1.78227548\r
-08/07/2020,8,7,2020,193,2,Japan,JP,JPN,126860299,Asia,1.69241285\r
-07/07/2020,7,7,2020,206,1,Japan,JP,JPN,126860299,Asia,1.58678485\r
-06/07/2020,6,7,2020,253,0,Japan,JP,JPN,126860299,Asia,1.46539147\r
-05/07/2020,5,7,2020,240,0,Japan,JP,JPN,126860299,Asia,1.35818693\r
-04/07/2020,4,7,2020,214,1,Japan,JP,JPN,126860299,Asia,1.16900245\r
-03/07/2020,3,7,2020,194,1,Japan,JP,JPN,126860299,Asia,1.0468208\r
-02/07/2020,2,7,2020,151,1,Japan,JP,JPN,126860299,Asia,0.95065202\r
-01/07/2020,1,7,2020,130,2,Japan,JP,JPN,126860299,Asia,0.8631542\r
-30/06/2020,30,6,2020,117,0,Japan,JP,JPN,126860299,Asia,0.79299829\r
-29/06/2020,29,6,2020,86,1,Japan,JP,JPN,126860299,Asia,0.76777369\r
-28/06/2020,28,6,2020,93,0,Japan,JP,JPN,126860299,Asia,0.7575262\r
-27/06/2020,27,6,2020,100,2,Japan,JP,JPN,126860299,Asia,0.72126584\r
-26/06/2020,26,6,2020,87,1,Japan,JP,JPN,126860299,Asia,0.68185241\r
-25/06/2020,25,6,2020,83,5,Japan,JP,JPN,126860299,Asia,0.64480378\r
-24/06/2020,24,6,2020,59,8,Japan,JP,JPN,126860299,Asia,0.61169649\r
-23/06/2020,23,6,2020,52,2,Japan,JP,JPN,126860299,Asia,0.59750766\r
-22/06/2020,22,6,2020,117,1,Japan,JP,JPN,126860299,Asia,0.58489536\r
-21/06/2020,21,6,2020,0,0,Japan,JP,JPN,126860299,Asia,0.51868079\r
-20/06/2020,20,6,2020,59,17,Japan,JP,JPN,126860299,Asia,0.548635\r
-19/06/2020,19,6,2020,72,0,Japan,JP,JPN,126860299,Asia,0.53286963\r
-18/06/2020,18,6,2020,40,4,Japan,JP,JPN,126860299,Asia,0.51237464\r
-17/06/2020,17,6,2020,41,4,Japan,JP,JPN,126860299,Asia,0.50606849\r
-16/06/2020,16,6,2020,85,2,Japan,JP,JPN,126860299,Asia,0.51789252\r
-15/06/2020,15,6,2020,73,0,Japan,JP,JPN,126860299,Asia,0.48715004\r
-14/06/2020,14,6,2020,47,1,Japan,JP,JPN,126860299,Asia,0.4556193\r
-13/06/2020,13,6,2020,50,2,Japan,JP,JPN,126860299,Asia,0.4556193\r
-12/06/2020,12,6,2020,40,2,Japan,JP,JPN,126860299,Asia,0.4832087\r
-11/06/2020,11,6,2020,41,1,Japan,JP,JPN,126860299,Asia,0.50528022\r
-10/06/2020,10,6,2020,41,3,Japan,JP,JPN,126860299,Asia,0.47296121\r
-09/06/2020,9,6,2020,36,0,Japan,JP,JPN,126860299,Asia,0.46271371\r
-08/06/2020,8,6,2020,33,0,Japan,JP,JPN,126860299,Asia,0.46744333\r
-07/06/2020,7,6,2020,38,2,Japan,JP,JPN,126860299,Asia,0.46586679\r
-06/06/2020,6,6,2020,39,7,Japan,JP,JPN,126860299,Asia,0.44694834\r
-05/06/2020,5,6,2020,46,4,Japan,JP,JPN,126860299,Asia,0.43433604\r
-04/06/2020,4,6,2020,32,3,Japan,JP,JPN,126860299,Asia,0.46823159\r
-03/06/2020,3,6,2020,56,6,Japan,JP,JPN,126860299,Asia,0.47374947\r
-02/06/2020,2,6,2020,46,2,Japan,JP,JPN,126860299,Asia,0.4453718\r
-01/06/2020,1,6,2020,33,1,Japan,JP,JPN,126860299,Asia,0.45640756\r
-31/05/2020,31,5,2020,47,5,Japan,JP,JPN,126860299,Asia,0.44616007\r
-30/05/2020,30,5,2020,85,12,Japan,JP,JPN,126860299,Asia,0.44694834\r
-29/05/2020,29,5,2020,68,16,Japan,JP,JPN,126860299,Asia,0.41462932\r
-28/05/2020,28,5,2020,0,0,Japan,JP,JPN,126860299,Asia,0.45088968\r
-27/05/2020,27,5,2020,28,12,Japan,JP,JPN,126860299,Asia,0.49424446\r
-26/05/2020,26,5,2020,42,16,Japan,JP,JPN,126860299,Asia,0.59041324\r
-25/05/2020,25,5,2020,31,10,Japan,JP,JPN,126860299,Asia,0.61721437\r
-24/05/2020,24,5,2020,14,12,Japan,JP,JPN,126860299,Asia,0.63297975\r
-23/05/2020,23,5,2020,23,12,Japan,JP,JPN,126860299,Asia,0.71574796\r
-22/05/2020,22,5,2020,89,19,Japan,JP,JPN,126860299,Asia,0.76146754\r
-21/05/2020,21,5,2020,39,6,Japan,JP,JPN,126860299,Asia,0.7575262\r
-20/05/2020,20,5,2020,20,8,Japan,JP,JPN,126860299,Asia,0.81270501\r
-19/05/2020,19,5,2020,60,14,Japan,JP,JPN,126860299,Asia,0.89389668\r
-18/05/2020,18,5,2020,20,5,Japan,JP,JPN,126860299,Asia,0.98375931\r
-17/05/2020,17,5,2020,48,19,Japan,JP,JPN,126860299,Asia,1.13983651\r
-16/05/2020,16,5,2020,44,15,Japan,JP,JPN,126860299,Asia,1.33453887\r
-15/05/2020,15,5,2020,114,23,Japan,JP,JPN,126860299,Asia,1.50716971\r
-14/05/2020,14,5,2020,55,19,Japan,JP,JPN,126860299,Asia,1.56944294\r
-13/05/2020,13,5,2020,150,25,Japan,JP,JPN,126860299,Asia,1.71211957\r
-12/05/2020,12,5,2020,76,22,Japan,JP,JPN,126860299,Asia,1.81144142\r
-11/05/2020,11,5,2020,51,8,Japan,JP,JPN,126860299,Asia,1.90209232\r
-10/05/2020,10,5,2020,119,12,Japan,JP,JPN,126860299,Asia,2.02190916\r
-09/05/2020,9,5,2020,81,44,Japan,JP,JPN,126860299,Asia,2.1567031\r
-08/05/2020,8,5,2020,84,6,Japan,JP,JPN,126860299,Asia,2.60680451\r
-07/05/2020,7,5,2020,109,8,Japan,JP,JPN,126860299,Asia,2.90949969\r
-06/05/2020,6,5,2020,123,22,Japan,JP,JPN,126860299,Asia,3.04114055\r
-05/05/2020,5,5,2020,174,11,Japan,JP,JPN,126860299,Asia,3.24214907\r
-04/05/2020,4,5,2020,218,18,Japan,JP,JPN,126860299,Asia,3.39428492\r
-03/05/2020,3,5,2020,295,34,Japan,JP,JPN,126860299,Asia,3.52986713\r
-02/05/2020,2,5,2020,263,26,Japan,JP,JPN,126860299,Asia,3.74348794\r
-01/05/2020,1,5,2020,193,17,Japan,JP,JPN,126860299,Asia,4.03120601\r
-30/04/2020,30,4,2020,236,26,Japan,JP,JPN,126860299,Asia,4.34020733\r
-29/04/2020,29,4,2020,276,13,Japan,JP,JPN,126860299,Asia,4.53412143\r
-28/04/2020,28,4,2020,191,25,Japan,JP,JPN,126860299,Asia,4.67522152\r
-27/04/2020,27,4,2020,203,3,Japan,JP,JPN,126860299,Asia,4.83208699\r
-26/04/2020,26,4,2020,290,14,Japan,JP,JPN,126860299,Asia,5.07172066\r
-25/04/2020,25,4,2020,652,17,Japan,JP,JPN,126860299,Asia,5.42880638\r
-24/04/2020,24,4,2020,468,30,Japan,JP,JPN,126860299,Asia,5.43353599\r
-23/04/2020,23,4,2020,276,101,Japan,JP,JPN,126860299,Asia,5.52103381\r
-22/04/2020,22,4,2020,378,0,Japan,JP,JPN,126860299,Asia,5.70627695\r
-21/04/2020,21,4,2020,367,15,Japan,JP,JPN,126860299,Asia,5.6849937\r
-20/04/2020,20,4,2020,390,10,Japan,JP,JPN,126860299,Asia,5.5943428\r
-19/04/2020,19,4,2020,566,7,Japan,JP,JPN,126860299,Asia,5.58882492\r
-18/04/2020,18,4,2020,628,6,Japan,JP,JPN,126860299,Asia,5.40752312\r
-17/04/2020,17,4,2020,585,12,Japan,JP,JPN,126860299,Asia,5.16315983\r
-16/04/2020,16,4,2020,482,17,Japan,JP,JPN,126860299,Asia,5.0480726\r
-15/04/2020,15,4,2020,455,10,Japan,JP,JPN,126860299,Asia,4.84548755\r
-14/04/2020,14,4,2020,390,7,Japan,JP,JPN,126860299,Asia,4.48682531\r
-13/04/2020,13,4,2020,507,4,Japan,JP,JPN,126860299,Asia,4.2479799\r
-12/04/2020,12,4,2020,743,4,Japan,JP,JPN,126860299,Asia,3.98469816\r
-11/04/2020,11,4,2020,658,6,Japan,JP,JPN,126860299,Asia,3.55193866\r
-10/04/2020,10,4,2020,579,3,Japan,JP,JPN,126860299,Asia,3.13967414\r
-09/04/2020,9,4,2020,511,4,Japan,JP,JPN,126860299,Asia,2.75894037\r
-08/04/2020,8,4,2020,351,1,Japan,JP,JPN,126860299,Asia,2.41525522\r
-07/04/2020,7,4,2020,252,7,Japan,JP,JPN,126860299,Asia,2.18981038\r
-06/04/2020,6,4,2020,383,3,Japan,JP,JPN,126860299,Asia,2.02190916\r
-05/04/2020,5,4,2020,336,1,Japan,JP,JPN,126860299,Asia,1.75389781\r
-04/04/2020,4,4,2020,318,6,Japan,JP,JPN,126860299,Asia,1.51978201\r
-03/04/2020,3,4,2020,439,6,Japan,JP,JPN,126860299,Asia,1.31404388\r
-02/04/2020,2,4,2020,225,1,Japan,JP,JPN,126860299,Asia,1.02869062\r
-01/04/2020,1,4,2020,0,0,Japan,JP,JPN,126860299,Asia,0.88601399\r
-31/03/2020,31,3,2020,87,2,Japan,JP,JPN,126860299,Asia,0.88995534\r
-30/03/2020,30,3,2020,173,2,Japan,JP,JPN,126860299,Asia,0.82925865\r
-29/03/2020,29,3,2020,194,3,Japan,JP,JPN,126860299,Asia,0.7196893\r
-28/03/2020,28,3,2020,135,3,Japan,JP,JPN,126860299,Asia,0.60066073\r
-27/03/2020,27,3,2020,96,1,Japan,JP,JPN,126860299,Asia,0.54311712\r
-26/03/2020,26,3,2020,75,2,Japan,JP,JPN,126860299,Asia,0.51158637\r
-25/03/2020,25,3,2020,65,1,Japan,JP,JPN,126860299,Asia,0.49266792\r
-24/03/2020,24,3,2020,39,1,Japan,JP,JPN,126860299,Asia,0.48399697\r
-23/03/2020,23,3,2020,43,5,Japan,JP,JPN,126860299,Asia,0.47374947\r
-22/03/2020,22,3,2020,39,1,Japan,JP,JPN,126860299,Asia,0.46586679\r
-21/03/2020,21,3,2020,57,2,Japan,JP,JPN,126860299,Asia,0.47217294\r
-20/03/2020,20,3,2020,77,4,Japan,JP,JPN,126860299,Asia,0.47374947\r
-19/03/2020,19,3,2020,44,1,Japan,JP,JPN,126860299,Asia,0.43827738\r
-18/03/2020,18,3,2020,5,0,Japan,JP,JPN,126860299,Asia,0.44221873\r
-17/03/2020,17,3,2020,10,4,Japan,JP,JPN,126860299,Asia,0.44931315\r
-16/03/2020,16,3,2020,34,2,Japan,JP,JPN,126860299,Asia,0.44143046\r
-15/03/2020,15,3,2020,43,1,Japan,JP,JPN,126860299,Asia,0.42645335\r
-14/03/2020,14,3,2020,62,2,Japan,JP,JPN,126860299,Asia,0.39965222\r
-13/03/2020,13,3,2020,56,4,Japan,JP,JPN,126860299,Asia,0.36654493\r
-12/03/2020,12,3,2020,51,3,Japan,JP,JPN,126860299,Asia,0.34132034\r
-11/03/2020,11,3,2020,54,3,Japan,JP,JPN,126860299,Asia,0.31846055\r
-10/03/2020,10,3,2020,26,2,Japan,JP,JPN,126860299,Asia,0.29165941\r
-09/03/2020,9,3,2020,33,1,Japan,JP,JPN,126860299,Asia,0.27116442\r
-08/03/2020,8,3,2020,47,0,Japan,JP,JPN,126860299,Asia,0.25461078\r
-07/03/2020,7,3,2020,59,0,Japan,JP,JPN,126860299,Asia,0.23884541\r
-06/03/2020,6,3,2020,32,0,Japan,JP,JPN,126860299,Asia,0.20179678\r
-05/03/2020,5,3,2020,49,0,Japan,JP,JPN,126860299,Asia,0.1836666\r
-04/03/2020,4,3,2020,14,0,Japan,JP,JPN,126860299,Asia,0.15923027\r
-03/03/2020,3,3,2020,0,0,Japan,JP,JPN,126860299,Asia,0.15371239\r
-02/03/2020,2,3,2020,15,1,Japan,JP,JPN,126860299,Asia,0.15371239\r
-01/03/2020,1,3,2020,9,2,Japan,JP,JPN,126860299,Asia,0.14740624\r
-29/02/2020,29,2,2020,20,0,Japan,JP,JPN,126860299,Asia,0.15134759\r
-28/02/2020,28,2,2020,24,0,Japan,JP,JPN,126860299,Asia,0.14188836\r
-27/02/2020,27,2,2020,22,2,Japan,JP,JPN,126860299,Asia,0.12375818\r
-26/02/2020,26,2,2020,20,0,Japan,JP,JPN,126860299,Asia,0.10956935\r
-25/02/2020,25,2,2020,0,0,Japan,JP,JPN,126860299,Asia,0.09380397\r
-24/02/2020,24,2,2020,12,0,Japan,JP,JPN,126860299,Asia,0.09380397\r
-23/02/2020,23,2,2020,27,0,Japan,JP,JPN,126860299,Asia,0.08434475\r
-22/02/2020,22,2,2020,12,0,Japan,JP,JPN,126860299,Asia,0.06306149\r
-21/02/2020,21,2,2020,9,0,Japan,JP,JPN,126860299,Asia,0.05360227\r
-20/02/2020,20,2,2020,18,0,Japan,JP,JPN,126860299,Asia,0.04650785\r
-19/02/2020,19,2,2020,7,0,Japan,JP,JPN,126860299,Asia,0.03231902\r
-18/02/2020,18,2,2020,0,0,Japan,JP,JPN,126860299,Asia,0.03074248\r
-17/02/2020,17,2,2020,7,0,Japan,JP,JPN,126860299,Asia,0.03074248\r
-16/02/2020,16,2,2020,14,0,Japan,JP,JPN,126860299,Asia,0.02601287\r
-15/02/2020,15,2,2020,8,0,Japan,JP,JPN,126860299,Asia,0.01813018\r
-14/02/2020,14,2,2020,1,0,Japan,JP,JPN,126860299,Asia,0.0126123\r
-13/02/2020,13,2,2020,4,1,Japan,JP,JPN,126860299,Asia,0.01418884\r
-12/02/2020,12,2,2020,0,0,Japan,JP,JPN,126860299,Asia,0.01418884\r
-11/02/2020,11,2,2020,0,0,Japan,JP,JPN,126860299,Asia,0.01655364\r
-10/02/2020,10,2,2020,0,0,Japan,JP,JPN,126860299,Asia,0.01734191\r
-09/02/2020,9,2,2020,0,0,Japan,JP,JPN,126860299,Asia,0.01734191\r
-08/02/2020,8,2,2020,0,0,Japan,JP,JPN,126860299,Asia,0.01813018\r
-07/02/2020,7,2,2020,0,0,Japan,JP,JPN,126860299,Asia,0.01813018\r
-06/02/2020,6,2,2020,0,0,Japan,JP,JPN,126860299,Asia,0.01891845\r
-05/02/2020,5,2,2020,5,0,Japan,JP,JPN,126860299,Asia,0.01891845\r
-04/02/2020,4,2,2020,0,0,Japan,JP,JPN,126860299,Asia,0.0149771\r
-03/02/2020,3,2,2020,1,0,Japan,JP,JPN,126860299,Asia,0.0149771\r
-02/02/2020,2,2,2020,4,0,Japan,JP,JPN,126860299,Asia,0.01418884\r
-01/02/2020,1,2,2020,1,0,Japan,JP,JPN,126860299,Asia,0.01103576\r
-31/01/2020,31,1,2020,3,0,Japan,JP,JPN,126860299,Asia,0.01024749\r
-30/01/2020,30,1,2020,4,0,Japan,JP,JPN,126860299,Asia,0.00788269\r
-29/01/2020,29,1,2020,3,0,Japan,JP,JPN,126860299,Asia,0.00472961\r
-28/01/2020,28,1,2020,1,0,Japan,JP,JPN,126860299,Asia,0.00315307\r
-27/01/2020,27,1,2020,0,0,Japan,JP,JPN,126860299,Asia,0.00236481\r
-26/01/2020,26,1,2020,1,0,Japan,JP,JPN,126860299,Asia,0.00236481\r
-25/01/2020,25,1,2020,0,0,Japan,JP,JPN,126860299,Asia,0.00157654\r
-24/01/2020,24,1,2020,1,0,Japan,JP,JPN,126860299,Asia,0.00157654\r
-23/01/2020,23,1,2020,0,0,Japan,JP,JPN,126860299,Asia,0.00078827\r
-22/01/2020,22,1,2020,0,0,Japan,JP,JPN,126860299,Asia,0.00078827\r
-21/01/2020,21,1,2020,0,0,Japan,JP,JPN,126860299,Asia,0.00078827\r
-20/01/2020,20,1,2020,0,0,Japan,JP,JPN,126860299,Asia,0.00078827\r
-19/01/2020,19,1,2020,0,0,Japan,JP,JPN,126860299,Asia,0.00078827\r
-18/01/2020,18,1,2020,0,0,Japan,JP,JPN,126860299,Asia,0.00078827\r
-17/01/2020,17,1,2020,0,0,Japan,JP,JPN,126860299,Asia,0.00078827\r
-16/01/2020,16,1,2020,0,0,Japan,JP,JPN,126860299,Asia,0.00078827\r
-15/01/2020,15,1,2020,1,0,Japan,JP,JPN,126860299,Asia,0.00078827\r
-14/01/2020,14,1,2020,0,0,Japan,JP,JPN,126860299,Asia,0\r
-13/01/2020,13,1,2020,0,0,Japan,JP,JPN,126860299,Asia,0\r
-12/01/2020,12,1,2020,0,0,Japan,JP,JPN,126860299,Asia,\r
-11/01/2020,11,1,2020,0,0,Japan,JP,JPN,126860299,Asia,\r
-10/01/2020,10,1,2020,0,0,Japan,JP,JPN,126860299,Asia,\r
-09/01/2020,9,1,2020,0,0,Japan,JP,JPN,126860299,Asia,\r
-08/01/2020,8,1,2020,0,0,Japan,JP,JPN,126860299,Asia,\r
-07/01/2020,7,1,2020,0,0,Japan,JP,JPN,126860299,Asia,\r
-06/01/2020,6,1,2020,0,0,Japan,JP,JPN,126860299,Asia,\r
-05/01/2020,5,1,2020,0,0,Japan,JP,JPN,126860299,Asia,\r
-04/01/2020,4,1,2020,0,0,Japan,JP,JPN,126860299,Asia,\r
-03/01/2020,3,1,2020,0,0,Japan,JP,JPN,126860299,Asia,\r
-02/01/2020,2,1,2020,0,0,Japan,JP,JPN,126860299,Asia,\r
-01/01/2020,1,1,2020,0,0,Japan,JP,JPN,126860299,Asia,\r
-31/12/2019,31,12,2019,0,0,Japan,JP,JPN,126860299,Asia,\r
-19/08/2020,19,8,2020,0,0,Jersey,JE,JEY,107796,Europe,12.9874949\r
-18/08/2020,18,8,2020,2,1,Jersey,JE,JEY,107796,Europe,16.69820773\r
-17/08/2020,17,8,2020,0,0,Jersey,JE,JEY,107796,Europe,18.55356414\r
-16/08/2020,16,8,2020,0,0,Jersey,JE,JEY,107796,Europe,18.55356414\r
-15/08/2020,15,8,2020,3,0,Jersey,JE,JEY,107796,Europe,18.55356414\r
-14/08/2020,14,8,2020,1,0,Jersey,JE,JEY,107796,Europe,15.77052952\r
-13/08/2020,13,8,2020,4,0,Jersey,JE,JEY,107796,Europe,14.84285131\r
-12/08/2020,12,8,2020,0,0,Jersey,JE,JEY,107796,Europe,11.13213848\r
-11/08/2020,11,8,2020,2,0,Jersey,JE,JEY,107796,Europe,12.05981669\r
-10/08/2020,10,8,2020,0,0,Jersey,JE,JEY,107796,Europe,12.05981669\r
-09/08/2020,9,8,2020,0,0,Jersey,JE,JEY,107796,Europe,12.05981669\r
-08/08/2020,8,8,2020,0,0,Jersey,JE,JEY,107796,Europe,12.05981669\r
-07/08/2020,7,8,2020,1,0,Jersey,JE,JEY,107796,Europe,12.9874949\r
-06/08/2020,6,8,2020,1,0,Jersey,JE,JEY,107796,Europe,12.05981669\r
-05/08/2020,5,8,2020,4,0,Jersey,JE,JEY,107796,Europe,11.13213848\r
-04/08/2020,4,8,2020,4,0,Jersey,JE,JEY,107796,Europe,7.42142566\r
-03/08/2020,3,8,2020,0,0,Jersey,JE,JEY,107796,Europe,3.71071283\r
-02/08/2020,2,8,2020,0,0,Jersey,JE,JEY,107796,Europe,3.71071283\r
-01/08/2020,1,8,2020,0,0,Jersey,JE,JEY,107796,Europe,3.71071283\r
-31/07/2020,31,7,2020,0,0,Jersey,JE,JEY,107796,Europe,3.71071283\r
-30/07/2020,30,7,2020,0,0,Jersey,JE,JEY,107796,Europe,5.56606924\r
-29/07/2020,29,7,2020,1,0,Jersey,JE,JEY,107796,Europe,5.56606924\r
-28/07/2020,28,7,2020,2,0,Jersey,JE,JEY,107796,Europe,4.63839103\r
-27/07/2020,27,7,2020,0,0,Jersey,JE,JEY,107796,Europe,6.49374745\r
-26/07/2020,26,7,2020,0,0,Jersey,JE,JEY,107796,Europe,6.49374745\r
-25/07/2020,25,7,2020,1,0,Jersey,JE,JEY,107796,Europe,6.49374745\r
-24/07/2020,24,7,2020,0,0,Jersey,JE,JEY,107796,Europe,5.56606924\r
-23/07/2020,23,7,2020,0,0,Jersey,JE,JEY,107796,Europe,5.56606924\r
-22/07/2020,22,7,2020,0,0,Jersey,JE,JEY,107796,Europe,5.56606924\r
-21/07/2020,21,7,2020,0,0,Jersey,JE,JEY,107796,Europe,5.56606924\r
-20/07/2020,20,7,2020,0,0,Jersey,JE,JEY,107796,Europe,10.20446028\r
-19/07/2020,19,7,2020,0,0,Jersey,JE,JEY,107796,Europe,10.20446028\r
-18/07/2020,18,7,2020,0,0,Jersey,JE,JEY,107796,Europe,10.20446028\r
-17/07/2020,17,7,2020,2,0,Jersey,JE,JEY,107796,Europe,10.20446028\r
-16/07/2020,16,7,2020,0,0,Jersey,JE,JEY,107796,Europe,9.27678207\r
-15/07/2020,15,7,2020,0,0,Jersey,JE,JEY,107796,Europe,9.27678207\r
-14/07/2020,14,7,2020,4,0,Jersey,JE,JEY,107796,Europe,9.27678207\r
-13/07/2020,13,7,2020,0,0,Jersey,JE,JEY,107796,Europe,5.56606924\r
-12/07/2020,12,7,2020,0,0,Jersey,JE,JEY,107796,Europe,5.56606924\r
-11/07/2020,11,7,2020,0,0,Jersey,JE,JEY,107796,Europe,5.56606924\r
-10/07/2020,10,7,2020,0,0,Jersey,JE,JEY,107796,Europe,5.56606924\r
-09/07/2020,9,7,2020,0,0,Jersey,JE,JEY,107796,Europe,5.56606924\r
-08/07/2020,8,7,2020,0,0,Jersey,JE,JEY,107796,Europe,6.49374745\r
-07/07/2020,7,7,2020,5,0,Jersey,JE,JEY,107796,Europe,6.49374745\r
-06/07/2020,6,7,2020,0,0,Jersey,JE,JEY,107796,Europe,1.85535641\r
-05/07/2020,5,7,2020,0,0,Jersey,JE,JEY,107796,Europe,1.85535641\r
-04/07/2020,4,7,2020,0,0,Jersey,JE,JEY,107796,Europe,1.85535641\r
-03/07/2020,3,7,2020,1,0,Jersey,JE,JEY,107796,Europe,1.85535641\r
-02/07/2020,2,7,2020,0,0,Jersey,JE,JEY,107796,Europe,0.92767821\r
-01/07/2020,1,7,2020,0,0,Jersey,JE,JEY,107796,Europe,2.78303462\r
-30/06/2020,30,6,2020,0,0,Jersey,JE,JEY,107796,Europe,2.78303462\r
-29/06/2020,29,6,2020,0,0,Jersey,JE,JEY,107796,Europe,5.56606924\r
-28/06/2020,28,6,2020,0,0,Jersey,JE,JEY,107796,Europe,5.56606924\r
-27/06/2020,27,6,2020,0,0,Jersey,JE,JEY,107796,Europe,5.56606924\r
-26/06/2020,26,6,2020,0,0,Jersey,JE,JEY,107796,Europe,5.56606924\r
-25/06/2020,25,6,2020,1,0,Jersey,JE,JEY,107796,Europe,5.56606924\r
-24/06/2020,24,6,2020,0,0,Jersey,JE,JEY,107796,Europe,4.63839103\r
-23/06/2020,23,6,2020,0,0,Jersey,JE,JEY,107796,Europe,5.56606924\r
-22/06/2020,22,6,2020,0,0,Jersey,JE,JEY,107796,Europe,6.49374745\r
-21/06/2020,21,6,2020,0,0,Jersey,JE,JEY,107796,Europe,6.49374745\r
-20/06/2020,20,6,2020,0,1,Jersey,JE,JEY,107796,Europe,8.34910386\r
-19/06/2020,19,6,2020,0,0,Jersey,JE,JEY,107796,Europe,8.34910386\r
-18/06/2020,18,6,2020,2,0,Jersey,JE,JEY,107796,Europe,8.34910386\r
-17/06/2020,17,6,2020,0,0,Jersey,JE,JEY,107796,Europe,7.42142566\r
-16/06/2020,16,6,2020,3,0,Jersey,JE,JEY,107796,Europe,7.42142566\r
-15/06/2020,15,6,2020,0,0,Jersey,JE,JEY,107796,Europe,4.63839103\r
-14/06/2020,14,6,2020,0,0,Jersey,JE,JEY,107796,Europe,4.63839103\r
-13/06/2020,13,6,2020,0,0,Jersey,JE,JEY,107796,Europe,4.63839103\r
-12/06/2020,12,6,2020,0,0,Jersey,JE,JEY,107796,Europe,4.63839103\r
-11/06/2020,11,6,2020,0,0,Jersey,JE,JEY,107796,Europe,4.63839103\r
-10/06/2020,10,6,2020,1,0,Jersey,JE,JEY,107796,Europe,5.56606924\r
-09/06/2020,9,6,2020,1,0,Jersey,JE,JEY,107796,Europe,4.63839103\r
-08/06/2020,8,6,2020,0,0,Jersey,JE,JEY,107796,Europe,4.63839103\r
-07/06/2020,7,6,2020,2,0,Jersey,JE,JEY,107796,Europe,4.63839103\r
-06/06/2020,6,6,2020,0,0,Jersey,JE,JEY,107796,Europe,2.78303462\r
-05/06/2020,5,6,2020,0,0,Jersey,JE,JEY,107796,Europe,2.78303462\r
-04/06/2020,4,6,2020,1,0,Jersey,JE,JEY,107796,Europe,2.78303462\r
-03/06/2020,3,6,2020,0,1,Jersey,JE,JEY,107796,Europe,4.63839103\r
-02/06/2020,2,6,2020,0,0,Jersey,JE,JEY,107796,Europe,4.63839103\r
-01/06/2020,1,6,2020,0,0,Jersey,JE,JEY,107796,Europe,5.56606924\r
-31/05/2020,31,5,2020,0,0,Jersey,JE,JEY,107796,Europe,5.56606924\r
-30/05/2020,30,5,2020,0,0,Jersey,JE,JEY,107796,Europe,10.20446028\r
-29/05/2020,29,5,2020,0,0,Jersey,JE,JEY,107796,Europe,10.20446028\r
-28/05/2020,28,5,2020,1,0,Jersey,JE,JEY,107796,Europe,11.13213848\r
-27/05/2020,27,5,2020,0,0,Jersey,JE,JEY,107796,Europe,11.13213848\r
-26/05/2020,26,5,2020,1,0,Jersey,JE,JEY,107796,Europe,12.05981669\r
-25/05/2020,25,5,2020,0,0,Jersey,JE,JEY,107796,Europe,11.13213848\r
-24/05/2020,24,5,2020,0,0,Jersey,JE,JEY,107796,Europe,12.05981669\r
-23/05/2020,23,5,2020,0,0,Jersey,JE,JEY,107796,Europe,12.05981669\r
-22/05/2020,22,5,2020,0,0,Jersey,JE,JEY,107796,Europe,12.05981669\r
-21/05/2020,21,5,2020,3,1,Jersey,JE,JEY,107796,Europe,12.05981669\r
-20/05/2020,20,5,2020,0,1,Jersey,JE,JEY,107796,Europe,9.27678207\r
-19/05/2020,19,5,2020,1,0,Jersey,JE,JEY,107796,Europe,9.27678207\r
-18/05/2020,18,5,2020,0,0,Jersey,JE,JEY,107796,Europe,9.27678207\r
-17/05/2020,17,5,2020,5,0,Jersey,JE,JEY,107796,Europe,10.20446028\r
-16/05/2020,16,5,2020,0,0,Jersey,JE,JEY,107796,Europe,10.20446028\r
-15/05/2020,15,5,2020,1,0,Jersey,JE,JEY,107796,Europe,10.20446028\r
-14/05/2020,14,5,2020,1,1,Jersey,JE,JEY,107796,Europe,9.27678207\r
-13/05/2020,13,5,2020,1,1,Jersey,JE,JEY,107796,Europe,10.20446028\r
-12/05/2020,12,5,2020,0,0,Jersey,JE,JEY,107796,Europe,10.20446028\r
-11/05/2020,11,5,2020,1,0,Jersey,JE,JEY,107796,Europe,12.05981669\r
-10/05/2020,10,5,2020,0,0,Jersey,JE,JEY,107796,Europe,12.05981669\r
-09/05/2020,9,5,2020,0,0,Jersey,JE,JEY,107796,Europe,13.9151731\r
-08/05/2020,8,5,2020,0,0,Jersey,JE,JEY,107796,Europe,15.77052952\r
-07/05/2020,7,5,2020,0,1,Jersey,JE,JEY,107796,Europe,35.25177187\r
-06/05/2020,6,5,2020,0,0,Jersey,JE,JEY,107796,Europe,35.25177187\r
-05/05/2020,5,5,2020,1,0,Jersey,JE,JEY,107796,Europe,40.81784111\r
-04/05/2020,4,5,2020,1,0,Jersey,JE,JEY,107796,Europe,39.8901629\r
-03/05/2020,3,5,2020,5,0,Jersey,JE,JEY,107796,Europe,42.67319752\r
-02/05/2020,2,5,2020,0,1,Jersey,JE,JEY,107796,Europe,57.51604883\r
-01/05/2020,1,5,2020,0,2,Jersey,JE,JEY,107796,Europe,58.44372704\r
-30/04/2020,30,4,2020,2,1,Jersey,JE,JEY,107796,Europe,64.00979628\r
-29/04/2020,29,4,2020,1,1,Jersey,JE,JEY,107796,Europe,62.15443987\r
-28/04/2020,28,4,2020,2,0,Jersey,JE,JEY,107796,Europe,61.22676166\r
-27/04/2020,27,4,2020,1,0,Jersey,JE,JEY,107796,Europe,63.08211807\r
-26/04/2020,26,4,2020,2,0,Jersey,JE,JEY,107796,Europe,76.06961297\r
-25/04/2020,25,4,2020,2,0,Jersey,JE,JEY,107796,Europe,74.21425656\r
-24/04/2020,24,4,2020,21,1,Jersey,JE,JEY,107796,Europe,86.27407325\r
-23/04/2020,23,4,2020,0,4,Jersey,JE,JEY,107796,Europe,78.85264759\r
-22/04/2020,22,4,2020,6,0,Jersey,JE,JEY,107796,Europe,78.85264759\r
-21/04/2020,21,4,2020,0,2,Jersey,JE,JEY,107796,Europe,74.21425656\r
-20/04/2020,20,4,2020,4,0,Jersey,JE,JEY,107796,Europe,87.20175146\r
-19/04/2020,19,4,2020,21,1,Jersey,JE,JEY,107796,Europe,113.17674125\r
-18/04/2020,18,4,2020,1,1,Jersey,JE,JEY,107796,Europe,98.33388994\r
-17/04/2020,17,4,2020,6,4,Jersey,JE,JEY,107796,Europe,131.73030539\r
-16/04/2020,16,4,2020,0,2,Jersey,JE,JEY,107796,Europe,126.16423615\r
-15/04/2020,15,4,2020,0,0,Jersey,JE,JEY,107796,Europe,126.16423615\r
-14/04/2020,14,4,2020,4,0,Jersey,JE,JEY,107796,Europe,142.86244388\r
-13/04/2020,13,4,2020,15,0,Jersey,JE,JEY,107796,Europe,139.15173105\r
-12/04/2020,12,4,2020,0,0,Jersey,JE,JEY,107796,Europe,127.09191436\r
-11/04/2020,11,4,2020,15,1,Jersey,JE,JEY,107796,Europe,135.44101822\r
-10/04/2020,10,4,2020,13,0,Jersey,JE,JEY,107796,Europe,140.07940925\r
-09/04/2020,9,4,2020,0,0,Jersey,JE,JEY,107796,Europe,141.00708746\r
-08/04/2020,8,4,2020,1,0,Jersey,JE,JEY,107796,Europe,141.00708746\r
-07/04/2020,7,4,2020,14,0,Jersey,JE,JEY,107796,Europe,140.07940925\r
-06/04/2020,6,4,2020,32,0,Jersey,JE,JEY,107796,Europe,129.87494898\r
-05/04/2020,5,4,2020,5,1,Jersey,JE,JEY,107796,Europe,102.97228098\r
-04/04/2020,4,4,2020,37,0,Jersey,JE,JEY,107796,Europe,98.33388994\r
-03/04/2020,3,4,2020,0,0,Jersey,JE,JEY,107796,Europe,70.50354373\r
-02/04/2020,2,4,2020,0,0,Jersey,JE,JEY,107796,Europe,75.14193477\r
-01/04/2020,1,4,2020,18,0,Jersey,JE,JEY,107796,Europe,\r
-31/03/2020,31,3,2020,0,0,Jersey,JE,JEY,107796,Europe,\r
-30/03/2020,30,3,2020,2,1,Jersey,JE,JEY,107796,Europe,\r
-29/03/2020,29,3,2020,9,0,Jersey,JE,JEY,107796,Europe,\r
-28/03/2020,28,3,2020,20,0,Jersey,JE,JEY,107796,Europe,\r
-27/03/2020,27,3,2020,14,1,Jersey,JE,JEY,107796,Europe,\r
-26/03/2020,26,3,2020,0,0,Jersey,JE,JEY,107796,Europe,\r
-25/03/2020,25,3,2020,0,0,Jersey,JE,JEY,107796,Europe,\r
-24/03/2020,24,3,2020,3,0,Jersey,JE,JEY,107796,Europe,\r
-23/03/2020,23,3,2020,3,0,Jersey,JE,JEY,107796,Europe,\r
-22/03/2020,22,3,2020,0,0,Jersey,JE,JEY,107796,Europe,\r
-21/03/2020,21,3,2020,7,0,Jersey,JE,JEY,107796,Europe,\r
-20/03/2020,20,3,2020,5,0,Jersey,JE,JEY,107796,Europe,\r
-19/08/2020,19,8,2020,40,0,Jordan,JO,JOR,10101697,Asia,2.11845594\r
-18/08/2020,18,8,2020,20,0,Jordan,JO,JOR,10101697,Asia,1.78187883\r
-17/08/2020,17,8,2020,39,0,Jordan,JO,JOR,10101697,Asia,1.63338892\r
-16/08/2020,16,8,2020,10,0,Jordan,JO,JOR,10101697,Asia,1.43540239\r
-15/08/2020,15,8,2020,9,0,Jordan,JO,JOR,10101697,Asia,1.34630845\r
-14/08/2020,14,8,2020,17,0,Jordan,JO,JOR,10101697,Asia,1.27701316\r
-13/08/2020,13,8,2020,20,0,Jordan,JO,JOR,10101697,Asia,1.14832191\r
-12/08/2020,12,8,2020,15,0,Jordan,JO,JOR,10101697,Asia,0.99983201\r
-11/08/2020,11,8,2020,16,0,Jordan,JO,JOR,10101697,Asia,0.91073807\r
-10/08/2020,10,8,2020,6,0,Jordan,JO,JOR,10101697,Asia,0.83154345\r
-09/08/2020,9,8,2020,9,0,Jordan,JO,JOR,10101697,Asia,0.91073807\r
-08/08/2020,8,8,2020,5,0,Jordan,JO,JOR,10101697,Asia,0.90083874\r
-07/08/2020,7,8,2020,1,0,Jordan,JO,JOR,10101697,Asia,0.99983201\r
-06/08/2020,6,8,2020,7,0,Jordan,JO,JOR,10101697,Asia,1.09882528\r
-05/08/2020,5,8,2020,6,0,Jordan,JO,JOR,10101697,Asia,1.09882528\r
-04/08/2020,4,8,2020,5,0,Jordan,JO,JOR,10101697,Asia,-0.04949663\r
-03/08/2020,3,8,2020,19,0,Jordan,JO,JOR,10101697,Asia,-0.04949663\r
-02/08/2020,2,8,2020,1,0,Jordan,JO,JOR,10101697,Asia,-0.19798654\r
-01/08/2020,1,8,2020,2,0,Jordan,JO,JOR,10101697,Asia,-0.15838923\r
-31/07/2020,31,7,2020,4,0,Jordan,JO,JOR,10101697,Asia,-0.1484899\r
-30/07/2020,30,7,2020,5,0,Jordan,JO,JOR,10101697,Asia,-0.13859058\r
-29/07/2020,29,7,2020,6,0,Jordan,JO,JOR,10101697,Asia,-0.15838923\r
-28/07/2020,28,7,2020,8,0,Jordan,JO,JOR,10101697,Asia,-0.06929529\r
-27/07/2020,27,7,2020,14,0,Jordan,JO,JOR,10101697,Asia,-0.10889259\r
-26/07/2020,26,7,2020,8,0,Jordan,JO,JOR,10101697,Asia,-0.21778519\r
-25/07/2020,25,7,2020,15,0,Jordan,JO,JOR,10101697,Asia,-0.26728182\r
-24/07/2020,24,7,2020,11,0,Jordan,JO,JOR,10101697,Asia,-0.37617442\r
-23/07/2020,23,7,2020,7,0,Jordan,JO,JOR,10101697,Asia,-0.48506701\r
-22/07/2020,22,7,2020,-110,0,Jordan,JO,JOR,10101697,Asia,-0.5543623\r
-21/07/2020,21,7,2020,5,0,Jordan,JO,JOR,10101697,Asia,0.5543623\r
-20/07/2020,20,7,2020,4,0,Jordan,JO,JOR,10101697,Asia,0.53456365\r
-19/07/2020,19,7,2020,5,1,Jordan,JO,JOR,10101697,Asia,0.63355692\r
-18/07/2020,18,7,2020,3,0,Jordan,JO,JOR,10101697,Asia,0.61375826\r
-17/07/2020,17,7,2020,5,0,Jordan,JO,JOR,10101697,Asia,0.69295288\r
-16/07/2020,16,7,2020,3,0,Jordan,JO,JOR,10101697,Asia,0.67315422\r
-15/07/2020,15,7,2020,15,0,Jordan,JO,JOR,10101697,Asia,0.65335557\r
-14/07/2020,14,7,2020,4,0,Jordan,JO,JOR,10101697,Asia,0.54446297\r
-13/07/2020,13,7,2020,3,0,Jordan,JO,JOR,10101697,Asia,0.57416096\r
-12/07/2020,12,7,2020,3,0,Jordan,JO,JOR,10101697,Asia,0.64345624\r
-11/07/2020,11,7,2020,4,0,Jordan,JO,JOR,10101697,Asia,0.68305355\r
-10/07/2020,10,7,2020,0,0,Jordan,JO,JOR,10101697,Asia,0.82164413\r
-09/07/2020,9,7,2020,0,0,Jordan,JO,JOR,10101697,Asia,0.97013403\r
-08/07/2020,8,7,2020,2,0,Jordan,JO,JOR,10101697,Asia,1.20771787\r
-07/07/2020,7,7,2020,3,0,Jordan,JO,JOR,10101697,Asia,1.23741585\r
-06/07/2020,6,7,2020,14,0,Jordan,JO,JOR,10101697,Asia,1.29681181\r
-05/07/2020,5,7,2020,3,0,Jordan,JO,JOR,10101697,Asia,1.33640912\r
-04/07/2020,4,7,2020,11,1,Jordan,JO,JOR,10101697,Asia,1.37600643\r
-03/07/2020,3,7,2020,3,0,Jordan,JO,JOR,10101697,Asia,1.33640912\r
-02/07/2020,2,7,2020,1,0,Jordan,JO,JOR,10101697,Asia,1.44530172\r
-01/07/2020,1,7,2020,4,0,Jordan,JO,JOR,10101697,Asia,1.49479835\r
-30/06/2020,30,6,2020,7,0,Jordan,JO,JOR,10101697,Asia,1.4749997\r
-29/06/2020,29,6,2020,10,0,Jordan,JO,JOR,10101697,Asia,1.58389229\r
-28/06/2020,28,6,2020,7,0,Jordan,JO,JOR,10101697,Asia,1.56409364\r
-27/06/2020,27,6,2020,18,0,Jordan,JO,JOR,10101697,Asia,1.87097277\r
-26/06/2020,26,6,2020,15,0,Jordan,JO,JOR,10101697,Asia,1.94026806\r
-25/06/2020,25,6,2020,24,0,Jordan,JO,JOR,10101697,Asia,2.05905998\r
-24/06/2020,24,6,2020,5,0,Jordan,JO,JOR,10101697,Asia,1.99966402\r
-23/06/2020,23,6,2020,9,0,Jordan,JO,JOR,10101697,Asia,2.08875796\r
-22/06/2020,22,6,2020,18,0,Jordan,JO,JOR,10101697,Asia,2.22734853\r
-21/06/2020,21,6,2020,7,0,Jordan,JO,JOR,10101697,Asia,2.1778519\r
-20/06/2020,20,6,2020,7,0,Jordan,JO,JOR,10101697,Asia,2.21744921\r
-19/06/2020,19,6,2020,14,0,Jordan,JO,JOR,10101697,Asia,2.33624113\r
-18/06/2020,18,6,2020,6,0,Jordan,JO,JOR,10101697,Asia,2.27684517\r
-17/06/2020,17,6,2020,2,0,Jordan,JO,JOR,10101697,Asia,2.23724786\r
-16/06/2020,16,6,2020,18,0,Jordan,JO,JOR,10101697,Asia,2.30654315\r
-15/06/2020,15,6,2020,8,0,Jordan,JO,JOR,10101697,Asia,2.19765055\r
-14/06/2020,14,6,2020,38,0,Jordan,JO,JOR,10101697,Asia,2.16795257\r
-13/06/2020,13,6,2020,25,0,Jordan,JO,JOR,10101697,Asia,1.83137546\r
-12/06/2020,12,6,2020,27,0,Jordan,JO,JOR,10101697,Asia,1.60369094\r
-11/06/2020,11,6,2020,18,0,Jordan,JO,JOR,10101697,Asia,1.41560373\r
-10/06/2020,10,6,2020,14,0,Jordan,JO,JOR,10101697,Asia,1.25721451\r
-09/06/2020,9,6,2020,23,0,Jordan,JO,JOR,10101697,Asia,1.18791922\r
-08/06/2020,8,6,2020,13,0,Jordan,JO,JOR,10101697,Asia,0.98993268\r
-07/06/2020,7,6,2020,11,0,Jordan,JO,JOR,10101697,Asia,0.90083874\r
-06/06/2020,6,6,2020,19,0,Jordan,JO,JOR,10101697,Asia,0.83154345\r
-05/06/2020,5,6,2020,8,0,Jordan,JO,JOR,10101697,Asia,0.80184547\r
-04/06/2020,4,6,2020,2,0,Jordan,JO,JOR,10101697,Asia,0.84144278\r
-03/06/2020,3,6,2020,9,0,Jordan,JO,JOR,10101697,Asia,1.04932864\r
-02/06/2020,2,6,2020,7,0,Jordan,JO,JOR,10101697,Asia,1.15822124\r
-01/06/2020,1,6,2020,5,0,Jordan,JO,JOR,10101697,Asia,1.24731518\r
-31/05/2020,31,5,2020,4,0,Jordan,JO,JOR,10101697,Asia,1.25721451\r
-30/05/2020,30,5,2020,2,0,Jordan,JO,JOR,10101697,Asia,1.32650979\r
-29/05/2020,29,5,2020,8,0,Jordan,JO,JOR,10101697,Asia,1.40570441\r
-28/05/2020,28,5,2020,2,0,Jordan,JO,JOR,10101697,Asia,1.3661071\r
-27/05/2020,27,5,2020,7,0,Jordan,JO,JOR,10101697,Asia,1.40570441\r
-26/05/2020,26,5,2020,3,0,Jordan,JO,JOR,10101697,Asia,1.4749997\r
-25/05/2020,25,5,2020,4,0,Jordan,JO,JOR,10101697,Asia,1.66308691\r
-24/05/2020,24,5,2020,4,0,Jordan,JO,JOR,10101697,Asia,1.80167748\r
-23/05/2020,23,5,2020,16,0,Jordan,JO,JOR,10101697,Asia,1.90067075\r
-22/05/2020,22,5,2020,12,0,Jordan,JO,JOR,10101697,Asia,1.8808721\r
-21/05/2020,21,5,2020,23,0,Jordan,JO,JOR,10101697,Asia,1.96996604\r
-20/05/2020,20,5,2020,20,0,Jordan,JO,JOR,10101697,Asia,1.76208017\r
-19/05/2020,19,5,2020,16,0,Jordan,JO,JOR,10101697,Asia,1.6234896\r
-18/05/2020,18,5,2020,6,0,Jordan,JO,JOR,10101697,Asia,1.50469768\r
-17/05/2020,17,5,2020,11,0,Jordan,JO,JOR,10101697,Asia,1.45520104\r
-16/05/2020,16,5,2020,10,0,Jordan,JO,JOR,10101697,Asia,1.35620777\r
-15/05/2020,15,5,2020,4,0,Jordan,JO,JOR,10101697,Asia,1.31661047\r
-14/05/2020,14,5,2020,6,0,Jordan,JO,JOR,10101697,Asia,1.29681181\r
-13/05/2020,13,5,2020,14,0,Jordan,JO,JOR,10101697,Asia,1.25721451\r
-12/05/2020,12,5,2020,22,0,Jordan,JO,JOR,10101697,Asia,1.11862393\r
-11/05/2020,11,5,2020,18,0,Jordan,JO,JOR,10101697,Asia,0.92063739\r
-10/05/2020,10,5,2020,14,0,Jordan,JO,JOR,10101697,Asia,0.77214749\r
-09/05/2020,9,5,2020,14,0,Jordan,JO,JOR,10101697,Asia,0.6632549\r
-08/05/2020,8,5,2020,21,0,Jordan,JO,JOR,10101697,Asia,0.56426163\r
-07/05/2020,7,5,2020,2,0,Jordan,JO,JOR,10101697,Asia,0.44546971\r
-06/05/2020,6,5,2020,6,0,Jordan,JO,JOR,10101697,Asia,0.45536903\r
-05/05/2020,5,5,2020,4,0,Jordan,JO,JOR,10101697,Asia,0.39597307\r
-04/05/2020,4,5,2020,1,0,Jordan,JO,JOR,10101697,Asia,0.43557038\r
-03/05/2020,3,5,2020,1,1,Jordan,JO,JOR,10101697,Asia,0.46526836\r
-02/05/2020,2,5,2020,6,0,Jordan,JO,JOR,10101697,Asia,0.51476499\r
-01/05/2020,1,5,2020,2,0,Jordan,JO,JOR,10101697,Asia,0.50486567\r
-30/04/2020,30,4,2020,2,0,Jordan,JO,JOR,10101697,Asia,0.49496634\r
-29/04/2020,29,4,2020,0,1,Jordan,JO,JOR,10101697,Asia,0.51476499\r
-28/04/2020,28,4,2020,2,0,Jordan,JO,JOR,10101697,Asia,0.57416096\r
-27/04/2020,27,4,2020,3,0,Jordan,JO,JOR,10101697,Asia,0.57416096\r
-26/04/2020,26,4,2020,3,0,Jordan,JO,JOR,10101697,Asia,0.62365759\r
-25/04/2020,25,4,2020,4,0,Jordan,JO,JOR,10101697,Asia,0.68305355\r
-24/04/2020,24,4,2020,9,0,Jordan,JO,JOR,10101697,Asia,0.64345624\r
-23/04/2020,23,4,2020,3,0,Jordan,JO,JOR,10101697,Asia,0.69295288\r
-22/04/2020,22,4,2020,0,0,Jordan,JO,JOR,10101697,Asia,0.75234884\r
-21/04/2020,21,4,2020,8,0,Jordan,JO,JOR,10101697,Asia,0.75234884\r
-20/04/2020,20,4,2020,4,0,Jordan,JO,JOR,10101697,Asia,0.71275153\r
-19/04/2020,19,4,2020,6,0,Jordan,JO,JOR,10101697,Asia,0.89093941\r
-18/04/2020,18,4,2020,5,0,Jordan,JO,JOR,10101697,Asia,1.0691273\r
-17/04/2020,17,4,2020,1,0,Jordan,JO,JOR,10101697,Asia,1.01963066\r
-16/04/2020,16,4,2020,4,0,Jordan,JO,JOR,10101697,Asia,1.2176172\r
-15/04/2020,15,4,2020,6,0,Jordan,JO,JOR,10101697,Asia,1.2176172\r
-14/04/2020,14,4,2020,2,0,Jordan,JO,JOR,10101697,Asia,1.2176172\r
-13/04/2020,13,4,2020,8,0,Jordan,JO,JOR,10101697,Asia,1.28691249\r
-12/04/2020,12,4,2020,9,0,Jordan,JO,JOR,10101697,Asia,1.44530172\r
-11/04/2020,11,4,2020,0,0,Jordan,JO,JOR,10101697,Asia,1.58389229\r
-10/04/2020,10,4,2020,14,1,Jordan,JO,JOR,10101697,Asia,1.97986536\r
-09/04/2020,9,4,2020,9,0,Jordan,JO,JOR,10101697,Asia,2.029362\r
-08/04/2020,8,4,2020,0,0,Jordan,JO,JOR,10101697,Asia,2.19765055\r
-07/04/2020,7,4,2020,4,1,Jordan,JO,JOR,10101697,Asia,2.34614046\r
-06/04/2020,6,4,2020,22,0,Jordan,JO,JOR,10101697,Asia,2.4352344\r
-05/04/2020,5,4,2020,24,0,Jordan,JO,JOR,10101697,Asia,2.36593911\r
-04/04/2020,4,4,2020,0,0,Jordan,JO,JOR,10101697,Asia,2.27684517\r
-03/04/2020,3,4,2020,21,0,Jordan,JO,JOR,10101697,Asia,2.40553642\r
-02/04/2020,2,4,2020,4,0,Jordan,JO,JOR,10101697,Asia,2.23724786\r
-01/04/2020,1,4,2020,6,0,Jordan,JO,JOR,10101697,Asia,2.36593911\r
-31/03/2020,31,3,2020,9,4,Jordan,JO,JOR,10101697,Asia,2.49463036\r
-30/03/2020,30,3,2020,24,0,Jordan,JO,JOR,10101697,Asia,2.41543574\r
-29/03/2020,29,3,2020,23,1,Jordan,JO,JOR,10101697,Asia,2.31644247\r
-28/03/2020,28,3,2020,40,0,Jordan,JO,JOR,10101697,Asia,2.08875796\r
-27/03/2020,27,3,2020,19,0,Jordan,JO,JOR,10101697,Asia,1.69278489\r
-26/03/2020,26,3,2020,26,0,Jordan,JO,JOR,10101697,Asia,1.514597\r
-25/03/2020,25,3,2020,15,0,Jordan,JO,JOR,10101697,Asia,\r
-24/03/2020,24,3,2020,13,0,Jordan,JO,JOR,10101697,Asia,\r
-23/03/2020,23,3,2020,15,0,Jordan,JO,JOR,10101697,Asia,\r
-22/03/2020,22,3,2020,15,0,Jordan,JO,JOR,10101697,Asia,\r
-21/03/2020,21,3,2020,13,0,Jordan,JO,JOR,10101697,Asia,\r
-20/03/2020,20,3,2020,4,0,Jordan,JO,JOR,10101697,Asia,\r
-19/03/2020,19,3,2020,17,0,Jordan,JO,JOR,10101697,Asia,\r
-18/03/2020,18,3,2020,19,0,Jordan,JO,JOR,10101697,Asia,\r
-17/03/2020,17,3,2020,1,0,Jordan,JO,JOR,10101697,Asia,\r
-16/03/2020,16,3,2020,14,0,Jordan,JO,JOR,10101697,Asia,\r
-15/03/2020,15,3,2020,0,0,Jordan,JO,JOR,10101697,Asia,\r
-08/03/2020,8,3,2020,0,0,Jordan,JO,JOR,10101697,Asia,\r
-03/03/2020,3,3,2020,1,0,Jordan,JO,JOR,10101697,Asia,\r
-19/08/2020,19,8,2020,1352,11,Kazakhstan,KZ,KAZ,18551428,Asia,109.905286\r
-18/08/2020,18,8,2020,334,148,Kazakhstan,KZ,KAZ,18551428,Asia,118.03943071\r
-17/08/2020,17,8,2020,478,2,Kazakhstan,KZ,KAZ,18551428,Asia,123.96889339\r
-16/08/2020,16,8,2020,1380,5,Kazakhstan,KZ,KAZ,18551428,Asia,131.45618763\r
-15/08/2020,15,8,2020,1267,47,Kazakhstan,KZ,KAZ,18551428,Asia,158.55383208\r
-14/08/2020,14,8,2020,1410,0,Kazakhstan,KZ,KAZ,18551428,Asia,158.67242134\r
-13/08/2020,13,8,2020,1489,0,Kazakhstan,KZ,KAZ,18551428,Asia,158.69398302\r
-12/08/2020,12,8,2020,2114,0,Kazakhstan,KZ,KAZ,18551428,Asia,158.60234587\r
-11/08/2020,11,8,2020,779,0,Kazakhstan,KZ,KAZ,18551428,Asia,155.52980612\r
-10/08/2020,10,8,2020,900,324,Kazakhstan,KZ,KAZ,18551428,Asia,159.55645032\r
-09/08/2020,9,8,2020,1883,0,Kazakhstan,KZ,KAZ,18551428,Asia,162.26244147\r
-08/08/2020,8,8,2020,2009,0,Kazakhstan,KZ,KAZ,18551428,Asia,160.16556785\r
-07/08/2020,7,8,2020,2404,0,Kazakhstan,KZ,KAZ,18551428,Asia,158.7155447\r
-06/08/2020,6,8,2020,2590,0,Kazakhstan,KZ,KAZ,18551428,Asia,154.85061312\r
-05/08/2020,5,8,2020,2861,0,Kazakhstan,KZ,KAZ,18551428,Asia,149.76205605\r
-04/08/2020,4,8,2020,1434,0,Kazakhstan,KZ,KAZ,18551428,Asia,143.42292141\r
-03/08/2020,3,8,2020,1867,286,Kazakhstan,KZ,KAZ,18551428,Asia,144.47944385\r
-02/08/2020,2,8,2020,6407,30,Kazakhstan,KZ,KAZ,18551428,Asia,142.49576906\r
-01/08/2020,1,8,2020,1289,0,Kazakhstan,KZ,KAZ,18551428,Asia,116.77807229\r
-31/07/2020,31,7,2020,1414,0,Kazakhstan,KZ,KAZ,18551428,Asia,119.57570059\r
-30/07/2020,30,7,2020,1472,0,Kazakhstan,KZ,KAZ,18551428,Asia,121.15509383\r
-29/07/2020,29,7,2020,1544,208,Kazakhstan,KZ,KAZ,18551428,Asia,122.24395879\r
-28/07/2020,28,7,2020,1526,0,Kazakhstan,KZ,KAZ,18551428,Asia,123.40289923\r
-27/07/2020,27,7,2020,1402,0,Kazakhstan,KZ,KAZ,18551428,Asia,125.23564224\r
-26/07/2020,26,7,2020,1494,0,Kazakhstan,KZ,KAZ,18551428,Asia,126.49700066\r
-25/07/2020,25,7,2020,1740,0,Kazakhstan,KZ,KAZ,18551428,Asia,128.13568853\r
-24/07/2020,24,7,2020,1687,0,Kazakhstan,KZ,KAZ,18551428,Asia,127.96319507\r
-23/07/2020,23,7,2020,1646,0,Kazakhstan,KZ,KAZ,18551428,Asia,128.17342147\r
-22/07/2020,22,7,2020,1685,0,Kazakhstan,KZ,KAZ,18551428,Asia,129.87679439\r
-21/07/2020,21,7,2020,1630,210,Kazakhstan,KZ,KAZ,18551428,Asia,128.21115442\r
-20/07/2020,20,7,2020,1499,0,Kazakhstan,KZ,KAZ,18551428,Asia,125.40274528\r
-19/07/2020,19,7,2020,1636,0,Kazakhstan,KZ,KAZ,18551428,Asia,124.8852649\r
-18/07/2020,18,7,2020,1808,0,Kazakhstan,KZ,KAZ,18551428,Asia,123.8934275\r
-17/07/2020,17,7,2020,1707,0,Kazakhstan,KZ,KAZ,18551428,Asia,123.00939852\r
-16/07/2020,16,7,2020,1674,0,Kazakhstan,KZ,KAZ,18551428,Asia,121.89897187\r
-15/07/2020,15,7,2020,1759,0,Kazakhstan,KZ,KAZ,18551428,Asia,121.00955247\r
-14/07/2020,14,7,2020,1866,0,Kazakhstan,KZ,KAZ,18551428,Asia,215.27183783\r
-13/07/2020,13,7,2020,1636,111,Kazakhstan,KZ,KAZ,18551428,Asia,207.8653999\r
-12/07/2020,12,7,2020,1798,0,Kazakhstan,KZ,KAZ,18551428,Asia,201.99523185\r
-11/07/2020,11,7,2020,1708,0,Kazakhstan,KZ,KAZ,18551428,Asia,194.78823948\r
-10/07/2020,10,7,2020,1726,0,Kazakhstan,KZ,KAZ,18551428,Asia,188.6485504\r
-09/07/2020,9,7,2020,1962,0,Kazakhstan,KZ,KAZ,18551428,Asia,181.85123\r
-08/07/2020,8,7,2020,1376,0,Kazakhstan,KZ,KAZ,18551428,Asia,174.07824346\r
-07/07/2020,7,7,2020,1109,76,Kazakhstan,KZ,KAZ,18551428,Asia,169.5395093\r
-06/07/2020,6,7,2020,1403,0,Kazakhstan,KZ,KAZ,18551428,Asia,166.25135273\r
-05/07/2020,5,7,2020,1452,0,Kazakhstan,KZ,KAZ,18551428,Asia,161.42153585\r
-04/07/2020,4,7,2020,1644,0,Kazakhstan,KZ,KAZ,18551428,Asia,155.99877271\r
-03/07/2020,3,7,2020,1501,0,Kazakhstan,KZ,KAZ,18551428,Asia,149.44402124\r
-02/07/2020,2,7,2020,1509,0,Kazakhstan,KZ,KAZ,18551428,Asia,143.90805926\r
-01/07/2020,1,7,2020,19246,0,Kazakhstan,KZ,KAZ,18551428,Asia,137.57970545\r
-30/06/2020,30,6,2020,492,5,Kazakhstan,KZ,KAZ,18551428,Asia,35.72231744\r
-29/06/2020,29,6,2020,547,10,Kazakhstan,KZ,KAZ,18551428,Asia,35.13476159\r
-28/06/2020,28,6,2020,461,23,Kazakhstan,KZ,KAZ,18551428,Asia,33.87340317\r
-27/06/2020,27,6,2020,569,3,Kazakhstan,KZ,KAZ,18551428,Asia,32.77914778\r
-26/06/2020,26,6,2020,465,11,Kazakhstan,KZ,KAZ,18551428,Asia,31.6848924\r
-25/06/2020,25,6,2020,520,2,Kazakhstan,KZ,KAZ,18551428,Asia,30.87093888\r
-24/06/2020,24,6,2020,534,7,Kazakhstan,KZ,KAZ,18551428,Asia,29.35623069\r
-23/06/2020,23,6,2020,499,7,Kazakhstan,KZ,KAZ,18551428,Asia,27.79839913\r
-22/06/2020,22,6,2020,507,2,Kazakhstan,KZ,KAZ,18551428,Asia,26.26751968\r
-21/06/2020,21,6,2020,446,5,Kazakhstan,KZ,KAZ,18551428,Asia,24.42399582\r
-20/06/2020,20,6,2020,428,8,Kazakhstan,KZ,KAZ,18551428,Asia,23.0063152\r
-19/06/2020,19,6,2020,474,5,Kazakhstan,KZ,KAZ,18551428,Asia,21.77190888\r
-18/06/2020,18,6,2020,335,12,Kazakhstan,KZ,KAZ,18551428,Asia,20.53750256\r
-17/06/2020,17,6,2020,350,7,Kazakhstan,KZ,KAZ,18551428,Asia,20.19251564\r
-16/06/2020,16,6,2020,383,4,Kazakhstan,KZ,KAZ,18551428,Asia,19.51871306\r
-15/06/2020,15,6,2020,313,4,Kazakhstan,KZ,KAZ,18551428,Asia,18.87186259\r
-14/06/2020,14,6,2020,258,3,Kazakhstan,KZ,KAZ,18551428,Asia,19.61035021\r
-13/06/2020,13,6,2020,366,3,Kazakhstan,KZ,KAZ,18551428,Asia,20.78546191\r
-12/06/2020,12,6,2020,314,0,Kazakhstan,KZ,KAZ,18551428,Asia,21.23825724\r
-11/06/2020,11,6,2020,239,6,Kazakhstan,KZ,KAZ,18551428,Asia,21.4646549\r
-10/06/2020,10,6,2020,245,3,Kazakhstan,KZ,KAZ,18551428,Asia,21.64253878\r
-09/06/2020,9,6,2020,215,2,Kazakhstan,KZ,KAZ,18551428,Asia,22.12767664\r
-08/06/2020,8,6,2020,165,3,Kazakhstan,KZ,KAZ,18551428,Asia,23.32974044\r
-07/06/2020,7,6,2020,183,1,Kazakhstan,KZ,KAZ,18551428,Asia,23.56691895\r
-06/06/2020,6,6,2020,199,0,Kazakhstan,KZ,KAZ,18551428,Asia,24.75281148\r
-05/06/2020,5,6,2020,245,4,Kazakhstan,KZ,KAZ,18551428,Asia,25.41583322\r
-04/06/2020,4,6,2020,271,4,Kazakhstan,KZ,KAZ,18551428,Asia,26.05190285\r
-03/06/2020,3,6,2020,225,3,Kazakhstan,KZ,KAZ,18551428,Asia,26.01956033\r
-02/06/2020,2,6,2020,263,0,Kazakhstan,KZ,KAZ,18551428,Asia,25.98182738\r
-01/06/2020,1,6,2020,450,3,Kazakhstan,KZ,KAZ,18551428,Asia,26.24056757\r
-31/05/2020,31,5,2020,476,1,Kazakhstan,KZ,KAZ,18551428,Asia,25.34036733\r
-30/05/2020,30,5,2020,450,0,Kazakhstan,KZ,KAZ,18551428,Asia,24.42938624\r
-29/05/2020,29,5,2020,356,0,Kazakhstan,KZ,KAZ,18551428,Asia,23.50762432\r
-28/05/2020,28,5,2020,272,0,Kazakhstan,KZ,KAZ,18551428,Asia,21.58863458\r
-27/05/2020,27,5,2020,335,2,Kazakhstan,KZ,KAZ,18551428,Asia,20.95256495\r
-26/05/2020,26,5,2020,438,0,Kazakhstan,KZ,KAZ,18551428,Asia,20.10087849\r
-25/05/2020,25,5,2020,209,0,Kazakhstan,KZ,KAZ,18551428,Asia,18.35438221\r
-24/05/2020,24,5,2020,403,0,Kazakhstan,KZ,KAZ,18551428,Asia,17.71292215\r
-23/05/2020,23,5,2020,322,0,Kazakhstan,KZ,KAZ,18551428,Asia,16.62944761\r
-22/05/2020,22,5,2020,363,0,Kazakhstan,KZ,KAZ,18551428,Asia,15.66995274\r
-21/05/2020,21,5,2020,265,0,Kazakhstan,KZ,KAZ,18551428,Asia,14.72662913\r
-20/05/2020,20,5,2020,218,0,Kazakhstan,KZ,KAZ,18551428,Asia,14.51101231\r
-19/05/2020,19,5,2020,311,1,Kazakhstan,KZ,KAZ,18551428,Asia,14.17680623\r
-18/05/2020,18,5,2020,283,0,Kazakhstan,KZ,KAZ,18551428,Asia,13.34668145\r
-17/05/2020,17,5,2020,307,0,Kazakhstan,KZ,KAZ,18551428,Asia,12.29015901\r
-16/05/2020,16,5,2020,279,2,Kazakhstan,KZ,KAZ,18551428,Asia,11.74572653\r
-15/05/2020,15,5,2020,0,0,Kazakhstan,KZ,KAZ,18551428,Asia,11.14199942\r
-14/05/2020,14,5,2020,154,0,Kazakhstan,KZ,KAZ,18551428,Asia,12.75373518\r
-13/05/2020,13,5,2020,177,0,Kazakhstan,KZ,KAZ,18551428,Asia,12.68905014\r
-12/05/2020,12,5,2020,114,1,Kazakhstan,KZ,KAZ,18551428,Asia,12.82920107\r
-11/05/2020,11,5,2020,90,0,Kazakhstan,KZ,KAZ,18551428,Asia,12.98552327\r
-10/05/2020,10,5,2020,202,0,Kazakhstan,KZ,KAZ,18551428,Asia,12.85076276\r
-09/05/2020,9,5,2020,144,0,Kazakhstan,KZ,KAZ,18551428,Asia,12.6782693\r
-08/05/2020,8,5,2020,188,1,Kazakhstan,KZ,KAZ,18551428,Asia,12.69983098\r
-07/05/2020,7,5,2020,225,1,Kazakhstan,KZ,KAZ,18551428,Asia,12.45726205\r
-06/05/2020,6,5,2020,156,0,Kazakhstan,KZ,KAZ,18551428,Asia,12.13922723\r
-05/05/2020,5,5,2020,157,2,Kazakhstan,KZ,KAZ,18551428,Asia,11.70799358\r
-04/05/2020,4,5,2020,87,2,Kazakhstan,KZ,KAZ,18551428,Asia,12.01524756\r
-03/05/2020,3,5,2020,206,0,Kazakhstan,KZ,KAZ,18551428,Asia,11.98290504\r
-02/05/2020,2,5,2020,167,0,Kazakhstan,KZ,KAZ,18551428,Asia,11.21207489\r
-01/05/2020,1,5,2020,299,0,Kazakhstan,KZ,KAZ,18551428,Asia,10.96411554\r
-30/04/2020,30,4,2020,142,0,Kazakhstan,KZ,KAZ,18551428,Asia,10.10164824\r
-29/04/2020,29,4,2020,203,0,Kazakhstan,KZ,KAZ,18551428,Asia,9.68119543\r
-28/04/2020,28,4,2020,143,0,Kazakhstan,KZ,KAZ,18551428,Asia,9.06129706\r
-27/04/2020,27,4,2020,65,0,Kazakhstan,KZ,KAZ,18551428,Asia,9.46557861\r
-26/04/2020,26,4,2020,170,0,Kazakhstan,KZ,KAZ,18551428,Asia,9.55182534\r
-25/04/2020,25,4,2020,148,3,Kazakhstan,KZ,KAZ,18551428,Asia,8.85107066\r
-24/04/2020,24,4,2020,143,3,Kazakhstan,KZ,KAZ,18551428,Asia,8.25812439\r
-23/04/2020,23,4,2020,166,0,Kazakhstan,KZ,KAZ,18551428,Asia,7.71908233\r
-22/04/2020,22,4,2020,76,0,Kazakhstan,KZ,KAZ,18551428,Asia,7.12074564\r
-21/04/2020,21,4,2020,214,0,Kazakhstan,KZ,KAZ,18551428,Asia,6.89434797\r
-20/04/2020,20,4,2020,81,2,Kazakhstan,KZ,KAZ,18551428,Asia,6.49006643\r
-19/04/2020,19,4,2020,63,0,Kazakhstan,KZ,KAZ,18551428,Asia,6.43616222\r
-18/04/2020,18,4,2020,121,0,Kazakhstan,KZ,KAZ,18551428,Asia,6.09656572\r
-17/04/2020,17,4,2020,139,1,Kazakhstan,KZ,KAZ,18551428,Asia,5.84321595\r
-16/04/2020,16,4,2020,64,2,Kazakhstan,KZ,KAZ,18551428,Asia,5.29878347\r
-15/04/2020,15,4,2020,88,0,Kazakhstan,KZ,KAZ,18551428,Asia,4.99691991\r
-14/04/2020,14,4,2020,218,4,Kazakhstan,KZ,KAZ,18551428,Asia,4.60341921\r
-13/04/2020,13,4,2020,81,0,Kazakhstan,KZ,KAZ,18551428,Asia,3.64931476\r
-12/04/2020,12,4,2020,40,0,Kazakhstan,KZ,KAZ,18551428,Asia,3.50916382\r
-11/04/2020,11,4,2020,38,1,Kazakhstan,KZ,KAZ,18551428,Asia,3.48760214\r
-10/04/2020,10,4,2020,43,2,Kazakhstan,KZ,KAZ,18551428,Asia,3.67626686\r
-09/04/2020,9,4,2020,55,1,Kazakhstan,KZ,KAZ,18551428,Asia,3.61697224\r
-08/04/2020,8,4,2020,34,0,Kazakhstan,KZ,KAZ,18551428,Asia,3.36901289\r
-07/04/2020,7,4,2020,139,1,Kazakhstan,KZ,KAZ,18551428,Asia,3.27737574\r
-06/04/2020,6,4,2020,71,2,Kazakhstan,KZ,KAZ,18551428,Asia,2.53888811\r
-05/04/2020,5,4,2020,0,0,Kazakhstan,KZ,KAZ,18551428,Asia,2.17772993\r
-04/04/2020,4,4,2020,74,0,Kazakhstan,KZ,KAZ,18551428,Asia,2.19390119\r
-03/04/2020,3,4,2020,38,1,Kazakhstan,KZ,KAZ,18551428,Asia,1.81657175\r
-02/04/2020,2,4,2020,8,1,Kazakhstan,KZ,KAZ,18551428,Asia,1.67642081\r
-01/04/2020,1,4,2020,15,0,Kazakhstan,KZ,KAZ,18551428,Asia,1.65485913\r
-31/03/2020,31,3,2020,41,0,Kazakhstan,KZ,KAZ,18551428,Asia,1.69259207\r
-30/03/2020,30,3,2020,55,1,Kazakhstan,KZ,KAZ,18551428,Asia,1.48236567\r
-29/03/2020,29,3,2020,36,0,Kazakhstan,KZ,KAZ,18551428,Asia,1.2020638\r
-28/03/2020,28,3,2020,73,0,Kazakhstan,KZ,KAZ,18551428,Asia,1.04035118\r
-27/03/2020,27,3,2020,32,0,Kazakhstan,KZ,KAZ,18551428,Asia,\r
-26/03/2020,26,3,2020,9,0,Kazakhstan,KZ,KAZ,18551428,Asia,\r
-25/03/2020,25,3,2020,17,0,Kazakhstan,KZ,KAZ,18551428,Asia,\r
-24/03/2020,24,3,2020,2,0,Kazakhstan,KZ,KAZ,18551428,Asia,\r
-23/03/2020,23,3,2020,4,0,Kazakhstan,KZ,KAZ,18551428,Asia,\r
-22/03/2020,22,3,2020,3,0,Kazakhstan,KZ,KAZ,18551428,Asia,\r
-21/03/2020,21,3,2020,4,0,Kazakhstan,KZ,KAZ,18551428,Asia,\r
-20/03/2020,20,3,2020,12,0,Kazakhstan,KZ,KAZ,18551428,Asia,\r
-19/03/2020,19,3,2020,4,0,Kazakhstan,KZ,KAZ,18551428,Asia,\r
-18/03/2020,18,3,2020,22,0,Kazakhstan,KZ,KAZ,18551428,Asia,\r
-17/03/2020,17,3,2020,2,0,Kazakhstan,KZ,KAZ,18551428,Asia,\r
-16/03/2020,16,3,2020,3,0,Kazakhstan,KZ,KAZ,18551428,Asia,\r
-15/03/2020,15,3,2020,6,0,Kazakhstan,KZ,KAZ,18551428,Asia,\r
-19/08/2020,19,8,2020,271,5,Kenya,KE,KEN,52573967,Africa,14.14007811\r
-18/08/2020,18,8,2020,245,8,Kenya,KE,KEN,52573967,Africa,14.77537352\r
-17/08/2020,17,8,2020,271,2,Kenya,KE,KEN,52573967,Africa,15.34409606\r
-16/08/2020,16,8,2020,515,7,Kenya,KE,KEN,52573967,Africa,16.14106845\r
-15/08/2020,15,8,2020,580,5,Kenya,KE,KEN,52573967,Africa,16.54430985\r
-14/08/2020,14,8,2020,650,4,Kenya,KE,KEN,52573967,Africa,16.81630758\r
-13/08/2020,13,8,2020,679,18,Kenya,KE,KEN,52573967,Africa,17.07879491\r
-12/08/2020,12,8,2020,497,15,Kenya,KE,KEN,52573967,Africa,16.82201383\r
-11/08/2020,11,8,2020,492,3,Kenya,KE,KEN,52573967,Africa,17.02934078\r
-10/08/2020,10,8,2020,599,2,Kenya,KE,KEN,52573967,Africa,16.80109093\r
-09/08/2020,9,8,2020,699,5,Kenya,KE,KEN,52573967,Africa,17.48774256\r
-08/08/2020,8,8,2020,727,14,Kenya,KE,KEN,52573967,Africa,16.87146796\r
-07/08/2020,7,8,2020,538,8,Kenya,KE,KEN,52573967,Africa,16.75734304\r
-06/08/2020,6,8,2020,671,3,Kenya,KE,KEN,52573967,Africa,17.24808021\r
-05/08/2020,5,8,2020,605,6,Kenya,KE,KEN,52573967,Africa,17.18340942\r
-04/08/2020,4,8,2020,544,13,Kenya,KE,KEN,52573967,Africa,16.78777635\r
-03/08/2020,3,8,2020,690,5,Kenya,KE,KEN,52573967,Africa,16.54811401\r
-02/08/2020,2,8,2020,727,23,Kenya,KE,KEN,52573967,Africa,16.38263287\r
-01/08/2020,1,8,2020,723,16,Kenya,KE,KEN,52573967,Africa,16.30845167\r
-31/07/2020,31,7,2020,788,14,Kenya,KE,KEN,52573967,Africa,15.67315626\r
-30/07/2020,30,7,2020,544,12,Kenya,KE,KEN,52573967,Africa,14.97509214\r
-29/07/2020,29,7,2020,606,14,Kenya,KE,KEN,52573967,Africa,14.81721933\r
-28/07/2020,28,7,2020,372,5,Kenya,KE,KEN,52573967,Africa,14.60989238\r
-27/07/2020,27,7,2020,960,2,Kenya,KE,KEN,52573967,Africa,14.26181136\r
-26/07/2020,26,7,2020,375,4,Kenya,KE,KEN,52573967,Africa,13.15670168\r
-25/07/2020,25,7,2020,667,11,Kenya,KE,KEN,52573967,Africa,12.97219972\r
-24/07/2020,24,7,2020,796,3,Kenya,KE,KEN,52573967,Africa,12.6031958\r
-23/07/2020,23,7,2020,637,10,Kenya,KE,KEN,52573967,Africa,11.93936916\r
-22/07/2020,22,7,2020,397,12,Kenya,KE,KEN,52573967,Africa,11.25652169\r
-21/07/2020,21,7,2020,418,4,Kenya,KE,KEN,52573967,Africa,10.84947613\r
-20/07/2020,20,7,2020,603,9,Kenya,KE,KEN,52573967,Africa,10.39868268\r
-19/07/2020,19,7,2020,688,3,Kenya,KE,KEN,52573967,Africa,9.83947055\r
-18/07/2020,18,7,2020,389,9,Kenya,KE,KEN,52573967,Africa,9.27074801\r
-17/07/2020,17,7,2020,421,4,Kenya,KE,KEN,52573967,Africa,9.00065236\r
-16/07/2020,16,7,2020,461,7,Kenya,KE,KEN,52573967,Africa,8.7096338\r
-15/07/2020,15,7,2020,497,5,Kenya,KE,KEN,52573967,Africa,8.41671316\r
-14/07/2020,14,7,2020,189,12,Kenya,KE,KEN,52573967,Africa,7.80614482\r
-13/07/2020,13,7,2020,379,1,Kenya,KE,KEN,52573967,Africa,7.67490115\r
-12/07/2020,12,7,2020,278,3,Kenya,KE,KEN,52573967,Africa,7.44665131\r
-11/07/2020,11,7,2020,473,8,Kenya,KE,KEN,52573967,Africa,7.44665131\r
-10/07/2020,10,7,2020,447,4,Kenya,KE,KEN,52573967,Africa,6.83037671\r
-09/07/2020,9,7,2020,278,2,Kenya,KE,KEN,52573967,Africa,6.31871664\r
-08/07/2020,8,7,2020,183,3,Kenya,KE,KEN,52573967,Africa,6.27306667\r
-07/07/2020,7,7,2020,181,4,Kenya,KE,KEN,52573967,Africa,6.21980837\r
-06/07/2020,6,7,2020,309,1,Kenya,KE,KEN,52573967,Africa,5.98775436\r
-05/07/2020,5,7,2020,389,5,Kenya,KE,KEN,52573967,Africa,5.89455234\r
-04/07/2020,4,7,2020,247,2,Kenya,KE,KEN,52573967,Africa,5.35245895\r
-03/07/2020,3,7,2020,268,3,Kenya,KE,KEN,52573967,Africa,5.10518828\r
-02/07/2020,2,7,2020,307,1,Kenya,KE,KEN,52573967,Africa,5.00057376\r
-01/07/2020,1,7,2020,176,4,Kenya,KE,KEN,52573967,Africa,4.76661767\r
-30/06/2020,30,6,2020,120,1,Kenya,KE,KEN,52573967,Africa,4.68482814\r
-29/06/2020,29,6,2020,259,2,Kenya,KE,KEN,52573967,Africa,4.70955521\r
-28/06/2020,28,6,2020,278,4,Kenya,KE,KEN,52573967,Africa,4.47750119\r
-27/06/2020,27,6,2020,149,5,Kenya,KE,KEN,52573967,Africa,4.23783885\r
-26/06/2020,26,6,2020,178,2,Kenya,KE,KEN,52573967,Africa,4.12561601\r
-25/06/2020,25,6,2020,254,2,Kenya,KE,KEN,52573967,Africa,4.01719733\r
-24/06/2020,24,6,2020,155,3,Kenya,KE,KEN,52573967,Africa,3.7337871\r
-23/06/2020,23,6,2020,59,2,Kenya,KE,KEN,52573967,Africa,3.68052881\r
-22/06/2020,22,6,2020,260,2,Kenya,KE,KEN,52573967,Africa,3.74900376\r
-21/06/2020,21,6,2020,104,2,Kenya,KE,KEN,52573967,Africa,3.57211013\r
-20/06/2020,20,6,2020,117,2,Kenya,KE,KEN,52573967,Africa,3.61395593\r
-19/06/2020,19,6,2020,213,10,Kenya,KE,KEN,52573967,Africa,3.64629133\r
-18/06/2020,18,6,2020,184,2,Kenya,KE,KEN,52573967,Africa,3.47700602\r
-17/06/2020,17,6,2020,133,1,Kenya,KE,KEN,52573967,Africa,3.36097902\r
-16/06/2020,16,6,2020,133,1,Kenya,KE,KEN,52573967,Africa,3.24495201\r
-15/06/2020,15,6,2020,137,3,Kenya,KE,KEN,52573967,Africa,3.10419794\r
-14/06/2020,14,6,2020,152,4,Kenya,KE,KEN,52573967,Africa,2.98436677\r
-13/06/2020,13,6,2020,90,4,Kenya,KE,KEN,52573967,Africa,2.96724803\r
-12/06/2020,12,6,2020,121,3,Kenya,KE,KEN,52573967,Africa,3.03762507\r
-11/06/2020,11,6,2020,105,1,Kenya,KE,KEN,52573967,Africa,3.0870792\r
-10/06/2020,10,6,2020,127,3,Kenya,KE,KEN,52573967,Africa,3.12131668\r
-09/06/2020,9,6,2020,95,1,Kenya,KE,KEN,52573967,Africa,2.99768134\r
-08/06/2020,8,6,2020,167,1,Kenya,KE,KEN,52573967,Africa,2.95393346\r
-07/06/2020,7,6,2020,126,4,Kenya,KE,KEN,52573967,Africa,2.67813156\r
-06/06/2020,6,6,2020,134,1,Kenya,KE,KEN,52573967,Africa,2.49743376\r
-05/06/2020,5,6,2020,124,4,Kenya,KE,KEN,52573967,Africa,2.34146303\r
-04/06/2020,4,6,2020,123,3,Kenya,KE,KEN,52573967,Africa,2.25777142\r
-03/06/2020,3,6,2020,72,2,Kenya,KE,KEN,52573967,Africa,2.14935274\r
-02/06/2020,2,6,2020,59,5,Kenya,KE,KEN,52573967,Africa,2.10940902\r
-01/06/2020,1,6,2020,74,1,Kenya,KE,KEN,52573967,Africa,2.04473823\r
-31/05/2020,31,5,2020,143,1,Kenya,KE,KEN,52573967,Africa,2.01240283\r
-30/05/2020,30,5,2020,127,4,Kenya,KE,KEN,52573967,Africa,1.83360712\r
-29/05/2020,29,5,2020,147,3,Kenya,KE,KEN,52573967,Africa,1.63579058\r
-28/05/2020,28,5,2020,123,3,Kenya,KE,KEN,52573967,Africa,1.39612824\r
-27/05/2020,27,5,2020,62,0,Kenya,KE,KEN,52573967,Africa,1.20401795\r
-26/05/2020,26,5,2020,72,1,Kenya,KE,KEN,52573967,Africa,1.11462009\r
-25/05/2020,25,5,2020,22,1,Kenya,KE,KEN,52573967,Africa,1.03092848\r
-24/05/2020,24,5,2020,31,0,Kenya,KE,KEN,52573967,Africa,1.03283056\r
-23/05/2020,23,5,2020,52,0,Kenya,KE,KEN,52573967,Africa,1.02712432\r
-22/05/2020,22,5,2020,80,0,Kenya,KE,KEN,52573967,Africa,0.9548452\r
-21/05/2020,21,5,2020,66,0,Kenya,KE,KEN,52573967,Africa,0.85023069\r
-20/05/2020,20,5,2020,51,0,Kenya,KE,KEN,52573967,Africa,0.81409113\r
-19/05/2020,19,5,2020,25,0,Kenya,KE,KEN,52573967,Africa,0.80267863\r
-18/05/2020,18,5,2020,57,0,Kenya,KE,KEN,52573967,Africa,0.80267863\r
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-16/04/2020,16,4,2020,41,1,Kosovo,XK,XKX,1798506,Europe,17.01412172\r
-15/04/2020,15,4,2020,15,0,Kosovo,XK,XKX,1798506,Europe,15.45727398\r
-14/04/2020,14,4,2020,18,1,Kosovo,XK,XKX,1798506,Europe,15.01246034\r
-13/04/2020,13,4,2020,79,0,Kosovo,XK,XKX,1798506,Europe,14.67885011\r
-12/04/2020,12,4,2020,33,0,Kosovo,XK,XKX,1798506,Europe,10.45312053\r
-11/04/2020,11,4,2020,23,0,Kosovo,XK,XKX,1798506,Europe,8.78506939\r
-10/04/2020,10,4,2020,3,1,Kosovo,XK,XKX,1798506,Europe,7.8398404\r
-09/04/2020,9,4,2020,14,1,Kosovo,XK,XKX,1798506,Europe,8.50706086\r
-08/04/2020,8,4,2020,19,2,Kosovo,XK,XKX,1798506,Europe,8.17345063\r
-07/04/2020,7,4,2020,26,2,Kosovo,XK,XKX,1798506,Europe,7.22822165\r
-06/04/2020,6,4,2020,10,0,Kosovo,XK,XKX,1798506,Europe,7.33942506\r
-05/04/2020,5,4,2020,8,0,Kosovo,XK,XKX,1798506,Europe,6.89461142\r
-04/04/2020,4,4,2020,9,0,Kosovo,XK,XKX,1798506,Europe,6.83900971\r
-03/04/2020,3,4,2020,8,0,Kosovo,XK,XKX,1798506,Europe,6.50539948\r
-02/04/2020,2,4,2020,13,0,Kosovo,XK,XKX,1798506,Europe,6.11618755\r
-01/04/2020,1,4,2020,7,0,Kosovo,XK,XKX,1798506,Europe,5.44896709\r
-31/03/2020,31,3,2020,12,0,Kosovo,XK,XKX,1798506,Europe,5.22656027\r
-30/03/2020,30,3,2020,3,0,Kosovo,XK,XKX,1798506,Europe,4.72614492\r
-29/03/2020,29,3,2020,3,0,Kosovo,XK,XKX,1798506,Europe,5.00415345\r
-28/03/2020,28,3,2020,6,0,Kosovo,XK,XKX,1798506,Europe,5.00415345\r
-27/03/2020,27,3,2020,15,0,Kosovo,XK,XKX,1798506,Europe,4.78174663\r
-26/03/2020,26,3,2020,8,0,Kosovo,XK,XKX,1798506,Europe,\r
-25/03/2020,25,3,2020,2,0,Kosovo,XK,XKX,1798506,Europe,\r
-24/03/2020,24,3,2020,28,0,Kosovo,XK,XKX,1798506,Europe,\r
-23/03/2020,23,3,2020,2,1,Kosovo,XK,XKX,1798506,Europe,\r
-22/03/2020,22,3,2020,7,0,Kosovo,XK,XKX,1798506,Europe,\r
-21/03/2020,21,3,2020,3,0,Kosovo,XK,XKX,1798506,Europe,\r
-20/03/2020,20,3,2020,1,0,Kosovo,XK,XKX,1798506,Europe,\r
-19/03/2020,19,3,2020,1,0,Kosovo,XK,XKX,1798506,Europe,\r
-18/03/2020,18,3,2020,3,0,Kosovo,XK,XKX,1798506,Europe,\r
-17/03/2020,17,3,2020,3,0,Kosovo,XK,XKX,1798506,Europe,\r
-16/03/2020,16,3,2020,8,0,Kosovo,XK,XKX,1798506,Europe,\r
-15/03/2020,15,3,2020,3,0,Kosovo,XK,XKX,1798506,Europe,\r
-14/03/2020,14,3,2020,2,0,Kosovo,XK,XKX,1798506,Europe,\r
-19/08/2020,19,8,2020,643,3,Kuwait,KW,KWT,4207077,Asia,206.69933068\r
-18/08/2020,18,8,2020,622,1,Kuwait,KW,KWT,4207077,Asia,202.70605934\r
-17/08/2020,17,8,2020,508,3,Kuwait,KW,KWT,4207077,Asia,197.14400283\r
-16/08/2020,16,8,2020,512,4,Kuwait,KW,KWT,4207077,Asia,196.07437658\r
-15/08/2020,15,8,2020,699,5,Kuwait,KW,KWT,4207077,Asia,195.57521766\r
-14/08/2020,14,8,2020,701,0,Kuwait,KW,KWT,4207077,Asia,189.13369068\r
-13/08/2020,13,8,2020,717,3,Kuwait,KW,KWT,4207077,Asia,187.35098026\r
-12/08/2020,12,8,2020,668,4,Kuwait,KW,KWT,4207077,Asia,188.23045074\r
-11/08/2020,11,8,2020,687,4,Kuwait,KW,KWT,4207077,Asia,190.65493691\r
-10/08/2020,10,8,2020,514,4,Kuwait,KW,KWT,4207077,Asia,188.72960966\r
-09/08/2020,9,8,2020,472,3,Kuwait,KW,KWT,4207077,Asia,187.54113604\r
-08/08/2020,8,8,2020,682,2,Kuwait,KW,KWT,4207077,Asia,192.58026416\r
-07/08/2020,7,8,2020,620,1,Kuwait,KW,KWT,4207077,Asia,194.26789669\r
-06/08/2020,6,8,2020,651,3,Kuwait,KW,KWT,4207077,Asia,195.86045133\r
-05/08/2020,5,8,2020,475,4,Kuwait,KW,KWT,4207077,Asia,198.23739855\r
-04/08/2020,4,8,2020,388,4,Kuwait,KW,KWT,4207077,Asia,202.89621512\r
-03/08/2020,3,8,2020,463,4,Kuwait,KW,KWT,4207077,Asia,206.96079487\r
-02/08/2020,2,8,2020,491,6,Kuwait,KW,KWT,4207077,Asia,203.08637089\r
-01/08/2020,1,8,2020,428,2,Kuwait,KW,KWT,4207077,Asia,207.65010957\r
-31/07/2020,31,7,2020,626,1,Kuwait,KW,KWT,4207077,Asia,210.6212936\r
-30/07/2020,30,7,2020,754,2,Kuwait,KW,KWT,4207077,Asia,214.54325652\r
-29/07/2020,29,7,2020,770,4,Kuwait,KW,KWT,4207077,Asia,213.33101343\r
-28/07/2020,28,7,2020,606,5,Kuwait,KW,KWT,4207077,Asia,210.85898832\r
-27/07/2020,27,7,2020,464,4,Kuwait,KW,KWT,4207077,Asia,211.0491441\r
-26/07/2020,26,7,2020,684,4,Kuwait,KW,KWT,4207077,Asia,219.89138777\r
-25/07/2020,25,7,2020,753,4,Kuwait,KW,KWT,4207077,Asia,214.99487649\r
-24/07/2020,24,7,2020,687,4,Kuwait,KW,KWT,4207077,Asia,214.68587335\r
-23/07/2020,23,7,2020,751,5,Kuwait,KW,KWT,4207077,Asia,218.1562163\r
-22/07/2020,22,7,2020,671,4,Kuwait,KW,KWT,4207077,Asia,218.41768049\r
-21/07/2020,21,7,2020,559,0,Kuwait,KW,KWT,4207077,Asia,216.75381744\r
-20/07/2020,20,7,2020,300,1,Kuwait,KW,KWT,4207077,Asia,220.17662144\r
-19/07/2020,19,7,2020,683,3,Kuwait,KW,KWT,4207077,Asia,228.21070306\r
-18/07/2020,18,7,2020,553,2,Kuwait,KW,KWT,4207077,Asia,226.9746905\r
-17/07/2020,17,7,2020,791,3,Kuwait,KW,KWT,4207077,Asia,233.15475329\r
-16/07/2020,16,7,2020,703,3,Kuwait,KW,KWT,4207077,Asia,236.19724574\r
-15/07/2020,15,7,2020,666,3,Kuwait,KW,KWT,4207077,Asia,237.19556357\r
-14/07/2020,14,7,2020,614,3,Kuwait,KW,KWT,4207077,Asia,237.31441093\r
-13/07/2020,13,7,2020,836,4,Kuwait,KW,KWT,4207077,Asia,236.55378782\r
-12/07/2020,12,7,2020,478,3,Kuwait,KW,KWT,4207077,Asia,229.77948823\r
-11/07/2020,11,7,2020,740,1,Kuwait,KW,KWT,4207077,Asia,234.7710774\r
-10/07/2020,10,7,2020,833,3,Kuwait,KW,KWT,4207077,Asia,238.93073504\r
-09/07/2020,9,7,2020,762,2,Kuwait,KW,KWT,4207077,Asia,240.73721494\r
-08/07/2020,8,7,2020,601,4,Kuwait,KW,KWT,4207077,Asia,242.7338506\r
-07/07/2020,7,7,2020,703,5,Kuwait,KW,KWT,4207077,Asia,246.08534619\r
-06/07/2020,6,7,2020,638,3,Kuwait,KW,KWT,4207077,Asia,244.61163891\r
-05/07/2020,5,7,2020,631,5,Kuwait,KW,KWT,4207077,Asia,241.4502991\r
-04/07/2020,4,7,2020,813,1,Kuwait,KW,KWT,4207077,Asia,237.55210565\r
-03/07/2020,3,7,2020,919,1,Kuwait,KW,KWT,4207077,Asia,232.58428595\r
-02/07/2020,2,7,2020,745,4,Kuwait,KW,KWT,4207077,Asia,223.59942544\r
-01/07/2020,1,7,2020,671,4,Kuwait,KW,KWT,4207077,Asia,219.55861516\r
-30/06/2020,30,6,2020,582,2,Kuwait,KW,KWT,4207077,Asia,216.13581116\r
-29/06/2020,29,6,2020,551,4,Kuwait,KW,KWT,4207077,Asia,214.44817863\r
-28/06/2020,28,6,2020,688,3,Kuwait,KW,KWT,4207077,Asia,212.14253982\r
-27/06/2020,27,6,2020,915,2,Kuwait,KW,KWT,4207077,Asia,208.00665165\r
-26/06/2020,26,6,2020,909,2,Kuwait,KW,KWT,4207077,Asia,198.61771011\r
-25/06/2020,25,6,2020,846,3,Kuwait,KW,KWT,4207077,Asia,191.48686844\r
-24/06/2020,24,6,2020,742,4,Kuwait,KW,KWT,4207077,Asia,187.61244446\r
-23/06/2020,23,6,2020,641,4,Kuwait,KW,KWT,4207077,Asia,184.95026357\r
-22/06/2020,22,6,2020,505,7,Kuwait,KW,KWT,4207077,Asia,185.44942249\r
-21/06/2020,21,6,2020,467,6,Kuwait,KW,KWT,4207077,Asia,190.4885506\r
-20/06/2020,20,6,2020,604,5,Kuwait,KW,KWT,4207077,Asia,190.96394005\r
-19/06/2020,19,6,2020,541,2,Kuwait,KW,KWT,4207077,Asia,193.79250724\r
-18/06/2020,18,6,2020,575,3,Kuwait,KW,KWT,4207077,Asia,194.29166616\r
-17/06/2020,17,6,2020,527,5,Kuwait,KW,KWT,4207077,Asia,197.50054492\r
-16/06/2020,16,6,2020,511,2,Kuwait,KW,KWT,4207077,Asia,206.05755492\r
-15/06/2020,15,6,2020,454,7,Kuwait,KW,KWT,4207077,Asia,211.00160515\r
-14/06/2020,14,6,2020,514,4,Kuwait,KW,KWT,4207077,Asia,220.43808564\r
-13/06/2020,13,6,2020,520,6,Kuwait,KW,KWT,4207077,Asia,232.18020493\r
-12/06/2020,12,6,2020,609,4,Kuwait,KW,KWT,4207077,Asia,245.30095361\r
-11/06/2020,11,6,2020,683,2,Kuwait,KW,KWT,4207077,Asia,250.91054906\r
-10/06/2020,10,6,2020,630,4,Kuwait,KW,KWT,4207077,Asia,251.12447431\r
-09/06/2020,9,6,2020,662,5,Kuwait,KW,KWT,4207077,Asia,250.60154592\r
-08/06/2020,8,6,2020,717,10,Kuwait,KW,KWT,4207077,Asia,250.67285434\r
-07/06/2020,7,6,2020,487,10,Kuwait,KW,KWT,4207077,Asia,253.54896048\r
-06/06/2020,6,6,2020,723,8,Kuwait,KW,KWT,4207077,Asia,263.36575252\r
-05/06/2020,5,6,2020,562,6,Kuwait,KW,KWT,4207077,Asia,268.88027008\r
-04/06/2020,4,6,2020,710,4,Kuwait,KW,KWT,4207077,Asia,280.26584729\r
-03/06/2020,3,6,2020,887,6,Kuwait,KW,KWT,4207077,Asia,282.50017768\r
-02/06/2020,2,6,2020,719,8,Kuwait,KW,KWT,4207077,Asia,286.92129952\r
-01/06/2020,1,6,2020,851,7,Kuwait,KW,KWT,4207077,Asia,289.82117513\r
-31/05/2020,31,5,2020,1008,11,Kuwait,KW,KWT,4207077,Asia,294.50376116\r
-30/05/2020,30,5,2020,1072,9,Kuwait,KW,KWT,4207077,Asia,292.93497599\r
-29/05/2020,29,5,2020,845,10,Kuwait,KW,KWT,4207077,Asia,288.49008468\r
-28/05/2020,28,5,2020,692,3,Kuwait,KW,KWT,4207077,Asia,290.91457085\r
-27/05/2020,27,5,2020,608,7,Kuwait,KW,KWT,4207077,Asia,292.31696972\r
-26/05/2020,26,5,2020,665,9,Kuwait,KW,KWT,4207077,Asia,301.42067759\r
-25/05/2020,25,5,2020,838,8,Kuwait,KW,KWT,4207077,Asia,299.82812295\r
-24/05/2020,24,5,2020,900,10,Kuwait,KW,KWT,4207077,Asia,305.22379315\r
-23/05/2020,23,5,2020,955,9,Kuwait,KW,KWT,4207077,Asia,293.69559911\r
-22/05/2020,22,5,2020,1041,5,Kuwait,KW,KWT,4207077,Asia,286.23198482\r
-21/05/2020,21,5,2020,804,3,Kuwait,KW,KWT,4207077,Asia,268.09587749\r
-20/05/2020,20,5,2020,1073,3,Kuwait,KW,KWT,4207077,Asia,260.51341585\r
-19/05/2020,19,5,2020,841,6,Kuwait,KW,KWT,4207077,Asia,247.51151453\r
-18/05/2020,18,5,2020,1048,5,Kuwait,KW,KWT,4207077,Asia,234.53338268\r
-17/05/2020,17,5,2020,942,11,Kuwait,KW,KWT,4207077,Asia,218.27506366\r
-16/05/2020,16,5,2020,885,8,Kuwait,KW,KWT,4207077,Asia,201.63643309\r
-15/05/2020,15,5,2020,947,6,Kuwait,KW,KWT,4207077,Asia,188.99107385\r
-14/05/2020,14,5,2020,751,7,Kuwait,KW,KWT,4207077,Asia,173.23191375\r
-13/05/2020,13,5,2020,991,10,Kuwait,KW,KWT,4207077,Asia,162.51188176\r
-12/05/2020,12,5,2020,598,7,Kuwait,KW,KWT,4207077,Asia,142.56929455\r
-11/05/2020,11,5,2020,1065,9,Kuwait,KW,KWT,4207077,Asia,133.41804773\r
-10/05/2020,10,5,2020,415,2,Kuwait,KW,KWT,4207077,Asia,112.45337321\r
-09/05/2020,9,5,2020,641,3,Kuwait,KW,KWT,4207077,Asia,109.19695551\r
-08/05/2020,8,5,2020,278,2,Kuwait,KW,KWT,4207077,Asia,99.07116033\r
-07/05/2020,7,5,2020,485,2,Kuwait,KW,KWT,4207077,Asia,96.05243736\r
-06/05/2020,6,5,2020,526,0,Kuwait,KW,KWT,4207077,Asia,88.51751465\r
-05/05/2020,5,5,2020,295,2,Kuwait,KW,KWT,4207077,Asia,78.03517739\r
-04/05/2020,4,5,2020,364,5,Kuwait,KW,KWT,4207077,Asia,72.92474086\r
-03/05/2020,3,5,2020,242,3,Kuwait,KW,KWT,4207077,Asia,68.14707694\r
-02/05/2020,2,5,2020,353,4,Kuwait,KW,KWT,4207077,Asia,64.62919504\r
-01/05/2020,1,5,2020,284,2,Kuwait,KW,KWT,4207077,Asia,59.42368062\r
-30/04/2020,30,4,2020,300,1,Kuwait,KW,KWT,4207077,Asia,55.5017177\r
-29/04/2020,29,4,2020,152,1,Kuwait,KW,KWT,4207077,Asia,49.55934964\r
-28/04/2020,28,4,2020,213,2,Kuwait,KW,KWT,4207077,Asia,47.25371083\r
-27/04/2020,27,4,2020,183,1,Kuwait,KW,KWT,4207077,Asia,43.75959841\r
-26/04/2020,26,4,2020,278,4,Kuwait,KW,KWT,4207077,Asia,41.31134277\r
-25/04/2020,25,4,2020,215,1,Kuwait,KW,KWT,4207077,Asia,38.53031452\r
-24/04/2020,24,4,2020,151,1,Kuwait,KW,KWT,4207077,Asia,35.39274418\r
-23/04/2020,23,4,2020,168,2,Kuwait,KW,KWT,4207077,Asia,33.11087484\r
-22/04/2020,22,4,2020,85,2,Kuwait,KW,KWT,4207077,Asia,31.7797844\r
-21/04/2020,21,4,2020,80,2,Kuwait,KW,KWT,4207077,Asia,31.61339809\r
-20/04/2020,20,4,2020,163,1,Kuwait,KW,KWT,4207077,Asia,32.30271279\r
-19/04/2020,19,4,2020,94,1,Kuwait,KW,KWT,4207077,Asia,30.25853817\r
-18/04/2020,18,4,2020,134,2,Kuwait,KW,KWT,4207077,Asia,31.28062548\r
-17/04/2020,17,4,2020,119,0,Kuwait,KW,KWT,4207077,Asia,28.0955162\r
-16/04/2020,16,4,2020,50,0,Kuwait,KW,KWT,4207077,Asia,25.86118581\r
-15/04/2020,15,4,2020,55,1,Kuwait,KW,KWT,4207077,Asia,25.33825742\r
-14/04/2020,14,4,2020,66,1,Kuwait,KW,KWT,4207077,Asia,24.57763431\r
-13/04/2020,13,4,2020,80,0,Kuwait,KW,KWT,4207077,Asia,23.27031333\r
-12/04/2020,12,4,2020,161,0,Kuwait,KW,KWT,4207077,Asia,21.844145\r
-11/04/2020,11,4,2020,83,0,Kuwait,KW,KWT,4207077,Asia,18.25495469\r
-10/04/2020,10,4,2020,55,0,Kuwait,KW,KWT,4207077,Asia,16.68616952\r
-09/04/2020,9,4,2020,112,0,Kuwait,KW,KWT,4207077,Asia,15.68785168\r
-08/04/2020,8,4,2020,78,0,Kuwait,KW,KWT,4207077,Asia,13.12074868\r
-07/04/2020,7,4,2020,109,0,Kuwait,KW,KWT,4207077,Asia,11.31426879\r
-06/04/2020,6,4,2020,77,0,Kuwait,KW,KWT,4207077,Asia,8.74716579\r
-05/04/2020,5,4,2020,137,1,Kuwait,KW,KWT,4207077,Asia,7.20215009\r
-04/04/2020,4,4,2020,0,0,Kuwait,KW,KWT,4207077,Asia,4.34981342\r
-03/04/2020,3,4,2020,25,0,Kuwait,KW,KWT,4207077,Asia,4.61127762\r
-02/04/2020,2,4,2020,28,0,Kuwait,KW,KWT,4207077,Asia,4.15965764\r
-01/04/2020,1,4,2020,23,0,Kuwait,KW,KWT,4207077,Asia,3.77934609\r
-31/03/2020,31,3,2020,11,0,Kuwait,KW,KWT,4207077,Asia,3.39903453\r
-30/03/2020,30,3,2020,20,0,Kuwait,KW,KWT,4207077,Asia,3.39903453\r
-29/03/2020,29,3,2020,10,0,Kuwait,KW,KWT,4207077,Asia,3.11380086\r
-28/03/2020,28,3,2020,17,0,Kuwait,KW,KWT,4207077,Asia,2.97118403\r
-27/03/2020,27,3,2020,13,0,Kuwait,KW,KWT,4207077,Asia,3.04249245\r
-26/03/2020,26,3,2020,4,0,Kuwait,KW,KWT,4207077,Asia,2.92364509\r
-25/03/2020,25,3,2020,2,0,Kuwait,KW,KWT,4207077,Asia,2.89987561\r
-24/03/2020,24,3,2020,1,0,Kuwait,KW,KWT,4207077,Asia,2.94741456\r
-23/03/2020,23,3,2020,12,0,Kuwait,KW,KWT,4207077,Asia,2.94741456\r
-22/03/2020,22,3,2020,17,0,Kuwait,KW,KWT,4207077,Asia,2.73348931\r
-21/03/2020,21,3,2020,11,0,Kuwait,KW,KWT,4207077,Asia,2.4007167\r
-20/03/2020,20,3,2020,6,0,Kuwait,KW,KWT,4207077,Asia,2.18679145\r
-19/03/2020,19,3,2020,12,0,Kuwait,KW,KWT,4207077,Asia,2.28186934\r
-18/03/2020,18,3,2020,7,0,Kuwait,KW,KWT,4207077,Asia,2.02040514\r
-17/03/2020,17,3,2020,11,0,Kuwait,KW,KWT,4207077,Asia,1.85401884\r
-16/03/2020,16,3,2020,8,0,Kuwait,KW,KWT,4207077,Asia,1.64009359\r
-15/03/2020,15,3,2020,4,0,Kuwait,KW,KWT,4207077,Asia,1.85401884\r
-14/03/2020,14,3,2020,20,0,Kuwait,KW,KWT,4207077,Asia,2.11548303\r
-13/03/2020,13,3,2020,8,0,Kuwait,KW,KWT,4207077,Asia,1.78271042\r
-12/03/2020,12,3,2020,3,0,Kuwait,KW,KWT,4207077,Asia,1.64009359\r
-11/03/2020,11,3,2020,4,0,Kuwait,KW,KWT,4207077,Asia,1.64009359\r
-10/03/2020,10,3,2020,1,0,Kuwait,KW,KWT,4207077,Asia,1.5450157\r
-09/03/2020,9,3,2020,3,0,Kuwait,KW,KWT,4207077,Asia,1.52124622\r
-08/03/2020,8,3,2020,3,0,Kuwait,KW,KWT,4207077,Asia,1.44993781\r
-06/03/2020,6,3,2020,2,0,Kuwait,KW,KWT,4207077,Asia,1.37862939\r
-03/03/2020,3,3,2020,10,0,Kuwait,KW,KWT,4207077,Asia,1.33109045\r
-02/03/2020,2,3,2020,1,0,Kuwait,KW,KWT,4207077,Asia,1.09339572\r
-01/03/2020,1,3,2020,0,0,Kuwait,KW,KWT,4207077,Asia,1.06962625\r
-29/02/2020,29,2,2020,2,0,Kuwait,KW,KWT,4207077,Asia,1.06962625\r
-28/02/2020,28,2,2020,17,0,Kuwait,KW,KWT,4207077,Asia,1.02208731\r
-27/02/2020,27,2,2020,15,0,Kuwait,KW,KWT,4207077,Asia,0.61800628\r
-26/02/2020,26,2,2020,6,0,Kuwait,KW,KWT,4207077,Asia,0.26146419\r
-25/02/2020,25,2,2020,2,0,Kuwait,KW,KWT,4207077,Asia,0.11884736\r
-24/02/2020,24,2,2020,3,0,Kuwait,KW,KWT,4207077,Asia,0.07130842\r
-23/02/2020,23,2,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-22/02/2020,22,2,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-21/02/2020,21,2,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-20/02/2020,20,2,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-19/02/2020,19,2,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-18/02/2020,18,2,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-17/02/2020,17,2,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-16/02/2020,16,2,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-15/02/2020,15,2,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-14/02/2020,14,2,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-13/02/2020,13,2,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-12/02/2020,12,2,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-11/02/2020,11,2,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-10/02/2020,10,2,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-09/02/2020,9,2,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-08/02/2020,8,2,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-07/02/2020,7,2,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-06/02/2020,6,2,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-05/02/2020,5,2,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-04/02/2020,4,2,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-03/02/2020,3,2,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-02/02/2020,2,2,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-01/02/2020,1,2,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-31/01/2020,31,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-30/01/2020,30,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-29/01/2020,29,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-28/01/2020,28,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-27/01/2020,27,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-26/01/2020,26,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-25/01/2020,25,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-24/01/2020,24,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-23/01/2020,23,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-22/01/2020,22,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-21/01/2020,21,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-20/01/2020,20,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-19/01/2020,19,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-18/01/2020,18,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-17/01/2020,17,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-16/01/2020,16,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-15/01/2020,15,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-14/01/2020,14,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-13/01/2020,13,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,0\r
-12/01/2020,12,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,\r
-11/01/2020,11,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,\r
-10/01/2020,10,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,\r
-09/01/2020,9,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,\r
-08/01/2020,8,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,\r
-07/01/2020,7,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,\r
-06/01/2020,6,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,\r
-05/01/2020,5,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,\r
-04/01/2020,4,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,\r
-03/01/2020,3,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,\r
-02/01/2020,2,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,\r
-01/01/2020,1,1,2020,0,0,Kuwait,KW,KWT,4207077,Asia,\r
-31/12/2019,31,12,2019,0,0,Kuwait,KW,KWT,4207077,Asia,\r
-19/08/2020,19,8,2020,0,0,Kyrgyzstan,KG,KGZ,6415851,Asia,62.9066978\r
-18/08/2020,18,8,2020,155,2,Kyrgyzstan,KG,KGZ,6415851,Asia,71.77535763\r
-17/08/2020,17,8,2020,135,1,Kyrgyzstan,KG,KGZ,6415851,Asia,75.78106162\r
-16/08/2020,16,8,2020,483,4,Kyrgyzstan,KG,KGZ,6415851,Asia,80.06732077\r
-15/08/2020,15,8,2020,304,4,Kyrgyzstan,KG,KGZ,6415851,Asia,79.08537776\r
-14/08/2020,14,8,2020,310,3,Kyrgyzstan,KG,KGZ,6415851,Asia,82.04679317\r
-13/08/2020,13,8,2020,0,0,Kyrgyzstan,KG,KGZ,6415851,Asia,86.28629312\r
-12/08/2020,12,8,2020,304,6,Kyrgyzstan,KG,KGZ,6415851,Asia,96.12130955\r
-11/08/2020,11,8,2020,278,4,Kyrgyzstan,KG,KGZ,6415851,Asia,103.04166976\r
-10/08/2020,10,8,2020,258,6,Kyrgyzstan,KG,KGZ,6415851,Asia,107.24999692\r
-09/08/2020,9,8,2020,332,8,Kyrgyzstan,KG,KGZ,6415851,Asia,110.75693622\r
-08/08/2020,8,8,2020,425,9,Kyrgyzstan,KG,KGZ,6415851,Asia,125.04966216\r
-07/08/2020,7,8,2020,503,4,Kyrgyzstan,KG,KGZ,6415851,Asia,123.36633129\r
-06/08/2020,6,8,2020,549,9,Kyrgyzstan,KG,KGZ,6415851,Asia,129.88144519\r
-05/08/2020,5,8,2020,569,11,Kyrgyzstan,KG,KGZ,6415851,Asia,136.39655908\r
-04/08/2020,4,8,2020,412,7,Kyrgyzstan,KG,KGZ,6415851,Asia,144.797627\r
-03/08/2020,3,8,2020,410,11,Kyrgyzstan,KG,KGZ,6415851,Asia,155.64575923\r
-02/08/2020,2,8,2020,420,12,Kyrgyzstan,KG,KGZ,6415851,Asia,158.778625\r
-01/08/2020,1,8,2020,494,19,Kyrgyzstan,KG,KGZ,6415851,Asia,182.2517387\r
-31/07/2020,31,7,2020,582,14,Kyrgyzstan,KG,KGZ,6415851,Asia,353.87355473\r
-30/07/2020,30,7,2020,631,17,Kyrgyzstan,KG,KGZ,6415851,Asia,354.20086907\r
-29/07/2020,29,7,2020,748,18,Kyrgyzstan,KG,KGZ,6415851,Asia,352.48636541\r
-28/07/2020,28,7,2020,548,28,Kyrgyzstan,KG,KGZ,6415851,Asia,347.67016877\r
-27/07/2020,27,7,2020,483,24,Kyrgyzstan,KG,KGZ,6415851,Asia,345.69069637\r
-26/07/2020,26,7,2020,1249,28,Kyrgyzstan,KG,KGZ,6415851,Asia,345.76862835\r
-25/07/2020,25,7,2020,317,38,Kyrgyzstan,KG,KGZ,6415851,Asia,337.50783801\r
-24/07/2020,24,7,2020,921,42,Kyrgyzstan,KG,KGZ,6415851,Asia,341.17064128\r
-23/07/2020,23,7,2020,967,46,Kyrgyzstan,KG,KGZ,6415851,Asia,334.78021856\r
-22/07/2020,22,7,2020,1108,44,Kyrgyzstan,KG,KGZ,6415851,Asia,325.33486205\r
-21/07/2020,21,7,2020,1108,42,Kyrgyzstan,KG,KGZ,6415851,Asia,313.44244123\r
-20/07/2020,20,7,2020,611,34,Kyrgyzstan,KG,KGZ,6415851,Asia,303.18659208\r
-19/07/2020,19,7,2020,1926,103,Kyrgyzstan,KG,KGZ,6415851,Asia,298.55743221\r
-18/07/2020,18,7,2020,11505,728,Kyrgyzstan,KG,KGZ,6415851,Asia,272.94898214\r
-17/07/2020,17,7,2020,603,5,Kyrgyzstan,KG,KGZ,6415851,Asia,98.72423783\r
-16/07/2020,16,7,2020,521,7,Kyrgyzstan,KG,KGZ,6415851,Asia,105.41080209\r
-15/07/2020,15,7,2020,439,11,Kyrgyzstan,KG,KGZ,6415851,Asia,97.29028932\r
-14/07/2020,14,7,2020,421,2,Kyrgyzstan,KG,KGZ,6415851,Asia,97.29028932\r
-13/07/2020,13,7,2020,488,15,Kyrgyzstan,KG,KGZ,6415851,Asia,95.07702096\r
-12/07/2020,12,7,2020,719,7,Kyrgyzstan,KG,KGZ,6415851,Asia,91.66360004\r
-11/07/2020,11,7,2020,552,3,Kyrgyzstan,KG,KGZ,6415851,Asia,84.11978395\r
-10/07/2020,10,7,2020,511,6,Kyrgyzstan,KG,KGZ,6415851,Asia,80.33228951\r
-09/07/2020,9,7,2020,361,4,Kyrgyzstan,KG,KGZ,6415851,Asia,76.26423993\r
-08/07/2020,8,7,2020,345,13,Kyrgyzstan,KG,KGZ,6415851,Asia,74.19124914\r
-07/07/2020,7,7,2020,450,7,Kyrgyzstan,KG,KGZ,6415851,Asia,72.04032637\r
-06/07/2020,6,7,2020,314,4,Kyrgyzstan,KG,KGZ,6415851,Asia,67.56703047\r
-05/07/2020,5,7,2020,283,10,Kyrgyzstan,KG,KGZ,6415851,Asia,65.86811321\r
-04/07/2020,4,7,2020,327,2,Kyrgyzstan,KG,KGZ,6415851,Asia,64.10685036\r
-03/07/2020,3,7,2020,1032,14,Kyrgyzstan,KG,KGZ,6415851,Asia,62.00268678\r
-02/07/2020,2,7,2020,0,0,Kyrgyzstan,KG,KGZ,6415851,Asia,47.97492959\r
-01/07/2020,1,7,2020,439,5,Kyrgyzstan,KG,KGZ,6415851,Asia,49.4556373\r
-30/06/2020,30,6,2020,279,7,Kyrgyzstan,KG,KGZ,6415851,Asia,44.01598479\r
-29/06/2020,29,6,2020,269,3,Kyrgyzstan,KG,KGZ,6415851,Asia,41.22601974\r
-28/06/2020,28,6,2020,235,1,Kyrgyzstan,KG,KGZ,6415851,Asia,38.38929551\r
-27/06/2020,27,6,2020,309,3,Kyrgyzstan,KG,KGZ,6415851,Asia,35.9422312\r
-26/06/2020,26,6,2020,250,0,Kyrgyzstan,KG,KGZ,6415851,Asia,31.76507684\r
-25/06/2020,25,6,2020,228,1,Kyrgyzstan,KG,KGZ,6415851,Asia,28.4451743\r
-24/06/2020,24,6,2020,207,1,Kyrgyzstan,KG,KGZ,6415851,Asia,25.4525861\r
-23/06/2020,23,6,2020,163,1,Kyrgyzstan,KG,KGZ,6415851,Asia,22.81848503\r
-22/06/2020,22,6,2020,205,3,Kyrgyzstan,KG,KGZ,6415851,Asia,20.63638947\r
-21/06/2020,21,6,2020,170,2,Kyrgyzstan,KG,KGZ,6415851,Asia,17.83083803\r
-20/06/2020,20,6,2020,192,3,Kyrgyzstan,KG,KGZ,6415851,Asia,15.69550166\r
-19/06/2020,19,6,2020,132,1,Kyrgyzstan,KG,KGZ,6415851,Asia,13.29519654\r
-18/06/2020,18,6,2020,95,1,Kyrgyzstan,KG,KGZ,6415851,Asia,11.81448883\r
-17/06/2020,17,6,2020,90,2,Kyrgyzstan,KG,KGZ,6415851,Asia,10.77020024\r
-16/06/2020,16,6,2020,100,1,Kyrgyzstan,KG,KGZ,6415851,Asia,9.77267084\r
-15/06/2020,15,6,2020,87,0,Kyrgyzstan,KG,KGZ,6415851,Asia,8.65045027\r
-14/06/2020,14,6,2020,78,0,Kyrgyzstan,KG,KGZ,6415851,Asia,8.36989512\r
-13/06/2020,13,6,2020,41,1,Kyrgyzstan,KG,KGZ,6415851,Asia,7.55940249\r
-12/06/2020,12,6,2020,37,0,Kyrgyzstan,KG,KGZ,6415851,Asia,7.85554403\r
-11/06/2020,11,6,2020,36,0,Kyrgyzstan,KG,KGZ,6415851,Asia,8.33872233\r
-10/06/2020,10,6,2020,38,2,Kyrgyzstan,KG,KGZ,6415851,Asia,8.93100541\r
-09/06/2020,9,6,2020,23,1,Kyrgyzstan,KG,KGZ,6415851,Asia,9.14921497\r
-08/06/2020,8,6,2020,25,1,Kyrgyzstan,KG,KGZ,6415851,Asia,9.33625173\r
-07/06/2020,7,6,2020,33,0,Kyrgyzstan,KG,KGZ,6415851,Asia,9.41418371\r
-06/06/2020,6,6,2020,38,0,Kyrgyzstan,KG,KGZ,6415851,Asia,9.5077021\r
-05/06/2020,5,6,2020,37,2,Kyrgyzstan,KG,KGZ,6415851,Asia,9.13362857\r
-04/06/2020,4,6,2020,28,0,Kyrgyzstan,KG,KGZ,6415851,Asia,9.13362857\r
-03/06/2020,3,6,2020,26,3,Kyrgyzstan,KG,KGZ,6415851,Asia,9.36742452\r
-02/06/2020,2,6,2020,28,1,Kyrgyzstan,KG,KGZ,6415851,Asia,9.38301092\r
-01/06/2020,1,6,2020,69,0,Kyrgyzstan,KG,KGZ,6415851,Asia,9.36742452\r
-31/05/2020,31,5,2020,26,0,Kyrgyzstan,KG,KGZ,6415851,Asia,9.5077021\r
-30/05/2020,30,5,2020,60,0,Kyrgyzstan,KG,KGZ,6415851,Asia,9.42977011\r
-29/05/2020,29,5,2020,68,0,Kyrgyzstan,KG,KGZ,6415851,Asia,8.58810468\r
-28/05/2020,28,5,2020,74,0,Kyrgyzstan,KG,KGZ,6415851,Asia,7.9802352\r
-27/05/2020,27,5,2020,52,0,Kyrgyzstan,KG,KGZ,6415851,Asia,7.41912491\r
-26/05/2020,26,5,2020,35,0,Kyrgyzstan,KG,KGZ,6415851,Asia,6.71773705\r
-25/05/2020,25,5,2020,30,2,Kyrgyzstan,KG,KGZ,6415851,Asia,6.4995275\r
-24/05/2020,24,5,2020,39,0,Kyrgyzstan,KG,KGZ,6415851,Asia,6.25014515\r
-23/05/2020,23,5,2020,14,0,Kyrgyzstan,KG,KGZ,6415851,Asia,6.74890985\r
-22/05/2020,22,5,2020,37,0,Kyrgyzstan,KG,KGZ,6415851,Asia,6.92036021\r
-21/05/2020,21,5,2020,43,0,Kyrgyzstan,KG,KGZ,6415851,Asia,6.5151139\r
-20/05/2020,20,5,2020,27,0,Kyrgyzstan,KG,KGZ,6415851,Asia,6.21897235\r
-19/05/2020,19,5,2020,27,0,Kyrgyzstan,KG,KGZ,6415851,Asia,6.23455875\r
-18/05/2020,18,5,2020,78,0,Kyrgyzstan,KG,KGZ,6415851,Asia,6.0163492\r
-17/05/2020,17,5,2020,21,0,Kyrgyzstan,KG,KGZ,6415851,Asia,5.34613413\r
-16/05/2020,16,5,2020,6,0,Kyrgyzstan,KG,KGZ,6415851,Asia,5.42406611\r
-15/05/2020,15,5,2020,29,2,Kyrgyzstan,KG,KGZ,6415851,Asia,5.68903486\r
-14/05/2020,14,5,2020,38,0,Kyrgyzstan,KG,KGZ,6415851,Asia,5.23702935\r
-13/05/2020,13,5,2020,7,0,Kyrgyzstan,KG,KGZ,6415851,Asia,4.90971502\r
-12/05/2020,12,5,2020,21,0,Kyrgyzstan,KG,KGZ,6415851,Asia,5.12792457\r
-11/05/2020,11,5,2020,14,0,Kyrgyzstan,KG,KGZ,6415851,Asia,5.0032334\r
-10/05/2020,10,5,2020,71,0,Kyrgyzstan,KG,KGZ,6415851,Asia,4.987647\r
-09/05/2020,9,5,2020,25,0,Kyrgyzstan,KG,KGZ,6415851,Asia,4.14598157\r
-08/05/2020,8,5,2020,11,0,Kyrgyzstan,KG,KGZ,6415851,Asia,3.89659922\r
-07/05/2020,7,5,2020,24,0,Kyrgyzstan,KG,KGZ,6415851,Asia,4.11480878\r
-06/05/2020,6,5,2020,28,1,Kyrgyzstan,KG,KGZ,6415851,Asia,4.03687679\r
-05/05/2020,5,5,2020,13,1,Kyrgyzstan,KG,KGZ,6415851,Asia,3.94335841\r
-04/05/2020,4,5,2020,35,0,Kyrgyzstan,KG,KGZ,6415851,Asia,4.08363598\r
-03/05/2020,3,5,2020,26,2,Kyrgyzstan,KG,KGZ,6415851,Asia,3.75632165\r
-02/05/2020,2,5,2020,23,0,Kyrgyzstan,KG,KGZ,6415851,Asia,4.09922238\r
-01/05/2020,1,5,2020,0,0,Kyrgyzstan,KG,KGZ,6415851,Asia,4.005704\r
-30/04/2020,30,4,2020,17,0,Kyrgyzstan,KG,KGZ,6415851,Asia,4.36419113\r
-29/04/2020,29,4,2020,21,0,Kyrgyzstan,KG,KGZ,6415851,Asia,4.36419113\r
-28/04/2020,28,4,2020,13,0,Kyrgyzstan,KG,KGZ,6415851,Asia,4.33301833\r
-27/04/2020,27,4,2020,13,0,Kyrgyzstan,KG,KGZ,6415851,Asia,4.30184554\r
-26/04/2020,26,4,2020,17,0,Kyrgyzstan,KG,KGZ,6415851,Asia,4.75385105\r
-25/04/2020,25,4,2020,9,0,Kyrgyzstan,KG,KGZ,6415851,Asia,5.08116538\r
-24/04/2020,24,4,2020,25,0,Kyrgyzstan,KG,KGZ,6415851,Asia,5.57993008\r
-23/04/2020,23,4,2020,19,1,Kyrgyzstan,KG,KGZ,6415851,Asia,5.4708253\r
-22/04/2020,22,4,2020,22,0,Kyrgyzstan,KG,KGZ,6415851,Asia,5.33054773\r
-21/04/2020,21,4,2020,22,0,Kyrgyzstan,KG,KGZ,6415851,Asia,5.64227567\r
-20/04/2020,20,4,2020,14,2,Kyrgyzstan,KG,KGZ,6415851,Asia,5.4864117\r
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-18/04/2020,18,4,2020,17,0,Kyrgyzstan,KG,KGZ,6415851,Asia,5.64227567\r
-17/04/2020,17,4,2020,23,0,Kyrgyzstan,KG,KGZ,6415851,Asia,5.67344846\r
-16/04/2020,16,4,2020,17,0,Kyrgyzstan,KG,KGZ,6415851,Asia,5.5175845\r
-15/04/2020,15,4,2020,19,0,Kyrgyzstan,KG,KGZ,6415851,Asia,5.33054773\r
-14/04/2020,14,4,2020,11,0,Kyrgyzstan,KG,KGZ,6415851,Asia,5.39289332\r
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-12/04/2020,12,4,2020,38,0,Kyrgyzstan,KG,KGZ,6415851,Asia,4.56681429\r
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-02/04/2020,2,4,2020,5,1,Kyrgyzstan,KG,KGZ,6415851,Asia,1.69891726\r
-01/04/2020,1,4,2020,23,0,Kyrgyzstan,KG,KGZ,6415851,Asia,1.66774447\r
-31/03/2020,31,3,2020,0,0,Kyrgyzstan,KG,KGZ,6415851,Asia,\r
-30/03/2020,30,3,2020,0,0,Kyrgyzstan,KG,KGZ,6415851,Asia,\r
-29/03/2020,29,3,2020,26,0,Kyrgyzstan,KG,KGZ,6415851,Asia,\r
-28/03/2020,28,3,2020,14,0,Kyrgyzstan,KG,KGZ,6415851,Asia,\r
-27/03/2020,27,3,2020,0,0,Kyrgyzstan,KG,KGZ,6415851,Asia,\r
-26/03/2020,26,3,2020,2,0,Kyrgyzstan,KG,KGZ,6415851,Asia,\r
-25/03/2020,25,3,2020,26,0,Kyrgyzstan,KG,KGZ,6415851,Asia,\r
-24/03/2020,24,3,2020,2,0,Kyrgyzstan,KG,KGZ,6415851,Asia,\r
-23/03/2020,23,3,2020,0,0,Kyrgyzstan,KG,KGZ,6415851,Asia,\r
-22/03/2020,22,3,2020,8,0,Kyrgyzstan,KG,KGZ,6415851,Asia,\r
-21/03/2020,21,3,2020,0,0,Kyrgyzstan,KG,KGZ,6415851,Asia,\r
-20/03/2020,20,3,2020,3,0,Kyrgyzstan,KG,KGZ,6415851,Asia,\r
-19/03/2020,19,3,2020,3,0,Kyrgyzstan,KG,KGZ,6415851,Asia,\r
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-18/08/2020,18,8,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-17/08/2020,17,8,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-16/08/2020,16,8,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-15/08/2020,15,8,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
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-13/08/2020,13,8,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-12/08/2020,12,8,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-11/08/2020,11,8,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-10/08/2020,10,8,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
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-01/08/2020,1,8,2020,0,0,Laos,LA,LAO,7169456,Asia,0.01394806\r
-31/07/2020,31,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0.01394806\r
-30/07/2020,30,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0.01394806\r
-29/07/2020,29,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0.01394806\r
-28/07/2020,28,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0.01394806\r
-27/07/2020,27,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0.01394806\r
-26/07/2020,26,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0.01394806\r
-25/07/2020,25,7,2020,1,0,Laos,LA,LAO,7169456,Asia,0.01394806\r
-24/07/2020,24,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-23/07/2020,23,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-22/07/2020,22,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-21/07/2020,21,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-20/07/2020,20,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-19/07/2020,19,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-18/07/2020,18,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-17/07/2020,17,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-16/07/2020,16,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-15/07/2020,15,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-14/07/2020,14,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-13/07/2020,13,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-12/07/2020,12,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-11/07/2020,11,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-10/07/2020,10,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-09/07/2020,9,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-08/07/2020,8,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-07/07/2020,7,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
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-04/07/2020,4,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
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-02/07/2020,2,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-01/07/2020,1,7,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-30/06/2020,30,6,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-29/06/2020,29,6,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-28/06/2020,28,6,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-27/06/2020,27,6,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-26/06/2020,26,6,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-25/06/2020,25,6,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-24/06/2020,24,6,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-23/06/2020,23,6,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-22/06/2020,22,6,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-21/06/2020,21,6,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
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-18/06/2020,18,6,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
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-15/06/2020,15,6,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
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-11/06/2020,11,6,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
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-01/06/2020,1,6,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-31/05/2020,31,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-30/05/2020,30,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-29/05/2020,29,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-28/05/2020,28,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-27/05/2020,27,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-26/05/2020,26,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-25/05/2020,25,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-24/05/2020,24,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-23/05/2020,23,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-22/05/2020,22,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-21/05/2020,21,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-20/05/2020,20,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-19/05/2020,19,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-18/05/2020,18,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-17/05/2020,17,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-16/05/2020,16,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-15/05/2020,15,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-14/05/2020,14,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-13/05/2020,13,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-12/05/2020,12,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-11/05/2020,11,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-10/05/2020,10,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-09/05/2020,9,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-08/05/2020,8,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-07/05/2020,7,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-06/05/2020,6,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-05/05/2020,5,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-04/05/2020,4,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-03/05/2020,3,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-02/05/2020,2,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-01/05/2020,1,5,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-30/04/2020,30,4,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-29/04/2020,29,4,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-28/04/2020,28,4,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-27/04/2020,27,4,2020,0,0,Laos,LA,LAO,7169456,Asia,0\r
-26/04/2020,26,4,2020,0,0,Laos,LA,LAO,7169456,Asia,0.01394806\r
-25/04/2020,25,4,2020,0,0,Laos,LA,LAO,7169456,Asia,0.04184418\r
-24/04/2020,24,4,2020,0,0,Laos,LA,LAO,7169456,Asia,0.04184418\r
-23/04/2020,23,4,2020,0,0,Laos,LA,LAO,7169456,Asia,0.05579224\r
-22/04/2020,22,4,2020,0,0,Laos,LA,LAO,7169456,Asia,0.09763642\r
-21/04/2020,21,4,2020,0,0,Laos,LA,LAO,7169456,Asia,0.09763642\r
-20/04/2020,20,4,2020,0,0,Laos,LA,LAO,7169456,Asia,0.11158448\r
-19/04/2020,19,4,2020,0,0,Laos,LA,LAO,7169456,Asia,0.12553254\r
-18/04/2020,18,4,2020,0,0,Laos,LA,LAO,7169456,Asia,0.12553254\r
-17/04/2020,17,4,2020,0,0,Laos,LA,LAO,7169456,Asia,0.12553254\r
-16/04/2020,16,4,2020,0,0,Laos,LA,LAO,7169456,Asia,0.12553254\r
-15/04/2020,15,4,2020,0,0,Laos,LA,LAO,7169456,Asia,0.1394806\r
-14/04/2020,14,4,2020,0,0,Laos,LA,LAO,7169456,Asia,0.1394806\r
-13/04/2020,13,4,2020,1,0,Laos,LA,LAO,7169456,Asia,0.18132478\r
-12/04/2020,12,4,2020,2,0,Laos,LA,LAO,7169456,Asia,0.16737672\r
-11/04/2020,11,4,2020,0,0,Laos,LA,LAO,7169456,Asia,0.1394806\r
-10/04/2020,10,4,2020,1,0,Laos,LA,LAO,7169456,Asia,0.1394806\r
-09/04/2020,9,4,2020,3,0,Laos,LA,LAO,7169456,Asia,0.18132478\r
-08/04/2020,8,4,2020,0,0,Laos,LA,LAO,7169456,Asia,0.1394806\r
-07/04/2020,7,4,2020,1,0,Laos,LA,LAO,7169456,Asia,0.16737672\r
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-02/04/2020,2,4,2020,1,0,Laos,LA,LAO,7169456,Asia,\r
-01/04/2020,1,4,2020,0,0,Laos,LA,LAO,7169456,Asia,\r
-31/03/2020,31,3,2020,3,0,Laos,LA,LAO,7169456,Asia,\r
-30/03/2020,30,3,2020,0,0,Laos,LA,LAO,7169456,Asia,\r
-29/03/2020,29,3,2020,0,0,Laos,LA,LAO,7169456,Asia,\r
-28/03/2020,28,3,2020,0,0,Laos,LA,LAO,7169456,Asia,\r
-27/03/2020,27,3,2020,4,0,Laos,LA,LAO,7169456,Asia,\r
-26/03/2020,26,3,2020,0,0,Laos,LA,LAO,7169456,Asia,\r
-25/03/2020,25,3,2020,2,0,Laos,LA,LAO,7169456,Asia,\r
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-18/08/2020,18,8,2020,1,0,Latvia,LV,LVA,1919968,Europe,4.01048351\r
-17/08/2020,17,8,2020,7,0,Latvia,LV,LVA,1919968,Europe,4.11465191\r
-16/08/2020,16,8,2020,7,0,Latvia,LV,LVA,1919968,Europe,4.01048351\r
-15/08/2020,15,8,2020,1,0,Latvia,LV,LVA,1919968,Europe,4.01048351\r
-14/08/2020,14,8,2020,4,0,Latvia,LV,LVA,1919968,Europe,4.11465191\r
-13/08/2020,13,8,2020,0,0,Latvia,LV,LVA,1919968,Europe,4.11465191\r
-12/08/2020,12,8,2020,10,0,Latvia,LV,LVA,1919968,Europe,4.32298872\r
-11/08/2020,11,8,2020,3,0,Latvia,LV,LVA,1919968,Europe,3.8021467\r
-10/08/2020,10,8,2020,2,0,Latvia,LV,LVA,1919968,Europe,3.6979783\r
-09/08/2020,9,8,2020,7,0,Latvia,LV,LVA,1919968,Europe,4.27090452\r
-08/08/2020,8,8,2020,6,0,Latvia,LV,LVA,1919968,Europe,3.95839931\r
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-06/08/2020,6,8,2020,8,0,Latvia,LV,LVA,1919968,Europe,3.12505208\r
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-04/08/2020,4,8,2020,3,0,Latvia,LV,LVA,1919968,Europe,2.81254688\r
-03/08/2020,3,8,2020,5,0,Latvia,LV,LVA,1919968,Europe,2.65629427\r
-02/08/2020,2,8,2020,7,0,Latvia,LV,LVA,1919968,Europe,2.55212587\r
-01/08/2020,1,8,2020,3,1,Latvia,LV,LVA,1919968,Europe,2.39587326\r
-31/07/2020,31,7,2020,4,0,Latvia,LV,LVA,1919968,Europe,2.55212587\r
-30/07/2020,30,7,2020,4,0,Latvia,LV,LVA,1919968,Europe,2.39587326\r
-29/07/2020,29,7,2020,0,0,Latvia,LV,LVA,1919968,Europe,2.18753646\r
-28/07/2020,28,7,2020,1,0,Latvia,LV,LVA,1919968,Europe,2.39587326\r
-27/07/2020,27,7,2020,13,0,Latvia,LV,LVA,1919968,Europe,2.39587326\r
-26/07/2020,26,7,2020,1,0,Latvia,LV,LVA,1919968,Europe,1.71877865\r
-25/07/2020,25,7,2020,2,0,Latvia,LV,LVA,1919968,Europe,2.65629427\r
-24/07/2020,24,7,2020,6,0,Latvia,LV,LVA,1919968,Europe,2.55212587\r
-23/07/2020,23,7,2020,4,0,Latvia,LV,LVA,1919968,Europe,2.91671528\r
-22/07/2020,22,7,2020,1,0,Latvia,LV,LVA,1919968,Europe,3.07296788\r
-21/07/2020,21,7,2020,0,0,Latvia,LV,LVA,1919968,Europe,3.38547309\r
-20/07/2020,20,7,2020,3,0,Latvia,LV,LVA,1919968,Europe,3.5417257\r
-19/07/2020,19,7,2020,4,0,Latvia,LV,LVA,1919968,Europe,3.43755729\r
-18/07/2020,18,7,2020,6,0,Latvia,LV,LVA,1919968,Europe,3.28130469\r
-17/07/2020,17,7,2020,1,0,Latvia,LV,LVA,1919968,Europe,2.96879948\r
-16/07/2020,16,7,2020,0,0,Latvia,LV,LVA,1919968,Europe,2.96879948\r
-15/07/2020,15,7,2020,4,0,Latvia,LV,LVA,1919968,Europe,3.12505208\r
-14/07/2020,14,7,2020,1,1,Latvia,LV,LVA,1919968,Europe,2.96879948\r
-13/07/2020,13,7,2020,0,0,Latvia,LV,LVA,1919968,Europe,2.96879948\r
-12/07/2020,12,7,2020,19,0,Latvia,LV,LVA,1919968,Europe,3.02088368\r
-11/07/2020,11,7,2020,0,0,Latvia,LV,LVA,1919968,Europe,2.18753646\r
-10/07/2020,10,7,2020,13,0,Latvia,LV,LVA,1919968,Europe,2.23962066\r
-09/07/2020,9,7,2020,7,0,Latvia,LV,LVA,1919968,Europe,1.56252604\r
-08/07/2020,8,7,2020,7,0,Latvia,LV,LVA,1919968,Europe,1.19793663\r
-07/07/2020,7,7,2020,3,0,Latvia,LV,LVA,1919968,Europe,0.83334722\r
-06/07/2020,6,7,2020,1,0,Latvia,LV,LVA,1919968,Europe,0.67709462\r
-05/07/2020,5,7,2020,1,0,Latvia,LV,LVA,1919968,Europe,0.62501042\r
-04/07/2020,4,7,2020,0,0,Latvia,LV,LVA,1919968,Europe,0.62501042\r
-03/07/2020,3,7,2020,1,0,Latvia,LV,LVA,1919968,Europe,0.72917882\r
-02/07/2020,2,7,2020,3,0,Latvia,LV,LVA,1919968,Europe,0.88543142\r
-01/07/2020,1,7,2020,1,0,Latvia,LV,LVA,1919968,Europe,1.04168403\r
-30/06/2020,30,6,2020,1,0,Latvia,LV,LVA,1919968,Europe,1.04168403\r
-29/06/2020,29,6,2020,1,0,Latvia,LV,LVA,1919968,Europe,0.98959983\r
-28/06/2020,28,6,2020,3,0,Latvia,LV,LVA,1919968,Europe,0.93751563\r
-27/06/2020,27,6,2020,1,0,Latvia,LV,LVA,1919968,Europe,0.83334722\r
-26/06/2020,26,6,2020,0,0,Latvia,LV,LVA,1919968,Europe,0.88543142\r
-25/06/2020,25,6,2020,0,0,Latvia,LV,LVA,1919968,Europe,0.98959983\r
-24/06/2020,24,6,2020,0,0,Latvia,LV,LVA,1919968,Europe,1.14585243\r
-23/06/2020,23,6,2020,0,0,Latvia,LV,LVA,1919968,Europe,1.19793663\r
-22/06/2020,22,6,2020,0,0,Latvia,LV,LVA,1919968,Europe,1.19793663\r
-21/06/2020,21,6,2020,1,0,Latvia,LV,LVA,1919968,Europe,1.30210504\r
-20/06/2020,20,6,2020,2,0,Latvia,LV,LVA,1919968,Europe,1.45835764\r
-19/06/2020,19,6,2020,4,0,Latvia,LV,LVA,1919968,Europe,1.35418924\r
-18/06/2020,18,6,2020,6,2,Latvia,LV,LVA,1919968,Europe,1.30210504\r
-17/06/2020,17,6,2020,1,0,Latvia,LV,LVA,1919968,Europe,0.98959983\r
-16/06/2020,16,6,2020,0,0,Latvia,LV,LVA,1919968,Europe,1.35418924\r
-15/06/2020,15,6,2020,0,0,Latvia,LV,LVA,1919968,Europe,1.61461024\r
-14/06/2020,14,6,2020,1,1,Latvia,LV,LVA,1919968,Europe,1.66669444\r
-13/06/2020,13,6,2020,2,1,Latvia,LV,LVA,1919968,Europe,1.66669444\r
-12/06/2020,12,6,2020,2,0,Latvia,LV,LVA,1919968,Europe,1.71877865\r
-11/06/2020,11,6,2020,3,0,Latvia,LV,LVA,1919968,Europe,1.82294705\r
-10/06/2020,10,6,2020,1,0,Latvia,LV,LVA,1919968,Europe,1.87503125\r
-09/06/2020,9,6,2020,0,1,Latvia,LV,LVA,1919968,Europe,2.03128385\r
-08/06/2020,8,6,2020,2,0,Latvia,LV,LVA,1919968,Europe,2.13545226\r
-07/06/2020,7,6,2020,4,0,Latvia,LV,LVA,1919968,Europe,2.08336806\r
-06/06/2020,6,6,2020,0,0,Latvia,LV,LVA,1919968,Europe,2.70837847\r
-05/06/2020,5,6,2020,3,1,Latvia,LV,LVA,1919968,Europe,2.96879948\r
-04/06/2020,4,6,2020,0,0,Latvia,LV,LVA,1919968,Europe,3.28130469\r
-03/06/2020,3,6,2020,8,0,Latvia,LV,LVA,1919968,Europe,3.48964149\r
-02/06/2020,2,6,2020,5,0,Latvia,LV,LVA,1919968,Europe,3.22922049\r
-01/06/2020,1,6,2020,1,0,Latvia,LV,LVA,1919968,Europe,3.02088368\r
-31/05/2020,31,5,2020,1,0,Latvia,LV,LVA,1919968,Europe,3.5417257\r
-30/05/2020,30,5,2020,3,0,Latvia,LV,LVA,1919968,Europe,4.89591493\r
-29/05/2020,29,5,2020,4,1,Latvia,LV,LVA,1919968,Europe,5.15633594\r
-28/05/2020,28,5,2020,4,1,Latvia,LV,LVA,1919968,Europe,5.52092535\r
-27/05/2020,27,5,2020,4,0,Latvia,LV,LVA,1919968,Europe,5.36467274\r
-26/05/2020,26,5,2020,2,0,Latvia,LV,LVA,1919968,Europe,5.36467274\r
-25/05/2020,25,5,2020,1,0,Latvia,LV,LVA,1919968,Europe,5.62509375\r
-24/05/2020,24,5,2020,16,0,Latvia,LV,LVA,1919968,Europe,6.04176736\r
-23/05/2020,23,5,2020,5,0,Latvia,LV,LVA,1919968,Europe,5.31258854\r
-22/05/2020,22,5,2020,9,1,Latvia,LV,LVA,1919968,Europe,6.04176736\r
-21/05/2020,21,5,2020,4,0,Latvia,LV,LVA,1919968,Europe,6.04176736\r
-20/05/2020,20,5,2020,3,2,Latvia,LV,LVA,1919968,Europe,6.04176736\r
-19/05/2020,19,5,2020,1,0,Latvia,LV,LVA,1919968,Europe,5.88551476\r
-18/05/2020,18,5,2020,11,0,Latvia,LV,LVA,1919968,Europe,6.71886198\r
-17/05/2020,17,5,2020,27,0,Latvia,LV,LVA,1919968,Europe,6.56260938\r
-16/05/2020,16,5,2020,8,0,Latvia,LV,LVA,1919968,Europe,5.20842014\r
-15/05/2020,15,5,2020,11,0,Latvia,LV,LVA,1919968,Europe,5.41675695\r
-14/05/2020,14,5,2020,1,1,Latvia,LV,LVA,1919968,Europe,5.31258854\r
-13/05/2020,13,5,2020,4,0,Latvia,LV,LVA,1919968,Europe,5.93759896\r
-12/05/2020,12,5,2020,7,0,Latvia,LV,LVA,1919968,Europe,6.66677778\r
-11/05/2020,11,5,2020,9,0,Latvia,LV,LVA,1919968,Europe,6.61469358\r
-10/05/2020,10,5,2020,2,0,Latvia,LV,LVA,1919968,Europe,6.56260938\r
-09/05/2020,9,5,2020,19,0,Latvia,LV,LVA,1919968,Europe,7.500125\r
-08/05/2020,8,5,2020,9,1,Latvia,LV,LVA,1919968,Europe,6.82303038\r
-07/05/2020,7,5,2020,4,0,Latvia,LV,LVA,1919968,Europe,7.239704\r
-06/05/2020,6,5,2020,0,1,Latvia,LV,LVA,1919968,Europe,7.70846181\r
-05/05/2020,5,5,2020,17,0,Latvia,LV,LVA,1919968,Europe,8.17721962\r
-04/05/2020,4,5,2020,8,0,Latvia,LV,LVA,1919968,Europe,7.91679861\r
-03/05/2020,3,5,2020,1,0,Latvia,LV,LVA,1919968,Europe,8.28138802\r
-02/05/2020,2,5,2020,12,1,Latvia,LV,LVA,1919968,Europe,9.79182986\r
-01/05/2020,1,5,2020,9,0,Latvia,LV,LVA,1919968,Europe,9.53140886\r
-30/04/2020,30,4,2020,13,2,Latvia,LV,LVA,1919968,Europe,9.53140886\r
-29/04/2020,29,4,2020,18,0,Latvia,LV,LVA,1919968,Europe,9.32307205\r
-28/04/2020,28,4,2020,6,1,Latvia,LV,LVA,1919968,Europe,8.48972483\r
-27/04/2020,27,4,2020,8,0,Latvia,LV,LVA,1919968,Europe,8.38555643\r
-26/04/2020,26,4,2020,20,0,Latvia,LV,LVA,1919968,Europe,9.06265104\r
-25/04/2020,25,4,2020,6,1,Latvia,LV,LVA,1919968,Europe,8.95848264\r
-24/04/2020,24,4,2020,17,0,Latvia,LV,LVA,1919968,Europe,9.84391407\r
-23/04/2020,23,4,2020,13,2,Latvia,LV,LVA,1919968,Europe,9.58349306\r
-22/04/2020,22,4,2020,9,4,Latvia,LV,LVA,1919968,Europe,10.41684028\r
-21/04/2020,21,4,2020,12,0,Latvia,LV,LVA,1919968,Europe,10.26058768\r
-20/04/2020,20,4,2020,15,0,Latvia,LV,LVA,1919968,Europe,10.10433507\r
-19/04/2020,19,4,2020,30,0,Latvia,LV,LVA,1919968,Europe,10.57309288\r
-18/04/2020,18,4,2020,7,0,Latvia,LV,LVA,1919968,Europe,9.84391407\r
-17/04/2020,17,4,2020,9,0,Latvia,LV,LVA,1919968,Europe,11.3022717\r
-16/04/2020,16,4,2020,9,0,Latvia,LV,LVA,1919968,Europe,11.45852431\r
-15/04/2020,15,4,2020,2,0,Latvia,LV,LVA,1919968,Europe,13.48980816\r
-14/04/2020,14,4,2020,4,0,Latvia,LV,LVA,1919968,Europe,14.53149219\r
-13/04/2020,13,4,2020,21,2,Latvia,LV,LVA,1919968,Europe,14.32315539\r
-12/04/2020,12,4,2020,18,1,Latvia,LV,LVA,1919968,Europe,16.92736546\r
-11/04/2020,11,4,2020,23,0,Latvia,LV,LVA,1919968,Europe,17.29195487\r
-10/04/2020,10,4,2020,12,0,Latvia,LV,LVA,1919968,Europe,17.96904948\r
-09/04/2020,9,4,2020,29,0,Latvia,LV,LVA,1919968,Europe,18.5419757\r
-08/04/2020,8,4,2020,6,1,Latvia,LV,LVA,1919968,Europe,18.28155469\r
-07/04/2020,7,4,2020,9,0,Latvia,LV,LVA,1919968,Europe,18.85448091\r
-06/04/2020,6,4,2020,24,0,Latvia,LV,LVA,1919968,Europe,20.52117535\r
-05/04/2020,5,4,2020,16,0,Latvia,LV,LVA,1919968,Europe,20.05241754\r
-04/04/2020,4,4,2020,35,1,Latvia,LV,LVA,1919968,Europe,19.89616494\r
-03/04/2020,3,4,2020,12,0,Latvia,LV,LVA,1919968,Europe,19.37532292\r
-02/04/2020,2,4,2020,48,0,Latvia,LV,LVA,1919968,Europe,19.53157553\r
-01/04/2020,1,4,2020,22,0,Latvia,LV,LVA,1919968,Europe,17.55237587\r
-31/03/2020,31,3,2020,0,0,Latvia,LV,LVA,1919968,Europe,17.70862848\r
-30/03/2020,30,3,2020,71,0,Latvia,LV,LVA,1919968,Europe,17.96904948\r
-29/03/2020,29,3,2020,25,0,Latvia,LV,LVA,1919968,Europe,14.53149219\r
-28/03/2020,28,3,2020,36,0,Latvia,LV,LVA,1919968,Europe,13.59397657\r
-27/03/2020,27,3,2020,23,0,Latvia,LV,LVA,1919968,Europe,11.87519792\r
-26/03/2020,26,3,2020,24,0,Latvia,LV,LVA,1919968,Europe,10.9897665\r
-25/03/2020,25,3,2020,17,0,Latvia,LV,LVA,1919968,Europe,9.84391407\r
-24/03/2020,24,3,2020,41,0,Latvia,LV,LVA,1919968,Europe,9.06265104\r
-23/03/2020,23,3,2020,15,0,Latvia,LV,LVA,1919968,Europe,7.08345139\r
-22/03/2020,22,3,2020,13,0,Latvia,LV,LVA,1919968,Europe,6.35427257\r
-21/03/2020,21,3,2020,25,0,Latvia,LV,LVA,1919968,Europe,5.72926215\r
-20/03/2020,20,3,2020,15,0,Latvia,LV,LVA,1919968,Europe,4.47924132\r
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-18/03/2020,18,3,2020,25,0,Latvia,LV,LVA,1919968,Europe,\r
-17/03/2020,17,3,2020,5,0,Latvia,LV,LVA,1919968,Europe,\r
-16/03/2020,16,3,2020,5,0,Latvia,LV,LVA,1919968,Europe,\r
-15/03/2020,15,3,2020,7,0,Latvia,LV,LVA,1919968,Europe,\r
-14/03/2020,14,3,2020,3,0,Latvia,LV,LVA,1919968,Europe,\r
-13/03/2020,13,3,2020,6,0,Latvia,LV,LVA,1919968,Europe,\r
-12/03/2020,12,3,2020,2,0,Latvia,LV,LVA,1919968,Europe,\r
-11/03/2020,11,3,2020,2,0,Latvia,LV,LVA,1919968,Europe,\r
-10/03/2020,10,3,2020,3,0,Latvia,LV,LVA,1919968,Europe,\r
-09/03/2020,9,3,2020,1,0,Latvia,LV,LVA,1919968,Europe,\r
-08/03/2020,8,3,2020,1,0,Latvia,LV,LVA,1919968,Europe,\r
-03/03/2020,3,3,2020,1,0,Latvia,LV,LVA,1919968,Europe,\r
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-18/08/2020,18,8,2020,456,2,Lebanon,LB,LBN,6855709,Asia,62.35678906\r
-17/08/2020,17,8,2020,439,6,Lebanon,LB,LBN,6855709,Asia,58.28718809\r
-16/08/2020,16,8,2020,397,3,Lebanon,LB,LBN,6855709,Asia,54.14465521\r
-15/08/2020,15,8,2020,334,2,Lebanon,LB,LBN,6855709,Asia,50.90647809\r
-14/08/2020,14,8,2020,298,3,Lebanon,LB,LBN,6855709,Asia,49.25821677\r
-13/08/2020,13,8,2020,292,2,Lebanon,LB,LBN,6855709,Asia,46.79311797\r
-12/08/2020,12,8,2020,309,7,Lebanon,LB,LBN,6855709,Asia,45.18861579\r
-11/08/2020,11,8,2020,295,4,Lebanon,LB,LBN,6855709,Asia,42.73810338\r
-10/08/2020,10,8,2020,294,0,Lebanon,LB,LBN,6855709,Asia,40.36052289\r
-09/08/2020,9,8,2020,272,6,Lebanon,LB,LBN,6855709,Asia,38.52263858\r
-08/08/2020,8,8,2020,279,0,Lebanon,LB,LBN,6855709,Asia,37.10775939\r
-07/08/2020,7,8,2020,255,2,Lebanon,LB,LBN,6855709,Asia,35.18235678\r
-06/08/2020,6,8,2020,355,3,Lebanon,LB,LBN,6855709,Asia,33.73830482\r
-05/08/2020,5,8,2020,0,0,Lebanon,LB,LBN,6855709,Asia,30.36885025\r
-04/08/2020,4,8,2020,177,3,Lebanon,LB,LBN,6855709,Asia,31.46282901\r
-03/08/2020,3,8,2020,155,1,Lebanon,LB,LBN,6855709,Asia,29.55201278\r
-02/08/2020,2,8,2020,175,0,Lebanon,LB,LBN,6855709,Asia,28.51637956\r
-01/08/2020,1,8,2020,221,4,Lebanon,LB,LBN,6855709,Asia,27.05774122\r
-31/07/2020,31,7,2020,129,2,Lebanon,LB,LBN,6855709,Asia,25.30737521\r
-30/07/2020,30,7,2020,182,1,Lebanon,LB,LBN,6855709,Asia,24.25715561\r
-29/07/2020,29,7,2020,141,3,Lebanon,LB,LBN,6855709,Asia,22.92979472\r
-28/07/2020,28,7,2020,132,0,Lebanon,LB,LBN,6855709,Asia,21.33987892\r
-27/07/2020,27,7,2020,168,4,Lebanon,LB,LBN,6855709,Asia,20.6543189\r
-26/07/2020,26,7,2020,175,1,Lebanon,LB,LBN,6855709,Asia,20.62514614\r
-25/07/2020,25,7,2020,147,3,Lebanon,LB,LBN,6855709,Asia,19.32695801\r
-24/07/2020,24,7,2020,156,0,Lebanon,LB,LBN,6855709,Asia,18.21839288\r
-23/07/2020,23,7,2020,124,2,Lebanon,LB,LBN,6855709,Asia,16.89103199\r
-22/07/2020,22,7,2020,75,0,Lebanon,LB,LBN,6855709,Asia,15.6511894\r
-21/07/2020,21,7,2020,46,1,Lebanon,LB,LBN,6855709,Asia,14.87811108\r
-20/07/2020,20,7,2020,84,0,Lebanon,LB,LBN,6855709,Asia,14.38217404\r
-19/07/2020,19,7,2020,75,0,Lebanon,LB,LBN,6855709,Asia,13.41947273\r
-18/07/2020,18,7,2020,101,0,Lebanon,LB,LBN,6855709,Asia,12.69015356\r
-17/07/2020,17,7,2020,57,2,Lebanon,LB,LBN,6855709,Asia,11.71286588\r
-16/07/2020,16,7,2020,91,1,Lebanon,LB,LBN,6855709,Asia,10.99813309\r
-15/07/2020,15,7,2020,32,1,Lebanon,LB,LBN,6855709,Asia,9.81663603\r
-14/07/2020,14,7,2020,85,0,Lebanon,LB,LBN,6855709,Asia,9.83122242\r
-13/07/2020,13,7,2020,166,0,Lebanon,LB,LBN,6855709,Asia,8.66431174\r
-12/07/2020,12,7,2020,86,0,Lebanon,LB,LBN,6855709,Asia,6.54928615\r
-11/07/2020,11,7,2020,71,0,Lebanon,LB,LBN,6855709,Asia,5.61575761\r
-10/07/2020,10,7,2020,65,0,Lebanon,LB,LBN,6855709,Asia,5.09064781\r
-09/07/2020,9,7,2020,39,0,Lebanon,LB,LBN,6855709,Asia,4.40508779\r
-08/07/2020,8,7,2020,22,0,Lebanon,LB,LBN,6855709,Asia,4.15711927\r
-07/07/2020,7,7,2020,12,0,Lebanon,LB,LBN,6855709,Asia,4.11336012\r
-06/07/2020,6,7,2020,18,1,Lebanon,LB,LBN,6855709,Asia,4.17170565\r
-05/07/2020,5,7,2020,25,0,Lebanon,LB,LBN,6855709,Asia,4.65305631\r
-04/07/2020,4,7,2020,34,0,Lebanon,LB,LBN,6855709,Asia,4.66764269\r
-03/07/2020,3,7,2020,8,1,Lebanon,LB,LBN,6855709,Asia,4.39050141\r
-02/07/2020,2,7,2020,10,0,Lebanon,LB,LBN,6855709,Asia,4.36132864\r
-01/07/2020,1,7,2020,33,0,Lebanon,LB,LBN,6855709,Asia,4.44884694\r
-30/06/2020,30,6,2020,5,0,Lebanon,LB,LBN,6855709,Asia,4.09877374\r
-29/06/2020,29,6,2020,21,1,Lebanon,LB,LBN,6855709,Asia,4.28839672\r
-28/06/2020,28,6,2020,22,0,Lebanon,LB,LBN,6855709,Asia,4.0404282\r
-27/06/2020,27,6,2020,35,0,Lebanon,LB,LBN,6855709,Asia,4.01125544\r
-26/06/2020,26,6,2020,18,0,Lebanon,LB,LBN,6855709,Asia,3.79245969\r
-25/06/2020,25,6,2020,22,1,Lebanon,LB,LBN,6855709,Asia,3.73411415\r
-24/06/2020,24,6,2020,19,0,Lebanon,LB,LBN,6855709,Asia,3.70494139\r
-23/06/2020,23,6,2020,16,0,Lebanon,LB,LBN,6855709,Asia,3.690355\r
-22/06/2020,22,6,2020,51,0,Lebanon,LB,LBN,6855709,Asia,3.73411415\r
-21/06/2020,21,6,2020,26,0,Lebanon,LB,LBN,6855709,Asia,3.15065882\r
-20/06/2020,20,6,2020,15,0,Lebanon,LB,LBN,6855709,Asia,2.88810391\r
-19/06/2020,19,6,2020,6,0,Lebanon,LB,LBN,6855709,Asia,2.75682646\r
-18/06/2020,18,6,2020,16,0,Lebanon,LB,LBN,6855709,Asia,3.39862733\r
-17/06/2020,17,6,2020,9,0,Lebanon,LB,LBN,6855709,Asia,3.36945457\r
-16/06/2020,16,6,2020,18,0,Lebanon,LB,LBN,6855709,Asia,3.36945457\r
-15/06/2020,15,6,2020,4,0,Lebanon,LB,LBN,6855709,Asia,3.29652265\r
-14/06/2020,14,6,2020,20,1,Lebanon,LB,LBN,6855709,Asia,3.66118224\r
-13/06/2020,13,6,2020,20,0,Lebanon,LB,LBN,6855709,Asia,3.64659585\r
-12/06/2020,12,6,2020,14,1,Lebanon,LB,LBN,6855709,Asia,3.41321372\r
-11/06/2020,11,6,2020,20,0,Lebanon,LB,LBN,6855709,Asia,3.31110903\r
-10/06/2020,10,6,2020,18,0,Lebanon,LB,LBN,6855709,Asia,3.32569542\r
-09/06/2020,9,6,2020,19,0,Lebanon,LB,LBN,6855709,Asia,3.36945457\r
-08/06/2020,8,6,2020,11,1,Lebanon,LB,LBN,6855709,Asia,3.1652452\r
-07/06/2020,7,6,2020,8,1,Lebanon,LB,LBN,6855709,Asia,3.2527635\r
-06/06/2020,6,6,2020,6,0,Lebanon,LB,LBN,6855709,Asia,3.29652265\r
-05/06/2020,5,6,2020,50,1,Lebanon,LB,LBN,6855709,Asia,4.11336012\r
-04/06/2020,4,6,2020,14,0,Lebanon,LB,LBN,6855709,Asia,4.30298311\r
-03/06/2020,3,6,2020,9,0,Lebanon,LB,LBN,6855709,Asia,4.20087842\r
-02/06/2020,2,6,2020,13,0,Lebanon,LB,LBN,6855709,Asia,4.40508779\r
-01/06/2020,1,6,2020,29,1,Lebanon,LB,LBN,6855709,Asia,4.50719247\r
-31/05/2020,31,5,2020,19,0,Lebanon,LB,LBN,6855709,Asia,4.2154648\r
-30/05/2020,30,5,2020,4,0,Lebanon,LB,LBN,6855709,Asia,4.09877374\r
-29/05/2020,29,5,2020,7,0,Lebanon,LB,LBN,6855709,Asia,4.11336012\r
-28/05/2020,28,5,2020,21,0,Lebanon,LB,LBN,6855709,Asia,4.1279465\r
-27/05/2020,27,5,2020,21,0,Lebanon,LB,LBN,6855709,Asia,3.93832352\r
-26/05/2020,26,5,2020,5,0,Lebanon,LB,LBN,6855709,Asia,3.79245969\r
-25/05/2020,25,5,2020,17,0,Lebanon,LB,LBN,6855709,Asia,3.92373714\r
-24/05/2020,24,5,2020,11,0,Lebanon,LB,LBN,6855709,Asia,4.20087842\r
-23/05/2020,23,5,2020,62,0,Lebanon,LB,LBN,6855709,Asia,4.23005119\r
-22/05/2020,22,5,2020,63,0,Lebanon,LB,LBN,6855709,Asia,3.50073202\r
-21/05/2020,21,5,2020,7,0,Lebanon,LB,LBN,6855709,Asia,3.0777269\r
-20/05/2020,20,5,2020,23,0,Lebanon,LB,LBN,6855709,Asia,3.10689967\r
-19/05/2020,19,5,2020,20,0,Lebanon,LB,LBN,6855709,Asia,2.78599923\r
-18/05/2020,18,5,2020,9,0,Lebanon,LB,LBN,6855709,Asia,2.53803071\r
-17/05/2020,17,5,2020,11,0,Lebanon,LB,LBN,6855709,Asia,2.4650988\r
-16/05/2020,16,5,2020,5,0,Lebanon,LB,LBN,6855709,Asia,2.36299411\r
-15/05/2020,15,5,2020,8,0,Lebanon,LB,LBN,6855709,Asia,2.34840773\r
-14/05/2020,14,5,2020,8,0,Lebanon,LB,LBN,6855709,Asia,2.29006219\r
-13/05/2020,13,5,2020,11,0,Lebanon,LB,LBN,6855709,Asia,2.23171666\r
-12/05/2020,12,5,2020,14,0,Lebanon,LB,LBN,6855709,Asia,2.17337113\r
-11/05/2020,11,5,2020,36,0,Lebanon,LB,LBN,6855709,Asia,2.01292091\r
-10/05/2020,10,5,2020,13,0,Lebanon,LB,LBN,6855709,Asia,1.53157026\r
-09/05/2020,9,5,2020,12,1,Lebanon,LB,LBN,6855709,Asia,1.45863834\r
-08/05/2020,8,5,2020,34,0,Lebanon,LB,LBN,6855709,Asia,1.40029281\r
-07/05/2020,7,5,2020,9,0,Lebanon,LB,LBN,6855709,Asia,0.99187407\r
-06/05/2020,6,5,2020,1,0,Lebanon,LB,LBN,6855709,Asia,0.93352854\r
-05/05/2020,5,5,2020,3,0,Lebanon,LB,LBN,6855709,Asia,0.91894215\r
-04/05/2020,4,5,2020,4,0,Lebanon,LB,LBN,6855709,Asia,0.93352854\r
-03/05/2020,3,5,2020,4,1,Lebanon,LB,LBN,6855709,Asia,0.88976939\r
-02/05/2020,2,5,2020,4,0,Lebanon,LB,LBN,6855709,Asia,0.88976939\r
-01/05/2020,1,5,2020,4,0,Lebanon,LB,LBN,6855709,Asia,0.90435577\r
-30/04/2020,30,4,2020,4,0,Lebanon,LB,LBN,6855709,Asia,0.91894215\r
-29/04/2020,29,4,2020,7,0,Lebanon,LB,LBN,6855709,Asia,1.10856514\r
-28/04/2020,28,4,2020,3,0,Lebanon,LB,LBN,6855709,Asia,1.13773791\r
-27/04/2020,27,4,2020,3,0,Lebanon,LB,LBN,6855709,Asia,1.12315152\r
-26/04/2020,26,4,2020,8,2,Lebanon,LB,LBN,6855709,Asia,1.23984259\r
-25/04/2020,25,4,2020,8,0,Lebanon,LB,LBN,6855709,Asia,1.26901536\r
-24/04/2020,24,4,2020,6,0,Lebanon,LB,LBN,6855709,Asia,1.54615664\r
-23/04/2020,23,4,2020,5,1,Lebanon,LB,LBN,6855709,Asia,1.56074302\r
-22/04/2020,22,4,2020,0,0,Lebanon,LB,LBN,6855709,Asia,1.88164346\r
-21/04/2020,21,4,2020,4,0,Lebanon,LB,LBN,6855709,Asia,1.98374814\r
-20/04/2020,20,4,2020,1,0,Lebanon,LB,LBN,6855709,Asia,2.12961198\r
-19/04/2020,19,4,2020,4,0,Lebanon,LB,LBN,6855709,Asia,2.21713028\r
-18/04/2020,18,4,2020,5,0,Lebanon,LB,LBN,6855709,Asia,2.53803071\r
-17/04/2020,17,4,2020,5,0,Lebanon,LB,LBN,6855709,Asia,2.4650988\r
-16/04/2020,16,4,2020,17,0,Lebanon,LB,LBN,6855709,Asia,2.61096263\r
-15/04/2020,15,4,2020,9,1,Lebanon,LB,LBN,6855709,Asia,2.59637625\r
-14/04/2020,14,4,2020,2,0,Lebanon,LB,LBN,6855709,Asia,2.71306731\r
-13/04/2020,13,4,2020,11,0,Lebanon,LB,LBN,6855709,Asia,2.80058561\r
-12/04/2020,12,4,2020,10,0,Lebanon,LB,LBN,6855709,Asia,3.01938137\r
-11/04/2020,11,4,2020,27,1,Lebanon,LB,LBN,6855709,Asia,3.17983158\r
-10/04/2020,10,4,2020,7,0,Lebanon,LB,LBN,6855709,Asia,3.12148605\r
-09/04/2020,9,4,2020,27,0,Lebanon,LB,LBN,6855709,Asia,3.52990478\r
-08/04/2020,8,4,2020,7,0,Lebanon,LB,LBN,6855709,Asia,3.55907755\r
-07/04/2020,7,4,2020,14,1,Lebanon,LB,LBN,6855709,Asia,3.99666905\r
-06/04/2020,6,4,2020,7,1,Lebanon,LB,LBN,6855709,Asia,4.06960097\r
-05/04/2020,5,4,2020,26,1,Lebanon,LB,LBN,6855709,Asia,4.23005119\r
-04/04/2020,4,4,2020,0,0,Lebanon,LB,LBN,6855709,Asia,4.82809291\r
-03/04/2020,3,4,2020,15,4,Lebanon,LB,LBN,6855709,Asia,5.03230228\r
-02/04/2020,2,4,2020,16,0,Lebanon,LB,LBN,6855709,Asia,5.04688866\r
-01/04/2020,1,4,2020,17,1,Lebanon,LB,LBN,6855709,Asia,5.00312951\r
-31/03/2020,31,3,2020,8,1,Lebanon,LB,LBN,6855709,Asia,4.75516099\r
-30/03/2020,30,3,2020,26,2,Lebanon,LB,LBN,6855709,Asia,4.94478397\r
-29/03/2020,29,3,2020,21,1,Lebanon,LB,LBN,6855709,Asia,4.65305631\r
-28/03/2020,28,3,2020,23,1,Lebanon,LB,LBN,6855709,Asia,4.74057461\r
-27/03/2020,27,3,2020,35,2,Lebanon,LB,LBN,6855709,Asia,4.47801971\r
-26/03/2020,26,3,2020,29,0,Lebanon,LB,LBN,6855709,Asia,4.25922395\r
-25/03/2020,25,3,2020,37,0,Lebanon,LB,LBN,6855709,Asia,3.83621884\r
-24/03/2020,24,3,2020,19,0,Lebanon,LB,LBN,6855709,Asia,3.4278001\r
-23/03/2020,23,3,2020,18,0,Lebanon,LB,LBN,6855709,Asia,3.29652265\r
-22/03/2020,22,3,2020,67,0,Lebanon,LB,LBN,6855709,Asia,3.12148605\r
-21/03/2020,21,3,2020,14,0,Lebanon,LB,LBN,6855709,Asia,2.18795751\r
-20/03/2020,20,3,2020,16,0,Lebanon,LB,LBN,6855709,Asia,2.02750729\r
-19/03/2020,19,3,2020,13,1,Lebanon,LB,LBN,6855709,Asia,1.88164346\r
-18/03/2020,18,3,2020,0,0,Lebanon,LB,LBN,6855709,Asia,1.70660686\r
-17/03/2020,17,3,2020,21,0,Lebanon,LB,LBN,6855709,Asia,1.70660686\r
-16/03/2020,16,3,2020,6,0,Lebanon,LB,LBN,6855709,Asia,1.41487919\r
-15/03/2020,15,3,2020,27,1,Lebanon,LB,LBN,6855709,Asia,1.34194727\r
-13/03/2020,13,3,2020,5,0,Lebanon,LB,LBN,6855709,Asia,0.94811492\r
-12/03/2020,12,3,2020,20,1,Lebanon,LB,LBN,6855709,Asia,0.875183\r
-11/03/2020,11,3,2020,0,1,Lebanon,LB,LBN,6855709,Asia,0.58345534\r
-10/03/2020,10,3,2020,9,0,Lebanon,LB,LBN,6855709,Asia,0.58345534\r
-09/03/2020,9,3,2020,10,0,Lebanon,LB,LBN,6855709,Asia,0.46676427\r
-07/03/2020,7,3,2020,6,0,Lebanon,LB,LBN,6855709,Asia,0.32090043\r
-06/03/2020,6,3,2020,3,0,Lebanon,LB,LBN,6855709,Asia,0.23338213\r
-03/03/2020,3,3,2020,3,0,Lebanon,LB,LBN,6855709,Asia,0.18962298\r
-02/03/2020,2,3,2020,6,0,Lebanon,LB,LBN,6855709,Asia,0.14586383\r
-01/03/2020,1,3,2020,1,0,Lebanon,LB,LBN,6855709,Asia,0.05834553\r
-29/02/2020,29,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0.04375915\r
-28/02/2020,28,2,2020,1,0,Lebanon,LB,LBN,6855709,Asia,0.04375915\r
-27/02/2020,27,2,2020,1,0,Lebanon,LB,LBN,6855709,Asia,0.02917277\r
-26/02/2020,26,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0.01458638\r
-25/02/2020,25,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0.01458638\r
-24/02/2020,24,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0.01458638\r
-23/02/2020,23,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0.01458638\r
-22/02/2020,22,2,2020,1,0,Lebanon,LB,LBN,6855709,Asia,0.01458638\r
-21/02/2020,21,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-20/02/2020,20,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-19/02/2020,19,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-18/02/2020,18,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-17/02/2020,17,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-16/02/2020,16,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-15/02/2020,15,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-14/02/2020,14,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-13/02/2020,13,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-12/02/2020,12,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-11/02/2020,11,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-10/02/2020,10,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-09/02/2020,9,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-08/02/2020,8,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-07/02/2020,7,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-06/02/2020,6,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-05/02/2020,5,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-04/02/2020,4,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-03/02/2020,3,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-02/02/2020,2,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-01/02/2020,1,2,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-31/01/2020,31,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-30/01/2020,30,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-29/01/2020,29,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-28/01/2020,28,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-27/01/2020,27,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-26/01/2020,26,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-25/01/2020,25,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-24/01/2020,24,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-23/01/2020,23,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-22/01/2020,22,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-21/01/2020,21,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-20/01/2020,20,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-19/01/2020,19,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-18/01/2020,18,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-17/01/2020,17,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-16/01/2020,16,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-15/01/2020,15,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-14/01/2020,14,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-13/01/2020,13,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,0\r
-12/01/2020,12,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,\r
-11/01/2020,11,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,\r
-10/01/2020,10,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,\r
-09/01/2020,9,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,\r
-08/01/2020,8,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,\r
-07/01/2020,7,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,\r
-06/01/2020,6,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,\r
-05/01/2020,5,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,\r
-04/01/2020,4,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,\r
-03/01/2020,3,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,\r
-02/01/2020,2,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,\r
-01/01/2020,1,1,2020,0,0,Lebanon,LB,LBN,6855709,Asia,\r
-31/12/2019,31,12,2019,0,0,Lebanon,LB,LBN,6855709,Asia,\r
-19/08/2020,19,8,2020,0,0,Lesotho,LS,LSO,2125267,Africa,10.35164052\r
-18/08/2020,18,8,2020,0,0,Lesotho,LS,LSO,2125267,Africa,10.72806382\r
-17/08/2020,17,8,2020,43,5,Lesotho,LS,LSO,2125267,Africa,10.72806382\r
-16/08/2020,16,8,2020,19,0,Lesotho,LS,LSO,2125267,Africa,9.45763521\r
-15/08/2020,15,8,2020,69,1,Lesotho,LS,LSO,2125267,Africa,13.17481521\r
-14/08/2020,14,8,2020,17,0,Lesotho,LS,LSO,2125267,Africa,9.92816432\r
-13/08/2020,13,8,2020,17,0,Lesotho,LS,LSO,2125267,Africa,10.44574635\r
-12/08/2020,12,8,2020,0,0,Lesotho,LS,LSO,2125267,Africa,12.98660357\r
-11/08/2020,11,8,2020,39,1,Lesotho,LS,LSO,2125267,Africa,12.98660357\r
-10/08/2020,10,8,2020,0,0,Lesotho,LS,LSO,2125267,Africa,13.92766179\r
-09/08/2020,9,8,2020,0,0,Lesotho,LS,LSO,2125267,Africa,15.1980904\r
-08/08/2020,8,8,2020,0,0,Lesotho,LS,LSO,2125267,Africa,18.02126509\r
-07/08/2020,7,8,2020,16,2,Lesotho,LS,LSO,2125267,Africa,18.02126509\r
-06/08/2020,6,8,2020,0,0,Lesotho,LS,LSO,2125267,Africa,17.26841851\r
-05/08/2020,5,8,2020,8,2,Lesotho,LS,LSO,2125267,Africa,17.26841851\r
-04/08/2020,4,8,2020,0,0,Lesotho,LS,LSO,2125267,Africa,16.89199522\r
-03/08/2020,3,8,2020,16,5,Lesotho,LS,LSO,2125267,Africa,16.89199522\r
-02/08/2020,2,8,2020,98,1,Lesotho,LS,LSO,2125267,Africa,16.13914863\r
-01/08/2020,1,8,2020,0,0,Lesotho,LS,LSO,2125267,Africa,13.78650306\r
-31/07/2020,31,7,2020,28,0,Lesotho,LS,LSO,2125267,Africa,16.37441319\r
-30/07/2020,30,7,2020,71,1,Lesotho,LS,LSO,2125267,Africa,15.05693167\r
-29/07/2020,29,7,2020,0,0,Lesotho,LS,LSO,2125267,Africa,12.23375698\r
-28/07/2020,28,7,2020,59,1,Lesotho,LS,LSO,2125267,Africa,12.79839192\r
-27/07/2020,27,7,2020,27,2,Lesotho,LS,LSO,2125267,Africa,10.02227014\r
-26/07/2020,26,7,2020,60,3,Lesotho,LS,LSO,2125267,Africa,11.0574342\r
-25/07/2020,25,7,2020,0,0,Lesotho,LS,LSO,2125267,Africa,10.58690508\r
-24/07/2020,24,7,2020,0,0,Lesotho,LS,LSO,2125267,Africa,10.58690508\r
-23/07/2020,23,7,2020,0,0,Lesotho,LS,LSO,2125267,Africa,12.61018027\r
-22/07/2020,22,7,2020,0,0,Lesotho,LS,LSO,2125267,Africa,12.61018027\r
-21/07/2020,21,7,2020,0,0,Lesotho,LS,LSO,2125267,Africa,12.61018027\r
-20/07/2020,20,7,2020,0,0,Lesotho,LS,LSO,2125267,Africa,13.17481521\r
-19/07/2020,19,7,2020,48,3,Lesotho,LS,LSO,2125267,Africa,15.24514332\r
-18/07/2020,18,7,2020,55,0,Lesotho,LS,LSO,2125267,Africa,12.98660357\r
-17/07/2020,17,7,2020,0,0,Lesotho,LS,LSO,2125267,Africa,10.39869343\r
-16/07/2020,16,7,2020,11,0,Lesotho,LS,LSO,2125267,Africa,10.39869343\r
-15/07/2020,15,7,2020,12,1,Lesotho,LS,LSO,2125267,Africa,10.2575347\r
-14/07/2020,14,7,2020,0,0,Lesotho,LS,LSO,2125267,Africa,9.69289976\r
-13/07/2020,13,7,2020,49,1,Lesotho,LS,LSO,2125267,Africa,9.69289976\r
-12/07/2020,12,7,2020,50,0,Lesotho,LS,LSO,2125267,Africa,7.52846584\r
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-29/06/2020,29,6,2020,3,0,Lesotho,LS,LSO,2125267,Africa,1.08221696\r
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-27/06/2020,27,6,2020,4,0,Lesotho,LS,LSO,2125267,Africa,0.94105823\r
-26/06/2020,26,6,2020,3,0,Lesotho,LS,LSO,2125267,Africa,0.75284658\r
-25/06/2020,25,6,2020,0,0,Lesotho,LS,LSO,2125267,Africa,0.61168785\r
-24/06/2020,24,6,2020,13,0,Lesotho,LS,LSO,2125267,Africa,0.61168785\r
-23/06/2020,23,6,2020,0,0,Lesotho,LS,LSO,2125267,Africa,0\r
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-21/06/2020,21,6,2020,0,0,Lesotho,LS,LSO,2125267,Africa,0\r
-20/06/2020,20,6,2020,0,0,Lesotho,LS,LSO,2125267,Africa,0\r
-19/06/2020,19,6,2020,0,0,Lesotho,LS,LSO,2125267,Africa,0\r
-18/06/2020,18,6,2020,0,0,Lesotho,LS,LSO,2125267,Africa,0.09410582\r
-17/06/2020,17,6,2020,0,0,Lesotho,LS,LSO,2125267,Africa,0.09410582\r
-16/06/2020,16,6,2020,0,0,Lesotho,LS,LSO,2125267,Africa,0.09410582\r
-15/06/2020,15,6,2020,0,0,Lesotho,LS,LSO,2125267,Africa,0.09410582\r
-14/06/2020,14,6,2020,0,0,Lesotho,LS,LSO,2125267,Africa,0.09410582\r
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-12/06/2020,12,6,2020,0,0,Lesotho,LS,LSO,2125267,Africa,0.09410582\r
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-01/06/2020,1,6,2020,0,0,Lesotho,LS,LSO,2125267,Africa,0.04705291\r
-31/05/2020,31,5,2020,0,0,Lesotho,LS,LSO,2125267,Africa,0.04705291\r
-30/05/2020,30,5,2020,0,0,Lesotho,LS,LSO,2125267,Africa,0.04705291\r
-29/05/2020,29,5,2020,0,0,Lesotho,LS,LSO,2125267,Africa,0.04705291\r
-28/05/2020,28,5,2020,0,0,Lesotho,LS,LSO,2125267,Africa,0.09410582\r
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-26/05/2020,26,5,2020,0,0,Lesotho,LS,LSO,2125267,Africa,\r
-25/05/2020,25,5,2020,0,0,Lesotho,LS,LSO,2125267,Africa,\r
-24/05/2020,24,5,2020,1,0,Lesotho,LS,LSO,2125267,Africa,\r
-23/05/2020,23,5,2020,0,0,Lesotho,LS,LSO,2125267,Africa,\r
-22/05/2020,22,5,2020,0,0,Lesotho,LS,LSO,2125267,Africa,\r
-21/05/2020,21,5,2020,0,0,Lesotho,LS,LSO,2125267,Africa,\r
-20/05/2020,20,5,2020,0,0,Lesotho,LS,LSO,2125267,Africa,\r
-19/05/2020,19,5,2020,0,0,Lesotho,LS,LSO,2125267,Africa,\r
-18/05/2020,18,5,2020,0,0,Lesotho,LS,LSO,2125267,Africa,\r
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-18/08/2020,18,8,2020,20,0,Liberia,LR,LBR,4937374,Africa,1.27598193\r
-17/08/2020,17,8,2020,0,0,Liberia,LR,LBR,4937374,Africa,1.01268407\r
-16/08/2020,16,8,2020,5,0,Liberia,LR,LBR,4937374,Africa,1.37725034\r
-15/08/2020,15,8,2020,0,0,Liberia,LR,LBR,4937374,Africa,1.33674297\r
-14/08/2020,14,8,2020,0,0,Liberia,LR,LBR,4937374,Africa,1.43801138\r
-13/08/2020,13,8,2020,2,1,Liberia,LR,LBR,4937374,Africa,1.47851874\r
-12/08/2020,12,8,2020,10,2,Liberia,LR,LBR,4937374,Africa,1.47851874\r
-11/08/2020,11,8,2020,3,0,Liberia,LR,LBR,4937374,Africa,1.47851874\r
-10/08/2020,10,8,2020,3,0,Liberia,LR,LBR,4937374,Africa,1.51902611\r
-09/08/2020,9,8,2020,4,1,Liberia,LR,LBR,4937374,Africa,1.60004083\r
-08/08/2020,8,8,2020,6,0,Liberia,LR,LBR,4937374,Africa,1.92409973\r
-07/08/2020,7,8,2020,3,0,Liberia,LR,LBR,4937374,Africa,2.16714391\r
-06/08/2020,6,8,2020,5,0,Liberia,LR,LBR,4937374,Africa,2.16714391\r
-05/08/2020,5,8,2020,2,0,Liberia,LR,LBR,4937374,Africa,2.18739759\r
-04/08/2020,4,8,2020,7,1,Liberia,LR,LBR,4937374,Africa,2.16714391\r
-03/08/2020,3,8,2020,18,2,Liberia,LR,LBR,4937374,Africa,2.34942704\r
-02/08/2020,2,8,2020,3,0,Liberia,LR,LBR,4937374,Africa,2.04562182\r
-01/08/2020,1,8,2020,5,2,Liberia,LR,LBR,4937374,Africa,2.04562182\r
-31/07/2020,31,7,2020,2,1,Liberia,LR,LBR,4937374,Africa,2.24815864\r
-30/07/2020,30,7,2020,2,0,Liberia,LR,LBR,4937374,Africa,2.49120281\r
-29/07/2020,29,7,2020,10,0,Liberia,LR,LBR,4937374,Africa,3.09881326\r
-28/07/2020,28,7,2020,5,0,Liberia,LR,LBR,4937374,Africa,2.89627644\r
-27/07/2020,27,7,2020,7,1,Liberia,LR,LBR,4937374,Africa,3.07855957\r
-26/07/2020,26,7,2020,20,0,Liberia,LR,LBR,4937374,Africa,3.17982798\r
-25/07/2020,25,7,2020,18,0,Liberia,LR,LBR,4937374,Africa,3.4836332\r
-24/07/2020,24,7,2020,3,1,Liberia,LR,LBR,4937374,Africa,3.24058903\r
-23/07/2020,23,7,2020,6,0,Liberia,LR,LBR,4937374,Africa,3.80769211\r
-22/07/2020,22,7,2020,1,0,Liberia,LR,LBR,4937374,Africa,3.86845315\r
-21/07/2020,21,7,2020,16,0,Liberia,LR,LBR,4937374,Africa,4.37479518\r
-20/07/2020,20,7,2020,3,0,Liberia,LR,LBR,4937374,Africa,4.39504887\r
-19/07/2020,19,7,2020,3,1,Liberia,LR,LBR,4937374,Africa,4.43555623\r
-18/07/2020,18,7,2020,15,1,Liberia,LR,LBR,4937374,Africa,5.10392772\r
-17/07/2020,17,7,2020,14,2,Liberia,LR,LBR,4937374,Africa,5.08367403\r
-16/07/2020,16,7,2020,32,15,Liberia,LR,LBR,4937374,Africa,5.10392772\r
-15/07/2020,15,7,2020,0,0,Liberia,LR,LBR,4937374,Africa,4.94189826\r
-14/07/2020,14,7,2020,14,0,Liberia,LR,LBR,4937374,Africa,5.14443508\r
-13/07/2020,13,7,2020,12,4,Liberia,LR,LBR,4937374,Africa,4.9013909\r
-12/07/2020,12,7,2020,35,0,Liberia,LR,LBR,4937374,Africa,5.4482403\r
-11/07/2020,11,7,2020,6,5,Liberia,LR,LBR,4937374,Africa,5.65077711\r
-10/07/2020,10,7,2020,31,1,Liberia,LR,LBR,4937374,Africa,5.59001607\r
-09/07/2020,9,7,2020,9,0,Liberia,LR,LBR,4937374,Africa,5.34697189\r
-08/07/2020,8,7,2020,26,2,Liberia,LR,LBR,4937374,Africa,5.36722557\r
-07/07/2020,7,7,2020,17,2,Liberia,LR,LBR,4937374,Africa,4.88113722\r
-06/07/2020,6,7,2020,5,0,Liberia,LR,LBR,4937374,Africa,5.02291299\r
-05/07/2020,5,7,2020,36,0,Liberia,LR,LBR,4937374,Africa,5.42798662\r
-04/07/2020,4,7,2020,14,0,Liberia,LR,LBR,4937374,Africa,5.10392772\r
-03/07/2020,3,7,2020,15,0,Liberia,LR,LBR,4937374,Africa,5.61026975\r
-02/07/2020,2,7,2020,24,1,Liberia,LR,LBR,4937374,Africa,5.97483602\r
-01/07/2020,1,7,2020,10,0,Liberia,LR,LBR,4937374,Africa,5.48874766\r
-30/06/2020,30,6,2020,2,2,Liberia,LR,LBR,4937374,Africa,5.50900134\r
-29/06/2020,29,6,2020,39,0,Liberia,LR,LBR,4937374,Africa,6.27864124\r
-28/06/2020,28,6,2020,45,0,Liberia,LR,LBR,4937374,Africa,5.73179184\r
-27/06/2020,27,6,2020,3,0,Liberia,LR,LBR,4937374,Africa,5.32671821\r
-26/06/2020,26,6,2020,19,0,Liberia,LR,LBR,4937374,Africa,5.48874766\r
-25/06/2020,25,6,2020,10,0,Liberia,LR,LBR,4937374,Africa,5.36722557\r
-24/06/2020,24,6,2020,2,0,Liberia,LR,LBR,4937374,Africa,5.4482403\r
-23/06/2020,23,6,2020,24,0,Liberia,LR,LBR,4937374,Africa,5.67103079\r
-22/06/2020,22,6,2020,25,1,Liberia,LR,LBR,4937374,Africa,5.40773294\r
-21/06/2020,21,6,2020,20,0,Liberia,LR,LBR,4937374,Africa,5.18494244\r
-20/06/2020,20,6,2020,39,0,Liberia,LR,LBR,4937374,Africa,5.00265931\r
-19/06/2020,19,6,2020,33,0,Liberia,LR,LBR,4937374,Africa,4.47606359\r
-18/06/2020,18,6,2020,0,0,Liberia,LR,LBR,4937374,Africa,3.90896051\r
-17/06/2020,17,6,2020,11,0,Liberia,LR,LBR,4937374,Africa,4.01022892\r
-16/06/2020,16,6,2020,40,1,Liberia,LR,LBR,4937374,Africa,4.09124364\r
-15/06/2020,15,6,2020,12,0,Liberia,LR,LBR,4937374,Africa,3.44312584\r
-14/06/2020,14,6,2020,25,0,Liberia,LR,LBR,4937374,Africa,3.36211111\r
-13/06/2020,13,6,2020,11,1,Liberia,LR,LBR,4937374,Africa,2.99754485\r
-12/06/2020,12,6,2020,13,0,Liberia,LR,LBR,4937374,Africa,2.85576908\r
-11/06/2020,11,6,2020,14,0,Liberia,LR,LBR,4937374,Africa,2.65323226\r
-10/06/2020,10,6,2020,13,1,Liberia,LR,LBR,4937374,Africa,2.36968073\r
-09/06/2020,9,6,2020,11,0,Liberia,LR,LBR,4937374,Africa,2.12663655\r
-08/06/2020,8,6,2020,14,0,Liberia,LR,LBR,4937374,Africa,1.90384605\r
-07/06/2020,7,6,2020,11,0,Liberia,LR,LBR,4937374,Africa,1.82283133\r
-06/06/2020,6,6,2020,13,2,Liberia,LR,LBR,4937374,Africa,1.72156292\r
-05/06/2020,5,6,2020,5,0,Liberia,LR,LBR,4937374,Africa,1.64054819\r
-04/06/2020,4,6,2020,5,0,Liberia,LR,LBR,4937374,Africa,1.57978715\r
-03/06/2020,3,6,2020,15,1,Liberia,LR,LBR,4937374,Africa,1.57978715\r
-02/06/2020,2,6,2020,8,0,Liberia,LR,LBR,4937374,Africa,1.35699665\r
-01/06/2020,1,6,2020,8,0,Liberia,LR,LBR,4937374,Africa,1.25572825\r
-31/05/2020,31,5,2020,7,0,Liberia,LR,LBR,4937374,Africa,1.15445984\r
-30/05/2020,30,5,2020,4,0,Liberia,LR,LBR,4937374,Africa,1.0936988\r
-29/05/2020,29,5,2020,3,0,Liberia,LR,LBR,4937374,Africa,1.0936988\r
-28/05/2020,28,5,2020,0,1,Liberia,LR,LBR,4937374,Africa,1.07344511\r
-27/05/2020,27,5,2020,1,0,Liberia,LR,LBR,4937374,Africa,1.0936988\r
-26/05/2020,26,5,2020,0,0,Liberia,LR,LBR,4937374,Africa,1.0936988\r
-25/05/2020,25,5,2020,10,0,Liberia,LR,LBR,4937374,Africa,1.33674297\r
-24/05/2020,24,5,2020,6,2,Liberia,LR,LBR,4937374,Africa,1.13420616\r
-23/05/2020,23,5,2020,9,1,Liberia,LR,LBR,4937374,Africa,1.01268407\r
-22/05/2020,22,5,2020,2,0,Liberia,LR,LBR,4937374,Africa,1.03293775\r
-21/05/2020,21,5,2020,5,0,Liberia,LR,LBR,4937374,Africa,1.21522088\r
-20/05/2020,20,5,2020,4,1,Liberia,LR,LBR,4937374,Africa,1.27598193\r
-19/05/2020,19,5,2020,3,1,Liberia,LR,LBR,4937374,Africa,1.27598193\r
-18/05/2020,18,5,2020,3,1,Liberia,LR,LBR,4937374,Africa,1.37725034\r
-17/05/2020,17,5,2020,4,0,Liberia,LR,LBR,4937374,Africa,1.39750402\r
-16/05/2020,16,5,2020,4,0,Liberia,LR,LBR,4937374,Africa,1.35699665\r
-15/05/2020,15,5,2020,2,0,Liberia,LR,LBR,4937374,Africa,1.49877242\r
-14/05/2020,14,5,2020,1,0,Liberia,LR,LBR,4937374,Africa,1.45826506\r
-13/05/2020,13,5,2020,1,0,Liberia,LR,LBR,4937374,Africa,1.43801138\r
-12/05/2020,12,5,2020,12,0,Liberia,LR,LBR,4937374,Africa,1.57978715\r
-11/05/2020,11,5,2020,0,0,Liberia,LR,LBR,4937374,Africa,1.51902611\r
-10/05/2020,10,5,2020,0,0,Liberia,LR,LBR,4937374,Africa,1.60004083\r
-09/05/2020,9,5,2020,10,0,Liberia,LR,LBR,4937374,Africa,1.66080188\r
-08/05/2020,8,5,2020,11,0,Liberia,LR,LBR,4937374,Africa,1.78232396\r
-07/05/2020,7,5,2020,8,0,Liberia,LR,LBR,4937374,Africa,1.55953347\r
-06/05/2020,6,5,2020,4,2,Liberia,LR,LBR,4937374,Africa,1.39750402\r
-05/05/2020,5,5,2020,8,0,Liberia,LR,LBR,4937374,Africa,1.35699665\r
-04/05/2020,4,5,2020,4,0,Liberia,LR,LBR,4937374,Africa,1.35699665\r
-03/05/2020,3,5,2020,2,0,Liberia,LR,LBR,4937374,Africa,1.47851874\r
-02/05/2020,2,5,2020,11,2,Liberia,LR,LBR,4937374,Africa,1.53927979\r
-01/05/2020,1,5,2020,0,0,Liberia,LR,LBR,4937374,Africa,1.37725034\r
-30/04/2020,30,4,2020,0,0,Liberia,LR,LBR,4937374,Africa,1.66080188\r
-29/04/2020,29,4,2020,8,0,Liberia,LR,LBR,4937374,Africa,1.66080188\r
-28/04/2020,28,4,2020,9,4,Liberia,LR,LBR,4937374,Africa,1.49877242\r
-27/04/2020,27,4,2020,4,1,Liberia,LR,LBR,4937374,Africa,1.49877242\r
-26/04/2020,26,4,2020,3,3,Liberia,LR,LBR,4937374,Africa,1.45826506\r
-25/04/2020,25,4,2020,16,0,Liberia,LR,LBR,4937374,Africa,1.62029451\r
-24/04/2020,24,4,2020,0,0,Liberia,LR,LBR,4937374,Africa,1.4177577\r
-23/04/2020,23,4,2020,0,0,Liberia,LR,LBR,4937374,Africa,1.4177577\r
-22/04/2020,22,4,2020,2,0,Liberia,LR,LBR,4937374,Africa,1.76207028\r
-21/04/2020,21,4,2020,8,0,Liberia,LR,LBR,4937374,Africa,1.72156292\r
-20/04/2020,20,4,2020,10,1,Liberia,LR,LBR,4937374,Africa,1.57978715\r
-19/04/2020,19,4,2020,5,0,Liberia,LR,LBR,4937374,Africa,1.43801138\r
-18/04/2020,18,4,2020,3,1,Liberia,LR,LBR,4937374,Africa,1.39750402\r
-17/04/2020,17,4,2020,14,0,Liberia,LR,LBR,4937374,Africa,1.35699665\r
-16/04/2020,16,4,2020,0,0,Liberia,LR,LBR,4937374,Africa,1.07344511\r
-15/04/2020,15,4,2020,0,0,Liberia,LR,LBR,4937374,Africa,1.13420616\r
-14/04/2020,14,4,2020,9,1,Liberia,LR,LBR,4937374,Africa,1.13420616\r
-13/04/2020,13,4,2020,2,0,Liberia,LR,LBR,4937374,Africa,0.95192303\r
-12/04/2020,12,4,2020,11,1,Liberia,LR,LBR,4937374,Africa,0.91141566\r
-11/04/2020,11,4,2020,6,0,Liberia,LR,LBR,4937374,Africa,0.68862517\r
-10/04/2020,10,4,2020,0,0,Liberia,LR,LBR,4937374,Africa,0.56710308\r
-09/04/2020,9,4,2020,17,1,Liberia,LR,LBR,4937374,Africa,0.56710308\r
-08/04/2020,8,4,2020,0,0,Liberia,LR,LBR,4937374,Africa,0.2227905\r
-07/04/2020,7,4,2020,1,0,Liberia,LR,LBR,4937374,Africa,0.2227905\r
-06/04/2020,6,4,2020,3,2,Liberia,LR,LBR,4937374,Africa,0.20253681\r
-05/04/2020,5,4,2020,3,1,Liberia,LR,LBR,4937374,Africa,0.14177577\r
-04/04/2020,4,4,2020,1,0,Liberia,LR,LBR,4937374,Africa,0.10126841\r
-03/04/2020,3,4,2020,0,0,Liberia,LR,LBR,4937374,Africa,0.08101473\r
-02/04/2020,2,4,2020,3,0,Liberia,LR,LBR,4937374,Africa,0.08101473\r
-01/04/2020,1,4,2020,0,0,Liberia,LR,LBR,4937374,Africa,0.02025368\r
-31/03/2020,31,3,2020,0,0,Liberia,LR,LBR,4937374,Africa,0.04050736\r
-30/03/2020,30,3,2020,0,0,Liberia,LR,LBR,4937374,Africa,0.06076104\r
-29/03/2020,29,3,2020,0,0,Liberia,LR,LBR,4937374,Africa,\r
-28/03/2020,28,3,2020,0,0,Liberia,LR,LBR,4937374,Africa,\r
-27/03/2020,27,3,2020,0,0,Liberia,LR,LBR,4937374,Africa,\r
-26/03/2020,26,3,2020,0,0,Liberia,LR,LBR,4937374,Africa,\r
-25/03/2020,25,3,2020,0,0,Liberia,LR,LBR,4937374,Africa,\r
-24/03/2020,24,3,2020,0,0,Liberia,LR,LBR,4937374,Africa,\r
-23/03/2020,23,3,2020,0,0,Liberia,LR,LBR,4937374,Africa,\r
-22/03/2020,22,3,2020,1,0,Liberia,LR,LBR,4937374,Africa,\r
-21/03/2020,21,3,2020,0,0,Liberia,LR,LBR,4937374,Africa,\r
-20/03/2020,20,3,2020,0,0,Liberia,LR,LBR,4937374,Africa,\r
-19/03/2020,19,3,2020,0,0,Liberia,LR,LBR,4937374,Africa,\r
-18/03/2020,18,3,2020,1,0,Liberia,LR,LBR,4937374,Africa,\r
-17/03/2020,17,3,2020,1,0,Liberia,LR,LBR,4937374,Africa,\r
-19/08/2020,19,8,2020,0,0,Libya,LY,LBY,6777453,Africa,66.6327011\r
-18/08/2020,18,8,2020,841,12,Libya,LY,LBY,6777453,Africa,66.6327011\r
-17/08/2020,17,8,2020,0,0,Libya,LY,LBY,6777453,Africa,59.71269738\r
-16/08/2020,16,8,2020,411,6,Libya,LY,LBY,6777453,Africa,60.74553376\r
-15/08/2020,15,8,2020,277,4,Libya,LY,LBY,6777453,Africa,60.56847609\r
-14/08/2020,14,8,2020,748,3,Libya,LY,LBY,6777453,Africa,56.481395\r
-13/08/2020,13,8,2020,373,7,Libya,LY,LBY,6777453,Africa,48.46953568\r
-12/08/2020,12,8,2020,388,5,Libya,LY,LBY,6777453,Africa,45.76940629\r
-11/08/2020,11,8,2020,309,7,Libya,LY,LBY,6777453,Africa,40.04454181\r
-10/08/2020,10,8,2020,153,5,Libya,LY,LBY,6777453,Africa,39.61665245\r
-09/08/2020,9,8,2020,0,0,Libya,LY,LBY,6777453,Africa,37.35916723\r
-08/08/2020,8,8,2020,604,9,Libya,LY,LBY,6777453,Africa,39.15925348\r
-07/08/2020,7,8,2020,251,3,Libya,LY,LBY,6777453,Africa,31.88513443\r
-06/08/2020,6,8,2020,161,3,Libya,LY,LBY,6777453,Africa,30.21784142\r
-05/08/2020,5,8,2020,0,0,Libya,LY,LBY,6777453,Africa,29.14074063\r
-04/08/2020,4,8,2020,372,13,Libya,LY,LBY,6777453,Africa,31.02935572\r
-03/08/2020,3,8,2020,70,6,Libya,LY,LBY,6777453,Africa,26.92751982\r
-02/08/2020,2,8,2020,399,3,Libya,LY,LBY,6777453,Africa,27.00129385\r
-01/08/2020,1,8,2020,0,0,Libya,LY,LBY,6777453,Africa,22.39779457\r
-31/07/2020,31,7,2020,205,4,Libya,LY,LBY,6777453,Africa,23.16504445\r
-30/07/2020,30,7,2020,190,3,Libya,LY,LBY,6777453,Africa,21.06986209\r
-29/07/2020,29,7,2020,0,0,Libya,LY,LBY,6777453,Africa,18.650074\r
-28/07/2020,28,7,2020,280,6,Libya,LY,LBY,6777453,Africa,19.40256908\r
-27/07/2020,27,7,2020,0,0,Libya,LY,LBY,6777453,Africa,16.4368532\r
-26/07/2020,26,7,2020,122,1,Libya,LY,LBY,6777453,Africa,17.08606463\r
-25/07/2020,25,7,2020,111,1,Libya,LY,LBY,6777453,Africa,15.97945423\r
-24/07/2020,24,7,2020,138,3,Libya,LY,LBY,6777453,Africa,15.43352643\r
-23/07/2020,23,7,2020,88,3,Libya,LY,LBY,6777453,Africa,14.66627655\r
-22/07/2020,22,7,2020,128,1,Libya,LY,LBY,6777453,Africa,13.36785368\r
-21/07/2020,21,7,2020,94,1,Libya,LY,LBY,6777453,Africa,13.48589212\r
-20/07/2020,20,7,2020,75,0,Libya,LY,LBY,6777453,Africa,12.93996432\r
-19/07/2020,19,7,2020,87,1,Libya,LY,LBY,6777453,Africa,11.83335392\r
-18/07/2020,18,7,2020,52,1,Libya,LY,LBY,6777453,Africa,11.59727703\r
-17/07/2020,17,7,2020,63,3,Libya,LY,LBY,6777453,Africa,11.2284069\r
-16/07/2020,16,7,2020,26,1,Libya,LY,LBY,6777453,Africa,10.78576273\r
-15/07/2020,15,7,2020,51,2,Libya,LY,LBY,6777453,Africa,10.90380118\r
-14/07/2020,14,7,2020,79,1,Libya,LY,LBY,6777453,Africa,11.06610404\r
-13/07/2020,13,7,2020,44,1,Libya,LY,LBY,6777453,Africa,9.90047441\r
-12/07/2020,12,7,2020,47,0,Libya,LY,LBY,6777453,Africa,9.97424844\r
-11/07/2020,11,7,2020,74,2,Libya,LY,LBY,6777453,Africa,9.50209467\r
-10/07/2020,10,7,2020,86,1,Libya,LY,LBY,6777453,Africa,8.41023907\r
-09/07/2020,9,7,2020,0,0,Libya,LY,LBY,6777453,Africa,8.01185932\r
-08/07/2020,8,7,2020,136,3,Libya,LY,LBY,6777453,Africa,8.01185932\r
-07/07/2020,7,7,2020,57,5,Libya,LY,LBY,6777453,Africa,7.00853256\r
-06/07/2020,6,7,2020,0,0,Libya,LY,LBY,6777453,Africa,6.56588839\r
-05/07/2020,5,7,2020,71,0,Libya,LY,LBY,6777453,Africa,6.92000372\r
-04/07/2020,4,7,2020,27,1,Libya,LY,LBY,6777453,Africa,6.0199606\r
-03/07/2020,3,7,2020,33,2,Libya,LY,LBY,6777453,Africa,5.7691289\r
-02/07/2020,2,7,2020,34,0,Libya,LY,LBY,6777453,Africa,5.7691289\r
-01/07/2020,1,7,2020,62,3,Libya,LY,LBY,6777453,Africa,5.26746552\r
-30/06/2020,30,6,2020,0,0,Libya,LY,LBY,6777453,Africa,4.35266759\r
-29/06/2020,29,6,2020,49,3,Libya,LY,LBY,6777453,Africa,5.07565305\r
-28/06/2020,28,6,2020,15,0,Libya,LY,LBY,6777453,Africa,4.35266759\r
-27/06/2020,27,6,2020,0,0,Libya,LY,LBY,6777453,Africa,4.26413876\r
-26/06/2020,26,6,2020,59,0,Libya,LY,LBY,6777453,Africa,4.50021564\r
-25/06/2020,25,6,2020,0,1,Libya,LY,LBY,6777453,Africa,3.8510042\r
-24/06/2020,24,6,2020,68,7,Libya,LY,LBY,6777453,Africa,4.52972525\r
-23/06/2020,23,6,2020,27,0,Libya,LY,LBY,6777453,Africa,4.44119642\r
-22/06/2020,22,6,2020,24,0,Libya,LY,LBY,6777453,Africa,4.24938395\r
-21/06/2020,21,6,2020,10,0,Libya,LY,LBY,6777453,Africa,3.89526862\r
-20/06/2020,20,6,2020,10,0,Libya,LY,LBY,6777453,Africa,3.99855226\r
-19/06/2020,19,6,2020,33,0,Libya,LY,LBY,6777453,Africa,4.48546084\r
-18/06/2020,18,6,2020,0,0,Libya,LY,LBY,6777453,Africa,3.99855226\r
-17/06/2020,17,6,2020,0,0,Libya,LY,LBY,6777453,Africa,4.20511953\r
-16/06/2020,16,6,2020,49,2,Libya,LY,LBY,6777453,Africa,4.41168681\r
-15/06/2020,15,6,2020,0,0,Libya,LY,LBY,6777453,Africa,3.86575901\r
-14/06/2020,14,6,2020,9,2,Libya,LY,LBY,6777453,Africa,4.24938395\r
-13/06/2020,13,6,2020,16,1,Libya,LY,LBY,6777453,Africa,4.29364837\r
-12/06/2020,12,6,2020,15,0,Libya,LY,LBY,6777453,Africa,4.24938395\r
-11/06/2020,11,6,2020,46,0,Libya,LY,LBY,6777453,Africa,4.1165907\r
-10/06/2020,10,6,2020,62,0,Libya,LY,LBY,6777453,Africa,3.76247537\r
-09/06/2020,9,6,2020,14,0,Libya,LY,LBY,6777453,Africa,2.87718705\r
-08/06/2020,8,6,2020,0,0,Libya,LY,LBY,6777453,Africa,2.67061977\r
-07/06/2020,7,6,2020,17,0,Libya,LY,LBY,6777453,Africa,2.67061977\r
-06/06/2020,6,6,2020,43,0,Libya,LY,LBY,6777453,Africa,2.4640525\r
-05/06/2020,5,6,2020,0,0,Libya,LY,LBY,6777453,Africa,1.84435067\r
-04/06/2020,4,6,2020,14,0,Libya,LY,LBY,6777453,Africa,1.87386028\r
-03/06/2020,3,6,2020,14,0,Libya,LY,LBY,6777453,Africa,1.68204781\r
-02/06/2020,2,6,2020,12,0,Libya,LY,LBY,6777453,Africa,1.51974495\r
-01/06/2020,1,6,2020,26,0,Libya,LY,LBY,6777453,Africa,1.34268729\r
-31/05/2020,31,5,2020,12,0,Libya,LY,LBY,6777453,Africa,0.95906235\r
-30/05/2020,30,5,2020,13,0,Libya,LY,LBY,6777453,Africa,0.79675949\r
-29/05/2020,29,5,2020,6,1,Libya,LY,LBY,6777453,Africa,0.60494702\r
-28/05/2020,28,5,2020,22,1,Libya,LY,LBY,6777453,Africa,0.51641819\r
-27/05/2020,27,5,2020,2,0,Libya,LY,LBY,6777453,Africa,0.19181247\r
-26/05/2020,26,5,2020,0,0,Libya,LY,LBY,6777453,Africa,0.16230286\r
-25/05/2020,25,5,2020,0,0,Libya,LY,LBY,6777453,Africa,0.16230286\r
-24/05/2020,24,5,2020,3,0,Libya,LY,LBY,6777453,Africa,0.16230286\r
-23/05/2020,23,5,2020,1,0,Libya,LY,LBY,6777453,Africa,0.11803844\r
-22/05/2020,22,5,2020,2,0,Libya,LY,LBY,6777453,Africa,0.10328364\r
-21/05/2020,21,5,2020,1,0,Libya,LY,LBY,6777453,Africa,0.07377403\r
-20/05/2020,20,5,2020,3,0,Libya,LY,LBY,6777453,Africa,0.07377403\r
-19/05/2020,19,5,2020,0,0,Libya,LY,LBY,6777453,Africa,0.02950961\r
-18/05/2020,18,5,2020,0,0,Libya,LY,LBY,6777453,Africa,0.02950961\r
-17/05/2020,17,5,2020,1,0,Libya,LY,LBY,6777453,Africa,0.02950961\r
-16/05/2020,16,5,2020,0,0,Libya,LY,LBY,6777453,Africa,0.01475481\r
-15/05/2020,15,5,2020,0,0,Libya,LY,LBY,6777453,Africa,0.04426442\r
-14/05/2020,14,5,2020,0,0,Libya,LY,LBY,6777453,Africa,0.04426442\r
-13/05/2020,13,5,2020,0,0,Libya,LY,LBY,6777453,Africa,0.04426442\r
-12/05/2020,12,5,2020,0,0,Libya,LY,LBY,6777453,Africa,0.04426442\r
-11/05/2020,11,5,2020,0,0,Libya,LY,LBY,6777453,Africa,0.04426442\r
-10/05/2020,10,5,2020,0,0,Libya,LY,LBY,6777453,Africa,0.04426442\r
-09/05/2020,9,5,2020,0,0,Libya,LY,LBY,6777453,Africa,0.04426442\r
-08/05/2020,8,5,2020,0,0,Libya,LY,LBY,6777453,Africa,0.05901922\r
-07/05/2020,7,5,2020,1,0,Libya,LY,LBY,6777453,Africa,0.07377403\r
-06/05/2020,6,5,2020,0,0,Libya,LY,LBY,6777453,Africa,0.17705766\r
-05/05/2020,5,5,2020,0,0,Libya,LY,LBY,6777453,Africa,0.17705766\r
-04/05/2020,4,5,2020,0,0,Libya,LY,LBY,6777453,Africa,0.20656728\r
-03/05/2020,3,5,2020,0,0,Libya,LY,LBY,6777453,Africa,0.20656728\r
-02/05/2020,2,5,2020,2,0,Libya,LY,LBY,6777453,Africa,0.20656728\r
-01/05/2020,1,5,2020,0,1,Libya,LY,LBY,6777453,Africa,0.17705766\r
-30/04/2020,30,4,2020,0,0,Libya,LY,LBY,6777453,Africa,0.19181247\r
-29/04/2020,29,4,2020,0,0,Libya,LY,LBY,6777453,Africa,0.38362494\r
-28/04/2020,28,4,2020,0,0,Libya,LY,LBY,6777453,Africa,0.51641819\r
-27/04/2020,27,4,2020,0,0,Libya,LY,LBY,6777453,Africa,0.53117299\r
-26/04/2020,26,4,2020,0,0,Libya,LY,LBY,6777453,Africa,0.53117299\r
-25/04/2020,25,4,2020,1,0,Libya,LY,LBY,6777453,Africa,0.5459278\r
-24/04/2020,24,4,2020,1,1,Libya,LY,LBY,6777453,Africa,0.53117299\r
-23/04/2020,23,4,2020,8,0,Libya,LY,LBY,6777453,Africa,0.5606826\r
-22/04/2020,22,4,2020,0,0,Libya,LY,LBY,6777453,Africa,0.47215377\r
-21/04/2020,21,4,2020,2,0,Libya,LY,LBY,6777453,Africa,0.48690858\r
-20/04/2020,20,4,2020,0,0,Libya,LY,LBY,6777453,Africa,0.45739897\r
-19/04/2020,19,4,2020,0,0,Libya,LY,LBY,6777453,Africa,0.45739897\r
-18/04/2020,18,4,2020,0,0,Libya,LY,LBY,6777453,Africa,0.5606826\r
-17/04/2020,17,4,2020,1,0,Libya,LY,LBY,6777453,Africa,0.5606826\r
-16/04/2020,16,4,2020,13,0,Libya,LY,LBY,6777453,Africa,0.5606826\r
-15/04/2020,15,4,2020,9,0,Libya,LY,LBY,6777453,Africa,0.36887013\r
-14/04/2020,14,4,2020,1,0,Libya,LY,LBY,6777453,Africa,0.2655865\r
-13/04/2020,13,4,2020,0,0,Libya,LY,LBY,6777453,Africa,0.25083169\r
-12/04/2020,12,4,2020,1,0,Libya,LY,LBY,6777453,Africa,0.35411533\r
-11/04/2020,11,4,2020,0,0,Libya,LY,LBY,6777453,Africa,0.33936052\r
-10/04/2020,10,4,2020,3,0,Libya,LY,LBY,6777453,Africa,0.33936052\r
-09/04/2020,9,4,2020,2,0,Libya,LY,LBY,6777453,Africa,0.29509611\r
-08/04/2020,8,4,2020,1,0,Libya,LY,LBY,6777453,Africa,0.2655865\r
-07/04/2020,7,4,2020,0,0,Libya,LY,LBY,6777453,Africa,0.2655865\r
-06/04/2020,6,4,2020,0,0,Libya,LY,LBY,6777453,Africa,\r
-05/04/2020,5,4,2020,7,0,Libya,LY,LBY,6777453,Africa,\r
-04/04/2020,4,4,2020,0,0,Libya,LY,LBY,6777453,Africa,\r
-03/04/2020,3,4,2020,1,1,Libya,LY,LBY,6777453,Africa,\r
-02/04/2020,2,4,2020,0,0,Libya,LY,LBY,6777453,Africa,\r
-01/04/2020,1,4,2020,2,0,Libya,LY,LBY,6777453,Africa,\r
-31/03/2020,31,3,2020,0,0,Libya,LY,LBY,6777453,Africa,\r
-30/03/2020,30,3,2020,7,0,Libya,LY,LBY,6777453,Africa,\r
-29/03/2020,29,3,2020,0,0,Libya,LY,LBY,6777453,Africa,\r
-28/03/2020,28,3,2020,0,0,Libya,LY,LBY,6777453,Africa,\r
-27/03/2020,27,3,2020,0,0,Libya,LY,LBY,6777453,Africa,\r
-26/03/2020,26,3,2020,0,0,Libya,LY,LBY,6777453,Africa,\r
-25/03/2020,25,3,2020,1,0,Libya,LY,LBY,6777453,Africa,\r
-19/08/2020,19,8,2020,3,0,Liechtenstein,LI,LIE,38378,Europe,20.84527594\r
-18/08/2020,18,8,2020,1,0,Liechtenstein,LI,LIE,38378,Europe,13.02829746\r
-17/08/2020,17,8,2020,0,0,Liechtenstein,LI,LIE,38378,Europe,10.42263797\r
-16/08/2020,16,8,2020,2,0,Liechtenstein,LI,LIE,38378,Europe,10.42263797\r
-15/08/2020,15,8,2020,0,0,Liechtenstein,LI,LIE,38378,Europe,5.21131898\r
-14/08/2020,14,8,2020,1,0,Liechtenstein,LI,LIE,38378,Europe,5.21131898\r
-13/08/2020,13,8,2020,1,0,Liechtenstein,LI,LIE,38378,Europe,5.21131898\r
-12/08/2020,12,8,2020,0,0,Liechtenstein,LI,LIE,38378,Europe,5.21131898\r
-11/08/2020,11,8,2020,0,0,Liechtenstein,LI,LIE,38378,Europe,5.21131898\r
-10/08/2020,10,8,2020,0,0,Liechtenstein,LI,LIE,38378,Europe,5.21131898\r
-09/08/2020,9,8,2020,0,0,Liechtenstein,LI,LIE,38378,Europe,5.21131898\r
-08/08/2020,8,8,2020,0,0,Liechtenstein,LI,LIE,38378,Europe,5.21131898\r
-07/08/2020,7,8,2020,0,0,Liechtenstein,LI,LIE,38378,Europe,5.21131898\r
-06/08/2020,6,8,2020,0,0,Liechtenstein,LI,LIE,38378,Europe,5.21131898\r
-05/08/2020,5,8,2020,0,0,Liechtenstein,LI,LIE,38378,Europe,5.21131898\r
-04/08/2020,4,8,2020,0,0,Liechtenstein,LI,LIE,38378,Europe,5.21131898\r
-03/08/2020,3,8,2020,0,0,Liechtenstein,LI,LIE,38378,Europe,5.21131898\r
-02/08/2020,2,8,2020,0,0,Liechtenstein,LI,LIE,38378,Europe,7.81697848\r
-01/08/2020,1,8,2020,0,0,Liechtenstein,LI,LIE,38378,Europe,7.81697848\r
-31/07/2020,31,7,2020,1,0,Liechtenstein,LI,LIE,38378,Europe,10.42263797\r
-30/07/2020,30,7,2020,1,0,Liechtenstein,LI,LIE,38378,Europe,7.81697848\r
-29/07/2020,29,7,2020,0,0,Liechtenstein,LI,LIE,38378,Europe,5.21131898\r
-28/07/2020,28,7,2020,0,0,Liechtenstein,LI,LIE,38378,Europe,5.21131898\r
-27/07/2020,27,7,2020,0,0,Liechtenstein,LI,LIE,38378,Europe,5.21131898\r
-26/07/2020,26,7,2020,0,0,Liechtenstein,LI,LIE,38378,Europe,5.21131898\r
-25/07/2020,25,7,2020,0,0,Liechtenstein,LI,LIE,38378,Europe,5.21131898\r
-24/07/2020,24,7,2020,0,0,Liechtenstein,LI,LIE,38378,Europe,5.21131898\r
-23/07/2020,23,7,2020,0,0,Liechtenstein,LI,LIE,38378,Europe,5.21131898\r
-22/07/2020,22,7,2020,0,0,Liechtenstein,LI,LIE,38378,Europe,5.21131898\r
-21/07/2020,21,7,2020,0,0,Liechtenstein,LI,LIE,38378,Europe,5.21131898\r
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-29/07/2020,29,7,2020,414,2,Madagascar,MG,MDG,26969306,Africa,17.65340198\r
-28/07/2020,28,7,2020,395,6,Madagascar,MG,MDG,26969306,Africa,17.09350623\r
-27/07/2020,27,7,2020,429,7,Madagascar,MG,MDG,26969306,Africa,16.41866498\r
-26/07/2020,26,7,2020,125,2,Madagascar,MG,MDG,26969306,Africa,15.89955633\r
-25/07/2020,25,7,2020,360,6,Madagascar,MG,MDG,26969306,Africa,17.0490112\r
-24/07/2020,24,7,2020,219,1,Madagascar,MG,MDG,26969306,Africa,17.05271912\r
-23/07/2020,23,7,2020,614,4,Madagascar,MG,MDG,26969306,Africa,17.01563993\r
-22/07/2020,22,7,2020,395,3,Madagascar,MG,MDG,26969306,Africa,15.11347752\r
-21/07/2020,21,7,2020,104,3,Madagascar,MG,MDG,26969306,Africa,14.47200755\r
-20/07/2020,20,7,2020,200,4,Madagascar,MG,MDG,26969306,Africa,16.02191766\r
-19/07/2020,19,7,2020,382,1,Madagascar,MG,MDG,26969306,Africa,15.28033387\r
-18/07/2020,18,7,2020,378,1,Madagascar,MG,MDG,26969306,Africa,14.66481933\r
-17/07/2020,17,7,2020,484,10,Madagascar,MG,MDG,26969306,Africa,13.66738914\r
-16/07/2020,16,7,2020,262,4,Madagascar,MG,MDG,26969306,Africa,12.24354828\r
-15/07/2020,15,7,2020,263,2,Madagascar,MG,MDG,26969306,Africa,11.6020783\r
-14/07/2020,14,7,2020,213,2,Madagascar,MG,MDG,26969306,Africa,10.90869747\r
-13/07/2020,13,7,2020,289,1,Madagascar,MG,MDG,26969306,Africa,10.34138587\r
-12/07/2020,12,7,2020,435,0,Madagascar,MG,MDG,26969306,Africa,9.54047538\r
-11/07/2020,11,7,2020,361,1,Madagascar,MG,MDG,26969306,Africa,8.23528792\r
-10/07/2020,10,7,2020,209,0,Madagascar,MG,MDG,26969306,Africa,7.24156565\r
-09/07/2020,9,7,2020,101,0,Madagascar,MG,MDG,26969306,Africa,6.62234319\r
-08/07/2020,8,7,2020,222,0,Madagascar,MG,MDG,26969306,Africa,6.48144227\r
-07/07/2020,7,7,2020,522,4,Madagascar,MG,MDG,26969306,Africa,5.96974946\r
-06/07/2020,6,7,2020,0,0,Madagascar,MG,MDG,26969306,Africa,4.19736422\r
-05/07/2020,5,7,2020,216,3,Madagascar,MG,MDG,26969306,Africa,4.54220068\r
-04/07/2020,4,7,2020,109,2,Madagascar,MG,MDG,26969306,Africa,3.96376533\r
-03/07/2020,3,7,2020,100,2,Madagascar,MG,MDG,26969306,Africa,3.70791892\r
-02/07/2020,2,7,2020,89,2,Madagascar,MG,MDG,26969306,Africa,3.429825\r
-01/07/2020,1,7,2020,76,0,Madagascar,MG,MDG,26969306,Africa,3.32600327\r
-30/06/2020,30,6,2020,60,2,Madagascar,MG,MDG,26969306,Africa,3.14431524\r
-29/06/2020,29,6,2020,73,2,Madagascar,MG,MDG,26969306,Africa,2.98858265\r
-28/06/2020,28,6,2020,83,0,Madagascar,MG,MDG,26969306,Africa,2.79206295\r
-27/06/2020,27,6,2020,93,0,Madagascar,MG,MDG,26969306,Africa,2.56587989\r
-26/06/2020,26,6,2020,42,0,Madagascar,MG,MDG,26969306,Africa,2.32115724\r
-25/06/2020,25,6,2020,63,1,Madagascar,MG,MDG,26969306,Africa,2.31744933\r
-24/06/2020,24,6,2020,84,0,Madagascar,MG,MDG,26969306,Africa,2.17284049\r
-23/06/2020,23,6,2020,44,1,Madagascar,MG,MDG,26969306,Africa,2.02452373\r
-22/06/2020,22,6,2020,93,1,Madagascar,MG,MDG,26969306,Africa,2.01710789\r
-21/06/2020,21,6,2020,60,0,Madagascar,MG,MDG,26969306,Africa,1.76867733\r
-20/06/2020,20,6,2020,40,0,Madagascar,MG,MDG,26969306,Africa,1.73530605\r
-19/06/2020,19,6,2020,25,1,Madagascar,MG,MDG,26969306,Africa,1.65373184\r
-18/06/2020,18,6,2020,61,0,Madagascar,MG,MDG,26969306,Africa,1.74272189\r
-17/06/2020,17,6,2020,27,2,Madagascar,MG,MDG,26969306,Africa,1.75013773\r
-16/06/2020,16,6,2020,18,0,Madagascar,MG,MDG,26969306,Africa,1.72047438\r
-15/06/2020,15,6,2020,20,0,Madagascar,MG,MDG,26969306,Africa,1.85766738\r
-14/06/2020,14,6,2020,22,0,Madagascar,MG,MDG,26969306,Africa,1.83171195\r
-13/06/2020,13,6,2020,27,0,Madagascar,MG,MDG,26969306,Africa,1.97261287\r
-12/06/2020,12,6,2020,41,0,Madagascar,MG,MDG,26969306,Africa,2.02823165\r
-11/06/2020,11,6,2020,24,1,Madagascar,MG,MDG,26969306,Africa,2.03935541\r
-10/06/2020,10,6,2020,44,0,Madagascar,MG,MDG,26969306,Africa,2.04677124\r
-09/06/2020,9,6,2020,42,0,Madagascar,MG,MDG,26969306,Africa,2.04677124\r
-08/06/2020,8,6,2020,26,1,Madagascar,MG,MDG,26969306,Africa,1.94665743\r
-07/06/2020,7,6,2020,51,1,Madagascar,MG,MDG,26969306,Africa,2.14317714\r
-06/06/2020,6,6,2020,18,0,Madagascar,MG,MDG,26969306,Africa,1.95407327\r
-05/06/2020,5,6,2020,49,1,Madagascar,MG,MDG,26969306,Africa,2.04677124\r
-04/06/2020,4,6,2020,63,0,Madagascar,MG,MDG,26969306,Africa,1.99115246\r
-03/06/2020,3,6,2020,19,0,Madagascar,MG,MDG,26969306,Africa,1.92440992\r
-02/06/2020,2,6,2020,55,0,Madagascar,MG,MDG,26969306,Africa,1.86879114\r
-01/06/2020,1,6,2020,13,0,Madagascar,MG,MDG,26969306,Africa,1.73159814\r
-31/05/2020,31,5,2020,60,1,Madagascar,MG,MDG,26969306,Africa,1.76126149\r
-30/05/2020,30,5,2020,42,3,Madagascar,MG,MDG,26969306,Africa,1.7056427\r
-29/05/2020,29,5,2020,44,0,Madagascar,MG,MDG,26969306,Africa,1.57957346\r
-28/05/2020,28,5,2020,26,0,Madagascar,MG,MDG,26969306,Africa,1.48316757\r
-27/05/2020,27,5,2020,44,0,Madagascar,MG,MDG,26969306,Africa,1.46092005\r
-26/05/2020,26,5,2020,15,0,Madagascar,MG,MDG,26969306,Africa,1.32001914\r
-25/05/2020,25,5,2020,79,0,Madagascar,MG,MDG,26969306,Africa,1.32001914\r
-24/05/2020,24,5,2020,0,0,Madagascar,MG,MDG,26969306,Africa,1.03450938\r
-23/05/2020,23,5,2020,43,0,Madagascar,MG,MDG,26969306,Africa,1.03450938\r
-22/05/2020,22,5,2020,34,0,Madagascar,MG,MDG,26969306,Africa,0.87506887\r
-21/05/2020,21,5,2020,45,0,Madagascar,MG,MDG,26969306,Africa,0.78978673\r
-20/05/2020,20,5,2020,4,1,Madagascar,MG,MDG,26969306,Africa,0.62293038\r
-19/05/2020,19,5,2020,18,0,Madagascar,MG,MDG,26969306,Africa,0.64146997\r
-18/05/2020,18,5,2020,21,1,Madagascar,MG,MDG,26969306,Africa,0.57472743\r
-17/05/2020,17,5,2020,45,0,Madagascar,MG,MDG,26969306,Africa,0.548772\r
-16/05/2020,16,5,2020,8,0,Madagascar,MG,MDG,26969306,Africa,0.38191565\r
-15/05/2020,15,5,2020,18,0,Madagascar,MG,MDG,26969306,Africa,0.36337605\r
-14/05/2020,14,5,2020,20,0,Madagascar,MG,MDG,26969306,Africa,0.31146519\r
-13/05/2020,13,5,2020,6,0,Madagascar,MG,MDG,26969306,Africa,0.23730681\r
-12/05/2020,12,5,2020,15,0,Madagascar,MG,MDG,26969306,Africa,0.2150593\r
-11/05/2020,11,5,2020,2,0,Madagascar,MG,MDG,26969306,Africa,0.17427219\r
-10/05/2020,10,5,2020,0,0,Madagascar,MG,MDG,26969306,Africa,0.16685635\r
-09/05/2020,9,5,2020,0,0,Madagascar,MG,MDG,26969306,Africa,0.17427219\r
-08/05/2020,8,5,2020,11,0,Madagascar,MG,MDG,26969306,Africa,0.17798011\r
-07/05/2020,7,5,2020,0,0,Madagascar,MG,MDG,26969306,Africa,0.137193\r
-06/05/2020,6,5,2020,9,0,Madagascar,MG,MDG,26969306,Africa,0.137193\r
-05/05/2020,5,5,2020,0,0,Madagascar,MG,MDG,26969306,Africa,0.10382173\r
-04/05/2020,4,5,2020,14,0,Madagascar,MG,MDG,26969306,Africa,0.10382173\r
-03/05/2020,3,5,2020,0,0,Madagascar,MG,MDG,26969306,Africa,0.06674254\r
-02/05/2020,2,5,2020,3,0,Madagascar,MG,MDG,26969306,Africa,0.06674254\r
-01/05/2020,1,5,2020,4,0,Madagascar,MG,MDG,26969306,Africa,0.0778663\r
-30/04/2020,30,4,2020,0,0,Madagascar,MG,MDG,26969306,Africa,0.06674254\r
-29/04/2020,29,4,2020,0,0,Madagascar,MG,MDG,26969306,Africa,0.07415838\r
-28/04/2020,28,4,2020,4,0,Madagascar,MG,MDG,26969306,Africa,0.08157422\r
-27/04/2020,27,4,2020,0,0,Madagascar,MG,MDG,26969306,Africa,0.06674254\r
-26/04/2020,26,4,2020,2,0,Madagascar,MG,MDG,26969306,Africa,0.08157422\r
-25/04/2020,25,4,2020,1,0,Madagascar,MG,MDG,26969306,Africa,0.07415838\r
-24/04/2020,24,4,2020,0,0,Madagascar,MG,MDG,26969306,Africa,0.10382173\r
-23/04/2020,23,4,2020,0,0,Madagascar,MG,MDG,26969306,Africa,0.10382173\r
-22/04/2020,22,4,2020,0,0,Madagascar,MG,MDG,26969306,Africa,0.13348508\r
-21/04/2020,21,4,2020,0,0,Madagascar,MG,MDG,26969306,Africa,0.16314843\r
-20/04/2020,20,4,2020,4,0,Madagascar,MG,MDG,26969306,Africa,0.18168803\r
-19/04/2020,19,4,2020,0,0,Madagascar,MG,MDG,26969306,Africa,0.17056427\r
-18/04/2020,18,4,2020,6,0,Madagascar,MG,MDG,26969306,Africa,0.19281178\r
-17/04/2020,17,4,2020,1,0,Madagascar,MG,MDG,26969306,Africa,0.19281178\r
-16/04/2020,16,4,2020,2,0,Madagascar,MG,MDG,26969306,Africa,0.20764346\r
-15/04/2020,15,4,2020,2,0,Madagascar,MG,MDG,26969306,Africa,0.22989097\r
-14/04/2020,14,4,2020,0,0,Madagascar,MG,MDG,26969306,Africa,0.22989097\r
-13/04/2020,13,4,2020,4,0,Madagascar,MG,MDG,26969306,Africa,0.25584641\r
-12/04/2020,12,4,2020,0,0,Madagascar,MG,MDG,26969306,Africa,0.274386\r
-11/04/2020,11,4,2020,9,0,Madagascar,MG,MDG,26969306,Africa,0.28921768\r
-10/04/2020,10,4,2020,0,0,Madagascar,MG,MDG,26969306,Africa,0.25955432\r
-09/04/2020,9,4,2020,8,0,Madagascar,MG,MDG,26969306,Africa,0.274386\r
-08/04/2020,8,4,2020,8,0,Madagascar,MG,MDG,26969306,Africa,0.24472265\r
-07/04/2020,7,4,2020,5,0,Madagascar,MG,MDG,26969306,Africa,0.22247514\r
-06/04/2020,6,4,2020,1,0,Madagascar,MG,MDG,26969306,Africa,0.25584641\r
-05/04/2020,5,4,2020,6,0,Madagascar,MG,MDG,26969306,Africa,0.25213849\r
-04/04/2020,4,4,2020,6,0,Madagascar,MG,MDG,26969306,Africa,0.22989097\r
-03/04/2020,3,4,2020,5,0,Madagascar,MG,MDG,26969306,Africa,0.21876722\r
-02/04/2020,2,4,2020,8,0,Madagascar,MG,MDG,26969306,Africa,\r
-01/04/2020,1,4,2020,2,0,Madagascar,MG,MDG,26969306,Africa,\r
-31/03/2020,31,3,2020,7,0,Madagascar,MG,MDG,26969306,Africa,\r
-30/03/2020,30,3,2020,9,0,Madagascar,MG,MDG,26969306,Africa,\r
-29/03/2020,29,3,2020,4,0,Madagascar,MG,MDG,26969306,Africa,\r
-28/03/2020,28,3,2020,1,0,Madagascar,MG,MDG,26969306,Africa,\r
-27/03/2020,27,3,2020,4,0,Madagascar,MG,MDG,26969306,Africa,\r
-26/03/2020,26,3,2020,0,0,Madagascar,MG,MDG,26969306,Africa,\r
-25/03/2020,25,3,2020,2,0,Madagascar,MG,MDG,26969306,Africa,\r
-24/03/2020,24,3,2020,14,0,Madagascar,MG,MDG,26969306,Africa,\r
-23/03/2020,23,3,2020,0,0,Madagascar,MG,MDG,26969306,Africa,\r
-22/03/2020,22,3,2020,0,0,Madagascar,MG,MDG,26969306,Africa,\r
-21/03/2020,21,3,2020,3,0,Madagascar,MG,MDG,26969306,Africa,\r
-19/08/2020,19,8,2020,121,2,Malawi,MW,MWI,18628749,Africa,4.54136775\r
-18/08/2020,18,8,2020,0,0,Malawi,MW,MWI,18628749,Africa,4.28906955\r
-17/08/2020,17,8,2020,46,4,Malawi,MW,MWI,18628749,Africa,4.51452752\r
-16/08/2020,16,8,2020,38,1,Malawi,MW,MWI,18628749,Africa,4.50915947\r
-15/08/2020,15,8,2020,76,3,Malawi,MW,MWI,18628749,Africa,4.88492276\r
-14/08/2020,14,8,2020,160,1,Malawi,MW,MWI,18628749,Africa,4.99765175\r
-13/08/2020,13,8,2020,40,0,Malawi,MW,MWI,18628749,Africa,4.79903401\r
-12/08/2020,12,8,2020,39,6,Malawi,MW,MWI,18628749,Africa,5.38415113\r
-11/08/2020,11,8,2020,15,0,Malawi,MW,MWI,18628749,Africa,5.1747973\r
-10/08/2020,10,8,2020,34,3,Malawi,MW,MWI,18628749,Africa,5.46467184\r
-09/08/2020,9,8,2020,49,6,Malawi,MW,MWI,18628749,Africa,6.28598303\r
-08/08/2020,8,8,2020,84,0,Malawi,MW,MWI,18628749,Africa,6.02294872\r
-07/08/2020,7,8,2020,65,1,Malawi,MW,MWI,18628749,Africa,5.93169192\r
-06/08/2020,6,8,2020,79,8,Malawi,MW,MWI,18628749,Africa,6.03368482\r
-05/08/2020,5,8,2020,74,5,Malawi,MW,MWI,18628749,Africa,6.43092029\r
-04/08/2020,4,8,2020,42,0,Malawi,MW,MWI,18628749,Africa,6.5919617\r
-03/08/2020,3,8,2020,45,3,Malawi,MW,MWI,18628749,Africa,6.65101022\r
-02/08/2020,2,8,2020,108,6,Malawi,MW,MWI,18628749,Africa,6.8657321\r
-01/08/2020,1,8,2020,97,5,Malawi,MW,MWI,18628749,Africa,6.80668358\r
-31/07/2020,31,7,2020,123,2,Malawi,MW,MWI,18628749,Africa,6.81205163\r
-30/07/2020,30,7,2020,149,4,Malawi,MW,MWI,18628749,Africa,6.67785046\r
-29/07/2020,29,7,2020,0,0,Malawi,MW,MWI,18628749,Africa,6.50607295\r
-28/07/2020,28,7,2020,69,4,Malawi,MW,MWI,18628749,Africa,6.8657321\r
-27/07/2020,27,7,2020,187,12,Malawi,MW,MWI,18628749,Africa,6.84962796\r
-26/07/2020,26,7,2020,0,0,Malawi,MW,MWI,18628749,Africa,6.39871201\r
-25/07/2020,25,7,2020,67,8,Malawi,MW,MWI,18628749,Africa,7.42937703\r
-24/07/2020,24,7,2020,84,3,Malawi,MW,MWI,18628749,Africa,7.52600188\r
-23/07/2020,23,7,2020,153,5,Malawi,MW,MWI,18628749,Africa,7.37032852\r
-22/07/2020,22,7,2020,104,7,Malawi,MW,MWI,18628749,Africa,6.82815577\r
-21/07/2020,21,7,2020,53,2,Malawi,MW,MWI,18628749,Africa,6.58659366\r
-20/07/2020,20,7,2020,85,3,Malawi,MW,MWI,18628749,Africa,6.71005874\r
-19/07/2020,19,7,2020,97,4,Malawi,MW,MWI,18628749,Africa,6.94625281\r
-18/07/2020,18,7,2020,98,4,Malawi,MW,MWI,18628749,Africa,7.04287765\r
-17/07/2020,17,7,2020,98,8,Malawi,MW,MWI,18628749,Africa,7.03214156\r
-16/07/2020,16,7,2020,117,3,Malawi,MW,MWI,18628749,Africa,6.82815577\r
-15/07/2020,15,7,2020,67,1,Malawi,MW,MWI,18628749,Africa,6.61343389\r
-14/07/2020,14,7,2020,66,1,Malawi,MW,MWI,18628749,Africa,6.47386467\r
-13/07/2020,13,7,2020,103,5,Malawi,MW,MWI,18628749,Africa,6.53828123\r
-12/07/2020,12,7,2020,192,2,Malawi,MW,MWI,18628749,Africa,6.56512147\r
-11/07/2020,11,7,2020,85,2,Malawi,MW,MWI,18628749,Africa,5.711602\r
-10/07/2020,10,7,2020,55,4,Malawi,MW,MWI,18628749,Africa,5.49688012\r
-09/07/2020,9,7,2020,52,1,Malawi,MW,MWI,18628749,Africa,5.30363043\r
-08/07/2020,8,7,2020,59,5,Malawi,MW,MWI,18628749,Africa,5.52372035\r
-07/07/2020,7,7,2020,76,0,Malawi,MW,MWI,18628749,Africa,5.4485677\r
-06/07/2020,6,7,2020,129,2,Malawi,MW,MWI,18628749,Africa,5.43246355\r
-05/07/2020,5,7,2020,115,1,Malawi,MW,MWI,18628749,Africa,5.33047066\r
-04/07/2020,4,7,2020,96,0,Malawi,MW,MWI,18628749,Africa,4.71314526\r
-03/07/2020,3,7,2020,60,0,Malawi,MW,MWI,18628749,Africa,4.34811806\r
-02/07/2020,2,7,2020,77,0,Malawi,MW,MWI,18628749,Africa,4.13339618\r
-01/07/2020,1,7,2020,41,2,Malawi,MW,MWI,18628749,Africa,3.76300094\r
-30/06/2020,30,6,2020,78,1,Malawi,MW,MWI,18628749,Africa,3.58585539\r
-29/06/2020,29,6,2020,108,0,Malawi,MW,MWI,18628749,Africa,3.21546015\r
-28/06/2020,28,6,2020,33,0,Malawi,MW,MWI,18628749,Africa,2.73233592\r
-27/06/2020,27,6,2020,45,1,Malawi,MW,MWI,18628749,Africa,2.81285662\r
-26/06/2020,26,6,2020,19,1,Malawi,MW,MWI,18628749,Africa,2.57129451\r
-25/06/2020,25,6,2020,93,0,Malawi,MW,MWI,18628749,Africa,2.60887084\r
-24/06/2020,24,6,2020,45,0,Malawi,MW,MWI,18628749,Africa,2.10964247\r
-23/06/2020,23,6,2020,73,0,Malawi,MW,MWI,18628749,Africa,1.93249692\r
-22/06/2020,22,6,2020,110,3,Malawi,MW,MWI,18628749,Africa,1.56746972\r
-21/06/2020,21,6,2020,0,0,Malawi,MW,MWI,18628749,Africa,1.13265791\r
-20/06/2020,20,6,2020,28,0,Malawi,MW,MWI,18628749,Africa,1.13265791\r
-19/06/2020,19,6,2020,20,2,Malawi,MW,MWI,18628749,Africa,1.06824135\r
-18/06/2020,18,6,2020,8,0,Malawi,MW,MWI,18628749,Africa,1.08971354\r
-17/06/2020,17,6,2020,8,0,Malawi,MW,MWI,18628749,Africa,1.10581768\r
-16/06/2020,16,6,2020,9,0,Malawi,MW,MWI,18628749,Africa,1.18097034\r
-15/06/2020,15,6,2020,18,1,Malawi,MW,MWI,18628749,Africa,1.41179636\r
-14/06/2020,14,6,2020,48,1,Malawi,MW,MWI,18628749,Africa,1.34201175\r
-13/06/2020,13,6,2020,0,0,Malawi,MW,MWI,18628749,Africa,1.11655377\r
-12/06/2020,12,6,2020,26,0,Malawi,MW,MWI,18628749,Africa,1.49231706\r
-11/06/2020,11,6,2020,0,0,Malawi,MW,MWI,18628749,Africa,1.90028863\r
-10/06/2020,10,6,2020,12,0,Malawi,MW,MWI,18628749,Africa,1.90028863\r
-09/06/2020,9,6,2020,5,0,Malawi,MW,MWI,18628749,Africa,1.83587207\r
-08/06/2020,8,6,2020,29,0,Malawi,MW,MWI,18628749,Africa,1.90565668\r
-07/06/2020,7,6,2020,0,0,Malawi,MW,MWI,18628749,Africa,1.74998332\r
-06/06/2020,6,6,2020,16,0,Malawi,MW,MWI,18628749,Africa,1.75535137\r
-05/06/2020,5,6,2020,24,0,Malawi,MW,MWI,18628749,Africa,1.72314308\r
-04/06/2020,4,6,2020,11,0,Malawi,MW,MWI,18628749,Africa,1.59430996\r
-03/06/2020,3,6,2020,22,0,Malawi,MW,MWI,18628749,Africa,1.54062949\r
-02/06/2020,2,6,2020,52,0,Malawi,MW,MWI,18628749,Africa,1.4279005\r
-01/06/2020,1,6,2020,5,0,Malawi,MW,MWI,18628749,Africa,1.14876206\r
-31/05/2020,31,5,2020,6,0,Malawi,MW,MWI,18628749,Africa,1.14876206\r
-30/05/2020,30,5,2020,70,0,Malawi,MW,MWI,18628749,Africa,1.12728987\r
-29/05/2020,29,5,2020,102,0,Malawi,MW,MWI,18628749,Africa,0.75152658\r
-28/05/2020,28,5,2020,0,0,Malawi,MW,MWI,18628749,Africa,0.20398579\r
-27/05/2020,27,5,2020,0,0,Malawi,MW,MWI,18628749,Africa,0.23082602\r
-26/05/2020,26,5,2020,18,0,Malawi,MW,MWI,18628749,Africa,0.23619407\r
-25/05/2020,25,5,2020,0,0,Malawi,MW,MWI,18628749,Africa,0.14493727\r
-24/05/2020,24,5,2020,1,1,Malawi,MW,MWI,18628749,Africa,0.14493727\r
-23/05/2020,23,5,2020,10,0,Malawi,MW,MWI,18628749,Africa,0.20935383\r
-22/05/2020,22,5,2020,0,0,Malawi,MW,MWI,18628749,Africa,0.15567336\r
-21/05/2020,21,5,2020,1,0,Malawi,MW,MWI,18628749,Africa,0.15567336\r
-20/05/2020,20,5,2020,1,0,Malawi,MW,MWI,18628749,Africa,0.16104141\r
-19/05/2020,19,5,2020,0,0,Malawi,MW,MWI,18628749,Africa,0.15567336\r
-18/05/2020,18,5,2020,5,0,Malawi,MW,MWI,18628749,Africa,0.16640946\r
-17/05/2020,17,5,2020,2,0,Malawi,MW,MWI,18628749,Africa,0.14493727\r
-16/05/2020,16,5,2020,0,0,Malawi,MW,MWI,18628749,Africa,0.13956922\r
-15/05/2020,15,5,2020,0,0,Malawi,MW,MWI,18628749,Africa,0.13956922\r
-14/05/2020,14,5,2020,5,0,Malawi,MW,MWI,18628749,Africa,0.14493727\r
-13/05/2020,13,5,2020,1,0,Malawi,MW,MWI,18628749,Africa,0.11809703\r
-12/05/2020,12,5,2020,1,0,Malawi,MW,MWI,18628749,Africa,0.11272899\r
-11/05/2020,11,5,2020,0,0,Malawi,MW,MWI,18628749,Africa,0.11809703\r
-10/05/2020,10,5,2020,13,0,Malawi,MW,MWI,18628749,Africa,0.12346508\r
-09/05/2020,9,5,2020,0,0,Malawi,MW,MWI,18628749,Africa,0.05368047\r
-08/05/2020,8,5,2020,0,0,Malawi,MW,MWI,18628749,Africa,0.05368047\r
-07/05/2020,7,5,2020,2,0,Malawi,MW,MWI,18628749,Africa,0.10736094\r
-06/05/2020,6,5,2020,0,0,Malawi,MW,MWI,18628749,Africa,0.12346508\r
-05/05/2020,5,5,2020,2,0,Malawi,MW,MWI,18628749,Africa,0.12883313\r
-04/05/2020,4,5,2020,1,0,Malawi,MW,MWI,18628749,Africa,0.11809703\r
-03/05/2020,3,5,2020,1,0,Malawi,MW,MWI,18628749,Africa,0.11272899\r
-02/05/2020,2,5,2020,0,0,Malawi,MW,MWI,18628749,Africa,0.10736094\r
-01/05/2020,1,5,2020,1,0,Malawi,MW,MWI,18628749,Africa,0.11272899\r
-30/04/2020,30,4,2020,0,0,Malawi,MW,MWI,18628749,Africa,0.10736094\r
-29/04/2020,29,4,2020,0,0,Malawi,MW,MWI,18628749,Africa,0.10736094\r
-28/04/2020,28,4,2020,2,0,Malawi,MW,MWI,18628749,Africa,0.10736094\r
-27/04/2020,27,4,2020,1,0,Malawi,MW,MWI,18628749,Africa,0.11272899\r
-26/04/2020,26,4,2020,0,0,Malawi,MW,MWI,18628749,Africa,0.11272899\r
-25/04/2020,25,4,2020,0,0,Malawi,MW,MWI,18628749,Africa,0.12883313\r
-24/04/2020,24,4,2020,10,0,Malawi,MW,MWI,18628749,Africa,0.13420117\r
-23/04/2020,23,4,2020,5,1,Malawi,MW,MWI,18628749,Africa,0.0805207\r
-22/04/2020,22,4,2020,1,0,Malawi,MW,MWI,18628749,Africa,0.05368047\r
-21/04/2020,21,4,2020,0,0,Malawi,MW,MWI,18628749,Africa,0.06441656\r
-20/04/2020,20,4,2020,0,0,Malawi,MW,MWI,18628749,Africa,0.06978461\r
-19/04/2020,19,4,2020,0,0,Malawi,MW,MWI,18628749,Africa,0.06978461\r
-18/04/2020,18,4,2020,1,0,Malawi,MW,MWI,18628749,Africa,0.07515266\r
-17/04/2020,17,4,2020,0,0,Malawi,MW,MWI,18628749,Africa,0.06978461\r
-16/04/2020,16,4,2020,0,0,Malawi,MW,MWI,18628749,Africa,0.08588875\r
-15/04/2020,15,4,2020,0,0,Malawi,MW,MWI,18628749,Africa,\r
-14/04/2020,14,4,2020,3,0,Malawi,MW,MWI,18628749,Africa,\r
-13/04/2020,13,4,2020,1,0,Malawi,MW,MWI,18628749,Africa,\r
-12/04/2020,12,4,2020,3,1,Malawi,MW,MWI,18628749,Africa,\r
-11/04/2020,11,4,2020,1,0,Malawi,MW,MWI,18628749,Africa,\r
-10/04/2020,10,4,2020,0,0,Malawi,MW,MWI,18628749,Africa,\r
-09/04/2020,9,4,2020,0,0,Malawi,MW,MWI,18628749,Africa,\r
-08/04/2020,8,4,2020,3,1,Malawi,MW,MWI,18628749,Africa,\r
-07/04/2020,7,4,2020,1,0,Malawi,MW,MWI,18628749,Africa,\r
-06/04/2020,6,4,2020,0,0,Malawi,MW,MWI,18628749,Africa,\r
-05/04/2020,5,4,2020,1,0,Malawi,MW,MWI,18628749,Africa,\r
-04/04/2020,4,4,2020,0,0,Malawi,MW,MWI,18628749,Africa,\r
-03/04/2020,3,4,2020,3,0,Malawi,MW,MWI,18628749,Africa,\r
-19/08/2020,19,8,2020,7,0,Malaysia,MY,MYS,31949789,Asia,0.67919071\r
-18/08/2020,18,8,2020,12,0,Malaysia,MY,MYS,31949789,Asia,0.66041125\r
-17/08/2020,17,8,2020,25,0,Malaysia,MY,MYS,31949789,Asia,0.62911214\r
-16/08/2020,16,8,2020,26,0,Malaysia,MY,MYS,31949789,Asia,0.59468311\r
-15/08/2020,15,8,2020,20,0,Malaysia,MY,MYS,31949789,Asia,0.54147462\r
-14/08/2020,14,8,2020,15,0,Malaysia,MY,MYS,31949789,Asia,0.51643534\r
-13/08/2020,13,8,2020,11,0,Malaysia,MY,MYS,31949789,Asia,0.49452596\r
-12/08/2020,12,8,2020,9,0,Malaysia,MY,MYS,31949789,Asia,0.50078578\r
-11/08/2020,11,8,2020,11,0,Malaysia,MY,MYS,31949789,Asia,0.59468311\r
-10/08/2020,10,8,2020,13,0,Malaysia,MY,MYS,31949789,Asia,0.58216347\r
-09/08/2020,9,8,2020,7,0,Malaysia,MY,MYS,31949789,Asia,0.58216347\r
-08/08/2020,8,8,2020,25,0,Malaysia,MY,MYS,31949789,Asia,0.63224205\r
-07/08/2020,7,8,2020,15,0,Malaysia,MY,MYS,31949789,Asia,0.6197224\r
-06/08/2020,6,8,2020,21,0,Malaysia,MY,MYS,31949789,Asia,0.60094294\r
-05/08/2020,5,8,2020,1,0,Malaysia,MY,MYS,31949789,Asia,0.58529338\r
-04/08/2020,4,8,2020,2,0,Malaysia,MY,MYS,31949789,Asia,0.62911214\r
-03/08/2020,3,8,2020,14,0,Malaysia,MY,MYS,31949789,Asia,0.68858045\r
-02/08/2020,2,8,2020,9,0,Malaysia,MY,MYS,31949789,Asia,0.69171036\r
-01/08/2020,1,8,2020,12,1,Malaysia,MY,MYS,31949789,Asia,0.69171036\r
-31/07/2020,31,7,2020,8,0,Malaysia,MY,MYS,31949789,Asia,0.71048983\r
-30/07/2020,30,7,2020,13,0,Malaysia,MY,MYS,31949789,Asia,0.69484027\r
-29/07/2020,29,7,2020,39,0,Malaysia,MY,MYS,31949789,Asia,0.66980098\r
-28/07/2020,28,7,2020,7,0,Malaysia,MY,MYS,31949789,Asia,0.56025409\r
-27/07/2020,27,7,2020,13,1,Malaysia,MY,MYS,31949789,Asia,0.56025409\r
-26/07/2020,26,7,2020,23,0,Malaysia,MY,MYS,31949789,Asia,0.563384\r
-25/07/2020,25,7,2020,21,0,Malaysia,MY,MYS,31949789,Asia,0.51643534\r
-24/07/2020,24,7,2020,9,0,Malaysia,MY,MYS,31949789,Asia,0.49139605\r
-23/07/2020,23,7,2020,16,0,Malaysia,MY,MYS,31949789,Asia,0.48200631\r
-22/07/2020,22,7,2020,15,0,Malaysia,MY,MYS,31949789,Asia,0.44131747\r
-21/07/2020,21,7,2020,21,0,Malaysia,MY,MYS,31949789,Asia,0.41314827\r
-20/07/2020,20,7,2020,15,1,Malaysia,MY,MYS,31949789,Asia,0.37871925\r
-19/07/2020,19,7,2020,9,0,Malaysia,MY,MYS,31949789,Asia,0.33177058\r
-18/07/2020,18,7,2020,18,0,Malaysia,MY,MYS,31949789,Asia,0.33490049\r
-17/07/2020,17,7,2020,3,0,Malaysia,MY,MYS,31949789,Asia,0.29421165\r
-16/07/2020,16,7,2020,5,0,Malaysia,MY,MYS,31949789,Asia,0.29421165\r
-15/07/2020,15,7,2020,4,0,Malaysia,MY,MYS,31949789,Asia,0.281692\r
-14/07/2020,14,7,2020,7,0,Malaysia,MY,MYS,31949789,Asia,0.27543218\r
-13/07/2020,13,7,2020,14,0,Malaysia,MY,MYS,31949789,Asia,0.26291253\r
-12/07/2020,12,7,2020,8,1,Malaysia,MY,MYS,31949789,Asia,0.27543218\r
-11/07/2020,11,7,2020,13,0,Malaysia,MY,MYS,31949789,Asia,0.281692\r
-10/07/2020,10,7,2020,6,0,Malaysia,MY,MYS,31949789,Asia,0.25978262\r
-09/07/2020,9,7,2020,3,0,Malaysia,MY,MYS,31949789,Asia,0.2535228\r
-08/07/2020,8,7,2020,6,0,Malaysia,MY,MYS,31949789,Asia,0.26291253\r
-07/07/2020,7,7,2020,10,0,Malaysia,MY,MYS,31949789,Asia,0.2535228\r
-06/07/2020,6,7,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0.26917236\r
-05/07/2020,5,7,2020,10,0,Malaysia,MY,MYS,31949789,Asia,0.31925093\r
-04/07/2020,4,7,2020,5,0,Malaysia,MY,MYS,31949789,Asia,0.35367996\r
-03/07/2020,3,7,2020,3,0,Malaysia,MY,MYS,31949789,Asia,0.35680987\r
-02/07/2020,2,7,2020,1,0,Malaysia,MY,MYS,31949789,Asia,0.39123889\r
-01/07/2020,1,7,2020,2,0,Malaysia,MY,MYS,31949789,Asia,0.41940809\r
-30/06/2020,30,6,2020,3,0,Malaysia,MY,MYS,31949789,Asia,0.44757729\r
-29/06/2020,29,6,2020,18,0,Malaysia,MY,MYS,31949789,Asia,0.56651391\r
-28/06/2020,28,6,2020,10,0,Malaysia,MY,MYS,31949789,Asia,0.5352148\r
-27/06/2020,27,6,2020,6,0,Malaysia,MY,MYS,31949789,Asia,0.63850187\r
-26/06/2020,26,6,2020,4,0,Malaysia,MY,MYS,31949789,Asia,0.72300947\r
-25/06/2020,25,6,2020,6,0,Malaysia,MY,MYS,31949789,Asia,0.80751707\r
-24/06/2020,24,6,2020,3,0,Malaysia,MY,MYS,31949789,Asia,0.79499743\r
-23/06/2020,23,6,2020,15,0,Malaysia,MY,MYS,31949789,Asia,0.80751707\r
-22/06/2020,22,6,2020,16,0,Malaysia,MY,MYS,31949789,Asia,0.78247778\r
-21/06/2020,21,6,2020,21,0,Malaysia,MY,MYS,31949789,Asia,0.79186751\r
-20/06/2020,20,6,2020,6,0,Malaysia,MY,MYS,31949789,Asia,0.84194609\r
-19/06/2020,19,6,2020,14,0,Malaysia,MY,MYS,31949789,Asia,1.74962032\r
-18/06/2020,18,6,2020,10,0,Malaysia,MY,MYS,31949789,Asia,1.70580156\r
-17/06/2020,17,6,2020,11,0,Malaysia,MY,MYS,31949789,Asia,1.96558419\r
-16/06/2020,16,6,2020,41,0,Malaysia,MY,MYS,31949789,Asia,1.99375339\r
-15/06/2020,15,6,2020,8,1,Malaysia,MY,MYS,31949789,Asia,1.98436365\r
-14/06/2020,14,6,2020,43,1,Malaysia,MY,MYS,31949789,Asia,2.1377293\r
-13/06/2020,13,6,2020,33,1,Malaysia,MY,MYS,31949789,Asia,2.09704045\r
-12/06/2020,12,6,2020,31,0,Malaysia,MY,MYS,31949789,Asia,2.31613423\r
-11/06/2020,11,6,2020,2,1,Malaysia,MY,MYS,31949789,Asia,2.2504061\r
-10/06/2020,10,6,2020,7,0,Malaysia,MY,MYS,31949789,Asia,2.29109494\r
-09/06/2020,9,6,2020,7,0,Malaysia,MY,MYS,31949789,Asia,2.85447895\r
-08/06/2020,8,6,2020,19,0,Malaysia,MY,MYS,31949789,Asia,3.37091428\r
-07/06/2020,7,6,2020,37,1,Malaysia,MY,MYS,31949789,Asia,3.49924064\r
-06/06/2020,6,6,2020,296,1,Malaysia,MY,MYS,31949789,Asia,3.53366966\r
-05/06/2020,5,6,2020,0,0,Malaysia,MY,MYS,31949789,Asia,2.85134903\r
-04/06/2020,4,6,2020,93,0,Malaysia,MY,MYS,31949789,Asia,3.00784459\r
-03/06/2020,3,6,2020,20,0,Malaysia,MY,MYS,31949789,Asia,2.8137901\r
-02/06/2020,2,6,2020,38,0,Malaysia,MY,MYS,31949789,Asia,2.86699859\r
-01/06/2020,1,6,2020,57,0,Malaysia,MY,MYS,31949789,Asia,2.89516779\r
-31/05/2020,31,5,2020,30,0,Malaysia,MY,MYS,31949789,Asia,2.7856209\r
-30/05/2020,30,5,2020,103,0,Malaysia,MY,MYS,31949789,Asia,2.74493206\r
-29/05/2020,29,5,2020,10,0,Malaysia,MY,MYS,31949789,Asia,2.53522801\r
-28/05/2020,28,5,2020,15,0,Malaysia,MY,MYS,31949789,Asia,2.62912534\r
-27/05/2020,27,5,2020,187,0,Malaysia,MY,MYS,31949789,Asia,2.69798339\r
-26/05/2020,26,5,2020,172,0,Malaysia,MY,MYS,31949789,Asia,2.16276859\r
-25/05/2020,25,5,2020,60,0,Malaysia,MY,MYS,31949789,Asia,1.84351765\r
-24/05/2020,24,5,2020,48,0,Malaysia,MY,MYS,31949789,Asia,1.86542703\r
-23/05/2020,23,5,2020,78,1,Malaysia,MY,MYS,31949789,Asia,1.8842065\r
-22/05/2020,22,5,2020,50,0,Malaysia,MY,MYS,31949789,Asia,1.85290739\r
-21/05/2020,21,5,2020,31,0,Malaysia,MY,MYS,31949789,Asia,1.81847836\r
-20/05/2020,20,5,2020,37,1,Malaysia,MY,MYS,31949789,Asia,1.86229712\r
-19/05/2020,19,5,2020,47,0,Malaysia,MY,MYS,31949789,Asia,1.84038774\r
-18/05/2020,18,5,2020,22,0,Malaysia,MY,MYS,31949789,Asia,1.86542703\r
-17/05/2020,17,5,2020,17,1,Malaysia,MY,MYS,31949789,Asia,2.17841814\r
-16/05/2020,16,5,2020,36,0,Malaysia,MY,MYS,31949789,Asia,2.45385032\r
-15/05/2020,15,5,2020,40,1,Malaysia,MY,MYS,31949789,Asia,2.55713739\r
-14/05/2020,14,5,2020,37,2,Malaysia,MY,MYS,31949789,Asia,2.61034588\r
-13/05/2020,13,5,2020,16,0,Malaysia,MY,MYS,31949789,Asia,2.78875081\r
-12/05/2020,12,5,2020,70,1,Malaysia,MY,MYS,31949789,Asia,2.83569948\r
-11/05/2020,11,5,2020,67,0,Malaysia,MY,MYS,31949789,Asia,2.74180214\r
-10/05/2020,10,5,2020,54,1,Malaysia,MY,MYS,31949789,Asia,2.65103472\r
-09/05/2020,9,5,2020,68,0,Malaysia,MY,MYS,31949789,Asia,2.64164499\r
-08/05/2020,8,5,2020,39,0,Malaysia,MY,MYS,31949789,Asia,2.70424321\r
-07/05/2020,7,5,2020,45,1,Malaysia,MY,MYS,31949789,Asia,2.80440037\r
-06/05/2020,6,5,2020,30,1,Malaysia,MY,MYS,31949789,Asia,2.82004992\r
-05/05/2020,5,5,2020,55,0,Malaysia,MY,MYS,31949789,Asia,2.90455752\r
-04/05/2020,4,5,2020,122,2,Malaysia,MY,MYS,31949789,Asia,2.84508921\r
-03/05/2020,3,5,2020,105,0,Malaysia,MY,MYS,31949789,Asia,2.72615259\r
-02/05/2020,2,5,2020,69,1,Malaysia,MY,MYS,31949789,Asia,2.56652712\r
-01/05/2020,1,5,2020,57,2,Malaysia,MY,MYS,31949789,Asia,2.56652712\r
-30/04/2020,30,4,2020,94,0,Malaysia,MY,MYS,31949789,Asia,2.73241241\r
-29/04/2020,29,4,2020,31,1,Malaysia,MY,MYS,31949789,Asia,2.70424321\r
-28/04/2020,28,4,2020,40,1,Malaysia,MY,MYS,31949789,Asia,3.13930086\r
-27/04/2020,27,4,2020,38,0,Malaysia,MY,MYS,31949789,Asia,3.4335125\r
-26/04/2020,26,4,2020,51,2,Malaysia,MY,MYS,31949789,Asia,3.79345228\r
-25/04/2020,25,4,2020,88,1,Malaysia,MY,MYS,31949789,Asia,4.20973046\r
-24/04/2020,24,4,2020,71,2,Malaysia,MY,MYS,31949789,Asia,4.3036278\r
-23/04/2020,23,4,2020,50,1,Malaysia,MY,MYS,31949789,Asia,4.42256442\r
-22/04/2020,22,4,2020,57,3,Malaysia,MY,MYS,31949789,Asia,4.754335\r
-21/04/2020,21,4,2020,36,0,Malaysia,MY,MYS,31949789,Asia,5.10801495\r
-20/04/2020,20,4,2020,84,1,Malaysia,MY,MYS,31949789,Asia,5.40535651\r
-19/04/2020,19,4,2020,54,2,Malaysia,MY,MYS,31949789,Asia,5.70269807\r
-18/04/2020,18,4,2020,69,2,Malaysia,MY,MYS,31949789,Asia,6.00316954\r
-17/04/2020,17,4,2020,110,1,Malaysia,MY,MYS,31949789,Asia,6.46639638\r
-16/04/2020,16,4,2020,85,1,Malaysia,MY,MYS,31949789,Asia,6.77312767\r
-15/04/2020,15,4,2020,170,5,Malaysia,MY,MYS,31949789,Asia,6.95153261\r
-14/04/2020,14,4,2020,134,1,Malaysia,MY,MYS,31949789,Asia,6.85763527\r
-13/04/2020,13,4,2020,153,3,Malaysia,MY,MYS,31949789,Asia,6.92649332\r
-12/04/2020,12,4,2020,184,3,Malaysia,MY,MYS,31949789,Asia,6.91710358\r
-11/04/2020,11,4,2020,118,3,Malaysia,MY,MYS,31949789,Asia,6.83885581\r
-10/04/2020,10,4,2020,109,2,Malaysia,MY,MYS,31949789,Asia,6.87641474\r
-09/04/2020,9,4,2020,156,2,Malaysia,MY,MYS,31949789,Asia,7.27078354\r
-08/04/2020,8,4,2020,170,1,Malaysia,MY,MYS,31949789,Asia,7.32086212\r
-07/04/2020,7,4,2020,131,1,Malaysia,MY,MYS,31949789,Asia,7.12054781\r
-06/04/2020,6,4,2020,179,4,Malaysia,MY,MYS,31949789,Asia,7.37407061\r
-05/04/2020,5,4,2020,150,4,Malaysia,MY,MYS,31949789,Asia,7.19879559\r
-04/04/2020,4,4,2020,217,3,Malaysia,MY,MYS,31949789,Asia,7.20818532\r
-03/04/2020,3,4,2020,208,5,Malaysia,MY,MYS,31949789,Asia,6.93588305\r
-02/04/2020,2,4,2020,142,2,Malaysia,MY,MYS,31949789,Asia,6.62915176\r
-01/04/2020,1,4,2020,140,6,Malaysia,MY,MYS,31949789,Asia,6.55090398\r
-31/03/2020,31,3,2020,156,3,Malaysia,MY,MYS,31949789,Asia,6.48830576\r
-30/03/2020,30,3,2020,150,7,Malaysia,MY,MYS,31949789,Asia,6.39127852\r
-29/03/2020,29,3,2020,159,1,Malaysia,MY,MYS,31949789,Asia,6.51647496\r
-28/03/2020,28,3,2020,130,3,Malaysia,MY,MYS,31949789,Asia,6.14714545\r
-27/03/2020,27,3,2020,235,4,Malaysia,MY,MYS,31949789,Asia,5.86232354\r
-26/03/2020,26,3,2020,172,4,Malaysia,MY,MYS,31949789,Asia,5.15496362\r
-25/03/2020,25,3,2020,106,1,Malaysia,MY,MYS,31949789,Asia,4.67921713\r
-24/03/2020,24,3,2020,212,4,Malaysia,MY,MYS,31949789,Asia,4.38500548\r
-23/03/2020,23,3,2020,123,6,Malaysia,MY,MYS,31949789,Asia,3.77780273\r
-22/03/2020,22,3,2020,153,2,Malaysia,MY,MYS,31949789,Asia,3.41160313\r
-21/03/2020,21,3,2020,130,0,Malaysia,MY,MYS,31949789,Asia,2.96402583\r
-20/03/2020,20,3,2020,110,0,Malaysia,MY,MYS,31949789,Asia,2.66042446\r
-19/03/2020,19,3,2020,117,0,Malaysia,MY,MYS,31949789,Asia,2.31613423\r
-18/03/2020,18,3,2020,120,2,Malaysia,MY,MYS,31949789,Asia,1.99375339\r
-17/03/2020,17,3,2020,125,0,Malaysia,MY,MYS,31949789,Asia,1.64007343\r
-16/03/2020,16,3,2020,190,0,Malaysia,MY,MYS,31949789,Asia,1.26135418\r
-15/03/2020,15,3,2020,41,0,Malaysia,MY,MYS,31949789,Asia,0.66667107\r
-14/03/2020,14,3,2020,39,0,Malaysia,MY,MYS,31949789,Asia,0.54460454\r
-13/03/2020,13,3,2020,9,0,Malaysia,MY,MYS,31949789,Asia,0.42566791\r
-12/03/2020,12,3,2020,20,0,Malaysia,MY,MYS,31949789,Asia,0.39749871\r
-11/03/2020,11,3,2020,12,0,Malaysia,MY,MYS,31949789,Asia,0.33490049\r
-10/03/2020,10,3,2020,18,0,Malaysia,MY,MYS,31949789,Asia,0.29734156\r
-09/03/2020,9,3,2020,6,0,Malaysia,MY,MYS,31949789,Asia,0.24100316\r
-08/03/2020,8,3,2020,10,0,Malaysia,MY,MYS,31949789,Asia,0.22222369\r
-07/03/2020,7,3,2020,33,0,Malaysia,MY,MYS,31949789,Asia,0.19092458\r
-06/03/2020,6,3,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0.08763751\r
-05/03/2020,5,3,2020,14,0,Malaysia,MY,MYS,31949789,Asia,0.08763751\r
-04/03/2020,4,3,2020,7,0,Malaysia,MY,MYS,31949789,Asia,0.04381876\r
-02/03/2020,2,3,2020,4,0,Malaysia,MY,MYS,31949789,Asia,0.02190938\r
-01/03/2020,1,3,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0.00938973\r
-29/02/2020,29,2,2020,2,0,Malaysia,MY,MYS,31949789,Asia,0.01251964\r
-28/02/2020,28,2,2020,1,0,Malaysia,MY,MYS,31949789,Asia,0.01251964\r
-27/02/2020,27,2,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0.01251964\r
-26/02/2020,26,2,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0.01251964\r
-25/02/2020,25,2,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0.01251964\r
-24/02/2020,24,2,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0.01251964\r
-23/02/2020,23,2,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0.01877947\r
-22/02/2020,22,2,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0.02190938\r
-21/02/2020,21,2,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0.02503929\r
-20/02/2020,20,2,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0.03129911\r
-19/02/2020,19,2,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0.03755893\r
-18/02/2020,18,2,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0.04381876\r
-17/02/2020,17,2,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0.04381876\r
-16/02/2020,16,2,2020,1,0,Malaysia,MY,MYS,31949789,Asia,0.04381876\r
-15/02/2020,15,2,2020,2,0,Malaysia,MY,MYS,31949789,Asia,0.04068884\r
-14/02/2020,14,2,2020,1,0,Malaysia,MY,MYS,31949789,Asia,0.03442902\r
-13/02/2020,13,2,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0.03442902\r
-12/02/2020,12,2,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0.03442902\r
-11/02/2020,11,2,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0.04381876\r
-10/02/2020,10,2,2020,2,0,Malaysia,MY,MYS,31949789,Asia,0.04381876\r
-09/02/2020,9,2,2020,1,0,Malaysia,MY,MYS,31949789,Asia,0.03755893\r
-08/02/2020,8,2,2020,1,0,Malaysia,MY,MYS,31949789,Asia,0.03755893\r
-07/02/2020,7,2,2020,2,0,Malaysia,MY,MYS,31949789,Asia,0.04381876\r
-06/02/2020,6,2,2020,2,0,Malaysia,MY,MYS,31949789,Asia,0.03755893\r
-05/02/2020,5,2,2020,2,0,Malaysia,MY,MYS,31949789,Asia,0.03129911\r
-04/02/2020,4,2,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0.02503929\r
-03/02/2020,3,2,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0.02503929\r
-02/02/2020,2,2,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0.02503929\r
-01/02/2020,1,2,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0.02503929\r
-31/01/2020,31,1,2020,1,0,Malaysia,MY,MYS,31949789,Asia,0.02503929\r
-30/01/2020,30,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0.02190938\r
-29/01/2020,29,1,2020,3,0,Malaysia,MY,MYS,31949789,Asia,0.02190938\r
-28/01/2020,28,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0.01251964\r
-27/01/2020,27,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0.01251964\r
-26/01/2020,26,1,2020,1,0,Malaysia,MY,MYS,31949789,Asia,0.01251964\r
-25/01/2020,25,1,2020,3,0,Malaysia,MY,MYS,31949789,Asia,0.00938973\r
-24/01/2020,24,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0\r
-23/01/2020,23,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0\r
-22/01/2020,22,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0\r
-21/01/2020,21,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0\r
-20/01/2020,20,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0\r
-19/01/2020,19,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0\r
-18/01/2020,18,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0\r
-17/01/2020,17,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0\r
-16/01/2020,16,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0\r
-15/01/2020,15,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0\r
-14/01/2020,14,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0\r
-13/01/2020,13,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,0\r
-12/01/2020,12,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,\r
-11/01/2020,11,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,\r
-10/01/2020,10,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,\r
-09/01/2020,9,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,\r
-08/01/2020,8,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,\r
-07/01/2020,7,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,\r
-06/01/2020,6,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,\r
-05/01/2020,5,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,\r
-04/01/2020,4,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,\r
-03/01/2020,3,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,\r
-02/01/2020,2,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,\r
-01/01/2020,1,1,2020,0,0,Malaysia,MY,MYS,31949789,Asia,\r
-31/12/2019,31,12,2019,0,0,Malaysia,MY,MYS,31949789,Asia,\r
-19/08/2020,19,8,2020,170,1,Maldives,MV,MDV,530957,Asia,307.5578625\r
-18/08/2020,18,8,2020,124,1,Maldives,MV,MDV,530957,Asia,304.35609663\r
-17/08/2020,17,8,2020,106,0,Maldives,MV,MDV,530957,Asia,305.29779248\r
-16/08/2020,16,8,2020,107,0,Maldives,MV,MDV,530957,Asia,325.82676187\r
-15/08/2020,15,8,2020,78,1,Maldives,MV,MDV,530957,Asia,335.05538113\r
-14/08/2020,14,8,2020,128,0,Maldives,MV,MDV,530957,Asia,334.30202446\r
-13/08/2020,13,8,2020,143,1,Maldives,MV,MDV,530957,Asia,338.82216451\r
-12/08/2020,12,8,2020,66,1,Maldives,MV,MDV,530957,Asia,323.37835267\r
-11/08/2020,11,8,2020,116,0,Maldives,MV,MDV,530957,Asia,336.75043365\r
-10/08/2020,10,8,2020,143,0,Maldives,MV,MDV,530957,Asia,327.52181438\r
-09/08/2020,9,8,2020,129,0,Maldives,MV,MDV,530957,Asia,310.00627169\r
-08/08/2020,8,8,2020,89,0,Maldives,MV,MDV,530957,Asia,310.5712892\r
-07/08/2020,7,8,2020,86,0,Maldives,MV,MDV,530957,Asia,297.01086905\r
-06/08/2020,6,8,2020,148,0,Maldives,MV,MDV,530957,Asia,280.81370054\r
-05/08/2020,5,8,2020,153,1,Maldives,MV,MDV,530957,Asia,264.05151453\r
-04/08/2020,4,8,2020,129,1,Maldives,MV,MDV,530957,Asia,249.92607688\r
-03/08/2020,3,8,2020,215,0,Maldives,MV,MDV,530957,Asia,225.63032411\r
-02/08/2020,2,8,2020,156,1,Maldives,MV,MDV,530957,Asia,191.91761291\r
-01/08/2020,1,8,2020,74,0,Maldives,MV,MDV,530957,Asia,165.73846846\r
-31/07/2020,31,7,2020,152,1,Maldives,MV,MDV,530957,Asia,154.43811834\r
-30/07/2020,30,7,2020,61,0,Maldives,MV,MDV,530957,Asia,138.61762817\r
-29/07/2020,29,7,2020,137,0,Maldives,MV,MDV,530957,Asia,132.77911394\r
-28/07/2020,28,7,2020,67,0,Maldives,MV,MDV,530957,Asia,114.32187541\r
-27/07/2020,27,7,2020,50,0,Maldives,MV,MDV,530957,Asia,107.54166533\r
-26/07/2020,26,7,2020,132,0,Maldives,MV,MDV,530957,Asia,110.7434312\r
-25/07/2020,25,7,2020,17,0,Maldives,MV,MDV,530957,Asia,94.73460186\r
-24/07/2020,24,7,2020,0,0,Maldives,MV,MDV,530957,Asia,103.58654279\r
-23/07/2020,23,7,2020,59,0,Maldives,MV,MDV,530957,Asia,110.36675286\r
-22/07/2020,22,7,2020,78,0,Maldives,MV,MDV,530957,Asia,102.26816861\r
-21/07/2020,21,7,2020,0,0,Maldives,MV,MDV,530957,Asia,89.46110514\r
-20/07/2020,20,7,2020,36,0,Maldives,MV,MDV,530957,Asia,93.79290602\r
-19/07/2020,19,7,2020,17,0,Maldives,MV,MDV,530957,Asia,93.22788851\r
-18/07/2020,18,7,2020,14,0,Maldives,MV,MDV,530957,Asia,94.73460186\r
-17/07/2020,17,7,2020,68,1,Maldives,MV,MDV,530957,Asia,93.98124519\r
-16/07/2020,16,7,2020,30,0,Maldives,MV,MDV,530957,Asia,84.56428675\r
-15/07/2020,15,7,2020,39,1,Maldives,MV,MDV,530957,Asia,82.86923423\r
-14/07/2020,14,7,2020,31,0,Maldives,MV,MDV,530957,Asia,80.23248587\r
-13/07/2020,13,7,2020,67,0,Maldives,MV,MDV,530957,Asia,76.84238083\r
-12/07/2020,12,7,2020,47,0,Maldives,MV,MDV,530957,Asia,67.61376157\r
-11/07/2020,11,7,2020,64,0,Maldives,MV,MDV,530957,Asia,62.90528235\r
-10/07/2020,10,7,2020,36,0,Maldives,MV,MDV,530957,Asia,51.98161056\r
-09/07/2020,9,7,2020,16,1,Maldives,MV,MDV,530957,Asia,48.21482719\r
-08/07/2020,8,7,2020,10,0,Maldives,MV,MDV,530957,Asia,49.53320137\r
-07/07/2020,7,7,2020,23,1,Maldives,MV,MDV,530957,Asia,51.60493223\r
-06/07/2020,6,7,2020,33,1,Maldives,MV,MDV,530957,Asia,49.90987971\r
-05/07/2020,5,7,2020,25,0,Maldives,MV,MDV,530957,Asia,46.70811384\r
-04/07/2020,4,7,2020,10,0,Maldives,MV,MDV,530957,Asia,48.96818386\r
-03/07/2020,3,7,2020,18,1,Maldives,MV,MDV,530957,Asia,49.53320137\r
-02/07/2020,2,7,2020,21,0,Maldives,MV,MDV,530957,Asia,49.3448622\r
-01/07/2020,1,7,2020,25,1,Maldives,MV,MDV,530957,Asia,50.28655805\r
-30/06/2020,30,6,2020,13,0,Maldives,MV,MDV,530957,Asia,51.03991472\r
-29/06/2020,29,6,2020,18,0,Maldives,MV,MDV,530957,Asia,54.24168059\r
-28/06/2020,28,6,2020,22,0,Maldives,MV,MDV,530957,Asia,54.99503726\r
-27/06/2020,27,6,2020,6,0,Maldives,MV,MDV,530957,Asia,52.73496724\r
-26/06/2020,26,6,2020,16,0,Maldives,MV,MDV,530957,Asia,56.69008978\r
-25/06/2020,25,6,2020,23,0,Maldives,MV,MDV,530957,Asia,56.31341144\r
-24/06/2020,24,6,2020,21,0,Maldives,MV,MDV,530957,Asia,55.74839394\r
-23/06/2020,23,6,2020,14,0,Maldives,MV,MDV,530957,Asia,56.69008978\r
-22/06/2020,22,6,2020,16,0,Maldives,MV,MDV,530957,Asia,56.50175061\r
-21/06/2020,21,6,2020,37,0,Maldives,MV,MDV,530957,Asia,53.86500225\r
-20/06/2020,20,6,2020,13,0,Maldives,MV,MDV,530957,Asia,50.28655805\r
-19/06/2020,19,6,2020,17,0,Maldives,MV,MDV,530957,Asia,49.90987971\r
-18/06/2020,18,6,2020,26,0,Maldives,MV,MDV,530957,Asia,50.85157555\r
-17/06/2020,17,6,2020,29,0,Maldives,MV,MDV,530957,Asia,47.64980968\r
-16/06/2020,16,6,2020,30,0,Maldives,MV,MDV,530957,Asia,44.44804382\r
-15/06/2020,15,6,2020,22,0,Maldives,MV,MDV,530957,Asia,49.3448622\r
-14/06/2020,14,6,2020,10,0,Maldives,MV,MDV,530957,Asia,64.22365653\r
-13/06/2020,13,6,2020,27,0,Maldives,MV,MDV,530957,Asia,77.59573751\r
-12/06/2020,12,6,2020,14,0,Maldives,MV,MDV,530957,Asia,87.20103511\r
-11/06/2020,11,6,2020,20,0,Maldives,MV,MDV,530957,Asia,95.1112802\r
-10/06/2020,10,6,2020,26,0,Maldives,MV,MDV,530957,Asia,94.92294103\r
-09/06/2020,9,6,2020,13,0,Maldives,MV,MDV,530957,Asia,98.1247069\r
-08/06/2020,8,6,2020,2,1,Maldives,MV,MDV,530957,Asia,100.19643775\r
-07/06/2020,7,6,2020,18,0,Maldives,MV,MDV,530957,Asia,112.62682289\r
-06/06/2020,6,6,2020,11,0,Maldives,MV,MDV,530957,Asia,114.69855374\r
-05/06/2020,5,6,2020,22,0,Maldives,MV,MDV,530957,Asia,123.55049467\r
-04/06/2020,4,6,2020,9,0,Maldives,MV,MDV,530957,Asia,125.05720802\r
-03/06/2020,3,6,2020,12,1,Maldives,MV,MDV,530957,Asia,131.46073976\r
-02/06/2020,2,6,2020,56,1,Maldives,MV,MDV,530957,Asia,136.16921898\r
-01/06/2020,1,6,2020,101,0,Maldives,MV,MDV,530957,Asia,127.88229555\r
-31/05/2020,31,5,2020,81,0,Maldives,MV,MDV,530957,Asia,111.87346621\r
-30/05/2020,30,5,2020,78,0,Maldives,MV,MDV,530957,Asia,105.46993448\r
-29/05/2020,29,5,2020,56,0,Maldives,MV,MDV,530957,Asia,100.00809858\r
-28/05/2020,28,5,2020,19,0,Maldives,MV,MDV,530957,Asia,94.54626269\r
-27/05/2020,27,5,2020,43,1,Maldives,MV,MDV,530957,Asia,100.57311609\r
-26/05/2020,26,5,2020,24,0,Maldives,MV,MDV,530957,Asia,93.79290602\r
-25/05/2020,25,5,2020,68,0,Maldives,MV,MDV,530957,Asia,100.94979443\r
-24/05/2020,24,5,2020,29,0,Maldives,MV,MDV,530957,Asia,96.61799355\r
-23/05/2020,23,5,2020,58,0,Maldives,MV,MDV,530957,Asia,118.65367629\r
-22/05/2020,22,5,2020,30,0,Maldives,MV,MDV,530957,Asia,108.10668284\r
-21/05/2020,21,5,2020,43,0,Maldives,MV,MDV,530957,Asia,107.164987\r
-20/05/2020,20,5,2020,37,0,Maldives,MV,MDV,530957,Asia,107.35332616\r
-19/05/2020,19,5,2020,12,0,Maldives,MV,MDV,530957,Asia,104.52823863\r
-18/05/2020,18,5,2020,16,0,Maldives,MV,MDV,530957,Asia,106.78830866\r
-17/05/2020,17,5,2020,47,0,Maldives,MV,MDV,530957,Asia,105.28159531\r
-16/05/2020,16,5,2020,49,0,Maldives,MV,MDV,530957,Asia,101.7031511\r
-15/05/2020,15,5,2020,27,0,Maldives,MV,MDV,530957,Asia,96.80633272\r
-14/05/2020,14,5,2020,51,1,Maldives,MV,MDV,530957,Asia,127.69395638\r
-13/05/2020,13,5,2020,7,0,Maldives,MV,MDV,530957,Asia,124.11551218\r
-12/05/2020,12,5,2020,62,0,Maldives,MV,MDV,530957,Asia,128.63565223\r
-11/05/2020,11,5,2020,45,0,Maldives,MV,MDV,530957,Asia,116.95862377\r
-10/05/2020,10,5,2020,146,0,Maldives,MV,MDV,530957,Asia,122.98547717\r
-09/05/2020,9,5,2020,2,0,Maldives,MV,MDV,530957,Asia,97.18301105\r
-08/05/2020,8,5,2020,25,1,Maldives,MV,MDV,530957,Asia,100.19643775\r
-07/05/2020,7,5,2020,44,1,Maldives,MV,MDV,530957,Asia,100.19643775\r
-06/05/2020,6,5,2020,22,0,Maldives,MV,MDV,530957,Asia,91.90951433\r
-05/05/2020,5,5,2020,24,0,Maldives,MV,MDV,530957,Asia,90.77947932\r
-04/05/2020,4,5,2020,8,0,Maldives,MV,MDV,530957,Asia,89.46110514\r
-03/05/2020,3,5,2020,28,0,Maldives,MV,MDV,530957,Asia,91.15615765\r
-02/05/2020,2,5,2020,23,0,Maldives,MV,MDV,530957,Asia,87.01269594\r
-01/05/2020,1,5,2020,191,1,Maldives,MV,MDV,530957,Asia,83.43425174\r
-30/04/2020,30,4,2020,32,0,Maldives,MV,MDV,530957,Asia,48.21482719\r
-29/04/2020,29,4,2020,31,0,Maldives,MV,MDV,530957,Asia,42.18797379\r
-28/04/2020,28,4,2020,0,0,Maldives,MV,MDV,530957,Asia,36.53779873\r
-27/04/2020,27,4,2020,77,0,Maldives,MV,MDV,530957,Asia,36.53779873\r
-26/04/2020,26,4,2020,9,0,Maldives,MV,MDV,530957,Asia,22.22402191\r
-25/04/2020,25,4,2020,18,0,Maldives,MV,MDV,530957,Asia,20.52896939\r
-24/04/2020,24,4,2020,25,0,Maldives,MV,MDV,530957,Asia,17.13886435\r
-23/04/2020,23,4,2020,0,0,Maldives,MV,MDV,530957,Asia,12.43038513\r
-22/04/2020,22,4,2020,16,0,Maldives,MV,MDV,530957,Asia,12.43038513\r
-21/04/2020,21,4,2020,17,0,Maldives,MV,MDV,530957,Asia,9.41695844\r
-20/04/2020,20,4,2020,17,0,Maldives,MV,MDV,530957,Asia,6.21519257\r
-19/04/2020,19,4,2020,6,0,Maldives,MV,MDV,530957,Asia,3.0134267\r
-18/04/2020,18,4,2020,4,0,Maldives,MV,MDV,530957,Asia,1.88339169\r
-17/04/2020,17,4,2020,4,0,Maldives,MV,MDV,530957,Asia,1.13003501\r
-16/04/2020,16,4,2020,0,0,Maldives,MV,MDV,530957,Asia,0.37667834\r
-15/04/2020,15,4,2020,1,0,Maldives,MV,MDV,530957,Asia,0.56501751\r
-14/04/2020,14,4,2020,0,0,Maldives,MV,MDV,530957,Asia,0.56501751\r
-13/04/2020,13,4,2020,1,0,Maldives,MV,MDV,530957,Asia,0.56501751\r
-12/04/2020,12,4,2020,0,0,Maldives,MV,MDV,530957,Asia,0.56501751\r
-11/04/2020,11,4,2020,0,0,Maldives,MV,MDV,530957,Asia,0.94169584\r
-10/04/2020,10,4,2020,0,0,Maldives,MV,MDV,530957,Asia,1.13003501\r
-09/04/2020,9,4,2020,0,0,Maldives,MV,MDV,530957,Asia,1.13003501\r
-08/04/2020,8,4,2020,0,0,Maldives,MV,MDV,530957,Asia,1.13003501\r
-07/04/2020,7,4,2020,0,0,Maldives,MV,MDV,530957,Asia,1.13003501\r
-06/04/2020,6,4,2020,0,0,Maldives,MV,MDV,530957,Asia,1.13003501\r
-05/04/2020,5,4,2020,0,0,Maldives,MV,MDV,530957,Asia,1.13003501\r
-04/04/2020,4,4,2020,0,0,Maldives,MV,MDV,530957,Asia,1.13003501\r
-03/04/2020,3,4,2020,0,0,Maldives,MV,MDV,530957,Asia,1.13003501\r
-02/04/2020,2,4,2020,1,0,Maldives,MV,MDV,530957,Asia,1.13003501\r
-01/04/2020,1,4,2020,1,0,Maldives,MV,MDV,530957,Asia,0.94169584\r
-31/03/2020,31,3,2020,0,0,Maldives,MV,MDV,530957,Asia,0.75335667\r
-30/03/2020,30,3,2020,1,0,Maldives,MV,MDV,530957,Asia,0.75335667\r
-29/03/2020,29,3,2020,2,0,Maldives,MV,MDV,530957,Asia,1.31837418\r
-28/03/2020,28,3,2020,1,0,Maldives,MV,MDV,530957,Asia,0.94169584\r
-27/03/2020,27,3,2020,0,0,Maldives,MV,MDV,530957,Asia,0.94169584\r
-26/03/2020,26,3,2020,0,0,Maldives,MV,MDV,530957,Asia,1.31837418\r
-25/03/2020,25,3,2020,0,0,Maldives,MV,MDV,530957,Asia,1.69505252\r
-24/03/2020,24,3,2020,0,0,Maldives,MV,MDV,530957,Asia,2.07173086\r
-23/03/2020,23,3,2020,0,0,Maldives,MV,MDV,530957,Asia,2.44840919\r
-22/03/2020,22,3,2020,0,0,Maldives,MV,MDV,530957,Asia,\r
-21/03/2020,21,3,2020,0,0,Maldives,MV,MDV,530957,Asia,\r
-20/03/2020,20,3,2020,0,0,Maldives,MV,MDV,530957,Asia,\r
-19/03/2020,19,3,2020,0,0,Maldives,MV,MDV,530957,Asia,\r
-18/03/2020,18,3,2020,0,0,Maldives,MV,MDV,530957,Asia,\r
-17/03/2020,17,3,2020,0,0,Maldives,MV,MDV,530957,Asia,\r
-16/03/2020,16,3,2020,4,0,Maldives,MV,MDV,530957,Asia,\r
-15/03/2020,15,3,2020,0,0,Maldives,MV,MDV,530957,Asia,\r
-14/03/2020,14,3,2020,1,0,Maldives,MV,MDV,530957,Asia,\r
-12/03/2020,12,3,2020,2,0,Maldives,MV,MDV,530957,Asia,\r
-11/03/2020,11,3,2020,2,0,Maldives,MV,MDV,530957,Asia,\r
-09/03/2020,9,3,2020,2,0,Maldives,MV,MDV,530957,Asia,\r
-08/03/2020,8,3,2020,2,0,Maldives,MV,MDV,530957,Asia,\r
-19/08/2020,19,8,2020,26,0,Mali,ML,MLI,19658023,Africa,0.62569873\r
-18/08/2020,18,8,2020,26,0,Mali,ML,MLI,19658023,Africa,0.49343721\r
-17/08/2020,17,8,2020,0,0,Mali,ML,MLI,19658023,Africa,0.37134965\r
-16/08/2020,16,8,2020,17,0,Mali,ML,MLI,19658023,Africa,0.40187154\r
-15/08/2020,15,8,2020,0,0,Mali,ML,MLI,19658023,Africa,0.31539286\r
-14/08/2020,14,8,2020,15,0,Mali,ML,MLI,19658023,Africa,0.38152362\r
-13/08/2020,13,8,2020,5,0,Mali,ML,MLI,19658023,Africa,0.31030587\r
-12/08/2020,12,8,2020,4,0,Mali,ML,MLI,19658023,Africa,0.28995795\r
-11/08/2020,11,8,2020,6,0,Mali,ML,MLI,19658023,Africa,0.30521889\r
-10/08/2020,10,8,2020,2,0,Mali,ML,MLI,19658023,Africa,0.28995795\r
-09/08/2020,9,8,2020,4,0,Mali,ML,MLI,19658023,Africa,0.31539286\r
-08/08/2020,8,8,2020,9,1,Mali,ML,MLI,19658023,Africa,0.29504493\r
-07/08/2020,7,8,2020,6,0,Mali,ML,MLI,19658023,Africa,0.29504493\r
-06/08/2020,6,8,2020,3,0,Mali,ML,MLI,19658023,Africa,0.26452304\r
-05/08/2020,5,8,2020,0,0,Mali,ML,MLI,19658023,Africa,0.33574078\r
-04/08/2020,4,8,2020,2,0,Mali,ML,MLI,19658023,Africa,0.34591474\r
-03/08/2020,3,8,2020,6,0,Mali,ML,MLI,19658023,Africa,0.33574078\r
-02/08/2020,2,8,2020,0,0,Mali,ML,MLI,19658023,Africa,0.32047984\r
-01/08/2020,1,8,2020,13,0,Mali,ML,MLI,19658023,Africa,0.34591474\r
-31/07/2020,31,7,2020,1,0,Mali,ML,MLI,19658023,Africa,0.41713249\r
-30/07/2020,30,7,2020,1,0,Mali,ML,MLI,19658023,Africa,0.44765438\r
-29/07/2020,29,7,2020,7,0,Mali,ML,MLI,19658023,Africa,0.49343721\r
-28/07/2020,28,7,2020,3,1,Mali,ML,MLI,19658023,Africa,0.51378513\r
-27/07/2020,27,7,2020,7,0,Mali,ML,MLI,19658023,Africa,0.50361117\r
-26/07/2020,26,7,2020,0,0,Mali,ML,MLI,19658023,Africa,0.49343721\r
-25/07/2020,25,7,2020,9,0,Mali,ML,MLI,19658023,Africa,0.50361117\r
-24/07/2020,24,7,2020,0,0,Mali,ML,MLI,19658023,Africa,0.69182949\r
-23/07/2020,23,7,2020,17,1,Mali,ML,MLI,19658023,Africa,0.69182949\r
-22/07/2020,22,7,2020,2,1,Mali,ML,MLI,19658023,Africa,0.65622062\r
-21/07/2020,21,7,2020,0,0,Mali,ML,MLI,19658023,Africa,0.73252534\r
-20/07/2020,20,7,2020,3,0,Mali,ML,MLI,19658023,Africa,0.73761232\r
-19/07/2020,19,7,2020,5,0,Mali,ML,MLI,19658023,Africa,0.85969988\r
-18/07/2020,18,7,2020,27,0,Mali,ML,MLI,19658023,Africa,0.92583064\r
-17/07/2020,17,7,2020,7,0,Mali,ML,MLI,19658023,Africa,0.91565668\r
-16/07/2020,16,7,2020,10,0,Mali,ML,MLI,19658023,Africa,1.17509273\r
-15/07/2020,15,7,2020,11,0,Mali,ML,MLI,19658023,Africa,1.23104953\r
-14/07/2020,14,7,2020,1,0,Mali,ML,MLI,19658023,Africa,1.21578859\r
-13/07/2020,13,7,2020,5,0,Mali,ML,MLI,19658023,Africa,1.34296313\r
-12/07/2020,12,7,2020,2,0,Mali,ML,MLI,19658023,Africa,1.46505068\r
-11/07/2020,11,7,2020,46,1,Mali,ML,MLI,19658023,Africa,1.85674826\r
-10/07/2020,10,7,2020,0,0,Mali,ML,MLI,19658023,Africa,1.78553052\r
-09/07/2020,9,7,2020,10,1,Mali,ML,MLI,19658023,Africa,1.81605241\r
-08/07/2020,8,7,2020,17,0,Mali,ML,MLI,19658023,Africa,1.88218317\r
-07/07/2020,7,7,2020,1,0,Mali,ML,MLI,19658023,Africa,1.88218317\r
-06/07/2020,6,7,2020,27,1,Mali,ML,MLI,19658023,Africa,1.87709619\r
-05/07/2020,5,7,2020,18,1,Mali,ML,MLI,19658023,Africa,1.88218317\r
-04/07/2020,4,7,2020,25,0,Mali,ML,MLI,19658023,Africa,1.84148732\r
-03/07/2020,3,7,2020,58,1,Mali,ML,MLI,19658023,Africa,1.80079146\r
-02/07/2020,2,7,2020,21,0,Mali,ML,MLI,19658023,Africa,1.58713824\r
-01/07/2020,1,7,2020,8,1,Mali,ML,MLI,19658023,Africa,1.50574653\r
-30/06/2020,30,6,2020,26,1,Mali,ML,MLI,19658023,Africa,1.59222522\r
-29/06/2020,29,6,2020,29,1,Mali,ML,MLI,19658023,Africa,1.71939976\r
-28/06/2020,28,6,2020,79,0,Mali,ML,MLI,19658023,Africa,1.73974768\r
-27/06/2020,27,6,2020,32,0,Mali,ML,MLI,19658023,Africa,1.4599637\r
-26/06/2020,26,6,2020,6,1,Mali,ML,MLI,19658023,Africa,1.44978974\r
-25/06/2020,25,6,2020,23,1,Mali,ML,MLI,19658023,Africa,1.69905183\r
-24/06/2020,24,6,2020,17,0,Mali,ML,MLI,19658023,Africa,1.99409676\r
-23/06/2020,23,6,2020,0,0,Mali,ML,MLI,19658023,Africa,2.10601036\r
-22/06/2020,22,6,2020,28,2,Mali,ML,MLI,19658023,Africa,2.1772281\r
-21/06/2020,21,6,2020,10,1,Mali,ML,MLI,19658023,Africa,2.08566243\r
-20/06/2020,20,6,2020,17,1,Mali,ML,MLI,19658023,Africa,2.22809791\r
-19/06/2020,19,6,2020,16,0,Mali,ML,MLI,19658023,Africa,2.26370678\r
-18/06/2020,18,6,2020,5,1,Mali,ML,MLI,19658023,Africa,2.74188305\r
-17/06/2020,17,6,2020,25,2,Mali,ML,MLI,19658023,Africa,2.71644814\r
-16/06/2020,16,6,2020,51,0,Mali,ML,MLI,19658023,Africa,2.77240494\r
-15/06/2020,15,6,2020,33,0,Mali,ML,MLI,19658023,Africa,2.76731795\r
-14/06/2020,14,6,2020,24,3,Mali,ML,MLI,19658023,Africa,2.67575229\r
-13/06/2020,13,6,2020,30,4,Mali,ML,MLI,19658023,Africa,2.67575229\r
-12/06/2020,12,6,2020,55,1,Mali,ML,MLI,19658023,Africa,2.68592625\r
-11/06/2020,11,6,2020,81,2,Mali,ML,MLI,19658023,Africa,2.80292683\r
-10/06/2020,10,6,2020,39,2,Mali,ML,MLI,19658023,Africa,2.5892736\r
-09/06/2020,9,6,2020,14,0,Mali,ML,MLI,19658023,Africa,2.48244699\r
-08/06/2020,8,6,2020,10,2,Mali,ML,MLI,19658023,Africa,2.55875171\r
-07/06/2020,7,6,2020,38,3,Mali,ML,MLI,19658023,Africa,2.58418662\r
-06/06/2020,6,6,2020,24,2,Mali,ML,MLI,19658023,Africa,2.62488247\r
-05/06/2020,5,6,2020,110,7,Mali,ML,MLI,19658023,Africa,2.61470851\r
-04/06/2020,4,6,2020,0,0,Mali,ML,MLI,19658023,Africa,2.13653224\r
-03/06/2020,3,6,2020,36,0,Mali,ML,MLI,19658023,Africa,2.28914169\r
-02/06/2020,2,6,2020,50,1,Mali,ML,MLI,19658023,Africa,2.24335886\r
-01/06/2020,1,6,2020,15,1,Mali,ML,MLI,19658023,Africa,2.06022752\r
-31/05/2020,31,5,2020,24,3,Mali,ML,MLI,19658023,Africa,2.11109734\r
-30/05/2020,30,5,2020,32,1,Mali,ML,MLI,19658023,Africa,2.13653224\r
-29/05/2020,29,5,2020,78,2,Mali,ML,MLI,19658023,Africa,2.11109734\r
-28/05/2020,28,5,2020,39,0,Mali,ML,MLI,19658023,Africa,1.82113939\r
-27/05/2020,27,5,2020,18,3,Mali,ML,MLI,19658023,Africa,1.76518259\r
-26/05/2020,26,5,2020,29,2,Mali,ML,MLI,19658023,Africa,1.76518259\r
-25/05/2020,25,5,2020,15,2,Mali,ML,MLI,19658023,Africa,1.65835598\r
-24/05/2020,24,5,2020,46,1,Mali,ML,MLI,19658023,Africa,1.64309504\r
-23/05/2020,23,5,2020,22,2,Mali,ML,MLI,19658023,Africa,1.53118144\r
-22/05/2020,22,5,2020,16,5,Mali,ML,MLI,19658023,Africa,1.51083352\r
-21/05/2020,21,5,2020,30,2,Mali,ML,MLI,19658023,Africa,1.52609446\r
-20/05/2020,20,5,2020,27,1,Mali,ML,MLI,19658023,Africa,1.47013766\r
-19/05/2020,19,5,2020,14,0,Mali,ML,MLI,19658023,Africa,1.49557257\r
-18/05/2020,18,5,2020,25,4,Mali,ML,MLI,19658023,Africa,1.51083352\r
-17/05/2020,17,5,2020,29,2,Mali,ML,MLI,19658023,Africa,1.48031163\r
-16/05/2020,16,5,2020,27,0,Mali,ML,MLI,19658023,Africa,1.5159205\r
-15/05/2020,15,5,2020,21,2,Mali,ML,MLI,19658023,Africa,1.47013766\r
-14/05/2020,14,5,2020,28,4,Mali,ML,MLI,19658023,Africa,1.4040069\r
-13/05/2020,13,5,2020,18,1,Mali,ML,MLI,19658023,Africa,1.55661635\r
-12/05/2020,12,5,2020,8,1,Mali,ML,MLI,19658023,Africa,1.54644239\r
-11/05/2020,11,5,2020,12,1,Mali,ML,MLI,19658023,Africa,1.60239918\r
-10/05/2020,10,5,2020,24,2,Mali,ML,MLI,19658023,Africa,1.63800805\r
-09/05/2020,9,5,2020,18,3,Mali,ML,MLI,19658023,Africa,1.74483467\r
-08/05/2020,8,5,2020,19,0,Mali,ML,MLI,19658023,Africa,1.7346607\r
-07/05/2020,7,5,2020,19,0,Mali,ML,MLI,19658023,Africa,1.71939976\r
-06/05/2020,6,5,2020,32,3,Mali,ML,MLI,19658023,Africa,1.80079146\r
-05/05/2020,5,5,2020,17,2,Mali,ML,MLI,19658023,Africa,1.69905183\r
-04/05/2020,4,5,2020,19,1,Mali,ML,MLI,19658023,Africa,1.72448674\r
-03/05/2020,3,5,2020,36,0,Mali,ML,MLI,19658023,Africa,1.66852994\r
-02/05/2020,2,5,2020,18,0,Mali,ML,MLI,19658023,Africa,1.61766013\r
-01/05/2020,1,5,2020,8,1,Mali,ML,MLI,19658023,Africa,1.62274711\r
-30/04/2020,30,4,2020,58,1,Mali,ML,MLI,19658023,Africa,1.69905183\r
-29/04/2020,29,4,2020,16,1,Mali,ML,MLI,19658023,Africa,1.42435483\r
-28/04/2020,28,4,2020,19,0,Mali,ML,MLI,19658023,Africa,1.44978974\r
-27/04/2020,27,4,2020,19,2,Mali,ML,MLI,19658023,Africa,1.38874596\r
-26/04/2020,26,4,2020,45,0,Mali,ML,MLI,19658023,Africa,1.34805011\r
-25/04/2020,25,4,2020,16,0,Mali,ML,MLI,19658023,Africa,1.21070161\r
-24/04/2020,24,4,2020,16,4,Mali,ML,MLI,19658023,Africa,1.27174538\r
-23/04/2020,23,4,2020,35,3,Mali,ML,MLI,19658023,Africa,1.19035368\r
-22/04/2020,22,4,2020,12,0,Mali,ML,MLI,19658023,Africa,1.02757027\r
-21/04/2020,21,4,2020,22,0,Mali,ML,MLI,19658023,Africa,1.01230933\r
-20/04/2020,20,4,2020,8,1,Mali,ML,MLI,19658023,Africa,0.91056969\r
-19/04/2020,19,4,2020,26,0,Mali,ML,MLI,19658023,Africa,0.89022177\r
-18/04/2020,18,4,2020,19,0,Mali,ML,MLI,19658023,Africa,0.76813421\r
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-30/06/2020,30,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.31504249\r
-29/06/2020,29,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.31504249\r
-28/06/2020,28,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.31504249\r
-27/06/2020,27,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.31504249\r
-26/06/2020,26,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.31504249\r
-25/06/2020,25,6,2020,1,0,Mauritius,MU,MUS,1269670,Africa,0.31504249\r
-24/06/2020,24,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.23628187\r
-23/06/2020,23,6,2020,3,0,Mauritius,MU,MUS,1269670,Africa,0.23628187\r
-22/06/2020,22,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0\r
-21/06/2020,21,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0\r
-20/06/2020,20,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0\r
-19/06/2020,19,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.15752125\r
-18/06/2020,18,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.15752125\r
-17/06/2020,17,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.15752125\r
-16/06/2020,16,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.15752125\r
-15/06/2020,15,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.15752125\r
-14/06/2020,14,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.15752125\r
-13/06/2020,13,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.15752125\r
-12/06/2020,12,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.23628187\r
-11/06/2020,11,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.23628187\r
-10/06/2020,10,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.23628187\r
-09/06/2020,9,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.23628187\r
-08/06/2020,8,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.23628187\r
-07/06/2020,7,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.39380311\r
-06/06/2020,6,6,2020,2,0,Mauritius,MU,MUS,1269670,Africa,0.39380311\r
-05/06/2020,5,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.23628187\r
-04/06/2020,4,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.23628187\r
-03/06/2020,3,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.23628187\r
-02/06/2020,2,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.23628187\r
-01/06/2020,1,6,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.23628187\r
-31/05/2020,31,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.23628187\r
-30/05/2020,30,5,2020,1,0,Mauritius,MU,MUS,1269670,Africa,0.23628187\r
-29/05/2020,29,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.15752125\r
-28/05/2020,28,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.15752125\r
-27/05/2020,27,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.15752125\r
-26/05/2020,26,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.15752125\r
-25/05/2020,25,5,2020,2,0,Mauritius,MU,MUS,1269670,Africa,0.15752125\r
-24/05/2020,24,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0\r
-23/05/2020,23,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0\r
-22/05/2020,22,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0\r
-21/05/2020,21,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0\r
-20/05/2020,20,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0\r
-19/05/2020,19,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0\r
-18/05/2020,18,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0\r
-17/05/2020,17,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0\r
-16/05/2020,16,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0\r
-15/05/2020,15,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0\r
-14/05/2020,14,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0\r
-13/05/2020,13,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0\r
-12/05/2020,12,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0\r
-11/05/2020,11,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0\r
-10/05/2020,10,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.07876062\r
-09/05/2020,9,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.07876062\r
-08/05/2020,8,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.07876062\r
-07/05/2020,7,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.23628187\r
-06/05/2020,6,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.31504249\r
-05/05/2020,5,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.31504249\r
-04/05/2020,4,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.31504249\r
-03/05/2020,3,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.55132436\r
-02/05/2020,2,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.63008498\r
-01/05/2020,1,5,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.63008498\r
-30/04/2020,30,4,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.63008498\r
-29/04/2020,29,4,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.63008498\r
-28/04/2020,28,4,2020,0,1,Mauritius,MU,MUS,1269670,Africa,0.63008498\r
-27/04/2020,27,4,2020,1,0,Mauritius,MU,MUS,1269670,Africa,0.63008498\r
-26/04/2020,26,4,2020,0,0,Mauritius,MU,MUS,1269670,Africa,0.94512747\r
-25/04/2020,25,4,2020,0,0,Mauritius,MU,MUS,1269670,Africa,1.0238881\r
-24/04/2020,24,4,2020,2,0,Mauritius,MU,MUS,1269670,Africa,1.33893059\r
-23/04/2020,23,4,2020,1,0,Mauritius,MU,MUS,1269670,Africa,4.41059488\r
-22/04/2020,22,4,2020,0,0,Mauritius,MU,MUS,1269670,Africa,4.72563737\r
-21/04/2020,21,4,2020,0,0,Mauritius,MU,MUS,1269670,Africa,6.61589232\r
-20/04/2020,20,4,2020,3,0,Mauritius,MU,MUS,1269670,Africa,7.95482291\r
-19/04/2020,19,4,2020,1,0,Mauritius,MU,MUS,1269670,Africa,10.16012035\r
-18/04/2020,18,4,2020,0,0,Mauritius,MU,MUS,1269670,Africa,10.86896595\r
-17/04/2020,17,4,2020,0,0,Mauritius,MU,MUS,1269670,Africa,12.20789654\r
-16/04/2020,16,4,2020,0,0,Mauritius,MU,MUS,1269670,Africa,13.38930588\r
-15/04/2020,15,4,2020,0,0,Mauritius,MU,MUS,1269670,Africa,14.25567273\r
-14/04/2020,14,4,2020,0,0,Mauritius,MU,MUS,1269670,Africa,15.43708208\r
-13/04/2020,13,4,2020,5,0,Mauritius,MU,MUS,1269670,Africa,16.85477329\r
-12/04/2020,12,4,2020,1,0,Mauritius,MU,MUS,1269670,Africa,17.09105516\r
-11/04/2020,11,4,2020,4,2,Mauritius,MU,MUS,1269670,Africa,17.64237952\r
-10/04/2020,10,4,2020,41,0,Mauritius,MU,MUS,1269670,Africa,18.35122512\r
-09/04/2020,9,4,2020,5,0,Mauritius,MU,MUS,1269670,Africa,17.72114014\r
-08/04/2020,8,4,2020,24,0,Mauritius,MU,MUS,1269670,Africa,17.79990076\r
-07/04/2020,7,4,2020,17,0,Mauritius,MU,MUS,1269670,Africa,16.38220955\r
-06/04/2020,6,4,2020,31,0,Mauritius,MU,MUS,1269670,Africa,15.67336394\r
-05/04/2020,5,4,2020,10,0,Mauritius,MU,MUS,1269670,Africa,14.33443336\r
-04/04/2020,4,4,2020,17,0,Mauritius,MU,MUS,1269670,Africa,13.70434837\r
-03/04/2020,3,4,2020,15,2,Mauritius,MU,MUS,1269670,Africa,13.07426339\r
-02/04/2020,2,4,2020,11,2,Mauritius,MU,MUS,1269670,Africa,12.12913592\r
-01/04/2020,1,4,2020,15,0,Mauritius,MU,MUS,1269670,Africa,\r
-31/03/2020,31,3,2020,18,0,Mauritius,MU,MUS,1269670,Africa,\r
-30/03/2020,30,3,2020,8,1,Mauritius,MU,MUS,1269670,Africa,\r
-29/03/2020,29,3,2020,8,0,Mauritius,MU,MUS,1269670,Africa,\r
-28/03/2020,28,3,2020,13,0,Mauritius,MU,MUS,1269670,Africa,\r
-27/03/2020,27,3,2020,33,0,Mauritius,MU,MUS,1269670,Africa,\r
-26/03/2020,26,3,2020,6,0,Mauritius,MU,MUS,1269670,Africa,\r
-25/03/2020,25,3,2020,6,0,Mauritius,MU,MUS,1269670,Africa,\r
-24/03/2020,24,3,2020,8,0,Mauritius,MU,MUS,1269670,Africa,\r
-23/03/2020,23,3,2020,14,1,Mauritius,MU,MUS,1269670,Africa,\r
-22/03/2020,22,3,2020,2,1,Mauritius,MU,MUS,1269670,Africa,\r
-21/03/2020,21,3,2020,9,0,Mauritius,MU,MUS,1269670,Africa,\r
-20/03/2020,20,3,2020,3,0,Mauritius,MU,MUS,1269670,Africa,\r
-19/08/2020,19,8,2020,5506,751,Mexico,MX,MEX,127575529,America,63.70971035\r
-18/08/2020,18,8,2020,3571,266,Mexico,MX,MEX,127575529,America,64.21294165\r
-17/08/2020,17,8,2020,4448,214,Mexico,MX,MEX,127575529,America,65.15042552\r
-16/08/2020,16,8,2020,6345,635,Mexico,MX,MEX,127575529,America,65.46788452\r
-15/08/2020,15,8,2020,5618,615,Mexico,MX,MEX,127575529,America,67.9848249\r
-14/08/2020,14,8,2020,7371,627,Mexico,MX,MEX,127575529,America,70.21095715\r
-13/08/2020,13,8,2020,5858,737,Mexico,MX,MEX,127575529,America,70.49235908\r
-12/08/2020,12,8,2020,6686,926,Mexico,MX,MEX,127575529,America,70.40927104\r
-11/08/2020,11,8,2020,5558,705,Mexico,MX,MEX,127575529,America,70.81844042\r
-10/08/2020,10,8,2020,4376,292,Mexico,MX,MEX,127575529,America,70.35988853\r
-09/08/2020,9,8,2020,6495,695,Mexico,MX,MEX,127575529,America,71.22525825\r
-08/08/2020,8,8,2020,6717,794,Mexico,MX,MEX,127575529,America,71.4259237\r
-07/08/2020,7,8,2020,6590,819,Mexico,MX,MEX,127575529,America,72.09689877\r
-06/08/2020,6,8,2020,6139,829,Mexico,MX,MEX,127575529,America,73.54545244\r
-05/08/2020,5,8,2020,6148,857,Mexico,MX,MEX,127575529,America,73.45139051\r
-04/08/2020,4,8,2020,4767,266,Mexico,MX,MEX,127575529,America,74.00870742\r
-03/08/2020,3,8,2020,4853,274,Mexico,MX,MEX,127575529,America,74.32616642\r
-02/08/2020,2,8,2020,9556,784,Mexico,MX,MEX,127575529,America,74.68516944\r
-01/08/2020,1,8,2020,8458,688,Mexico,MX,MEX,127575529,America,73.16371778\r
-31/07/2020,31,7,2020,7730,639,Mexico,MX,MEX,127575529,America,72.22231467\r
-30/07/2020,30,7,2020,5752,485,Mexico,MX,MEX,127575529,America,71.18449809\r
-29/07/2020,29,7,2020,7208,854,Mexico,MX,MEX,127575529,America,71.49568629\r
-28/07/2020,28,7,2020,4973,342,Mexico,MX,MEX,127575529,America,71.37262194\r
-27/07/2020,27,7,2020,5480,306,Mexico,MX,MEX,127575529,America,71.14687332\r
-26/07/2020,26,7,2020,6751,729,Mexico,MX,MEX,127575529,America,70.36459163\r
-25/07/2020,25,7,2020,7573,737,Mexico,MX,MEX,127575529,America,69.84960258\r
-24/07/2020,24,7,2020,8438,718,Mexico,MX,MEX,127575529,America,69.3150173\r
-23/07/2020,23,7,2020,6019,790,Mexico,MX,MEX,127575529,America,68.40731971\r
-22/07/2020,22,7,2020,6859,915,Mexico,MX,MEX,127575529,America,69.17235671\r
-21/07/2020,21,7,2020,5172,301,Mexico,MX,MEX,127575529,America,68.70126323\r
-20/07/2020,20,7,2020,5311,296,Mexico,MX,MEX,127575529,America,68.4896239\r
-19/07/2020,19,7,2020,7615,578,Mexico,MX,MEX,127575529,America,67.99736649\r
-18/07/2020,18,7,2020,7257,736,Mexico,MX,MEX,127575529,America,67.44788807\r
-17/07/2020,17,7,2020,6406,668,Mexico,MX,MEX,127575529,America,67.04263793\r
-16/07/2020,16,7,2020,6149,579,Mexico,MX,MEX,127575529,America,67.30522748\r
-15/07/2020,15,7,2020,7051,878,Mexico,MX,MEX,127575529,America,66.93838597\r
-14/07/2020,14,7,2020,4685,443,Mexico,MX,MEX,127575529,America,65.66933381\r
-13/07/2020,13,7,2020,4482,276,Mexico,MX,MEX,127575529,America,64.97954635\r
-12/07/2020,12,7,2020,6094,539,Mexico,MX,MEX,127575529,America,64.64092342\r
-11/07/2020,11,7,2020,6891,665,Mexico,MX,MEX,127575529,America,63.32092105\r
-10/07/2020,10,7,2020,7280,730,Mexico,MX,MEX,127575529,America,62.18433944\r
-09/07/2020,9,7,2020,6995,782,Mexico,MX,MEX,127575529,America,61.26253257\r
-08/07/2020,8,7,2020,6258,895,Mexico,MX,MEX,127575529,America,60.04129522\r
-07/07/2020,7,7,2020,4902,480,Mexico,MX,MEX,127575529,America,60.06481071\r
-06/07/2020,6,7,2020,4683,273,Mexico,MX,MEX,127575529,America,59.81005965\r
-05/07/2020,5,7,2020,6914,523,Mexico,MX,MEX,127575529,America,60.32740025\r
-04/07/2020,4,7,2020,6740,654,Mexico,MX,MEX,127575529,America,58.60528315\r
-03/07/2020,3,7,2020,6741,679,Mexico,MX,MEX,127575529,America,57.2649007\r
-02/07/2020,2,7,2020,5681,741,Mexico,MX,MEX,127575529,America,56.41912721\r
-01/07/2020,1,7,2020,5432,648,Mexico,MX,MEX,127575529,America,55.83045633\r
-30/06/2020,30,6,2020,3805,473,Mexico,MX,MEX,127575529,America,55.17750979\r
-29/06/2020,29,6,2020,4050,267,Mexico,MX,MEX,127575529,America,54.88121472\r
-28/06/2020,28,6,2020,4410,602,Mexico,MX,MEX,127575529,America,54.95724811\r
-27/06/2020,27,6,2020,5441,719,Mexico,MX,MEX,127575529,America,54.23924207\r
-26/06/2020,26,6,2020,6104,718,Mexico,MX,MEX,127575529,America,54.06757906\r
-25/06/2020,25,6,2020,5437,965,Mexico,MX,MEX,127575529,America,53.03760096\r
-24/06/2020,24,6,2020,6288,793,Mexico,MX,MEX,127575529,America,52.60334841\r
-23/06/2020,23,6,2020,4577,759,Mexico,MX,MEX,127575529,America,50.96588704\r
-22/06/2020,22,6,2020,5343,1044,Mexico,MX,MEX,127575529,America,49.72897271\r
-21/06/2020,21,6,2020,4717,387,Mexico,MX,MEX,127575529,America,48.2717967\r
-20/06/2020,20,6,2020,5030,647,Mexico,MX,MEX,127575529,America,47.39074999\r
-19/06/2020,19,6,2020,5662,667,Mexico,MX,MEX,127575529,America,46.85459701\r
-18/06/2020,18,6,2020,4930,770,Mexico,MX,MEX,127575529,America,45.89830076\r
-17/06/2020,17,6,2020,4599,730,Mexico,MX,MEX,127575529,America,45.10034209\r
-16/06/2020,16,6,2020,3427,439,Mexico,MX,MEX,127575529,America,44.54537672\r
-15/06/2020,15,6,2020,4147,269,Mexico,MX,MEX,127575529,America,44.03117153\r
-14/06/2020,14,6,2020,3494,424,Mexico,MX,MEX,127575529,America,43.25124139\r
-13/06/2020,13,6,2020,5222,504,Mexico,MX,MEX,127575529,America,42.77387711\r
-12/06/2020,12,6,2020,4790,587,Mexico,MX,MEX,127575529,America,41.21009759\r
-11/06/2020,11,6,2020,4883,708,Mexico,MX,MEX,127575529,America,40.10251841\r
-10/06/2020,10,6,2020,4199,596,Mexico,MX,MEX,127575529,America,38.98945228\r
-09/06/2020,9,6,2020,2999,354,Mexico,MX,MEX,127575529,America,38.40626834\r
-08/06/2020,8,6,2020,3484,188,Mexico,MX,MEX,127575529,America,38.00336975\r
-07/06/2020,7,6,2020,3593,341,Mexico,MX,MEX,127575529,America,37.4389982\r
-06/06/2020,6,6,2020,4346,625,Mexico,MX,MEX,127575529,America,37.23206196\r
-05/06/2020,5,6,2020,4442,817,Mexico,MX,MEX,127575529,America,36.14564671\r
-04/06/2020,4,6,2020,3912,1091,Mexico,MX,MEX,127575529,America,34.99417196\r
-03/06/2020,3,6,2020,3891,470,Mexico,MX,MEX,127575529,America,33.68984658\r
-02/06/2020,2,6,2020,2771,237,Mexico,MX,MEX,127575529,America,32.76647201\r
-01/06/2020,1,6,2020,3152,151,Mexico,MX,MEX,127575529,America,32.48663778\r
-31/05/2020,31,5,2020,2885,364,Mexico,MX,MEX,127575529,America,31.64243199\r
-30/05/2020,30,5,2020,3227,371,Mexico,MX,MEX,127575529,America,31.03651642\r
-29/05/2020,29,5,2020,3377,447,Mexico,MX,MEX,127575529,America,30.4172754\r
-28/05/2020,28,5,2020,3463,463,Mexico,MX,MEX,127575529,America,29.6585092\r
-27/05/2020,27,5,2020,3455,501,Mexico,MX,MEX,127575529,America,28.40356633\r
-26/05/2020,26,5,2020,2485,239,Mexico,MX,MEX,127575529,America,27.26071393\r
-25/05/2020,25,5,2020,2764,215,Mexico,MX,MEX,127575529,America,26.33577165\r
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-30/04/2020,30,4,2020,0,0,Monaco,MC,MCO,33085,Europe,6.04503551\r
-29/04/2020,29,4,2020,0,0,Monaco,MC,MCO,33085,Europe,6.04503551\r
-28/04/2020,28,4,2020,1,0,Monaco,MC,MCO,33085,Europe,6.04503551\r
-27/04/2020,27,4,2020,0,0,Monaco,MC,MCO,33085,Europe,3.02251776\r
-26/04/2020,26,4,2020,0,0,Monaco,MC,MCO,33085,Europe,6.04503551\r
-25/04/2020,25,4,2020,0,0,Monaco,MC,MCO,33085,Europe,12.09007103\r
-24/04/2020,24,4,2020,0,1,Monaco,MC,MCO,33085,Europe,30.22517757\r
-23/04/2020,23,4,2020,0,0,Monaco,MC,MCO,33085,Europe,39.29273084\r
-22/04/2020,22,4,2020,0,0,Monaco,MC,MCO,33085,Europe,45.33776636\r
-21/04/2020,21,4,2020,0,0,Monaco,MC,MCO,33085,Europe,51.38280187\r
-20/04/2020,20,4,2020,0,0,Monaco,MC,MCO,33085,Europe,63.4728729\r
-19/04/2020,19,4,2020,0,0,Monaco,MC,MCO,33085,Europe,84.6304972\r
-18/04/2020,18,4,2020,1,0,Monaco,MC,MCO,33085,Europe,90.67553272\r
-17/04/2020,17,4,2020,0,0,Monaco,MC,MCO,33085,Europe,99.74308599\r
-16/04/2020,16,4,2020,0,1,Monaco,MC,MCO,33085,Europe,114.85567478\r
-15/04/2020,15,4,2020,0,0,Monaco,MC,MCO,33085,Europe,123.92322805\r
-14/04/2020,14,4,2020,0,0,Monaco,MC,MCO,33085,Europe,132.99078132\r
-13/04/2020,13,4,2020,1,0,Monaco,MC,MCO,33085,Europe,142.05833459\r
-12/04/2020,12,4,2020,2,0,Monaco,MC,MCO,33085,Europe,148.10337011\r
-11/04/2020,11,4,2020,6,0,Monaco,MC,MCO,33085,Europe,145.08085235\r
-10/04/2020,10,4,2020,3,0,Monaco,MC,MCO,33085,Europe,154.14840562\r
-09/04/2020,9,4,2020,2,0,Monaco,MC,MCO,33085,Europe,151.12588786\r
-08/04/2020,8,4,2020,2,0,Monaco,MC,MCO,33085,Europe,157.17092338\r
-07/04/2020,7,4,2020,4,0,Monaco,MC,MCO,33085,Europe,163.21595889\r
-06/04/2020,6,4,2020,7,0,Monaco,MC,MCO,33085,Europe,151.12588786\r
-05/04/2020,5,4,2020,2,2,Monaco,MC,MCO,33085,Europe,145.08085235\r
-04/04/2020,4,4,2020,4,0,Monaco,MC,MCO,33085,Europe,157.17092338\r
-03/04/2020,3,4,2020,5,0,Monaco,MC,MCO,33085,Europe,148.10337011\r
-02/04/2020,2,4,2020,3,0,Monaco,MC,MCO,33085,Europe,139.03581684\r
-01/04/2020,1,4,2020,3,0,Monaco,MC,MCO,33085,Europe,129.96826356\r
-31/03/2020,31,3,2020,3,0,Monaco,MC,MCO,33085,Europe,120.90071029\r
-30/03/2020,30,3,2020,3,0,Monaco,MC,MCO,33085,Europe,117.87819253\r
-29/03/2020,29,3,2020,1,0,Monaco,MC,MCO,33085,Europe,120.90071029\r
-28/03/2020,28,3,2020,9,0,Monaco,MC,MCO,33085,Europe,123.92322805\r
-27/03/2020,27,3,2020,2,0,Monaco,MC,MCO,33085,Europe,96.72056823\r
-26/03/2020,26,3,2020,4,0,Monaco,MC,MCO,33085,Europe,90.67553272\r
-25/03/2020,25,3,2020,4,0,Monaco,MC,MCO,33085,Europe,81.60797945\r
-24/03/2020,24,3,2020,0,0,Monaco,MC,MCO,33085,Europe,69.51790842\r
-23/03/2020,23,3,2020,5,0,Monaco,MC,MCO,33085,Europe,69.51790842\r
-22/03/2020,22,3,2020,6,0,Monaco,MC,MCO,33085,Europe,54.40531963\r
-21/03/2020,21,3,2020,1,0,Monaco,MC,MCO,33085,Europe,36.27021309\r
-20/03/2020,20,3,2020,2,0,Monaco,MC,MCO,33085,Europe,33.24769533\r
-19/03/2020,19,3,2020,0,0,Monaco,MC,MCO,33085,Europe,27.20265982\r
-18/03/2020,18,3,2020,0,0,Monaco,MC,MCO,33085,Europe,27.20265982\r
-17/03/2020,17,3,2020,2,0,Monaco,MC,MCO,33085,Europe,27.20265982\r
-16/03/2020,16,3,2020,4,0,Monaco,MC,MCO,33085,Europe,21.1576243\r
-15/03/2020,15,3,2020,2,0,Monaco,MC,MCO,33085,Europe,9.06755327\r
-02/03/2020,2,3,2020,0,0,Monaco,MC,MCO,33085,Europe,3.02251776\r
-01/03/2020,1,3,2020,0,0,Monaco,MC,MCO,33085,Europe,3.02251776\r
-29/02/2020,29,2,2020,1,0,Monaco,MC,MCO,33085,Europe,3.02251776\r
-28/02/2020,28,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-27/02/2020,27,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-26/02/2020,26,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-25/02/2020,25,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-24/02/2020,24,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-23/02/2020,23,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-22/02/2020,22,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-21/02/2020,21,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-20/02/2020,20,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-19/02/2020,19,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-18/02/2020,18,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-17/02/2020,17,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-16/02/2020,16,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-15/02/2020,15,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-14/02/2020,14,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-13/02/2020,13,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-12/02/2020,12,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-11/02/2020,11,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-10/02/2020,10,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-09/02/2020,9,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-08/02/2020,8,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-07/02/2020,7,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-06/02/2020,6,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-05/02/2020,5,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-04/02/2020,4,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-03/02/2020,3,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-02/02/2020,2,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-01/02/2020,1,2,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-31/01/2020,31,1,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-30/01/2020,30,1,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-29/01/2020,29,1,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-28/01/2020,28,1,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-27/01/2020,27,1,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-26/01/2020,26,1,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-25/01/2020,25,1,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-24/01/2020,24,1,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-23/01/2020,23,1,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-22/01/2020,22,1,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-21/01/2020,21,1,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-20/01/2020,20,1,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-19/01/2020,19,1,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-18/01/2020,18,1,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-17/01/2020,17,1,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-16/01/2020,16,1,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-15/01/2020,15,1,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-14/01/2020,14,1,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-13/01/2020,13,1,2020,0,0,Monaco,MC,MCO,33085,Europe,0\r
-12/01/2020,12,1,2020,0,0,Monaco,MC,MCO,33085,Europe,\r
-11/01/2020,11,1,2020,0,0,Monaco,MC,MCO,33085,Europe,\r
-10/01/2020,10,1,2020,0,0,Monaco,MC,MCO,33085,Europe,\r
-09/01/2020,9,1,2020,0,0,Monaco,MC,MCO,33085,Europe,\r
-08/01/2020,8,1,2020,0,0,Monaco,MC,MCO,33085,Europe,\r
-07/01/2020,7,1,2020,0,0,Monaco,MC,MCO,33085,Europe,\r
-06/01/2020,6,1,2020,0,0,Monaco,MC,MCO,33085,Europe,\r
-05/01/2020,5,1,2020,0,0,Monaco,MC,MCO,33085,Europe,\r
-04/01/2020,4,1,2020,0,0,Monaco,MC,MCO,33085,Europe,\r
-03/01/2020,3,1,2020,0,0,Monaco,MC,MCO,33085,Europe,\r
-02/01/2020,2,1,2020,0,0,Monaco,MC,MCO,33085,Europe,\r
-01/01/2020,1,1,2020,0,0,Monaco,MC,MCO,33085,Europe,\r
-31/12/2019,31,12,2019,0,0,Monaco,MC,MCO,33085,Europe,\r
-19/08/2020,19,8,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.15503078\r
-18/08/2020,18,8,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.15503078\r
-17/08/2020,17,8,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.15503078\r
-16/08/2020,16,8,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.15503078\r
-15/08/2020,15,8,2020,1,0,Mongolia,MN,MNG,3225166,Asia,0.21704309\r
-14/08/2020,14,8,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.18603694\r
-13/08/2020,13,8,2020,4,0,Mongolia,MN,MNG,3225166,Asia,0.18603694\r
-12/08/2020,12,8,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.06201231\r
-11/08/2020,11,8,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.12402462\r
-10/08/2020,10,8,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.15503078\r
-09/08/2020,9,8,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.15503078\r
-08/08/2020,8,8,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.15503078\r
-07/08/2020,7,8,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.15503078\r
-06/08/2020,6,8,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.18603694\r
-05/08/2020,5,8,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.18603694\r
-04/08/2020,4,8,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.18603694\r
-03/08/2020,3,8,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.18603694\r
-02/08/2020,2,8,2020,2,0,Mongolia,MN,MNG,3225166,Asia,0.18603694\r
-01/08/2020,1,8,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.12402462\r
-31/07/2020,31,7,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.89917852\r
-30/07/2020,30,7,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.93018468\r
-29/07/2020,29,7,2020,2,0,Mongolia,MN,MNG,3225166,Asia,0.93018468\r
-28/07/2020,28,7,2020,1,0,Mongolia,MN,MNG,3225166,Asia,1.42628317\r
-27/07/2020,27,7,2020,0,0,Mongolia,MN,MNG,3225166,Asia,1.79835705\r
-26/07/2020,26,7,2020,0,0,Mongolia,MN,MNG,3225166,Asia,1.79835705\r
-25/07/2020,25,7,2020,0,0,Mongolia,MN,MNG,3225166,Asia,1.89137551\r
-24/07/2020,24,7,2020,1,0,Mongolia,MN,MNG,3225166,Asia,1.89137551\r
-23/07/2020,23,7,2020,0,0,Mongolia,MN,MNG,3225166,Asia,1.86036936\r
-22/07/2020,22,7,2020,0,0,Mongolia,MN,MNG,3225166,Asia,2.07741245\r
-21/07/2020,21,7,2020,0,0,Mongolia,MN,MNG,3225166,Asia,2.07741245\r
-20/07/2020,20,7,2020,0,0,Mongolia,MN,MNG,3225166,Asia,2.07741245\r
-19/07/2020,19,7,2020,0,0,Mongolia,MN,MNG,3225166,Asia,2.07741245\r
-18/07/2020,18,7,2020,25,0,Mongolia,MN,MNG,3225166,Asia,2.07741245\r
-17/07/2020,17,7,2020,1,0,Mongolia,MN,MNG,3225166,Asia,1.30225855\r
-16/07/2020,16,7,2020,0,0,Mongolia,MN,MNG,3225166,Asia,1.27125239\r
-15/07/2020,15,7,2020,18,0,Mongolia,MN,MNG,3225166,Asia,1.27125239\r
-14/07/2020,14,7,2020,13,0,Mongolia,MN,MNG,3225166,Asia,0.71314159\r
-13/07/2020,13,7,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.31006156\r
-12/07/2020,12,7,2020,3,0,Mongolia,MN,MNG,3225166,Asia,0.34106772\r
-11/07/2020,11,7,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.24804925\r
-10/07/2020,10,7,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.24804925\r
-09/07/2020,9,7,2020,7,0,Mongolia,MN,MNG,3225166,Asia,0.34106772\r
-08/07/2020,8,7,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.15503078\r
-07/07/2020,7,7,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.15503078\r
-06/07/2020,6,7,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.21704309\r
-05/07/2020,5,7,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.43408618\r
-04/07/2020,4,7,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.4960985\r
-03/07/2020,3,7,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.4960985\r
-02/07/2020,2,7,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.58911696\r
-01/07/2020,1,7,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.71314159\r
-30/06/2020,30,6,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.71314159\r
-29/06/2020,29,6,2020,1,0,Mongolia,MN,MNG,3225166,Asia,0.71314159\r
-28/06/2020,28,6,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.68213543\r
-27/06/2020,27,6,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.68213543\r
-26/06/2020,26,6,2020,3,0,Mongolia,MN,MNG,3225166,Asia,0.68213543\r
-25/06/2020,25,6,2020,1,0,Mongolia,MN,MNG,3225166,Asia,0.68213543\r
-24/06/2020,24,6,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.65112928\r
-23/06/2020,23,6,2020,2,0,Mongolia,MN,MNG,3225166,Asia,0.65112928\r
-22/06/2020,22,6,2020,7,0,Mongolia,MN,MNG,3225166,Asia,0.58911696\r
-21/06/2020,21,6,2020,2,0,Mongolia,MN,MNG,3225166,Asia,0.40308003\r
-20/06/2020,20,6,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.40308003\r
-19/06/2020,19,6,2020,3,0,Mongolia,MN,MNG,3225166,Asia,0.40308003\r
-18/06/2020,18,6,2020,4,0,Mongolia,MN,MNG,3225166,Asia,0.46509234\r
-17/06/2020,17,6,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.37207387\r
-16/06/2020,16,6,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.37207387\r
-15/06/2020,15,6,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.37207387\r
-14/06/2020,14,6,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.55811081\r
-13/06/2020,13,6,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.55811081\r
-12/06/2020,12,6,2020,3,0,Mongolia,MN,MNG,3225166,Asia,0.55811081\r
-11/06/2020,11,6,2020,0,0,Mongolia,MN,MNG,3225166,Asia,1.02320315\r
-10/06/2020,10,6,2020,0,0,Mongolia,MN,MNG,3225166,Asia,1.42628317\r
-09/06/2020,9,6,2020,0,0,Mongolia,MN,MNG,3225166,Asia,1.64332627\r
-08/06/2020,8,6,2020,1,0,Mongolia,MN,MNG,3225166,Asia,1.64332627\r
-07/06/2020,7,6,2020,2,0,Mongolia,MN,MNG,3225166,Asia,1.61232011\r
-06/06/2020,6,6,2020,0,0,Mongolia,MN,MNG,3225166,Asia,1.5503078\r
-05/06/2020,5,6,2020,5,0,Mongolia,MN,MNG,3225166,Asia,1.5503078\r
-04/06/2020,4,6,2020,1,0,Mongolia,MN,MNG,3225166,Asia,1.42628317\r
-03/06/2020,3,6,2020,0,0,Mongolia,MN,MNG,3225166,Asia,1.39527702\r
-02/06/2020,2,6,2020,0,0,Mongolia,MN,MNG,3225166,Asia,1.39527702\r
-01/06/2020,1,6,2020,6,0,Mongolia,MN,MNG,3225166,Asia,1.39527702\r
-31/05/2020,31,5,2020,0,0,Mongolia,MN,MNG,3225166,Asia,1.33326471\r
-30/05/2020,30,5,2020,0,0,Mongolia,MN,MNG,3225166,Asia,1.36427086\r
-29/05/2020,29,5,2020,18,0,Mongolia,MN,MNG,3225166,Asia,3.6587264\r
-28/05/2020,28,5,2020,13,0,Mongolia,MN,MNG,3225166,Asia,3.1006156\r
-27/05/2020,27,5,2020,7,0,Mongolia,MN,MNG,3225166,Asia,3.28665253\r
-26/05/2020,26,5,2020,0,0,Mongolia,MN,MNG,3225166,Asia,3.06960944\r
-25/05/2020,25,5,2020,0,0,Mongolia,MN,MNG,3225166,Asia,3.06960944\r
-24/05/2020,24,5,2020,0,0,Mongolia,MN,MNG,3225166,Asia,3.06960944\r
-23/05/2020,23,5,2020,0,0,Mongolia,MN,MNG,3225166,Asia,3.06960944\r
-22/05/2020,22,5,2020,1,0,Mongolia,MN,MNG,3225166,Asia,3.06960944\r
-21/05/2020,21,5,2020,0,0,Mongolia,MN,MNG,3225166,Asia,3.06960944\r
-20/05/2020,20,5,2020,0,0,Mongolia,MN,MNG,3225166,Asia,3.06960944\r
-19/05/2020,19,5,2020,0,0,Mongolia,MN,MNG,3225166,Asia,3.06960944\r
-18/05/2020,18,5,2020,4,0,Mongolia,MN,MNG,3225166,Asia,3.1006156\r
-17/05/2020,17,5,2020,1,0,Mongolia,MN,MNG,3225166,Asia,3.00759713\r
-16/05/2020,16,5,2020,74,0,Mongolia,MN,MNG,3225166,Asia,2.97659097\r
-15/05/2020,15,5,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.71314159\r
-14/05/2020,14,5,2020,19,0,Mongolia,MN,MNG,3225166,Asia,0.71314159\r
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-12/05/2020,12,5,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.12402462\r
-11/05/2020,11,5,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.12402462\r
-10/05/2020,10,5,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.12402462\r
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-06/05/2020,6,5,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.18603694\r
-05/05/2020,5,5,2020,1,0,Mongolia,MN,MNG,3225166,Asia,0.21704309\r
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-02/05/2020,2,5,2020,1,0,Mongolia,MN,MNG,3225166,Asia,0.24804925\r
-01/05/2020,1,5,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.21704309\r
-30/04/2020,30,4,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.24804925\r
-29/04/2020,29,4,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.24804925\r
-28/04/2020,28,4,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.68213543\r
-27/04/2020,27,4,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.68213543\r
-26/04/2020,26,4,2020,2,0,Mongolia,MN,MNG,3225166,Asia,0.68213543\r
-25/04/2020,25,4,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.62012312\r
-24/04/2020,24,4,2020,1,0,Mongolia,MN,MNG,3225166,Asia,0.62012312\r
-23/04/2020,23,4,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.58911696\r
-22/04/2020,22,4,2020,1,0,Mongolia,MN,MNG,3225166,Asia,0.62012312\r
-21/04/2020,21,4,2020,2,0,Mongolia,MN,MNG,3225166,Asia,0.58911696\r
-20/04/2020,20,4,2020,1,0,Mongolia,MN,MNG,3225166,Asia,0.55811081\r
-19/04/2020,19,4,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.52710465\r
-18/04/2020,18,4,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.52710465\r
-17/04/2020,17,4,2020,1,0,Mongolia,MN,MNG,3225166,Asia,0.52710465\r
-16/04/2020,16,4,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.4960985\r
-15/04/2020,15,4,2020,14,0,Mongolia,MN,MNG,3225166,Asia,0.55811081\r
-14/04/2020,14,4,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.12402462\r
-13/04/2020,13,4,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.12402462\r
-12/04/2020,12,4,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.12402462\r
-11/04/2020,11,4,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.15503078\r
-10/04/2020,10,4,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.15503078\r
-09/04/2020,9,4,2020,1,0,Mongolia,MN,MNG,3225166,Asia,0.18603694\r
-08/04/2020,8,4,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.15503078\r
-07/04/2020,7,4,2020,1,0,Mongolia,MN,MNG,3225166,Asia,0.15503078\r
-06/04/2020,6,4,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.12402462\r
-05/04/2020,5,4,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.12402462\r
-04/04/2020,4,4,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.24804925\r
-03/04/2020,3,4,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.2790554\r
-02/04/2020,2,4,2020,2,0,Mongolia,MN,MNG,3225166,Asia,0.2790554\r
-01/04/2020,1,4,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.24804925\r
-31/03/2020,31,3,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.34106772\r
-30/03/2020,30,3,2020,0,0,Mongolia,MN,MNG,3225166,Asia,0.34106772\r
-29/03/2020,29,3,2020,1,0,Mongolia,MN,MNG,3225166,Asia,0.37207387\r
-28/03/2020,28,3,2020,0,0,Mongolia,MN,MNG,3225166,Asia,\r
-27/03/2020,27,3,2020,1,0,Mongolia,MN,MNG,3225166,Asia,\r
-26/03/2020,26,3,2020,0,0,Mongolia,MN,MNG,3225166,Asia,\r
-25/03/2020,25,3,2020,0,0,Mongolia,MN,MNG,3225166,Asia,\r
-24/03/2020,24,3,2020,0,0,Mongolia,MN,MNG,3225166,Asia,\r
-23/03/2020,23,3,2020,0,0,Mongolia,MN,MNG,3225166,Asia,\r
-22/03/2020,22,3,2020,4,0,Mongolia,MN,MNG,3225166,Asia,\r
-21/03/2020,21,3,2020,1,0,Mongolia,MN,MNG,3225166,Asia,\r
-20/03/2020,20,3,2020,0,0,Mongolia,MN,MNG,3225166,Asia,\r
-19/03/2020,19,3,2020,1,0,Mongolia,MN,MNG,3225166,Asia,\r
-18/03/2020,18,3,2020,3,0,Mongolia,MN,MNG,3225166,Asia,\r
-15/03/2020,15,3,2020,0,0,Mongolia,MN,MNG,3225166,Asia,\r
-10/03/2020,10,3,2020,1,0,Mongolia,MN,MNG,3225166,Asia,\r
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-18/08/2020,18,8,2020,50,3,Montenegro,ME,MNE,622182,Europe,126.00814553\r
-17/08/2020,17,8,2020,75,2,Montenegro,ME,MNE,622182,Europe,124.8830728\r
-16/08/2020,16,8,2020,30,2,Montenegro,ME,MNE,622182,Europe,122.47220267\r
-15/08/2020,15,8,2020,73,0,Montenegro,ME,MNE,622182,Europe,131.47278449\r
-14/08/2020,14,8,2020,44,0,Montenegro,ME,MNE,622182,Europe,126.00814553\r
-13/08/2020,13,8,2020,65,2,Montenegro,ME,MNE,622182,Europe,128.09756631\r
-12/08/2020,12,8,2020,52,3,Montenegro,ME,MNE,622182,Europe,128.41901566\r
-11/08/2020,11,8,2020,78,4,Montenegro,ME,MNE,622182,Europe,129.06191436\r
-10/08/2020,10,8,2020,30,2,Montenegro,ME,MNE,622182,Europe,168.60018451\r
-09/08/2020,9,8,2020,39,1,Montenegro,ME,MNE,622182,Europe,163.77844425\r
-08/08/2020,8,8,2020,69,1,Montenegro,ME,MNE,622182,Europe,157.51018191\r
-07/08/2020,7,8,2020,69,3,Montenegro,ME,MNE,622182,Europe,195.92337933\r
-06/08/2020,6,8,2020,50,4,Montenegro,ME,MNE,622182,Europe,236.90817156\r
-05/08/2020,5,8,2020,60,1,Montenegro,ME,MNE,622182,Europe,231.60425728\r
-04/08/2020,4,8,2020,43,1,Montenegro,ME,MNE,622182,Europe,231.4435326\r
-03/08/2020,3,8,2020,60,1,Montenegro,ME,MNE,622182,Europe,238.99759234\r
-02/08/2020,2,8,2020,86,1,Montenegro,ME,MNE,622182,Europe,246.55165209\r
-01/08/2020,1,8,2020,39,1,Montenegro,ME,MNE,622182,Europe,240.12266507\r
-31/07/2020,31,7,2020,57,1,Montenegro,ME,MNE,622182,Europe,233.85440273\r
-30/07/2020,30,7,2020,67,2,Montenegro,ME,MNE,622182,Europe,230.47918455\r
-29/07/2020,29,7,2020,56,2,Montenegro,ME,MNE,622182,Europe,229.35411182\r
-28/07/2020,28,7,2020,324,3,Montenegro,ME,MNE,622182,Europe,231.4435326\r
-27/07/2020,27,7,2020,0,0,Montenegro,ME,MNE,622182,Europe,216.65686246\r
-26/07/2020,26,7,2020,0,0,Montenegro,ME,MNE,622182,Europe,225.81816896\r
-25/07/2020,25,7,2020,308,1,Montenegro,ME,MNE,622182,Europe,239.80121572\r
-24/07/2020,24,7,2020,324,4,Montenegro,ME,MNE,622182,Europe,199.62004687\r
-23/07/2020,23,7,2020,17,0,Montenegro,ME,MNE,622182,Europe,157.02800788\r
-22/07/2020,22,7,2020,59,3,Montenegro,ME,MNE,622182,Europe,162.8140962\r
-21/07/2020,21,7,2020,90,2,Montenegro,ME,MNE,622182,Europe,163.93916892\r
-20/07/2020,20,7,2020,107,2,Montenegro,ME,MNE,622182,Europe,159.11742866\r
-19/07/2020,19,7,2020,46,2,Montenegro,ME,MNE,622182,Europe,151.72409359\r
-18/07/2020,18,7,2020,0,0,Montenegro,ME,MNE,622182,Europe,153.49206502\r
-17/07/2020,17,7,2020,36,1,Montenegro,ME,MNE,622182,Europe,161.04612477\r
-16/07/2020,16,7,2020,60,0,Montenegro,ME,MNE,622182,Europe,161.68902347\r
-15/07/2020,15,7,2020,69,1,Montenegro,ME,MNE,622182,Europe,156.54583386\r
-14/07/2020,14,7,2020,232,1,Montenegro,ME,MNE,622182,Europe,153.009891\r
-13/07/2020,13,7,2020,57,0,Montenegro,ME,MNE,622182,Europe,118.93625981\r
-12/07/2020,12,7,2020,87,4,Montenegro,ME,MNE,622182,Europe,111.70364941\r
-11/07/2020,11,7,2020,58,0,Montenegro,ME,MNE,622182,Europe,102.54234292\r
-10/07/2020,10,7,2020,59,2,Montenegro,ME,MNE,622182,Europe,97.23842863\r
-09/07/2020,9,7,2020,53,0,Montenegro,ME,MNE,622182,Europe,91.77378966\r
-08/07/2020,8,7,2020,66,3,Montenegro,ME,MNE,622182,Europe,85.0233533\r
-07/07/2020,7,7,2020,60,0,Montenegro,ME,MNE,622182,Europe,76.18349615\r
-06/07/2020,6,7,2020,61,0,Montenegro,ME,MNE,622182,Europe,67.343639\r
-05/07/2020,5,7,2020,57,1,Montenegro,ME,MNE,622182,Europe,58.02160783\r
-04/07/2020,4,7,2020,47,0,Montenegro,ME,MNE,622182,Europe,49.50320003\r
-03/07/2020,3,7,2020,40,1,Montenegro,ME,MNE,622182,Europe,44.84218444\r
-02/07/2020,2,7,2020,28,0,Montenegro,ME,MNE,622182,Europe,39.05609613\r
-01/07/2020,1,7,2020,47,1,Montenegro,ME,MNE,622182,Europe,35.68087794\r
-30/06/2020,30,6,2020,20,0,Montenegro,ME,MNE,622182,Europe,28.1268182\r
-29/06/2020,29,6,2020,12,2,Montenegro,ME,MNE,622182,Europe,25.07304936\r
-28/06/2020,28,6,2020,30,0,Montenegro,ME,MNE,622182,Europe,23.30507794\r
-27/06/2020,27,6,2020,25,0,Montenegro,ME,MNE,622182,Europe,18.48333767\r
-26/06/2020,26,6,2020,25,0,Montenegro,ME,MNE,622182,Europe,14.46522079\r
-25/06/2020,25,6,2020,11,0,Montenegro,ME,MNE,622182,Europe,10.4471039\r
-24/06/2020,24,6,2020,11,0,Montenegro,ME,MNE,622182,Europe,8.67913247\r
-23/06/2020,23,6,2020,5,0,Montenegro,ME,MNE,622182,Europe,6.91116104\r
-22/06/2020,22,6,2020,3,0,Montenegro,ME,MNE,622182,Europe,6.10753767\r
-21/06/2020,21,6,2020,4,0,Montenegro,ME,MNE,622182,Europe,5.62536364\r
-20/06/2020,20,6,2020,18,0,Montenegro,ME,MNE,622182,Europe,4.98246494\r
-19/06/2020,19,6,2020,4,0,Montenegro,ME,MNE,622182,Europe,2.08942078\r
-18/06/2020,18,6,2020,7,0,Montenegro,ME,MNE,622182,Europe,1.44652208\r
-17/06/2020,17,6,2020,0,0,Montenegro,ME,MNE,622182,Europe,0.32144935\r
-16/06/2020,16,6,2020,1,0,Montenegro,ME,MNE,622182,Europe,0.32144935\r
-15/06/2020,15,6,2020,1,0,Montenegro,ME,MNE,622182,Europe,0.16072468\r
-14/06/2020,14,6,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-13/06/2020,13,6,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-12/06/2020,12,6,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-11/06/2020,11,6,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-10/06/2020,10,6,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-09/06/2020,9,6,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-08/06/2020,8,6,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-07/06/2020,7,6,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-06/06/2020,6,6,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-05/06/2020,5,6,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-04/06/2020,4,6,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-03/06/2020,3,6,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-02/06/2020,2,6,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-01/06/2020,1,6,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-31/05/2020,31,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-30/05/2020,30,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-29/05/2020,29,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-28/05/2020,28,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-27/05/2020,27,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-26/05/2020,26,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-25/05/2020,25,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-24/05/2020,24,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-23/05/2020,23,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-22/05/2020,22,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-21/05/2020,21,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-20/05/2020,20,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,0\r
-19/05/2020,19,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,0.16072468\r
-18/05/2020,18,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,0.32144935\r
-17/05/2020,17,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,0.32144935\r
-16/05/2020,16,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,0.32144935\r
-15/05/2020,15,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,0.32144935\r
-14/05/2020,14,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,0.32144935\r
-13/05/2020,13,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,0.48217403\r
-12/05/2020,12,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,0.48217403\r
-11/05/2020,11,5,2020,0,1,Montenegro,ME,MNE,622182,Europe,0.48217403\r
-10/05/2020,10,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,0.6428987\r
-09/05/2020,9,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,0.80362338\r
-08/05/2020,8,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,0.80362338\r
-07/05/2020,7,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,1.44652208\r
-06/05/2020,6,5,2020,1,0,Montenegro,ME,MNE,622182,Europe,1.76797143\r
-05/05/2020,5,5,2020,1,0,Montenegro,ME,MNE,622182,Europe,1.76797143\r
-04/05/2020,4,5,2020,0,1,Montenegro,ME,MNE,622182,Europe,2.25014546\r
-03/05/2020,3,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,2.41087013\r
-02/05/2020,2,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,3.05376883\r
-01/05/2020,1,5,2020,0,0,Montenegro,ME,MNE,622182,Europe,3.05376883\r
-30/04/2020,30,4,2020,1,0,Montenegro,ME,MNE,622182,Europe,5.46463896\r
-29/04/2020,29,4,2020,0,0,Montenegro,ME,MNE,622182,Europe,6.10753767\r
-28/04/2020,28,4,2020,0,0,Montenegro,ME,MNE,622182,Europe,7.55405974\r
-27/04/2020,27,4,2020,1,1,Montenegro,ME,MNE,622182,Europe,7.8755091\r
-26/04/2020,26,4,2020,1,0,Montenegro,ME,MNE,622182,Europe,9.1613065\r
-25/04/2020,25,4,2020,0,1,Montenegro,ME,MNE,622182,Europe,9.96492988\r
-24/04/2020,24,4,2020,4,0,Montenegro,ME,MNE,622182,Europe,10.76855325\r
-23/04/2020,23,4,2020,2,0,Montenegro,ME,MNE,622182,Europe,10.60782858\r
-22/04/2020,22,4,2020,1,0,Montenegro,ME,MNE,622182,Europe,11.57217663\r
-21/04/2020,21,4,2020,4,0,Montenegro,ME,MNE,622182,Europe,12.69724936\r
-20/04/2020,20,4,2020,1,0,Montenegro,ME,MNE,622182,Europe,15.10811949\r
-19/04/2020,19,4,2020,4,1,Montenegro,ME,MNE,622182,Europe,17.03681559\r
-18/04/2020,18,4,2020,0,0,Montenegro,ME,MNE,622182,Europe,20.73348313\r
-17/04/2020,17,4,2020,15,0,Montenegro,ME,MNE,622182,Europe,25.55522339\r
-16/04/2020,16,4,2020,5,0,Montenegro,ME,MNE,622182,Europe,26.51957144\r
-15/04/2020,15,4,2020,9,1,Montenegro,ME,MNE,622182,Europe,27.96609352\r
-14/04/2020,14,4,2020,2,0,Montenegro,ME,MNE,622182,Europe,29.4126156\r
-13/04/2020,13,4,2020,9,1,Montenegro,ME,MNE,622182,Europe,30.0555143\r
-12/04/2020,12,4,2020,6,0,Montenegro,ME,MNE,622182,Europe,28.7697169\r
-11/04/2020,11,4,2020,5,0,Montenegro,ME,MNE,622182,Europe,29.25189093\r
-10/04/2020,10,4,2020,3,0,Montenegro,ME,MNE,622182,Europe,29.73406495\r
-09/04/2020,9,4,2020,8,0,Montenegro,ME,MNE,622182,Europe,31.50203638\r
-08/04/2020,8,4,2020,8,0,Montenegro,ME,MNE,622182,Europe,31.18058703\r
-07/04/2020,7,4,2020,19,0,Montenegro,ME,MNE,622182,Europe,33.10928314\r
-06/04/2020,6,4,2020,13,0,Montenegro,ME,MNE,622182,Europe,31.01986236\r
-05/04/2020,5,4,2020,27,0,Montenegro,ME,MNE,622182,Europe,30.0555143\r
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-31/03/2020,31,3,2020,6,0,Montenegro,ME,MNE,622182,Europe,14.62594546\r
-30/03/2020,30,3,2020,1,0,Montenegro,ME,MNE,622182,Europe,\r
-29/03/2020,29,3,2020,9,0,Montenegro,ME,MNE,622182,Europe,\r
-28/03/2020,28,3,2020,8,0,Montenegro,ME,MNE,622182,Europe,\r
-27/03/2020,27,3,2020,14,1,Montenegro,ME,MNE,622182,Europe,\r
-26/03/2020,26,3,2020,6,0,Montenegro,ME,MNE,622182,Europe,\r
-25/03/2020,25,3,2020,20,0,Montenegro,ME,MNE,622182,Europe,\r
-24/03/2020,24,3,2020,6,0,Montenegro,ME,MNE,622182,Europe,\r
-23/03/2020,23,3,2020,7,0,Montenegro,ME,MNE,622182,Europe,\r
-22/03/2020,22,3,2020,0,0,Montenegro,ME,MNE,622182,Europe,\r
-21/03/2020,21,3,2020,1,0,Montenegro,ME,MNE,622182,Europe,\r
-20/03/2020,20,3,2020,5,0,Montenegro,ME,MNE,622182,Europe,\r
-19/03/2020,19,3,2020,6,0,Montenegro,ME,MNE,622182,Europe,\r
-18/03/2020,18,3,2020,2,0,Montenegro,ME,MNE,622182,Europe,\r
-19/08/2020,19,8,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-18/08/2020,18,8,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-17/08/2020,17,8,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-16/08/2020,16,8,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-15/08/2020,15,8,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-14/08/2020,14,8,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-13/08/2020,13,8,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-12/08/2020,12,8,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-11/08/2020,11,8,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-10/08/2020,10,8,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-09/08/2020,9,8,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
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-07/08/2020,7,8,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-06/08/2020,6,8,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-05/08/2020,5,8,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-04/08/2020,4,8,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-03/08/2020,3,8,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-02/08/2020,2,8,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-01/08/2020,1,8,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-31/07/2020,31,7,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-30/07/2020,30,7,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-29/07/2020,29,7,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-28/07/2020,28,7,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-27/07/2020,27,7,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-26/07/2020,26,7,2020,1,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-25/07/2020,25,7,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-24/07/2020,24,7,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-23/07/2020,23,7,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-22/07/2020,22,7,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-21/07/2020,21,7,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-20/07/2020,20,7,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-19/07/2020,19,7,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-18/07/2020,18,7,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-17/07/2020,17,7,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-16/07/2020,16,7,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-15/07/2020,15,7,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-14/07/2020,14,7,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-13/07/2020,13,7,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-12/07/2020,12,7,2020,0,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-11/07/2020,11,7,2020,1,0,Montserrat,MS,MSF,4991,America,20.03606492\r
-10/07/2020,10,7,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-09/07/2020,9,7,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-08/07/2020,8,7,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-07/07/2020,7,7,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-06/07/2020,6,7,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-05/07/2020,5,7,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-04/07/2020,4,7,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-03/07/2020,3,7,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-02/07/2020,2,7,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-01/07/2020,1,7,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-30/06/2020,30,6,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-29/06/2020,29,6,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-28/06/2020,28,6,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-27/06/2020,27,6,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-26/06/2020,26,6,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-25/06/2020,25,6,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-24/06/2020,24,6,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-23/06/2020,23,6,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-22/06/2020,22,6,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-21/06/2020,21,6,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-20/06/2020,20,6,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-19/06/2020,19,6,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-18/06/2020,18,6,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-17/06/2020,17,6,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-16/06/2020,16,6,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-15/06/2020,15,6,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-14/06/2020,14,6,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-13/06/2020,13,6,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-12/06/2020,12,6,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-11/06/2020,11,6,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-10/06/2020,10,6,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-09/06/2020,9,6,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-08/06/2020,8,6,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-07/06/2020,7,6,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
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-31/05/2020,31,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-30/05/2020,30,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-29/05/2020,29,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-28/05/2020,28,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-27/05/2020,27,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-26/05/2020,26,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-25/05/2020,25,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-24/05/2020,24,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-23/05/2020,23,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-22/05/2020,22,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-21/05/2020,21,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-20/05/2020,20,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-19/05/2020,19,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-18/05/2020,18,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-17/05/2020,17,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-16/05/2020,16,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-15/05/2020,15,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-14/05/2020,14,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-13/05/2020,13,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-12/05/2020,12,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-11/05/2020,11,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-10/05/2020,10,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-09/05/2020,9,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
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-05/05/2020,5,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-04/05/2020,4,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
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-02/05/2020,2,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-01/05/2020,1,5,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-30/04/2020,30,4,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-29/04/2020,29,4,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-28/04/2020,28,4,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-27/04/2020,27,4,2020,0,0,Montserrat,MS,MSF,4991,America,0\r
-26/04/2020,26,4,2020,0,1,Montserrat,MS,MSF,4991,America,40.07212983\r
-25/04/2020,25,4,2020,0,0,Montserrat,MS,MSF,4991,America,40.07212983\r
-24/04/2020,24,4,2020,0,0,Montserrat,MS,MSF,4991,America,40.07212983\r
-23/04/2020,23,4,2020,0,0,Montserrat,MS,MSF,4991,America,40.07212983\r
-22/04/2020,22,4,2020,0,0,Montserrat,MS,MSF,4991,America,100.18032458\r
-21/04/2020,21,4,2020,0,0,Montserrat,MS,MSF,4991,America,100.18032458\r
-20/04/2020,20,4,2020,0,0,Montserrat,MS,MSF,4991,America,100.18032458\r
-19/04/2020,19,4,2020,0,0,Montserrat,MS,MSF,4991,America,100.18032458\r
-18/04/2020,18,4,2020,0,0,Montserrat,MS,MSF,4991,America,120.2163895\r
-17/04/2020,17,4,2020,0,0,Montserrat,MS,MSF,4991,America,120.2163895\r
-16/04/2020,16,4,2020,0,0,Montserrat,MS,MSF,4991,America,120.2163895\r
-15/04/2020,15,4,2020,0,0,Montserrat,MS,MSF,4991,America,120.2163895\r
-14/04/2020,14,4,2020,0,0,Montserrat,MS,MSF,4991,America,120.2163895\r
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-11/04/2020,11,4,2020,0,0,Montserrat,MS,MSF,4991,America,80.14425967\r
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-29/03/2020,29,3,2020,0,0,Montserrat,MS,MSF,4991,America,\r
-28/03/2020,28,3,2020,0,0,Montserrat,MS,MSF,4991,America,\r
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-25/03/2020,25,3,2020,0,0,Montserrat,MS,MSF,4991,America,\r
-24/03/2020,24,3,2020,0,0,Montserrat,MS,MSF,4991,America,\r
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-30/07/2020,30,7,2020,826,7,Morocco,MA,MAR,36471766,Africa,16.31673114\r
-29/07/2020,29,7,2020,500,11,Morocco,MA,MAR,36471766,Africa,14.50437031\r
-28/07/2020,28,7,2020,609,3,Morocco,MA,MAR,36471766,Africa,13.5748842\r
-27/07/2020,27,7,2020,633,8,Morocco,MA,MAR,36471766,Africa,12.42879218\r
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-24/07/2020,24,7,2020,302,7,Morocco,MA,MAR,36471766,Africa,9.08922261\r
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-11/07/2020,11,7,2020,379,1,Morocco,MA,MAR,36471766,Africa,10.13112444\r
-10/07/2020,10,7,2020,178,0,Morocco,MA,MAR,36471766,Africa,9.9008093\r
-09/07/2020,9,7,2020,442,7,Morocco,MA,MAR,36471766,Africa,10.59449658\r
-08/07/2020,8,7,2020,0,0,Morocco,MA,MAR,36471766,Africa,11.14560781\r
-07/07/2020,7,7,2020,114,0,Morocco,MA,MAR,36471766,Africa,11.39785773\r
-06/07/2020,6,7,2020,393,3,Morocco,MA,MAR,36471766,Africa,11.61994733\r
-05/07/2020,5,7,2020,534,2,Morocco,MA,MAR,36471766,Africa,11.02496655\r
-04/07/2020,4,7,2020,319,1,Morocco,MA,MAR,36471766,Africa,10.0762875\r
-03/07/2020,3,7,2020,333,1,Morocco,MA,MAR,36471766,Africa,10.67949383\r
-02/07/2020,2,7,2020,103,0,Morocco,MA,MAR,36471766,Africa,9.97758101\r
-01/07/2020,1,7,2020,243,3,Morocco,MA,MAR,36471766,Africa,9.90355115\r
-30/06/2020,30,6,2020,238,4,Morocco,MA,MAR,36471766,Africa,9.46485564\r
-29/06/2020,29,6,2020,175,1,Morocco,MA,MAR,36471766,Africa,9.09744815\r
-28/06/2020,28,6,2020,244,2,Morocco,MA,MAR,36471766,Africa,8.7327825\r
-27/06/2020,27,6,2020,295,1,Morocco,MA,MAR,36471766,Africa,8.2886033\r
-26/06/2020,26,6,2020,431,1,Morocco,MA,MAR,36471766,Africa,7.67991328\r
-25/06/2020,25,6,2020,643,2,Morocco,MA,MAR,36471766,Africa,6.7230087\r
-24/06/2020,24,6,2020,92,0,Morocco,MA,MAR,36471766,Africa,5.00935436\r
-23/06/2020,23,6,2020,195,0,Morocco,MA,MAR,36471766,Africa,5.12725378\r
-22/06/2020,22,6,2020,176,1,Morocco,MA,MAR,36471766,Africa,4.80645769\r
-21/06/2020,21,6,2020,188,0,Morocco,MA,MAR,36471766,Africa,4.57614254\r
-20/06/2020,20,6,2020,539,0,Morocco,MA,MAR,36471766,Africa,4.22792798\r
-19/06/2020,19,6,2020,77,0,Morocco,MA,MAR,36471766,Africa,2.93651807\r
-18/06/2020,18,6,2020,76,1,Morocco,MA,MAR,36471766,Africa,2.94748546\r
-17/06/2020,17,6,2020,83,0,Morocco,MA,MAR,36471766,Africa,2.89264852\r
-16/06/2020,16,6,2020,104,0,Morocco,MA,MAR,36471766,Africa,2.75555617\r
-15/06/2020,15,6,2020,42,0,Morocco,MA,MAR,36471766,Africa,2.54169211\r
-14/06/2020,14,6,2020,82,0,Morocco,MA,MAR,36471766,Africa,2.50056441\r
-13/06/2020,13,6,2020,73,1,Morocco,MA,MAR,36471766,Africa,2.45669486\r
-12/06/2020,12,6,2020,82,1,Morocco,MA,MAR,36471766,Africa,2.45121116\r
-11/06/2020,11,6,2020,18,0,Morocco,MA,MAR,36471766,Africa,2.34153729\r
-10/06/2020,10,6,2020,135,2,Morocco,MA,MAR,36471766,Africa,2.35798837\r
-09/06/2020,9,6,2020,78,0,Morocco,MA,MAR,36471766,Africa,2.11122214\r
-08/06/2020,8,6,2020,92,0,Morocco,MA,MAR,36471766,Africa,2.16880093\r
-07/06/2020,7,6,2020,61,0,Morocco,MA,MAR,36471766,Africa,1.99058088\r
-06/06/2020,6,6,2020,68,0,Morocco,MA,MAR,36471766,Africa,2.02622489\r
-05/06/2020,5,6,2020,81,2,Morocco,MA,MAR,36471766,Africa,2.17154278\r
-04/06/2020,4,6,2020,56,0,Morocco,MA,MAR,36471766,Africa,2.16331724\r
-03/06/2020,3,6,2020,33,1,Morocco,MA,MAR,36471766,Africa,2.31137697\r
-02/06/2020,2,6,2020,26,0,Morocco,MA,MAR,36471766,Africa,2.41556715\r
-01/06/2020,1,6,2020,27,1,Morocco,MA,MAR,36471766,Africa,2.56911058\r
-31/05/2020,31,5,2020,66,2,Morocco,MA,MAR,36471766,Africa,2.84877897\r
-30/05/2020,30,5,2020,71,0,Morocco,MA,MAR,36471766,Africa,2.91184145\r
-29/05/2020,29,5,2020,42,0,Morocco,MA,MAR,36471766,Africa,2.84055343\r
-28/05/2020,28,5,2020,24,0,Morocco,MA,MAR,36471766,Africa,2.98587132\r
-27/05/2020,27,5,2020,45,2,Morocco,MA,MAR,36471766,Africa,3.1778006\r
-26/05/2020,26,5,2020,99,1,Morocco,MA,MAR,36471766,Africa,3.43005052\r
-25/05/2020,25,5,2020,27,1,Morocco,MA,MAR,36471766,Africa,3.75633031\r
-24/05/2020,24,5,2020,74,1,Morocco,MA,MAR,36471766,Africa,4.10180302\r
-23/05/2020,23,5,2020,121,1,Morocco,MA,MAR,36471766,Africa,4.44453389\r
-22/05/2020,22,5,2020,78,2,Morocco,MA,MAR,36471766,Africa,4.55969146\r
-21/05/2020,21,5,2020,110,1,Morocco,MA,MAR,36471766,Africa,4.72968597\r
-20/05/2020,20,5,2020,71,1,Morocco,MA,MAR,36471766,Africa,4.94629188\r
-19/05/2020,19,5,2020,82,0,Morocco,MA,MAR,36471766,Africa,5.23418581\r
-18/05/2020,18,5,2020,129,0,Morocco,MA,MAR,36471766,Africa,5.39321293\r
-17/05/2020,17,5,2020,89,2,Morocco,MA,MAR,36471766,Africa,5.51659604\r
-16/05/2020,16,5,2020,45,0,Morocco,MA,MAR,36471766,Africa,5.71126718\r
-15/05/2020,15,5,2020,95,2,Morocco,MA,MAR,36471766,Africa,5.98819372\r
-14/05/2020,14,5,2020,94,0,Morocco,MA,MAR,36471766,Africa,6.00738665\r
-13/05/2020,13,5,2020,137,0,Morocco,MA,MAR,36471766,Africa,5.93884047\r
-12/05/2020,12,5,2020,218,0,Morocco,MA,MAR,36471766,Africa,5.92513124\r
-11/05/2020,11,5,2020,153,2,Morocco,MA,MAR,36471766,Africa,5.47821019\r
-10/05/2020,10,5,2020,199,0,Morocco,MA,MAR,36471766,Africa,5.51933789\r
-09/05/2020,9,5,2020,163,3,Morocco,MA,MAR,36471766,Africa,5.35482707\r
-08/05/2020,8,5,2020,140,0,Morocco,MA,MAR,36471766,Africa,5.42885694\r
-07/05/2020,7,5,2020,189,2,Morocco,MA,MAR,36471766,Africa,5.56869113\r
-06/05/2020,6,5,2020,176,2,Morocco,MA,MAR,36471766,Africa,5.51111235\r
-05/05/2020,5,5,2020,140,5,Morocco,MA,MAR,36471766,Africa,5.47546834\r
-04/05/2020,4,5,2020,174,1,Morocco,MA,MAR,36471766,Africa,5.61530253\r
-03/05/2020,3,5,2020,160,2,Morocco,MA,MAR,36471766,Africa,5.60433515\r
-02/05/2020,2,5,2020,146,1,Morocco,MA,MAR,36471766,Africa,5.49740311\r
-01/05/2020,1,5,2020,102,2,Morocco,MA,MAR,36471766,Africa,5.86755245\r
-30/04/2020,30,4,2020,69,3,Morocco,MA,MAR,36471766,Africa,6.29802242\r
-29/04/2020,29,4,2020,132,3,Morocco,MA,MAR,36471766,Africa,6.48172617\r
-28/04/2020,28,4,2020,55,1,Morocco,MA,MAR,36471766,Africa,6.46253324\r
-27/04/2020,27,4,2020,168,2,Morocco,MA,MAR,36471766,Africa,6.59140004\r
-26/04/2020,26,4,2020,139,1,Morocco,MA,MAR,36471766,Africa,6.448824\r
-25/04/2020,25,4,2020,190,3,Morocco,MA,MAR,36471766,Africa,6.33366643\r
-24/04/2020,24,4,2020,191,6,Morocco,MA,MAR,36471766,Africa,6.01561219\r
-23/04/2020,23,4,2020,168,4,Morocco,MA,MAR,36471766,Africa,5.76336227\r
-22/04/2020,22,4,2020,163,2,Morocco,MA,MAR,36471766,Africa,5.55224005\r
-21/04/2020,21,4,2020,191,2,Morocco,MA,MAR,36471766,Africa,5.28079721\r
-20/04/2020,20,4,2020,170,4,Morocco,MA,MAR,36471766,Africa,5.02854729\r
-19/04/2020,19,4,2020,121,2,Morocco,MA,MAR,36471766,Africa,4.8421017\r
-18/04/2020,18,4,2020,281,5,Morocco,MA,MAR,36471766,Africa,5.08886792\r
-17/04/2020,17,4,2020,259,3,Morocco,MA,MAR,36471766,Africa,4.31840893\r
-16/04/2020,16,4,2020,136,1,Morocco,MA,MAR,36471766,Africa,3.75633031\r
-15/04/2020,15,4,2020,125,0,Morocco,MA,MAR,36471766,Africa,3.48488746\r
-14/04/2020,14,4,2020,102,8,Morocco,MA,MAR,36471766,Africa,3.30940926\r
-13/04/2020,13,4,2020,116,7,Morocco,MA,MAR,36471766,Africa,3.24086308\r
-12/04/2020,12,4,2020,97,4,Morocco,MA,MAR,36471766,Africa,3.25457232\r
-11/04/2020,11,4,2020,74,10,Morocco,MA,MAR,36471766,Africa,3.02425717\r
-10/04/2020,10,4,2020,99,4,Morocco,MA,MAR,36471766,Africa,3.01328979\r
-09/04/2020,9,4,2020,91,3,Morocco,MA,MAR,36471766,Africa,2.87893929\r
-08/04/2020,8,4,2020,64,10,Morocco,MA,MAR,36471766,Africa,2.7802328\r
-07/04/2020,7,4,2020,99,10,Morocco,MA,MAR,36471766,Africa,2.70346108\r
-06/04/2020,6,4,2020,102,11,Morocco,MA,MAR,36471766,Africa,2.48411333\r
-05/04/2020,5,4,2020,211,15,Morocco,MA,MAR,36471766,Africa,2.25654003\r
-04/04/2020,4,4,2020,0,0,Morocco,MA,MAR,36471766,Africa,1.7054288\r
-03/04/2020,3,4,2020,54,5,Morocco,MA,MAR,36471766,Africa,1.76849128\r
-02/04/2020,2,4,2020,37,3,Morocco,MA,MAR,36471766,Africa,1.64510816\r
-01/04/2020,1,4,2020,61,3,Morocco,MA,MAR,36471766,Africa,1.5710783\r
-31/03/2020,31,3,2020,77,7,Morocco,MA,MAR,36471766,Africa,1.42301856\r
-30/03/2020,30,3,2020,121,3,Morocco,MA,MAR,36471766,Africa,1.23657297\r
-29/03/2020,29,3,2020,13,0,Morocco,MA,MAR,36471766,Africa,0.93222796\r
-28/03/2020,28,3,2020,70,13,Morocco,MA,MAR,36471766,Africa,0.92674427\r
-27/03/2020,27,3,2020,50,4,Morocco,MA,MAR,36471766,Africa,0.73755683\r
-26/03/2020,26,3,2020,55,1,Morocco,MA,MAR,36471766,Africa,0.60320633\r
-25/03/2020,25,3,2020,36,1,Morocco,MA,MAR,36471766,Africa,0.46063029\r
-24/03/2020,24,3,2020,19,0,Morocco,MA,MAR,36471766,Africa,0.36466564\r
-23/03/2020,23,3,2020,19,1,Morocco,MA,MAR,36471766,Africa,0.3153124\r
-22/03/2020,22,3,2020,10,0,Morocco,MA,MAR,36471766,Africa,\r
-21/03/2020,21,3,2020,23,1,Morocco,MA,MAR,36471766,Africa,\r
-20/03/2020,20,3,2020,9,0,Morocco,MA,MAR,36471766,Africa,\r
-19/03/2020,19,3,2020,10,0,Morocco,MA,MAR,36471766,Africa,\r
-18/03/2020,18,3,2020,7,1,Morocco,MA,MAR,36471766,Africa,\r
-17/03/2020,17,3,2020,9,0,Morocco,MA,MAR,36471766,Africa,\r
-16/03/2020,16,3,2020,10,0,Morocco,MA,MAR,36471766,Africa,\r
-15/03/2020,15,3,2020,11,0,Morocco,MA,MAR,36471766,Africa,\r
-14/03/2020,14,3,2020,1,0,Morocco,MA,MAR,36471766,Africa,\r
-13/03/2020,13,3,2020,1,0,Morocco,MA,MAR,36471766,Africa,\r
-12/03/2020,12,3,2020,3,1,Morocco,MA,MAR,36471766,Africa,\r
-06/03/2020,6,3,2020,1,0,Morocco,MA,MAR,36471766,Africa,\r
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-18/08/2020,18,8,2020,59,0,Mozambique,MZ,MOZ,30366043,Africa,3.09885618\r
-17/08/2020,17,8,2020,64,0,Mozambique,MZ,MOZ,30366043,Africa,2.99347531\r
-16/08/2020,16,8,2020,83,0,Mozambique,MZ,MOZ,30366043,Africa,2.91114651\r
-15/08/2020,15,8,2020,70,0,Mozambique,MZ,MOZ,30366043,Africa,2.77942042\r
-14/08/2020,14,8,2020,79,0,Mozambique,MZ,MOZ,30366043,Africa,2.73331629\r
-13/08/2020,13,8,2020,78,2,Mozambique,MZ,MOZ,30366043,Africa,2.6707464\r
-12/08/2020,12,8,2020,70,1,Mozambique,MZ,MOZ,30366043,Africa,2.50608879\r
-11/08/2020,11,8,2020,142,0,Mozambique,MZ,MOZ,30366043,Africa,2.33813803\r
-10/08/2020,10,8,2020,28,0,Mozambique,MZ,MOZ,30366043,Africa,1.97589129\r
-09/08/2020,9,8,2020,28,1,Mozambique,MZ,MOZ,30366043,Africa,2.0582201\r
-08/08/2020,8,8,2020,93,0,Mozambique,MZ,MOZ,30366043,Africa,2.05163379\r
-07/08/2020,7,8,2020,41,0,Mozambique,MZ,MOZ,30366043,Africa,1.77171586\r
-06/08/2020,6,8,2020,50,0,Mozambique,MZ,MOZ,30366043,Africa,1.71902543\r
-05/08/2020,5,8,2020,56,1,Mozambique,MZ,MOZ,30366043,Africa,1.62352401\r
-04/08/2020,4,8,2020,27,1,Mozambique,MZ,MOZ,30366043,Africa,1.53460891\r
-03/08/2020,3,8,2020,39,2,Mozambique,MZ,MOZ,30366043,Africa,1.49838423\r
-02/08/2020,2,8,2020,43,0,Mozambique,MZ,MOZ,30366043,Africa,1.55436782\r
-01/08/2020,1,8,2020,56,0,Mozambique,MZ,MOZ,30366043,Africa,1.5214363\r
-31/07/2020,31,7,2020,60,0,Mozambique,MZ,MOZ,30366043,Africa,1.39958967\r
-30/07/2020,30,7,2020,28,0,Mozambique,MZ,MOZ,30366043,Africa,1.3765376\r
-29/07/2020,29,7,2020,19,0,Mozambique,MZ,MOZ,30366043,Africa,1.48850477\r
-28/07/2020,28,7,2020,32,0,Mozambique,MZ,MOZ,30366043,Africa,1.58729934\r
-27/07/2020,27,7,2020,53,0,Mozambique,MZ,MOZ,30366043,Africa,1.6860939\r
-26/07/2020,26,7,2020,26,0,Mozambique,MZ,MOZ,30366043,Africa,1.58400619\r
-25/07/2020,25,7,2020,8,0,Mozambique,MZ,MOZ,30366043,Africa,1.57741988\r
-24/07/2020,24,7,2020,25,0,Mozambique,MZ,MOZ,30366043,Africa,1.61364456\r
-23/07/2020,23,7,2020,21,0,Mozambique,MZ,MOZ,30366043,Africa,1.60047195\r
-22/07/2020,22,7,2020,29,0,Mozambique,MZ,MOZ,30366043,Africa,1.63340347\r
-21/07/2020,21,7,2020,16,1,Mozambique,MZ,MOZ,30366043,Africa,1.63011032\r
-20/07/2020,20,7,2020,56,0,Mozambique,MZ,MOZ,30366043,Africa,1.65974869\r
-19/07/2020,19,7,2020,33,1,Mozambique,MZ,MOZ,30366043,Africa,1.53460891\r
-18/07/2020,18,7,2020,19,0,Mozambique,MZ,MOZ,30366043,Africa,1.52472945\r
-17/07/2020,17,7,2020,53,0,Mozambique,MZ,MOZ,30366043,Africa,1.53131575\r
-16/07/2020,16,7,2020,62,0,Mozambique,MZ,MOZ,30366043,Africa,1.40617597\r
-15/07/2020,15,7,2020,49,0,Mozambique,MZ,MOZ,30366043,Africa,1.24810467\r
-14/07/2020,14,7,2020,62,0,Mozambique,MZ,MOZ,30366043,Africa,1.10649912\r
-13/07/2020,13,7,2020,22,0,Mozambique,MZ,MOZ,30366043,Africa,0.98135934\r
-12/07/2020,12,7,2020,24,0,Mozambique,MZ,MOZ,30366043,Africa,0.97477304\r
-11/07/2020,11,7,2020,19,0,Mozambique,MZ,MOZ,30366043,Africa,0.97147989\r
-10/07/2020,10,7,2020,21,1,Mozambique,MZ,MOZ,30366043,Africa,1.00111826\r
-09/07/2020,9,7,2020,31,0,Mozambique,MZ,MOZ,30366043,Africa,1.01758402\r
-08/07/2020,8,7,2020,28,0,Mozambique,MZ,MOZ,30366043,Africa,0.93196206\r
-07/07/2020,7,7,2020,25,0,Mozambique,MZ,MOZ,30366043,Africa,0.90561684\r
-06/07/2020,6,7,2020,18,1,Mozambique,MZ,MOZ,30366043,Africa,0.83646065\r
-05/07/2020,5,7,2020,30,1,Mozambique,MZ,MOZ,30366043,Africa,0.92537576\r
-04/07/2020,4,7,2020,21,0,Mozambique,MZ,MOZ,30366043,Africa,0.89244423\r
-03/07/2020,3,7,2020,15,0,Mozambique,MZ,MOZ,30366043,Africa,0.84304695\r
-02/07/2020,2,7,2020,14,0,Mozambique,MZ,MOZ,30366043,Africa,0.82987434\r
-01/07/2020,1,7,2020,6,0,Mozambique,MZ,MOZ,30366043,Africa,0.82658119\r
-30/06/2020,30,6,2020,24,1,Mozambique,MZ,MOZ,30366043,Africa,0.90232369\r
-29/06/2020,29,6,2020,20,0,Mozambique,MZ,MOZ,30366043,Africa,0.90891\r
-28/06/2020,28,6,2020,23,0,Mozambique,MZ,MOZ,30366043,Africa,0.94184152\r
-27/06/2020,27,6,2020,28,0,Mozambique,MZ,MOZ,30366043,Africa,1.01099771\r
-26/06/2020,26,6,2020,26,0,Mozambique,MZ,MOZ,30366043,Africa,0.98465249\r
-25/06/2020,25,6,2020,5,0,Mozambique,MZ,MOZ,30366043,Africa,0.95501413\r
-24/06/2020,24,6,2020,20,0,Mozambique,MZ,MOZ,30366043,Africa,1.00111826\r
-23/06/2020,23,6,2020,4,0,Mozambique,MZ,MOZ,30366043,Africa,1.00111826\r
-22/06/2020,22,6,2020,45,1,Mozambique,MZ,MOZ,30366043,Africa,1.01099771\r
-21/06/2020,21,6,2020,20,0,Mozambique,MZ,MOZ,30366043,Africa,0.91220315\r
-20/06/2020,20,6,2020,6,0,Mozambique,MZ,MOZ,30366043,Africa,1.03404978\r
-19/06/2020,19,6,2020,11,0,Mozambique,MZ,MOZ,30366043,Africa,1.02087717\r
-18/06/2020,18,6,2020,13,0,Mozambique,MZ,MOZ,30366043,Africa,1.10320597\r
-17/06/2020,17,6,2020,29,1,Mozambique,MZ,MOZ,30366043,Africa,1.09003336\r
-16/06/2020,16,6,2020,26,0,Mozambique,MZ,MOZ,30366043,Africa,1.16906902\r
-15/06/2020,15,6,2020,30,1,Mozambique,MZ,MOZ,30366043,Africa,1.08344706\r
-14/06/2020,14,6,2020,44,0,Mozambique,MZ,MOZ,30366043,Africa,1.01758402\r
-13/06/2020,13,6,2020,20,0,Mozambique,MZ,MOZ,30366043,Africa,0.90561684\r
-12/06/2020,12,6,2020,17,0,Mozambique,MZ,MOZ,30366043,Africa,0.84304695\r
-11/06/2020,11,6,2020,19,0,Mozambique,MZ,MOZ,30366043,Africa,0.80682228\r
-10/06/2020,10,6,2020,20,0,Mozambique,MZ,MOZ,30366043,Africa,0.79035652\r
-09/06/2020,9,6,2020,7,0,Mozambique,MZ,MOZ,30366043,Africa,0.73766608\r
-08/06/2020,8,6,2020,15,0,Mozambique,MZ,MOZ,30366043,Africa,0.7640113\r
-07/06/2020,7,6,2020,57,0,Mozambique,MZ,MOZ,30366043,Africa,0.80023597\r
-06/06/2020,6,6,2020,2,0,Mozambique,MZ,MOZ,30366043,Africa,0.62569891\r
-05/06/2020,5,6,2020,36,0,Mozambique,MZ,MOZ,30366043,Africa,0.62569891\r
-04/06/2020,4,6,2020,9,0,Mozambique,MZ,MOZ,30366043,Africa,0.52690435\r
-03/06/2020,3,6,2020,53,0,Mozambique,MZ,MOZ,30366043,Africa,0.5301975\r
-02/06/2020,2,6,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,0.35895359\r
-01/06/2020,1,6,2020,10,0,Mozambique,MZ,MOZ,30366043,Africa,0.3852988\r
-31/05/2020,31,5,2020,10,0,Mozambique,MZ,MOZ,30366043,Africa,0.3787125\r
-30/05/2020,30,5,2020,1,0,Mozambique,MZ,MOZ,30366043,Africa,0.3787125\r
-29/05/2020,29,5,2020,6,1,Mozambique,MZ,MOZ,30366043,Africa,0.38859195\r
-28/05/2020,28,5,2020,14,0,Mozambique,MZ,MOZ,30366043,Africa,0.39517826\r
-27/05/2020,27,5,2020,4,0,Mozambique,MZ,MOZ,30366043,Africa,0.35895359\r
-26/05/2020,26,5,2020,15,1,Mozambique,MZ,MOZ,30366043,Africa,0.34907413\r
-25/05/2020,25,5,2020,26,0,Mozambique,MZ,MOZ,30366043,Africa,0.33919467\r
-24/05/2020,24,5,2020,4,0,Mozambique,MZ,MOZ,30366043,Africa,0.26674532\r
-23/05/2020,23,5,2020,2,0,Mozambique,MZ,MOZ,30366043,Africa,0.27003848\r
-22/05/2020,22,5,2020,6,0,Mozambique,MZ,MOZ,30366043,Africa,0.26674532\r
-21/05/2020,21,5,2020,10,0,Mozambique,MZ,MOZ,30366043,Africa,0.24698641\r
-20/05/2020,20,5,2020,1,0,Mozambique,MZ,MOZ,30366043,Africa,0.21405489\r
-19/05/2020,19,5,2020,8,0,Mozambique,MZ,MOZ,30366043,Africa,0.21405489\r
-18/05/2020,18,5,2020,8,0,Mozambique,MZ,MOZ,30366043,Africa,0.18770967\r
-17/05/2020,17,5,2020,10,0,Mozambique,MZ,MOZ,30366043,Africa,0.16465761\r
-16/05/2020,16,5,2020,4,0,Mozambique,MZ,MOZ,30366043,Africa,0.13172609\r
-15/05/2020,15,5,2020,8,0,Mozambique,MZ,MOZ,30366043,Africa,0.12843293\r
-14/05/2020,14,5,2020,3,0,Mozambique,MZ,MOZ,30366043,Africa,0.10208772\r
-13/05/2020,13,5,2020,1,0,Mozambique,MZ,MOZ,30366043,Africa,0.09220826\r
-12/05/2020,12,5,2020,12,0,Mozambique,MZ,MOZ,30366043,Africa,0.08891511\r
-11/05/2020,11,5,2020,4,0,Mozambique,MZ,MOZ,30366043,Africa,0.04939728\r
-10/05/2020,10,5,2020,5,0,Mozambique,MZ,MOZ,30366043,Africa,0.05598359\r
-09/05/2020,9,5,2020,1,0,Mozambique,MZ,MOZ,30366043,Africa,0.05598359\r
-08/05/2020,8,5,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,0.11526033\r
-07/05/2020,7,5,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,0.13172609\r
-06/05/2020,6,5,2020,1,0,Mozambique,MZ,MOZ,30366043,Africa,0.13831239\r
-05/05/2020,5,5,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,0.13501924\r
-04/05/2020,4,5,2020,1,0,Mozambique,MZ,MOZ,30366043,Africa,0.13501924\r
-03/05/2020,3,5,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,0.14489869\r
-02/05/2020,2,5,2020,3,0,Mozambique,MZ,MOZ,30366043,Africa,0.14819185\r
-01/05/2020,1,5,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,0.14819185\r
-30/04/2020,30,4,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,0.15477815\r
-29/04/2020,29,4,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,0.1580713\r
-28/04/2020,28,4,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,0.16136446\r
-27/04/2020,27,4,2020,6,0,Mozambique,MZ,MOZ,30366043,Africa,0.18112337\r
-26/04/2020,26,4,2020,5,0,Mozambique,MZ,MOZ,30366043,Africa,0.16465761\r
-25/04/2020,25,4,2020,19,0,Mozambique,MZ,MOZ,30366043,Africa,0.14819185\r
-24/04/2020,24,4,2020,5,0,Mozambique,MZ,MOZ,30366043,Africa,0.09550141\r
-23/04/2020,23,4,2020,2,0,Mozambique,MZ,MOZ,30366043,Africa,0.07903565\r
-22/04/2020,22,4,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,0.09550141\r
-21/04/2020,21,4,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,0.09550141\r
-20/04/2020,20,4,2020,4,0,Mozambique,MZ,MOZ,30366043,Africa,0.09550141\r
-19/04/2020,19,4,2020,1,0,Mozambique,MZ,MOZ,30366043,Africa,0.0823288\r
-18/04/2020,18,4,2020,3,0,Mozambique,MZ,MOZ,30366043,Africa,0.07903565\r
-17/04/2020,17,4,2020,2,0,Mozambique,MZ,MOZ,30366043,Africa,0.0691562\r
-16/04/2020,16,4,2020,1,0,Mozambique,MZ,MOZ,30366043,Africa,0.06256989\r
-15/04/2020,15,4,2020,1,0,Mozambique,MZ,MOZ,30366043,Africa,0.06586304\r
-14/04/2020,14,4,2020,6,0,Mozambique,MZ,MOZ,30366043,Africa,0.06256989\r
-13/04/2020,13,4,2020,1,0,Mozambique,MZ,MOZ,30366043,Africa,0.04281098\r
-12/04/2020,12,4,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,0.03951783\r
-11/04/2020,11,4,2020,3,0,Mozambique,MZ,MOZ,30366043,Africa,0.04281098\r
-10/04/2020,10,4,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,0.03293152\r
-09/04/2020,9,4,2020,7,0,Mozambique,MZ,MOZ,30366043,Africa,0.03951783\r
-08/04/2020,8,4,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,0.02963837\r
-07/04/2020,7,4,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,0.02963837\r
-06/04/2020,6,4,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,0.02963837\r
-05/04/2020,5,4,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,0.03293152\r
-04/04/2020,4,4,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,\r
-03/04/2020,3,4,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,\r
-02/04/2020,2,4,2020,2,0,Mozambique,MZ,MOZ,30366043,Africa,\r
-01/04/2020,1,4,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,\r
-31/03/2020,31,3,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,\r
-30/03/2020,30,3,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,\r
-29/03/2020,29,3,2020,1,0,Mozambique,MZ,MOZ,30366043,Africa,\r
-28/03/2020,28,3,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,\r
-27/03/2020,27,3,2020,2,0,Mozambique,MZ,MOZ,30366043,Africa,\r
-26/03/2020,26,3,2020,4,0,Mozambique,MZ,MOZ,30366043,Africa,\r
-25/03/2020,25,3,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,\r
-24/03/2020,24,3,2020,0,0,Mozambique,MZ,MOZ,30366043,Africa,\r
-23/03/2020,23,3,2020,1,0,Mozambique,MZ,MOZ,30366043,Africa,\r
-19/08/2020,19,8,2020,3,0,Myanmar,MM,MMR,54045422,Asia,0.0425568\r
-18/08/2020,18,8,2020,1,0,Myanmar,MM,MMR,54045422,Asia,0.03885621\r
-17/08/2020,17,8,2020,1,0,Myanmar,MM,MMR,54045422,Asia,0.0407065\r
-16/08/2020,16,8,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.03885621\r
-15/08/2020,15,8,2020,5,0,Myanmar,MM,MMR,54045422,Asia,0.03885621\r
-14/08/2020,14,8,2020,8,0,Myanmar,MM,MMR,54045422,Asia,0.02960473\r
-13/08/2020,13,8,2020,1,0,Myanmar,MM,MMR,54045422,Asia,0.01480236\r
-12/08/2020,12,8,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.01665266\r
-11/08/2020,11,8,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.01850295\r
-10/08/2020,10,8,2020,1,0,Myanmar,MM,MMR,54045422,Asia,0.01850295\r
-09/08/2020,9,8,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.01850295\r
-08/08/2020,8,8,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.02405384\r
-07/08/2020,7,8,2020,2,0,Myanmar,MM,MMR,54045422,Asia,0.02960473\r
-06/08/2020,6,8,2020,1,0,Myanmar,MM,MMR,54045422,Asia,0.02590414\r
-05/08/2020,5,8,2020,1,0,Myanmar,MM,MMR,54045422,Asia,0.02775443\r
-04/08/2020,4,8,2020,2,0,Myanmar,MM,MMR,54045422,Asia,0.02590414\r
-03/08/2020,3,8,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.02220355\r
-02/08/2020,2,8,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.02220355\r
-01/08/2020,1,8,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.02590414\r
-31/07/2020,31,7,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.02590414\r
-30/07/2020,30,7,2020,2,0,Myanmar,MM,MMR,54045422,Asia,0.02960473\r
-29/07/2020,29,7,2020,1,0,Myanmar,MM,MMR,54045422,Asia,0.02590414\r
-28/07/2020,28,7,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.02590414\r
-27/07/2020,27,7,2020,1,0,Myanmar,MM,MMR,54045422,Asia,0.03515561\r
-26/07/2020,26,7,2020,3,0,Myanmar,MM,MMR,54045422,Asia,0.03515561\r
-25/07/2020,25,7,2020,3,0,Myanmar,MM,MMR,54045422,Asia,0.03700591\r
-24/07/2020,24,7,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.0407065\r
-23/07/2020,23,7,2020,2,0,Myanmar,MM,MMR,54045422,Asia,0.04625739\r
-22/07/2020,22,7,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.04625739\r
-21/07/2020,21,7,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.04625739\r
-20/07/2020,20,7,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.05180827\r
-19/07/2020,19,7,2020,2,0,Myanmar,MM,MMR,54045422,Asia,0.05180827\r
-18/07/2020,18,7,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.06105975\r
-17/07/2020,17,7,2020,2,0,Myanmar,MM,MMR,54045422,Asia,0.06476034\r
-16/07/2020,16,7,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.06105975\r
-15/07/2020,15,7,2020,1,0,Myanmar,MM,MMR,54045422,Asia,0.07031123\r
-14/07/2020,14,7,2020,5,0,Myanmar,MM,MMR,54045422,Asia,0.06846093\r
-13/07/2020,13,7,2020,1,0,Myanmar,MM,MMR,54045422,Asia,0.05920946\r
-12/07/2020,12,7,2020,4,0,Myanmar,MM,MMR,54045422,Asia,0.06291005\r
-11/07/2020,11,7,2020,5,0,Myanmar,MM,MMR,54045422,Asia,0.06105975\r
-10/07/2020,10,7,2020,3,0,Myanmar,MM,MMR,54045422,Asia,0.05180827\r
-09/07/2020,9,7,2020,2,0,Myanmar,MM,MMR,54045422,Asia,0.04625739\r
-08/07/2020,8,7,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.04440709\r
-07/07/2020,7,7,2020,3,0,Myanmar,MM,MMR,54045422,Asia,0.04625739\r
-06/07/2020,6,7,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.0425568\r
-05/07/2020,5,7,2020,7,0,Myanmar,MM,MMR,54045422,Asia,0.04810768\r
-04/07/2020,4,7,2020,2,0,Myanmar,MM,MMR,54045422,Asia,0.03700591\r
-03/07/2020,3,7,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.03330532\r
-02/07/2020,2,7,2020,5,0,Myanmar,MM,MMR,54045422,Asia,0.07586211\r
-01/07/2020,1,7,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.06846093\r
-30/06/2020,30,6,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.06846093\r
-29/06/2020,29,6,2020,3,0,Myanmar,MM,MMR,54045422,Asia,0.06846093\r
-28/06/2020,28,6,2020,3,0,Myanmar,MM,MMR,54045422,Asia,0.06476034\r
-27/06/2020,27,6,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.05920946\r
-26/06/2020,26,6,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.05920946\r
-25/06/2020,25,6,2020,1,0,Myanmar,MM,MMR,54045422,Asia,0.081413\r
-24/06/2020,24,6,2020,1,0,Myanmar,MM,MMR,54045422,Asia,0.08511359\r
-23/06/2020,23,6,2020,1,0,Myanmar,MM,MMR,54045422,Asia,0.08696389\r
-22/06/2020,22,6,2020,3,0,Myanmar,MM,MMR,54045422,Asia,0.08696389\r
-21/06/2020,21,6,2020,1,0,Myanmar,MM,MMR,54045422,Asia,0.08696389\r
-20/06/2020,20,6,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.09251477\r
-19/06/2020,19,6,2020,23,0,Myanmar,MM,MMR,54045422,Asia,0.09251477\r
-18/06/2020,18,6,2020,1,0,Myanmar,MM,MMR,54045422,Asia,0.05365857\r
-17/06/2020,17,6,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.05365857\r
-16/06/2020,16,6,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.06291005\r
-15/06/2020,15,6,2020,1,0,Myanmar,MM,MMR,54045422,Asia,0.06291005\r
-14/06/2020,14,6,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.06846093\r
-13/06/2020,13,6,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.06846093\r
-12/06/2020,12,6,2020,12,0,Myanmar,MM,MMR,54045422,Asia,0.10176625\r
-11/06/2020,11,6,2020,3,0,Myanmar,MM,MMR,54045422,Asia,0.07956271\r
-10/06/2020,10,6,2020,2,0,Myanmar,MM,MMR,54045422,Asia,0.07401182\r
-09/06/2020,9,6,2020,1,0,Myanmar,MM,MMR,54045422,Asia,0.07586211\r
-08/06/2020,8,6,2020,3,0,Myanmar,MM,MMR,54045422,Asia,0.07771241\r
-07/06/2020,7,6,2020,4,0,Myanmar,MM,MMR,54045422,Asia,0.07216152\r
-06/06/2020,6,6,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.06476034\r
-05/06/2020,5,6,2020,2,0,Myanmar,MM,MMR,54045422,Asia,0.06846093\r
-04/06/2020,4,6,2020,1,0,Myanmar,MM,MMR,54045422,Asia,0.06476034\r
-03/06/2020,3,6,2020,5,0,Myanmar,MM,MMR,54045422,Asia,0.07401182\r
-02/06/2020,2,6,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.06846093\r
-01/06/2020,1,6,2020,4,0,Myanmar,MM,MMR,54045422,Asia,0.07586211\r
-31/05/2020,31,5,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.07771241\r
-30/05/2020,30,5,2020,18,0,Myanmar,MM,MMR,54045422,Asia,0.07771241\r
-29/05/2020,29,5,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.04625739\r
-28/05/2020,28,5,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.04625739\r
-27/05/2020,27,5,2020,3,0,Myanmar,MM,MMR,54045422,Asia,0.04810768\r
-26/05/2020,26,5,2020,2,0,Myanmar,MM,MMR,54045422,Asia,0.0425568\r
-25/05/2020,25,5,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.03885621\r
-24/05/2020,24,5,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.0425568\r
-23/05/2020,23,5,2020,2,0,Myanmar,MM,MMR,54045422,Asia,0.04440709\r
-22/05/2020,22,5,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.0425568\r
-21/05/2020,21,5,2020,6,0,Myanmar,MM,MMR,54045422,Asia,0.06846093\r
-20/05/2020,20,5,2020,2,0,Myanmar,MM,MMR,54045422,Asia,0.05920946\r
-19/05/2020,19,5,2020,4,0,Myanmar,MM,MMR,54045422,Asia,0.05550886\r
-18/05/2020,18,5,2020,5,0,Myanmar,MM,MMR,54045422,Asia,0.05920946\r
-17/05/2020,17,5,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.05735916\r
-16/05/2020,16,5,2020,1,0,Myanmar,MM,MMR,54045422,Asia,0.05735916\r
-15/05/2020,15,5,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.05550886\r
-14/05/2020,14,5,2020,1,0,Myanmar,MM,MMR,54045422,Asia,0.05735916\r
-13/05/2020,13,5,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.05550886\r
-12/05/2020,12,5,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.06291005\r
-11/05/2020,11,5,2020,2,0,Myanmar,MM,MMR,54045422,Asia,0.06291005\r
-10/05/2020,10,5,2020,1,0,Myanmar,MM,MMR,54045422,Asia,0.05920946\r
-09/05/2020,9,5,2020,1,0,Myanmar,MM,MMR,54045422,Asia,0.06105975\r
-08/05/2020,8,5,2020,14,0,Myanmar,MM,MMR,54045422,Asia,0.081413\r
-07/05/2020,7,5,2020,1,0,Myanmar,MM,MMR,54045422,Asia,0.06476034\r
-06/05/2020,6,5,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.07401182\r
-05/05/2020,5,5,2020,6,0,Myanmar,MM,MMR,54045422,Asia,0.07771241\r
-04/05/2020,4,5,2020,4,0,Myanmar,MM,MMR,54045422,Asia,0.081413\r
-03/05/2020,3,5,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.081413\r
-02/05/2020,2,5,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.10546684\r
-01/05/2020,1,5,2020,1,0,Myanmar,MM,MMR,54045422,Asia,0.1221195\r
-30/04/2020,30,4,2020,0,1,Myanmar,MM,MMR,54045422,Asia,0.14062246\r
-29/04/2020,29,4,2020,4,0,Myanmar,MM,MMR,54045422,Asia,0.14062246\r
-28/04/2020,28,4,2020,0,0,Myanmar,MM,MMR,54045422,Asia,0.15542482\r
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-14/08/2020,14,8,2020,525,4,Nepal,NP,NPL,28608715,Asia,18.91032156\r
-13/08/2020,13,8,2020,484,8,Nepal,NP,NPL,28608715,Asia,18.03296653\r
-12/08/2020,12,8,2020,638,4,Nepal,NP,NPL,28608715,Asia,17.07521642\r
-11/08/2020,11,8,2020,338,4,Nepal,NP,NPL,28608715,Asia,15.93220807\r
-10/08/2020,10,8,2020,380,2,Nepal,NP,NPL,28608715,Asia,15.23661584\r
-09/08/2020,9,8,2020,378,3,Nepal,NP,NPL,28608715,Asia,14.36275624\r
-08/08/2020,8,8,2020,464,5,Nepal,NP,NPL,28608715,Asia,13.42248332\r
-07/08/2020,7,8,2020,360,5,Nepal,NP,NPL,28608715,Asia,12.26549322\r
-06/08/2020,6,8,2020,381,2,Nepal,NP,NPL,28608715,Asia,11.52096485\r
-05/08/2020,5,8,2020,259,1,Nepal,NP,NPL,28608715,Asia,10.71351859\r
-04/08/2020,4,8,2020,418,0,Nepal,NP,NPL,28608715,Asia,10.15774389\r
-03/08/2020,3,8,2020,246,1,Nepal,NP,NPL,28608715,Asia,9.34680219\r
-02/08/2020,2,8,2020,315,0,Nepal,NP,NPL,28608715,Asia,9.03221274\r
-01/08/2020,1,8,2020,224,4,Nepal,NP,NPL,28608715,Asia,8.13038964\r
-31/07/2020,31,7,2020,274,3,Nepal,NP,NPL,28608715,Asia,7.70045072\r
-30/07/2020,30,7,2020,210,0,Nepal,NP,NPL,28608715,Asia,7.32643881\r
-29/07/2020,29,7,2020,311,1,Nepal,NP,NPL,28608715,Asia,6.99786761\r
-28/07/2020,28,7,2020,139,3,Nepal,NP,NPL,28608715,Asia,6.31625713\r
-27/07/2020,27,7,2020,130,0,Nepal,NP,NPL,28608715,Asia,6.33373432\r
-26/07/2020,26,7,2020,109,1,Nepal,NP,NPL,28608715,Asia,6.16595328\r
-25/07/2020,25,7,2020,133,1,Nepal,NP,NPL,28608715,Asia,6.02963118\r
-24/07/2020,24,7,2020,147,1,Nepal,NP,NPL,28608715,Asia,5.97719961\r
-23/07/2020,23,7,2020,150,2,Nepal,NP,NPL,28608715,Asia,5.84087751\r
-22/07/2020,22,7,2020,100,0,Nepal,NP,NPL,28608715,Asia,6.92096796\r
-21/07/2020,21,7,2020,186,0,Nepal,NP,NPL,28608715,Asia,6.57142413\r
-20/07/2020,20,7,2020,156,0,Nepal,NP,NPL,28608715,Asia,6.5504515\r
-19/07/2020,19,7,2020,57,0,Nepal,NP,NPL,28608715,Asia,7.02932655\r
-18/07/2020,18,7,2020,101,1,Nepal,NP,NPL,28608715,Asia,7.64102827\r
-17/07/2020,17,7,2020,167,0,Nepal,NP,NPL,28608715,Asia,9.87461338\r
-16/07/2020,16,7,2020,116,1,Nepal,NP,NPL,28608715,Asia,10.94421752\r
-15/07/2020,15,7,2020,116,0,Nepal,NP,NPL,28608715,Asia,12.22354796\r
-14/07/2020,14,7,2020,144,0,Nepal,NP,NPL,28608715,Asia,12.92263564\r
-13/07/2020,13,7,2020,82,0,Nepal,NP,NPL,28608715,Asia,14.08312117\r
-12/07/2020,12,7,2020,70,3,Nepal,NP,NPL,28608715,Asia,17.35135605\r
-11/07/2020,11,7,2020,118,0,Nepal,NP,NPL,28608715,Asia,17.10667536\r
-10/07/2020,10,7,2020,108,0,Nepal,NP,NPL,28608715,Asia,18.76700858\r
-09/07/2020,9,7,2020,459,0,Nepal,NP,NPL,28608715,Asia,19.90652149\r
-08/07/2020,8,7,2020,0,0,Nepal,NP,NPL,28608715,Asia,24.25135138\r
-07/07/2020,7,7,2020,180,1,Nepal,NP,NPL,28608715,Asia,24.25135138\r
-06/07/2020,6,7,2020,293,0,Nepal,NP,NPL,28608715,Asia,23.62217247\r
-05/07/2020,5,7,2020,232,2,Nepal,NP,NPL,28608715,Asia,24.06958859\r
-04/07/2020,4,7,2020,740,1,Nepal,NP,NPL,28608715,Asia,24.41563698\r
-03/07/2020,3,7,2020,473,1,Nepal,NP,NPL,28608715,Asia,23.31806934\r
-02/07/2020,2,7,2020,482,1,Nepal,NP,NPL,28608715,Asia,24.01016613\r
-01/07/2020,1,7,2020,316,0,Nepal,NP,NPL,28608715,Asia,24.37369172\r
-30/06/2020,30,6,2020,476,1,Nepal,NP,NPL,28608715,Asia,24.59739978\r
-29/06/2020,29,6,2020,1017,1,Nepal,NP,NPL,28608715,Asia,24.51001382\r
-28/06/2020,28,6,2020,0,0,Nepal,NP,NPL,28608715,Asia,22.44071431\r
-27/06/2020,27,6,2020,593,1,Nepal,NP,NPL,28608715,Asia,23.39496898\r
-26/06/2020,26,6,2020,434,3,Nepal,NP,NPL,28608715,Asia,22.88813042\r
-25/06/2020,25,6,2020,1702,0,Nepal,NP,NPL,28608715,Asia,22.24496976\r
-24/06/2020,24,6,2020,0,0,Nepal,NP,NPL,28608715,Asia,17.27096096\r
-23/06/2020,23,6,2020,0,0,Nepal,NP,NPL,28608715,Asia,18.39998756\r
-22/06/2020,22,6,2020,421,1,Nepal,NP,NPL,28608715,Asia,19.4975552\r
-21/06/2020,21,6,2020,331,0,Nepal,NP,NPL,28608715,Asia,19.89953062\r
-20/06/2020,20,6,2020,426,0,Nepal,NP,NPL,28608715,Asia,18.74254052\r
-19/06/2020,19,6,2020,671,2,Nepal,NP,NPL,28608715,Asia,18.22521564\r
-18/06/2020,18,6,2020,586,1,Nepal,NP,NPL,28608715,Asia,17.04725291\r
-17/06/2020,17,6,2020,380,0,Nepal,NP,NPL,28608715,Asia,15.70150914\r
-16/06/2020,16,6,2020,451,0,Nepal,NP,NPL,28608715,Asia,15.42536951\r
-15/06/2020,15,6,2020,425,1,Nepal,NP,NPL,28608715,Asia,14.63889587\r
-14/06/2020,14,6,2020,273,2,Nepal,NP,NPL,28608715,Asia,13.75105453\r
-13/06/2020,13,6,2020,448,1,Nepal,NP,NPL,28608715,Asia,13.45743771\r
-12/06/2020,12,6,2020,250,0,Nepal,NP,NPL,28608715,Asia,12.48570584\r
-11/06/2020,11,6,2020,279,0,Nepal,NP,NPL,28608715,Asia,12.15713464\r
-10/06/2020,10,6,2020,323,1,Nepal,NP,NPL,28608715,Asia,11.58038731\r
-09/06/2020,9,6,2020,314,1,Nepal,NP,NPL,28608715,Asia,10.76595017\r
-08/06/2020,8,6,2020,536,2,Nepal,NP,NPL,28608715,Asia,9.94452215\r
-07/06/2020,7,6,2020,0,0,Nepal,NP,NPL,28608715,Asia,8.13738051\r
-06/06/2020,6,6,2020,278,1,Nepal,NP,NPL,28608715,Asia,8.2632163\r
-05/06/2020,5,6,2020,334,1,Nepal,NP,NPL,28608715,Asia,7.50470617\r
-04/06/2020,4,6,2020,201,1,Nepal,NP,NPL,28608715,Asia,6.48753361\r
-03/06/2020,3,6,2020,301,0,Nepal,NP,NPL,28608715,Asia,5.93175891\r
-02/06/2020,2,6,2020,226,0,Nepal,NP,NPL,28608715,Asia,4.97400879\r
-01/06/2020,1,6,2020,171,2,Nepal,NP,NPL,28608715,Asia,4.43221585\r
-31/05/2020,31,5,2020,189,0,Nepal,NP,NPL,28608715,Asia,3.87993659\r
-30/05/2020,30,5,2020,170,1,Nepal,NP,NPL,28608715,Asia,3.27173031\r
-29/05/2020,29,5,2020,156,1,Nepal,NP,NPL,28608715,Asia,2.74042368\r
-28/05/2020,28,5,2020,114,0,Nepal,NP,NPL,28608715,Asia,2.33145739\r
-27/05/2020,27,5,2020,90,0,Nepal,NP,NPL,28608715,Asia,1.93996829\r
-26/05/2020,26,5,2020,79,1,Nepal,NP,NPL,28608715,Asia,1.91550022\r
-25/05/2020,25,5,2020,19,0,Nepal,NP,NPL,28608715,Asia,1.68829673\r
-24/05/2020,24,5,2020,36,0,Nepal,NP,NPL,28608715,Asia,1.66033322\r
-23/05/2020,23,5,2020,61,0,Nepal,NP,NPL,28608715,Asia,1.56246095\r
-22/05/2020,22,5,2020,43,1,Nepal,NP,NPL,28608715,Asia,1.34923921\r
-21/05/2020,21,5,2020,42,0,Nepal,NP,NPL,28608715,Asia,1.20592624\r
-20/05/2020,20,5,2020,27,0,Nepal,NP,NPL,28608715,Asia,1.11854028\r
-19/05/2020,19,5,2020,71,0,Nepal,NP,NPL,28608715,Asia,1.02416344\r
-18/05/2020,18,5,2020,13,1,Nepal,NP,NPL,28608715,Asia,0.80045539\r
-17/05/2020,17,5,2020,15,1,Nepal,NP,NPL,28608715,Asia,0.8109417\r
-16/05/2020,16,5,2020,18,0,Nepal,NP,NPL,28608715,Asia,0.75851013\r
-15/05/2020,15,5,2020,39,0,Nepal,NP,NPL,28608715,Asia,0.70258311\r
-14/05/2020,14,5,2020,2,0,Nepal,NP,NPL,28608715,Asia,0.56626102\r
-13/05/2020,13,5,2020,83,0,Nepal,NP,NPL,28608715,Asia,0.56975645\r
-12/05/2020,12,5,2020,14,0,Nepal,NP,NPL,28608715,Asia,0.28662595\r
-11/05/2020,11,5,2020,11,0,Nepal,NP,NPL,28608715,Asia,0.23768981\r
-10/05/2020,10,5,2020,8,0,Nepal,NP,NPL,28608715,Asia,0.2097263\r
-09/05/2020,9,5,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.1817628\r
-08/05/2020,8,5,2020,2,0,Nepal,NP,NPL,28608715,Asia,0.18525823\r
-07/05/2020,7,5,2020,17,0,Nepal,NP,NPL,28608715,Asia,0.18875367\r
-06/05/2020,6,5,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.13981753\r
-05/05/2020,5,5,2020,7,0,Nepal,NP,NPL,28608715,Asia,0.17826736\r
-04/05/2020,4,5,2020,16,0,Nepal,NP,NPL,28608715,Asia,0.15379929\r
-03/05/2020,3,5,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.09787227\r
-02/05/2020,2,5,2020,2,0,Nepal,NP,NPL,28608715,Asia,0.10136771\r
-01/05/2020,1,5,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.14331297\r
-30/04/2020,30,4,2020,3,0,Nepal,NP,NPL,28608715,Asia,0.14331297\r
-29/04/2020,29,4,2020,2,0,Nepal,NP,NPL,28608715,Asia,0.13282666\r
-28/04/2020,28,4,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.13282666\r
-27/04/2020,27,4,2020,3,0,Nepal,NP,NPL,28608715,Asia,0.13981753\r
-26/04/2020,26,4,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.13981753\r
-25/04/2020,25,4,2020,1,0,Nepal,NP,NPL,28608715,Asia,0.13981753\r
-24/04/2020,24,4,2020,3,0,Nepal,NP,NPL,28608715,Asia,0.1363221\r
-23/04/2020,23,4,2020,3,0,Nepal,NP,NPL,28608715,Asia,0.12583578\r
-22/04/2020,22,4,2020,11,0,Nepal,NP,NPL,28608715,Asia,0.11534947\r
-21/04/2020,21,4,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.07689964\r
-20/04/2020,20,4,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.07689964\r
-19/04/2020,19,4,2020,1,0,Nepal,NP,NPL,28608715,Asia,0.08738596\r
-18/04/2020,18,4,2020,14,0,Nepal,NP,NPL,28608715,Asia,0.08389052\r
-17/04/2020,17,4,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.03844982\r
-16/04/2020,16,4,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.03844982\r
-15/04/2020,15,4,2020,2,0,Nepal,NP,NPL,28608715,Asia,0.03844982\r
-14/04/2020,14,4,2020,2,0,Nepal,NP,NPL,28608715,Asia,0.03145895\r
-13/04/2020,13,4,2020,3,0,Nepal,NP,NPL,28608715,Asia,0.02446807\r
-12/04/2020,12,4,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.01398175\r
-11/04/2020,11,4,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.02097263\r
-10/04/2020,10,4,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.02097263\r
-09/04/2020,9,4,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.02097263\r
-08/04/2020,8,4,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.02097263\r
-07/04/2020,7,4,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.02446807\r
-06/04/2020,6,4,2020,3,0,Nepal,NP,NPL,28608715,Asia,0.02796351\r
-05/04/2020,5,4,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.01747719\r
-04/04/2020,4,4,2020,1,0,Nepal,NP,NPL,28608715,Asia,0.01747719\r
-03/04/2020,3,4,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.01398175\r
-02/04/2020,2,4,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.01398175\r
-01/04/2020,1,4,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.01398175\r
-31/03/2020,31,3,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.01398175\r
-30/03/2020,30,3,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.01398175\r
-29/03/2020,29,3,2020,2,0,Nepal,NP,NPL,28608715,Asia,0.01398175\r
-28/03/2020,28,3,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.00699088\r
-27/03/2020,27,3,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.00699088\r
-26/03/2020,26,3,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.00699088\r
-25/03/2020,25,3,2020,1,0,Nepal,NP,NPL,28608715,Asia,0.00699088\r
-24/03/2020,24,3,2020,1,0,Nepal,NP,NPL,28608715,Asia,0.00349544\r
-23/03/2020,23,3,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-22/03/2020,22,3,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-21/03/2020,21,3,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-20/03/2020,20,3,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-19/03/2020,19,3,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-18/03/2020,18,3,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-17/03/2020,17,3,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-15/03/2020,15,3,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-02/03/2020,2,3,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-01/03/2020,1,3,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-29/02/2020,29,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-28/02/2020,28,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-27/02/2020,27,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-26/02/2020,26,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-25/02/2020,25,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-24/02/2020,24,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-23/02/2020,23,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-22/02/2020,22,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-21/02/2020,21,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-20/02/2020,20,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-19/02/2020,19,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-18/02/2020,18,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-17/02/2020,17,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-16/02/2020,16,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-15/02/2020,15,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-14/02/2020,14,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-13/02/2020,13,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-12/02/2020,12,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-11/02/2020,11,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-10/02/2020,10,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-09/02/2020,9,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-08/02/2020,8,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-07/02/2020,7,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.00349544\r
-06/02/2020,6,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.00349544\r
-05/02/2020,5,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.00349544\r
-04/02/2020,4,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.00349544\r
-03/02/2020,3,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.00349544\r
-02/02/2020,2,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.00349544\r
-01/02/2020,1,2,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.00349544\r
-31/01/2020,31,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.00349544\r
-30/01/2020,30,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.00349544\r
-29/01/2020,29,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.00349544\r
-28/01/2020,28,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.00349544\r
-27/01/2020,27,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.00349544\r
-26/01/2020,26,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,0.00349544\r
-25/01/2020,25,1,2020,1,0,Nepal,NP,NPL,28608715,Asia,0.00349544\r
-24/01/2020,24,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-23/01/2020,23,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-22/01/2020,22,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-21/01/2020,21,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-20/01/2020,20,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-19/01/2020,19,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-18/01/2020,18,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-17/01/2020,17,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-16/01/2020,16,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-15/01/2020,15,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-14/01/2020,14,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-13/01/2020,13,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,0\r
-12/01/2020,12,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,\r
-11/01/2020,11,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,\r
-10/01/2020,10,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,\r
-09/01/2020,9,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,\r
-08/01/2020,8,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,\r
-07/01/2020,7,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,\r
-06/01/2020,6,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,\r
-05/01/2020,5,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,\r
-04/01/2020,4,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,\r
-03/01/2020,3,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,\r
-02/01/2020,2,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,\r
-01/01/2020,1,1,2020,0,0,Nepal,NP,NPL,28608715,Asia,\r
-31/12/2019,31,12,2019,0,0,Nepal,NP,NPL,28608715,Asia,\r
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-18/08/2020,18,8,2020,481,0,Netherlands,NL,NLD,17282163,Europe,46.34257876\r
-17/08/2020,17,8,2020,506,3,Netherlands,NL,NLD,17282163,Europe,45.71187067\r
-16/08/2020,16,8,2020,652,2,Netherlands,NL,NLD,17282163,Europe,44.58353969\r
-15/08/2020,15,8,2020,636,2,Netherlands,NL,NLD,17282163,Europe,43.30476457\r
-14/08/2020,14,8,2020,577,4,Netherlands,NL,NLD,17282163,Europe,41.58044337\r
-13/08/2020,13,8,2020,654,2,Netherlands,NL,NLD,17282163,Europe,40.22065988\r
-12/08/2020,12,8,2020,779,2,Netherlands,NL,NLD,17282163,Europe,37.86563059\r
-11/08/2020,11,8,2020,575,0,Netherlands,NL,NLD,17282163,Europe,34.64844071\r
-10/08/2020,10,8,2020,577,0,Netherlands,NL,NLD,17282163,Europe,32.50750499\r
-09/08/2020,9,8,2020,486,3,Netherlands,NL,NLD,17282163,Europe,30.40707347\r
-08/08/2020,8,8,2020,519,0,Netherlands,NL,NLD,17282163,Europe,28.38765032\r
-07/08/2020,7,8,2020,601,0,Netherlands,NL,NLD,17282163,Europe,26.48973974\r
-06/08/2020,6,8,2020,426,4,Netherlands,NL,NLD,17282163,Europe,23.95533476\r
-05/08/2020,5,8,2020,540,1,Netherlands,NL,NLD,17282163,Europe,22.46246607\r
-04/08/2020,4,8,2020,372,0,Netherlands,NL,NLD,17282163,Europe,20.28102617\r
-03/08/2020,3,8,2020,311,0,Netherlands,NL,NLD,17282163,Europe,19.19898568\r
-02/08/2020,2,8,2020,431,0,Netherlands,NL,NLD,17282163,Europe,18.23267145\r
-01/08/2020,1,8,2020,338,0,Netherlands,NL,NLD,17282163,Europe,16.47363238\r
-31/07/2020,31,7,2020,342,0,Netherlands,NL,NLD,17282163,Europe,15.11384889\r
-30/07/2020,30,7,2020,247,0,Netherlands,NL,NLD,17282163,Europe,13.70777489\r
-29/07/2020,29,7,2020,223,0,Netherlands,NL,NLD,17282163,Europe,12.89190479\r
-28/07/2020,28,7,2020,205,0,Netherlands,NL,NLD,17282163,Europe,11.90823163\r
-27/07/2020,27,7,2020,214,0,Netherlands,NL,NLD,17282163,Europe,11.13286572\r
-26/07/2020,26,7,2020,137,1,Netherlands,NL,NLD,17282163,Europe,10.47901238\r
-25/07/2020,25,7,2020,191,0,Netherlands,NL,NLD,17282163,Europe,10.15497886\r
-24/07/2020,24,7,2020,163,0,Netherlands,NL,NLD,17282163,Europe,9.29281827\r
-23/07/2020,23,7,2020,168,3,Netherlands,NL,NLD,17282163,Europe,8.65053755\r
-22/07/2020,22,7,2020,163,0,Netherlands,NL,NLD,17282163,Europe,7.97932527\r
-21/07/2020,21,7,2020,185,0,Netherlands,NL,NLD,17282163,Europe,7.25024987\r
-20/07/2020,20,7,2020,144,0,Netherlands,NL,NLD,17282163,Europe,6.38808927\r
-19/07/2020,19,7,2020,127,0,Netherlands,NL,NLD,17282163,Europe,5.97726106\r
-18/07/2020,18,7,2020,103,0,Netherlands,NL,NLD,17282163,Europe,5.59536442\r
-17/07/2020,17,7,2020,99,0,Netherlands,NL,NLD,17282163,Europe,5.43334767\r
-16/07/2020,16,7,2020,106,1,Netherlands,NL,NLD,17282163,Europe,5.30604879\r
-15/07/2020,15,7,2020,53,0,Netherlands,NL,NLD,17282163,Europe,5.05145102\r
-14/07/2020,14,7,2020,71,0,Netherlands,NL,NLD,17282163,Europe,5.03409209\r
-13/07/2020,13,7,2020,101,0,Netherlands,NL,NLD,17282163,Europe,5.06302365\r
-12/07/2020,12,7,2020,81,0,Netherlands,NL,NLD,17282163,Europe,4.90100689\r
-11/07/2020,11,7,2020,42,0,Netherlands,NL,NLD,17282163,Europe,4.83157114\r
-10/07/2020,10,7,2020,52,0,Netherlands,NL,NLD,17282163,Europe,5.11510047\r
-09/07/2020,9,7,2020,52,3,Netherlands,NL,NLD,17282163,Europe,5.4507066\r
-08/07/2020,8,7,2020,37,4,Netherlands,NL,NLD,17282163,Europe,5.62429599\r
-07/07/2020,7,7,2020,36,1,Netherlands,NL,NLD,17282163,Europe,5.78052643\r
-06/07/2020,6,7,2020,73,1,Netherlands,NL,NLD,17282163,Europe,5.9483295\r
-05/07/2020,5,7,2020,61,6,Netherlands,NL,NLD,17282163,Europe,6.05248313\r
-04/07/2020,4,7,2020,75,2,Netherlands,NL,NLD,17282163,Europe,6.13927782\r
-03/07/2020,3,7,2020,77,3,Netherlands,NL,NLD,17282163,Europe,6.32443983\r
-02/07/2020,2,7,2020,62,2,Netherlands,NL,NLD,17282163,Europe,6.54431971\r
-01/07/2020,1,7,2020,50,6,Netherlands,NL,NLD,17282163,Europe,6.86256691\r
-30/06/2020,30,6,2020,76,2,Netherlands,NL,NLD,17282163,Europe,7.37754875\r
-29/06/2020,29,6,2020,73,0,Netherlands,NL,NLD,17282163,Europe,7.89253058\r
-28/06/2020,28,6,2020,69,2,Netherlands,NL,NLD,17282163,Europe,8.29757247\r
-27/06/2020,27,6,2020,91,3,Netherlands,NL,NLD,17282163,Europe,8.93406688\r
-26/06/2020,26,6,2020,110,3,Netherlands,NL,NLD,17282163,Europe,9.62263809\r
-25/06/2020,25,6,2020,82,2,Netherlands,NL,NLD,17282163,Europe,9.93509898\r
-24/06/2020,24,6,2020,64,5,Netherlands,NL,NLD,17282163,Europe,10.52530288\r
-23/06/2020,23,6,2020,65,0,Netherlands,NL,NLD,17282163,Europe,11.10393415\r
-22/06/2020,22,6,2020,91,1,Netherlands,NL,NLD,17282163,Europe,11.68256543\r
-21/06/2020,21,6,2020,76,8,Netherlands,NL,NLD,17282163,Europe,12.53893971\r
-20/06/2020,20,6,2020,107,3,Netherlands,NL,NLD,17282163,Europe,13.15807518\r
-19/06/2020,19,6,2020,115,4,Netherlands,NL,NLD,17282163,Europe,13.75406539\r
-18/06/2020,18,6,2020,117,4,Netherlands,NL,NLD,17282163,Europe,14.29797879\r
-17/06/2020,17,6,2020,139,5,Netherlands,NL,NLD,17282163,Europe,14.11860309\r
-16/06/2020,16,6,2020,165,6,Netherlands,NL,NLD,17282163,Europe,13.90450952\r
-15/06/2020,15,6,2020,143,2,Netherlands,NL,NLD,17282163,Europe,13.54575813\r
-14/06/2020,14,6,2020,179,4,Netherlands,NL,NLD,17282163,Europe,13.78878327\r
-13/06/2020,13,6,2020,210,9,Netherlands,NL,NLD,17282163,Europe,13.51104026\r
-12/06/2020,12,6,2020,164,2,Netherlands,NL,NLD,17282163,Europe,13.31430562\r
-11/06/2020,11,6,2020,184,11,Netherlands,NL,NLD,17282163,Europe,13.41845925\r
-10/06/2020,10,6,2020,164,15,Netherlands,NL,NLD,17282163,Europe,13.45317713\r
-09/06/2020,9,6,2020,165,3,Netherlands,NL,NLD,17282163,Europe,13.27380143\r
-08/06/2020,8,6,2020,239,2,Netherlands,NL,NLD,17282163,Europe,13.52839919\r
-07/06/2020,7,6,2020,183,6,Netherlands,NL,NLD,17282163,Europe,13.14071624\r
-06/06/2020,6,6,2020,210,15,Netherlands,NL,NLD,17282163,Europe,13.10021205\r
-05/06/2020,5,6,2020,209,13,Netherlands,NL,NLD,17282163,Europe,12.97291317\r
-04/06/2020,4,6,2020,86,10,Netherlands,NL,NLD,17282163,Europe,13.22751093\r
-03/06/2020,3,6,2020,102,5,Netherlands,NL,NLD,17282163,Europe,13.87557796\r
-02/06/2020,2,6,2020,103,6,Netherlands,NL,NLD,17282163,Europe,13.91029584\r
-01/06/2020,1,6,2020,185,5,Netherlands,NL,NLD,17282163,Europe,14.15910728\r
-31/05/2020,31,5,2020,131,20,Netherlands,NL,NLD,17282163,Europe,13.81192852\r
-30/05/2020,30,5,2020,176,28,Netherlands,NL,NLD,17282163,Europe,14.14753466\r
-29/05/2020,29,5,2020,182,32,Netherlands,NL,NLD,17282163,Europe,14.28640616\r
-28/05/2020,28,5,2020,190,15,Netherlands,NL,NLD,17282163,Europe,14.79560168\r
-27/05/2020,27,5,2020,133,26,Netherlands,NL,NLD,17282163,Europe,15.00969526\r
-26/05/2020,26,5,2020,209,8,Netherlands,NL,NLD,17282163,Europe,15.37423296\r
-25/05/2020,25,5,2020,172,11,Netherlands,NL,NLD,17282163,Europe,15.09648995\r
-24/05/2020,24,5,2020,176,23,Netherlands,NL,NLD,17282163,Europe,15.51889078\r
-23/05/2020,23,5,2020,188,13,Netherlands,NL,NLD,17282163,Europe,16.17274412\r
-22/05/2020,22,5,2020,253,27,Netherlands,NL,NLD,17282163,Europe,16.93075109\r
-21/05/2020,21,5,2020,198,33,Netherlands,NL,NLD,17282163,Europe,18.09958626\r
-20/05/2020,20,5,2020,108,21,Netherlands,NL,NLD,17282163,Europe,18.29632089\r
-19/05/2020,19,5,2020,146,14,Netherlands,NL,NLD,17282163,Europe,19.50566026\r
-18/05/2020,18,5,2020,125,10,Netherlands,NL,NLD,17282163,Europe,19.81233483\r
-17/05/2020,17,5,2020,189,27,Netherlands,NL,NLD,17282163,Europe,21.02746051\r
-16/05/2020,16,5,2020,200,53,Netherlands,NL,NLD,17282163,Europe,22.50875657\r
-15/05/2020,15,5,2020,270,28,Netherlands,NL,NLD,17282163,Europe,24.09999258\r
-14/05/2020,14,5,2020,227,52,Netherlands,NL,NLD,17282163,Europe,25.51185289\r
-13/05/2020,13,5,2020,196,54,Netherlands,NL,NLD,17282163,Europe,26.43187661\r
-12/05/2020,12,5,2020,161,16,Netherlands,NL,NLD,17282163,Europe,26.28721879\r
-11/05/2020,11,5,2020,245,18,Netherlands,NL,NLD,17282163,Europe,27.67014754\r
-10/05/2020,10,5,2020,289,63,Netherlands,NL,NLD,17282163,Europe,30.04253576\r
-09/05/2020,9,5,2020,319,71,Netherlands,NL,NLD,17282163,Europe,32.16032623\r
-08/05/2020,8,5,2020,455,84,Netherlands,NL,NLD,17282163,Europe,34.97826053\r
-07/05/2020,7,5,2020,232,36,Netherlands,NL,NLD,17282163,Europe,37.47794764\r
-06/05/2020,6,5,2020,317,86,Netherlands,NL,NLD,17282163,Europe,40.2322325\r
-05/05/2020,5,5,2020,199,26,Netherlands,NL,NLD,17282163,Europe,42.61619335\r
-04/05/2020,4,5,2020,335,69,Netherlands,NL,NLD,17282163,Europe,45.80445168\r
-03/05/2020,3,5,2020,445,94,Netherlands,NL,NLD,17282163,Europe,50.03424629\r
-02/05/2020,2,5,2020,475,98,Netherlands,NL,NLD,17282163,Europe,54.05573365\r
-01/05/2020,1,5,2020,514,84,Netherlands,NL,NLD,17282163,Europe,58.45333133\r
-30/04/2020,30,4,2020,386,145,Netherlands,NL,NLD,17282163,Europe,61.6184444\r
-29/04/2020,29,4,2020,171,48,Netherlands,NL,NLD,17282163,Europe,63.63208124\r
-28/04/2020,28,4,2020,400,43,Netherlands,NL,NLD,17282163,Europe,67.66514122\r
-27/04/2020,27,4,2020,655,66,Netherlands,NL,NLD,17282163,Europe,70.92862161\r
-26/04/2020,26,4,2020,655,120,Netherlands,NL,NLD,17282163,Europe,73.93171792\r
-25/04/2020,25,4,2020,806,112,Netherlands,NL,NLD,17282163,Europe,77.75647065\r
-24/04/2020,24,4,2020,887,123,Netherlands,NL,NLD,17282163,Europe,80.81743009\r
-23/04/2020,23,4,2020,708,138,Netherlands,NL,NLD,17282163,Europe,82.70376804\r
-22/04/2020,22,4,2020,729,165,Netherlands,NL,NLD,17282163,Europe,84.21399567\r
-21/04/2020,21,4,2020,750,67,Netherlands,NL,NLD,17282163,Europe,84.49173868\r
-20/04/2020,20,4,2020,1066,83,Netherlands,NL,NLD,17282163,Europe,85.66057385\r
-19/04/2020,19,4,2020,1140,142,Netherlands,NL,NLD,17282163,Europe,86.57481127\r
-18/04/2020,18,4,2020,1235,144,Netherlands,NL,NLD,17282163,Europe,85.20924146\r
-17/04/2020,17,4,2020,1061,181,Netherlands,NL,NLD,17282163,Europe,83.9999021\r
-16/04/2020,16,4,2020,734,189,Netherlands,NL,NLD,17282163,Europe,84.12720098\r
-15/04/2020,15,4,2020,868,122,Netherlands,NL,NLD,17282163,Europe,85.77630011\r
-14/04/2020,14,4,2020,964,86,Netherlands,NL,NLD,17282163,Europe,85.64321491\r
-13/04/2020,13,4,2020,1174,94,Netherlands,NL,NLD,17282163,Europe,85.1803099\r
-12/04/2020,12,4,2020,1316,132,Netherlands,NL,NLD,17282163,Europe,84.775268\r
-11/04/2020,11,4,2020,1335,115,Netherlands,NL,NLD,17282163,Europe,83.8668169\r
-10/04/2020,10,4,2020,1213,148,Netherlands,NL,NLD,17282163,Europe,82.92364793\r
-09/04/2020,9,4,2020,969,147,Netherlands,NL,NLD,17282163,Europe,81.80110325\r
-08/04/2020,8,4,2020,777,234,Netherlands,NL,NLD,17282163,Europe,81.12410466\r
-07/04/2020,7,4,2020,952,101,Netherlands,NL,NLD,17282163,Europe,81.3208393\r
-06/04/2020,6,4,2020,1224,115,Netherlands,NL,NLD,17282163,Europe,78.96581001\r
-05/04/2020,5,4,2020,904,164,Netherlands,NL,NLD,17282163,Europe,75.19892041\r
-04/04/2020,4,4,2020,1026,148,Netherlands,NL,NLD,17282163,Europe,73.65397491\r
-03/04/2020,3,4,2020,1083,166,Netherlands,NL,NLD,17282163,Europe,70.80710904\r
-02/04/2020,2,4,2020,1019,134,Netherlands,NL,NLD,17282163,Europe,66.90713425\r
-01/04/2020,1,4,2020,845,175,Netherlands,NL,NLD,17282163,Europe,63.01294578\r
-31/03/2020,31,3,2020,884,93,Netherlands,NL,NLD,17282163,Europe,59.81311483\r
-30/03/2020,30,3,2020,1104,132,Netherlands,NL,NLD,17282163,Europe,56.30660931\r
-29/03/2020,29,3,2020,1159,93,Netherlands,NL,NLD,17282163,Europe,50.93691108\r
-28/03/2020,28,3,2020,1172,112,Netherlands,NL,NLD,17282163,Europe,45.12745309\r
-27/03/2020,27,3,2020,1019,78,Netherlands,NL,NLD,17282163,Europe,39.44529397\r
-26/03/2020,26,3,2020,852,80,Netherlands,NL,NLD,17282163,Europe,34.191322\r
-25/03/2020,25,3,2020,811,63,Netherlands,NL,NLD,17282163,Europe,29.96152739\r
-24/03/2020,24,3,2020,545,34,Netherlands,NL,NLD,17282163,Europe,25.62179283\r
-23/03/2020,23,3,2020,573,43,Netherlands,NL,NLD,17282163,Europe,22.7922859\r
-22/03/2020,22,3,2020,637,30,Netherlands,NL,NLD,17282163,Europe,19.92227478\r
-21/03/2020,21,3,2020,534,30,Netherlands,NL,NLD,17282163,Europe,16.58357232\r
-20/03/2020,20,3,2020,409,18,Netherlands,NL,NLD,17282163,Europe,13.7598517\r
-19/03/2020,19,3,2020,346,15,Netherlands,NL,NLD,17282163,Europe,11.64784755\r
-18/03/2020,18,3,2020,292,19,Netherlands,NL,NLD,17282163,Europe,9.70364647\r
-17/03/2020,17,3,2020,278,4,Netherlands,NL,NLD,17282163,Europe,8.07190628\r
-16/03/2020,16,3,2020,176,8,Netherlands,NL,NLD,17282163,Europe,6.4922429\r
-15/03/2020,15,3,2020,155,7,Netherlands,NL,NLD,17282163,Europe,5.50856973\r
-14/03/2020,14,3,2020,190,0,Netherlands,NL,NLD,17282163,Europe,4.64062282\r
-13/03/2020,13,3,2020,111,0,Netherlands,NL,NLD,17282163,Europe,3.54700971\r
-12/03/2020,12,3,2020,121,1,Netherlands,NL,NLD,17282163,Europe,2.91051531\r
-11/03/2020,11,3,2020,61,1,Netherlands,NL,NLD,17282163,Europe,2.21037147\r
-10/03/2020,10,3,2020,56,0,Netherlands,NL,NLD,17282163,Europe,1.85740639\r
-09/03/2020,9,3,2020,77,2,Netherlands,NL,NLD,17282163,Europe,1.53337288\r
-08/03/2020,8,3,2020,60,0,Netherlands,NL,NLD,17282163,Europe,1.0878268\r
-07/03/2020,7,3,2020,46,1,Netherlands,NL,NLD,17282163,Europe,0.74064803\r
-06/03/2020,6,3,2020,44,0,Netherlands,NL,NLD,17282163,Europe,0.47447764\r
-05/03/2020,5,3,2020,10,0,Netherlands,NL,NLD,17282163,Europe,0.21987988\r
-04/03/2020,4,3,2020,10,0,Netherlands,NL,NLD,17282163,Europe,0.16201676\r
-03/03/2020,3,3,2020,5,0,Netherlands,NL,NLD,17282163,Europe,0.10415363\r
-02/03/2020,2,3,2020,6,0,Netherlands,NL,NLD,17282163,Europe,0.07522207\r
-01/03/2020,1,3,2020,5,0,Netherlands,NL,NLD,17282163,Europe,0.04050419\r
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-23/06/2020,23,6,2020,2,0,New_Zealand,NZ,NZL,4783062,Oceania,0.2299782\r
-22/06/2020,22,6,2020,2,0,New_Zealand,NZ,NZL,4783062,Oceania,0.18816398\r
-21/06/2020,21,6,2020,2,0,New_Zealand,NZ,NZL,4783062,Oceania,0.14634977\r
-20/06/2020,20,6,2020,2,0,New_Zealand,NZ,NZL,4783062,Oceania,0.10453555\r
-19/06/2020,19,6,2020,0,0,New_Zealand,NZ,NZL,4783062,Oceania,0.06272133\r
-18/06/2020,18,6,2020,1,0,New_Zealand,NZ,NZL,4783062,Oceania,0.06272133\r
-17/06/2020,17,6,2020,0,0,New_Zealand,NZ,NZL,4783062,Oceania,0.04181422\r
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-13/06/2020,13,6,2020,0,0,New_Zealand,NZ,NZL,4783062,Oceania,0\r
-12/06/2020,12,6,2020,0,0,New_Zealand,NZ,NZL,4783062,Oceania,0\r
-11/06/2020,11,6,2020,0,0,New_Zealand,NZ,NZL,4783062,Oceania,0\r
-10/06/2020,10,6,2020,0,0,New_Zealand,NZ,NZL,4783062,Oceania,0\r
-09/06/2020,9,6,2020,0,0,New_Zealand,NZ,NZL,4783062,Oceania,0\r
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-06/06/2020,6,6,2020,0,0,New_Zealand,NZ,NZL,4783062,Oceania,0\r
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-01/06/2020,1,6,2020,0,0,New_Zealand,NZ,NZL,4783062,Oceania,0.10453555\r
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-29/05/2020,29,5,2020,0,0,New_Zealand,NZ,NZL,4783062,Oceania,0.12544266\r
-28/05/2020,28,5,2020,0,1,New_Zealand,NZ,NZL,4783062,Oceania,0.14634977\r
-27/05/2020,27,5,2020,0,0,New_Zealand,NZ,NZL,4783062,Oceania,0.14634977\r
-26/05/2020,26,5,2020,0,0,New_Zealand,NZ,NZL,4783062,Oceania,0.14634977\r
-25/05/2020,25,5,2020,0,0,New_Zealand,NZ,NZL,4783062,Oceania,0.14634977\r
-24/05/2020,24,5,2020,0,0,New_Zealand,NZ,NZL,4783062,Oceania,0.20907109\r
-23/05/2020,23,5,2020,0,0,New_Zealand,NZ,NZL,4783062,Oceania,0.25088531\r
-22/05/2020,22,5,2020,1,0,New_Zealand,NZ,NZL,4783062,Oceania,0.27179242\r
-21/05/2020,21,5,2020,0,0,New_Zealand,NZ,NZL,4783062,Oceania,0.29269953\r
-20/05/2020,20,5,2020,0,0,New_Zealand,NZ,NZL,4783062,Oceania,0.31360664\r
-19/05/2020,19,5,2020,4,0,New_Zealand,NZ,NZL,4783062,Oceania,0.33451375\r
-18/05/2020,18,5,2020,0,0,New_Zealand,NZ,NZL,4783062,Oceania,0.25088531\r
-17/05/2020,17,5,2020,1,0,New_Zealand,NZ,NZL,4783062,Oceania,0.27179242\r
-16/05/2020,16,5,2020,0,0,New_Zealand,NZ,NZL,4783062,Oceania,0.29269953\r
-15/05/2020,15,5,2020,1,0,New_Zealand,NZ,NZL,4783062,Oceania,0.33451375\r
-14/05/2020,14,5,2020,0,0,New_Zealand,NZ,NZL,4783062,Oceania,0.37632797\r
-13/05/2020,13,5,2020,0,0,New_Zealand,NZ,NZL,4783062,Oceania,0.4390493\r
-12/05/2020,12,5,2020,0,0,New_Zealand,NZ,NZL,4783062,Oceania,0.48086351\r
-11/05/2020,11,5,2020,3,0,New_Zealand,NZ,NZL,4783062,Oceania,0.52267773\r
-10/05/2020,10,5,2020,2,0,New_Zealand,NZ,NZL,4783062,Oceania,0.48086351\r
-09/05/2020,9,5,2020,1,0,New_Zealand,NZ,NZL,4783062,Oceania,0.52267773\r
-08/05/2020,8,5,2020,2,0,New_Zealand,NZ,NZL,4783062,Oceania,0.56449195\r
-07/05/2020,7,5,2020,1,0,New_Zealand,NZ,NZL,4783062,Oceania,0.56449195\r
-06/05/2020,6,5,2020,1,1,New_Zealand,NZ,NZL,4783062,Oceania,0.54358484\r
-05/05/2020,5,5,2020,0,0,New_Zealand,NZ,NZL,4783062,Oceania,0.62721328\r
-04/05/2020,4,5,2020,1,0,New_Zealand,NZ,NZL,4783062,Oceania,0.6690275\r
-03/05/2020,3,5,2020,2,0,New_Zealand,NZ,NZL,4783062,Oceania,0.79447015\r
-02/05/2020,2,5,2020,2,1,New_Zealand,NZ,NZL,4783062,Oceania,0.83628437\r
-01/05/2020,1,5,2020,3,0,New_Zealand,NZ,NZL,4783062,Oceania,0.96172703\r
-30/04/2020,30,4,2020,3,0,New_Zealand,NZ,NZL,4783062,Oceania,0.94081992\r
-29/04/2020,29,4,2020,2,0,New_Zealand,NZ,NZL,4783062,Oceania,1.00354125\r
-28/04/2020,28,4,2020,2,0,New_Zealand,NZ,NZL,4783062,Oceania,1.08716968\r
-27/04/2020,27,4,2020,1,1,New_Zealand,NZ,NZL,4783062,Oceania,1.21261234\r
-26/04/2020,26,4,2020,4,0,New_Zealand,NZ,NZL,4783062,Oceania,1.50531187\r
-25/04/2020,25,4,2020,3,1,New_Zealand,NZ,NZL,4783062,Oceania,1.71438296\r
-24/04/2020,24,4,2020,2,1,New_Zealand,NZ,NZL,4783062,Oceania,2.06980382\r
-23/04/2020,23,4,2020,0,2,New_Zealand,NZ,NZL,4783062,Oceania,2.50885312\r
-22/04/2020,22,4,2020,5,1,New_Zealand,NZ,NZL,4783062,Oceania,2.98971663\r
-21/04/2020,21,4,2020,2,1,New_Zealand,NZ,NZL,4783062,Oceania,3.42876592\r
-20/04/2020,20,4,2020,7,0,New_Zealand,NZ,NZL,4783062,Oceania,4.0559792\r
-19/04/2020,19,4,2020,4,1,New_Zealand,NZ,NZL,4783062,Oceania,4.7250067\r
-18/04/2020,18,4,2020,8,0,New_Zealand,NZ,NZL,4783062,Oceania,5.64491951\r
-17/04/2020,17,4,2020,2,2,New_Zealand,NZ,NZL,4783062,Oceania,6.56483232\r
-16/04/2020,16,4,2020,6,0,New_Zealand,NZ,NZL,4783062,Oceania,7.54746646\r
-15/04/2020,15,4,2020,6,0,New_Zealand,NZ,NZL,4783062,Oceania,9.01096411\r
-14/04/2020,14,4,2020,8,4,New_Zealand,NZ,NZL,4783062,Oceania,8.88552145\r
-13/04/2020,13,4,2020,15,1,New_Zealand,NZ,NZL,4783062,Oceania,10.70443996\r
-12/04/2020,12,4,2020,14,0,New_Zealand,NZ,NZL,4783062,Oceania,11.97977363\r
-11/04/2020,11,4,2020,20,2,New_Zealand,NZ,NZL,4783062,Oceania,12.94150065\r
-10/04/2020,10,4,2020,23,1,New_Zealand,NZ,NZL,4783062,Oceania,14.15411299\r
-09/04/2020,9,4,2020,23,0,New_Zealand,NZ,NZL,4783062,Oceania,15.26218979\r
-08/04/2020,8,4,2020,26,0,New_Zealand,NZ,NZL,4783062,Oceania,16.30754525\r
-07/04/2020,7,4,2020,32,0,New_Zealand,NZ,NZL,4783062,Oceania,16.74659455\r
-06/04/2020,6,4,2020,39,0,New_Zealand,NZ,NZL,4783062,Oceania,16.91385142\r
-05/04/2020,5,4,2020,48,0,New_Zealand,NZ,NZL,4783062,Oceania,16.85113009\r
-04/04/2020,4,4,2020,52,0,New_Zealand,NZ,NZL,4783062,Oceania,16.11938127\r
-03/04/2020,3,4,2020,49,0,New_Zealand,NZ,NZL,4783062,Oceania,15.32491111\r
-02/04/2020,2,4,2020,76,0,New_Zealand,NZ,NZL,4783062,Oceania,14.53044096\r
-01/04/2020,1,4,2020,0,0,New_Zealand,NZ,NZL,4783062,Oceania,13.10875753\r
-31/03/2020,31,3,2020,95,0,New_Zealand,NZ,NZL,4783062,Oceania,13.35964284\r
-30/03/2020,30,3,2020,76,0,New_Zealand,NZ,NZL,4783062,Oceania,11.41528168\r
-29/03/2020,29,3,2020,60,1,New_Zealand,NZ,NZL,4783062,Oceania,9.84724848\r
-28/03/2020,28,3,2020,78,0,New_Zealand,NZ,NZL,4783062,Oceania,8.61372903\r
-27/03/2020,27,3,2020,76,0,New_Zealand,NZ,NZL,4783062,Oceania,7.00388161\r
-26/03/2020,26,3,2020,73,0,New_Zealand,NZ,NZL,4783062,Oceania,5.43584842\r
-25/03/2020,25,3,2020,47,0,New_Zealand,NZ,NZL,4783062,Oceania,3.93053655\r
-24/03/2020,24,3,2020,40,0,New_Zealand,NZ,NZL,4783062,Oceania,2.94790241\r
-23/03/2020,23,3,2020,36,0,New_Zealand,NZ,NZL,4783062,Oceania,2.11161804\r
-22/03/2020,22,3,2020,13,0,New_Zealand,NZ,NZL,4783062,Oceania,1.3589621\r
-21/03/2020,21,3,2020,14,0,New_Zealand,NZ,NZL,4783062,Oceania,1.10807679\r
-20/03/2020,20,3,2020,11,0,New_Zealand,NZ,NZL,4783062,Oceania,0.81537726\r
-19/03/2020,19,3,2020,8,0,New_Zealand,NZ,NZL,4783062,Oceania,0.58539906\r
-18/03/2020,18,3,2020,12,0,New_Zealand,NZ,NZL,4783062,Oceania,0.41814219\r
-15/03/2020,15,3,2020,2,0,New_Zealand,NZ,NZL,4783062,Oceania,0.16725687\r
-14/03/2020,14,3,2020,1,0,New_Zealand,NZ,NZL,4783062,Oceania,0.12544266\r
-07/03/2020,7,3,2020,1,0,New_Zealand,NZ,NZL,4783062,Oceania,0.10453555\r
-06/03/2020,6,3,2020,1,0,New_Zealand,NZ,NZL,4783062,Oceania,0.08362844\r
-05/03/2020,5,3,2020,1,0,New_Zealand,NZ,NZL,4783062,Oceania,0.06272133\r
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-14/08/2020,14,8,2020,140,2,North_Macedonia,MK,MKD,2077132,Europe,83.48049137\r
-13/08/2020,13,8,2020,252,2,North_Macedonia,MK,MKD,2077132,Europe,82.46948196\r
-12/08/2020,12,8,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,79.38831042\r
-11/08/2020,11,8,2020,109,1,North_Macedonia,MK,MKD,2077132,Europe,84.29892756\r
-10/08/2020,10,8,2020,85,4,North_Macedonia,MK,MKD,2077132,Europe,85.21365036\r
-09/08/2020,9,8,2020,200,4,North_Macedonia,MK,MKD,2077132,Europe,88.43925181\r
-08/08/2020,8,8,2020,282,8,North_Macedonia,MK,MKD,2077132,Europe,85.40622358\r
-07/08/2020,7,8,2020,88,6,North_Macedonia,MK,MKD,2077132,Europe,77.99215457\r
-06/08/2020,6,8,2020,61,5,North_Macedonia,MK,MKD,2077132,Europe,79.62902695\r
-05/08/2020,5,8,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,83.19163154\r
-04/08/2020,4,8,2020,86,3,North_Macedonia,MK,MKD,2077132,Europe,91.0389903\r
-03/08/2020,3,8,2020,154,4,North_Macedonia,MK,MKD,2077132,Europe,92.53143276\r
-02/08/2020,2,8,2020,138,7,North_Macedonia,MK,MKD,2077132,Europe,91.0389903\r
-01/08/2020,1,8,2020,139,6,North_Macedonia,MK,MKD,2077132,Europe,95.80517752\r
-31/07/2020,31,7,2020,119,4,North_Macedonia,MK,MKD,2077132,Europe,96.81618693\r
-30/07/2020,30,7,2020,188,5,North_Macedonia,MK,MKD,2077132,Europe,95.42003108\r
-29/07/2020,29,7,2020,102,5,North_Macedonia,MK,MKD,2077132,Europe,95.70889091\r
-28/07/2020,28,7,2020,128,6,North_Macedonia,MK,MKD,2077132,Europe,97.10504677\r
-27/07/2020,27,7,2020,152,0,North_Macedonia,MK,MKD,2077132,Europe,95.08302794\r
-26/07/2020,26,7,2020,137,9,North_Macedonia,MK,MKD,2077132,Europe,94.6978815\r
-25/07/2020,25,7,2020,128,6,North_Macedonia,MK,MKD,2077132,Europe,97.58647982\r
-24/07/2020,24,7,2020,122,3,North_Macedonia,MK,MKD,2077132,Europe,101.19722772\r
-23/07/2020,23,7,2020,135,10,North_Macedonia,MK,MKD,2077132,Europe,103.31553315\r
-22/07/2020,22,7,2020,163,0,North_Macedonia,MK,MKD,2077132,Europe,104.56725909\r
-21/07/2020,21,7,2020,117,10,North_Macedonia,MK,MKD,2077132,Europe,102.40081035\r
-20/07/2020,20,7,2020,123,8,North_Macedonia,MK,MKD,2077132,Europe,100.42693483\r
-19/07/2020,19,7,2020,237,8,North_Macedonia,MK,MKD,2077132,Europe,99.99364508\r
-18/07/2020,18,7,2020,160,5,North_Macedonia,MK,MKD,2077132,Europe,102.49709696\r
-17/07/2020,17,7,2020,90,8,North_Macedonia,MK,MKD,2077132,Europe,94.79416811\r
-16/07/2020,16,7,2020,194,4,North_Macedonia,MK,MKD,2077132,Europe,98.79006245\r
-15/07/2020,15,7,2020,131,4,North_Macedonia,MK,MKD,2077132,Europe,95.22745786\r
-14/07/2020,14,7,2020,86,3,North_Macedonia,MK,MKD,2077132,Europe,94.98674133\r
-13/07/2020,13,7,2020,144,7,North_Macedonia,MK,MKD,2077132,Europe,97.20133338\r
-12/07/2020,12,7,2020,197,8,North_Macedonia,MK,MKD,2077132,Europe,98.74191915\r
-11/07/2020,11,7,2020,203,6,North_Macedonia,MK,MKD,2077132,Europe,96.4791838\r
-10/07/2020,10,7,2020,166,2,North_Macedonia,MK,MKD,2077132,Europe,94.55345159\r
-09/07/2020,9,7,2020,161,8,North_Macedonia,MK,MKD,2077132,Europe,93.92758862\r
-08/07/2020,8,7,2020,118,5,North_Macedonia,MK,MKD,2077132,Europe,92.72400599\r
-07/07/2020,7,7,2020,76,5,North_Macedonia,MK,MKD,2077132,Europe,92.72400599\r
-06/07/2020,6,7,2020,114,7,North_Macedonia,MK,MKD,2077132,Europe,93.39801226\r
-05/07/2020,5,7,2020,289,13,North_Macedonia,MK,MKD,2077132,Europe,92.77214929\r
-04/07/2020,4,7,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,87.76524554\r
-03/07/2020,3,7,2020,173,15,North_Macedonia,MK,MKD,2077132,Europe,95.27560117\r
-02/07/2020,2,7,2020,120,4,North_Macedonia,MK,MKD,2077132,Europe,95.70889091\r
-01/07/2020,1,7,2020,126,4,North_Macedonia,MK,MKD,2077132,Europe,99.2233522\r
-30/06/2020,30,6,2020,132,12,North_Macedonia,MK,MKD,2077132,Europe,99.51221203\r
-29/06/2020,29,6,2020,176,9,North_Macedonia,MK,MKD,2077132,Europe,97.97162626\r
-28/06/2020,28,6,2020,150,9,North_Macedonia,MK,MKD,2077132,Europe,96.96061685\r
-27/06/2020,27,6,2020,163,3,North_Macedonia,MK,MKD,2077132,Europe,99.17520889\r
-26/06/2020,26,6,2020,153,6,North_Macedonia,MK,MKD,2077132,Europe,99.2233522\r
-25/06/2020,25,6,2020,136,8,North_Macedonia,MK,MKD,2077132,Europe,100.28250492\r
-24/06/2020,24,6,2020,118,4,North_Macedonia,MK,MKD,2077132,Europe,99.75292856\r
-23/06/2020,23,6,2020,90,9,North_Macedonia,MK,MKD,2077132,Europe,98.26048609\r
-22/06/2020,22,6,2020,101,5,North_Macedonia,MK,MKD,2077132,Europe,100.04178839\r
-21/06/2020,21,6,2020,185,11,North_Macedonia,MK,MKD,2077132,Europe,100.52322144\r
-20/06/2020,20,6,2020,156,6,North_Macedonia,MK,MKD,2077132,Europe,97.63462312\r
-19/06/2020,19,6,2020,182,6,North_Macedonia,MK,MKD,2077132,Europe,98.79006245\r
-18/06/2020,18,6,2020,193,9,North_Macedonia,MK,MKD,2077132,Europe,95.80517752\r
-17/06/2020,17,6,2020,132,8,North_Macedonia,MK,MKD,2077132,Europe,91.37599344\r
-16/06/2020,16,6,2020,100,5,North_Macedonia,MK,MKD,2077132,Europe,88.67996834\r
-15/06/2020,15,6,2020,155,9,North_Macedonia,MK,MKD,2077132,Europe,88.15039198\r
-14/06/2020,14,6,2020,196,8,North_Macedonia,MK,MKD,2077132,Europe,83.67306459\r
-13/06/2020,13,6,2020,164,2,North_Macedonia,MK,MKD,2077132,Europe,75.87384913\r
-12/06/2020,12,6,2020,175,5,North_Macedonia,MK,MKD,2077132,Europe,70.48179894\r
-11/06/2020,11,6,2020,125,7,North_Macedonia,MK,MKD,2077132,Europe,63.88616612\r
-10/06/2020,10,6,2020,87,1,North_Macedonia,MK,MKD,2077132,Europe,59.07183559\r
-09/06/2020,9,6,2020,127,3,North_Macedonia,MK,MKD,2077132,Europe,55.65366091\r
-08/06/2020,8,6,2020,111,2,North_Macedonia,MK,MKD,2077132,Europe,50.55047055\r
-07/06/2020,7,6,2020,125,2,North_Macedonia,MK,MKD,2077132,Europe,46.98786596\r
-06/06/2020,6,6,2020,180,2,North_Macedonia,MK,MKD,2077132,Europe,41.93281891\r
-05/06/2020,5,6,2020,120,2,North_Macedonia,MK,MKD,2077132,Europe,34.37431998\r
-04/06/2020,4,6,2020,101,4,North_Macedonia,MK,MKD,2077132,Europe,30.52285555\r
-03/06/2020,3,6,2020,76,1,North_Macedonia,MK,MKD,2077132,Europe,26.57510452\r
-02/06/2020,2,6,2020,89,7,North_Macedonia,MK,MKD,2077132,Europe,23.97536603\r
-01/06/2020,1,6,2020,62,2,North_Macedonia,MK,MKD,2077132,Europe,20.8941945\r
-31/05/2020,31,5,2020,34,5,North_Macedonia,MK,MKD,2077132,Europe,19.35360873\r
-30/05/2020,30,5,2020,52,4,North_Macedonia,MK,MKD,2077132,Europe,18.77588906\r
-29/05/2020,29,5,2020,38,3,North_Macedonia,MK,MKD,2077132,Europe,17.09087338\r
-28/05/2020,28,5,2020,25,3,North_Macedonia,MK,MKD,2077132,Europe,16.65758363\r
-27/05/2020,27,5,2020,16,3,North_Macedonia,MK,MKD,2077132,Europe,16.4168671\r
-26/05/2020,26,5,2020,21,0,North_Macedonia,MK,MKD,2077132,Europe,16.12800727\r
-25/05/2020,25,5,2020,37,0,North_Macedonia,MK,MKD,2077132,Europe,16.17615058\r
-24/05/2020,24,5,2020,20,1,North_Macedonia,MK,MKD,2077132,Europe,15.35771439\r
-23/05/2020,23,5,2020,23,1,North_Macedonia,MK,MKD,2077132,Europe,16.12800727\r
-22/05/2020,22,5,2020,40,1,North_Macedonia,MK,MKD,2077132,Europe,15.69471752\r
-21/05/2020,21,5,2020,19,4,North_Macedonia,MK,MKD,2077132,Europe,15.35771439\r
-20/05/2020,20,5,2020,22,2,North_Macedonia,MK,MKD,2077132,Europe,15.06885456\r
-19/05/2020,19,5,2020,25,3,North_Macedonia,MK,MKD,2077132,Europe,14.39484828\r
-18/05/2020,18,5,2020,30,3,North_Macedonia,MK,MKD,2077132,Europe,13.52826879\r
-17/05/2020,17,5,2020,22,1,North_Macedonia,MK,MKD,2077132,Europe,12.32468615\r
-16/05/2020,16,5,2020,17,2,North_Macedonia,MK,MKD,2077132,Europe,11.8432531\r
-15/05/2020,15,5,2020,29,0,North_Macedonia,MK,MKD,2077132,Europe,12.42097276\r
-14/05/2020,14,5,2020,20,3,North_Macedonia,MK,MKD,2077132,Europe,12.13211293\r
-13/05/2020,13,5,2020,10,1,North_Macedonia,MK,MKD,2077132,Europe,12.18025624\r
-12/05/2020,12,5,2020,22,0,North_Macedonia,MK,MKD,2077132,Europe,12.7579759\r
-11/05/2020,11,5,2020,20,0,North_Macedonia,MK,MKD,2077132,Europe,12.32468615\r
-10/05/2020,10,5,2020,36,1,North_Macedonia,MK,MKD,2077132,Europe,12.27654285\r
-09/05/2020,9,5,2020,14,1,North_Macedonia,MK,MKD,2077132,Europe,12.51725937\r
-08/05/2020,8,5,2020,33,1,North_Macedonia,MK,MKD,2077132,Europe,13.09497904\r
-07/05/2020,7,5,2020,13,2,North_Macedonia,MK,MKD,2077132,Europe,13.48012548\r
-06/05/2020,6,5,2020,8,1,North_Macedonia,MK,MKD,2077132,Europe,14.20227506\r
-05/05/2020,5,5,2020,7,1,North_Macedonia,MK,MKD,2077132,Europe,14.10598845\r
-04/05/2020,4,5,2020,5,2,North_Macedonia,MK,MKD,2077132,Europe,14.63556481\r
-03/05/2020,3,5,2020,12,1,North_Macedonia,MK,MKD,2077132,Europe,16.17615058\r
-02/05/2020,2,5,2020,29,4,North_Macedonia,MK,MKD,2077132,Europe,18.15002609\r
-01/05/2020,1,5,2020,23,4,North_Macedonia,MK,MKD,2077132,Europe,18.48702923\r
-30/04/2020,30,4,2020,21,2,North_Macedonia,MK,MKD,2077132,Europe,22.53106687\r
-29/04/2020,29,4,2020,22,6,North_Macedonia,MK,MKD,2077132,Europe,24.69751561\r
-28/04/2020,28,4,2020,13,4,North_Macedonia,MK,MKD,2077132,Europe,26.23810138\r
-27/04/2020,27,4,2020,19,2,North_Macedonia,MK,MKD,2077132,Europe,26.86396435\r
-26/04/2020,26,4,2020,41,2,North_Macedonia,MK,MKD,2077132,Europe,29.22298631\r
-25/04/2020,25,4,2020,26,1,North_Macedonia,MK,MKD,2077132,Europe,29.60813275\r
-24/04/2020,24,4,2020,41,0,North_Macedonia,MK,MKD,2077132,Europe,30.66728547\r
-23/04/2020,23,4,2020,28,1,North_Macedonia,MK,MKD,2077132,Europe,30.908002\r
-22/04/2020,22,4,2020,6,1,North_Macedonia,MK,MKD,2077132,Europe,30.42656894\r
-21/04/2020,21,4,2020,18,3,North_Macedonia,MK,MKD,2077132,Europe,31.53386496\r
-20/04/2020,20,4,2020,37,2,North_Macedonia,MK,MKD,2077132,Europe,34.85575303\r
-19/04/2020,19,4,2020,53,0,North_Macedonia,MK,MKD,2077132,Europe,33.07445073\r
-18/04/2020,18,4,2020,36,3,North_Macedonia,MK,MKD,2077132,Europe,33.07445073\r
-17/04/2020,17,4,2020,107,1,North_Macedonia,MK,MKD,2077132,Europe,35.00018294\r
-16/04/2020,16,4,2020,66,1,North_Macedonia,MK,MKD,2077132,Europe,29.84884928\r
-15/04/2020,15,4,2020,54,6,North_Macedonia,MK,MKD,2077132,Europe,27.87497376\r
-14/04/2020,14,4,2020,26,4,North_Macedonia,MK,MKD,2077132,Europe,27.39354071\r
-13/04/2020,13,4,2020,68,0,North_Macedonia,MK,MKD,2077132,Europe,27.39354071\r
-12/04/2020,12,4,2020,49,2,North_Macedonia,MK,MKD,2077132,Europe,24.98637544\r
-11/04/2020,11,4,2020,48,0,North_Macedonia,MK,MKD,2077132,Europe,23.6865062\r
-10/04/2020,10,4,2020,46,2,North_Macedonia,MK,MKD,2077132,Europe,22.24220704\r
-09/04/2020,9,4,2020,18,4,North_Macedonia,MK,MKD,2077132,Europe,21.18305433\r
-08/04/2020,8,4,2020,29,5,North_Macedonia,MK,MKD,2077132,Europe,21.71263069\r
-07/04/2020,7,4,2020,87,4,North_Macedonia,MK,MKD,2077132,Europe,20.8941945\r
-06/04/2020,6,4,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,17.76487965\r
-05/04/2020,5,4,2020,53,5,North_Macedonia,MK,MKD,2077132,Europe,19.1610355\r
-04/04/2020,4,4,2020,76,1,North_Macedonia,MK,MKD,2077132,Europe,17.3315899\r
-03/04/2020,3,4,2020,0,1,North_Macedonia,MK,MKD,2077132,Europe,14.73185142\r
-02/04/2020,2,4,2020,25,1,North_Macedonia,MK,MKD,2077132,Europe,15.02071125\r
-01/04/2020,1,4,2020,44,2,North_Macedonia,MK,MKD,2077132,Europe,14.34670498\r
-31/03/2020,31,3,2020,26,1,North_Macedonia,MK,MKD,2077132,Europe,12.80611921\r
-30/03/2020,30,3,2020,18,2,North_Macedonia,MK,MKD,2077132,Europe,11.8432531\r
-29/03/2020,29,3,2020,22,1,North_Macedonia,MK,MKD,2077132,Europe,10.97667361\r
-28/03/2020,28,3,2020,18,0,North_Macedonia,MK,MKD,2077132,Europe,10.11009411\r
-27/03/2020,27,3,2020,24,1,North_Macedonia,MK,MKD,2077132,Europe,9.33980123\r
-26/03/2020,26,3,2020,29,0,North_Macedonia,MK,MKD,2077132,Europe,8.37693512\r
-25/03/2020,25,3,2020,12,0,North_Macedonia,MK,MKD,2077132,Europe,7.07706588\r
-24/03/2020,24,3,2020,22,1,North_Macedonia,MK,MKD,2077132,Europe,6.49934621\r
-23/03/2020,23,3,2020,29,1,North_Macedonia,MK,MKD,2077132,Europe,5.4401935\r
-22/03/2020,22,3,2020,15,0,North_Macedonia,MK,MKD,2077132,Europe,4.04403764\r
-21/03/2020,21,3,2020,22,0,North_Macedonia,MK,MKD,2077132,Europe,3.32188806\r
-20/03/2020,20,3,2020,6,0,North_Macedonia,MK,MKD,2077132,Europe,2.31087865\r
-19/03/2020,19,3,2020,11,0,North_Macedonia,MK,MKD,2077132,Europe,2.02201882\r
-18/03/2020,18,3,2020,12,0,North_Macedonia,MK,MKD,2077132,Europe,1.49244246\r
-17/03/2020,17,3,2020,6,0,North_Macedonia,MK,MKD,2077132,Europe,0.9147228\r
-16/03/2020,16,3,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0.62586297\r
-14/03/2020,14,3,2020,4,0,North_Macedonia,MK,MKD,2077132,Europe,0.62586297\r
-13/03/2020,13,3,2020,2,0,North_Macedonia,MK,MKD,2077132,Europe,0.43328975\r
-11/03/2020,11,3,2020,4,0,North_Macedonia,MK,MKD,2077132,Europe,0.33700314\r
-07/03/2020,7,3,2020,2,0,North_Macedonia,MK,MKD,2077132,Europe,0.14442992\r
-02/03/2020,2,3,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0.04814331\r
-01/03/2020,1,3,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0.04814331\r
-29/02/2020,29,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0.04814331\r
-28/02/2020,28,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0.04814331\r
-27/02/2020,27,2,2020,1,0,North_Macedonia,MK,MKD,2077132,Europe,0.04814331\r
-26/02/2020,26,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-25/02/2020,25,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-24/02/2020,24,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-23/02/2020,23,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-22/02/2020,22,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-21/02/2020,21,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-20/02/2020,20,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-19/02/2020,19,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-18/02/2020,18,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-17/02/2020,17,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-16/02/2020,16,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-15/02/2020,15,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-14/02/2020,14,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-13/02/2020,13,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-12/02/2020,12,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-11/02/2020,11,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-10/02/2020,10,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-09/02/2020,9,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-08/02/2020,8,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-07/02/2020,7,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-06/02/2020,6,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-05/02/2020,5,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-04/02/2020,4,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-03/02/2020,3,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-02/02/2020,2,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-01/02/2020,1,2,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-31/01/2020,31,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-30/01/2020,30,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-29/01/2020,29,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-28/01/2020,28,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-27/01/2020,27,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-26/01/2020,26,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-25/01/2020,25,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-24/01/2020,24,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-23/01/2020,23,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-22/01/2020,22,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-21/01/2020,21,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-20/01/2020,20,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-19/01/2020,19,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-18/01/2020,18,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-17/01/2020,17,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-16/01/2020,16,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-15/01/2020,15,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-14/01/2020,14,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-13/01/2020,13,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,0\r
-12/01/2020,12,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,\r
-11/01/2020,11,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,\r
-10/01/2020,10,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,\r
-09/01/2020,9,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,\r
-08/01/2020,8,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,\r
-07/01/2020,7,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,\r
-06/01/2020,6,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,\r
-05/01/2020,5,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,\r
-04/01/2020,4,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,\r
-03/01/2020,3,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,\r
-02/01/2020,2,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,\r
-01/01/2020,1,1,2020,0,0,North_Macedonia,MK,MKD,2077132,Europe,\r
-31/12/2019,31,12,2019,0,0,North_Macedonia,MK,MKD,2077132,Europe,\r
-19/08/2020,19,8,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,13.98283607\r
-18/08/2020,18,8,2020,4,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,13.98283607\r
-17/08/2020,17,8,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,6.99141803\r
-16/08/2020,16,8,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,8.73927254\r
-15/08/2020,15,8,2020,1,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,13.98283607\r
-14/08/2020,14,8,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,12.23498156\r
-13/08/2020,13,8,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,12.23498156\r
-12/08/2020,12,8,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,15.73069058\r
-11/08/2020,11,8,2020,1,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,15.73069058\r
-10/08/2020,10,8,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,13.98283607\r
-09/08/2020,9,8,2020,1,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,13.98283607\r
-08/08/2020,8,8,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,15.73069058\r
-07/08/2020,7,8,2020,1,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,15.73069058\r
-06/08/2020,6,8,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,13.98283607\r
-05/08/2020,5,8,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,13.98283607\r
-04/08/2020,4,8,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,13.98283607\r
-03/08/2020,3,8,2020,1,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,15.73069058\r
-02/08/2020,2,8,2020,3,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,13.98283607\r
-01/08/2020,1,8,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,8.73927254\r
-31/07/2020,31,7,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,8.73927254\r
-30/07/2020,30,7,2020,2,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,10.48712705\r
-29/07/2020,29,7,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,6.99141803\r
-28/07/2020,28,7,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,12.23498156\r
-27/07/2020,27,7,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,12.23498156\r
-26/07/2020,26,7,2020,2,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,12.23498156\r
-25/07/2020,25,7,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,12.23498156\r
-24/07/2020,24,7,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,12.23498156\r
-23/07/2020,23,7,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,12.23498156\r
-22/07/2020,22,7,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,12.23498156\r
-21/07/2020,21,7,2020,1,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,12.23498156\r
-20/07/2020,20,7,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,10.48712705\r
-19/07/2020,19,7,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,10.48712705\r
-18/07/2020,18,7,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,10.48712705\r
-17/07/2020,17,7,2020,1,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,10.48712705\r
-16/07/2020,16,7,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,10.48712705\r
-15/07/2020,15,7,2020,3,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,10.48712705\r
-14/07/2020,14,7,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,5.24356353\r
-13/07/2020,13,7,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,5.24356353\r
-12/07/2020,12,7,2020,2,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,5.24356353\r
-11/07/2020,11,7,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,1.74785451\r
-10/07/2020,10,7,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,1.74785451\r
-09/07/2020,9,7,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,1.74785451\r
-08/07/2020,8,7,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,1.74785451\r
-07/07/2020,7,7,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,1.74785451\r
-06/07/2020,6,7,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,1.74785451\r
-05/07/2020,5,7,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,1.74785451\r
-04/07/2020,4,7,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,1.74785451\r
-03/07/2020,3,7,2020,1,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,1.74785451\r
-02/07/2020,2,7,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,0\r
-01/07/2020,1,7,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,0\r
-30/06/2020,30,6,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,0\r
-29/06/2020,29,6,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,0\r
-28/06/2020,28,6,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,0\r
-27/06/2020,27,6,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,0\r
-26/06/2020,26,6,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,0\r
-25/06/2020,25,6,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,0\r
-24/06/2020,24,6,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,0\r
-23/06/2020,23,6,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,3.49570902\r
-22/06/2020,22,6,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,5.24356353\r
-21/06/2020,21,6,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,5.24356353\r
-20/06/2020,20,6,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,6.99141803\r
-19/06/2020,19,6,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,6.99141803\r
-18/06/2020,18,6,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,10.48712705\r
-17/06/2020,17,6,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,12.23498156\r
-16/06/2020,16,6,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,13.98283607\r
-15/06/2020,15,6,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,13.98283607\r
-14/06/2020,14,6,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,13.98283607\r
-13/06/2020,13,6,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,13.98283607\r
-12/06/2020,12,6,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,13.98283607\r
-11/06/2020,11,6,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,13.98283607\r
-10/06/2020,10,6,2020,2,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,13.98283607\r
-09/06/2020,9,6,2020,1,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,10.48712705\r
-08/06/2020,8,6,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,8.73927254\r
-07/06/2020,7,6,2020,1,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,8.73927254\r
-06/06/2020,6,6,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,6.99141803\r
-05/06/2020,5,6,2020,2,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,6.99141803\r
-04/06/2020,4,6,2020,1,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,3.49570902\r
-03/06/2020,3,6,2020,1,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,3.49570902\r
-02/06/2020,2,6,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,1.74785451\r
-01/06/2020,1,6,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,1.74785451\r
-31/05/2020,31,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,1.74785451\r
-30/05/2020,30,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,5.24356353\r
-29/05/2020,29,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,5.24356353\r
-28/05/2020,28,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,5.24356353\r
-27/05/2020,27,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,5.24356353\r
-26/05/2020,26,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,5.24356353\r
-25/05/2020,25,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,10.48712705\r
-24/05/2020,24,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,10.48712705\r
-23/05/2020,23,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,12.23498156\r
-22/05/2020,22,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,12.23498156\r
-21/05/2020,21,5,2020,1,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,12.23498156\r
-20/05/2020,20,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,12.23498156\r
-19/05/2020,19,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,12.23498156\r
-18/05/2020,18,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,12.23498156\r
-17/05/2020,17,5,2020,2,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,12.23498156\r
-16/05/2020,16,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,8.73927254\r
-15/05/2020,15,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,8.73927254\r
-14/05/2020,14,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,8.73927254\r
-13/05/2020,13,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,8.73927254\r
-12/05/2020,12,5,2020,3,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,8.73927254\r
-11/05/2020,11,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,3.49570902\r
-10/05/2020,10,5,2020,1,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,3.49570902\r
-09/05/2020,9,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,1.74785451\r
-08/05/2020,8,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,1.74785451\r
-07/05/2020,7,5,2020,1,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,1.74785451\r
-06/05/2020,6,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,0\r
-05/05/2020,5,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,0\r
-04/05/2020,4,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,0\r
-03/05/2020,3,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,0\r
-02/05/2020,2,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,0\r
-01/05/2020,1,5,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,1.74785451\r
-30/04/2020,30,4,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,1.74785451\r
-29/04/2020,29,4,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,1.74785451\r
-28/04/2020,28,4,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,5.24356353\r
-27/04/2020,27,4,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,5.24356353\r
-26/04/2020,26,4,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,5.24356353\r
-25/04/2020,25,4,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,5.24356353\r
-24/04/2020,24,4,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,5.24356353\r
-23/04/2020,23,4,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,5.24356353\r
-22/04/2020,22,4,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,10.48712705\r
-21/04/2020,21,4,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,10.48712705\r
-20/04/2020,20,4,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,10.48712705\r
-19/04/2020,19,4,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,10.48712705\r
-18/04/2020,18,4,2020,1,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,10.48712705\r
-17/04/2020,17,4,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,8.73927254\r
-16/04/2020,16,4,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,12.23498156\r
-15/04/2020,15,4,2020,2,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,12.23498156\r
-14/04/2020,14,4,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,15.73069058\r
-13/04/2020,13,4,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,19.22639959\r
-12/04/2020,12,4,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,\r
-11/04/2020,11,4,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,\r
-10/04/2020,10,4,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,\r
-09/04/2020,9,4,2020,3,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,\r
-08/04/2020,8,4,2020,0,1,Northern_Mariana_Islands,MP,MNP,57213,Oceania,\r
-07/04/2020,7,4,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,\r
-06/04/2020,6,4,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,\r
-05/04/2020,5,4,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,\r
-04/04/2020,4,4,2020,0,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,\r
-03/04/2020,3,4,2020,2,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,\r
-02/04/2020,2,4,2020,0,1,Northern_Mariana_Islands,MP,MNP,57213,Oceania,\r
-01/04/2020,1,4,2020,4,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,\r
-31/03/2020,31,3,2020,2,0,Northern_Mariana_Islands,MP,MNP,57213,Oceania,\r
-19/08/2020,19,8,2020,56,1,Norway,NO,NOR,5328212,Europe,13.64435199\r
-18/08/2020,18,8,2020,154,0,Norway,NO,NOR,5328212,Europe,13.81326419\r
-17/08/2020,17,8,2020,0,0,Norway,NO,NOR,5328212,Europe,12.04907012\r
-16/08/2020,16,8,2020,0,0,Norway,NO,NOR,5328212,Europe,12.04907012\r
-15/08/2020,15,8,2020,67,4,Norway,NO,NOR,5328212,Europe,12.04907012\r
-14/08/2020,14,8,2020,33,1,Norway,NO,NOR,5328212,Europe,11.46726144\r
-13/08/2020,13,8,2020,66,0,Norway,NO,NOR,5328212,Europe,11.2608132\r
-12/08/2020,12,8,2020,46,0,Norway,NO,NOR,5328212,Europe,10.35994814\r
-11/08/2020,11,8,2020,170,0,Norway,NO,NOR,5328212,Europe,9.77813946\r
-10/08/2020,10,8,2020,0,0,Norway,NO,NOR,5328212,Europe,7.18815242\r
-09/08/2020,9,8,2020,0,0,Norway,NO,NOR,5328212,Europe,7.18815242\r
-08/08/2020,8,8,2020,59,0,Norway,NO,NOR,5328212,Europe,7.18815242\r
-07/08/2020,7,8,2020,47,0,Norway,NO,NOR,5328212,Europe,6.51250363\r
-06/08/2020,6,8,2020,29,0,Norway,NO,NOR,5328212,Europe,5.7993188\r
-05/08/2020,5,8,2020,65,0,Norway,NO,NOR,5328212,Europe,5.53656649\r
-04/08/2020,4,8,2020,60,1,Norway,NO,NOR,5328212,Europe,4.50432528\r
-03/08/2020,3,8,2020,0,0,Norway,NO,NOR,5328212,Europe,3.62222824\r
-02/08/2020,2,8,2020,0,0,Norway,NO,NOR,5328212,Europe,3.62222824\r
-01/08/2020,1,8,2020,36,0,Norway,NO,NOR,5328212,Europe,3.62222824\r
-31/07/2020,31,7,2020,22,0,Norway,NO,NOR,5328212,Europe,3.02165154\r
-30/07/2020,30,7,2020,18,0,Norway,NO,NOR,5328212,Europe,2.79643528\r
-29/07/2020,29,7,2020,15,0,Norway,NO,NOR,5328212,Europe,2.77766725\r
-28/07/2020,28,7,2020,32,0,Norway,NO,NOR,5328212,Europe,2.55245099\r
-27/07/2020,27,7,2020,0,0,Norway,NO,NOR,5328212,Europe,2.25216264\r
-26/07/2020,26,7,2020,0,0,Norway,NO,NOR,5328212,Europe,2.25216264\r
-25/07/2020,25,7,2020,23,0,Norway,NO,NOR,5328212,Europe,2.25216264\r
-24/07/2020,24,7,2020,9,0,Norway,NO,NOR,5328212,Europe,2.02694638\r
-23/07/2020,23,7,2020,15,0,Norway,NO,NOR,5328212,Europe,1.98941033\r
-22/07/2020,22,7,2020,10,0,Norway,NO,NOR,5328212,Europe,1.91433824\r
-21/07/2020,21,7,2020,13,0,Norway,NO,NOR,5328212,Europe,1.83926616\r
-20/07/2020,20,7,2020,0,0,Norway,NO,NOR,5328212,Europe,2.25216264\r
-19/07/2020,19,7,2020,0,0,Norway,NO,NOR,5328212,Europe,2.25216264\r
-18/07/2020,18,7,2020,4,1,Norway,NO,NOR,5328212,Europe,2.25216264\r
-17/07/2020,17,7,2020,10,1,Norway,NO,NOR,5328212,Europe,2.17709055\r
-16/07/2020,16,7,2020,17,0,Norway,NO,NOR,5328212,Europe,2.13955451\r
-15/07/2020,15,7,2020,3,0,Norway,NO,NOR,5328212,Europe,2.23339462\r
-14/07/2020,14,7,2020,16,1,Norway,NO,NOR,5328212,Europe,2.36477077\r
-13/07/2020,13,7,2020,0,0,Norway,NO,NOR,5328212,Europe,2.8152033\r
-12/07/2020,12,7,2020,0,0,Norway,NO,NOR,5328212,Europe,2.8152033\r
-11/07/2020,11,7,2020,11,0,Norway,NO,NOR,5328212,Europe,2.8152033\r
-10/07/2020,10,7,2020,7,1,Norway,NO,NOR,5328212,Europe,3.02165154\r
-09/07/2020,9,7,2020,11,0,Norway,NO,NOR,5328212,Europe,3.19056374\r
-08/07/2020,8,7,2020,6,0,Norway,NO,NOR,5328212,Europe,3.47208407\r
-07/07/2020,7,7,2020,35,0,Norway,NO,NOR,5328212,Europe,3.47208407\r
-06/07/2020,6,7,2020,0,0,Norway,NO,NOR,5328212,Europe,3.50962011\r
-05/07/2020,5,7,2020,0,0,Norway,NO,NOR,5328212,Europe,3.50962011\r
-04/07/2020,4,7,2020,0,0,Norway,NO,NOR,5328212,Europe,3.80990846\r
-03/07/2020,3,7,2020,8,0,Norway,NO,NOR,5328212,Europe,3.80990846\r
-02/07/2020,2,7,2020,22,1,Norway,NO,NOR,5328212,Europe,4.26034099\r
-01/07/2020,1,7,2020,10,1,Norway,NO,NOR,5328212,Europe,4.39171715\r
-30/06/2020,30,6,2020,40,0,Norway,NO,NOR,5328212,Europe,4.20403693\r
-29/06/2020,29,6,2020,0,0,Norway,NO,NOR,5328212,Europe,3.9225166\r
-28/06/2020,28,6,2020,0,0,Norway,NO,NOR,5328212,Europe,3.9225166\r
-27/06/2020,27,6,2020,22,0,Norway,NO,NOR,5328212,Europe,3.9225166\r
-26/06/2020,26,6,2020,16,0,Norway,NO,NOR,5328212,Europe,3.73483638\r
-25/06/2020,25,6,2020,26,1,Norway,NO,NOR,5328212,Europe,3.77237242\r
-24/06/2020,24,6,2020,6,0,Norway,NO,NOR,5328212,Europe,3.52838813\r
-23/06/2020,23,6,2020,37,4,Norway,NO,NOR,5328212,Europe,3.71606835\r
-22/06/2020,22,6,2020,0,0,Norway,NO,NOR,5328212,Europe,3.82867649\r
-21/06/2020,21,6,2020,16,0,Norway,NO,NOR,5328212,Europe,3.82867649\r
-20/06/2020,20,6,2020,0,0,Norway,NO,NOR,5328212,Europe,3.52838813\r
-19/06/2020,19,6,2020,32,1,Norway,NO,NOR,5328212,Europe,4.03512473\r
-18/06/2020,18,6,2020,29,1,Norway,NO,NOR,5328212,Europe,4.01635671\r
-17/06/2020,17,6,2020,0,0,Norway,NO,NOR,5328212,Europe,3.47208407\r
-16/06/2020,16,6,2020,25,0,Norway,NO,NOR,5328212,Europe,4.12896484\r
-15/06/2020,15,6,2020,0,0,Norway,NO,NOR,5328212,Europe,3.65976429\r
-14/06/2020,14,6,2020,0,0,Norway,NO,NOR,5328212,Europe,3.65976429\r
-13/06/2020,13,6,2020,12,0,Norway,NO,NOR,5328212,Europe,3.65976429\r
-12/06/2020,12,6,2020,18,3,Norway,NO,NOR,5328212,Europe,3.62222824\r
-11/06/2020,11,6,2020,13,0,Norway,NO,NOR,5328212,Europe,3.62222824\r
-10/06/2020,10,6,2020,16,0,Norway,NO,NOR,5328212,Europe,3.73483638\r
-09/06/2020,9,6,2020,43,1,Norway,NO,NOR,5328212,Europe,3.65976429\r
-08/06/2020,8,6,2020,0,0,Norway,NO,NOR,5328212,Europe,3.65976429\r
-07/06/2020,7,6,2020,0,0,Norway,NO,NOR,5328212,Europe,3.65976429\r
-06/06/2020,6,6,2020,27,0,Norway,NO,NOR,5328212,Europe,3.65976429\r
-05/06/2020,5,6,2020,31,1,Norway,NO,NOR,5328212,Europe,3.9225166\r
-04/06/2020,4,6,2020,0,0,Norway,NO,NOR,5328212,Europe,3.34070791\r
-03/06/2020,3,6,2020,35,1,Norway,NO,NOR,5328212,Europe,3.54715616\r
-02/06/2020,2,6,2020,0,0,Norway,NO,NOR,5328212,Europe,3.04041956\r
-01/06/2020,1,6,2020,0,0,Norway,NO,NOR,5328212,Europe,4.01635671\r
-31/05/2020,31,5,2020,0,0,Norway,NO,NOR,5328212,Europe,4.01635671\r
-30/05/2020,30,5,2020,10,0,Norway,NO,NOR,5328212,Europe,4.01635671\r
-29/05/2020,29,5,2020,18,1,Norway,NO,NOR,5328212,Europe,4.24157297\r
-28/05/2020,28,5,2020,19,0,Norway,NO,NOR,5328212,Europe,4.22280495\r
-27/05/2020,27,5,2020,12,0,Norway,NO,NOR,5328212,Europe,4.29787704\r
-26/05/2020,26,5,2020,43,0,Norway,NO,NOR,5328212,Europe,4.61693341\r
-25/05/2020,25,5,2020,0,0,Norway,NO,NOR,5328212,Europe,3.94128462\r
-24/05/2020,24,5,2020,0,0,Norway,NO,NOR,5328212,Europe,4.50432528\r
-23/05/2020,23,5,2020,41,1,Norway,NO,NOR,5328212,Europe,5.16120605\r
-22/05/2020,22,5,2020,0,0,Norway,NO,NOR,5328212,Europe,5.12367\r
-21/05/2020,21,5,2020,11,1,Norway,NO,NOR,5328212,Europe,5.91192693\r
-20/05/2020,20,5,2020,8,0,Norway,NO,NOR,5328212,Europe,6.64387979\r
-19/05/2020,19,5,2020,52,1,Norway,NO,NOR,5328212,Europe,7.54474484\r
-18/05/2020,18,5,2020,0,0,Norway,NO,NOR,5328212,Europe,7.28199253\r
-17/05/2020,17,5,2020,0,0,Norway,NO,NOR,5328212,Europe,8.22039363\r
-16/05/2020,16,5,2020,22,0,Norway,NO,NOR,5328212,Europe,8.22039363\r
-15/05/2020,15,5,2020,17,3,Norway,NO,NOR,5328212,Europe,8.72713023\r
-14/05/2020,14,5,2020,23,1,Norway,NO,NOR,5328212,Europe,9.2150988\r
-13/05/2020,13,5,2020,29,4,Norway,NO,NOR,5328212,Europe,9.94705166\r
-12/05/2020,12,5,2020,7,7,Norway,NO,NOR,5328212,Europe,10.7540766\r
-11/05/2020,11,5,2020,30,4,Norway,NO,NOR,5328212,Europe,11.14820506\r
-10/05/2020,10,5,2020,35,0,Norway,NO,NOR,5328212,Europe,11.29834924\r
-09/05/2020,9,5,2020,39,4,Norway,NO,NOR,5328212,Europe,11.74878177\r
-08/05/2020,8,5,2020,42,0,Norway,NO,NOR,5328212,Europe,12.1992143\r
-07/05/2020,7,5,2020,50,0,Norway,NO,NOR,5328212,Europe,13.19391946\r
-06/05/2020,6,5,2020,56,1,Norway,NO,NOR,5328212,Europe,13.83203221\r
-05/05/2020,5,5,2020,38,0,Norway,NO,NOR,5328212,Europe,13.77572814\r
-04/05/2020,4,5,2020,50,4,Norway,NO,NOR,5328212,Europe,13.9071043\r
-03/05/2020,3,5,2020,0,0,Norway,NO,NOR,5328212,Europe,14.54521704\r
-02/05/2020,2,5,2020,49,0,Norway,NO,NOR,5328212,Europe,18.16744529\r
-01/05/2020,1,5,2020,43,2,Norway,NO,NOR,5328212,Europe,17.24781221\r
-30/04/2020,30,4,2020,62,7,Norway,NO,NOR,5328212,Europe,18.58034177\r
-29/04/2020,29,4,2020,72,2,Norway,NO,NOR,5328212,Europe,19.49997485\r
-28/04/2020,28,4,2020,28,0,Norway,NO,NOR,5328212,Europe,19.61258298\r
-27/04/2020,27,4,2020,38,0,Norway,NO,NOR,5328212,Europe,20.45714397\r
-26/04/2020,26,4,2020,59,2,Norway,NO,NOR,5328212,Europe,21.52692123\r
-25/04/2020,25,4,2020,63,11,Norway,NO,NOR,5328212,Europe,21.8459776\r
-24/04/2020,24,4,2020,95,11,Norway,NO,NOR,5328212,Europe,22.24010606\r
-23/04/2020,23,4,2020,84,6,Norway,NO,NOR,5328212,Europe,23.27234727\r
-22/04/2020,22,4,2020,53,9,Norway,NO,NOR,5328212,Europe,24.45473266\r
-21/04/2020,21,4,2020,45,0,Norway,NO,NOR,5328212,Europe,25.48697387\r
-20/04/2020,20,4,2020,84,6,Norway,NO,NOR,5328212,Europe,26.80073541\r
-19/04/2020,19,4,2020,193,12,Norway,NO,NOR,5328212,Europe,27.66406442\r
-18/04/2020,18,4,2020,0,0,Norway,NO,NOR,5328212,Europe,29.70977882\r
-17/04/2020,17,4,2020,114,6,Norway,NO,NOR,5328212,Europe,34.83344882\r
-16/04/2020,16,4,2020,111,3,Norway,NO,NOR,5328212,Europe,37.76126025\r
-15/04/2020,15,4,2020,78,13,Norway,NO,NOR,5328212,Europe,39.7694386\r
-14/04/2020,14,4,2020,73,11,Norway,NO,NOR,5328212,Europe,42.45326575\r
-13/04/2020,13,4,2020,95,5,Norway,NO,NOR,5328212,Europe,43.41043487\r
-12/04/2020,12,4,2020,76,6,Norway,NO,NOR,5328212,Europe,46.45085443\r
-11/04/2020,11,4,2020,84,4,Norway,NO,NOR,5328212,Europe,49.97924257\r
-10/04/2020,10,4,2020,150,8,Norway,NO,NOR,5328212,Europe,56.37913807\r
-09/04/2020,9,4,2020,147,11,Norway,NO,NOR,5328212,Europe,58.06826005\r
-08/04/2020,8,4,2020,108,10,Norway,NO,NOR,5328212,Europe,61.87816851\r
-07/04/2020,7,4,2020,115,1,Norway,NO,NOR,5328212,Europe,63.51098642\r
-06/04/2020,6,4,2020,130,8,Norway,NO,NOR,5328212,Europe,65.83822115\r
-05/04/2020,5,4,2020,302,6,Norway,NO,NOR,5328212,Europe,67.26459082\r
-04/04/2020,4,4,2020,273,2,Norway,NO,NOR,5328212,Europe,65.04996423\r
-03/04/2020,3,4,2020,270,10,Norway,NO,NOR,5328212,Europe,63.4922184\r
-02/04/2020,2,4,2020,218,4,Norway,NO,NOR,5328212,Europe,60.8459273\r
-01/04/2020,1,4,2020,221,2,Norway,NO,NOR,5328212,Europe,58.91282104\r
-31/03/2020,31,3,2020,124,4,Norway,NO,NOR,5328212,Europe,57.37384323\r
-30/03/2020,30,3,2020,257,2,Norway,NO,NOR,5328212,Europe,56.77326653\r
-29/03/2020,29,3,2020,264,4,Norway,NO,NOR,5328212,Europe,55.14044862\r
-28/03/2020,28,3,2020,425,2,Norway,NO,NOR,5328212,Europe,55.5533451\r
-27/03/2020,27,3,2020,240,2,Norway,NO,NOR,5328212,Europe,47.57693575\r
-26/03/2020,26,3,2020,350,2,Norway,NO,NOR,5328212,Europe,45.54998938\r
-25/03/2020,25,3,2020,195,2,Norway,NO,NOR,5328212,Europe,42.96000234\r
-24/03/2020,24,3,2020,239,1,Norway,NO,NOR,5328212,Europe,40.89551992\r
-23/03/2020,23,3,2020,206,0,Norway,NO,NOR,5328212,Europe,36.84162717\r
-22/03/2020,22,3,2020,184,0,Norway,NO,NOR,5328212,Europe,33.38831113\r
-21/03/2020,21,3,2020,190,1,Norway,NO,NOR,5328212,Europe,30.57310783\r
-20/03/2020,20,3,2020,129,3,Norway,NO,NOR,5328212,Europe,27.51392024\r
-19/03/2020,19,3,2020,115,0,Norway,NO,NOR,5328212,Europe,25.65588606\r
-18/03/2020,18,3,2020,139,0,Norway,NO,NOR,5328212,Europe,23.92922804\r
-17/03/2020,17,3,2020,92,2,Norway,NO,NOR,5328212,Europe,21.47061716\r
-16/03/2020,16,3,2020,170,0,Norway,NO,NOR,5328212,Europe,19.85656727\r
-15/03/2020,15,3,2020,286,0,Norway,NO,NOR,5328212,Europe,16.74107562\r
-14/03/2020,14,3,2020,0,0,Norway,NO,NOR,5328212,Europe,11.54233353\r
-13/03/2020,13,3,2020,132,1,Norway,NO,NOR,5328212,Europe,11.57986957\r
-12/03/2020,12,3,2020,212,0,Norway,NO,NOR,5328212,Europe,9.15879473\r
-11/03/2020,11,3,2020,85,0,Norway,NO,NOR,5328212,Europe,5.19874209\r
-10/03/2020,10,3,2020,23,0,Norway,NO,NOR,5328212,Europe,3.60346022\r
-09/03/2020,9,3,2020,22,0,Norway,NO,NOR,5328212,Europe,3.17179572\r
-08/03/2020,8,3,2020,34,0,Norway,NO,NOR,5328212,Europe,2.75889923\r
-07/03/2020,7,3,2020,27,0,Norway,NO,NOR,5328212,Europe,2.12078649\r
-06/03/2020,6,3,2020,30,0,Norway,NO,NOR,5328212,Europe,1.61404989\r
-05/03/2020,5,3,2020,23,0,Norway,NO,NOR,5328212,Europe,1.05100923\r
-04/03/2020,4,3,2020,8,0,Norway,NO,NOR,5328212,Europe,0.61934473\r
-03/03/2020,3,3,2020,6,0,Norway,NO,NOR,5328212,Europe,0.46920055\r
-02/03/2020,2,3,2020,4,0,Norway,NO,NOR,5328212,Europe,0.35659242\r
-01/03/2020,1,3,2020,9,0,Norway,NO,NOR,5328212,Europe,0.28152033\r
-29/02/2020,29,2,2020,2,0,Norway,NO,NOR,5328212,Europe,0.11260813\r
-28/02/2020,28,2,2020,3,0,Norway,NO,NOR,5328212,Europe,0.07507209\r
-27/02/2020,27,2,2020,1,0,Norway,NO,NOR,5328212,Europe,0.01876802\r
-26/02/2020,26,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-25/02/2020,25,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-24/02/2020,24,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-23/02/2020,23,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-22/02/2020,22,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-21/02/2020,21,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-20/02/2020,20,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-19/02/2020,19,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-18/02/2020,18,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-17/02/2020,17,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-16/02/2020,16,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-15/02/2020,15,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-14/02/2020,14,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-13/02/2020,13,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-12/02/2020,12,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-11/02/2020,11,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-10/02/2020,10,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-09/02/2020,9,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-08/02/2020,8,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-07/02/2020,7,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-06/02/2020,6,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-05/02/2020,5,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-04/02/2020,4,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-03/02/2020,3,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-02/02/2020,2,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-01/02/2020,1,2,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-31/01/2020,31,1,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-30/01/2020,30,1,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-29/01/2020,29,1,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-28/01/2020,28,1,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-27/01/2020,27,1,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-26/01/2020,26,1,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-25/01/2020,25,1,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-24/01/2020,24,1,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-23/01/2020,23,1,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-22/01/2020,22,1,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-21/01/2020,21,1,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-20/01/2020,20,1,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-19/01/2020,19,1,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-18/01/2020,18,1,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-17/01/2020,17,1,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-16/01/2020,16,1,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-15/01/2020,15,1,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-14/01/2020,14,1,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-13/01/2020,13,1,2020,0,0,Norway,NO,NOR,5328212,Europe,0\r
-12/01/2020,12,1,2020,0,0,Norway,NO,NOR,5328212,Europe,\r
-11/01/2020,11,1,2020,0,0,Norway,NO,NOR,5328212,Europe,\r
-10/01/2020,10,1,2020,0,0,Norway,NO,NOR,5328212,Europe,\r
-09/01/2020,9,1,2020,0,0,Norway,NO,NOR,5328212,Europe,\r
-08/01/2020,8,1,2020,0,0,Norway,NO,NOR,5328212,Europe,\r
-07/01/2020,7,1,2020,0,0,Norway,NO,NOR,5328212,Europe,\r
-06/01/2020,6,1,2020,0,0,Norway,NO,NOR,5328212,Europe,\r
-05/01/2020,5,1,2020,0,0,Norway,NO,NOR,5328212,Europe,\r
-04/01/2020,4,1,2020,0,0,Norway,NO,NOR,5328212,Europe,\r
-03/01/2020,3,1,2020,0,0,Norway,NO,NOR,5328212,Europe,\r
-02/01/2020,2,1,2020,0,0,Norway,NO,NOR,5328212,Europe,\r
-01/01/2020,1,1,2020,0,0,Norway,NO,NOR,5328212,Europe,\r
-31/12/2019,31,12,2019,0,0,Norway,NO,NOR,5328212,Europe,\r
-19/08/2020,19,8,2020,192,9,Oman,OM,OMN,4974992,Asia,85.60817786\r
-18/08/2020,18,8,2020,140,16,Oman,OM,OMN,4974992,Asia,81.74887517\r
-17/08/2020,17,8,2020,162,10,Oman,OM,OMN,4974992,Asia,78.9348003\r
-16/08/2020,16,8,2020,181,5,Oman,OM,OMN,4974992,Asia,75.67851365\r
-15/08/2020,15,8,2020,212,6,Oman,OM,OMN,4974992,Asia,72.04031685\r
-14/08/2020,14,8,2020,232,12,Oman,OM,OMN,4974992,Asia,67.77900346\r
-13/08/2020,13,8,2020,249,6,Oman,OM,OMN,4974992,Asia,74.97499493\r
-12/08/2020,12,8,2020,263,12,Oman,OM,OMN,4974992,Asia,83.33681743\r
-11/08/2020,11,8,2020,207,8,Oman,OM,OMN,4974992,Asia,95.05542923\r
-10/08/2020,10,8,2020,223,4,Oman,OM,OMN,4974992,Asia,112.06048171\r
-09/08/2020,9,8,2020,290,7,Oman,OM,OMN,4974992,Asia,130.63337589\r
-08/08/2020,8,8,2020,354,10,Oman,OM,OMN,4974992,Asia,146.25149146\r
-07/08/2020,7,8,2020,427,4,Oman,OM,OMN,4974992,Asia,162.15101451\r
-06/08/2020,6,8,2020,1127,67,Oman,OM,OMN,4974992,Asia,175.65857392\r
-05/08/2020,5,8,2020,0,0,Oman,OM,OMN,4974992,Asia,186.37215899\r
-04/08/2020,4,8,2020,0,0,Oman,OM,OMN,4974992,Asia,216.26165429\r
-03/08/2020,3,8,2020,0,0,Oman,OM,OMN,4974992,Asia,251.21648437\r
-02/08/2020,2,8,2020,0,0,Oman,OM,OMN,4974992,Asia,274.47280317\r
-01/08/2020,1,8,2020,0,0,Oman,OM,OMN,4974992,Asia,300.82460434\r
-31/07/2020,31,7,2020,590,9,Oman,OM,OMN,4974992,Asia,333.36737024\r
-30/07/2020,30,7,2020,665,10,Oman,OM,OMN,4974992,Asia,348.18146441\r
-29/07/2020,29,7,2020,846,9,Oman,OM,OMN,4974992,Asia,368.56340674\r
-28/07/2020,28,7,2020,1053,9,Oman,OM,OMN,4974992,Asia,379.47799715\r
-27/07/2020,27,7,2020,1147,13,Oman,OM,OMN,4974992,Asia,401.80969135\r
-26/07/2020,26,7,2020,1067,12,Oman,OM,OMN,4974992,Asia,405.24688281\r
-25/07/2020,25,7,2020,1145,4,Oman,OM,OMN,4974992,Asia,405.56849137\r
-24/07/2020,24,7,2020,1099,6,Oman,OM,OMN,4974992,Asia,420.52328928\r
-23/07/2020,23,7,2020,1660,12,Oman,OM,OMN,4974992,Asia,428.94541338\r
-22/07/2020,22,7,2020,1487,11,Oman,OM,OMN,4974992,Asia,419.9001727\r
-21/07/2020,21,7,2020,1739,8,Oman,OM,OMN,4974992,Asia,415.37755237\r
-20/07/2020,20,7,2020,1157,10,Oman,OM,OMN,4974992,Asia,411.71925503\r
-19/07/2020,19,7,2020,1311,10,Oman,OM,OMN,4974992,Asia,410.01070956\r
-18/07/2020,18,7,2020,1619,8,Oman,OM,OMN,4974992,Asia,407.3172379\r
-17/07/2020,17,7,2020,1327,9,Oman,OM,OMN,4974992,Asia,402.39260686\r
-16/07/2020,16,7,2020,1679,8,Oman,OM,OMN,4974992,Asia,403.07602505\r
-15/07/2020,15,7,2020,1389,14,Oman,OM,OMN,4974992,Asia,391.92022821\r
-14/07/2020,14,7,2020,2164,2,Oman,OM,OMN,4974992,Asia,384.30212551\r
-13/07/2020,13,7,2020,1318,9,Oman,OM,OMN,4974992,Asia,359.09605483\r
-12/07/2020,12,7,2020,1083,4,Oman,OM,OMN,4974992,Asia,356.66389011\r
-11/07/2020,11,7,2020,1889,8,Oman,OM,OMN,4974992,Asia,353.3674024\r
-10/07/2020,10,7,2020,1518,3,Oman,OM,OMN,4974992,Asia,338.15129753\r
-09/07/2020,9,7,2020,1210,9,Oman,OM,OMN,4974992,Asia,335.09601623\r
-08/07/2020,8,7,2020,1262,6,Oman,OM,OMN,4974992,Asia,333.72917987\r
-07/07/2020,7,7,2020,1557,5,Oman,OM,OMN,4974992,Asia,334.85480982\r
-06/07/2020,6,7,2020,1072,10,Oman,OM,OMN,4974992,Asia,335.81963549\r
-05/07/2020,5,7,2020,1177,10,Oman,OM,OMN,4974992,Asia,332.46284617\r
-04/07/2020,4,7,2020,1374,5,Oman,OM,OMN,4974992,Asia,326.81459588\r
-03/07/2020,3,7,2020,1361,3,Oman,OM,OMN,4974992,Asia,316.3221167\r
-02/07/2020,2,7,2020,1124,9,Oman,OM,OMN,4974992,Asia,303.81958403\r
-01/07/2020,1,7,2020,1010,7,Oman,OM,OMN,4974992,Asia,297.50801609\r
-30/06/2020,30,6,2020,910,6,Oman,OM,OMN,4974992,Asia,292.18137436\r
-29/06/2020,29,6,2020,1197,4,Oman,OM,OMN,4974992,Asia,294.8547455\r
-28/06/2020,28,6,2020,919,6,Oman,OM,OMN,4974992,Asia,299.01555621\r
-27/06/2020,27,6,2020,1132,9,Oman,OM,OMN,4974992,Asia,300.76430274\r
-26/06/2020,26,6,2020,1366,2,Oman,OM,OMN,4974992,Asia,300.46279471\r
-25/06/2020,25,6,2020,1142,2,Oman,OM,OMN,4974992,Asia,294.4527348\r
-24/06/2020,24,6,2020,1318,3,Oman,OM,OMN,4974992,Asia,285.34719252\r
-23/06/2020,23,6,2020,1605,6,Oman,OM,OMN,4974992,Asia,273.16626841\r
-22/06/2020,22,6,2020,905,3,Oman,OM,OMN,4974992,Asia,253.04563304\r
-21/06/2020,21,6,2020,896,3,Oman,OM,OMN,4974992,Asia,252.26171218\r
-20/06/2020,20,6,2020,852,6,Oman,OM,OMN,4974992,Asia,252.94513036\r
-19/06/2020,19,6,2020,739,3,Oman,OM,OMN,4974992,Asia,251.29688651\r
-18/06/2020,18,6,2020,810,2,Oman,OM,OMN,4974992,Asia,252.1009079\r
-17/06/2020,17,6,2020,745,6,Oman,OM,OMN,4974992,Asia,250.65366939\r
-16/06/2020,16,6,2020,1043,4,Oman,OM,OMN,4974992,Asia,247.25667901\r
-15/06/2020,15,6,2020,1404,5,Oman,OM,OMN,4974992,Asia,242.09084155\r
-14/06/2020,14,6,2020,1006,3,Oman,OM,OMN,4974992,Asia,234.25163297\r
-13/06/2020,13,6,2020,1117,7,Oman,OM,OMN,4974992,Asia,226.15111743\r
-12/06/2020,12,6,2020,1067,5,Oman,OM,OMN,4974992,Asia,220.00035377\r
-11/06/2020,11,6,2020,689,1,Oman,OM,OMN,4974992,Asia,211.33702326\r
-10/06/2020,10,6,2020,712,2,Oman,OM,OMN,4974992,Asia,202.61339114\r
-09/06/2020,9,6,2020,604,6,Oman,OM,OMN,4974992,Asia,195.29679646\r
-08/06/2020,8,6,2020,866,3,Oman,OM,OMN,4974992,Asia,183.15607342\r
-07/06/2020,7,6,2020,930,0,Oman,OM,OMN,4974992,Asia,176.06058462\r
-06/06/2020,6,6,2020,770,5,Oman,OM,OMN,4974992,Asia,166.67363485\r
-05/06/2020,5,6,2020,779,0,Oman,OM,OMN,4974992,Asia,159.7188498\r
-04/06/2020,4,6,2020,738,8,Oman,OM,OMN,4974992,Asia,150.63340805\r
-03/06/2020,3,6,2020,576,9,Oman,OM,OMN,4974992,Asia,143.2766123\r
-02/06/2020,2,6,2020,786,3,Oman,OM,OMN,4974992,Asia,137.56806041\r
-01/06/2020,1,6,2020,1014,5,Oman,OM,OMN,4974992,Asia,125.64844325\r
-31/05/2020,31,5,2020,603,2,Oman,OM,OMN,4974992,Asia,108.4222849\r
-30/05/2020,30,5,2020,811,0,Oman,OM,OMN,4974992,Asia,104.42227847\r
-29/05/2020,29,5,2020,636,2,Oman,OM,OMN,4974992,Asia,93.82929661\r
-28/05/2020,28,5,2020,255,1,Oman,OM,OMN,4974992,Asia,87.51772867\r
-27/05/2020,27,5,2020,348,0,Oman,OM,OMN,4974992,Asia,88.38205167\r
-26/05/2020,26,5,2020,0,0,Oman,OM,OMN,4974992,Asia,84.34184417\r
-25/05/2020,25,5,2020,513,1,Oman,OM,OMN,4974992,Asia,87.85943776\r
-24/05/2020,24,5,2020,463,4,Oman,OM,OMN,4974992,Asia,81.06545699\r
-23/05/2020,23,5,2020,424,1,Oman,OM,OMN,4974992,Asia,74.01016926\r
-22/05/2020,22,5,2020,327,1,Oman,OM,OMN,4974992,Asia,68.58302486\r
-21/05/2020,21,5,2020,372,3,Oman,OM,OMN,4974992,Asia,63.11567938\r
-20/05/2020,20,5,2020,292,1,Oman,OM,OMN,4974992,Asia,59.01517028\r
-19/05/2020,19,5,2020,193,4,Oman,OM,OMN,4974992,Asia,55.11566652\r
-18/05/2020,18,5,2020,157,1,Oman,OM,OMN,4974992,Asia,52.6232002\r
-17/05/2020,17,5,2020,404,2,Oman,OM,OMN,4974992,Asia,51.17596169\r
-16/05/2020,16,5,2020,284,0,Oman,OM,OMN,4974992,Asia,43.77896487\r
-15/05/2020,15,5,2020,322,2,Oman,OM,OMN,4974992,Asia,40.06036593\r
-14/05/2020,14,5,2020,298,0,Oman,OM,OMN,4974992,Asia,35.07543329\r
-13/05/2020,13,5,2020,147,0,Oman,OM,OMN,4974992,Asia,31.95985039\r
-12/05/2020,12,5,2020,175,0,Oman,OM,OMN,4974992,Asia,30.65331562\r
-11/05/2020,11,5,2020,175,0,Oman,OM,OMN,4974992,Asia,28.1608493\r
-10/05/2020,10,5,2020,112,2,Oman,OM,OMN,4974992,Asia,26.51260545\r
-09/05/2020,9,5,2020,154,1,Oman,OM,OMN,4974992,Asia,26.57290705\r
-08/05/2020,8,5,2020,55,1,Oman,OM,OMN,4974992,Asia,24.96486427\r
-07/05/2020,7,5,2020,168,1,Oman,OM,OMN,4974992,Asia,25.9095894\r
-06/05/2020,6,5,2020,98,0,Oman,OM,OMN,4974992,Asia,24.66335624\r
-05/05/2020,5,5,2020,69,0,Oman,OM,OMN,4974992,Asia,22.69350383\r
-04/05/2020,4,5,2020,85,0,Oman,OM,OMN,4974992,Asia,26.17089636\r
-03/05/2020,3,5,2020,36,1,Oman,OM,OMN,4974992,Asia,26.19099689\r
-02/05/2020,2,5,2020,99,0,Oman,OM,OMN,4974992,Asia,27.698537\r
-01/05/2020,1,5,2020,74,1,Oman,OM,OMN,4974992,Asia,26.7136108\r
-30/04/2020,30,4,2020,143,0,Oman,OM,OMN,4974992,Asia,27.41712951\r
-29/04/2020,29,4,2020,82,0,Oman,OM,OMN,4974992,Asia,24.54275303\r
-28/04/2020,28,4,2020,51,0,Oman,OM,OMN,4974992,Asia,24.84426106\r
-27/04/2020,27,4,2020,93,0,Oman,OM,OMN,4974992,Asia,28.12064823\r
-26/04/2020,26,4,2020,115,0,Oman,OM,OMN,4974992,Asia,27.31662684\r
-25/04/2020,25,4,2020,74,1,Oman,OM,OMN,4974992,Asia,26.25129849\r
-24/04/2020,24,4,2020,102,1,Oman,OM,OMN,4974992,Asia,25.30657336\r
-23/04/2020,23,4,2020,106,0,Oman,OM,OMN,4974992,Asia,24.02013913\r
-22/04/2020,22,4,2020,0,0,Oman,OM,OMN,4974992,Asia,21.88948244\r
-21/04/2020,21,4,2020,242,1,Oman,OM,OMN,4974992,Asia,22.85430811\r
-20/04/2020,20,4,2020,86,1,Oman,OM,OMN,4974992,Asia,19.45731772\r
-19/04/2020,19,4,2020,111,0,Oman,OM,OMN,4974992,Asia,18.15078296\r
-18/04/2020,18,4,2020,50,2,Oman,OM,OMN,4974992,Asia,16.84424819\r
-17/04/2020,17,4,2020,109,0,Oman,OM,OMN,4974992,Asia,15.83922145\r
-16/04/2020,16,4,2020,0,0,Oman,OM,OMN,4974992,Asia,14.07037438\r
-15/04/2020,15,4,2020,97,0,Oman,OM,OMN,4974992,Asia,14.43218401\r
-14/04/2020,14,4,2020,214,0,Oman,OM,OMN,4974992,Asia,12.74373909\r
-13/04/2020,13,4,2020,53,1,Oman,OM,OMN,4974992,Asia,8.68343105\r
-12/04/2020,12,4,2020,62,0,Oman,OM,OMN,4974992,Asia,7.91961073\r
-11/04/2020,11,4,2020,27,0,Oman,OM,OMN,4974992,Asia,7.0954888\r
-10/04/2020,10,4,2020,38,1,Oman,OM,OMN,4974992,Asia,6.99498612\r
-09/04/2020,9,4,2020,0,0,Oman,OM,OMN,4974992,Asia,6.43217115\r
-08/04/2020,8,4,2020,48,0,Oman,OM,OMN,4974992,Asia,6.73367917\r
-07/04/2020,7,4,2020,73,0,Oman,OM,OMN,4974992,Asia,6.13066312\r
-06/04/2020,6,4,2020,21,0,Oman,OM,OMN,4974992,Asia,4.88442996\r
-05/04/2020,5,4,2020,46,1,Oman,OM,OMN,4974992,Asia,4.52262034\r
-04/04/2020,4,4,2020,0,0,Oman,OM,OMN,4974992,Asia,3.67839787\r
-03/04/2020,3,4,2020,21,0,Oman,OM,OMN,4974992,Asia,3.85930269\r
-02/04/2020,2,4,2020,18,0,Oman,OM,OMN,4974992,Asia,3.43719146\r
-01/04/2020,1,4,2020,13,1,Oman,OM,OMN,4974992,Asia,3.37688985\r
-31/03/2020,31,3,2020,12,0,Oman,OM,OMN,4974992,Asia,3.1155829\r
-30/03/2020,30,3,2020,15,0,Oman,OM,OMN,4974992,Asia,2.91457755\r
-29/03/2020,29,3,2020,21,0,Oman,OM,OMN,4974992,Asia,2.6532706\r
-28/03/2020,28,3,2020,22,0,Oman,OM,OMN,4974992,Asia,2.23115937\r
-27/03/2020,27,3,2020,10,0,Oman,OM,OMN,4974992,Asia,1.82914867\r
-26/03/2020,26,3,2020,15,0,Oman,OM,OMN,4974992,Asia,1.62814332\r
-25/03/2020,25,3,2020,18,0,Oman,OM,OMN,4974992,Asia,1.36683637\r
-24/03/2020,24,3,2020,11,0,Oman,OM,OMN,4974992,Asia,1.02512728\r
-23/03/2020,23,3,2020,3,0,Oman,OM,OMN,4974992,Asia,0.96482567\r
-22/03/2020,22,3,2020,4,0,Oman,OM,OMN,4974992,Asia,0.9246246\r
-21/03/2020,21,3,2020,9,0,Oman,OM,OMN,4974992,Asia,0.84422246\r
-20/03/2020,20,3,2020,0,0,Oman,OM,OMN,4974992,Asia,0.66331765\r
-19/03/2020,19,3,2020,15,0,Oman,OM,OMN,4974992,Asia,0.66331765\r
-18/03/2020,18,3,2020,0,0,Oman,OM,OMN,4974992,Asia,0.4020107\r
-17/03/2020,17,3,2020,2,0,Oman,OM,OMN,4974992,Asia,0.4020107\r
-16/03/2020,16,3,2020,2,0,Oman,OM,OMN,4974992,Asia,0.4020107\r
-15/03/2020,15,3,2020,0,0,Oman,OM,OMN,4974992,Asia,0.4020107\r
-14/03/2020,14,3,2020,2,0,Oman,OM,OMN,4974992,Asia,0.4020107\r
-11/03/2020,11,3,2020,0,0,Oman,OM,OMN,4974992,Asia,0.36180963\r
-10/03/2020,10,3,2020,2,0,Oman,OM,OMN,4974992,Asia,0.36180963\r
-06/03/2020,6,3,2020,1,0,Oman,OM,OMN,4974992,Asia,0.32160856\r
-05/03/2020,5,3,2020,8,0,Oman,OM,OMN,4974992,Asia,0.30150802\r
-03/03/2020,3,3,2020,1,0,Oman,OM,OMN,4974992,Asia,0.14070374\r
-02/03/2020,2,3,2020,0,0,Oman,OM,OMN,4974992,Asia,0.12060321\r
-01/03/2020,1,3,2020,0,0,Oman,OM,OMN,4974992,Asia,0.12060321\r
-29/02/2020,29,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0.12060321\r
-28/02/2020,28,2,2020,2,0,Oman,OM,OMN,4974992,Asia,0.12060321\r
-27/02/2020,27,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0.08040214\r
-26/02/2020,26,2,2020,2,0,Oman,OM,OMN,4974992,Asia,0.08040214\r
-25/02/2020,25,2,2020,2,0,Oman,OM,OMN,4974992,Asia,0.04020107\r
-24/02/2020,24,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-23/02/2020,23,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-22/02/2020,22,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-21/02/2020,21,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-20/02/2020,20,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-19/02/2020,19,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-18/02/2020,18,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-17/02/2020,17,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-16/02/2020,16,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-15/02/2020,15,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-14/02/2020,14,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-13/02/2020,13,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-12/02/2020,12,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-11/02/2020,11,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-10/02/2020,10,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-09/02/2020,9,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-08/02/2020,8,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-07/02/2020,7,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-06/02/2020,6,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-05/02/2020,5,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-04/02/2020,4,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-03/02/2020,3,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-02/02/2020,2,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-01/02/2020,1,2,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-31/01/2020,31,1,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-30/01/2020,30,1,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-29/01/2020,29,1,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-28/01/2020,28,1,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-27/01/2020,27,1,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-26/01/2020,26,1,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-25/01/2020,25,1,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-24/01/2020,24,1,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-23/01/2020,23,1,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-22/01/2020,22,1,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-21/01/2020,21,1,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-20/01/2020,20,1,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-19/01/2020,19,1,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-18/01/2020,18,1,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-17/01/2020,17,1,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-16/01/2020,16,1,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-15/01/2020,15,1,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-14/01/2020,14,1,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-13/01/2020,13,1,2020,0,0,Oman,OM,OMN,4974992,Asia,0\r
-12/01/2020,12,1,2020,0,0,Oman,OM,OMN,4974992,Asia,\r
-11/01/2020,11,1,2020,0,0,Oman,OM,OMN,4974992,Asia,\r
-10/01/2020,10,1,2020,0,0,Oman,OM,OMN,4974992,Asia,\r
-09/01/2020,9,1,2020,0,0,Oman,OM,OMN,4974992,Asia,\r
-08/01/2020,8,1,2020,0,0,Oman,OM,OMN,4974992,Asia,\r
-07/01/2020,7,1,2020,0,0,Oman,OM,OMN,4974992,Asia,\r
-06/01/2020,6,1,2020,0,0,Oman,OM,OMN,4974992,Asia,\r
-05/01/2020,5,1,2020,0,0,Oman,OM,OMN,4974992,Asia,\r
-04/01/2020,4,1,2020,0,0,Oman,OM,OMN,4974992,Asia,\r
-03/01/2020,3,1,2020,0,0,Oman,OM,OMN,4974992,Asia,\r
-02/01/2020,2,1,2020,0,0,Oman,OM,OMN,4974992,Asia,\r
-01/01/2020,1,1,2020,0,0,Oman,OM,OMN,4974992,Asia,\r
-31/12/2019,31,12,2019,0,0,Oman,OM,OMN,4974992,Asia,\r
-19/08/2020,19,8,2020,0,0,Pakistan,PK,PAK,216565317,Asia,4.01541674\r
-18/08/2020,18,8,2020,617,15,Pakistan,PK,PAK,216565317,Asia,4.327101\r
-17/08/2020,17,8,2020,498,7,Pakistan,PK,PAK,216565317,Asia,4.24167643\r
-16/08/2020,16,8,2020,670,6,Pakistan,PK,PAK,216565317,Asia,4.80778739\r
-15/08/2020,15,8,2020,747,9,Pakistan,PK,PAK,216565317,Asia,4.4984119\r
-14/08/2020,14,8,2020,626,14,Pakistan,PK,PAK,216565317,Asia,4.15348133\r
-13/08/2020,13,8,2020,753,10,Pakistan,PK,PAK,216565317,Asia,4.28138731\r
-12/08/2020,12,8,2020,730,17,Pakistan,PK,PAK,216565317,Asia,4.44808067\r
-11/08/2020,11,8,2020,531,15,Pakistan,PK,PAK,216565317,Asia,4.6018449\r
-10/08/2020,10,8,2020,539,15,Pakistan,PK,PAK,216565317,Asia,4.78885546\r
-09/08/2020,9,8,2020,634,14,Pakistan,PK,PAK,216565317,Asia,5.08299304\r
-08/08/2020,8,8,2020,842,16,Pakistan,PK,PAK,216565317,Asia,5.35635168\r
-07/08/2020,7,8,2020,782,17,Pakistan,PK,PAK,216565317,Asia,5.65418331\r
-06/08/2020,6,8,2020,727,21,Pakistan,PK,PAK,216565317,Asia,5.85135246\r
-05/08/2020,5,8,2020,675,15,Pakistan,PK,PAK,216565317,Asia,6.32973007\r
-04/08/2020,4,8,2020,432,15,Pakistan,PK,PAK,216565317,Asia,6.63310275\r
-03/08/2020,3,8,2020,1724,33,Pakistan,PK,PAK,216565317,Asia,6.90138209\r
-02/08/2020,2,8,2020,0,0,Pakistan,PK,PAK,216565317,Asia,6.83812173\r
-01/08/2020,1,8,2020,0,0,Pakistan,PK,PAK,216565317,Asia,7.56723201\r
-31/07/2020,31,7,2020,903,27,Pakistan,PK,PAK,216565317,Asia,8.45287706\r
-30/07/2020,30,7,2020,1114,32,Pakistan,PK,PAK,216565317,Asia,8.99867083\r
-29/07/2020,29,7,2020,1063,27,Pakistan,PK,PAK,216565317,Asia,9.47473967\r
-28/07/2020,28,7,2020,936,23,Pakistan,PK,PAK,216565317,Asia,9.98359308\r
-27/07/2020,27,7,2020,1176,20,Pakistan,PK,PAK,216565317,Asia,10.46520298\r
-26/07/2020,26,7,2020,1226,35,Pakistan,PK,PAK,216565317,Asia,11.19338975\r
-25/07/2020,25,7,2020,1487,24,Pakistan,PK,PAK,216565317,Asia,11.79136177\r
-24/07/2020,24,7,2020,1209,54,Pakistan,PK,PAK,216565317,Asia,12.37548116\r
-23/07/2020,23,7,2020,1763,32,Pakistan,PK,PAK,216565317,Asia,13.08750653\r
-22/07/2020,22,7,2020,1332,38,Pakistan,PK,PAK,216565317,Asia,13.82446664\r
-21/07/2020,21,7,2020,1013,40,Pakistan,PK,PAK,216565317,Asia,14.58543798\r
-20/07/2020,20,7,2020,1587,31,Pakistan,PK,PAK,216565317,Asia,15.36026196\r
-19/07/2020,19,7,2020,1579,46,Pakistan,PK,PAK,216565317,Asia,16.17156454\r
-18/07/2020,18,7,2020,1918,47,Pakistan,PK,PAK,216565317,Asia,16.91591272\r
-17/07/2020,17,7,2020,2085,49,Pakistan,PK,PAK,216565317,Asia,17.59423001\r
-16/07/2020,16,7,2020,2145,40,Pakistan,PK,PAK,216565317,Asia,18.51866243\r
-15/07/2020,15,7,2020,2165,66,Pakistan,PK,PAK,216565317,Asia,19.53175171\r
-14/07/2020,14,7,2020,1979,54,Pakistan,PK,PAK,216565317,Asia,20.44048448\r
-13/07/2020,13,7,2020,2753,69,Pakistan,PK,PAK,216565317,Asia,20.83112874\r
-12/07/2020,12,7,2020,2521,74,Pakistan,PK,PAK,216565317,Asia,21.20237933\r
-11/07/2020,11,7,2020,2752,65,Pakistan,PK,PAK,216565317,Asia,21.91856049\r
-10/07/2020,10,7,2020,2751,75,Pakistan,PK,PAK,216565317,Asia,22.09679771\r
-09/07/2020,9,7,2020,3359,61,Pakistan,PK,PAK,216565317,Asia,22.10787981\r
-08/07/2020,8,7,2020,2980,83,Pakistan,PK,PAK,216565317,Asia,22.42418162\r
-07/07/2020,7,7,2020,2691,77,Pakistan,PK,PAK,216565317,Asia,22.84530168\r
-06/07/2020,6,7,2020,3344,50,Pakistan,PK,PAK,216565317,Asia,23.42480352\r
-05/07/2020,5,7,2020,3191,93,Pakistan,PK,PAK,216565317,Asia,23.94520079\r
-04/07/2020,4,7,2020,3387,68,Pakistan,PK,PAK,216565317,Asia,24.75788863\r
-03/07/2020,3,7,2020,4087,78,Pakistan,PK,PAK,216565317,Asia,26.24335272\r
-02/07/2020,2,7,2020,4339,78,Pakistan,PK,PAK,216565317,Asia,26.63907628\r
-01/07/2020,1,7,2020,4133,91,Pakistan,PK,PAK,216565317,Asia,27.10960407\r
-30/06/2020,30,6,2020,2825,137,Pakistan,PK,PAK,216565317,Asia,27.89735717\r
-29/06/2020,29,6,2020,3557,49,Pakistan,PK,PAK,216565317,Asia,28.64447588\r
-28/06/2020,28,6,2020,4072,83,Pakistan,PK,PAK,216565317,Asia,29.42530267\r
-27/06/2020,27,6,2020,3138,73,Pakistan,PK,PAK,216565317,Asia,30.69651268\r
-26/06/2020,26,6,2020,2775,59,Pakistan,PK,PAK,216565317,Asia,32.23600204\r
-25/06/2020,25,6,2020,4044,148,Pakistan,PK,PAK,216565317,Asia,33.90847667\r
-24/06/2020,24,6,2020,3892,60,Pakistan,PK,PAK,216565317,Asia,34.73501715\r
-23/06/2020,23,6,2020,3946,105,Pakistan,PK,PAK,216565317,Asia,35.42441655\r
-22/06/2020,22,6,2020,4471,89,Pakistan,PK,PAK,216565317,Asia,35.74764467\r
-21/06/2020,21,6,2020,4951,119,Pakistan,PK,PAK,216565317,Asia,35.86631557\r
-20/06/2020,20,6,2020,6604,153,Pakistan,PK,PAK,216565317,Asia,35.87047136\r
-19/06/2020,19,6,2020,4944,136,Pakistan,PK,PAK,216565317,Asia,35.00699052\r
-18/06/2020,18,6,2020,5358,118,Pakistan,PK,PAK,216565317,Asia,34.564168\r
-17/06/2020,17,6,2020,5839,136,Pakistan,PK,PAK,216565317,Asia,34.30697077\r
-16/06/2020,16,6,2020,4443,110,Pakistan,PK,PAK,216565317,Asia,33.48781837\r
-15/06/2020,15,6,2020,5248,97,Pakistan,PK,PAK,216565317,Asia,33.25463237\r
-14/06/2020,14,6,2020,6825,81,Pakistan,PK,PAK,216565317,Asia,32.19998519\r
-13/06/2020,13,6,2020,6472,88,Pakistan,PK,PAK,216565317,Asia,30.45178282\r
-12/06/2020,12,6,2020,6397,107,Pakistan,PK,PAK,216565317,Asia,28.58490956\r
-11/06/2020,11,6,2020,5834,101,Pakistan,PK,PAK,216565317,Asia,26.92444054\r
-10/06/2020,10,6,2020,5385,83,Pakistan,PK,PAK,216565317,Asia,25.18916729\r
-09/06/2020,9,6,2020,4646,105,Pakistan,PK,PAK,216565317,Asia,23.37031649\r
-08/06/2020,8,6,2020,4728,65,Pakistan,PK,PAK,216565317,Asia,21.85114434\r
-07/06/2020,7,6,2020,4960,67,Pakistan,PK,PAK,216565317,Asia,20.47511606\r
-06/06/2020,6,6,2020,4734,97,Pakistan,PK,PAK,216565317,Asia,19.1840506\r
-05/06/2020,5,6,2020,3985,68,Pakistan,PK,PAK,216565317,Asia,17.80294303\r
-04/06/2020,4,6,2020,4801,82,Pakistan,PK,PAK,216565317,Asia,17.16479837\r
-03/06/2020,3,6,2020,4065,67,Pakistan,PK,PAK,216565317,Asia,15.96054275\r
-02/06/2020,2,6,2020,3938,78,Pakistan,PK,PAK,216565317,Asia,14.9756205\r
-01/06/2020,1,6,2020,2964,60,Pakistan,PK,PAK,216565317,Asia,14.0073214\r
-31/05/2020,31,5,2020,3039,88,Pakistan,PK,PAK,216565317,Asia,13.55018449\r
-30/05/2020,30,5,2020,2429,78,Pakistan,PK,PAK,216565317,Asia,12.77120473\r
-29/05/2020,29,5,2020,2801,57,Pakistan,PK,PAK,216565317,Asia,12.37963695\r
-28/05/2020,28,5,2020,2076,35,Pakistan,PK,PAK,216565317,Asia,11.74657159\r
-27/05/2020,27,5,2020,1446,28,Pakistan,PK,PAK,216565317,Asia,11.45843681\r
-26/05/2020,26,5,2020,1356,30,Pakistan,PK,PAK,216565317,Asia,11.83199616\r
-25/05/2020,25,5,2020,1748,34,Pakistan,PK,PAK,216565317,Asia,11.7322572\r
-24/05/2020,24,5,2020,2164,32,Pakistan,PK,PAK,216565317,Asia,11.60665999\r
-23/05/2020,23,5,2020,1743,34,Pakistan,PK,PAK,216565317,Asia,11.52677647\r
-22/05/2020,22,5,2020,2603,50,Pakistan,PK,PAK,216565317,Asia,11.4778305\r
-21/05/2020,21,5,2020,2193,32,Pakistan,PK,PAK,216565317,Asia,11.09041851\r
-20/05/2020,20,5,2020,1932,46,Pakistan,PK,PAK,216565317,Asia,10.78104302\r
-19/05/2020,19,5,2020,1841,36,Pakistan,PK,PAK,216565317,Asia,10.37331384\r
-18/05/2020,18,5,2020,1974,30,Pakistan,PK,PAK,216565317,Asia,10.130431\r
-17/05/2020,17,5,2020,1352,39,Pakistan,PK,PAK,216565317,Asia,9.71900778\r
-16/05/2020,16,5,2020,1581,31,Pakistan,PK,PAK,216565317,Asia,9.55139091\r
-15/05/2020,15,5,2020,1430,33,Pakistan,PK,PAK,216565317,Asia,9.42025264\r
-14/05/2020,14,5,2020,1452,33,Pakistan,PK,PAK,216565317,Asia,9.24847999\r
-13/05/2020,13,5,2020,2255,31,Pakistan,PK,PAK,216565317,Asia,8.98158591\r
-12/05/2020,12,5,2020,1140,39,Pakistan,PK,PAK,216565317,Asia,8.31250371\r
-11/05/2020,11,5,2020,1476,28,Pakistan,PK,PAK,216565317,Asia,8.13288122\r
-10/05/2020,10,5,2020,1991,21,Pakistan,PK,PAK,216565317,Asia,7.73069309\r
-09/05/2020,9,5,2020,1637,24,Pakistan,PK,PAK,216565317,Asia,7.17289371\r
-08/05/2020,8,5,2020,1764,30,Pakistan,PK,PAK,216565317,Asia,6.77947891\r
-07/05/2020,7,5,2020,1523,38,Pakistan,PK,PAK,216565317,Asia,6.61417082\r
-06/05/2020,6,5,2020,1049,40,Pakistan,PK,PAK,216565317,Asia,5.91091878\r
-05/05/2020,5,5,2020,1315,24,Pakistan,PK,PAK,216565317,Asia,5.67265348\r
-04/05/2020,4,5,2020,1083,22,Pakistan,PK,PAK,216565317,Asia,5.43392643\r
-03/05/2020,3,5,2020,989,23,Pakistan,PK,PAK,216565317,Asia,5.130092\r
-02/05/2020,2,5,2020,1297,32,Pakistan,PK,PAK,216565317,Asia,4.90983512\r
-01/05/2020,1,5,2020,1058,39,Pakistan,PK,PAK,216565317,Asia,4.52149963\r
-30/04/2020,30,4,2020,874,19,Pakistan,PK,PAK,216565317,Asia,4.27307573\r
-29/04/2020,29,4,2020,806,26,Pakistan,PK,PAK,216565317,Asia,4.10822939\r
-28/04/2020,28,4,2020,751,20,Pakistan,PK,PAK,216565317,Asia,3.86165251\r
-27/04/2020,27,4,2020,605,12,Pakistan,PK,PAK,216565317,Asia,3.67279494\r
-26/04/2020,26,4,2020,783,16,Pakistan,PK,PAK,216565317,Asia,3.54858299\r
-25/04/2020,25,4,2020,785,16,Pakistan,PK,PAK,216565317,Asia,3.30246786\r
-24/04/2020,24,4,2020,1406,28,Pakistan,PK,PAK,216565317,Asia,3.0263387\r
-23/04/2020,23,4,2020,0,0,Pakistan,PK,PAK,216565317,Asia,2.50594143\r
-22/04/2020,22,4,2020,533,17,Pakistan,PK,PAK,216565317,Asia,2.62138004\r
-21/04/2020,21,4,2020,798,16,Pakistan,PK,PAK,216565317,Asia,2.47130985\r
-20/04/2020,20,4,2020,425,17,Pakistan,PK,PAK,216565317,Asia,2.37387965\r
-19/04/2020,19,4,2020,512,16,Pakistan,PK,PAK,216565317,Asia,2.55950495\r
-18/04/2020,18,4,2020,456,8,Pakistan,PK,PAK,216565317,Asia,2.39650562\r
-17/04/2020,17,4,2020,520,11,Pakistan,PK,PAK,216565317,Asia,2.18594559\r
-16/04/2020,16,4,2020,517,17,Pakistan,PK,PAK,216565317,Asia,1.94583327\r
-15/04/2020,15,4,2020,272,11,Pakistan,PK,PAK,216565317,Asia,1.82346834\r
-14/04/2020,14,4,2020,342,3,Pakistan,PK,PAK,216565317,Asia,1.88903748\r
-13/04/2020,13,4,2020,336,7,Pakistan,PK,PAK,216565317,Asia,1.77683114\r
-12/04/2020,12,4,2020,250,15,Pakistan,PK,PAK,216565317,Asia,1.67616867\r
-11/04/2020,11,4,2020,187,5,Pakistan,PK,PAK,216565317,Asia,1.65816025\r
-10/04/2020,10,4,2020,279,3,Pakistan,PK,PAK,216565317,Asia,1.57181217\r
-09/04/2020,9,4,2020,250,5,Pakistan,PK,PAK,216565317,Asia,1.5076283\r
-08/04/2020,8,4,2020,208,4,Pakistan,PK,PAK,216565317,Asia,1.42266548\r
-07/04/2020,7,4,2020,587,4,Pakistan,PK,PAK,216565317,Asia,1.37464301\r
-06/04/2020,6,4,2020,827,15,Pakistan,PK,PAK,216565317,Asia,1.15115386\r
-05/04/2020,5,4,2020,159,4,Pakistan,PK,PAK,216565317,Asia,0.83300504\r
-04/04/2020,4,4,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0.829311\r
-03/04/2020,3,4,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0.83716083\r
-02/04/2020,2,4,2020,252,5,Pakistan,PK,PAK,216565317,Asia,0.91842961\r
-01/04/2020,1,4,2020,414,8,Pakistan,PK,PAK,216565317,Asia,0.85516925\r
-31/03/2020,31,3,2020,99,5,Pakistan,PK,PAK,216565317,Asia,0.66400291\r
-30/03/2020,30,3,2020,118,2,Pakistan,PK,PAK,216565317,Asia,0.69032291\r
-29/03/2020,29,3,2020,211,2,Pakistan,PK,PAK,216565317,Asia,0.63629764\r
-28/03/2020,28,3,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0.54302324\r
-27/03/2020,27,3,2020,140,1,Pakistan,PK,PAK,216565317,Asia,0.54302324\r
-26/03/2020,26,3,2020,66,1,Pakistan,PK,PAK,216565317,Asia,0.47883937\r
-25/03/2020,25,3,2020,104,1,Pakistan,PK,PAK,216565317,Asia,0.45021059\r
-24/03/2020,24,3,2020,103,1,Pakistan,PK,PAK,216565317,Asia,0.40218813\r
-23/03/2020,23,3,2020,138,2,Pakistan,PK,PAK,216565317,Asia,0.35924497\r
-22/03/2020,22,3,2020,151,0,Pakistan,PK,PAK,216565317,Asia,0.29598461\r
-21/03/2020,21,3,2020,17,1,Pakistan,PK,PAK,216565317,Asia,0.22672144\r
-20/03/2020,20,3,2020,176,2,Pakistan,PK,PAK,216565317,Asia,0.21887161\r
-19/03/2020,19,3,2020,115,0,Pakistan,PK,PAK,216565317,Asia,0.13852634\r
-18/03/2020,18,3,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0.08542457\r
-17/03/2020,17,3,2020,156,0,Pakistan,PK,PAK,216565317,Asia,0.08542457\r
-16/03/2020,16,3,2020,1,0,Pakistan,PK,PAK,216565317,Asia,0.01431439\r
-15/03/2020,15,3,2020,9,0,Pakistan,PK,PAK,216565317,Asia,0.01385263\r
-14/03/2020,14,3,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0.00969684\r
-13/03/2020,13,3,2020,1,0,Pakistan,PK,PAK,216565317,Asia,0.00969684\r
-12/03/2020,12,3,2020,4,0,Pakistan,PK,PAK,216565317,Asia,0.00923509\r
-11/03/2020,11,3,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0.00738807\r
-10/03/2020,10,3,2020,10,0,Pakistan,PK,PAK,216565317,Asia,0.00738807\r
-07/03/2020,7,3,2020,1,0,Pakistan,PK,PAK,216565317,Asia,0.00277053\r
-04/03/2020,4,3,2020,1,0,Pakistan,PK,PAK,216565317,Asia,0.00230877\r
-02/03/2020,2,3,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0.00184702\r
-01/03/2020,1,3,2020,2,0,Pakistan,PK,PAK,216565317,Asia,0.00184702\r
-29/02/2020,29,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0.00092351\r
-28/02/2020,28,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0.00092351\r
-27/02/2020,27,2,2020,2,0,Pakistan,PK,PAK,216565317,Asia,0.00092351\r
-26/02/2020,26,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-25/02/2020,25,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-24/02/2020,24,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-23/02/2020,23,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-22/02/2020,22,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-21/02/2020,21,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-20/02/2020,20,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-19/02/2020,19,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-18/02/2020,18,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-17/02/2020,17,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-16/02/2020,16,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-15/02/2020,15,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-14/02/2020,14,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-13/02/2020,13,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-12/02/2020,12,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-11/02/2020,11,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-10/02/2020,10,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-09/02/2020,9,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-08/02/2020,8,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-07/02/2020,7,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-06/02/2020,6,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-05/02/2020,5,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-04/02/2020,4,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-03/02/2020,3,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-02/02/2020,2,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-01/02/2020,1,2,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-31/01/2020,31,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-30/01/2020,30,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-29/01/2020,29,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-28/01/2020,28,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-27/01/2020,27,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-26/01/2020,26,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-25/01/2020,25,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-24/01/2020,24,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-23/01/2020,23,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-22/01/2020,22,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-21/01/2020,21,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-20/01/2020,20,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-19/01/2020,19,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-18/01/2020,18,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-17/01/2020,17,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-16/01/2020,16,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-15/01/2020,15,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-14/01/2020,14,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-13/01/2020,13,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,0\r
-12/01/2020,12,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,\r
-11/01/2020,11,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,\r
-10/01/2020,10,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,\r
-09/01/2020,9,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,\r
-08/01/2020,8,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,\r
-07/01/2020,7,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,\r
-06/01/2020,6,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,\r
-05/01/2020,5,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,\r
-04/01/2020,4,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,\r
-03/01/2020,3,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,\r
-02/01/2020,2,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,\r
-01/01/2020,1,1,2020,0,0,Pakistan,PK,PAK,216565317,Asia,\r
-31/12/2019,31,12,2019,0,0,Pakistan,PK,PAK,216565317,Asia,\r
-19/08/2020,19,8,2020,612,3,Palestine,PS,PSE,4981422,Asia,127.97550579\r
-18/08/2020,18,8,2020,456,0,Palestine,PS,PSE,4981422,Asia,127.81490908\r
-17/08/2020,17,8,2020,381,2,Palestine,PS,PSE,4981422,Asia,123.55909618\r
-16/08/2020,16,8,2020,498,3,Palestine,PS,PSE,4981422,Asia,120.42746027\r
-15/08/2020,15,8,2020,531,1,Palestine,PS,PSE,4981422,Asia,116.91440717\r
-14/08/2020,14,8,2020,432,1,Palestine,PS,PSE,4981422,Asia,114.16418846\r
-13/08/2020,13,8,2020,499,1,Palestine,PS,PSE,4981422,Asia,113.12030982\r
-12/08/2020,12,8,2020,473,3,Palestine,PS,PSE,4981422,Asia,113.5418762\r
-11/08/2020,11,8,2020,470,7,Palestine,PS,PSE,4981422,Asia,113.70247291\r
-10/08/2020,10,8,2020,277,0,Palestine,PS,PSE,4981422,Asia,110.85188125\r
-09/08/2020,9,8,2020,426,6,Palestine,PS,PSE,4981422,Asia,111.71508858\r
-08/08/2020,8,8,2020,514,5,Palestine,PS,PSE,4981422,Asia,110.83180666\r
-07/08/2020,7,8,2020,453,1,Palestine,PS,PSE,4981422,Asia,111.45411892\r
-06/08/2020,6,8,2020,353,4,Palestine,PS,PSE,4981422,Asia,114.44523271\r
-05/08/2020,5,8,2020,604,0,Palestine,PS,PSE,4981422,Asia,114.52553106\r
-04/08/2020,4,8,2020,244,0,Palestine,PS,PSE,4981422,Asia,110.49053865\r
-03/08/2020,3,8,2020,225,2,Palestine,PS,PSE,4981422,Asia,114.98724661\r
-02/08/2020,2,8,2020,323,0,Palestine,PS,PSE,4981422,Asia,119.80514801\r
-01/08/2020,1,8,2020,394,1,Palestine,PS,PSE,4981422,Asia,123.98066255\r
-31/07/2020,31,7,2020,380,2,Palestine,PS,PSE,4981422,Asia,124.88401906\r
-30/07/2020,30,7,2020,520,1,Palestine,PS,PSE,4981422,Asia,126.55020996\r
-29/07/2020,29,7,2020,481,2,Palestine,PS,PSE,4981422,Asia,124.54275105\r
-28/07/2020,28,7,2020,328,1,Palestine,PS,PSE,4981422,Asia,120.76872829\r
-27/07/2020,27,7,2020,320,4,Palestine,PS,PSE,4981422,Asia,122.27432247\r
-26/07/2020,26,7,2020,382,3,Palestine,PS,PSE,4981422,Asia,122.69588884\r
-25/07/2020,25,7,2020,545,1,Palestine,PS,PSE,4981422,Asia,124.50260187\r
-24/07/2020,24,7,2020,602,3,Palestine,PS,PSE,4981422,Asia,121.51148809\r
-23/07/2020,23,7,2020,357,0,Palestine,PS,PSE,4981422,Asia,114.68612778\r
-22/07/2020,22,7,2020,403,1,Palestine,PS,PSE,4981422,Asia,117.0549293\r
-21/07/2020,21,7,2020,468,4,Palestine,PS,PSE,4981422,Asia,115.10769415\r
-20/07/2020,20,7,2020,465,4,Palestine,PS,PSE,4981422,Asia,112.29725167\r
-19/07/2020,19,7,2020,531,3,Palestine,PS,PSE,4981422,Asia,107.13808226\r
-18/07/2020,18,7,2020,439,6,Palestine,PS,PSE,4981422,Asia,107.74031993\r
-17/07/2020,17,7,2020,463,2,Palestine,PS,PSE,4981422,Asia,104.38786355\r
-16/07/2020,16,7,2020,420,0,Palestine,PS,PSE,4981422,Asia,101.55734648\r
-15/07/2020,15,7,2020,293,6,Palestine,PS,PSE,4981422,Asia,99.75063345\r
-14/07/2020,14,7,2020,403,4,Palestine,PS,PSE,4981422,Asia,100.33279654\r
-13/07/2020,13,7,2020,341,5,Palestine,PS,PSE,4981422,Asia,96.157282\r
-12/07/2020,12,7,2020,472,2,Palestine,PS,PSE,4981422,Asia,93.22639198\r
-11/07/2020,11,7,2020,396,3,Palestine,PS,PSE,4981422,Asia,88.93042991\r
-10/07/2020,10,7,2020,262,2,Palestine,PS,PSE,4981422,Asia,85.13633256\r
-09/07/2020,9,7,2020,475,3,Palestine,PS,PSE,4981422,Asia,80.96081802\r
-08/07/2020,8,7,2020,306,1,Palestine,PS,PSE,4981422,Asia,74.61724785\r
-07/07/2020,7,7,2020,328,1,Palestine,PS,PSE,4981422,Asia,72.06777502\r
-06/07/2020,6,7,2020,208,4,Palestine,PS,PSE,4981422,Asia,68.9762883\r
-05/07/2020,5,7,2020,561,1,Palestine,PS,PSE,4981422,Asia,65.66398109\r
-04/07/2020,4,7,2020,272,4,Palestine,PS,PSE,4981422,Asia,56.83116187\r
-03/07/2020,3,7,2020,322,0,Palestine,PS,PSE,4981422,Asia,52.63557273\r
-02/07/2020,2,7,2020,330,2,Palestine,PS,PSE,4981422,Asia,48.05856641\r
-01/07/2020,1,7,2020,322,1,Palestine,PS,PSE,4981422,Asia,41.65477247\r
-30/06/2020,30,6,2020,195,1,Palestine,PS,PSE,4981422,Asia,35.27105312\r
-29/06/2020,29,6,2020,195,1,Palestine,PS,PSE,4981422,Asia,31.6174779\r
-28/06/2020,28,6,2020,258,1,Palestine,PS,PSE,4981422,Asia,27.70293302\r
-27/06/2020,27,6,2020,207,0,Palestine,PS,PSE,4981422,Asia,22.60398738\r
-26/06/2020,26,6,2020,54,0,Palestine,PS,PSE,4981422,Asia,18.4886966\r
-25/06/2020,25,6,2020,159,0,Palestine,PS,PSE,4981422,Asia,17.44481797\r
-24/06/2020,24,6,2020,179,0,Palestine,PS,PSE,4981422,Asia,14.33325665\r
-23/06/2020,23,6,2020,174,0,Palestine,PS,PSE,4981422,Asia,10.92057649\r
-22/06/2020,22,6,2020,43,0,Palestine,PS,PSE,4981422,Asia,7.44767257\r
-21/06/2020,21,6,2020,121,0,Palestine,PS,PSE,4981422,Asia,6.74506195\r
-20/06/2020,20,6,2020,63,0,Palestine,PS,PSE,4981422,Asia,4.31603667\r
-19/06/2020,19,6,2020,94,0,Palestine,PS,PSE,4981422,Asia,3.05133755\r
-18/06/2020,18,6,2020,11,0,Palestine,PS,PSE,4981422,Asia,1.32492288\r
-17/06/2020,17,6,2020,4,0,Palestine,PS,PSE,4981422,Asia,1.20447535\r
-16/06/2020,16,6,2020,13,0,Palestine,PS,PSE,4981422,Asia,1.16432617\r
-15/06/2020,15,6,2020,0,0,Palestine,PS,PSE,4981422,Asia,0.9234311\r
-14/06/2020,14,6,2020,4,0,Palestine,PS,PSE,4981422,Asia,0.94350569\r
-13/06/2020,13,6,2020,2,0,Palestine,PS,PSE,4981422,Asia,0.88328192\r
-12/06/2020,12,6,2020,2,0,Palestine,PS,PSE,4981422,Asia,0.84313274\r
-11/06/2020,11,6,2020,4,0,Palestine,PS,PSE,4981422,Asia,1.04387864\r
-10/06/2020,10,6,2020,9,0,Palestine,PS,PSE,4981422,Asia,1.12417699\r
-09/06/2020,9,6,2020,1,0,Palestine,PS,PSE,4981422,Asia,1.00372946\r
-08/06/2020,8,6,2020,8,0,Palestine,PS,PSE,4981422,Asia,0.98365487\r
-07/06/2020,7,6,2020,0,0,Palestine,PS,PSE,4981422,Asia,0.82305815\r
-06/06/2020,6,6,2020,0,0,Palestine,PS,PSE,4981422,Asia,0.82305815\r
-05/06/2020,5,6,2020,8,0,Palestine,PS,PSE,4981422,Asia,0.82305815\r
-04/06/2020,4,6,2020,5,0,Palestine,PS,PSE,4981422,Asia,1.16432617\r
-03/06/2020,3,6,2020,2,0,Palestine,PS,PSE,4981422,Asia,1.20447535\r
-02/06/2020,2,6,2020,1,0,Palestine,PS,PSE,4981422,Asia,1.22454994\r
-01/06/2020,1,6,2020,1,0,Palestine,PS,PSE,4981422,Asia,1.34499747\r
-31/05/2020,31,5,2020,1,0,Palestine,PS,PSE,4981422,Asia,1.44537042\r
-30/05/2020,30,5,2020,0,0,Palestine,PS,PSE,4981422,Asia,1.42529583\r
-29/05/2020,29,5,2020,12,0,Palestine,PS,PSE,4981422,Asia,1.54574336\r
-28/05/2020,28,5,2020,8,0,Palestine,PS,PSE,4981422,Asia,1.30484829\r
-27/05/2020,27,5,2020,3,0,Palestine,PS,PSE,4981422,Asia,1.16432617\r
-26/05/2020,26,5,2020,0,0,Palestine,PS,PSE,4981422,Asia,1.1041024\r
-25/05/2020,25,5,2020,0,0,Palestine,PS,PSE,4981422,Asia,1.1041024\r
-24/05/2020,24,5,2020,0,1,Palestine,PS,PSE,4981422,Asia,1.1041024\r
-23/05/2020,23,5,2020,0,0,Palestine,PS,PSE,4981422,Asia,1.1041024\r
-22/05/2020,22,5,2020,25,0,Palestine,PS,PSE,4981422,Asia,1.1041024\r
-21/05/2020,21,5,2020,7,0,Palestine,PS,PSE,4981422,Asia,0.62231226\r
-20/05/2020,20,5,2020,3,0,Palestine,PS,PSE,4981422,Asia,0.64238685\r
-19/05/2020,19,5,2020,7,0,Palestine,PS,PSE,4981422,Asia,0.86320733\r
-18/05/2020,18,5,2020,6,0,Palestine,PS,PSE,4981422,Asia,0.76283439\r
-17/05/2020,17,5,2020,0,0,Palestine,PS,PSE,4981422,Asia,0.7427598\r
-16/05/2020,16,5,2020,6,0,Palestine,PS,PSE,4981422,Asia,0.7427598\r
-15/05/2020,15,5,2020,0,0,Palestine,PS,PSE,4981422,Asia,0.82305815\r
-14/05/2020,14,5,2020,1,0,Palestine,PS,PSE,4981422,Asia,0.82305815\r
-13/05/2020,13,5,2020,0,0,Palestine,PS,PSE,4981422,Asia,1.04387864\r
-12/05/2020,12,5,2020,0,0,Palestine,PS,PSE,4981422,Asia,1.04387864\r
-11/05/2020,11,5,2020,0,0,Palestine,PS,PSE,4981422,Asia,1.04387864\r
-10/05/2020,10,5,2020,0,0,Palestine,PS,PSE,4981422,Asia,4.11529077\r
-09/05/2020,9,5,2020,0,0,Palestine,PS,PSE,4981422,Asia,4.15543995\r
-08/05/2020,8,5,2020,1,0,Palestine,PS,PSE,4981422,Asia,4.23573831\r
-07/05/2020,7,5,2020,8,0,Palestine,PS,PSE,4981422,Asia,4.23573831\r
-06/05/2020,6,5,2020,14,0,Palestine,PS,PSE,4981422,Asia,4.19558913\r
-05/05/2020,5,5,2020,2,0,Palestine,PS,PSE,4981422,Asia,3.91454488\r
-04/05/2020,4,5,2020,5,0,Palestine,PS,PSE,4981422,Asia,4.01491783\r
-03/05/2020,3,5,2020,0,0,Palestine,PS,PSE,4981422,Asia,4.09521619\r
-02/05/2020,2,5,2020,10,0,Palestine,PS,PSE,4981422,Asia,4.21566372\r
-01/05/2020,1,5,2020,0,2,Palestine,PS,PSE,4981422,Asia,4.27588749\r
-30/04/2020,30,4,2020,12,0,Palestine,PS,PSE,4981422,Asia,4.33611125\r
-29/04/2020,29,4,2020,0,0,Palestine,PS,PSE,4981422,Asia,4.17551454\r
-28/04/2020,28,4,2020,0,0,Palestine,PS,PSE,4981422,Asia,4.55693174\r
-27/04/2020,27,4,2020,153,0,Palestine,PS,PSE,4981422,Asia,4.55693174\r
-26/04/2020,26,4,2020,2,0,Palestine,PS,PSE,4981422,Asia,1.4855196\r
-25/04/2020,25,4,2020,4,0,Palestine,PS,PSE,4981422,Asia,1.4855196\r
-24/04/2020,24,4,2020,1,0,Palestine,PS,PSE,4981422,Asia,1.46544501\r
-23/04/2020,23,4,2020,6,0,Palestine,PS,PSE,4981422,Asia,1.44537042\r
-22/04/2020,22,4,2020,0,0,Palestine,PS,PSE,4981422,Asia,1.38514665\r
-21/04/2020,21,4,2020,7,0,Palestine,PS,PSE,4981422,Asia,1.52566877\r
-20/04/2020,20,4,2020,9,0,Palestine,PS,PSE,4981422,Asia,2.10783186\r
-19/04/2020,19,4,2020,6,0,Palestine,PS,PSE,4981422,Asia,3.17178508\r
-18/04/2020,18,4,2020,13,0,Palestine,PS,PSE,4981422,Asia,3.05133755\r
-17/04/2020,17,4,2020,3,0,Palestine,PS,PSE,4981422,Asia,3.21193426\r
-16/04/2020,16,4,2020,4,0,Palestine,PS,PSE,4981422,Asia,3.49297851\r
-15/04/2020,15,4,2020,19,0,Palestine,PS,PSE,4981422,Asia,3.45282933\r
-14/04/2020,14,4,2020,0,0,Palestine,PS,PSE,4981422,Asia,3.25208344\r
-13/04/2020,13,4,2020,0,0,Palestine,PS,PSE,4981422,Asia,3.43275474\r
-12/04/2020,12,4,2020,2,0,Palestine,PS,PSE,4981422,Asia,3.55320228\r
-11/04/2020,11,4,2020,3,1,Palestine,PS,PSE,4981422,Asia,3.65357522\r
-10/04/2020,10,4,2020,0,0,Palestine,PS,PSE,4981422,Asia,4.03499242\r
-09/04/2020,9,4,2020,3,0,Palestine,PS,PSE,4981422,Asia,4.0751416\r
-08/04/2020,8,4,2020,7,0,Palestine,PS,PSE,4981422,Asia,4.03499242\r
-07/04/2020,7,4,2020,36,0,Palestine,PS,PSE,4981422,Asia,3.89447029\r
-06/04/2020,6,4,2020,62,0,Palestine,PS,PSE,4981422,Asia,3.31230721\r
-04/04/2020,4,4,2020,0,0,Palestine,PS,PSE,4981422,Asia,2.14798104\r
-03/04/2020,3,4,2020,21,0,Palestine,PS,PSE,4981422,Asia,2.16805563\r
-02/04/2020,2,4,2020,17,0,Palestine,PS,PSE,4981422,Asia,1.80671302\r
-01/04/2020,1,4,2020,2,0,Palestine,PS,PSE,4981422,Asia,1.52566877\r
-31/03/2020,31,3,2020,9,0,Palestine,PS,PSE,4981422,Asia,1.52566877\r
-30/03/2020,30,3,2020,9,0,Palestine,PS,PSE,4981422,Asia,1.36507206\r
-29/03/2020,29,3,2020,6,0,Palestine,PS,PSE,4981422,Asia,1.18440076\r
-28/03/2020,28,3,2020,7,0,Palestine,PS,PSE,4981422,Asia,1.12417699\r
-27/03/2020,27,3,2020,22,1,Palestine,PS,PSE,4981422,Asia,1.08402781\r
-26/03/2020,26,3,2020,2,0,Palestine,PS,PSE,4981422,Asia,0.66246144\r
-25/03/2020,25,3,2020,1,0,Palestine,PS,PSE,4981422,Asia,0.80298357\r
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-22/04/2020,22,4,2020,163,5,Panama,PA,PAN,4246440,America,60.56838199\r
-21/04/2020,21,4,2020,191,10,Panama,PA,PAN,4246440,America,60.23869406\r
-20/04/2020,20,4,2020,194,6,Panama,PA,PAN,4246440,America,58.37831219\r
-19/04/2020,19,4,2020,63,4,Panama,PA,PAN,4246440,America,58.21346822\r
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-15/04/2020,15,4,2020,102,1,Panama,PA,PAN,4246440,America,56.35308635\r
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-24/03/2020,24,3,2020,32,3,Panama,PA,PAN,4246440,America,8.10090334\r
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-25/05/2020,25,5,2020,4205,83,Peru,PE,PER,32510462,America,161.9540196\r
-24/05/2020,24,5,2020,4056,129,Peru,PE,PER,32510462,America,156.06975994\r
-23/05/2020,23,5,2020,2929,96,Peru,PE,PER,32510462,America,153.33833152\r
-22/05/2020,22,5,2020,4749,124,Peru,PE,PER,32510462,America,154.54409722\r
-21/05/2020,21,5,2020,4537,110,Peru,PE,PER,32510462,America,151.34512699\r
-20/05/2020,20,5,2020,4550,125,Peru,PE,PER,32510462,America,148.54910398\r
-19/05/2020,19,5,2020,2660,141,Peru,PE,PER,32510462,America,146.29444515\r
-18/05/2020,18,5,2020,3732,125,Peru,PE,PER,32510462,America,142.55411074\r
-17/05/2020,17,5,2020,4046,130,Peru,PE,PER,32510462,America,141.51444541\r
-16/05/2020,16,5,2020,3891,126,Peru,PE,PER,32510462,America,135.45178164\r
-15/05/2020,15,5,2020,4298,98,Peru,PE,PER,32510462,America,134.19680102\r
-14/05/2020,14,5,2020,4247,112,Peru,PE,PER,32510462,America,130.34265708\r
-13/05/2020,13,5,2020,3237,96,Peru,PE,PER,32510462,America,125.71030212\r
-12/05/2020,12,5,2020,1515,72,Peru,PE,PER,32510462,America,123.41565617\r
-11/05/2020,11,5,2020,2292,75,Peru,PE,PER,32510462,America,122.39137051\r
-10/05/2020,10,5,2020,3168,100,Peru,PE,PER,32510462,America,122.06532162\r
-09/05/2020,9,5,2020,3321,87,Peru,PE,PER,32510462,America,123.64942707\r
-08/05/2020,8,5,2020,3709,94,Peru,PE,PER,32510462,America,115.69198863\r
-07/05/2020,7,5,2020,3628,89,Peru,PE,PER,32510462,America,109.40170583\r
-06/05/2020,6,5,2020,3817,100,Peru,PE,PER,32510462,America,102.58851443\r
-05/05/2020,5,5,2020,1444,58,Peru,PE,PER,32510462,America,95.49848907\r
-04/05/2020,4,5,2020,3394,86,Peru,PE,PER,32510462,America,93.20076719\r
-03/05/2020,3,5,2020,2075,76,Peru,PE,PER,32510462,America,86.47677784\r
-02/05/2020,2,5,2020,3483,73,Peru,PE,PER,32510462,America,82.9579106\r
-01/05/2020,1,5,2020,3045,108,Peru,PE,PER,32510462,America,75.31421731\r
-30/04/2020,30,4,2020,2741,89,Peru,PE,PER,32510462,America,69.07314944\r
-29/04/2020,29,4,2020,2491,72,Peru,PE,PER,32510462,America,64.2470107\r
-28/04/2020,28,4,2020,1182,54,Peru,PE,PER,32510462,America,65.14825904\r
-27/04/2020,27,4,2020,2186,28,Peru,PE,PER,32510462,America,61.51250634\r
-26/04/2020,26,4,2020,3683,66,Peru,PE,PER,32510462,America,56.85246798\r
-25/04/2020,25,4,2020,734,62,Peru,PE,PER,32510462,America,48.44901927\r
-24/04/2020,24,4,2020,1664,42,Peru,PE,PER,32510462,America,48.16295751\r
-23/04/2020,23,4,2020,1413,46,Peru,PE,PER,32510462,America,45.85600783\r
-22/04/2020,22,4,2020,1512,39,Peru,PE,PER,32510462,America,45.77910951\r
-21/04/2020,21,4,2020,697,45,Peru,PE,PER,32510462,America,42.33714058\r
-20/04/2020,20,4,2020,1208,52,Peru,PE,PER,32510462,America,41.05447656\r
-19/04/2020,19,4,2020,931,48,Peru,PE,PER,32510462,America,38.98437371\r
-18/04/2020,18,4,2020,998,26,Peru,PE,PER,32510462,America,36.58514604\r
-17/04/2020,17,4,2020,1016,20,Peru,PE,PER,32510462,America,34.07210885\r
-16/04/2020,16,4,2020,1172,24,Peru,PE,PER,32510462,America,31.22687091\r
-15/04/2020,15,4,2020,2784,37,Peru,PE,PER,32510462,America,28.41546823\r
-14/04/2020,14,4,2020,0,0,Peru,PE,PER,32510462,America,20.20580329\r
-13/04/2020,13,4,2020,671,12,Peru,PE,PER,32510462,America,20.50724471\r
-12/04/2020,12,4,2020,951,12,Peru,PE,PER,32510462,America,19.00003759\r
-11/04/2020,11,4,2020,641,31,Peru,PE,PER,32510462,America,16.18555897\r
-10/04/2020,10,4,2020,914,17,Peru,PE,PER,32510462,America,14.38306229\r
-09/04/2020,9,4,2020,1388,14,Peru,PE,PER,32510462,America,11.63933013\r
-08/04/2020,8,4,2020,393,15,Peru,PE,PER,32510462,America,7.80671773\r
-07/04/2020,7,4,2020,280,9,Peru,PE,PER,32510462,America,6.66247068\r
-06/04/2020,6,4,2020,535,10,Peru,PE,PER,32510462,America,5.89963932\r
-05/04/2020,5,4,2020,151,12,Peru,PE,PER,32510462,America,4.3924322\r
-04/04/2020,4,4,2020,181,6,Peru,PE,PER,32510462,America,4.09714264\r
-03/04/2020,3,4,2020,91,8,Peru,PE,PER,32510462,America,3.62960083\r
-02/04/2020,2,4,2020,258,17,Peru,PE,PER,32510462,America,3.62344897\r
-01/04/2020,1,4,2020,115,6,Peru,PE,PER,32510462,America,2.9159844\r
-31/03/2020,31,3,2020,98,6,Peru,PE,PER,32510462,America,2.65760603\r
-30/03/2020,30,3,2020,181,2,Peru,PE,PER,32510462,America,2.4023036\r
-29/03/2020,29,3,2020,36,5,Peru,PE,PER,32510462,America,1.93168587\r
-28/03/2020,28,3,2020,55,2,Peru,PE,PER,32510462,America,1.83633195\r
-27/03/2020,27,3,2020,22,1,Peru,PE,PER,32510462,America,1.71637056\r
-26/03/2020,26,3,2020,142,1,Peru,PE,PER,32510462,America,1.6640797\r
-25/03/2020,25,3,2020,21,2,Peru,PE,PER,32510462,America,1.24575283\r
-24/03/2020,24,3,2020,32,0,Peru,PE,PER,32510462,America,1.1873101\r
-23/03/2020,23,3,2020,45,0,Peru,PE,PER,32510462,America,1.09503212\r
-22/03/2020,22,3,2020,55,2,Peru,PE,PER,32510462,America,0.97507073\r
-21/03/2020,21,3,2020,29,1,Peru,PE,PER,32510462,America,0.80897036\r
-20/03/2020,20,3,2020,89,2,Peru,PE,PER,32510462,America,\r
-19/03/2020,19,3,2020,28,0,Peru,PE,PER,32510462,America,\r
-18/03/2020,18,3,2020,31,0,Peru,PE,PER,32510462,America,\r
-17/03/2020,17,3,2020,15,0,Peru,PE,PER,32510462,America,\r
-16/03/2020,16,3,2020,28,0,Peru,PE,PER,32510462,America,\r
-15/03/2020,15,3,2020,5,0,Peru,PE,PER,32510462,America,\r
-14/03/2020,14,3,2020,16,0,Peru,PE,PER,32510462,America,\r
-13/03/2020,13,3,2020,5,0,Peru,PE,PER,32510462,America,\r
-12/03/2020,12,3,2020,6,0,Peru,PE,PER,32510462,America,\r
-11/03/2020,11,3,2020,2,0,Peru,PE,PER,32510462,America,\r
-10/03/2020,10,3,2020,2,0,Peru,PE,PER,32510462,America,\r
-09/03/2020,9,3,2020,6,0,Peru,PE,PER,32510462,America,\r
-07/03/2020,7,3,2020,1,0,Peru,PE,PER,32510462,America,\r
-19/08/2020,19,8,2020,4739,6,Philippines,PH,PHL,108116622,Asia,52.36937573\r
-18/08/2020,18,8,2020,3221,16,Philippines,PH,PHL,108116622,Asia,53.77896472\r
-17/08/2020,17,8,2020,3335,65,Philippines,PH,PHL,108116622,Asia,53.70867025\r
-16/08/2020,16,8,2020,4258,158,Philippines,PH,PHL,108116622,Asia,55.2052024\r
-15/08/2020,15,8,2020,6134,16,Philippines,PH,PHL,108116622,Asia,55.77865724\r
-14/08/2020,14,8,2020,3777,22,Philippines,PH,PHL,108116622,Asia,53.78636414\r
-13/08/2020,13,8,2020,4211,92,Philippines,PH,PHL,108116622,Asia,53.88903105\r
-12/08/2020,12,8,2020,2900,19,Philippines,PH,PHL,108116622,Asia,51.67105572\r
-11/08/2020,11,8,2020,6725,23,Philippines,PH,PHL,108116622,Asia,50.49917301\r
-10/08/2020,10,8,2020,3028,61,Philippines,PH,PHL,108116622,Asia,45.75152191\r
-09/08/2020,9,8,2020,4131,41,Philippines,PH,PHL,108116622,Asia,44.83399417\r
-08/08/2020,8,8,2020,3294,18,Philippines,PH,PHL,108116622,Asia,42.83337672\r
-07/08/2020,7,8,2020,3480,27,Philippines,PH,PHL,108116622,Asia,41.68646704\r
-06/08/2020,6,8,2020,3387,8,Philippines,PH,PHL,108116622,Asia,40.42949104\r
-05/08/2020,5,8,2020,6263,11,Philippines,PH,PHL,108116622,Asia,38.68877812\r
-04/08/2020,4,8,2020,3145,45,Philippines,PH,PHL,108116622,Asia,34.62187341\r
-03/08/2020,3,8,2020,4953,20,Philippines,PH,PHL,108116622,Asia,33.04672245\r
-02/08/2020,2,8,2020,4878,16,Philippines,PH,PHL,108116622,Asia,30.45600148\r
-01/08/2020,1,8,2020,3980,40,Philippines,PH,PHL,108116622,Asia,28.07431405\r
-31/07/2020,31,7,2020,3888,21,Philippines,PH,PHL,108116622,Asia,25.99785258\r
-30/07/2020,30,7,2020,1813,15,Philippines,PH,PHL,108116622,Asia,24.6363598\r
-29/07/2020,29,7,2020,1633,2,Philippines,PH,PHL,108116622,Asia,24.1664968\r
-28/07/2020,28,7,2020,1592,13,Philippines,PH,PHL,108116622,Asia,23.15462649\r
-27/07/2020,27,7,2020,2036,35,Philippines,PH,PHL,108116622,Asia,22.37306304\r
-26/07/2020,26,7,2020,1968,18,Philippines,PH,PHL,108116622,Asia,22.37398797\r
-25/07/2020,25,7,2020,2054,8,Philippines,PH,PHL,108116622,Asia,21.76353605\r
-24/07/2020,24,7,2020,2121,28,Philippines,PH,PHL,108116622,Asia,20.93665117\r
-23/07/2020,23,7,2020,1505,6,Philippines,PH,PHL,108116622,Asia,20.26515405\r
-22/07/2020,22,7,2020,1866,2,Philippines,PH,PHL,108116622,Asia,21.17250759\r
-21/07/2020,21,7,2020,1442,4,Philippines,PH,PHL,108116622,Asia,20.87098134\r
-20/07/2020,20,7,2020,2152,58,Philippines,PH,PHL,108116622,Asia,23.70218337\r
-19/07/2020,19,7,2020,2303,113,Philippines,PH,PHL,108116622,Asia,21.71174012\r
-18/07/2020,18,7,2020,1735,17,Philippines,PH,PHL,108116622,Asia,20.96347405\r
-17/07/2020,17,7,2020,2416,29,Philippines,PH,PHL,108116622,Asia,20.77478891\r
-16/07/2020,16,7,2020,1305,11,Philippines,PH,PHL,108116622,Asia,18.81209348\r
-15/07/2020,15,7,2020,539,4,Philippines,PH,PHL,108116622,Asia,18.52721592\r
-14/07/2020,14,7,2020,747,65,Philippines,PH,PHL,108116622,Asia,19.0239018\r
-13/07/2020,13,7,2020,2037,162,Philippines,PH,PHL,108116622,Asia,19.24218461\r
-12/07/2020,12,7,2020,1308,12,Philippines,PH,PHL,108116622,Asia,17.9611605\r
-11/07/2020,11,7,2020,1160,42,Philippines,PH,PHL,108116622,Asia,17.4265526\r
-10/07/2020,10,7,2020,1395,4,Philippines,PH,PHL,108116622,Asia,17.28226396\r
-09/07/2020,9,7,2020,2486,5,Philippines,PH,PHL,108116622,Asia,16.7078842\r
-08/07/2020,8,7,2020,1540,6,Philippines,PH,PHL,108116622,Asia,14.84323104\r
-07/07/2020,7,7,2020,4503,13,Philippines,PH,PHL,108116622,Asia,14.47603496\r
-06/07/2020,6,7,2020,0,0,Philippines,PH,PHL,108116622,Asia,10.89379208\r
-05/07/2020,5,7,2020,1494,10,Philippines,PH,PHL,108116622,Asia,11.49684458\r
-04/07/2020,4,7,2020,1531,6,Philippines,PH,PHL,108116622,Asia,10.98535986\r
-03/07/2020,3,7,2020,294,4,Philippines,PH,PHL,108116622,Asia,10.17974831\r
-02/07/2020,2,7,2020,997,4,Philippines,PH,PHL,108116622,Asia,10.42670386\r
-01/07/2020,1,7,2020,1076,11,Philippines,PH,PHL,108116622,Asia,9.92724319\r
-30/06/2020,30,6,2020,983,11,Philippines,PH,PHL,108116622,Asia,9.26592028\r
-29/06/2020,29,6,2020,652,8,Philippines,PH,PHL,108116622,Asia,8.80993119\r
-28/06/2020,28,6,2020,730,12,Philippines,PH,PHL,108116622,Asia,8.70448949\r
-27/06/2020,27,6,2020,1004,12,Philippines,PH,PHL,108116622,Asia,8.5888736\r
-26/06/2020,26,6,2020,774,8,Philippines,PH,PHL,108116622,Asia,8.22630215\r
-25/06/2020,25,6,2020,470,18,Philippines,PH,PHL,108116622,Asia,7.92015126\r
-24/06/2020,24,6,2020,1143,9,Philippines,PH,PHL,108116622,Asia,8.16988159\r
-23/06/2020,23,6,2020,630,8,Philippines,PH,PHL,108116622,Asia,7.59180212\r
-22/06/2020,22,6,2020,652,19,Philippines,PH,PHL,108116622,Asia,7.54463083\r
-21/06/2020,21,6,2020,941,20,Philippines,PH,PHL,108116622,Asia,7.4549129\r
-20/06/2020,20,6,2020,660,14,Philippines,PH,PHL,108116622,Asia,7.24495443\r
-19/06/2020,19,6,2020,561,8,Philippines,PH,PHL,108116622,Asia,6.86018474\r
-18/06/2020,18,6,2020,457,5,Philippines,PH,PHL,108116622,Asia,6.92770442\r
-17/06/2020,17,6,2020,361,5,Philippines,PH,PHL,108116622,Asia,7.199633\r
-16/06/2020,16,6,2020,490,10,Philippines,PH,PHL,108116622,Asia,7.19778315\r
-15/06/2020,15,6,2020,538,14,Philippines,PH,PHL,108116622,Asia,7.25512863\r
-14/06/2020,14,6,2020,605,22,Philippines,PH,PHL,108116622,Asia,7.55480503\r
-13/06/2020,13,6,2020,612,16,Philippines,PH,PHL,108116622,Asia,7.54093113\r
-12/06/2020,12,6,2020,443,9,Philippines,PH,PHL,108116622,Asia,7.94234951\r
-11/06/2020,11,6,2020,740,10,Philippines,PH,PHL,108116622,Asia,8.03114252\r
-10/06/2020,10,6,2020,518,6,Philippines,PH,PHL,108116622,Asia,7.69816874\r
-09/06/2020,9,6,2020,579,8,Philippines,PH,PHL,108116622,Asia,7.54278098\r
-08/06/2020,8,6,2020,555,9,Philippines,PH,PHL,108116622,Asia,7.26992747\r
-07/06/2020,7,6,2020,714,7,Philippines,PH,PHL,108116622,Asia,6.9952241\r
-06/06/2020,6,6,2020,244,3,Philippines,PH,PHL,108116622,Asia,6.501313\r
-05/06/2020,5,6,2020,634,10,Philippines,PH,PHL,108116622,Asia,6.4263939\r
-04/06/2020,4,6,2020,751,8,Philippines,PH,PHL,108116622,Asia,6.03699957\r
-03/06/2020,3,6,2020,359,6,Philippines,PH,PHL,108116622,Asia,5.60043395\r
-02/06/2020,2,6,2020,552,3,Philippines,PH,PHL,108116622,Asia,5.47556878\r
-01/06/2020,1,6,2020,862,7,Philippines,PH,PHL,108116622,Asia,5.15461906\r
-31/05/2020,31,5,2020,590,8,Philippines,PH,PHL,108116622,Asia,4.54971669\r
-30/05/2020,30,5,2020,1046,21,Philippines,PH,PHL,108116622,Asia,4.20194408\r
-29/05/2020,29,5,2020,539,17,Philippines,PH,PHL,108116622,Asia,3.43332961\r
-28/05/2020,28,5,2020,380,18,Philippines,PH,PHL,108116622,Asia,3.17342508\r
-27/05/2020,27,5,2020,350,13,Philippines,PH,PHL,108116622,Asia,3.06983324\r
-26/05/2020,26,5,2020,284,5,Philippines,PH,PHL,108116622,Asia,2.9902895\r
-25/05/2020,25,5,2020,258,5,Philippines,PH,PHL,108116622,Asia,2.99768892\r
-24/05/2020,24,5,2020,180,6,Philippines,PH,PHL,108116622,Asia,2.92924431\r
-23/05/2020,23,5,2020,163,11,Philippines,PH,PHL,108116622,Asia,2.89872172\r
-22/05/2020,22,5,2020,213,4,Philippines,PH,PHL,108116622,Asia,2.85894985\r
-21/05/2020,21,5,2020,279,5,Philippines,PH,PHL,108116622,Asia,2.97549067\r
-20/05/2020,20,5,2020,224,6,Philippines,PH,PHL,108116622,Asia,3.01341268\r
-19/05/2020,19,5,2020,205,7,Philippines,PH,PHL,108116622,Asia,2.9902895\r
-18/05/2020,18,5,2020,208,7,Philippines,PH,PHL,108116622,Asia,3.04301035\r
-17/05/2020,17,5,2020,214,11,Philippines,PH,PHL,108116622,Asia,3.12347902\r
-16/05/2020,16,5,2020,215,16,Philippines,PH,PHL,108116622,Asia,3.06983324\r
-15/05/2020,15,5,2020,258,18,Philippines,PH,PHL,108116622,Asia,3.13365321\r
-14/05/2020,14,5,2020,268,21,Philippines,PH,PHL,108116622,Asia,3.1503019\r
-13/05/2020,13,5,2020,264,25,Philippines,PH,PHL,108116622,Asia,3.13735292\r
-12/05/2020,12,5,2020,292,7,Philippines,PH,PHL,108116622,Asia,3.06058397\r
-11/05/2020,11,5,2020,184,15,Philippines,PH,PHL,108116622,Asia,2.97364082\r
-10/05/2020,10,5,2020,147,8,Philippines,PH,PHL,108116622,Asia,3.06705846\r
-09/05/2020,9,5,2020,120,11,Philippines,PH,PHL,108116622,Asia,3.02543674\r
-08/05/2020,8,5,2020,339,27,Philippines,PH,PHL,108116622,Asia,3.10960511\r
-07/05/2020,7,5,2020,320,21,Philippines,PH,PHL,108116622,Asia,3.04671006\r
-06/05/2020,6,5,2020,199,14,Philippines,PH,PHL,108116622,Asia,2.85340028\r
-05/05/2020,5,5,2020,262,16,Philippines,PH,PHL,108116622,Asia,2.79882958\r
-04/05/2020,4,5,2020,295,4,Philippines,PH,PHL,108116622,Asia,2.7414841\r
-03/05/2020,3,5,2020,156,24,Philippines,PH,PHL,108116622,Asia,2.62771806\r
-02/05/2020,2,5,2020,284,11,Philippines,PH,PHL,108116622,Asia,2.6767392\r
-01/05/2020,1,5,2020,276,10,Philippines,PH,PHL,108116622,Asia,2.615694\r
-30/04/2020,30,4,2020,254,28,Philippines,PH,PHL,108116622,Asia,2.55187403\r
-29/04/2020,29,4,2020,181,19,Philippines,PH,PHL,108116622,Asia,2.52967578\r
-28/04/2020,28,4,2020,198,10,Philippines,PH,PHL,108116622,Asia,2.63141777\r
-27/04/2020,27,4,2020,285,7,Philippines,PH,PHL,108116622,Asia,2.7109615\r
-26/04/2020,26,4,2020,102,17,Philippines,PH,PHL,108116622,Asia,2.65084124\r
-25/04/2020,25,4,2020,211,15,Philippines,PH,PHL,108116622,Asia,2.88207303\r
-24/04/2020,24,4,2020,271,16,Philippines,PH,PHL,108116622,Asia,2.6869134\r
-23/04/2020,23,4,2020,111,9,Philippines,PH,PHL,108116622,Asia,2.62679313\r
-22/04/2020,22,4,2020,140,9,Philippines,PH,PHL,108116622,Asia,2.6221685\r
-21/04/2020,21,4,2020,200,19,Philippines,PH,PHL,108116622,Asia,2.58887112\r
-20/04/2020,20,4,2020,172,12,Philippines,PH,PHL,108116622,Asia,2.78680553\r
-19/04/2020,19,4,2020,209,10,Philippines,PH,PHL,108116622,Asia,2.76830699\r
-18/04/2020,18,4,2020,218,25,Philippines,PH,PHL,108116622,Asia,2.64529167\r
-17/04/2020,17,4,2020,207,13,Philippines,PH,PHL,108116622,Asia,2.79975451\r
-16/04/2020,16,4,2020,230,14,Philippines,PH,PHL,108116622,Asia,2.90612113\r
-15/04/2020,15,4,2020,291,20,Philippines,PH,PHL,108116622,Asia,2.90334635\r
-14/04/2020,14,4,2020,284,18,Philippines,PH,PHL,108116622,Asia,2.63419255\r
-13/04/2020,13,4,2020,220,50,Philippines,PH,PHL,108116622,Asia,2.98751472\r
-12/04/2020,12,4,2020,352,44,Philippines,PH,PHL,108116622,Asia,3.10128076\r
-11/04/2020,11,4,2020,0,0,Philippines,PH,PHL,108116622,Asia,3.02728659\r
-10/04/2020,10,4,2020,206,21,Philippines,PH,PHL,108116622,Asia,3.1160796\r
-09/04/2020,9,4,2020,106,5,Philippines,PH,PHL,108116622,Asia,2.99121443\r
-08/04/2020,8,4,2020,104,14,Philippines,PH,PHL,108116622,Asia,2.97086603\r
-07/04/2020,7,4,2020,414,11,Philippines,PH,PHL,108116622,Asia,2.95791705\r
-06/04/2020,6,4,2020,152,8,Philippines,PH,PHL,108116622,Asia,2.65084124\r
-05/04/2020,5,4,2020,76,8,Philippines,PH,PHL,108116622,Asia,2.51025231\r
-04/04/2020,4,4,2020,385,29,Philippines,PH,PHL,108116622,Asia,2.57869692\r
-03/04/2020,3,4,2020,322,11,Philippines,PH,PHL,108116622,Asia,2.22259996\r
-02/04/2020,2,4,2020,227,8,Philippines,PH,PHL,108116622,Asia,1.95067138\r
-01/04/2020,1,4,2020,0,0,Philippines,PH,PHL,108116622,Asia,1.75458682\r
-31/03/2020,31,3,2020,666,17,Philippines,PH,PHL,108116622,Asia,1.79620854\r
-30/03/2020,30,3,2020,343,3,Philippines,PH,PHL,108116622,Asia,1.18205691\r
-29/03/2020,29,3,2020,272,14,Philippines,PH,PHL,108116622,Asia,0.89162978\r
-28/03/2020,28,3,2020,96,9,Philippines,PH,PHL,108116622,Asia,0.68352117\r
-27/03/2020,27,3,2020,71,7,Philippines,PH,PHL,108116622,Asia,0.60582729\r
-26/03/2020,26,3,2020,84,3,Philippines,PH,PHL,108116622,Asia,0.54293224\r
-25/03/2020,25,3,2020,90,2,Philippines,PH,PHL,108116622,Asia,0.4800372\r
-24/03/2020,24,3,2020,82,8,Philippines,PH,PHL,108116622,Asia,0.39679375\r
-23/03/2020,23,3,2020,0,0,Philippines,PH,PHL,108116622,Asia,0.34222305\r
-22/03/2020,22,3,2020,150,7,Philippines,PH,PHL,108116622,Asia,0.34592276\r
-21/03/2020,21,3,2020,0,0,Philippines,PH,PHL,108116622,Asia,0.20810861\r
-20/03/2020,20,3,2020,28,1,Philippines,PH,PHL,108116622,Asia,0.20995847\r
-19/03/2020,19,3,2020,15,3,Philippines,PH,PHL,108116622,Asia,0.1840605\r
-18/03/2020,18,3,2020,45,2,Philippines,PH,PHL,108116622,Asia,0.1701866\r
-17/03/2020,17,3,2020,2,0,Philippines,PH,PHL,108116622,Asia,0.12856488\r
-16/03/2020,16,3,2020,29,6,Philippines,PH,PHL,108116622,Asia,0.12671502\r
-15/03/2020,15,3,2020,47,0,Philippines,PH,PHL,108116622,Asia,0.09989213\r
-14/03/2020,14,3,2020,12,4,Philippines,PH,PHL,108116622,Asia,0.05642056\r
-13/03/2020,13,3,2020,3,0,Philippines,PH,PHL,108116622,Asia,0.04532143\r
-12/03/2020,12,3,2020,16,1,Philippines,PH,PHL,108116622,Asia,0.04254665\r
-11/03/2020,11,3,2020,0,0,Philippines,PH,PHL,108116622,Asia,0.02774781\r
-10/03/2020,10,3,2020,23,0,Philippines,PH,PHL,108116622,Asia,0.02774781\r
-09/03/2020,9,3,2020,4,0,Philippines,PH,PHL,108116622,Asia,0.00647449\r
-08/03/2020,8,3,2020,1,0,Philippines,PH,PHL,108116622,Asia,0.00277478\r
-07/03/2020,7,3,2020,2,0,Philippines,PH,PHL,108116622,Asia,0.00184985\r
-02/03/2020,2,3,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-01/03/2020,1,3,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-29/02/2020,29,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-28/02/2020,28,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-27/02/2020,27,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-26/02/2020,26,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-25/02/2020,25,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-24/02/2020,24,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-23/02/2020,23,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-22/02/2020,22,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-21/02/2020,21,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-20/02/2020,20,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-19/02/2020,19,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0.00092493\r
-18/02/2020,18,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0.00092493\r
-17/02/2020,17,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0.00092493\r
-16/02/2020,16,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0.00092493\r
-15/02/2020,15,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0.00184985\r
-14/02/2020,14,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0.00184985\r
-13/02/2020,13,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0.00184985\r
-12/02/2020,12,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0.00277478\r
-11/02/2020,11,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0.00277478\r
-10/02/2020,10,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0.00277478\r
-09/02/2020,9,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0.00277478\r
-08/02/2020,8,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0.00277478\r
-07/02/2020,7,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0.00277478\r
-06/02/2020,6,2,2020,1,0,Philippines,PH,PHL,108116622,Asia,0.00277478\r
-05/02/2020,5,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0.00184985\r
-04/02/2020,4,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0.00184985\r
-03/02/2020,3,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0.00184985\r
-02/02/2020,2,2,2020,1,1,Philippines,PH,PHL,108116622,Asia,0.00184985\r
-01/02/2020,1,2,2020,0,0,Philippines,PH,PHL,108116622,Asia,0.00092493\r
-31/01/2020,31,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,0.00092493\r
-30/01/2020,30,1,2020,1,0,Philippines,PH,PHL,108116622,Asia,0.00092493\r
-29/01/2020,29,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-28/01/2020,28,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-27/01/2020,27,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-26/01/2020,26,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-25/01/2020,25,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-24/01/2020,24,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-23/01/2020,23,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-22/01/2020,22,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-21/01/2020,21,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-20/01/2020,20,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-19/01/2020,19,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-18/01/2020,18,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-17/01/2020,17,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-16/01/2020,16,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-15/01/2020,15,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-14/01/2020,14,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-13/01/2020,13,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,0\r
-12/01/2020,12,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,\r
-11/01/2020,11,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,\r
-10/01/2020,10,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,\r
-09/01/2020,9,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,\r
-08/01/2020,8,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,\r
-07/01/2020,7,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,\r
-06/01/2020,6,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,\r
-05/01/2020,5,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,\r
-04/01/2020,4,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,\r
-03/01/2020,3,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,\r
-02/01/2020,2,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,\r
-01/01/2020,1,1,2020,0,0,Philippines,PH,PHL,108116622,Asia,\r
-31/12/2019,31,12,2019,0,0,Philippines,PH,PHL,108116622,Asia,\r
-19/08/2020,19,8,2020,597,11,Poland,PL,POL,37972812,Europe,25.61569578\r
-18/08/2020,18,8,2020,595,8,Poland,PL,POL,37972812,Europe,25.83427322\r
-17/08/2020,17,8,2020,594,8,Poland,PL,POL,37972812,Europe,25.78160395\r
-16/08/2020,16,8,2020,771,11,Poland,PL,POL,37972812,Europe,25.66046465\r
-15/08/2020,15,8,2020,832,14,Poland,PL,POL,37972812,Europe,25.36288332\r
-14/08/2020,14,8,2020,811,14,Poland,PL,POL,37972812,Europe,24.90202727\r
-13/08/2020,13,8,2020,715,9,Poland,PL,POL,37972812,Europe,24.3858685\r
-12/08/2020,12,8,2020,551,12,Poland,PL,POL,37972812,Europe,23.85127549\r
-11/08/2020,11,8,2020,619,2,Poland,PL,POL,37972812,Europe,23.72223579\r
-10/08/2020,10,8,2020,624,7,Poland,PL,POL,37972812,Europe,22.97959919\r
-09/08/2020,9,8,2020,843,13,Poland,PL,POL,37972812,Europe,22.50294237\r
-08/08/2020,8,8,2020,809,13,Poland,PL,POL,37972812,Europe,21.82087542\r
-07/08/2020,7,8,2020,726,18,Poland,PL,POL,37972812,Europe,20.89652986\r
-06/08/2020,6,8,2020,640,18,Poland,PL,POL,37972812,Europe,20.08542322\r
-05/08/2020,5,8,2020,680,6,Poland,PL,POL,37972812,Europe,19.40072281\r
-04/08/2020,4,8,2020,575,1,Poland,PL,POL,37972812,Europe,18.66071967\r
-03/08/2020,3,8,2020,548,10,Poland,PL,POL,37972812,Europe,17.88121459\r
-02/08/2020,2,8,2020,658,5,Poland,PL,POL,37972812,Europe,17.3808566\r
-01/08/2020,1,8,2020,657,7,Poland,PL,POL,37972812,Europe,16.54078186\r
-31/07/2020,31,7,2020,615,15,Poland,PL,POL,37972812,Europe,15.74020907\r
-30/07/2020,30,7,2020,512,12,Poland,PL,POL,37972812,Europe,14.84219815\r
-29/07/2020,29,7,2020,502,6,Poland,PL,POL,37972812,Europe,14.34447362\r
-28/07/2020,28,7,2020,337,5,Poland,PL,POL,37972812,Europe,13.72560979\r
-27/07/2020,27,7,2020,443,7,Poland,PL,POL,37972812,Europe,13.62553819\r
-26/07/2020,26,7,2020,584,9,Poland,PL,POL,37972812,Europe,13.43329538\r
-25/07/2020,25,7,2020,458,4,Poland,PL,POL,37972812,Europe,12.69855917\r
-24/07/2020,24,7,2020,418,9,Poland,PL,POL,37972812,Europe,12.19030079\r
-23/07/2020,23,7,2020,380,6,Poland,PL,POL,37972812,Europe,11.77948054\r
-22/07/2020,22,7,2020,399,9,Poland,PL,POL,37972812,Europe,11.50823384\r
-21/07/2020,21,7,2020,279,3,Poland,PL,POL,37972812,Europe,11.13428208\r
-20/07/2020,20,7,2020,358,6,Poland,PL,POL,37972812,Europe,10.9394058\r
-19/07/2020,19,7,2020,339,6,Poland,PL,POL,37972812,Europe,10.60495599\r
-18/07/2020,18,7,2020,353,7,Poland,PL,POL,37972812,Europe,10.53911941\r
-17/07/2020,17,7,2020,274,11,Poland,PL,POL,37972812,Europe,10.29157388\r
-16/07/2020,16,7,2020,323,6,Poland,PL,POL,37972812,Europe,10.5470198\r
-15/07/2020,15,7,2020,267,12,Poland,PL,POL,37972812,Europe,10.70239412\r
-14/07/2020,14,7,2020,299,5,Poland,PL,POL,37972812,Europe,10.62865716\r
-13/07/2020,13,7,2020,370,3,Poland,PL,POL,37972812,Europe,10.49171707\r
-12/07/2020,12,7,2020,305,6,Poland,PL,POL,37972812,Europe,10.0255941\r
-11/07/2020,11,7,2020,265,11,Poland,PL,POL,37972812,Europe,10.06246259\r
-10/07/2020,10,7,2020,262,9,Poland,PL,POL,37972812,Europe,10.09143068\r
-09/07/2020,9,7,2020,277,14,Poland,PL,POL,37972812,Europe,10.18623535\r
-08/07/2020,8,7,2020,257,7,Poland,PL,POL,37972812,Europe,10.23100422\r
-07/07/2020,7,7,2020,205,4,Poland,PL,POL,37972812,Europe,10.34424314\r
-06/07/2020,6,7,2020,231,5,Poland,PL,POL,37972812,Europe,10.58388828\r
-05/07/2020,5,7,2020,314,5,Poland,PL,POL,37972812,Europe,10.79456533\r
-04/07/2020,4,7,2020,259,15,Poland,PL,POL,37972812,Europe,10.7682307\r
-03/07/2020,3,7,2020,371,15,Poland,PL,POL,37972812,Europe,10.87883615\r
-02/07/2020,2,7,2020,382,14,Poland,PL,POL,37972812,Europe,10.72872875\r
-01/07/2020,1,7,2020,239,19,Poland,PL,POL,37972812,Europe,11.05527818\r
-30/06/2020,30,6,2020,247,6,Poland,PL,POL,37972812,Europe,11.49769999\r
-29/06/2020,29,6,2020,193,3,Poland,PL,POL,37972812,Europe,11.89008599\r
-28/06/2020,28,6,2020,319,6,Poland,PL,POL,37972812,Europe,12.36937628\r
-27/06/2020,27,6,2020,276,17,Poland,PL,POL,37972812,Europe,12.68802532\r
-26/06/2020,26,6,2020,298,16,Poland,PL,POL,37972812,Europe,12.95137163\r
-25/06/2020,25,6,2020,294,21,Poland,PL,POL,37972812,Europe,13.33585724\r
-24/06/2020,24,6,2020,300,16,Poland,PL,POL,37972812,Europe,13.08041132\r
-23/06/2020,23,6,2020,296,3,Poland,PL,POL,37972812,Europe,13.34375763\r
-22/06/2020,22,6,2020,311,10,Poland,PL,POL,37972812,Europe,14.14169696\r
-21/06/2020,21,6,2020,304,12,Poland,PL,POL,37972812,Europe,14.83693122\r
-20/06/2020,20,6,2020,301,18,Poland,PL,POL,37972812,Europe,15.52953202\r
-19/06/2020,19,6,2020,314,30,Poland,PL,POL,37972812,Europe,15.71387444\r
-18/06/2020,18,6,2020,506,14,Poland,PL,POL,37972812,Europe,15.83764721\r
-17/06/2020,17,6,2020,407,16,Poland,PL,POL,37972812,Europe,15.2740861\r
-16/06/2020,16,6,2020,396,9,Poland,PL,POL,37972812,Europe,14.80796313\r
-15/06/2020,15,6,2020,375,10,Poland,PL,POL,37972812,Europe,14.76319426\r
-14/06/2020,14,6,2020,440,15,Poland,PL,POL,37972812,Europe,14.34184016\r
-13/06/2020,13,6,2020,376,7,Poland,PL,POL,37972812,Europe,14.27863704\r
-12/06/2020,12,6,2020,444,9,Poland,PL,POL,37972812,Europe,14.15749774\r
-11/06/2020,11,6,2020,197,23,Poland,PL,POL,37972812,Europe,13.91521913\r
-10/06/2020,10,6,2020,400,17,Poland,PL,POL,37972812,Europe,14.44717868\r
-09/06/2020,9,6,2020,599,9,Poland,PL,POL,37972812,Europe,14.5604176\r
-08/06/2020,8,6,2020,575,4,Poland,PL,POL,37972812,Europe,13.78617944\r
-07/06/2020,7,6,2020,567,16,Poland,PL,POL,37972812,Europe,13.31215608\r
-06/06/2020,6,6,2020,371,20,Poland,PL,POL,37972812,Europe,12.64062298\r
-05/06/2020,5,6,2020,361,2,Poland,PL,POL,37972812,Europe,12.91713661\r
-04/06/2020,4,6,2020,292,23,Poland,PL,POL,37972812,Europe,13.03037552\r
-03/06/2020,3,6,2020,230,18,Poland,PL,POL,37972812,Europe,13.50176542\r
-02/06/2020,2,6,2020,379,10,Poland,PL,POL,37972812,Europe,13.90468528\r
-01/06/2020,1,6,2020,215,3,Poland,PL,POL,37972812,Europe,13.84411563\r
-31/05/2020,31,5,2020,416,10,Poland,PL,POL,37972812,Europe,13.99422302\r
-30/05/2020,30,5,2020,330,13,Poland,PL,POL,37972812,Europe,13.53336698\r
-29/05/2020,29,5,2020,352,10,Poland,PL,POL,37972812,Europe,13.72034286\r
-28/05/2020,28,5,2020,399,4,Poland,PL,POL,37972812,Europe,13.87571718\r
-27/05/2020,27,5,2020,443,17,Poland,PL,POL,37972812,Europe,13.57023546\r
-26/05/2020,26,5,2020,305,11,Poland,PL,POL,37972812,Europe,13.97052186\r
-25/05/2020,25,5,2020,395,3,Poland,PL,POL,37972812,Europe,14.03635843\r
-24/05/2020,24,5,2020,312,11,Poland,PL,POL,37972812,Europe,13.90468528\r
-23/05/2020,23,5,2020,476,10,Poland,PL,POL,37972812,Europe,13.83358177\r
-22/05/2020,22,5,2020,404,10,Poland,PL,POL,37972812,Europe,13.42012806\r
-21/05/2020,21,5,2020,471,14,Poland,PL,POL,37972812,Europe,13.16468214\r
-20/05/2020,20,5,2020,383,12,Poland,PL,POL,37972812,Europe,12.73806112\r
-19/05/2020,19,5,2020,356,11,Poland,PL,POL,37972812,Europe,12.84866657\r
-18/05/2020,18,5,2020,272,10,Poland,PL,POL,37972812,Europe,12.73542765\r
-17/05/2020,17,5,2020,241,8,Poland,PL,POL,37972812,Europe,12.85656696\r
-16/05/2020,16,5,2020,401,24,Poland,PL,POL,37972812,Europe,12.93293739\r
-15/05/2020,15,5,2020,411,22,Poland,PL,POL,37972812,Europe,12.47734827\r
-14/05/2020,14,5,2020,283,22,Poland,PL,POL,37972812,Europe,12.01912568\r
-13/05/2020,13,5,2020,595,28,Poland,PL,POL,37972812,Europe,12.38517706\r
-12/05/2020,12,5,2020,330,11,Poland,PL,POL,37972812,Europe,11.65044085\r
-11/05/2020,11,5,2020,345,15,Poland,PL,POL,37972812,Europe,11.53193501\r
-10/05/2020,10,5,2020,285,9,Poland,PL,POL,37972812,Europe,11.52930154\r
-09/05/2020,9,5,2020,319,21,Poland,PL,POL,37972812,Europe,11.782114\r
-08/05/2020,8,5,2020,307,22,Poland,PL,POL,37972812,Europe,11.94538872\r
-07/05/2020,7,5,2020,309,17,Poland,PL,POL,37972812,Europe,12.03755993\r
-06/05/2020,6,5,2020,425,18,Poland,PL,POL,37972812,Europe,12.04809378\r
-05/05/2020,5,5,2020,313,20,Poland,PL,POL,37972812,Europe,11.62147275\r
-04/05/2020,4,5,2020,318,14,Poland,PL,POL,37972812,Europe,11.60303851\r
-03/05/2020,3,5,2020,270,13,Poland,PL,POL,37972812,Europe,12.20083464\r
-02/05/2020,2,5,2020,228,7,Poland,PL,POL,37972812,Europe,12.44574671\r
-01/05/2020,1,5,2020,237,20,Poland,PL,POL,37972812,Europe,13.05934362\r
-30/04/2020,30,4,2020,422,28,Poland,PL,POL,37972812,Europe,13.32005647\r
-29/04/2020,29,4,2020,316,34,Poland,PL,POL,37972812,Europe,13.20945101\r
-28/04/2020,28,4,2020,285,27,Poland,PL,POL,37972812,Europe,13.08304478\r
-27/04/2020,27,4,2020,344,11,Poland,PL,POL,37972812,Europe,13.01720821\r
-26/04/2020,26,4,2020,381,30,Poland,PL,POL,37972812,Europe,12.94873817\r
-25/04/2020,25,4,2020,381,40,Poland,PL,POL,37972812,Europe,13.00140743\r
-24/04/2020,24,4,2020,342,28,Poland,PL,POL,37972812,Europe,12.99877396\r
-23/04/2020,23,4,2020,313,25,Poland,PL,POL,37972812,Europe,13.07251093\r
-22/04/2020,22,4,2020,263,21,Poland,PL,POL,37972812,Europe,13.18838331\r
-21/04/2020,21,4,2020,306,20,Poland,PL,POL,37972812,Europe,13.64133897\r
-20/04/2020,20,4,2020,545,13,Poland,PL,POL,37972812,Europe,13.65450628\r
-19/04/2020,19,4,2020,363,15,Poland,PL,POL,37972812,Europe,13.47016386\r
-18/04/2020,18,4,2020,461,18,Poland,PL,POL,37972812,Europe,13.15678175\r
-17/04/2020,17,4,2020,336,28,Poland,PL,POL,37972812,Europe,13.09357864\r
-16/04/2020,16,4,2020,380,23,Poland,PL,POL,37972812,Europe,13.24105257\r
-15/04/2020,15,4,2020,268,18,Poland,PL,POL,37972812,Europe,12.88026812\r
-14/04/2020,14,4,2020,260,13,Poland,PL,POL,37972812,Europe,12.84866657\r
-13/04/2020,13,4,2020,318,24,Poland,PL,POL,37972812,Europe,12.67222454\r
-12/04/2020,12,4,2020,401,27,Poland,PL,POL,37972812,Europe,12.424679\r
-11/04/2020,11,4,2020,380,7,Poland,PL,POL,37972812,Europe,12.02439261\r
-10/04/2020,10,4,2020,370,15,Poland,PL,POL,37972812,Europe,11.46609843\r
-09/04/2020,9,4,2020,357,30,Poland,PL,POL,37972812,Europe,10.9394058\r
-08/04/2020,8,4,2020,435,22,Poland,PL,POL,37972812,Europe,10.39427894\r
-07/04/2020,7,4,2020,311,13,Poland,PL,POL,37972812,Europe,9.64900888\r
-06/04/2020,6,4,2020,475,15,Poland,PL,POL,37972812,Europe,9.1328501\r
-05/04/2020,5,4,2020,244,8,Poland,PL,POL,37972812,Europe,8.14003451\r
-04/04/2020,4,4,2020,437,14,Poland,PL,POL,37972812,Europe,7.78978391\r
-03/04/2020,3,4,2020,392,14,Poland,PL,POL,37972812,Europe,6.82330295\r
-02/04/2020,2,4,2020,243,10,Poland,PL,POL,37972812,Europe,5.9700609\r
-01/04/2020,1,4,2020,256,2,Poland,PL,POL,37972812,Europe,5.45916905\r
-31/03/2020,31,3,2020,193,9,Poland,PL,POL,37972812,Europe,4.94564374\r
-30/03/2020,30,3,2020,224,4,Poland,PL,POL,37972812,Europe,4.57432544\r
-29/03/2020,29,3,2020,249,2,Poland,PL,POL,37972812,Europe,4.03973243\r
-28/03/2020,28,3,2020,168,0,Poland,PL,POL,37972812,Europe,3.47880478\r
-27/03/2020,27,3,2020,170,2,Poland,PL,POL,37972812,Europe,3.08641878\r
-26/03/2020,26,3,2020,150,4,Poland,PL,POL,37972812,Europe,2.68613238\r
-25/03/2020,25,3,2020,152,2,Poland,PL,POL,37972812,Europe,2.31481408\r
-24/03/2020,24,3,2020,115,1,Poland,PL,POL,37972812,Europe,1.927695\r
-23/03/2020,23,3,2020,98,2,Poland,PL,POL,37972812,Europe,1.64064752\r
-22/03/2020,22,3,2020,111,0,Poland,PL,POL,37972812,Europe,1.39573545\r
-21/03/2020,21,3,2020,70,0,Poland,PL,POL,37972812,Europe,1.10605451\r
-20/03/2020,20,3,2020,68,0,Poland,PL,POL,37972812,Europe,0.93224594\r
-19/03/2020,19,3,2020,49,0,Poland,PL,POL,37972812,Europe,0.75580392\r
-18/03/2020,18,3,2020,61,1,Poland,PL,POL,37972812,Europe,\r
-17/03/2020,17,3,2020,52,1,Poland,PL,POL,37972812,Europe,\r
-16/03/2020,16,3,2020,21,0,Poland,PL,POL,37972812,Europe,\r
-15/03/2020,15,3,2020,36,1,Poland,PL,POL,37972812,Europe,\r
-14/03/2020,14,3,2020,19,1,Poland,PL,POL,37972812,Europe,\r
-13/03/2020,13,3,2020,18,1,Poland,PL,POL,37972812,Europe,\r
-12/03/2020,12,3,2020,9,0,Poland,PL,POL,37972812,Europe,\r
-11/03/2020,11,3,2020,5,0,Poland,PL,POL,37972812,Europe,\r
-10/03/2020,10,3,2020,6,0,Poland,PL,POL,37972812,Europe,\r
-09/03/2020,9,3,2020,5,0,Poland,PL,POL,37972812,Europe,\r
-08/03/2020,8,3,2020,1,0,Poland,PL,POL,37972812,Europe,\r
-07/03/2020,7,3,2020,4,0,Poland,PL,POL,37972812,Europe,\r
-04/03/2020,4,3,2020,1,0,Poland,PL,POL,37972812,Europe,\r
-19/08/2020,19,8,2020,214,5,Portugal,PT,PRT,10276617,Europe,26.92520311\r
-18/08/2020,18,8,2020,132,1,Portugal,PT,PRT,10276617,Europe,25.93265858\r
-17/08/2020,17,8,2020,121,3,Portugal,PT,PRT,10276617,Europe,25.67965703\r
-16/08/2020,16,8,2020,198,3,Portugal,PT,PRT,10276617,Europe,25.99104355\r
-15/08/2020,15,8,2020,235,2,Portugal,PT,PRT,10276617,Europe,26.3802767\r
-14/08/2020,14,8,2020,325,6,Portugal,PT,PRT,10276617,Europe,26.07862101\r
-13/08/2020,13,8,2020,278,3,Portugal,PT,PRT,10276617,Europe,25.397463\r
-12/08/2020,12,8,2020,120,2,Portugal,PT,PRT,10276617,Europe,24.66765084\r
-11/08/2020,11,8,2020,157,3,Portugal,PT,PRT,10276617,Europe,24.58007338\r
-10/08/2020,10,8,2020,131,6,Portugal,PT,PRT,10276617,Europe,24.36599515\r
-09/08/2020,9,8,2020,186,4,Portugal,PT,PRT,10276617,Europe,25.12499979\r
-08/08/2020,8,8,2020,290,3,Portugal,PT,PRT,10276617,Europe,25.87427361\r
-07/08/2020,7,8,2020,213,3,Portugal,PT,PRT,10276617,Europe,26.09808267\r
-06/08/2020,6,8,2020,167,1,Portugal,PT,PRT,10276617,Europe,26.25377593\r
-05/08/2020,5,8,2020,112,1,Portugal,PT,PRT,10276617,Europe,27.08089637\r
-04/08/2020,4,8,2020,106,0,Portugal,PT,PRT,10276617,Europe,27.2268588\r
-03/08/2020,3,8,2020,153,1,Portugal,PT,PRT,10276617,Europe,27.50905283\r
-02/08/2020,2,8,2020,238,2,Portugal,PT,PRT,10276617,Europe,28.41401991\r
-01/08/2020,1,8,2020,204,8,Portugal,PT,PRT,10276617,Europe,29.14383206\r
-31/07/2020,31,7,2020,255,2,Portugal,PT,PRT,10276617,Europe,30.19476156\r
-30/07/2020,30,7,2020,203,3,Portugal,PT,PRT,10276617,Europe,31.01215118\r
-29/07/2020,29,7,2020,111,3,Portugal,PT,PRT,10276617,Europe,32.68585372\r
-28/07/2020,28,7,2020,135,2,Portugal,PT,PRT,10276617,Europe,33.87301483\r
-27/07/2020,27,7,2020,209,1,Portugal,PT,PRT,10276617,Europe,35.53698654\r
-26/07/2020,26,7,2020,263,4,Portugal,PT,PRT,10276617,Europe,36.3349145\r
-25/07/2020,25,7,2020,313,7,Portugal,PT,PRT,10276617,Europe,39.04981571\r
-24/07/2020,24,7,2020,229,3,Portugal,PT,PRT,10276617,Europe,39.91585947\r
-23/07/2020,23,7,2020,252,5,Portugal,PT,PRT,10276617,Europe,41.7549861\r
-22/07/2020,22,7,2020,127,6,Portugal,PT,PRT,10276617,Europe,43.61357439\r
-21/07/2020,21,7,2020,135,2,Portugal,PT,PRT,10276617,Europe,45.17050699\r
-20/07/2020,20,7,2020,246,5,Portugal,PT,PRT,10276617,Europe,46.11439737\r
-19/07/2020,19,7,2020,313,2,Portugal,PT,PRT,10276617,Europe,46.91232533\r
-18/07/2020,18,7,2020,312,3,Portugal,PT,PRT,10276617,Europe,47.8854082\r
-17/07/2020,17,7,2020,339,3,Portugal,PT,PRT,10276617,Europe,48.48871959\r
-16/07/2020,16,7,2020,375,8,Portugal,PT,PRT,10276617,Europe,48.38168047\r
-15/07/2020,15,7,2020,233,6,Portugal,PT,PRT,10276617,Europe,47.77836909\r
-14/07/2020,14,7,2020,306,2,Portugal,PT,PRT,10276617,Europe,47.73944577\r
-13/07/2020,13,7,2020,291,6,Portugal,PT,PRT,10276617,Europe,47.35021262\r
-12/07/2020,12,7,2020,542,8,Portugal,PT,PRT,10276617,Europe,48.96553019\r
-11/07/2020,11,7,2020,402,2,Portugal,PT,PRT,10276617,Europe,46.8344787\r
-10/07/2020,10,7,2020,418,13,Portugal,PT,PRT,10276617,Europe,47.31128931\r
-09/07/2020,9,7,2020,443,2,Portugal,PT,PRT,10276617,Europe,46.27009063\r
-08/07/2020,8,7,2020,287,9,Portugal,PT,PRT,10276617,Europe,45.53054765\r
-07/07/2020,7,7,2020,232,6,Portugal,PT,PRT,10276617,Europe,46.09493572\r
-06/07/2020,6,7,2020,328,9,Portugal,PT,PRT,10276617,Europe,46.35766809\r
-05/07/2020,5,7,2020,413,7,Portugal,PT,PRT,10276617,Europe,46.00735826\r
-04/07/2020,4,7,2020,374,11,Portugal,PT,PRT,10276617,Europe,45.65704842\r
-03/07/2020,3,7,2020,328,8,Portugal,PT,PRT,10276617,Europe,45.66677925\r
-02/07/2020,2,7,2020,313,3,Portugal,PT,PRT,10276617,Europe,46.53282301\r
-01/07/2020,1,7,2020,229,8,Portugal,PT,PRT,10276617,Europe,46.75663207\r
-30/06/2020,30,6,2020,266,4,Portugal,PT,PRT,10276617,Europe,47.44752091\r
-29/06/2020,29,6,2020,457,3,Portugal,PT,PRT,10276617,Europe,48.22598721\r
-28/06/2020,28,6,2020,323,6,Portugal,PT,PRT,10276617,Europe,45.9878966\r
-27/06/2020,27,6,2020,451,6,Portugal,PT,PRT,10276617,Europe,45.59866345\r
-26/06/2020,26,6,2020,311,6,Portugal,PT,PRT,10276617,Europe,43.83738345\r
-25/06/2020,25,6,2020,367,3,Portugal,PT,PRT,10276617,Europe,43.82765262\r
-24/06/2020,24,6,2020,345,6,Portugal,PT,PRT,10276617,Europe,43.11730212\r
-23/06/2020,23,6,2020,259,4,Portugal,PT,PRT,10276617,Europe,43.85684511\r
-22/06/2020,22,6,2020,292,2,Portugal,PT,PRT,10276617,Europe,45.15104533\r
-21/06/2020,21,6,2020,377,1,Portugal,PT,PRT,10276617,Europe,43.69142102\r
-20/06/2020,20,6,2020,375,3,Portugal,PT,PRT,10276617,Europe,43.74007516\r
-19/06/2020,19,6,2020,417,1,Portugal,PT,PRT,10276617,Europe,43.75953682\r
-18/06/2020,18,6,2020,336,1,Portugal,PT,PRT,10276617,Europe,42.92268555\r
-17/06/2020,17,6,2020,300,2,Portugal,PT,PRT,10276617,Europe,43.21461041\r
-16/06/2020,16,6,2020,346,3,Portugal,PT,PRT,10276617,Europe,42.19287339\r
-15/06/2020,15,6,2020,227,5,Portugal,PT,PRT,10276617,Europe,40.7721724\r
-14/06/2020,14,6,2020,283,7,Portugal,PT,PRT,10276617,Europe,41.45333041\r
-13/06/2020,13,6,2020,270,1,Portugal,PT,PRT,10276617,Europe,41.20032886\r
-12/06/2020,12,6,2020,310,9,Portugal,PT,PRT,10276617,Europe,41.97879516\r
-11/06/2020,11,6,2020,294,3,Portugal,PT,PRT,10276617,Europe,41.92041019\r
-10/06/2020,10,6,2020,421,7,Portugal,PT,PRT,10276617,Europe,41.83283273\r
-09/06/2020,9,6,2020,392,6,Portugal,PT,PRT,10276617,Europe,39.86720533\r
-08/06/2020,8,6,2020,142,5,Portugal,PT,PRT,10276617,Europe,37.6583072\r
-07/06/2020,7,6,2020,382,9,Portugal,PT,PRT,10276617,Europe,37.75561549\r
-06/06/2020,6,6,2020,377,10,Portugal,PT,PRT,10276617,Europe,36.6754935\r
-05/06/2020,5,6,2020,331,8,Portugal,PT,PRT,10276617,Europe,35.80944974\r
-04/06/2020,4,6,2020,366,11,Portugal,PT,PRT,10276617,Europe,35.04071427\r
-03/06/2020,3,6,2020,195,12,Portugal,PT,PRT,10276617,Europe,33.69785991\r
-02/06/2020,2,6,2020,200,14,Portugal,PT,PRT,10276617,Europe,33.97032311\r
-01/06/2020,1,6,2020,297,14,Portugal,PT,PRT,10276617,Europe,33.70759074\r
-31/05/2020,31,5,2020,257,13,Portugal,PT,PRT,10276617,Europe,33.0167019\r
-30/05/2020,30,5,2020,350,14,Portugal,PT,PRT,10276617,Europe,32.72477704\r
-29/05/2020,29,5,2020,304,13,Portugal,PT,PRT,10276617,Europe,31.88792576\r
-28/05/2020,28,5,2020,285,14,Portugal,PT,PRT,10276617,Europe,30.7494188\r
-27/05/2020,27,5,2020,219,12,Portugal,PT,PRT,10276617,Europe,30.10718411\r
-26/05/2020,26,5,2020,165,14,Portugal,PT,PRT,10276617,Europe,30.25314654\r
-25/05/2020,25,5,2020,152,14,Portugal,PT,PRT,10276617,Europe,29.60118101\r
-24/05/2020,24,5,2020,271,13,Portugal,PT,PRT,10276617,Europe,29.82499007\r
-23/05/2020,23,5,2020,288,12,Portugal,PT,PRT,10276617,Europe,28.53078985\r
-22/05/2020,22,5,2020,252,14,Portugal,PT,PRT,10276617,Europe,31.10945947\r
-21/05/2020,21,5,2020,228,16,Portugal,PT,PRT,10276617,Europe,33.84382234\r
-20/05/2020,20,5,2020,223,16,Portugal,PT,PRT,10276617,Europe,36.29599118\r
-19/05/2020,19,5,2020,173,13,Portugal,PT,PRT,10276617,Europe,35.85810389\r
-18/05/2020,18,5,2020,226,15,Portugal,PT,PRT,10276617,Europe,34.17467052\r
-17/05/2020,17,5,2020,227,13,Portugal,PT,PRT,10276617,Europe,35.22560002\r
-16/05/2020,16,5,2020,264,6,Portugal,PT,PRT,10276617,Europe,31.45003847\r
-15/05/2020,15,5,2020,187,9,Portugal,PT,PRT,10276617,Europe,32.42312134\r
-14/05/2020,14,5,2020,219,12,Portugal,PT,PRT,10276617,Europe,33.47405085\r
-13/05/2020,13,5,2020,234,19,Portugal,PT,PRT,10276617,Europe,34.92394433\r
-12/05/2020,12,5,2020,98,9,Portugal,PT,PRT,10276617,Europe,34.39847958\r
-11/05/2020,11,5,2020,175,9,Portugal,PT,PRT,10276617,Europe,36.34464532\r
-10/05/2020,10,5,2020,138,12,Portugal,PT,PRT,10276617,Europe,36.22787538\r
-09/05/2020,9,5,2020,553,9,Portugal,PT,PRT,10276617,Europe,38.89412245\r
-08/05/2020,8,5,2020,533,16,Portugal,PT,PRT,10276617,Europe,42.44587494\r
-07/05/2020,7,5,2020,480,15,Portugal,PT,PRT,10276617,Europe,40.86948069\r
-06/05/2020,6,5,2020,178,11,Portugal,PT,PRT,10276617,Europe,42.06637262\r
-05/05/2020,5,5,2020,0,0,Portugal,PT,PRT,10276617,Europe,45.35539273\r
-04/05/2020,4,5,2020,334,40,Portugal,PT,PRT,10276617,Europe,51.74854721\r
-03/05/2020,3,5,2020,-161,16,Portugal,PT,PRT,10276617,Europe,53.56821219\r
-02/05/2020,2,5,2020,364,0,Portugal,PT,PRT,10276617,Europe,61.58641506\r
-01/05/2020,1,5,2020,295,18,Portugal,PT,PRT,10276617,Europe,59.8056734\r
-30/04/2020,30,4,2020,368,16,Portugal,PT,PRT,10276617,Europe,64.23320048\r
-29/04/2020,29,4,2020,180,25,Portugal,PT,PRT,10276617,Europe,66.90917838\r
-28/04/2020,28,4,2020,298,20,Portugal,PT,PRT,10276617,Europe,70.15927518\r
-27/04/2020,27,4,2020,163,25,Portugal,PT,PRT,10276617,Europe,70.65554744\r
-26/04/2020,26,4,2020,412,23,Portugal,PT,PRT,10276617,Europe,74.88845794\r
-25/04/2020,25,4,2020,918,60,Portugal,PT,PRT,10276617,Europe,75.8907333\r
-24/04/2020,24,4,2020,371,35,Portugal,PT,PRT,10276617,Europe,81.70976889\r
-23/04/2020,23,4,2020,603,23,Portugal,PT,PRT,10276617,Europe,86.03025684\r
-22/04/2020,22,4,2020,516,27,Portugal,PT,PRT,10276617,Europe,86.9644164\r
-21/04/2020,21,4,2020,657,21,Portugal,PT,PRT,10276617,Europe,88.87165883\r
-20/04/2020,20,4,2020,521,27,Portugal,PT,PRT,10276617,Europe,86.87683894\r
-19/04/2020,19,4,2020,663,30,Portugal,PT,PRT,10276617,Europe,89.14412204\r
-18/04/2020,18,4,2020,181,28,Portugal,PT,PRT,10276617,Europe,88.90085132\r
-17/04/2020,17,4,2020,750,30,Portugal,PT,PRT,10276617,Europe,95.4302374\r
-16/04/2020,16,4,2020,643,32,Portugal,PT,PRT,10276617,Europe,95.75135475\r
-15/04/2020,15,4,2020,514,32,Portugal,PT,PRT,10276617,Europe,97.35694149\r
-14/04/2020,14,4,2020,349,31,Portugal,PT,PRT,10276617,Europe,102.42670326\r
-13/04/2020,13,4,2020,598,34,Portugal,PT,PRT,10276617,Europe,103.37059365\r
-12/04/2020,12,4,2020,515,35,Portugal,PT,PRT,10276617,Europe,105.25837442\r
-11/04/2020,11,4,2020,1516,26,Portugal,PT,PRT,10276617,Europe,109.02420514\r
-10/04/2020,10,4,2020,815,29,Portugal,PT,PRT,10276617,Europe,101.31738879\r
-09/04/2020,9,4,2020,699,35,Portugal,PT,PRT,10276617,Europe,98.72898834\r
-08/04/2020,8,4,2020,712,34,Portugal,PT,PRT,10276617,Europe,98.08675365\r
-07/04/2020,7,4,2020,452,16,Portugal,PT,PRT,10276617,Europe,94.09711387\r
-06/04/2020,6,4,2020,754,29,Portugal,PT,PRT,10276617,Europe,94.1749605\r
-05/04/2020,5,4,2020,638,20,Portugal,PT,PRT,10276617,Europe,89.95178082\r
-04/04/2020,4,4,2020,852,37,Portugal,PT,PRT,10276617,Europe,86.27352756\r
-03/04/2020,3,4,2020,783,22,Portugal,PT,PRT,10276617,Europe,80.26960623\r
-02/04/2020,2,4,2020,808,27,Portugal,PT,PRT,10276617,Europe,74.04187584\r
-01/04/2020,1,4,2020,1035,20,Portugal,PT,PRT,10276617,Europe,68.067147\r
-31/03/2020,31,3,2020,446,21,Portugal,PT,PRT,10276617,Europe,59.13424622\r
-30/03/2020,30,3,2020,792,19,Portugal,PT,PRT,10276617,Europe,55.63114788\r
-29/03/2020,29,3,2020,902,24,Portugal,PT,PRT,10276617,Europe,48.6638745\r
-28/03/2020,28,3,2020,724,16,Portugal,PT,PRT,10276617,Europe,40.44132422\r
-27/03/2020,27,3,2020,549,17,Portugal,PT,PRT,10276617,Europe,33.72705239\r
-26/03/2020,26,3,2020,633,10,Portugal,PT,PRT,10276617,Europe,28.56971317\r
-25/03/2020,25,3,2020,302,10,Portugal,PT,PRT,10276617,Europe,22.58525349\r
-24/03/2020,24,3,2020,460,9,Portugal,PT,PRT,10276617,Europe,19.66600487\r
-23/03/2020,23,3,2020,320,2,Portugal,PT,PRT,10276617,Europe,15.27740111\r
-22/03/2020,22,3,2020,260,6,Portugal,PT,PRT,10276617,Europe,12.25111338\r
-21/03/2020,21,3,2020,235,3,Portugal,PT,PRT,10276617,Europe,9.79894454\r
-20/03/2020,20,3,2020,143,1,Portugal,PT,PRT,10276617,Europe,7.5511231\r
-19/03/2020,19,3,2020,194,1,Portugal,PT,PRT,10276617,Europe,6.1985379\r
-18/03/2020,18,3,2020,117,1,Portugal,PT,PRT,10276617,Europe,4.32048796\r
-17/03/2020,17,3,2020,86,0,Portugal,PT,PRT,10276617,Europe,3.20144265\r
-16/03/2020,16,3,2020,76,0,Portugal,PT,PRT,10276617,Europe,2.38405304\r
-15/03/2020,15,3,2020,57,0,Portugal,PT,PRT,10276617,Europe,\r
-14/03/2020,14,3,2020,34,0,Portugal,PT,PRT,10276617,Europe,\r
-13/03/2020,13,3,2020,19,0,Portugal,PT,PRT,10276617,Europe,\r
-12/03/2020,12,3,2020,18,0,Portugal,PT,PRT,10276617,Europe,\r
-11/03/2020,11,3,2020,2,0,Portugal,PT,PRT,10276617,Europe,\r
-10/03/2020,10,3,2020,9,0,Portugal,PT,PRT,10276617,Europe,\r
-09/03/2020,9,3,2020,9,0,Portugal,PT,PRT,10276617,Europe,\r
-08/03/2020,8,3,2020,8,0,Portugal,PT,PRT,10276617,Europe,\r
-07/03/2020,7,3,2020,4,0,Portugal,PT,PRT,10276617,Europe,\r
-06/03/2020,6,3,2020,4,0,Portugal,PT,PRT,10276617,Europe,\r
-05/03/2020,5,3,2020,1,0,Portugal,PT,PRT,10276617,Europe,\r
-04/03/2020,4,3,2020,2,0,Portugal,PT,PRT,10276617,Europe,\r
-03/03/2020,3,3,2020,2,0,Portugal,PT,PRT,10276617,Europe,\r
-19/08/2020,19,8,2020,953,11,Puerto_Rico,PR,PRI,2933404,America,285.9817468\r
-18/08/2020,18,8,2020,754,0,Puerto_Rico,PR,PRI,2933404,America,271.66390991\r
-17/08/2020,17,8,2020,311,6,Puerto_Rico,PR,PRI,2933404,America,258.91421707\r
-16/08/2020,16,8,2020,567,18,Puerto_Rico,PR,PRI,2933404,America,266.68675709\r
-15/08/2020,15,8,2020,682,5,Puerto_Rico,PR,PRI,2933404,America,284.54996311\r
-14/08/2020,14,8,2020,372,11,Puerto_Rico,PR,PRI,2933404,America,268.42535157\r
-13/08/2020,13,8,2020,671,8,Puerto_Rico,PR,PRI,2933404,America,273.16387378\r
-12/08/2020,12,8,2020,585,8,Puerto_Rico,PR,PRI,2933404,America,257.82333426\r
-11/08/2020,11,8,2020,697,0,Puerto_Rico,PR,PRI,2933404,America,251.48257792\r
-10/08/2020,10,8,2020,697,5,Puerto_Rico,PR,PRI,2933404,America,237.88063288\r
-09/08/2020,9,8,2020,738,9,Puerto_Rico,PR,PRI,2933404,America,234.67616462\r
-08/08/2020,8,8,2020,752,7,Puerto_Rico,PR,PRI,2933404,America,229.05130013\r
-07/08/2020,7,8,2020,283,12,Puerto_Rico,PR,PRI,2933404,America,220.25605747\r
-06/08/2020,6,8,2020,327,9,Puerto_Rico,PR,PRI,2933404,America,225.43775082\r
-05/08/2020,5,8,2020,533,7,Puerto_Rico,PR,PRI,2933404,America,217.6311207\r
-04/08/2020,4,8,2020,380,0,Puerto_Rico,PR,PRI,2933404,America,215.79025596\r
-03/08/2020,3,8,2020,539,5,Puerto_Rico,PR,PRI,2933404,America,216.40387754\r
-02/08/2020,2,8,2020,1091,6,Puerto_Rico,PR,PRI,2933404,America,218.82427378\r
-01/08/2020,1,8,2020,209,5,Puerto_Rico,PR,PRI,2933404,America,192.9839872\r
-31/07/2020,31,7,2020,511,3,Puerto_Rico,PR,PRI,2933404,America,204.4723468\r
-30/07/2020,30,7,2020,221,2,Puerto_Rico,PR,PRI,2933404,America,193.69987905\r
-29/07/2020,29,7,2020,399,8,Puerto_Rico,PR,PRI,2933404,America,194.89303212\r
-28/07/2020,28,7,2020,298,0,Puerto_Rico,PR,PRI,2933404,America,185.143267\r
-27/07/2020,27,7,2020,603,0,Puerto_Rico,PR,PRI,2933404,America,181.42744743\r
-26/07/2020,26,7,2020,573,10,Puerto_Rico,PR,PRI,2933404,America,170.68906976\r
-25/07/2020,25,7,2020,494,3,Puerto_Rico,PR,PRI,2933404,America,159.23480025\r
-24/07/2020,24,7,2020,435,3,Puerto_Rico,PR,PRI,2933404,America,155.75761129\r
-23/07/2020,23,7,2020,98,5,Puerto_Rico,PR,PRI,2933404,America,140.92842309\r
-22/07/2020,22,7,2020,479,0,Puerto_Rico,PR,PRI,2933404,America,144.06471117\r
-21/07/2020,21,7,2020,398,2,Puerto_Rico,PR,PRI,2933404,America,132.13318043\r
-20/07/2020,20,7,2020,610,0,Puerto_Rico,PR,PRI,2933404,America,141.37159423\r
-19/07/2020,19,7,2020,333,1,Puerto_Rico,PR,PRI,2933404,America,128.38327077\r
-18/07/2020,18,7,2020,546,5,Puerto_Rico,PR,PRI,2933404,America,117.16763187\r
-17/07/2020,17,7,2020,195,1,Puerto_Rico,PR,PRI,2933404,America,101.1112005\r
-16/07/2020,16,7,2020,256,2,Puerto_Rico,PR,PRI,2933404,America,96.88402961\r
-15/07/2020,15,7,2020,113,2,Puerto_Rico,PR,PRI,2933404,America,90.61145345\r
-14/07/2020,14,7,2020,189,0,Puerto_Rico,PR,PRI,2933404,America,94.08864241\r
-13/07/2020,13,7,2020,288,0,Puerto_Rico,PR,PRI,2933404,America,89.72511117\r
-12/07/2020,12,7,2020,237,8,Puerto_Rico,PR,PRI,2933404,America,84.10024668\r
-11/07/2020,11,7,2020,392,0,Puerto_Rico,PR,PRI,2933404,America,80.92986851\r
-10/07/2020,10,7,2020,0,0,Puerto_Rico,PR,PRI,2933404,America,69.10060803\r
-09/07/2020,9,7,2020,190,2,Puerto_Rico,PR,PRI,2933404,America,71.04374304\r
-08/07/2020,8,7,2020,129,2,Puerto_Rico,PR,PRI,2933404,America,69.16878821\r
-07/07/2020,7,7,2020,669,0,Puerto_Rico,PR,PRI,2933404,America,68.8960675\r
-06/07/2020,6,7,2020,229,0,Puerto_Rico,PR,PRI,2933404,America,47.41931217\r
-05/07/2020,5,7,2020,4,1,Puerto_Rico,PR,PRI,2933404,America,41.7262675\r
-04/07/2020,4,7,2020,75,1,Puerto_Rico,PR,PRI,2933404,America,53.58961807\r
-03/07/2020,3,7,2020,71,0,Puerto_Rico,PR,PRI,2933404,America,51.03286148\r
-02/07/2020,2,7,2020,72,0,Puerto_Rico,PR,PRI,2933404,America,52.29419473\r
-01/07/2020,1,7,2020,215,0,Puerto_Rico,PR,PRI,2933404,America,51.61239297\r
-30/06/2020,30,6,2020,61,0,Puerto_Rico,PR,PRI,2933404,America,46.36251945\r
-29/06/2020,29,6,2020,123,1,Puerto_Rico,PR,PRI,2933404,America,46.97614103\r
-28/06/2020,28,6,2020,144,1,Puerto_Rico,PR,PRI,2933404,America,46.90796085\r
-27/06/2020,27,6,2020,45,0,Puerto_Rico,PR,PRI,2933404,America,47.24886173\r
-26/06/2020,26,6,2020,57,2,Puerto_Rico,PR,PRI,2933404,America,51.98738394\r
-25/06/2020,25,6,2020,135,0,Puerto_Rico,PR,PRI,2933404,America,50.82832095\r
-24/06/2020,24,6,2020,121,0,Puerto_Rico,PR,PRI,2933404,America,51.13513174\r
-23/06/2020,23,6,2020,39,0,Puerto_Rico,PR,PRI,2933404,America,51.74875333\r
-22/06/2020,22,6,2020,62,2,Puerto_Rico,PR,PRI,2933404,America,52.49873526\r
-21/06/2020,21,6,2020,352,0,Puerto_Rico,PR,PRI,2933404,America,52.77145596\r
-20/06/2020,20,6,2020,0,0,Puerto_Rico,PR,PRI,2933404,America,50.82832095\r
-19/06/2020,19,6,2020,108,0,Puerto_Rico,PR,PRI,2933404,America,54.64641079\r
-18/06/2020,18,6,2020,52,0,Puerto_Rico,PR,PRI,2933404,America,67.4983739\r
-17/06/2020,17,6,2020,61,0,Puerto_Rico,PR,PRI,2933404,America,68.72561706\r
-16/06/2020,16,6,2020,79,0,Puerto_Rico,PR,PRI,2933404,America,68.75970715\r
-15/06/2020,15,6,2020,121,1,Puerto_Rico,PR,PRI,2933404,America,69.37332873\r
-14/06/2020,14,6,2020,154,0,Puerto_Rico,PR,PRI,2933404,America,67.2256532\r
-13/06/2020,13,6,2020,184,2,Puerto_Rico,PR,PRI,2933404,America,64.39617591\r
-12/06/2020,12,6,2020,23,1,Puerto_Rico,PR,PRI,2933404,America,63.61210389\r
-11/06/2020,11,6,2020,144,1,Puerto_Rico,PR,PRI,2933404,America,65.86204969\r
-10/06/2020,10,6,2020,139,0,Puerto_Rico,PR,PRI,2933404,America,63.44165345\r
-09/06/2020,9,6,2020,61,0,Puerto_Rico,PR,PRI,2933404,America,60.88489686\r
-08/06/2020,8,6,2020,70,0,Puerto_Rico,PR,PRI,2933404,America,61.22579774\r
-07/06/2020,7,6,2020,295,1,Puerto_Rico,PR,PRI,2933404,America,61.87350941\r
-06/06/2020,6,6,2020,112,1,Puerto_Rico,PR,PRI,2933404,America,54.20323965\r
-05/06/2020,5,6,2020,485,0,Puerto_Rico,PR,PRI,2933404,America,54.37369009\r
-04/06/2020,4,6,2020,88,2,Puerto_Rico,PR,PRI,2933404,America,39.44223162\r
-03/06/2020,3,6,2020,62,2,Puerto_Rico,PR,PRI,2933404,America,38.52179925\r
-02/06/2020,2,6,2020,97,0,Puerto_Rico,PR,PRI,2933404,America,39.64677215\r
-01/06/2020,1,6,2020,58,3,Puerto_Rico,PR,PRI,2933404,America,38.52179925\r
-31/05/2020,31,5,2020,71,1,Puerto_Rico,PR,PRI,2933404,America,38.48770916\r
-30/05/2020,30,5,2020,161,1,Puerto_Rico,PR,PRI,2933404,America,37.66954705\r
-29/05/2020,29,5,2020,89,2,Puerto_Rico,PR,PRI,2933404,America,36.10140301\r
-28/05/2020,28,5,2020,73,0,Puerto_Rico,PR,PRI,2933404,America,36.4082138\r
-27/05/2020,27,5,2020,64,0,Puerto_Rico,PR,PRI,2933404,America,34.94234003\r
-26/05/2020,26,5,2020,71,2,Puerto_Rico,PR,PRI,2933404,America,34.22644818\r
-25/05/2020,25,5,2020,89,0,Puerto_Rico,PR,PRI,2933404,America,33.78327704\r
-24/05/2020,24,5,2020,70,1,Puerto_Rico,PR,PRI,2933404,America,31.60151142\r
-23/05/2020,23,5,2020,117,0,Puerto_Rico,PR,PRI,2933404,America,29.79473676\r
-22/05/2020,22,5,2020,47,1,Puerto_Rico,PR,PRI,2933404,America,30.06745747\r
-21/05/2020,21,5,2020,61,1,Puerto_Rico,PR,PRI,2933404,America,30.61289887\r
-20/05/2020,20,5,2020,95,0,Puerto_Rico,PR,PRI,2933404,America,30.03336738\r
-19/05/2020,19,5,2020,64,1,Puerto_Rico,PR,PRI,2933404,America,29.55610615\r
-18/05/2020,18,5,2020,57,1,Puerto_Rico,PR,PRI,2933404,America,28.5674936\r
-17/05/2020,17,5,2020,47,0,Puerto_Rico,PR,PRI,2933404,America,28.36295307\r
-16/05/2020,16,5,2020,115,5,Puerto_Rico,PR,PRI,2933404,America,32.96511493\r
-15/05/2020,15,5,2020,98,2,Puerto_Rico,PR,PRI,2933404,America,30.27199799\r
-14/05/2020,14,5,2020,30,1,Puerto_Rico,PR,PRI,2933404,America,30.5447187\r
-13/05/2020,13,5,2020,43,1,Puerto_Rico,PR,PRI,2933404,America,30.64698896\r
-12/05/2020,12,5,2020,58,2,Puerto_Rico,PR,PRI,2933404,America,29.55610615\r
-11/05/2020,11,5,2020,25,3,Puerto_Rico,PR,PRI,2933404,America,28.19250264\r
-10/05/2020,10,5,2020,17,1,Puerto_Rico,PR,PRI,2933404,America,29.52201606\r
-09/05/2020,9,5,2020,125,5,Puerto_Rico,PR,PRI,2933404,America,29.99927729\r
-08/05/2020,8,5,2020,63,3,Puerto_Rico,PR,PRI,2933404,America,26.55617842\r
-07/05/2020,7,5,2020,44,0,Puerto_Rico,PR,PRI,2933404,America,24.40850289\r
-06/05/2020,6,5,2020,81,2,Puerto_Rico,PR,PRI,2933404,America,22.90853902\r
-05/05/2020,5,5,2020,35,0,Puerto_Rico,PR,PRI,2933404,America,20.14724191\r
-04/05/2020,4,5,2020,51,2,Puerto_Rico,PR,PRI,2933404,America,20.28360226\r
-03/05/2020,3,5,2020,182,1,Puerto_Rico,PR,PRI,2933404,America,21.78356612\r
-02/05/2020,2,5,2020,36,2,Puerto_Rico,PR,PRI,2933404,America,17.28367453\r
-01/05/2020,1,5,2020,106,6,Puerto_Rico,PR,PRI,2933404,America,16.90868356\r
-30/04/2020,30,4,2020,33,0,Puerto_Rico,PR,PRI,2933404,America,15.64735031\r
-29/04/2020,29,4,2020,11,2,Puerto_Rico,PR,PRI,2933404,America,16.26097189\r
-28/04/2020,28,4,2020,18,0,Puerto_Rico,PR,PRI,2933404,America,16.56778269\r
-27/04/2020,27,4,2020,64,1,Puerto_Rico,PR,PRI,2933404,America,16.15870163\r
-26/04/2020,26,4,2020,31,6,Puerto_Rico,PR,PRI,2933404,America,17.69275558\r
-25/04/2020,25,4,2020,24,8,Puerto_Rico,PR,PRI,2933404,America,18.78363839\r
-24/04/2020,24,4,2020,0,5,Puerto_Rico,PR,PRI,2933404,America,19.39725998\r
-23/04/2020,23,4,2020,0,1,Puerto_Rico,PR,PRI,2933404,America,21.54493551\r
-22/04/2020,22,4,2020,0,0,Puerto_Rico,PR,PRI,2933404,America,23.14716964\r
-21/04/2020,21,4,2020,39,1,Puerto_Rico,PR,PRI,2933404,America,25.19257491\r
-20/04/2020,20,4,2020,95,2,Puerto_Rico,PR,PRI,2933404,America,25.15848482\r
-19/04/2020,19,4,2020,50,2,Puerto_Rico,PR,PRI,2933404,America,22.70399849\r
-18/04/2020,18,4,2020,25,2,Puerto_Rico,PR,PRI,2933404,America,23.5221606\r
-17/04/2020,17,4,2020,69,5,Puerto_Rico,PR,PRI,2933404,America,24.78349385\r
-16/04/2020,16,4,2020,51,6,Puerto_Rico,PR,PRI,2933404,America,23.45398043\r
-15/04/2020,15,4,2020,20,0,Puerto_Rico,PR,PRI,2933404,America,23.31762008\r
-14/04/2020,14,4,2020,6,1,Puerto_Rico,PR,PRI,2933404,America,24.85167403\r
-13/04/2020,13,4,2020,109,2,Puerto_Rico,PR,PRI,2933404,America,26.24936763\r
-12/04/2020,12,4,2020,63,3,Puerto_Rico,PR,PRI,2933404,America,23.45398043\r
-11/04/2020,11,4,2020,42,6,Puerto_Rico,PR,PRI,2933404,America,22.53354806\r
-10/04/2020,10,4,2020,63,9,Puerto_Rico,PR,PRI,2933404,America,23.28352999\r
-09/04/2020,9,4,2020,47,1,Puerto_Rico,PR,PRI,2933404,America,\r
-08/04/2020,8,4,2020,60,2,Puerto_Rico,PR,PRI,2933404,America,\r
-07/04/2020,7,4,2020,38,1,Puerto_Rico,PR,PRI,2933404,America,\r
-06/04/2020,6,4,2020,23,2,Puerto_Rico,PR,PRI,2933404,America,\r
-05/04/2020,5,4,2020,74,3,Puerto_Rico,PR,PRI,2933404,America,\r
-04/04/2020,4,4,2020,62,3,Puerto_Rico,PR,PRI,2933404,America,\r
-03/04/2020,3,4,2020,30,1,Puerto_Rico,PR,PRI,2933404,America,\r
-02/04/2020,2,4,2020,47,3,Puerto_Rico,PR,PRI,2933404,America,\r
-01/04/2020,1,4,2020,65,2,Puerto_Rico,PR,PRI,2933404,America,\r
-31/03/2020,31,3,2020,47,1,Puerto_Rico,PR,PRI,2933404,America,\r
-30/03/2020,30,3,2020,27,2,Puerto_Rico,PR,PRI,2933404,America,\r
-29/03/2020,29,3,2020,36,1,Puerto_Rico,PR,PRI,2933404,America,\r
-28/03/2020,28,3,2020,64,2,Puerto_Rico,PR,PRI,2933404,America,\r
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-27/01/2020,27,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,0\r
-26/01/2020,26,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,0\r
-25/01/2020,25,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,0\r
-24/01/2020,24,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,0\r
-23/01/2020,23,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,0\r
-22/01/2020,22,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,0\r
-21/01/2020,21,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,0\r
-20/01/2020,20,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,0\r
-19/01/2020,19,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,0\r
-18/01/2020,18,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,0\r
-17/01/2020,17,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,0\r
-16/01/2020,16,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,0\r
-15/01/2020,15,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,0\r
-14/01/2020,14,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,0\r
-13/01/2020,13,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,0\r
-12/01/2020,12,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,\r
-11/01/2020,11,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,\r
-10/01/2020,10,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,\r
-09/01/2020,9,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,\r
-08/01/2020,8,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,\r
-07/01/2020,7,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,\r
-06/01/2020,6,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,\r
-05/01/2020,5,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,\r
-04/01/2020,4,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,\r
-03/01/2020,3,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,\r
-02/01/2020,2,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,\r
-01/01/2020,1,1,2020,0,0,Qatar,QA,QAT,2832071,Asia,\r
-31/12/2019,31,12,2019,0,0,Qatar,QA,QAT,2832071,Asia,\r
-19/08/2020,19,8,2020,1014,45,Romania,RO,ROU,19414458,Europe,87.39363211\r
-18/08/2020,18,8,2020,733,38,Romania,RO,ROU,19414458,Europe,88.51650662\r
-17/08/2020,17,8,2020,1087,37,Romania,RO,ROU,19414458,Europe,88.98007866\r
-16/08/2020,16,8,2020,1328,50,Romania,RO,ROU,19414458,Europe,88.91826905\r
-15/08/2020,15,8,2020,1415,44,Romania,RO,ROU,19414458,Europe,88.3877366\r
-14/08/2020,14,8,2020,1454,53,Romania,RO,ROU,19414458,Europe,87.76964054\r
-13/08/2020,13,8,2020,1415,43,Romania,RO,ROU,19414458,Europe,87.26486209\r
-12/08/2020,12,8,2020,1215,35,Romania,RO,ROU,19414458,Europe,86.06472558\r
-11/08/2020,11,8,2020,779,29,Romania,RO,ROU,19414458,Europe,85.73507435\r
-10/08/2020,10,8,2020,1145,41,Romania,RO,ROU,19414458,Europe,87.40908451\r
-09/08/2020,9,8,2020,1350,43,Romania,RO,ROU,19414458,Europe,87.2803145\r
-08/08/2020,8,8,2020,1378,50,Romania,RO,ROU,19414458,Europe,86.94036166\r
-07/08/2020,7,8,2020,1345,45,Romania,RO,ROU,19414458,Europe,85.60630433\r
-06/08/2020,6,8,2020,1309,41,Romania,RO,ROU,19414458,Europe,84.40616782\r
-05/08/2020,5,8,2020,1232,48,Romania,RO,ROU,19414458,Europe,82.96909448\r
-04/08/2020,4,8,2020,823,19,Romania,RO,ROU,19414458,Europe,81.74320396\r
-03/08/2020,3,8,2020,1075,34,Romania,RO,ROU,19414458,Europe,81.01179029\r
-02/08/2020,2,8,2020,1225,36,Romania,RO,ROU,19414458,Europe,79.42534373\r
-01/08/2020,1,8,2020,1295,39,Romania,RO,ROU,19414458,Europe,77.69467476\r
-31/07/2020,31,7,2020,1356,35,Romania,RO,ROU,19414458,Europe,75.13987771\r
-30/07/2020,30,7,2020,1182,30,Romania,RO,ROU,19414458,Europe,72.15756422\r
-29/07/2020,29,7,2020,1151,33,Romania,RO,ROU,19414458,Europe,69.37098115\r
-28/07/2020,28,7,2020,1104,19,Romania,RO,ROU,19414458,Europe,66.72346969\r
-27/07/2020,27,7,2020,1120,22,Romania,RO,ROU,19414458,Europe,63.16426655\r
-26/07/2020,26,7,2020,1284,15,Romania,RO,ROU,19414458,Europe,59.74413502\r
-25/07/2020,25,7,2020,1119,24,Romania,RO,ROU,19414458,Europe,56.72576592\r
-24/07/2020,24,7,2020,1112,25,Romania,RO,ROU,19414458,Europe,54.01129406\r
-23/07/2020,23,7,2020,1030,27,Romania,RO,ROU,19414458,Europe,51.44619541\r
-22/07/2020,22,7,2020,994,36,Romania,RO,ROU,19414458,Europe,48.99956517\r
-21/07/2020,21,7,2020,681,12,Romania,RO,ROU,19414458,Europe,45.92453727\r
-20/07/2020,20,7,2020,767,17,Romania,RO,ROU,19414458,Europe,43.70454225\r
-19/07/2020,19,7,2020,889,21,Romania,RO,ROU,19414458,Europe,41.76784127\r
-18/07/2020,18,7,2020,799,17,Romania,RO,ROU,19414458,Europe,39.33151263\r
-17/07/2020,17,7,2020,777,19,Romania,RO,ROU,19414458,Europe,37.37935924\r
-16/07/2020,16,7,2020,641,21,Romania,RO,ROU,19414458,Europe,35.69504747\r
-15/07/2020,15,7,2020,637,30,Romania,RO,ROU,19414458,Europe,34.07254532\r
-14/07/2020,14,7,2020,413,17,Romania,RO,ROU,19414458,Europe,32.78999599\r
-13/07/2020,13,7,2020,456,13,Romania,RO,ROU,19414458,Europe,32.04828072\r
-12/07/2020,12,7,2020,698,24,Romania,RO,ROU,19414458,Europe,31.19839864\r
-11/07/2020,11,7,2020,592,13,Romania,RO,ROU,19414458,Europe,29.27715005\r
-10/07/2020,10,7,2020,614,17,Romania,RO,ROU,19414458,Europe,28.34485516\r
-09/07/2020,9,7,2020,555,18,Romania,RO,ROU,19414458,Europe,27.55163188\r
-08/07/2020,8,7,2020,397,31,Romania,RO,ROU,19414458,Europe,26.34634456\r
-07/07/2020,7,7,2020,250,18,Romania,RO,ROU,19414458,Europe,25.40374807\r
-06/07/2020,6,7,2020,391,19,Romania,RO,ROU,19414458,Europe,25.38314487\r
-05/07/2020,5,7,2020,416,23,Romania,RO,ROU,19414458,Europe,24.99168403\r
-04/07/2020,4,7,2020,420,21,Romania,RO,ROU,19414458,Europe,24.54871519\r
-03/07/2020,3,7,2020,450,20,Romania,RO,ROU,19414458,Europe,24.03363514\r
-02/07/2020,2,7,2020,326,16,Romania,RO,ROU,19414458,Europe,23.36403107\r
-01/07/2020,1,7,2020,388,17,Romania,RO,ROU,19414458,Europe,23.46189628\r
-30/06/2020,30,6,2020,269,22,Romania,RO,ROU,19414458,Europe,22.75108581\r
-29/06/2020,29,6,2020,291,23,Romania,RO,ROU,19414458,Europe,22.22055336\r
-28/06/2020,28,6,2020,325,10,Romania,RO,ROU,19414458,Europe,22.36992658\r
-27/06/2020,27,6,2020,411,14,Romania,RO,ROU,19414458,Europe,22.11238655\r
-26/06/2020,26,6,2020,460,10,Romania,RO,ROU,19414458,Europe,21.13888526\r
-25/06/2020,25,6,2020,321,16,Romania,RO,ROU,19414458,Europe,19.99025675\r
-24/06/2020,24,6,2020,214,16,Romania,RO,ROU,19414458,Europe,19.34640668\r
-23/06/2020,23,6,2020,246,11,Romania,RO,ROU,19414458,Europe,18.99100145\r
-22/06/2020,22,6,2020,315,12,Romania,RO,ROU,19414458,Europe,18.36775459\r
-21/06/2020,21,6,2020,330,16,Romania,RO,ROU,19414458,Europe,17.71875372\r
-20/06/2020,20,6,2020,320,11,Romania,RO,ROU,19414458,Europe,16.98218925\r
-19/06/2020,19,6,2020,320,22,Romania,RO,ROU,19414458,Europe,16.34348999\r
-18/06/2020,18,6,2020,345,14,Romania,RO,ROU,19414458,Europe,15.92112435\r
-17/06/2020,17,6,2020,250,10,Romania,RO,ROU,19414458,Europe,14.92701985\r
-16/06/2020,16,6,2020,166,17,Romania,RO,ROU,19414458,Europe,14.25226499\r
-15/06/2020,15,6,2020,320,19,Romania,RO,ROU,19414458,Europe,14.12349497\r
-14/06/2020,14,6,2020,275,11,Romania,RO,ROU,19414458,Europe,13.11393808\r
-13/06/2020,13,6,2020,222,11,Romania,RO,ROU,19414458,Europe,12.47523881\r
-12/06/2020,12,6,2020,237,9,Romania,RO,ROU,19414458,Europe,12.315564\r
-11/06/2020,11,6,2020,196,15,Romania,RO,ROU,19414458,Europe,12.10953198\r
-10/06/2020,10,6,2020,145,11,Romania,RO,ROU,19414458,Europe,11.94985716\r
-09/06/2020,9,6,2020,125,8,Romania,RO,ROU,19414458,Europe,11.95500796\r
-08/06/2020,8,6,2020,189,8,Romania,RO,ROU,19414458,Europe,12.40827841\r
-07/06/2020,7,6,2020,187,10,Romania,RO,ROU,19414458,Europe,12.53189762\r
-06/06/2020,6,6,2020,196,9,Romania,RO,ROU,19414458,Europe,12.315564\r
-05/06/2020,5,6,2020,238,11,Romania,RO,ROU,19414458,Europe,11.96015876\r
-04/06/2020,4,6,2020,152,9,Romania,RO,ROU,19414458,Europe,11.75412674\r
-03/06/2020,3,6,2020,119,0,Romania,RO,ROU,19414458,Europe,11.98076197\r
-02/06/2020,2,6,2020,141,17,Romania,RO,ROU,19414458,Europe,12.16619078\r
-01/06/2020,1,6,2020,124,9,Romania,RO,ROU,19414458,Europe,12.28981\r
-31/05/2020,31,5,2020,151,13,Romania,RO,ROU,19414458,Europe,12.51129442\r
-30/05/2020,30,5,2020,191,11,Romania,RO,ROU,19414458,Europe,13.10878728\r
-29/05/2020,29,5,2020,197,10,Romania,RO,ROU,19414458,Europe,13.10363648\r
-28/05/2020,28,5,2020,165,9,Romania,RO,ROU,19414458,Europe,13.3508749\r
-27/05/2020,27,5,2020,146,13,Romania,RO,ROU,19414458,Europe,13.65477213\r
-26/05/2020,26,5,2020,213,18,Romania,RO,ROU,19414458,Europe,13.88140735\r
-25/05/2020,25,5,2020,213,9,Romania,RO,ROU,19414458,Europe,13.94836776\r
-24/05/2020,24,5,2020,145,11,Romania,RO,ROU,19414458,Europe,14.04108217\r
-23/05/2020,23,5,2020,127,8,Romania,RO,ROU,19414458,Europe,14.94247225\r
-22/05/2020,22,5,2020,198,10,Romania,RO,ROU,19414458,Europe,15.89537035\r
-21/05/2020,21,5,2020,196,15,Romania,RO,ROU,19414458,Europe,16.89462564\r
-20/05/2020,20,5,2020,155,19,Romania,RO,ROU,19414458,Europe,17.27578488\r
-19/05/2020,19,5,2020,165,10,Romania,RO,ROU,19414458,Europe,18.15142097\r
-18/05/2020,18,5,2020,167,16,Romania,RO,ROU,19414458,Europe,19.09916826\r
-17/05/2020,17,5,2020,267,25,Romania,RO,ROU,19414458,Europe,20.45897959\r
-16/05/2020,16,5,2020,190,10,Romania,RO,ROU,19414458,Europe,19.93359794\r
-15/05/2020,15,5,2020,245,30,Romania,RO,ROU,19414458,Europe,20.63925761\r
-14/05/2020,14,5,2020,224,14,Romania,RO,ROU,19414458,Europe,20.72682122\r
-13/05/2020,13,5,2020,190,30,Romania,RO,ROU,19414458,Europe,21.43763169\r
-12/05/2020,12,5,2020,226,20,Romania,RO,ROU,19414458,Europe,21.88575133\r
-11/05/2020,11,5,2020,231,26,Romania,RO,ROU,19414458,Europe,22.28236297\r
-10/05/2020,10,5,2020,320,28,Romania,RO,ROU,19414458,Europe,23.15799905\r
-09/05/2020,9,5,2020,312,22,Romania,RO,ROU,19414458,Europe,22.6326174\r
-08/05/2020,8,5,2020,392,18,Romania,RO,ROU,19414458,Europe,22.67897461\r
-07/05/2020,7,5,2020,270,31,Romania,RO,ROU,19414458,Europe,22.6480698\r
-06/05/2020,6,5,2020,325,24,Romania,RO,ROU,19414458,Europe,23.6679283\r
-05/05/2020,5,5,2020,349,23,Romania,RO,ROU,19414458,Europe,23.57006309\r
-04/05/2020,4,5,2020,431,9,Romania,RO,ROU,19414458,Europe,22.75108581\r
-03/05/2020,3,5,2020,165,27,Romania,RO,ROU,19414458,Europe,22.22055336\r
-02/05/2020,2,5,2020,327,27,Romania,RO,ROU,19414458,Europe,23.17860226\r
-01/05/2020,1,5,2020,262,42,Romania,RO,ROU,19414458,Europe,23.34857867\r
-30/04/2020,30,4,2020,362,25,Romania,RO,ROU,19414458,Europe,24.52811199\r
-29/04/2020,29,4,2020,277,19,Romania,RO,ROU,19414458,Europe,24.39934197\r
-28/04/2020,28,4,2020,303,23,Romania,RO,ROU,19414458,Europe,24.23966716\r
-27/04/2020,27,4,2020,401,33,Romania,RO,ROU,19414458,Europe,24.39419117\r
-26/04/2020,26,4,2020,218,23,Romania,RO,ROU,19414458,Europe,23.92546833\r
-25/04/2020,25,4,2020,321,25,Romania,RO,ROU,19414458,Europe,25.49646248\r
-24/04/2020,24,4,2020,386,19,Romania,RO,ROU,19414458,Europe,25.20801765\r
-23/04/2020,23,4,2020,468,25,Romania,RO,ROU,19414458,Europe,25.49131168\r
-22/04/2020,22,4,2020,306,32,Romania,RO,ROU,19414458,Europe,24.85261242\r
-21/04/2020,21,4,2020,190,17,Romania,RO,ROU,19414458,Europe,25.13075565\r
-20/04/2020,20,4,2020,328,17,Romania,RO,ROU,19414458,Europe,25.14620805\r
-19/04/2020,19,4,2020,351,17,Romania,RO,ROU,19414458,Europe,24.74959641\r
-18/04/2020,18,4,2020,360,13,Romania,RO,ROU,19414458,Europe,25.15650965\r
-17/04/2020,17,4,2020,491,15,Romania,RO,ROU,19414458,Europe,25.59432769\r
-16/04/2020,16,4,2020,337,28,Romania,RO,ROU,19414458,Europe,24.49720718\r
-15/04/2020,15,4,2020,246,26,Romania,RO,ROU,19414458,Europe,23.86880952\r
-14/04/2020,14,4,2020,333,12,Romania,RO,ROU,19414458,Europe,24.11089715\r
-13/04/2020,13,4,2020,310,24,Romania,RO,ROU,19414458,Europe,23.38463428\r
-12/04/2020,12,4,2020,523,25,Romania,RO,ROU,19414458,Europe,23.37433268\r
-11/04/2020,11,4,2020,265,28,Romania,RO,ROU,19414458,Europe,21.50459209\r
-10/04/2020,10,4,2020,441,20,Romania,RO,ROU,19414458,Europe,21.49429049\r
-09/04/2020,9,4,2020,344,27,Romania,RO,ROU,19414458,Europe,19.85633593\r
-08/04/2020,8,4,2020,360,25,Romania,RO,ROU,19414458,Europe,18.82617583\r
-07/04/2020,7,4,2020,193,9,Romania,RO,ROU,19414458,Europe,17.92993655\r
-06/04/2020,6,4,2020,251,7,Romania,RO,ROU,19414458,Europe,17.67239652\r
-05/04/2020,5,4,2020,430,8,Romania,RO,ROU,19414458,Europe,16.71949843\r
-04/04/2020,4,4,2020,445,39,Romania,RO,ROU,19414458,Europe,14.80855144\r
-03/04/2020,3,4,2020,278,9,Romania,RO,ROU,19414458,Europe,12.67612003\r
-02/04/2020,2,4,2020,215,16,Romania,RO,ROU,19414458,Europe,11.3317611\r
-01/04/2020,1,4,2020,293,25,Romania,RO,ROU,19414458,Europe,10.44582342\r
-31/03/2020,31,3,2020,192,4,Romania,RO,ROU,19414458,Europe,9.10661529\r
-30/03/2020,30,3,2020,308,11,Romania,RO,ROU,19414458,Europe,8.34944761\r
-29/03/2020,29,3,2020,160,5,Romania,RO,ROU,19414458,Europe,6.89692187\r
-28/03/2020,28,3,2020,263,7,Romania,RO,ROU,19414458,Europe,6.196413\r
-27/03/2020,27,3,2020,123,4,Romania,RO,ROU,19414458,Europe,4.97052248\r
-26/03/2020,26,3,2020,144,2,Romania,RO,ROU,19414458,Europe,4.43483923\r
-25/03/2020,25,3,2020,186,4,Romania,RO,ROU,19414458,Europe,3.79613997\r
-24/03/2020,24,3,2020,143,5,Romania,RO,ROU,19414458,Europe,2.87929748\r
-23/03/2020,23,3,2020,66,2,Romania,RO,ROU,19414458,Europe,2.15303461\r
-22/03/2020,22,3,2020,59,0,Romania,RO,ROU,19414458,Europe,1.82338338\r
-21/03/2020,21,3,2020,31,0,Romania,RO,ROU,19414458,Europe,1.55039095\r
-20/03/2020,20,3,2020,17,0,Romania,RO,ROU,19414458,Europe,1.39586694\r
-19/03/2020,19,3,2020,43,0,Romania,RO,ROU,19414458,Europe,1.31860493\r
-18/03/2020,18,3,2020,33,0,Romania,RO,ROU,19414458,Europe,1.10227131\r
-17/03/2020,17,3,2020,45,0,Romania,RO,ROU,19414458,Europe,0.93229489\r
-16/03/2020,16,3,2020,26,0,Romania,RO,ROU,19414458,Europe,0.70050887\r
-15/03/2020,15,3,2020,24,0,Romania,RO,ROU,19414458,Europe,0.57688966\r
-14/03/2020,14,3,2020,25,0,Romania,RO,ROU,19414458,Europe,0.45327044\r
-13/03/2020,13,3,2020,19,0,Romania,RO,ROU,19414458,Europe,0.32965123\r
-12/03/2020,12,3,2020,20,0,Romania,RO,ROU,19414458,Europe,0.23178602\r
-11/03/2020,11,3,2020,8,0,Romania,RO,ROU,19414458,Europe,0.12877001\r
-10/03/2020,10,3,2020,2,0,Romania,RO,ROU,19414458,Europe,0.08756361\r
-09/03/2020,9,3,2020,2,0,Romania,RO,ROU,19414458,Europe,0.07726201\r
-08/03/2020,8,3,2020,6,0,Romania,RO,ROU,19414458,Europe,0.06696041\r
-07/03/2020,7,3,2020,1,0,Romania,RO,ROU,19414458,Europe,0.0360556\r
-06/03/2020,6,3,2020,2,0,Romania,RO,ROU,19414458,Europe,0.0309048\r
-04/03/2020,4,3,2020,1,0,Romania,RO,ROU,19414458,Europe,0.0206032\r
-02/03/2020,2,3,2020,0,0,Romania,RO,ROU,19414458,Europe,0.0154524\r
-01/03/2020,1,3,2020,0,0,Romania,RO,ROU,19414458,Europe,0.0154524\r
-29/02/2020,29,2,2020,2,0,Romania,RO,ROU,19414458,Europe,0.0154524\r
-28/02/2020,28,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0.0051508\r
-27/02/2020,27,2,2020,1,0,Romania,RO,ROU,19414458,Europe,0.0051508\r
-26/02/2020,26,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-25/02/2020,25,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-24/02/2020,24,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-23/02/2020,23,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-22/02/2020,22,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-21/02/2020,21,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-20/02/2020,20,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-19/02/2020,19,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-18/02/2020,18,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-17/02/2020,17,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-16/02/2020,16,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-15/02/2020,15,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-14/02/2020,14,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-13/02/2020,13,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-12/02/2020,12,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-11/02/2020,11,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-10/02/2020,10,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-09/02/2020,9,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-08/02/2020,8,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-07/02/2020,7,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-06/02/2020,6,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-05/02/2020,5,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-04/02/2020,4,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-03/02/2020,3,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-02/02/2020,2,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-01/02/2020,1,2,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-31/01/2020,31,1,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-30/01/2020,30,1,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-29/01/2020,29,1,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-28/01/2020,28,1,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-27/01/2020,27,1,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-26/01/2020,26,1,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-25/01/2020,25,1,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-24/01/2020,24,1,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-23/01/2020,23,1,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-22/01/2020,22,1,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-21/01/2020,21,1,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-20/01/2020,20,1,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-19/01/2020,19,1,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-18/01/2020,18,1,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-17/01/2020,17,1,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-16/01/2020,16,1,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-15/01/2020,15,1,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-14/01/2020,14,1,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-13/01/2020,13,1,2020,0,0,Romania,RO,ROU,19414458,Europe,0\r
-12/01/2020,12,1,2020,0,0,Romania,RO,ROU,19414458,Europe,\r
-11/01/2020,11,1,2020,0,0,Romania,RO,ROU,19414458,Europe,\r
-10/01/2020,10,1,2020,0,0,Romania,RO,ROU,19414458,Europe,\r
-09/01/2020,9,1,2020,0,0,Romania,RO,ROU,19414458,Europe,\r
-08/01/2020,8,1,2020,0,0,Romania,RO,ROU,19414458,Europe,\r
-07/01/2020,7,1,2020,0,0,Romania,RO,ROU,19414458,Europe,\r
-06/01/2020,6,1,2020,0,0,Romania,RO,ROU,19414458,Europe,\r
-05/01/2020,5,1,2020,0,0,Romania,RO,ROU,19414458,Europe,\r
-04/01/2020,4,1,2020,0,0,Romania,RO,ROU,19414458,Europe,\r
-03/01/2020,3,1,2020,0,0,Romania,RO,ROU,19414458,Europe,\r
-02/01/2020,2,1,2020,0,0,Romania,RO,ROU,19414458,Europe,\r
-01/01/2020,1,1,2020,0,0,Romania,RO,ROU,19414458,Europe,\r
-31/12/2019,31,12,2019,0,0,Romania,RO,ROU,19414458,Europe,\r
-19/08/2020,19,8,2020,4748,132,Russia,RU,RUS,145872260,Europe,48.72070948\r
-18/08/2020,18,8,2020,4892,55,Russia,RU,RUS,145872260,Europe,49.00246284\r
-17/08/2020,17,8,2020,4969,68,Russia,RU,RUS,145872260,Europe,49.34659955\r
-16/08/2020,16,8,2020,5061,119,Russia,RU,RUS,145872260,Europe,49.66057289\r
-15/08/2020,15,8,2020,5065,114,Russia,RU,RUS,145872260,Europe,49.93547094\r
-14/08/2020,14,8,2020,5057,124,Russia,RU,RUS,145872260,Europe,50.22133749\r
-13/08/2020,13,8,2020,5102,129,Russia,RU,RUS,145872260,Europe,50.53119764\r
-12/08/2020,12,8,2020,4945,70,Russia,RU,RUS,145872260,Europe,50.78690081\r
-11/08/2020,11,8,2020,5118,130,Russia,RU,RUS,145872260,Europe,51.0953899\r
-10/08/2020,10,8,2020,5189,77,Russia,RU,RUS,145872260,Europe,51.44980958\r
-09/08/2020,9,8,2020,5212,129,Russia,RU,RUS,145872260,Europe,51.84467561\r
-08/08/2020,8,8,2020,5241,119,Russia,RU,RUS,145872260,Europe,52.29644074\r
-07/08/2020,7,8,2020,4551,74,Russia,RU,RUS,145872260,Europe,52.68719358\r
-06/08/2020,6,8,2020,5920,181,Russia,RU,RUS,145872260,Europe,53.57632767\r
-05/08/2020,5,8,2020,5159,144,Russia,RU,RUS,145872260,Europe,53.53656686\r
-04/08/2020,4,8,2020,5394,79,Russia,RU,RUS,145872260,Europe,54.00478473\r
-03/08/2020,3,8,2020,5427,70,Russia,RU,RUS,145872260,Europe,54.37908482\r
-02/08/2020,2,8,2020,5462,95,Russia,RU,RUS,145872260,Europe,50.65870646\r
-01/08/2020,1,8,2020,5482,161,Russia,RU,RUS,145872260,Europe,51.10224521\r
-31/07/2020,31,7,2020,5509,129,Russia,RU,RUS,145872260,Europe,56.00927825\r
-30/07/2020,30,7,2020,5475,169,Russia,RU,RUS,145872260,Europe,56.63928152\r
-29/07/2020,29,7,2020,5395,150,Russia,RU,RUS,145872260,Europe,57.28847966\r
-28/07/2020,28,7,2020,5635,85,Russia,RU,RUS,145872260,Europe,57.87323786\r
-27/07/2020,27,7,2020,5765,77,Russia,RU,RUS,145872260,Europe,58.49158709\r
-26/07/2020,26,7,2020,5871,146,Russia,RU,RUS,145872260,Europe,59.0742887\r
-25/07/2020,25,7,2020,5811,154,Russia,RU,RUS,145872260,Europe,59.58158186\r
-24/07/2020,24,7,2020,5848,147,Russia,RU,RUS,145872260,Europe,60.14645965\r
-23/07/2020,23,7,2020,5862,165,Russia,RU,RUS,145872260,Europe,60.59959584\r
-22/07/2020,22,7,2020,5842,153,Russia,RU,RUS,145872260,Europe,61.07946775\r
-21/07/2020,21,7,2020,5940,85,Russia,RU,RUS,145872260,Europe,61.44005721\r
-20/07/2020,20,7,2020,0,0,Russia,RU,RUS,145872260,Europe,61.90004871\r
-19/07/2020,19,7,2020,6109,95,Russia,RU,RUS,145872260,Europe,66.51778755\r
-18/07/2020,18,7,2020,12640,310,Russia,RU,RUS,145872260,Europe,66.87632042\r
-17/07/2020,17,7,2020,6428,167,Russia,RU,RUS,145872260,Europe,62.81660406\r
-16/07/2020,16,7,2020,6422,156,Russia,RU,RUS,145872260,Europe,63.04420045\r
-15/07/2020,15,7,2020,6248,175,Russia,RU,RUS,145872260,Europe,63.13606165\r
-14/07/2020,14,7,2020,6537,104,Russia,RU,RUS,145872260,Europe,63.44112308\r
-13/07/2020,13,7,2020,6615,130,Russia,RU,RUS,145872260,Europe,63.56588977\r
-12/07/2020,12,7,2020,6611,188,Russia,RU,RUS,145872260,Europe,63.68654328\r
-11/07/2020,11,7,2020,6635,174,Russia,RU,RUS,145872260,Europe,63.85175632\r
-10/07/2020,10,7,2020,6509,176,Russia,RU,RUS,145872260,Europe,63.96486899\r
-09/07/2020,9,7,2020,6562,173,Russia,RU,RUS,145872260,Europe,64.37892989\r
-08/07/2020,8,7,2020,6368,198,Russia,RU,RUS,145872260,Europe,64.79984611\r
-07/07/2020,7,7,2020,6611,135,Russia,RU,RUS,145872260,Europe,65.5244527\r
-06/07/2020,6,7,2020,6736,134,Russia,RU,RUS,145872260,Europe,66.20244315\r
-05/07/2020,5,7,2020,6632,168,Russia,RU,RUS,145872260,Europe,66.8824902\r
-04/07/2020,4,7,2020,6718,176,Russia,RU,RUS,145872260,Europe,67.74420304\r
-03/07/2020,3,7,2020,6760,147,Russia,RU,RUS,145872260,Europe,68.60385929\r
-02/07/2020,2,7,2020,6556,216,Russia,RU,RUS,145872260,Europe,69.30995653\r
-01/07/2020,1,7,2020,6693,154,Russia,RU,RUS,145872260,Europe,70.19223532\r
-30/06/2020,30,6,2020,6719,93,Russia,RU,RUS,145872260,Europe,71.25823649\r
-29/06/2020,29,6,2020,6791,104,Russia,RU,RUS,145872260,Europe,72.30504278\r
-28/06/2020,28,6,2020,6852,188,Russia,RU,RUS,145872260,Europe,73.70626876\r
-27/06/2020,27,6,2020,6800,176,Russia,RU,RUS,145872260,Europe,74.97724379\r
-26/06/2020,26,6,2020,7113,92,Russia,RU,RUS,145872260,Europe,76.47650074\r
-25/06/2020,25,6,2020,7176,154,Russia,RU,RUS,145872260,Europe,77.61859589\r
-24/06/2020,24,6,2020,7425,153,Russia,RU,RUS,145872260,Europe,78.46042832\r
-23/06/2020,23,6,2020,7600,95,Russia,RU,RUS,145872260,Europe,79.26249994\r
-22/06/2020,22,6,2020,7728,109,Russia,RU,RUS,145872260,Europe,80.21196079\r
-21/06/2020,21,6,2020,7889,30,Russia,RU,RUS,145872260,Europe,81.07298811\r
-20/06/2020,20,6,2020,7972,182,Russia,RU,RUS,145872260,Europe,81.73521134\r
-19/06/2020,19,6,2020,7790,312,Russia,RU,RUS,145872260,Europe,82.25210194\r
-18/06/2020,18,6,2020,7843,194,Russia,RU,RUS,145872260,Europe,82.96574002\r
-17/06/2020,17,6,2020,8248,193,Russia,RU,RUS,145872260,Europe,83.44081322\r
-16/06/2020,16,6,2020,8246,143,Russia,RU,RUS,145872260,Europe,83.86241496\r
-15/06/2020,15,6,2020,8835,119,Russia,RU,RUS,145872260,Europe,84.40329916\r
-14/06/2020,14,6,2020,8706,114,Russia,RU,RUS,145872260,Europe,84.70013421\r
-13/06/2020,13,6,2020,8987,183,Russia,RU,RUS,145872260,Europe,84.86877491\r
-12/06/2020,12,6,2020,8779,174,Russia,RU,RUS,145872260,Europe,84.58427942\r
-11/06/2020,11,6,2020,8404,217,Russia,RU,RUS,145872260,Europe,84.30458265\r
-10/06/2020,10,6,2020,8595,170,Russia,RU,RUS,145872260,Europe,84.25933759\r
-09/06/2020,9,6,2020,8985,112,Russia,RU,RUS,145872260,Europe,84.4787076\r
-08/06/2020,8,6,2020,8984,134,Russia,RU,RUS,145872260,Europe,84.45197188\r
-07/06/2020,7,6,2020,8855,197,Russia,RU,RUS,145872260,Europe,84.18804233\r
-06/06/2020,6,6,2020,8726,144,Russia,RU,RUS,145872260,Europe,84.58496495\r
-05/06/2020,5,6,2020,8831,169,Russia,RU,RUS,145872260,Europe,84.70013421\r
-04/06/2020,4,6,2020,8536,178,Russia,RU,RUS,145872260,Europe,84.71247378\r
-03/06/2020,3,6,2020,8863,182,Russia,RU,RUS,145872260,Europe,84.86877491\r
-02/06/2020,2,6,2020,9035,162,Russia,RU,RUS,145872260,Europe,85.14298743\r
-01/06/2020,1,6,2020,9268,138,Russia,RU,RUS,145872260,Europe,85.06826452\r
-31/05/2020,31,5,2020,8952,181,Russia,RU,RUS,145872260,Europe,85.37058382\r
-30/05/2020,30,5,2020,8572,232,Russia,RU,RUS,145872260,Europe,85.54059559\r
-29/05/2020,29,5,2020,8371,174,Russia,RU,RUS,145872260,Europe,86.929482\r
-28/05/2020,28,5,2020,8338,161,Russia,RU,RUS,145872260,Europe,88.02838867\r
-27/05/2020,27,5,2020,8915,174,Russia,RU,RUS,145872260,Europe,89.18693657\r
-26/05/2020,26,5,2020,8946,92,Russia,RU,RUS,145872260,Europe,90.54703067\r
-25/05/2020,25,5,2020,8599,153,Russia,RU,RUS,145872260,Europe,92.40482049\r
-24/05/2020,24,5,2020,9434,139,Russia,RU,RUS,145872260,Europe,94.05900752\r
-23/05/2020,23,5,2020,8894,150,Russia,RU,RUS,145872260,Europe,95.00709731\r
-22/05/2020,22,5,2020,8849,127,Russia,RU,RUS,145872260,Europe,96.2444813\r
-21/05/2020,21,5,2020,8764,135,Russia,RU,RUS,145872260,Europe,97.87741686\r
-20/05/2020,20,5,2020,9263,115,Russia,RU,RUS,145872260,Europe,99.10794554\r
-19/05/2020,19,5,2020,8926,91,Russia,RU,RUS,145872260,Europe,99.6831063\r
-18/05/2020,18,5,2020,9709,94,Russia,RU,RUS,145872260,Europe,100.8176606\r
-17/05/2020,17,5,2020,9200,119,Russia,RU,RUS,145872260,Europe,101.45109152\r
-16/05/2020,16,5,2020,10598,113,Russia,RU,RUS,145872260,Europe,101.74107126\r
-15/05/2020,15,5,2020,9974,93,Russia,RU,RUS,145872260,Europe,99.91413035\r
-14/05/2020,14,5,2020,10028,96,Russia,RU,RUS,145872260,Europe,97.94322786\r
-13/05/2020,13,5,2020,10899,107,Russia,RU,RUS,145872260,Europe,95.07290831\r
-12/05/2020,12,5,2020,11656,94,Russia,RU,RUS,145872260,Europe,91.99624384\r
-11/05/2020,11,5,2020,11012,88,Russia,RU,RUS,145872260,Europe,88.254614\r
-10/05/2020,10,5,2020,10817,104,Russia,RU,RUS,145872260,Europe,85.06620793\r
-09/05/2020,9,5,2020,10699,98,Russia,RU,RUS,145872260,Europe,81.74069559\r
-08/05/2020,8,5,2020,11231,88,Russia,RU,RUS,145872260,Europe,78.41586879\r
-07/05/2020,7,5,2020,10559,86,Russia,RU,RUS,145872260,Europe,73.98939319\r
-06/05/2020,6,5,2020,10102,95,Russia,RU,RUS,145872260,Europe,70.34031008\r
-05/05/2020,5,5,2020,10581,76,Russia,RU,RUS,145872260,Europe,67.28284048\r
-04/05/2020,4,5,2020,10633,58,Russia,RU,RUS,145872260,Europe,62.95508138\r
-03/05/2020,3,5,2020,9623,53,Russia,RU,RUS,145872260,Europe,59.82014675\r
-02/05/2020,2,5,2020,7933,96,Russia,RU,RUS,145872260,Europe,56.50354632\r
-01/05/2020,1,5,2020,7099,101,Russia,RU,RUS,145872260,Europe,53.85533891\r
-30/04/2020,30,4,2020,5841,105,Russia,RU,RUS,145872260,Europe,51.35246414\r
-29/04/2020,29,4,2020,6411,72,Russia,RU,RUS,145872260,Europe,49.67085586\r
-28/04/2020,28,4,2020,6198,48,Russia,RU,RUS,145872260,Europe,47.17757852\r
-27/04/2020,27,4,2020,6361,66,Russia,RU,RUS,145872260,Europe,44.68224459\r
-26/04/2020,26,4,2020,5966,66,Russia,RU,RUS,145872260,Europe,41.82015141\r
-25/04/2020,25,4,2020,5849,60,Russia,RU,RUS,145872260,Europe,38.87305235\r
-24/04/2020,24,4,2020,4774,42,Russia,RU,RUS,145872260,Europe,36.08773868\r
-23/04/2020,23,4,2020,5236,57,Russia,RU,RUS,145872260,Europe,33.81520242\r
-22/04/2020,22,4,2020,5642,51,Russia,RU,RUS,145872260,Europe,31.03125982\r
-21/04/2020,21,4,2020,4268,44,Russia,RU,RUS,145872260,Europe,27.95459534\r
-20/04/2020,20,4,2020,6060,48,Russia,RU,RUS,145872260,Europe,25.68274462\r
-19/04/2020,19,4,2020,4785,40,Russia,RU,RUS,145872260,Europe,21.97950453\r
-18/04/2020,18,4,2020,4070,41,Russia,RU,RUS,145872260,Europe,19.09821648\r
-17/04/2020,17,4,2020,3448,34,Russia,RU,RUS,145872260,Europe,16.7201084\r
-16/04/2020,16,4,2020,3388,28,Russia,RU,RUS,145872260,Europe,14.88494111\r
-15/04/2020,15,4,2020,2774,22,Russia,RU,RUS,145872260,Europe,12.86399484\r
-14/04/2020,14,4,2020,2558,18,Russia,RU,RUS,145872260,Europe,11.3057822\r
-13/04/2020,13,4,2020,2186,24,Russia,RU,RUS,145872260,Europe,9.75922358\r
-12/04/2020,12,4,2020,1667,12,Russia,RU,RUS,145872260,Europe,8.44574561\r
-11/04/2020,11,4,2020,1786,18,Russia,RU,RUS,145872260,Europe,7.45926607\r
-10/04/2020,10,4,2020,1459,13,Russia,RU,RUS,145872260,Europe,6.36927131\r
-09/04/2020,9,4,2020,1175,5,Russia,RU,RUS,145872260,Europe,5.49384784\r
-08/04/2020,8,4,2020,1154,11,Russia,RU,RUS,145872260,Europe,4.80009016\r
-07/04/2020,7,4,2020,954,2,Russia,RU,RUS,145872260,Europe,4.04806233\r
-06/04/2020,6,4,2020,658,2,Russia,RU,RUS,145872260,Europe,3.39406547\r
-05/04/2020,5,4,2020,582,9,Russia,RU,RUS,145872260,Europe,3.033476\r
-04/04/2020,4,4,2020,601,4,Russia,RU,RUS,145872260,Europe,2.67082994\r
-03/04/2020,3,4,2020,771,6,Russia,RU,RUS,145872260,Europe,2.29584432\r
-02/04/2020,2,4,2020,440,7,Russia,RU,RUS,145872260,Europe,1.80294732\r
-01/04/2020,1,4,2020,501,7,Russia,RU,RUS,145872260,Europe,1.52393608\r
-31/03/2020,31,3,2020,302,2,Russia,RU,RUS,145872260,Europe,1.19488106\r
-30/03/2020,30,3,2020,270,3,Russia,RU,RUS,145872260,Europe,1.00841654\r
-29/03/2020,29,3,2020,228,1,Russia,RU,RUS,145872260,Europe,0.82606522\r
-28/03/2020,28,3,2020,196,2,Russia,RU,RUS,145872260,Europe,0.67936152\r
-27/03/2020,27,3,2020,182,2,Russia,RU,RUS,145872260,Europe,0.55528035\r
-26/03/2020,26,3,2020,163,0,Russia,RU,RUS,145872260,Europe,0.43394131\r
-25/03/2020,25,3,2020,57,0,Russia,RU,RUS,145872260,Europe,0.33248268\r
-24/03/2020,24,3,2020,0,0,Russia,RU,RUS,145872260,Europe,0.2934074\r
-23/03/2020,23,3,2020,132,0,Russia,RU,RUS,145872260,Europe,0.2934074\r
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-02/08/2020,2,8,2020,3,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,60.91663257\r
-01/08/2020,1,8,2020,1,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,60.4516201\r
-31/07/2020,31,7,2020,2,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,60.4516201\r
-30/07/2020,30,7,2020,1,1,Sao_Tome_and_Principe,ST,STP,215048,Africa,60.91663257\r
-29/07/2020,29,7,2020,2,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,62.77668242\r
-28/07/2020,28,7,2020,2,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,61.84665749\r
-27/07/2020,27,7,2020,1,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,62.31166995\r
-26/07/2020,26,7,2020,2,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,62.77668242\r
-25/07/2020,25,7,2020,111,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,61.84665749\r
-24/07/2020,24,7,2020,2,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,10.69528663\r
-23/07/2020,23,7,2020,1,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,10.69528663\r
-22/07/2020,22,7,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,10.23027417\r
-21/07/2020,21,7,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,11.62531156\r
-20/07/2020,20,7,2020,3,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,12.09032402\r
-19/07/2020,19,7,2020,2,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,11.1602991\r
-18/07/2020,18,7,2020,1,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,10.23027417\r
-17/07/2020,17,7,2020,3,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,10.69528663\r
-16/07/2020,16,7,2020,5,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,10.23027417\r
-15/07/2020,15,7,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,8.37022432\r
-14/07/2020,14,7,2020,3,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,8.83523678\r
-13/07/2020,13,7,2020,2,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,7.4401994\r
-12/07/2020,12,7,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,6.51017447\r
-11/07/2020,11,7,2020,1,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,6.97518694\r
-10/07/2020,10,7,2020,2,1,Sao_Tome_and_Principe,ST,STP,215048,Africa,6.97518694\r
-09/07/2020,9,7,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,6.51017447\r
-08/07/2020,8,7,2020,3,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,7.90521186\r
-07/07/2020,7,7,2020,1,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,8.83523678\r
-06/07/2020,6,7,2020,1,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,10.23027417\r
-05/07/2020,5,7,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,9.76526171\r
-04/07/2020,4,7,2020,2,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,12.09032402\r
-03/07/2020,3,7,2020,2,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,13.48536141\r
-02/07/2020,2,7,2020,1,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,14.88039879\r
-01/07/2020,1,7,2020,1,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,19.99553588\r
-30/06/2020,30,6,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,24.18064804\r
-29/06/2020,29,6,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,24.18064804\r
-28/06/2020,28,6,2020,1,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,25.11067297\r
-27/06/2020,27,6,2020,1,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,28.83077266\r
-26/06/2020,26,6,2020,1,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,33.48089729\r
-25/06/2020,25,6,2020,3,1,Sao_Tome_and_Principe,ST,STP,215048,Africa,36.27097206\r
-24/06/2020,24,6,2020,5,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,89.74740523\r
-23/06/2020,23,6,2020,4,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,87.42234292\r
-22/06/2020,22,6,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,85.56229307\r
-21/06/2020,21,6,2020,5,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,86.02730553\r
-20/06/2020,20,6,2020,5,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,85.56229307\r
-19/06/2020,19,6,2020,5,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,87.88735538\r
-18/06/2020,18,6,2020,12,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,92.53748\r
-17/06/2020,17,6,2020,10,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,86.95733046\r
-16/06/2020,16,6,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,82.30720583\r
-15/06/2020,15,6,2020,2,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,82.7722183\r
-14/06/2020,14,6,2020,9,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,83.70224322\r
-13/06/2020,13,6,2020,11,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,86.95733046\r
-12/06/2020,12,6,2020,7,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,84.16725568\r
-11/06/2020,11,6,2020,118,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,87.88735538\r
-10/06/2020,10,6,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,33.94590975\r
-09/06/2020,9,6,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,99.9776794\r
-08/06/2020,8,6,2020,1,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,99.9776794\r
-07/06/2020,7,6,2020,4,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,103.23276664\r
-06/06/2020,6,6,2020,10,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,119.97321528\r
-05/06/2020,5,6,2020,15,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,115.32309066\r
-04/06/2020,4,6,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,108.34790372\r
-03/06/2020,3,6,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,108.34790372\r
-02/06/2020,2,6,2020,1,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,110.67296604\r
-01/06/2020,1,6,2020,4,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,115.32309066\r
-31/05/2020,31,5,2020,16,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,113.46304081\r
-30/05/2020,30,5,2020,5,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,106.02284141\r
-29/05/2020,29,5,2020,15,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,103.6977791\r
-28/05/2020,28,5,2020,2,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,96.72259217\r
-27/05/2020,27,5,2020,142,1,Sao_Tome_and_Principe,ST,STP,215048,Africa,102.76775418\r
-26/05/2020,26,5,2020,0,2,Sao_Tome_and_Principe,ST,STP,215048,Africa,40.45608422\r
-25/05/2020,25,5,2020,8,1,Sao_Tome_and_Principe,ST,STP,215048,Africa,42.31613407\r
-24/05/2020,24,5,2020,40,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,38.59603437\r
-23/05/2020,23,5,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,19.99553588\r
-22/05/2020,22,5,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,29.76079759\r
-21/05/2020,21,5,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,35.8059596\r
-20/05/2020,20,5,2020,5,1,Sao_Tome_and_Principe,ST,STP,215048,Africa,35.8059596\r
-19/05/2020,19,5,2020,11,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,33.48089729\r
-18/05/2020,18,5,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,100.90770433\r
-17/05/2020,17,5,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,100.90770433\r
-16/05/2020,16,5,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,100.90770433\r
-15/05/2020,15,5,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,101.83772925\r
-14/05/2020,14,5,2020,15,1,Sao_Tome_and_Principe,ST,STP,215048,Africa,102.76775418\r
-13/05/2020,13,5,2020,8,1,Sao_Tome_and_Principe,ST,STP,215048,Africa,97.18760463\r
-12/05/2020,12,5,2020,4,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,94.86254232\r
-11/05/2020,11,5,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,93.00249247\r
-10/05/2020,10,5,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,93.00249247\r
-09/05/2020,9,5,2020,21,1,Sao_Tome_and_Principe,ST,STP,215048,Africa,93.00249247\r
-08/05/2020,8,5,2020,13,1,Sao_Tome_and_Principe,ST,STP,215048,Africa,83.23723076\r
-07/05/2020,7,5,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,77.65708121\r
-06/05/2020,6,5,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,79.0521186\r
-05/05/2020,5,5,2020,156,2,Sao_Tome_and_Principe,ST,STP,215048,Africa,79.0521186\r
-04/05/2020,4,5,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,6.51017447\r
-03/05/2020,3,5,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,6.51017447\r
-02/05/2020,2,5,2020,2,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,6.51017447\r
-01/05/2020,1,5,2020,2,1,Sao_Tome_and_Principe,ST,STP,215048,Africa,5.58014955\r
-30/04/2020,30,4,2020,3,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,4.65012462\r
-29/04/2020,29,4,2020,3,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,3.25508724\r
-28/04/2020,28,4,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,1.86004985\r
-27/04/2020,27,4,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,1.86004985\r
-26/04/2020,26,4,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,1.86004985\r
-25/04/2020,25,4,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,1.86004985\r
-24/04/2020,24,4,2020,1,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,1.86004985\r
-23/04/2020,23,4,2020,3,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,1.39503739\r
-22/04/2020,22,4,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,1.86004985\r
-21/04/2020,21,4,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,\r
-20/04/2020,20,4,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,\r
-19/04/2020,19,4,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,\r
-18/04/2020,18,4,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,\r
-17/04/2020,17,4,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,\r
-16/04/2020,16,4,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,\r
-15/04/2020,15,4,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,\r
-14/04/2020,14,4,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,\r
-13/04/2020,13,4,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,\r
-12/04/2020,12,4,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,\r
-11/04/2020,11,4,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,\r
-10/04/2020,10,4,2020,0,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,\r
-09/04/2020,9,4,2020,4,0,Sao_Tome_and_Principe,ST,STP,215048,Africa,\r
-19/08/2020,19,8,2020,1419,34,Saudi_Arabia,SA,SAU,34268529,Asia,58.06493766\r
-18/08/2020,18,8,2020,1372,28,Saudi_Arabia,SA,SAU,34268529,Asia,57.8402417\r
-17/08/2020,17,8,2020,1227,39,Saudi_Arabia,SA,SAU,34268529,Asia,57.50757495\r
-16/08/2020,16,8,2020,1413,31,Saudi_Arabia,SA,SAU,34268529,Asia,57.88693177\r
-15/08/2020,15,8,2020,1383,35,Saudi_Arabia,SA,SAU,34268529,Asia,58.35383246\r
-14/08/2020,14,8,2020,1482,34,Saudi_Arabia,SA,SAU,34268529,Asia,59.23802565\r
-13/08/2020,13,8,2020,1569,36,Saudi_Arabia,SA,SAU,34268529,Asia,59.66699067\r
-12/08/2020,12,8,2020,1521,34,Saudi_Arabia,SA,SAU,34268529,Asia,60.22143524\r
-11/08/2020,11,8,2020,1257,32,Saudi_Arabia,SA,SAU,34268529,Asia,61.31865187\r
-10/08/2020,10,8,2020,1428,37,Saudi_Arabia,SA,SAU,34268529,Asia,63.46639507\r
-09/08/2020,9,8,2020,1469,37,Saudi_Arabia,SA,SAU,34268529,Asia,65.04218492\r
-08/08/2020,8,8,2020,1567,38,Saudi_Arabia,SA,SAU,34268529,Asia,67.17825559\r
-07/08/2020,7,8,2020,1402,35,Saudi_Arabia,SA,SAU,34268529,Asia,69.54485849\r
-06/08/2020,6,8,2020,1389,36,Saudi_Arabia,SA,SAU,34268529,Asia,71.98441462\r
-05/08/2020,5,8,2020,1342,35,Saudi_Arabia,SA,SAU,34268529,Asia,74.73329246\r
-04/08/2020,4,8,2020,1258,32,Saudi_Arabia,SA,SAU,34268529,Asia,78.04245114\r
-03/08/2020,3,8,2020,1357,50,Saudi_Arabia,SA,SAU,34268529,Asia,81.4595806\r
-02/08/2020,2,8,2020,1573,1,Saudi_Arabia,SA,SAU,34268529,Asia,84.80667495\r
-01/08/2020,1,8,2020,1686,0,Saudi_Arabia,SA,SAU,34268529,Asia,87.70145926\r
-31/07/2020,31,7,2020,1629,50,Saudi_Arabia,SA,SAU,34268529,Asia,90.40656516\r
-30/07/2020,30,7,2020,1759,27,Saudi_Arabia,SA,SAU,34268529,Asia,93.71864196\r
-29/07/2020,29,7,2020,1897,29,Saudi_Arabia,SA,SAU,34268529,Asia,96.37997592\r
-28/07/2020,28,7,2020,1993,27,Saudi_Arabia,SA,SAU,34268529,Asia,98.69988875\r
-27/07/2020,27,7,2020,1968,30,Saudi_Arabia,SA,SAU,34268529,Asia,101.20656186\r
-26/07/2020,26,7,2020,2201,31,Saudi_Arabia,SA,SAU,34268529,Asia,103.57316475\r
-25/07/2020,25,7,2020,2378,37,Saudi_Arabia,SA,SAU,34268529,Asia,105.88724132\r
-24/07/2020,24,7,2020,2238,34,Saudi_Arabia,SA,SAU,34268529,Asia,108.16630034\r
-23/07/2020,23,7,2020,2331,44,Saudi_Arabia,SA,SAU,34268529,Asia,110.92393257\r
-22/07/2020,22,7,2020,2476,34,Saudi_Arabia,SA,SAU,34268529,Asia,112.98121375\r
-21/07/2020,21,7,2020,2429,37,Saudi_Arabia,SA,SAU,34268529,Asia,115.65422023\r
-20/07/2020,20,7,2020,2504,39,Saudi_Arabia,SA,SAU,34268529,Asia,120.8426542\r
-19/07/2020,19,7,2020,2565,40,Saudi_Arabia,SA,SAU,34268529,Asia,123.98256138\r
-18/07/2020,18,7,2020,2613,37,Saudi_Arabia,SA,SAU,34268529,Asia,128.54359754\r
-17/07/2020,17,7,2020,2764,45,Saudi_Arabia,SA,SAU,34268529,Asia,133.1542419\r
-16/07/2020,16,7,2020,2671,42,Saudi_Arabia,SA,SAU,34268529,Asia,134.96056396\r
-15/07/2020,15,7,2020,2692,40,Saudi_Arabia,SA,SAU,34268529,Asia,137.09371651\r
-14/07/2020,14,7,2020,2852,20,Saudi_Arabia,SA,SAU,34268529,Asia,142.03994575\r
-13/07/2020,13,7,2020,2779,42,Saudi_Arabia,SA,SAU,34268529,Asia,145.22362486\r
-12/07/2020,12,7,2020,2994,30,Saudi_Arabia,SA,SAU,34268529,Asia,148.75456136\r
-11/07/2020,11,7,2020,3159,51,Saudi_Arabia,SA,SAU,34268529,Asia,151.47717604\r
-10/07/2020,10,7,2020,3183,41,Saudi_Arabia,SA,SAU,34268529,Asia,153.7503988\r
-09/07/2020,9,7,2020,3036,42,Saudi_Arabia,SA,SAU,34268529,Asia,154.30192524\r
-08/07/2020,8,7,2020,3392,49,Saudi_Arabia,SA,SAU,34268529,Asia,154.5558025\r
-07/07/2020,7,7,2020,4207,52,Saudi_Arabia,SA,SAU,34268529,Asia,153.81751577\r
-06/07/2020,6,7,2020,3580,58,Saudi_Arabia,SA,SAU,34268529,Asia,151.44215849\r
-05/07/2020,5,7,2020,4128,56,Saudi_Arabia,SA,SAU,34268529,Asia,150.85561449\r
-04/07/2020,4,7,2020,4193,50,Saudi_Arabia,SA,SAU,34268529,Asia,150.3099243\r
-03/07/2020,3,7,2020,3383,54,Saudi_Arabia,SA,SAU,34268529,Asia,150.62508227\r
-02/07/2020,2,7,2020,3402,49,Saudi_Arabia,SA,SAU,34268529,Asia,154.63459199\r
-01/07/2020,1,7,2020,4387,50,Saudi_Arabia,SA,SAU,34268529,Asia,159.0613942\r
-30/06/2020,30,6,2020,3943,48,Saudi_Arabia,SA,SAU,34268529,Asia,158.71121868\r
-29/06/2020,29,6,2020,3989,40,Saudi_Arabia,SA,SAU,34268529,Asia,160.35704363\r
-28/06/2020,28,6,2020,3927,37,Saudi_Arabia,SA,SAU,34268529,Asia,161.06906719\r
-27/06/2020,27,6,2020,3938,46,Saudi_Arabia,SA,SAU,34268529,Asia,159.43199663\r
-26/06/2020,26,6,2020,3372,41,Saudi_Arabia,SA,SAU,34268529,Asia,159.38238843\r
-25/06/2020,25,6,2020,3123,41,Saudi_Arabia,SA,SAU,34268529,Asia,160.43583312\r
-24/06/2020,24,6,2020,3139,39,Saudi_Arabia,SA,SAU,34268529,Asia,162.16920195\r
-23/06/2020,23,6,2020,3393,40,Saudi_Arabia,SA,SAU,34268529,Asia,162.60400322\r
-22/06/2020,22,6,2020,3379,37,Saudi_Arabia,SA,SAU,34268529,Asia,162.53396812\r
-21/06/2020,21,6,2020,3941,46,Saudi_Arabia,SA,SAU,34268529,Asia,161.55931292\r
-20/06/2020,20,6,2020,4301,45,Saudi_Arabia,SA,SAU,34268529,Asia,159.16644686\r
-19/06/2020,19,6,2020,4757,48,Saudi_Arabia,SA,SAU,34268529,Asia,154.17644568\r
-18/06/2020,18,6,2020,4919,39,Saudi_Arabia,SA,SAU,34268529,Asia,146.05820985\r
-17/06/2020,17,6,2020,4267,41,Saudi_Arabia,SA,SAU,34268529,Asia,138.03919042\r
-16/06/2020,16,6,2020,4507,39,Saudi_Arabia,SA,SAU,34268529,Asia,131.04151626\r
-15/06/2020,15,6,2020,4233,40,Saudi_Arabia,SA,SAU,34268529,Asia,123.3785086\r
-14/06/2020,14,6,2020,3366,39,Saudi_Arabia,SA,SAU,34268529,Asia,116.50339587\r
-13/06/2020,13,6,2020,3921,36,Saudi_Arabia,SA,SAU,34268529,Asia,111.40250578\r
-12/06/2020,12,6,2020,3733,38,Saudi_Arabia,SA,SAU,34268529,Asia,104.57408312\r
-11/06/2020,11,6,2020,3717,36,Saudi_Arabia,SA,SAU,34268529,Asia,98.47811092\r
-10/06/2020,10,6,2020,3288,37,Saudi_Arabia,SA,SAU,34268529,Asia,92.92782891\r
-09/06/2020,9,6,2020,3369,34,Saudi_Arabia,SA,SAU,34268529,Asia,88.96792739\r
-08/06/2020,8,6,2020,3045,36,Saudi_Arabia,SA,SAU,34268529,Asia,85.65876872\r
-07/06/2020,7,6,2020,3121,34,Saudi_Arabia,SA,SAU,34268529,Asia,83.77365717\r
-06/06/2020,6,6,2020,2591,31,Saudi_Arabia,SA,SAU,34268529,Asia,81.79224734\r
-05/06/2020,5,6,2020,1975,32,Saudi_Arabia,SA,SAU,34268529,Asia,81.94107194\r
-04/06/2020,4,6,2020,2171,30,Saudi_Arabia,SA,SAU,34268529,Asia,83.56646998\r
-03/06/2020,3,6,2020,1869,24,Saudi_Arabia,SA,SAU,34268529,Asia,85.08389724\r
-02/06/2020,2,6,2020,1881,22,Saudi_Arabia,SA,SAU,34268529,Asia,86.95150002\r
-01/06/2020,1,6,2020,1877,23,Saudi_Arabia,SA,SAU,34268529,Asia,89.02920811\r
-31/05/2020,31,5,2020,1618,22,Saudi_Arabia,SA,SAU,34268529,Asia,91.53588122\r
-30/05/2020,30,5,2020,1581,17,Saudi_Arabia,SA,SAU,34268529,Asia,95.10183527\r
-29/05/2020,29,5,2020,1644,16,Saudi_Arabia,SA,SAU,34268529,Asia,97.22039718\r
-28/05/2020,28,5,2020,1815,14,Saudi_Arabia,SA,SAU,34268529,Asia,98.37305827\r
-27/05/2020,27,5,2020,1931,12,Saudi_Arabia,SA,SAU,34268529,Asia,98.63568991\r
-26/05/2020,26,5,2020,2235,9,Saudi_Arabia,SA,SAU,34268529,Asia,98.57732732\r
-25/05/2020,25,5,2020,2399,11,Saudi_Arabia,SA,SAU,34268529,Asia,97.79235053\r
-24/05/2020,24,5,2020,2442,15,Saudi_Arabia,SA,SAU,34268529,Asia,96.37122154\r
-23/05/2020,23,5,2020,2642,13,Saudi_Arabia,SA,SAU,34268529,Asia,94.21764208\r
-22/05/2020,22,5,2020,2532,12,Saudi_Arabia,SA,SAU,34268529,Asia,91.47168237\r
-21/05/2020,21,5,2020,2691,10,Saudi_Arabia,SA,SAU,34268529,Asia,89.31518479\r
-20/05/2020,20,5,2020,2509,9,Saudi_Arabia,SA,SAU,34268529,Asia,86.38538293\r
-19/05/2020,19,5,2020,2593,8,Saudi_Arabia,SA,SAU,34268529,Asia,83.71821271\r
-18/05/2020,18,5,2020,2736,10,Saudi_Arabia,SA,SAU,34268529,Asia,80.95182609\r
-17/05/2020,17,5,2020,2840,10,Saudi_Arabia,SA,SAU,34268529,Asia,77.49676095\r
-16/05/2020,16,5,2020,2307,9,Saudi_Arabia,SA,SAU,34268529,Asia,73.18376578\r
-15/05/2020,15,5,2020,2039,10,Saudi_Arabia,SA,SAU,34268529,Asia,70.37360722\r
-14/05/2020,14,5,2020,1905,9,Saudi_Arabia,SA,SAU,34268529,Asia,68.36593424\r
-13/05/2020,13,5,2020,1911,9,Saudi_Arabia,SA,SAU,34268529,Asia,66.67341922\r
-12/05/2020,12,5,2020,1966,9,Saudi_Arabia,SA,SAU,34268529,Asia,64.79122579\r
-11/05/2020,11,5,2020,1912,7,Saudi_Arabia,SA,SAU,34268529,Asia,62.81565223\r
-10/05/2020,10,5,2020,1704,10,Saudi_Arabia,SA,SAU,34268529,Asia,60.80506111\r
-09/05/2020,9,5,2020,1701,10,Saudi_Arabia,SA,SAU,34268529,Asia,59.32556953\r
-08/05/2020,8,5,2020,1793,10,Saudi_Arabia,SA,SAU,34268529,Asia,57.78187911\r
-07/05/2020,7,5,2020,1687,9,Saudi_Arabia,SA,SAU,34268529,Asia,55.92886698\r
-06/05/2020,6,5,2020,1595,9,Saudi_Arabia,SA,SAU,34268529,Asia,54.33556836\r
-05/05/2020,5,5,2020,1645,7,Saudi_Arabia,SA,SAU,34268529,Asia,53.02824641\r
-04/05/2020,4,5,2020,1552,8,Saudi_Arabia,SA,SAU,34268529,Asia,51.50206477\r
-03/05/2020,3,5,2020,1362,7,Saudi_Arabia,SA,SAU,34268529,Asia,50.14805275\r
-02/05/2020,2,5,2020,1344,7,Saudi_Arabia,SA,SAU,34268529,Asia,49.476883\r
-01/05/2020,1,5,2020,1351,5,Saudi_Arabia,SA,SAU,34268529,Asia,47.77853173\r
-30/04/2020,30,4,2020,1325,5,Saudi_Arabia,SA,SAU,34268529,Asia,45.34772998\r
-29/04/2020,29,4,2020,1266,8,Saudi_Arabia,SA,SAU,34268529,Asia,42.91984637\r
-28/04/2020,28,4,2020,1289,5,Saudi_Arabia,SA,SAU,34268529,Asia,40.49488089\r
-27/04/2020,27,4,2020,1223,3,Saudi_Arabia,SA,SAU,34268529,Asia,38.11076921\r
-26/04/2020,26,4,2020,1197,9,Saudi_Arabia,SA,SAU,34268529,Asia,35.79377452\r
-25/04/2020,25,4,2020,1172,6,Saudi_Arabia,SA,SAU,34268529,Asia,33.4154991\r
-24/04/2020,24,4,2020,1158,7,Saudi_Arabia,SA,SAU,34268529,Asia,31.05765059\r
-23/04/2020,23,4,2020,1141,5,Saudi_Arabia,SA,SAU,34268529,Asia,28.71439273\r
-22/04/2020,22,4,2020,1147,6,Saudi_Arabia,SA,SAU,34268529,Asia,25.78459087\r
-21/04/2020,21,4,2020,1122,6,Saudi_Arabia,SA,SAU,34268529,Asia,23.2312277\r
-20/04/2020,20,4,2020,1088,5,Saudi_Arabia,SA,SAU,34268529,Asia,20.35978842\r
-19/04/2020,19,4,2020,1132,5,Saudi_Arabia,SA,SAU,34268529,Asia,17.78599834\r
-18/04/2020,18,4,2020,762,4,Saudi_Arabia,SA,SAU,34268529,Asia,15.34060595\r
-17/04/2020,17,4,2020,518,4,Saudi_Arabia,SA,SAU,34268529,Asia,13.11699139\r
-16/04/2020,16,4,2020,493,6,Saudi_Arabia,SA,SAU,34268529,Asia,12.08689174\r
-15/04/2020,15,4,2020,435,8,Saudi_Arabia,SA,SAU,34268529,Asia,11.10640028\r
-14/04/2020,14,4,2020,472,6,Saudi_Arabia,SA,SAU,34268529,Asia,10.15800824\r
-13/04/2020,13,4,2020,429,7,Saudi_Arabia,SA,SAU,34268529,Asia,9.43431216\r
-12/04/2020,12,4,2020,382,5,Saudi_Arabia,SA,SAU,34268529,Asia,8.25830604\r
-11/04/2020,11,4,2020,364,3,Saudi_Arabia,SA,SAU,34268529,Asia,7.43247544\r
-10/04/2020,10,4,2020,355,3,Saudi_Arabia,SA,SAU,34268529,Asia,6.63874425\r
-09/04/2020,9,4,2020,137,0,Saudi_Arabia,SA,SAU,34268529,Asia,5.92963882\r
-08/04/2020,8,4,2020,272,3,Saudi_Arabia,SA,SAU,34268529,Asia,5.91796631\r
-07/04/2020,7,4,2020,138,4,Saudi_Arabia,SA,SAU,34268529,Asia,5.72245164\r
-06/04/2020,6,4,2020,206,5,Saudi_Arabia,SA,SAU,34268529,Asia,5.46857439\r
-05/04/2020,5,4,2020,294,8,Saudi_Arabia,SA,SAU,34268529,Asia,5.21469714\r
-04/04/2020,4,4,2020,0,0,Saudi_Arabia,SA,SAU,34268529,Asia,4.70110637\r
-03/04/2020,3,4,2020,165,5,Saudi_Arabia,SA,SAU,34268529,Asia,4.80615903\r
-02/04/2020,2,4,2020,157,6,Saudi_Arabia,SA,SAU,34268529,Asia,4.52018235\r
-01/04/2020,1,4,2020,110,2,Saudi_Arabia,SA,SAU,34268529,Asia,4.17292496\r
-31/03/2020,31,3,2020,224,0,Saudi_Arabia,SA,SAU,34268529,Asia,3.85193073\r
-30/03/2020,30,3,2020,26,4,Saudi_Arabia,SA,SAU,34268529,Asia,3.2420417\r
-29/03/2020,29,3,2020,99,1,Saudi_Arabia,SA,SAU,34268529,Asia,3.25955048\r
-28/03/2020,28,3,2020,92,0,Saudi_Arabia,SA,SAU,34268529,Asia,2.97065567\r
-27/03/2020,27,3,2020,112,1,Saudi_Arabia,SA,SAU,34268529,Asia,2.77222288\r
-26/03/2020,26,3,2020,133,1,Saudi_Arabia,SA,SAU,34268529,Asia,2.49500059\r
-25/03/2020,25,3,2020,205,1,Saudi_Arabia,SA,SAU,34268529,Asia,2.17984262\r
-24/03/2020,24,3,2020,51,0,Saudi_Arabia,SA,SAU,34268529,Asia,1.59621675\r
-23/03/2020,23,3,2020,119,0,Saudi_Arabia,SA,SAU,34268529,Asia,1.45906467\r
-22/03/2020,22,3,2020,118,0,Saudi_Arabia,SA,SAU,34268529,Asia,1.1234798\r
-21/03/2020,21,3,2020,36,0,Saudi_Arabia,SA,SAU,34268529,Asia,0.78497679\r
-20/03/2020,20,3,2020,67,0,Saudi_Arabia,SA,SAU,34268529,Asia,0.69159665\r
-19/03/2020,19,3,2020,38,0,Saudi_Arabia,SA,SAU,34268529,Asia,0.49900012\r
-18/03/2020,18,3,2020,0,0,Saudi_Arabia,SA,SAU,34268529,Asia,\r
-17/03/2020,17,3,2020,15,0,Saudi_Arabia,SA,SAU,34268529,Asia,\r
-16/03/2020,16,3,2020,32,0,Saudi_Arabia,SA,SAU,34268529,Asia,\r
-15/03/2020,15,3,2020,0,0,Saudi_Arabia,SA,SAU,34268529,Asia,\r
-14/03/2020,14,3,2020,24,0,Saudi_Arabia,SA,SAU,34268529,Asia,\r
-13/03/2020,13,3,2020,17,0,Saudi_Arabia,SA,SAU,34268529,Asia,\r
-12/03/2020,12,3,2020,25,0,Saudi_Arabia,SA,SAU,34268529,Asia,\r
-11/03/2020,11,3,2020,5,0,Saudi_Arabia,SA,SAU,34268529,Asia,\r
-10/03/2020,10,3,2020,4,0,Saudi_Arabia,SA,SAU,34268529,Asia,\r
-09/03/2020,9,3,2020,4,0,Saudi_Arabia,SA,SAU,34268529,Asia,\r
-08/03/2020,8,3,2020,2,0,Saudi_Arabia,SA,SAU,34268529,Asia,\r
-06/03/2020,6,3,2020,4,0,Saudi_Arabia,SA,SAU,34268529,Asia,\r
-03/03/2020,3,3,2020,1,0,Saudi_Arabia,SA,SAU,34268529,Asia,\r
-19/08/2020,19,8,2020,68,0,Senegal,SN,SEN,16296362,Africa,11.49336275\r
-18/08/2020,18,8,2020,75,3,Senegal,SN,SEN,16296362,Africa,11.3583633\r
-17/08/2020,17,8,2020,130,2,Senegal,SN,SEN,16296362,Africa,11.15586411\r
-16/08/2020,16,8,2020,160,2,Senegal,SN,SEN,16296362,Africa,10.72632039\r
-15/08/2020,15,8,2020,132,5,Senegal,SN,SEN,16296362,Africa,10.06359579\r
-14/08/2020,14,8,2020,153,2,Senegal,SN,SEN,16296362,Africa,10.02677776\r
-13/08/2020,13,8,2020,207,4,Senegal,SN,SEN,16296362,Africa,9.97768704\r
-12/08/2020,12,8,2020,68,2,Senegal,SN,SEN,16296362,Africa,9.66473376\r
-11/08/2020,11,8,2020,137,4,Senegal,SN,SEN,16296362,Africa,9.49905261\r
-10/08/2020,10,8,2020,142,3,Senegal,SN,SEN,16296362,Africa,9.16769031\r
-09/08/2020,9,8,2020,146,4,Senegal,SN,SEN,16296362,Africa,9.0879179\r
-08/08/2020,8,8,2020,172,2,Senegal,SN,SEN,16296362,Africa,8.98973648\r
-07/08/2020,7,8,2020,177,9,Senegal,SN,SEN,16296362,Africa,8.89155506\r
-06/08/2020,6,8,2020,106,0,Senegal,SN,SEN,16296362,Africa,8.69519222\r
-05/08/2020,5,8,2020,46,3,Senegal,SN,SEN,16296362,Africa,8.87928238\r
-04/08/2020,4,8,2020,42,2,Senegal,SN,SEN,16296362,Africa,8.82405533\r
-03/08/2020,3,8,2020,60,0,Senegal,SN,SEN,16296362,Africa,9.41314387\r
-02/08/2020,2,8,2020,52,4,Senegal,SN,SEN,16296362,Africa,9.91018732\r
-01/08/2020,1,8,2020,126,1,Senegal,SN,SEN,16296362,Africa,10.35814006\r
-31/07/2020,31,7,2020,145,4,Senegal,SN,SEN,16296362,Africa,9.97155071\r
-30/07/2020,30,7,2020,156,2,Senegal,SN,SEN,16296362,Africa,9.76905152\r
-29/07/2020,29,7,2020,41,4,Senegal,SN,SEN,16296362,Africa,9.58496136\r
-28/07/2020,28,7,2020,83,3,Senegal,SN,SEN,16296362,Africa,9.60950671\r
-27/07/2020,27,7,2020,129,4,Senegal,SN,SEN,16296362,Africa,9.48677993\r
-26/07/2020,26,7,2020,130,5,Senegal,SN,SEN,16296362,Africa,9.43768922\r
-25/07/2020,25,7,2020,156,4,Senegal,SN,SEN,16296362,Africa,9.4499619\r
-24/07/2020,24,7,2020,145,1,Senegal,SN,SEN,16296362,Africa,9.09405424\r
-23/07/2020,23,7,2020,136,3,Senegal,SN,SEN,16296362,Africa,8.98360014\r
-22/07/2020,22,7,2020,37,4,Senegal,SN,SEN,16296362,Africa,8.82405533\r
-21/07/2020,21,7,2020,138,3,Senegal,SN,SEN,16296362,Africa,9.02041818\r
-20/07/2020,20,7,2020,141,4,Senegal,SN,SEN,16296362,Africa,8.65223784\r
-19/07/2020,19,7,2020,125,3,Senegal,SN,SEN,16296362,Africa,8.57246544\r
-18/07/2020,18,7,2020,63,4,Senegal,SN,SEN,16296362,Africa,8.46814768\r
-17/07/2020,17,7,2020,112,3,Senegal,SN,SEN,16296362,Africa,8.7565556\r
-16/07/2020,16,7,2020,126,3,Senegal,SN,SEN,16296362,Africa,8.86087337\r
-15/07/2020,15,7,2020,45,0,Senegal,SN,SEN,16296362,Africa,8.8976914\r
-14/07/2020,14,7,2020,63,2,Senegal,SN,SEN,16296362,Africa,9.20450834\r
-13/07/2020,13,7,2020,121,3,Senegal,SN,SEN,16296362,Africa,9.50518895\r
-12/07/2020,12,7,2020,132,0,Senegal,SN,SEN,16296362,Africa,9.54200698\r
-11/07/2020,11,7,2020,98,2,Senegal,SN,SEN,16296362,Africa,9.37632583\r
-10/07/2020,10,7,2020,127,2,Senegal,SN,SEN,16296362,Africa,9.51746163\r
-09/07/2020,9,7,2020,110,4,Senegal,SN,SEN,16296362,Africa,9.37632583\r
-08/07/2020,8,7,2020,69,1,Senegal,SN,SEN,16296362,Africa,9.28428075\r
-07/07/2020,7,7,2020,78,3,Senegal,SN,SEN,16296362,Africa,9.25359905\r
-06/07/2020,6,7,2020,128,4,Senegal,SN,SEN,16296362,Africa,9.27814441\r
-05/07/2020,5,7,2020,108,4,Senegal,SN,SEN,16296362,Africa,9.41314387\r
-04/07/2020,4,7,2020,110,4,Senegal,SN,SEN,16296362,Africa,9.35791682\r
-03/07/2020,3,7,2020,129,5,Senegal,SN,SEN,16296362,Africa,9.68927912\r
-02/07/2020,2,7,2020,132,4,Senegal,SN,SEN,16296362,Africa,9.54814332\r
-01/07/2020,1,7,2020,95,4,Senegal,SN,SEN,16296362,Africa,9.48677993\r
-30/06/2020,30,6,2020,112,3,Senegal,SN,SEN,16296362,Africa,9.35791682\r
-29/06/2020,29,6,2020,127,3,Senegal,SN,SEN,16296362,Africa,9.17996299\r
-28/06/2020,28,6,2020,105,4,Senegal,SN,SEN,16296362,Africa,8.9774638\r
-27/06/2020,27,6,2020,121,4,Senegal,SN,SEN,16296362,Africa,9.22291736\r
-26/06/2020,26,6,2020,104,1,Senegal,SN,SEN,16296362,Africa,9.04496353\r
-25/06/2020,25,6,2020,95,4,Senegal,SN,SEN,16296362,Africa,9.13700862\r
-24/06/2020,24,6,2020,64,3,Senegal,SN,SEN,16296362,Africa,9.31496244\r
-23/06/2020,23,6,2020,82,2,Senegal,SN,SEN,16296362,Africa,9.46837092\r
-22/06/2020,22,6,2020,150,2,Senegal,SN,SEN,16296362,Africa,9.57268868\r
-21/06/2020,21,6,2020,99,3,Senegal,SN,SEN,16296362,Africa,9.13700862\r
-20/06/2020,20,6,2020,164,3,Senegal,SN,SEN,16296362,Africa,9.10632692\r
-19/06/2020,19,6,2020,106,3,Senegal,SN,SEN,16296362,Africa,8.92223675\r
-18/06/2020,18,6,2020,122,3,Senegal,SN,SEN,16296362,Africa,8.81791899\r
-17/06/2020,17,6,2020,74,6,Senegal,SN,SEN,16296362,Africa,8.65837418\r
-16/06/2020,16,6,2020,83,4,Senegal,SN,SEN,16296362,Africa,8.79950998\r
-15/06/2020,15,6,2020,94,0,Senegal,SN,SEN,16296362,Africa,8.8670097\r
-14/06/2020,14,6,2020,145,4,Senegal,SN,SEN,16296362,Africa,8.96519113\r
-13/06/2020,13,6,2020,92,0,Senegal,SN,SEN,16296362,Africa,8.72587391\r
-12/06/2020,12,6,2020,119,2,Senegal,SN,SEN,16296362,Africa,8.65837418\r
-11/06/2020,11,6,2020,124,2,Senegal,SN,SEN,16296362,Africa,8.51110205\r
-10/06/2020,10,6,2020,89,0,Senegal,SN,SEN,16296362,Africa,8.3147392\r
-09/06/2020,9,6,2020,99,3,Senegal,SN,SEN,16296362,Africa,7.95883155\r
-08/06/2020,8,6,2020,79,2,Senegal,SN,SEN,16296362,Africa,7.86065013\r
-07/06/2020,7,6,2020,94,2,Senegal,SN,SEN,16296362,Africa,7.81155941\r
-06/06/2020,6,6,2020,134,0,Senegal,SN,SEN,16296362,Africa,7.64587826\r
-05/06/2020,5,6,2020,89,0,Senegal,SN,SEN,16296362,Africa,7.41883372\r
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-31/07/2020,31,7,2020,15,0,Sierra_Leone,SL,SLE,7813207,Africa,1.79183785\r
-30/07/2020,30,7,2020,17,1,Sierra_Leone,SL,SLE,7813207,Africa,1.72784364\r
-29/07/2020,29,7,2020,3,0,Sierra_Leone,SL,SLE,7813207,Africa,1.72784364\r
-28/07/2020,28,7,2020,0,0,Sierra_Leone,SL,SLE,7813207,Africa,1.80463669\r
-27/07/2020,27,7,2020,15,0,Sierra_Leone,SL,SLE,7813207,Africa,1.89422858\r
-26/07/2020,26,7,2020,16,0,Sierra_Leone,SL,SLE,7813207,Africa,1.91982626\r
-25/07/2020,25,7,2020,0,0,Sierra_Leone,SL,SLE,7813207,Africa,1.779039\r
-24/07/2020,24,7,2020,21,0,Sierra_Leone,SL,SLE,7813207,Africa,1.97102163\r
-23/07/2020,23,7,2020,4,0,Sierra_Leone,SL,SLE,7813207,Africa,1.88142974\r
-22/07/2020,22,7,2020,16,0,Sierra_Leone,SL,SLE,7813207,Africa,1.98382047\r
-21/07/2020,21,7,2020,0,1,Sierra_Leone,SL,SLE,7813207,Africa,2.16300426\r
-20/07/2020,20,7,2020,10,0,Sierra_Leone,SL,SLE,7813207,Africa,2.16300426\r
-19/07/2020,19,7,2020,13,0,Sierra_Leone,SL,SLE,7813207,Africa,2.15020542\r
-18/07/2020,18,7,2020,10,1,Sierra_Leone,SL,SLE,7813207,Africa,2.09901005\r
-17/07/2020,17,7,2020,10,0,Sierra_Leone,SL,SLE,7813207,Africa,2.04781468\r
-16/07/2020,16,7,2020,17,0,Sierra_Leone,SL,SLE,7813207,Africa,2.1758031\r
-15/07/2020,15,7,2020,9,1,Sierra_Leone,SL,SLE,7813207,Africa,2.41898109\r
-14/07/2020,14,7,2020,7,0,Sierra_Leone,SL,SLE,7813207,Africa,2.45737762\r
-13/07/2020,13,7,2020,17,0,Sierra_Leone,SL,SLE,7813207,Africa,2.66215909\r
-12/07/2020,12,7,2020,5,0,Sierra_Leone,SL,SLE,7813207,Africa,2.66215909\r
-11/07/2020,11,7,2020,15,0,Sierra_Leone,SL,SLE,7813207,Africa,2.80294634\r
-10/07/2020,10,7,2020,14,0,Sierra_Leone,SL,SLE,7813207,Africa,2.77734866\r
-09/07/2020,9,7,2020,12,0,Sierra_Leone,SL,SLE,7813207,Africa,2.9437336\r
-08/07/2020,8,7,2020,30,1,Sierra_Leone,SL,SLE,7813207,Africa,2.8797394\r
-07/07/2020,7,7,2020,0,0,Sierra_Leone,SL,SLE,7813207,Africa,2.58536603\r
-06/07/2020,6,7,2020,9,0,Sierra_Leone,SL,SLE,7813207,Africa,2.75175098\r
-05/07/2020,5,7,2020,9,0,Sierra_Leone,SL,SLE,7813207,Africa,2.86694055\r
-04/07/2020,4,7,2020,6,2,Sierra_Leone,SL,SLE,7813207,Africa,2.89253824\r
-03/07/2020,3,7,2020,20,0,Sierra_Leone,SL,SLE,7813207,Africa,3.14851507\r
-02/07/2020,2,7,2020,36,0,Sierra_Leone,SL,SLE,7813207,Africa,3.1869116\r
-01/07/2020,1,7,2020,12,0,Sierra_Leone,SL,SLE,7813207,Africa,3.0333255\r
-30/06/2020,30,6,2020,23,0,Sierra_Leone,SL,SLE,7813207,Africa,3.50688264\r
-29/06/2020,29,6,2020,17,1,Sierra_Leone,SL,SLE,7813207,Africa,3.30210117\r
-28/06/2020,28,6,2020,16,0,Sierra_Leone,SL,SLE,7813207,Africa,3.55807801\r
-27/06/2020,27,6,2020,13,3,Sierra_Leone,SL,SLE,7813207,Africa,3.72446295\r
-26/06/2020,26,6,2020,27,0,Sierra_Leone,SL,SLE,7813207,Africa,3.78845716\r
-25/06/2020,25,6,2020,7,1,Sierra_Leone,SL,SLE,7813207,Africa,3.73726179\r
-24/06/2020,24,6,2020,7,0,Sierra_Leone,SL,SLE,7813207,Africa,4.12122705\r
-23/06/2020,23,6,2020,13,0,Sierra_Leone,SL,SLE,7813207,Africa,4.33880736\r
-22/06/2020,22,6,2020,18,2,Sierra_Leone,SL,SLE,7813207,Africa,4.58198535\r
-21/06/2020,21,6,2020,11,0,Sierra_Leone,SL,SLE,7813207,Africa,4.64597956\r
-20/06/2020,20,6,2020,26,2,Sierra_Leone,SL,SLE,7813207,Africa,4.72277261\r
-19/06/2020,19,6,2020,23,0,Sierra_Leone,SL,SLE,7813207,Africa,4.58198535\r
-18/06/2020,18,6,2020,24,0,Sierra_Leone,SL,SLE,7813207,Africa,4.3516062\r
-17/06/2020,17,6,2020,49,0,Sierra_Leone,SL,SLE,7813207,Africa,4.21081894\r
-16/06/2020,16,6,2020,7,0,Sierra_Leone,SL,SLE,7813207,Africa,4.03163515\r
-15/06/2020,15,6,2020,37,0,Sierra_Leone,SL,SLE,7813207,Africa,3.94204326\r
-14/06/2020,14,6,2020,29,0,Sierra_Leone,SL,SLE,7813207,Africa,3.58367569\r
-13/06/2020,13,6,2020,18,1,Sierra_Leone,SL,SLE,7813207,Africa,3.50688264\r
-12/06/2020,12,6,2020,23,0,Sierra_Leone,SL,SLE,7813207,Africa,3.4940838\r
-11/06/2020,11,6,2020,37,0,Sierra_Leone,SL,SLE,7813207,Africa,3.58367569\r
-10/06/2020,10,6,2020,24,1,Sierra_Leone,SL,SLE,7813207,Africa,3.46848612\r
-09/06/2020,9,6,2020,32,1,Sierra_Leone,SL,SLE,7813207,Africa,3.40449191\r
-08/06/2020,8,6,2020,23,0,Sierra_Leone,SL,SLE,7813207,Africa,3.35329654\r
-07/06/2020,7,6,2020,17,1,Sierra_Leone,SL,SLE,7813207,Africa,4.15962357\r
-06/06/2020,6,6,2020,15,0,Sierra_Leone,SL,SLE,7813207,Africa,4.13402589\r
-05/06/2020,5,6,2020,5,0,Sierra_Leone,SL,SLE,7813207,Africa,4.21081894\r
-04/06/2020,4,6,2020,13,1,Sierra_Leone,SL,SLE,7813207,Africa,4.33880736\r
-03/06/2020,3,6,2020,35,0,Sierra_Leone,SL,SLE,7813207,Africa,4.63318072\r
-02/06/2020,2,6,2020,0,0,Sierra_Leone,SL,SLE,7813207,Africa,4.37720388\r
-01/06/2020,1,6,2020,9,0,Sierra_Leone,SL,SLE,7813207,Africa,4.55638767\r
-31/05/2020,31,5,2020,23,1,Sierra_Leone,SL,SLE,7813207,Africa,4.99154828\r
-30/05/2020,30,5,2020,17,0,Sierra_Leone,SL,SLE,7813207,Africa,4.88915755\r
-29/05/2020,29,5,2020,30,0,Sierra_Leone,SL,SLE,7813207,Africa,5.17073207\r
-28/05/2020,28,5,2020,28,1,Sierra_Leone,SL,SLE,7813207,Africa,5.05554249\r
-27/05/2020,27,5,2020,19,2,Sierra_Leone,SL,SLE,7813207,Africa,5.32431817\r
-26/05/2020,26,5,2020,28,2,Sierra_Leone,SL,SLE,7813207,Africa,5.08114018\r
-25/05/2020,25,5,2020,86,1,Sierra_Leone,SL,SLE,7813207,Africa,5.1195367\r
-24/05/2020,24,5,2020,15,1,Sierra_Leone,SL,SLE,7813207,Africa,4.22361778\r
-23/05/2020,23,5,2020,21,3,Sierra_Leone,SL,SLE,7813207,Africa,4.46679577\r
-22/05/2020,22,5,2020,15,1,Sierra_Leone,SL,SLE,7813207,Africa,4.53078998\r
-21/05/2020,21,5,2020,36,1,Sierra_Leone,SL,SLE,7813207,Africa,4.41560041\r
-20/05/2020,20,5,2020,15,0,Sierra_Leone,SL,SLE,7813207,Africa,4.28761199\r
-19/05/2020,19,5,2020,14,1,Sierra_Leone,SL,SLE,7813207,Africa,4.36440504\r
-18/05/2020,18,5,2020,43,3,Sierra_Leone,SL,SLE,7813207,Africa,4.45399693\r
-17/05/2020,17,5,2020,15,2,Sierra_Leone,SL,SLE,7813207,Africa,3.92924442\r
-16/05/2020,16,5,2020,39,1,Sierra_Leone,SL,SLE,7813207,Africa,3.98043979\r
-15/05/2020,15,5,2020,21,5,Sierra_Leone,SL,SLE,7813207,Africa,3.63487106\r
-14/05/2020,14,5,2020,49,1,Sierra_Leone,SL,SLE,7813207,Africa,3.46848612\r
-13/05/2020,13,5,2020,0,1,Sierra_Leone,SL,SLE,7813207,Africa,2.99492897\r
-12/05/2020,12,5,2020,31,1,Sierra_Leone,SL,SLE,7813207,Africa,3.05892318\r
-11/05/2020,11,5,2020,16,0,Sierra_Leone,SL,SLE,7813207,Africa,2.73895214\r
-10/05/2020,10,5,2020,34,1,Sierra_Leone,SL,SLE,7813207,Africa,2.67495793\r
-09/05/2020,9,5,2020,26,1,Sierra_Leone,SL,SLE,7813207,Africa,2.23979731\r
-08/05/2020,8,5,2020,6,2,Sierra_Leone,SL,SLE,7813207,Africa,2.13740657\r
-07/05/2020,7,5,2020,26,3,Sierra_Leone,SL,SLE,7813207,Africa,2.09901005\r
-06/05/2020,6,5,2020,21,2,Sierra_Leone,SL,SLE,7813207,Africa,1.90702742\r
-05/05/2020,5,5,2020,21,1,Sierra_Leone,SL,SLE,7813207,Africa,1.72784364\r
-04/05/2020,4,5,2020,2,0,Sierra_Leone,SL,SLE,7813207,Africa,1.56145869\r
-03/05/2020,3,5,2020,19,1,Sierra_Leone,SL,SLE,7813207,Africa,1.59985522\r
-02/05/2020,2,5,2020,12,0,Sierra_Leone,SL,SLE,7813207,Africa,1.40787259\r
-01/05/2020,1,5,2020,8,3,Sierra_Leone,SL,SLE,7813207,Africa,1.39507375\r
-30/04/2020,30,4,2020,12,0,Sierra_Leone,SL,SLE,7813207,Africa,1.3182807\r
-29/04/2020,29,4,2020,5,0,Sierra_Leone,SL,SLE,7813207,Africa,1.19029228\r
-28/04/2020,28,4,2020,6,0,Sierra_Leone,SL,SLE,7813207,Africa,1.12629807\r
-27/04/2020,27,4,2020,11,1,Sierra_Leone,SL,SLE,7813207,Africa,1.06230387\r
-26/04/2020,26,4,2020,0,0,Sierra_Leone,SL,SLE,7813207,Africa,0.92151661\r
-25/04/2020,25,4,2020,18,2,Sierra_Leone,SL,SLE,7813207,Africa,0.94711429\r
-24/04/2020,24,4,2020,3,1,Sierra_Leone,SL,SLE,7813207,Africa,0.72953398\r
-23/04/2020,23,4,2020,11,0,Sierra_Leone,SL,SLE,7813207,Africa,0.69113745\r
-22/04/2020,22,4,2020,7,0,Sierra_Leone,SL,SLE,7813207,Africa,0.56314904\r
-21/04/2020,21,4,2020,8,0,Sierra_Leone,SL,SLE,7813207,Africa,0.47355714\r
-20/04/2020,20,4,2020,5,0,Sierra_Leone,SL,SLE,7813207,Africa,0.37116641\r
-19/04/2020,19,4,2020,4,0,Sierra_Leone,SL,SLE,7813207,Africa,0.33276989\r
-18/04/2020,18,4,2020,11,0,Sierra_Leone,SL,SLE,7813207,Africa,0.3071722\r
-17/04/2020,17,4,2020,2,0,Sierra_Leone,SL,SLE,7813207,Africa,0.16638494\r
-16/04/2020,16,4,2020,2,0,Sierra_Leone,SL,SLE,7813207,Africa,0.1535861\r
-15/04/2020,15,4,2020,0,0,Sierra_Leone,SL,SLE,7813207,Africa,0.12798842\r
-14/04/2020,14,4,2020,1,0,Sierra_Leone,SL,SLE,7813207,Africa,0.14078726\r
-13/04/2020,13,4,2020,0,0,Sierra_Leone,SL,SLE,7813207,Africa,\r
-12/04/2020,12,4,2020,2,0,Sierra_Leone,SL,SLE,7813207,Africa,\r
-11/04/2020,11,4,2020,1,0,Sierra_Leone,SL,SLE,7813207,Africa,\r
-10/04/2020,10,4,2020,0,0,Sierra_Leone,SL,SLE,7813207,Africa,\r
-09/04/2020,9,4,2020,1,0,Sierra_Leone,SL,SLE,7813207,Africa,\r
-08/04/2020,8,4,2020,0,0,Sierra_Leone,SL,SLE,7813207,Africa,\r
-07/04/2020,7,4,2020,0,0,Sierra_Leone,SL,SLE,7813207,Africa,\r
-06/04/2020,6,4,2020,2,0,Sierra_Leone,SL,SLE,7813207,Africa,\r
-05/04/2020,5,4,2020,2,0,Sierra_Leone,SL,SLE,7813207,Africa,\r
-04/04/2020,4,4,2020,0,0,Sierra_Leone,SL,SLE,7813207,Africa,\r
-03/04/2020,3,4,2020,1,0,Sierra_Leone,SL,SLE,7813207,Africa,\r
-02/04/2020,2,4,2020,0,0,Sierra_Leone,SL,SLE,7813207,Africa,\r
-01/04/2020,1,4,2020,1,0,Sierra_Leone,SL,SLE,7813207,Africa,\r
-19/08/2020,19,8,2020,100,0,Singapore,SG,SGP,5804343,Asia,44.65621691\r
-18/08/2020,18,8,2020,91,0,Singapore,SG,SGP,5804343,Asia,48.01577026\r
-17/08/2020,17,8,2020,86,0,Singapore,SG,SGP,5804343,Asia,50.34161489\r
-16/08/2020,16,8,2020,81,0,Singapore,SG,SGP,5804343,Asia,54.25247957\r
-15/08/2020,15,8,2020,83,0,Singapore,SG,SGP,5804343,Asia,58.14611576\r
-14/08/2020,14,8,2020,102,0,Singapore,SG,SGP,5804343,Asia,63.53862961\r
-13/08/2020,13,8,2020,42,0,Singapore,SG,SGP,5804343,Asia,66.57084187\r
-12/08/2020,12,8,2020,61,0,Singapore,SG,SGP,5804343,Asia,71.60155766\r
-11/08/2020,11,8,2020,188,0,Singapore,SG,SGP,5804343,Asia,76.73564433\r
-10/08/2020,10,8,2020,175,0,Singapore,SG,SGP,5804343,Asia,81.57684685\r
-09/08/2020,9,8,2020,132,0,Singapore,SG,SGP,5804343,Asia,86.84876135\r
-08/08/2020,8,8,2020,242,0,Singapore,SG,SGP,5804343,Asia,93.41281175\r
-07/08/2020,7,8,2020,301,0,Singapore,SG,SGP,5804343,Asia,94.01580851\r
-06/08/2020,6,8,2020,908,0,Singapore,SG,SGP,5804343,Asia,94.92891788\r
-05/08/2020,5,8,2020,295,0,Singapore,SG,SGP,5804343,Asia,84.62628759\r
-04/08/2020,4,8,2020,226,0,Singapore,SG,SGP,5804343,Asia,86.41804938\r
-03/08/2020,3,8,2020,313,0,Singapore,SG,SGP,5804343,Asia,84.64351607\r
-02/08/2020,2,8,2020,307,0,Singapore,SG,SGP,5804343,Asia,83.67872126\r
-01/08/2020,1,8,2020,396,0,Singapore,SG,SGP,5804343,Asia,81.86973099\r
-31/07/2020,31,7,2020,278,0,Singapore,SG,SGP,5804343,Asia,80.68096596\r
-30/07/2020,30,7,2020,334,0,Singapore,SG,SGP,5804343,Asia,80.1641116\r
-29/07/2020,29,7,2020,359,0,Singapore,SG,SGP,5804343,Asia,78.6996909\r
-28/07/2020,28,7,2020,469,0,Singapore,SG,SGP,5804343,Asia,78.47572068\r
-27/07/2020,27,7,2020,481,0,Singapore,SG,SGP,5804343,Asia,75.9431343\r
-26/07/2020,26,7,2020,513,0,Singapore,SG,SGP,5804343,Asia,70.72290525\r
-25/07/2020,25,7,2020,277,0,Singapore,SG,SGP,5804343,Asia,64.81353704\r
-24/07/2020,24,7,2020,354,0,Singapore,SG,SGP,5804343,Asia,63.33188786\r
-23/07/2020,23,7,2020,310,0,Singapore,SG,SGP,5804343,Asia,59.36933775\r
-22/07/2020,22,7,2020,399,0,Singapore,SG,SGP,5804343,Asia,56.75060898\r
-21/07/2020,21,7,2020,123,0,Singapore,SG,SGP,5804343,Asia,52.58131713\r
-20/07/2020,20,7,2020,257,0,Singapore,SG,SGP,5804343,Asia,55.95809896\r
-19/07/2020,19,7,2020,202,0,Singapore,SG,SGP,5804343,Asia,51.53037992\r
-18/07/2020,18,7,2020,327,0,Singapore,SG,SGP,5804343,Asia,51.23749579\r
-17/07/2020,17,7,2020,248,0,Singapore,SG,SGP,5804343,Asia,48.51539614\r
-16/07/2020,16,7,2020,249,0,Singapore,SG,SGP,5804343,Asia,47.48168742\r
-15/07/2020,15,7,2020,346,1,Singapore,SG,SGP,5804343,Asia,46.89591914\r
-14/07/2020,14,7,2020,322,0,Singapore,SG,SGP,5804343,Asia,45.17307127\r
-13/07/2020,13,7,2020,178,0,Singapore,SG,SGP,5804343,Asia,43.10565382\r
-12/07/2020,12,7,2020,170,0,Singapore,SG,SGP,5804343,Asia,43.70865057\r
-11/07/2020,11,7,2020,191,0,Singapore,SG,SGP,5804343,Asia,45.7932965\r
-10/07/2020,10,7,2020,124,0,Singapore,SG,SGP,5804343,Asia,46.27569391\r
-09/07/2020,9,7,2020,158,0,Singapore,SG,SGP,5804343,Asia,46.08618064\r
-08/07/2020,8,7,2020,157,0,Singapore,SG,SGP,5804343,Asia,46.65472044\r
-07/07/2020,7,7,2020,319,0,Singapore,SG,SGP,5804343,Asia,46.00003825\r
-06/07/2020,6,7,2020,0,0,Singapore,SG,SGP,5804343,Asia,44.25996189\r
-05/07/2020,5,7,2020,185,0,Singapore,SG,SGP,5804343,Asia,48.77382333\r
-04/07/2020,4,7,2020,169,0,Singapore,SG,SGP,5804343,Asia,49.34236312\r
-03/07/2020,3,7,2020,188,0,Singapore,SG,SGP,5804343,Asia,48.8771942\r
-02/07/2020,2,7,2020,215,0,Singapore,SG,SGP,5804343,Asia,50.06595923\r
-01/07/2020,1,7,2020,246,0,Singapore,SG,SGP,5804343,Asia,50.61727055\r
-30/06/2020,30,6,2020,202,0,Singapore,SG,SGP,5804343,Asia,48.98056507\r
-29/06/2020,29,6,2020,213,0,Singapore,SG,SGP,5804343,Asia,49.18730681\r
-28/06/2020,28,6,2020,291,0,Singapore,SG,SGP,5804343,Asia,52.52963169\r
-27/06/2020,27,6,2020,219,0,Singapore,SG,SGP,5804343,Asia,53.4944265\r
-26/06/2020,26,6,2020,113,0,Singapore,SG,SGP,5804343,Asia,57.69817531\r
-25/06/2020,25,6,2020,191,0,Singapore,SG,SGP,5804343,Asia,63.02177525\r
-24/06/2020,24,6,2020,119,0,Singapore,SG,SGP,5804343,Asia,67.50117972\r
-23/06/2020,23,6,2020,218,0,Singapore,SG,SGP,5804343,Asia,69.20679912\r
-22/06/2020,22,6,2020,262,0,Singapore,SG,SGP,5804343,Asia,72.10118354\r
-21/06/2020,21,6,2020,218,0,Singapore,SG,SGP,5804343,Asia,74.18582947\r
-20/06/2020,20,6,2020,142,0,Singapore,SG,SGP,5804343,Asia,76.35661779\r
-19/06/2020,19,6,2020,257,0,Singapore,SG,SGP,5804343,Asia,78.40680677\r
-18/06/2020,18,6,2020,247,0,Singapore,SG,SGP,5804343,Asia,82.88621124\r
-17/06/2020,17,6,2020,151,0,Singapore,SG,SGP,5804343,Asia,88.43378139\r
-16/06/2020,16,6,2020,214,0,Singapore,SG,SGP,5804343,Asia,95.20457354\r
-15/06/2020,15,6,2020,407,0,Singapore,SG,SGP,5804343,Asia,98.54689842\r
-14/06/2020,14,6,2020,347,1,Singapore,SG,SGP,5804343,Asia,100.45925956\r
-13/06/2020,13,6,2020,463,0,Singapore,SG,SGP,5804343,Asia,103.19858768\r
-12/06/2020,12,6,2020,422,0,Singapore,SG,SGP,5804343,Asia,105.74840253\r
-11/06/2020,11,6,2020,451,0,Singapore,SG,SGP,5804343,Asia,104.90420707\r
-10/06/2020,10,6,2020,218,0,Singapore,SG,SGP,5804343,Asia,106.31694233\r
-09/06/2020,9,6,2020,386,0,Singapore,SG,SGP,5804343,Asia,109.15964132\r
-08/06/2020,8,6,2020,383,0,Singapore,SG,SGP,5804343,Asia,108.43604522\r
-07/06/2020,7,6,2020,344,1,Singapore,SG,SGP,5804343,Asia,111.27874421\r
-06/06/2020,6,6,2020,261,0,Singapore,SG,SGP,5804343,Asia,116.41283088\r
-05/06/2020,5,6,2020,517,0,Singapore,SG,SGP,5804343,Asia,122.49448387\r
-04/06/2020,4,6,2020,569,0,Singapore,SG,SGP,5804343,Asia,121.30571884\r
-03/06/2020,3,6,2020,544,0,Singapore,SG,SGP,5804343,Asia,121.32294732\r
-02/06/2020,2,6,2020,408,1,Singapore,SG,SGP,5804343,Asia,119.72069879\r
-01/06/2020,1,6,2020,518,0,Singapore,SG,SGP,5804343,Asia,117.94616548\r
-31/05/2020,31,5,2020,506,0,Singapore,SG,SGP,5804343,Asia,120.771636\r
-30/05/2020,30,5,2020,611,0,Singapore,SG,SGP,5804343,Asia,120.06526837\r
-29/05/2020,29,5,2020,373,0,Singapore,SG,SGP,5804343,Asia,123.2008515\r
-28/05/2020,28,5,2020,533,0,Singapore,SG,SGP,5804343,Asia,129.73044494\r
-27/05/2020,27,5,2020,383,0,Singapore,SG,SGP,5804343,Asia,132.17688893\r
-26/05/2020,26,5,2020,344,0,Singapore,SG,SGP,5804343,Asia,140.80835678\r
-25/05/2020,25,5,2020,548,0,Singapore,SG,SGP,5804343,Asia,142.651804\r
-24/05/2020,24,5,2020,642,0,Singapore,SG,SGP,5804343,Asia,148.30274503\r
-23/05/2020,23,5,2020,614,0,Singapore,SG,SGP,5804343,Asia,150.21510617\r
-22/05/2020,22,5,2020,448,1,Singapore,SG,SGP,5804343,Asia,152.8682919\r
-21/05/2020,21,5,2020,570,0,Singapore,SG,SGP,5804343,Asia,157.91623617\r
-20/05/2020,20,5,2020,451,0,Singapore,SG,SGP,5804343,Asia,161.67204454\r
-19/05/2020,19,5,2020,305,0,Singapore,SG,SGP,5804343,Asia,164.79039919\r
-18/05/2020,18,5,2020,682,0,Singapore,SG,SGP,5804343,Asia,169.40763149\r
-17/05/2020,17,5,2020,465,1,Singapore,SG,SGP,5804343,Asia,168.97691952\r
-16/05/2020,16,5,2020,793,0,Singapore,SG,SGP,5804343,Asia,168.66680691\r
-15/05/2020,15,5,2020,752,0,Singapore,SG,SGP,5804343,Asia,171.06156545\r
-14/05/2020,14,5,2020,675,0,Singapore,SG,SGP,5804343,Asia,167.20238621\r
-13/05/2020,13,5,2020,884,0,Singapore,SG,SGP,5804343,Asia,167.46081339\r
-12/05/2020,12,5,2020,451,1,Singapore,SG,SGP,5804343,Asia,161.32747496\r
-11/05/2020,11,5,2020,876,0,Singapore,SG,SGP,5804343,Asia,167.32298556\r
-10/05/2020,10,5,2020,753,0,Singapore,SG,SGP,5804343,Asia,168.2705519\r
-09/05/2020,9,5,2020,768,0,Singapore,SG,SGP,5804343,Asia,165.94470726\r
-08/05/2020,8,5,2020,741,0,Singapore,SG,SGP,5804343,Asia,168.16718102\r
-07/05/2020,7,5,2020,788,2,Singapore,SG,SGP,5804343,Asia,173.26681073\r
-06/05/2020,6,5,2020,632,0,Singapore,SG,SGP,5804343,Asia,177.19490388\r
-05/05/2020,5,5,2020,573,0,Singapore,SG,SGP,5804343,Asia,185.4473452\r
-04/05/2020,4,5,2020,657,1,Singapore,SG,SGP,5804343,Asia,200.14323757\r
-03/05/2020,3,5,2020,447,1,Singapore,SG,SGP,5804343,Asia,199.09230037\r
-02/05/2020,2,5,2020,932,1,Singapore,SG,SGP,5804343,Asia,207.62039735\r
-01/05/2020,1,5,2020,528,1,Singapore,SG,SGP,5804343,Asia,202.29679742\r
-30/04/2020,30,4,2020,690,0,Singapore,SG,SGP,5804343,Asia,205.74249316\r
-29/04/2020,29,4,2020,528,0,Singapore,SG,SGP,5804343,Asia,201.55597283\r
-28/04/2020,28,4,2020,799,2,Singapore,SG,SGP,5804343,Asia,198.21364795\r
-27/04/2020,27,4,2020,931,0,Singapore,SG,SGP,5804343,Asia,191.09828623\r
-26/04/2020,26,4,2020,618,0,Singapore,SG,SGP,5804343,Asia,179.07280807\r
-25/04/2020,25,4,2020,897,0,Singapore,SG,SGP,5804343,Asia,175.14471491\r
-24/04/2020,24,4,2020,1037,0,Singapore,SG,SGP,5804343,Asia,159.69076948\r
-23/04/2020,23,4,2020,1016,1,Singapore,SG,SGP,5804343,Asia,146.75218194\r
-22/04/2020,22,4,2020,1111,0,Singapore,SG,SGP,5804343,Asia,131.69449152\r
-21/04/2020,21,4,2020,1426,0,Singapore,SG,SGP,5804343,Asia,114.37987038\r
-20/04/2020,20,4,2020,596,0,Singapore,SG,SGP,5804343,Asia,90.94913929\r
-19/04/2020,19,4,2020,942,0,Singapore,SG,SGP,5804343,Asia,82.74838341\r
-18/04/2020,18,4,2020,623,1,Singapore,SG,SGP,5804343,Asia,67.81129234\r
-17/04/2020,17,4,2020,728,0,Singapore,SG,SGP,5804343,Asia,58.1978012\r
-16/04/2020,16,4,2020,447,0,Singapore,SG,SGP,5804343,Asia,46.49966413\r
-15/04/2020,15,4,2020,334,1,Singapore,SG,SGP,5804343,Asia,40.88318006\r
-14/04/2020,14,4,2020,386,1,Singapore,SG,SGP,5804343,Asia,35.73186492\r
-13/04/2020,13,4,2020,233,0,Singapore,SG,SGP,5804343,Asia,29.08167212\r
-12/04/2020,12,4,2020,390,2,Singapore,SG,SGP,5804343,Asia,25.7738042\r
-11/04/2020,11,4,2020,0,0,Singapore,SG,SGP,5804343,Asia,20.27791948\r
-10/04/2020,10,4,2020,286,0,Singapore,SG,SGP,5804343,Asia,22.65544955\r
-09/04/2020,9,4,2020,142,0,Singapore,SG,SGP,5804343,Asia,18.17604508\r
-08/04/2020,8,4,2020,106,0,Singapore,SG,SGP,5804343,Asia,15.90188588\r
-07/04/2020,7,4,2020,66,0,Singapore,SG,SGP,5804343,Asia,14.91986259\r
-06/04/2020,6,4,2020,120,0,Singapore,SG,SGP,5804343,Asia,14.71312085\r
-05/04/2020,5,4,2020,75,1,Singapore,SG,SGP,5804343,Asia,13.04195841\r
-04/04/2020,4,4,2020,65,0,Singapore,SG,SGP,5804343,Asia,12.559561\r
-03/04/2020,3,4,2020,49,1,Singapore,SG,SGP,5804343,Asia,12.12884904\r
-02/04/2020,2,4,2020,121,1,Singapore,SG,SGP,5804343,Asia,11.8359649\r
-01/04/2020,1,4,2020,35,0,Singapore,SG,SGP,5804343,Asia,10.56105747\r
-31/03/2020,31,3,2020,0,0,Singapore,SG,SGP,5804343,Asia,10.35431573\r
-30/03/2020,30,3,2020,41,0,Singapore,SG,SGP,5804343,Asia,10.64719986\r
-29/03/2020,29,3,2020,71,1,Singapore,SG,SGP,5804343,Asia,10.14757398\r
-28/03/2020,28,3,2020,138,0,Singapore,SG,SGP,5804343,Asia,9.16555069\r
-27/03/2020,27,3,2020,26,0,Singapore,SG,SGP,5804343,Asia,7.01199085\r
-26/03/2020,26,3,2020,10,0,Singapore,SG,SGP,5804343,Asia,6.71910671\r
-25/03/2020,25,3,2020,49,0,Singapore,SG,SGP,5804343,Asia,6.75356367\r
-24/03/2020,24,3,2020,54,0,Singapore,SG,SGP,5804343,Asia,6.01273908\r
-23/03/2020,23,3,2020,23,0,Singapore,SG,SGP,5804343,Asia,5.25468602\r
-22/03/2020,22,3,2020,47,2,Singapore,SG,SGP,5804343,Asia,5.06517275\r
-21/03/2020,21,3,2020,40,0,Singapore,SG,SGP,5804343,Asia,4.39326208\r
-20/03/2020,20,3,2020,32,0,Singapore,SG,SGP,5804343,Asia,3.92809315\r
-19/03/2020,19,3,2020,47,0,Singapore,SG,SGP,5804343,Asia,3.46292423\r
-18/03/2020,18,3,2020,23,0,Singapore,SG,SGP,5804343,Asia,2.68764268\r
-17/03/2020,17,3,2020,17,0,Singapore,SG,SGP,5804343,Asia,2.32584463\r
-16/03/2020,16,3,2020,12,0,Singapore,SG,SGP,5804343,Asia,2.06741745\r
-15/03/2020,15,3,2020,14,0,Singapore,SG,SGP,5804343,Asia,1.92958962\r
-14/03/2020,14,3,2020,13,0,Singapore,SG,SGP,5804343,Asia,1.75730483\r
-13/03/2020,13,3,2020,9,0,Singapore,SG,SGP,5804343,Asia,1.56779157\r
-12/03/2020,12,3,2020,12,0,Singapore,SG,SGP,5804343,Asia,1.46442069\r
-11/03/2020,11,3,2020,6,0,Singapore,SG,SGP,5804343,Asia,1.29213591\r
-10/03/2020,10,3,2020,10,0,Singapore,SG,SGP,5804343,Asia,1.20599351\r
-09/03/2020,9,3,2020,12,0,Singapore,SG,SGP,5804343,Asia,1.0509372\r
-08/03/2020,8,3,2020,8,0,Singapore,SG,SGP,5804343,Asia,0.84419546\r
-07/03/2020,7,3,2020,13,0,Singapore,SG,SGP,5804343,Asia,0.75805306\r
-06/03/2020,6,3,2020,5,0,Singapore,SG,SGP,5804343,Asia,0.55131132\r
-05/03/2020,5,3,2020,2,0,Singapore,SG,SGP,5804343,Asia,0.4823974\r
-04/03/2020,4,3,2020,2,0,Singapore,SG,SGP,5804343,Asia,0.49962588\r
-03/03/2020,3,3,2020,2,0,Singapore,SG,SGP,5804343,Asia,0.53408284\r
-02/03/2020,2,3,2020,4,0,Singapore,SG,SGP,5804343,Asia,0.53408284\r
-01/03/2020,1,3,2020,4,0,Singapore,SG,SGP,5804343,Asia,0.51685436\r
-29/02/2020,29,2,2020,2,0,Singapore,SG,SGP,5804343,Asia,0.53408284\r
-28/02/2020,28,2,2020,3,0,Singapore,SG,SGP,5804343,Asia,0.65468219\r
-27/02/2020,27,2,2020,2,0,Singapore,SG,SGP,5804343,Asia,0.74082459\r
-26/02/2020,26,2,2020,1,0,Singapore,SG,SGP,5804343,Asia,0.75805306\r
-25/02/2020,25,2,2020,1,0,Singapore,SG,SGP,5804343,Asia,0.77528154\r
-24/02/2020,24,2,2020,0,0,Singapore,SG,SGP,5804343,Asia,0.79251002\r
-23/02/2020,23,2,2020,3,0,Singapore,SG,SGP,5804343,Asia,0.84419546\r
-22/02/2020,22,2,2020,1,0,Singapore,SG,SGP,5804343,Asia,0.91310937\r
-21/02/2020,21,2,2020,1,0,Singapore,SG,SGP,5804343,Asia,0.94756633\r
-20/02/2020,20,2,2020,3,0,Singapore,SG,SGP,5804343,Asia,0.96479481\r
-19/02/2020,19,2,2020,4,0,Singapore,SG,SGP,5804343,Asia,0.98202329\r
-18/02/2020,18,2,2020,2,0,Singapore,SG,SGP,5804343,Asia,1.01648025\r
-17/02/2020,17,2,2020,3,0,Singapore,SG,SGP,5804343,Asia,0.98202329\r
-16/02/2020,16,2,2020,5,0,Singapore,SG,SGP,5804343,Asia,0.93033785\r
-15/02/2020,15,2,2020,9,0,Singapore,SG,SGP,5804343,Asia,0.87865242\r
-14/02/2020,14,2,2020,8,0,Singapore,SG,SGP,5804343,Asia,0.77528154\r
-13/02/2020,13,2,2020,3,0,Singapore,SG,SGP,5804343,Asia,0.68913915\r
-12/02/2020,12,2,2020,2,0,Singapore,SG,SGP,5804343,Asia,0.68913915\r
-11/02/2020,11,2,2020,2,0,Singapore,SG,SGP,5804343,Asia,0.68913915\r
-10/02/2020,10,2,2020,3,0,Singapore,SG,SGP,5804343,Asia,0.67191067\r
-09/02/2020,9,2,2020,7,0,Singapore,SG,SGP,5804343,Asia,0.62022523\r
-08/02/2020,8,2,2020,3,0,Singapore,SG,SGP,5804343,Asia,0.51685436\r
-07/02/2020,7,2,2020,2,0,Singapore,SG,SGP,5804343,Asia,0.46516893\r
-06/02/2020,6,2,2020,4,0,Singapore,SG,SGP,5804343,Asia,0.4823974\r
-05/02/2020,5,2,2020,6,0,Singapore,SG,SGP,5804343,Asia,0.41348349\r
-04/02/2020,4,2,2020,0,0,Singapore,SG,SGP,5804343,Asia,0.31011262\r
-03/02/2020,3,2,2020,0,0,Singapore,SG,SGP,5804343,Asia,0.31011262\r
-02/02/2020,2,2,2020,2,0,Singapore,SG,SGP,5804343,Asia,0.31011262\r
-01/02/2020,1,2,2020,3,0,Singapore,SG,SGP,5804343,Asia,0.27565566\r
-31/01/2020,31,1,2020,3,0,Singapore,SG,SGP,5804343,Asia,0.22397022\r
-30/01/2020,30,1,2020,3,0,Singapore,SG,SGP,5804343,Asia,0.17228479\r
-29/01/2020,29,1,2020,2,0,Singapore,SG,SGP,5804343,Asia,0.12059935\r
-28/01/2020,28,1,2020,1,0,Singapore,SG,SGP,5804343,Asia,0.08614239\r
-27/01/2020,27,1,2020,0,0,Singapore,SG,SGP,5804343,Asia,0.06891391\r
-26/01/2020,26,1,2020,1,0,Singapore,SG,SGP,5804343,Asia,0.06891391\r
-25/01/2020,25,1,2020,0,0,Singapore,SG,SGP,5804343,Asia,0.05168544\r
-24/01/2020,24,1,2020,3,0,Singapore,SG,SGP,5804343,Asia,0.05168544\r
-23/01/2020,23,1,2020,0,0,Singapore,SG,SGP,5804343,Asia,0\r
-22/01/2020,22,1,2020,0,0,Singapore,SG,SGP,5804343,Asia,0\r
-21/01/2020,21,1,2020,0,0,Singapore,SG,SGP,5804343,Asia,0\r
-20/01/2020,20,1,2020,0,0,Singapore,SG,SGP,5804343,Asia,0\r
-19/01/2020,19,1,2020,0,0,Singapore,SG,SGP,5804343,Asia,0\r
-18/01/2020,18,1,2020,0,0,Singapore,SG,SGP,5804343,Asia,0\r
-17/01/2020,17,1,2020,0,0,Singapore,SG,SGP,5804343,Asia,0\r
-16/01/2020,16,1,2020,0,0,Singapore,SG,SGP,5804343,Asia,0\r
-15/01/2020,15,1,2020,0,0,Singapore,SG,SGP,5804343,Asia,0\r
-14/01/2020,14,1,2020,0,0,Singapore,SG,SGP,5804343,Asia,0\r
-13/01/2020,13,1,2020,0,0,Singapore,SG,SGP,5804343,Asia,0\r
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-17/08/2020,17,8,2020,17,0,Sint_Maarten,SX,SXM,42389,America,403.40654415\r
-16/08/2020,16,8,2020,31,0,Sint_Maarten,SX,SXM,42389,America,405.76564675\r
-15/08/2020,15,8,2020,6,0,Sint_Maarten,SX,SXM,42389,America,332.63346623\r
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-12/08/2020,12,8,2020,30,0,Sint_Maarten,SX,SXM,42389,America,231.19205454\r
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-26/04/2020,26,4,2020,62,2,Somalia,SO,SOM,15442906,Africa,2.38944665\r
-25/04/2020,25,4,2020,0,2,Somalia,SO,SOM,15442906,Africa,1.98796781\r
-24/04/2020,24,4,2020,42,0,Somalia,SO,SOM,15442906,Africa,2.046247\r
-23/04/2020,23,4,2020,0,6,Somalia,SO,SOM,15442906,Africa,1.80017932\r
-22/04/2020,22,4,2020,49,0,Somalia,SO,SOM,15442906,Africa,1.80017932\r
-21/04/2020,21,4,2020,73,1,Somalia,SO,SOM,15442906,Africa,1.48935699\r
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-19/04/2020,19,4,2020,19,2,Somalia,SO,SOM,15442906,Africa,0.82885954\r
-18/04/2020,18,4,2020,36,0,Somalia,SO,SOM,15442906,Africa,0.71877663\r
-17/04/2020,17,4,2020,0,0,Somalia,SO,SOM,15442906,Africa,0.48565989\r
-16/04/2020,16,4,2020,20,3,Somalia,SO,SOM,15442906,Africa,0.48565989\r
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-13/04/2020,13,4,2020,4,1,Somalia,SO,SOM,15442906,Africa,0.14246023\r
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-27/03/2020,27,3,2020,1,0,Somalia,SO,SOM,15442906,Africa,\r
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-24/03/2020,24,3,2020,0,0,Somalia,SO,SOM,15442906,Africa,\r
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-18/08/2020,18,8,2020,2541,143,South_Africa,ZA,ZAF,58558267,Africa,124.70314396\r
-17/08/2020,17,8,2020,3692,162,South_Africa,ZA,ZAF,58558267,Africa,129.54618346\r
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-14/08/2020,14,8,2020,3946,260,South_Africa,ZA,ZAF,58558267,Africa,154.88163268\r
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-12/08/2020,12,8,2020,2511,130,South_Africa,ZA,ZAF,58558267,Africa,181.61056576\r
-11/08/2020,11,8,2020,3740,213,South_Africa,ZA,ZAF,58558267,Africa,189.67262129\r
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-31/07/2020,31,7,2020,11046,315,South_Africa,ZA,ZAF,58558267,Africa,269.72792757\r
-30/07/2020,30,7,2020,11362,240,South_Africa,ZA,ZAF,58558267,Africa,273.35849949\r
-29/07/2020,29,7,2020,7232,190,South_Africa,ZA,ZAF,58558267,Africa,275.74074212\r
-28/07/2020,28,7,2020,7096,298,South_Africa,ZA,ZAF,58558267,Africa,281.31467757\r
-27/07/2020,27,7,2020,11233,114,South_Africa,ZA,ZAF,58558267,Africa,288.92760778\r
-26/07/2020,26,7,2020,12204,312,South_Africa,ZA,ZAF,58558267,Africa,290.33646095\r
-25/07/2020,25,7,2020,13944,250,South_Africa,ZA,ZAF,58558267,Africa,292.5445181\r
-24/07/2020,24,7,2020,13104,153,South_Africa,ZA,ZAF,58558267,Africa,289.8190276\r
-23/07/2020,23,7,2020,13150,572,South_Africa,ZA,ZAF,58558267,Africa,290.79241706\r
-22/07/2020,22,7,2020,8170,195,South_Africa,ZA,ZAF,58558267,Africa,283.38099555\r
-21/07/2020,21,7,2020,9300,140,South_Africa,ZA,ZAF,58558267,Africa,286.73491994\r
-20/07/2020,20,7,2020,13449,85,South_Africa,ZA,ZAF,58558267,Africa,286.17308637\r
-19/07/2020,19,7,2020,13285,144,South_Africa,ZA,ZAF,58558267,Africa,278.18787738\r
-18/07/2020,18,7,2020,13373,135,South_Africa,ZA,ZAF,58558267,Africa,274.03474901\r
-17/07/2020,17,7,2020,13172,216,South_Africa,ZA,ZAF,58558267,Africa,266.67455852\r
-16/07/2020,16,7,2020,12757,107,South_Africa,ZA,ZAF,58558267,Africa,259.08553612\r
-15/07/2020,15,7,2020,10496,174,South_Africa,ZA,ZAF,58558267,Africa,251.17375827\r
-14/07/2020,14,7,2020,11554,93,South_Africa,ZA,ZAF,58558267,Africa,245.10971269\r
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-30/06/2020,30,6,2020,6130,73,South_Africa,ZA,ZAF,58558267,Africa,120.78738601\r
-29/06/2020,29,6,2020,6334,43,South_Africa,ZA,ZAF,58558267,Africa,116.28759437\r
-28/06/2020,28,6,2020,7210,73,South_Africa,ZA,ZAF,58558267,Africa,112.81754633\r
-27/06/2020,27,6,2020,6215,48,South_Africa,ZA,ZAF,58558267,Africa,107.00965587\r
-26/06/2020,26,6,2020,6579,87,South_Africa,ZA,ZAF,58558267,Africa,102.13246236\r
-25/06/2020,25,6,2020,5688,103,South_Africa,ZA,ZAF,58558267,Africa,96.27163318\r
-24/06/2020,24,6,2020,4518,111,South_Africa,ZA,ZAF,58558267,Africa,90.70794394\r
-23/06/2020,23,6,2020,4288,61,South_Africa,ZA,ZAF,58558267,Africa,86.59921579\r
-22/06/2020,22,6,2020,4621,53,South_Africa,ZA,ZAF,58558267,Africa,83.70637061\r
-21/06/2020,21,6,2020,4966,46,South_Africa,ZA,ZAF,58558267,Africa,79.76328944\r
-20/06/2020,20,6,2020,3825,94,South_Africa,ZA,ZAF,58558267,Africa,75.61869958\r
-19/06/2020,19,6,2020,3478,63,South_Africa,ZA,ZAF,58558267,Africa,73.59848952\r
-18/06/2020,18,6,2020,4078,49,South_Africa,ZA,ZAF,58558267,Africa,73.23816465\r
-17/06/2020,17,6,2020,2801,57,South_Africa,ZA,ZAF,58558267,Africa,69.19945223\r
-16/06/2020,16,6,2020,3495,88,South_Africa,ZA,ZAF,58558267,Africa,66.90088694\r
-15/06/2020,15,6,2020,4302,57,South_Africa,ZA,ZAF,58558267,Africa,63.79116377\r
-14/06/2020,14,6,2020,3809,69,South_Africa,ZA,ZAF,58558267,Africa,59.37504947\r
-13/06/2020,13,6,2020,3359,65,South_Africa,ZA,ZAF,58558267,Africa,55.81961638\r
-12/06/2020,12,6,2020,3147,79,South_Africa,ZA,ZAF,58558267,Africa,53.22049575\r
-11/06/2020,11,6,2020,2430,48,South_Africa,ZA,ZAF,58558267,Africa,50.34985069\r
-10/06/2020,10,6,2020,2112,82,South_Africa,ZA,ZAF,58558267,Africa,49.05712117\r
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-01/06/2020,1,6,2020,1716,40,South_Africa,ZA,ZAF,58558267,Africa,29.31780751\r
-31/05/2020,31,5,2020,1727,32,South_Africa,ZA,ZAF,58558267,Africa,28.36832586\r
-30/05/2020,30,5,2020,1837,34,South_Africa,ZA,ZAF,58558267,Africa,26.83822593\r
-29/05/2020,29,5,2020,1466,25,South_Africa,ZA,ZAF,58558267,Africa,25.04172468\r
-28/05/2020,28,5,2020,1673,28,South_Africa,ZA,ZAF,58558267,Africa,23.67385633\r
-27/05/2020,27,5,2020,649,43,South_Africa,ZA,ZAF,58558267,Africa,22.05324826\r
-26/05/2020,26,5,2020,1032,52,South_Africa,ZA,ZAF,58558267,Africa,22.1369256\r
-25/05/2020,25,5,2020,1240,22,South_Africa,ZA,ZAF,58558267,Africa,21.46238378\r
-24/05/2020,24,5,2020,1218,10,South_Africa,ZA,ZAF,58558267,Africa,20.36091676\r
-23/05/2020,23,5,2020,988,28,South_Africa,ZA,ZAF,58558267,Africa,19.1774801\r
-22/05/2020,22,5,2020,1134,30,South_Africa,ZA,ZAF,58558267,Africa,18.62247734\r
-21/05/2020,21,5,2020,803,27,South_Africa,ZA,ZAF,58558267,Africa,17.41000976\r
-20/05/2020,20,5,2020,767,26,South_Africa,ZA,ZAF,58558267,Africa,16.4417434\r
-19/05/2020,19,5,2020,918,22,South_Africa,ZA,ZAF,58558267,Africa,15.73304756\r
-18/05/2020,18,5,2020,1160,3,South_Africa,ZA,ZAF,58558267,Africa,14.91164347\r
-17/05/2020,17,5,2020,831,14,South_Africa,ZA,ZAF,58558267,Africa,13.6940528\r
-16/05/2020,16,5,2020,785,9,South_Africa,ZA,ZAF,58558267,Africa,12.93241824\r
-15/05/2020,15,5,2020,665,19,South_Africa,ZA,ZAF,58558267,Africa,12.11101415\r
-14/05/2020,14,5,2020,724,13,South_Africa,ZA,ZAF,58558267,Africa,11.48258025\r
-13/05/2020,13,5,2020,698,0,South_Africa,ZA,ZAF,58558267,Africa,10.85073095\r
-12/05/2020,12,5,2020,637,12,South_Africa,ZA,ZAF,58558267,Africa,10.00541905\r
-11/05/2020,11,5,2020,595,8,South_Africa,ZA,ZAF,58558267,Africa,9.33941573\r
-10/05/2020,10,5,2020,525,8,South_Africa,ZA,ZAF,58558267,Africa,8.6392584\r
-09/05/2020,9,5,2020,663,17,South_Africa,ZA,ZAF,58558267,Africa,7.98350129\r
-08/05/2020,8,5,2020,424,8,South_Africa,ZA,ZAF,58558267,Africa,7.30725177\r
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-02/05/2020,2,5,2020,304,13,South_Africa,ZA,ZAF,58558267,Africa,5.40999617\r
-01/05/2020,1,5,2020,297,0,South_Africa,ZA,ZAF,58558267,Africa,5.19482586\r
-30/04/2020,30,4,2020,354,10,South_Africa,ZA,ZAF,58558267,Africa,4.8567011\r
-29/04/2020,29,4,2020,203,3,South_Africa,ZA,ZAF,58558267,Africa,4.40757579\r
-28/04/2020,28,4,2020,247,3,South_Africa,ZA,ZAF,58558267,Africa,4.30511374\r
-27/04/2020,27,4,2020,185,1,South_Africa,ZA,ZAF,58558267,Africa,4.05237402\r
-26/04/2020,26,4,2020,141,7,South_Africa,ZA,ZAF,58558267,Africa,3.98406599\r
-25/04/2020,25,4,2020,267,4,South_Africa,ZA,ZAF,58558267,Africa,3.7859727\r
-24/04/2020,24,4,2020,318,10,South_Africa,ZA,ZAF,58558267,Africa,3.44784794\r
-23/04/2020,23,4,2020,170,7,South_Africa,ZA,ZAF,58558267,Africa,3.05678445\r
-22/04/2020,22,4,2020,165,0,South_Africa,ZA,ZAF,58558267,Africa,2.93041459\r
-21/04/2020,21,4,2020,142,4,South_Africa,ZA,ZAF,58558267,Africa,2.75622911\r
-20/04/2020,20,4,2020,124,2,South_Africa,ZA,ZAF,58558267,Africa,2.56667432\r
-19/04/2020,19,4,2020,251,2,South_Africa,ZA,ZAF,58558267,Africa,2.47445847\r
-18/04/2020,18,4,2020,178,2,South_Africa,ZA,ZAF,58558267,Africa,2.18244164\r
-17/04/2020,17,4,2020,99,14,South_Africa,ZA,ZAF,58558267,Africa,1.95190203\r
-16/04/2020,16,4,2020,91,7,South_Africa,ZA,ZAF,58558267,Africa,1.92287111\r
-15/04/2020,15,4,2020,143,0,South_Africa,ZA,ZAF,58558267,Africa,1.81357826\r
-14/04/2020,14,4,2020,99,2,South_Africa,ZA,ZAF,58558267,Africa,1.61548497\r
-13/04/2020,13,4,2020,145,0,South_Africa,ZA,ZAF,58558267,Africa,1.52497682\r
-12/04/2020,12,4,2020,25,1,South_Africa,ZA,ZAF,58558267,Africa,1.43617638\r
-11/04/2020,11,4,2020,69,6,South_Africa,ZA,ZAF,58558267,Africa,1.42251477\r
-10/04/2020,10,4,2020,89,0,South_Africa,ZA,ZAF,58558267,Africa,1.71965472\r
-09/04/2020,9,4,2020,96,5,South_Africa,ZA,ZAF,58558267,Africa,1.93994812\r
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-01/04/2020,1,4,2020,27,2,South_Africa,ZA,ZAF,58558267,Africa,2.16536463\r
-31/03/2020,31,3,2020,46,1,South_Africa,ZA,ZAF,58558267,Africa,2.15853382\r
-30/03/2020,30,3,2020,93,0,South_Africa,ZA,ZAF,58558267,Africa,2.0987643\r
-29/03/2020,29,3,2020,17,0,South_Africa,ZA,ZAF,58558267,Africa,1.98605604\r
-28/03/2020,28,3,2020,243,0,South_Africa,ZA,ZAF,58558267,Africa,1.95702513\r
-27/03/2020,27,3,2020,218,2,South_Africa,ZA,ZAF,58558267,Africa,1.55400774\r
-26/03/2020,26,3,2020,152,0,South_Africa,ZA,ZAF,58558267,Africa,1.18855976\r
-25/03/2020,25,3,2020,155,0,South_Africa,ZA,ZAF,58558267,Africa,0.93923545\r
-24/03/2020,24,3,2020,128,0,South_Africa,ZA,ZAF,58558267,Africa,0.68137262\r
-23/03/2020,23,3,2020,34,0,South_Africa,ZA,ZAF,58558267,Africa,0.46449462\r
-22/03/2020,22,3,2020,35,0,South_Africa,ZA,ZAF,58558267,Africa,0.40814049\r
-21/03/2020,21,3,2020,55,0,South_Africa,ZA,ZAF,58558267,Africa,0.35007867\r
-20/03/2020,20,3,2020,34,0,South_Africa,ZA,ZAF,58558267,Africa,\r
-19/03/2020,19,3,2020,31,0,South_Africa,ZA,ZAF,58558267,Africa,\r
-18/03/2020,18,3,2020,23,0,South_Africa,ZA,ZAF,58558267,Africa,\r
-17/03/2020,17,3,2020,11,0,South_Africa,ZA,ZAF,58558267,Africa,\r
-16/03/2020,16,3,2020,27,0,South_Africa,ZA,ZAF,58558267,Africa,\r
-15/03/2020,15,3,2020,0,0,South_Africa,ZA,ZAF,58558267,Africa,\r
-14/03/2020,14,3,2020,7,0,South_Africa,ZA,ZAF,58558267,Africa,\r
-13/03/2020,13,3,2020,4,0,South_Africa,ZA,ZAF,58558267,Africa,\r
-12/03/2020,12,3,2020,6,0,South_Africa,ZA,ZAF,58558267,Africa,\r
-10/03/2020,10,3,2020,4,0,South_Africa,ZA,ZAF,58558267,Africa,\r
-09/03/2020,9,3,2020,1,0,South_Africa,ZA,ZAF,58558267,Africa,\r
-08/03/2020,8,3,2020,1,0,South_Africa,ZA,ZAF,58558267,Africa,\r
-06/03/2020,6,3,2020,1,0,South_Africa,ZA,ZAF,58558267,Africa,\r
-19/08/2020,19,8,2020,297,0,South_Korea,KR,KOR,51225321,Asia,3.12735961\r
-18/08/2020,18,8,2020,246,1,South_Korea,KR,KOR,51225321,Asia,2.61198949\r
-17/08/2020,17,8,2020,197,0,South_Korea,KR,KOR,51225321,Asia,2.19813166\r
-16/08/2020,16,8,2020,279,0,South_Korea,KR,KOR,51225321,Asia,1.91702069\r
-15/08/2020,15,8,2020,166,0,South_Korea,KR,KOR,51225321,Asia,1.37236817\r
-14/08/2020,14,8,2020,103,0,South_Korea,KR,KOR,51225321,Asia,1.10882663\r
-13/08/2020,13,8,2020,56,0,South_Korea,KR,KOR,51225321,Asia,0.97803194\r
-12/08/2020,12,8,2020,54,0,South_Korea,KR,KOR,51225321,Asia,0.90384988\r
-11/08/2020,11,8,2020,34,0,South_Korea,KR,KOR,51225321,Asia,0.89213692\r
-10/08/2020,10,8,2020,28,0,South_Korea,KR,KOR,51225321,Asia,0.88042396\r
-09/08/2020,9,8,2020,36,1,South_Korea,KR,KOR,51225321,Asia,0.87456748\r
-08/08/2020,8,8,2020,43,1,South_Korea,KR,KOR,51225321,Asia,0.91751499\r
-07/08/2020,7,8,2020,20,1,South_Korea,KR,KOR,51225321,Asia,1.05416616\r
-06/08/2020,6,8,2020,43,0,South_Korea,KR,KOR,51225321,Asia,1.09516151\r
-05/08/2020,5,8,2020,33,1,South_Korea,KR,KOR,51225321,Asia,1.12639606\r
-04/08/2020,4,8,2020,34,0,South_Korea,KR,KOR,51225321,Asia,1.18496085\r
-03/08/2020,3,8,2020,53,0,South_Korea,KR,KOR,51225321,Asia,1.20643461\r
-02/08/2020,2,8,2020,0,0,South_Korea,KR,KOR,51225321,Asia,1.1537263\r
-01/08/2020,1,8,2020,31,0,South_Korea,KR,KOR,51225321,Asia,1.22009972\r
-31/07/2020,31,7,2020,36,1,South_Korea,KR,KOR,51225321,Asia,1.235717\r
-30/07/2020,30,7,2020,18,0,South_Korea,KR,KOR,51225321,Asia,1.28256883\r
-29/07/2020,29,7,2020,48,0,South_Korea,KR,KOR,51225321,Asia,1.36651169\r
-28/07/2020,28,7,2020,28,1,South_Korea,KR,KOR,51225321,Asia,1.34894225\r
-27/07/2020,27,7,2020,25,1,South_Korea,KR,KOR,51225321,Asia,1.35870305\r
-26/07/2020,26,7,2020,58,0,South_Korea,KR,KOR,51225321,Asia,1.43093296\r
-25/07/2020,25,7,2020,113,0,South_Korea,KR,KOR,51225321,Asia,1.40360272\r
-24/07/2020,24,7,2020,41,1,South_Korea,KR,KOR,51225321,Asia,1.25133428\r
-23/07/2020,23,7,2020,59,0,South_Korea,KR,KOR,51225321,Asia,1.25914291\r
-22/07/2020,22,7,2020,63,1,South_Korea,KR,KOR,51225321,Asia,1.23962132\r
-21/07/2020,21,7,2020,45,0,South_Korea,KR,KOR,51225321,Asia,1.23962132\r
-20/07/2020,20,7,2020,26,1,South_Korea,KR,KOR,51225321,Asia,1.3274685\r
-19/07/2020,19,7,2020,34,1,South_Korea,KR,KOR,51225321,Asia,1.27671235\r
-18/07/2020,18,7,2020,39,1,South_Korea,KR,KOR,51225321,Asia,1.32942066\r
-17/07/2020,17,7,2020,60,2,South_Korea,KR,KOR,51225321,Asia,1.37627249\r
-16/07/2020,16,7,2020,61,2,South_Korea,KR,KOR,51225321,Asia,1.38212897\r
-15/07/2020,15,7,2020,39,0,South_Korea,KR,KOR,51225321,Asia,1.36846385\r
-14/07/2020,14,7,2020,33,0,South_Korea,KR,KOR,51225321,Asia,1.38993761\r
-13/07/2020,13,7,2020,62,0,South_Korea,KR,KOR,51225321,Asia,1.4094592\r
-12/07/2020,12,7,2020,44,1,South_Korea,KR,KOR,51225321,Asia,1.37041601\r
-11/07/2020,11,7,2020,35,0,South_Korea,KR,KOR,51225321,Asia,1.40555488\r
-10/07/2020,10,7,2020,45,1,South_Korea,KR,KOR,51225321,Asia,1.43678943\r
-09/07/2020,9,7,2020,49,2,South_Korea,KR,KOR,51225321,Asia,1.42507648\r
-08/07/2020,8,7,2020,63,0,South_Korea,KR,KOR,51225321,Asia,1.38408113\r
-07/07/2020,7,7,2020,90,2,South_Korea,KR,KOR,51225321,Asia,1.36065521\r
-06/07/2020,6,7,2020,0,0,South_Korea,KR,KOR,51225321,Asia,1.27476019\r
-05/07/2020,5,7,2020,61,0,South_Korea,KR,KOR,51225321,Asia,1.3079469\r
-04/07/2020,4,7,2020,63,1,South_Korea,KR,KOR,51225321,Asia,1.28256883\r
-03/07/2020,3,7,2020,63,0,South_Korea,KR,KOR,51225321,Asia,1.29037747\r
-02/07/2020,2,7,2020,54,0,South_Korea,KR,KOR,51225321,Asia,1.26304723\r
-01/07/2020,1,7,2020,50,0,South_Korea,KR,KOR,51225321,Asia,1.27280803\r
-30/06/2020,30,6,2020,43,0,South_Korea,KR,KOR,51225321,Asia,1.25914291\r
-29/06/2020,29,6,2020,42,0,South_Korea,KR,KOR,51225321,Asia,1.24157348\r
-28/06/2020,28,6,2020,62,0,South_Korea,KR,KOR,51225321,Asia,1.23181268\r
-27/06/2020,27,6,2020,51,0,South_Korea,KR,KOR,51225321,Asia,1.17520005\r
-26/06/2020,26,6,2020,39,0,South_Korea,KR,KOR,51225321,Asia,1.16934358\r
-25/06/2020,25,6,2020,28,1,South_Korea,KR,KOR,51225321,Asia,1.20253029\r
-24/06/2020,24,6,2020,51,0,South_Korea,KR,KOR,51225321,Asia,1.235717\r
-23/06/2020,23,6,2020,46,1,South_Korea,KR,KOR,51225321,Asia,1.23376484\r
-22/06/2020,22,6,2020,17,0,South_Korea,KR,KOR,51225321,Asia,1.21814756\r
-21/06/2020,21,6,2020,48,0,South_Korea,KR,KOR,51225321,Asia,1.25914291\r
-20/06/2020,20,6,2020,67,0,South_Korea,KR,KOR,51225321,Asia,1.27671235\r
-19/06/2020,19,6,2020,49,0,South_Korea,KR,KOR,51225321,Asia,1.2454778\r
-18/06/2020,18,6,2020,59,1,South_Korea,KR,KOR,51225321,Asia,1.2259562\r
-17/06/2020,17,6,2020,43,1,South_Korea,KR,KOR,51225321,Asia,1.18691301\r
-16/06/2020,16,6,2020,34,1,South_Korea,KR,KOR,51225321,Asia,1.19862597\r
-15/06/2020,15,6,2020,37,0,South_Korea,KR,KOR,51225321,Asia,1.20643461\r
-14/06/2020,14,6,2020,33,0,South_Korea,KR,KOR,51225321,Asia,1.20253029\r
-13/06/2020,13,6,2020,48,0,South_Korea,KR,KOR,51225321,Asia,1.19081733\r
-12/06/2020,12,6,2020,56,1,South_Korea,KR,KOR,51225321,Asia,1.17324789\r
-11/06/2020,11,6,2020,45,0,South_Korea,KR,KOR,51225321,Asia,1.17715221\r
-10/06/2020,10,6,2020,50,2,South_Korea,KR,KOR,51225321,Asia,1.24352564\r
-09/06/2020,9,6,2020,38,1,South_Korea,KR,KOR,51225321,Asia,1.22400404\r
-08/06/2020,8,6,2020,38,0,South_Korea,KR,KOR,51225321,Asia,1.18691301\r
-07/06/2020,7,6,2020,57,0,South_Korea,KR,KOR,51225321,Asia,1.1439655\r
-06/06/2020,6,6,2020,51,0,South_Korea,KR,KOR,51225321,Asia,1.0814964\r
-05/06/2020,5,6,2020,39,0,South_Korea,KR,KOR,51225321,Asia,1.02683593\r
-04/06/2020,4,6,2020,39,0,South_Korea,KR,KOR,51225321,Asia,0.9897449\r
-03/06/2020,3,6,2020,49,1,South_Korea,KR,KOR,51225321,Asia,0.93703659\r
-02/06/2020,2,6,2020,38,1,South_Korea,KR,KOR,51225321,Asia,0.90384988\r
-01/06/2020,1,6,2020,35,1,South_Korea,KR,KOR,51225321,Asia,0.85504589\r
-31/05/2020,31,5,2020,27,1,South_Korea,KR,KOR,51225321,Asia,0.8160027\r
-30/05/2020,30,5,2020,39,0,South_Korea,KR,KOR,51225321,Asia,0.78867246\r
-29/05/2020,29,5,2020,58,0,South_Korea,KR,KOR,51225321,Asia,0.74962927\r
-28/05/2020,28,5,2020,79,0,South_Korea,KR,KOR,51225321,Asia,0.68911232\r
-27/05/2020,27,5,2020,40,0,South_Korea,KR,KOR,51225321,Asia,0.59150435\r
-26/05/2020,26,5,2020,19,2,South_Korea,KR,KOR,51225321,Asia,0.56417411\r
-25/05/2020,25,5,2020,16,1,South_Korea,KR,KOR,51225321,Asia,0.57979139\r
-24/05/2020,24,5,2020,25,0,South_Korea,KR,KOR,51225321,Asia,0.61688242\r
-23/05/2020,23,5,2020,23,2,South_Korea,KR,KOR,51225321,Asia,0.63445186\r
-22/05/2020,22,5,2020,20,0,South_Korea,KR,KOR,51225321,Asia,0.62469106\r
-21/05/2020,21,5,2020,12,1,South_Korea,KR,KOR,51225321,Asia,0.60907378\r
-20/05/2020,20,5,2020,32,0,South_Korea,KR,KOR,51225321,Asia,0.59345651\r
-19/05/2020,19,5,2020,13,0,South_Korea,KR,KOR,51225321,Asia,0.53489172\r
-18/05/2020,18,5,2020,15,1,South_Korea,KR,KOR,51225321,Asia,0.51537012\r
-17/05/2020,17,5,2020,13,0,South_Korea,KR,KOR,51225321,Asia,0.50170501\r
-16/05/2020,16,5,2020,19,2,South_Korea,KR,KOR,51225321,Asia,0.50170501\r
-15/05/2020,15,5,2020,27,0,South_Korea,KR,KOR,51225321,Asia,0.47632693\r
-14/05/2020,14,5,2020,29,1,South_Korea,KR,KOR,51225321,Asia,0.44118806\r
-13/05/2020,13,5,2020,26,1,South_Korea,KR,KOR,51225321,Asia,0.39238407\r
-12/05/2020,12,5,2020,27,2,South_Korea,KR,KOR,51225321,Asia,0.35919736\r
-11/05/2020,11,5,2020,35,0,South_Korea,KR,KOR,51225321,Asia,0.33381928\r
-10/05/2020,10,5,2020,34,0,South_Korea,KR,KOR,51225321,Asia,0.2850153\r
-09/05/2020,9,5,2020,18,0,South_Korea,KR,KOR,51225321,Asia,0.23816347\r
-08/05/2020,8,5,2020,12,0,South_Korea,KR,KOR,51225321,Asia,0.22254619\r
-07/05/2020,7,5,2020,4,1,South_Korea,KR,KOR,51225321,Asia,0.21083323\r
-06/05/2020,6,5,2020,2,1,South_Korea,KR,KOR,51225321,Asia,0.21864187\r
-05/05/2020,5,5,2020,3,2,South_Korea,KR,KOR,51225321,Asia,0.23621131\r
-04/05/2020,4,5,2020,8,2,South_Korea,KR,KOR,51225321,Asia,0.24792426\r
-03/05/2020,3,5,2020,13,0,South_Korea,KR,KOR,51225321,Asia,0.25768506\r
-02/05/2020,2,5,2020,6,2,South_Korea,KR,KOR,51225321,Asia,0.24792426\r
-01/05/2020,1,5,2020,9,1,South_Korea,KR,KOR,51225321,Asia,0.27135018\r
-30/04/2020,30,4,2020,4,1,South_Korea,KR,KOR,51225321,Asia,0.29672825\r
-29/04/2020,29,4,2020,9,2,South_Korea,KR,KOR,51225321,Asia,0.33186712\r
-28/04/2020,28,4,2020,14,1,South_Korea,KR,KOR,51225321,Asia,0.367006\r
-27/04/2020,27,4,2020,10,1,South_Korea,KR,KOR,51225321,Asia,0.39238407\r
-26/04/2020,26,4,2020,10,2,South_Korea,KR,KOR,51225321,Asia,0.42166646\r
-25/04/2020,25,4,2020,10,0,South_Korea,KR,KOR,51225321,Asia,0.52317876\r
-24/04/2020,24,4,2020,6,0,South_Korea,KR,KOR,51225321,Asia,0.50365717\r
-23/04/2020,23,4,2020,8,2,South_Korea,KR,KOR,51225321,Asia,0.54465252\r
-22/04/2020,22,4,2020,11,1,South_Korea,KR,KOR,51225321,Asia,0.60516946\r
-21/04/2020,21,4,2020,9,1,South_Korea,KR,KOR,51225321,Asia,0.68716016\r
-20/04/2020,20,4,2020,13,2,South_Korea,KR,KOR,51225321,Asia,0.76134223\r
-19/04/2020,19,4,2020,8,2,South_Korea,KR,KOR,51225321,Asia,0.82771565\r
-18/04/2020,18,4,2020,18,2,South_Korea,KR,KOR,51225321,Asia,0.9702233\r
-17/04/2020,17,4,2020,22,1,South_Korea,KR,KOR,51225321,Asia,1.11858743\r
-16/04/2020,16,4,2020,22,4,South_Korea,KR,KOR,51225321,Asia,1.24352564\r
-15/04/2020,15,4,2020,27,3,South_Korea,KR,KOR,51225321,Asia,1.57148844\r
-14/04/2020,14,4,2020,27,5,South_Korea,KR,KOR,51225321,Asia,1.51878014\r
-13/04/2020,13,4,2020,25,3,South_Korea,KR,KOR,51225321,Asia,1.71009177\r
-12/04/2020,12,4,2020,62,6,South_Korea,KR,KOR,51225321,Asia,1.81355623\r
-11/04/2020,11,4,2020,0,0,South_Korea,KR,KOR,51225321,Asia,1.89749909\r
-10/04/2020,10,4,2020,27,4,South_Korea,KR,KOR,51225321,Asia,2.18251439\r
-09/04/2020,9,4,2020,39,4,South_Korea,KR,KOR,51225321,Asia,2.3074526\r
-08/04/2020,8,4,2020,53,8,South_Korea,KR,KOR,51225321,Asia,2.43434297\r
-07/04/2020,7,4,2020,47,6,South_Korea,KR,KOR,51225321,Asia,2.52609447\r
-06/04/2020,6,4,2020,47,3,South_Korea,KR,KOR,51225321,Asia,2.5827071\r
-05/04/2020,5,4,2020,81,6,South_Korea,KR,KOR,51225321,Asia,2.61589381\r
-04/04/2020,4,4,2020,94,3,South_Korea,KR,KOR,51225321,Asia,2.64908052\r
-03/04/2020,3,4,2020,86,5,South_Korea,KR,KOR,51225321,Asia,2.75254498\r
-02/04/2020,2,4,2020,190,6,South_Korea,KR,KOR,51225321,Asia,2.75449714\r
-01/04/2020,1,4,2020,0,0,South_Korea,KR,KOR,51225321,Asia,2.68031507\r
-31/03/2020,31,3,2020,125,5,South_Korea,KR,KOR,51225321,Asia,2.86186591\r
-30/03/2020,30,3,2020,78,6,South_Korea,KR,KOR,51225321,Asia,2.78182737\r
-29/03/2020,29,3,2020,105,8,South_Korea,KR,KOR,51225321,Asia,2.77401873\r
-28/03/2020,28,3,2020,146,5,South_Korea,KR,KOR,51225321,Asia,2.7174061\r
-27/03/2020,27,3,2020,91,8,South_Korea,KR,KOR,51225321,Asia,2.64127188\r
-26/03/2020,26,3,2020,104,5,South_Korea,KR,KOR,51225321,Asia,2.67836291\r
-25/03/2020,25,3,2020,100,6,South_Korea,KR,KOR,51225321,Asia,2.69788451\r
-24/03/2020,24,3,2020,76,7,South_Korea,KR,KOR,51225321,Asia,2.97509117\r
-23/03/2020,23,3,2020,64,9,South_Korea,KR,KOR,51225321,Asia,3.08245994\r
-22/03/2020,22,3,2020,98,1,South_Korea,KR,KOR,51225321,Asia,3.4416573\r
-21/03/2020,21,3,2020,147,3,South_Korea,KR,KOR,51225321,Asia,3.96678822\r
-20/03/2020,20,3,2020,87,9,South_Korea,KR,KOR,51225321,Asia,4.62271383\r
-19/03/2020,19,3,2020,152,5,South_Korea,KR,KOR,51225321,Asia,5.4640946\r
-18/03/2020,18,3,2020,93,5,South_Korea,KR,KOR,51225321,Asia,6.02241224\r
-17/03/2020,17,3,2020,84,6,South_Korea,KR,KOR,51225321,Asia,6.84817573\r
-16/03/2020,16,3,2020,74,0,South_Korea,KR,KOR,51225321,Asia,7.85549006\r
-15/03/2020,15,3,2020,76,3,South_Korea,KR,KOR,51225321,Asia,9.05021171\r
-14/03/2020,14,3,2020,107,5,South_Korea,KR,KOR,51225321,Asia,10.06338252\r
-13/03/2020,13,3,2020,110,1,South_Korea,KR,KOR,51225321,Asia,11.62901449\r
-12/03/2020,12,3,2020,114,6,South_Korea,KR,KOR,51225321,Asia,12.24784907\r
-11/03/2020,11,3,2020,242,6,South_Korea,KR,KOR,51225321,Asia,12.90182252\r
-10/03/2020,10,3,2020,131,3,South_Korea,KR,KOR,51225321,Asia,12.92524843\r
-09/03/2020,9,3,2020,248,1,South_Korea,KR,KOR,51225321,Asia,12.92329627\r
-08/03/2020,8,3,2020,367,6,South_Korea,KR,KOR,51225321,Asia,12.75345839\r
-07/03/2020,7,3,2020,483,2,South_Korea,KR,KOR,51225321,Asia,12.53676868\r
-06/03/2020,6,3,2020,518,7,South_Korea,KR,KOR,51225321,Asia,11.96478593\r
-05/03/2020,5,3,2020,438,3,South_Korea,KR,KOR,51225321,Asia,11.09997925\r
-04/03/2020,4,3,2020,516,4,South_Korea,KR,KOR,51225321,Asia,10.31130679\r
-03/03/2020,3,3,2020,600,6,South_Korea,KR,KOR,51225321,Asia,9.33327485\r
-02/03/2020,2,3,2020,686,5,South_Korea,KR,KOR,51225321,Asia,8.16393127\r
-01/03/2020,1,3,2020,595,1,South_Korea,KR,KOR,51225321,Asia,6.82670197\r
-29/02/2020,29,2,2020,909,3,South_Korea,KR,KOR,51225321,Asia,5.6671192\r
-28/02/2020,28,2,2020,427,1,South_Korea,KR,KOR,51225321,Asia,3.89260616\r
-27/02/2020,27,2,2020,449,1,South_Korea,KR,KOR,51225321,Asia,3.05903403\r
-26/02/2020,26,2,2020,254,3,South_Korea,KR,KOR,51225321,Asia,2.18251439\r
-25/02/2020,25,2,2020,130,1,South_Korea,KR,KOR,51225321,Asia,1.68666586\r
-24/02/2020,24,2,2020,161,2,South_Korea,KR,KOR,51225321,Asia,1.43483728\r
-23/02/2020,23,2,2020,256,3,South_Korea,KR,KOR,51225321,Asia,1.12444391\r
-22/02/2020,22,2,2020,190,1,South_Korea,KR,KOR,51225321,Asia,0.62664322\r
-21/02/2020,21,2,2020,75,1,South_Korea,KR,KOR,51225321,Asia,0.2557329\r
-20/02/2020,20,2,2020,34,0,South_Korea,KR,KOR,51225321,Asia,0.11127309\r
-19/02/2020,19,2,2020,15,0,South_Korea,KR,KOR,51225321,Asia,0.05466047\r
-18/02/2020,18,2,2020,1,0,South_Korea,KR,KOR,51225321,Asia,0.02928239\r
-17/02/2020,17,2,2020,1,0,South_Korea,KR,KOR,51225321,Asia,0.02928239\r
-16/02/2020,16,2,2020,1,0,South_Korea,KR,KOR,51225321,Asia,0.02733023\r
-15/02/2020,15,2,2020,0,0,South_Korea,KR,KOR,51225321,Asia,0.03123455\r
-14/02/2020,14,2,2020,0,0,South_Korea,KR,KOR,51225321,Asia,0.04099535\r
-13/02/2020,13,2,2020,0,0,South_Korea,KR,KOR,51225321,Asia,0.04685183\r
-12/02/2020,12,2,2020,0,0,South_Korea,KR,KOR,51225321,Asia,0.04685183\r
-11/02/2020,11,2,2020,1,0,South_Korea,KR,KOR,51225321,Asia,0.04685183\r
-10/02/2020,10,2,2020,2,0,South_Korea,KR,KOR,51225321,Asia,0.04489967\r
-09/02/2020,9,2,2020,1,0,South_Korea,KR,KOR,51225321,Asia,0.04294751\r
-08/02/2020,8,2,2020,0,0,South_Korea,KR,KOR,51225321,Asia,0.04294751\r
-07/02/2020,7,2,2020,1,0,South_Korea,KR,KOR,51225321,Asia,0.04294751\r
-06/02/2020,6,2,2020,5,0,South_Korea,KR,KOR,51225321,Asia,0.04294751\r
-05/02/2020,5,2,2020,2,0,South_Korea,KR,KOR,51225321,Asia,0.03318671\r
-04/02/2020,4,2,2020,1,0,South_Korea,KR,KOR,51225321,Asia,0.02928239\r
-03/02/2020,3,2,2020,0,0,South_Korea,KR,KOR,51225321,Asia,0.02733023\r
-02/02/2020,2,2,2020,3,0,South_Korea,KR,KOR,51225321,Asia,0.02928239\r
-01/02/2020,1,2,2020,5,0,South_Korea,KR,KOR,51225321,Asia,0.02342591\r
-31/01/2020,31,1,2020,3,0,South_Korea,KR,KOR,51225321,Asia,0.01366512\r
-30/01/2020,30,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,0.00780864\r
-29/01/2020,29,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,0.00780864\r
-28/01/2020,28,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,0.00780864\r
-27/01/2020,27,1,2020,1,0,South_Korea,KR,KOR,51225321,Asia,0.00780864\r
-26/01/2020,26,1,2020,1,0,South_Korea,KR,KOR,51225321,Asia,0.00585648\r
-25/01/2020,25,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,0.00390432\r
-24/01/2020,24,1,2020,1,0,South_Korea,KR,KOR,51225321,Asia,0.00390432\r
-23/01/2020,23,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,0.00195216\r
-22/01/2020,22,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,0.00195216\r
-21/01/2020,21,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,0.00195216\r
-20/01/2020,20,1,2020,1,0,South_Korea,KR,KOR,51225321,Asia,0.00195216\r
-19/01/2020,19,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,0\r
-18/01/2020,18,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,0\r
-17/01/2020,17,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,0\r
-16/01/2020,16,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,0\r
-15/01/2020,15,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,0\r
-14/01/2020,14,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,0\r
-13/01/2020,13,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,0\r
-12/01/2020,12,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,\r
-11/01/2020,11,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,\r
-10/01/2020,10,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,\r
-09/01/2020,9,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,\r
-08/01/2020,8,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,\r
-07/01/2020,7,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,\r
-06/01/2020,6,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,\r
-05/01/2020,5,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,\r
-04/01/2020,4,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,\r
-03/01/2020,3,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,\r
-02/01/2020,2,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,\r
-01/01/2020,1,1,2020,0,0,South_Korea,KR,KOR,51225321,Asia,\r
-31/12/2019,31,12,2019,0,0,South_Korea,KR,KOR,51225321,Asia,\r
-19/08/2020,19,8,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,0.47911276\r
-18/08/2020,18,8,2020,1,0,South_Sudan,SS,SSD,11062114,Africa,0.55143167\r
-17/08/2020,17,8,2020,1,0,South_Sudan,SS,SSD,11062114,Africa,0.54239181\r
-16/08/2020,16,8,2020,6,0,South_Sudan,SS,SSD,11062114,Africa,1.22942143\r
-15/08/2020,15,8,2020,4,0,South_Sudan,SS,SSD,11062114,Africa,1.44637815\r
-14/08/2020,14,8,2020,1,0,South_Sudan,SS,SSD,11062114,Africa,1.4102187\r
-13/08/2020,13,8,2020,5,0,South_Sudan,SS,SSD,11062114,Africa,1.40117883\r
-12/08/2020,12,8,2020,2,0,South_Sudan,SS,SSD,11062114,Africa,1.35597952\r
-11/08/2020,11,8,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,1.49157747\r
-10/08/2020,10,8,2020,7,0,South_Sudan,SS,SSD,11062114,Africa,1.8802916\r
-09/08/2020,9,8,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,1.85317201\r
-08/08/2020,8,8,2020,5,0,South_Sudan,SS,SSD,11062114,Africa,1.85317201\r
-07/08/2020,7,8,2020,8,0,South_Sudan,SS,SSD,11062114,Africa,1.97973009\r
-06/08/2020,6,8,2020,13,0,South_Sudan,SS,SSD,11062114,Africa,2.16052736\r
-05/08/2020,5,8,2020,8,1,South_Sudan,SS,SSD,11062114,Africa,2.04300914\r
-04/08/2020,4,8,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,1.97069023\r
-03/08/2020,3,8,2020,77,0,South_Sudan,SS,SSD,11062114,Africa,2.07012873\r
-02/08/2020,2,8,2020,30,0,South_Sudan,SS,SSD,11062114,Africa,1.45541802\r
-01/08/2020,1,8,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,1.18422211\r
-31/07/2020,31,7,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,1.36501938\r
-30/07/2020,30,7,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,1.52773692\r
-29/07/2020,29,7,2020,17,0,South_Sudan,SS,SSD,11062114,Africa,1.57293624\r
-28/07/2020,28,7,2020,43,1,South_Sudan,SS,SSD,11062114,Africa,1.41925856\r
-27/07/2020,27,7,2020,4,0,South_Sudan,SS,SSD,11062114,Africa,1.1119032\r
-26/07/2020,26,7,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,1.16614238\r
-25/07/2020,25,7,2020,19,0,South_Sudan,SS,SSD,11062114,Africa,1.16614238\r
-24/07/2020,24,7,2020,28,0,South_Sudan,SS,SSD,11062114,Africa,1.13902279\r
-23/07/2020,23,7,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,0.94918566\r
-22/07/2020,22,7,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,1.02150457\r
-21/07/2020,21,7,2020,11,2,South_Sudan,SS,SSD,11062114,Africa,1.06670389\r
-20/07/2020,20,7,2020,9,0,South_Sudan,SS,SSD,11062114,Africa,1.48253761\r
-19/07/2020,19,7,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,1.40117883\r
-18/07/2020,18,7,2020,20,2,South_Sudan,SS,SSD,11062114,Africa,1.40117883\r
-17/07/2020,17,7,2020,18,0,South_Sudan,SS,SSD,11062114,Africa,1.22038157\r
-16/07/2020,16,7,2020,5,0,South_Sudan,SS,SSD,11062114,Africa,1.32885993\r
-15/07/2020,15,7,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,1.28366061\r
-14/07/2020,14,7,2020,9,0,South_Sudan,SS,SSD,11062114,Africa,1.28366061\r
-13/07/2020,13,7,2020,10,0,South_Sudan,SS,SSD,11062114,Africa,1.35597952\r
-12/07/2020,12,7,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,1.54581665\r
-11/07/2020,11,7,2020,16,1,South_Sudan,SS,SSD,11062114,Africa,1.60005583\r
-10/07/2020,10,7,2020,7,0,South_Sudan,SS,SSD,11062114,Africa,1.54581665\r
-09/07/2020,9,7,2020,8,0,South_Sudan,SS,SSD,11062114,Africa,1.59101597\r
-08/07/2020,8,7,2020,5,0,South_Sudan,SS,SSD,11062114,Africa,1.64525515\r
-07/07/2020,7,7,2020,57,2,South_Sudan,SS,SSD,11062114,Africa,1.81701255\r
-06/07/2020,6,7,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,1.39213897\r
-05/07/2020,5,7,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,1.55485651\r
-04/07/2020,4,7,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,2.01588955\r
-03/07/2020,3,7,2020,30,1,South_Sudan,SS,SSD,11062114,Africa,2.01588955\r
-02/07/2020,2,7,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,1.79893283\r
-01/07/2020,1,7,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,2.07916859\r
-30/06/2020,30,6,2020,17,1,South_Sudan,SS,SSD,11062114,Africa,2.26900573\r
-29/06/2020,29,6,2020,31,0,South_Sudan,SS,SSD,11062114,Africa,2.67579958\r
-28/06/2020,28,6,2020,6,0,South_Sudan,SS,SSD,11062114,Africa,2.39556381\r
-27/06/2020,27,6,2020,10,0,South_Sudan,SS,SSD,11062114,Africa,2.54924149\r
-26/06/2020,26,6,2020,12,0,South_Sudan,SS,SSD,11062114,Africa,3.05547385\r
-25/06/2020,25,6,2020,14,1,South_Sudan,SS,SSD,11062114,Africa,2.94699548\r
-24/06/2020,24,6,2020,24,1,South_Sudan,SS,SSD,11062114,Africa,2.8204374\r
-23/06/2020,23,6,2020,10,0,South_Sudan,SS,SSD,11062114,Africa,2.60348067\r
-22/06/2020,22,6,2020,18,0,South_Sudan,SS,SSD,11062114,Africa,5.10752285\r
-21/06/2020,21,6,2020,51,3,South_Sudan,SS,SSD,11062114,Africa,4.94480531\r
-20/06/2020,20,6,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,4.48377227\r
-19/06/2020,19,6,2020,6,0,South_Sudan,SS,SSD,11062114,Africa,4.48377227\r
-18/06/2020,18,6,2020,31,1,South_Sudan,SS,SSD,11062114,Africa,7.34940898\r
-17/06/2020,17,6,2020,21,0,South_Sudan,SS,SSD,11062114,Africa,7.06917322\r
-16/06/2020,16,6,2020,62,3,South_Sudan,SS,SSD,11062114,Africa,6.87933608\r
-15/06/2020,15,6,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,6.31886455\r
-14/06/2020,14,6,2020,23,5,South_Sudan,SS,SSD,11062114,Africa,6.31886455\r
-13/06/2020,13,6,2020,66,3,South_Sudan,SS,SSD,11062114,Africa,6.11094769\r
-12/06/2020,12,6,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,7.21381103\r
-11/06/2020,11,6,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,7.21381103\r
-10/06/2020,10,6,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,7.21381103\r
-09/06/2020,9,6,2020,287,5,South_Sudan,SS,SSD,11062114,Africa,8.57883041\r
-08/06/2020,8,6,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,6.81605704\r
-07/06/2020,7,6,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,6.81605704\r
-06/06/2020,6,6,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,8.84098645\r
-05/06/2020,5,6,2020,323,4,South_Sudan,SS,SSD,11062114,Africa,8.84098645\r
-04/06/2020,4,6,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,6.40926318\r
-03/06/2020,3,6,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,6.40926318\r
-02/06/2020,2,6,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,6.43638277\r
-01/06/2020,1,6,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,6.43638277\r
-31/05/2020,31,5,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,6.85221649\r
-30/05/2020,30,5,2020,188,2,South_Sudan,SS,SSD,11062114,Africa,6.85221649\r
-29/05/2020,29,5,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,5.19792148\r
-28/05/2020,28,5,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,5.45103766\r
-27/05/2020,27,5,2020,151,0,South_Sudan,SS,SSD,11062114,Africa,5.53239643\r
-26/05/2020,26,5,2020,92,2,South_Sudan,SS,SSD,11062114,Africa,4.51089186\r
-25/05/2020,25,5,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,3.67922442\r
-24/05/2020,24,5,2020,224,0,South_Sudan,SS,SSD,11062114,Africa,3.79674265\r
-23/05/2020,23,5,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,1.97973009\r
-22/05/2020,22,5,2020,54,0,South_Sudan,SS,SSD,11062114,Africa,2.250926\r
-21/05/2020,21,5,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,1.90741119\r
-20/05/2020,20,5,2020,3,2,South_Sudan,SS,SSD,11062114,Africa,2.10628818\r
-19/05/2020,19,5,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,2.13340777\r
-18/05/2020,18,5,2020,46,0,South_Sudan,SS,SSD,11062114,Africa,2.13340777\r
-17/05/2020,17,5,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,1.72661392\r
-16/05/2020,16,5,2020,5,3,South_Sudan,SS,SSD,11062114,Africa,1.72661392\r
-15/05/2020,15,5,2020,28,1,South_Sudan,SS,SSD,11062114,Africa,1.77181324\r
-14/05/2020,14,5,2020,9,0,South_Sudan,SS,SSD,11062114,Africa,1.52773692\r
-13/05/2020,13,5,2020,38,0,South_Sudan,SS,SSD,11062114,Africa,1.44637815\r
-12/05/2020,12,5,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,1.35597952\r
-11/05/2020,11,5,2020,13,0,South_Sudan,SS,SSD,11062114,Africa,1.35597952\r
-10/05/2020,10,5,2020,23,0,South_Sudan,SS,SSD,11062114,Africa,1.24750116\r
-09/05/2020,9,5,2020,30,0,South_Sudan,SS,SSD,11062114,Africa,1.0395843\r
-08/05/2020,8,5,2020,16,0,South_Sudan,SS,SSD,11062114,Africa,0.77742826\r
-07/05/2020,7,5,2020,22,0,South_Sudan,SS,SSD,11062114,Africa,0.63279044\r
-06/05/2020,6,5,2020,6,0,South_Sudan,SS,SSD,11062114,Africa,0.43391345\r
-05/05/2020,5,5,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,0.37967426\r
-04/05/2020,4,5,2020,1,0,South_Sudan,SS,SSD,11062114,Africa,0.37967426\r
-03/05/2020,3,5,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,0.3706344\r
-02/05/2020,2,5,2020,10,0,South_Sudan,SS,SSD,11062114,Africa,0.3706344\r
-01/05/2020,1,5,2020,1,0,South_Sudan,SS,SSD,11062114,Africa,0.28023577\r
-30/04/2020,30,4,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,0.2711959\r
-29/04/2020,29,4,2020,28,0,South_Sudan,SS,SSD,11062114,Africa,0.2711959\r
-28/04/2020,28,4,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,0.01807973\r
-27/04/2020,27,4,2020,1,0,South_Sudan,SS,SSD,11062114,Africa,0.01807973\r
-26/04/2020,26,4,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,0.00903986\r
-25/04/2020,25,4,2020,1,0,South_Sudan,SS,SSD,11062114,Africa,0.01807973\r
-24/04/2020,24,4,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,0.01807973\r
-23/04/2020,23,4,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,0.01807973\r
-22/04/2020,22,4,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,0.02711959\r
-21/04/2020,21,4,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,0.02711959\r
-20/04/2020,20,4,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,0.02711959\r
-19/04/2020,19,4,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,0.03615945\r
-18/04/2020,18,4,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,\r
-17/04/2020,17,4,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,\r
-16/04/2020,16,4,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,\r
-15/04/2020,15,4,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,\r
-14/04/2020,14,4,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,\r
-13/04/2020,13,4,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,\r
-12/04/2020,12,4,2020,1,0,South_Sudan,SS,SSD,11062114,Africa,\r
-11/04/2020,11,4,2020,1,0,South_Sudan,SS,SSD,11062114,Africa,\r
-10/04/2020,10,4,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,\r
-09/04/2020,9,4,2020,1,0,South_Sudan,SS,SSD,11062114,Africa,\r
-08/04/2020,8,4,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,\r
-07/04/2020,7,4,2020,0,0,South_Sudan,SS,SSD,11062114,Africa,\r
-06/04/2020,6,4,2020,1,0,South_Sudan,SS,SSD,11062114,Africa,\r
-18/08/2020,18,8,2020,5114,24,Spain,ES,ESP,46937060,Europe,130.77512737\r
-17/08/2020,17,8,2020,16269,29,Spain,ES,ESP,46937060,Europe,132.15143854\r
-16/08/2020,16,8,2020,0,0,Spain,ES,ESP,46937060,Europe,115.66766218\r
-15/08/2020,15,8,2020,0,0,Spain,ES,ESP,46937060,Europe,115.66766218\r
-14/08/2020,14,8,2020,5479,12,Spain,ES,ESP,46937060,Europe,115.66766218\r
-13/08/2020,13,8,2020,7550,26,Spain,ES,ESP,46937060,Europe,110.58212849\r
-12/08/2020,12,8,2020,3172,-2,Spain,ES,ESP,46937060,Europe,100.43875777\r
-11/08/2020,11,8,2020,3632,5,Spain,ES,ESP,46937060,Europe,98.00784284\r
-10/08/2020,10,8,2020,8618,73,Spain,ES,ESP,46937060,Europe,94.16439803\r
-09/08/2020,9,8,2020,0,0,Spain,ES,ESP,46937060,Europe,89.35583098\r
-08/08/2020,8,8,2020,0,0,Spain,ES,ESP,46937060,Europe,89.35583098\r
-07/08/2020,7,8,2020,4507,3,Spain,ES,ESP,46937060,Europe,89.35583098\r
-06/08/2020,6,8,2020,4088,1,Spain,ES,ESP,46937060,Europe,84.55791649\r
-05/08/2020,5,8,2020,2953,1,Spain,ES,ESP,46937060,Europe,81.41967136\r
-04/08/2020,4,8,2020,5760,26,Spain,ES,ESP,46937060,Europe,78.01937318\r
-03/08/2020,3,8,2020,8532,27,Spain,ES,ESP,46937060,Europe,68.6408565\r
-02/08/2020,2,8,2020,0,0,Spain,ES,ESP,46937060,Europe,60.22320103\r
-01/08/2020,1,8,2020,0,0,Spain,ES,ESP,46937060,Europe,60.22320103\r
-31/07/2020,31,7,2020,3092,2,Spain,ES,ESP,46937060,Europe,60.22320103\r
-30/07/2020,30,7,2020,2789,2,Spain,ES,ESP,46937060,Europe,56.61837363\r
-29/07/2020,29,7,2020,2031,5,Spain,ES,ESP,46937060,Europe,53.57600156\r
-28/07/2020,28,7,2020,1828,2,Spain,ES,ESP,46937060,Europe,51.11312894\r
-27/07/2020,27,7,2020,6361,2,Spain,ES,ESP,46937060,Europe,48.63747325\r
-26/07/2020,26,7,2020,0,0,Spain,ES,ESP,46937060,Europe,39.44218066\r
-25/07/2020,25,7,2020,0,0,Spain,ES,ESP,46937060,Europe,39.44218066\r
-24/07/2020,24,7,2020,2255,3,Spain,ES,ESP,46937060,Europe,39.44218066\r
-23/07/2020,23,7,2020,2615,3,Spain,ES,ESP,46937060,Europe,36.45307141\r
-22/07/2020,22,7,2020,1357,2,Spain,ES,ESP,46937060,Europe,32.0386492\r
-21/07/2020,21,7,2020,1358,2,Spain,ES,ESP,46937060,Europe,29.96352988\r
-20/07/2020,20,7,2020,4581,2,Spain,ES,ESP,46937060,Europe,27.79679852\r
-19/07/2020,19,7,2020,0,0,Spain,ES,ESP,46937060,Europe,20.68727781\r
-18/07/2020,18,7,2020,0,0,Spain,ES,ESP,46937060,Europe,20.68727781\r
-17/07/2020,17,7,2020,1400,4,Spain,ES,ESP,46937060,Europe,20.68727781\r
-16/07/2020,16,7,2020,1361,3,Spain,ES,ESP,46937060,Europe,18.6462467\r
-15/07/2020,15,7,2020,875,4,Spain,ES,ESP,46937060,Europe,16.6925666\r
-14/07/2020,14,7,2020,666,3,Spain,ES,ESP,46937060,Europe,15.65500694\r
-13/07/2020,13,7,2020,2045,3,Spain,ES,ESP,46937060,Europe,14.87736982\r
-12/07/2020,12,7,2020,0,0,Spain,ES,ESP,46937060,Europe,10.94657399\r
-11/07/2020,11,7,2020,0,0,Spain,ES,ESP,46937060,Europe,11.58785829\r
-10/07/2020,10,7,2020,852,2,Spain,ES,ESP,46937060,Europe,12.78946743\r
-09/07/2020,9,7,2020,543,5,Spain,ES,ESP,46937060,Europe,11.86695545\r
-08/07/2020,8,7,2020,383,4,Spain,ES,ESP,46937060,Europe,11.56229214\r
-07/07/2020,7,7,2020,341,4,Spain,ES,ESP,46937060,Europe,11.45789702\r
-06/07/2020,6,7,2020,1244,3,Spain,ES,ESP,46937060,Europe,11.25975935\r
-05/07/2020,5,7,2020,0,0,Spain,ES,ESP,46937060,Europe,9.10368055\r
-04/07/2020,4,7,2020,0,0,Spain,ES,ESP,46937060,Europe,9.81527177\r
-03/07/2020,3,7,2020,442,17,Spain,ES,ESP,46937060,Europe,10.58864786\r
-02/07/2020,2,7,2020,444,5,Spain,ES,ESP,46937060,Europe,10.30102865\r
-01/07/2020,1,7,2020,388,8,Spain,ES,ESP,46937060,Europe,10.60143094\r
-30/06/2020,30,6,2020,301,9,Spain,ES,ESP,46937060,Europe,10.53112402\r
-29/06/2020,29,6,2020,200,3,Spain,ES,ESP,46937060,Europe,10.35642198\r
-28/06/2020,28,6,2020,301,2,Spain,ES,ESP,46937060,Europe,10.31594224\r
-27/06/2020,27,6,2020,564,3,Spain,ES,ESP,46937060,Europe,10.36281352\r
-26/06/2020,26,6,2020,419,8,Spain,ES,ESP,46937060,Europe,10.0048874\r
-25/06/2020,25,6,2020,400,3,Spain,ES,ESP,46937060,Europe,10.18171995\r
-24/06/2020,24,6,2020,334,2,Spain,ES,ESP,46937060,Europe,10.23924379\r
-23/06/2020,23,6,2020,248,1,Spain,ES,ESP,46937060,Europe,10.19663353\r
-22/06/2020,22,6,2020,232,1,Spain,ES,ESP,46937060,Europe,10.19876405\r
-21/06/2020,21,6,2020,334,1,Spain,ES,ESP,46937060,Europe,10.06028072\r
-20/06/2020,20,6,2020,363,7,Spain,ES,ESP,46937060,Europe,9.86001254\r
-19/06/2020,19,6,2020,307,1179,Spain,ES,ESP,46937060,Europe,9.79396664\r
-18/06/2020,18,6,2020,585,0,Spain,ES,ESP,46937060,Europe,9.81740228\r
-17/06/2020,17,6,2020,355,0,Spain,ES,ESP,46937060,Europe,9.28264361\r
-16/06/2020,16,6,2020,219,0,Spain,ES,ESP,46937060,Europe,9.3657336\r
-15/06/2020,15,6,2020,181,0,Spain,ES,ESP,46937060,Europe,9.52552205\r
-14/06/2020,14,6,2020,323,0,Spain,ES,ESP,46937060,Europe,9.5851764\r
-13/06/2020,13,6,2020,396,0,Spain,ES,ESP,46937060,Europe,9.32525386\r
-12/06/2020,12,6,2020,502,0,Spain,ES,ESP,46937060,Europe,9.89623125\r
-11/06/2020,11,6,2020,427,0,Spain,ES,ESP,46937060,Europe,10.22859122\r
-10/06/2020,10,6,2020,314,0,Spain,ES,ESP,46937060,Europe,11.7412552\r
-09/06/2020,9,6,2020,249,0,Spain,ES,ESP,46937060,Europe,12.15883568\r
-08/06/2020,8,6,2020,167,0,Spain,ES,ESP,46937060,Europe,13.4584484\r
-07/06/2020,7,6,2020,240,1,Spain,ES,ESP,46937060,Europe,12.31010208\r
-06/06/2020,6,6,2020,332,1,Spain,ES,ESP,46937060,Europe,12.82568614\r
-05/06/2020,5,6,2020,318,1,Spain,ES,ESP,46937060,Europe,13.11117484\r
-04/06/2020,4,6,2020,334,5,Spain,ES,ESP,46937060,Europe,16.24089792\r
-03/06/2020,3,6,2020,394,1,Spain,ES,ESP,46937060,Europe,16.55621379\r
-02/06/2020,2,6,2020,294,0,Spain,ES,ESP,46937060,Europe,16.82039736\r
-01/06/2020,1,6,2020,209,0,Spain,ES,ESP,46937060,Europe,17.11227759\r
-31/05/2020,31,5,2020,201,2,Spain,ES,ESP,46937060,Europe,17.21241168\r
-30/05/2020,30,5,2020,664,4,Spain,ES,ESP,46937060,Europe,18.17327289\r
-29/05/2020,29,5,2020,658,2,Spain,ES,ESP,46937060,Europe,17.8558265\r
-28/05/2020,28,5,2020,1137,1,Spain,ES,ESP,46937060,Europe,17.82386881\r
-27/05/2020,27,5,2020,510,1,Spain,ES,ESP,46937060,Europe,17.21028117\r
-26/05/2020,26,5,2020,859,283,Spain,ES,ESP,46937060,Europe,17.05901477\r
-25/05/2020,25,5,2020,-372,-1918,Spain,ES,ESP,46937060,Europe,16.25581151\r
-24/05/2020,24,5,2020,482,74,Spain,ES,ESP,46937060,Europe,17.88565368\r
-23/05/2020,23,5,2020,466,50,Spain,ES,ESP,46937060,Europe,24.13657779\r
-22/05/2020,22,5,2020,1787,688,Spain,ES,ESP,46937060,Europe,24.7267298\r
-21/05/2020,21,5,2020,482,52,Spain,ES,ESP,46937060,Europe,23.41859503\r
-20/05/2020,20,5,2020,518,110,Spain,ES,ESP,46937060,Europe,24.35389008\r
-19/05/2020,19,5,2020,431,69,Spain,ES,ESP,46937060,Europe,25.12513566\r
-18/05/2020,18,5,2020,256,59,Spain,ES,ESP,46937060,Europe,26.42048735\r
-17/05/2020,17,5,2020,652,87,Spain,ES,ESP,46937060,Europe,26.86789501\r
-16/05/2020,16,5,2020,515,104,Spain,ES,ESP,46937060,Europe,27.47083009\r
-15/05/2020,15,5,2020,643,138,Spain,ES,ESP,46937060,Europe,29.00266868\r
-14/05/2020,14,5,2020,849,217,Spain,ES,ESP,46937060,Europe,30.58777009\r
-13/05/2020,13,5,2020,439,184,Spain,ES,ESP,46937060,Europe,31.42293105\r
-12/05/2020,12,5,2020,482,176,Spain,ES,ESP,46937060,Europe,32.29218021\r
-11/05/2020,11,5,2020,393,123,Spain,ES,ESP,46937060,Europe,34.5143049\r
-10/05/2020,10,5,2020,3416,143,Spain,ES,ESP,46937060,Europe,37.21366443\r
-09/05/2020,9,5,2020,743,227,Spain,ES,ESP,46937060,Europe,33.43200448\r
-08/05/2020,8,5,2020,1173,181,Spain,ES,ESP,46937060,Europe,37.18809827\r
-07/05/2020,7,5,2020,921,213,Spain,ES,ESP,46937060,Europe,39.19291068\r
-06/05/2020,6,5,2020,880,244,Spain,ES,ESP,46937060,Europe,43.44328341\r
-05/05/2020,5,5,2020,1039,185,Spain,ES,ESP,46937060,Europe,46.49417752\r
-04/05/2020,4,5,2020,466,164,Spain,ES,ESP,46937060,Europe,50.56771771\r
-03/05/2020,3,5,2020,935,164,Spain,ES,ESP,46937060,Europe,54.30037587\r
-02/05/2020,2,5,2020,1234,276,Spain,ES,ESP,46937060,Europe,50.78929102\r
-01/05/2020,1,5,2020,1387,281,Spain,ES,ESP,46937060,Europe,56.33288493\r
-30/04/2020,30,4,2020,1241,268,Spain,ES,ESP,46937060,Europe,61.51216118\r
-29/04/2020,29,4,2020,847,453,Spain,ES,ESP,46937060,Europe,67.0067533\r
-28/04/2020,28,4,2020,1525,632,Spain,ES,ESP,46937060,Europe,74.62759704\r
-27/04/2020,27,4,2020,1660,0,Spain,ES,ESP,46937060,Europe,78.01724266\r
-26/04/2020,26,4,2020,1641,288,Spain,ES,ESP,46937060,Europe,80.93604499\r
-25/04/2020,25,4,2020,2506,378,Spain,ES,ESP,46937060,Europe,85.74674255\r
-24/04/2020,24,4,2020,2114,367,Spain,ES,ESP,46937060,Europe,90.10151041\r
-23/04/2020,23,4,2020,2916,440,Spain,ES,ESP,46937060,Europe,95.26374255\r
-22/04/2020,22,4,2020,2312,435,Spain,ES,ESP,46937060,Europe,101.29096283\r
-21/04/2020,21,4,2020,2951,430,Spain,ES,ESP,46937060,Europe,108.25986971\r
-20/04/2020,20,4,2020,2218,399,Spain,ES,ESP,46937060,Europe,113.07056727\r
-19/04/2020,19,4,2020,-713,410,Spain,ES,ESP,46937060,Europe,116.15768009\r
-18/04/2020,18,4,2020,3836,565,Spain,ES,ESP,46937060,Europe,129.46486209\r
-17/04/2020,17,4,2020,3818,585,Spain,ES,ESP,46937060,Europe,135.48782135\r
-16/04/2020,16,4,2020,3820,617,Spain,ES,ESP,46937060,Europe,142.84661204\r
-15/04/2020,15,4,2020,4424,787,Spain,ES,ESP,46937060,Europe,150.86373113\r
-14/04/2020,14,4,2020,3116,517,Spain,ES,ESP,46937060,Europe,157.23183344\r
-13/04/2020,13,4,2020,3030,619,Spain,ES,ESP,46937060,Europe,167.94618155\r
-12/04/2020,12,4,2020,3899,510,Spain,ES,ESP,46937060,Europe,173.87539825\r
-11/04/2020,11,4,2020,4550,605,Spain,ES,ESP,46937060,Europe,179.25494268\r
-10/04/2020,10,4,2020,4537,683,Spain,ES,ESP,46937060,Europe,187.12505641\r
-09/04/2020,9,4,2020,5745,757,Spain,ES,ESP,46937060,Europe,197.01915714\r
-08/04/2020,8,4,2020,5583,743,Spain,ES,ESP,46937060,Europe,203.85597223\r
-07/04/2020,7,4,2020,5209,637,Spain,ES,ESP,46937060,Europe,210.1835948\r
-06/04/2020,6,4,2020,3667,674,Spain,ES,ESP,46937060,Europe,215.47152719\r
-05/04/2020,5,4,2020,5533,809,Spain,ES,ESP,46937060,Europe,217.55729907\r
-04/04/2020,4,4,2020,6663,932,Spain,ES,ESP,46937060,Europe,216.13624714\r
-03/04/2020,3,4,2020,7272,950,Spain,ES,ESP,46937060,Europe,213.54341324\r
-02/04/2020,2,4,2020,7583,864,Spain,ES,ESP,46937060,Europe,207.78463756\r
-01/04/2020,1,4,2020,7413,849,Spain,ES,ESP,46937060,Europe,200.25114483\r
-31/03/2020,31,3,2020,8145,812,Spain,ES,ESP,46937060,Europe,192.32776829\r
-30/03/2020,30,3,2020,5813,838,Spain,ES,ESP,46937060,Europe,180.30741593\r
-29/03/2020,29,3,2020,6424,832,Spain,ES,ESP,46937060,Europe,171.55740048\r
-28/03/2020,28,3,2020,8244,769,Spain,ES,ESP,46937060,Europe,162.43880635\r
-27/03/2020,27,3,2020,9181,655,Spain,ES,ESP,46937060,Europe,148.46051287\r
-26/03/2020,26,3,2020,8954,738,Spain,ES,ESP,46937060,Europe,132.16209111\r
-25/03/2020,25,3,2020,8553,514,Spain,ES,ESP,46937060,Europe,115.54196194\r
-24/03/2020,24,3,2020,7691,462,Spain,ES,ESP,46937060,Europe,99.39693709\r
-23/03/2020,23,3,2020,4646,394,Spain,ES,ESP,46937060,Europe,84.65592008\r
-22/03/2020,22,3,2020,4866,324,Spain,ES,ESP,46937060,Europe,75.68007029\r
-21/03/2020,21,3,2020,5446,235,Spain,ES,ESP,46937060,Europe,66.01606492\r
-20/03/2020,20,3,2020,4569,169,Spain,ES,ESP,46937060,Europe,54.90970248\r
-19/03/2020,19,3,2020,4047,107,Spain,ES,ESP,46937060,Europe,45.56527401\r
-18/03/2020,18,3,2020,3694,182,Spain,ES,ESP,46937060,Europe,37.11566084\r
-17/03/2020,17,3,2020,2503,21,Spain,ES,ESP,46937060,Europe,29.40533557\r
-16/03/2020,16,3,2020,1706,152,Spain,ES,ESP,46937060,Europe,24.19197112\r
-15/03/2020,15,3,2020,2144,15,Spain,ES,ESP,46937060,Europe,20.67236423\r
-14/03/2020,14,3,2020,1683,37,Spain,ES,ESP,46937060,Europe,16.16419946\r
-13/03/2020,13,3,2020,1531,37,Spain,ES,ESP,46937060,Europe,12.61902642\r
-12/03/2020,12,3,2020,1153,12,Spain,ES,ESP,46937060,Europe,9.39556078\r
-11/03/2020,11,3,2020,975,7,Spain,ES,ESP,46937060,Europe,6.9561238\r
-10/03/2020,10,3,2020,772,23,Spain,ES,ESP,46937060,Europe,4.89165704\r
-09/03/2020,9,3,2020,433,0,Spain,ES,ESP,46937060,Europe,3.24903179\r
-08/03/2020,8,3,2020,330,0,Spain,ES,ESP,46937060,Europe,2.32651981\r
-07/03/2020,7,3,2020,233,2,Spain,ES,ESP,46937060,Europe,1.62345064\r
-06/03/2020,6,3,2020,183,2,Spain,ES,ESP,46937060,Europe,1.12704119\r
-05/03/2020,5,3,2020,81,1,Spain,ES,ESP,46937060,Europe,0.73715738\r
-04/03/2020,4,3,2020,75,0,Spain,ES,ESP,46937060,Europe,0.56458585\r
-03/03/2020,3,3,2020,56,0,Spain,ES,ESP,46937060,Europe,0.4047974\r
-02/03/2020,2,3,2020,54,0,Spain,ES,ESP,46937060,Europe,0.28548869\r
-01/03/2020,1,3,2020,28,0,Spain,ES,ESP,46937060,Europe,0.17044101\r
-29/02/2020,29,2,2020,19,0,Spain,ES,ESP,46937060,Europe,0.11078666\r
-28/02/2020,28,2,2020,18,0,Spain,ES,ESP,46937060,Europe,0.07030692\r
-27/02/2020,27,2,2020,8,0,Spain,ES,ESP,46937060,Europe,0.03195769\r
-26/02/2020,26,2,2020,6,0,Spain,ES,ESP,46937060,Europe,0.01491359\r
-25/02/2020,25,2,2020,1,0,Spain,ES,ESP,46937060,Europe,0.00213051\r
-24/02/2020,24,2,2020,0,0,Spain,ES,ESP,46937060,Europe,0\r
-23/02/2020,23,2,2020,0,0,Spain,ES,ESP,46937060,Europe,0.00213051\r
-22/02/2020,22,2,2020,0,0,Spain,ES,ESP,46937060,Europe,0.00213051\r
-21/02/2020,21,2,2020,0,0,Spain,ES,ESP,46937060,Europe,0.00213051\r
-20/02/2020,20,2,2020,0,0,Spain,ES,ESP,46937060,Europe,0.00213051\r
-19/02/2020,19,2,2020,0,0,Spain,ES,ESP,46937060,Europe,0.00213051\r
-18/02/2020,18,2,2020,0,0,Spain,ES,ESP,46937060,Europe,0.00213051\r
-17/02/2020,17,2,2020,0,0,Spain,ES,ESP,46937060,Europe,0.00213051\r
-16/02/2020,16,2,2020,0,0,Spain,ES,ESP,46937060,Europe,0.00213051\r
-15/02/2020,15,2,2020,0,0,Spain,ES,ESP,46937060,Europe,0.00213051\r
-14/02/2020,14,2,2020,0,0,Spain,ES,ESP,46937060,Europe,0.00426103\r
-13/02/2020,13,2,2020,0,0,Spain,ES,ESP,46937060,Europe,0.00426103\r
-12/02/2020,12,2,2020,0,0,Spain,ES,ESP,46937060,Europe,0.00426103\r
-11/02/2020,11,2,2020,0,0,Spain,ES,ESP,46937060,Europe,0.00426103\r
-10/02/2020,10,2,2020,1,0,Spain,ES,ESP,46937060,Europe,0.00426103\r
-09/02/2020,9,2,2020,0,0,Spain,ES,ESP,46937060,Europe,0.00213051\r
-08/02/2020,8,2,2020,0,0,Spain,ES,ESP,46937060,Europe,0.00213051\r
-07/02/2020,7,2,2020,0,0,Spain,ES,ESP,46937060,Europe,0.00213051\r
-06/02/2020,6,2,2020,0,0,Spain,ES,ESP,46937060,Europe,0.00213051\r
-05/02/2020,5,2,2020,0,0,Spain,ES,ESP,46937060,Europe,0.00213051\r
-04/02/2020,4,2,2020,0,0,Spain,ES,ESP,46937060,Europe,0.00213051\r
-03/02/2020,3,2,2020,0,0,Spain,ES,ESP,46937060,Europe,0.00213051\r
-02/02/2020,2,2,2020,0,0,Spain,ES,ESP,46937060,Europe,0.00213051\r
-01/02/2020,1,2,2020,1,0,Spain,ES,ESP,46937060,Europe,0.00213051\r
-31/01/2020,31,1,2020,0,0,Spain,ES,ESP,46937060,Europe,0\r
-30/01/2020,30,1,2020,0,0,Spain,ES,ESP,46937060,Europe,0\r
-29/01/2020,29,1,2020,0,0,Spain,ES,ESP,46937060,Europe,0\r
-28/01/2020,28,1,2020,0,0,Spain,ES,ESP,46937060,Europe,0\r
-27/01/2020,27,1,2020,0,0,Spain,ES,ESP,46937060,Europe,0\r
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-19/08/2020,19,8,2020,2,0,Sri_Lanka,LK,LKA,21323734,Asia,0.31889349\r
-18/08/2020,18,8,2020,7,0,Sri_Lanka,LK,LKA,21323734,Asia,0.33765193\r
-17/08/2020,17,8,2020,3,0,Sri_Lanka,LK,LKA,21323734,Asia,0.32827271\r
-16/08/2020,16,8,2020,4,0,Sri_Lanka,LK,LKA,21323734,Asia,0.35172076\r
-15/08/2020,15,8,2020,4,0,Sri_Lanka,LK,LKA,21323734,Asia,0.33296232\r
-14/08/2020,14,8,2020,1,0,Sri_Lanka,LK,LKA,21323734,Asia,0.31889349\r
-13/08/2020,13,8,2020,1,0,Sri_Lanka,LK,LKA,21323734,Asia,0.32827271\r
-12/08/2020,12,8,2020,9,0,Sri_Lanka,LK,LKA,21323734,Asia,0.32827271\r
-11/08/2020,11,8,2020,27,0,Sri_Lanka,LK,LKA,21323734,Asia,0.30951427\r
-10/08/2020,10,8,2020,3,0,Sri_Lanka,LK,LKA,21323734,Asia,0.29075583\r
-09/08/2020,9,8,2020,2,0,Sri_Lanka,LK,LKA,21323734,Asia,0.33296232\r
-08/08/2020,8,8,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0.35172076\r
-07/08/2020,7,8,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0.40330648\r
-06/08/2020,6,8,2020,5,0,Sri_Lanka,LK,LKA,21323734,Asia,0.40799609\r
-05/08/2020,5,8,2020,6,0,Sri_Lanka,LK,LKA,21323734,Asia,0.48771946\r
-04/08/2020,4,8,2020,5,0,Sri_Lanka,LK,LKA,21323734,Asia,0.4595818\r
-03/08/2020,3,8,2020,8,0,Sri_Lanka,LK,LKA,21323734,Asia,0.46427141\r
-02/08/2020,2,8,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0.52054673\r
-01/08/2020,1,8,2020,1,0,Sri_Lanka,LK,LKA,21323734,Asia,0.553374\r
-31/07/2020,31,7,2020,3,0,Sri_Lanka,LK,LKA,21323734,Asia,0.59558049\r
-30/07/2020,30,7,2020,1,0,Sri_Lanka,LK,LKA,21323734,Asia,0.64247659\r
-29/07/2020,29,7,2020,5,0,Sri_Lanka,LK,LKA,21323734,Asia,0.67999348\r
-28/07/2020,28,7,2020,23,0,Sri_Lanka,LK,LKA,21323734,Asia,0.74564802\r
-27/07/2020,27,7,2020,12,0,Sri_Lanka,LK,LKA,21323734,Asia,0.77378568\r
-26/07/2020,26,7,2020,6,0,Sri_Lanka,LK,LKA,21323734,Asia,1.21460904\r
-25/07/2020,25,7,2020,11,0,Sri_Lanka,LK,LKA,21323734,Asia,1.45377916\r
-24/07/2020,24,7,2020,1,0,Sri_Lanka,LK,LKA,21323734,Asia,1.8899129\r
-23/07/2020,23,7,2020,22,0,Sri_Lanka,LK,LKA,21323734,Asia,3.0857635\r
-22/07/2020,22,7,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,3.04355701\r
-21/07/2020,21,7,2020,6,0,Sri_Lanka,LK,LKA,21323734,Asia,3.05762584\r
-20/07/2020,20,7,2020,20,0,Sri_Lanka,LK,LKA,21323734,Asia,3.0388674\r
-19/07/2020,19,7,2020,7,0,Sri_Lanka,LK,LKA,21323734,Asia,2.95445441\r
-18/07/2020,18,7,2020,10,0,Sri_Lanka,LK,LKA,21323734,Asia,2.94507519\r
-17/07/2020,17,7,2020,13,0,Sri_Lanka,LK,LKA,21323734,Asia,2.91224792\r
-16/07/2020,16,7,2020,9,0,Sri_Lanka,LK,LKA,21323734,Asia,2.90755831\r
-15/07/2020,15,7,2020,19,0,Sri_Lanka,LK,LKA,21323734,Asia,2.89817909\r
-14/07/2020,14,7,2020,29,0,Sri_Lanka,LK,LKA,21323734,Asia,2.83252455\r
-13/07/2020,13,7,2020,106,0,Sri_Lanka,LK,LKA,21323734,Asia,2.7199739\r
-12/07/2020,12,7,2020,57,0,Sri_Lanka,LK,LKA,21323734,Asia,2.24163367\r
-11/07/2020,11,7,2020,104,0,Sri_Lanka,LK,LKA,21323734,Asia,2.06342848\r
-10/07/2020,10,7,2020,256,0,Sri_Lanka,LK,LKA,21323734,Asia,1.59446746\r
-09/07/2020,9,7,2020,13,0,Sri_Lanka,LK,LKA,21323734,Asia,0.43613375\r
-08/07/2020,8,7,2020,3,0,Sri_Lanka,LK,LKA,21323734,Asia,0.42206492\r
-07/07/2020,7,7,2020,2,0,Sri_Lanka,LK,LKA,21323734,Asia,0.59558049\r
-06/07/2020,6,7,2020,2,0,Sri_Lanka,LK,LKA,21323734,Asia,0.59089088\r
-05/07/2020,5,7,2020,5,0,Sri_Lanka,LK,LKA,21323734,Asia,0.58151166\r
-04/07/2020,4,7,2020,3,0,Sri_Lanka,LK,LKA,21323734,Asia,0.55806361\r
-03/07/2020,3,7,2020,12,0,Sri_Lanka,LK,LKA,21323734,Asia,0.55806361\r
-02/07/2020,2,7,2020,7,0,Sri_Lanka,LK,LKA,21323734,Asia,0.60964932\r
-01/07/2020,1,7,2020,5,0,Sri_Lanka,LK,LKA,21323734,Asia,0.61902854\r
-30/06/2020,30,6,2020,5,0,Sri_Lanka,LK,LKA,21323734,Asia,0.64247659\r
-29/06/2020,29,6,2020,4,0,Sri_Lanka,LK,LKA,21323734,Asia,0.69406231\r
-28/06/2020,28,6,2020,19,0,Sri_Lanka,LK,LKA,21323734,Asia,0.69875192\r
-27/06/2020,27,6,2020,4,0,Sri_Lanka,LK,LKA,21323734,Asia,0.62840776\r
-26/06/2020,26,6,2020,9,0,Sri_Lanka,LK,LKA,21323734,Asia,0.62371815\r
-25/06/2020,25,6,2020,10,0,Sri_Lanka,LK,LKA,21323734,Asia,0.61902854\r
-24/06/2020,24,6,2020,40,0,Sri_Lanka,LK,LKA,21323734,Asia,0.61902854\r
-23/06/2020,23,6,2020,1,0,Sri_Lanka,LK,LKA,21323734,Asia,0.44082336\r
-22/06/2020,22,6,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0.53930517\r
-21/06/2020,21,6,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0.63778698\r
-20/06/2020,20,6,2020,3,0,Sri_Lanka,LK,LKA,21323734,Asia,0.69875192\r
-19/06/2020,19,6,2020,23,0,Sri_Lanka,LK,LKA,21323734,Asia,0.70344153\r
-18/06/2020,18,6,2020,9,0,Sri_Lanka,LK,LKA,21323734,Asia,0.82068178\r
-17/06/2020,17,6,2020,10,0,Sri_Lanka,LK,LKA,21323734,Asia,1.08798956\r
-16/06/2020,16,6,2020,16,0,Sri_Lanka,LK,LKA,21323734,Asia,1.22867787\r
-15/06/2020,15,6,2020,5,0,Sri_Lanka,LK,LKA,21323734,Asia,1.20054021\r
-14/06/2020,14,6,2020,4,0,Sri_Lanka,LK,LKA,21323734,Asia,1.23805709\r
-13/06/2020,13,6,2020,3,0,Sri_Lanka,LK,LKA,21323734,Asia,1.51005448\r
-12/06/2020,12,6,2020,8,0,Sri_Lanka,LK,LKA,21323734,Asia,1.62729473\r
-11/06/2020,11,6,2020,10,0,Sri_Lanka,LK,LKA,21323734,Asia,1.87584407\r
-10/06/2020,10,6,2020,2,0,Sri_Lanka,LK,LKA,21323734,Asia,2.5323895\r
-09/06/2020,9,6,2020,22,0,Sri_Lanka,LK,LKA,21323734,Asia,3.16548687\r
-08/06/2020,8,6,2020,21,0,Sri_Lanka,LK,LKA,21323734,Asia,3.25458946\r
-07/06/2020,7,6,2020,13,0,Sri_Lanka,LK,LKA,21323734,Asia,3.39996738\r
-06/06/2020,6,6,2020,4,0,Sri_Lanka,LK,LKA,21323734,Asia,3.43748426\r
-05/06/2020,5,6,2020,48,0,Sri_Lanka,LK,LKA,21323734,Asia,3.47969075\r
-04/06/2020,4,6,2020,66,0,Sri_Lanka,LK,LKA,21323734,Asia,3.38120894\r
-03/06/2020,3,6,2020,40,0,Sri_Lanka,LK,LKA,21323734,Asia,3.07638428\r
-02/06/2020,2,6,2020,10,1,Sri_Lanka,LK,LKA,21323734,Asia,3.05293623\r
-01/06/2020,1,6,2020,13,0,Sri_Lanka,LK,LKA,21323734,Asia,3.05762584\r
-31/05/2020,31,5,2020,62,0,Sri_Lanka,LK,LKA,21323734,Asia,3.09514272\r
-30/05/2020,30,5,2020,28,0,Sri_Lanka,LK,LKA,21323734,Asia,2.92162714\r
-29/05/2020,29,5,2020,61,0,Sri_Lanka,LK,LKA,21323734,Asia,2.83721416\r
-28/05/2020,28,5,2020,150,0,Sri_Lanka,LK,LKA,21323734,Asia,2.59804404\r
-27/05/2020,27,5,2020,137,0,Sri_Lanka,LK,LKA,21323734,Asia,2.01653238\r
-26/05/2020,26,5,2020,41,1,Sri_Lanka,LK,LKA,21323734,Asia,1.46784799\r
-25/05/2020,25,5,2020,52,0,Sri_Lanka,LK,LKA,21323734,Asia,1.30371163\r
-24/05/2020,24,5,2020,21,0,Sri_Lanka,LK,LKA,21323734,Asia,1.13488566\r
-23/05/2020,23,5,2020,13,0,Sri_Lanka,LK,LKA,21323734,Asia,1.09267917\r
-22/05/2020,22,5,2020,27,0,Sri_Lanka,LK,LKA,21323734,Asia,1.08329995\r
-21/05/2020,21,5,2020,1,0,Sri_Lanka,LK,LKA,21323734,Asia,1.08329995\r
-20/05/2020,20,5,2020,35,0,Sri_Lanka,LK,LKA,21323734,Asia,1.20054021\r
-19/05/2020,19,5,2020,11,0,Sri_Lanka,LK,LKA,21323734,Asia,1.11143761\r
-18/05/2020,18,5,2020,21,0,Sri_Lanka,LK,LKA,21323734,Asia,1.23336748\r
-17/05/2020,17,5,2020,25,0,Sri_Lanka,LK,LKA,21323734,Asia,1.1958506\r
-16/05/2020,16,5,2020,10,0,Sri_Lanka,LK,LKA,21323734,Asia,1.14895449\r
-15/05/2020,15,5,2020,10,0,Sri_Lanka,LK,LKA,21323734,Asia,1.21929865\r
-14/05/2020,14,5,2020,26,0,Sri_Lanka,LK,LKA,21323734,Asia,1.24743631\r
-13/05/2020,13,5,2020,20,0,Sri_Lanka,LK,LKA,21323734,Asia,1.26619475\r
-12/05/2020,12,5,2020,6,0,Sri_Lanka,LK,LKA,21323734,Asia,1.31778046\r
-11/05/2020,11,5,2020,16,0,Sri_Lanka,LK,LKA,21323734,Asia,1.59446746\r
-10/05/2020,10,5,2020,12,0,Sri_Lanka,LK,LKA,21323734,Asia,1.80549992\r
-09/05/2020,9,5,2020,11,0,Sri_Lanka,LK,LKA,21323734,Asia,1.94618822\r
-08/05/2020,8,5,2020,27,0,Sri_Lanka,LK,LKA,21323734,Asia,2.13846224\r
-07/05/2020,7,5,2020,26,0,Sri_Lanka,LK,LKA,21323734,Asia,2.19004795\r
-06/05/2020,6,5,2020,16,1,Sri_Lanka,LK,LKA,21323734,Asia,2.16191029\r
-05/05/2020,5,5,2020,37,1,Sri_Lanka,LK,LKA,21323734,Asia,2.11501419\r
-04/05/2020,4,5,2020,13,0,Sri_Lanka,LK,LKA,21323734,Asia,1.98370511\r
-03/05/2020,3,5,2020,15,0,Sri_Lanka,LK,LKA,21323734,Asia,2.11501419\r
-02/05/2020,2,5,2020,25,0,Sri_Lanka,LK,LKA,21323734,Asia,2.09156614\r
-01/05/2020,1,5,2020,16,0,Sri_Lanka,LK,LKA,21323734,Asia,2.00246355\r
-30/04/2020,30,4,2020,30,0,Sri_Lanka,LK,LKA,21323734,Asia,1.93211939\r
-29/04/2020,29,4,2020,31,0,Sri_Lanka,LK,LKA,21323734,Asia,1.81018953\r
-28/04/2020,28,4,2020,65,0,Sri_Lanka,LK,LKA,21323734,Asia,1.73515577\r
-27/04/2020,27,4,2020,61,0,Sri_Lanka,LK,LKA,21323734,Asia,1.46784799\r
-26/04/2020,26,4,2020,42,0,Sri_Lanka,LK,LKA,21323734,Asia,1.23336748\r
-25/04/2020,25,4,2020,52,0,Sri_Lanka,LK,LKA,21323734,Asia,1.04578307\r
-24/04/2020,24,4,2020,38,0,Sri_Lanka,LK,LKA,21323734,Asia,0.83475061\r
-23/04/2020,23,4,2020,20,0,Sri_Lanka,LK,LKA,21323734,Asia,0.66123504\r
-22/04/2020,22,4,2020,6,0,Sri_Lanka,LK,LKA,21323734,Asia,0.58620127\r
-21/04/2020,21,4,2020,9,0,Sri_Lanka,LK,LKA,21323734,Asia,0.59089088\r
-20/04/2020,20,4,2020,41,0,Sri_Lanka,LK,LKA,21323734,Asia,0.60495971\r
-19/04/2020,19,4,2020,10,0,Sri_Lanka,LK,LKA,21323734,Asia,0.44551297\r
-18/04/2020,18,4,2020,6,0,Sri_Lanka,LK,LKA,21323734,Asia,0.43613375\r
-17/04/2020,17,4,2020,1,0,Sri_Lanka,LK,LKA,21323734,Asia,0.42206492\r
-16/04/2020,16,4,2020,4,0,Sri_Lanka,LK,LKA,21323734,Asia,0.44082336\r
-15/04/2020,15,4,2020,15,0,Sri_Lanka,LK,LKA,21323734,Asia,0.52054673\r
-14/04/2020,14,4,2020,8,0,Sri_Lanka,LK,LKA,21323734,Asia,0.4595818\r
-13/04/2020,13,4,2020,11,0,Sri_Lanka,LK,LKA,21323734,Asia,0.42206492\r
-12/04/2020,12,4,2020,2,0,Sri_Lanka,LK,LKA,21323734,Asia,0.39392725\r
-11/04/2020,11,4,2020,7,0,Sri_Lanka,LK,LKA,21323734,Asia,0.42675453\r
-10/04/2020,10,4,2020,1,0,Sri_Lanka,LK,LKA,21323734,Asia,0.39392725\r
-09/04/2020,9,4,2020,4,1,Sri_Lanka,LK,LKA,21323734,Asia,0.40799609\r
-08/04/2020,8,4,2020,7,1,Sri_Lanka,LK,LKA,21323734,Asia,0.38923764\r
-07/04/2020,7,4,2020,12,0,Sri_Lanka,LK,LKA,21323734,Asia,0.37985842\r
-06/04/2020,6,4,2020,7,0,Sri_Lanka,LK,LKA,21323734,Asia,0.3704792\r
-05/04/2020,5,4,2020,8,1,Sri_Lanka,LK,LKA,21323734,Asia,0.37985842\r
-04/04/2020,4,4,2020,3,1,Sri_Lanka,LK,LKA,21323734,Asia,0.39861687\r
-03/04/2020,3,4,2020,5,1,Sri_Lanka,LK,LKA,21323734,Asia,0.44551297\r
-02/04/2020,2,4,2020,21,0,Sri_Lanka,LK,LKA,21323734,Asia,0.47365063\r
-01/04/2020,1,4,2020,2,1,Sri_Lanka,LK,LKA,21323734,Asia,0.37516881\r
-31/03/2020,31,3,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0.42675453\r
-30/03/2020,30,3,2020,5,0,Sri_Lanka,LK,LKA,21323734,Asia,0.47365063\r
-29/03/2020,29,3,2020,9,1,Sri_Lanka,LK,LKA,21323734,Asia,0.48771946\r
-28/03/2020,28,3,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0.46896102\r
-27/03/2020,27,3,2020,4,0,Sri_Lanka,LK,LKA,21323734,Asia,0.48302985\r
-26/03/2020,26,3,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0.46896102\r
-25/03/2020,25,3,2020,5,0,Sri_Lanka,LK,LKA,21323734,Asia,0.47365063\r
-24/03/2020,24,3,2020,10,0,Sri_Lanka,LK,LKA,21323734,Asia,0.45020258\r
-23/03/2020,23,3,2020,9,0,Sri_Lanka,LK,LKA,21323734,Asia,0.40330648\r
-22/03/2020,22,3,2020,12,0,Sri_Lanka,LK,LKA,21323734,Asia,0.36109998\r
-21/03/2020,21,3,2020,13,0,Sri_Lanka,LK,LKA,21323734,Asia,0.30482466\r
-20/03/2020,20,3,2020,11,0,Sri_Lanka,LK,LKA,21323734,Asia,0.24385973\r
-19/03/2020,19,3,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0.19227402\r
-18/03/2020,18,3,2020,13,0,Sri_Lanka,LK,LKA,21323734,Asia,0.19227402\r
-17/03/2020,17,3,2020,10,0,Sri_Lanka,LK,LKA,21323734,Asia,0.13130908\r
-16/03/2020,16,3,2020,8,0,Sri_Lanka,LK,LKA,21323734,Asia,0.08441298\r
-15/03/2020,15,3,2020,5,0,Sri_Lanka,LK,LKA,21323734,Asia,0.0468961\r
-14/03/2020,14,3,2020,3,0,Sri_Lanka,LK,LKA,21323734,Asia,0.02344805\r
-13/03/2020,13,3,2020,1,0,Sri_Lanka,LK,LKA,21323734,Asia,0.00937922\r
-12/03/2020,12,3,2020,1,0,Sri_Lanka,LK,LKA,21323734,Asia,0.00468961\r
-02/03/2020,2,3,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-01/03/2020,1,3,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-29/02/2020,29,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-28/02/2020,28,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-27/02/2020,27,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-26/02/2020,26,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-25/02/2020,25,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-24/02/2020,24,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-23/02/2020,23,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-22/02/2020,22,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-21/02/2020,21,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-20/02/2020,20,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-19/02/2020,19,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-18/02/2020,18,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-17/02/2020,17,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-16/02/2020,16,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-15/02/2020,15,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-14/02/2020,14,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-13/02/2020,13,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-12/02/2020,12,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-11/02/2020,11,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-10/02/2020,10,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0.00468961\r
-09/02/2020,9,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0.00468961\r
-08/02/2020,8,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0.00468961\r
-07/02/2020,7,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0.00468961\r
-06/02/2020,6,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0.00468961\r
-05/02/2020,5,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0.00468961\r
-04/02/2020,4,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0.00468961\r
-03/02/2020,3,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0.00468961\r
-02/02/2020,2,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0.00468961\r
-01/02/2020,1,2,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0.00468961\r
-31/01/2020,31,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0.00468961\r
-30/01/2020,30,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0.00468961\r
-29/01/2020,29,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0.00468961\r
-28/01/2020,28,1,2020,1,0,Sri_Lanka,LK,LKA,21323734,Asia,0.00468961\r
-27/01/2020,27,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-26/01/2020,26,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-25/01/2020,25,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-24/01/2020,24,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-23/01/2020,23,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-22/01/2020,22,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-21/01/2020,21,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-20/01/2020,20,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-19/01/2020,19,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-18/01/2020,18,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-17/01/2020,17,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-16/01/2020,16,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-15/01/2020,15,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-14/01/2020,14,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-13/01/2020,13,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,0\r
-12/01/2020,12,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,\r
-11/01/2020,11,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,\r
-10/01/2020,10,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,\r
-09/01/2020,9,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,\r
-08/01/2020,8,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,\r
-07/01/2020,7,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,\r
-06/01/2020,6,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,\r
-05/01/2020,5,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,\r
-04/01/2020,4,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,\r
-03/01/2020,3,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,\r
-02/01/2020,2,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,\r
-01/01/2020,1,1,2020,0,0,Sri_Lanka,LK,LKA,21323734,Asia,\r
-31/12/2019,31,12,2019,0,0,Sri_Lanka,LK,LKA,21323734,Asia,\r
-19/08/2020,19,8,2020,75,2,Sudan,SD,SDN,42813237,Africa,1.64668698\r
-18/08/2020,18,8,2020,0,0,Sudan,SD,SDN,42813237,Africa,1.56960802\r
-17/08/2020,17,8,2020,96,5,Sudan,SD,SDN,42813237,Africa,1.56960802\r
-16/08/2020,16,8,2020,152,5,Sudan,SD,SDN,42813237,Africa,1.56493656\r
-15/08/2020,15,8,2020,47,1,Sudan,SD,SDN,42813237,Africa,1.20990618\r
-14/08/2020,14,8,2020,0,0,Sudan,SD,SDN,42813237,Africa,1.44581453\r
-13/08/2020,13,8,2020,82,6,Sudan,SD,SDN,42813237,Africa,1.44581453\r
-12/08/2020,12,8,2020,77,5,Sudan,SD,SDN,42813237,Africa,1.25428498\r
-11/08/2020,11,8,2020,62,8,Sudan,SD,SDN,42813237,Africa,1.24260635\r
-10/08/2020,10,8,2020,0,0,Sudan,SD,SDN,42813237,Africa,1.18888464\r
-09/08/2020,9,8,2020,44,4,Sudan,SD,SDN,42813237,Africa,1.38274992\r
-08/08/2020,8,8,2020,70,6,Sudan,SD,SDN,42813237,Africa,1.43180017\r
-07/08/2020,7,8,2020,0,0,Sudan,SD,SDN,42813237,Africa,1.26829933\r
-06/08/2020,6,8,2020,0,0,Sudan,SD,SDN,42813237,Africa,1.52522922\r
-05/08/2020,5,8,2020,42,11,Sudan,SD,SDN,42813237,Africa,1.52522922\r
-04/08/2020,4,8,2020,0,0,Sudan,SD,SDN,42813237,Africa,1.74245176\r
-03/08/2020,3,8,2020,94,6,Sudan,SD,SDN,42813237,Africa,2.27966879\r
-02/08/2020,2,8,2020,0,0,Sudan,SD,SDN,42813237,Africa,2.24696862\r
-01/08/2020,1,8,2020,148,21,Sudan,SD,SDN,42813237,Africa,2.60900618\r
-31/07/2020,31,7,2020,0,0,Sudan,SD,SDN,42813237,Africa,2.2633187\r
-30/07/2020,30,7,2020,0,0,Sudan,SD,SDN,42813237,Africa,2.2633187\r
-29/07/2020,29,7,2020,72,5,Sudan,SD,SDN,42813237,Africa,2.75615693\r
-28/07/2020,28,7,2020,39,3,Sudan,SD,SDN,42813237,Africa,2.58798465\r
-27/07/2020,27,7,2020,83,2,Sudan,SD,SDN,42813237,Africa,2.65104925\r
-26/07/2020,26,7,2020,65,7,Sudan,SD,SDN,42813237,Africa,2.45718398\r
-25/07/2020,25,7,2020,0,0,Sudan,SD,SDN,42813237,Africa,2.41280518\r
-24/07/2020,24,7,2020,110,2,Sudan,SD,SDN,42813237,Africa,2.52024859\r
-23/07/2020,23,7,2020,0,0,Sudan,SD,SDN,42813237,Africa,2.43616244\r
-22/07/2020,22,7,2020,135,13,Sudan,SD,SDN,42813237,Africa,2.63937062\r
-21/07/2020,21,7,2020,230,13,Sudan,SD,SDN,42813237,Africa,2.86126461\r
-20/07/2020,20,7,2020,80,7,Sudan,SD,SDN,42813237,Africa,2.32404758\r
-19/07/2020,19,7,2020,155,5,Sudan,SD,SDN,42813237,Africa,2.38010501\r
-18/07/2020,18,7,2020,0,0,Sudan,SD,SDN,42813237,Africa,2.01806745\r
-17/07/2020,17,7,2020,0,0,Sudan,SD,SDN,42813237,Africa,2.22828281\r
-16/07/2020,16,7,2020,211,11,Sudan,SD,SDN,42813237,Africa,2.22828281\r
-15/07/2020,15,7,2020,0,0,Sudan,SD,SDN,42813237,Africa,2.47119834\r
-14/07/2020,14,7,2020,66,7,Sudan,SD,SDN,42813237,Africa,2.47119834\r
-13/07/2020,13,7,2020,0,0,Sudan,SD,SDN,42813237,Africa,2.31704041\r
-12/07/2020,12,7,2020,46,1,Sudan,SD,SDN,42813237,Africa,2.31704041\r
-11/07/2020,11,7,2020,46,8,Sudan,SD,SDN,42813237,Africa,2.21193273\r
-10/07/2020,10,7,2020,74,5,Sudan,SD,SDN,42813237,Africa,2.74214258\r
-09/07/2020,9,7,2020,87,14,Sudan,SD,SDN,42813237,Africa,2.79119283\r
-08/07/2020,8,7,2020,230,14,Sudan,SD,SDN,42813237,Africa,2.58798465\r
-07/07/2020,7,7,2020,0,0,Sudan,SD,SDN,42813237,Africa,2.49689132\r
-06/07/2020,6,7,2020,104,4,Sudan,SD,SDN,42813237,Africa,2.77250702\r
-05/07/2020,5,7,2020,0,0,Sudan,SD,SDN,42813237,Africa,2.52959149\r
-04/07/2020,4,7,2020,90,2,Sudan,SD,SDN,42813237,Africa,3.14622321\r
-03/07/2020,3,7,2020,0,0,Sudan,SD,SDN,42813237,Africa,3.62738281\r
-02/07/2020,2,7,2020,315,30,Sudan,SD,SDN,42813237,Africa,3.62738281\r
-01/07/2020,1,7,2020,0,0,Sudan,SD,SDN,42813237,Africa,3.54563239\r
-30/06/2020,30,6,2020,0,0,Sudan,SD,SDN,42813237,Africa,4.76021003\r
-29/06/2020,29,6,2020,0,0,Sudan,SD,SDN,42813237,Africa,4.76021003\r
-28/06/2020,28,6,2020,1,0,Sudan,SD,SDN,42813237,Africa,5.55669266\r
-27/06/2020,27,6,2020,273,16,Sudan,SD,SDN,42813237,Africa,5.55435694\r
-26/06/2020,26,6,2020,95,8,Sudan,SD,SDN,42813237,Africa,5.26472689\r
-25/06/2020,25,6,2020,0,0,Sudan,SD,SDN,42813237,Africa,5.75055794\r
-24/06/2020,24,6,2020,191,15,Sudan,SD,SDN,42813237,Africa,6.18266729\r
-23/06/2020,23,6,2020,118,12,Sudan,SD,SDN,42813237,Africa,5.73654358\r
-22/06/2020,22,6,2020,0,0,Sudan,SD,SDN,42813237,Africa,5.83230836\r
-21/06/2020,21,6,2020,264,15,Sudan,SD,SDN,42813237,Africa,6.34149667\r
-20/06/2020,20,6,2020,296,19,Sudan,SD,SDN,42813237,Africa,6.07755961\r
-19/06/2020,19,6,2020,0,0,Sudan,SD,SDN,42813237,Africa,5.88836579\r
-18/06/2020,18,6,2020,280,10,Sudan,SD,SDN,42813237,Africa,6.32981804\r
-17/06/2020,17,6,2020,520,18,Sudan,SD,SDN,42813237,Africa,5.6758147\r
-16/06/2020,16,6,2020,0,0,Sudan,SD,SDN,42813237,Africa,4.78123156\r
-15/06/2020,15,6,2020,341,26,Sudan,SD,SDN,42813237,Africa,5.12458332\r
-14/06/2020,14,6,2020,0,0,Sudan,SD,SDN,42813237,Africa,4.8559748\r
-13/06/2020,13,6,2020,149,20,Sudan,SD,SDN,42813237,Africa,5.50764241\r
-12/06/2020,12,6,2020,303,24,Sudan,SD,SDN,42813237,Africa,5.5683713\r
-11/06/2020,11,6,2020,185,17,Sudan,SD,SDN,42813237,Africa,5.3277915\r
-10/06/2020,10,6,2020,0,0,Sudan,SD,SDN,42813237,Africa,5.2927556\r
-09/06/2020,9,6,2020,159,13,Sudan,SD,SDN,42813237,Africa,5.64311453\r
-08/06/2020,8,6,2020,218,12,Sudan,SD,SDN,42813237,Africa,5.7201935\r
-07/06/2020,7,6,2020,151,14,Sudan,SD,SDN,42813237,Africa,5.22501954\r
-06/06/2020,6,6,2020,215,19,Sudan,SD,SDN,42813237,Africa,5.45625644\r
-05/06/2020,5,6,2020,189,7,Sudan,SD,SDN,42813237,Africa,5.51464959\r
-04/06/2020,4,6,2020,0,0,Sudan,SD,SDN,42813237,Africa,6.03084509\r
-03/06/2020,3,6,2020,137,9,Sudan,SD,SDN,42813237,Africa,6.35083958\r
-02/06/2020,2,6,2020,147,12,Sudan,SD,SDN,42813237,Africa,6.03084509\r
-01/06/2020,1,6,2020,226,24,Sudan,SD,SDN,42813237,Africa,6.39288265\r
-31/05/2020,31,5,2020,279,29,Sudan,SD,SDN,42813237,Africa,6.62411955\r
-30/05/2020,30,5,2020,175,38,Sudan,SD,SDN,42813237,Africa,5.97245193\r
-29/05/2020,29,5,2020,200,11,Sudan,SD,SDN,42813237,Africa,5.56369984\r
-28/05/2020,28,5,2020,170,14,Sudan,SD,SDN,42813237,Africa,5.43757063\r
-27/05/2020,27,5,2020,150,5,Sudan,SD,SDN,42813237,Africa,5.40720619\r
-26/05/2020,26,5,2020,192,19,Sudan,SD,SDN,42813237,Africa,5.37217029\r
-25/05/2020,25,5,2020,6,0,Sudan,SD,SDN,42813237,Africa,5.30443423\r
-24/05/2020,24,5,2020,250,9,Sudan,SD,SDN,42813237,Africa,5.75522939\r
-23/05/2020,23,5,2020,240,16,Sudan,SD,SDN,42813237,Africa,5.29509133\r
-22/05/2020,22,5,2020,410,10,Sudan,SD,SDN,42813237,Africa,5.15728348\r
-21/05/2020,21,5,2020,137,6,Sudan,SD,SDN,42813237,Africa,4.38182238\r
-20/05/2020,20,5,2020,0,0,Sudan,SD,SDN,42813237,Africa,4.23467163\r
-19/05/2020,19,5,2020,302,8,Sudan,SD,SDN,42813237,Africa,4.46824425\r
-18/05/2020,18,5,2020,325,6,Sudan,SD,SDN,42813237,Africa,3.76285493\r
-17/05/2020,17,5,2020,0,0,Sudan,SD,SDN,42813237,Africa,3.20461637\r
-16/05/2020,16,5,2020,0,0,Sudan,SD,SDN,42813237,Africa,3.5549753\r
-15/05/2020,15,5,2020,146,1,Sudan,SD,SDN,42813237,Africa,3.5549753\r
-14/05/2020,14,5,2020,157,10,Sudan,SD,SDN,42813237,Africa,3.37045293\r
-13/05/2020,13,5,2020,135,6,Sudan,SD,SDN,42813237,Africa,3.13688031\r
-12/05/2020,12,5,2020,163,4,Sudan,SD,SDN,42813237,Africa,2.92199349\r
-11/05/2020,11,5,2020,199,6,Sudan,SD,SDN,42813237,Africa,2.63002772\r
-10/05/2020,10,5,2020,53,5,Sudan,SD,SDN,42813237,Africa,2.22127563\r
-09/05/2020,9,5,2020,181,7,Sudan,SD,SDN,42813237,Africa,2.18857546\r
-08/05/2020,8,5,2020,78,3,Sudan,SD,SDN,42813237,Africa,1.79383773\r
-07/05/2020,7,5,2020,74,4,Sudan,SD,SDN,42813237,Africa,1.66303706\r
-06/05/2020,6,5,2020,100,4,Sudan,SD,SDN,42813237,Africa,1.56727229\r
-05/05/2020,5,5,2020,0,0,Sudan,SD,SDN,42813237,Africa,1.36873556\r
-04/05/2020,4,5,2020,86,0,Sudan,SD,SDN,42813237,Africa,1.42946444\r
-03/05/2020,3,5,2020,150,10,Sudan,SD,SDN,42813237,Africa,1.22859199\r
-02/05/2020,2,5,2020,0,0,Sudan,SD,SDN,42813237,Africa,0.95764775\r
-01/05/2020,1,5,2020,67,3,Sudan,SD,SDN,42813237,Africa,0.95764775\r
-30/04/2020,30,4,2020,57,3,Sudan,SD,SDN,42813237,Africa,0.80115409\r
-29/04/2020,29,4,2020,43,3,Sudan,SD,SDN,42813237,Africa,0.6680177\r
-28/04/2020,28,4,2020,38,1,Sudan,SD,SDN,42813237,Africa,0.57458865\r
-27/04/2020,27,4,2020,24,4,Sudan,SD,SDN,42813237,Africa,0.50918831\r
-26/04/2020,26,4,2020,39,1,Sudan,SD,SDN,42813237,Africa,0.45313089\r
-25/04/2020,25,4,2020,12,3,Sudan,SD,SDN,42813237,Africa,0.37138047\r
-24/04/2020,24,4,2020,22,0,Sudan,SD,SDN,42813237,Africa,0.34568748\r
-23/04/2020,23,4,2020,33,1,Sudan,SD,SDN,42813237,Africa,0.2943015\r
-22/04/2020,22,4,2020,15,0,Sudan,SD,SDN,42813237,Africa,0.21722254\r
-21/04/2020,21,4,2020,26,2,Sudan,SD,SDN,42813237,Africa,0.1868581\r
-20/04/2020,20,4,2020,0,0,Sudan,SD,SDN,42813237,Africa,0.12612922\r
-19/04/2020,19,4,2020,34,5,Sudan,SD,SDN,42813237,Africa,0.13080067\r
-18/04/2020,18,4,2020,0,0,Sudan,SD,SDN,42813237,Africa,0.05839316\r
-17/04/2020,17,4,2020,0,0,Sudan,SD,SDN,42813237,Africa,0.05839316\r
-16/04/2020,16,4,2020,0,0,Sudan,SD,SDN,42813237,Africa,0.05839316\r
-15/04/2020,15,4,2020,3,1,Sudan,SD,SDN,42813237,Africa,0.05839316\r
-14/04/2020,14,4,2020,10,2,Sudan,SD,SDN,42813237,Africa,0.0537217\r
-13/04/2020,13,4,2020,0,0,Sudan,SD,SDN,42813237,Africa,0.03270017\r
-12/04/2020,12,4,2020,4,0,Sudan,SD,SDN,42813237,Africa,0.03270017\r
-11/04/2020,11,4,2020,1,0,Sudan,SD,SDN,42813237,Africa,0.02802871\r
-10/04/2020,10,4,2020,0,0,Sudan,SD,SDN,42813237,Africa,0.02569299\r
-09/04/2020,9,4,2020,0,0,Sudan,SD,SDN,42813237,Africa,0.02569299\r
-08/04/2020,8,4,2020,2,0,Sudan,SD,SDN,42813237,Africa,0.02569299\r
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-25/07/2020,25,7,2020,234,21,Sweden,SE,SWE,10230185,Europe,40.06770161\r
-24/07/2020,24,7,2020,259,9,Sweden,SE,SWE,10230185,Europe,43.30322472\r
-23/07/2020,23,7,2020,338,21,Sweden,SE,SWE,10230185,Europe,45.41462349\r
-22/07/2020,22,7,2020,118,7,Sweden,SE,SWE,10230185,Europe,47.13502248\r
-21/07/2020,21,7,2020,767,20,Sweden,SE,SWE,10230185,Europe,48.74789654\r
-20/07/2020,20,7,2020,0,0,Sweden,SE,SWE,10230185,Europe,57.30101655\r
-19/07/2020,19,7,2020,0,0,Sweden,SE,SWE,10230185,Europe,57.30101655\r
-18/07/2020,18,7,2020,404,26,Sweden,SE,SWE,10230185,Europe,57.30101655\r
-17/07/2020,17,7,2020,385,21,Sweden,SE,SWE,10230185,Europe,60.97641441\r
-16/07/2020,16,7,2020,491,27,Sweden,SE,SWE,10230185,Europe,66.4699612\r
-15/07/2020,15,7,2020,175,9,Sweden,SE,SWE,10230185,Europe,73.80120692\r
-14/07/2020,14,7,2020,928,10,Sweden,SE,SWE,10230185,Europe,79.75417844\r
-13/07/2020,13,7,2020,0,0,Sweden,SE,SWE,10230185,Europe,95.4137193\r
-12/07/2020,12,7,2020,0,0,Sweden,SE,SWE,10230185,Europe,95.4137193\r
-11/07/2020,11,7,2020,565,26,Sweden,SE,SWE,10230185,Europe,95.4137193\r
-10/07/2020,10,7,2020,475,18,Sweden,SE,SWE,10230185,Europe,102.08026541\r
-09/07/2020,9,7,2020,514,35,Sweden,SE,SWE,10230185,Europe,112.74478419\r
-08/07/2020,8,7,2020,283,14,Sweden,SE,SWE,10230185,Europe,122.25585363\r
-07/07/2020,7,7,2020,1642,13,Sweden,SE,SWE,10230185,Europe,138.11089438\r
-06/07/2020,6,7,2020,0,0,Sweden,SE,SWE,10230185,Europe,150.30031226\r
-05/07/2020,5,7,2020,0,0,Sweden,SE,SWE,10230185,Europe,150.30031226\r
-04/07/2020,4,7,2020,780,9,Sweden,SE,SWE,10230185,Europe,150.30031226\r
-03/07/2020,3,7,2020,947,41,Sweden,SE,SWE,10230185,Europe,142.67581671\r
-02/07/2020,2,7,2020,1241,37,Sweden,SE,SWE,10230185,Europe,147.89566367\r
-01/07/2020,1,7,2020,784,23,Sweden,SE,SWE,10230185,Europe,147.87611368\r
-30/06/2020,30,6,2020,2530,30,Sweden,SE,SWE,10230185,Europe,149.40101279\r
-29/06/2020,29,6,2020,0,0,Sweden,SE,SWE,10230185,Europe,132.18724784\r
-28/06/2020,28,6,2020,0,0,Sweden,SE,SWE,10230185,Europe,138.86356894\r
-27/06/2020,27,6,2020,1247,50,Sweden,SE,SWE,10230185,Europe,151.05298682\r
-26/06/2020,26,6,2020,1566,21,Sweden,SE,SWE,10230185,Europe,152.50946097\r
-25/06/2020,25,6,2020,1487,48,Sweden,SE,SWE,10230185,Europe,151.6101615\r
-24/06/2020,24,6,2020,1905,39,Sweden,SE,SWE,10230185,Europe,145.7744899\r
-23/06/2020,23,6,2020,2889,69,Sweden,SE,SWE,10230185,Europe,134.88514626\r
-22/06/2020,22,6,2020,0,0,Sweden,SE,SWE,10230185,Europe,110.58451045\r
-21/06/2020,21,6,2020,0,0,Sweden,SE,SWE,10230185,Europe,118.82483064\r
-20/06/2020,20,6,2020,0,0,Sweden,SE,SWE,10230185,Europe,128.09152523\r
-19/06/2020,19,6,2020,1481,12,Sweden,SE,SWE,10230185,Europe,138.4139192\r
-18/06/2020,18,6,2020,1239,102,Sweden,SE,SWE,10230185,Europe,134.49414649\r
-17/06/2020,17,6,2020,940,48,Sweden,SE,SWE,10230185,Europe,144.02476593\r
-16/06/2020,16,6,2020,769,17,Sweden,SE,SWE,10230185,Europe,142.41189187\r
-15/06/2020,15,6,2020,683,0,Sweden,SE,SWE,10230185,Europe,137.5537197\r
-14/06/2020,14,6,2020,1247,20,Sweden,SE,SWE,10230185,Europe,135.07087115\r
-13/06/2020,13,6,2020,1396,40,Sweden,SE,SWE,10230185,Europe,129.10812463\r
-12/06/2020,12,6,2020,1474,19,Sweden,SE,SWE,10230185,Europe,122.78370333\r
-11/06/2020,11,6,2020,890,78,Sweden,SE,SWE,10230185,Europe,114.62158309\r
-10/06/2020,10,6,2020,791,23,Sweden,SE,SWE,10230185,Europe,112.25603447\r
-09/06/2020,9,6,2020,403,35,Sweden,SE,SWE,10230185,Europe,110.35968558\r
-08/06/2020,8,6,2020,843,3,Sweden,SE,SWE,10230185,Europe,110.17396069\r
-07/06/2020,7,6,2020,948,17,Sweden,SE,SWE,10230185,Europe,104.58266395\r
-06/06/2020,6,6,2020,1056,77,Sweden,SE,SWE,10230185,Europe,99.0206922\r
-05/06/2020,5,6,2020,1080,20,Sweden,SE,SWE,10230185,Europe,94.92496959\r
-04/06/2020,4,6,2020,2214,74,Sweden,SE,SWE,10230185,Europe,90.71194705\r
-03/06/2020,3,6,2020,775,65,Sweden,SE,SWE,10230185,Europe,76.14720555\r
-02/06/2020,2,6,2020,272,8,Sweden,SE,SWE,10230185,Europe,72.69663256\r
-01/06/2020,1,6,2020,429,0,Sweden,SE,SWE,10230185,Europe,72.32518278\r
-31/05/2020,31,5,2020,637,45,Sweden,SE,SWE,10230185,Europe,72.68685757\r
-30/05/2020,30,5,2020,749,84,Sweden,SE,SWE,10230185,Europe,71.05443352\r
-29/05/2020,29,5,2020,639,46,Sweden,SE,SWE,10230185,Europe,69.84233423\r
-28/05/2020,28,5,2020,648,95,Sweden,SE,SWE,10230185,Europe,70.17468404\r
-27/05/2020,27,5,2020,597,96,Sweden,SE,SWE,10230185,Europe,70.0671591\r
-26/05/2020,26,5,2020,384,31,Sweden,SE,SWE,10230185,Europe,70.11603407\r
-25/05/2020,25,5,2020,271,6,Sweden,SE,SWE,10230185,Europe,69.76413428\r
-24/05/2020,24,5,2020,379,67,Sweden,SE,SWE,10230185,Europe,71.03488353\r
-23/05/2020,23,5,2020,637,54,Sweden,SE,SWE,10230185,Europe,73.74255695\r
-22/05/2020,22,5,2020,649,40,Sweden,SE,SWE,10230185,Europe,73.79143192\r
-21/05/2020,21,5,2020,724,88,Sweden,SE,SWE,10230185,Europe,74.3388316\r
-20/05/2020,20,5,2020,422,45,Sweden,SE,SWE,10230185,Europe,74.12378173\r
-19/05/2020,19,5,2020,234,19,Sweden,SE,SWE,10230185,Europe,74.83735631\r
-18/05/2020,18,5,2020,466,5,Sweden,SE,SWE,10230185,Europe,76.49910534\r
-17/05/2020,17,5,2020,470,28,Sweden,SE,SWE,10230185,Europe,74.24108166\r
-16/05/2020,16,5,2020,625,117,Sweden,SE,SWE,10230185,Europe,75.14038114\r
-15/05/2020,15,5,2020,673,69,Sweden,SE,SWE,10230185,Europe,73.21470726\r
-14/05/2020,14,5,2020,637,147,Sweden,SE,SWE,10230185,Europe,74.35838159\r
-13/05/2020,13,5,2020,602,57,Sweden,SE,SWE,10230185,Europe,74.78848134\r
-12/05/2020,12,5,2020,348,31,Sweden,SE,SWE,10230185,Europe,75.69755581\r
-11/05/2020,11,5,2020,401,5,Sweden,SE,SWE,10230185,Europe,75.09150617\r
-10/05/2020,10,5,2020,656,45,Sweden,SE,SWE,10230185,Europe,75.69755581\r
-09/05/2020,9,5,2020,642,135,Sweden,SE,SWE,10230185,Europe,75.24790607\r
-08/05/2020,8,5,2020,705,99,Sweden,SE,SWE,10230185,Europe,76.9096551\r
-07/05/2020,7,5,2020,702,87,Sweden,SE,SWE,10230185,Europe,77.35930484\r
-06/05/2020,6,5,2020,495,85,Sweden,SE,SWE,10230185,Europe,77.16380496\r
-05/05/2020,5,5,2020,404,90,Sweden,SE,SWE,10230185,Europe,77.65255467\r
-04/05/2020,4,5,2020,235,10,Sweden,SE,SWE,10230185,Europe,77.53525474\r
-03/05/2020,3,5,2020,562,16,Sweden,SE,SWE,10230185,Europe,80.74145287\r
-02/05/2020,2,5,2020,428,67,Sweden,SE,SWE,10230185,Europe,81.17155262\r
-01/05/2020,1,5,2020,790,124,Sweden,SE,SWE,10230185,Europe,83.5957512\r
-30/04/2020,30,4,2020,681,107,Sweden,SE,SWE,10230185,Europe,81.86557721\r
-29/04/2020,29,4,2020,695,81,Sweden,SE,SWE,10230185,Europe,79.92035335\r
-28/04/2020,28,4,2020,286,80,Sweden,SE,SWE,10230185,Europe,77.98490448\r
-27/04/2020,27,4,2020,463,2,Sweden,SE,SWE,10230185,Europe,79.73462845\r
-26/04/2020,26,4,2020,610,40,Sweden,SE,SWE,10230185,Europe,78.4541042\r
-25/04/2020,25,4,2020,812,131,Sweden,SE,SWE,10230185,Europe,77.04650502\r
-24/04/2020,24,4,2020,751,84,Sweden,SE,SWE,10230185,Europe,74.42680655\r
-23/04/2020,23,4,2020,682,172,Sweden,SE,SWE,10230185,Europe,74.14333172\r
-22/04/2020,22,4,2020,545,185,Sweden,SE,SWE,10230185,Europe,74.57343147\r
-21/04/2020,21,4,2020,392,40,Sweden,SE,SWE,10230185,Europe,74.0064818\r
-20/04/2020,20,4,2020,563,29,Sweden,SE,SWE,10230185,Europe,73.85008189\r
-19/04/2020,19,4,2020,606,111,Sweden,SE,SWE,10230185,Europe,72.12968289\r
-18/04/2020,18,4,2020,676,67,Sweden,SE,SWE,10230185,Europe,69.77390927\r
-17/04/2020,17,4,2020,613,130,Sweden,SE,SWE,10230185,Europe,69.14830963\r
-16/04/2020,16,4,2020,482,170,Sweden,SE,SWE,10230185,Europe,68.22946017\r
-15/04/2020,15,4,2020,497,114,Sweden,SE,SWE,10230185,Europe,68.52271\r
-14/04/2020,14,4,2020,465,20,Sweden,SE,SWE,10230185,Europe,67.64296051\r
-13/04/2020,13,4,2020,332,12,Sweden,SE,SWE,10230185,Europe,66.3037863\r
-12/04/2020,12,4,2020,466,17,Sweden,SE,SWE,10230185,Europe,65.53156175\r
-11/04/2020,11,4,2020,544,77,Sweden,SE,SWE,10230185,Europe,64.89618712\r
-10/04/2020,10,4,2020,722,106,Sweden,SE,SWE,10230185,Europe,61.92458885\r
-09/04/2020,9,4,2020,726,96,Sweden,SE,SWE,10230185,Europe,57.76044128\r
-08/04/2020,8,4,2020,487,114,Sweden,SE,SWE,10230185,Europe,52.99024407\r
-07/04/2020,7,4,2020,376,76,Sweden,SE,SWE,10230185,Europe,50.73222039\r
-06/04/2020,6,4,2020,387,28,Sweden,SE,SWE,10230185,Europe,48.1320719\r
-05/04/2020,5,4,2020,365,40,Sweden,SE,SWE,10230185,Europe,45.9131482\r
-04/04/2020,4,4,2020,612,51,Sweden,SE,SWE,10230185,Europe,43.54759958\r
-03/04/2020,3,4,2020,519,43,Sweden,SE,SWE,10230185,Europe,39.52030193\r
-02/04/2020,2,4,2020,512,59,Sweden,SE,SWE,10230185,Europe,35.6396292\r
-01/04/2020,1,4,2020,407,34,Sweden,SE,SWE,10230185,Europe,31.94468135\r
-31/03/2020,31,3,2020,328,36,Sweden,SE,SWE,10230185,Europe,28.41590841\r
-30/03/2020,30,3,2020,253,8,Sweden,SE,SWE,10230185,Europe,26.07968478\r
-29/03/2020,29,3,2020,401,10,Sweden,SE,SWE,10230185,Europe,24.6623106\r
-28/03/2020,28,3,2020,240,26,Sweden,SE,SWE,10230185,Europe,22.19901204\r
-27/03/2020,27,3,2020,296,24,Sweden,SE,SWE,10230185,Europe,21.36813753\r
-26/03/2020,26,3,2020,238,6,Sweden,SE,SWE,10230185,Europe,20.01918831\r
-25/03/2020,25,3,2020,256,11,Sweden,SE,SWE,10230185,Europe,19.0221389\r
-24/03/2020,24,3,2020,110,4,Sweden,SE,SWE,10230185,Europe,17.28218991\r
-23/03/2020,23,3,2020,160,1,Sweden,SE,SWE,10230185,Europe,16.64681528\r
-22/03/2020,22,3,2020,123,4,Sweden,SE,SWE,10230185,Europe,15.49336596\r
-21/03/2020,21,3,2020,200,6,Sweden,SE,SWE,10230185,Europe,14.52564152\r
-20/03/2020,20,3,2020,122,0,Sweden,SE,SWE,10230185,Europe,13.31354223\r
-19/03/2020,19,3,2020,134,2,Sweden,SE,SWE,10230185,Europe,12.37514278\r
-18/03/2020,18,3,2020,46,1,Sweden,SE,SWE,10230185,Europe,11.17281848\r
-17/03/2020,17,3,2020,89,4,Sweden,SE,SWE,10230185,Europe,10.81114369\r
-16/03/2020,16,3,2020,108,2,Sweden,SE,SWE,10230185,Europe,9.95094419\r
-15/03/2020,15,3,2020,149,0,Sweden,SE,SWE,10230185,Europe,8.9050198\r
-14/03/2020,14,3,2020,155,0,Sweden,SE,SWE,10230185,Europe,7.45832065\r
-13/03/2020,13,3,2020,158,0,Sweden,SE,SWE,10230185,Europe,5.9920715\r
-12/03/2020,12,3,2020,136,1,Sweden,SE,SWE,10230185,Europe,4.49649738\r
-11/03/2020,11,3,2020,78,0,Sweden,SE,SWE,10230185,Europe,3.17687315\r
-10/03/2020,10,3,2020,45,0,Sweden,SE,SWE,10230185,Europe,2.41442359\r
-09/03/2020,9,3,2020,42,0,Sweden,SE,SWE,10230185,Europe,1.97454885\r
-08/03/2020,8,3,2020,24,0,Sweden,SE,SWE,10230185,Europe,1.56399909\r
-07/03/2020,7,3,2020,76,0,Sweden,SE,SWE,10230185,Europe,1.32939922\r
-06/03/2020,6,3,2020,26,0,Sweden,SE,SWE,10230185,Europe,0.58649966\r
-05/03/2020,5,3,2020,11,0,Sweden,SE,SWE,10230185,Europe,0.33234981\r
-04/03/2020,4,3,2020,9,0,Sweden,SE,SWE,10230185,Europe,0.22482487\r
-03/03/2020,3,3,2020,1,0,Sweden,SE,SWE,10230185,Europe,0.13684992\r
-02/03/2020,2,3,2020,1,0,Sweden,SE,SWE,10230185,Europe,0.12707493\r
-01/03/2020,1,3,2020,1,0,Sweden,SE,SWE,10230185,Europe,0.11729993\r
-29/02/2020,29,2,2020,5,0,Sweden,SE,SWE,10230185,Europe,0.10752494\r
-28/02/2020,28,2,2020,5,0,Sweden,SE,SWE,10230185,Europe,0.05864997\r
-27/02/2020,27,2,2020,1,0,Sweden,SE,SWE,10230185,Europe,0.00977499\r
-26/02/2020,26,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-25/02/2020,25,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-24/02/2020,24,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-23/02/2020,23,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-22/02/2020,22,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-21/02/2020,21,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-20/02/2020,20,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-19/02/2020,19,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-18/02/2020,18,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-17/02/2020,17,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-16/02/2020,16,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-15/02/2020,15,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-14/02/2020,14,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0.00977499\r
-13/02/2020,13,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0.00977499\r
-12/02/2020,12,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0.00977499\r
-11/02/2020,11,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0.00977499\r
-10/02/2020,10,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0.00977499\r
-09/02/2020,9,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0.00977499\r
-08/02/2020,8,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0.00977499\r
-07/02/2020,7,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0.00977499\r
-06/02/2020,6,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0.00977499\r
-05/02/2020,5,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0.00977499\r
-04/02/2020,4,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0.00977499\r
-03/02/2020,3,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0.00977499\r
-02/02/2020,2,2,2020,0,0,Sweden,SE,SWE,10230185,Europe,0.00977499\r
-01/02/2020,1,2,2020,1,0,Sweden,SE,SWE,10230185,Europe,0.00977499\r
-31/01/2020,31,1,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-30/01/2020,30,1,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-29/01/2020,29,1,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-28/01/2020,28,1,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-27/01/2020,27,1,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-26/01/2020,26,1,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-25/01/2020,25,1,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-24/01/2020,24,1,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-23/01/2020,23,1,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-22/01/2020,22,1,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-21/01/2020,21,1,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-20/01/2020,20,1,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-19/01/2020,19,1,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-18/01/2020,18,1,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-17/01/2020,17,1,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-16/01/2020,16,1,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-15/01/2020,15,1,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-14/01/2020,14,1,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-13/01/2020,13,1,2020,0,0,Sweden,SE,SWE,10230185,Europe,0\r
-12/01/2020,12,1,2020,0,0,Sweden,SE,SWE,10230185,Europe,\r
-11/01/2020,11,1,2020,0,0,Sweden,SE,SWE,10230185,Europe,\r
-10/01/2020,10,1,2020,0,0,Sweden,SE,SWE,10230185,Europe,\r
-09/01/2020,9,1,2020,0,0,Sweden,SE,SWE,10230185,Europe,\r
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-29/01/2020,29,1,2020,0,0,Switzerland,CH,CHE,8544527,Europe,0\r
-28/01/2020,28,1,2020,0,0,Switzerland,CH,CHE,8544527,Europe,0\r
-27/01/2020,27,1,2020,0,0,Switzerland,CH,CHE,8544527,Europe,0\r
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-18/01/2020,18,1,2020,0,0,Switzerland,CH,CHE,8544527,Europe,0\r
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-11/01/2020,11,1,2020,0,0,Switzerland,CH,CHE,8544527,Europe,\r
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-07/01/2020,7,1,2020,0,0,Switzerland,CH,CHE,8544527,Europe,\r
-06/01/2020,6,1,2020,0,0,Switzerland,CH,CHE,8544527,Europe,\r
-05/01/2020,5,1,2020,0,0,Switzerland,CH,CHE,8544527,Europe,\r
-04/01/2020,4,1,2020,0,0,Switzerland,CH,CHE,8544527,Europe,\r
-03/01/2020,3,1,2020,0,0,Switzerland,CH,CHE,8544527,Europe,\r
-02/01/2020,2,1,2020,0,0,Switzerland,CH,CHE,8544527,Europe,\r
-01/01/2020,1,1,2020,0,0,Switzerland,CH,CHE,8544527,Europe,\r
-31/12/2019,31,12,2019,0,0,Switzerland,CH,CHE,8544527,Europe,\r
-19/08/2020,19,8,2020,0,0,Syria,SY,SYR,17070132,Asia,5.10833777\r
-18/08/2020,18,8,2020,87,4,Syria,SY,SYR,17070132,Asia,5.37195612\r
-17/08/2020,17,8,2020,84,4,Syria,SY,SYR,17070132,Asia,5.08490503\r
-16/08/2020,16,8,2020,78,2,Syria,SY,SYR,17070132,Asia,4.89744309\r
-15/08/2020,15,8,2020,83,3,Syria,SY,SYR,17070132,Asia,4.55181014\r
-14/08/2020,14,8,2020,100,2,Syria,SY,SYR,17070132,Asia,4.06558075\r
-13/08/2020,13,8,2020,5,0,Syria,SY,SYR,17070132,Asia,3.60278409\r
-12/08/2020,12,8,2020,139,1,Syria,SY,SYR,17070132,Asia,3.70823143\r
-11/08/2020,11,8,2020,0,0,Syria,SY,SYR,17070132,Asia,3.01110735\r
-10/08/2020,10,8,2020,63,2,Syria,SY,SYR,17070132,Asia,3.15170381\r
-09/08/2020,9,8,2020,65,2,Syria,SY,SYR,17070132,Asia,2.91737639\r
-08/08/2020,8,8,2020,116,0,Syria,SY,SYR,17070132,Asia,2.7884963\r
-07/08/2020,7,8,2020,0,0,Syria,SY,SYR,17070132,Asia,2.10894678\r
-06/08/2020,6,8,2020,52,2,Syria,SY,SYR,17070132,Asia,2.24368505\r
-05/08/2020,5,8,2020,45,0,Syria,SY,SYR,17070132,Asia,2.0620813\r
-04/08/2020,4,8,2020,38,2,Syria,SY,SYR,17070132,Asia,1.90391029\r
-03/08/2020,3,8,2020,52,1,Syria,SY,SYR,17070132,Asia,1.83361207\r
-02/08/2020,2,8,2020,19,2,Syria,SY,SYR,17070132,Asia,1.52898642\r
-01/08/2020,1,8,2020,0,0,Syria,SY,SYR,17070132,Asia,1.41768089\r
-31/07/2020,31,7,2020,21,1,Syria,SY,SYR,17070132,Asia,1.52898642\r
-30/07/2020,30,7,2020,23,0,Syria,SY,SYR,17070132,Asia,1.51727005\r
-29/07/2020,29,7,2020,20,0,Syria,SY,SYR,17070132,Asia,1.49383731\r
-28/07/2020,28,7,2020,24,2,Syria,SY,SYR,17070132,Asia,1.50555368\r
-27/07/2020,27,7,2020,23,2,Syria,SY,SYR,17070132,Asia,1.49969549\r
-26/07/2020,26,7,2020,43,1,Syria,SY,SYR,17070132,Asia,1.36495722\r
-25/07/2020,25,7,2020,0,0,Syria,SY,SYR,17070132,Asia,1.11305525\r
-24/07/2020,24,7,2020,23,3,Syria,SY,SYR,17070132,Asia,1.24193533\r
-23/07/2020,23,7,2020,21,1,Syria,SY,SYR,17070132,Asia,1.10719706\r
-22/07/2020,22,7,2020,18,2,Syria,SY,SYR,17070132,Asia,0.98417517\r
-21/07/2020,21,7,2020,26,4,Syria,SY,SYR,17070132,Asia,0.87872783\r
-20/07/2020,20,7,2020,0,0,Syria,SY,SYR,17070132,Asia,0.8084296\r
-19/07/2020,19,7,2020,0,0,Syria,SY,SYR,17070132,Asia,0.92559331\r
-18/07/2020,18,7,2020,19,3,Syria,SY,SYR,17070132,Asia,0.98417517\r
-17/07/2020,17,7,2020,19,0,Syria,SY,SYR,17070132,Asia,0.96660061\r
-16/07/2020,16,7,2020,19,1,Syria,SY,SYR,17070132,Asia,0.96660061\r
-15/07/2020,15,7,2020,22,2,Syria,SY,SYR,17070132,Asia,0.93730968\r
-14/07/2020,14,7,2020,23,3,Syria,SY,SYR,17070132,Asia,0.86701146\r
-13/07/2020,13,7,2020,0,0,Syria,SY,SYR,17070132,Asia,0.8084296\r
-12/07/2020,12,7,2020,0,0,Syria,SY,SYR,17070132,Asia,0.8084296\r
-11/07/2020,11,7,2020,22,2,Syria,SY,SYR,17070132,Asia,0.81428779\r
-10/07/2020,10,7,2020,0,0,Syria,SY,SYR,17070132,Asia,0.76156412\r
-09/07/2020,9,7,2020,0,0,Syria,SY,SYR,17070132,Asia,0.82600416\r
-08/07/2020,8,7,2020,0,0,Syria,SY,SYR,17070132,Asia,0.82600416\r
-07/07/2020,7,7,2020,14,1,Syria,SY,SYR,17070132,Asia,0.89630238\r
-06/07/2020,6,7,2020,20,3,Syria,SY,SYR,17070132,Asia,0.90216057\r
-05/07/2020,5,7,2020,10,0,Syria,SY,SYR,17070132,Asia,0.82014597\r
-04/07/2020,4,7,2020,16,1,Syria,SY,SYR,17070132,Asia,0.82600416\r
-03/07/2020,3,7,2020,19,0,Syria,SY,SYR,17070132,Asia,0.73227319\r
-02/07/2020,2,7,2020,14,0,Syria,SY,SYR,17070132,Asia,0.67369133\r
-01/07/2020,1,7,2020,10,0,Syria,SY,SYR,17070132,Asia,0.59753492\r
-30/06/2020,30,6,2020,13,0,Syria,SY,SYR,17070132,Asia,0.53895307\r
-29/06/2020,29,6,2020,0,0,Syria,SY,SYR,17070132,Asia,0.46279666\r
-28/06/2020,28,6,2020,1,1,Syria,SY,SYR,17070132,Asia,0.50380395\r
-27/06/2020,27,6,2020,13,1,Syria,SY,SYR,17070132,Asia,0.53309488\r
-26/06/2020,26,6,2020,11,0,Syria,SY,SYR,17070132,Asia,0.45693847\r
-25/06/2020,25,6,2020,0,0,Syria,SY,SYR,17070132,Asia,0.46279666\r
-24/06/2020,24,6,2020,12,0,Syria,SY,SYR,17070132,Asia,0.49794577\r
-23/06/2020,23,6,2020,15,0,Syria,SY,SYR,17070132,Asia,0.43936391\r
-22/06/2020,22,6,2020,6,0,Syria,SY,SYR,17070132,Asia,0.36906569\r
-21/06/2020,21,6,2020,11,0,Syria,SY,SYR,17070132,Asia,0.43350573\r
-20/06/2020,20,6,2020,0,0,Syria,SY,SYR,17070132,Asia,0.36906569\r
-19/06/2020,19,6,2020,9,0,Syria,SY,SYR,17070132,Asia,0.36906569\r
-18/06/2020,18,6,2020,1,1,Syria,SY,SYR,17070132,Asia,0.3222002\r
-17/06/2020,17,6,2020,0,0,Syria,SY,SYR,17070132,Asia,0.31634202\r
-16/06/2020,16,6,2020,0,0,Syria,SY,SYR,17070132,Asia,0.31634202\r
-15/06/2020,15,6,2020,7,0,Syria,SY,SYR,17070132,Asia,0.3222002\r
-14/06/2020,14,6,2020,6,0,Syria,SY,SYR,17070132,Asia,0.2811929\r
-13/06/2020,13,6,2020,0,0,Syria,SY,SYR,17070132,Asia,0.24604379\r
-12/06/2020,12,6,2020,12,0,Syria,SY,SYR,17070132,Asia,0.25190198\r
-11/06/2020,11,6,2020,6,0,Syria,SY,SYR,17070132,Asia,0.18160375\r
-10/06/2020,10,6,2020,2,0,Syria,SY,SYR,17070132,Asia,0.14645464\r
-09/06/2020,9,6,2020,3,0,Syria,SY,SYR,17070132,Asia,0.22261105\r
-08/06/2020,8,6,2020,17,0,Syria,SY,SYR,17070132,Asia,0.3222002\r
-07/06/2020,7,6,2020,0,0,Syria,SY,SYR,17070132,Asia,0.31634202\r
-06/06/2020,6,6,2020,0,0,Syria,SY,SYR,17070132,Asia,0.38078206\r
-05/06/2020,5,6,2020,1,0,Syria,SY,SYR,17070132,Asia,0.38664024\r
-04/06/2020,4,6,2020,0,0,Syria,SY,SYR,17070132,Asia,0.38078206\r
-03/06/2020,3,6,2020,0,1,Syria,SY,SYR,17070132,Asia,0.38078206\r
-02/06/2020,2,6,2020,1,1,Syria,SY,SYR,17070132,Asia,0.38078206\r
-01/06/2020,1,6,2020,0,0,Syria,SY,SYR,17070132,Asia,0.37492387\r
-31/05/2020,31,5,2020,0,0,Syria,SY,SYR,17070132,Asia,0.41593117\r
-30/05/2020,30,5,2020,1,0,Syria,SY,SYR,17070132,Asia,0.42178936\r
-29/05/2020,29,5,2020,0,0,Syria,SY,SYR,17070132,Asia,0.42764754\r
-28/05/2020,28,5,2020,0,0,Syria,SY,SYR,17070132,Asia,0.42764754\r
-27/05/2020,27,5,2020,15,0,Syria,SY,SYR,17070132,Asia,0.43350573\r
-26/05/2020,26,5,2020,20,0,Syria,SY,SYR,17070132,Asia,0.34563295\r
-25/05/2020,25,5,2020,16,0,Syria,SY,SYR,17070132,Asia,0.22846924\r
-24/05/2020,24,5,2020,11,0,Syria,SY,SYR,17070132,Asia,0.13473827\r
-23/05/2020,23,5,2020,1,1,Syria,SY,SYR,17070132,Asia,0.07029823\r
-22/05/2020,22,5,2020,0,0,Syria,SY,SYR,17070132,Asia,0.07615641\r
-21/05/2020,21,5,2020,0,0,Syria,SY,SYR,17070132,Asia,0.07615641\r
-20/05/2020,20,5,2020,0,0,Syria,SY,SYR,17070132,Asia,0.0820146\r
-19/05/2020,19,5,2020,0,0,Syria,SY,SYR,17070132,Asia,0.0820146\r
-18/05/2020,18,5,2020,7,0,Syria,SY,SYR,17070132,Asia,0.0820146\r
-17/05/2020,17,5,2020,1,0,Syria,SY,SYR,17070132,Asia,0.0410073\r
-16/05/2020,16,5,2020,2,0,Syria,SY,SYR,17070132,Asia,0.03514911\r
-15/05/2020,15,5,2020,0,0,Syria,SY,SYR,17070132,Asia,0.02929093\r
-14/05/2020,14,5,2020,1,0,Syria,SY,SYR,17070132,Asia,0.02929093\r
-13/05/2020,13,5,2020,0,0,Syria,SY,SYR,17070132,Asia,0.02343274\r
-12/05/2020,12,5,2020,0,0,Syria,SY,SYR,17070132,Asia,0.02343274\r
-11/05/2020,11,5,2020,0,0,Syria,SY,SYR,17070132,Asia,0.02343274\r
-10/05/2020,10,5,2020,0,0,Syria,SY,SYR,17070132,Asia,0.02929093\r
-09/05/2020,9,5,2020,2,0,Syria,SY,SYR,17070132,Asia,0.02929093\r
-08/05/2020,8,5,2020,0,0,Syria,SY,SYR,17070132,Asia,0.01757456\r
-07/05/2020,7,5,2020,1,0,Syria,SY,SYR,17070132,Asia,0.01757456\r
-06/05/2020,6,5,2020,0,0,Syria,SY,SYR,17070132,Asia,0.01171637\r
-05/05/2020,5,5,2020,0,0,Syria,SY,SYR,17070132,Asia,0.02929093\r
-04/05/2020,4,5,2020,0,0,Syria,SY,SYR,17070132,Asia,0.02929093\r
-03/05/2020,3,5,2020,0,0,Syria,SY,SYR,17070132,Asia,0.03514911\r
-02/05/2020,2,5,2020,1,0,Syria,SY,SYR,17070132,Asia,0.03514911\r
-01/05/2020,1,5,2020,0,0,Syria,SY,SYR,17070132,Asia,0.05858186\r
-30/04/2020,30,4,2020,0,0,Syria,SY,SYR,17070132,Asia,0.05858186\r
-29/04/2020,29,4,2020,0,0,Syria,SY,SYR,17070132,Asia,0.0820146\r
-28/04/2020,28,4,2020,0,0,Syria,SY,SYR,17070132,Asia,0.10544734\r
-27/04/2020,27,4,2020,1,0,Syria,SY,SYR,17070132,Asia,0.10544734\r
-26/04/2020,26,4,2020,0,0,Syria,SY,SYR,17070132,Asia,0.09958915\r
-25/04/2020,25,4,2020,0,0,Syria,SY,SYR,17070132,Asia,0.13473827\r
-24/04/2020,24,4,2020,0,0,Syria,SY,SYR,17070132,Asia,0.13473827\r
-23/04/2020,23,4,2020,0,0,Syria,SY,SYR,17070132,Asia,0.13473827\r
-22/04/2020,22,4,2020,3,0,Syria,SY,SYR,17070132,Asia,0.13473827\r
-21/04/2020,21,4,2020,0,0,Syria,SY,SYR,17070132,Asia,0.11716371\r
-20/04/2020,20,4,2020,1,1,Syria,SY,SYR,17070132,Asia,0.11716371\r
-19/04/2020,19,4,2020,0,0,Syria,SY,SYR,17070132,Asia,0.12888008\r
-18/04/2020,18,4,2020,5,0,Syria,SY,SYR,17070132,Asia,0.12888008\r
-17/04/2020,17,4,2020,0,0,Syria,SY,SYR,17070132,Asia,0.09958915\r
-16/04/2020,16,4,2020,4,0,Syria,SY,SYR,17070132,Asia,0.13473827\r
-15/04/2020,15,4,2020,4,0,Syria,SY,SYR,17070132,Asia,0.11130552\r
-14/04/2020,14,4,2020,0,0,Syria,SY,SYR,17070132,Asia,0.08787278\r
-13/04/2020,13,4,2020,0,0,Syria,SY,SYR,17070132,Asia,0.09373097\r
-12/04/2020,12,4,2020,6,0,Syria,SY,SYR,17070132,Asia,0.11716371\r
-11/04/2020,11,4,2020,0,0,Syria,SY,SYR,17070132,Asia,0.0820146\r
-10/04/2020,10,4,2020,0,0,Syria,SY,SYR,17070132,Asia,0.0820146\r
-09/04/2020,9,4,2020,0,0,Syria,SY,SYR,17070132,Asia,0.10544734\r
-08/04/2020,8,4,2020,0,0,Syria,SY,SYR,17070132,Asia,0.10544734\r
-07/04/2020,7,4,2020,0,0,Syria,SY,SYR,17070132,Asia,0.10544734\r
-06/04/2020,6,4,2020,3,0,Syria,SY,SYR,17070132,Asia,0.10544734\r
-05/04/2020,5,4,2020,0,0,Syria,SY,SYR,17070132,Asia,0.09373097\r
-04/04/2020,4,4,2020,0,0,Syria,SY,SYR,17070132,Asia,\r
-03/04/2020,3,4,2020,6,0,Syria,SY,SYR,17070132,Asia,\r
-02/04/2020,2,4,2020,0,0,Syria,SY,SYR,17070132,Asia,\r
-01/04/2020,1,4,2020,0,0,Syria,SY,SYR,17070132,Asia,\r
-31/03/2020,31,3,2020,1,1,Syria,SY,SYR,17070132,Asia,\r
-30/03/2020,30,3,2020,4,1,Syria,SY,SYR,17070132,Asia,\r
-29/03/2020,29,3,2020,0,0,Syria,SY,SYR,17070132,Asia,\r
-28/03/2020,28,3,2020,0,0,Syria,SY,SYR,17070132,Asia,\r
-27/03/2020,27,3,2020,4,0,Syria,SY,SYR,17070132,Asia,\r
-26/03/2020,26,3,2020,0,0,Syria,SY,SYR,17070132,Asia,\r
-25/03/2020,25,3,2020,0,0,Syria,SY,SYR,17070132,Asia,\r
-24/03/2020,24,3,2020,0,0,Syria,SY,SYR,17070132,Asia,\r
-23/03/2020,23,3,2020,1,0,Syria,SY,SYR,17070132,Asia,\r
-19/08/2020,19,8,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.04206297\r
-18/08/2020,18,8,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.03785667\r
-17/08/2020,17,8,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.04206297\r
-16/08/2020,16,8,2020,2,0,Taiwan,TW,CNG1925,23773881,Asia,0.04206297\r
-15/08/2020,15,8,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.03365037\r
-14/08/2020,14,8,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.05888816\r
-13/08/2020,13,8,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.05888816\r
-12/08/2020,12,8,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.05888816\r
-11/08/2020,11,8,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.05468186\r
-10/08/2020,10,8,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.07571334\r
-09/08/2020,9,8,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.09253853\r
-08/08/2020,8,8,2020,2,0,Taiwan,TW,CNG1925,23773881,Asia,0.08833223\r
-07/08/2020,7,8,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.07991964\r
-06/08/2020,6,8,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.09253853\r
-05/08/2020,5,8,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.08833223\r
-04/08/2020,4,8,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.08833223\r
-03/08/2020,3,8,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.08412594\r
-02/08/2020,2,8,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.07991964\r
-01/08/2020,1,8,2020,7,0,Taiwan,TW,CNG1925,23773881,Asia,0.08412594\r
-31/07/2020,31,7,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.05468186\r
-30/07/2020,30,7,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.06309445\r
-29/07/2020,29,7,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.06730075\r
-28/07/2020,28,7,2020,5,0,Taiwan,TW,CNG1925,23773881,Asia,0.06730075\r
-27/07/2020,27,7,2020,4,0,Taiwan,TW,CNG1925,23773881,Asia,0.04626926\r
-26/07/2020,26,7,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.02944408\r
-25/07/2020,25,7,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.02944408\r
-24/07/2020,24,7,2020,3,0,Taiwan,TW,CNG1925,23773881,Asia,0.02944408\r
-23/07/2020,23,7,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.02523778\r
-22/07/2020,22,7,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.02523778\r
-21/07/2020,21,7,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.02523778\r
-20/07/2020,20,7,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.02523778\r
-19/07/2020,19,7,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.02523778\r
-18/07/2020,18,7,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.02103148\r
-17/07/2020,17,7,2020,2,0,Taiwan,TW,CNG1925,23773881,Asia,0.02103148\r
-16/07/2020,16,7,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.01682519\r
-15/07/2020,15,7,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.01682519\r
-14/07/2020,14,7,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.01682519\r
-13/07/2020,13,7,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.01682519\r
-12/07/2020,12,7,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.01682519\r
-11/07/2020,11,7,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.01682519\r
-10/07/2020,10,7,2020,2,0,Taiwan,TW,CNG1925,23773881,Asia,0.01682519\r
-09/07/2020,9,7,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.01261889\r
-08/07/2020,8,7,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.01261889\r
-07/07/2020,7,7,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.01261889\r
-06/07/2020,6,7,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.01261889\r
-05/07/2020,5,7,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.01261889\r
-04/07/2020,4,7,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.01261889\r
-03/07/2020,3,7,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.01261889\r
-02/07/2020,2,7,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.01261889\r
-01/07/2020,1,7,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.00841259\r
-30/06/2020,30,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.00841259\r
-29/06/2020,29,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.01682519\r
-28/06/2020,28,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.01682519\r
-27/06/2020,27,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.01682519\r
-26/06/2020,26,6,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.01682519\r
-25/06/2020,25,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.01261889\r
-24/06/2020,24,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.01261889\r
-23/06/2020,23,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.01261889\r
-22/06/2020,22,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.01261889\r
-21/06/2020,21,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.01261889\r
-20/06/2020,20,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.01261889\r
-19/06/2020,19,6,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.01261889\r
-18/06/2020,18,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.00841259\r
-17/06/2020,17,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.00841259\r
-16/06/2020,16,6,2020,2,0,Taiwan,TW,CNG1925,23773881,Asia,0.00841259\r
-15/06/2020,15,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.0042063\r
-14/06/2020,14,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.0042063\r
-13/06/2020,13,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.0042063\r
-12/06/2020,12,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.00841259\r
-11/06/2020,11,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.00841259\r
-10/06/2020,10,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.00841259\r
-09/06/2020,9,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.00841259\r
-08/06/2020,8,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.00841259\r
-07/06/2020,7,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.00841259\r
-06/06/2020,6,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.00841259\r
-05/06/2020,5,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.00841259\r
-04/06/2020,4,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.00841259\r
-03/06/2020,3,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.01261889\r
-02/06/2020,2,6,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.01261889\r
-01/06/2020,1,6,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.00841259\r
-31/05/2020,31,5,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.00841259\r
-30/05/2020,30,5,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.00841259\r
-29/05/2020,29,5,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.0042063\r
-28/05/2020,28,5,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.0042063\r
-27/05/2020,27,5,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.0042063\r
-26/05/2020,26,5,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.0042063\r
-25/05/2020,25,5,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.0042063\r
-24/05/2020,24,5,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.0042063\r
-23/05/2020,23,5,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.0042063\r
-22/05/2020,22,5,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.0042063\r
-21/05/2020,21,5,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.00841259\r
-20/05/2020,20,5,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.00841259\r
-19/05/2020,19,5,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.00841259\r
-18/05/2020,18,5,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.01682519\r
-17/05/2020,17,5,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.03365037\r
-16/05/2020,16,5,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.04626926\r
-15/05/2020,15,5,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.04626926\r
-14/05/2020,14,5,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.04626926\r
-13/05/2020,13,5,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.04626926\r
-12/05/2020,12,5,2020,0,1,Taiwan,TW,CNG1925,23773881,Asia,0.04626926\r
-11/05/2020,11,5,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.04626926\r
-10/05/2020,10,5,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.04626926\r
-09/05/2020,9,5,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.05047556\r
-08/05/2020,8,5,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.05468186\r
-07/05/2020,7,5,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.05468186\r
-06/05/2020,6,5,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.05468186\r
-05/05/2020,5,5,2020,2,0,Taiwan,TW,CNG1925,23773881,Asia,0.06730075\r
-04/05/2020,4,5,2020,4,0,Taiwan,TW,CNG1925,23773881,Asia,0.06730075\r
-03/05/2020,3,5,2020,3,0,Taiwan,TW,CNG1925,23773881,Asia,0.14301409\r
-02/05/2020,2,5,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.14301409\r
-01/05/2020,1,5,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.14301409\r
-30/04/2020,30,4,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.14301409\r
-29/04/2020,29,4,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.14301409\r
-28/04/2020,28,4,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.15142669\r
-27/04/2020,27,4,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.17245817\r
-26/04/2020,26,4,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.18507706\r
-25/04/2020,25,4,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.20190225\r
-24/04/2020,24,4,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.19769595\r
-23/04/2020,23,4,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.19769595\r
-22/04/2020,22,4,2020,3,0,Taiwan,TW,CNG1925,23773881,Asia,0.20610854\r
-21/04/2020,21,4,2020,2,0,Taiwan,TW,CNG1925,23773881,Asia,0.20610854\r
-20/04/2020,20,4,2020,22,0,Taiwan,TW,CNG1925,23773881,Asia,0.23975892\r
-19/04/2020,19,4,2020,3,0,Taiwan,TW,CNG1925,23773881,Asia,0.14722039\r
-18/04/2020,18,4,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.16825187\r
-17/04/2020,17,4,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.23555262\r
-16/04/2020,16,4,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.23555262\r
-15/04/2020,15,4,2020,2,0,Taiwan,TW,CNG1925,23773881,Asia,0.30705967\r
-14/04/2020,14,4,2020,5,0,Taiwan,TW,CNG1925,23773881,Asia,0.36594782\r
-13/04/2020,13,4,2020,3,0,Taiwan,TW,CNG1925,23773881,Asia,0.34491634\r
-12/04/2020,12,4,2020,5,1,Taiwan,TW,CNG1925,23773881,Asia,0.42904228\r
-11/04/2020,11,4,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.47531154\r
-10/04/2020,10,4,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.53840599\r
-09/04/2020,9,4,2020,3,0,Taiwan,TW,CNG1925,23773881,Asia,0.60570674\r
-08/04/2020,8,4,2020,3,0,Taiwan,TW,CNG1925,23773881,Asia,0.67300749\r
-07/04/2020,7,4,2020,10,0,Taiwan,TW,CNG1925,23773881,Asia,0.74872083\r
-06/04/2020,6,4,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.83284677\r
-05/04/2020,5,4,2020,8,0,Taiwan,TW,CNG1925,23773881,Asia,0.88332233\r
-04/04/2020,4,4,2020,16,0,Taiwan,TW,CNG1925,23773881,Asia,0.9253853\r
-03/04/2020,3,4,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.97165456\r
-02/04/2020,2,4,2020,17,0,Taiwan,TW,CNG1925,23773881,Asia,0.97165456\r
-01/04/2020,1,4,2020,16,0,Taiwan,TW,CNG1925,23773881,Asia,1.03054272\r
-31/03/2020,31,3,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,1.00530494\r
-30/03/2020,30,3,2020,23,3,Taiwan,TW,CNG1925,23773881,Asia,1.03895531\r
-29/03/2020,29,3,2020,16,0,Taiwan,TW,CNG1925,23773881,Asia,0.94221049\r
-28/03/2020,28,3,2020,15,0,Taiwan,TW,CNG1925,23773881,Asia,0.90014752\r
-27/03/2020,27,3,2020,17,0,Taiwan,TW,CNG1925,23773881,Asia,0.85387825\r
-26/03/2020,26,3,2020,19,0,Taiwan,TW,CNG1925,23773881,Asia,0.7865775\r
-25/03/2020,25,3,2020,21,0,Taiwan,TW,CNG1925,23773881,Asia,0.70665787\r
-24/03/2020,24,3,2020,30,0,Taiwan,TW,CNG1925,23773881,Asia,0.63094452\r
-23/03/2020,23,3,2020,12,0,Taiwan,TW,CNG1925,23773881,Asia,0.50475562\r
-22/03/2020,22,3,2020,18,0,Taiwan,TW,CNG1925,23773881,Asia,0.45428006\r
-21/03/2020,21,3,2020,27,1,Taiwan,TW,CNG1925,23773881,Asia,0.37856671\r
-20/03/2020,20,3,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.269203\r
-19/03/2020,19,3,2020,31,0,Taiwan,TW,CNG1925,23773881,Asia,0.27761559\r
-18/03/2020,18,3,2020,10,0,Taiwan,TW,CNG1925,23773881,Asia,0.14722039\r
-17/03/2020,17,3,2020,8,0,Taiwan,TW,CNG1925,23773881,Asia,0.10936372\r
-16/03/2020,16,3,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.07991964\r
-15/03/2020,15,3,2020,6,0,Taiwan,TW,CNG1925,23773881,Asia,0.07991964\r
-14/03/2020,14,3,2020,4,0,Taiwan,TW,CNG1925,23773881,Asia,0.05888816\r
-13/03/2020,13,3,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.06309445\r
-12/03/2020,12,3,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.06730075\r
-11/03/2020,11,3,2020,3,0,Taiwan,TW,CNG1925,23773881,Asia,0.07150705\r
-10/03/2020,10,3,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.06309445\r
-09/03/2020,9,3,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.07150705\r
-08/03/2020,8,3,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.07991964\r
-07/03/2020,7,3,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.07991964\r
-06/03/2020,6,3,2020,2,0,Taiwan,TW,CNG1925,23773881,Asia,0.08412594\r
-05/03/2020,5,3,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.07571334\r
-04/03/2020,4,3,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.08412594\r
-03/03/2020,3,3,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.07991964\r
-02/03/2020,2,3,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.08412594\r
-01/03/2020,1,3,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.09253853\r
-29/02/2020,29,2,2020,5,0,Taiwan,TW,CNG1925,23773881,Asia,0.08833223\r
-28/02/2020,28,2,2020,2,0,Taiwan,TW,CNG1925,23773881,Asia,0.06730075\r
-27/02/2020,27,2,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.05888816\r
-26/02/2020,26,2,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.05468186\r
-25/02/2020,25,2,2020,2,0,Taiwan,TW,CNG1925,23773881,Asia,0.05047556\r
-24/02/2020,24,2,2020,2,0,Taiwan,TW,CNG1925,23773881,Asia,0.04206297\r
-23/02/2020,23,2,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.03365037\r
-22/02/2020,22,2,2020,2,0,Taiwan,TW,CNG1925,23773881,Asia,0.03785667\r
-21/02/2020,21,2,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.03365037\r
-20/02/2020,20,2,2020,2,0,Taiwan,TW,CNG1925,23773881,Asia,0.05468186\r
-19/02/2020,19,2,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.04626926\r
-18/02/2020,18,2,2020,2,0,Taiwan,TW,CNG1925,23773881,Asia,0.05047556\r
-17/02/2020,17,2,2020,2,1,Taiwan,TW,CNG1925,23773881,Asia,0.04206297\r
-16/02/2020,16,2,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.03365037\r
-15/02/2020,15,2,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.03365037\r
-14/02/2020,14,2,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.03785667\r
-13/02/2020,13,2,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.04206297\r
-12/02/2020,12,2,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.04206297\r
-11/02/2020,11,2,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.04626926\r
-10/02/2020,10,2,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.05468186\r
-09/02/2020,9,2,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.06309445\r
-08/02/2020,8,2,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.05888816\r
-07/02/2020,7,2,2020,5,0,Taiwan,TW,CNG1925,23773881,Asia,0.06309445\r
-06/02/2020,6,2,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.04206297\r
-05/02/2020,5,2,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.04206297\r
-04/02/2020,4,2,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.03785667\r
-03/02/2020,3,2,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.04206297\r
-02/02/2020,2,2,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.04206297\r
-01/02/2020,1,2,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.04206297\r
-31/01/2020,31,1,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.03785667\r
-30/01/2020,30,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.03365037\r
-29/01/2020,29,1,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.03365037\r
-28/01/2020,28,1,2020,2,0,Taiwan,TW,CNG1925,23773881,Asia,0.02944408\r
-27/01/2020,27,1,2020,2,0,Taiwan,TW,CNG1925,23773881,Asia,0.02103148\r
-26/01/2020,26,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.01261889\r
-25/01/2020,25,1,2020,2,0,Taiwan,TW,CNG1925,23773881,Asia,0.01261889\r
-24/01/2020,24,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.0042063\r
-23/01/2020,23,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.0042063\r
-22/01/2020,22,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0.0042063\r
-21/01/2020,21,1,2020,1,0,Taiwan,TW,CNG1925,23773881,Asia,0.0042063\r
-20/01/2020,20,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0\r
-19/01/2020,19,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0\r
-18/01/2020,18,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0\r
-17/01/2020,17,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0\r
-16/01/2020,16,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0\r
-15/01/2020,15,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0\r
-14/01/2020,14,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0\r
-13/01/2020,13,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,0\r
-12/01/2020,12,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,\r
-11/01/2020,11,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,\r
-10/01/2020,10,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,\r
-09/01/2020,9,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,\r
-08/01/2020,8,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,\r
-07/01/2020,7,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,\r
-06/01/2020,6,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,\r
-05/01/2020,5,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,\r
-04/01/2020,4,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,\r
-03/01/2020,3,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,\r
-02/01/2020,2,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,\r
-01/01/2020,1,1,2020,0,0,Taiwan,TW,CNG1925,23773881,Asia,\r
-31/12/2019,31,12,2019,0,0,Taiwan,TW,CNG1925,23773881,Asia,\r
-19/08/2020,19,8,2020,32,1,Tajikistan,TJ,TJK,9321023,Asia,5.879183\r
-18/08/2020,18,8,2020,34,0,Tajikistan,TJ,TJK,9321023,Asia,6.01865267\r
-17/08/2020,17,8,2020,36,0,Tajikistan,TJ,TJK,9321023,Asia,6.1152086\r
-16/08/2020,16,8,2020,40,1,Tajikistan,TJ,TJK,9321023,Asia,6.20103609\r
-15/08/2020,15,8,2020,39,0,Tajikistan,TJ,TJK,9321023,Asia,6.22249296\r
-14/08/2020,14,8,2020,38,0,Tajikistan,TJ,TJK,9321023,Asia,6.2654067\r
-13/08/2020,13,8,2020,41,0,Tajikistan,TJ,TJK,9321023,Asia,6.35123419\r
-12/08/2020,12,8,2020,44,1,Tajikistan,TJ,TJK,9321023,Asia,6.3834195\r
-11/08/2020,11,8,2020,82,0,Tajikistan,TJ,TJK,9321023,Asia,6.35123419\r
-10/08/2020,10,8,2020,39,0,Tajikistan,TJ,TJK,9321023,Asia,5.93282518\r
-09/08/2020,9,8,2020,0,0,Tajikistan,TJ,TJK,9321023,Asia,5.96501049\r
-08/08/2020,8,8,2020,41,0,Tajikistan,TJ,TJK,9321023,Asia,6.45851856\r
-07/08/2020,7,8,2020,40,1,Tajikistan,TJ,TJK,9321023,Asia,6.49070386\r
-06/08/2020,6,8,2020,42,0,Tajikistan,TJ,TJK,9321023,Asia,6.54434604\r
-05/08/2020,5,8,2020,45,0,Tajikistan,TJ,TJK,9321023,Asia,6.60871666\r
-04/08/2020,4,8,2020,43,0,Tajikistan,TJ,TJK,9321023,Asia,6.6194451\r
-03/08/2020,3,8,2020,44,1,Tajikistan,TJ,TJK,9321023,Asia,6.6194451\r
-02/08/2020,2,8,2020,42,0,Tajikistan,TJ,TJK,9321023,Asia,6.6194451\r
-01/08/2020,1,8,2020,43,0,Tajikistan,TJ,TJK,9321023,Asia,6.68381571\r
-31/07/2020,31,7,2020,46,0,Tajikistan,TJ,TJK,9321023,Asia,6.70527259\r
-30/07/2020,30,7,2020,44,0,Tajikistan,TJ,TJK,9321023,Asia,6.70527259\r
-29/07/2020,29,7,2020,41,0,Tajikistan,TJ,TJK,9321023,Asia,6.79110008\r
-28/07/2020,28,7,2020,43,1,Tajikistan,TJ,TJK,9321023,Asia,6.86619913\r
-27/07/2020,27,7,2020,42,0,Tajikistan,TJ,TJK,9321023,Asia,6.86619913\r
-26/07/2020,26,7,2020,46,1,Tajikistan,TJ,TJK,9321023,Asia,6.90911287\r
-25/07/2020,25,7,2020,44,0,Tajikistan,TJ,TJK,9321023,Asia,6.94129818\r
-24/07/2020,24,7,2020,45,0,Tajikistan,TJ,TJK,9321023,Asia,6.97348349\r
-23/07/2020,23,7,2020,48,1,Tajikistan,TJ,TJK,9321023,Asia,6.98421193\r
-22/07/2020,22,7,2020,46,0,Tajikistan,TJ,TJK,9321023,Asia,6.99494036\r
-21/07/2020,21,7,2020,43,0,Tajikistan,TJ,TJK,9321023,Asia,7.07003942\r
-20/07/2020,20,7,2020,44,0,Tajikistan,TJ,TJK,9321023,Asia,7.13441003\r
-19/07/2020,19,7,2020,48,1,Tajikistan,TJ,TJK,9321023,Asia,7.24169439\r
-18/07/2020,18,7,2020,45,0,Tajikistan,TJ,TJK,9321023,Asia,7.2738797\r
-17/07/2020,17,7,2020,46,0,Tajikistan,TJ,TJK,9321023,Asia,7.32752188\r
-16/07/2020,16,7,2020,52,0,Tajikistan,TJ,TJK,9321023,Asia,7.40262094\r
-15/07/2020,15,7,2020,48,1,Tajikistan,TJ,TJK,9321023,Asia,7.3918925\r
-14/07/2020,14,7,2020,43,0,Tajikistan,TJ,TJK,9321023,Asia,7.45626312\r
-13/07/2020,13,7,2020,46,0,Tajikistan,TJ,TJK,9321023,Asia,7.54209061\r
-12/07/2020,12,7,2020,49,0,Tajikistan,TJ,TJK,9321023,Asia,7.58500435\r
-11/07/2020,11,7,2020,47,1,Tajikistan,TJ,TJK,9321023,Asia,7.61718966\r
-10/07/2020,10,7,2020,46,0,Tajikistan,TJ,TJK,9321023,Asia,7.71374558\r
-09/07/2020,9,7,2020,49,1,Tajikistan,TJ,TJK,9321023,Asia,7.87467213\r
-08/07/2020,8,7,2020,53,0,Tajikistan,TJ,TJK,9321023,Asia,8.02487023\r
-07/07/2020,7,7,2020,49,0,Tajikistan,TJ,TJK,9321023,Asia,8.03559867\r
-06/07/2020,6,7,2020,54,1,Tajikistan,TJ,TJK,9321023,Asia,8.11069772\r
-05/07/2020,5,7,2020,51,0,Tajikistan,TJ,TJK,9321023,Asia,8.15361147\r
-04/07/2020,4,7,2020,50,0,Tajikistan,TJ,TJK,9321023,Asia,8.26089583\r
-03/07/2020,3,7,2020,53,0,Tajikistan,TJ,TJK,9321023,Asia,8.35745175\r
-02/07/2020,2,7,2020,51,0,Tajikistan,TJ,TJK,9321023,Asia,8.41109393\r
-01/07/2020,1,7,2020,54,0,Tajikistan,TJ,TJK,9321023,Asia,8.51837829\r
-30/06/2020,30,6,2020,51,0,Tajikistan,TJ,TJK,9321023,Asia,8.61493422\r
-29/06/2020,29,6,2020,50,0,Tajikistan,TJ,TJK,9321023,Asia,8.73294702\r
-28/06/2020,28,6,2020,52,0,Tajikistan,TJ,TJK,9321023,Asia,8.88314512\r
-27/06/2020,27,6,2020,56,0,Tajikistan,TJ,TJK,9321023,Asia,9.06552854\r
-26/06/2020,26,6,2020,61,0,Tajikistan,TJ,TJK,9321023,Asia,9.19426977\r
-25/06/2020,25,6,2020,63,0,Tajikistan,TJ,TJK,9321023,Asia,9.30155413\r
-24/06/2020,24,6,2020,54,0,Tajikistan,TJ,TJK,9321023,Asia,9.40883849\r
-23/06/2020,23,6,2020,56,0,Tajikistan,TJ,TJK,9321023,Asia,9.69850627\r
-22/06/2020,22,6,2020,58,0,Tajikistan,TJ,TJK,9321023,Asia,9.95598874\r
-21/06/2020,21,6,2020,61,1,Tajikistan,TJ,TJK,9321023,Asia,10.14910059\r
-20/06/2020,20,6,2020,59,0,Tajikistan,TJ,TJK,9321023,Asia,10.38512618\r
-19/06/2020,19,6,2020,58,0,Tajikistan,TJ,TJK,9321023,Asia,10.62115178\r
-18/06/2020,18,6,2020,61,1,Tajikistan,TJ,TJK,9321023,Asia,12.02657691\r
-17/06/2020,17,6,2020,63,0,Tajikistan,TJ,TJK,9321023,Asia,12.30551625\r
-16/06/2020,16,6,2020,62,0,Tajikistan,TJ,TJK,9321023,Asia,12.52008497\r
-15/06/2020,15,6,2020,64,0,Tajikistan,TJ,TJK,9321023,Asia,13.17451958\r
-14/06/2020,14,6,2020,69,1,Tajikistan,TJ,TJK,9321023,Asia,12.48789967\r
-13/06/2020,13,6,2020,68,0,Tajikistan,TJ,TJK,9321023,Asia,14.36537599\r
-12/06/2020,12,6,2020,71,1,Tajikistan,TJ,TJK,9321023,Asia,13.63584233\r
-11/06/2020,11,6,2020,73,0,Tajikistan,TJ,TJK,9321023,Asia,17.8413893\r
-10/06/2020,10,6,2020,81,0,Tajikistan,TJ,TJK,9321023,Asia,17.05821346\r
-09/06/2020,9,6,2020,80,0,Tajikistan,TJ,TJK,9321023,Asia,16.18921013\r
-08/06/2020,8,6,2020,76,0,Tajikistan,TJ,TJK,9321023,Asia,19.21462912\r
-07/06/2020,7,6,2020,83,0,Tajikistan,TJ,TJK,9321023,Asia,20.40548554\r
-06/06/2020,6,6,2020,81,0,Tajikistan,TJ,TJK,9321023,Asia,21.671441\r
-05/06/2020,5,6,2020,189,1,Tajikistan,TJ,TJK,9321023,Asia,23.05540926\r
-04/06/2020,4,6,2020,87,0,Tajikistan,TJ,TJK,9321023,Asia,23.2163358\r
-03/06/2020,3,6,2020,83,0,Tajikistan,TJ,TJK,9321023,Asia,24.50374814\r
-02/06/2020,2,6,2020,123,0,Tajikistan,TJ,TJK,9321023,Asia,23.61328794\r
-01/06/2020,1,6,2020,0,0,Tajikistan,TJ,TJK,9321023,Asia,24.4930197\r
-31/05/2020,31,5,2020,244,0,Tajikistan,TJ,TJK,9321023,Asia,26.6601638\r
-30/05/2020,30,5,2020,0,0,Tajikistan,TJ,TJK,9321023,Asia,26.23102636\r
-29/05/2020,29,5,2020,463,1,Tajikistan,TJ,TJK,9321023,Asia,28.49472638\r
-28/05/2020,28,5,2020,0,0,Tajikistan,TJ,TJK,9321023,Asia,24.66467468\r
-27/05/2020,27,5,2020,0,0,Tajikistan,TJ,TJK,9321023,Asia,25.43712208\r
-26/05/2020,26,5,2020,362,2,Tajikistan,TJ,TJK,9321023,Asia,26.16665574\r
-25/05/2020,25,5,2020,187,0,Tajikistan,TJ,TJK,9321023,Asia,22.80865523\r
-24/05/2020,24,5,2020,201,0,Tajikistan,TJ,TJK,9321023,Asia,20.80243767\r
-23/05/2020,23,5,2020,210,0,Tajikistan,TJ,TJK,9321023,Asia,19.61158126\r
-22/05/2020,22,5,2020,204,0,Tajikistan,TJ,TJK,9321023,Asia,18.01304428\r
-21/05/2020,21,5,2020,207,3,Tajikistan,TJ,TJK,9321023,Asia,16.70417507\r
-20/05/2020,20,5,2020,0,0,Tajikistan,TJ,TJK,9321023,Asia,15.40603429\r
-19/05/2020,19,5,2020,205,2,Tajikistan,TJ,TJK,9321023,Asia,16.08192577\r
-18/05/2020,18,5,2020,202,3,Tajikistan,TJ,TJK,9321023,Asia,15.53477553\r
-17/05/2020,17,5,2020,204,3,Tajikistan,TJ,TJK,9321023,Asia,13.83968262\r
-16/05/2020,16,5,2020,211,4,Tajikistan,TJ,TJK,9321023,Asia,11.83346506\r
-15/05/2020,15,5,2020,106,6,Tajikistan,TJ,TJK,9321023,Asia,9.56976504\r
-14/05/2020,14,5,2020,72,0,Tajikistan,TJ,TJK,9321023,Asia,8.59347735\r
-13/05/2020,13,5,2020,68,2,Tajikistan,TJ,TJK,9321023,Asia,\r
-12/05/2020,12,5,2020,49,1,Tajikistan,TJ,TJK,9321023,Asia,\r
-11/05/2020,11,5,2020,0,0,Tajikistan,TJ,TJK,9321023,Asia,\r
-10/05/2020,10,5,2020,90,8,Tajikistan,TJ,TJK,9321023,Asia,\r
-09/05/2020,9,5,2020,61,0,Tajikistan,TJ,TJK,9321023,Asia,\r
-08/05/2020,8,5,2020,82,4,Tajikistan,TJ,TJK,9321023,Asia,\r
-07/05/2020,7,5,2020,86,3,Tajikistan,TJ,TJK,9321023,Asia,\r
-06/05/2020,6,5,2020,63,2,Tajikistan,TJ,TJK,9321023,Asia,\r
-05/05/2020,5,5,2020,154,1,Tajikistan,TJ,TJK,9321023,Asia,\r
-04/05/2020,4,5,2020,44,2,Tajikistan,TJ,TJK,9321023,Asia,\r
-03/05/2020,3,5,2020,17,0,Tajikistan,TJ,TJK,9321023,Asia,\r
-02/05/2020,2,5,2020,0,0,Tajikistan,TJ,TJK,9321023,Asia,\r
-01/05/2020,1,5,2020,15,0,Tajikistan,TJ,TJK,9321023,Asia,\r
-19/08/2020,19,8,2020,4,0,Thailand,TH,THA,69625581,Asia,0.0775577\r
-18/08/2020,18,8,2020,0,0,Thailand,TH,THA,69625581,Asia,0.08186646\r
-17/08/2020,17,8,2020,1,0,Thailand,TH,THA,69625581,Asia,0.08330272\r
-16/08/2020,16,8,2020,1,0,Thailand,TH,THA,69625581,Asia,0.08617522\r
-15/08/2020,15,8,2020,0,0,Thailand,TH,THA,69625581,Asia,0.09192024\r
-14/08/2020,14,8,2020,20,0,Thailand,TH,THA,69625581,Asia,0.09479275\r
-13/08/2020,13,8,2020,0,0,Thailand,TH,THA,69625581,Asia,0.07468519\r
-12/08/2020,12,8,2020,5,0,Thailand,TH,THA,69625581,Asia,0.08330272\r
-11/08/2020,11,8,2020,0,0,Thailand,TH,THA,69625581,Asia,0.0775577\r
-10/08/2020,10,8,2020,0,0,Thailand,TH,THA,69625581,Asia,0.08043021\r
-09/08/2020,9,8,2020,3,0,Thailand,TH,THA,69625581,Asia,0.08617522\r
-08/08/2020,8,8,2020,3,0,Thailand,TH,THA,69625581,Asia,0.09479275\r
-07/08/2020,7,8,2020,15,0,Thailand,TH,THA,69625581,Asia,0.09479275\r
-06/08/2020,6,8,2020,2,0,Thailand,TH,THA,69625581,Asia,0.08761148\r
-05/08/2020,5,8,2020,7,0,Thailand,TH,THA,69625581,Asia,0.096229\r
-04/08/2020,4,8,2020,1,0,Thailand,TH,THA,69625581,Asia,0.09479275\r
-03/08/2020,3,8,2020,3,0,Thailand,TH,THA,69625581,Asia,0.10053776\r
-02/08/2020,2,8,2020,5,0,Thailand,TH,THA,69625581,Asia,0.09766525\r
-01/08/2020,1,8,2020,2,0,Thailand,TH,THA,69625581,Asia,0.09479275\r
-31/07/2020,31,7,2020,6,0,Thailand,TH,THA,69625581,Asia,0.10197401\r
-30/07/2020,30,7,2020,6,0,Thailand,TH,THA,69625581,Asia,0.09766525\r
-29/07/2020,29,7,2020,1,0,Thailand,TH,THA,69625581,Asia,0.09479275\r
-28/07/2020,28,7,2020,2,0,Thailand,TH,THA,69625581,Asia,0.10053776\r
-27/07/2020,27,7,2020,4,0,Thailand,TH,THA,69625581,Asia,0.10771903\r
-26/07/2020,26,7,2020,9,0,Thailand,TH,THA,69625581,Asia,0.10628278\r
-25/07/2020,25,7,2020,3,0,Thailand,TH,THA,69625581,Asia,0.09479275\r
-24/07/2020,24,7,2020,10,0,Thailand,TH,THA,69625581,Asia,0.11059154\r
-23/07/2020,23,7,2020,8,0,Thailand,TH,THA,69625581,Asia,0.096229\r
-22/07/2020,22,7,2020,6,0,Thailand,TH,THA,69625581,Asia,0.09192024\r
-21/07/2020,21,7,2020,5,0,Thailand,TH,THA,69625581,Asia,0.08617522\r
-20/07/2020,20,7,2020,1,0,Thailand,TH,THA,69625581,Asia,0.07899395\r
-19/07/2020,19,7,2020,3,0,Thailand,TH,THA,69625581,Asia,0.08473897\r
-18/07/2020,18,7,2020,7,0,Thailand,TH,THA,69625581,Asia,0.08761148\r
-17/07/2020,17,7,2020,3,0,Thailand,TH,THA,69625581,Asia,0.08473897\r
-16/07/2020,16,7,2020,4,0,Thailand,TH,THA,69625581,Asia,0.08186646\r
-15/07/2020,15,7,2020,5,0,Thailand,TH,THA,69625581,Asia,0.08473897\r
-14/07/2020,14,7,2020,7,0,Thailand,TH,THA,69625581,Asia,0.08043021\r
-13/07/2020,13,7,2020,3,0,Thailand,TH,THA,69625581,Asia,0.08330272\r
-12/07/2020,12,7,2020,1,0,Thailand,TH,THA,69625581,Asia,0.07899395\r
-11/07/2020,11,7,2020,14,0,Thailand,TH,THA,69625581,Asia,0.0775577\r
-10/07/2020,10,7,2020,0,0,Thailand,TH,THA,69625581,Asia,0.06319516\r
-09/07/2020,9,7,2020,5,0,Thailand,TH,THA,69625581,Asia,0.06319516\r
-08/07/2020,8,7,2020,2,0,Thailand,TH,THA,69625581,Asia,0.0588864\r
-07/07/2020,7,7,2020,0,0,Thailand,TH,THA,69625581,Asia,0.06319516\r
-06/07/2020,6,7,2020,5,0,Thailand,TH,THA,69625581,Asia,0.06750393\r
-05/07/2020,5,7,2020,5,0,Thailand,TH,THA,69625581,Asia,0.06175891\r
-04/07/2020,4,7,2020,5,0,Thailand,TH,THA,69625581,Asia,0.0560139\r
-03/07/2020,3,7,2020,1,0,Thailand,TH,THA,69625581,Asia,0.0560139\r
-02/07/2020,2,7,2020,6,0,Thailand,TH,THA,69625581,Asia,0.05457764\r
-01/07/2020,1,7,2020,2,0,Thailand,TH,THA,69625581,Asia,0.05457764\r
-30/06/2020,30,6,2020,9,0,Thailand,TH,THA,69625581,Asia,0.05170513\r
-29/06/2020,29,6,2020,0,0,Thailand,TH,THA,69625581,Asia,0.03877885\r
-28/06/2020,28,6,2020,0,0,Thailand,TH,THA,69625581,Asia,0.0402151\r
-27/06/2020,27,6,2020,4,0,Thailand,TH,THA,69625581,Asia,0.04739637\r
-26/06/2020,26,6,2020,0,0,Thailand,TH,THA,69625581,Asia,0.04739637\r
-25/06/2020,25,6,2020,2,0,Thailand,TH,THA,69625581,Asia,0.04739637\r
-24/06/2020,24,6,2020,5,0,Thailand,TH,THA,69625581,Asia,0.04452387\r
-23/06/2020,23,6,2020,3,0,Thailand,TH,THA,69625581,Asia,0.04596012\r
-22/06/2020,22,6,2020,1,0,Thailand,TH,THA,69625581,Asia,0.04165136\r
-21/06/2020,21,6,2020,1,0,Thailand,TH,THA,69625581,Asia,0.05026888\r
-20/06/2020,20,6,2020,5,0,Thailand,TH,THA,69625581,Asia,0.06032266\r
-19/06/2020,19,6,2020,0,0,Thailand,TH,THA,69625581,Asia,0.0560139\r
-18/06/2020,18,6,2020,6,0,Thailand,TH,THA,69625581,Asia,0.05745015\r
-17/06/2020,17,6,2020,0,0,Thailand,TH,THA,69625581,Asia,0.07468519\r
-16/06/2020,16,6,2020,0,0,Thailand,TH,THA,69625581,Asia,0.07612145\r
-15/06/2020,15,6,2020,1,0,Thailand,TH,THA,69625581,Asia,0.0775577\r
-14/06/2020,14,6,2020,5,0,Thailand,TH,THA,69625581,Asia,0.07612145\r
-13/06/2020,13,6,2020,4,0,Thailand,TH,THA,69625581,Asia,0.07612145\r
-12/06/2020,12,6,2020,0,0,Thailand,TH,THA,69625581,Asia,0.08617522\r
-11/06/2020,11,6,2020,0,0,Thailand,TH,THA,69625581,Asia,0.10197401\r
-10/06/2020,10,6,2020,6,0,Thailand,TH,THA,69625581,Asia,0.1149003\r
-09/06/2020,9,6,2020,0,0,Thailand,TH,THA,69625581,Asia,0.11059154\r
-08/06/2020,8,6,2020,7,0,Thailand,TH,THA,69625581,Asia,0.11059154\r
-07/06/2020,7,6,2020,8,0,Thailand,TH,THA,69625581,Asia,0.10341027\r
-06/06/2020,6,6,2020,2,0,Thailand,TH,THA,69625581,Asia,0.09192024\r
-05/06/2020,5,6,2020,1,0,Thailand,TH,THA,69625581,Asia,0.09335649\r
-04/06/2020,4,6,2020,18,0,Thailand,TH,THA,69625581,Asia,0.096229\r
-03/06/2020,3,6,2020,1,1,Thailand,TH,THA,69625581,Asia,0.07037643\r
-02/06/2020,2,6,2020,1,0,Thailand,TH,THA,69625581,Asia,0.07324894\r
-01/06/2020,1,6,2020,0,0,Thailand,TH,THA,69625581,Asia,0.07612145\r
-31/05/2020,31,5,2020,5,0,Thailand,TH,THA,69625581,Asia,0.07612145\r
-30/05/2020,30,5,2020,11,0,Thailand,TH,THA,69625581,Asia,0.07324894\r
-29/05/2020,29,5,2020,11,0,Thailand,TH,THA,69625581,Asia,0.06750393\r
-28/05/2020,28,5,2020,9,0,Thailand,TH,THA,69625581,Asia,0.05314139\r
-27/05/2020,27,5,2020,3,0,Thailand,TH,THA,69625581,Asia,0.0402151\r
-26/05/2020,26,5,2020,0,0,Thailand,TH,THA,69625581,Asia,0.03877885\r
-25/05/2020,25,5,2020,2,1,Thailand,TH,THA,69625581,Asia,0.03877885\r
-24/05/2020,24,5,2020,0,0,Thailand,TH,THA,69625581,Asia,0.05170513\r
-23/05/2020,23,5,2020,3,0,Thailand,TH,THA,69625581,Asia,0.05745015\r
-22/05/2020,22,5,2020,3,0,Thailand,TH,THA,69625581,Asia,0.06463142\r
-21/05/2020,21,5,2020,0,0,Thailand,TH,THA,69625581,Asia,0.06463142\r
-20/05/2020,20,5,2020,3,0,Thailand,TH,THA,69625581,Asia,0.06606767\r
-19/05/2020,19,5,2020,3,0,Thailand,TH,THA,69625581,Asia,0.06319516\r
-18/05/2020,18,5,2020,0,0,Thailand,TH,THA,69625581,Asia,0.08473897\r
-17/05/2020,17,5,2020,3,0,Thailand,TH,THA,69625581,Asia,0.08904773\r
-16/05/2020,16,5,2020,7,0,Thailand,TH,THA,69625581,Asia,0.09335649\r
-15/05/2020,15,5,2020,1,0,Thailand,TH,THA,69625581,Asia,0.08330272\r
-14/05/2020,14,5,2020,0,0,Thailand,TH,THA,69625581,Asia,0.09048398\r
-13/05/2020,13,5,2020,2,0,Thailand,TH,THA,69625581,Asia,0.11346404\r
-12/05/2020,12,5,2020,0,0,Thailand,TH,THA,69625581,Asia,0.11059154\r
-11/05/2020,11,5,2020,11,0,Thailand,TH,THA,69625581,Asia,0.1335716\r
-10/05/2020,10,5,2020,4,1,Thailand,TH,THA,69625581,Asia,0.11777281\r
-09/05/2020,9,5,2020,8,0,Thailand,TH,THA,69625581,Asia,0.20969304\r
-08/05/2020,8,5,2020,3,0,Thailand,TH,THA,69625581,Asia,0.21974682\r
-07/05/2020,7,5,2020,1,1,Thailand,TH,THA,69625581,Asia,0.21543806\r
-06/05/2020,6,5,2020,1,0,Thailand,TH,THA,69625581,Asia,0.25421691\r
-05/05/2020,5,5,2020,18,0,Thailand,TH,THA,69625581,Asia,0.28006948\r
-04/05/2020,4,5,2020,3,0,Thailand,TH,THA,69625581,Asia,0.29299576\r
-03/05/2020,3,5,2020,6,0,Thailand,TH,THA,69625581,Asia,0.33464712\r
-02/05/2020,2,5,2020,0,0,Thailand,TH,THA,69625581,Asia,0.37342597\r
-01/05/2020,1,5,2020,6,0,Thailand,TH,THA,69625581,Asia,0.37342597\r
-30/04/2020,30,4,2020,16,0,Thailand,TH,THA,69625581,Asia,0.40502355\r
-29/04/2020,29,4,2020,0,0,Thailand,TH,THA,69625581,Asia,0.42369485\r
-28/04/2020,28,4,2020,16,3,Thailand,TH,THA,69625581,Asia,0.46678246\r
-27/04/2020,27,4,2020,0,0,Thailand,TH,THA,69625581,Asia,0.49263503\r
-26/04/2020,26,4,2020,68,1,Thailand,TH,THA,69625581,Asia,0.53285013\r
-25/04/2020,25,4,2020,15,0,Thailand,TH,THA,69625581,Asia,0.48258125\r
-24/04/2020,24,4,2020,0,0,Thailand,TH,THA,69625581,Asia,0.52566886\r
-23/04/2020,23,4,2020,28,2,Thailand,TH,THA,69625581,Asia,0.59748155\r
-22/04/2020,22,4,2020,19,1,Thailand,TH,THA,69625581,Asia,0.63482415\r
-21/04/2020,21,4,2020,27,0,Thailand,TH,THA,69625581,Asia,0.76695949\r
-20/04/2020,20,4,2020,32,0,Thailand,TH,THA,69625581,Asia,0.78275828\r
-19/04/2020,19,4,2020,33,0,Thailand,TH,THA,69625581,Asia,0.8100471\r
-18/04/2020,18,4,2020,0,0,Thailand,TH,THA,69625581,Asia,1.03697519\r
-17/04/2020,17,4,2020,28,1,Thailand,TH,THA,69625581,Asia,1.18490932\r
-16/04/2020,16,4,2020,29,3,Thailand,TH,THA,69625581,Asia,1.29406461\r
-15/04/2020,15,4,2020,30,2,Thailand,TH,THA,69625581,Asia,1.42476369\r
-14/04/2020,14,4,2020,34,1,Thailand,TH,THA,69625581,Asia,1.38167608\r
-13/04/2020,13,4,2020,28,2,Thailand,TH,THA,69625581,Asia,1.71057819\r
-12/04/2020,12,4,2020,33,3,Thailand,TH,THA,69625581,Asia,1.87574736\r
-11/04/2020,11,4,2020,45,2,Thailand,TH,THA,69625581,Asia,1.98490265\r
-10/04/2020,10,4,2020,50,1,Thailand,TH,THA,69625581,Asia,1.92027123\r
-09/04/2020,9,4,2020,54,2,Thailand,TH,THA,69625581,Asia,1.97915763\r
-08/04/2020,8,4,2020,111,4,Thailand,TH,THA,69625581,Asia,2.06102409\r
-07/04/2020,7,4,2020,38,0,Thailand,TH,THA,69625581,Asia,2.05527908\r
-06/04/2020,6,4,2020,51,3,Thailand,TH,THA,69625581,Asia,2.15294433\r
-05/04/2020,5,4,2020,191,4,Thailand,TH,THA,69625581,Asia,2.25491835\r
-04/04/2020,4,4,2020,103,4,Thailand,TH,THA,69625581,Asia,2.315241\r
-03/04/2020,3,4,2020,104,3,Thailand,TH,THA,69625581,Asia,2.38848994\r
-02/04/2020,2,4,2020,120,2,Thailand,TH,THA,69625581,Asia,2.28938844\r
-01/04/2020,1,4,2020,0,0,Thailand,TH,THA,69625581,Asia,2.11703799\r
-31/03/2020,31,3,2020,263,3,Thailand,TH,THA,69625581,Asia,2.11703799\r
-30/03/2020,30,3,2020,143,1,Thailand,TH,THA,69625581,Asia,1.82978724\r
-29/03/2020,29,3,2020,109,1,Thailand,TH,THA,69625581,Asia,1.67036308\r
-28/03/2020,28,3,2020,0,0,Thailand,TH,THA,69625581,Asia,1.51381143\r
-27/03/2020,27,3,2020,91,1,Thailand,TH,THA,69625581,Asia,1.53104647\r
-26/03/2020,26,3,2020,111,0,Thailand,TH,THA,69625581,Asia,1.41614617\r
-25/03/2020,25,3,2020,107,0,Thailand,TH,THA,69625581,Asia,1.26964829\r
-24/03/2020,24,3,2020,106,3,Thailand,TH,THA,69625581,Asia,1.1202779\r
-23/03/2020,23,3,2020,122,0,Thailand,TH,THA,69625581,Asia,0.97378002\r
-22/03/2020,22,3,2020,233,0,Thailand,TH,THA,69625581,Asia,0.79999332\r
-21/03/2020,21,3,2020,154,0,Thailand,TH,THA,69625581,Asia,0.46534621\r
-20/03/2020,20,3,2020,35,0,Thailand,TH,THA,69625581,Asia,0.24703564\r
-19/03/2020,19,3,2020,0,0,Thailand,TH,THA,69625581,Asia,0.19676676\r
-18/03/2020,18,3,2020,0,0,Thailand,TH,THA,69625581,Asia,0.19676676\r
-17/03/2020,17,3,2020,63,0,Thailand,TH,THA,69625581,Asia,0.20107552\r
-16/03/2020,16,3,2020,32,0,Thailand,TH,THA,69625581,Asia,0.11346404\r
-15/03/2020,15,3,2020,0,0,Thailand,TH,THA,69625581,Asia,0.06750393\r
-14/03/2020,14,3,2020,12,0,Thailand,TH,THA,69625581,Asia,0.06750393\r
-12/03/2020,12,3,2020,11,0,Thailand,TH,THA,69625581,Asia,0.05026888\r
-11/03/2020,11,3,2020,9,0,Thailand,TH,THA,69625581,Asia,0.03447009\r
-07/03/2020,7,3,2020,3,0,Thailand,TH,THA,69625581,Asia,0.02154381\r
-05/03/2020,5,3,2020,4,0,Thailand,TH,THA,69625581,Asia,0.01723504\r
-02/03/2020,2,3,2020,1,0,Thailand,TH,THA,69625581,Asia,0.01292628\r
-01/03/2020,1,3,2020,0,1,Thailand,TH,THA,69625581,Asia,0.01149003\r
-29/02/2020,29,2,2020,2,0,Thailand,TH,THA,69625581,Asia,0.01149003\r
-28/02/2020,28,2,2020,0,0,Thailand,TH,THA,69625581,Asia,0.01005378\r
-27/02/2020,27,2,2020,0,0,Thailand,TH,THA,69625581,Asia,0.01005378\r
-26/02/2020,26,2,2020,3,0,Thailand,TH,THA,69625581,Asia,0.01005378\r
-25/02/2020,25,2,2020,2,0,Thailand,TH,THA,69625581,Asia,0.00718127\r
-24/02/2020,24,2,2020,0,0,Thailand,TH,THA,69625581,Asia,0.00430876\r
-23/02/2020,23,2,2020,0,0,Thailand,TH,THA,69625581,Asia,0.00430876\r
-22/02/2020,22,2,2020,0,0,Thailand,TH,THA,69625581,Asia,0.00430876\r
-21/02/2020,21,2,2020,0,0,Thailand,TH,THA,69625581,Asia,0.01436254\r
-20/02/2020,20,2,2020,0,0,Thailand,TH,THA,69625581,Asia,0.01436254\r
-19/02/2020,19,2,2020,0,0,Thailand,TH,THA,69625581,Asia,0.01436254\r
-18/02/2020,18,2,2020,1,0,Thailand,TH,THA,69625581,Asia,0.02298006\r
-17/02/2020,17,2,2020,0,0,Thailand,TH,THA,69625581,Asia,0.02154381\r
-16/02/2020,16,2,2020,0,0,Thailand,TH,THA,69625581,Asia,0.02154381\r
-15/02/2020,15,2,2020,1,0,Thailand,TH,THA,69625581,Asia,0.02154381\r
-14/02/2020,14,2,2020,0,0,Thailand,TH,THA,69625581,Asia,0.02728882\r
-13/02/2020,13,2,2020,0,0,Thailand,TH,THA,69625581,Asia,0.02728882\r
-12/02/2020,12,2,2020,1,0,Thailand,TH,THA,69625581,Asia,0.02728882\r
-11/02/2020,11,2,2020,0,0,Thailand,TH,THA,69625581,Asia,0.02585257\r
-10/02/2020,10,2,2020,0,0,Thailand,TH,THA,69625581,Asia,0.03447009\r
-09/02/2020,9,2,2020,0,0,Thailand,TH,THA,69625581,Asia,0.03877885\r
-08/02/2020,8,2,2020,7,0,Thailand,TH,THA,69625581,Asia,0.03877885\r
-07/02/2020,7,2,2020,0,0,Thailand,TH,THA,69625581,Asia,0.03016133\r
-06/02/2020,6,2,2020,0,0,Thailand,TH,THA,69625581,Asia,0.03016133\r
-05/02/2020,5,2,2020,6,0,Thailand,TH,THA,69625581,Asia,0.03016133\r
-04/02/2020,4,2,2020,0,0,Thailand,TH,THA,69625581,Asia,0.02441631\r
-03/02/2020,3,2,2020,0,0,Thailand,TH,THA,69625581,Asia,0.02441631\r
-02/02/2020,2,2,2020,0,0,Thailand,TH,THA,69625581,Asia,0.02441631\r
-01/02/2020,1,2,2020,5,0,Thailand,TH,THA,69625581,Asia,0.02441631\r
-31/01/2020,31,1,2020,0,0,Thailand,TH,THA,69625581,Asia,0.01723504\r
-30/01/2020,30,1,2020,0,0,Thailand,TH,THA,69625581,Asia,0.0186713\r
-29/01/2020,29,1,2020,0,0,Thailand,TH,THA,69625581,Asia,0.0186713\r
-28/01/2020,28,1,2020,6,0,Thailand,TH,THA,69625581,Asia,0.0186713\r
-27/01/2020,27,1,2020,3,0,Thailand,TH,THA,69625581,Asia,0.01005378\r
-26/01/2020,26,1,2020,0,0,Thailand,TH,THA,69625581,Asia,0.00718127\r
-25/01/2020,25,1,2020,1,0,Thailand,TH,THA,69625581,Asia,0.00718127\r
-24/01/2020,24,1,2020,0,0,Thailand,TH,THA,69625581,Asia,0.00574501\r
-23/01/2020,23,1,2020,0,0,Thailand,TH,THA,69625581,Asia,0.00574501\r
-22/01/2020,22,1,2020,2,0,Thailand,TH,THA,69625581,Asia,0.00574501\r
-21/01/2020,21,1,2020,0,0,Thailand,TH,THA,69625581,Asia,0.00287251\r
-20/01/2020,20,1,2020,0,0,Thailand,TH,THA,69625581,Asia,0.00287251\r
-19/01/2020,19,1,2020,0,0,Thailand,TH,THA,69625581,Asia,0.00287251\r
-18/01/2020,18,1,2020,0,0,Thailand,TH,THA,69625581,Asia,0.00287251\r
-17/01/2020,17,1,2020,1,0,Thailand,TH,THA,69625581,Asia,0.00287251\r
-16/01/2020,16,1,2020,0,0,Thailand,TH,THA,69625581,Asia,0.00143625\r
-15/01/2020,15,1,2020,0,0,Thailand,TH,THA,69625581,Asia,0.00143625\r
-14/01/2020,14,1,2020,0,0,Thailand,TH,THA,69625581,Asia,0.00143625\r
-13/01/2020,13,1,2020,1,0,Thailand,TH,THA,69625581,Asia,0.00143625\r
-12/01/2020,12,1,2020,0,0,Thailand,TH,THA,69625581,Asia,\r
-11/01/2020,11,1,2020,0,0,Thailand,TH,THA,69625581,Asia,\r
-10/01/2020,10,1,2020,0,0,Thailand,TH,THA,69625581,Asia,\r
-09/01/2020,9,1,2020,0,0,Thailand,TH,THA,69625581,Asia,\r
-08/01/2020,8,1,2020,0,0,Thailand,TH,THA,69625581,Asia,\r
-07/01/2020,7,1,2020,0,0,Thailand,TH,THA,69625581,Asia,\r
-06/01/2020,6,1,2020,0,0,Thailand,TH,THA,69625581,Asia,\r
-05/01/2020,5,1,2020,0,0,Thailand,TH,THA,69625581,Asia,\r
-04/01/2020,4,1,2020,0,0,Thailand,TH,THA,69625581,Asia,\r
-03/01/2020,3,1,2020,0,0,Thailand,TH,THA,69625581,Asia,\r
-02/01/2020,2,1,2020,0,0,Thailand,TH,THA,69625581,Asia,\r
-01/01/2020,1,1,2020,0,0,Thailand,TH,THA,69625581,Asia,\r
-31/12/2019,31,12,2019,0,0,Thailand,TH,THA,69625581,Asia,\r
-19/08/2020,19,8,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-18/08/2020,18,8,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.07733234\r
-17/08/2020,17,8,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.07733234\r
-16/08/2020,16,8,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.07733234\r
-15/08/2020,15,8,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.07733234\r
-14/08/2020,14,8,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.07733234\r
-13/08/2020,13,8,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.07733234\r
-12/08/2020,12,8,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.07733234\r
-11/08/2020,11,8,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.07733234\r
-10/08/2020,10,8,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.07733234\r
-09/08/2020,9,8,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.07733234\r
-08/08/2020,8,8,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.07733234\r
-07/08/2020,7,8,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.07733234\r
-06/08/2020,6,8,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.07733234\r
-05/08/2020,5,8,2020,1,0,Timor_Leste,TL,TLS,1293120,Asia,0.07733234\r
-04/08/2020,4,8,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-03/08/2020,3,8,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-02/08/2020,2,8,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-01/08/2020,1,8,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-31/07/2020,31,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-30/07/2020,30,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-29/07/2020,29,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-28/07/2020,28,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-27/07/2020,27,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-26/07/2020,26,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-25/07/2020,25,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-24/07/2020,24,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-23/07/2020,23,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-22/07/2020,22,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-21/07/2020,21,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-20/07/2020,20,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-19/07/2020,19,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-18/07/2020,18,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-17/07/2020,17,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-16/07/2020,16,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-15/07/2020,15,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-14/07/2020,14,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-13/07/2020,13,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-12/07/2020,12,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-11/07/2020,11,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-10/07/2020,10,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-09/07/2020,9,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-08/07/2020,8,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-07/07/2020,7,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-06/07/2020,6,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-05/07/2020,5,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-04/07/2020,4,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-03/07/2020,3,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-02/07/2020,2,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-01/07/2020,1,7,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-30/06/2020,30,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-29/06/2020,29,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-28/06/2020,28,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-27/06/2020,27,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-26/06/2020,26,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-25/06/2020,25,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-24/06/2020,24,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-23/06/2020,23,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-22/06/2020,22,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-21/06/2020,21,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-20/06/2020,20,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-19/06/2020,19,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-18/06/2020,18,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-17/06/2020,17,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-16/06/2020,16,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-15/06/2020,15,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-14/06/2020,14,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-13/06/2020,13,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-12/06/2020,12,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-11/06/2020,11,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-10/06/2020,10,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-09/06/2020,9,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-08/06/2020,8,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-07/06/2020,7,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-06/06/2020,6,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-05/06/2020,5,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-04/06/2020,4,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-03/06/2020,3,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-02/06/2020,2,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-01/06/2020,1,6,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-31/05/2020,31,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-30/05/2020,30,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-29/05/2020,29,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-28/05/2020,28,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-27/05/2020,27,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-26/05/2020,26,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-25/05/2020,25,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-24/05/2020,24,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-23/05/2020,23,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-22/05/2020,22,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-21/05/2020,21,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-20/05/2020,20,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-19/05/2020,19,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-18/05/2020,18,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-17/05/2020,17,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-16/05/2020,16,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-15/05/2020,15,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-14/05/2020,14,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-13/05/2020,13,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-12/05/2020,12,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-11/05/2020,11,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-10/05/2020,10,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-09/05/2020,9,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-08/05/2020,8,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.07733234\r
-07/05/2020,7,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.07733234\r
-06/05/2020,6,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.07733234\r
-05/05/2020,5,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.15466469\r
-04/05/2020,4,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.38666172\r
-03/05/2020,3,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.46399406\r
-02/05/2020,2,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.46399406\r
-01/05/2020,1,5,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.46399406\r
-30/04/2020,30,4,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,1.39198218\r
-29/04/2020,29,4,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,1.39198218\r
-28/04/2020,28,4,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,1.54664687\r
-27/04/2020,27,4,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,1.70131156\r
-26/04/2020,26,4,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,1.70131156\r
-25/04/2020,25,4,2020,1,0,Timor_Leste,TL,TLS,1293120,Asia,1.70131156\r
-24/04/2020,24,4,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,1.62397921\r
-23/04/2020,23,4,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,1.70131156\r
-22/04/2020,22,4,2020,1,0,Timor_Leste,TL,TLS,1293120,Asia,1.70131156\r
-21/04/2020,21,4,2020,3,0,Timor_Leste,TL,TLS,1293120,Asia,1.62397921\r
-20/04/2020,20,4,2020,1,0,Timor_Leste,TL,TLS,1293120,Asia,1.39198218\r
-19/04/2020,19,4,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,1.31464984\r
-18/04/2020,18,4,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,1.31464984\r
-17/04/2020,17,4,2020,12,0,Timor_Leste,TL,TLS,1293120,Asia,1.31464984\r
-16/04/2020,16,4,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.38666172\r
-15/04/2020,15,4,2020,2,0,Timor_Leste,TL,TLS,1293120,Asia,0.38666172\r
-14/04/2020,14,4,2020,2,0,Timor_Leste,TL,TLS,1293120,Asia,0.23199703\r
-13/04/2020,13,4,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.07733234\r
-12/04/2020,12,4,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.07733234\r
-11/04/2020,11,4,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.07733234\r
-10/04/2020,10,4,2020,1,0,Timor_Leste,TL,TLS,1293120,Asia,0.07733234\r
-09/04/2020,9,4,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-08/04/2020,8,4,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-07/04/2020,7,4,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-06/04/2020,6,4,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-05/04/2020,5,4,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0\r
-04/04/2020,4,4,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,0.07733234\r
-03/04/2020,3,4,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,\r
-02/04/2020,2,4,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,\r
-01/04/2020,1,4,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,\r
-31/03/2020,31,3,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,\r
-30/03/2020,30,3,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,\r
-29/03/2020,29,3,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,\r
-28/03/2020,28,3,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,\r
-27/03/2020,27,3,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,\r
-26/03/2020,26,3,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,\r
-25/03/2020,25,3,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,\r
-24/03/2020,24,3,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,\r
-23/03/2020,23,3,2020,0,0,Timor_Leste,TL,TLS,1293120,Asia,\r
-22/03/2020,22,3,2020,1,0,Timor_Leste,TL,TLS,1293120,Asia,\r
-19/08/2020,19,8,2020,19,0,Togo,TG,TGO,8082359,Africa,2.28893569\r
-18/08/2020,18,8,2020,7,0,Togo,TG,TGO,8082359,Africa,2.20232732\r
-17/08/2020,17,8,2020,17,0,Togo,TG,TGO,8082359,Africa,2.30130832\r
-16/08/2020,16,8,2020,6,1,Togo,TG,TGO,8082359,Africa,2.12809156\r
-15/08/2020,15,8,2020,20,0,Togo,TG,TGO,8082359,Africa,2.26419044\r
-14/08/2020,14,8,2020,12,0,Togo,TG,TGO,8082359,Africa,2.18995469\r
-13/08/2020,13,8,2020,22,0,Togo,TG,TGO,8082359,Africa,2.42503457\r
-12/08/2020,12,8,2020,3,1,Togo,TG,TGO,8082359,Africa,2.15283681\r
-11/08/2020,11,8,2020,7,2,Togo,TG,TGO,8082359,Africa,2.3879167\r
-10/08/2020,10,8,2020,14,0,Togo,TG,TGO,8082359,Africa,2.37554407\r
-09/08/2020,9,8,2020,18,1,Togo,TG,TGO,8082359,Africa,2.3879167\r
-08/08/2020,8,8,2020,16,0,Togo,TG,TGO,8082359,Africa,2.33842619\r
-07/08/2020,7,8,2020,11,1,Togo,TG,TGO,8082359,Africa,2.27656307\r
-06/08/2020,6,8,2020,13,2,Togo,TG,TGO,8082359,Africa,2.41266195\r
-05/08/2020,5,8,2020,12,0,Togo,TG,TGO,8082359,Africa,2.44977982\r
-04/08/2020,4,8,2020,15,0,Togo,TG,TGO,8082359,Africa,2.3879167\r
-03/08/2020,3,8,2020,3,0,Togo,TG,TGO,8082359,Africa,2.31368094\r
-02/08/2020,2,8,2020,17,0,Togo,TG,TGO,8082359,Africa,2.37554407\r
-01/08/2020,1,8,2020,14,1,Togo,TG,TGO,8082359,Africa,2.37554407\r
-31/07/2020,31,7,2020,31,0,Togo,TG,TGO,8082359,Africa,2.20232732\r
-30/07/2020,30,7,2020,0,0,Togo,TG,TGO,8082359,Africa,1.93012956\r
-29/07/2020,29,7,2020,22,0,Togo,TG,TGO,8082359,Africa,2.04148319\r
-28/07/2020,28,7,2020,6,0,Togo,TG,TGO,8082359,Africa,1.89301168\r
-27/07/2020,27,7,2020,15,1,Togo,TG,TGO,8082359,Africa,1.83114855\r
-26/07/2020,26,7,2020,14,0,Togo,TG,TGO,8082359,Africa,1.67030442\r
-25/07/2020,25,7,2020,11,1,Togo,TG,TGO,8082359,Africa,1.59606867\r
-24/07/2020,24,7,2020,22,0,Togo,TG,TGO,8082359,Africa,1.53420555\r
-23/07/2020,23,7,2020,16,1,Togo,TG,TGO,8082359,Africa,1.37336142\r
-22/07/2020,22,7,2020,7,0,Togo,TG,TGO,8082359,Africa,1.24963516\r
-21/07/2020,21,7,2020,9,0,Togo,TG,TGO,8082359,Africa,1.27438041\r
-20/07/2020,20,7,2020,8,0,Togo,TG,TGO,8082359,Africa,1.16302678\r
-19/07/2020,19,7,2020,17,0,Togo,TG,TGO,8082359,Africa,1.11353628\r
-18/07/2020,18,7,2020,0,0,Togo,TG,TGO,8082359,Africa,0.96506478\r
-17/07/2020,17,7,2020,9,0,Togo,TG,TGO,8082359,Africa,1.01455528\r
-16/07/2020,16,7,2020,9,0,Togo,TG,TGO,8082359,Africa,0.9774374\r
-15/07/2020,15,7,2020,10,0,Togo,TG,TGO,8082359,Africa,1.00218265\r
-14/07/2020,14,7,2020,1,0,Togo,TG,TGO,8082359,Africa,0.96506478\r
-13/07/2020,13,7,2020,2,0,Togo,TG,TGO,8082359,Africa,0.96506478\r
-12/07/2020,12,7,2020,8,0,Togo,TG,TGO,8082359,Africa,1.27438041\r
-11/07/2020,11,7,2020,6,0,Togo,TG,TGO,8082359,Africa,1.47234242\r
-10/07/2020,10,7,2020,9,0,Togo,TG,TGO,8082359,Africa,1.43522454\r
-09/07/2020,9,7,2020,6,0,Togo,TG,TGO,8082359,Africa,1.38573404\r
-08/07/2020,8,7,2020,9,0,Togo,TG,TGO,8082359,Africa,1.39810667\r
-07/07/2020,7,7,2020,0,0,Togo,TG,TGO,8082359,Africa,1.37336142\r
-06/07/2020,6,7,2020,4,0,Togo,TG,TGO,8082359,Africa,1.37336142\r
-05/07/2020,5,7,2020,5,1,Togo,TG,TGO,8082359,Africa,1.42285192\r
-04/07/2020,4,7,2020,4,0,Togo,TG,TGO,8082359,Africa,1.43522454\r
-03/07/2020,3,7,2020,6,0,Togo,TG,TGO,8082359,Africa,1.48471504\r
-02/07/2020,2,7,2020,11,0,Togo,TG,TGO,8082359,Africa,1.44759717\r
-01/07/2020,1,7,2020,7,0,Togo,TG,TGO,8082359,Africa,1.39810667\r
-30/06/2020,30,6,2020,1,0,Togo,TG,TGO,8082359,Africa,1.37336142\r
-29/06/2020,29,6,2020,27,0,Togo,TG,TGO,8082359,Africa,1.37336142\r
-28/06/2020,28,6,2020,24,0,Togo,TG,TGO,8082359,Africa,1.05167316\r
-27/06/2020,27,6,2020,3,0,Togo,TG,TGO,8082359,Africa,0.81659327\r
-26/06/2020,26,6,2020,5,0,Togo,TG,TGO,8082359,Africa,0.79184802\r
-25/06/2020,25,6,2020,7,1,Togo,TG,TGO,8082359,Africa,0.75473015\r
-24/06/2020,24,6,2020,7,0,Togo,TG,TGO,8082359,Africa,0.9279469\r
-23/06/2020,23,6,2020,0,0,Togo,TG,TGO,8082359,Africa,0.89082903\r
-22/06/2020,22,6,2020,8,0,Togo,TG,TGO,8082359,Africa,0.91557428\r
-21/06/2020,21,6,2020,6,0,Togo,TG,TGO,8082359,Africa,0.91557428\r
-20/06/2020,20,6,2020,8,0,Togo,TG,TGO,8082359,Africa,0.86608378\r
-19/06/2020,19,6,2020,3,0,Togo,TG,TGO,8082359,Africa,1.01455528\r
-18/06/2020,18,6,2020,7,0,Togo,TG,TGO,8082359,Africa,1.13828153\r
-17/06/2020,17,6,2020,5,0,Togo,TG,TGO,8082359,Africa,1.13828153\r
-16/06/2020,16,6,2020,1,0,Togo,TG,TGO,8082359,Africa,1.10116366\r
-15/06/2020,15,6,2020,1,0,Togo,TG,TGO,8082359,Africa,1.10116366\r
-14/06/2020,14,6,2020,5,0,Togo,TG,TGO,8082359,Africa,1.20014466\r
-13/06/2020,13,6,2020,1,0,Togo,TG,TGO,8082359,Africa,1.20014466\r
-12/06/2020,12,6,2020,2,0,Togo,TG,TGO,8082359,Africa,1.26200779\r
-11/06/2020,11,6,2020,21,0,Togo,TG,TGO,8082359,Africa,1.57132342\r
-10/06/2020,10,6,2020,4,0,Togo,TG,TGO,8082359,Africa,1.36098879\r
-09/06/2020,9,6,2020,2,0,Togo,TG,TGO,8082359,Africa,1.37336142\r
-08/06/2020,8,6,2020,8,0,Togo,TG,TGO,8082359,Africa,1.41047929\r
-07/06/2020,7,6,2020,2,0,Togo,TG,TGO,8082359,Africa,1.41047929\r
-06/06/2020,6,6,2020,20,0,Togo,TG,TGO,8082359,Africa,1.50946029\r
-05/06/2020,5,6,2020,13,0,Togo,TG,TGO,8082359,Africa,1.37336142\r
-04/06/2020,4,6,2020,7,0,Togo,TG,TGO,8082359,Africa,1.38573404\r
-03/06/2020,3,6,2020,2,0,Togo,TG,TGO,8082359,Africa,1.32387091\r
-02/06/2020,2,6,2020,1,0,Togo,TG,TGO,8082359,Africa,1.39810667\r
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-16/04/2020,16,4,2020,33,1,Tunisia,TN,TUN,11694721,Africa,3.30063453\r
-15/04/2020,15,4,2020,21,0,Tunisia,TN,TUN,11694721,Africa,3.29208367\r
-14/04/2020,14,4,2020,19,3,Tunisia,TN,TUN,11694721,Africa,3.5400588\r
-13/04/2020,13,4,2020,22,3,Tunisia,TN,TUN,11694721,Africa,3.6683218\r
-12/04/2020,12,4,2020,14,3,Tunisia,TN,TUN,11694721,Africa,3.91629693\r
-11/04/2020,11,4,2020,28,0,Tunisia,TN,TUN,11694721,Africa,3.7965848\r
-10/04/2020,10,4,2020,20,2,Tunisia,TN,TUN,11694721,Africa,4.01890733\r
-09/04/2020,9,4,2020,27,1,Tunisia,TN,TUN,11694721,Africa,3.84789\r
-08/04/2020,8,4,2020,22,0,Tunisia,TN,TUN,11694721,Africa,4.12151773\r
-07/04/2020,7,4,2020,21,3,Tunisia,TN,TUN,11694721,Africa,4.14717033\r
-06/04/2020,6,4,2020,58,1,Tunisia,TN,TUN,11694721,Africa,4.08731427\r
-05/04/2020,5,4,2020,40,5,Tunisia,TN,TUN,11694721,Africa,3.719627\r
-04/04/2020,4,4,2020,0,0,Tunisia,TN,TUN,11694721,Africa,3.42889753\r
-03/04/2020,3,4,2020,61,3,Tunisia,TN,TUN,11694721,Africa,3.55716053\r
-02/04/2020,2,4,2020,32,1,Tunisia,TN,TUN,11694721,Africa,3.12106633\r
-01/04/2020,1,4,2020,50,1,Tunisia,TN,TUN,11694721,Africa,2.89019293\r
-31/03/2020,31,3,2020,34,0,Tunisia,TN,TUN,11694721,Africa,2.49685307\r
-30/03/2020,30,3,2020,51,2,Tunisia,TN,TUN,11694721,Africa,2.22322533\r
-29/03/2020,29,3,2020,0,0,Tunisia,TN,TUN,11694721,Africa,1.80423287\r
-28/03/2020,28,3,2020,54,1,Tunisia,TN,TUN,11694721,Africa,1.80423287\r
-27/03/2020,27,3,2020,0,0,Tunisia,TN,TUN,11694721,Africa,1.36813867\r
-26/03/2020,26,3,2020,59,2,Tunisia,TN,TUN,11694721,Africa,1.41944387\r
-25/03/2020,25,3,2020,25,0,Tunisia,TN,TUN,11694721,Africa,0.93204447\r
-24/03/2020,24,3,2020,14,0,Tunisia,TN,TUN,11694721,Africa,0.7439254\r
-23/03/2020,23,3,2020,15,2,Tunisia,TN,TUN,11694721,Africa,0.63276413\r
-22/03/2020,22,3,2020,6,0,Tunisia,TN,TUN,11694721,Africa,0.513052\r
-21/03/2020,21,3,2020,15,1,Tunisia,TN,TUN,11694721,Africa,\r
-20/03/2020,20,3,2020,10,0,Tunisia,TN,TUN,11694721,Africa,\r
-19/03/2020,19,3,2020,5,0,Tunisia,TN,TUN,11694721,Africa,\r
-18/03/2020,18,3,2020,4,0,Tunisia,TN,TUN,11694721,Africa,\r
-17/03/2020,17,3,2020,2,0,Tunisia,TN,TUN,11694721,Africa,\r
-16/03/2020,16,3,2020,2,0,Tunisia,TN,TUN,11694721,Africa,\r
-15/03/2020,15,3,2020,0,0,Tunisia,TN,TUN,11694721,Africa,\r
-14/03/2020,14,3,2020,3,0,Tunisia,TN,TUN,11694721,Africa,\r
-13/03/2020,13,3,2020,6,0,Tunisia,TN,TUN,11694721,Africa,\r
-12/03/2020,12,3,2020,2,0,Tunisia,TN,TUN,11694721,Africa,\r
-11/03/2020,11,3,2020,3,0,Tunisia,TN,TUN,11694721,Africa,\r
-10/03/2020,10,3,2020,1,0,Tunisia,TN,TUN,11694721,Africa,\r
-03/03/2020,3,3,2020,1,0,Tunisia,TN,TUN,11694721,Africa,\r
-19/08/2020,19,8,2020,1263,20,Turkey,TR,TUR,82003882,Asia,20.57341627\r
-18/08/2020,18,8,2020,1233,22,Turkey,TR,TUR,82003882,Asia,20.35391446\r
-17/08/2020,17,8,2020,1192,19,Turkey,TR,TUR,82003882,Asia,20.0636843\r
-16/08/2020,16,8,2020,1256,21,Turkey,TR,TUR,82003882,Asia,19.81369614\r
-15/08/2020,15,8,2020,1226,22,Turkey,TR,TUR,82003882,Asia,19.49663798\r
-14/08/2020,14,8,2020,1243,21,Turkey,TR,TUR,82003882,Asia,19.19909109\r
-13/08/2020,13,8,2020,1212,18,Turkey,TR,TUR,82003882,Asia,18.86252165\r
-12/08/2020,12,8,2020,1183,15,Turkey,TR,TUR,82003882,Asia,18.53326895\r
-11/08/2020,11,8,2020,1193,14,Turkey,TR,TUR,82003882,Asia,18.26498897\r
-10/08/2020,10,8,2020,1182,15,Turkey,TR,TUR,82003882,Asia,17.93085844\r
-09/08/2020,9,8,2020,1172,16,Turkey,TR,TUR,82003882,Asia,17.61989756\r
-08/08/2020,8,8,2020,1185,15,Turkey,TR,TUR,82003882,Asia,17.31381449\r
-07/08/2020,7,8,2020,1153,14,Turkey,TR,TUR,82003882,Asia,17.01138978\r
-06/08/2020,6,8,2020,1178,19,Turkey,TR,TUR,82003882,Asia,16.71872071\r
-05/08/2020,5,8,2020,1083,18,Turkey,TR,TUR,82003882,Asia,16.38215127\r
-04/08/2020,4,8,2020,995,19,Turkey,TR,TUR,82003882,Asia,16.19313583\r
-03/08/2020,3,8,2020,987,18,Turkey,TR,TUR,82003882,Asia,16.11509075\r
-02/08/2020,2,8,2020,996,19,Turkey,TR,TUR,82003882,Asia,16.03826512\r
-01/08/2020,1,8,2020,982,17,Turkey,TR,TUR,82003882,Asia,15.94314767\r
-31/07/2020,31,7,2020,967,15,Turkey,TR,TUR,82003882,Asia,15.87485822\r
-30/07/2020,30,7,2020,942,14,Turkey,TR,TUR,82003882,Asia,15.83339677\r
-29/07/2020,29,7,2020,963,15,Turkey,TR,TUR,82003882,Asia,15.83949404\r
-28/07/2020,28,7,2020,919,17,Turkey,TR,TUR,82003882,Asia,15.87485822\r
-27/07/2020,27,7,2020,927,17,Turkey,TR,TUR,82003882,Asia,15.98338966\r
-26/07/2020,26,7,2020,921,16,Turkey,TR,TUR,82003882,Asia,16.08704329\r
-25/07/2020,25,7,2020,937,17,Turkey,TR,TUR,82003882,Asia,16.20289147\r
-24/07/2020,24,7,2020,913,18,Turkey,TR,TUR,82003882,Asia,16.28337546\r
-23/07/2020,23,7,2020,902,19,Turkey,TR,TUR,82003882,Asia,16.41873491\r
-22/07/2020,22,7,2020,928,18,Turkey,TR,TUR,82003882,Asia,16.58823908\r
-21/07/2020,21,7,2020,931,17,Turkey,TR,TUR,82003882,Asia,16.74067089\r
-20/07/2020,20,7,2020,924,16,Turkey,TR,TUR,82003882,Asia,16.92968633\r
-19/07/2020,19,7,2020,918,17,Turkey,TR,TUR,82003882,Asia,17.20284413\r
-18/07/2020,18,7,2020,926,18,Turkey,TR,TUR,82003882,Asia,17.49063538\r
-17/07/2020,17,7,2020,933,21,Turkey,TR,TUR,82003882,Asia,17.79062118\r
-16/07/2020,16,7,2020,947,17,Turkey,TR,TUR,82003882,Asia,18.09914316\r
-15/07/2020,15,7,2020,992,20,Turkey,TR,TUR,82003882,Asia,18.3979095\r
-14/07/2020,14,7,2020,1008,19,Turkey,TR,TUR,82003882,Asia,18.7649653\r
-13/07/2020,13,7,2020,1012,19,Turkey,TR,TUR,82003882,Asia,19.21128563\r
-12/07/2020,12,7,2020,1016,21,Turkey,TR,TUR,82003882,Asia,19.63077797\r
-11/07/2020,11,7,2020,1003,23,Turkey,TR,TUR,82003882,Asia,20.06490376\r
-10/07/2020,10,7,2020,1024,18,Turkey,TR,TUR,82003882,Asia,20.54414936\r
-09/07/2020,9,7,2020,1041,22,Turkey,TR,TUR,82003882,Asia,21.0733926\r
-08/07/2020,8,7,2020,1053,19,Turkey,TR,TUR,82003882,Asia,21.62336656\r
-07/07/2020,7,7,2020,1086,16,Turkey,TR,TUR,82003882,Asia,21.88554927\r
-06/07/2020,6,7,2020,1148,19,Turkey,TR,TUR,82003882,Asia,22.03920053\r
-05/07/2020,5,7,2020,1154,20,Turkey,TR,TUR,82003882,Asia,22.09285653\r
-04/07/2020,4,7,2020,1172,19,Turkey,TR,TUR,82003882,Asia,22.20748525\r
-03/07/2020,3,7,2020,1186,17,Turkey,TR,TUR,82003882,Asia,22.25870234\r
-02/07/2020,2,7,2020,1192,19,Turkey,TR,TUR,82003882,Asia,22.40259796\r
-01/07/2020,1,7,2020,1293,16,Turkey,TR,TUR,82003882,Asia,22.69160867\r
-30/06/2020,30,6,2020,1374,18,Turkey,TR,TUR,82003882,Asia,22.90379375\r
-29/06/2020,29,6,2020,1356,15,Turkey,TR,TUR,82003882,Asia,23.16963482\r
-28/06/2020,28,6,2020,1372,17,Turkey,TR,TUR,82003882,Asia,23.42084244\r
-27/06/2020,27,6,2020,1396,19,Turkey,TR,TUR,82003882,Asia,23.52693498\r
-26/06/2020,26,6,2020,1458,21,Turkey,TR,TUR,82003882,Asia,23.28182463\r
-25/06/2020,25,6,2020,1492,24,Turkey,TR,TUR,82003882,Asia,22.70746158\r
-24/06/2020,24,6,2020,1268,27,Turkey,TR,TUR,82003882,Asia,22.01237254\r
-23/06/2020,23,6,2020,1212,24,Turkey,TR,TUR,82003882,Asia,21.67702256\r
-22/06/2020,22,6,2020,1192,23,Turkey,TR,TUR,82003882,Asia,21.40508421\r
-21/06/2020,21,6,2020,1248,22,Turkey,TR,TUR,82003882,Asia,21.06607587\r
-20/06/2020,20,6,2020,1214,23,Turkey,TR,TUR,82003882,Asia,20.61487772\r
-19/06/2020,19,6,2020,1304,21,Turkey,TR,TUR,82003882,Asia,20.26855265\r
-18/06/2020,18,6,2020,1429,19,Turkey,TR,TUR,82003882,Asia,19.88320504\r
-17/06/2020,17,6,2020,1467,17,Turkey,TR,TUR,82003882,Asia,19.19787163\r
-16/06/2020,16,6,2020,1592,18,Turkey,TR,TUR,82003882,Asia,18.36742314\r
-15/06/2020,15,6,2020,1562,15,Turkey,TR,TUR,82003882,Asia,17.43454048\r
-14/06/2020,14,6,2020,1459,14,Turkey,TR,TUR,82003882,Asia,16.5528749\r
-13/06/2020,13,6,2020,1195,15,Turkey,TR,TUR,82003882,Asia,15.97241457\r
-12/06/2020,12,6,2020,987,17,Turkey,TR,TUR,82003882,Asia,15.90656403\r
-11/06/2020,11,6,2020,922,17,Turkey,TR,TUR,82003882,Asia,16.14435765\r
-10/06/2020,10,6,2020,993,18,Turkey,TR,TUR,82003882,Asia,16.28215601\r
-09/06/2020,9,6,2020,989,19,Turkey,TR,TUR,82003882,Asia,16.22728056\r
-08/06/2020,8,6,2020,914,23,Turkey,TR,TUR,82003882,Asia,16.22484165\r
-07/06/2020,7,6,2020,878,21,Turkey,TR,TUR,82003882,Asia,16.50165781\r
-06/06/2020,6,6,2020,930,18,Turkey,TR,TUR,82003882,Asia,16.87724979\r
-05/06/2020,5,6,2020,988,21,Turkey,TR,TUR,82003882,Asia,16.90407779\r
-04/06/2020,4,6,2020,867,24,Turkey,TR,TUR,82003882,Asia,16.87115251\r
-03/06/2020,3,6,2020,786,22,Turkey,TR,TUR,82003882,Asia,16.99919523\r
-02/06/2020,2,6,2020,827,23,Turkey,TR,TUR,82003882,Asia,17.28698649\r
-01/06/2020,1,6,2020,839,25,Turkey,TR,TUR,82003882,Asia,17.69062591\r
-31/05/2020,31,5,2020,983,26,Turkey,TR,TUR,82003882,Asia,18.33571733\r
-30/05/2020,30,5,2020,1141,28,Turkey,TR,TUR,82003882,Asia,19.10031528\r
-29/05/2020,29,5,2020,1182,30,Turkey,TR,TUR,82003882,Asia,19.79174596\r
-28/05/2020,28,5,2020,1035,34,Turkey,TR,TUR,82003882,Asia,20.34415883\r
-27/05/2020,27,5,2020,948,28,Turkey,TR,TUR,82003882,Asia,21.08070933\r
-26/05/2020,26,5,2020,987,29,Turkey,TR,TUR,82003882,Asia,22.0026169\r
-25/05/2020,25,5,2020,1141,32,Turkey,TR,TUR,82003882,Asia,22.15748762\r
-24/05/2020,24,5,2020,1186,32,Turkey,TR,TUR,82003882,Asia,22.64648886\r
-23/05/2020,23,5,2020,952,27,Turkey,TR,TUR,82003882,Asia,23.08549246\r
-22/05/2020,22,5,2020,961,27,Turkey,TR,TUR,82003882,Asia,24.17812366\r
-21/05/2020,21,5,2020,972,23,Turkey,TR,TUR,82003882,Asia,25.4170894\r
-20/05/2020,20,5,2020,1022,28,Turkey,TR,TUR,82003882,Asia,26.97921057\r
-19/05/2020,19,5,2020,1158,31,Turkey,TR,TUR,82003882,Asia,27.96696869\r
-18/05/2020,18,5,2020,1368,44,Turkey,TR,TUR,82003882,Asia,28.52303992\r
-17/05/2020,17,5,2020,1610,41,Turkey,TR,TUR,82003882,Asia,28.89131517\r
-16/05/2020,16,5,2020,1708,48,Turkey,TR,TUR,82003882,Asia,29.34617168\r
-15/05/2020,15,5,2020,1635,55,Turkey,TR,TUR,82003882,Asia,29.93150983\r
-14/05/2020,14,5,2020,1639,58,Turkey,TR,TUR,82003882,Asia,31.1265752\r
-13/05/2020,13,5,2020,1704,53,Turkey,TR,TUR,82003882,Asia,32.70820764\r
-12/05/2020,12,5,2020,1114,55,Turkey,TR,TUR,82003882,Asia,33.54719231\r
-11/05/2020,11,5,2020,1542,47,Turkey,TR,TUR,82003882,Asia,34.7873775\r
-10/05/2020,10,5,2020,1546,50,Turkey,TR,TUR,82003882,Asia,35.78123289\r
-09/05/2020,9,5,2020,1848,48,Turkey,TR,TUR,82003882,Asia,37.38481551\r
-08/05/2020,8,5,2020,1977,57,Turkey,TR,TUR,82003882,Asia,38.9384005\r
-07/05/2020,7,5,2020,2253,64,Turkey,TR,TUR,82003882,Asia,40.32735914\r
-06/05/2020,6,5,2020,1832,59,Turkey,TR,TUR,82003882,Asia,41.33950634\r
-05/05/2020,5,5,2020,1614,64,Turkey,TR,TUR,82003882,Asia,44.7283703\r
-04/05/2020,4,5,2020,1670,61,Turkey,TR,TUR,82003882,Asia,48.45990096\r
-03/05/2020,3,5,2020,1983,78,Turkey,TR,TUR,82003882,Asia,51.27318241\r
-02/05/2020,2,5,2020,2188,84,Turkey,TR,TUR,82003882,Asia,53.46820044\r
-01/05/2020,1,5,2020,2615,93,Turkey,TR,TUR,82003882,Asia,56.10831936\r
-30/04/2020,30,4,2020,2936,89,Turkey,TR,TUR,82003882,Asia,58.77404682\r
-29/04/2020,29,4,2020,2392,92,Turkey,TR,TUR,82003882,Asia,60.41421307\r
-28/04/2020,28,4,2020,2131,95,Turkey,TR,TUR,82003882,Asia,62.45070203\r
-27/04/2020,27,4,2020,2357,99,Turkey,TR,TUR,82003882,Asia,64.84327169\r
-26/04/2020,26,4,2020,2861,106,Turkey,TR,TUR,82003882,Asia,67.80898495\r
-25/04/2020,25,4,2020,3122,109,Turkey,TR,TUR,82003882,Asia,70.58568276\r
-24/04/2020,24,4,2020,3116,115,Turkey,TR,TUR,82003882,Asia,72.56729627\r
-23/04/2020,23,4,2020,3083,117,Turkey,TR,TUR,82003882,Asia,73.71358346\r
-22/04/2020,22,4,2020,4611,119,Turkey,TR,TUR,82003882,Asia,74.97449938\r
-21/04/2020,21,4,2020,4674,123,Turkey,TR,TUR,82003882,Asia,74.09771162\r
-20/04/2020,20,4,2020,3977,127,Turkey,TR,TUR,82003882,Asia,72.23682411\r
-19/04/2020,19,4,2020,3783,121,Turkey,TR,TUR,82003882,Asia,71.21004345\r
-18/04/2020,18,4,2020,4353,126,Turkey,TR,TUR,82003882,Asia,70.27106351\r
-17/04/2020,17,4,2020,4801,125,Turkey,TR,TUR,82003882,Asia,68.36017836\r
-16/04/2020,16,4,2020,4281,115,Turkey,TR,TUR,82003882,Asia,65.50055764\r
-15/04/2020,15,4,2020,4062,107,Turkey,TR,TUR,82003882,Asia,62.89946127\r
-14/04/2020,14,4,2020,4093,98,Turkey,TR,TUR,82003882,Asia,61.24344211\r
-13/04/2020,13,4,2020,4789,97,Turkey,TR,TUR,82003882,Asia,58.21553667\r
-12/04/2020,12,4,2020,5138,95,Turkey,TR,TUR,82003882,Asia,54.5888791\r
-11/04/2020,11,4,2020,4747,98,Turkey,TR,TUR,82003882,Asia,50.40127247\r
-10/04/2020,10,4,2020,4056,96,Turkey,TR,TUR,82003882,Asia,47.13557341\r
-09/04/2020,9,4,2020,4117,87,Turkey,TR,TUR,82003882,Asia,43.64793364\r
-08/04/2020,8,4,2020,3892,76,Turkey,TR,TUR,82003882,Asia,39.31155357\r
-07/04/2020,7,4,2020,3148,75,Turkey,TR,TUR,82003882,Asia,34.98370967\r
-06/04/2020,6,4,2020,3135,73,Turkey,TR,TUR,82003882,Asia,31.50216718\r
-05/04/2020,5,4,2020,3013,76,Turkey,TR,TUR,82003882,Asia,28.03159977\r
-04/04/2020,4,4,2020,2786,69,Turkey,TR,TUR,82003882,Asia,24.69517236\r
-03/04/2020,3,4,2020,2456,79,Turkey,TR,TUR,82003882,Asia,21.67702256\r
-02/04/2020,2,4,2020,2148,63,Turkey,TR,TUR,82003882,Asia,18.88691074\r
-01/04/2020,1,4,2020,2704,46,Turkey,TR,TUR,82003882,Asia,16.38093182\r
-31/03/2020,31,3,2020,1610,37,Turkey,TR,TUR,82003882,Asia,13.14571913\r
-30/03/2020,30,3,2020,1815,23,Turkey,TR,TUR,82003882,Asia,11.21776162\r
-29/03/2020,29,3,2020,1704,16,Turkey,TR,TUR,82003882,Asia,9.02396304\r
-28/03/2020,28,3,2020,2069,17,Turkey,TR,TUR,82003882,Asia,6.94723208\r
-27/03/2020,27,3,2020,1196,16,Turkey,TR,TUR,82003882,Asia,4.42540025\r
-26/03/2020,26,3,2020,561,15,Turkey,TR,TUR,82003882,Asia,\r
-25/03/2020,25,3,2020,343,7,Turkey,TR,TUR,82003882,Asia,\r
-24/03/2020,24,3,2020,293,7,Turkey,TR,TUR,82003882,Asia,\r
-23/03/2020,23,3,2020,289,9,Turkey,TR,TUR,82003882,Asia,\r
-22/03/2020,22,3,2020,277,12,Turkey,TR,TUR,82003882,Asia,\r
-21/03/2020,21,3,2020,311,5,Turkey,TR,TUR,82003882,Asia,\r
-20/03/2020,20,3,2020,168,3,Turkey,TR,TUR,82003882,Asia,\r
-19/03/2020,19,3,2020,93,1,Turkey,TR,TUR,82003882,Asia,\r
-18/03/2020,18,3,2020,51,0,Turkey,TR,TUR,82003882,Asia,\r
-17/03/2020,17,3,2020,29,0,Turkey,TR,TUR,82003882,Asia,\r
-16/03/2020,16,3,2020,16,0,Turkey,TR,TUR,82003882,Asia,\r
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-14/06/2020,14,6,2020,753,10,Ukraine,UA,UKR,43993643,Europe,16.59785256\r
-13/06/2020,13,6,2020,683,16,Ukraine,UA,UKR,43993643,Europe,15.77955251\r
-12/06/2020,12,6,2020,689,21,Ukraine,UA,UKR,43993643,Europe,15.20219637\r
-11/06/2020,11,6,2020,525,23,Ukraine,UA,UKR,43993643,Europe,14.72030857\r
-10/06/2020,10,6,2020,394,13,Ukraine,UA,UKR,43993643,Europe,14.25660521\r
-09/06/2020,9,6,2020,463,9,Ukraine,UA,UKR,43993643,Europe,14.13158715\r
-08/06/2020,8,6,2020,485,11,Ukraine,UA,UKR,43993643,Europe,13.66788379\r
-07/06/2020,7,6,2020,550,15,Ukraine,UA,UKR,43993643,Europe,13.48831239\r
-06/06/2020,6,6,2020,553,15,Ukraine,UA,UKR,43993643,Europe,13.22009182\r
-05/06/2020,5,6,2020,588,12,Ukraine,UA,UKR,43993643,Europe,12.96778264\r
-04/06/2020,4,6,2020,483,8,Ukraine,UA,UKR,43993643,Europe,12.7132004\r
-03/06/2020,3,6,2020,328,9,Ukraine,UA,UKR,43993643,Europe,12.41997622\r
-02/06/2020,2,6,2020,340,10,Ukraine,UA,UKR,43993643,Europe,12.26540844\r
-01/06/2020,1,6,2020,468,12,Ukraine,UA,UKR,43993643,Europe,12.2313126\r
-31/05/2020,31,5,2020,393,17,Ukraine,UA,UKR,43993643,Europe,12.15175565\r
-30/05/2020,30,5,2020,429,10,Ukraine,UA,UKR,43993643,Europe,12.45861817\r
-29/05/2020,29,5,2020,477,11,Ukraine,UA,UKR,43993643,Europe,12.58136318\r
-28/05/2020,28,5,2020,321,14,Ukraine,UA,UKR,43993643,Europe,12.45634511\r
-27/05/2020,27,5,2020,339,21,Ukraine,UA,UKR,43993643,Europe,12.64046262\r
-26/05/2020,26,5,2020,259,6,Ukraine,UA,UKR,43993643,Europe,12.72229263\r
-25/05/2020,25,5,2020,406,12,Ukraine,UA,UKR,43993643,Europe,13.07916237\r
-24/05/2020,24,5,2020,432,17,Ukraine,UA,UKR,43993643,Europe,13.34283683\r
-23/05/2020,23,5,2020,442,9,Ukraine,UA,UKR,43993643,Europe,13.53150045\r
-22/05/2020,22,5,2020,476,15,Ukraine,UA,UKR,43993643,Europe,13.6724299\r
-21/05/2020,21,5,2020,354,16,Ukraine,UA,UKR,43993643,Europe,13.74289463\r
-20/05/2020,20,5,2020,260,13,Ukraine,UA,UKR,43993643,Europe,14.04521103\r
-19/05/2020,19,5,2020,325,21,Ukraine,UA,UKR,43993643,Europe,14.28615493\r
-18/05/2020,18,5,2020,433,17,Ukraine,UA,UKR,43993643,Europe,14.49754911\r
-17/05/2020,17,5,2020,528,21,Ukraine,UA,UKR,43993643,Europe,14.65438995\r
-16/05/2020,16,5,2020,483,20,Ukraine,UA,UKR,43993643,Europe,14.70439718\r
-15/05/2020,15,5,2020,422,17,Ukraine,UA,UKR,43993643,Europe,14.64075162\r
-14/05/2020,14,5,2020,402,14,Ukraine,UA,UKR,43993643,Europe,14.90897219\r
-13/05/2020,13,5,2020,375,17,Ukraine,UA,UKR,43993643,Europe,15.0317172\r
-12/05/2020,12,5,2020,416,17,Ukraine,UA,UKR,43993643,Europe,15.09081664\r
-11/05/2020,11,5,2020,522,15,Ukraine,UA,UKR,43993643,Europe,15.03626331\r
-10/05/2020,10,5,2020,515,15,Ukraine,UA,UKR,43993643,Europe,14.96807164\r
-09/05/2020,9,5,2020,504,21,Ukraine,UA,UKR,43993643,Europe,14.88396858\r
-08/05/2020,8,5,2020,507,13,Ukraine,UA,UKR,43993643,Europe,14.82259607\r
-07/05/2020,7,5,2020,487,11,Ukraine,UA,UKR,43993643,Europe,14.98398303\r
-06/05/2020,6,5,2020,366,13,Ukraine,UA,UKR,43993643,Europe,14.93852191\r
-05/05/2020,5,5,2020,418,15,Ukraine,UA,UKR,43993643,Europe,15.04990164\r
-04/05/2020,4,5,2020,502,9,Ukraine,UA,UKR,43993643,Europe,14.6930319\r
-03/05/2020,3,5,2020,550,7,Ukraine,UA,UKR,43993643,Europe,14.33161605\r
-02/05/2020,2,5,2020,455,11,Ukraine,UA,UKR,43993643,Europe,14.54528328\r
-01/05/2020,1,5,2020,540,11,Ukraine,UA,UKR,43993643,Europe,14.19523271\r
-30/04/2020,30,4,2020,456,11,Ukraine,UA,UKR,43993643,Europe,13.87018574\r
-29/04/2020,29,4,2020,401,19,Ukraine,UA,UKR,43993643,Europe,13.72471018\r
-28/04/2020,28,4,2020,392,11,Ukraine,UA,UKR,43993643,Europe,13.42693989\r
-27/04/2020,27,4,2020,492,8,Ukraine,UA,UKR,43993643,Europe,13.27464516\r
-26/04/2020,26,4,2020,478,8,Ukraine,UA,UKR,43993643,Europe,12.76093457\r
-25/04/2020,25,4,2020,477,6,Ukraine,UA,UKR,43993643,Europe,12.37451511\r
-24/04/2020,24,4,2020,578,13,Ukraine,UA,UKR,43993643,Europe,11.99718787\r
-23/04/2020,23,4,2020,467,13,Ukraine,UA,UKR,43993643,Europe,11.19252616\r
-22/04/2020,22,4,2020,415,10,Ukraine,UA,UKR,43993643,Europe,10.59925862\r
-21/04/2020,21,4,2020,261,10,Ukraine,UA,UKR,43993643,Europe,9.98098748\r
-20/04/2020,20,4,2020,343,8,Ukraine,UA,UKR,43993643,Europe,9.41272356\r
-19/04/2020,19,4,2020,644,8,Ukraine,UA,UKR,43993643,Europe,8.82172908\r
-18/04/2020,18,4,2020,301,9,Ukraine,UA,UKR,43993643,Europe,7.70565875\r
-17/04/2020,17,4,2020,397,8,Ukraine,UA,UKR,43993643,Europe,7.41925373\r
-16/04/2020,16,4,2020,392,10,Ukraine,UA,UKR,43993643,Europe,6.75097536\r
-15/04/2020,15,4,2020,270,5,Ukraine,UA,UKR,43993643,Europe,6.41683618\r
-14/04/2020,14,4,2020,325,10,Ukraine,UA,UKR,43993643,Europe,5.95995199\r
-13/04/2020,13,4,2020,266,10,Ukraine,UA,UKR,43993643,Europe,5.36213834\r
-12/04/2020,12,4,2020,308,4,Ukraine,UA,UKR,43993643,Europe,5.00072249\r
-11/04/2020,11,4,2020,311,12,Ukraine,UA,UKR,43993643,Europe,4.51201552\r
-10/04/2020,10,4,2020,224,5,Ukraine,UA,UKR,43993643,Europe,3.94602466\r
-09/04/2020,9,4,2020,206,7,Ukraine,UA,UKR,43993643,Europe,3.53460158\r
-08/04/2020,8,4,2020,143,7,Ukraine,UA,UKR,43993643,Europe,3.13227072\r
-07/04/2020,7,4,2020,11,1,Ukraine,UA,UKR,43993643,Europe,2.83222737\r
-06/04/2020,6,4,2020,83,5,Ukraine,UA,UKR,43993643,Europe,2.86632321\r
-05/04/2020,5,4,2020,153,5,Ukraine,UA,UKR,43993643,Europe,2.69129792\r
-04/04/2020,4,4,2020,175,5,Ukraine,UA,UKR,43993643,Europe,2.37761624\r
-03/04/2020,3,4,2020,103,2,Ukraine,UA,UKR,43993643,Europe,1.9798315\r
-02/04/2020,2,4,2020,245,7,Ukraine,UA,UKR,43993643,Europe,1.76161815\r
-01/04/2020,1,4,2020,69,2,Ukraine,UA,UKR,43993643,Europe,1.21608479\r
-31/03/2020,31,3,2020,62,2,Ukraine,UA,UKR,43993643,Europe,1.07970145\r
-30/03/2020,30,3,2020,107,1,Ukraine,UA,UKR,43993643,Europe,0.94331811\r
-29/03/2020,29,3,2020,93,3,Ukraine,UA,UKR,43993643,Europe,0.70010115\r
-28/03/2020,28,3,2020,62,0,Ukraine,UA,UKR,43993643,Europe,0.49325308\r
-27/03/2020,27,3,2020,43,1,Ukraine,UA,UKR,43993643,Europe,0.35459669\r
-26/03/2020,26,3,2020,29,1,Ukraine,UA,UKR,43993643,Europe,\r
-25/03/2020,25,3,2020,11,0,Ukraine,UA,UKR,43993643,Europe,\r
-24/03/2020,24,3,2020,26,0,Ukraine,UA,UKR,43993643,Europe,\r
-23/03/2020,23,3,2020,6,0,Ukraine,UA,UKR,43993643,Europe,\r
-22/03/2020,22,3,2020,15,0,Ukraine,UA,UKR,43993643,Europe,\r
-21/03/2020,21,3,2020,0,1,Ukraine,UA,UKR,43993643,Europe,\r
-20/03/2020,20,3,2020,7,0,Ukraine,UA,UKR,43993643,Europe,\r
-19/03/2020,19,3,2020,5,2,Ukraine,UA,UKR,43993643,Europe,\r
-18/03/2020,18,3,2020,9,0,Ukraine,UA,UKR,43993643,Europe,\r
-17/03/2020,17,3,2020,2,0,Ukraine,UA,UKR,43993643,Europe,\r
-16/03/2020,16,3,2020,0,0,Ukraine,UA,UKR,43993643,Europe,\r
-13/03/2020,13,3,2020,2,0,Ukraine,UA,UKR,43993643,Europe,\r
-04/03/2020,4,3,2020,1,0,Ukraine,UA,UKR,43993643,Europe,\r
-19/08/2020,19,8,2020,365,2,United_Arab_Emirates,AE,ARE,9770526,Asia,36.3747049\r
-18/08/2020,18,8,2020,229,0,United_Arab_Emirates,AE,ARE,9770526,Asia,34.57336893\r
-17/08/2020,17,8,2020,210,3,United_Arab_Emirates,AE,ARE,9770526,Asia,33.9081028\r
-16/08/2020,16,8,2020,283,2,United_Arab_Emirates,AE,ARE,9770526,Asia,34.20491384\r
-15/08/2020,15,8,2020,330,1,United_Arab_Emirates,AE,ARE,9770526,Asia,33.9081028\r
-14/08/2020,14,8,2020,277,1,United_Arab_Emirates,AE,ARE,9770526,Asia,30.53059784\r
-13/08/2020,13,8,2020,246,0,United_Arab_Emirates,AE,ARE,9770526,Asia,33.6829358\r
-12/08/2020,12,8,2020,262,0,United_Arab_Emirates,AE,ARE,9770526,Asia,35.00323319\r
-11/08/2020,11,8,2020,179,0,United_Arab_Emirates,AE,ARE,9770526,Asia,36.09836359\r
-10/08/2020,10,8,2020,225,1,United_Arab_Emirates,AE,ARE,9770526,Asia,36.96832699\r
-09/08/2020,9,8,2020,239,0,United_Arab_Emirates,AE,ARE,9770526,Asia,38.25791979\r
-08/08/2020,8,8,2020,216,2,United_Arab_Emirates,AE,ARE,9770526,Asia,39.01529969\r
-07/08/2020,7,8,2020,239,1,United_Arab_Emirates,AE,ARE,9770526,Asia,39.47586855\r
-06/08/2020,6,8,2020,254,2,United_Arab_Emirates,AE,ARE,9770526,Asia,39.6293915\r
-05/08/2020,5,8,2020,189,0,United_Arab_Emirates,AE,ARE,9770526,Asia,39.44516396\r
-04/08/2020,4,8,2020,164,0,United_Arab_Emirates,AE,ARE,9770526,Asia,40.63240812\r
-03/08/2020,3,8,2020,239,0,United_Arab_Emirates,AE,ARE,9770526,Asia,41.72753852\r
-02/08/2020,2,8,2020,254,0,United_Arab_Emirates,AE,ARE,9770526,Asia,41.44096234\r
-01/08/2020,1,8,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,41.79918256\r
-31/07/2020,31,7,2020,585,4,United_Arab_Emirates,AE,ARE,9770526,Asia,44.79799757\r
-30/07/2020,30,7,2020,375,0,United_Arab_Emirates,AE,ARE,9770526,Asia,41.68659906\r
-29/07/2020,29,7,2020,369,2,United_Arab_Emirates,AE,ARE,9770526,Asia,40.66311271\r
-28/07/2020,28,7,2020,264,1,United_Arab_Emirates,AE,ARE,9770526,Asia,40.72452189\r
-27/07/2020,27,7,2020,351,1,United_Arab_Emirates,AE,ARE,9770526,Asia,41.54331097\r
-26/07/2020,26,7,2020,313,0,United_Arab_Emirates,AE,ARE,9770526,Asia,42.05505415\r
-25/07/2020,25,7,2020,261,1,United_Arab_Emirates,AE,ARE,9770526,Asia,42.97619187\r
-24/07/2020,24,7,2020,254,0,United_Arab_Emirates,AE,ARE,9770526,Asia,45.14598293\r
-23/07/2020,23,7,2020,236,1,United_Arab_Emirates,AE,ARE,9770526,Asia,47.99127498\r
-22/07/2020,22,7,2020,305,1,United_Arab_Emirates,AE,ARE,9770526,Asia,50.13036146\r
-21/07/2020,21,7,2020,271,1,United_Arab_Emirates,AE,ARE,9770526,Asia,52.45367547\r
-20/07/2020,20,7,2020,211,1,United_Arab_Emirates,AE,ARE,9770526,Asia,55.08403539\r
-19/07/2020,19,7,2020,289,1,United_Arab_Emirates,AE,ARE,9770526,Asia,59.91489097\r
-18/07/2020,18,7,2020,293,2,United_Arab_Emirates,AE,ARE,9770526,Asia,64.28517769\r
-17/07/2020,17,7,2020,281,0,United_Arab_Emirates,AE,ARE,9770526,Asia,68.16419096\r
-16/07/2020,16,7,2020,275,0,United_Arab_Emirates,AE,ARE,9770526,Asia,69.38213971\r
-15/07/2020,15,7,2020,375,1,United_Arab_Emirates,AE,ARE,9770526,Asia,70.68196738\r
-14/07/2020,14,7,2020,344,1,United_Arab_Emirates,AE,ARE,9770526,Asia,71.1527711\r
-13/07/2020,13,7,2020,401,2,United_Arab_Emirates,AE,ARE,9770526,Asia,72.22743177\r
-12/07/2020,12,7,2020,403,1,United_Arab_Emirates,AE,ARE,9770526,Asia,72.59588685\r
-11/07/2020,11,7,2020,473,2,United_Arab_Emirates,AE,ARE,9770526,Asia,72.43212904\r
-10/07/2020,10,7,2020,532,1,United_Arab_Emirates,AE,ARE,9770526,Asia,71.78733264\r
-09/07/2020,9,7,2020,445,1,United_Arab_Emirates,AE,ARE,9770526,Asia,70.74337656\r
-08/07/2020,8,7,2020,532,2,United_Arab_Emirates,AE,ARE,9770526,Asia,70.79455088\r
-07/07/2020,7,7,2020,528,1,United_Arab_Emirates,AE,ARE,9770526,Asia,69.23885162\r
-06/07/2020,6,7,2020,683,2,United_Arab_Emirates,AE,ARE,9770526,Asia,67.7036221\r
-05/07/2020,5,7,2020,716,3,United_Arab_Emirates,AE,ARE,9770526,Asia,64.72527682\r
-04/07/2020,4,7,2020,672,1,United_Arab_Emirates,AE,ARE,9770526,Asia,61.36824159\r
-03/07/2020,3,7,2020,400,1,United_Arab_Emirates,AE,ARE,9770526,Asia,58.51271467\r
-02/07/2020,2,7,2020,402,1,United_Arab_Emirates,AE,ARE,9770526,Asia,58.38989631\r
-01/07/2020,1,7,2020,421,1,United_Arab_Emirates,AE,ARE,9770526,Asia,58.18519904\r
-30/06/2020,30,6,2020,449,1,United_Arab_Emirates,AE,ARE,9770526,Asia,57.41758427\r
-29/06/2020,29,6,2020,437,2,United_Arab_Emirates,AE,ARE,9770526,Asia,56.32245388\r
-28/06/2020,28,6,2020,387,1,United_Arab_Emirates,AE,ARE,9770526,Asia,54.96121703\r
-27/06/2020,27,6,2020,410,2,United_Arab_Emirates,AE,ARE,9770526,Asia,56.02564284\r
-26/06/2020,26,6,2020,430,1,United_Arab_Emirates,AE,ARE,9770526,Asia,57.07983378\r
-25/06/2020,25,6,2020,450,2,United_Arab_Emirates,AE,ARE,9770526,Asia,57.58134209\r
-24/06/2020,24,6,2020,380,2,United_Arab_Emirates,AE,ARE,9770526,Asia,59.14727621\r
-23/06/2020,23,6,2020,378,1,United_Arab_Emirates,AE,ARE,9770526,Asia,60.66203601\r
-22/06/2020,22,6,2020,392,1,United_Arab_Emirates,AE,ARE,9770526,Asia,62.60666007\r
-21/06/2020,21,6,2020,388,1,United_Arab_Emirates,AE,ARE,9770526,Asia,64.12141987\r
-20/06/2020,20,6,2020,393,2,United_Arab_Emirates,AE,ARE,9770526,Asia,66.55731738\r
-19/06/2020,19,6,2020,388,3,United_Arab_Emirates,AE,ARE,9770526,Asia,68.92157086\r
-18/06/2020,18,6,2020,382,2,United_Arab_Emirates,AE,ARE,9770526,Asia,71.69521887\r
-17/06/2020,17,6,2020,346,2,United_Arab_Emirates,AE,ARE,9770526,Asia,73.62960807\r
-16/06/2020,16,6,2020,342,2,United_Arab_Emirates,AE,ARE,9770526,Asia,76.18832394\r
-15/06/2020,15,6,2020,304,1,United_Arab_Emirates,AE,ARE,9770526,Asia,79.18713895\r
-14/06/2020,14,6,2020,491,1,United_Arab_Emirates,AE,ARE,9770526,Asia,82.84098522\r
-13/06/2020,13,6,2020,513,1,United_Arab_Emirates,AE,ARE,9770526,Asia,85.24617815\r
-12/06/2020,12,6,2020,479,2,United_Arab_Emirates,AE,ARE,9770526,Asia,86.52553609\r
-11/06/2020,11,6,2020,603,1,United_Arab_Emirates,AE,ARE,9770526,Asia,87.38526462\r
-10/06/2020,10,6,2020,528,2,United_Arab_Emirates,AE,ARE,9770526,Asia,90.2510264\r
-09/06/2020,9,6,2020,568,5,United_Arab_Emirates,AE,ARE,9770526,Asia,92.81997714\r
-08/06/2020,8,6,2020,540,1,United_Arab_Emirates,AE,ARE,9770526,Asia,95.41963247\r
-07/06/2020,7,6,2020,626,1,United_Arab_Emirates,AE,ARE,9770526,Asia,97.88623458\r
-06/06/2020,6,6,2020,624,1,United_Arab_Emirates,AE,ARE,9770526,Asia,99.78991919\r
-05/06/2020,5,6,2020,659,3,United_Arab_Emirates,AE,ARE,9770526,Asia,103.57681869\r
-04/06/2020,4,6,2020,571,1,United_Arab_Emirates,AE,ARE,9770526,Asia,105.98201161\r
-03/06/2020,3,6,2020,596,3,United_Arab_Emirates,AE,ARE,9770526,Asia,109.76891111\r
-02/06/2020,2,6,2020,635,2,United_Arab_Emirates,AE,ARE,9770526,Asia,112.6039683\r
-01/06/2020,1,6,2020,661,2,United_Arab_Emirates,AE,ARE,9770526,Asia,114.62023641\r
-31/05/2020,31,5,2020,726,2,United_Arab_Emirates,AE,ARE,9770526,Asia,115.33667686\r
-30/05/2020,30,5,2020,638,2,United_Arab_Emirates,AE,ARE,9770526,Asia,116.0531173\r
-29/05/2020,29,5,2020,563,3,United_Arab_Emirates,AE,ARE,9770526,Asia,117.16871743\r
-28/05/2020,28,5,2020,883,2,United_Arab_Emirates,AE,ARE,9770526,Asia,118.550424\r
-27/05/2020,27,5,2020,779,5,United_Arab_Emirates,AE,ARE,9770526,Asia,116.93331557\r
-26/05/2020,26,5,2020,822,3,United_Arab_Emirates,AE,ARE,9770526,Asia,116.97425502\r
-25/05/2020,25,5,2020,781,1,United_Arab_Emirates,AE,ARE,9770526,Asia,115.5209044\r
-24/05/2020,24,5,2020,812,3,United_Arab_Emirates,AE,ARE,9770526,Asia,115.5209044\r
-23/05/2020,23,5,2020,994,4,United_Arab_Emirates,AE,ARE,9770526,Asia,113.59675006\r
-22/05/2020,22,5,2020,894,4,United_Arab_Emirates,AE,ARE,9770526,Asia,109.08317526\r
-21/05/2020,21,5,2020,941,6,United_Arab_Emirates,AE,ARE,9770526,Asia,105.07110876\r
-20/05/2020,20,5,2020,873,3,United_Arab_Emirates,AE,ARE,9770526,Asia,101.02833768\r
-19/05/2020,19,5,2020,832,4,United_Arab_Emirates,AE,ARE,9770526,Asia,96.82180877\r
-18/05/2020,18,5,2020,731,6,United_Arab_Emirates,AE,ARE,9770526,Asia,94.10956995\r
-17/05/2020,17,5,2020,796,4,United_Arab_Emirates,AE,ARE,9770526,Asia,92.40034774\r
-16/05/2020,16,5,2020,747,2,United_Arab_Emirates,AE,ARE,9770526,Asia,89.99515482\r
-15/05/2020,15,5,2020,698,2,United_Arab_Emirates,AE,ARE,9770526,Asia,88.05053075\r
-14/05/2020,14,5,2020,725,3,United_Arab_Emirates,AE,ARE,9770526,Asia,86.55624068\r
-13/05/2020,13,5,2020,783,2,United_Arab_Emirates,AE,ARE,9770526,Asia,84.7549047\r
-12/05/2020,12,5,2020,680,3,United_Arab_Emirates,AE,ARE,9770526,Asia,82.27806773\r
-11/05/2020,11,5,2020,781,13,United_Arab_Emirates,AE,ARE,9770526,Asia,80.33344367\r
-10/05/2020,10,5,2020,624,11,United_Arab_Emirates,AE,ARE,9770526,Asia,77.82590211\r
-09/05/2020,9,5,2020,553,9,United_Arab_Emirates,AE,ARE,9770526,Asia,76.59771849\r
-08/05/2020,8,5,2020,502,8,United_Arab_Emirates,AE,ARE,9770526,Asia,76.02456613\r
-07/05/2020,7,5,2020,546,11,United_Arab_Emirates,AE,ARE,9770526,Asia,75.90174777\r
-06/05/2020,6,5,2020,462,9,United_Arab_Emirates,AE,ARE,9770526,Asia,74.99084491\r
-05/05/2020,5,5,2020,567,11,United_Arab_Emirates,AE,ARE,9770526,Asia,75.01131464\r
-04/05/2020,4,5,2020,564,7,United_Arab_Emirates,AE,ARE,9770526,Asia,73.89571452\r
-03/05/2020,3,5,2020,561,8,United_Arab_Emirates,AE,ARE,9770526,Asia,72.75964467\r
-02/05/2020,2,5,2020,557,6,United_Arab_Emirates,AE,ARE,9770526,Asia,71.5724005\r
-01/05/2020,1,5,2020,552,7,United_Arab_Emirates,AE,ARE,9770526,Asia,70.49773984\r
-30/04/2020,30,4,2020,549,9,United_Arab_Emirates,AE,ARE,9770526,Asia,69.3002608\r
-29/04/2020,29,4,2020,541,7,United_Arab_Emirates,AE,ARE,9770526,Asia,67.86737991\r
-28/04/2020,28,4,2020,490,6,United_Arab_Emirates,AE,ARE,9770526,Asia,66.32191552\r
-27/04/2020,27,4,2020,536,5,United_Arab_Emirates,AE,ARE,9770526,Asia,65.16537595\r
-26/04/2020,26,4,2020,504,7,United_Arab_Emirates,AE,ARE,9770526,Asia,63.42544915\r
-25/04/2020,25,4,2020,497,8,United_Arab_Emirates,AE,ARE,9770526,Asia,61.91068935\r
-24/04/2020,24,4,2020,490,4,United_Arab_Emirates,AE,ARE,9770526,Asia,60.40616442\r
-23/04/2020,23,4,2020,457,6,United_Arab_Emirates,AE,ARE,9770526,Asia,58.59459358\r
-22/04/2020,22,4,2020,464,3,United_Arab_Emirates,AE,ARE,9770526,Asia,56.82396219\r
-21/04/2020,21,4,2020,458,2,United_Arab_Emirates,AE,ARE,9770526,Asia,54.81792894\r
-20/04/2020,20,4,2020,453,4,United_Arab_Emirates,AE,ARE,9770526,Asia,52.8118957\r
-19/04/2020,19,4,2020,445,0,United_Arab_Emirates,AE,ARE,9770526,Asia,51.02079458\r
-18/04/2020,18,4,2020,452,2,United_Arab_Emirates,AE,ARE,9770526,Asia,48.93288243\r
-17/04/2020,17,4,2020,435,2,United_Arab_Emirates,AE,ARE,9770526,Asia,46.76309136\r
-16/04/2020,16,4,2020,409,5,United_Arab_Emirates,AE,ARE,9770526,Asia,44.46024707\r
-15/04/2020,15,4,2020,390,3,United_Arab_Emirates,AE,ARE,9770526,Asia,41.80941743\r
-14/04/2020,14,4,2020,377,3,United_Arab_Emirates,AE,ARE,9770526,Asia,38.36026842\r
-13/04/2020,13,4,2020,366,2,United_Arab_Emirates,AE,ARE,9770526,Asia,34.92135429\r
-12/04/2020,12,4,2020,356,4,United_Arab_Emirates,AE,ARE,9770526,Asia,32.21935032\r
-11/04/2020,11,4,2020,350,2,United_Arab_Emirates,AE,ARE,9770526,Asia,29.22053531\r
-10/04/2020,10,4,2020,313,2,United_Arab_Emirates,AE,ARE,9770526,Asia,26.37524326\r
-09/04/2020,9,4,2020,284,0,United_Arab_Emirates,AE,ARE,9770526,Asia,23.17173098\r
-08/04/2020,8,4,2020,268,1,United_Arab_Emirates,AE,ARE,9770526,Asia,21.13499314\r
-07/04/2020,7,4,2020,262,1,United_Arab_Emirates,AE,ARE,9770526,Asia,18.9037929\r
-06/04/2020,6,4,2020,278,0,United_Arab_Emirates,AE,ARE,9770526,Asia,16.68282752\r
-05/04/2020,5,4,2020,241,1,United_Arab_Emirates,AE,ARE,9770526,Asia,13.83753546\r
-04/04/2020,4,4,2020,240,1,United_Arab_Emirates,AE,ARE,9770526,Asia,11.50398658\r
-03/04/2020,3,4,2020,210,0,United_Arab_Emirates,AE,ARE,9770526,Asia,9.04761934\r
-02/04/2020,2,4,2020,150,2,United_Arab_Emirates,AE,ARE,9770526,Asia,7.17463932\r
-01/04/2020,1,4,2020,53,1,United_Arab_Emirates,AE,ARE,9770526,Asia,5.63940979\r
-31/03/2020,31,3,2020,41,2,United_Arab_Emirates,AE,ARE,9770526,Asia,5.25048498\r
-30/03/2020,30,3,2020,102,1,United_Arab_Emirates,AE,ARE,9770526,Asia,4.83085558\r
-29/03/2020,29,3,2020,63,0,United_Arab_Emirates,AE,ARE,9770526,Asia,3.90971786\r
-28/03/2020,28,3,2020,72,0,United_Arab_Emirates,AE,ARE,9770526,Asia,3.27515632\r
-27/03/2020,27,3,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,2.65082965\r
-26/03/2020,26,3,2020,85,0,United_Arab_Emirates,AE,ARE,9770526,Asia,2.8043526\r
-25/03/2020,25,3,2020,50,0,United_Arab_Emirates,AE,ARE,9770526,Asia,2.07767729\r
-24/03/2020,24,3,2020,45,0,United_Arab_Emirates,AE,ARE,9770526,Asia,1.72969193\r
-23/03/2020,23,3,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,1.2895928\r
-22/03/2020,22,3,2020,13,2,United_Arab_Emirates,AE,ARE,9770526,Asia,1.35100198\r
-21/03/2020,21,3,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,1.21794876\r
-20/03/2020,20,3,2020,27,0,United_Arab_Emirates,AE,ARE,9770526,Asia,1.21794876\r
-19/03/2020,19,3,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.96207717\r
-18/03/2020,18,3,2020,15,0,United_Arab_Emirates,AE,ARE,9770526,Asia,1.02348635\r
-17/03/2020,17,3,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.8699634\r
-16/03/2020,16,3,2020,12,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.8699634\r
-15/03/2020,15,3,2020,1,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.74714504\r
-13/03/2020,13,3,2020,11,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.73691017\r
-11/03/2020,11,3,2020,15,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.6447964\r
-10/03/2020,10,3,2020,14,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.51174318\r
-08/03/2020,8,3,2020,16,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.36845509\r
-06/03/2020,6,3,2020,2,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.20469727\r
-04/03/2020,4,3,2020,6,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.18422754\r
-02/03/2020,2,3,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.12281836\r
-01/03/2020,1,3,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.13305323\r
-29/02/2020,29,2,2020,2,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.13305323\r
-28/02/2020,28,2,2020,6,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.1125835\r
-27/02/2020,27,2,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.05117432\r
-26/02/2020,26,2,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.05117432\r
-25/02/2020,25,2,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.05117432\r
-24/02/2020,24,2,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.06140918\r
-23/02/2020,23,2,2020,2,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.06140918\r
-22/02/2020,22,2,2020,2,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.04093945\r
-21/02/2020,21,2,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.04093945\r
-20/02/2020,20,2,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.04093945\r
-19/02/2020,19,2,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.04093945\r
-18/02/2020,18,2,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.04093945\r
-17/02/2020,17,2,2020,1,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.04093945\r
-16/02/2020,16,2,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.03070459\r
-15/02/2020,15,2,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.04093945\r
-14/02/2020,14,2,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.04093945\r
-13/02/2020,13,2,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.04093945\r
-12/02/2020,12,2,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.07164404\r
-11/02/2020,11,2,2020,1,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.07164404\r
-10/02/2020,10,2,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.06140918\r
-09/02/2020,9,2,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.07164404\r
-08/02/2020,8,2,2020,2,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.07164404\r
-07/02/2020,7,2,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.05117432\r
-06/02/2020,6,2,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.05117432\r
-05/02/2020,5,2,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.05117432\r
-04/02/2020,4,2,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.05117432\r
-03/02/2020,3,2,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.05117432\r
-02/02/2020,2,2,2020,1,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.05117432\r
-01/02/2020,1,2,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.04093945\r
-31/01/2020,31,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.04093945\r
-30/01/2020,30,1,2020,3,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.04093945\r
-29/01/2020,29,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.01023486\r
-28/01/2020,28,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.01023486\r
-27/01/2020,27,1,2020,1,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0.01023486\r
-26/01/2020,26,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0\r
-25/01/2020,25,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0\r
-24/01/2020,24,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0\r
-23/01/2020,23,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0\r
-22/01/2020,22,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0\r
-21/01/2020,21,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0\r
-20/01/2020,20,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0\r
-19/01/2020,19,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0\r
-18/01/2020,18,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0\r
-17/01/2020,17,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0\r
-16/01/2020,16,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0\r
-15/01/2020,15,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0\r
-14/01/2020,14,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0\r
-13/01/2020,13,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,0\r
-12/01/2020,12,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,\r
-11/01/2020,11,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,\r
-10/01/2020,10,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,\r
-09/01/2020,9,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,\r
-08/01/2020,8,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,\r
-07/01/2020,7,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,\r
-06/01/2020,6,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,\r
-05/01/2020,5,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,\r
-04/01/2020,4,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,\r
-03/01/2020,3,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,\r
-02/01/2020,2,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,\r
-01/01/2020,1,1,2020,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,\r
-31/12/2019,31,12,2019,0,0,United_Arab_Emirates,AE,ARE,9770526,Asia,\r
-19/08/2020,19,8,2020,1089,12,United_Kingdom,UK,GBR,66647112,Europe,20.99565845\r
-18/08/2020,18,8,2020,713,3,United_Kingdom,UK,GBR,66647112,Europe,20.36697404\r
-17/08/2020,17,8,2020,1040,5,United_Kingdom,UK,GBR,66647112,Europe,20.68956866\r
-16/08/2020,16,8,2020,1077,3,United_Kingdom,UK,GBR,66647112,Europe,20.24393795\r
-15/08/2020,15,8,2020,1440,11,United_Kingdom,UK,GBR,66647112,Europe,19.78480328\r
-14/08/2020,14,8,2020,1129,18,United_Kingdom,UK,GBR,66647112,Europe,18.94455682\r
-13/08/2020,13,8,2020,1009,20,United_Kingdom,UK,GBR,66647112,Europe,18.51993227\r
-12/08/2020,12,8,2020,1148,13,United_Kingdom,UK,GBR,66647112,Europe,18.150824\r
-11/08/2020,11,8,2020,816,18,United_Kingdom,UK,GBR,66647112,Europe,16.53334956\r
-10/08/2020,10,8,2020,1062,5,United_Kingdom,UK,GBR,66647112,Europe,15.86565371\r
-09/08/2020,9,8,2020,758,3,United_Kingdom,UK,GBR,66647112,Europe,14.9038716\r
-08/08/2020,8,8,2020,871,12,United_Kingdom,UK,GBR,66647112,Europe,14.76733155\r
-07/08/2020,7,8,2020,950,18,United_Kingdom,UK,GBR,66647112,Europe,14.55726994\r
-06/08/2020,6,8,2020,891,14,United_Kingdom,UK,GBR,66647112,Europe,14.29169204\r
-05/08/2020,5,8,2020,670,18,United_Kingdom,UK,GBR,66647112,Europe,14.08163042\r
-04/08/2020,4,8,2020,928,1,United_Kingdom,UK,GBR,66647112,Europe,14.26618456\r
-03/08/2020,3,8,2020,743,5,United_Kingdom,UK,GBR,66647112,Europe,13.4934579\r
-02/08/2020,2,8,2020,771,13,United_Kingdom,UK,GBR,66647112,Europe,13.11834787\r
-01/08/2020,1,8,2020,880,20,United_Kingdom,UK,GBR,66647112,Europe,12.81525897\r
-31/07/2020,31,7,2020,846,0,United_Kingdom,UK,GBR,66647112,Europe,12.55118151\r
-30/07/2020,30,7,2020,763,34,United_Kingdom,UK,GBR,66647112,Europe,12.44014894\r
-29/07/2020,29,7,2020,70,21,United_Kingdom,UK,GBR,66647112,Europe,12.32311462\r
-28/07/2020,28,7,2020,371,3,United_Kingdom,UK,GBR,66647112,Europe,13.30740333\r
-27/07/2020,27,7,2020,421,8,United_Kingdom,UK,GBR,66647112,Europe,13.29239893\r
-26/07/2020,26,7,2020,667,15,United_Kingdom,UK,GBR,66647112,Europe,13.32390817\r
-25/07/2020,25,7,2020,731,32,United_Kingdom,UK,GBR,66647112,Europe,13.17086328\r
-24/07/2020,24,7,2020,773,9,United_Kingdom,UK,GBR,66647112,Europe,13.14685624\r
-23/07/2020,23,7,2020,751,17,United_Kingdom,UK,GBR,66647112,Europe,13.02682103\r
-22/07/2020,22,7,2020,793,25,United_Kingdom,UK,GBR,66647112,Europe,12.79575325\r
-21/07/2020,21,7,2020,413,10,United_Kingdom,UK,GBR,66647112,Europe,12.66221408\r
-20/07/2020,20,7,2020,493,11,United_Kingdom,UK,GBR,66647112,Europe,12.87527658\r
-19/07/2020,19,7,2020,569,9,United_Kingdom,UK,GBR,66647112,Europe,12.73723609\r
-18/07/2020,18,7,2020,704,26,United_Kingdom,UK,GBR,66647112,Europe,12.75224049\r
-17/07/2020,17,7,2020,772,24,United_Kingdom,UK,GBR,66647112,Europe,12.5991956\r
-16/07/2020,16,7,2020,685,26,United_Kingdom,UK,GBR,66647112,Europe,12.41764234\r
-15/07/2020,15,7,2020,726,44,United_Kingdom,UK,GBR,66647112,Europe,12.31561242\r
-14/07/2020,14,7,2020,361,10,United_Kingdom,UK,GBR,66647112,Europe,12.32161418\r
-13/07/2020,13,7,2020,442,9,United_Kingdom,UK,GBR,66647112,Europe,12.44915159\r
-12/07/2020,12,7,2020,565,17,United_Kingdom,UK,GBR,66647112,Europe,12.75974269\r
-11/07/2020,11,7,2020,715,34,United_Kingdom,UK,GBR,66647112,Europe,12.91878934\r
-10/07/2020,10,7,2020,693,31,United_Kingdom,UK,GBR,66647112,Europe,12.92779198\r
-09/07/2020,9,7,2020,597,57,United_Kingdom,UK,GBR,66647112,Europe,13.05532939\r
-08/07/2020,8,7,2020,704,54,United_Kingdom,UK,GBR,66647112,Europe,13.48895658\r
-07/07/2020,7,7,2020,555,11,United_Kingdom,UK,GBR,66647112,Europe,13.77704108\r
-06/07/2020,6,7,2020,401,19,United_Kingdom,UK,GBR,66647112,Europe,13.90307805\r
-05/07/2020,5,7,2020,579,32,United_Kingdom,UK,GBR,66647112,Europe,14.33220392\r
-04/07/2020,4,7,2020,602,49,United_Kingdom,UK,GBR,66647112,Europe,14.94288305\r
-03/07/2020,3,7,2020,651,41,United_Kingdom,UK,GBR,66647112,Europe,15.58057009\r
-02/07/2020,2,7,2020,617,97,United_Kingdom,UK,GBR,66647112,Europe,16.12372941\r
-01/07/2020,1,7,2020,730,53,United_Kingdom,UK,GBR,66647112,Europe,16.85144287\r
-30/06/2020,30,6,2020,446,21,United_Kingdom,UK,GBR,66647112,Europe,17.32108062\r
-29/06/2020,29,6,2020,649,31,United_Kingdom,UK,GBR,66647112,Europe,17.8852461\r
-28/06/2020,28,6,2020,671,40,United_Kingdom,UK,GBR,66647112,Europe,18.24685217\r
-27/06/2020,27,6,2020,721,77,United_Kingdom,UK,GBR,66647112,Europe,18.81851985\r
-26/06/2020,26,6,2020,778,99,United_Kingdom,UK,GBR,66647112,Europe,19.26265012\r
-25/06/2020,25,6,2020,886,87,United_Kingdom,UK,GBR,66647112,Europe,19.89433541\r
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-17/06/2020,17,6,2020,1043,120,United_Kingdom,UK,GBR,66647112,Europe,22.51410384\r
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-31/05/2020,31,5,2020,1527,154,United_Kingdom,UK,GBR,66647112,Europe,42.34392032\r
-30/05/2020,30,5,2020,1760,274,United_Kingdom,UK,GBR,66647112,Europe,43.84285999\r
-29/05/2020,29,5,2020,1835,343,United_Kingdom,UK,GBR,66647112,Europe,45.145242\r
-28/05/2020,28,5,2020,1672,422,United_Kingdom,UK,GBR,66647112,Europe,47.35388984\r
-27/05/2020,27,5,2020,1624,131,United_Kingdom,UK,GBR,66647112,Europe,49.94965123\r
-26/05/2020,26,5,2020,1364,104,United_Kingdom,UK,GBR,66647112,Europe,52.89351473\r
-25/05/2020,25,5,2020,1527,379,United_Kingdom,UK,GBR,66647112,Europe,54.34143943\r
-24/05/2020,24,5,2020,2062,220,United_Kingdom,UK,GBR,66647112,Europe,55.2867167\r
-23/05/2020,23,5,2020,2574,291,United_Kingdom,UK,GBR,66647112,Europe,56.78865725\r
-22/05/2020,22,5,2020,2718,273,United_Kingdom,UK,GBR,66647112,Europe,58.5786823\r
-21/05/2020,21,5,2020,3052,328,United_Kingdom,UK,GBR,66647112,Europe,60.24267038\r
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-19/05/2020,19,5,2020,1838,146,United_Kingdom,UK,GBR,66647112,Europe,62.38829974\r
-18/05/2020,18,5,2020,2079,67,United_Kingdom,UK,GBR,66647112,Europe,64.10480322\r
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-16/05/2020,16,5,2020,2628,350,United_Kingdom,UK,GBR,66647112,Europe,69.14778243\r
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-12/05/2020,12,5,2020,2329,187,United_Kingdom,UK,GBR,66647112,Europe,79.53082798\r
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-29/04/2020,29,4,2020,4706,969,United_Kingdom,UK,GBR,66647112,Europe,98.08226949\r
-28/04/2020,28,4,2020,3473,320,United_Kingdom,UK,GBR,66647112,Europe,97.29003711\r
-27/04/2020,27,4,2020,3748,364,United_Kingdom,UK,GBR,66647112,Europe,97.31404416\r
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-24/04/2020,24,4,2020,5487,682,United_Kingdom,UK,GBR,66647112,Europe,95.62454859\r
-23/04/2020,23,4,2020,4760,847,United_Kingdom,UK,GBR,66647112,Europe,95.09039191\r
-22/04/2020,22,4,2020,4854,1224,United_Kingdom,UK,GBR,66647112,Europe,96.12569559\r
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-01/08/2020,1,8,2020,21,0,Uruguay,UY,URY,3461731,America,6.55741304\r
-31/07/2020,31,7,2020,6,0,Uruguay,UY,URY,3461731,America,6.75962401\r
-30/07/2020,30,7,2020,19,0,Uruguay,UY,URY,3461731,America,6.58630032\r
-29/07/2020,29,7,2020,16,0,Uruguay,UY,URY,3461731,America,6.38408935\r
-28/07/2020,28,7,2020,10,1,Uruguay,UY,URY,3461731,America,6.15299109\r
-27/07/2020,27,7,2020,18,0,Uruguay,UY,URY,3461731,America,5.92189283\r
-26/07/2020,26,7,2020,8,0,Uruguay,UY,URY,3461731,America,5.43080904\r
-25/07/2020,25,7,2020,25,0,Uruguay,UY,URY,3461731,America,5.22859806\r
-24/07/2020,24,7,2020,24,0,Uruguay,UY,URY,3461731,America,4.73751427\r
-23/07/2020,23,7,2020,21,1,Uruguay,UY,URY,3461731,America,4.13088134\r
-22/07/2020,22,7,2020,32,0,Uruguay,UY,URY,3461731,America,3.78423396\r
-21/07/2020,21,7,2020,10,0,Uruguay,UY,URY,3461731,America,3.00427734\r
-20/07/2020,20,7,2020,10,0,Uruguay,UY,URY,3461731,America,2.83095365\r
-19/07/2020,19,7,2020,7,1,Uruguay,UY,URY,3461731,America,2.57096811\r
-18/07/2020,18,7,2020,28,1,Uruguay,UY,URY,3461731,America,2.45541898\r
-17/07/2020,17,7,2020,0,0,Uruguay,UY,URY,3461731,America,1.79101149\r
-16/07/2020,16,7,2020,12,0,Uruguay,UY,URY,3461731,America,1.90656062\r
-15/07/2020,15,7,2020,8,0,Uruguay,UY,URY,3461731,America,1.76212421\r
-14/07/2020,14,7,2020,2,0,Uruguay,UY,URY,3461731,America,1.64657508\r
-13/07/2020,13,7,2020,1,1,Uruguay,UY,URY,3461731,America,1.67546236\r
-12/07/2020,12,7,2020,1,1,Uruguay,UY,URY,3461731,America,1.79101149\r
-11/07/2020,11,7,2020,8,0,Uruguay,UY,URY,3461731,America,1.90656062\r
-10/07/2020,10,7,2020,3,0,Uruguay,UY,URY,3461731,America,2.02210975\r
-09/07/2020,9,7,2020,9,0,Uruguay,UY,URY,3461731,America,2.07988431\r
-08/07/2020,8,7,2020,5,0,Uruguay,UY,URY,3461731,America,2.31098257\r
-07/07/2020,7,7,2020,4,1,Uruguay,UY,URY,3461731,America,2.253208\r
-06/07/2020,6,7,2020,1,0,Uruguay,UY,URY,3461731,America,2.31098257\r
-05/07/2020,5,7,2020,3,0,Uruguay,UY,URY,3461731,America,2.77317908\r
-04/07/2020,4,7,2020,5,0,Uruguay,UY,URY,3461731,America,2.85984093\r
-03/07/2020,3,7,2020,4,0,Uruguay,UY,URY,3461731,America,2.80206637\r
-02/07/2020,2,7,2020,7,1,Uruguay,UY,URY,3461731,America,2.71540452\r
-01/07/2020,1,7,2020,4,0,Uruguay,UY,URY,3461731,America,2.51319354\r
-30/06/2020,30,6,2020,3,0,Uruguay,UY,URY,3461731,America,2.4265317\r
-29/06/2020,29,6,2020,5,1,Uruguay,UY,URY,3461731,America,2.33986985\r
-28/06/2020,28,6,2020,5,0,Uruguay,UY,URY,3461731,America,2.22432072\r
-27/06/2020,27,6,2020,12,0,Uruguay,UY,URY,3461731,America,2.07988431\r
-26/06/2020,26,6,2020,5,0,Uruguay,UY,URY,3461731,America,1.73323693\r
-25/06/2020,25,6,2020,17,1,Uruguay,UY,URY,3461731,America,1.58880052\r
-24/06/2020,24,6,2020,3,0,Uruguay,UY,URY,3461731,America,1.126604\r
-23/06/2020,23,6,2020,6,0,Uruguay,UY,URY,3461731,America,1.06882944\r
-22/06/2020,22,6,2020,17,0,Uruguay,UY,URY,3461731,America,0.89550575\r
-21/06/2020,21,6,2020,6,1,Uruguay,UY,URY,3461731,America,0.40442195\r
-20/06/2020,20,6,2020,3,0,Uruguay,UY,URY,3461731,America,0.54885836\r
-19/06/2020,19,6,2020,1,0,Uruguay,UY,URY,3461731,America,0.51997108\r
-18/06/2020,18,6,2020,0,0,Uruguay,UY,URY,3461731,America,0.60663292\r
-17/06/2020,17,6,2020,1,1,Uruguay,UY,URY,3461731,America,0.66440749\r
-16/06/2020,16,6,2020,0,0,Uruguay,UY,URY,3461731,America,0.66440749\r
-15/06/2020,15,6,2020,1,0,Uruguay,UY,URY,3461731,America,0.72218205\r
-14/06/2020,14,6,2020,0,0,Uruguay,UY,URY,3461731,America,0.75106933\r
-13/06/2020,13,6,2020,0,0,Uruguay,UY,URY,3461731,America,0.89550575\r
-12/06/2020,12,6,2020,0,0,Uruguay,UY,URY,3461731,America,1.03994216\r
-11/06/2020,11,6,2020,1,0,Uruguay,UY,URY,3461731,America,1.27104041\r
-10/06/2020,10,6,2020,1,0,Uruguay,UY,URY,3461731,America,1.64657508\r
-09/06/2020,9,6,2020,0,0,Uruguay,UY,URY,3461731,America,1.67546236\r
-08/06/2020,8,6,2020,0,0,Uruguay,UY,URY,3461731,America,2.19543344\r
-07/06/2020,7,6,2020,11,0,Uruguay,UY,URY,3461731,America,2.33986985\r
-06/06/2020,6,6,2020,2,0,Uruguay,UY,URY,3461731,America,2.33986985\r
-05/06/2020,5,6,2020,4,0,Uruguay,UY,URY,3461731,America,2.39764442\r
-04/06/2020,4,6,2020,2,0,Uruguay,UY,URY,3461731,America,2.36875713\r
-03/06/2020,3,6,2020,1,0,Uruguay,UY,URY,3461731,America,2.54208083\r
-02/06/2020,2,6,2020,2,1,Uruguay,UY,URY,3461731,America,2.54208083\r
-01/06/2020,1,6,2020,2,0,Uruguay,UY,URY,3461731,America,2.57096811\r
-31/05/2020,31,5,2020,5,0,Uruguay,UY,URY,3461731,America,2.54208083\r
-30/05/2020,30,5,2020,5,0,Uruguay,UY,URY,3461731,America,2.4265317\r
-29/05/2020,29,5,2020,8,0,Uruguay,UY,URY,3461731,America,2.51319354\r
-28/05/2020,28,5,2020,14,0,Uruguay,UY,URY,3461731,America,2.4265317\r
-27/05/2020,27,5,2020,2,0,Uruguay,UY,URY,3461731,America,2.07988431\r
-26/05/2020,26,5,2020,18,0,Uruguay,UY,URY,3461731,America,2.19543344\r
-25/05/2020,25,5,2020,5,0,Uruguay,UY,URY,3461731,America,1.79101149\r
-24/05/2020,24,5,2020,11,2,Uruguay,UY,URY,3461731,America,1.79101149\r
-23/05/2020,23,5,2020,4,0,Uruguay,UY,URY,3461731,America,1.70434964\r
-22/05/2020,22,5,2020,3,0,Uruguay,UY,URY,3461731,America,1.87767334\r
-21/05/2020,21,5,2020,8,0,Uruguay,UY,URY,3461731,America,2.10877159\r
-20/05/2020,20,5,2020,1,0,Uruguay,UY,URY,3461731,America,1.96433518\r
-19/05/2020,19,5,2020,3,0,Uruguay,UY,URY,3461731,America,2.31098257\r
-18/05/2020,18,5,2020,1,1,Uruguay,UY,URY,3461731,America,2.28209529\r
-17/05/2020,17,5,2020,1,0,Uruguay,UY,URY,3461731,America,2.33986985\r
-16/05/2020,16,5,2020,8,0,Uruguay,UY,URY,3461731,America,2.4265317\r
-15/05/2020,15,5,2020,5,0,Uruguay,UY,URY,3461731,America,2.33986985\r
-14/05/2020,14,5,2020,2,0,Uruguay,UY,URY,3461731,America,2.57096811\r
-13/05/2020,13,5,2020,6,0,Uruguay,UY,URY,3461731,America,2.65762995\r
-12/05/2020,12,5,2020,4,0,Uruguay,UY,URY,3461731,America,2.62874267\r
-11/05/2020,11,5,2020,5,1,Uruguay,UY,URY,3461731,America,2.91761549\r
-10/05/2020,10,5,2020,8,0,Uruguay,UY,URY,3461731,America,3.0620519\r
-09/05/2020,9,5,2020,10,1,Uruguay,UY,URY,3461731,America,3.78423396\r
-08/05/2020,8,5,2020,11,0,Uruguay,UY,URY,3461731,America,3.66868483\r
-07/05/2020,7,5,2020,3,0,Uruguay,UY,URY,3461731,America,3.58202298\r
-06/05/2020,6,5,2020,13,0,Uruguay,UY,URY,3461731,America,3.66868483\r
-05/05/2020,5,5,2020,2,0,Uruguay,UY,URY,3461731,America,3.52424842\r
-04/05/2020,4,5,2020,3,0,Uruguay,UY,URY,3461731,America,3.66868483\r
-03/05/2020,3,5,2020,4,0,Uruguay,UY,URY,3461731,America,3.89978309\r
-02/05/2020,2,5,2020,5,0,Uruguay,UY,URY,3461731,America,4.0442195\r
-01/05/2020,1,5,2020,13,2,Uruguay,UY,URY,3461731,America,4.07310678\r
-30/04/2020,30,4,2020,5,0,Uruguay,UY,URY,3461731,America,3.95755765\r
-29/04/2020,29,4,2020,5,0,Uruguay,UY,URY,3461731,America,4.10199406\r
-28/04/2020,28,4,2020,14,0,Uruguay,UY,URY,3461731,America,4.27531775\r
-27/04/2020,27,4,2020,10,1,Uruguay,UY,URY,3461731,America,4.07310678\r
-26/04/2020,26,4,2020,33,2,Uruguay,UY,URY,3461731,America,4.13088134\r
-25/04/2020,25,4,2020,6,0,Uruguay,UY,URY,3461731,America,3.37981201\r
-24/04/2020,24,4,2020,8,0,Uruguay,UY,URY,3461731,America,3.58202298\r
-23/04/2020,23,4,2020,6,0,Uruguay,UY,URY,3461731,America,3.5531357\r
-22/04/2020,22,4,2020,8,2,Uruguay,UY,URY,3461731,America,3.63979755\r
-21/04/2020,21,4,2020,7,0,Uruguay,UY,URY,3461731,America,3.58202298\r
-20/04/2020,20,4,2020,11,1,Uruguay,UY,URY,3461731,America,3.49536114\r
-19/04/2020,19,4,2020,9,0,Uruguay,UY,URY,3461731,America,3.66868483\r
-18/04/2020,18,4,2020,6,0,Uruguay,UY,URY,3461731,America,3.95755765\r
-17/04/2020,17,4,2020,9,0,Uruguay,UY,URY,3461731,America,4.13088134\r
-16/04/2020,16,4,2020,10,1,Uruguay,UY,URY,3461731,America,4.39086688\r
-15/04/2020,15,4,2020,11,0,Uruguay,UY,URY,3461731,America,4.41975416\r
-14/04/2020,14,4,2020,7,0,Uruguay,UY,URY,3461731,America,4.27531775\r
-13/04/2020,13,4,2020,12,1,Uruguay,UY,URY,3461731,America,4.91083796\r
-12/04/2020,12,4,2020,7,0,Uruguay,UY,URY,3461731,America,5.60413273\r
-11/04/2020,11,4,2020,13,0,Uruguay,UY,URY,3461731,America,6.00855468\r
-10/04/2020,10,4,2020,7,0,Uruguay,UY,URY,3461731,America,5.63302001\r
-09/04/2020,9,4,2020,9,0,Uruguay,UY,URY,3461731,America,6.03744196\r
-08/04/2020,8,4,2020,6,1,Uruguay,UY,URY,3461731,America,6.58630032\r
-07/04/2020,7,4,2020,4,0,Uruguay,UY,URY,3461731,America,7.19293325\r
-06/04/2020,6,4,2020,17,1,Uruguay,UY,URY,3461731,America,7.19293325\r
-05/04/2020,5,4,2020,19,1,Uruguay,UY,URY,3461731,America,7.36625694\r
-04/04/2020,4,4,2020,12,0,Uruguay,UY,URY,3461731,America,7.53958063\r
-03/04/2020,3,4,2020,18,2,Uruguay,UY,URY,3461731,America,7.65512976\r
-02/04/2020,2,4,2020,11,1,Uruguay,UY,URY,3461731,America,7.56846791\r
-01/04/2020,1,4,2020,6,0,Uruguay,UY,URY,3461731,America,8.08843899\r
-31/03/2020,31,3,2020,29,0,Uruguay,UY,URY,3461731,America,8.52174822\r
-30/03/2020,30,3,2020,36,1,Uruguay,UY,URY,3461731,America,8.29064997\r
-29/03/2020,29,3,2020,21,0,Uruguay,UY,URY,3461731,America,7.30848237\r
-28/03/2020,28,3,2020,0,0,Uruguay,UY,URY,3461731,America,6.87517314\r
-27/03/2020,27,3,2020,21,0,Uruguay,UY,URY,3461731,America,\r
-26/03/2020,26,3,2020,28,0,Uruguay,UY,URY,3461731,America,\r
-25/03/2020,25,3,2020,27,0,Uruguay,UY,URY,3461731,America,\r
-24/03/2020,24,3,2020,4,0,Uruguay,UY,URY,3461731,America,\r
-23/03/2020,23,3,2020,23,0,Uruguay,UY,URY,3461731,America,\r
-22/03/2020,22,3,2020,25,0,Uruguay,UY,URY,3461731,America,\r
-21/03/2020,21,3,2020,16,0,Uruguay,UY,URY,3461731,America,\r
-20/03/2020,20,3,2020,15,0,Uruguay,UY,URY,3461731,America,\r
-19/03/2020,19,3,2020,29,0,Uruguay,UY,URY,3461731,America,\r
-18/03/2020,18,3,2020,21,0,Uruguay,UY,URY,3461731,America,\r
-17/03/2020,17,3,2020,21,0,Uruguay,UY,URY,3461731,America,\r
-16/03/2020,16,3,2020,2,0,Uruguay,UY,URY,3461731,America,\r
-15/03/2020,15,3,2020,6,0,Uruguay,UY,URY,3461731,America,\r
-19/08/2020,19,8,2020,660,5,Uzbekistan,UZ,UZB,32981715,Asia,30.95654668\r
-18/08/2020,18,8,2020,1156,12,Uzbekistan,UZ,UZB,32981715,Asia,31.14452963\r
-16/08/2020,16,8,2020,693,5,Uzbekistan,UZ,UZB,32981715,Asia,30.02875987\r
-15/08/2020,15,8,2020,690,5,Uzbekistan,UZ,UZB,32981715,Asia,30.15913515\r
-14/08/2020,14,8,2020,724,5,Uzbekistan,UZ,UZB,32981715,Asia,30.32892619\r
-13/08/2020,13,8,2020,622,5,Uzbekistan,UZ,UZB,32981715,Asia,30.21371084\r
-12/08/2020,12,8,2020,670,6,Uzbekistan,UZ,UZB,32981715,Asia,30.45930146\r
-11/08/2020,11,8,2020,725,6,Uzbekistan,UZ,UZB,32981715,Asia,30.43807758\r
-10/08/2020,10,8,2020,623,6,Uzbekistan,UZ,UZB,32981715,Asia,30.31983025\r
-09/08/2020,9,8,2020,738,5,Uzbekistan,UZ,UZB,32981715,Asia,30.23190274\r
-08/08/2020,8,8,2020,650,6,Uzbekistan,UZ,UZB,32981715,Asia,29.73162554\r
-07/08/2020,7,8,2020,740,6,Uzbekistan,UZ,UZB,32981715,Asia,29.78316925\r
-06/08/2020,6,8,2020,755,6,Uzbekistan,UZ,UZB,32981715,Asia,28.91905409\r
-05/08/2020,5,8,2020,764,6,Uzbekistan,UZ,UZB,32981715,Asia,27.72142079\r
-04/08/2020,4,8,2020,722,6,Uzbekistan,UZ,UZB,32981715,Asia,27.1665679\r
-03/08/2020,3,8,2020,788,6,Uzbekistan,UZ,UZB,32981715,Asia,26.86943356\r
-02/08/2020,2,8,2020,736,6,Uzbekistan,UZ,UZB,32981715,Asia,26.10840582\r
-01/08/2020,1,8,2020,746,6,Uzbekistan,UZ,UZB,32981715,Asia,25.49291327\r
-31/07/2020,31,7,2020,686,5,Uzbekistan,UZ,UZB,32981715,Asia,24.88954865\r
-30/07/2020,30,7,2020,703,5,Uzbekistan,UZ,UZB,32981715,Asia,24.51358275\r
-29/07/2020,29,7,2020,663,5,Uzbekistan,UZ,UZB,32981715,Asia,23.8798983\r
-28/07/2020,28,7,2020,686,5,Uzbekistan,UZ,UZB,32981715,Asia,23.14615841\r
-27/07/2020,27,7,2020,594,5,Uzbekistan,UZ,UZB,32981715,Asia,23.12493453\r
-26/07/2020,26,7,2020,573,5,Uzbekistan,UZ,UZB,32981715,Asia,23.38568507\r
-25/07/2020,25,7,2020,667,4,Uzbekistan,UZ,UZB,32981715,Asia,22.57917758\r
-24/07/2020,24,7,2020,455,4,Uzbekistan,UZ,UZB,32981715,Asia,22.02129271\r
-23/07/2020,23,7,2020,360,3,Uzbekistan,UZ,UZB,32981715,Asia,22.04858055\r
-22/07/2020,22,7,2020,581,4,Uzbekistan,UZ,UZB,32981715,Asia,22.23353152\r
-21/07/2020,21,7,2020,624,4,Uzbekistan,UZ,UZB,32981715,Asia,21.62107095\r
-20/07/2020,20,7,2020,537,4,Uzbekistan,UZ,UZB,32981715,Asia,20.68722018\r
-19/07/2020,19,7,2020,533,4,Uzbekistan,UZ,UZB,32981715,Asia,20.01108796\r
-18/07/2020,18,7,2020,547,4,Uzbekistan,UZ,UZB,32981715,Asia,19.39256342\r
-17/07/2020,17,7,2020,562,4,Uzbekistan,UZ,UZB,32981715,Asia,18.6466956\r
-16/07/2020,16,7,2020,494,4,Uzbekistan,UZ,UZB,32981715,Asia,17.83715613\r
-15/07/2020,15,7,2020,421,4,Uzbekistan,UZ,UZB,32981715,Asia,17.17921582\r
-14/07/2020,14,7,2020,679,3,Uzbekistan,UZ,UZB,32981715,Asia,16.90027338\r
-13/07/2020,13,7,2020,680,4,Uzbekistan,UZ,UZB,32981715,Asia,15.65109637\r
-12/07/2020,12,7,2020,307,2,Uzbekistan,UZ,UZB,32981715,Asia,14.51713472\r
-11/07/2020,11,7,2020,483,3,Uzbekistan,UZ,UZB,32981715,Asia,14.29883194\r
-10/07/2020,10,7,2020,464,5,Uzbekistan,UZ,UZB,32981715,Asia,13.6287637\r
-09/07/2020,9,7,2020,421,6,Uzbekistan,UZ,UZB,32981715,Asia,12.94353553\r
-08/07/2020,8,7,2020,379,3,Uzbekistan,UZ,UZB,32981715,Asia,12.37958669\r
-07/07/2020,7,7,2020,316,3,Uzbekistan,UZ,UZB,32981715,Asia,12.00362079\r
-06/07/2020,6,7,2020,314,4,Uzbekistan,UZ,UZB,32981715,Asia,11.47605575\r
-05/07/2020,5,7,2020,329,2,Uzbekistan,UZ,UZB,32981715,Asia,10.95455467\r
-04/07/2020,4,7,2020,301,2,Uzbekistan,UZ,UZB,32981715,Asia,10.53614101\r
-03/07/2020,3,7,2020,295,1,Uzbekistan,UZ,UZB,32981715,Asia,10.13895123\r
-02/07/2020,2,7,2020,277,0,Uzbekistan,UZ,UZB,32981715,Asia,9.72356956\r
-01/07/2020,1,7,2020,329,2,Uzbekistan,UZ,UZB,32981715,Asia,9.29605995\r
-30/06/2020,30,6,2020,267,2,Uzbekistan,UZ,UZB,32981715,Asia,9.11110899\r
-29/06/2020,29,6,2020,306,2,Uzbekistan,UZ,UZB,32981715,Asia,8.8776463\r
-28/06/2020,28,6,2020,235,0,Uzbekistan,UZ,UZB,32981715,Asia,8.28034564\r
-27/06/2020,27,6,2020,262,0,Uzbekistan,UZ,UZB,32981715,Asia,7.84980405\r
-26/06/2020,26,6,2020,238,1,Uzbekistan,UZ,UZB,32981715,Asia,7.30404711\r
-25/06/2020,25,6,2020,235,0,Uzbekistan,UZ,UZB,32981715,Asia,6.95840104\r
-24/06/2020,24,6,2020,255,0,Uzbekistan,UZ,UZB,32981715,Asia,6.69461852\r
-23/06/2020,23,6,2020,142,0,Uzbekistan,UZ,UZB,32981715,Asia,6.22162917\r
-22/06/2020,22,6,2020,142,0,Uzbekistan,UZ,UZB,32981715,Asia,6.08215795\r
-21/06/2020,21,6,2020,191,0,Uzbekistan,UZ,UZB,32981715,Asia,6.17008545\r
-20/06/2020,20,6,2020,170,0,Uzbekistan,UZ,UZB,32981715,Asia,6.073062\r
-19/06/2020,19,6,2020,158,0,Uzbekistan,UZ,UZB,32981715,Asia,5.73044792\r
-18/06/2020,18,6,2020,136,0,Uzbekistan,UZ,UZB,32981715,Asia,5.52730505\r
-17/06/2020,17,6,2020,268,0,Uzbekistan,UZ,UZB,32981715,Asia,5.43331358\r
-16/06/2020,16,6,2020,190,0,Uzbekistan,UZ,UZB,32981715,Asia,4.77537326\r
-15/06/2020,15,6,2020,109,0,Uzbekistan,UZ,UZB,32981715,Asia,4.36908754\r
-14/06/2020,14,6,2020,93,0,Uzbekistan,UZ,UZB,32981715,Asia,4.36605556\r
-13/06/2020,13,6,2020,82,0,Uzbekistan,UZ,UZB,32981715,Asia,4.20839244\r
-12/06/2020,12,6,2020,124,0,Uzbekistan,UZ,UZB,32981715,Asia,4.16897666\r
-11/06/2020,11,6,2020,148,1,Uzbekistan,UZ,UZB,32981715,Asia,4.12956088\r
-10/06/2020,10,6,2020,99,0,Uzbekistan,UZ,UZB,32981715,Asia,3.68082739\r
-09/06/2020,9,6,2020,96,1,Uzbekistan,UZ,UZB,32981715,Asia,3.59896385\r
-08/06/2020,8,6,2020,171,0,Uzbekistan,UZ,UZB,32981715,Asia,3.60199583\r
-07/06/2020,7,6,2020,159,1,Uzbekistan,UZ,UZB,32981715,Asia,3.18055019\r
-06/06/2020,6,6,2020,57,0,Uzbekistan,UZ,UZB,32981715,Asia,2.86219198\r
-05/06/2020,5,6,2020,91,0,Uzbekistan,UZ,UZB,32981715,Asia,2.90767172\r
-04/06/2020,4,6,2020,105,1,Uzbekistan,UZ,UZB,32981715,Asia,2.80155231\r
-03/06/2020,3,6,2020,51,0,Uzbekistan,UZ,UZB,32981715,Asia,2.69543291\r
-02/06/2020,2,6,2020,56,0,Uzbekistan,UZ,UZB,32981715,Asia,2.77729645\r
-01/06/2020,1,6,2020,108,1,Uzbekistan,UZ,UZB,32981715,Asia,2.75607257\r
-31/05/2020,31,5,2020,41,0,Uzbekistan,UZ,UZB,32981715,Asia,2.4650022\r
-30/05/2020,30,5,2020,69,0,Uzbekistan,UZ,UZB,32981715,Asia,2.49229005\r
-29/05/2020,29,5,2020,111,0,Uzbekistan,UZ,UZB,32981715,Asia,2.42255444\r
-28/05/2020,28,5,2020,0,0,Uzbekistan,UZ,UZB,32981715,Asia,2.18605976\r
-27/05/2020,27,5,2020,72,1,Uzbekistan,UZ,UZB,32981715,Asia,2.38313866\r
-26/05/2020,26,5,2020,97,0,Uzbekistan,UZ,UZB,32981715,Asia,2.28005123\r
-25/05/2020,25,5,2020,32,0,Uzbekistan,UZ,UZB,32981715,Asia,2.26185934\r
-24/05/2020,24,5,2020,54,0,Uzbekistan,UZ,UZB,32981715,Asia,2.25882735\r
-23/05/2020,23,5,2020,72,0,Uzbekistan,UZ,UZB,32981715,Asia,2.2497314\r
-22/05/2020,22,5,2020,56,0,Uzbekistan,UZ,UZB,32981715,Asia,2.14664398\r
-21/05/2020,21,5,2020,70,0,Uzbekistan,UZ,UZB,32981715,Asia,2.17393183\r
-20/05/2020,20,5,2020,78,0,Uzbekistan,UZ,UZB,32981715,Asia,2.04052458\r
-19/05/2020,19,5,2020,49,1,Uzbekistan,UZ,UZB,32981715,Asia,1.85860559\r
-18/05/2020,18,5,2020,12,1,Uzbekistan,UZ,UZB,32981715,Asia,1.83131775\r
-17/05/2020,17,5,2020,50,0,Uzbekistan,UZ,UZB,32981715,Asia,1.86163758\r
-16/05/2020,16,5,2020,46,0,Uzbekistan,UZ,UZB,32981715,Asia,1.81009387\r
-15/05/2020,15,5,2020,33,0,Uzbekistan,UZ,UZB,32981715,Asia,1.81615783\r
-14/05/2020,14,5,2020,65,1,Uzbekistan,UZ,UZB,32981715,Asia,1.84950964\r
-13/05/2020,13,5,2020,38,0,Uzbekistan,UZ,UZB,32981715,Asia,1.84344568\r
-12/05/2020,12,5,2020,91,0,Uzbekistan,UZ,UZB,32981715,Asia,1.83434973\r
-11/05/2020,11,5,2020,31,0,Uzbekistan,UZ,UZB,32981715,Asia,1.60998299\r
-10/05/2020,10,5,2020,51,0,Uzbekistan,UZ,UZB,32981715,Asia,1.58269514\r
-09/05/2020,9,5,2020,38,0,Uzbekistan,UZ,UZB,32981715,Asia,1.51599151\r
-08/05/2020,8,5,2020,65,0,Uzbekistan,UZ,UZB,32981715,Asia,1.57663117\r
-07/05/2020,7,5,2020,26,0,Uzbekistan,UZ,UZB,32981715,Asia,1.56753522\r
-06/05/2020,6,5,2020,18,0,Uzbekistan,UZ,UZB,32981715,Asia,1.56147126\r
-05/05/2020,5,5,2020,40,0,Uzbekistan,UZ,UZB,32981715,Asia,1.61301497\r
-04/05/2020,4,5,2020,22,1,Uzbekistan,UZ,UZB,32981715,Asia,1.77067809\r
-03/05/2020,3,5,2020,33,0,Uzbekistan,UZ,UZB,32981715,Asia,1.91621327\r
-02/05/2020,2,5,2020,48,0,Uzbekistan,UZ,UZB,32981715,Asia,1.95259707\r
-01/05/2020,1,5,2020,44,0,Uzbekistan,UZ,UZB,32981715,Asia,2.01930069\r
-30/04/2020,30,4,2020,63,1,Uzbekistan,UZ,UZB,32981715,Asia,2.12238812\r
-29/04/2020,29,4,2020,35,0,Uzbekistan,UZ,UZB,32981715,Asia,2.34675486\r
-28/04/2020,28,4,2020,17,0,Uzbekistan,UZ,UZB,32981715,Asia,2.74697662\r
-27/04/2020,27,4,2020,22,0,Uzbekistan,UZ,UZB,32981715,Asia,3.09868665\r
-26/04/2020,26,4,2020,29,0,Uzbekistan,UZ,UZB,32981715,Asia,3.24118985\r
-25/04/2020,25,4,2020,58,1,Uzbekistan,UZ,UZB,32981715,Asia,3.67476343\r
-24/04/2020,24,4,2020,62,0,Uzbekistan,UZ,UZB,32981715,Asia,3.6262517\r
-23/04/2020,23,4,2020,24,1,Uzbekistan,UZ,UZB,32981715,Asia,3.52013229\r
-22/04/2020,22,4,2020,35,1,Uzbekistan,UZ,UZB,32981715,Asia,3.60199583\r
-21/04/2020,21,4,2020,92,0,Uzbekistan,UZ,UZB,32981715,Asia,3.82029861\r
-20/04/2020,20,4,2020,70,0,Uzbekistan,UZ,UZB,32981715,Asia,3.70811524\r
-19/04/2020,19,4,2020,45,1,Uzbekistan,UZ,UZB,32981715,Asia,3.72630714\r
-18/04/2020,18,4,2020,70,0,Uzbekistan,UZ,UZB,32981715,Asia,3.70811524\r
-17/04/2020,17,4,2020,78,0,Uzbekistan,UZ,UZB,32981715,Asia,3.6080598\r
-16/04/2020,16,4,2020,137,0,Uzbekistan,UZ,UZB,32981715,Asia,3.38066107\r
-15/04/2020,15,4,2020,167,0,Uzbekistan,UZ,UZB,32981715,Asia,3.00772716\r
-14/04/2020,14,4,2020,133,0,Uzbekistan,UZ,UZB,32981715,Asia,2.57415359\r
-13/04/2020,13,4,2020,69,0,Uzbekistan,UZ,UZB,32981715,Asia,2.18302778\r
-12/04/2020,12,4,2020,172,1,Uzbekistan,UZ,UZB,32981715,Asia,2.01020475\r
-11/04/2020,11,4,2020,42,0,Uzbekistan,UZ,UZB,32981715,Asia,1.57663117\r
-10/04/2020,10,4,2020,27,0,Uzbekistan,UZ,UZB,32981715,Asia,1.51295953\r
-09/04/2020,9,4,2020,51,1,Uzbekistan,UZ,UZB,32981715,Asia,1.48567168\r
-08/04/2020,8,4,2020,107,0,Uzbekistan,UZ,UZB,32981715,Asia,1.36136038\r
-07/04/2020,7,4,2020,55,0,Uzbekistan,UZ,UZB,32981715,Asia,1.05513009\r
-06/04/2020,6,4,2020,76,0,Uzbekistan,UZ,UZB,32981715,Asia,0.89746698\r
-05/04/2020,5,4,2020,39,0,Uzbekistan,UZ,UZB,32981715,Asia,0.70645204\r
-04/04/2020,4,4,2020,37,0,Uzbekistan,UZ,UZB,32981715,Asia,0.58820471\r
-03/04/2020,3,4,2020,3,0,Uzbekistan,UZ,UZB,32981715,Asia,0.50634117\r
-02/04/2020,2,4,2020,14,0,Uzbekistan,UZ,UZB,32981715,Asia,0.49724522\r
-01/04/2020,1,4,2020,24,0,Uzbekistan,UZ,UZB,32981715,Asia,0.47602133\r
-31/03/2020,31,3,2020,4,1,Uzbekistan,UZ,UZB,32981715,Asia,0.42750961\r
-30/03/2020,30,3,2020,12,0,Uzbekistan,UZ,UZB,32981715,Asia,0.42144564\r
-29/03/2020,29,3,2020,29,1,Uzbekistan,UZ,UZB,32981715,Asia,0.40325374\r
-28/03/2020,28,3,2020,21,0,Uzbekistan,UZ,UZB,32981715,Asia,\r
-27/03/2020,27,3,2020,18,0,Uzbekistan,UZ,UZB,32981715,Asia,\r
-26/03/2020,26,3,2020,10,0,Uzbekistan,UZ,UZB,32981715,Asia,\r
-25/03/2020,25,3,2020,6,0,Uzbekistan,UZ,UZB,32981715,Asia,\r
-24/03/2020,24,3,2020,3,0,Uzbekistan,UZ,UZB,32981715,Asia,\r
-23/03/2020,23,3,2020,13,0,Uzbekistan,UZ,UZB,32981715,Asia,\r
-22/03/2020,22,3,2020,0,0,Uzbekistan,UZ,UZB,32981715,Asia,\r
-21/03/2020,21,3,2020,10,0,Uzbekistan,UZ,UZB,32981715,Asia,\r
-20/03/2020,20,3,2020,0,0,Uzbekistan,UZ,UZB,32981715,Asia,\r
-19/03/2020,19,3,2020,7,0,Uzbekistan,UZ,UZB,32981715,Asia,\r
-18/03/2020,18,3,2020,8,0,Uzbekistan,UZ,UZB,32981715,Asia,\r
-17/03/2020,17,3,2020,2,0,Uzbekistan,UZ,UZB,32981715,Asia,\r
-16/03/2020,16,3,2020,6,0,Uzbekistan,UZ,UZB,32981715,Asia,\r
-19/08/2020,19,8,2020,895,9,Venezuela,VE,VEN,28515829,America,50.00380666\r
-18/08/2020,18,8,2020,1047,7,Venezuela,VE,VEN,28515829,America,51.18560642\r
-17/08/2020,17,8,2020,1148,5,Venezuela,VE,VEN,28515829,America,47.51396146\r
-16/08/2020,16,8,2020,1226,10,Venezuela,VE,VEN,28515829,America,46.16383413\r
-15/08/2020,15,8,2020,1012,7,Venezuela,VE,VEN,28515829,America,44.91189788\r
-14/08/2020,14,8,2020,1281,12,Venezuela,VE,VEN,28515829,America,43.87037108\r
-13/08/2020,13,8,2020,1150,9,Venezuela,VE,VEN,28515829,America,43.89491885\r
-12/08/2020,12,8,2020,2133,15,Venezuela,VE,VEN,28515829,America,39.86207099\r
-11/08/2020,11,8,2020,0,0,Venezuela,VE,VEN,28515829,America,34.42649344\r
-10/08/2020,10,8,2020,1639,15,Venezuela,VE,VEN,28515829,America,36.26757616\r
-09/08/2020,9,8,2020,0,0,Venezuela,VE,VEN,28515829,America,34.72808032\r
-08/08/2020,8,8,2020,886,6,Venezuela,VE,VEN,28515829,America,34.72808032\r
-07/08/2020,7,8,2020,981,7,Venezuela,VE,VEN,28515829,America,33.90046981\r
-06/08/2020,6,8,2020,861,8,Venezuela,VE,VEN,28515829,America,33.40250077\r
-05/08/2020,5,8,2020,1232,13,Venezuela,VE,VEN,28515829,America,30.38312511\r
-04/08/2020,4,8,2020,0,0,Venezuela,VE,VEN,28515829,America,27.60572032\r
-03/08/2020,3,8,2020,763,5,Venezuela,VE,VEN,28515829,America,29.15924345\r
-02/08/2020,2,8,2020,869,5,Venezuela,VE,VEN,28515829,America,27.91432085\r
-01/08/2020,1,8,2020,715,6,Venezuela,VE,VEN,28515829,America,25.89088327\r
-31/07/2020,31,7,2020,1288,7,Venezuela,VE,VEN,28515829,America,24.56530371\r
-30/07/2020,30,7,2020,0,0,Venezuela,VE,VEN,28515829,America,21.54242123\r
-29/07/2020,29,7,2020,583,5,Venezuela,VE,VEN,28515829,America,23.00827376\r
-28/07/2020,28,7,2020,525,4,Venezuela,VE,VEN,28515829,America,22.02636297\r
-27/07/2020,27,7,2020,1200,8,Venezuela,VE,VEN,28515829,America,21.03393172\r
-26/07/2020,26,7,2020,0,0,Venezuela,VE,VEN,28515829,America,17.8322012\r
-25/07/2020,25,7,2020,650,5,Venezuela,VE,VEN,28515829,America,19.14726028\r
-24/07/2020,24,7,2020,839,9,Venezuela,VE,VEN,28515829,America,18.37926578\r
-23/07/2020,23,7,2020,0,0,Venezuela,VE,VEN,28515829,America,16.70651062\r
-22/07/2020,22,7,2020,440,4,Venezuela,VE,VEN,28515829,America,17.8181739\r
-21/07/2020,21,7,2020,443,4,Venezuela,VE,VEN,28515829,America,17.26409567\r
-20/07/2020,20,7,2020,408,2,Venezuela,VE,VEN,28515829,America,16.559224\r
-19/07/2020,19,7,2020,292,3,Venezuela,VE,VEN,28515829,America,16.59779907\r
-18/07/2020,18,7,2020,337,3,Venezuela,VE,VEN,28515829,America,16.32075995\r
-17/07/2020,17,7,2020,426,4,Venezuela,VE,VEN,28515829,America,16.06476179\r
-16/07/2020,16,7,2020,418,4,Venezuela,VE,VEN,28515829,America,15.31079458\r
-15/07/2020,15,7,2020,303,3,Venezuela,VE,VEN,28515829,America,14.65151162\r
-14/07/2020,14,7,2020,242,4,Venezuela,VE,VEN,28515829,America,14.6480048\r
-13/07/2020,13,7,2020,287,4,Venezuela,VE,VEN,28515829,America,14.61644338\r
-12/07/2020,12,7,2020,375,2,Venezuela,VE,VEN,28515829,America,14.19562447\r
-11/07/2020,11,7,2020,431,3,Venezuela,VE,VEN,28515829,America,14.11146069\r
-10/07/2020,10,7,2020,362,5,Venezuela,VE,VEN,28515829,America,13.35749348\r
-09/07/2020,9,7,2020,317,4,Venezuela,VE,VEN,28515829,America,12.78237431\r
-08/07/2020,8,7,2020,282,3,Venezuela,VE,VEN,28515829,America,12.29843257\r
-07/07/2020,7,7,2020,242,4,Venezuela,VE,VEN,28515829,America,11.79344988\r
-06/07/2020,6,7,2020,419,2,Venezuela,VE,VEN,28515829,America,11.40068556\r
-05/07/2020,5,7,2020,213,3,Venezuela,VE,VEN,28515829,America,10.38019971\r
-04/07/2020,4,7,2020,264,2,Venezuela,VE,VEN,28515829,America,10.33110417\r
-03/07/2020,3,7,2020,211,3,Venezuela,VE,VEN,28515829,America,9.78053277\r
-02/07/2020,2,7,2020,230,3,Venezuela,VE,VEN,28515829,America,10.21187215\r
-01/07/2020,1,7,2020,302,3,Venezuela,VE,VEN,28515829,America,9.71390311\r
-30/06/2020,30,6,2020,233,4,Venezuela,VE,VEN,28515829,America,8.94941543\r
-29/06/2020,29,6,2020,167,2,Venezuela,VE,VEN,28515829,America,8.39183038\r
-28/06/2020,28,6,2020,351,1,Venezuela,VE,VEN,28515829,America,7.89386134\r
-27/06/2020,27,6,2020,216,2,Venezuela,VE,VEN,28515829,America,6.89090961\r
-26/06/2020,26,6,2020,198,1,Venezuela,VE,VEN,28515829,America,6.39995421\r
-25/06/2020,25,6,2020,179,3,Venezuela,VE,VEN,28515829,America,6.07732639\r
-24/06/2020,24,6,2020,138,0,Venezuela,VE,VEN,28515829,America,6.0071899\r
-23/06/2020,23,6,2020,130,2,Venezuela,VE,VEN,28515829,America,5.85990328\r
-22/06/2020,22,6,2020,128,0,Venezuela,VE,VEN,28515829,America,5.61793241\r
-21/06/2020,21,6,2020,199,3,Venezuela,VE,VEN,28515829,America,5.76872585\r
-20/06/2020,20,6,2020,107,2,Venezuela,VE,VEN,28515829,America,5.27426364\r
-19/06/2020,19,6,2020,334,1,Venezuela,VE,VEN,28515829,America,5.37245472\r
-17/06/2020,17,6,2020,88,1,Venezuela,VE,VEN,28515829,America,4.66758305\r
-16/06/2020,16,6,2020,84,1,Venezuela,VE,VEN,28515829,America,4.90955392\r
-15/06/2020,15,6,2020,74,1,Venezuela,VE,VEN,28515829,America,5.14801797\r
-14/06/2020,14,6,2020,25,1,Venezuela,VE,VEN,28515829,America,5.06736101\r
-13/06/2020,13,6,2020,65,0,Venezuela,VE,VEN,28515829,America,5.29530458\r
-12/06/2020,12,6,2020,76,0,Venezuela,VE,VEN,28515829,America,5.21464763\r
-11/06/2020,11,6,2020,106,0,Venezuela,VE,VEN,28515829,America,5.23568857\r
-10/06/2020,10,6,2020,159,1,Venezuela,VE,VEN,28515829,America,4.98319723\r
-09/06/2020,9,6,2020,96,0,Venezuela,VE,VEN,28515829,America,4.5448442\r
-08/06/2020,8,6,2020,61,0,Venezuela,VE,VEN,28515829,America,4.40457123\r
-07/06/2020,7,6,2020,171,2,Venezuela,VE,VEN,28515829,America,4.81136284\r
-06/06/2020,6,6,2020,58,0,Venezuela,VE,VEN,28515829,America,4.2116959\r
-05/06/2020,5,6,2020,135,0,Venezuela,VE,VEN,28515829,America,4.22572319\r
-04/06/2020,4,6,2020,133,2,Venezuela,VE,VEN,28515829,America,3.95569773\r
-03/06/2020,3,6,2020,157,1,Venezuela,VE,VEN,28515829,America,3.75230192\r
-02/06/2020,2,6,2020,152,3,Venezuela,VE,VEN,28515829,America,3.66112449\r
-01/06/2020,1,6,2020,51,0,Venezuela,VE,VEN,28515829,America,3.39811268\r
-31/05/2020,31,5,2020,90,0,Venezuela,VE,VEN,28515829,America,3.34901714\r
-30/05/2020,30,5,2020,42,3,Venezuela,VE,VEN,28515829,America,3.19121005\r
-29/05/2020,29,5,2020,82,0,Venezuela,VE,VEN,28515829,America,3.05795073\r
-28/05/2020,28,5,2020,34,0,Venezuela,VE,VEN,28515829,America,2.8229935\r
-27/05/2020,27,5,2020,34,1,Venezuela,VE,VEN,28515829,America,2.76337749\r
-26/05/2020,26,5,2020,56,0,Venezuela,VE,VEN,28515829,America,2.64765229\r
-25/05/2020,25,5,2020,177,0,Venezuela,VE,VEN,28515829,America,2.47932473\r
-24/05/2020,24,5,2020,0,0,Venezuela,VE,VEN,28515829,America,1.90069873\r
-23/05/2020,23,5,2020,62,0,Venezuela,VE,VEN,28515829,America,1.94979427\r
-22/05/2020,22,5,2020,58,0,Venezuela,VE,VEN,28515829,America,1.75691894\r
-21/05/2020,21,5,2020,75,0,Venezuela,VE,VEN,28515829,America,1.56053678\r
-20/05/2020,20,5,2020,131,0,Venezuela,VE,VEN,28515829,America,1.33960685\r
-19/05/2020,19,5,2020,77,0,Venezuela,VE,VEN,28515829,America,0.90125383\r
-18/05/2020,18,5,2020,37,0,Venezuela,VE,VEN,28515829,America,0.64525566\r
-17/05/2020,17,5,2020,45,0,Venezuela,VE,VEN,28515829,America,0.55758505\r
-16/05/2020,16,5,2020,4,0,Venezuela,VE,VEN,28515829,America,0.4348462\r
-15/05/2020,15,5,2020,15,0,Venezuela,VE,VEN,28515829,America,0.42783256\r
-14/05/2020,14,5,2020,17,0,Venezuela,VE,VEN,28515829,America,0.38224384\r
-13/05/2020,13,5,2020,1,0,Venezuela,VE,VEN,28515829,America,0.32964148\r
-12/05/2020,12,5,2020,8,0,Venezuela,VE,VEN,28515829,America,0.32613465\r
-11/05/2020,11,5,2020,12,0,Venezuela,VE,VEN,28515829,America,0.31210736\r
-10/05/2020,10,5,2020,14,0,Venezuela,VE,VEN,28515829,America,0.27703911\r
-09/05/2020,9,5,2020,7,0,Venezuela,VE,VEN,28515829,America,0.2454777\r
-08/05/2020,8,5,2020,2,0,Venezuela,VE,VEN,28515829,America,0.29106641\r
-07/05/2020,7,5,2020,12,0,Venezuela,VE,VEN,28515829,America,0.319121\r
-06/05/2020,6,5,2020,6,0,Venezuela,VE,VEN,28515829,America,0.28755959\r
-05/05/2020,5,5,2020,4,0,Venezuela,VE,VEN,28515829,America,0.36821654\r
-04/05/2020,4,5,2020,12,0,Venezuela,VE,VEN,28515829,America,0.35418925\r
-03/05/2020,3,5,2020,10,0,Venezuela,VE,VEN,28515829,America,0.41380526\r
-02/05/2020,2,5,2020,2,0,Venezuela,VE,VEN,28515829,America,0.37873702\r
-01/05/2020,1,5,2020,2,0,Venezuela,VE,VEN,28515829,America,0.45238033\r
-30/04/2020,30,4,2020,2,0,Venezuela,VE,VEN,28515829,America,0.46991445\r
-29/04/2020,29,4,2020,0,0,Venezuela,VE,VEN,28515829,America,0.47692809\r
-28/04/2020,28,4,2020,4,0,Venezuela,VE,VEN,28515829,America,0.49095539\r
-27/04/2020,27,4,2020,2,0,Venezuela,VE,VEN,28515829,America,0.50498269\r
-26/04/2020,26,4,2020,5,0,Venezuela,VE,VEN,28515829,America,0.51900999\r
-25/04/2020,25,4,2020,20,0,Venezuela,VE,VEN,28515829,America,0.50147586\r
-24/04/2020,24,4,2020,10,0,Venezuela,VE,VEN,28515829,America,0.44536668\r
-23/04/2020,23,4,2020,3,0,Venezuela,VE,VEN,28515829,America,0.42432573\r
-22/04/2020,22,4,2020,29,1,Venezuela,VE,VEN,28515829,America,0.41731208\r
-21/04/2020,21,4,2020,0,0,Venezuela,VE,VEN,28515829,America,0.34016195\r
-20/04/2020,20,4,2020,29,0,Venezuela,VE,VEN,28515829,America,0.37873702\r
-19/04/2020,19,4,2020,0,0,Venezuela,VE,VEN,28515829,America,0.29106641\r
-18/04/2020,18,4,2020,23,0,Venezuela,VE,VEN,28515829,America,0.29106641\r
-17/04/2020,17,4,2020,7,0,Venezuela,VE,VEN,28515829,America,0.21040945\r
-16/04/2020,16,4,2020,4,0,Venezuela,VE,VEN,28515829,America,0.18936851\r
-15/04/2020,15,4,2020,4,0,Venezuela,VE,VEN,28515829,America,0.20339581\r
-14/04/2020,14,4,2020,8,0,Venezuela,VE,VEN,28515829,America,0.18936851\r
-13/04/2020,13,4,2020,6,0,Venezuela,VE,VEN,28515829,America,0.2174231\r
-12/04/2020,12,4,2020,0,0,Venezuela,VE,VEN,28515829,America,0.19638216\r
-11/04/2020,11,4,2020,4,0,Venezuela,VE,VEN,28515829,America,0.19638216\r
-10/04/2020,10,4,2020,4,1,Venezuela,VE,VEN,28515829,America,0.22443675\r
-09/04/2020,9,4,2020,1,1,Venezuela,VE,VEN,28515829,America,0.21391628\r
-08/04/2020,8,4,2020,7,2,Venezuela,VE,VEN,28515829,America,0.26301182\r
-07/04/2020,7,4,2020,11,0,Venezuela,VE,VEN,28515829,America,0.26301182\r
-06/04/2020,6,4,2020,4,0,Venezuela,VE,VEN,28515829,America,0.39276431\r
-05/04/2020,5,4,2020,0,2,Venezuela,VE,VEN,28515829,America,0.37873702\r
-04/04/2020,4,4,2020,0,0,Venezuela,VE,VEN,28515829,America,0.37873702\r
-03/04/2020,3,4,2020,1,0,Venezuela,VE,VEN,28515829,America,0.38925749\r
-02/04/2020,2,4,2020,8,0,Venezuela,VE,VEN,28515829,America,0.38575067\r
-01/04/2020,1,4,2020,0,0,Venezuela,VE,VEN,28515829,America,0.35769607\r
-31/03/2020,31,3,2020,16,2,Venezuela,VE,VEN,28515829,America,0.35769607\r
-30/03/2020,30,3,2020,0,0,Venezuela,VE,VEN,28515829,America,0.36470972\r
-29/03/2020,29,3,2020,0,0,Venezuela,VE,VEN,28515829,America,0.38224384\r
-28/03/2020,28,3,2020,12,0,Venezuela,VE,VEN,28515829,America,0.41731208\r
-27/03/2020,27,3,2020,1,1,Venezuela,VE,VEN,28515829,America,\r
-26/03/2020,26,3,2020,15,0,Venezuela,VE,VEN,28515829,America,\r
-25/03/2020,25,3,2020,7,0,Venezuela,VE,VEN,28515829,America,\r
-24/03/2020,24,3,2020,48,0,Venezuela,VE,VEN,28515829,America,\r
-23/03/2020,23,3,2020,0,0,Venezuela,VE,VEN,28515829,America,\r
-22/03/2020,22,3,2020,0,0,Venezuela,VE,VEN,28515829,America,\r
-21/03/2020,21,3,2020,3,0,Venezuela,VE,VEN,28515829,America,\r
-20/03/2020,20,3,2020,0,0,Venezuela,VE,VEN,28515829,America,\r
-19/03/2020,19,3,2020,0,0,Venezuela,VE,VEN,28515829,America,\r
-18/03/2020,18,3,2020,0,0,Venezuela,VE,VEN,28515829,America,\r
-17/03/2020,17,3,2020,18,0,Venezuela,VE,VEN,28515829,America,\r
-16/03/2020,16,3,2020,5,0,Venezuela,VE,VEN,28515829,America,\r
-15/03/2020,15,3,2020,10,0,Venezuela,VE,VEN,28515829,America,\r
-19/08/2020,19,8,2020,6,1,Vietnam,VN,VNM,96462108,Asia,0.32862645\r
-18/08/2020,18,8,2020,19,1,Vietnam,VN,VNM,96462108,Asia,0.34313992\r
-17/08/2020,17,8,2020,30,2,Vietnam,VN,VNM,96462108,Asia,0.35558004\r
-16/08/2020,16,8,2020,4,1,Vietnam,VN,VNM,96462108,Asia,0.35661671\r
-15/08/2020,15,8,2020,19,0,Vietnam,VN,VNM,96462108,Asia,0.38564366\r
-14/08/2020,14,8,2020,28,3,Vietnam,VN,VNM,96462108,Asia,0.41674395\r
-13/08/2020,13,8,2020,17,1,Vietnam,VN,VNM,96462108,Asia,0.43955083\r
-12/08/2020,12,8,2020,20,4,Vietnam,VN,VNM,96462108,Asia,0.44888092\r
-11/08/2020,11,8,2020,5,0,Vietnam,VN,VNM,96462108,Asia,0.43022075\r
-10/08/2020,10,8,2020,29,3,Vietnam,VN,VNM,96462108,Asia,0.4364408\r
-09/08/2020,9,8,2020,23,0,Vietnam,VN,VNM,96462108,Asia,0.41156057\r
-08/08/2020,8,8,2020,39,0,Vietnam,VN,VNM,96462108,Asia,0.38771701\r
-07/08/2020,7,8,2020,33,1,Vietnam,VN,VNM,96462108,Asia,0.35039666\r
-06/08/2020,6,8,2020,45,1,Vietnam,VN,VNM,96462108,Asia,0.32033304\r
-05/08/2020,5,8,2020,20,0,Vietnam,VN,VNM,96462108,Asia,0.28093933\r
-04/08/2020,4,8,2020,31,2,Vietnam,VN,VNM,96462108,Asia,0.28923274\r
-03/08/2020,3,8,2020,31,1,Vietnam,VN,VNM,96462108,Asia,0.25709577\r
-02/08/2020,2,8,2020,32,2,Vietnam,VN,VNM,96462108,Asia,0.2249588\r
-01/08/2020,1,8,2020,49,3,Vietnam,VN,VNM,96462108,Asia,0.19178515\r
-31/07/2020,31,7,2020,50,0,Vietnam,VN,VNM,96462108,Asia,0.140988\r
-30/07/2020,30,7,2020,26,0,Vietnam,VN,VNM,96462108,Asia,0.08915418\r
-29/07/2020,29,7,2020,2,0,Vietnam,VN,VNM,96462108,Asia,0.06220059\r
-28/07/2020,28,7,2020,11,0,Vietnam,VN,VNM,96462108,Asia,0.06012724\r
-27/07/2020,27,7,2020,5,0,Vietnam,VN,VNM,96462108,Asia,0.04976047\r
-26/07/2020,26,7,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.04665044\r
-25/07/2020,25,7,2020,3,0,Vietnam,VN,VNM,96462108,Asia,0.04665044\r
-24/07/2020,24,7,2020,4,0,Vietnam,VN,VNM,96462108,Asia,0.04457709\r
-23/07/2020,23,7,2020,7,0,Vietnam,VN,VNM,96462108,Asia,0.04043038\r
-22/07/2020,22,7,2020,28,0,Vietnam,VN,VNM,96462108,Asia,0.03317365\r
-21/07/2020,21,7,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00414671\r
-20/07/2020,20,7,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.01866018\r
-19/07/2020,19,7,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.01866018\r
-18/07/2020,18,7,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.01866018\r
-17/07/2020,17,7,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.01866018\r
-16/07/2020,16,7,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.01866018\r
-15/07/2020,15,7,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.01866018\r
-14/07/2020,14,7,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.01866018\r
-13/07/2020,13,7,2020,2,0,Vietnam,VN,VNM,96462108,Asia,0.0176235\r
-12/07/2020,12,7,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.01658682\r
-11/07/2020,11,7,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.0176235\r
-10/07/2020,10,7,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.0176235\r
-09/07/2020,9,7,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.0176235\r
-08/07/2020,8,7,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.02073353\r
-07/07/2020,7,7,2020,14,0,Vietnam,VN,VNM,96462108,Asia,0.02073353\r
-06/07/2020,6,7,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00622006\r
-05/07/2020,5,7,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00622006\r
-04/07/2020,4,7,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00622006\r
-03/07/2020,3,7,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.01347679\r
-02/07/2020,2,7,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.02073353\r
-01/07/2020,1,7,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.02073353\r
-30/06/2020,30,6,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.02177021\r
-29/06/2020,29,6,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.02177021\r
-28/06/2020,28,6,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.02073353\r
-27/06/2020,27,6,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.02073353\r
-26/06/2020,26,6,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.02073353\r
-25/06/2020,25,6,2020,3,0,Vietnam,VN,VNM,96462108,Asia,0.02073353\r
-24/06/2020,24,6,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.0176235\r
-23/06/2020,23,6,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.0176235\r
-22/06/2020,22,6,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.01866018\r
-21/06/2020,21,6,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.02073353\r
-20/06/2020,20,6,2020,7,0,Vietnam,VN,VNM,96462108,Asia,0.02073353\r
-19/06/2020,19,6,2020,7,0,Vietnam,VN,VNM,96462108,Asia,0.01451347\r
-18/06/2020,18,6,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00725674\r
-17/06/2020,17,6,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.00725674\r
-16/06/2020,16,6,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00622006\r
-15/06/2020,15,6,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00622006\r
-14/06/2020,14,6,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.00725674\r
-13/06/2020,13,6,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.00622006\r
-12/06/2020,12,6,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00518338\r
-11/06/2020,11,6,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00518338\r
-10/06/2020,10,6,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00518338\r
-09/06/2020,9,6,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.00622006\r
-08/06/2020,8,6,2020,2,0,Vietnam,VN,VNM,96462108,Asia,0.00622006\r
-07/06/2020,7,6,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00518338\r
-06/06/2020,6,6,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.00518338\r
-05/06/2020,5,6,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00414671\r
-04/06/2020,4,6,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00414671\r
-03/06/2020,3,6,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00414671\r
-02/06/2020,2,6,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00414671\r
-01/06/2020,1,6,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.00829341\r
-31/05/2020,31,5,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00933009\r
-30/05/2020,30,5,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.01451347\r
-29/05/2020,29,5,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.01555015\r
-28/05/2020,28,5,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.04043038\r
-27/05/2020,27,5,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.04043038\r
-26/05/2020,26,5,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.03939371\r
-25/05/2020,25,5,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.03835703\r
-24/05/2020,24,5,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.03732035\r
-23/05/2020,23,5,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.03732035\r
-22/05/2020,22,5,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.03732035\r
-21/05/2020,21,5,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.05494385\r
-20/05/2020,20,5,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.05494385\r
-19/05/2020,19,5,2020,4,0,Vietnam,VN,VNM,96462108,Asia,0.05494385\r
-18/05/2020,18,5,2020,2,0,Vietnam,VN,VNM,96462108,Asia,0.05079715\r
-17/05/2020,17,5,2020,5,0,Vietnam,VN,VNM,96462108,Asia,0.04976047\r
-16/05/2020,16,5,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.04457709\r
-15/05/2020,15,5,2020,24,0,Vietnam,VN,VNM,96462108,Asia,0.04354041\r
-14/05/2020,14,5,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.01866018\r
-13/05/2020,13,5,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.01866018\r
-12/05/2020,12,5,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.01866018\r
-11/05/2020,11,5,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.01866018\r
-10/05/2020,10,5,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.01866018\r
-09/05/2020,9,5,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.01866018\r
-08/05/2020,8,5,2020,17,0,Vietnam,VN,VNM,96462108,Asia,0.01866018\r
-07/05/2020,7,5,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00311003\r
-06/05/2020,6,5,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00311003\r
-05/05/2020,5,5,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00311003\r
-04/05/2020,4,5,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.00311003\r
-03/05/2020,3,5,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00207335\r
-02/05/2020,2,5,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00207335\r
-01/05/2020,1,5,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00207335\r
-30/04/2020,30,4,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00207335\r
-29/04/2020,29,4,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00207335\r
-28/04/2020,28,4,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00311003\r
-27/04/2020,27,4,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00622006\r
-26/04/2020,26,4,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00829341\r
-25/04/2020,25,4,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.01244012\r
-24/04/2020,24,4,2020,2,0,Vietnam,VN,VNM,96462108,Asia,0.01347679\r
-23/04/2020,23,4,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.01347679\r
-22/04/2020,22,4,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.0176235\r
-21/04/2020,21,4,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.0176235\r
-20/04/2020,20,4,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.02384356\r
-19/04/2020,19,4,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.02799027\r
-18/04/2020,18,4,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.02902694\r
-17/04/2020,17,4,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.03317365\r
-16/04/2020,16,4,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.03628368\r
-15/04/2020,15,4,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.05805388\r
-14/04/2020,14,4,2020,3,0,Vietnam,VN,VNM,96462108,Asia,0.06323727\r
-13/04/2020,13,4,2020,2,0,Vietnam,VN,VNM,96462108,Asia,0.06323727\r
-12/04/2020,12,4,2020,4,0,Vietnam,VN,VNM,96462108,Asia,0.07671406\r
-11/04/2020,11,4,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.09019086\r
-10/04/2020,10,4,2020,2,0,Vietnam,VN,VNM,96462108,Asia,0.09744759\r
-09/04/2020,9,4,2020,4,0,Vietnam,VN,VNM,96462108,Asia,0.105741\r
-08/04/2020,8,4,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.11818112\r
-07/04/2020,7,4,2020,6,0,Vietnam,VN,VNM,96462108,Asia,0.1233645\r
-06/04/2020,6,4,2020,4,0,Vietnam,VN,VNM,96462108,Asia,0.12854789\r
-05/04/2020,5,4,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.15135477\r
-04/04/2020,4,4,2020,4,0,Vietnam,VN,VNM,96462108,Asia,0.15757483\r
-03/04/2020,3,4,2020,3,0,Vietnam,VN,VNM,96462108,Asia,0.1544648\r
-02/04/2020,2,4,2020,21,0,Vietnam,VN,VNM,96462108,Asia,0.16275821\r
-01/04/2020,1,4,2020,6,0,Vietnam,VN,VNM,96462108,Asia,0.14928142\r
-31/03/2020,31,3,2020,3,0,Vietnam,VN,VNM,96462108,Asia,0.15031809\r
-30/03/2020,30,3,2020,15,0,Vietnam,VN,VNM,96462108,Asia,0.15135477\r
-29/03/2020,29,3,2020,17,0,Vietnam,VN,VNM,96462108,Asia,0.13995133\r
-28/03/2020,28,3,2020,8,0,Vietnam,VN,VNM,96462108,Asia,0.12232783\r
-27/03/2020,27,3,2020,10,0,Vietnam,VN,VNM,96462108,Asia,0.1233645\r
-26/03/2020,26,3,2020,16,0,Vietnam,VN,VNM,96462108,Asia,0.11818112\r
-25/03/2020,25,3,2020,5,0,Vietnam,VN,VNM,96462108,Asia,0.10263097\r
-24/03/2020,24,3,2020,11,0,Vietnam,VN,VNM,96462108,Asia,0.1015943\r
-23/03/2020,23,3,2020,26,0,Vietnam,VN,VNM,96462108,Asia,0.09433756\r
-22/03/2020,22,3,2020,7,0,Vietnam,VN,VNM,96462108,Asia,0.07671406\r
-21/03/2020,21,3,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.07360403\r
-20/03/2020,20,3,2020,11,0,Vietnam,VN,VNM,96462108,Asia,0.07360403\r
-19/03/2020,19,3,2020,8,0,Vietnam,VN,VNM,96462108,Asia,0.06220059\r
-18/03/2020,18,3,2020,7,0,Vietnam,VN,VNM,96462108,Asia,0.05390718\r
-17/03/2020,17,3,2020,4,0,Vietnam,VN,VNM,96462108,Asia,0.04665044\r
-16/03/2020,16,3,2020,4,0,Vietnam,VN,VNM,96462108,Asia,0.04250374\r
-15/03/2020,15,3,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.03835703\r
-14/03/2020,14,3,2020,9,0,Vietnam,VN,VNM,96462108,Asia,0.03835703\r
-13/03/2020,13,3,2020,5,0,Vietnam,VN,VNM,96462108,Asia,0.02902694\r
-12/03/2020,12,3,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.02384356\r
-11/03/2020,11,3,2020,4,0,Vietnam,VN,VNM,96462108,Asia,0.02280688\r
-10/03/2020,10,3,2020,4,0,Vietnam,VN,VNM,96462108,Asia,0.01866018\r
-09/03/2020,9,3,2020,9,0,Vietnam,VN,VNM,96462108,Asia,0.01451347\r
-08/03/2020,8,3,2020,4,0,Vietnam,VN,VNM,96462108,Asia,0.00518338\r
-07/03/2020,7,3,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.00103668\r
-02/03/2020,2,3,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0\r
-01/03/2020,1,3,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0\r
-29/02/2020,29,2,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0\r
-28/02/2020,28,2,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0\r
-27/02/2020,27,2,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0\r
-26/02/2020,26,2,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00103668\r
-25/02/2020,25,2,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00103668\r
-24/02/2020,24,2,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00207335\r
-23/02/2020,23,2,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00207335\r
-22/02/2020,22,2,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00311003\r
-21/02/2020,21,2,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00414671\r
-20/02/2020,20,2,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00622006\r
-19/02/2020,19,2,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00622006\r
-18/02/2020,18,2,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00725674\r
-17/02/2020,17,2,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00829341\r
-16/02/2020,16,2,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00933009\r
-15/02/2020,15,2,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.01140344\r
-14/02/2020,14,2,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.01140344\r
-13/02/2020,13,2,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.01451347\r
-12/02/2020,12,2,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.01347679\r
-11/02/2020,11,2,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.01347679\r
-10/02/2020,10,2,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.01244012\r
-09/02/2020,9,2,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.01244012\r
-08/02/2020,8,2,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.01140344\r
-07/02/2020,7,2,2020,2,0,Vietnam,VN,VNM,96462108,Asia,0.01036676\r
-06/02/2020,6,2,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.01036676\r
-05/02/2020,5,2,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.01036676\r
-04/02/2020,4,2,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.00933009\r
-03/02/2020,3,2,2020,1,0,Vietnam,VN,VNM,96462108,Asia,0.00829341\r
-02/02/2020,2,2,2020,2,0,Vietnam,VN,VNM,96462108,Asia,0.00725674\r
-01/02/2020,1,2,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00518338\r
-31/01/2020,31,1,2020,3,0,Vietnam,VN,VNM,96462108,Asia,0.00518338\r
-30/01/2020,30,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00207335\r
-29/01/2020,29,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00207335\r
-28/01/2020,28,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00207335\r
-27/01/2020,27,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00207335\r
-26/01/2020,26,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00207335\r
-25/01/2020,25,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0.00207335\r
-24/01/2020,24,1,2020,2,0,Vietnam,VN,VNM,96462108,Asia,0.00207335\r
-23/01/2020,23,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0\r
-22/01/2020,22,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0\r
-21/01/2020,21,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0\r
-20/01/2020,20,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0\r
-19/01/2020,19,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0\r
-18/01/2020,18,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0\r
-17/01/2020,17,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0\r
-16/01/2020,16,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0\r
-15/01/2020,15,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0\r
-14/01/2020,14,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0\r
-13/01/2020,13,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,0\r
-12/01/2020,12,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,\r
-11/01/2020,11,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,\r
-10/01/2020,10,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,\r
-09/01/2020,9,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,\r
-08/01/2020,8,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,\r
-07/01/2020,7,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,\r
-06/01/2020,6,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,\r
-05/01/2020,5,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,\r
-04/01/2020,4,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,\r
-03/01/2020,3,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,\r
-02/01/2020,2,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,\r
-01/01/2020,1,1,2020,0,0,Vietnam,VN,VNM,96462108,Asia,\r
-31/12/2019,31,12,2019,0,0,Vietnam,VN,VNM,96462108,Asia,\r
-19/08/2020,19,8,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-18/08/2020,18,8,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-17/08/2020,17,8,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-16/08/2020,16,8,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-15/08/2020,15,8,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-14/08/2020,14,8,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-13/08/2020,13,8,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-12/08/2020,12,8,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-11/08/2020,11,8,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-10/08/2020,10,8,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-09/08/2020,9,8,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-08/08/2020,8,8,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-07/08/2020,7,8,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-06/08/2020,6,8,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-05/08/2020,5,8,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-04/08/2020,4,8,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-03/08/2020,3,8,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-02/08/2020,2,8,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-01/08/2020,1,8,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-31/07/2020,31,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-30/07/2020,30,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-29/07/2020,29,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-28/07/2020,28,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0.85843099\r
-27/07/2020,27,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,42.40649111\r
-26/07/2020,26,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,42.40649111\r
-25/07/2020,25,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,42.40649111\r
-24/07/2020,24,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,42.40649111\r
-23/07/2020,23,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,42.40649111\r
-22/07/2020,22,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,42.40649111\r
-21/07/2020,21,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,42.40649111\r
-20/07/2020,20,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,42.40649111\r
-19/07/2020,19,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,42.40649111\r
-18/07/2020,18,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,42.40649111\r
-17/07/2020,17,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,52.36429064\r
-16/07/2020,16,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,52.36429064\r
-15/07/2020,15,7,2020,5,0,Western_Sahara,EH,ESH,582458,Africa,66.27087275\r
-14/07/2020,14,7,2020,242,0,Western_Sahara,EH,ESH,582458,Africa,94.94246795\r
-13/07/2020,13,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,53.39440784\r
-12/07/2020,12,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,53.39440784\r
-11/07/2020,11,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,84.81298222\r
-10/07/2020,10,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,84.81298222\r
-09/07/2020,9,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,84.81298222\r
-08/07/2020,8,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,84.81298222\r
-07/07/2020,7,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,84.81298222\r
-06/07/2020,6,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,84.81298222\r
-05/07/2020,5,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,84.81298222\r
-04/07/2020,4,7,2020,58,0,Western_Sahara,EH,ESH,582458,Africa,84.81298222\r
-03/07/2020,3,7,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,75.19855509\r
-02/07/2020,2,7,2020,81,0,Western_Sahara,EH,ESH,582458,Africa,75.19855509\r
-01/07/2020,1,7,2020,172,0,Western_Sahara,EH,ESH,582458,Africa,61.29197298\r
-30/06/2020,30,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,31.76194678\r
-29/06/2020,29,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,31.76194678\r
-28/06/2020,28,6,2020,183,0,Western_Sahara,EH,ESH,582458,Africa,31.76194678\r
-27/06/2020,27,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0.3433724\r
-26/06/2020,26,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0.3433724\r
-25/06/2020,25,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0.3433724\r
-24/06/2020,24,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0.3433724\r
-23/06/2020,23,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0.3433724\r
-22/06/2020,22,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0.3433724\r
-21/06/2020,21,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0.3433724\r
-20/06/2020,20,6,2020,2,0,Western_Sahara,EH,ESH,582458,Africa,0.3433724\r
-19/06/2020,19,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-18/06/2020,18,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-17/06/2020,17,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-16/06/2020,16,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-15/06/2020,15,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-14/06/2020,14,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-13/06/2020,13,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-12/06/2020,12,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,2.91866538\r
-11/06/2020,11,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,2.91866538\r
-10/06/2020,10,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,2.91866538\r
-09/06/2020,9,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,2.91866538\r
-08/06/2020,8,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,2.91866538\r
-07/06/2020,7,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,2.91866538\r
-06/06/2020,6,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,2.91866538\r
-05/06/2020,5,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,2.91866538\r
-04/06/2020,4,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,2.91866538\r
-03/06/2020,3,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,2.91866538\r
-02/06/2020,2,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,2.91866538\r
-01/06/2020,1,6,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,2.91866538\r
-31/05/2020,31,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,2.91866538\r
-30/05/2020,30,5,2020,17,1,Western_Sahara,EH,ESH,582458,Africa,2.91866538\r
-29/05/2020,29,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-28/05/2020,28,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-27/05/2020,27,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-26/05/2020,26,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-25/05/2020,25,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-24/05/2020,24,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-23/05/2020,23,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-22/05/2020,22,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-21/05/2020,21,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-20/05/2020,20,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-19/05/2020,19,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-18/05/2020,18,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-17/05/2020,17,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-16/05/2020,16,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-15/05/2020,15,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-14/05/2020,14,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-13/05/2020,13,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-12/05/2020,12,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-11/05/2020,11,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-10/05/2020,10,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,0\r
-09/05/2020,9,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,1.03011719\r
-08/05/2020,8,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,\r
-07/05/2020,7,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,\r
-06/05/2020,6,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,\r
-05/05/2020,5,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,\r
-04/05/2020,4,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,\r
-03/05/2020,3,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,\r
-02/05/2020,2,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,\r
-01/05/2020,1,5,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,\r
-30/04/2020,30,4,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,\r
-29/04/2020,29,4,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,\r
-28/04/2020,28,4,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,\r
-27/04/2020,27,4,2020,0,0,Western_Sahara,EH,ESH,582458,Africa,\r
-26/04/2020,26,4,2020,6,0,Western_Sahara,EH,ESH,582458,Africa,\r
-19/08/2020,19,8,2020,4,1,Yemen,YE,YEM,29161922,Asia,0.43207029\r
-18/08/2020,18,8,2020,13,5,Yemen,YE,YEM,29161922,Asia,0.49379461\r
-17/08/2020,17,8,2020,7,1,Yemen,YE,YEM,29161922,Asia,0.46293245\r
-16/08/2020,16,8,2020,4,1,Yemen,YE,YEM,29161922,Asia,0.45264506\r
-15/08/2020,15,8,2020,11,0,Yemen,YE,YEM,29161922,Asia,0.4457868\r
-14/08/2020,14,8,2020,6,0,Yemen,YE,YEM,29161922,Asia,0.41492464\r
-13/08/2020,13,8,2020,10,5,Yemen,YE,YEM,29161922,Asia,0.4457868\r
-12/08/2020,12,8,2020,0,5,Yemen,YE,YEM,29161922,Asia,0.46636158\r
-11/08/2020,11,8,2020,27,3,Yemen,YE,YEM,29161922,Asia,0.4800781\r
-10/08/2020,10,8,2020,4,2,Yemen,YE,YEM,29161922,Asia,0.4217829\r
-09/08/2020,9,8,2020,4,1,Yemen,YE,YEM,29161922,Asia,0.43207029\r
-08/08/2020,8,8,2020,29,3,Yemen,YE,YEM,29161922,Asia,0.48693635\r
-07/08/2020,7,8,2020,3,1,Yemen,YE,YEM,29161922,Asia,0.38749161\r
-06/08/2020,6,8,2020,4,2,Yemen,YE,YEM,29161922,Asia,0.42521203\r
-05/08/2020,5,8,2020,22,7,Yemen,YE,YEM,29161922,Asia,0.44921593\r
-04/08/2020,4,8,2020,4,2,Yemen,YE,YEM,29161922,Asia,0.40806638\r
-03/08/2020,3,8,2020,4,3,Yemen,YE,YEM,29161922,Asia,0.43892855\r
-02/08/2020,2,8,2020,2,1,Yemen,YE,YEM,29161922,Asia,0.51094026\r
-01/08/2020,1,8,2020,2,6,Yemen,YE,YEM,29161922,Asia,0.52122765\r
-31/07/2020,31,7,2020,15,2,Yemen,YE,YEM,29161922,Asia,0.59666849\r
-30/07/2020,30,7,2020,16,1,Yemen,YE,YEM,29161922,Asia,0.63438891\r
-29/07/2020,29,7,2020,4,1,Yemen,YE,YEM,29161922,Asia,0.66182195\r
-28/07/2020,28,7,2020,10,4,Yemen,YE,YEM,29161922,Asia,0.66182195\r
-27/07/2020,27,7,2020,7,5,Yemen,YE,YEM,29161922,Asia,0.74069192\r
-26/07/2020,26,7,2020,20,13,Yemen,YE,YEM,29161922,Asia,0.97730184\r
-25/07/2020,25,7,2020,0,0,Yemen,YE,YEM,29161922,Asia,0.93958142\r
-24/07/2020,24,7,2020,14,3,Yemen,YE,YEM,29161922,Asia,1.02188052\r
-23/07/2020,23,7,2020,11,2,Yemen,YE,YEM,29161922,Asia,1.10417962\r
-22/07/2020,22,7,2020,10,9,Yemen,YE,YEM,29161922,Asia,1.13847091\r
-21/07/2020,21,7,2020,13,2,Yemen,YE,YEM,29161922,Asia,1.12818353\r
-20/07/2020,20,7,2020,25,2,Yemen,YE,YEM,29161922,Asia,1.16933308\r
-19/07/2020,19,7,2020,5,3,Yemen,YE,YEM,29161922,Asia,1.14190004\r
-18/07/2020,18,7,2020,24,2,Yemen,YE,YEM,29161922,Asia,1.15218743\r
-17/07/2020,17,7,2020,26,5,Yemen,YE,YEM,29161922,Asia,1.13504178\r
-16/07/2020,16,7,2020,24,3,Yemen,YE,YEM,29161922,Asia,1.15218743\r
-15/07/2020,15,7,2020,4,6,Yemen,YE,YEM,29161922,Asia,1.17962047\r
-14/07/2020,14,7,2020,33,7,Yemen,YE,YEM,29161922,Asia,1.26877783\r
-13/07/2020,13,7,2020,76,52,Yemen,YE,YEM,29161922,Asia,1.18990785\r
-12/07/2020,12,7,2020,9,1,Yemen,YE,YEM,29161922,Asia,0.98073097\r
-11/07/2020,11,7,2020,24,3,Yemen,YE,YEM,29161922,Asia,0.99787661\r
-10/07/2020,10,7,2020,38,10,Yemen,YE,YEM,29161922,Asia,0.96015619\r
-09/07/2020,9,7,2020,21,3,Yemen,YE,YEM,29161922,Asia,1.03902617\r
-08/07/2020,8,7,2020,7,3,Yemen,YE,YEM,29161922,Asia,1.04588442\r
-07/07/2020,7,7,2020,25,7,Yemen,YE,YEM,29161922,Asia,1.10760875\r
-06/07/2020,6,7,2020,17,1,Yemen,YE,YEM,29161922,Asia,1.11103788\r
-05/07/2020,5,7,2020,8,2,Yemen,YE,YEM,29161922,Asia,1.11446701\r
-04/07/2020,4,7,2020,19,10,Yemen,YE,YEM,29161922,Asia,1.10075049\r
-03/07/2020,3,7,2020,31,7,Yemen,YE,YEM,29161922,Asia,1.08017572\r
-02/07/2020,2,7,2020,32,6,Yemen,YE,YEM,29161922,Asia,0.98758923\r
-01/07/2020,1,7,2020,30,8,Yemen,YE,YEM,29161922,Asia,0.92243577\r
-30/06/2020,30,6,2020,10,2,Yemen,YE,YEM,29161922,Asia,0.97387271\r
-29/06/2020,29,6,2020,15,6,Yemen,YE,YEM,29161922,Asia,1.33736041\r
-28/06/2020,28,6,2020,14,3,Yemen,YE,YEM,29161922,Asia,1.36479345\r
-27/06/2020,27,6,2020,13,5,Yemen,YE,YEM,29161922,Asia,1.56711207\r
-26/06/2020,26,6,2020,61,14,Yemen,YE,YEM,29161922,Asia,1.66312769\r
-25/06/2020,25,6,2020,23,13,Yemen,YE,YEM,29161922,Asia,1.56025381\r
-24/06/2020,24,6,2020,25,4,Yemen,YE,YEM,29161922,Asia,1.60483249\r
-23/06/2020,23,6,2020,26,1,Yemen,YE,YEM,29161922,Asia,1.61511988\r
-22/06/2020,22,6,2020,18,2,Yemen,YE,YEM,29161922,Asia,1.56025381\r
-21/06/2020,21,6,2020,4,3,Yemen,YE,YEM,29161922,Asia,1.54310817\r
-20/06/2020,20,6,2020,13,3,Yemen,YE,YEM,29161922,Asia,1.54310817\r
-19/06/2020,19,6,2020,4,4,Yemen,YE,YEM,29161922,Asia,1.55339555\r
-18/06/2020,18,6,2020,13,29,Yemen,YE,YEM,29161922,Asia,1.7111355\r
-17/06/2020,17,6,2020,45,7,Yemen,YE,YEM,29161922,Asia,1.68027334\r
-16/06/2020,16,6,2020,116,44,Yemen,YE,YEM,29161922,Asia,1.68027334\r
-15/06/2020,15,6,2020,23,4,Yemen,YE,YEM,29161922,Asia,1.38879735\r
-14/06/2020,14,6,2020,73,21,Yemen,YE,YEM,29161922,Asia,1.35450606\r
-13/06/2020,13,6,2020,41,3,Yemen,YE,YEM,29161922,Asia,1.18304959\r
-12/06/2020,12,6,2020,31,7,Yemen,YE,YEM,29161922,Asia,1.07331746\r
-11/06/2020,11,6,2020,36,2,Yemen,YE,YEM,29161922,Asia,1.04588442\r
-10/06/2020,10,6,2020,28,15,Yemen,YE,YEM,29161922,Asia,0.94301055\r
-09/06/2020,9,6,2020,10,0,Yemen,YE,YEM,29161922,Asia,0.88814448\r
-08/06/2020,8,6,2020,13,0,Yemen,YE,YEM,29161922,Asia,0.90529012\r
-07/06/2020,7,6,2020,4,1,Yemen,YE,YEM,29161922,Asia,0.89500274\r
-06/06/2020,6,6,2020,16,8,Yemen,YE,YEM,29161922,Asia,0.90529012\r
-05/06/2020,5,6,2020,50,15,Yemen,YE,YEM,29161922,Asia,0.89157361\r
-04/06/2020,4,6,2020,4,1,Yemen,YE,YEM,29161922,Asia,0.76469582\r
-03/06/2020,3,6,2020,45,3,Yemen,YE,YEM,29161922,Asia,0.79555799\r
-02/06/2020,2,6,2020,31,4,Yemen,YE,YEM,29161922,Asia,0.76812495\r
-01/06/2020,1,6,2020,13,3,Yemen,YE,YEM,29161922,Asia,0.66868021\r
-31/05/2020,31,5,2020,23,11,Yemen,YE,YEM,29161922,Asia,0.63781804\r
-30/05/2020,30,5,2020,9,9,Yemen,YE,YEM,29161922,Asia,0.6206724\r
-29/05/2020,29,5,2020,23,4,Yemen,YE,YEM,29161922,Asia,0.65496369\r
-28/05/2020,28,5,2020,6,4,Yemen,YE,YEM,29161922,Asia,0.63438891\r
-27/05/2020,27,5,2020,12,4,Yemen,YE,YEM,29161922,Asia,0.62410153\r
-26/05/2020,26,5,2020,15,3,Yemen,YE,YEM,29161922,Asia,0.6206724\r
-25/05/2020,25,5,2020,10,3,Yemen,YE,YEM,29161922,Asia,0.5863811\r
-24/05/2020,24,5,2020,7,6,Yemen,YE,YEM,29161922,Asia,0.61038501\r
-23/05/2020,23,5,2020,12,0,Yemen,YE,YEM,29161922,Asia,0.5863811\r
-22/05/2020,22,5,2020,13,4,Yemen,YE,YEM,29161922,Asia,0.57266459\r
-21/05/2020,21,5,2020,13,1,Yemen,YE,YEM,29161922,Asia,0.53151504\r
-20/05/2020,20,5,2020,37,8,Yemen,YE,YEM,29161922,Asia,0.50065287\r
-19/05/2020,19,5,2020,2,0,Yemen,YE,YEM,29161922,Asia,0.40463725\r
-18/05/2020,18,5,2020,4,1,Yemen,YE,YEM,29161922,Asia,0.40463725\r
-17/05/2020,17,5,2020,18,4,Yemen,YE,YEM,29161922,Asia,0.39092074\r
-16/05/2020,16,5,2020,19,2,Yemen,YE,YEM,29161922,Asia,0.3394838\r
-15/05/2020,15,5,2020,17,1,Yemen,YE,YEM,29161922,Asia,0.27775947\r
-14/05/2020,14,5,2020,3,1,Yemen,YE,YEM,29161922,Asia,0.21946427\r
-13/05/2020,13,5,2020,11,2,Yemen,YE,YEM,29161922,Asia,0.22632253\r
-12/05/2020,12,5,2020,5,1,Yemen,YE,YEM,29161922,Asia,0.18860211\r
-11/05/2020,11,5,2020,17,1,Yemen,YE,YEM,29161922,Asia,0.17145646\r
-10/05/2020,10,5,2020,0,0,Yemen,YE,YEM,29161922,Asia,0.11316127\r
-09/05/2020,9,5,2020,8,1,Yemen,YE,YEM,29161922,Asia,0.11316127\r
-08/05/2020,8,5,2020,1,1,Yemen,YE,YEM,29161922,Asia,0.08572823\r
-07/05/2020,7,5,2020,4,2,Yemen,YE,YEM,29161922,Asia,0.0822991\r
-06/05/2020,6,5,2020,9,1,Yemen,YE,YEM,29161922,Asia,0.06858259\r
-05/05/2020,5,5,2020,2,0,Yemen,YE,YEM,29161922,Asia,0.03772042\r
-04/05/2020,4,5,2020,0,0,Yemen,YE,YEM,29161922,Asia,0.03086216\r
-03/05/2020,3,5,2020,3,0,Yemen,YE,YEM,29161922,Asia,0.03086216\r
-02/05/2020,2,5,2020,1,0,Yemen,YE,YEM,29161922,Asia,0.02057478\r
-01/05/2020,1,5,2020,0,2,Yemen,YE,YEM,29161922,Asia,0.01714565\r
-30/04/2020,30,4,2020,5,0,Yemen,YE,YEM,29161922,Asia,0.01714565\r
-29/04/2020,29,4,2020,0,0,Yemen,YE,YEM,29161922,Asia,0\r
-28/04/2020,28,4,2020,0,0,Yemen,YE,YEM,29161922,Asia,0\r
-27/04/2020,27,4,2020,0,0,Yemen,YE,YEM,29161922,Asia,0\r
-26/04/2020,26,4,2020,0,0,Yemen,YE,YEM,29161922,Asia,0\r
-25/04/2020,25,4,2020,0,0,Yemen,YE,YEM,29161922,Asia,0\r
-24/04/2020,24,4,2020,0,0,Yemen,YE,YEM,29161922,Asia,0\r
-23/04/2020,23,4,2020,0,0,Yemen,YE,YEM,29161922,Asia,0.00342913\r
-22/04/2020,22,4,2020,0,0,Yemen,YE,YEM,29161922,Asia,\r
-21/04/2020,21,4,2020,0,0,Yemen,YE,YEM,29161922,Asia,\r
-20/04/2020,20,4,2020,0,0,Yemen,YE,YEM,29161922,Asia,\r
-19/04/2020,19,4,2020,0,0,Yemen,YE,YEM,29161922,Asia,\r
-18/04/2020,18,4,2020,0,0,Yemen,YE,YEM,29161922,Asia,\r
-17/04/2020,17,4,2020,0,0,Yemen,YE,YEM,29161922,Asia,\r
-16/04/2020,16,4,2020,0,0,Yemen,YE,YEM,29161922,Asia,\r
-15/04/2020,15,4,2020,0,0,Yemen,YE,YEM,29161922,Asia,\r
-14/04/2020,14,4,2020,0,0,Yemen,YE,YEM,29161922,Asia,\r
-13/04/2020,13,4,2020,0,0,Yemen,YE,YEM,29161922,Asia,\r
-12/04/2020,12,4,2020,0,0,Yemen,YE,YEM,29161922,Asia,\r
-11/04/2020,11,4,2020,0,0,Yemen,YE,YEM,29161922,Asia,\r
-10/04/2020,10,4,2020,1,0,Yemen,YE,YEM,29161922,Asia,\r
-19/08/2020,19,8,2020,142,0,Zambia,ZM,ZMB,17861034,Africa,19.04145079\r
-18/08/2020,18,8,2020,496,4,Zambia,ZM,ZMB,17861034,Africa,18.24642403\r
-17/08/2020,17,8,2020,157,0,Zambia,ZM,ZMB,17861034,Africa,16.77394489\r
-16/08/2020,16,8,2020,165,4,Zambia,ZM,ZMB,17861034,Africa,16.56119125\r
-15/08/2020,15,8,2020,358,10,Zambia,ZM,ZMB,17861034,Africa,17.12106925\r
-14/08/2020,14,8,2020,162,0,Zambia,ZM,ZMB,17861034,Africa,17.40100825\r
-13/08/2020,13,8,2020,226,5,Zambia,ZM,ZMB,17861034,Africa,18.20723257\r
-12/08/2020,12,8,2020,65,0,Zambia,ZM,ZMB,17861034,Africa,18.32480695\r
-11/08/2020,11,8,2020,125,6,Zambia,ZM,ZMB,17861034,Africa,20.48033725\r
-10/08/2020,10,8,2020,182,32,Zambia,ZM,ZMB,17861034,Africa,20.17800313\r
-09/08/2020,9,8,2020,417,3,Zambia,ZM,ZMB,17861034,Africa,20.01563851\r
-08/08/2020,8,8,2020,322,1,Zambia,ZM,ZMB,17861034,Africa,20.32357141\r
-07/08/2020,7,8,2020,142,23,Zambia,ZM,ZMB,17861034,Africa,20.04923119\r
-06/08/2020,6,8,2020,442,5,Zambia,ZM,ZMB,17861034,Africa,19.25420443\r
-05/08/2020,5,8,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,18.21843013\r
-04/08/2020,4,8,2020,233,1,Zambia,ZM,ZMB,17861034,Africa,18.21843013\r
-03/08/2020,3,8,2020,119,5,Zambia,ZM,ZMB,17861034,Africa,18.85109227\r
-02/08/2020,2,8,2020,265,14,Zambia,ZM,ZMB,17861034,Africa,18.18483745\r
-01/08/2020,1,8,2020,408,2,Zambia,ZM,ZMB,17861034,Africa,17.65295335\r
-31/07/2020,31,7,2020,306,3,Zambia,ZM,ZMB,17861034,Africa,18.31920817\r
-30/07/2020,30,7,2020,247,4,Zambia,ZM,ZMB,17861034,Africa,16.60598149\r
-29/07/2020,29,7,2020,450,2,Zambia,ZM,ZMB,17861034,Africa,15.22308283\r
-28/07/2020,28,7,2020,71,1,Zambia,ZM,ZMB,17861034,Africa,14.87595847\r
-27/07/2020,27,7,2020,153,9,Zambia,ZM,ZMB,17861034,Africa,14.47844509\r
-26/07/2020,26,7,2020,472,0,Zambia,ZM,ZMB,17861034,Africa,13.62183175\r
-25/07/2020,25,7,2020,273,2,Zambia,ZM,ZMB,17861034,Africa,10.97920759\r
-24/07/2020,24,7,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,9.45074065\r
-23/07/2020,23,7,2020,257,8,Zambia,ZM,ZMB,17861034,Africa,9.45074065\r
-22/07/2020,22,7,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,8.01185418\r
-21/07/2020,21,7,2020,346,11,Zambia,ZM,ZMB,17861034,Africa,9.48433333\r
-20/07/2020,20,7,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,7.54715544\r
-19/07/2020,19,7,2020,170,0,Zambia,ZM,ZMB,17861034,Africa,7.54715544\r
-18/07/2020,18,7,2020,527,27,Zambia,ZM,ZMB,17861034,Africa,6.59536284\r
-17/07/2020,17,7,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,3.64480578\r
-16/07/2020,16,7,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,3.64480578\r
-15/07/2020,15,7,2020,388,40,Zambia,ZM,ZMB,17861034,Africa,3.85755942\r
-14/07/2020,14,7,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,1.83080106\r
-13/07/2020,13,7,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,1.89238764\r
-12/07/2020,12,7,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,2.03795592\r
-11/07/2020,11,7,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,2.03795592\r
-10/07/2020,10,7,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,2.22831444\r
-09/07/2020,9,7,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,2.27310468\r
-08/07/2020,8,7,2020,263,12,Zambia,ZM,ZMB,17861034,Africa,2.34029004\r
-07/07/2020,7,7,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,1.13095356\r
-06/07/2020,6,7,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,1.13095356\r
-05/07/2020,5,7,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,1.13095356\r
-04/07/2020,4,7,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,1.13095356\r
-03/07/2020,3,7,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,1.20933648\r
-02/07/2020,2,7,2020,38,6,Zambia,ZM,ZMB,17861034,Africa,1.2317316\r
-01/07/2020,1,7,2020,26,2,Zambia,ZM,ZMB,17861034,Africa,1.05816942\r
-30/06/2020,30,6,2020,11,0,Zambia,ZM,ZMB,17861034,Africa,1.04137308\r
-29/06/2020,29,6,2020,26,1,Zambia,ZM,ZMB,17861034,Africa,1.11415722\r
-28/06/2020,28,6,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,0.97418772\r
-27/06/2020,27,6,2020,34,3,Zambia,ZM,ZMB,17861034,Africa,1.1757438\r
-26/06/2020,26,6,2020,8,0,Zambia,ZM,ZMB,17861034,Africa,1.3717011\r
-25/06/2020,25,6,2020,12,0,Zambia,ZM,ZMB,17861034,Africa,1.32691086\r
-24/06/2020,24,6,2020,47,7,Zambia,ZM,ZMB,17861034,Africa,1.55086206\r
-23/06/2020,23,6,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,1.2877194\r
-22/06/2020,22,6,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,1.54526328\r
-21/06/2020,21,6,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,1.54526328\r
-20/06/2020,20,6,2020,14,0,Zambia,ZM,ZMB,17861034,Africa,1.78601082\r
-19/06/2020,19,6,2020,4,0,Zambia,ZM,ZMB,17861034,Africa,1.7076279\r
-18/06/2020,18,6,2020,7,0,Zambia,ZM,ZMB,17861034,Africa,1.80840594\r
-17/06/2020,17,6,2020,23,0,Zambia,ZM,ZMB,17861034,Africa,1.76921448\r
-16/06/2020,16,6,2020,24,0,Zambia,ZM,ZMB,17861034,Africa,1.64044254\r
-15/06/2020,15,6,2020,1,1,Zambia,ZM,ZMB,17861034,Africa,1.68523278\r
-14/06/2020,14,6,2020,36,0,Zambia,ZM,ZMB,17861034,Africa,1.679634\r
-13/06/2020,13,6,2020,69,0,Zambia,ZM,ZMB,17861034,Africa,1.47807792\r
-12/06/2020,12,6,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,1.0917621\r
-11/06/2020,11,6,2020,52,0,Zambia,ZM,ZMB,17861034,Africa,1.0917621\r
-10/06/2020,10,6,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,1.5676584\r
-09/06/2020,9,6,2020,46,3,Zambia,ZM,ZMB,17861034,Africa,1.5676584\r
-08/06/2020,8,6,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,1.31011452\r
-07/06/2020,7,6,2020,43,0,Zambia,ZM,ZMB,17861034,Africa,1.31011452\r
-06/06/2020,6,6,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,1.06936698\r
-05/06/2020,5,6,2020,22,0,Zambia,ZM,ZMB,17861034,Africa,1.3717011\r
-04/06/2020,4,6,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,1.43888646\r
-03/06/2020,3,6,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,1.77481326\r
-02/06/2020,2,6,2020,32,0,Zambia,ZM,ZMB,17861034,Africa,1.83639984\r
-01/06/2020,1,6,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,1.70202912\r
-31/05/2020,31,5,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,2.11633884\r
-30/05/2020,30,5,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,2.17792542\r
-29/05/2020,29,5,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,2.25630834\r
-28/05/2020,28,5,2020,137,0,Zambia,ZM,ZMB,17861034,Africa,3.42085458\r
-27/05/2020,27,5,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,2.68181562\r
-26/05/2020,26,5,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,3.65600334\r
-25/05/2020,25,5,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,3.65600334\r
-24/05/2020,24,5,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,3.73998504\r
-23/05/2020,23,5,2020,54,0,Zambia,ZM,ZMB,17861034,Africa,4.21588134\r
-22/05/2020,22,5,2020,34,0,Zambia,ZM,ZMB,17861034,Africa,3.99193014\r
-21/05/2020,21,5,2020,60,0,Zambia,ZM,ZMB,17861034,Africa,3.84076308\r
-20/05/2020,20,5,2020,11,0,Zambia,ZM,ZMB,17861034,Africa,3.54402774\r
-19/05/2020,19,5,2020,8,0,Zambia,ZM,ZMB,17861034,Africa,3.49363872\r
-18/05/2020,18,5,2020,74,0,Zambia,ZM,ZMB,17861034,Africa,3.52163262\r
-17/05/2020,17,5,2020,11,0,Zambia,ZM,ZMB,17861034,Africa,3.1353168\r
-16/05/2020,16,5,2020,14,0,Zambia,ZM,ZMB,17861034,Africa,3.12971802\r
-15/05/2020,15,5,2020,208,0,Zambia,ZM,ZMB,17861034,Africa,3.06813144\r
-14/05/2020,14,5,2020,5,0,Zambia,ZM,ZMB,17861034,Africa,1.95397422\r
-13/05/2020,13,5,2020,174,0,Zambia,ZM,ZMB,17861034,Africa,1.93717788\r
-12/05/2020,12,5,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,0.99658284\r
-11/05/2020,11,5,2020,15,0,Zambia,ZM,ZMB,17861034,Africa,1.00218162\r
-10/05/2020,10,5,2020,85,3,Zambia,ZM,ZMB,17861034,Africa,0.94059504\r
-09/05/2020,9,5,2020,14,0,Zambia,ZM,ZMB,17861034,Africa,0.46469874\r
-08/05/2020,8,5,2020,7,0,Zambia,ZM,ZMB,17861034,Africa,0.43110606\r
-07/05/2020,7,5,2020,7,0,Zambia,ZM,ZMB,17861034,Africa,0.40311216\r
-06/05/2020,6,5,2020,2,1,Zambia,ZM,ZMB,17861034,Africa,0.41430972\r
-05/05/2020,5,5,2020,13,0,Zambia,ZM,ZMB,17861034,Africa,0.40311216\r
-04/05/2020,4,5,2020,5,0,Zambia,ZM,ZMB,17861034,Africa,0.35272314\r
-03/05/2020,3,5,2020,10,0,Zambia,ZM,ZMB,17861034,Africa,0.34712436\r
-02/05/2020,2,5,2020,3,0,Zambia,ZM,ZMB,17861034,Africa,0.31913046\r
-01/05/2020,1,5,2020,9,0,Zambia,ZM,ZMB,17861034,Africa,0.32472924\r
-30/04/2020,30,4,2020,2,0,Zambia,ZM,ZMB,17861034,Africa,0.27434022\r
-29/04/2020,29,4,2020,6,0,Zambia,ZM,ZMB,17861034,Africa,0.279939\r
-28/04/2020,28,4,2020,1,0,Zambia,ZM,ZMB,17861034,Africa,0.24634632\r
-27/04/2020,27,4,2020,4,0,Zambia,ZM,ZMB,17861034,Africa,0.2519451\r
-26/04/2020,26,4,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,0.24634632\r
-25/04/2020,25,4,2020,8,0,Zambia,ZM,ZMB,17861034,Africa,0.24634632\r
-24/04/2020,24,4,2020,2,0,Zambia,ZM,ZMB,17861034,Africa,0.20715486\r
-23/04/2020,23,4,2020,9,0,Zambia,ZM,ZMB,17861034,Africa,0.1959573\r
-22/04/2020,22,4,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,0.14556828\r
-21/04/2020,21,4,2020,4,0,Zambia,ZM,ZMB,17861034,Africa,0.14556828\r
-20/04/2020,20,4,2020,4,1,Zambia,ZM,ZMB,17861034,Africa,0.12317316\r
-19/04/2020,19,4,2020,5,0,Zambia,ZM,ZMB,17861034,Africa,0.10077804\r
-18/04/2020,18,4,2020,4,0,Zambia,ZM,ZMB,17861034,Africa,0.07278414\r
-17/04/2020,17,4,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,0.05038902\r
-16/04/2020,16,4,2020,3,0,Zambia,ZM,ZMB,17861034,Africa,0.06718536\r
-15/04/2020,15,4,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,0.0559878\r
-14/04/2020,14,4,2020,2,0,Zambia,ZM,ZMB,17861034,Africa,0.0559878\r
-13/04/2020,13,4,2020,3,0,Zambia,ZM,ZMB,17861034,Africa,0.07838292\r
-12/04/2020,12,4,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,0.06718536\r
-11/04/2020,11,4,2020,1,1,Zambia,ZM,ZMB,17861034,Africa,0.13437072\r
-10/04/2020,10,4,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,0.1399695\r
-09/04/2020,9,4,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,0.15116706\r
-08/04/2020,8,4,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,0.20155608\r
-07/04/2020,7,4,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,0.20155608\r
-06/04/2020,6,4,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,0.20155608\r
-05/04/2020,5,4,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,0.20715486\r
-04/04/2020,4,4,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,0.20715486\r
-03/04/2020,3,4,2020,3,1,Zambia,ZM,ZMB,17861034,Africa,0.20715486\r
-02/04/2020,2,4,2020,1,0,Zambia,ZM,ZMB,17861034,Africa,0.19035852\r
-01/04/2020,1,4,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,0.1959573\r
-31/03/2020,31,3,2020,6,0,Zambia,ZM,ZMB,17861034,Africa,\r
-30/03/2020,30,3,2020,1,0,Zambia,ZM,ZMB,17861034,Africa,\r
-29/03/2020,29,3,2020,12,0,Zambia,ZM,ZMB,17861034,Africa,\r
-28/03/2020,28,3,2020,2,0,Zambia,ZM,ZMB,17861034,Africa,\r
-27/03/2020,27,3,2020,2,0,Zambia,ZM,ZMB,17861034,Africa,\r
-26/03/2020,26,3,2020,9,0,Zambia,ZM,ZMB,17861034,Africa,\r
-25/03/2020,25,3,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,\r
-24/03/2020,24,3,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,\r
-23/03/2020,23,3,2020,1,0,Zambia,ZM,ZMB,17861034,Africa,\r
-22/03/2020,22,3,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,\r
-21/03/2020,21,3,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,\r
-20/03/2020,20,3,2020,0,0,Zambia,ZM,ZMB,17861034,Africa,\r
-19/03/2020,19,3,2020,2,0,Zambia,ZM,ZMB,17861034,Africa,\r
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-18/08/2020,18,8,2020,47,3,Zimbabwe,ZW,ZWE,14645473,Africa,8.4189838\r
-17/08/2020,17,8,2020,85,2,Zimbabwe,ZW,ZWE,14645473,Africa,9.14958499\r
-16/08/2020,16,8,2020,104,2,Zimbabwe,ZW,ZWE,14645473,Africa,10.35814958\r
-15/08/2020,15,8,2020,82,0,Zimbabwe,ZW,ZWE,14645473,Africa,12.9937763\r
-14/08/2020,14,8,2020,97,6,Zimbabwe,ZW,ZWE,14645473,Africa,12.95963606\r
-13/08/2020,13,8,2020,75,18,Zimbabwe,ZW,ZWE,14645473,Africa,13.75168969\r
-12/08/2020,12,8,2020,70,0,Zimbabwe,ZW,ZWE,14645473,Africa,13.66292506\r
-11/08/2020,11,8,2020,99,0,Zimbabwe,ZW,ZWE,14645473,Africa,13.95653114\r
-10/08/2020,10,8,2020,74,2,Zimbabwe,ZW,ZWE,14645473,Africa,14.59153965\r
-09/08/2020,9,8,2020,124,0,Zimbabwe,ZW,ZWE,14645473,Africa,14.61885185\r
-08/08/2020,8,8,2020,56,5,Zimbabwe,ZW,ZWE,14645473,Africa,14.71444452\r
-07/08/2020,7,8,2020,56,13,Zimbabwe,ZW,ZWE,14645473,Africa,15.50649815\r
-06/08/2020,6,8,2020,118,3,Zimbabwe,ZW,ZWE,14645473,Africa,15.7386518\r
-05/08/2020,5,8,2020,146,1,Zimbabwe,ZW,ZWE,14645473,Africa,16.39414446\r
-04/08/2020,4,8,2020,154,10,Zimbabwe,ZW,ZWE,14645473,Africa,16.12785057\r
-03/08/2020,3,8,2020,262,1,Zimbabwe,ZW,ZWE,14645473,Africa,15.77279204\r
-02/08/2020,2,8,2020,490,2,Zimbabwe,ZW,ZWE,14645473,Africa,14.89197379\r
-01/08/2020,1,8,2020,77,14,Zimbabwe,ZW,ZWE,14645473,Africa,11.94225683\r
-31/07/2020,31,7,2020,213,12,Zimbabwe,ZW,ZWE,14645473,Africa,11.81252391\r
-30/07/2020,30,7,2020,62,1,Zimbabwe,ZW,ZWE,14645473,Africa,12.22220682\r
-29/07/2020,29,7,2020,113,4,Zimbabwe,ZW,ZWE,14645473,Africa,12.17441048\r
-28/07/2020,28,7,2020,192,2,Zimbabwe,ZW,ZWE,14645473,Africa,11.402841\r
-27/07/2020,27,7,2020,78,0,Zimbabwe,ZW,ZWE,14645473,Africa,10.42643006\r
-26/07/2020,26,7,2020,138,2,Zimbabwe,ZW,ZWE,14645473,Africa,9.91432643\r
-25/07/2020,25,7,2020,172,4,Zimbabwe,ZW,ZWE,14645473,Africa,9.24517767\r
-24/07/2020,24,7,2020,90,2,Zimbabwe,ZW,ZWE,14645473,Africa,8.18000211\r
-23/07/2020,23,7,2020,214,0,Zimbabwe,ZW,ZWE,14645473,Africa,7.84542773\r
-22/07/2020,22,7,2020,107,0,Zimbabwe,ZW,ZWE,14645473,Africa,7.0533741\r
-21/07/2020,21,7,2020,102,1,Zimbabwe,ZW,ZWE,14645473,Africa,6.68465948\r
-20/07/2020,20,7,2020,133,0,Zimbabwe,ZW,ZWE,14645473,Africa,6.11110341\r
-19/07/2020,19,7,2020,58,1,Zimbabwe,ZW,ZWE,14645473,Africa,5.32587783\r
-18/07/2020,18,7,2020,58,1,Zimbabwe,ZW,ZWE,14645473,Africa,5.42829856\r
-17/07/2020,17,7,2020,273,3,Zimbabwe,ZW,ZWE,14645473,Africa,5.08689614\r
-16/07/2020,16,7,2020,55,1,Zimbabwe,ZW,ZWE,14645473,Africa,3.30477548\r
-15/07/2020,15,7,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,3.02482549\r
-14/07/2020,14,7,2020,49,1,Zimbabwe,ZW,ZWE,14645473,Africa,3.14090231\r
-13/07/2020,13,7,2020,3,0,Zimbabwe,ZW,ZWE,14645473,Africa,2.85412427\r
-12/07/2020,12,7,2020,40,5,Zimbabwe,ZW,ZWE,14645473,Africa,2.83364013\r
-11/07/2020,11,7,2020,16,1,Zimbabwe,ZW,ZWE,14645473,Africa,2.60148648\r
-10/07/2020,10,7,2020,41,3,Zimbabwe,ZW,ZWE,14645473,Africa,2.56051819\r
-09/07/2020,9,7,2020,98,0,Zimbabwe,ZW,ZWE,14645473,Africa,2.42395722\r
-08/07/2020,8,7,2020,53,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.78894871\r
-07/07/2020,7,7,2020,18,1,Zimbabwe,ZW,ZWE,14645473,Africa,1.51582677\r
-06/07/2020,6,7,2020,18,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.54996701\r
-05/07/2020,5,7,2020,73,1,Zimbabwe,ZW,ZWE,14645473,Africa,1.44754628\r
-04/07/2020,4,7,2020,8,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.99689508\r
-03/07/2020,3,7,2020,12,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.05151947\r
-02/07/2020,2,7,2020,14,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.39292189\r
-01/07/2020,1,7,2020,17,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.34512556\r
-30/06/2020,30,6,2020,7,1,Zimbabwe,ZW,ZWE,14645473,Africa,1.27684507\r
-29/06/2020,29,6,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.25636092\r
-28/06/2020,28,6,2020,6,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.44071823\r
-27/06/2020,27,6,2020,10,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.48851457\r
-26/06/2020,26,6,2020,21,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.49534262\r
-25/06/2020,25,6,2020,5,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.43389019\r
-24/06/2020,24,6,2020,13,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.44071823\r
-23/06/2020,23,6,2020,23,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.53631091\r
-22/06/2020,22,6,2020,3,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.41340604\r
-21/06/2020,21,6,2020,7,2,Zimbabwe,ZW,ZWE,14645473,Africa,1.41340604\r
-20/06/2020,20,6,2020,16,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.46120238\r
-19/06/2020,19,6,2020,62,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.54313896\r
-18/06/2020,18,6,2020,7,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.22222068\r
-17/06/2020,17,6,2020,7,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.28367312\r
-16/06/2020,16,6,2020,4,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.25636092\r
-15/06/2020,15,6,2020,27,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.39974994\r
-14/06/2020,14,6,2020,13,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.24270483\r
-13/06/2020,13,6,2020,11,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.24953288\r
-12/06/2020,12,6,2020,12,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.24953288\r
-11/06/2020,11,6,2020,6,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.28367312\r
-10/06/2020,10,6,2020,27,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.76163651\r
-09/06/2020,9,6,2020,5,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.5772792\r
-08/06/2020,8,6,2020,3,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.54313896\r
-07/06/2020,7,6,2020,14,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.52265482\r
-06/06/2020,6,6,2020,28,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.42706214\r
-05/06/2020,5,6,2020,15,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.27001702\r
-04/06/2020,4,6,2020,16,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.18808044\r
-03/06/2020,3,6,2020,3,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.09248776\r
-02/06/2020,2,6,2020,25,0,Zimbabwe,ZW,ZWE,14645473,Africa,1.07200362\r
-01/06/2020,1,6,2020,4,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.9013024\r
-31/05/2020,31,5,2020,14,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.88764631\r
-30/05/2020,30,5,2020,11,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.80570972\r
-29/05/2020,29,5,2020,17,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.76474143\r
-28/05/2020,28,5,2020,76,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.64866461\r
-27/05/2020,27,5,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.12973292\r
-26/05/2020,26,5,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.12973292\r
-25/05/2020,25,5,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.13656097\r
-24/05/2020,24,5,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.13656097\r
-23/05/2020,23,5,2020,5,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.14338902\r
-22/05/2020,22,5,2020,3,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.11607682\r
-21/05/2020,21,5,2020,2,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.09559268\r
-20/05/2020,20,5,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.08193658\r
-19/05/2020,19,5,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.08193658\r
-18/05/2020,18,5,2020,2,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.08193658\r
-17/05/2020,17,5,2020,2,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.06828049\r
-16/05/2020,16,5,2020,5,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.05462439\r
-15/05/2020,15,5,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.02048415\r
-14/05/2020,14,5,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.02048415\r
-13/05/2020,13,5,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.03414024\r
-12/05/2020,12,5,2020,1,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.03414024\r
-11/05/2020,11,5,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.03414024\r
-10/05/2020,10,5,2020,1,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.03414024\r
-09/05/2020,9,5,2020,1,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.04096829\r
-08/05/2020,8,5,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.03414024\r
-07/05/2020,7,5,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.04096829\r
-06/05/2020,6,5,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.04096829\r
-05/05/2020,5,5,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.06145244\r
-04/05/2020,4,5,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.06145244\r
-03/05/2020,3,5,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.06145244\r
-02/05/2020,2,5,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.06828049\r
-01/05/2020,1,5,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.06828049\r
-30/04/2020,30,4,2020,2,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.07510853\r
-29/04/2020,29,4,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.10242073\r
-28/04/2020,28,4,2020,1,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.10242073\r
-27/04/2020,27,4,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.11607682\r
-26/04/2020,26,4,2020,2,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.11607682\r
-25/04/2020,25,4,2020,0,1,Zimbabwe,ZW,ZWE,14645473,Africa,0.12290487\r
-24/04/2020,24,4,2020,1,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.12290487\r
-23/04/2020,23,4,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.11607682\r
-22/04/2020,22,4,2020,3,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.12290487\r
-21/04/2020,21,4,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.10924878\r
-20/04/2020,20,4,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.10924878\r
-19/04/2020,19,4,2020,1,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.10924878\r
-18/04/2020,18,4,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.10242073\r
-17/04/2020,17,4,2020,1,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.10924878\r
-16/04/2020,16,4,2020,6,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.10242073\r
-15/04/2020,15,4,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.06145244\r
-14/04/2020,14,4,2020,3,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.06828049\r
-13/04/2020,13,4,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.04779634\r
-12/04/2020,12,4,2020,3,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.04779634\r
-11/04/2020,11,4,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.04096829\r
-10/04/2020,10,4,2020,0,1,Zimbabwe,ZW,ZWE,14645473,Africa,0.05462439\r
-09/04/2020,9,4,2020,1,1,Zimbabwe,ZW,ZWE,14645473,Africa,0.05462439\r
-08/04/2020,8,4,2020,1,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.05462439\r
-07/04/2020,7,4,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.04779634\r
-06/04/2020,6,4,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.04779634\r
-05/04/2020,5,4,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.04779634\r
-04/04/2020,4,4,2020,1,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.05462439\r
-03/04/2020,3,4,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,0.05462439\r
-02/04/2020,2,4,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,\r
-01/04/2020,1,4,2020,1,0,Zimbabwe,ZW,ZWE,14645473,Africa,\r
-31/03/2020,31,3,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,\r
-30/03/2020,30,3,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,\r
-29/03/2020,29,3,2020,2,0,Zimbabwe,ZW,ZWE,14645473,Africa,\r
-28/03/2020,28,3,2020,2,0,Zimbabwe,ZW,ZWE,14645473,Africa,\r
-27/03/2020,27,3,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,\r
-26/03/2020,26,3,2020,1,0,Zimbabwe,ZW,ZWE,14645473,Africa,\r
-25/03/2020,25,3,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,\r
-24/03/2020,24,3,2020,0,1,Zimbabwe,ZW,ZWE,14645473,Africa,\r
-23/03/2020,23,3,2020,0,0,Zimbabwe,ZW,ZWE,14645473,Africa,\r
-22/03/2020,22,3,2020,1,0,Zimbabwe,ZW,ZWE,14645473,Africa,\r
-21/03/2020,21,3,2020,1,0,Zimbabwe,ZW,ZWE,14645473,Africa,\r
diff --git a/covid.ipynb b/covid.ipynb

deleted file mode 100644 (file)

index 50b3ad8..0000000
--- a/covid.ipynb
+++ /dev/null
@@ -1,15016 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Data from [European Centre for Disease Prevention and Control](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import itertools\n",
-    "import collections\n",
-    "import json\n",
-    "import pandas as pd\n",
-    "import numpy as np\n",
-    "from scipy.stats import gmean\n",
-    "import datetime\n",
-    "\n",
-    "import matplotlib as mpl\n",
-    "import matplotlib.pyplot as plt\n",
-    "%matplotlib inline"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "DEATH_COUNT_THRESHOLD = 10\n",
-    "COUNTRIES_CORE = 'IT DE UK ES IE FR'.split()\n",
-    "COUNTRIES_NORDIC = 'SE NO DK FI UK'.split()\n",
-    "# COUNTRIES_FRIENDS = 'IT UK ES BE SI MX'.split()\n",
-    "COUNTRIES_FRIENDS = 'IT UK ES BE SI PT'.split()\n",
-    "\n",
-    "COUNTRIES_AMERICAS = ['AG', 'AR', 'AW', 'BS', 'BB', 'BZ', 'BM', 'BO', 'BR', 'VG', 'KY', # excluding Canada and USA\n",
-    "       'CL', 'CO', 'CR', 'CU', 'CW', 'DM', 'DO', 'EC', 'SV', 'GL', 'GD', 'GT',\n",
-    "       'GY', 'HT', 'HN', 'JM', 'MX', 'MS', 'NI', 'PA', 'PY', 'PE', 'PR', 'KN',\n",
-    "       'LC', 'VC', 'SX', 'SR', 'TT', 'TC', 'VI', 'UY', 'VE']\n",
-    "COUNTRIES_OF_INTEREST = list(set(COUNTRIES_CORE + COUNTRIES_FRIENDS))\n",
-    "COUNTRIES_ALL = list(set(COUNTRIES_CORE + COUNTRIES_FRIENDS + COUNTRIES_NORDIC + COUNTRIES_AMERICAS))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 364,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
-      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
-      "100 2481k  100 2481k    0     0   621k      0  0:00:03  0:00:03 --:--:--  621k\n"
-     ]
-    }
-   ],
-   "source": [
-    "!curl https://opendata.ecdc.europa.eu/covid19/casedistribution/csv/ > covid.csv"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 565,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# First col is a date, treat geoId of NA as 'Namibia', not \"NA\" value\n",
-    "raw_data = pd.read_csv('covid.csv', \n",
-    "                       parse_dates=[0], dayfirst=True,\n",
-    "                       keep_default_na=False, na_values = [''],\n",
-    "#                        dtype = {'day': np.int64, \n",
-    "#                                 'month': np.int64, \n",
-    "#                                 'year': np.int64, \n",
-    "#                                 'cases': np.int64, \n",
-    "#                                 'deaths': np.int64, \n",
-    "#                                 'countriesAndTerritories': str, \n",
-    "#                                 'geoId': str, \n",
-    "#                                 'countryterritoryCode': str, \n",
-    "#                                 'popData2019': np.int64, \n",
-    "#                                 'continentExp': str, \n",
-    "#                                 }\n",
-    "                      )"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 566,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "446856"
-      ]
-     },
-     "execution_count": 566,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "raw_data.size"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 567,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "raw_data.fillna(0, inplace=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 568,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th>day</th>\n",
-       "      <th>month</th>\n",
-       "      <th>year</th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>countriesAndTerritories</th>\n",
-       "      <th>geoId</th>\n",
-       "      <th>countryterritoryCode</th>\n",
-       "      <th>popData2019</th>\n",
-       "      <th>continentExp</th>\n",
-       "      <th>Cumulative_number_for_14_days_of_COVID-19_cases_per_100000</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>0</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>19</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Afghanistan</td>\n",
-       "      <td>AF</td>\n",
-       "      <td>AFG</td>\n",
-       "      <td>38041757.0</td>\n",
-       "      <td>Asia</td>\n",
-       "      <td>2.024092</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>1</td>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>18</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>3</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Afghanistan</td>\n",
-       "      <td>AF</td>\n",
-       "      <td>AFG</td>\n",
-       "      <td>38041757.0</td>\n",
-       "      <td>Asia</td>\n",
-       "      <td>2.239644</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2</td>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>17</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>45</td>\n",
-       "      <td>5</td>\n",
-       "      <td>Afghanistan</td>\n",
-       "      <td>AF</td>\n",
-       "      <td>AFG</td>\n",
-       "      <td>38041757.0</td>\n",
-       "      <td>Asia</td>\n",
-       "      <td>2.329020</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>3</td>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>16</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>120</td>\n",
-       "      <td>7</td>\n",
-       "      <td>Afghanistan</td>\n",
-       "      <td>AF</td>\n",
-       "      <td>AFG</td>\n",
-       "      <td>38041757.0</td>\n",
-       "      <td>Asia</td>\n",
-       "      <td>2.210729</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>4</td>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>15</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>7</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Afghanistan</td>\n",
-       "      <td>AF</td>\n",
-       "      <td>AFG</td>\n",
-       "      <td>38041757.0</td>\n",
-       "      <td>Asia</td>\n",
-       "      <td>1.895286</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "     dateRep  day  month  year  cases  deaths countriesAndTerritories geoId  \\\n",
-       "0 2020-08-19   19      8  2020      0       0             Afghanistan    AF   \n",
-       "1 2020-08-18   18      8  2020      3       0             Afghanistan    AF   \n",
-       "2 2020-08-17   17      8  2020     45       5             Afghanistan    AF   \n",
-       "3 2020-08-16   16      8  2020    120       7             Afghanistan    AF   \n",
-       "4 2020-08-15   15      8  2020      7       0             Afghanistan    AF   \n",
-       "\n",
-       "  countryterritoryCode  popData2019 continentExp  \\\n",
-       "0                  AFG   38041757.0         Asia   \n",
-       "1                  AFG   38041757.0         Asia   \n",
-       "2                  AFG   38041757.0         Asia   \n",
-       "3                  AFG   38041757.0         Asia   \n",
-       "4                  AFG   38041757.0         Asia   \n",
-       "\n",
-       "   Cumulative_number_for_14_days_of_COVID-19_cases_per_100000  \n",
-       "0                                           2.024092           \n",
-       "1                                           2.239644           \n",
-       "2                                           2.329020           \n",
-       "3                                           2.210729           \n",
-       "4                                           1.895286           "
-      ]
-     },
-     "execution_count": 568,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "raw_data.head()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 569,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "dateRep                                                       datetime64[ns]\n",
-       "day                                                                    int64\n",
-       "month                                                                  int64\n",
-       "year                                                                   int64\n",
-       "cases                                                                  int64\n",
-       "deaths                                                                 int64\n",
-       "countriesAndTerritories                                               object\n",
-       "geoId                                                                 object\n",
-       "countryterritoryCode                                                  object\n",
-       "popData2019                                                          float64\n",
-       "continentExp                                                          object\n",
-       "Cumulative_number_for_14_days_of_COVID-19_cases_per_100000           float64\n",
-       "dtype: object"
-      ]
-     },
-     "execution_count": 569,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "raw_data.dtypes"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 570,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "raw_data = raw_data.astype({'dateRep': np.datetime64, \n",
-    "    'day': np.int64, \n",
-    "    'month': np.int64, \n",
-    "    'year': np.int64, \n",
-    "    'cases': np.int64, \n",
-    "    'deaths': np.int64, \n",
-    "    'countriesAndTerritories': str, \n",
-    "    'geoId': str, \n",
-    "    'countryterritoryCode': str, \n",
-    "    'popData2019': np.int64, \n",
-    "    'continentExp': str })"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 571,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "dateRep                                                       datetime64[ns]\n",
-       "day                                                                    int64\n",
-       "month                                                                  int64\n",
-       "year                                                                   int64\n",
-       "cases                                                                  int64\n",
-       "deaths                                                                 int64\n",
-       "countriesAndTerritories                                               object\n",
-       "geoId                                                                 object\n",
-       "countryterritoryCode                                                  object\n",
-       "popData2019                                                            int64\n",
-       "continentExp                                                          object\n",
-       "Cumulative_number_for_14_days_of_COVID-19_cases_per_100000           float64\n",
-       "dtype: object"
-      ]
-     },
-     "execution_count": 571,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "raw_data.dtypes"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 572,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th>day</th>\n",
-       "      <th>month</th>\n",
-       "      <th>year</th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>countriesAndTerritories</th>\n",
-       "      <th>geoId</th>\n",
-       "      <th>countryterritoryCode</th>\n",
-       "      <th>popData2019</th>\n",
-       "      <th>continentExp</th>\n",
-       "      <th>Cumulative_number_for_14_days_of_COVID-19_cases_per_100000</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>35214</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>19</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>1089</td>\n",
-       "      <td>12</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>20.995658</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35215</td>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>18</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>713</td>\n",
-       "      <td>3</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>20.366974</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35216</td>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>17</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>1040</td>\n",
-       "      <td>5</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>20.689569</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35217</td>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>16</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>1077</td>\n",
-       "      <td>3</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>20.243938</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35218</td>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>15</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>1440</td>\n",
-       "      <td>11</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>19.784803</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35219</td>\n",
-       "      <td>2020-08-14</td>\n",
-       "      <td>14</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>1129</td>\n",
-       "      <td>18</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>18.944557</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35220</td>\n",
-       "      <td>2020-08-13</td>\n",
-       "      <td>13</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>1009</td>\n",
-       "      <td>20</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>18.519932</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35221</td>\n",
-       "      <td>2020-08-12</td>\n",
-       "      <td>12</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>1148</td>\n",
-       "      <td>13</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>18.150824</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35222</td>\n",
-       "      <td>2020-08-11</td>\n",
-       "      <td>11</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>816</td>\n",
-       "      <td>18</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>16.533350</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35223</td>\n",
-       "      <td>2020-08-10</td>\n",
-       "      <td>10</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>1062</td>\n",
-       "      <td>5</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>15.865654</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35224</td>\n",
-       "      <td>2020-08-09</td>\n",
-       "      <td>9</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>758</td>\n",
-       "      <td>3</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>14.903872</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35225</td>\n",
-       "      <td>2020-08-08</td>\n",
-       "      <td>8</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>871</td>\n",
-       "      <td>12</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>14.767332</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35226</td>\n",
-       "      <td>2020-08-07</td>\n",
-       "      <td>7</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>950</td>\n",
-       "      <td>18</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>14.557270</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35227</td>\n",
-       "      <td>2020-08-06</td>\n",
-       "      <td>6</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>891</td>\n",
-       "      <td>14</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>14.291692</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35228</td>\n",
-       "      <td>2020-08-05</td>\n",
-       "      <td>5</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>670</td>\n",
-       "      <td>18</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>14.081630</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35229</td>\n",
-       "      <td>2020-08-04</td>\n",
-       "      <td>4</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>928</td>\n",
-       "      <td>1</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>14.266185</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35230</td>\n",
-       "      <td>2020-08-03</td>\n",
-       "      <td>3</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>743</td>\n",
-       "      <td>5</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>13.493458</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35231</td>\n",
-       "      <td>2020-08-02</td>\n",
-       "      <td>2</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>771</td>\n",
-       "      <td>13</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>13.118348</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35232</td>\n",
-       "      <td>2020-08-01</td>\n",
-       "      <td>1</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>880</td>\n",
-       "      <td>20</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>12.815259</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35233</td>\n",
-       "      <td>2020-07-31</td>\n",
-       "      <td>31</td>\n",
-       "      <td>7</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>846</td>\n",
-       "      <td>0</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>12.551182</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35234</td>\n",
-       "      <td>2020-07-30</td>\n",
-       "      <td>30</td>\n",
-       "      <td>7</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>763</td>\n",
-       "      <td>34</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>12.440149</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35235</td>\n",
-       "      <td>2020-07-29</td>\n",
-       "      <td>29</td>\n",
-       "      <td>7</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>70</td>\n",
-       "      <td>21</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>12.323115</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35236</td>\n",
-       "      <td>2020-07-28</td>\n",
-       "      <td>28</td>\n",
-       "      <td>7</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>371</td>\n",
-       "      <td>3</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>13.307403</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35237</td>\n",
-       "      <td>2020-07-27</td>\n",
-       "      <td>27</td>\n",
-       "      <td>7</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>421</td>\n",
-       "      <td>8</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>13.292399</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35238</td>\n",
-       "      <td>2020-07-26</td>\n",
-       "      <td>26</td>\n",
-       "      <td>7</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>667</td>\n",
-       "      <td>15</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>13.323908</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35239</td>\n",
-       "      <td>2020-07-25</td>\n",
-       "      <td>25</td>\n",
-       "      <td>7</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>731</td>\n",
-       "      <td>32</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>13.170863</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35240</td>\n",
-       "      <td>2020-07-24</td>\n",
-       "      <td>24</td>\n",
-       "      <td>7</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>773</td>\n",
-       "      <td>9</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>13.146856</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35241</td>\n",
-       "      <td>2020-07-23</td>\n",
-       "      <td>23</td>\n",
-       "      <td>7</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>751</td>\n",
-       "      <td>17</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>13.026821</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35242</td>\n",
-       "      <td>2020-07-22</td>\n",
-       "      <td>22</td>\n",
-       "      <td>7</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>793</td>\n",
-       "      <td>25</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>12.795753</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35243</td>\n",
-       "      <td>2020-07-21</td>\n",
-       "      <td>21</td>\n",
-       "      <td>7</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>413</td>\n",
-       "      <td>10</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>12.662214</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35244</td>\n",
-       "      <td>2020-07-20</td>\n",
-       "      <td>20</td>\n",
-       "      <td>7</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>493</td>\n",
-       "      <td>11</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>12.875277</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35245</td>\n",
-       "      <td>2020-07-19</td>\n",
-       "      <td>19</td>\n",
-       "      <td>7</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>569</td>\n",
-       "      <td>9</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>12.737236</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35246</td>\n",
-       "      <td>2020-07-18</td>\n",
-       "      <td>18</td>\n",
-       "      <td>7</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>704</td>\n",
-       "      <td>26</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>12.752240</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35247</td>\n",
-       "      <td>2020-07-17</td>\n",
-       "      <td>17</td>\n",
-       "      <td>7</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>772</td>\n",
-       "      <td>24</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>12.599196</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35248</td>\n",
-       "      <td>2020-07-16</td>\n",
-       "      <td>16</td>\n",
-       "      <td>7</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>685</td>\n",
-       "      <td>26</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>12.417642</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35249</td>\n",
-       "      <td>2020-07-15</td>\n",
-       "      <td>15</td>\n",
-       "      <td>7</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>726</td>\n",
-       "      <td>44</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>12.315612</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35250</td>\n",
-       "      <td>2020-07-14</td>\n",
-       "      <td>14</td>\n",
-       "      <td>7</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>361</td>\n",
-       "      <td>10</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>12.321614</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35251</td>\n",
-       "      <td>2020-07-13</td>\n",
-       "      <td>13</td>\n",
-       "      <td>7</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>442</td>\n",
-       "      <td>9</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>12.449152</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35252</td>\n",
-       "      <td>2020-07-12</td>\n",
-       "      <td>12</td>\n",
-       "      <td>7</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>565</td>\n",
-       "      <td>17</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>12.759743</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35253</td>\n",
-       "      <td>2020-07-11</td>\n",
-       "      <td>11</td>\n",
-       "      <td>7</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>715</td>\n",
-       "      <td>34</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>12.918789</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35254</td>\n",
-       "      <td>2020-07-10</td>\n",
-       "      <td>10</td>\n",
-       "      <td>7</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>693</td>\n",
-       "      <td>31</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>GBR</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>12.927792</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "         dateRep  day  month  year  cases  deaths countriesAndTerritories  \\\n",
-       "35214 2020-08-19   19      8  2020   1089      12          United_Kingdom   \n",
-       "35215 2020-08-18   18      8  2020    713       3          United_Kingdom   \n",
-       "35216 2020-08-17   17      8  2020   1040       5          United_Kingdom   \n",
-       "35217 2020-08-16   16      8  2020   1077       3          United_Kingdom   \n",
-       "35218 2020-08-15   15      8  2020   1440      11          United_Kingdom   \n",
-       "35219 2020-08-14   14      8  2020   1129      18          United_Kingdom   \n",
-       "35220 2020-08-13   13      8  2020   1009      20          United_Kingdom   \n",
-       "35221 2020-08-12   12      8  2020   1148      13          United_Kingdom   \n",
-       "35222 2020-08-11   11      8  2020    816      18          United_Kingdom   \n",
-       "35223 2020-08-10   10      8  2020   1062       5          United_Kingdom   \n",
-       "35224 2020-08-09    9      8  2020    758       3          United_Kingdom   \n",
-       "35225 2020-08-08    8      8  2020    871      12          United_Kingdom   \n",
-       "35226 2020-08-07    7      8  2020    950      18          United_Kingdom   \n",
-       "35227 2020-08-06    6      8  2020    891      14          United_Kingdom   \n",
-       "35228 2020-08-05    5      8  2020    670      18          United_Kingdom   \n",
-       "35229 2020-08-04    4      8  2020    928       1          United_Kingdom   \n",
-       "35230 2020-08-03    3      8  2020    743       5          United_Kingdom   \n",
-       "35231 2020-08-02    2      8  2020    771      13          United_Kingdom   \n",
-       "35232 2020-08-01    1      8  2020    880      20          United_Kingdom   \n",
-       "35233 2020-07-31   31      7  2020    846       0          United_Kingdom   \n",
-       "35234 2020-07-30   30      7  2020    763      34          United_Kingdom   \n",
-       "35235 2020-07-29   29      7  2020     70      21          United_Kingdom   \n",
-       "35236 2020-07-28   28      7  2020    371       3          United_Kingdom   \n",
-       "35237 2020-07-27   27      7  2020    421       8          United_Kingdom   \n",
-       "35238 2020-07-26   26      7  2020    667      15          United_Kingdom   \n",
-       "35239 2020-07-25   25      7  2020    731      32          United_Kingdom   \n",
-       "35240 2020-07-24   24      7  2020    773       9          United_Kingdom   \n",
-       "35241 2020-07-23   23      7  2020    751      17          United_Kingdom   \n",
-       "35242 2020-07-22   22      7  2020    793      25          United_Kingdom   \n",
-       "35243 2020-07-21   21      7  2020    413      10          United_Kingdom   \n",
-       "35244 2020-07-20   20      7  2020    493      11          United_Kingdom   \n",
-       "35245 2020-07-19   19      7  2020    569       9          United_Kingdom   \n",
-       "35246 2020-07-18   18      7  2020    704      26          United_Kingdom   \n",
-       "35247 2020-07-17   17      7  2020    772      24          United_Kingdom   \n",
-       "35248 2020-07-16   16      7  2020    685      26          United_Kingdom   \n",
-       "35249 2020-07-15   15      7  2020    726      44          United_Kingdom   \n",
-       "35250 2020-07-14   14      7  2020    361      10          United_Kingdom   \n",
-       "35251 2020-07-13   13      7  2020    442       9          United_Kingdom   \n",
-       "35252 2020-07-12   12      7  2020    565      17          United_Kingdom   \n",
-       "35253 2020-07-11   11      7  2020    715      34          United_Kingdom   \n",
-       "35254 2020-07-10   10      7  2020    693      31          United_Kingdom   \n",
-       "\n",
-       "      geoId countryterritoryCode  popData2019 continentExp  \\\n",
-       "35214    UK                  GBR     66647112       Europe   \n",
-       "35215    UK                  GBR     66647112       Europe   \n",
-       "35216    UK                  GBR     66647112       Europe   \n",
-       "35217    UK                  GBR     66647112       Europe   \n",
-       "35218    UK                  GBR     66647112       Europe   \n",
-       "35219    UK                  GBR     66647112       Europe   \n",
-       "35220    UK                  GBR     66647112       Europe   \n",
-       "35221    UK                  GBR     66647112       Europe   \n",
-       "35222    UK                  GBR     66647112       Europe   \n",
-       "35223    UK                  GBR     66647112       Europe   \n",
-       "35224    UK                  GBR     66647112       Europe   \n",
-       "35225    UK                  GBR     66647112       Europe   \n",
-       "35226    UK                  GBR     66647112       Europe   \n",
-       "35227    UK                  GBR     66647112       Europe   \n",
-       "35228    UK                  GBR     66647112       Europe   \n",
-       "35229    UK                  GBR     66647112       Europe   \n",
-       "35230    UK                  GBR     66647112       Europe   \n",
-       "35231    UK                  GBR     66647112       Europe   \n",
-       "35232    UK                  GBR     66647112       Europe   \n",
-       "35233    UK                  GBR     66647112       Europe   \n",
-       "35234    UK                  GBR     66647112       Europe   \n",
-       "35235    UK                  GBR     66647112       Europe   \n",
-       "35236    UK                  GBR     66647112       Europe   \n",
-       "35237    UK                  GBR     66647112       Europe   \n",
-       "35238    UK                  GBR     66647112       Europe   \n",
-       "35239    UK                  GBR     66647112       Europe   \n",
-       "35240    UK                  GBR     66647112       Europe   \n",
-       "35241    UK                  GBR     66647112       Europe   \n",
-       "35242    UK                  GBR     66647112       Europe   \n",
-       "35243    UK                  GBR     66647112       Europe   \n",
-       "35244    UK                  GBR     66647112       Europe   \n",
-       "35245    UK                  GBR     66647112       Europe   \n",
-       "35246    UK                  GBR     66647112       Europe   \n",
-       "35247    UK                  GBR     66647112       Europe   \n",
-       "35248    UK                  GBR     66647112       Europe   \n",
-       "35249    UK                  GBR     66647112       Europe   \n",
-       "35250    UK                  GBR     66647112       Europe   \n",
-       "35251    UK                  GBR     66647112       Europe   \n",
-       "35252    UK                  GBR     66647112       Europe   \n",
-       "35253    UK                  GBR     66647112       Europe   \n",
-       "35254    UK                  GBR     66647112       Europe   \n",
-       "\n",
-       "       Cumulative_number_for_14_days_of_COVID-19_cases_per_100000  \n",
-       "35214                                          20.995658           \n",
-       "35215                                          20.366974           \n",
-       "35216                                          20.689569           \n",
-       "35217                                          20.243938           \n",
-       "35218                                          19.784803           \n",
-       "35219                                          18.944557           \n",
-       "35220                                          18.519932           \n",
-       "35221                                          18.150824           \n",
-       "35222                                          16.533350           \n",
-       "35223                                          15.865654           \n",
-       "35224                                          14.903872           \n",
-       "35225                                          14.767332           \n",
-       "35226                                          14.557270           \n",
-       "35227                                          14.291692           \n",
-       "35228                                          14.081630           \n",
-       "35229                                          14.266185           \n",
-       "35230                                          13.493458           \n",
-       "35231                                          13.118348           \n",
-       "35232                                          12.815259           \n",
-       "35233                                          12.551182           \n",
-       "35234                                          12.440149           \n",
-       "35235                                          12.323115           \n",
-       "35236                                          13.307403           \n",
-       "35237                                          13.292399           \n",
-       "35238                                          13.323908           \n",
-       "35239                                          13.170863           \n",
-       "35240                                          13.146856           \n",
-       "35241                                          13.026821           \n",
-       "35242                                          12.795753           \n",
-       "35243                                          12.662214           \n",
-       "35244                                          12.875277           \n",
-       "35245                                          12.737236           \n",
-       "35246                                          12.752240           \n",
-       "35247                                          12.599196           \n",
-       "35248                                          12.417642           \n",
-       "35249                                          12.315612           \n",
-       "35250                                          12.321614           \n",
-       "35251                                          12.449152           \n",
-       "35252                                          12.759743           \n",
-       "35253                                          12.918789           \n",
-       "35254                                          12.927792           "
-      ]
-     },
-     "execution_count": 572,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "raw_data[((raw_data.geoId == 'UK') & (raw_data.dateRep >= '2020-07-10'))]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 573,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# raw_data = raw_data[~ ((raw_data.geoId == 'ES') & (raw_data.dateRep >= '2020-05-22'))]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 574,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th>day</th>\n",
-       "      <th>month</th>\n",
-       "      <th>year</th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>countriesAndTerritories</th>\n",
-       "      <th>countryterritoryCode</th>\n",
-       "      <th>popData2019</th>\n",
-       "      <th>continentExp</th>\n",
-       "      <th>Cumulative_number_for_14_days_of_COVID-19_cases_per_100000</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>geoId</th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td rowspan=\"5\" valign=\"top\">AD</td>\n",
-       "      <td>2020-03-03</td>\n",
-       "      <td>3</td>\n",
-       "      <td>3</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Andorra</td>\n",
-       "      <td>AND</td>\n",
-       "      <td>76177</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>0.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-14</td>\n",
-       "      <td>14</td>\n",
-       "      <td>3</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Andorra</td>\n",
-       "      <td>AND</td>\n",
-       "      <td>76177</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>0.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-16</td>\n",
-       "      <td>16</td>\n",
-       "      <td>3</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>3</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Andorra</td>\n",
-       "      <td>AND</td>\n",
-       "      <td>76177</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>0.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-17</td>\n",
-       "      <td>17</td>\n",
-       "      <td>3</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>9</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Andorra</td>\n",
-       "      <td>AND</td>\n",
-       "      <td>76177</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>0.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-18</td>\n",
-       "      <td>18</td>\n",
-       "      <td>3</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Andorra</td>\n",
-       "      <td>AND</td>\n",
-       "      <td>76177</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>0.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td rowspan=\"5\" valign=\"top\">ZW</td>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>15</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>82</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Zimbabwe</td>\n",
-       "      <td>ZWE</td>\n",
-       "      <td>14645473</td>\n",
-       "      <td>Africa</td>\n",
-       "      <td>12.993776</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>16</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>104</td>\n",
-       "      <td>2</td>\n",
-       "      <td>Zimbabwe</td>\n",
-       "      <td>ZWE</td>\n",
-       "      <td>14645473</td>\n",
-       "      <td>Africa</td>\n",
-       "      <td>10.358150</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>17</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>85</td>\n",
-       "      <td>2</td>\n",
-       "      <td>Zimbabwe</td>\n",
-       "      <td>ZWE</td>\n",
-       "      <td>14645473</td>\n",
-       "      <td>Africa</td>\n",
-       "      <td>9.149585</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>18</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>47</td>\n",
-       "      <td>3</td>\n",
-       "      <td>Zimbabwe</td>\n",
-       "      <td>ZWE</td>\n",
-       "      <td>14645473</td>\n",
-       "      <td>Africa</td>\n",
-       "      <td>8.418984</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>19</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>70</td>\n",
-       "      <td>6</td>\n",
-       "      <td>Zimbabwe</td>\n",
-       "      <td>ZWE</td>\n",
-       "      <td>14645473</td>\n",
-       "      <td>Africa</td>\n",
-       "      <td>7.900052</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>37238 rows × 10 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                  day  month  year  cases  deaths countriesAndTerritories  \\\n",
-       "geoId dateRep                                                               \n",
-       "AD    2020-03-03    3      3  2020      1       0                 Andorra   \n",
-       "      2020-03-14   14      3  2020      1       0                 Andorra   \n",
-       "      2020-03-16   16      3  2020      3       0                 Andorra   \n",
-       "      2020-03-17   17      3  2020      9       0                 Andorra   \n",
-       "      2020-03-18   18      3  2020      0       0                 Andorra   \n",
-       "...               ...    ...   ...    ...     ...                     ...   \n",
-       "ZW    2020-08-15   15      8  2020     82       0                Zimbabwe   \n",
-       "      2020-08-16   16      8  2020    104       2                Zimbabwe   \n",
-       "      2020-08-17   17      8  2020     85       2                Zimbabwe   \n",
-       "      2020-08-18   18      8  2020     47       3                Zimbabwe   \n",
-       "      2020-08-19   19      8  2020     70       6                Zimbabwe   \n",
-       "\n",
-       "                 countryterritoryCode  popData2019 continentExp  \\\n",
-       "geoId dateRep                                                     \n",
-       "AD    2020-03-03                  AND        76177       Europe   \n",
-       "      2020-03-14                  AND        76177       Europe   \n",
-       "      2020-03-16                  AND        76177       Europe   \n",
-       "      2020-03-17                  AND        76177       Europe   \n",
-       "      2020-03-18                  AND        76177       Europe   \n",
-       "...                               ...          ...          ...   \n",
-       "ZW    2020-08-15                  ZWE     14645473       Africa   \n",
-       "      2020-08-16                  ZWE     14645473       Africa   \n",
-       "      2020-08-17                  ZWE     14645473       Africa   \n",
-       "      2020-08-18                  ZWE     14645473       Africa   \n",
-       "      2020-08-19                  ZWE     14645473       Africa   \n",
-       "\n",
-       "                  Cumulative_number_for_14_days_of_COVID-19_cases_per_100000  \n",
-       "geoId dateRep                                                                 \n",
-       "AD    2020-03-03                                           0.000000           \n",
-       "      2020-03-14                                           0.000000           \n",
-       "      2020-03-16                                           0.000000           \n",
-       "      2020-03-17                                           0.000000           \n",
-       "      2020-03-18                                           0.000000           \n",
-       "...                                                             ...           \n",
-       "ZW    2020-08-15                                          12.993776           \n",
-       "      2020-08-16                                          10.358150           \n",
-       "      2020-08-17                                           9.149585           \n",
-       "      2020-08-18                                           8.418984           \n",
-       "      2020-08-19                                           7.900052           \n",
-       "\n",
-       "[37238 rows x 10 columns]"
-      ]
-     },
-     "execution_count": 574,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "base_data = raw_data.set_index(['geoId', 'dateRep'])\n",
-    "base_data.sort_index(inplace=True)\n",
-    "base_data"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 575,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>day</th>\n",
-       "      <th>month</th>\n",
-       "      <th>year</th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>countriesAndTerritories</th>\n",
-       "      <th>countryterritoryCode</th>\n",
-       "      <th>popData2019</th>\n",
-       "      <th>continentExp</th>\n",
-       "      <th>Cumulative_number_for_14_days_of_COVID-19_cases_per_100000</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>dateRep</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>2020-05-10</td>\n",
-       "      <td>10</td>\n",
-       "      <td>5</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>3416</td>\n",
-       "      <td>143</td>\n",
-       "      <td>Spain</td>\n",
-       "      <td>ESP</td>\n",
-       "      <td>46937060</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>37.213664</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-05-11</td>\n",
-       "      <td>11</td>\n",
-       "      <td>5</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>393</td>\n",
-       "      <td>123</td>\n",
-       "      <td>Spain</td>\n",
-       "      <td>ESP</td>\n",
-       "      <td>46937060</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>34.514305</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-05-12</td>\n",
-       "      <td>12</td>\n",
-       "      <td>5</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>482</td>\n",
-       "      <td>176</td>\n",
-       "      <td>Spain</td>\n",
-       "      <td>ESP</td>\n",
-       "      <td>46937060</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>32.292180</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-05-13</td>\n",
-       "      <td>13</td>\n",
-       "      <td>5</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>439</td>\n",
-       "      <td>184</td>\n",
-       "      <td>Spain</td>\n",
-       "      <td>ESP</td>\n",
-       "      <td>46937060</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>31.422931</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-05-14</td>\n",
-       "      <td>14</td>\n",
-       "      <td>5</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>849</td>\n",
-       "      <td>217</td>\n",
-       "      <td>Spain</td>\n",
-       "      <td>ESP</td>\n",
-       "      <td>46937060</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>30.587770</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-14</td>\n",
-       "      <td>14</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>5479</td>\n",
-       "      <td>12</td>\n",
-       "      <td>Spain</td>\n",
-       "      <td>ESP</td>\n",
-       "      <td>46937060</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>115.667662</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>15</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Spain</td>\n",
-       "      <td>ESP</td>\n",
-       "      <td>46937060</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>115.667662</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>16</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Spain</td>\n",
-       "      <td>ESP</td>\n",
-       "      <td>46937060</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>115.667662</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>17</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>16269</td>\n",
-       "      <td>29</td>\n",
-       "      <td>Spain</td>\n",
-       "      <td>ESP</td>\n",
-       "      <td>46937060</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>132.151439</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>18</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>5114</td>\n",
-       "      <td>24</td>\n",
-       "      <td>Spain</td>\n",
-       "      <td>ESP</td>\n",
-       "      <td>46937060</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>130.775127</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>101 rows × 10 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "            day  month  year  cases  deaths countriesAndTerritories  \\\n",
-       "dateRep                                                               \n",
-       "2020-05-10   10      5  2020   3416     143                   Spain   \n",
-       "2020-05-11   11      5  2020    393     123                   Spain   \n",
-       "2020-05-12   12      5  2020    482     176                   Spain   \n",
-       "2020-05-13   13      5  2020    439     184                   Spain   \n",
-       "2020-05-14   14      5  2020    849     217                   Spain   \n",
-       "...         ...    ...   ...    ...     ...                     ...   \n",
-       "2020-08-14   14      8  2020   5479      12                   Spain   \n",
-       "2020-08-15   15      8  2020      0       0                   Spain   \n",
-       "2020-08-16   16      8  2020      0       0                   Spain   \n",
-       "2020-08-17   17      8  2020  16269      29                   Spain   \n",
-       "2020-08-18   18      8  2020   5114      24                   Spain   \n",
-       "\n",
-       "           countryterritoryCode  popData2019 continentExp  \\\n",
-       "dateRep                                                     \n",
-       "2020-05-10                  ESP     46937060       Europe   \n",
-       "2020-05-11                  ESP     46937060       Europe   \n",
-       "2020-05-12                  ESP     46937060       Europe   \n",
-       "2020-05-13                  ESP     46937060       Europe   \n",
-       "2020-05-14                  ESP     46937060       Europe   \n",
-       "...                         ...          ...          ...   \n",
-       "2020-08-14                  ESP     46937060       Europe   \n",
-       "2020-08-15                  ESP     46937060       Europe   \n",
-       "2020-08-16                  ESP     46937060       Europe   \n",
-       "2020-08-17                  ESP     46937060       Europe   \n",
-       "2020-08-18                  ESP     46937060       Europe   \n",
-       "\n",
-       "            Cumulative_number_for_14_days_of_COVID-19_cases_per_100000  \n",
-       "dateRep                                                                 \n",
-       "2020-05-10                                          37.213664           \n",
-       "2020-05-11                                          34.514305           \n",
-       "2020-05-12                                          32.292180           \n",
-       "2020-05-13                                          31.422931           \n",
-       "2020-05-14                                          30.587770           \n",
-       "...                                                       ...           \n",
-       "2020-08-14                                         115.667662           \n",
-       "2020-08-15                                         115.667662           \n",
-       "2020-08-16                                         115.667662           \n",
-       "2020-08-17                                         132.151439           \n",
-       "2020-08-18                                         130.775127           \n",
-       "\n",
-       "[101 rows x 10 columns]"
-      ]
-     },
-     "execution_count": 575,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "base_data.loc['ES'].loc['2020-05-10':]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 576,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>countriesAndTerritories</th>\n",
-       "      <th>popData2019</th>\n",
-       "      <th>continentExp</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>geoId</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>AF</td>\n",
-       "      <td>Afghanistan</td>\n",
-       "      <td>38041757</td>\n",
-       "      <td>Asia</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>AL</td>\n",
-       "      <td>Albania</td>\n",
-       "      <td>2862427</td>\n",
-       "      <td>Europe</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>DZ</td>\n",
-       "      <td>Algeria</td>\n",
-       "      <td>43053054</td>\n",
-       "      <td>Africa</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>AD</td>\n",
-       "      <td>Andorra</td>\n",
-       "      <td>76177</td>\n",
-       "      <td>Europe</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>AO</td>\n",
-       "      <td>Angola</td>\n",
-       "      <td>31825299</td>\n",
-       "      <td>Africa</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "      countriesAndTerritories  popData2019 continentExp\n",
-       "geoId                                                  \n",
-       "AF                Afghanistan     38041757         Asia\n",
-       "AL                    Albania      2862427       Europe\n",
-       "DZ                    Algeria     43053054       Africa\n",
-       "AD                    Andorra        76177       Europe\n",
-       "AO                     Angola     31825299       Africa"
-      ]
-     },
-     "execution_count": 576,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "countries = raw_data[['geoId', 'countriesAndTerritories', 'popData2019', 'continentExp']]\n",
-    "countries = countries[countries['popData2019'] != '']\n",
-    "countries = countries.drop_duplicates()\n",
-    "countries.set_index('geoId', inplace=True)\n",
-    "countries = countries.astype({'popData2019': 'int64'})\n",
-    "countries.head()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 577,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(210, 3)"
-      ]
-     },
-     "execution_count": 577,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "countries.shape"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 578,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>countriesAndTerritories</th>\n",
-       "      <th>popData2019</th>\n",
-       "      <th>continentExp</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>geoId</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>FI</td>\n",
-       "      <td>Finland</td>\n",
-       "      <td>5517919</td>\n",
-       "      <td>Europe</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "      countriesAndTerritories  popData2019 continentExp\n",
-       "geoId                                                  \n",
-       "FI                    Finland      5517919       Europe"
-      ]
-     },
-     "execution_count": 578,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "countries[countries.countriesAndTerritories == 'Finland']"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 579,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>countriesAndTerritories</th>\n",
-       "      <th>popData2019</th>\n",
-       "      <th>continentExp</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>geoId</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>PT</td>\n",
-       "      <td>Portugal</td>\n",
-       "      <td>10276617</td>\n",
-       "      <td>Europe</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>ES</td>\n",
-       "      <td>Spain</td>\n",
-       "      <td>46937060</td>\n",
-       "      <td>Europe</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>BE</td>\n",
-       "      <td>Belgium</td>\n",
-       "      <td>11455519</td>\n",
-       "      <td>Europe</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>IT</td>\n",
-       "      <td>Italy</td>\n",
-       "      <td>60359546</td>\n",
-       "      <td>Europe</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>IE</td>\n",
-       "      <td>Ireland</td>\n",
-       "      <td>4904240</td>\n",
-       "      <td>Europe</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>DE</td>\n",
-       "      <td>Germany</td>\n",
-       "      <td>83019213</td>\n",
-       "      <td>Europe</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>FR</td>\n",
-       "      <td>France</td>\n",
-       "      <td>67012883</td>\n",
-       "      <td>Europe</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>UK</td>\n",
-       "      <td>United_Kingdom</td>\n",
-       "      <td>66647112</td>\n",
-       "      <td>Europe</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>SI</td>\n",
-       "      <td>Slovenia</td>\n",
-       "      <td>2080908</td>\n",
-       "      <td>Europe</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "      countriesAndTerritories  popData2019 continentExp\n",
-       "geoId                                                  \n",
-       "PT                   Portugal     10276617       Europe\n",
-       "ES                      Spain     46937060       Europe\n",
-       "BE                    Belgium     11455519       Europe\n",
-       "IT                      Italy     60359546       Europe\n",
-       "IE                    Ireland      4904240       Europe\n",
-       "DE                    Germany     83019213       Europe\n",
-       "FR                     France     67012883       Europe\n",
-       "UK             United_Kingdom     66647112       Europe\n",
-       "SI                   Slovenia      2080908       Europe"
-      ]
-     },
-     "execution_count": 579,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "countries.loc[COUNTRIES_OF_INTEREST]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 580,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Index(['AI', 'AG', 'AR', 'AW', 'BS', 'BB', 'BZ', 'BM', 'BO', 'BQ', 'BR', 'VG',\n",
-       "       'CA', 'KY', 'CL', 'CO', 'CR', 'CU', 'CW', 'DM', 'DO', 'EC', 'SV', 'FK',\n",
-       "       'GL', 'GD', 'GT', 'GY', 'HT', 'HN', 'JM', 'MX', 'MS', 'NI', 'PA', 'PY',\n",
-       "       'PE', 'PR', 'KN', 'LC', 'VC', 'SX', 'SR', 'TT', 'TC', 'US', 'VI', 'UY',\n",
-       "       'VE'],\n",
-       "      dtype='object', name='geoId')"
-      ]
-     },
-     "execution_count": 580,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "countries[countries.continentExp == 'America'].index"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 581,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>geoId</th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td rowspan=\"5\" valign=\"top\">AD</td>\n",
-       "      <td>2020-03-03</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-14</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-16</td>\n",
-       "      <td>3</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-17</td>\n",
-       "      <td>9</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-18</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                  cases  deaths\n",
-       "geoId dateRep                  \n",
-       "AD    2020-03-03      1       0\n",
-       "      2020-03-14      1       0\n",
-       "      2020-03-16      3       0\n",
-       "      2020-03-17      9       0\n",
-       "      2020-03-18      0       0"
-      ]
-     },
-     "execution_count": 581,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_by_date = base_data[['cases', 'deaths']]\n",
-    "data_by_date.head()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 582,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>dateRep</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>2019-12-31</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-01</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-02</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-03</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-04</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>1440</td>\n",
-       "      <td>11</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>1077</td>\n",
-       "      <td>3</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>1040</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>713</td>\n",
-       "      <td>3</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>1089</td>\n",
-       "      <td>12</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>233 rows × 2 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "            cases  deaths\n",
-       "dateRep                  \n",
-       "2019-12-31      0       0\n",
-       "2020-01-01      0       0\n",
-       "2020-01-02      0       0\n",
-       "2020-01-03      0       0\n",
-       "2020-01-04      0       0\n",
-       "...           ...     ...\n",
-       "2020-08-15   1440      11\n",
-       "2020-08-16   1077       3\n",
-       "2020-08-17   1040       5\n",
-       "2020-08-18    713       3\n",
-       "2020-08-19   1089      12\n",
-       "\n",
-       "[233 rows x 2 columns]"
-      ]
-     },
-     "execution_count": 582,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_by_date.loc['UK']"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 583,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# data_by_date.deaths.drop_duplicates().sort_values().to_csv('dth.csv', header=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 584,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>geoId</th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td rowspan=\"5\" valign=\"top\">AD</td>\n",
-       "      <td>2020-03-03</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-14</td>\n",
-       "      <td>2</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-16</td>\n",
-       "      <td>5</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-17</td>\n",
-       "      <td>14</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-18</td>\n",
-       "      <td>14</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td rowspan=\"5\" valign=\"top\">ZW</td>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>5072</td>\n",
-       "      <td>128</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>5176</td>\n",
-       "      <td>130</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>5261</td>\n",
-       "      <td>132</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>5308</td>\n",
-       "      <td>135</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>5378</td>\n",
-       "      <td>141</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>37238 rows × 2 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                  cases  deaths\n",
-       "geoId dateRep                  \n",
-       "AD    2020-03-03      1       0\n",
-       "      2020-03-14      2       0\n",
-       "      2020-03-16      5       0\n",
-       "      2020-03-17     14       0\n",
-       "      2020-03-18     14       0\n",
-       "...                 ...     ...\n",
-       "ZW    2020-08-15   5072     128\n",
-       "      2020-08-16   5176     130\n",
-       "      2020-08-17   5261     132\n",
-       "      2020-08-18   5308     135\n",
-       "      2020-08-19   5378     141\n",
-       "\n",
-       "[37238 rows x 2 columns]"
-      ]
-     },
-     "execution_count": 584,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_by_date.groupby(level=0).cumsum()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 585,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>geoId</th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td rowspan=\"5\" valign=\"top\">AD</td>\n",
-       "      <td>2020-03-03</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-14</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-16</td>\n",
-       "      <td>3</td>\n",
-       "      <td>0</td>\n",
-       "      <td>5</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-17</td>\n",
-       "      <td>9</td>\n",
-       "      <td>0</td>\n",
-       "      <td>14</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-18</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>14</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td rowspan=\"5\" valign=\"top\">ZW</td>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>82</td>\n",
-       "      <td>0</td>\n",
-       "      <td>5072</td>\n",
-       "      <td>128</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>104</td>\n",
-       "      <td>2</td>\n",
-       "      <td>5176</td>\n",
-       "      <td>130</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>85</td>\n",
-       "      <td>2</td>\n",
-       "      <td>5261</td>\n",
-       "      <td>132</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>47</td>\n",
-       "      <td>3</td>\n",
-       "      <td>5308</td>\n",
-       "      <td>135</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>70</td>\n",
-       "      <td>6</td>\n",
-       "      <td>5378</td>\n",
-       "      <td>141</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>37238 rows × 4 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                  cases  deaths  cases_culm  deaths_culm\n",
-       "geoId dateRep                                           \n",
-       "AD    2020-03-03      1       0           1            0\n",
-       "      2020-03-14      1       0           2            0\n",
-       "      2020-03-16      3       0           5            0\n",
-       "      2020-03-17      9       0          14            0\n",
-       "      2020-03-18      0       0          14            0\n",
-       "...                 ...     ...         ...          ...\n",
-       "ZW    2020-08-15     82       0        5072          128\n",
-       "      2020-08-16    104       2        5176          130\n",
-       "      2020-08-17     85       2        5261          132\n",
-       "      2020-08-18     47       3        5308          135\n",
-       "      2020-08-19     70       6        5378          141\n",
-       "\n",
-       "[37238 rows x 4 columns]"
-      ]
-     },
-     "execution_count": 585,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_by_date = data_by_date.merge(\n",
-    "    data_by_date.groupby(level=0).cumsum(), \n",
-    "    suffixes=('', '_culm'), \n",
-    "    left_index=True, right_index=True)\n",
-    "data_by_date"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 586,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>geoId</th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td rowspan=\"5\" valign=\"top\">AD</td>\n",
-       "      <td>2020-03-03</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-14</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-16</td>\n",
-       "      <td>3</td>\n",
-       "      <td>0</td>\n",
-       "      <td>5</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-17</td>\n",
-       "      <td>9</td>\n",
-       "      <td>0</td>\n",
-       "      <td>14</td>\n",
-       "      <td>0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-18</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>14</td>\n",
-       "      <td>0</td>\n",
-       "      <td>-9.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td rowspan=\"5\" valign=\"top\">ZW</td>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>82</td>\n",
-       "      <td>0</td>\n",
-       "      <td>5072</td>\n",
-       "      <td>128</td>\n",
-       "      <td>-15.0</td>\n",
-       "      <td>-6.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>104</td>\n",
-       "      <td>2</td>\n",
-       "      <td>5176</td>\n",
-       "      <td>130</td>\n",
-       "      <td>22.0</td>\n",
-       "      <td>2.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>85</td>\n",
-       "      <td>2</td>\n",
-       "      <td>5261</td>\n",
-       "      <td>132</td>\n",
-       "      <td>-19.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>47</td>\n",
-       "      <td>3</td>\n",
-       "      <td>5308</td>\n",
-       "      <td>135</td>\n",
-       "      <td>-38.0</td>\n",
-       "      <td>1.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>70</td>\n",
-       "      <td>6</td>\n",
-       "      <td>5378</td>\n",
-       "      <td>141</td>\n",
-       "      <td>23.0</td>\n",
-       "      <td>3.0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>37238 rows × 6 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                  cases  deaths  cases_culm  deaths_culm  cases_diff  \\\n",
-       "geoId dateRep                                                          \n",
-       "AD    2020-03-03      1       0           1            0         NaN   \n",
-       "      2020-03-14      1       0           2            0         0.0   \n",
-       "      2020-03-16      3       0           5            0         2.0   \n",
-       "      2020-03-17      9       0          14            0         6.0   \n",
-       "      2020-03-18      0       0          14            0        -9.0   \n",
-       "...                 ...     ...         ...          ...         ...   \n",
-       "ZW    2020-08-15     82       0        5072          128       -15.0   \n",
-       "      2020-08-16    104       2        5176          130        22.0   \n",
-       "      2020-08-17     85       2        5261          132       -19.0   \n",
-       "      2020-08-18     47       3        5308          135       -38.0   \n",
-       "      2020-08-19     70       6        5378          141        23.0   \n",
-       "\n",
-       "                  deaths_diff  \n",
-       "geoId dateRep                  \n",
-       "AD    2020-03-03          NaN  \n",
-       "      2020-03-14          0.0  \n",
-       "      2020-03-16          0.0  \n",
-       "      2020-03-17          0.0  \n",
-       "      2020-03-18          0.0  \n",
-       "...                       ...  \n",
-       "ZW    2020-08-15         -6.0  \n",
-       "      2020-08-16          2.0  \n",
-       "      2020-08-17          0.0  \n",
-       "      2020-08-18          1.0  \n",
-       "      2020-08-19          3.0  \n",
-       "\n",
-       "[37238 rows x 6 columns]"
-      ]
-     },
-     "execution_count": 586,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_by_date = data_by_date.merge(\n",
-    "    data_by_date[['cases', 'deaths']].groupby(level=0).diff(), \n",
-    "    suffixes=('', '_diff'), \n",
-    "    left_index=True, right_index=True)\n",
-    "data_by_date"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 587,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "cases            5065.0\n",
-       "deaths           1036.0\n",
-       "cases_culm     106443.0\n",
-       "deaths_culm     16029.0\n",
-       "cases_diff        739.0\n",
-       "deaths_diff       156.0\n",
-       "Name: (UK, 2020-04-17 00:00:00), dtype: float64"
-      ]
-     },
-     "execution_count": 587,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_by_date.loc['UK', '2020-04-17']"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 588,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>dateRep</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>2019-12-31</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-01</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-02</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-03</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-04</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>1440</td>\n",
-       "      <td>11</td>\n",
-       "      <td>316367</td>\n",
-       "      <td>41358</td>\n",
-       "      <td>311.0</td>\n",
-       "      <td>-7.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>1077</td>\n",
-       "      <td>3</td>\n",
-       "      <td>317444</td>\n",
-       "      <td>41361</td>\n",
-       "      <td>-363.0</td>\n",
-       "      <td>-8.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>1040</td>\n",
-       "      <td>5</td>\n",
-       "      <td>318484</td>\n",
-       "      <td>41366</td>\n",
-       "      <td>-37.0</td>\n",
-       "      <td>2.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>713</td>\n",
-       "      <td>3</td>\n",
-       "      <td>319197</td>\n",
-       "      <td>41369</td>\n",
-       "      <td>-327.0</td>\n",
-       "      <td>-2.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>1089</td>\n",
-       "      <td>12</td>\n",
-       "      <td>320286</td>\n",
-       "      <td>41381</td>\n",
-       "      <td>376.0</td>\n",
-       "      <td>9.0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>233 rows × 6 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff\n",
-       "dateRep                                                                    \n",
-       "2019-12-31      0       0           0            0         NaN          NaN\n",
-       "2020-01-01      0       0           0            0         0.0          0.0\n",
-       "2020-01-02      0       0           0            0         0.0          0.0\n",
-       "2020-01-03      0       0           0            0         0.0          0.0\n",
-       "2020-01-04      0       0           0            0         0.0          0.0\n",
-       "...           ...     ...         ...          ...         ...          ...\n",
-       "2020-08-15   1440      11      316367        41358       311.0         -7.0\n",
-       "2020-08-16   1077       3      317444        41361      -363.0         -8.0\n",
-       "2020-08-17   1040       5      318484        41366       -37.0          2.0\n",
-       "2020-08-18    713       3      319197        41369      -327.0         -2.0\n",
-       "2020-08-19   1089      12      320286        41381       376.0          9.0\n",
-       "\n",
-       "[233 rows x 6 columns]"
-      ]
-     },
-     "execution_count": 588,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_by_date.loc['UK']"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 589,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# data_by_date[data_by_date.deaths_culm > DEATH_COUNT_THRESHOLD]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 590,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# days_since_threshold = data_by_date[data_by_date.deaths_culm > DEATH_COUNT_THRESHOLD].groupby(level=0).cumcount()\n",
-    "# days_since_threshold.rename('since_threshold', inplace=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 591,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "geoId  dateRep   \n",
-       "AD     2020-04-01     0\n",
-       "       2020-04-02     1\n",
-       "       2020-04-03     2\n",
-       "       2020-04-04     3\n",
-       "       2020-04-05     4\n",
-       "                     ..\n",
-       "ZW     2020-08-15    36\n",
-       "       2020-08-16    37\n",
-       "       2020-08-17    38\n",
-       "       2020-08-18    39\n",
-       "       2020-08-19    40\n",
-       "Name: since_threshold, Length: 18722, dtype: int64"
-      ]
-     },
-     "execution_count": 591,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "dbd = data_by_date[data_by_date.deaths_culm > DEATH_COUNT_THRESHOLD].reset_index(level=1)\n",
-    "dbd['since_threshold'] = dbd.dateRep\n",
-    "dbd.set_index('dateRep', append=True, inplace=True)\n",
-    "dbd.sort_index(inplace=True)\n",
-    "days_since_threshold = dbd.groupby(level=0).diff().since_threshold.dt.days.fillna(0).astype(int).groupby(level=0).cumsum()\n",
-    "# days_since_threshold.groupby(level=0).cumsum()\n",
-    "\n",
-    "# days_since_threshold = dbd.rename('since_threshold')\n",
-    "days_since_threshold"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 592,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# days_since_threshold = (data_by_date[data_by_date.deaths_culm > DEATH_COUNT_THRESHOLD]\n",
-    "#                         .reset_index(level=1).groupby(level=0)\n",
-    "#                         .diff().dateRep.dt.days\n",
-    "#                         .groupby(level=0).cumcount()\n",
-    "#                        )\n",
-    "# days_since_threshold.rename('since_threshold', inplace=True)\n",
-    "# days_since_threshold"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 593,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "      <th>since_threshold</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>geoId</th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td rowspan=\"5\" valign=\"top\">AD</td>\n",
-       "      <td>2020-04-01</td>\n",
-       "      <td>6</td>\n",
-       "      <td>4</td>\n",
-       "      <td>376</td>\n",
-       "      <td>12</td>\n",
-       "      <td>-30.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-04-02</td>\n",
-       "      <td>14</td>\n",
-       "      <td>2</td>\n",
-       "      <td>390</td>\n",
-       "      <td>14</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>-2.0</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-04-03</td>\n",
-       "      <td>38</td>\n",
-       "      <td>1</td>\n",
-       "      <td>428</td>\n",
-       "      <td>15</td>\n",
-       "      <td>24.0</td>\n",
-       "      <td>-1.0</td>\n",
-       "      <td>2</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-04-04</td>\n",
-       "      <td>11</td>\n",
-       "      <td>1</td>\n",
-       "      <td>439</td>\n",
-       "      <td>16</td>\n",
-       "      <td>-27.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-04-05</td>\n",
-       "      <td>27</td>\n",
-       "      <td>1</td>\n",
-       "      <td>466</td>\n",
-       "      <td>17</td>\n",
-       "      <td>16.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>4</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td rowspan=\"5\" valign=\"top\">ZW</td>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>82</td>\n",
-       "      <td>0</td>\n",
-       "      <td>5072</td>\n",
-       "      <td>128</td>\n",
-       "      <td>-15.0</td>\n",
-       "      <td>-6.0</td>\n",
-       "      <td>36</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>104</td>\n",
-       "      <td>2</td>\n",
-       "      <td>5176</td>\n",
-       "      <td>130</td>\n",
-       "      <td>22.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>37</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>85</td>\n",
-       "      <td>2</td>\n",
-       "      <td>5261</td>\n",
-       "      <td>132</td>\n",
-       "      <td>-19.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>38</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>47</td>\n",
-       "      <td>3</td>\n",
-       "      <td>5308</td>\n",
-       "      <td>135</td>\n",
-       "      <td>-38.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>39</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>70</td>\n",
-       "      <td>6</td>\n",
-       "      <td>5378</td>\n",
-       "      <td>141</td>\n",
-       "      <td>23.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>40</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>18722 rows × 7 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                  cases  deaths  cases_culm  deaths_culm  cases_diff  \\\n",
-       "geoId dateRep                                                          \n",
-       "AD    2020-04-01      6       4         376           12       -30.0   \n",
-       "      2020-04-02     14       2         390           14         8.0   \n",
-       "      2020-04-03     38       1         428           15        24.0   \n",
-       "      2020-04-04     11       1         439           16       -27.0   \n",
-       "      2020-04-05     27       1         466           17        16.0   \n",
-       "...                 ...     ...         ...          ...         ...   \n",
-       "ZW    2020-08-15     82       0        5072          128       -15.0   \n",
-       "      2020-08-16    104       2        5176          130        22.0   \n",
-       "      2020-08-17     85       2        5261          132       -19.0   \n",
-       "      2020-08-18     47       3        5308          135       -38.0   \n",
-       "      2020-08-19     70       6        5378          141        23.0   \n",
-       "\n",
-       "                  deaths_diff  since_threshold  \n",
-       "geoId dateRep                                   \n",
-       "AD    2020-04-01          2.0                0  \n",
-       "      2020-04-02         -2.0                1  \n",
-       "      2020-04-03         -1.0                2  \n",
-       "      2020-04-04          0.0                3  \n",
-       "      2020-04-05          0.0                4  \n",
-       "...                       ...              ...  \n",
-       "ZW    2020-08-15         -6.0               36  \n",
-       "      2020-08-16          2.0               37  \n",
-       "      2020-08-17          0.0               38  \n",
-       "      2020-08-18          1.0               39  \n",
-       "      2020-08-19          3.0               40  \n",
-       "\n",
-       "[18722 rows x 7 columns]"
-      ]
-     },
-     "execution_count": 593,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_since_threshold = data_by_date.merge(days_since_threshold, \n",
-    "    left_index=True, right_index=True)\n",
-    "data_since_threshold"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 594,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>since_threshold</th>\n",
-       "      <th>geoId</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td rowspan=\"5\" valign=\"top\">0</td>\n",
-       "      <td>AD</td>\n",
-       "      <td>2020-04-01</td>\n",
-       "      <td>6</td>\n",
-       "      <td>4</td>\n",
-       "      <td>376</td>\n",
-       "      <td>12</td>\n",
-       "      <td>-30.0</td>\n",
-       "      <td>2.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>AE</td>\n",
-       "      <td>2020-04-07</td>\n",
-       "      <td>262</td>\n",
-       "      <td>1</td>\n",
-       "      <td>2045</td>\n",
-       "      <td>11</td>\n",
-       "      <td>-16.0</td>\n",
-       "      <td>1.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>AF</td>\n",
-       "      <td>2020-04-08</td>\n",
-       "      <td>30</td>\n",
-       "      <td>4</td>\n",
-       "      <td>367</td>\n",
-       "      <td>11</td>\n",
-       "      <td>-8.0</td>\n",
-       "      <td>4.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>AL</td>\n",
-       "      <td>2020-03-31</td>\n",
-       "      <td>11</td>\n",
-       "      <td>2</td>\n",
-       "      <td>223</td>\n",
-       "      <td>12</td>\n",
-       "      <td>-4.0</td>\n",
-       "      <td>2.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>AM</td>\n",
-       "      <td>2020-04-10</td>\n",
-       "      <td>16</td>\n",
-       "      <td>1</td>\n",
-       "      <td>937</td>\n",
-       "      <td>11</td>\n",
-       "      <td>-24.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>206</td>\n",
-       "      <td>CN</td>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>70</td>\n",
-       "      <td>1</td>\n",
-       "      <td>89214</td>\n",
-       "      <td>4701</td>\n",
-       "      <td>-29.0</td>\n",
-       "      <td>-2.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>207</td>\n",
-       "      <td>CN</td>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>65</td>\n",
-       "      <td>2</td>\n",
-       "      <td>89279</td>\n",
-       "      <td>4703</td>\n",
-       "      <td>-5.0</td>\n",
-       "      <td>1.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>208</td>\n",
-       "      <td>CN</td>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>96</td>\n",
-       "      <td>0</td>\n",
-       "      <td>89375</td>\n",
-       "      <td>4703</td>\n",
-       "      <td>31.0</td>\n",
-       "      <td>-2.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>209</td>\n",
-       "      <td>CN</td>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>66</td>\n",
-       "      <td>0</td>\n",
-       "      <td>89441</td>\n",
-       "      <td>4703</td>\n",
-       "      <td>-30.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>210</td>\n",
-       "      <td>CN</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>53</td>\n",
-       "      <td>2</td>\n",
-       "      <td>89494</td>\n",
-       "      <td>4705</td>\n",
-       "      <td>-13.0</td>\n",
-       "      <td>2.0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>18722 rows × 7 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                         dateRep  cases  deaths  cases_culm  deaths_culm  \\\n",
-       "since_threshold geoId                                                      \n",
-       "0               AD    2020-04-01      6       4         376           12   \n",
-       "                AE    2020-04-07    262       1        2045           11   \n",
-       "                AF    2020-04-08     30       4         367           11   \n",
-       "                AL    2020-03-31     11       2         223           12   \n",
-       "                AM    2020-04-10     16       1         937           11   \n",
-       "...                          ...    ...     ...         ...          ...   \n",
-       "206             CN    2020-08-15     70       1       89214         4701   \n",
-       "207             CN    2020-08-16     65       2       89279         4703   \n",
-       "208             CN    2020-08-17     96       0       89375         4703   \n",
-       "209             CN    2020-08-18     66       0       89441         4703   \n",
-       "210             CN    2020-08-19     53       2       89494         4705   \n",
-       "\n",
-       "                       cases_diff  deaths_diff  \n",
-       "since_threshold geoId                           \n",
-       "0               AD          -30.0          2.0  \n",
-       "                AE          -16.0          1.0  \n",
-       "                AF           -8.0          4.0  \n",
-       "                AL           -4.0          2.0  \n",
-       "                AM          -24.0          0.0  \n",
-       "...                           ...          ...  \n",
-       "206             CN          -29.0         -2.0  \n",
-       "207             CN           -5.0          1.0  \n",
-       "208             CN           31.0         -2.0  \n",
-       "209             CN          -30.0          0.0  \n",
-       "210             CN          -13.0          2.0  \n",
-       "\n",
-       "[18722 rows x 7 columns]"
-      ]
-     },
-     "execution_count": 594,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_since_threshold = data_since_threshold.set_index('since_threshold', append=True\n",
-    "                              ).reorder_levels(['since_threshold', 'geoId', 'dateRep']\n",
-    "                                              ).reset_index('dateRep')\n",
-    "data_since_threshold.sort_index(inplace=True)\n",
-    "data_since_threshold"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 595,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>since_threshold</th>\n",
-       "      <th>geoId</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td rowspan=\"3\" valign=\"top\">0</td>\n",
-       "      <td>DE</td>\n",
-       "      <td>2020-03-16</td>\n",
-       "      <td>1043</td>\n",
-       "      <td>4</td>\n",
-       "      <td>4838</td>\n",
-       "      <td>12</td>\n",
-       "      <td>310.0</td>\n",
-       "      <td>1.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-02-26</td>\n",
-       "      <td>93</td>\n",
-       "      <td>5</td>\n",
-       "      <td>322</td>\n",
-       "      <td>11</td>\n",
-       "      <td>-4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-03-15</td>\n",
-       "      <td>478</td>\n",
-       "      <td>19</td>\n",
-       "      <td>2244</td>\n",
-       "      <td>29</td>\n",
-       "      <td>-6.0</td>\n",
-       "      <td>18.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td rowspan=\"2\" valign=\"top\">1</td>\n",
-       "      <td>DE</td>\n",
-       "      <td>2020-03-17</td>\n",
-       "      <td>1174</td>\n",
-       "      <td>1</td>\n",
-       "      <td>6012</td>\n",
-       "      <td>13</td>\n",
-       "      <td>131.0</td>\n",
-       "      <td>-3.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-02-27</td>\n",
-       "      <td>78</td>\n",
-       "      <td>1</td>\n",
-       "      <td>400</td>\n",
-       "      <td>12</td>\n",
-       "      <td>-15.0</td>\n",
-       "      <td>-4.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>171</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>574</td>\n",
-       "      <td>3</td>\n",
-       "      <td>252809</td>\n",
-       "      <td>35234</td>\n",
-       "      <td>52.0</td>\n",
-       "      <td>-3.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>172</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>629</td>\n",
-       "      <td>158</td>\n",
-       "      <td>253438</td>\n",
-       "      <td>35392</td>\n",
-       "      <td>55.0</td>\n",
-       "      <td>155.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>173</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>477</td>\n",
-       "      <td>4</td>\n",
-       "      <td>253915</td>\n",
-       "      <td>35396</td>\n",
-       "      <td>-152.0</td>\n",
-       "      <td>-154.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>174</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>320</td>\n",
-       "      <td>4</td>\n",
-       "      <td>254235</td>\n",
-       "      <td>35400</td>\n",
-       "      <td>-157.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>175</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>401</td>\n",
-       "      <td>5</td>\n",
-       "      <td>254636</td>\n",
-       "      <td>35405</td>\n",
-       "      <td>81.0</td>\n",
-       "      <td>1.0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>491 rows × 7 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                         dateRep  cases  deaths  cases_culm  deaths_culm  \\\n",
-       "since_threshold geoId                                                      \n",
-       "0               DE    2020-03-16   1043       4        4838           12   \n",
-       "                IT    2020-02-26     93       5         322           11   \n",
-       "                UK    2020-03-15    478      19        2244           29   \n",
-       "1               DE    2020-03-17   1174       1        6012           13   \n",
-       "                IT    2020-02-27     78       1         400           12   \n",
-       "...                          ...    ...     ...         ...          ...   \n",
-       "171             IT    2020-08-15    574       3      252809        35234   \n",
-       "172             IT    2020-08-16    629     158      253438        35392   \n",
-       "173             IT    2020-08-17    477       4      253915        35396   \n",
-       "174             IT    2020-08-18    320       4      254235        35400   \n",
-       "175             IT    2020-08-19    401       5      254636        35405   \n",
-       "\n",
-       "                       cases_diff  deaths_diff  \n",
-       "since_threshold geoId                           \n",
-       "0               DE          310.0          1.0  \n",
-       "                IT           -4.0          1.0  \n",
-       "                UK           -6.0         18.0  \n",
-       "1               DE          131.0         -3.0  \n",
-       "                IT          -15.0         -4.0  \n",
-       "...                           ...          ...  \n",
-       "171             IT           52.0         -3.0  \n",
-       "172             IT           55.0        155.0  \n",
-       "173             IT         -152.0       -154.0  \n",
-       "174             IT         -157.0          0.0  \n",
-       "175             IT           81.0          1.0  \n",
-       "\n",
-       "[491 rows x 7 columns]"
-      ]
-     },
-     "execution_count": 595,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT']), :]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 596,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>since_threshold</th>\n",
-       "      <th>geoId</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>154</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-11</td>\n",
-       "      <td>3632</td>\n",
-       "      <td>5</td>\n",
-       "      <td>326612</td>\n",
-       "      <td>28581</td>\n",
-       "      <td>-4986.0</td>\n",
-       "      <td>-68.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>155</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-12</td>\n",
-       "      <td>3172</td>\n",
-       "      <td>-2</td>\n",
-       "      <td>329784</td>\n",
-       "      <td>28579</td>\n",
-       "      <td>-460.0</td>\n",
-       "      <td>-7.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>156</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-13</td>\n",
-       "      <td>7550</td>\n",
-       "      <td>26</td>\n",
-       "      <td>337334</td>\n",
-       "      <td>28605</td>\n",
-       "      <td>4378.0</td>\n",
-       "      <td>28.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>157</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-14</td>\n",
-       "      <td>5479</td>\n",
-       "      <td>12</td>\n",
-       "      <td>342813</td>\n",
-       "      <td>28617</td>\n",
-       "      <td>-2071.0</td>\n",
-       "      <td>-14.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>158</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>342813</td>\n",
-       "      <td>28617</td>\n",
-       "      <td>-5479.0</td>\n",
-       "      <td>-12.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>159</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>342813</td>\n",
-       "      <td>28617</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>160</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>16269</td>\n",
-       "      <td>29</td>\n",
-       "      <td>359082</td>\n",
-       "      <td>28646</td>\n",
-       "      <td>16269.0</td>\n",
-       "      <td>29.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>161</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>5114</td>\n",
-       "      <td>24</td>\n",
-       "      <td>364196</td>\n",
-       "      <td>28670</td>\n",
-       "      <td>-11155.0</td>\n",
-       "      <td>-5.0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                         dateRep  cases  deaths  cases_culm  deaths_culm  \\\n",
-       "since_threshold geoId                                                      \n",
-       "154             ES    2020-08-11   3632       5      326612        28581   \n",
-       "155             ES    2020-08-12   3172      -2      329784        28579   \n",
-       "156             ES    2020-08-13   7550      26      337334        28605   \n",
-       "157             ES    2020-08-14   5479      12      342813        28617   \n",
-       "158             ES    2020-08-15      0       0      342813        28617   \n",
-       "159             ES    2020-08-16      0       0      342813        28617   \n",
-       "160             ES    2020-08-17  16269      29      359082        28646   \n",
-       "161             ES    2020-08-18   5114      24      364196        28670   \n",
-       "\n",
-       "                       cases_diff  deaths_diff  \n",
-       "since_threshold geoId                           \n",
-       "154             ES        -4986.0        -68.0  \n",
-       "155             ES         -460.0         -7.0  \n",
-       "156             ES         4378.0         28.0  \n",
-       "157             ES        -2071.0        -14.0  \n",
-       "158             ES        -5479.0        -12.0  \n",
-       "159             ES            0.0          0.0  \n",
-       "160             ES        16269.0         29.0  \n",
-       "161             ES       -11155.0         -5.0  "
-      ]
-     },
-     "execution_count": 596,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_since_threshold.loc[(slice(None), ['ES']), :].tail(8)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 597,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f03fd2ebe90>"
-      ]
-     },
-     "execution_count": 597,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT']), ['deaths_culm']].unstack().plot(logy=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 598,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# deaths = data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT', 'IE']), ['deaths_culm']].unstack().xs('deaths_culm', axis=1, drop_level=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 599,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "deaths = data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['deaths_culm']].unstack().sort_index().xs('deaths_culm', axis=1, drop_level=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 600,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "cases = data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['cases_culm']].unstack().sort_index().xs('cases_culm', axis=1, drop_level=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 601,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "COUNTRIES_AMERICAS_DEAD = list(set(deaths.columns) & set(COUNTRIES_AMERICAS))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 602,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "      <th>countriesAndTerritories</th>\n",
-       "      <th>popData2019</th>\n",
-       "      <th>continentExp</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>since_threshold</th>\n",
-       "      <th>geoId</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>0</td>\n",
-       "      <td>AD</td>\n",
-       "      <td>2020-04-01</td>\n",
-       "      <td>6</td>\n",
-       "      <td>4</td>\n",
-       "      <td>376</td>\n",
-       "      <td>12</td>\n",
-       "      <td>-30.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>Andorra</td>\n",
-       "      <td>76177</td>\n",
-       "      <td>Europe</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>1</td>\n",
-       "      <td>AD</td>\n",
-       "      <td>2020-04-02</td>\n",
-       "      <td>14</td>\n",
-       "      <td>2</td>\n",
-       "      <td>390</td>\n",
-       "      <td>14</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>-2.0</td>\n",
-       "      <td>Andorra</td>\n",
-       "      <td>76177</td>\n",
-       "      <td>Europe</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2</td>\n",
-       "      <td>AD</td>\n",
-       "      <td>2020-04-03</td>\n",
-       "      <td>38</td>\n",
-       "      <td>1</td>\n",
-       "      <td>428</td>\n",
-       "      <td>15</td>\n",
-       "      <td>24.0</td>\n",
-       "      <td>-1.0</td>\n",
-       "      <td>Andorra</td>\n",
-       "      <td>76177</td>\n",
-       "      <td>Europe</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>3</td>\n",
-       "      <td>AD</td>\n",
-       "      <td>2020-04-04</td>\n",
-       "      <td>11</td>\n",
-       "      <td>1</td>\n",
-       "      <td>439</td>\n",
-       "      <td>16</td>\n",
-       "      <td>-27.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>Andorra</td>\n",
-       "      <td>76177</td>\n",
-       "      <td>Europe</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>4</td>\n",
-       "      <td>AD</td>\n",
-       "      <td>2020-04-05</td>\n",
-       "      <td>27</td>\n",
-       "      <td>1</td>\n",
-       "      <td>466</td>\n",
-       "      <td>17</td>\n",
-       "      <td>16.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>Andorra</td>\n",
-       "      <td>76177</td>\n",
-       "      <td>Europe</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>36</td>\n",
-       "      <td>ZW</td>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>82</td>\n",
-       "      <td>0</td>\n",
-       "      <td>5072</td>\n",
-       "      <td>128</td>\n",
-       "      <td>-15.0</td>\n",
-       "      <td>-6.0</td>\n",
-       "      <td>Zimbabwe</td>\n",
-       "      <td>14645473</td>\n",
-       "      <td>Africa</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>37</td>\n",
-       "      <td>ZW</td>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>104</td>\n",
-       "      <td>2</td>\n",
-       "      <td>5176</td>\n",
-       "      <td>130</td>\n",
-       "      <td>22.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>Zimbabwe</td>\n",
-       "      <td>14645473</td>\n",
-       "      <td>Africa</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>38</td>\n",
-       "      <td>ZW</td>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>85</td>\n",
-       "      <td>2</td>\n",
-       "      <td>5261</td>\n",
-       "      <td>132</td>\n",
-       "      <td>-19.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>Zimbabwe</td>\n",
-       "      <td>14645473</td>\n",
-       "      <td>Africa</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>39</td>\n",
-       "      <td>ZW</td>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>47</td>\n",
-       "      <td>3</td>\n",
-       "      <td>5308</td>\n",
-       "      <td>135</td>\n",
-       "      <td>-38.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>Zimbabwe</td>\n",
-       "      <td>14645473</td>\n",
-       "      <td>Africa</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>40</td>\n",
-       "      <td>ZW</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>70</td>\n",
-       "      <td>6</td>\n",
-       "      <td>5378</td>\n",
-       "      <td>141</td>\n",
-       "      <td>23.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>Zimbabwe</td>\n",
-       "      <td>14645473</td>\n",
-       "      <td>Africa</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>18722 rows × 10 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                         dateRep  cases  deaths  cases_culm  deaths_culm  \\\n",
-       "since_threshold geoId                                                      \n",
-       "0               AD    2020-04-01      6       4         376           12   \n",
-       "1               AD    2020-04-02     14       2         390           14   \n",
-       "2               AD    2020-04-03     38       1         428           15   \n",
-       "3               AD    2020-04-04     11       1         439           16   \n",
-       "4               AD    2020-04-05     27       1         466           17   \n",
-       "...                          ...    ...     ...         ...          ...   \n",
-       "36              ZW    2020-08-15     82       0        5072          128   \n",
-       "37              ZW    2020-08-16    104       2        5176          130   \n",
-       "38              ZW    2020-08-17     85       2        5261          132   \n",
-       "39              ZW    2020-08-18     47       3        5308          135   \n",
-       "40              ZW    2020-08-19     70       6        5378          141   \n",
-       "\n",
-       "                       cases_diff  deaths_diff countriesAndTerritories  \\\n",
-       "since_threshold geoId                                                    \n",
-       "0               AD          -30.0          2.0                 Andorra   \n",
-       "1               AD            8.0         -2.0                 Andorra   \n",
-       "2               AD           24.0         -1.0                 Andorra   \n",
-       "3               AD          -27.0          0.0                 Andorra   \n",
-       "4               AD           16.0          0.0                 Andorra   \n",
-       "...                           ...          ...                     ...   \n",
-       "36              ZW          -15.0         -6.0                Zimbabwe   \n",
-       "37              ZW           22.0          2.0                Zimbabwe   \n",
-       "38              ZW          -19.0          0.0                Zimbabwe   \n",
-       "39              ZW          -38.0          1.0                Zimbabwe   \n",
-       "40              ZW           23.0          3.0                Zimbabwe   \n",
-       "\n",
-       "                       popData2019 continentExp  \n",
-       "since_threshold geoId                            \n",
-       "0               AD           76177       Europe  \n",
-       "1               AD           76177       Europe  \n",
-       "2               AD           76177       Europe  \n",
-       "3               AD           76177       Europe  \n",
-       "4               AD           76177       Europe  \n",
-       "...                            ...          ...  \n",
-       "36              ZW        14645473       Africa  \n",
-       "37              ZW        14645473       Africa  \n",
-       "38              ZW        14645473       Africa  \n",
-       "39              ZW        14645473       Africa  \n",
-       "40              ZW        14645473       Africa  \n",
-       "\n",
-       "[18722 rows x 10 columns]"
-      ]
-     },
-     "execution_count": 602,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_since_threshold.reset_index().merge(countries, on='geoId').set_index(['since_threshold', 'geoId'])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 603,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "data_since_threshold.reset_index().merge(countries, on='geoId').set_index(['since_threshold', 'geoId']).sort_index(inplace=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 604,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "      <th>countriesAndTerritories</th>\n",
-       "      <th>popData2019</th>\n",
-       "      <th>continentExp</th>\n",
-       "      <th>cases_culm_pc</th>\n",
-       "      <th>deaths_culm_pc</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>since_threshold</th>\n",
-       "      <th>geoId</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>0</td>\n",
-       "      <td>AD</td>\n",
-       "      <td>2020-04-01</td>\n",
-       "      <td>6</td>\n",
-       "      <td>4</td>\n",
-       "      <td>376</td>\n",
-       "      <td>12</td>\n",
-       "      <td>-30.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>Andorra</td>\n",
-       "      <td>76177</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>0.004936</td>\n",
-       "      <td>0.000158</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>1</td>\n",
-       "      <td>AD</td>\n",
-       "      <td>2020-04-02</td>\n",
-       "      <td>14</td>\n",
-       "      <td>2</td>\n",
-       "      <td>390</td>\n",
-       "      <td>14</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>-2.0</td>\n",
-       "      <td>Andorra</td>\n",
-       "      <td>76177</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>0.005120</td>\n",
-       "      <td>0.000184</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2</td>\n",
-       "      <td>AD</td>\n",
-       "      <td>2020-04-03</td>\n",
-       "      <td>38</td>\n",
-       "      <td>1</td>\n",
-       "      <td>428</td>\n",
-       "      <td>15</td>\n",
-       "      <td>24.0</td>\n",
-       "      <td>-1.0</td>\n",
-       "      <td>Andorra</td>\n",
-       "      <td>76177</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>0.005618</td>\n",
-       "      <td>0.000197</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>3</td>\n",
-       "      <td>AD</td>\n",
-       "      <td>2020-04-04</td>\n",
-       "      <td>11</td>\n",
-       "      <td>1</td>\n",
-       "      <td>439</td>\n",
-       "      <td>16</td>\n",
-       "      <td>-27.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>Andorra</td>\n",
-       "      <td>76177</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>0.005763</td>\n",
-       "      <td>0.000210</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>4</td>\n",
-       "      <td>AD</td>\n",
-       "      <td>2020-04-05</td>\n",
-       "      <td>27</td>\n",
-       "      <td>1</td>\n",
-       "      <td>466</td>\n",
-       "      <td>17</td>\n",
-       "      <td>16.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>Andorra</td>\n",
-       "      <td>76177</td>\n",
-       "      <td>Europe</td>\n",
-       "      <td>0.006117</td>\n",
-       "      <td>0.000223</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>36</td>\n",
-       "      <td>ZW</td>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>82</td>\n",
-       "      <td>0</td>\n",
-       "      <td>5072</td>\n",
-       "      <td>128</td>\n",
-       "      <td>-15.0</td>\n",
-       "      <td>-6.0</td>\n",
-       "      <td>Zimbabwe</td>\n",
-       "      <td>14645473</td>\n",
-       "      <td>Africa</td>\n",
-       "      <td>0.000346</td>\n",
-       "      <td>0.000009</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>37</td>\n",
-       "      <td>ZW</td>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>104</td>\n",
-       "      <td>2</td>\n",
-       "      <td>5176</td>\n",
-       "      <td>130</td>\n",
-       "      <td>22.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>Zimbabwe</td>\n",
-       "      <td>14645473</td>\n",
-       "      <td>Africa</td>\n",
-       "      <td>0.000353</td>\n",
-       "      <td>0.000009</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>38</td>\n",
-       "      <td>ZW</td>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>85</td>\n",
-       "      <td>2</td>\n",
-       "      <td>5261</td>\n",
-       "      <td>132</td>\n",
-       "      <td>-19.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>Zimbabwe</td>\n",
-       "      <td>14645473</td>\n",
-       "      <td>Africa</td>\n",
-       "      <td>0.000359</td>\n",
-       "      <td>0.000009</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>39</td>\n",
-       "      <td>ZW</td>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>47</td>\n",
-       "      <td>3</td>\n",
-       "      <td>5308</td>\n",
-       "      <td>135</td>\n",
-       "      <td>-38.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>Zimbabwe</td>\n",
-       "      <td>14645473</td>\n",
-       "      <td>Africa</td>\n",
-       "      <td>0.000362</td>\n",
-       "      <td>0.000009</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>40</td>\n",
-       "      <td>ZW</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>70</td>\n",
-       "      <td>6</td>\n",
-       "      <td>5378</td>\n",
-       "      <td>141</td>\n",
-       "      <td>23.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>Zimbabwe</td>\n",
-       "      <td>14645473</td>\n",
-       "      <td>Africa</td>\n",
-       "      <td>0.000367</td>\n",
-       "      <td>0.000010</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>18722 rows × 12 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                         dateRep  cases  deaths  cases_culm  deaths_culm  \\\n",
-       "since_threshold geoId                                                      \n",
-       "0               AD    2020-04-01      6       4         376           12   \n",
-       "1               AD    2020-04-02     14       2         390           14   \n",
-       "2               AD    2020-04-03     38       1         428           15   \n",
-       "3               AD    2020-04-04     11       1         439           16   \n",
-       "4               AD    2020-04-05     27       1         466           17   \n",
-       "...                          ...    ...     ...         ...          ...   \n",
-       "36              ZW    2020-08-15     82       0        5072          128   \n",
-       "37              ZW    2020-08-16    104       2        5176          130   \n",
-       "38              ZW    2020-08-17     85       2        5261          132   \n",
-       "39              ZW    2020-08-18     47       3        5308          135   \n",
-       "40              ZW    2020-08-19     70       6        5378          141   \n",
-       "\n",
-       "                       cases_diff  deaths_diff countriesAndTerritories  \\\n",
-       "since_threshold geoId                                                    \n",
-       "0               AD          -30.0          2.0                 Andorra   \n",
-       "1               AD            8.0         -2.0                 Andorra   \n",
-       "2               AD           24.0         -1.0                 Andorra   \n",
-       "3               AD          -27.0          0.0                 Andorra   \n",
-       "4               AD           16.0          0.0                 Andorra   \n",
-       "...                           ...          ...                     ...   \n",
-       "36              ZW          -15.0         -6.0                Zimbabwe   \n",
-       "37              ZW           22.0          2.0                Zimbabwe   \n",
-       "38              ZW          -19.0          0.0                Zimbabwe   \n",
-       "39              ZW          -38.0          1.0                Zimbabwe   \n",
-       "40              ZW           23.0          3.0                Zimbabwe   \n",
-       "\n",
-       "                       popData2019 continentExp  cases_culm_pc  deaths_culm_pc  \n",
-       "since_threshold geoId                                                           \n",
-       "0               AD           76177       Europe       0.004936        0.000158  \n",
-       "1               AD           76177       Europe       0.005120        0.000184  \n",
-       "2               AD           76177       Europe       0.005618        0.000197  \n",
-       "3               AD           76177       Europe       0.005763        0.000210  \n",
-       "4               AD           76177       Europe       0.006117        0.000223  \n",
-       "...                            ...          ...            ...             ...  \n",
-       "36              ZW        14645473       Africa       0.000346        0.000009  \n",
-       "37              ZW        14645473       Africa       0.000353        0.000009  \n",
-       "38              ZW        14645473       Africa       0.000359        0.000009  \n",
-       "39              ZW        14645473       Africa       0.000362        0.000009  \n",
-       "40              ZW        14645473       Africa       0.000367        0.000010  \n",
-       "\n",
-       "[18722 rows x 12 columns]"
-      ]
-     },
-     "execution_count": 604,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_since_threshold_per_capita = data_since_threshold.reset_index().merge(countries, on='geoId').set_index(['since_threshold', 'geoId'])\n",
-    "data_since_threshold_per_capita['cases_culm_pc'] = data_since_threshold_per_capita.cases_culm / data_since_threshold_per_capita.popData2019\n",
-    "data_since_threshold_per_capita['deaths_culm_pc'] = data_since_threshold_per_capita.deaths_culm / data_since_threshold_per_capita.popData2019\n",
-    "data_since_threshold_per_capita"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 605,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "deaths_pc = data_since_threshold_per_capita.loc[(slice(None), ['UK', 'DE', 'IT', 'IE']), ['deaths_culm_pc']].unstack().sort_index().xs('deaths_culm_pc', axis=1, drop_level=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 606,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Int64Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,\n",
-       "            ...\n",
-       "            166, 167, 168, 169, 170, 171, 172, 173, 174, 175],\n",
-       "           dtype='int64', name='since_threshold', length=176)"
-      ]
-     },
-     "execution_count": 606,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "deaths_pc.index"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 607,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "deaths_pc = data_since_threshold_per_capita.loc[(slice(None), COUNTRIES_ALL), ['deaths_culm_pc']].unstack().xs('deaths_culm_pc', axis=1, drop_level=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 608,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f03f74c7290>"
-      ]
-     },
-     "execution_count": 608,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "deaths[COUNTRIES_CORE].plot()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 609,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f03f733d810>"
-      ]
-     },
-     "execution_count": 609,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "deaths[COUNTRIES_FRIENDS].plot()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 610,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths[COUNTRIES_FRIENDS].plot(figsize=(10, 6), title=\"Total deaths, linear\")\n",
-    "ax.set_xlabel(f\"Days since {DEATH_COUNT_THRESHOLD} deaths\")\n",
-    "for c in COUNTRIES_FRIENDS:\n",
-    "    lvi = deaths[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = deaths[c][lvi], s = f\"{c}: {deaths[c][lvi]:.0f}\")\n",
-    "# plt.savefig('covid_deaths_total_linear.png')    "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 611,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths[COUNTRIES_CORE].plot(figsize=(10, 6), title=\"Total deaths, linear\")\n",
-    "ax.set_xlabel(f\"Days since {DEATH_COUNT_THRESHOLD} deaths\")\n",
-    "for c in COUNTRIES_CORE:\n",
-    "    lvi = deaths[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = deaths[c][lvi], s = f\"{c}: {deaths[c][lvi]:.0f}\")\n",
-    "plt.savefig('covid_deaths_total_linear.png')    "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 612,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "deaths_prime = deaths[COUNTRIES_CORE].copy()\n",
-    "deaths_prime.loc[73:, 'ES'] = np.NaN\n",
-    "# deaths_prime['ES'][70:]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 613,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths_prime[COUNTRIES_CORE].plot(figsize=(10, 6), title=\"Total deaths, linear\")\n",
-    "for c in COUNTRIES_CORE:\n",
-    "    lvi = deaths_prime[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = deaths_prime[c][lvi], s = f\"{c}: {deaths_prime[c][lvi]:.0f}\")\n",
-    "# plt.savefig('covid_deaths_total_linear.png')    "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 614,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = cases[COUNTRIES_CORE].plot(figsize=(10, 6), title=\"Total cases, linear\")\n",
-    "for c in COUNTRIES_CORE:\n",
-    "    lvi = cases[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = cases[c][lvi], s = c)\n",
-    "plt.savefig('covid_cases_total_linear.png')    "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 615,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths[COUNTRIES_AMERICAS_DEAD].plot(figsize=(10, 6), title=\"Total deaths, linear\")\n",
-    "for c in COUNTRIES_AMERICAS_DEAD:\n",
-    "    lvi = deaths[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)\n",
-    "# plt.savefig('covid_deaths_total_linear.png')    "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 616,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths[COUNTRIES_CORE + ['BR', 'MX']].plot(figsize=(10, 6), title=\"Total deaths, linear\")\n",
-    "for c in COUNTRIES_CORE + ['BR', 'MX']:\n",
-    "    lvi = deaths[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)\n",
-    "# plt.savefig('covid_deaths_total_linear.png')    "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 617,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths[COUNTRIES_NORDIC].plot(figsize=(10, 6), title=\"Total deaths, linear\")\n",
-    "for c in COUNTRIES_NORDIC:\n",
-    "    lvi = deaths[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)\n",
-    "# plt.savefig('covid_deaths_total_linear.png')    "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 618,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths[COUNTRIES_OF_INTEREST].plot(figsize=(10, 6), title=\"Total deaths, linear\")\n",
-    "for c in COUNTRIES_OF_INTEREST:\n",
-    "    lvi = deaths[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)\n",
-    "plt.savefig('covid_deaths_total_linear_of_interest.png') "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 619,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths[COUNTRIES_CORE].plot(logy=True, figsize=(10, 6), title=\"Total deaths, log\")\n",
-    "for c in COUNTRIES_CORE:\n",
-    "    lvi = deaths[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)\n",
-    "\n",
-    "plt.savefig('covid_deaths_total_log.png')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 620,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ylim = (5*10**3, 5*10**4)\n",
-    "ax = deaths[COUNTRIES_CORE].plot(logy=True, figsize=(10, 6), ylim=ylim, title=\"Total deaths, log\")\n",
-    "for c in COUNTRIES_CORE:\n",
-    "    lvi = deaths[c].last_valid_index()\n",
-    "    if ylim[0] < deaths[c][lvi] < ylim[1]:\n",
-    "        ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)\n",
-    "\n",
-    "# plt.savefig('covid_deaths_total_log.png')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 621,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths[COUNTRIES_FRIENDS].plot(logy=True, figsize=(10, 6), title=\"Total deaths, log\")\n",
-    "for c in COUNTRIES_FRIENDS:\n",
-    "    lvi = deaths[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)\n",
-    "\n",
-    "# plt.savefig('covid_deaths_total_log.png')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 622,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths[COUNTRIES_NORDIC].plot(logy=True, figsize=(10, 6), title=\"Total deaths, log\")\n",
-    "for c in COUNTRIES_NORDIC:\n",
-    "    lvi = deaths[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)\n",
-    "\n",
-    "# plt.savefig('covid_deaths_total_log.png')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 623,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths[COUNTRIES_OF_INTEREST].plot(logy=True, figsize=(10, 6), title=\"Total deaths, log\")\n",
-    "for c in COUNTRIES_OF_INTEREST:\n",
-    "    lvi = deaths[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)\n",
-    "\n",
-    "plt.savefig('covid_deaths_total_log.png')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 624,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths_pc.plot(figsize=(10, 6), title=\"Deaths per capita, linear\")\n",
-    "for c in deaths_pc.columns:\n",
-    "    lvi = deaths_pc[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = deaths_pc[c][lvi], s = c)\n",
-    "plt.savefig('covid_deaths_per_capita_linear.png')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 625,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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E3MGc8P6iaIrzirVr1+7v7ri4vDekVMIq0QPJHpUmuiHZWyhLxxzR5WzZonxOiElr169t+Aubxw9GAAwfeJx0h/vF5/lV+a6IrHy5tyBuXFxchiCl5OGHH2bNmjVDjvl8PgKBAMFgsCQdrqysrIyKior9cAe7xurVq5k1a1Z+P51Os27duhKHtNu2bUPTNJLJJOXl5VRVVdHX18e2bdsIhUKcffbZ/OIXv+Cwww7bH7dQwuD7ARBCLJVSDj80uIuMyVic7hSny5jFtpXIirdDrANibYX8wHZHePWqOokesIb+2s3jDYM/At4ytXnKINTg7AfVaFLxMe+gzRN0Nn+pIDN8rihycXkfsHLlStasWcNHPvIRpk+fXiK6dF3f390bE5imyYUXXsimTZuIx+N84hOfwOfzsXLlSqqqqmhsbMwLOCklUkrq6+upra3d313fbcakQHNx2efYFgx0OYKrA2LtaisRYh1qs82h5/srIFQHwWqomARNcyFQBcGq4dNAJRjefX+fLi4uY4JkMslTTz1FY2Mjxx13HFrOPs4lj23brF27ll//+tfU19fz5ptvDhk5s22bTZs2MWvWLLxeL7Ztl6wC3d8IIeLAUcD9TtFEoN/ZuqSUx490rivQXP61sW1HcLUNL7hyQmygc/ipxGC1GtUKN0DdLAjVQ7gRwvWF8lC9GsVycXFxGSV/+9vfSCQSXHjhhe8rcfa9732PBx98EF3X0TSNu+++m69//eu0tbXlXWFMnTqV3//+97t9rS1btlBbW5tfvTkctm0jpcyHidI0rSTI+lhASvk2MBdACPG/wBNSyp0+oDEp0Fw3Gy67hG1Dz3rYvhp6W6Bvk0p7N0Hf5mGmGQWU1RZEVsPBBaEVbizkQ/XuKJeLi8seZ9OmTSxdupSjjjqKpqamndZvb2/n+uuv54033sDn89Hc3MxPfvITzj77bFasWLEPeqx45ZVXeOKJJ3jzzTfx+Xx0dXXlR6sWLVo04qrM90okEqGvr4/6+no8Hs8QtxyNjY1UVVVRUVHB8uXLiUQiebu194srjR0xJgWaa4PmMiKWCV3vQttb0LZMpe1vK2P6HP4KqJwE9QfCjFNUPtykhFe4QYmzQcu9XVxcXHYH27ZJJBLE43Hi8TixWGzYfDweJ5PJUF5ezjHHHLPTdqWUnHXWWVx66aU8/PDDACxbtoyOjo69fEdDaWtro6amBp/PB0BNTc1utWcYxpDIAaZpEgwGAaisrCQUCrF27VpmzJhREhqqmObmZhKJBLFYjI6ODqLRKJMnT96tvo0FxqRAc3EBwMxA52rY5gixtregY4VyBwHKQL7hEJh7ITTOgfrZUNkMgbG/msnFxeX9gWVZJUIrtw0nvIbziuDz+QiFQoRCIZqamvL5WbNm5YXOjnjuuefweDxcffXV+bK5c+fS0tKyJ29zVJx44omcc845+Hw+wuEwlZWV3HfffQB88pOfpKWlBZ/PRzAY5OMf/zj33HMPHs/IP4Z1Xcfj8RCNRolEIpimSX9/P3V1dcRiMQDq6+vJZrOsW7duh30LBoMEg0Gqqqp4++23XYHm4rJHiXXA5n/Apldgy6vQsUo5MQXwRZQIO/xzKm2cA9VTlRsHl32O1ddH8u0V2PEY0jSRmaxKzSyYJr7p0yk76qj93c0PJLZtY9s2lmXl8zk7Hdspy+WllIXjto0tJdI5LgfnpVTHh9t2cM6w5YBtFx9XzoalE8UgJ3Py+86WLxuU5oXRcOcWl5dc3yZrmmSzWTKZTCHvpFknLqRpDe/mRtd1PIaBoesYuk5VeXk+r+dSTSuZaktHY6SjUbqkpMVxrTG4f4PLnlm8mIDHw713311Sr6u7m96eHu65886S+y7JFz2nwfkdHZO5aAX5fwvPzuPxcPXll/PuunU8//LLfOLMMymPRDhu4UKeSCT4xg03YFkWd/7qV1x+8cXMm3tovpWPnXACVjRaiPAATKqtZcuWLWyx1f+BhooKjFQKmclgJxLIykrGjx/Pxo0bicViQyIBWJZFIpEgHA4DavHFzoTvY489xtlnn83q1auZOXMmLS0tzJo1ixkzZpDJZJg/f/5OxeW+wBVoLvsPM6OE2NpnYN3fYPsqVe4Jwvj5cNS1BTFWObngBdxl1Ejbxk4kkZk0MpNBplVqpzMlZXYmg0xn1H4mPbTMMsE0sWJxksvfIrNu/U6vHTntNOr/498xKiv3wZ2OHiklpvMSHk7IDFe2r+tYmQzZzi4yPd3Y2Sy2EEhNU6nQsDWBFAJb04akHxgXK1Iiil70Qg4dvSqpXvRc8vnBz8ppQzhtCykxpESz7fx+Lp+/pgQLiQVkJIh8+KXSPIxwbCd109u2kYlGGVi+vOQ+U9EoMpUi7ZQXM/hZlOwXtS+KygQ76FNRmSYlB2cyHDxxIta2Nl7bsB7NMPC3tqKl05StfgeAqcEgqXXriAQC+bbsI44gs3lzSZMaMAkKn0V/P9n+fhoB+vqgqQmEYPLkyXR3d7Nq1ar8ueXl5TQ2NtLe3s6mTZsQQqDrOs3NzUUicOi9P/TggyxY8BEefuhBbvrOd8C2mDJlCsveXIJlWZxw4sn87uGHuPCCC0rPH9yQbUJ/66BQW3uOMSnQ3EUC/8L0txYE2Ya/K9sxzQMTPwTH3wTNC5Ugc23EAEdgxeNY0Rh2LFpIY/HS/WgMKxbFjsawYjHsaFSlsdjuf2kYBsIwELqOCATwHziL8tNOJzB3LkZ1lTru8SI8qh6aRu+iB+m66y4GXnmF6s99DpnJYG7fjtXbg7RH7o8E9aITgqwQZEClQpARxXl13AJsBLYAC4ENWAJU9EiBdPJZITCFIIvAFKUv672NJtWLUJMSx69/Pq+hXp65vCYlwpbIaBTNMvGFw3hqa9GEKNQRQrUB6Ll8/rhAE8V1VLkQAoFEw0ZDIoSNJm00IRFOmSYcAYJEE7mXs51/kWu5vFAvIpGrJ22EyNWTTj0Q6pNRwQtQ1xO5NqQsOsd2PjknEEORcFDtqf8vtpQM4GHA1olLlcakh7htMCA9xG0PcWmQkEa+JYraKRNZQlqWMpElrGUoI0tYzxASagtrGYJk0UTxi13m+1RchnQuURQPUwyuA4NEQsm4ViGVw12jUG9GJsp3/9bG1c1GSXlLd5rfeZNcOfnVknIx7HWcvohc0aBYnvm+FJ9XdMx5nO92ZsiYJnc8tYiUabOxJ8uZB4bYHu/nuHGreW5lgstmvkgqa/HAC+384LhqDmnozbf5TvAi/NUjhWYbKgYB6Hg73+f5TQaQLarUCR2dTCsDyoqK+99VTiyGIT6Q4OWXnue53/2CMy77N2666izo3KZMZ9rfRgeOmN3M1jVLoePgEfrqEN0O/71gx3V2gzEp0NxFAv9CWCZsfgXWPg1r/6ZsygAi4+Hgc2HqCXDA0eAL799+7mVkNovZ24vV24vV3Y3Z3YPV24PV1z9EUJXsx+M7FVhaWRlaJIIeDqNFwngaGtCnT0MLqX09FEL4/AivB83nQ/h8CK8X4fWNrmwnI5dSSlKplLLJ6e8nFouRmHcYAzd9h57nniP17GKyHg+m34/l92MZuhrtcbZc3tQ0srquRoF2gm5ZeGwb3XaEhi2dvCxsOOJHSsK2jeGcYxRtmm0XBJMs1BfF7eTEiFRiRMNGEzY6Et2RhTo2Gha6kGjSQtNsdCw0YSOERGiOsBGOMBG5/VzeLhzXJJ66GnzTJmOEU2DFnZik2dI4pfkYpdlBMU3N0nzu3DEas9RCMECAAYIkCDBAgCQBEs6WxE8SHxm8Sjyinq2Oic4AQVJUkiJIiqBI4RdpgiKNnzQ+sviEiUdYpZJNOntmbiQt/0+uQlEynJjZNYqnCfMleT0kC9dxEJqW780J4yXfyqS498U1XDFfuY94Y2uWRFaCzGKkNg3pmripl4sO8XD/2UGQYNqSxv8X48hxOk9cEOTHr6RZud3mnjOVW4xFy7M8uCLLkxcEh3Z++knKqbYQJLQuhGghowfwejSOmuHjre4EjZVhbvhrnJbtGcq+tZGMaXPRMdOZc+xxlIQa8wQQgQpA8J9/28aqjqTT4V19okNPiCXSTKv2ceV8ZYM8dVw1mazFuq1d+DwGtpSUlwV4/u8vc/IJxzN97lFUVdfw5oYuqirrQDMgMo5UKsVry9/lf269Wb2nhr2cUxA04fTbS0Op/efFJTWllKFB+58Z7V2OSYHm8j7HMqHlRVj1J1j9Z0h0qVGySR+GQy9Uoqx2xvt2KsaKxzE7Osi2t2P19qkRrP6oM4LljGZF+9VoVjSKFY1i94/wcw7QwmFHXCmR5WlqQp8xo0R06eFIPtUj4cI5oZAatdpNstksqVQqvyV6e/PG0IlEQtniDNqy2SwDAwPEYrEhK7FyeJqa8E2ahM/vx+f3E/R60R0bHU3T0DQtn/d6vfh8vvzm9/tL9nNlXq8XQ2ZVKKzswKA04YTMShbli9JsUk2tW8VbthAQviQY/DDiZ2+LHKE7YbL6YOumorBaxqBQWk65N1QUZssohNfSDGfzqH3d47RtFI4VxxFFKsFnDrp/M63c1JgZNcIgzVIxUSxcZJGQyZfLohiwKeczSGFnBtAc9zc6kggJIiR2//kNHoTSfY6d6uCg4FAQDhQdU/9Iww+GF6l5sTUvUhhYwkBKZTuXt9uzbCxnX1oWlm1jWza2bWFbys7Psi1syy6ymRODuinyuk06fZr5kaMxPF4QAoHgsZsTXP+rF7jlzu34vQbNddX85MqPseY39zL+9my+//991fGc99FZlPl/xIqBKpLzLifg9/LM6+sY17gYqiLw0Uv44gKb+VffycvVZzB7cgPfvPt2Fv/4izCuetCzETD/MuVYG5gHBP4rxKotuVExZcT/4rPLSCQSnHbaaaxYsYK2tjaOOeYYHhcnccYZZxQ+n9WroWKiyvuiYOy5vychMlTV1DD74MIqz0wsRiicYdq0adi2zapVq7j/93/mK1/5CoTrOf/Ci3noT3/l2muvZf3GTcxdcCJr167l3HPP5ZAPHbvzi3o7Yc6lgwovHrbqe8EVaC57BsuElhdg5R/hnSdUqCNPmfr1deCZMPW498UombQsMps3k9m4kWx7O2Z7hxJj2zvyeTsx/ItE+HxKREXK0cNh9JpqvJMno0ci6FVVGNVV6FXVGFWV6NXV6JWV6JEIYi+FdMlkMvT29tLX10cikWBgYGDYNJFI7NDzdiAQwOPxYBhGyeb1eqmoqCAcDg/ZgsEgXkeMlWBbKv5oOgbpaFGc0m5n64VotzqWF1eDBFg2setCKR8WK6h82+lFm+FTIbd0X0HsGD5H8AwSPzlxtCPhtKNjaIV4q2bKiVVqFASUpilxYyYhHVcmAOmYSjMDTlmscCwzoCJgFJflVjnvSfLPzkdJUPqRtlzgeWfUBH+5Ot9bhvQEePPtdzANL5GaBoxgOZ5AGH+wDH+gDH+wDF8giJYTkZpeeDZa8TMdlHeeu9QMTDSyJpiZLNl0mmw6RTadIjUQJxmNkoz2k4z1k4xGScSipOIxMskk2VSKTCpBJplE2qP7P6YbBp5AEK8/gDcQwOP35/Nef1DtBwJFxwND93NlgQC6MdS8own43WeGXjt7xa+G7dNA6vtsi0lmXPMARx55JB6Ph09fcT0vvvgij/UfyNlnn82DDz7ItT/8IUcccQSXX/NvTD73Rsx4HKu3l+y2NrLbtpJta6PmMC8jjWm/8847WJZFdXU1iaLvxcbGRm655RZ+8IMflAq0Ir5z+lB3GbuDijIwcpuappFKpXjhhRd45513EEJgWRZCCK655hplg7ZsWUFcPv74iH3fV7gCzeW9Y2Vh4/POSNkT6kXrDcH0k2H2J2Dq8erLeQxj9feTeOMNBl57neRbb5FeuxaZTBYqGAZGbS2eujq1MnHhAjz19Rh19Rj1dRjV1eiRCFokgjaKJfPvBSklyWSSaDQ6ZEun01iWNWR0K5lM5pepF2MYBsFgkLKyMoLBINXV1fl8IBDA7/fj9/sJBAKEw2FCoVCpyMomVazRZJ+T9kKqE5LvQmcUWh3hlY4WCbEYpJz97MCOb9YbUuGwfOWFeKSheuflHnRikgbzL3slHAKFfD4tqmsE9t4Ck2xSOUPu26JGiuPbnefSU4jLmk8fPqIAACAASURBVMzFZ+1VQuq9IjQnPmsIfLk4rSGomDC0TPfsWEDlBJbucwSpd5h4r6HCc9yDz+/dNWt4YslDnHfeeRw4jE+rwdi2RSoWIxHtJxntJxGNkoh25PMq7VNiK9pPKhbLrwrdER6fn0AkQiBcjj8UIlJdWxBPeeHkx+uIL0/A2fcH8AaC+f3hBNVY4C+/+Q3f/eEPsbd38tzby/lUfT1/W7eOX994I4fX1/Pqd29mQm8vT/3mNzw5fQbvLHpwaCOaRvnpp+M74IB8UTKZZO7cuYD6brrvvvuGjRv6iU98gptuuokXX3yRhQsX7rX7zFHsxNbn8zHYht00TZ544gkuuugifvnLX+bLjz76aFpbW/P7oxGX+4oxKdDcRQJjnIEuWPq/8MY9ENum7BNmnFIYKRsDosxOJsls3Eh6w0Y1GrZ1K9lt28i2tyPTTmQBKTE7O5WRrt9P4JBDqPzkefhmzMQ3dQqexkb06uqd2mDtLlJK+vv76e7upr+/f8gWjUaHTCEKIQiFQvh8vpJRrWAwiGEY+P1+KisrqaqqorKyMi/CvF5vqYdt24Z0vxJcqT5Idqm0t6sQHiu6zcm3QWrkqVoQyh2KL1zY/BVQPkGNUA0+5gs78UmrCzFK90XILMtUYqp/K7Qvd/zrrVSjUdJSo3z51B7ZBtBKqxBhQxDKF18u5mqoHmpnFsVirVSbv3zkaX4j4AiukHpOOeH5PjULAEdoxeO8/MILBP1+tL4u3nrmKVIDcdKJAdLxOL/505/5+5I3ERKQNp86ah4PvfQ6Z8ydxZRaNf32i+df48gDJjJnQiP+UJhApJxgJEJl4zjGzTiQQCSCxx/A4/Ph8fnx+HwYTuovCzmiLILHN7bCAY0GaVlq0VAsjtm5HbO9XY12tbdjtrfl8wDBL13PupYWpvi8VKbT9P3hD6T6+3k7nWbRsR/jin+8jNQ0LK8P67TTaBw/Dj0URq+swNPYiKexEaO+fogJhTWC25Hm5uaSqAZCCN5666299zAGMZIT23g8zsqVK0mlUjz99NN85zvfKTl+zjnn8P3vf7+kbF+Ly5EQwznWGyvMnz9fLlmyZH93wyVH7yZ48f/BWw+rl9OUj8H8zzojZfvny05mMqTXrSO1ejXpd99Vgmz9erLbthUqaRpGXR2epiY8DQ2IYEFAehoaKfvQkfgPOQTNu+fCOkkpyWQyJBIJkslkfioxmUySSqVIp9OkUim6u7vp6OgglSqdlgqHw5SXl1NeXk4kEhmyDRnZGtoBNWIV3w7RVuhaC51rVEisRHdBkKWijGj8LPRC9IVwYyEGabC6IDIClUqEBSqUUN9bYtbKQs9GFcYrb2M2oEalctOjxXZmVtoxojdVaptKcGUTqm7xPfvKVbivQMWgKTUnFSPck6ZD+XiomKTsakJ1BeH1AfLPZ2YyxLo7GejtJd7Xw0BvLwN9PQz09jDQ30eir5eBfjXCZRkeBqYejLdzK76utnwbumGwNZ7ksdeX8a1LzydcXkFKCjSfj2gqw49+dS+P3vdr/v7qGzz65JM88ac/EQhH0PaSecC+REqZn1Y029vItrWTbW/DbGsju307dn9hAZE9MPwItBYMYjiiytPYQNPNN9P7+z9w65NPcNv99/Pl667jhFNP5YavfpV58+Zxzz330NTUxOmnn86hhx7K4sWLeeSRR/b6va5evZpZs2btlbaHC6Qei8Vob29n2rRppFIp3nnnHaZPn56PVLC7DHc/QoilUso9EvNqTI6guYwx+luVMHvzfvULfu6FcOTVUDdzn3bDHhggtWYNqVWrSa1epUTZ2nWQVcuuRSCAd3IzgcMOo/zcc/AdMAXvAZPxNjfvUfFVjGma9PX10d3dTWdnJx0dHXR0dNDd3T3iL01QU40+n4/Kykpmz55NQ0MDNTU1eZsuY0eG/1KqKbO+TWpqrW8z9G9RI13xDmfbrsRIMd4w1ExVIzo1M5QgyYmrwWmwWoXE2lNCw7ac+KgtpUb8+S1ZZNg/qGygE3o3KpE1HN6wMy0aUaO3Hr8asdOMIoN5j0oNrxNntU7FYc1Fn3gfj0ztaaSUJKP99LZto6+jjWS0n0wqRSaVJJtKkkkmyaSSpGIx+js7GOjtGdKGbhgEKyoJVVQRqWugYdoMysorWN8bY2NHJ+dc9jmq6xvwl4XwlZVheH089thjvGPfy6W3/M+Q9pZu3sbDTy/mwQcf5JlnnqGsYt/41is4u3VWXUrbWQvhjKwWleXXZMqCuwqJxI4PkG1vI9vRgdmxPW/Pmt2u8tb2TuVrsOi6wutFr63FqK1FnzAOUVaGUVaGVhZCCwXRysrQKxwbVssGXcM7c2b+mtx8Mwu//S2y2SzzDjuML33pC7z2xhK2trbyra99lReeeZpsJoMwTc46+UR+cdedPHL/bzh64YL8PQ9//7LoPik6VnrPyqmts1d0zJSCdGIEM4fiVa0jHC+6ghoZ9Yz+e93v9+d9ph1QNGU7lnEFmsvIRNvgpR+r6Uwp4bBLYOGXoXzcXr+02dtLatUqUqtWkV69mtSq1WQ2bcp/cehVVfhnzSL0mUvxz5qFb9YsvJMm7dXpSNu26erqUl6vt2yhtbWV7u7uEg/ckUiE+vp6pk6dSllZGYFAIB+CJJfPTUuOSKofOlvU849tU8KrON+3ZagtlzcMkSY1wjX+CEeAOAHfI41QPU2NhO0NIWLbqm/d65xtvRKJOeP+gW5VPiRofRFCd6bxAs5WlK+bpabPa6YrMeULO8eCSkwae972L+fdXua83duWk+Y84tsF7/h2Ud45x3bySJn30j+4zk7bzdUrKrdtG+xCvrSOHPac4fqYTafp2txCOjFAJqGM4s1sBjObxcpmsIf5cSE0DU3X1abpaIaBx+ujatwEDI8HzfCgG4ZzXMtfLz0QJxWPsn3LJlq0MsqkyZJHHx7yAk+mUyx/7RUaqiqYPXE8h0+fyswJTUgpma2l+eqtt3LCoQfx/E9/yPNSvaaVTz3n+eWFQSEtzpeUFZ8z6Nxcf0ZjxzZavvrIkzSWR5BSognBWYfNprmmCso9tBPmsX+uJJpIgpQsaGrgvIZKAuk4vpZ+DEu5g9GlciWj2xLDlviyJl5L9THq9/LSjAkl1/zMQSrU0b8/+n8s+voXeXX9Jrq6u/nURRdjOf24/4H7mRpr56O1Ya677lpuOGEhhr73vkMXXPtVetu27bziKIjU1u2SQAOora2lvb2ddDo9qjBb+xtXoLkMJdEDL9wGS+5RoxZzL4SPfqWwPHoPY6fTJN98k8QbS0itXk1q9WpMx44CHFcNB84icvpp+GcdiH/2gRh1daW2VHuInOuIeDyeT6PRKFu3bmXLli2kHfu1QCDAhAkTOPDAA6mqqqK6upqamhoCgV2wv0v1q3BW21cqG6jONWoqcmB7aT2hKaEVblThrQ44Vn0WFROVgXjFRDXytSeeRyahIjr0bHDszjrUaJ107LHydlm2+r/Rt0VNmxaN1kkjgAzVq9QIYPtqyM6chxmeRKZsHJbmwxQeLAxMDEzpwZZgmSa2ZWKbFrZlKg/7pqnCE3WZWB1JbGtFSR3bspzzLGcz86mVr2OPUF50jmkVBE/RCMIHBSGUWwUhNISm4TE8SmgZOppuoGmqXAjhpEV5R4zZlom0bYRWWkedaxDXdWxbUOfR8QcijkcLkb92WAh+/OUvsrplEyvWbeTu/1vMJaeexPFHzmfdilWEggG6khkapkzP9znXB+UWAueaKlX7ajFESRkCoRX8VomiLfc3JJNJrN5e7N5eNbUYi2FH41ixKDKZVH2XBfdpWjDo+A70o/mUP0HN50Pz+9BCYfyeZ3js29/EMC1ee3sl9zz3HFc1zyTV2cVZz7/Ot5uaWFBZS9K2+dK2razqT3BBZSUy4Ae/H/wB8HrB60V6vQivFyrqEJWNiHAtFRXlnHxQdf478Vt/Xsyp1325kP/CV9hy/wNE3m3htf970qknuPia62g67uOcMXcO1zrPECGY+aEFTJ8yJf+VctqJJ3L15ZdiZi1+fOddPL34WbxeD35/gH+75mqOXbCg8LzVp+N46VBuQnLt9mYsqprGD/IrJobmRvI7BvnPcPD09uDpTSC/qjyHpmnMmTNnmL+AsYkr0FwKmBl445fw/A+V/dKcT8NHvwpVez7obKa1lfizzxF/8UUSb7yBTKVA0/BOnkzw8MPxz5qF/8BZ+GfORK/YO8HPo9FofjRsy5YtdHV15QXYYOrq6jjooIMYP348EyZMoLq6mlELRCurRpA6HCG2fZVK+7cU6vjK1ZTxtBPVNGTVARAZp0RZqF65EdhNzEyGeE83mWQC2bMBreMttOhWtIEO9GQn3oFWfMm2Ek/klvCQFgFsKfI+oKQadMCWEDP99KZr6E756E376c0EiJteSr9hbWCjs71HnBAumm4URnGc0Rq9uEw38qJC13UMb1D5W8uN7Djlhf2iNjUNoelKYBSJlWIhUlKuqbzmhFcSmkDT9BLhMETUaIPaLWlLqOsXtZUTEDmBRC6fa2sYsbSzdp+//9e8+Zc/ccq1NzBrwTF7bNQ559alt7eXnp6efNrT00N/fz+2bdPQ0MDFV101qr+d3//+99x333187Mov8OVDD+Xl117n8ssvR0ydzamnnrpLfZPZrPJb2NNT8E1Y5LPQ6uvD3N6J2dlJtq2txG+hCASU/WpTE54D5zj5RpU2NqLX1UEmgxUfwB6IY/X1q0VJW1vJbNlC5t0NCNMkfPevAUjFopRHo3hXruaJTJojJk3i9IsuxtNQj15bzx0DGT5+w3X8x+MvIE0NK5rG6stg9acx+9JY/WrDcv5OY2AEgjQcPS/fZ03TmbXw2EJ+wTG8+pUbqaisYuaHP5qvd9Fll/Pisre54KprSp5XIBBg9bvvDnmON954I0lb8s7atfh8Pjo6Onj++eeZdMjcUX0OsdWr8e7Kj9gPOO4iARfFxhfhz19UIydTj4cTb1ZTS3sIadukVqwg9uyzxJ99jrTzx++dPJmyBQso+8iHKTv8cLSysp209N6wLIuOjo4SQdbvfAkbhkFTUxMNDQ2EQiFCoRBlZWWUlZXl86MKmiulmtrrWKFGxjpWqtGxzjXK6ScoO6ia6VB3oLJ/ym2Rce9pBCyTShLr7iLe3U2sp4t4Tzfxni6S0Wh+yspORglE11JpbaMpEKUxECNoFMKlpCyDeNZLXzbA9lQZnakyejJBUoQgEFZuBgLBvO8mw+vD8HjQPR50jxfD61X7hge9KK8ZpWJIz43K6IaaCjOKBZMH3SgSS7lzc4LrA2R0vzeQUrLhzTdY8dxfWffGq9RNnkLzIYfucjuWZZNMJUklUySTyZJ8JlvqSy+3mjjg9+N3XLhUVVXhdf6WPP4AHzr7U/n6a9asQdM0pk2bBsA3v/lN+vr68n9/N998M8uWLeNTn/oUb731Fn5/6cIkO5kk09JCZuNGMltaybZuIdPaSnZLK9m2NhjBJlT4fOjl5Rh1dRi1tRj1dfimTMU3bRq+aVPRq6oAMLdvJ7NpE9nNm8ls2qzE1+ZNZDdvURE/hkGvqcF3wAEc8MD9HDh+Imlb0tHbw+O3PcCc8QfxjZ/9F+PK6rj8sHORKROZVVOWB/3kVF75/COEfc73oQZ6xIde7kOvUKlR7s3n9Qofemj46b5QKEQ8Hi8JCJ7jpz/96bCrFHPnFJNIJJgwYQIbN24kEokMe62dsTcXCewPPpCLBFw3G/sQy4QXboXnb1WjNhf+AaYdv8eaT61aRe/vfkds8WKszi7QdYLz5lF349cJH3ss3kmT9ti1ipFS0tHRwbp161i/fj2tra1kncUE4XCYiRMnctRRRzF+/HgaGhp2bBM2HJYJXe9C+9vKVUP7ciXIEt2FOuFGJb4OOBbqD4L6A5U4K7KZskyTeE83sXdWkoj2kx4YUC4HEgMqPxAnnUyU5M1MBmGlCMo4EdFPtS9BlTdBQDcpE5Jxho7XAL+WwScy+DxpRLX6IZYONJGuOoyumoOx6g5B1kzDCEYwvD4avF7GGUo86Y7Icnn/0926mcX33sWWFbmg2oLuLZvo3rJp2Pr56Eb5cESFUETD/ZwXznSWPzfNmE/V2OmAswFsLTovUF5RItDi8Thf+MIX6OvrwzAMpk6dyvXXX8/nPve5vLuGOXPmcMLChXz3uuv48rHHktnYQmbDBtItGzG3tVGMXl2Nd/x4AnPnEjn9NLzjx2PU1qooHOXl+egdxf4LpW2T3bqV9Pr1pFauoP/xx0mvX0dm/YZSEWYYeMeNwzNxIsFDD8PT2IAIhkGLAGUgwthpD1ZPBiuWwW88wlMX3A/A0q0ruPJb17P48w9gJbNoVQb+GZVoASO/iZ/r1Fw0i/K6KvSIFy3sdaZlob29nWuvv5433ngDn89Hc3MzP/nJT8hms3zhC1+gtbUVKSWXXHIJ3/zmN0ueSc4Z684o9nUG8I1vfINZs2YxceLE9yzOXHadMSnQ3Fic+4j+Vnj0Stj0Msy5AE79kfK9tJtY8QHizz1H70MPkXzzTUQgQOiYowl/7GOEFi7ca1OWAB0dHSxbtowVK1bkHbXW19dz2GGHMWHCBCZMmEB5efmuN9zfCi0vw+Z/OH6zVhWM3nWfEl8zTnWE2GzMqulk8JFOJkjFY2qE680NRLteI9bdRayrk1h3J/G+3uHtnYQgVOZlXCTD+MAAEW+GcCRJMBInIKN47dIVmmagFsoa0L1+hO5RIjDndytUD02Hwfj5+IJVjH3TWJfB2LbF24ufpuWtfw46IvO2dDlbPMsyMdMpsqkU6YT6/5fDHwpz8Q9vJ1BeQU9PD93d3flpyFx+sIPjsrKyvJ1lVVVVSX5PGVpLKZnT3Mziu+4iu20bZnc3Vk8v1t//zrOnfpztV38eq6eH7NatXOt4rO946WW0YFCZRcybj/fcZnyTJ+OdPBnP+AnoocJovBUfINPSgtXbg9neTnrdOuz4AHY8jj0wgNnZSXrDBjIbNypzCwe9tgbfAVOInH4G3uap6DUT0MO1oJdhx0013RjNkOlNYa1PFVYaijhGlR+jNoh3UhihCyrOnIJe7uOUikO58umb8Fw3lSMmfYwXXniBqnOn56+5YcMGQuVhaucN/fEqpeSss87i0ksv5eGHHwZg2bJldHR08JnPfIY777yTE088kUQiwTnnnMPPf/7z9/R5BAKBIUJu+fLlI9R+f6HrOgcffDBSSnRd54477uDDH/7wsCOMN9xwA5dccsl+6+uYFGguexkp4Z8PwNP/roy+z7ob5py/W01mWluJ/fUZ4i+8QGLpUshm8UyaSP03bqT8rLPQ9/CvLsuy6OvrK7F3aWlpoa2tLT9NMmPGDKZOnfrefvFF21Q80Y3Pq+nfPjXaYHvDpCumM9B0Mn2ilu5shM64QWxLH8lV/aQTL5FOPI2VzZY0J5D49Sxlfo1IRTk1lRU0H1hPODKFcMhHMOghIDJ4M10YyS603nWI7asKIY28YbUgIHKw8r2V26qnQs00DP97EJ0uYx5p22xctpS//+ZX9LZtxRcsU36zzCy2abIjExUhNDSPh7L6RsqnH4QdLCOLxj33P5Cf3s+RE2EHHHBAiRCrqqoaMpW40z7LnJ2iGnGTRSsure5uUhs2kF6/geSmzfRv2050eyfxrl5kKl2IUelM92uhEFqkHK08gn7AeLTDP4a3qQmjqRGjaZz6sSecWKIDcejoQFv2LuLJxWitWxCtm9G2bkbr6R6pu8hAADtcjj1hEtZJZ0DTVETFBDRvFSQh25eBvjTWaltdh+1OH8EMGGSDOgMBSfdUaPMl2GxEmTnl8JIRaEvAM34bmUrS+srbJDNZnt+UIjjraJ6+6bt8++cPcciRC0knk/z4G1dz/PlX8Lsljo1qkfuKFW+8TF/KpuKwU3n49c3OoSqee/qvNM2YS1f5TB58bTOfPmICd9xxB8ccc8wufXY7YurUqWzevJlYLFZieP9+o1h8Pv3003zjG9/g+eefB0Y/wrivcG3Q9jKZVJJX//AwXZtb9ndXFGZaGakPdCmnmvWz37PnfzuTxezqxNzeiR1VX/haWRl6VZXaysuHLsZ5j1gSojb025CyQVm7FK/+kfgFVGpQoYOxqxe2svmwPDLRg8ioSRlb6GSFn6RpMJCGjK2VXFfTdMcWq+BiQOg6ugZeewCPGcPIxhAj+fAajNDU6JcnqByeBsrVAgL9/TndaDsv6lyae3lDUVzrvM+l4nJZNNVWlOaOy9LptpwIoKhukdsk5KD2ir/3ZFGZlGAj83G/5SCRUdLPIr9NsqSfctDx3DmDvDyVHJfYtuW437CdxRg2wraoS28nrfl4s/xQNgUnojsuLTTdUE6YkZRpacrIECRFkBRlMkVQJtApuIow0UiIIAMiQEJT6QB+EiKA6QQCl0X3Uiy0bMkQ4ZUrJ1/H2d+LhDIJJvdv44BoG+PindQleqlL9lGb6CU0KAZpvzdIa6iOraEaJ62lxx8mYfgxjQCVniANhp8JQmcSOpPQmIimpmoderDZhE0LNpux2YZNFzadSPqQjNYRx6Zbz8BT64yISUnF0ZcSnHI4AJnOFnqeuQtroBdsm7LZx1L+kU8Pu5AiuuRxzP4Oqo4rnVzqWfxLjPI6IvPPBODxGyaQtJIcP/N4zKzJn1b9iW1btnHVCVfRNLlJdQPJgk8sYOH5C6kL1nHWtLMKz3kYGzSAr33ta3R2dnL33Xfj9Xppa2tj8eLFXHTRRaN6DmPBBq343h555BEWLVrEH//4R1paWvLB3kfL3rZBcwXaXmTT8mX89Re3E+3qpH7ylL3iFmKXSMfUIgAplVF6qHaXm7DTaaz+KHYsmg8arvn8aJUVGOUVCO+eExISSAiDft1LQhhIITCkjd828WLjkYVNR+6SGJSWiZXog3QMLTuAsDOo3+GCjK2Rtgwyto4pNTTDg8frU8bwXh+6x8gbuuc/UzOtvPLnHK+aKfWcdY9yoGp4VVBsrcgzfUnAad0J+Lzrg9o5AVH8khz5z9oRS7Z0BFPRy5hi8VF4KdvOi7tkf6R0UL2RfE6OeQqeAQruIIoPi1w1MWg/d1yUtAMU/HEVOf3M+SgDu2h6zBn9clZmDkQa2T55Ad5AAD9pPNk4enYAIxvHyMbRi4SJBGxPEMsbwvaGsLwhpDeE7QsjDb/jSqK037n7zN2PEDkXFqAJVD+ce9KQ2AMDyGgUBuIqbm0ygUwmkYkEJAaQiQQik0EgEVKi+/3o1dUY1VV4qqqcfDXeSIiQz0OZT8ePjbd9K57WTXi2bkaL9qMNxNBiUbS4k8aiaLHCyJ9dFsKqa8CurceqrceurceuU6nVNB4iFYisjbcvjacvjbdHpZ7+DHosm/9cJGCFPZgVPrIVXqxKP5kKDz3BFJvNdlZ2reCtzrfYFi/EawQo90WYEBnPpMgExoebqCurpS5QQ22wBkPTiWfjxDMxlWbjDGQHyNpZTNvEkiZZ28R2UkuaWLZVlDcxbRPTKTftLKa0WP6n14m29zLlooNJmymSZpKUlWLrw+vw1PipPq5BfY5GDCFg1TWrmPH/ZqAHdrzI5rC6w7jvlPvy+7lpwBwnn3wyt9xyC5lMhm9+85s8+uij+P1+ysrK+K//+i9OOumkHbafo0TQPHWjsuHdkzQcDKfcssMquXtLpVK0tbXx7LPPMm/evF1aRJHjA7lI4P1Cx8b1vL34aWxr6OhIIhpl/ZJXqWwcx/k3/ZBxMw/cDz10kBJe+Rk88y04YDp8apFy5TBKrL4++v/yF/r/+CdSjh2C/+CDCZ1yMuHjjsc/Y/pOWtg1EokEK1eu5LXXXqOrq4uysjKOPPhgZs+ezbhx45Rbg1FiZrNs37ie/vVvYba8gqdrBRWpDdT6e9ADEtMWbEtGaE1W0e1txqo7hKqJB1A9bgLV4ydSPW4CnpGmeCwT1vwF3viVmgoNojzwNxwCTUcpm7Rx8/Lhj9KmRX8ySzSZdVKTZNYia9lkLYlp2fl81rIxbUnGtEmZFl2xDJ3xNF2xNImMSSprk8xapLIWabPod7zj3mlP4vdo+Awdn6HhK84bGn5PLq87x4bWLT7fo2voWu7lL5zNefnnxMCgdEgdrUgwFNXJ19ccP0lF5+haoU4urw0639DV5tE0NO29PURp2/S2b6Njwzo6Nqylff06etu2kujvG1pZCKoax1E/ZRr1k6dSPX4CFQ2N2B4vXV0qMkVuq+x8i0x/YZWkz+ejpqaG6uomJ1V++Kqqqka34ngU95FtbVXh09auLWwtm/KRO3Lo5eXoNTUY1dUYNdXoM2rwNjfjmzoV39SpGM4qSFA/8DItLaTXrSOzbD3pdetJr1+vnFAXxZvVQiHVbkUFenU5+pSJaJEI3vHj8c2YiX/mDIzawg9MmbXJdiYwOxJkOwbIrkiQ7diI1VMQr8KjYdQGkM1l9IcStPm7WK9v5m37HbamtmFLG1vapJNpOro7yNjqeWtCY0J4Ah9tmEDYq6b2pJRk7AwZO0aP9RZbe14l2h4lmo4Sy8Qw5ShHzB08mgdDM/JpLj+4vH5qmI7XNzK3cRIBT4CgESRgBFi6ZSkb/rmBG46+IV/es7WHqyuu5tFPPooudLVpOprQ0IWOV/fi1/34DB8erfT/zEhRULxeL7feeiu33nrrLt3fWKJ4ivOVV17hkksuyY+ajbUpTlegvQds22LJnx/j5d8+gG4Y+IaL66VpHH7GORx13gV4vPvRLDsdgz9fDyt+D7NOh0/cqTyxj+bUtWvp+c399D/+ODKdxjd9OnVf/zqRU0/FU1+3R7vZ19fHypUrWbNmDVu2bEFKSWNjI2eddRazZ88e9SrLdGKAre+sonXlP7HffZaq2Fs0l3XT5FEG/bYU9PubaK86Cdn8UbwzjqWmbhwTQuGCP6hMAuLtSoD1b4CeNAx0k4m2k+rZhuheN01yZQAAIABJREFUi9G9Bm/vWnQzQTLQyP9n77zj46jv9P+e3Z3ZLq2klVa92bJsyx13MCZgMARC7wQIJIRwBEI6gdwd5C4kkEJIIIWEXyC5gwSSo8aAMeBesHEv6r2stKrbd2Zn5vfHyGu5UNwN6Hm95jWzM9+d+a7KzjOf8jw14+5iW8Zi2tVMBmJJBjsUhuplhmKrGBomZHHlyJTJJYuJbJcVr9tKXroNp9WCXTSIj00yY7OYsYlm7KJBmOySGYvJdEjVDgGwS2YckgWHZJAms0nAYjIZBMUkYDEb2zaLGdEsnPzI7ykKXdcZ6vbjb6wzCFlDHd1N9cixGAAWUSK7rJzyGbNJ82bjzvLiysjEnpaOzeUmoekMDA0RCARoDQR4f8MmAoFAqtsYjHRMdnY206ZNIzs7m+zsbLxeL06n85j8XnRdJ9kTOJiINTQY0bFhiIWFWMeNw3XWWUglJUglJYhFRVgyMw3R1ENAi0aJV1cTfO014rt2Edu5C7mpyXCeAEP3sLgYaewY3IsWDRO6MUhlZZg+4KFI13XUoQRKe5jQlkYS/jDJ7ih6v2IYrAOaSSeerjKUFqXL10eLtZMaSzMNtNAb7yWejMMIvmzChPYhyUpN12gJttASbMFmtuEUnThFJzaLDavZIDdpUhqFrkLckps0axppkrGMfO2W3NjMtoOImFkwf+zfpf55nbkvzqWitoLbbjPSnBs3bmTq56Zyy19uwd3iZtGiRcRiMa762lXcf+/9jM88sZZ8HxsfEek6EZg3bx69vb0EAoGTPZVD4lND0HRdp3XHNqKhoY8efHQXYsfbb9K2ewcVc+Zz7m1fx+4+RduOOzbDP241CtzP+Q8441sfS2srunkLvU88QWTNGgSrlfRLLiHj2muwTphwTG/WqqpSU1PD5s2bqa+vB4yOywULFjB+/Hjy8vI+8npyLEpH9W5ad22nZ/cmXL3vU+7qZY5zAKtZRc2QiOXMJDZmIdbKM9FzpyKoImosSTBuRLPi1U3k1D2Ht2c9rmgbLuXQBcXS8NKje6jVCqjTF7BWq+Kd+HTUATMQxC5G8DhE0u0iHodImddJul3cb0kbsXYMkynJbEK0CAdtjxKkUwe6rjPU003L9i20bN9C267txCNGLYvZYiG7tJwJC87GVz6G3PIKsgqLEUwmwuEwfr+f7u5uahtbUlGx5IiIkdvtJjs7mxkzZpCdnU1OTg5er/eoTZ3VwUGUri6Svb0ke/tQ+4x1sq8PpauTRF39fqKs5mwvtooKMq6+Cuu4cYYW2JgxB+kTqkNDKF1dRmfk4OCIZYhkXx+J6j0kGhpTZMySnY1t0iTc552LdcxY9NJCEgWZREwKA3KYaDKKpmlo9JEMdDMQH6Av2keiP4ylRyetT8I7lEZBJJu0pDEXFY0uKUCLtYuWrE6arZ20WDvpkHpQhRGEKzG8AGbBjFty47F6yLZn43P4yLRnkial4RJduCQXDtFhbIv7tveSMssRlCAcDrSoghKIGZHAHmPxfKEcMdv4OxAEgRdffJF77rmHn/70p9hstpTMxssvv8xdd93FnXfeiaqq3HjjjXz9618/rvP9pKO6uhpVVcnKyiIajX70G04wPhU1aHIsytInH6dm7coTMCsQrTY+d8tXmXTWuafmzVPXYf1v4a3/NCQWrvgTlMz7yLfFd++m57HHiKxYidnrJfPGG/FcfRWWjGNvTFxXV8frr79Of38/breb6dOnM23aNDJHpEMOBTkWpbNmD627d9C+awextu2UO3sZ4+6n0D6ESdCJiZm05SykLvMs9tin058w0T4Qo7UvQvtAjKSmI6Ew37SLq83LOc+0CRM67+sVNOn59FhyGRJ9SFYbDpsVu82KyenFnObDmp6H5HAjDafrXFYLHodIhkPC4xCxiaOCqp90KPE4ve0t9DQ10tPcwEBXJ+H+XkL9fSSHnSbcWdmUTJlGXkUlvvIKvEXF6AgEAgG6u7tThKy7u3u/L/60tLRUJGwkETssi7BDQFcU5OZm4jW1JGqqidfUkKipJdndfdBYwWYz0pE+nxG12kvEKvZPR4JB8OI1tSSq9xCvriHR2IDS3II6dOgHYc1mRXXbiRRl0VfqoaPQTmOuQLstQn+sn6AcJKJEUPURKTQd8hQvY+JFjIkXUZYooEDOwSdnIQ7HEFRBo9cVxO/up8XRRbW1iZ3mWnqVvv3U2TJtmZSklVCcVkxZWhll6WWUp5fjc/gQzeJxJ1gfF7quo/bHkdtCyO1hlK4wSk8ULTQifWwxIebY8Vw6FmvxKRoEOEycCk0CI+vrdF3noYce4sILLzxkDdqtt97K3Xff/YHn+kw2CYwQqr2trq7uQ8f2trXw6i9/wkBXJ6df80Uq5sw/7vNzpHmwuY5eL+y4QNPg9e8adVHjL4KLf2NoYX0IEg0NBH79G0JvvokpPZ2sr3yZzBtuwHSUT++HQl9fH0uXLqWmpoasrCzOPfdcxo0b94F1ZQP+Thrffw9/Qx1dTQ20BEK4XBrj3H3MsLdQYjI8O/doRSzTTmOZOoPtejk6xvksJoE0u0iBx87EdJkz2UxVaA2F/euwqDEUyUNwwrUoM27B6RuDy2o5NUn3KI4LgoEemrZuomXHVgb9XYT6evfTDbM6nWQWFOHOysadmYXHl0fRpCmI7vQUAdtLyHp7e1PdoRaLhZycHHw+H7m5ufh8Pnw+31ETMcCIUNXUDJOxGuK1Nch19eh7U6OiiLW8HGvlOGyVlUYqcrhGzJzlxeR07Pc3rmoqfe31DO7ZQbShBqWxCZo7kNq6kYb2pTmjaRJ9uQ76vFZ6vSJ+t0qreZA+USZsh7AdlBHt0xbBQoYtg0xbZmqdbk03olMWF3mDGeS2p+FpFhGDwx6YAmhZJkxeG4k0jRZzBztNtaxT36cmVEtyuBs615lLVVYV5enllHvKKUsvoyytDId47L+zjgXUoIzcHjKWthBKRxgtOhxBtZgQcx2IPidijgOLz4GYbcecYUuJ035acCoQtGOJzyRB24uS7Cz93ssu+NAx8XAYm8vFhXd/j+JJU07QzE5RqAq89G+w43k4/Ruw6MEPTWnKra30PvFbhl59FZPNRuaXvkTmLV/CfAw1bmRZpqOjg/r6emprawkEAoiiyMKFC5k7d+4ha8uCgR52rXibzRs2sb1PpcOWh9etcqa4nQvN6/AJgyR1EzvESdR5FtCZsxCLt5wct41st5VstxWvy0q6zYJtsBah9g2ofQPa3gN0cOdD5flGEX/pAhAPT+dpFJ9saKrKrpVv8/5rL9HX3gqA25tNdnEp7iwv7qxsMvMLySkrx+3NYWBggM7OTjo7O1ORsZFRsfT09BQB20vIMjMzD6uZ5ZDzlGWjPqyulviOncR27iC+ew9qb29qjCU7G2tlJdZx44zC+XEVCMX5BPUYA/EBBuID9Cf6GYwP0h/vZyjSi9zlB38Ae0cf+Q1BxrQm8Ab3XTdsg44s6MgS6PXZ6M130lvgJOFxIJkkrGYrklnCKTrJd+VT4Cog15GLW3LjlJw4LU4ybBmkSWkIgmB09IZkFH8UuS1EoiWI3BJET6hgFrCN9SBVZtCdMcg2fTeb+7awvms9gZhRF+S1e6nMrKQyo5KqrCqmZk/F5/Qd1c/2eEKLJ4eJWBi5PYTSHkLd2+BhAtHnRCp0Ixa6kIrciD4HgvnY+KGe6hglaIeHU5qgjSst1p+4/3sfOka02ph50WW4MrNO0KxOUShxeOFLUPs6nPOfsOBbHzg0XltL35N/JLhkCYIoknH99WTd9pWD0htHiqGhIdatW0drayt+vx9N0zCZTJSUlFBRUcGkSZNS4rExWaV9IEpzb5itO2rYubuB1sEYA6IHp5jkEvNaLresYazQjipY8OeciV51KdnTL8LqPsTvXFWgZS3UvG78LAaajf150wxCVnm+0WU5GiX7zEFNJqlZt4p1/3iWQX8XvvKxjD99IWXTZ5KZX4iu6/T399PV1UVnZyddXV10dXWRGE5rms3m/UjY0UbFdFVFbm0lUVNLor4exd9FsqeHZHcPyZ4e1IGBfYNNJtTKMganlNBb5qE3x4bfqdCp9NIebscf8ZNQE5hlleIA5Pfp5Pfr5A1ARkjHHSO1mEZ85cc8doLjC1AmliNWjMVRMY70/FKy7FmkW9MP6u77WJ9L01E6wsTrB0jUDyJ3RtBj++rtLD4HUkka4TyF9c7trOpdwyb/JsKKUc+Xactkdu5s5ubNZW7+XApcBUf08z1R0KIKieYgiYZBEo1DKF2R1DFLlg2x0I1U5EYqdCHmuzBJn90yiFGCdng4pQnaJ10H7YRBicFz10Hjcrjw5zDrK4cclmhoIPCrxwi99RaCw0HGtdeS+aWbEXOOTUdmMplk/fr1rFixAk3TUtZKvrx8cvKKsFqtaLrOjo4hVtQGWF7TQ0Mgst85CvUeLrdv5kLpfSrlXQDoRfMQpl4NEy6GSABCfpAjw0t433ZvLdS/DYkhsNigbCFUXgDjFkNa/jH5jKP4ZEFNKrTu2EbthjXUb1xPPBwiu6SM+Vd/kYyysXR0dOxHyGTZiHSYzWZyc3PJy8sjPz+fvLw8cnJyMJuP7OaqRSLE9+whvnu3UR9Wa3RL6vE4UQn8mQJxXzqyN414povBTIlet07AJhOwxOjWBgkp+wuHppuczAxmMdkvUdwu42kdwNk5iLBX+NdkQs/LxuLzIWV5sWZ6EbO8iAX5iPn5SMXFWPLzjzqlr+s6al/cIGR1g8QbhtDjBiET85xIxW7EHAeJLNgq7GZ1/1rWda6jI2w4cxa6CpmbP5cZOTOYmj2VInfRKVtmoOs6yd4YckuQRHMQuTVIsmc4DWwxYS1Nw1qWjlTsRipwYXJ8MgWmjxdGCdrhYZSgfdIhR+G5a6FpJVzyBEy/4aAhit9P4PHHGfq/FzHZ7WTefBMZN954zIr/dV2nrq6OpUuX0tvby7jKSjLGzWJrt8L6xj52dAwdpDAuWUxUSBHcHTvwJvu4pLiXee4mXMFqY4C3EqZcBePOh5Z1BvlsXWuo/X8QXLlQca5BysrPAsn5wWNH8alFUlFo2b6Fug1rqN+0nkQkgmS3M+a0OYydM5+o5GDjxo10dBgEwWKx4PP5UkQsPz+f7OzsIyJjiqYwGOqlZc96Guo30eqvoX+wk0Q4SNKko5hBtUvo6S5ibisdtii9euiQ5/JYPeQ58/A5feQ58yhW0ihuCuOt70eqaSa5uwZ9mFBacnOxTZyIbfx4rOMrsY6tQCos+EAJjKOBrukonWHi9YPIrSHk1iBa2Kh/M6dbsVZ4sFV4sJS52R2vYU3nGtZ2rmVn7040XcMlupidO5v5+fOZnz+forSiYz7HYwVdUZHbwiRajbSs3BJM1Y4JdgvWkjSkErexLk5DsHw2UpVHilGCdngYJWifZMgRePYaaF5t6JtNu26/w7quM/j35+l+5BFQFDKuv46s228/ZqlMgNbWVpYtW0Zrays2Vxp9nom80SYQSiQRzQLTijzMKcsi07nvRpHngN6X/0i0fiOLT7NTnNiGKTEIOVUw6TIjUmbPgPW/M5odEkHIKIPS06F4PmSWGeRLcg2vnSA6U4Kwo/hsIh4Js23pEt5//RXCCRnBk4U1twBsDiS7URg/ODhILBYjKyuLmTNnUlZWth8Z03WdiBIhKAdT6u+yuk8gNp6M44/48Uf99ER76I/1MRjpYyDax6A8RESQD5qXI2lGMolIog3JakcS7YgmEbvFbnQbppdRmlaKx+pJyTlkWdKx+PuQm5qIbt5MZM1aEtXGw4sgSdiqqrBPmza8TEX0Hd+aLF3ViNcPEt/ZR6y6Hy00TAy9diN9V+LGOsZDNE1hXec6VrSvYHXHagYTg5gEE5O8k1KEbJJ30hGlTk8E1LBMomkIuTlIotUo5t/7dGnJtiOVpA2TsjQsXvunroj/eGOUoB0eTo2e41EcPhIh+N+roW39sNn5NfsdVrq76br/h0RWr8Y5fx65P/oRUmHhMbt8KBTi7y++QntjHYpJYnOyhJpeL2lRExdM9nHBpDzmlmdhP6Deoq+9lSU/u58JbGVGZRemkGp0m869A4rngX87rP01bH8BNAUmXgKn3wP5047Z3EfxyUQw0EPzts0kohHkeAwlHkfXNJKqRn8oRHNzE7JoQ8sfkzL+khxuvF5vKmWWnZ3N1KlTySnMoWGogVWDq6hrqaNhsAF/xE8gFiCWjH3YNAAwaZAZM+EOaaRFNcpi4IpBhsOLN7+cgpLJjJ0wl+Ly6dgP4XWr6zrJri4S9fUkNjYgN60gGegl2d+P3NtLq9+/T9BVFHHMmEH2N7+Jc+4cbBMmHJfI2IFQIwpKV4TYrl5i23vRIgqC1YxtXAa2CZnYxmWAw0ztQC0bupaycvNKNndvRtVVPFYPCwoWcGbhmczLn0e6Nf24z/dIoEYUEo1DJBoHSTQMkewZbv6wmJCKXLjPLEQqcSMVp2F2npqkchSfXowStE8iYoPwP1dA5xa4/I8w+cr9DkfWraP9nm+iyzK+//h3Mq47tPHukUDTNF5+ew1b1q5A11R2qAWY8yr53Jgc7h/jZU55JuIhOpL6O9t5/8X/xbHnOa7ObEMyqQiTr4Ozvm+Ygu95DZY9aBBO0WGkaud9HbLGHJN5j+KTCU1Vady8ke1vv0HT1vdTJumazYmenknS4UKx2g0/U08O2VmZlIwpJyM3AylTImKO0BvrTS1dkS7+sOUPdK7uTF3DYXEw1jOWiVkTyXZk4xUzcPSEEJs7Mde2oDU0ow+bK4uqQI6URXZGIbb8AsT8fMQJBYgF+dgmTfrAsgFNlg01/S1biW3ZTHTL1v26Mc2ZmVhyfVgys5BKS0gvLEQqLU1ZJh0PyZuRUCOKocnVGhzW5YqkomRYBOwTsnBMy8FS4aY2WMem7jfYtGET73e/T0gxUrQVGRXcMukWFhYuZLJ3MmbTqVcMr0UVEk1DJBoMUqb4DUImSCak0nQcM3Kwlqcj5btG05WfUuzVQdN1HbPZzOOPP878+YY8165du7jrrrtob29H13VuuukmfvjDH560mshRgvZJQ6QP/nopBKrhmr/C+Av3Ozzwwgv4H/wR1rIyCn/za6TS0iO+lKJq1PhDbGsfpCkQobOrC5t/O2nqEH2kMXbWQp45ewrpH1AIq2kqrdu3suPtJTjqXmK+txWnVyZZfi7CWd+D/gZY8l1oeNeIlmWWw+KHYNoNYPcc8bxH8cmHEo+zc/lbbHrtJYYC3di8PrwLz2HQpDMUCKEN+48mnUki7hB9jj78op9+tZ9EIAGHcG7xWD3kOHKYmjOVKz1XUpFRQUVGBbm2HOQ91UTWrSeybi2xzVvQhzs3rRVjsU+7AFtVFbaqKqzjKjBZP9q6LdnfT2zrVmKbDTIW37EjVS8mFhXhOn0+tqlTsY0bhzRmzHERg/4w6EkNuS1EvGaAeG0/Sudws45gyEDYKjxYfA56XIPssTdRHVlHbUctO7ftTHVblqSVcF7peZzmO41ZubPIdeae0M/wcaBrOnJ7iHh1P/GaAZTOMOiGL6dUkkba4mys5R6kQtdnRuris46RXpxvvvkmP/jBD1ixYgWxWIyLL76Y3/3ud5x33nlEo1GuuOIKfvvb33LnnXeelLmOErRPEkLd8JdLYKAJrn0OKhalDumaRuCXv6TvT0/hXLCAgkd/ifkIxXSHogp3/20L6xv7SCQ1bCjMlDoYYwqgmSQ84+fxnUvPxmU7NDHr7+xg14pl1K16k0p2cE5WF45cBS29BCrPxzLUBs9cCKoM6UUw92tQdTnkTx+Vv/gMQtVUArEAffE++sIBtm54m/ptWzEl7bh8BVjyCgkrAr3dg0QsEXpsPQQcAbQMDZfTRZo1jSwpizJrWcoDMcOWQbY9G6/dS5Y9iyxbFqLZ+HvVdR25qZnIyrVE1/+T+g3voQUNITDruHFkXHsNjtmzsc+Y8bGI014V/+jWrcQ2byG2ZQtyc7NxUBSxT5xIxg03YJ8+Dcf06fuZfJ8I6JqOOphA6Y4gt4eRm4aQ20LoigYmkIrTSDuvBEuxixann00D77PRv5HNXZsZShiOAVazlbGesVxQdgEzfTOZmTuTHMex9eM9VtCiCvHagRT51CJJEIY/5znFWMd4kIrcoxGyj4m9EadkMsmECRP41a9+xYUXGoEBv9+P2Wwme/hv+r333kM6Aen3Y4VgMEjG8P/4s88+y+mnn855550HgMPh4PHHH+ess84aJWij+AgMtcMzFxsSEze8AGVnpg7pySRd99/P0MuvkHH9dfjuuw/hY5qLHwrPvtfKitoAX5pfyhgpSNuWFSQVmdmz57Jw4cJD6j7J8RjVa1awa/kyPN3LOSO7hTNyZEbSLdNQC7z3B0ModtZXDFJWOHOUlH0Koes6HeEOdvftpjXUSlSJEkvGiCVjqe1IMoI/4qcr0oVJMeGNe8mJ5ZATzyFTPA1ESOgJ/FIHYoHIhIoJXDjmQorcRXjt3o9l26PFYshtbcTbdhFsaSVRU0Nk/fqUBZIlPw/3uYtwzpuPc+4cLF7voT+Pqhr1YrW1JHsCJAMBFL8fuaGeRHMLDKv4mz0e7DNmkH7F5ThmzMBWVfWBxt/HE+pQgtiuPmI7e5Hbw+jysLWSAGK+C+fsXKxl6UQKNFYEVrG8fTnvb3yfkGykK4vcRZxddDYzc2cy2TuZYnfxKZmyhOGuUn+EeE0/8eoB5NYg6GByWrCNy8Q2PgNbRcao5MURYmTE6YYbbuDvf/976vUDDzyAy+XiO9/5zmGf9+H3Hqa6v/qYznV85ni+P/v7HzomFosxbdo04vE4XV1dvPPOO4CR3jzttNP2GztmzBjC4TDBYDCl3XkiMUrQPgkYaIZnvmDUnt34IhTPSR3SZZmO73yX0NKlZN/zDbJuv/2o8uWqpvM/61uYV5bB6fZO1qxZQ25uLldccUXqKWkkwv19bHnjVbYte520ZDfnF7eSkz9sNm7PMNKVp91ipCwFk0HGrOmjHZefUCiqQleki45wB/6IH0UziImu6/TF++gId9AeaqdhqCEVfQHDpNpuseOwOLCLdpwmJxnRDKZHpzNnYDZaWEdAAF0jKyeDiokTKCwpJCsnC7fkxiV9eDRYVxQSdXXEduwkvnMnicZGlNZWkoH9c53mjAwcs2fjnDcP57y5iMXFh/x/0ZNJYjt2EFmzluimTcS3b0cb4R4g2GxYcnKwlpfjOussrGPHYps8Bams9KTUq2iJpNF5OFxfJbcZRMvic+Cc6TPsg3wOklkmdoX3sLnnLda3r2fL5i1oukaBq4DzSs5jZu5MZvpmnpLpyr3QFdUo7G8KpqyT9IRBQMUCF+7PFWEbn4lU6P7Edlm6XC7C4X26d08//TSbNm3i8ccf54EHHuCRRx6hubmZnGENywPHHy8sWLCA7du3H/frHE+MJJzr1q3jpptuYufOnei6/oH/u6M1aCMwwovzZE/l5CMcgKe/AHIIbn7FSAMOQ4vHaf/GN4isWInvB/eSefPNR325d6p7iAz1MdPZx5o1fmbOnMnixYsRxf2fPtWkwuq//ZXNS16m0NbPZeUy+cka46BghrPvh/l3g3n0qfVUhK7rJNQEmm7UcukY8hL98f59S8xYB2IBOsIddIQ76In2pN5zIAQEchw5FLoLWVS8iIlZEw2/RE85NrONYDBIXV0dtbW1NDY2kkwmEQQwR0LYEjGmzZ3H5y6/Csn60RGnZG8vkbVriW3bTmznDhJ7qlM1Xqb0dKwVY3GecQZSSTFiURFScTFSURFmzwfXNsrtHUTWrCGyejWR9evRQiEQBGwTJpB+6aXYp03FNnEiFp8Pk8t1UsVUtViSRPOQQcgah4zaKg0wCUiFLtLOLcE+2UvQHeO97vfZ0rOFLTu3UN1fnTIqH5cxjq9O+SqLihcxLmPcKSsOC4b8RWxHL7E9/SQahyCpgUlAzHPimJaNVJyGbVwGZvcnJ712NPB6vfziF7/g4YcfPmHXTCaTvP7665x//vnH5HwfFek6EZg3bx69vb0EAgGqqqpYuXLlfscbGxtxuVy4j6H94eHglCRouq6/Crw6c+bM2072XE4qkjI8f6Ohnn/Lkv3JWSRC251fJ7phA7kPPkjGNVcf9eUGBgZ447WXucTaiRy2cvnllzNlysH+pkM9fl771cO4etbx1Qk9ONU+0CVAh+zxcMVTkDvpqOcziiOHrut0RjrZEdhBzUAN/oif7mg3PdEegokgISWUMp7+MFgEC1n2LApcBczyzUp5Lxa6C8lz5mGz7CNTaVIaknnfDVLTNDo6Oli7bS21tbV0D6cVPR4PY4oKCGx5D9nfwcTTz+TMG275ULs2XddJVFcTevsdwitWEN+xAwDB4UjVeNkmVWGfPBmx6OMr0Ss9PQy99DJDL72E3NhofObcXNyLz8N1+uk45s494QX8h4Ku6SQaBolXGwRF8UdAB8wCUpEb98IirOXpUGCjJlLLmo7XWPneSnb1GW4cNrONSd5J3DrpVqblTGNq9tRTVvpiL3RFJbazj+jWHuJ1A6AZumuuObnYxmUglaV/Zm2Tbr31Vp5++mm+//3vk3kMdS0Phb0pQTAiaF/+8peP6/VOJKqrq1FVlaysLG644QYeeughli1bxqJFi4jFYtx9991873sfbjd5PHFKErRRALoO//oWtK6DK/8fFMxIHVJDIdq+ejuxbdvIf/inpF988VFdKhKJsGrVKt57byMOVcNeOIG7b/gCjkO09tdvXM8bv32Uae4mziisgbQyiAOxfljwbVh4L1g+G0+xpwJagi2sal/F6o7VdEe7U/v3RsHAIFk5jhx8Th/jM8eTLqWn0oYWYd9XgEN0kGnLTC0jDa8/LmKxGA0NDdTW1lJfX080GkUQBIqLizn33HMpystl60vPU7dkGVmFxSz6j4conHhoMq+rKrFM4VUFAAAgAElEQVStWwm9tYzQsmUo7e0gCNinTCH7nm/gOvNMrJWVCIep+K+Gw4SXryD4r38RXrkSVBX7zNPwXfsDI+pWVnZKRJN0TUduCxHbHiC6PYAWUgw7oWI3aecUI5WlE8qW2di7iU3dL7Ozeid16+tIakkEBKZkT+Gu6XcxN28uEzInpJokTmXouo7SFSGy0U90SwA9nsTsseI+sxDHtBzE3M+GO8hIUgTQ39/PxSO+510uF7feeiuPPfYYDz744HGdy8iU4KcBI3+2uq7zzDPPYDabsdvtvPzyy9x1113ceeedqKrKjTfeyNe//vWTNtdRgnaqYsPvYctf4czvwqQrUruTAwO0ffkrxOvqKHj0UdIWn3fEl5BlmXXr1rFmzRoURUHPLOEVfzrLrv08DsfBUgJNWzbxyi9/zAVj+5hgroHMMYZURmY5XP83KJp9xHMZxaHhj/hZ2b6S9nA7neFO/BE/ESVCQk2kUpIApWmljPGMMeq4gEneSUzKmsTk7MlUZFQcN+V2XdcJBALU1tZSV1dHa2sruq4jiRa8LidF9nRscoxkRwPNddvZ3NmOqiicfvUXmXXJFZgt++alqypySyuJ2loia9cSevtt1L4+BFHEMX8eWbd/FffZZ2PJ+uBI2wdBDQYJv/suwTeXElm9Gl2WseTkkHXrrXiuuPyo5GiOJTRZJb6nj/iefuK1A4atkFnANj4Tx7QcrJXp7BjcxfK2F1m5ayV1A3UAuEU3Vd4qbp54M1XeKmb6ZpJhO/mRv48DPamRaBwiXt1PrLoftT9uaK9N8uKcZTQzfFJryY4UB5KivTVoI3H33Xczbdo0vv3tbx/Ta39YLdanAaqqfuCxyZMns3z58hM3mY/AKEE7FVH/Nrx5n6Gwf9Z9qd3q4CCtt9yK3NhI0eO/wbVw4RFfoqOjg3/+85/09/czfvx45i1YyEVPbuecyTlkuw8mZ/76Wl599CEuHdNOubkRbB6DnM36Cpz7o1Hfy2OEvcX26zrX8UrDK2zo2oCOjmgSyXflk+vMxWv3YrPYsJltVGZWckbBGRS5T4yfoSzL9PT00N3dTVdXF/X19QwODgLg8/moyM+l673V6MEBQoDscOL0ZGB1OrG53FTMOZ3Zl1yJS9UJvfIaclMTclsbcmsLckNjSn/M5HDgOmsh7kWLcJ555hFJxuiqSuitZQy++H9E1q4DRcGSm0vGddfiXrwY+7RpCKdAs4quaMQbBo1U3q4+dEUzOhArMzFXuGj29rA9/D47enfw3ovv0RfvwyJYOM13Gt+Y8Y1UhOxU7bI8FNSgTLzGIGTtWxp44I1fs6VrF570DKxuO9/87jd5+KdG5KK+vp6CggLsdjtTpkzhL3/5ywmbp67ryLqOrOkkNJ2Ephnbuoaqg6rraDpouo7K8FoHDWO/qutoGGt9eD3y+N73qbqOroOKcTyp6zzR2oM8fL0NPQO0D4a5r7adFb1DmKMKLV1DZJ53IYv+48ckNJ0btzeS1HVUXeeF0ypJGzsOTUmC2YzvwkvJveZGNMFEUtcZ3Po+7b95BDUSRgfSr7oR5xeuQNF1HCYTdWceXNoyihOPUYJ2qqG3Hv5xC+RMNCychm8gajhC61dvR25ooPB3v8N1xulHdHpN01i7di3vvPMOLpeLS6++nrU9Jm74nz2EEkluml960HsGujr4v4cfYHF+A+WWZqMb02KHL/4/GHvOUXzYzy4UTaEj1EFLsIXmYDPNwWYaBxv3634scBVwx9Q7+Hz55ylyF2ESTjyZSCaTtLW10dTURGNjIx0dHez175UkidLSUs444wx8nnTW/u9TtO/eSenUGSy4/kE8vlwku5EmTwYCRNZvILJhPf03fonuYaNyRBGpoACxuAjn7DlYx40bXiowHaGekibLDL38Mv1/egq5pQVLfh6ZN95I2uLzsE2efEqQMi2eJLa9l1h1P4m6AXRFQ7CbiU4w01zYzwbLVrb37aBuZx1J3agV9Dl8zMqdxVlFZ7GgcAFp0olv+z8cJIeJTELTSagaYX+EcP0AkaYhYoEoSQFUl8h3l/w7i664lq/d9TxJk0BnaytL31zC95a8jaLrPHTlJVx2/39SMHkqsqbzcGMXsq6T1HQU3VhkTUfWjGvFh9d7yZQyghTtJUh7idNeQrOXTI0kWXvHnAzIms5/Nexzu1D6QySjcULdA/RFE4iYiQ6GMV1+PdtvvQZVTeJPKJgFAVEQMFttnPf3V7EIAsn+Ptb84JtEE1HmfP1bxHsD/ONH93LF43+kYPIU5IF+/vblL3LG+LFUnX0u9gOilR/WHfrAAw8crx/BKBg1Sz+1EBuEP50DsQG47V3IKAEMLae2275KdMsWCn/za9xnn31Ep08mk7zwwgvU1NTgzi2lxjqO5fVDyKrG3PJMvnxGOedO3Ge6rCYVdq14h3X/+F/mObYxxd1sHKi6HC76pSGjMYqPRFgOs7NvJ9sD29nZu5OmoSbaQ+2pGy8YKvdl6WWM8YxhrGcsVVlVTMmecsJJmaZp+P3+FCFraWkZ7rYUKCgooKysjPz8fHw+Hx6PB5PJxJ7Vy3nryccxmc2cddNXqDprEYIgkOztZfCFFwguWUKirh4AU1oazjmzccydi3POHKPe6zBryA6E0tFB6J13ie/aRby2Brm+AV2WsVVVkXXbbbjPXXTU1zhWUHpjhNd0EH2/G13WUFw6Nd423rSsZLllA0nBSL+4RBdV3iomeyczyTuJyd7JRyUMq+s6UU0jqmpEhpeYqqUIi6LrDChJBpIqA0qSuDpMcvR9RCe+N3qUWg9v6wdEl4a3Pw65SWzeQOQvT5L5q6c+cEz/N7+C+2vfRKysAkAAJJOAZZiMiCZjbTOZsJoEJNPIbROiIGASwCwImDHWe19bBAHT8D6zACZBwIyxbRkeJwkmpOHzWk3D28PXNQGCrqBrUXQ1gqZGQI2ga2G0ZARdDaGpETQ1ZGwnQ+hqEDUZQlODmHQFAQ27NZdZp/0NswBmBMqzMugeGkISTFgEeOaZZ/aT2RipPfatb32LRx99lJH38gNlNxobG5k6dSrhcJivfe1rZGdnc+uttzJhwgQqKysZGBggHo/T3t5+UMf+scSoWfrhYZSgnSpQk/Ds1dC0Am5+FUoMbzBdUWj7tzuJrF5N/s9/RvqFF37EiT7g9KrKH//yLP6WBjYki9mTzCE/3c7iSblcP7uYCt++NmJd19m+7HU2vPg85mAbp5dGGG/ZYxxc8F1DQuNTXKNwNFA1lU3dm1jXuY76wXrqB+vpCHekjpemlVKRUUFpWiklaSWUppdS4i7BYzs51la6rjMwMEBjYyONjY00NTURixlm4dnZ2ZSXl1NWVkZpaSm2AwRXk7LMu888yfZlb1AwfiIX3v09XJlZxLdto//ZZwm9/ga6ohi6YwvOwDl3HraJE46aLOm6jtzQQGjZMkJL3yK+ezcAluxsrJWVWCvH4TrjDBxz554StTTJwQSxnb3EdvUiNwXRTDrbcxr4i+Ml9kiNuK1u5ubOY1xWFYVpY8hzlZDp8CHrAglNS5GlmKYRHyY/cc0gWGFVI5RU91uHh9cRVU2RsaiqcTjf9KIgpMiOdS/ZEYz1XuJz0PZeIqNoCIEYQncUy0ACSQN7pg1XYRquIjeSXUwRrJef/D09ba185ycPp4iWRRD2I2BXnLeIHz/8CHNmzUI0CZiP0+9U11USiW4SCT+KMoiiDJFMDqEkgyjKIMnkEEkliJIcRFGCxuvkEJomf8hZBSyWNERLOhYxfXidhih6sFjSES3GtiR58XqP7MH7UDiULpokSUyfPp1gMMhPf/pTpk6dykUXXcTOnTvp7+/H5/Px9NNPc8MNNxyzeRyIUYJ2eBhNcZ4qeOs/oOFt+MJj+8iZrtP1w38nsmoVuf/1oyMmZxub+njuhX+SFu1kl6mMcxfO4+dVPibmHdChF/KDfyedK5/HuvNtvpgdxZGzT5yTC38Jsz49LdbHEs1DzTxb/SxLm5caNUImC6VppUz2TuaysZcx2TuZKm/VKSNtMDAwwNq1a6mrq0vVkLndbsaNG5ciZR+mnD3g7+TVR39KoLmRWZdcybwLLiG0ZAlNf3+eRG0tJqcTzzXXkHH99VjLy47JnBP19Qy98iqht95CbmoCwD51Kjnf/Q7uRYuQSkr2G6/r+jC5MaI88eE02AfWCB3wWtPZt42R+koOR4tGRpNGptXiikosohCLyMSiCrGYQiKpkTBBODdJf2GSIUsCwVKGxXw/CCJDuolndR36MBYGh5ePB7tJwGUx4zKbcJvNOC0m8q0iTrMVp9mM02zCYTbhNJtwDo9zmk3YTKZUlEgUBDyihUzRjMdiQTzMonxd1YnX9BNZ10W8dgB0QzTWMbUQ+9RsLOmH9i/d5bRhtorMTDdqWO+8805Wr16NJEls3LgRMCJZTosZ21F4Zeq6jiwHiEabicWaiUabSSS6h8nWELIcIJHwo+uHlp4xm12IYrpBqsR0nM6xKXJl2Uu6LOnDr9OGx3qwWFwIJ6E04UCEw2GSySSPPvooixcvPujBxWw2Y7FY6Ojo+IAzjOJkYJSgnQrY/FdY/wTMvh1O+1Jqd+DRXzH08st4776LjKuuOuzTdgzGeOhfu+nbs57xlgBp5dP4y7VfwH6gdpAchTfuhc3PAFAARD1u7BPOg67tMNgCV/8VJhwZQfy0Y0/fHr6y9Csk1ARnFp7J+aXns6BwAXbLwZZYJxuhUIhVq1axadMmBEGgoqKC+fPnU15eTlZW1seKONWuX82bv38MwWTm81d+kfTN22l45Gz0eBxbVRW5Dz5I2oUXYnYZN11d14moGkNJlWBSTaXARhKbQ9UPJTSduCwTamom1NRMdGgIWXKgXfcVtJwckhmZyGaLMbYrSrxj13C6be85Tmx2QNJ0JBWsmo6kgajpaGICWYwQM4Ww20RybR5mOHPxSA5sJlMqFbc3SmUzmbCZD3g9YnvkGJvJhMtsPmwydaygxZKGNlvdALE9/WhBGZNbwn1WEY4ZOYjZB8v0HIiqqir++c9/pl4/8cQT9Pb2MnPm4QUgdF0lORzpkuU+orFmYtFmorGWYVLWgqpGUuMFQcRqzUEUPYiWDOzphdhshdhs+diseYhSJqIlzSBfljRMH8NW7FjiQP/LZ555BofDsd/+srIy/vrXv+L5EPHlvXjyySeRJIl58+aRnp7Oq6++up/G5bp167BarcdMhHYUxwajBO1ko3U9vPZNKD8LFj+U2t3/P/9L35NP4rn6arx33HFYp9Q0ncffree3y+sZRxczLAHmzJ3H+YvPO/gG7N8J/7gVemvRZt3O0pVNdAwKXPeTJxBe/zfDmP3Kp0bJ2Qdgd99ublt6G07Ryd8u+tsJ66b8MKiqSltbWypt2dXVlapP0TQNk8nE9OnTOfPMM0lP//gRvWB/P6/99Wm21uxB8pWSJwu89sYqwp4MEvf8gHhlJWF3GoOKSnBPe4qQDSXVIyq2FnQdSZGRVDNSURm2sVbsLic2UUyRGo9JwGqy7EdoRhKeA9eSIAzXIO2tPTLqjwRG1CYhGA4HwzVLpuH9ekhG64xg7olh6o4idEWQYupwCs+OmmOixtzIO7HVbNC3ELRFOafkbC4ou4A5eReckoT9cJEcShDf2UtsVx+J5iHQQJDMWMek47zEh218JsJhRLrOPvts7rvvPn73u99xx/D3XHSEpZYBjXC4hta2HcTjHSjKwHAKct+STA7BAUlcQTBjsxXicJTi8czC4SjFYS/F4SjFas0/4aTrcHCg/+Xvf/97vvWtb+23/+abbuKJx37B/fd8DXQVPMWHPFcgEOAnP/kJV111FYIgcPvtt/Ozn/2Myy67jIaGBiZNmsSePXtYuHDhIYXJP23YS3J1XcdsNvP4448zf/58mpubUzV5siwzc+ZMnnrqqeNak/dROHX/Qj8LGGqHv38RPEVw5Z/BbPw6IuvW0f3QQ7g+9zly/+PfD7uO5qEle/jT6iYuKxNI72pl4sSJLD7v3P3PE+2H956EVb80fDJvfJEVq+vZ1byby773Qxzv3At1S+GiR/fTYfssIqJEiCgRFE1BURVjrSn0RHu4b/V9uEU3Ty1+ikJ34UmbYzQapb6+npqaGurr60kkEqnC/lmzZmGxGH9bFouFyZMnkzWsJabpOv2KSo+sDC9JehIKATlJ18AgXYE+AkqSgGQjYnfAlLON5QBIgoBHM5MeiZMhWsixioxz2kizmFNLusWMy2LCbjLtT5x0DVO3H33PHtStW1E3bURobEQURdLPPx/P1Vdhnz79hNaT6ZqO2h9H7oogNw8Rrx0gGTBq8wTRhJjrRJyYTX9OjLXi+7zZ+zbbAtsQkgKzi2Zz95hvsahkEU7xky0/oyc1Es1BEnUDxOsHUTqMuiZLjsNwL6jwIOW70GUNNSQTrxtEC8losoquaOiyihqUUQcTqIMJxHwnWdfvq9kRBIGXXnqJb37zmzzyyCNkZ3uxWnW++70L2bPnB4TD1QwObmL3nkZUzYrZ7DSiXnsjX7ZCLHtfix5EMQNJzMBuL8ZmK8R0nPT/ThgSYRZMKWP7e0thhQpqAv54DvQ3MK+/m+17VNB/DbmT4WurU2/bK8aqKAqCIDA4OMiKFSsoLS1FVVVsNhv33nsvmqahKAo//vGP+fOf/8wrr7yynyDu8cCmTZuw2+0pvbWsrCx8Ph+CIBAKhaivr0ca0cFdVFR0TI3KR5LcN998kx/84AesWLECMMzRt27diqqqnHvuuTz//PPHtSbvozBK0E4m/vVtI734pX+Bw7DrULp76PjOd5HKyij4+c8QLIf3K/rzmib+tLqJL03PQGpYTlZeHpdeeimmvdICwS5Y+xt4/2lQIjDhYrjwl9TsqGbzkpeZuehsynf9FBrfhXP+E2beeow/9CcHmq7xx+1/5LfbfvuB/pMFrgKeWvwUBa6CEzw76Ovro6amhpqampRArNPpZOLEiRSNrcCRX8CQYKZHTtIhG6SrR1b4Y/sQgcZeeuQkAUVBPUQm0C4nyBzsJyM4RAZJMmIhMpQE04tLqZw8hSxfNhmiBY/FTLpoxmEyfSwCpSeTxPdUE920idjmzSQaGpDb2tAVw3RdTE8n/bTTcN1wvZEmPUEeeLquk+yJEq8ZIF7dj9weRpeHBS0tJqzl6Tjn5GEdk061qYHXW95gWesy/PV+AMZnjucbM77BReUXndJG4x8HmqwSrxkgtrOX+J5+4+cggDnLjjQmHcFiQgsrRN7rIrSynUP+Ae2FACaXiMVjQ8xzIhUffKPNy8vj6acfpbPrH3R1Pk880Qm8QU/Ag9s1nn/84z9JS59Geto0rFbfwdf4pCMpw0Az9NUbS38DJOPwi/Ekhzp5/fkY54+xwLvrQFNBcqBWXszbr7/Ll69bAAtno7ty6RqMsb19kKbe6H5irH/4wx/YvHkzf/jDH1L7Fi5cyH//939zxx13sHPnTgAqKyv5yU9+chBB2xtxUhQFi8XCzTffzD333IPJZGL58uX8/Oc/57XXXgPghz/8IRs3buSVV17Baj103aHJZKKqyujIVRSFxsZGVFWloMD4DnW5XFRUVByzH++HIRgMknEIKzez2czs2bNPek3eKEE7Wah5A2rfgHP/C7IrAePm1fntb6NFo5Q88zQm5+E9fb+xs4sfvbabCyo9eLreIylJXHfddfueRnqq4ZkvQLQPJl8FZ9wDORPY8e5S3vrD40yo9HFm5Gnwd8EXfg2nHb35+icVQ4kh7l99PyvaV7C4dDFz8uYgmsTUYjFZEE0iU7KnnLDC/7gss7Wxia1NLezu9NMjJ4lKVvD4EBZMRLY7GRJMdMtJIj0y9DTt936zANmiSI5kIVsSqXLbyZFEckQL6e2t2N5ehu3tt8js7yVz0iTU+XNZUb2VgUA3My64mDOuuQXR9tFG5gci2ddHeMVKwu++S2TtWrSIUQskFhdjqxyH+5yzkUpLsU2ahLWi4oTolGmJJHJzELkjjNIRRm4Pow4ZIrlirhPHaTlIeS7EfCdKpsD7/ZtZ2/kay9cupyPcgWgSOaPgDP5t6r9xesHpRyWBcSKh67oR2UqoaAnVWMeTaBGFRPMQcnMQxR8FTQcT+9KVOqi9MdS+GOYMGxavHanQhcluQbBZMNksmN0iJreE2SVhspkRRDNYhA8k7ooSJBB4k+7uV+kfWAdoZGaczpgx38WTMRur5DslunCPCTQNgu3DJKxh//VgC4x8AHRkEZNVpj3eCxYXC2Yv4Ms/+S/IrST2X2lM+kUrLc0rKa6cxPryO3huW4zdXUECoXcAkMwmbpxXgstq3N6fe+457r333v2mc8UVV/DQQw/tt+/SSy/lgQceYNWqVSxYsCC1f2TEqaenh+uvv56hoaGDLKZ+/OMfs2bNGpYsWfKB5Gwk/A89RGJPNZKuMRiJorhcqKpKUpZpsR9ZOYB1wnhy77vvQ8fsjS7G43G6urp45513DhoTj8fZsGEDjz322BHN41hhlKCdDChxoyjfOw7mfC21O/DYY0Q3bSL/kYexjh37sU+n6zr/3NzB/S/uYEZhGqep1fjDYW655ZZ9oeHu3QY5M5mNULhvIgDv/+tllv/lj8ydnMF8YQlCMs2I6H3GbJtCcoh3296lP9bPQGKApc1L8Uf83DfnPq6tvPa43yhkTaMrodCZUOiMy3QmFDoSCq2RGE3BEL2KSthkQRcEsOVA+T5C4Dab8FlFsiULxZLIIsnYzpFEfFaDjOVIFrJEC6YRn0MNhxl65RUGn/sbibo6TG436ZddSsa119LY1cbSP/wayWbn6n//MUVVh1ebogaDBN98k+ArrxLdtAl0HYvPR9rnP49j7hwcM2ci+k5sNEQJRIlt7yVeN4DcGjJICGDJsiEVu7GOLcJWmYnFYyWpJVnVvor/q/k/1nSuQdEUbGYbs3JnccfUOzi7+Gzc0omJ7h0JtFgSuS2E3BZCCURRBxIk++NoYfnAUq1DQrCZEXMcWLIdWLLtiF47lmw7lkw7gng03ZQaAwPr6Oj8G4HAMnRdxm4rprT0DvLzrsRuP3Qd1ScCug6RwAgCVr+PiPU3GunJvRCdkDUG8qcbD8tZYyBrrGGb58jE/iMXW5t60TSdnZ1D/L4mwOol28EsEf78Q2QkIjT840F+97vfMuui61kw1svUIg9TCtOZkJeGTdzXCHYo66K7776bu+++e799giCwbdu2D/2IOTk5PPnkk8yaNWs/kdpf/OIXLFmyhDfffBP7YZKrvVqPqTpZVSUS3dfQYbfZ92WAjgFGEs5169Zx0003paKIDQ0NTJs2jbq6Oq688sqTXpM3StBOBtb9xii+v/HFlLF4eM0a+v74JzxXX31Y5udNvRHuf3EHaxv6mFns4cpsP9W72rjyyitTIWP8O+Avl4BZMjTWvBXIsSirnnuGrW/+i7OnpzEt8S+E3Mlw3d8gLe94fOpTGt9e/m3Wda0DwGKyUOIu4c/n/5lpOdM+4p0fDUXT8csG8eoaJl77to11QE4edN906hr2aBhHPEo5OsXpLiq8WYzP9ZHnsKUiYY7DlB/4/+ydd5wV5b3/3zOn1z1nz9le2GWX3pYiHUEUFRtqUERji8Yk6o2meJOr5pdijCZ6vSaadhMTjA2xIxZUugoIuyy9Lmyvp/c2M78/ZgtLExRbrp/Xa17TZ54zO/s8n/k+3+fzSezdi/+55wgtfR0pFiM1fCj+q+cTs1mIx6LE/vI/dDUcomjocC664ydYs0/e+zK+Yye+RYsIL1+Okk6jLy/Hfdtt2GafhWHYsM8/jyyQJLHfT6y6QyVlAugKrdjOLMJQ6UBfbEM09lWDLZEWXt7yMq/uf5XOeCduk5uFQxcyrWga4/PGY9B8fGTg84aSlkh3xkk1hUg1qqSsJ18OATQOA1qnEeNgJxq7HkVWyHTFSbeEkYIp0IoYBzsxjXTxyMt/YfHLS9BoNYiiSEFBAVVVVTzwwAO996utrWXhwoXs3r37pMuYSnlpa3uJltbFxOMNaLUOiooWkp8/D7tt9FcvUibLKvlq/giaNqp1rLcOkqG+Y0SdSrhclTDoHHXeM1nzerUk0+kg8XgDdrtKBvzRFJKs8MPna1m7vwtPJIUgwOiiLDQagV9cPJyKXCvxy0q4+ZsLeGXZHz7XRPaBAwciyzKdnZ0AfPDBB+zdu5fq6mqsp2DJdnika8uWLQweOZJEIkF7e/vn1sU5ZcoUPB4PXV1dQF8OWltbG7NmzfpccvJOhK8J2ueNQBOs/W8196tCTbaWIlHafvYz9AMHknf3f53UZWRZ4Yn3D/HQO3sxaETuv2wkpakmVqzYzqxZsxg5cqR6YKQTnroMtEaVnLkqqKveyHtP/JmIz8u8aQ4qfa9D+Uy46hkwfHmjAp8VtnZtZX3bem6tupVrh12LRWc5YYORlhV+dt99vLh4MYooIgsCC37zO5b85j6CnR2IegNotQz+r/uIlFXQeQzyZdOIFBr1FBp0jLSaKDDoKTTqMEXDdO3ZTcu2WoRUkhEjRjB9+nQKCj4daZZTKcLLl+N/9jniW7YgGAy0TD2Dg3KSUMAHu2rJysnFZM/C5nIzeNI0zpg3H81J5EAqmQyRtWvxLXqS2EcfqRpoV11F1iWXYBw54jNvfJWMTLozRqYzRrorTqYrRqYzTtoTh4zadaTNM5N1QTnmqlw09v4WUikpxZrmNby07yU+bP0QgGlF07h78N2cWXzmZ2Y0fzJQZAU5lkYKpZDDKTXhvmceSKrRMV+iNyomWnXoS2yYx+WiL7Gr3ZBGLRlfgvj2LmLbPaSb1UR/XbEV2+xSzFU5iAYt69ev580Vb1OzpQaDwYDH42Hnzp3ceOON/Qja4sWLufrqq09cbkUhmWwnEtlDe8drdHYuR1FSZGVNoLz8++TmzEXzJSS7/ZCOQ9QDXXugfZs64nUI8dQAACAASURBVD3YpOpFRjpA6haoNTrUSNiYq7oJWAVkV6ijKrv9USUpSSx+CFmKg9yGEmohFNqGp+s9AoFNCFo321KLWL2vi61NAZIZmVV7OzlzcA6zhuRw5qAcXFYD1p+K3DCtW1dwUA5jxoxh8eLFXHvttZ/rozlc4L6yshK/388777zD/PnzT/laPQOatKeYb306sGfPHiRJwuVy9Rs9XFBQwIMPPnjMnLzPE18TtM8TiqJ2bQKcd3/v5s6HHyLT3kHZs88gnkSOT0cowY+WbOX9Ax7mDM/j15eOJNLVwlNPvceIESOY2WOirijw+p2QCMF31oCrghX/+Au1y5fhLhnAwrPd2Lf/DYbPg8v/BtoveYX5GeGvW/+Kw+Dg+uHXo9EYaUum8aYzeFIZvOkMnakMdbEEB2JJDsSStNVWE1nyIs5HFyHo9chBP08k0wQTKXJ/+mvcI0YTe/tV6h57iIWLnqXQoKPQoJKxHlJm0/Z1QUiSxM6dO/loxUfsa25Gq9UybtQopk2bhtvt/lS/Lbl/P8HXXiPw0stIfj/6AQPI/clPUKZO4o3/dxeFg4cx6cqrqRg/CYvj1Ky70i0tBF56mcBLL5Hp6EBbUEDuT36C44r5n8jc/OMgx9K9uWJSKIUUTJJqjZBui/YlqgugyTaiyzFjqHSgzTWhL7KhK+xPuhVFobarlqV1S1lev5xwKkyeOY/vjPkOl1VeRqG18LSX/0RQFAU5kibdHiXdEeudZzqiKKmjB6iIZi0aux59kRXd2Fy0uWb0xTY0TgOCIKDICum2KJH1rcR3eHtHX+qKrWTNLcM00o3W1b8rqq2tDbfb3Zs/5Ha7mTlzJg6Hg40bNzJp0iQAlixZwvLly48qUzR6gM7Ot/F4VxKN7keS1AZPq7VTVLSQosKrsFoHn9bn9qmgKJBJQiqi5oE1rIeGD6GtVs3TzST6H+4YgOIshwFTUaz5yNkVSMUTkd2D1NQDReXJPVMksJX2lkXEIrtIxhvgGGIzsracDZ65rGwcysFoHcMKsrh2dgUTb25gSL4dQVB74r0odEXjbGrvYlckjtxtvv7rZ59HUaAmFEXpvn/PPvmw5d593QLNhx/X75zDjus5R1LgxXZf7/XaG+qRBJF3Mxp2eYKks5zc/Mjj3LLgcjbKGoZMnd7vejcUuTEdJ8qfTqdpaGggJyfnc4ui9uSggfp/9+STT6I5hrvJ8XLyPk98rgRNEAQLsBb4uaIoyz7Pe38psPMV2LMMzvllr2ZNdMMGAoufJ/vGGzFVfXx32ordHfzoha0k0zIPXD6Kq84oIZVK8ezSpbjdbubNm9f3otc+C3vfgHPvh9xh7F3/PrXLl1F13kWcNUJEfOsuGHM1zHu890vv3xGKouDPSNTHkzTEU3T0ELB0hvqIn02Zs7AXXMfo9QeISMcerenSaRlkNnC+245Xk6G2sID7xw3GpdPi1mtx67Rc+kcrD48bxIQJI9jj0nD5S8/wP0OPn1OTSqWora3lww8/JBAI4HK5OO+886iqqjrlPI7e3yrLJPfsIbxiJaG33yZVVwcaDbbZZ+FcuFC1PxJFNi97BYALv38X9pwTJ7grioLk85FuaiJ58BCxmmpimzaRbmgEQcAyYzr5P7sX68yZCKepq0VRFORQilRrhFRDmMQBv0oyDgtFihYtujwL1mmFKlHJt6B1mRC0J+7y3eHZwSPVj7CpfRMmrYnZpbO5aOBFTC6YjPYktLEkRSEtq64C6W53gZ71TLevZc82qXv58Mayx8FAiGUwHQphORTG0hBBF+tTsU+bNMRcRqLDHcSzdCTMOhJWDXGTlrhZQ0Yjdpt/d7sgIJP2eEntTZDyxkn5EkhpCUkQoECPZlQOgsuEYtAgKwpylwepS+nnmJAqGcL6/XVklZVTNHk6ZeddSMEZk9DMOo8bH/8rZ5hz6Ni6haDZyi9iGuStdWiUBIMS7zA8uZRsqRGANs0wOrTn4teX4BeLadMOIRU2oOwFWdnXTQr6CMCRpELdfjSxONZyzzFy9/EaKUNhvIW8ZBc5CQ/ulJecpJfcZBc5KS/2dBirFMOSiWGRYuiPcA6oNxax2T6cDrsLv85OQGtjv3kAu6wVhLVHfHSEgd1JYEe/zXlKK1fyLJNZTxgbexhOE+NpoYQY5t53uIN8OtIF4EKdgFqgljh/rW+B+hZ6X5juSeizt/jY9/QTQwAlqy/KnJRlbt+t/m3lgI/g/fegu+QKfryvmVRTF9FogkczBoSf/Y5Hbv0OjgceQ1c5pPf8K/Oz+xE0WZbZuXPnUTIbPYhEIuzcubN3vaCggOzs7NP28w4f4Xo4ysrKenPR4ORy8j5rnBRBEwThH8BFQKeiKCMP234+8HtAA/xdUZQHP+ZSPwGWfMKyfrUR9cCbd0HhOJhyOwByNErbPfeiHzCAnDu+f8LTFUXh7+sO8Zu3djO8wM4fFo6lIketMN59912CwSA33XRT34jNQCO89RMYMB0m30rE5+W9v/+R/IpBzDojF/Glb8Hg8+GSx76y5MyXztCU6PPBi0kyrYkULck0Ld3z1kSK5mSKUKY/8dIJAi6dlkTSg44M07Pd5BmN3YRLh0unwaXT4uomX1m6vn+VSPECpv/1MX4wbSLnnHMOCxYsoLInatmNt99+m0svvbTfNkmSqK+vp6GhgcbGRlpaWkin0xQXFzN37lwGDRr0iZJhFUkisno14XfeJfLBB0geDwgC5gkTcF5zNfY5c9Dm5PQ752DNJtylZcckZ3IqRbymhthHm4ht2kRi507kw8L/YlYW5vHjcV61EPu5c9AVnbrEiHKYSbekKKTSEqnmCKn6IEpDGKE1ithNWBQB4oVmgpNz8ReaCdu0hI0iCVHoNvSWSUhp4n4vKa/qRpCRIdN97Uw3eYqlEzSEmvAlA2iEC8kp+RZWnYONisAH+2Uye3chyQqSpJ4jKQqSrCAfTrYklRz0C5eoP6h7zmHzvmMERWF8BCZHZMqTMDABBWkQAb8G3rPC7jyBOgPUGcGvkYEYJGPQceTDO8aK0n+TiGoqLioghFIIwTBCnbpNUI49R4HcO/5EbP9WuvZuYd+dt5F3yS1Yh47j4D9vwzxlPp0v/53cESOI1bxDhXk/M5zvYdVGaIiXszp4DdvD4wllepTtBVAUBHw9a0ehd5vSt6wcZ/vh5whAtuSnUqpnUKZenUv1lMtN6OlPuuIY6BKy6RKctOImgpkYRiKimSgmIpjwCQ5qGIJHcoK/70/Xs6AnhkuJqTSw55ErICIxyLGPQVn7yDN3qJOpg7Ss5fXGubzTMJuEZFRHzx7FqRSMtB7jqXyxMOk1vPqTWer7I8CQVJLsO64nk0mj0Wq5ZeHV3HLHnWhFkQ1pD3922nh22giYNoI1pdnc+b3v8Po771JRWYkAWI6Inp3IJcJmszF27NjP9gd+hXCyEbRFwOPAv3o2CIKgAf4IzAGagU2CICxFJWsPHHH+t4DRwC7g1Mfp/zvgrZ9AIgjz/tgrSNv12OOkW1sZ8PRTJ+zaTEsy/++1HTz3URMXjMrnv6+o6rVrOnjwIJs3b2bKlCmUlHSr2MsSvHoroMClf0IRBN7+86NkUikuvvxMNK/eoo7SPEwc96uCpCzzrifECx0+VnhDZI7zIenUaigy6ik26pnksFJm0lNuMjDAZKDAoMOmEdnn38f81+/k+2O+x62jTn7UrNVqpbq6mnXr1rFq1SoWLFjAgw+q3ybXXHMN0WgUSZKoqakB1KHptbW1bNu2jUgkgiAI5OfnM27cOIYPH05paeknCu/LsRiBV17B969/kW5oRONwYJk2DcuM6VinT0d7nO7RRDRCy56dTLj48n7bpVAI/3PP4f3XU8heL4giwpChyBddTKK4hGhBAeG8AjwFRXjjGbzxFJHWBJHGfUTSEtGMRCwjE8tIJNISmbRMJikhZWRkSSU7iqTgTqkkpTLVPaUFBkgCWlR1/0OCzE6NzD69zD5R5oAoE/PHwN8FW+lHRgRJgUx3ZOEkoUGVRekiSBfBkz5PAE4lPqgFChE5Ey0XoacYkRQKjcjsRuYNJDaRYa8kIwfh8KKczqy3w3lkj0OCIAiqRpko9DoliN1G5ObsEeRNG0HEWUBy+xLuvGwXjxXFWRi/md9u6+R3jxWRk/MRAPsCY1jfMZemaCUCAloBslFUEtX9SvdfFjj8Ve957/sdI6jHAQgi6JUUxVITZVI9ZZlD3VM9DqXPr9QnumjUlbNcN4EWfRl+bS4hrYuQ1kVStCCK6n1FQei7vtBzX/VuY4S+ZYS+svaUre/cDA7tPnJ168nVvY9BDKAoInGlgLhcSnNmBjsCc2jNmMi1J/DFUoTifaQx326kMtfK8EIbWab++ZDHgkErdk8aDDp1Wa8V+43IPp3QiAJDLH3t0fEiTgCXn3sOl597Tu/6/AvnMr+x8TMp1/9FnFTrrCjKWkEQyo7YPBE4oCjKQQBBEBYD8xRFeQA12tYPgiCcBViA4UBcEIQ3FeU46p//btjzBux4Ec66p1feIrF3H76nnsJx5ZWYx48/7qnBeJpbn6nmgwNebp1VwY/PHYLY7b2XTCZZunQp2dnZnHXWWeoJiqKSwfp1Khl0DqB2+TIatm3hkitmY19+mzqyaOFi0H+8V97nCW8qw75Ygn3RBA3xFHJ3syIpCk2JFHWxJPXxFGlFIU+v5ZbiXCZmWeixIjSIYneelw7LETkFaTlNbWcty/eupz3aTiAZoC5Qh0Vn4Zphp64UrdFomDVrFrNmzWLUqFE8+aTqY/rMM88wYsQIbrvtNr7xjW+wYMEC/H4/oigyaNAgxowZQ0VFxUnpBAEkMxKeSApJUjt9ZAVSXR4Cry8j+NZbSJEo2iGDMdz8AzJjxxKQwZ/KEGiKEjgYIpDJEEpJxNMSiYxEPCUTDkcITrmZRUkn0qIPEOIJLl//JpdsWYk5nWBz8VCWzvkG23MriGmNandKm4LQooDUBpnWY0ZDQK1QBqOhDJE8BHIRcSFg756ciNjo+9t0CgpNOthlEWgwiRwyQVyryoFoBAGzAGO7lzWC2nhoBAGtIKAVBax6DVaDFrNei07Tp7nV0wh3xNpZ1bSK9mgr5VnlnDtgDnaDvbch1mkENKKIVhTQiAJaTfdcVK+lEdR1ofveYrdNlLoMmoyMsS6E4VAIIS33PhcxmkYIphB6oi3FVuTRbnRDnFToRCq7ycB3DytrDxlQf8CRBEEg0xUjXttFfHsXSjSDxqLFNCYXS1UO+jxLL5E4nAT1EIteuypZwdsSpa0uiK8tysyFg3uf2d69exFFkYEDS2hueYp7711EuCzGuOIM37hsIk88sY/KymGcc/bv0WjMGI2FnG0q5dSM6I4BRYFQK3TshM5d4NkPMY/qdhLzqiKuSo9osBFyhkLeRZA3onsaSbbFRTbw6cdcH6t4CtHoPny+D/D5PyAQ+AhJiiGKelyus8jPuwSDZRrv7QmybGsrHxzwIMlxIM7AHAszBuVQmWNlUJ6ViWXZ5Nr/b8Yovsap49OET4qApsPWm4FJxztYUZR7AARBuAHwHI+cCYJwC3ALQGnpV1gTpwdxPyz7IeSNguk/ANR/+Pb7foXGZiPnzjuOe2qjN8aNiz6i0RfjofmjuWJCn89jKpXixRdfJBAIcMMNN/R1bb7/CGz6G0z9Dxj7TaRMmvef+xcTRuVRufdhyCqC65b2Ohd8EVAUhYPxJBsCUbaFY92kLIk33feVqe9ugEHtriky6hlsMXK+O4upDitnZtvQnOALMpqOssu7i+2e7Wzt3MrG9o1E01G0gpY8Sx5ZhiwG2Acwf/D8jxWalSKRfknvPQ1Zz1Dw2tpaSktLqamp4f3332fFihUUFBTw4osvcsm8S5kx+1ycRQOJK1rqoil2bOsk0R1lSqRlEmmJZEYmlsrgjafxxdP4oim6QgnC0fRxSlUGkw5rGqslqN58wt/RHyJxgozy1HFH7QsURTx8UFrF0lFzaMkdgF6nIU8rYtCJGLUazHoNFr0Gq15LtklHvl5HIQK2pIwxLmGIZjD7kpg8CcTD82MsOjR2PRqLDo1Ji2jRocszoyuwoMuzUGzSMu4USn0ykBWZ91veZ9HORWzq2oQzy8n/zPkpc8vnfqJIpZKW1Vy4pjAZb7w3HCVH08R3+yAjo8k2ojksb0fjMqF1q5O+1I7O/clyCuV4htjWLqLVHaSbwmhEAfewbCzj8zAOcfbzvZTSMm0Hg7Ts9RP2JYiFUsSCKaTDuvejgSTppEp2LA4Dk+cNxGhR43WdnTu4444f4vN1IooyZeX5PPH35ykvP5OB5V08+GAhjz12D2730VZfJ/4Rkio/kQyrSfmypAqz+uuhbgUceE9d7oE1H6y5ah2VVQQjLuslYmQPPO1Rf0VRiMfriUT2EYnuIx7vE46V5ATBYDWplAcAk6mM/PzLyc6eisU2iffrEvz13Vbe2/0+yYxMsdPEzTPKmTzQxdgSBw7zx0fIvsbXOB4+zZt+rJruY/sZFEVZ9DH7/xf4X4AJEyZ8hpmQnxOW36uKF179PGjUijD0+uvEN1eTf9+v0B7DZgJgc72PW56qRpIVnrppEpMH9mlRRSIRnn32Wdra2rjooosoKytTd9Q+Cyt+pQofnvMrAFr27CKHNmYoaxAcpXD9MrB9vgKhkqKwOxJnQzDKhkCEjcEoXSmVjNk0IkMsRs5z2xlsNjLYok6FBt3HhvBlRUZSJCRZQlIkmsPNrG1ey9rmtWzzbOu1Zyq2FjO3fC7Ti6YzuWDyKfkjhqtraPne9xB+/ht8Q6vwx1JUV+/nHw/9PyKhIIogkOVwcsEFF9DW1sb2XbsxlI6h1ToQy+Qr+fUz7+H2jwCqj3+T7mQPRSOgaAXQiihaEcWhQ8k3Yjbr0KeT6MNh9JkUZosFsysbs9mISSNi0ogYRRGrVoNdp3pe2nVaHDoRi0aDRhQx6bu7SDTw4s9+SOWw4UwOhIm8/zy6khIKHvsHw6ZM4eYjn3EyQ7IuSLojSro9RqY5RsYfRUkc0e2hEdDlWzBMLkBfZkdfaEWTZfjYhP3TCUVRWNW0ise2PMaBwAHyLfn8eMKP+cagb2DVn9qoUjmWJr7DS6y2k2RDqDcpWzBqEboDgIJWxDIhr1vSwnbaRqEpskKyLkB0cwfxnV7IyOjyzWRdOBDz2Bw0Vj2ZlISvI4avJYqnJYKnMUzrgQCZlIwgClgcesx2AzaXEZ2+729QMiyb/IF2bHntpPiIxtZVpJJdRGMHSKX38PB/G8jOvoYBpTfjdE7uPS8nJ4d0+rCPBVlWJScinRDtVGUnIl3dy51qndczP1wb7EjoLFB+pvqxUTAacoeB6dRGE38SyHKGQHATXV3v0NX1Dslke/ceAYMhv9fDUxA0OJ1TyHZOw+mcSlrIZd0+D/+7qoN3d20knMjgsui56owSLqkqYlyp46un6fY1vrT4NAStGSg5bL0YvoQZj18kDrwHtU/DjB9BoRp8l0IhOn73EMYxo3F849gm5K/VtnDXC9socpp44voJDMzpa1w8Hg9PP/00kUiEqy6cyRCbB1beDy3VcHC1qmc270/QnWzeufF1Li/dieAY+LmRs5QsszUcZ0MgwoZAlE2hSG+SfpFBx0ynjUkOC5OzrFSaDSddoYVTYb773nfZ7d2NpEjH9ccc7hrOzaNupiqnipHukTiNfRW+oigE42nagnHaAgm6Ikn80RS+WApfJIU/lsIXTeGPpdG3NvHL9x4lojPzo/c8BNdt6L1Owby7GKPrIE8IIABBnYMpd/yWg8Y80oIWWYDKq29C1GuQdAIBQcEnKCh6EUUjgChg1msoNhsoMOrJM2jJ1+vIM+jIN6gRqhxBwfD2m4T/8lfSra3Yzj+fvLt+/ImS8nvQsmcXxkAbI9eHiGzfQfYNN5Bzx/cRjxg1mmqNEN3YRmxLV68npcZhQJdnRl9mR+swonEaVBFUhxHRqkMQv5iGSVEU1reu5/Hax9nu2U6ZvYzfTP8N55eff9IaZoqskG6PkqwLkjygGoMjKWjdJmzTi9CX2tCX2I/SUDtdyGQkgnsDeGs68e/xEY2miQsCKasO2W5ElICPOkitbSHiT5KI9JElURRw5JsZNrWQkmFOigY70ZuOrtrj8WY6u96ire1lmur2AaDRmNHrczAaChg86Gfk5V2EXt+duyjLKvFKRdSIkixB127Y945at8U8R/8Qo0MVYbXmQsEYdW5yqvqKBrvaRSmKIGjA7FJzYT8neZ9otA6vdzV+/wb8gY+QpAiiaMTlOhOX6/vYrMOwWAah0fT/Xwgl0ry9vZ2lbzaz4eBWMrJClknHnOF5zKsqYlqFC+0pikV/ja9xMvg0BG0TMEgQhHKgBbgKOLF64UlCEISLgYsrT8Hu6EuHRAiW3gHuIXDmf/Zu7nrscSSvl5K//uUoz0FFUXj0vf38fsV+JpVn85dvjsdp0UOwGeo/wFO/nUXbFGRZ5gblFYqXPaSeKGggdziccRPM/lmvOwFRD0Ma/oQkGtBfv/QzJWdtyRRPtXrZEIhSE4qS6E7aHmQ2MC/XyaQsC5McVkqMn6yBkxWZu9+/m12eXVw97GqMWiNaQYtG1KARNGhFLXZ9FgNMY/GHjTR4Y9R4M6xJtBFKNNIeStIaiNMWiBNNHZ30qteKuCx6nGY92RY9lboUV7z8d/R6HY0/+y33lJTiI0N7y0GS+7djCPmJ6g1UFwxhX14pIZMFkyhi0ggYRBGDKKDrnptFkSqjnjKTgTJTz9yAS6c5JjmVIhH8zz6L76l/Ee3yYBwxgoIHHsAy6dPbbx36cB0TD7VDNEH+r35J1qXfIOOJk9nfpWpvtcdIt0WQ/EnQiphHuzGPz0NfZO2nuP9lQCwdY9nBZTy357neiNmvpv6KiysuPq5chpyUVB21YFIVem2Pkm6LkmqLonQncmvdJqxTCjFX5aArsn6mERHfHh/VSw9Sdyh0lHKC0aLFatRiMPbl7JntBvLK7FidRmwuI64iK848M5rD7JcymTDhcDOJZCuJRCvh0Db8gY0kEqrxs90+liFD7iM353z0Oqfa9RjpUMVY9/wB2rapXY7BZpCP0cVuckLlOVA2HWyFYM0BSy5Ycvrqni8JFEXB719PY9Pf8XrXAN3dlHkXk509A5drBhrNsXNxtzcH+cuaOt7d3UEqIzPAZeamGeWcMyyPsSWOr0nZVxQ95u+KoqDRaHj88ceZOnUqsixz5513snLlSgRBwGg0smTJEsrLy7+wsp6szMZzwCzALQhCM6qO2ROCINwOLEcdufkPRVF2nuAyJw1FUV4HXp8wYcK3T8f1vhC89wsItcBN74JOTQpN7NmD/5lncC68CtOIEf0OT2Yk/vPFbbxW28r88cX85rJR6LWi+rX6wvX40jqe5EpkUc8Ng4LkFlwHjgGqanX+KNAf0W2XSZF55iqMxNk/9B6G2z8b4U1FUXixw8+9+1sIZyRGWk1cV+hmksPCxCwLOfrTMx7tf7f9L6ubVvPTiT/l8oqrqOuKqFN7hLquKAc6IxzyRElJ/TWJzHoNdqOOPLuByhwrMwa5KcwyUeAwUpBlItdmINuix6xXyZKSydC5dx8ddz+IGA2x+JcPssplxbRrI6Ob67AnYqTNNsLjplA+YiQzbRbKTHoGmAz9xGc/KcKrV9P+81+Q6ejAMn06roduwjxp0qcmCXIqQ3hFNdlv7MdQ+Q3MVVNJHDAT/X8f9h0kqOREX2LDMKNYVZg3f3Eq+seCrMhUd1Sz7OAy3ql/h0g6wrDsYdw37T4uKL8AvUaPHM+QDqkCr0paIuNLkKwPkaoPkfHE+11P0ImqOfooN/oBdgwVDrSO0x/RScbSNO7y4WuLIscyZDqj+JsiNIdUAjTAZaBwaDbZI13YCyxYnUZ0ho9/nyQpTjiyhXBoO6HQNoKhrcTj9f2O0Yk2nGIRpalRuPwZzHV+WP/fEL8X4oG+BHxQ7eByh0HROFXA2lEChqzu0QYasBdB0fgvvTRPMuWho+N12tpeJhLZhU7nYmD5Dygo+AZG4/FdORRFYVtzkD+s2M+KPZ1kmXRcPbGUeVWFVJV83X3574DDvTiXL1/Of/3Xf7FmzRqef/55Wltb2bZtG6Io0tzcjMVy8ukwnwVOdhTnwuNsfxN487SW6N8Bh9bB5idUvbOSMwBVQLT9l79Ck5VFzh39BwakMjK3Pl3Dij2d3HXeEG6dVaFWBDX/gtfvJOAez5PxOWQkheuvv57c/PwT319R4M0foW3dxLK2IUz+9hWfyc9sTaS4e38zb3tCTMyy8PuhpZSbT2/jlsrILN65nD/W/ol8cRp/XVbAPd63e/eLApRmm6nMtTJrSA4VOVYqcq2UucxkmXRHfeXKikJHKk1zIk1jIkVNNEowGMK2bi0VLy3GfagOQyqFKIr88uY70IeCzN5VgyaVxF5QyLRpF3DG8OGn1bwXIOP10vHAg4SWLcMwqJLi3z96UsLFx4KiKEj+JKnGEIn9XST2dCBFRARBg33QPGQhjcbu7E1i75l0OSYE3Zer4ZUVmf3+/Wzt2sq2rm1sbN9Ie7Qdk9bEnAFzuGLwFYx2jSZVHyL+Tgv+usBRgragKu/rB9gxj8tF6zQi2vVoHQY0TuNp75qNhVJ4WyKEPHFC3gTtdQHaDgSP0sHSigLDhjsZd3klWcXHtlhTFAVZjiNJcWQ5qUbEwjsIhXcQDu8gGq2jR6Fer3Nj1xZTyARMgQDGriaM3jb0KQ8Ch1SilV2uRsAcpWByqMtGB1jcaiJ+zrAvXRTsZBGPN+HxrsbjWYHP9wEgY7OOYOiQ+8nPv6yftVQ4kWZve5hDnigN3hiHvFHqPeoUTUk4zDp+fO5grp9ahs345fpI+RqnD6FQCGd3HnhbWxsFBQW9dXtxcfEXWTTgS2r19JXu4kxFYent4CxXZTW6EXz1NeJbtlBwNZDvaAAAIABJREFU//1osvpGDaYlmf94TiVn980bwbVTytQdq38Lq39Dqvwcng7NJJmJcd1115H/ceQMYO9bUPMv9ukm06orxFV8+kbDKorCh4EI/2zx8JYniFYQ+HlFIbeU5JxwVOXJIJWR2dcRZntLkO0tQXa0BNnT0Y6+/LfI6Xz8nksYX2rninElVORaqcixUuY2YzhO5MqbyrDWE+TDQIT6eJKmRIrWRJrUES3llG3V3PfXR+jIL2TnuRegG1hOQq9ldHsr0sFWhg4dytSpU0/7qGJFlolt3EjghRcJv/suCuC+/Xbct3wbQf/xjaSSkcl446rxdUeUVIOHdEcUKSyDrOk+JokUqCcZbaYx1Uqg0sFF99yLyWY/5fK2t7dz5513smnTJgwGA2VlZTz66KOMGTOGIUOGkEqlmDBhAk888cSnNm/uiHbwyoFXeGX/K7RG1dRWp8HJmNwx3DnuTmYVz0LnUYht7qS9dhNyKAUaAX2JDfvZpWhzzQh6DYJORGPTo3WbPvMcuWggSfVb9ex8vxW5Z1CBAHatSKVeJE8nkFtqw1qVi2m0G63j2HILiUQrXu8afP4P8fvXk077jzpGr8nCpi0iRzMBe0TC1tmFoWk7grxHFQ9zD4bcSTCse/Rj3gjIKu4TG/sKQpKSRCK7CIW2EgptI9Gb2A+pVCex2CEATKZSygZ8h7z8eVgt6khrRVH4sM7D6r1dbDjoZUdLkB7pPI0oUOI0Uea2cEZZNoPzbFw8puBrYvYZY92SfXiaIqf1mu4SKzOuPLGdWI/VUyKRoK2tjZUrVwJw5ZVXMn36dNatW8fZZ5/NN7/5zS9cNPdLSdC+0l2cK+9X8zdueKNXZ0wKBul8+GFMY8eSdVmfunxGkrlj8RaW7+zg5xcP7yNnWxfD6t/AmKtZYbgIz6FNXHfddRQWnkQ3ZSYJy+9GcQ/h3c1WBk8d/6nD8jFJ5sNAhJXeECu8IRoSKZxaDbcU53BDkZsBplOPmgXjaQ52RdjTHu4jY21hUt1WSzajlpGFWUwaU0dtNMFfZj/MjAGjPtbEvCYUZZUvzCpfiG3hOAqQpdVQaTYwxmbmohxVvLbYqKfEqCdr6xYC/3gMw4gRjPv9o3xQU0NNTQ2CIDBmzBimTJlCzhEq/J8GcjxOdMMGImvXElmzhkxrG6LdjmPBApxXX41hYP98B0VWkKNpNU+sK066K0amxxD8MJNs9dp+5Eg7crgDpACafD3tGQ87O+pJ5LqZ8e0bOWfWOUflPp4MFEXhsssu4/rrr2fx4sWAKi/S0dFBRUUFtbW1SJLEnDlzWLJkCddcc+racp64h1VNq1jRuIL1reuRFZnJBZO5bextjM0dS7G1GCmUIl7bSfi1PWQ6YiAKGIc4MV+Ui3FINuJJdAt+WiiKQmd9mIYdnl4iFo+m2buhHUVSGDTUQUFaQtcRw6gVMA91YRqWjXGIE439+P8rmUyUQ/V/oKlpEYqSwaB14dYPxiKJiKEONP5mdEEPtkgGQ8qDQJ16oiUHXINgym1qXljJJDCeOgH/skGSkoTD2/EHNuL3rycYrEaWVecQgyEfk6mUHjEBs6mcoqJrcLtmYTKV9dYTibTEK1ta+Mf7h9jfGUGnERhb4uT22YOoKsmi3G2l2GlC9xXNJ+vJp+rBq6++Sn19PQ8//DDLlv3fc1M8GRzexbl+/Xquu+46duzYQXFxMXv37mXlypWsXLmSs88+mxdeeIGzzz77Cyvrl5KgfWXR9BFs+BOccbNaUXaj6w+PIQUC5D/x997GMZLM8P3ntrByTyf3XjiMG6d1N8zeOnjjR1A6lUOjf8TGp55m4sSJDBw48OTKsOFP4D9E15n/Q2Ldy5RVfTKVqYQks8oX4pXOAO96gsRlBZMoMM1p4wdleczLdR7XAFdRFBp9MVoDCTrDCdqDCTpCSTrCCTqCCRp8MbrCyd7j7UYtI4uyuHFaGSOLshhVlEVpthkEhYte+RXjcsdxZtnoY94rkpFY4QvxZleQld4QYUlGBMbbLfy4LJ+zXDbG2MxHRfcUWSa2eTPN//EfaAoL2XflFXz0xBMoisK4ceOYMWMGWVkn1kc7FcjxOL5Fi/D+/QnkaBTBbMYydTbmG2djGDwKOa4Q254k/P4upFASOZxCTkgoySMGNGhFtA4dSsqL1LWDVP0OlIQX87gh2GdOQz/wDHQDBnBgRy2rn/4HsVCQMZdezvQF12L8FAbmq1atQqfT8d3vfrd3W1VVFfX19b3rGo2GiRMn0tLSctLXbQo1saJxBSsaV7C1aysKCiW2Er418ltcXnk5JfYSFEWVnfC+vIvEHp9qvVNqwzGvAtPoHDSWzy7SEeyK4Wvrs7kKtMfYvb4Nf1tUVeI/TBi3xG1kUEbC3BpB4zRguaAcy4Q8NNYjoqGypAqz+utRfAdJBnYTiO3ggGE/SW2Gwo4UpY1RzHEPAnvVc5xlUDARBgzrHiWZpw76ya5Quyq/wshkomoELN5APN5ELHaQUGgr4fAuFEXN0bNah1FcdC1ZjvHY7WMwGo7fkyDJChvqPLy+tZW3drQTjKcZXmDn4SvGcOGogl4Xln8HmEwmrrjiCp599lk0Gg2XXnopt9xyC+vXr2fz5s0ntFX6ovFxka7PA1OmTMHj8dDV1UVubi4Gg4G5c+cyd+5c8vLyePXVV78maP8WSCfgtdvUboRzftG7OePxEFiyBMf8+RiHDQOgJRDnpkWb2N8Z4b5LR3Lt5AHdB6fgpZtA1JK8+I+89ozqEnDOOeccfb9jIdwOax+GIReyp11E1GgoHXnyeUwN8SRrfGFW+8Ks9YeJSDIunZYr87O5IMfBpCwLxhN8aR7yRFla28prW1s42BXtt8+s15BvN5JjMzBrcE5vF+XgPCul2eZjRsY+aPmQpnATt1fd3rtNURT2RBOs9YdZ4wvzQSBCUlZw67RcnOtgdradGU5rP+9MACWVIr5zp+oxubmaeE0NUjBIJjubd6qqiOzaRVVVFTNnzsThOH0NniJJBF56He+i51ESIuYzb0A/YAxSVIccThPfCfGdateMYNSiydKjyTKgyzUjmrQIRi2iWYvObSLdcYjA84vwv7oaMhmMI0fiuvFS7Bdc0Kun521uYtljD9G0azv5FYO4/Ke/IG/gp08V2LFjB+NP4HgBkEgk2LhxI7///e9P/EwUhTXNa/hj7R/Z49sDwNDsoXyv6nucXXo2lVmVyKE06aYIwdYG4js8ZDpiiBYdtrNKsIzPQ+v6ZMKvJwMpLXNwaxc717XSsvfo7sX8gXbO+uZQKsa4yezxEV7bTKYrjiCCeXwepmFGDNkRhNghOLRRHSzkr0fxHyIWPUhQ6CJgEwnZtMRNGmRRAAtYUwZGhUaT5R4G5YVgL1ST8rPLv1Bh6dMJRZHx+9fT1vYywWANyVQXstx/4IZGY8ZmG0lpyY3Ys6pwZJ2BXn/i3y/LCtWNfpZtbeWN7e14Ikkseg3nDM9j4cRSJpVn/1sm+EuSxLJly6ipqcFgMODxeFi9evUXXayvDPbs2YMkSbhcLmpqasjPz6ewsBBZltm2bRujRx87MPB54UtJ0L6SOWjrHwfPPvjmS6rmTzf8zz+Pkk6TfcMNyLLC2v1d3PXiNhIpiX/ccAYzBx/WfbbyV9C6BRY8zTsbdhIIBPjWt77V5xLwcXjvFyCl4LxfU//AIxQNGY7BfGI7p7gks6wrwL9avGwKqaSq2KjjsjwnF+ZkMd1h61X0PxyyrLC/M8LmBh+b6/1sbvDR5IsjCDCxLJsbp5ZRkWslz24kz27Eajj1V+35vc+TZXASMo7j5wda2BWJszMSx5dWo0qVZgPXFrq4MMfBxCxLvyiZFIkQ31JLrKaa+OZq4tu2oSTVqJ1YXIxv0CD2a7W0FBYwZMIEZs6cicvlOmY5Pg6KoiAFk6Q7Yki+BBl/AsmbINXkJeNPIGhcGEff2vfs0kaMFTb0pXa0ueZeUiYe48teURRiGzfS8Zu/ENu4EY3TSfb11+G49FIM3U4GAOlEgg0vL2bzslfRG42cc/NtjDr7XMTPYbRdXV0dVVVV7N+/n/nz55+wUtvr28tDmx9iY9tGyuxl3DXhLmaXzqbYVkzGnyBW00lHTTWSN6GeIICuyIpz/mDMY3IQdKe3K0rKyPhao3Q1htWpKYynOYKUlrG5jEy6ZCAlw7IRum9rMGkwxSMkanYTfvQthHgn5qwYptEptDQgNOyEbX1ehLIAfocOT64NT66OhE4CzOgEM1nGQbhsQzBlDcdsGYjDMQnxOPIgXxWEwjtobX0eKRM7ap+CTDCwmUSyFa3WRnb2DHIMBej1LvT6XEymEkymAej17pMmU02+GM9vauLlmmZagwkMWpGzh+Vy0ehCzhqS+28VLTsWkskku3btYtKkSZSXl/PKK6/gPo4H79dQ0ZODBmr9+uSTT6LRaOjs7OTb3/42ye52YuLEidx+++0nutRnji9lbfCVy0ELtcK6R2DoRao+UDeUVAr/4sXIZ87mqRaFZ15ewyFPlGKniWdunsTgvMNGbtWthA8fgwk30WgZQ3X1P5gyZcrJJ6Y3fQRbn4PpP6CxNUJXYz0zrr7huIfvjyZ4qtXLknYfgYxEhcnAzyoKOc9tp8J0bPHY9mCCZdtaef+Ah5oGP6GEqhvltuoZP8DJjVPLmTsqn4KsTx7dCGUkVnhDLGs9wEdNq4nZL+LOve0YRYGhFhNz3VlMyLIww2mj+DBNNd+TT9Lx29/RO1SuZ67RYBw2DMeCBYSKi9gQCHDQ50On0zFmzBgumDz5pCo0OZ5RE/J9CeRoGjmWUeUcOmOkWyLIh1syaUBJBpE8jSDEsUwejWVqFVqXCW228aT1xOK1tXQ+8j/EPvoIbU4OuT/9Cc4rr0Q8gnQ37drO8j8/SrCzgxGzzuHMa27EbD993bMAI0aM4MUXXzzmvp4ctLa2NmbNmsXSpUu55JJLevfLisz61vUs3rOYNc1rsBvs/HTiT7li0BXQniSxOUDnvq2k6kOggKEiC9u0InRFVnQFlmMS108KWZJpPxSiYbuXpt0+vC2R3jwyvVFDTqmNkWcWUlocp8S8D6HjTfioHiXQjuJvg4QHkQS9b54eiAP7NSjuShKlo4m5ziZoTOCXmwkm65CVFKJoIjt7GmWuWTgcEzGbB/7bRHQURSEUquVQ/R/xelep4re6Y/9PWayDqaz8CW73OWg0J+9JKckKtU1+Gn0xIokMoUSGjYd8rNvfhQDMHJzDf54/lHOG532ij8GvKkwmE+Xl5cRiMQoKClizZs0XXaQvPY5n/n7++edz/vnnf86lOTH+77zJnyXe/TnIGTjv/n6bQ8uX0xKV+WnhhXS8sZvxA5x8/+xK5o4swHi4nEHMB6/eCu4hyHPu481/PoXdbu8zQP84SGlY9gOwFdJeeAmv/vY+XMWljD67/8uWlGXe6gryZKuH9YEoOkFgbk4W1xW6mOboL8ipKAreaIq6zgh7O8K8vaOd9Qe9KApU5lq5cHQB4wdkM2GAkwGuY3dRnixSsswbXUGWtPt43x8hrSi4w68jALePXMh5BZUMNhuPGckDUDIZvP9chGHwYGyz1Wcm6A2YRo/CMHo0jZ2dvLFqFU0HD5KVlcX5559PVVUVRuPRDYScyCCFUmQ8cVLNYVLNEdItYeRo5qhjBb2INtuIcWg2+mIrgjFF8KWnCb68GNFqwf3d7+L85s2IJxsB7Uby4EE6//sRIitWoHG7ybvnHhxXXoF4hMF6Opng/ef+Rc1bS3HkFbDg5w9SPHzkKd3rZDF79mzuvvtu/va3v/Htb6vfTZs2bSIW64uUFBQU8OCDD/LAAw9wySWXcDB4kHfr32Vp3VIaw41kG7O5edTNXJt/FUJtFM9LNcjdivi6Agv2s0sxj89D6/x0ZtKJSJpIING7Hg2m6KwP0Vkfou1gkGQ0gyAKFJRbGTNBIEdbR056M1nJXQjRdtjVBTvVwSqKoEMSi8ikspCoRLBNQ1NSgm5gOaKrgKTJQEesmo7AGqKx/UjSBlX1IiZgtQ6jKOebZDun4nROOSVC8mWEJCWJxvYTix4kFjtELNY9jx9CkmJotQ4Glv+AkpLr0WqPLRtyJE4kGvr9O+5g2dvvEklKxCQR58X/ic7Rl3tWmGXkjrMHceWEEgodn12X95cZgiBQXV3NunXrWLVqFQsWLOCGG274oov1NU4TviZonxaNG2H7EpjxYzWRtxuKorD3mZe4e+ZtJAQtL33vDMYPOI7H3Js/Vj3rFi6mZvtu2tvbmT9//sl3bW74M3TsIDj7EV56+HdYshzMv/fXvUnhDfEk/2r1srjNhzedodSo556BBVxVkN0rJJuRZLa3BPjokI9N9T6qG/z4Y31RoTKXme/PHsS8qsJ+1lOfBs0J1X3gmVYvnnSGEqOem4rdnJtt4Z731jG8eAY/GDTqY68TWbeOTHs7effcjX3OHED9Stq9ezcfPvssra2t2Gw2LrzwQsaOHYtWq0WRZNJdMdKtEVKNYVJNYdIdsf5J+QLo8iwYh7nQ5ZjRuoyqKbZNr+aHdftMytEo3n8uwvvEEyiZDNnXXoPru989rs/q8SDH43j+/Be8//wnosFAzp13kH3ttYjHEEts3LGN9/7+OP62VqrOu4gzr74B3TEI5yndX5ZpaWlh9+7dJJNJLr744r5HIQi88sor3HnnnTz44IMYjcZemY0eRFIRXBNcNHobmfGbGQSKAgCMyx3H7cNvZWqkilSNj+iBvSCCcagL0yg3xkoHGtun197qbAixbWUz+6s7kDNH2vgqOM1Byi1NlGZvo1T4EEO0FXpSJV2DIHsgSuEYMnEbiS4n0fZ8MlIx2jw75rG5mEfnIDpEwuFddIS24PM9h69pLYoiYbONoqDgCizmgZjN5dhsI9DpvlrJ+5lMhGSynWSyE6VbvFZBIhLehc//Yb9RlCBgNBZhNpdT4JiA1TqEvNwL0WpPrW44lmjoq2++y48e/BOvrdqK9fKHKDIbOCNHYc7oUiYOLcVm1GI1aDFoxX+bKOSngUajYdasWcyaNYtRo0bxyCOPfNFF+hqnCV8TtE8DWYa3/lO1O5nxw367mjfW8APXTMImO8/eNJHRxceprLe/CDtegtn3EnMMZsVTj1FWVsaII5wGjotAE6x+gPSAs3j26ZVoDQbm3/trrM5stoZjPN7QyRtdAQQBznNlcW2hi5nZNgRgX0eE1w8088EBDxsP+Ygk1SjRQLeFOcPzGJpvpyLXykC3hWKn6bRUhrKisNYfZlGLh3c8qonyHLedGwrdzMy2IQoCL+x7AU/cw4IhC07uESx5AU2OG9usWQSDQbZt20Z1dTWBQABnlpPzJs1mWFY5dKQJPL1XlazwJegRQhJ0IroiK5bxeWiyDGpOmNP4sd1riiQRePlluv7wB6QuD7bzzyf3hz9Af4p6aRmfj8jKlXj+9GfSra1kXXopuXf9GO0xcuJioSBrnnqCXWtX4sgr4Iqf3U/pyDGndL9+985kOHToEHv27GHv3r1EIhFEUaSyshJZlvsJ8hYWFrJkyZLe9ZSUYkvnFm5edDMLly5kj28viqJQ8F+FDM4ZwuyS2czMTMKwI0HyAz/hzEFEhwHzWSUYq3LQ2PQoCqSBdHckTUEBhX6irsrhK8ko6Xicui0e6raFyCQSkEkipTKEEna0QpJKw3pyjHUoiICAVkjg0HvQ2WxgcYHRid90NZiyVWKWOwzFYCPVGCa6oY2MN45o1WMc7sAwyImSbSSiyBw6+Hu84SdRFDVHRacpINv2TbLMF2PQdY/CjkMirpDwKoC/u/yHPfAjeOORNPJINduj9594/f+zd97hcVTn/v/MzPam1a56l1zlbmEbbAwYA6aYDgFCgilJSIBAICTc3AsJ8EuFkJBwCSSEEkoSAoHQscEUF2xcZMtFlpusYvW6vUz9/bGybNmSLYrBydXneebZ3dmZc87Mzs555z3v+b7GIBWoeg+x5Fpi8sfIagO6EUU3ohhG4oDNVAxjYLD+gVik0bitl2AzTcYsFWOWChAFW6q2BMgJ2NuVgIPKMIxUG3Q9laLO0Ax0PSUfkxLhNahe0YxuwNJ3ttPWDd+4+wN2rNtGoTuT/6kYzfgcN5IogAGxmgAxoH3Ilg6NYYAqa8gJDTmuoqmD5/IdXmGgqjpKXCUZV1FlHTAGRFgYhk5I6iEihIiJYWJiFA11QBkH7rN/3UHXf99/AuD0mSey4NTZ/d/pus6uXbsY0xePWlVVRXZ2Njt27Biy6YIg8P3vf5/f/OY3ADzwwANEIhHuueceAB577LF+I8/j8fDb3/6WuXPnDlXcCEeRY9JA+7eZJLD5eWitgosfH5BqqTkQZ9HLu+lyeHl2UcXQxlmwGd78PhTMghNv44PFS0gkEpx99tnDN4bevgMDeG2HD12Ncdndv2K31cX9VbUs6w3jlkRuKsriuoIMMk0mllS3c9u7tXy0u5uuSKqjKfE7uGBaHnNGZTCr1Eem++gkL36vO8S9u1vYGUvgN5u4uTibr+f5B+Tn7Ip38WDlg8zInsFJ+ScdsUylrS2lJ3bOuTz952eo79gLQA7pnC5Ppqg9E7FdIEI9mETMGSnDyz45I6Wen+PEnONA+IQ6SMndu2m+4w6S22qwT5tG1u8fwlExPFFDQ9dJbKshumoVkQ8/JL5xIxgG1rFjKX7uWRx9U+N13UBTdDRFJxlLsOWD99j0zhIUxcLo468lo3gyDdugvnpnX4e3v+Mb+Bl0zUCRFSKRKIqsoCgqqqKRiCcwdANBEHHbJpNptWM1WWGPwAs/X9ffmeqajq4ZyKqCrChoqoahg2BImI0pzGUK+27hApBvFhhtk0BqIagbtCg6TbJBb0CB+gj8a88nOt9DIwH7Y/JUw8rOxDx2Mu/QTbuHKmPXoasicWiLw4pWBClJ3vFP4i7YQKhxBuGmGcS7y1Dj+zykvewzxr5QRBWzvReTvRezoweTo+/V3otkiSGa4ojmOBZX6sDVpItEbxG64kdXCtA1Cxh99xlDQE2kocbTUeNpGPr+rkGOZKElD9RViwE7P5dDSCQSnHnRKaiaTDDWwy3nPkBRxExF4Wk8+Or3+P5N5zEufzozx5xOYcaYIxc4TMxWCckk7pNRGxRFkImbwsSlaOrVFEEX9ht1oihgsoiYzCKiK3X/EARICDEaTLtokHYSEYOfW5sBCnQXC9hvoK1YsYKrr76aQCCAyWRi9OjR/PnPf+bSSy8dsgyr1crLL7/Mf//3fx8Sf/vGG2/wpz/9iZUrV5KRkcGGDRu48MILWbt27fBE0kf4XBEM45BntGOGGTNmGOvXr/+ymzE4qgwPH5d6Cr/+w36F7g2NvVz/l7XEghF+7W1l4Y8PMwvkXzdA9ctwwyraVRd//OMfmTlzJuecc87w2rDtVXhhEdudZ/Dm+gRTfng3z1n9LOkK4TebuKEwk0X5GeiyxvPr9vLMqnpaggkyXFZOHO3nxNEZnDg6g/yjHL+xPRrn3t0tfNATptRu4QclOZyb5cU6iGDqHcvvYGnDUl46/yVK04ZOUqtFZBoqd9P4+O/IXreCN85diODMYIyeS7l/FBn5WZjSrUje1GLKsCN5rJ9ZTd4wDLqf/Sstv38U1ZNJ+vXfwX7C7H6vzwADSaffS6C2NqNuXIe+pRJj2wbEWMp7GPcVE8ibTk/OVCLOAjTVQFVTRpmhH/6/KYgCZouIIAoIgoAgpp6OBSH1nSAKGIaOoijIShJFlVNP44KBIApIkojVZsXpdOJw2JEkEQQBUaTvNVWWikprvIWGcD29Si+6oOG2uch155DnySPflYsnpmMNyphDMuawjKAbqE4zsUI3iRxnSv+v79QL/a8H/hY6RDoIN7fS2xojGVNBjYOuIOsOQloOWl9ovj89SWGhjNcnIrgywZMDkiXVXlFAlFLnQ5RSx4BwcF2pLAyJmm7iNT3oUQXJZU4Nt471IUhCf1sVrY2W3tuR1Voy3d/D6/hqqqyDLyPhsB8PUfAXhvyQ2tQwFILRt+gOP4esNgx+AXCoB0gU3JhN2UiiF1F0IokOrOYyXPbZ2CzjEYRBHkQOafvhD+ZIz44xLYbSPxSaSmwgiPt+i9Trjo4wL21o4vEbFjL+9qeZXuLEm9zCS7/7X7755LfQ0VFllYaN9dRvrGfTW1VcdPcllB736RNXG4ZBXI8RUAIEkr3E1cE9hpqhEUgESGiJQb8fDnnOPCqyK5iaOZVcZy5emxev1YtZ/GyafR6LB5fls4WYuFwu7rzzTiKRCD//+c8HeNBOOukk7r33XubPn9+//Y9//GMAfvrTn36megFqamoo75Ob+k9gsOMRBKHSMIzPRYDumPSg/Vuw8VkINMLCB/vvWK9WNfPDf24mU43xi1WPcOorfxt6/5462PwPmHU9+Efx7nPPYbVamTdv3vDq766FV28m5irjhWqJ7VffzgNhM+54hB+V5nBNnp/1u3v40T+qWFrTgazqnDjaz08vnMSp47JSN8ujiGYYLO0O8ZfmLj7oCZNmkrh3dB7X5mdgGULJfmXzSt6ue5sbp954iHGmJ1SSe4IkawN07Gzm48BW6oQ2zq2uJJxfwsKTL2dUxXgsOc7+2LChMAyDWEgm1JUgEZFRZA1V1lGSGqqspV6TOkrfeyWpkQgniXUGiYcVFHJgZt/NahmwrHLIujI7NlBW9zrOeAcAsiWNHl850fLJaGOnY87wI5lF0swiPpOIySQimUUkk0iws4WGzZXEgl14MvyMm3Mi2aUlONMsuP02HGnWQX/H7u5uampqqKnZlhKNtUBWVhZTyssZP348fr//iPGNUSXKiuYVLG1YyrK9y0jYEpSPKueSMZdwSuEpZJkzSe4JEt/SRXxzF0ZCS6VaynNhmeTHNjYd69j0wT3BhgGxbvTOXXRv3kTbjjba2iT2xicS170IOHCaIyA37SvdAAAgAElEQVR5wWzC6rAwfnw2uWP85I3x4vZ9+lg7QzOIrmsjtLQBU0TBX5aGa04etnJ/yjA7gECwks2bb0A3kkyb+jh+/ymful5IBdknky3EE80kEs3IyU4GGcRE0xO0tb1CMtmG2zWRPP93BrWKBMGMzZqN1ZqLzZaL1ZqLyfTlJHfuinfxbsO7LK5bzMaOjYcOtQ6GCRAVxPE/YxOADTq7O1iy423c6X2TDErBWeqgwFzAineX0V7Y+pna6TA78Nl8FHuKsZvshxqjgCiIeK1evDYvPpsPrzX1mmZNwyodeXTBKlnx2z+dZM8XxU033cSUKVO44447Bqyvrq4+RO9wxowZPP30019k80boY8RA+zQocVj+ayg8AUanVIb/uqaBO/+1lVn5Lm5/6l6KLzwHc3b20GWsfBBECU68hdraWnbv3s2CBQtwHEG3DAA5Bi8sIiJY+LZ4JSu+diqYzHwzz89xssRH69o5tWYzvTEFv9PClbOKuHxmIeW5Rzf9S2M8ycfBKB8HInzYE6YlqZBjMfODkhyuzc/Abxn6cospMX728c8oTSvlG5O/AYDaHSe2pYtEdTdyU5iokWCTpZHtYhOiWWK+xYsjFiP/l7fhOXPmIWWqikYsKBPpTdC5N0JXn85VsCOOqgwdfyIIYLJKmCwSJkNBiASQAh3YkmE8kop3+gS8J0zH7jZjtkh93qsDPFiigBHoIfHYb1C3fYBUNhbbWV/HfvxsrKNHMdljRRpCz0vRFKq3fszy1/5GZ30tnsxsKi49n+Ip0/uMnTAxUoNMpJxw6LpOR0cHdXV11NXV0dubGm7LyspiwkkTKCsr608IHCOWmnl5qEwVhmFQ3V3N4rrFrGldg2IopFnSOKXgFM4oPoNSSzHRmk42rfqQzo5WgkIYzWxgHuPEnOfE7LfDPiNHBTYnINQG0fbUTOVYD8R7MaIhlK6TkXvOB30sMBbBEkXK78Va2otpjBkc+zv4JNDAXhoAWvuWI9AWbWN3YDe7A7vpincdukHhAe8r+5bDUf9l6CE5gLq+5d+DUWmjuH7K9fjtfhp7YqzY2Um4T45HMww6gkmsZpG5YzI4oczPt6Vv8D/H/w8W0QIdcL35elZ/czWbNm0aIBp6zRvXMOX0Kfzgsh98yUf4n4HH42HRokU89NBD2O2HH0ExDOM/bjLGUHmFL774YrZu3fplN6+fEQPt07D+KQi3wsV/BkHg9U0t3PXKVk4dl8m9DYuJKjH83zqMhFuwCar+BhWL0F05vPu3x0hLS2PmzEONjEMwDPQ3buOfRh53T/kFvfY05jmt5LSpvPT+Vp6VNdw2E/PHZ3H+1DxOHpt5VPPMJTSd1zoDPNXUxcZwqtf3miRO8Dr52Zh8FvjTBshjJNQEtcFamsPNNEea2RPcw46eHdQGapF1mWdmPkFiWRu9W7pQWlNT7JK5EltKWtjSvhPD0DkhI4PyQIDEW69iZGT0S2skIgr1W7uo29RFy84AiQO1yQC7x0JWkZuCch8evx1Phg2Hx5IyxCwiohlMVhFRVwm9+Sa9zz5HcucutAwvgYXH01JRyJ40SOpVQFXKCDlUfQO5oYH4hg0YHhXbD6dhGz8OxFbQXx4QumNgEJbDdMe76U500xXtJKz2JQ8u6lto5Zn6Kqgf5g/i7Fv20dS3fEqCcpAlDUtY0rBk/0oJyD1gIxVo7FsOQjBEPAk/+8bJfLFxnNBwHmnJTBq81ezMXEeHq4GwtSe1iQJs+/Tt3YdZgFyLwGizyIw0+lMGfZ4ICIiiFVG0IIpWhgpoEkULJpMHk8l90KtzyH0GHYo8hrGZbJyUfxKjvaOpbgnx4Ls7eW97BxmuYqYWpOGIaOQ0J3GnWbn6huNIc6SG+q5LLOK+K+4DUobAM08/c8yKhv6nceutt1JRUcG1117bv27ChAlUVlYOGOLcsGEDEyZM+DKaeFQ4XF7hY40RA+2TkozAyt9C6SlQehIf7ujg+y9UMbPYx+9PL6DlnH/ivfhizLm5Q5fx0e8BA+beytatW2lra+Piiy/GbD5yfML6tS9wp3Qqm8rHk9PRxILmECv3iEiiwPlT87lgWh4nlPmxHGGY77OS0HT+tLeTPzV10KNojHZYuWdUHqf43Ixz2vpzFB6IbugsensRNT01/et8Nh/z9Ap+8JYF99atoH+LZki5scTUPpqhUwaMEgREDERFIySJdI0uoOb4qTz91O+IhxXCsRhxU4ikIwpTZExmEcksIJlELDZTKih4HyoYbQbRvVG64l10x7sPjTm5GFJ/kQjwHrSCvdOOwzSEl1PX0SMRdFlGGG1GcnlBaoWmoV0+LouLNMmNq9vA2izg0jMpL5/JhIoTMZkPHYaUZZmG+gZ2795NNBrFZDKRnZ1Nfn4+Obk5hw5dGqAb8iHlQEoWY3XLata0rEFVo4y2+TnOW0aRLQ1i3SS6Y8gJK6oooJp70a3tGJYILlHDLRq4RQNDAn2Qa01XrITr5xLadQZabOBwj9ndgm/m7yjJqWb4g4ZHfoI3WzKwW3Ox2vNxmr0IMRW1O4HSEcFAQ8yTkHwSosnaZ1CJKEoPstxBMtGOrHSmahIsZGWeRVHRdQjCwFukIEiYzB7MJg+i+PnMbP53JqForNzVxYpdnSxe2UVN2x7CCRWPzcQPzxzHwjwfW95ppLE6jNVhomJ6br9xBv9eoqFfBoZhEAsG6G1tJtDehqYc+UFD1zVUWUaVk6jJJNPPPh9X+qGpsnw+H5dddhlPPPEE1113HQB33HEH//Vf/8XixYvx+/1UVVXxl7/8hTVr1nzux/ZlMZy8wscKx6SBdkzP4lz7WEqzbP5dVDb08J3nKhmT5ebxa2YQ+/V9GIZBxvWH8Z6F26DyaZh6BYozl/fee4nc3FwmTTq8wGhM07lv+24ei44hyxbknPdeINkOG/NO4VsnF3HdiaVke46+EKZhGLzVFeSe3S3sTcic7vfw7YJM5qa7DttZGYbBsoYP6Wnr4OsZX8EvpBOLR7BtqaNiyXIc4Rj1EwsI+yTiokxYjpBQE2jioS6qxkyRytECUXsL0JJa2RcaYhWtZDgy8Fq9iIKEQZ+jS0/CIHaK3WxnWtY0/FYf0pZdxD7+GNFqxTV/PtZRowCQRIkSTwnj0seR785HPMi7YRgGwVdfpf0Xv8RI6mTe+gN8i65CkA6vgB8Ph1jzrxeoeudNwMT0s77JrAsuxe4eOBStaRq1tbVs3lxJQ0MlZnMvc/NM5OfZSfM6EAUZgz3oyjaUWABVDaEoQVQ1hKoG+zWtDsYKnAucm7dvTXNq0QEbkL/vAMEquLGLXmymEgTRCpIZRBMmsweTOR2z1QdmL73tNpq32mjaZEdNiviLZAqnBJHMqSFLk8Uga5SIKF1x2HNjMrmx2wqx2wswm/3DNoTUrjjRDe3EqjpReyO0Tn6CcN7q/Rv07H8rCBIWSxY2Wx7pvtl43JNI887A7ZqA+BmDuQ/EMAx0TUVJpjpMpa/jVJXBDefPXiFoitJfj64fWU7CMPRUp55MosrJQSPIAjGZzmCMSDRONBanJxilozeMoClYBJ0xVhPTbSbcNhM+w0z4xaX8KyQjSgLeLDtuv53GzQKNmz//Q/48MfTUuVDkJKosHyJ98kXWL8diKMlPP1lBlCTGnjB3UAMN4Pbbb+fhhx/u/3z++efT3NzMnDlzEAQBt9vNc889R+7hHA6fkg/+8hgdDZ/XbO4UWcVlnHrN9YfdZjh5hY8VjkkD7ZhN9ZQIprxfY86kxjSea/+0mtw0O09fNwt7qJeWF1/Ee9GFmPPzhy5j5YOgKzD3+1RWVhIMBrngggsG6E0dzLpglO9ua6AhIfP1ljfI+aCKqOZm1Dfv4rGZpTi/oNQm3bLKzTUNvN8TZrzTxotTR3GSb79iuKIr1O5cS9srLyKtrkJNxFE0BVVXUVExMLgZgL8DIBpQ1godXrj/6xK7CrpxqC7Mqgmrno5dduOTC8l1FZBpy8RvzyDD7ucUn4fvZtjw+B3YPeb+ztsiWXCYPnlWA6W9nebbbye+vhL3mWeSc8/dwxaZVXt6aLv7bsLvLsV+3HHk/fxnWEpKDl9fIkHlW6+y7rWXUBIJJpwyn9mXXo7kiNAbeoeGlk1EI/XE4nFisSjxeBizOYg3PcaB91lZcdLbaU5lktAURF3HrOiYFBWbrGJWDcyqgaRqCAbogkDAbCOkKxiiiMviwePMwiRmkQhmowXTkJJOJMOJIy8T1/RxOIrzMZvTEMWhJxVois7GpY3UfNRCqCuBZBIpnZrBtNOLyC4dPO7RMAzi4RD6EB4UAHSQoyAPIWFhGDqarJAMRonu6CCyrZ1ESxDNUBByzPSMeptYZCf+nvNxusZgtWSnkm73GdiaohDY20pLy14CrS2o6jpgHRgGmqqmPBByEl09TBuHgaapGMMwkv5dMABFMGEXzYyyWnE6bLgcdgRRQ1cVoh0ybTEFQRBweCzYXGYEMUqkN3rEso8FBARMVitmqw272/OFDzcLgoDJYsHc14a07BzSc/Px5uRith75IVwQBMxWKyaLFXGQh8RIJNL/Pjs7e0A2EIAbbriBG2644bMfyAifmWPSQDtmWf0IJALUT7+Dq55Yi8Ni4tlvzCLTbaXjib9hKMrhY8/at8HaP8P0q9DTS1mz5g0KCwspKysbdHPNMPjlzmb+0NyFLRHnnzv/G6VNZGPMzbd/fhc5ZZ+fLtBQ6PE4XY89RntjE6sCEU7Qdb7hNJEuxAnKAV6TwyTUBAk1gbM7xvhGnWygLltEtlkwixJmyYldtJBUk1iwYcOJlhRBlWgqKKCu5BxO6RSZpdYToQ2bxcmsaScy84QKXOmD5wX9vIis/IiWO+5ATyTIu/8+POedN6z6DMMg8t57tN59D3ooRMYdt+K6fCG6JJJItPRvo6oKSjJKItFELFJLa/0aulpqQEow5iILNo8JgydZv+V/+8vWNQvRiBMMkAQDp8mEU0nHGfJg7enBEoxhiapISgLNEFF1EcWeje7KAYsLrG4wpWKiQmqchmgLa+RudogqDpuPufkncnzuCViTJgJVrcTqutEEDXO+E1O2HVO6jV5DR92wGWXVWjR16GGVRNRGa30uctyG3RXGn9OJ2dZOpEtm5fOHbq+rCuHuLkJdncMarvnUdOx7k08DuxhU6wwQRBFvdi7puXkDOj/JZOrrpK2I0me7TYqShNlqw2RJlWeyWjFZLKkh7KN0aZvMFkyWVD2DddIHs88o2LdPWyjJr5fsYEl1O2aTwKwSPyeNzmBqcTq5PjcZbitW0/5yYyGZyrfr2bq8GckucMI5BVScWYzN+fl5Ikf4z+JInq6jxeHyCh9rjBhowyXWA6v/QPvoy/j66yE0Xef562dTkO5ATyQIPP8PXKfNH1pF3jBSKZ1sHjjtbnbt2kVvby+nnXbaoJtXdYT4xqY6mk0G5rYo7+69jXytl8fqRzPnsiu/EOMsuaeOpu99j+Tu3fSkOShHRURFMzTCgAj4BQnREBF1Ad3spG36OHzTzuKE8llYir20hhW2rW9n164e0FK9UVqmndzRaeSO8jKu0IWvbRdL338HXdc5de6pzJ49e/hprj4liWCQ2t8/SOebb0BBFq4rvsY2oZ7oX39ELNqOIgcOGOYxEM0KokVGNCugqxiJBIaqIn1bx+xTaXbcD2vuP2K9miBgTTehJiTivTLhNg0tYUFN2lHCZqIddpIBC0P33Ifz7OmkpnaGDvkmAz/7JCmjrOV91h66e+fAj4IoYrbakMwpL6VBGqnpj6mO2RAcQDEQRzDeQY21E9OsmONWRNPgRoEoSmSWjGLUjBNw+zOQTJ+sA9fCSZK7gyT3hhE0A0u6E1tRGkJBGNXeRlKtJ5rYhqJ2Mbrsh2RmnTFkWYIo4snI/MRt+E8kEJPZ2xunpTPO1uYO/ryiDt0wuPnMiXzzpFIcB83A3rq8mQ2LG/qzPMQjCrpmUH5iLjPPKcWVfnTErkcY4bMynLzCxwojBtpw+ej3IEe4I/JVeqMyf7/+BEZnpYb3gq+9hhYI4Fu0aOj9t7wIDR/Beb8Hp581a97E7XYPELlTNZ33t3fwm5omNrkFkATmRCT+nPER/p07eL2jgswxE5l1wdAq0Z8WQ9NI1tamAt0Nnd3rliL89s/EBY3fXyawuSxJliOHye5yxjGK8XoZYxJFiDVx9LCCbVw67tOKsBS4iQSSbFvZQvVfdxAPyXgybLQUVdPlbeS3l/8MpzflqQiHw7z55pts376doqIiLrzwQny+wWMljkQ4vI1gqKo/XsQwFBQliKL0Iis9JOKdxMItyHIPuqZgGDpUgHi8jmTuJUgqNYrgHDgJcuA5ktATEoaigxsEkxkEJ0LCjRFwIspSKv2XoYGuIMphhGQQiyEjxgSkiICQBLNgYBaTmEQd8aBoH91jRigqQPDkgysLHBmpV1/ZgGwV+0h5Siz0aEF2hXazvXs7O3p3sCe4B5tk49zChZwlzcPUrCLXh9BjSirHaI4TS7EH1/RcbBmePk/RfqNKlCQkkxlF1ti1rp2aj1po23OQ4SfA+Nm5zL10NFbHeRwtDN0gsbOXyMpmkrsDGKYMTKfJyOMaCapr6OlZhaalhm1szjxycieTl/sVMjJOPWpt+k9A1w2W7+rkyY/qWb5zoHW+YEI2Pz53AoW+QyfE1G3uYtnfd5Bd4iE9N3VNWqwSk07JJz3ny9FhG2GE4XK4vMI7duygoKCgf9sHH3yQr3zlK19aW0cMtOEQboc1f2J50Y0s2xnnroXl/embDMOg55lnsJaX4xhKJiMRhCV3Qv5xMH0RHR0d7Nmzh9NOOw2pr1NcvrOTWxdX01rowPBbyNUFfj+hmJNNHRh/+i3NlFIX8XPVT74/rCGL4aJ0dBB86SV6XngBrbWtf70Z2JEvcP8Vkxk34RwW55+CbWWMeOX+fDmiM4Y5z4X7ykLEHBft9SG2PraVus1dGIZBySQ/k04pQM7t4f43/swPZvwAp9dGc3Mza9asobq6GoAzzjiD2bNnHzYOb9C2K0E6O5fQ3PI8odCmQbcxNBtaQiIR1tESEoJiwxQRsAgirlGjceaUYrH4sFj9OJzZ2J05mM1eJMFJctdu4uvWEFu7FrlyB8Q0kES807PJnCViSu6F6N5B69UEM11xK92KG2fZ8eQePwuLxw8mW0r/DlAUhVVrK6lr7qBs3CTmnHEBJl8JHOE8JNQE27q3salzE1UdVWzq3ER3IvW72E12TnLPZpH5Sib0FKOtioGuIzoseCeNwT7Oh3VsOtIRhp6SMYWN79az6b29JCIK6TkO5lw8mrHHZ2NzpfYVAPEoSrjoSZVYZQeRVS2oXXGUnDZ6F7xFxLQVRe2BVrBZ88jOXojfdzJp3hlYLRlHLvj/ID1RmXeq29jRHiYua8QVja3NQWo7o2S5rdxy2hgm5HrI99rJ89rwuwb3gHU1RXj3iWoyC91ccNt0zIfJVTvCCMcqB+cV3odyNMMuPgUjBtpw+Oh3aKrCL3rmU+gTuWp2cf9X0Y9WIe+uJfdXvxw8dknXYMn/pGZ+XvkPEEXWrFmDyWSioqICwzD4w7JafrWnFXVSGh5R4t6x+Vye60PUFHjim2hIvL4ri3nXfpP0nLxD6ziI+JattP74x2iBwP5mGDqaoaHpGpqhofe9t4eSSDpsLhFYsVBEtpkYnTaWmFJKKGsB9zmzGb8dkq/vJWGVcJ9WhGlcOnsbw+zZ0k1nbYj4xqr+xMM2p5npZxQy8aR8PBkpAcQH1j2FSTAxxzOHp556ioaGBiwWCxUVFcyaORMhGWfHquWEOjtSaZIwMIiiKD2oWg+qHkIQY2CKgxRHsAQRLD0I5j6dtKCdzq3ZBOvdGH3DqIYBWlLC6nCRWVRKQXEZzrffwbKlGu+lF5J9+RykvcthRz3I1alodE1Glw26NyTo2ZRET0kwYfUq+AqTOLOTOLI0xAwR0krAeyakl/QvqtXH5pUrWfP6a8RjSSbNX8Ccr3ztkBlUsixTVVXF6tWrCQRsnHX29cyaNeuIsW+rW1bz6KZH2dK1BVVPzW4tchcxJ28OUzOnMl2ciG+DRGJtF+gg5os45hViG+fDUug+bJorOa7S2Sfk27U3Qt2mTuSERtFEP8edVUTuaO8XJimh9iSIrGohuq4NI6lhKXRjXNxEfeznSJIdv/8U0r2z8HpnYreXDLtd7e3t3HbbbXz88cekp6djsVi49dZb+dGPfsTq1av7cw3eeOONFBUV8aMf/ehoHuZRRdV0treFWVffw9Kadj7e04OmGzgtEk6rCYdFItdp5aYLyzhjQvYhWokHawhC6hp585FNWGwS59wwZcQ4G2GEo8wxmYvzAJmNb+3aNXhw7xdGrAcenMgLGTdzR91UHr5yOudO2W8kNV5/PYltNYx+/z3Eg+OmevbAv74De9fAnFtgwU+JxWL89re/ZfLkyZx+1kK+8+pmllpVDI+Fr2an8//GFuDeF7/z3v+DFb/htZZJaKMWcOEdPzmkM9INnV29u6hsr2R7z3ZyNjZx0mNrSbgs1I1xE1NjxNU4ujFwFplJNKX0vHxpdJ06BVfpWHKiPkbvKcKyPYG1b+KaYJUQPRbkTAetVhPNDWHa64IYBrjSreSN9eL0WLF7LHj8NgrKPTRv30LdxkoiPV2Ee7upbdmJlFaAmpaDYOi4owHsiQiiYZAIhcAcxZ0Xw5ETx56exJaexGQ/dOacYYAum1CidpSwAznkQI/l4vVWkFlURlp2Tv/5kUwm/AVFuDxuoq88Tvi5h7B4ZDwzSjBHdoASBbMDMsaCxYVhdhDcGqbzvRbUsIJ7Qjru40pwThmPKa8YvEUpQyytICUxMaBdBrvWfMSy554k1NlB6bTjOPlr15JRVDLwUorFWLVqFevXryeRSJCXl8cZZ5xBaenh8ws2R5p5YN0DLG1cSr4rn7NKzmJq5lSmZE7Bb/ejxxR6X6slXtWJYBFxzsrFNTcPk3foGV9yXKWhupvWXQFaaoN0N0f6sw45PBbyx6Uz/YwiMovcQ5bxeWIYBnJdiPBHzSS2dYMA9smZOOdk06w+QX3Do6SlVTB50iNYrZmfqvw5c+Zw9dVX9+sfNTQ08Nprr2E2m1m5ciXPPfccGzZs4JprrqGysnJYuoTHEk29Md6r6eC97R1U1vcQlVP/obIMJ+dMzuXsyTlMyPUQDST58G87aNgyZPb4ITGZRS76QQVZxUc3K8kI/5mM5OL8ZByTHrRjSmZjwzNEZY0HOiqYXuRm4eT9ejDJPXuILl9Bxi03H2qcbXgW3v4vkExw8eMwORU3tmHDBlRVxVVYztzn1tBa7MAhWfnjpBIWZKbt379hNcbKB9kWzidgn8TFl34NtS01BGkYBlu7t7KkfgmrWlYRlsMAzNvj4JTFYZryLDx+lR9rVjZ5zjxyXDnkOnP3L65c3GY3hqwRr+4mUdND4uVeDFkjaE6yJN/CrOPysAZ1dm5spHX7HowaDVESSM91Mu54D3ljvKTnOlCTSaKBViI9Pez6uI63H15NMhrFbLOTlpVNkxBGKSjHkFz4bSZG5XRisgcQTDGQYoj2HjCnUvFIkguncxxOx1iczjJsthzMZh8Wix+zxY/Z5EUUB7lkdR0SAYi0Q2AvBBuhdQ/G2rXQtAGXoOGaDoZoStU79XIYezaUngRmO7HKStp/8UsS1Q3Ypk4h/0c/wjF9+rAuj1BXB+898Sh7Nqwjs6iES+/8GcVTpg3YJplMsnr1alatWoUsy5SXlzN79mwKCwsH9f4YhkF9qJ5VLatY3bKa1S2rkUSJW6bfwqKJiwbkA0zWB+l5fgdaSMZ9aiGuuflDDl+GuuM0be9lT1Une2t60FUDs1Uiu9TDzIWlZJd6yChw4Uz74gK8lc5YXz7PThKd3SSz96DMb0L2tZJUm4nX7UXXE+TlXsa4cff0Ccx+ct5//30sFssAccri4mJuvvlmdF3n6aef5oMPPuDOO+/k4Ycf/rcwznTdYEtzkKU17by7rZ3tban7QFmGk4srCphRks6MEh/53pQn2zAMala18tGLu9A1g+POLsbu+mSTcXJHp40YZyOM8AVxTBpoxwyaAmsf4xHXzXR0azy6qHxAh9r7t78jmM2kX375wP3WPAZv/zCVbeDCRyEtpYsWjUZZsXIlgieHa9a0oIz3Mtlq5W8zRpNpOaBDkKPoL32TQMhB0xY/09tXsXfJwCBsO3Bh37KfMK5TT+WM3zzAmYfJ6anLGuFlTUSWN6HHVES3hYbRLp5VE2gJnZl7NrF8xcMYeggY6MlqDUBrDVS9fWi5FruD0TOOZ9yck8kdP4EnXn0KeUcnVgecc7oXWX6DWCyVV1CSnFgsfuz2cnzpc0j3zcHtmjC05lCkE5pWpqRKeutSieoDjamUW/EAByedNiQriaCVWLMN07Rz8Cy6DSFr7ADvl9zURMcDvyG8eDGmnBzyfn0/noULEYYRC6frGhvffoOP/vEsBganXPUNKs4+f0B8oKqqrF+/nuXLlxOLxRg/fjzz588nKytr0DIbQ428VfcWb+55k/pQPQCF7kIuGXsJ1026jhxnzv6yu+NE17YRXt6E5LORdcNULIUDvV2R3iTNO3tp3tFL885eQl0pwUu338bkeQWUTcskp9RzVOPIBkOLKQQ31NCzvZKYsoukuwl5bDOJKY2AjiCYcGqjcdhLUrFlaRVkZp75mYZYq6urqaioGPQ7URR59NFHmT9/Pueffz4nn3zyp65nuOzd3sPiP25B1z75CIYBqLqBpusYRmpO7TmCwHmiA1EUEKNAQxdtdPHGgfsZoKk6eWO8zF80nrTMYeT9HWGEEb40Rgy0w2BUv8qjPRX8Qa3goun5HFe8P5ZIj8cJvvoq7gULMPkPSGWz+cWUcTZuIVz2TMqD1sfri98lkUjyUloRyngvZ/o8PDa5BOtBBkH8xZ9iaS8AACAASURBVLvofjdCoMFDvtHFRxMEWsb4+jsorzWdaVlTKfdPwCrtfwIWXW7cZ5w+QMHeMAy0ngRKV7z/NbaxAyOmEk+zssUrsrM7gbMpygSlFSX2ASGtDXdGMcVTTiKzMBtnug9pkLRDACaLBZc3HafPj9lmQhCgtraWP/75ASzmWkZNa6TYFyIQCOJ2T2LSxN+TkXEaknT4BL3Ee6H2A9i9FGrfTxli+7Cm9Q05lkLxHLD7wJ6O4cxA7tEJfLie3n++i+j2kH//fTjnzBlQtBaJ0v2nP9Hz9NMgSWTc/F38112HeISkwftor6vl3ccepn3PLkqnHcdp37iRtKzs/u91XWfTpk18+OGHBINBSkpKOP300wfMDjqQ2kAt96+7n1UtqwCYkT2Dr5V/jRPzT6TQvT+rt9qTIF7dRWxzF8relLfEMT0L7wWjEG0mYiG53yBr2tFLsCOeOl0OE3ljvEyZX0jBuHR8ec4vLJ5M15NEIjsJh7cTbNlMuKeauLEHzRKGPvk/izkLl3scuZ7z8HpnkpZWceTr4zNy0003sXLlSiwWC+vWrWPatGlMmjSJG2+88ajWu4/KtxswWSTGHZ9z5I1J5W0NxhW2t4XZ1hJC0XSKfQ7KslwUpTuwmYcXD+bLczLu+JzDxiOOMMIIxwYjBtoQGLrOL9/cymPqV7lgai73XzplwPehtxejh8N4L79s/8pd78Ir34HiuXDpkwONs4+3UbOlipq0IrrG53Flro/7xxYOSCQu791L54P3EXx7KYro4L3pAq0XzOKbp/8343zjhtduw0BuChPf2o28N4TcHMVI7E+XpAHdis72hE53SKHDI6F4knhYRbxxPY40L6d8/fuUz503wJNkGDrxeAOh8FYUJUBUiVAXrCMcacYa7MBW247J2K8UPmVy6lUypZPhP5Xc3EtIT5899ESKzh3QvB6a1kNzJXRsA0MHmxdGnQoFMyFrAmRPTMlOHIAWDBJ8/Q0CLz1PsqYGwWrFc/Y5ZP3gdkwZ+2f1GYZB8OV/0fHgg2hdXaRdcAGZ378Nc3b2wS0aFCWRYNU//0blm69gd3tY+L07GDf7pP5j0nWdrVu3smzZMrq7u8nNzeX888+nrKxs0OOOyBEe3fQof6v5G3azne9VfI9zy84d4CnTwjKR1S3Eq7tR21M6PeY8J2lnl2CblEEgprL+3Ub2bOqiuyklNWGxSeSN8TLp5Hzyx6bjL3AhfkEdsq7LBALr6O1dTSBYSSi4Cd1IzbYQNAvWeAFe6xzSMqeSVjAFl3NcSt3/KDNx4kReeuml/s9/+MMf6OrqYsaM/aEioih+4pnEn4bu5gjNO3qZfdEoKs4sHnSbmKxStTfAxsYAlQ29bGjsJRBTEAQ4d2YePzh1FONzRoYaRxjhP5kRA20QDMPgv599n+eDM7m6LMLdl08/pIML/OMfWMrK9ktrdGyHf1yVMiC++ncwpwK020MJnlixh8Y1b5FuNvPxxEl8uyCTe0bn9XfaclMTXX/8I4F/vYIqaLwzQ2Td8T5uvfjXzM6bPaw26zGF8Mpm4ps6UbsTIAqYc51Io730Kjo7dvbSFZBRMqysGWdnkxtsmWauatqM+u5rJGWFmRdcyozzziah7Kax6UmSiVaScgfJZBuRyM5+ral9WIB0A9pVgT1xO/aeSUi6iU57Jz2OEBdO+QEnll05+LBlsBm2vJDyjjVvhL44OmzelBzJ+HNh1PzU+yGU3OObN9PzzLOE33kHQ5axTZhAzt0/wbNwIZJnYOeldHTQetddRJevwD59OtmPPoJ98uRhnVuAuqpKlj7+CKHOdiafdiYnX3ktNpcrde4PMsyysrK47LLLKC8vH9JTtat3Fze9dxNt0TYuHnMxt1Tcgs+231AxNJ3IqlZCSxswZA1LSRqJmTms3tBJsiECDRGMf+1BTmgIAuSMSmP2RaPIH5dOZqHrqA5bGoaOLHeRSLSgKL2oahhFDRIIrKO7e1nfdSJhj5eS1j4Pe2QMadmTSSufhH18JuJRnv3X0NCAJEkDPJb7xCkfffTR/jQ2X5Yw5eb392Iyi0yYm5pstKMtzLvb2mjqjdMaTNAajFPbGUXTU8Ofo7NcLJiQzXHF6cwZlTGoNtkII4wwfNra2rj11ltZt24dVqu1XwdNURRuvvlmmpqaMAyDRYsWcdddd31hIw4HM2KgDcJzaxp5vibJjdbF/PDqXw4YDkjW1hJ8/XXimzbhWrCAwPPPp4I7Vj0MUSfkfx3+9SaN3TFW1XazrTWE2QU5BSYCmoVfbN/AOV21BNanykts20bgX6+gobNkusHqmXByzMuz31qKZRh51+CAQPFgEusoL46T8tm8O0RtdTeR6lQeQ73AzlvT0qjyw7xACzc2bSf51nri0ShlFTOYdH4eXcG/snrdT/vLlSQHZksWccNMreJlfUCmSZEo9U1nRs5MZubMYJxvKq0tXTz33HOY09K48NJLye7zSA24qDUl5RVrroRtr8KeZYABOZNTQfv5M6BgBvhGHVEHTAsE6PjNbwm8+CKix4P30kvxXnoJtgkTBt0+tHgxbXffg55Mkv3ju0j/6leHFWcGkIhEeO/JR9n+0TJ8eQVcfs+vKChPJbYfyjAbP378YT0xa1rXcNsHt2Ez2Xj2nGeZmjl1/7GFZRI7egivaEZtj2Edm473vDKaWqIsfbwal9fK2Jn7PWwZhS5KJmfg8BzdzAuxWAOtbS/R0bGERKIRXT800bdZ8JEWm42jbhL21nGY07y45uThnJGNaDv6txrDMFi3bh2LFy+muLiYq6++uv87QRB45ZVXuO2227j//vvJzMzE6XRy3333HfV2HUg8IrNjbTtZk308ta6RV6ua+4P7M1xWctNsFPmcnDkxh4ridKYXevE6ju5vO8II/5cwDIOLLrqIq6++muefT+Wjq6qqor29nWuuuYZHH32UBQsWEIvFuOSSS3jkkUe46aabvpS2HpMyG/uYMWOGsX79+i+0zprWEBc8vJLZRhVPzUsiLrgXAKW9g66H/5fASy+nZg0OE00UeWvhOVhkmTPeeRfx4PNtNvPxLDdPTQ9yjp5kUVsU8/XLyCw5cionQzcIf7iX0NIGJK8N3xXjsBZ5WP6PnWz5oInSaRl0FNj4XylKsxUuaa9lwkeLSXS2YbbZGTPzBMbMnUjI+Cu9vavweKaR4Z9P3JTNtkiED1rW8XHLx8i6TLYjm0vGXMJFYy4aMATX3NzM008/jdvt5tprr8XV51UCUsH7W19KZVFo3gBan7BYeglMuQKmXAb+UcM+l4ZhEHr9ddp/dR9aMIjvqqvI+O53kVyDq5cbhkHnQw/R/egfsU2ZQt6vfoW17PCSFgfStnsnr//uPiI93Rx/0WXMuvArRGMxamtrqa+vp66ujnA4TFZWFvPmzTuiYQbweu3r/GTVTyjxlPDIaY+Q48xBaY2mZtJu70FuCoMBJr+NtIVl2Mp91Kxq5cPntpNZ5Obc707F7j66HbaqRgmFNhFP7CUR30sguIFAYA0g4kufjctdjs1WgN2Wj9mcjlqrElnciRhyIjmt2MamY5+Uga3c94XFOimKwptvvklVVRVjx47l4osvxmYb3gPOF0FTb4wl1e3s+rCZwiaZJ90JuiWDiiIvF0zL55zJuWS6R9IjjfCfzbEgs/H+++9zzz33sHz58gHrn3jiCZYtW8YzzzzTv662tpZ58+axd+/gguT/J2U2DtBB+0LrjckqN/99I2ligp/ueJKWwGnw5q0Ymkp05UcYmkb6FVcQeOUVnHPnkvuTH0OkA548C3ImwleeYXF1Oz95dSsTS9MpnpnD1m1bmbZ3F6bTz2bMnXfy8u6X+aj5o/46N0d3olrhdnUaF9e+zs7J/8XYIxhnhqoTq+ogvKwJtTOOfWom6ReNRrSZqNvUyeb3G8idEOEtXw9bOmLMtMD3Gt/D0HbhO0EgvcCLzW1CECrZG3gSQTDhyb+BF1vbWb/nJTrjqbQv+a58Lht3GacWnkpFdgWmgyQuWltbefbZZ3E4HCxatChlnOk61C+Hjc9BzeugJlKxY8dfD3nTIa8iZaB9Qpex0t5B2913E/nwQ+xTp5Lz5BPYxo8/zDlSabv3XgIv/pO0Sy8h9+67EYYpnWAYBlVL3uDDZ57AmZ7OFffeR2bpKJYvX87KlSvRdR2n00lJSQkTJ04clmFmGAaPb3mchzY+xMycmTx4wgMYywK0bV6LFpRBAEuBG8/pxdjKfZhyHLTsDFD1yGYatnRTOMHHWddPwnKUPVGdnUvZseMnJOV2AARBwuEoY1TZ7eTkXITNtl9mRk9qBF6rJV7Zjr0oj7Svl2EpOLwg7udBIpGgqqqKrVu39it/x+NxQqEQ8+bN4+STT/5CYsmGwjAMmnrjbG0Osrk5yPKdnVS3hBANuDFqJ+E38+NLxzGr1Eee9+hOhhhhhGOVwOu1yC3RI2/4CbDkOfGed/iH/q1bt3Lccccdsr66uvqQ9aNGjSISiRAKhfB4vviYz2PagzaudJLxx//34hdW35PNnawMhPlF67tMW7ME1ZuNYUp5K9ScUiInX4GloZq0N/9A96KfoxSWM7HtTvyxFawreI5lcR9/bOogL8dF8+Q0dF1l0Zp38ZjdTMmZy/P8iUpWkkcxdlJxJG7SODd5Pmc1fJO44Wbb+FeHlJowJ1XcQRlPbwKzqpO0SfRkOIh4LBiWPciWp1HUesyOEGaHOmgZqBmgZbMvGbeuZvBe0MNb2ns4cDGeqYwWyhlFOdnkDzn2Hkp0s6V1OZIgMS3vFDKMVjKiK8gJv4ldbUMR3bS7FtDqOY+IZdwnNsj2YQBKYyOxjRtB07FPnoRlzJghU4kDiMFOPEsex7ZrHZETLyVyyleHXX8y1sveLS8T6tyOJ6uckmlXENcT7OhcS1QOku0qoTB9PA6zZ9hxCToGVR0bqQvWUegqYr51IpkdcSTNIOq29C+aScTQDYJdcXpaoiSiKpJZxJfrICPfdVQNH0PsxUh7DBwrQClBCC0CpZhozERvvBNB07HFVawJtV/RRDQMBB1iLjNxp5mhE7x/fsTVCB3hBjRDxWVNxyql/keCADnuMvzOI2faOFqousGezijb28JE5dT/TxTA57RQkO4gy2KmvaaXhTdOoWRKavKKJElMnjwZVVUpLy/nL3/5C2eeeSZ33nknZ599NgAvvPACTz75JIsXL/7Sjm2EET4PDvQ4fVkG2kMPPURdXR0PPvjggPW33XYbpaWl3HLLLQPWp6en09jYiNt9qGj3/0kP2j7kuErD1k+udv1pqEJmhRDnJBXGVFeRcGSw+aR7MA70GjXDhNWLibty2B3IpCD8NlnW99igXMXinVaepgN/uo29Ez2kxXSurNxBkiRioogH0u6i3d7A3I7zmdV1FsIBnVla5DekZSZYF/s2TX0xY/sQMSgEcgFX3y49BtQDPXEN9oZwFS/GO+ZFBFlADdvpjBWw11VKWbcNm2KAAFqiBCU4Di2ZCkRXBJnd7ipWZb1BwNLJ5N65nNx+ETY91eElgUZ6Bj1XCbGLDssmbKicp1cyqvFBLEIcwxBo0aexW1tEozYbLWqBdmCIco6EYRjo4TB6IoHgm4jk8RBMSnDwNWHoOAONeNs2kd6+CWdwLwYCdVOupCPjVKg+cv2GoZMIVRILpNzeDt9pGI5yqurWEZXakLCSJU/DHs+gq1M97DEZgGao6EYq8XxCTaBpdmaYZzEzaSdNiNFrwA4gElL4/+ydd3hUZdqH7+kzmUnvvZIQEpIQepUqRVBRxIIVxe6KZV1d66er67rNXrCBiiIiSBVECAjSQkkgEEjvmUmd3mfO98dgIAJSREU393XNBcw55z3vHJI5z3ne5/n9MLoQBDMuhxe304MggEgsQq6SIJWJsRqc1BnO7Rr+xCdGLDegCi9CFbkbZeghQIShfDqG6snYRSaM0v3YJT86r4jucZgE3w+L4zxP75TTFqP2RBLgjkdh6/5Ea24DM7/O9wWAyyvgFQS8XvB4BaxON14B4iUilHIFMrEYqUSEyAO0OTHjJD4zmMTsY7I8KpWKoqIiAGbNmsU777zD22+/zVVXXcWYMWPweDw8/vjjPcFZD384ThdI/VJkZWWxZMmSk77/42XPqqoqNBrNSYOzX4MLOoP2a9WglTQauPKtbfRPCOL1ojvQbXQR869/ETj1km77OWtqqJw0mYiHHyL0hmvgzSEg12C4aQOTX9uBK1hOW29/okSNTJGW4iowolfoKYgowE/qx4sjX2RMwphuY1bs2o7myxkEBqpRPXq4q0BeEATspR3oV1Xh6bAjTw7ELycMVVYokgBfrYrD2caB/fdjMO5AX+1P044JHBh6KRvSAlmR34sszYnLJ0c6jvDp4U9ZV7MOi8tCUkASTw55kkHRg059gQQBdCVQWUDZgUIWaxMJxsANfElAWBwkDYfE4ZA0AvzPTNfpdNgOHKDxwYdwNTURft+9hM6Z003fDcC6dx+G5csxFxTgbmkBsRhVfj/8x4zFf/w45IknlzD4MY1HStn44du0VFeS3G8A/a+8jl1FxRw8eBCZTMbAgQMZOXIkqp/QSbO4LOxo2sGGug1sbtiM0Wns2iYVSXnF/zlS9gQjVogJnJqKX144IpEIj9tLyeZGCldX47C6ic8MJnd8Agl9Qs5r55DLpae9fTMdHVuxWCuxWqtxu31zFBGOThdLXV0CNtsxNwu1WEkfRywZ8ngC86NRD4xCGvLbLsmJxWKk0t/muVIQBPbW6Vm1v4k1B5rRGbtHpSPSwrh3bBqDk8/8/06j0WA2+7qj3377bfbv38+bb77JI488glqtxmKx4O/vz5NPPnneP08PPfzaXAg1aIIgMGTIEG677TbmzPGZFRUWFmK1WrnllluYN28e48ePx2azcdVVVzFx4kTuu+++k471P51B+zXotDi54+M9hKrlvNqvhY63bSiSEwiYMvmEffXLl4NYTMC0S6HgBTDUI9yylsdXHKFRbUce/T0BzdswOxs5qM+it7s3AfkBPJz4MGPix5AQkNBtPIfVQuknzzItxIx3/LNdwZlLZ8Gwphr7kU6kEX6E3dYXZVoQHreL8p3baKuvRRBZcATORxB30LgtBlfnLMqnDGdVkIePs5JOCM4EQeCzw5/xz93/RCaWcXHixVyaeikDogYgdjugbgc0FUHLQZ9af3sFHDXkxusGt51d5PA1Y4jyg+snjEbd6ynQnL0v4mn/TxYtQvu355GGh5P48Uf4/UgB3llf73MAWLcOsZ8f6pEj0YwZjeaii5AGB5/xecydHXy38ENKtxSgCQ1j0r0P02R3seCzRUilUkaMGMHQoUNRq09sQnB73Wxu2My2xm0UtxZTri/HK3gJkAcwOn40Q2OGEu0XRVh7AIrtNtw7jSjSAzBk+rTL2NaM2+lhf0EDhhYb8ZnBDL0ijbA4DRUVFXzzzbk8mAhAByJRPYhaEWEGkRkRrSCqQiTyIggaBCEWhFzc7lDKyqCzU0NycgpDcuNxNVlwNZpR22SkBMYTNCEev/6Rv7g0xoWKIAiUNBpZub+J1fubadTbkEvFjE4PZ1J2FPEhfgT7yQnTyH9Wt6Xb7ebrr79m0qRJADz99NPk5+cjl8v5tRuleujhj4xIJGLZsmXMnTuXF198EaVS2SWzsXz5cu677z7uuecePB4PN9xwA/fee+9vNtf/6QDN4xX406J9tJodLLlzKOIXpuKySon/69MnyDAIXi+G5ctRDx+OzNMIO9+CAbP5tDWKNe6FaIJXI9abyQ7PZ0rkDdSuqyWldwrXTLnmlOcvXLGUbHkpHmUIkn6zcBscGL+pxbpXh0ghIfCSZDTDYrAY9ez4chFF69dg6exAohRIu6QGhdhB1bre9B32GKuzEljc3M6L6XGMC+2+9GNxWXh6y19ZV7+RizTJPK/JIrDDCI2vQmct6A6CcNTSSRXi03LLvhJkviDPI8A6XRi7qg2kp6dz5ZVXolCc/44zweVC+/zz6Bd9jnrUSGJfeglJUFDXdq/VSttbb9Mxfz5IpT4HgFtuQfwTtlYnw+N2sXfNCrZ/uQiv28Xg6TMJ7dufr9etw2g0kpuby/jx40+a1jY4DCwtX8pnhz+j2dKMWqYmJyyHO3LuYEDkAPpF9oN2F7biViz7WvC06/DIJSguTmL7gTbqF5R2Gy84yo9L7skhISuEsrIylr37HU1NTUgkEiSS0wdFIpGHoOA6wsIq8ffXIpMdy+p4vWLcbiVOpx8GfV869QlYzOH8sEYpEolITU5hanYfNIc9uEpNIA5CmZ6CX/9IVFmh/3OK8yKRiAceeICbH3yKNQe0zHvjZTr0RsJGXY/m4DIuSo7k9Refxl95frw6bTYbeXk+79aRI0dy6623AqBWq7n66qvRaDS/yO9aDz38LxMTE8PixYtPum3Tpk2/7mR+gj98gCY4nbS9/Q7WkzyFao12Lmmz8KdwNYF//oDWA62o+ySgGXmiF5911y7cTc1EPDgXVvwJ1OF8mTiV54vmoBZ0RATk8cqIx8gI7MV7772HWCxm4sSJp5yXy+mgYfPnjIjsRBjyBOa9nehXVoEgoBkRS7OihuLiz2n+4jB6nc/mKCk3nwm3306H92VMJg/awgdIzryIQ4Mjeb+8kTviw7k59phyvsFhYNn2l/i0eiU6kZf7Ow3Mrt6MWLwN/EJ8wZh/FIyY69Mhi80HTWS3gnqTycRXX31FZXUlQ4cOZcKECb9Ih5y7s5PGP92PtbCQ0NtuJfyBB7otaZo2bUL37HO4mprO2gHgeGqK9rBx/jw6mxtJ6T+I0TfcRvGRMj7/4gsiIyOZMWMGCQnHMp1mp5lvar+hWFtM8+FmQrQhKDwKhuJzRRAhgnJopZWvha/5mjXHbEFFgFKEzBGM/xIjIq8ES0A1TuWxOqk2nJQvXYfwpe+goKAgLr30UnJyck65lCcIXvSGPWi1y2hp+Rq324hcHk5Y6GX4+2fj75+FWp2KRKI55VKbx+zEvLURyy4t3iI9QoSKwKkp+OWGI/mFZTwuRARBoKhej1Qm5835n/GFewAKTRDBfnLyoyN574nxvPzSLl89ynkKzqB7DdqP+bWcDXrooYcLkz90gOaoqqLp4T9jP3QIZU4OYvmxG49HgKYOK4EKCeFqORgaUIU7ify/5086lmHZMsT+/vgH1cHu/eyZ8BxP73scxAquzn6ex/N9ZubLly9Hp9Nx3XXXEfwTy21l361lbOBe3NIQjM2TsBZX+ERJL09l25rP2L1yKeqgYKJ79SZn/CRS+g9CFeyh5OBczOZDxEf8g9KqQGT9/HiyvJEpYYE8nRqDV/CyR7eH5SUfs7ZxEw4E8r3wQtwkBgyb4MuOBcSeUVfjwYMHWbVqFU6nk2nTpp20Nfl84NK1UDd7Nq76emJe+geBl17atc1jMtH85FOY1q5FnppK4icf4zfg7Jf3LfpOCha8y5Ft3xEcHcMVjz5DdGY2y5Yt48iRI+Tm5jJ16lRkR6U42mxtLCxdyOLSxQR3BpOlzyLGHYM0TEpGcgahqtCjPqcOnPVG3B12EIE0SIE03A9pmAqPIKX1ABi0PvvQ2CGgCEwDTi4fExYWRlZW1ikzZxZLJVrtMrS6FdjtjYjFKiLCJxIVdTkhIcMQiU6fcfOYnJg2N2DZ2Yzg9qLsE4pmaAyK1MDfTC3710QQBCpazGw43MKOqnY6rS5MdhedFiedVhcexOSMnU6ieTsfvPhv3nvzEGaz+byIxdpdHqrbLGRG91g09dBDD6fndxGgOSorMX3zzVkd4zGb6Vz4KWKlkrg3Xsd/3Lhu2+d9V8kLaw7z+e1DSEoJhbdHgqwX9D2xWN5jtmD8Zj2Bl05DXLSAg3F53FKxEK9ExZT0l3iiv++YPXv2UFRUxKhRo0hPTz/pvASXB2ejCc3GJaikY2iT3457v56A8Qn4j01g25KF7F65lLyJlzD2ljsRiUQIgoBWu4wDhc8gEknom/0GtYVpQDXPeI3k+vvxYloIr+/5L6vKl9LsNODn9XKpzcU1mbNIH/koSM98mUSr1bJ161ZKSkqIiYlh+vTphIef/1ozAGdDI3W33IKnvZ34995FPejY9Xc1N1N/x504qqoIn3s/obNnI5Kf3Y1SEAQObvqWzR+/j8thZ+iM6xh0+VXY7Hbef/992tvbmTx5MoOOnreopYgvyr5gbdVawsxhjDWPRWKVEBsby7hx40hJScGtt2Pd14p1nw53qw2xfwiacTGoB0Yh0cjxuL0Ub6xn9+oaPB4v+RPjGXhJMtKzrOMSBC8WSzkdndvQar/CZCoBxISEDCc15SHCwsYjlZ5cpPfHeAwOTJsbMO/SgteLX14E/mPikYX/cW2DXB4vWoOdylYzpc0mDmuN7K3rpL7DZyKfEelPVKCSuGAVAUop/RNDuPl1CQUfvEhOTg4i19/O21zsLg9zPtpNUb2eLY+M6XEH6KGHHk7LBR+gecwW6m69DbdWe9bHqi8aRfRzzyGL6G6ubXa4eWtTJSN7hTE4JRQ6a0C7Hy4++Reyad06BJuNoFEZ7Ch8iz9p4nGLNQRGP8VLR70429vbWbNmDSkpKYwePfqk4zgbzXR8Woq73Y6E2zF4QeyUEXpTGqIkJ9tW/oOS7evoe8kA8qZk09S8GKu1GpPxAJ36HQQFDSKrz79RKmMoOLCbtjAZCn8Z/wqs4/Yvb6LabWKozc79HgVjM69GNeRuUIeddC4/xuVydQWYWq0WiUTC6NGjGTly5BnVQp0Ljqoq6m6ZjdduJ2H+h6hyjhnS2w8dov6OO/HabCTMewf1sGFnPX6ntolv332dupL9xPbuw6gbb6esvoHlK1ZQVlaGy+UiLS2NRm0jL3/yMlWGKgwOA1KxlGlMA4MvqzV26lh6Z/TGcbiD1vcO4KjUgwDypACCR8fjlxuOSOpbimpvNPPt/EO0meoviwAAIABJREFU1ZtJ6hvK8Bm9CIo88yDI63Wj061Aq12OwVjU5X/q759Fr15PEBkxFYXizINlV4sV87YmLIVaEAT88iMJGB2PNOyPKZB6WGvkjYJK9tZ2ojXau/wsAWIClWTFBnLnRamM6x1JVOCJTgM3AwEBAdx44428+uqrP9m5e6b8EJxtrWjjnzNyuwVnP3RwnoxnnnnmZ5/7ZBzfOQowf/58du/eTXR0NF984dOdPHDgAH2PetXOnj37BG2oHnro4Zfngg/Q2l57FbdOR+KnC7vdwM8E0SlqeD7cWk2n1cVDF2f43ihd5fuz99STz+GrL9k6Jpynml/ncHQkAmpMkY+zfMgwxEeXhb7/3ucOMH369BPqRgRBwLytCcOaaiQKD8Gyl6hSmpBdOg6DbTdHtNV4m2zgD2nTAOoo2r/U9xlEcvz8EklNeZjExNsRiSTYzS5aaoxI4+t4/cCj3CPrxIWId1UZDBpxN6SMAfGZB1UOh4PPPvuMmpoaoqOjmTx5Mn379sXvLIvvzwbD6tVon3oakVJJ4kcLUGZkdG0zrllD0xNPIgkMJHHhQpQZJ89Gngqvx0Phii/Z8eUixFIp4269G3dIBJ98uRSr1dqVlZQpZBypOYLT40RAIFAUSKQ0EoVEgUqlYtilw8hJz8K2txXdit149A4kQQoCxiXg1y8Caeixm7fgFSjeWM+Or6qQqyRMvrMvKXlnHkgJggedbjXVNa9itVbj55dCVNSlBAb0IzCwP35+ZyYZAuC1ubHub8W6R4ezzgRiEeoBkfiPjkcacuHYH50vnG4vpc1G3vmukjUHtGgUUsZlRpAQ4kd8sB8JoX5kRgUQ6HfmtWNz584lPz+fW2655WfN7cfB2Yz+cac/6Dfi8ccf5/HHHwd8QdypauN66KGHX4cLOkDz2mx0fPwJQddcfYLUwrlisLqYt6WK8ZmR5MUf7RAsXekz7Q450adxZ9FqHu9fjC5YRIrdw3RzOPP6vsQjKYn0UvtudkajkaKiIvLz80/o/BNcXjoWH8F6oAVPThMm8d8oC7DhVooQtX1GUNAgRJZA6guriUwYwKDLrjka4IlQKqNRKmO6aovMTjMf7PwHVbta6SXMRKdYyH0KI5HyYN4Y+xrJUWd/jex2OwsXLqShoYHp06eTm5t7+oN+Bl6bDd0LL6D/Ygmqfv2I/fe/kMX41N+9Fgvavz2PYdkyVHl5xL7yCrLIY9lPg8FAQUEBer3+lOMLXi9tDXXYTUZUGbkER8Ww5Ugl7e27CA0Nxev14vK6KE8pZ59jHyqpiinJU7gq/SqywrK6xnHpLJi3NaFbthvB5UWeHEjQ1BSUmaGIJMdqtQRBoKG0kx3LK2mpNZGcG8boWb1PMC93uy04nS04HC3YbHVYbTVYrTU4HFqczlaczla8XicadQY5fd8iLGzCWdWEee1ubAfbsR1ow17eCR4BaYQfgVOS8esX8Ycq/He4PWwsbWH1gWYOa03UtFlwewU0Cin3jU3j1hHJP7mEKHgFmir0HNmpZej0VFSaE/cNCQlh5syZvP/++8yePfus5+jxCqw7qOW1jRUc1hov+OCshx56uPC4oAM0V1MTkuxsIh588LyN+d9vyzDZ3Tw44WhWxqSF+p0w5q/dz+1x8Wbxm3yw/31CRfBa7FVctPXfzOpzHxnqAO5NPBY4bN++HUEQGD58eLcx3FYbdUsX0+HdjOXiYtzoEXsEnE1K0oc9RlzSZWz/Yil7li8he8xMJtx8L+KTZL48Xg/LKpbxWuE/6XBbmd5+HU6phc4Uf8aH5vPooEcJVp65/tcPWK1WPvnkE7RaLVdddRV9+vQ56zHOFI/ZgmHZMjoWLMDV2EjoHXcQfu89Xf6Y9rIyGu/7E866OkLvupPwe+7pyoB6PB527dpFQUEBXq+XmJiYkwYvXo+HtvpanDYrQVGxaEJ8rglyuZzAwEDa29vRK/XsCt9FjF8MT+Q9wSUpl6CRHzN4d1QbMG2qx36kE6Ri1P0iUA+LQR59Yq2XrtrItqUVNJXr0YQoGH9zJumDoxCJRDid7bS1F9DWtoHOzu243aZux4pEUlSqeJSKWPyCklHIwwkIyCM8fMIprb5+jCAIOKoMWHfrsB5oA7cXSZACzfAY/HLCkcWeuovz90JrnYmWWiMuj0BNm4VSrZGiej02pweNUsqAED+mJEQSGaAkI9IflVxC455WGk8xnqndTtkuHaYOOzKFhF4DIonPDDnpvg899BCvv/76Wc1XEARWFDfxyrflVLVZSAr1461Z/ZmUfX4EnM8Hx0t7AHR0dHDpcY05PfTwR0er1TJ37lwKCwtRKBRdOmi5ublkZGTgdDoZMGAA77//flfj2G/BBRmg/WCWnqVQEvX440jOk83C+kM65m+r4eZhSfSJOdpJdXg1IEDmtK799HY9d357JwfbDzLuiIy7LIOQK/bRIguhJGwwG/LTkB9dxrRarezevZvs7Oyurk2Px0ZZ6d/QNq/EG2NBjB9hEWMI2/Md0godhRF3I7Jls+yFv1N/6AC5E6YwbvadJ2ivAexs3slLu/5Bmb6cfLud+9yx1JoHk5QTzgPTl57ztbBYLHz00Ue0tbVx9dVXk3HcEuP5xOt00vba63QuWoTXZEKVl0f0c8+iHjq0ax9bcTF1t9+BWC4nYf581IOPNQo0NTWxYsUKtFotvXr1YsqUKSftjm1vqGP1Ky8hb2zg8vseImPoSACKi4tZtmwZbrmbPeF7CE8O580Bb5IbntsVvAiCgKNCj3FDHc4aI2K1jICLE1EPjkaiPvkvZ31pB6vf2I/CT8qoa9LpMzwGu7OGurp3aW3bgMGwF/CiUEQRETEFlSoRhTwcuSIClTIepTIWsfjsf/0EtxdHtQH74Q5spR14OuyIFBLU/SPwy49EnuD/mwRlNpMTi8F5nkYTqDzYTsnWJuyt9m5bAoBRSAAJ2IBOO2BHj4GdPl+xn0QkgvjMEIZcnkJyXjiyHzVuHF+bFRkZidVq7fr36WrC7C4PTy8/yOe76+kTHcDr1/VjcnY0kgtMS+7H0h4/1KD10MP/AoIgMH36dG666SYWLVoEQFFRETqdjtTUVIqKivB4PEyYMIHFixcza9as32yuF2SAJgjCSmBlTnj4HP+f0BI7G5oNNv68pJismAAem9L72IbSlRCaBuG+9/R2PXPWz6FKX8XzwTfTa9l7mP89mb67Z/Nh1BWsHNyHcPmxm3ZhYSEul4sRI0YA4HR2UFQ4G5O9hIDWocT0uYKovlOQVG6G6gV82ZSD2V7Dl88/iSY4hDE330G/SVO731Q9LmoPf8W/D82nwFpHjEfgX21tWGOv4QX5tdx8wEKf3HPvqjSZTCxYsAC9Xs+1115LWtrJZR9+Lh69nob7/oS1sJCAKZMJuekmVD9aQrXs3EXDXXchCQ0l4cMPkcfFAj5l9c2bN7N161bUajUzZ84kMzOzW1Clq6qgonA75bu209FYj0yhZPqjT5OU0w/w+ah9tfwr2lXt7I7Zzf0D72dmxkzEx2WoHHVGjGtrcFQZkAQqCJqWgt/AqJ9Uzm8q72D1m0WogixkTl2FRVTL1u26Luskf00WyUn3EhY+Dn9N1nkJmLx2N+bvmzBtbUSwuUEqRpkWRMD4BFTZYb+Z0r/D5mbv2hqKNzTgcXvP69haiZeDKjeiGD/6JwczMDmEvPggVLJz/9qSKcQozqIW7Uxp0tu4a+Feiuv13DsmjQcmpF9wgVkPPfQABQUFyGQy7rzzzq738vLyqKmp6fq3RCJh0KBBNDaeKhf/63BBBmg/IIuJPS83N7fHy/2fFeF0e3nt2n4opEdvZtYOqNkCw+4DkQiDw8Dt62+nSl/Fq2NfJf7ZjzDExbGqfS/9BTcZ/W8kUX2syNrpdLJjxw569epFZGQk5o5qivbcjBMtcVUPkDTpBhSJvkxd26oX2FSXRa0lkEC1nQm330efUWOR/pA+ddmhqgDjwaW807yZT9Vy5ILA/XYx1wfn8EH/KTxHFs/WSnCKLCRknXxZ5nQYDAYWLFiAyWTi+uuvJykp6edc2lPirKuj/o47cTU0EPPPfxI4rXsDhsftpvi111C8/wHO4GCqZl7Fnu+3dm1vaWmhvb2d3NxcJk2ahEqlQvB6qS8toXznNioKd2Bqb0UkFhPfJ5u8i6fQa/BwNMG+61LTWMOChQswSUxYs60svWgp0ZrorvEFl4fOpRVY97UgVssImpaCenB0VzfmjxEEAZOphMP71rFnSR+kyk5iRryCSBKLnyKJ4KAhqNVphIWNRamMOW/X0Wt3Y9nZjGlzA16rG2VmCOqBUSjSgs46KPO4vFQWteCye87L3OwWF8Ub6rGZXGQMjiI5N6y7kfppMNnd7K7pYGd1BzVtFgD85FJSwtUkJwcyKSeSv8QHoVFc0F9T6Ix2Ln39e+wuD+/c0J+JWRfOcmYPPVyofP3112jPQZ3hp4iKimLy5BNtGo+npKTktJqedrudnTt38sorr5zP6Z01F/Q3n+hnPCkfz5ubKtlV08F/ZuaSEn6s3oiDS30+k5nTsLltzPlmDhX6Cl4d+yqDxClUbNnKG395lvt0z1Pvl8boASO7jVtcXIzNZmPEiBEYqkspOnI9XpGTdOGfxNxyCWK5BIu+k+Iv5lG4S4UXNUOuvJYhV8xEIpWB0wKH1sChFXjL1rFYIfBGcBAGjYIrwgdy75DH0ASm8kxxLRXbtTxea8ZpdJHYN/Skhc2no7KykmXLluFyubjhhhu6KeafT2wHD1I/53bweEj48INuwrKC10vLypU0/Ovf+LW2YoiIYP+l03A5ndDW1rWfUqlk1qxZpKWloauqYOe27ziy7TvMHe1IZXISc/sxbOYsUvsPQuV/TPhTEAQ2HNnAxi834sFDypgU7hpyF5Ljavs8JiftHx3C2WDCf0w8/qPjEJ8iCPB6nTQ1fUFd7ZfU742j48gk5H5uxs0JIi55I1Kp5qTH/VycDSYsO7VYi1oQXF6UGcEETEhEHnduy/1tDSa+/bCU9sZTyzqcCzG9gph6bxoRiacXX7U5PWwua2VHVTs7qzs4rDUiCNAnOoCZIzIY0zuClDA14t9R5kkQBJ74qgSzw8VX9wynd9T5FaFtsDvZa7Sy32TlgMlGk+Psl5HHhQbwTFrseZ1XDz38EamsrCQvL4/y8nJmzJhBzlkqR5xvLugA7XxQ127l9YIKpuZEc0X+cV1UXg9sfwNi8iEmn/nFb1PaUcqrY15lROwIWt94g/0pvXCoGsmyVOK89O0Txi4qKiIiIoIIhZLdu69HkLnJy/iE4KRcdFUV7FmznLLtW/C43SSr9URNmMOwqZOhdDkc+grKvwW3Das6lMeSerHR1cbAyP48MuhRMoIzWLu7iYJvdxBXZydegLiMYLKviSUp98y0zX7A4/GwceNGvv/+e8LCwrjhhhuIPAebpDPBtn8/dbfNQaxRk/D++yiSfZ2xXqsVw8pVaN9/H+rq8Pj7Y7/7LgbdfTdDfiSH4nLYqSvZT1XBOjb++znMnR2IJVKS8vK56PrZpPQfhFx5ohn8lsYtLNiygIjyCCRIGHvFWMZnj+8+ts5C2/yDeM0uQmdloso+8Vo6bW5qS9qxmGtpbPocc6cTfcVs3HY/knKCGHVNH/x/AbkKt96Otcjn4dnWaPYtY6YHo8oKxR3hR4fLC9WGsx63obSTwtXVKNQyJt/Z94yCqTNBJAa/APlPZrkFQaC4wcDi3fWsLGrC5HCjlInJTwhm7rh0JmVHkRF1fmpMfwvWHNCy/pCOv07p/bODM48gUGF1UGS0sl1vZpveTJ3dF5DJRCIy1Uoy1MouaZ8zJU7Z/WHux9prN998MzfffPNP7tNDD+eb02W6fimysrJYsmTJSbf9UIPW3NzM6NGjWbFixW/aQPOHD9CeX3MIqVjEE5f8qEPx8CroqIKrFqC16vig5AMmJE5gTMIYBI+H5hWreOH2h/i08hHsgSkoc6/qdnhbWxuNjY2MGzma4u134fTXkZP6LsFJuRwo+Ib177yOTKmg75B8+jW9SaUtivyWN+ClB3wDaKKg3yy0KSO5r/wTyvTlPDroUa7rfR0dWisvP/E98nYnUQoRkcMjmTgh+awET3/AbDazaNEiGhoa6N+/PxMnTkR+lmr8Z4p17z7q58xBEhxM4oL5yGJjcdbW0vnpZ+iXLsVrMtEZFIRu4kSGP/oXIqKPLTmaOtqo3rubyj07qSvZj9vpQKZUkZTbj5T8QaQOGIxKc/IbudFp5K/f/ZXGQ43kdOSgDFQye9ZsIiO6B6HW/a10flmOSC4m/I6ck2ajDK02Vr2+F73uB9PxSwCI7xPC4EtTiEw6fxkSt8GBs9qAo9aIs86Eq9GMzSuwyyWgt3kAD+xq8b1+Jqn5EVx0Xfo5ZV7PlooWM1vKWyms6aCwppNWkwOlTMyU7Giu7B/HwKQQ5KdYSv49obc6eXpFCX1jA5k9vLtEj0cQOGCysaXTRLXNgdnjxeT24DhOOPd4nF4vpRY7Fo+vji9IKmFokIbb48MZGKimt1qJoseXs4cefjZjx47lr3/9K++++y5z5swBfLXkxzcERUdH8+KLL/L3v/+9J0D7pfi+oo11B3X8eWJGd9VwQYCtL0NICmRO4+XvH8creHlowEMAmDd/x1uDLyLfe4gsayVMnweS7pequLgYkUiETPslluhiekU8TVjSKHZ+9QVbP1tAUm4+U+f+BWHBZQgSFyoZSCIyIH8WJA6HuIEc0Zdz57d3YnPbeH3s64yMG0lTuZ6lbxThEgTsk6O45+JeBKjOrai5tbWVhQsXYjabmTFjBtnZ2ed8LU+HraiI+ttuQxoeTvz8D3GUl9P87LNYvtsCYjGtvXqxPzaG5MmTmTZpEhKxGG1lOZV7dlG1dxct1ZUABIRH0nfsxaT0H0RcZvaxGr1TUNZZxtyCuYTUhpBryCWjdwZXTL8CheKYtZXg9qJfXYVlezPyBH9CrstEGnTcdkHAaq2mbN92dn0RjFfwEDfiA+LS+pOUeAcKpT+a4POTMXO327CVtGMtacNV75PeEMnFyOP8cfSPZOtOHS5BYMz1vVEHnbk910+hUEuJTAr4Rbs7y3QmVhU3saZES0WLL/sSG6RieGoow1LDmNQ3ioDzaDJ+IfC31aXorS4+mj0YqUSMxeNhQ7uJ1a16vusw0en21fpFyKUESCWoJWJUpwiyFGIxM6NCyPVXkRfgR7rf2WfKeuihh9MjEolYtmwZc+fO5cUXX0SpVHbJbBzP5ZdfzjPPPMOWLVsYOXLkKUb7hecqCCd/orsQGDBggHAu7d/t7e18vvgL5tWF4UHMFapDSEXHfU7BC14XiKW0K/RsiNpApiGTvgaftUllUDjrsgaxZceNBDvNzFdPJzC4GY1/G/7+rcjlZnYXXoGfn57svhsxNORzsKYvMm0dsnYt7sBQnLEpxImaucX7Geu9w9khHexbE/phCgi4vW4ApGIpInzq9l6Pb56CWIT0Z9TiCIKA1+t7GheLxb+s9IIgILh9nyVEbyB3717C2tqwKZVU9epFZWoKbn9/xo4YTrBMTN2BIqr27cbS2YFIJCY6vTep/QeRkj+Q0LiE085VEATqTHUU1BXwZvGbpBvTSdOlMWjQICZNmtTNycHZYKLzqwpcDWbUI6IQDzPjcLfgdhtxuQ2YTYdoa92N7lA2rSWXo9AYGTyzhaTeY/HX9P7JORze3kxbw2mWggTwWly4O+y42214Lb7rJPaXIQ1VIQ1WIPaT4fUIlG5rRh0kZ8rdOYTG/DK1becTu8vD1yXNLNxRx+7aTsQiGJQcwuTsaMZlRhAX/Mfw+fQKAkUmKxvbTZRafD6e2moDB79vJCk7jNS8CKweLzv0vgxomEzKuNAALgrxZ2SwplvXdw89/C9TWlpKZmbmbz2N88bJPo9IJNojCMKAUxxyVvzhMmhVVVUsXryYg84w9IKKe3Kk9IsY0n2ng8vArMM7YDavtL9BgCeAm3rfhEKsoM5o4T11FFfXfE2as56SjAzyIlf4jvMGozRkYKlKwOFQkxEqILZfS0DMKNI6imk6qCUsK4+YoRchEonIK34Ki0FBszuCoSOH+USYALvbzsqqldjddqalTCNQEYiu2khjmR6rWkx1gpKr40PPeUlDq9VSWVmJSqUiKysLpfKXs/cRPB6Mq1aBTkcCIjT79+PWaGicMpnm5AQsFgsKowFp+X627d8OgFzlR1JuPqn9B5GU1x+/gMCfPocg0GBqYF/rPva17GN703Yazb7251HSUYTrwsnMzOwWnLk77RjX1aA/cghb9CGc06qp9OzBXXRMMNbrlmOqmUJb6aO4bEri+6i5+NYxKE+hffYDLqeHgo8PU16oQ6aQIDohkBbAC4LHCx4BQQBE+PYTi3xOBFYPWM1QfyzAi80IYvwtfX6VZchzweH2cKDBQGFN59Hlyw5MdjdJoX48PiWTy/vFEu5/frJ+vxY6h4tdBgt7jRasR5cXBcDm9WJ2ezG6PZRabHS4PIiAVD8FjiYLrbt0KMKUeFP9qbQ6kIjgmuhQpoUHMThIjaQn+9VDDz38TC7oAM1ut1NaWnrG+7e1tbFx40aCQ8Mo6YhnWGogD187uHtGRncQtn6C/qKHeUGyiTpXHX8b/jcuSbsEi9vDI6u2oHDaebr9LSwqCZ2xIlLiHySgYTj29RYQYGt0FQpFA9NueRyZTEZrXQ0L579FSv5ALn/kKd/5ar6HrQfZ1JrMZTOHEjhmAgBWl5U538zhSMAR5k2YR15YHt8tKsOwtwnS43k/R8bi/r0YFnz2GRS3283atWupqKggNTWVGTNmnBez55+i6emnadm4EZlECm431TFhlIX442ksg8Yy/EPDSYhPIGzCJMLiEwmNTyQsPsHXxXoK9ur2Mu/APDrtnZidZvQOPUbnUY0xmT/9I/tzc9bNJLmS+Hb5t0TFRXHFFVcgFotxu00071pLS8V6LCEluEb6xEsVRBMRPpmQkBH4+SXT2SRn00c6TO0O4noHM3BqMjFpQaf9vMZ2G1+/fYC2BjODL0uh/6RERCIRXrsb+5FObKXt2A93ItjdIJWi7BWEKisUZe8QJBdo4PVTNHRa+WxXHYXVnRQ16HEe1TpLDVdzSd9opubEMCw19FfvvHR7BUweD0a372Vwe/ihvEsA7F5v17Y2p5sGh5MGu5M2p7trDKvHS6PDBYBCLEIjOdbpqxSLCJBKCJBKGBsSwNjQAC4K9mdfRTt3FlbTPyGYj2YPQn2BS4D8XqmpqWHq1KmUlJR0vffMM8/g5+fHnj17+PzzzwGfzV6/fv349ttvSU4+0aqvhx5+z1zQ3y4dHR1dv4hnSq9evdBkjqRz8QFuH5Vy4nLZrnmsDwjib7r1GJ0m7s67m2mp0xAEgVt3l6ENCODf+ocJtpjQj7yRQb2eRb+0Flu9CWVGMKrJ8VS8v4m+ffsik8lwO52see1fKPzUTLzz/q7zeTc+j80tx+TVEDjiRgAsLgv3F9xPSXsJ/7noP2Sqs1nz1gFqS9rRjIjkuRgnf0qMPKfgzGKxsGjRIurr6xk+fDjjxo07wbT9fOKx29jz1BM4N2wk1OOlUyFCO3YUQbl5jD0uEFP4nWiRdMoxvR7mHZjH28VvE64KJz04ncSARALkAaQHp5MXkUeiOpFDBw+xe8tuthoWkpxioF8/qKh4Cou1CoN+L4i8iGOUBAUNwW24n+LVkThsR0VUBYDu2jsNRzppONJ5ZpMUQK6UcMndOcQn+GPZ3oyttB1HlQE8AmK1FFVWKKrMEBTpwb+ZgOzPRRAEluxp4P9WHsLm8pAdE8CNQxIZkBTCwKRgQjU/L1PW6XLzpa4Tk/tETTYBMLg81Nt9QVWH+1hQ5RHA6PZ0FdOfCWIgWiEjTinv1gUpE4noq1ExKEhNX40fsp8IMjssThZvr+U/35SRFRPAh7cM7AnOfgNEIhENDQ18++23jB8/nqeeeorZs2f3BGc9/CG5oL9hwsPDu6n9ng6xWExYWBi3LthNVICSkb1+pLbvsrGwehUvhgaQqY5i3sXvkhHiszj6oLqRTTYH17CQse0tCBI5Eu6i9Y2DiOUSQq7NQJUTTnFxMS6Xq8vLbuuiBbTV1TD90afxCzyagdEeQFz3PYXtyeQMHQgyFe22du7ecDdH2st4Iv4FPOsjmV/0PYIXel2ZzB1yI0P8NTycfPYil1arlY8//pi2tjauvPJK+vbte9ZjnCkej5v9779L8aplZNc0E+zyYJ80nqzH/sqwyOjTD3AKms3NPLb1Mfbo9jA1ZSpPDHkCtcwX3BkMBsrLy9m7by9LqpbgdDrI6F1NSuo2QECrLUQmC0JqCSKkfgqh4aOInXIJpdva2L6kjLB4NYnZoViNThrLOjG02AiMUJGcE4b0LAMokQiSYtVI9rfS/FkpeEEarkIzPBZVnxDkCQEnWfL8fWB1umk3O2m3OHmzoIJvDukYlBTCv2fmEh9yfurJjG4P79S3MK++FdNPBFkqsYg4pdwXVGmUXfq3EpGIAIkEf6mEwKMZrgCpGH+pBNlxD2NKibhrvyCp5JzrOQ81GXl7cyVrS7Q4PV5GpIXxxnX5f7iGh98LIpGIt956i+uuu4758+ezYcMG9uzZ81tPq4cefhEu6ABNJpMRFXV2AYvWYGdzWSt3jU49wWrFVbqCD9RyBgWm884lnyIVSxEEgYVFjfxfewO9xDVcv72BcK8Ru2gYhvXtKLNCCb48DYm/HEEQ2LVrF6GhocTHx1N7oIg9q5eTN/ESUvoN7DqPsPcjvIKIJmsAF116P43mRu5Yfwct5lYebPsPLdsFDH4dZI+MJWZIJDMbGwhGyrvZSV0en2eKzWbj448/prW19Re1bfJ6PRz8ainbv1iI12plSFUTcomUpE8/wq9fv3MfV/Cy+Mhi/rv7ZYKsETzT90Uuih8s/+GYAAAgAElEQVSFTedF72insLCQkpISBEHAX6MhIzGNwMACHM5a1OLrSEq8A49WhHlzA+52O+qh0ajyo9i5soF939SRmB1C39Hx7C+op+5gBzKlhOEz0sgdF39WjROuNhu2A23Yiltxft+ISCVFMyIO9YBIZBG/v2J4u8vDgUYDe2o72VPbyb66TtrMx0RQ5RIxj03uzeSBcdQ6nHzX1E6tzUGTw8UPYZVXEDB7vBhcHvRuN+4zaDhqdboxe7xMCQvk4eQo0v1OXh8pEfGzGltGjx7NY489xsTjrOJefvllvvnmGwoKCrp5zz744IPceOON3Y4XBIH522p4YU0pSpmE6wYncN3gBNIjf7+abX8UcnJymDhxIuPGjeOrr776xWSDeujht+aCDtDOhS/3NuAV4Kr+8SdsW1/0Hi1SKU/3/xNSsZQOi5M/f1HMJj8jnrAAHmjZQZKlP2L5WpyhlxAyzZc1++FGUVNTQ1NTE1OnTsVps7Hu7VcIjo5l1Kxbjp3EZUfY+wnlxlD6ZIRj0oRw68qZGB1GHrH/B125g6HTU8kZG4cgEXNNcSXtLjdf9et11t1edrudTz75BJ1OxzXXXPOLBGd2i5mKLZvY8dkCDHYbUUYr/Zo7kAYEkvDhByh/hsl6nbGOJ79/kn26fVxd9xBBTfFo98LnFB63l5xg8n1/bQdtLWjxadLVAHs40n3Qb+p9L3zaZTazi1WvF6MKkDPk8hSyR8WekRej1+nBWW3AXqnHUdaJS+vTyJHH+xM0PQ2/fhG/q+VLp9vLruoONh1pYXdtJyUtRhwBcpCKCPdXkNQ3nMwAOXaZCIMI9CIvzzvNPL3zWA2oVARRClm3TJW/REKgTEK64sx0uvzEYm6MDSXH/5cNaq+99loWLVrULUBbtGgR//znP6mrq+tmFv5jDDYXjywpZt1BHeMzI/jXVbkE+fUEAb8mpwrOf3j/nnvu4euvv2bMmDG/5rR66OFX5Q8VoP1QNzMoOYSksB/VPhmbWGivJUkdxoi4kbSaHMx6bweVuLEkhnKVewl5u/MIyfkadBEE3j37BO2zbdu24efnR25uLps+fAdzezvXPPsPZIqjWQBrByyahdht5YgpmUkPPsVj255Ba9HyrOIt6vfY6D85kfyJiQC8UNnE93ozr2UmkBdwdjcsr9fL0qVLaW5uZubMmaSnp5/zdfsxNrOJgwXrqdjxPU0VZQgIaOxOLvIPw79Fizg4hIQPjrkEnAvlneXc9s1tuDwuHrC8hLVJzoApSYTH+1Naeojqmg1EhLciV7SCSIxCEel7ySMJChqIShmLYX0Nrhabr+YrOwxBgE6dlY4mM7oaI/WHOggIU3LRdRn0HhqFVPbTAZXX6sJ2qB3bgTbsFXpfwZNEhDwhgMCpKaiyw7rpp13IGO0uDjUZKWk0sLumky3lrZjdHkj2R5GkxpKpRjh6D2w6+gInAYKYJIWCHJWSS1UKElVykpQKElRyYhXynyX98msyY8YMnnjiCRwOBwqFouvhKi4u7pTHGKwuPtlZy4ff16C3OnnikkxuHZH8y0rU9HBSQkND6ezsXhfa0dHRVWsmFot/0RrbHv7YaLVa5s6dS2FhIQqFgqSkJC6//HJWrFjBqlWruva7+eabmTp1KjNmzPhN5vmHCtB213ZS3Wbh7tGpJ2zbv+s19isUPNb7WlpNTq57dweNJgfK0cEEe2uZXaoiOFeJuHoDDL7jhOCspaWF8vJyxowZQ2NpCfs3rGXAtCuISc/0Cd8eXApf/wW3uR2LW0HAsFl8ZTnM+tr13Kd4kvoCG72HRDH40hQA9hgsvF7XwrXRIVwVdfbG59u3b6esrIzJkyfTu/ep9brOBnNHO7tXf0XxutW4XU78bU5STFYSM/oQ07sPHe++hyw1lfh33kYWfe71ZmWdZdy27jZkYhl/lf6XigN6+k9OZPClKVRUbMeheozMITqUilhiYq8mJvoqFIqIbmN4DA4a2m04B0TSqZZR8V0j2moDXreASCwiKiWAYVemkdovHLHk1F/k7nYbttIO7Ec6cFQawCsgCVagGRaDslcw8qSACzpT5vZ4Oaw1sa+ukyM6E9VtFmrarDTqbV37xAQqmdgvhj3hEo64XPT2VzEmxKfTFXlc1jZIJiFYKvlDBCShoaEMGjSItWvXctlll7Fo0SKuvvpqRCJRl9/eD/zrvy+z0xrBwp11WJ0eRqWH89CEdHLjT9/V28O5YbPVYzDs6/ZeePgEJBJf17lGoyE6OpoNGzYwbtw4Ojo6WLt2Lffff/9vMd0e/kAIgsD06dO56aabWLRoEeCzbVy5cuVvPLMT+UMFaIsL61HLJUzp+6PgQRD4pGYNGqmIIYnXcc28HbQY7YycFs8qs4O/G1cTvD+doNv0UOmC3GtPGHvbtm3IZDJysrP54qmHCY6JY9jMWWBohNUPQdnXENEHqaWVg/ooAofl8eedc5nReg+uijAS+oQw+obeiEQirB4vfyqtI1oh49lzMDGuq6vj22+/JTMzk0GDBp3r5Tp6aQSayg5TvH4NR77/Dq/XQ0yniTSjnYTLLidw5kwMS76k4+13UI8cif6qv7D+q1ag9ZzOZ3aZ2deyj5Gia8kJyqWiXE/vYaHkTw6mqnoBVdUvoNGISUt9joSEqwExumojDlu7b75egbZ6M7W7tLQY3Hg3NSISQVi8P7lj4onNCCY6LRC58sQfbcHt9dkq1ftslZwNJjydPksnaYQKzchY/PqGIYvVXJBBis3pYUd1O+U6E1WtFipbzZQ0GrG5fJ2QAUopyeEaBiWHkBquJis2kOyYQOwyEdcVV1Jrc/JOViKXRQT/xp/k1+GHZc4fArQPPvgAOOa3B9BudnDHx3vYXVvN9H6x3D4qhczo82t43sMxrNZqamreQqv7CkHo3sE7Yvi2rgAN4KOPPuKee+7hoYd8Di9PP/00qaknPnz30MPZUFBQgEwm69aAmJeXh16vZ+fOnb/hzE7kVwvQRCLRaOA54CCwSBCETedz/A6Lk9UHmpmWE3NC+7uu8lvWSz1cEzaAf6+rRWe08+z1/bi/sYmxwnqG78gh5NpsRPv/DyL7QlR3S6SDO7dRXFREgMfBxw/eidvh4JpnX0JWsRaW3wseF1z8N7yWDkS6QzSED+bTvf9l2qF7CDMkkDMmjmFXpiE5msn5e1UTlTYHS/JS8ZeeXXbGarWyZMkSgoKCuOyyy845kHA57Bz6roCib1bTVleDVCQmvrWTNJGc+Fm3EHjlFVi3bqV+zhzcTc0EXXM19svuYss7BwkIUyI7C4kBr9eBw23C7jLi9TpJFPkjFYkwtZQTlFqBELOILVt9pecmUzQDB7xGQkI/tFUGti2toLniRIPwQKWElGAF6dekE9Mr6JR1ZR6z07dkeaQTR6UeweU7jyREiTzOH/mIWFS9Q5CG/rJ6ceeKye5i4+EW1pZo2XSktSsYC1HLSQlTc/XAePolBJGfEExcsAqnILBE28kOg5kjXhtLG2x812HC5vWyKDf1nCRcfq9cfvnlPPjgg+zduxebzUZ+fj41NTVd2ytazMyeX4jOaOeN6/K5JOfcs8L/67jdFgyGPXR2bsdgLMLrdZywjyB4MJkOIRbLiIu9gejoGYjFx0oGZLLQbvv36dOHgoKCk54vKSmpm0ZaD78/ysqew2Q+c53TM8Ffk0l6+pM/uU9JSQn9+/c/r+f9pTiju6xIJPoAmAq0CIKQfdz7k4BXAAnwniAIL/7EMAJgBpRAwznP+Ee0t7czbtw4GvU2OttamO+vYs3/hSKRSHA6nXR0dGBz6nFqRLyvduGcdjl3jc3gI5MBP8HKDYatyHRp+HtaoGkvTHyh2/ht9bWs+PQThKBwIuQSokePJzk3nxjdatjwLMQNhCvmQVAizhfT0FqCKJDCqO03o8KPcbf2IX3gsU7U7ztNvNvQxuzYMEYEn11HmCAILF++HIvFwq233npODgHGthaK1q3mwIZ12C1mwuMT6S/xI7SohOi5DxB05RWYN22m4fY7sBUVoejdm5gX/g6Zeax5bhdh8RpmPDIAiez09R9tpgr2HHocqcVn1+X0glMaRkxQLgF+ccjloUglqcATVFRWcrCknsGD7yLIrzdr5x2gcm8rfgFyLro2nbD4Y9dKrZRgeHUfARPiCcgNP+G8gsuD/Ugnlj06/p+98w6vokz7/2dOrznpvRdS6KEjCAgqNkTELrL27rr+trir68rqru6+uuvuq2vvvYAKSFWRXkINCRAgvZ/k9N5mfn8Eg5HQrPDu+VxXruTMmZnzzJzJme+5n/v+3v4aG4gSikQtupEpPdOWOTHIj9Mt4OfE5gmyck8ny6o7WHegm2BEJNGgZlZ5BucOTGVIpumIpHVPJMKLLV0829xFeyBEikrRWxGcplbxz5IsSg2npgj9IajzBtDKBdLUh8+LwWBg8uTJ3HDDDVx11eGoeCgi8sTyGl7f2IBaIePdW8ZSnn16RRUlKYLf34Yk9XzhiES82B0V2KwbsDu2Eg57fuLxhAAJQVBiNA5Cqei/O0hO9s1kZd+AWpX4k44vSpTjcbzClJ+DEw2DvAY8Dbzx9QJBEOTAM8DZ9AiuCkEQFtIj1h771vY3AGslSVotCEIK8A/gmu839B4SEhJ48t3l3Pj6Vspbl3H20Bx+/etfAz2C5oJbz2OHcxd3X1RKRPsU87e3klgcz5aGdm7mdTJ3OMkasg5hw34Y8QsYdVPvvsOhEJ/97xOEYuIpKizkmjlzIByARffCrndg8GUw42mqHbVs/PQX3BS0sttZzkDhSjJL45h4+YA+PRUDoshvalrI1ap4oODkv61v27aNmpoazj33XNLT0094u6+nMbcv+ZQDWzaABEWjxzFk1HhCj/2dcHMzCXfeiXdrBV3//jeEwygzMkh79BFMl1wCgoyF/95JOBDhnBsHHlOcWf1WVjWuoLn5VQZwEJkA630m0tJmcWnZbcRrj/xgrq+vZ83qBspKLkDqSOSdNzYjyARGX5TH0KlZR0xXutb1tHnSDj68r7AjgH+fFf9ea2+kTGZUYZiYgb48GWXKiRvm/tQEwyJNVg8bay0srepgc72ViCiREavlunE5TClLZkhWbB+3fk8kQliUWGtzs6jLzkqLE29EZFysnqdKsjkz7tScpv2h8EZEtjo8fGFx8rnFSa0vwK9yUvhdft//q6uuuopZs2bx5tvv8FllOy8s2cGBg7U8cN15GNQKUk0a1sXcRPk99/zoY/b72/B4Dn6vffj8LVit67HZNhIOHxlZ1mgySUychkqV0M/WPx4ymRpTzHBiY0cgl59+tjNRfnqOF+n6sRg4cCAfffTREcuPVpiSmPjzfZk4IYEmSdIaQRByv7V4NHBQkqQ6AEEQ3gMuliTpMXqibUfDBvxgpXBOf4gHPq6iOMXIaNXhZPuIGOGvm//KVvN2hghh7hh0P5M/aOXikRn8s76DEr+FS7zLKJWcyAImuPxNKJvRZ9/r33+TDnMXYm4CQ4cPh4AL3rsa6tfA5D/QXH4VD3x+CzvMO3j+oIYgcqxxM5h960hS84/8Bvl8cxd1vgDvDMlHLz+5qc3u7m6WLVtGfn4+Y8aMOe761nYPji4nzVWV1G2vwNbeilKjofiMKykcNRZVMEzH448T8cegmXgplrdWIjeZMFx+J9pRo1Hl5uIWwH3AQfNeKy37bEy+ppi41P6FztaOrTy76z8EHJu5KDbAYIWEXZFPfsFveDB9GjKhf1HndruZP38+8cpsfJXpVFgaKByZzBmXFmKI6z9C6NvdjTJVj+gO4dhWj3+ftdcGQx6nRjcyBW1pAuqC2J6+l6cQkiRx0Oxm/cFuNtRaqOl00Wz1ElHJkDQKMuI0XDw5l8LsWJqFCMvtbp5ubIHGowed45VyLk2J4/LUeEaZTl0h+l0JiCIHvQH2un3sdvuocHiodHkJSz0tmsbHGrghM5FzEo/8nxs/9Tz+saKGGz9pwuyqJyPWxL+WVTF7ZCZpphOPKEqSiMtV1TMlcwJ+b9/YEo/nIBbrWrze2pPY7uio1akkJZ2DyTQcmdATMRRkCkwxQ9Fqs3+Q14gS5f8qZ511Fn/4wx948cUXufnmmwGoqKjA6/XS1tbW2wC9sbGRXbt29Sko+qn5PjloGUDzNx63AEdVDoIgzALOBWLpicYdbb1bgFsAsrOP/2Hz2JK9mF1+np8zgo9f/rJ3+UMbHmJh7UKGC1qmhf283pJJWKxHpVdgIcD/Ov/JsBoH4Ugs8tvXg6lv+X1TVSVbF39M7IgzCAXCFGUmwuszoH0XXPI80pAr+OPy6zloO8ivTPcznHup96Vy9V9uP2y78c2T4w/yz4ZOzks0cVbCySUhRyIRFixYgFKpZObMmccsL5ckiR0rdrHxY+uhJUpgPKpDM4QNVdBQ1dDzIOvant8iMHRiz99twKd2oK9PVMHwJMomHBm1C0aCPL3jaT7Z9wpzkyA30Y9Ck8Og4kdISDjjmMcliiIfvv0J8pZcZP54FKkyLr53GJkl/Ve1ir4wnu2dBBudoJDR9XwlyATUuTGYzstDUxKHIll3SkaO6rrcfLithY+3t9Lu9CPpFMSn6dCVxqLRxWMVem769UA9QWg3o5PLGGPSMzM5Ds1RKlEHG7SMjzWcNvYXJ4otFGZxl50FnTa2ODxEDmkilSAwPEbHHVnJjI41MC5Wf8SXHUmS2FRn5c1NDSyv7kSUJCYNSOKxsTlMLk5GJkg4nZU0Nm5BlELHHogk4fXWY7GuIRSyHnvdoyCTqYmNHU1G+hUYY4YgE757VbBSGYdWm3tKXuNRTh/7hv9mBEHg448/5t577+Xxxx9Ho9GQm5vLU089xVtvvcX111+P3+9HqVTy0ksvYTL1P13/U/B9BFp/nxBH/WopSdICYMHxdipJ0gvACwAjR4485lfVHU023t3SzC1n5jM0K5aPDy2v7q5mYe1CbhxwJXbbIwQKp/Delmb+nJLI3yN+7u1ex6QDa/GFFPhS7yLxW+LMY7ex9JkniU1NxyYoKMxNRf3WDLA1wJVvQ/F5LDz4Kds6t/FAyTz0b61CmxBEO35uv+IM4OGDrUhIzCs88anJr1m1ahVtbW1cfvnlxMT0L+68Tgc1G9awa+Uq3K4pgI/MAU7yy0eRkJnN15/nIXM3nX/9CxGvDwGQxxhJvO021IVHr44SBIGUvJg+NwVREtnWuY3HtjxGk30/D2WpiZGFKCj4ExnpVyOTHf3SEkWJ9gN2vlq4HU9tKhqljLGzChlyViZyRV8hIvrDPQ7+Vd/wJgM0xXHohiWhKYpD1k/F5s9FRJJYZ3Oz2urkgMNHndNHpy+IJxhBEEA/Ih5JJRCkpyOoTi5jnMnAxDgDA/SHWxrFKOQMNmpPurPE6UpYlKh0e1lvc/f82N2EJIkinZo7s5IZaNRSoteSr1Ufs2dms9XLPe/tYEeTnVidkhsn5HHNmGwyTBJW63pqar6ku3sVoZDlhMemVMaTEH8mCQmTMJnKEY5xbfe7vSIOufz08M+L8t05newb/ttJT0/ngw8+OGJ5UVERmzZt+hlG1D/f587WAnzTrj+Tr/0ufyJeXldPjEbBL6cW9V1e9TJGlZGbwiqeQGKbWMhlARmqcIQiXzW/PvgwLoOClsUJ5Dw6vs+24VCIhU/+Fb/bzaRf3MYnS5czsGMNBNtgzgLInYAj4OCfW//JWPUkIksSyFN8TlBSkXVR/x49a6wuFnc5+G1eKtnaE/+gFkWRlStXsnHjRsrLyykrK+vzfMDroWbjWmo2rqO5uhJJFDEkX4lMoWPmfWNJL+ybQB9saaXpj7cR43KhTEoi3NVF3msfosrJOeExdXg6mH9gPotqF9HqbiVRE8/fiweAt4ohg18lPv7oUTO3zc/2FU0c3NqJzxVCQkSfITL7rgkYvzGdKYkSgTo73m1mfFXdSCERebwG/bg0AjU2BIWMxDllR32dnxpfRGSP28eCVivzzTbskgiiBIEIQlDEIAgUmbSkmjRoFHJytWpKDRoGGrSU6DX/NSKsPyzBMK+1dvNKazeWUE9T9GK9hhszE7k0JY5BBi2CIBAOu7FYvqC+dTsSRzZYB2iyeFl/sJshRrjhgngKEvXI5QLW5gZqKzcjSUEUihgSEiaRmHAW8fETUCiOX6gjCIpoxCrKcTmd7BuinB58H4FWARQJgpAHtAJXAlf/EIMSBOEi4KL+WheJ3hC+vVZchSaWVnVw/fjcPrYaVr+Vzxs/56bBN2HY+A5hYxbB5hA3Jmt4YJCRuw9+SFilZG9RNqYOD9qhQ3u3lSSJL15+lrb9e7nw3t9RZ7UjF0SKPFtg7keQO4GG3d188sE6Zlp+h1JUY/OtoDC7k0jheaiUR0bPREnioYOt5GhU3JGVfMTzRyMUCrFgwQL27t3L6NGjmT59eu9zbpuV7UsXsmvFEoI+L7GpaYy++DLUhqFsWdzNuEsKjhBnodZWmubOJexyoR85EveqVWQ++5+TEmd1jjrmLp2LI+BgbNpY7hx2J4WRXbS1vMqAAQ8fVZx5HAG2LWukem0riBCXp6RDvoe8QUlcftVs5IemqMLdPjzbO/FuMxNxBBA0CnQjUtCVJ6NM02N9t4Zwl4+42T9c14STxROOsNvtY7fLxw6Hhwqbm5ZQuMeVX5KQdQeItwSZFh/DpMJUJhQlkhJz8tW2/5eRJIkdTi/vdVj5sMOKT5SYlhDD7JQ4zogz9LY8CwattLd/RlfXCqy2dYhiEJlM28eaASAiSgTDIoFwhJEpAnq1Apkk0HXIqk+lSiArcw6JiWdhMo1AJjt1K3ijnL6cTvYNUU4PTtRm411gMpAoCEIL8CdJkl4WBOEuYDk9lZuvSJJU/UMMSpKkRcCikSNH3vzN5SGzF8vr1YQdARaNikeUJK4bl9tn260dW1Hlqrgmbgh0/ZFG2XSGhWW0FBrZonDzknUr7WkyNLUm1AMykBsOV1nuWLaYqlUrGDvrCorGnMFnf/szhVI9mvP+DLkTsLS6WfpCJV55AF2pj7FFZbTM/wqNPAJjf9HvsXxhcbLP4+fp0uyj5hEB+D0hKhbXE/CG8Yc91HRtxBW0khc3DGVHDl++vg9JkuhqrMPS0owkiRiTZ5OYmYXGGIPfJ7B3UxdphSaGnd03dy/U2krjdXOJuFzEXX451pdfJvGOOzCeRB+7Dk8Ht6+8hTP1bi4cUI5eqUR0f0qbZRUZGdeQlTmn72sGIzRUdrN/SydN1RYkCUrGpRJTGOKzFR+TW5rL7CtmIZfLCTQ4cK1q7rHEEEBdFIfpgjy0pQkIShliMILljT0EDtiJvbgA/ciUEx73D4EkSWx1enm9tZtFXXYCYs80qywQAUcIlSdEiVbDuemxnDexgJJUYzTiQo/1Q3f3Kpyu3YCEM6LkI3cOK73ptIT1qIhwtr6NK4wN5Cnd4AK7C+yShMtVjc2+BRDRaDLIyLiGpKRziTWVIwhybJ4gz66u5bPKdlrtPmQCXDcul9+fX4L6JL0Fo0T5MTkV7RuinB6caBXnkdb6PcuXAEt+0BEdBf9+G5Z39iIoZMTeMJCX39nKWcXJZCccLum+/Te38+mCT5ldOJuEPYuJyBL57cA78Quwc2oaEyreQSkG6UowoV5gRTtmApIk0bqvmm2ffcLBrZspGDmW8ZddQ8uGD3EGYGp2Ioy+mYAvzNLnduOXeVk/4h0+uPId1r74AsUx3UiaWIT8yf2O+z/NZjLUyuO6t2/8uJa969sQEh10yaqRkEgRhyLrSqajy4EkSngddkLBECpdHmq9AblCjt0sgbmn3D42Vc/UuWV97BjCViuNv7ieiMtF7KxZWF9+GcPkySTedecJn3u7385vPr+eqwzNZKnCEGzF6dbhsyYjeu+jtXkylfMrcHb7egvcwqEIYlhCb1IxeHIG+uwQ26s20Ly8mYyMDC47/xJC1TbsWzoI1DmQ6RXEnJ2DfmQKctPhCIkUEul+tYpgg5O42QN+MnEWDEf4otXGgjYrG7w+LDIJhSgRaw0hNjpReyPMKElh5vBsRufFozlOn8/TEUkSsdu34nDugEN+Wye4JS7XHrotqxBFPwgq1nMmb3E1LoyUsZfzWc9otqL3esF7pDGiVptJbu7tJCWdg9EwsM/NbEV1B3/4uAq7N8iZA5L45dQippYmk2CI5nlF+fk4newbopwenDrZ1f0Qtvjofr0aRAn/fhvKFD0Jc8tYWN9NtzvI3PG5fdZ/a+9bSJLE3NI5SM9Npk72OAYRms5q5bUmD3/qWkpQKUOXcRnUL0G6roi3/3AfnXUH0BhjGDPzcsaMGYAw/0b2VFuQM4ziy/6EJMHnr+7BYfGypPRF7hj7CyIOD/vXf8G0AVaEsitBfuS0yXaHh412D/MK04+Z2GxudFK9vgV1SQettoNkZGRw6aWXEh/fU83Y3dzIp088is/WxdQbb2fI1HNP6PyJwSAtd99DqKMD04wZWF97DePZZ5P+5BMIx8l7kiSJUMjGns41fFL1FFfoWhAtw/Bab6WlWYfbdtgpXGu0kphpIDUvpdfWQi6XkT0wHkOqnPfee5eO6g5MxhgmZ4yiwBKP9cldAMhiVJguzEc/OrXfnpeOlQ0E653EX1mMbtiJTxF/E1c4Qos/SHsgREcgRODbNgmSxNZGG5UdThyiiFuQ8GnkSPqefw+ZM0iiJUiGTyJZp+LM0fnMHpFJnF7Vz6udHkQiAWy29YRCR3ppgYTbvY9O82cEAh0nve9aCjkoH4HR+DsMhjLWe02ss3sYEaPjf4qzKDOU811sEC3uAH/5bC8LdrRSmhbDGzeMpiw92pbpdCYSCRAIdBAKWZCOXmN2SqKQGzAYinsfn072DVFOD05JgfZ1DtrA9AFEHD1CQFeeQuyMAmRqOa+/3UBBkp6JRT3fQCRJYnnDct6veZ/pedPJdHbido1GG05jSe4y5IotNMv3WvsAACAASURBVIX/yiRbJYqBs0ltGEMHS9hr6aSrsZ5pN91B2YBklF/Ng9fXIKli2KO6gYKsPAS5nrUfHqChspuq4i+IyVEwo2AGa954mXy9BYUUhIGz+j2OZ5rNxChkXJN2dNNISZJY/d5e3Il76LZZmTBhAlOmTEEul+N1Oti84H12rliCxmDg8of+SkbJiSXHS5JEx8Pz8G3bhn7iRBzz52OaNYu0P89DUPR92/2BDhoanqGzc1FvfzxRDCFJIcSwitLaabTW/5Kwx4RapyB7YCyJmQYSMw0kZBrQm/qPXDidTl577TXcLjdnp44hq1GHzCZHU2xCPcGEOjcGZZrhqF5l/lo77rWt6MeknrQ46wqG+KzLwUKznY1294l99McrUIgSelEgRZAxTqfjsowERqWZUBxjevpUIBDsxu9vPe564ZADs3kp5q6lhMOuo64nCEoS4idSWPA7EhOnIAhKwmEXwWBXr3v9t/FGJP7ZJvKGWeoJuDl7fmLkHv6co+TKJAkZzbjdxxulRDjswh9oJ+Bvx+lz8dHuBD6ojCcQljGnvJurh+1F6dvMwR/GWuz7I0UIBrt7xhzo7LfVUZS+RCK+72xdcioQFzuW8vK3ex+fTvYNUU4PTkmB9s0ctJR7yvs8t6PJxq4WB3++uGfao8nZxKObHmVj+0bKEsq4s/h2rO9vxhO+nd3Fb1GQ8zkfaB9mcvtO1GEflM3C9+oahPh4anZupWD4cIaGVsFrL4E2Hs55lI706Thee5tMfyqv/2EDIX8E5SA36wyLeH7E8wTcbiq/XM6cYg/osiF34hHHUOcNsKTLwd3ZyRiOkRNTtb6JGsd6IioXM2fOZNiwYXgddnau+Ixtn31CyB9g0JRpjL/8Wgxx/fuD9Yf1lVdxLFiAbtw4PGvXEnfdHFJ+//s+U0WhkIOGxv/Q0vImkiSSknIB7oiMaks1dY56pM7RZBy4BsmtI7M0jrIz0skbmojiBKbznE4nr738Ki6ni+n+YaQGTRgmpWE4IwO58fiRJ9EfxvbhfhTxGkwX5B93/TZ/kC0OD5sdHiocHqrdPiSgSKfm3pwUSgwa0tUqkhVhVIRptflYc6CLtzc3Ikpw2+R8LhuagbGfY5NEJ4daeCJJ4qEbcRt+fxtixH/csX0XjiaC+q4TweM5gNNViddbxzFcbr6FDIXCiFaTg0zW/3shCHICgU6aml6ivuFpAoEOIpHD7YN8aDhACYFDntN+NHzMZXQKaZwjLWEmH6KkpypTFQ6iaAhT0XD8kfnDKlY0nkWTK+PQMQrUOfJwBo2MSK5kVtFS0gxm2o+vRX9iBFSqeDTqNAz64j5Nv6P0j0yuQaNOQ61OPdT54NT+EvRtlMojBdbpYt/w34xcLmfw4MGEQiEUCgVz587l3nvvRSaT8dVXX3HxxReTl5fXu/4TTzzBtGnTfpaxnpIC7Vgsq+5AJZcxqzyTio4Kblt5Gyq5ij+M+QMXeCbhfq4Rq9xL3ci/oo4/iCbxer6wD+UVz79BqYf8Kfh2/htb2QB8ri4GOxZARVNPi6cpD4A2lt3LPgcJOnfAgPIEcsfH8qv1v2Sq/nwGSIPZ8OESTDIFolege+jd0O47YpwvN3SSbo8wO0dLd0v/kQqvx8uiFR8RUbmZPXs28RoFS59+kpqNa4mEwxSNHs8ZV84hISOr3+2PhmfTJsxPPIFm+HC8mzZhPG86Kfff30ecWazr2LT8FWxNuWi1v0NQZbN+Uy1mrxm5bDJ5sltQtMcQl65n0q0DSC868V6FjiYLr731Gu6Al+mUUzR1EIYJGSflV2ZfWEvEESDp9qH9Tn1GJInPuhws7bKxxe6iNdgjaLRChDJlN9dqG5mgqiNHbgVXmEC3GbevFWfE2buPocDQ0Yce+GDHaf/5KaBQxKJUxqFUGKDfJGQBpTIW4STMUr+Oppnluaz1Z7LBo2OHV0VY6rv/DGWYlzK6GaUfBpzc9I0oSXxWDc9uBosHChJlyGUKZHIlI/J03D21iPLsC4Dfn9R+o0SJEuWbaLVadu7sMWI3m81cffXVOBwO5s2bB8DEiRP7mAr/nJx2Am1nk53S9BhCkov719xPuiGdl899GcMBgZbPP8Y2bAluw26CYQ21rpvQFN2Ip7uFcR1roGgaYbePYEMDTblJGJQhchIkuPIrSDtst7FzWxWKsJG2c7bQGPcFCW+O4HxbT1L9+19UAEmguZX3LcBiYHHFEeNMp6cB6crlO456LE7TXoIaNxOGjmfvp+/RWLkDpUbL4KnTGXbuBSctzKCnKKDtN79FkZ5OYO9eNIMHk/7YY705Z5GIn+rKf7DzMyWulmtR6wRc8jDOoBU1CZQos9EptCiUCgZdmtFjHnuU6b1IJNBnWi3QbsG2Yzc7LOuJyzAzIllPOL6CncEOpC3HcWw/hNxvIr7mQmJax2AtXEZtwz3Q8I3XlGRskMawQLqINtKIxUaxtJez2Ecxe8mWGtCIsaiVyQhhOb6ghDck0urUUdM9BLs/joz4OIpTjBSlGInTnazlgoBKlYBak4ZGnXZMH61QyEFn5yK6LV8daiZ9LCTc7v2Ioh+9rpCExCm9bXyOMRSMhoHExY1BEOTIZJof3EKiPRDkow4bi8x2Kt09X0TK9BpuzYphUpyRRNXhj5B8rfqYlcr94fKH+HRnG29ubKSm08Xw7FhemlvG8NOseXmUKFFOP5KTk3nhhRcYNWoUDz/88M89nCM4JQXa0XzQIqLE7lYHs8sz+OP6P2IL2Hhm2jPE+2PYt/HvdI56HZVgoGb/QJ5tuY5PfzmdKw40cZ1Yj9LTCSUX4tuxE79CTqvNwugUK7JrPoDkkt7X2L2hDm/IjkXtpyq4mdTGXHJtycgHOzhn/AQObN1E3bplnJNei1B4DpT3tZcA+KzLzkedNh4pTCdT039+VkdXCys2dJEkU7PrvX+hNcZw5rU3MGTqdNS679ZsWBJF2u6/n7DdjjwmBnlcHFnPPI1M0+PD5fEcZPXCp2ncMBVELUMvSGa+7hU+b1nJGeln8OiER0nsp5l5n9eQJFyu3bS1f0hn56Ij85gSIC4B4lAi12WjUqcTYxqETHYcL7CQDOXubJS7s0ESCA5uRD1CQ5I0HZ+vEXdEpCYYS00oFpeo4hzZKoZruskUvLiCGro8Sqy+YirF4YiSgnBEwuoN4g32TLPplAqGZpkYlhWHsTeSFyYSCZ/0efb5vPh8zcdcx+OtxWxegigGMBjKUCmPLzhSU2eSnn45McYhP2sJfkSSWGV18WZbNyu7nYhAeYyOhwvSuTA5lkzNdy+OCEdEDpjdVLbY2VxvZenuDnyhCKVpMfzrymHMGJoetR+IEuW/gD8eaKHKfeTs0/dhkEHLI0WZx1/xG+Tn5yOKImazGYC1a9f2KeCYP38+BQVH77TzY3JKCrSj+aAdNLvxBiP4dKtZ3bKa+0ffT7FpAPvee4LOAa+TEDMZZbWW/6k/lxsnFLBHDNPsD3KLZwvIFPhCWZifeJTWxBgkBAZd87s+4izgC7Nq8WZQwfbUtTw75Vmcq7TsVrTwi7kXghBg6dPvcFZBFwXiVrjkWYjvawgbkSRe32QmOymeM4f3f6FEIhEWPvUGsnCQSOtezrj8WsrPn4FK+92E2ddYX38Dz5q16MaOwbt5C7kffIAiqWd87e0fs37hF3TumEVitoBhepgHD9yFw+7g1yN/zZyyOb0NzQMBM62t7+Lx1uL3t+DztfQmPUuSiCh6EVARqxyLurMA0RoElRyy9aytPUBMTA6XXDKn14D2eARanDhW1hOxB1AMFjBOziKiNdLcspMO82KEQ9GngkM/QE//UC/46ek2mq7q+Tke5jYwn/AZ/e7I5XrS0i4lI/0qjMZTp+vB8ajx+Ll7byOVLh+JSgV3ZidzTXoCuSfRAeObOHwhVu/vYlezncoWO1WtTnyhnkIUo0bBxcPSuWp0NkMyTVFhFiVKlJ8F6RuV/dEpzu/IzmYbMnUbn3e+wuTMyVxdcjW1K5+hLe154pRnMHjIv5n7ybOYFGHuPquIOfsayNGoyN+3jqAsi4brbkZuVNGeF09WegKxY/o2qt244CBuyYyglhHWhxlgKubtzVvIG5KExqBkzdtvEfY6KFYegLwLID7viDF+bnHS4g/xcEFGv8cgiSIfvvQ8dpeLlIifqx7/F7Epqd/73LhXr8b8j3+gmTAK76atMDWbWuFFqIJg0M7+dfFY9swifZCGtaULWLl7OaXxpTx39nOUxPeI1HDYRWPj8zQ1v4ooBtFqM9FqsklKmoZcriMUtNPVuaLnOAhiC62BlDXwDWuy4kN6d9Pml0/uAIZ84+89Pb/8aFnDVLYpL2CQPh9Vh59Nuztps/tQygXGFyQypSSZ8uw4ilIMyE+hhuE97YFOH280UZJ4saWLv9a1o5fL+N/SbC5Ojv3ObagaLR5eXd/AB1ub8QYjqBUyBqbHcMWoLIZmmRiSGUtegr6PZ1+UKFH+ezjZSNePRV1dHXK5nOTkZPbu3ftzD6cPp5VA295kRZ8xn1i1iXnj59G67lMaFf8kJjSKYZNfZPW6TawLl/LQyAi14Z6qvsezTdBRjaNaj+mMCYT0G3G2pXPGjOv67Lu7xcXudU2EUh10mjoYnjKc1ioHfk+I0jPScHab2b50IVNHxCFz22HsHf2O8ZWWbtLVSqYnHq7wEUWRcDiMGAnz2bP/Yp/Ni0mj4sb7/4JK8/2qvSRJwvL883S8/C9c92jRfFGBoNJwIHc44uc9VZ8hTxmO5iJiStpoy3ucYaEg0/ISidd4cRz8DV93ifP7WwiHnaSkXER+3q/Q6Q63gbK2VFDZcAuE5aSZb0KdFosiTYcTHx0dHbS3t+PxeCgvLycr69i5cxISoRY3vmoLoiuIKs+EbmgigkKOPRTmxdYuGv0Cgm4CJpsSb4WZT2y1KOUCE4uSuGdaGmeXpmA66fyxKP6IyEa7m1VWF2ttLlyRnmhWQJToCoY5OyGGJ4uzSFaf/LmVDvnJvbS2jhV7OlHIBGYMzeDasdkMyjChPMWtSqJEifLfRVdXF7fddht33XXXKRnBPyUF2tFy0DZ0fQLaVn43/O+IC9qoNz6JSp3KsEmv0OkSefSrLnIFB9dOn8U9jV0Y5TKuiNQiCBJSQglJaV/yXusYNAYDRWP79o3csbIJUe9AkkT2yPcwJ2UOe1e3o49Vk1Uaz/L//AOAkgQ3qAogp2+TdYADHj+rbS7uz0tFcSgyUFNTw9KlS7Hb7b3ryRQK5tx6O/GJSVRVVZGXl8eDDz7II488AkB3dzdpaWnceuutPP3000c9TxG3h/bf/x7XypUEf5tFJNRI6GA21ePvxlurR6kJIUkick0XycPfIq5wNTGSkgRjKRrFkcIwJmY4KSkXotcXEArbcTjtEBaxVe2mLvA4imAMZQn/S8L0kZjNZj799FPa2jqQyWTk5U1g/PghDBly7PypQJMTx+I6pCYXcSlDib0gH82AOMxOP69Wt/KC10WAEhJqXDia2npF2X3TBnB2WQombVSUnSx13gBfWp18aXGy0e7GJ0qoZQJjTQYGqw9fBxPijFyWEndSH1SSJNFk9bKpzsI7m5vY1eIgVqfkzsmFXDcuh+RoH9IoUaKcQvh8PoYNG9ZrszFnzhzuu+++3ue/nYP24IMPMnv27P529aNzSgq0/nLQ6m0t2NSLyFUMZ+inibTrPiSY1kZJyTM8u76VZ7+qRQwreD6jgoDmFyzpauK6jAQ0zYuQJJCsDXyhGozZCTN/ex9K9eEbh8vq52CFGXWhB0VAgUVtYYiunIpqC+XTc+hqrGPPuq8YddElKJvnQelF/VoYvNbajUoQuCY9AbvdzrJly9i3bx8JCQkkC2HsHR0UjR7H6LOm9WnzkZ+fz+LFi3sF2ocffsjAgQOPeY4C9fU03fVLnB1O4u77fzQlvIHw5mQqy2chV7jJPvNvGFM6iEggRTy9wzUIIQKeKo5mo2m1ru53uSacy7DRr6GJT2f16tWsWbMGjUbDjBkzKCsrQ6M5/o042Oyi64XdyHQK4i4t4uN0BYvNFho/b6bZ5iUcq0IISwxo9DHIZOCsy/KZFhVl34lWf5CPO20s6LSxx9Pj1ZavVXNNegJT4mMYF2tA9z0iWtVtDl5cU8eGWgtmV8/VlJ+o59GZg7i0PBNtP9YoUaJEifJzEzk0a9AfkydPxuHor7vKz8MpKdC+jSRJPLT+EUDivsBcQh4r1pGL0OnHcsWbSlps+zmvJI4/1N1J1rC7+NTqJChJXGSUIW17m6BdQZ06lmqzjrGXXkXBiNF99l+5qgUREWegnUhiBJ1Sh1RjQpJslIxL46vX/4HGYGTsxOHwih2yxx4xRlc4wvsdVmYkmajfuYOVK1ciSRJTJk2i7aultNfs4+Lbf8nASVOP2Far1VJQkMIHH86lrCyeV175kEmTcjB3raOq+lcEfWFCwUMXlQT+LhvuTifBSw1Igp5GvgBrBlzgJFvxDImFciJyHX63B78I1aEkJg+4mXzTsQ1fJQnCXV6CzS4CdQ5ETwhFohb98FSSBk7GZvPy5osv0tHRwaBBgzjvvPPQ6/Un9B5GHAG639iD3Kgk6Y6h/LGxg1f3dyD3hhFDIrEmNYPiDPx7YA5p2tO3hdLPiXio+vKlli6+srqQ6Km+fKQwg7MTY75zov832dvu5KnP97O8uhOjRsFZJcmMzI1ndG48RcmGaE5ZlChRovxAnNICrcvbxX92/ger38pOywYCXeczIGTAMvwdwqKL3dY5tNn9vHXjGMZ5V7No+z2sWTKUN1tqMcQKHHj0c8rju6gVRrAhpEGlz6O+Ko+G6sOOpJIo4ej2EdZbCQQCqA7kcIX4e3aEmkkvisUYr6Jx9w4GTT4bVVdP/0iyjhRoj9S2IXc7Kd6/hSUtLRQUFHDe9Ol89cK/aa/ZxwW//A3F447sOOBy7cPvb2XosG7mzxdRqQqRJA8Go5WWFiedLRUE/d9S/ALIUyPopTbkoWDPcSgEFFo9gkFFl9+JK+hlT0BHaf7d/KrsepTH8MeSIiLuje24VrcguhTIZSbiCgZiOCsDzYAee4itW7eyfPlyVCoVV1xxBaWlpSf8PorBCN1v7EEKhFk3IpFHl+3CnKhC3uphekTNr88poTQt2lPxRJEkib0ePyu6HdjCkUPL4Eurk4PeAMkqBb/KTeGylHjydD9MA/GaDhf/+mI/S3Z3YFQruGdqETdOyItGN6NEiRLlR+KUFmhmn5lndz0LQKxQRlZwGgGpgW7DUtLTr+ShT1ScUahnQlEi3e9U0hqcRFKCkX0JMKalmfy4WpSyIA1uJ0p1MgWjrkGh7GtlYevwggRBUzsqdJiVXRTHJ5AXm8iQKZl01h0gHAiQNXAwNL0JukRI6OuJstbqYtGBeq7csQaPUsHFF1/MkMGDWfzU4zRW7uDc235J8biJOBzbOXjw79gdPca2kYiXyt23EBH9XHjOg7z5youk6idxzrgLkawyLAc2s3/hPeSPdhKj3oZ/dyVYvOi6/MRU2xGNAtLFeXQN3EfG6H/x/IFVrKxdiUquYlbR9dw75Jbj+pr5D9iwL6olbPahLoxFf0EemuJ4ZFoFkUiEAwcOsHnzZmpraykoKGDmzJkYjUc3Z/02kijR/X4N3jY3/y9NYpPdipiiZbxMxX9mFJMaE22JcyL4IyIVDg+rrC6Wdtup9wURoM80ZbFewzOl2Vz0PaovbZ4gG2otNFm9vcuqWh0sqWpHr1Jw91mF3DQhP1qgESVKlCg/Mqe0QBuYMJCtc7cCMOFvX3KRTocl9VXkMg0O+Vxa7TX8+twBANjre4xDVcU1+BVlzInfj6GtEkLgtSi4/oV/YExKRhIlnBZ/j++JBJ8+tYPYApEuj5WisToq7K9x7ZgHyI91AnvYu241hnQPxgwf1t3roKAU7IcjcL6IyP/ua+Ky7j0kxds5Z8oUAvZtLHnxJTpa9zDh+gtJG6KmcvcddHUtR6VKIif7ViRJgSD8HpxXEXK9z4ZXhpOgyuPVd5/ngctfpqpxIyqDg9xzf4/C0IVXBM6A5L8okflkqG+aStYtD1NRfRmBcCbXfjUPARk3Dr6Ra0uvJUF7jAbtIRFfVTfuLR0E6x3I4zUkXFeGpjQeQRDo7u5m+9rtVFZW4na70el0TJ8+ndGjRyM7wRu/OxBmdY2Z6k0tNKrhs0l6/GoZWkHg3txU7slJPiWrZk4lpENTls83d7HZ4cYvSigEmBBr5PasZM5LMpGk+v5CyReM8NqGBpZWtbO71YH0rZaeBrWCOyYXcPPEfGJ10ennKFGiRPkpOCUF2rerOLvdAVpsPsqSXHSnVJCTeRMv7fKiU8k5d2AquM04bD13lbX2enTaQlpW1TJAXoVfq2W414AxKRmnxceSl3eyx7wX6RuNpZMMftJi60lVreOuZHDUP0RvgyY9FF4Ee/bfCvkAe2HHtX3GeytAds/fzR1LANAVQ2ExuPkPO3eBINOQnnIroa4L2bfMT0uNg0hIRtOW4ShU8zlrbg4FM85ic4WTEWfcT/dyG946BbHebCJ1AurCAjSbJBSWZkIPDsQ52M+mvTcS9DXxZreKYUkTmTd+HmmGtKOe11CHB8+WDjw7zEi+MPJ4Dabz8zCMSyciiFRVVbFt2zYaGhqQyWQUFRUxbNgwioqKUCiOfqlIkkRVq5N1B7vZ1+GkstvNQYOAIkWLr0iFKiIx2qjjxvwUpsTHnHQ7oP9Gqt0+/nywjdU2F5kaJdelJzIxzsC4WAMGxQ+TgC+KEgt3tfG3Zftod/gpz47ll1OLmFiUSGlaDLJDAlohE1BE37MoUaJE+Uk5JQXat6s4dzXbSUIglLgIQZCTnHYdn71VyfSBqehUCti/DnskHY3MysrUSQz2u/G0t5BfLuFvN6LKyaZ2h5n3PlrBsuzXsKd09r6WLqTjcmc5JUPWU+OXscJ58hGJQdZBGINGtiRvISKLgAT51qHoA7EACAjEdJehtZYBHSj13eiztqPWRMia8nuEVa20+c5BqYEJh9LUBAEiEQ/e5C6U8QYIyZB/2khgtJ7WrFYc5j0EIwHsERUzhz7M7AGX9xuRinhC+KsteLZ2EGxygVxAOzAB/ehU1PmxdFu62fDlSnbu3InP5yMuLo6pU6cybNiw405lVrU6mL+9hRXVnbTafUgKAU1JHK5SA4IgMMYc4gK3ilkzS9ErT8lL7WfHHgqz0GxnfqeNWu/h2lpLKEysQs4jhRnMzUj4zlOWR6Oq1cEDn1Sxq9nO4AwTT10xjDH5R4+6RokSJUqUn5bT4q65s9nOVLUXZ/paUuJmsrYWXP4wl5QfcutvXI8jnI89xYdZbmD0xg8ZdeYYFF3r8LQkcTB/DO8seoqKoiUkaON5fNTjxKl7kt8Pbt5EctZLCMpEXmtzM71gFtNzpwNgaWtm1WsvMOaSK8jybIH9y+HKt0CmJCJJ/G5/C1qbC4W5BVeghVum/gVjfCLmzWFad4eRayAiegERTZxIziQLKUUejIlB9uyRkZMbT25+Gi+9LEOlSiYxYTJaXR4CkDZiM4H6dSTtvJLM++ZRf9utuGUt/GZMhI4GFyNSRnFB/gVcknMOJrWpz/kSgxF8ld14K7sIHLSDKKFI0mK6II8vu7ZSWb0KanvWjUQiyGQySkpKGDFiBHl5eQiCQKM/SEt/fdIkicpWB+9VtLCt0YpCqyBnQCyDk1LZL0VwRiJcYjRy/dIOchINJN1UhqCMWi58G0swzJ8OtrLQbCcoSQzQaTgvycTXEjtVreSGjERif2Bh6/KHeHLFft7Y2ECCQc2Tlw3lkuEZ0erLKFGi/Fcgl8sZPHhwrw/a3Llzuffee5HJZHz11Vc88cQTva2eHnzwQSoqKli4cCFq9Q9TcHUynPICrcsV4N0tTTyWvwZJFiF3wG3886MWUmLUjC84lAC/fzn2yDz2FsUhE0WKLc3UllaTq9TwRrFAh/JJ1ILIjXHFTM+bjkZhBtFMOBTGonobuVxGo+EifNJ73DDoBnJNuQBs2foRGd1aLhx5GfoP34OEQZA1CYCXmjqpE/TcvGcRQjjErXPvI6ukjK4mF7u+3ErO4Hgyzngaq/UrBg96huTkcwHw+Vr5+99v5dVXv+D2O2IRBCVlZU+SmjID4VAvTM+mzXj/9E+SL7qYtF8+xIp3/krWV2t4b4qMkUOmc+ewO8k0HtkmI2zx4d7YjmdrJ5K/ZwrTODED7eBElBkGGhoa2PHFTkpKSkhI6ImWGAwGBg8ejMFgwBYK80qbhXfaLL3eWUclUwmZKQSBvUCaXGJijIF7spJJeb2GiExOwnVRcdYfK7sd3FfTjCMU4bqMBC5PjWewQfuj5uRJksSS3R3MW1RNlzvAdWNz+H/nFhOjiSb7R4kS5b8HrVbLzp07ATCbzVx99dU4HA7mzZvXZ72//OUvrF+/niVLlvws4gxOA4H22492IQ+6UKR9iSlyJn4pna9q9nLDhLye3osuM0FbN14xji1xOsradxI/bSvZcQEOYGAcIvTaslbRXF/VZ/9qtZys7L/xlx3/YkLGhF5xBtCyZzfxGVnodWpo3wXj76ZuewVrln/Go8PPZURDDfJIhFHlw8kqKSPoD7P8pSq0BhWZ4z7CYl1FcfEjveIsFLKxfcfVTDzTzKxLbyY97TLi48f36dko+ny0P/QQyuxs4h9+gL8u/Q1nPrWU7mQNVz/0KgPThvUZvyRK+A/Y8Gxow7/fBoKAdlAChnHpqHJjem/6oiiycuVKYmJiuPTSS1EqD9+YvRGRx+raea7ZTECUGGLU8mhhOvEKBf5QBLsvxPKqDrY32TBqlJw3KJUzChNRymWYFHLKDFoSVT2XkvOrZpxtHuKvKUWu/++++YdFiQ12N+tsLkKHMu9bAyEWmu2U6jW8P7SAMsOPX8XaZPHyx0+rWL2/i4HpMbx4mNGxXwAAIABJREFU3UiGZsX+6K8bJUqUKKcyycnJvPDCC4waNYqHH364d/mTTz7JkiVLWL58OVrtz+c0cEoLtAZ7G07rm/xpeDeiwseBYD7PrnocWUI3PkMmT21bDnWrQVeE2WhjgLqS65OfQyGPkN+hIbnTyDv77yO9JIFz7hjZZ987d+5g+fLljB8/mQPyIBa/hWtLDyf/i5EIrTV7KJ0wGVq3gRjmoFnGpy/9mdVnX45KFBlnacUUH8/ZF12MJEqseW8/zi4fE+d6MdvfJTf3LjIzru7ZnximquqXBAJmRpS/i8nUV2h9TdfTTxNqasLw3D+4bclNXPm/VcQHlOS/8ga6tMG960mhCJ6tnbjWtRKx+JEZlcRMzUY/Og15zJGVdtXV1bS1tTFz5sw+4uxzi5M/7G+hyR9kdkoct2YlYWv3cM+rO7B7Q73raZVy7jszn1vOzEev7v+yCXX7cH7ehGZgArrBx7b3+L9KSJRYZ3OxuMvO0m4H1lAEhQDKQ9FRhQB3Zifz27xU1D9wXlmfcURE1h3sZvGudhZXtqGUy/jTRWXMGZsTTfiPEiXKz868RdXsaXP+oPssS4/hTxcduwvPt8nPz0cURcxmMwDr16+npqaGbdu2YTAYftDxnSyntEDzhu3cVbiSVGMIbfsonoh8QlCKoE6Q+Kzx0E0mEmS4ZxCagZu5nfm4FKmcqTkf4/6/s1+6jqCUSPn5Q1EqD+dptbS0sGzZWvLyBjJp0jSuWXoNuTG5jEsf17uOub6WoM9HZukgpKaNCMDyRetRTzifHTll3FC9AblMxozzZrNjWTP7NnXgsvgZPj0Za3AuMTHDyc+7p3d/tXX/g9W2ntKSx48qznzV1VhffY2WySU82vwI97ztIsciI/v5Z9EN6hFnoi+Me3M77nWtiO4QqmwjpnNy0Q5MQFD0f+MNh8N88cUXpKSkkDCghDdau9nu9LLN6eGAN0ChTs38YQWcEWdk1T4zt761jfxEPTdPzMegVmBQK5hYlHjMvoqSJGFfcABBIRB3ccFR1/u/RlAUqfUG2Ovxs8bqYlm3A3s4gkEu45xEExcmmZgSH4P2JxBFEVFic52FRZVtLKvqwOYNYdQouGR4BvdOG0CqKdoXM0qUKFG+jfQNb6HCwkJsNhsrVqz42Xpwfs0pKdC+ttnIzo9hojFEXMN55KXdS8V5hVzyn/Wo5DLevywVFtzM3uoGFjs8FEz+HLssj0sGPo3s+clIBdNYu2E68d560orO6t23x+Phgw8+wGg0MmvWLHZbdlNtqeaBMQ8gEw7fRJv39kyFZhSXYX3ubqSAjpKzZ/LWyHM4a8NqBKuFwZnns/jJfSBAVkkcY2fm41M/gtXqpaz08d6py46OT2lqeomMjGtJT7+sz7GGxTAH7QfZ1bad9HufQqYTmTf0IL9bmkBhQ5j0v/8N/ZixeCu78O7qwl9jhbCEekAcMZOzUOXFHDd3qaKiApvdju7iyzmzYj8+USReKWe4Uc916Ylcl5GAWiZj5Z5O7nx7OwNSDbx5wxji9CfmeSWFRRxL6gnUOYidVYg85ueZr/8p8EVENjvcrLa6WGtzs8/jI3zof9sol3FuoomLkmOZFGf8yexEQhGRZ1Yd5K1NTXS7A+hUcs4uS+GiIelMHJCI+gey5YgSJUqUH4qTjXT9WNTV1SGXy0lOTmbv3r2kpKTw9ttvM3XqVBISEpgyZcrPNrZTUqB9bbNRXKy5Oav7HvRNozFdmYMkSRzodPHnnEp47l80ewwsaSsh8dIgesGDoeh5ZAvvAYWKA+kP4pdsDFXU9tn3qlWr8Hg83HTTTeh0Ot6peAeD0sCMghl91mvZs5u4tAzq3/8zQ8KNNObMZsBVN9D60WLOaGsjRziTxm1uBk5MZ8R5uRjjNXSal9BctYyC/N+g1xcSifiprf0fmlteI9Y0igFFD/TuPxQJ8Vzlc7y55018YR/nVYgMaRGpumECr3zeTaR6H0m//jWy2HLaH9uC6A0jMyoxjElDV56CKuP4oVe32826dev4orKKjWOmctAeZEq8kXmFGeSqlaw90E1FlYXfrGuhze5jZ7OdgRkm3rhh9Am38Al1+7C+u49QqxvD+HT0o1JPaLvTBUmS2O32sdrqYrXVRYXTQ0CUUAoCo0x67sxOoVSvoVivoUCn/sHtMI5Hi83LPe/uYHuTnf/P3n2GR1WmDRz/n6mZmUx675UUCISOSAk2EBAUVwSsuwq6u+q6rquy6qqruyqWra5rW3XFXlEUBZTee0IgQEjvySSZkulzzvshEolgRxhen9915cOc8pz7DCX39bT7nII4Zg1LYVJenChWLgiC8A3a29u5/vrrueGGG/p1dAwYMIB33nmHCy+8kA8//JDi4uOPev3YgjJBO8KgSce4cxhh56eiMmpp7HYx1b+SWXXPQPqZbN4XR3zOQRJjWvnIP5dHqzdC/RbqCx5m/ccOzM5GktK/SDQ8Hg+lpaUMGjSIxMREaqw1rKhdwdyCuRiPKgEV8Ptp2F9OXFIcmU2v4TAlknbtk/x5w07OrDhMrGM07oDEWVfmUTA26fO22zhw4B7M5iLS0q7FZiujfN+tOJ2VpKRcQU727ahUvT1Sh7sPs3DdQvZ37mdyxmTOjhhNxhOPoMtLYvDbpSgBmegb78XbloG7shp9bgTmiSnosyKQvmI7hO7ubsrKyggEemszOp1Odu3ahU1S8d7o85A1Gh7NTWGIrOZ/Kw7xYWkzXU4fWrVEYriBpIgQ5o1O49ZvubJPURSc21vp/qAK1BLRVxRgGPj/Z95Zm8fHGy2dvNbSSeXn+5MVmkK4OjmGiZFmRkeYMKl//CTI65dZc7Adly9wzLmuHi+PLT+ArMA/5g5lxpCkHz0eQRCE05nL5aK4uLhvm40rrriCW2655ZjrRo4cyfPPP8+MGTNYtWoV2dknf+pOUCdoXo+FlqHPYY2Ohn0SLVY30wZ+RqkuCW9KCri3E5/l4DA5mGznomz6GXWBM1i6Kpf4dB3pn72AfuK8vvb27t2L1+tl6LChLN63mH/s+gd6jZ55+fP6Pbd+Xxlel5Mc+6eERnvh8hepa+3AvXoVsbahGAwGpv5qMPEZvQW+AwEne0rnI8tuMjNuZN/+W2ltXYpeH09x8YtER40DepOaVype4fHtj2PSmvhbyd84O/1sWv7yF7rsDry2A+jz8jGO/xXe+hB06SGEz8lHn9V/n7OjuVwu1q1bx5YtW/qSMwBJkhg0aBDvZw7CY3PzYk4a766p4a49TYRoVZxbmMCFxUmMz41F9xVz176Kr81J17uH8Fbb0GWGE3VpHpqI039Y0ycrrLRYebW5k087bQQUGBVu4vG8OM6NCTshZZW+C0VRuP3tUt7d1fiV1wxJCeefc4eRFm38ymsEQRCEXkf/nvyykpISSkpK+j6fd9551NXVnYSoji+oEzRZcuGOq8RjqwbA7/IQEu7EFhKOq2sLoUluHOo4npJv5O/Vm1EpXqrMVzHzsqFE+ZqofbEJbWpqX3s7duwgMiaSP5T9gTJLGeOTx3PXmLtICu3f87Bn+UfEhTgYGt2MMvzn9EQW8tKTTxHWnYsmoOP8Xxb1JWeKEmBv+W+x2/cRETGS0rLrUan0pKfNJz39+r7FCVaPlXs23sOndZ8yIWUC9429jxhDDJ6qaroWvwyKgnHMBDQZlxGwqom4KAvTqIR+3a4ej4d169ZRX1/fd6y1tRW3201xcTElJSWEhYX1nfuow8Yn5TWM9qhZ8O9NqFUSN0zKYcHErO+0/5Xs9OFt7sHf5sTX1EPPzlYkrZrIWbkYR8R/Za/e6cAjy2zqdvBJh40P2rrp8PmJ02n4ZWoccxKjyDGeuon1T6+t4t1djdwwKYcLhyYfc16SICPa1LvdjCAIgvD/SlAnaHp3OmdOXNeXALz69F+Y3PQwnRc+w/MP/Z2hMc3cfPE/SK7zEdexHm9oFCW3zkZSqbEt2wKALj0dgObmZpqamrCkW6ix1/Dw+Ic5P/P8YybY2zraOLx9E/MyDiOZYpHP+iOvv/o6aksEJlcUYy/OJiHzix6tffvvoKNjJSBhs+0hLe0XpKfNR6f7YrivrL2MW9fcSpuzjVtH3MqVhVciSRKKolD/y1+CLBMyZByquLloIkKJmpuHNt7Ud7+iKOzdu5fly5djt9tJSUlB/fnwWnZ2NuPHjychof/cryanh9+U16Kx+yjd3Milw1P57bkDiP+alZhfFrB5sK2qp2drCwR6Z8JLejXGwbGET81EbT59C2fvsjl5rqGdZR1WegIyBpXEWdFhXJoQxVlRYWhOcdKzqqKNhz6uYFpRIr87b4AoLC8IgvATE9QJmiZC3693JrN9NR3qWHZs2odaJWHJG4AVFRdUOckw7kY7cCqSqjdx8db2dkvqPu9B27FjByq1ig3KBu4YdgdTs6Ye8zy/z8c7D91LnN6OWaumbeAf2flJKW2VLkJthahyzRSf01sV3evtYG/5zXR1bQLUpKVeTVr6AvS6/vOw3jn0Dg9sfoBYQywvnv8ig2MH951rffAhfLW1aDNHo8m4nNAxSURMz0bSfjHk2NbWxkcffURNTQ2JiYlceumlpKQcW0Wg0+dnt82JV1bYeLiDxY0WnBFaJjjgz7+ZQG7819fVPJrs8WNbUYdjcxPIYBoR31uNIM6IKkx32iYLXlnmw3Yrzza0s8PmJFSt4sK4CCbHhDM+0nxStsL4NnbWdXHTq7soSAjjkUsGn7bftyAIgvD9BXWCJum/mIQdcDso9u7kY37N4dWfotYP5jnjDPRemVFdFeiibJB7bt/13ro61LExqIzGvsUBbWFtpEalMit31nGft+r5p7DU1zEsNpKX2hcSeF8HyIQzEJtRxYJri5BlL/UNL1Bd/QSy3INOF8PIEUsICenfg+WTfTyy7RFerXiVMxLP4JGJj/SrmRmw2+l65TVUUVnoh/2CqFl5mIbH9513u92sWbOGzZs3o9frmT59OsOGDUP1+SrBgKKw2+bks04bqzrt7LI5UY4OIErHvPAwHj876zt95956O5bXKgh0ujEOiyfsrFQ00aduJ+UTod3r46UmCy82dtDq9ZNl0PNAbjKXJkRhDpItKBRFYfXBdp5eU8WmKguxZj3PXDUCoy6o/4kKgiAIP5LT5n9/y56PiVF81NZZAYXhUfU8laam0AoDwktBUkH2F/udeetq0aX1Dm+Wl5fj9Xopiy7jvuH3oVEd+9qHd2yh9NOPMZgHcMB/HuGmHizRLXh8XpZlFjFmcAJ+90o2ly/C7W4kJCQNt9vJkMHP9kvOmh3NrG1Yy5LDSyjrKOOqwqu4efjN/Z7p73BRf9P94PdiGDaL+F8Po0vdw5OPPorf7wfA5/MRCAQYNmwYZ599NiZT75DnZxYbr7d0sqbTTrc/AIqC3hFA3epE1ekhMVTPlWdkcPaAWPK/QxkhRVawr23AtrwWtVlH7ILB6DO/enFCMLP6/KzqtLPV2sN2aw/lPS4CCkyKMvN4SiyTosyogqRXyuuXeX9PE8+sreJAq52EsBAWnp/P3NFpok6mIAjCT1hQJmhHNqrNycnpO+bf9wHLO0bgd1WSl1NIRORqujQapnb7SdftgKSRYIwCwFNVhWfffsxTzycQCLB+w3ocegdZaVlMTJl4zPN8HjefPf8U5tgh+H3jCdc0Yy7yc6CmEdM5U9nr0/Erz0PsLV9JaGgB+Xk3cODgXSQnzcEYWsDO1p2sbVjLmoY1VHZXApBqTuWh8Q8xLWta33MURcGxtoHupftxl32KKiqFlL9ejUqrZu2by3pXmA4deuQ7YNCgQX3DmbUuD3cdamSFxUasVkO8S6ZnXycZsophSeFkZCQwYLSZcwvjv/OqTG+9na4llfgaHBiKYoi8KAeV8fRKDjyyzPIOG++2drHSYsOrKBjVKoaZjdyUFs+s+EhyTT9swn9nj5fXt9XT7fSemJj9Msv2NtNq85AXb+axS4ZwwZCk7/znJwiCIPz/E5QJ2pGNakeMGDEfgIAf14EtlFtyUetzODd+K0+m9O7In1fZRGTIAci9CwBfaxv1185HMhiIWbCArVu30mnpZE/8Hv428m/Hnc+z8c23cNqz0RpHY1Q1Ex+7jLU1hWRle3jYZ2eQUk+sbw/Z+Q+RkHAR23ddhizpWdzqYNWuidi8NjSShmHxw7h1xK1MSJlARlhGv2cpskL3B4fp2dSM9/D74HMSf/sfUWnVWCwW9u3bx9ixYzn33HOPie/JujYeqm5GLUnclBjDpk9rKavv5pqxGSycmv+9d4oP9PiwfVJDz7YWVKFaoubkYRgSe9rNeVrXaeeOgw0cdnmI02m4OjmGmXERDDEbT8hk/3a7h2fWVbF4cy1Ob4AQ7YlLoIalRfLwxYOZOOD0+94FQRBON2q1mqKior590K666ipuvvnmvulD69ev55ZbbsFm660Tesstt7BgwYJTEmtQJmhfZi/9mE/q0kEVQeGYi9C3/ZdPB/+JwYYQstzbIATIOZeA3U79ddfh7+4m/cUX8UVH89nil2g1tDJq0CgGxgzE6/bTVmuHz2tvNVQ0UrY2Ao0hCZ22geTwd1mrDCE2tpqWlBAsRDNCXs7dDWr0jY8z2vgAE00O3uzUUhHYRUlqCRNSJjA2aSxm3fEn4it+mc43DuAq7UCfK2F/71M0iYlEzJwJwMaNG1GpVIwZM+aYe5e0dXHf4SbOiTKT3eLjxcVl6NQqnrxsGOcXJX6v71ORFXq2tWD7pAbZ7Sf0zGTCzklDFXJa/HXo0+71cW9lE2+3dpFh0PFiUSbnRIeh/o6Jjiwr3PN+Oa9vq0fpP5MPAL+sIAEzhiRxw1k55MR9+wUXgiAIQvAwGAzs3r0b6F2EN2/ePKxWK/fddx8tLS3MmzeP9957j2HDhtHR0cHkyZNJTk5m2rRp39DyiRfUv5E7m3t45b7NWA6/hzdgQBc2g9YqJ8/K/2S7bOaccjtp+p349bGo4wfRcO18PJWVpD75JIaiQSx5fwler5farFoeHPkgB7e1sOGtSpzWLw9RWZlwaQpblj7DBvUQUqJrGDDkEEv8E5nmf5XInk+YnhBBhNyACgWHNotfTniYopghqFXH771SZAVfkwN3RSfOsg78rU7Mk9Nou/cqAJIe/AsAdrud3bt3U1xcjNnc/xf/Yaeb31XUk6HSUPFhNettHmYWJ3HblHySI777xH1FUfDW2OheWoWv0YEuM5zImdloE0zffHMQsfr8/Ke+naca2vHJCr9Nj+em9PjvtQpTURTu/3AfL22uZWZx0nG/V51GxYwhSWTFfnN5LUEQBOH0EBcXx9NPP83IkSO59957eeKJJ7j66qsZNmwYADExMSxatIh7771XJGhfptaokL278Hpa0JlKkHQxxIRUszlKjyJJjFGpyTTtQcqdjrtsL85Nm4n/wx8IHT+O5uZmdu3cRWVYJTcOvJVVT1TRdKibuHQzJZflozeoqdi4jt2fvEfJlRezce1bNJvzGKTeT3jBdnxemMoboALMoNOEkJgwn4TEWYSacr827oDdS/vTpfjbXSCBLtVM1Lx82hb9Fn9rK6Yzz8T0eW/Z5s2bkWWZsWPH9mvD4Qswe9shXB4/zRvbGB5n5pnLhzM0LfI7f4+KX8ZZ2o5jQxO+Rgcqs+60HM7s8PpZ3NTBf+rb6fYHmBEXwe2ZCWT/gM1k/7byEM9vqOEXZ2Zy9/SC0+r7EARBOG0tuwNayk5smwlFcP5D3+mWrKwsZFmmra2N8vJyrrrqqn7nR4wYQXl5+YmM8lsL6gTNFKHGUvsJqSYnbdqhhAwxM6b7n7yTv5BItYrLi2vR1thxpJ5J5/IVoFKhTBhPV1cXby15C4/KS748gernQKu3M+qiVLJGRCNJsPbTNzm04mPsafBJ1VN4lWJyqWJwyjrWesx8ormS3doSlhUmE6FRo1IZkSQVPi90ebu+MmbFL/cWD+92EXZ+GvrsCNQmLc0PL8K7fQekpxO66GG6urrw+Xxs376dwsJCoqOjgd7i12/ubuQ/HV1YY3RkN7i5b/ZQzi6I+17JQ8Dhpf0/pfg7XGjiDERcmINxWByq06iY9g5rD/9t7OCDtm68isJZUWYWZiVSZP7+5Y38AZknVh3m758eYvaIFJGcCYIg/EQpn095UhTluL8HTtXvhqBO0GxtrahVmUSaB9Pigb11a6nTzGSFJp2Mxircn/0OMPOvZRVMWL6WrswS3n9iBbLkx2O0ENqTTnhTDk5DMz3mKuzlzRzuqiAsvA19KAy6DHx+DaWlUwhV27g4sIxPpAKqd5zLprGTyW5tZPHaFd8veDWwqvcnub6BsRs30pKYyPrRo1D++c9+l44bN47ttZ0sXHOIclUAOT4EYnRMN5h4+uohqL7nRHfFJ2P53z4CVg/RVxYSUhB1WiUhtS4PfzrcxIftVsxqFVckRXNlcgx5P3A15pYqC/e8X05Fi52ZxUk8OEtsBisIgnBSfceerh9LVVUVarWauLg4Bg4cyPbt25kxY0bf+R07dlBYWHhKYgvqBM3n8VAQ4aTCM429ugDXDDdRVbUdt/ZC7lVtJ54OKoacxyhF5lD7NbgCaYTawWVsxEMrEVoDA6auwxjTjc+3l0CgGo9fjb0+GrQhRKdmU7opkoBXw4UhH+Iz6Egb8hiHCrT4nTA/N51BBenfOl7XfguuMguGQdEYCqNBlpFefx3thg14jUYi7vwDM2Ni8Bw1D71Ta+Dasg52BjwoqXr0wPlR4VydHsvocNP3ThwURaHz7YN46+xEXZbfG89pot7tZXGThf/Ut6GWJO7ITGB+SiymH7ipbJvNzYPLKnh3VyPJEQb+c/lwJg+MF8mZIAjCT1B7ezvXX389N9xwA5Ik8etf/5rRo0cza9YsiouLsVgs3H777fzxj388JfEFdYLmVWnpUmYhSz6a002M1lawITaJOK+FiVUv0JM0mN31yVj2n4Va5yBl9LOYEg6xZ+9IQrwhFJY8giSBzwdqXSIfNIQTtyye2KgMLr//MZa+9x4u70HStTvI9rQRGHMrQ4eO5MHdlaTJXi4b/vXDXopfxrXPgqeyG/fhbgIWHYbiwURdmodss9F4y+/o2bAB1GoG/Pc5QoYM4ab9dbzVevQQqQvUCilouDU3hZmJUSek5JD90zpcu9sJm5yOsSj2B7f3Y6t2enijpZPlFivlDjcAP4uP5M7sRBL1P6zmpy8g8+LGGv628hBev8yNZ+Xwq5IcDKfRMK8gCILww7lcLoqLi/u22bjiiiu45ZZbAEhMTGTx4sXMnz8fu92OoijcfPPNXHDBBack1qBO0EK1Olp9eQyaHMpl5xXDiwvZlfEbFtU9S7crkg9qb8RuiSFF3UD2rpcY+NdP+PeOJ7HaWskblsekkscB6HB1cPmHl1O0Pg6dR8+M39yBpbOL0ooD6F0djBtyCA6BeuAlNLm9rOtycEvG1/esBOxeLIv34621IenV6LPCMZ+ZjGlkArLDQfUls/HV14NKReozT2MsLuaRqmbeau0iptNLd4cLgBi9lgfOyGZ6XvxXPuu7UAIK1o+rcaxrxDgsDnNJ6glp98eyz+HiH7WtvN/WDcCocBN/zE5iSkw4WUb992qzvMnKQ8sqcHkDALTa3dR3uijJi+WeCwaSGXN6rVoVBEEQToxAIPC15ydMmMC2bdtOUjRfL6gTtEDASGpoJSUXzkfy2FDayskK30fqIR9v9DyOonYz8PwdJP3lbUInTaLDbWHF9hUUU8zEYb0VAxRF4fa1txNx0ElCSxgTr/o5Manp/P3BB0CWyRu8m0xPCsSYIS6ft2tbUYBLEqK+Mi5vkwPLi/uQnT6iLs3DMDgWSf1FMtd63yJ8db3F2pMWPUzo2LE8dbCJxxrbUDX2kNmtMHVQCmcXxJEbF3rChtgCDi+dr1TgqbJiOiORiGlZQTl81+bx8WGHlQ/autnY7cCkVnF9ahzXpcYSr/9hFQzsbh+/XLwTh8dPQWLvtiXZsaHcPa2QcwvFcKYgCIJwegjqBE1RYOJEB5LPBSvvxSWbOGOrltWeX5GQrcJUcAeZsVfhtFoJnTCex3c/QZwjDqPJSFJSEgAr61ay//BOfrY/ndRBAxk65QLWffwRXR4/UbpKxk/4LZrnF8C4m1EUhTdaOhkVbiLDcPzeG/ehLiz/24fKqCH2+iHokvvvjeXYsAHrW2/h0WqRb/oNHZPO4Y8r9vE6brTOAI8WpDF7WMoJTRQURcG9v5PuJZUEevxEXjKgX+H1YLHD2sOjNS2s7rSjALlGPXdkJnB1cgwR2h/+V1FRFO56by8NXU5ev+4MRmZ8dZItCIIgCMEsKBO0I7U4C+KjCR9xDrx7HZbS3XxofRRbIJ6M81MZOHgFVdXdaLf1gEpFbV4kS9YtYaZ7JoVDC1GpVHgCHp787DGm7kxGp9Uz5Ve/pcdmZfW6daglmXMuGUysxQ1KAApmsMfu4pDTwyN5x5+zpcgK3e8fRh2hJ3bBYNTm/nOjAo4e6u68i86ISK645zFcIQbYdgA0YAio+HhCHnmRJ3Z4zdvkwPphFZ7DVjSxBuKuHHhM0niq7bU7ebi6hRUWG9FaDb/NiGdGXAT5pu++2e7XeWtHA0t2N3HLuQNEciYIgiCc1oIyQeurxZlqmI9Kw4GdVlbbHsGjhdcmhLP6gmzKdt9DaGghnlU7CBkymN+WPUyOnAMByM/PB+C/Sx5h5EoVMckyIy5Op7X7eZa/1UpAG0pRXj35BX+GV+dBRBokDuHNQ43oVRIXxEYcNy73fgv+dhdRc/P6JWeKorC6007tffcxsrWVv9y4kClKgHWVdhyeAD8bnsItQ9NICvlhk92/9B1hW1mH/bM6VAYNETOyMY1OQDoBCwy+j84eLyv2teCXv1iiapVlPvK52BHwEoLEVK2BcRo9+jYvO9ra2HECn+/zyyz65ABjsqIA7MiSAAAgAElEQVT49aScE9iyIAiCIJx8QZmg9TFEsumFVey03kyyfh+vnJtLRGIYKtmJ1bqTlJg5uMtfp3L2KA5b93JjyI1Y9BYyMjJY8+5iel7fhDZVRe7UOiyOQ+wqH0KbaxAmfzvTZz2MyuuEqlUwagFeReHdti7Oiw4nQquhye2l0ePrC0VRFLq2NCCnGYhONSJZe4DeckxP1bejKi3lX8s/oiIjhyuWfczCgfNIiTTw2uXDGZQcfkK/FkVW6H6vkp6tLRiHxhFxQRYq4w+bu/VD7Kjt5Ncv76LF1rv6UlFL+DNCCWSGgiShrnEgV9v5zK/w2Y8YR3yYnr9dOhT1CSiQLgiCIAinUlAnaFZ3ODurCxiYfJAz/PfxW9MnzDMb6e7eiqL4MDZFYgdeMO5iRtYMujd1k5ubS0d7A9tef42GeBeXzI7C61QI+BdRV7cHbXc7506dhl4fA6VvQMALBRfwVH07nb4AVyRFs7rTxlVl1XjkLxXOzgTQwJ7KfocLDDoeeO8VXGoduTWHeeSSP3Lb2XlcNiqd8BOcOCk+mc7XKnCVWzCXpBA2OeOUTXxXFIXn1lfz0LIKkiMNvHn9GHbLPv7Z1EGbz8+USDM3JceSMvLE9Rx+nTCDlhCt2DpDEARBOP0FdYLmdQcYH/4cReMGU7E9BRcqhoYZsXSuR6UKQVXhRZbAlhrFZUmX8YbzDZqNzdz3z/lkoWPkrAzcjjU4e25mx449JEeGY63YQe6oM3ofUPoGhKdSGzOEx7cdZFpsOApwdVk1OUY9d2YlcaQzxvpJDX6Lm6jZeUiaLxKiMLWarFUraa48gIyENHMWL94/54R+D4qs4K234yrrwLW3g0C3h/DpWZjHJZ/Q53wXLm+A37+1h6WlzZxXGM81U/P4Q3UTZQ4XQ81GnivKZGS42M5CEARBCB5qtZqioqK+z3PmzOGOO+7A5/Nx99138/bbb6PX6zEajdx3332cf/75pyzWoE7QwjUtDB4TBh0V7IrtLS4+NMxIW816tKaBbF77JuYouGXs7Xy8+WNkZBY3vMDPapNIG5tFvPQZsnQ2O3d2UlRURM+2tSTl5mGKiARHGxz+DHnsTdx2sBEVMD02nKvKqsgy6HljSA7Rut6vx9vooG2PlbDJGYTF9R+ulJ1O9i96FKcmhBCNioI7fveD39tZ2k730irkns+HWBUFZEAtEZIbScSFORjyT90k+BarmwUvbaes0crtU/JJK4xmTnk14Ro1TxamMzMuApXYzkIQBEEIMgaDgd27dx9z/O6776a5uZm9e/ei1+tpbW1lzZo1pyDCLwR1gqajh40J8+hZ+QgfZl5GqMVDeUUlh2oMbOmROdOTjrswirdWvMW41lhURj0XBH5JrX4nIckBGlqKqK8biV8no8TlsaV1FQMnTGTFvlY4sAz8Q7izeSgNne0A/LrlACl6HTdExrKz0gL0DuPZV9fj0wSIilQj7WvtF6N16QfYdXEQE0foRbNoafZCc+sx7/JtKB4/ji0teGusqKMN6ArC+s6pI/ToUsxIOjXIPtj3/Z7xQzm9fv784X56PH6evnw4+0wS15TXMCzMyPODMn/wPmaCIAiCcDI5nU6eeeYZqqur0et7t9iKj49n9uzZpzQu6UgV92A0IClM8V756jdeZ5bcXKwvY4svlf2BhJMQ2U9bUoSBBT8r5H27g43dDi6Oj+SxvFRCTtEKUkEQBCH47d+/n4KCAgAe3vowFZ0VJ7T9/Kh8bh91+9de8+UhzoULF1JQUMBVV13Frl27vtPzjn6fIyRJ2qEoyojv1NBXCOoeNHV4DPeP+Qcuxc99qr8wOeQwWT1v0emXmRF6I/b7HmTNxdmcOXgOezbDz4vjqKt+iqgBVkJNl7FuvZW8AQMoKSlh+TP/wm23M+OWhVQ3HSTzg2v5X9ocXoo9m38VpJNnCjnm+X6rh85XK9BEG4i8OBfpqNWBfquV5rvvxt3UgkYOEHvbbYSOGf2N7+Q+0Im72tb3WbZ78LU4AdAlhxI6LhltnPEEfHsnlk9RqHR7KHN5+LSnhzvqW0jUa/lzbjK/SI4RO/QLgiAIQe94Q5ylpaWnKJqvF9QJmiw3MiAkBFfnEAKJei4eOJl7l/+VWbmzaPj0BYZbGymc8QDrtxwgNjYWdet/GDqigpTkK1m9WiEjTMU1s84Dvw8ObGHCzJ+hj9DTuPIlpqrqqMwdzxBTBBcPOHbXfUVWaP+glFiVhvgri9BEfZHABbq7qf7VTaQcrsaNhCa/kOJZ5359YXVfgK4lh3Fub0UVpkP1eaFuKUSLYUo2xuI4NBHfr/bkj0VRFNZ2OfhPfRubuh24P1/VOths4N+F6VwQG4FWbGkhCIIgfEff1NN1MuXk5FBXV4fdbsdsNp/qcPoEdYKm08Uyclsrz46d2vvZW4M74CbFnIJl72J8Ri0Z6UOofWM56SkWIjIqCJGGkZR0M83Nf+Wcc87BYDBQvmYjPiQ+HTCc/26rYEPzcrpSx7FRDuX++MjjPtu+ph5vjY3I2QP6J2cOB4d+fg2+Q4dZlzSIksY9ZP7prmOSM7/Fhez0AyB7A1iXVuFr7sE8KZWwc9P79cYFmx5/gM867fyrrpU9dheJei1XJsUwMtzEqHCTmGcmCIIg/L9hNBq55ppruOmmm3jqqafQ6XQ0Nzfz6aefcvnll5+yuII6QdMrBgg4+MhQQDJaKjs2oZJU7Kl7i8kdoM9JY8vW55BlGXP4FroPZDHz2v9xqLIGgLS0NGQ5wAfbtvPS3N9gsfq4RVVNiruZD9JuRi3BhfHHVg0I2DzYVtZhGByDcWhcv3N7fn8X2ooK/n3G5dyw+23CJk/GUFgI9O5R5trbgWNzM95aW7/7JIOG6KsHntLVl1+nzePj2YZ2NnY72G134lcg06Dj8bxULk6IRK8S88sEQRCE05vL5aK4uLjv85QpU3jooYd44IEHuOuuuygsLCQkJASTycSf/vSnUxhpkCdoeOy8kDqbzR4Nj+TF82npFhL0es7X7CWhTYs98yDl5VFotak0fmLm3KvvRqM1UFdXh1qtJikpiU3vvsnzuaPQmcN4dXAWk7a9gaIJ4dGQ4UwIMxOrO7Y3yLGhCWSF8C9tAlu+pQzd6uWsHXwOvx8UimdjDzHXXweAu7KLzlcPIPf40ESHED41E81Rc8l0yaHH1O4MFtusPVy7txqLz89Qs4lfpcYxNjKUcRFmNEHc0ycIgiAI30UgEDjucZ1Ox6JFi1i0aNFJjuirBXWC5vE6uT/jWiZFmRmt7+SR1p1MCPXSYYkmyW0nYcw12Fr86Hq6CQvPI2/MOADq6upITk6m5VAFz+8qw3p2Pi8MymBSdBjUrseWMIwDfi03HGd4U3b7cWxuxlAUgyb6i2LebTY3m/70KCNUGi665ybsP7+c0EmTCMnPp2d7K13vHEITayBqbh76rIigHsI8QlEUnm/s4I+VjaSE6FgxJI+C0BNbwFwQBEEQhO8uqBO0em008SoVM03VzPnoNhQU8kMCTFJ+jYWHsCcPxVO7EamtmTOvuwFJpcLr9dLc3MzI4cNZ+o9H2Db5CnINOs6LCQe3FVrK2DrwOgwqFVNjjq2R2bO1BcUTwDwhpe+Yyxvgjn98xC1V21FdPBvdprUErFair1uAdUUt9k/r0OdGEH1ZAaqQ4P1Kt3Q7uP9wE3sdLgAUwCMrnBsdxr8K0gjXBm/sgiAIgvBTEtS/kXvUBu5LNvDMrtuJ0JmxuDsZkTgOaXNvofIdzc2o5ABJsbFkj+jd4qKxsRFZlmkv20l5WByt4THcmZHQu7N9/VZQZF7W5jMlJgyTpn/dRsUvY1/fiD47HF1K70oORVG47e1Site+i6TVkHP9NdTMmYtp7Fg8VSZ6ttZhHB5P5KwcpCDaB6zF46Pb37tIwRmQ+XddG0vbrSTqtVydHIP686HbTIOeeYlRYud/QRAEQQgiQZ2ghQechKlraXO2kW6MxKwLkJ/1axwvLsaZl0dldTU6SwsT5l/fN1esvr4egLY92yn/+e0k67VcFPf5UGbtBmSVhjWmfJ4+zvCmc3c7ss2L+WcD+o69urWe7RtLub5hJzFXXI7js1UELJ2EjPgFPVtbeldlnpceVPuAvdDYwcKDDRy9BbFBpeK2zASuT43DGESJpCAIgiAIxzppCZokSSrgfiAM2K4oyovfdE+K5OblAy+TFppMnaORC2LjiYgYgeXA3RwYMhgUmbSYSNKHDOu7p66uDqNWQ3NCGvu0Rh5Ii/tir67ajdREDiREb6IkKqzfsxRZwb62AW2CCX1u78rOihYb972/l7/Ur0Kt1WKefhENv76R0Mm3462TCZucTtiktBP1Ff1giqLwaE0Lj9W0cm50GJck9K4YlUBsjyEIgiAIp5FvlaBJkvRfYDrQpijKoKOOTwH+DqiBZxVFeehrmpkJJAOdQMO3ea7PGEVpeynD0+awVx/Jvqg8ri89TM+kqWS6O2kxhFI9/mI27KvtvUGRia2tpVVvZMt5lxKlVTM38fNtLbxOlMadrEydzTkxYf02WFX8Mp2vH8Df5iRqbj6SJOH0+rnhlV1cVbWWwootaPOm0/lyO8axfwQgfHoW5nHJ3+Y1ToqAorDwYAP/a7IwJyGKR/NSxQpMQRAEQThNfduxrheAKUcfkCRJDTwBnA8UAnMlSSqUJKlIkqSlX/qJA/KATYqi3AL88ts81OLuIixuHh8zDZ8+nxYS2N1lJ2AMQaUolGUP5JCkY4/dxR67i8PNrah8PmojE9CZQlmYlYhJ/fk8s8btSLKPNebBTDlqcYDs8dPx/F5cZR2ET8vEOCQWr1/mznf3krFrPRftWoImZSSRl8/FXfYakuYAMdcOCqrk7ECPm+k7DvG/Jgs3pMXx13yRnAmCIAjCl6nVaoqLi/t+Hnqot19p6dKlDB06lCFDhlBYWMhTTz11iiP9lj1oiqKslSQp40uHRwGViqJUAUiS9BowU1GUB+ntbetHkqQGwPv5x+NvRPIldkXP4ZDzCXOs5DxjNf8a8wTtr73Gs42HUTxO3i7KIGlAft/1W7du5SNgVvkG5v9ibv95YTUbkJEojSzi6ajeBQABu5eOF8rxNfcQOXsApmHx7Krr4o63y9DvK+Whna+hjs4h6ZEHsTxxL4H2UuJvuR9N1PGrD5xsPlnh33VtPFbTQqhGxX8K07nwKyojCIIgCMJP3fFqcfp8PhYsWMDWrVtJSUnB4/FQU1NzagI8yg+Zg5YM1B/1uQH4umrh7wD/lCRpPLD2qy6SJGkBsABAO6CAKXzMjs6XmTe8N5vdvXkznogIssNC+iVnAIcq9iP5vAw765xjJu0rtRs4aM6lOLa3V81TZ8OyeD+Ky0/0lYVIZh1rHttCU3sP16sU8rcvRgqJIuHBx5Gth+hZv574hXegiTr5lQDcAZmegEy0rv8f1/2Hm3i6oZ0ZcRH8JTeFGF1Qr/kQBEEQhKBjt9vx+/1ER0cDoNfrycvLO8VR/bAE7XhjaMpxjvWeUBQncM03NaooytPA0wDxefGK37WXjLAMxiSOwd/VRa3djjZEz7lXzj/m3rraWjRuJwNLzul/wu9FadjGmvgLmBITTs/WFrqWVKIO1xP180G49rTh2NJCHAphxhCiLGU4XVZibn0Q8/gcqmf8Dl1mJpHz5n1T+CeMoihstzl5o6WTJW1dXBgXyaK81H7XXJcay6hwE9Pjji1XJQiCIAjBquUvf8Gzv+KEtqkvyCfhD3/42mu+XOpp4cKFXHrppcyYMYP09HTOPvtspk+fzty5c1Gd4hKHPyRBawCOzhhSgKYfFk5/EfoI9rTv4baRt6GSVOz4859oj40lNiyUhKyc/sHU1eIJyKQnxKPpUdHx5l78nW4AtIFyov1uxjfnYf7vIbocPiSdCkkFlhfLkb0B3pG81BaE89gVw2m86VXUMTFEXz2dng0b8Rw6ROJDDyJpf/xVkLUuD2+1dPFmayc1Li8GlYppseFcGHfs0GVyiI7kkOAsHyUIgiAIweZ4Q5wAzz77LGVlZaxcuZJHH32UFStW8MILL5z8AI/yQxK0bUCuJEmZQCMwBzghXUySJF0AXBCdGU2mOpOZOTPZs2IZlu078JScxYgpU4+55+P3l0AgwISEibT+fReSXk1ITgRIENJZAU6oiRjCkA4ZyahBn917Tq1VcWt1C/t9Cp9cPJhAdzf21WuIuuwyJI2GzhdeQBMbS/jUY595orgCMh+0d/NKk4XN1h4k4MyIUH6bnsD02PBjNtQVBEEQhNPZN/V0nQpFRUUUFRVxxRVXkJmZeXokaJIkvQqUADGfT/a/R1GU5yRJugH4hN5tNv6rKEr5iQhKUZQPgA9MWab507Km0VF+gA1P/oNkc+9QXmZmJgDeRgddbx6k22Wj0d1JoZKGvjyAcXg84ednoA7t7V1y/6+Cg850Dk7IY/BrdUTMGIBpRDwA9y/dx5pOBy/+YhSRJh2dS94Cn4/wC2fiPniQnvXrib35ZiTdie+p2u9wsbjJwlutXVj9AbIMehZmJnJxQiQpomdMEARBEH50DoeD7du3U1JSAsDu3btJT08/tUHx7Vdxzv2K4x8BH53QiI4iKzJz8uew/qEnyA6oqIuLIzw0lMjISGS3H8sr+1G8Mru0hwEojMsgdnoR+qyj5mT5vajrNrEubgrjqlxIOjWGohgA3txez3Prq7nyjHQmDogFwLpkCfq8PELy82m6804kg4HIOZd+q3jr3V5cAflrr1GA3TYnLzV1sN3mRCdJTIsN5/KkaMZGhAZVRQJBEARB+P/ky3PQpkyZwp133smiRYu47rrrMBgMmEymU957BkFe6smoMRLtCKG9tpphdhc7BydSkJODoih0v1dJoNON8cocDrz+ESEuOwW/moRa86VXatiG1u/iYPwYpuywYBgci6yReOCDffx3QzVjs6NZeH4BAJ6qatx7Som77Tb8HR3Y3v+AiEt+hjriqyfhe2SZpW3dPNfYwU6b81u/W45Rz73ZSVySEHXM6kxBEARBEE68QOD4u3x99NGP1tf0vQVlZnBkDlpqdir71n5GmNePzenCo1aTkZGBc2cbzt3thJ2bztqKTSgKjBg69NjkDAhUrQZU6MNGonidyIOiuer5rWyotPDzMzO4c2oBms9rU1o/eB9UKsKmT6PrlVdR/H5CL7+cPx5qZFO347ixNnq8dPoCZBt6E66Eb1FOKUmvZWS4SfSWCYIgCIJwXEGZoB2ZgzZixIj5FetXM1BjpC3BAEBqWALdL1SiywxHNzaOXYvK0PZYOWPajOO21XPoMw6Z8xnYqEaJ0jP7gzIarC4evWQIPxue8sUzZRnbkvcxjR2LpNHQ9fLLaM4+m+sdsNLSzoTIUEKOs+Q21xTCJfGRTIwyoxIJlyAIgiAIJ0BQJmhHeF1OXB0dRFe3cvC884iMjCSwvBXUKqLm5LFtxzYCikJhRhrGsPBjG3DbCG3ZxfrUuZxXYed/Kh+dGj+vXDuaERn9N5y1LV2Kr6mJuFt/R8uf7qcbifvmzmeXxcaiASlcmRxzkt5aEARBEISfuqBO0Fx2O5l2N7LTRavJRF5oPN5DNiIvzkUTrmf71i2oPC7OnHr58Ruo3YhKCVBtGo7Rr7ApHN66Ziw5caEAfNxu5d7Djbj9AfxKGDzyNKoQI/LEC3BPvwyvT+HpgRliI1hBEARBEE6qoEzQjsxBS4kMJ8tiw33mmXj8fqLrtegywzCOiKezsxOLzY7Z6yI+M/u47XgrPyOg0mO25bIhROG/N4wlzhwC9CZn15ZXM8AYwtCGSryHKjFNGI9zyyZUJhNhZ53F7MRoRkWEnsQ3FwRBEARBCNIE7cgctOww83yNo4eOkhKoPESCL4LIi3KRJIk9e/aAopCTmXHcyfayN4CrdDm7wouwd8mYZ+b0JWfLO6zML6+hKNTIi8YAlj8tJGL2bAJvL8axahWZ776DPufU74EiCIIgCMJP06ktNPUNDCojhjGXUmdxES4bSZiYjTbOiKIo7NqxA7XTTv7wkcfcpygKnc+uJdxTzYbw4azzeZlclIhfVvhfYwfX7K1hYKiBVwdn4XzgAdTh4RiHD8O+fDkxN96IPifnONEIgiAIgnA6U6vVFBcX9/3U1NSwevVqpk+ffqpDO0ZQ9qAdoTJEIiVMor5zLXmGVMImpQHQ0NCAzeEgxNZJWlHxMfd5a2xIDetAB2vVRcwensLqbjsPHG7moNPNGREmXhiUibR6Fa6dO4m/5x7a//4PdDnZRP/86pP8loIgCIIgnAzHq8VZU1NzaoL5BkHdg6Y4WwlckYhfCjBwxigkbW+4paWlSIpCcmw0hlDzMfc5NjUh6Uvp1ISxz5lCXVIIV5ZV41cUnhuUwTvFOYRrNXS/9Raa+Hj8lg58DQ0k3HXXSSmILgiCIAiC8HWCsgftyCKBAUlJ1LY1IkkSmVm99Tf9fj9lZWWo7V1knzH6mHsDVg/uvQ1EmXawMnwoBRGhvG2xcmVSNH/OTUGr6p2v5mttpWfdeiLmzKHzmWcxT5mCacyYk/magiAIgvCTtO6Ng3TUH38D+O8rJjWU8bMHfO01R5d6yszM5N133z2hMZxIQZmgHb1RbVVVFUlJSRgMvRvVVlRU4Ha7MXRbyBgy7Jh7HVuaCVW9j8HXyXPxF6EkmYiUA9yZldiXnAFYl7wPsoyvthZUKuJv+/3Jej1BEARBEE6B4w1xBqugTNCOUBSFhoYGxo0bB0BbWxtLly7FoFZhIkBC9heZsscf4OGl+zlvTzXF2jdZFjmO3bpBuL1e7s1OIlyr6deu9Z130A8YQM+GDcTefDPapKST/n6CIAiC8FP0TT1dQpDPQfN4PCiKQlZWFlarlcWLF6PRaDA3V5NeVIxKre679vn11XxotXEw/g3UePlr3LVERYSQrNdy9ZeqALh27cJbU4Pi9aKJiyNKLAwQBEEQBCGIBH2CptFoiI2N5eWXX8btdjPt7LNwWdrJKO4d3gwoCk1WN3/bXI0uuo3ZrcuwDf05v5pUQpMc4PasRELU/V+z+513kPR6vDU1RF97DSq9/lS8niAIgiAIwnEF5RDnkUUCycnJpKen89lnn9HR0cHcOXPYv/QtADIGD2OHtYeLdlXiVRQYHUs3sWRMWNnbyL5aCkwhXBwf2a9t2enE/tEy1OHhKIEAEZdccpLfThAEQRCEU8HhOHZhQklJCSUlJSc/mG8QlAnakUUCSUlJ8zMzM9m4cSMF+XnsefMlakt3MeHyX2COjuHfe6vRSxLywW5KIv2MsL+DLWUCYQMmIiFxUXwE6i9VGbAt+xjZ6UR2Oon7/a2oPl98IAiCIAiCECyCMkE7WlhYGE6nk/Y9O3BXVTD5lzczqOQc6lwelrVbSe70Edni5QbbUsY4FtN4we0kxyYcty3Z46Hj3/9GZTKBRkPknDkn+W0EQRAEQRC+WVDPQVOpVHR1dQHgaahh5q13MqjkHBRF4c/lDSiKQluZhfsHppDuXsfWsEFERaV8ZXudL7yIr7ERuaeH6J9f3ZuoCYIgCIIgBJmgTtD0ej1VVVVofB4GDB9J9vDRHGq1c/HTm1jSaSXE4uWec/IYYakj0X+YlXETMaiP/0q+tjY6nvoP6qgoVGFhRF522Ul+G0EQBEEQhG8nqBO00NBQ6uvrUVk7ScoroKajh7nPbKFcFQCtisVnFXBVURLqumUAbEs6+yvbav/r31A8XgKdncTecANq87ElogRBEARBEIJBUM9BCwQCyLKMuseKNjGLy57dgl+WiSiMIkOvYWyUGfvqBgyqjVSGFeAPTztuO66yvVjffRdVaCjaxAQi5809yW8iCIIgCILw7QVlgnZkm43Q7FxWFI5EmzaA5w7Z8WQaGZwRyTani99nJwLg3raXMNUBViX8khjd8V+n/Z//QDIYkB0O4u+8E0kTlK8tCIIgCMKPSK1WU1RU1Pf5vffeo6amhpkzZ5KVlYXL5WL69Ok8+uijpzDKXkGZqRzZZsOQmz+/yxiKojfiUKtIjjfQjUxJpJkZcRG49rSjs34GWlgSPZ6C4yRofouFnvUbQJIwT54sCqILgiAIwk/U8Wpx1tTUMH78eJYuXYrL5WLo0KFcdNFFnHnmmacoyl5BmaAdEdlj48qlL7JXlU7K2Rfx0LhBfedcBzrpfPMgccatKOH57NQlM1577OvYPv4YZBl0OlEQXRAEQRCEr2QwGCguLqaxsfFUhxLcCRqA2tFNbdQoriqI7zvmqbbSuXg/ulgPWmspzvxbkOG4Q5y2D5aCJBEx6yK0ycknMXJBEARBEI5n1QtP01ZbdULbjEvPYtLVC772GpfLRXFxMQCZmZm8++67/c53dXVx6NAhJkyYcEJj+z6COkFTSRKSz0eXKYFxOb0Fz90Hu7C8vB91hJ6YwjVIG2Vaci6AaojVafvd72tqwvV5V2b4tGknPX5BEARBEILH8YY4AdatW8fgwYM5cOAAd9xxBwkJx9/w/mQK7gQNBZshmlF5yWhtXjo+rMK9vxNNjIGYK9JR/fc/kDeNprBs4DAxXxritC3r3X5DHRODYfjwU/AGgiAIgiB82Tf1dJ1sR+agHTx4kHHjxnHRRRf19bSdKkG9D5ricVOnieMKvYGWv+7Ac9hK2JQM4m8ehqbiBXBbYeJtdPj8wLFDnNYl74MkEX7BBUiqoH5VQRAEQRBOsQEDBrBw4UIefvjhUx1KcCdoyDIhIcnklnYRkhNBwq3DCStJRQr0wKYnYMD5kFRMu9cHQOxRCZqnqhrPwYOgKISJ4U1BEARBEL6F66+/nrVr11JdXX1K4wjqIU6ABYYsNHFGouYVoNKrew9ufRpcXTDxNgA6vH40EoRr1H332T78EABtcjIhAwtPetyCIAiCIAQXh8NxzLGSkhJKSkr6PhsMhqBYxRmUPWiSJF0gSdLTkqQiXBtB9OVHJWceB5aVoJ0AACAASURBVGz8F+SeB8nDAOjw+YnRalFJEgCKLGNdsgSA8JkzkT4/LgiCIAiCcDoIygRNUZQPFEVZoJW0eKeko401fnFy98vg6oSJt/cdavf6+80/69m4CV9DAwBh08XwpiAIgiAIp5egHuL0akLJG5fa/+D+DyCuEFJG9B3q8Pr7reDsWrwYNBp02dnos7JOVriCIAiCIAgnRFD2oB3hN4WgUh01POnqhtqNMGBKv+vafb6+HjRvbS2ONWvA7yfykktOZriCIAiCIAgnRFAnaEkRhv4HKleCEoC88/sOKYqC5aghzq5XXgFAFRVFxM8uPmmxCoIgCIIgnChBnaAdM7f/4MdgjIbkLzaddQZkXLJCjFaD3NND1xtvgqIQc+21qEJCTm7AgiAIgiD8X3t3Hl9Vde///71yyHBCQkKYIdEACYQkEAQElYAULWpBpOKEAzj2OkIv4i9aFK3tFWnVqhVpb60K1AlLxaFqENC2yrd61XhImCmCEAgQAknghJBh/f7ICY00AZST7E3O6/l48DB77Z193ssdw8e19t4LQeDqAu1baqqljR9IqRdIYf9+ncaewEtqO0WEa/+bb8pWVCgsNlbtr7rSqaQAAMCldu3apauvvlq9evXS4MGDdfbZZ+u1117TwIEDNXDgQMXExKhv374aOHCgJk+e7FhOVz8k8C3b/ikd2i/1/fb9Z8WHqyVr1XXLZu39w3OSpISbblJYdHRjZwEAACHKWqsJEyZoypQpejlwS9TWrVv11ltvHVmjc9SoUXrsscc0ZMiQY52q2Z06Bdr69yRPhNR79JEmW1Wlqt//TgveeUeddxep2hgZr1cJ117jYFAAAOBGK1asUEREhG699dYjbaeffrruuusuB1M17tQp0Da8LyVnS5GxR5pK335H8c8/p819M9T7qit0+Omn1eGGG+SJiXEwKAAAOJb9b/9Lh3ccDOo5I7q3VfzFvY95zOrVqzVo0KCgfm5zOTXuQSveJO3dVLf2ZgPly5erolNn3T1tprxt6mrN+ImXOpEQAACcYu644w5lZWXpzDPPdDrKfzg1RtDWv1v3zwb3n9VWVOjgJ59o6/kXKi68jQ799a/ynnGGwnv0cCgkAAA4Eccb6WouGRkZWrx48ZHtuXPnqri42PH7zRrjyhG0+rU4S0tLpVWvSyt+KSWeKcWfduSYgytXyh46pILBQ9VBtapcv17tfvQjB1MDAAA3Gz16tA4dOqR58+YdafP7/Q4maporC7T6tTjjwvzSX26uW9Zp0mvfOqZ82XKFtWsnX0o/xZful4xR7AVjHEoMAADczhijJUuW6G9/+5t69uypoUOHasqUKZozZ47T0f6Du6c4y4ukM26Txj4htYk40myrq3Xgww8Vc+652lVr1WP7NkUPHarwzp0dDAsAANyuW7duevXVV5vc/9FHH7VcmGNw5QjaEXE9pPG//VZxJkkVeXmq2b9fseedp+KKSrUr2sn0JgAAaDXcXaC17dzIek9105smPFyRw4drn5USDpYrdswPHQgIAAAQfO4u0BphrVX5ihWKPuds7QuvG1nr3KmD2rRv73AyAACA4HD3PWgBlbW1+rqiUpJkN26Utm1T1eTJ+nLVGklSYno/J+MBAAAElesLtDUHKnRzwRZtDhRoNy95RZOM0eWxPVQSeAlxr8FnOJgQAAAguFxdoJVUVetHX2xQXBuPnkhLUrtDh5T8yQodPHeUHj0rS0UPPaS4Ht01eFSO01EBAACCxtX3oG07dFiD27XVsjP76upuHXT2ivflOXBA/e+4Xed9s0kjPvpAFw0eINPIgwQAAABH27Vrl66++mr16tVLgwcP1tlnn63XXntNPXv2VFFR0ZHjbr/9dj366KOO5XR1gdYlIlyLBvZWp4hw1VZWau+LL6rtOWfL2z9TZe++K+P1KmbUKKdjAgCAU4C1VhMmTNDIkSO1efNmffHFF3r11Ve1e/du5eTkaMaMGZKkL7/8Uh9//LHuvvtux7K6eoqza2S4PIHRsdI331TNnmJ1+NWvZKuqVJ67VLE/GKWw6GiHUwIAgFPBihUrFBERoVtvvfVI2+mnn6677rpLtbW1mj9/vj788EPNnDlTzzzzjMLDwx3L6uoCrZ6tqdHeP/5RUZmZij7rLB38+BPV7NvHy2kBADgFvffee9+aTgyGrl276qKLLjrmMatXr9agQYMa3RcWFqZ58+Zp9OjRGj9+vEaOHBnUfN+Vq6c465V/8IGqtn6jDrfcImOMyt57T2ExMWo7YoTT0QAAwCnqjjvuUFZWls4880xJ0sCBA5WZmanbb7/d4WSnyAjavj+9pPDTT1Ps+eep9vBhlX/wgWLPP19hkZFORwMAAN/R8Ua6mktGRoYWL158ZHvu3LkqLi7WkCFDjrSFhYUpLMz58SvnExzH4e2F8n/+ueJ//GMZj0cHP/5YteXlavcjZy4uAAA4NY0ePVqHDh3SvHnzjrT5/X4HEzXN9QVa2TtvS5LajbtYklSem6uwuDi1PftsJ2MBAIBTjDFGS5Ys0d/+9jf17NlTQ4cO1ZQpUzRnzhyno/0H109xlr75lqKHDFFEYo+6pzc//EixP/iBjINPVgAAgFNTt27d9Oqrrza5/6OPPmq5MMfQYgWaMWaEpGsCn5lurT3neN9TW1Ghw19/rYQbb5AkHfzsM9WWlSl2zA+bNywAAICDTmiK0xjzvDFmtzGm4Kj2C40x640xm4wx9x7rHNbaf1hrb5X0jqT5J/K5Nfv3y0REqN0FF0iSypctk/F61Xb48BP5dgAAgFPSid6D9qKkCxs2GGM8kuZKukhSuqRJxph0Y0x/Y8w7R/3p3OBbr5b0yol8aE1pqWJGj5anXTvZ2lodWLZcMSNGKCwq6gRjAwAAnHpOaIrTWvt3Y0zyUc1DJW2y1m6WJGPMq5IusdbOljSusfMYY06TVGqtLWvqs4wxP5H0E0nKiIxS3PjxkqQKn0/Ve/Yo9odMbwIAgNbtZJ7i7CFpW4Pt7YG2Y7lJ0gvHOsBa+7/W2iHW2iFq41HMiGxJUvkHy6TwcMWMOvckIgMAALjfyTwkYBpps8f6Bmvtg9/lAzxxcTLh4bLWqnzZMrU96yx5YmO/U0gAAIBTzcmMoG2XlNRgO1HSjpOLU8cYc7Ex5n/9Xq8kqXLDBlV9841izz8/GKcHAAAhKCYm5lvbL774ou68805J0kMPPaTo6Gjt3r27yeNb0skUaP8nKdUY09MYEyHpKklvBSOUtfZta+1P4uLjJQWmN41R7Hmjg3F6AACA/9CxY0c9/vjjTseQdOKv2XhF0v+T1NcYs90Yc5O1tlrSnZJyJa2VtMhau7o5Qvo//VRRmZlq07Fjc5weAABAN954o1577TWVlJQ4HeWEn+Kc1ET7u5LeDWqioz+jpkYVq1cr/tJLm/NjAABAC9mw4RcqP7A2qOeMjemnPn0eOOYxFRUVGjhw4JHtkpISjQ+8LUKqm9K88cYb9dRTT+nnP/95UPN9V65c6skYc7Gki1NSUlS56V+yfr+8WQOcjgUAAE5hXq9XX3311ZHtF198UZ9//vm3jpk6daoGDhyou+++u6XjfYsrCzRr7duS3h4yZMgth/JXSZK8/fs7GwoAAATF8Ua6nBQfH6+rr75azz77rKM5XFmgNVThW6WwuDiFn36601EAAEAImD59us4880xVV1c7luFknuJsERX5+fL27y9jGnvtGgAAQHB17NhRP/7xj1VZWelYBmPtMd8t64gj96D16nXLW1Fedfyvn6jT1KlOxwIAAN/T2rVr1a9fP6djBE1j/THGfGGtHRKM87tyBK3+PWixkZFSTY2iuP8MAACEEFcWaPVq/X5JkncAT3ACAIDQ4e4CraJC4T16qE2HDk5HAQAAaDGuLtBsRYWiBjC9CQAAQosrC7T6xdLt4Sp5B2Q5HQcAAKBFubJAq39IQJK8jKABAIAQ4+4X1RopKj3d6RQAAKAViImJ0YEDB45s1y/11K1bN73++uuSpPz8fPUPvD3ixhtv1FSHXvPl6gLNREUpzOt1OgYAAGjFZs6cqZkzZ0qqK+IartfpFFdOcdajOAMAAKHIlSNoR1YS6N3b6SgAACDIHti4XQUHKoJ6zswYr36RmnjMYyoqKjRw4MAj2yUlJRo/fnxQcwSLKws0a+3bkt4eMmTILU5nAQAArYPX6/3W9GX9PWhu5MoCDQAAtF7HG+mCy+9BAwAACEUUaAAAAC7DFCcAAAgJDd+BJknXX3+9rr/++mMe4xRG0AAAAFzGlQVa/VqcpaWlTkcBAABoca4s0OrX4oyLi3M6CgAAQItzZYEGAAAQyijQAAAAXIYCDQAAwGUo0AAAQEiIiYmRJG3ZskVer1cDBw488mfBggUOp/s23oMGAABCTu/evb+1LqfbuLpA++KLLw4YY9Y7ncNBHSUVOx3CIaHcd4n+03/6H6r9b7V9/+CDD/rX1NRUH+uYmpqaNh6P55jHnIza2trogoIC//bt201FRUVUQUFBxfc9V1FRUZv09PT8o5pPP8mIR7i6QJO03lo7xOkQTjHGfB6q/Q/lvkv0n/7T/1Dtf2vuu8/n25KZmVksSff82Ze0oag8+uhjqg8fatMmIurw9zl/n66x/l9flrXtOIedkZmZuTY8PDyisLAw87LLLjP1O5588slvLrzwwhNeRqCmpqZjc14rtxdoAAAAQZeUlFS5bt26NU7naAoFGgAAaFFNjXQVFBT0y8zMDOVbm45w+1Oc/+t0AIeFcv9Due8S/af/oS2U+x/KfVfHjh33OJ3BLVw9gmatDekf1FDufyj3XaL/9J/+O53BKaHcd0nq2rVriz0gsW3btsi0tLT0+u1rr722+P7779/dUp9/PK4u0AAAAILF7/fnSVLfvn0PHzp06Eun8xyLK6c4jTEXGmPWG2M2GWPudTpPczPGJBljPjTGrDXGrDbGTAu0JxhjPjDGbAz8s73TWZuTMcZjjMkzxrwT2O5pjPk00P/XjDERTmdsLsaYeGPMn40x6wI/B2eHyvU3xvx34Oe+wBjzijEmqjVfe2PM88aY3caYggZtjV5rU+fpwO/CVcaYQc4lD44m+v/rwM/+KmPMG8aY+Ab77gv0f70x5gJnUgdPY/1vsG+GMcYaYzoGtlvd9f/Xv/6VnJeXl5Wfn5/RsH3nzp2dV61alZmfn5+xdevWxPr27du3d121alXmqlWrMvft29eu5RM7x3UFmjHGI2mupIskpUuaZIxJP/Z3nfKqJd1tre0n6SxJdwT6fK+k5dbaVEnLA9ut2TRJaxtsz5H0m0D/90m6yZFULeMpSe9ba9MkZanu30Orv/7GmB6SpkoaYq3NlOSRdJVa97V/UdKFR7U1da0vkpQa+PMTSfNaKGNzelH/2f8PJGVaawdI2iDpPkkK/B68SlJG4HueDfwdcSp7Uf/ZfxljkiT9UNI3DZpb3fXv2LFjcUpKysaGbfv374/dv39/fGZm5ur+/fuv7tatW5EkHTx4MGr//v0JmZmZq1NTUzds27btNGutM8Ed4LoCTdJQSZustZuttYclvSrpEoczNStr7U5r7ZeBr8tV95dzD9X1e37gsPmSJjiTsPkZYxIljZX0XGDbSBot6c+BQ1pt/40x7SSNlPRHSbLWHrbW7lfoXP82krzGmDaSoiXtVCu+9tbav0sqOaq5qWt9iaQFts4/JcUbY7q1TNLm0Vj/rbVLrbX1Lyf9p6T6EZRLJL1qra201n4taZPq/o44ZTVx/SXpN5L+P0kNK5BWd/3j4uIOhIeHf+tFtHv27OnUtWvXnWFhYVaSIiIiqiVp37598fHx8SVhYWHW6/UejoiIqCwvL2/rRG4nuLFA6yGp4eO32wNtIcEYkyzpDEmfSupird0p1RVxkjo7l6zZPam6X061ge0OkvY3+KXdmn8OeknaI+mFwBTvc8aYtgqB62+tLZT0mOpGDXZKKpX0hULn2tdr6lqH4u/DGyW9F/g6JPpvjBkvqdBa6ztqV0j0v7KyMqq8vDx29erVaWvWrOlbXl73AtuqqqqIiIiIIy+tDQ8PP3z48OFWc7vD8bixQDONtIXEmKYxJkbSYkk/tdaWOZ2npRhjxknaba39omFzI4e21p+DNpIGSZpnrT1D0kG1wunMxgTutbpEUk9J3SW1Vd20ztFa67U/nlD670DGmJmqu+XjpfqmRg5rVf03xkRLmilpVmO7G2lrVf2XJGutqamp8aSnp69LTEzctnnz5t7HmMpsdf1vihsLtO2SkhpsJ0ra4VCWFmOMCVddcfaStfYvgeZd9cPZgX+65vHfIBsuabwxZovqprRHq25ELT4w7SW17p+D7ZK2W2s/DWz/WXUFWyhc//MlfW2t3WOtrZL0F0nnKHSufb2mrnXI/D40xkyRNE7SNfbffzuHQv97q+5/UHyB34GJkr40xnRVaPRf4eHhh9u3b7/fGKN27dr5jTG2qqqqzdEjZoERtSons7YkNxZo/ycpNfAUV4TqbhB9y+FMzSpwv9UfJa211j7RYNdbkqYEvp4i6c2WztYSrLX3WWsTrbXJqrveK6y110j6UNJlgcNac/+LJG0zxvQNNJ0naY1C4/p/I+ksY0x04L+D+r6HxLVvoKlr/ZakyYGn+c6SVFo/FdqaGGMulJQjaby11t9g11uSrjLGRBpjeqruZvnPnMjYXKy1+dbaztba5MDvwO2SBgV+L4TE9Y+Pj99fVlYWK0l+vz+ytrY2LDw8vLp9+/b79+/fn1BbW2sqKioiKisro2JjYw+ezGdFR0ef8dlnn3nT0tLS09LS0uPi4gb26NGjf1paWvo555zTJzg9Cg7jxicijDE/Ut0IikfS89ba/3E4UrMyxmRL+oekfP37Hqyfqe4+tEWSTlPdX2SXW2sbu7m01TDGjJI0w1o7zhjTS3UjagmS8iRda62tdDJfczHGDFTdAxIRkjZLukF1/wPV6q+/Mebnkq5U3dRWnqSbVXefTau89saYVySNktRR0i5JD0paokaudaBofUZ1T/35Jd1grf3cidzB0kT/75MUKWlv4LB/WmtvDRw/U3X3pVWr7vaP944+56mksf5ba//YYP8W1T3VXNzarr/P59sSHR0de/Dgwdiampo2Ho+nulu3bjs6deq0d/PmzckVFRXRxpjaxMTE7fHx8eVS3Ws2SkpKOkpSYmLiNwkJCSd1+090dPQZ9e9Ck6SJEycmjxs3rvSGG27Y9z360zErKyv5ZPIciysLNAAA0Lr4fL4tWVlZLbZSQGNOpQKNlQQAAEDLWnJHknaviQ7qOTun+zVhbqOLsJ+K3HgPGgAAQEhjBA0AALSsVjTS1VwYQQMAAHAZCjQAAACXYYoTAACEhIZPcErS4sWLtzgU5bgYQQPQYgLrjKa3wOf8rMHXycaYgmb4jFHGmHe+4/d8ZIwZ0kj79caYZ4KXDsCpjgINQIux1t5srV3TAh/1s+Mf8m0NlpYCAMdRoAFoFsaYtsaYvxpjfMaYAmPMlQ1HkIwxB4wx/xPY/09jTJdAexdjzBuBdp8x5pxA+7XGmM+MMV8ZY35vjPE08bmPSvIGjqtfdNtjjPmDMWa1MWapMcYbOPYjY8wjxpi/SZpmjOlkjFlsjPm/wJ/hgePODZzvK2NMnjEmNnDeGGPMn40x64wxLwXe/C5jzHmB4/KNMc8bYyIbyXmDMWZD4LOHB+1fPIBWgQINQHO5UNIOa22WtTZT0vtH7W+ruiV9siT9XdItgfanJf0t0D5I0mpjTD/VLQc13Fo7UFKNpGsa+1Br7b2SKqy1AwNrukp1azjOtdZmSNovaWKDb4m31p5rrX1c0lOSfmOtPTNwzHOBY2ZIuiPw2SMkVQTaz5D0U0npknpJGm6MiZL0oqQrrbX9VXev720NMwYWRP+56gqzHwa+HwCOoEAD0FzyJZ1vjJljjBlhrS09av9hSfX3cH0hKTnw9WhJ8yTJWlsT+L7zJA2W9H/GmK8C272+Q5avrbVfNfJZkvRag6/Pl/RM4DPektQuMFr2iaQnjDFTVVfQVQeO/8xau91aWyvpq8B5+wY+b0PgmPmSRh6VZ5ikj6y1e6y1h4/KAAA8xQmgeVhrNxhjBkv6kaTZxpilRx1SZf+9GHCNjv37yEiab62973vGabjQeo0kb4Ptgw2+DpN0trW2Qt/2qDHmr6rryz+NMec3cd42gawngoWQATSJETQAzcIY012S31r7J0mPqW668kQsV2BK0BjjMca0C7RdZozpHGhPMMacfoxzVBljwr9H7KWS7mzQh4GBf/a21uZba+dI+lxS2jHOsU5SsjEmJbB9naS/HXXMp5JGGWM6BHJe/j2yAvgeoqOjz1i/fn2EMWbwtGnTute379y5s02bNm0GTZ48+TQn89WjQAPQXPpL+iwwXThT0i9P8PumSfqBMSZfddORGYEnP++XtNQYs0rSB5K6HeMc/ytpVYOHBE7UVElDjDGrjDFrJN0aaP9p4EEHn+ruP3uvqRNYaw9JukHS64E+1Er63VHH7JT0kKT/J2mZpC+/Y04AJykxMbFy6dKl8fXbCxYsaJ+SknLIyUwNmX/PMAAAADQPn8+3JSsrq9jpHNHR0Wfk5eWtHjduXGpaWpr/nnvu2TVy5Ej/0KFD+44ePbp0x44dEQsWLPjmeOfx+Xwds7KykpsrJ/egAQCAFvXAJw8kbdq3KTqY50xpn+L/xfBffKdF2K+66qqSP/3pTwk9evSo8ng8tnv37lU7duyICGau74sCDcApyxjzqaSj3zF2nbU234k8AE4tEydOLHv44Yd7dOnSpWrixIklTudpiAINwCnLWjvM6QwAvrvvOtLVXKKiouyAAQP88+bN61pQUFCwaNGi+ON/V8ugQAMAACErJyenaOTIkeVdu3atcTpLQxRoAAAgJFRVVSkiIuJbT0cOGTLk0JAhQ1zz9GY9CjQAABASPv/8c29SUlJl3759D2/cuHH10funTp26V9JeB6L9Bwo0AADQ6v3qV7/q9Pvf/77zr3/9a1fc/3Y8vAcNAAA0O7e8By1Ymvs9aKwkAAAA4DIUaAAAAC5DgQYAAOAyFGgAAAAuQ4EGAABCgjFm8IQJE3rWb1dVVal9+/ZZP/jBD1Ik6aGHHupyxRVXnF6/f968eQmjRo1KcSIrBRoAAAgJXq+3dv369d4DBw4YSXrjjTfadenSpap+/8yZM3etWrWq7dKlS9sWFxd7fvnLX/Z49tlnv3EiKwUaAAAIGeedd17p66+/Hi9Jr7zySkLDRdLDw8P129/+duvUqVNPv+uuuxKvvvrq4vT09MNO5ORFtQAAoEXt+NnMpMqNG6ODec7I1FR/90f+57gvob3uuutKHnzwwW5XXnnl/rVr10bfdNNNe1euXBlTv/+HP/zhwdTU1Ip//OMf7TZu3FgQzIzfBSNoAAAgZAwbNqxi+/btkX/4wx8Szj///NKj95eWloatWrWqbXV1tdmxY4djA1mMoAEAgBZ1IiNdzenCCy/c/+CDDyYtXbp0/e7du79VC82YMaP7ZZddtrdLly7Vd955Z9J777232YmMFGgAACCk3HbbbcVxcXE1Q4cOrXjnnXdi69s/++wz77Jly+JWr169JjIy0i5cuLDjG2+80e7HP/5xWUtnZIoTAACElN69e1c98MADuxu21dbW6rbbbjttzpw526Kjo63H49HcuXO3zpgxI+nQoUOmpTOyWDoAAGh2LJb+3TCCBgAA4DIUaAAAAC5DgQYAAOAyFGgAAAAuQ4EGAADgMhRoAAAALkOBBgAAQoIxZvAtt9ySWL89a9asLtOnT+8uSdOnT+8+a9asLs6l+zYKNAAAEBIiIiLsu+++237nzp2uX0mJAg0AAIQEj8djJ0+evOeRRx5xzUhZU1xfQQIAgNZl+YK1SSWFB6KDec6EHjH+8yb3O+4i7Pfcc8/u/v37Zzz00ENFwfz8YGMEDQAAhIyEhITayy+/fO+jjz7a2eksx8IIGgAAaFEnMtLVnO67775dgwYNSr/qqqtcuzYoI2gAACCkdOnSpebiiy/e9/LLL3d0OktTKNAAAEDImTlzZtH+/ftdO5Po2mAAAADB5Pf78+q/TkpKqq6oqDiy/cQTT+xwJlXjGEEDAABwGQo0AAAAl6FAAwAAcBkKNAAAAJehQAMAAHAZCjQAAACXoUADAAAhwRgz+JZbbkms3541a1aX6dOnd6/ffuyxxzr27Nkzo2fPnhn9+/fvl5ubG+NMUgo0AAAQIiIiIuy7777bfufOnf/xHthXXnkl7oUXXui0cuXK9V9//fXqefPmbb3++ut7fvPNN468M5YCDQAAhASPx2MnT56855FHHuly9L7HHnus6+zZs7d369atWpKys7P9V1xxxd7HH3/ckUXVWUkAAAC0qNx5TyYVb9saHcxzdkw63X/BbT897iLs99xzz+7+/ftnPPTQQ0UN2zdt2uQdPny4v2HbmWee6V+wYEGHYOY8UYygAQCAkJGQkFB7+eWX73300UePOzJmrZUxpiVi/QdG0AAAQIs6kZGu5nTfffftGjRoUPpVV11VXN+WkpJS8cknn0SPHz++vL7tiy++iE5LS6twIiMjaAAAIKR06dKl5uKLL9738ssvd6xvmz59etHPfvazxKKiIo8krVy50vvaa691mD59+h4nMjKCBgAAQs7MmTOL5s+f36l++5prrindvn17xFlnndXPGGPbtm1b+/zzz399+umnVzmRz1hrnfhcAAAQQnw+35asrKzi4x95avD5fB2zsrKSm+v8THECAAC4DAUaAACAy1CgAQAAuAwFGgAAgMtQoAEAALgMBRoAAIDLUKABAICQ4PF4BqelpaWnpqZmXHTRRb3Ky8uP1EELFiyIN8YMzsvLi3IyYz0KNAAAEBIiIyNr161bt2bjxo2rw8PD7eOPP37kRbWvvvpqwqBBgw4sXLgw22E6agAAFYxJREFUwcmM9SjQAABAyMnOzj6wadOmSEkqLS0N+/zzz2NeeOGFLW+88UZ7p7NJLPUEAABaWMmfNyRVFR2MDuY5w7u29Sdc1ueEFmGvqqpSbm5uuzFjxpRJ0ksvvRQ/atSo0gEDBlTGx8fXfPzxx9HZ2dn+YOb7rhhBAwAAIaGysjIsLS0tvX///umJiYmHp02bVixJixYtSpg0adI+SZo4cWKJG6Y5WYsTAAA0OzesxRkdHX2G3+/Pa9hWVFTkSU5OzkpISKgyxqimpsYYY2xhYWF+WFjT41isxQkAANBMFi5c2P7SSy/du2PHjvzCwsL8oqKiVYmJiYeXLl0a42QuCjQAABCyXn/99Q6XXnrpvoZtl1xyyT6npzmZ4gQAAM3ODVOcwcQUJwAAQIihQAMAAHAZCjQAAACXoUADAABwGQo0AAAAl6FAAwAAcBnW4gQAACHB4/EMTk1NraipqTEpKSkVixYt2hIbG1tb315/3KWXXlryyCOPFDmZlQINAACEhMjIyNp169atkaTx48f3fPzxxzs99NBDuxq2uwVTnAAAIORkZ2cf2LRpU6TTOZrCCBoAAGhRS5YsSdq9e3d0MM/ZuXNn/4QJE7adyLFVVVXKzc1tN2bMmDJJqqysDEtLS0uv33/33XfvvOWWW/Y1fYbmR4EGAABCQsNCbNiwYeXTpk0rlr499ekWFGgAAKBFnehIV7C5sRBrCvegAQAAuAwjaAAAIKQdfQ/a6NGjS5999tlCJzNRoAEAgJDg9/vzGmuvqan5oqWzHA9TnAAAAC5DgQYAAOAyFGgAAAAuQ4EGAADgMhRoAAAALkOBBgAA4DK8ZgMAAIQEj8czODU1taKmpsakpKRULFq0aEtsbGxtw/akpKTKRYsWfd2xY8caJ7MyggYAAEJC/VJPGzduXB0eHm4ff/zxTke3x8fHV//617/u5HRWCjQAABBysrOzD2zatCny6PazzjrrYGFhYYQTmRpiihMAALSoNWtzkg4e2BAdzHO2jenjT+8354QWYa+qqlJubm67MWPGlDVsr66u1ocffhh70003FQcz2/dBgQYAAEJCwzU3hw0bVj5t2rTihu2FhYURmZmZ/gkTJpQd+0zNjwINAAC0qBMd6Qq2+nvNmmrfu3evZ8yYMSmPPvpo5/vvv3+3ExnrcQ8aAACApA4dOtQ8/fTT38ydO7dLZWWlcTILBRoAAEDA8OHDK/r161fx3HPPtXcyB1OcAAAgJPj9/rwTaV+xYsWmlknUNEbQAAAAXIYCDQAAwGUo0AAAAFyGAg0AAMBlKNAAAABchgINAADAZXjNBgAACAkej2dwampqRU1NjUlJSal49tlnt1100UWpklRcXBweFhZmExISqiXpq6++WhsVFWWdykqBBgAAQkLDpZ7Gjx/fc/78+Qn129OnT+8eExNT8/DDD+9yNmUdpjgBAEDIyc7OPrBp06ZIp3M0hRE0AADQon669pukdQcPRQfznGlto/xP9jvthBZhr6qqUm5ubrsxY8aUBTNDMFGgAQCAkFBZWRmWlpaWLknDhg0rnzZtWrHTmZpCgQYAAFrUiY50BVvDe9DcjnvQAAAAXIYCDQAAwGWY4gQAACHB7/fnNbXviSee2NGSWY6HETQAAACXoUADAABwGQo0AAAAl6FAAwAAcBkKNAAAAJehQAMAAHAZCjQAABASPB7P4LS0tPTU1NSMiy66qFdZWVnY4MGD+y5atKhd/THPPfdc+xEjRqQ6mVOiQAMAACGifqmnjRs3rg4PD7dPPPFEp9/97ndb77333iS/32/KysrCfvGLX/T43e9+943TWXlRLQAACDnZ2dkHVq1a5T3zzDMPjRkzpvSBBx7oevDgQc8VV1yxNyMjo9LpfBRoAACgRd3zZ1/ShqLy6GCes0/XWP+vL8s6oUXYq6qqlJub227MmDFlkvSrX/1qx4ABA9IjIiJqfT7f2mDm+r4o0AAAQEiorKwMS0tLS5ekYcOGlU+bNq1Yktq1a1c7YcKEkpiYmBqv12udTVmHAg0AALSoEx3pCrb6e9Aa2xcWFqawMPfcmu+eJAAAAJBEgQYAAOA6THECAICQ4Pf785ra98QTT+xoySzHwwgaAACAy1CgAQAAuAwFGgAAgMtQoAEAALgMBRoAAIDLUKABAAC4DK/ZAAAAISMnJ6fr4sWLO4SFhdmwsDA9++yzW++9997E3bt3h0dFRdVKUnJy8qH3339/s5M5KdAAAEBIWLZsWdvc3Nz4/Pz8NV6v1+7cubNNZWWlkaQFCxZsHjlypN/pjPUo0AAAQEgoLCwMT0hIqK5fEL1bt27VTmdqCgUaAABoWUvuSNLuNdFBPWfndL8mzD3mIuwTJkwomz17dvfk5OTM7OzsskmTJpWMHTv2gCRNnjy5V/0U57nnnlv2+9//fntQ831HFGgAACAkxMXF1RYUFKx5//33Y5cvXx47ZcqU3rNmzdouMcUJAABC3XFGuppTmzZtNG7cuPJx48aVDxgwoGLhwoUdnMpyLLxmAwAAhASfzxeZn58fWb+dl5fnTUxMPOxkpqYwggYAAEJCWVmZZ+rUqaeVlZV5PB6PTU5Orpw/f/7WSy65pHfDe9ASEhKqV65cucHJrBRoAAAgJIwYMcKfl5e37uj2zz77bL0TeY6FKU4AAACXoUADAABwGQo0AAAAl6FAAwAAcBkKNAAAAJehQAMAAHAZCjQAABAycnJyuqakpGT06dMnPS0tLX3FihVthw4d2vfvf/97cNcGPUm8Bw0AAISEZcuWtc3NzY3Pz89f4/V67c6dO9tUVlYap3M1hgINAACEhMLCwvCEhIRqr9drJalbt27VTmdqCgUaAABoUQ988kDSpn2bgjqlmNI+xf+L4b845iLsEyZMKJs9e3b35OTkzOzs7LJJkyaVjB079kAwcwQL96ABAICQEBcXV1tQULDmmWee2dqpU6fqKVOm9H766ac7OJ2rMYygAQCAFnW8ka7m1KZNG40bN6583Lhx5QMGDKhYuHChKws0RtAAAEBI8Pl8kfn5+ZH123l5ed7ExMTDTmZqCiNoAAAgJJSVlXmmTp16WllZmcfj8djk5OTK+fPnb73kkkt6O53taBRoAAAgJIwYMcKfl5e37uj2zz77bL0TeY6FKU4AAACXoUADAABwGQo0AAAAl6FAAwAAcBkKNAAAAJehQAMAAHAZCjQAABAycnJyuqakpGT06dMnPS0tLX3FihVthw4d2jc5OTmzb9++6ZmZmf1WrlzpdTon70EDAAAhYdmyZW1zc3Pj8/Pz13i9Xrtz5842lZWVRpIWLFiweeTIkf6nnnqqw4wZMxJXrly50cmsjKABAICQUFhYGJ6QkFDt9XqtJHXr1q06OTm5quExI0eOPLhr164IZxL+GyNoAACgRe342cykyo0bo4N5zsjUVH/3R/7nmIuwT5gwoWz27Nndk5OTM7Ozs8smTZpUMnbs2AMNj3n77bfbXXTRRfuDme37oEADAAAhIS4urragoGDN+++/H7t8+fLYKVOm9J41a9Z2SZo8eXKvioqKsNraWn3++edrnc5qrLVOZwAAAK2cz+fbkpWVVex0joZeeOGF9gsXLuxw4MABz2OPPbZt2LBhFXfeeWePrVu3Ri5duvRfx/pen8/XMSsrK7m5snEPGgAACAk+ny8yPz8/sn47Ly/Pm5iYeLh+OzIy0v7mN78p/Oqrr9p++eWXUc6krEOBBgAAQkJZWZln8uTJPXv37p3Rp0+f9HXr1nnnzJmzo+ExMTEx9rbbbtv16KOPdnEqp8QUJwAAaAFunOI8GUxxAgAAhBgKNAAAAJehQAMAAHAZCjQAAACXoUADAABwGQo0AAAAl6FAAwAAISMnJ6drSkpKRp8+fdLT0tLSR44cmXrHHXf0aHjMypUrvb169cpwKqPEWpwAACBELFu2rG1ubm58fn7+Gq/Xa3fu3Nnmyy+/jPqv//qvnnPnzi2sP+5Pf/pTwsSJE0uczMoIGgAACAmFhYXhCQkJ1V6v10pSt27dqseOHXugXbt21StWrGhbf9xbb72VMHnyZEcLNEbQAABAi1q+YG1SSeGB6GCeM6FHjP+8yf22HeuYCRMmlM2ePbt7cnJyZnZ2dtmkSZNKxo4de2DixIklL730UsLo0aMPLl++vG18fHx1//79K4OZ77tiBA0AAISEuLi42oKCgjXPPPPM1k6dOlVPmTKl99NPP91hypQpJX/961/b19TU6KWXXkq47LLLHB09kxhBAwAALex4I13NqU2bNho3blz5uHHjygcMGFCxcOHCDlOnTt3bo0ePynfffTf23Xffbf/JJ5+sdSpfPUbQAABASPD5fJH5+fmR9dt5eXnexMTEw5J0+eWXl9xzzz1Jp512WmXv3r2rnEtZhwINAACEhLKyMs/kyZN79u7dO6NPnz7p69at886ZM2eHJE2ePHnfpk2botwwvSkxxQkAAELEiBEj/Hl5eesa29e9e/fq6urqL1s6U1MYQQMAAHAZCjQAAACXoUADAABwGQo0AAAAl6FAAwAAcBkKNAAAAJehQAMAACEjJyena0pKSkafPn3S09LS0lesWNE2IyOj33vvvRdTf8zw4cNTn3/++fZO5uQ9aAAAICQsW7asbW5ubnx+fv4ar9drd+7c2aaystL89re//ebWW289ffTo0WtffPHF9sYY3XjjjfuczEqBBgAAQkJhYWF4QkJCtdfrtZLUrVu3aklKTk6uGjJkyMEZM2Z0/8tf/pKQm5u7wdmkFGgAAKCF5c57Mql429boYJ6zY9Lp/gtu++kxF2GfMGFC2ezZs7snJydnZmdnl02aNKlk7NixByTpN7/5zfbk5OQBN9988+7MzMzKYGb7PrgHDQAAhIS4uLjagoKCNc8888zWTp06VU+ZMqX3008/3UGSli5dGhsbG1uzZs2aKKdzSpKx1jqdAQAAtHI+n29LVlZWsdM5GnrhhRfaL1y4sMOSJUs2DxgwIP2NN97YdOONNybfe++9O6+88srSY32vz+frmJWVldxc2RhBAwAAIcHn80Xm5+dH1m/n5eV5ExMTD+fk5HQbP358yRlnnHFo7ty5W3NycpL8fr9xMisFGgAACAllZWWeyZMn9+zdu3dGnz590tetW+edNGlSyXvvvdf+kUce2SlJ55xzTsWoUaNKH3jgga5OZmWKEwAANDs3TnGeDKY4AQAAQgwFGgAAgMtQoAEAALgMBRoAAIDLUKABAAC4DAUaAACAy7AWJwAAaPWKioo8o0aN6itJxcXF4WFhYTY+Pr46LCxMVVVVprS0tE1YWJhNSEiolqSvvvpqbVRUlGPvIqNAAwAArV7Xrl1r1q1bt0aSpk+f3j0mJqbm4Ycf3lW/v7E2JzHFCQAA4DKMoAEAgBZV8ucNSVVFB6ODec7wrm39CZf12RbMczqJETQAAACXYQQNAAC0qNY00tVcGEEDAABwGQo0AAAAlzHWOvaKDwAAECJ8Pt+WrKysYqdzBIvP5+uYlZWV3FznZwQNAADAZSjQAAAAXIYCDQAAwGUo0AAAAFyGAg0AAMBlKNAAAABchgINAACEhPXr10ekpqZmNGybPn1691mzZnWZOHFi8gsvvNBeknbt2uXp169f+lNPPdXBmaQUaAAAAEfs3bvXc9555/W5/vrr90ybNm2vUzko0AAAACSVl5eHnX/++amXX3753pycnD1OZmGxdAAA0KKWLFmStHv37uhgnrNz587+CRMmnNQi7A888EDSpEmTih988MHdwcr1fTGCBgAAQoIx5pjtZ599dtn7778fX1hY6PgAluMBAABAaDnZka7vq0uXLtWlpaWehm0lJSWenj17VkrSlVdeuW/btm0HLrjggtR//OMf69u3b1/rRE6JETQAABAi4uLiajt37lz15ptvxkp1T2t+9NFHcaNHjz5Qf8ysWbN2jxgxomzs2LEphw4danzIrQVQoAEAgJAxf/78rx955JFuaWlp6eeee27fnJycHRkZGZUNj5k3b15h9+7dD0+cOLFnTU2NIzmNtdaRDwYAAKHD5/NtycrKKnY6R7D4fL6OWVlZyc11fkbQAAAAXIYCDQAAwGUo0AAAAFyGAg0AAMBlKNAAAABchgINAADAZSjQAABASFi/fn1EampqRsO26dOnd7///vu7jB07tld9W0lJSVhSUlLmunXrIlo+ZR0KNAAAENKMMdq5c2fEkiVLYiVpxowZPa6++uritLS0w05lYi1OAAAQ0owxmjdv3tZrr722V0JCwtcff/xx7KpVq9Y6mYkCDQAAtKg1a3OSDh7YEB3Mc7aN6eNP7zfney/CPmzYsIpRo0aVjh07ts/LL7/8r6ioKEeXWmKKEwAAhARjGl/7vL79v//7v3d37ty56uKLLy5vyVyNYQQNAAC0qJMZ6ToZXbp0qS4tLfU0bCspKfH07NmzUpI8Ho/CwtwxduWOFAAAAM0sLi6utnPnzlVvvvlmrCTt2rXL89FHH8WNHj36gNPZjsYIGgAACBnz58//+vbbbz8tJycnSZJycnJ2ZGRkVDqd62gUaAAAIGQMHjz40KeffrqhsX19+/Y9vHHjxtUtnakxTHECAAC4DAUaAACAy1CgAQAAuAwFGgAAgMtQoAEAALgMBRoAAIDLUKABAIBWb+jQoX0XL17crmHbww8/3Pncc89NiYqKGpSWlpZe/+eZZ57p4FTOerwHDQAAtHqXX3753ldeeSVh4sSJZfVtixcvTpgzZ872u+66K3LdunVrnMx3NEbQAABAq3fdddftW758eVxFRYWRpPXr10fs3r07PDk5+bDT2RrDCBoAAGhRP137TdK6g4eig3nOtLZR/if7ndbkIuxdu3atycrKOrh48eK4a6+9dv/8+fMTxo8fv88Yo23btkWmpaWl1x/75JNPfnPhhRc6uj4nBRoAAAgJV1xxRclrr73W/tprr93/l7/8JeG5557bIklJSUmVbpvipEADAAAt6lgjXc3pmmuu2X///fcnffzxx9GHDh0Ky87O9q9fvz7CiSzHwz1oAAAgJMTFxdWeddZZ5TfffHPypZdeWuJ0nmOhQAMAACHjqquuKlm/fr33uuuuO1Kg1d+DVv/nl7/8ZWcnM0qSsdY6nQEAALRyPp9vS1ZWVrHTOYLF5/N1zMrKSm6u8zOCBgAA4DIUaAAAAC5DgQYAAOAyFGgAAKAl1NbW1hqnQwRDoB+1zfkZFGgAAKAlFOzZsyfuVC/SamtrzZ49e+IkFTTn5/CiWgAA0Oyqq6tvLioqeq6oqChTp/YAUa2kgurq6pub80N4zQYAAIDLnMoVLAAAQKtEgQYAAOAyFGgAAAAuQ4EGAADgMhRoAAAALvP/AxS/4GZAx2noAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths_pc.plot(logy=True, figsize=(10, 6), title=\"Deaths per capita, log\")\n",
-    "for c in deaths_pc.columns:\n",
-    "    lvi = deaths_pc[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = deaths_pc[c][lvi], s = c)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 626,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f03f4da4050>"
-      ]
-     },
-     "execution_count": 626,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "deaths_pc[['UK', 'IE']].plot( figsize=(10, 6), title=\"Deaths per capita, linear\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 627,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f03f4ca4910>"
-      ]
-     },
-     "execution_count": 627,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "deaths_pc[['UK', 'IE']].plot(logy=True, figsize=(10, 6), title=\"Deaths per capita, log\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 628,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "deaths[['UK', 'ES', 'IT']].plot(logy=True, figsize=(10, 6), title=\"Deaths, log\")\n",
-    "plt.savefig('covid_deaths_selected_log.png')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 629,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f03f4ace110>"
-      ]
-     },
-     "execution_count": 629,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "deaths[['UK', 'ES', 'IT', 'MX']].plot(logy=True, figsize=(10, 6), title=\"Deaths, log\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 630,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>since_threshold</th>\n",
-       "      <th>geoId</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td rowspan=\"3\" valign=\"top\">0</td>\n",
-       "      <td>DE</td>\n",
-       "      <td>2020-03-16</td>\n",
-       "      <td>1043</td>\n",
-       "      <td>4</td>\n",
-       "      <td>4838</td>\n",
-       "      <td>12</td>\n",
-       "      <td>310.0</td>\n",
-       "      <td>1.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-02-26</td>\n",
-       "      <td>93</td>\n",
-       "      <td>5</td>\n",
-       "      <td>322</td>\n",
-       "      <td>11</td>\n",
-       "      <td>-4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-03-15</td>\n",
-       "      <td>478</td>\n",
-       "      <td>19</td>\n",
-       "      <td>2244</td>\n",
-       "      <td>29</td>\n",
-       "      <td>-6.0</td>\n",
-       "      <td>18.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td rowspan=\"2\" valign=\"top\">1</td>\n",
-       "      <td>DE</td>\n",
-       "      <td>2020-03-17</td>\n",
-       "      <td>1174</td>\n",
-       "      <td>1</td>\n",
-       "      <td>6012</td>\n",
-       "      <td>13</td>\n",
-       "      <td>131.0</td>\n",
-       "      <td>-3.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-02-27</td>\n",
-       "      <td>78</td>\n",
-       "      <td>1</td>\n",
-       "      <td>400</td>\n",
-       "      <td>12</td>\n",
-       "      <td>-15.0</td>\n",
-       "      <td>-4.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>171</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>574</td>\n",
-       "      <td>3</td>\n",
-       "      <td>252809</td>\n",
-       "      <td>35234</td>\n",
-       "      <td>52.0</td>\n",
-       "      <td>-3.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>172</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>629</td>\n",
-       "      <td>158</td>\n",
-       "      <td>253438</td>\n",
-       "      <td>35392</td>\n",
-       "      <td>55.0</td>\n",
-       "      <td>155.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>173</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>477</td>\n",
-       "      <td>4</td>\n",
-       "      <td>253915</td>\n",
-       "      <td>35396</td>\n",
-       "      <td>-152.0</td>\n",
-       "      <td>-154.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>174</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>320</td>\n",
-       "      <td>4</td>\n",
-       "      <td>254235</td>\n",
-       "      <td>35400</td>\n",
-       "      <td>-157.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>175</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>401</td>\n",
-       "      <td>5</td>\n",
-       "      <td>254636</td>\n",
-       "      <td>35405</td>\n",
-       "      <td>81.0</td>\n",
-       "      <td>1.0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>491 rows × 7 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                         dateRep  cases  deaths  cases_culm  deaths_culm  \\\n",
-       "since_threshold geoId                                                      \n",
-       "0               DE    2020-03-16   1043       4        4838           12   \n",
-       "                IT    2020-02-26     93       5         322           11   \n",
-       "                UK    2020-03-15    478      19        2244           29   \n",
-       "1               DE    2020-03-17   1174       1        6012           13   \n",
-       "                IT    2020-02-27     78       1         400           12   \n",
-       "...                          ...    ...     ...         ...          ...   \n",
-       "171             IT    2020-08-15    574       3      252809        35234   \n",
-       "172             IT    2020-08-16    629     158      253438        35392   \n",
-       "173             IT    2020-08-17    477       4      253915        35396   \n",
-       "174             IT    2020-08-18    320       4      254235        35400   \n",
-       "175             IT    2020-08-19    401       5      254636        35405   \n",
-       "\n",
-       "                       cases_diff  deaths_diff  \n",
-       "since_threshold geoId                           \n",
-       "0               DE          310.0          1.0  \n",
-       "                IT           -4.0          1.0  \n",
-       "                UK           -6.0         18.0  \n",
-       "1               DE          131.0         -3.0  \n",
-       "                IT          -15.0         -4.0  \n",
-       "...                           ...          ...  \n",
-       "171             IT           52.0         -3.0  \n",
-       "172             IT           55.0        155.0  \n",
-       "173             IT         -152.0       -154.0  \n",
-       "174             IT         -157.0          0.0  \n",
-       "175             IT           81.0          1.0  \n",
-       "\n",
-       "[491 rows x 7 columns]"
-      ]
-     },
-     "execution_count": 630,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT']), :]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 631,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "      <th>deaths_m4</th>\n",
-       "      <th>deaths_m7</th>\n",
-       "      <th>cases_m7</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>since_threshold</th>\n",
-       "      <th>geoId</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td rowspan=\"3\" valign=\"top\">0</td>\n",
-       "      <td>DE</td>\n",
-       "      <td>2020-03-16</td>\n",
-       "      <td>1043</td>\n",
-       "      <td>4</td>\n",
-       "      <td>4838</td>\n",
-       "      <td>12</td>\n",
-       "      <td>310.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.00</td>\n",
-       "      <td>4.000000</td>\n",
-       "      <td>1043.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-02-26</td>\n",
-       "      <td>93</td>\n",
-       "      <td>5</td>\n",
-       "      <td>322</td>\n",
-       "      <td>11</td>\n",
-       "      <td>-4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>5.00</td>\n",
-       "      <td>5.000000</td>\n",
-       "      <td>93.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-03-15</td>\n",
-       "      <td>478</td>\n",
-       "      <td>19</td>\n",
-       "      <td>2244</td>\n",
-       "      <td>29</td>\n",
-       "      <td>-6.0</td>\n",
-       "      <td>18.0</td>\n",
-       "      <td>19.00</td>\n",
-       "      <td>19.000000</td>\n",
-       "      <td>478.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td rowspan=\"2\" valign=\"top\">1</td>\n",
-       "      <td>DE</td>\n",
-       "      <td>2020-03-17</td>\n",
-       "      <td>1174</td>\n",
-       "      <td>1</td>\n",
-       "      <td>6012</td>\n",
-       "      <td>13</td>\n",
-       "      <td>131.0</td>\n",
-       "      <td>-3.0</td>\n",
-       "      <td>2.50</td>\n",
-       "      <td>2.500000</td>\n",
-       "      <td>1108.500000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-02-27</td>\n",
-       "      <td>78</td>\n",
-       "      <td>1</td>\n",
-       "      <td>400</td>\n",
-       "      <td>12</td>\n",
-       "      <td>-15.0</td>\n",
-       "      <td>-4.0</td>\n",
-       "      <td>3.00</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>85.500000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>171</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>574</td>\n",
-       "      <td>3</td>\n",
-       "      <td>252809</td>\n",
-       "      <td>35234</td>\n",
-       "      <td>52.0</td>\n",
-       "      <td>-3.0</td>\n",
-       "      <td>6.25</td>\n",
-       "      <td>6.285714</td>\n",
-       "      <td>436.142857</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>172</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>629</td>\n",
-       "      <td>158</td>\n",
-       "      <td>253438</td>\n",
-       "      <td>35392</td>\n",
-       "      <td>55.0</td>\n",
-       "      <td>155.0</td>\n",
-       "      <td>44.25</td>\n",
-       "      <td>27.000000</td>\n",
-       "      <td>476.428571</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>173</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>477</td>\n",
-       "      <td>4</td>\n",
-       "      <td>253915</td>\n",
-       "      <td>35396</td>\n",
-       "      <td>-152.0</td>\n",
-       "      <td>-154.0</td>\n",
-       "      <td>42.75</td>\n",
-       "      <td>27.285714</td>\n",
-       "      <td>478.428571</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>174</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>320</td>\n",
-       "      <td>4</td>\n",
-       "      <td>254235</td>\n",
-       "      <td>35400</td>\n",
-       "      <td>-157.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>42.25</td>\n",
-       "      <td>27.285714</td>\n",
-       "      <td>487.142857</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>175</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>401</td>\n",
-       "      <td>5</td>\n",
-       "      <td>254636</td>\n",
-       "      <td>35405</td>\n",
-       "      <td>81.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>42.75</td>\n",
-       "      <td>27.142857</td>\n",
-       "      <td>485.571429</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>491 rows × 10 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                         dateRep  cases  deaths  cases_culm  deaths_culm  \\\n",
-       "since_threshold geoId                                                      \n",
-       "0               DE    2020-03-16   1043       4        4838           12   \n",
-       "                IT    2020-02-26     93       5         322           11   \n",
-       "                UK    2020-03-15    478      19        2244           29   \n",
-       "1               DE    2020-03-17   1174       1        6012           13   \n",
-       "                IT    2020-02-27     78       1         400           12   \n",
-       "...                          ...    ...     ...         ...          ...   \n",
-       "171             IT    2020-08-15    574       3      252809        35234   \n",
-       "172             IT    2020-08-16    629     158      253438        35392   \n",
-       "173             IT    2020-08-17    477       4      253915        35396   \n",
-       "174             IT    2020-08-18    320       4      254235        35400   \n",
-       "175             IT    2020-08-19    401       5      254636        35405   \n",
-       "\n",
-       "                       cases_diff  deaths_diff  deaths_m4  deaths_m7  \\\n",
-       "since_threshold geoId                                                  \n",
-       "0               DE          310.0          1.0       4.00   4.000000   \n",
-       "                IT           -4.0          1.0       5.00   5.000000   \n",
-       "                UK           -6.0         18.0      19.00  19.000000   \n",
-       "1               DE          131.0         -3.0       2.50   2.500000   \n",
-       "                IT          -15.0         -4.0       3.00   3.000000   \n",
-       "...                           ...          ...        ...        ...   \n",
-       "171             IT           52.0         -3.0       6.25   6.285714   \n",
-       "172             IT           55.0        155.0      44.25  27.000000   \n",
-       "173             IT         -152.0       -154.0      42.75  27.285714   \n",
-       "174             IT         -157.0          0.0      42.25  27.285714   \n",
-       "175             IT           81.0          1.0      42.75  27.142857   \n",
-       "\n",
-       "                          cases_m7  \n",
-       "since_threshold geoId               \n",
-       "0               DE     1043.000000  \n",
-       "                IT       93.000000  \n",
-       "                UK      478.000000  \n",
-       "1               DE     1108.500000  \n",
-       "                IT       85.500000  \n",
-       "...                            ...  \n",
-       "171             IT      436.142857  \n",
-       "172             IT      476.428571  \n",
-       "173             IT      478.428571  \n",
-       "174             IT      487.142857  \n",
-       "175             IT      485.571429  \n",
-       "\n",
-       "[491 rows x 10 columns]"
-      ]
-     },
-     "execution_count": 631,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_since_threshold['deaths_m4'] = data_since_threshold.groupby(level=1)['deaths'].transform(lambda x: x.rolling(4, 1).mean())\n",
-    "data_since_threshold['deaths_m7'] = data_since_threshold.groupby(level=1)['deaths'].transform(lambda x: x.rolling(7, 1).mean())\n",
-    "data_since_threshold['cases_m7'] = data_since_threshold.groupby(level=1)['cases'].transform(lambda x: x.rolling(7, 1).mean())\n",
-    "# data_since_threshold['deaths_diff_m4'] = data_since_threshold.groupby(level=1)['deaths_diff'].transform(lambda x: x.rolling(4, 1).mean())\n",
-    "# data_since_threshold['deaths_diff_m7'] = data_since_threshold.groupby(level=1)['deaths_diff'].transform(lambda x: x.rolling(7, 1).mean())\n",
-    "data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT']), :]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 632,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "deaths_m4 = (data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['deaths_m4']]\n",
-    "             .unstack().sort_index().xs('deaths_m4', axis=1, drop_level=True))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 633,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "deaths_m7 = (data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['deaths_m7']]\n",
-    "             .unstack().sort_index().xs('deaths_m7', axis=1, drop_level=True))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 634,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "cases_m7 = (data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['cases_m7']]\n",
-    "             .unstack().sort_index().xs('cases_m7', axis=1, drop_level=True))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 635,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths_m4.plot(figsize=(10, 6), title=\"Deaths per day, 4 day moving average\")\n",
-    "for c in deaths_m4.columns:\n",
-    "    lvi = deaths_m4[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = deaths_m4[c][lvi], s = c)\n",
-    "plt.savefig('covid_deaths_per_day.png') "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 636,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths_m4[COUNTRIES_CORE].plot(figsize=(10, 6), title=\"Deaths per day, 4 day moving average\")\n",
-    "for c in COUNTRIES_CORE:\n",
-    "    lvi = deaths_m4[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = deaths_m4[c][lvi], s = c)\n",
-    "plt.savefig('covid_deaths_per_day-core.png') "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 637,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths_m4[COUNTRIES_FRIENDS].plot(figsize=(10, 6), title=\"Deaths per day, 4 day moving average\")\n",
-    "for c in COUNTRIES_FRIENDS:\n",
-    "    lvi = deaths_m4[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = deaths_m4[c][lvi], s = c)\n",
-    "plt.savefig('covid_deaths_per_day-friends.png') "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 638,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "C7s = 'ES FR IT UK'.split()\n",
-    "ax = deaths_m7[C7s].plot(figsize=(10, 6), title=\"Deaths per day, 7 day moving average\")\n",
-    "for c in C7s:\n",
-    "    lvi = deaths_m7[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = c)\n",
-    "# plt.savefig('covid_deaths_per_day-friends.png') "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 639,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths_m7[COUNTRIES_CORE].plot(figsize=(10, 6), title=\"Deaths per day, 7 day moving average\")\n",
-    "ax.set_xlabel(f\"Days since {DEATH_COUNT_THRESHOLD} deaths\")\n",
-    "for c in COUNTRIES_CORE:\n",
-    "    lvi = deaths_m7[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = c)\n",
-    "# plt.axhline(0, color='0.7')\n",
-    "plt.savefig('covid_deaths_per_day_7.png') "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 640,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths_m7[COUNTRIES_FRIENDS].plot(figsize=(10, 6), title=\"Deaths per day, 7 day moving average\")\n",
-    "ax.set_xlabel(f\"Days since {DEATH_COUNT_THRESHOLD} deaths\")\n",
-    "for c in COUNTRIES_FRIENDS:\n",
-    "    lvi = deaths_m7[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = c)\n",
-    "# plt.axhline(0, color='0.7')\n",
-    "# plt.savefig('covid_deaths_per_day_7.png') "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 641,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "since_threshold\n",
-       "70     122.571429\n",
-       "71     112.000000\n",
-       "72      88.428571\n",
-       "73            NaN\n",
-       "74            NaN\n",
-       "          ...    \n",
-       "171           NaN\n",
-       "172           NaN\n",
-       "173           NaN\n",
-       "174           NaN\n",
-       "175           NaN\n",
-       "Name: ES, Length: 106, dtype: float64"
-      ]
-     },
-     "execution_count": 641,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "deaths_m7_prime = deaths_m7[COUNTRIES_CORE].copy()\n",
-    "deaths_m7_prime.loc[73:, 'ES'] = np.NaN\n",
-    "deaths_m7_prime['ES'][70:]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 642,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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SzCGh+BtJmczkFEIIIXqGtKAJl1WXlRIcFdOqBU0IIYTorPOhpaunSAuacJm9BS2kRQuazOQUQggheoIkaMIljQ0NWCvKMYeE4R8YBEgLmhBCCNFTpItTuMRSYV9iwxwSiqeXF75ms4xBE0IIMSBVnbMKwSuvvNI3gTghLWjCJZaybxM0AFNQsLSgCSGEED1EEjThkipjFwFzqD1B8wsMwlopCZoQQgjREyRBEy5p2oezdQuaTBIQQggheoIkaMIl1WX2FjRTsD1B8w8Mlv04hRBCiB4iCZpwSXVZGX4BgXh5ewNgCgrCWlGB1rqPIxNCCCHOPx0maEqpl5VSBUqpgy2OhSmlPlNKHTN+hhrHlVLqGaXUcaXUfqXU5BbX3G6UP6aUur1n3o7oKRZjF4Em/kHB2BobqLVU92FUQgghxPnJlRa0V4Arzzn2ALBBaz0c2GC8BrgKGG48VgB/A3tCBzwETAemAQ81JXViYKgqK2mVoMluAkIIIQYqT09PUlJSGDt2LBMnTuQvf/kLNpsNgI0bNxIcHExKSkrz4/PPP+/1GDtcB01rvUkplXTO4euBy4znrwIbgfuN42u0vd9ru1IqRCkVa5T9TGtdAqCU+gx70vdGl9+B6BWWslLiRoxuft1yN4HQ2EF9FZYQQgjhNn9/f9LT0wEoKChgyZIllJeX84c//AGAWbNmsW7dur4MsdNj0KK11rkAxs8o4/ggIKtFuWzjmKPjYgDQWlNdVoZJWtCEEEKcZ6KionjhhRd47rnn+tW46u7eSUC1c0w7Od62AqVWYO8eJSEhofsiE51WZ7XQUFdLQMsxaMZ2T7KbgBBCiE5b/wDkHejeOmPGw1WPuXXJkCFDsNlsFBQUALB582ZSUlKaz7/77rsMHTq0W8PsSGcTtHylVKzWOtfowiwwjmcDg1uUiwfOGscvO+f4xvYq1lq/ALwAMGXKlP6Tyl7Azl0DDcA/yNiPU5baEEIIcR5o2XrWH7o4O5ugfQjcDjxm/PygxfF7lVJvYp8QUG4kcZ8Cj7aYGPAd4MHOhy16U3XzLgJhzce8ff3w8vWVLk4hhBCd52ZLV085efIknp6eREVFkZGR0dfhAC4kaEqpN7C3fkUopbKxz8Z8DHhLKXUncAa42Sj+b+Bq4DhgAe4A0FqXKKX+COwyyv1304QB0f+114IGsh+nEEKIga+wsJC7776be++9F6XaG5HVN1yZxXmrg1Nz2ymrgXsc1PMy8LJb0Yl+odrYKN10ToImuwkIIYQYiKxWKykpKdTX1+Pl5cXSpUv5xS9+0Xz+3DFov/3tb1m0aFGvxtjdkwTEeaYsL5fM/Xvx9PLCzxzQ6pwpKEgmCQghhBhwGhsbHZ677LLLKC/v+79tkqCJdp05uJ/t775B1uEDKOXBuMvntWn69Q8Kpij7TB9FKIQQQpy/JEET7dr8+mrKC/K5ZPFSxl46l8DwiDZl/APt+3EKIYQQontJgibaVVVWypDJU7l44WKHZfyDgmmoq6W+pgZvP79ejE4IIYQ4v3V2JwFxHtNaYy0vazMp4FzNuwnIRAEhhBCiW0mCJtqora6msaEBc3CI03Lf7sfZ94MphRBCiPOJJGiijepy+7pnpg4StKYWtKZ10oQQQgjRPSRBE21YylxL0MIGxQNQdCazp0MSQgghuk1mZibjxo1rdezhhx9m1apVLFu2jHfeeQeAkpISJk2axOrVq3s9RknQRBvV5faFaTvq4vQzBxASHUv+qeO9EZYQQgjRa8rLy7niiitYsWIFd9xxR6/fXxI00YbFSNC2le/FUm9xWjZqyDDyT57ojbCEEEKIXlFVVcVVV13FkiVL+NGPftQnMcgyG6KN0pJ8bErz6z0P4b//MS6Lv4xbRt3C5OjJbcpGJw/l6LbNWCsr8A8M6oNohRBCDFSP73ycIyVHurXOUWGjuH/a/V2q4xe/+AV33XUXP//5z7spKvdJC5poY1/mbmp8GlmZupLrhl7Httxt3PWfu8iuzG5TNjp5GAAFp072dphCCCFEpzjaFL3p+Jw5c/jggw8oKCjozbBakRY00UqRtYjs/JNEBQZz/bDruX7Y9dw1/i6ufe9ankl7hidmP9GqfNSQoQDknzpO4oSU9qoUQggh2tXVlq7OCg8Pp7S09QoEJSUlJCcnA3DLLbeQmprK1VdfzZdffklgYGCvxygtaKKV5/c9j2+NIj56SPOxGHMMS8csZf2p9RwqOtSqvH9AIEGR0eSflIkCQgghBoaAgABiY2PZsGEDYE/OPvnkE1JTU5vL/Nd//Rdz587lxhtvpK6urtdjlARNNMuuzOadY+8QZgsgPDym1bnl45YT5hfGqt2r0Fq3Ohc9ZKjM5BRCCDGgrFmzhpUrV5KSksKcOXN46KGHGDp0aKsyjz/+OIMHD2bp0qXYbLZejU+6OAVg397pmbRn8MQTL6utzRpoAT4B/Hjij1m5YyUbszZyecLlzeeik4dxbMdWaqqq8AsI6O3QhRBCCLeNGTOGL7/8ss3xV155pdXrvlgDDaQFTWAfd3bPhntYf2o9S4fdis3BNk8LRywkKSiJv+z5C9YGa/Px6CHGRIFMWW5DCCGE6A6SoF3gvjjzBQs/WMjOvJ08OO1BvpfwXYB2N0r39vDm/mn3c6byDD/6/EdU11cDEJVsTBRoMQ5tY9ZG0grSeuEdCCGEEOcfSdAuYG998xY/+/JnxJhjeGvBWywZvQRruX3jc0fbPKUOSuWxWY+RXpDOis9WUFFXgSkomMCIyOYErb6xnl9v/jUPb324zXg1IYQQQnRMErQL1EcnPmLl9pXMjp/N2qvXMiTEPmvTlW2erkq+iicvfZLDxYe569O7qKyrJDp5WHMX5868nVTWV3Ky/CSHig85rEcIIYQQ7ZME7QL0+enP+d3Xv2NazDT+ctlf8Pb0bj5nKbevC2Nup4uzpbmJc3n68qfJKMng7aNvEz1kGKW5Z6m1VLPh6KdMPhVOYnEgH574sEffixBCCHE+kgTtAvNNyTf8atOvGB8xnmfmPIOvp2+r85byMpTywM+FRflmx89mctRk3j36LlFJ9ha4DS//He+X9jAhI4BZR2NYf2o99Y317V5flpfLP35yJ+UFeV1/Y0IIIcR5RBK0C8yXWV/SaGvk6TlPY/I2tTlfXV6Gf1AQHh6eLtW3aMQizlSe4WxAFQAZm78kL9RK6MzxeJXWoYur2JSzqd1r808dp7wgn7NHu3cfNiGEEMIZT09PUlJSmh+PPfYYAOvWrWPSpElMnDiRMWPG8Pzzz/dZjLIO2gXmYNFBkoOTCfMLa/e8pbzM6fizc81PnM+fdv6JD3PXs/xn97Gu8DM2Vazjgfk/5PWt9zKqKIKPTnzE3IS5ba6tLrOPdyvLy+3cmxFCCCE6wd/fn/T09FbH6uvrWbFiBTt37iQ+Pp7a2loyMzP7JkCkBe2CorXmQNEBxkeMd1jGUlbW7hIbjvh5+XHtkGv5/MznRE8ez4aG3UyPnU5sTBKxw0Yyqjicr7K/oqymrO29jPFuZXln3X8zQgghRDeqrKykoaGB8PBwAHx9fRk5cmSfxSMtaBeQnKocSmpKmBA5wWGZ6vIyQmLj3Kr3phE38fqR13ly95NkV2Vzx7g7ABg2bQa5r7+Cb7VmfeZ6bh11a+t7GS1opfnSgiaEEBeivEcfpTaje4e5+I4eRcyvf+20jNVqJSUlpfn1gw8+yOLFi7nuuutITExk7ty5LFiwgFtvvRUPj75py5IWtAvIgaIDAA5b0LTWWMrLHK6B5siI0BFMiJzAByc+QKGYkzAHgOHTZgAwpSKR946912ZNtLKSfAAKck47nEgghBBCdLemLs6mx+LFiwH4xz/+wYYNG5g2bRqrVq1i+fLlfRajtKBdQPYX7sfP04/hocPbPV9ntdJQV+vWGLQmi4YvYn/hfiZGTiTCPwKA0NhBRCQk4Vdcw1clO9hwZgPzEuc1X3M69xieQGO1lSvfmMc1o6/n7gl3tzt5QQghxPmno5auvjB+/HjGjx/P0qVLSU5ObrM3Z2+RFrQLyIGiA4wJH4OXR/t5uatroLXniqQrSAhMYOHwha2OD582g5rT+YzwSeLpvU/TYGsA7Mt91FRUoH3tsUzyHs3qg6tZm7HW7XsLIYQQXVVVVcXGjRubX6enp5OYmNhn8UiCdp6yHjhI2XvvU59v70asb6wnozjD6QSBpl0E3O3iBDB5m/h44cfcOPzGVseHT5sJWrPYay6ZFZm8f/x9tNas2vVn/Gs9SRg1DoAfJNzGsJBh7Mnf4/a9hRBCCHc0jUFrejzwwANorXniiScYOXIkKSkpPPTQQ33WegbSxXlestXWkn3PPTQUFADgO3wY1vkzqAuuY3ykkxmcXUjQHIlISCIkOhaPYyVMTJnIX9P/SpBPEGlndjFKDyZx9ASy9qVTlpfL5JjJfHzqYxptjXi6uA6bEEII4a7GxsZ2j//73//u5Ugckxa081DZP9+ioaCA2EdWEvWrX+EREIjHX19j9Bnd4RIb0LkuTkeUUiSMm0j+yeP8/KKfU2gt5P7N9zPEezAAwVHRmEPDKM07y6ToSVTXV3Os7Fi33V8IIYQYiCRBO8/YrFaKXnwB07RphNx0E+F3Lidh9ctYgn257WsPYs2xDq+tLi8DpfAPDOrWmIKjY6iprGB80Ggujb+UBlsDSxJuAuzJYEh0rL0FLWoyAHvz93br/YUQQoiBRhK080zpm/+ksbCIyJ/c23zMw8+Pz2YFMiKzHsuOnQ6vtZSX4h8YhIdn93YvBkVGAVBeWMDDMx/msVmPMdInGQBTSCghMbGU5ecSa44l2hRNWkFat95fCCGEGGgkQTuP2CwWil98EfPMGZimTm0+Xl5bzlujS6kNNVP43LNt1iNr4u42T64Kjoq2x1GQT4R/BNcMuaZ5vJs5OJTQmDiqS0toqK1lctRk9ubvdRijEEIIcSGQBO08UrJ2LY0lJUTc+5NWxw8WHaTeS2FbegPW3XuwbNvW7vXVnVik1hXBkfYEraIw/9t7lZXi6eWFr9lMSIx954KmcWgF1gLOVsv2T0IIIS5ckqCdJ7TNRsmrazCnpmKaPKnVuQNFB1Aohi/9EV4xMRQ++1y7LVSW8rJunSDQxD8oGC9f31YJmn3HglCUUoTE2MfFleXLODQhhBACJEE7b9QczqCxqIjg665tc+6bkm9ICEogMDCciB+uwJqW1qYVTdtsVJeWurVRuquUUgRHRlNe0LoFzRxib60LiTYStLxchoUMI8A7oNU4tINFByVhE0II0W0CAgIAyMzMxN/fv9WaaGvWrOnj6OxkHbTzRPWWzQCYL7mkzbmjpUcZGTYSgOCbbqLor3+j6IUXMc+c2VymJDeHhrpaIhOSeiS+oMgoygsLvo23rJTAiEgAfE0mTMEhlOWdxdPDk4lRE5sTtENFh7jjkzsweZv48rtf4qHk3xRCCCG6z9ChQ0lPT+/rMNqQv3bniarNW/AbOxav8PBWxy31FrIqsxgROgIADx8fwpYtw7J9O9b9+5vL5Z88DkB08tAeiS84KpqKgtZdnC0nJDQttQEwOWoyx8uO803JN9z7xb006kZKakrIKMnokdiEEEKI/kZa0M4DjRUVWNPTCf/BXW3OHS87jkY3J2gAIYsXU/TCCxS98AKDn3sOsCdoXj6+hA0a3CMxBkVGU2uppqa6Ch9/fyzl5a3Gu4XExHLmkD1hnBRlH0N3x6d3oLXm+fnPs/zT5WzJ3sLY8LE9Ep8QQojet/mtoxRlVXVrnRGDA5j13REdFzScOHGClJSU5tfPPvsss2bN6taYOkNa0M4D1du2Q2MjAe18ob4p/QagVYLmGWAm7LYlVH2+gdrj9paz/JPHiUxK7vY10Jo0LbVRUVhATWUlWttajXcLiYmlqriI+rpaxkWMw0t5Yam38ORlTzI1Zipjw8eyJWdLj8QmhBDiwtXUxdn06A/JGUgL2nmhestmPAID8Z84sc25oyVHMXubiQuIa3U8dOlSile/QvGL/yD2T49SkHmSsZfO7bEYm5ba+GDzAT7LbmA6tO7iNJbaKM/PI2JwIj9O+TGDAwczM84+Ti51UCovHniR8tpygn2DeyxOIYQQvcedlq4LjbSgDXBaa6o2b8E8Y7pKlxMAACAASURBVAbKq22+fbT0KCNCR7QZXO8VGkrod2+mfN068tP2Ul9jJXrIsB6Ls2k3gX9vPURubiFAqxa0UCNBaxqH9oMJP+DK5Cubz6cOSsWmbWw72/4abkIIIcT5RBK0Aa7uxAka8vIwz0ptc05rzbHSY626N1sKu+MOlK8vR//8OECPJmhZ1VDn4U2iby1DAmwAmIK+bUELjY1DKQ9yj3/T7vXjI8YT7BvM5pzNPRajEEKIC0/TGLSmxzPPPNPXIQFd7OJUSv0cuAvQwAHgDiAWeBMIA/YCS7XWdUopX2ANcBFQDCzWWmd25f7CPnsTICC1bYKWW51LZX2lwwTNOyaGuEdWcujPj+AZFUZ4D00QKK2u4wev7WG2TzAXR0JZkA/VJ+BUtQdhRhlfk5nEiZPI2LKR1MVLUR6t/+3g6eHJzNiZbMnZgk3bZLkNIYQQnVZVZZ+YkJSUhNVq7eNo2tfpv3JKqUHAT4EpWutxgCdwC/A48JTWejhQCtxpXHInUKq1HgY8ZZQTXVS9eTO+w4fhHRvb5tzR0qMADhM0gKCrrsKSlEBglYXK9Z90a2x1DTb+b/tprn5mM7nlNQwbkkBtWTFDAmzUKy/e3lfQqvyY2XOoLCokO+Ngu/XNip8ly20IIYS4IHS1GcIL8FdKeQEmIBeYA7xjnH8VuMF4fr3xGuP8XKWU6uL9L2gNpaVYdu/GnNr+jJOmBG146HCHdWibjbLGesIDgsj93e+oOXq0W2L7eH8ul6/ayG/fP0hssB9r75rO4MRBlBfkU19ZjjIF8uH+XCpr6puvGTZlOj7+/hza9EW7dTZNGNiSLbM5hRBCnN86naBprXOAVcAZ7IlZObAHKNNaNxjFsoFBxvNBQJZxbYNRvvWqqsIt+Y/+CW2zEXzjDe2eP1p6lPiAeMzeZod1lOadpa7GSvKS7+ERYCbnpz+jsbKyS3H951Ae976xl1CzN68un8a7P5rJ1KQwgiOjqa+xUpyTRXhEBJa6Rt5P/3ZTdG9fP0ZcnMrR7V9TX1vTpt5w/3DGho+VcWhCCCHOe13p4gzF3iqWDMQBZuCqdoo27crdXmtZmx27lVIrlFK7lVK7CwsLOxveea/yiy+p+OgjIn74Q/xGtN+F2TSD05n8E8cAiEuZTPxTT1GXlUXur3/d7mbqrtifXcbP3kxnQnwIb/9wJpeOiKSpoTTIWAut6EwmkVERjI4N4vUdZ1rda8zsOdTXWDm+a3u79c9NmMu+wn38edefabA1tFtGCCGEGOi60sU5DziltS7UWtcD/wJmAiFGlydAPNDURJINDAYwzgcDJedWqrV+QWs9RWs9JTIysgvhnb8aKyrIe/hhfEeMIOKHK9otU9NQw+mK04wI6yBBO2XfQSB80GBMU6YQ9ctfUvnZ55S89JLbcWWXWlj+ym7CA3z4x/en4O/TetHbprXQtM2GOSSEJdMTyMitYF92eXOZ+FFjCYqM4rCDbs5l45axZNQS1hxew70b7qWirsLtOIUQQoj+risJ2hngYqWUyRhLNhc4DHwJLDLK3A58YDz/0HiNcf4L3dlmmgtc/uOP01BcTOyjj6J8fNotc6LsBDZtY2ToSOd1nTxBZGJS8w4CYctuJ/CKKyj4y1NUb9/hckwNjTbuenU3tQ2NrF42lchA3zZlmtZCAzAFh3JDShwmH09e33G6+bjy8GB06uWc3p9OVWmb/B1vD28enP4gD814iB15O7jt49uorOtal6wQQgjR33RlDNoO7IP992JfYsMDeAG4H/iFUuo49jFmTU0xLwHhxvFfAA90Ie4LlvXAQcrf/Rfhy5fjP87xvpSuzODUNhsFmSdarX+mlCL2kUfwHhxPwRNPuBzXxm8KOZJXySM3jmd4dGC7ZfzMAfia7ePhzCEhBPp5c93EOD7al0tFi8kCY2ZfjtY23n3kd6y5/6c8f/f3+fiZP7eqa9GIRTxz+TNkVmTy+enPXY5TCCGE8PT0bLX2WWZmJhs3biQ4OJhJkyYxatQofvnLX/ZpjF2axam1fkhrPUprPU5rvVRrXau1Pqm1nqa1Hqa1vllrXWuUrTFeDzPOn+yet3Bhqdq8CZQi/M7lTssdLT2Kv5c/8YHxDssUnsmkzmolekjrWZ6eAWZCFi2i5vBh6s+edXB1a2/uOkNkoC9XjYtxWi7I6OZs2kXg1mkJWOsb+SAtp7lMWFw84+degbevH4Fh4YQNiufI11+1WX4jdVAqgwIG8Z/T/3EpRiGEEALA39+/1f6bSUlJAMyaNYu0tDTS0tJYt24dX3/9dZ/FKKt9DjCWnbvwHTkSz5AQp+UOFx9meOhwpwu6ZmzZiIenF0MmT21zLnDuPMA+GaEjueVWvjhSwM0XxePt6fwr1TQOzRxsT9AmxAczNi6ItedMFvjOip+w5JEnufH+h7jhvt9jCg5h2ztvtKpLKcV3Er/D9tztlNeWI4QQQnQHf39/UlJSyMnJ6bhwD5HN0gcQW10d1vR0Qr57s9NydY11HCo+xOKRix3X1dhIxuYvGTJ5CqagtpuP+w5Jxic5mcoNnxP2vduc3u+tXdnYNNwyNaHD9xAcZR+HZjYSTKUUS6Yn8Jv3DpKWVcbkhNA213j7+jHt+kVsXPMPsjMOEj96XPO5+YnzWX1oNV9lf8V1Q6/r8P5CCCH6jy9feYGC093boRaVOITLl7U/ga6J1WolJSUFgOTkZN57771W50tLSzl27BizZ8/u1tjcIS1oA0jNgQPomhpMU9u2eLV0uPgwtY21TIqa5LDMmQPpVJeVMmbWHIdlAufNxbJrN43ljlunGm2at3ZnkTosgoRwU4fvYdDocYTGxmEO/XYJvOtTBmHy8eSNHWccXjdh3pXttqKNixhHjDmGzzI/6/DeQgghBLTu4myZnG3evJkJEyYQExPDggULiIlxPmynJ0kL2gBi2bULANOUKU7LpRekA5ASleKwzKFNX+BnDiC5ne7NJgFz5lD84j+o2rSJ4GuvbbfMpmOF5JRZ+fXVozsKH4DhU2cwfOqM1vfx9eL6lDjeS8vhtwvGEOzv3eY6b18/pl53E1+99lKrVjSlFPMT5/PmkTepqqsiwCfApTiEEEL0vY5aunrbrFmzWLduHUePHiU1NZUbb7yxuaWtt0kL2gBi2bkL3xEj8Apt2w3YUlpBGgmBCUT4R7R7vtZi4fiu7YycORsv77bJUBP/iRPxjIigckP7a5IBvLnzDOFmH+aPiXbtTTiwZFoiNfU2Pkx33N8/cf5VmIJD2LR2NYWnTzWPWftO4neot9XzVfZXXYpBCCGEABgxYgQPPvggjz/ed9uGS4I2QOj6eixpaR12b2qtSS9Md9p6dmzH1zTU1TJmtuPuTbCvSRZ4+eVUb9qEra6uzfmsEgufZxSw6KJ4fLy69lUaHx/MqJhA3ktznKB5+/ox69bbyTt+jDX3/YSX/2sF2955g3HhY4nyj+Kz09LNKYQQonvcfffdbNq0iVOnTvXJ/SVBGyCsBw+irdYOE7TTFacpqSlxOv7s8KYvCI2NI3a480VswT4OzWaxYNneeuulugYbP3kjDX9vT5bOSHTtTXTghkmD2HumjNPF1Q7LjLt8Pnc/v4b5P7iXwPBItr69lpO7dzIvcR5bcrZgqbd0SyxCCCHOX1VVVW2OXXbZZaxbt675tb+/Pzk5OSQnJ/dmaM0kQRsgLDuN8WdTnY8/SytIA3CYoFUUFpB1+ABjZs1p3iPTGdPFF+NhMrXp5vzT+gzSs8p4YtEE4kM7nhzgiusmxqEUvJ/mfO01U3AIE+ZdyaLf/BFzSCgZmzcyP3E+tY21bMrZ1C2xCCGEEH1JErQBwrJrFz7DhuIVHu60XHphOsG+wSQHt5/xZx0+AMDw6TNduq+Hry/mWbOo+uKL5jFf6w/ksvrrTJbNTOLq8bFuvAvn4kL8mZ4cxvvpOS5t1u7h6cmoS2ZzKm0Xo03DCPcLl9mcQgghzguSoA0Aur4e6969HXZvgr0FLSUyxeECtZVFhQAERbk+qN98yUwaCgupO3WKk4VV3PfOfiYODnF55qY7bpw0iFNF1a02UHdmdOrlNDY0cGLnduYlzmNzzmasDdZuj0sIIYToTZKgDQA1hw9js1gwT5vmtFxpTSmnyk85nSBQWVyEf2AQ3j5tNzN3xDx9OgD5X23h9tU78fby4H+XTOryxID2XDkuFh8vD953MlmgpajkoYQNGszhzV8yP3E+1gYrX+f03dYcQgghOuZKL0l/1hvxS4I2ALi7/tnkqMkOy1QWFxIYHunW/b0TEvCMjmbrO/+hqLKOl5dN7bZxZ+cK9vdm3ugoPtp3lvpGW4fllVKMTr2MnCOHGO4RT6hvKP/JlL05hRCiv/Lz86O4uHjAJmlaa4qLi/Hz8+vR+8hCtQOAZc9efJKS8Ip0nlilFabh7eHN2IixDstUFhcRHO3eysh1jTbSwoeSeGI/f31yEimDne8D2lU3pAzi3wfy2HKsiMtHRXVYfnTqpXz9z9c4tvVr5iTMYf2p9dQ01ODn1bP/8QghhHBffHw82dnZFBYW9nUonebn50d8fHyP3kMStH5O22xY9u4lcN7cDsumF6QzJnwMvp6Ouy8rS4qIHzPO4fn2/O8XxzniG8/Pa7eS7FEOdG1R2o5cNjKKEJM3b+4641KCFhwVw6BRY+zdnL/4Hu8ee5etZ7cyJ8H5Om9CCCF6n7e3d58tXTGQSBdnP1d7/Di28nJMFznv3tRac7T0KGPDHbee1dVYqa2udruLc+PRQph0EQCWHTvdurYzfLw8WHpxIp8eyud4QaVL14xOvZySnCySaiMI8gmSRWuFEEIMaJKg9XPWvXsBMF3keFwZQEVdBdX11cQFxDksU1lUBEBgePtbQLWnqraBgznljEwZiXdcHJadO1y+tivuuCQZf29P/rbxpEvlkyfZE9jCEyeYkzCHjVkbqWtsu/uBEEIIMRBIgtbPWXbvwTMyAu+EBKfl8qrzAIg1O16XrLLY3t/vToK293QpNg3TksMwTZ+OZecutK3jwftdFWb24dZpCbyfnkNWSce7A5hDQkEpLOWlzE+cT1V9Fdtzt3d4nRBCCNEfSYLWz1n27sF00ZQOV/3Prc4FOkrQmlrQXO/i3JVZgqeHYnJCKKbp02gsL6f2m29cvr4rfjA7GQ8FL27uuBXN08sL/8AgqstKmRE7gxDfEB7f+Thnq5zvSiCEEEL0R5Kg9WP1Z8/ScDYX02Tn3ZvQIkEL6KAFTSkCwpzvRtDSjlMljI0Lwuzr1bwOm2Vnz49DA4gN9uemyfG8uSuLgsqaDsubQ0KxlJfh7enNs3OepbS2lO+v/z6nyvtmo1shhBCisyRB68cse4zxZ1Mu6rBsbnUuPh4+hPmFOSxTWVyEOSQUTy/XJu/WNjSSnlXGtCR7nd5xcXgPHkx1L0wUaPLDS4fS0GjjpS0dJ1mm4BCqy0oBSIlKYfUVq6m31bPsk2UcLj7c06EKIYQQ3UYStH7Msmc3HmYzviNHdlg2tyqXGHOMwy2ewJ6gBbrRenYgu5y6BhtTk79N+kzTp2HZtQvd2OhyPV2RHGHmynEx/HNXFnUNzse+mUNCqS4ra349Mmwkr175Kj6ePiz5eAmP73yc8lrXtpASQggh+pIkaP2Ydc8e/CdNQnl6dlg2tzrX6fgzsO/D6c74sx2nSgCYmvRtgmaefjG2ykpqDh1yuZ6uumlyPGWWerYcd76ooTkkFEtZaavVqZOCk3hrwVssHL6QtRlrWfDeAj4++XFPhyyEEEJ0iSRo/VRjWRm1x4671L0J9gQtxux4hwCttb0FzY0ZnLsySxgeFUCY2af5mHnmDACqtmxxuZ6umjU8khCTN++nOR/wbwoOoaG+jjpr683SQ/1C+f2M3/PWtW8RHxDPb7/+LZb6jmeGCiGEEH1FErR+yrI3DQB/FyYI1NvqKbQUOl0Drba6mvraGpcTtEabZk9maavuTQCv8HD8xoyhekvvbUju4+XB1eNj+exwPtW1DQ7LmUNCAZrHoZ1rVNgofjr5pzTYGtiTv6dHYhVCCCG6gyRo/ZR17x7w9sZ/woQOy+ZX56PRzpfYKDGW2IhwrYszI7eCytqG5gkCLZlTU7Hu20djpWur/HeHG1IGYa1v5POMfIdlzMH2BM3iIEEDmBQ1CR8PH1kjTQghRL8mCVo/ZT1wEL/Ro/Hw63jD76YlNpx1cbq7SO2uTGP8WXJ7Cdol0NhI9fbeS3KmJIYSF+zHB+mOuznNIfZN3KvLHSdofl5+TIqeJAmaEEKIfk0StH5Ia03NkSP4jRrlUnmXdhEocm+R2p2nShgU4s+gEP8250wpKXiYTL3azenhobg2JY5NRwspqW5/CydTcxdnWbvnm1wcezFHS49SZC3q9jiFEEKI7iAJWj/UkJuLrbwcv9GuJWiutaAVoTw8MIeGdlifpa6Br44WMntE+61tyscH08UXU71lS6sZkz3t+omDaLBpPj6Q2+55/4BAlIcHFictaAAzYu0THXbm9t56bkIIIYQ7JEHrh2qOHAHA18UWtLNVZwnzC8PPy3F3aGVxIQGh4Xh4dLxkx2eH87HUNXJ9yiCHZcypl1Cfk0NdZqZLMXaH0bGBDI8K4MP0nHbPKw8PzC0Wq3VkVNgognyCpJtTCCFEvyUJWj9Uk5EBSuE3YoRL5fOq8zpeA82NJTbeS8shLtiv3QkCTQJSUwF6tZtTKcWNkwexK7OUY/ntT1AwhYR2mKB5engyPXY623K39WoLoBBCCOEqSdD6odojR/BJSMDDbHapvEuL1BYXEuBCglZUVcvmY0VcP2kQHh6ON2j3SUjAOyGB6l5cDw3glqkJ+Hp58PLX7W/95EoLGtjHoeVV53Gm8kx3hyiEEEJ0mSRo/VDNkW/wHT3apbJaa5cWqa0qLnapBW3dvrM02jQ3TnLcvdkkIPUSqnfuxFbX/qD9nhBm9mHh5Hje3ZtDcVVtm/MmY8P0jlwcezEA289KN6cQQoj+RxK0fqaxspL6rCyXZ3BW1FVgbbA6XaTWWllBQ30dQS4kaO+ln2VMbBAjogM7LGtOTUVbrRT+5aleTdLuTE2irsHG2h1tW7/MRoKmbc737RwcOJg4c5yMQxNCCNEvSYLWz9R+8w2AyzM4z1bZ1wVzvsRG0xpozpfYOFlYxb6sMpdazwACZs8meNFNlLzyCqcWLsS6f79L13XVsKhALhsZyZptp6ltaL1puzkkFFtjI9Yq54voKqW4OO5iduTtoNHWOxu/CyGEEK6SBK2fqclomsHpWhdn0xIbThO04qY10Jy3oL2ffhal4LoUx61xLSkvL+JWrmTwiy9gq6om85ZbKXv/fZeu7ao7U5Mpqqrlw3MWrjUF2xerdbabQJMZcTOorKuUbZ+EEEL0O5Kg9TM1RzLwDA3FK8q1BWVdWgPNhW2etNa8n5bDzKHhRAd1vHtBSwGzZjHkow8xXXQRef/9R+rO9PzA+9RhEYyMDuSlLadazcRs3o/ThXFol8ZfisnLxMenPu6xOIUQQojOkAStn6nNOILf6FEo5XgGZUt51Xn4evoS5ud4SYzq0hKUhwemoGCHZbafLOFMiYWFk+LdjhnAMzCQuCceR3l6cvb+B9CNPdttqJTiztRkjuRV8nlGQfPxpgTNlRY0fy9/5iXO47PMz6htbDvhQAghhOgrkqD1I7q+ntrjx13u3gT7GLRYc6zThK7WYsHX34TycPxx/3PXGQL9vLh6vPPlOpzxjo0l5ve/w5qWRvFLLwNg3b+fM8vv5Mydd3V70nbj5EEMiTTzp39nUN9onxTQ1MXpylIbANcMuYbK+ko2ZW/q1tiEEEKIrpAErR+pPXUKXVfn8gQBsLegOeveBKivseLt33ZPzSbllnr+fTCPG1IG4e/T8U4DzgQtWEDgFVdQ+OyzZP3wbjK/uxjrvn1Uf/01ZW+/06W6z+Xt6cGvrxrNyaJq1m4/DYCvyYynt7dLXZwA02OmE+EfwboT67o1NiGEEKIrJEHrR2qNLZ5cXWIDXFuktq7Gio+f4wTt/fQc6hpsLJ462OX7OqKUIubhh/AKCcGyezcRP7mXYV99hWnaNAqfeoqGUtdatlw1d3QUM4eG8/SGY5Rb61FK2ZfacLEFzdPDk6uTr2ZTzibKa8u7NTYhhBCisyRB60dqMo6gfHzwSU52qXx9Yz1F1qKOEzSr4wRNa80bO88wblAQ4wY5HqPmDq/QUJI/eJ9hX2wg8p578AwwE/3b39BYVUXh0093yz2aKKX4zTWjKbPW879fHgfAHBzqcgsawIIhC2iwNfBp5qfdGpsQQgjRWZKg9SM1RzLwHT4c5eXlUvmtZ7ei0YwIdb5nZ31NDd5+7c/MPJBTzpG8ShZPTXA7Xme8wsLwDP424fMbMYLQ25ZQ9s+3sB461K33GhsXzKLJ8bzydSZnii2YQlzb7qnJqLBRDA0eyscnZTanEEKI/kEStH6k9ugxfEeOdLn82oy1RJmimD14ttNy9TVWvB20oL25Kws/bw+um+ja2mddEXnvvXiGhpL/x5XdPmHgl1fYf2//2HLS3oLmRoKmlOKaIdewt2AvWZVZ3RqXEEII0RmSoPUTDaWlNBYX4zt0qEvlT5SdYFvuNm4ZeQveHt5Oy9bVWPFpZ5KAta6RD9PPcvX4WIL9ndfRHTyDgoh+4H6s6ekUPPFEt9YdHeTHgomxvLsnG6+AIKyVFdjcSAKvHXotfp5+/GHrH2RnASGEEH1OErR+ou7kSQB8h7mWoL1x5A18PHy4acRNHdddU4NPO12caWdKqapt4NoJPd961iT4uusIu/37lLy6htI33+zWupfNTKK6rpEj5YDWWCpcH/QfY47h19N/zY68Hbxw4IVujUsIIYRwV5cSNKVUiFLqHaXUEaVUhlJqhlIqTCn1mVLqmPEz1CirlFLPKKWOK6X2K6Umd89bOD/UHj8BgM/QYR2Wrair4MMTH3L1kKudLlDbpN7afhfnvmx7ApMyOMTNaLsm6r77CLj0UvL+uJKqr7/utnonxIcwOSGEr7JqANfXQmtyw7AbWDBkAX/f93d25e3qtriEEEIId3W1Be1p4BOt9ShgIpABPABs0FoPBzYYrwGuAoYbjxXA37p47/NK7YnjKH9/vOM6Xij2vWPvYW2wsmTUkg7L2hobaaiva3cW576sMhLDTYSafToVc2cpT0/innwS36FDyfmvn1P65j+x1dV1S923z0wi02Jfy83VpTaa41KK3138OxICE7hv030UWgq7JSYhhBDCXZ1O0JRSQcBs4CUArXWd1roMuB541Sj2KnCD8fx6YI222w6EKKU6v2z9eabuxEl8hwxxuto/QKOtkTeOvMHkqMmMDu94x4G6GitAu2PQ9meXMSG+d1vPmngGmBn897/hMySZvIcf5sS8+ZS8+mqXE7WrxsXiF2TsJuDGUhtNTN4mVl26isq6ShZ+uJB/HvknDbaGLsUkhBBCuKsrLWhDgEJgtVIqTSn1D6WUGYjWWucCGD+jjPKDgJZT5LKNY60opVYopXYrpXYXFl44LRi1J07gM3RIh+V25e8ipyqHW0ff6lK99TX27r5zl9koqKzhbHkNE+O7Z+2zzvCOiyPpzTdJePklfJKSyP/TY5z91X1om63Tdfp4eXD9DPuyI1k5+Z2qY2TYSF6/5nWGhw5n5Y6VfHfddzlU3L1LgwghhBDOdCVB8wImA3/TWk8Cqvm2O7M97W0Wqdsc0PoFrfUUrfWUyMjILoQ3cDRWVdGQl4evC+PP0grSUChS41JdqrvOarSgndPFuT/LPv5sYi+PPzuXUgrzzJkkrnmVqF/9kspPP6Xor13r/b4tdTi1Hr58seMQZ8usnapjROgIXvrOSzx12VOU1ZTx8NaHuxSTEEII4Y6uJGjZQLbWeofx+h3sCVt+U9el8bOgRfmWewnFA2e7cP/zhjszOA8UHmBI8BACfAJcqrve6OI8d5LAvuwyPD0UY+OC3Iy254QtX07wDTdQ9NxzVHzySafriQr0I3L0REILv2HB/2xkQ0bnWtKUUsxLnMeyscs4UnKEzPLMTsckhBBCuKPTCZrWOg/IUko1raw6FzgMfAjcbhy7HfjAeP4h8H1jNufFQHlTV+iFrmkGZ0droGmtOVh0kPGR412uu87o4jx3mY30rDKGRwVg8nFt14LeoJQi5r//gP+kSZx94MEu7Tgw55or8bXVMlbnceeru3n682OdruuKpCtQKD7J7HzSKIQQQrijq7M4fwKsVUrtB1KAR4HHgPlKqWPAfOM1wL+Bk8Bx4EXgx12893mj9sRxlLc33vHxTstlV2VTWlvK+Ah3ErSmSQKm5mNaa/Znl/f68hqu8PDxIf65Z/EMDKRg1apO15M0cRJ+AYHcHFrIwsmDeOrzo6zdcbpTdUWbo5kUNUn26hRCCNFrupSgaa3TjfFiE7TWN2itS7XWxVrruVrr4cbPEqOs1lrfo7UeqrUer7Xe3T1vYeCrO34Cn+TkDvfgPFB4AMCtBO3bLs5vW9BOF1sot9b3+fgzR7zCwwlZvBjL9h3Un+1cL7inlzcjpl/Cqb07eOSaEVw+MpLff3CIjd8UdHxxO65MvpLjZcc5Vtr5ljghhBDCVbKTQD9Qe/Kka+PPig7g5+nH8NDhLtfd3iSBfdn25Scm9OEMzo4E33ADaE35Bx90XNiBUamX0lBbS2b6Lp5bMpmR0YHcs3Yvh89WuF3X/MT5eCgP6eYUQgjRKyRB62M2q5X67Gx8XNiD80DRAcaEj8HLw/VxY+1NEtiXVY6ftwcjogPdD7iX+MQPwjR9OmXvvY/WbSb7uiR+1FgCwsI58vVXmH29eHnZVAL9vLl99U4O5ri+DRRAhH8EU2Om8mnmp52ORwghhHCVJGh9rO7UKdC6wwkC9Y31ZBRnuNW9Cd+OQfP2820+tj+7jLFxwXh79u+PP2ThjdSfbX+BDAAAIABJREFUOYN1z55OXa88PBg5czaZ6XuxVlUSE+zHa3dOw9tDsfj5bXzpoLtzd2YJv3grnS+PtD5/ZdKVnK44TUZJRqfiEUIIIVzVv/9CXwBqT7g2g/No6VHqbHVuzeAE+yxOL19fPDzs2x81NNo4eLaciX20g4A7AufPx8Nspuy99zpdx+hLLsXW2MCxHfY9P4dHB/LePZeQFGHmrld388KmE2w5VsSWY0V8kJ7Dwr9+zaK/b+O9tBx++NoeNh39drHkeQnz8FJe0s0phBCix0mC1sdqT5wAT098EhOdlttftB+ACRET3Kq/3mptNf7saH4VNfU2Jg7uv+PPmniYTARedSWV6z/BZrF0qo6o5KGExg7i6PZvN2WPDvLjrR/OYPbwCB799xG+99IOvvfSDn72ZjqFVbX84bqxbH1gDkOjAljx2m52nioBIMQvhIvjLuajEx9RUef+ODYhhBDCVf1nEawLVN2JE/gkJqJ8nG9YfrDoIOF+4cSYY9yrv6Z1grb1RBEAkxNC3Q+2D4TceCPl77xLxX/+Q8gNN3R8wTmUUiSMT+Hwpi+w2RqbWxLNvl784/apHMgpp77RvrWUl4di/KBgvIyu39funMZ3n9/G8ld28bO5w6lrtGGqvppi61ae2PkEK1NXdt8bFUIIIVqQFrQ+Vnv8RIfdmwD7C/czPnI8SrW3Y5ZjdTXWVktsrD+Yx+jYIAaHmZxc1X/4T56Md2ICJa+82ulWtLgRo6ivsVKcdabVcU8PRcrgEKYmhTE1KYxJCaHNyRn8f/buOyyKq3vg+He2wLL0Lk0QBUHB3ntsMWo0+pqqqab3njc9McW0X3re9ETTNMUSY4uxxwb2CtKUogjSpWyf3x+LGiJ1Yan38zw8gZm5M2c1TziZe+854OPiyE+3D8HbxYHXVifw9p/HWR6nRJ83mt9Tf2dTxqZGfTZBEARBqIlI0FqQbDBgyMios0l6sb6YkyUnGzy9CdZm6Q5O1jdoZ4p17E0vZHJMw97CtSRJkvB/8kn0SUlk3ncfFr2+wfcIjIgC4HRSYoPHdnLX8Ncjo9n97HgSX5nEgRcm4FIxGQdzEC/vfJlCXWGD7ykIgiAIdREJWgsyZGaC2VznG7SjedaWRw3dIADWMhvnS2z8efQMAFfEtp0EDcB13DgCXn+N8p27OPXQw8hGY4PGu/t3wsnNndNJtu2+dFAp8HV1RKNW4qpR8+zkGArT/0OhrphXd4lpTkEQBKHpiQStBekrm6Q7dKn9DdqR/CMA9PTu2eBnGP6xSWDNkWwi/Fzo5td665/VxOOqq+j04guUbt7M6WeebdBYSZIIjIwiO7nhb9CqM6NvEP0DekLReNalr+NA7oEmua8gCIIgnCcStBZkSDsBgENYWK3XJRUmEewSjKtDwxMrg16HWqMhr1RP/IkCrmhD05v/5nn99XjfPpeSP/7AmNOwlk0BEVEUZp+mvKRhBWqrI0kSL0+L4VzOMNS48Hbcp2xJOkv8iQJRxFYQBEFoEiJBa0GGtDRU/v4oXZxrvS65MJlIz0ibnmGsqMDByYl1R3OwyHBFbIBN92ktXC+/HICKfQ0rXhsYaV2Hlp18vEni6BHoxk1DIik9O4RDBTu49ccVXPP5Tj7emNIk9xcEQRA6NpGgtSD9yRM4hHep/RqznpMlJxvUf/M8WZYvlNlYcySbMG8tUZ3a3vTmP2miopCcnCjfu69B4zqFRyApFE02zQnwwtQefHrlAzgqNIwfeoypvQJ4b33ShVImgiAIgmArkaC1EFmWMaSdwLGO9WepRalYZItNb9BMRgOyxYJJ4cCO1HyuiA1ocJmO1kZSq3Hq3ZvyBr5BU2s0+IZ2sWknZ00UColx3cO5Jupq4nM38NDl3oT5OFsL3p5r+G5TQRAEQThPJGgtxJyXh+XcORy61P4GLakwCcCmBM2o0wGQWmTEbJHb9Pqzf9L2748+8Tjm0tIGjQuMjOJMShIWs7lJ47mpx01IksTPyd/zv9n9OKcz8tDi/ZgtYj2aIAiCYBuRoLUQ/fkNAnVMcSYXJqNRaghxDWnwMwwV1kbpCWd1BLpriA1q/e2d6kPbvx9YLFTsb9juycCIKIx6HXmZ6U0aTyfnTkzrOo3lKcvxdtMzb1oMO1LzeeK3gxhMliZ9liAIgtAxiASthRhOWEtsOIbXPsWZVJhEV4+uKCtbFDWEUWdN0I7l6RkX7d/mpzfP0/TqDUplg6c5AyKjAdsK1tZlbsxcZFlm3s55zOofxCPjI1m67xRzvo6joMzQ5M8TBEEQ2jeRoLUQw4kTSFotKn//Wq9LKkyyeQenoXKKs9SsZGy0n033aI2ULs5ooqKoaOBGAXc/f7TuHmTbWLC2Np3dOvNw/4fZnLWZpSlLeWh8BB9c14cDmUXM+N920s42bDpWEARB6NhEgtZC9GkncAgLRVLU/FeQV5FHga7Aph2cAMYKa+9KyUHD0HBvm+7RWmkH9Kfi0CFkQ/3fTkmSREBElF3eoAHMjp7N4IDBvLX7LTJKMpjeJ4hFdwyhVGfi3h/3YTKL6U5BEAShfkSC1kIMaWl17uBMLkwGbNsgAKCvnOKMCfVFo274FGlr5tSvP7JOh+7YsQaN69wzlqKcbArPnG7ymBSSgleHv4pKoeKZbc9gspjoH+rJq1fFkHjmHIviM+q+iSAIgiAgErQWYdHpMJ4+XecGgfM7OG19g5aZUwTAkKhAm8a3Ztp+fQEaXA8tvP9gANL2xjd5TGDdMPDc4Oc4ePYgy1OWAzApphPDunrzzroksR5NEARBqBeRoLUAQ3o6yHK9Ngj4OPngpfGy6TnHMs4CMDI6yKbxrZnK1xd1aGfK9zUsQfPw74RPSCipdkrQACaHTybYJZgtWVsA69TqS9N6Uqo38X/rmqaTgSAIgtC+iQStBRguNEmvu8SGrdObACmn8gEI9vO0+R6tmbb/ACr27m1w/8uuAwaTlXAEXQPrqDXE0MCh7D6zG6PFCECkvys3DQ3lp/gMjpxqfD9QQRAEoX0TCVoL0KelgSThEBpa4zUmi4nUolSbE7SCMgNnC0tAUqBUq20NtVXT9u+HuaiowevQwvsNQrZYOHFgj50igyEBQygzlnEk78iFYw+Pj8RT68CjvxzgZF6Z3Z4tCIIgtH0iQWsBhrQTqAMDUTg51XhNRkkGBovB5gRtS1IuaosRlaOm3dQ/+zfX8eNRaLUULFjYoHEB3SLRunvYdZpzcMBgJCR2nd514Zi7k5oPrutDTomeqR9t4/cDp+z2fEEQBKFtEwlaC9CfSMOhHuvPwPYNApuPn8VVaUaj1do0vi1Qurvjce21lKxejSErq97jJIWC8H6DOHlgL2aT0S6xuTu609O7Jzuzd1Y5PjLCl9UPjSSqkysPLT7AM8sON3iKVhAEQWj/RILWzGSLBcOJkzjWYwenUlIS7l57Ilfj+JxSfBzBQaOxaXxb4XXLzaBQUPDNtw0a13XAYPTlZWQlHLVTZDAkcAiHzh6i1FB1rVuQhxOL7xzCbcO78FNcBhsScu0WgyAIgtA2iQStmZlycpArKurVJD3MLQwHpUODnyHLMpkF5WglEw61TKO2B2p/f9ynT6NoyRJM+fn1Hhca2xuV2sFu5TYAhgYMxSyb2ZNz6Vo3lVLB05Oj6OLjzFt/JorG6oIgCEIVIkFrZvrU8zs4a38zdrzwON29utv0jMJyI6V6ExpMqDXtO0ED8L5tLrLBQMH339d7jNpRQ+fY3qTujbPbFGMfvz5olBp2nt5Z7Xm1UsFjEyNJyill2X6xHk0QBEG4SCRozUyfbO0O4BjRrcZrivXFnCk7Y3OCllFgbfGkshjb/Rs0AMfwLriOH0/hT4swN6B0RreBQynOzSHz6CG7xOWgdKC/f392Ze+q8ZrJMQHEBrnz3l9J6Ixmu8QhCIIgtD0iQWtm+uRklD4+qLxqLj57vMBazDTKM8qmZ5xP0BRmA2rH9r0G7TzvO27HUlJC8bLl9R4TPWIMrt6+bP1xgd3eog0NHEpacRpnys5Ue16hkHhqUhSniir4YVe6XWIQBEEQ2h6RoDUzfUoKjt1qfnsG1ulNgEgv20psZFYmaLJB1yHeoAE49eqFpkcPipYtrfcYlYMDw6+dQ05aMkm7ttklriEBQwBqfYs2IsKHEd18+GRTCtnFFXaJQxAEQWhbRILWjGSLxZqgRdReOiOxIBEfJx98nHxsek5Gfjl+ro4Y9boOsQbtPPeZM9EfS0CXkFDvMdEjx+DTOYxti76zS8mNCM8I/Jz8eCv+Ld7Z/Q6nSqtfa/bM5GgMJgtTP9zGjtS8Jo9DEARBaFtEgtaMjKezkcvLa11/BtYdnN09bVt/BpBeUEZnTw0mvb7dl9n4J/epU5DUaoqWLqv3GIVCycgbbqYoJ5tD69c2eUwKScGnEz5leNBwfkj4gclLJ/PSjpcwWUxVrusR6Mbv94/AQ6tmzldxfLE1VdRHEwRB6MBEgtaM9MnW4rOO3Wp+g2Y0G0kpSrF5ehMgs6CCUDcVAA4d6A2a0sMDl/HjKPnjDywGQ73HdekzgJAesexcshh9eXmTxxXpGcnbo99m7X/WckPUDSxJXsJz25/DbKm6KaCbnwu/3z+Cy3t24vXVifwYl9HksQiCIAhtg0jQmpE+OQWofQdnWnEaJovJ5g0CBpOF08UVBLlY/2o70hQngMfMmZiLiijduKneYyRJYtTsW6k4V8KmBZ/bLbZOzp14atBTPNTvIValreLFHS9ikS1VrnFxVPG/2f3oH+rJp5tTMZotNdxNEARBaM9EgtaM9CnJqAICULq61njN+RZPtpbYOFVUgSxDoNb6V9tRNgmc5zxsGCp//wZtFgDo1C2SITOv5eiWDRzZ9JedorO6PfZ27u19L7+n/s6ru169ZCpTkiTuv6wbp4oqWC7qowmCIHRIIkFrRvrkundwJhYk4qh0JNQt1KZnnC+x4ae1NkjvaG/QJKUS96uuouzvbRhzGtZCaeis6wnp2YsN33xGXsZJ+wRY6e7ed3NbzG38mvQrS5KXXHJ+THdfegS48enmVNFlQBAEoQMSCVozkc1mDKmpde7gPF54nG4e3VApVDY953yC5u1o/aXekdagnecxcwZYLBQvq/9mAbBuGJjy4BM4ODnxx3tvYNDZr+SFJEk81O8hhgUO4434Ny68Of3n+fsu60ZaXhlrjmTbLQ5BEAShdRIJWjMxZGQgGwy1JmiyLHO8wPYWT2CtgeaoUuAsWRegd6RdnOc5hIaiHTKEwkWLkI0NK53h7OHJlAefoDD7NDt++cFOEVopJAWvjXgNVwdXntjyBOXGqhsUJsV0ItzXmU82iR2dgiAIHY1I0JrJhRZPtUxx5pbnUqQvalSJjYz8ckK8tBj1OgDUHWwN2nlet9yMKSeHkj/XNXhs55je9Bh1GQfXraG0sMAO0V3k4+TD/JHzOVF8gvnx86ucUyok7hndlYTsEjYmNmy6VhAEQWjbRILWTPQpKSBJOHatuUn6+Q4CjXmDllFQTmcvLcbK6bmOOMUJ4DJqFA5dulCwwLY2TkNmXofZbCL+91/tEN2/nhUwhDt63cHylOXsPrO7yrmr+gbR2UvLvJXHKDeYariDIAiC0N6IBK2Z6JOTUYeEoNBqa7zmfA/OSE/baqDJsnwhQTNUWBM0dQec4gSQFAq8broR3ZEjVOzb1+DxHp0C6Dl6HIfWr+Vcgf0r+98eeztuDm78fPznKsfVSgVvzepFRkE581cn2j0OQRAEoXUQCVoz0Scn16sHZ5BLEK4ONZfhqE1huZFSvanyDZp1irOjvkEDcJ8+HaW7OwULFto0fsjMa5EtFuKX2/8tmpPKiau6XcWG9A2cLT9bNY5wb24b3oXvd6WzNelsDXcQBEEQ2hORoDUD2WDAcDK97h2cBccbt/6scgdnZy8tBl0FKrUDCqXS5vu1dQqtFo9rr+Xc+vUYMjMbPN7drxM9x4zn8IY/Kcmzf2J0bfdrMckmfkv+7ZJzT1zenW5+Ljz52yGKy5u+Z6ggCILQujQ6QZMkSSlJ0n5JklZW/txFkqQ4SZKSJUn6WZIkh8rjjpU/p1SeD2vss9sK/cmTYDLVmqDpTDoyzmUQ4Vl7ElebCwmat3UNWkfdIPBPnrNng0pl+1u0Gdciy7Dzt5+aOLJLdXbrzPDA4fx2/DeMlqpJmEat5N1renO2VM+8lcfsHosgCILQspriDdpDQMI/fn4TeE+W5QigEJhbeXwuUCjLcjfgvcrrOoQLOzhrafF0ovgEFtnSqAQtszJBC/G0rkHriCU2/k3t74fHjBkULl5MxaFDDR7v5utH/ynTObLpL1L3xtkhwqqu7X4tuRW5bMnccsm5XsEe3DEynCX7sjhyqtjusQiCIAgtp1EJmiRJwcAU4KvKnyVgLHB+jmYhcFXl99Mrf6by/LjK69s9Q3o6AA5hYTVek1Jk7dMZ4dGIN2j55fi6OuLkoERfXtah15/9k98Tj6Py8+P0f5/GUrk2ryGGXTMH37Bw/vzsQ8qKCu0Q4UWjgkcR4BzA4uOLqz1/72Vd8dSqmb8mQdRGEwRBaMca+wbtfeBJ4HxHZ2+gSJbl8/UAsoCgyu+DgEyAyvPFlddXIUnSnZIk7ZEkac/Zs+1jQbQx6xQqPz8Ujo41XpNcmIxaoSbELcTm55zfwZl++AAn9u8lIMK2huvtjdLVlcDXXsWQlsbZ9z9o8HiVWs2UB57AWFHB2k/ft2tipFQouTryauKy40grSrvkvJtGzQNjI9ieks/WZPvvLhUEQRBahs0JmiRJU4FcWZb3/vNwNZfK9Th38YAsfyHL8gBZlgf4+vraGl6rYszMRB1Se+KVXJRMuHs4aoXa5uek55fRRWNg1Qdv4RUUzOib5tY9qINwHjYMzxuup2DhQsp37657wL94B4cw6sbbOHlgL/vXrrRDhBfNiJiBVqXl+e3PYzAbLjk/e0hnQryceGNNoujTKQiC0E415g3acGCaJEkngcVYpzbfBzwkSTrfSDIYOF35fRYQAlB53h2wb5n2VsKQlYVDcHCt16QUpdDNs/YyHLU5e07PmaIygvb9itlkZNpjz4gpzn/xe+wx1CEhZL/wok3j+0ycQljvfmz/+XuMBn0TR3eRj5MPrwx/hUN5h3hr91uXnHdUKXni8igSsktYvv+U3eIQBEEQWo7NCZosy0/Lshwsy3IYcB2wUZbl2cAmYFblZTcDv1d+v6LyZyrPb5Q7wCIa2WDAdOYM6loStBJDCWfKztDNw/YEbV9GISPzd2DJTWfSvY/gFVh7QtgRKZyd8ZozB8OJExhzcho8XpIkBlw5E0NFOWl74+0Q4UUTwyZya89b+fn4z6xIXXHJ+amxAfQKdueddccprhBlNwRBENobe9RBewp4VJKkFKxrzL6uPP414F15/FHgv3Z4dqtjPH0aZBl1SM0JU2pRKmB7BwGAfSmn6XnuGD3HTSJi0DCb79PeaWJjANAdPmzT+JCesbh4eXNs68amDKtaD/Z7kIGdBjJv57wLXSbOUygk5k2P4ew5Pc8sPSw2DAiCILQzTZKgybK8WZblqZXfp8myPEiW5W6yLF8ty7K+8riu8udulecvXQHdDhkyswBqneJMLrSW4WjMG7T0g/tRYiF21Fib79ERaKKjQaWi4vARm8YrFEqiR4zhxIG9lBcXNXF0VakUKt4e9TbOamc+3v/xJef7hHjw6MRIVh3O5pc9DS/EKwiCILReopOAnRlPWRO02jYJJBcm46x2JsA5wLZnmC2QcQzZUUtApO2dCDoChUaDY2SEzW/QAHqMvAzZYiFx+6W1ypqat5M307tOZ9upbRTqLi3xcfeorozo5sNLK46RknvO7vEIgiAIzUMkaHZmyMxEcnBAVcuO1JSiFLp5dMPWsnDHThURXJaOe2QvFIqO29qpvpxiYqk4csTmaUGfzmH4hXXl2N+bmjiy6k0Jn4JJNrH25NpLzikUEu9e0xsnByX3/7Qfg8lSzR0EQRCEtkYkaHZmzDqFOigISVH9H7UsyxcSNFvFx+3HyaIjdshQm+/RkWhiY7CUlGCsLCBcHUtFRa0JXI9RY8lJSyE/K8MeIVbR3as7kZ6RrEytWt5jVdoqntjyBF4uKubPjCXxzDmWHxC7OgVBENoDkaDZmbUGWs3rz/Iq8ijSFzWuxdPBPVhQ0HfYEJvv0ZE4xcYCVFmHJssyxStWcPqp/5J6xWSO9+1H/mef1XiPqOGjkBSKZtksADA1fCqH8g6RXmJNKnPKcpi3cx5rT65lafJSJvbwJzrAjc+3pGIRtdEEQRDaPJGg2VldNdCSi6wbBBrT4knKPIbOJxRHrbPN9+hIHLt1Q9Jo0B25uA6tdONGTj/5FKXbtuHQpQuamBjyv/kW87nq13U5e3gS1qsvx7ZtxmIx2z3myV0mIyGxMs36Fu2dPe9gls109+zO/w78j3JTOXePDif1bBkbEnPtHo8gCIJgXyJBsyNzcTGWkhLUwTVvEEgptPbgtLVIbWpaOm66fDy797FpfEckqVRooqOpOHQxQSv8aRGqTp2I2LKZkP99QsC8l7GcO0fhjz/VeJ+YsRMpzc8jOW6H3WP2d/ZncMBgVqauZMepHaw9uZbbY2/nhaEvkK/L59sj3zIlNoBgTyc+25Jq93gEQRAE+xIJmh0Zsip3cAYH1XhNclEyXhovvDReNj1j15btAPQeJtafNYQmNgZdQgKyyYQhPZ2y7dvxuHoWksraBEPTowfOo0ZSsHAhlvLyau/RbeAQvAKD2bX0Z2SL/RfnTw2fSlZpFk/+/SShbqHcGnMrvXx7MSlsEt8d+44CfR53jAxnb3ohu092iCYdgiAI7ZZI0OzIeL4GWi0lNlIKUxq1/uz0oT0Uqj0Y2FuU12gIp9hYZJ0OfUoKhT//AkolHrOurnKNz913Yy4spOjXX6u9h0KhZPDMa8nLOEnqvob392yo8aHj0Sg1FOuLeWbQMzgqHQFrQVujxcgnBz7h6gHBeGrVfC7eogmCILRpIkGzows10GpYg2aRLaQWp9q8/sxQUQ7ZqZT5R6JRi/IaDXF+o0D5nr0UL12K67hxqP39qlyj7dcP7aBB5H/9DRbDpU3LAaKGjcLdvxNxSxfbvZq/s9qZW2Nu5cYeNzIs6GK3iBDXEG6IuoFlyct4Je55pg9Usz4hl+NnRF00QRCEtkokaHZkyMxE6e6O0tW12vOnzp2iwlRhc4mN5L17UMhmvKP7NSbMDkkdGorCzY28zz/DXFSE5/XXVXudz913YcrNpXjJkmrPK5RKBk2/mjOpyaQf2m/PkAG4t8+9PDnwyUuO39/3fm7ueTMbMjawLPdhXIN/Zv6fe+0ejyAIgmAfIkGzI2NmVu0dBM7v4LRxijNu02bKFU4MGtLfpvEdmSRJOMX0xHw2D4ewMLRDqi9Roh06FKcB/cl58y3K4qtvkN5z9FhcvH3YtfRne4ZcKyeVE48NeIw1M9dwc8zNKFwPE3fuE3al5rVYTIIgCILtRIJmR8asrBqnN8HaQQCgq0fXBt/bZDCQn3iATLdwRkf51T1AuIQmxjrN6XHdtTV2cZAkieAPPkAdFETW3fdQvv/St2RKlZpB0/7DqcSjnEo8ZteY6+Lt5M2j/R/lkf6PoXJN5L8bPq0y9VqmN6Ez2r8siCAIgtA4IkGzE9lsxnD6NA61FKlNLkwmyCUIZ3XD65elHNiHwmTAN2YAjiqx/swWrpdPRDt4MB4zZtR6ncrbm87ffIPSx4fMO++i4ujRS66JuWwCjlpnDqxbZa9wG+TmnrOJcBlEnnoJX8ZtA2Dd0TOMeHMjUz78m7Pn9C0coSAIglAbkaDZiSknB4zG2mugFaXYvEFg+/pN6CUHJowbYWuIHZ5Tz56ELlyA0t29zmvV/n6ELvgWpasrmXfcifFU1ZZKakcNPUaPJTluO+UlxfYKud4kSeKLK95GiQufHH2JJ5fu5s7v9+LvpuFUUQU3fh1HUXn1Gx8EQRCElicSNDupqwaa0WzkZPFJmwrUWsxm8o/t47RbF0Z0929UnEL9qQMDCfnqK2SDgcz7H8BSUVHlfO/xkzGbTBzZ9FcLRViVj9aLe3s+j1l5lhWZn3HX6HBW3D+CL28aQFpeGTd+HU+JztjSYQqCIAjVEAmandRVA+1EyQlMssmmHZzJhw6iNFbgFzsQlVL8FTYnx/AuBP3fO+gTE8l+9tkq67u8g0MI7hHDofVryHr8CSoOHWrBSK3uHDiRwV4zUXvEMzQmBweVgpERvnw6ux8J2SXcsXCP6N0pCILQConf7nZiyMoEhQJ1QEC158+3eLJlB+ff6zZilFRMmDi6UTEKtnEZPRrfRx+hZPUa8r/8qsq53hMmU5ybQ9qWDZSsavn1aJIk8emUZ+ju2Z0Xd7xIfkU+AOOi/XltRgxxJwr4dW9mC0cpCIIg/JtI0OxEfzwJdUgwklpd7fmUohRUkooubl0adF/ZYiHv6F5y3cIYHNGpKUIVbOB9++24TZ7M2ffeo3zfxZ2dXXv3w8FsIcPbDV3i8RaM8CIHpQPzR86n1FDKSztfuvDW75oBIQwM8+SNNYliPZogCEIrIxI0O5AtFsr37kU7cGCN1yQXJhPqFopaWX0CV+O4o0dR68/hGzsAhaL60hCC/UmSRKd581AHBJD99NMX1qOdW7qckLxictxcKExOsnt3gfqK8IzgoX4PsTlzM78mWVtXSZLEvOkxlOhMvP1n60gmBUEQBCuRoNmB/vhxLMXFOA8aVOM1yUXJNk1vbl69DpOkZOLlYxsTotAElC7OBLz+Gob0dM6+/wEWnY68Lz4nMjgMSZJIcFFjzM5u6TAvmNNjDsMCh/Fa3GssS14GQHSAGzcNDeWn+AwOZ126+9RoNnL7utt5ZecrnCk709whC4IgdFgiQbOD8sqK8zW9QSs3lnOq9FSDNwiYTSb1kK+YAAAgAElEQVSKjsST7RZOv4jq17YJzct5yBA8rr+Ogu++I/u55zGfzSP0wYcYMOIyTnu6sn9Jy3UX+DeFpOC9Me8xuNNgXtjxAosSFwHwyIRIvJ0dee73I5dsGDiUd4i47Dh+SfqFyUsn89qu1yjQFbRE+IIgCB2KSNDsoCx+N+qQkBo3CKQWpQI0uMRG6oH9KA1luMcOrrHyvdD8/B9/HHVgICUrV6IdMgTnQYMYdvMd+JaUsWP7RrKTW8/0oVat5aNxHzEmZAyvx73OF4e+wMVRyTOToziYWcTS/VXru+3K3oVCUvDblb8xvdt0fkv6jTfi3mih6AVBEDoOkaA1MdlioXzPHrSDall/VtmDM9IjskH33vHnn+gUjgwfM7JRMQpNS+HsTMD811EFBOD3yMMAqNxcGWBxwEmhZMV781tF8drzHJWOvDvmXSZ3mcxH+z/i3vX3MjzSgd7B7rz9ZyLlBtOFa3ed3kVP75509+rOi0Nf5PIul7M7Z3erWVsnCILQXokErYnVa/1ZYTIapYYg1+qL2FbHoKsg7+he0ly6MbK72L3Z2jgPGkS3jRtw6t37wjG37lEMKKqgoqSYdZ9/2KqSGrVCzRsj3+D5Ic+zN2cvV6+cxZVDCskp0fPZljQASg2lHM47zJCAi43k+/j2Ia8ij9Nlp1sqdEEQhA5BJGhNrK71Z2AtsdHVoysKqf5//Cm7dyGZjThFD8TJQfTebI3+Pe3sGNUd5xOZDJtxLal74kiO39FCkVVPkiSu6X4NP0/9GX9nfz469hxjY2W+2JpKdnEFe3P2YpbNHEz25anfDvHJphSKCgMBOJB7oIWjFwRBaN9ULR1Ae3Nh/VlgYI3XJBcmMzK4YdOUezesp0TpwuCh/RsbotBMNFHRIMv0CO3G8bCubPz2czrH9Ebj7NLSoVUR7hHOZ+M/Y8JvE/AL3oMlYTAvrzhGtmolskXNrmMuaB1yKxusm3Hp7sArf63heHgEV/cPJsRL29IfQRAEod0Rb9CaUH3WnxXoCsjX5TdoB2dZUSG5iYdJcolgfA8xvdlWaKK6A2BMTmbiXQ9QXlTEtkULWziq6nk7eTO5y2Q2Zq3mxmG+rD16hpRz+/F3iGbrExPZ/ex4js27nDUPjSFEG4XZ4QQfbUxmztdxrWrqVhAEob0QCVoT0icl1bn+7NBZa3/GKK+oet83YdtmkC2Yw/sS4O7U2DCFZqIKCEDh7o4uIRH/8G70mzyNg3+tISvxaEuHVq05PeZQYarAP+gQ9473ReGYw5ze4/F2cQRA66AiOsCNKyIGY1Se4sVpEaTnl3M851wLRy4IgtD+iAStCdVn/dn69PW4ql3p59evXvc0m0zsWf07pzWdGNKvZ5PEKTQPSZLQdO+O7ngiAMOumY2brx/L35rH34sWUlqQ38IRVhXlFUV///4sSf6ZyDDrJoB/bhA4r49fH8yymQC/swBsSMitcl5n0rE+fT1H849iNBvtH7ggCEI7JBK0JlQWH1/r+jOjxcimzE2MCRlT7xZPSbu2UZafx173voyL9m/KcIVmoImOQn88CdlsxkHjxMz/vkTnmN7s/n0JX94/l/Vff4pssbR0mBfMiZ7D6bLTfHLgEzwcPeju1f2Sa3r7WneqZpYnEBvkzqbEiwlaXkUec/+cyyObH+G6ldcx+KfBXL/yev7O+rvZPoMgCEJ7IBK0JqQ7dBinvn1qPL/7zG5KDCWMDx1fr/vJsszuFUsoc/KG4Ghig9ybKlShmTh2j0LW6TCkZwDgHdyZaY8+w20ffEGPUWM5uG4ViTtbT/JyWchlBDoHcqbsDIMDBle709jd0Z0u7l04kHuAsVF+7MsopKDMQFJhEjesuoHkomReG/Ea74x+hzk95lBmKuO+Dffx+cHPscitJxkVBEFozUSC1kRM+fmYcnPRRPeo8Zq/0v9Cq9IyLHBYve6Zfmg/Z9NPsNO5F7eP6iqao7dBmmjrWkN9YkKV4x7+nZh45/34hoWzbdFCTAZDS4R3CaVCyQ3RNwDVT2+e19u3NwfPHuSy7r5YZPh231/cuPpGzBYzCyYtYFrXaVwedjmP9n+Un6f+zOTwyXx84GMe2fQIpYbS5vo4giAIbZZI0JqILtG6zuj8L+R/M1vMbMzYyKjgUWhUmnrdc/eKJRgdXcnz68Gs/sFNFqvQfBy6dgWVCl1C4iXnJIWCMTfOpeRsLvvWrGiB6Kp3deTV3NP7HiaFTarxmj6+fSjSF+HmVoSXZx7fp71EoEsgP035iR7eVf8nxUnlxPwR83ly4JNsydrC+/vet/dHEARBaPNEgtZE9JUJmmP3S9fsAOzL3UeBrqDe05s5aSlkHDlInLYnN43ohkYtitO2RQoHB5x69qR08+Zqy1F0julNeL+BxC37pdW0g9Kqtdzb515cHGqu13Z+Hdpf6etQBHyN2eTIR5f9D3/n6tdJSpLEjT1uZHTwaLad2maXuAVBENoTkaA1EV1CIqqAAFSentWeX5++HkelIyOD6legds/KZVhUjqR6xXLj0NCmDFVoZu7/mYk+ORndwYPVnh81+zaMeh07f1vUzJHZLtwjHFe1Kx8f+BhJ0lOWcStZeQ51jhsUMIhTpafIOpfVDFEKgiC0XSJBayK6xAQ0UdVPb1pkC+sz1jM8cDhadd1V18tLikmK284R50hmDumGh7buX3xC6+U2eQqSVkvhL79We947OIRe4yZx8K/V5J5Ma+bobKOQFPT2641KoeLt0e+hNAWwMTG3znHn17XFn4m3d4iCIAhtmkjQmoBFp8OQdqLG9WeH8w6TW57LhLAJ9brfsS0bsJhMHHXrydwRXZoyVKEFKF2ccZ8yhZI1azCfq76o67BrZuPs7sHK99/EUFHezBHa5plBz7Bg0gLGdB7GkHBvVh3K5pfdmWxNOktKbikm86U7NsPdw/Fx8iEuO64FIhYEQWg7RILWBPTJyWCx4FjDG7QtmVtQSSpGB4+u816yLHNow5/kaQPpExsl+hy2Ex7XXI1cUUHJypXVnte6uTPlwScpOpPNX19+0ibaJ4W4hVxYizazXxCniyt4cskhbvomnvHvbqHni38y/ZPtPLf8MGlnrTs3JUliUKdBxJ+JbxOfURAEoaWIZulNQJdgLaGg6VF9iY1tp7bRy7cXrg6udd4r69hhCrNPsd9nLHf3CmjSOO3OYgFJsn7981j2fihMBwcXcHAGz1Bw71i7UjUxMThGR1P4y694XHcdknRpyZTgHjEMu/oGtv/yAyE9e9Fz9DiyEo5w8uA+wnr3IzS25hp7LW1G32AmxwaQW6Inu1hHZkE5CdklHDldzNJ9p1i+/zRvz+rFFbEBDA4YzOoTq0krTqOrR9eWDl0QBKFVEglaE9AnJqJwcUEdFHTJufyKfBIKEnig7wP1utfB9WuRHZxId49gXLRfU4dqH7IMB36Edc+BpISAXtCpF5TmQPJfUJ5X9XqFCuYshfC63yi2F5Ik4XH1LHLmvYLuyFGcYmOqvW7QjKvJTDjCxm8/Y+sP36AvLwNg/9o/mPHUi606SXNUKQnx0hLipWVQF68Lx08XVXDvj/u458d93D6iCzeOtLZC25W9SyRogiAINRBTnE1Al5CIJiqq2rciO7N3AjA8cHid9ykvKSY5bgcpbt0ZERWAq6Z+7aBaVHEW/DgLfr8PfKMgchKUnYWdn0DSn9B1LMz8Eu7ZAbdvgBuXg3c3+OUmyE9t6eiblfuVVyJpNBR8912N7Z0UCiWT73+MwMhoIgYPY/rjz3HHJ9/gGRDE8rdfISvhSDNH3XiBHk78ctdQbh4aylfbTvD15mKCXIKIz65+o8DxguM8u+1ZivWto+yIIAhCSxBv0BpJNpvRHT+Ox3/+U+35Had24OnoSbR3dJ33OrplAxaziXjH7rwQ2wamN5PWwZK5YDHBFW/DwNtBUZnzm40gKUBRTf226xfBl2Nh0fVw+1+g6RgtrJSurnhedx0FCxZgyskh4LVXcQgJueQ6Zw9Prnnh9SrHZj37Cj+//DTL3nyZWc++SkBE9fX2WisHlYKXp8dgMMssjs/kqgkD2Ja9EbPFjPIf/45UmCp4fMvjnCw5SaBLIPf1ua8FoxYEQWg54g1aIxkyMpDLy6stsWGRLew4vYOhgUOr7Wn4T7Isc3jDn5h9wyjV+rT+6c34L2HRteAZZn07NvjOi8kZgFJdfXIG4BUO13wPBanw21wwm5ol5NbA76knCXj1FXTHjpE2bTqFixfXa5yzhydXP/8qTm7u/DLvGRL+3mTnSO3jntFdMcsyRQWhnDOcI7GgaoeFd/e8y8mSk0R4RvDjsR8pMZS0UKSCIAgtSyRojaSvpcXT8YLj5OvyGR5U9/RmdnIihdmn2KeJZHSkb+ud3jQbYe3TsPpxiLgcbl0DXjaUAukyEia/Ayl/weLrQd8x+jNKkoTHrFmE/7ECbf/+nHnpZYp++61eY129fLh+3tt06hrB6o//j43ffo7ZZLRzxE2rs7eWab0D2XbYA7CuQztva9ZWFh9fzE09buL1Ea9zzniOHxN+bKlQBUEQWpRI0BpJl5AIajWO3bpdcm776e0A9WqOfnTzBhRqB/YqQpjSGqc3C0/ChlfgvRjY9T8Yci9c9yM41twOqE4DboWp70HKBvj2CijJbrJwWzt1QAAhn32K8/DhZL88j/I9e+o1ztnDk1nPvUr/KdPZv/YPFr/4VJtbl3bPmK6UV2jxUIWw8OhCnt32LD8l/MQL218gwjOCB/s9SJRXFJeFXMb3x74XzdUFQeiQbE7QJEkKkSRpkyRJCZIkHZUk6aHK416SJP0lSVJy5T89K49LkiR9KElSiiRJhyRJ6tdUH6Il6RITcOzaFcnh0mr/O07voLtnd3ycfGq9h9GgJ3HHVvQhsUgOmtY1vWkywMpH4YM+sO1dCOwDN/wKk+bXPIXZEANugxt+tm4Y+Go8ZB9q/D3bCEmlIui9d3EICiLrgQcxZJ2q1zilSsWYm+5g6sNPcS4/j59f+i9LXn+BtH272f/nSlZ//H/88PQj1XYlaA21xyL9XZnQw5/irEnE+vRm+6ntzI+fT4mhhDdGvoGj0hGAu3rfxTnDORYltp0WWIIgCE2lMW/QTMBjsixHA0OA+yRJ6gH8F9ggy3IEsKHyZ4ArgIjKrzuBTxvx7FZBlmV0CdW3eCo3lrM/dz/Dgup+e5ayexeGinK2S10YFdGKpjfLC+D7GbDnaxh8Fzx82JpMRU5s2udETIDb1oBssSZpexdaS3d0AEo3N4I//R+y2UzWPfdgPFW/JA2g+9CRzP3gC0bNuY0zqckse/NlNn7zGRmHD5CflUH875dOnf7x3nxWffh2iydq947pSklhV3zL7+bjEctZOnUVy6YvI9Iz8sI1Pb17Mjp4NAuPLaTMWNaC0QqCIDQ/m3dxyrKcDWRXfn9OkqQEIAiYDoypvGwhsBl4qvL4d7L1N8MuSZI8JEkKqLxPm6Q7dgzz2Ty0A/pfci7+TDwmi4kRgSPqvM/Rzetx9PDhsNmHO/oE2iPUhss+ZC2FUXLaWiaj1zX2fV5Ab7j7b1hyO/zxIKTvgKnvWgvbtnOOXboQ/MH7ZN57H6mTp+B9xx143z4XhUZT51i1o4aBV86k17hJnD5+DO+Qzrh6+7L5u6848OdKSgvycfHyBiAr4QjJcTsA6NQ1gv5TrrLr56pN386ejI/2Z8GOkyzYcRIAdyc1KkUSkiTh5qTihkGduaXH7dy67kaWpyxndvTsFotXEAShuTVJmQ1JksKAvkAc4H8+6ZJlOVuSpPPzdUFA5j+GZVUeq5KgSZJ0J9Y3bHTu3LkpwrObktWrQa3Gdfz4S85tzNiIk8qJPn61FxY9l59H+uEDlPe4DK1JxfimnN4sPQtHlsChxVBRCBNfg+ipF8/LsnVq0WIElcZaQDZlPRz4CbLiwdkPblkFIQObLqbaOPvAnCWw9R3YPB9ObIUx/4U+s0HZvivCOA8dStfVq8h56y3yPv6Y4mXLcJ8+De2gwTj17YPC0bHW8Y5aLV36Drjwc5/Lp7BvzQoOrl/L8GusiU3c8l9xcnMnoFskW39cQHB0DP7hl66dbC6fzelHUk4pJ/PLOJFXRm6JDrMsY7ZAam4pr65KwMfFAb+u3Vic8Bs3RN1Qba1BQRCE9qjRv/UkSXIBlgAPy7JcUst/QKs7cck8iyzLXwBfAAwYMKDVznPJskzJmjW4DBuG0sOjyrnc8lxWpq1kRrcZOCgvXZv2T8e2bgRZ5k9DMBNi/NE6NFEismEebHsfZLO1qr+DC/w8G2JmwfgXrQvz93wNZw5fOtY3CibMsyZGzrWvn2tyCiWMecraZWDdc9a3aTs+hN7XWRNIACcviL4StF6136uNUQcEEPzee5Rdex1n33+fvM8+h/99iuTggOvEifjcczeOXetXed+zUyBd+vTn0Po1DJl5DXkZ6Zw8sJcR199Mr/GT+P7JB1n5/pvMeeMDHLUt0+9VpVTQI9CNHoFu1Z6PP1HAhxuSiUuPRROwjKHvLmBocF9uH9mFnoEdo3aeIAgdV6OyAUmS1FiTsx9lWV5aeTjn/NSlJEkBQG7l8Szgn1U5g4HTjXl+S6o4cADT6WzcHn74knM/HPsBs2zmlp631HoPWZY5umUDzp0jyDI5M6+ppjeT/4K//w96zoTRT4JftLU8xrb3YMtbcKRybZJ/jLXArLMPmHTWr4DeENivaj/NltB5CMz9C46vho2vWr/+adVj0H0S9L3JuoatpeNtQs5DBuO8eBHmc+co37OHsm3bKVq2jJJVq3C7YhLuM2aiDgpE5eeP0qXmKeC+k65k6fwXSdq5jeT4nThqnekzcQqOWi2TH3ycX156mkXPP47KwZGyogJ0ZaUolSoUKhUaZ2cuu+UuuvS5dPq+uQzq4sUPtw9mX2Zn5m5ahavvPjYdD+KvYzksuHUgA8LaV4IuCILwT5Kti4Ul66uyhUCBLMsP/+P420C+LMtvSJL0X8BLluUnJUmaAtwPTAYGAx/KsjyotmcMGDBA3lPP8gPN7cxrr1P0yy9EbN+G0uViqYlifTETf5vI6JDRvDXqrdrvkZLEj88+Sn7f6awxhBL/7HjUykZWPikvgP8NBSdPuHMzqP+1junMETi2HLpNgJBBbSOxkWVr8nhefgocWASHf7G2lRr2AEx4pW18FhuZCgsp+HYBhT/8gKW8/MJxh7AwAl5/HW2/vpeMkS0Wvn30bmSLTFFONkNmXsvwa2+8cP7Q+rUcXL8GrbsHzh6eaFxckc1mzCYTWQlHKMw+zRX3P0rUsFHN8hlr8+y2Z9mQsYFFl69h7rcHOVOi46ubBzCsazO/4RUEQaiFJEl7ZVkeUPeVdWvMG7ThwI3AYUmSDlQeewZ4A/hFkqS5QAZwdeW51ViTsxSgHLi1Ec9uUbLZTMnaNbiMGlUlOQNYnLiYclM5c2Pm1nmfxB1bUKhUrCrxZcrAgMYnZ2AtIFueB7N/uTQ5A+gUY/1qSyQJ1E4Xf+4UC5NiYcLL1qK5Oz4CQ7m18K2ifZb2U3l64vfoI3jfPhf98eMYz+RgPJNN0c+/kH7jjfg+cD/ed9yBpLxY+kRSKOhz+VQ2LfgClaMjfa+YVuWevcZPotf4SdU+T19exrI357Hqw7fRl5XRe8IVdv18dZkZMZMVqSs4VLiVxXddzpyv4rj12908NjGSCD9Xgjyd6OylRaNugtIvgiAIrUBjdnFuo/p1ZQDjqrleBtpFY73y3Xswn83DbcrkKscrTBX8mPAjI4NG0t2r9l6JFouZxB1/4xQeQ7FRzfTeTTC9eWSJ9euy56xTle2dUg2T37bu9Nz+PhjLYdpH1uPtlNLNDe3Ai5s2PK+7jjMvvczZ9z+gZN06VD4+WMrKkU1G3KdMIXralexcspjYsRPRutV/3Zaj1pn/PPMyK99/k/VffYLGxYXuQ0fa4yPVSz+/foS5hbE0eSnTu01n8Z1DufXbeF5ffbFVlNZByVV9g5gzOLTGdW2CIAhtRft83WBnJWvWIGm1uIweXeX40uSlFOoLmRtb99uzrGNHKSss4LhzNwLcNQxs7HqagjRY+QgE9YcRjzTuXm2JJMH4l2Dsc3BwEXw8APb/2GH6eypdXQl8520C5s8HGcyFRUgqFZgt5Lw+n6yrZjLrsskMn3V9g++tdtQw7bFn8QoMZt+aP+wQff1JksTMiJnsy91HWnEaXs4OLLt3OLueHseSe4bywXV9mBIbwJK9WUz+8G+u/XwnxeVtqw2WIAjCP9m8Bq05tMY1aLLRSPLIUTgPH07Q/71z8bgsc+XyK/Fw9OCHyT/UeZ91n39IwvatfBZ0IzeOjOSZydG2B2Uoh68nQnEG3LnFtt6Y7UHSOtj0KmQftDZkH/YgxF7duHZUbVjZzp3kvv8+uoOHcJ/1HwJffbXuQdWI//03/v5pAbd98AWenVquTl9eRR4TfpsAQIRHBNHe0XR170qwazDBrsF0cu6Exajht31ZvLk2kRHdfPj65oEoFO13baIgCK1La1mD1iGV79uPuagI10mXVzl+JO8I6SXp3DbstjrvYTIaSYrbQZ53BEoHDXNHNCKhkmVY+TDkHIHZv3bc5AysHQ4iJlh3fm550/rnsu55a4mOofdak7YOxHnoUMKGDCH3rbcp+PZb3CZMuOStb31EjxzDtkXfcWzrRoZfM8cOkdaPj5MP317+LZsyN5GQn8CmjE0s1S+tco1SUuLu6E5orBfbTvbivQ3OPDahZwtFLAiCYDuRoDVQ2c4doFTiPHRoleOrT6xGrVAzPvTSorX/dvLgPvRlpWx1CeHh8RH4u9VdMb5G8V/CoZ9hzDPW5KSjkySImgLdJ0PWbtj9FexbaC0tcvPKtrdBopEkScL3kYcp2/Y32c+/QPgfK1C6N6yGmKuXD51je3Ns60aGzboBqQU3YvTx63Oh+LMsy5QYSsg6l0VmaSY5ZTkU64sp0hdxOO8wOQFL+SZ9PUWbrue5UXdc6PEpCILQFog1aA1UtmMnTr16Vdm9abKYWHNiDaODR+PmUPfi5KNbN6FXatCGRXPLsDDbg8nYBX8+DZGTYNQTtt+nPZIkaxmRmV/AffGg1sJ30yA3oaUja3YKBwcC5r+BKT+fnNdft+kePUePo+RsLpnHjjRxdLaTJAl3R3d6+vRkUtgkbu55Mw/2e5AXhr7AL1N/4aMxn+JEAMszPmfG8lkcyD1Q900FQRBaCZGgNYC5uBjdkSM4D6vaAD0+O558XT6TwyfXMPIig66C5D1xHNd25eUZvVHZWlrjXA78cjO4h8CMz9tteYkm4dUFbv4DFGpYOA3ykls6ombnFNMTn7vupPj3FZSs/bPB47sNHIKDkxPHtm6wQ3RNT5IkxoSOYMmMhXDmDrJLSrhpzU3Mj5tPubG87hsIgiC0MPFbvQHK4uLAYsF5WNXpzVUnVuGqdmVUcN0FPbeu+APJbCSg/3AGdbFx56bZCL/eAvoSuPYHcPKoc0iH590Vbl4ByPDtZMiIa+mImp3P3Xej6dGDU488Qs5bb2PR6+s9Vu2oIXLISJJ2bcegq0C2WDiVeIyz6SfsGHHjhXo78+bkqylMeogIp8tZlLiIBzc+iN5c/88uCILQEkSC1gBlO3agcHbGqVevC8d0Jh0bMjYwPnR8nWtcjDodB1YtIdMpmIdvmGh7IOueh4wd1ppfHWxNVaP4drc2f3dwhgVTYM+3LR1Rs5IcHOj83Xd4XH01Bd98w4mZ/6HicP2nLHuOHotRr2PF/73O5/fewuIXn+S3157HYjHbMerGmxwbwJzBEezdN4bZXZ8i7kwcT219CpOlY5RiEQShbRIJWgOU7diJdtAgJPXFQqhbsrZQZiyr1/Tm7tUrkHRlSP0m0cndho0BBWnw660Q9ykMvgdiZzX8Hh2db3e4cxN0GWXd5fnHw2AytHRUzUbp4kzAvJcJ+fJLLKWlnLzhBgq+/4H6lNsJiuqJd3BnTh0/RlBkNH0un0p5cRHZyUnNEHnjPDelB1GdXFm80Ze50Q+zIWMDr+x6pV6fWxAEoSWIBK2eDFlZGDMyLtm9uSptFb5Ovgz0H1jDSCt9eTlxvy/hpFNn/nPFiIY9vCANVj8JHw+CpLUw6kmY+EpDP4JwnpOntSTJiEdg77ewcCqcO9PSUTUrl5EjCF/xOy4jRpDz2mucfuxxLGVltY6RJInZr73LvV/+yJWPPs3wa+egUCpJ3bOrmaK2nUat5JPZ/TCaZd5f2gl/y1SWJi/lhe0vUmas/XMLgiC0BJGg1VPZjh0AOA+/uEHgnOEcf5/6m0ldJqFU1N4DcN+a37HoysjsMophXb3rfmDxKdj4qrXx+Yd9reUi+s6GB/fD2GfbdTujZqFQWjsQzPoWzhyGL8ZA5u4WDqp5Kd3dCf7kY3wfeYSStWs5ed11mIuKah2j1mhQO1rf/mqcXQjuEUvK7tafoAF09XVh42OjeWR8JOeyx6HPG8PylOVctXwGO07taOnwBEEQqhAJWj2V7diJys8Ph/CLxU63ZG3BZDExMbT29WS60lLi/1hGmjaMqWMH1V3Z3FBuLQnx9/+B1hsmvQEPHYQrPwDXTk3xcYTzYmbC3L9A6QDfXgGLZ8PeBdYEuQOQFAp87rqTkC+/QH8ynVNPPolssdR7fLeBQyjMPkX+qUw7Rtl0/Nw0PDQ+gu1PjeW5YY9Rln435yok7lp/F2/Gv9nS4QmCIFwgErR6kM1mynfuxHnYMCTpYnK1Pn09fk5+9PLtVctoOLh+DaaKcvb6DOY//YLrfuD6FyE/BW5cDreshCH3gEdIYz+GUJNOMXDnZhhwq7VN1B8PwXs9YOGVkPQnNCBhaatchg+n0zNPU7b1b/I++6ze47r2HwxA6p62tStWpVRw09AwHh4xgTMJ9xClvZwfEn5gQ3rbKCMiCEL7JxK0etAlJGIuLq4yvZl2mY8AACAASURBVFluLGf7qe2MCx2HQqr5j1GWZQ5t+JNsp0CGDYzF09mh9oelboT4L2DIvRDe8LY8go20XjD5bXj4MNy7y9p8PT8VfroGPhkEB3+2ttVqxzyuuw736dPI++hjSrdtr9cYNx9f/Lp0JaUNrEOrzgNju3FN/y7s3jsKL1UYz2+fx9aUDPJKRRkOQRBalkjQ6qHkjz9ApapSoHbbqW3ozDomhNbeXinr2GFKcs9w2CWa2YNDa39QRSEsvw98usO4F5oidKGhJAn8oq2dGR46CDO/ArUGlt1pnQLNOdrSEdqNJEl0euklHCMiOP344+jT6lfjrNuAIWQnH6esqNDOETY9SZJ4bUYsY6MCyEy6khJDEXeueoFhb2xk0/Hclg5PEIQOTCRodbBUVFC0bBluEyeg8r64uH99+no8HT3p69e31vH7/voTg8IBn5gB9OtcS0FZkx5+vx/Kcq3tidROTfURBFsp1dDrarhzq7Xm3Nnj8NlIWPNfKC9o6ejsQuHkRPCHH4BSSfr111O+f3+dY7oOGAyyTOre+GaIsOmplQq+vnkA2x65kRldZqP22EtwYAZ3fb+XLUlnWzo8QRA6KJGg1aF45UosJSV43nDDhWN6s54tWVsY23ksKkXN/eZ1paUkx28n0SWCZ6b1qrJ+rYrSs/DddEhcCRNfhcA+Tf0xhMZQKKDfTfDAXus/4z+HD/vAjo+tibXJAIUnrbtB28E0qENYGGGLF6HwcCfjlls5t3Fjrdf7hnbBzde/TZTbqIkkSQR6OPHciIfo4t4Fs/ciOgUd5M7vd7ItOa+lwxMEoQMSCVotZFmm8KdFOEZG4tS//4XjO0/vpNxUzvjQ8bWO37FuHZLZRODAMfQMdK/+opyj8OVYOL0fZn1j3RAgtE5aL7jyfbh7GwQPhHXPwpth8KovfNAbPhsB31xu/bts4xxCQghbZP13P+v+Bzi3cVON16pUKt5csY7733iX7l3DmT9/PgArV66kb9++9O7dmx49evD55583V/g2c1Q68taot/B18qFQ+yOa8Ne5c+U8Xl67gVKdsaXDEwShA6n59Y9Axf4D6BMS6PTSS1Xefv2V/heualcGdxpc6/hda9dwztGXh6+7rPoLTh+ABVOtrYduXQ1B/au/Tmhd/HvCnCWQsgGOrwFnX3ALBGM5bH0bvrjMWrNu4B3QqVebbWSv8vIidOECTl57LbnvvIPL6FFIykvr/Tk5OfH/7Z13nBXV+f/fZ+b2e/dub7DLLksHQZoooIIBO1GjiZqYaDTGXywxJsZ8NaZovvmmaTTGVI3GWGJib9gSBIyFjhTpS9tdtvfby5zfHzPbYBfBsGw7b17D3Dkzc+Y598zO/cxzyrNx82Zef/Be9m1cz4hkkPrKCq677jpWrVpFQUEB0WiUvXv3Hv9CfArGZ4zn2c8+y5rqNfx10xP8R1vGc9VLef7JHGblzOOr089kas5kfA5fX5uqUCgGMUqgHYbGp55C8/lI/eyi9rS4EWdZ2TLmF87HfpjJYpe9vw5ncyWuuZeQ6+8mrFN9KTx5iTmr/TVvQOoRTL+h6F+MXmAunTnxi6ZIW/FHWP+kWb8j50HJfHPJGHn87fwv0Dwesm68iYpbbqHl9Te6/C10xuNP5ZLv/4SN/36D5U88ysPfuYFIMIg/xRQxTqeTcePGHU/T/yuEEJyUdxIn5Z1EXbiOv65/lee2vc6KhudZueRZBIJRaaP48oQvc8nYS/raXIVCMQgZmK/2x4FEXR0tb79N6sWfQ/N629Of3f4sLbEWzh157mHPf+PZF0gInau/8rlDd7ZUwhMXARK+8qISZ4MJl98Mw/WdLXDxwzDuPChbZcb9/O1U+M1kM0JEcuA0l6WcdSbOceOo+8MfkMlDA6OHw2GmTp3KtGnTuOq275Ny6pmMmzqdMZmpFOTlc+5nzuCJxx/HGKDzyWW5s7htztWsuPoZrh/5JKH911Ckfw63zc1dH97Fg+sfVDE9FQrFMUd50Hqg4cknIR4n/YtfbE+rDdXy4PoHmZ0/m1OH9xxPc/nabWRWbsQzZS7p6QeN3Aw3wpMXm6MAr3oVskb3VhEUfYkvB6Zcai5SmhMP714GO/9letj2/Ae+8FezabSfIzSNrBtvoOLmb9GyeDGpF1zQZb/b7eajjz465LyZn72Yp+6/hw9Xr+H737mFvz/yMP949jlSc3KPl+nHFCEEN86bjJBufvXmdi6ZfiGjR7/EQxsfoj5czw9O+cFhBw0pFArF0aA8aN0Q3b2HhkcexX/eeThHdjRJ3bP6HmLJGHeecmfPIzKBN596CoTg8muv7rojFoK/X27+WF/+FAyf3ltFUPQnhICsMTDr63DFM+ZgkKpN8OfTobTnzvf9iZSFCy0v2h+RicQRnVM4cTL/89DfuO+Rv/LTG65l6Qcf8pebr2XFC//sZWt7lxvmj+bmBWN4fl0l+3ecz8UlV/H8zue5aclNVAer+9o8hUIxSFAC7SCklFTddRfC7Sb3jtvb0z848AFv7H2DaydfS5G/5wln31u/nfSKDbhOmEtWbk7HjmQcnv0qlK00m75K5vdaGRT9nBMugeuWgjvDbOp+eAF89HeIh/vash4RmkbWTTcS27uXlsWLP/H4QCDAsmXLEEIwasbJDD/9LEpGj2HMrNl88MxTVGzfehys7j2+vXAMPzh/Amv3NvH46xMYq3+V1VVruOClC3l66zPUtUZ4dk0Z33hiLfPvWcpdr3zM1sqWvjZboVAMIER/7jsxc+ZMuWbNmuN6zabnX6DyzjvJu/tu0i+7FDDnPbvklUuQUvLChS/g1J09nn/nrT8ktWIjX/3NQ+TkWU05hgEvXQ8b/wHn3wcnfe14FEXR34kFYd0TsOYRqNthDig47bump83W8z3WV0jDYM/Fl+AsGcnw++5rT9d1ncmTJ7dvn3POOdx5551cdtlllJaW4na78Xq9PPDAA0yeOJHHv/dNNE3jyl89iN3VzQCaAURTKMZD7+7mr+/vJUI1rvwXsHl3k4zkY0Tz8GgZ5HsL2Vk6mljCxpSCVM6elMfpY7KZNMyPpvXsiVcoFAMPIcRaKeXMY5KXEmgdJBoa2H3ueThGjaLoyScQ1vQIj25+lPvX3s+fF/6ZOcPn9Hj+hx/t4L2f34p98qnc8oP/6djx3v3w77vgjDth3vd6uRSKAYeUsPc98z4pXQJpRbDwLpj0ObN5tB+RqK9Hz8g4bBP/J1G2ZRPP/OT7nHjmeSz82uCY968hGGNjeRPVLWHerVrMjuBSEqKJpmgdCZkg253LjJQvsWXXKD6uCACQ6XVw6UmFXD9/FH5XzyPCFQrFwEEJtF5AGgYVt3yb1qVLKXnxBZyjzc77LbEWzn3+XKZkT+GPC/942PN//O3b8VVv56rfPExuntW82RYeaOxZcOkT/e4HV9HP2LUE/vUjqN5sToZ71v/BiMPPtzcQWfb4w6xd/DIXfe9HjJoxq6/N6TUMabCueh33rLmHLfVbmJw1mcvGXE28dRxLttbyxuYqMrwOblk4hpNHZrKhrIn1ZY1UNEVw6AK7rpHmcfClWSOYXNDDZNcKhaLfoARaL1Dz6/uof/hhcm67jcyvXdOe/tt1v+XhTQ/zzKJnmJA5odtzk4k4f/vFL2jctBL7rPO4+dYbzB1GEh49B+p3wg0rIWVgjl5THGeMJGx4Gpb8LwSqYOKFUHgyBOsgWAuJCAgdNB38w+Hk/wferL62+qiIx6I8efstNFSUkVkwgrGnzGXcnNPJHF7Y16b1CoY0eLX0VR5c/yDVoWpGpIzgSxO+hBbP44lV29lR04A0nBiRfHy2LEZm+UgaknjS4EBThEA0wamjs7h+/ihml2T22DQaTSRZtaeBPXXB9jS/y86ZE3PxOtUIU4Wit1EC7RjT+M9nqPrxj0m77DLy7vpxe/NNXbiO8144j3kF87hn3j3dnhuPRHjp3v9j/6b1bC04jd//4rs47dZs6x/+Ad66Az73EJx4Wa+X41hSuq6Gmn0tZA73kVngIz3Xg6arMSXHlVjQjPf5/gMQD4JmM6MW2N2miJMGtFSA3QtzvgmzbwBnSl9bfcSEW1vY+t5ydq58n/JtH4OUjJ87jzmXXkF6Xv+ffuTTEDfiLNm3hCe3PsmG2g3dHpNiT2Fi5kROKziN0wtOJ8MxnKdXlfGX/+yhLhAl3WNnzugsphbZ8Dg0EnE3gahk/f4mPiitIxQ7dK66FKeNz88s4CunFFGSrSIgKBS9hRJox5DA8uWU3XAj3lPnUvj73yNsHW+ZP1/5c/65/Z+8fNHL3Y7cjEcjPPfTH3Jg5zaWZM7jjluu4rQx2ebO+lL441womQdf/MeAatqMRRI8dvv7xCMdD3pfupMzr5nIsDHpfWjZECUaACMOrrRD76Pa7fDO/8LWV8GVCiPmQMEMKJgFRXPgMNEu+hPBpkbWv/kqaxe/jJFMMGneAopPnE7eqLGkZGX/V33e+is7GnfQEm3Ba/fitrlpijaxo3EHOxp3sLZ6LbuadgFQmFLIvIJ5nJJ/KtU1Oby8/R02t/6LpHMHQkikFMikB3uikGnpC7nshHOZUZhLm5NtT12Qxz/cx+ubKkkYkhlF6Vxw4jDOn5KP32WnORynORzDadPJ9btw2NSLmELxaVEC7RiRDATYtWAh9mHDKH7yiS4RAyoCFSx6cREXjb6IH8/+8SHnSilZ/MCv2L7iPf6ddxbFM+fwxy9bsTSjAfjrudC4D25cMSAmI+3MxqXl/OefO/jcrdNxemzUlbWy+vW9tNSGmfXZEmacU4TQBIlYkpb6CE63DXeKHU3XiIbi1O5vpWZfK7FwAs2modsEOcV+Csdn9HXRBi/la83RoOWrzRGhYHrbTrwcpl0J2WP71r4jJNDYwIoX/snmd94iac235vanUjjhBEZMnsqIE6aQTCSoL99PXdl+4pEwDrcbu8tNWk4eJTNOQrf1LEqlYbQP/unvHAgc4N3yd1levpxVlauIGbH2ffnefE7PP5dURzoRo4VAopEPK9+nMliJz+5jeu50dGF68uNGnMZII7WhelqiIfTQTKr3z0Ymu/e2ZvkcTClI47rTSzh55H83IEShGGoogXaMqP/LX6i599cUP/ss7skndNl367JbWV6+nMWfW0yu99C+Yx8+/zQfPPMUteMX8pIxjiW3zmd4mhuSCfjHl2DXv+FL/4QxZ/aa/b2BNCR/v3slDreNL9zecY/FIgmWPbWdnauryRzuM8VZXZj220eAy2MnEuwIYaRpAsMwD7A7da6551RsjkODbSuOMeFG2PeBObfajjfBSMDMa+Dce0AfGP2QEvE4dfv2ULV7F5U7t7H/440E6uu6HCOEhu6wk4hG29M8qWmccMaZjJt9GrFQiNbGelpqqqkr20fd/r00HCjHn51D0eSpjJg8lazCYlw+Hy6fD03rv/dmKB5iVdUqNtZuZGbuTE7OPxn9IHsNabCmag0vl77M9obt7em6ppPuSifTlUk4EWbJ/iXowsZYz0JcWipx6gnLegpcJzDSvojqlhj/3lpNXSDG9BFp3HjGaD4zPkcJNYXiCFAC7RhgRKPsWrAQ19gxjHj00S77lpct56Z3buKb077JdVOuO+TcHSvf59X7fk60eBoPcTK3nzeBb8wbZU6X8PptsPrhATvf2f6P63n1wQ0svHoi407O67JPSsmW9w6w5b0DpGS6yMj3kprjIR5JEGyJEW6J4Ut3kVOcQk6RH5fXjjQkZdsaePW3Gzjr2kmMmakGShxXAjXw3m9gxe9h7LlmFAOHp6+tOmqklDRWVlC+ZTM2p5OswiLShw3H7nAiDYN4NELF9q1s+Nfr7F67Gim7xv1Mycwmu6iYjOGFNBwop3zLJmLhThMDC0FqTi6jZpzMmJNmM2z8hG4FW7CpEZcvBd02MIRud+xv2c/Dmx7m1dJXScokGa4M0p3plDaXMiVrCj877Wfkugt4dm05D71bSllDmJlF6dxx3nhmFCkvuEJxOJRAOwY0Pv00VXf/hBGP/RXvKae0p4fiIS58+UJ8dh/PLHoG+0F9eLa+v5y3//QA4ZRcHvadw7VnjOX2c8Yj4mH4z6/hP/fCnJvNgNkDkNd+t4Ha/a1c+bM56MeoL4phSP52x/vkFvs57/opxyRPxVGy6mHz5aFgJlz2JKTkffI5A5SWuhoqtn6MOzWNlIwsfBmZOD1dRWkykaCqdCctNVWEA62EW1up2bOLfRvXk0wkcHl95I0ZR/7ocaTnD+PAjq3s3bCOpqpK7E4X+WPHUzBhEhNOPYO03IH5XbbGWrFrdlw2c7LgN/e8yU9W/ISEkeAbJ36DRSWLyHBm8ezacu7/1w5qWqMsnJDLF2cVctqY7C591ZKGRBMoL5tiyNOdQBNCBIDZwBNW0gig2VrqpJQLu81rKAo0mUhQes656JkZFP/jH10eKr9c9Uue2voUj5/7OFNzpranxyJh3nn0z3y8/N/EMkfwuPcMrj1zCt+ZNwyx5lH44EFzCoQpl8FFf4I+7udiGJJoMI5hSIykxEga1loiNEFqjhv9oFGZTdUhnvrxCk5aNJJZi0b2kPOn473ndrJpaTlX/+pUXN6B0XF90LH1VXjua5CMgr8AcidBejHYHKA7Tc9aWpGZllECnqHnLYmFQ+z5aB17N6yjatd26sr3g5TYnE4KJ06mcOJkWupqqdj2MbX792JzODjjyq8zecHZg0KcVAWr+PEHP+aDAx8gEEzPnc68gnlkOHNYuTPOa+uDtAR8+J0uzhifQySepLQ2yL76IJoQ5Ke6yEt1MTE/lQumDuPEgtRB8b0oFEdKTwJNSunrtP0Y8JqU8rnD5jUUBVrzq69y4LbvUfD735GyYEF7+ua6zVzx+hV8YewX+MEpP2hPb6qq5IVf/Jimqircs87mV9Uj+O784dzoXWJOpRFugJIzzCgBRT1HGjgeSCkpXVfLhy+V0lLbc2xH3a6RVeAjp8iPP8uFL93Fng217Fpbw5U/m4M39diGGqrd38ozP1vN/CvGMem04cc0b8VRUL0Fdr4N1R+bk+E2V0AyZi7yoOkZhk2DCReY87Bljuobe/uYaChEU3UlmQUjsNm7vli01NXy1p8eYP+mjyiZfhILv34jKRkDaz66ntjdtJu39r7Fm3vfZHfz7i77BAKnyCAaTsNJNtmufAr8BejSSUMoQmMoyr5KH9FwLkWZHs6bnM8pJZnMKErHp+ZiUwxylEA7SpLNzdQ/9hgyEkXY7bS89SbCbqfklVcQmoaUkrf2vsXPV/0cm7Dx0kUvkeIwRzglE3Ge/uFtNFdXMfv/fZdrFlfxw/S3uDj6MiLSDGPOhtNvg8KT/ms7/xsMQ3JgZxMrX95N1e5mMoZ5mTh3GLpdQ9NFx6JpJONJassD1Oxtoa4sQDza8cM89uRczrx60jG3T0rJ3+9aicfv4HO3Tj/m+SuOAbEQNO2Hxr1Q8zFsWwwVa819I2bDKdfDuPMPHWgQaYGGUgjUmt44u8ecjy1zzIAZlPBpkYbB+jdf5d2/P0YyHictN5+80WPJGzWW/DFjyS4uwe7of3FVj4amSBN14Tpqw7XUhGo4EDhAeaCc8lZzqQnXdHveaN9J0LSQjaVp7U2gY3JS8LttuOw6HofOqGwfJwxP5YRhqRRmuJW3TTHgUQLtKKm47Xu0vPYawuVCxuMgJcPvuw//2WdRHazmpyt/yrKyZUzOmsxP5/6UkrSS9nPffeqvrH7leT77nTu4f0OIqyt+xCyxBcYvgtO/a3oZjjPxWJJQc5Rgc4zW+ghlWxvYt7meSCCOx+/g5AtKGD8n/4gCMUspiYYSBBqjhJqj5I704/T0ThPk6sV7WPXqHq782RxSMgZ2kOwhQ1MZfPwCrP6LKd5SCyFvCkRbINIErVVm0353OHxmBIQRp4DTb3ropGH+zRTNHVBzA34SDQcq2LX6Q6pKd1C5a0f7iFNN18kcXog3IxOPPxW3PxWnx4PD5cbucpFTPIrckaPap/6QUlJXto/afXuIBgNEg0FikTBGMok0DGswQx5ZhUVkFY7A7e/7JsRIIsKBwAGiySia0BBCsKxsGU9seYKmaBNj08fj14cRDftpDfrR4vkQyyMYsbO3LkjCGum9aEo+937hRFz2/juaVtF/0XWdyZMnt2+/9NJL7N27lwsvvJCSkhLC4TCLFi3i3nvv7VU7lEA7CgL/eY+yr3+drBuuJ/vmm5FSsr56He8deJ+VlSvZXL8Zh+bgpmk38eUJX+4ydH3fxo947v9+wJQF55AYO4Xx71zLCL0B/XN/gCmX/rfFOyKMpEFLXYTaslYqdzZxYFcT9QeC0KnanB4bRSdkUjwli+LJWdid/fMB11wb4skfrmD2xaOYflbHxL/SkBhSguSYDUxQHGOMJGx/wxyhHKg1J8V1+c0QUxmjIHM0pOSb/dviEQjVQ9lK2P8h1Gw5NL+scebUH1MuHZR93QIN9VSV7qSqdAe1+/YQbGoi1NJEuKWFRCza5Vhvegajps8CAXvWr6W1vqvg1W02NN1mevutEatt2BxOvGlpeNLScXm8aDY7us2G3emypg9JIS0vn7GnzD3u04iE4iGe3fEs75a/y4HAAapCVSSMRPv+4b7hjEkbS4a9mIbGTBavizF9WAmPXHk6qW7VT3UosHfvXhYtWsTmzZvb0+666y58Ph+bN29m0aJFfP7zn6ehoYEFCxZw8803c/XVV3ebl8/nIxAIdElbtmwZ9957L6+99hrhcJhp06bxyCOPMHfu3F4rkxJoR4gRCrH7sxcgHA5GvPAcS6rf5dFNj7K1YSu60JmcNZlThp3CBSUXUOjvGgMw1NLM47fdhMOuMX9ONlk7/o7UbKRc9Qxa0Sk9XPHoSSYNYqEE0XCCWDhBS12EhsogjVVBGiuDNFaHMBJmHdmcOvmjUskrScWf6cLjd+BNc5KeN3DCMD33yzWEmmPkFKfQcCBIc024fa40gOHj0pm6sJCiSZmII/AAKgYA0VZIxkFopgdt+xvmpLptzaeZo2H4TCiea/Z3cw3uoOBGMkk8GiESCFC+dTO7165iz4Z1CAEjTpjKyGkzGT5+Iu4UP06Pp8vEu1JKgk2N1JXto75sP60NdQQbGwg2NRKPhEkmEiQTCeKRCJFAa7uYyx8zjrO/8S0yC0b0VbFJGkmqQ9XsbNzJ9sbt7VET9rXsw+g0LYowXOT40nHoNnSh47a5yffmM8w3jGJ/MQuKFpDlHhx9/YYibZ6ueDyOYRg0NTVRUVGBpmksW7aMs88+m8zMTCKRCH6/nwceeICf/vSnXHPNNVx//fU95vtJAg3g8ssv5+KLL+bSS/97B4uUkqQhSUqJlKBrAl0IdF0bIgJtxgy5Zu3aoz4vbsRZcWAFgft+R/HrG3npOzN5N7OO8kA5xf5irj7has4qOgufo/uYdPvWr+TN3/2SUDDCFcUfkeEMs1pMZvhX/sSIURN7vK40JPFYEiMpSSYMQs0xastaqSsL0Fofxum1405x4HDpNFaFqK8I0FQV6iJQABDgt+YZS8/3kp7nJXO4l6wC34ARYj2x9YNKlj65zSzfMC9puR5sDh1Ng3jUYPvKKoJNUdLzPGQVphANmcLV5tBIz/eSaZ3jTnHgSXGg2zXqrP50DVVBsgtTGDklC2/awO73MySo3AC7lkD5GjMCQrAGbG6YdBFM/oI5mtSTaQq2g5vxpLQCx0dNT54jxQwsv/11s+9c5QYzgkd6sTky1ZVqNrk6fZA/FfIm96sm1raoCcd6frVELMbOle/zzt8eJh4OMeuiSxk/93TS84b1m4gKkUSE0uZSylvL+WDfLp7fsIkkYfJSHRRmuPG44lQFKzkQPEA4EUYXOqcNP43zR51PSWoJma5M0l3paKJ/lKc/0iZe9u7dy4QJExg3blz7vu985ztceeWVx90WgDVr1jB//nxuvfVW7r77bpYtW8Z1113Hddddx+bNm5k/fz4PPfQQX/jCF/j2t7992Hw7N3GOHDmSF198sYtAa2xsZOHChSxevJi8vKObGicYTXDFX1aytbIFQ0oShqQn6bTvl4uGhkCb7PfLFf/6N96TZ/V4jDQMIps307R0CXXvvE2stoZKT4waX5KTt0s+mOHhzUuLyfZkc/Hoi1kwYsEhM3C3EWlt5e0HfsTOTTtJd4TIyNNpHH02I2ZdwNwTRrX3jWgLcdRSF6a5NkzDgSD1FQHqKwIkYsYh+dqdOv4sN9FwnEhrnETcwJfuJKvAR8ZwH95UJ063jsNtw5fuIi3Pg30Qz7gvDdmjdyyZNChdW8OmZeWEW+M4PTYcbhuxSJLGymCXAQ0H43DpxKz4obkj/WQV+HCnOHCnOLA5NKQhkYbE6bUzYlImTvfg7sA+oJASDqyDdU/A5ufNPm5taDZwZ5hizZ1u9n1r3AvxUKcMBO3t/hmjoGi22RTbuNfsO5c4aERzSj6MXgjFp5liLWvMgIlb+mkINTfxzmMPsf2DdwFwerzkjByFPysHT6rZNy4aDNJYdYCmygMAZBePJHfkKDILivCmpeP2+3G43DTXVtNUdYDWujpyR40mb9TYY9oPbn99iCdX7uOFdeXUBWL4XTamFKRxwnA/I3JbqTTeY/Hu16gNdzQF60Inw5VBljuLTHcmma5MstxZZLmz8Nq9JGWSaCJBZXMITTOw6eB1OJiaO4kSewHrXnqB1vp64pEQsUgEl9dHak4eqbl5uH0p3Yp5Xdfx5+SRnj8Md4q/z/sCHo7OAu3gJsW+sgXMJs6zzjqL+vp66urqWL58eReB9sorr3Dttdfyq1/96qjybWPZsmVceOGFFBUVsX37dm6//Xbuvvvuo7b5vre389t3dnHV7CI8TpvpKdM6FjAH6iWl5NtnjhsaE9WO93nkiwVFNF1wKmm33ESt0cye5j2UtZYhYzHGvLePMa9vwVMXwBCwYxjUZdgoA3cZWwAAGzxJREFUiaWSE9DxeNMofvIJdL//kLyllESCAVoqyyn78HV2rF1NdXUrUsLIjBYCp13L+YsuxxY3PWEt9WGqSluoLG2ivjzQRT07PTayCnxkDvfhTXOiW/EnnV472YUppGa72wWJlOZcZKqv1dEjDUlrQ4Tm2jDhQIxwS5x4LEnmMC85RX48qQ4aK0Ps/qiWvZvqaKkLEw7Eu/TXa0OzCQonZFAyNZthY9LMOurHD9ghRSxkhqoK1pp92bosDeBOMz1j6cVgc1kDFlrA4YVx50LW2EN/UJNxiAU7wmDtfAtKl3YIQd0JORNMsZY3BbJGm9483WHmmzW2z+c2PBbUl+/nwM5tVJfuomZPKa2N9YRbmknG4whNIzU7l/T8YRiGQc3e3YRbmj8xz5TMbMbMmo0nNY1QcxMh6xxvWhqe1HQ8qWl408y1OyWlR8+dy+vD7uwYPBRPGizZWsPyHbVsqmhiW2UrCUMyOsfHDWeMpHhYA7XhaurD9dSF66iPWOtO2537vHVHQY2buRszcSR0gj47cWEjIm24khqpsSi2eOSw57dh2B3Y7Hbsmo6ua0w/9wJO/lxHM1prrJUt9VtojDSS7ckm15NLrif3kInQe4v+KtD27dvH+eefT0VFBdu2bWPr1q1dmjgNwyAjI4MVK1aQk5NzxPm20dmDtmPHDk499VTefvttpk6d2kMuh1LRFOYz9y7jrEl5PPjFTx4UOGQiCWSPzpQ/nD2cM1fHqU6DHcMELV4QTidzNsRIazXYWaCxbm4O/tPnM3PcGczMnYnHfmgoGykldfv3smPl++xeu4rGynLi0Y7gw26bHbsrC5k6nZSs6USa4oRaYl3ysDl1cov95JX4Sc/zkprtJsXqC6Z+3PsnhiGJBOIk4kk0TUNo0FIXoXR9DbvX1dLaYD6A3X4HeZbXLWOYj4x8Ly6fHU0X6DYNzSbQNKHqeTCRTED9TqjaBFUboWqzuQ7VH3qsv8Bsep1wgTkatb4UGnZ39eJFA2Yza6DaFJmeTDNgvbdtnW2maT14bl2p5nxzqYVwHDv0SymJhcPYHI4uTaxSSgKN9TSUlxNqbSbc3EQsHMafnUNa3jB86RmUbdnEjpXvmxEY4nEcbjduv9mHMNjU2CVO6pHgcLvxpmWQnj+M3BLTO+fy+agvL6N6315K95RRWhMgEE3gtQt8xLDHQ9hiQTRA1wW6pqNpAikEEkE4kSSSMNA0jRSvB3tmNiI1m3CgBbavp8nn5J0JcVrTm0FvRooOL709nIIt6kboEYQWRoiOFhLdEKSE7PiDNnxhG5phXs8fdDK83s7GUZJtY1ygtxCSVYeUVSBIdeSQbs/Hp+eR4U4hJ8VLtteH2+bEoTtw6uZaYCMc1UgmdZy6A6fNidfmx25k0xCK0RJO4HPZSHPbsdsj+JxuXLoTzeoXNak4lx3ltVRX7GfuzKldmjgffPBBZpwyA6fu7NK6FDfitERb2kWuEAJB12dg23bbPwCbZuux+xB0FVKBQIBx48YRDAbZvn07W7du5eqrr+auu+5i6dKlnHfeeZTt28dTTz/N4hdfwC4g0NRIqKkRzWZj/JzTu823jYP7oN1///2sWrWKp59+uueb8CC++fR63v64ine+a8Xb/gSGjECbOHaSfO3Zpylfu4TgG0tIbQ6SWt9CMgr2GSfju/RSwtlZRFqbScTCxGMhQk3NNFXX0FpfTyTYgkwaSCmJRwLEwo2AwOlIR4phGFomQktB0/NA92NzaHh8DvzZLvxZblIyXHjTnHj8DnzpTjLyvQO+D5iiAyklDQeCVO1uprK0mardzTTXhrv1uLWh2QR2h47Ta8flseHy2XF57Ti9dpweW0dDm+y4BrJTltLsK2+z69gcGg6XDbffgTfVbIp1um3YnboaINFXSGlOHdKw25rAN24Krm2vmf3ljHjHsZrN9K61YfeAL9cMo2X3dHj9grUQrDt0IuCe0B1WNIdRpmBLyTeFYKQZYgHTs+fwdsRUTcZNWxPRjs/ta0sgebI6BKIzxTzf6TPFYFqROX/df0E8FkUgsDm65hOLhAk1NRFsbiLU3Ei4tZVu/8AkhAOtBJsaCDY2Ul++n/qKMjo3VdgcTlJzchGaRmskQVM4QczmImrzENZdNEWSGIbElEkSIc21DozP8zExP4VkJExjZQWNlRUkEwlmnH8hp15+VbvdhjRoiDSwu2k32xu3s7V+Gy3RIGmuNDJcaaS7UklzppHqTMVn9xEzYkQTUQKxIDvra9hRV0l5UzVj1lUxoiLCxjEaGwt9BFuGkYwMRyb8CFsLwtaMZm9Cc9SjOeoQ9gaEFgeRQIjD/ybrSYErpuGK6jjDXhyBbJyRFDQtgGZvRNMj5jPHcIDhgqSL537zGpfc+CUS9UGWvvZvblz0GRzJJEEvtPjCNHtCRBxJDIcNw+kg4AzT6AgQs0n4FI+iDFcGY9PHMjZ9LCn2FLRwAoIxcoxUvnThTSz9+98INjUSbGzghl/cR11TMw98/Qo+2rWHR955j+8tWsCbH21hQn4OJxbm89qGrVQ0NvO102Zhs36DMwtG8NVf/6H9mkci0MLhMKNHj+a9995j5MhPjpazdl8Dl/zxQ27+zGi+c9a4TzweBrhAE0KcAzwA6MBfpJS/6OnYwow0ecuZpx6UqiH0DKQRBdnaw0XcCM2HEB5AIISBJjRcjhzczhwSmpsGO0SKRjJtVjHzpuXjcdmUd0RBIpaksSpEQ2WQeCRBMmEO+DCSBsmEGTIrHkkSCSWIBONEg3EiwTiRQLy9/1sXhPV8E9b7pTCbaj/pz87u0nG4bDhcOnaXjWTCaL+WNMx+jXaXbq6txeGydWy7uqYLTSC0jliJQjPffh0eG5nDfHjTjr0XWErzu0vEDJJxg0Q8SSJmoOkCu9OG3aWj2zrevIUujmjuvj4j3Ai7l5kDEjJLIHXEkU/Eaxhm37lQvTllySFIc199qTnpb5uHrmE3JKxmNrvHFFaJGMRazRGxbWg2U9jpdrO5Vrdb246OvEMNdCuOhA5pheBK++RyCAF2ryUQvR2ePiktkRiBeNjctjk62WR91nRzn5GwjnGa+dg9puC0e8HuBk8mMWcmNY1xooaDzBEj28VZT0QTSXZUBdhY0UQ0bpDisuF32xmfl0JRprfLsUYySSwSxuXt2dNjHmhYolxYfzSd1oc9Lcmbf/gNW/+zlNEnzcaTnUtQ8xC1uXG63TjdHhwuJ16nHa9Tx65r1LREKWsMUt4YIBQOkoiaizvShCdQi625HhkIQPzwzbbd8f0X3uRnF59DTTjAo++t4bIrTyJmM8gIuvAF7bh7cHQmNDCEAET7nWNuiXbdJpBITSOW4iGR6sXwO0kGGxHNLThbE7ijGprs+L7abBFON0Fh55F/LaMlGMLpdBGNx7DZHVx7zTd5/c0XmThxMidMnkkMjReee4JIPMH8K75Nq+4j4UzBn+Il1WPHadOobY1S2xqlORwn1W0nw+sg0+ck0+cg0+sgw+vEYTMnpgfz9pOYz2LrPZqD9dBjH+ylLhBl6Xfn43Ec2d/6gBVoQggd2AGcCZQDq4EvSim7mSgJRuWky+9f+nViRgmJeAZoNSSpJpFsIGl3EXdlEndnkJusYUJ8K34iOPUEGfZafFo9Hr2RgLSzVRbzsSzmQMbJpE2Yz5wJI5hamNauxBWKY4FsG437CUGj2/ohJuIGsXCCUEuMUHOUUEuMWCRJLJIgHjbX5pJEt2m4vDZcXjtCE8SjSXOJJIlHE8SjSWKRZJf0ZOLQASs94fTaSM/1Ynfp2OwaNnvXHyG7U8fpNgdsxGNJgo1RAk2RdmEajyZJxDtdz5AkEsZhvZGHIMDts+NJdeJJsWN32bA7dGxOHbtDs9YdwtPW/llr/9y+tmvmQ9eQ5ihpaTZ3SykPTTMk0jDrxdzfOV125CO7bred156vdW7bfWBG7+iI5KG3fbZ1je7Rnq6bfVe7nCckItpser0691eS0hRDQgPNfmT945IJU2TGWs3+eJEWcwBFmyCMBT85D5k0BVgsYB7fWSTqDrNPoN1t2tUWQqzdmxczbdD0dpGTjMcJh22Eok6QSTQS6CLRZa2JJNjdCKcfnF6E7gCbJfqcPoQrBRx+sLsQVrquW5JCGtC2Niu5U5rs2JZJ8/sIN5qh+8KNpqCNNHUt48E3rCXYktKGFDYkGlLogIYhBf+pzGVPawqhhI2k/PQvH6n2MJnOEGmOCB49hscWx6PH8djiuPU40pbAh2HOKZg+EuHwgNARug7xCKnXv0HNzyeyrbqBKx6r4r0b/bilxGP9/ielIJK0EUnaCCftBBIOAnEngYSDhNS6iDGr5ObLJgIDQdzQaYy5aY65CCXsuPQ46Y4waY4wH2sl/EebQlB3E7R5WPnADTiyisyJlzUN76TPkHbyRWT6XIjKLXz06J24M/JJWtNY5Jz+RfJOnI/HoeN22PA4zCgUSUPSHI7TFIoTTRhk+Rzk+F2kuu20hOPUB6PUB2LUB2LEkkf+LOyMJuCBy6fx2ROHHfE5A1mgzQbuklKebW3fASCl/Hl3x59YmCKXXZdNerKepLShi57fHHY7x7M096uUZZ6GS8TwyQBeuyBrWAkjs30UZ3lVHDjFkCKZNEhYwq1dWLQ1uVpz90QCMerKzVHIzTUh4jGDZNwSW23NtEAimiQaTpCMG2iawJvmxJvmxJ1ib/fc6Y6OBzlCYLNr6HYNu0NHt2vYHBq6zRxN2yYkO4vIRNywxGqMcGus/ZhErG396R6yAx1NEx3CThPtdScNs/mprW+k0EBolhdS0MnH0YHsXKltabLtv65N8bLLAdZHw5w8O5mUGG1118k73H5d0fEjLkTHdlvTvRBmOaLhxNGJ+CNEJ4ZXb8Cn1ePUgmaBRIfM6DC407Zmt7x9nTx+ut30MFpGGoYgFteIx3VibUtCxzAOL5DNv7soUoZBxkHGkMS7PdamJbDbBA67jt2u43B50XSXJcZ10x5NA9peoiyhaHO1ezRPXFDIqGkdneoPmWZjzGhTlBpJrrnkbG6+fKHl/QyZHlpnijli2p1uNpOHGkzhGguZHsVkwlrH27dlMk4yESMSjZKweYnoPsKal2DeLBg+A4/D9BS215EmcNt1XHYdp3Vv9wZSSgLRBPWBGAnDwGxVs+5H694Voq0/Xddz3Q6dLN/RTdl0LAXa8VYsw4GyTtvlwMmdDxBCXAdcBzBixAjSf7gb4hG0lgrr7cZaYkHzhkpEYNg0SkbOo0Q1USoU7ei6hu7RPiF0l5dhY9KPOM9k3Gyi7Is+ctIwvY4HC7d4LEmifW1Y3rykJVqswR1W867QrIdzW7r1WVgip03caG1plugx93XK45B8ul4DTCFjJGX7kmzfNjAS3aS1HZfofJ4lhjod0/laSDo8e9ZiSODguRU7065LOkk4QRdx3V1am6bRdWvQjG7tbRNz1n+m4Gvb7Lzd9nJgpQMunx1vqtnPV9OE+X0kzO8lGe/4HsysOgnFznm2X7vjBSQajBNoKiDQFKUlfIR9/3qi01ep2QQOn47P6n7gcNlwuPX2fqMdYlR0ONg6f5+iQwQISxkIYTlEY0li4US7Fz1medGNT+H9OdiD39Y3q7i4mHA43N0p/zUCU1B8QqPxcUcIQYrLTopr4E2jc7wFWndP9S5PEinlQ8BDYEYSAEzXdeaoXjdOoVAcHt3ed90ChCbamzcVCoVisHO8n7blQOeYSgXAgeNsg0KhUCgUCkW/5ngLtNXAGCHESCGEA7gceOU426BQKBQKhULRrzmuTZxSyoQQ4ibgLcxpNh6VUn58PG1QKBQKhUKh6O8c92GNUsrXgdeP93UVCoVCoVAoBgpqIjCFQqFQKBSKfoYSaAqFQqFQKBT9DCXQFAqFQqFQKPoZSqApFAqFQqFQ9DOUQFMoFAqFQqHoZyiBplAoFAqFQtHPUAJNoVAoFAqFop+hBJpCoVAoFApFP0MJNIVCoVAoFIp+hpBS9rUNPSKEaAW297UdfUgWUNfXRvQhqvxDt/xDueygyq/KP3TLP9DLXiSlzD4WGR33UE9HyXYp5cy+NqKvEEKsUeVX5e9rO/qCoVx2UOVX5R+65R/KZT8Y1cSpUCgUCoVC0c9QAk2hUCgUCoWin9HfBdpDfW1AH6PKP7QZyuUfymUHVX5V/qHLUC57F/r1IAGFQqFQKBSKoUh/96ApFAqFQqFQDDn6rUATQpwjhNguhNglhLi9r+3pbYQQhUKIpUKIrUKIj4UQ37LSM4QQ/xJC7LTW6X1ta28hhNCFEOuFEK9Z2yOFECutsv9TCOHoaxt7CyFEmhDiOSHENusemD3E6v7b1n2/WQjxtBDCNZjrXwjxqBCiRgixuVNat/UtTH5rPQs3CiGm953lx4Yeyn+Pdf9vFEK8KIRI67TvDqv824UQZ/eN1ceG7sread93hRBSCJFlbQ+JurfSv2nV78dCiF91Sh80dX+09EuBJoTQgd8D5wITgS8KISb2rVW9TgK4VUo5ATgFuNEq8+3AEinlGGCJtT1Y+RawtdP2L4H7rbI3Al/rE6uODw8Ab0opxwMnYn4PQ6LuhRDDgZuBmVLKEwAduJzBXf+PAecclNZTfZ8LjLGW64A/Hicbe5PHOLT8/wJOkFJOAXYAdwBYz8HLgUnWOX+wfiMGKo9xaNkRQhQCZwL7OyUPiboXQpwBXAhMkVJOAu610gdb3R8V/VKgAbOAXVLK3VLKGPAPzMobtEgpK6WU66zPrZg/0MMxy/0367C/ARf1jYW9ixCiADgf+Iu1LYDPAM9ZhwzmsvuB04FHAKSUMSllE0Ok7i1sgFsIYQM8QCWDuP6llO8CDQcl91TfFwKPS5MVQJoQIv/4WNo7dFd+KeXbUsqEtbkCKLA+Xwj8Q0oZlVLuAXZh/kYMSHqoe4D7ge8BnTuGD4m6B64HfiGljFrH1Fjpg6ruj5b+KtCGA2WdtsuttCGBEKIYmAasBHKllJVgijggp+8s61V+g/lwMqztTKCp0wN7MN8DJUAt8FerifcvQggvQ6TupZQVmG/M+zGFWTOwlqFT/230VN9D8Xl4DfCG9XnQl18IcQFQIaXccNCuQV92i7HAaVaXhuVCiJOs9KFS/m7prwJNdJM2JIabCiF8wPPALVLKlr6253gghFgE1Egp13ZO7ubQwXoP2IDpwB+llNOAIIO0ObM7rL5WFwIjgWGAF7Np52AGa/1/EkPpbwEhxJ2YXT6eakvq5rBBU34hhAe4E/hRd7u7SRs0Ze+EDUjH7N5zG/CM1YoyVMrfLf1VoJUDhZ22C4ADfWTLcUMIYccUZ09JKV+wkqvbXNrWuqan8wcwc4ELhBB7MZuzP4PpUUuzmrxgcN8D5UC5lHKltf0cpmAbCnUPsBDYI6WslVLGgReAOQyd+m+jp/oeMs9DIcRVwCLgCtkxB9RgL/8ozJeTDdYzsABYJ4TIY/CXvY1y4AWrKXcVZktKFkOn/N3SXwXaamCMNYrLgdlJ8JU+tqlXsd4WHgG2Sinv67TrFeAq6/NVwMvH27beRkp5h5SyQEpZjFnX70gprwCWAp+3DhuUZQeQUlYBZUKIcVbSAmALQ6DuLfYDpwghPNbfQVv5h0T9d6Kn+n4FuNIa0XcK0NzWFDqYEEKcA/wPcIGUMtRp1yvA5UIIpxBiJGaH+VV9YWNvIKXcJKXMkVIWW8/AcmC69VwYEnUPvIT5Yo4QYizgwAyYPqjr/hORUvbLBTgPcyRPKXBnX9tzHMp7KqbrdiPwkbWch9kXawmw01pn9LWtvfw9zAdesz6XYP4x7gKeBZx9bV8vlnsqsMaq/5cw3f1Dpu6Bu4FtwGbgCcA5mOsfeBqzv10c8wf5az3VN2Yzz++tZ+EmzNGufV6GXij/Lsz+Rm3Pvz91Ov5Oq/zbgXP72v5jXfaD9u8FsoZY3TuAJ62//3XAZwZj3R/toiIJKBQKhUKhUPQz+msTp0KhUCgUCsWQRQk0hUKhUCgUin6GEmgKhUKhUCgU/Qwl0BQKhUKhUCj6GUqgKRQKhUKhUPQzlEBTKBQKhUKh6GcogaZQKI4rVqzRicfhOt/v9LlYCLG5F64xXwjx2lGes0wIMbOb9K8KIX537KxTKBQDGSXQFArFcUVKea2UcstxuNT3P/mQrnQKLaVQKBR9ihJoCoWi1xBCeIUQi4UQG4QQm4UQl3X2IAkhAkKI/7P2rxBC5FrpuUKIF630DUKIOVb6l4UQq4QQHwkh/iyE0Hu47i8At3VcW9BtXQjxsBDiYyHE20IIt3XsMiHEz4QQy4FvCSGyhRDPCyFWW8tc67h5Vn4fCSHWCyFSrHx9QojnhBDbhBBPWeGqEEIssI7bJIR4VAjh7MbOq4UQO6xrzz1mX7xCoRjwKIGmUCh6k3OAA1LKE6WUJwBvHrTfC6yQUp4IvAt83Ur/LbDcSp8OfCyEmABcBsyVUk4FksAV3V1USnk7EJZSTpVmXFcw4/j9Xko5CWgCLul0SpqUcp6U8tfAA8D9UsqTrGP+Yh3zXeBG69qnAWErfRpwCzARMzzVXCGEC3gMuExKORmwAdd3ttEKiH43pjA70zpfoVAoACXQFApF77IJWCiE+KUQ4jQpZfNB+2NAWx+utUCx9fkzwB8BpJRJ67wFwAxgtRDiI2u75Chs2SOl/KibawH8s9PnhcDvrGu8Avgtb9n7wH1CiJsxBV3COn6VlLJcSmlgxpAsBsZZ19thHfM34PSD7DkZWCalrJVSxg6yQaFQDHFUfwuFQtFrSCl3CCFmAOcBPxdCvH3QIXHZERA4yeGfSQL4m5Tyjk9pTrTT5yTg7rQd7PRZA2ZLKcN05RdCiMWYZVkhhFjYQ742y9YjQQVDVigU3aI8aAqFotcQQgwDQlLKJ4F7MZsrj4QlWE2CQghdCOG30j4vhMix0jOEEEWHySMuhLB/CrPfBm7qVIap1nqUlHKTlPKXwBpg/GHy2AYUCyFGW9tfAZYfdMxKYL4QItOy8wufwlaFQjFIUQJNoVD0JpOBVVZz4Z3AT4/wvG8BZwghNmE2R06yRn7+AHhbCLER+BeQf5g8HgI2dhokcKTcDMwUQmwUQmwBvmGl32INdNiA2f/sjZ4ykFJGgKuBZ60yGMCfDjqmErgL+BD4N7DuKO1UKBSDGNHRuqBQKBQKhUKh6A8oD5pCoVAoFApFP0MNElAoFAMaIcRK4OA5xr4ipdzUF/YoFArFsUA1cSoUCoVCoVD0M1QTp0KhUCgUCkU/Qwk0hUKhUCgUin6GEmgKhUKhUCgU/Qwl0BQKhUKhUCj6GUqgKRQKhUKhUPQz/j8FuwmQkx4zvgAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths_m7_prime[COUNTRIES_CORE].plot(figsize=(10, 6), title=\"Deaths per day, 7 day moving average\")\n",
-    "for c in COUNTRIES_CORE:\n",
-    "    lvi = deaths_m7_prime[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = deaths_m7_prime[c][lvi], s = c)\n",
-    "# plt.savefig('covid_deaths_per_day_7.png') # see below for where this is written, with the projection"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 643,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths_m7[COUNTRIES_FRIENDS].plot(figsize=(10, 6), title=\"Deaths per day, 7 day moving average\")\n",
-    "for c in COUNTRIES_FRIENDS:\n",
-    "    lvi = deaths_m7[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = c)\n",
-    "plt.savefig('covid_deaths_per_day_friends_7.png') "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 644,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths_m7[COUNTRIES_CORE + ['BR', 'MX']].plot(figsize=(10, 6), title=\"Deaths per day, 7 day moving average\")\n",
-    "for c in COUNTRIES_CORE + ['BR', 'MX']:\n",
-    "    lvi = deaths_m7[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = c)\n",
-    "# plt.savefig('covid_deaths_per_day_7.png') "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 645,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = cases_m7[COUNTRIES_CORE].plot(figsize=(10, 6), title=\"Cases per day, 7 day moving average\")\n",
-    "for c in COUNTRIES_CORE:\n",
-    "    lvi = cases_m7[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = cases_m7[c][lvi], s = c)\n",
-    "plt.savefig('covid_cases_per_day-core.png') "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 646,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = cases_m7[COUNTRIES_FRIENDS].plot(figsize=(10, 6), title=\"Cases per day, 7 day moving average\")\n",
-    "for c in COUNTRIES_FRIENDS:\n",
-    "    lvi = cases_m7[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = cases_m7[c][lvi], s = c)\n",
-    "# plt.savefig('covid_cases_per_day-core.png') "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 647,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def gmean_scale(items):\n",
-    "    return gmean(items) / items[-1]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 648,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def doubling_time(df):\n",
-    "    return np.log(2) / np.log((df.deaths_culm + df.deaths_g4) / df.deaths_culm)\n",
-    "\n",
-    "def doubling_time_7(df):\n",
-    "    return np.log(2) / np.log((df.deaths_culm + df.deaths_g7) / df.deaths_culm)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 649,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# data_since_threshold['deaths_g4'] = data_since_threshold.groupby(level=1)['deaths'].transform(lambda x: x.rolling(4, 1).apply(gmean_scale, raw=True))\n",
-    "# data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT']), :]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 650,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "      <th>deaths_m4</th>\n",
-       "      <th>deaths_m7</th>\n",
-       "      <th>cases_m7</th>\n",
-       "      <th>deaths_g4</th>\n",
-       "      <th>deaths_g7</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>since_threshold</th>\n",
-       "      <th>geoId</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td rowspan=\"3\" valign=\"top\">0</td>\n",
-       "      <td>DE</td>\n",
-       "      <td>2020-03-16</td>\n",
-       "      <td>1043</td>\n",
-       "      <td>4</td>\n",
-       "      <td>4838</td>\n",
-       "      <td>12</td>\n",
-       "      <td>310.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.00</td>\n",
-       "      <td>4.000000</td>\n",
-       "      <td>1043.000000</td>\n",
-       "      <td>4.000000</td>\n",
-       "      <td>4.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-02-26</td>\n",
-       "      <td>93</td>\n",
-       "      <td>5</td>\n",
-       "      <td>322</td>\n",
-       "      <td>11</td>\n",
-       "      <td>-4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>5.00</td>\n",
-       "      <td>5.000000</td>\n",
-       "      <td>93.000000</td>\n",
-       "      <td>5.000000</td>\n",
-       "      <td>5.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-03-15</td>\n",
-       "      <td>478</td>\n",
-       "      <td>19</td>\n",
-       "      <td>2244</td>\n",
-       "      <td>29</td>\n",
-       "      <td>-6.0</td>\n",
-       "      <td>18.0</td>\n",
-       "      <td>19.00</td>\n",
-       "      <td>19.000000</td>\n",
-       "      <td>478.000000</td>\n",
-       "      <td>19.000000</td>\n",
-       "      <td>19.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td rowspan=\"2\" valign=\"top\">1</td>\n",
-       "      <td>DE</td>\n",
-       "      <td>2020-03-17</td>\n",
-       "      <td>1174</td>\n",
-       "      <td>1</td>\n",
-       "      <td>6012</td>\n",
-       "      <td>13</td>\n",
-       "      <td>131.0</td>\n",
-       "      <td>-3.0</td>\n",
-       "      <td>2.50</td>\n",
-       "      <td>2.500000</td>\n",
-       "      <td>1108.500000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>2.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-02-27</td>\n",
-       "      <td>78</td>\n",
-       "      <td>1</td>\n",
-       "      <td>400</td>\n",
-       "      <td>12</td>\n",
-       "      <td>-15.0</td>\n",
-       "      <td>-4.0</td>\n",
-       "      <td>3.00</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>85.500000</td>\n",
-       "      <td>2.236068</td>\n",
-       "      <td>2.236068</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>171</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>574</td>\n",
-       "      <td>3</td>\n",
-       "      <td>252809</td>\n",
-       "      <td>35234</td>\n",
-       "      <td>52.0</td>\n",
-       "      <td>-3.0</td>\n",
-       "      <td>6.25</td>\n",
-       "      <td>6.285714</td>\n",
-       "      <td>436.142857</td>\n",
-       "      <td>5.732657</td>\n",
-       "      <td>5.266158</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>172</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>629</td>\n",
-       "      <td>158</td>\n",
-       "      <td>253438</td>\n",
-       "      <td>35392</td>\n",
-       "      <td>55.0</td>\n",
-       "      <td>155.0</td>\n",
-       "      <td>44.25</td>\n",
-       "      <td>27.000000</td>\n",
-       "      <td>476.428571</td>\n",
-       "      <td>12.986209</td>\n",
-       "      <td>7.524073</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>173</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>477</td>\n",
-       "      <td>4</td>\n",
-       "      <td>253915</td>\n",
-       "      <td>35396</td>\n",
-       "      <td>-152.0</td>\n",
-       "      <td>-154.0</td>\n",
-       "      <td>42.75</td>\n",
-       "      <td>27.285714</td>\n",
-       "      <td>478.428571</td>\n",
-       "      <td>10.327552</td>\n",
-       "      <td>8.307250</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>174</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>320</td>\n",
-       "      <td>4</td>\n",
-       "      <td>254235</td>\n",
-       "      <td>35400</td>\n",
-       "      <td>-157.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>42.25</td>\n",
-       "      <td>27.285714</td>\n",
-       "      <td>487.142857</td>\n",
-       "      <td>9.331997</td>\n",
-       "      <td>8.307250</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>175</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>401</td>\n",
-       "      <td>5</td>\n",
-       "      <td>254636</td>\n",
-       "      <td>35405</td>\n",
-       "      <td>81.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>42.75</td>\n",
-       "      <td>27.142857</td>\n",
-       "      <td>485.571429</td>\n",
-       "      <td>10.603195</td>\n",
-       "      <td>8.093673</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>491 rows × 12 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                         dateRep  cases  deaths  cases_culm  deaths_culm  \\\n",
-       "since_threshold geoId                                                      \n",
-       "0               DE    2020-03-16   1043       4        4838           12   \n",
-       "                IT    2020-02-26     93       5         322           11   \n",
-       "                UK    2020-03-15    478      19        2244           29   \n",
-       "1               DE    2020-03-17   1174       1        6012           13   \n",
-       "                IT    2020-02-27     78       1         400           12   \n",
-       "...                          ...    ...     ...         ...          ...   \n",
-       "171             IT    2020-08-15    574       3      252809        35234   \n",
-       "172             IT    2020-08-16    629     158      253438        35392   \n",
-       "173             IT    2020-08-17    477       4      253915        35396   \n",
-       "174             IT    2020-08-18    320       4      254235        35400   \n",
-       "175             IT    2020-08-19    401       5      254636        35405   \n",
-       "\n",
-       "                       cases_diff  deaths_diff  deaths_m4  deaths_m7  \\\n",
-       "since_threshold geoId                                                  \n",
-       "0               DE          310.0          1.0       4.00   4.000000   \n",
-       "                IT           -4.0          1.0       5.00   5.000000   \n",
-       "                UK           -6.0         18.0      19.00  19.000000   \n",
-       "1               DE          131.0         -3.0       2.50   2.500000   \n",
-       "                IT          -15.0         -4.0       3.00   3.000000   \n",
-       "...                           ...          ...        ...        ...   \n",
-       "171             IT           52.0         -3.0       6.25   6.285714   \n",
-       "172             IT           55.0        155.0      44.25  27.000000   \n",
-       "173             IT         -152.0       -154.0      42.75  27.285714   \n",
-       "174             IT         -157.0          0.0      42.25  27.285714   \n",
-       "175             IT           81.0          1.0      42.75  27.142857   \n",
-       "\n",
-       "                          cases_m7  deaths_g4  deaths_g7  \n",
-       "since_threshold geoId                                     \n",
-       "0               DE     1043.000000   4.000000   4.000000  \n",
-       "                IT       93.000000   5.000000   5.000000  \n",
-       "                UK      478.000000  19.000000  19.000000  \n",
-       "1               DE     1108.500000   2.000000   2.000000  \n",
-       "                IT       85.500000   2.236068   2.236068  \n",
-       "...                            ...        ...        ...  \n",
-       "171             IT      436.142857   5.732657   5.266158  \n",
-       "172             IT      476.428571  12.986209   7.524073  \n",
-       "173             IT      478.428571  10.327552   8.307250  \n",
-       "174             IT      487.142857   9.331997   8.307250  \n",
-       "175             IT      485.571429  10.603195   8.093673  \n",
-       "\n",
-       "[491 rows x 12 columns]"
-      ]
-     },
-     "execution_count": 650,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_since_threshold['deaths_g4'] = data_since_threshold.groupby(level=1)['deaths'].transform(lambda x: x.rolling(4, 1).apply(gmean, raw=True))\n",
-    "data_since_threshold['deaths_g7'] = data_since_threshold.groupby(level=1)['deaths'].transform(lambda x: x.rolling(7, 1).apply(gmean, raw=True))\n",
-    "data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT']), :]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 651,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "data_since_threshold['doubling_time'] = data_since_threshold.groupby(level=1).apply(doubling_time).reset_index(level=0, drop=True).sort_index()\n",
-    "data_since_threshold['doubling_time_7'] = data_since_threshold.groupby(level=1).apply(doubling_time_7).reset_index(level=0, drop=True).sort_index()\n",
-    "# data_since_threshold.loc[(slice(None), 'UK'), :]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 652,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "doubling_times = (data_since_threshold.loc[(slice(None), COUNTRIES_OF_INTEREST), ['doubling_time']]\n",
-    "             .unstack().sort_index().xs('doubling_time', axis=1, drop_level=True))\n",
-    "doubling_times.replace([np.inf, -np.inf], np.nan, inplace=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 653,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "doubling_times_7 = (data_since_threshold.loc[(slice(None), COUNTRIES_OF_INTEREST), ['doubling_time_7']]\n",
-    "             .unstack().sort_index().xs('doubling_time_7', axis=1, drop_level=True))\n",
-    "doubling_times_7.replace([np.inf, -np.inf], np.nan, inplace=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 654,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = doubling_times.plot(figsize=(10, 6), title=\"Doubling times, 4 day average\")\n",
-    "for c in doubling_times.columns:\n",
-    "    lvi = doubling_times[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = doubling_times[c][lvi], s = c)\n",
-    "# plt.savefig('covid_deaths_per_day.png') "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 655,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = doubling_times_7[COUNTRIES_CORE].plot(figsize=(10, 6), title=\"Doubling times, 7 day average\")\n",
-    "ax.legend(loc=\"upper left\")\n",
-    "for c in COUNTRIES_CORE:\n",
-    "    lvi = doubling_times_7[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = doubling_times_7[c][lvi], s = c)\n",
-    "plt.savefig('covid_doubling_times_7.png') "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 656,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = doubling_times[COUNTRIES_CORE].plot(figsize=(10, 6), title=\"Doubling times, 4 day average\")\n",
-    "for c in COUNTRIES_CORE:\n",
-    "    lvi = doubling_times[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = doubling_times[c][lvi], s = c)\n",
-    "plt.savefig('covid_doubling_times.png') "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 657,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = doubling_times[COUNTRIES_FRIENDS].plot(figsize=(10, 6), title=\"Doubling times\")\n",
-    "for c in COUNTRIES_FRIENDS:\n",
-    "    lvi = doubling_times[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = doubling_times[c][lvi], s = c)\n",
-    "plt.savefig('covid_doubling_times_friends.png')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 658,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = doubling_times[C7s].plot(figsize=(10, 6), title=\"Doubling times\")\n",
-    "for c in C7s:\n",
-    "    lvi = doubling_times[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = doubling_times[c][lvi], s = c)\n",
-    "# plt.savefig('covid_doubling_times_friends.png')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 659,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# deaths_diff_m4 = (data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['deaths_diff_m4']]\n",
-    "#              .unstack().sort_index().xs('deaths_diff_m4', axis=1, drop_level=True))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 660,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# deaths_diff_m7 = (data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['deaths_diff_m7']]\n",
-    "#              .unstack().sort_index().xs('deaths_diff_m7', axis=1, drop_level=True))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 661,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# deaths_diff_m7"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 662,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# data_since_threshold.replace([np.inf, -np.inf], np.nan).groupby(level=1).last().loc[COUNTRIES_ALL]#, [doubling_time]]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 663,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "      <th>deaths_m4</th>\n",
-       "      <th>deaths_m7</th>\n",
-       "      <th>cases_m7</th>\n",
-       "      <th>deaths_g4</th>\n",
-       "      <th>deaths_g7</th>\n",
-       "      <th>doubling_time</th>\n",
-       "      <th>doubling_time_7</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>AR</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>4557</td>\n",
-       "      <td>127</td>\n",
-       "      <td>299113</td>\n",
-       "      <td>5877</td>\n",
-       "      <td>-912.0</td>\n",
-       "      <td>34.0</td>\n",
-       "      <td>112.250000</td>\n",
-       "      <td>156.000000</td>\n",
-       "      <td>6465.428571</td>\n",
-       "      <td>110.458405</td>\n",
-       "      <td>144.209930</td>\n",
-       "      <td>37.224774</td>\n",
-       "      <td>28.593061</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>BE</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>0</td>\n",
-       "      <td>3</td>\n",
-       "      <td>78804</td>\n",
-       "      <td>9959</td>\n",
-       "      <td>-124.0</td>\n",
-       "      <td>-3.0</td>\n",
-       "      <td>5.750000</td>\n",
-       "      <td>8.142857</td>\n",
-       "      <td>318.285714</td>\n",
-       "      <td>5.449632</td>\n",
-       "      <td>7.455740</td>\n",
-       "      <td>1267.047349</td>\n",
-       "      <td>926.217464</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>BO</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>1796</td>\n",
-       "      <td>49</td>\n",
-       "      <td>103019</td>\n",
-       "      <td>4172</td>\n",
-       "      <td>917.0</td>\n",
-       "      <td>-26.0</td>\n",
-       "      <td>72.000000</td>\n",
-       "      <td>58.714286</td>\n",
-       "      <td>1384.428571</td>\n",
-       "      <td>66.604597</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>43.763233</td>\n",
-       "      <td>42.879681</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>BR</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>47784</td>\n",
-       "      <td>1352</td>\n",
-       "      <td>3407354</td>\n",
-       "      <td>109888</td>\n",
-       "      <td>28411.0</td>\n",
-       "      <td>668.0</td>\n",
-       "      <td>841.250000</td>\n",
-       "      <td>980.285714</td>\n",
-       "      <td>42532.000000</td>\n",
-       "      <td>798.486687</td>\n",
-       "      <td>938.016642</td>\n",
-       "      <td>95.737298</td>\n",
-       "      <td>81.547795</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>BS</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>95</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1424</td>\n",
-       "      <td>20</td>\n",
-       "      <td>81.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.714286</td>\n",
-       "      <td>62.142857</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>4.149238</td>\n",
-       "      <td>4.149238</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>CL</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>1353</td>\n",
-       "      <td>33</td>\n",
-       "      <td>388855</td>\n",
-       "      <td>10546</td>\n",
-       "      <td>-203.0</td>\n",
-       "      <td>-28.0</td>\n",
-       "      <td>51.500000</td>\n",
-       "      <td>52.571429</td>\n",
-       "      <td>1748.428571</td>\n",
-       "      <td>50.121070</td>\n",
-       "      <td>48.774613</td>\n",
-       "      <td>146.191754</td>\n",
-       "      <td>150.217927</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>CO</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>12462</td>\n",
-       "      <td>247</td>\n",
-       "      <td>489122</td>\n",
-       "      <td>15619</td>\n",
-       "      <td>4134.0</td>\n",
-       "      <td>-28.0</td>\n",
-       "      <td>281.750000</td>\n",
-       "      <td>306.285714</td>\n",
-       "      <td>11238.428571</td>\n",
-       "      <td>280.598061</td>\n",
-       "      <td>303.981235</td>\n",
-       "      <td>38.928370</td>\n",
-       "      <td>35.960375</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>CR</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>559</td>\n",
-       "      <td>10</td>\n",
-       "      <td>29643</td>\n",
-       "      <td>314</td>\n",
-       "      <td>-60.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>8.250000</td>\n",
-       "      <td>8.428571</td>\n",
-       "      <td>733.571429</td>\n",
-       "      <td>7.400828</td>\n",
-       "      <td>7.913802</td>\n",
-       "      <td>29.753858</td>\n",
-       "      <td>27.847494</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>CU</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>44</td>\n",
-       "      <td>0</td>\n",
-       "      <td>3408</td>\n",
-       "      <td>88</td>\n",
-       "      <td>-4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>45.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>26.041848</td>\n",
-       "      <td>15.646131</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>DE</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>2900</td>\n",
-       "      <td>11</td>\n",
-       "      <td>226914</td>\n",
-       "      <td>9243</td>\n",
-       "      <td>2900.0</td>\n",
-       "      <td>11.0</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>5.142857</td>\n",
-       "      <td>1199.285714</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>955.232651</td>\n",
-       "      <td>1770.437439</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>DK</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>115</td>\n",
-       "      <td>0</td>\n",
-       "      <td>15855</td>\n",
-       "      <td>621</td>\n",
-       "      <td>-8.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>128.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>173.165809</td>\n",
-       "      <td>84.145334</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>DO</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>386</td>\n",
-       "      <td>8</td>\n",
-       "      <td>87123</td>\n",
-       "      <td>1489</td>\n",
-       "      <td>-42.0</td>\n",
-       "      <td>-20.0</td>\n",
-       "      <td>20.000000</td>\n",
-       "      <td>20.428571</td>\n",
-       "      <td>861.285714</td>\n",
-       "      <td>17.667875</td>\n",
-       "      <td>18.887491</td>\n",
-       "      <td>58.762434</td>\n",
-       "      <td>54.990273</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>EC</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>1190</td>\n",
-       "      <td>22</td>\n",
-       "      <td>102941</td>\n",
-       "      <td>6105</td>\n",
-       "      <td>981.0</td>\n",
-       "      <td>9.0</td>\n",
-       "      <td>18.750000</td>\n",
-       "      <td>22.000000</td>\n",
-       "      <td>1054.000000</td>\n",
-       "      <td>14.957225</td>\n",
-       "      <td>18.891850</td>\n",
-       "      <td>283.264126</td>\n",
-       "      <td>224.340531</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>5114</td>\n",
-       "      <td>24</td>\n",
-       "      <td>364196</td>\n",
-       "      <td>28670</td>\n",
-       "      <td>-11155.0</td>\n",
-       "      <td>-5.0</td>\n",
-       "      <td>13.250000</td>\n",
-       "      <td>12.714286</td>\n",
-       "      <td>5369.142857</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>6648.367576</td>\n",
-       "      <td>3746.842165</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>FI</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>24</td>\n",
-       "      <td>0</td>\n",
-       "      <td>7776</td>\n",
-       "      <td>334</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>-1.0</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>21.857143</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>153.756713</td>\n",
-       "      <td>94.796834</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>FR</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>2238</td>\n",
-       "      <td>22</td>\n",
-       "      <td>221267</td>\n",
-       "      <td>30451</td>\n",
-       "      <td>1745.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>11.250000</td>\n",
-       "      <td>13.857143</td>\n",
-       "      <td>2442.142857</td>\n",
-       "      <td>5.950787</td>\n",
-       "      <td>9.407959</td>\n",
-       "      <td>3547.276714</td>\n",
-       "      <td>2243.875146</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>GT</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>903</td>\n",
-       "      <td>30</td>\n",
-       "      <td>63847</td>\n",
-       "      <td>2419</td>\n",
-       "      <td>521.0</td>\n",
-       "      <td>20.0</td>\n",
-       "      <td>19.500000</td>\n",
-       "      <td>26.571429</td>\n",
-       "      <td>840.142857</td>\n",
-       "      <td>17.818253</td>\n",
-       "      <td>23.913877</td>\n",
-       "      <td>94.447574</td>\n",
-       "      <td>70.461069</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>GY</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>28</td>\n",
-       "      <td>2</td>\n",
-       "      <td>737</td>\n",
-       "      <td>25</td>\n",
-       "      <td>28.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>24.142857</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>7.966167</td>\n",
-       "      <td>7.966167</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>HN</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>675</td>\n",
-       "      <td>10</td>\n",
-       "      <td>51670</td>\n",
-       "      <td>1593</td>\n",
-       "      <td>182.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>11.250000</td>\n",
-       "      <td>11.142857</td>\n",
-       "      <td>466.714286</td>\n",
-       "      <td>10.501066</td>\n",
-       "      <td>10.241685</td>\n",
-       "      <td>105.495847</td>\n",
-       "      <td>108.158881</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>HT</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>24</td>\n",
-       "      <td>0</td>\n",
-       "      <td>7921</td>\n",
-       "      <td>196</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.857143</td>\n",
-       "      <td>38.857143</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>36.735711</td>\n",
-       "      <td>34.687679</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>IE</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>186</td>\n",
-       "      <td>1</td>\n",
-       "      <td>27499</td>\n",
-       "      <td>1775</td>\n",
-       "      <td>130.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>99.714286</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>776.717987</td>\n",
-       "      <td>505.737213</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>401</td>\n",
-       "      <td>5</td>\n",
-       "      <td>254636</td>\n",
-       "      <td>35405</td>\n",
-       "      <td>81.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>42.750000</td>\n",
-       "      <td>27.142857</td>\n",
-       "      <td>485.571429</td>\n",
-       "      <td>10.603195</td>\n",
-       "      <td>8.093673</td>\n",
-       "      <td>2314.825805</td>\n",
-       "      <td>3032.452741</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>JM</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>17</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1146</td>\n",
-       "      <td>14</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>14.142857</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>4.496556</td>\n",
-       "      <td>4.496556</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>MX</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>5506</td>\n",
-       "      <td>751</td>\n",
-       "      <td>531239</td>\n",
-       "      <td>57774</td>\n",
-       "      <td>1935.0</td>\n",
-       "      <td>485.0</td>\n",
-       "      <td>466.500000</td>\n",
-       "      <td>549.285714</td>\n",
-       "      <td>5531.000000</td>\n",
-       "      <td>405.907680</td>\n",
-       "      <td>499.101022</td>\n",
-       "      <td>99.003788</td>\n",
-       "      <td>80.582108</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>NI</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>196</td>\n",
-       "      <td>5</td>\n",
-       "      <td>4311</td>\n",
-       "      <td>133</td>\n",
-       "      <td>196.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.250000</td>\n",
-       "      <td>0.714286</td>\n",
-       "      <td>28.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.631383</td>\n",
-       "      <td>1.631383</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>NO</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>56</td>\n",
-       "      <td>1</td>\n",
-       "      <td>10060</td>\n",
-       "      <td>262</td>\n",
-       "      <td>-98.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.857143</td>\n",
-       "      <td>53.714286</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>53.464058</td>\n",
-       "      <td>15.836088</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>PA</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>247</td>\n",
-       "      <td>21</td>\n",
-       "      <td>82790</td>\n",
-       "      <td>1809</td>\n",
-       "      <td>-356.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>18.750000</td>\n",
-       "      <td>18.428571</td>\n",
-       "      <td>903.714286</td>\n",
-       "      <td>18.258277</td>\n",
-       "      <td>17.873703</td>\n",
-       "      <td>69.021875</td>\n",
-       "      <td>70.499528</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>PE</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>7828</td>\n",
-       "      <td>177</td>\n",
-       "      <td>549321</td>\n",
-       "      <td>26658</td>\n",
-       "      <td>2281.0</td>\n",
-       "      <td>-23.0</td>\n",
-       "      <td>200.500000</td>\n",
-       "      <td>736.714286</td>\n",
-       "      <td>8520.142857</td>\n",
-       "      <td>199.907298</td>\n",
-       "      <td>310.318996</td>\n",
-       "      <td>92.778573</td>\n",
-       "      <td>59.890818</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>PR</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>953</td>\n",
-       "      <td>11</td>\n",
-       "      <td>27713</td>\n",
-       "      <td>346</td>\n",
-       "      <td>199.0</td>\n",
-       "      <td>11.0</td>\n",
-       "      <td>8.750000</td>\n",
-       "      <td>8.428571</td>\n",
-       "      <td>615.714286</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>26.794956</td>\n",
-       "      <td>47.461217</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>PT</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>214</td>\n",
-       "      <td>5</td>\n",
-       "      <td>54448</td>\n",
-       "      <td>1784</td>\n",
-       "      <td>82.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>3.285714</td>\n",
-       "      <td>214.714286</td>\n",
-       "      <td>2.590020</td>\n",
-       "      <td>2.874102</td>\n",
-       "      <td>477.784710</td>\n",
-       "      <td>430.593793</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>PY</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>471</td>\n",
-       "      <td>16</td>\n",
-       "      <td>10606</td>\n",
-       "      <td>161</td>\n",
-       "      <td>127.0</td>\n",
-       "      <td>9.0</td>\n",
-       "      <td>13.250000</td>\n",
-       "      <td>10.714286</td>\n",
-       "      <td>441.000000</td>\n",
-       "      <td>12.369185</td>\n",
-       "      <td>9.543378</td>\n",
-       "      <td>9.364453</td>\n",
-       "      <td>12.036873</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>SE</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>174</td>\n",
-       "      <td>3</td>\n",
-       "      <td>85219</td>\n",
-       "      <td>5790</td>\n",
-       "      <td>-577.0</td>\n",
-       "      <td>-1.0</td>\n",
-       "      <td>1.750000</td>\n",
-       "      <td>2.857143</td>\n",
-       "      <td>299.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1036.482262</td>\n",
-       "      <td>150.913952</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>SI</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>18</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2456</td>\n",
-       "      <td>124</td>\n",
-       "      <td>-4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.571429</td>\n",
-       "      <td>26.285714</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>58.049517</td>\n",
-       "      <td>51.331425</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>SR</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>139</td>\n",
-       "      <td>6</td>\n",
-       "      <td>3216</td>\n",
-       "      <td>54</td>\n",
-       "      <td>78.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>3.250000</td>\n",
-       "      <td>2.142857</td>\n",
-       "      <td>93.857143</td>\n",
-       "      <td>2.340347</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>16.337453</td>\n",
-       "      <td>6.712288</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>SV</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>269</td>\n",
-       "      <td>15</td>\n",
-       "      <td>23462</td>\n",
-       "      <td>633</td>\n",
-       "      <td>-12.0</td>\n",
-       "      <td>15.0</td>\n",
-       "      <td>9.500000</td>\n",
-       "      <td>8.000000</td>\n",
-       "      <td>313.285714</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>45.848824</td>\n",
-       "      <td>26.323070</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>SX</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>326</td>\n",
-       "      <td>17</td>\n",
-       "      <td>-9.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>15.285714</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>4.496556</td>\n",
-       "      <td>4.496556</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>TT</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>77</td>\n",
-       "      <td>1</td>\n",
-       "      <td>629</td>\n",
-       "      <td>12</td>\n",
-       "      <td>77.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>51.666667</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>7.966167</td>\n",
-       "      <td>7.966167</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>1089</td>\n",
-       "      <td>12</td>\n",
-       "      <td>320286</td>\n",
-       "      <td>41381</td>\n",
-       "      <td>376.0</td>\n",
-       "      <td>9.0</td>\n",
-       "      <td>5.750000</td>\n",
-       "      <td>10.285714</td>\n",
-       "      <td>1071.000000</td>\n",
-       "      <td>4.820571</td>\n",
-       "      <td>8.022291</td>\n",
-       "      <td>5950.497778</td>\n",
-       "      <td>3575.774437</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>UY</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>28</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1485</td>\n",
-       "      <td>40</td>\n",
-       "      <td>11.0</td>\n",
-       "      <td>-2.0</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>14.285714</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>4.496556</td>\n",
-       "      <td>4.496556</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>VE</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>895</td>\n",
-       "      <td>9</td>\n",
-       "      <td>35697</td>\n",
-       "      <td>297</td>\n",
-       "      <td>-152.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>7.750000</td>\n",
-       "      <td>8.428571</td>\n",
-       "      <td>1108.428571</td>\n",
-       "      <td>7.491653</td>\n",
-       "      <td>8.146594</td>\n",
-       "      <td>27.824346</td>\n",
-       "      <td>25.615047</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "      dateRep  cases  deaths  cases_culm  deaths_culm  cases_diff  \\\n",
-       "AR 2020-08-19   4557     127      299113         5877      -912.0   \n",
-       "BE 2020-08-19      0       3       78804         9959      -124.0   \n",
-       "BO 2020-08-19   1796      49      103019         4172       917.0   \n",
-       "BR 2020-08-19  47784    1352     3407354       109888     28411.0   \n",
-       "BS 2020-08-19     95       1        1424           20        81.0   \n",
-       "CL 2020-08-19   1353      33      388855        10546      -203.0   \n",
-       "CO 2020-08-19  12462     247      489122        15619      4134.0   \n",
-       "CR 2020-08-19    559      10       29643          314       -60.0   \n",
-       "CU 2020-08-19     44       0        3408           88        -4.0   \n",
-       "DE 2020-08-19   2900      11      226914         9243      2900.0   \n",
-       "DK 2020-08-19    115       0       15855          621        -8.0   \n",
-       "DO 2020-08-19    386       8       87123         1489       -42.0   \n",
-       "EC 2020-08-19   1190      22      102941         6105       981.0   \n",
-       "ES 2020-08-18   5114      24      364196        28670    -11155.0   \n",
-       "FI 2020-08-19     24       0        7776          334         3.0   \n",
-       "FR 2020-08-19   2238      22      221267        30451      1745.0   \n",
-       "GT 2020-08-19    903      30       63847         2419       521.0   \n",
-       "GY 2020-08-19     28       2         737           25        28.0   \n",
-       "HN 2020-08-19    675      10       51670         1593       182.0   \n",
-       "HT 2020-08-19     24       0        7921          196         6.0   \n",
-       "IE 2020-08-19    186       1       27499         1775       130.0   \n",
-       "IT 2020-08-19    401       5      254636        35405        81.0   \n",
-       "JM 2020-08-19     17       0        1146           14         1.0   \n",
-       "MX 2020-08-19   5506     751      531239        57774      1935.0   \n",
-       "NI 2020-08-19    196       5        4311          133       196.0   \n",
-       "NO 2020-08-19     56       1       10060          262       -98.0   \n",
-       "PA 2020-08-19    247      21       82790         1809      -356.0   \n",
-       "PE 2020-08-19   7828     177      549321        26658      2281.0   \n",
-       "PR 2020-08-19    953      11       27713          346       199.0   \n",
-       "PT 2020-08-19    214       5       54448         1784        82.0   \n",
-       "PY 2020-08-19    471      16       10606          161       127.0   \n",
-       "SE 2020-08-19    174       3       85219         5790      -577.0   \n",
-       "SI 2020-08-19     18       0        2456          124        -4.0   \n",
-       "SR 2020-08-19    139       6        3216           54        78.0   \n",
-       "SV 2020-08-19    269      15       23462          633       -12.0   \n",
-       "SX 2020-08-19      0       0         326           17        -9.0   \n",
-       "TT 2020-08-19     77       1         629           12        77.0   \n",
-       "UK 2020-08-19   1089      12      320286        41381       376.0   \n",
-       "UY 2020-08-19     28       0        1485           40        11.0   \n",
-       "VE 2020-08-19    895       9       35697          297      -152.0   \n",
-       "\n",
-       "    deaths_diff   deaths_m4   deaths_m7      cases_m7   deaths_g4   deaths_g7  \\\n",
-       "AR         34.0  112.250000  156.000000   6465.428571  110.458405  144.209930   \n",
-       "BE         -3.0    5.750000    8.142857    318.285714    5.449632    7.455740   \n",
-       "BO        -26.0   72.000000   58.714286   1384.428571   66.604597    0.000000   \n",
-       "BR        668.0  841.250000  980.285714  42532.000000  798.486687  938.016642   \n",
-       "BS          0.0    0.750000    0.714286     62.142857    0.000000    0.000000   \n",
-       "CL        -28.0   51.500000   52.571429   1748.428571   50.121070   48.774613   \n",
-       "CO        -28.0  281.750000  306.285714  11238.428571  280.598061  303.981235   \n",
-       "CR          0.0    8.250000    8.428571    733.571429    7.400828    7.913802   \n",
-       "CU          0.0    0.000000    0.000000     45.000000    0.000000    0.000000   \n",
-       "DE         11.0    3.000000    5.142857   1199.285714    0.000000    0.000000   \n",
-       "DK          0.0    0.000000    0.000000    128.000000    0.000000    0.000000   \n",
-       "DO        -20.0   20.000000   20.428571    861.285714   17.667875   18.887491   \n",
-       "EC          9.0   18.750000   22.000000   1054.000000   14.957225   18.891850   \n",
-       "ES         -5.0   13.250000   12.714286   5369.142857    0.000000    0.000000   \n",
-       "FI         -1.0    0.250000    0.142857     21.857143    0.000000    0.000000   \n",
-       "FR          3.0   11.250000   13.857143   2442.142857    5.950787    9.407959   \n",
-       "GT         20.0   19.500000   26.571429    840.142857   17.818253   23.913877   \n",
-       "GY          2.0    0.750000    0.428571     24.142857    0.000000    0.000000   \n",
-       "HN          2.0   11.250000   11.142857    466.714286   10.501066   10.241685   \n",
-       "HT          0.0    0.000000    1.857143     38.857143    0.000000    0.000000   \n",
-       "IE          1.0    0.250000    0.285714     99.714286    0.000000    0.000000   \n",
-       "IT          1.0   42.750000   27.142857    485.571429   10.603195    8.093673   \n",
-       "JM          0.0    0.000000    0.000000     14.142857    0.000000    0.000000   \n",
-       "MX        485.0  466.500000  549.285714   5531.000000  405.907680  499.101022   \n",
-       "NI          5.0    1.250000    0.714286     28.000000    0.000000    0.000000   \n",
-       "NO          1.0    0.250000    0.857143     53.714286    0.000000    0.000000   \n",
-       "PA          0.0   18.750000   18.428571    903.714286   18.258277   17.873703   \n",
-       "PE        -23.0  200.500000  736.714286   8520.142857  199.907298  310.318996   \n",
-       "PR         11.0    8.750000    8.428571    615.714286    0.000000    0.000000   \n",
-       "PT          4.0    3.000000    3.285714    214.714286    2.590020    2.874102   \n",
-       "PY          9.0   13.250000   10.714286    441.000000   12.369185    9.543378   \n",
-       "SE         -1.0    1.750000    2.857143    299.000000    0.000000    0.000000   \n",
-       "SI          0.0    0.000000    0.571429     26.285714    0.000000    0.000000   \n",
-       "SR          5.0    3.250000    2.142857     93.857143    2.340347    0.000000   \n",
-       "SV         15.0    9.500000    8.000000    313.285714    0.000000    0.000000   \n",
-       "SX          0.0    0.000000    0.000000     15.285714    0.000000    0.000000   \n",
-       "TT          1.0    0.666667    0.666667     51.666667    0.000000    0.000000   \n",
-       "UK          9.0    5.750000   10.285714   1071.000000    4.820571    8.022291   \n",
-       "UY         -2.0    0.500000    0.428571     14.285714    0.000000    0.000000   \n",
-       "VE          2.0    7.750000    8.428571   1108.428571    7.491653    8.146594   \n",
-       "\n",
-       "    doubling_time  doubling_time_7  \n",
-       "AR      37.224774        28.593061  \n",
-       "BE    1267.047349       926.217464  \n",
-       "BO      43.763233        42.879681  \n",
-       "BR      95.737298        81.547795  \n",
-       "BS       4.149238         4.149238  \n",
-       "CL     146.191754       150.217927  \n",
-       "CO      38.928370        35.960375  \n",
-       "CR      29.753858        27.847494  \n",
-       "CU      26.041848        15.646131  \n",
-       "DE     955.232651      1770.437439  \n",
-       "DK     173.165809        84.145334  \n",
-       "DO      58.762434        54.990273  \n",
-       "EC     283.264126       224.340531  \n",
-       "ES    6648.367576      3746.842165  \n",
-       "FI     153.756713        94.796834  \n",
-       "FR    3547.276714      2243.875146  \n",
-       "GT      94.447574        70.461069  \n",
-       "GY       7.966167         7.966167  \n",
-       "HN     105.495847       108.158881  \n",
-       "HT      36.735711        34.687679  \n",
-       "IE     776.717987       505.737213  \n",
-       "IT    2314.825805      3032.452741  \n",
-       "JM       4.496556         4.496556  \n",
-       "MX      99.003788        80.582108  \n",
-       "NI       1.631383         1.631383  \n",
-       "NO      53.464058        15.836088  \n",
-       "PA      69.021875        70.499528  \n",
-       "PE      92.778573        59.890818  \n",
-       "PR      26.794956        47.461217  \n",
-       "PT     477.784710       430.593793  \n",
-       "PY       9.364453        12.036873  \n",
-       "SE    1036.482262       150.913952  \n",
-       "SI      58.049517        51.331425  \n",
-       "SR      16.337453         6.712288  \n",
-       "SV      45.848824        26.323070  \n",
-       "SX       4.496556         4.496556  \n",
-       "TT       7.966167         7.966167  \n",
-       "UK    5950.497778      3575.774437  \n",
-       "UY       4.496556         4.496556  \n",
-       "VE      27.824346        25.615047  "
-      ]
-     },
-     "execution_count": 663,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "dstl = data_since_threshold.replace([np.inf, -np.inf], np.nan).groupby(level=1).last()\n",
-    "dstl.loc[dstl.index.intersection(COUNTRIES_ALL)]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 664,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "      <th>deaths_m4</th>\n",
-       "      <th>deaths_m7</th>\n",
-       "      <th>cases_m7</th>\n",
-       "      <th>deaths_g4</th>\n",
-       "      <th>deaths_g7</th>\n",
-       "      <th>doubling_time</th>\n",
-       "      <th>doubling_time_7</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>geoId</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>1089</td>\n",
-       "      <td>12</td>\n",
-       "      <td>320286</td>\n",
-       "      <td>41381</td>\n",
-       "      <td>376.0</td>\n",
-       "      <td>9.0</td>\n",
-       "      <td>5.75</td>\n",
-       "      <td>10.285714</td>\n",
-       "      <td>1071.000000</td>\n",
-       "      <td>4.820571</td>\n",
-       "      <td>8.022291</td>\n",
-       "      <td>5950.497778</td>\n",
-       "      <td>3575.774437</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>DE</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>2900</td>\n",
-       "      <td>11</td>\n",
-       "      <td>226914</td>\n",
-       "      <td>9243</td>\n",
-       "      <td>2900.0</td>\n",
-       "      <td>11.0</td>\n",
-       "      <td>3.00</td>\n",
-       "      <td>5.142857</td>\n",
-       "      <td>1199.285714</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>955.232651</td>\n",
-       "      <td>1770.437439</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>IT</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>401</td>\n",
-       "      <td>5</td>\n",
-       "      <td>254636</td>\n",
-       "      <td>35405</td>\n",
-       "      <td>81.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>42.75</td>\n",
-       "      <td>27.142857</td>\n",
-       "      <td>485.571429</td>\n",
-       "      <td>10.603195</td>\n",
-       "      <td>8.093673</td>\n",
-       "      <td>2314.825805</td>\n",
-       "      <td>3032.452741</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>FR</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>2238</td>\n",
-       "      <td>22</td>\n",
-       "      <td>221267</td>\n",
-       "      <td>30451</td>\n",
-       "      <td>1745.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>11.25</td>\n",
-       "      <td>13.857143</td>\n",
-       "      <td>2442.142857</td>\n",
-       "      <td>5.950787</td>\n",
-       "      <td>9.407959</td>\n",
-       "      <td>3547.276714</td>\n",
-       "      <td>2243.875146</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>5114</td>\n",
-       "      <td>24</td>\n",
-       "      <td>364196</td>\n",
-       "      <td>28670</td>\n",
-       "      <td>-11155.0</td>\n",
-       "      <td>-5.0</td>\n",
-       "      <td>13.25</td>\n",
-       "      <td>12.714286</td>\n",
-       "      <td>5369.142857</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>6648.367576</td>\n",
-       "      <td>3746.842165</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "         dateRep  cases  deaths  cases_culm  deaths_culm  cases_diff  \\\n",
-       "geoId                                                                  \n",
-       "UK    2020-08-19   1089      12      320286        41381       376.0   \n",
-       "DE    2020-08-19   2900      11      226914         9243      2900.0   \n",
-       "IT    2020-08-19    401       5      254636        35405        81.0   \n",
-       "FR    2020-08-19   2238      22      221267        30451      1745.0   \n",
-       "ES    2020-08-18   5114      24      364196        28670    -11155.0   \n",
-       "\n",
-       "       deaths_diff  deaths_m4  deaths_m7     cases_m7  deaths_g4  deaths_g7  \\\n",
-       "geoId                                                                         \n",
-       "UK             9.0       5.75  10.285714  1071.000000   4.820571   8.022291   \n",
-       "DE            11.0       3.00   5.142857  1199.285714   0.000000   0.000000   \n",
-       "IT             1.0      42.75  27.142857   485.571429  10.603195   8.093673   \n",
-       "FR             3.0      11.25  13.857143  2442.142857   5.950787   9.407959   \n",
-       "ES            -5.0      13.25  12.714286  5369.142857   0.000000   0.000000   \n",
-       "\n",
-       "       doubling_time  doubling_time_7  \n",
-       "geoId                                  \n",
-       "UK       5950.497778      3575.774437  \n",
-       "DE        955.232651      1770.437439  \n",
-       "IT       2314.825805      3032.452741  \n",
-       "FR       3547.276714      2243.875146  \n",
-       "ES       6648.367576      3746.842165  "
-      ]
-     },
-     "execution_count": 664,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# data_since_threshold.replace([np.inf, -np.inf], np.nan).groupby(level=1).last().loc[['UK', 'DE', 'IT']]#, [doubling_time]]\n",
-    "dstl.loc[['UK', 'DE', 'IT', 'FR', 'ES']]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 665,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "      <th>deaths_m4</th>\n",
-       "      <th>deaths_m7</th>\n",
-       "      <th>cases_m7</th>\n",
-       "      <th>deaths_g4</th>\n",
-       "      <th>deaths_g7</th>\n",
-       "      <th>doubling_time</th>\n",
-       "      <th>doubling_time_7</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>since_threshold</th>\n",
-       "      <th>geoId</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>138</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-07-31</td>\n",
-       "      <td>846</td>\n",
-       "      <td>0</td>\n",
-       "      <td>302301</td>\n",
-       "      <td>41169</td>\n",
-       "      <td>83.0</td>\n",
-       "      <td>-34.0</td>\n",
-       "      <td>14.50</td>\n",
-       "      <td>16.142857</td>\n",
-       "      <td>552.714286</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>inf</td>\n",
-       "      <td>inf</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>139</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-01</td>\n",
-       "      <td>880</td>\n",
-       "      <td>20</td>\n",
-       "      <td>303181</td>\n",
-       "      <td>41189</td>\n",
-       "      <td>34.0</td>\n",
-       "      <td>20.0</td>\n",
-       "      <td>18.75</td>\n",
-       "      <td>14.428571</td>\n",
-       "      <td>574.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>inf</td>\n",
-       "      <td>inf</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>140</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-02</td>\n",
-       "      <td>771</td>\n",
-       "      <td>13</td>\n",
-       "      <td>303952</td>\n",
-       "      <td>41202</td>\n",
-       "      <td>-109.0</td>\n",
-       "      <td>-7.0</td>\n",
-       "      <td>16.75</td>\n",
-       "      <td>14.142857</td>\n",
-       "      <td>588.857143</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>inf</td>\n",
-       "      <td>inf</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>141</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-03</td>\n",
-       "      <td>743</td>\n",
-       "      <td>5</td>\n",
-       "      <td>304695</td>\n",
-       "      <td>41207</td>\n",
-       "      <td>-28.0</td>\n",
-       "      <td>-8.0</td>\n",
-       "      <td>9.50</td>\n",
-       "      <td>13.714286</td>\n",
-       "      <td>634.857143</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>inf</td>\n",
-       "      <td>inf</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>142</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-04</td>\n",
-       "      <td>928</td>\n",
-       "      <td>1</td>\n",
-       "      <td>305623</td>\n",
-       "      <td>41208</td>\n",
-       "      <td>185.0</td>\n",
-       "      <td>-4.0</td>\n",
-       "      <td>9.75</td>\n",
-       "      <td>13.428571</td>\n",
-       "      <td>714.428571</td>\n",
-       "      <td>6.004624</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>4757.215218</td>\n",
-       "      <td>inf</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>143</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-05</td>\n",
-       "      <td>670</td>\n",
-       "      <td>18</td>\n",
-       "      <td>306293</td>\n",
-       "      <td>41226</td>\n",
-       "      <td>-258.0</td>\n",
-       "      <td>17.0</td>\n",
-       "      <td>9.25</td>\n",
-       "      <td>13.000000</td>\n",
-       "      <td>800.142857</td>\n",
-       "      <td>5.848527</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>4886.309798</td>\n",
-       "      <td>inf</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>144</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-06</td>\n",
-       "      <td>891</td>\n",
-       "      <td>14</td>\n",
-       "      <td>307184</td>\n",
-       "      <td>41240</td>\n",
-       "      <td>221.0</td>\n",
-       "      <td>-4.0</td>\n",
-       "      <td>9.50</td>\n",
-       "      <td>10.142857</td>\n",
-       "      <td>818.428571</td>\n",
-       "      <td>5.957892</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>4798.249763</td>\n",
-       "      <td>inf</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>145</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-07</td>\n",
-       "      <td>950</td>\n",
-       "      <td>18</td>\n",
-       "      <td>308134</td>\n",
-       "      <td>41258</td>\n",
-       "      <td>59.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>12.75</td>\n",
-       "      <td>12.714286</td>\n",
-       "      <td>833.285714</td>\n",
-       "      <td>8.206694</td>\n",
-       "      <td>9.273227</td>\n",
-       "      <td>3485.046367</td>\n",
-       "      <td>3084.263827</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>146</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-08</td>\n",
-       "      <td>871</td>\n",
-       "      <td>12</td>\n",
-       "      <td>309005</td>\n",
-       "      <td>41270</td>\n",
-       "      <td>-79.0</td>\n",
-       "      <td>-6.0</td>\n",
-       "      <td>15.50</td>\n",
-       "      <td>11.571429</td>\n",
-       "      <td>832.000000</td>\n",
-       "      <td>15.274379</td>\n",
-       "      <td>8.620615</td>\n",
-       "      <td>1873.167925</td>\n",
-       "      <td>3318.692768</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>147</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-09</td>\n",
-       "      <td>758</td>\n",
-       "      <td>3</td>\n",
-       "      <td>309763</td>\n",
-       "      <td>41273</td>\n",
-       "      <td>-113.0</td>\n",
-       "      <td>-9.0</td>\n",
-       "      <td>11.75</td>\n",
-       "      <td>10.142857</td>\n",
-       "      <td>830.142857</td>\n",
-       "      <td>9.759459</td>\n",
-       "      <td>6.991392</td>\n",
-       "      <td>2931.683481</td>\n",
-       "      <td>4092.273291</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>148</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-10</td>\n",
-       "      <td>1062</td>\n",
-       "      <td>5</td>\n",
-       "      <td>310825</td>\n",
-       "      <td>41278</td>\n",
-       "      <td>304.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>9.50</td>\n",
-       "      <td>10.142857</td>\n",
-       "      <td>875.714286</td>\n",
-       "      <td>7.544601</td>\n",
-       "      <td>6.991392</td>\n",
-       "      <td>3792.691701</td>\n",
-       "      <td>4092.769006</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>149</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-11</td>\n",
-       "      <td>816</td>\n",
-       "      <td>18</td>\n",
-       "      <td>311641</td>\n",
-       "      <td>41296</td>\n",
-       "      <td>-246.0</td>\n",
-       "      <td>13.0</td>\n",
-       "      <td>9.50</td>\n",
-       "      <td>12.571429</td>\n",
-       "      <td>859.714286</td>\n",
-       "      <td>7.544601</td>\n",
-       "      <td>10.565457</td>\n",
-       "      <td>3794.345420</td>\n",
-       "      <td>2709.572058</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>150</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-12</td>\n",
-       "      <td>1148</td>\n",
-       "      <td>13</td>\n",
-       "      <td>312789</td>\n",
-       "      <td>41309</td>\n",
-       "      <td>332.0</td>\n",
-       "      <td>-5.0</td>\n",
-       "      <td>9.75</td>\n",
-       "      <td>11.857143</td>\n",
-       "      <td>928.000000</td>\n",
-       "      <td>7.697094</td>\n",
-       "      <td>10.085523</td>\n",
-       "      <td>3720.350193</td>\n",
-       "      <td>2839.387976</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>151</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-13</td>\n",
-       "      <td>1009</td>\n",
-       "      <td>20</td>\n",
-       "      <td>313798</td>\n",
-       "      <td>41329</td>\n",
-       "      <td>-139.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>14.00</td>\n",
-       "      <td>12.714286</td>\n",
-       "      <td>944.857143</td>\n",
-       "      <td>12.368128</td>\n",
-       "      <td>10.612734</td>\n",
-       "      <td>2316.548351</td>\n",
-       "      <td>2699.658600</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>152</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-14</td>\n",
-       "      <td>1129</td>\n",
-       "      <td>18</td>\n",
-       "      <td>314927</td>\n",
-       "      <td>41347</td>\n",
-       "      <td>120.0</td>\n",
-       "      <td>-2.0</td>\n",
-       "      <td>17.25</td>\n",
-       "      <td>12.714286</td>\n",
-       "      <td>970.428571</td>\n",
-       "      <td>17.036469</td>\n",
-       "      <td>10.612734</td>\n",
-       "      <td>1682.593988</td>\n",
-       "      <td>2700.834230</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>153</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>1440</td>\n",
-       "      <td>11</td>\n",
-       "      <td>316367</td>\n",
-       "      <td>41358</td>\n",
-       "      <td>311.0</td>\n",
-       "      <td>-7.0</td>\n",
-       "      <td>15.50</td>\n",
-       "      <td>12.571429</td>\n",
-       "      <td>1051.714286</td>\n",
-       "      <td>15.062936</td>\n",
-       "      <td>10.481632</td>\n",
-       "      <td>1903.506790</td>\n",
-       "      <td>2735.338743</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>154</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>1077</td>\n",
-       "      <td>3</td>\n",
-       "      <td>317444</td>\n",
-       "      <td>41361</td>\n",
-       "      <td>-363.0</td>\n",
-       "      <td>-8.0</td>\n",
-       "      <td>13.00</td>\n",
-       "      <td>12.571429</td>\n",
-       "      <td>1097.285714</td>\n",
-       "      <td>10.440087</td>\n",
-       "      <td>10.481632</td>\n",
-       "      <td>2746.421476</td>\n",
-       "      <td>2735.537132</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>155</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>1040</td>\n",
-       "      <td>5</td>\n",
-       "      <td>318484</td>\n",
-       "      <td>41366</td>\n",
-       "      <td>-37.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>9.25</td>\n",
-       "      <td>12.571429</td>\n",
-       "      <td>1094.142857</td>\n",
-       "      <td>7.382256</td>\n",
-       "      <td>10.481632</td>\n",
-       "      <td>3884.352422</td>\n",
-       "      <td>2735.867781</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>156</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>713</td>\n",
-       "      <td>3</td>\n",
-       "      <td>319197</td>\n",
-       "      <td>41369</td>\n",
-       "      <td>-327.0</td>\n",
-       "      <td>-2.0</td>\n",
-       "      <td>5.50</td>\n",
-       "      <td>10.428571</td>\n",
-       "      <td>1079.428571</td>\n",
-       "      <td>4.716842</td>\n",
-       "      <td>8.114550</td>\n",
-       "      <td>6079.585100</td>\n",
-       "      <td>3534.098405</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>157</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>1089</td>\n",
-       "      <td>12</td>\n",
-       "      <td>320286</td>\n",
-       "      <td>41381</td>\n",
-       "      <td>376.0</td>\n",
-       "      <td>9.0</td>\n",
-       "      <td>5.75</td>\n",
-       "      <td>10.285714</td>\n",
-       "      <td>1071.000000</td>\n",
-       "      <td>4.820571</td>\n",
-       "      <td>8.022291</td>\n",
-       "      <td>5950.497778</td>\n",
-       "      <td>3575.774437</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                         dateRep  cases  deaths  cases_culm  deaths_culm  \\\n",
-       "since_threshold geoId                                                      \n",
-       "138             UK    2020-07-31    846       0      302301        41169   \n",
-       "139             UK    2020-08-01    880      20      303181        41189   \n",
-       "140             UK    2020-08-02    771      13      303952        41202   \n",
-       "141             UK    2020-08-03    743       5      304695        41207   \n",
-       "142             UK    2020-08-04    928       1      305623        41208   \n",
-       "143             UK    2020-08-05    670      18      306293        41226   \n",
-       "144             UK    2020-08-06    891      14      307184        41240   \n",
-       "145             UK    2020-08-07    950      18      308134        41258   \n",
-       "146             UK    2020-08-08    871      12      309005        41270   \n",
-       "147             UK    2020-08-09    758       3      309763        41273   \n",
-       "148             UK    2020-08-10   1062       5      310825        41278   \n",
-       "149             UK    2020-08-11    816      18      311641        41296   \n",
-       "150             UK    2020-08-12   1148      13      312789        41309   \n",
-       "151             UK    2020-08-13   1009      20      313798        41329   \n",
-       "152             UK    2020-08-14   1129      18      314927        41347   \n",
-       "153             UK    2020-08-15   1440      11      316367        41358   \n",
-       "154             UK    2020-08-16   1077       3      317444        41361   \n",
-       "155             UK    2020-08-17   1040       5      318484        41366   \n",
-       "156             UK    2020-08-18    713       3      319197        41369   \n",
-       "157             UK    2020-08-19   1089      12      320286        41381   \n",
-       "\n",
-       "                       cases_diff  deaths_diff  deaths_m4  deaths_m7  \\\n",
-       "since_threshold geoId                                                  \n",
-       "138             UK           83.0        -34.0      14.50  16.142857   \n",
-       "139             UK           34.0         20.0      18.75  14.428571   \n",
-       "140             UK         -109.0         -7.0      16.75  14.142857   \n",
-       "141             UK          -28.0         -8.0       9.50  13.714286   \n",
-       "142             UK          185.0         -4.0       9.75  13.428571   \n",
-       "143             UK         -258.0         17.0       9.25  13.000000   \n",
-       "144             UK          221.0         -4.0       9.50  10.142857   \n",
-       "145             UK           59.0          4.0      12.75  12.714286   \n",
-       "146             UK          -79.0         -6.0      15.50  11.571429   \n",
-       "147             UK         -113.0         -9.0      11.75  10.142857   \n",
-       "148             UK          304.0          2.0       9.50  10.142857   \n",
-       "149             UK         -246.0         13.0       9.50  12.571429   \n",
-       "150             UK          332.0         -5.0       9.75  11.857143   \n",
-       "151             UK         -139.0          7.0      14.00  12.714286   \n",
-       "152             UK          120.0         -2.0      17.25  12.714286   \n",
-       "153             UK          311.0         -7.0      15.50  12.571429   \n",
-       "154             UK         -363.0         -8.0      13.00  12.571429   \n",
-       "155             UK          -37.0          2.0       9.25  12.571429   \n",
-       "156             UK         -327.0         -2.0       5.50  10.428571   \n",
-       "157             UK          376.0          9.0       5.75  10.285714   \n",
-       "\n",
-       "                          cases_m7  deaths_g4  deaths_g7  doubling_time  \\\n",
-       "since_threshold geoId                                                     \n",
-       "138             UK      552.714286   0.000000   0.000000            inf   \n",
-       "139             UK      574.000000   0.000000   0.000000            inf   \n",
-       "140             UK      588.857143   0.000000   0.000000            inf   \n",
-       "141             UK      634.857143   0.000000   0.000000            inf   \n",
-       "142             UK      714.428571   6.004624   0.000000    4757.215218   \n",
-       "143             UK      800.142857   5.848527   0.000000    4886.309798   \n",
-       "144             UK      818.428571   5.957892   0.000000    4798.249763   \n",
-       "145             UK      833.285714   8.206694   9.273227    3485.046367   \n",
-       "146             UK      832.000000  15.274379   8.620615    1873.167925   \n",
-       "147             UK      830.142857   9.759459   6.991392    2931.683481   \n",
-       "148             UK      875.714286   7.544601   6.991392    3792.691701   \n",
-       "149             UK      859.714286   7.544601  10.565457    3794.345420   \n",
-       "150             UK      928.000000   7.697094  10.085523    3720.350193   \n",
-       "151             UK      944.857143  12.368128  10.612734    2316.548351   \n",
-       "152             UK      970.428571  17.036469  10.612734    1682.593988   \n",
-       "153             UK     1051.714286  15.062936  10.481632    1903.506790   \n",
-       "154             UK     1097.285714  10.440087  10.481632    2746.421476   \n",
-       "155             UK     1094.142857   7.382256  10.481632    3884.352422   \n",
-       "156             UK     1079.428571   4.716842   8.114550    6079.585100   \n",
-       "157             UK     1071.000000   4.820571   8.022291    5950.497778   \n",
-       "\n",
-       "                       doubling_time_7  \n",
-       "since_threshold geoId                   \n",
-       "138             UK                 inf  \n",
-       "139             UK                 inf  \n",
-       "140             UK                 inf  \n",
-       "141             UK                 inf  \n",
-       "142             UK                 inf  \n",
-       "143             UK                 inf  \n",
-       "144             UK                 inf  \n",
-       "145             UK         3084.263827  \n",
-       "146             UK         3318.692768  \n",
-       "147             UK         4092.273291  \n",
-       "148             UK         4092.769006  \n",
-       "149             UK         2709.572058  \n",
-       "150             UK         2839.387976  \n",
-       "151             UK         2699.658600  \n",
-       "152             UK         2700.834230  \n",
-       "153             UK         2735.338743  \n",
-       "154             UK         2735.537132  \n",
-       "155             UK         2735.867781  \n",
-       "156             UK         3534.098405  \n",
-       "157             UK         3575.774437  "
-      ]
-     },
-     "execution_count": 665,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_since_threshold.loc[(slice(None), ['UK']), :].tail(20)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 666,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "      <th>deaths_m4</th>\n",
-       "      <th>deaths_m7</th>\n",
-       "      <th>cases_m7</th>\n",
-       "      <th>deaths_g4</th>\n",
-       "      <th>deaths_g7</th>\n",
-       "      <th>doubling_time</th>\n",
-       "      <th>doubling_time_7</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>since_threshold</th>\n",
-       "      <th>geoId</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>142</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-07-30</td>\n",
-       "      <td>2789</td>\n",
-       "      <td>2</td>\n",
-       "      <td>285430</td>\n",
-       "      <td>28443</td>\n",
-       "      <td>758.0</td>\n",
-       "      <td>-3.0</td>\n",
-       "      <td>2.75</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>2180.571429</td>\n",
-       "      <td>2.514867</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>7839.801442</td>\n",
-       "      <td>inf</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>143</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-07-31</td>\n",
-       "      <td>3092</td>\n",
-       "      <td>2</td>\n",
-       "      <td>288522</td>\n",
-       "      <td>28445</td>\n",
-       "      <td>303.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.75</td>\n",
-       "      <td>1.857143</td>\n",
-       "      <td>2300.142857</td>\n",
-       "      <td>2.514867</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>7840.352682</td>\n",
-       "      <td>inf</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>144</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-01</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>288522</td>\n",
-       "      <td>28445</td>\n",
-       "      <td>-3092.0</td>\n",
-       "      <td>-2.0</td>\n",
-       "      <td>2.25</td>\n",
-       "      <td>1.857143</td>\n",
-       "      <td>2300.142857</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>inf</td>\n",
-       "      <td>inf</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>145</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-02</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>288522</td>\n",
-       "      <td>28445</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.00</td>\n",
-       "      <td>1.857143</td>\n",
-       "      <td>2300.142857</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>inf</td>\n",
-       "      <td>inf</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>146</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-03</td>\n",
-       "      <td>8532</td>\n",
-       "      <td>27</td>\n",
-       "      <td>297054</td>\n",
-       "      <td>28472</td>\n",
-       "      <td>8532.0</td>\n",
-       "      <td>27.0</td>\n",
-       "      <td>7.25</td>\n",
-       "      <td>5.428571</td>\n",
-       "      <td>2610.285714</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>inf</td>\n",
-       "      <td>inf</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>147</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-04</td>\n",
-       "      <td>5760</td>\n",
-       "      <td>26</td>\n",
-       "      <td>302814</td>\n",
-       "      <td>28498</td>\n",
-       "      <td>-2772.0</td>\n",
-       "      <td>-1.0</td>\n",
-       "      <td>13.25</td>\n",
-       "      <td>8.857143</td>\n",
-       "      <td>3172.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>inf</td>\n",
-       "      <td>inf</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>148</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-05</td>\n",
-       "      <td>2953</td>\n",
-       "      <td>1</td>\n",
-       "      <td>305767</td>\n",
-       "      <td>28499</td>\n",
-       "      <td>-2807.0</td>\n",
-       "      <td>-25.0</td>\n",
-       "      <td>13.50</td>\n",
-       "      <td>8.285714</td>\n",
-       "      <td>3303.714286</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>inf</td>\n",
-       "      <td>inf</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>149</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-06</td>\n",
-       "      <td>4088</td>\n",
-       "      <td>1</td>\n",
-       "      <td>309855</td>\n",
-       "      <td>28500</td>\n",
-       "      <td>1135.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>13.75</td>\n",
-       "      <td>8.142857</td>\n",
-       "      <td>3489.285714</td>\n",
-       "      <td>5.147357</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3838.179299</td>\n",
-       "      <td>inf</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>150</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-07</td>\n",
-       "      <td>4507</td>\n",
-       "      <td>3</td>\n",
-       "      <td>314362</td>\n",
-       "      <td>28503</td>\n",
-       "      <td>419.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>7.75</td>\n",
-       "      <td>8.285714</td>\n",
-       "      <td>3691.428571</td>\n",
-       "      <td>2.971828</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>6648.367576</td>\n",
-       "      <td>inf</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>151</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-08</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>314362</td>\n",
-       "      <td>28503</td>\n",
-       "      <td>-4507.0</td>\n",
-       "      <td>-3.0</td>\n",
-       "      <td>1.25</td>\n",
-       "      <td>8.285714</td>\n",
-       "      <td>3691.428571</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>inf</td>\n",
-       "      <td>inf</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>152</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-09</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>314362</td>\n",
-       "      <td>28503</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.00</td>\n",
-       "      <td>8.285714</td>\n",
-       "      <td>3691.428571</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>inf</td>\n",
-       "      <td>inf</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>153</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-10</td>\n",
-       "      <td>8618</td>\n",
-       "      <td>73</td>\n",
-       "      <td>322980</td>\n",
-       "      <td>28576</td>\n",
-       "      <td>8618.0</td>\n",
-       "      <td>73.0</td>\n",
-       "      <td>19.00</td>\n",
-       "      <td>14.857143</td>\n",
-       "      <td>3703.714286</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>inf</td>\n",
-       "      <td>inf</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>154</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-11</td>\n",
-       "      <td>3632</td>\n",
-       "      <td>5</td>\n",
-       "      <td>326612</td>\n",
-       "      <td>28581</td>\n",
-       "      <td>-4986.0</td>\n",
-       "      <td>-68.0</td>\n",
-       "      <td>19.50</td>\n",
-       "      <td>11.857143</td>\n",
-       "      <td>3399.714286</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>inf</td>\n",
-       "      <td>inf</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>155</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-12</td>\n",
-       "      <td>3172</td>\n",
-       "      <td>-2</td>\n",
-       "      <td>329784</td>\n",
-       "      <td>28579</td>\n",
-       "      <td>-460.0</td>\n",
-       "      <td>-7.0</td>\n",
-       "      <td>19.00</td>\n",
-       "      <td>11.428571</td>\n",
-       "      <td>3431.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>156</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-13</td>\n",
-       "      <td>7550</td>\n",
-       "      <td>26</td>\n",
-       "      <td>337334</td>\n",
-       "      <td>28605</td>\n",
-       "      <td>4378.0</td>\n",
-       "      <td>28.0</td>\n",
-       "      <td>25.50</td>\n",
-       "      <td>15.000000</td>\n",
-       "      <td>3925.571429</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>157</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-14</td>\n",
-       "      <td>5479</td>\n",
-       "      <td>12</td>\n",
-       "      <td>342813</td>\n",
-       "      <td>28617</td>\n",
-       "      <td>-2071.0</td>\n",
-       "      <td>-14.0</td>\n",
-       "      <td>10.25</td>\n",
-       "      <td>16.285714</td>\n",
-       "      <td>4064.428571</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>158</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>342813</td>\n",
-       "      <td>28617</td>\n",
-       "      <td>-5479.0</td>\n",
-       "      <td>-12.0</td>\n",
-       "      <td>9.00</td>\n",
-       "      <td>16.285714</td>\n",
-       "      <td>4064.428571</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>159</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>342813</td>\n",
-       "      <td>28617</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>9.50</td>\n",
-       "      <td>16.285714</td>\n",
-       "      <td>4064.428571</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>inf</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>160</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>16269</td>\n",
-       "      <td>29</td>\n",
-       "      <td>359082</td>\n",
-       "      <td>28646</td>\n",
-       "      <td>16269.0</td>\n",
-       "      <td>29.0</td>\n",
-       "      <td>10.25</td>\n",
-       "      <td>10.000000</td>\n",
-       "      <td>5157.428571</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>inf</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>161</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>5114</td>\n",
-       "      <td>24</td>\n",
-       "      <td>364196</td>\n",
-       "      <td>28670</td>\n",
-       "      <td>-11155.0</td>\n",
-       "      <td>-5.0</td>\n",
-       "      <td>13.25</td>\n",
-       "      <td>12.714286</td>\n",
-       "      <td>5369.142857</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>inf</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                         dateRep  cases  deaths  cases_culm  deaths_culm  \\\n",
-       "since_threshold geoId                                                      \n",
-       "142             ES    2020-07-30   2789       2      285430        28443   \n",
-       "143             ES    2020-07-31   3092       2      288522        28445   \n",
-       "144             ES    2020-08-01      0       0      288522        28445   \n",
-       "145             ES    2020-08-02      0       0      288522        28445   \n",
-       "146             ES    2020-08-03   8532      27      297054        28472   \n",
-       "147             ES    2020-08-04   5760      26      302814        28498   \n",
-       "148             ES    2020-08-05   2953       1      305767        28499   \n",
-       "149             ES    2020-08-06   4088       1      309855        28500   \n",
-       "150             ES    2020-08-07   4507       3      314362        28503   \n",
-       "151             ES    2020-08-08      0       0      314362        28503   \n",
-       "152             ES    2020-08-09      0       0      314362        28503   \n",
-       "153             ES    2020-08-10   8618      73      322980        28576   \n",
-       "154             ES    2020-08-11   3632       5      326612        28581   \n",
-       "155             ES    2020-08-12   3172      -2      329784        28579   \n",
-       "156             ES    2020-08-13   7550      26      337334        28605   \n",
-       "157             ES    2020-08-14   5479      12      342813        28617   \n",
-       "158             ES    2020-08-15      0       0      342813        28617   \n",
-       "159             ES    2020-08-16      0       0      342813        28617   \n",
-       "160             ES    2020-08-17  16269      29      359082        28646   \n",
-       "161             ES    2020-08-18   5114      24      364196        28670   \n",
-       "\n",
-       "                       cases_diff  deaths_diff  deaths_m4  deaths_m7  \\\n",
-       "since_threshold geoId                                                  \n",
-       "142             ES          758.0         -3.0       2.75   2.000000   \n",
-       "143             ES          303.0          0.0       2.75   1.857143   \n",
-       "144             ES        -3092.0         -2.0       2.25   1.857143   \n",
-       "145             ES            0.0          0.0       1.00   1.857143   \n",
-       "146             ES         8532.0         27.0       7.25   5.428571   \n",
-       "147             ES        -2772.0         -1.0      13.25   8.857143   \n",
-       "148             ES        -2807.0        -25.0      13.50   8.285714   \n",
-       "149             ES         1135.0          0.0      13.75   8.142857   \n",
-       "150             ES          419.0          2.0       7.75   8.285714   \n",
-       "151             ES        -4507.0         -3.0       1.25   8.285714   \n",
-       "152             ES            0.0          0.0       1.00   8.285714   \n",
-       "153             ES         8618.0         73.0      19.00  14.857143   \n",
-       "154             ES        -4986.0        -68.0      19.50  11.857143   \n",
-       "155             ES         -460.0         -7.0      19.00  11.428571   \n",
-       "156             ES         4378.0         28.0      25.50  15.000000   \n",
-       "157             ES        -2071.0        -14.0      10.25  16.285714   \n",
-       "158             ES        -5479.0        -12.0       9.00  16.285714   \n",
-       "159             ES            0.0          0.0       9.50  16.285714   \n",
-       "160             ES        16269.0         29.0      10.25  10.000000   \n",
-       "161             ES       -11155.0         -5.0      13.25  12.714286   \n",
-       "\n",
-       "                          cases_m7  deaths_g4  deaths_g7  doubling_time  \\\n",
-       "since_threshold geoId                                                     \n",
-       "142             ES     2180.571429   2.514867        0.0    7839.801442   \n",
-       "143             ES     2300.142857   2.514867        0.0    7840.352682   \n",
-       "144             ES     2300.142857   0.000000        0.0            inf   \n",
-       "145             ES     2300.142857   0.000000        0.0            inf   \n",
-       "146             ES     2610.285714   0.000000        0.0            inf   \n",
-       "147             ES     3172.000000   0.000000        0.0            inf   \n",
-       "148             ES     3303.714286   0.000000        0.0            inf   \n",
-       "149             ES     3489.285714   5.147357        0.0    3838.179299   \n",
-       "150             ES     3691.428571   2.971828        0.0    6648.367576   \n",
-       "151             ES     3691.428571   0.000000        0.0            inf   \n",
-       "152             ES     3691.428571   0.000000        0.0            inf   \n",
-       "153             ES     3703.714286   0.000000        0.0            inf   \n",
-       "154             ES     3399.714286   0.000000        0.0            inf   \n",
-       "155             ES     3431.000000        NaN        NaN            NaN   \n",
-       "156             ES     3925.571429        NaN        NaN            NaN   \n",
-       "157             ES     4064.428571        NaN        NaN            NaN   \n",
-       "158             ES     4064.428571        NaN        NaN            NaN   \n",
-       "159             ES     4064.428571   0.000000        NaN            inf   \n",
-       "160             ES     5157.428571   0.000000        NaN            inf   \n",
-       "161             ES     5369.142857   0.000000        NaN            inf   \n",
-       "\n",
-       "                       doubling_time_7  \n",
-       "since_threshold geoId                   \n",
-       "142             ES                 inf  \n",
-       "143             ES                 inf  \n",
-       "144             ES                 inf  \n",
-       "145             ES                 inf  \n",
-       "146             ES                 inf  \n",
-       "147             ES                 inf  \n",
-       "148             ES                 inf  \n",
-       "149             ES                 inf  \n",
-       "150             ES                 inf  \n",
-       "151             ES                 inf  \n",
-       "152             ES                 inf  \n",
-       "153             ES                 inf  \n",
-       "154             ES                 inf  \n",
-       "155             ES                 NaN  \n",
-       "156             ES                 NaN  \n",
-       "157             ES                 NaN  \n",
-       "158             ES                 NaN  \n",
-       "159             ES                 NaN  \n",
-       "160             ES                 NaN  \n",
-       "161             ES                 NaN  "
-      ]
-     },
-     "execution_count": 666,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_since_threshold.loc[(slice(None), ['ES']), :].tail(20)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Death projections"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 667,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "      <th>deaths_m4</th>\n",
-       "      <th>deaths_m7</th>\n",
-       "      <th>cases_m7</th>\n",
-       "      <th>deaths_g4</th>\n",
-       "      <th>deaths_g7</th>\n",
-       "      <th>doubling_time</th>\n",
-       "      <th>doubling_time_7</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>since_threshold</th>\n",
-       "      <th>geoId</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>143</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-05</td>\n",
-       "      <td>670</td>\n",
-       "      <td>18</td>\n",
-       "      <td>306293</td>\n",
-       "      <td>41226</td>\n",
-       "      <td>-258.0</td>\n",
-       "      <td>17.0</td>\n",
-       "      <td>9.25</td>\n",
-       "      <td>13.000000</td>\n",
-       "      <td>800.142857</td>\n",
-       "      <td>5.848527</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>4886.309798</td>\n",
-       "      <td>inf</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>144</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-06</td>\n",
-       "      <td>891</td>\n",
-       "      <td>14</td>\n",
-       "      <td>307184</td>\n",
-       "      <td>41240</td>\n",
-       "      <td>221.0</td>\n",
-       "      <td>-4.0</td>\n",
-       "      <td>9.50</td>\n",
-       "      <td>10.142857</td>\n",
-       "      <td>818.428571</td>\n",
-       "      <td>5.957892</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>4798.249763</td>\n",
-       "      <td>inf</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>145</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-07</td>\n",
-       "      <td>950</td>\n",
-       "      <td>18</td>\n",
-       "      <td>308134</td>\n",
-       "      <td>41258</td>\n",
-       "      <td>59.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>12.75</td>\n",
-       "      <td>12.714286</td>\n",
-       "      <td>833.285714</td>\n",
-       "      <td>8.206694</td>\n",
-       "      <td>9.273227</td>\n",
-       "      <td>3485.046367</td>\n",
-       "      <td>3084.263827</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>146</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-08</td>\n",
-       "      <td>871</td>\n",
-       "      <td>12</td>\n",
-       "      <td>309005</td>\n",
-       "      <td>41270</td>\n",
-       "      <td>-79.0</td>\n",
-       "      <td>-6.0</td>\n",
-       "      <td>15.50</td>\n",
-       "      <td>11.571429</td>\n",
-       "      <td>832.000000</td>\n",
-       "      <td>15.274379</td>\n",
-       "      <td>8.620615</td>\n",
-       "      <td>1873.167925</td>\n",
-       "      <td>3318.692768</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>147</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-09</td>\n",
-       "      <td>758</td>\n",
-       "      <td>3</td>\n",
-       "      <td>309763</td>\n",
-       "      <td>41273</td>\n",
-       "      <td>-113.0</td>\n",
-       "      <td>-9.0</td>\n",
-       "      <td>11.75</td>\n",
-       "      <td>10.142857</td>\n",
-       "      <td>830.142857</td>\n",
-       "      <td>9.759459</td>\n",
-       "      <td>6.991392</td>\n",
-       "      <td>2931.683481</td>\n",
-       "      <td>4092.273291</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>148</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-10</td>\n",
-       "      <td>1062</td>\n",
-       "      <td>5</td>\n",
-       "      <td>310825</td>\n",
-       "      <td>41278</td>\n",
-       "      <td>304.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>9.50</td>\n",
-       "      <td>10.142857</td>\n",
-       "      <td>875.714286</td>\n",
-       "      <td>7.544601</td>\n",
-       "      <td>6.991392</td>\n",
-       "      <td>3792.691701</td>\n",
-       "      <td>4092.769006</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>149</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-11</td>\n",
-       "      <td>816</td>\n",
-       "      <td>18</td>\n",
-       "      <td>311641</td>\n",
-       "      <td>41296</td>\n",
-       "      <td>-246.0</td>\n",
-       "      <td>13.0</td>\n",
-       "      <td>9.50</td>\n",
-       "      <td>12.571429</td>\n",
-       "      <td>859.714286</td>\n",
-       "      <td>7.544601</td>\n",
-       "      <td>10.565457</td>\n",
-       "      <td>3794.345420</td>\n",
-       "      <td>2709.572058</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>150</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-12</td>\n",
-       "      <td>1148</td>\n",
-       "      <td>13</td>\n",
-       "      <td>312789</td>\n",
-       "      <td>41309</td>\n",
-       "      <td>332.0</td>\n",
-       "      <td>-5.0</td>\n",
-       "      <td>9.75</td>\n",
-       "      <td>11.857143</td>\n",
-       "      <td>928.000000</td>\n",
-       "      <td>7.697094</td>\n",
-       "      <td>10.085523</td>\n",
-       "      <td>3720.350193</td>\n",
-       "      <td>2839.387976</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>151</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-13</td>\n",
-       "      <td>1009</td>\n",
-       "      <td>20</td>\n",
-       "      <td>313798</td>\n",
-       "      <td>41329</td>\n",
-       "      <td>-139.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>14.00</td>\n",
-       "      <td>12.714286</td>\n",
-       "      <td>944.857143</td>\n",
-       "      <td>12.368128</td>\n",
-       "      <td>10.612734</td>\n",
-       "      <td>2316.548351</td>\n",
-       "      <td>2699.658600</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>152</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-14</td>\n",
-       "      <td>1129</td>\n",
-       "      <td>18</td>\n",
-       "      <td>314927</td>\n",
-       "      <td>41347</td>\n",
-       "      <td>120.0</td>\n",
-       "      <td>-2.0</td>\n",
-       "      <td>17.25</td>\n",
-       "      <td>12.714286</td>\n",
-       "      <td>970.428571</td>\n",
-       "      <td>17.036469</td>\n",
-       "      <td>10.612734</td>\n",
-       "      <td>1682.593988</td>\n",
-       "      <td>2700.834230</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>153</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>1440</td>\n",
-       "      <td>11</td>\n",
-       "      <td>316367</td>\n",
-       "      <td>41358</td>\n",
-       "      <td>311.0</td>\n",
-       "      <td>-7.0</td>\n",
-       "      <td>15.50</td>\n",
-       "      <td>12.571429</td>\n",
-       "      <td>1051.714286</td>\n",
-       "      <td>15.062936</td>\n",
-       "      <td>10.481632</td>\n",
-       "      <td>1903.506790</td>\n",
-       "      <td>2735.338743</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>154</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>1077</td>\n",
-       "      <td>3</td>\n",
-       "      <td>317444</td>\n",
-       "      <td>41361</td>\n",
-       "      <td>-363.0</td>\n",
-       "      <td>-8.0</td>\n",
-       "      <td>13.00</td>\n",
-       "      <td>12.571429</td>\n",
-       "      <td>1097.285714</td>\n",
-       "      <td>10.440087</td>\n",
-       "      <td>10.481632</td>\n",
-       "      <td>2746.421476</td>\n",
-       "      <td>2735.537132</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>155</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>1040</td>\n",
-       "      <td>5</td>\n",
-       "      <td>318484</td>\n",
-       "      <td>41366</td>\n",
-       "      <td>-37.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>9.25</td>\n",
-       "      <td>12.571429</td>\n",
-       "      <td>1094.142857</td>\n",
-       "      <td>7.382256</td>\n",
-       "      <td>10.481632</td>\n",
-       "      <td>3884.352422</td>\n",
-       "      <td>2735.867781</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>156</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>713</td>\n",
-       "      <td>3</td>\n",
-       "      <td>319197</td>\n",
-       "      <td>41369</td>\n",
-       "      <td>-327.0</td>\n",
-       "      <td>-2.0</td>\n",
-       "      <td>5.50</td>\n",
-       "      <td>10.428571</td>\n",
-       "      <td>1079.428571</td>\n",
-       "      <td>4.716842</td>\n",
-       "      <td>8.114550</td>\n",
-       "      <td>6079.585100</td>\n",
-       "      <td>3534.098405</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>157</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>1089</td>\n",
-       "      <td>12</td>\n",
-       "      <td>320286</td>\n",
-       "      <td>41381</td>\n",
-       "      <td>376.0</td>\n",
-       "      <td>9.0</td>\n",
-       "      <td>5.75</td>\n",
-       "      <td>10.285714</td>\n",
-       "      <td>1071.000000</td>\n",
-       "      <td>4.820571</td>\n",
-       "      <td>8.022291</td>\n",
-       "      <td>5950.497778</td>\n",
-       "      <td>3575.774437</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                         dateRep  cases  deaths  cases_culm  deaths_culm  \\\n",
-       "since_threshold geoId                                                      \n",
-       "143             UK    2020-08-05    670      18      306293        41226   \n",
-       "144             UK    2020-08-06    891      14      307184        41240   \n",
-       "145             UK    2020-08-07    950      18      308134        41258   \n",
-       "146             UK    2020-08-08    871      12      309005        41270   \n",
-       "147             UK    2020-08-09    758       3      309763        41273   \n",
-       "148             UK    2020-08-10   1062       5      310825        41278   \n",
-       "149             UK    2020-08-11    816      18      311641        41296   \n",
-       "150             UK    2020-08-12   1148      13      312789        41309   \n",
-       "151             UK    2020-08-13   1009      20      313798        41329   \n",
-       "152             UK    2020-08-14   1129      18      314927        41347   \n",
-       "153             UK    2020-08-15   1440      11      316367        41358   \n",
-       "154             UK    2020-08-16   1077       3      317444        41361   \n",
-       "155             UK    2020-08-17   1040       5      318484        41366   \n",
-       "156             UK    2020-08-18    713       3      319197        41369   \n",
-       "157             UK    2020-08-19   1089      12      320286        41381   \n",
-       "\n",
-       "                       cases_diff  deaths_diff  deaths_m4  deaths_m7  \\\n",
-       "since_threshold geoId                                                  \n",
-       "143             UK         -258.0         17.0       9.25  13.000000   \n",
-       "144             UK          221.0         -4.0       9.50  10.142857   \n",
-       "145             UK           59.0          4.0      12.75  12.714286   \n",
-       "146             UK          -79.0         -6.0      15.50  11.571429   \n",
-       "147             UK         -113.0         -9.0      11.75  10.142857   \n",
-       "148             UK          304.0          2.0       9.50  10.142857   \n",
-       "149             UK         -246.0         13.0       9.50  12.571429   \n",
-       "150             UK          332.0         -5.0       9.75  11.857143   \n",
-       "151             UK         -139.0          7.0      14.00  12.714286   \n",
-       "152             UK          120.0         -2.0      17.25  12.714286   \n",
-       "153             UK          311.0         -7.0      15.50  12.571429   \n",
-       "154             UK         -363.0         -8.0      13.00  12.571429   \n",
-       "155             UK          -37.0          2.0       9.25  12.571429   \n",
-       "156             UK         -327.0         -2.0       5.50  10.428571   \n",
-       "157             UK          376.0          9.0       5.75  10.285714   \n",
-       "\n",
-       "                          cases_m7  deaths_g4  deaths_g7  doubling_time  \\\n",
-       "since_threshold geoId                                                     \n",
-       "143             UK      800.142857   5.848527   0.000000    4886.309798   \n",
-       "144             UK      818.428571   5.957892   0.000000    4798.249763   \n",
-       "145             UK      833.285714   8.206694   9.273227    3485.046367   \n",
-       "146             UK      832.000000  15.274379   8.620615    1873.167925   \n",
-       "147             UK      830.142857   9.759459   6.991392    2931.683481   \n",
-       "148             UK      875.714286   7.544601   6.991392    3792.691701   \n",
-       "149             UK      859.714286   7.544601  10.565457    3794.345420   \n",
-       "150             UK      928.000000   7.697094  10.085523    3720.350193   \n",
-       "151             UK      944.857143  12.368128  10.612734    2316.548351   \n",
-       "152             UK      970.428571  17.036469  10.612734    1682.593988   \n",
-       "153             UK     1051.714286  15.062936  10.481632    1903.506790   \n",
-       "154             UK     1097.285714  10.440087  10.481632    2746.421476   \n",
-       "155             UK     1094.142857   7.382256  10.481632    3884.352422   \n",
-       "156             UK     1079.428571   4.716842   8.114550    6079.585100   \n",
-       "157             UK     1071.000000   4.820571   8.022291    5950.497778   \n",
-       "\n",
-       "                       doubling_time_7  \n",
-       "since_threshold geoId                   \n",
-       "143             UK                 inf  \n",
-       "144             UK                 inf  \n",
-       "145             UK         3084.263827  \n",
-       "146             UK         3318.692768  \n",
-       "147             UK         4092.273291  \n",
-       "148             UK         4092.769006  \n",
-       "149             UK         2709.572058  \n",
-       "150             UK         2839.387976  \n",
-       "151             UK         2699.658600  \n",
-       "152             UK         2700.834230  \n",
-       "153             UK         2735.338743  \n",
-       "154             UK         2735.537132  \n",
-       "155             UK         2735.867781  \n",
-       "156             UK         3534.098405  \n",
-       "157             UK         3575.774437  "
-      ]
-     },
-     "execution_count": 667,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_since_threshold.loc[(slice(None), ['UK']), :].tail(15)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 668,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "175"
-      ]
-     },
-     "execution_count": 668,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "it_since_threshold = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['IT']), :]\n",
-    "s_end = it_since_threshold.index.max()[0]\n",
-    "s_end"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 669,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "158"
-      ]
-     },
-     "execution_count": 669,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "uk_projection = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), :]\n",
-    "uk_current_end = uk_projection.index.max()[0] + 1\n",
-    "# s_start = uk_projection.index.max()[0] + 1\n",
-    "uk_current_end"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 670,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "10.285714285714286"
-      ]
-     },
-     "execution_count": 670,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "current_uk_deaths_m7 = uk_projection[uk_projection.deaths_m7 >= 0].iloc[-1].deaths_m7\n",
-    "current_uk_deaths_m7"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 671,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "150"
-      ]
-     },
-     "execution_count": 671,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "it_since_threshold[it_since_threshold.deaths_m7 <= current_uk_deaths_m7].loc[60:].first_valid_index()[0]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 672,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "150"
-      ]
-     },
-     "execution_count": 672,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "s_start = it_since_threshold[it_since_threshold.deaths_m7 <= current_uk_deaths_m7].loc[60:].first_valid_index()[0]\n",
-    "s_start"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 673,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Timestamp('2020-05-25 00:00:00')"
-      ]
-     },
-     "execution_count": 673,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "s_start_date = data_since_threshold.loc[(89, 'IT'), 'dateRep']# .iloc[0]\n",
-    "s_start_date"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 674,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "25"
-      ]
-     },
-     "execution_count": 674,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "s_end - s_start"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 675,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "183"
-      ]
-     },
-     "execution_count": 675,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "uk_end = s_end - s_start + uk_current_end\n",
-    "uk_end"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 676,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>deaths_m7</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>since_threshold</th>\n",
-       "      <th>geoId</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>158</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>252</td>\n",
-       "      <td>5</td>\n",
-       "      <td>9.857143</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>159</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>274</td>\n",
-       "      <td>5</td>\n",
-       "      <td>8.571429</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>160</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>254</td>\n",
-       "      <td>5</td>\n",
-       "      <td>8.857143</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>161</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>168</td>\n",
-       "      <td>5</td>\n",
-       "      <td>7.714286</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>162</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>202</td>\n",
-       "      <td>11</td>\n",
-       "      <td>7.142857</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>163</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>288</td>\n",
-       "      <td>6</td>\n",
-       "      <td>6.714286</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>164</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>382</td>\n",
-       "      <td>3</td>\n",
-       "      <td>5.714286</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>165</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>379</td>\n",
-       "      <td>9</td>\n",
-       "      <td>6.285714</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>166</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>295</td>\n",
-       "      <td>5</td>\n",
-       "      <td>6.285714</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>167</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>238</td>\n",
-       "      <td>8</td>\n",
-       "      <td>6.714286</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>168</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>159</td>\n",
-       "      <td>12</td>\n",
-       "      <td>7.714286</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>169</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>190</td>\n",
-       "      <td>5</td>\n",
-       "      <td>6.857143</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>170</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>384</td>\n",
-       "      <td>10</td>\n",
-       "      <td>7.428571</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>171</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>401</td>\n",
-       "      <td>6</td>\n",
-       "      <td>7.857143</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>172</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>552</td>\n",
-       "      <td>3</td>\n",
-       "      <td>7.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>173</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>347</td>\n",
-       "      <td>13</td>\n",
-       "      <td>8.142857</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>174</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>463</td>\n",
-       "      <td>2</td>\n",
-       "      <td>7.285714</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>175</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>259</td>\n",
-       "      <td>4</td>\n",
-       "      <td>6.142857</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>176</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>412</td>\n",
-       "      <td>6</td>\n",
-       "      <td>6.285714</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>177</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>476</td>\n",
-       "      <td>10</td>\n",
-       "      <td>6.285714</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>178</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>522</td>\n",
-       "      <td>6</td>\n",
-       "      <td>6.285714</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>179</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>574</td>\n",
-       "      <td>3</td>\n",
-       "      <td>6.285714</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>180</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>629</td>\n",
-       "      <td>158</td>\n",
-       "      <td>27.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>181</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>477</td>\n",
-       "      <td>4</td>\n",
-       "      <td>27.285714</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>182</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>320</td>\n",
-       "      <td>4</td>\n",
-       "      <td>27.285714</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>183</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>401</td>\n",
-       "      <td>5</td>\n",
-       "      <td>27.142857</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                       cases  deaths  deaths_m7\n",
-       "since_threshold geoId                          \n",
-       "158             UK       252       5   9.857143\n",
-       "159             UK       274       5   8.571429\n",
-       "160             UK       254       5   8.857143\n",
-       "161             UK       168       5   7.714286\n",
-       "162             UK       202      11   7.142857\n",
-       "163             UK       288       6   6.714286\n",
-       "164             UK       382       3   5.714286\n",
-       "165             UK       379       9   6.285714\n",
-       "166             UK       295       5   6.285714\n",
-       "167             UK       238       8   6.714286\n",
-       "168             UK       159      12   7.714286\n",
-       "169             UK       190       5   6.857143\n",
-       "170             UK       384      10   7.428571\n",
-       "171             UK       401       6   7.857143\n",
-       "172             UK       552       3   7.000000\n",
-       "173             UK       347      13   8.142857\n",
-       "174             UK       463       2   7.285714\n",
-       "175             UK       259       4   6.142857\n",
-       "176             UK       412       6   6.285714\n",
-       "177             UK       476      10   6.285714\n",
-       "178             UK       522       6   6.285714\n",
-       "179             UK       574       3   6.285714\n",
-       "180             UK       629     158  27.000000\n",
-       "181             UK       477       4  27.285714\n",
-       "182             UK       320       4  27.285714\n",
-       "183             UK       401       5  27.142857"
-      ]
-     },
-     "execution_count": 676,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "proj = it_since_threshold.loc[(slice(s_start, s_end), slice(None)), ['cases', 'deaths', 'deaths_m7']]\n",
-    "ndiff = uk_current_end - s_start\n",
-    "proj.index = pd.MultiIndex.from_tuples([(n + ndiff, 'UK') for n, _ in proj.index], names=proj.index.names)\n",
-    "proj"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 677,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>deaths_m7</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>since_threshold</th>\n",
-       "      <th>geoId</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>142</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>230</td>\n",
-       "      <td>20</td>\n",
-       "      <td>13.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>143</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>231</td>\n",
-       "      <td>11</td>\n",
-       "      <td>12.857143</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>144</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>249</td>\n",
-       "      <td>14</td>\n",
-       "      <td>13.857143</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>145</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>218</td>\n",
-       "      <td>3</td>\n",
-       "      <td>13.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>146</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>190</td>\n",
-       "      <td>13</td>\n",
-       "      <td>13.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>147</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>128</td>\n",
-       "      <td>15</td>\n",
-       "      <td>12.714286</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>148</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>280</td>\n",
-       "      <td>9</td>\n",
-       "      <td>12.142857</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>149</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>306</td>\n",
-       "      <td>10</td>\n",
-       "      <td>10.714286</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>150</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>252</td>\n",
-       "      <td>5</td>\n",
-       "      <td>9.857143</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>151</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>274</td>\n",
-       "      <td>5</td>\n",
-       "      <td>8.571429</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>152</td>\n",
-       "      <td>IT</td>\n",
-       "      <td>254</td>\n",
-       "      <td>5</td>\n",
-       "      <td>8.857143</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                       cases  deaths  deaths_m7\n",
-       "since_threshold geoId                          \n",
-       "142             IT       230      20  13.000000\n",
-       "143             IT       231      11  12.857143\n",
-       "144             IT       249      14  13.857143\n",
-       "145             IT       218       3  13.000000\n",
-       "146             IT       190      13  13.000000\n",
-       "147             IT       128      15  12.714286\n",
-       "148             IT       280       9  12.142857\n",
-       "149             IT       306      10  10.714286\n",
-       "150             IT       252       5   9.857143\n",
-       "151             IT       274       5   8.571429\n",
-       "152             IT       254       5   8.857143"
-      ]
-     },
-     "execution_count": 677,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "it_since_threshold.loc[(slice(s_start - 8, s_start + 2), slice(None)), ['cases', 'deaths', 'deaths_m7']]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 678,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>deaths_m7</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>since_threshold</th>\n",
-       "      <th>geoId</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>153</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>1440</td>\n",
-       "      <td>11</td>\n",
-       "      <td>12.571429</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>154</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>1077</td>\n",
-       "      <td>3</td>\n",
-       "      <td>12.571429</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>155</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>1040</td>\n",
-       "      <td>5</td>\n",
-       "      <td>12.571429</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>156</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>713</td>\n",
-       "      <td>3</td>\n",
-       "      <td>10.428571</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>157</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>1089</td>\n",
-       "      <td>12</td>\n",
-       "      <td>10.285714</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                       cases  deaths  deaths_m7\n",
-       "since_threshold geoId                          \n",
-       "153             UK      1440      11  12.571429\n",
-       "154             UK      1077       3  12.571429\n",
-       "155             UK      1040       5  12.571429\n",
-       "156             UK       713       3  10.428571\n",
-       "157             UK      1089      12  10.285714"
-      ]
-     },
-     "execution_count": 678,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "uk_projection[['cases', 'deaths', 'deaths_m7']].tail()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 679,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# proj['deaths_m7'] = proj['deaths_m7'] + 20\n",
-    "# proj"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Projected deaths, UK following IT trend from now."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 680,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "41684"
-      ]
-     },
-     "execution_count": 680,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "uk_projection = uk_projection.append(proj, sort=True)\n",
-    "uk_projection.deaths.sum()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 681,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>cases</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>cases_m7</th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "      <th>deaths_g4</th>\n",
-       "      <th>deaths_g7</th>\n",
-       "      <th>deaths_m4</th>\n",
-       "      <th>deaths_m7</th>\n",
-       "      <th>doubling_time</th>\n",
-       "      <th>doubling_time_7</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>since_threshold</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>0</td>\n",
-       "      <td>478</td>\n",
-       "      <td>2244.0</td>\n",
-       "      <td>-6.0</td>\n",
-       "      <td>478.0</td>\n",
-       "      <td>2020-03-15</td>\n",
-       "      <td>19</td>\n",
-       "      <td>29.0</td>\n",
-       "      <td>18.0</td>\n",
-       "      <td>19.000000</td>\n",
-       "      <td>19.000000</td>\n",
-       "      <td>19.000000</td>\n",
-       "      <td>19.000000</td>\n",
-       "      <td>1.375551</td>\n",
-       "      <td>1.375551</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>1</td>\n",
-       "      <td>361</td>\n",
-       "      <td>2605.0</td>\n",
-       "      <td>-117.0</td>\n",
-       "      <td>419.5</td>\n",
-       "      <td>2020-03-16</td>\n",
-       "      <td>14</td>\n",
-       "      <td>43.0</td>\n",
-       "      <td>-5.0</td>\n",
-       "      <td>16.309506</td>\n",
-       "      <td>16.309506</td>\n",
-       "      <td>16.500000</td>\n",
-       "      <td>16.500000</td>\n",
-       "      <td>2.155513</td>\n",
-       "      <td>2.155513</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2</td>\n",
-       "      <td>442</td>\n",
-       "      <td>3047.0</td>\n",
-       "      <td>81.0</td>\n",
-       "      <td>427.0</td>\n",
-       "      <td>2020-03-17</td>\n",
-       "      <td>22</td>\n",
-       "      <td>65.0</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>18.020553</td>\n",
-       "      <td>18.020553</td>\n",
-       "      <td>18.333333</td>\n",
-       "      <td>18.333333</td>\n",
-       "      <td>2.832630</td>\n",
-       "      <td>2.832630</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>3</td>\n",
-       "      <td>611</td>\n",
-       "      <td>3658.0</td>\n",
-       "      <td>169.0</td>\n",
-       "      <td>473.0</td>\n",
-       "      <td>2020-03-18</td>\n",
-       "      <td>17</td>\n",
-       "      <td>82.0</td>\n",
-       "      <td>-5.0</td>\n",
-       "      <td>17.759810</td>\n",
-       "      <td>17.759810</td>\n",
-       "      <td>18.000000</td>\n",
-       "      <td>18.000000</td>\n",
-       "      <td>3.535633</td>\n",
-       "      <td>3.535633</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>4</td>\n",
-       "      <td>769</td>\n",
-       "      <td>4427.0</td>\n",
-       "      <td>158.0</td>\n",
-       "      <td>532.2</td>\n",
-       "      <td>2020-03-19</td>\n",
-       "      <td>34</td>\n",
-       "      <td>116.0</td>\n",
-       "      <td>17.0</td>\n",
-       "      <td>20.540908</td>\n",
-       "      <td>20.223040</td>\n",
-       "      <td>21.750000</td>\n",
-       "      <td>21.200000</td>\n",
-       "      <td>4.251548</td>\n",
-       "      <td>4.313209</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>179</td>\n",
-       "      <td>574</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>3</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>6.285714</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>180</td>\n",
-       "      <td>629</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>158</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>27.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>181</td>\n",
-       "      <td>477</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>4</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>27.285714</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>182</td>\n",
-       "      <td>320</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>4</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>27.285714</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>183</td>\n",
-       "      <td>401</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>5</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>27.142857</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>184 rows × 14 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                 cases  cases_culm  cases_diff  cases_m7    dateRep  deaths  \\\n",
-       "since_threshold                                                               \n",
-       "0                  478      2244.0        -6.0     478.0 2020-03-15      19   \n",
-       "1                  361      2605.0      -117.0     419.5 2020-03-16      14   \n",
-       "2                  442      3047.0        81.0     427.0 2020-03-17      22   \n",
-       "3                  611      3658.0       169.0     473.0 2020-03-18      17   \n",
-       "4                  769      4427.0       158.0     532.2 2020-03-19      34   \n",
-       "...                ...         ...         ...       ...        ...     ...   \n",
-       "179                574         NaN         NaN       NaN        NaT       3   \n",
-       "180                629         NaN         NaN       NaN        NaT     158   \n",
-       "181                477         NaN         NaN       NaN        NaT       4   \n",
-       "182                320         NaN         NaN       NaN        NaT       4   \n",
-       "183                401         NaN         NaN       NaN        NaT       5   \n",
-       "\n",
-       "                 deaths_culm  deaths_diff  deaths_g4  deaths_g7  deaths_m4  \\\n",
-       "since_threshold                                                              \n",
-       "0                       29.0         18.0  19.000000  19.000000  19.000000   \n",
-       "1                       43.0         -5.0  16.309506  16.309506  16.500000   \n",
-       "2                       65.0          8.0  18.020553  18.020553  18.333333   \n",
-       "3                       82.0         -5.0  17.759810  17.759810  18.000000   \n",
-       "4                      116.0         17.0  20.540908  20.223040  21.750000   \n",
-       "...                      ...          ...        ...        ...        ...   \n",
-       "179                      NaN          NaN        NaN        NaN        NaN   \n",
-       "180                      NaN          NaN        NaN        NaN        NaN   \n",
-       "181                      NaN          NaN        NaN        NaN        NaN   \n",
-       "182                      NaN          NaN        NaN        NaN        NaN   \n",
-       "183                      NaN          NaN        NaN        NaN        NaN   \n",
-       "\n",
-       "                 deaths_m7  doubling_time  doubling_time_7  \n",
-       "since_threshold                                             \n",
-       "0                19.000000       1.375551         1.375551  \n",
-       "1                16.500000       2.155513         2.155513  \n",
-       "2                18.333333       2.832630         2.832630  \n",
-       "3                18.000000       3.535633         3.535633  \n",
-       "4                21.200000       4.251548         4.313209  \n",
-       "...                    ...            ...              ...  \n",
-       "179               6.285714            NaN              NaN  \n",
-       "180              27.000000            NaN              NaN  \n",
-       "181              27.285714            NaN              NaN  \n",
-       "182              27.285714            NaN              NaN  \n",
-       "183              27.142857            NaN              NaN  \n",
-       "\n",
-       "[184 rows x 14 columns]"
-      ]
-     },
-     "execution_count": 681,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "uk_projection = uk_projection.droplevel(1)\n",
-    "uk_projection"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 682,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "18"
-      ]
-     },
-     "execution_count": 682,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "uk_projection.loc[152, 'deaths']"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Correction for cumulative deaths correction on 14 August"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 683,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# uk_projection.loc[152, 'deaths'] = 50"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 684,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>cases</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>cases_m7</th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "      <th>deaths_g4</th>\n",
-       "      <th>deaths_g7</th>\n",
-       "      <th>deaths_m4</th>\n",
-       "      <th>deaths_m7</th>\n",
-       "      <th>doubling_time</th>\n",
-       "      <th>doubling_time_7</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>since_threshold</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>138</td>\n",
-       "      <td>846</td>\n",
-       "      <td>302301.0</td>\n",
-       "      <td>83.0</td>\n",
-       "      <td>552.714286</td>\n",
-       "      <td>2020-07-31</td>\n",
-       "      <td>0</td>\n",
-       "      <td>41169.0</td>\n",
-       "      <td>-34.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>14.50</td>\n",
-       "      <td>16.142857</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>139</td>\n",
-       "      <td>880</td>\n",
-       "      <td>303181.0</td>\n",
-       "      <td>34.0</td>\n",
-       "      <td>574.000000</td>\n",
-       "      <td>2020-08-01</td>\n",
-       "      <td>20</td>\n",
-       "      <td>41189.0</td>\n",
-       "      <td>20.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>18.75</td>\n",
-       "      <td>14.428571</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>140</td>\n",
-       "      <td>771</td>\n",
-       "      <td>303952.0</td>\n",
-       "      <td>-109.0</td>\n",
-       "      <td>588.857143</td>\n",
-       "      <td>2020-08-02</td>\n",
-       "      <td>13</td>\n",
-       "      <td>41202.0</td>\n",
-       "      <td>-7.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>16.75</td>\n",
-       "      <td>14.142857</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>141</td>\n",
-       "      <td>743</td>\n",
-       "      <td>304695.0</td>\n",
-       "      <td>-28.0</td>\n",
-       "      <td>634.857143</td>\n",
-       "      <td>2020-08-03</td>\n",
-       "      <td>5</td>\n",
-       "      <td>41207.0</td>\n",
-       "      <td>-8.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>9.50</td>\n",
-       "      <td>13.714286</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>142</td>\n",
-       "      <td>928</td>\n",
-       "      <td>305623.0</td>\n",
-       "      <td>185.0</td>\n",
-       "      <td>714.428571</td>\n",
-       "      <td>2020-08-04</td>\n",
-       "      <td>1</td>\n",
-       "      <td>41208.0</td>\n",
-       "      <td>-4.0</td>\n",
-       "      <td>6.004624</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>9.75</td>\n",
-       "      <td>13.428571</td>\n",
-       "      <td>4757.215218</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>143</td>\n",
-       "      <td>670</td>\n",
-       "      <td>306293.0</td>\n",
-       "      <td>-258.0</td>\n",
-       "      <td>800.142857</td>\n",
-       "      <td>2020-08-05</td>\n",
-       "      <td>18</td>\n",
-       "      <td>41226.0</td>\n",
-       "      <td>17.0</td>\n",
-       "      <td>5.848527</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>9.25</td>\n",
-       "      <td>13.000000</td>\n",
-       "      <td>4886.309798</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>144</td>\n",
-       "      <td>891</td>\n",
-       "      <td>307184.0</td>\n",
-       "      <td>221.0</td>\n",
-       "      <td>818.428571</td>\n",
-       "      <td>2020-08-06</td>\n",
-       "      <td>14</td>\n",
-       "      <td>41240.0</td>\n",
-       "      <td>-4.0</td>\n",
-       "      <td>5.957892</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>9.50</td>\n",
-       "      <td>10.142857</td>\n",
-       "      <td>4798.249763</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>145</td>\n",
-       "      <td>950</td>\n",
-       "      <td>308134.0</td>\n",
-       "      <td>59.0</td>\n",
-       "      <td>833.285714</td>\n",
-       "      <td>2020-08-07</td>\n",
-       "      <td>18</td>\n",
-       "      <td>41258.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>8.206694</td>\n",
-       "      <td>9.273227</td>\n",
-       "      <td>12.75</td>\n",
-       "      <td>12.714286</td>\n",
-       "      <td>3485.046367</td>\n",
-       "      <td>3084.263827</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>146</td>\n",
-       "      <td>871</td>\n",
-       "      <td>309005.0</td>\n",
-       "      <td>-79.0</td>\n",
-       "      <td>832.000000</td>\n",
-       "      <td>2020-08-08</td>\n",
-       "      <td>12</td>\n",
-       "      <td>41270.0</td>\n",
-       "      <td>-6.0</td>\n",
-       "      <td>15.274379</td>\n",
-       "      <td>8.620615</td>\n",
-       "      <td>15.50</td>\n",
-       "      <td>11.571429</td>\n",
-       "      <td>1873.167925</td>\n",
-       "      <td>3318.692768</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>147</td>\n",
-       "      <td>758</td>\n",
-       "      <td>309763.0</td>\n",
-       "      <td>-113.0</td>\n",
-       "      <td>830.142857</td>\n",
-       "      <td>2020-08-09</td>\n",
-       "      <td>3</td>\n",
-       "      <td>41273.0</td>\n",
-       "      <td>-9.0</td>\n",
-       "      <td>9.759459</td>\n",
-       "      <td>6.991392</td>\n",
-       "      <td>11.75</td>\n",
-       "      <td>10.142857</td>\n",
-       "      <td>2931.683481</td>\n",
-       "      <td>4092.273291</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>148</td>\n",
-       "      <td>1062</td>\n",
-       "      <td>310825.0</td>\n",
-       "      <td>304.0</td>\n",
-       "      <td>875.714286</td>\n",
-       "      <td>2020-08-10</td>\n",
-       "      <td>5</td>\n",
-       "      <td>41278.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>7.544601</td>\n",
-       "      <td>6.991392</td>\n",
-       "      <td>9.50</td>\n",
-       "      <td>10.142857</td>\n",
-       "      <td>3792.691701</td>\n",
-       "      <td>4092.769006</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>149</td>\n",
-       "      <td>816</td>\n",
-       "      <td>311641.0</td>\n",
-       "      <td>-246.0</td>\n",
-       "      <td>859.714286</td>\n",
-       "      <td>2020-08-11</td>\n",
-       "      <td>18</td>\n",
-       "      <td>41296.0</td>\n",
-       "      <td>13.0</td>\n",
-       "      <td>7.544601</td>\n",
-       "      <td>10.565457</td>\n",
-       "      <td>9.50</td>\n",
-       "      <td>12.571429</td>\n",
-       "      <td>3794.345420</td>\n",
-       "      <td>2709.572058</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>150</td>\n",
-       "      <td>1148</td>\n",
-       "      <td>312789.0</td>\n",
-       "      <td>332.0</td>\n",
-       "      <td>928.000000</td>\n",
-       "      <td>2020-08-12</td>\n",
-       "      <td>13</td>\n",
-       "      <td>41309.0</td>\n",
-       "      <td>-5.0</td>\n",
-       "      <td>7.697094</td>\n",
-       "      <td>10.085523</td>\n",
-       "      <td>9.75</td>\n",
-       "      <td>11.857143</td>\n",
-       "      <td>3720.350193</td>\n",
-       "      <td>2839.387976</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>151</td>\n",
-       "      <td>1009</td>\n",
-       "      <td>313798.0</td>\n",
-       "      <td>-139.0</td>\n",
-       "      <td>944.857143</td>\n",
-       "      <td>2020-08-13</td>\n",
-       "      <td>20</td>\n",
-       "      <td>41329.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>12.368128</td>\n",
-       "      <td>10.612734</td>\n",
-       "      <td>14.00</td>\n",
-       "      <td>12.714286</td>\n",
-       "      <td>2316.548351</td>\n",
-       "      <td>2699.658600</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>152</td>\n",
-       "      <td>1129</td>\n",
-       "      <td>314927.0</td>\n",
-       "      <td>120.0</td>\n",
-       "      <td>970.428571</td>\n",
-       "      <td>2020-08-14</td>\n",
-       "      <td>18</td>\n",
-       "      <td>41347.0</td>\n",
-       "      <td>-2.0</td>\n",
-       "      <td>17.036469</td>\n",
-       "      <td>10.612734</td>\n",
-       "      <td>17.25</td>\n",
-       "      <td>12.714286</td>\n",
-       "      <td>1682.593988</td>\n",
-       "      <td>2700.834230</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>153</td>\n",
-       "      <td>1440</td>\n",
-       "      <td>316367.0</td>\n",
-       "      <td>311.0</td>\n",
-       "      <td>1051.714286</td>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>11</td>\n",
-       "      <td>41358.0</td>\n",
-       "      <td>-7.0</td>\n",
-       "      <td>15.062936</td>\n",
-       "      <td>10.481632</td>\n",
-       "      <td>15.50</td>\n",
-       "      <td>12.571429</td>\n",
-       "      <td>1903.506790</td>\n",
-       "      <td>2735.338743</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>154</td>\n",
-       "      <td>1077</td>\n",
-       "      <td>317444.0</td>\n",
-       "      <td>-363.0</td>\n",
-       "      <td>1097.285714</td>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>3</td>\n",
-       "      <td>41361.0</td>\n",
-       "      <td>-8.0</td>\n",
-       "      <td>10.440087</td>\n",
-       "      <td>10.481632</td>\n",
-       "      <td>13.00</td>\n",
-       "      <td>12.571429</td>\n",
-       "      <td>2746.421476</td>\n",
-       "      <td>2735.537132</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>155</td>\n",
-       "      <td>1040</td>\n",
-       "      <td>318484.0</td>\n",
-       "      <td>-37.0</td>\n",
-       "      <td>1094.142857</td>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>5</td>\n",
-       "      <td>41366.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>7.382256</td>\n",
-       "      <td>10.481632</td>\n",
-       "      <td>9.25</td>\n",
-       "      <td>12.571429</td>\n",
-       "      <td>3884.352422</td>\n",
-       "      <td>2735.867781</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>156</td>\n",
-       "      <td>713</td>\n",
-       "      <td>319197.0</td>\n",
-       "      <td>-327.0</td>\n",
-       "      <td>1079.428571</td>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>3</td>\n",
-       "      <td>41369.0</td>\n",
-       "      <td>-2.0</td>\n",
-       "      <td>4.716842</td>\n",
-       "      <td>8.114550</td>\n",
-       "      <td>5.50</td>\n",
-       "      <td>10.428571</td>\n",
-       "      <td>6079.585100</td>\n",
-       "      <td>3534.098405</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>157</td>\n",
-       "      <td>1089</td>\n",
-       "      <td>320286.0</td>\n",
-       "      <td>376.0</td>\n",
-       "      <td>1071.000000</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>12</td>\n",
-       "      <td>41381.0</td>\n",
-       "      <td>9.0</td>\n",
-       "      <td>4.820571</td>\n",
-       "      <td>8.022291</td>\n",
-       "      <td>5.75</td>\n",
-       "      <td>10.285714</td>\n",
-       "      <td>5950.497778</td>\n",
-       "      <td>3575.774437</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>158</td>\n",
-       "      <td>252</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>5</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>8.142857</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>159</td>\n",
-       "      <td>274</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>5</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>6.285714</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>160</td>\n",
-       "      <td>254</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>5</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>5.428571</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>161</td>\n",
-       "      <td>168</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>5</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>5.714286</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>162</td>\n",
-       "      <td>202</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>11</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>6.571429</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>163</td>\n",
-       "      <td>288</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>6</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>7.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                 cases  cases_culm  cases_diff     cases_m7    dateRep  \\\n",
-       "since_threshold                                                          \n",
-       "138                846    302301.0        83.0   552.714286 2020-07-31   \n",
-       "139                880    303181.0        34.0   574.000000 2020-08-01   \n",
-       "140                771    303952.0      -109.0   588.857143 2020-08-02   \n",
-       "141                743    304695.0       -28.0   634.857143 2020-08-03   \n",
-       "142                928    305623.0       185.0   714.428571 2020-08-04   \n",
-       "143                670    306293.0      -258.0   800.142857 2020-08-05   \n",
-       "144                891    307184.0       221.0   818.428571 2020-08-06   \n",
-       "145                950    308134.0        59.0   833.285714 2020-08-07   \n",
-       "146                871    309005.0       -79.0   832.000000 2020-08-08   \n",
-       "147                758    309763.0      -113.0   830.142857 2020-08-09   \n",
-       "148               1062    310825.0       304.0   875.714286 2020-08-10   \n",
-       "149                816    311641.0      -246.0   859.714286 2020-08-11   \n",
-       "150               1148    312789.0       332.0   928.000000 2020-08-12   \n",
-       "151               1009    313798.0      -139.0   944.857143 2020-08-13   \n",
-       "152               1129    314927.0       120.0   970.428571 2020-08-14   \n",
-       "153               1440    316367.0       311.0  1051.714286 2020-08-15   \n",
-       "154               1077    317444.0      -363.0  1097.285714 2020-08-16   \n",
-       "155               1040    318484.0       -37.0  1094.142857 2020-08-17   \n",
-       "156                713    319197.0      -327.0  1079.428571 2020-08-18   \n",
-       "157               1089    320286.0       376.0  1071.000000 2020-08-19   \n",
-       "158                252         NaN         NaN          NaN        NaT   \n",
-       "159                274         NaN         NaN          NaN        NaT   \n",
-       "160                254         NaN         NaN          NaN        NaT   \n",
-       "161                168         NaN         NaN          NaN        NaT   \n",
-       "162                202         NaN         NaN          NaN        NaT   \n",
-       "163                288         NaN         NaN          NaN        NaT   \n",
-       "\n",
-       "                 deaths  deaths_culm  deaths_diff  deaths_g4  deaths_g7  \\\n",
-       "since_threshold                                                           \n",
-       "138                   0      41169.0        -34.0   0.000000   0.000000   \n",
-       "139                  20      41189.0         20.0   0.000000   0.000000   \n",
-       "140                  13      41202.0         -7.0   0.000000   0.000000   \n",
-       "141                   5      41207.0         -8.0   0.000000   0.000000   \n",
-       "142                   1      41208.0         -4.0   6.004624   0.000000   \n",
-       "143                  18      41226.0         17.0   5.848527   0.000000   \n",
-       "144                  14      41240.0         -4.0   5.957892   0.000000   \n",
-       "145                  18      41258.0          4.0   8.206694   9.273227   \n",
-       "146                  12      41270.0         -6.0  15.274379   8.620615   \n",
-       "147                   3      41273.0         -9.0   9.759459   6.991392   \n",
-       "148                   5      41278.0          2.0   7.544601   6.991392   \n",
-       "149                  18      41296.0         13.0   7.544601  10.565457   \n",
-       "150                  13      41309.0         -5.0   7.697094  10.085523   \n",
-       "151                  20      41329.0          7.0  12.368128  10.612734   \n",
-       "152                  18      41347.0         -2.0  17.036469  10.612734   \n",
-       "153                  11      41358.0         -7.0  15.062936  10.481632   \n",
-       "154                   3      41361.0         -8.0  10.440087  10.481632   \n",
-       "155                   5      41366.0          2.0   7.382256  10.481632   \n",
-       "156                   3      41369.0         -2.0   4.716842   8.114550   \n",
-       "157                  12      41381.0          9.0   4.820571   8.022291   \n",
-       "158                   5          NaN          NaN        NaN        NaN   \n",
-       "159                   5          NaN          NaN        NaN        NaN   \n",
-       "160                   5          NaN          NaN        NaN        NaN   \n",
-       "161                   5          NaN          NaN        NaN        NaN   \n",
-       "162                  11          NaN          NaN        NaN        NaN   \n",
-       "163                   6          NaN          NaN        NaN        NaN   \n",
-       "\n",
-       "                 deaths_m4  deaths_m7  doubling_time  doubling_time_7  \n",
-       "since_threshold                                                        \n",
-       "138                  14.50  16.142857            NaN              NaN  \n",
-       "139                  18.75  14.428571            NaN              NaN  \n",
-       "140                  16.75  14.142857            NaN              NaN  \n",
-       "141                   9.50  13.714286            NaN              NaN  \n",
-       "142                   9.75  13.428571    4757.215218              NaN  \n",
-       "143                   9.25  13.000000    4886.309798              NaN  \n",
-       "144                   9.50  10.142857    4798.249763              NaN  \n",
-       "145                  12.75  12.714286    3485.046367      3084.263827  \n",
-       "146                  15.50  11.571429    1873.167925      3318.692768  \n",
-       "147                  11.75  10.142857    2931.683481      4092.273291  \n",
-       "148                   9.50  10.142857    3792.691701      4092.769006  \n",
-       "149                   9.50  12.571429    3794.345420      2709.572058  \n",
-       "150                   9.75  11.857143    3720.350193      2839.387976  \n",
-       "151                  14.00  12.714286    2316.548351      2699.658600  \n",
-       "152                  17.25  12.714286    1682.593988      2700.834230  \n",
-       "153                  15.50  12.571429    1903.506790      2735.338743  \n",
-       "154                  13.00  12.571429    2746.421476      2735.537132  \n",
-       "155                   9.25  12.571429    3884.352422      2735.867781  \n",
-       "156                   5.50  10.428571    6079.585100      3534.098405  \n",
-       "157                   5.75  10.285714    5950.497778      3575.774437  \n",
-       "158                    NaN   8.142857            NaN              NaN  \n",
-       "159                    NaN   6.285714            NaN              NaN  \n",
-       "160                    NaN   5.428571            NaN              NaN  \n",
-       "161                    NaN   5.714286            NaN              NaN  \n",
-       "162                    NaN   6.571429            NaN              NaN  \n",
-       "163                    NaN   7.000000            NaN              NaN  "
-      ]
-     },
-     "execution_count": 684,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "uk_projection['deaths_m7'] = uk_projection['deaths'].transform(lambda x: x.rolling(7, 1).mean())\n",
-    "uk_projection.loc[(uk_current_end - 20):(uk_current_end + 5)]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 685,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>cases</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>cases_m7</th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "      <th>deaths_g4</th>\n",
-       "      <th>deaths_g7</th>\n",
-       "      <th>deaths_m4</th>\n",
-       "      <th>deaths_m7</th>\n",
-       "      <th>doubling_time</th>\n",
-       "      <th>doubling_time_7</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>since_threshold</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
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-       "      <td>NaN</td>\n",
-       "      <td>6.285714</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>178</td>\n",
-       "      <td>522</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>6</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>6.285714</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>179</td>\n",
-       "      <td>574</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>3</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>6.285714</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>180</td>\n",
-       "      <td>629</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>158</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>27.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>181</td>\n",
-       "      <td>477</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>4</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>27.285714</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>182</td>\n",
-       "      <td>320</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>4</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>27.285714</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>183</td>\n",
-       "      <td>401</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>5</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>27.142857</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                 cases  cases_culm  cases_diff     cases_m7    dateRep  \\\n",
-       "since_threshold                                                          \n",
-       "153               1440    316367.0       311.0  1051.714286 2020-08-15   \n",
-       "154               1077    317444.0      -363.0  1097.285714 2020-08-16   \n",
-       "155               1040    318484.0       -37.0  1094.142857 2020-08-17   \n",
-       "156                713    319197.0      -327.0  1079.428571 2020-08-18   \n",
-       "157               1089    320286.0       376.0  1071.000000 2020-08-19   \n",
-       "158                252         NaN         NaN          NaN        NaT   \n",
-       "159                274         NaN         NaN          NaN        NaT   \n",
-       "160                254         NaN         NaN          NaN        NaT   \n",
-       "161                168         NaN         NaN          NaN        NaT   \n",
-       "162                202         NaN         NaN          NaN        NaT   \n",
-       "163                288         NaN         NaN          NaN        NaT   \n",
-       "164                382         NaN         NaN          NaN        NaT   \n",
-       "165                379         NaN         NaN          NaN        NaT   \n",
-       "166                295         NaN         NaN          NaN        NaT   \n",
-       "167                238         NaN         NaN          NaN        NaT   \n",
-       "168                159         NaN         NaN          NaN        NaT   \n",
-       "169                190         NaN         NaN          NaN        NaT   \n",
-       "170                384         NaN         NaN          NaN        NaT   \n",
-       "171                401         NaN         NaN          NaN        NaT   \n",
-       "172                552         NaN         NaN          NaN        NaT   \n",
-       "173                347         NaN         NaN          NaN        NaT   \n",
-       "174                463         NaN         NaN          NaN        NaT   \n",
-       "175                259         NaN         NaN          NaN        NaT   \n",
-       "176                412         NaN         NaN          NaN        NaT   \n",
-       "177                476         NaN         NaN          NaN        NaT   \n",
-       "178                522         NaN         NaN          NaN        NaT   \n",
-       "179                574         NaN         NaN          NaN        NaT   \n",
-       "180                629         NaN         NaN          NaN        NaT   \n",
-       "181                477         NaN         NaN          NaN        NaT   \n",
-       "182                320         NaN         NaN          NaN        NaT   \n",
-       "183                401         NaN         NaN          NaN        NaT   \n",
-       "\n",
-       "                 deaths  deaths_culm  deaths_diff  deaths_g4  deaths_g7  \\\n",
-       "since_threshold                                                           \n",
-       "153                  11      41358.0         -7.0  15.062936  10.481632   \n",
-       "154                   3      41361.0         -8.0  10.440087  10.481632   \n",
-       "155                   5      41366.0          2.0   7.382256  10.481632   \n",
-       "156                   3      41369.0         -2.0   4.716842   8.114550   \n",
-       "157                  12      41381.0          9.0   4.820571   8.022291   \n",
-       "158                   5          NaN          NaN        NaN        NaN   \n",
-       "159                   5          NaN          NaN        NaN        NaN   \n",
-       "160                   5          NaN          NaN        NaN        NaN   \n",
-       "161                   5          NaN          NaN        NaN        NaN   \n",
-       "162                  11          NaN          NaN        NaN        NaN   \n",
-       "163                   6          NaN          NaN        NaN        NaN   \n",
-       "164                   3          NaN          NaN        NaN        NaN   \n",
-       "165                   9          NaN          NaN        NaN        NaN   \n",
-       "166                   5          NaN          NaN        NaN        NaN   \n",
-       "167                   8          NaN          NaN        NaN        NaN   \n",
-       "168                  12          NaN          NaN        NaN        NaN   \n",
-       "169                   5          NaN          NaN        NaN        NaN   \n",
-       "170                  10          NaN          NaN        NaN        NaN   \n",
-       "171                   6          NaN          NaN        NaN        NaN   \n",
-       "172                   3          NaN          NaN        NaN        NaN   \n",
-       "173                  13          NaN          NaN        NaN        NaN   \n",
-       "174                   2          NaN          NaN        NaN        NaN   \n",
-       "175                   4          NaN          NaN        NaN        NaN   \n",
-       "176                   6          NaN          NaN        NaN        NaN   \n",
-       "177                  10          NaN          NaN        NaN        NaN   \n",
-       "178                   6          NaN          NaN        NaN        NaN   \n",
-       "179                   3          NaN          NaN        NaN        NaN   \n",
-       "180                 158          NaN          NaN        NaN        NaN   \n",
-       "181                   4          NaN          NaN        NaN        NaN   \n",
-       "182                   4          NaN          NaN        NaN        NaN   \n",
-       "183                   5          NaN          NaN        NaN        NaN   \n",
-       "\n",
-       "                 deaths_m4  deaths_m7  doubling_time  doubling_time_7  \n",
-       "since_threshold                                                        \n",
-       "153                  15.50  12.571429    1903.506790      2735.338743  \n",
-       "154                  13.00  12.571429    2746.421476      2735.537132  \n",
-       "155                   9.25  12.571429    3884.352422      2735.867781  \n",
-       "156                   5.50  10.428571    6079.585100      3534.098405  \n",
-       "157                   5.75  10.285714    5950.497778      3575.774437  \n",
-       "158                    NaN   8.142857            NaN              NaN  \n",
-       "159                    NaN   6.285714            NaN              NaN  \n",
-       "160                    NaN   5.428571            NaN              NaN  \n",
-       "161                    NaN   5.714286            NaN              NaN  \n",
-       "162                    NaN   6.571429            NaN              NaN  \n",
-       "163                    NaN   7.000000            NaN              NaN  \n",
-       "164                    NaN   5.714286            NaN              NaN  \n",
-       "165                    NaN   6.285714            NaN              NaN  \n",
-       "166                    NaN   6.285714            NaN              NaN  \n",
-       "167                    NaN   6.714286            NaN              NaN  \n",
-       "168                    NaN   7.714286            NaN              NaN  \n",
-       "169                    NaN   6.857143            NaN              NaN  \n",
-       "170                    NaN   7.428571            NaN              NaN  \n",
-       "171                    NaN   7.857143            NaN              NaN  \n",
-       "172                    NaN   7.000000            NaN              NaN  \n",
-       "173                    NaN   8.142857            NaN              NaN  \n",
-       "174                    NaN   7.285714            NaN              NaN  \n",
-       "175                    NaN   6.142857            NaN              NaN  \n",
-       "176                    NaN   6.285714            NaN              NaN  \n",
-       "177                    NaN   6.285714            NaN              NaN  \n",
-       "178                    NaN   6.285714            NaN              NaN  \n",
-       "179                    NaN   6.285714            NaN              NaN  \n",
-       "180                    NaN  27.000000            NaN              NaN  \n",
-       "181                    NaN  27.285714            NaN              NaN  \n",
-       "182                    NaN  27.285714            NaN              NaN  \n",
-       "183                    NaN  27.142857            NaN              NaN  "
-      ]
-     },
-     "execution_count": 685,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "uk_projection.loc[(uk_current_end - 5):]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 686,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f03f55d86d0>"
-      ]
-     },
-     "execution_count": 686,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "uk_projection.deaths_m7.plot()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 687,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>deaths_m7</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>since_threshold</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>158</td>\n",
-       "      <td>252</td>\n",
-       "      <td>5</td>\n",
-       "      <td>9.857143</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>159</td>\n",
-       "      <td>274</td>\n",
-       "      <td>5</td>\n",
-       "      <td>8.571429</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>160</td>\n",
-       "      <td>254</td>\n",
-       "      <td>5</td>\n",
-       "      <td>8.857143</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>161</td>\n",
-       "      <td>168</td>\n",
-       "      <td>5</td>\n",
-       "      <td>7.714286</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>162</td>\n",
-       "      <td>202</td>\n",
-       "      <td>11</td>\n",
-       "      <td>7.142857</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>163</td>\n",
-       "      <td>288</td>\n",
-       "      <td>6</td>\n",
-       "      <td>6.714286</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>164</td>\n",
-       "      <td>382</td>\n",
-       "      <td>3</td>\n",
-       "      <td>5.714286</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>165</td>\n",
-       "      <td>379</td>\n",
-       "      <td>9</td>\n",
-       "      <td>6.285714</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>166</td>\n",
-       "      <td>295</td>\n",
-       "      <td>5</td>\n",
-       "      <td>6.285714</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>167</td>\n",
-       "      <td>238</td>\n",
-       "      <td>8</td>\n",
-       "      <td>6.714286</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>168</td>\n",
-       "      <td>159</td>\n",
-       "      <td>12</td>\n",
-       "      <td>7.714286</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>169</td>\n",
-       "      <td>190</td>\n",
-       "      <td>5</td>\n",
-       "      <td>6.857143</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>170</td>\n",
-       "      <td>384</td>\n",
-       "      <td>10</td>\n",
-       "      <td>7.428571</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>171</td>\n",
-       "      <td>401</td>\n",
-       "      <td>6</td>\n",
-       "      <td>7.857143</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>172</td>\n",
-       "      <td>552</td>\n",
-       "      <td>3</td>\n",
-       "      <td>7.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>173</td>\n",
-       "      <td>347</td>\n",
-       "      <td>13</td>\n",
-       "      <td>8.142857</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>174</td>\n",
-       "      <td>463</td>\n",
-       "      <td>2</td>\n",
-       "      <td>7.285714</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>175</td>\n",
-       "      <td>259</td>\n",
-       "      <td>4</td>\n",
-       "      <td>6.142857</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>176</td>\n",
-       "      <td>412</td>\n",
-       "      <td>6</td>\n",
-       "      <td>6.285714</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>177</td>\n",
-       "      <td>476</td>\n",
-       "      <td>10</td>\n",
-       "      <td>6.285714</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>178</td>\n",
-       "      <td>522</td>\n",
-       "      <td>6</td>\n",
-       "      <td>6.285714</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>179</td>\n",
-       "      <td>574</td>\n",
-       "      <td>3</td>\n",
-       "      <td>6.285714</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>180</td>\n",
-       "      <td>629</td>\n",
-       "      <td>158</td>\n",
-       "      <td>27.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>181</td>\n",
-       "      <td>477</td>\n",
-       "      <td>4</td>\n",
-       "      <td>27.285714</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>182</td>\n",
-       "      <td>320</td>\n",
-       "      <td>4</td>\n",
-       "      <td>27.285714</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>183</td>\n",
-       "      <td>401</td>\n",
-       "      <td>5</td>\n",
-       "      <td>27.142857</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                 cases  deaths  deaths_m7\n",
-       "since_threshold                          \n",
-       "158                252       5   9.857143\n",
-       "159                274       5   8.571429\n",
-       "160                254       5   8.857143\n",
-       "161                168       5   7.714286\n",
-       "162                202      11   7.142857\n",
-       "163                288       6   6.714286\n",
-       "164                382       3   5.714286\n",
-       "165                379       9   6.285714\n",
-       "166                295       5   6.285714\n",
-       "167                238       8   6.714286\n",
-       "168                159      12   7.714286\n",
-       "169                190       5   6.857143\n",
-       "170                384      10   7.428571\n",
-       "171                401       6   7.857143\n",
-       "172                552       3   7.000000\n",
-       "173                347      13   8.142857\n",
-       "174                463       2   7.285714\n",
-       "175                259       4   6.142857\n",
-       "176                412       6   6.285714\n",
-       "177                476      10   6.285714\n",
-       "178                522       6   6.285714\n",
-       "179                574       3   6.285714\n",
-       "180                629     158  27.000000\n",
-       "181                477       4  27.285714\n",
-       "182                320       4  27.285714\n",
-       "183                401       5  27.142857"
-      ]
-     },
-     "execution_count": 687,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "proj.droplevel(level=1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 688,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths_m7[COUNTRIES_CORE].plot()\n",
-    "# uk_projection['deaths_m7'].plot(figsize=(10, 6), title=\"Deaths per day, 7 day moving average\", label=\"Projection\", style='--', ax=ax)\n",
-    "proj.droplevel(level=1)['deaths_m7'].plot(figsize=(10, 6), title=\"Deaths per day, 7 day moving average\", label=\"Projection\", style='--', ax=ax)\n",
-    "ax.set_xlabel(f\"Days since {DEATH_COUNT_THRESHOLD} deaths\")\n",
-    "for c in COUNTRIES_CORE:\n",
-    "    lvi = deaths_m7[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = c)\n",
-    "plt.savefig('covid_deaths_per_day_7.png') "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 689,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "35399"
-      ]
-     },
-     "execution_count": 689,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "it_since_threshold.deaths.sum()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Excess deaths calculation"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 690,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "({'start_date': '2020-03-20 00:00:00',\n",
-       "  'end_date': '2020-07-03 00:00:00',\n",
-       "  'excess_deaths': 64733.6},\n",
-       " 1)"
-      ]
-     },
-     "execution_count": 690,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "with open('excess_deaths.json') as f:\n",
-    "    excess_deaths_data = json.load(f)\n",
-    "    \n",
-    "with open('excess_death_accuracy.json') as f:\n",
-    "    excess_death_accuracy = json.load(f)\n",
-    "    \n",
-    "excess_deaths_data, excess_death_accuracy"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 691,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# excess_deaths_upto = '2020-05-08'\n",
-    "# excess_deaths = 54500"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 692,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "excess_deaths_upto = excess_deaths_data['end_date']\n",
-    "excess_deaths = excess_deaths_data['excess_deaths']"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Recorded deaths in period where ONS has reported total deaths"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 693,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "40532"
-      ]
-     },
-     "execution_count": 693,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "ons_reported_deaths = base_data.loc['UK'][:excess_deaths_upto]['deaths'].sum()\n",
-    "ons_reported_deaths"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 694,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'2020-07-03 00:00:00'"
-      ]
-     },
-     "execution_count": 694,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "excess_deaths_upto"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Correction for deaths total correction on 14 August"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 695,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ons_unreported_deaths_data = base_data.loc['UK'][excess_deaths_upto:].iloc[1:]['deaths']\n",
-    "# ons_unreported_deaths_data['2020-08-14'] = 50"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 696,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "849"
-      ]
-     },
-     "execution_count": 696,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "ons_unreported_deaths = ons_unreported_deaths_data.sum()\n",
-    "ons_unreported_deaths"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 697,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "849"
-      ]
-     },
-     "execution_count": 697,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "scaled_ons_unreported_deaths = ons_unreported_deaths * excess_death_accuracy\n",
-    "scaled_ons_unreported_deaths"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 698,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "65582.6"
-      ]
-     },
-     "execution_count": 698,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "uk_deaths_to_date = excess_deaths + scaled_ons_unreported_deaths\n",
-    "uk_deaths_to_date"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 699,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# data_since_threshold.loc[(slice(None), 'UK'), :][data_since_threshold.dateRep == excess_deaths_data['end_date']]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 700,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "      <th>deaths_m4</th>\n",
-       "      <th>deaths_m7</th>\n",
-       "      <th>cases_m7</th>\n",
-       "      <th>deaths_g4</th>\n",
-       "      <th>deaths_g7</th>\n",
-       "      <th>doubling_time</th>\n",
-       "      <th>doubling_time_7</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>since_threshold</th>\n",
-       "      <th>geoId</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>110</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-07-03</td>\n",
-       "      <td>651</td>\n",
-       "      <td>41</td>\n",
-       "      <td>285539</td>\n",
-       "      <td>40532</td>\n",
-       "      <td>34.0</td>\n",
-       "      <td>-56.0</td>\n",
-       "      <td>53.0</td>\n",
-       "      <td>51.428571</td>\n",
-       "      <td>640.714286</td>\n",
-       "      <td>45.868305</td>\n",
-       "      <td>45.798566</td>\n",
-       "      <td>612.853155</td>\n",
-       "      <td>613.785835</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                         dateRep  cases  deaths  cases_culm  deaths_culm  \\\n",
-       "since_threshold geoId                                                      \n",
-       "110             UK    2020-07-03    651      41      285539        40532   \n",
-       "\n",
-       "                       cases_diff  deaths_diff  deaths_m4  deaths_m7  \\\n",
-       "since_threshold geoId                                                  \n",
-       "110             UK           34.0        -56.0       53.0  51.428571   \n",
-       "\n",
-       "                         cases_m7  deaths_g4  deaths_g7  doubling_time  \\\n",
-       "since_threshold geoId                                                    \n",
-       "110             UK     640.714286  45.868305  45.798566     612.853155   \n",
-       "\n",
-       "                       doubling_time_7  \n",
-       "since_threshold geoId                   \n",
-       "110             UK          613.785835  "
-      ]
-     },
-     "execution_count": 700,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_since_threshold[data_since_threshold.dateRep == excess_deaths_data['end_date']].loc[(slice(None), 'UK'), :]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 701,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "111"
-      ]
-     },
-     "execution_count": 701,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "ons_unreported_start = data_since_threshold[data_since_threshold.dateRep == excess_deaths_data['end_date']].loc[(slice(None), 'UK'), :].first_valid_index()[0] + 1\n",
-    "ons_unreported_start"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 702,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1162"
-      ]
-     },
-     "execution_count": 702,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "unreported_projected_deaths = uk_projection.loc[ons_unreported_start:].deaths.sum()\n",
-    "unreported_projected_deaths"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 703,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1162"
-      ]
-     },
-     "execution_count": 703,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "unreported_projected_deaths_scaled = unreported_projected_deaths * excess_death_accuracy\n",
-    "unreported_projected_deaths_scaled"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 704,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "398"
-      ]
-     },
-     "execution_count": 704,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "uk_projection.loc[(s_start):].deaths.sum()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 705,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "65980.6"
-      ]
-     },
-     "execution_count": 705,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "deaths_actual_projected_scaled = uk_deaths_to_date + uk_projection.loc[(s_start):].deaths.sum() * excess_death_accuracy\n",
-    "deaths_actual_projected_scaled"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 706,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# excess_deaths / reported_deaths"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "True deaths to date, if we follow the scaling of excess deaths over reported deaths so far."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 707,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "41381"
-      ]
-     },
-     "execution_count": 707,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "uk_covid_deaths = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), 'deaths_culm'].iloc[-1]\n",
-    "uk_covid_deaths"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 708,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# uk_covid_deaths_scaled = excess_deaths + unreported_deaths * excess_death_accuracy\n",
-    "# uk_covid_deaths_scaled"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 709,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['IT']), 'dateRep'].iloc[-1] + pd.Timedelta(s_end - s_start, unit='days')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 710,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), 'dateRep'].iloc[-1].strftime(\"%Y-%m-%d\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 711,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# uk_covid_deaths * excess_deaths / reported_deaths"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 712,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# uk_projection.deaths.sum() * excess_deaths / reported_deaths"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 713,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# data_since_threshold.loc[(slice(None), 'FR'), :]\n",
-    "# data_since_threshold[data_since_threshold.dateRep == '2020-05-18'].loc[(slice(None), 'FR'), :]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## School reopenings"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 714,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "school_reopenings = {\n",
-    "    'ES': {'date': '2020-05-18'},\n",
-    "    'FR': {'date': '2020-05-18'}, # some areas only\n",
-    "#     'IT': {'date': '2020-09-01'},\n",
-    "    # 'IE': {'date': '2020-09-01'},\n",
-    "    'DE': {'date': '2020-05-04'},\n",
-    "    'UK': {'date': '2020-06-01'}\n",
-    "}"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 715,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(49, 'DE')"
-      ]
-     },
-     "execution_count": 715,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_since_threshold[data_since_threshold.dateRep == '2020-05-04'].loc[(slice(None), ['DE']), :].first_valid_index()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 716,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "134.57142857142858"
-      ]
-     },
-     "execution_count": 716,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_since_threshold[data_since_threshold.dateRep == '2020-05-04'].loc[(slice(None), ['DE']), :].iloc[0].deaths_m7"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 717,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "{'ES': {'date': '2020-05-18',\n",
-       "  'since_threshold': 69,\n",
-       "  'deaths_m7': 137.85714285714286},\n",
-       " 'FR': {'date': '2020-05-18',\n",
-       "  'since_threshold': 70,\n",
-       "  'deaths_m7': 190.14285714285714},\n",
-       " 'DE': {'date': '2020-05-04',\n",
-       "  'since_threshold': 49,\n",
-       "  'deaths_m7': 134.57142857142858},\n",
-       " 'UK': {'date': '2020-06-01',\n",
-       "  'since_threshold': 78,\n",
-       "  'deaths_m7': 212.57142857142858}}"
-      ]
-     },
-     "execution_count": 717,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "for cID in school_reopenings:\n",
-    "    dst_in = data_since_threshold[data_since_threshold.dateRep == (school_reopenings[cID]['date'])].loc[(slice(None), [cID]), :]\n",
-    "    dst_i = dst_in.first_valid_index()\n",
-    "    dst_n = dst_in.iloc[0].deaths_m7\n",
-    "    school_reopenings[cID]['since_threshold'] = dst_i[0]\n",
-    "    school_reopenings[cID]['deaths_m7'] = dst_n\n",
-    "school_reopenings"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 718,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 1080x648 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths_m7[COUNTRIES_CORE].plot(figsize=(15, 9), title=\"Deaths per day, 7 day moving average\")\n",
-    "# uk_projection.deaths_m7.plot(ax=ax)\n",
-    "for c in COUNTRIES_CORE:\n",
-    "    lvi = deaths_m7[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = f\"{c}: {deaths_m7[c][lvi]:.0f}\")\n",
-    "    if c in school_reopenings:\n",
-    "        marker_col = [l for l in ax.lines if l.get_label() == c][0].get_color()\n",
-    "        ax.plot(school_reopenings[c]['since_threshold'], school_reopenings[c]['deaths_m7'], '*', \n",
-    "                markersize=18, markerfacecolor=marker_col, markeredgecolor=marker_col)\n",
-    "        ax.text(x = school_reopenings[c]['since_threshold'] + 1, y = school_reopenings[c]['deaths_m7'], \n",
-    "                s = f\"{school_reopenings[c]['date']}: {school_reopenings[c]['deaths_m7']:.0f}\")\n",
-    "plt.savefig('school_reopenings.png')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 719,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# ax = deaths_m7[COUNTRIES_CORE].plot(figsize=(15, 9), title=\"Deaths per day, 7 day moving average\",\n",
-    "#                                    xlim=(46, 91), ylim=(0, 400))\n",
-    "# # uk_projection.deaths_m7.plot(ax=ax)\n",
-    "# for c in COUNTRIES_CORE:\n",
-    "#     lvi = deaths_m7[c].last_valid_index()\n",
-    "#     ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = f\"{c}: {deaths_m7[c][lvi]:.0f}\", fontsize=14)\n",
-    "#     if c in school_reopenings:\n",
-    "#         marker_col = [l for l in ax.lines if l.get_label() == c][0].get_color()\n",
-    "#         ax.plot(school_reopenings[c]['since_threshold'], school_reopenings[c]['deaths_m7'], '*', \n",
-    "#                 markersize=18, markerfacecolor=marker_col, markeredgecolor=marker_col)\n",
-    "#         ax.text(x = school_reopenings[c]['since_threshold'] + 1, y = school_reopenings[c]['deaths_m7'], \n",
-    "#                 s = f\"{school_reopenings[c]['date']}: {school_reopenings[c]['deaths_m7']:.0f}\",\n",
-    "#                 fontsize=14)\n",
-    "# plt.savefig('school_reopenings_detail.png')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Lockdown graphs"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 720,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "lockdown_dates = {\n",
-    "    'ES': { 'part_start': {'date': '2020-03-14'}\n",
-    "          , 'full_start': {'date': '2020-03-15'}\n",
-    "          , 'part_finish': {'date': '2020-05-18'}\n",
-    "          },\n",
-    "    'FR': { 'part_start': {'date': '2020-03-13'}\n",
-    "          , 'full_start': {'date': '2020-03-17'}\n",
-    "          , 'part_finish': {'date': '2020-05-11'}\n",
-    "          },\n",
-    "    'IT': { 'part_start': {'date': '2020-03-08'}\n",
-    "          , 'full_start': {'date': '2020-03-10'}\n",
-    "          , 'part_finish': {'date': '2020-05-04'}\n",
-    "          },\n",
-    "    'DE': { #'part_start': {'date': '2020-03-13'}\n",
-    "          'full_start': {'date': '2020-03-22'}\n",
-    "          , 'part_finish': {'date': '2020-05-06'}\n",
-    "          },\n",
-    "    'UK': { 'part_start': {'date': '2020-03-23'}\n",
-    "          , 'full_start': {'date': '2020-03-23'}\n",
-    "          , 'part_finish': {'date': '2020-05-31'}\n",
-    "          },\n",
-    "    'IE': { #'part_start': {'date': '2020-03-12'}\n",
-    "          'full_start': {'date': '2020-03-27'}\n",
-    "          , 'part_finish': {'date': '2020-05-18'}\n",
-    "          },\n",
-    "}"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 721,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "{'ES': {'part_start': {'date': '2020-03-14',\n",
-       "   'since_threshold': 4,\n",
-       "   'deaths_m7': 23.2,\n",
-       "   'cases_m7': 1222.8},\n",
-       "  'full_start': {'date': '2020-03-15',\n",
-       "   'since_threshold': 5,\n",
-       "   'deaths_m7': 21.833333333333332,\n",
-       "   'cases_m7': 1376.3333333333333},\n",
-       "  'part_finish': {'date': '2020-05-18',\n",
-       "   'since_threshold': 69,\n",
-       "   'deaths_m7': 137.85714285714286,\n",
-       "   'cases_m7': 548.0}},\n",
-       " 'FR': {'part_start': {'date': '2020-03-13',\n",
-       "   'since_threshold': 4,\n",
-       "   'deaths_m7': 10.2,\n",
-       "   'cases_m7': 432.0},\n",
-       "  'full_start': {'date': '2020-03-17',\n",
-       "   'since_threshold': 8,\n",
-       "   'deaths_m7': 16.857142857142858,\n",
-       "   'cases_m7': 745.8571428571429},\n",
-       "  'part_finish': {'date': '2020-05-11',\n",
-       "   'since_threshold': 63,\n",
-       "   'deaths_m7': 212.14285714285714,\n",
-       "   'cases_m7': 1110.857142857143}},\n",
-       " 'IT': {'part_start': {'date': '2020-03-08',\n",
-       "   'since_threshold': 11,\n",
-       "   'deaths_m7': 29.142857142857142,\n",
-       "   'cases_m7': 679.2857142857143},\n",
-       "  'full_start': {'date': '2020-03-10',\n",
-       "   'since_threshold': 13,\n",
-       "   'deaths_m7': 58.857142857142854,\n",
-       "   'cases_m7': 1019.4285714285714},\n",
-       "  'part_finish': {'date': '2020-05-04',\n",
-       "   'since_threshold': 68,\n",
-       "   'deaths_m7': 320.0,\n",
-       "   'cases_m7': 1863.142857142857}},\n",
-       " 'DE': {'full_start': {'date': '2020-03-22',\n",
-       "   'since_threshold': 6,\n",
-       "   'deaths_m7': 8.428571428571429,\n",
-       "   'cases_m7': 2524.0},\n",
-       "  'part_finish': {'date': '2020-05-06',\n",
-       "   'since_threshold': 51,\n",
-       "   'deaths_m7': 125.85714285714286,\n",
-       "   'cases_m7': 1036.5714285714287}},\n",
-       " 'UK': {'part_start': {'date': '2020-03-23',\n",
-       "   'since_threshold': 8,\n",
-       "   'deaths_m7': 35.0,\n",
-       "   'cases_m7': 904.1428571428571},\n",
-       "  'full_start': {'date': '2020-03-23',\n",
-       "   'since_threshold': 8,\n",
-       "   'deaths_m7': 35.0,\n",
-       "   'cases_m7': 904.1428571428571},\n",
-       "  'part_finish': {'date': '2020-05-31',\n",
-       "   'since_threshold': 77,\n",
-       "   'deaths_m7': 258.14285714285717,\n",
-       "   'cases_m7': 1615.5714285714287}},\n",
-       " 'IE': {'full_start': {'date': '2020-03-27',\n",
-       "   'since_threshold': 0,\n",
-       "   'deaths_m7': 10.0,\n",
-       "   'cases_m7': 255.0},\n",
-       "  'part_finish': {'date': '2020-05-18',\n",
-       "   'since_threshold': 52,\n",
-       "   'deaths_m7': 12.142857142857142,\n",
-       "   'cases_m7': 159.42857142857142}}}"
-      ]
-     },
-     "execution_count": 721,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "for cID in lockdown_dates:\n",
-    "    for phase in lockdown_dates[cID]:\n",
-    "        dst_in = data_since_threshold[data_since_threshold.dateRep == (lockdown_dates[cID][phase]['date'])].loc[(slice(None), [cID]), :]\n",
-    "        dst_i = dst_in.first_valid_index()\n",
-    "        dst_n = dst_in.iloc[0].deaths_m7\n",
-    "        dst_c = dst_in.iloc[0].cases_m7\n",
-    "        lockdown_dates[cID][phase]['since_threshold'] = dst_i[0]\n",
-    "        lockdown_dates[cID][phase]['deaths_m7'] = dst_n\n",
-    "        lockdown_dates[cID][phase]['cases_m7'] = dst_c\n",
-    "\n",
-    "lockdown_dates"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 722,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 1080x648 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths_m7[COUNTRIES_CORE].plot(figsize=(15, 9), title=\"Deaths per day, 7 day moving averagee, with lockdown dates\")\n",
-    "ax.set_xlabel(f\"Days since {DEATH_COUNT_THRESHOLD} deaths\")\n",
-    "# uk_projection.deaths_m7.plot(ax=ax)\n",
-    "for c in COUNTRIES_CORE:\n",
-    "    lvi = deaths_m7[c].last_valid_index()\n",
-    "    if c != 'UK':\n",
-    "        ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = f\"{c}: {deaths_m7[c][lvi]:.0f}\")\n",
-    "    if c in lockdown_dates:\n",
-    "        for phase in lockdown_dates[c]:\n",
-    "            marker_col = [l for l in ax.lines if l.get_label() == c][0].get_color()\n",
-    "            ax.plot(lockdown_dates[c][phase]['since_threshold'], lockdown_dates[c][phase]['deaths_m7'], '*',\n",
-    "                    markersize=18, markerfacecolor=marker_col, markeredgecolor=marker_col)\n",
-    "            if 'start' not in phase:\n",
-    "                ax.text(x = lockdown_dates[c][phase]['since_threshold'] + 1, y = lockdown_dates[c][phase]['deaths_m7'], \n",
-    "                        s = f\"{lockdown_dates[c][phase]['date']}: {lockdown_dates[c][phase]['deaths_m7']:.0f}\")\n",
-    "# plt.savefig('school_reopenings.png')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 723,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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M7FfyBkY6LugsdVGX3Gb2kKRnnXNvNHwyAADqhhZTAAgzfhfm/yfpodDr2JxzJc65vmFUlP5c3jVvVVuhwp6ZdTKz4WYWYWa95bUs1Vd35AZzILmdcxdRlAIAwlW1I2YCABqfmfWVd+3nV/K6JIYlM1so7/q/yfs5CEzQYiQ9ICld3k9qzJHXbTjcNdXcAADUiK68AAAAAIBA0ZUXAAAAABAoClMAAAAAQKDC+hrTdu3aubS0tKBjAAAAAEAgFi9evNU51z7oHA0trAvTtLQ0LVq0KOgYAAAAABAIM1sTdIbGQFdeAAAAAECgKEwBAAAAAIGiMAUAAAAABCqsrzEFAAAAgH0pLS1Vdna2ioqKgo6y3+Li4pSamqro6OigowSCwhQAAABAk5adna2kpCSlpaXJzIKOU2fOOW3btk3Z2dlKT08POk4g6MoLAAAAoEkrKipSSkpKkyxKJcnMlJKS0qRbfA8UhSkAAACAJq+pFqWVmnr+A0VhCgAAAAD74YYbbtBdd931o/mrV6/WgAEDAkjUdFGYAgAAAAACxeBHAAAAAFqcP/3pT3ryySfVtWtXtWvXTkcccYQmTpyoadOmacuWLWrVqpX+/e9/q0+fPlqzZo0uuOACbdmyRe3bt9fMmTPVrVu3Pfa3ePFiXXDBBWrVqpVGjBgR0Fk1XbSYAgAAAGhRFi1apOeff15ffvmlXnjhBS1atEiSNHXqVP3973/X4sWLddddd+nSSy+VJP3617/WlClTtHTpUp1zzjn67W9/+6N9nn/++br33nv18ccfN+q5NBe0mAIAAABoUT744AONHz9e8fHxkqTTTjtNRUVF+uijj3TGGWfsXq+4uFiS9PHHH+uFF16QJE2ePFlXXXXVHvvLzc3Vjh07dNxxx+1e57XXXmuMU2k2aDEFAABArUVGRiojI2P37fbbb5ckvfzyyxo8eLAGDRqkfv366YEHHqjTvsaNG7d7/oUXXqhBgwbpsMMO0+mnn678/Pzdy5555hn169dP/fv319lnn717/tVXX60BAwZowIABevrpp+vxjNEcOed+NK+iokJt2rTRkiVLdt8yMzP3un3VEXSdcy1+VN0DRWEKAACAWouPj9/jg/v06dNVWlqqqVOnav78+frqq6/05ZdfatSoUXXa17x583bPv/vuu/XVV19p6dKl6tatm+677z5J0vLly3Xbbbfpww8/1DfffKN77rlHkvTKK6/oiy++0JIlS/Tpp5/qzjvvVF5eXoOcP5qHESNGaP78+SoqKlJ+fr5eeeUVtWrVSunp6Xr22WclecXmV199JUk65phjNGfOHEnSk08++aNrSNu0aaPk5GR98MEHu9dB3VCYAgAA4IDs3LlTZWVlSklJkSTFxsaqd+/e+72/1q1bS/IKg8LCwt0tUf/+9781bdo0tW3bVpLUoUMHSdK3336r4447TlFRUUpISNCgQYP0+uuvH8gpoZk78sgjNW7cOA0aNEg/+9nPNGTIECUnJ+vJJ5/Uww8/rEGDBql///6aO3euJOnee+/VzJkzddhhh+nxxx/X3/72tx/tc+bMmZo2bZqOPvro3V2EUXu2t2bscDFkyBBXeSEyAAAAghcZGamBAwfunp4xY4YmTZqkiy66SPPmzdOJJ56osWPH6qyzzlJERITmzZunRYsW6aabbvrRvqKiopSRkaGoqChNnz5dEyZM2L3s/PPP16uvvqp+/frtbs2aMGGCevXqpQ8//FDl5eW64YYbNGbMGL355pu68cYbtWDBAhUUFGjo0KGaNm2arrjiikZ5TBC8zMxM9e3bt07b5OfnKzExUQUFBTr22GP14IMP6vDDD2+ghLWzt/Mws8XOuSEBRWo0DH4EAACAWqvsflvVQw89pP/+97966623dNddd2nBggWaNWuWxo0bt8f1o6F++OEHde7cWStXrtQJJ5yggQMH6pBDDpHktT6Vl5frN7/5jZ5++mmdf/75Kisr0/Lly7Vw4UJlZ2dr5MiR+vrrr/XTn/5Un3/+uY455hi1b99eRx99tKKi+JiLmk2dOlXffvutioqKdO655wZelLZ0dOUFAABAvRg4cKAuu+wyLViwQM8///w+1+/cubMkqUePHho1apS+/PLLPZZHRkZq0qRJu/eVmpqq8ePHKzo6Wunp6erdu7eWL18uSbr22mu1ZMkSLViwQM459ezZs57PDs3N7NmztWTJEmVlZWnGjBlBx2nxKEwBAACaOVdRofLc3Abbf35+vhYuXLh7esmSJerevXuN2+Tk5Oz+KY6tW7fqww8/VL9+/eSc04oVK7zczmn+/Pnq06ePJGnChAl65513dm+zbNky9ejRQ+Xl5dq2bZskaenSpVq6dKl++tOf1vdpAmhA9HEAAABoxpxz2nTLrdr14YdKe/YZRSYlHdD+CgsLlZGRsXt6zJgxuvbaa/XnP/9ZF198seLj45WQkKBZs2ZJUrXXmGZmZuriiy9WRESEKioqNH36dPXr108VFRU699xzlZeXJ+ecBg0apH/961+SpNGjR+vNN99Uv379FBkZqTvvvFMpKSkqKirSyJEjJXkDJz3xxBN05QWaGAY/AgAAaKacc9r85zu1feZMHXTBBepw5e/5rUU0S/sz+FE4asmDH9GVFwAAoJnacu+92j5zptqecw5FKYCwRh8HAACAZmjrv/6lbf+6X23OOEMHX3sNRSnQwBITE/Xxxx9r8uTJkrxRp5OTk5WcnKx27drprbfeCjhheKMwBQAAaGa2PfyItvztXiWPH6eON94gi6CTHNAYBg4cuPvnlM477zyNHTtWp59+esCpmgbepQAAAJqR7U88qc133qnWp5ysTrfcQlEKoEmgxRQAAKCZyHnmGW26+WYl/uREdb7jDhkj06IFunH+N/p2fV697rNf59a6/rT+9bpP7Imv0AAAAJqBHS+9pI3X36CE445Vl7/+VRYdHXQkAKg1vkYDAABo4vJefVUbrrlWCUcPU+q99yoiJiboSEBgaNlsmmgxBQAAaMLyFizQuiuvUqvDD1fqffcpIjY26EgAUGcUpgAAAE1U/rvvat3lVyh+wACl3n+/Ilq1CjoSAOwXuvICAAA0Qbs++kjZv/mt4nr1Utd/P6jIxISgIwEtWn5+/h7Ts2bNCiZIE0WLKQAAQBNT8PnnWnvpNMWkp6vrQ/9WZOvWQUcCgANCYQoAANCEFHz5pdZefImiu3RRt0ceVlTbtkFHAoADRmEKAADQRBT+92ut/eVURbZvp24zH1FUSkrQkQCgXlCYAgAANAFFWVn64aKLFJmcrO6zZim6Q4egIwFAvaEwBQAACHPFK1bohwsuVER8vLo9OkvRnToFHQkA6hWFKQAAQBgrWbNGa84/X4qMUPdZMxWTmhp0JACodxSmAAAAYWzz3ffIFZeo+8yZiklLCzoOgGpERkYqIyND/fv316BBg/TXv/5VFRUVkqSFCxcqOTlZGRkZu29vvfVWwInDC79jCgAAEMaKvvlGCcOPUeyhhwYdBUAN4uPjtWTJEknS5s2bdfbZZys3N1c33nijJGnkyJF6+eWXg4wY1mgxBQAACFPlO3eqdO1axfXpG3QUAHXQoUMHPfjgg7rvvvvknAs6TpNAiykAAECYKs7KkiTF9e0TcBKgCXlturTxv/W7z44DpZNvr9MmPXr0UEVFhTZv3ixJev/995WRkbF7+fPPP69DDjmkXmM2ZRSmAAAAYaoo0ytMY/tQmAJNUWhrKV15a0ZhCgAAEKaKsrIUmZKiqPbtg44CNB11bNlsKCtXrlRkZKQ6dOigzMzMoOOEPa4xBQAACFNFWZmK69NHZhZ0FAB1sGXLFl1yySX69a9/zd9vLdFiCgAAEIZcSYlKlq9Q4rlTgo4CoBYKCwuVkZGh0tJSRUVFafLkybr88st3L696jel1112n008/PYioYYnCFAAAIAwVr1olV1qqWEbkBZqE8vLyapeNGjVKubm5jZim6aErLwAAQBgq8q9JY0ReAC1BrQpTM1ttZv81syVmtsifd5CZLTCz5f6/bf35Zmb3mtkKM1tqZoeH7Odcf/3lZnZuw5wSAABA01ecmSWLi1NMWlrQUQCgwdWlxfR451yGc26IPz1d0n+ccz0l/ceflqSTJfX0b1Ml/UvyCllJ10s6StJQSddXFrMAAADYU1FWlmJ79ZJFRgYdBQAa3IF05R0v6VH//qOSJoTMf8x5PpHUxsw6SRotaYFzbrtzLkfSAkljDuD4AAAAzZJzTkVZWYrj90sBtBC1LUydpDfNbLGZTfXnHeyc2yBJ/r8d/PldJK0N2Tbbn1fdfAAAAIQo27BBFbm5XF8KoMWo7ai8w51z682sg6QFZpZVw7p7+6EeV8P8PTf2Ct+pktStW7daxgMAAGg+irK8j1qxtJgCaCFq1WLqnFvv/7tZ0ovyrhHd5HfRlf/vZn/1bEldQzZPlbS+hvlVj/Wgc26Ic25I+/bt63Y2AAAAzUBRZqZkprhevYKOAqCWVq9erQEDBuwx74YbbtBdd92l8847T88995wkafv27Ro8eLBmzpwZRMywtc/C1MwSzCyp8r6kn0r6WtI8SZUj654raa5/f56kKf7ovMMk5fpdfd+Q9FMza+sPevRTfx4AAABCFGdlKaZ7d0UkJAQdBUA9ys3N1ejRozV16lSdf/75QccJK7XpynuwpBfNrHL92c65183sc0nPmNmFkn6QdIa//quSTpG0QlKBpPMlyTm33cz+JOlzf72bnHPb6+1MAAAAmomizCzFDRyw7xUBNBn5+fk6+eSTdfbZZ+tXv/pV0HHCzj4LU+fcSkmD9jJ/m6QT9zLfSZpWzb4ekfRI3WMCAAC0DOV5eSrNzlabM87Y98oAfuSOz+5Q1vaahsSpuz4H9dHVQ68+oH1cfvnluuiii3TZZZfVU6rm5UB+LgYAAAD1rPi77ySJEXmBJsbvYVrt/BNOOEFz587V5s2b97peS1fbUXkBAADQCIoyGZEXOBAH2rK5v1JSUpSTk7PHvO3btys9PV2SdOaZZ2rEiBE65ZRT9M477ygpKSmImGGLFlMAAIAwUpSVpciUFEXx6wRAk5KYmKhOnTrpP//5jySvKH399dc1YsSI3ev87ne/04knnqiJEyeqpKQkqKhhicIUAAAgjBRlZSquT59quwUCCF+PPfaYbr75ZmVkZOiEE07Q9ddfr0MOOWSPde644w517dpVkydPVkVFRUBJww9deQEAAMKEKylRyfIVSjx3StBRAOyHfv366Z133vnR/FmzZu0xzW+Y/hgtpgAAAGGieNUqudJSxfbpG3QUAGhUFKYAAABhoigzUxIj8gJoeShMAQAAwkRxZpYsLk4xaWlBRwGARkVhCgAAECaKsrIU27uXLDIy6CgA0KgoTAEAAMKAc05FWVmK4/pSAC0QhSkAAEAYKNuwQRW5uVxfCqBFojAFAAAIA0VZWZKkuD4UpkBTFBkZqYyMjN2322+/XZL08ssva/DgwRo0aJD69eunBx54IOCk4YnfMQUAAAgDRd9mSmaK7dUr6CgA9kN8fLyWLFmyx7zS0lJNnTpVn332mVJTU1VcXKzVq1cHEzDM0WIKAAAQBoqyMhWTlqaIVq2CjgKgnuzcuVNlZWVKSUmRJMXGxqp3794BpwpPtJgCAACEgeLMLMUPOizoGECTt/HWW1WcmVWv+4zt20cdr7mmxnUKCwuVkZGxe3rGjBmaNGmSxo0bp+7du+vEE0/U2LFjddZZZykigvbBqihMAQAAAlael6fSdevUZtKkoKMA2E9768orSQ899JD++9//6q233tJdd92lBQsWaNasWY0fMMxRmAIAAARs98BHjMgLHLB9tWwGYeDAgRo4cKAmT56s9PR0CtO9oA0ZAAAgYMWMyAs0S/n5+Vq4cOHu6SVLlqh79+7BBQpjtJgCAAAErCgzS5Ht2imqffugowDYT1WvMR0zZoyuvfZa/fnPf9bFF1+s+Ph4JSQk0FpaDQpTAACAgBVlZdFaCjRx5eXle53/6quvNnKSpomuvAAAAAFyJSUqXrGC60sBtGgUpgAAAAEqXrlSKi1VLC2mAFowClMAAIAAFWVWjsjbN+AkABAcClMAAIAAFWdlyuLiFMNInQBaMApTAACAABVlZim2d8DWigoAACAASURBVC9ZZGTQUQAgMBSmAAAAAXHO+SPy0o0XQMtGYQoAABCQsvXrVZGXx4i8QDOQmJgoSVq9erXi4+OVkZGx+/bYY48FnC788TumAAAAASnK8gc+YkReoFk55JBDtGTJkqBjNCm0mAIAAASkKDNLMlNsr15BRwGAQNFiCgAAEJCirEzFpKUpolWroKMAzcb7zyzT1rX59brPdl0TNfIXtf8C6fvvv1dGRsbu6b///e8aOXJkvWZqbihMAQAAAlKcmaX4QYcFHQNAPaMrb91RmAIAAASgPC9PpevWqc2kSUFHAZqVurRsInxwjSkAAEAAdg98xIi8AEBhCgAAEIRiRuQFmq3Ka0wrb/fee2/QkcIeXXkBAAACUJSZpch27RTVvn3QUQDUg/x8b8CltLQ0FRYWBpym6aHFFAAAIABFWVm0lgKAj8IUAACgkbmSEhWvWKG4vn2DjgIAYYHCFAAAoJEVr1wplZYy8BEA+ChMAQAAGllRpjfwUWwfWkwBQKIwBQAAaHTFWZmy+HjFdO8WdBQACAsUpgAAAI2s6NtMxfXqJYuMDDoKAIQFClMAAIBG5JxTUVaWYrm+FGhWIiMj9/jt0tWrV2vhwoVKTk7W4MGD1adPH/3+978POmbY4ndMAQAAGlHpuvWq2LlTcVxfCjQr8fHxWrJkyR7zVq9erZEjR+rll19WYWGhBg8erIkTJ2r48OEBpQxftJgCAAA0ouKsTEliRF6ghYmPj1dGRobWrVsXdJSwRIspAABAIyrKzJIiIhTbq1fQUYBm6Z1ZD2rzmpX1us8O3Xvo+POm1rhOYWGhMjIyJEnp6el68cUX91iek5Oj5cuX69hjj63XbM0FhSkAAEAjKsrKUkxamiLi44OOAqAe7a0rryS9//77Ouyww/Tdd99p+vTp6tixYwDpwh+FKQAAQCMqzsxUvN+qAqD+7atls7FVXmO6bNkyjRgxQhMnTtzdsor/4RpTAACARlKem6vS9esZkRdogXr16qUZM2bojjvuCDpKWKIwBQAAaCRFWd9JEiPyAi3UJZdcovfee0+rVq0KOkrYoSsvAABAI2FEXqD5ys/P/9G8UaNGadSoUbun4+PjGZW3GrSYAgAANJKizCxFtm+nqHbtgo4CAGGFwhQAAKCRFGVl0Y0XAPaCwhQAAKARuJISFX//veL60I0XAKqiMAUAAGgExd9/L5WWcn0p0ECcc0FHOCBNPf+BojAFAABoBEWZWZKkWLryAvUuLi5O27Zta7LFnXNO27ZtU1xcXNBRAsOovAAAAI2gKCtTFh+vmO7dgo4CNDupqanKzs7Wli1bgo6y3+Li4pSamhp0jMBQmAIAADSC4swsxfXqJYuMDDoK0OxER0crPT096Bg4AHTlBQAAaGDOORVlZSmW60sBYK8oTAEAABpY6br1qti5k5+KAYBqUJgCAAA0sOKsTEliRF4AqAaFKQAAQAMrysySIiIU26tX0FEAICxRmAIAADSwoqwsxaSlKSI+PugoABCWKEwBAAAaWHFmpuL60I0XAKpDYQoAANCAynNzVbp+PSPyAkANKEwBAAAaUFHWd5KkuL79Ak4CAOGLwhQAAKAB7R6Rt0/vgJMAQPiiMAUAAGhARZlZimrfXlHt2gUdBQDCFoUpAABAAyrKyuL6UgDYBwpTAACABuJKSlT8/feK69M36CgAENYoTAEAABpI8YoVUmmp4mgxBYAaUZgCAAA0kKLMLElSLL9hCgA1igo6AAAAQH0r/v57laxdG3QM5S9cKGvVSjHdugUdBQDCGoUpAABoNiqKi7Xl3nu1feYsqaIi6DiSpFZHHSWLjAw6BgCENQpTAADQLBR+/Y3WT79aJSu+V5szzlCbM06XzIKOpZju3YOOAABhr9aFqZlFSlokaZ1zbqyZpUuaI+kgSV9ImuycKzGzWEmPSTpC0jZJk5xzq/19zJB0oaRySb91zr1RnycDAABaHldSoq33P6CtDzygqJQUdX3wASUee2zQsQAAdVCXwY/+n6TMkOk7JN3tnOspKUdewSn/3xzn3KGS7vbXk5n1k3SmpP6Sxkj6p1/sAgAA7Jei75Zp1Zlnaus//6nksaeqx/x5FKUA0ATVqjA1s1RJp0p6yJ82SSdIes5f5VFJE/z74/1p+ctP9NcfL2mOc67YObdK0gpJQ+vjJAAAQMviysq09YEHter001W2abNS/3GfOt9xhyKTk4OOBgDYD7XtynuPpKskJfnTKZJ2OOfK/OlsSV38+10krZUk51yZmeX663eR9EnIPkO3AQAAqJXilau0fsZ0FX21VEljxqjj9X9UVNu2QccCAByAfRamZjZW0mbn3GIzG1U5ey+run0sq2mb0ONNlTRVkroxtDoAAPC5igptf+wxbbn7HkXExanLX/+i1qecEnQsAEA9qE2L6XBJ48zsFElxklrLa0FtY2ZRfqtpqqT1/vrZkrpKyjazKEnJkraHzK8Uus1uzrkHJT0oSUOGDPlR4QoAAFqekrVrtWHGNSpYtEiJxx+vTjfdqKj27YOOBQCoJ/u8xtQ5N8M5l+qcS5M3eNHbzrlzJL0j6XR/tXMlzfXvz/On5S9/2znn/PlnmlmsP6JvT0mf1duZAACAZsc5p5w5c7Ry/AQVffedOt12m1L/+Q+KUgBoZg7kd0yvljTHzG6W9KWkh/35D0t63MxWyGspPVOSnHPfmNkzkr6VVCZpmnOu/ACODwAAmrHSDRu04drrtOujj5QwfLg63XKzojt2DDoWAKABmNeYGZ6GDBniFi1aFHQMAADQiJxzyn3xJW269Va5igodfNVVajPpF/IG+QeAlsXMFjvnhgSdo6EdSIspAABAvXLOad3ll2vna6+r1ZFHqtOttyima9d9bwgAaNIoTAEAQNgoXLxYO197XSkXX6z2/++3soha/eQ6AKCJ490eAACEjZzZTymidWu1u+RiilIAaEF4xwcAAGGhbMsW5S1YoDYTJyoiPj7oOACARkRhCgAAwsKO55+XSkvV5sxJQUcBADQyClMAABA4V1amnDlPK+GYYxSbnh50HABAI6MwBQAAgctfuFBlGzeq7dlnBR0FABAAClMAABC4nNlPKapTJyWOGhV0FABAAChMAQBAoIpXrdKujz5S20m/kEXxS3YA0BJRmAIAgEDtmPO0FB2tNj//edBRAAABoTAFAACBqSgs1I4XX1Trk05SVPv2QccBAASEwhQAAAQm75VXVJGXx6BHANDCUZgCAIBAOOe0ffZsxfbsqfgjjgg6DgAgQBSmAAAgEEVLl6r420y1PfssmVnQcQAAAaIwBQAAgciZ/ZQiEhLU+rRxQUcBAASMwhQAADS6spwc5b32mpLHj1dkYkLQcQAAAaMwBQAAjS73hRfkSkrU9qwzg44CAAgDFKYAAKBRufJy5Tw1R62OPFKxPXsGHQcAEAaigg4AAADqzpWVqXznTlXk56s8L08WFaW43r2DjlUruz74QKXZ2epwxeVBRwEAhAkKUwBAi+TKylT07bdyZeVBR5EqylWen6+KnTu9YnNnvip25ql8Z+i8kH/z8+UKCn60m4OvmaGDpkwJ4ATqJmf2U4ps305JJ54YdBQAQJigMAUAtDgVhYXKnjZNuz76OOgo1bLoaEW0bq3IxERFJCUpsnWSojp0UERSoiKTWof8m6TIpETlzHlam//yVyWMHKnY9PSg41erJDtb+e+9p3a/ukQWExN0HABAmKAwBQC0KBUFBVp76TQVfPqpOlx9dVhc42gRpojEREUkegVoRFKSImJj67SPuMMO08rTxmnDjGvU/cknZJGRDZT2wOx4+mkpIkJtfvGLoKMAAMIIhSkAoMWo2LVLay/5lQoWL1bnO25X8rjm8/uZ0R06qON112n9lVdq+8yZSrnooqAj/UhFcbF2PPuckk44QdEdOwYdBwAQRhiVFwDQIpTn79IPUy9WwRdfqPOdf25WRWml1mNPVdJJP9GWv92r4uXLg47zIztff13lO3ao7dlnBR0FABBmKEwBAM1eeX6+1l50kQqXLFGXv9yl5FNPDTpSgzAzdbzhBkUkJmr99BlypaVBR9pDzuynFJOerlbDhgUdBQAQZihMAQDNWvnOnfrhwgtV+PXX6vLXv6r1mDFBR2pQUSkp6nj9H1X0zTfa9tBDQcfZrfCbb1T41Vdqe9aZMrOg4wAAwgyFKQCg2SrPzdUPF1yoom8zlfq3e9R69E+DjtQoWo8Zo9annKwt//yXirKygo4jSdoxZ44sLk7JEyYEHQUAEIYoTAEAzVL5jh364fwLVJyVpdR7/9bifjPz4D/8QZHJyV6X3pKSQLOU5+Upd/7LSj5trCJbtw40CwAgPFGYAgCanbKcHK05/wIVr1ih1Pv+rqTjjw86UqOLattWnW68QcVZWdp6//2BZsl98UW5oiK1PYtBjwAAe0dhCgBoVsq2b9cP552vku+/V+o//qHE444LOlJgkk48Ucnjx2nrAw+q8L9fB5LBVVQoZ/ZTis/IUFy/foFkAACEPwpTAECzUbZ1q34491yVrF6trvf/S4kjRwQdKXAHX3ONolJStH7GdFUUFzf68Qs++UQla9bwEzEAgBpRmAIAmoWyLVu05tzzVLI2W10fuF8JxxwTdKSwEJmcrE43/0klK77X1vvua/Tj5zz1lCLbtlXS6NGNfmwAQNNBYQoAaPJKN23WminnqnTDBnV98AEl8DuZe0g89lgln/5zbXv4ERUuWdJoxy3duFE7//O22pz+c0XExjbacQEATQ+FKQCgSSvdtEk/TJmisk2b1O3BB5QwdGjQkcLSwdOnK6rjwVo/fYYqCgsb5Zg7nnlGck5tJk1qlOMBAJouClMAQJNVumGD1kyeorKtW9X1oYfUasiQoCOFrcjERHW+5RaVrF6tLff8rcGP50pKlPPMs0o89ljFpKY2+PEAAE0bhSkAoEkqXbdOayZPUfn27er28ENqdfjgoCOFvYSjj1bbs8/S9sceU8GiRQ16rJ1vvaXyrVsZ9AgAUCsUpgCAJqckO1trppyr8rw8dZv5iOIzMoKO1GR0uOIKRaemav2Ma1Sxa1eDHSdn9lOKTk1VwsiRDXYMAEDzQWEKAGhSir77TmvOOlvl+fnq9sgjih84MOhITUpEQoI633qLSrOztfkvf2mQYxQtW6aCRYvU9qwzZRF81AAA7Bv/WwAAmoxdn32mNf83WYqIUNoTjyt+QP+gIzVJrY48UgdNmayc2U9p18cf1/v+d8yZI4uJUfLPflbv+wYANE8UpgCAJiHvzTe19qJfKqpDB6U9NVuxPXsGHalJa/+73ymme3etv/Zalefn19t+y/PzlfvSXLU++WRFtW1bb/sFADRvFKYAgLCXM2eO1v3uMsX17avuTzyu6M6dg47U5EXEx6vT7bepbOMmbb7jjnrbb+68eaooKGDQIwBAnVCYAgDClnNOW+77hzbecKMSR45Ut1kzaYWrR60GD1bKBedrx7PPKf/99/d7P+V5eSr86ivteOklbX/0UcX166e4ww6rx6QAgOYuKugAAADsjSsv18ab/qQdTz+t5IkT1emmG2XR0UHHanba/eY32rlwoTZc9wf1mD9Pka1b73U9V1qqkuxslaxarZJVq1SyepWKV61SyarVKt+2bfd6FhOjg++5W2bWWKcAAGgGKEwBAGGnorhY639/pXYuWKCUqVPV/rLfUeg0kIjYWHW+7XatPvNMbbrlVnW4+iqv8Fz1v8KzZNUqlaxdK5WV7d4u8qCDFJOersTjRyk2PV0x6emKSUtXTNdUvkAAANQZhSkAIKyU5+Up+9JpKli0SAdfM0MHTZkSdKRmL37gAKVM/aW2/et+5c6du3u+RUcrJq27Yg89VEknnaSY9HTFpqcpJj1dkcnJwQUGADQ7FKYAgLBRummz1v7ylypetUqd/3KXkk89NehILUb7X/1KFh2tiFatvBbQHj0U3bmzLDIy6GgAgBaAwhQAEBaKV67S2osuUvmOHer2wP1KOOaYoCO1KBYTo/aXXhp0DABAC0VhCgAIXOHSpVo79WIpMlLdHntM8QP6Bx0JAAA0In4uBgAQqPz339eac89TRFKS0mY/SVEKAEALRGEKAAhM7ty5WvurSxWTlqa02U8qpnv3oCMBAIAAUJgCAAKx7eFHtP7q6Wo1ZIi6P/6Yotq3DzoSAAAICNeYAgAalauo0OY779L2mTOVdPIYdb7jDkXExAQdCwAABIjCFADQaEo3bdbGG29U/ttvq+055+jga6+RRdB5BwCAlo7CFADQ4FxFhXY8+5w233mnXGmpDp4xXW2nTJGZBR0NAACEAQpTAECDKl61Shv/eL0KPv9crYYNU6cbb2CQIwAAsAcKUwBAg3Clpdr2yExt/cc/ZHFx6nTLzUr+2c9oJQUAAD9CYQoAqHeF//1aG/7wBxVnZSlp9GgdfO01iu7QIehYAAAgTFGYAgDqTUVBgbb8/T5tf/RRRaWkKPW+vyvpJz8JOhYAAAhzFKYAgHqx66OPtOGP16s0O1ttJk1ShysuV2Tr1kHHAgAATQCFKQDggJTv2KFNf75TuS+8oJju3dXtsUeVMHRo0LEAAEATQmEKANgvzjntfP11bbz5FpXv2KGUqVPVbtqlioiNDToaAABoYihMAQB1VrpxozbeeJPy33lHcf37q9vDDymuT5+gYwEAgCaKwhQAUGuuokI7nn5am+/6i1x5uTpcdZUOmjJZFsV/JwAAYP/xSQIAUGsbb7pJO+Y8rYRjjlbHG29UTNeuQUcCAADNAIUpAKBWyvPylPvCi0qeOFGdbr1FZhZ0JAAA0ExEBB0AANA05L3xhlxJidqefRZFKQAAqFcUpgCAWsmbO08x6emKGzAg6CgAAKCZoTAFAOxTSfY6FSxapOTx42gtBQAA9Y7CFACwT3nz50mSkk87LeAkAACgOaIwBQDUyDmn3Lnz1OrIIxXdpUvQcQAAQDNEYQoAqFHR0qUqWb1ayRPGBx0FAAA0UxSmAIAa5c6dJ4uNVdLo0UFHAQAAzRSFKQCgWq6kRHmvvKKkE09UZGJi0HEAAEAzRWEKAKhW/vvvqzw3V8njxwUdBQAANGMUpgCAauW+NFeRKSlKGD486CgAAKAZ22dhamZxZvaZmX1lZt+Y2Y3+/HQz+9TMlpvZ02YW48+P9adX+MvTQvY1w5//nZlxsRIAhLHyHTuUv3ChkseeKouKCjoOAABoxmrTYlos6QTn3CBJGZLGmNkwSXdIuts511NSjqQL/fUvlJTjnDtU0t3+ejKzfpLOlNRf0hhJ/zSzyPo8GQBA/cl7/XW50lIlj2c0XgAA0LD2WZg6T74/Ge3fnKQTJD3nz39U0gT//nh/Wv7yE83M/PlznHPFzrlVklZIGlovZwEAqHe5c+cptuehiu3bN+goAACgmavVNaZmFmlmSyRtlrRA0veSdjjnyvxVsiVV/up6F0lrJclfnispJXT+XrYJPdZUM1tkZou2bNlS9zMCABywkjVrVPjll0oeP17ed4sAAAANp1aFqXOu3DmXISlVXivn3r4+d/6/e/sE42qYX/VYDzrnhjjnhrRv37428QAA9Sx33nzJTK3Hjg06CgAAaAHqNCqvc26HpIWShklqY2aVo2GkSlrv38+W1FWS/OXJkraHzt/LNgCAMOGcU+68eWo17ChFd+wYdBwAANAC1GZU3vZm1sa/Hy/pJ5IyJb0j6XR/tXMlzfXvz/On5S9/2znn/Pln+qP2pkvqKemz+joRAED9KPzyS5WuXcugR0Az4pyT93EMAMJTbVpMO0l6x8yWSvpc0gLn3MuSrpZ0uZmtkHcN6cP++g9LSvHnXy5puiQ5576R9IykbyW9Lmmac668Pk8GAHDgcl+aK4uPV+uTTgo6CoB68uHTj2vmZZeoooKPXgDC0z5/mM45t1TS4L3MX6m9jKrrnCuSdEY1+7pF0i11jwkAaAwVxcXKe/11JZ30E0UkJAQdB0A9KMjL1eJX5qqspFjrv8tUat8BQUcCgB+p0zWmAIDmLX/hu6rIy1PyOLrxAs3FF6/OU1lpiSKjorTs0w+DjgMAe0VhCgDYLXfuXEW1b6+Eo4cFHQVAPSgu2KUlb7ysnkOPVvrgIVr+6UdyFRVBxwKAH6EwBQBIkspycpT/3ntqfdppssjIoOMAqAdL3nxVxQW7dNSEX6jXUcOVv32b1i//LuhYAPAjFKYAAElS3iuvSmVljMYLNBOlxUVa/MpLSht0uA7ucah6HDFUkVFRWv7pB0FHA4AfoTAFAEiScufNU2yfPorr3SvoKADqwdfvLFBhXq6OmvALSVJsqwR1H3S4ln3yET8dAyDsUJgCAFS8cpWKli6ltRRoJsrLyvT5/BfUuXc/denbf/f8XkcN185tW7RxxbIA0wHAj1GYAgCUO2+uFBGh1qeeEnQUAPUg68N3tXPrFh018QyZ2e75hww5ShGRjM4LIPxQmAJAC+cqKpQ7b54Shg9XdIcOQccBcIAqKsr16UvPqn33dKVnDNljWVxCoroflqFln3xId14AYYXCFABauIJFi1S2foOSx40LOgqAerDi80+Usz5bQyfs2VpaqddRw5W3ZZM2r/o+gHQAsHcUpgDQwuXOnauIVq2U9JMTg44C4AA55/Tpi8+oTcdO6jVs+F7XOeTIYYqIjNR3nzA6L4DwQWEKAC1YRVGRdr7+hpJGj1ZEfHzQcQAcoDVffaHNq77X0PFnKCJi779HHJ+YpK79D9NyuvMCCCMUpgDQgu38z39UsWuXksfTjRdoDj596VklprRTv2OPr3G9XsNGaMemDdqyZlUjJQOAmlGYAkALljtvnqI6dVKroUODjgLgAGVnfaPszK915NiJioyKrnHdQ48cJouI0DK68wIIExSmANBClW3dql0ffKjksWNlEfx3ADR1n730rOKTWmvgCaP3uW6r1snq2m+gln3yAd15AYQFPokAQAuV98orUnk53XiBZmDz6pVa9eUiHX7KeEXHxdVqm17DRihnw3ptXbumgdMBwL5RmAJAC7Vj7lzF9e+v2EMPDToKgAP02UvPKiY+XhmjT631NoceOUxmEVr2yYcNmAwAaofCFABaoOLly1X8baaSx48POgqAA7R9/Tp998kHyvjpqYpLSKz1dglt2iq1b3+uMwUQFihMAaAFyp03T4qMVOtTTwk6CoAD9Pm85xUVFa3DT6n7F009hw3X9nVrtS37hwZIBgC1R2EKAC2MKy9X7rz5Shw5UlEpKUHHAXAA8rZu0bfvva0BJ5ykhDZt67x9z6HHSGZ05wUQOApTAGhhCj77TGWbNjHoEdAMLH75RUlOR5728/3aPrHtQerSux/deQEEjsIUAFqY3JfmKiIpSYnHHx90FAAHoCAvV0v/84b6jhil1u077Pd+eg0brq1r12jburX1mA4A6obCFABakIqCAuUtWKDWY0YropY/KQEgPH3x6jyVlZboyHGnH9B+eg49RpK0/NOP6iMWAOwXClMAaEF2vvWWXEGBksfRjRdoyooLdmnJGy+r59CjlZLa9YD2lZTSTp179dWyT7nOFEBwKEwBoAXJnTtP0V26KP6II4KOAuAALHnzVRUX7NJRE35RL/vrNWy4tqxeqZyN6+tlfwBQVxSmANBClG7arF0ff6zW406TRfD2DzRVpSXF+uLVuUobdLgO7nFoveyz51Fed15G5wUQFD6ZAEALkffyy1JFBd14gSbu63cWqCB3R721lkpS63Yd1OnQ3lpOd14AAaEwBYAWoKKgQDlPPaX4QYMUm54edBwA+6m8rEyfz3tenXv3U5e+/et13z2HDdemlSu0Y9PGet0vANQGhSkAtACb77lHpdnZ6vD7K4KOAuAAZH34rnZu3aKjJpwhM6vXffc6qnJ0XlpNATQ+ClMAaOYKFi9WzuNPqO0556jVkUcGHQfAfqqoKNenLz2r9t3SlD54SL3vP7lDRx3c41BG5wUQCApTAGjGKgoLteGaaxXdpYs6XH5Z0HEAHIAVn3+inPXZGjrxF/XeWlqp17AR2rhimfK2bG6Q/QNAdShMAaAZ23Lv31WyZo063fwnRSQkBB0HwH5yzunTF59Rm46d1GvY8AY7zu7ReWk1BdDIKEwBoJkq+PJLbX/0UbU5c5IShg0LOg6AA7Dmqy+0edX3Gjr+DEVERDbYcdp27Kz2aT0oTAE0OgpTAGiGKoqLteHa6xTV8WB1+P2VQccBcIA+felZJaa0U79jj2/wY/UeNkIblmVp57b/z959h0dVJmwc/p2Z9F5IDz0JPRSDgAiKIFVFisq6C5Z1LfvZVl1X7L3v2l1FdNF1rYAKClIEBFGR0KuEEkglvffM+f6YGEHpJJyU576uuWZy5uTMM1k3zJP3nPfNafTXEhH5hYqpiEgLlPPqq1Tt3UvEY49h99EpvCLNWerObaTu2Er/iyZgd3Ft9NeLHeA8Vbipz85rt9vp06dP/S05OZkVK1bg7+9P37596dq1K3fddddxj5OSksKwYcPo1q0bPXr04KWXXvrdPs8//zyGYZCTc3hZX7t2LXa7ndmzZwOwceNGBg0aRI8ePYiPj+fjjz9umDcr0gq4WB1AREQaVvmWLeS+/Q4Bl03GZ3DjXYsmImfG2nlz8PD1o9cFo87I6wVFRtGmXQd2rVlNv7Hjz8hrngpPT082btx42Lbk5GSGDBnCl19+SXl5OX379mXChAkMPsbvQhcXF/75z3/Sr18/iouLOeuss7jwwgvp3r074CyuS5YsoV27dod9X21tLf/4xz8YNerX/128vLx47733iI2NJT09nbPOOotRo0YREBDQgO9cpGXSiKmISAviqKoiffp0XEJDCb37bqvjiMhpKsjMYO/6tfS5cAyuHh5n7HXjBgwm7ecdlOTlnrHXbGienp706dOHtLS0Y+4XERFBv379APD19aVbt26Hfc/f/vY38cJ+ZAAAIABJREFUnn322d/NhPzKK68wadIkQkND67fFxcURGxsLQGRkJKGhoWRnZzfUWxJp0VRMRURakJzXX6dq9x4iHn0Eu6+v1XFE5DRt+Ho+NpuN3heOPaOvGzfwXDBNkn76/oy+7skoLy+vP413woQJv3s+Pz+fpKQkhg4dCkBiYiLXXXfdMY+ZnJzMhg0bGDBgAADz5s0jKiqK3r17H7ZfWloan332GTfeeONRj/XTTz9RVVVF586dT/atibRKOpVXRKSFKN+2jdy3ZuI/YQI+dR/ERKT5qiwrY+uKJcQNPBefoOAz+trB0W0Jjm7HrjWr6Tv64jP62ifqSKfyAqxatYr4+Hh+/vln7rnnHsLDwwFISEhg5syZRz1eSUkJkyZN4sUXX8TPz4+ysjKeeOIJFi9e/Lt9b7/9dp555hns9iPPkJyRkcHUqVN59913sdk0DiRyIlRMRURaALOqiozp9+ISFETYPf+wOo6INIBt3y6lqrycfmMvseT1YwcM5se5H1FakI93QKAlGU7FL9eY7tq1i3PPPZcJEybQp0+fY35PdXU1kyZN4o9//CMTJ04EYM+ePezbt69+tDQ1NZV+/frx008/kZiYyJQpUwDIyclhwYIFuLi4cOmll1JUVMS4ceN4/PHHGailukROmP6EIyLSAuS8OYPKXbsIf+QR7P7+VscRkdNkOhxs+Ho+EbFdiIjpYkmGLgMHg2mye+0PDXZMh6OW1B1bG+x4xxIXF8f06dN55plnjrmfaZr8+c9/plu3btxxxx3123v16kVWVhbJyckkJycTHR3N+vXrCQ8PZ9++ffXbJ0+ezOuvv86ll15KVVUVEyZMYNq0aVx22WWN/RZFWhQVUxGRZq5i505y3nwTv0suxveCxl/jUEQa394NiRRkZlg6K25w2/YERkaz68fvGuR4aTu387/pd/DxI9PJTUtpkGMez4033sjKlSvZt2/fUa8xXb16Nf/9739ZtmxZ/TWrCxYsOKXX++STT1i5ciWzZs2qP9aRTjcWkd8zTNO0OsNRJSQkmImJiVbHEBFpsszqavZdfgU12dl0/nI+di1JINIifPr4/eSlpXDdK29jd7HuyqvvPvovP33+KTfO+C9efqd2NkZxXg6r/jeLHd+twCe4Def96Vq6DBryu1luReTIDMNYZ5pmgtU5GpuuMRURacZyZ86kcscOol55WaVUpIXISdnPgS0bOXfKNEtLKUDcwMGs+exjdq/9gfjho0/qe2uqq1n31eesmfsxDkctAydewdnjLzujy96ISPOhYioi0kxV7NpF9uv/xm/sWPwuvNDqOCLSQDYsnI+LqxvxI06uCDaGkPYdCQiPYNePq0+qmO5Z9xMr3n2LgoMZxPQfyHlTryMgLLwRk4pIc6diKiLSDJk1NWRMvxe7ry9hD9xvdRwRaSDlxUVsX7mMbkPOx9PXz+o4GIZB3IDBrJ0/l/LiouNmyktPY8W7M9i3cR1BkdFMuvdROvTud4bSikhzpmIqItIM5b7zHyq2bSPqxRdwCWw+yziIyLFt/mYRNdVV9B1jzRIxRxI38Fx++mI2uxN/pNewkUfcp7KsjB/nfsT6BfNwcXPj/GnX0WfURZafiiwizYd+W4iINDOVu3eT88or+I4ahd9o60/1E5GGUVtTw8bFX9GuZzwh7TpYHadeaMfO+IeGkfTj6t8VU9PhYPuq5az6YBalBfn0HHYh506Z1qzWPRWRpkHFVESkGTFra0m/7z5s3t6EP/iA1XFEpAHtXvsDJbk5DL/2JqujHMYwDGIHDGb9gnlUlJTg4eMDQOaeJJb95w0ykn4mIqYL4/9+v2VrropI86diKiLSjOTNepeKTZuJfP55XIKDrY4jIg1o/YJ5+IeF06lf01sVIm7gYBLnz2XPujV07HMWqz58j60rluDl58/ov/6N7kOGYdhsVscUkWZMxVREpJmo3LuP7JdfxmfEcPzGjbU6jog0oMw9SaTv2sH50/6CzWa3Os7vhHeOw7dNCD/O/Yjls2ZQXVlBwkUTGDhxCu5eXlbHE5EWQMVURKQZMGtrybjvPgwPDyIeekgL04u0MOsXzsPVw5Oew0ZYHeWIDMOgy6AhJM6fS4fe/Tj/qr8QHNXW6lgi0oKomIqIHIVpmpR+t5ra/Dyro1C+dSvlGzYQ+czTuISEWB1HRBpQSX4eP3+/it4XjsHdy9vqOEd1zmVX0vWcoYR27Kw/jolIg1MxFRE5gvItWzn4xBOUb9xodZR6vheOwO+SprOEhIg0jE1LFuJw1NJ39EVWRzkmV3cPwjrFWB1DRFooFVMRkUPU5OaS9cILFM6Ziz0oiIjHH8Orf3+rY4Fh4BodrVEKkRamprqazUsX0qlvAoERUVbHERGxjIqpiAhgVleT97//kfPqazgqKgi6+mra/PUm7L6+VkcTkRbs5+9XUlZYQN8xOhtCRFo3FVMRafVKVn3HwaeeomrvXryHDCFs+nTcO3W0OpaItHCmabJ+wTyCo9vRvlcfq+OIiFhKxVREWq2q/fs5+PQzlCxfjmv7dkT/+3V8zj9fp8uKyBmRtnMbWcl7GHHd/+n3joi0eiqmItLqOEpLyXnjTfJmzcJwdSX0rjsJnDYNm5ub1dFEpBVZv3AeHt4+dB86zOooIiKWUzEVkVbDNE2K5s8n67nnqcnOxn/8eELuvAPX0FCro4lIK1OUncXun34k4eIJuLp7WB1HRMRyKqYi0iocuvyLR69eRL/6Cp69e1sdS0RaqQ2LvgQD+owaZ3UUEZEmQcVURFq0mpwc5/Ivcz/DHhxMxJNP4n/peAybzepoItJKVVdUsGXZImL7D8Kvjc7YEBEBFVMRaWEcFRVUp2dQnZ5OxdYt5M58G0dlJUHXXONc/sXHx+qIItLKbV+1jMrSUvqO1RIxIiK/UDEVkWaltriY6vR0qtPSnfe/3NLSqE5PpzY397D9vYfWLf/SUcu/iIj1TNNk/cL5hHWKIapLd6vjiIg0GSqmItLkOKqqKF21iqrk/YeXz/R0HMXFh+1ruLvjGhGBa2QkHhcMwzUy8tdbdDSuEREWvQsRkd/bv3kDeWkpjPm/O7REjIjIIVRMRaTJqC0ppeCTT8ibNYuarCwAbL6+9UXTKyHB+Tjq1/JpDw7WhzsRaTbWL5yHl38AcYOGWB1FRKRJUTEVEcvV5OWR//775P3vAxyFhXgNGkjEE4/j2acPdl9fq+OJiDSIvPQ09m1IZNDkK3FxdbU6johIk6JiKiKWqU5LI/c/syiYPRuzshLfESMI/st1eMbHWx1NRKTBbfh6PnYXF3pfOMbqKCIiTY6KqYiccZVJSeTOnEnhl1+BzYb/JRcT/Oc/496pk9XRREQaRWVZKdu+/YYu5wzFOyDQ6jgiIk2OiqmInDFlGzaQ+9ZMSpYtw/DyIuhPfyLo6qs0QZGItHhbly+huqKcfmO0RIyIyJGomIpIozJNk9JVq8id8RZliYnYAwJoc8vNBF55JS6BGjUQkZbP4ahlw9fzieranbBOMVbHERFpklRMRaRRmDU1FC1aRO5bM6ncuROXiAjC7r2XgMmTsHl5WR1PROSM2btuLYVZBxn6x2usjiIi0mSpmIpIg6otLqboyy/Jfec/VKek4Na5MxFPPYX/uLEYbm5WxxMROePWL5yHb5sQYvoPsjqKiEiTpWIqIqetJj+fkmXLKVq8iNLvf4Dqajx6xxN2zz/wGTYMw2azOqKIiCWy9+8jZdtmhlx5NTa73eo4IiJNloqpiJySmtxcipd+Q/GiRZSuWQO1tbhGRRE0dSp+o0biER+PYRhWxxQRsYTDUcv+zRv5Yc6HuLi502v4KKsjiYg0acctpoZhtAXeA8IBBzDDNM2XDMMIAj4GOgDJwOWmaeYbzk+iLwFjgTLgatM019cd6yrg/rpDP26a5rsN+3ZEpDFVH8yieOkSihctpiwxERwOXNu3I/jaa/EdNQqPHt1VRkWkVSvMOsjWFUvZtmIpxbnZePr6Meyqv+Dp42t1NBGRJu1ERkxrgDtN01xvGIYvsM4wjCXA1cA3pmk+bRjGPcA9wD+AMUBs3W0A8G9gQF2RfQhIAMy648wzTTO/od+UiDSc6owMihcvpmjxEsrXrwfTxK1TJ9rceAO+o0bhHhenMioirVpNdTV7En9ky7LF7N+yEYAO8X05b+qf6ZwwABdXV4sTiog0fcctpqZpZgAZdY+LDcPYAUQB44Hz63Z7F1iBs5iOB94zTdMEfjQMI8AwjIi6fZeYppkHUFduRwMfNuD7EZEGUJWaSvGixRQtXkTFps0AuHfpQpub/w+/UaNwj9FyByIiOQeS2bJ8CdtXLaeiuAjfNiEMmvQHep4/Ar+QUKvjiYg0Kyd1jalhGB2AvsAaIKyutGKaZoZhGL/8Bo4CUg75ttS6bUfb/tvXuB64HqBdu3YnE09ETlPFzp1k3Hc/Fdu2AeDRvTshf/sbviMvxL1jR4vTiYhYr6q8jJ3fr2TrsiVk7P4Zm92FmP4D6XXBSNr16o3NpgmOREROxQkXU8MwfIA5wO2maRYd49S9Iz1hHmP74RtMcwYwAyAhIeF3z4tI46jJzSXlpr9CTQ2hf78L35EjcWvb1upYIiKWM02T9F072bJsEbt++I7qygqCo9tx/rTr6DZkGF5+/lZHFBFp9k6omBqG4YqzlP7PNM25dZsPGoYRUTdaGgFk1W1PBQ79NBsNpNdtP/8321ecenQRaShmdTVpt91ObV4e7d9/H89ePa2OJCJiubKiQrZ/+w1bli0mLz0VVw9Pug4eSs9hI4mI7aLr60VEGtCJzMprAG8DO0zT/NchT80DrgKerrv/4pDtNxuG8RHOyY8K68rrIuBJwzAC6/YbCUxvmLchIqfj4NPPUJaYSOSzz6iUiogAe9at4evXX6SipJiIuK6MvPFWugwagpuHp9XRRERapBMZMR0MTAW2GIaxsW7bvTgL6SeGYfwZOABcVvfcApxLxezGuVzMNQCmaeYZhvEYsLZuv0d/mQhJRKxTMGcO+f/7H0FXX43/JZdYHUdExFK1NdWs+mAW6776gpAOnbj8wScJaa9r7EVEGpvhnDy3aUpISDATExOtjiHSYpVv3Mj+qdPw6p9A2xkzMFxOaj40EZEWpeBgJl+99AyZe5LoM+oizvvTtbi4uVkdS0RaOcMw1pmmmWB1jsamT6EirVR1Vhapt9yKS1gYkf/8p0qpiLRqu378jkVvvIxhGFxyx73EDjjH6kgiIq2KPomKtEKOqirSbrmV2pISOsx8C5fAwON/k4hIC1RTVcWK92ayackCImK6MO62u/EPDbM6lohIq6NiKtLKmKZJ5qOPUr5pE1EvvohHly5WRxIRsUReeipfvvgM2fv3kXDxRM6dMg27zh4REbGEfvuKtDL5H35I4ew5BN9wA36jR1kdR0TEEttXLmPpzNexu7kx4Z6H6NS3v9WRRERaNRVTkVakbO1aDj75FD7nnUfIrbdYHUdE5Iyrrqjgm3feYNu3S4nq2oNxt/4d3+A2VscSEWn1VExFWonq9HRSb7sdt+hoIp9/DsNutzqSiMgZlX0gmS9ffIa89FQGTprCoEl/wKbfhSIiTYKKqUgr4KioIPXmWzArK4l+/TXsvr5WRxIROWNM02TLskUs/88M3Ly8mHzfY7Tv1cfqWCIicggVU5EWzjRNMh54kIodO4h+7TXcO3WyOpKIyBlTWVbGkrde5efvV9KuVx/G3nwn3gGaiVxEpKlRMRVp4fJmvUvR/PmE3HYrvhcMszqOiMgZc3Dvbr588RkKsw9y7pRpnD1+MobNZnUsERE5AhVTkRasZPVqsp57Dt8LLyT4hhusjiMickY4amvZ8PV8Vn0wC0//AC5/6Cmiu/awOpaIiByDiqlIC1WVkkLaHXfi3rkzkU8/pVECEWkV9m/ZyIp33yInZT+dzjqb0Tfdjqevn9WxRETkOFRMRVogR2kpqX/9PwCiX3sVm7e3xYlERBpXQWYG377/NrvX/oh/aBiX3HkvMf0HYRiG1dFEROQEqJiKtDCmaZI+/V4q9+yh7VszcGvXzupIIiKNpqq8jDWffcK6rz7HZnfh3CnTOGvcpbi4uVkdTUREToKKqUgLk/vmmxQvXkzo3XfjM3iw1XFERBqF6XCwfdVyVn0wi9KCfLoPvYAhf7gKn6Bgq6OJiMgpUDEVaUGKly8n+6WX8bv4YoKuudrqOCIijSJ91w6Wz5pB5p4kImK6MP7v9xMR08XqWCIichpUTEVOU8mq7yj94QerY4BpUvDpp3h060bEY4/quioRaXGKc3NY9cEsdny3Ap/AIMbcfCfdBp+nyd1ERFoAFVORU1SVksLBJ5+iZPlyDFdXcLH+/06uERFEv/oKNg8Pq6OIiDSY6qpK1s3/jDVffIrpcDBgwhWcfelk3Dw8rY4mIiINxPpP0iLNjKOigty3ZpL71lvg4kLoXXcSNG0ahibaEBFpUKZpkrRmNd++/w5F2VnEDRjM0D9dg39ouNXRRESkgamYipwg0zQpWbaMg08+RXVaGn7jxhF6999xDQuzOpqISIuTlbyX5bNmkLpjKyHtOnD5g0/Stke81bFERKSRqJiKnICq5GQyn3iS0lWrcI+Nod277+I94GyrY4mItCgl+Xmkbt/C3g2J7PhuBZ4+voy47v/oNXwkNpvd6ngiItKIVExFjsFRVkbOmzPIe+cdDHd3wqbfQ+CVVzqvKRURkdNSkpdLyo6tpG7bQsr2LeRnpAHg5ulFvzGXMGjyH/Dw9rE4pYiInAkqpiJHYJomxYsWcfDpZ6jJzMR//HhC77oTl5AQq6OJiDRbxXk5pG7fSsr2LaRu30J+RjrgLKLR3XoQP3wUbXvEE9Kho0ZIRURaGRVTkd+o3LOHzMcfp+yHH3Hv1o2of/0Tr379rI4lItLsFOfmkLrdORqasn0LBZkZALh7eRPVrQfxw0eriIqICKBiKlKvtqSUnNdfJ++997B5eRH2wP0ETpmCYdeHJRGRE7V77Y/sWfcTqTt+X0R7XziWtt17qYiKiMjvqJhKq2eaJkVffkXWs89Sk52N/+RJhN5xBy5BQVZHExFpVn6c+zGrP/4v7t7eRHfrSZ+R44ju3ouQ9h1UREVE5JhUTKVVq9y9m8yHH6EsMRGPnj2Jfu1VPOO1HIGIyMlaO38uqz/+L92HDGPUX29XERURkZOiYiqtVsl3q0m77TYMV1fCH32EgEmTdNquiMgpWL9wHivff4cug4Yw6iaVUhEROXkqptIqFcyZQ8aDD+EeG0vbN9/ANSzM6kgiIs3SpiULWT5rBjH9BzHm5jux6Q98IiJyClRMpVUxTZPsl18m999v4H3uuUS9+AJ2H62RJyJyKrauWMrSma/RqV9/Lrr9buwu+lghIiKnRv+CSKthVlWR8cADFH4xD//Jk4h46CEMV1erY4mINEs7vlvBojdeon18Xy7+23TsLvp9KiIip07FVFqF2qIiUm+5lbI1awi57VaCb7wRwzCsjiUi0izt+vE7Fr72L9p268n4u+7Dxc3N6kgiItLMqZhKi1ednk7KDTdQmbyfyGeexn/8eKsjiYg0W7sT1/DVy88REduVS//xIK7uHlZHEhGRFkDFVFq0iu3bSbnhRhwVFbR7awbeAwdaHUlEpNnat3EdX77wFKEdOzPxnodx8/C0OpKIiLQQNqsDiDSWkpUrSf7TVHB1ocMH/1MpFRE5Dfu3bOSL5x8nOLo9k6Y/iruXl9WRRESkBVExlRYp/+NPSLnpr7h1aE+Hjz7CPTbW6kgiIs1W6vatfP7sYwRGRDHpvkfx0GzmIiLSwHQqr7QopmmS/eJL5L75Jt5DhxD9wgvYvL2tjiUi0myl79rB3Gcewa9NCJfd/zhefv5WRxIRkRZIxVRaDEdVFRn33kfRl18ScPnlhD/4AIbW1BMROWWZe5KY8+RDeAcEcNkDT+DlH2B1JBERaaH0qV1ahNrCQlJvvoWytWsJueMOgv9ynZaDERE5DVnJe5nzxAN4+Phy2QNP4hMUbHUkERFpwVRMpdmrSk0j5YYbqD5wgMjnnsP/4ousjiQi0qzlpOxn9uP34+rhyeUPPoFfmxCrI4mISAunYirNWvmWraTcdBNmVRVt356J99lnWx1JRKRZy0tP5dPH7sPm4sJlDz6Bf2i41ZFERKQV0Ky80iw5ysoomDOX/dOmYXNzo8OHH6iUioicpoLMDD599F4ALnvgCQLDIy1OJCIirYVGTKXZcJSXU7JyFUVfL6RkxbeY5eV49OxJ23+/jkuITjMTkeZp15rVrPvyc2prqq2OQmF2FgCXP/gkwVFtLU4jIiKtiYqpNGmOigpKVq6k+OuvKV7xLWZZGfbgYPwvHY/f6DF4JZyFYbdbHVNE5KSVFuSz7J032LVmNUFRbQkIs/6UWb+QUAZOnEJIuw5WRxERkVZGxVSaHEdlJaWrVlG08GtKli/HUVaGPSgI/4svxm/MaLwSErQMjIg0W6ZpsvO7FSybNYPqinLO/cNV9L94Ijb9kU1ERFoxfbqXJsFRWUnp6tXOMrpsGY7SUuwBAfhddJGzjPbvrzIqIs1ecV4OS996jb3r1xIR15VRN9xGcLROmRUREdEnfbGMo6qK0tWrnafpfrMMR0kJdn9//MaOwXf0aLzPPhvD1dXqmCIip800TbYuX8KK92biqK3l/Gl/oe+Yi7DZNEoqIiICKqZigar9+8l9+x2KFi7EUVyMzd8f31Ej8Rs9Bu+BA1RGRaRFKcw6yOIZr3Bgy0badu/FyBtuJSA8wupYIiIiTYqKqZwxFbt2kfvmDIoWLsRwccFv7Fj8xo7Be+BADDc3q+OJiDQo0+Fg4+KvWPXBu2AYjLjur8QPH41h00ptIiIiv6ViKo2ufMtWct58g5Kl32Dz8iLomqsJvvpqLfEiIi1WfkYai954mbSd2+jQux8XXn8zfm1CrY4lIiLSZKmYSqMpS0wk5403Kf3uO2x+frT5618JnPonXAIDrY4mItIoHI5a1n/1Bas/fh+7myujbrqdHucNxzAMq6OJiIg0aSqm0qBM06R09ffkvvEGZYmJ2IOCCLnzDgL/8AfsPj5WxxMRaTQ5KftZ9MZLZO7eReeEAYz481/xCQq2OpaIiEizoGIqDcJ0OChZvpycN96kYssWXMLDCbv3XgIum4zN09PqeCIijaa2poa1X8zmhzkf4e7lxbhb/06Xc4ZqlFREROQkqJjKaTFrayn6+mty35xB5a5duLZtS/ijj+B/6aXYNKGRiLRAjtpaCg5mkpeeSl5aCjtXf0v2/n10GTSEC669ES8/f6sjioiINDsqpnJKzOpqCufNJ3fGDKr278etc2cin3sWvzFjMFz0n5WINH9VFeXkp6eRm5ZCXloqeenO+/yMdBy1NfX7+YeFc8md9xJ79jkWphUREWne1CDkpBXOm0fWiy9Sk56Be/duRL38Er4jRmgJBBFpdkzTpKywgLy0FHIPKZ95aakU52bX72fYbASERRAU1ZZOZ51NcFRbgiKjCYqKxt3L28J3IMdjt9vp1asX1dXVuLi4cNVVV3H77bdjs9lYsWIF48ePp2PHjvX7P//884wYMeKox/v00095+OGH2bFjBz/99BMJCQkA5ObmMnnyZNauXcvVV1/Nq6++Wv89H3/8MU888QS1tbWMGzeOZ599FoD9+/dz7bXXkp2dTVBQEO+//z7R0dGN9JMQEWnaVEzlpFRs3076P+7Bo2dPIh5+GO8hQ3QdlYg0G8V5OWTu3uW87dnFwX17qCwtrX/e1d2DoKhoorv1ICiqLUFR0QRHtSUgPAK7i6uFyeVUeXp6snHjRgCysrK48sorKSws5JFHHgFgyJAhfPnllyd8vJ49ezJ37lxuuOGGw7Z7eHjw2GOPsXXrVrZu3Vq/PTc3l7///e+sW7eOkJAQrrrqKr755huGDx/OXXfdxbRp07jqqqtYtmwZ06dP57///W8DvGsRkeZHxVROmGmaHHz6GewBAbR7523svr5WRxIROarKslIy9yTVl9DM3bsoyc8DwGZ3IaR9R7oMGkJwdLu60c+2+AYF6+yPFiw0NJQZM2bQv39/Hn744VM6Rrdu3Y643dvbm3PPPZfdu3cftn3v3r3ExcURUrd294gRI5gzZw7Dhw9n+/btvPDCCwAMGzaMSy+99JQyiYi0BCqmcsJKvvmGsp9+IvyhB1VKRaRJqamuJmf/PjLqCmjm7l3kpafWPx8YEUXbnr0J7xxHREwcIe074qIJ2lqlTp064XA4yMrKAmDVqlX06dOn/vk5c+bQuXNnxo4dy8yZM4mMjDyt14uJiWHnzp0kJycTHR3N559/TlVVFQC9e/dmzpw53HbbbXz22WcUFxeTm5tLcLCWGRKR1kfFVE6IWVXFweeewy2mMwGXXWZ1HBFpxUzTJD8jnczdP5NRNxqanbyX2hrnhERe/gFExHah25BhhMfEEd4pFg+toyyHME2z/vHRTuVdsGBBg7xWYGAg//73v7niiiuw2Wycc8457N27F3Bez3rzzTcza9Yshg4dSlRUFC6aQFBEWin99pMTkve/D6jef4C2b83QrLsickZVlJaQuXsXGUk/k5G0k4zdu6goKQbA1cOT8E4x9Bs73llCO8fhG9xG177LUe3duxe73U5oaCg7duw4I6958cUXc/HFFwMwY8YM7HY7AJGRkcydOxeAkpIS5syZg7+/lhsSkdZJDUOOqyY/n5zXX8d7yBB8hgyxOo6ItGAORy25KQfISPqZ9KSdZCT9TF5aivNJw6BNdDtizx5ERGxXImLiCIpui81mtza0NKzaGphzLcRPga5jG/TQ2dnZ3Hjjjdx8881n9I8XWVlZhIaGkp+fz+uvv84nn3wCQE5ODkFBQdhsNp566imuvfbaM5ZJRKSpUTGV48p55VUcZWWE/eNuq6OISAtTVlgeHsiyAAAgAElEQVRA+i8joUk/k7knieqKcgA8ff2IiOtK9yHDiIjtQlinWNy9vCxOLI3KNGHh3bD9C+h8QYMcsry8nD59+tQvFzN16lTuuOOO+ud/e43p/fffz+TJk496jelnn33GLbfcQnZ2NuPGjaNPnz4sWrQIgA4dOlBUVERVVRWff/45ixcvpnv37tx2221s2rQJgAcffJC4uDgAVqxYwfTp0zEMg6FDh/Laa681yHsWEWmOjEOvs2hqEhISzMTERKtjtGqVu3ezd/ylBF5xOeEPPmh1HBFp5kzTZO/6n9i5eiUZSTspzDoIgM1uJ6R9JyJiuxAZ24WI2K74h4XrlNzW5ofXYNG9cM6tMPIxq9OIiDQJhmGsM00zweocjU0jpnJMB599FpuXF21uucXqKCLSzOUcSGb5u29xYOsmvAODiIrrRp+R44iI7Upop864urlbHVGstONLWHQfdLsERjxidRoRETnDtFibHFXJqu8oXbmKNjfdhEtgoNVxRKSZKisqZOnM13nv7lvJ2reHC665getf+w8X3zGdhIsnEtW1u0ppa5e2Hub+BaL6wYQ3oQmtJZucnEzPnj0P2/bwww/z/PPPA3D11Vcze/ZsAPLy8ujbty//+c9/jnnMV199lZiYGAzDICcnp367aZrceuutxMTEEB8fz/r16wFYvnw5ffr0qb95eHjw+eefH/NYIiLNjUZM5YjMmhqynn0G13btCPzTH62OIyLNUG1NDZsWf8X3sz+gqrycPqPGMeiyK/H00TrIcoiCFPhwCni1gT98BG7N8zriwsJCRo0axfXXX88111xzzH0HDx7MRRddxPnnn3/Y9oULF5KUlERSUhJr1qzhpptuYs2aNQwbNoyNGzcCzvIbExPDyJEjj3ksEZHmRsVUjqhg9mwqk3YT9crL2LQIvYicpH0bElnx3kzy0lNpH9+XYVf9heDodlbHkqamogg+uAKqy2HaF+ATanWiU1JSUsKYMWO48soruemmm467f9++fY+4/YsvvmDatGkYhsHAgQMpKCggIyODiIiI+n1mz57NmDFj8KqbCOxoxxIRaW5UTOV3aouLyX75Fbz698d3xAir44hIM5KblsK3781k38Z1BEZEcundD9KpX39NYiS/V1sDs6+B7J3wp9kQ2s3qRKfsjjvu4LrrruNvf/vbYdv79OlTP9J5ItLS0mjbtm3919HR0aSlpR1WTD/66KPDZhUWEWkpVEzld3LeeIPa/HzCpt+jD5MickIqSkr4YfYHbFz8Fa7uHpw39c/0HX0RdhdXq6PJ8TgcUFFAbUkmB/L3UNsmDruLGy6GC3abHbthP+z+sO2G/dT+nTBNWPh32L0ULn6pwZaGaQxHe3+Hbr/gggv44osvuOuuuwgN/XXU92RKKTivMT3W62RkZLBlyxZGjRp1UscVEWkOVEzlMFUpKeS/91/8J0zAo3t3q+OISBPnqK1l89KvWf3p/6gsKaHX8JEMvmIqXn7+Vkdr3aoroDT7CLccKMmC0mwKS7PYVJ3HJrOcTe5ubHV3o/QUJh36paAeWlp9XH3wd/f/9ebmvA9wD3B+vXcV/lvex3/AtQT0uBRfRy12m70RfhCnLzg4mPz8/MO25eXl0bFjx/qvp0yZwrnnnsvYsWNZvnw5vr6ndh11dHQ0KSkp9V+npqYeto7qJ598woQJE3B11R98RKTlUTGVw2Q99zy4uhJy221WRxGRJm7/5o2seO8tclL207Z7L86/6i+EduhkdazmyzSd11pWlUJVsfO+suQIX/9y+83XlSVQlgMl2c79D1EL7HZ1ZZO3L5u8fNjsZifZqxZwxY4bce7BXOTbgZ7ubfDc9jm1NRXUdr+E2s7DqcWk1qylxlFDrVlLraOWGrOGWkctDtNR//iXfaod1ZRWl1JQWUBRZRFpJWn1j00OGRGMDIespfDxUgB83XydxbWuxHq5euHp4ll/83DxcN7bPY683eU32+0eDVJ2fXx8iIiI4JtvvmH48OHk5eXx9ddfc9tv/p28/fbbycjIYMKECSxYsAC3U5if4ZJLLuHVV19lypQprFmzBn9//8NO4/3www956qmnTvs9iYg0RSqmUq9s7VqKFy+mza234BrWPCegEJHGl5+Zzrf/fYc9iT/iHxrGJXfcS8zZg3Tq/4lyOCB/H6RvcC6Tkr4BsrZDZRGYjhM7hs0F3Hzqbt7gXvc4si94h1Do4ccmo4pN1QVsKs9ka/E+SmvKAQh0D6R3SG/Gh/amd0hvegT3wMv1kJlwB94NX/0N1rwPqTthwhvQJvb037bpoHj/dxR+NIXCNjEUXPgQhbXlFFYW1t8KKgsorCqksKKQjNIMKmoqKK8pp7ymnIraipN+zUmxk3j4nIdPO/t7773H//3f/3HnnXcC8NBDD9G5c+ff7ffMM89wzTXXMHXqVD788EP69et3xNN5X375ZZ599lkyMzOJj49n7NixzJw5k7Fjx7JgwQJiYmLw8vI6bNmZ5ORkUlJSOO+8807oWCIizY1xpOsZmoqEhAQzMTHR6hitgulwkHzZ5dTk5tJ54QJsnp5WRxJptUzTpLyokLyMNPLT08jPcN6qKk7+g3nDh3OQumM7dldXBky4nLPGjsdFM3cfnWlCwQFn+UzfAOnrIX0TVBY6n3fxgPB4CO8JnkG/FsxfCqebN7j71j2u2+7uA3Y3OOQPAYWVhSzdv5T1WevZnL2Z5KJkwHmabVxgHPEh8fQO6U2fkD5E+0Yf/48Ipglb58CCu5yjuBc8AANvgtMZgSxIgZnDwcUdrvvmpGfgdZgOKmoqqKh1ltVDS+uhX9dvry2nS2AXLmjXdK9fFRE5EYZhrDNNM8HqHI1NI6YCQOEX86jYto3I555VKRU5Q6orKyjIzCDvl/KZnkp+Rjp5GalUlpbW72d3ccE/LAIPbx8L0/6q57ARDJp8JT6BQVZHaXqK0g8poXW3slznczZXCOsBvSY5RzYj+0JIN7Cf2j/FpmmSeDCROUlzWJK8hCpHFUEeQcSHxDM+ZvyRR0NPlGFAr8nQYQh8eTssvg92zIdLX4fg348UHldFEXxwufPa12nzTmlZGJthw8vV69Tej4iINHnHHTE1DOMd4CIgyzTNnnXbgoCPgQ5AMnC5aZr5hvNPsC8BY4Ey4GrTNNfXfc9VwP11h33cNM13jxdOI6ZnhqOsjD2jx+ASHk6Hjz7EOIXJL0TkyEzTpDg3h7zUA84R0Iy0+iJanJN92L4+wW0IiogiMCKKoEjnfWBkNH4hIdia6MQwrVpZnvNU3LR1v5bQkkznc4bdufxJZB+I7OcsoWE9nKOFpymvIo95u+cxJ2kOyUXJ+Lr6Mq7TOCbFTaJLYJeGP6XaNGHzx7Dwbqipggsfgf5/gRP9t6K2xllK930Lf5wNnYc1bD4RkRZOI6a/mgW8Crx3yLZ7gG9M03zaMIx76r7+BzAGiK27DQD+DQyoK7IPAQmACawzDGOeaZqHT3Mnlsid+TY1WVlEvfiiSqnIaaqurODg3t1kJP1M+q6dZOz+mdL8vPrn3Ty9CIqMIrprDwIjfymh0QSGR+Lq4WFhcjmmqjLI3Owsob/c8pPrnjSgTRx0Ot9ZQKP6QVhPcGu4kT2H6eCnzJ+YvWs23xz4hhpHDX1D+/KX+L9wYfsL8XRpxDNdDAN6T4GOQ2Herc6Cun0ejH8Vgjoe+3t/WRZmzzdw8csqpSIiclTHLaamaa40DKPDbzaPB86ve/wusAJnMR0PvGc6h2F/NAwjwDCMiLp9l5immQdgGMYSYDTw4Wm/Azkt1ZmZ5L7zDn5jx+DVr6/VcUSaFdM0KTiY8WsJTdpJ9v59mA7nBDYBYRG06xFPeEwXQtt3JDAyCi//AE0S1NTV1kD2zl8LaPp6OLgdzFrn837RzvJ51jUQdRZE9AYPv0aJklOew+e7P2fOrjmklqTi7+7PlC5TmBw3mc4Bp3BK7enwi4Q/fgob3oevp8O/B8PIR+Gsa48+evrDa5D4Dpz7NzjrqjObV0REmpVTvcY0zDTNDADTNDMMw/jlYpEoIOWQ/VLrth1tu1gs61//AoeD0LqZBkXk6CrLysjcvYuMJOdIaHrSz1QUFwHg6uFJREwsZ4+fTERsVyJiu2gtz+bANKFgf10JXe+8ZWyE6jLn8x7+zvI55A7nfWQ/8A1r1Ei1jlp+yPiB2btm823Kt9SYNfQP78/NfW9mRPsRuNtP/3TgU2YY0G+qc3R43i3w1Z2/jp4GtDt83x1fwuL7ofulcMGDVqQVEZFmpKEnPzrSMIB5jO2/P4BhXA9cD9CuXbsj7SINpHzzZormzSf4+utxjdLfCUR+qygnmwNbNpK+awcZST+Tk3rAWWSA4Oh2xCQMICK2CxGxXQmObqvrQJuLwjTnqaW7l0LyaufanwB2d+foZ7+rnCU0qh8EdTps9tvGdLD0IJ/t/oy5SXPJKM0g0D2Qqd2nMjF2Ih38O5yRDCcsoC1M/QzW/QcW3Q+vnwOjnoB+05w/r7T1MOc6589xwhsnfj2qiIi0WqdaTA8ahhFRN1oaAWTVbU8F2h6yXzSQXrf9/N9sX3GkA5umOQOYAc7Jj04xnxyHaZocfPoZ7G3aEHz99VbHEWkSqisqSNmxhf2bNpC8eQN5ac4TPTy8fYiI7ULcwHOJiO1CeExck5khV05AdTns/x52f+MspNk7ndt9IyF2JEQnOAtUWA+wuzZ+HEc1maWZpJekO2+l6WzL2cbq9NU4TAcDIwZyZ8KdXND2AlzPQJ5TZhiQcC10vgC+uBnm3wrbv4Dz/gGfTAWfEPjDR+Cqmd5FROT4TrWYzgOuAp6uu//ikO03G4bxEc7Jjwrryusi4EnDMALr9hsJTD/12HK6ihctonz9esIfexS7j7fVcUQsYTocZB9IJnnTevZvXk/azu3U1tTg4upGdPee9LpgJO3j+9KmbXtdF9qcmCbk7HIW0d1LYf9qqKlwjoi2Pwf6/gk6D3fOmtsI/7tW1zqLZ1ppGhklGaSVpJFeku68L00nqywLh+mo399m2IjwjuDantcyMWYibf3aHuPoTVBgB+cSMGtnwtKH4J2R4O5ftyxMiNXpRESkmThuMTUM40Oco51tDMNIxTm77tPAJ4Zh/Bk4AFxWt/sCnEvF7Ma5XMw1AKZp5hmG8Riwtm6/R3+ZCEnOPEdlJVnPPY97164ETJxodRyRM6q0IL+uiG5g/5aNlBUWABDSrgN9x1xC+/i+RHXtjqubhdfxyckrL3AuR7J7KexeBkWpzu1t4pyTFMUMh/aDT2um3BpHDQWVBeRV5JFfkU9+RT55FXnklOeQUZpRXz6zyrIwD7laxWbYCPMKI9InkrPDzybSJ5JI70iifKKI8Ikg3Cu8aY+MngibDQZc7/w5f/us85Te0K5WpxIRkWbkuOuYWknrmDaOnLfeIvuf/6Ldf97Be9Agq+OINKqaqipSd25zFtFN68k+kAyAl38A7Xv1oX18X9rH98UnMMjaoHJyHA7nuqG/XCuamuicNdfdDzqd5xwRjRn++wl5DmGaJlllWfVFM6/y8MKZX5FPfuWvXxdVFR3xODbDRrhXuLNw+jgL5y/3Ed4RhHmH4Wpr5sVTREQso3VMpUWqyckh94038Rk2TKVUWoSaqipKC/Ioyc933uflUVqQR2l+PkU5WWTs2klNdRV2FxeiunZnyJVX06F3P0LaddC6vc2NwwGpa2HbXNj2OZRkAgZE9nHOmtt5uPN60WOMPpqmyfa87SxOXszi5MWklqT+bh+7YSfAPYBAj0CCPILoEtSFQHfn40CPwPrtge7OxwHuAdg18ZWIiMhpUTE9AxyVlZStTcSsrLA6CoVffomjspLQu/9udRSRY6quqKA4L7euZOZRWpBPSd19aX5ufRGtLC393ffa7Ha8AgLxCQwi/sIxdIjvS3S3nrh6eFjwTuS0mKZzKZdtnznLaFGq81rR2Auh+3hnGfUOPs4hnGV0UfIiliQvIbUkFRfDhQGRA/hT9z8R5hVWXzqDPILwdfPFZuiPFiIiImeSimkjMU2Tiu3bKZwzl8KvvsJRWGh1pHpB116Le8eOVscQ+Z2SvFyS1v5A0o+rSd2xDfOQCWIA7K6ueAcE4R0YSHBUW9r17I1PYBDeAYF41937BAbh6eun0dDmzDSda4lurRsZLTwAdjdnCR3xEMSNBg+/4xzCZHvudhbtX8Ti5MWklaTVl9Hr46/ngnYX4O+udWZFRESaChXTBlaTn0/R/PkUzP2Myp07Mdzc8B0xAv/xl+AS0gRmJ3RxwT021uoUIvWKcrLZ/dP37FqzmrSfd4BpEhTVlrMvnUxQZDTeAUH4BAXhHRCEu7e3ZsdtqUwTMrfUjYx+Bvn7wObiXIpk2HToMhY8A45ziLoymryIxfsPL6M3xN+gMioiItKEqZg2ALOmhtLVqymY+xnFy5ZBdTUePXsS9uAD+I8bh91fH4REDlWYdZCkNavZtWY1GUk/A9CmXQfOmXwlcQMHExx99AlrpHlymA72FuxlU/YmNmVvIrci13kdZ62DgPwDBGZuI6Aok0AHBESeReCgm/DrMRG797H/oGeaJttytzmvGVUZFRERabY0K+9pqEpOpmDuZxR+/jk1WVnYAwLwH38J/hMn4tGli9XxRJqU/Mx0ktZ8z64fV3NwbxIAoR07EzdgMLEDBhMUGWVxwlagNBcqi8DdF9x8wMW9UdbxBCiqKmJz9mY2Z21iU9YGtuRspbjGeT2wv4sXEYY7hZUFFFBL+VFOuzYw8Hf3J8A9wHnzCCDQPbD+Pq8ijyX7lxxWRke1H6UyKiIiLYpm5ZUjcpSWUvT1Igo+m0t54jqw2fAZMgT/++/D9/zzMdzcrI4o0mTkpqU4y+ia1WQn7wUgPCaOoX+8htgBgwkIC7c4YQtWWw0Ht0LKWudMtqlrnafHHsrm4iyovxRVd59D7n2P/jU4C25FIVQU4igvZG9ZBpsqs9hUXcAms5y9Nuf1wTbTJKaqmtGVlfSurKJ3RSXta2owMJzrivacQHnsSApd3eqXZymoKHDeVxaQX+G8L6goIL0kne0528mvzKfaUa2RURERkRZExfQEmKZJ+fr1FMydS9HCrzHLynDr0IGQO+/A/5LxuIaFWh1RWrnSgnwy9+yiIDODpnAWREVJCbvX/kBu6gEAIuO6cf6064g9+xz8QvT/l5NRVVtFQWUBhZWFVDuqsRk2DAwMw8CGzTl7rAG2khyMg1uwZW7FyNyCcXAbtppKDMDwboMtog9G7yuw+YRgqyrFqCrFVlWGvboUo7IUW1UJtspSbFXF2IozMKpKobIYqkrAUXNYpiKbwWZ3dza7u7PJ3Y0tHh4U25wjr/4YxNu9GesaQG+PcHr5ROPt1ca5vqiHv3PSIo8A5/qiPs7/FjzrbuHeJ/aHCtM0Kaspw8DAy9WrAX/aIiIiYhUV02MwTZOiBQvIefU1qvbtw+blhd/YMQRMnIhn376ahEUsUV5cxMG9u8nck8TBvUlk7kmiJC/X6liHMwyiu/Zg2NU3EHv2IHyD21idyHI1jhoKKwsprCp03lcW1hfO3z4urPr16/Ka8pN/MTsQ+ZufedUO2L/j+N/r6rwZ2LAZgRhGEDZs2OsKsc2AkrpMNsNGTEAMo0N607vu1t6vfaP/bjQMA29X70Z9DRERETmzVEyPonzzZg4+9TTlGzbg3rUrEU8+id+okdi89WFIzpzKsjKy9u0m85AiWngws/75wIgoorv1JLxzHGGdYwiObofNZrcwsZPNxY6rm7vVMRpdWXUZuRW55Jbn1t/nVeT9/uuKXIqrio96HLthx9/dv/56ynCvcLoEdsHf1ZsA08C/tga/qnLcClIxc5Mw8w/gMGswAdM7BEdwJ8ygTjgCO4J/NA6bHUfdUjsO04EDB6Zp4jAdmNTdmya1Zq1zOw7nfnW3X577Zf/6/eqeD3APoHdob3q16aWCKCIiIg1CxfQ3qjMzyX7hBQq/mIe9TRsinngc/0svxbBb/2FfWrbqygqykvfVj4Ie3JNEXkaacxkNwC8kjPBOMcQPH01451jCOsXg7qVS0JhKq0tZun8pKcUpRyygRxvN9Hf3J9gjmCCPILoEdSHYI5gAD+cEPv5u/nX3vvjX1uJfUYxPSQ5GURoUpUFhChRugcJUKM0+/MCuXhDZD/pcCNH9IToBfHWdroiIiDR/KqZ1HOXl5L79Drlvvw21tQRffz3B11+P3Ucf/KXxVFWUk7Tme7avXEbK9i2YDucol3dgEOGdY+l67nnO0dBOMXj5aWKXM2VvwV4+3Pkh8/fOp7S6FJthI9A9kGBPZ9lsG9qWYI9ggj2D6wvooY9d7a7OA9VUQfYO5/qcuclQuMlZOAtTnSW0turwF3b1Bv9o5y08/tfH/tHgFwUB7cGuX9siIiLS8rT6Tzimw0HRV1+R9c9/UZOZie+Y0YTeeRdu0Vq6QhqHw1FLytYtbF/5Dbt++p6aykr8Q8NIuHgikbFdCe8ci09QsNUxW50aRw3LU5bz0c6P+CnzJ1xtrozuMJorul5Bz+Ce2I93inRVKWRuhcx5kLHJecvaAY5q5/OGDXwjnSUzqh90vwT82x5ePD0DG235FhEREZGmrFUX0/KNG8l86ikqNm3Go0cPop5/Dq+EFr9EkFgkNzWF7Su/Yft3KyjJzcHN04tu555P96EXENWluybTskhOeQ6zd83m012fklWWRaR3JLf1u42JsRMJ8gg68jeV5UHmZsjY7CygmZshJwmomxHZK9g54jnorxDRG8J7Q2AHjXaKiIiIHEWr/JRUnZ5O1j//RdFXX+ESEkLEU0/hP/4SjKMs8i5yqsqKCtm5eiXbVy7j4N4kDJuNDr37cf7UP9PprLNbxQRBTZFpmmzI2sBHOz9iyYEl1DhqOCfyHO4fcD9Do4f+OjpaWw3FGXBwe10R3eQso4UHfj2YXzRExEOPic4SGhHvHP3UHxpERERETpjRFNY8PJqEhAQzMTGxwY7nKC0l9+23yX37HQCCrr2GNtddp5l2pUHVVFezb/1atq1cxr4Na3HU1hLSoRM9hl5A18Hn4R0QaHXEVqusuoyv9n3FRzs+ZFdBEr4unowP7scV3p3oUFUJxZlQkum8L86EspzDDxAc4xwJ/aWAhvcGb512LSIiIo3HMIx1pmm2+NM6W8WIqelwUDhvHtn/eoGarCz8xo4l9M47cI3SdaTSMEzTJCPpZ7avXMbP36+korQE74BA+o0dT/chwwhp39HqiC2HaTonDaoug+py562qtO5x2SH3ZVBVBqVZJBfs5eOSPXxhFlBsQJfKKh4qLmZsSRleST87j2vYwScMfMMgoJ1z1lvfcOetTRcI7wnuvta+dxEREZEWqsUX07L16zn45FNUbN2KR3w8US++iFe/vlbHkibKNE2qKyuorqigqryMqvJy5+OKcufXFRVUV5RTVV5OVUV5/ePMPbvIz0jHxc2dmP4D6TH0Atr16oNNywyduLI8yN4JWdudkwblJEFl8W8KZ91js/a4h6sBVnp58pGfLz94euBiwoV2f/7gE0ufwK4YvuHgG+Esor4RzutCm8AasCIiIiL/396dh9lx13e+f3/r1Fl7lXqRtcuWJVuWF9mWV2yHAI6XYewxkIG5uQEnw5NhuyyZZPLkCYEwk7k3k0tuHjKZYYYthmxAgmFYbGPMADbgTTaWV7zJlrXYUrd6U/fZq373j6pzTp1WS5ZsqU9L+ryep56q+lV1nTpHJel8+redjE7IYFrbvZup2+9g6vbbKT/+OP6SJSz78/9C71vfqn6kAkQBdOeTj7H1rjvY+8LzrZBZLjfnDX01qXSaTC5PJp+nb3gJF934DtZfcgXZQuEY3/1xrjINI0+3AmhjPf1K65xsLwyuh8JiSOejaVTS+Wgez3QeMoXWdtu6wPbqJN985ed8e9dPGKmMsaSwhA+t/3Xevv7tDOYHO/e+RUREROSgTphgWh8ZYeqO7zN1++2UHn4YgNzZZzP8B3/Aonf+azyFBQHK09M8efcP2fqD2xnbvZNsVxerz95EptBFJh+FzHQ2RyZfIJPLkc7no/AZB9B0vJ3O5Uj5J8xfn2OjXoHRZ+Lw+VQrhE5sb53j52HoDFj7Jhg+E4bPguENRzx4UKle4q7td3HrU3/Hlj1bSFmKK5dfyU3rbuKqFVfhe/qzEhEREVnIjutva/Xxcfb/4AdM3XY7xQcegDAku349Qx/9CL3XXUdm9epO36IsAM45XnnuGbb+4Hae/vnd1GtVlq47g2s/8DHWX3aFRsZ9rYIaTO2GyZ3xsiNedsL4dhjb1mpy6/lRDejyC+H834zC5/CGaAqV19h81jnHk2NPcuszt3LbC7cxXZtmVc8qPnLBR7hh7Q0MF4aP3nsVERERkWPquAumwf797P/hD5m67TZmfn4v1OtkVq9m8H3/jt7rriO7bl2nb1EWiGqpyFM//Qlb77qdkRe3kc7l2fjGN3PuW65jeM1pnb69169ehaldURiciENhcSxu6toVLekCZLrj/Xg7XWgdz3SBnzuwdtI5KE8kQufOxOvE+/tfpjlvZ0NhEPpWRLWfG/9VHEDPgsVrwc8clbc9WZnku9u+yzef/SZPjz9NNpXl6tVX87Z1b2Pzks2aD1ZERETkOHRcBNOwWGT6xz9m8rbbmLn7Hly1SnrZMgZufg+9119PdsMGfRldAIIwYLo2zWRlkqnqVHM9VZlisjp5wNowutJdFNIFutJddPmt7UK6QJff1dxO7nelu8j7+YP+me99cRuP3nUHT/30R1RLJYZWn8pb3vtBNlzxK2Tyx1GT7upMK3BOvNQeQCd2zB0Mc31QK0NQOfzXMS/qw9kIr5aKrl2dbj8vlYlCZ98KWPur8fbKxHp5FIqPgdCFPPDKA9z67K38cPsPqYZVNizewMcv+TjXnXYdvZneY/K6InI41EUAACAASURBVCIiIjI/FvQ8pheccYb7zr94K/t/9CNcqYQ/NETPddfSd/315M4774QNo845SvUSxXqRUi1ex/uhC+c8f87rzA4tsXpYJ3AB9bDeXGph7YCyg5a7OjO1mQMC6HR1+qCvCZD38/RkeujL9tGb6W2+z5naDDO1meb7PByGUUgXyKVyZFIZ8i7DKbtSLHvO0T0SEqZgZm0XpY2LYWkPWT86L5PKkPEyZFNZ0qk02VSWtf1ruWzpZUfveXIu6l9ZL7WPJFuba78I9XK0XZqAyZei0DnxEpTG2q/r+VHfy/5VURDsX9m+7lsBftwsOahDbSYKt8mlVowCZ7UYl03HZYlzwhr0LIuvu6IVPAuDMM+Dh70y8wr/67n/xTef+ya7pnfRk+nhrae9lbetextnLj5zXu9FREREpBNOlnlMF3QwPTuXd7eefz491/wavddfT+HCC7EFNv1GLahRrBcp1lrhsVgrzr1OnFeql+Y8r3HsUAFvPhmG7/nNJe2lSVmKrnQXvdle+jJ9beveTG8zeM5eZ1Kv3pQzCAOK9WIzqBZrxWZwnanNND+rxn5lZJzUo6+QeWoMrxJS7fMZOzPH3lM9Sn4UrCtBhWpQjZawSiWoUA/rba97zuA5vP+893PF8isOL6BW9sPOB+Gl++Gle2Hshfaw+Vr+/NKFOQLnqtZ+zykn/HQm5XqZJ/c9ydaRrdz/8v3c+/K9hC7kklMu4aZ1N/HmVW8m5+c6fZsiIiIi80bBdAG44Mwz3UOPPYal00f8s0EYUAkqlIMylXq0LtfLzbJyvdw8VgkqlOql6FjjnMbxoEKlXpkzYBbrxQMCzqFkU1kKftQsNe/nKfgF8ul47eejJqvx8QPK/AI5P0fqIMHEmDtMzVWe8lJR0DS/LXT6nk/KUqS9dHPfs4U3vc7k3ld49oF7efaBe9n99JN4KZ91F1/GeVdfx4qzzjmsYBm6kGoQhdS7tt/F5x79HLtndnPu0Ll84LwPcPmyy9uvM7krCqA77oeX7oM9j4MLo2awSzbC8Ma4T2c+sSSmMfFzif3GsUSZn4fUcdGy/qh6ZeYVHhl5hK17t7J1ZCtPjT3V/Du1smcl1665lptOv4mVvSs7fKciIiIinaFgugCs2bjG/e7f/m4UDpOhMREoDxY8jyQwJnnmkUvlyPk5sqksOT9HLpWbMzgeECTjkDl7uxFENWXFa+OcY3THdp574F6efeDnjGx/AYCh1adyxmVXcvavXk1X/6LX9Rq1oMa3nv8Wn3/087w88zKb+tfz/p6zuGxsN7bj/qhfJ0R9MVdshlWXwspLYMVFkFP/xsNRC2o8NfYUW0e28sjeR9g6spU9xT1A9EubjQMb2TS8ifOGzuO8ofMYyA90+I5FREREOk/BdAHIn5p36z+1PgqIqRxZP16nsm3bjRCZ3G4EyoOV5f188zqN7Vwqh+/5J2zf1eOJC0N2P/s0zz14L889cC8Te14GM5at38C6iy7l9Isvp3/JKUfnxaozsOsheOl+qtt/xrfGH+Nz3Rn2+D7n10I+0LWeS9Zcja2+DJacc1LWbL4Wo6XRZk3oIyOP8OS+J6nEgzIt7VrKpqFNnDcchdAzFp1BOnXkLSNERERETnQKpgvAhZsvdFse3KKgeJII6jV2PPFYFEYfvI+ZiXG8lM+qc85j3UWXsXbzJa+vZrRWhn3PwejTMPJM+zqsAxZNb7LqUqrLN3Orm+Dzz9/K3uJeLhi+gA9u+iAXL734qL3f40ljoKqJygQTlQkmK5PNZaIywWS1fX+kOMLumd0ApL00GwY2REE0rg1d0rWkw+9IRERE5PigYLoAbN682W3ZsuWwz6+WiozueInRHS8y+tJ2RndsZ2ZinNXnbmL9pVewfP0GbJ5HFZVDq5XLvLD1IZ574F62PfwgleIM6WyOUzddyOkXX8ZpF1xEttB1ZBctTyaC59Mw+ky0ntge9QsFwGDRahg8A045G1ZeCisvgnx78K0EFb7xzDf44mNfZG9pL5uXbOYDmz7ARadcdHQ+gA4KwoB95X2MFEfYU9zTXI+WRtvDZzUKm4dqHl/wC/Rl++jP9tOb7WVxbjEbBzZy3tB5bBjYQDaVncd3JiIiInLiUDBdAA4WTIN6jbHduxh96UVGd2yP1y8xNbKneU46m2Nw5Wqy3d3sfOIx6rUqXYsWs+7iyznj0itYduYGvBN8hFOIaroqMzNMjuxhanQv+0dHCGq1Tt8Wzjl2P/NLtm99mHqtSq6nl7UXXsy6iy9j1TmbSGcOEWSci6Y5Ke6D8e2t4NmoAZ1+pXVuKgMDp8Pgehg6o7UeOP2I5tysBBX++Zl/5ouPfZGR0ggXn3IxH9j0AS5ccuHr+BSODeccU9UpRooj7C3uZW9pb7SOl0b5aHn0gOmHUpZiIDdAf66/FTQzvfRn+9uCZ3+2n75MH/25/sMecVlEREREjtzRCqZmNg1cBvxtXLQKmIyXUefcWw7jGp8F/o1zrj/eXwN8GegFPOAPnHN3xMc2Af8D6AFC4ALn3EGDyIIPpnd977uJ8Bmtx1/eRRgEAHipFIuXrWBg5WqGVq2J16vpHRxu1o5WS0W2Pfwgz9z3M174xZYopPYv4vSLL+eMS9/A8g0bj1lIrVer7Nv5EmO7d5JKp8nmu8h2xUuhi2yhQMp/7X3rnHOUp/czNbI3Cp8jew/YrpaKR/EdHT3dA4NRf9FN57Ni5RBeZSKau7M4FoXO5jLWvi6NQVBtv1imB4bWRzWgzfUZ0L/6qPYJLdfLUUB9/IuMlka5ZOklfHDTBzl/+PzXfW3nHNWw2jY1TnOqnHr7fnO73r7fCKTloHzA9fuyfQzlh1hSWMJwYZihQrQ9lB9iuGuY4fwwi3OLDzrys4iIiIjMv6MZTJ1z3Yn9W4DvOuf++TB//hLgQ8C/TATTLwH3Ouc+b2bnArc65043szTwMPB/OOceM7NBYMy5WbUiyesv5GC6amCR+8hb3tDc7x1awuCq1QyuXM3gqjUMrlzN4mXLjyjYVcslXvjFFp6596ds+8UW6tUKhb5+1l18GesvvYIVG87Ge41zpc5MjDPy4jb2bn+BkXgZ270TFx708wfAz2SjoJovJAJrvCT207kcxalJpuLQObl3D1OjI9TKpbbrZfJ5eoeW0Ds0TN/QEnoHh+gdXkLf0BJ6BocOXRv5WoQh1PZDaRLKU1CJ1+XJxHZcnjjHr4xhpTGIB8Q5kEFhMRQGIB+vC7PWvcujANqzFOaxL3KpXuKfnv4nvvT4l9hX3sea3jX4nk/owrbF4QhdSOACnHNtZbPPqwU16u7wRpPOprJ0pbso+AW60l3RdrpAT7qHocIQw4XhKHTG20P5Ic3/KSIiInIcWgjB1Mx84C7gN4AnEsH0i8CTzrm/MLMrgf/snLvKzG4A3uacu/mw728hB9Mz1qx2//TF/8ngyjUMrFhFtlA4qtevlcu88MgWnr7vZ2x7+AHqlQr53j7WXRSF1JUbz5kzpAb1OuO7dzKy/YW2EFqcnGie0z0wyPDqUxmKl4EVq3BhSGVmhkppJloX43WpSGVmmkqxGJUVE8eLMwc0vc12dUXBc3CYvqHhaHt4ON5fQrar67UNGFWvQmk8qpEsjUc1lKXx9rJGeXkiCp7lOGjyKs9Rtg9yfZDvg1w/ZHuhsCgOmcngOdAKnrk+WOC1d6V6ia8//XV+sfcXeOZFCx5m1tw3WtuHKktZqhkwG2Gzy++iKxOv42OFdIG0pxFsRURERE4G8xVMzSwF3D/Xa5nZvweqwGeJmv02guly4E6gDygAb3bO/cLMfg84B1gKDAJ/75z7i0Pe30IOpkc6+NHrUauUeeGRh3jmvp+x7aEHqFXK5Hp6WXfRpaw57wL279vXDKD7dm4nqEc1WynfZ2DF6mYAjZY15HuO3tyW9WqVSnGGarlEobfvyAcDCuowtg32Pgkjv4T9r8wKmxNR2KzNHPwanh8NDJRccn2Jpb+1ne9vP5btXfABU0RERERkIep0jamZrQD+EXgjYLQH0/8AVJxznzGzK4j6lJ4D/AHwXuASoAz8CPh959xPDvY6mpAxls7mWH/JG1h/yRuoVSu8GIfUX/78Hh7733cCUOjrZ2j1qZx/3Q3N2tBFy1aQ8o/tx+hnMviZDF28ylQpzkWhc+8TsOfJKIjueSIaGKjRXNa8uIYyDpe9K6K5OfOLohrMtvC5uLWd7ZnXprIiIiIiIrIgXACsA56P93vN7Gnn3BnAvyUKrDjnfmpmvcAiYCfwY+fcPgAzuz2+joLpkUhnsqy7+HLWXXw59WqVvS9uo294yeubQ/NoK09FtZ97nogD6JNRIC2Nt87pWQrDZ8FpvxKth8+K+mMewWi0IiIiIiJyoDB0lOsBxWpAqRpQqkXbxWqdUjXartZDPA88s7irV7TtGfF+q8yax5LHO/0uwTn3beDb0OxrOhqHUoCXgDcDf2dmGwHPOTcWB9GPmVkeqAFXAX92qNdRMH0VfibDsvVndu4GqjPxdCjPREG0EUInX2qdk+mB4Q1w1o0wvBGWxCG0sLhz9y0iIiIiMo9qQchze6d5bNckeybLhA4C53DOEYSO0EHoHGFyO3ksjPedi2YnDMI4YNbbgmcjdJZqQaff8lF1qD6mh/Ax4HNm9vtEU8LcDOCc22dmfwU8FJd/xzn3/UO+vvqYLhDFsdZ8nMk5OZMB1PNhYF0reC7ZGK37V6mZrYiIiIicNCr1gGdemebx3ZM8tmuSJ3ZN8tQr+6nWD5wNw0vWRMa1l6m4hjLlNcqj2slUXLOZ8gzfM/KZFIVMinzGp5BubCfKMiny6VZZtO83tzO+h2uGYOJZGlqhOHksjEN0KyRH579h3dBR6WO60KnGdD41+oA2QufIL1thdGZv6zw/B4PrYNUlMPjuaF7OoTNh0angZzp3/yIiIiIi86xcC3jq5Ske3zXJ47umeHz3JM/s2U8tiCrYenI+Zy/r4+bL17BxWS9nL+9j5aICvheFz9c0W4XMOwXT2cIgmgIlOV1KeQLqFQiq7Uu9sV2L15XWdj2xHdSiEW/3bYvm8mzI9kWhc/2vweAZUf/PoTOgbxV4Xuc+AxERERGRYyQMHfUwakIbOEcQOOphSBCX75oo8fiuRk3oFM+NTBOEUQhdVEhz9vI+3nvlaZy9rI9zlvexcnFe4fMEcOIG0zCMQmDbXJzJuTnH5igbj0Lpq83JmZTKQioDqXS09jPxfqIslY1GuD33wjiAxjWg3UvUBFdEREREFrQwdEyVa4xOVxmbqbJvusLoTJWx6Sr7Zirsi8v2TVcp1YJmwAwSSzJ4Hm5PwsHuLOcs7+WajUvYuLyPs5f3sawvpxB6gjo+gmkYRrWWxTEo7otCZXHfrP3ZZePgDtEhOdfXmg6lsBgG1rZPkVJITJWS6wc/Gy3NsJmJ+nzqL4aIiIiIHCdqQchUqcZkqcZUuZ7YrjE+U22Fz5koaO6bifYbNZaz9eXTDHRlGOjOcNpQF11ZH9+L+mhG/TS9Zn/N1trDT9mc5SmvEUj7GO7NzfOnI520sIPp3qfgz0+LQ+aBHZkB8NLRvJyFgShMDp8ZhcvGfn5xa90InLk+8FLz+15ERERERI6iehCyY7zEC6PTjE5XmSrVomVW4Jws1Zgq1Zkq1yhWDz2SbE/WZ6A7w+KuDCsXF9i0sj/ezzLYnWGgK8virgyD3RkWdWVIp9T9TI6OhR1M03k4619FYbIw0B44G2WZbtVaioiIiMgJa7JUY9vINM+PzMTrabaNzPDivpnmAEBJPTmfvnya3lyavnyaUwe7mvu9+aisN++3lfXm0izqSpP1VXkjnbGwg+miNfDW/6/TdyEiIiIickwFoWPXeInn4+DZCqEzjE5Xmuf5nrF6oMBpQ928ecMSThvqYu1QF8M9OXrzabqzPilPlTZy/FnYwVRERERE5DjknKNYDZgo1ZgoVpks1uLtqGntRCkqG5upsn1fkRf2zbTNwdlfSLN2qJs3nTnEaUPdrB3qZu1QFysXF9R8Vk5ICqYiIiIiIoepXAt4cd8Mz++d4YXRacZmWiGzGULj/p1zNbNtyKQ8+gtp+gtpVi0u8CtnDLF2qIu1Q92cNtTN4i7NXS8nFwVTEREREZFZxmaqUZPavdM8t7fVvHbHeLFtupPubNRXsxEyzzyll97Gfrzuy2eax/vzGfryaXJpT9OeiCQomIqIiIjISSkIHTvHi63guXem2cdzvFhrnpf1PU4b6ubcFX3cdP5y1g5HzWpPG+wmn9FgQSJHg4KpiIiIiBwXwtAxOlNh71SFYjWgVAsox0ulFib2Q8r1gFI1oFKP92tB2/HpSp2X9hWpBq1+nYPdGU4b6ubas5eydqiL04ejvp3L+/N4GlBI5JhSMBURERGRBaEWhLwyWWbneIldEyV2jZfYNVFk10SJ3RNldk2U2gYIOpRMyiOb9silU+TSHvl0Ktr2U/Tm05zSm+PNG4bjQYWiGtD+gvp1inSKgqmIiIiIvC7OOUIXNY0NQkfgXGs7dITOUQ8dYego1YJE6Gxf79lfbuu/CTDUk2V5f56zlvXya2ctYfmiPEt6c3RnfXJpj6wfBc58JkXObwTRlKZMETnOKJiKiIjICc3FIakettZh235IGEI9DNvOC8IoIaU8wyxap8zw4nXKi7Y9o63c8yxxLnhmeGYYYMaCGPAmDB37K3Um46lLZi8TpSpTc5TPVALqQUjoaH5ujRD6WqRTxtK+PMv6c7zh9EGWL8qzoj/P8kV5lvfnWdqfI+urD6fIyUDBVERERI4LzjlmqgGj+yuMTlcYna4yOl1hX7yevV2uhVF4em2Z6ZjyLAqsjaBqtPab5YDnJY8ZqWTQtcY2cUC2xHXjwOy1tuuBawbMqXLtgJrJpEzKozefpi8fjTg71J3l9KFuunM+vudFwbstgBt+vO9ZtN0oawT2xnbW91jWn2N5f4GhnqxqNkUEUDAVERGReVYLQmYqdaYbS7m1PVOps79cZ7xYZXR/HDJnqs0wWjlI/8L+QpqBrgyD3Vk2LOtlsCtDIes3azZ9z0ilbNa+1wxMKc/wU61Q1QhdQLOJauhc27qxPft4a5voeOhwRNvORQG7sR862svmODd0yXNbr9k4p/F6rnlefDxsPzflGacNdUVTm+TTcfBMLIV0fCyjqUxEZN4t6GD6ymSZnz47yuY1i8il1YxDRETktXLOUamH7C/Xm6FwplJnplpnuhIwXa5TrNbjkAOORIhyNMtCBzjXtj87WBVr0fVmKnX2V9pfb3+5ftBwmZTyrBk0B7ozrB3sYrAn21Y22J1lqCfLokKGjO8d889QRESOnQUdTEenK/yfX7yfXNrjklMHuGr9EFetG+T04W79Fk9ERA7L4fQlrAVhvG6dVw8d9aB9OwjDxDmOehBSCx21ekg1CKnVQ2pBSCUIqdUd1SCI163j1SA6p1oPqQaOaj0kCMOopq6tRs9r1uKlEs0km+Wzavk8M4rVIBE2681wOF2pM1MNXnM/wNmazUxnNUVtNC0tZFJ0ZX264+WU3hzdOZ+urE9P1m871p2L1l1Zn574nO5MtK3pOURETh7mDtXBoMMuuPBC9xd/fzs/eWaEe54d4fmRGQCW9uW4ct0gV64b4orTB1nUpaG9RUSON5V6o1YtYH8lGlRlulJr1t4lt9uafcaBq1QLms0mo4AZzjGoTWf+j8v4HtmUR9r3yKQ80r5F65RHplEWb6dTHumUHTCaaT0RkmcP3NMsD+KBfOKfKWR8urKtUNiVSQa/g5X7dMfHChmfdMowGoETjKh/YqOfon4xLCIyv8zsIefc5k7fx7G2oIPp5s2b3ZYtW5r7O8eL/PTZUe5+doSfPjvKVLmOGZy7vI+r1g9x5bohzl/VTzql5jxy7NWDkHI9pFQNcM6R9VNk0x5Zf/775TgX1cgEoSOd8vDjwS5E5ksQOsaLVcZmquybjtZjMxX2zcRlM1XGplvbk6UqteDw/v9phKpkDVtXxiefSeF73kH6Dlqi76B3QN/B5L4f/53xU+3n+3Ht5FzbKc9Ip1o1mplEyNTfPxEROZoUTBeA2cE0KQgdW3dOcM8zUVB9ZMcEQejozvpctnaAq9YNctX6IVYPdM3zXZ94gtAxXa6zv1JjfzxART1wNL53Rc23WiMIRuV24HFav30344BBGtoHeEgO4tAY4MERhrMHgEheI3m8fbCItgEgZg0GUQtCSrWASi0KmeV6QLkWUKqFlGtBcynVAsq1kHJ8zqG+VGf8KKDm0qk513OVpTyPahDdRzUIW+t6QLUeUqmHs9YBlcR+khnNL8rZuHYm4yeW5n4qmoA8UZ72re3LfvOL+uwv7p4d0JyweV78pd1PWbM2KPrC7pGJr5/2PdIHnOcdcnTG5Dx5yUFIktMVJAcfcQ7SvkW/NIg/C/8Y/eKqFoQUq9GzUqwGFKt1StVou1SLfnnhJaaXSMVNLz2PtmknmtuJY41yBwRhSDCrKersGsLWftg27UXjWJD4O9ToT9j4exHMGkwljI8Hib+XM5V6M4Dum6kwNlNlonTwET778tGgNIvjZaA7Q18+Q09bjV17s87GdiGdUnNOERE5qSmYLgCHCqazTZZq3Pv8Pu5+doS7nxlh53gJiJr9DvVk6Ztr9Lk5lt58mp7swuvX0ghPjaZds0f+S37hDMLkF/XoS2zyvFK1zlQ5GoBiulxnf7kVOKfKNabjwSn2l2tRE7pq0Om3f8xlfI+c70WTc6dT5PwUuXii7mjC7nji7ngi71ZZFCzNrBkWy7U4NCbW5eZ+FHaT68bPBKFrBsTWOjVrPwqTc50XhVtr9mFrhthGX7bGEvdvq8wqS263gkyr39188Qz8VBRaG4EoGaBeLz+eqiCb+CVBsra7GWLjP+tMyqMaRL+0KNYCStV6FDariQBaO/QvKo53Ka/VhDNlRj6TaoXMWevF3dHgNAPd0f6iQkatWERERF6HkyWYLujBj45EXz7NtWefwrVnn4Jzjhf3Fbnn2REe3j7OeDx59K7xUnP+rkP1O/IMenLJsOo3+wO11f6kPDJzbKf9qNYo2azLTxmVWtisPWnVpLTXqiS3GzUux/pLbyGToifn05NL0x0PPrG0L0dPNk13zm8e60kMTOGn4uDuIB6gsTWCI1FNTHw4PqcxumPreKNGyGz23GutOdqS/Zpmz9vWmOy8dU70pdni+dxSs34+OZdbo+bKjOZAInJwjZrKtr5uway+bomBY2pB2BwYphqE1IOorBY0joXNAWHqjfK4rB62fsZr+7NM1ijSVrsYBSbaayPjWsdaEFKptWqXK4lfEjRrnWut7VItYKJUbTsn43vk0ynymagG75TeNPlMikIm1Spv7Mdl0bbfPMeMZo1+ENdENvoTzlU+1xQUjc8gWVvdvu+R8mir0U4lz40H1zl9+RAvvDzKrpe2c/nmTZy+bn2zhcNHPvIxfvPd7277O5N0991389GPfpQfP/ooX/3qV3nHO97RPPblL3+Zf/+nfwrAxz/+cd7znvcA8NBDD3HzzTdTKpW4/vrr+cxnPqOmriIiItLmhAmmSWbGqYNdnDrYxbsvW3PAceccxWrQDKmTpRpTB9meLNXi2sN680t1rTHyYvwFvLE9uznloXgGhbiPVOtLbLTdX0iTz/jk017znEI6qslLpw5s8tdYkhNaJ5sGNr6QRudFr9uT85vBU6FMXk0r+GnaphOBAcM9OYpdWdauXctjj2497J9dtWoVt9xyC5/+9KfbysfGxvjUpz7Fli1bMDMuvPBCbrjhBhYtWsT73/9+Pve5z3HppZdy/fXXc8cdd3Ddddcd5XclIiIix7MTMpi+GjOjK+7XtKw/f9Su22hu2Kr9SdYQRc00C3FT0U4MkCMi8nqtWbMGAM9rb577/e9/n6uvvprFixcDcPXVV3PHHXfwxje+kampKS677DIA3v3ud/Otb31LwVRERETaqOPPUWQWje6Yz6TozaUZ6M5ySl+OlYsLnDrYxbL+PP2FTLNPoohIpz3//PNs2rSpudxzzz0AvPe97+Vw+/gD7Nq1i5UrVzb3V6xYwa5du9i1axcrVqw4oFxEREQk6aSsMRURkcjatWt55JFHDij/whe+cETXmWsgPTM7aLmIiIhIkmpMRUTkdVuxYgU7duxo7u/cuZNly5axYsUKdu7ceUC5iIiISJKCqYjIAuecozxTo7S/2ulbOahrrrmGO++8k/HxccbHx7nzzju55pprWLp0KT09Pdx333045/jKV77CjTfe2OnbFRERkQVGTXlFRDooDEKKU1WmJyrMjFeidbxMj7e267WQDZcv5U3v3nBUX7/Rx7Tht3/7t/nwhz/Me9/7Xt73vvexeXP7tGkPPvggN910E+Pj43znO9/hk5/8JE888QSLFy/mj//4j7nooosA+MQnPtEcCOmzn/1sc7qY6667TgMfiYiIyAFsrv4/C8XmzZvdkQy+IXIkglpIcX+VarmOC8GFDudctO1ccz9M7s+xHYbR5KzONeZqjY7RmLs1jNa4xFyu7sCfwUV978ybtTYgXls8r2TymJlBPN9nY9u85Pmtn/O8xrVmXaNxXQOM5ucRBtH7c2FIGETvKwzjsvhYGIat7cA13695Rso3vJSHlzJSfrxOeXh+a99LefF5je1GuUWfTeLaYRjOuq/kNs37TN5Lm0TfxrZejnN0eWzrB/l6u0Q6KE8fGD6nJyqUpqrM/mfY842uvizdi7J09UdLd3+WoVU9LF+/6HXejIiIiBxPzOwh59zmVz/z+KYaUzmh1GsBxakqpakaxf1VSlNVilMVilO1qHx/leJUtFRL9U7frpyEsgW/GTYHlne3Bc+uRdE6153WAEEiIiJyUlEwlcMSho6gHhLWQ4J6VL3TqHHzPGuvmfMSNXmHc+0gpF4NqVUDapWAejWkHm/XKgH1WkC9Eja3nRCgegAADRxJREFUa5V4vxZQmWkEzhrFyQrVcjDna2QLPvmeDIXeDIMrusn3ZijE+5m8n6ilbL0Pr632ctYxr1VLibU+h2i7VYtpidpJOERNaPxZNWtQ56yFba+BbdSyhnHNbmObRK3tgT934DXat6O1l2r9ubZte4bF+16qVdbajmo7IXqNIAgJ6/E6cLO2Q4LAER5wTvSMhYHDPOa+l1T8Wl78eSaORfeSOJb4bOfSVuwaK3dA2euV60rT1Z8lnU0dnQuKiIiInEAUTI8B56Iv4PV6SFALCephHOqicJf8sh7Uoi/jQT2xjr+Yt32pj8taTUBpNQ2lvWlo+zr6kh01LY1+Jpj9OvXGPTZCQRwYGvc/V5PIw3BAUG0EmzichYGjVg0I60d2bTPwsynSmVQzcA6u6KZw1uIocDZCZ18mCqM9GVJpjfMlIiIiIrJQLehgWq+G7HlxKupHFjb69bX6kx1YljyPtj5ozrWv23827sfmWv3mZl8zGTCDWiLMtZWH1OMAerR5jb56ccCDZK0crZo3DnEcwCDlt/rxpXyPTC5Fyk9HZX7c3y8+J9XoGxiXRz/nYdaqnWt+lonat+Sfgwujz5aQ6DOOj3m+Rzrj4WdSpLOpaJ3x8JvbjfLkOdF9qZmjiIiIiMiJY96DqZldC3wGSAFfcM792cHOHXt5hn/+s2M3+JHFTf3amikmmyZaq9liI5Sl0h5+xiPb5TcDXiodr33DT3vNUOc3y9vDnpey6Gcag8A0BnxJDAjTDI9+q5ZRRERERETkRDSvwdTMUsB/A64GdgIPmtm3nXNPznV+31Cef/GBc6NwGDf/nB0YzVohMupbRmK7Vd4ePlujkIqIiIiIiEhnzXeN6cXAc865bQBm9lXgRmDOYJot+Kw5d3Aeb09ERERERETm23yPCLMc2JHY3xmXNZnZ75jZFjPbMjIyMq83JyIiIiIiIvNvvoPpXG1n20YKcs59zjm32Tm3eWhoaJ5uS0RERERERDplvoPpTmBlYn8FsHue70FEREREREQWkPkOpg8C68zsVDPLAO8Cvj3P9yAiIiIiIiILyLwOfuScq5vZh4DvE00X8yXn3BPzeQ8iIiIiIiKysMz7PKbOuduA2+b7dUVERERERGRhmu+mvCIiIiIiIiJtFExFRERERESkoxRMRUREREREpKMUTEVERERERKSjFExFRERERESkoxRMRUREREREpKMUTEVERERERKSjFExFRERERESkoxRMRUREREREpKMUTEVERERERKSjFExFRERERESkoxRMRUREREREpKMUTEVERERERKSjFExFRERERESko8w51+l7OCgzGwG2d/o+FphBYLTTNyHyKvScyvFCz6ocL/SsyvFCz+rRt9o5N9TpmzjWFnQwlQOZ2Rbn3OZO34fIoeg5leOFnlU5XuhZleOFnlV5rdSUV0RERERERDpKwVREREREREQ6SsH0+PO5Tt+AyGHQcyrHCz2rcrzQsyrHCz2r8pqoj6mIiIiIiIh0lGpMRUREREREpKMUTBcQM/uSme01s8cTZf/JzB41s0fM7E4zWxaXm5n9lZk9Fx+/oHN3LiebuZ7VxLHfMzNnZoPxvp5V6ZiD/Lv6J2a2K/539REzuz5x7A/jZ/VpM7umM3ctJ6OD/btqZv9X/Dw+YWZ/nijXsyodcZB/V7+W+Df1RTN7JHFMz6ocFgXTheUW4NpZZf+vc+5c59wm4LvAJ+Ly64B18fI7wGfn6yZFmPtZxcxWAlcDLyWK9axKJ93CHM8q8JfOuU3xchuAmZ0FvAvYGP/Mfzez1LzdqZzsbmHWs2pmvwrcCJzrnNsIfDou17MqnXQLs55V59w7G/+mAt8AbgU9q3JkFEwXEOfc3cDYrLKpxG4X0OgUfCPwFRe5D+g3s6Xzc6dyspvrWY39JfAfaD2noGdVOugQz+pcbgS+6pyrOOdeAJ4DLj5mNyeScJBn9f3AnznnKvE5e+NyPavSMYf6d9XMDPjXwD/GRXpW5bApmB4HzOw/m9kO4Ddo1ZguB3YkTtsZl4l0hJndAOxyzm2ddUjPqixEH4qbln/JzBbFZXpWZaFZD1xpZveb2U/M7KK4XM+qLFRXAnucc8/G+3pW5bApmB4HnHN/5JxbCfw98KG42OY6df7uSqTFzArAH9H6xUnb4TnK9KxKJ30WWAtsAl4G/iIu17MqC40PLAIuBX4f+HpcI6VnVRaqf0OrthT0rMoRUDA9vvwD8PZ4eyewMnFsBbB73u9IJLIWOBXYamYvEj2PD5vZKehZlQXGObfHORc450Lg87SalelZlYVmJ3Br3BXiASAEBtGzKguQmfnA24CvJYr1rMphUzBd4MxsXWL3BuCX8fa3gXfHI55eCkw6516e9xsUAZxzjznnhp1za5xza4j+I7rAOfcKelZlgZnVx/kmoDGy5LeBd5lZ1sxOJRqw64H5vj+RhG8BbwIws/VABhhFz6osTG8Bfumc25ko07Mqh83v9A1Ii5n9I/BGYNDMdgKfBK43szOIfku6HXhffPptwPVEnciLwG/N+w3LSWuuZ9U598WDnK5nVTrmIP+uvtHMNhE1J3sR+HcAzrknzOzrwJNAHfigcy7oxH3Lyecgz+qXgC/F03JUgfc45xygZ1U65hDfAd5FezNe/bsqR8Sif99EREREREREOkNNeUVERERERKSjFExFRERERESkoxRMRUREREREpKMUTEVERERERKSjFExFRERERESkoxRMRUTkqDGzwMweMbMnzGyrmf2umc3r/zVm9h/N7C3H8Pq/Hr+/0Mw2zzr2h2b2nJk9bWbXHMa1bjazv36N97HJzK5P7P+Jmf3ea7mWiIhIp2keUxEROZpKzrlNAGY2DPwD0Ec0J+O8cM594hi/xOPA24D/mSw0s7OI5vHbCCwD7jKz9cdwzr5NwGaiuYJFRESOa6oxFRGRY8I5txf4HeBDFlljZveY2cPxcjmAmf2tmd3Y+Dkz+3szu8HMNprZA3EN7KNmti55fTNLmdktZva4mT1mZh+Ly28xs3fE2y+a2afi13vMzM6My7vN7G/iskfN7O1x+a+Z2b3x+f9kZt1zvK+nnHNPz/GWbwS+6pyrOOdeAJ4DLp59kpn9lpk9Y2Y/Ad6QKB8ys2+Y2YPx8oa4/GIz+7mZ/SJen2FmGeA/Au+MP593xpc5y8x+bGbbzOzD8c93mdn34hrsxxPnioiILBgKpiIicsw457YR/V8zDOwFrnbOXQC8E/ir+LQvAL8FYGZ9wOVEtYDvAz4T18BuBnbOuvwmYLlz7mzn3DnA3xzkNkbj1/ws0Gjq+sfApHPuHOfcucD/NrNB4OPAW+LztwC/ewRvdzmwI7G/My5rMrOlwKeIAunVwFmJw58B/tI5dxHwdqLPBeCXwFXOufOBTwD/t3OuGm9/zTm3yTn3tfjcM4FriALxJ80sDVwL7HbOneecOxu44wjek4iIyLxQU14RETnWLF6ngb82s01AAKwHcM79xMz+W9z0923AN5xzdTO7F/gjM1sB3Oqce3bWdbcBp5nZfwW+B9x5kNe/NV4/FF8f4C1EzW6J72HczN5KFBR/ZmYAGeDe1/A+k9ys/UuAHzvnRgDM7GvEn0N8T2fFrw3Qa2Y9RE2hvxzXGDuiz/FgvuecqwAVM9sLLAEeAz5tZv8F+K5z7p4jeE8iIiLzQjWmIiJyzJjZaUQhdC/wMWAPcB5RDWgmcerfAr9BVHP6NwDOuX8AbgBKwPfN7E3JazvnxuNr/Rj4IK0axtkq8Tqg9QtZ48DQaMAP4hrITc65s5xz//YI3u5OYGVifwWwe47zZr9ugwdclnj95c65/cB/An4U13b+SyB3iHuoJLYDwHfOPQNcSBRQ/x8zO9Z9cEVERI6YgqmIiBwTZjYE/A/gr51zjqjm72XnXAj8JpBKnH4L8FEA59wT8c+fBmxzzv0V8G3g3FnXHwQ859w3iJrmXnAEt3cn8KHEtRYB9wFvMLPT47KCma0/yM/P5dvAu8wsa2anAuuAB2adcz/wRjMbiJvZ/voh7mlTvNkH7Iq3b06cvx/oebWbMrNlQNE593fApzmyz0lERGReKJiKiMjRlG9MFwPcRRS2PhUf++/Ae8zsPqLmqzONH3LO7QGeor2f6DuBx83sEaK+k1+Z9VrLgR/Hx28B/vAI7vNPgUXxYEBbgV+Nm9feDPyjmT1KFFTPnP2DZnaTme0ELgO+Z2bfj9/DE8DXgSeJ+nF+cPaIvM65l4E/IWoifBfwcOLwh4HN8WBMTxL1sQX4c6Kazp/RHuZ/RNT0Nzn40VzOAR6IP6c/it+7iIjIgmLRL7FFREQ6x8wKRE1NL3DOTXb6fkRERGR+qcZUREQ6yszeQjTy7H9VKBURETk5qcZUREREREREOko1piIiIiIiItJRCqYiIiIiIiLSUQqmIiIiIiIi0lEKpiIiIiIiItJRCqYiIiIiIiLSUQqmIiIiIiIi0lH/P/qi6ElwJ41PAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<Figure size 1080x648 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = cases_m7.iloc[-50:][COUNTRIES_CORE].plot(figsize=(15, 9), title=\"Cases per day, 7 day moving average, with lockdown dates\") #, ylim=(-10, 1500))\n",
-    "ax.set_xlabel(f\"Days since {DEATH_COUNT_THRESHOLD} deaths\")\n",
-    "# uk_projection.deaths_m7.plot(ax=ax)\n",
-    "for c in COUNTRIES_CORE:\n",
-    "    lvi = cases_m7[c].last_valid_index()\n",
-    "#     if c != 'UK':\n",
-    "    ax.text(x = lvi + 1, y = cases_m7[c][lvi], s = f\"{c}: {cases_m7[c][lvi]:.0f}\")\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 724,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 1080x648 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = cases_m7[COUNTRIES_CORE].plot(figsize=(15, 9), title=\"Cases per day, 7 day moving average, with lockdown dates\")\n",
-    "ax.set_xlabel(f\"Days since {DEATH_COUNT_THRESHOLD} deaths\")\n",
-    "# uk_projection.deaths_m7.plot(ax=ax)\n",
-    "for c in COUNTRIES_CORE:\n",
-    "    lvi = cases_m7[c].last_valid_index()\n",
-    "#     if c != 'UK':\n",
-    "    ax.text(x = lvi + 1, y = cases_m7[c][lvi], s = f\"{c}: {cases_m7[c][lvi]:.0f}\")\n",
-    "    if c in lockdown_dates:\n",
-    "        for phase in lockdown_dates[c]:\n",
-    "            marker_col = [l for l in ax.lines if l.get_label() == c][0].get_color()\n",
-    "            if 'start' in phase:\n",
-    "                marker_shape = '^'\n",
-    "            else:\n",
-    "                marker_shape = 'v'\n",
-    "            ax.plot(lockdown_dates[c][phase]['since_threshold'], lockdown_dates[c][phase]['cases_m7'], \n",
-    "                    marker_shape,\n",
-    "                    markersize=18, markerfacecolor=marker_col, markeredgecolor=marker_col)\n",
-    "            if 'start' not in phase:\n",
-    "                ax.text(x = lockdown_dates[c][phase]['since_threshold'] + 1, y = lockdown_dates[c][phase]['cases_m7'], \n",
-    "                        s = f\"{lockdown_dates[c][phase]['date']}: {lockdown_dates[c][phase]['cases_m7']:.0f}\")\n",
-    "plt.savefig('cases_per_day_with_lockdown.png')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 725,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = cases_m7[COUNTRIES_CORE].plot(figsize=(10, 6), title=\"Cases per day, 7 day moving average\")\n",
-    "for c in COUNTRIES_CORE:\n",
-    "    lvi = cases_m7[c].last_valid_index()\n",
-    "    ax.text(x = lvi + 1, y = cases_m7[c][lvi], s = c)\n",
-    "plt.savefig('covid_cases_per_day-core.png') "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 726,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "IT part_start\n",
-      "IT full_start\n",
-      "DE full_start\n",
-      "UK part_start\n",
-      "UK full_start\n",
-      "ES part_start\n",
-      "ES full_start\n",
-      "IE full_start\n",
-      "FR part_start\n",
-      "FR full_start\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 1080x648 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths_m7[COUNTRIES_CORE].plot(figsize=(15, 9), title=\"Deaths per day, 7 day moving average\",\n",
-    "                                   xlim=(0, 15), \n",
-    "                                    ylim=(0, 66)\n",
-    "                                   )\n",
-    "# uk_projection.deaths_m7.plot(ax=ax)\n",
-    "for c in COUNTRIES_CORE:\n",
-    "    lvi = deaths_m7[c].last_valid_index()\n",
-    "    if c in lockdown_dates:\n",
-    "        for phase in lockdown_dates[c]:\n",
-    "            if 'start' in phase:\n",
-    "                print(c, phase)\n",
-    "                marker_col = [l for l in ax.lines if l.get_label() == c][0].get_color()\n",
-    "                ax.plot(lockdown_dates[c][phase]['since_threshold'], lockdown_dates[c][phase]['deaths_m7'], '*', \n",
-    "                        markersize=18, markerfacecolor=marker_col, markeredgecolor=marker_col)\n",
-    "                ax.text(x = lockdown_dates[c][phase]['since_threshold'] + 0.3, y = lockdown_dates[c][phase]['deaths_m7'], \n",
-    "                        s = f\"{lockdown_dates[c][phase]['date']}: {lockdown_dates[c][phase]['deaths_m7']:.0f}\")\n",
-    "# plt.savefig('school_reopenings.png')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Write results to summary file"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 727,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "with open('covid_summary.md', 'w') as f:\n",
-    "    f.write('% Covid death data summary\\n')\n",
-    "    f.write('% Neil Smith\\n')\n",
-    "    f.write(f'% Created on {datetime.datetime.now().strftime(\"%Y-%m-%d\")}\\n')\n",
-    "    f.write('\\n')\n",
-    "        \n",
-    "    last_uk_date = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), 'dateRep'].iloc[-1]\n",
-    "    f.write(f'> Last UK data from {last_uk_date.strftime(\"%Y-%m-%d\")}\\n')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 728,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "with open('covid_summary.md', 'a') as f:\n",
-    "    f.write('\\n')\n",
-    "    f.write('## Headlines\\n')\n",
-    "    f.write('\\n')\n",
-    "    f.write('| []() | |\\n')\n",
-    "    f.write('|:---|---:|\\n')\n",
-    "    f.write(f'| Deaths reported so far | {uk_covid_deaths} | \\n')\n",
-    "    f.write(f'| Total Covid deaths to date (estimated) | {uk_deaths_to_date:.0f} |\\n')\n",
-    "    projection_date = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['IT']), 'dateRep'].iloc[-1] + pd.Timedelta(s_end - s_start, unit='days')\n",
-    "    f.write(f'| Projected total deaths up to {projection_date.strftime(\"%Y-%m-%d\")} | {deaths_actual_projected_scaled:.0f} | \\n')\n",
-    "    f.write('\\n')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 729,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "with open('covid_summary.md', 'a') as f:\n",
-    "    f.write('\\n')\n",
-    "    f.write('## Total deaths\\n')\n",
-    "    f.write(f'Time based on days since {DEATH_COUNT_THRESHOLD} deaths\\n')\n",
-    "    f.write('\\n')\n",
-    "    f.write('![Total deaths](covid_deaths_total_linear.png)\\n')\n",
-    "    f.write('\\n')\n",
-    "    f.write('| Country ID | Country name | Total deaths |\\n')\n",
-    "    f.write('|:-----------|:-------------|-------------:|\\n')\n",
-    "    for c in sorted(COUNTRIES_CORE):\n",
-    "        lvi = deaths[c].last_valid_index()\n",
-    "        f.write(f'| {c} | {countries.loc[c].countriesAndTerritories} | {int(deaths[c][lvi])} |\\n')\n",
-    "    f.write('\\n')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 730,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "with open('covid_summary.md', 'a') as f:\n",
-    "    f.write('\\n')\n",
-    "    f.write('## All-causes deaths, UK\\n')\n",
-    "    f.write('\\n')\n",
-    "    f.write('![All-causes deaths](deaths-radar.png)\\n')\n",
-    "    f.write('\\n')\n",
-    "    f.write('### Excess deaths\\n')\n",
-    "    f.write('\\n')\n",
-    "    f.write(f'From week ending 20 March 2020 until week ending {pd.to_datetime(excess_deaths_upto).strftime(\"%d %B %Y\")}, ')\n",
-    "    f.write(f'there were approximately **{excess_deaths:.0f}** excess deaths, over the average for the previous five years.\\n')\n",
-    "    f.write('\\n')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 731,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "with open('covid_summary.md', 'a') as f:\n",
-    "    f.write(f'In that period, the UK reported {ons_reported_deaths} Covid deaths.\\n')\n",
-    "    f.write(f'In the last three weeks for which excess deaths have been reported, the excess deaths have been {excess_death_accuracy:.3f} higher than the Covid-reported deaths.\\n')\n",
-    "#     f.write(f'That means the actual number of Covid death is about {excess_deaths / reported_deaths:.2f} times higher than the reported figures.\\n')\n",
-    "    f.write('\\n')\n",
-    "    f.write(f'The UK has reported {uk_covid_deaths} deaths so far.\\n')\n",
-    "    f.write(f'Using the scaling factor above (for Covid-19 deaths after the ONS figures), I infer that there have been **{uk_deaths_to_date:.0f}** total deaths so far.\\n')\n",
-    "    f.write('\\n')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 732,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "with open('covid_summary.md', 'a') as f:\n",
-    "    f.write('\\n')\n",
-    "    f.write('## Deaths per day\\n')\n",
-    "    f.write(f'Based on a 7-day moving average\\n')\n",
-    "    f.write('\\n')\n",
-    "    f.write('![Deaths per day](covid_deaths_per_day_7.png)\\n')\n",
-    "    f.write('\\n')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 733,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "24"
-      ]
-     },
-     "execution_count": 733,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "s_end - s_start - 1"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 734,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "with open('covid_summary.md', 'a') as f:\n",
-    "    f.write('\\n')\n",
-    "    f.write('## Projected deaths\\n')\n",
-    "    f.write(f\"The UK's daily deaths data is very similar to Italy's.\\n\")\n",
-    "    f.write(f'If I use the Italian data for the next {s_end - s_start - 1} days (from {s_start_date.strftime(\"%d %B %Y\")} onwards),')\n",
-    "    f.write(f' the UK will report {uk_projection.deaths.sum()} deaths on day {uk_end} of the epidemic.\\n')\n",
-    "    f.write('\\n')\n",
-    "    f.write('Using the excess deaths scaling from above, that will translate into ')\n",
-    "    f.write(f'**{deaths_actual_projected_scaled:.0f}** Covid deaths total.\\n')\n",
-    "    f.write('\\n')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 735,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "with open('covid_summary.md', 'a') as f:\n",
-    "    f.write('\\n')\n",
-    "    f.write('## Deaths doubling times\\n')\n",
-    "    f.write(f'Based on a 7-day moving average\\n')\n",
-    "    f.write('\\n')\n",
-    "    f.write('![Deaths doubling times](covid_doubling_times_7.png)\\n')\n",
-    "    f.write('\\n')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 736,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "with open('covid_summary.md', 'a') as f:\n",
-    "    f.write('\\n')\n",
-    "    f.write('## Cases per day and lockdown dates\\n')\n",
-    "    f.write(f'Based on a 7-day moving average\\n')\n",
-    "    f.write('\\n')\n",
-    "    f.write('![Cases per day](cases_per_day_with_lockdown.png)\\n')\n",
-    "    f.write('\\n')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 737,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "with open('covid_summary.md', 'a') as f:\n",
-    "    f.write('\\n')\n",
-    "    f.write('| Country ID | Country name | Most recent daily cases | Most recent daily deaths |\\n')\n",
-    "    f.write('|:-----------|:-------------|------------------------:|-------------------------:|\\n')\n",
-    "    for c in sorted(COUNTRIES_CORE):\n",
-    "        lvic = cases_m7[c].last_valid_index()\n",
-    "        lvid = deaths_m7[c].last_valid_index()\n",
-    "        f.write(f'| {c} | {countries.loc[c].countriesAndTerritories} | {cases_m7[c][lvic]:.0f} | {deaths_m7[c][lvid]:.0f} | \\n')\n",
-    "    f.write('\\n')\n",
-    "    f.write('(Figures are 7-day averages)\\n')\n",
-    "    f.write('\\n')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 738,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "with open('covid_summary.md', 'a') as f:\n",
-    "    f.write('# Data sources\\n')\n",
-    "    f.write('\\n')\n",
-    "    f.write('> Covid data from [European Centre for Disease Prevention and Control](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide)\\n')\n",
-    "    f.write('\\n')    \n",
-    "    f.write(\"\"\"> Population data from:\n",
-    "\n",
-    "* [Office of National Statistics](https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/weeklyprovisionalfiguresondeathsregisteredinenglandandwales) (Endland and Wales) Weeks start on a Saturday.\n",
-    "* [Northern Ireland Statistics and Research Agency](https://www.nisra.gov.uk/publications/weekly-deaths) (Northern Ireland). Weeks start on a Saturday. Note that the week numbers don't match the England and Wales data.\n",
-    "* [National Records of Scotland](https://www.nrscotland.gov.uk/statistics-and-data/statistics/statistics-by-theme/vital-events/general-publications/weekly-and-monthly-data-on-births-and-deaths/weekly-data-on-births-and-deaths) (Scotland). Note that Scotland uses ISO8601 week numbers, which start on a Monday.\"\"\")\n",
-    "    \n",
-    "    f.write('\\n\\n')\n",
-    "    f.write('> [Source code available](https://git.njae.me.uk/?p=covid19.git;a=tree)\\n')\n",
-    "    f.write('\\n') \n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 739,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "!pandoc -s covid_summary.md > covid_summary.html"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 740,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "covid_summary.html                            100% 7405     3.9MB/s   00:00    \n",
-      "covid_deaths_total_linear.png                 100%   42KB   7.9MB/s   00:00    \n",
-      "deaths-radar.png                              100%  199KB  10.4MB/s   00:00    \n",
-      "covid_deaths_per_day_7.png                    100%   50KB   7.6MB/s   00:00    \n",
-      "covid_doubling_times_7.png                    100%   31KB   7.2MB/s   00:00    \n",
-      "cases_per_day_with_lockdown.png               100%  104KB   9.9MB/s   00:00    \n"
-     ]
-    }
-   ],
-   "source": [
-    "!scp covid_summary.html neil@ogedei:/var/www/scripts.njae.me.uk/covid/index.html\n",
-    "!scp covid_deaths_total_linear.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
-    "!scp deaths-radar.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
-    "!scp covid_deaths_per_day_7.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
-    "!scp covid_doubling_times_7.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
-    "!scp cases_per_day_with_lockdown.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 741,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "with open('uk_covid_deaths.js', 'w') as f:\n",
-    "    f.write(f\"document.write('{uk_covid_deaths}');\")\n",
-    "    \n",
-    "with open('estimated_total_deaths.js', 'w') as f:\n",
-    "    f.write(f\"document.write('{uk_deaths_to_date:.0f}');\")\n",
-    "\n",
-    "with open('projection_date.js', 'w') as f:\n",
-    "    f.write(f\"document.write(\\'{projection_date.strftime('%d %B %Y')}\\');\")\n",
-    "\n",
-    "with open('projected_deaths.js', 'w') as f:\n",
-    "    f.write(f\"document.write('{uk_projection.deaths.sum():.0f}');\")\n",
-    "\n",
-    "with open('projected_excess_deaths.js', 'w') as f:\n",
-    "    f.write(f\"document.write('{deaths_actual_projected_scaled:.0f}');\")\n",
-    "\n",
-    "with open('excess_deaths_upto.js', 'w') as f:\n",
-    "    f.write(f\"document.write('{pd.to_datetime(excess_deaths_upto).strftime('%d %B %Y')}');\")\n",
-    "\n",
-    "with open('excess_deaths.js', 'w') as f:\n",
-    "    f.write(f\"document.write('{excess_deaths:.0f}');\")\n",
-    "    \n",
-    "with open('reported_deaths.js', 'w') as f:\n",
-    "    f.write(f\"document.write('{ons_reported_deaths:.0f}');\")\n",
-    "    \n",
-    "with open('scaling_factor.js', 'w') as f:\n",
-    "    f.write(f\"document.write('{excess_death_accuracy:.2f}');\")  \n",
-    "\n",
-    "with open('projection_length.js', 'w') as f:\n",
-    "    f.write(f\"document.write('{s_end - s_start - 1}');\")\n",
-    "    \n",
-    "with open('s_end.js', 'w') as f:\n",
-    "    f.write(f\"document.write('{s_end}');\")\n",
-    "    \n",
-    "s_start_date_str = s_start_date.strftime(\"%d %B %Y\")\n",
-    "with open('s_start_date.js', 'w') as f:\n",
-    "    f.write(f\"document.write('{s_start_date_str}');\")\n",
-    "    \n",
-    "with open('uk_end.js', 'w') as f:\n",
-    "    f.write(f\"document.write('{uk_end}');\")\n",
-    "    \n",
-    "with open('last_uk_date.js', 'w') as f:\n",
-    "    f.write(f\"document.write('{pd.to_datetime(last_uk_date).strftime('%d %B %Y')}');\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 742,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'03 July 2020'"
-      ]
-     },
-     "execution_count": 742,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "pd.to_datetime(excess_deaths_upto).strftime('%d %B %Y')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 743,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "uk_covid_deaths.js                            100%   24    25.7KB/s   00:00    \n",
-      "estimated_total_deaths.js                     100%   24    24.7KB/s   00:00    \n",
-      "projection_date.js                            100%   36    41.9KB/s   00:00    \n",
-      "projected_deaths.js                           100%   24    25.1KB/s   00:00    \n",
-      "projected_excess_deaths.js                    100%   24    19.9KB/s   00:00    \n",
-      "excess_deaths_upto.js                         100%   31    28.2KB/s   00:00    \n",
-      "excess_deaths.js                              100%   24    19.9KB/s   00:00    \n",
-      "reported_deaths.js                            100%   24    19.5KB/s   00:00    \n",
-      "scaling_factor.js                             100%   23    30.1KB/s   00:00    \n",
-      "projection_length.js                          100%   21    21.3KB/s   00:00    \n",
-      "s_end.js                                      100%   22    23.2KB/s   00:00    \n",
-      "s_start_date.js                               100%   30    23.3KB/s   00:00    \n",
-      "uk_end.js                                     100%   22    23.8KB/s   00:00    \n",
-      "last_uk_date.js                               100%   33    42.3KB/s   00:00    \n"
-     ]
-    }
-   ],
-   "source": [
-    "!scp uk_covid_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
-    "!scp estimated_total_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
-    "!scp projection_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
-    "!scp projected_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
-    "!scp projected_excess_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
-    "!scp excess_deaths_upto.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
-    "!scp excess_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
-    "!scp reported_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
-    "!scp scaling_factor.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
-    "!scp projection_length.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
-    "!scp s_end.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
-    "!scp s_start_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
-    "!scp uk_end.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
-    "!scp last_uk_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/    "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 744,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "data_by_date.loc['UK'].to_csv('data_by_day_uk.csv', header=True, index=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 745,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[<matplotlib.axis.XTick at 0x7f03f7822150>,\n",
-       " <matplotlib.axis.XTick at 0x7f03f57b7810>,\n",
-       " <matplotlib.axis.XTick at 0x7f03f5480410>,\n",
-       " <matplotlib.axis.XTick at 0x7f03f5c85b90>,\n",
-       " <matplotlib.axis.XTick at 0x7f03f5c85090>,\n",
-       " <matplotlib.axis.XTick at 0x7f03f517f550>]"
-      ]
-     },
-     "execution_count": 745,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 864x576 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ukd = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), ['deaths', 'deaths_m7']].droplevel(1)\n",
-    "ax = ukd.deaths.plot.bar(figsize=(12, 8))\n",
-    "ukd.deaths_m7.plot.line(ax=ax, color='red')\n",
-    "# ax = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), 'deaths_m7'].plot.line(figsize=(12, 8), color='red')\n",
-    "# ax = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), 'deaths'].plot.bar(ax=ax)\n",
-    "ax.set_xticks(range(0, 120, 20))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 746,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([  0,  20,  40,  60,  80, 100, 120])"
-      ]
-     },
-     "execution_count": 746,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.arange(0, 130, 20)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 747,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>dateRep</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>2019-12-31</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-01</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-02</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-03</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-04</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>1440</td>\n",
-       "      <td>11</td>\n",
-       "      <td>316367</td>\n",
-       "      <td>41358</td>\n",
-       "      <td>311.0</td>\n",
-       "      <td>-7.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>1077</td>\n",
-       "      <td>3</td>\n",
-       "      <td>317444</td>\n",
-       "      <td>41361</td>\n",
-       "      <td>-363.0</td>\n",
-       "      <td>-8.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>1040</td>\n",
-       "      <td>5</td>\n",
-       "      <td>318484</td>\n",
-       "      <td>41366</td>\n",
-       "      <td>-37.0</td>\n",
-       "      <td>2.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>713</td>\n",
-       "      <td>3</td>\n",
-       "      <td>319197</td>\n",
-       "      <td>41369</td>\n",
-       "      <td>-327.0</td>\n",
-       "      <td>-2.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>1089</td>\n",
-       "      <td>12</td>\n",
-       "      <td>320286</td>\n",
-       "      <td>41381</td>\n",
-       "      <td>376.0</td>\n",
-       "      <td>9.0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>233 rows × 6 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff\n",
-       "dateRep                                                                    \n",
-       "2019-12-31      0       0           0            0         NaN          NaN\n",
-       "2020-01-01      0       0           0            0         0.0          0.0\n",
-       "2020-01-02      0       0           0            0         0.0          0.0\n",
-       "2020-01-03      0       0           0            0         0.0          0.0\n",
-       "2020-01-04      0       0           0            0         0.0          0.0\n",
-       "...           ...     ...         ...          ...         ...          ...\n",
-       "2020-08-15   1440      11      316367        41358       311.0         -7.0\n",
-       "2020-08-16   1077       3      317444        41361      -363.0         -8.0\n",
-       "2020-08-17   1040       5      318484        41366       -37.0          2.0\n",
-       "2020-08-18    713       3      319197        41369      -327.0         -2.0\n",
-       "2020-08-19   1089      12      320286        41381       376.0          9.0\n",
-       "\n",
-       "[233 rows x 6 columns]"
-      ]
-     },
-     "execution_count": 747,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_by_date.loc['UK']"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 748,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f03f53cfe50>"
-      ]
-     },
-     "execution_count": 748,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
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x9/cw9y8byDjVscnFtENVKeU2m44UsPFIAfdfmEhIoG+22oF2h2/6t1Bzb23qm7z6ZfoKOzhqRssySim3MMbwf1+m0LdnELdMH+TpcDpVw1BI/1ZKLQEt1dzbedCq4elVR2lyV0q5xX9S80k6dooH5iQ2tlZ9lV99y7y14Y1Na+4Nf28oyzQsyXcmq61jo2Y0uSulOp0xhmfXHmJARLBTMzR2FaGBdT+8rp44oMX3/VuowTS03MOC/Fvsj9iTWcxHOzMdjsF3i15KKa/x+d6T7Ewv4o/Xje3wOqZdUUzPYL5/7CL692x5cZ2mZZkGDS33QH9Li52rv19zAICrJ8Q6FIMmd6VUpyirtvLJrixWJqez/UQRCVGhLJrcfRabiW1hfHuDlhYOaWi5B/pZnJ7oDHQ+d6WUi+3JKObNTcdYsyebihobQ6JD+eUVI1g0eeBZr4bka1rqaG1M7v6WVjtiAex20+rTrKdd4+zDc57O566Ub8ksquS6F78n0M/C/HEDuGHqQCYN6qXrIJ+hpR9yp5Vl2kjelbU2h2an1LKMUsplViVnUGszfP3wbAZFhrR/QDfVI7B5v0NDvg/yt7Q6FQFARY1jyV1/R1JKuYTdbnh3WzrnJ0ZqYm9HvxY6WhsSens198oax2aJ1OSulHKJzWkFZJyq5IYpvj/U0Vn9WpgpsqEUE9AkuY+NbT7mvdLBKYA1uSulXGJlcjrhwf5cPrqfp0Pxei09xNXQcvdvktxbasBX1Dg2S6TW3JVSTiuurOWzvSe5fkqczz996iov3TqJuN7Ny1cBftLYudpSR7SjZRlN7kqp09RY7ZRW1VJWbaW0ykpJVS1lVVZqbHYuHdW3xYeQVu/Kotpq15JMB8wd0/+011Z73dwxfhZpHArZUr9qRVdI7jrOXSnvYbXZueuNZNYfymt1n59dPpwH5jT/9/pucjoj+oW3WCNWjrHVJ3d/izTW31t6UtXRmruOc1dKAfDa90dZfyiP2887h4SoUMKDAwgL9ic82J+ewQH88bMD/PP7Y9w9K+G01vvBkyXsyijm11eN0vHsTvih5W6hYXaClmruWpZRSjnsaH45z649xKWj+vLEgtEtJun7L0jk1le38OGOTBZP/WHK3neTMwjwE66Z0PIkWcoxDR2lQf4WAuqnDLa3MMtvtVVHyyilHGC3G36+ajdB/hZ+f82YVlvf5ydGMqp/T15en4a9PuvUWO18sCOTS0b2JbKV6W2VY9IL61Zaiu3dg+D634xamub31x/tI+lYYbvn0+SuVDf37y3H2XqskF9fNYq+rcxiCHUjN+69YDBH8sr5NiUXgG8O5lBYXsMN3WAa3852yai+AEwc2KvxCdbWFuh45ouUds+nyV2pbiy9sIKnPjvI7GHRDs3YeMXY/sT26sE/1qcBsDI5g349g5k9NLqzQ/V5N08bxOEn5xHTM5jggLrUbGupLgMYBxZl0uSuVDdljOGXH+xBgD9eN9ahztAAPwt3nh/P1qOFrN13knUpuSycHOuSKWq7OxFpnFCssSxj79jqS01pcleqm3o3OYMNh/N57IqRbc49fqYbpw0iPNif/1qxE7uB6ydrScbVggIaknsrLXfab7prcleqG8opqeJ3a/YzPaEPt0zr2GLVYUH+3HruOVTU2JiW0If4qNBOirL7aijLWDu4KHZTmtyV6maMMTz+wR5qbXb+tHCcQws/nOmOGfFEhQVy1/nxrg9Q0SPA+bKMjnNXqpv5eFcWXx3I5VdXjjzrVnffnsEk/+pSF0emGjTMz9Nah2pro2ia0ukHlPIhxRW1/HvLcSJDA5k4qDeJMWGndXbml1XzxMf7mDCwF3een+DBSFVbAusfYmotie9ML2r3HDr9gFI+YseJUzz49g4yiyobt4UF+TMuLoKJg3oxcWBv3tueQXm1jf9dNE5HuHixoPrk3j8imOLK2rM6h5ZllOrijDG8suEof/r8IP0igvngxzPoFRLIjhOn2HGiiJ3pRfzju7TGkRePXDaMoX3DPRy1akt4cAAv3DyJKfG9mf6Hr8/qHJrclerCTpXX8Mi7u/j6YC6Xj+7L04vGE9EjAICEqFCum1T3YFJljY29WcVknqrkqnH92zql8hJXjuvfOM3D2dDkrlQXlXyskJ+8s4P8shp+u2A0PzrvnFYfROoR6MfU+D5MjXdvjMo5zkyyqcldqS7Gbje8tP4Iz649RFzvHrx3/wzGxuk86up0mtyV6kIKyqp5eOUuvjuUx5Xj+vPH68bSMzjA02EpL6TJXakuYseJU9z3722cqqjl99eM4Zbpg3RxDB/nzP9fTe5KdQHVVhsPvbODAD8LH/x4BqMHaBlGtU2Tu1JdwJsbj5NxqpJ/L5muiV05ROeWUcrLFVXU8LdvDnPh8GhmDo3ydDiqi9DkrpSX+9s3qZRVW/nFvJGeDkV1IZrclfJiJwoqeHPTMa6fPJDh/fSpUuU4Te5KebE/fXEQf4uFhy8b5ulQlJepsbY9HbAmd6W81PYTp1izO5ulswe3uXC16p5Wbcto831N7kp5IWMMf1hzgKiwIO6dPdjT4Sgv1N5skZ2S3EXkGhFZJiIfichlnXENpXzZF/tySD5+iocvHUZokI5YVs1V1FjbfN/h5C4ir4lIrojsPWP7XBFJEZFUEXkMwBjzoTFmKXAHsLjjYSvVfdXa7Pzp84MkxoRxw5Q4T4ejvFRri2c36EjL/XVgbtMNIuIHvADMA0YBN4nIqCa7/Kr+faWUg97ecoKj+eX8Yt4I/P20cqrqXDAs+rTXp8pr2tzf4W+OMWY9UHjG5mlAqjEmzRhTAywHrpY6fwI+M8Zsb+l8InKPiCSLSHJeXp6jYSjl00qqavnr14c5b3AkF42I8XQ4you8cde0014vT0pvc39nmwWxQNMrZNRvewi4BFgkIve1dKAx5mVjzBRjzJTo6OiWdlGq23lx3REKy2v45RUjdVIw5RRne2pa+vYZY8xzwHNOnlupbiWrqJLX/nOUayYM0PnZldOcbblnAAObvI4Dshw9WETmi8jLxcXFToahVNf3zNoUDPDI5cM9HYryAc4m9yRgqIgkiEggcCPwsaMHG2NWG2PuiYjQVorq3vZmFvPBjkzuPD+euN4hng5H+YCODIV8B9gEDBeRDBFZYoyxAg8CXwAHgJXGmH2dE6pSvskYwx8+PUCvHgH8+MJET4ejfITDNXdjzE2tbP8U+PRsLi4i84H5iYn6hVbd17qUPDYeKeA380cR0UOXzFOu4dFBtFqWUd2dMYanv0ghPjKEW6af4+lwlA/RJySU8qCUnFIOZJewZGYCgf76z1G5jn6blPKgNbuzsQjMG9vf06EoH+PR5K5DIVV3Zozhk93ZnDckkqiwIE+Ho3yM1tyV8pD92SUczS/nqnEDPB2K8nJLZyV0+BidS1QpD/lkdzZ+FuHy0f08HYryYseeuvKsjtOau1IeYIxhze5szk+Mok9ooKfDUT5Ia+5KdYLNaQVkFVW2+v6ezGJOFFZwlXakqk6iNXelXCyzqJJbX9nCk58eaHWfT3ZnE+CnJRnVMalPznN4Xy3LKOViy9anYbUbvkvJa3GF+oaSzKyh0USE6BOpynEdWbxFk7tSLpRfVs07W09wTmQIZdVWth49c30b2JFeRGZRJVdqSUZ1Ik3uSrnQP78/So3Nzgs3TyLI38JXB3Ka7bNmdzaBfhYuHd3XAxGq7kI7VJVykZKqWt7ceJx5Y/oxJjaCmYlRfHUgB2N+WMjYbq8rycweFk3PYC3JqM6jHapKuci/Nx+ntNraOG3vxSP7knGqkkM5ZY37bD9xipMlVcwfryUZ1bm0LKNUGz7bk835T33DxiP5be5XVWvjtf8cZdbQKMbE1jVWLh5Zt8B109LMJ7uzCfK3cPFILcmozqXJXakWGGN4/pvD3P/WdjKLKvndJwew202r+69MTie/rIYH5vywNkHfnsGMjY1oTO42u2HNnmzmDI8hLEgfDldnZ3B0qEP7aXJX6gxVtTb+e8VOnll7iGsmDODpheM4kF3C6t0tLw9ca7Pzj+/SmDSoF9MT+pz23iUj+7IzvYi80mqSjhWSV1rNVVqSUW6gyV2pJvJKq7l52WY+3JnFI5cN48+LJ7Bochyj+vfkmbUpLY5b/3hnFplFlTwwJxEROe29i0fGYAx8ezCXT3Zn0SPAj4tGxLjr46huTJO7UvUOnizhmhe+Z392CX+/ZRIPXjQUEcFiER6dO5z0wkre3nL8tGPsdsOL3x1hRL/wFpP26AE96R8RzNr9J/l870kuGhlDSKCWZFTn06GQSgFfH8hh4d83YrXbWXnveVxxxgNGFwyL5tzBffjbN6mUVVsbt6/dn0Nqbhn3XzikWasdQES4eGQMXx3IJb+sRueSUc5rvevnNDoUUnVrxhiWrU/j7jeTGRwdxkcPzGRcXK9m+4kIP587goLyGl7ZkNZ47IvrUhnUJ6TNp00bRsaEBPoxR0syykkO5nYty6juq8Zq57H39vDkpweYO7ofK+89j34Rwa3uP3FQb+aN6cey9Wnkl1Wz8UgBuzKKue+CIW3O+XHe4EjCg/y5bFRfggP8OuOjKNWMFv9Ut1RZY+PO17eyOa2QB+ck8vClw7BYmpdVzvTI5cNZuz+H579J5VBOKTHhQSycHNvmMcEBfnzwwAxdSk+5RPvf0jqa3FW39Op/0ticVsiz149n4eQ4h48bEh3GDVPi+Nfm49jshsevGEmQf/ut8cSYcGfCVarDtCyjup3C8hpe+i6Ny0b17VBib/DTi4fhbxEiegRw0/RBnRChUq1ztOauLXfV7Tz/TSoVNVYenTv8rI7vFxHMXxZPINDfok+aKrdrOhFdW/SbqbqV9MIK/rX5GDdMGehUqWSeDmlUXk7Huatu5dm1KVhE+K9Lhnk6FKU6lY5zV93G3sxiPtyZxV0zE9oc8qiUN7M5WJbRDlXVbTz9RQq9QgK474Ihng5FqbM2eVBvh/bT5K66he9T81l/KI8H5yQS0UNXQFJd12+vHuPQfprclc+z2w1PfXaQ2F49uPXcczwdjlJOCfJ3LG1rclc+b82ebPZkFvPwpcP08X/VbWhyVz6txmrnmbUpjOgXzjUT254mQClfoslddTlH8spYu++kQ/u+s/UExwsq+Pm8Efg5MHeMUr5Ck7vqUvZnlbDwxY3c869tLFuf1ua+ZdVWnvv6MOcO7sOFw6LdFKFS3kGfUFVdRsrJUm59dQs9AvyYMrIPT356gEB/C7fPiG9x/2Xr0ygor+HVeSNbXEhDqa7IwWHumtxV13A4p5Sbl20mwE94Z+m5xPbuwQNvbec3H+8jwM/CzWdM4JVXWs2yDWlcMbYfEwY2X3xDKV+n0w8olzucU0rKyVKXnS81t4yblm3BYqlL7PFRoQT4WfjbzROZMzyaxz/cw6ptGacd89zXh6m22vnZ5SNcFodS3sDRX0J1+gHlUja74fbXtnLFcxt4/pvD2OyOTlDasrS8Mm5ethmAd5aey+DosMb3gvz9ePHWycxMjOLRVbv4aGcmAEfzy3ln6wlumjaQhKhQp66vlLdxtCyjHarKpdYfziOruIpR/XvyzNpD3LRsM1lFlWd1rmP55dy0bDM2u+GdpdNJjAlrtk9wgB8v3zaFaQl9eHjlLj7bk80za1MI8LPwk4uHOvtxlOqyNLkrl1qxNZ0+oYG8d/8Mnr1+PPsyi5n31w18tie7Q+c5XlCX2GtthreXnsvQvq1Pz9sj0I9Xb5/KxIG9eOidHazZnc3SWQnEhOvkYMr3GAeX69Dkrlwmr7Sarw7ksHBSLIH+FhZOjmPNT2YRHxnC/W9t5xfv76aixtruedILK7jp5c1U1tp46+7pDO/X/rzroUH+/PPOqYyJjSAmPIilswe74iMp1WXpaBnlMu9vz8BqNyyeOrBxW3xUKKvun8GfvzzEi98dYcvRQp67cSJjYlvuZ8k4VcGNL2+mvMbG20unM7J/T4evHx4cwKr7zqO8xkZ4sE4OpnyTOLhEtrbclUsYY1iRnM6Uc3o3W+EowM/Co3NH8Nbd06motnHt379n2fo07Gd0tmYVVXLTss2UVtXy1t3TGT2g4x3t/n4WnfVR+TQtyyi3Sj5+irS88tNa7WeaMSSKz346i4tGxA2bn+IAABL8SURBVPDkpwe4/Z9byS2pAiC7uC6xF1XU8q8l01tt2SulHKPJXbnE8q3phAX5c+W4ttcW7R0ayEu3TuYP144l6Vghc/+6gVXbMrh52RYKymp4865pjNeHjpRymiZ35bSSqlrW7MliwYQBhAS2340jItw8fRCfPDSTvj2DeeTdXeSWVPHGXVOZ6OAqM0p1VxYHn2LSDlXltI93ZlFVa2fxlNZLMi1JjAnnwwdm8MbGY0xPiNQWu1IOcHRNAk3uymkrktIZ0S+ccXEdr5MH+ftxz2xd01QpV9OyjHLK3sxi9mQWc+PUgTrzolJeRJO7csrK5HQC/S26ypFSXkaTuzprVbU2PtyRybwx/egVEujpcJRSTWhyV2ft870nKamytjm2XSnlGS5P7iIyWEReFZFVrj638i7Lk05wTmQI5yZEejoUpdQZHEruIvKaiOSKyN4zts8VkRQRSRWRxwCMMWnGmCWdEazyHkfzy9mcVsgNUwZi0YWnlXKr0QPan3PJ0Zb768DcphtExA94AZgHjAJuEpFRHQtRdVUrk9OxCCyaHOfpUJTqdoL820/dDiV3Y8x6oPCMzdOA1PqWeg2wHLja0eBE5B4RSRaR5Ly8PEcPU16g1mZn1bYMLhoRQ9+eOme6Uu7myLBjZ2rusUB6k9cZQKyIRIrIS8BEEflFawcbY142xkwxxkyJjo52Igzlbt8ezCWvtJrFUwe1v7NSyuUcKYQ684RqS+c3xpgC4D4nzqu83IqkdGLCg5gzXH8oK+UJjjwv6EzLPQNoOgYuDsjqyAlEZL6IvFxcXOxEGMqdThZX8W1KLosmx+HvpyNplfKEq8YNaHcfZ/51JgFDRSRBRAKBG4GPO3ICY8xqY8w9ERE6d3dX8d72DOwGbujgJGFKKdeJDg9qdx9Hh0K+A2wChotIhogsMcZYgQeBL4ADwEpjzD4n4lVezm43rEhK57zBkcRHhXo6HKVUGxyquRtjbmpl+6fAp2d7cRGZD8xPTEw821MoN9qcVsCJwgr+57Jhng5FKdUOjxZNtSzTtSxPSqdnsD+Xj+7n6VCUUu3QHjHlkFPlNXy+9yTXTox1eLEApZTnaHJXDvlwZyY1NruObVfKCzgyzt2jyV2HQnYNxtR1pI6Li2CUA3NaKKU8T2vuql27M4o5eLJUp/ZVqgvRsoxq1/KkdHoE+LFgfPsPTiilOl9nP6GquoHyaisf78zkynH9CQ8O8HQ4SinAmPb30Zq7atOaPdmU19i0JKNUF6M1d9WmFUnpDI4OZco5vT0dilKqnpZllFMO55Sy7fgpbpw60KH5o5VS3kOTu2rViqR0/C3CdZN0tSWluhpN7qpFNVY77+/I5NJRfYkKa38GOqWUO3XuSkxO0w5V7/XVgRwKy2u0I1WpLko7VFWLlielMyAimFlDdbUlpboiLcuoZjJOVbDhcB7XTxmIn0U7UpXqijS5q2beTc4A4Pop2pGqVFelyV2dxmY3vJuczszEKOJ6h3g6HKVUC3Scu4+x2uydfo0Nh/PIKq7iRp3aV6kuTZN7F/HP748y6XdfUllj69TrrEhKp09oIJeMiunU6yilOpcOhewC0vLKeOqzg5RUWSmrtnbadfLLqvnqQA7XTYwlyF9XW1KqK9OhkF7OZjc8umo31dbOL8l8sD2TWpvRse1K+QAty3i5NzYeI/n4KSYN6tWp1zHGsDzpBJPP6c3QvuGdei2lVOfT5O7FjheU8/QXB7lweDTXTozt1GttO36KI3nl2mpXqgvw+jVUVevsdsPP39tNgMXCH68b69jYJycsT0onNNCPK8f279TrKKXcQ5O7l3pr6wk2pxXy+JUj6R/Ro1OvVVJVy5rd2SyYMIDQIP9OvZZSynmOTMGtyd0LZZyq4KlPDzAzMcotZZLVu7KorLWxWMe2K+UzNLl7GWMMv3h/Dwb443Vj3bJIxsqkdEb0C2d8nI5aUqoriOjR/nrGOs7dy6xISmfD4Xx+MW8EA/t0/uP/+7NK2JVRzGJdbUmpLmNoTFi7++g4dy+SXVzJk2sOcO7gPtwy/Ry3XHNlcjqB/pZOH42jlHIvLct4CWMMv3x/D7V2O39aOA6LG6baraq18f72DOaO7kevkMBOv55Syn00uXuJ97dn8m1KHj+7fATnRIa65Zpf7DtJSZVVx7Yr1cUYB/bR5O4Fckuq+O3qfUw+pzd3zIh323WXb01nYJ8enDc40m3XVEq5hyZ3DzPG8PiHe6m22nl60Ti3rXx0LL+cTWkFLJ4y0C0lIKWUe2ly97DVu7P5cn8OD186jCHR7feAu8rK5HQsAosma0lGKV+kyd2D8suq+c1Hexk/sBd3zxrstutabXZWbctgzvAY+kUEu+26Sin30eTuQb/5aB/l1Tb+143lGIB1KXnkllZrR6pSXZQx7XepanL3kM/2ZLNmTzY/uTiRYW6eYnd5UjrR4UHMGaGrLSnlqzS5e0BheQ2//mgvowf05N4LhrjknP+3NoXVu7La3S+npIpvU3JZNDmOAD/936+Ur9LpBzzg/1+9j6KKWv530XiXJdj3tmeyMjm93f1WbcvAZjfcMEVLMkr5Mp1+wM2+2p/DhzuzeGBOIqMG9HTpuQ/nlLX5vt1uWJmczvSEPiREuedBKaWUZ+jv5W5UXFHLLz/Yw4h+4TwwJ9Hl5z9ZUkVJVW2r728+WsDxggpunKatdqV8nSZ3N/rdmv0UlNfwv4vGE+jfObc+Nbf11vuKpHTCg/2ZN0ZXW1KqK9PpB7zItym5rNqWwb2zBzO2E+dNT22lNFNcUctne09y7cRYggP8Ou36SinvoMndDUqravnl+3tIjAnjJxcP7dRrHc4tbXH7hzszqbHadWy7Ut2ELpjpBn/49CA5JVW8d/+MTm81H26hLGOM4Z2tJxgbG8HoAd2n81qp7kxb7p3s+9R83tl6grtnDWbioN6dfr2WRszsySzm4MlSbbUr1Y1ocu9E5dVWfv7ebhKiQnn40mFuuWZmUSXl1dbTti1PSic4wMKCCQPcEoNSqnM5MPuAJvfO9KfPD5JZVMnTi8a5pRMzPKiuynYk74fWe0WNlY93ZnHF2P70DG5/UV2llG/Q5N5JtqQV8Oam49x+XjxT4/u45ZqJfeumDG5amlmzO5uyais3Th3klhiUUt5Bk3snqKyx8eh7uxnUJ4RH5w5323XP6RNCgJ+c1qm6IimdwVGhTI3v/Hq/Usp7aHLvBM+sTeF4QQVPLRxLSKD7BiT5WSwMjgojtX44ZGpuGcnHT7F46kBEdLUlpboTTe4utu14Ia99f5Rbpg9ixpAot18/sW9Y41OqK5PT8bcI102Kc3scSqnOYxx4RlWTuwtV1dr42ardDIjowS+uGOmRGIbGhHGisILSqlre25bBJSP7Eh0e5JFYlFKeow8xudBfvjpMWl45b941jbAgz9zaoTHh2A0sW59GQXkNi3WSMKW6JZdnIBEJBf4O1ADrjDFvufoa3mhXehEvrz/C4ikDmT0s2mNxDK0fMfPyhjT6RwQze6jnYlFKeY5DZRkReU1EckVk7xnb54pIioikishj9ZuvA1YZY5YCC1wcr1eqttr42apdxIQH8/hVninHNIiPDMXPIlTV2rl+cpxb12ZVSnkPR1vurwPPA282bBARP+AF4FIgA0gSkY+BOGBP/W42l0Xaii/355B8rNCl5xQRbp42iEGRIQ7t/8K3RziUU8Zrd0zx+INCgf4W4iNDSMsv53pdbUkp3+TAE6oOJXdjzHoRiT9j8zQg1RiTBiAiy4GrqUv0ccBO2vjNQETuAe4BGDTo7B6weXn9Ef7w6UEC/SxYXNg1XFVrJ9Df4vCUAWv3nWTGkEguGtHXdUE44fLR/cgrrWZgH8d+OCmlfI8zNfdYoOminRnAdOA54HkRuRJY3drBxpiXgZcBpkyZ4sjc802P5ekvUnhx3RGuHNefP98wwaWLXwz+xRqMI5M31LMbQ0QP73m0/9G5IzwdglLKw5xJ7i0Vc40xphy404nztslmN/zqw728s/UEN08fxO+uHqN1ZaWUOoMzyT0DaFrUjQOyOnICEZkPzE9MdGw90Rqrnf9esZM1e7J5YM4QHrlsuD55qZRSLXCmlpEEDBWRBBEJBG4EPu7ICYwxq40x90REtL+AREWNlSVvJLFmTzaPXzGSn10+QhO7UqpbctkaqiLyDrAJGC4iGSKyxBhjBR4EvgAOACuNMfvOOto2FFXUcOsrW/g+NZ+nF45j6ezBnXEZpZTyGY6Olrmple2fAp+e7cUdKcvkllRx26tbOZpfzt9vmcTcMf3P9nJKKdVteHRumfbKMscLyln40kbST1XwzzunamJXSikHee3cMgdPlnDbq1uptdl5e+m5TBjYy9MhKaVUl+GVs0JuO17IDS9twk+Ed+89TxO7Ukp1kHTkYZ1OC0IkDygCiptsjujA6ygg38VhnXk9V+zf2j6Obtd7ovdE78nZb2/rPnTVe9LLGNPy7IDGGK/4A7x8tq+B5M6OxxX7t7aPo9v1nug90Xty9tvbuQ8+c08a/nhTWebMqQo6+trVOnp+R/ZvbR9Ht+s90XviyHa9Jy1vb+s++NI9AbykLOMsEUk2xkzxdBzeRO9Jc3pPmtN70pyv3BNvark742VPB+CF9J40p/ekOb0nzfnEPfGJlrtSSqnT+UrLXSmlVBOa3JVSygdpcldKKR/kk8ldREJF5A0RWSYit3g6Hm8gIoNF5FURWeXpWLyFiFxT/x35SEQu83Q83kBERorISyKySkTu93Q83qI+p2wTkas8HYujukxyF5HXRCRXRPaesX2uiKSISKqIPFa/+TpglTFmKbDA7cG6SUfuiTEmzRizxDORuk8H78mH9d+RO4DFHgjXLTp4Tw4YY+4DbgC6/HDA1nQwnwD8HFjp3iid02WSO/A6MLfpBhHxA14A5gGjgJtEZBR1q0I1rO9qc2OM7vY6jt+T7uJ1On5PflX/vq96nQ7cExFZAPwH+Nq9YbrV6zh4T0TkEmA/kOPuIJ3RZZK7MWY9UHjG5mlAan2rtAZYDlxN3RKAcfX7dJnP2FEdvCfdQkfuidT5E/CZMWa7u2N1l45+T4wxHxtjZgA+W9Ls4D2ZA5wL3AwsFZEukVO8dspfB8XyQwsd6pL6dOA54HkRuZLOf6zY27R4T0QkEngSmCgivzDG/NEj0XlGa9+Th4BLgAgRSTTGvOSJ4Dykte/JhdSVNYNwYiGeLqrFe2KMeRBARO4A8o0xdg/E1mFdPbm3tIiqMcaUA3e6Oxgv0do9KQDuc3cwXqK1e/IcdQ2B7qi1e7IOWOfeULxGi/ek8S/GvO6+UJzXJX69aEMGMLDJ6zggy0OxeAu9J83pPWlO70lzPnVPunpyTwKGikiCiAQCNwIfezgmT9N70pzek+b0njTnU/ekyyR3EXkH2AQMF5EMEVlijLECDwJfAAeAlcaYfZ6M0530njSn96Q5vSfNdYd7ohOHKaWUD+oyLXellFKO0+SulFI+SJO7Ukr5IE3uSinlgzS5K6WUD9LkrpRSPkiTu1JK+SBN7qrLEZEnROSRszjuQhGZ0eT16yKyyLXRtRtDmTuvp7ovTe6qO7kQmNHeTkr5Ak3uqksQkcfrV8j5Chhev22IiHxev/zZBhEZUb99vohsEZEdIvKViPQVkXjqZsX8bxHZKSKz6k89W0Q2ikhaQyteRPqLyPr6/fY22beluOaKyHYR2SUiX9dvO+03i/pzxJ9x3IUi8p2IrBSRQyLylIjcIiJbRWSPiAxx1b1T3VNXn/JXdQMiMpm6SZwmUved3Q5sA14G7jPGHBaR6cDfgYuoW0XoXGOMEZG7gUeNMf8jIi8BZcaYZ+rPuwToD8wERlA3SdQq6hZl+MIY82T96jwhrcQVDSwDZhtjjopInw5+tPHASOoWjUgDXjHGTBORn1I31/x/dfB8SjXS5K66glnAB8aYCgAR+RgIpq7E8q5I4zTcQfX/jQNWiEh/IBA42sa5P6xffGG/iPSt35YEvCYiAfXv72zl2HOB9caYowDGmDNX9mlPkjEmu/4zHQHW1m/fQ93qP0qdNS3LqK7izBnuLECRMWZCkz8j69/7G/C8MWYscC91PwhaU93k7wKNS7DNBjKBf4nIj1o5VlqIC8DK6f+2Wrt+02vbm7y2ow0v5SRN7qorWA9cKyI9RCQcmA9UAEdF5HqA+vVQx9fvH0FdYga4vcl5SoHw9i4mIucAucaYZcCrwKRWdt0EXCAiCfXHNZRljjUcIyKTgARHPqRSrqTJXXm9+sWrVwA7gfeADfVv3QIsEZFdwD5+WAj8CerKNRuA/CanWk3dD4mmHaotuRDYKSI7gIXAX1uJKw+4B3i/PoYV9W+9B/QRkZ3A/cAhxz+tUq6h87krpZQP0pa7Ukr5IO20UcoBIrKFH0bjNLjNGLPHE/Eo1R4tyyillA/SsoxSSvkgTe5KKeWDNLkrpZQP0uSulFI+SJO7Ukr5oP8Ham3TX61DygkAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "data_by_date.loc['UK'].plot(x='deaths_culm', y='deaths', logx=True, logy=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 749,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f03f767bd10>"
-      ]
-     },
-     "execution_count": 749,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "data_by_date.loc['UK'].plot(x='cases_culm', y='cases')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 750,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "      <th>deaths_m7</th>\n",
-       "      <th>cases_m7</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>dateRep</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>2019-12-31</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-01</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-02</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-03</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-04</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>1440</td>\n",
-       "      <td>11</td>\n",
-       "      <td>316367</td>\n",
-       "      <td>41358</td>\n",
-       "      <td>311.0</td>\n",
-       "      <td>-7.0</td>\n",
-       "      <td>12.571429</td>\n",
-       "      <td>1051.714286</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>1077</td>\n",
-       "      <td>3</td>\n",
-       "      <td>317444</td>\n",
-       "      <td>41361</td>\n",
-       "      <td>-363.0</td>\n",
-       "      <td>-8.0</td>\n",
-       "      <td>12.571429</td>\n",
-       "      <td>1097.285714</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>1040</td>\n",
-       "      <td>5</td>\n",
-       "      <td>318484</td>\n",
-       "      <td>41366</td>\n",
-       "      <td>-37.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>12.571429</td>\n",
-       "      <td>1094.142857</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>713</td>\n",
-       "      <td>3</td>\n",
-       "      <td>319197</td>\n",
-       "      <td>41369</td>\n",
-       "      <td>-327.0</td>\n",
-       "      <td>-2.0</td>\n",
-       "      <td>10.428571</td>\n",
-       "      <td>1079.428571</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>1089</td>\n",
-       "      <td>12</td>\n",
-       "      <td>320286</td>\n",
-       "      <td>41381</td>\n",
-       "      <td>376.0</td>\n",
-       "      <td>9.0</td>\n",
-       "      <td>10.285714</td>\n",
-       "      <td>1071.000000</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>233 rows × 8 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff  \\\n",
-       "dateRep                                                                       \n",
-       "2019-12-31      0       0           0            0         NaN          NaN   \n",
-       "2020-01-01      0       0           0            0         0.0          0.0   \n",
-       "2020-01-02      0       0           0            0         0.0          0.0   \n",
-       "2020-01-03      0       0           0            0         0.0          0.0   \n",
-       "2020-01-04      0       0           0            0         0.0          0.0   \n",
-       "...           ...     ...         ...          ...         ...          ...   \n",
-       "2020-08-15   1440      11      316367        41358       311.0         -7.0   \n",
-       "2020-08-16   1077       3      317444        41361      -363.0         -8.0   \n",
-       "2020-08-17   1040       5      318484        41366       -37.0          2.0   \n",
-       "2020-08-18    713       3      319197        41369      -327.0         -2.0   \n",
-       "2020-08-19   1089      12      320286        41381       376.0          9.0   \n",
-       "\n",
-       "            deaths_m7     cases_m7  \n",
-       "dateRep                             \n",
-       "2019-12-31   0.000000     0.000000  \n",
-       "2020-01-01   0.000000     0.000000  \n",
-       "2020-01-02   0.000000     0.000000  \n",
-       "2020-01-03   0.000000     0.000000  \n",
-       "2020-01-04   0.000000     0.000000  \n",
-       "...               ...          ...  \n",
-       "2020-08-15  12.571429  1051.714286  \n",
-       "2020-08-16  12.571429  1097.285714  \n",
-       "2020-08-17  12.571429  1094.142857  \n",
-       "2020-08-18  10.428571  1079.428571  \n",
-       "2020-08-19  10.285714  1071.000000  \n",
-       "\n",
-       "[233 rows x 8 columns]"
-      ]
-     },
-     "execution_count": 750,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "ukdbd = data_by_date.loc['UK'].copy()\n",
-    "ukdbd['deaths_m7'] = ukdbd.deaths.transform(lambda x: x.rolling(7, 1).mean())\n",
-    "ukdbd['cases_m7'] = ukdbd.cases.transform(lambda x: x.rolling(7, 1).mean())\n",
-    "ukdbd"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 751,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f03fc51b690>"
-      ]
-     },
-     "execution_count": 751,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ukdbd.plot(x='deaths_culm', y='deaths_m7', logx=True, logy=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 752,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 864x576 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig, ax = plt.subplots(figsize=(12, 8))\n",
-    "xmax = 10\n",
-    "for c in COUNTRIES_CORE:\n",
-    "    if data_since_threshold.loc[(slice(None), c), 'deaths_culm'].max() > xmax:\n",
-    "        xmax = data_since_threshold.loc[(slice(None), c), 'deaths_culm'].max()\n",
-    "    data_since_threshold.loc[(slice(None), c), :].plot(x='deaths_culm', y='deaths_m7', logx=True, logy=True, xlim=(10, xmax * 1.1), label=c, ax=ax)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 753,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "41381"
-      ]
-     },
-     "execution_count": 753,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_since_threshold.loc[(slice(None), 'UK'), 'deaths_culm'].max()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 754,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array(['Asia', 'Europe', 'Africa', 'America', 'Oceania', 'Other'],\n",
-       "      dtype=object)"
-      ]
-     },
-     "execution_count": 754,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "countries.continentExp.unique()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 755,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "countriesAndTerritories     Kuwait\n",
-       "popData2019                4207077\n",
-       "continentExp                  Asia\n",
-       "Name: KW, dtype: object"
-      ]
-     },
-     "execution_count": 755,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "countries.loc['KW']"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 756,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "geoId  dateRep   \n",
-       "AD     2020-03-03    1.0\n",
-       "       2020-03-14    1.0\n",
-       "       2020-03-16    2.0\n",
-       "       2020-03-17    1.0\n",
-       "       2020-03-18    2.0\n",
-       "                    ... \n",
-       "ZW     2020-08-15    NaN\n",
-       "       2020-08-16    NaN\n",
-       "       2020-08-17    NaN\n",
-       "       2020-08-18    NaN\n",
-       "       2020-08-19    NaN\n",
-       "Name: deaths, Length: 37238, dtype: float64"
-      ]
-     },
-     "execution_count": 756,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_by_date.groupby(level=0)['deaths'].shift(-25)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 757,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_m7</th>\n",
-       "      <th>deaths_m7</th>\n",
-       "      <th>deaths_per_case</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>geoId</th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td rowspan=\"5\" valign=\"top\">AD</td>\n",
-       "      <td>2020-03-03</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-14</td>\n",
-       "      <td>1</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-16</td>\n",
-       "      <td>3</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.666667</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>0.800000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-17</td>\n",
-       "      <td>9</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.500000</td>\n",
-       "      <td>1.250000</td>\n",
-       "      <td>0.357143</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-18</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.800000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>0.500000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td rowspan=\"5\" valign=\"top\">ZW</td>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>82</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>88.714286</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>104</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>85.857143</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>85</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>87.428571</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>47</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>80.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>70</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>80.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>37238 rows × 5 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                  cases  deaths   cases_m7  deaths_m7  deaths_per_case\n",
-       "geoId dateRep                                                         \n",
-       "AD    2020-03-03      1     1.0   1.000000   1.000000         1.000000\n",
-       "      2020-03-14      1     1.0   1.000000   1.000000         1.000000\n",
-       "      2020-03-16      3     2.0   1.666667   1.333333         0.800000\n",
-       "      2020-03-17      9     1.0   3.500000   1.250000         0.357143\n",
-       "      2020-03-18      0     2.0   2.800000   1.400000         0.500000\n",
-       "...                 ...     ...        ...        ...              ...\n",
-       "ZW    2020-08-15     82     NaN  88.714286        NaN              NaN\n",
-       "      2020-08-16    104     NaN  85.857143        NaN              NaN\n",
-       "      2020-08-17     85     NaN  87.428571        NaN              NaN\n",
-       "      2020-08-18     47     NaN  80.000000        NaN              NaN\n",
-       "      2020-08-19     70     NaN  80.000000        NaN              NaN\n",
-       "\n",
-       "[37238 rows x 5 columns]"
-      ]
-     },
-     "execution_count": 757,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "offset_data = data_by_date.loc[:, ['cases']]\n",
-    "offset_data['deaths'] = data_by_date.groupby(level=0)['deaths'].shift(-25)\n",
-    "offset_data['cases_m7'] = offset_data.groupby(level=0)['cases'].transform(lambda x: x.rolling(7, 1).mean())\n",
-    "offset_data['deaths_m7'] = offset_data['deaths'].dropna().groupby(level=0).transform(lambda x: x.rolling(7, 1).mean())\n",
-    "offset_data['deaths_per_case'] = offset_data.deaths_m7 / offset_data.cases_m7\n",
-    "offset_data"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 758,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th>geoId</th>\n",
-       "      <th>AR</th>\n",
-       "      <th>BE</th>\n",
-       "      <th>BO</th>\n",
-       "      <th>BR</th>\n",
-       "      <th>BS</th>\n",
-       "      <th>CL</th>\n",
-       "      <th>CO</th>\n",
-       "      <th>CR</th>\n",
-       "      <th>CU</th>\n",
-       "      <th>DE</th>\n",
-       "      <th>...</th>\n",
-       "      <th>PY</th>\n",
-       "      <th>SE</th>\n",
-       "      <th>SI</th>\n",
-       "      <th>SR</th>\n",
-       "      <th>SV</th>\n",
-       "      <th>SX</th>\n",
-       "      <th>TT</th>\n",
-       "      <th>UK</th>\n",
-       "      <th>UY</th>\n",
-       "      <th>VE</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>since_threshold</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>0</td>\n",
-       "      <td>4.000000</td>\n",
-       "      <td>5.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>5.000000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>4.000000</td>\n",
-       "      <td>4.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.000000</td>\n",
-       "      <td>...</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>6.000000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>1.00</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>19.000000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>1</td>\n",
-       "      <td>4.500000</td>\n",
-       "      <td>5.500000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>6.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>4.000000</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.5</td>\n",
-       "      <td>2.500000</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>5.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.50</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>16.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2</td>\n",
-       "      <td>3.666667</td>\n",
-       "      <td>7.333333</td>\n",
-       "      <td>1.666667</td>\n",
-       "      <td>6.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>3.333333</td>\n",
-       "      <td>2.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.666667</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>3.666667</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.00</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>18.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.333333</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>3</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>8.500000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>7.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>3.500000</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.5</td>\n",
-       "      <td>1.250000</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>3.750000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>0.75</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>18.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>4</td>\n",
-       "      <td>3.200000</td>\n",
-       "      <td>11.200000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>8.000000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>3.800000</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>1.4</td>\n",
-       "      <td>7.000000</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>5.200000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>0.60</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.600000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>21.200000</td>\n",
-       "      <td>0.800000</td>\n",
-       "      <td>0.800000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>171</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>172</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>173</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>174</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>175</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>176 rows × 40 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "geoId                  AR         BE        BO        BR        BS        CL  \\\n",
-       "since_threshold                                                                \n",
-       "0                4.000000   5.000000  1.000000  5.000000  2.000000  4.000000   \n",
-       "1                4.500000   5.500000  2.000000  6.000000  1.000000  4.000000   \n",
-       "2                3.666667   7.333333  1.666667  6.333333  0.666667  3.333333   \n",
-       "3                3.000000   8.500000  2.000000  7.000000  0.500000  3.500000   \n",
-       "4                3.200000  11.200000  1.800000  8.000000  0.400000  3.800000   \n",
-       "...                   ...        ...       ...       ...       ...       ...   \n",
-       "171                   NaN        NaN       NaN       NaN       NaN       NaN   \n",
-       "172                   NaN        NaN       NaN       NaN       NaN       NaN   \n",
-       "173                   NaN        NaN       NaN       NaN       NaN       NaN   \n",
-       "174                   NaN        NaN       NaN       NaN       NaN       NaN   \n",
-       "175                   NaN        NaN       NaN       NaN       NaN       NaN   \n",
-       "\n",
-       "geoId                  CO        CR   CU        DE  ...        PY        SE  \\\n",
-       "since_threshold                                     ...                       \n",
-       "0                4.000000  1.000000  2.0  4.000000  ...  1.000000  6.000000   \n",
-       "1                3.000000  1.000000  1.5  2.500000  ...  0.500000  5.000000   \n",
-       "2                2.333333  0.666667  2.0  1.666667  ...  0.333333  3.666667   \n",
-       "3                2.250000  0.500000  1.5  1.250000  ...  0.250000  3.750000   \n",
-       "4                3.000000  0.400000  1.4  7.000000  ...  0.200000  5.200000   \n",
-       "...                   ...       ...  ...       ...  ...       ...       ...   \n",
-       "171                   NaN       NaN  NaN       NaN  ...       NaN       NaN   \n",
-       "172                   NaN       NaN  NaN       NaN  ...       NaN       NaN   \n",
-       "173                   NaN       NaN  NaN       NaN  ...       NaN       NaN   \n",
-       "174                   NaN       NaN  NaN       NaN  ...       NaN       NaN   \n",
-       "175                   NaN       NaN  NaN       NaN  ...       NaN       NaN   \n",
-       "\n",
-       "geoId                  SI    SR   SV        SX        TT         UK        UY  \\\n",
-       "since_threshold                                                                 \n",
-       "0                2.000000  1.00  1.0  2.000000  1.000000  19.000000  2.000000   \n",
-       "1                1.000000  1.50  1.0  1.000000  0.500000  16.500000  1.000000   \n",
-       "2                1.333333  1.00  1.0  0.666667  0.666667  18.333333  0.666667   \n",
-       "3                1.500000  0.75  1.0  0.500000       NaN  18.000000  0.500000   \n",
-       "4                1.400000  0.60  1.0  0.600000       NaN  21.200000  0.800000   \n",
-       "...                   ...   ...  ...       ...       ...        ...       ...   \n",
-       "171                   NaN   NaN  NaN       NaN       NaN        NaN       NaN   \n",
-       "172                   NaN   NaN  NaN       NaN       NaN        NaN       NaN   \n",
-       "173                   NaN   NaN  NaN       NaN       NaN        NaN       NaN   \n",
-       "174                   NaN   NaN  NaN       NaN       NaN        NaN       NaN   \n",
-       "175                   NaN   NaN  NaN       NaN       NaN        NaN       NaN   \n",
-       "\n",
-       "geoId                  VE  \n",
-       "since_threshold            \n",
-       "0                1.000000  \n",
-       "1                0.500000  \n",
-       "2                0.333333  \n",
-       "3                1.000000  \n",
-       "4                0.800000  \n",
-       "...                   ...  \n",
-       "171                   NaN  \n",
-       "172                   NaN  \n",
-       "173                   NaN  \n",
-       "174                   NaN  \n",
-       "175                   NaN  \n",
-       "\n",
-       "[176 rows x 40 columns]"
-      ]
-     },
-     "execution_count": 758,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "deaths_m7"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 759,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th>geoId</th>\n",
-       "      <th>AG</th>\n",
-       "      <th>AR</th>\n",
-       "      <th>AW</th>\n",
-       "      <th>BB</th>\n",
-       "      <th>BE</th>\n",
-       "      <th>BM</th>\n",
-       "      <th>BO</th>\n",
-       "      <th>BR</th>\n",
-       "      <th>BS</th>\n",
-       "      <th>BZ</th>\n",
-       "      <th>...</th>\n",
-       "      <th>SV</th>\n",
-       "      <th>SX</th>\n",
-       "      <th>TC</th>\n",
-       "      <th>TT</th>\n",
-       "      <th>UK</th>\n",
-       "      <th>UY</th>\n",
-       "      <th>VC</th>\n",
-       "      <th>VE</th>\n",
-       "      <th>VG</th>\n",
-       "      <th>VI</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>dateRep</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>2019-12-31</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-01</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-02</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-03</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-04</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>233 rows × 57 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "geoId       AG  AR  AW  BB   BE  BM  BO   BR  BS  BZ  ...  SV  SX  TC  TT  \\\n",
-       "dateRep                                               ...                   \n",
-       "2019-12-31 NaN NaN NaN NaN  0.0 NaN NaN  0.0 NaN NaN  ... NaN NaN NaN NaN   \n",
-       "2020-01-01 NaN NaN NaN NaN  0.0 NaN NaN  0.0 NaN NaN  ... NaN NaN NaN NaN   \n",
-       "2020-01-02 NaN NaN NaN NaN  0.0 NaN NaN  0.0 NaN NaN  ... NaN NaN NaN NaN   \n",
-       "2020-01-03 NaN NaN NaN NaN  0.0 NaN NaN  0.0 NaN NaN  ... NaN NaN NaN NaN   \n",
-       "2020-01-04 NaN NaN NaN NaN  0.0 NaN NaN  0.0 NaN NaN  ... NaN NaN NaN NaN   \n",
-       "...         ..  ..  ..  ..  ...  ..  ..  ...  ..  ..  ...  ..  ..  ..  ..   \n",
-       "2020-08-15 NaN NaN NaN NaN  NaN NaN NaN  NaN NaN NaN  ... NaN NaN NaN NaN   \n",
-       "2020-08-16 NaN NaN NaN NaN  NaN NaN NaN  NaN NaN NaN  ... NaN NaN NaN NaN   \n",
-       "2020-08-17 NaN NaN NaN NaN  NaN NaN NaN  NaN NaN NaN  ... NaN NaN NaN NaN   \n",
-       "2020-08-18 NaN NaN NaN NaN  NaN NaN NaN  NaN NaN NaN  ... NaN NaN NaN NaN   \n",
-       "2020-08-19 NaN NaN NaN NaN  NaN NaN NaN  NaN NaN NaN  ... NaN NaN NaN NaN   \n",
-       "\n",
-       "geoId        UK  UY  VC  VE  VG  VI  \n",
-       "dateRep                              \n",
-       "2019-12-31  0.0 NaN NaN NaN NaN NaN  \n",
-       "2020-01-01  0.0 NaN NaN NaN NaN NaN  \n",
-       "2020-01-02  0.0 NaN NaN NaN NaN NaN  \n",
-       "2020-01-03  0.0 NaN NaN NaN NaN NaN  \n",
-       "2020-01-04  0.0 NaN NaN NaN NaN NaN  \n",
-       "...         ...  ..  ..  ..  ..  ..  \n",
-       "2020-08-15  NaN NaN NaN NaN NaN NaN  \n",
-       "2020-08-16  NaN NaN NaN NaN NaN NaN  \n",
-       "2020-08-17  NaN NaN NaN NaN NaN NaN  \n",
-       "2020-08-18  NaN NaN NaN NaN NaN NaN  \n",
-       "2020-08-19  NaN NaN NaN NaN NaN NaN  \n",
-       "\n",
-       "[233 rows x 57 columns]"
-      ]
-     },
-     "execution_count": 759,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "offset_deaths_m7 = (offset_data.loc[COUNTRIES_ALL, ['deaths_m7']]\n",
-    "             .unstack().sort_index().xs('deaths_m7', axis=1, drop_level=True)).T.sort_index()\n",
-    "offset_deaths_m7"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 760,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "dateRep\n",
-       "2019-12-31    0.0\n",
-       "2020-01-01    0.0\n",
-       "2020-01-02    0.0\n",
-       "2020-01-03    0.0\n",
-       "2020-01-04    0.0\n",
-       "             ... \n",
-       "2020-08-15    NaN\n",
-       "2020-08-16    NaN\n",
-       "2020-08-17    NaN\n",
-       "2020-08-18    NaN\n",
-       "2020-08-19    NaN\n",
-       "Name: UK, Length: 233, dtype: float64"
-      ]
-     },
-     "execution_count": 760,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "offset_deaths_m7['UK']"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 761,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th>dateRep</th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "      <th>deaths_m4</th>\n",
-       "      <th>deaths_m7</th>\n",
-       "      <th>cases_m7</th>\n",
-       "      <th>deaths_g4</th>\n",
-       "      <th>deaths_g7</th>\n",
-       "      <th>doubling_time</th>\n",
-       "      <th>doubling_time_7</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>since_threshold</th>\n",
-       "      <th>geoId</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>153</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>1440</td>\n",
-       "      <td>11</td>\n",
-       "      <td>316367</td>\n",
-       "      <td>41358</td>\n",
-       "      <td>311.0</td>\n",
-       "      <td>-7.0</td>\n",
-       "      <td>15.50</td>\n",
-       "      <td>12.571429</td>\n",
-       "      <td>1051.714286</td>\n",
-       "      <td>15.062936</td>\n",
-       "      <td>10.481632</td>\n",
-       "      <td>1903.506790</td>\n",
-       "      <td>2735.338743</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>154</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>1077</td>\n",
-       "      <td>3</td>\n",
-       "      <td>317444</td>\n",
-       "      <td>41361</td>\n",
-       "      <td>-363.0</td>\n",
-       "      <td>-8.0</td>\n",
-       "      <td>13.00</td>\n",
-       "      <td>12.571429</td>\n",
-       "      <td>1097.285714</td>\n",
-       "      <td>10.440087</td>\n",
-       "      <td>10.481632</td>\n",
-       "      <td>2746.421476</td>\n",
-       "      <td>2735.537132</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>155</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>1040</td>\n",
-       "      <td>5</td>\n",
-       "      <td>318484</td>\n",
-       "      <td>41366</td>\n",
-       "      <td>-37.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>9.25</td>\n",
-       "      <td>12.571429</td>\n",
-       "      <td>1094.142857</td>\n",
-       "      <td>7.382256</td>\n",
-       "      <td>10.481632</td>\n",
-       "      <td>3884.352422</td>\n",
-       "      <td>2735.867781</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>156</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>713</td>\n",
-       "      <td>3</td>\n",
-       "      <td>319197</td>\n",
-       "      <td>41369</td>\n",
-       "      <td>-327.0</td>\n",
-       "      <td>-2.0</td>\n",
-       "      <td>5.50</td>\n",
-       "      <td>10.428571</td>\n",
-       "      <td>1079.428571</td>\n",
-       "      <td>4.716842</td>\n",
-       "      <td>8.114550</td>\n",
-       "      <td>6079.585100</td>\n",
-       "      <td>3534.098405</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>157</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>2020-08-19</td>\n",
-       "      <td>1089</td>\n",
-       "      <td>12</td>\n",
-       "      <td>320286</td>\n",
-       "      <td>41381</td>\n",
-       "      <td>376.0</td>\n",
-       "      <td>9.0</td>\n",
-       "      <td>5.75</td>\n",
-       "      <td>10.285714</td>\n",
-       "      <td>1071.000000</td>\n",
-       "      <td>4.820571</td>\n",
-       "      <td>8.022291</td>\n",
-       "      <td>5950.497778</td>\n",
-       "      <td>3575.774437</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                         dateRep  cases  deaths  cases_culm  deaths_culm  \\\n",
-       "since_threshold geoId                                                      \n",
-       "153             UK    2020-08-15   1440      11      316367        41358   \n",
-       "154             UK    2020-08-16   1077       3      317444        41361   \n",
-       "155             UK    2020-08-17   1040       5      318484        41366   \n",
-       "156             UK    2020-08-18    713       3      319197        41369   \n",
-       "157             UK    2020-08-19   1089      12      320286        41381   \n",
-       "\n",
-       "                       cases_diff  deaths_diff  deaths_m4  deaths_m7  \\\n",
-       "since_threshold geoId                                                  \n",
-       "153             UK          311.0         -7.0      15.50  12.571429   \n",
-       "154             UK         -363.0         -8.0      13.00  12.571429   \n",
-       "155             UK          -37.0          2.0       9.25  12.571429   \n",
-       "156             UK         -327.0         -2.0       5.50  10.428571   \n",
-       "157             UK          376.0          9.0       5.75  10.285714   \n",
-       "\n",
-       "                          cases_m7  deaths_g4  deaths_g7  doubling_time  \\\n",
-       "since_threshold geoId                                                     \n",
-       "153             UK     1051.714286  15.062936  10.481632    1903.506790   \n",
-       "154             UK     1097.285714  10.440087  10.481632    2746.421476   \n",
-       "155             UK     1094.142857   7.382256  10.481632    3884.352422   \n",
-       "156             UK     1079.428571   4.716842   8.114550    6079.585100   \n",
-       "157             UK     1071.000000   4.820571   8.022291    5950.497778   \n",
-       "\n",
-       "                       doubling_time_7  \n",
-       "since_threshold geoId                   \n",
-       "153             UK         2735.338743  \n",
-       "154             UK         2735.537132  \n",
-       "155             UK         2735.867781  \n",
-       "156             UK         3534.098405  \n",
-       "157             UK         3575.774437  "
-      ]
-     },
-     "execution_count": 761,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_since_threshold.loc[(slice(None), 'UK'), :].tail()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 762,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "countriesAndTerritories    Portugal\n",
-       "popData2019                10276617\n",
-       "continentExp                 Europe\n",
-       "Name: PT, dtype: object"
-      ]
-     },
-     "execution_count": 762,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "countries.loc['PT']"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 763,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 1080x648 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = cases_m7.iloc[-50:][COUNTRIES_FRIENDS].plot(figsize=(15, 9), title=\"Cases per day, 7 day moving average\", ylim=(-10, 1500))\n",
-    "ax.set_xlabel(f\"Days since {DEATH_COUNT_THRESHOLD} deaths\")\n",
-    "# uk_projection.deaths_m7.plot(ax=ax)\n",
-    "for c in COUNTRIES_FRIENDS:\n",
-    "    lvi = cases_m7[c].last_valid_index()\n",
-    "    if c != 'ES':\n",
-    "        ax.text(x = lvi + 1, y = cases_m7[c][lvi], s = f\"{c}: {cases_m7[c][lvi]:.0f}\")\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 764,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 1080x648 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = deaths_m7.iloc[-50:][COUNTRIES_FRIENDS].plot(figsize=(15, 9), title=\"Cases per day, 7 day moving average\", ylim=(-10, 100))\n",
-    "ax.set_xlabel(f\"Days since {DEATH_COUNT_THRESHOLD} deaths\")\n",
-    "# uk_projection.deaths_m7.plot(ax=ax)\n",
-    "for c in COUNTRIES_FRIENDS:\n",
-    "    lvi = deaths_m7[c].last_valid_index()\n",
-    "#     if c != 'ES':\n",
-    "    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = f\"{c}: {deaths_m7[c][lvi]:.0f}\")\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "jupytext": {
-   "formats": "ipynb,md"
-  },
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.7.4"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/covid.md b/covid.md

deleted file mode 100644 (file)

index e86f0ed..0000000
--- a/covid.md
+++ /dev/null
@@ -1,1482 +0,0 @@
----
-jupyter:
-  jupytext:
-    formats: ipynb,md
-    text_representation:
-      extension: .md
-      format_name: markdown
-      format_version: '1.2'
-      jupytext_version: 1.3.4
-  kernelspec:
-    display_name: Python 3
-    language: python
-    name: python3
----
-
-Data from [European Centre for Disease Prevention and Control](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide)
-
-```python
-import itertools
-import collections
-import json
-import pandas as pd
-import numpy as np
-from scipy.stats import gmean
-import datetime
-
-import matplotlib as mpl
-import matplotlib.pyplot as plt
-%matplotlib inline
-```
-
-```python
-DEATH_COUNT_THRESHOLD = 10
-COUNTRIES_CORE = 'IT DE UK ES IE FR'.split()
-COUNTRIES_NORDIC = 'SE NO DK FI UK'.split()
-# COUNTRIES_FRIENDS = 'IT UK ES BE SI MX'.split()
-COUNTRIES_FRIENDS = 'IT UK ES BE SI PT'.split()
-
-COUNTRIES_AMERICAS = ['AG', 'AR', 'AW', 'BS', 'BB', 'BZ', 'BM', 'BO', 'BR', 'VG', 'KY', # excluding Canada and USA
-       'CL', 'CO', 'CR', 'CU', 'CW', 'DM', 'DO', 'EC', 'SV', 'GL', 'GD', 'GT',
-       'GY', 'HT', 'HN', 'JM', 'MX', 'MS', 'NI', 'PA', 'PY', 'PE', 'PR', 'KN',
-       'LC', 'VC', 'SX', 'SR', 'TT', 'TC', 'VI', 'UY', 'VE']
-COUNTRIES_OF_INTEREST = list(set(COUNTRIES_CORE + COUNTRIES_FRIENDS))
-COUNTRIES_ALL = list(set(COUNTRIES_CORE + COUNTRIES_FRIENDS + COUNTRIES_NORDIC + COUNTRIES_AMERICAS))
-```
-
-```python
-!curl https://opendata.ecdc.europa.eu/covid19/casedistribution/csv/ > covid.csv
-```
-
-```python
-# First col is a date, treat geoId of NA as 'Namibia', not "NA" value
-raw_data = pd.read_csv('covid.csv', 
-                       parse_dates=[0], dayfirst=True,
-                       keep_default_na=False, na_values = [''],
-#                        dtype = {'day': np.int64, 
-#                                 'month': np.int64, 
-#                                 'year': np.int64, 
-#                                 'cases': np.int64, 
-#                                 'deaths': np.int64, 
-#                                 'countriesAndTerritories': str, 
-#                                 'geoId': str, 
-#                                 'countryterritoryCode': str, 
-#                                 'popData2019': np.int64, 
-#                                 'continentExp': str, 
-#                                 }
-                      )
-```
-
-```python
-raw_data.size
-```
-
-```python
-raw_data.fillna(0, inplace=True)
-```
-
-```python
-raw_data.head()
-```
-
-```python
-raw_data.dtypes
-```
-
-```python
-raw_data = raw_data.astype({'dateRep': np.datetime64, 
-    'day': np.int64, 
-    'month': np.int64, 
-    'year': np.int64, 
-    'cases': np.int64, 
-    'deaths': np.int64, 
-    'countriesAndTerritories': str, 
-    'geoId': str, 
-    'countryterritoryCode': str, 
-    'popData2019': np.int64, 
-    'continentExp': str })
-```
-
-```python
-raw_data.dtypes
-```
-
-```python
-raw_data[((raw_data.geoId == 'UK') & (raw_data.dateRep >= '2020-07-10'))]
-```
-
-```python
-# raw_data = raw_data[~ ((raw_data.geoId == 'ES') & (raw_data.dateRep >= '2020-05-22'))]
-```
-
-```python
-base_data = raw_data.set_index(['geoId', 'dateRep'])
-base_data.sort_index(inplace=True)
-base_data
-```
-
-```python
-base_data.loc['ES'].loc['2020-05-10':]
-```
-
-```python
-countries = raw_data[['geoId', 'countriesAndTerritories', 'popData2019', 'continentExp']]
-countries = countries[countries['popData2019'] != '']
-countries = countries.drop_duplicates()
-countries.set_index('geoId', inplace=True)
-countries = countries.astype({'popData2019': 'int64'})
-countries.head()
-```
-
-```python
-countries.shape
-```
-
-```python
-countries[countries.countriesAndTerritories == 'Finland']
-```
-
-```python
-countries.loc[COUNTRIES_OF_INTEREST]
-```
-
-```python
-countries[countries.continentExp == 'America'].index
-```
-
-```python
-data_by_date = base_data[['cases', 'deaths']]
-data_by_date.head()
-```
-
-```python
-data_by_date.loc['UK']
-```
-
-```python
-# data_by_date.deaths.drop_duplicates().sort_values().to_csv('dth.csv', header=True)
-```
-
-```python
-data_by_date.groupby(level=0).cumsum()
-```
-
-```python
-data_by_date = data_by_date.merge(
-    data_by_date.groupby(level=0).cumsum(), 
-    suffixes=('', '_culm'), 
-    left_index=True, right_index=True)
-data_by_date
-```
-
-```python
-data_by_date = data_by_date.merge(
-    data_by_date[['cases', 'deaths']].groupby(level=0).diff(), 
-    suffixes=('', '_diff'), 
-    left_index=True, right_index=True)
-data_by_date
-```
-
-```python
-data_by_date.loc['UK', '2020-04-17']
-```
-
-```python
-data_by_date.loc['UK']
-```
-
-```python
-# data_by_date[data_by_date.deaths_culm > DEATH_COUNT_THRESHOLD]
-```
-
-```python
-# days_since_threshold = data_by_date[data_by_date.deaths_culm > DEATH_COUNT_THRESHOLD].groupby(level=0).cumcount()
-# days_since_threshold.rename('since_threshold', inplace=True)
-```
-
-```python
-dbd = data_by_date[data_by_date.deaths_culm > DEATH_COUNT_THRESHOLD].reset_index(level=1)
-dbd['since_threshold'] = dbd.dateRep
-dbd.set_index('dateRep', append=True, inplace=True)
-dbd.sort_index(inplace=True)
-days_since_threshold = dbd.groupby(level=0).diff().since_threshold.dt.days.fillna(0).astype(int).groupby(level=0).cumsum()
-# days_since_threshold.groupby(level=0).cumsum()
-
-# days_since_threshold = dbd.rename('since_threshold')
-days_since_threshold
-```
-
-```python
-# days_since_threshold = (data_by_date[data_by_date.deaths_culm > DEATH_COUNT_THRESHOLD]
-#                         .reset_index(level=1).groupby(level=0)
-#                         .diff().dateRep.dt.days
-#                         .groupby(level=0).cumcount()
-#                        )
-# days_since_threshold.rename('since_threshold', inplace=True)
-# days_since_threshold
-```
-
-```python
-data_since_threshold = data_by_date.merge(days_since_threshold, 
-    left_index=True, right_index=True)
-data_since_threshold
-```
-
-```python
-data_since_threshold = data_since_threshold.set_index('since_threshold', append=True
-                              ).reorder_levels(['since_threshold', 'geoId', 'dateRep']
-                                              ).reset_index('dateRep')
-data_since_threshold.sort_index(inplace=True)
-data_since_threshold
-```
-
-```python
-data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT']), :]
-```
-
-```python
-data_since_threshold.loc[(slice(None), ['ES']), :].tail(8)
-```
-
-```python
-data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT']), ['deaths_culm']].unstack().plot(logy=True)
-```
-
-```python
-# deaths = data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT', 'IE']), ['deaths_culm']].unstack().xs('deaths_culm', axis=1, drop_level=True)
-```
-
-```python
-deaths = data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['deaths_culm']].unstack().sort_index().xs('deaths_culm', axis=1, drop_level=True)
-```
-
-```python
-cases = data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['cases_culm']].unstack().sort_index().xs('cases_culm', axis=1, drop_level=True)
-```
-
-```python
-COUNTRIES_AMERICAS_DEAD = list(set(deaths.columns) & set(COUNTRIES_AMERICAS))
-```
-
-```python
-data_since_threshold.reset_index().merge(countries, on='geoId').set_index(['since_threshold', 'geoId'])
-```
-
-```python
-data_since_threshold.reset_index().merge(countries, on='geoId').set_index(['since_threshold', 'geoId']).sort_index(inplace=True)
-```
-
-```python
-data_since_threshold_per_capita = data_since_threshold.reset_index().merge(countries, on='geoId').set_index(['since_threshold', 'geoId'])
-data_since_threshold_per_capita['cases_culm_pc'] = data_since_threshold_per_capita.cases_culm / data_since_threshold_per_capita.popData2019
-data_since_threshold_per_capita['deaths_culm_pc'] = data_since_threshold_per_capita.deaths_culm / data_since_threshold_per_capita.popData2019
-data_since_threshold_per_capita
-```
-
-```python
-deaths_pc = data_since_threshold_per_capita.loc[(slice(None), ['UK', 'DE', 'IT', 'IE']), ['deaths_culm_pc']].unstack().sort_index().xs('deaths_culm_pc', axis=1, drop_level=True)
-```
-
-```python
-deaths_pc.index
-```
-
-```python
-deaths_pc = data_since_threshold_per_capita.loc[(slice(None), COUNTRIES_ALL), ['deaths_culm_pc']].unstack().xs('deaths_culm_pc', axis=1, drop_level=True)
-```
-
-```python
-deaths[COUNTRIES_CORE].plot()
-```
-
-```python
-deaths[COUNTRIES_FRIENDS].plot()
-```
-
-```python
-ax = deaths[COUNTRIES_FRIENDS].plot(figsize=(10, 6), title="Total deaths, linear")
-ax.set_xlabel(f"Days since {DEATH_COUNT_THRESHOLD} deaths")
-for c in COUNTRIES_FRIENDS:
-    lvi = deaths[c].last_valid_index()
-    ax.text(x = lvi + 1, y = deaths[c][lvi], s = f"{c}: {deaths[c][lvi]:.0f}")
-# plt.savefig('covid_deaths_total_linear.png')    
-```
-
-```python
-ax = deaths[COUNTRIES_CORE].plot(figsize=(10, 6), title="Total deaths, linear")
-ax.set_xlabel(f"Days since {DEATH_COUNT_THRESHOLD} deaths")
-for c in COUNTRIES_CORE:
-    lvi = deaths[c].last_valid_index()
-    ax.text(x = lvi + 1, y = deaths[c][lvi], s = f"{c}: {deaths[c][lvi]:.0f}")
-plt.savefig('covid_deaths_total_linear.png')    
-```
-
-```python
-deaths_prime = deaths[COUNTRIES_CORE].copy()
-deaths_prime.loc[73:, 'ES'] = np.NaN
-# deaths_prime['ES'][70:]
-```
-
-```python
-ax = deaths_prime[COUNTRIES_CORE].plot(figsize=(10, 6), title="Total deaths, linear")
-for c in COUNTRIES_CORE:
-    lvi = deaths_prime[c].last_valid_index()
-    ax.text(x = lvi + 1, y = deaths_prime[c][lvi], s = f"{c}: {deaths_prime[c][lvi]:.0f}")
-# plt.savefig('covid_deaths_total_linear.png')    
-```
-
-```python
-ax = cases[COUNTRIES_CORE].plot(figsize=(10, 6), title="Total cases, linear")
-for c in COUNTRIES_CORE:
-    lvi = cases[c].last_valid_index()
-    ax.text(x = lvi + 1, y = cases[c][lvi], s = c)
-plt.savefig('covid_cases_total_linear.png')    
-```
-
-```python
-ax = deaths[COUNTRIES_AMERICAS_DEAD].plot(figsize=(10, 6), title="Total deaths, linear")
-for c in COUNTRIES_AMERICAS_DEAD:
-    lvi = deaths[c].last_valid_index()
-    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)
-# plt.savefig('covid_deaths_total_linear.png')    
-```
-
-```python
-ax = deaths[COUNTRIES_CORE + ['BR', 'MX']].plot(figsize=(10, 6), title="Total deaths, linear")
-for c in COUNTRIES_CORE + ['BR', 'MX']:
-    lvi = deaths[c].last_valid_index()
-    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)
-# plt.savefig('covid_deaths_total_linear.png')    
-```
-
-```python
-ax = deaths[COUNTRIES_NORDIC].plot(figsize=(10, 6), title="Total deaths, linear")
-for c in COUNTRIES_NORDIC:
-    lvi = deaths[c].last_valid_index()
-    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)
-# plt.savefig('covid_deaths_total_linear.png')    
-```
-
-```python
-ax = deaths[COUNTRIES_OF_INTEREST].plot(figsize=(10, 6), title="Total deaths, linear")
-for c in COUNTRIES_OF_INTEREST:
-    lvi = deaths[c].last_valid_index()
-    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)
-plt.savefig('covid_deaths_total_linear_of_interest.png') 
-```
-
-```python
-ax = deaths[COUNTRIES_CORE].plot(logy=True, figsize=(10, 6), title="Total deaths, log")
-for c in COUNTRIES_CORE:
-    lvi = deaths[c].last_valid_index()
-    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)
-
-plt.savefig('covid_deaths_total_log.png')
-```
-
-```python
-ylim = (5*10**3, 5*10**4)
-ax = deaths[COUNTRIES_CORE].plot(logy=True, figsize=(10, 6), ylim=ylim, title="Total deaths, log")
-for c in COUNTRIES_CORE:
-    lvi = deaths[c].last_valid_index()
-    if ylim[0] < deaths[c][lvi] < ylim[1]:
-        ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)
-
-# plt.savefig('covid_deaths_total_log.png')
-```
-
-```python
-ax = deaths[COUNTRIES_FRIENDS].plot(logy=True, figsize=(10, 6), title="Total deaths, log")
-for c in COUNTRIES_FRIENDS:
-    lvi = deaths[c].last_valid_index()
-    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)
-
-# plt.savefig('covid_deaths_total_log.png')
-```
-
-```python
-ax = deaths[COUNTRIES_NORDIC].plot(logy=True, figsize=(10, 6), title="Total deaths, log")
-for c in COUNTRIES_NORDIC:
-    lvi = deaths[c].last_valid_index()
-    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)
-
-# plt.savefig('covid_deaths_total_log.png')
-```
-
-```python
-ax = deaths[COUNTRIES_OF_INTEREST].plot(logy=True, figsize=(10, 6), title="Total deaths, log")
-for c in COUNTRIES_OF_INTEREST:
-    lvi = deaths[c].last_valid_index()
-    ax.text(x = lvi + 1, y = deaths[c][lvi], s = c)
-
-plt.savefig('covid_deaths_total_log.png')
-```
-
-```python
-ax = deaths_pc.plot(figsize=(10, 6), title="Deaths per capita, linear")
-for c in deaths_pc.columns:
-    lvi = deaths_pc[c].last_valid_index()
-    ax.text(x = lvi + 1, y = deaths_pc[c][lvi], s = c)
-plt.savefig('covid_deaths_per_capita_linear.png')
-```
-
-```python
-ax = deaths_pc.plot(logy=True, figsize=(10, 6), title="Deaths per capita, log")
-for c in deaths_pc.columns:
-    lvi = deaths_pc[c].last_valid_index()
-    ax.text(x = lvi + 1, y = deaths_pc[c][lvi], s = c)
-```
-
-```python
-deaths_pc[['UK', 'IE']].plot( figsize=(10, 6), title="Deaths per capita, linear")
-```
-
-```python
-deaths_pc[['UK', 'IE']].plot(logy=True, figsize=(10, 6), title="Deaths per capita, log")
-```
-
-```python
-deaths[['UK', 'ES', 'IT']].plot(logy=True, figsize=(10, 6), title="Deaths, log")
-plt.savefig('covid_deaths_selected_log.png')
-```
-
-```python
-deaths[['UK', 'ES', 'IT', 'MX']].plot(logy=True, figsize=(10, 6), title="Deaths, log")
-```
-
-```python
-data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT']), :]
-```
-
-```python
-data_since_threshold['deaths_m4'] = data_since_threshold.groupby(level=1)['deaths'].transform(lambda x: x.rolling(4, 1).mean())
-data_since_threshold['deaths_m7'] = data_since_threshold.groupby(level=1)['deaths'].transform(lambda x: x.rolling(7, 1).mean())
-data_since_threshold['cases_m7'] = data_since_threshold.groupby(level=1)['cases'].transform(lambda x: x.rolling(7, 1).mean())
-# data_since_threshold['deaths_diff_m4'] = data_since_threshold.groupby(level=1)['deaths_diff'].transform(lambda x: x.rolling(4, 1).mean())
-# data_since_threshold['deaths_diff_m7'] = data_since_threshold.groupby(level=1)['deaths_diff'].transform(lambda x: x.rolling(7, 1).mean())
-data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT']), :]
-```
-
-```python
-deaths_m4 = (data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['deaths_m4']]
-             .unstack().sort_index().xs('deaths_m4', axis=1, drop_level=True))
-```
-
-```python
-deaths_m7 = (data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['deaths_m7']]
-             .unstack().sort_index().xs('deaths_m7', axis=1, drop_level=True))
-```
-
-```python
-cases_m7 = (data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['cases_m7']]
-             .unstack().sort_index().xs('cases_m7', axis=1, drop_level=True))
-```
-
-```python
-ax = deaths_m4.plot(figsize=(10, 6), title="Deaths per day, 4 day moving average")
-for c in deaths_m4.columns:
-    lvi = deaths_m4[c].last_valid_index()
-    ax.text(x = lvi + 1, y = deaths_m4[c][lvi], s = c)
-plt.savefig('covid_deaths_per_day.png') 
-```
-
-```python
-ax = deaths_m4[COUNTRIES_CORE].plot(figsize=(10, 6), title="Deaths per day, 4 day moving average")
-for c in COUNTRIES_CORE:
-    lvi = deaths_m4[c].last_valid_index()
-    ax.text(x = lvi + 1, y = deaths_m4[c][lvi], s = c)
-plt.savefig('covid_deaths_per_day-core.png') 
-```
-
-```python
-ax = deaths_m4[COUNTRIES_FRIENDS].plot(figsize=(10, 6), title="Deaths per day, 4 day moving average")
-for c in COUNTRIES_FRIENDS:
-    lvi = deaths_m4[c].last_valid_index()
-    ax.text(x = lvi + 1, y = deaths_m4[c][lvi], s = c)
-plt.savefig('covid_deaths_per_day-friends.png') 
-```
-
-```python
-C7s = 'ES FR IT UK'.split()
-ax = deaths_m7[C7s].plot(figsize=(10, 6), title="Deaths per day, 7 day moving average")
-for c in C7s:
-    lvi = deaths_m7[c].last_valid_index()
-    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = c)
-# plt.savefig('covid_deaths_per_day-friends.png') 
-```
-
-```python
-ax = deaths_m7[COUNTRIES_CORE].plot(figsize=(10, 6), title="Deaths per day, 7 day moving average")
-ax.set_xlabel(f"Days since {DEATH_COUNT_THRESHOLD} deaths")
-for c in COUNTRIES_CORE:
-    lvi = deaths_m7[c].last_valid_index()
-    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = c)
-# plt.axhline(0, color='0.7')
-plt.savefig('covid_deaths_per_day_7.png') 
-```
-
-```python
-ax = deaths_m7[COUNTRIES_FRIENDS].plot(figsize=(10, 6), title="Deaths per day, 7 day moving average")
-ax.set_xlabel(f"Days since {DEATH_COUNT_THRESHOLD} deaths")
-for c in COUNTRIES_FRIENDS:
-    lvi = deaths_m7[c].last_valid_index()
-    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = c)
-# plt.axhline(0, color='0.7')
-# plt.savefig('covid_deaths_per_day_7.png') 
-```
-
-```python
-deaths_m7_prime = deaths_m7[COUNTRIES_CORE].copy()
-deaths_m7_prime.loc[73:, 'ES'] = np.NaN
-deaths_m7_prime['ES'][70:]
-```
-
-```python
-ax = deaths_m7_prime[COUNTRIES_CORE].plot(figsize=(10, 6), title="Deaths per day, 7 day moving average")
-for c in COUNTRIES_CORE:
-    lvi = deaths_m7_prime[c].last_valid_index()
-    ax.text(x = lvi + 1, y = deaths_m7_prime[c][lvi], s = c)
-# plt.savefig('covid_deaths_per_day_7.png') # see below for where this is written, with the projection
-```
-
-```python
-ax = deaths_m7[COUNTRIES_FRIENDS].plot(figsize=(10, 6), title="Deaths per day, 7 day moving average")
-for c in COUNTRIES_FRIENDS:
-    lvi = deaths_m7[c].last_valid_index()
-    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = c)
-plt.savefig('covid_deaths_per_day_friends_7.png') 
-```
-
-```python
-ax = deaths_m7[COUNTRIES_CORE + ['BR', 'MX']].plot(figsize=(10, 6), title="Deaths per day, 7 day moving average")
-for c in COUNTRIES_CORE + ['BR', 'MX']:
-    lvi = deaths_m7[c].last_valid_index()
-    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = c)
-# plt.savefig('covid_deaths_per_day_7.png') 
-```
-
-```python
-ax = cases_m7[COUNTRIES_CORE].plot(figsize=(10, 6), title="Cases per day, 7 day moving average")
-for c in COUNTRIES_CORE:
-    lvi = cases_m7[c].last_valid_index()
-    ax.text(x = lvi + 1, y = cases_m7[c][lvi], s = c)
-plt.savefig('covid_cases_per_day-core.png') 
-```
-
-```python
-ax = cases_m7[COUNTRIES_FRIENDS].plot(figsize=(10, 6), title="Cases per day, 7 day moving average")
-for c in COUNTRIES_FRIENDS:
-    lvi = cases_m7[c].last_valid_index()
-    ax.text(x = lvi + 1, y = cases_m7[c][lvi], s = c)
-# plt.savefig('covid_cases_per_day-core.png') 
-```
-
-```python
-def gmean_scale(items):
-    return gmean(items) / items[-1]
-```
-
-```python
-def doubling_time(df):
-    return np.log(2) / np.log((df.deaths_culm + df.deaths_g4) / df.deaths_culm)
-
-def doubling_time_7(df):
-    return np.log(2) / np.log((df.deaths_culm + df.deaths_g7) / df.deaths_culm)
-```
-
-```python
-# data_since_threshold['deaths_g4'] = data_since_threshold.groupby(level=1)['deaths'].transform(lambda x: x.rolling(4, 1).apply(gmean_scale, raw=True))
-# data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT']), :]
-```
-
-```python
-data_since_threshold['deaths_g4'] = data_since_threshold.groupby(level=1)['deaths'].transform(lambda x: x.rolling(4, 1).apply(gmean, raw=True))
-data_since_threshold['deaths_g7'] = data_since_threshold.groupby(level=1)['deaths'].transform(lambda x: x.rolling(7, 1).apply(gmean, raw=True))
-data_since_threshold.loc[(slice(None), ['UK', 'DE', 'IT']), :]
-```
-
-```python
-data_since_threshold['doubling_time'] = data_since_threshold.groupby(level=1).apply(doubling_time).reset_index(level=0, drop=True).sort_index()
-data_since_threshold['doubling_time_7'] = data_since_threshold.groupby(level=1).apply(doubling_time_7).reset_index(level=0, drop=True).sort_index()
-# data_since_threshold.loc[(slice(None), 'UK'), :]
-```
-
-```python
-doubling_times = (data_since_threshold.loc[(slice(None), COUNTRIES_OF_INTEREST), ['doubling_time']]
-             .unstack().sort_index().xs('doubling_time', axis=1, drop_level=True))
-doubling_times.replace([np.inf, -np.inf], np.nan, inplace=True)
-```
-
-```python
-doubling_times_7 = (data_since_threshold.loc[(slice(None), COUNTRIES_OF_INTEREST), ['doubling_time_7']]
-             .unstack().sort_index().xs('doubling_time_7', axis=1, drop_level=True))
-doubling_times_7.replace([np.inf, -np.inf], np.nan, inplace=True)
-```
-
-```python
-ax = doubling_times.plot(figsize=(10, 6), title="Doubling times, 4 day average")
-for c in doubling_times.columns:
-    lvi = doubling_times[c].last_valid_index()
-    ax.text(x = lvi + 1, y = doubling_times[c][lvi], s = c)
-# plt.savefig('covid_deaths_per_day.png') 
-```
-
-```python
-ax = doubling_times_7[COUNTRIES_CORE].plot(figsize=(10, 6), title="Doubling times, 7 day average")
-ax.legend(loc="upper left")
-for c in COUNTRIES_CORE:
-    lvi = doubling_times_7[c].last_valid_index()
-    ax.text(x = lvi + 1, y = doubling_times_7[c][lvi], s = c)
-plt.savefig('covid_doubling_times_7.png') 
-```
-
-```python
-ax = doubling_times[COUNTRIES_CORE].plot(figsize=(10, 6), title="Doubling times, 4 day average")
-for c in COUNTRIES_CORE:
-    lvi = doubling_times[c].last_valid_index()
-    ax.text(x = lvi + 1, y = doubling_times[c][lvi], s = c)
-plt.savefig('covid_doubling_times.png') 
-```
-
-```python
-ax = doubling_times[COUNTRIES_FRIENDS].plot(figsize=(10, 6), title="Doubling times")
-for c in COUNTRIES_FRIENDS:
-    lvi = doubling_times[c].last_valid_index()
-    ax.text(x = lvi + 1, y = doubling_times[c][lvi], s = c)
-plt.savefig('covid_doubling_times_friends.png')
-```
-
-```python
-ax = doubling_times[C7s].plot(figsize=(10, 6), title="Doubling times")
-for c in C7s:
-    lvi = doubling_times[c].last_valid_index()
-    ax.text(x = lvi + 1, y = doubling_times[c][lvi], s = c)
-# plt.savefig('covid_doubling_times_friends.png')
-```
-
-```python
-# deaths_diff_m4 = (data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['deaths_diff_m4']]
-#              .unstack().sort_index().xs('deaths_diff_m4', axis=1, drop_level=True))
-```
-
-```python
-# deaths_diff_m7 = (data_since_threshold.loc[(slice(None), COUNTRIES_ALL), ['deaths_diff_m7']]
-#              .unstack().sort_index().xs('deaths_diff_m7', axis=1, drop_level=True))
-```
-
-```python
-# deaths_diff_m7
-```
-
-```python
-# data_since_threshold.replace([np.inf, -np.inf], np.nan).groupby(level=1).last().loc[COUNTRIES_ALL]#, [doubling_time]]
-```
-
-```python
-dstl = data_since_threshold.replace([np.inf, -np.inf], np.nan).groupby(level=1).last()
-dstl.loc[dstl.index.intersection(COUNTRIES_ALL)]
-```
-
-```python
-# data_since_threshold.replace([np.inf, -np.inf], np.nan).groupby(level=1).last().loc[['UK', 'DE', 'IT']]#, [doubling_time]]
-dstl.loc[['UK', 'DE', 'IT', 'FR', 'ES']]
-```
-
-```python
-data_since_threshold.loc[(slice(None), ['UK']), :].tail(20)
-```
-
-```python
-data_since_threshold.loc[(slice(None), ['ES']), :].tail(20)
-```
-
-## Death projections
-
-```python
-data_since_threshold.loc[(slice(None), ['UK']), :].tail(15)
-```
-
-```python
-it_since_threshold = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['IT']), :]
-s_end = it_since_threshold.index.max()[0]
-s_end
-```
-
-```python
-uk_projection = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), :]
-uk_current_end = uk_projection.index.max()[0] + 1
-# s_start = uk_projection.index.max()[0] + 1
-uk_current_end
-```
-
-```python
-current_uk_deaths_m7 = uk_projection[uk_projection.deaths_m7 >= 0].iloc[-1].deaths_m7
-current_uk_deaths_m7
-```
-
-```python
-it_since_threshold[it_since_threshold.deaths_m7 <= current_uk_deaths_m7].loc[60:].first_valid_index()[0]
-```
-
-```python
-s_start = it_since_threshold[it_since_threshold.deaths_m7 <= current_uk_deaths_m7].loc[60:].first_valid_index()[0]
-s_start
-```
-
-```python
-s_start_date = data_since_threshold.loc[(89, 'IT'), 'dateRep']# .iloc[0]
-s_start_date
-```
-
-```python
-s_end - s_start
-```
-
-```python
-uk_end = s_end - s_start + uk_current_end
-uk_end
-```
-
-```python
-proj = it_since_threshold.loc[(slice(s_start, s_end), slice(None)), ['cases', 'deaths', 'deaths_m7']]
-ndiff = uk_current_end - s_start
-proj.index = pd.MultiIndex.from_tuples([(n + ndiff, 'UK') for n, _ in proj.index], names=proj.index.names)
-proj
-```
-
-```python
-it_since_threshold.loc[(slice(s_start - 8, s_start + 2), slice(None)), ['cases', 'deaths', 'deaths_m7']]
-```
-
-```python
-uk_projection[['cases', 'deaths', 'deaths_m7']].tail()
-```
-
-```python
-# proj['deaths_m7'] = proj['deaths_m7'] + 20
-# proj
-```
-
-Projected deaths, UK following IT trend from now.
-
-```python
-uk_projection = uk_projection.append(proj, sort=True)
-uk_projection.deaths.sum()
-```
-
-```python
-uk_projection = uk_projection.droplevel(1)
-uk_projection
-```
-
-```python
-uk_projection.loc[152, 'deaths']
-```
-
-## Correction for cumulative deaths correction on 14 August
-
-```python
-# uk_projection.loc[152, 'deaths'] = 50
-```
-
-```python
-uk_projection['deaths_m7'] = uk_projection['deaths'].transform(lambda x: x.rolling(7, 1).mean())
-uk_projection.loc[(uk_current_end - 20):(uk_current_end + 5)]
-```
-
-```python
-uk_projection.loc[(uk_current_end - 5):]
-```
-
-```python
-uk_projection.deaths_m7.plot()
-```
-
-```python
-proj.droplevel(level=1)
-```
-
-```python
-ax = deaths_m7[COUNTRIES_CORE].plot()
-# uk_projection['deaths_m7'].plot(figsize=(10, 6), title="Deaths per day, 7 day moving average", label="Projection", style='--', ax=ax)
-proj.droplevel(level=1)['deaths_m7'].plot(figsize=(10, 6), title="Deaths per day, 7 day moving average", label="Projection", style='--', ax=ax)
-ax.set_xlabel(f"Days since {DEATH_COUNT_THRESHOLD} deaths")
-for c in COUNTRIES_CORE:
-    lvi = deaths_m7[c].last_valid_index()
-    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = c)
-plt.savefig('covid_deaths_per_day_7.png') 
-```
-
-```python
-it_since_threshold.deaths.sum()
-```
-
-# Excess deaths calculation
-
-```python
-with open('excess_deaths.json') as f:
-    excess_deaths_data = json.load(f)
-    
-with open('excess_death_accuracy.json') as f:
-    excess_death_accuracy = json.load(f)
-    
-excess_deaths_data, excess_death_accuracy
-```
-
-```python
-# excess_deaths_upto = '2020-05-08'
-# excess_deaths = 54500
-```
-
-```python
-excess_deaths_upto = excess_deaths_data['end_date']
-excess_deaths = excess_deaths_data['excess_deaths']
-```
-
-Recorded deaths in period where ONS has reported total deaths
-
-```python
-ons_reported_deaths = base_data.loc['UK'][:excess_deaths_upto]['deaths'].sum()
-ons_reported_deaths
-```
-
-```python
-excess_deaths_upto
-```
-
-## Correction for deaths total correction on 14 August
-
-```python
-ons_unreported_deaths_data = base_data.loc['UK'][excess_deaths_upto:].iloc[1:]['deaths']
-# ons_unreported_deaths_data['2020-08-14'] = 50
-```
-
-```python
-ons_unreported_deaths = ons_unreported_deaths_data.sum()
-ons_unreported_deaths
-```
-
-```python
-scaled_ons_unreported_deaths = ons_unreported_deaths * excess_death_accuracy
-scaled_ons_unreported_deaths
-```
-
-```python
-uk_deaths_to_date = excess_deaths + scaled_ons_unreported_deaths
-uk_deaths_to_date
-```
-
-```python
-# data_since_threshold.loc[(slice(None), 'UK'), :][data_since_threshold.dateRep == excess_deaths_data['end_date']]
-```
-
-```python
-data_since_threshold[data_since_threshold.dateRep == excess_deaths_data['end_date']].loc[(slice(None), 'UK'), :]
-```
-
-```python
-ons_unreported_start = data_since_threshold[data_since_threshold.dateRep == excess_deaths_data['end_date']].loc[(slice(None), 'UK'), :].first_valid_index()[0] + 1
-ons_unreported_start
-```
-
-```python
-unreported_projected_deaths = uk_projection.loc[ons_unreported_start:].deaths.sum()
-unreported_projected_deaths
-```
-
-```python
-unreported_projected_deaths_scaled = unreported_projected_deaths * excess_death_accuracy
-unreported_projected_deaths_scaled
-```
-
-```python
-uk_projection.loc[(s_start):].deaths.sum()
-```
-
-```python
-deaths_actual_projected_scaled = uk_deaths_to_date + uk_projection.loc[(s_start):].deaths.sum() * excess_death_accuracy
-deaths_actual_projected_scaled
-```
-
-```python
-# excess_deaths / reported_deaths
-```
-
-True deaths to date, if we follow the scaling of excess deaths over reported deaths so far.
-
-```python
-uk_covid_deaths = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), 'deaths_culm'].iloc[-1]
-uk_covid_deaths
-```
-
-```python
-# uk_covid_deaths_scaled = excess_deaths + unreported_deaths * excess_death_accuracy
-# uk_covid_deaths_scaled
-```
-
-```python
-# data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['IT']), 'dateRep'].iloc[-1] + pd.Timedelta(s_end - s_start, unit='days')
-```
-
-```python
-# data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), 'dateRep'].iloc[-1].strftime("%Y-%m-%d")
-```
-
-```python
-# uk_covid_deaths * excess_deaths / reported_deaths
-```
-
-```python
-# uk_projection.deaths.sum() * excess_deaths / reported_deaths
-```
-
-```python
-# data_since_threshold.loc[(slice(None), 'FR'), :]
-# data_since_threshold[data_since_threshold.dateRep == '2020-05-18'].loc[(slice(None), 'FR'), :]
-```
-
-## School reopenings
-
-```python
-school_reopenings = {
-    'ES': {'date': '2020-05-18'},
-    'FR': {'date': '2020-05-18'}, # some areas only
-#     'IT': {'date': '2020-09-01'},
-    # 'IE': {'date': '2020-09-01'},
-    'DE': {'date': '2020-05-04'},
-    'UK': {'date': '2020-06-01'}
-}
-```
-
-```python
-data_since_threshold[data_since_threshold.dateRep == '2020-05-04'].loc[(slice(None), ['DE']), :].first_valid_index()
-```
-
-```python
-data_since_threshold[data_since_threshold.dateRep == '2020-05-04'].loc[(slice(None), ['DE']), :].iloc[0].deaths_m7
-```
-
-```python
-for cID in school_reopenings:
-    dst_in = data_since_threshold[data_since_threshold.dateRep == (school_reopenings[cID]['date'])].loc[(slice(None), [cID]), :]
-    dst_i = dst_in.first_valid_index()
-    dst_n = dst_in.iloc[0].deaths_m7
-    school_reopenings[cID]['since_threshold'] = dst_i[0]
-    school_reopenings[cID]['deaths_m7'] = dst_n
-school_reopenings
-```
-
-```python
-ax = deaths_m7[COUNTRIES_CORE].plot(figsize=(15, 9), title="Deaths per day, 7 day moving average")
-# uk_projection.deaths_m7.plot(ax=ax)
-for c in COUNTRIES_CORE:
-    lvi = deaths_m7[c].last_valid_index()
-    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = f"{c}: {deaths_m7[c][lvi]:.0f}")
-    if c in school_reopenings:
-        marker_col = [l for l in ax.lines if l.get_label() == c][0].get_color()
-        ax.plot(school_reopenings[c]['since_threshold'], school_reopenings[c]['deaths_m7'], '*', 
-                markersize=18, markerfacecolor=marker_col, markeredgecolor=marker_col)
-        ax.text(x = school_reopenings[c]['since_threshold'] + 1, y = school_reopenings[c]['deaths_m7'], 
-                s = f"{school_reopenings[c]['date']}: {school_reopenings[c]['deaths_m7']:.0f}")
-plt.savefig('school_reopenings.png')
-```
-
-```python
-# ax = deaths_m7[COUNTRIES_CORE].plot(figsize=(15, 9), title="Deaths per day, 7 day moving average",
-#                                    xlim=(46, 91), ylim=(0, 400))
-# # uk_projection.deaths_m7.plot(ax=ax)
-# for c in COUNTRIES_CORE:
-#     lvi = deaths_m7[c].last_valid_index()
-#     ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = f"{c}: {deaths_m7[c][lvi]:.0f}", fontsize=14)
-#     if c in school_reopenings:
-#         marker_col = [l for l in ax.lines if l.get_label() == c][0].get_color()
-#         ax.plot(school_reopenings[c]['since_threshold'], school_reopenings[c]['deaths_m7'], '*', 
-#                 markersize=18, markerfacecolor=marker_col, markeredgecolor=marker_col)
-#         ax.text(x = school_reopenings[c]['since_threshold'] + 1, y = school_reopenings[c]['deaths_m7'], 
-#                 s = f"{school_reopenings[c]['date']}: {school_reopenings[c]['deaths_m7']:.0f}",
-#                 fontsize=14)
-# plt.savefig('school_reopenings_detail.png')
-```
-
-# Lockdown graphs
-
-```python
-lockdown_dates = {
-    'ES': { 'part_start': {'date': '2020-03-14'}
-          , 'full_start': {'date': '2020-03-15'}
-          , 'part_finish': {'date': '2020-05-18'}
-          },
-    'FR': { 'part_start': {'date': '2020-03-13'}
-          , 'full_start': {'date': '2020-03-17'}
-          , 'part_finish': {'date': '2020-05-11'}
-          },
-    'IT': { 'part_start': {'date': '2020-03-08'}
-          , 'full_start': {'date': '2020-03-10'}
-          , 'part_finish': {'date': '2020-05-04'}
-          },
-    'DE': { #'part_start': {'date': '2020-03-13'}
-          'full_start': {'date': '2020-03-22'}
-          , 'part_finish': {'date': '2020-05-06'}
-          },
-    'UK': { 'part_start': {'date': '2020-03-23'}
-          , 'full_start': {'date': '2020-03-23'}
-          , 'part_finish': {'date': '2020-05-31'}
-          },
-    'IE': { #'part_start': {'date': '2020-03-12'}
-          'full_start': {'date': '2020-03-27'}
-          , 'part_finish': {'date': '2020-05-18'}
-          },
-}
-```
-
-```python
-for cID in lockdown_dates:
-    for phase in lockdown_dates[cID]:
-        dst_in = data_since_threshold[data_since_threshold.dateRep == (lockdown_dates[cID][phase]['date'])].loc[(slice(None), [cID]), :]
-        dst_i = dst_in.first_valid_index()
-        dst_n = dst_in.iloc[0].deaths_m7
-        dst_c = dst_in.iloc[0].cases_m7
-        lockdown_dates[cID][phase]['since_threshold'] = dst_i[0]
-        lockdown_dates[cID][phase]['deaths_m7'] = dst_n
-        lockdown_dates[cID][phase]['cases_m7'] = dst_c
-
-lockdown_dates
-```
-
-```python
-ax = deaths_m7[COUNTRIES_CORE].plot(figsize=(15, 9), title="Deaths per day, 7 day moving averagee, with lockdown dates")
-ax.set_xlabel(f"Days since {DEATH_COUNT_THRESHOLD} deaths")
-# uk_projection.deaths_m7.plot(ax=ax)
-for c in COUNTRIES_CORE:
-    lvi = deaths_m7[c].last_valid_index()
-    if c != 'UK':
-        ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = f"{c}: {deaths_m7[c][lvi]:.0f}")
-    if c in lockdown_dates:
-        for phase in lockdown_dates[c]:
-            marker_col = [l for l in ax.lines if l.get_label() == c][0].get_color()
-            ax.plot(lockdown_dates[c][phase]['since_threshold'], lockdown_dates[c][phase]['deaths_m7'], '*',
-                    markersize=18, markerfacecolor=marker_col, markeredgecolor=marker_col)
-            if 'start' not in phase:
-                ax.text(x = lockdown_dates[c][phase]['since_threshold'] + 1, y = lockdown_dates[c][phase]['deaths_m7'], 
-                        s = f"{lockdown_dates[c][phase]['date']}: {lockdown_dates[c][phase]['deaths_m7']:.0f}")
-# plt.savefig('school_reopenings.png')
-```
-
-```python
-ax = cases_m7.iloc[-50:][COUNTRIES_CORE].plot(figsize=(15, 9), title="Cases per day, 7 day moving average, with lockdown dates") #, ylim=(-10, 1500))
-ax.set_xlabel(f"Days since {DEATH_COUNT_THRESHOLD} deaths")
-# uk_projection.deaths_m7.plot(ax=ax)
-for c in COUNTRIES_CORE:
-    lvi = cases_m7[c].last_valid_index()
-#     if c != 'UK':
-    ax.text(x = lvi + 1, y = cases_m7[c][lvi], s = f"{c}: {cases_m7[c][lvi]:.0f}")
-
-```
-
-```python
-ax = cases_m7[COUNTRIES_CORE].plot(figsize=(15, 9), title="Cases per day, 7 day moving average, with lockdown dates")
-ax.set_xlabel(f"Days since {DEATH_COUNT_THRESHOLD} deaths")
-# uk_projection.deaths_m7.plot(ax=ax)
-for c in COUNTRIES_CORE:
-    lvi = cases_m7[c].last_valid_index()
-#     if c != 'UK':
-    ax.text(x = lvi + 1, y = cases_m7[c][lvi], s = f"{c}: {cases_m7[c][lvi]:.0f}")
-    if c in lockdown_dates:
-        for phase in lockdown_dates[c]:
-            marker_col = [l for l in ax.lines if l.get_label() == c][0].get_color()
-            if 'start' in phase:
-                marker_shape = '^'
-            else:
-                marker_shape = 'v'
-            ax.plot(lockdown_dates[c][phase]['since_threshold'], lockdown_dates[c][phase]['cases_m7'], 
-                    marker_shape,
-                    markersize=18, markerfacecolor=marker_col, markeredgecolor=marker_col)
-            if 'start' not in phase:
-                ax.text(x = lockdown_dates[c][phase]['since_threshold'] + 1, y = lockdown_dates[c][phase]['cases_m7'], 
-                        s = f"{lockdown_dates[c][phase]['date']}: {lockdown_dates[c][phase]['cases_m7']:.0f}")
-plt.savefig('cases_per_day_with_lockdown.png')
-```
-
-```python
-ax = cases_m7[COUNTRIES_CORE].plot(figsize=(10, 6), title="Cases per day, 7 day moving average")
-for c in COUNTRIES_CORE:
-    lvi = cases_m7[c].last_valid_index()
-    ax.text(x = lvi + 1, y = cases_m7[c][lvi], s = c)
-plt.savefig('covid_cases_per_day-core.png') 
-```
-
-```python
-ax = deaths_m7[COUNTRIES_CORE].plot(figsize=(15, 9), title="Deaths per day, 7 day moving average",
-                                   xlim=(0, 15), 
-                                    ylim=(0, 66)
-                                   )
-# uk_projection.deaths_m7.plot(ax=ax)
-for c in COUNTRIES_CORE:
-    lvi = deaths_m7[c].last_valid_index()
-    if c in lockdown_dates:
-        for phase in lockdown_dates[c]:
-            if 'start' in phase:
-                print(c, phase)
-                marker_col = [l for l in ax.lines if l.get_label() == c][0].get_color()
-                ax.plot(lockdown_dates[c][phase]['since_threshold'], lockdown_dates[c][phase]['deaths_m7'], '*', 
-                        markersize=18, markerfacecolor=marker_col, markeredgecolor=marker_col)
-                ax.text(x = lockdown_dates[c][phase]['since_threshold'] + 0.3, y = lockdown_dates[c][phase]['deaths_m7'], 
-                        s = f"{lockdown_dates[c][phase]['date']}: {lockdown_dates[c][phase]['deaths_m7']:.0f}")
-# plt.savefig('school_reopenings.png')
-```
-
-```python
-
-```
-
-```python
-
-```
-
-# Write results to summary file
-
-```python
-with open('covid_summary.md', 'w') as f:
-    f.write('% Covid death data summary\n')
-    f.write('% Neil Smith\n')
-    f.write(f'% Created on {datetime.datetime.now().strftime("%Y-%m-%d")}\n')
-    f.write('\n')
-        
-    last_uk_date = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), 'dateRep'].iloc[-1]
-    f.write(f'> Last UK data from {last_uk_date.strftime("%Y-%m-%d")}\n')
-```
-
-```python
-with open('covid_summary.md', 'a') as f:
-    f.write('\n')
-    f.write('## Headlines\n')
-    f.write('\n')
-    f.write('| []() | |\n')
-    f.write('|:---|---:|\n')
-    f.write(f'| Deaths reported so far | {uk_covid_deaths} | \n')
-    f.write(f'| Total Covid deaths to date (estimated) | {uk_deaths_to_date:.0f} |\n')
-    projection_date = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['IT']), 'dateRep'].iloc[-1] + pd.Timedelta(s_end - s_start, unit='days')
-    f.write(f'| Projected total deaths up to {projection_date.strftime("%Y-%m-%d")} | {deaths_actual_projected_scaled:.0f} | \n')
-    f.write('\n')
-```
-
-```python
-with open('covid_summary.md', 'a') as f:
-    f.write('\n')
-    f.write('## Total deaths\n')
-    f.write(f'Time based on days since {DEATH_COUNT_THRESHOLD} deaths\n')
-    f.write('\n')
-    f.write('![Total deaths](covid_deaths_total_linear.png)\n')
-    f.write('\n')
-    f.write('| Country ID | Country name | Total deaths |\n')
-    f.write('|:-----------|:-------------|-------------:|\n')
-    for c in sorted(COUNTRIES_CORE):
-        lvi = deaths[c].last_valid_index()
-        f.write(f'| {c} | {countries.loc[c].countriesAndTerritories} | {int(deaths[c][lvi])} |\n')
-    f.write('\n')
-```
-
-```python
-with open('covid_summary.md', 'a') as f:
-    f.write('\n')
-    f.write('## All-causes deaths, UK\n')
-    f.write('\n')
-    f.write('![All-causes deaths](deaths-radar.png)\n')
-    f.write('\n')
-    f.write('### Excess deaths\n')
-    f.write('\n')
-    f.write(f'From week ending 20 March 2020 until week ending {pd.to_datetime(excess_deaths_upto).strftime("%d %B %Y")}, ')
-    f.write(f'there were approximately **{excess_deaths:.0f}** excess deaths, over the average for the previous five years.\n')
-    f.write('\n')
-```
-
-```python
-with open('covid_summary.md', 'a') as f:
-    f.write(f'In that period, the UK reported {ons_reported_deaths} Covid deaths.\n')
-    f.write(f'In the last three weeks for which excess deaths have been reported, the excess deaths have been {excess_death_accuracy:.3f} higher than the Covid-reported deaths.\n')
-#     f.write(f'That means the actual number of Covid death is about {excess_deaths / reported_deaths:.2f} times higher than the reported figures.\n')
-    f.write('\n')
-    f.write(f'The UK has reported {uk_covid_deaths} deaths so far.\n')
-    f.write(f'Using the scaling factor above (for Covid-19 deaths after the ONS figures), I infer that there have been **{uk_deaths_to_date:.0f}** total deaths so far.\n')
-    f.write('\n')
-```
-
-```python
-with open('covid_summary.md', 'a') as f:
-    f.write('\n')
-    f.write('## Deaths per day\n')
-    f.write(f'Based on a 7-day moving average\n')
-    f.write('\n')
-    f.write('![Deaths per day](covid_deaths_per_day_7.png)\n')
-    f.write('\n')
-```
-
-```python
-s_end - s_start - 1
-```
-
-```python
-with open('covid_summary.md', 'a') as f:
-    f.write('\n')
-    f.write('## Projected deaths\n')
-    f.write(f"The UK's daily deaths data is very similar to Italy's.\n")
-    f.write(f'If I use the Italian data for the next {s_end - s_start - 1} days (from {s_start_date.strftime("%d %B %Y")} onwards),')
-    f.write(f' the UK will report {uk_projection.deaths.sum()} deaths on day {uk_end} of the epidemic.\n')
-    f.write('\n')
-    f.write('Using the excess deaths scaling from above, that will translate into ')
-    f.write(f'**{deaths_actual_projected_scaled:.0f}** Covid deaths total.\n')
-    f.write('\n')
-```
-
-```python
-with open('covid_summary.md', 'a') as f:
-    f.write('\n')
-    f.write('## Deaths doubling times\n')
-    f.write(f'Based on a 7-day moving average\n')
-    f.write('\n')
-    f.write('![Deaths doubling times](covid_doubling_times_7.png)\n')
-    f.write('\n')
-```
-
-```python
-with open('covid_summary.md', 'a') as f:
-    f.write('\n')
-    f.write('## Cases per day and lockdown dates\n')
-    f.write(f'Based on a 7-day moving average\n')
-    f.write('\n')
-    f.write('![Cases per day](cases_per_day_with_lockdown.png)\n')
-    f.write('\n')
-```
-
-```python
-with open('covid_summary.md', 'a') as f:
-    f.write('\n')
-    f.write('| Country ID | Country name | Most recent daily cases | Most recent daily deaths |\n')
-    f.write('|:-----------|:-------------|------------------------:|-------------------------:|\n')
-    for c in sorted(COUNTRIES_CORE):
-        lvic = cases_m7[c].last_valid_index()
-        lvid = deaths_m7[c].last_valid_index()
-        f.write(f'| {c} | {countries.loc[c].countriesAndTerritories} | {cases_m7[c][lvic]:.0f} | {deaths_m7[c][lvid]:.0f} | \n')
-    f.write('\n')
-    f.write('(Figures are 7-day averages)\n')
-    f.write('\n')
-```
-
-```python
-with open('covid_summary.md', 'a') as f:
-    f.write('# Data sources\n')
-    f.write('\n')
-    f.write('> Covid data from [European Centre for Disease Prevention and Control](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide)\n')
-    f.write('\n')    
-    f.write("""> Population data from:
-
-* [Office of National Statistics](https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/weeklyprovisionalfiguresondeathsregisteredinenglandandwales) (Endland and Wales) Weeks start on a Saturday.
-* [Northern Ireland Statistics and Research Agency](https://www.nisra.gov.uk/publications/weekly-deaths) (Northern Ireland). Weeks start on a Saturday. Note that the week numbers don't match the England and Wales data.
-* [National Records of Scotland](https://www.nrscotland.gov.uk/statistics-and-data/statistics/statistics-by-theme/vital-events/general-publications/weekly-and-monthly-data-on-births-and-deaths/weekly-data-on-births-and-deaths) (Scotland). Note that Scotland uses ISO8601 week numbers, which start on a Monday.""")
-    
-    f.write('\n\n')
-    f.write('> [Source code available](https://git.njae.me.uk/?p=covid19.git;a=tree)\n')
-    f.write('\n') 
-
-```
-
-```python
-!pandoc -s covid_summary.md > covid_summary.html
-```
-
-```python
-!scp covid_summary.html neil@ogedei:/var/www/scripts.njae.me.uk/covid/index.html
-!scp covid_deaths_total_linear.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
-!scp deaths-radar.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
-!scp covid_deaths_per_day_7.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
-!scp covid_doubling_times_7.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
-!scp cases_per_day_with_lockdown.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
-```
-
-```python
-with open('uk_covid_deaths.js', 'w') as f:
-    f.write(f"document.write('{uk_covid_deaths}');")
-    
-with open('estimated_total_deaths.js', 'w') as f:
-    f.write(f"document.write('{uk_deaths_to_date:.0f}');")
-
-with open('projection_date.js', 'w') as f:
-    f.write(f"document.write(\'{projection_date.strftime('%d %B %Y')}\');")
-
-with open('projected_deaths.js', 'w') as f:
-    f.write(f"document.write('{uk_projection.deaths.sum():.0f}');")
-
-with open('projected_excess_deaths.js', 'w') as f:
-    f.write(f"document.write('{deaths_actual_projected_scaled:.0f}');")
-
-with open('excess_deaths_upto.js', 'w') as f:
-    f.write(f"document.write('{pd.to_datetime(excess_deaths_upto).strftime('%d %B %Y')}');")
-
-with open('excess_deaths.js', 'w') as f:
-    f.write(f"document.write('{excess_deaths:.0f}');")
-    
-with open('reported_deaths.js', 'w') as f:
-    f.write(f"document.write('{ons_reported_deaths:.0f}');")
-    
-with open('scaling_factor.js', 'w') as f:
-    f.write(f"document.write('{excess_death_accuracy:.2f}');")  
-
-with open('projection_length.js', 'w') as f:
-    f.write(f"document.write('{s_end - s_start - 1}');")
-    
-with open('s_end.js', 'w') as f:
-    f.write(f"document.write('{s_end}');")
-    
-s_start_date_str = s_start_date.strftime("%d %B %Y")
-with open('s_start_date.js', 'w') as f:
-    f.write(f"document.write('{s_start_date_str}');")
-    
-with open('uk_end.js', 'w') as f:
-    f.write(f"document.write('{uk_end}');")
-    
-with open('last_uk_date.js', 'w') as f:
-    f.write(f"document.write('{pd.to_datetime(last_uk_date).strftime('%d %B %Y')}');")
-```
-
-```python
-pd.to_datetime(excess_deaths_upto).strftime('%d %B %Y')
-```
-
-```python
-!scp uk_covid_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
-!scp estimated_total_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
-!scp projection_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
-!scp projected_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
-!scp projected_excess_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
-!scp excess_deaths_upto.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
-!scp excess_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
-!scp reported_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
-!scp scaling_factor.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
-!scp projection_length.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
-!scp s_end.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
-!scp s_start_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
-!scp uk_end.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
-!scp last_uk_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/    
-```
-
-```python
-data_by_date.loc['UK'].to_csv('data_by_day_uk.csv', header=True, index=True)
-```
-
-```python
-ukd = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), ['deaths', 'deaths_m7']].droplevel(1)
-ax = ukd.deaths.plot.bar(figsize=(12, 8))
-ukd.deaths_m7.plot.line(ax=ax, color='red')
-# ax = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), 'deaths_m7'].plot.line(figsize=(12, 8), color='red')
-# ax = data_since_threshold.replace([np.inf, -np.inf], np.nan).loc[(slice(None), ['UK']), 'deaths'].plot.bar(ax=ax)
-ax.set_xticks(range(0, 120, 20))
-```
-
-```python
-np.arange(0, 130, 20)
-```
-
-```python
-data_by_date.loc['UK']
-```
-
-```python
-data_by_date.loc['UK'].plot(x='deaths_culm', y='deaths', logx=True, logy=True)
-```
-
-```python
-data_by_date.loc['UK'].plot(x='cases_culm', y='cases')
-```
-
-```python
-ukdbd = data_by_date.loc['UK'].copy()
-ukdbd['deaths_m7'] = ukdbd.deaths.transform(lambda x: x.rolling(7, 1).mean())
-ukdbd['cases_m7'] = ukdbd.cases.transform(lambda x: x.rolling(7, 1).mean())
-ukdbd
-```
-
-```python
-ukdbd.plot(x='deaths_culm', y='deaths_m7', logx=True, logy=True)
-```
-
-```python
-fig, ax = plt.subplots(figsize=(12, 8))
-xmax = 10
-for c in COUNTRIES_CORE:
-    if data_since_threshold.loc[(slice(None), c), 'deaths_culm'].max() > xmax:
-        xmax = data_since_threshold.loc[(slice(None), c), 'deaths_culm'].max()
-    data_since_threshold.loc[(slice(None), c), :].plot(x='deaths_culm', y='deaths_m7', logx=True, logy=True, xlim=(10, xmax * 1.1), label=c, ax=ax)
-```
-
-```python
-data_since_threshold.loc[(slice(None), 'UK'), 'deaths_culm'].max()
-```
-
-```python
-countries.continentExp.unique()
-```
-
-```python
-countries.loc['KW']
-```
-
-```python
-data_by_date.groupby(level=0)['deaths'].shift(-25)
-```
-
-```python
-offset_data = data_by_date.loc[:, ['cases']]
-offset_data['deaths'] = data_by_date.groupby(level=0)['deaths'].shift(-25)
-offset_data['cases_m7'] = offset_data.groupby(level=0)['cases'].transform(lambda x: x.rolling(7, 1).mean())
-offset_data['deaths_m7'] = offset_data['deaths'].dropna().groupby(level=0).transform(lambda x: x.rolling(7, 1).mean())
-offset_data['deaths_per_case'] = offset_data.deaths_m7 / offset_data.cases_m7
-offset_data
-```
-
-```python
-deaths_m7
-```
-
-```python
-offset_deaths_m7 = (offset_data.loc[COUNTRIES_ALL, ['deaths_m7']]
-             .unstack().sort_index().xs('deaths_m7', axis=1, drop_level=True)).T.sort_index()
-offset_deaths_m7
-```
-
-```python
-offset_deaths_m7['UK']
-```
-
-```python
-data_since_threshold.loc[(slice(None), 'UK'), :].tail()
-```
-
-```python
-countries.loc['PT']
-```
-
-```python
-ax = cases_m7.iloc[-50:][COUNTRIES_FRIENDS].plot(figsize=(15, 9), title="Cases per day, 7 day moving average", ylim=(-10, 1500))
-ax.set_xlabel(f"Days since {DEATH_COUNT_THRESHOLD} deaths")
-# uk_projection.deaths_m7.plot(ax=ax)
-for c in COUNTRIES_FRIENDS:
-    lvi = cases_m7[c].last_valid_index()
-    if c != 'ES':
-        ax.text(x = lvi + 1, y = cases_m7[c][lvi], s = f"{c}: {cases_m7[c][lvi]:.0f}")
-
-```
-
-```python
-ax = deaths_m7.iloc[-50:][COUNTRIES_FRIENDS].plot(figsize=(15, 9), title="Cases per day, 7 day moving average", ylim=(-10, 100))
-ax.set_xlabel(f"Days since {DEATH_COUNT_THRESHOLD} deaths")
-# uk_projection.deaths_m7.plot(ax=ax)
-for c in COUNTRIES_FRIENDS:
-    lvi = deaths_m7[c].last_valid_index()
-#     if c != 'ES':
-    ax.text(x = lvi + 1, y = deaths_m7[c][lvi], s = f"{c}: {deaths_m7[c][lvi]:.0f}")
-
-```
-
-```python
-
-```
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-<!DOCTYPE html>
-<html xmlns="http://www.w3.org/1999/xhtml" lang="" xml:lang="">
-<head>
-  <meta charset="utf-8" />
-  <meta name="generator" content="pandoc" />
-  <meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes" />
-  <meta name="author" content="Neil Smith" />
-  <title>Covid death data summary</title>
-  <style type="text/css">
-      code{white-space: pre-wrap;}
-      span.smallcaps{font-variant: small-caps;}
-      span.underline{text-decoration: underline;}
-      div.column{display: inline-block; vertical-align: top; width: 50%;}
-  </style>
-  <!--[if lt IE 9]>
-    <script src="//cdnjs.cloudflare.com/ajax/libs/html5shiv/3.7.3/html5shiv-printshiv.min.js"></script>
-  <![endif]-->
-</head>
-<body>
-<header>
-<h1 class="title">Covid death data summary</h1>
-<p class="author">Neil Smith</p>
-<p class="date">Created on 2020-08-19</p>
-</header>
-<blockquote>
-<p>Last UK data from 2020-08-19</p>
-</blockquote>
-<h2 id="headlines">Headlines</h2>
-<table>
-<thead>
-<tr class="header">
-<th style="text-align: left;"><a href=""></a></th>
-<th style="text-align: right;"></th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td style="text-align: left;">Deaths reported so far</td>
-<td style="text-align: right;">41381</td>
-</tr>
-<tr class="even">
-<td style="text-align: left;">Total Covid deaths to date (estimated)</td>
-<td style="text-align: right;">65583</td>
-</tr>
-<tr class="odd">
-<td style="text-align: left;">Projected total deaths up to 2020-09-13</td>
-<td style="text-align: right;">65981</td>
-</tr>
-</tbody>
-</table>
-<h2 id="total-deaths">Total deaths</h2>
-<p>Time based on days since 10 deaths</p>
-<figure>
-<img src="covid_deaths_total_linear.png" alt="Total deaths" /><figcaption>Total deaths</figcaption>
-</figure>
-<table>
-<thead>
-<tr class="header">
-<th style="text-align: left;">Country ID</th>
-<th style="text-align: left;">Country name</th>
-<th style="text-align: right;">Total deaths</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td style="text-align: left;">DE</td>
-<td style="text-align: left;">Germany</td>
-<td style="text-align: right;">9243</td>
-</tr>
-<tr class="even">
-<td style="text-align: left;">ES</td>
-<td style="text-align: left;">Spain</td>
-<td style="text-align: right;">28670</td>
-</tr>
-<tr class="odd">
-<td style="text-align: left;">FR</td>
-<td style="text-align: left;">France</td>
-<td style="text-align: right;">30451</td>
-</tr>
-<tr class="even">
-<td style="text-align: left;">IE</td>
-<td style="text-align: left;">Ireland</td>
-<td style="text-align: right;">1775</td>
-</tr>
-<tr class="odd">
-<td style="text-align: left;">IT</td>
-<td style="text-align: left;">Italy</td>
-<td style="text-align: right;">35405</td>
-</tr>
-<tr class="even">
-<td style="text-align: left;">UK</td>
-<td style="text-align: left;">United_Kingdom</td>
-<td style="text-align: right;">41381</td>
-</tr>
-</tbody>
-</table>
-<h2 id="all-causes-deaths-uk">All-causes deaths, UK</h2>
-<figure>
-<img src="deaths-radar.png" alt="All-causes deaths" /><figcaption>All-causes deaths</figcaption>
-</figure>
-<h3 id="excess-deaths">Excess deaths</h3>
-<p>From week ending 20 March 2020 until week ending 03 July 2020, there were approximately <strong>64734</strong> excess deaths, over the average for the previous five years.</p>
-<p>In that period, the UK reported 40532 Covid deaths. In the last three weeks for which excess deaths have been reported, the excess deaths have been 1.000 higher than the Covid-reported deaths.</p>
-<p>The UK has reported 41381 deaths so far. Using the scaling factor above (for Covid-19 deaths after the ONS figures), I infer that there have been <strong>65583</strong> total deaths so far.</p>
-<h2 id="deaths-per-day">Deaths per day</h2>
-<p>Based on a 7-day moving average</p>
-<figure>
-<img src="covid_deaths_per_day_7.png" alt="Deaths per day" /><figcaption>Deaths per day</figcaption>
-</figure>
-<h2 id="projected-deaths">Projected deaths</h2>
-<p>The UK’s daily deaths data is very similar to Italy’s. If I use the Italian data for the next 24 days (from 25 May 2020 onwards), the UK will report 41684 deaths on day 183 of the epidemic.</p>
-<p>Using the excess deaths scaling from above, that will translate into <strong>65981</strong> Covid deaths total.</p>
-<h2 id="deaths-doubling-times">Deaths doubling times</h2>
-<p>Based on a 7-day moving average</p>
-<figure>
-<img src="covid_doubling_times_7.png" alt="Deaths doubling times" /><figcaption>Deaths doubling times</figcaption>
-</figure>
-<h2 id="cases-per-day-and-lockdown-dates">Cases per day and lockdown dates</h2>
-<p>Based on a 7-day moving average</p>
-<figure>
-<img src="cases_per_day_with_lockdown.png" alt="Cases per day" /><figcaption>Cases per day</figcaption>
-</figure>
-<table>
-<thead>
-<tr class="header">
-<th style="text-align: left;">Country ID</th>
-<th style="text-align: left;">Country name</th>
-<th style="text-align: right;">Most recent daily cases</th>
-<th style="text-align: right;">Most recent daily deaths</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td style="text-align: left;">DE</td>
-<td style="text-align: left;">Germany</td>
-<td style="text-align: right;">1199</td>
-<td style="text-align: right;">5</td>
-</tr>
-<tr class="even">
-<td style="text-align: left;">ES</td>
-<td style="text-align: left;">Spain</td>
-<td style="text-align: right;">5369</td>
-<td style="text-align: right;">13</td>
-</tr>
-<tr class="odd">
-<td style="text-align: left;">FR</td>
-<td style="text-align: left;">France</td>
-<td style="text-align: right;">2442</td>
-<td style="text-align: right;">14</td>
-</tr>
-<tr class="even">
-<td style="text-align: left;">IE</td>
-<td style="text-align: left;">Ireland</td>
-<td style="text-align: right;">100</td>
-<td style="text-align: right;">0</td>
-</tr>
-<tr class="odd">
-<td style="text-align: left;">IT</td>
-<td style="text-align: left;">Italy</td>
-<td style="text-align: right;">486</td>
-<td style="text-align: right;">27</td>
-</tr>
-<tr class="even">
-<td style="text-align: left;">UK</td>
-<td style="text-align: left;">United_Kingdom</td>
-<td style="text-align: right;">1071</td>
-<td style="text-align: right;">10</td>
-</tr>
-</tbody>
-</table>
-<p>(Figures are 7-day averages)</p>
-<h1 id="data-sources">Data sources</h1>
-<blockquote>
-<p>Covid data from <a href="https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide">European Centre for Disease Prevention and Control</a></p>
-</blockquote>
-<blockquote>
-<p>Population data from:</p>
-</blockquote>
-<ul>
-<li><a href="https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/weeklyprovisionalfiguresondeathsregisteredinenglandandwales">Office of National Statistics</a> (Endland and Wales) Weeks start on a Saturday.</li>
-<li><a href="https://www.nisra.gov.uk/publications/weekly-deaths">Northern Ireland Statistics and Research Agency</a> (Northern Ireland). Weeks start on a Saturday. Note that the week numbers don’t match the England and Wales data.</li>
-<li><a href="https://www.nrscotland.gov.uk/statistics-and-data/statistics/statistics-by-theme/vital-events/general-publications/weekly-and-monthly-data-on-births-and-deaths/weekly-data-on-births-and-deaths">National Records of Scotland</a> (Scotland). Note that Scotland uses ISO8601 week numbers, which start on a Monday.</li>
-</ul>
-<blockquote>
-<p><a href="https://git.njae.me.uk/?p=covid19.git;a=tree">Source code available</a></p>
-</blockquote>
-</body>
-</html>
diff --git a/covid_summary.md b/covid_summary.md

index e0006c239ee4969e832284780441d3ae208a3e0f..914f3d809dc14107dafc31be9c297e6647dc47f1 100644 (file)
--- a/covid_summary.md
+++ b/covid_summary.md
@@ -1,83 +1,86 @@
  % Covid death data summary
  % Neil Smith
  % Covid death data summary
  % Neil Smith
-% Created on 2020-08-19
+% Created on 2021-02-10
  
  
-> Last UK data from 2020-08-19
+> Last UK data from 09 Feb 2021.  Last international data from 01 Feb 2021.
  
  
-## Headlines
+## Headlines (UK data)
  
  | []() | |
  |:---|---:|
  
  | []() | |
  |:---|---:|
-| Deaths reported so far | 41381 | 
-| Total Covid deaths to date (estimated) | 65583 |
-| Projected total deaths up to 2020-09-13 | 65981 | 
+| Deaths reported so far | 113872 | 
+| Deaths in last 30 days | 32419 | 
+| Cases in last 30 days  | 794103 | 
  
  
+## International comparison
  
  
-## Total deaths
-Time based on days since 10 deaths
+Based on weekly data. Last data from 01 Feb 2021
+
+### Total deaths
  
  ![Total deaths](covid_deaths_total_linear.png)
  
  | Country ID | Country name | Total deaths |
  |:-----------|:-------------|-------------:|
  
  ![Total deaths](covid_deaths_total_linear.png)
  
  | Country ID | Country name | Total deaths |
  |:-----------|:-------------|-------------:|
-| DE | Germany | 9243 |
-| ES | Spain | 28670 |
-| FR | France | 30451 |
-| IE | Ireland | 1775 |
-| IT | Italy | 35405 |
-| UK | United_Kingdom | 41381 |
+| BE | Belgium | 21135 |
+| DE | Germany | 57120 |
+| ES | Spain | 59081 |
+| FR | France | 76057 |
+| IE | Ireland | 3307 |
+| IT | Italy | 88516 |
+| UK | United_Kingdom | 106158 |
+
+### Deaths per week
  
  
+![Deaths per week](covid_deaths_per_week.png)
  
  
-## All-causes deaths, UK
+![Deaths per week, last 6 weeks](deaths_by_date_last_6_weeks.png)
  
  
-![All-causes deaths](deaths-radar.png)
+## UK data
  
  
-### Excess deaths
+### Total deaths
  
  
-From week ending 20 March 2020 until week ending 03 July 2020, there were approximately **64734** excess deaths, over the average for the previous five years.
+Deaths reported up to 09 Feb 2021: 113872
  
  
-In that period, the UK reported 40532 Covid deaths.
-In the last three weeks for which excess deaths have been reported, the excess deaths have been 1.000 higher than the Covid-reported deaths.
+![Total deaths](cases_and_deaths.png)
  
  
-The UK has reported 41381 deaths so far.
-Using the scaling factor above (for Covid-19 deaths after the ONS figures), I infer that there have been **65583** total deaths so far.
+![Cases and deaths in last 60 days](cases_and_deaths_last_60_days.png)
  
  
+![Deaths compared to past five years](deaths-radar-2021.png)
  
  
-## Deaths per day
+### Hospital care
  Based on a 7-day moving average
  
  Based on a 7-day moving average
  
-![Deaths per day](covid_deaths_per_day_7.png)
+![Cases, admissions, deaths](cases_admissions_deaths.png)
  
  
+Due to the large scale differences between the three measures, they are all normalised to show changes since 01 August 2020.
  
  
-## Projected deaths
-The UK's daily deaths data is very similar to Italy's.
-If I use the Italian data for the next 24 days (from 25 May 2020 onwards), the UK will report 41684 deaths on day 183 of the epidemic.
+People in hospital, and on mechanical ventilators
  
  
-Using the excess deaths scaling from above, that will translate into **65981** Covid deaths total.
+![People in hospital and on mechancial ventilators](people_in_hospital.png)
  
  
+### Testing effectiveness
  
  
-## Deaths doubling times
-Based on a 7-day moving average
+A question about testing is whether more detected cases is a result of more tests being done or is because the number of cases is increasing. One way of telling the differeence is by looking at the fraction of tests that are positive.
  
  
-![Deaths doubling times](covid_doubling_times_7.png)
+![Positive tests and cases](tests_and_cases.png)
  
  
+Numbers of positive tests and cases, 7-day moving average.
+Note the different y-axes
  
  
-## Cases per day and lockdown dates
-Based on a 7-day moving average
+![Fraction of tests with positive result](fraction_positive_tests.png)
+
+Fraction of tests with a positive result, both daily figures and 7-day moving average.
+
+
+![Tests against fraction positive, trajectory](fraction_positive_tests_vs_tests.png)
  
  
-![Cases per day](cases_per_day_with_lockdown.png)
+The trajectory of tests done vs fraction positive tests.
  
  
+Points higher indicate more tests; points to the right indicate more positive tests.More tests being done with the same infection prevelance will move the point up and to the left.
  
  
-| Country ID | Country name | Most recent daily cases | Most recent daily deaths |
-|:-----------|:-------------|------------------------:|-------------------------:|
-| DE | Germany | 1199 | 5 | 
-| ES | Spain | 5369 | 13 | 
-| FR | France | 2442 | 14 | 
-| IE | Ireland | 100 | 0 | 
-| IT | Italy | 486 | 27 | 
-| UK | United_Kingdom | 1071 | 10 | 
  
  
-(Figures are 7-day averages)
+![Tests against fraction positive, trajectory](tests_vs_fraction_positive_animation.png)
  
  # Data sources
  
  
  # Data sources
  
diff --git a/data_import.ipynb b/data_import.ipynb

new file mode 100644 (file)

index 0000000..31d7ef9
--- /dev/null
+++ b/data_import.ipynb
@@ -0,0 +1,2933 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "source": [
+    "Data from [European Centre for Disease Prevention and Control](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 314,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "from sqlalchemy.types import Integer, Text, String, DateTime, Date, Float\n",
+    "from sqlalchemy import create_engine"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 315,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "import itertools\n",
+    "import collections\n",
+    "import json\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "from scipy.stats import gmean\n",
+    "import datetime\n",
+    "\n",
+    "import matplotlib as mpl\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 316,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The sql extension is already loaded. To reload it, use:\n",
+      "  %reload_ext sql\n"
+     ]
+    }
+   ],
+   "source": [
+    "%load_ext sql"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 317,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 318,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Connected: covid@covid'"
+      ]
+     },
+     "execution_count": 318,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql $connection_string"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 319,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "eng = create_engine(connection_string)\n",
+    "engine = eng.execution_options(isolation_level=\"AUTOCOMMIT\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 320,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "DEATH_COUNT_THRESHOLD = 10\n",
+    "COUNTRIES_CORE = 'IT DE UK ES IE FR BE'.split()\n",
+    "COUNTRIES_NORDIC = 'SE NO DK FI UK'.split()\n",
+    "COUNTRIES_FRIENDS = 'IT UK ES BE SI MX'.split()\n",
+    "# COUNTRIES_FRIENDS = 'IT UK ES BE SI PT'.split()\n",
+    "\n",
+    "COUNTRIES_AMERICAS = ['AG', 'AR', 'AW', 'BS', 'BB', 'BZ', 'BM', 'BO', 'BR', 'VG', 'KY', # excluding Canada and USA\n",
+    "       'CL', 'CO', 'CR', 'CU', 'CW', 'DM', 'DO', 'EC', 'SV', 'GL', 'GD', 'GT',\n",
+    "       'GY', 'HT', 'HN', 'JM', 'MX', 'MS', 'NI', 'PA', 'PY', 'PE', 'PR', 'KN',\n",
+    "       'LC', 'VC', 'SX', 'SR', 'TT', 'TC', 'VI', 'UY', 'VE']\n",
+    "COUNTRIES_OF_INTEREST = list(set(COUNTRIES_CORE + COUNTRIES_FRIENDS))\n",
+    "COUNTRIES_ALL = list(set(COUNTRIES_CORE + COUNTRIES_FRIENDS + COUNTRIES_NORDIC + COUNTRIES_AMERICAS))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 321,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
+      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
+      "100  623k  100  623k    0     0   927k      0 --:--:-- --:--:-- --:--:--  925k\n"
+     ]
+    }
+   ],
+   "source": [
+    "!curl https://opendata.ecdc.europa.eu/covid19/casedistribution/csv/ > covid.csv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 322,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# First col is a date, treat geoId of NA as 'Namibia', not \"NA\" value\n",
+    "raw_data = pd.read_csv('covid.csv', \n",
+    "                       parse_dates=[0], dayfirst=True,\n",
+    "                       keep_default_na=False, na_values = [''],\n",
+    "#                        dtype = {'day': np.int64, \n",
+    "#                                 'month': np.int64, \n",
+    "#                                 'year': np.int64, \n",
+    "#                                 'cases': np.int64, \n",
+    "#                                 'deaths': np.int64, \n",
+    "#                                 'countriesAndTerritories': str, \n",
+    "#                                 'geoId': str, \n",
+    "#                                 'countryterritoryCode': str, \n",
+    "#                                 'popData2019': np.int64, \n",
+    "#                                 'continentExp': str, \n",
+    "#                                 }\n",
+    "                      )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 323,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "100050"
+      ]
+     },
+     "execution_count": 323,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data.size"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 324,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "raw_data.fillna(0, inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 325,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>dateRep</th>\n",
+       "      <th>year_week</th>\n",
+       "      <th>cases_weekly</th>\n",
+       "      <th>deaths_weekly</th>\n",
+       "      <th>countriesAndTerritories</th>\n",
+       "      <th>geoId</th>\n",
+       "      <th>countryterritoryCode</th>\n",
+       "      <th>popData2019</th>\n",
+       "      <th>continentExp</th>\n",
+       "      <th>notification_rate_per_100000_population_14-days</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2021-01-18</td>\n",
+       "      <td>2021-02</td>\n",
+       "      <td>557</td>\n",
+       "      <td>45</td>\n",
+       "      <td>Afghanistan</td>\n",
+       "      <td>AF</td>\n",
+       "      <td>AFG</td>\n",
+       "      <td>38041757.0</td>\n",
+       "      <td>Asia</td>\n",
+       "      <td>3.24</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2021-01-11</td>\n",
+       "      <td>2021-01</td>\n",
+       "      <td>675</td>\n",
+       "      <td>71</td>\n",
+       "      <td>Afghanistan</td>\n",
+       "      <td>AF</td>\n",
+       "      <td>AFG</td>\n",
+       "      <td>38041757.0</td>\n",
+       "      <td>Asia</td>\n",
+       "      <td>4.15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2021-01-04</td>\n",
+       "      <td>2020-53</td>\n",
+       "      <td>902</td>\n",
+       "      <td>60</td>\n",
+       "      <td>Afghanistan</td>\n",
+       "      <td>AF</td>\n",
+       "      <td>AFG</td>\n",
+       "      <td>38041757.0</td>\n",
+       "      <td>Asia</td>\n",
+       "      <td>7.61</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2020-12-28</td>\n",
+       "      <td>2020-52</td>\n",
+       "      <td>1994</td>\n",
+       "      <td>88</td>\n",
+       "      <td>Afghanistan</td>\n",
+       "      <td>AF</td>\n",
+       "      <td>AFG</td>\n",
+       "      <td>38041757.0</td>\n",
+       "      <td>Asia</td>\n",
+       "      <td>7.19</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2020-12-21</td>\n",
+       "      <td>2020-51</td>\n",
+       "      <td>740</td>\n",
+       "      <td>111</td>\n",
+       "      <td>Afghanistan</td>\n",
+       "      <td>AF</td>\n",
+       "      <td>AFG</td>\n",
+       "      <td>38041757.0</td>\n",
+       "      <td>Asia</td>\n",
+       "      <td>6.56</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     dateRep year_week  cases_weekly  deaths_weekly countriesAndTerritories  \\\n",
+       "0 2021-01-18   2021-02           557             45             Afghanistan   \n",
+       "1 2021-01-11   2021-01           675             71             Afghanistan   \n",
+       "2 2021-01-04   2020-53           902             60             Afghanistan   \n",
+       "3 2020-12-28   2020-52          1994             88             Afghanistan   \n",
+       "4 2020-12-21   2020-51           740            111             Afghanistan   \n",
+       "\n",
+       "  geoId countryterritoryCode  popData2019 continentExp  \\\n",
+       "0    AF                  AFG   38041757.0         Asia   \n",
+       "1    AF                  AFG   38041757.0         Asia   \n",
+       "2    AF                  AFG   38041757.0         Asia   \n",
+       "3    AF                  AFG   38041757.0         Asia   \n",
+       "4    AF                  AFG   38041757.0         Asia   \n",
+       "\n",
+       "   notification_rate_per_100000_population_14-days  \n",
+       "0                                             3.24  \n",
+       "1                                             4.15  \n",
+       "2                                             7.61  \n",
+       "3                                             7.19  \n",
+       "4                                             6.56  "
+      ]
+     },
+     "execution_count": 325,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 326,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "raw_data.rename(columns={'dateRep':'report_date', 'geoId': 'geo_id',\n",
+    "                        'countriesAndTerritories': 'country_name',\n",
+    "                        'countryterritoryCode': 'country_territory_code',\n",
+    "                        'popData2019': 'population_2019',\n",
+    "                        'continentExp': 'continent'}, inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 327,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['report_date', 'year_week', 'cases_weekly', 'deaths_weekly',\n",
+       "       'country_name', 'geo_id', 'country_territory_code', 'population_2019',\n",
+       "       'continent', 'notification_rate_per_100000_population_14-days'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 327,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 328,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "report_date                                        datetime64[ns]\n",
+       "year_week                                                  object\n",
+       "cases_weekly                                                int64\n",
+       "deaths_weekly                                               int64\n",
+       "country_name                                               object\n",
+       "geo_id                                                     object\n",
+       "country_territory_code                                     object\n",
+       "population_2019                                           float64\n",
+       "continent                                                  object\n",
+       "notification_rate_per_100000_population_14-days           float64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 328,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 329,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>report_date</th>\n",
+       "      <th>cases_weekly</th>\n",
+       "      <th>deaths_weekly</th>\n",
+       "      <th>geo_id</th>\n",
+       "      <th>notification_rate_per_100000_population_14-days</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2021-01-18</td>\n",
+       "      <td>557</td>\n",
+       "      <td>45</td>\n",
+       "      <td>AF</td>\n",
+       "      <td>3.24</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2021-01-11</td>\n",
+       "      <td>675</td>\n",
+       "      <td>71</td>\n",
+       "      <td>AF</td>\n",
+       "      <td>4.15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2021-01-04</td>\n",
+       "      <td>902</td>\n",
+       "      <td>60</td>\n",
+       "      <td>AF</td>\n",
+       "      <td>7.61</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2020-12-28</td>\n",
+       "      <td>1994</td>\n",
+       "      <td>88</td>\n",
+       "      <td>AF</td>\n",
+       "      <td>7.19</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2020-12-21</td>\n",
+       "      <td>740</td>\n",
+       "      <td>111</td>\n",
+       "      <td>AF</td>\n",
+       "      <td>6.56</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10000</th>\n",
+       "      <td>2020-04-20</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0</td>\n",
+       "      <td>ZW</td>\n",
+       "      <td>0.11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10001</th>\n",
+       "      <td>2020-04-13</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2</td>\n",
+       "      <td>ZW</td>\n",
+       "      <td>0.05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10002</th>\n",
+       "      <td>2020-04-06</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>ZW</td>\n",
+       "      <td>0.05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10003</th>\n",
+       "      <td>2020-03-30</td>\n",
+       "      <td>5</td>\n",
+       "      <td>1</td>\n",
+       "      <td>ZW</td>\n",
+       "      <td>0.05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10004</th>\n",
+       "      <td>2020-03-23</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>ZW</td>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>10005 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      report_date  cases_weekly  deaths_weekly geo_id  \\\n",
+       "0      2021-01-18           557             45     AF   \n",
+       "1      2021-01-11           675             71     AF   \n",
+       "2      2021-01-04           902             60     AF   \n",
+       "3      2020-12-28          1994             88     AF   \n",
+       "4      2020-12-21           740            111     AF   \n",
+       "...           ...           ...            ...    ...   \n",
+       "10000  2020-04-20            11              0     ZW   \n",
+       "10001  2020-04-13             5              2     ZW   \n",
+       "10002  2020-04-06             2              0     ZW   \n",
+       "10003  2020-03-30             5              1     ZW   \n",
+       "10004  2020-03-23             2              0     ZW   \n",
+       "\n",
+       "       notification_rate_per_100000_population_14-days  \n",
+       "0                                                 3.24  \n",
+       "1                                                 4.15  \n",
+       "2                                                 7.61  \n",
+       "3                                                 7.19  \n",
+       "4                                                 6.56  \n",
+       "...                                                ...  \n",
+       "10000                                             0.11  \n",
+       "10001                                             0.05  \n",
+       "10002                                             0.05  \n",
+       "10003                                             0.05  \n",
+       "10004                                             0.00  \n",
+       "\n",
+       "[10005 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 329,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data[['report_date', 'cases_weekly', 'deaths_weekly', 'geo_id', 'notification_rate_per_100000_population_14-days']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 330,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>country_name</th>\n",
+       "      <th>geo_id</th>\n",
+       "      <th>country_territory_code</th>\n",
+       "      <th>population_2019</th>\n",
+       "      <th>continent</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Afghanistan</td>\n",
+       "      <td>AF</td>\n",
+       "      <td>AFG</td>\n",
+       "      <td>38041757.0</td>\n",
+       "      <td>Asia</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Afghanistan</td>\n",
+       "      <td>AF</td>\n",
+       "      <td>AFG</td>\n",
+       "      <td>38041757.0</td>\n",
+       "      <td>Asia</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Afghanistan</td>\n",
+       "      <td>AF</td>\n",
+       "      <td>AFG</td>\n",
+       "      <td>38041757.0</td>\n",
+       "      <td>Asia</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Afghanistan</td>\n",
+       "      <td>AF</td>\n",
+       "      <td>AFG</td>\n",
+       "      <td>38041757.0</td>\n",
+       "      <td>Asia</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Afghanistan</td>\n",
+       "      <td>AF</td>\n",
+       "      <td>AFG</td>\n",
+       "      <td>38041757.0</td>\n",
+       "      <td>Asia</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10000</th>\n",
+       "      <td>Zimbabwe</td>\n",
+       "      <td>ZW</td>\n",
+       "      <td>ZWE</td>\n",
+       "      <td>14645473.0</td>\n",
+       "      <td>Africa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10001</th>\n",
+       "      <td>Zimbabwe</td>\n",
+       "      <td>ZW</td>\n",
+       "      <td>ZWE</td>\n",
+       "      <td>14645473.0</td>\n",
+       "      <td>Africa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10002</th>\n",
+       "      <td>Zimbabwe</td>\n",
+       "      <td>ZW</td>\n",
+       "      <td>ZWE</td>\n",
+       "      <td>14645473.0</td>\n",
+       "      <td>Africa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10003</th>\n",
+       "      <td>Zimbabwe</td>\n",
+       "      <td>ZW</td>\n",
+       "      <td>ZWE</td>\n",
+       "      <td>14645473.0</td>\n",
+       "      <td>Africa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10004</th>\n",
+       "      <td>Zimbabwe</td>\n",
+       "      <td>ZW</td>\n",
+       "      <td>ZWE</td>\n",
+       "      <td>14645473.0</td>\n",
+       "      <td>Africa</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>10005 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      country_name geo_id country_territory_code  population_2019 continent\n",
+       "0      Afghanistan     AF                    AFG       38041757.0      Asia\n",
+       "1      Afghanistan     AF                    AFG       38041757.0      Asia\n",
+       "2      Afghanistan     AF                    AFG       38041757.0      Asia\n",
+       "3      Afghanistan     AF                    AFG       38041757.0      Asia\n",
+       "4      Afghanistan     AF                    AFG       38041757.0      Asia\n",
+       "...            ...    ...                    ...              ...       ...\n",
+       "10000     Zimbabwe     ZW                    ZWE       14645473.0    Africa\n",
+       "10001     Zimbabwe     ZW                    ZWE       14645473.0    Africa\n",
+       "10002     Zimbabwe     ZW                    ZWE       14645473.0    Africa\n",
+       "10003     Zimbabwe     ZW                    ZWE       14645473.0    Africa\n",
+       "10004     Zimbabwe     ZW                    ZWE       14645473.0    Africa\n",
+       "\n",
+       "[10005 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 330,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data[['country_name', 'geo_id', 'country_territory_code',\n",
+    "       'population_2019', 'continent']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 331,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "raw_data[['report_date', 'cases_weekly', 'deaths_weekly', 'geo_id', 'notification_rate_per_100000_population_14-days']].to_sql(\n",
+    "    'weekly_cases',\n",
+    "    engine,\n",
+    "    if_exists='replace',\n",
+    "    index=False,\n",
+    "    chunksize=500,\n",
+    "    dtype={\n",
+    "        \"report_date\": Date,\n",
+    "        \"cases_weekly\": Integer,\n",
+    "        \"deaths_weekly\": Integer,\n",
+    "        \"geo_id\": String,\n",
+    "        \"notification_rate_per_100000_population_14-days\": Float\n",
+    "    }\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 332,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "raw_data[['country_name', 'geo_id', 'country_territory_code',\n",
+    "       'population_2019', 'continent']].drop_duplicates().to_sql(\n",
+    "    'countries',\n",
+    "    engine,\n",
+    "    if_exists='replace',\n",
+    "    index=False,\n",
+    "    chunksize=500,\n",
+    "    dtype={\n",
+    "        \"country_name\": Text,\n",
+    "        \"geo_id\": String,\n",
+    "        \"country_territory_code\": String,\n",
+    "        \"population_2019\": Integer,\n",
+    "        \"continent\": Text\n",
+    "    }\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 333,
+   "metadata": {
+    "Collapsed": "false",
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "# %sql select geo_id from weekly_cases limit 10"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 334,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# %%sql alter table weekly_cases add primary key (geo_id, report_date);\n",
+    "# alter table countries add primary key (geo_id);\n",
+    "# alter table weekly_cases add foreign key (geo_id) references countries(geo_id);\n",
+    "# alter table weekly_cases add culm_cases integer;\n",
+    "# alter table weekly_cases add culm_deaths integer;"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 335,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "with engine.connect() as connection:\n",
+    "    connection.execute('alter table weekly_cases add primary key (geo_id, report_date)')\n",
+    "    connection.execute('alter table countries add primary key (geo_id);')\n",
+    "    connection.execute('alter table weekly_cases add foreign key (geo_id) references countries(geo_id);')\n",
+    "    connection.execute('alter table weekly_cases add culm_cases integer;')\n",
+    "    connection.execute('alter table weekly_cases add culm_deaths integer;')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 336,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# %sql select report_date, cases_weekly, country_name from weekly_cases join countries using (geo_id) order by report_date desc limit 10"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 337,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# %sql select report_date, cases_weekly, country_name from weekly_cases join countries on weekly_cases.geo_id = countries.geo_id order by report_date desc limit 10"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 338,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "10 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>report_date</th>\n",
+       "            <th>cases_weekly</th>\n",
+       "            <th>deaths_weekly</th>\n",
+       "            <th>geo_id</th>\n",
+       "            <th>notification_rate_per_100000_population_14-days</th>\n",
+       "            <th>culm_cases</th>\n",
+       "            <th>culm_deaths</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2021-01-18</td>\n",
+       "            <td>557</td>\n",
+       "            <td>45</td>\n",
+       "            <td>AF</td>\n",
+       "            <td>3.24</td>\n",
+       "            <td>None</td>\n",
+       "            <td>None</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-11</td>\n",
+       "            <td>675</td>\n",
+       "            <td>71</td>\n",
+       "            <td>AF</td>\n",
+       "            <td>4.15</td>\n",
+       "            <td>None</td>\n",
+       "            <td>None</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-04</td>\n",
+       "            <td>902</td>\n",
+       "            <td>60</td>\n",
+       "            <td>AF</td>\n",
+       "            <td>7.61</td>\n",
+       "            <td>None</td>\n",
+       "            <td>None</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020-12-28</td>\n",
+       "            <td>1994</td>\n",
+       "            <td>88</td>\n",
+       "            <td>AF</td>\n",
+       "            <td>7.19</td>\n",
+       "            <td>None</td>\n",
+       "            <td>None</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020-12-21</td>\n",
+       "            <td>740</td>\n",
+       "            <td>111</td>\n",
+       "            <td>AF</td>\n",
+       "            <td>6.56</td>\n",
+       "            <td>None</td>\n",
+       "            <td>None</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020-12-14</td>\n",
+       "            <td>1757</td>\n",
+       "            <td>71</td>\n",
+       "            <td>AF</td>\n",
+       "            <td>9.01</td>\n",
+       "            <td>None</td>\n",
+       "            <td>None</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020-12-07</td>\n",
+       "            <td>1672</td>\n",
+       "            <td>137</td>\n",
+       "            <td>AF</td>\n",
+       "            <td>7.22</td>\n",
+       "            <td>None</td>\n",
+       "            <td>None</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020-11-30</td>\n",
+       "            <td>1073</td>\n",
+       "            <td>68</td>\n",
+       "            <td>AF</td>\n",
+       "            <td>6.42</td>\n",
+       "            <td>None</td>\n",
+       "            <td>None</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020-11-23</td>\n",
+       "            <td>1368</td>\n",
+       "            <td>69</td>\n",
+       "            <td>AF</td>\n",
+       "            <td>6.66</td>\n",
+       "            <td>None</td>\n",
+       "            <td>None</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020-11-16</td>\n",
+       "            <td>1164</td>\n",
+       "            <td>61</td>\n",
+       "            <td>AF</td>\n",
+       "            <td>4.65</td>\n",
+       "            <td>None</td>\n",
+       "            <td>None</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(datetime.date(2021, 1, 18), 557, 45, 'AF', 3.24, None, None),\n",
+       " (datetime.date(2021, 1, 11), 675, 71, 'AF', 4.15, None, None),\n",
+       " (datetime.date(2021, 1, 4), 902, 60, 'AF', 7.61, None, None),\n",
+       " (datetime.date(2020, 12, 28), 1994, 88, 'AF', 7.19, None, None),\n",
+       " (datetime.date(2020, 12, 21), 740, 111, 'AF', 6.56, None, None),\n",
+       " (datetime.date(2020, 12, 14), 1757, 71, 'AF', 9.01, None, None),\n",
+       " (datetime.date(2020, 12, 7), 1672, 137, 'AF', 7.22, None, None),\n",
+       " (datetime.date(2020, 11, 30), 1073, 68, 'AF', 6.42, None, None),\n",
+       " (datetime.date(2020, 11, 23), 1368, 69, 'AF', 6.66, None, None),\n",
+       " (datetime.date(2020, 11, 16), 1164, 61, 'AF', 4.65, None, None)]"
+      ]
+     },
+     "execution_count": 338,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select * from weekly_cases limit 10"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 339,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# %%sql\n",
+    "# with culm as \n",
+    "#     (select report_date, geo_id,\n",
+    "#         sum(cases_weekly) over (partition by geo_id \n",
+    "#                                 order by report_date) as culm_data\n",
+    "#      from weekly_cases\n",
+    "#     )\n",
+    "# update weekly_cases\n",
+    "#     set culm_cases = culm_data\n",
+    "#     from culm\n",
+    "#     where weekly_cases.report_date = culm.report_date and\n",
+    "#           weekly_cases.geo_id = culm.geo_id"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 340,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "query_string = '''with culm as \n",
+    "    (select report_date, geo_id,\n",
+    "        sum(cases_weekly) over (partition by geo_id \n",
+    "                                order by report_date) as culm_data\n",
+    "     from weekly_cases\n",
+    "    )\n",
+    "update weekly_cases\n",
+    "    set culm_cases = culm_data\n",
+    "    from culm\n",
+    "    where weekly_cases.report_date = culm.report_date and\n",
+    "          weekly_cases.geo_id = culm.geo_id'''\n",
+    "with engine.connect() as connection:\n",
+    "    connection.execute(query_string)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 341,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# %%sql\n",
+    "# with culm as \n",
+    "#     (select report_date, geo_id,\n",
+    "#         sum(deaths_weekly) over (partition by geo_id \n",
+    "#                                 order by report_date) as culm_data\n",
+    "#      from weekly_cases\n",
+    "#     )\n",
+    "# update weekly_cases\n",
+    "#     set culm_deaths = culm_data\n",
+    "#     from culm\n",
+    "#     where weekly_cases.report_date = culm.report_date and\n",
+    "#           weekly_cases.geo_id = culm.geo_id"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 342,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "query_string = '''with culm as \n",
+    "    (select report_date, geo_id,\n",
+    "        sum(deaths_weekly) over (partition by geo_id \n",
+    "                                order by report_date) as culm_data\n",
+    "     from weekly_cases\n",
+    "    )\n",
+    "update weekly_cases\n",
+    "    set culm_deaths = culm_data\n",
+    "    from culm\n",
+    "    where weekly_cases.report_date = culm.report_date and\n",
+    "          weekly_cases.geo_id = culm.geo_id'''\n",
+    "with engine.connect() as connection:\n",
+    "    connection.execute(query_string)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 343,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
+      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
+      "100 26053  100 26053    0     0  54277      0 --:--:-- --:--:-- --:--:-- 54277\n"
+     ]
+    }
+   ],
+   "source": [
+    "uk_query_string = (\n",
+    "\"https://api.coronavirus.data.gov.uk/v2/data?areaType=overview&\"\n",
+    "\"metric=covidOccupiedMVBeds&\"\n",
+    "\"metric=newAdmissions&\"\n",
+    "\"metric=newCasesBySpecimenDate&\"\n",
+    "\"metric=hospitalCases&\"\n",
+    "\"metric=newDeaths28DaysByPublishDate&\"\n",
+    "\"format=csv\"\n",
+    ")\n",
+    "\n",
+    "!curl \"$uk_query_string\" > uk_data.csv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 344,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
+      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
+      "100 20223  100 20223    0     0  78688      0 --:--:-- --:--:-- --:--:-- 78383\n"
+     ]
+    }
+   ],
+   "source": [
+    "test_query_string = (\n",
+    "\"https://api.coronavirus.data.gov.uk/v2/data?areaType=overview&\"\n",
+    "\"metric=newPCRTestsByPublishDate&\"\n",
+    "\"metric=newTestsByPublishDate&\"\n",
+    "\"metric=newPillarOneTwoTestsByPublishDate&\"\n",
+    "\"format=csv\"\n",
+    ")\n",
+    "!curl \"$test_query_string\" > test_data.csv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 345,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# hospital_query_string = (\n",
+    "# \"https://api.coronavirus.data.gov.uk/v2/data?areaType=overview&\"\n",
+    "# \"metric=newAdmissions&\"\n",
+    "# \"format=csv\"\n",
+    "# )\n",
+    "# !curl \"$hospital_query_string\" > hospital_admissions.csv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 346,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# hospital_query_string = (\n",
+    "# \"https://api.coronavirus.data.gov.uk/v1/data?\"\n",
+    "# \"filters=areaName=United%2520Kingdom;areaType=overview&\"\n",
+    "# \"structure=%7B%22date%22:%22date%22,%22areaName%22:%22areaName%22,%22areaType%22:%22areaType%22,\"\n",
+    "# \"%22newAdmissions%22:%22newAdmissions%22,%22cumAdmissions%22:%22cumAdmissions%22%7D&format=csv\"\n",
+    "# )\n",
+    "    \n",
+    "# !curl \"$hospital_query_string\" | gunzip > hospital_admissions.csv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 347,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date</th>\n",
+       "      <th>areaType</th>\n",
+       "      <th>areaCode</th>\n",
+       "      <th>areaName</th>\n",
+       "      <th>covidOccupiedMVBeds</th>\n",
+       "      <th>newAdmissions</th>\n",
+       "      <th>newCasesBySpecimenDate</th>\n",
+       "      <th>hospitalCases</th>\n",
+       "      <th>newDeaths28DaysByPublishDate</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2021-01-26</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1631</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2021-01-25</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>4032.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4482.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>592</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2021-01-24</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>4077.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14266.0</td>\n",
+       "      <td>37561.0</td>\n",
+       "      <td>610</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2021-01-23</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>4066.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>20495.0</td>\n",
+       "      <td>37266.0</td>\n",
+       "      <td>1348</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2021-01-22</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>4076.0</td>\n",
+       "      <td>3341.0</td>\n",
+       "      <td>29094.0</td>\n",
+       "      <td>38144.0</td>\n",
+       "      <td>1401</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>385</th>\n",
+       "      <td>2020-01-06</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>386</th>\n",
+       "      <td>2020-01-05</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>387</th>\n",
+       "      <td>2020-01-04</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>388</th>\n",
+       "      <td>2020-01-03</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>389</th>\n",
+       "      <td>2020-06-14</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>393.0</td>\n",
+       "      <td>364.0</td>\n",
+       "      <td>821.0</td>\n",
+       "      <td>4907.0</td>\n",
+       "      <td>27</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>390 rows × 9 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          date  areaType   areaCode        areaName  covidOccupiedMVBeds  \\\n",
+       "0   2021-01-26  overview  K02000001  United Kingdom                  NaN   \n",
+       "1   2021-01-25  overview  K02000001  United Kingdom               4032.0   \n",
+       "2   2021-01-24  overview  K02000001  United Kingdom               4077.0   \n",
+       "3   2021-01-23  overview  K02000001  United Kingdom               4066.0   \n",
+       "4   2021-01-22  overview  K02000001  United Kingdom               4076.0   \n",
+       "..         ...       ...        ...             ...                  ...   \n",
+       "385 2020-01-06  overview  K02000001  United Kingdom                  NaN   \n",
+       "386 2020-01-05  overview  K02000001  United Kingdom                  NaN   \n",
+       "387 2020-01-04  overview  K02000001  United Kingdom                  NaN   \n",
+       "388 2020-01-03  overview  K02000001  United Kingdom                  NaN   \n",
+       "389 2020-06-14  overview  K02000001  United Kingdom                393.0   \n",
+       "\n",
+       "     newAdmissions  newCasesBySpecimenDate  hospitalCases  \\\n",
+       "0              NaN                     NaN            NaN   \n",
+       "1              NaN                  4482.0            NaN   \n",
+       "2              NaN                 14266.0        37561.0   \n",
+       "3              NaN                 20495.0        37266.0   \n",
+       "4           3341.0                 29094.0        38144.0   \n",
+       "..             ...                     ...            ...   \n",
+       "385            NaN                     NaN            NaN   \n",
+       "386            NaN                     NaN            NaN   \n",
+       "387            NaN                     NaN            NaN   \n",
+       "388            NaN                     NaN            NaN   \n",
+       "389          364.0                   821.0         4907.0   \n",
+       "\n",
+       "     newDeaths28DaysByPublishDate  \n",
+       "0                            1631  \n",
+       "1                             592  \n",
+       "2                             610  \n",
+       "3                            1348  \n",
+       "4                            1401  \n",
+       "..                            ...  \n",
+       "385                             0  \n",
+       "386                             0  \n",
+       "387                             0  \n",
+       "388                             0  \n",
+       "389                            27  \n",
+       "\n",
+       "[390 rows x 9 columns]"
+      ]
+     },
+     "execution_count": 347,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "uk_data = pd.read_csv('uk_data.csv', \n",
+    "                       parse_dates=[0], dayfirst=True)\n",
+    "uk_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 348,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date</th>\n",
+       "      <th>areaType</th>\n",
+       "      <th>areaCode</th>\n",
+       "      <th>areaName</th>\n",
+       "      <th>newPCRTestsByPublishDate</th>\n",
+       "      <th>newTestsByPublishDate</th>\n",
+       "      <th>newPillarOneTwoTestsByPublishDate</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2021-01-25</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>196510.0</td>\n",
+       "      <td>546734</td>\n",
+       "      <td>531104</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2021-01-24</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>262111.0</td>\n",
+       "      <td>412775</td>\n",
+       "      <td>394479</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2021-01-23</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>389209.0</td>\n",
+       "      <td>486425</td>\n",
+       "      <td>465231</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2021-01-22</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>401075.0</td>\n",
+       "      <td>631901</td>\n",
+       "      <td>608829</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2021-01-21</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>439408.0</td>\n",
+       "      <td>668989</td>\n",
+       "      <td>644537</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>296</th>\n",
+       "      <td>2020-04-03</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14629</td>\n",
+       "      <td>14293</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>297</th>\n",
+       "      <td>2020-04-02</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13623</td>\n",
+       "      <td>13457</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>298</th>\n",
+       "      <td>2020-04-01</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11947</td>\n",
+       "      <td>11924</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>299</th>\n",
+       "      <td>2020-03-31</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11896</td>\n",
+       "      <td>11896</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>300</th>\n",
+       "      <td>2020-06-14</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>69529.0</td>\n",
+       "      <td>83965</td>\n",
+       "      <td>66688</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>301 rows × 7 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          date  areaType   areaCode        areaName  newPCRTestsByPublishDate  \\\n",
+       "0   2021-01-25  overview  K02000001  United Kingdom                  196510.0   \n",
+       "1   2021-01-24  overview  K02000001  United Kingdom                  262111.0   \n",
+       "2   2021-01-23  overview  K02000001  United Kingdom                  389209.0   \n",
+       "3   2021-01-22  overview  K02000001  United Kingdom                  401075.0   \n",
+       "4   2021-01-21  overview  K02000001  United Kingdom                  439408.0   \n",
+       "..         ...       ...        ...             ...                       ...   \n",
+       "296 2020-04-03  overview  K02000001  United Kingdom                       NaN   \n",
+       "297 2020-04-02  overview  K02000001  United Kingdom                       NaN   \n",
+       "298 2020-04-01  overview  K02000001  United Kingdom                       NaN   \n",
+       "299 2020-03-31  overview  K02000001  United Kingdom                       NaN   \n",
+       "300 2020-06-14  overview  K02000001  United Kingdom                   69529.0   \n",
+       "\n",
+       "     newTestsByPublishDate  newPillarOneTwoTestsByPublishDate  \n",
+       "0                   546734                             531104  \n",
+       "1                   412775                             394479  \n",
+       "2                   486425                             465231  \n",
+       "3                   631901                             608829  \n",
+       "4                   668989                             644537  \n",
+       "..                     ...                                ...  \n",
+       "296                  14629                              14293  \n",
+       "297                  13623                              13457  \n",
+       "298                  11947                              11924  \n",
+       "299                  11896                              11896  \n",
+       "300                  83965                              66688  \n",
+       "\n",
+       "[301 rows x 7 columns]"
+      ]
+     },
+     "execution_count": 348,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "test_data = pd.read_csv('test_data.csv', \n",
+    "                       parse_dates=[0], dayfirst=True)\n",
+    "test_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 349,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['date', 'areaType', 'areaCode', 'areaName', 'newPCRTestsByPublishDate',\n",
+       "       'newTestsByPublishDate', 'newPillarOneTwoTestsByPublishDate'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 349,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "test_data.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 350,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "uk_data = uk_data.merge(test_data[['date', 'newPCRTestsByPublishDate',\n",
+    "       'newTestsByPublishDate', 'newPillarOneTwoTestsByPublishDate']], how='outer', on='date')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 351,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['date', 'areaType', 'areaCode', 'areaName', 'covidOccupiedMVBeds',\n",
+       "       'newAdmissions', 'newCasesBySpecimenDate', 'hospitalCases',\n",
+       "       'newDeaths28DaysByPublishDate', 'newPCRTestsByPublishDate',\n",
+       "       'newTestsByPublishDate', 'newPillarOneTwoTestsByPublishDate'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 351,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "uk_data.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 352,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "uk_data.rename(\n",
+    "    columns={\n",
+    "        'covidOccupiedMVBeds': 'ventilator_beds',\n",
+    "        'newCasesBySpecimenDate': 'new_cases',\n",
+    "        'hospitalCases': 'hospital_cases', \n",
+    "        'newDeaths28DaysByPublishDate': 'new_deaths',\n",
+    "        'newAdmissions': 'new_admissions',\n",
+    "        'newPCRTestsByPublishDate': 'new_pcr_tests',\n",
+    "        'newTestsByPublishDate': 'new_tests',\n",
+    "        'newPillarOneTwoTestsByPublishDate': 'new_pillar_1_2_tests'\n",
+    "    }, inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 353,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "date                    datetime64[ns]\n",
+       "areaType                        object\n",
+       "areaCode                        object\n",
+       "areaName                        object\n",
+       "ventilator_beds                float64\n",
+       "new_admissions                 float64\n",
+       "new_cases                      float64\n",
+       "hospital_cases                 float64\n",
+       "new_deaths                       int64\n",
+       "new_pcr_tests                  float64\n",
+       "new_tests                      float64\n",
+       "new_pillar_1_2_tests           float64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 353,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "uk_data.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 354,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['date', 'areaType', 'areaCode', 'areaName', 'ventilator_beds',\n",
+       "       'new_admissions', 'new_cases', 'hospital_cases', 'new_deaths',\n",
+       "       'new_pcr_tests', 'new_tests', 'new_pillar_1_2_tests'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 354,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    " uk_data.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 355,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "uk_data[['date', \n",
+    "         'hospital_cases', 'ventilator_beds',\n",
+    "         'new_cases', 'new_deaths', \n",
+    "         'hospital_cases', 'new_admissions',\n",
+    "         'new_pcr_tests', 'new_tests', 'new_pillar_1_2_tests'\n",
+    "        ]].to_sql(\n",
+    "    'uk_data',\n",
+    "    engine,\n",
+    "    if_exists='replace',\n",
+    "    index=False,\n",
+    "    chunksize=500,\n",
+    "    dtype={\n",
+    "        \"date\": Date,\n",
+    "        \"hospital_cases\": Integer,\n",
+    "        \"ventilator_beds\": Integer,\n",
+    "        \"new_cases\": Integer,\n",
+    "        \"hospital_cases\": Integer,\n",
+    "        \"new_deaths\": Integer,\n",
+    "        \"new_admissions\": Integer,\n",
+    "        'new_pcr_tests': Integer, \n",
+    "        'new_tests': Integer, \n",
+    "        'new_pillar_1_2_tests': Integer\n",
+    "    }\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 356,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# %sql select * from uk_data order by date desc limit 10"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 424,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "query_string = '''drop table if exists uk_data_7;\n",
+    "create table uk_data_7 \n",
+    "(date date primary key,\n",
+    " hospital_cases real,\n",
+    " ventilator_beds real,\n",
+    " new_cases real,\n",
+    " new_deaths real,\n",
+    " new_admissions real,\n",
+    " new_pcr_tests real,\n",
+    " new_tests real,\n",
+    " new_pillar_1_2_tests real\n",
+    ");'''\n",
+    "\n",
+    "with engine.connect() as connection:\n",
+    "    connection.execute(query_string)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 425,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "update_string = '''with ownd as (\n",
+    "    select date,\n",
+    "        avg(hospital_cases) over wnd as w_hospital_cases,\n",
+    "        avg(ventilator_beds) over wnd as w_ventilator_beds,\n",
+    "        avg(new_cases) over wnd as w_new_cases,\n",
+    "        avg(new_deaths) over wnd as w_new_deaths,\n",
+    "        avg(new_admissions) over wnd as w_new_admissions,\n",
+    "        avg(new_pcr_tests) over wnd as w_new_pcr_tests,\n",
+    "        avg(new_tests) over wnd as w_new_tests,\n",
+    "        avg(new_pillar_1_2_tests) over wnd as w_new_pillar_1_2_tests,\n",
+    "        count(*) over wnd as w_size\n",
+    "    from uk_data\n",
+    "    window wnd as (\n",
+    "        order by uk_data.date\n",
+    "        rows between 3 preceding and 3 following\n",
+    "    )\n",
+    ")\n",
+    "insert into uk_data_7(date, \n",
+    "    hospital_cases, \n",
+    "    ventilator_beds, \n",
+    "    new_cases,\n",
+    "    new_deaths,\n",
+    "    new_admissions, \n",
+    "    new_pcr_tests, \n",
+    "    new_tests, \n",
+    "    new_pillar_1_2_tests\n",
+    "    )\n",
+    "(select date,\n",
+    "        w_hospital_cases,\n",
+    "        w_ventilator_beds,\n",
+    "        w_new_cases,\n",
+    "        w_new_deaths,\n",
+    "        w_new_admissions,\n",
+    "        w_new_pcr_tests,\n",
+    "        w_new_tests,\n",
+    "        w_new_pillar_1_2_tests\n",
+    "    from ownd\n",
+    "    where w_size = 7\n",
+    ")'''\n",
+    "with engine.connect() as connection:\n",
+    "    connection.execute(update_string)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 398,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# %%sql insert into uk_data_7(date, ventilator_beds, new_cases, hospital_cases, new_deaths, new_admissions)\n",
+    "# values (\n",
+    "#     select date, \n",
+    "#     avg(ventilator_beds) over (order by date rows between 6 preceding and current row)\n",
+    "#     from uk_data\n",
+    "# )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 399,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# query_string = '''insert into uk_data_7(date, hospital_cases)\n",
+    "#     select uk_data.date, \n",
+    "#         avg(uk_data.hospital_cases) over (order by uk_data.date rows between 3 preceding and 3 following) as hospital_cases\n",
+    "#     from uk_data'''\n",
+    "# with engine.connect() as connection:\n",
+    "#     connection.execute(query_string)   "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 360,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# %%sql \n",
+    "# with m7 as \n",
+    "#     (select uk_data.date as date7, \n",
+    "#         avg(uk_data.ventilator_beds) over (order by uk_data.date rows between 6 preceding and current row) as nc7\n",
+    "#      from uk_data\n",
+    "#     )\n",
+    "# update uk_data_7\n",
+    "#     set ventilator_beds = nc7\n",
+    "#     from m7\n",
+    "#     where uk_data_7.date = m7.date7"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 361,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "390 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[]"
+      ]
+     },
+     "execution_count": 361,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# %%sql\n",
+    "# with m7 as \n",
+    "#     (select uk_data.date as date7, \n",
+    "#         avg(uk_data.ventilator_beds) over (order by uk_data.date rows between 3 preceding and 3 following) as nc7\n",
+    "#      from uk_data\n",
+    "#     )\n",
+    "# update uk_data_7\n",
+    "#     set ventilator_beds = nc7\n",
+    "#     from m7\n",
+    "#     where uk_data_7.date = m7.date7"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 362,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "390 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[]"
+      ]
+     },
+     "execution_count": 362,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# %%sql\n",
+    "# with m7 as \n",
+    "#     (select uk_data.date as date7, \n",
+    "#         avg(uk_data.new_cases) over (order by uk_data.date rows between 3 preceding and 3 following) as nc7\n",
+    "#      from uk_data\n",
+    "#     )\n",
+    "# update uk_data_7\n",
+    "#     set new_cases = nc7\n",
+    "#     from m7\n",
+    "#     where uk_data_7.date = m7.date7"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 363,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "390 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[]"
+      ]
+     },
+     "execution_count": 363,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# %%sql\n",
+    "# with m7 as \n",
+    "#     (select uk_data.date as date7, \n",
+    "#         avg(uk_data.hospital_cases) over (order by uk_data.date rows between 3 preceding and 3 following) as d7\n",
+    "#      from uk_data\n",
+    "#     )\n",
+    "# update uk_data_7\n",
+    "#     set hospital_cases = d7\n",
+    "#     from m7\n",
+    "#     where uk_data_7.date = m7.date7"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 364,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "390 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[]"
+      ]
+     },
+     "execution_count": 364,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# %%sql\n",
+    "# with m7 as \n",
+    "#     (select uk_data.date as date7, \n",
+    "#         avg(uk_data.new_deaths) over (order by uk_data.date rows between 3 preceding and 3 following) as d7\n",
+    "#      from uk_data\n",
+    "#     )\n",
+    "# update uk_data_7\n",
+    "#     set new_deaths = d7\n",
+    "#     from m7\n",
+    "#     where uk_data_7.date = m7.date7"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 365,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "390 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[]"
+      ]
+     },
+     "execution_count": 365,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# %%sql\n",
+    "# with m7 as \n",
+    "#     (select uk_data.date as date7, \n",
+    "#         avg(uk_data.new_admissions) over (order by uk_data.date rows between 3 preceding and 3 following) as d7\n",
+    "#      from uk_data\n",
+    "#     )\n",
+    "# update uk_data_7\n",
+    "#     set new_admissions = d7\n",
+    "#     from m7\n",
+    "#     where uk_data_7.date = m7.date7"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 366,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "390 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[]"
+      ]
+     },
+     "execution_count": 366,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# %%sql\n",
+    "# with m7 as \n",
+    "#     (select uk_data.date as date7, \n",
+    "#         avg(uk_data.new_pcr_tests) over (order by uk_data.date rows between 3 preceding and 3 following) as d7\n",
+    "#      from uk_data\n",
+    "#     )\n",
+    "# update uk_data_7\n",
+    "#     set new_pcr_tests = d7\n",
+    "#     from m7\n",
+    "#     where uk_data_7.date = m7.date7"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 367,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "390 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[]"
+      ]
+     },
+     "execution_count": 367,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# %%sql\n",
+    "# with m7 as \n",
+    "#     (select uk_data.date as date7, \n",
+    "#         avg(uk_data.new_tests) over (order by uk_data.date rows between 3 preceding and 3 following) as d7\n",
+    "#      from uk_data\n",
+    "#     )\n",
+    "# update uk_data_7\n",
+    "#     set new_tests = d7\n",
+    "#     from m7\n",
+    "#     where uk_data_7.date = m7.date7"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 309,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# %%sql\n",
+    "# with m7 as \n",
+    "#     (select uk_data.date as date7, \n",
+    "#         avg(uk_data.new_pillar_1_2_tests) over (order by uk_data.date rows between 3 preceding and 3 following) as d7\n",
+    "#      from uk_data\n",
+    "#     )\n",
+    "# update uk_data_7\n",
+    "#     set new_pillar_1_2_tests = d7\n",
+    "#     from m7\n",
+    "#     where uk_data_7.date = m7.date7"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 310,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "0 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[]"
+      ]
+     },
+     "execution_count": 310,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# %%sql\n",
+    "# with wnd as\n",
+    "#     (   select date, \n",
+    "#              avg(new_pillar_1_2_tests)\n",
+    "#                 over (order by uk_data.date rows between 3 preceding and 3 following) as a_new_pillar_1_2_tests\n",
+    "#         from uk_data\n",
+    "#     )\n",
+    "# update uk_data_7\n",
+    "#     set new_pillar_1_2_tests = wnd.a_new_pillar_1_2_tests\n",
+    "#     from wnd\n",
+    "#     where uk_data_7.date = wnd.date\n",
+    "#     and (select count(*) from wnd) = 7"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 379,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "10 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>date</th>\n",
+       "            <th>new_pillar_1_2_tests</th>\n",
+       "            <th>a_new_pillar_1_2_tests</th>\n",
+       "            <th>a_count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2021-01-26</td>\n",
+       "            <td>None</td>\n",
+       "            <td>463604.666666666667</td>\n",
+       "            <td>3</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-25</td>\n",
+       "            <td>None</td>\n",
+       "            <td>499910.750000000000</td>\n",
+       "            <td>4</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-24</td>\n",
+       "            <td>None</td>\n",
+       "            <td>528836.000000000000</td>\n",
+       "            <td>5</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-23</td>\n",
+       "            <td>None</td>\n",
+       "            <td>543566.833333333333</td>\n",
+       "            <td>6</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-22</td>\n",
+       "            <td>None</td>\n",
+       "            <td>545780.285714285714</td>\n",
+       "            <td>7</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-21</td>\n",
+       "            <td>None</td>\n",
+       "            <td>546626.571428571429</td>\n",
+       "            <td>7</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-20</td>\n",
+       "            <td>None</td>\n",
+       "            <td>546806.285714285714</td>\n",
+       "            <td>7</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-19</td>\n",
+       "            <td>None</td>\n",
+       "            <td>547402.428571428571</td>\n",
+       "            <td>7</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-18</td>\n",
+       "            <td>None</td>\n",
+       "            <td>542617.857142857143</td>\n",
+       "            <td>7</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-17</td>\n",
+       "            <td>None</td>\n",
+       "            <td>545088.142857142857</td>\n",
+       "            <td>7</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(datetime.date(2021, 1, 26), None, Decimal('463604.666666666667'), 3),\n",
+       " (datetime.date(2021, 1, 25), None, Decimal('499910.750000000000'), 4),\n",
+       " (datetime.date(2021, 1, 24), None, Decimal('528836.000000000000'), 5),\n",
+       " (datetime.date(2021, 1, 23), None, Decimal('543566.833333333333'), 6),\n",
+       " (datetime.date(2021, 1, 22), None, Decimal('545780.285714285714'), 7),\n",
+       " (datetime.date(2021, 1, 21), None, Decimal('546626.571428571429'), 7),\n",
+       " (datetime.date(2021, 1, 20), None, Decimal('546806.285714285714'), 7),\n",
+       " (datetime.date(2021, 1, 19), None, Decimal('547402.428571428571'), 7),\n",
+       " (datetime.date(2021, 1, 18), None, Decimal('542617.857142857143'), 7),\n",
+       " (datetime.date(2021, 1, 17), None, Decimal('545088.142857142857'), 7)]"
+      ]
+     },
+     "execution_count": 379,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# %%sql\n",
+    "# with wnd as\n",
+    "#     (   select date, \n",
+    "#              avg(new_pillar_1_2_tests)\n",
+    "#                 over (order by uk_data.date rows between 3 preceding and 3 following) as a_new_pillar_1_2_tests,\n",
+    "#              count(new_pillar_1_2_tests)\n",
+    "#                 over (order by uk_data.date rows between 3 preceding and 3 following) as a_count\n",
+    "#         from uk_data\n",
+    "#     )\n",
+    "# select uk_data_7.date, new_pillar_1_2_tests, wnd.a_new_pillar_1_2_tests, wnd.a_count\n",
+    "#     from uk_data_7, wnd\n",
+    "#     where uk_data_7.date = wnd.date\n",
+    "#     order by uk_data_7.date desc limit 10\n",
+    "    \n",
+    "# select date, \n",
+    "#     count(*) over wnd as w_size\n",
+    "# from uk_data\n",
+    "# window wnd as (\n",
+    "#     order by uk_data.date\n",
+    "#     rows between 3 preceding and 3 following\n",
+    "# );"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 401,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# %%sql\n",
+    "# select date, \n",
+    "#     count(*) over wnd as w_size\n",
+    "# from uk_data\n",
+    "# window wnd as (\n",
+    "#     order by uk_data.date\n",
+    "#     rows between 3 preceding and 3 following\n",
+    "# )\n",
+    "# order by date desc limit 10"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 407,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "0 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[]"
+      ]
+     },
+     "execution_count": 407,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# %%sql\n",
+    "# with ownd as (\n",
+    "#     select date,\n",
+    "#         avg(hospital_cases) over wnd as w_hospital_cases,\n",
+    "#         avg(ventilator_beds) over wnd as w_ventilator_beds,\n",
+    "#         avg(new_cases) over wnd as w_new_cases,\n",
+    "#         avg(new_deaths) over wnd as w_new_deaths,\n",
+    "#         avg(new_admissions) over wnd as w_new_admissions,\n",
+    "#         avg(new_pcr_tests) over wnd as w_new_pcr_tests,\n",
+    "#         avg(new_tests) over wnd as w_new_tests,\n",
+    "#         avg(new_pillar_1_2_tests) over wnd as w_new_pillar_1_2_tests,\n",
+    "#         count(*) over wnd as w_size\n",
+    "#     from uk_data\n",
+    "#     window wnd as (\n",
+    "#         order by uk_data.date\n",
+    "#         rows between 3 preceding and 3 following\n",
+    "#     ))\n",
+    "# insert into uk_data_7(date, \n",
+    "#     hospital_cases, \n",
+    "#     ventilator_beds, \n",
+    "#     new_cases,\n",
+    "#     new_deaths,\n",
+    "#     new_admissions, \n",
+    "#     new_pcr_tests, \n",
+    "#     new_tests, \n",
+    "#     new_pillar_1_2_tests\n",
+    "#     )\n",
+    "# (select date,\n",
+    "#         avg(hospital_cases) over wnd as w_hospital_cases,\n",
+    "#         avg(ventilator_beds) over wnd as w_ventilator_beds,\n",
+    "#         avg(new_cases) over wnd as w_new_cases,\n",
+    "#         avg(new_deaths) over wnd as w_new_deaths,\n",
+    "#         avg(new_admissions) over wnd as w_new_admissions,\n",
+    "#         avg(new_pcr_tests) over wnd as w_new_pcr_tests,\n",
+    "#         avg(new_tests) over wnd as w_new_tests,\n",
+    "#         avg(new_pillar_1_2_tests) over wnd as w_new_pillar_1_2_tests,\n",
+    "#         count(*) over wnd as w_size\n",
+    "#     from uk_data\n",
+    "#     window wnd as (\n",
+    "#         order by uk_data.date\n",
+    "#         rows between 3 preceding and 3 following\n",
+    "#     )\n",
+    "# )\n",
+    "#     set date = ownd.date,\n",
+    "#         hospital_cases = w_hospital_cases,\n",
+    "#         ventilator_beds = w_ventilator_beds,\n",
+    "#         new_cases = w_new_cases,\n",
+    "#         new_deaths = w_new_deaths,\n",
+    "#         new_admissions = w_new_admissions,\n",
+    "#         new_pcr_tests = w_new_pcr_tests,\n",
+    "#         new_tests = w_new_tests,\n",
+    "#         new_pillar_1_2_tests = w_new_pillar_1_2_tests\n",
+    "#     from ownd\n",
+    "#     where w_size = 7"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 417,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "384 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[]"
+      ]
+     },
+     "execution_count": 417,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# %%sql\n",
+    "# with ownd as (\n",
+    "#     select date,\n",
+    "#         avg(hospital_cases) over wnd as w_hospital_cases,\n",
+    "#         avg(ventilator_beds) over wnd as w_ventilator_beds,\n",
+    "#         avg(new_cases) over wnd as w_new_cases,\n",
+    "#         avg(new_deaths) over wnd as w_new_deaths,\n",
+    "#         avg(new_admissions) over wnd as w_new_admissions,\n",
+    "#         avg(new_pcr_tests) over wnd as w_new_pcr_tests,\n",
+    "#         avg(new_tests) over wnd as w_new_tests,\n",
+    "#         avg(new_pillar_1_2_tests) over wnd as w_new_pillar_1_2_tests,\n",
+    "#         count(*) over wnd as w_size\n",
+    "#     from uk_data\n",
+    "#     window wnd as (\n",
+    "#         order by uk_data.date\n",
+    "#         rows between 3 preceding and 3 following\n",
+    "#     )\n",
+    "# )\n",
+    "# insert into uk_data_7(date, \n",
+    "#     hospital_cases, \n",
+    "#     ventilator_beds, \n",
+    "#     new_cases,\n",
+    "#     new_deaths,\n",
+    "#     new_admissions, \n",
+    "#     new_pcr_tests, \n",
+    "#     new_tests, \n",
+    "#     new_pillar_1_2_tests\n",
+    "#     )\n",
+    "# (select date,\n",
+    "#         w_hospital_cases,\n",
+    "#         w_ventilator_beds,\n",
+    "#         w_new_cases,\n",
+    "#         w_new_deaths,\n",
+    "#         w_new_admissions,\n",
+    "#         w_new_pcr_tests,\n",
+    "#         w_new_tests,\n",
+    "#         w_new_pillar_1_2_tests\n",
+    "#     from ownd\n",
+    "#     where w_size = 7\n",
+    "# )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 427,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "10 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>date</th>\n",
+       "            <th>hospital_cases</th>\n",
+       "            <th>ventilator_beds</th>\n",
+       "            <th>new_cases</th>\n",
+       "            <th>new_deaths</th>\n",
+       "            <th>new_admissions</th>\n",
+       "            <th>new_pcr_tests</th>\n",
+       "            <th>new_tests</th>\n",
+       "            <th>new_pillar_1_2_tests</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2021-01-23</td>\n",
+       "            <td>37915.6</td>\n",
+       "            <td>4027.3333</td>\n",
+       "            <td>22463.666</td>\n",
+       "            <td>1241.7142</td>\n",
+       "            <td>3651.6667</td>\n",
+       "            <td>353735.34</td>\n",
+       "            <td>565312.3</td>\n",
+       "            <td>543566.8</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-22</td>\n",
+       "            <td>38057.168</td>\n",
+       "            <td>4015.8572</td>\n",
+       "            <td>24870.428</td>\n",
+       "            <td>1238.7142</td>\n",
+       "            <td>3771.75</td>\n",
+       "            <td>354323.16</td>\n",
+       "            <td>567830.3</td>\n",
+       "            <td>545780.3</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-21</td>\n",
+       "            <td>38217.715</td>\n",
+       "            <td>3999.2856</td>\n",
+       "            <td>30620.428</td>\n",
+       "            <td>1239.7142</td>\n",
+       "            <td>3828.2</td>\n",
+       "            <td>363750.16</td>\n",
+       "            <td>569716.7</td>\n",
+       "            <td>546626.56</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-20</td>\n",
+       "            <td>38294.0</td>\n",
+       "            <td>3969.8572</td>\n",
+       "            <td>32707.428</td>\n",
+       "            <td>1248.4286</td>\n",
+       "            <td>3811.0</td>\n",
+       "            <td>372037.44</td>\n",
+       "            <td>570458.1</td>\n",
+       "            <td>546806.3</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-19</td>\n",
+       "            <td>38348.43</td>\n",
+       "            <td>3939.5715</td>\n",
+       "            <td>34143.285</td>\n",
+       "            <td>1240.8572</td>\n",
+       "            <td>3825.8572</td>\n",
+       "            <td>374771.16</td>\n",
+       "            <td>571336.56</td>\n",
+       "            <td>547402.44</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-18</td>\n",
+       "            <td>38338.145</td>\n",
+       "            <td>3898.5715</td>\n",
+       "            <td>35766.57</td>\n",
+       "            <td>1223.5714</td>\n",
+       "            <td>3872.8572</td>\n",
+       "            <td>377019.28</td>\n",
+       "            <td>566901.1</td>\n",
+       "            <td>542617.9</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-17</td>\n",
+       "            <td>38292.285</td>\n",
+       "            <td>3857.4285</td>\n",
+       "            <td>37337.855</td>\n",
+       "            <td>1217.5714</td>\n",
+       "            <td>3939.0</td>\n",
+       "            <td>389469.84</td>\n",
+       "            <td>571242.56</td>\n",
+       "            <td>545088.1</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-16</td>\n",
+       "            <td>38119.855</td>\n",
+       "            <td>3810.7144</td>\n",
+       "            <td>38824.0</td>\n",
+       "            <td>1181.0</td>\n",
+       "            <td>3967.2856</td>\n",
+       "            <td>395066.72</td>\n",
+       "            <td>569445.0</td>\n",
+       "            <td>541938.0</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-15</td>\n",
+       "            <td>37858.715</td>\n",
+       "            <td>3746.2856</td>\n",
+       "            <td>40268.57</td>\n",
+       "            <td>1128.5714</td>\n",
+       "            <td>4029.2856</td>\n",
+       "            <td>403526.72</td>\n",
+       "            <td>570188.7</td>\n",
+       "            <td>540199.9</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-14</td>\n",
+       "            <td>37505.57</td>\n",
+       "            <td>3667.2856</td>\n",
+       "            <td>41989.145</td>\n",
+       "            <td>1118.5714</td>\n",
+       "            <td>4065.2856</td>\n",
+       "            <td>412496.44</td>\n",
+       "            <td>567178.7</td>\n",
+       "            <td>537417.1</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(datetime.date(2021, 1, 23), 37915.6, 4027.3333, 22463.666, 1241.7142, 3651.6667, 353735.34, 565312.3, 543566.8),\n",
+       " (datetime.date(2021, 1, 22), 38057.168, 4015.8572, 24870.428, 1238.7142, 3771.75, 354323.16, 567830.3, 545780.3),\n",
+       " (datetime.date(2021, 1, 21), 38217.715, 3999.2856, 30620.428, 1239.7142, 3828.2, 363750.16, 569716.7, 546626.56),\n",
+       " (datetime.date(2021, 1, 20), 38294.0, 3969.8572, 32707.428, 1248.4286, 3811.0, 372037.44, 570458.1, 546806.3),\n",
+       " (datetime.date(2021, 1, 19), 38348.43, 3939.5715, 34143.285, 1240.8572, 3825.8572, 374771.16, 571336.56, 547402.44),\n",
+       " (datetime.date(2021, 1, 18), 38338.145, 3898.5715, 35766.57, 1223.5714, 3872.8572, 377019.28, 566901.1, 542617.9),\n",
+       " (datetime.date(2021, 1, 17), 38292.285, 3857.4285, 37337.855, 1217.5714, 3939.0, 389469.84, 571242.56, 545088.1),\n",
+       " (datetime.date(2021, 1, 16), 38119.855, 3810.7144, 38824.0, 1181.0, 3967.2856, 395066.72, 569445.0, 541938.0),\n",
+       " (datetime.date(2021, 1, 15), 37858.715, 3746.2856, 40268.57, 1128.5714, 4029.2856, 403526.72, 570188.7, 540199.9),\n",
+       " (datetime.date(2021, 1, 14), 37505.57, 3667.2856, 41989.145, 1118.5714, 4065.2856, 412496.44, 567178.7, 537417.1)]"
+      ]
+     },
+     "execution_count": 427,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select * from uk_data_7 order by date desc limit 10"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 428,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "10 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>date</th>\n",
+       "            <th>hospital_cases</th>\n",
+       "            <th>ventilator_beds</th>\n",
+       "            <th>new_cases</th>\n",
+       "            <th>new_deaths</th>\n",
+       "            <th>new_admissions</th>\n",
+       "            <th>new_pcr_tests</th>\n",
+       "            <th>new_tests</th>\n",
+       "            <th>new_pillar_1_2_tests</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2021-01-26</td>\n",
+       "            <td>None</td>\n",
+       "            <td>None</td>\n",
+       "            <td>None</td>\n",
+       "            <td>1631</td>\n",
+       "            <td>None</td>\n",
+       "            <td>None</td>\n",
+       "            <td>None</td>\n",
+       "            <td>None</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-25</td>\n",
+       "            <td>None</td>\n",
+       "            <td>4032</td>\n",
+       "            <td>4482</td>\n",
+       "            <td>592</td>\n",
+       "            <td>None</td>\n",
+       "            <td>196510</td>\n",
+       "            <td>546734</td>\n",
+       "            <td>531104</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-24</td>\n",
+       "            <td>37561</td>\n",
+       "            <td>4077</td>\n",
+       "            <td>14266</td>\n",
+       "            <td>610</td>\n",
+       "            <td>None</td>\n",
+       "            <td>262111</td>\n",
+       "            <td>412775</td>\n",
+       "            <td>394479</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-23</td>\n",
+       "            <td>37266</td>\n",
+       "            <td>4066</td>\n",
+       "            <td>20495</td>\n",
+       "            <td>1348</td>\n",
+       "            <td>None</td>\n",
+       "            <td>389209</td>\n",
+       "            <td>486425</td>\n",
+       "            <td>465231</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-22</td>\n",
+       "            <td>38144</td>\n",
+       "            <td>4076</td>\n",
+       "            <td>29094</td>\n",
+       "            <td>1401</td>\n",
+       "            <td>3341</td>\n",
+       "            <td>401075</td>\n",
+       "            <td>631901</td>\n",
+       "            <td>608829</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-21</td>\n",
+       "            <td>37957</td>\n",
+       "            <td>3960</td>\n",
+       "            <td>31430</td>\n",
+       "            <td>1290</td>\n",
+       "            <td>3598</td>\n",
+       "            <td>439408</td>\n",
+       "            <td>668989</td>\n",
+       "            <td>644537</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-20</td>\n",
+       "            <td>38650</td>\n",
+       "            <td>3953</td>\n",
+       "            <td>35015</td>\n",
+       "            <td>1820</td>\n",
+       "            <td>4016</td>\n",
+       "            <td>434099</td>\n",
+       "            <td>645050</td>\n",
+       "            <td>617221</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-19</td>\n",
+       "            <td>38765</td>\n",
+       "            <td>3947</td>\n",
+       "            <td>39311</td>\n",
+       "            <td>1610</td>\n",
+       "            <td>4132</td>\n",
+       "            <td>357850</td>\n",
+       "            <td>582938</td>\n",
+       "            <td>559061</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-18</td>\n",
+       "            <td>39181</td>\n",
+       "            <td>3916</td>\n",
+       "            <td>44732</td>\n",
+       "            <td>599</td>\n",
+       "            <td>4054</td>\n",
+       "            <td>262499</td>\n",
+       "            <td>559939</td>\n",
+       "            <td>537028</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2021-01-17</td>\n",
+       "            <td>38095</td>\n",
+       "            <td>3871</td>\n",
+       "            <td>28875</td>\n",
+       "            <td>671</td>\n",
+       "            <td>3725</td>\n",
+       "            <td>320122</td>\n",
+       "            <td>417965</td>\n",
+       "            <td>395737</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(datetime.date(2021, 1, 26), None, None, None, 1631, None, None, None, None),\n",
+       " (datetime.date(2021, 1, 25), None, 4032, 4482, 592, None, 196510, 546734, 531104),\n",
+       " (datetime.date(2021, 1, 24), 37561, 4077, 14266, 610, None, 262111, 412775, 394479),\n",
+       " (datetime.date(2021, 1, 23), 37266, 4066, 20495, 1348, None, 389209, 486425, 465231),\n",
+       " (datetime.date(2021, 1, 22), 38144, 4076, 29094, 1401, 3341, 401075, 631901, 608829),\n",
+       " (datetime.date(2021, 1, 21), 37957, 3960, 31430, 1290, 3598, 439408, 668989, 644537),\n",
+       " (datetime.date(2021, 1, 20), 38650, 3953, 35015, 1820, 4016, 434099, 645050, 617221),\n",
+       " (datetime.date(2021, 1, 19), 38765, 3947, 39311, 1610, 4132, 357850, 582938, 559061),\n",
+       " (datetime.date(2021, 1, 18), 39181, 3916, 44732, 599, 4054, 262499, 559939, 537028),\n",
+       " (datetime.date(2021, 1, 17), 38095, 3871, 28875, 671, 3725, 320122, 417965, 395737)]"
+      ]
+     },
+     "execution_count": 428,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select * from uk_data order by date desc limit 10"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "jupytext": {
+   "formats": "ipynb,md"
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/data_import.md b/data_import.md

new file mode 100644 (file)

index 0000000..0a680eb
--- /dev/null
+++ b/data_import.md
@@ -0,0 +1,742 @@
+---
+jupyter:
+  jupytext:
+    formats: ipynb,md
+    text_representation:
+      extension: .md
+      format_name: markdown
+      format_version: '1.2'
+      jupytext_version: 1.9.1
+  kernelspec:
+    display_name: Python 3
+    language: python
+    name: python3
+---
+
+<!-- #region Collapsed="false" -->
+Data from [European Centre for Disease Prevention and Control](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide)
+<!-- #endregion -->
+
+```python Collapsed="false"
+from sqlalchemy.types import Integer, Text, String, DateTime, Date, Float
+from sqlalchemy import create_engine
+```
+
+```python Collapsed="false"
+import itertools
+import collections
+import json
+import pandas as pd
+import numpy as np
+from scipy.stats import gmean
+import datetime
+
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+%matplotlib inline
+```
+
+```python Collapsed="false"
+%load_ext sql
+```
+
+```python Collapsed="false"
+connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'
+```
+
+```python Collapsed="false"
+%sql $connection_string
+```
+
+```python Collapsed="false"
+eng = create_engine(connection_string)
+engine = eng.execution_options(isolation_level="AUTOCOMMIT")
+```
+
+```python Collapsed="false"
+DEATH_COUNT_THRESHOLD = 10
+COUNTRIES_CORE = 'IT DE UK ES IE FR BE'.split()
+COUNTRIES_NORDIC = 'SE NO DK FI UK'.split()
+COUNTRIES_FRIENDS = 'IT UK ES BE SI MX'.split()
+# COUNTRIES_FRIENDS = 'IT UK ES BE SI PT'.split()
+
+COUNTRIES_AMERICAS = ['AG', 'AR', 'AW', 'BS', 'BB', 'BZ', 'BM', 'BO', 'BR', 'VG', 'KY', # excluding Canada and USA
+       'CL', 'CO', 'CR', 'CU', 'CW', 'DM', 'DO', 'EC', 'SV', 'GL', 'GD', 'GT',
+       'GY', 'HT', 'HN', 'JM', 'MX', 'MS', 'NI', 'PA', 'PY', 'PE', 'PR', 'KN',
+       'LC', 'VC', 'SX', 'SR', 'TT', 'TC', 'VI', 'UY', 'VE']
+COUNTRIES_OF_INTEREST = list(set(COUNTRIES_CORE + COUNTRIES_FRIENDS))
+COUNTRIES_ALL = list(set(COUNTRIES_CORE + COUNTRIES_FRIENDS + COUNTRIES_NORDIC + COUNTRIES_AMERICAS))
+```
+
+```python Collapsed="false"
+!curl https://opendata.ecdc.europa.eu/covid19/casedistribution/csv/ > covid.csv
+```
+
+```python Collapsed="false"
+# First col is a date, treat geoId of NA as 'Namibia', not "NA" value
+raw_data = pd.read_csv('covid.csv', 
+                       parse_dates=[0], dayfirst=True,
+                       keep_default_na=False, na_values = [''],
+#                        dtype = {'day': np.int64, 
+#                                 'month': np.int64, 
+#                                 'year': np.int64, 
+#                                 'cases': np.int64, 
+#                                 'deaths': np.int64, 
+#                                 'countriesAndTerritories': str, 
+#                                 'geoId': str, 
+#                                 'countryterritoryCode': str, 
+#                                 'popData2019': np.int64, 
+#                                 'continentExp': str, 
+#                                 }
+                      )
+```
+
+```python Collapsed="false"
+raw_data.size
+```
+
+```python Collapsed="false"
+raw_data.fillna(0, inplace=True)
+```
+
+```python Collapsed="false"
+raw_data.head()
+```
+
+```python Collapsed="false"
+raw_data.rename(columns={'dateRep':'report_date', 'geoId': 'geo_id',
+                        'countriesAndTerritories': 'country_name',
+                        'countryterritoryCode': 'country_territory_code',
+                        'popData2019': 'population_2019',
+                        'continentExp': 'continent'}, inplace=True)
+```
+
+```python Collapsed="false"
+raw_data.columns
+```
+
+```python Collapsed="false"
+raw_data.dtypes
+```
+
+```python Collapsed="false"
+raw_data[['report_date', 'cases_weekly', 'deaths_weekly', 'geo_id', 'notification_rate_per_100000_population_14-days']]
+```
+
+```python Collapsed="false"
+raw_data[['country_name', 'geo_id', 'country_territory_code',
+       'population_2019', 'continent']]
+```
+
+```python Collapsed="false"
+raw_data[['report_date', 'cases_weekly', 'deaths_weekly', 'geo_id', 'notification_rate_per_100000_population_14-days']].to_sql(
+    'weekly_cases',
+    engine,
+    if_exists='replace',
+    index=False,
+    chunksize=500,
+    dtype={
+        "report_date": Date,
+        "cases_weekly": Integer,
+        "deaths_weekly": Integer,
+        "geo_id": String,
+        "notification_rate_per_100000_population_14-days": Float
+    }
+)
+```
+
+```python Collapsed="false"
+raw_data[['country_name', 'geo_id', 'country_territory_code',
+       'population_2019', 'continent']].drop_duplicates().to_sql(
+    'countries',
+    engine,
+    if_exists='replace',
+    index=False,
+    chunksize=500,
+    dtype={
+        "country_name": Text,
+        "geo_id": String,
+        "country_territory_code": String,
+        "population_2019": Integer,
+        "continent": Text
+    }
+)
+```
+
+```python Collapsed="false"
+# %sql select geo_id from weekly_cases limit 10
+```
+
+```python Collapsed="false"
+# %%sql alter table weekly_cases add primary key (geo_id, report_date);
+# alter table countries add primary key (geo_id);
+# alter table weekly_cases add foreign key (geo_id) references countries(geo_id);
+# alter table weekly_cases add culm_cases integer;
+# alter table weekly_cases add culm_deaths integer;
+```
+
+```python
+with engine.connect() as connection:
+    connection.execute('alter table weekly_cases add primary key (geo_id, report_date)')
+    connection.execute('alter table countries add primary key (geo_id);')
+    connection.execute('alter table weekly_cases add foreign key (geo_id) references countries(geo_id);')
+    connection.execute('alter table weekly_cases add culm_cases integer;')
+    connection.execute('alter table weekly_cases add culm_deaths integer;')
+```
+
+```python Collapsed="false"
+# %sql select report_date, cases_weekly, country_name from weekly_cases join countries using (geo_id) order by report_date desc limit 10
+```
+
+```python Collapsed="false"
+# %sql select report_date, cases_weekly, country_name from weekly_cases join countries on weekly_cases.geo_id = countries.geo_id order by report_date desc limit 10
+```
+
+```python Collapsed="false"
+%sql select * from weekly_cases limit 10
+```
+
+```python Collapsed="false"
+# %%sql
+# with culm as 
+#     (select report_date, geo_id,
+#         sum(cases_weekly) over (partition by geo_id 
+#                                 order by report_date) as culm_data
+#      from weekly_cases
+#     )
+# update weekly_cases
+#     set culm_cases = culm_data
+#     from culm
+#     where weekly_cases.report_date = culm.report_date and
+#           weekly_cases.geo_id = culm.geo_id
+```
+
+```python Collapsed="false"
+query_string = '''with culm as 
+    (select report_date, geo_id,
+        sum(cases_weekly) over (partition by geo_id 
+                                order by report_date) as culm_data
+     from weekly_cases
+    )
+update weekly_cases
+    set culm_cases = culm_data
+    from culm
+    where weekly_cases.report_date = culm.report_date and
+          weekly_cases.geo_id = culm.geo_id'''
+with engine.connect() as connection:
+    connection.execute(query_string)
+```
+
+```python Collapsed="false"
+# %%sql
+# with culm as 
+#     (select report_date, geo_id,
+#         sum(deaths_weekly) over (partition by geo_id 
+#                                 order by report_date) as culm_data
+#      from weekly_cases
+#     )
+# update weekly_cases
+#     set culm_deaths = culm_data
+#     from culm
+#     where weekly_cases.report_date = culm.report_date and
+#           weekly_cases.geo_id = culm.geo_id
+```
+
+```python Collapsed="false"
+query_string = '''with culm as 
+    (select report_date, geo_id,
+        sum(deaths_weekly) over (partition by geo_id 
+                                order by report_date) as culm_data
+     from weekly_cases
+    )
+update weekly_cases
+    set culm_deaths = culm_data
+    from culm
+    where weekly_cases.report_date = culm.report_date and
+          weekly_cases.geo_id = culm.geo_id'''
+with engine.connect() as connection:
+    connection.execute(query_string)
+```
+
+```python Collapsed="false"
+uk_query_string = (
+"https://api.coronavirus.data.gov.uk/v2/data?areaType=overview&"
+"metric=covidOccupiedMVBeds&"
+"metric=newAdmissions&"
+"metric=newCasesBySpecimenDate&"
+"metric=hospitalCases&"
+"metric=newDeaths28DaysByPublishDate&"
+"format=csv"
+)
+
+!curl "$uk_query_string" > uk_data.csv
+```
+
+```python Collapsed="false"
+test_query_string = (
+"https://api.coronavirus.data.gov.uk/v2/data?areaType=overview&"
+"metric=newPCRTestsByPublishDate&"
+"metric=newTestsByPublishDate&"
+"metric=newPillarOneTwoTestsByPublishDate&"
+"format=csv"
+)
+!curl "$test_query_string" > test_data.csv
+```
+
+```python Collapsed="false"
+# hospital_query_string = (
+# "https://api.coronavirus.data.gov.uk/v2/data?areaType=overview&"
+# "metric=newAdmissions&"
+# "format=csv"
+# )
+# !curl "$hospital_query_string" > hospital_admissions.csv
+```
+
+```python Collapsed="false"
+# hospital_query_string = (
+# "https://api.coronavirus.data.gov.uk/v1/data?"
+# "filters=areaName=United%2520Kingdom;areaType=overview&"
+# "structure=%7B%22date%22:%22date%22,%22areaName%22:%22areaName%22,%22areaType%22:%22areaType%22,"
+# "%22newAdmissions%22:%22newAdmissions%22,%22cumAdmissions%22:%22cumAdmissions%22%7D&format=csv"
+# )
+    
+# !curl "$hospital_query_string" | gunzip > hospital_admissions.csv
+```
+
+```python Collapsed="false"
+uk_data = pd.read_csv('uk_data.csv', 
+                       parse_dates=[0], dayfirst=True)
+uk_data
+```
+
+```python Collapsed="false"
+test_data = pd.read_csv('test_data.csv', 
+                       parse_dates=[0], dayfirst=True)
+test_data
+```
+
+```python Collapsed="false"
+test_data.columns
+```
+
+```python Collapsed="false"
+uk_data = uk_data.merge(test_data[['date', 'newPCRTestsByPublishDate',
+       'newTestsByPublishDate', 'newPillarOneTwoTestsByPublishDate']], how='outer', on='date')
+```
+
+```python Collapsed="false"
+uk_data.columns
+```
+
+```python Collapsed="false"
+uk_data.rename(
+    columns={
+        'covidOccupiedMVBeds': 'ventilator_beds',
+        'newCasesBySpecimenDate': 'new_cases',
+        'hospitalCases': 'hospital_cases', 
+        'newDeaths28DaysByPublishDate': 'new_deaths',
+        'newAdmissions': 'new_admissions',
+        'newPCRTestsByPublishDate': 'new_pcr_tests',
+        'newTestsByPublishDate': 'new_tests',
+        'newPillarOneTwoTestsByPublishDate': 'new_pillar_1_2_tests'
+    }, inplace=True)
+```
+
+```python Collapsed="false"
+uk_data.dtypes
+```
+
+```python Collapsed="false"
+ uk_data.columns
+```
+
+```python Collapsed="false"
+uk_data[['date', 
+         'hospital_cases', 'ventilator_beds',
+         'new_cases', 'new_deaths', 
+         'hospital_cases', 'new_admissions',
+         'new_pcr_tests', 'new_tests', 'new_pillar_1_2_tests'
+        ]].to_sql(
+    'uk_data',
+    engine,
+    if_exists='replace',
+    index=False,
+    chunksize=500,
+    dtype={
+        "date": Date,
+        "hospital_cases": Integer,
+        "ventilator_beds": Integer,
+        "new_cases": Integer,
+        "hospital_cases": Integer,
+        "new_deaths": Integer,
+        "new_admissions": Integer,
+        'new_pcr_tests': Integer, 
+        'new_tests': Integer, 
+        'new_pillar_1_2_tests': Integer
+    }
+)
+```
+
+```python Collapsed="false"
+# %sql select * from uk_data order by date desc limit 10
+```
+
+```python Collapsed="false"
+query_string = '''drop table if exists uk_data_7;
+create table uk_data_7 
+(date date primary key,
+ hospital_cases real,
+ ventilator_beds real,
+ new_cases real,
+ new_deaths real,
+ new_admissions real,
+ new_pcr_tests real,
+ new_tests real,
+ new_pillar_1_2_tests real
+);'''
+
+with engine.connect() as connection:
+    connection.execute(query_string)
+```
+
+```python
+update_string = '''with ownd as (
+    select date,
+        avg(hospital_cases) over wnd as w_hospital_cases,
+        avg(ventilator_beds) over wnd as w_ventilator_beds,
+        avg(new_cases) over wnd as w_new_cases,
+        avg(new_deaths) over wnd as w_new_deaths,
+        avg(new_admissions) over wnd as w_new_admissions,
+        avg(new_pcr_tests) over wnd as w_new_pcr_tests,
+        avg(new_tests) over wnd as w_new_tests,
+        avg(new_pillar_1_2_tests) over wnd as w_new_pillar_1_2_tests,
+        count(*) over wnd as w_size
+    from uk_data
+    window wnd as (
+        order by uk_data.date
+        rows between 3 preceding and 3 following
+    )
+)
+insert into uk_data_7(date, 
+    hospital_cases, 
+    ventilator_beds, 
+    new_cases,
+    new_deaths,
+    new_admissions, 
+    new_pcr_tests, 
+    new_tests, 
+    new_pillar_1_2_tests
+    )
+(select date,
+        w_hospital_cases,
+        w_ventilator_beds,
+        w_new_cases,
+        w_new_deaths,
+        w_new_admissions,
+        w_new_pcr_tests,
+        w_new_tests,
+        w_new_pillar_1_2_tests
+    from ownd
+    where w_size = 7
+)'''
+with engine.connect() as connection:
+    connection.execute(update_string)
+```
+
+```python Collapsed="false"
+# %%sql insert into uk_data_7(date, ventilator_beds, new_cases, hospital_cases, new_deaths, new_admissions)
+# values (
+#     select date, 
+#     avg(ventilator_beds) over (order by date rows between 6 preceding and current row)
+#     from uk_data
+# )
+```
+
+```python Collapsed="false"
+# query_string = '''insert into uk_data_7(date, hospital_cases)
+#     select uk_data.date, 
+#         avg(uk_data.hospital_cases) over (order by uk_data.date rows between 3 preceding and 3 following) as hospital_cases
+#     from uk_data'''
+# with engine.connect() as connection:
+#     connection.execute(query_string)   
+```
+
+```python Collapsed="false"
+# %%sql 
+# with m7 as 
+#     (select uk_data.date as date7, 
+#         avg(uk_data.ventilator_beds) over (order by uk_data.date rows between 6 preceding and current row) as nc7
+#      from uk_data
+#     )
+# update uk_data_7
+#     set ventilator_beds = nc7
+#     from m7
+#     where uk_data_7.date = m7.date7
+```
+
+```python Collapsed="false"
+# %%sql
+# with m7 as 
+#     (select uk_data.date as date7, 
+#         avg(uk_data.ventilator_beds) over (order by uk_data.date rows between 3 preceding and 3 following) as nc7
+#      from uk_data
+#     )
+# update uk_data_7
+#     set ventilator_beds = nc7
+#     from m7
+#     where uk_data_7.date = m7.date7
+```
+
+```python Collapsed="false"
+# %%sql
+# with m7 as 
+#     (select uk_data.date as date7, 
+#         avg(uk_data.new_cases) over (order by uk_data.date rows between 3 preceding and 3 following) as nc7
+#      from uk_data
+#     )
+# update uk_data_7
+#     set new_cases = nc7
+#     from m7
+#     where uk_data_7.date = m7.date7
+```
+
+```python Collapsed="false"
+# %%sql
+# with m7 as 
+#     (select uk_data.date as date7, 
+#         avg(uk_data.hospital_cases) over (order by uk_data.date rows between 3 preceding and 3 following) as d7
+#      from uk_data
+#     )
+# update uk_data_7
+#     set hospital_cases = d7
+#     from m7
+#     where uk_data_7.date = m7.date7
+```
+
+```python Collapsed="false"
+# %%sql
+# with m7 as 
+#     (select uk_data.date as date7, 
+#         avg(uk_data.new_deaths) over (order by uk_data.date rows between 3 preceding and 3 following) as d7
+#      from uk_data
+#     )
+# update uk_data_7
+#     set new_deaths = d7
+#     from m7
+#     where uk_data_7.date = m7.date7
+```
+
+```python Collapsed="false"
+# %%sql
+# with m7 as 
+#     (select uk_data.date as date7, 
+#         avg(uk_data.new_admissions) over (order by uk_data.date rows between 3 preceding and 3 following) as d7
+#      from uk_data
+#     )
+# update uk_data_7
+#     set new_admissions = d7
+#     from m7
+#     where uk_data_7.date = m7.date7
+```
+
+```python Collapsed="false"
+# %%sql
+# with m7 as 
+#     (select uk_data.date as date7, 
+#         avg(uk_data.new_pcr_tests) over (order by uk_data.date rows between 3 preceding and 3 following) as d7
+#      from uk_data
+#     )
+# update uk_data_7
+#     set new_pcr_tests = d7
+#     from m7
+#     where uk_data_7.date = m7.date7
+```
+
+```python Collapsed="false"
+# %%sql
+# with m7 as 
+#     (select uk_data.date as date7, 
+#         avg(uk_data.new_tests) over (order by uk_data.date rows between 3 preceding and 3 following) as d7
+#      from uk_data
+#     )
+# update uk_data_7
+#     set new_tests = d7
+#     from m7
+#     where uk_data_7.date = m7.date7
+```
+
+```python Collapsed="false"
+# %%sql
+# with m7 as 
+#     (select uk_data.date as date7, 
+#         avg(uk_data.new_pillar_1_2_tests) over (order by uk_data.date rows between 3 preceding and 3 following) as d7
+#      from uk_data
+#     )
+# update uk_data_7
+#     set new_pillar_1_2_tests = d7
+#     from m7
+#     where uk_data_7.date = m7.date7
+```
+
+```python Collapsed="false"
+# %%sql
+# with wnd as
+#     (   select date, 
+#              avg(new_pillar_1_2_tests)
+#                 over (order by uk_data.date rows between 3 preceding and 3 following) as a_new_pillar_1_2_tests
+#         from uk_data
+#     )
+# update uk_data_7
+#     set new_pillar_1_2_tests = wnd.a_new_pillar_1_2_tests
+#     from wnd
+#     where uk_data_7.date = wnd.date
+#     and (select count(*) from wnd) = 7
+```
+
+```python Collapsed="false"
+# %%sql
+# with wnd as
+#     (   select date, 
+#              avg(new_pillar_1_2_tests)
+#                 over (order by uk_data.date rows between 3 preceding and 3 following) as a_new_pillar_1_2_tests,
+#              count(new_pillar_1_2_tests)
+#                 over (order by uk_data.date rows between 3 preceding and 3 following) as a_count
+#         from uk_data
+#     )
+# select uk_data_7.date, new_pillar_1_2_tests, wnd.a_new_pillar_1_2_tests, wnd.a_count
+#     from uk_data_7, wnd
+#     where uk_data_7.date = wnd.date
+#     order by uk_data_7.date desc limit 10
+    
+# select date, 
+#     count(*) over wnd as w_size
+# from uk_data
+# window wnd as (
+#     order by uk_data.date
+#     rows between 3 preceding and 3 following
+# );
+```
+
+```python Collapsed="false"
+# %%sql
+# select date, 
+#     count(*) over wnd as w_size
+# from uk_data
+# window wnd as (
+#     order by uk_data.date
+#     rows between 3 preceding and 3 following
+# )
+# order by date desc limit 10
+```
+
+```python
+# %%sql
+# with ownd as (
+#     select date,
+#         avg(hospital_cases) over wnd as w_hospital_cases,
+#         avg(ventilator_beds) over wnd as w_ventilator_beds,
+#         avg(new_cases) over wnd as w_new_cases,
+#         avg(new_deaths) over wnd as w_new_deaths,
+#         avg(new_admissions) over wnd as w_new_admissions,
+#         avg(new_pcr_tests) over wnd as w_new_pcr_tests,
+#         avg(new_tests) over wnd as w_new_tests,
+#         avg(new_pillar_1_2_tests) over wnd as w_new_pillar_1_2_tests,
+#         count(*) over wnd as w_size
+#     from uk_data
+#     window wnd as (
+#         order by uk_data.date
+#         rows between 3 preceding and 3 following
+#     ))
+# insert into uk_data_7(date, 
+#     hospital_cases, 
+#     ventilator_beds, 
+#     new_cases,
+#     new_deaths,
+#     new_admissions, 
+#     new_pcr_tests, 
+#     new_tests, 
+#     new_pillar_1_2_tests
+#     )
+# (select date,
+#         avg(hospital_cases) over wnd as w_hospital_cases,
+#         avg(ventilator_beds) over wnd as w_ventilator_beds,
+#         avg(new_cases) over wnd as w_new_cases,
+#         avg(new_deaths) over wnd as w_new_deaths,
+#         avg(new_admissions) over wnd as w_new_admissions,
+#         avg(new_pcr_tests) over wnd as w_new_pcr_tests,
+#         avg(new_tests) over wnd as w_new_tests,
+#         avg(new_pillar_1_2_tests) over wnd as w_new_pillar_1_2_tests,
+#         count(*) over wnd as w_size
+#     from uk_data
+#     window wnd as (
+#         order by uk_data.date
+#         rows between 3 preceding and 3 following
+#     )
+# )
+#     set date = ownd.date,
+#         hospital_cases = w_hospital_cases,
+#         ventilator_beds = w_ventilator_beds,
+#         new_cases = w_new_cases,
+#         new_deaths = w_new_deaths,
+#         new_admissions = w_new_admissions,
+#         new_pcr_tests = w_new_pcr_tests,
+#         new_tests = w_new_tests,
+#         new_pillar_1_2_tests = w_new_pillar_1_2_tests
+#     from ownd
+#     where w_size = 7
+```
+
+```python
+# %%sql
+# with ownd as (
+#     select date,
+#         avg(hospital_cases) over wnd as w_hospital_cases,
+#         avg(ventilator_beds) over wnd as w_ventilator_beds,
+#         avg(new_cases) over wnd as w_new_cases,
+#         avg(new_deaths) over wnd as w_new_deaths,
+#         avg(new_admissions) over wnd as w_new_admissions,
+#         avg(new_pcr_tests) over wnd as w_new_pcr_tests,
+#         avg(new_tests) over wnd as w_new_tests,
+#         avg(new_pillar_1_2_tests) over wnd as w_new_pillar_1_2_tests,
+#         count(*) over wnd as w_size
+#     from uk_data
+#     window wnd as (
+#         order by uk_data.date
+#         rows between 3 preceding and 3 following
+#     )
+# )
+# insert into uk_data_7(date, 
+#     hospital_cases, 
+#     ventilator_beds, 
+#     new_cases,
+#     new_deaths,
+#     new_admissions, 
+#     new_pcr_tests, 
+#     new_tests, 
+#     new_pillar_1_2_tests
+#     )
+# (select date,
+#         w_hospital_cases,
+#         w_ventilator_beds,
+#         w_new_cases,
+#         w_new_deaths,
+#         w_new_admissions,
+#         w_new_pcr_tests,
+#         w_new_tests,
+#         w_new_pillar_1_2_tests
+#     from ownd
+#     where w_size = 7
+# )
+```
+
+```python Collapsed="false"
+%sql select * from uk_data_7 order by date desc limit 10
+```
+
+```python Collapsed="false"
+%sql select * from uk_data order by date desc limit 10
+```
+
+```python Collapsed="false"
+
+```
diff --git a/data_import.py b/data_import.py

new file mode 100644 (file)

index 0000000..20593c7
--- /dev/null
+++ b/data_import.py
@@ -0,0 +1,291 @@
+#!/usr/bin/env python
+# coding: utf-8
+# %%
+# Data from [European Centre for Disease Prevention and Control](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide)
+
+from sqlalchemy.types import Integer, Text, String, DateTime, Date, Float
+from sqlalchemy import create_engine
+
+# import itertools
+# import collections
+# import json
+import pandas as pd
+import numpy as np
+# from scipy.stats import gmean
+import datetime
+import os
+
+
+# %%
+connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'
+
+eng = create_engine(connection_string)
+engine = eng.execution_options(isolation_level="AUTOCOMMIT")
+
+
+# %%
+DEATH_COUNT_THRESHOLD = 10
+COUNTRIES_CORE = 'IT DE UK ES IE FR BE'.split()
+COUNTRIES_NORDIC = 'SE NO DK FI UK'.split()
+COUNTRIES_FRIENDS = 'IT UK ES BE SI MX'.split()
+# COUNTRIES_FRIENDS = 'IT UK ES BE SI PT'.split()
+
+COUNTRIES_AMERICAS = ['AG', 'AR', 'AW', 'BS', 'BB', 'BZ', 'BM', 'BO', 'BR', 'VG', 'KY', # excluding Canada and USA
+       'CL', 'CO', 'CR', 'CU', 'CW', 'DM', 'DO', 'EC', 'SV', 'GL', 'GD', 'GT',
+       'GY', 'HT', 'HN', 'JM', 'MX', 'MS', 'NI', 'PA', 'PY', 'PE', 'PR', 'KN',
+       'LC', 'VC', 'SX', 'SR', 'TT', 'TC', 'VI', 'UY', 'VE']
+COUNTRIES_OF_INTEREST = list(set(COUNTRIES_CORE + COUNTRIES_FRIENDS))
+COUNTRIES_ALL = list(set(COUNTRIES_CORE + COUNTRIES_FRIENDS + COUNTRIES_NORDIC + COUNTRIES_AMERICAS))
+
+
+# %%
+os.system('curl https://opendata.ecdc.europa.eu/covid19/casedistribution/csv/ > covid.csv')
+
+
+# %%
+# First col is a date, treat geoId of NA as 'Namibia', not "NA" value
+raw_data = pd.read_csv('covid.csv', 
+                       parse_dates=[0], dayfirst=True,
+                       keep_default_na=False, na_values = [''],
+#                        dtype = {'day': np.int64, 
+#                                 'month': np.int64, 
+#                                 'year': np.int64, 
+#                                 'cases': np.int64, 
+#                                 'deaths': np.int64, 
+#                                 'countriesAndTerritories': str, 
+#                                 'geoId': str, 
+#                                 'countryterritoryCode': str, 
+#                                 'popData2019': np.int64, 
+#                                 'continentExp': str, 
+#                                 }
+                      )
+
+raw_data.fillna(0, inplace=True)
+
+
+# %%
+raw_data.rename(columns={'dateRep':'report_date', 'geoId': 'geo_id',
+                        'countriesAndTerritories': 'country_name',
+                        'countryterritoryCode': 'country_territory_code',
+                        'popData2019': 'population_2019',
+                        'continentExp': 'continent'}, inplace=True)
+
+
+# %%
+raw_data[['report_date', 'cases_weekly', 'deaths_weekly', 'geo_id', 'notification_rate_per_100000_population_14-days']].to_sql(
+    'weekly_cases',
+    engine,
+    if_exists='replace',
+    index=False,
+    chunksize=500,
+    dtype={
+        "report_date": Date,
+        "cases_weekly": Integer,
+        "deaths_weekly": Integer,
+        "geo_id": String,
+        "notification_rate_per_100000_population_14-days": Float
+    }
+)
+
+
+# %%
+raw_data[['country_name', 'geo_id', 'country_territory_code',
+       'population_2019', 'continent']].drop_duplicates().to_sql(
+    'countries',
+    engine,
+    if_exists='replace',
+    index=False,
+    chunksize=500,
+    dtype={
+        "country_name": Text,
+        "geo_id": String,
+        "country_territory_code": String,
+        "population_2019": Integer,
+        "continent": Text
+    }
+)
+
+
+# %%
+with engine.connect() as connection:
+    connection.execute('alter table weekly_cases add primary key (geo_id, report_date)')
+    connection.execute('alter table countries add primary key (geo_id);')
+    connection.execute('alter table weekly_cases add foreign key (geo_id) references countries(geo_id);')
+    connection.execute('alter table weekly_cases add culm_cases integer;')
+    connection.execute('alter table weekly_cases add culm_deaths integer;')
+
+
+# %%
+query_string = '''with culm as 
+    (select report_date, geo_id,
+        sum(cases_weekly) over (partition by geo_id 
+                                order by report_date) as culm_data
+     from weekly_cases
+    )
+update weekly_cases
+    set culm_cases = culm_data
+    from culm
+    where weekly_cases.report_date = culm.report_date and
+          weekly_cases.geo_id = culm.geo_id'''
+with engine.connect() as connection:
+    connection.execute(query_string)
+
+
+# %%
+query_string = '''with culm as 
+    (select report_date, geo_id,
+        sum(deaths_weekly) over (partition by geo_id 
+                                order by report_date) as culm_data
+     from weekly_cases
+    )
+update weekly_cases
+    set culm_deaths = culm_data
+    from culm
+    where weekly_cases.report_date = culm.report_date and
+          weekly_cases.geo_id = culm.geo_id'''
+with engine.connect() as connection:
+    connection.execute(query_string)
+
+
+# %%
+uk_query_string = (
+"https://api.coronavirus.data.gov.uk/v2/data?areaType=overview&"
+"metric=covidOccupiedMVBeds&"
+"metric=newAdmissions&"
+"metric=newCasesBySpecimenDate&"
+"metric=hospitalCases&"
+"metric=newDeaths28DaysByPublishDate&"
+"format=csv"
+)
+
+os.system(f'curl "{uk_query_string}" > uk_data.csv')
+
+
+# %%
+test_query_string = (
+"https://api.coronavirus.data.gov.uk/v2/data?areaType=overview&"
+"metric=newPCRTestsByPublishDate&"
+"metric=newTestsByPublishDate&"
+"metric=newPillarOneTwoTestsByPublishDate&"
+"format=csv"
+)
+os.system(f'curl "{test_query_string}" > test_data.csv')
+
+
+# %%
+uk_data = pd.read_csv('uk_data.csv', 
+                       parse_dates=[0], dayfirst=True)
+
+
+# %%
+test_data = pd.read_csv('test_data.csv', 
+                       parse_dates=[0], dayfirst=True)
+
+
+# %%
+uk_data = uk_data.merge(test_data[['date', 'newPCRTestsByPublishDate',
+       'newTestsByPublishDate', 'newPillarOneTwoTestsByPublishDate']], how='outer', on='date')
+
+
+# %%
+uk_data.rename(
+    columns={
+        'covidOccupiedMVBeds': 'ventilator_beds',
+        'newCasesBySpecimenDate': 'new_cases',
+        'hospitalCases': 'hospital_cases', 
+        'newDeaths28DaysByPublishDate': 'new_deaths',
+        'newAdmissions': 'new_admissions',
+        'newPCRTestsByPublishDate': 'new_pcr_tests',
+        'newTestsByPublishDate': 'new_tests',
+        'newPillarOneTwoTestsByPublishDate': 'new_pillar_1_2_tests'
+    }, inplace=True)
+
+
+# %%
+uk_data[['date', 
+         'hospital_cases', 'ventilator_beds',
+         'new_cases', 'new_deaths', 
+         'hospital_cases', 'new_admissions',
+         'new_pcr_tests', 'new_tests', 'new_pillar_1_2_tests'
+        ]].to_sql(
+    'uk_data',
+    engine,
+    if_exists='replace',
+    index=False,
+    chunksize=500,
+    dtype={
+        "date": Date,
+        "hospital_cases": Integer,
+        "ventilator_beds": Integer,
+        "new_cases": Integer,
+        "hospital_cases": Integer,
+        "new_deaths": Integer,
+        "new_admissions": Integer,
+        'new_pcr_tests': Integer, 
+        'new_tests': Integer, 
+        'new_pillar_1_2_tests': Integer
+    }
+)
+
+
+# %%
+query_string = '''drop table if exists uk_data_7;
+create table uk_data_7 
+(date date primary key,
+ hospital_cases real,
+ ventilator_beds real,
+ new_cases real,
+ new_deaths real,
+ new_admissions real,
+ new_pcr_tests real,
+ new_tests real,
+ new_pillar_1_2_tests real
+);'''
+
+with engine.connect() as connection:
+    connection.execute(query_string)
+
+
+# %%
+query_string = '''with ownd as (
+    select date,
+        avg(hospital_cases) over wnd as w_hospital_cases,
+        avg(ventilator_beds) over wnd as w_ventilator_beds,
+        avg(new_cases) over wnd as w_new_cases,
+        avg(new_deaths) over wnd as w_new_deaths,
+        avg(new_admissions) over wnd as w_new_admissions,
+        avg(new_pcr_tests) over wnd as w_new_pcr_tests,
+        avg(new_tests) over wnd as w_new_tests,
+        avg(new_pillar_1_2_tests) over wnd as w_new_pillar_1_2_tests,
+        count(*) over wnd as w_size
+    from uk_data
+    window wnd as (
+        order by uk_data.date
+        rows between 3 preceding and 3 following
+    )
+)
+insert into uk_data_7(date, 
+    hospital_cases, 
+    ventilator_beds, 
+    new_cases,
+    new_deaths,
+    new_admissions, 
+    new_pcr_tests, 
+    new_tests, 
+    new_pillar_1_2_tests
+    )
+(select date,
+        w_hospital_cases,
+        w_ventilator_beds,
+        w_new_cases,
+        w_new_deaths,
+        w_new_admissions,
+        w_new_pcr_tests,
+        w_new_tests,
+        w_new_pillar_1_2_tests
+    from ownd
+    where w_size = 7
+)'''
+with engine.connect() as connection:
+    connection.execute(query_string)
+
diff --git a/deaths-radar-cover.png b/deaths-radar-cover.png

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diff --git a/deaths_import.ipynb b/deaths_import.ipynb

new file mode 100644 (file)

index 0000000..f8f21cf
--- /dev/null
+++ b/deaths_import.ipynb
@@ -0,0 +1,15710 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "source": [
+    "Data from:\n",
+    "\n",
+    "* [Office of National Statistics](https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/weeklyprovisionalfiguresondeathsregisteredinenglandandwales) (Endland and Wales) Weeks start on a Saturday.\n",
+    "* [Northern Ireland Statistics and Research Agency](https://www.nisra.gov.uk/publications/weekly-deaths) (Northern Ireland). Weeks start on a Saturday. Note that the week numbers don't match the England and Wales data.\n",
+    "* [National Records of Scotland](https://www.nrscotland.gov.uk/statistics-and-data/statistics/statistics-by-theme/vital-events/general-publications/weekly-and-monthly-data-on-births-and-deaths/weekly-data-on-births-and-deaths) (Scotland). Note that Scotland uses ISO8601 week numbers, which start on a Monday.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 392,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The sql extension is already loaded. To reload it, use:\n",
+      "  %reload_ext sql\n"
+     ]
+    }
+   ],
+   "source": [
+    "import itertools\n",
+    "import collections\n",
+    "import json\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "from scipy.stats import gmean\n",
+    "import datetime\n",
+    "\n",
+    "import matplotlib as mpl\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline\n",
+    "\n",
+    "from sqlalchemy.types import Integer, Text, String, DateTime, Float\n",
+    "from sqlalchemy import create_engine\n",
+    "%load_ext sql"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 393,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 394,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Connected: covid@covid'"
+      ]
+     },
+     "execution_count": 394,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql $connection_string"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 395,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "conn = create_engine(connection_string)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 396,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "england_wales_filename = 'uk-deaths-data/publishedweek532020.xlsx'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 397,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "Done.\n",
+      "Done.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[]"
+      ]
+     },
+     "execution_count": 397,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%sql\n",
+    "drop table if exists all_causes_deaths;\n",
+    "create table all_causes_deaths (\n",
+    "    week integer,\n",
+    "    year integer,\n",
+    "    date_up_to date,\n",
+    "    nation varchar(20),\n",
+    "    deaths integer,\n",
+    "    CONSTRAINT week_nation PRIMARY KEY(year, week, nation)\n",
+    ");"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 525,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>total_2015</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>(Registration Week, Unnamed: 0_level_1)</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>294</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>343</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>301</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>232</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>232</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                         total_2015\n",
+       "(Registration Week, Unnamed: 0_level_1)            \n",
+       "49                                              294\n",
+       "50                                              343\n",
+       "51                                              301\n",
+       "52                                              232\n",
+       "53                                              232"
+      ]
+     },
+     "execution_count": 525,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data_2015 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2015.csv', \n",
+    "                       parse_dates=[1, 2], dayfirst=True,\n",
+    "#                       index_col=0,\n",
+    "                      header=[0, 1]\n",
+    "                           )\n",
+    "dh15i = raw_data_2015.iloc[:, [0, 3]]\n",
+    "dh15i.set_index(dh15i.columns[0], inplace=True)\n",
+    "dh15i.columns = ['total_2015']\n",
+    "dh15i.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 399,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead tr th {\n",
+       "        text-align: left;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th>Registration Week</th>\n",
+       "      <th>Week Starts (Saturday)</th>\n",
+       "      <th>Week Ends (Friday)</th>\n",
+       "      <th>Total Number of Deaths Registered in Week (2015P)</th>\n",
+       "      <th>Average number of deaths registered in corresponding week in previous 5 years (2010 to 2014P)</th>\n",
+       "      <th>Range</th>\n",
+       "      <th>Unnamed: 6_level_0</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th>Unnamed: 0_level_1</th>\n",
+       "      <th>Unnamed: 1_level_1</th>\n",
+       "      <th>Unnamed: 2_level_1</th>\n",
+       "      <th>Unnamed: 3_level_1</th>\n",
+       "      <th>Unnamed: 4_level_1</th>\n",
+       "      <th>Minimum in Previous 5 years</th>\n",
+       "      <th>Maximum in Previous 5 years</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2014-12-29</td>\n",
+       "      <td>2015-01-02</td>\n",
+       "      <td>319</td>\n",
+       "      <td>317.2</td>\n",
+       "      <td>248</td>\n",
+       "      <td>372</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2015-01-03</td>\n",
+       "      <td>2015-01-09</td>\n",
+       "      <td>373</td>\n",
+       "      <td>384.0</td>\n",
+       "      <td>344</td>\n",
+       "      <td>421</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2015-01-10</td>\n",
+       "      <td>2015-01-16</td>\n",
+       "      <td>383</td>\n",
+       "      <td>347.8</td>\n",
+       "      <td>319</td>\n",
+       "      <td>373</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2015-01-17</td>\n",
+       "      <td>2015-01-23</td>\n",
+       "      <td>397</td>\n",
+       "      <td>319.0</td>\n",
+       "      <td>282</td>\n",
+       "      <td>353</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2015-01-24</td>\n",
+       "      <td>2015-01-30</td>\n",
+       "      <td>374</td>\n",
+       "      <td>309.2</td>\n",
+       "      <td>284</td>\n",
+       "      <td>336</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Registration Week Week Starts (Saturday) Week Ends (Friday)  \\\n",
+       "  Unnamed: 0_level_1     Unnamed: 1_level_1 Unnamed: 2_level_1   \n",
+       "0                  1             2014-12-29         2015-01-02   \n",
+       "1                  2             2015-01-03         2015-01-09   \n",
+       "2                  3             2015-01-10         2015-01-16   \n",
+       "3                  4             2015-01-17         2015-01-23   \n",
+       "4                  5             2015-01-24         2015-01-30   \n",
+       "\n",
+       "  Total Number of Deaths Registered in Week (2015P)  \\\n",
+       "                                 Unnamed: 3_level_1   \n",
+       "0                                               319   \n",
+       "1                                               373   \n",
+       "2                                               383   \n",
+       "3                                               397   \n",
+       "4                                               374   \n",
+       "\n",
+       "  Average number of deaths registered in corresponding week in previous 5 years (2010 to 2014P)  \\\n",
+       "                                                                             Unnamed: 4_level_1   \n",
+       "0                                              317.2                                              \n",
+       "1                                              384.0                                              \n",
+       "2                                              347.8                                              \n",
+       "3                                              319.0                                              \n",
+       "4                                              309.2                                              \n",
+       "\n",
+       "                        Range          Unnamed: 6_level_0  \n",
+       "  Minimum in Previous 5 years Maximum in Previous 5 years  \n",
+       "0                         248                         372  \n",
+       "1                         344                         421  \n",
+       "2                         319                         373  \n",
+       "3                         282                         353  \n",
+       "4                         284                         336  "
+      ]
+     },
+     "execution_count": 399,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data_2015.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 400,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2015-01-02</td>\n",
+       "      <td>319</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2015-01-09</td>\n",
+       "      <td>373</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2015-01-16</td>\n",
+       "      <td>383</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2015-01-23</td>\n",
+       "      <td>397</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2015-01-30</td>\n",
+       "      <td>374</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week date_up_to  deaths  year            nation\n",
+       "0     1 2015-01-02     319  2015  Northern Ireland\n",
+       "1     2 2015-01-09     373  2015  Northern Ireland\n",
+       "2     3 2015-01-16     383  2015  Northern Ireland\n",
+       "3     4 2015-01-23     397  2015  Northern Ireland\n",
+       "4     5 2015-01-30     374  2015  Northern Ireland"
+      ]
+     },
+     "execution_count": 400,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = raw_data_2015.iloc[:, [0, 2, 3]].droplevel(1, axis=1).rename(\n",
+    "    columns={'Week Ends (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2015P)': 'deaths',\n",
+    "            'Registration Week': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2015\n",
+    "rd['nation'] = 'Northern Ireland'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 401,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 402,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "10 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>week</th>\n",
+       "            <th>year</th>\n",
+       "            <th>date_up_to</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>deaths</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>1</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-01-02</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>319</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-01-09</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>373</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>3</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-01-16</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>383</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>4</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-01-23</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>397</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>5</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-01-30</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>374</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>6</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-02-06</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>347</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>7</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-02-13</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>328</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>8</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-02-20</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>317</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>9</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-02-27</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>401</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>10</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-03-06</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>346</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(1, 2015, datetime.date(2015, 1, 2), 'Northern Ireland', 319),\n",
+       " (2, 2015, datetime.date(2015, 1, 9), 'Northern Ireland', 373),\n",
+       " (3, 2015, datetime.date(2015, 1, 16), 'Northern Ireland', 383),\n",
+       " (4, 2015, datetime.date(2015, 1, 23), 'Northern Ireland', 397),\n",
+       " (5, 2015, datetime.date(2015, 1, 30), 'Northern Ireland', 374),\n",
+       " (6, 2015, datetime.date(2015, 2, 6), 'Northern Ireland', 347),\n",
+       " (7, 2015, datetime.date(2015, 2, 13), 'Northern Ireland', 328),\n",
+       " (8, 2015, datetime.date(2015, 2, 20), 'Northern Ireland', 317),\n",
+       " (9, 2015, datetime.date(2015, 2, 27), 'Northern Ireland', 401),\n",
+       " (10, 2015, datetime.date(2015, 3, 6), 'Northern Ireland', 346)]"
+      ]
+     },
+     "execution_count": 402,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select * from all_causes_deaths limit 10"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 526,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>total_2016</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>(Registration Week, Unnamed: 0_level_1)</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>303</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>322</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>324</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>360</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>199</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                         total_2016\n",
+       "(Registration Week, Unnamed: 0_level_1)            \n",
+       "48                                              303\n",
+       "49                                              322\n",
+       "50                                              324\n",
+       "51                                              360\n",
+       "52                                              199"
+      ]
+     },
+     "execution_count": 526,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data_2016 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2016.csv', \n",
+    "                        parse_dates=[1, 2], dayfirst=True,\n",
+    "#                       index_col=0,\n",
+    "                      header=[0, 1]\n",
+    "                           )\n",
+    "raw_data_2016.head()\n",
+    "# dh16i = raw_data_2016.iloc[:, [2]]\n",
+    "# dh16i.columns = ['total_2016']\n",
+    "# # dh16i.head()\n",
+    "dh16i = raw_data_2016.iloc[:, [0, 3]]\n",
+    "dh16i.set_index(dh16i.columns[0], inplace=True)\n",
+    "dh16i.columns = ['total_2016']\n",
+    "dh16i.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 404,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2016-01-08</td>\n",
+       "      <td>424</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2016-01-15</td>\n",
+       "      <td>348</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2016-01-22</td>\n",
+       "      <td>372</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2016-01-29</td>\n",
+       "      <td>355</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2016-02-05</td>\n",
+       "      <td>314</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week date_up_to  deaths  year            nation\n",
+       "0     1 2016-01-08     424  2016  Northern Ireland\n",
+       "1     2 2016-01-15     348  2016  Northern Ireland\n",
+       "2     3 2016-01-22     372  2016  Northern Ireland\n",
+       "3     4 2016-01-29     355  2016  Northern Ireland\n",
+       "4     5 2016-02-05     314  2016  Northern Ireland"
+      ]
+     },
+     "execution_count": 404,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = raw_data_2016.iloc[:, [0, 2, 3]].droplevel(1, axis=1).rename(\n",
+    "    columns={'Week Ends (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2016P)': 'deaths',\n",
+    "            'Registration Week': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2016\n",
+    "rd['nation'] = 'Northern Ireland'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 405,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 406,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "2 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2015, 'Northern Ireland', 53), (2016, 'Northern Ireland', 52)]"
+      ]
+     },
+     "execution_count": 406,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 527,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>total_2017</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>(Registration Week, Unnamed: 0_level_1)</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>355</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>324</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>372</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>354</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>249</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                         total_2017\n",
+       "(Registration Week, Unnamed: 0_level_1)            \n",
+       "48                                              355\n",
+       "49                                              324\n",
+       "50                                              372\n",
+       "51                                              354\n",
+       "52                                              249"
+      ]
+     },
+     "execution_count": 527,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data_2017 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2017.csv', \n",
+    "                        parse_dates=[1, 2], dayfirst=True,\n",
+    "#                       index_col=0,\n",
+    "                      header=[0, 1]\n",
+    "                           )\n",
+    "raw_data_2017.head()\n",
+    "dh17i = raw_data_2017.iloc[:, [0, 3]]\n",
+    "dh17i.set_index(dh17i.columns[0], inplace=True)\n",
+    "dh17i.columns = ['total_2017']\n",
+    "dh17i.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 408,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2017-01-06</td>\n",
+       "      <td>416</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2017-01-13</td>\n",
+       "      <td>434</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2017-01-20</td>\n",
+       "      <td>397</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2017-01-27</td>\n",
+       "      <td>387</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2017-02-03</td>\n",
+       "      <td>371</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week date_up_to  deaths  year            nation\n",
+       "0     1 2017-01-06     416  2017  Northern Ireland\n",
+       "1     2 2017-01-13     434  2017  Northern Ireland\n",
+       "2     3 2017-01-20     397  2017  Northern Ireland\n",
+       "3     4 2017-01-27     387  2017  Northern Ireland\n",
+       "4     5 2017-02-03     371  2017  Northern Ireland"
+      ]
+     },
+     "execution_count": 408,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = raw_data_2017.iloc[:, [0, 2, 3]].droplevel(1, axis=1).rename(\n",
+    "    columns={'Week Ends (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2017P)': 'deaths',\n",
+    "            'Registration Week': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2017\n",
+    "rd['nation'] = 'Northern Ireland'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 409,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 410,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "3 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2015, 'Northern Ireland', 53),\n",
+       " (2017, 'Northern Ireland', 52),\n",
+       " (2016, 'Northern Ireland', 52)]"
+      ]
+     },
+     "execution_count": 410,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 528,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>total_2018</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>(Registration Week, Unnamed: 0_level_1)</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>297</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>324</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>316</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>317</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>195</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                         total_2018\n",
+       "(Registration Week, Unnamed: 0_level_1)            \n",
+       "48                                              297\n",
+       "49                                              324\n",
+       "50                                              316\n",
+       "51                                              317\n",
+       "52                                              195"
+      ]
+     },
+     "execution_count": 528,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data_2018 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2018.csv', \n",
+    "                        parse_dates=[1, 2], dayfirst=True,\n",
+    "#                       index_col=0,\n",
+    "                      header=[0, 1]\n",
+    "                           )\n",
+    "raw_data_2018.head()\n",
+    "dh18i = raw_data_2018.iloc[:, [0, 3]]\n",
+    "dh18i.set_index(dh18i.columns[0], inplace=True)\n",
+    "dh18i.columns = ['total_2018']\n",
+    "dh18i.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 412,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2018-01-05</td>\n",
+       "      <td>447</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2018-01-12</td>\n",
+       "      <td>481</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2018-01-19</td>\n",
+       "      <td>470</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2018-01-26</td>\n",
+       "      <td>426</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2018-02-02</td>\n",
+       "      <td>433</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week date_up_to  deaths  year            nation\n",
+       "0     1 2018-01-05     447  2018  Northern Ireland\n",
+       "1     2 2018-01-12     481  2018  Northern Ireland\n",
+       "2     3 2018-01-19     470  2018  Northern Ireland\n",
+       "3     4 2018-01-26     426  2018  Northern Ireland\n",
+       "4     5 2018-02-02     433  2018  Northern Ireland"
+      ]
+     },
+     "execution_count": 412,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = raw_data_2018.iloc[:, [0, 2, 3]].droplevel(1, axis=1).rename(\n",
+    "    columns={'Week Ends (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2018P)': 'deaths',\n",
+    "            'Registration Week': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2018\n",
+    "rd['nation'] = 'Northern Ireland'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 413,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 414,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "4 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2015, 'Northern Ireland', 53),\n",
+       " (2018, 'Northern Ireland', 52),\n",
+       " (2017, 'Northern Ireland', 52),\n",
+       " (2016, 'Northern Ireland', 52)]"
+      ]
+     },
+     "execution_count": 414,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 529,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>total_2019</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>(Registration Week, Unnamed: 0_level_1)</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>334</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>351</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>353</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>363</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>194</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                         total_2019\n",
+       "(Registration Week, Unnamed: 0_level_1)            \n",
+       "48                                              334\n",
+       "49                                              351\n",
+       "50                                              353\n",
+       "51                                              363\n",
+       "52                                              194"
+      ]
+     },
+     "execution_count": 529,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data_2019 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2019.csv', \n",
+    "                        parse_dates=[1, 2], dayfirst=True,\n",
+    "#                       index_col=0,\n",
+    "                      header=[0, 1]\n",
+    "                           )\n",
+    "raw_data_2019.head()\n",
+    "dh19i = raw_data_2019.iloc[:, [0, 3]]\n",
+    "dh19i.set_index(dh19i.columns[0], inplace=True)\n",
+    "dh19i.columns = ['total_2019']\n",
+    "dh19i.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 416,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2019-01-04</td>\n",
+       "      <td>365</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2019-01-11</td>\n",
+       "      <td>371</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2019-01-18</td>\n",
+       "      <td>332</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2019-01-25</td>\n",
+       "      <td>335</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2019-02-01</td>\n",
+       "      <td>296</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week date_up_to  deaths  year            nation\n",
+       "0     1 2019-01-04     365  2019  Northern Ireland\n",
+       "1     2 2019-01-11     371  2019  Northern Ireland\n",
+       "2     3 2019-01-18     332  2019  Northern Ireland\n",
+       "3     4 2019-01-25     335  2019  Northern Ireland\n",
+       "4     5 2019-02-01     296  2019  Northern Ireland"
+      ]
+     },
+     "execution_count": 416,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = raw_data_2019.iloc[:, [0, 2, 3]].droplevel(1, axis=1).rename(\n",
+    "    columns={'Week Ends (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2019P)': 'deaths',\n",
+    "            'Registration Week': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2019\n",
+    "rd['nation'] = 'Northern Ireland'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 417,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 418,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "5 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2015, 'Northern Ireland', 53),\n",
+       " (2018, 'Northern Ireland', 52),\n",
+       " (2019, 'Northern Ireland', 52),\n",
+       " (2017, 'Northern Ireland', 52),\n",
+       " (2016, 'Northern Ireland', 52)]"
+      ]
+     },
+     "execution_count": 418,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 419,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead tr th {\n",
+       "        text-align: left;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th>Registration Week</th>\n",
+       "      <th>Week Ending (Friday)</th>\n",
+       "      <th>Total Number of Deaths Registered in Week (2020P)</th>\n",
+       "      <th>Average number of deaths registered in corresponding week over previous 5 years (2015 to 2019P)</th>\n",
+       "      <th>Range</th>\n",
+       "      <th>Unnamed: 5_level_0</th>\n",
+       "      <th>Respiratory2 deaths registered in week (2020P)</th>\n",
+       "      <th>Average number of respiratory2 deaths registered in corresponding week over previous 5 years (2015 to 2019P)</th>\n",
+       "      <th>Covid-193 deaths registered in week (2020P)</th>\n",
+       "      <th>Unnamed: 9_level_0</th>\n",
+       "      <th>Unnamed: 10_level_0</th>\n",
+       "      <th>Unnamed: 11_level_0</th>\n",
+       "      <th>Unnamed: 12_level_0</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th>Unnamed: 0_level_1</th>\n",
+       "      <th>Unnamed: 1_level_1</th>\n",
+       "      <th>Unnamed: 2_level_1</th>\n",
+       "      <th>Unnamed: 3_level_1</th>\n",
+       "      <th>Minimum in Previous 5 years</th>\n",
+       "      <th>Maximum in Previous 5 years</th>\n",
+       "      <th>Unnamed: 6_level_1</th>\n",
+       "      <th>Unnamed: 7_level_1</th>\n",
+       "      <th>Unnamed: 8_level_1</th>\n",
+       "      <th>Unnamed: 9_level_1</th>\n",
+       "      <th>Unnamed: 10_level_1</th>\n",
+       "      <th>Unnamed: 11_level_1</th>\n",
+       "      <th>Unnamed: 12_level_1</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-01-03</td>\n",
+       "      <td>353</td>\n",
+       "      <td>250.0</td>\n",
+       "      <td>199</td>\n",
+       "      <td>365</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2020-01-10</td>\n",
+       "      <td>395</td>\n",
+       "      <td>402.2</td>\n",
+       "      <td>319</td>\n",
+       "      <td>481</td>\n",
+       "      <td>131</td>\n",
+       "      <td>144</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2020-01-17</td>\n",
+       "      <td>411</td>\n",
+       "      <td>391.4</td>\n",
+       "      <td>332</td>\n",
+       "      <td>470</td>\n",
+       "      <td>116</td>\n",
+       "      <td>127.6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2020-01-24</td>\n",
+       "      <td>347</td>\n",
+       "      <td>382.6</td>\n",
+       "      <td>335</td>\n",
+       "      <td>426</td>\n",
+       "      <td>113</td>\n",
+       "      <td>123.8</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2020-01-31</td>\n",
+       "      <td>323</td>\n",
+       "      <td>373.6</td>\n",
+       "      <td>296</td>\n",
+       "      <td>433</td>\n",
+       "      <td>78</td>\n",
+       "      <td>124</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Registration Week Week Ending (Friday)  \\\n",
+       "  Unnamed: 0_level_1   Unnamed: 1_level_1   \n",
+       "0                  1           2020-01-03   \n",
+       "1                  2           2020-01-10   \n",
+       "2                  3           2020-01-17   \n",
+       "3                  4           2020-01-24   \n",
+       "4                  5           2020-01-31   \n",
+       "\n",
+       "  Total Number of Deaths Registered in Week (2020P)  \\\n",
+       "                                 Unnamed: 2_level_1   \n",
+       "0                                               353   \n",
+       "1                                               395   \n",
+       "2                                               411   \n",
+       "3                                               347   \n",
+       "4                                               323   \n",
+       "\n",
+       "  Average number of deaths registered in corresponding week over previous 5 years (2015 to 2019P)  \\\n",
+       "                                                                               Unnamed: 3_level_1   \n",
+       "0                                              250.0                                                \n",
+       "1                                              402.2                                                \n",
+       "2                                              391.4                                                \n",
+       "3                                              382.6                                                \n",
+       "4                                              373.6                                                \n",
+       "\n",
+       "                        Range          Unnamed: 5_level_0  \\\n",
+       "  Minimum in Previous 5 years Maximum in Previous 5 years   \n",
+       "0                         199                         365   \n",
+       "1                         319                         481   \n",
+       "2                         332                         470   \n",
+       "3                         335                         426   \n",
+       "4                         296                         433   \n",
+       "\n",
+       "  Respiratory2 deaths registered in week (2020P)  \\\n",
+       "                              Unnamed: 6_level_1   \n",
+       "0                                              0   \n",
+       "1                                            131   \n",
+       "2                                            116   \n",
+       "3                                            113   \n",
+       "4                                             78   \n",
+       "\n",
+       "  Average number of respiratory2 deaths registered in corresponding week over previous 5 years (2015 to 2019P)  \\\n",
+       "                                                                                            Unnamed: 7_level_1   \n",
+       "0                                                  0                                                             \n",
+       "1                                                144                                                             \n",
+       "2                                              127.6                                                             \n",
+       "3                                              123.8                                                             \n",
+       "4                                                124                                                             \n",
+       "\n",
+       "  Covid-193 deaths registered in week (2020P) Unnamed: 9_level_0  \\\n",
+       "                           Unnamed: 8_level_1 Unnamed: 9_level_1   \n",
+       "0                                           0                NaN   \n",
+       "1                                           0                NaN   \n",
+       "2                                           0                NaN   \n",
+       "3                                           0                NaN   \n",
+       "4                                           0                NaN   \n",
+       "\n",
+       "  Unnamed: 10_level_0 Unnamed: 11_level_0 Unnamed: 12_level_0  \n",
+       "  Unnamed: 10_level_1 Unnamed: 11_level_1 Unnamed: 12_level_1  \n",
+       "0                 NaN                 NaN                 NaN  \n",
+       "1                 NaN                 NaN                 NaN  \n",
+       "2                 NaN                 NaN                 NaN  \n",
+       "3                 NaN                 NaN                 NaN  \n",
+       "4                 NaN                 NaN                 NaN  "
+      ]
+     },
+     "execution_count": 419,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data_2020_i = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2020.csv', \n",
+    "                        parse_dates=[1], dayfirst=True,\n",
+    "                      header=[0, 1]\n",
+    "                           )\n",
+    "raw_data_2020_i.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 420,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-01-03</td>\n",
+       "      <td>353</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2020-01-10</td>\n",
+       "      <td>395</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2020-01-17</td>\n",
+       "      <td>411</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2020-01-24</td>\n",
+       "      <td>347</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2020-01-31</td>\n",
+       "      <td>323</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week date_up_to  deaths  year            nation\n",
+       "0     1 2020-01-03     353  2020  Northern Ireland\n",
+       "1     2 2020-01-10     395  2020  Northern Ireland\n",
+       "2     3 2020-01-17     411  2020  Northern Ireland\n",
+       "3     4 2020-01-24     347  2020  Northern Ireland\n",
+       "4     5 2020-01-31     323  2020  Northern Ireland"
+      ]
+     },
+     "execution_count": 420,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = raw_data_2020_i.iloc[:, [0, 1, 2]].droplevel(1, axis=1).rename(\n",
+    "    columns={'Week Ending (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2020P)': 'deaths',\n",
+    "            'Registration Week': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2020\n",
+    "rd['nation'] = 'Northern Ireland'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 421,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>49</td>\n",
+       "      <td>2020-12-04</td>\n",
+       "      <td>387</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>50</td>\n",
+       "      <td>2020-12-11</td>\n",
+       "      <td>366</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>51</td>\n",
+       "      <td>2020-12-18</td>\n",
+       "      <td>350</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>52</td>\n",
+       "      <td>2020-12-25</td>\n",
+       "      <td>310</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>53</td>\n",
+       "      <td>2021-01-01</td>\n",
+       "      <td>333</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    week date_up_to  deaths  year            nation\n",
+       "48    49 2020-12-04     387  2020  Northern Ireland\n",
+       "49    50 2020-12-11     366  2020  Northern Ireland\n",
+       "50    51 2020-12-18     350  2020  Northern Ireland\n",
+       "51    52 2020-12-25     310  2020  Northern Ireland\n",
+       "52    53 2021-01-01     333  2020  Northern Ireland"
+      ]
+     },
+     "execution_count": 421,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 422,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 423,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "6 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2015, 'Northern Ireland', 53),\n",
+       " (2016, 'Northern Ireland', 52),\n",
+       " (2017, 'Northern Ireland', 52),\n",
+       " (2018, 'Northern Ireland', 52),\n",
+       " (2019, 'Northern Ireland', 52),\n",
+       " (2020, 'Northern Ireland', 53)]"
+      ]
+     },
+     "execution_count": 423,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 521,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead tr th {\n",
+       "        text-align: left;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead tr:last-of-type th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th>Week Ending (Friday)</th>\n",
+       "      <th>Total Number of Deaths Registered in Week (2020P)</th>\n",
+       "      <th>Average number of deaths registered in corresponding week over previous 5 years (2015 to 2019P)</th>\n",
+       "      <th>Range</th>\n",
+       "      <th>Unnamed: 5_level_0</th>\n",
+       "      <th>Respiratory2 deaths registered in week (2020P)</th>\n",
+       "      <th>Average number of respiratory2 deaths registered in corresponding week over previous 5 years (2015 to 2019P)</th>\n",
+       "      <th>Covid-193 deaths registered in week (2020P)</th>\n",
+       "      <th>Unnamed: 9_level_0</th>\n",
+       "      <th>Unnamed: 10_level_0</th>\n",
+       "      <th>Unnamed: 11_level_0</th>\n",
+       "      <th>Unnamed: 12_level_0</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th>Unnamed: 1_level_1</th>\n",
+       "      <th>Unnamed: 2_level_1</th>\n",
+       "      <th>Unnamed: 3_level_1</th>\n",
+       "      <th>Minimum in Previous 5 years</th>\n",
+       "      <th>Maximum in Previous 5 years</th>\n",
+       "      <th>Unnamed: 6_level_1</th>\n",
+       "      <th>Unnamed: 7_level_1</th>\n",
+       "      <th>Unnamed: 8_level_1</th>\n",
+       "      <th>Unnamed: 9_level_1</th>\n",
+       "      <th>Unnamed: 10_level_1</th>\n",
+       "      <th>Unnamed: 11_level_1</th>\n",
+       "      <th>Unnamed: 12_level_1</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>(Registration Week, Unnamed: 0_level_1)</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>2020-12-04</td>\n",
+       "      <td>387</td>\n",
+       "      <td>322.0</td>\n",
+       "      <td>279</td>\n",
+       "      <td>355</td>\n",
+       "      <td>-</td>\n",
+       "      <td>-</td>\n",
+       "      <td>-</td>\n",
+       "      <td>155.0</td>\n",
+       "      <td>87.0</td>\n",
+       "      <td>-</td>\n",
+       "      <td>98.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>2020-12-11</td>\n",
+       "      <td>366</td>\n",
+       "      <td>322.0</td>\n",
+       "      <td>294</td>\n",
+       "      <td>353</td>\n",
+       "      <td>-</td>\n",
+       "      <td>-</td>\n",
+       "      <td>-</td>\n",
+       "      <td>138.0</td>\n",
+       "      <td>93.0</td>\n",
+       "      <td>-</td>\n",
+       "      <td>87.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>2020-12-18</td>\n",
+       "      <td>350</td>\n",
+       "      <td>344.0</td>\n",
+       "      <td>317</td>\n",
+       "      <td>372</td>\n",
+       "      <td>-</td>\n",
+       "      <td>-</td>\n",
+       "      <td>-</td>\n",
+       "      <td>140.0</td>\n",
+       "      <td>102.0</td>\n",
+       "      <td>-</td>\n",
+       "      <td>82.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>2020-12-25</td>\n",
+       "      <td>310</td>\n",
+       "      <td>281.0</td>\n",
+       "      <td>194</td>\n",
+       "      <td>360</td>\n",
+       "      <td>-</td>\n",
+       "      <td>-</td>\n",
+       "      <td>-</td>\n",
+       "      <td>132.0</td>\n",
+       "      <td>92.0</td>\n",
+       "      <td>-</td>\n",
+       "      <td>88.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>2021-01-01</td>\n",
+       "      <td>333</td>\n",
+       "      <td>280.0</td>\n",
+       "      <td>199</td>\n",
+       "      <td>365</td>\n",
+       "      <td>-</td>\n",
+       "      <td>-</td>\n",
+       "      <td>-</td>\n",
+       "      <td>146.0</td>\n",
+       "      <td>97.0</td>\n",
+       "      <td>-</td>\n",
+       "      <td>94.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                        Week Ending (Friday)  \\\n",
+       "                                          Unnamed: 1_level_1   \n",
+       "(Registration Week, Unnamed: 0_level_1)                        \n",
+       "49                                                2020-12-04   \n",
+       "50                                                2020-12-11   \n",
+       "51                                                2020-12-18   \n",
+       "52                                                2020-12-25   \n",
+       "53                                                2021-01-01   \n",
+       "\n",
+       "                                        Total Number of Deaths Registered in Week (2020P)  \\\n",
+       "                                                                       Unnamed: 2_level_1   \n",
+       "(Registration Week, Unnamed: 0_level_1)                                                     \n",
+       "49                                                                                    387   \n",
+       "50                                                                                    366   \n",
+       "51                                                                                    350   \n",
+       "52                                                                                    310   \n",
+       "53                                                                                    333   \n",
+       "\n",
+       "                                        Average number of deaths registered in corresponding week over previous 5 years (2015 to 2019P)  \\\n",
+       "                                                                                                                     Unnamed: 3_level_1   \n",
+       "(Registration Week, Unnamed: 0_level_1)                                                                                                   \n",
+       "49                                                                                   322.0                                                \n",
+       "50                                                                                   322.0                                                \n",
+       "51                                                                                   344.0                                                \n",
+       "52                                                                                   281.0                                                \n",
+       "53                                                                                   280.0                                                \n",
+       "\n",
+       "                                                              Range  \\\n",
+       "                                        Minimum in Previous 5 years   \n",
+       "(Registration Week, Unnamed: 0_level_1)                               \n",
+       "49                                                              279   \n",
+       "50                                                              294   \n",
+       "51                                                              317   \n",
+       "52                                                              194   \n",
+       "53                                                              199   \n",
+       "\n",
+       "                                                 Unnamed: 5_level_0  \\\n",
+       "                                        Maximum in Previous 5 years   \n",
+       "(Registration Week, Unnamed: 0_level_1)                               \n",
+       "49                                                              355   \n",
+       "50                                                              353   \n",
+       "51                                                              372   \n",
+       "52                                                              360   \n",
+       "53                                                              365   \n",
+       "\n",
+       "                                        Respiratory2 deaths registered in week (2020P)  \\\n",
+       "                                                                    Unnamed: 6_level_1   \n",
+       "(Registration Week, Unnamed: 0_level_1)                                                  \n",
+       "49                                                                                   -   \n",
+       "50                                                                                   -   \n",
+       "51                                                                                   -   \n",
+       "52                                                                                   -   \n",
+       "53                                                                                   -   \n",
+       "\n",
+       "                                        Average number of respiratory2 deaths registered in corresponding week over previous 5 years (2015 to 2019P)  \\\n",
+       "                                                                                                                                  Unnamed: 7_level_1   \n",
+       "(Registration Week, Unnamed: 0_level_1)                                                                                                                \n",
+       "49                                                                                       -                                                             \n",
+       "50                                                                                       -                                                             \n",
+       "51                                                                                       -                                                             \n",
+       "52                                                                                       -                                                             \n",
+       "53                                                                                       -                                                             \n",
+       "\n",
+       "                                        Covid-193 deaths registered in week (2020P)  \\\n",
+       "                                                                 Unnamed: 8_level_1   \n",
+       "(Registration Week, Unnamed: 0_level_1)                                               \n",
+       "49                                                                                -   \n",
+       "50                                                                                -   \n",
+       "51                                                                                -   \n",
+       "52                                                                                -   \n",
+       "53                                                                                -   \n",
+       "\n",
+       "                                        Unnamed: 9_level_0  \\\n",
+       "                                        Unnamed: 9_level_1   \n",
+       "(Registration Week, Unnamed: 0_level_1)                      \n",
+       "49                                                   155.0   \n",
+       "50                                                   138.0   \n",
+       "51                                                   140.0   \n",
+       "52                                                   132.0   \n",
+       "53                                                   146.0   \n",
+       "\n",
+       "                                        Unnamed: 10_level_0  \\\n",
+       "                                        Unnamed: 10_level_1   \n",
+       "(Registration Week, Unnamed: 0_level_1)                       \n",
+       "49                                                     87.0   \n",
+       "50                                                     93.0   \n",
+       "51                                                    102.0   \n",
+       "52                                                     92.0   \n",
+       "53                                                     97.0   \n",
+       "\n",
+       "                                        Unnamed: 11_level_0  \\\n",
+       "                                        Unnamed: 11_level_1   \n",
+       "(Registration Week, Unnamed: 0_level_1)                       \n",
+       "49                                                        -   \n",
+       "50                                                        -   \n",
+       "51                                                        -   \n",
+       "52                                                        -   \n",
+       "53                                                        -   \n",
+       "\n",
+       "                                        Unnamed: 12_level_0  \n",
+       "                                        Unnamed: 12_level_1  \n",
+       "(Registration Week, Unnamed: 0_level_1)                      \n",
+       "49                                                     98.0  \n",
+       "50                                                     87.0  \n",
+       "51                                                     82.0  \n",
+       "52                                                     88.0  \n",
+       "53                                                     94.0  "
+      ]
+     },
+     "execution_count": 521,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data_2020_i.set_index(raw_data_2020_i.columns[0], inplace=True)\n",
+    "raw_data_2020_i.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 424,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(2021, 3, 1)"
+      ]
+     },
+     "execution_count": 424,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "datetime.datetime.now().isocalendar()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 425,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "datetime.datetime(2021, 1, 18, 0, 0)"
+      ]
+     },
+     "execution_count": 425,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "datetime.datetime.fromisocalendar(2021, 3, 1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 426,
+   "metadata": {
+    "Collapsed": "false",
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "raw_data_s = pd.read_csv('uk-deaths-data/weekly-deaths-scotland.csv', \n",
+    "                      index_col=0,\n",
+    "                      header=0,\n",
+    "                        skiprows=2\n",
+    "                           )\n",
+    "# raw_data_s"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 427,
+   "metadata": {
+    "Collapsed": "false",
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>total_2020</th>\n",
+       "      <th>total_2019</th>\n",
+       "      <th>total_2018</th>\n",
+       "      <th>total_2017</th>\n",
+       "      <th>total_2016</th>\n",
+       "      <th>total_2015</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1161</td>\n",
+       "      <td>1104.0</td>\n",
+       "      <td>1531.0</td>\n",
+       "      <td>1205.0</td>\n",
+       "      <td>1394.0</td>\n",
+       "      <td>1146</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1567</td>\n",
+       "      <td>1507.0</td>\n",
+       "      <td>1899.0</td>\n",
+       "      <td>1379.0</td>\n",
+       "      <td>1305.0</td>\n",
+       "      <td>1708</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1322</td>\n",
+       "      <td>1353.0</td>\n",
+       "      <td>1629.0</td>\n",
+       "      <td>1224.0</td>\n",
+       "      <td>1215.0</td>\n",
+       "      <td>1489</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1226</td>\n",
+       "      <td>1208.0</td>\n",
+       "      <td>1610.0</td>\n",
+       "      <td>1197.0</td>\n",
+       "      <td>1187.0</td>\n",
+       "      <td>1381</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>1188</td>\n",
+       "      <td>1206.0</td>\n",
+       "      <td>1369.0</td>\n",
+       "      <td>1332.0</td>\n",
+       "      <td>1205.0</td>\n",
+       "      <td>1286</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>1216</td>\n",
+       "      <td>1243.0</td>\n",
+       "      <td>1265.0</td>\n",
+       "      <td>1200.0</td>\n",
+       "      <td>1217.0</td>\n",
+       "      <td>1344</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>1162</td>\n",
+       "      <td>1181.0</td>\n",
+       "      <td>1315.0</td>\n",
+       "      <td>1231.0</td>\n",
+       "      <td>1209.0</td>\n",
+       "      <td>1360</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>1162</td>\n",
+       "      <td>1245.0</td>\n",
+       "      <td>1245.0</td>\n",
+       "      <td>1185.0</td>\n",
+       "      <td>1239.0</td>\n",
+       "      <td>1320</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>1171</td>\n",
+       "      <td>1125.0</td>\n",
+       "      <td>1022.0</td>\n",
+       "      <td>1219.0</td>\n",
+       "      <td>1150.0</td>\n",
+       "      <td>1308</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>1208</td>\n",
+       "      <td>1156.0</td>\n",
+       "      <td>1475.0</td>\n",
+       "      <td>1146.0</td>\n",
+       "      <td>1174.0</td>\n",
+       "      <td>1192</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>1156</td>\n",
+       "      <td>1108.0</td>\n",
+       "      <td>1220.0</td>\n",
+       "      <td>1141.0</td>\n",
+       "      <td>1175.0</td>\n",
+       "      <td>1201</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>1196</td>\n",
+       "      <td>1101.0</td>\n",
+       "      <td>1158.0</td>\n",
+       "      <td>1152.0</td>\n",
+       "      <td>1042.0</td>\n",
+       "      <td>1149</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>1079</td>\n",
+       "      <td>1086.0</td>\n",
+       "      <td>1050.0</td>\n",
+       "      <td>1112.0</td>\n",
+       "      <td>1172.0</td>\n",
+       "      <td>1171</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>1744</td>\n",
+       "      <td>1032.0</td>\n",
+       "      <td>1192.0</td>\n",
+       "      <td>1060.0</td>\n",
+       "      <td>1166.0</td>\n",
+       "      <td>1042</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>1978</td>\n",
+       "      <td>1069.0</td>\n",
+       "      <td>1192.0</td>\n",
+       "      <td>998.0</td>\n",
+       "      <td>1048.0</td>\n",
+       "      <td>1192</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>1916</td>\n",
+       "      <td>902.0</td>\n",
+       "      <td>1136.0</td>\n",
+       "      <td>1111.0</td>\n",
+       "      <td>1092.0</td>\n",
+       "      <td>1095</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>1836</td>\n",
+       "      <td>1121.0</td>\n",
+       "      <td>1008.0</td>\n",
+       "      <td>1121.0</td>\n",
+       "      <td>1076.0</td>\n",
+       "      <td>1108</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>1679</td>\n",
+       "      <td>1131.0</td>\n",
+       "      <td>1093.0</td>\n",
+       "      <td>1050.0</td>\n",
+       "      <td>1006.0</td>\n",
+       "      <td>1117</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>1435</td>\n",
+       "      <td>1018.0</td>\n",
+       "      <td>967.0</td>\n",
+       "      <td>1119.0</td>\n",
+       "      <td>1047.0</td>\n",
+       "      <td>1020</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>1421</td>\n",
+       "      <td>1115.0</td>\n",
+       "      <td>977.0</td>\n",
+       "      <td>1115.0</td>\n",
+       "      <td>1010.0</td>\n",
+       "      <td>1103</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>1226</td>\n",
+       "      <td>1061.0</td>\n",
+       "      <td>1070.0</td>\n",
+       "      <td>1063.0</td>\n",
+       "      <td>994.0</td>\n",
+       "      <td>1039</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>1125</td>\n",
+       "      <td>1029.0</td>\n",
+       "      <td>998.0</td>\n",
+       "      <td>1015.0</td>\n",
+       "      <td>999.0</td>\n",
+       "      <td>1043</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>1093</td>\n",
+       "      <td>1042.0</td>\n",
+       "      <td>1033.0</td>\n",
+       "      <td>1076.0</td>\n",
+       "      <td>1023.0</td>\n",
+       "      <td>1106</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>1034</td>\n",
+       "      <td>1028.0</td>\n",
+       "      <td>915.0</td>\n",
+       "      <td>1031.0</td>\n",
+       "      <td>988.0</td>\n",
+       "      <td>1038</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>1065</td>\n",
+       "      <td>1053.0</td>\n",
+       "      <td>993.0</td>\n",
+       "      <td>1032.0</td>\n",
+       "      <td>994.0</td>\n",
+       "      <td>1025</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>1008</td>\n",
+       "      <td>1051.0</td>\n",
+       "      <td>1046.0</td>\n",
+       "      <td>994.0</td>\n",
+       "      <td>1007.0</td>\n",
+       "      <td>1032</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>983</td>\n",
+       "      <td>981.0</td>\n",
+       "      <td>1041.0</td>\n",
+       "      <td>1040.0</td>\n",
+       "      <td>988.0</td>\n",
+       "      <td>1040</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>976</td>\n",
+       "      <td>1077.0</td>\n",
+       "      <td>1002.0</td>\n",
+       "      <td>1014.0</td>\n",
+       "      <td>1022.0</td>\n",
+       "      <td>1011</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>1033</td>\n",
+       "      <td>964.0</td>\n",
+       "      <td>928.0</td>\n",
+       "      <td>1025.0</td>\n",
+       "      <td>1041.0</td>\n",
+       "      <td>1023</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>961</td>\n",
+       "      <td>1041.0</td>\n",
+       "      <td>933.0</td>\n",
+       "      <td>978.0</td>\n",
+       "      <td>979.0</td>\n",
+       "      <td>956</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>1043</td>\n",
+       "      <td>1020.0</td>\n",
+       "      <td>969.0</td>\n",
+       "      <td>1011.0</td>\n",
+       "      <td>987.0</td>\n",
+       "      <td>985</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>1011</td>\n",
+       "      <td>1018.0</td>\n",
+       "      <td>953.0</td>\n",
+       "      <td>1002.0</td>\n",
+       "      <td>997.0</td>\n",
+       "      <td>1043</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>922</td>\n",
+       "      <td>1028.0</td>\n",
+       "      <td>978.0</td>\n",
+       "      <td>1004.0</td>\n",
+       "      <td>982.0</td>\n",
+       "      <td>969</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>1046</td>\n",
+       "      <td>1011.0</td>\n",
+       "      <td>941.0</td>\n",
+       "      <td>1045.0</td>\n",
+       "      <td>1017.0</td>\n",
+       "      <td>982</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>1029</td>\n",
+       "      <td>1013.0</td>\n",
+       "      <td>930.0</td>\n",
+       "      <td>980.0</td>\n",
+       "      <td>1039.0</td>\n",
+       "      <td>954</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>1050</td>\n",
+       "      <td>980.0</td>\n",
+       "      <td>970.0</td>\n",
+       "      <td>1006.0</td>\n",
+       "      <td>1007.0</td>\n",
+       "      <td>977</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>1069</td>\n",
+       "      <td>1074.0</td>\n",
+       "      <td>1020.0</td>\n",
+       "      <td>972.0</td>\n",
+       "      <td>983.0</td>\n",
+       "      <td>991</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>952</td>\n",
+       "      <td>1071.0</td>\n",
+       "      <td>946.0</td>\n",
+       "      <td>1049.0</td>\n",
+       "      <td>966.0</td>\n",
+       "      <td>1001</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>933</td>\n",
+       "      <td>1142.0</td>\n",
+       "      <td>1015.0</td>\n",
+       "      <td>1056.0</td>\n",
+       "      <td>1009.0</td>\n",
+       "      <td>1010</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>1195</td>\n",
+       "      <td>1051.0</td>\n",
+       "      <td>1042.0</td>\n",
+       "      <td>1016.0</td>\n",
+       "      <td>1072.0</td>\n",
+       "      <td>1008</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>1071</td>\n",
+       "      <td>1143.0</td>\n",
+       "      <td>1081.0</td>\n",
+       "      <td>1133.0</td>\n",
+       "      <td>1009.0</td>\n",
+       "      <td>1028</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>1131</td>\n",
+       "      <td>1153.0</td>\n",
+       "      <td>1031.0</td>\n",
+       "      <td>1067.0</td>\n",
+       "      <td>1070.0</td>\n",
+       "      <td>989</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>1187</td>\n",
+       "      <td>1115.0</td>\n",
+       "      <td>1019.0</td>\n",
+       "      <td>1095.0</td>\n",
+       "      <td>1052.0</td>\n",
+       "      <td>981</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>1262</td>\n",
+       "      <td>1101.0</td>\n",
+       "      <td>1085.0</td>\n",
+       "      <td>1062.0</td>\n",
+       "      <td>1032.0</td>\n",
+       "      <td>1116</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>1250</td>\n",
+       "      <td>1184.0</td>\n",
+       "      <td>1144.0</td>\n",
+       "      <td>1126.0</td>\n",
+       "      <td>1043.0</td>\n",
+       "      <td>1028</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>1138</td>\n",
+       "      <td>1160.0</td>\n",
+       "      <td>1084.0</td>\n",
+       "      <td>1175.0</td>\n",
+       "      <td>1174.0</td>\n",
+       "      <td>1103</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>1360</td>\n",
+       "      <td>1229.0</td>\n",
+       "      <td>1058.0</td>\n",
+       "      <td>1178.0</td>\n",
+       "      <td>1132.0</td>\n",
+       "      <td>1054</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>1328</td>\n",
+       "      <td>1163.0</td>\n",
+       "      <td>1062.0</td>\n",
+       "      <td>1153.0</td>\n",
+       "      <td>1159.0</td>\n",
+       "      <td>1115</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>1296</td>\n",
+       "      <td>1108.0</td>\n",
+       "      <td>1076.0</td>\n",
+       "      <td>1237.0</td>\n",
+       "      <td>1188.0</td>\n",
+       "      <td>1089</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>1284</td>\n",
+       "      <td>1312.0</td>\n",
+       "      <td>1212.0</td>\n",
+       "      <td>1335.0</td>\n",
+       "      <td>1219.0</td>\n",
+       "      <td>1101</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>1297</td>\n",
+       "      <td>1277.0</td>\n",
+       "      <td>1216.0</td>\n",
+       "      <td>1437.0</td>\n",
+       "      <td>1284.0</td>\n",
+       "      <td>1146</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>1205</td>\n",
+       "      <td>1000.0</td>\n",
+       "      <td>1058.0</td>\n",
+       "      <td>1168.0</td>\n",
+       "      <td>1133.0</td>\n",
+       "      <td>944</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>1178</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1018</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    total_2020  total_2019  total_2018  total_2017  total_2016  total_2015\n",
+       "1         1161      1104.0      1531.0      1205.0      1394.0        1146\n",
+       "2         1567      1507.0      1899.0      1379.0      1305.0        1708\n",
+       "3         1322      1353.0      1629.0      1224.0      1215.0        1489\n",
+       "4         1226      1208.0      1610.0      1197.0      1187.0        1381\n",
+       "5         1188      1206.0      1369.0      1332.0      1205.0        1286\n",
+       "6         1216      1243.0      1265.0      1200.0      1217.0        1344\n",
+       "7         1162      1181.0      1315.0      1231.0      1209.0        1360\n",
+       "8         1162      1245.0      1245.0      1185.0      1239.0        1320\n",
+       "9         1171      1125.0      1022.0      1219.0      1150.0        1308\n",
+       "10        1208      1156.0      1475.0      1146.0      1174.0        1192\n",
+       "11        1156      1108.0      1220.0      1141.0      1175.0        1201\n",
+       "12        1196      1101.0      1158.0      1152.0      1042.0        1149\n",
+       "13        1079      1086.0      1050.0      1112.0      1172.0        1171\n",
+       "14        1744      1032.0      1192.0      1060.0      1166.0        1042\n",
+       "15        1978      1069.0      1192.0       998.0      1048.0        1192\n",
+       "16        1916       902.0      1136.0      1111.0      1092.0        1095\n",
+       "17        1836      1121.0      1008.0      1121.0      1076.0        1108\n",
+       "18        1679      1131.0      1093.0      1050.0      1006.0        1117\n",
+       "19        1435      1018.0       967.0      1119.0      1047.0        1020\n",
+       "20        1421      1115.0       977.0      1115.0      1010.0        1103\n",
+       "21        1226      1061.0      1070.0      1063.0       994.0        1039\n",
+       "22        1125      1029.0       998.0      1015.0       999.0        1043\n",
+       "23        1093      1042.0      1033.0      1076.0      1023.0        1106\n",
+       "24        1034      1028.0       915.0      1031.0       988.0        1038\n",
+       "25        1065      1053.0       993.0      1032.0       994.0        1025\n",
+       "26        1008      1051.0      1046.0       994.0      1007.0        1032\n",
+       "27         983       981.0      1041.0      1040.0       988.0        1040\n",
+       "28         976      1077.0      1002.0      1014.0      1022.0        1011\n",
+       "29        1033       964.0       928.0      1025.0      1041.0        1023\n",
+       "30         961      1041.0       933.0       978.0       979.0         956\n",
+       "31        1043      1020.0       969.0      1011.0       987.0         985\n",
+       "32        1011      1018.0       953.0      1002.0       997.0        1043\n",
+       "33         922      1028.0       978.0      1004.0       982.0         969\n",
+       "34        1046      1011.0       941.0      1045.0      1017.0         982\n",
+       "35        1029      1013.0       930.0       980.0      1039.0         954\n",
+       "36        1050       980.0       970.0      1006.0      1007.0         977\n",
+       "37        1069      1074.0      1020.0       972.0       983.0         991\n",
+       "38         952      1071.0       946.0      1049.0       966.0        1001\n",
+       "39         933      1142.0      1015.0      1056.0      1009.0        1010\n",
+       "40        1195      1051.0      1042.0      1016.0      1072.0        1008\n",
+       "41        1071      1143.0      1081.0      1133.0      1009.0        1028\n",
+       "42        1131      1153.0      1031.0      1067.0      1070.0         989\n",
+       "43        1187      1115.0      1019.0      1095.0      1052.0         981\n",
+       "44        1262      1101.0      1085.0      1062.0      1032.0        1116\n",
+       "45        1250      1184.0      1144.0      1126.0      1043.0        1028\n",
+       "46        1138      1160.0      1084.0      1175.0      1174.0        1103\n",
+       "47        1360      1229.0      1058.0      1178.0      1132.0        1054\n",
+       "48        1328      1163.0      1062.0      1153.0      1159.0        1115\n",
+       "49        1296      1108.0      1076.0      1237.0      1188.0        1089\n",
+       "50        1284      1312.0      1212.0      1335.0      1219.0        1101\n",
+       "51        1297      1277.0      1216.0      1437.0      1284.0        1146\n",
+       "52        1205      1000.0      1058.0      1168.0      1133.0         944\n",
+       "53        1178         NaN         NaN         NaN         NaN        1018"
+      ]
+     },
+     "execution_count": 427,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_headlines_s = raw_data_s[reversed('2015 2016 2017 2018 2019 2020'.split())]\n",
+    "deaths_headlines_s.columns = ['total_' + c for c in deaths_headlines_s.columns]\n",
+    "deaths_headlines_s.reset_index(drop=True, inplace=True)\n",
+    "deaths_headlines_s.index = deaths_headlines_s.index + 1\n",
+    "deaths_headlines_s"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 428,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "5 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>week</th>\n",
+       "            <th>year</th>\n",
+       "            <th>date_up_to</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>deaths</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>1</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-01-02</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>319</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-01-09</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>373</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>3</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-01-16</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>383</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>4</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-01-23</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>397</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>5</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-01-30</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>374</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(1, 2015, datetime.date(2015, 1, 2), 'Northern Ireland', 319),\n",
+       " (2, 2015, datetime.date(2015, 1, 9), 'Northern Ireland', 373),\n",
+       " (3, 2015, datetime.date(2015, 1, 16), 'Northern Ireland', 383),\n",
+       " (4, 2015, datetime.date(2015, 1, 23), 'Northern Ireland', 397),\n",
+       " (5, 2015, datetime.date(2015, 1, 30), 'Northern Ireland', 374)]"
+      ]
+     },
+     "execution_count": 428,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select * from all_causes_deaths limit 5"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 429,
+   "metadata": {
+    "Collapsed": "false",
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n"
+     ]
+    }
+   ],
+   "source": [
+    "for year, ser in deaths_headlines_s.items():\n",
+    "    year_i = int(year[-4:])\n",
+    "#     print(year_i)\n",
+    "    for week, deaths in ser.dropna().iteritems():\n",
+    "#         print(datetime.date.fromisocalendar(year_i, week, 7), deaths)\n",
+    "        dut = datetime.date.fromisocalendar(year_i, week, 7)\n",
+    "        %sql insert into all_causes_deaths(week, year, date_up_to, nation, deaths) values ({week}, {year_i}, :dut, 'Scotland', {deaths})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 430,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "12 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2015, 'Northern Ireland', 53),\n",
+       " (2016, 'Northern Ireland', 52),\n",
+       " (2017, 'Northern Ireland', 52),\n",
+       " (2018, 'Northern Ireland', 52),\n",
+       " (2019, 'Northern Ireland', 52),\n",
+       " (2020, 'Northern Ireland', 53),\n",
+       " (2015, 'Scotland', 53),\n",
+       " (2016, 'Scotland', 52),\n",
+       " (2017, 'Scotland', 52),\n",
+       " (2018, 'Scotland', 52),\n",
+       " (2019, 'Scotland', 52),\n",
+       " (2020, 'Scotland', 53)]"
+      ]
+     },
+     "execution_count": 430,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 431,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "12 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>date_up_to</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>2015-01-16</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>2015-01-18</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>2016-01-22</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>2016-01-24</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>2017-01-20</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>2017-01-22</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>2018-01-19</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>2018-01-21</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>2019-01-18</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>2019-01-20</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>2020-01-17</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>2020-01-19</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2015, 'Northern Ireland', datetime.date(2015, 1, 16)),\n",
+       " (2015, 'Scotland', datetime.date(2015, 1, 18)),\n",
+       " (2016, 'Northern Ireland', datetime.date(2016, 1, 22)),\n",
+       " (2016, 'Scotland', datetime.date(2016, 1, 24)),\n",
+       " (2017, 'Northern Ireland', datetime.date(2017, 1, 20)),\n",
+       " (2017, 'Scotland', datetime.date(2017, 1, 22)),\n",
+       " (2018, 'Northern Ireland', datetime.date(2018, 1, 19)),\n",
+       " (2018, 'Scotland', datetime.date(2018, 1, 21)),\n",
+       " (2019, 'Northern Ireland', datetime.date(2019, 1, 18)),\n",
+       " (2019, 'Scotland', datetime.date(2019, 1, 20)),\n",
+       " (2020, 'Northern Ireland', datetime.date(2020, 1, 17)),\n",
+       " (2020, 'Scotland', datetime.date(2020, 1, 19))]"
+      ]
+     },
+     "execution_count": 431,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select year, nation, date_up_to from all_causes_deaths where week=3 order by year, nation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 432,
+   "metadata": {
+    "Collapsed": "false",
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>...</th>\n",
+       "      <th>North East</th>\n",
+       "      <th>North West</th>\n",
+       "      <th>Yorkshire and The Humber</th>\n",
+       "      <th>East Midlands</th>\n",
+       "      <th>West Midlands</th>\n",
+       "      <th>East</th>\n",
+       "      <th>London</th>\n",
+       "      <th>South East</th>\n",
+       "      <th>South West</th>\n",
+       "      <th>Wales</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Week number</th>\n",
+       "      <td>Week ended</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Total deaths, all ages</td>\n",
+       "      <td>Total deaths: average of corresponding</td>\n",
+       "      <td>week over the previous 5 years 1, 10, 11 (Engl...</td>\n",
+       "      <td>Total deaths: average of corresponding</td>\n",
+       "      <td>week over the previous 5 years 1, 10, 11 (Engl...</td>\n",
+       "      <td>Total deaths: average of corresponding</td>\n",
+       "      <td>week over the previous 5 years 1, 10, 11 (Wales)</td>\n",
+       "      <td>...</td>\n",
+       "      <td>E12000001</td>\n",
+       "      <td>E12000002</td>\n",
+       "      <td>E12000003</td>\n",
+       "      <td>E12000004</td>\n",
+       "      <td>E12000005</td>\n",
+       "      <td>E12000006</td>\n",
+       "      <td>E12000007</td>\n",
+       "      <td>E12000008</td>\n",
+       "      <td>E12000009</td>\n",
+       "      <td>W92000004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2020-01-03 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12254</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12175</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11412</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>756</td>\n",
+       "      <td>...</td>\n",
+       "      <td>673</td>\n",
+       "      <td>1806</td>\n",
+       "      <td>1240</td>\n",
+       "      <td>1060</td>\n",
+       "      <td>1349</td>\n",
+       "      <td>1162</td>\n",
+       "      <td>1113</td>\n",
+       "      <td>1814</td>\n",
+       "      <td>1225</td>\n",
+       "      <td>787</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2020-01-10 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14058</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13822</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12933</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>856</td>\n",
+       "      <td>...</td>\n",
+       "      <td>707</td>\n",
+       "      <td>1932</td>\n",
+       "      <td>1339</td>\n",
+       "      <td>1195</td>\n",
+       "      <td>1450</td>\n",
+       "      <td>1573</td>\n",
+       "      <td>1272</td>\n",
+       "      <td>2132</td>\n",
+       "      <td>1487</td>\n",
+       "      <td>939</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2020-01-17 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12990</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13216</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12370</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>812</td>\n",
+       "      <td>...</td>\n",
+       "      <td>647</td>\n",
+       "      <td>1696</td>\n",
+       "      <td>1278</td>\n",
+       "      <td>1106</td>\n",
+       "      <td>1407</td>\n",
+       "      <td>1457</td>\n",
+       "      <td>1073</td>\n",
+       "      <td>2064</td>\n",
+       "      <td>1466</td>\n",
+       "      <td>767</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2020-01-24 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11856</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12760</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11933</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>802</td>\n",
+       "      <td>...</td>\n",
+       "      <td>612</td>\n",
+       "      <td>1529</td>\n",
+       "      <td>1187</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>1231</td>\n",
+       "      <td>1410</td>\n",
+       "      <td>1028</td>\n",
+       "      <td>1833</td>\n",
+       "      <td>1253</td>\n",
+       "      <td>723</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2020-01-31 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11612</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12206</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11419</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>760</td>\n",
+       "      <td>...</td>\n",
+       "      <td>561</td>\n",
+       "      <td>1461</td>\n",
+       "      <td>1136</td>\n",
+       "      <td>1015</td>\n",
+       "      <td>1262</td>\n",
+       "      <td>1286</td>\n",
+       "      <td>1092</td>\n",
+       "      <td>1820</td>\n",
+       "      <td>1233</td>\n",
+       "      <td>727</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2020-02-07 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10986</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11925</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11154</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>729</td>\n",
+       "      <td>...</td>\n",
+       "      <td>564</td>\n",
+       "      <td>1529</td>\n",
+       "      <td>1072</td>\n",
+       "      <td>922</td>\n",
+       "      <td>1052</td>\n",
+       "      <td>1259</td>\n",
+       "      <td>987</td>\n",
+       "      <td>1729</td>\n",
+       "      <td>1157</td>\n",
+       "      <td>690</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2020-02-14 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10944</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11627</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10876</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>722</td>\n",
+       "      <td>...</td>\n",
+       "      <td>573</td>\n",
+       "      <td>1427</td>\n",
+       "      <td>1059</td>\n",
+       "      <td>976</td>\n",
+       "      <td>1159</td>\n",
+       "      <td>1172</td>\n",
+       "      <td>967</td>\n",
+       "      <td>1688</td>\n",
+       "      <td>1169</td>\n",
+       "      <td>728</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2020-02-21 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10841</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11548</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10790</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>724</td>\n",
+       "      <td>...</td>\n",
+       "      <td>539</td>\n",
+       "      <td>1477</td>\n",
+       "      <td>1087</td>\n",
+       "      <td>924</td>\n",
+       "      <td>1116</td>\n",
+       "      <td>1167</td>\n",
+       "      <td>1032</td>\n",
+       "      <td>1675</td>\n",
+       "      <td>1118</td>\n",
+       "      <td>679</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2020-02-28 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10816</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11183</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10448</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>698</td>\n",
+       "      <td>...</td>\n",
+       "      <td>572</td>\n",
+       "      <td>1476</td>\n",
+       "      <td>1078</td>\n",
+       "      <td>919</td>\n",
+       "      <td>1174</td>\n",
+       "      <td>1115</td>\n",
+       "      <td>1085</td>\n",
+       "      <td>1587</td>\n",
+       "      <td>1133</td>\n",
+       "      <td>651</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>2020-03-06 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10895</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11498</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10745</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>720</td>\n",
+       "      <td>...</td>\n",
+       "      <td>568</td>\n",
+       "      <td>1490</td>\n",
+       "      <td>1112</td>\n",
+       "      <td>930</td>\n",
+       "      <td>1098</td>\n",
+       "      <td>1149</td>\n",
+       "      <td>982</td>\n",
+       "      <td>1726</td>\n",
+       "      <td>1170</td>\n",
+       "      <td>652</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>2020-03-13 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11019</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11205</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10447</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>727</td>\n",
+       "      <td>...</td>\n",
+       "      <td>590</td>\n",
+       "      <td>1472</td>\n",
+       "      <td>1053</td>\n",
+       "      <td>915</td>\n",
+       "      <td>1187</td>\n",
+       "      <td>1211</td>\n",
+       "      <td>964</td>\n",
+       "      <td>1751</td>\n",
+       "      <td>1174</td>\n",
+       "      <td>675</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>2020-03-20 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10645</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10573</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9841</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>677</td>\n",
+       "      <td>...</td>\n",
+       "      <td>522</td>\n",
+       "      <td>1443</td>\n",
+       "      <td>1012</td>\n",
+       "      <td>947</td>\n",
+       "      <td>1115</td>\n",
+       "      <td>1043</td>\n",
+       "      <td>1008</td>\n",
+       "      <td>1657</td>\n",
+       "      <td>1156</td>\n",
+       "      <td>719</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>2020-03-27 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11141</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10130</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9414</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>665</td>\n",
+       "      <td>...</td>\n",
+       "      <td>542</td>\n",
+       "      <td>1538</td>\n",
+       "      <td>982</td>\n",
+       "      <td>922</td>\n",
+       "      <td>1035</td>\n",
+       "      <td>1182</td>\n",
+       "      <td>1297</td>\n",
+       "      <td>1822</td>\n",
+       "      <td>1092</td>\n",
+       "      <td>719</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>2020-04-03 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>16387</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10305</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9601</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>667</td>\n",
+       "      <td>...</td>\n",
+       "      <td>770</td>\n",
+       "      <td>2137</td>\n",
+       "      <td>1436</td>\n",
+       "      <td>1246</td>\n",
+       "      <td>1812</td>\n",
+       "      <td>1717</td>\n",
+       "      <td>2511</td>\n",
+       "      <td>2294</td>\n",
+       "      <td>1520</td>\n",
+       "      <td>920</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>2020-04-10 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>18516</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10520</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9807</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>671</td>\n",
+       "      <td>...</td>\n",
+       "      <td>849</td>\n",
+       "      <td>2597</td>\n",
+       "      <td>1503</td>\n",
+       "      <td>1452</td>\n",
+       "      <td>2182</td>\n",
+       "      <td>1984</td>\n",
+       "      <td>2832</td>\n",
+       "      <td>2604</td>\n",
+       "      <td>1560</td>\n",
+       "      <td>928</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>2020-04-17 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>22351</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10497</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9787</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>661</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1155</td>\n",
+       "      <td>3195</td>\n",
+       "      <td>1960</td>\n",
+       "      <td>1632</td>\n",
+       "      <td>2536</td>\n",
+       "      <td>2466</td>\n",
+       "      <td>3275</td>\n",
+       "      <td>3084</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1169</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>2020-04-24 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>21997</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10458</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9768</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>662</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1103</td>\n",
+       "      <td>3109</td>\n",
+       "      <td>2095</td>\n",
+       "      <td>1711</td>\n",
+       "      <td>2481</td>\n",
+       "      <td>2299</td>\n",
+       "      <td>2785</td>\n",
+       "      <td>3334</td>\n",
+       "      <td>1924</td>\n",
+       "      <td>1124</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>2020-05-01 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>17953</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9941</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9289</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>624</td>\n",
+       "      <td>...</td>\n",
+       "      <td>922</td>\n",
+       "      <td>2503</td>\n",
+       "      <td>1844</td>\n",
+       "      <td>1418</td>\n",
+       "      <td>1975</td>\n",
+       "      <td>1982</td>\n",
+       "      <td>1953</td>\n",
+       "      <td>2853</td>\n",
+       "      <td>1554</td>\n",
+       "      <td>929</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>2020-05-08 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12657</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9576</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8937</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>612</td>\n",
+       "      <td>...</td>\n",
+       "      <td>769</td>\n",
+       "      <td>1790</td>\n",
+       "      <td>1328</td>\n",
+       "      <td>1094</td>\n",
+       "      <td>1326</td>\n",
+       "      <td>1321</td>\n",
+       "      <td>1213</td>\n",
+       "      <td>1887</td>\n",
+       "      <td>1218</td>\n",
+       "      <td>692</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>2020-05-15 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14573</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10188</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9526</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>635</td>\n",
+       "      <td>...</td>\n",
+       "      <td>845</td>\n",
+       "      <td>1992</td>\n",
+       "      <td>1589</td>\n",
+       "      <td>1283</td>\n",
+       "      <td>1502</td>\n",
+       "      <td>1543</td>\n",
+       "      <td>1329</td>\n",
+       "      <td>2251</td>\n",
+       "      <td>1449</td>\n",
+       "      <td>772</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>2020-05-22 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12288</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9940</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9299</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>614</td>\n",
+       "      <td>...</td>\n",
+       "      <td>718</td>\n",
+       "      <td>1636</td>\n",
+       "      <td>1236</td>\n",
+       "      <td>1041</td>\n",
+       "      <td>1319</td>\n",
+       "      <td>1397</td>\n",
+       "      <td>1125</td>\n",
+       "      <td>1937</td>\n",
+       "      <td>1177</td>\n",
+       "      <td>692</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>2020-05-29 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9824</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8171</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7607</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>546</td>\n",
+       "      <td>...</td>\n",
+       "      <td>550</td>\n",
+       "      <td>1337</td>\n",
+       "      <td>1046</td>\n",
+       "      <td>863</td>\n",
+       "      <td>970</td>\n",
+       "      <td>1095</td>\n",
+       "      <td>841</td>\n",
+       "      <td>1515</td>\n",
+       "      <td>1011</td>\n",
+       "      <td>587</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>2020-06-05 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10709</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9977</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9346</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>610</td>\n",
+       "      <td>...</td>\n",
+       "      <td>576</td>\n",
+       "      <td>1478</td>\n",
+       "      <td>1090</td>\n",
+       "      <td>931</td>\n",
+       "      <td>1172</td>\n",
+       "      <td>1131</td>\n",
+       "      <td>891</td>\n",
+       "      <td>1610</td>\n",
+       "      <td>1116</td>\n",
+       "      <td>700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>2020-06-12 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9976</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9417</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8803</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>588</td>\n",
+       "      <td>...</td>\n",
+       "      <td>478</td>\n",
+       "      <td>1374</td>\n",
+       "      <td>980</td>\n",
+       "      <td>967</td>\n",
+       "      <td>1096</td>\n",
+       "      <td>1048</td>\n",
+       "      <td>883</td>\n",
+       "      <td>1530</td>\n",
+       "      <td>1035</td>\n",
+       "      <td>574</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>2020-06-19 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9339</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9404</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8810</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>573</td>\n",
+       "      <td>...</td>\n",
+       "      <td>498</td>\n",
+       "      <td>1234</td>\n",
+       "      <td>952</td>\n",
+       "      <td>835</td>\n",
+       "      <td>973</td>\n",
+       "      <td>927</td>\n",
+       "      <td>896</td>\n",
+       "      <td>1411</td>\n",
+       "      <td>990</td>\n",
+       "      <td>617</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>2020-06-26 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8979</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9293</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8695</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>571</td>\n",
+       "      <td>...</td>\n",
+       "      <td>485</td>\n",
+       "      <td>1300</td>\n",
+       "      <td>922</td>\n",
+       "      <td>800</td>\n",
+       "      <td>946</td>\n",
+       "      <td>880</td>\n",
+       "      <td>791</td>\n",
+       "      <td>1311</td>\n",
+       "      <td>979</td>\n",
+       "      <td>552</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>2020-07-03 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9140</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9183</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8606</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>555</td>\n",
+       "      <td>...</td>\n",
+       "      <td>515</td>\n",
+       "      <td>1225</td>\n",
+       "      <td>875</td>\n",
+       "      <td>827</td>\n",
+       "      <td>949</td>\n",
+       "      <td>922</td>\n",
+       "      <td>837</td>\n",
+       "      <td>1454</td>\n",
+       "      <td>938</td>\n",
+       "      <td>584</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>2020-07-10 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8690</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9250</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8648</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>578</td>\n",
+       "      <td>...</td>\n",
+       "      <td>468</td>\n",
+       "      <td>1154</td>\n",
+       "      <td>848</td>\n",
+       "      <td>771</td>\n",
+       "      <td>902</td>\n",
+       "      <td>999</td>\n",
+       "      <td>803</td>\n",
+       "      <td>1228</td>\n",
+       "      <td>930</td>\n",
+       "      <td>572</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>2020-07-17 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8823</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9093</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8502</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>557</td>\n",
+       "      <td>...</td>\n",
+       "      <td>445</td>\n",
+       "      <td>1159</td>\n",
+       "      <td>843</td>\n",
+       "      <td>816</td>\n",
+       "      <td>956</td>\n",
+       "      <td>945</td>\n",
+       "      <td>806</td>\n",
+       "      <td>1339</td>\n",
+       "      <td>953</td>\n",
+       "      <td>550</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>2020-07-24 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8891</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9052</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8452</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>566</td>\n",
+       "      <td>...</td>\n",
+       "      <td>493</td>\n",
+       "      <td>1197</td>\n",
+       "      <td>817</td>\n",
+       "      <td>798</td>\n",
+       "      <td>964</td>\n",
+       "      <td>951</td>\n",
+       "      <td>816</td>\n",
+       "      <td>1340</td>\n",
+       "      <td>941</td>\n",
+       "      <td>565</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>2020-07-31 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8946</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9036</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8436</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>572</td>\n",
+       "      <td>...</td>\n",
+       "      <td>507</td>\n",
+       "      <td>1272</td>\n",
+       "      <td>837</td>\n",
+       "      <td>729</td>\n",
+       "      <td>902</td>\n",
+       "      <td>949</td>\n",
+       "      <td>773</td>\n",
+       "      <td>1447</td>\n",
+       "      <td>988</td>\n",
+       "      <td>531</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>2020-08-07 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8945</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9102</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8502</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>571</td>\n",
+       "      <td>...</td>\n",
+       "      <td>486</td>\n",
+       "      <td>1211</td>\n",
+       "      <td>851</td>\n",
+       "      <td>798</td>\n",
+       "      <td>933</td>\n",
+       "      <td>955</td>\n",
+       "      <td>832</td>\n",
+       "      <td>1370</td>\n",
+       "      <td>929</td>\n",
+       "      <td>563</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>2020-08-14 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9392</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9085</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8494</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>564</td>\n",
+       "      <td>...</td>\n",
+       "      <td>520</td>\n",
+       "      <td>1304</td>\n",
+       "      <td>853</td>\n",
+       "      <td>829</td>\n",
+       "      <td>923</td>\n",
+       "      <td>1006</td>\n",
+       "      <td>928</td>\n",
+       "      <td>1395</td>\n",
+       "      <td>1009</td>\n",
+       "      <td>617</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>2020-08-21 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9631</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9157</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8560</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>573</td>\n",
+       "      <td>...</td>\n",
+       "      <td>479</td>\n",
+       "      <td>1269</td>\n",
+       "      <td>870</td>\n",
+       "      <td>780</td>\n",
+       "      <td>1028</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>920</td>\n",
+       "      <td>1608</td>\n",
+       "      <td>1043</td>\n",
+       "      <td>594</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>2020-08-28 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9032</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8241</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7674</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>539</td>\n",
+       "      <td>...</td>\n",
+       "      <td>455</td>\n",
+       "      <td>1148</td>\n",
+       "      <td>922</td>\n",
+       "      <td>724</td>\n",
+       "      <td>945</td>\n",
+       "      <td>951</td>\n",
+       "      <td>810</td>\n",
+       "      <td>1511</td>\n",
+       "      <td>959</td>\n",
+       "      <td>591</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>2020-09-04 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7739</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9182</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8604</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>552</td>\n",
+       "      <td>...</td>\n",
+       "      <td>431</td>\n",
+       "      <td>1057</td>\n",
+       "      <td>780</td>\n",
+       "      <td>640</td>\n",
+       "      <td>770</td>\n",
+       "      <td>806</td>\n",
+       "      <td>737</td>\n",
+       "      <td>1208</td>\n",
+       "      <td>803</td>\n",
+       "      <td>488</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>2020-09-11 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9811</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9306</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8708</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>577</td>\n",
+       "      <td>...</td>\n",
+       "      <td>502</td>\n",
+       "      <td>1229</td>\n",
+       "      <td>952</td>\n",
+       "      <td>867</td>\n",
+       "      <td>1021</td>\n",
+       "      <td>1052</td>\n",
+       "      <td>898</td>\n",
+       "      <td>1610</td>\n",
+       "      <td>1084</td>\n",
+       "      <td>578</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>2020-09-18 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9523</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9264</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8663</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>575</td>\n",
+       "      <td>...</td>\n",
+       "      <td>465</td>\n",
+       "      <td>1287</td>\n",
+       "      <td>939</td>\n",
+       "      <td>795</td>\n",
+       "      <td>1051</td>\n",
+       "      <td>1023</td>\n",
+       "      <td>844</td>\n",
+       "      <td>1530</td>\n",
+       "      <td>1021</td>\n",
+       "      <td>555</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>2020-09-25 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9634</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9377</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8744</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>604</td>\n",
+       "      <td>...</td>\n",
+       "      <td>514</td>\n",
+       "      <td>1271</td>\n",
+       "      <td>965</td>\n",
+       "      <td>825</td>\n",
+       "      <td>1036</td>\n",
+       "      <td>963</td>\n",
+       "      <td>869</td>\n",
+       "      <td>1521</td>\n",
+       "      <td>1041</td>\n",
+       "      <td>617</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>2020-10-02 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9945</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9555</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8942</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>587</td>\n",
+       "      <td>...</td>\n",
+       "      <td>558</td>\n",
+       "      <td>1301</td>\n",
+       "      <td>978</td>\n",
+       "      <td>842</td>\n",
+       "      <td>1045</td>\n",
+       "      <td>1054</td>\n",
+       "      <td>899</td>\n",
+       "      <td>1577</td>\n",
+       "      <td>1003</td>\n",
+       "      <td>671</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>2020-10-09 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9954</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9811</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9168</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>615</td>\n",
+       "      <td>...</td>\n",
+       "      <td>544</td>\n",
+       "      <td>1367</td>\n",
+       "      <td>1067</td>\n",
+       "      <td>884</td>\n",
+       "      <td>1053</td>\n",
+       "      <td>1019</td>\n",
+       "      <td>902</td>\n",
+       "      <td>1462</td>\n",
+       "      <td>1010</td>\n",
+       "      <td>638</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>2020-10-16 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10534</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9865</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9215</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>630</td>\n",
+       "      <td>...</td>\n",
+       "      <td>606</td>\n",
+       "      <td>1553</td>\n",
+       "      <td>1001</td>\n",
+       "      <td>904</td>\n",
+       "      <td>1154</td>\n",
+       "      <td>1056</td>\n",
+       "      <td>923</td>\n",
+       "      <td>1462</td>\n",
+       "      <td>1174</td>\n",
+       "      <td>688</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>2020-10-23 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10739</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9759</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9104</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>628</td>\n",
+       "      <td>...</td>\n",
+       "      <td>600</td>\n",
+       "      <td>1714</td>\n",
+       "      <td>1111</td>\n",
+       "      <td>891</td>\n",
+       "      <td>1124</td>\n",
+       "      <td>1154</td>\n",
+       "      <td>922</td>\n",
+       "      <td>1510</td>\n",
+       "      <td>1044</td>\n",
+       "      <td>661</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>2020-10-30 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10887</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9891</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9248</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>616</td>\n",
+       "      <td>...</td>\n",
+       "      <td>591</td>\n",
+       "      <td>1754</td>\n",
+       "      <td>1168</td>\n",
+       "      <td>882</td>\n",
+       "      <td>1102</td>\n",
+       "      <td>1089</td>\n",
+       "      <td>888</td>\n",
+       "      <td>1563</td>\n",
+       "      <td>1129</td>\n",
+       "      <td>712</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>2020-11-06 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11812</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10331</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9675</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>625</td>\n",
+       "      <td>...</td>\n",
+       "      <td>675</td>\n",
+       "      <td>1900</td>\n",
+       "      <td>1294</td>\n",
+       "      <td>990</td>\n",
+       "      <td>1186</td>\n",
+       "      <td>1177</td>\n",
+       "      <td>952</td>\n",
+       "      <td>1614</td>\n",
+       "      <td>1174</td>\n",
+       "      <td>832</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>2020-11-13 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12254</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10350</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9662</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>658</td>\n",
+       "      <td>...</td>\n",
+       "      <td>711</td>\n",
+       "      <td>1950</td>\n",
+       "      <td>1350</td>\n",
+       "      <td>1099</td>\n",
+       "      <td>1317</td>\n",
+       "      <td>1172</td>\n",
+       "      <td>1112</td>\n",
+       "      <td>1616</td>\n",
+       "      <td>1168</td>\n",
+       "      <td>742</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>2020-11-20 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12535</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10380</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9701</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>653</td>\n",
+       "      <td>...</td>\n",
+       "      <td>691</td>\n",
+       "      <td>1935</td>\n",
+       "      <td>1441</td>\n",
+       "      <td>1105</td>\n",
+       "      <td>1385</td>\n",
+       "      <td>1186</td>\n",
+       "      <td>1086</td>\n",
+       "      <td>1687</td>\n",
+       "      <td>1159</td>\n",
+       "      <td>848</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>2020-11-27 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12456</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10357</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9690</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>646</td>\n",
+       "      <td>...</td>\n",
+       "      <td>679</td>\n",
+       "      <td>1791</td>\n",
+       "      <td>1501</td>\n",
+       "      <td>1218</td>\n",
+       "      <td>1358</td>\n",
+       "      <td>1159</td>\n",
+       "      <td>1012</td>\n",
+       "      <td>1655</td>\n",
+       "      <td>1272</td>\n",
+       "      <td>797</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>2020-12-04 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12303</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10695</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9995</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>679</td>\n",
+       "      <td>...</td>\n",
+       "      <td>645</td>\n",
+       "      <td>1679</td>\n",
+       "      <td>1403</td>\n",
+       "      <td>1121</td>\n",
+       "      <td>1340</td>\n",
+       "      <td>1229</td>\n",
+       "      <td>1029</td>\n",
+       "      <td>1720</td>\n",
+       "      <td>1284</td>\n",
+       "      <td>836</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>2020-12-11 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12292</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10750</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10034</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>693</td>\n",
+       "      <td>...</td>\n",
+       "      <td>661</td>\n",
+       "      <td>1691</td>\n",
+       "      <td>1326</td>\n",
+       "      <td>1199</td>\n",
+       "      <td>1432</td>\n",
+       "      <td>1224</td>\n",
+       "      <td>1065</td>\n",
+       "      <td>1706</td>\n",
+       "      <td>1156</td>\n",
+       "      <td>814</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>2020-12-18 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13011</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11548</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10804</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>718</td>\n",
+       "      <td>...</td>\n",
+       "      <td>689</td>\n",
+       "      <td>1718</td>\n",
+       "      <td>1380</td>\n",
+       "      <td>1199</td>\n",
+       "      <td>1385</td>\n",
+       "      <td>1317</td>\n",
+       "      <td>1167</td>\n",
+       "      <td>1947</td>\n",
+       "      <td>1311</td>\n",
+       "      <td>882</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>2020-12-25 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11520</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7954</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7421</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>518</td>\n",
+       "      <td>...</td>\n",
+       "      <td>669</td>\n",
+       "      <td>1463</td>\n",
+       "      <td>1130</td>\n",
+       "      <td>1097</td>\n",
+       "      <td>1217</td>\n",
+       "      <td>1198</td>\n",
+       "      <td>1090</td>\n",
+       "      <td>1701</td>\n",
+       "      <td>1115</td>\n",
+       "      <td>825</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>2021-01-01 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10069</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7954</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7421</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>518</td>\n",
+       "      <td>...</td>\n",
+       "      <td>547</td>\n",
+       "      <td>1346</td>\n",
+       "      <td>886</td>\n",
+       "      <td>842</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>997</td>\n",
+       "      <td>1159</td>\n",
+       "      <td>1595</td>\n",
+       "      <td>929</td>\n",
+       "      <td>727</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>54 rows × 91 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                             NaN  NaN  NaN                     NaN  \\\n",
+       "Week number           Week ended  NaN  NaN  Total deaths, all ages   \n",
+       "1            2020-01-03 00:00:00  NaN  NaN                   12254   \n",
+       "2            2020-01-10 00:00:00  NaN  NaN                   14058   \n",
+       "3            2020-01-17 00:00:00  NaN  NaN                   12990   \n",
+       "4            2020-01-24 00:00:00  NaN  NaN                   11856   \n",
+       "5            2020-01-31 00:00:00  NaN  NaN                   11612   \n",
+       "6            2020-02-07 00:00:00  NaN  NaN                   10986   \n",
+       "7            2020-02-14 00:00:00  NaN  NaN                   10944   \n",
+       "8            2020-02-21 00:00:00  NaN  NaN                   10841   \n",
+       "9            2020-02-28 00:00:00  NaN  NaN                   10816   \n",
+       "10           2020-03-06 00:00:00  NaN  NaN                   10895   \n",
+       "11           2020-03-13 00:00:00  NaN  NaN                   11019   \n",
+       "12           2020-03-20 00:00:00  NaN  NaN                   10645   \n",
+       "13           2020-03-27 00:00:00  NaN  NaN                   11141   \n",
+       "14           2020-04-03 00:00:00  NaN  NaN                   16387   \n",
+       "15           2020-04-10 00:00:00  NaN  NaN                   18516   \n",
+       "16           2020-04-17 00:00:00  NaN  NaN                   22351   \n",
+       "17           2020-04-24 00:00:00  NaN  NaN                   21997   \n",
+       "18           2020-05-01 00:00:00  NaN  NaN                   17953   \n",
+       "19           2020-05-08 00:00:00  NaN  NaN                   12657   \n",
+       "20           2020-05-15 00:00:00  NaN  NaN                   14573   \n",
+       "21           2020-05-22 00:00:00  NaN  NaN                   12288   \n",
+       "22           2020-05-29 00:00:00  NaN  NaN                    9824   \n",
+       "23           2020-06-05 00:00:00  NaN  NaN                   10709   \n",
+       "24           2020-06-12 00:00:00  NaN  NaN                    9976   \n",
+       "25           2020-06-19 00:00:00  NaN  NaN                    9339   \n",
+       "26           2020-06-26 00:00:00  NaN  NaN                    8979   \n",
+       "27           2020-07-03 00:00:00  NaN  NaN                    9140   \n",
+       "28           2020-07-10 00:00:00  NaN  NaN                    8690   \n",
+       "29           2020-07-17 00:00:00  NaN  NaN                    8823   \n",
+       "30           2020-07-24 00:00:00  NaN  NaN                    8891   \n",
+       "31           2020-07-31 00:00:00  NaN  NaN                    8946   \n",
+       "32           2020-08-07 00:00:00  NaN  NaN                    8945   \n",
+       "33           2020-08-14 00:00:00  NaN  NaN                    9392   \n",
+       "34           2020-08-21 00:00:00  NaN  NaN                    9631   \n",
+       "35           2020-08-28 00:00:00  NaN  NaN                    9032   \n",
+       "36           2020-09-04 00:00:00  NaN  NaN                    7739   \n",
+       "37           2020-09-11 00:00:00  NaN  NaN                    9811   \n",
+       "38           2020-09-18 00:00:00  NaN  NaN                    9523   \n",
+       "39           2020-09-25 00:00:00  NaN  NaN                    9634   \n",
+       "40           2020-10-02 00:00:00  NaN  NaN                    9945   \n",
+       "41           2020-10-09 00:00:00  NaN  NaN                    9954   \n",
+       "42           2020-10-16 00:00:00  NaN  NaN                   10534   \n",
+       "43           2020-10-23 00:00:00  NaN  NaN                   10739   \n",
+       "44           2020-10-30 00:00:00  NaN  NaN                   10887   \n",
+       "45           2020-11-06 00:00:00  NaN  NaN                   11812   \n",
+       "46           2020-11-13 00:00:00  NaN  NaN                   12254   \n",
+       "47           2020-11-20 00:00:00  NaN  NaN                   12535   \n",
+       "48           2020-11-27 00:00:00  NaN  NaN                   12456   \n",
+       "49           2020-12-04 00:00:00  NaN  NaN                   12303   \n",
+       "50           2020-12-11 00:00:00  NaN  NaN                   12292   \n",
+       "51           2020-12-18 00:00:00  NaN  NaN                   13011   \n",
+       "52           2020-12-25 00:00:00  NaN  NaN                   11520   \n",
+       "53           2021-01-01 00:00:00  NaN  NaN                   10069   \n",
+       "\n",
+       "                                                NaN  \\\n",
+       "Week number  Total deaths: average of corresponding   \n",
+       "1                                               NaN   \n",
+       "2                                               NaN   \n",
+       "3                                               NaN   \n",
+       "4                                               NaN   \n",
+       "5                                               NaN   \n",
+       "6                                               NaN   \n",
+       "7                                               NaN   \n",
+       "8                                               NaN   \n",
+       "9                                               NaN   \n",
+       "10                                              NaN   \n",
+       "11                                              NaN   \n",
+       "12                                              NaN   \n",
+       "13                                              NaN   \n",
+       "14                                              NaN   \n",
+       "15                                              NaN   \n",
+       "16                                              NaN   \n",
+       "17                                              NaN   \n",
+       "18                                              NaN   \n",
+       "19                                              NaN   \n",
+       "20                                              NaN   \n",
+       "21                                              NaN   \n",
+       "22                                              NaN   \n",
+       "23                                              NaN   \n",
+       "24                                              NaN   \n",
+       "25                                              NaN   \n",
+       "26                                              NaN   \n",
+       "27                                              NaN   \n",
+       "28                                              NaN   \n",
+       "29                                              NaN   \n",
+       "30                                              NaN   \n",
+       "31                                              NaN   \n",
+       "32                                              NaN   \n",
+       "33                                              NaN   \n",
+       "34                                              NaN   \n",
+       "35                                              NaN   \n",
+       "36                                              NaN   \n",
+       "37                                              NaN   \n",
+       "38                                              NaN   \n",
+       "39                                              NaN   \n",
+       "40                                              NaN   \n",
+       "41                                              NaN   \n",
+       "42                                              NaN   \n",
+       "43                                              NaN   \n",
+       "44                                              NaN   \n",
+       "45                                              NaN   \n",
+       "46                                              NaN   \n",
+       "47                                              NaN   \n",
+       "48                                              NaN   \n",
+       "49                                              NaN   \n",
+       "50                                              NaN   \n",
+       "51                                              NaN   \n",
+       "52                                              NaN   \n",
+       "53                                              NaN   \n",
+       "\n",
+       "                                                           NaN  \\\n",
+       "Week number  week over the previous 5 years 1, 10, 11 (Engl...   \n",
+       "1                                                        12175   \n",
+       "2                                                        13822   \n",
+       "3                                                        13216   \n",
+       "4                                                        12760   \n",
+       "5                                                        12206   \n",
+       "6                                                        11925   \n",
+       "7                                                        11627   \n",
+       "8                                                        11548   \n",
+       "9                                                        11183   \n",
+       "10                                                       11498   \n",
+       "11                                                       11205   \n",
+       "12                                                       10573   \n",
+       "13                                                       10130   \n",
+       "14                                                       10305   \n",
+       "15                                                       10520   \n",
+       "16                                                       10497   \n",
+       "17                                                       10458   \n",
+       "18                                                        9941   \n",
+       "19                                                        9576   \n",
+       "20                                                       10188   \n",
+       "21                                                        9940   \n",
+       "22                                                        8171   \n",
+       "23                                                        9977   \n",
+       "24                                                        9417   \n",
+       "25                                                        9404   \n",
+       "26                                                        9293   \n",
+       "27                                                        9183   \n",
+       "28                                                        9250   \n",
+       "29                                                        9093   \n",
+       "30                                                        9052   \n",
+       "31                                                        9036   \n",
+       "32                                                        9102   \n",
+       "33                                                        9085   \n",
+       "34                                                        9157   \n",
+       "35                                                        8241   \n",
+       "36                                                        9182   \n",
+       "37                                                        9306   \n",
+       "38                                                        9264   \n",
+       "39                                                        9377   \n",
+       "40                                                        9555   \n",
+       "41                                                        9811   \n",
+       "42                                                        9865   \n",
+       "43                                                        9759   \n",
+       "44                                                        9891   \n",
+       "45                                                       10331   \n",
+       "46                                                       10350   \n",
+       "47                                                       10380   \n",
+       "48                                                       10357   \n",
+       "49                                                       10695   \n",
+       "50                                                       10750   \n",
+       "51                                                       11548   \n",
+       "52                                                        7954   \n",
+       "53                                                        7954   \n",
+       "\n",
+       "                                                NaN  \\\n",
+       "Week number  Total deaths: average of corresponding   \n",
+       "1                                               NaN   \n",
+       "2                                               NaN   \n",
+       "3                                               NaN   \n",
+       "4                                               NaN   \n",
+       "5                                               NaN   \n",
+       "6                                               NaN   \n",
+       "7                                               NaN   \n",
+       "8                                               NaN   \n",
+       "9                                               NaN   \n",
+       "10                                              NaN   \n",
+       "11                                              NaN   \n",
+       "12                                              NaN   \n",
+       "13                                              NaN   \n",
+       "14                                              NaN   \n",
+       "15                                              NaN   \n",
+       "16                                              NaN   \n",
+       "17                                              NaN   \n",
+       "18                                              NaN   \n",
+       "19                                              NaN   \n",
+       "20                                              NaN   \n",
+       "21                                              NaN   \n",
+       "22                                              NaN   \n",
+       "23                                              NaN   \n",
+       "24                                              NaN   \n",
+       "25                                              NaN   \n",
+       "26                                              NaN   \n",
+       "27                                              NaN   \n",
+       "28                                              NaN   \n",
+       "29                                              NaN   \n",
+       "30                                              NaN   \n",
+       "31                                              NaN   \n",
+       "32                                              NaN   \n",
+       "33                                              NaN   \n",
+       "34                                              NaN   \n",
+       "35                                              NaN   \n",
+       "36                                              NaN   \n",
+       "37                                              NaN   \n",
+       "38                                              NaN   \n",
+       "39                                              NaN   \n",
+       "40                                              NaN   \n",
+       "41                                              NaN   \n",
+       "42                                              NaN   \n",
+       "43                                              NaN   \n",
+       "44                                              NaN   \n",
+       "45                                              NaN   \n",
+       "46                                              NaN   \n",
+       "47                                              NaN   \n",
+       "48                                              NaN   \n",
+       "49                                              NaN   \n",
+       "50                                              NaN   \n",
+       "51                                              NaN   \n",
+       "52                                              NaN   \n",
+       "53                                              NaN   \n",
+       "\n",
+       "                                                           NaN  \\\n",
+       "Week number  week over the previous 5 years 1, 10, 11 (Engl...   \n",
+       "1                                                        11412   \n",
+       "2                                                        12933   \n",
+       "3                                                        12370   \n",
+       "4                                                        11933   \n",
+       "5                                                        11419   \n",
+       "6                                                        11154   \n",
+       "7                                                        10876   \n",
+       "8                                                        10790   \n",
+       "9                                                        10448   \n",
+       "10                                                       10745   \n",
+       "11                                                       10447   \n",
+       "12                                                        9841   \n",
+       "13                                                        9414   \n",
+       "14                                                        9601   \n",
+       "15                                                        9807   \n",
+       "16                                                        9787   \n",
+       "17                                                        9768   \n",
+       "18                                                        9289   \n",
+       "19                                                        8937   \n",
+       "20                                                        9526   \n",
+       "21                                                        9299   \n",
+       "22                                                        7607   \n",
+       "23                                                        9346   \n",
+       "24                                                        8803   \n",
+       "25                                                        8810   \n",
+       "26                                                        8695   \n",
+       "27                                                        8606   \n",
+       "28                                                        8648   \n",
+       "29                                                        8502   \n",
+       "30                                                        8452   \n",
+       "31                                                        8436   \n",
+       "32                                                        8502   \n",
+       "33                                                        8494   \n",
+       "34                                                        8560   \n",
+       "35                                                        7674   \n",
+       "36                                                        8604   \n",
+       "37                                                        8708   \n",
+       "38                                                        8663   \n",
+       "39                                                        8744   \n",
+       "40                                                        8942   \n",
+       "41                                                        9168   \n",
+       "42                                                        9215   \n",
+       "43                                                        9104   \n",
+       "44                                                        9248   \n",
+       "45                                                        9675   \n",
+       "46                                                        9662   \n",
+       "47                                                        9701   \n",
+       "48                                                        9690   \n",
+       "49                                                        9995   \n",
+       "50                                                       10034   \n",
+       "51                                                       10804   \n",
+       "52                                                        7421   \n",
+       "53                                                        7421   \n",
+       "\n",
+       "                                                NaN  \\\n",
+       "Week number  Total deaths: average of corresponding   \n",
+       "1                                               NaN   \n",
+       "2                                               NaN   \n",
+       "3                                               NaN   \n",
+       "4                                               NaN   \n",
+       "5                                               NaN   \n",
+       "6                                               NaN   \n",
+       "7                                               NaN   \n",
+       "8                                               NaN   \n",
+       "9                                               NaN   \n",
+       "10                                              NaN   \n",
+       "11                                              NaN   \n",
+       "12                                              NaN   \n",
+       "13                                              NaN   \n",
+       "14                                              NaN   \n",
+       "15                                              NaN   \n",
+       "16                                              NaN   \n",
+       "17                                              NaN   \n",
+       "18                                              NaN   \n",
+       "19                                              NaN   \n",
+       "20                                              NaN   \n",
+       "21                                              NaN   \n",
+       "22                                              NaN   \n",
+       "23                                              NaN   \n",
+       "24                                              NaN   \n",
+       "25                                              NaN   \n",
+       "26                                              NaN   \n",
+       "27                                              NaN   \n",
+       "28                                              NaN   \n",
+       "29                                              NaN   \n",
+       "30                                              NaN   \n",
+       "31                                              NaN   \n",
+       "32                                              NaN   \n",
+       "33                                              NaN   \n",
+       "34                                              NaN   \n",
+       "35                                              NaN   \n",
+       "36                                              NaN   \n",
+       "37                                              NaN   \n",
+       "38                                              NaN   \n",
+       "39                                              NaN   \n",
+       "40                                              NaN   \n",
+       "41                                              NaN   \n",
+       "42                                              NaN   \n",
+       "43                                              NaN   \n",
+       "44                                              NaN   \n",
+       "45                                              NaN   \n",
+       "46                                              NaN   \n",
+       "47                                              NaN   \n",
+       "48                                              NaN   \n",
+       "49                                              NaN   \n",
+       "50                                              NaN   \n",
+       "51                                              NaN   \n",
+       "52                                              NaN   \n",
+       "53                                              NaN   \n",
+       "\n",
+       "                                                          NaN  ... North East  \\\n",
+       "Week number  week over the previous 5 years 1, 10, 11 (Wales)  ...  E12000001   \n",
+       "1                                                         756  ...        673   \n",
+       "2                                                         856  ...        707   \n",
+       "3                                                         812  ...        647   \n",
+       "4                                                         802  ...        612   \n",
+       "5                                                         760  ...        561   \n",
+       "6                                                         729  ...        564   \n",
+       "7                                                         722  ...        573   \n",
+       "8                                                         724  ...        539   \n",
+       "9                                                         698  ...        572   \n",
+       "10                                                        720  ...        568   \n",
+       "11                                                        727  ...        590   \n",
+       "12                                                        677  ...        522   \n",
+       "13                                                        665  ...        542   \n",
+       "14                                                        667  ...        770   \n",
+       "15                                                        671  ...        849   \n",
+       "16                                                        661  ...       1155   \n",
+       "17                                                        662  ...       1103   \n",
+       "18                                                        624  ...        922   \n",
+       "19                                                        612  ...        769   \n",
+       "20                                                        635  ...        845   \n",
+       "21                                                        614  ...        718   \n",
+       "22                                                        546  ...        550   \n",
+       "23                                                        610  ...        576   \n",
+       "24                                                        588  ...        478   \n",
+       "25                                                        573  ...        498   \n",
+       "26                                                        571  ...        485   \n",
+       "27                                                        555  ...        515   \n",
+       "28                                                        578  ...        468   \n",
+       "29                                                        557  ...        445   \n",
+       "30                                                        566  ...        493   \n",
+       "31                                                        572  ...        507   \n",
+       "32                                                        571  ...        486   \n",
+       "33                                                        564  ...        520   \n",
+       "34                                                        573  ...        479   \n",
+       "35                                                        539  ...        455   \n",
+       "36                                                        552  ...        431   \n",
+       "37                                                        577  ...        502   \n",
+       "38                                                        575  ...        465   \n",
+       "39                                                        604  ...        514   \n",
+       "40                                                        587  ...        558   \n",
+       "41                                                        615  ...        544   \n",
+       "42                                                        630  ...        606   \n",
+       "43                                                        628  ...        600   \n",
+       "44                                                        616  ...        591   \n",
+       "45                                                        625  ...        675   \n",
+       "46                                                        658  ...        711   \n",
+       "47                                                        653  ...        691   \n",
+       "48                                                        646  ...        679   \n",
+       "49                                                        679  ...        645   \n",
+       "50                                                        693  ...        661   \n",
+       "51                                                        718  ...        689   \n",
+       "52                                                        518  ...        669   \n",
+       "53                                                        518  ...        547   \n",
+       "\n",
+       "            North West Yorkshire and The Humber East Midlands West Midlands  \\\n",
+       "Week number  E12000002                E12000003     E12000004     E12000005   \n",
+       "1                 1806                     1240          1060          1349   \n",
+       "2                 1932                     1339          1195          1450   \n",
+       "3                 1696                     1278          1106          1407   \n",
+       "4                 1529                     1187          1024          1231   \n",
+       "5                 1461                     1136          1015          1262   \n",
+       "6                 1529                     1072           922          1052   \n",
+       "7                 1427                     1059           976          1159   \n",
+       "8                 1477                     1087           924          1116   \n",
+       "9                 1476                     1078           919          1174   \n",
+       "10                1490                     1112           930          1098   \n",
+       "11                1472                     1053           915          1187   \n",
+       "12                1443                     1012           947          1115   \n",
+       "13                1538                      982           922          1035   \n",
+       "14                2137                     1436          1246          1812   \n",
+       "15                2597                     1503          1452          2182   \n",
+       "16                3195                     1960          1632          2536   \n",
+       "17                3109                     2095          1711          2481   \n",
+       "18                2503                     1844          1418          1975   \n",
+       "19                1790                     1328          1094          1326   \n",
+       "20                1992                     1589          1283          1502   \n",
+       "21                1636                     1236          1041          1319   \n",
+       "22                1337                     1046           863           970   \n",
+       "23                1478                     1090           931          1172   \n",
+       "24                1374                      980           967          1096   \n",
+       "25                1234                      952           835           973   \n",
+       "26                1300                      922           800           946   \n",
+       "27                1225                      875           827           949   \n",
+       "28                1154                      848           771           902   \n",
+       "29                1159                      843           816           956   \n",
+       "30                1197                      817           798           964   \n",
+       "31                1272                      837           729           902   \n",
+       "32                1211                      851           798           933   \n",
+       "33                1304                      853           829           923   \n",
+       "34                1269                      870           780          1028   \n",
+       "35                1148                      922           724           945   \n",
+       "36                1057                      780           640           770   \n",
+       "37                1229                      952           867          1021   \n",
+       "38                1287                      939           795          1051   \n",
+       "39                1271                      965           825          1036   \n",
+       "40                1301                      978           842          1045   \n",
+       "41                1367                     1067           884          1053   \n",
+       "42                1553                     1001           904          1154   \n",
+       "43                1714                     1111           891          1124   \n",
+       "44                1754                     1168           882          1102   \n",
+       "45                1900                     1294           990          1186   \n",
+       "46                1950                     1350          1099          1317   \n",
+       "47                1935                     1441          1105          1385   \n",
+       "48                1791                     1501          1218          1358   \n",
+       "49                1679                     1403          1121          1340   \n",
+       "50                1691                     1326          1199          1432   \n",
+       "51                1718                     1380          1199          1385   \n",
+       "52                1463                     1130          1097          1217   \n",
+       "53                1346                      886           842          1024   \n",
+       "\n",
+       "                  East     London South East South West      Wales  \n",
+       "Week number  E12000006  E12000007  E12000008  E12000009  W92000004  \n",
+       "1                 1162       1113       1814       1225        787  \n",
+       "2                 1573       1272       2132       1487        939  \n",
+       "3                 1457       1073       2064       1466        767  \n",
+       "4                 1410       1028       1833       1253        723  \n",
+       "5                 1286       1092       1820       1233        727  \n",
+       "6                 1259        987       1729       1157        690  \n",
+       "7                 1172        967       1688       1169        728  \n",
+       "8                 1167       1032       1675       1118        679  \n",
+       "9                 1115       1085       1587       1133        651  \n",
+       "10                1149        982       1726       1170        652  \n",
+       "11                1211        964       1751       1174        675  \n",
+       "12                1043       1008       1657       1156        719  \n",
+       "13                1182       1297       1822       1092        719  \n",
+       "14                1717       2511       2294       1520        920  \n",
+       "15                1984       2832       2604       1560        928  \n",
+       "16                2466       3275       3084       1854       1169  \n",
+       "17                2299       2785       3334       1924       1124  \n",
+       "18                1982       1953       2853       1554        929  \n",
+       "19                1321       1213       1887       1218        692  \n",
+       "20                1543       1329       2251       1449        772  \n",
+       "21                1397       1125       1937       1177        692  \n",
+       "22                1095        841       1515       1011        587  \n",
+       "23                1131        891       1610       1116        700  \n",
+       "24                1048        883       1530       1035        574  \n",
+       "25                 927        896       1411        990        617  \n",
+       "26                 880        791       1311        979        552  \n",
+       "27                 922        837       1454        938        584  \n",
+       "28                 999        803       1228        930        572  \n",
+       "29                 945        806       1339        953        550  \n",
+       "30                 951        816       1340        941        565  \n",
+       "31                 949        773       1447        988        531  \n",
+       "32                 955        832       1370        929        563  \n",
+       "33                1006        928       1395       1009        617  \n",
+       "34                1024        920       1608       1043        594  \n",
+       "35                 951        810       1511        959        591  \n",
+       "36                 806        737       1208        803        488  \n",
+       "37                1052        898       1610       1084        578  \n",
+       "38                1023        844       1530       1021        555  \n",
+       "39                 963        869       1521       1041        617  \n",
+       "40                1054        899       1577       1003        671  \n",
+       "41                1019        902       1462       1010        638  \n",
+       "42                1056        923       1462       1174        688  \n",
+       "43                1154        922       1510       1044        661  \n",
+       "44                1089        888       1563       1129        712  \n",
+       "45                1177        952       1614       1174        832  \n",
+       "46                1172       1112       1616       1168        742  \n",
+       "47                1186       1086       1687       1159        848  \n",
+       "48                1159       1012       1655       1272        797  \n",
+       "49                1229       1029       1720       1284        836  \n",
+       "50                1224       1065       1706       1156        814  \n",
+       "51                1317       1167       1947       1311        882  \n",
+       "52                1198       1090       1701       1115        825  \n",
+       "53                 997       1159       1595        929        727  \n",
+       "\n",
+       "[54 rows x 91 columns]"
+      ]
+     },
+     "execution_count": 432,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "eng_xls = pd.read_excel(england_wales_filename, \n",
+    "                        sheet_name=\"Weekly figures 2020\",\n",
+    "                        skiprows=[0, 1, 2, 3],\n",
+    "                        header=0,\n",
+    "                        index_col=[1]\n",
+    "                       ).iloc[:91].T\n",
+    "eng_xls"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 433,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# eng_xls_columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 434,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "eng_xls_columns = list(eng_xls.columns)\n",
+    "\n",
+    "for i, c in enumerate(eng_xls_columns):\n",
+    "#     print(i, c, type(c), isinstance(c, float))\n",
+    "    if isinstance(c, float) and np.isnan(c):\n",
+    "        if eng_xls.iloc[0].iloc[i] is not pd.NaT:\n",
+    "            eng_xls_columns[i] = eng_xls.iloc[0].iloc[i]\n",
+    "\n",
+    "# np.isnan(eng_xls_columns[0])\n",
+    "# eng_xls_columns\n",
+    "\n",
+    "eng_xls.columns = eng_xls_columns\n",
+    "# eng_xls.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 435,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Week ended</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>Total deaths, all ages</th>\n",
+       "      <th>Total deaths: average of corresponding</th>\n",
+       "      <th>week over the previous 5 years 1, 10, 11 (England and Wales)</th>\n",
+       "      <th>Total deaths: average of corresponding</th>\n",
+       "      <th>week over the previous 5 years 1, 10, 11 (England)</th>\n",
+       "      <th>Total deaths: average of corresponding</th>\n",
+       "      <th>week over the previous 5 years 1, 10, 11 (Wales)</th>\n",
+       "      <th>...</th>\n",
+       "      <th>North East</th>\n",
+       "      <th>North West</th>\n",
+       "      <th>Yorkshire and The Humber</th>\n",
+       "      <th>East Midlands</th>\n",
+       "      <th>West Midlands</th>\n",
+       "      <th>East</th>\n",
+       "      <th>London</th>\n",
+       "      <th>South East</th>\n",
+       "      <th>South West</th>\n",
+       "      <th>Wales</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Week number</th>\n",
+       "      <td>Week ended</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Total deaths, all ages</td>\n",
+       "      <td>Total deaths: average of corresponding</td>\n",
+       "      <td>week over the previous 5 years 1, 10, 11 (Engl...</td>\n",
+       "      <td>Total deaths: average of corresponding</td>\n",
+       "      <td>week over the previous 5 years 1, 10, 11 (Engl...</td>\n",
+       "      <td>Total deaths: average of corresponding</td>\n",
+       "      <td>week over the previous 5 years 1, 10, 11 (Wales)</td>\n",
+       "      <td>...</td>\n",
+       "      <td>E12000001</td>\n",
+       "      <td>E12000002</td>\n",
+       "      <td>E12000003</td>\n",
+       "      <td>E12000004</td>\n",
+       "      <td>E12000005</td>\n",
+       "      <td>E12000006</td>\n",
+       "      <td>E12000007</td>\n",
+       "      <td>E12000008</td>\n",
+       "      <td>E12000009</td>\n",
+       "      <td>W92000004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2020-01-03 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12254</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12175</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11412</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>756</td>\n",
+       "      <td>...</td>\n",
+       "      <td>673</td>\n",
+       "      <td>1806</td>\n",
+       "      <td>1240</td>\n",
+       "      <td>1060</td>\n",
+       "      <td>1349</td>\n",
+       "      <td>1162</td>\n",
+       "      <td>1113</td>\n",
+       "      <td>1814</td>\n",
+       "      <td>1225</td>\n",
+       "      <td>787</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2020-01-10 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14058</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13822</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12933</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>856</td>\n",
+       "      <td>...</td>\n",
+       "      <td>707</td>\n",
+       "      <td>1932</td>\n",
+       "      <td>1339</td>\n",
+       "      <td>1195</td>\n",
+       "      <td>1450</td>\n",
+       "      <td>1573</td>\n",
+       "      <td>1272</td>\n",
+       "      <td>2132</td>\n",
+       "      <td>1487</td>\n",
+       "      <td>939</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2020-01-17 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12990</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13216</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12370</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>812</td>\n",
+       "      <td>...</td>\n",
+       "      <td>647</td>\n",
+       "      <td>1696</td>\n",
+       "      <td>1278</td>\n",
+       "      <td>1106</td>\n",
+       "      <td>1407</td>\n",
+       "      <td>1457</td>\n",
+       "      <td>1073</td>\n",
+       "      <td>2064</td>\n",
+       "      <td>1466</td>\n",
+       "      <td>767</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2020-01-24 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11856</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12760</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11933</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>802</td>\n",
+       "      <td>...</td>\n",
+       "      <td>612</td>\n",
+       "      <td>1529</td>\n",
+       "      <td>1187</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>1231</td>\n",
+       "      <td>1410</td>\n",
+       "      <td>1028</td>\n",
+       "      <td>1833</td>\n",
+       "      <td>1253</td>\n",
+       "      <td>723</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2020-01-31 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11612</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12206</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11419</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>760</td>\n",
+       "      <td>...</td>\n",
+       "      <td>561</td>\n",
+       "      <td>1461</td>\n",
+       "      <td>1136</td>\n",
+       "      <td>1015</td>\n",
+       "      <td>1262</td>\n",
+       "      <td>1286</td>\n",
+       "      <td>1092</td>\n",
+       "      <td>1820</td>\n",
+       "      <td>1233</td>\n",
+       "      <td>727</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2020-02-07 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10986</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11925</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11154</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>729</td>\n",
+       "      <td>...</td>\n",
+       "      <td>564</td>\n",
+       "      <td>1529</td>\n",
+       "      <td>1072</td>\n",
+       "      <td>922</td>\n",
+       "      <td>1052</td>\n",
+       "      <td>1259</td>\n",
+       "      <td>987</td>\n",
+       "      <td>1729</td>\n",
+       "      <td>1157</td>\n",
+       "      <td>690</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2020-02-14 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10944</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11627</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10876</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>722</td>\n",
+       "      <td>...</td>\n",
+       "      <td>573</td>\n",
+       "      <td>1427</td>\n",
+       "      <td>1059</td>\n",
+       "      <td>976</td>\n",
+       "      <td>1159</td>\n",
+       "      <td>1172</td>\n",
+       "      <td>967</td>\n",
+       "      <td>1688</td>\n",
+       "      <td>1169</td>\n",
+       "      <td>728</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2020-02-21 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10841</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11548</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10790</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>724</td>\n",
+       "      <td>...</td>\n",
+       "      <td>539</td>\n",
+       "      <td>1477</td>\n",
+       "      <td>1087</td>\n",
+       "      <td>924</td>\n",
+       "      <td>1116</td>\n",
+       "      <td>1167</td>\n",
+       "      <td>1032</td>\n",
+       "      <td>1675</td>\n",
+       "      <td>1118</td>\n",
+       "      <td>679</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2020-02-28 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10816</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11183</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10448</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>698</td>\n",
+       "      <td>...</td>\n",
+       "      <td>572</td>\n",
+       "      <td>1476</td>\n",
+       "      <td>1078</td>\n",
+       "      <td>919</td>\n",
+       "      <td>1174</td>\n",
+       "      <td>1115</td>\n",
+       "      <td>1085</td>\n",
+       "      <td>1587</td>\n",
+       "      <td>1133</td>\n",
+       "      <td>651</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>2020-03-06 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10895</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11498</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10745</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>720</td>\n",
+       "      <td>...</td>\n",
+       "      <td>568</td>\n",
+       "      <td>1490</td>\n",
+       "      <td>1112</td>\n",
+       "      <td>930</td>\n",
+       "      <td>1098</td>\n",
+       "      <td>1149</td>\n",
+       "      <td>982</td>\n",
+       "      <td>1726</td>\n",
+       "      <td>1170</td>\n",
+       "      <td>652</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>2020-03-13 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11019</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11205</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10447</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>727</td>\n",
+       "      <td>...</td>\n",
+       "      <td>590</td>\n",
+       "      <td>1472</td>\n",
+       "      <td>1053</td>\n",
+       "      <td>915</td>\n",
+       "      <td>1187</td>\n",
+       "      <td>1211</td>\n",
+       "      <td>964</td>\n",
+       "      <td>1751</td>\n",
+       "      <td>1174</td>\n",
+       "      <td>675</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>2020-03-20 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10645</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10573</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9841</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>677</td>\n",
+       "      <td>...</td>\n",
+       "      <td>522</td>\n",
+       "      <td>1443</td>\n",
+       "      <td>1012</td>\n",
+       "      <td>947</td>\n",
+       "      <td>1115</td>\n",
+       "      <td>1043</td>\n",
+       "      <td>1008</td>\n",
+       "      <td>1657</td>\n",
+       "      <td>1156</td>\n",
+       "      <td>719</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>2020-03-27 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11141</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10130</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9414</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>665</td>\n",
+       "      <td>...</td>\n",
+       "      <td>542</td>\n",
+       "      <td>1538</td>\n",
+       "      <td>982</td>\n",
+       "      <td>922</td>\n",
+       "      <td>1035</td>\n",
+       "      <td>1182</td>\n",
+       "      <td>1297</td>\n",
+       "      <td>1822</td>\n",
+       "      <td>1092</td>\n",
+       "      <td>719</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>2020-04-03 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>16387</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10305</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9601</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>667</td>\n",
+       "      <td>...</td>\n",
+       "      <td>770</td>\n",
+       "      <td>2137</td>\n",
+       "      <td>1436</td>\n",
+       "      <td>1246</td>\n",
+       "      <td>1812</td>\n",
+       "      <td>1717</td>\n",
+       "      <td>2511</td>\n",
+       "      <td>2294</td>\n",
+       "      <td>1520</td>\n",
+       "      <td>920</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>2020-04-10 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>18516</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10520</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9807</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>671</td>\n",
+       "      <td>...</td>\n",
+       "      <td>849</td>\n",
+       "      <td>2597</td>\n",
+       "      <td>1503</td>\n",
+       "      <td>1452</td>\n",
+       "      <td>2182</td>\n",
+       "      <td>1984</td>\n",
+       "      <td>2832</td>\n",
+       "      <td>2604</td>\n",
+       "      <td>1560</td>\n",
+       "      <td>928</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>2020-04-17 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>22351</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10497</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9787</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>661</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1155</td>\n",
+       "      <td>3195</td>\n",
+       "      <td>1960</td>\n",
+       "      <td>1632</td>\n",
+       "      <td>2536</td>\n",
+       "      <td>2466</td>\n",
+       "      <td>3275</td>\n",
+       "      <td>3084</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1169</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>2020-04-24 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>21997</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10458</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9768</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>662</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1103</td>\n",
+       "      <td>3109</td>\n",
+       "      <td>2095</td>\n",
+       "      <td>1711</td>\n",
+       "      <td>2481</td>\n",
+       "      <td>2299</td>\n",
+       "      <td>2785</td>\n",
+       "      <td>3334</td>\n",
+       "      <td>1924</td>\n",
+       "      <td>1124</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>2020-05-01 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>17953</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9941</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9289</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>624</td>\n",
+       "      <td>...</td>\n",
+       "      <td>922</td>\n",
+       "      <td>2503</td>\n",
+       "      <td>1844</td>\n",
+       "      <td>1418</td>\n",
+       "      <td>1975</td>\n",
+       "      <td>1982</td>\n",
+       "      <td>1953</td>\n",
+       "      <td>2853</td>\n",
+       "      <td>1554</td>\n",
+       "      <td>929</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>2020-05-08 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12657</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9576</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8937</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>612</td>\n",
+       "      <td>...</td>\n",
+       "      <td>769</td>\n",
+       "      <td>1790</td>\n",
+       "      <td>1328</td>\n",
+       "      <td>1094</td>\n",
+       "      <td>1326</td>\n",
+       "      <td>1321</td>\n",
+       "      <td>1213</td>\n",
+       "      <td>1887</td>\n",
+       "      <td>1218</td>\n",
+       "      <td>692</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>2020-05-15 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14573</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10188</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9526</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>635</td>\n",
+       "      <td>...</td>\n",
+       "      <td>845</td>\n",
+       "      <td>1992</td>\n",
+       "      <td>1589</td>\n",
+       "      <td>1283</td>\n",
+       "      <td>1502</td>\n",
+       "      <td>1543</td>\n",
+       "      <td>1329</td>\n",
+       "      <td>2251</td>\n",
+       "      <td>1449</td>\n",
+       "      <td>772</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>2020-05-22 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12288</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9940</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9299</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>614</td>\n",
+       "      <td>...</td>\n",
+       "      <td>718</td>\n",
+       "      <td>1636</td>\n",
+       "      <td>1236</td>\n",
+       "      <td>1041</td>\n",
+       "      <td>1319</td>\n",
+       "      <td>1397</td>\n",
+       "      <td>1125</td>\n",
+       "      <td>1937</td>\n",
+       "      <td>1177</td>\n",
+       "      <td>692</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>2020-05-29 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9824</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8171</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7607</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>546</td>\n",
+       "      <td>...</td>\n",
+       "      <td>550</td>\n",
+       "      <td>1337</td>\n",
+       "      <td>1046</td>\n",
+       "      <td>863</td>\n",
+       "      <td>970</td>\n",
+       "      <td>1095</td>\n",
+       "      <td>841</td>\n",
+       "      <td>1515</td>\n",
+       "      <td>1011</td>\n",
+       "      <td>587</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>2020-06-05 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10709</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9977</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9346</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>610</td>\n",
+       "      <td>...</td>\n",
+       "      <td>576</td>\n",
+       "      <td>1478</td>\n",
+       "      <td>1090</td>\n",
+       "      <td>931</td>\n",
+       "      <td>1172</td>\n",
+       "      <td>1131</td>\n",
+       "      <td>891</td>\n",
+       "      <td>1610</td>\n",
+       "      <td>1116</td>\n",
+       "      <td>700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>2020-06-12 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9976</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9417</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8803</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>588</td>\n",
+       "      <td>...</td>\n",
+       "      <td>478</td>\n",
+       "      <td>1374</td>\n",
+       "      <td>980</td>\n",
+       "      <td>967</td>\n",
+       "      <td>1096</td>\n",
+       "      <td>1048</td>\n",
+       "      <td>883</td>\n",
+       "      <td>1530</td>\n",
+       "      <td>1035</td>\n",
+       "      <td>574</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>2020-06-19 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9339</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9404</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8810</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>573</td>\n",
+       "      <td>...</td>\n",
+       "      <td>498</td>\n",
+       "      <td>1234</td>\n",
+       "      <td>952</td>\n",
+       "      <td>835</td>\n",
+       "      <td>973</td>\n",
+       "      <td>927</td>\n",
+       "      <td>896</td>\n",
+       "      <td>1411</td>\n",
+       "      <td>990</td>\n",
+       "      <td>617</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>2020-06-26 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8979</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9293</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8695</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>571</td>\n",
+       "      <td>...</td>\n",
+       "      <td>485</td>\n",
+       "      <td>1300</td>\n",
+       "      <td>922</td>\n",
+       "      <td>800</td>\n",
+       "      <td>946</td>\n",
+       "      <td>880</td>\n",
+       "      <td>791</td>\n",
+       "      <td>1311</td>\n",
+       "      <td>979</td>\n",
+       "      <td>552</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>2020-07-03 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9140</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9183</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8606</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>555</td>\n",
+       "      <td>...</td>\n",
+       "      <td>515</td>\n",
+       "      <td>1225</td>\n",
+       "      <td>875</td>\n",
+       "      <td>827</td>\n",
+       "      <td>949</td>\n",
+       "      <td>922</td>\n",
+       "      <td>837</td>\n",
+       "      <td>1454</td>\n",
+       "      <td>938</td>\n",
+       "      <td>584</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>2020-07-10 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8690</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9250</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8648</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>578</td>\n",
+       "      <td>...</td>\n",
+       "      <td>468</td>\n",
+       "      <td>1154</td>\n",
+       "      <td>848</td>\n",
+       "      <td>771</td>\n",
+       "      <td>902</td>\n",
+       "      <td>999</td>\n",
+       "      <td>803</td>\n",
+       "      <td>1228</td>\n",
+       "      <td>930</td>\n",
+       "      <td>572</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>2020-07-17 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8823</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9093</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8502</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>557</td>\n",
+       "      <td>...</td>\n",
+       "      <td>445</td>\n",
+       "      <td>1159</td>\n",
+       "      <td>843</td>\n",
+       "      <td>816</td>\n",
+       "      <td>956</td>\n",
+       "      <td>945</td>\n",
+       "      <td>806</td>\n",
+       "      <td>1339</td>\n",
+       "      <td>953</td>\n",
+       "      <td>550</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>2020-07-24 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8891</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9052</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8452</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>566</td>\n",
+       "      <td>...</td>\n",
+       "      <td>493</td>\n",
+       "      <td>1197</td>\n",
+       "      <td>817</td>\n",
+       "      <td>798</td>\n",
+       "      <td>964</td>\n",
+       "      <td>951</td>\n",
+       "      <td>816</td>\n",
+       "      <td>1340</td>\n",
+       "      <td>941</td>\n",
+       "      <td>565</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>2020-07-31 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8946</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9036</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8436</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>572</td>\n",
+       "      <td>...</td>\n",
+       "      <td>507</td>\n",
+       "      <td>1272</td>\n",
+       "      <td>837</td>\n",
+       "      <td>729</td>\n",
+       "      <td>902</td>\n",
+       "      <td>949</td>\n",
+       "      <td>773</td>\n",
+       "      <td>1447</td>\n",
+       "      <td>988</td>\n",
+       "      <td>531</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>2020-08-07 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8945</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9102</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8502</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>571</td>\n",
+       "      <td>...</td>\n",
+       "      <td>486</td>\n",
+       "      <td>1211</td>\n",
+       "      <td>851</td>\n",
+       "      <td>798</td>\n",
+       "      <td>933</td>\n",
+       "      <td>955</td>\n",
+       "      <td>832</td>\n",
+       "      <td>1370</td>\n",
+       "      <td>929</td>\n",
+       "      <td>563</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>2020-08-14 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9392</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9085</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8494</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>564</td>\n",
+       "      <td>...</td>\n",
+       "      <td>520</td>\n",
+       "      <td>1304</td>\n",
+       "      <td>853</td>\n",
+       "      <td>829</td>\n",
+       "      <td>923</td>\n",
+       "      <td>1006</td>\n",
+       "      <td>928</td>\n",
+       "      <td>1395</td>\n",
+       "      <td>1009</td>\n",
+       "      <td>617</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>2020-08-21 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9631</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9157</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8560</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>573</td>\n",
+       "      <td>...</td>\n",
+       "      <td>479</td>\n",
+       "      <td>1269</td>\n",
+       "      <td>870</td>\n",
+       "      <td>780</td>\n",
+       "      <td>1028</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>920</td>\n",
+       "      <td>1608</td>\n",
+       "      <td>1043</td>\n",
+       "      <td>594</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>2020-08-28 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9032</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8241</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7674</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>539</td>\n",
+       "      <td>...</td>\n",
+       "      <td>455</td>\n",
+       "      <td>1148</td>\n",
+       "      <td>922</td>\n",
+       "      <td>724</td>\n",
+       "      <td>945</td>\n",
+       "      <td>951</td>\n",
+       "      <td>810</td>\n",
+       "      <td>1511</td>\n",
+       "      <td>959</td>\n",
+       "      <td>591</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>2020-09-04 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7739</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9182</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8604</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>552</td>\n",
+       "      <td>...</td>\n",
+       "      <td>431</td>\n",
+       "      <td>1057</td>\n",
+       "      <td>780</td>\n",
+       "      <td>640</td>\n",
+       "      <td>770</td>\n",
+       "      <td>806</td>\n",
+       "      <td>737</td>\n",
+       "      <td>1208</td>\n",
+       "      <td>803</td>\n",
+       "      <td>488</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>2020-09-11 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9811</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9306</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8708</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>577</td>\n",
+       "      <td>...</td>\n",
+       "      <td>502</td>\n",
+       "      <td>1229</td>\n",
+       "      <td>952</td>\n",
+       "      <td>867</td>\n",
+       "      <td>1021</td>\n",
+       "      <td>1052</td>\n",
+       "      <td>898</td>\n",
+       "      <td>1610</td>\n",
+       "      <td>1084</td>\n",
+       "      <td>578</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>2020-09-18 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9523</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9264</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8663</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>575</td>\n",
+       "      <td>...</td>\n",
+       "      <td>465</td>\n",
+       "      <td>1287</td>\n",
+       "      <td>939</td>\n",
+       "      <td>795</td>\n",
+       "      <td>1051</td>\n",
+       "      <td>1023</td>\n",
+       "      <td>844</td>\n",
+       "      <td>1530</td>\n",
+       "      <td>1021</td>\n",
+       "      <td>555</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>2020-09-25 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9634</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9377</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8744</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>604</td>\n",
+       "      <td>...</td>\n",
+       "      <td>514</td>\n",
+       "      <td>1271</td>\n",
+       "      <td>965</td>\n",
+       "      <td>825</td>\n",
+       "      <td>1036</td>\n",
+       "      <td>963</td>\n",
+       "      <td>869</td>\n",
+       "      <td>1521</td>\n",
+       "      <td>1041</td>\n",
+       "      <td>617</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>2020-10-02 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9945</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9555</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8942</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>587</td>\n",
+       "      <td>...</td>\n",
+       "      <td>558</td>\n",
+       "      <td>1301</td>\n",
+       "      <td>978</td>\n",
+       "      <td>842</td>\n",
+       "      <td>1045</td>\n",
+       "      <td>1054</td>\n",
+       "      <td>899</td>\n",
+       "      <td>1577</td>\n",
+       "      <td>1003</td>\n",
+       "      <td>671</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>2020-10-09 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9954</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9811</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9168</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>615</td>\n",
+       "      <td>...</td>\n",
+       "      <td>544</td>\n",
+       "      <td>1367</td>\n",
+       "      <td>1067</td>\n",
+       "      <td>884</td>\n",
+       "      <td>1053</td>\n",
+       "      <td>1019</td>\n",
+       "      <td>902</td>\n",
+       "      <td>1462</td>\n",
+       "      <td>1010</td>\n",
+       "      <td>638</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>2020-10-16 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10534</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9865</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9215</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>630</td>\n",
+       "      <td>...</td>\n",
+       "      <td>606</td>\n",
+       "      <td>1553</td>\n",
+       "      <td>1001</td>\n",
+       "      <td>904</td>\n",
+       "      <td>1154</td>\n",
+       "      <td>1056</td>\n",
+       "      <td>923</td>\n",
+       "      <td>1462</td>\n",
+       "      <td>1174</td>\n",
+       "      <td>688</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>2020-10-23 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10739</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9759</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9104</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>628</td>\n",
+       "      <td>...</td>\n",
+       "      <td>600</td>\n",
+       "      <td>1714</td>\n",
+       "      <td>1111</td>\n",
+       "      <td>891</td>\n",
+       "      <td>1124</td>\n",
+       "      <td>1154</td>\n",
+       "      <td>922</td>\n",
+       "      <td>1510</td>\n",
+       "      <td>1044</td>\n",
+       "      <td>661</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>2020-10-30 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10887</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9891</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9248</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>616</td>\n",
+       "      <td>...</td>\n",
+       "      <td>591</td>\n",
+       "      <td>1754</td>\n",
+       "      <td>1168</td>\n",
+       "      <td>882</td>\n",
+       "      <td>1102</td>\n",
+       "      <td>1089</td>\n",
+       "      <td>888</td>\n",
+       "      <td>1563</td>\n",
+       "      <td>1129</td>\n",
+       "      <td>712</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>2020-11-06 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11812</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10331</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9675</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>625</td>\n",
+       "      <td>...</td>\n",
+       "      <td>675</td>\n",
+       "      <td>1900</td>\n",
+       "      <td>1294</td>\n",
+       "      <td>990</td>\n",
+       "      <td>1186</td>\n",
+       "      <td>1177</td>\n",
+       "      <td>952</td>\n",
+       "      <td>1614</td>\n",
+       "      <td>1174</td>\n",
+       "      <td>832</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>2020-11-13 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12254</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10350</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9662</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>658</td>\n",
+       "      <td>...</td>\n",
+       "      <td>711</td>\n",
+       "      <td>1950</td>\n",
+       "      <td>1350</td>\n",
+       "      <td>1099</td>\n",
+       "      <td>1317</td>\n",
+       "      <td>1172</td>\n",
+       "      <td>1112</td>\n",
+       "      <td>1616</td>\n",
+       "      <td>1168</td>\n",
+       "      <td>742</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>2020-11-20 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12535</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10380</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9701</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>653</td>\n",
+       "      <td>...</td>\n",
+       "      <td>691</td>\n",
+       "      <td>1935</td>\n",
+       "      <td>1441</td>\n",
+       "      <td>1105</td>\n",
+       "      <td>1385</td>\n",
+       "      <td>1186</td>\n",
+       "      <td>1086</td>\n",
+       "      <td>1687</td>\n",
+       "      <td>1159</td>\n",
+       "      <td>848</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>2020-11-27 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12456</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10357</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9690</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>646</td>\n",
+       "      <td>...</td>\n",
+       "      <td>679</td>\n",
+       "      <td>1791</td>\n",
+       "      <td>1501</td>\n",
+       "      <td>1218</td>\n",
+       "      <td>1358</td>\n",
+       "      <td>1159</td>\n",
+       "      <td>1012</td>\n",
+       "      <td>1655</td>\n",
+       "      <td>1272</td>\n",
+       "      <td>797</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>2020-12-04 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12303</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10695</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9995</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>679</td>\n",
+       "      <td>...</td>\n",
+       "      <td>645</td>\n",
+       "      <td>1679</td>\n",
+       "      <td>1403</td>\n",
+       "      <td>1121</td>\n",
+       "      <td>1340</td>\n",
+       "      <td>1229</td>\n",
+       "      <td>1029</td>\n",
+       "      <td>1720</td>\n",
+       "      <td>1284</td>\n",
+       "      <td>836</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>2020-12-11 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12292</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10750</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10034</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>693</td>\n",
+       "      <td>...</td>\n",
+       "      <td>661</td>\n",
+       "      <td>1691</td>\n",
+       "      <td>1326</td>\n",
+       "      <td>1199</td>\n",
+       "      <td>1432</td>\n",
+       "      <td>1224</td>\n",
+       "      <td>1065</td>\n",
+       "      <td>1706</td>\n",
+       "      <td>1156</td>\n",
+       "      <td>814</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>2020-12-18 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13011</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11548</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10804</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>718</td>\n",
+       "      <td>...</td>\n",
+       "      <td>689</td>\n",
+       "      <td>1718</td>\n",
+       "      <td>1380</td>\n",
+       "      <td>1199</td>\n",
+       "      <td>1385</td>\n",
+       "      <td>1317</td>\n",
+       "      <td>1167</td>\n",
+       "      <td>1947</td>\n",
+       "      <td>1311</td>\n",
+       "      <td>882</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>2020-12-25 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11520</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7954</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7421</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>518</td>\n",
+       "      <td>...</td>\n",
+       "      <td>669</td>\n",
+       "      <td>1463</td>\n",
+       "      <td>1130</td>\n",
+       "      <td>1097</td>\n",
+       "      <td>1217</td>\n",
+       "      <td>1198</td>\n",
+       "      <td>1090</td>\n",
+       "      <td>1701</td>\n",
+       "      <td>1115</td>\n",
+       "      <td>825</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>2021-01-01 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10069</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7954</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7421</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>518</td>\n",
+       "      <td>...</td>\n",
+       "      <td>547</td>\n",
+       "      <td>1346</td>\n",
+       "      <td>886</td>\n",
+       "      <td>842</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>997</td>\n",
+       "      <td>1159</td>\n",
+       "      <td>1595</td>\n",
+       "      <td>929</td>\n",
+       "      <td>727</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>54 rows × 91 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                      Week ended  NaN  NaN  Total deaths, all ages  \\\n",
+       "Week number           Week ended  NaN  NaN  Total deaths, all ages   \n",
+       "1            2020-01-03 00:00:00  NaN  NaN                   12254   \n",
+       "2            2020-01-10 00:00:00  NaN  NaN                   14058   \n",
+       "3            2020-01-17 00:00:00  NaN  NaN                   12990   \n",
+       "4            2020-01-24 00:00:00  NaN  NaN                   11856   \n",
+       "5            2020-01-31 00:00:00  NaN  NaN                   11612   \n",
+       "6            2020-02-07 00:00:00  NaN  NaN                   10986   \n",
+       "7            2020-02-14 00:00:00  NaN  NaN                   10944   \n",
+       "8            2020-02-21 00:00:00  NaN  NaN                   10841   \n",
+       "9            2020-02-28 00:00:00  NaN  NaN                   10816   \n",
+       "10           2020-03-06 00:00:00  NaN  NaN                   10895   \n",
+       "11           2020-03-13 00:00:00  NaN  NaN                   11019   \n",
+       "12           2020-03-20 00:00:00  NaN  NaN                   10645   \n",
+       "13           2020-03-27 00:00:00  NaN  NaN                   11141   \n",
+       "14           2020-04-03 00:00:00  NaN  NaN                   16387   \n",
+       "15           2020-04-10 00:00:00  NaN  NaN                   18516   \n",
+       "16           2020-04-17 00:00:00  NaN  NaN                   22351   \n",
+       "17           2020-04-24 00:00:00  NaN  NaN                   21997   \n",
+       "18           2020-05-01 00:00:00  NaN  NaN                   17953   \n",
+       "19           2020-05-08 00:00:00  NaN  NaN                   12657   \n",
+       "20           2020-05-15 00:00:00  NaN  NaN                   14573   \n",
+       "21           2020-05-22 00:00:00  NaN  NaN                   12288   \n",
+       "22           2020-05-29 00:00:00  NaN  NaN                    9824   \n",
+       "23           2020-06-05 00:00:00  NaN  NaN                   10709   \n",
+       "24           2020-06-12 00:00:00  NaN  NaN                    9976   \n",
+       "25           2020-06-19 00:00:00  NaN  NaN                    9339   \n",
+       "26           2020-06-26 00:00:00  NaN  NaN                    8979   \n",
+       "27           2020-07-03 00:00:00  NaN  NaN                    9140   \n",
+       "28           2020-07-10 00:00:00  NaN  NaN                    8690   \n",
+       "29           2020-07-17 00:00:00  NaN  NaN                    8823   \n",
+       "30           2020-07-24 00:00:00  NaN  NaN                    8891   \n",
+       "31           2020-07-31 00:00:00  NaN  NaN                    8946   \n",
+       "32           2020-08-07 00:00:00  NaN  NaN                    8945   \n",
+       "33           2020-08-14 00:00:00  NaN  NaN                    9392   \n",
+       "34           2020-08-21 00:00:00  NaN  NaN                    9631   \n",
+       "35           2020-08-28 00:00:00  NaN  NaN                    9032   \n",
+       "36           2020-09-04 00:00:00  NaN  NaN                    7739   \n",
+       "37           2020-09-11 00:00:00  NaN  NaN                    9811   \n",
+       "38           2020-09-18 00:00:00  NaN  NaN                    9523   \n",
+       "39           2020-09-25 00:00:00  NaN  NaN                    9634   \n",
+       "40           2020-10-02 00:00:00  NaN  NaN                    9945   \n",
+       "41           2020-10-09 00:00:00  NaN  NaN                    9954   \n",
+       "42           2020-10-16 00:00:00  NaN  NaN                   10534   \n",
+       "43           2020-10-23 00:00:00  NaN  NaN                   10739   \n",
+       "44           2020-10-30 00:00:00  NaN  NaN                   10887   \n",
+       "45           2020-11-06 00:00:00  NaN  NaN                   11812   \n",
+       "46           2020-11-13 00:00:00  NaN  NaN                   12254   \n",
+       "47           2020-11-20 00:00:00  NaN  NaN                   12535   \n",
+       "48           2020-11-27 00:00:00  NaN  NaN                   12456   \n",
+       "49           2020-12-04 00:00:00  NaN  NaN                   12303   \n",
+       "50           2020-12-11 00:00:00  NaN  NaN                   12292   \n",
+       "51           2020-12-18 00:00:00  NaN  NaN                   13011   \n",
+       "52           2020-12-25 00:00:00  NaN  NaN                   11520   \n",
+       "53           2021-01-01 00:00:00  NaN  NaN                   10069   \n",
+       "\n",
+       "             Total deaths: average of corresponding  \\\n",
+       "Week number  Total deaths: average of corresponding   \n",
+       "1                                               NaN   \n",
+       "2                                               NaN   \n",
+       "3                                               NaN   \n",
+       "4                                               NaN   \n",
+       "5                                               NaN   \n",
+       "6                                               NaN   \n",
+       "7                                               NaN   \n",
+       "8                                               NaN   \n",
+       "9                                               NaN   \n",
+       "10                                              NaN   \n",
+       "11                                              NaN   \n",
+       "12                                              NaN   \n",
+       "13                                              NaN   \n",
+       "14                                              NaN   \n",
+       "15                                              NaN   \n",
+       "16                                              NaN   \n",
+       "17                                              NaN   \n",
+       "18                                              NaN   \n",
+       "19                                              NaN   \n",
+       "20                                              NaN   \n",
+       "21                                              NaN   \n",
+       "22                                              NaN   \n",
+       "23                                              NaN   \n",
+       "24                                              NaN   \n",
+       "25                                              NaN   \n",
+       "26                                              NaN   \n",
+       "27                                              NaN   \n",
+       "28                                              NaN   \n",
+       "29                                              NaN   \n",
+       "30                                              NaN   \n",
+       "31                                              NaN   \n",
+       "32                                              NaN   \n",
+       "33                                              NaN   \n",
+       "34                                              NaN   \n",
+       "35                                              NaN   \n",
+       "36                                              NaN   \n",
+       "37                                              NaN   \n",
+       "38                                              NaN   \n",
+       "39                                              NaN   \n",
+       "40                                              NaN   \n",
+       "41                                              NaN   \n",
+       "42                                              NaN   \n",
+       "43                                              NaN   \n",
+       "44                                              NaN   \n",
+       "45                                              NaN   \n",
+       "46                                              NaN   \n",
+       "47                                              NaN   \n",
+       "48                                              NaN   \n",
+       "49                                              NaN   \n",
+       "50                                              NaN   \n",
+       "51                                              NaN   \n",
+       "52                                              NaN   \n",
+       "53                                              NaN   \n",
+       "\n",
+       "            week over the previous 5 years 1, 10, 11 (England and Wales)  \\\n",
+       "Week number  week over the previous 5 years 1, 10, 11 (Engl...             \n",
+       "1                                                        12175             \n",
+       "2                                                        13822             \n",
+       "3                                                        13216             \n",
+       "4                                                        12760             \n",
+       "5                                                        12206             \n",
+       "6                                                        11925             \n",
+       "7                                                        11627             \n",
+       "8                                                        11548             \n",
+       "9                                                        11183             \n",
+       "10                                                       11498             \n",
+       "11                                                       11205             \n",
+       "12                                                       10573             \n",
+       "13                                                       10130             \n",
+       "14                                                       10305             \n",
+       "15                                                       10520             \n",
+       "16                                                       10497             \n",
+       "17                                                       10458             \n",
+       "18                                                        9941             \n",
+       "19                                                        9576             \n",
+       "20                                                       10188             \n",
+       "21                                                        9940             \n",
+       "22                                                        8171             \n",
+       "23                                                        9977             \n",
+       "24                                                        9417             \n",
+       "25                                                        9404             \n",
+       "26                                                        9293             \n",
+       "27                                                        9183             \n",
+       "28                                                        9250             \n",
+       "29                                                        9093             \n",
+       "30                                                        9052             \n",
+       "31                                                        9036             \n",
+       "32                                                        9102             \n",
+       "33                                                        9085             \n",
+       "34                                                        9157             \n",
+       "35                                                        8241             \n",
+       "36                                                        9182             \n",
+       "37                                                        9306             \n",
+       "38                                                        9264             \n",
+       "39                                                        9377             \n",
+       "40                                                        9555             \n",
+       "41                                                        9811             \n",
+       "42                                                        9865             \n",
+       "43                                                        9759             \n",
+       "44                                                        9891             \n",
+       "45                                                       10331             \n",
+       "46                                                       10350             \n",
+       "47                                                       10380             \n",
+       "48                                                       10357             \n",
+       "49                                                       10695             \n",
+       "50                                                       10750             \n",
+       "51                                                       11548             \n",
+       "52                                                        7954             \n",
+       "53                                                        7954             \n",
+       "\n",
+       "             Total deaths: average of corresponding  \\\n",
+       "Week number  Total deaths: average of corresponding   \n",
+       "1                                               NaN   \n",
+       "2                                               NaN   \n",
+       "3                                               NaN   \n",
+       "4                                               NaN   \n",
+       "5                                               NaN   \n",
+       "6                                               NaN   \n",
+       "7                                               NaN   \n",
+       "8                                               NaN   \n",
+       "9                                               NaN   \n",
+       "10                                              NaN   \n",
+       "11                                              NaN   \n",
+       "12                                              NaN   \n",
+       "13                                              NaN   \n",
+       "14                                              NaN   \n",
+       "15                                              NaN   \n",
+       "16                                              NaN   \n",
+       "17                                              NaN   \n",
+       "18                                              NaN   \n",
+       "19                                              NaN   \n",
+       "20                                              NaN   \n",
+       "21                                              NaN   \n",
+       "22                                              NaN   \n",
+       "23                                              NaN   \n",
+       "24                                              NaN   \n",
+       "25                                              NaN   \n",
+       "26                                              NaN   \n",
+       "27                                              NaN   \n",
+       "28                                              NaN   \n",
+       "29                                              NaN   \n",
+       "30                                              NaN   \n",
+       "31                                              NaN   \n",
+       "32                                              NaN   \n",
+       "33                                              NaN   \n",
+       "34                                              NaN   \n",
+       "35                                              NaN   \n",
+       "36                                              NaN   \n",
+       "37                                              NaN   \n",
+       "38                                              NaN   \n",
+       "39                                              NaN   \n",
+       "40                                              NaN   \n",
+       "41                                              NaN   \n",
+       "42                                              NaN   \n",
+       "43                                              NaN   \n",
+       "44                                              NaN   \n",
+       "45                                              NaN   \n",
+       "46                                              NaN   \n",
+       "47                                              NaN   \n",
+       "48                                              NaN   \n",
+       "49                                              NaN   \n",
+       "50                                              NaN   \n",
+       "51                                              NaN   \n",
+       "52                                              NaN   \n",
+       "53                                              NaN   \n",
+       "\n",
+       "            week over the previous 5 years 1, 10, 11 (England)  \\\n",
+       "Week number  week over the previous 5 years 1, 10, 11 (Engl...   \n",
+       "1                                                        11412   \n",
+       "2                                                        12933   \n",
+       "3                                                        12370   \n",
+       "4                                                        11933   \n",
+       "5                                                        11419   \n",
+       "6                                                        11154   \n",
+       "7                                                        10876   \n",
+       "8                                                        10790   \n",
+       "9                                                        10448   \n",
+       "10                                                       10745   \n",
+       "11                                                       10447   \n",
+       "12                                                        9841   \n",
+       "13                                                        9414   \n",
+       "14                                                        9601   \n",
+       "15                                                        9807   \n",
+       "16                                                        9787   \n",
+       "17                                                        9768   \n",
+       "18                                                        9289   \n",
+       "19                                                        8937   \n",
+       "20                                                        9526   \n",
+       "21                                                        9299   \n",
+       "22                                                        7607   \n",
+       "23                                                        9346   \n",
+       "24                                                        8803   \n",
+       "25                                                        8810   \n",
+       "26                                                        8695   \n",
+       "27                                                        8606   \n",
+       "28                                                        8648   \n",
+       "29                                                        8502   \n",
+       "30                                                        8452   \n",
+       "31                                                        8436   \n",
+       "32                                                        8502   \n",
+       "33                                                        8494   \n",
+       "34                                                        8560   \n",
+       "35                                                        7674   \n",
+       "36                                                        8604   \n",
+       "37                                                        8708   \n",
+       "38                                                        8663   \n",
+       "39                                                        8744   \n",
+       "40                                                        8942   \n",
+       "41                                                        9168   \n",
+       "42                                                        9215   \n",
+       "43                                                        9104   \n",
+       "44                                                        9248   \n",
+       "45                                                        9675   \n",
+       "46                                                        9662   \n",
+       "47                                                        9701   \n",
+       "48                                                        9690   \n",
+       "49                                                        9995   \n",
+       "50                                                       10034   \n",
+       "51                                                       10804   \n",
+       "52                                                        7421   \n",
+       "53                                                        7421   \n",
+       "\n",
+       "             Total deaths: average of corresponding  \\\n",
+       "Week number  Total deaths: average of corresponding   \n",
+       "1                                               NaN   \n",
+       "2                                               NaN   \n",
+       "3                                               NaN   \n",
+       "4                                               NaN   \n",
+       "5                                               NaN   \n",
+       "6                                               NaN   \n",
+       "7                                               NaN   \n",
+       "8                                               NaN   \n",
+       "9                                               NaN   \n",
+       "10                                              NaN   \n",
+       "11                                              NaN   \n",
+       "12                                              NaN   \n",
+       "13                                              NaN   \n",
+       "14                                              NaN   \n",
+       "15                                              NaN   \n",
+       "16                                              NaN   \n",
+       "17                                              NaN   \n",
+       "18                                              NaN   \n",
+       "19                                              NaN   \n",
+       "20                                              NaN   \n",
+       "21                                              NaN   \n",
+       "22                                              NaN   \n",
+       "23                                              NaN   \n",
+       "24                                              NaN   \n",
+       "25                                              NaN   \n",
+       "26                                              NaN   \n",
+       "27                                              NaN   \n",
+       "28                                              NaN   \n",
+       "29                                              NaN   \n",
+       "30                                              NaN   \n",
+       "31                                              NaN   \n",
+       "32                                              NaN   \n",
+       "33                                              NaN   \n",
+       "34                                              NaN   \n",
+       "35                                              NaN   \n",
+       "36                                              NaN   \n",
+       "37                                              NaN   \n",
+       "38                                              NaN   \n",
+       "39                                              NaN   \n",
+       "40                                              NaN   \n",
+       "41                                              NaN   \n",
+       "42                                              NaN   \n",
+       "43                                              NaN   \n",
+       "44                                              NaN   \n",
+       "45                                              NaN   \n",
+       "46                                              NaN   \n",
+       "47                                              NaN   \n",
+       "48                                              NaN   \n",
+       "49                                              NaN   \n",
+       "50                                              NaN   \n",
+       "51                                              NaN   \n",
+       "52                                              NaN   \n",
+       "53                                              NaN   \n",
+       "\n",
+       "             week over the previous 5 years 1, 10, 11 (Wales)  ... North East  \\\n",
+       "Week number  week over the previous 5 years 1, 10, 11 (Wales)  ...  E12000001   \n",
+       "1                                                         756  ...        673   \n",
+       "2                                                         856  ...        707   \n",
+       "3                                                         812  ...        647   \n",
+       "4                                                         802  ...        612   \n",
+       "5                                                         760  ...        561   \n",
+       "6                                                         729  ...        564   \n",
+       "7                                                         722  ...        573   \n",
+       "8                                                         724  ...        539   \n",
+       "9                                                         698  ...        572   \n",
+       "10                                                        720  ...        568   \n",
+       "11                                                        727  ...        590   \n",
+       "12                                                        677  ...        522   \n",
+       "13                                                        665  ...        542   \n",
+       "14                                                        667  ...        770   \n",
+       "15                                                        671  ...        849   \n",
+       "16                                                        661  ...       1155   \n",
+       "17                                                        662  ...       1103   \n",
+       "18                                                        624  ...        922   \n",
+       "19                                                        612  ...        769   \n",
+       "20                                                        635  ...        845   \n",
+       "21                                                        614  ...        718   \n",
+       "22                                                        546  ...        550   \n",
+       "23                                                        610  ...        576   \n",
+       "24                                                        588  ...        478   \n",
+       "25                                                        573  ...        498   \n",
+       "26                                                        571  ...        485   \n",
+       "27                                                        555  ...        515   \n",
+       "28                                                        578  ...        468   \n",
+       "29                                                        557  ...        445   \n",
+       "30                                                        566  ...        493   \n",
+       "31                                                        572  ...        507   \n",
+       "32                                                        571  ...        486   \n",
+       "33                                                        564  ...        520   \n",
+       "34                                                        573  ...        479   \n",
+       "35                                                        539  ...        455   \n",
+       "36                                                        552  ...        431   \n",
+       "37                                                        577  ...        502   \n",
+       "38                                                        575  ...        465   \n",
+       "39                                                        604  ...        514   \n",
+       "40                                                        587  ...        558   \n",
+       "41                                                        615  ...        544   \n",
+       "42                                                        630  ...        606   \n",
+       "43                                                        628  ...        600   \n",
+       "44                                                        616  ...        591   \n",
+       "45                                                        625  ...        675   \n",
+       "46                                                        658  ...        711   \n",
+       "47                                                        653  ...        691   \n",
+       "48                                                        646  ...        679   \n",
+       "49                                                        679  ...        645   \n",
+       "50                                                        693  ...        661   \n",
+       "51                                                        718  ...        689   \n",
+       "52                                                        518  ...        669   \n",
+       "53                                                        518  ...        547   \n",
+       "\n",
+       "            North West Yorkshire and The Humber East Midlands West Midlands  \\\n",
+       "Week number  E12000002                E12000003     E12000004     E12000005   \n",
+       "1                 1806                     1240          1060          1349   \n",
+       "2                 1932                     1339          1195          1450   \n",
+       "3                 1696                     1278          1106          1407   \n",
+       "4                 1529                     1187          1024          1231   \n",
+       "5                 1461                     1136          1015          1262   \n",
+       "6                 1529                     1072           922          1052   \n",
+       "7                 1427                     1059           976          1159   \n",
+       "8                 1477                     1087           924          1116   \n",
+       "9                 1476                     1078           919          1174   \n",
+       "10                1490                     1112           930          1098   \n",
+       "11                1472                     1053           915          1187   \n",
+       "12                1443                     1012           947          1115   \n",
+       "13                1538                      982           922          1035   \n",
+       "14                2137                     1436          1246          1812   \n",
+       "15                2597                     1503          1452          2182   \n",
+       "16                3195                     1960          1632          2536   \n",
+       "17                3109                     2095          1711          2481   \n",
+       "18                2503                     1844          1418          1975   \n",
+       "19                1790                     1328          1094          1326   \n",
+       "20                1992                     1589          1283          1502   \n",
+       "21                1636                     1236          1041          1319   \n",
+       "22                1337                     1046           863           970   \n",
+       "23                1478                     1090           931          1172   \n",
+       "24                1374                      980           967          1096   \n",
+       "25                1234                      952           835           973   \n",
+       "26                1300                      922           800           946   \n",
+       "27                1225                      875           827           949   \n",
+       "28                1154                      848           771           902   \n",
+       "29                1159                      843           816           956   \n",
+       "30                1197                      817           798           964   \n",
+       "31                1272                      837           729           902   \n",
+       "32                1211                      851           798           933   \n",
+       "33                1304                      853           829           923   \n",
+       "34                1269                      870           780          1028   \n",
+       "35                1148                      922           724           945   \n",
+       "36                1057                      780           640           770   \n",
+       "37                1229                      952           867          1021   \n",
+       "38                1287                      939           795          1051   \n",
+       "39                1271                      965           825          1036   \n",
+       "40                1301                      978           842          1045   \n",
+       "41                1367                     1067           884          1053   \n",
+       "42                1553                     1001           904          1154   \n",
+       "43                1714                     1111           891          1124   \n",
+       "44                1754                     1168           882          1102   \n",
+       "45                1900                     1294           990          1186   \n",
+       "46                1950                     1350          1099          1317   \n",
+       "47                1935                     1441          1105          1385   \n",
+       "48                1791                     1501          1218          1358   \n",
+       "49                1679                     1403          1121          1340   \n",
+       "50                1691                     1326          1199          1432   \n",
+       "51                1718                     1380          1199          1385   \n",
+       "52                1463                     1130          1097          1217   \n",
+       "53                1346                      886           842          1024   \n",
+       "\n",
+       "                  East     London South East South West      Wales  \n",
+       "Week number  E12000006  E12000007  E12000008  E12000009  W92000004  \n",
+       "1                 1162       1113       1814       1225        787  \n",
+       "2                 1573       1272       2132       1487        939  \n",
+       "3                 1457       1073       2064       1466        767  \n",
+       "4                 1410       1028       1833       1253        723  \n",
+       "5                 1286       1092       1820       1233        727  \n",
+       "6                 1259        987       1729       1157        690  \n",
+       "7                 1172        967       1688       1169        728  \n",
+       "8                 1167       1032       1675       1118        679  \n",
+       "9                 1115       1085       1587       1133        651  \n",
+       "10                1149        982       1726       1170        652  \n",
+       "11                1211        964       1751       1174        675  \n",
+       "12                1043       1008       1657       1156        719  \n",
+       "13                1182       1297       1822       1092        719  \n",
+       "14                1717       2511       2294       1520        920  \n",
+       "15                1984       2832       2604       1560        928  \n",
+       "16                2466       3275       3084       1854       1169  \n",
+       "17                2299       2785       3334       1924       1124  \n",
+       "18                1982       1953       2853       1554        929  \n",
+       "19                1321       1213       1887       1218        692  \n",
+       "20                1543       1329       2251       1449        772  \n",
+       "21                1397       1125       1937       1177        692  \n",
+       "22                1095        841       1515       1011        587  \n",
+       "23                1131        891       1610       1116        700  \n",
+       "24                1048        883       1530       1035        574  \n",
+       "25                 927        896       1411        990        617  \n",
+       "26                 880        791       1311        979        552  \n",
+       "27                 922        837       1454        938        584  \n",
+       "28                 999        803       1228        930        572  \n",
+       "29                 945        806       1339        953        550  \n",
+       "30                 951        816       1340        941        565  \n",
+       "31                 949        773       1447        988        531  \n",
+       "32                 955        832       1370        929        563  \n",
+       "33                1006        928       1395       1009        617  \n",
+       "34                1024        920       1608       1043        594  \n",
+       "35                 951        810       1511        959        591  \n",
+       "36                 806        737       1208        803        488  \n",
+       "37                1052        898       1610       1084        578  \n",
+       "38                1023        844       1530       1021        555  \n",
+       "39                 963        869       1521       1041        617  \n",
+       "40                1054        899       1577       1003        671  \n",
+       "41                1019        902       1462       1010        638  \n",
+       "42                1056        923       1462       1174        688  \n",
+       "43                1154        922       1510       1044        661  \n",
+       "44                1089        888       1563       1129        712  \n",
+       "45                1177        952       1614       1174        832  \n",
+       "46                1172       1112       1616       1168        742  \n",
+       "47                1186       1086       1687       1159        848  \n",
+       "48                1159       1012       1655       1272        797  \n",
+       "49                1229       1029       1720       1284        836  \n",
+       "50                1224       1065       1706       1156        814  \n",
+       "51                1317       1167       1947       1311        882  \n",
+       "52                1198       1090       1701       1115        825  \n",
+       "53                 997       1159       1595        929        727  \n",
+       "\n",
+       "[54 rows x 91 columns]"
+      ]
+     },
+     "execution_count": 435,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "eng_xls"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 436,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-01-03 00:00:00</td>\n",
+       "      <td>787</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2020-01-10 00:00:00</td>\n",
+       "      <td>939</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2020-01-17 00:00:00</td>\n",
+       "      <td>767</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2020-01-24 00:00:00</td>\n",
+       "      <td>723</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2020-01-31 00:00:00</td>\n",
+       "      <td>727</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week           date_up_to deaths  year nation\n",
+       "0     1  2020-01-03 00:00:00    787  2020  Wales\n",
+       "1     2  2020-01-10 00:00:00    939  2020  Wales\n",
+       "2     3  2020-01-17 00:00:00    767  2020  Wales\n",
+       "3     4  2020-01-24 00:00:00    723  2020  Wales\n",
+       "4     5  2020-01-31 00:00:00    727  2020  Wales"
+      ]
+     },
+     "execution_count": 436,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = eng_xls.iloc[1:][['Week ended', 'Wales']].reset_index(level=0).rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'Wales': 'deaths',\n",
+    "            'index': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2020\n",
+    "rd['nation'] = 'Wales'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 437,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 438,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "<ipython-input-438-7dd1e0e9987b>:2: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  eng_xls['England deaths'] = eng_xls.loc[:, 'Total deaths, all ages'] - eng_xls.loc[:, 'Wales']\n"
+     ]
+    }
+   ],
+   "source": [
+    "eng_xls = eng_xls.iloc[1:]\n",
+    "eng_xls['England deaths'] = eng_xls.loc[:, 'Total deaths, all ages'] - eng_xls.loc[:, 'Wales']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 439,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Week ended</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>Total deaths, all ages</th>\n",
+       "      <th>Total deaths: average of corresponding</th>\n",
+       "      <th>week over the previous 5 years 1, 10, 11 (England and Wales)</th>\n",
+       "      <th>Total deaths: average of corresponding</th>\n",
+       "      <th>week over the previous 5 years 1, 10, 11 (England)</th>\n",
+       "      <th>Total deaths: average of corresponding</th>\n",
+       "      <th>week over the previous 5 years 1, 10, 11 (Wales)</th>\n",
+       "      <th>...</th>\n",
+       "      <th>North West</th>\n",
+       "      <th>Yorkshire and The Humber</th>\n",
+       "      <th>East Midlands</th>\n",
+       "      <th>West Midlands</th>\n",
+       "      <th>East</th>\n",
+       "      <th>London</th>\n",
+       "      <th>South East</th>\n",
+       "      <th>South West</th>\n",
+       "      <th>Wales</th>\n",
+       "      <th>England deaths</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2020-01-03 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12254</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12175</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11412</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>756</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1806</td>\n",
+       "      <td>1240</td>\n",
+       "      <td>1060</td>\n",
+       "      <td>1349</td>\n",
+       "      <td>1162</td>\n",
+       "      <td>1113</td>\n",
+       "      <td>1814</td>\n",
+       "      <td>1225</td>\n",
+       "      <td>787</td>\n",
+       "      <td>11467</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2020-01-10 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14058</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13822</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12933</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>856</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1932</td>\n",
+       "      <td>1339</td>\n",
+       "      <td>1195</td>\n",
+       "      <td>1450</td>\n",
+       "      <td>1573</td>\n",
+       "      <td>1272</td>\n",
+       "      <td>2132</td>\n",
+       "      <td>1487</td>\n",
+       "      <td>939</td>\n",
+       "      <td>13119</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2020-01-17 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12990</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13216</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12370</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>812</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1696</td>\n",
+       "      <td>1278</td>\n",
+       "      <td>1106</td>\n",
+       "      <td>1407</td>\n",
+       "      <td>1457</td>\n",
+       "      <td>1073</td>\n",
+       "      <td>2064</td>\n",
+       "      <td>1466</td>\n",
+       "      <td>767</td>\n",
+       "      <td>12223</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2020-01-24 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11856</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12760</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11933</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>802</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1529</td>\n",
+       "      <td>1187</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>1231</td>\n",
+       "      <td>1410</td>\n",
+       "      <td>1028</td>\n",
+       "      <td>1833</td>\n",
+       "      <td>1253</td>\n",
+       "      <td>723</td>\n",
+       "      <td>11133</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2020-01-31 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11612</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12206</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11419</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>760</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1461</td>\n",
+       "      <td>1136</td>\n",
+       "      <td>1015</td>\n",
+       "      <td>1262</td>\n",
+       "      <td>1286</td>\n",
+       "      <td>1092</td>\n",
+       "      <td>1820</td>\n",
+       "      <td>1233</td>\n",
+       "      <td>727</td>\n",
+       "      <td>10885</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 92 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Week ended  NaN  NaN Total deaths, all ages  \\\n",
+       "1  2020-01-03 00:00:00  NaN  NaN                  12254   \n",
+       "2  2020-01-10 00:00:00  NaN  NaN                  14058   \n",
+       "3  2020-01-17 00:00:00  NaN  NaN                  12990   \n",
+       "4  2020-01-24 00:00:00  NaN  NaN                  11856   \n",
+       "5  2020-01-31 00:00:00  NaN  NaN                  11612   \n",
+       "\n",
+       "  Total deaths: average of corresponding  \\\n",
+       "1                                    NaN   \n",
+       "2                                    NaN   \n",
+       "3                                    NaN   \n",
+       "4                                    NaN   \n",
+       "5                                    NaN   \n",
+       "\n",
+       "  week over the previous 5 years 1, 10, 11 (England and Wales)  \\\n",
+       "1                                              12175             \n",
+       "2                                              13822             \n",
+       "3                                              13216             \n",
+       "4                                              12760             \n",
+       "5                                              12206             \n",
+       "\n",
+       "  Total deaths: average of corresponding  \\\n",
+       "1                                    NaN   \n",
+       "2                                    NaN   \n",
+       "3                                    NaN   \n",
+       "4                                    NaN   \n",
+       "5                                    NaN   \n",
+       "\n",
+       "  week over the previous 5 years 1, 10, 11 (England)  \\\n",
+       "1                                              11412   \n",
+       "2                                              12933   \n",
+       "3                                              12370   \n",
+       "4                                              11933   \n",
+       "5                                              11419   \n",
+       "\n",
+       "  Total deaths: average of corresponding  \\\n",
+       "1                                    NaN   \n",
+       "2                                    NaN   \n",
+       "3                                    NaN   \n",
+       "4                                    NaN   \n",
+       "5                                    NaN   \n",
+       "\n",
+       "  week over the previous 5 years 1, 10, 11 (Wales)  ... North West  \\\n",
+       "1                                              756  ...       1806   \n",
+       "2                                              856  ...       1932   \n",
+       "3                                              812  ...       1696   \n",
+       "4                                              802  ...       1529   \n",
+       "5                                              760  ...       1461   \n",
+       "\n",
+       "  Yorkshire and The Humber East Midlands West Midlands  East London  \\\n",
+       "1                     1240          1060          1349  1162   1113   \n",
+       "2                     1339          1195          1450  1573   1272   \n",
+       "3                     1278          1106          1407  1457   1073   \n",
+       "4                     1187          1024          1231  1410   1028   \n",
+       "5                     1136          1015          1262  1286   1092   \n",
+       "\n",
+       "  South East South West Wales England deaths  \n",
+       "1       1814       1225   787          11467  \n",
+       "2       2132       1487   939          13119  \n",
+       "3       2064       1466   767          12223  \n",
+       "4       1833       1253   723          11133  \n",
+       "5       1820       1233   727          10885  \n",
+       "\n",
+       "[5 rows x 92 columns]"
+      ]
+     },
+     "execution_count": 439,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "eng_xls.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 440,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-01-03 00:00:00</td>\n",
+       "      <td>11467</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2020-01-10 00:00:00</td>\n",
+       "      <td>13119</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2020-01-17 00:00:00</td>\n",
+       "      <td>12223</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2020-01-24 00:00:00</td>\n",
+       "      <td>11133</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2020-01-31 00:00:00</td>\n",
+       "      <td>10885</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week           date_up_to deaths  year   nation\n",
+       "0     1  2020-01-03 00:00:00  11467  2020  England\n",
+       "1     2  2020-01-10 00:00:00  13119  2020  England\n",
+       "2     3  2020-01-17 00:00:00  12223  2020  England\n",
+       "3     4  2020-01-24 00:00:00  11133  2020  England\n",
+       "4     5  2020-01-31 00:00:00  10885  2020  England"
+      ]
+     },
+     "execution_count": 440,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = eng_xls[['Week ended', 'England deaths']].reset_index(level=0).rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'England deaths': 'deaths',\n",
+    "            'index': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2020\n",
+    "rd['nation'] = 'England'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 441,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "0 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[]"
+      ]
+     },
+     "execution_count": 441,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql delete from all_causes_deaths where nation = 'England'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 442,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 443,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>49</td>\n",
+       "      <td>2020-12-04 00:00:00</td>\n",
+       "      <td>11467</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>50</td>\n",
+       "      <td>2020-12-11 00:00:00</td>\n",
+       "      <td>11478</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>51</td>\n",
+       "      <td>2020-12-18 00:00:00</td>\n",
+       "      <td>12129</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>52</td>\n",
+       "      <td>2020-12-25 00:00:00</td>\n",
+       "      <td>10695</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>53</td>\n",
+       "      <td>2021-01-01 00:00:00</td>\n",
+       "      <td>9342</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    week           date_up_to deaths  year   nation\n",
+       "48    49  2020-12-04 00:00:00  11467  2020  England\n",
+       "49    50  2020-12-11 00:00:00  11478  2020  England\n",
+       "50    51  2020-12-18 00:00:00  12129  2020  England\n",
+       "51    52  2020-12-25 00:00:00  10695  2020  England\n",
+       "52    53  2021-01-01 00:00:00   9342  2020  England"
+      ]
+     },
+     "execution_count": 443,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 444,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "14 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>England</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2020, 'England', 53),\n",
+       " (2015, 'Northern Ireland', 53),\n",
+       " (2016, 'Northern Ireland', 52),\n",
+       " (2017, 'Northern Ireland', 52),\n",
+       " (2018, 'Northern Ireland', 52),\n",
+       " (2019, 'Northern Ireland', 52),\n",
+       " (2020, 'Northern Ireland', 53),\n",
+       " (2015, 'Scotland', 53),\n",
+       " (2016, 'Scotland', 52),\n",
+       " (2017, 'Scotland', 52),\n",
+       " (2018, 'Scotland', 52),\n",
+       " (2019, 'Scotland', 52),\n",
+       " (2020, 'Scotland', 53),\n",
+       " (2020, 'Wales', 53)]"
+      ]
+     },
+     "execution_count": 444,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 445,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# raw_data_2020 = pd.read_csv('uk-deaths-data/publishedweek272020.csv', \n",
+    "#                        parse_dates=[1], dayfirst=True,\n",
+    "#                       index_col=0,\n",
+    "#                       header=[0, 1])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 446,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# raw_data_2020.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 447,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# raw_data_2020['W92000004', 'Wales']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 448,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "raw_data_2019 = pd.read_csv('uk-deaths-data/publishedweek522019.csv', \n",
+    "                       parse_dates=[1], dayfirst=True,\n",
+    "#                       index_col=0,\n",
+    "                      header=[0, 1])\n",
+    "# raw_data_2019.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 449,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Week number</th>\n",
+       "      <th>Week ended</th>\n",
+       "      <th>Total deaths, all ages</th>\n",
+       "      <th>W92000004</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2019-01-04</td>\n",
+       "      <td>10955</td>\n",
+       "      <td>718</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2019-01-11</td>\n",
+       "      <td>12609</td>\n",
+       "      <td>809</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2019-01-18</td>\n",
+       "      <td>11860</td>\n",
+       "      <td>683</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2019-01-25</td>\n",
+       "      <td>11740</td>\n",
+       "      <td>734</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2019-02-01</td>\n",
+       "      <td>11297</td>\n",
+       "      <td>745</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Week number Week ended  Total deaths, all ages  W92000004\n",
+       "0            1 2019-01-04                   10955        718\n",
+       "1            2 2019-01-11                   12609        809\n",
+       "2            3 2019-01-18                   11860        683\n",
+       "3            4 2019-01-25                   11740        734\n",
+       "4            5 2019-02-01                   11297        745"
+      ]
+     },
+     "execution_count": 449,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rdew = raw_data_2019.iloc[:, [0, 1, 2, -1]].droplevel(axis=1, level=1)\n",
+    "rdew.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 450,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2019-01-04</td>\n",
+       "      <td>718</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2019-01-11</td>\n",
+       "      <td>809</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2019-01-18</td>\n",
+       "      <td>683</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2019-01-25</td>\n",
+       "      <td>734</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2019-02-01</td>\n",
+       "      <td>745</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week date_up_to  deaths  year nation\n",
+       "0     1 2019-01-04     718  2019  Wales\n",
+       "1     2 2019-01-11     809  2019  Wales\n",
+       "2     3 2019-01-18     683  2019  Wales\n",
+       "3     4 2019-01-25     734  2019  Wales\n",
+       "4     5 2019-02-01     745  2019  Wales"
+      ]
+     },
+     "execution_count": 450,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = rdew.drop(columns=['Total deaths, all ages']).rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'W92000004': 'deaths',\n",
+    "            'Week number': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2019\n",
+    "rd['nation'] = 'Wales'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 451,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 452,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>week</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2019-01-04</td>\n",
+       "      <td>1</td>\n",
+       "      <td>10237</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2019-01-11</td>\n",
+       "      <td>2</td>\n",
+       "      <td>11800</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2019-01-18</td>\n",
+       "      <td>3</td>\n",
+       "      <td>11177</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2019-01-25</td>\n",
+       "      <td>4</td>\n",
+       "      <td>11006</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2019-02-01</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10552</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  date_up_to  week  deaths  year   nation\n",
+       "0 2019-01-04     1   10237  2019  England\n",
+       "1 2019-01-11     2   11800  2019  England\n",
+       "2 2019-01-18     3   11177  2019  England\n",
+       "3 2019-01-25     4   11006  2019  England\n",
+       "4 2019-02-01     5   10552  2019  England"
+      ]
+     },
+     "execution_count": 452,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = rdew.loc[:, ['Week ended','Week number']]\n",
+    "rd['deaths'] = rdew['Total deaths, all ages'] - rdew['W92000004']\n",
+    "rd = rd.rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'Week number': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2019\n",
+    "rd['nation'] = 'England'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 453,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 454,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "16 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>England</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2019, 'England', 52),\n",
+       " (2020, 'England', 53),\n",
+       " (2015, 'Northern Ireland', 53),\n",
+       " (2016, 'Northern Ireland', 52),\n",
+       " (2017, 'Northern Ireland', 52),\n",
+       " (2018, 'Northern Ireland', 52),\n",
+       " (2019, 'Northern Ireland', 52),\n",
+       " (2020, 'Northern Ireland', 53),\n",
+       " (2015, 'Scotland', 53),\n",
+       " (2016, 'Scotland', 52),\n",
+       " (2017, 'Scotland', 52),\n",
+       " (2018, 'Scotland', 52),\n",
+       " (2019, 'Scotland', 52),\n",
+       " (2020, 'Scotland', 53),\n",
+       " (2019, 'Wales', 52),\n",
+       " (2020, 'Wales', 53)]"
+      ]
+     },
+     "execution_count": 454,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 455,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "raw_data_2018 = pd.read_csv('uk-deaths-data/publishedweek522018.csv', \n",
+    "                       parse_dates=[1], dayfirst=True,\n",
+    "#                       index_col=0,\n",
+    "                      header=[0, 1])\n",
+    "# raw_data_2018.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 456,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Week number</th>\n",
+       "      <th>Week ended</th>\n",
+       "      <th>Total deaths, all ages</th>\n",
+       "      <th>W92000004</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2018-01-05</td>\n",
+       "      <td>12723</td>\n",
+       "      <td>783</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2018-01-12</td>\n",
+       "      <td>15050</td>\n",
+       "      <td>904</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2018-01-19</td>\n",
+       "      <td>14256</td>\n",
+       "      <td>885</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2018-01-26</td>\n",
+       "      <td>13935</td>\n",
+       "      <td>850</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2018-02-02</td>\n",
+       "      <td>13285</td>\n",
+       "      <td>815</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Week number Week ended  Total deaths, all ages  W92000004\n",
+       "0            1 2018-01-05                   12723        783\n",
+       "1            2 2018-01-12                   15050        904\n",
+       "2            3 2018-01-19                   14256        885\n",
+       "3            4 2018-01-26                   13935        850\n",
+       "4            5 2018-02-02                   13285        815"
+      ]
+     },
+     "execution_count": 456,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rdew = raw_data_2018.iloc[:, [0, 1, 2, -1]].droplevel(axis=1, level=1)\n",
+    "rdew.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 457,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2018-01-05</td>\n",
+       "      <td>783</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2018-01-12</td>\n",
+       "      <td>904</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2018-01-19</td>\n",
+       "      <td>885</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2018-01-26</td>\n",
+       "      <td>850</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2018-02-02</td>\n",
+       "      <td>815</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week date_up_to  deaths  year nation\n",
+       "0     1 2018-01-05     783  2018  Wales\n",
+       "1     2 2018-01-12     904  2018  Wales\n",
+       "2     3 2018-01-19     885  2018  Wales\n",
+       "3     4 2018-01-26     850  2018  Wales\n",
+       "4     5 2018-02-02     815  2018  Wales"
+      ]
+     },
+     "execution_count": 457,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = rdew.drop(columns=['Total deaths, all ages']).rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'W92000004': 'deaths',\n",
+    "            'Week number': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2018\n",
+    "rd['nation'] = 'Wales'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 458,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 459,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>week</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2018-01-05</td>\n",
+       "      <td>1</td>\n",
+       "      <td>11940</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2018-01-12</td>\n",
+       "      <td>2</td>\n",
+       "      <td>14146</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2018-01-19</td>\n",
+       "      <td>3</td>\n",
+       "      <td>13371</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2018-01-26</td>\n",
+       "      <td>4</td>\n",
+       "      <td>13085</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2018-02-02</td>\n",
+       "      <td>5</td>\n",
+       "      <td>12470</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  date_up_to  week  deaths  year   nation\n",
+       "0 2018-01-05     1   11940  2018  England\n",
+       "1 2018-01-12     2   14146  2018  England\n",
+       "2 2018-01-19     3   13371  2018  England\n",
+       "3 2018-01-26     4   13085  2018  England\n",
+       "4 2018-02-02     5   12470  2018  England"
+      ]
+     },
+     "execution_count": 459,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = rdew.loc[:, ['Week ended','Week number']]\n",
+    "rd['deaths'] = rdew['Total deaths, all ages'] - rdew['W92000004']\n",
+    "rd = rd.rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'Week number': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2018\n",
+    "rd['nation'] = 'England'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 460,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 461,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "18 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>England</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2018, 'England', 52),\n",
+       " (2019, 'England', 52),\n",
+       " (2020, 'England', 53),\n",
+       " (2015, 'Northern Ireland', 53),\n",
+       " (2016, 'Northern Ireland', 52),\n",
+       " (2017, 'Northern Ireland', 52),\n",
+       " (2018, 'Northern Ireland', 52),\n",
+       " (2019, 'Northern Ireland', 52),\n",
+       " (2020, 'Northern Ireland', 53),\n",
+       " (2015, 'Scotland', 53),\n",
+       " (2016, 'Scotland', 52),\n",
+       " (2017, 'Scotland', 52),\n",
+       " (2018, 'Scotland', 52),\n",
+       " (2019, 'Scotland', 52),\n",
+       " (2020, 'Scotland', 53),\n",
+       " (2018, 'Wales', 52),\n",
+       " (2019, 'Wales', 52),\n",
+       " (2020, 'Wales', 53)]"
+      ]
+     },
+     "execution_count": 461,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 462,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "raw_data_2017 = pd.read_csv('uk-deaths-data/publishedweek522017.csv', \n",
+    "                       parse_dates=[1], dayfirst=True,\n",
+    "#                       index_col=0,\n",
+    "                      header=[0, 1])\n",
+    "# raw_data_2017.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 463,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Week number</th>\n",
+       "      <th>Week ended</th>\n",
+       "      <th>Total deaths, all ages</th>\n",
+       "      <th>W92000004</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2017-01-06</td>\n",
+       "      <td>11991</td>\n",
+       "      <td>744</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2017-01-13</td>\n",
+       "      <td>13715</td>\n",
+       "      <td>825</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2017-01-20</td>\n",
+       "      <td>13610</td>\n",
+       "      <td>835</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2017-01-27</td>\n",
+       "      <td>12877</td>\n",
+       "      <td>881</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2017-02-03</td>\n",
+       "      <td>12485</td>\n",
+       "      <td>749</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Week number Week ended  Total deaths, all ages  W92000004\n",
+       "0            1 2017-01-06                   11991        744\n",
+       "1            2 2017-01-13                   13715        825\n",
+       "2            3 2017-01-20                   13610        835\n",
+       "3            4 2017-01-27                   12877        881\n",
+       "4            5 2017-02-03                   12485        749"
+      ]
+     },
+     "execution_count": 463,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rdew = raw_data_2017.iloc[:, [0, 1, 2, -1]].droplevel(axis=1, level=1)\n",
+    "rdew.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 464,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2017-01-06</td>\n",
+       "      <td>744</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2017-01-13</td>\n",
+       "      <td>825</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2017-01-20</td>\n",
+       "      <td>835</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2017-01-27</td>\n",
+       "      <td>881</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2017-02-03</td>\n",
+       "      <td>749</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week date_up_to  deaths  year nation\n",
+       "0     1 2017-01-06     744  2017  Wales\n",
+       "1     2 2017-01-13     825  2017  Wales\n",
+       "2     3 2017-01-20     835  2017  Wales\n",
+       "3     4 2017-01-27     881  2017  Wales\n",
+       "4     5 2017-02-03     749  2017  Wales"
+      ]
+     },
+     "execution_count": 464,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = rdew.drop(columns=['Total deaths, all ages']).rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'W92000004': 'deaths',\n",
+    "            'Week number': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2017\n",
+    "rd['nation'] = 'Wales'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 465,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 466,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>week</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2017-01-06</td>\n",
+       "      <td>1</td>\n",
+       "      <td>11247</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2017-01-13</td>\n",
+       "      <td>2</td>\n",
+       "      <td>12890</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2017-01-20</td>\n",
+       "      <td>3</td>\n",
+       "      <td>12775</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2017-01-27</td>\n",
+       "      <td>4</td>\n",
+       "      <td>11996</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2017-02-03</td>\n",
+       "      <td>5</td>\n",
+       "      <td>11736</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  date_up_to  week  deaths  year   nation\n",
+       "0 2017-01-06     1   11247  2017  England\n",
+       "1 2017-01-13     2   12890  2017  England\n",
+       "2 2017-01-20     3   12775  2017  England\n",
+       "3 2017-01-27     4   11996  2017  England\n",
+       "4 2017-02-03     5   11736  2017  England"
+      ]
+     },
+     "execution_count": 466,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = rdew.loc[:, ['Week ended','Week number']]\n",
+    "rd['deaths'] = rdew['Total deaths, all ages'] - rdew['W92000004']\n",
+    "rd = rd.rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'Week number': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2017\n",
+    "rd['nation'] = 'England'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 467,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 468,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "20 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>England</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2017, 'England', 52),\n",
+       " (2018, 'England', 52),\n",
+       " (2019, 'England', 52),\n",
+       " (2020, 'England', 53),\n",
+       " (2015, 'Northern Ireland', 53),\n",
+       " (2016, 'Northern Ireland', 52),\n",
+       " (2017, 'Northern Ireland', 52),\n",
+       " (2018, 'Northern Ireland', 52),\n",
+       " (2019, 'Northern Ireland', 52),\n",
+       " (2020, 'Northern Ireland', 53),\n",
+       " (2015, 'Scotland', 53),\n",
+       " (2016, 'Scotland', 52),\n",
+       " (2017, 'Scotland', 52),\n",
+       " (2018, 'Scotland', 52),\n",
+       " (2019, 'Scotland', 52),\n",
+       " (2020, 'Scotland', 53),\n",
+       " (2017, 'Wales', 52),\n",
+       " (2018, 'Wales', 52),\n",
+       " (2019, 'Wales', 52),\n",
+       " (2020, 'Wales', 53)]"
+      ]
+     },
+     "execution_count": 468,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 469,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "raw_data_2016 = pd.read_csv('uk-deaths-data/publishedweek522016.csv', \n",
+    "                       parse_dates=[1], dayfirst=True,\n",
+    "#                       index_col=0,\n",
+    "                      header=[0, 1])\n",
+    "# raw_data_2016.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 470,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead tr th {\n",
+       "        text-align: left;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th>Week number</th>\n",
+       "      <th>Week ended</th>\n",
+       "      <th>Total deaths, all ages</th>\n",
+       "      <th>Total deaths: average of corresponding</th>\n",
+       "      <th>Unnamed: 4_level_0</th>\n",
+       "      <th>Unnamed: 5_level_0</th>\n",
+       "      <th>Persons</th>\n",
+       "      <th>Unnamed: 7_level_0</th>\n",
+       "      <th>Unnamed: 8_level_0</th>\n",
+       "      <th>Unnamed: 9_level_0</th>\n",
+       "      <th>...</th>\n",
+       "      <th>E12000001</th>\n",
+       "      <th>E12000002</th>\n",
+       "      <th>E12000003</th>\n",
+       "      <th>E12000004</th>\n",
+       "      <th>E12000005</th>\n",
+       "      <th>E12000006</th>\n",
+       "      <th>E12000007</th>\n",
+       "      <th>E12000008</th>\n",
+       "      <th>E12000009</th>\n",
+       "      <th>W92000004</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th>Unnamed: 0_level_1</th>\n",
+       "      <th>Unnamed: 1_level_1</th>\n",
+       "      <th>Unnamed: 2_level_1</th>\n",
+       "      <th>Unnamed: 3_level_1</th>\n",
+       "      <th>Deaths by underlying cause</th>\n",
+       "      <th>All respiratory diseases (ICD-10 J00-J99)\\nICD-10 v 2013 (IRIS)</th>\n",
+       "      <th>Deaths by age group</th>\n",
+       "      <th>Under 1 year</th>\n",
+       "      <th>01-14</th>\n",
+       "      <th>15-44</th>\n",
+       "      <th>...</th>\n",
+       "      <th>North East</th>\n",
+       "      <th>North West</th>\n",
+       "      <th>Yorkshire and The Humber</th>\n",
+       "      <th>East Midlands</th>\n",
+       "      <th>West Midlands</th>\n",
+       "      <th>East</th>\n",
+       "      <th>London</th>\n",
+       "      <th>South East</th>\n",
+       "      <th>South West</th>\n",
+       "      <th>Wales</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2016-01-08</td>\n",
+       "      <td>13045</td>\n",
+       "      <td>11701.4</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2046</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>49</td>\n",
+       "      <td>17</td>\n",
+       "      <td>299</td>\n",
+       "      <td>...</td>\n",
+       "      <td>705</td>\n",
+       "      <td>1748</td>\n",
+       "      <td>1284</td>\n",
+       "      <td>1067</td>\n",
+       "      <td>1396</td>\n",
+       "      <td>1401</td>\n",
+       "      <td>1226</td>\n",
+       "      <td>1951</td>\n",
+       "      <td>1424</td>\n",
+       "      <td>809</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2016-01-15</td>\n",
+       "      <td>11501</td>\n",
+       "      <td>13016.4</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1835</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>64</td>\n",
+       "      <td>24</td>\n",
+       "      <td>326</td>\n",
+       "      <td>...</td>\n",
+       "      <td>600</td>\n",
+       "      <td>1532</td>\n",
+       "      <td>1148</td>\n",
+       "      <td>956</td>\n",
+       "      <td>1208</td>\n",
+       "      <td>1237</td>\n",
+       "      <td>1048</td>\n",
+       "      <td>1771</td>\n",
+       "      <td>1263</td>\n",
+       "      <td>711</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2016-01-22</td>\n",
+       "      <td>11473</td>\n",
+       "      <td>11765.4</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1775</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>50</td>\n",
+       "      <td>18</td>\n",
+       "      <td>345</td>\n",
+       "      <td>...</td>\n",
+       "      <td>612</td>\n",
+       "      <td>1602</td>\n",
+       "      <td>1119</td>\n",
+       "      <td>929</td>\n",
+       "      <td>1209</td>\n",
+       "      <td>1253</td>\n",
+       "      <td>1068</td>\n",
+       "      <td>1710</td>\n",
+       "      <td>1219</td>\n",
+       "      <td>720</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2016-01-29</td>\n",
+       "      <td>11317</td>\n",
+       "      <td>11289.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1810</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>47</td>\n",
+       "      <td>14</td>\n",
+       "      <td>324</td>\n",
+       "      <td>...</td>\n",
+       "      <td>631</td>\n",
+       "      <td>1516</td>\n",
+       "      <td>1131</td>\n",
+       "      <td>858</td>\n",
+       "      <td>1195</td>\n",
+       "      <td>1236</td>\n",
+       "      <td>1065</td>\n",
+       "      <td>1730</td>\n",
+       "      <td>1207</td>\n",
+       "      <td>717</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2016-02-05</td>\n",
+       "      <td>11052</td>\n",
+       "      <td>10965.6</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1748</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>60</td>\n",
+       "      <td>22</td>\n",
+       "      <td>314</td>\n",
+       "      <td>...</td>\n",
+       "      <td>620</td>\n",
+       "      <td>1459</td>\n",
+       "      <td>1109</td>\n",
+       "      <td>954</td>\n",
+       "      <td>1197</td>\n",
+       "      <td>1160</td>\n",
+       "      <td>1059</td>\n",
+       "      <td>1604</td>\n",
+       "      <td>1169</td>\n",
+       "      <td>690</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 41 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         Week number         Week ended Total deaths, all ages  \\\n",
+       "  Unnamed: 0_level_1 Unnamed: 1_level_1     Unnamed: 2_level_1   \n",
+       "0                  1         2016-01-08                  13045   \n",
+       "1                  2         2016-01-15                  11501   \n",
+       "2                  3         2016-01-22                  11473   \n",
+       "3                  4         2016-01-29                  11317   \n",
+       "4                  5         2016-02-05                  11052   \n",
+       "\n",
+       "  Total deaths: average of corresponding         Unnamed: 4_level_0  \\\n",
+       "                      Unnamed: 3_level_1 Deaths by underlying cause   \n",
+       "0                                11701.4                        NaN   \n",
+       "1                                13016.4                        NaN   \n",
+       "2                                11765.4                        NaN   \n",
+       "3                                11289.0                        NaN   \n",
+       "4                                10965.6                        NaN   \n",
+       "\n",
+       "                                               Unnamed: 5_level_0  \\\n",
+       "  All respiratory diseases (ICD-10 J00-J99)\\nICD-10 v 2013 (IRIS)   \n",
+       "0                                               2046                \n",
+       "1                                               1835                \n",
+       "2                                               1775                \n",
+       "3                                               1810                \n",
+       "4                                               1748                \n",
+       "\n",
+       "              Persons Unnamed: 7_level_0 Unnamed: 8_level_0  \\\n",
+       "  Deaths by age group       Under 1 year              01-14   \n",
+       "0                 NaN                 49                 17   \n",
+       "1                 NaN                 64                 24   \n",
+       "2                 NaN                 50                 18   \n",
+       "3                 NaN                 47                 14   \n",
+       "4                 NaN                 60                 22   \n",
+       "\n",
+       "  Unnamed: 9_level_0  ...  E12000001  E12000002                E12000003  \\\n",
+       "               15-44  ... North East North West Yorkshire and The Humber   \n",
+       "0                299  ...        705       1748                     1284   \n",
+       "1                326  ...        600       1532                     1148   \n",
+       "2                345  ...        612       1602                     1119   \n",
+       "3                324  ...        631       1516                     1131   \n",
+       "4                314  ...        620       1459                     1109   \n",
+       "\n",
+       "      E12000004     E12000005 E12000006 E12000007  E12000008  E12000009  \\\n",
+       "  East Midlands West Midlands      East    London South East South West   \n",
+       "0          1067          1396      1401      1226       1951       1424   \n",
+       "1           956          1208      1237      1048       1771       1263   \n",
+       "2           929          1209      1253      1068       1710       1219   \n",
+       "3           858          1195      1236      1065       1730       1207   \n",
+       "4           954          1197      1160      1059       1604       1169   \n",
+       "\n",
+       "  W92000004  \n",
+       "      Wales  \n",
+       "0       809  \n",
+       "1       711  \n",
+       "2       720  \n",
+       "3       717  \n",
+       "4       690  \n",
+       "\n",
+       "[5 rows x 41 columns]"
+      ]
+     },
+     "execution_count": 470,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data_2016.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 471,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Week number</th>\n",
+       "      <th>Week ended</th>\n",
+       "      <th>Total deaths, all ages</th>\n",
+       "      <th>W92000004</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2016-01-08</td>\n",
+       "      <td>13045</td>\n",
+       "      <td>809</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2016-01-15</td>\n",
+       "      <td>11501</td>\n",
+       "      <td>711</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2016-01-22</td>\n",
+       "      <td>11473</td>\n",
+       "      <td>720</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2016-01-29</td>\n",
+       "      <td>11317</td>\n",
+       "      <td>717</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2016-02-05</td>\n",
+       "      <td>11052</td>\n",
+       "      <td>690</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Week number Week ended  Total deaths, all ages  W92000004\n",
+       "0            1 2016-01-08                   13045        809\n",
+       "1            2 2016-01-15                   11501        711\n",
+       "2            3 2016-01-22                   11473        720\n",
+       "3            4 2016-01-29                   11317        717\n",
+       "4            5 2016-02-05                   11052        690"
+      ]
+     },
+     "execution_count": 471,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rdew = raw_data_2016.iloc[:, [0, 1, 2, -1]].droplevel(axis=1, level=1)\n",
+    "rdew.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 472,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2016-01-08</td>\n",
+       "      <td>809</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2016-01-15</td>\n",
+       "      <td>711</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2016-01-22</td>\n",
+       "      <td>720</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2016-01-29</td>\n",
+       "      <td>717</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2016-02-05</td>\n",
+       "      <td>690</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week date_up_to  deaths  year nation\n",
+       "0     1 2016-01-08     809  2016  Wales\n",
+       "1     2 2016-01-15     711  2016  Wales\n",
+       "2     3 2016-01-22     720  2016  Wales\n",
+       "3     4 2016-01-29     717  2016  Wales\n",
+       "4     5 2016-02-05     690  2016  Wales"
+      ]
+     },
+     "execution_count": 472,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = rdew.drop(columns=['Total deaths, all ages']).rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'W92000004': 'deaths',\n",
+    "            'Week number': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2016\n",
+    "rd['nation'] = 'Wales'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 473,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 474,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>week</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2016-01-08</td>\n",
+       "      <td>1</td>\n",
+       "      <td>12236</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2016-01-15</td>\n",
+       "      <td>2</td>\n",
+       "      <td>10790</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2016-01-22</td>\n",
+       "      <td>3</td>\n",
+       "      <td>10753</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2016-01-29</td>\n",
+       "      <td>4</td>\n",
+       "      <td>10600</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2016-02-05</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10362</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  date_up_to  week  deaths  year   nation\n",
+       "0 2016-01-08     1   12236  2016  England\n",
+       "1 2016-01-15     2   10790  2016  England\n",
+       "2 2016-01-22     3   10753  2016  England\n",
+       "3 2016-01-29     4   10600  2016  England\n",
+       "4 2016-02-05     5   10362  2016  England"
+      ]
+     },
+     "execution_count": 474,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = rdew.loc[:, ['Week ended','Week number']]\n",
+    "rd['deaths'] = rdew['Total deaths, all ages'] - rdew['W92000004']\n",
+    "rd = rd.rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'Week number': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2016\n",
+    "rd['nation'] = 'England'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 475,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 476,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "22 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>England</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2016, 'England', 52),\n",
+       " (2017, 'England', 52),\n",
+       " (2018, 'England', 52),\n",
+       " (2019, 'England', 52),\n",
+       " (2020, 'England', 53),\n",
+       " (2015, 'Northern Ireland', 53),\n",
+       " (2016, 'Northern Ireland', 52),\n",
+       " (2017, 'Northern Ireland', 52),\n",
+       " (2018, 'Northern Ireland', 52),\n",
+       " (2019, 'Northern Ireland', 52),\n",
+       " (2020, 'Northern Ireland', 53),\n",
+       " (2015, 'Scotland', 53),\n",
+       " (2016, 'Scotland', 52),\n",
+       " (2017, 'Scotland', 52),\n",
+       " (2018, 'Scotland', 52),\n",
+       " (2019, 'Scotland', 52),\n",
+       " (2020, 'Scotland', 53),\n",
+       " (2016, 'Wales', 52),\n",
+       " (2017, 'Wales', 52),\n",
+       " (2018, 'Wales', 52),\n",
+       " (2019, 'Wales', 52),\n",
+       " (2020, 'Wales', 53)]"
+      ]
+     },
+     "execution_count": 476,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    " %sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 477,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "raw_data_2015 = pd.read_csv('uk-deaths-data/publishedweek2015.csv', \n",
+    "                       parse_dates=[1], dayfirst=True,\n",
+    "#                       index_col=0,\n",
+    "                      header=[0, 1])\n",
+    "# raw_data_2015.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 478,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Week number</th>\n",
+       "      <th>Week ended</th>\n",
+       "      <th>Total deaths, all ages</th>\n",
+       "      <th>W92000004</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2015-01-02</td>\n",
+       "      <td>12286</td>\n",
+       "      <td>725</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2015-01-09</td>\n",
+       "      <td>16237</td>\n",
+       "      <td>1031</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2015-01-16</td>\n",
+       "      <td>14866</td>\n",
+       "      <td>936</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2015-01-23</td>\n",
+       "      <td>13934</td>\n",
+       "      <td>828</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2015-01-30</td>\n",
+       "      <td>12900</td>\n",
+       "      <td>801</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Week number Week ended  Total deaths, all ages  W92000004\n",
+       "0            1 2015-01-02                   12286        725\n",
+       "1            2 2015-01-09                   16237       1031\n",
+       "2            3 2015-01-16                   14866        936\n",
+       "3            4 2015-01-23                   13934        828\n",
+       "4            5 2015-01-30                   12900        801"
+      ]
+     },
+     "execution_count": 478,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rdew = raw_data_2015.iloc[:, [0, 1, 2, -1]].droplevel(axis=1, level=1)\n",
+    "rdew.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 479,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2015-01-02</td>\n",
+       "      <td>725</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2015-01-09</td>\n",
+       "      <td>1031</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2015-01-16</td>\n",
+       "      <td>936</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2015-01-23</td>\n",
+       "      <td>828</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2015-01-30</td>\n",
+       "      <td>801</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week date_up_to  deaths  year nation\n",
+       "0     1 2015-01-02     725  2015  Wales\n",
+       "1     2 2015-01-09    1031  2015  Wales\n",
+       "2     3 2015-01-16     936  2015  Wales\n",
+       "3     4 2015-01-23     828  2015  Wales\n",
+       "4     5 2015-01-30     801  2015  Wales"
+      ]
+     },
+     "execution_count": 479,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = rdew.drop(columns=['Total deaths, all ages']).rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'W92000004': 'deaths',\n",
+    "            'Week number': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2015\n",
+    "rd['nation'] = 'Wales'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 480,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 481,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>week</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2015-01-02</td>\n",
+       "      <td>1</td>\n",
+       "      <td>11561</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2015-01-09</td>\n",
+       "      <td>2</td>\n",
+       "      <td>15206</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2015-01-16</td>\n",
+       "      <td>3</td>\n",
+       "      <td>13930</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2015-01-23</td>\n",
+       "      <td>4</td>\n",
+       "      <td>13106</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2015-01-30</td>\n",
+       "      <td>5</td>\n",
+       "      <td>12099</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  date_up_to  week  deaths  year   nation\n",
+       "0 2015-01-02     1   11561  2015  England\n",
+       "1 2015-01-09     2   15206  2015  England\n",
+       "2 2015-01-16     3   13930  2015  England\n",
+       "3 2015-01-23     4   13106  2015  England\n",
+       "4 2015-01-30     5   12099  2015  England"
+      ]
+     },
+     "execution_count": 481,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = rdew.loc[:, ['Week ended','Week number']]\n",
+    "rd['deaths'] = rdew['Total deaths, all ages'] - rdew['W92000004']\n",
+    "rd = rd.rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'Week number': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2015\n",
+    "rd['nation'] = 'England'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 482,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 483,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "24 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>England</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>England</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2015, 'England', 53),\n",
+       " (2015, 'Northern Ireland', 53),\n",
+       " (2015, 'Scotland', 53),\n",
+       " (2015, 'Wales', 53),\n",
+       " (2016, 'England', 52),\n",
+       " (2016, 'Northern Ireland', 52),\n",
+       " (2016, 'Scotland', 52),\n",
+       " (2016, 'Wales', 52),\n",
+       " (2017, 'England', 52),\n",
+       " (2017, 'Northern Ireland', 52),\n",
+       " (2017, 'Scotland', 52),\n",
+       " (2017, 'Wales', 52),\n",
+       " (2018, 'England', 52),\n",
+       " (2018, 'Northern Ireland', 52),\n",
+       " (2018, 'Scotland', 52),\n",
+       " (2018, 'Wales', 52),\n",
+       " (2019, 'England', 52),\n",
+       " (2019, 'Northern Ireland', 52),\n",
+       " (2019, 'Scotland', 52),\n",
+       " (2019, 'Wales', 52),\n",
+       " (2020, 'England', 53),\n",
+       " (2020, 'Northern Ireland', 53),\n",
+       " (2020, 'Scotland', 53),\n",
+       " (2020, 'Wales', 53)]"
+      ]
+     },
+     "execution_count": 483,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by year, nation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 568,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "314 rows affected.\n",
+      "Returning data to local variable res\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%sql res << select week, year, deaths\n",
+    "from all_causes_deaths\n",
+    "where nation = 'England'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 569,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>year</th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>2017</th>\n",
+       "      <th>2018</th>\n",
+       "      <th>2019</th>\n",
+       "      <th>2020</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>week</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>11561.0</td>\n",
+       "      <td>12236.0</td>\n",
+       "      <td>11247.0</td>\n",
+       "      <td>11940.0</td>\n",
+       "      <td>10237.0</td>\n",
+       "      <td>11467.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>15206.0</td>\n",
+       "      <td>10790.0</td>\n",
+       "      <td>12890.0</td>\n",
+       "      <td>14146.0</td>\n",
+       "      <td>11800.0</td>\n",
+       "      <td>13119.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>13930.0</td>\n",
+       "      <td>10753.0</td>\n",
+       "      <td>12775.0</td>\n",
+       "      <td>13371.0</td>\n",
+       "      <td>11177.0</td>\n",
+       "      <td>12223.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>13106.0</td>\n",
+       "      <td>10600.0</td>\n",
+       "      <td>11996.0</td>\n",
+       "      <td>13085.0</td>\n",
+       "      <td>11006.0</td>\n",
+       "      <td>11133.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>12099.0</td>\n",
+       "      <td>10362.0</td>\n",
+       "      <td>11736.0</td>\n",
+       "      <td>12470.0</td>\n",
+       "      <td>10552.0</td>\n",
+       "      <td>10885.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>11319.0</td>\n",
+       "      <td>10470.0</td>\n",
+       "      <td>11546.0</td>\n",
+       "      <td>11694.0</td>\n",
+       "      <td>10959.0</td>\n",
+       "      <td>10296.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>11112.0</td>\n",
+       "      <td>9933.0</td>\n",
+       "      <td>10954.0</td>\n",
+       "      <td>11443.0</td>\n",
+       "      <td>11076.0</td>\n",
+       "      <td>10216.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>10695.0</td>\n",
+       "      <td>10360.0</td>\n",
+       "      <td>11093.0</td>\n",
+       "      <td>11353.0</td>\n",
+       "      <td>10600.0</td>\n",
+       "      <td>10162.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>10736.0</td>\n",
+       "      <td>10564.0</td>\n",
+       "      <td>10533.0</td>\n",
+       "      <td>10220.0</td>\n",
+       "      <td>10360.0</td>\n",
+       "      <td>10165.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>10757.0</td>\n",
+       "      <td>10276.0</td>\n",
+       "      <td>10443.0</td>\n",
+       "      <td>12101.0</td>\n",
+       "      <td>10276.0</td>\n",
+       "      <td>10243.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>10290.0</td>\n",
+       "      <td>10284.0</td>\n",
+       "      <td>10044.0</td>\n",
+       "      <td>11870.0</td>\n",
+       "      <td>9901.0</td>\n",
+       "      <td>10344.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>9888.0</td>\n",
+       "      <td>8967.0</td>\n",
+       "      <td>9690.0</td>\n",
+       "      <td>11139.0</td>\n",
+       "      <td>9774.0</td>\n",
+       "      <td>9926.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>9827.0</td>\n",
+       "      <td>9574.0</td>\n",
+       "      <td>9369.0</td>\n",
+       "      <td>9308.0</td>\n",
+       "      <td>9213.0</td>\n",
+       "      <td>10422.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>8482.0</td>\n",
+       "      <td>10857.0</td>\n",
+       "      <td>9297.0</td>\n",
+       "      <td>10064.0</td>\n",
+       "      <td>9484.0</td>\n",
+       "      <td>15467.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>9429.0</td>\n",
+       "      <td>10679.0</td>\n",
+       "      <td>7916.0</td>\n",
+       "      <td>11558.0</td>\n",
+       "      <td>9654.0</td>\n",
+       "      <td>17588.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>10968.0</td>\n",
+       "      <td>10211.0</td>\n",
+       "      <td>8990.0</td>\n",
+       "      <td>10535.0</td>\n",
+       "      <td>8445.0</td>\n",
+       "      <td>21182.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>9937.0</td>\n",
+       "      <td>9784.0</td>\n",
+       "      <td>10181.0</td>\n",
+       "      <td>9692.0</td>\n",
+       "      <td>9381.0</td>\n",
+       "      <td>20873.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>9506.0</td>\n",
+       "      <td>8568.0</td>\n",
+       "      <td>8464.0</td>\n",
+       "      <td>9520.0</td>\n",
+       "      <td>10519.0</td>\n",
+       "      <td>17024.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>8273.0</td>\n",
+       "      <td>9985.0</td>\n",
+       "      <td>10006.0</td>\n",
+       "      <td>8094.0</td>\n",
+       "      <td>8455.0</td>\n",
+       "      <td>11965.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>9668.0</td>\n",
+       "      <td>9342.0</td>\n",
+       "      <td>9673.0</td>\n",
+       "      <td>9474.0</td>\n",
+       "      <td>9614.0</td>\n",
+       "      <td>13801.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>9391.0</td>\n",
+       "      <td>9115.0</td>\n",
+       "      <td>9438.0</td>\n",
+       "      <td>9033.0</td>\n",
+       "      <td>9657.0</td>\n",
+       "      <td>11596.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>7625.0</td>\n",
+       "      <td>7409.0</td>\n",
+       "      <td>7746.0</td>\n",
+       "      <td>7609.0</td>\n",
+       "      <td>7742.0</td>\n",
+       "      <td>9237.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>9509.0</td>\n",
+       "      <td>9289.0</td>\n",
+       "      <td>9182.0</td>\n",
+       "      <td>9343.0</td>\n",
+       "      <td>9514.0</td>\n",
+       "      <td>10009.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>8942.0</td>\n",
+       "      <td>8808.0</td>\n",
+       "      <td>8768.0</td>\n",
+       "      <td>8782.0</td>\n",
+       "      <td>8847.0</td>\n",
+       "      <td>9402.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>8717.0</td>\n",
+       "      <td>8807.0</td>\n",
+       "      <td>9019.0</td>\n",
+       "      <td>8694.0</td>\n",
+       "      <td>8916.0</td>\n",
+       "      <td>8722.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>8593.0</td>\n",
+       "      <td>8679.0</td>\n",
+       "      <td>8788.0</td>\n",
+       "      <td>8613.0</td>\n",
+       "      <td>8947.0</td>\n",
+       "      <td>8427.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>8670.0</td>\n",
+       "      <td>8614.0</td>\n",
+       "      <td>8707.0</td>\n",
+       "      <td>8633.0</td>\n",
+       "      <td>8528.0</td>\n",
+       "      <td>8556.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>8461.0</td>\n",
+       "      <td>8789.0</td>\n",
+       "      <td>8812.0</td>\n",
+       "      <td>8710.0</td>\n",
+       "      <td>8591.0</td>\n",
+       "      <td>8118.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>8228.0</td>\n",
+       "      <td>8790.0</td>\n",
+       "      <td>8562.0</td>\n",
+       "      <td>8579.0</td>\n",
+       "      <td>8527.0</td>\n",
+       "      <td>8273.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>8262.0</td>\n",
+       "      <td>8725.0</td>\n",
+       "      <td>8296.0</td>\n",
+       "      <td>8581.0</td>\n",
+       "      <td>8569.0</td>\n",
+       "      <td>8326.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>8071.0</td>\n",
+       "      <td>8602.0</td>\n",
+       "      <td>8351.0</td>\n",
+       "      <td>8587.0</td>\n",
+       "      <td>8701.0</td>\n",
+       "      <td>8415.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>8298.0</td>\n",
+       "      <td>8531.0</td>\n",
+       "      <td>8466.0</td>\n",
+       "      <td>8782.0</td>\n",
+       "      <td>8580.0</td>\n",
+       "      <td>8382.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>8600.0</td>\n",
+       "      <td>8496.0</td>\n",
+       "      <td>8707.0</td>\n",
+       "      <td>8312.0</td>\n",
+       "      <td>8504.0</td>\n",
+       "      <td>8775.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>8564.0</td>\n",
+       "      <td>8700.0</td>\n",
+       "      <td>8812.0</td>\n",
+       "      <td>8413.0</td>\n",
+       "      <td>8441.0</td>\n",
+       "      <td>9037.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>8423.0</td>\n",
+       "      <td>7453.0</td>\n",
+       "      <td>7594.0</td>\n",
+       "      <td>7354.0</td>\n",
+       "      <td>7684.0</td>\n",
+       "      <td>8441.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>7389.0</td>\n",
+       "      <td>8847.0</td>\n",
+       "      <td>8955.0</td>\n",
+       "      <td>8851.0</td>\n",
+       "      <td>9113.0</td>\n",
+       "      <td>7251.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>8704.0</td>\n",
+       "      <td>8548.0</td>\n",
+       "      <td>8845.0</td>\n",
+       "      <td>8612.0</td>\n",
+       "      <td>8946.0</td>\n",
+       "      <td>9233.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>8542.0</td>\n",
+       "      <td>8382.0</td>\n",
+       "      <td>8949.0</td>\n",
+       "      <td>8707.0</td>\n",
+       "      <td>8868.0</td>\n",
+       "      <td>8968.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>8865.0</td>\n",
+       "      <td>8402.0</td>\n",
+       "      <td>9096.0</td>\n",
+       "      <td>8590.0</td>\n",
+       "      <td>8906.0</td>\n",
+       "      <td>9017.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>8858.0</td>\n",
+       "      <td>8729.0</td>\n",
+       "      <td>9147.0</td>\n",
+       "      <td>8908.0</td>\n",
+       "      <td>9202.0</td>\n",
+       "      <td>9274.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>9124.0</td>\n",
+       "      <td>9132.0</td>\n",
+       "      <td>9300.0</td>\n",
+       "      <td>9043.0</td>\n",
+       "      <td>9383.0</td>\n",
+       "      <td>9316.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>8899.0</td>\n",
+       "      <td>9144.0</td>\n",
+       "      <td>9381.0</td>\n",
+       "      <td>9224.0</td>\n",
+       "      <td>9534.0</td>\n",
+       "      <td>9846.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>9104.0</td>\n",
+       "      <td>9100.0</td>\n",
+       "      <td>9131.0</td>\n",
+       "      <td>8970.0</td>\n",
+       "      <td>9351.0</td>\n",
+       "      <td>10078.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>9025.0</td>\n",
+       "      <td>9508.0</td>\n",
+       "      <td>9389.0</td>\n",
+       "      <td>8925.0</td>\n",
+       "      <td>9522.0</td>\n",
+       "      <td>10175.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>9388.0</td>\n",
+       "      <td>9844.0</td>\n",
+       "      <td>9748.0</td>\n",
+       "      <td>9509.0</td>\n",
+       "      <td>10044.0</td>\n",
+       "      <td>10980.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>9325.0</td>\n",
+       "      <td>10013.0</td>\n",
+       "      <td>9609.0</td>\n",
+       "      <td>9537.0</td>\n",
+       "      <td>9976.0</td>\n",
+       "      <td>11512.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>9219.0</td>\n",
+       "      <td>9942.0</td>\n",
+       "      <td>9982.0</td>\n",
+       "      <td>9300.0</td>\n",
+       "      <td>10183.0</td>\n",
+       "      <td>11687.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>9233.0</td>\n",
+       "      <td>9796.0</td>\n",
+       "      <td>9902.0</td>\n",
+       "      <td>9360.0</td>\n",
+       "      <td>10269.0</td>\n",
+       "      <td>11659.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>9706.0</td>\n",
+       "      <td>10530.0</td>\n",
+       "      <td>10151.0</td>\n",
+       "      <td>9613.0</td>\n",
+       "      <td>10079.0</td>\n",
+       "      <td>11467.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>9581.0</td>\n",
+       "      <td>9870.0</td>\n",
+       "      <td>10509.0</td>\n",
+       "      <td>9842.0</td>\n",
+       "      <td>10489.0</td>\n",
+       "      <td>11478.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>10043.0</td>\n",
+       "      <td>10802.0</td>\n",
+       "      <td>11755.0</td>\n",
+       "      <td>10392.0</td>\n",
+       "      <td>11159.0</td>\n",
+       "      <td>12129.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>8095.0</td>\n",
+       "      <td>7445.0</td>\n",
+       "      <td>7946.0</td>\n",
+       "      <td>6670.0</td>\n",
+       "      <td>7037.0</td>\n",
+       "      <td>10695.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>7008.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9342.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "year     2015     2016     2017     2018     2019     2020\n",
+       "week                                                      \n",
+       "1     11561.0  12236.0  11247.0  11940.0  10237.0  11467.0\n",
+       "2     15206.0  10790.0  12890.0  14146.0  11800.0  13119.0\n",
+       "3     13930.0  10753.0  12775.0  13371.0  11177.0  12223.0\n",
+       "4     13106.0  10600.0  11996.0  13085.0  11006.0  11133.0\n",
+       "5     12099.0  10362.0  11736.0  12470.0  10552.0  10885.0\n",
+       "6     11319.0  10470.0  11546.0  11694.0  10959.0  10296.0\n",
+       "7     11112.0   9933.0  10954.0  11443.0  11076.0  10216.0\n",
+       "8     10695.0  10360.0  11093.0  11353.0  10600.0  10162.0\n",
+       "9     10736.0  10564.0  10533.0  10220.0  10360.0  10165.0\n",
+       "10    10757.0  10276.0  10443.0  12101.0  10276.0  10243.0\n",
+       "11    10290.0  10284.0  10044.0  11870.0   9901.0  10344.0\n",
+       "12     9888.0   8967.0   9690.0  11139.0   9774.0   9926.0\n",
+       "13     9827.0   9574.0   9369.0   9308.0   9213.0  10422.0\n",
+       "14     8482.0  10857.0   9297.0  10064.0   9484.0  15467.0\n",
+       "15     9429.0  10679.0   7916.0  11558.0   9654.0  17588.0\n",
+       "16    10968.0  10211.0   8990.0  10535.0   8445.0  21182.0\n",
+       "17     9937.0   9784.0  10181.0   9692.0   9381.0  20873.0\n",
+       "18     9506.0   8568.0   8464.0   9520.0  10519.0  17024.0\n",
+       "19     8273.0   9985.0  10006.0   8094.0   8455.0  11965.0\n",
+       "20     9668.0   9342.0   9673.0   9474.0   9614.0  13801.0\n",
+       "21     9391.0   9115.0   9438.0   9033.0   9657.0  11596.0\n",
+       "22     7625.0   7409.0   7746.0   7609.0   7742.0   9237.0\n",
+       "23     9509.0   9289.0   9182.0   9343.0   9514.0  10009.0\n",
+       "24     8942.0   8808.0   8768.0   8782.0   8847.0   9402.0\n",
+       "25     8717.0   8807.0   9019.0   8694.0   8916.0   8722.0\n",
+       "26     8593.0   8679.0   8788.0   8613.0   8947.0   8427.0\n",
+       "27     8670.0   8614.0   8707.0   8633.0   8528.0   8556.0\n",
+       "28     8461.0   8789.0   8812.0   8710.0   8591.0   8118.0\n",
+       "29     8228.0   8790.0   8562.0   8579.0   8527.0   8273.0\n",
+       "30     8262.0   8725.0   8296.0   8581.0   8569.0   8326.0\n",
+       "31     8071.0   8602.0   8351.0   8587.0   8701.0   8415.0\n",
+       "32     8298.0   8531.0   8466.0   8782.0   8580.0   8382.0\n",
+       "33     8600.0   8496.0   8707.0   8312.0   8504.0   8775.0\n",
+       "34     8564.0   8700.0   8812.0   8413.0   8441.0   9037.0\n",
+       "35     8423.0   7453.0   7594.0   7354.0   7684.0   8441.0\n",
+       "36     7389.0   8847.0   8955.0   8851.0   9113.0   7251.0\n",
+       "37     8704.0   8548.0   8845.0   8612.0   8946.0   9233.0\n",
+       "38     8542.0   8382.0   8949.0   8707.0   8868.0   8968.0\n",
+       "39     8865.0   8402.0   9096.0   8590.0   8906.0   9017.0\n",
+       "40     8858.0   8729.0   9147.0   8908.0   9202.0   9274.0\n",
+       "41     9124.0   9132.0   9300.0   9043.0   9383.0   9316.0\n",
+       "42     8899.0   9144.0   9381.0   9224.0   9534.0   9846.0\n",
+       "43     9104.0   9100.0   9131.0   8970.0   9351.0  10078.0\n",
+       "44     9025.0   9508.0   9389.0   8925.0   9522.0  10175.0\n",
+       "45     9388.0   9844.0   9748.0   9509.0  10044.0  10980.0\n",
+       "46     9325.0  10013.0   9609.0   9537.0   9976.0  11512.0\n",
+       "47     9219.0   9942.0   9982.0   9300.0  10183.0  11687.0\n",
+       "48     9233.0   9796.0   9902.0   9360.0  10269.0  11659.0\n",
+       "49     9706.0  10530.0  10151.0   9613.0  10079.0  11467.0\n",
+       "50     9581.0   9870.0  10509.0   9842.0  10489.0  11478.0\n",
+       "51    10043.0  10802.0  11755.0  10392.0  11159.0  12129.0\n",
+       "52     8095.0   7445.0   7946.0   6670.0   7037.0  10695.0\n",
+       "53     7008.0      NaN      NaN      NaN      NaN   9342.0"
+      ]
+     },
+     "execution_count": 569,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_headlines_e = res.DataFrame().pivot(index='week', columns='year', values='deaths')\n",
+    "deaths_headlines_e"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 570,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "314 rows affected.\n",
+      "Returning data to local variable res\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%sql res << select week, year, deaths\n",
+    "from all_causes_deaths\n",
+    "where nation = 'Scotland'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 571,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>year</th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>2017</th>\n",
+       "      <th>2018</th>\n",
+       "      <th>2019</th>\n",
+       "      <th>2020</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>week</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1146.0</td>\n",
+       "      <td>1394.0</td>\n",
+       "      <td>1205.0</td>\n",
+       "      <td>1531.0</td>\n",
+       "      <td>1104.0</td>\n",
+       "      <td>1161.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1708.0</td>\n",
+       "      <td>1305.0</td>\n",
+       "      <td>1379.0</td>\n",
+       "      <td>1899.0</td>\n",
+       "      <td>1507.0</td>\n",
+       "      <td>1567.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1489.0</td>\n",
+       "      <td>1215.0</td>\n",
+       "      <td>1224.0</td>\n",
+       "      <td>1629.0</td>\n",
+       "      <td>1353.0</td>\n",
+       "      <td>1322.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1381.0</td>\n",
+       "      <td>1187.0</td>\n",
+       "      <td>1197.0</td>\n",
+       "      <td>1610.0</td>\n",
+       "      <td>1208.0</td>\n",
+       "      <td>1226.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>1286.0</td>\n",
+       "      <td>1205.0</td>\n",
+       "      <td>1332.0</td>\n",
+       "      <td>1369.0</td>\n",
+       "      <td>1206.0</td>\n",
+       "      <td>1188.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>1344.0</td>\n",
+       "      <td>1217.0</td>\n",
+       "      <td>1200.0</td>\n",
+       "      <td>1265.0</td>\n",
+       "      <td>1243.0</td>\n",
+       "      <td>1216.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>1360.0</td>\n",
+       "      <td>1209.0</td>\n",
+       "      <td>1231.0</td>\n",
+       "      <td>1315.0</td>\n",
+       "      <td>1181.0</td>\n",
+       "      <td>1162.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>1320.0</td>\n",
+       "      <td>1239.0</td>\n",
+       "      <td>1185.0</td>\n",
+       "      <td>1245.0</td>\n",
+       "      <td>1245.0</td>\n",
+       "      <td>1162.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>1308.0</td>\n",
+       "      <td>1150.0</td>\n",
+       "      <td>1219.0</td>\n",
+       "      <td>1022.0</td>\n",
+       "      <td>1125.0</td>\n",
+       "      <td>1171.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>1192.0</td>\n",
+       "      <td>1174.0</td>\n",
+       "      <td>1146.0</td>\n",
+       "      <td>1475.0</td>\n",
+       "      <td>1156.0</td>\n",
+       "      <td>1208.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>1201.0</td>\n",
+       "      <td>1175.0</td>\n",
+       "      <td>1141.0</td>\n",
+       "      <td>1220.0</td>\n",
+       "      <td>1108.0</td>\n",
+       "      <td>1156.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>1149.0</td>\n",
+       "      <td>1042.0</td>\n",
+       "      <td>1152.0</td>\n",
+       "      <td>1158.0</td>\n",
+       "      <td>1101.0</td>\n",
+       "      <td>1196.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>1171.0</td>\n",
+       "      <td>1172.0</td>\n",
+       "      <td>1112.0</td>\n",
+       "      <td>1050.0</td>\n",
+       "      <td>1086.0</td>\n",
+       "      <td>1079.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>1042.0</td>\n",
+       "      <td>1166.0</td>\n",
+       "      <td>1060.0</td>\n",
+       "      <td>1192.0</td>\n",
+       "      <td>1032.0</td>\n",
+       "      <td>1744.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>1192.0</td>\n",
+       "      <td>1048.0</td>\n",
+       "      <td>998.0</td>\n",
+       "      <td>1192.0</td>\n",
+       "      <td>1069.0</td>\n",
+       "      <td>1978.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>1095.0</td>\n",
+       "      <td>1092.0</td>\n",
+       "      <td>1111.0</td>\n",
+       "      <td>1136.0</td>\n",
+       "      <td>902.0</td>\n",
+       "      <td>1916.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>1108.0</td>\n",
+       "      <td>1076.0</td>\n",
+       "      <td>1121.0</td>\n",
+       "      <td>1008.0</td>\n",
+       "      <td>1121.0</td>\n",
+       "      <td>1836.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>1117.0</td>\n",
+       "      <td>1006.0</td>\n",
+       "      <td>1050.0</td>\n",
+       "      <td>1093.0</td>\n",
+       "      <td>1131.0</td>\n",
+       "      <td>1679.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>1020.0</td>\n",
+       "      <td>1047.0</td>\n",
+       "      <td>1119.0</td>\n",
+       "      <td>967.0</td>\n",
+       "      <td>1018.0</td>\n",
+       "      <td>1435.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>1103.0</td>\n",
+       "      <td>1010.0</td>\n",
+       "      <td>1115.0</td>\n",
+       "      <td>977.0</td>\n",
+       "      <td>1115.0</td>\n",
+       "      <td>1421.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>1039.0</td>\n",
+       "      <td>994.0</td>\n",
+       "      <td>1063.0</td>\n",
+       "      <td>1070.0</td>\n",
+       "      <td>1061.0</td>\n",
+       "      <td>1226.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>1043.0</td>\n",
+       "      <td>999.0</td>\n",
+       "      <td>1015.0</td>\n",
+       "      <td>998.0</td>\n",
+       "      <td>1029.0</td>\n",
+       "      <td>1125.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>1106.0</td>\n",
+       "      <td>1023.0</td>\n",
+       "      <td>1076.0</td>\n",
+       "      <td>1033.0</td>\n",
+       "      <td>1042.0</td>\n",
+       "      <td>1093.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>1038.0</td>\n",
+       "      <td>988.0</td>\n",
+       "      <td>1031.0</td>\n",
+       "      <td>915.0</td>\n",
+       "      <td>1028.0</td>\n",
+       "      <td>1034.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>1025.0</td>\n",
+       "      <td>994.0</td>\n",
+       "      <td>1032.0</td>\n",
+       "      <td>993.0</td>\n",
+       "      <td>1053.0</td>\n",
+       "      <td>1065.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>1032.0</td>\n",
+       "      <td>1007.0</td>\n",
+       "      <td>994.0</td>\n",
+       "      <td>1046.0</td>\n",
+       "      <td>1051.0</td>\n",
+       "      <td>1008.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>1040.0</td>\n",
+       "      <td>988.0</td>\n",
+       "      <td>1040.0</td>\n",
+       "      <td>1041.0</td>\n",
+       "      <td>981.0</td>\n",
+       "      <td>983.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>1011.0</td>\n",
+       "      <td>1022.0</td>\n",
+       "      <td>1014.0</td>\n",
+       "      <td>1002.0</td>\n",
+       "      <td>1077.0</td>\n",
+       "      <td>976.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>1023.0</td>\n",
+       "      <td>1041.0</td>\n",
+       "      <td>1025.0</td>\n",
+       "      <td>928.0</td>\n",
+       "      <td>964.0</td>\n",
+       "      <td>1033.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>956.0</td>\n",
+       "      <td>979.0</td>\n",
+       "      <td>978.0</td>\n",
+       "      <td>933.0</td>\n",
+       "      <td>1041.0</td>\n",
+       "      <td>961.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>985.0</td>\n",
+       "      <td>987.0</td>\n",
+       "      <td>1011.0</td>\n",
+       "      <td>969.0</td>\n",
+       "      <td>1020.0</td>\n",
+       "      <td>1043.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>1043.0</td>\n",
+       "      <td>997.0</td>\n",
+       "      <td>1002.0</td>\n",
+       "      <td>953.0</td>\n",
+       "      <td>1018.0</td>\n",
+       "      <td>1011.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>969.0</td>\n",
+       "      <td>982.0</td>\n",
+       "      <td>1004.0</td>\n",
+       "      <td>978.0</td>\n",
+       "      <td>1028.0</td>\n",
+       "      <td>922.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>982.0</td>\n",
+       "      <td>1017.0</td>\n",
+       "      <td>1045.0</td>\n",
+       "      <td>941.0</td>\n",
+       "      <td>1011.0</td>\n",
+       "      <td>1046.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>954.0</td>\n",
+       "      <td>1039.0</td>\n",
+       "      <td>980.0</td>\n",
+       "      <td>930.0</td>\n",
+       "      <td>1013.0</td>\n",
+       "      <td>1029.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>977.0</td>\n",
+       "      <td>1007.0</td>\n",
+       "      <td>1006.0</td>\n",
+       "      <td>970.0</td>\n",
+       "      <td>980.0</td>\n",
+       "      <td>1050.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>991.0</td>\n",
+       "      <td>983.0</td>\n",
+       "      <td>972.0</td>\n",
+       "      <td>1020.0</td>\n",
+       "      <td>1074.0</td>\n",
+       "      <td>1069.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>1001.0</td>\n",
+       "      <td>966.0</td>\n",
+       "      <td>1049.0</td>\n",
+       "      <td>946.0</td>\n",
+       "      <td>1071.0</td>\n",
+       "      <td>952.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>1010.0</td>\n",
+       "      <td>1009.0</td>\n",
+       "      <td>1056.0</td>\n",
+       "      <td>1015.0</td>\n",
+       "      <td>1142.0</td>\n",
+       "      <td>933.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>1008.0</td>\n",
+       "      <td>1072.0</td>\n",
+       "      <td>1016.0</td>\n",
+       "      <td>1042.0</td>\n",
+       "      <td>1051.0</td>\n",
+       "      <td>1195.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>1028.0</td>\n",
+       "      <td>1009.0</td>\n",
+       "      <td>1133.0</td>\n",
+       "      <td>1081.0</td>\n",
+       "      <td>1143.0</td>\n",
+       "      <td>1071.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>989.0</td>\n",
+       "      <td>1070.0</td>\n",
+       "      <td>1067.0</td>\n",
+       "      <td>1031.0</td>\n",
+       "      <td>1153.0</td>\n",
+       "      <td>1131.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>981.0</td>\n",
+       "      <td>1052.0</td>\n",
+       "      <td>1095.0</td>\n",
+       "      <td>1019.0</td>\n",
+       "      <td>1115.0</td>\n",
+       "      <td>1187.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>1116.0</td>\n",
+       "      <td>1032.0</td>\n",
+       "      <td>1062.0</td>\n",
+       "      <td>1085.0</td>\n",
+       "      <td>1101.0</td>\n",
+       "      <td>1262.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>1028.0</td>\n",
+       "      <td>1043.0</td>\n",
+       "      <td>1126.0</td>\n",
+       "      <td>1144.0</td>\n",
+       "      <td>1184.0</td>\n",
+       "      <td>1250.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>1103.0</td>\n",
+       "      <td>1174.0</td>\n",
+       "      <td>1175.0</td>\n",
+       "      <td>1084.0</td>\n",
+       "      <td>1160.0</td>\n",
+       "      <td>1138.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>1054.0</td>\n",
+       "      <td>1132.0</td>\n",
+       "      <td>1178.0</td>\n",
+       "      <td>1058.0</td>\n",
+       "      <td>1229.0</td>\n",
+       "      <td>1360.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>1115.0</td>\n",
+       "      <td>1159.0</td>\n",
+       "      <td>1153.0</td>\n",
+       "      <td>1062.0</td>\n",
+       "      <td>1163.0</td>\n",
+       "      <td>1328.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>1089.0</td>\n",
+       "      <td>1188.0</td>\n",
+       "      <td>1237.0</td>\n",
+       "      <td>1076.0</td>\n",
+       "      <td>1108.0</td>\n",
+       "      <td>1296.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>1101.0</td>\n",
+       "      <td>1219.0</td>\n",
+       "      <td>1335.0</td>\n",
+       "      <td>1212.0</td>\n",
+       "      <td>1312.0</td>\n",
+       "      <td>1284.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>1146.0</td>\n",
+       "      <td>1284.0</td>\n",
+       "      <td>1437.0</td>\n",
+       "      <td>1216.0</td>\n",
+       "      <td>1277.0</td>\n",
+       "      <td>1297.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>944.0</td>\n",
+       "      <td>1133.0</td>\n",
+       "      <td>1168.0</td>\n",
+       "      <td>1058.0</td>\n",
+       "      <td>1000.0</td>\n",
+       "      <td>1205.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>1018.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1178.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "year    2015    2016    2017    2018    2019    2020\n",
+       "week                                                \n",
+       "1     1146.0  1394.0  1205.0  1531.0  1104.0  1161.0\n",
+       "2     1708.0  1305.0  1379.0  1899.0  1507.0  1567.0\n",
+       "3     1489.0  1215.0  1224.0  1629.0  1353.0  1322.0\n",
+       "4     1381.0  1187.0  1197.0  1610.0  1208.0  1226.0\n",
+       "5     1286.0  1205.0  1332.0  1369.0  1206.0  1188.0\n",
+       "6     1344.0  1217.0  1200.0  1265.0  1243.0  1216.0\n",
+       "7     1360.0  1209.0  1231.0  1315.0  1181.0  1162.0\n",
+       "8     1320.0  1239.0  1185.0  1245.0  1245.0  1162.0\n",
+       "9     1308.0  1150.0  1219.0  1022.0  1125.0  1171.0\n",
+       "10    1192.0  1174.0  1146.0  1475.0  1156.0  1208.0\n",
+       "11    1201.0  1175.0  1141.0  1220.0  1108.0  1156.0\n",
+       "12    1149.0  1042.0  1152.0  1158.0  1101.0  1196.0\n",
+       "13    1171.0  1172.0  1112.0  1050.0  1086.0  1079.0\n",
+       "14    1042.0  1166.0  1060.0  1192.0  1032.0  1744.0\n",
+       "15    1192.0  1048.0   998.0  1192.0  1069.0  1978.0\n",
+       "16    1095.0  1092.0  1111.0  1136.0   902.0  1916.0\n",
+       "17    1108.0  1076.0  1121.0  1008.0  1121.0  1836.0\n",
+       "18    1117.0  1006.0  1050.0  1093.0  1131.0  1679.0\n",
+       "19    1020.0  1047.0  1119.0   967.0  1018.0  1435.0\n",
+       "20    1103.0  1010.0  1115.0   977.0  1115.0  1421.0\n",
+       "21    1039.0   994.0  1063.0  1070.0  1061.0  1226.0\n",
+       "22    1043.0   999.0  1015.0   998.0  1029.0  1125.0\n",
+       "23    1106.0  1023.0  1076.0  1033.0  1042.0  1093.0\n",
+       "24    1038.0   988.0  1031.0   915.0  1028.0  1034.0\n",
+       "25    1025.0   994.0  1032.0   993.0  1053.0  1065.0\n",
+       "26    1032.0  1007.0   994.0  1046.0  1051.0  1008.0\n",
+       "27    1040.0   988.0  1040.0  1041.0   981.0   983.0\n",
+       "28    1011.0  1022.0  1014.0  1002.0  1077.0   976.0\n",
+       "29    1023.0  1041.0  1025.0   928.0   964.0  1033.0\n",
+       "30     956.0   979.0   978.0   933.0  1041.0   961.0\n",
+       "31     985.0   987.0  1011.0   969.0  1020.0  1043.0\n",
+       "32    1043.0   997.0  1002.0   953.0  1018.0  1011.0\n",
+       "33     969.0   982.0  1004.0   978.0  1028.0   922.0\n",
+       "34     982.0  1017.0  1045.0   941.0  1011.0  1046.0\n",
+       "35     954.0  1039.0   980.0   930.0  1013.0  1029.0\n",
+       "36     977.0  1007.0  1006.0   970.0   980.0  1050.0\n",
+       "37     991.0   983.0   972.0  1020.0  1074.0  1069.0\n",
+       "38    1001.0   966.0  1049.0   946.0  1071.0   952.0\n",
+       "39    1010.0  1009.0  1056.0  1015.0  1142.0   933.0\n",
+       "40    1008.0  1072.0  1016.0  1042.0  1051.0  1195.0\n",
+       "41    1028.0  1009.0  1133.0  1081.0  1143.0  1071.0\n",
+       "42     989.0  1070.0  1067.0  1031.0  1153.0  1131.0\n",
+       "43     981.0  1052.0  1095.0  1019.0  1115.0  1187.0\n",
+       "44    1116.0  1032.0  1062.0  1085.0  1101.0  1262.0\n",
+       "45    1028.0  1043.0  1126.0  1144.0  1184.0  1250.0\n",
+       "46    1103.0  1174.0  1175.0  1084.0  1160.0  1138.0\n",
+       "47    1054.0  1132.0  1178.0  1058.0  1229.0  1360.0\n",
+       "48    1115.0  1159.0  1153.0  1062.0  1163.0  1328.0\n",
+       "49    1089.0  1188.0  1237.0  1076.0  1108.0  1296.0\n",
+       "50    1101.0  1219.0  1335.0  1212.0  1312.0  1284.0\n",
+       "51    1146.0  1284.0  1437.0  1216.0  1277.0  1297.0\n",
+       "52     944.0  1133.0  1168.0  1058.0  1000.0  1205.0\n",
+       "53    1018.0     NaN     NaN     NaN     NaN  1178.0"
+      ]
+     },
+     "execution_count": 571,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_headlines_s = res.DataFrame().pivot(index='week', columns='year', values='deaths')\n",
+    "deaths_headlines_s"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 572,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "314 rows affected.\n",
+      "Returning data to local variable res\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%sql res << select week, year, deaths\n",
+    "from all_causes_deaths\n",
+    "where nation = 'Wales'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 573,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>year</th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>2017</th>\n",
+       "      <th>2018</th>\n",
+       "      <th>2019</th>\n",
+       "      <th>2020</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>week</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>725.0</td>\n",
+       "      <td>809.0</td>\n",
+       "      <td>744.0</td>\n",
+       "      <td>783.0</td>\n",
+       "      <td>718.0</td>\n",
+       "      <td>787.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1031.0</td>\n",
+       "      <td>711.0</td>\n",
+       "      <td>825.0</td>\n",
+       "      <td>904.0</td>\n",
+       "      <td>809.0</td>\n",
+       "      <td>939.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>936.0</td>\n",
+       "      <td>720.0</td>\n",
+       "      <td>835.0</td>\n",
+       "      <td>885.0</td>\n",
+       "      <td>683.0</td>\n",
+       "      <td>767.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>828.0</td>\n",
+       "      <td>717.0</td>\n",
+       "      <td>881.0</td>\n",
+       "      <td>850.0</td>\n",
+       "      <td>734.0</td>\n",
+       "      <td>723.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>801.0</td>\n",
+       "      <td>690.0</td>\n",
+       "      <td>749.0</td>\n",
+       "      <td>815.0</td>\n",
+       "      <td>745.0</td>\n",
+       "      <td>727.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>720.0</td>\n",
+       "      <td>700.0</td>\n",
+       "      <td>723.0</td>\n",
+       "      <td>801.0</td>\n",
+       "      <td>701.0</td>\n",
+       "      <td>690.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>710.0</td>\n",
+       "      <td>657.0</td>\n",
+       "      <td>690.0</td>\n",
+       "      <td>803.0</td>\n",
+       "      <td>748.0</td>\n",
+       "      <td>728.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>739.0</td>\n",
+       "      <td>696.0</td>\n",
+       "      <td>701.0</td>\n",
+       "      <td>789.0</td>\n",
+       "      <td>695.0</td>\n",
+       "      <td>679.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>736.0</td>\n",
+       "      <td>721.0</td>\n",
+       "      <td>715.0</td>\n",
+       "      <td>634.0</td>\n",
+       "      <td>684.0</td>\n",
+       "      <td>651.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>712.0</td>\n",
+       "      <td>734.0</td>\n",
+       "      <td>634.0</td>\n",
+       "      <td>896.0</td>\n",
+       "      <td>622.0</td>\n",
+       "      <td>652.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>661.0</td>\n",
+       "      <td>738.0</td>\n",
+       "      <td>653.0</td>\n",
+       "      <td>918.0</td>\n",
+       "      <td>666.0</td>\n",
+       "      <td>675.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>680.0</td>\n",
+       "      <td>668.0</td>\n",
+       "      <td>635.0</td>\n",
+       "      <td>774.0</td>\n",
+       "      <td>628.0</td>\n",
+       "      <td>719.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>666.0</td>\n",
+       "      <td>712.0</td>\n",
+       "      <td>658.0</td>\n",
+       "      <td>633.0</td>\n",
+       "      <td>654.0</td>\n",
+       "      <td>719.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>580.0</td>\n",
+       "      <td>742.0</td>\n",
+       "      <td>642.0</td>\n",
+       "      <td>730.0</td>\n",
+       "      <td>642.0</td>\n",
+       "      <td>920.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>660.0</td>\n",
+       "      <td>738.0</td>\n",
+       "      <td>577.0</td>\n",
+       "      <td>743.0</td>\n",
+       "      <td>637.0</td>\n",
+       "      <td>928.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>671.0</td>\n",
+       "      <td>714.0</td>\n",
+       "      <td>654.0</td>\n",
+       "      <td>688.0</td>\n",
+       "      <td>580.0</td>\n",
+       "      <td>1169.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>662.0</td>\n",
+       "      <td>629.0</td>\n",
+       "      <td>727.0</td>\n",
+       "      <td>614.0</td>\n",
+       "      <td>678.0</td>\n",
+       "      <td>1124.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>628.0</td>\n",
+       "      <td>569.0</td>\n",
+       "      <td>600.0</td>\n",
+       "      <td>633.0</td>\n",
+       "      <td>688.0</td>\n",
+       "      <td>929.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>589.0</td>\n",
+       "      <td>652.0</td>\n",
+       "      <td>687.0</td>\n",
+       "      <td>530.0</td>\n",
+       "      <td>600.0</td>\n",
+       "      <td>692.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>622.0</td>\n",
+       "      <td>611.0</td>\n",
+       "      <td>615.0</td>\n",
+       "      <td>667.0</td>\n",
+       "      <td>658.0</td>\n",
+       "      <td>772.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>614.0</td>\n",
+       "      <td>624.0</td>\n",
+       "      <td>602.0</td>\n",
+       "      <td>603.0</td>\n",
+       "      <td>627.0</td>\n",
+       "      <td>692.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>588.0</td>\n",
+       "      <td>500.0</td>\n",
+       "      <td>586.0</td>\n",
+       "      <td>538.0</td>\n",
+       "      <td>518.0</td>\n",
+       "      <td>587.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>648.0</td>\n",
+       "      <td>584.0</td>\n",
+       "      <td>584.0</td>\n",
+       "      <td>607.0</td>\n",
+       "      <td>626.0</td>\n",
+       "      <td>700.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>606.0</td>\n",
+       "      <td>578.0</td>\n",
+       "      <td>599.0</td>\n",
+       "      <td>561.0</td>\n",
+       "      <td>598.0</td>\n",
+       "      <td>574.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>595.0</td>\n",
+       "      <td>558.0</td>\n",
+       "      <td>608.0</td>\n",
+       "      <td>562.0</td>\n",
+       "      <td>542.0</td>\n",
+       "      <td>617.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>597.0</td>\n",
+       "      <td>549.0</td>\n",
+       "      <td>546.0</td>\n",
+       "      <td>599.0</td>\n",
+       "      <td>564.0</td>\n",
+       "      <td>552.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>535.0</td>\n",
+       "      <td>524.0</td>\n",
+       "      <td>556.0</td>\n",
+       "      <td>625.0</td>\n",
+       "      <td>534.0</td>\n",
+       "      <td>584.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>554.0</td>\n",
+       "      <td>599.0</td>\n",
+       "      <td>564.0</td>\n",
+       "      <td>583.0</td>\n",
+       "      <td>588.0</td>\n",
+       "      <td>572.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>574.0</td>\n",
+       "      <td>560.0</td>\n",
+       "      <td>551.0</td>\n",
+       "      <td>548.0</td>\n",
+       "      <td>553.0</td>\n",
+       "      <td>550.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>529.0</td>\n",
+       "      <td>610.0</td>\n",
+       "      <td>586.0</td>\n",
+       "      <td>560.0</td>\n",
+       "      <td>543.0</td>\n",
+       "      <td>565.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>546.0</td>\n",
+       "      <td>580.0</td>\n",
+       "      <td>590.0</td>\n",
+       "      <td>574.0</td>\n",
+       "      <td>570.0</td>\n",
+       "      <td>531.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>564.0</td>\n",
+       "      <td>641.0</td>\n",
+       "      <td>572.0</td>\n",
+       "      <td>537.0</td>\n",
+       "      <td>542.0</td>\n",
+       "      <td>563.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>548.0</td>\n",
+       "      <td>574.0</td>\n",
+       "      <td>592.0</td>\n",
+       "      <td>518.0</td>\n",
+       "      <td>589.0</td>\n",
+       "      <td>617.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>557.0</td>\n",
+       "      <td>619.0</td>\n",
+       "      <td>570.0</td>\n",
+       "      <td>565.0</td>\n",
+       "      <td>553.0</td>\n",
+       "      <td>594.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>603.0</td>\n",
+       "      <td>470.0</td>\n",
+       "      <td>555.0</td>\n",
+       "      <td>511.0</td>\n",
+       "      <td>558.0</td>\n",
+       "      <td>591.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>489.0</td>\n",
+       "      <td>552.0</td>\n",
+       "      <td>542.0</td>\n",
+       "      <td>594.0</td>\n",
+       "      <td>582.0</td>\n",
+       "      <td>488.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>554.0</td>\n",
+       "      <td>576.0</td>\n",
+       "      <td>609.0</td>\n",
+       "      <td>579.0</td>\n",
+       "      <td>567.0</td>\n",
+       "      <td>578.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>555.0</td>\n",
+       "      <td>563.0</td>\n",
+       "      <td>585.0</td>\n",
+       "      <td>598.0</td>\n",
+       "      <td>572.0</td>\n",
+       "      <td>555.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>664.0</td>\n",
+       "      <td>592.0</td>\n",
+       "      <td>593.0</td>\n",
+       "      <td>560.0</td>\n",
+       "      <td>611.0</td>\n",
+       "      <td>617.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>552.0</td>\n",
+       "      <td>562.0</td>\n",
+       "      <td>631.0</td>\n",
+       "      <td>595.0</td>\n",
+       "      <td>597.0</td>\n",
+       "      <td>671.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>652.0</td>\n",
+       "      <td>587.0</td>\n",
+       "      <td>640.0</td>\n",
+       "      <td>606.0</td>\n",
+       "      <td>590.0</td>\n",
+       "      <td>638.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>612.0</td>\n",
+       "      <td>624.0</td>\n",
+       "      <td>650.0</td>\n",
+       "      <td>640.0</td>\n",
+       "      <td>622.0</td>\n",
+       "      <td>688.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>607.0</td>\n",
+       "      <td>624.0</td>\n",
+       "      <td>608.0</td>\n",
+       "      <td>633.0</td>\n",
+       "      <td>670.0</td>\n",
+       "      <td>661.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>593.0</td>\n",
+       "      <td>644.0</td>\n",
+       "      <td>595.0</td>\n",
+       "      <td>604.0</td>\n",
+       "      <td>642.0</td>\n",
+       "      <td>712.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>606.0</td>\n",
+       "      <td>626.0</td>\n",
+       "      <td>598.0</td>\n",
+       "      <td>642.0</td>\n",
+       "      <td>653.0</td>\n",
+       "      <td>832.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>613.0</td>\n",
+       "      <td>681.0</td>\n",
+       "      <td>666.0</td>\n",
+       "      <td>656.0</td>\n",
+       "      <td>674.0</td>\n",
+       "      <td>742.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>611.0</td>\n",
+       "      <td>661.0</td>\n",
+       "      <td>639.0</td>\n",
+       "      <td>657.0</td>\n",
+       "      <td>699.0</td>\n",
+       "      <td>848.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>589.0</td>\n",
+       "      <td>643.0</td>\n",
+       "      <td>636.0</td>\n",
+       "      <td>673.0</td>\n",
+       "      <td>689.0</td>\n",
+       "      <td>797.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>659.0</td>\n",
+       "      <td>693.0</td>\n",
+       "      <td>630.0</td>\n",
+       "      <td>674.0</td>\n",
+       "      <td>737.0</td>\n",
+       "      <td>836.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>688.0</td>\n",
+       "      <td>663.0</td>\n",
+       "      <td>708.0</td>\n",
+       "      <td>708.0</td>\n",
+       "      <td>699.0</td>\n",
+       "      <td>814.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>646.0</td>\n",
+       "      <td>691.0</td>\n",
+       "      <td>762.0</td>\n",
+       "      <td>724.0</td>\n",
+       "      <td>767.0</td>\n",
+       "      <td>882.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>535.0</td>\n",
+       "      <td>558.0</td>\n",
+       "      <td>541.0</td>\n",
+       "      <td>461.0</td>\n",
+       "      <td>496.0</td>\n",
+       "      <td>825.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>516.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>727.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "year    2015   2016   2017   2018   2019    2020\n",
+       "week                                            \n",
+       "1      725.0  809.0  744.0  783.0  718.0   787.0\n",
+       "2     1031.0  711.0  825.0  904.0  809.0   939.0\n",
+       "3      936.0  720.0  835.0  885.0  683.0   767.0\n",
+       "4      828.0  717.0  881.0  850.0  734.0   723.0\n",
+       "5      801.0  690.0  749.0  815.0  745.0   727.0\n",
+       "6      720.0  700.0  723.0  801.0  701.0   690.0\n",
+       "7      710.0  657.0  690.0  803.0  748.0   728.0\n",
+       "8      739.0  696.0  701.0  789.0  695.0   679.0\n",
+       "9      736.0  721.0  715.0  634.0  684.0   651.0\n",
+       "10     712.0  734.0  634.0  896.0  622.0   652.0\n",
+       "11     661.0  738.0  653.0  918.0  666.0   675.0\n",
+       "12     680.0  668.0  635.0  774.0  628.0   719.0\n",
+       "13     666.0  712.0  658.0  633.0  654.0   719.0\n",
+       "14     580.0  742.0  642.0  730.0  642.0   920.0\n",
+       "15     660.0  738.0  577.0  743.0  637.0   928.0\n",
+       "16     671.0  714.0  654.0  688.0  580.0  1169.0\n",
+       "17     662.0  629.0  727.0  614.0  678.0  1124.0\n",
+       "18     628.0  569.0  600.0  633.0  688.0   929.0\n",
+       "19     589.0  652.0  687.0  530.0  600.0   692.0\n",
+       "20     622.0  611.0  615.0  667.0  658.0   772.0\n",
+       "21     614.0  624.0  602.0  603.0  627.0   692.0\n",
+       "22     588.0  500.0  586.0  538.0  518.0   587.0\n",
+       "23     648.0  584.0  584.0  607.0  626.0   700.0\n",
+       "24     606.0  578.0  599.0  561.0  598.0   574.0\n",
+       "25     595.0  558.0  608.0  562.0  542.0   617.0\n",
+       "26     597.0  549.0  546.0  599.0  564.0   552.0\n",
+       "27     535.0  524.0  556.0  625.0  534.0   584.0\n",
+       "28     554.0  599.0  564.0  583.0  588.0   572.0\n",
+       "29     574.0  560.0  551.0  548.0  553.0   550.0\n",
+       "30     529.0  610.0  586.0  560.0  543.0   565.0\n",
+       "31     546.0  580.0  590.0  574.0  570.0   531.0\n",
+       "32     564.0  641.0  572.0  537.0  542.0   563.0\n",
+       "33     548.0  574.0  592.0  518.0  589.0   617.0\n",
+       "34     557.0  619.0  570.0  565.0  553.0   594.0\n",
+       "35     603.0  470.0  555.0  511.0  558.0   591.0\n",
+       "36     489.0  552.0  542.0  594.0  582.0   488.0\n",
+       "37     554.0  576.0  609.0  579.0  567.0   578.0\n",
+       "38     555.0  563.0  585.0  598.0  572.0   555.0\n",
+       "39     664.0  592.0  593.0  560.0  611.0   617.0\n",
+       "40     552.0  562.0  631.0  595.0  597.0   671.0\n",
+       "41     652.0  587.0  640.0  606.0  590.0   638.0\n",
+       "42     612.0  624.0  650.0  640.0  622.0   688.0\n",
+       "43     607.0  624.0  608.0  633.0  670.0   661.0\n",
+       "44     593.0  644.0  595.0  604.0  642.0   712.0\n",
+       "45     606.0  626.0  598.0  642.0  653.0   832.0\n",
+       "46     613.0  681.0  666.0  656.0  674.0   742.0\n",
+       "47     611.0  661.0  639.0  657.0  699.0   848.0\n",
+       "48     589.0  643.0  636.0  673.0  689.0   797.0\n",
+       "49     659.0  693.0  630.0  674.0  737.0   836.0\n",
+       "50     688.0  663.0  708.0  708.0  699.0   814.0\n",
+       "51     646.0  691.0  762.0  724.0  767.0   882.0\n",
+       "52     535.0  558.0  541.0  461.0  496.0   825.0\n",
+       "53     516.0    NaN    NaN    NaN    NaN   727.0"
+      ]
+     },
+     "execution_count": 573,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_headlines_w = res.DataFrame().pivot(index='week', columns='year', values='deaths')\n",
+    "deaths_headlines_w"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 574,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "314 rows affected.\n",
+      "Returning data to local variable res\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%sql res << select week, year, deaths\n",
+    "from all_causes_deaths\n",
+    "where nation = 'Northern Ireland'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 575,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>year</th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>2017</th>\n",
+       "      <th>2018</th>\n",
+       "      <th>2019</th>\n",
+       "      <th>2020</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>week</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>319.0</td>\n",
+       "      <td>424.0</td>\n",
+       "      <td>416.0</td>\n",
+       "      <td>447.0</td>\n",
+       "      <td>365.0</td>\n",
+       "      <td>353.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>373.0</td>\n",
+       "      <td>348.0</td>\n",
+       "      <td>434.0</td>\n",
+       "      <td>481.0</td>\n",
+       "      <td>371.0</td>\n",
+       "      <td>395.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>383.0</td>\n",
+       "      <td>372.0</td>\n",
+       "      <td>397.0</td>\n",
+       "      <td>470.0</td>\n",
+       "      <td>332.0</td>\n",
+       "      <td>411.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>397.0</td>\n",
+       "      <td>355.0</td>\n",
+       "      <td>387.0</td>\n",
+       "      <td>426.0</td>\n",
+       "      <td>335.0</td>\n",
+       "      <td>347.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>374.0</td>\n",
+       "      <td>314.0</td>\n",
+       "      <td>371.0</td>\n",
+       "      <td>433.0</td>\n",
+       "      <td>296.0</td>\n",
+       "      <td>323.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>347.0</td>\n",
+       "      <td>310.0</td>\n",
+       "      <td>336.0</td>\n",
+       "      <td>351.0</td>\n",
+       "      <td>319.0</td>\n",
+       "      <td>332.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>328.0</td>\n",
+       "      <td>217.0</td>\n",
+       "      <td>337.0</td>\n",
+       "      <td>364.0</td>\n",
+       "      <td>342.0</td>\n",
+       "      <td>306.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>317.0</td>\n",
+       "      <td>423.0</td>\n",
+       "      <td>351.0</td>\n",
+       "      <td>366.0</td>\n",
+       "      <td>337.0</td>\n",
+       "      <td>297.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>401.0</td>\n",
+       "      <td>298.0</td>\n",
+       "      <td>352.0</td>\n",
+       "      <td>314.0</td>\n",
+       "      <td>310.0</td>\n",
+       "      <td>347.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>346.0</td>\n",
+       "      <td>309.0</td>\n",
+       "      <td>357.0</td>\n",
+       "      <td>387.0</td>\n",
+       "      <td>342.0</td>\n",
+       "      <td>312.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>323.0</td>\n",
+       "      <td>292.0</td>\n",
+       "      <td>251.0</td>\n",
+       "      <td>359.0</td>\n",
+       "      <td>343.0</td>\n",
+       "      <td>324.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>310.0</td>\n",
+       "      <td>306.0</td>\n",
+       "      <td>356.0</td>\n",
+       "      <td>326.0</td>\n",
+       "      <td>294.0</td>\n",
+       "      <td>271.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>323.0</td>\n",
+       "      <td>280.0</td>\n",
+       "      <td>314.0</td>\n",
+       "      <td>319.0</td>\n",
+       "      <td>307.0</td>\n",
+       "      <td>287.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>221.0</td>\n",
+       "      <td>295.0</td>\n",
+       "      <td>306.0</td>\n",
+       "      <td>286.0</td>\n",
+       "      <td>287.0</td>\n",
+       "      <td>434.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>294.0</td>\n",
+       "      <td>292.0</td>\n",
+       "      <td>270.0</td>\n",
+       "      <td>350.0</td>\n",
+       "      <td>301.0</td>\n",
+       "      <td>435.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>327.0</td>\n",
+       "      <td>293.0</td>\n",
+       "      <td>245.0</td>\n",
+       "      <td>280.0</td>\n",
+       "      <td>316.0</td>\n",
+       "      <td>424.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>316.0</td>\n",
+       "      <td>306.0</td>\n",
+       "      <td>327.0</td>\n",
+       "      <td>282.0</td>\n",
+       "      <td>272.0</td>\n",
+       "      <td>470.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>335.0</td>\n",
+       "      <td>258.0</td>\n",
+       "      <td>258.0</td>\n",
+       "      <td>292.0</td>\n",
+       "      <td>357.0</td>\n",
+       "      <td>427.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>256.0</td>\n",
+       "      <td>318.0</td>\n",
+       "      <td>302.0</td>\n",
+       "      <td>230.0</td>\n",
+       "      <td>288.0</td>\n",
+       "      <td>336.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>299.0</td>\n",
+       "      <td>259.0</td>\n",
+       "      <td>315.0</td>\n",
+       "      <td>268.0</td>\n",
+       "      <td>330.0</td>\n",
+       "      <td>396.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>290.0</td>\n",
+       "      <td>280.0</td>\n",
+       "      <td>328.0</td>\n",
+       "      <td>268.0</td>\n",
+       "      <td>308.0</td>\n",
+       "      <td>325.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>258.0</td>\n",
+       "      <td>284.0</td>\n",
+       "      <td>256.0</td>\n",
+       "      <td>252.0</td>\n",
+       "      <td>245.0</td>\n",
+       "      <td>316.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>340.0</td>\n",
+       "      <td>275.0</td>\n",
+       "      <td>292.0</td>\n",
+       "      <td>276.0</td>\n",
+       "      <td>279.0</td>\n",
+       "      <td>304.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>272.0</td>\n",
+       "      <td>299.0</td>\n",
+       "      <td>300.0</td>\n",
+       "      <td>277.0</td>\n",
+       "      <td>281.0</td>\n",
+       "      <td>292.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>292.0</td>\n",
+       "      <td>252.0</td>\n",
+       "      <td>271.0</td>\n",
+       "      <td>265.0</td>\n",
+       "      <td>296.0</td>\n",
+       "      <td>290.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>303.0</td>\n",
+       "      <td>291.0</td>\n",
+       "      <td>296.0</td>\n",
+       "      <td>271.0</td>\n",
+       "      <td>262.0</td>\n",
+       "      <td>295.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>300.0</td>\n",
+       "      <td>286.0</td>\n",
+       "      <td>262.0</td>\n",
+       "      <td>266.0</td>\n",
+       "      <td>285.0</td>\n",
+       "      <td>289.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>252.0</td>\n",
+       "      <td>237.0</td>\n",
+       "      <td>253.0</td>\n",
+       "      <td>172.0</td>\n",
+       "      <td>256.0</td>\n",
+       "      <td>275.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>203.0</td>\n",
+       "      <td>281.0</td>\n",
+       "      <td>288.0</td>\n",
+       "      <td>298.0</td>\n",
+       "      <td>280.0</td>\n",
+       "      <td>240.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>274.0</td>\n",
+       "      <td>298.0</td>\n",
+       "      <td>287.0</td>\n",
+       "      <td>282.0</td>\n",
+       "      <td>269.0</td>\n",
+       "      <td>307.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>291.0</td>\n",
+       "      <td>264.0</td>\n",
+       "      <td>287.0</td>\n",
+       "      <td>278.0</td>\n",
+       "      <td>273.0</td>\n",
+       "      <td>273.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>248.0</td>\n",
+       "      <td>270.0</td>\n",
+       "      <td>238.0</td>\n",
+       "      <td>270.0</td>\n",
+       "      <td>266.0</td>\n",
+       "      <td>280.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>235.0</td>\n",
+       "      <td>260.0</td>\n",
+       "      <td>266.0</td>\n",
+       "      <td>283.0</td>\n",
+       "      <td>284.0</td>\n",
+       "      <td>278.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>251.0</td>\n",
+       "      <td>301.0</td>\n",
+       "      <td>271.0</td>\n",
+       "      <td>280.0</td>\n",
+       "      <td>274.0</td>\n",
+       "      <td>313.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>259.0</td>\n",
+       "      <td>264.0</td>\n",
+       "      <td>243.0</td>\n",
+       "      <td>251.0</td>\n",
+       "      <td>223.0</td>\n",
+       "      <td>303.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>237.0</td>\n",
+       "      <td>275.0</td>\n",
+       "      <td>278.0</td>\n",
+       "      <td>265.0</td>\n",
+       "      <td>243.0</td>\n",
+       "      <td>234.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>324.0</td>\n",
+       "      <td>294.0</td>\n",
+       "      <td>266.0</td>\n",
+       "      <td>285.0</td>\n",
+       "      <td>305.0</td>\n",
+       "      <td>296.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>283.0</td>\n",
+       "      <td>272.0</td>\n",
+       "      <td>292.0</td>\n",
+       "      <td>247.0</td>\n",
+       "      <td>281.0</td>\n",
+       "      <td>322.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>287.0</td>\n",
+       "      <td>275.0</td>\n",
+       "      <td>282.0</td>\n",
+       "      <td>298.0</td>\n",
+       "      <td>295.0</td>\n",
+       "      <td>323.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>282.0</td>\n",
+       "      <td>308.0</td>\n",
+       "      <td>307.0</td>\n",
+       "      <td>324.0</td>\n",
+       "      <td>263.0</td>\n",
+       "      <td>328.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>304.0</td>\n",
+       "      <td>288.0</td>\n",
+       "      <td>284.0</td>\n",
+       "      <td>318.0</td>\n",
+       "      <td>287.0</td>\n",
+       "      <td>348.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>299.0</td>\n",
+       "      <td>296.0</td>\n",
+       "      <td>291.0</td>\n",
+       "      <td>282.0</td>\n",
+       "      <td>316.0</td>\n",
+       "      <td>278.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>274.0</td>\n",
+       "      <td>272.0</td>\n",
+       "      <td>318.0</td>\n",
+       "      <td>263.0</td>\n",
+       "      <td>279.0</td>\n",
+       "      <td>391.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>292.0</td>\n",
+       "      <td>279.0</td>\n",
+       "      <td>320.0</td>\n",
+       "      <td>252.0</td>\n",
+       "      <td>302.0</td>\n",
+       "      <td>368.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>290.0</td>\n",
+       "      <td>290.0</td>\n",
+       "      <td>295.0</td>\n",
+       "      <td>293.0</td>\n",
+       "      <td>296.0</td>\n",
+       "      <td>386.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>297.0</td>\n",
+       "      <td>341.0</td>\n",
+       "      <td>323.0</td>\n",
+       "      <td>275.0</td>\n",
+       "      <td>336.0</td>\n",
+       "      <td>406.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>294.0</td>\n",
+       "      <td>329.0</td>\n",
+       "      <td>303.0</td>\n",
+       "      <td>274.0</td>\n",
+       "      <td>361.0</td>\n",
+       "      <td>396.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>279.0</td>\n",
+       "      <td>303.0</td>\n",
+       "      <td>355.0</td>\n",
+       "      <td>297.0</td>\n",
+       "      <td>334.0</td>\n",
+       "      <td>348.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>294.0</td>\n",
+       "      <td>322.0</td>\n",
+       "      <td>324.0</td>\n",
+       "      <td>324.0</td>\n",
+       "      <td>351.0</td>\n",
+       "      <td>387.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>343.0</td>\n",
+       "      <td>324.0</td>\n",
+       "      <td>372.0</td>\n",
+       "      <td>316.0</td>\n",
+       "      <td>353.0</td>\n",
+       "      <td>366.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>301.0</td>\n",
+       "      <td>360.0</td>\n",
+       "      <td>354.0</td>\n",
+       "      <td>317.0</td>\n",
+       "      <td>363.0</td>\n",
+       "      <td>350.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>232.0</td>\n",
+       "      <td>199.0</td>\n",
+       "      <td>249.0</td>\n",
+       "      <td>195.0</td>\n",
+       "      <td>194.0</td>\n",
+       "      <td>310.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>232.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>333.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "year   2015   2016   2017   2018   2019   2020\n",
+       "week                                          \n",
+       "1     319.0  424.0  416.0  447.0  365.0  353.0\n",
+       "2     373.0  348.0  434.0  481.0  371.0  395.0\n",
+       "3     383.0  372.0  397.0  470.0  332.0  411.0\n",
+       "4     397.0  355.0  387.0  426.0  335.0  347.0\n",
+       "5     374.0  314.0  371.0  433.0  296.0  323.0\n",
+       "6     347.0  310.0  336.0  351.0  319.0  332.0\n",
+       "7     328.0  217.0  337.0  364.0  342.0  306.0\n",
+       "8     317.0  423.0  351.0  366.0  337.0  297.0\n",
+       "9     401.0  298.0  352.0  314.0  310.0  347.0\n",
+       "10    346.0  309.0  357.0  387.0  342.0  312.0\n",
+       "11    323.0  292.0  251.0  359.0  343.0  324.0\n",
+       "12    310.0  306.0  356.0  326.0  294.0  271.0\n",
+       "13    323.0  280.0  314.0  319.0  307.0  287.0\n",
+       "14    221.0  295.0  306.0  286.0  287.0  434.0\n",
+       "15    294.0  292.0  270.0  350.0  301.0  435.0\n",
+       "16    327.0  293.0  245.0  280.0  316.0  424.0\n",
+       "17    316.0  306.0  327.0  282.0  272.0  470.0\n",
+       "18    335.0  258.0  258.0  292.0  357.0  427.0\n",
+       "19    256.0  318.0  302.0  230.0  288.0  336.0\n",
+       "20    299.0  259.0  315.0  268.0  330.0  396.0\n",
+       "21    290.0  280.0  328.0  268.0  308.0  325.0\n",
+       "22    258.0  284.0  256.0  252.0  245.0  316.0\n",
+       "23    340.0  275.0  292.0  276.0  279.0  304.0\n",
+       "24    272.0  299.0  300.0  277.0  281.0  292.0\n",
+       "25    292.0  252.0  271.0  265.0  296.0  290.0\n",
+       "26    303.0  291.0  296.0  271.0  262.0  295.0\n",
+       "27    300.0  286.0  262.0  266.0  285.0  289.0\n",
+       "28    252.0  237.0  253.0  172.0  256.0  275.0\n",
+       "29    203.0  281.0  288.0  298.0  280.0  240.0\n",
+       "30    274.0  298.0  287.0  282.0  269.0  307.0\n",
+       "31    291.0  264.0  287.0  278.0  273.0  273.0\n",
+       "32    248.0  270.0  238.0  270.0  266.0  280.0\n",
+       "33    235.0  260.0  266.0  283.0  284.0  278.0\n",
+       "34    251.0  301.0  271.0  280.0  274.0  313.0\n",
+       "35    259.0  264.0  243.0  251.0  223.0  303.0\n",
+       "36    237.0  275.0  278.0  265.0  243.0  234.0\n",
+       "37    324.0  294.0  266.0  285.0  305.0  296.0\n",
+       "38    283.0  272.0  292.0  247.0  281.0  322.0\n",
+       "39    287.0  275.0  282.0  298.0  295.0  323.0\n",
+       "40    282.0  308.0  307.0  324.0  263.0  328.0\n",
+       "41    304.0  288.0  284.0  318.0  287.0  348.0\n",
+       "42    299.0  296.0  291.0  282.0  316.0  278.0\n",
+       "43    274.0  272.0  318.0  263.0  279.0  391.0\n",
+       "44    292.0  279.0  320.0  252.0  302.0  368.0\n",
+       "45    290.0  290.0  295.0  293.0  296.0  386.0\n",
+       "46    297.0  341.0  323.0  275.0  336.0  406.0\n",
+       "47    294.0  329.0  303.0  274.0  361.0  396.0\n",
+       "48    279.0  303.0  355.0  297.0  334.0  348.0\n",
+       "49    294.0  322.0  324.0  324.0  351.0  387.0\n",
+       "50    343.0  324.0  372.0  316.0  353.0  366.0\n",
+       "51    301.0  360.0  354.0  317.0  363.0  350.0\n",
+       "52    232.0  199.0  249.0  195.0  194.0  310.0\n",
+       "53    232.0    NaN    NaN    NaN    NaN  333.0"
+      ]
+     },
+     "execution_count": 575,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_headlines_i = res.DataFrame().pivot(index='week', columns='year', values='deaths')\n",
+    "deaths_headlines_i"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 579,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>year</th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>2017</th>\n",
+       "      <th>2018</th>\n",
+       "      <th>2019</th>\n",
+       "      <th>2020</th>\n",
+       "      <th>previous_mean</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>week</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>13751.0</td>\n",
+       "      <td>14863.0</td>\n",
+       "      <td>13612.0</td>\n",
+       "      <td>14701.0</td>\n",
+       "      <td>12424.0</td>\n",
+       "      <td>13768.0</td>\n",
+       "      <td>13870.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>18318.0</td>\n",
+       "      <td>13154.0</td>\n",
+       "      <td>15528.0</td>\n",
+       "      <td>17430.0</td>\n",
+       "      <td>14487.0</td>\n",
+       "      <td>16020.0</td>\n",
+       "      <td>15783.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>16738.0</td>\n",
+       "      <td>13060.0</td>\n",
+       "      <td>15231.0</td>\n",
+       "      <td>16355.0</td>\n",
+       "      <td>13545.0</td>\n",
+       "      <td>14723.0</td>\n",
+       "      <td>14985.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>15712.0</td>\n",
+       "      <td>12859.0</td>\n",
+       "      <td>14461.0</td>\n",
+       "      <td>15971.0</td>\n",
+       "      <td>13283.0</td>\n",
+       "      <td>13429.0</td>\n",
+       "      <td>14457.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>14560.0</td>\n",
+       "      <td>12571.0</td>\n",
+       "      <td>14188.0</td>\n",
+       "      <td>15087.0</td>\n",
+       "      <td>12799.0</td>\n",
+       "      <td>13123.0</td>\n",
+       "      <td>13841.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>13730.0</td>\n",
+       "      <td>12697.0</td>\n",
+       "      <td>13805.0</td>\n",
+       "      <td>14111.0</td>\n",
+       "      <td>13222.0</td>\n",
+       "      <td>12534.0</td>\n",
+       "      <td>13513.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>13510.0</td>\n",
+       "      <td>12016.0</td>\n",
+       "      <td>13212.0</td>\n",
+       "      <td>13925.0</td>\n",
+       "      <td>13347.0</td>\n",
+       "      <td>12412.0</td>\n",
+       "      <td>13202.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>13071.0</td>\n",
+       "      <td>12718.0</td>\n",
+       "      <td>13330.0</td>\n",
+       "      <td>13753.0</td>\n",
+       "      <td>12877.0</td>\n",
+       "      <td>12300.0</td>\n",
+       "      <td>13149.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>13181.0</td>\n",
+       "      <td>12733.0</td>\n",
+       "      <td>12819.0</td>\n",
+       "      <td>12190.0</td>\n",
+       "      <td>12479.0</td>\n",
+       "      <td>12334.0</td>\n",
+       "      <td>12680.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>13007.0</td>\n",
+       "      <td>12493.0</td>\n",
+       "      <td>12580.0</td>\n",
+       "      <td>14859.0</td>\n",
+       "      <td>12396.0</td>\n",
+       "      <td>12415.0</td>\n",
+       "      <td>13067.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>12475.0</td>\n",
+       "      <td>12489.0</td>\n",
+       "      <td>12089.0</td>\n",
+       "      <td>14367.0</td>\n",
+       "      <td>12018.0</td>\n",
+       "      <td>12499.0</td>\n",
+       "      <td>12687.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>12027.0</td>\n",
+       "      <td>10983.0</td>\n",
+       "      <td>11833.0</td>\n",
+       "      <td>13397.0</td>\n",
+       "      <td>11797.0</td>\n",
+       "      <td>12112.0</td>\n",
+       "      <td>12007.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>11987.0</td>\n",
+       "      <td>11738.0</td>\n",
+       "      <td>11453.0</td>\n",
+       "      <td>11310.0</td>\n",
+       "      <td>11260.0</td>\n",
+       "      <td>12507.0</td>\n",
+       "      <td>11549.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>10325.0</td>\n",
+       "      <td>13060.0</td>\n",
+       "      <td>11305.0</td>\n",
+       "      <td>12272.0</td>\n",
+       "      <td>11445.0</td>\n",
+       "      <td>18565.0</td>\n",
+       "      <td>11681.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>11575.0</td>\n",
+       "      <td>12757.0</td>\n",
+       "      <td>9761.0</td>\n",
+       "      <td>13843.0</td>\n",
+       "      <td>11661.0</td>\n",
+       "      <td>20929.0</td>\n",
+       "      <td>11919.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>13061.0</td>\n",
+       "      <td>12310.0</td>\n",
+       "      <td>11000.0</td>\n",
+       "      <td>12639.0</td>\n",
+       "      <td>10243.0</td>\n",
+       "      <td>24691.0</td>\n",
+       "      <td>11850.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>12023.0</td>\n",
+       "      <td>11795.0</td>\n",
+       "      <td>12356.0</td>\n",
+       "      <td>11596.0</td>\n",
+       "      <td>11452.0</td>\n",
+       "      <td>24303.0</td>\n",
+       "      <td>11844.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>11586.0</td>\n",
+       "      <td>10401.0</td>\n",
+       "      <td>10372.0</td>\n",
+       "      <td>11538.0</td>\n",
+       "      <td>12695.0</td>\n",
+       "      <td>20059.0</td>\n",
+       "      <td>11318.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>10138.0</td>\n",
+       "      <td>12002.0</td>\n",
+       "      <td>12114.0</td>\n",
+       "      <td>9821.0</td>\n",
+       "      <td>10361.0</td>\n",
+       "      <td>14428.0</td>\n",
+       "      <td>10887.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>11692.0</td>\n",
+       "      <td>11222.0</td>\n",
+       "      <td>11718.0</td>\n",
+       "      <td>11386.0</td>\n",
+       "      <td>11717.0</td>\n",
+       "      <td>16390.0</td>\n",
+       "      <td>11547.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>11334.0</td>\n",
+       "      <td>11013.0</td>\n",
+       "      <td>11431.0</td>\n",
+       "      <td>10974.0</td>\n",
+       "      <td>11653.0</td>\n",
+       "      <td>13839.0</td>\n",
+       "      <td>11281.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>9514.0</td>\n",
+       "      <td>9192.0</td>\n",
+       "      <td>9603.0</td>\n",
+       "      <td>9397.0</td>\n",
+       "      <td>9534.0</td>\n",
+       "      <td>11265.0</td>\n",
+       "      <td>9448.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>11603.0</td>\n",
+       "      <td>11171.0</td>\n",
+       "      <td>11134.0</td>\n",
+       "      <td>11259.0</td>\n",
+       "      <td>11461.0</td>\n",
+       "      <td>12106.0</td>\n",
+       "      <td>11325.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>10858.0</td>\n",
+       "      <td>10673.0</td>\n",
+       "      <td>10698.0</td>\n",
+       "      <td>10535.0</td>\n",
+       "      <td>10754.0</td>\n",
+       "      <td>11302.0</td>\n",
+       "      <td>10703.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>10629.0</td>\n",
+       "      <td>10611.0</td>\n",
+       "      <td>10930.0</td>\n",
+       "      <td>10514.0</td>\n",
+       "      <td>10807.0</td>\n",
+       "      <td>10694.0</td>\n",
+       "      <td>10698.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>10525.0</td>\n",
+       "      <td>10526.0</td>\n",
+       "      <td>10624.0</td>\n",
+       "      <td>10529.0</td>\n",
+       "      <td>10824.0</td>\n",
+       "      <td>10282.0</td>\n",
+       "      <td>10605.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>10545.0</td>\n",
+       "      <td>10412.0</td>\n",
+       "      <td>10565.0</td>\n",
+       "      <td>10565.0</td>\n",
+       "      <td>10328.0</td>\n",
+       "      <td>10412.0</td>\n",
+       "      <td>10483.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>10278.0</td>\n",
+       "      <td>10647.0</td>\n",
+       "      <td>10643.0</td>\n",
+       "      <td>10467.0</td>\n",
+       "      <td>10512.0</td>\n",
+       "      <td>9941.0</td>\n",
+       "      <td>10509.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>10028.0</td>\n",
+       "      <td>10672.0</td>\n",
+       "      <td>10426.0</td>\n",
+       "      <td>10353.0</td>\n",
+       "      <td>10324.0</td>\n",
+       "      <td>10096.0</td>\n",
+       "      <td>10360.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>10021.0</td>\n",
+       "      <td>10612.0</td>\n",
+       "      <td>10147.0</td>\n",
+       "      <td>10356.0</td>\n",
+       "      <td>10422.0</td>\n",
+       "      <td>10159.0</td>\n",
+       "      <td>10311.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>9893.0</td>\n",
+       "      <td>10433.0</td>\n",
+       "      <td>10239.0</td>\n",
+       "      <td>10408.0</td>\n",
+       "      <td>10564.0</td>\n",
+       "      <td>10262.0</td>\n",
+       "      <td>10307.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>10153.0</td>\n",
+       "      <td>10439.0</td>\n",
+       "      <td>10278.0</td>\n",
+       "      <td>10542.0</td>\n",
+       "      <td>10406.0</td>\n",
+       "      <td>10236.0</td>\n",
+       "      <td>10363.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>10352.0</td>\n",
+       "      <td>10312.0</td>\n",
+       "      <td>10569.0</td>\n",
+       "      <td>10091.0</td>\n",
+       "      <td>10405.0</td>\n",
+       "      <td>10592.0</td>\n",
+       "      <td>10345.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>10354.0</td>\n",
+       "      <td>10637.0</td>\n",
+       "      <td>10698.0</td>\n",
+       "      <td>10199.0</td>\n",
+       "      <td>10279.0</td>\n",
+       "      <td>10990.0</td>\n",
+       "      <td>10433.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>10239.0</td>\n",
+       "      <td>9226.0</td>\n",
+       "      <td>9372.0</td>\n",
+       "      <td>9046.0</td>\n",
+       "      <td>9478.0</td>\n",
+       "      <td>10364.0</td>\n",
+       "      <td>9472.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>9092.0</td>\n",
+       "      <td>10681.0</td>\n",
+       "      <td>10781.0</td>\n",
+       "      <td>10680.0</td>\n",
+       "      <td>10918.0</td>\n",
+       "      <td>9023.0</td>\n",
+       "      <td>10430.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>10573.0</td>\n",
+       "      <td>10401.0</td>\n",
+       "      <td>10692.0</td>\n",
+       "      <td>10496.0</td>\n",
+       "      <td>10892.0</td>\n",
+       "      <td>11176.0</td>\n",
+       "      <td>10610.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>10381.0</td>\n",
+       "      <td>10183.0</td>\n",
+       "      <td>10875.0</td>\n",
+       "      <td>10498.0</td>\n",
+       "      <td>10792.0</td>\n",
+       "      <td>10797.0</td>\n",
+       "      <td>10545.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>10826.0</td>\n",
+       "      <td>10278.0</td>\n",
+       "      <td>11027.0</td>\n",
+       "      <td>10463.0</td>\n",
+       "      <td>10954.0</td>\n",
+       "      <td>10890.0</td>\n",
+       "      <td>10709.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>10700.0</td>\n",
+       "      <td>10671.0</td>\n",
+       "      <td>11101.0</td>\n",
+       "      <td>10869.0</td>\n",
+       "      <td>11113.0</td>\n",
+       "      <td>11468.0</td>\n",
+       "      <td>10890.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>11108.0</td>\n",
+       "      <td>11016.0</td>\n",
+       "      <td>11357.0</td>\n",
+       "      <td>11048.0</td>\n",
+       "      <td>11403.0</td>\n",
+       "      <td>11373.0</td>\n",
+       "      <td>11186.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>10799.0</td>\n",
+       "      <td>11134.0</td>\n",
+       "      <td>11389.0</td>\n",
+       "      <td>11177.0</td>\n",
+       "      <td>11625.0</td>\n",
+       "      <td>11943.0</td>\n",
+       "      <td>11224.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>10966.0</td>\n",
+       "      <td>11048.0</td>\n",
+       "      <td>11152.0</td>\n",
+       "      <td>10885.0</td>\n",
+       "      <td>11415.0</td>\n",
+       "      <td>12317.0</td>\n",
+       "      <td>11093.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>11026.0</td>\n",
+       "      <td>11463.0</td>\n",
+       "      <td>11366.0</td>\n",
+       "      <td>10866.0</td>\n",
+       "      <td>11567.0</td>\n",
+       "      <td>12517.0</td>\n",
+       "      <td>11257.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>11312.0</td>\n",
+       "      <td>11803.0</td>\n",
+       "      <td>11767.0</td>\n",
+       "      <td>11588.0</td>\n",
+       "      <td>12177.0</td>\n",
+       "      <td>13448.0</td>\n",
+       "      <td>11729.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>11338.0</td>\n",
+       "      <td>12209.0</td>\n",
+       "      <td>11773.0</td>\n",
+       "      <td>11552.0</td>\n",
+       "      <td>12146.0</td>\n",
+       "      <td>13798.0</td>\n",
+       "      <td>11803.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>11178.0</td>\n",
+       "      <td>12064.0</td>\n",
+       "      <td>12102.0</td>\n",
+       "      <td>11289.0</td>\n",
+       "      <td>12472.0</td>\n",
+       "      <td>14291.0</td>\n",
+       "      <td>11821.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>11216.0</td>\n",
+       "      <td>11901.0</td>\n",
+       "      <td>12046.0</td>\n",
+       "      <td>11392.0</td>\n",
+       "      <td>12455.0</td>\n",
+       "      <td>14132.0</td>\n",
+       "      <td>11802.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>11748.0</td>\n",
+       "      <td>12733.0</td>\n",
+       "      <td>12342.0</td>\n",
+       "      <td>11687.0</td>\n",
+       "      <td>12275.0</td>\n",
+       "      <td>13986.0</td>\n",
+       "      <td>12157.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>11713.0</td>\n",
+       "      <td>12076.0</td>\n",
+       "      <td>12924.0</td>\n",
+       "      <td>12078.0</td>\n",
+       "      <td>12853.0</td>\n",
+       "      <td>13942.0</td>\n",
+       "      <td>12328.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>12136.0</td>\n",
+       "      <td>13137.0</td>\n",
+       "      <td>14308.0</td>\n",
+       "      <td>12649.0</td>\n",
+       "      <td>13566.0</td>\n",
+       "      <td>14658.0</td>\n",
+       "      <td>13159.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>9806.0</td>\n",
+       "      <td>9335.0</td>\n",
+       "      <td>9904.0</td>\n",
+       "      <td>8384.0</td>\n",
+       "      <td>8727.0</td>\n",
+       "      <td>13035.0</td>\n",
+       "      <td>9231.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>8774.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11580.0</td>\n",
+       "      <td>8774.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "year     2015     2016     2017     2018     2019     2020  previous_mean\n",
+       "week                                                                     \n",
+       "1     13751.0  14863.0  13612.0  14701.0  12424.0  13768.0        13870.2\n",
+       "2     18318.0  13154.0  15528.0  17430.0  14487.0  16020.0        15783.4\n",
+       "3     16738.0  13060.0  15231.0  16355.0  13545.0  14723.0        14985.8\n",
+       "4     15712.0  12859.0  14461.0  15971.0  13283.0  13429.0        14457.2\n",
+       "5     14560.0  12571.0  14188.0  15087.0  12799.0  13123.0        13841.0\n",
+       "6     13730.0  12697.0  13805.0  14111.0  13222.0  12534.0        13513.0\n",
+       "7     13510.0  12016.0  13212.0  13925.0  13347.0  12412.0        13202.0\n",
+       "8     13071.0  12718.0  13330.0  13753.0  12877.0  12300.0        13149.8\n",
+       "9     13181.0  12733.0  12819.0  12190.0  12479.0  12334.0        12680.4\n",
+       "10    13007.0  12493.0  12580.0  14859.0  12396.0  12415.0        13067.0\n",
+       "11    12475.0  12489.0  12089.0  14367.0  12018.0  12499.0        12687.6\n",
+       "12    12027.0  10983.0  11833.0  13397.0  11797.0  12112.0        12007.4\n",
+       "13    11987.0  11738.0  11453.0  11310.0  11260.0  12507.0        11549.6\n",
+       "14    10325.0  13060.0  11305.0  12272.0  11445.0  18565.0        11681.4\n",
+       "15    11575.0  12757.0   9761.0  13843.0  11661.0  20929.0        11919.4\n",
+       "16    13061.0  12310.0  11000.0  12639.0  10243.0  24691.0        11850.6\n",
+       "17    12023.0  11795.0  12356.0  11596.0  11452.0  24303.0        11844.4\n",
+       "18    11586.0  10401.0  10372.0  11538.0  12695.0  20059.0        11318.4\n",
+       "19    10138.0  12002.0  12114.0   9821.0  10361.0  14428.0        10887.2\n",
+       "20    11692.0  11222.0  11718.0  11386.0  11717.0  16390.0        11547.0\n",
+       "21    11334.0  11013.0  11431.0  10974.0  11653.0  13839.0        11281.0\n",
+       "22     9514.0   9192.0   9603.0   9397.0   9534.0  11265.0         9448.0\n",
+       "23    11603.0  11171.0  11134.0  11259.0  11461.0  12106.0        11325.6\n",
+       "24    10858.0  10673.0  10698.0  10535.0  10754.0  11302.0        10703.6\n",
+       "25    10629.0  10611.0  10930.0  10514.0  10807.0  10694.0        10698.2\n",
+       "26    10525.0  10526.0  10624.0  10529.0  10824.0  10282.0        10605.6\n",
+       "27    10545.0  10412.0  10565.0  10565.0  10328.0  10412.0        10483.0\n",
+       "28    10278.0  10647.0  10643.0  10467.0  10512.0   9941.0        10509.4\n",
+       "29    10028.0  10672.0  10426.0  10353.0  10324.0  10096.0        10360.6\n",
+       "30    10021.0  10612.0  10147.0  10356.0  10422.0  10159.0        10311.6\n",
+       "31     9893.0  10433.0  10239.0  10408.0  10564.0  10262.0        10307.4\n",
+       "32    10153.0  10439.0  10278.0  10542.0  10406.0  10236.0        10363.6\n",
+       "33    10352.0  10312.0  10569.0  10091.0  10405.0  10592.0        10345.8\n",
+       "34    10354.0  10637.0  10698.0  10199.0  10279.0  10990.0        10433.4\n",
+       "35    10239.0   9226.0   9372.0   9046.0   9478.0  10364.0         9472.2\n",
+       "36     9092.0  10681.0  10781.0  10680.0  10918.0   9023.0        10430.4\n",
+       "37    10573.0  10401.0  10692.0  10496.0  10892.0  11176.0        10610.8\n",
+       "38    10381.0  10183.0  10875.0  10498.0  10792.0  10797.0        10545.8\n",
+       "39    10826.0  10278.0  11027.0  10463.0  10954.0  10890.0        10709.6\n",
+       "40    10700.0  10671.0  11101.0  10869.0  11113.0  11468.0        10890.8\n",
+       "41    11108.0  11016.0  11357.0  11048.0  11403.0  11373.0        11186.4\n",
+       "42    10799.0  11134.0  11389.0  11177.0  11625.0  11943.0        11224.8\n",
+       "43    10966.0  11048.0  11152.0  10885.0  11415.0  12317.0        11093.2\n",
+       "44    11026.0  11463.0  11366.0  10866.0  11567.0  12517.0        11257.6\n",
+       "45    11312.0  11803.0  11767.0  11588.0  12177.0  13448.0        11729.4\n",
+       "46    11338.0  12209.0  11773.0  11552.0  12146.0  13798.0        11803.6\n",
+       "47    11178.0  12064.0  12102.0  11289.0  12472.0  14291.0        11821.0\n",
+       "48    11216.0  11901.0  12046.0  11392.0  12455.0  14132.0        11802.0\n",
+       "49    11748.0  12733.0  12342.0  11687.0  12275.0  13986.0        12157.0\n",
+       "50    11713.0  12076.0  12924.0  12078.0  12853.0  13942.0        12328.8\n",
+       "51    12136.0  13137.0  14308.0  12649.0  13566.0  14658.0        13159.2\n",
+       "52     9806.0   9335.0   9904.0   8384.0   8727.0  13035.0         9231.2\n",
+       "53     8774.0      NaN      NaN      NaN      NaN  11580.0         8774.0"
+      ]
+     },
+     "execution_count": 579,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_headlines = deaths_headlines_e + deaths_headlines_w + deaths_headlines_i + deaths_headlines_s\n",
+    "deaths_headlines"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 577,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Int64Index([2015, 2016, 2017, 2018, 2019, 2020], dtype='int64', name='year')"
+      ]
+     },
+     "execution_count": 577,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_headlines_e.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 578,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>year</th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>2017</th>\n",
+       "      <th>2018</th>\n",
+       "      <th>2019</th>\n",
+       "      <th>2020</th>\n",
+       "      <th>previous_mean</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>week</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>13751.0</td>\n",
+       "      <td>14863.0</td>\n",
+       "      <td>13612.0</td>\n",
+       "      <td>14701.0</td>\n",
+       "      <td>12424.0</td>\n",
+       "      <td>13768.0</td>\n",
+       "      <td>13870.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>18318.0</td>\n",
+       "      <td>13154.0</td>\n",
+       "      <td>15528.0</td>\n",
+       "      <td>17430.0</td>\n",
+       "      <td>14487.0</td>\n",
+       "      <td>16020.0</td>\n",
+       "      <td>15783.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>16738.0</td>\n",
+       "      <td>13060.0</td>\n",
+       "      <td>15231.0</td>\n",
+       "      <td>16355.0</td>\n",
+       "      <td>13545.0</td>\n",
+       "      <td>14723.0</td>\n",
+       "      <td>14985.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>15712.0</td>\n",
+       "      <td>12859.0</td>\n",
+       "      <td>14461.0</td>\n",
+       "      <td>15971.0</td>\n",
+       "      <td>13283.0</td>\n",
+       "      <td>13429.0</td>\n",
+       "      <td>14457.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>14560.0</td>\n",
+       "      <td>12571.0</td>\n",
+       "      <td>14188.0</td>\n",
+       "      <td>15087.0</td>\n",
+       "      <td>12799.0</td>\n",
+       "      <td>13123.0</td>\n",
+       "      <td>13841.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>13730.0</td>\n",
+       "      <td>12697.0</td>\n",
+       "      <td>13805.0</td>\n",
+       "      <td>14111.0</td>\n",
+       "      <td>13222.0</td>\n",
+       "      <td>12534.0</td>\n",
+       "      <td>13513.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>13510.0</td>\n",
+       "      <td>12016.0</td>\n",
+       "      <td>13212.0</td>\n",
+       "      <td>13925.0</td>\n",
+       "      <td>13347.0</td>\n",
+       "      <td>12412.0</td>\n",
+       "      <td>13202.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>13071.0</td>\n",
+       "      <td>12718.0</td>\n",
+       "      <td>13330.0</td>\n",
+       "      <td>13753.0</td>\n",
+       "      <td>12877.0</td>\n",
+       "      <td>12300.0</td>\n",
+       "      <td>13149.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>13181.0</td>\n",
+       "      <td>12733.0</td>\n",
+       "      <td>12819.0</td>\n",
+       "      <td>12190.0</td>\n",
+       "      <td>12479.0</td>\n",
+       "      <td>12334.0</td>\n",
+       "      <td>12680.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>13007.0</td>\n",
+       "      <td>12493.0</td>\n",
+       "      <td>12580.0</td>\n",
+       "      <td>14859.0</td>\n",
+       "      <td>12396.0</td>\n",
+       "      <td>12415.0</td>\n",
+       "      <td>13067.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>12475.0</td>\n",
+       "      <td>12489.0</td>\n",
+       "      <td>12089.0</td>\n",
+       "      <td>14367.0</td>\n",
+       "      <td>12018.0</td>\n",
+       "      <td>12499.0</td>\n",
+       "      <td>12687.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>12027.0</td>\n",
+       "      <td>10983.0</td>\n",
+       "      <td>11833.0</td>\n",
+       "      <td>13397.0</td>\n",
+       "      <td>11797.0</td>\n",
+       "      <td>12112.0</td>\n",
+       "      <td>12007.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>11987.0</td>\n",
+       "      <td>11738.0</td>\n",
+       "      <td>11453.0</td>\n",
+       "      <td>11310.0</td>\n",
+       "      <td>11260.0</td>\n",
+       "      <td>12507.0</td>\n",
+       "      <td>11549.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>10325.0</td>\n",
+       "      <td>13060.0</td>\n",
+       "      <td>11305.0</td>\n",
+       "      <td>12272.0</td>\n",
+       "      <td>11445.0</td>\n",
+       "      <td>18565.0</td>\n",
+       "      <td>11681.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>11575.0</td>\n",
+       "      <td>12757.0</td>\n",
+       "      <td>9761.0</td>\n",
+       "      <td>13843.0</td>\n",
+       "      <td>11661.0</td>\n",
+       "      <td>20929.0</td>\n",
+       "      <td>11919.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>13061.0</td>\n",
+       "      <td>12310.0</td>\n",
+       "      <td>11000.0</td>\n",
+       "      <td>12639.0</td>\n",
+       "      <td>10243.0</td>\n",
+       "      <td>24691.0</td>\n",
+       "      <td>11850.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>12023.0</td>\n",
+       "      <td>11795.0</td>\n",
+       "      <td>12356.0</td>\n",
+       "      <td>11596.0</td>\n",
+       "      <td>11452.0</td>\n",
+       "      <td>24303.0</td>\n",
+       "      <td>11844.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>11586.0</td>\n",
+       "      <td>10401.0</td>\n",
+       "      <td>10372.0</td>\n",
+       "      <td>11538.0</td>\n",
+       "      <td>12695.0</td>\n",
+       "      <td>20059.0</td>\n",
+       "      <td>11318.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>10138.0</td>\n",
+       "      <td>12002.0</td>\n",
+       "      <td>12114.0</td>\n",
+       "      <td>9821.0</td>\n",
+       "      <td>10361.0</td>\n",
+       "      <td>14428.0</td>\n",
+       "      <td>10887.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>11692.0</td>\n",
+       "      <td>11222.0</td>\n",
+       "      <td>11718.0</td>\n",
+       "      <td>11386.0</td>\n",
+       "      <td>11717.0</td>\n",
+       "      <td>16390.0</td>\n",
+       "      <td>11547.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>11334.0</td>\n",
+       "      <td>11013.0</td>\n",
+       "      <td>11431.0</td>\n",
+       "      <td>10974.0</td>\n",
+       "      <td>11653.0</td>\n",
+       "      <td>13839.0</td>\n",
+       "      <td>11281.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>9514.0</td>\n",
+       "      <td>9192.0</td>\n",
+       "      <td>9603.0</td>\n",
+       "      <td>9397.0</td>\n",
+       "      <td>9534.0</td>\n",
+       "      <td>11265.0</td>\n",
+       "      <td>9448.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>11603.0</td>\n",
+       "      <td>11171.0</td>\n",
+       "      <td>11134.0</td>\n",
+       "      <td>11259.0</td>\n",
+       "      <td>11461.0</td>\n",
+       "      <td>12106.0</td>\n",
+       "      <td>11325.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>10858.0</td>\n",
+       "      <td>10673.0</td>\n",
+       "      <td>10698.0</td>\n",
+       "      <td>10535.0</td>\n",
+       "      <td>10754.0</td>\n",
+       "      <td>11302.0</td>\n",
+       "      <td>10703.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>10629.0</td>\n",
+       "      <td>10611.0</td>\n",
+       "      <td>10930.0</td>\n",
+       "      <td>10514.0</td>\n",
+       "      <td>10807.0</td>\n",
+       "      <td>10694.0</td>\n",
+       "      <td>10698.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>10525.0</td>\n",
+       "      <td>10526.0</td>\n",
+       "      <td>10624.0</td>\n",
+       "      <td>10529.0</td>\n",
+       "      <td>10824.0</td>\n",
+       "      <td>10282.0</td>\n",
+       "      <td>10605.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>10545.0</td>\n",
+       "      <td>10412.0</td>\n",
+       "      <td>10565.0</td>\n",
+       "      <td>10565.0</td>\n",
+       "      <td>10328.0</td>\n",
+       "      <td>10412.0</td>\n",
+       "      <td>10483.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>10278.0</td>\n",
+       "      <td>10647.0</td>\n",
+       "      <td>10643.0</td>\n",
+       "      <td>10467.0</td>\n",
+       "      <td>10512.0</td>\n",
+       "      <td>9941.0</td>\n",
+       "      <td>10509.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>10028.0</td>\n",
+       "      <td>10672.0</td>\n",
+       "      <td>10426.0</td>\n",
+       "      <td>10353.0</td>\n",
+       "      <td>10324.0</td>\n",
+       "      <td>10096.0</td>\n",
+       "      <td>10360.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>10021.0</td>\n",
+       "      <td>10612.0</td>\n",
+       "      <td>10147.0</td>\n",
+       "      <td>10356.0</td>\n",
+       "      <td>10422.0</td>\n",
+       "      <td>10159.0</td>\n",
+       "      <td>10311.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>9893.0</td>\n",
+       "      <td>10433.0</td>\n",
+       "      <td>10239.0</td>\n",
+       "      <td>10408.0</td>\n",
+       "      <td>10564.0</td>\n",
+       "      <td>10262.0</td>\n",
+       "      <td>10307.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>10153.0</td>\n",
+       "      <td>10439.0</td>\n",
+       "      <td>10278.0</td>\n",
+       "      <td>10542.0</td>\n",
+       "      <td>10406.0</td>\n",
+       "      <td>10236.0</td>\n",
+       "      <td>10363.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>10352.0</td>\n",
+       "      <td>10312.0</td>\n",
+       "      <td>10569.0</td>\n",
+       "      <td>10091.0</td>\n",
+       "      <td>10405.0</td>\n",
+       "      <td>10592.0</td>\n",
+       "      <td>10345.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>10354.0</td>\n",
+       "      <td>10637.0</td>\n",
+       "      <td>10698.0</td>\n",
+       "      <td>10199.0</td>\n",
+       "      <td>10279.0</td>\n",
+       "      <td>10990.0</td>\n",
+       "      <td>10433.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>10239.0</td>\n",
+       "      <td>9226.0</td>\n",
+       "      <td>9372.0</td>\n",
+       "      <td>9046.0</td>\n",
+       "      <td>9478.0</td>\n",
+       "      <td>10364.0</td>\n",
+       "      <td>9472.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>9092.0</td>\n",
+       "      <td>10681.0</td>\n",
+       "      <td>10781.0</td>\n",
+       "      <td>10680.0</td>\n",
+       "      <td>10918.0</td>\n",
+       "      <td>9023.0</td>\n",
+       "      <td>10430.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>10573.0</td>\n",
+       "      <td>10401.0</td>\n",
+       "      <td>10692.0</td>\n",
+       "      <td>10496.0</td>\n",
+       "      <td>10892.0</td>\n",
+       "      <td>11176.0</td>\n",
+       "      <td>10610.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>10381.0</td>\n",
+       "      <td>10183.0</td>\n",
+       "      <td>10875.0</td>\n",
+       "      <td>10498.0</td>\n",
+       "      <td>10792.0</td>\n",
+       "      <td>10797.0</td>\n",
+       "      <td>10545.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>10826.0</td>\n",
+       "      <td>10278.0</td>\n",
+       "      <td>11027.0</td>\n",
+       "      <td>10463.0</td>\n",
+       "      <td>10954.0</td>\n",
+       "      <td>10890.0</td>\n",
+       "      <td>10709.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>10700.0</td>\n",
+       "      <td>10671.0</td>\n",
+       "      <td>11101.0</td>\n",
+       "      <td>10869.0</td>\n",
+       "      <td>11113.0</td>\n",
+       "      <td>11468.0</td>\n",
+       "      <td>10890.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>11108.0</td>\n",
+       "      <td>11016.0</td>\n",
+       "      <td>11357.0</td>\n",
+       "      <td>11048.0</td>\n",
+       "      <td>11403.0</td>\n",
+       "      <td>11373.0</td>\n",
+       "      <td>11186.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>10799.0</td>\n",
+       "      <td>11134.0</td>\n",
+       "      <td>11389.0</td>\n",
+       "      <td>11177.0</td>\n",
+       "      <td>11625.0</td>\n",
+       "      <td>11943.0</td>\n",
+       "      <td>11224.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>10966.0</td>\n",
+       "      <td>11048.0</td>\n",
+       "      <td>11152.0</td>\n",
+       "      <td>10885.0</td>\n",
+       "      <td>11415.0</td>\n",
+       "      <td>12317.0</td>\n",
+       "      <td>11093.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>11026.0</td>\n",
+       "      <td>11463.0</td>\n",
+       "      <td>11366.0</td>\n",
+       "      <td>10866.0</td>\n",
+       "      <td>11567.0</td>\n",
+       "      <td>12517.0</td>\n",
+       "      <td>11257.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>11312.0</td>\n",
+       "      <td>11803.0</td>\n",
+       "      <td>11767.0</td>\n",
+       "      <td>11588.0</td>\n",
+       "      <td>12177.0</td>\n",
+       "      <td>13448.0</td>\n",
+       "      <td>11729.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>11338.0</td>\n",
+       "      <td>12209.0</td>\n",
+       "      <td>11773.0</td>\n",
+       "      <td>11552.0</td>\n",
+       "      <td>12146.0</td>\n",
+       "      <td>13798.0</td>\n",
+       "      <td>11803.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>11178.0</td>\n",
+       "      <td>12064.0</td>\n",
+       "      <td>12102.0</td>\n",
+       "      <td>11289.0</td>\n",
+       "      <td>12472.0</td>\n",
+       "      <td>14291.0</td>\n",
+       "      <td>11821.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>11216.0</td>\n",
+       "      <td>11901.0</td>\n",
+       "      <td>12046.0</td>\n",
+       "      <td>11392.0</td>\n",
+       "      <td>12455.0</td>\n",
+       "      <td>14132.0</td>\n",
+       "      <td>11802.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>11748.0</td>\n",
+       "      <td>12733.0</td>\n",
+       "      <td>12342.0</td>\n",
+       "      <td>11687.0</td>\n",
+       "      <td>12275.0</td>\n",
+       "      <td>13986.0</td>\n",
+       "      <td>12157.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>11713.0</td>\n",
+       "      <td>12076.0</td>\n",
+       "      <td>12924.0</td>\n",
+       "      <td>12078.0</td>\n",
+       "      <td>12853.0</td>\n",
+       "      <td>13942.0</td>\n",
+       "      <td>12328.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>12136.0</td>\n",
+       "      <td>13137.0</td>\n",
+       "      <td>14308.0</td>\n",
+       "      <td>12649.0</td>\n",
+       "      <td>13566.0</td>\n",
+       "      <td>14658.0</td>\n",
+       "      <td>13159.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>9806.0</td>\n",
+       "      <td>9335.0</td>\n",
+       "      <td>9904.0</td>\n",
+       "      <td>8384.0</td>\n",
+       "      <td>8727.0</td>\n",
+       "      <td>13035.0</td>\n",
+       "      <td>9231.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>8774.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11580.0</td>\n",
+       "      <td>8774.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "year     2015     2016     2017     2018     2019     2020  previous_mean\n",
+       "week                                                                     \n",
+       "1     13751.0  14863.0  13612.0  14701.0  12424.0  13768.0        13870.2\n",
+       "2     18318.0  13154.0  15528.0  17430.0  14487.0  16020.0        15783.4\n",
+       "3     16738.0  13060.0  15231.0  16355.0  13545.0  14723.0        14985.8\n",
+       "4     15712.0  12859.0  14461.0  15971.0  13283.0  13429.0        14457.2\n",
+       "5     14560.0  12571.0  14188.0  15087.0  12799.0  13123.0        13841.0\n",
+       "6     13730.0  12697.0  13805.0  14111.0  13222.0  12534.0        13513.0\n",
+       "7     13510.0  12016.0  13212.0  13925.0  13347.0  12412.0        13202.0\n",
+       "8     13071.0  12718.0  13330.0  13753.0  12877.0  12300.0        13149.8\n",
+       "9     13181.0  12733.0  12819.0  12190.0  12479.0  12334.0        12680.4\n",
+       "10    13007.0  12493.0  12580.0  14859.0  12396.0  12415.0        13067.0\n",
+       "11    12475.0  12489.0  12089.0  14367.0  12018.0  12499.0        12687.6\n",
+       "12    12027.0  10983.0  11833.0  13397.0  11797.0  12112.0        12007.4\n",
+       "13    11987.0  11738.0  11453.0  11310.0  11260.0  12507.0        11549.6\n",
+       "14    10325.0  13060.0  11305.0  12272.0  11445.0  18565.0        11681.4\n",
+       "15    11575.0  12757.0   9761.0  13843.0  11661.0  20929.0        11919.4\n",
+       "16    13061.0  12310.0  11000.0  12639.0  10243.0  24691.0        11850.6\n",
+       "17    12023.0  11795.0  12356.0  11596.0  11452.0  24303.0        11844.4\n",
+       "18    11586.0  10401.0  10372.0  11538.0  12695.0  20059.0        11318.4\n",
+       "19    10138.0  12002.0  12114.0   9821.0  10361.0  14428.0        10887.2\n",
+       "20    11692.0  11222.0  11718.0  11386.0  11717.0  16390.0        11547.0\n",
+       "21    11334.0  11013.0  11431.0  10974.0  11653.0  13839.0        11281.0\n",
+       "22     9514.0   9192.0   9603.0   9397.0   9534.0  11265.0         9448.0\n",
+       "23    11603.0  11171.0  11134.0  11259.0  11461.0  12106.0        11325.6\n",
+       "24    10858.0  10673.0  10698.0  10535.0  10754.0  11302.0        10703.6\n",
+       "25    10629.0  10611.0  10930.0  10514.0  10807.0  10694.0        10698.2\n",
+       "26    10525.0  10526.0  10624.0  10529.0  10824.0  10282.0        10605.6\n",
+       "27    10545.0  10412.0  10565.0  10565.0  10328.0  10412.0        10483.0\n",
+       "28    10278.0  10647.0  10643.0  10467.0  10512.0   9941.0        10509.4\n",
+       "29    10028.0  10672.0  10426.0  10353.0  10324.0  10096.0        10360.6\n",
+       "30    10021.0  10612.0  10147.0  10356.0  10422.0  10159.0        10311.6\n",
+       "31     9893.0  10433.0  10239.0  10408.0  10564.0  10262.0        10307.4\n",
+       "32    10153.0  10439.0  10278.0  10542.0  10406.0  10236.0        10363.6\n",
+       "33    10352.0  10312.0  10569.0  10091.0  10405.0  10592.0        10345.8\n",
+       "34    10354.0  10637.0  10698.0  10199.0  10279.0  10990.0        10433.4\n",
+       "35    10239.0   9226.0   9372.0   9046.0   9478.0  10364.0         9472.2\n",
+       "36     9092.0  10681.0  10781.0  10680.0  10918.0   9023.0        10430.4\n",
+       "37    10573.0  10401.0  10692.0  10496.0  10892.0  11176.0        10610.8\n",
+       "38    10381.0  10183.0  10875.0  10498.0  10792.0  10797.0        10545.8\n",
+       "39    10826.0  10278.0  11027.0  10463.0  10954.0  10890.0        10709.6\n",
+       "40    10700.0  10671.0  11101.0  10869.0  11113.0  11468.0        10890.8\n",
+       "41    11108.0  11016.0  11357.0  11048.0  11403.0  11373.0        11186.4\n",
+       "42    10799.0  11134.0  11389.0  11177.0  11625.0  11943.0        11224.8\n",
+       "43    10966.0  11048.0  11152.0  10885.0  11415.0  12317.0        11093.2\n",
+       "44    11026.0  11463.0  11366.0  10866.0  11567.0  12517.0        11257.6\n",
+       "45    11312.0  11803.0  11767.0  11588.0  12177.0  13448.0        11729.4\n",
+       "46    11338.0  12209.0  11773.0  11552.0  12146.0  13798.0        11803.6\n",
+       "47    11178.0  12064.0  12102.0  11289.0  12472.0  14291.0        11821.0\n",
+       "48    11216.0  11901.0  12046.0  11392.0  12455.0  14132.0        11802.0\n",
+       "49    11748.0  12733.0  12342.0  11687.0  12275.0  13986.0        12157.0\n",
+       "50    11713.0  12076.0  12924.0  12078.0  12853.0  13942.0        12328.8\n",
+       "51    12136.0  13137.0  14308.0  12649.0  13566.0  14658.0        13159.2\n",
+       "52     9806.0   9335.0   9904.0   8384.0   8727.0  13035.0         9231.2\n",
+       "53     8774.0      NaN      NaN      NaN      NaN  11580.0         8774.0"
+      ]
+     },
+     "execution_count": 578,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_headlines_e['previous_mean'] = deaths_headlines_e[[int(y) for y in '2019 2018 2017 2016 2015'.split()]].apply(np.mean, axis=1)\n",
+    "deaths_headlines_w['previous_mean'] = deaths_headlines_w[[int(y) for y in '2019 2018 2017 2016 2015'.split()]].apply(np.mean, axis=1)\n",
+    "deaths_headlines_s['previous_mean'] = deaths_headlines_s[[int(y) for y in '2019 2018 2017 2016 2015'.split()]].apply(np.mean, axis=1)\n",
+    "deaths_headlines_i['previous_mean'] = deaths_headlines_i[[int(y) for y in '2019 2018 2017 2016 2015'.split()]].apply(np.mean, axis=1)\n",
+    "deaths_headlines['previous_mean'] = deaths_headlines[[int(y) for y in '2019 2018 2017 2016 2015'.split()]].apply(np.mean, axis=1)\n",
+    "deaths_headlines"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 580,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='week'>"
+      ]
+     },
+     "execution_count": 580,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1008x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "deaths_headlines[[2020, 2019, 2018, 2017, 2016, 2015]].plot(figsize=(14, 8))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 581,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='week'>"
+      ]
+     },
+     "execution_count": 581,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "deaths_headlines[[2020, 'previous_mean']].plot(figsize=(10, 8))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 582,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='week'>"
+      ]
+     },
+     "execution_count": 582,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "deaths_headlines_i.plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 591,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "83207.6000000001"
+      ]
+     },
+     "execution_count": 591,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_headlines[2020].sum() - deaths_headlines.previous_mean.sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 583,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
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996twLGm/bIXV9CqzGAAxKpUqg8fjpVoslvCQkBBRcHAw1Gq1f1JSkl2r1QoCAwOJRqNBYGAg5HI5WKz1vbiYx+NBKpVCKpXO9zAbgPjiO6emptDf3x/e29uL3t5e9PT02Ovq6sxtbW22tra2yeDgYGq320c5HE7D+Ph46cjISCWABgDNlFKjm3dpXUAICQawA8DTAL7r5ekwMKwbGGHFwPCZ6zkFsI9S+icAqukUESilvdPGnZc0hBAWHOIpISAgIMXPzy/DarXGsFgs/5SUFJKYmMhOS0vzjY+P58fExCA8PBw8Hg8AUFpaiujoaIjFczTIZQmPx0NISAhCQkKcd7Gam5uFHA4HWq3WFwAMBoOqsbExpqGh4Ybq6urJ8vLyifr6egQGBlpZLNYAIaRGr9eXTE5O1sDRuLnnMqv9ehHAowD8vDwPBoZ1BSOsGBjmcT339oTWynTtSwwhJEOj0VxNKc0OCQmRxcXFkU2bNvkkJiaKYmJiEBUVBT+/pc+LIpEIk5OTV4ywmg+j0QiVSjXzf19fX2zYsAEbNmwAHMX3IgCglGJoaEjT0NCQWl9fv6uysnL89OnTpvb2dhocHNxpsVhODAwMHANwDkDXpSi2CCE3ABiglJYSQgq8PB0GhnUFU2PFwDALQsgeOBrc3g+gYDpapQFwlFIa69XJLcC0iIqbLaI4HI4kISGBbN261S87O1uQnp6OgICAVY/R3t4Om82GiIiIZT2fUoqpqSlYLBZYrdY5N5vNNu/9VqsVlNKZm3NblFKMj4/Dz88PhJCZxtTOv1ksFjgczgU3Nps9577ZNx6PBw6Hs+wm12fOnEFiYiJ8fHxW9R5SStHd3Y3S0lKcOnXKcOLEicm2tjbKYrG6LBbLyWmxVQqgc72LLULI/wL4MgArAAEc6dR/UUrv8urEGAAApaWlSg6H8xKAJFxZRuB2AOetVut9GRkZA96aBCOsGK5opp3OWZTS8em/jwB4EsDVAHSzitellNJHvTlXJ4QQCYAtarX6ZkJILpfLlSQmJmLr1q3+2dnZ/A0bNsDf39+lYw4MDGBwcBDx8fEwm80wm80wmUwzt9n/dx5TeDzejHhZTOQ4H5teDQgWizVHOAHAsWPHsHXrVgC4QHxRSmG325cUbBeLOqfwAwA2mw2BQAA+nw+BQHDBjc/ng8fj4fjx49i8ebPLa8p6enouEFutra2UENJtMpn+q9PpDgEoppSaXTqoC5mOWD3CFK+vHyoqKg6q1ep4hUIxxmKxrpiTvN1uJ4ODg/59fX01qampN3lrHkwqkOFKZyHX87MA3iKE/D8AHQB2emuC00Jqs0aj+QKltCAxMdHnuuuuE2zfvl2cnZ3t8vScxWKBwWDAxMQEDAbDzCo6o9GIoaGhGfHh/Nff3/8CEeLOYvbZguti+Hz+qrdrtVrniMXx8fGZ+6ampjA+Po5Tp07Bx8cHvr6+8PX1hY+PD3x8fMBms1c9dmBgIAIDA3HjjTc6fbzQ09OjKiws3HDo0KH7jh49agsKCuo3m83vTwut0+tZaDGsC5IUCsXwlSSqAIDFYlGFQjHa19eX5M15MBErBoZ1xsVCSiqV+qanp0vuvvtuTm5u7qpTUbOx2WyYmJi4QDxNTEzAarWCw+HMiAangODz+SguLsaWLVvWvoOrZLV2C67AarWiqKgImzZtmvOeTUxMwG63g8/nzxFdIpFo2anGxejv78d///tf+s9//nOqrKxsbGpqyim03gdwhhFaDLOpqKhoS01NHVr6mZcnFRUV8tTU1DBvjc9ErBgYvAwhRABgW2Bg4BcppQUJCQl+1113neC6667zcwqpwsJCZGRkQCAQrHj7U1NTGB0dxcjICEZGRjAxMQEWizUTbfH19YVCoYCPjw+4XO6C27Hbr1zfTKPRCKFQCC6Xi4CAgDn1apRSmM3mGdE1ODiI1tZWGI1GEEIgFotnXicWi1cc4VKpVCgoKCCZmZn82NhYRX9/v+Lo0aOJhw4duv/48eO2oKCgvmmh9S6AEsbklMHbNDU1ce+8887wwcFBLovFwj333DP405/+dKC/v599yy23RHR3d/ODgoLM//73v1sUCoWtr6+PffPNN0dWVVX5fPGLX9S99tprHc5tZWVlxQ4MDHAFAoEdAD7++OOGoKAgq/f2bnEYYcXA4AUIIUo+n3+TXC6/JzQ0NHbHjh28m2++2T8vLw++vr5zni+TyaDT6RAUFLTodqempjAyMjIjpAwGA7hcLvz9/REQEIC4uDj4+vquKorCYrFgs9nWlPa6VHEKq4UghMykQ2Uy2QWP2Ww2jI2NYWRkBG1tbRgbGwOAGbHl7+8Pf3//Jd/XoaGhmc9fpVLhtttuI7fddpsUAPr7+xWffvpp0ltvvXV/UVGRNTg4uLC7u/sVAB9TSifXsOsMDKuCy+Xi+eef78rPz58cHh5mbdiwIeH6668f+/Of/ywvKCgYf+aZZxp/9KMfqR9//HH1H/7wh26RSESffPLJnoqKCuH58+fn/Nhee+21li1btlwS32VGWDEweIBpB/P4gICALwmFwl1JSUnS22+/3e/WW28VxMbGLil05HI5enp6LhBWNpsNw8PD0Ov1GB0dnRFRzpP1WkTUfAiFQhiNxnmF3+XO5OQkRCLRql7LZrMhkUggkUhm7psttjo6OjA6OgoA8PPzQ0BAAGQyGcRi8QWf3fDwMJKS5i8dUalU2LVrF9m1a5fMZrOhqKjo1rfeeuua9957zxwcHNys0+leMZlM/6aU9q1qJxgYVohWq7VotVoLAEgkEntkZKSxo6OD9+GHHwYcO3asHgB2796t27p1ayyAbrFYbN++fbuhvr5+9cWS6wRGWDEwuAlCCBdAvlqt/rJKpdqenJzMvfPOO6U7duxgKxSKFW1LIpHg/PnzGBoawtDQEHQ6HSwWy4yjuEajcamImg+nl9WVKqwujkSthYXE1vj4OEZGRtDU1ISxsTGIRCLI5XKIxeKZFZTL2XZ+fj7y8/PFv/71r9HY2Kh49913N/z9739/KjAwcMRsNr+l1+vfAlC13m0dGC4P6uvreTU1NaKtW7cadDodxym4tFqtRa/XL0uH3HfffWEsFgs33njj8P/93//1rueOD4ywYmBwIYQQPovF2qHRaB4IDAxM+9znPsfZtWuXpKCgYMX1Uc6IlFNIGQwGdHZ2QqVSITw8fE2r4FaDM2J1JbJUKtAVsNnsmTqssLAwUEoxMTEBnU6Huro6TExM4MyZM5DJZDNiazlCOjo6Go8++ij/0UcfVej1esWhQ4d++MYbb3ytvLzcGhgYeKS3t3cfgCJGZF2eDL/7bohlYGB14dYF4CqVk5JbbulcznNHR0dZt956a+Szzz7bKZVKV1X7t3///pbw8HDL8PAw64Ybboj8/e9/L/vmN7+pW822PAEjrBjWDdNGlyUAuimlNxBCUgH8EY4l6G0A7qSUjnlxivMy3Spmc2Bg4DcDAwO3fvGLX+Tfe++94rS0tBVFkOx2O/R6PXQ6HYaGhmCxWCCRSKBQKBAeHo6Wlhb4+/sjMDDQfTuzCCKRCMPDV2bv4bWkAlcLIWRmheHo6ChiY2MhEokwNDQ0E9Hy8fGBTCaDQqGYMU9dDKlUirvuuot11113KaampnD06NG79+3bt6OwsNCsUCj2Dw0N/YlSekl0Hphunj4OwAbASinN9O6MGC7GbDaTHTt2RO7cuVN/zz33jACATCaztre3c7VaraW9vZ0rlUqXLEIPDw+fSSnedttt+jNnzvgAYIQVA8MyeAhALT5rivsSHMaDxwghXwXwfQA/9dbkLoYQkqRUKh9UqVS3bNu2jb97927pli1bVuTjZLFY0N/fj76+PoyPj0MqlUIul0Or1c6JcMnlcvT19XlVWHV3d3tlbG9js9nA4XjvcDk8PIzExESw2Wz4+vpeENEaGhpCfX09DAYDZDIZ1Gr1sppj83g8XHvttbj22mtlk5OTOHjw4EO/+93v7tJoNGNGo/HPo6Ojr14CNVnbKKVXrK3AclhuZMnV2O127Nq1SxsTE2Pas2dPv/P+7du3j+zbt0/2zDPP9O3bt0923XXXjSy2HYvFgqGhIY5Go7GazWZy6NAh/6uuumrc7TuwBhhhxbAuIIQEA9gB4GkA352+OxbA8em/jwA4DC8LK0JIcEBAwFcEAsFXrrrqKr+vf/3r0h07drBWkuabmJhAX18f+vr6YLPZoFKpZhocLxZxkEgkqKmpccVurIorNRVot9vdWru2FFNTU2Cz2XPqq2ZHtMLCwmC32zE0NIT+/n5UV1fD19cXarUaKpVqppn2QohEIuzatYu1a9cuxdDQkOLNN9986k9/+tP3goKCuvR6/a9NJtM/KaXr+mTGsL44cuSI74EDB2TR0dHGuLi4BADYu3dv9969e3tvueWWSK1WKw8MDJw6cOBAs/M1QUFByQaDgW2xWMjhw4cDDh061BAdHT11zTXXRFssFmK328nmzZvHvvvd7w56b8+WhhFWDOuFFwE8CmB2R+DzAG4C8G84nM9DPD8tgBDiLxQKb5NKpd9OTU1VPvjgg5IvfelLnNmFx4tBKcXw8DD6+vowMDAAgUAAtVqN9PT0FdXtcDgcsFgsTE1NLXmidAdcLhdW67q1jnEbnqivWgydTreswnkWiwWlUgmlUjnTW7Gvrw+nT58GIQRqtRpqtXrJxQdyuRzf+ta3uN/61rcUzc3NildfffV3r7322s/DwsLOt7e3/wLAR5RSi4t2by1QAB8RQiiAfZTSP3l7QgyfsX37dgOltHS+x4qKihrmu7+7u7tqvvurq6trXTk3d8MIKwavQwi5AcAApbR0uu+Yk68C+DUh5HEABwFMeXBOBMCmwMDAH4aFheXceeedfllZWfybblpe+ym73Y6BgQH09vZieHgYEokEarUaMTExa0opOf2sNBrNqrexFgghsNvtbm1bs97wtrAaGhqCSqVa0WucpqRisRgxMTEwmUwzkSyj0QiFQgGNRgOJRLJoNC4yMhJPPvmk6IknnhD9+c9/LigrK9tw8OBBs1Kp3D84OPhLSmnrWvdvDeRRSnsIIUoARwghdZTS40u+ioHBzTDCimE9kAfgJkLI9QAEAMSEkDcopXcBuBYACCExcKQK3QohROzn53evSqX6TlZWlviRRx6Rbd68GQBw/PjxRaNFlFLo9Xp0dXVBr9dDoVBAq9VipUXsiyGXyzEwMOA1YSUQCGAymTxeyO1NvFG4Phu9Xo/4+Pg1bUMgEECr1UKr1cJms804w1dWVkKtViM4OHjRSNbg4CDy8vLwwAMP+P/617/Gv/71r6///Oc/3xUUFNTW19f3tN1uf59S6tFwJqW0Z/rfAULIuwCy8FnpAAOD12CEFYPXoZT+EMAPAWA6YvUIpfQuQohy+qDJAvATOFYIugVCSKparf5xaGhowYMPPuh73333CeVy+QXPCQ4ORldXFyIiIi64f3x8HF1dXejr64O/vz+Cg4ORkpLilrociUSCujrvLdpy1lldScLKaDTCz89v6Se6AYvFAhaL5dLCeTabPZMWtFqt6O3tRVVVFaxWK4KCghAUFDTHyqOjowOxsbEAHM2ub7/9dvbtt9+uqKurU/zqV7969cCBA0aFQvH60NDQLymlvS6b7AIQQnwAsCil49N/XwvgSXePy8CwHBhhxbCeuZ0Q8o3pv/8F4K+u3DghhMvlcm+Vy+U/KSgoUP/4xz+WX3XVVQumuYKDg3H69GlERETAZDKhu7sb3d3d4PP5CA4ORkxMjNvbvTh7+VkslkX7+rkLp0moK80y1zuTk5MrTsW5Cp1OB6lU6rbtczgchISEICQkZOY7febMGXC5XAQHB0OtVsNms8FkMsHf33/O6+Pi4vCHP/zB/4UXXvD/xz/+8fBzzz13b1BQUHlPT88euNcbSwXg3emLFw6Av1NKP3TTWAwMK4IRVgzrCkrpUQBHp//+FYBfuXoMQohKJpN9R6VS3Xvbbbf5PPzww35hYWFLvo7FYsFut+P48eNgsVgICgpCdna2x406ZTIZ9Hq9V072IpEI4+NX1uIwb6YCdTodLo6cuguBQIDIyEhERkbCYDCgq6sLJ0+eBOCIlC5WWycUCvGVr3yFc++99ypOnz79uWeeeSb97Nmzwz4+Ps9NTk6+QSl16XJSSmkLgFRXbpOBwVUwworhioEQEqNWq5+Njo7e/P3vfz/gzjvv5Cx1wqSUzjTPHR0dnTFhTE9P99Cs5yKTyVZV0OwKhEIhBgYGPD6uN/FWdBBwCKuYmBiPj+vr64u4uDjExsbik08+AaUUx44dg1qthlarXVBoEkKwadMmHDx4UNbX1yf77W9/+8u//OUvP1MoFK8MDQ39H6VU7+FdYWDwOFfO0h6GKxZCSHpgYODH6enphX/961+/UF9fL7///vsXFVUWiwVtbW04ceIEmpubERISgq1bt2LDhg0YHR2F3b6qzgwuwRmx8gbOVOCVgjOT5Q0fK4vF4WjgLVEHAKOjoxCLxUhLS8OWLVvg6+uLsrIyFBcXo6+vD4tl+tRqNX72s5/5tLa2Kp988snvhIaG1qvV6j8RQrzjcMvgUZqamrjZ2dkxERERiVFRUYlPPfWUEgD6+/vZubm50VqtNik3Nzd6cHCQDQB9fX3s7OzsGJFItOHuu+8Onb0tk8lEbr/9dm1YWFhSeHh44iuvvBLghV1aNoywYrgsIQ62ajSas1u3bv3on//851WlpaXy6667jix2khwbG0NFRQUKCwthsViQnZ2NzMxMyOVyEEJmvIL6+rxnSM3lckEpnTnxehIej4epKY+5Xngdk8m04h6PrkKv13u9lq2jowOhoY5zHJvNRkhICPLy8pCQkIDBwUEcPXoU9fX1MJlMC26Dz+fjwQcf5LW0tMhffPHFr0ZHR1doNJq3CCFRntoPBs/D5XLx/PPPd7W0tFSfPXu29uWXX1aWlpYKnnjiCU1BQcF4e3v7+YKCgvHHH39cDQAikYg++eSTPXv27Om6eFs//OEPNQqFwtLW1na+qampevv27QbP79HyYVKBDJcVhBAWh8O5Qa1WP5udna166qmnpMnJyYu+xm63o6+vD62treBwOAgPD190VV9ISAhqamq81loGcPR8Gx4ehlKp9Oi4zveEUupVN3JP4U0Pq6GhIa8KK5vNhqGhISQlJc15TCwWIzk5GVardabg3cfHB+Hh4QsW27PZbOzatYt92223yQ8dOvTFH//4x9sCAwPP9fb2PkoprXD3/jB4Fq1Wa9FqtTM9/iIjI40dHR28Dz/8MODYsWP1ALB7927d1q1bYwF0i8Vi+/bt2w319fVzilbffPNNeUNDw3nA8T3SaDTr2qmYiVgxXBYQQjhCofBulUrVdOedd75aWFgYf+DAgUVFldlsRkNDA44dOwa9Xo+0tDRkZ2dDqVQuKhrEYjEsFsuiV+nuxlln5Q34fD7MZrNXxvY03ixc93bEqq+vDyqValEzWA6HA61Wi82bNyMsLAwtLS04ceIEOjo6YLPZ5n0NIQQ7duwg5eXl8rfeeuva/Pz8jwMDA4sJIfnu2hcG71JfX8+rqakRbd261aDT6ThOwaXVai16vX7RAM/Q0BAbAL773e8GJiQkxH/+85+P6OzsXNdBoXU9OQaGpSCECMRi8W6VSvXorl27/H7wgx/4qdXqRV8zMTGBpqYmjIyMzJwUVuoTFBISgs7OTkRHR69l+qtGJpOhqanJK2M7vay8lSLzJN6KWFmtVtjtdq/WV3V2diIxMXFZzyWEQCaTQSaTwWg0or29HcePH0dQUBDCw8MX3I/8/HycOHFCVlFRIfvxj3/8b41G0zswMPCo3W7/wI1WDVcU5+pfDxmb7HHp1YFYFDiZHvvlZTV3Hh0dZd16662Rzz77bKdUKl1xcarFYiH9/f3c/Px8w0svvdS1Z88e1be+9a2QAwcOeNP1f1GYiBXDJQkhhO3n53e/SqVq+c53vvNMXV1d4IsvvrioqBobG0NpaSnKysqgUqmwZcsWhIWFrcp8MSgoCN3d3YsW77oTHo8Hu93uld59V1IBu7ciVnq93q3+VUthNBphtVpXZYwqFAoRFxeHLVu2gMvl4uTJk6ipqVk0ypmamor//Oc/0hMnTiR+6Utf+ptarT5PCNm8ln1g8D5ms5ns2LEjcufOnfp77rlnBABkMpm1vb2dCwDt7e1cqVS66EFMpVJZBQKB/ctf/vIIANx111368+fPr2uHYiZixXBJQQghPB7vZpVK9cvbbrtN9sQTT/gtdQLS6/VobGyE3W5HdHQ0ZDLZmuuDuFwu/Pz8MDw87LUToLPOSqFQeHRcZ8TqSsBbEStP+lfNR2dnJ0JC1tbznM1mIzw8HFqtFt3d3SguLoZEIkFUVNSCYjUqKgpvvvlmQF1dXcBDDz10QKPR1Pf19e2mlM7bnJdhaZYbWXI1drsdu3bt0sbExJj27NnT77x/+/btI/v27ZM988wzffv27ZNdd911I4tth8Vi4eqrrx59//33/W666abxQ4cOiaOjo9f1AYgRVgyXDISQfI1G89LGjRu1v/vd7wTBwcELPpdSisHBQTQ2NoLH4yE2NhYBAQEunY8zHegtYeWss/K0sBKJRBgeHvbomN7CW6sCdTodIiMjPT4u4Pjt9PT0IC8vzyXbY7FYCAkJQXBwMPr6+lBaWgqRSITo6GiIxeJ5XxMXF4fDhw9Li4uLcx588MEzgYGBH/f29n6TUtrmkkkxuJ0jR474HjhwQBYdHW2Mi4tLAIC9e/d27927t/eWW26J1Gq18sDAwKkDBw40O18TFBSUbDAY2BaLhRw+fDjg0KFDDRkZGaYXXnih64477gh/5JFH2DKZzPraa6+1eW3HlgEjrBjmQAhhAygB0E0pvYEQkgZHnz4BACuAr1NKz3hwPslqtfqPn/vc5+J+9atfSYeGhhYUSc6TQnNzM/z8/JCamrpoc9m1oFAoUF1dDZvN5vZWNvMhk8nQ0tLi8XFFItEVEbHyloeVzWaDzWZbsNm3uxkeHoafn5/L67sIIdBoNFCr1RgaGsL58+fBZrMRHR294MWJRqPBG2+8Iejq6rr+oYceOqtWq//T39//KKV00KWTWyaEkAAALwFIAkABfJVSWuSNuax3tm/fbqCUls73WFFRUcN893d3d88bmYyJiZkqKSmpd+X83AlTY8UwHw8BqJ31/+cA7KWUpgF4fPr/bocQEqbRaN7LzMz89N///nfuRx99JI2Pj0dcXNycRsR2ux3t7e04duwYhoeHsXHjRmzYsMFtomp6flCr1ejtdXvP2Xnh8/mwWq0Lrr5yFwKB4IoQVt5yXNfr9ZBIJB4f18ls7yp3QAiBQqFAbm4uYmJi0NTUhMLCQgwOXqiVbDYbWlpaEB0dje3bt5Oamhr5Cy+88GWtVlutUCieI4R4ozP2rwB8SCmNg6OlTu0Sz2e4AmGEFcMFEEKCAeyA46rMCQXgjNn7A+hx8xwUarX6LzExMWf/+te/7jhz5owsKytr5nGFQoGpqSmMjo7ORKiOHz+OiYkJ5ObmIikpyWN1MaGhoejo6PDIWPMhkUg8npa7EvyrAO8VrnuzvspqtWJ4eNhj40skEmRlZSElJQXt7e0oKirCyMgIAKCtrQ1BQUEzkTsWi4U77riD3dDQoHj88ce/rdFoGiUSySOEEI+E9gghYgBbALwMAJTSKUrpiCfGZri0YIQVw8W8COBRALOXxX4HwM8JIZ0AfgHgh+4YmBDClUqlPwkNDa1+/vnnv1xbW7ugU3p8fDwqKipw8uRJDA4OYtOmTUhISPB4+sTHxweUUq+tkpPL5V7xs+JyuV5xfvckRqPRa8LKW/5Vvb290Gg0HhfPfn5+yMzMRHx8PGpra3HmzBm0tbUhIiJiznN5PB6+9a1v8RsaGlQPPfTQXpVK1czn82/2wDQjAAwC+CshpIwQ8hIhxMcD4zJcYjDCimEGQsgNAAbmyYs/COBhSmkIgIcxfcXmSths9jaVStXwzW9+8wf19fWKO++8k7OQMeHIyAjq6upgNBoRERGB1NRUr3oqOYvYvYFMJoNOp/P4uEKh8LK3XJicnPT4ikCbzQaLxQI+f475tEdwdxpwKQICApCTkwMulwu73Y7q6uoFjXh9fX2xZ88eUVlZWfD111//V7VaXUgImavEXAcHQDqAP1BKNwCYAPADN47HcInCCCuG2eQBuIkQ0gbgHwCuIoS8AeAeAP+afs7bALLmf/nKIYQEqdXqD7dt2/ZOcXFx2JNPPumzkEgyGAwoKSlBbW0t4uPjkZOTg7a2Nq95STkJDAxET0+PV+YhEAhgsVg8Xmd1JXhZeSMVODw87LX6qomJCQDwmtO8k6mpKYyMjGDbtm1QKBQoLi5GbW3tghFSjUaDd999V/LWW2/lRkVFnVEqlT8nhLhDEXcB6KKUnp7+/ztwCC0GhgtghBXDDJTSH1JKgymlYQB2AfiEUnoXHDVVW6efdhWAxrWORQjhymSyn2q12vK//OUvn/vvf/8rDQsLm/e5JpMJFRUVKCsrg1arRU5ODgICAiAWiyEUCucUvXoaDoeDgIAAr0SOAEedirMuxVNcCV5W3vCw8mZ9VWdnp1ejVU6ampoQGRkJDoeDwMBAbNmyBSKRCCdPnkRTU9OCFxFbtmxBTU2N7NFHH/2mSqVqdHV6kFLaB6CTEBI7fdfVAGpcOQbD5QEjrBiWw/0AnieEVAB4BsDX1rIxZ9rvG9/4xmN1dXXy66+/ft7vocViQW1tLYqLi6FQKJCfnz/Hsyk2NhZ1dXVej1p5s4jdG30Dr4SIlbeElTfqqyilM/VV3sRkMmFgYACzPepYLBa0Wi22bNkCSimOHz+O9vb2eX/zXC4XjzzyiKCsrCxox44d7kgPfgvA3wghlQDS4DgeMsxDU1MTNzs7OyYiIiIxKioq8amnnlICQH9/Pzs3Nzdaq9Um5ebmRg8ODrIBoK+vj52dnR0jEok23H333TMKf3h4mBUXF5fgvEkkktSvfvWra3OvdTOMsGKYF0rpUUrpDdN/n6SUZlBKUyml2Qt5kywFISRIo9EsmfajlKKzsxMnT56EUCjEli1bEBgYOG9BrY+PDwICArxmeeBEKpVibGzMKwXd3qizuhIiVpTSRRsQuxq73Y6pqSmv1AsODQ1BIpGsqr2TK2loaEBMTMy877vT8yovLw8GgwEnTpyAXq+fdzsajQb/+te/XJ4epJSWU0ozKaUplNIvUEqvDKfcVcDlcvH88893tbS0VJ89e7b25ZdfVpaWlgqeeOIJTUFBwXh7e/v5goKC8ccff1wNACKRiD755JM9e/bs6Zq9HYlEYq+rq6tx3gIDA6d27ty5rt93RlgxuJ3Zab+XX3550bTf2NgYTp06heHhYeTl5SEsLGzJk1tMTAwaGhq8GrUihMzUWnkaoVCIqakp2O0r7m+6pjEvZ2FltVo9bvo6MjLi8u4Ay8XbReuAo8ZrZGRkyagZj8dDYmIiNmzYgLq6OpSXly/Yh3DLli2ora2VPfbYY99wR3qQYWG0Wq0lPz9/EnCIo8jISGNHRwfvww8/DNi9e7cOAHbv3q374IMPJAAgFovt27dvNwgEggUPZFVVVXydTsfdvn27wTN7sToYYcXgVgghG5RKZe03v/nNHyyV9quqqkJlZSWSkpKQkpKybOsEgUAAhULhtZV5Try5OtDf39+jdVZsNtujQs7TeKNwfWhoyCtpQIvFgvHxca+akgJAfX094uLilm314Ofnh5ycHCiVSpw6dQqtra3zXlxxOBx873vfE5aXlwddf/31r6jV6v8SQpSunj/DwtTX1/NqampEW7duNeh0Oo5Wq7UADvGl1+uXHSZ99dVXpTfddJPek5Hk1cC0tGFwC4QQnkKheCY5Ofne/fv3y+Lj4+d9HqUUXV1dMwWrSUlJq/LQiY6ORmFhIYKCgrzSXgZwRHHYbDYMBoNbHd/nQy6XQ6fTebRvIYvF8lo7H3fjrfqqtLQ0j44JAN3d3QgKCvKq8evY2BiMRuOK+146I8VKpRINDQ04efIkEhMT5/0dqNVqvPvuuwHvvfdewYMPPljp6+v7sMFgeNNV+7BeeXf4dMiAZcSlVwlKbsDkLZLsZV1Fjo6Osm699dbIZ599tlMqla7pauzdd9+VvvLKK61r2YYnWN+yj+GShBCSplQqqx966KEHz507t6Comp32y8/PR2ho6KoP7jweD4GBgWhvb1/L1NeMt4rYmQJ21+LpiJXdbofJZPK4mAMcqwFDQrxbC1xXV7eiaNXFcDgcJCQkIC0tDfX19YumB2+88UZ2VVWVavv27b9XqVRHCCGe7WJ+BWE2m8mOHTsid+7cqb/nnntGAEAmk1nb29u5ANDe3s6VSqXW5WyrqKhIaLPZyObNm9f9QYeJWDG4jOko1dNJSUlf3b9/vzQhIWHe51ksFtTV1WF0dBTJycnw9/d3yfiRkZE4ceIEQkNDvVaEq1ar0dDQgPj4eI9GAEQiEUwmE+x2u8cKrp11Vn5+3mjZ5l6MRqNH03Leqq8aHx8Hl8v1qsHu8PAw7Ha7S95vPz8/bNq0Cb29vTh16hTCwsIQFhY257cokUjwz3/+M+DgwYPbHnzwwfO+vr7fuVyjV8uNLLkau92OXbt2aWNiYkx79uzpd96/ffv2kX379smeeeaZvn379smuu+66keVs7/XXX5fecsst869WWGcwESsGl+CMUn3729/+ellZ2byiypn2O3nyJPz9/ZGXl+cyUQU4rlpDQ0PR0tLism2uFDabDZlMhoGBAY+P7e/vj9HRUY+Nx0SsXIe3bBbWQ9G60/DXVTjTg5s3b4bRaMSJEycW7Kd50003sauqqpTbt2//vVqtPsxEr1zHkSNHfA8cOCA7efKkn9MqYf/+/f579+7t/fTTT8VarTbp008/Fe/du3dmSXdQUFDyT3/605B33nlHplKpUkpLS2cU/8GDB6V33333JSGsmIgVw5oghHDlcvnTiYmJX33rrbdkC0WpnCafPB4P+fn54HK5bplPWFgYjh8/jrCwMI/3DXQSGhqKxsZGqFQqj47rrLPyVBGySCRacLn7pY6na6x0Oh1SUlI8Nh7giCgMDAy4VNSslMHBQfB4PJdeYDlxpgfHx8dRUVEBqVSK2NjYOTWBUqkU//znPwP+/e9/X/31r3+9SiQSPTQ5Obnf5RO6wti+fbthIWueoqKihvnu7+7urlpoe11dXQs+tt5gIlYMq4YQkqpWqxtuv/3275SXl88rqpxRqqKiIoSFhWHDhg1uE1WAI2IUERGBpqYmt42xFP7+/picnMTU1JRHx/V0ndXl3C/QZrN5LJ1MKfVKw+eBgQHI5XKPenXNhlI6sxLQnfj5+SEvLw88Hg8nT55ccPXszTffzC4vL1fl5eW9plarjxBCvGOBz3DJwwgrhhVDCGErFIqfJSQkfHzkyJGwO++8kzufQaXJZMLZs2cxODiI/Px8j0VwQkJCMDAwsGDzVndDCEFwcDC6urqWfrILEYlEMBqNHvPzulxTgXa73aP1caOjo26J2CyFt9OA/f398PX19cgKWkIIoqKikJ6ejvPnz6O2tnbe1jgDAwP44x//yPvjH/+4TaPRnBeJRDe5fXIMlx2MsGJYEYQQtVKpLLr33nu/XVFRIUtKSkJqaipqampmIjSzo1RardbtUaqLYbFYiI6ORkPDvNFmj+ANYUUIgVgs9lidFYfD8XjzZ0/g6TSgN/yrzGYzTCaTVwQd8Fm0KjY2duknuxBn9IrL5c6JXul0OoyMjCAiIgJf+MIX2JWVlaqsrKxXVCrVnwgh3qkrYLgkYYQVw7Lh8Xif02g05a+//nrGz3/+cz9nqkQgECA2NhYVFRUwGo1eiVJdTGBgIEZGRrwWUeHz+RAIBB4tJgc+q7PyFISQy84o1BuF655uvNzV1XVBPz5P093dDZlM5hV7ifmiV2azGVVVVdiwYcNMtFIul+PTTz+VfPe7371LoVBUuLjnIMNlDCOsGJaEEMJRKpUvpqen/+PcuXOqa6+9ds73RqPRwGQy4cSJE16JUl0MIWSmQbO38IanlafrrAQCgddSru5icnLSYyd8SqlXXN69KazsdjuampoQHR3tlfGdzI5effLJJ1Cr1XM+B0IIHnvsMeF//vOfuNDQ0GJfX99dXpouwyUEI6wuEQghbEJIGSHkP9P/308IKZ++tRFCyt00brBCoSh98MEH7yssLJSq1eo5zzGbzTh79iyEQiE4HA7EYrE7prJilEoljEYjxsbGvDb+0NCQRyM6Pj4+mJycZOqs1oAnC8nHxsYgFos9WtM1MjICkUjktVWzHR0dUKvV4PP5Xhl/NoQQ+Pr6wt/fH4ODg6itrZ3395qVlYWKigpFfn7+71Uq1RuEELcbfxFCYmcd48sJIWOEkO+4e1yGtcMIq0uHhwDUOv9DKb2NUppGKU0D8E8A/3L1gCKR6MagoKDSt99+O3nv3r0+87UuGRwcxKlTpxAaGorMzEwkJyejrKzMqw2RnRBCEBcX57WoFYvFglKpRF9fn8fGJITAz88P4+PjHhnvchRWnowgeaO+yptF6zabDa2trYiMjPTK+BdjNptRW1uLjIwM5Ofng81mo7CwcN7vdEBAAD744APJj3/84/9RKpVVhBC3FohRSutnHeMzAEwCeNedY7qSpqYmbnZ2dkxERERiVFRU4lNPPaUEgP7+fnZubm60VqtNys3NjR4cHGQDQF9fHzs7OztGJBJtuPvuuy/4gu7bt08aExOTEBMTk7B58+bo3t7edW0VxQirSwBCSDCAHQBemucxAuBLAFzmGkwI4alUqj9lZWW9Wl5erty6deucy2m73Y7a2lo0NjYiJycHzkiWQqGAWCxGa+v6aOckk8lgt9sXNAh0N95ozCyXyz2WDnS6r19OeLJ43dP1VTabDTqdbsU9+VxFa2srQkJCvFom4IRSioqKCsTHx4PP54MQgpiYGCQmJuLMmTPo6emZ8xpCCL797W8LDh8+HBUeHn7S39//qx6a7tUAmiml3u3ZtQK4XC6ef/75rpaWluqzZ8/Wvvzyy8rS0lLBE088oSkoKBhvb28/X1BQMP7444+rAUAkEtEnn3yyZ8+ePRes+rFYLPjhD38YcuzYsYaGhoaaxMRE489//vN13USbEVaXBi8CeBTAfDmlzQD6KaWNrhiIEBKuVCrLH3744bs++eQTyXwHfaPRiKKiIrBYLOTk5MxphxEfH4/Ozk6PRU2WwptRK7FYjKmpKY/WIXmyzupyjFhZLBaPnPgppZiYmICPj4/bx3LS398PpVLpFe8qi8WCzs5OhIeHe3zs+ejs7ASXy8XF5Q1SqRS5ubno6upCZWXlvCtf09LSUFFRIb/qqqueV6lU/yKEuPtD3AUXXjx7Aq1Wa8nPz58EAIlEYo+MjDR2dHTwPvzww4Ddu3frAGD37t26Dz74QAIAYrHYvn37doNAILjgPGe32wmlFOPj4yy73Y6xsTFWYGCgZ00CVwgjrNY5hJAbAAws5GAL4Ha46Afn6+t7c0hIyOmDBw/G/+AHPxDOd/Dt7+9HcXExYmNjERsbO29tCJvNRmpqKsrLy9fFirGAgABwuVyPNyl24mnrBV9fX0xMTHgkHXu5Rayc75knap7Gx8fh5+fn0foqb6YBm5ubER4ePsf53BtMTk6ipaUFSUlJ8z7O4/GwceNG+Pr6orCwEAaDYc5z/Pz88K9//Svg6aef3jGdGoxxx1ynrR5uAvC2O7bvCerr63k1NTWirVu3GnQ6HUer1VoAh/jS6/WLpvX4fD594YUXOtLT0xNVKlVKQ0OD8Dvf+Y53DubLZF3nKRkAAHkAbiKEXA9AAEBMCHmDUnoXIYQD4FY48u+rhhBC5HL53uTk5G++//77EqlUOuc5ztTf+Pg4cnNzlyw8DQgIgFKpRGNjo8e9auYjLi4O5eXlyMvL8+iJDHAIq8LCQkRGRnpkbGdB7vj4uNsXEvB4vBU5zFNKYbVaF7zZbLaZf53Pd95MJhNqax1lhoSQmfeSw+GAw+GAzWbP/H3xjc1mL+u9N5lMHmtI7On6KqPRCKvV6pWm2WazGX19fdiyZYvHx74YSinKy8uRnJy8aGSSEIKIiAhIpVKUlJQgKipqzkpKQgjuu+8+XlZWVviNN954UiAQ3GMymT5w8ZQ/D+AcpbR/yWfOw7unh0MGRiwuLRpUBnAnb8mWLKvGYXR0lHXrrbdGPvvss51SqXTFV9pms5n86U9/Upw+fbomPj7efO+994b+6Ec/0jz33HO9S7/aOzDCap1DKf0hgB8CACGkAMAjlNK7ph++BkAdpXTV4RBCiFCpVL7zhS98If93v/udeL42HpOTkzh37hxUKhWys7OXLQ6io6Nx6tQpKJVKj/WvWwinw3N/f/+c0L+74XK58PX1xcjIiMfeB5lMBp1O53ZhRQgBpRRms3nGdNL5r/NmNpthtVpnnn+x4LlYBAkEArBYrBnx5Py+dXd3QyqVzkSVnILLKcampqbmFWnOmxMulwuBQDDnxufzPVq4rtPpPHrR4U2LhcbGRkRFRXmtfc5sWlpa4O/vv2xRGxAQgLy8PFRUVGBwcBDJyclz2h2lpKSgpKRE8fnPf/4NuVz+vE6n+1/qupCxy7ISnsZsNpMdO3ZE7ty5U3/PPfeMAIBMJrO2t7dztVqtpb29nSuVSq2LbaO4uFgIAImJiWYAuP322/XPPvusZw/iK4QRVpc2a8q7E0KClUrlkSeffDJ89+7d84agenp60NDQgJSUFMwXyVoMFouFtLQ0lJSUYPPmzV5PAcTGxuLMmTNQqVQej1o5Pa08JazkcjkaGhpcVs/iFE8TExMwGAwzN6PRiMnJSZw5cwYikWhGoAiFQkgkkpn/u6JmicvlrtlwllIKi8VygfCbmJiAXq+HyWTC6OgorFYrhoeH4ePjMyPInX+7qvaKUgqDweCx6BGlFN3d3cjLy/PIeLMxGo3Q6XRITEz0+NgXMzY2hq6uLuTn56/odVwuFxkZGejo6EBhYSE2bNgw56JFoVDg1KlT0vvuu++xw4cPZxJCbqeUmtcyX0KICMDnAOxe7TaWG1lyNXa7Hbt27dLGxMSY9uzZMxNt2759+8i+fftkzzzzTN++fftk11133chi29FqtZampiZBT08PJzAw0Prhhx+KY2Ji1rV5HiOsLiEopUcBHJ31/3tXuy0Oh7MpMDDw3X/84x+qzZs3z7vq7/z58zCZTMjNzV21542vry+0Wi1qamqQnJy82um6BKFQCKlUiu7ubo9fuSsUClRXV8Nms3lEYDotFyilKxKRTsPK0dFRjI2NzQgpSin4fP6MwFAoFAgPD4dQKERlZSVCQkJWLLy9ASEEPB4PPB5v3mheQ0MDfHx8oFarMTExMbP/g4ODmJiYgNVqBYfDmRFbYrEYAQEBK/ZkMhgM8PHx8ZjAHx4ehp+fn1dW49XX1yMmJsbjFzMXY7fbUV5ejrS0tFX9Bgkh0Gq1kEgkKCsrQ3h4+Jx6NR6Ph1dffVX8m9/85vM/+9nPSgkh11BKV+23QimdBOBZPw4XceTIEd8DBw7IoqOjjXFxcQkAsHfv3u69e/f23nLLLZFarVYeGBg4deDAgWbna4KCgpINBgPbYrGQw4cPBxw6dKghIyPD9P3vf783Pz8/lsPh0ODg4Km///3v62PZ+QKQ9eA3xOBZAgIC7tdoNP97+PBh2XyFrGazGSUlJVCpVC6pC6KUori4GFFRUV5b5u3EbDajqKgIW7Zs8Xhaora2Fn5+fh4TdWfOnEFCQsKCTW6dq9JGR0cxMjKCkZERTE1NQSQSISAgAGKxGD4+PvDx8Vn0ROQUI0FBQe7aFQDA0aNHUVBQ4NYxKioqlhSJFotlJmI3NjY2530LCAiAv7//orVabW1tsNvtiIjwTJeU8vJyBAUFefz3ZzAYvFbbeDG1tbVgs9mIiVl7jbnVakV5eTn4fD4SExPnPZZ8/PHH9rvuuqu/r6/vxkUWH7mFioqKttTU1HVd4O1OKioq5KmpqWHeGp+JWF1BEELYCoXi97m5uV96++23A+Zb5j06OoqysjIkJCRAqXSNVQghBGlpaSguLkZ+fr5XPWz4fD5UKhU6OjoQFhbm0bFDQ0NRUVHhMWHltF1wCiuTyTTTaNYpBnx8fODv7w+5XI6oqKhVuWFfTpYLy6mx4nK5kEgkF6R1nZG+kZERDA0Nobm5GWazeUZsSSQSSKXSmdqcoaEhj7V0caY2U1NTPTLebOrq6hZcPexJ9Ho9dDqdy1KhHA4HGRkZaGxsxOnTp5GRkTEnqn/11VezCgsLNdddd91hf3//h0dHR193yeAM6x5GWF0hEEICFArFB7t3705+8sknfeY70DnrqTIzMxeMcqwWoVCImJgYVFZWIiNjTYsY10xUVBROnjyJkJAQj9Z9+fj4eLQ3nFgsRl1dHUZHRzE8PAwulwu5XA6FQrFqETUfIpHIo42f3YnZbF7V+0IImYnuOSN3s9OqAwMDqKurAyEEMpkMw8PDHiuS7+3thUaj8bi4GR0dxdTUlNej1FarFZWVldi4caNL3wOnoWhfXx9OnTqFjIyMOTVzERERKC0tld1yyy2/UiqVmYODgw9TSr3vQcPgVhhhdQVACIlRKpWHf//73wf/z//8z5zPnFKKhoYGDA8PzzQldQdBQUHo7e1FT08PAgMD3TLGcuByuQgODkZrayuioqI8OrbTid0dq8GcEamhoaEZITUxMYH4+HgkJSW5TUReLl5Wrvawmi22nN/3qakpdHd3AwBOnToFFosFmUwGuVx+QUTLlXR0dGDDhg0u3+5S1NbWIj4+3uPjXkxNTQ3CwsLcZsTqbN5cWlqKuLi4OauO/fz88NFHH0kee+yxr7z66quphJAbKaXrwz2ZwS0wwuoyhxCSHRQUdPDQoUPKlJSUOY9brVaUlZVBJBKtyEphtaSkpKCwsBBSqdRjfkHzER4ejhMnTkCr1Xo0NRkYGIgTJ064pJiXUgq9Xo++vj4MDQ2Bw+FALpcjKChoRkidPn0aQqHQrZE5gUDgUWd5dzE1NeX2xsQ8Hg8sFgsRERGIjIzE1NQUdDodBgYGZmqAVCoV1Gq1S1YMTkxMgBDiseiYE71eDxaL5XWblYGBAUxOTrp94YxYLEZubi5KSkowPj6OqKioC37fLBYLP//5z/3S0tJyH3744bOEkC2U0gG3TorBazDC6jJGJBLtiIyMfPWTTz6Zt0h9cnISJSUlCAsL85gbM4/HQ2JiIsrLyz0i5BaCw+EgLCwMzc3NiIuL8+i4AQEBq+4RZ7VaMTAwgL6+PoyOjiIgIABqtRqxsbHzRjucdVbubJvi/AxXugJxveGpHoFDQ0MzTYh5PB40Gg00Gg0AR9Sxv78fNTU1MBqNkMvlUKvVkEqlq1ps0dnZiZCQEJfOfykopaitrfX6KuCpqSlUV1cjJyfHI99LHo+HTZs24fz58zh37ty8qw/vvPNOrkqlir7rrrvOEkK2UUpb3D4xBo/jfbc2BrcgkUjui4yMfKu4uHheUaXT6XD69GkkJSV5vMWFUqmEUChEe7t3+4lqtVr09fXBbF6T1cyKcXpaLRej0YjW1lYUFRWhsLAQo6OjCAsLQ0FBATZs2ACNRrNgCkkul3uk/onL5cJisbh9HHfiido3SinGxsbg7+8/7+MCgQBarRbZ2dnYvHkz5HI5uru7cezYMZSWlqK7u3vZ7zOldKa+ypMMDg5CKBS63Zx2KSorKxEbG+vRyDiLxUJKSgpkMhlOnTo1b4r8mmuuYR08eDA0ODj4HCEkzWOTY/AYjLC6DJHL5T9NTU197qWXXhINDg7Oeby9vR01NTXYtGmT17yHEhMT0dbWhomJCa+MDzgOgpGRkWhqavLouFKpFGNjY4ueII1GI5qamnD8+HGUlZWBUorU1FRs3boV8fHxkEqly7oK9/f3x+joqCunPy+XQ52VJyJWk5OTEAqFy/rs2Gw21Go1UlNTUVBQgMjISIyPj6OoqAhFRUXo7Oy8wFH+YoaGhiCRSNxSt7UQlNKZlYDepLu7G4QQr9VyhoWFIT4+HsXFxdDr9Rc85uwIsH//fn+tVnuEx+Nd5ZVJupmmpiZudnZ2TERERGJUVFTiU089pQSA/v5+dm5ubrRWq03Kzc2NHhwcZANAX18fOzs7O0YkEm24++67L7ja//Of/yyJiYlJiIqKSnzggQe80z5gBTDC6jKCEMJSKpX7rrrqqu8dOXJEkpWVBYPBgLa2NgCfhegHBgaQm5vrkbTHQnA4HKSkpMyIBm8RHByMoaEhj4oC5wG/p6fngvstFgva29tx6tQpnDt3DhwOB5s2bUJubi4iIiJWFU0hhEAoFLrdDuFysFzwRMRqtSlgQggCAgIQFxeHLVu2ICUlBZOTkzh58iRKS0vR398/p+G5Nxou9/b2wt/f362p56UwGo0z3SK8iVwuR3Z2NqqqqtDX5/AIpZSirKwMarUaubm5OH36tDwqKuptsVi8y6uTdQNcLhfPP/98V0tLS/XZs2drX375ZWVpaangiSee0BQUFIy3t7efLygoGH/88cfVACASieiTTz7Zs2fPngtatPX19bEff/zx4KNHjzY0NTVVDwwMcP797397vuHlCmCE1WUCIYSrVCoP3HHHHbfv37/fn8vlghCC9PR0dHd3o7e3F+Xl5bBYLMjMzPR6exnAEbmRyWQejxjNxrlkuqGhwaPjOlcH2u129Pb24uzZsygsLITZbEZaWhry8vIQFhbmkmJqZ52VO2GE1fJwVeNlHx8fxMbGYuvWrYiIiMDAwACOHTuGyspK6PV6TE1NYXx83KPF487Vxd6MVjkbLCclJXnVL8+JSCRCTk4OmpqaZjIFQqFwxhhWpVKhuLhYmpCQ8HuZTPZdL0/XpWi1Wkt+fv4kAEgkEntkZKSxo6OD9+GHHwbs3r1bBwC7d+/WffDBBxIAEIvF9u3btxsEAsEFVwj19fX88PBwc2BgoBUArr766rG3337bu6siloARVpcBhBBfhUJx/JFHHrn6xRdf9JudZmCz2UhPT8e5c+fAYrGQnJy8rgqMY2Nj0dvb65F01UKo1WqMjY3BYDB4ZDxK6UyPvU8++QQ6nQ4xMTHYunUrYmJiXH5ydzZkdieXQyrQZDK5vR5ndHR0wfqq1UAIgUQiQXJyMrZu3QqVSoXW1lZ8+umn4HK5HhW7nZ2dUCgUXl3t29bWNtNyab3A4/GQk5ODlpYWDAwMzLGgEIvFOHbsmGTTpk0/VSqVz5P1dIB2EfX19byamhrR1q1bDTqdjqPVai2AQ3zp9fpFc9UJCQnm5uZmQX19Pc9iseDgwYOSnp4e9y7fXSPMqsBLHEKIXKFQHHvhhRei7rrrrjlftqmpKZSWliImJgZdXV2YmJhwufnnWnA2ai4rK0N+fr5XImmEEMTFxaG+vt6t5qUWiwWdnZ3o7OyEr68vQkJCYLfb3d6cNiAgAJWVlW4d43KIWFFK3drmyGg0QiAQuG0MFosFlUoFlUqF48ePQ6PRoLy8HCwWC1qtFmq12m1j22w2tLS0IDc31y3bXw4GgwHt7e3YvHmz1+awEP39/eDxeBCJRKiurkZSUtIFF7h8Ph/vvfdewNe+9rX73nvvvUBCyJcppQsX0K2AjneHQ0wDFpderQmU3MnQW5bX3Hl0dJR16623Rj777LOdUql0xeaoCoXC9stf/rJ9586dESwWCxs3bjS0tbW5xt3YTTARq0sYQohWqVSeff311+PmE1VGoxFFRUWIjIxEdHQ00tPTUVJS4vFVcEshFosRHByMuro6r81BoVDAbDa7JXI2PDyMsrIyFBYWwm63IycnBxkZGYiJicHAwIDba8xYLBZ4PJ5bI0qXesTKYrG4vcjbVWnApRgfHwePx0NERATy8vKQnJwMvV6PY8eOoba21i2fU3t7OzQajdt9wBbCbrejrKwMqamp66LMYTY6nQ6NjY3IyspCWloaOBwOSktLYbPZLngei8XCn//8Z/EDDzxwo0Kh+IgQ4r3Qn4swm81kx44dkTt37tTfc889IwAgk8ms7e3tXABob2/nSqXSJQXkHXfcMVpZWVlXXl5eFxsba4qMjFxfJ7GLYCJWlyiEkAiVSnX84MGDQVlZWXMeHx8fR0lJyczSX8CxQiwhIQFnzpxBTk6OR1cLLUVERASKioqg0+k8cvKZj7i4ONTV1SE7O3vN27LZbOjp6UFbWxsEAgHCw8ORlpaGi9O0MpkMAwMDUKlUax5zMeRyOYaGhtzmacRisby6CGGteGJF4NDQELRarVvHAOYWrfv6+iIpKWnmO1laWjojvGQy2ZpLA6xWq9cjRY2NjVAoFF43JL2Y8fFxVFZWYtOmTTM1X/Hx8WhpacHp06excePGC2rBCCHYu3evj0qlytmzZ8/Raa+rNSnh5UaWXI3dbseuXbu0MTExpj179vQ779++ffvIvn37ZM8880zfvn37ZNddd93IUtvq7u7mBAUFWQcHB9kvvfSS8q233mp26+TXyPo5szIsG0JItFqtPnro0KHA+VpV6PV6VFRUICMjY46XjFKphNlsRmlpKTZu3OjW1MdKcDZqPnPmjFvb6iyG03pCr9ev2obCZDKhtbUVfX19UKvVyMzMXPSEHRoaisbGRo8Iq46ODreaRbLZbFit1nUl2JeLJwrXnYau7sRut89bxwM4Pp+QkBCEhIRgZGQELS0tqK6uhlarRXBw8Ko/t5aWFoSGhnrtcx8ZGcHAwIDLGiy7CpPJhNLSUmRkZMw5BkRERIDP56OoqAjZ2dlz+lN+/etfF/B4vLQf/ehHxwkhWymll1ye/ciRI74HDhyQRUdHG+Pi4hIAYO/evd179+7tveWWWyK1Wq08MDBw6sCBAzMiKSgoKNlgMLAtFgs5fPhwwKFDhxoyMjJMDzzwQEhNTY0IAB577LGelJQUJmJ1JUAIYQMoAdBNKb1h+r5vAfgmACuA9ymlj7pgnFiNRvPpBx98oJmvW31/f/9M1GWhE0VISAiMRiMqKyuRmpq6borZRSIRIiIiUF1djbS0NK/MIT4+HlVVVcjNzV3R+zIxMYHGxkaMjo4iIiICW7ZsWVZKwt/fH5OTk25vp+KJOitnOtAVrVg8jamxESI3Fl0bjcaZdjbuZGBgAHK5fMlxAgICkJ6eDrPZjPb2dpw4cQJBQUEIDw9f0UWNs/fhli1b1jr1VWGz2VBRUYH09PR1c5EIOFLLZ86cQVJS0oJGqUFBQeDxeCgqKsLGjRvnWFTcd999fA6Hk/zoo4+emBZXLl9d09PTo9TpdAoAEAgEkxEREW1sNtsloeft27cbKKWl8z1WVFQ07zLs7u7uqvnuf++991pdMSdPsX6+iZc+DwGodf6HELINwM0AUiiliQB+sdYBCCHxGo3m6EcffTSvqOrs7ERjYyNycnKWvPqOjo4GIcTjNgNLERISgqmpqRnfF08jFoshEAgwn7HqfIyOjqKkpARlZWXQaDTYsmULQkJCll3nQQhBcHAwurq6ln7yGnDWWbmzp9+lWsBuGxsD5+OPwfngA5jd1A3AUynulXpX8fl8xMTEYMuWLeByuTh58iSqq6uX/T1pampCRESE1+qaamtrERISsq7EvN1uR0lJCSIjI5f0LFMoFDOR+vnqO++9917+L3/5yySFQnGCEOLSnTSbzdzBwUFVQkJCTXJycjUAMjQ05B3H6MsMRli5AEJIMIAdAF6adfeDAJ6llJoBYK0NNwkhCYGBgZ9+/PHH6qSkpDmPt7W1obOzE5s2bVpW5IMQgpSUFIyMjKyovYq7IYQgNTUVtbW1Xiuyd64QXKxmSKfTobi4GLW1tQgPD0d+fj5UKtWqon+eEFaA+20XLtUC9vETJwBKQXx8oPvb32Bxg6hfrTHoSjCbzTCZTKuyc2Cz2QgPD8fWrVshFotx+vRpVFRULNoZwWQyYWBgwOO9CJ0MDQ1hbGwM4eHhXhl/Ppw+WgqFAkFBQct6TUBAADZu3Ihz585heHh4zuN33nkn79e//nWiQqEoJIS4tE8QpZTY7XaW3W6H3W5n8Xi8S7sv1TqBEVau4UUAjwKYvZQ0BsBmQshpQsgxQsjG1W6cEBIXGBj4yccff6yar3bCWdOTnZ29ojoHQggyMjLQ0dGBgYH102idz+cjPj4eFRUVXimI9vHxgVgsRm9v7wX3U0rR39+PwsJCtLa2Ij4+Hps2bVpzJILP54PP52NsbGxN21kKdxuFXooRK9vYGCZKSzGu0UB+771g8XgYeu01WF0sQIeHh91eX9XV1bXsk/lCsFgshISEYMuWLVAqlTh37hxKS0vn/W42NDQgOjraKyk4i8WC8+fPY8OGDeumlAEA6urqwOVyZ5psLxdfX19kZWWhoqJiXnG1a9cu7m9/+9s4hUJxnBDiEr8cPp9vUSqVfVVVVSkVFRWpbDbbJpFI3HsQukJghNUaIYTcAGBgnlwyB4AEwCYA3wfw1mqM3wghMRqN5tMjR46o4uLi5jzuNJ3buHHjqsLxHA4HGzduRE1NDUZGRlb8enehVqvB4/HQ2emVBS2IiYlBY2MjKKUzgurEiRPo7e1FamoqMjMzXWr0uNLGzKtBIpHMe9B2FSKR6JKLWI2fOAHY7dBpteDJZJDdcw9gt2Po1Vdhc5HQNZlM4HK5bk+XdXd3IzjYNW3UCCHQaDTIz8+HVqtFdXU1zpw5MyOwJicnMTIy4rVefFVVVYiKivJqW66LaWtrg8FgmONRtVx8fHxmxNXF/QUB4Etf+hL3xRdfTJgWV2vuGWSxWNijo6MBSUlJVampqZU2m401MDDApAJdACOs1k4egJsIIW0A/gHgKkLIGwC6APyLOjgDRzRrRbkAQkiUWq0+evjwYXVCQsKcx5ubmzE4OLhqUeWEz+dj48aNKCsrW1cRh8TERLS0tHhlTkKhEHK5HHV1dTh16hS6u7uRmZmJtLQ0txisqlQqDA4Ozun35krYbDa4XK7bUqye6EnoSpzRKmFKCuzThcNchQKyu++G3Wh0iCsXNAn3RH3VyMgIBALBnNVla4UQArlcjpycHERGRqKqqgplZWU4f/48YmNjvRIt6u3thc1mW3N0zpX09fWhu7sb6enpa3pPRCIRsrOzUVlZOW/a/o477uD+/Oc/T1AoFMcIIWtaxjo6Oirm8XhmHo9nZbFYVCKRjBgMhvXjHn0JwwirNUIp/SGlNJhSGgZgF4BPKKV3ATgA4CrAEXUCwAOw7DzMtE/VsQ8//FCTnJw85/GmpibodDqXWSb4+PjMFFFOTU2teXuugMvlIjk52SuNmsfHxzE+Po6WlhYkJiYiPT3drcvxWSwWFAqF24v23VlnxeFw5pgermfGT54E7HZwsrIuiHzwAgMhu+MOWIeHoXvjDdjXKEQ9UV/liYbLMpkMubm5CAgIwODgIAYHBz1+rDCZTKirq1tXq5mHh4dRX1+/5gtcJ0KhcKZ583y/1XvuuYf/7LPPJikUik8JIasO2fF4vKnJyUlfm83GopRibGzMTygUum91yxUEI6zcx18ARBBCzsMRybqHLlMdEEKCVCrVsUOHDgXOt/qvubkZer0emZmZLq1vkEgkiI+Px5kzZ9bNCVImkyEgIAAtLS0eGc9oNKKsrAwVFRWIjo5GVFTUvGF5dxAaGur21Ke766wIIW6NurkK2/g4JkpKIEpNhWm61chs+OHhkH7pS7D09kL/97+DWlZf06vX691qXGmz2aDT6aBUKt02hhNCCAYHB5GdnQ1/f38UFhaioaEBVqtLuq8sCqUUFRUVSEhI8JrD+8UYDAaUl5dj48aNLp3TbHE13/Hnq1/9Kv9nP/tZqkKhOEIIWZXpn1gsnvD39x+urq6OP3/+fCIAolKplrccmmFRGGHlQiilR50eVpTSKUrpXZTSJEppOqX0k+VsgxAiUSgUx955552g9PT0OY+3tLRgaGjI5aLKiUqlQkhICEpLS9eNk3ZcXBy6urrcWtw9NTU1U0ei0WiQl5cHmUyGiIgItLe3e+TEIRaLMTU15VZLBHfXWV0qKwOdtVV+W7cu6LoujIuD5JZbYG5thf6dd0BXcbFhNpvB4XDcWl/V398PpVLpkSLy4eFh2O12yOXymSJ3NpuNEydOoLW11a2iuqOjAwKBwO1musvFbDajpKTEbdFsp7iqrKycV1x97Wtf43/ve9/boFAo3iGErOrDDw0N7UlJSalOTk6ujoqKamWxWOvjoH+JwwirdQQhRKhQKD596aWXtPn5+XPi3G1tbRgYGHCbqHKi1WohFotRVVW1LsQVm81GWloaysvLXX7gttvtaG5uRmFhIfz8/LBlyxao1eqZNAOXy0VoaChaWz3jT+du6wXnSd5dKZxLYWXg7GgVRyrF2PjkgkXQotRU+F9/PUy1tRg5eBB0hd8/T9RXeSIN6KSurg6zF9Gw2WxERkYiPz8fZrMZx48fR39//yJbWB0TExNobW11e8Py5WK1WnHmzBkkJCS4dBHLxQiFQmRlZaGysnLeC6LHHntMtGvXrm0KheK3bpvEKqmvr+eFh4cn3nbbbdro6OjEm266KfzAgQN+6enpcVqtNunTTz8VjY2NsXbu3BmWlJQUHx8fn/DGG28EOF+bkZERm5CQEJ+QkBB/5MgRHwD4z3/+45eVlRV73XXXRYSHhyfedNNN4esxQs4Iq3UCIYSjUCg+ePrpp2NvuummOZ4J7e3t6O3tdVkefyliY2Nhs9nQ1NTk9rGWg7+/PzQaDerr6122zaGhIZw4cQIWiwVbtmxBaGjovHUbYWFh6OrqgmUN6aDl4hRW7hS07qyzuhQiVs7aKr8tWzAwasG71b74TyWBwTR/RMp30yb4bduGybIyjB4+vKLPxt31VUajEVar1SMGmUNDQ+ByufPaRnC5XMTFxSE7OxudnZ04ffq0ywS20xsqJSVlXbRLstvtKC0tRVhYmEfSryKRCFlZWSgvL5935faLL77ot2XLljvkcvlP3D6ZFdLZ2Sn43ve+N1BXV1fd3Nws+Nvf/iYrKSmpe/rpp7uefvppzY9+9CPNtm3bxs6fP1974sSJ+p/85CfBY2NjrMDAQOuJEycaampqavfv39/y8MMPz1w51NbWCn/3u991NjU1VXd0dPCPHDmy7gruvf8tZQAhhCgUir994xvfyLz//vvn9NXo7u5Gd3c3srOzPeZw7DTqPHPmDIRCocuWca+FqKgoFBYWrqmXH+AogK2urobFYkFmZuacVhIXw2azERERgaampnl7sLkSLpcLX19fjIyMuK0uRyaTob+/HxqNxuXbFolE8zpIrxds4+OYOHsWopQUWPwk+PvhARBQ9I7Y8McPB3Bbvgwh8rm1Mn4FBbAbjZgoKgJLKIS4oGBZ4+n1erd+Z7q6ujzy26SUoq6ubslWU0KhEJmZmRgcHJxJq0dFRa3puNXc3AyJRLKm37yroJSisrISEonEo8aoTnF15swZZGZmXiCkWSwW3nzzTf9rrrnmuwEBAd0jIyN/vfj1WVlZsRffd+utt+p/8IMfDI6Pj7Ouvvrq6Isfv+uuu4a+/e1v63p7ezk333zzBcZcZ86cWdYVblBQkDkrK8sIADExMcarrrpqjMViIT09ffJnP/tZYF9fH+/w4cMBv/71r9UAYDabSVNTE0+r1Vr+3//7f9qamhohi8VCe3v7zHLX5OTkicjISAsAJCYmTjY3N6+PgrtZMBGrdYBCoXjhlltuue7xxx+fc4YfHBxEc3OzxyJVs2GxWMjMzERLS8uyW7y4E0IINmzYgMrKylXVPDnTfsXFxQgKCsKmTZuWFFVOQkJC0N/f79b6Jyfu9rSSSqVuK8hf7xErZ7TKZ8sWvH1Kj9FJG5IlPbj/WgXYLIK/fDyIs40Tc6JShBD4X3cdhGlpGP/kExhOn15yrKmpKbBYLLdFWSil6O7u9ojtQH9/P3x8fJZtNaJQKC6ov1ptenBsbAw9PT2Yz8PPGzQ0NIAQgujoOTrE7fj4+CAjIwOlpaVzfmNcLheHDh2SaLXaX4hEous9PrkF4PF4Mz8kFosFgUBAAcfFqs1mI5RSvPPOO011dXU1dXV1Nb29vVXp6emmp59+WqVUKi21tbU1VVVVNRaLZUar8Pn8mW1ON35fH8tDZ8FErLyMTCZ7JDc3994//OEP4ovTUCMjI6iursamTZtW1BjVlXA4HGRlZaG4uBjp6ekLNhT1FD4+PggLC0NNTQ1SUlKW/bqhoSFUV1dDpVJh8+bNKxapLBYL0dHRaGxsxHz2F65EoVCguroaNpvNLWKaw+GAxWLBYrG4/Hu1nmusbOPjmCwpgTAlBUe7uGjqNeDGTH9MdDdCI+Fh93Yl3inS472SEXTppnBDZgC4nM9+k4TFguTmm0FNJoy+/z5YAgFE86zadeLu+qrh4WH4+fm5/dhAKUV9fT2ysrJW9DoWi4WoqCgEBQWhuroabW1tSE5OXnaht91uR3l5OdLS0tZFg+WOjg6MjIwgKyvLa1YPYrEYycnJOHPmDHJzcy/47H18fPDxxx9Ls7OzX5uamrqgbmGxCJOfn599scc1Go11uRGqlbJt27ax559/XvXKK690sFgsFBYWCvPy8oyjo6Ps4ODgKTabjd/+9rey9bJKfbl4/9t6BRMQEHBnZGTk4++8807AxQeOiYkJlJWVYePGjRAI5mQHPYpAIEBmZua8V0reQKvVYnJycllteMxmM0pLS9Hc3IzMzEzExcWtWqwEBgZieHjY7cKBEAK1Wj2npY4rkUqlbqmz4nK5HqlFWw2GwkJQqxUdMfk4WWtAZpQIScHsmcJ1EZ+Fu7bIUJDkh7LWSbz030EMGy6MjBI2G9KdO8ELD8fwu+/CuEjNn7vrqzxVtN7d3Q2pVLpql3NnejAyMhJnz55FfX39shah1NXVITAw0OsXcwAwMDCAjo4OZGRkeN0/SyaTISYmZl5bHLlcjo8//lg2NjamnJycdK1brBt49tlne6xWK4mLi0uIjo5O/MlPfhIEAN/5zncG3nzzTVlqampcQ0ODQCgUrr8K9UUg62HV15UIj8e7Jioq6q1f/vKXkri4OGi12pnHTCYTiouLkZaW5vb+YitBr9ejqqpqzpWSNzCZTCgqKkJeXt6C/jHd3d1oaGhAXFycy+qJ+vv70dPTgw0bNrhkewsxMTGBiooK5ObmumX7/f39GBoacssqq6NHj2Lr1q0uPwEdPXoUBcusbboYm8GA/l/+EmNxmXibpkIj5eLebXKMjujR3d09J/pZ323EP4uGQQiwM1eKKM2FFzd2sxlDf/0rLAMDkN99N/hhYXPGPH78OHJyctzyW7FarThx4gQKCgrceqK32+0z++EKV3e73Y6mpib09fUhNTV1wRV1er0etbW1yM3N9bqQGRkZQXl5ucveA1fR3t6Ovr6+C0yi7XY7KisrYbPZIBAILFFRUbV8Pn99Xum4kYqKCnlqamqYt8ZnIlZegBCyISgo6M1PP/1Ucs0116C/vx91dXWglMJiseDMmTNITExcV6IKcEQ5FrpS8jQCgQCxsbGorKyc85jZbMbZs2fR19eHvLw8lxZpK5VKTExMYHx83GXbnA8fHx9QSt0WHXNXxApwfDaeqEVbCYaTJzFJOXifkwIhj2BXnhQcNsHk5OS8qanYICF2b1dCLGTj9aM6HKseh33WRSiLz4fsy18GJyAAur/9DVM9PRe83hm1c9cFSG9vLzQajdtFR0dHB1QqlcsEBYvFQkxMDNLS0lBZWYm6uro50Sur1YrKysp10WB5cnJyJnOwnkQV4IjcBwQEoLKyEpTSGQsIHx8fiEQihIaGcpubm2OtVqtni3MZGGHlaQghIRqN5tB///tfuUqlApvNxsaNGzE1NYXy8nKcOXMGkZGRUCgU3p7qvGg0GgQGBnqlzczFBAYGghByge9TT08PTp06heDgYGRkZLjcoZkQgvj4eNTV1bl0u/MREhLiNid25wnfHWm79VbAbjMYMHa2BJ/E3IyJKeD2zTL4Ch3nGqPRuGDNj8yPg/uvVSBZK8THlWP4xwk9TFOfiQC2jw/k99wDlkAA3WuvwTJrgYder3drfVVHR4fbV6XZbDa0trYiKirK5dsWi8XIy8sDi8XCyZMnL1hJWl1djfDwcLe2kFoOU1NTOHPmDNLS0pa9yMXTxMTEgMViobq6GkVFRQgKCpoprPfz84NGo+E1NTXF2O32dVfgfTnDCCsPQggRKRSKI2+//bYqMjJy9v1ISkrCyMgIzGbzunEWXgjnQa+mpsbbU0FKSgoaGxsxOjqKs2fPore31+VRqouRyWSwWq3zesq4ksDAQPT09LhNwMpkMresDlxvBeyGwkIUSTeii/rjpiwJgmSfie3JyYXNQQGAx2Hhf3IkuD7dHw09Juz7aAD9I5+JUba/P2T33AMQAt1rr8E6/Z0YGhpyW33VxHRjaHef7FtbWxEcHOy2qNvF0av6+nr09vbCZDJ5zPB0IWw2G86cOYP4+Hi3tiNaK4QQhIeHo6OjA/7+/nPEtkQiIQEBAYL29vYw78zwyoQRVh6CEEKUSuW/nn766bC8vLwLrh4opTh//jzUajWio6NRVFS07lIpFxMfHw+TyYTm5mavzoPL5UKj0eDkyZMICgpyS5RqPuLj41FbW+vWMTgcDgICAtyWsnNX38D1JKxsBgNKa4dxXpqEnFgfpIVfGAVZKBU4G0IINsX64itXy2G2UPzpo0FUtX+2f1y5HLK774bdZILu1VdhMxjW7LW2GJ2dnW4XHhaLBZ2dnQgPD3frOMBn0SubzYbS0lJERkZ6NQVIKUVpaSlCQkLW/UWuXq9HSUkJcnJyYDAY0HNRShoAVCoVi1Lq39fX5343UwYAjLDyGAqF4qlbb7015/7775+TqG9sbITdbkdcXBxCQkIQFxeH4uJiGAwGb0x1WTg9pZzF3N7AYrGgtLQUExMTCAoKgtls9tjYAQEB4HA4bm1oDLjX08pdEav1lApsPHYOxxW5CJcSXJs2t1B6ampq2UJcq+DjweuU0Ei4ePvUMD44NwKb3RFN5Gk0kN11F2xjYxh67TUQN1hZAI6TvrO+yp20tLQgLCzMY07nhBBMTEwgPj4eNTU1aGho8EqpAaUUVVVVEIvFFywoWo/09vaiqqoK2dnZkEgk2LhxI5qamuZ4DhJCEBYWxh4eHg4cHR11v0U/AyOsPIGPj8+t0dHRX//Nb34zZ91wT08P9Ho9UlJSZq7SFAoFNmzYgLNnz7rNyNEVsFismR+zu6IqCzE8PIzCwkKoVCpkZGQgOTkZ7e3tHhWjcXFxM4sO3IVUKsXY2JhbaqG4XC7sdrvLG0yvl4jViG4cB/Rq+LIsuK1ABTbrwiiI83NbSXTET8jGV66WY1OMD4rqJ/DKJ0MwGB0LOfhaLaS33QbrwACCz5+H3Q1Cf2hoCBKJxK2Cx2w2o7e316PCoqurCxwOZ6bvoNVqRXFxsccj901NTbDZbIiNnWNUvq5obW1FS0sLcnJyZiKuXC4XWVlZqK6unrMggMViITIykt3V1RVhNBrXnVP55QYjrNwMISRJpVLt+89//iO5+GA4OjqKhoYGZGRkzDHA8/f3R3Z2NqqqqtzqZ7RWuFwuNm7ciKqqKrevlAMcJ8Pm5mZUVVUhMzNzpp0Hm81GamoqysrKXN6oeSH8/Pzg4+OzLD+t1UIImam1cgfucGHn8/kejR7Oh9VG8eYnfZhi8bAr2xci/tyFUSuJVs2GzSK4PiMA/5MjQY/egj8cHkDHoGN/BTExmNy0CVydDro33nC5uPKEd1VTUxMiIyM9ZsppNBrR3NyMpKQkAA4RkJCQgMjISBQVFXms60NXVxd0Oh1SU1O9vhpxISilqKmpwdDQEDZt2jTn+ysQCJCWloapqak5x0Eej4ewsDBOa2trjNVqdfuH29TUxM3Ozo6JiIhIjIqKSnzqqaeUANDf38/Ozc2N1mq1Sbm5udGDg4NsAHj33XfFiYmJ8TExMQmJiYnxBw8enImunThxQhQTE5MQGhqadO+994asx8bLs2GElRshhMhVKtUHhw4dkl9cAGk2m1FWVobMzMwFUwYikQg5OTloaWlBa2urJ6a8KoRCIdLT091uIOpcpTM5OYm8vLw57TUkEgmUSiUaGxvdNoeLiY2NRX19vVujVu5cHSiXy10ebXSelLy1apRSiveKh9BrFWE7pwXBEfPXySynvmoxUsNEuP9zCnDZBH/9ZAinGwyglKLPxwd+t9yCqc5O6F5/3WXiymKxYHx83K3F1EajEUNDQx7rDUopRVlZGZKSkuYcB5VKJTZt2oSGhga3R4YHBwfR0tKCzMzMdeHyPh92u33mwjEzM3NBo2NnmcLk5OSc98zHxwcqlYrX0tIS5e7fJ5fLxfPPP9/V0tJSffbs2dqXX35ZWVpaKnjiiSc0BQUF4+3t7ecLCgrGH3/8cTUAKJVKy/vvv9/U0NBQ88orr7Ted999MwV+X//617W///3v29va2s63tLQI3nnnHe+7xi7C+vwGXQYQQrgKheLwX/7yF83Ffa7sdjtKSkqQkJCwZO8tHo+HTZs2QafToaamxusWBwshFouRlJSEs2fPuiVtpdfrUVhYiNDQUCQnJy94UImOjsbAwIDbV+w5EYlEkEgkbq0zEwqFYLPZbklzymSyy86B/WzTBMo6prBhqAzpVy3cfsjU2wvRGq981RIudm9XIlLNx/ulo/hnkR4WK4U4LQ3SL34RU11dLhNXzr6A7oymNDQ0ICYmxmMRm9bWVojF4gVXUAqFwhmT0FOnTrnlwm1sbAzV1dXIysryWE3ZSrFYLDh9+jT8/f2RlJS05OfD4XDAZrPnTaXKZDIiEol8urq63KqetVqtJT8/fxIAJBKJPTIy0tjR0cH78MMPA3bv3q0DgN27d+s++OADCQDk5eUZw8LCLACQkZFhmpqaYhmNRtLe3s41GAysa665ZoLFYuHOO+/UHThwYP0u1QQjrNyGUqn8y8MPPxx3/fXXX6AAnN3R1Wo1lMrlLdJgs9nIyMiA3W7HuXPnPJbqWilyuRyRkZEoKSlx2RwppWhsbERNTQ2ys7OXLNplsVhIS0tDRUWFx0xMnT0E3fm5uKuIncfjwWazufy98ladVduAGYdKRxE60YktKiO4C/nBtbRAUVCAiC98AVhjNFDIY+GOLTJsS/ZDZbsJpfow1HYZIUhMdKm46urqcmskyWAwYGxsDGq12m1jzGZ8fBydnZ2Ij49f9HmEEMTGxiI2NhbFxcWrbug8H0ajEaWlpcjMzPR667CFMBqNKCoqQmhoKGbb9CyFQCCA3W7H1NTUnMeCgoJYJpNJPjQ05J6lqxdRX1/Pq6mpEW3dutWg0+k4Wq3WAjjEl16vn6NmX331VUlCQsKkUCik7e3tXI1GM3OVptVqp3p7e73b+mMJ1qc8v8SRSqUPXXXVVTf+4Ac/mJNnaG1tBaUUERERK9qm0+uqubkZp0+fXjSF6E2CgoJgMplQXl6+Zudks9mMc+fOwd/fH7m5ucsO0fv5+SEkJAS1tbUzdRvuRCAQQKVSobOz020Fv2q1Gg0NDYiPj3d5NEEikUCv17vUlNYprDzZPWBkwor9J/XwZ5lxVfd/Ib7pa/M/cWAA2L4dMJvBMpmAbduAo0eBNYgWFiHYliQGnehDea8P3jyhR6iCh2tTo6HYuRP6t9+G7rXXIPvyl8FaxQl8fHwcHA5n1f36lkN9fT3i4uI8Eq1yNlhOTU1ddu9OuVyO3NxcnDt3DkNDQ4iPj19T2s7Z5SI1NXXJzIG3GB8fR2lpKZKSklbsi0YIgUgkguUb3wCtrr7gcyUAoihlT05OhtkAFZuQlV0VJiVN4i9/WdYVyejoKOvWW2+NfPbZZzulUumS45SUlAgef/zxoA8//LARmL+kYL3WwDlhIlYuhsPhbA4ODn78jTfe8L/4wx8cHERPT88FKwBXSmRkJEJDQ1FUVLRulrRfTGRkJHg83pp8nsbGxlBUVISIiAgkJCSs+AAaHh6O8fFxjxW+RkVFoaWlxW1RMjabDalU6pb9cUedlactF6asdrx5Qg+rzY7trf9BQEIsuPNFhMfHgR07QLu78cPkZBz94Q8dQuuqq4Du7jXPg2cZwIPbZbhxYwD041a89N8hHNCrQW+8DVPd3Y7I1SpWurm7aH10dBRms9ljHR8aGhqgUqlWLLz5fD42bdoEDoeD06dPzxuNWQ5OA9CYmBi3+Y2tFZ1Oh5KSEqSnp6/abJYQAg6XC5vdjovlCSEEQqGQmCgV2h1ay+WYzWayY8eOyJ07d+rvueeeEQCQyWTW9vZ2LgC0t7dzpVLpzLLk5uZm7he/+MWol19+uTUxMdEMAGFhYZbZEar29naeWq1e1/0Pr7iIFSGEDaAEQDel9AZCyB4A9wNwnrF+RCk9tMpty9Vq9f5Dhw5JLw4rT0xM4Pz588jJyVn2FdpCBAUFQSAQ4PTp08jIyICf3/qzJklMTERJSQlaW1tXbDLY29uL+vr6Ne0bIQRpaWkoLi5Gfn6+26N7XC4XwcHBaGtrW1G4fiWEhoaiubl52Snk5SKTyVy+OEIkEnlsNSulFAfPjKBv2IKbxZ3wn9TBb+uuuU+cmgL+539Ay8rwdY0GfywsxK/PnkXnW29BedddDnF19CiwSo8oZ0pVKBRgYxSQGibEqToDCmsNqLOJkZpzN5LOvAO8/vqKIld2ux0DAwO4uFbTldTV1bl1+7MZHh7G0NDQqhuMO1ODvb29OHXq1IqPE86C+cDAQLf7ga2Wnp4eNDU1YdOmTWuOUrJ+9SvYLBYYTCb4+vpecFHPAmAZGSFd/f2IiYmpd0UkqKenR6nT6RSUUvzkJz+xxcTETOzZs2cmf7t9+/aRffv2yZ555pm+ffv2ya677roRABgaGmJff/310Xv27Om69tprJ5zP12q1Fh8fH/vHH3/ss23btom//e1vsm984xvuW4rtAq7EiNVDAC4OpfySUpo2fVutqGIplcoDf/7zn5UX10FYLBaUlJRgw4YNLsvjy2SymZV4nvaQWg6EEKSnp6Onp2fZJ1hKKerr69HW1obc3Nw1C0ahUIjo6GhUVVWtaTvLxdlawl1F2wEBAZiYmFj1VfpC8Pl8WCwWl0bbPFljdarOgMp2IwriBFCX/RfCxMS50Sq7HfjKV4AjR/CYRIK/jY7iF7/4BY4cOQLlzTcDH34IW2enIy3Y17eqeQwPD1+wYo/HYaEgSYzv3KhCdrQPqkb4+Ef0HThp1qDn9TeXHbkaGBiAXC5f8wXZQjjtNjwRubFaraioqEBaWtqaV99pNJqZY+BK6q5qamogEok84iq/Gpqbm9HW1oacnByXpX65XC54PN68KwUDAgIgEomEPT09a1aZExMTAp1Op0hISKjt7u5uf++993xOnjwpjouLS4iLi0vYv3+//969e3s//fRTsVarTfr000/Fe/fu7QWA5557TtnR0cF/9tlnA53P7+7u5gDA73//+/YHHnggTKvVJoWFhZl37tw5uvhMvMsVFbEihAQD2AHgaQDfdeW25XL5j3bu3Jl8ww03zClWP3fuHKKiolxebyIWi5GdnY2zZ88iKioKgYGBLt3+WnE2mC4qKgKfz1/0wG21WlFWVgahUIjs7GyXLXkOCgpCb28venp63P7+cDgchIWFoaWlxS0Gg4QQBAcHo6ura8U1ekshkUgwPDzssv52AoHAI+aOTb0mfFQxhsQQAdKHymCwWOBXUHDhkygFHnkE+PvfcbigAC9XVuKZd/8AfQwbAz4cNJh60GwYxzNGI440N4OzZQs4J04AK2xnMjQ0NG/jZR8BG9dnBGBTrC8+rhxDGd2AWqsJmW8eR8GXNoPns/jJs6Ojw22GlZRS1NbWIjl54dWTrqS2thZardZlNU1isRg5OTkoKSnB+Pj4ku1wmpubYTKZkJ6e7pLxXYnTo8pkMmHTpk0ut33g8/mw2Wwwm81zLvCDgoJY9fX1Kj8/vzGxWDyxwCaWxGg0CkUikYHNZts///nPGzo6OnpYLJY9KCjoAuVbVFTUcPFrn3vuud7nnntu3qvwLVu2TDY2Nlavdl6e5kqLWL0I4FEAFxfQfZMQUkkI+QshZMXLOAkh2Wq1+uEXXnhhjrdGY2Mj/Pz8EBQUtLoZL4FQKEROTg7a2tq83rdvPng8HjZu3IiKiooF7QKMRiNOnToFpVKJpKQklx5QCCFITU1FfX29R070Wq0Wvb29Lo8qOXEKK1fj6jorFovldmsQ/bgVb5/SQynm4KYUASbOnJ4/WvWLXwC//CXw7W/jmiNH8MKnr2IgjgV/qwCNpl68oTuG0rhRhP7ga/g8pZhqbMTYxo2O2qsVoNPp5hVWTqS+HOzMleKB7QqoA9g4KUjErw50obxxFPYF3iuz2QyTyQR//7nteFzB4OAgBAIBxGL32wINDAxgYmICYWFhLt0un89HTk4OJiYmcO7cuQUjrz09Pejv71/zohp34OyT6Iz0u8tLSygUwmq1zum2wGKxEBERwe7s7Iy0WCyrDo0KhULjxMSEn8ViYdtsNtbY2Jj/1NTUFef0fsUIK0LIDQAGKKWlFz30BwCRANIA9AJ4foXblahUqn8ePHhQerELrk6nc3ttBOAI827atAkjIyM4f/78uvO6EolESE9PR0lJyRxxo9frUVxcjKSkJLetqOPxeEhISEBFRYXb35vpA5TbTEr5fD74fD7GxsZcul13+Fmx2WyXt8txYrbY8fcTjvnevkUGy9liULMZflu3XvjE114DHn0UH/j7o/Whh3DIUIZm2TiSSTA+Z4rB9zVfwB3SLYjxC0bct65G9Ac/w91hanA6O9EVFwssc7GAzWaDxWJZVqo/UMrDV28Mw20RE+BNTeJfJQb88YN+NPXOFf5dXV1uuyhzpt49UVtlsVhQXV3tNldzFouF1NRUSKXSef2udDodmpqasHHjxnVnAGqxWFBcXAyZTIaEhAS3ij7nSsHJyck59jB8Ph+BgYGc1tbWyNUeJ318fEwqlaqvvr4+pr6+PlooFE6uNxHrCdbXN8y95AG4iRDSBuAfAK4ihLxBKe2nlNoopXYAfwaQtdwNEkKIUql85ze/+Y3q4nz91NQUKisr521X4w5YLNbMlU5paanHPJyWi7+/PxITE3H27NmZk21XVxfOnz+PTZs2ub2+Q6VSQSAQuK2h8WxCQkIwNDTktlVx7vC0EggE87bBWAvuqrOyU4p/FQ9jcMyKL+VJEcCagqG42BGtmp2+O3QI9q98BZ+wWPi+QoH/TlTh7EQT8n3jkW4KhI/IBxzCRpwwCF+S5uFR9S34et5tuP7U6/jpl7ZCYTBgaGsWTrWexIh18ezIyMjIih3RE7NjcH82D1f1fIKJ4XG8dlSHVz4ZQo/+s2hnd3e327yrent7IRaL4ePj45btz6ayshIxMTFutYsAHHWO8fHxKC4uxuioowxnfHwcVVVV2Lhx47qzqHFG6yMiIjxW88VisSAUCuett5JIJITP54v6+vpWlgefhUqlGkpKSqpNSEioZ7PZNj6f79mGj+uAK0ZYUUp/SCkNppSGAdgF4BNK6V2EkNkFe7cAOL/cbUql0u/ecMMNGTt37rygVs256iQ+Pt7tB5LZEEKQkJAAmUyG4uJirzlfL4RCoUBYWBhKSkrQ1NSEzs5O5Obmeuw9SkxMRGtrKyYmVl1CsCwIIYiOjkZDw5wyApegUqkwODjockPSgIAAlzrWr9RywWlmODk5ibGxMQwPD0Ov10On00Gn08FqtUKn0+FwyQBqu0zYEsuF0seC4RMnQM1m+M6OVp0+Deutt6KcUvw0IQEPvfcCOqWT2OaXjM+JU2EymuZ87/gsLtJE4fiq5hrs/fuHaPnXSwho7YE69yZcf8NWvFj7Ds5ONGLSNtfoc6H6qqUQJcQj+/pM3Nb8D+SbqtE7PIU/Hh7E26f0aO8dhkAgAJ/PX/F2l8JpvBsTE+PybV9M97SNhbsibxcjl8uxceNGlJWVoaenB6WlpUhPT/fosXg5jI2Nobi4GMnJyW5ZnbhY1InL5YLNZs/b0zMkJIQ9MjKiHh8fX1W/p6mpKQ4AmEwm3ujoaIBcLndtM9IlsNvtBHPLfTzKFVW8vgDPEULSAFAAbQB2L+dFhJC0uLi4H/7ud7+bU/zQ0tICHx8fjzkYX0x4eDgEAgFOnTqFrKysdXVACQ4ORnt7O9ra2rBt2za3rXSaDw6Hg5SUFJSXl8+0yXAXGo0Gzc3NmJiYcHlEgMViQaFQoL+/36UHZJlMhqGhIZdFDwUCAUZGRsDlcmEymebcLq5DI4SAw+FccHN+RnY6BZO9HWdrg1DUKUaovwlSDKKhahLK06dhVKnQVF8PWlcHUUcHkh58ED1mMx6Oi8Wtr/0YnX4GbLSFIn5SjhHbCMbHxxf1hfJlCxB/wz3AwUCEXn89fn+4FDflfRUn//crSLohB1ECDVKEWsQJgsFjcaDT6VbtMyWMj4fiSzvB3r8f8epO1GV+AcXNJpzvsKMg1j3Rqs7OTsjlcrcfG0wmExoaGpCXl+fWcS7G19cXGRkZOHbsGKKjoz1SQ7YSBgcHUV1djczMTLfY5QgEgpmav4WOcwKBAAaDYea35oTFYiE8PJzT3NwcGRsbW83hcFYkUpqamiJtNhuHEEJDQ0M7uFyux9IndrudDA4O+mMFARJ3QNZbPc6lACHET6lUnj9x4kToxVd8w8PDOH/+PPLy8ryey9fr9aioqEBGRsa6OLA43Za5XO6034/QbaudFqOmpgZcLhfR0dFuHWdgYACdnZ3IyMhw+bbHxsZQW1uL7Oxsl23TaDSivLwcOTk5y34NpRSTk5OYmJiAwWCAwWDAxMQEzGYzbDYbKKVQKpXg8/kQCAQX3Hg83rLF7dFzz6J3eAJNuvuh8Bfg/12tAJdDMPbJJxg/ehTKb3zDkQbs7gZyc2E3GrH3umuh2Xs7enhjyCdRiDbLZ4rBe3p6ZhowC4VC+Pr6ztx8fHzA5/M/m9vhw7DfdBMaOBzkTE4i6eZrcPVTd8Iu5YNHOIjlB4HTNI5bsrev+D2fjbGuDvr9+8FVqcDdeSdeOdqLEYsPvrxVhiiN69qt2O12HDt2DHl5ebi4LtSVUEpx+vRpREREuNx7bSnsdjtOnz6NwMDAmTo1VxfNr5auri60tLQgKyvLbW10LBYLurq6llyw44wSX/B9n2b6N22USCTr2jPqIuwAzlut1vsyMjK8Nm8mYrVCpuuq3vzFL36hvlhUWSwWVFRUrJsCSalUio0bN6KkpASJiYkec1WeD6vVipKSEsjlckRFRYFSirNnz6K9vd1tResLERcXh5MnT0KlUrlVcCoUCjQ1NWFsbMzl44jFYkxNTcFkMrns4CwUCmEymWC32+f9/tpsNoyNjWFkZAQjIyMYGxsDpfQCYRIUFARfX1/weDwYDAbU19cjJSVlzXOzIQ61AxtBYMOODSZwOQR2oxGGoiIIEhIcompkBCObNsF/ZATWTz9GmHYcbVMDuDkgCxk+F5q2joyMoKCgAJRSGI3GGVHY3d2NiYkJmEwmcLlc+Pv7IyAhAbK//x2xd9yBmqAgpH1wHI9/8zFExSSjcrId5yfbYQ62QjpejS2+qy8+FsbFQXrbbdDv3w/L31/BVTmbcXLAH/sL9bj/cwoo/V1TH9TW1obAwEC3iioAaG9vh0gk8rioopSivLwcSqUSWq0WwcHBKC0thdls9miD6fnm1dTUBJ1Oh9zcXLc2fOZyucuu2erp6UFXVxc2btw457254447zB988MH/DQ8P/8Ed87xc8f7Z/xLDz8/vK9u2bcv78pe/fMFRyfljjo6O9kgx6HLx9fXFpk2bUFdX55Zl+sthamoKxcXFCAwMRFRUFABH2icjIwOdnZ0ubaq6HJyNmsvLy91a5E8IQVxc3Jpa+yyGO6wXAgICMDo6CkopxsbG0NrairKyMhw7dgwnT55EW1sbACAsLAz5+fkoKChAdnY2EhMTodVqIZPJZq5+XdnWpqTNEV2MVn6C882/x4RJB0NREajZDHFBAejkJFpTUiDq6sKbt9+G17SjaJ8axK2SnDmiymazzQhH5yoppVKJiIgIpKSkICcnB9u2bUNWVhbUajVMJhNqtFpU7d0L1cAAGsPDEa9WQ20XY/LDZmztCEQUVeDjsUocGDkNK139d0oYFwfprl2gQ0NQ11Tiji1ScNkEbxzTwWBc+3fVarWivb3d5T5oFzMxMYG2tjYkJCS4dZz5qKurA4/Hm+mA4PTTM5lMqKys9MqqaUopqqqqYDAYkJWV5VZRtVICAwPB5/NnftuzeemllwJkMtmThBDPpxYuYRhhtQIIIYH+/v7P/ulPfwq4+LG2tjbweDyPFWiuBIFAgJycHHR1daGxsdGjBxZnZ/bo6Og5NSjOA15tba1Li6aXg1gsRmBgIOrr6906jrNeyelu7UqCgoLQ1dXlks/TKaTsdjvKyspw9OjRmeJ7p4jaunUrNmzYgPDwcEgkkiXr4zgcjkuEq53a4MN1eLTdmH0t7NSCosrfYKTkFAQJCWDLZKhMToa2sxMvb9uKkb23omtKh53SPKSKwuZsz2g0Lqu2iMfjQaFQIDo6GpmZmUj5wQ9gf+st+LW0QHbXXTj5/vv46le/iuu3fx66d6qQJ4hF2WQrXhs6ikn73KLgZRMaCn1UFKxNTeC31uHOLTJMmOz42wkdpqxrq8ltbW1FaGioW1fHORfvpKamelxAtLW1wWAwIDEx8YL7CSFISUkBn89HSUmJR1dN22w2nD17FjwezyWO8+4gKSkJHR0dMyspnYhEIuzfv1+uVCrfmW4Hx7AM1t8nvE4hhJCgoKB/P/fcc7KL0zqjo6Po6OhAUlKSl2a3NBwOB1lZWTAYDKiqqvKIuDIYDDh9+jSSk5OhWsDFms/nz6zgcfdqvYuJjIzE8PCw21sCxcfHo66uzuXb5fF48PX1XbUoNRqNaG1txZkzZ2aElJ+fH3g8HgoKCpCZmblsEbUQLBZrzScxw2Q/jBYJfLmj8PcNRHbCbkwYh9AQOwB+TjaOJSUhtaUF/yzYCtvfH8WQfRy3yzYjURgy7/YmJydn6qtWCucLXwB55x0Ia2rwueefR8knnyAoKAjfffi7ePaL30NQDdBhHsQfej9Av3F4VWN0dXVBnJcHblAQRt9/H2r+FL6YK0GPzoJ/FQ8vaCa6FM66G3fXGjU2NkIul6/YfmKt9Pb2oru7G+np6fOm+5wRZLlcjtOnT7vNY202U1NTKCoqgkqlQlxc3LozJnXCZrORnp6OsrKyOavJN2zYgJtvvjlaoVD82EvTu+RghNUyEYvF/6+goCA6OjqaVVpaOvPls9lsKCsrQ3p6ukdXuK0GZwqMx+Ph7Nmzbr1qGx8fx9mzZ5Genr7kKjMfHx9s2LABZ8+enXf5r7sghGDDhg2oqqpy60FWLBaDz+djcJlmkythJZ5WlFIMDw+jrq4Ox44dQ1lZGSilSEhImBFSMTExLrXpcEU6cHi8HSaLHD4cx2ck5Ycgoj4ABokV3T+9H9saGnA0Pxe9bz6CYbsBd8q2IlYwf+TYbqEY+KcZ9JgYlvFVfv9vugl46y2gpASx3/kOXv/97/F///d/OHXqFJ689xHssCfDZJ/CnwY/wvuln8ysDl0OlFJ0d3cjKCQEkltvhX1qCiP/+Q/iggS4doMYNZ0m/LdideawTU1NiIiIcOtxanR0FP2Ohr5uG2M+9Ho9GhoasHHjxiX3Lzw8HCEhITh9+rRbLWkmJydx6tQpREdHe7yOdDX4+fkhMjLygt6q4+PjKCwsxLe//W2+v7//t5iU4PJghNUyIIQE+fv7P/OHP/zBPzMzE2q1GidPnsTg4OBM7yt3LJl1B86rNpVKhaKiIre0XhkbG0NJScmKViMGBAQgPj7+AgNRT+Bsxnr+vHtX58bGxqKurs7lkUKFQgG9Xr+gSLbZbOjr60N5eTmOHj2KlpYWiMVi5ObmIjc3FxEREXM63qt7emA4dswl83OFsBoc7YbFLoaI43jvDMXF8GmzI/u/VsS+/jG6bsxH+VuPYcxuxJdlBYgUzG9zQu0U7W/rYeslsA2y0LhvEJO9q/z+f+ELwP79YJeWIvHJJ/HoI4+grKwM//u//4uNoYl4QPN58CwEJepBtHL0qKysxLFjx1BTU4Ph4eEFvwfDw8Pw8/MDl8sFV6GAeNs2mGpqYKyuRm6sLzZG+eBkrQGlzSuL7ppMJvT39yMkZP4oniuw2WwoLy/3eLrLYDDMLBpabkF+SEgIwsLC3CauRkZGcPr0aaSmpi4YrV+PhISEwGazobe3F83NzTh37hz+P3tnHR5Zeb7/zxnJTHwycXe3jW5ss4ZLsbZQKF6gtLRQoVSAfktLS12QFihSoEipAC3QRZe4u7u7yyQZO78/ZhM2G53YLvx6X9dehDNzZGbOed/nfZ77ue+YmBiioqJ4+eWXnVxcXP7xv5LgxvhfYLUBTnQB/u3pp592XAyePD09SUlJoa6ujr6+vl0drHYLvr6+BAcHk5eXt6MluKmpKUpLS0lMTDS7E87V1RVvb2/Kysr2lAfm4+PDwsICAwMDu3YOGxsb7OzsdvwcgiDg5uZGf//H3qWiKDIyMkJFRQVZWVmMjIzg7e3NwYMHSUhIwMPDY22OzZNPEnbDDdgcOQLf/CZsUzl9J9TX+0dNvA8bmRbj/Dz9H37Ik3/5C64/fpKxw3H85TfXM2PUcL3TYfwUq3egiaJI75uTTDXMY4iexuNqKxCg5c8jTNRsMfC7/HI6vvlNLI8fh4cfJiIiguuuuw6AnDc/4FepdzB4rI4sWQvzkTakpaWhUqloa2vjo48+or6+nunp6WWH7OrqWsZFtElLM5UE//MfjLOzXJBgT5Cbgn8XT9A6sHlB6+bmZoKDg3c14GloaMDLy2tPF5kLCwuUlJQQHx9vdnnX09OTgICAHQ+uhoaGqKioIDk5ec/LoTuB4OBgSktLmZ2dJSMjY8mnMiEhgeuvv95XrVZ//zRf4hmP/wVWG8DOzu5L5513XuRZZ5217LuSy+WIooivry85OTmMj2+NT3E64erqSmxsLEVFRTtCHl8MqpKSkrY8uPr6+mJvb79nPDAwBSf79u2jvr5+V0uRISEhNDU17fjnWiwHTk1NUVdXx/Hjx+nu7sbLy4tDhw4RFRWFo6Pj+pOqXg/f+AbceiuGQ4cYuuwyk3Hxvn2Qm7vla9tuxsooGhiZNmUwraRauo4d4xePPsr/9fUxHBzIX568B6PCkoDuMmRTvWseZyhrhtHiWZwzbNC4j6LysyH4Nmcs3eR0/m2MgfenEI3m/S6iKNJx3nmIF18M3/kOVFUtvRYYGIiPtzd/vPkBPvj6M7zZlc/r08W4uLuSkJBARkYGtra21NbWkpWVtVQuHB8fx8nJaek4glSKw2WXYVxYYPLNN5FKBD6focbJTsYrOWMMTW4cEGg0GsbHx/Hw8DDr85mDkZERJicnd73b8GTo9XqKioqIjIzcskm1h4cHAQEBO+ZU0dXVRVNTE6mpqWdUd/hmIIoi3d3dVFRUEBQUhE6nW1FW/clPfmLj6Oh4pyAIu28w+QnG/wKrdXCiBPjgI488suKpbWhowNfXl9DQUBITE6mtraWhoWHHbUZ2Gw4ODiQnJ1NRUcHQ0Nb11E7OVNnY2GzrmkJCQjAajbS0tGzrOOZAoVAQFha2q+3YlpaWODk57ahEglarZWBgYEmYVqVSkZmZSVxcHE5OTpsjy05OwsUXw+9+B3fdhfStt6i74w7E994DnQ4OHNhy9mq7Gavp2X40WgcEQWR+tIc7b7yR34yNMeflycuv3YfOyoKbnc/FU+FEScPTjE21rzjGWPksA+9P4RBriftZduj1elOpzUZK4I1OqOOtGPxoms5XxjAsbP75nZycxM7eHuGpp0CthmuugRNBZFRUFAUFBfz4xz+m6N/Hefro9/n7v//FsyMfMmtYQCaT4eXlRUpKCvv370cikVBQUIDBYKCvr2/ZOCJ3ccHu8GHmamuZq6lBKZfwxYOOyDYpw9DY2EhoaOiuEad1Oh01NTXExcXtGTnbaDRSUlKCn5/ftvX5PDw8CAwM3FbmatHQur+/n5SUlF2xIdpNLGb+RkZGSE9PJywsDKPRuCLDbmFhwcsvv+z4vy7B9fG/wGoNLJYAn3nmGcdTsy+jo6NMTU0tddfY2NgsWaTk5uauSO+f6bC2tiY1NZWmpqYtmftOT08vBVU7UQZYbI0eHR2lu7t728fbLNzd3ZHJZLuq9xUcHExra+u2AnBRFBkbG6OsrIz8/HwEQSA8PBxHR0c8PDzMIye3tkJqKrz3HjzxhClLJZPR7bFAYaw7VFfD7bdvOXtlZWW1rYzVxEw383pHbC10/PZrd/D4+DgyRzUv/PM+dGoVNzkdxUPpRErk7Sgs7Cmo/SMzcx8vEKaa5ul+fQKbQAVelzggIi6b/CUyAa9LVHicZ89kwzwtfx5GO745jt/o6Kgpu+TsDM8+CzU1cM89S6/L5XLuvfdeSkpK8PXwJkbnQZ92lCeH32FE9zEBXaFQ4O/vj6WlJbGxsUxOTi7xsRbL9Dbp6cg9PJh4800Ms7OorGVLMgwvZo+i06++GJienkaj0eyqSGdNTQ2BgYF7Zp0liiJVVVWo1eodo2F4eHjg7+9PUVGR2RxPo9FIZWUl8/PzJCUlnVEaVZvBwMAAeXl5eHl5ERcXt0QTiImJob6+fgUPNz4+nhtuuMHX0dHxf12Ca+B/gdUasLe3v/WCCy6IPHr06LLvSK/XU11dzb59+5YP0BIJoaGhREdHU1ZWRltb22kRotsqFAoFKSkp9Pf309jYuOlrn5mZWSKq7yS3QiKRkJiYSEdHx650062FqKgoWltbd0zY8lRYWFjg7u5OZ2en2fsuijtmZ2fT3t6Or68vmZmZBAQE4OPjQ39/v3n33PHjkJwMg4Pw7rtwyy0AVM910mIzzjvz1cxYSuHRR+H99z/OXn3rW5vOXsnl8m2VWCamO1nQO9Py2iM8NTKCg1LJC6/ei9bbnZudjuIkN/H4FBa2pEV9FUSR/OpHWdBOo+nV0vnKGJaucvyuUiORCasq1QuCgHOaDf5fdEQ7aaDp8WFmOjYuCS8zXj73XLjrLnj4YXjrrWXvi4mJoaioiO/dfBc3OB0l72/v8s2//pT2hY+FcTUaDaIo4uzsTEREBAcPHsTe3p6KigoKCgoYGhlBdemlGOfnmXzzTQA8HS24ItWB3nVkGBoaGna1zb+/vx+9Xo+X1+54Gq6GpqamJaPznYSnpye+vr5mSTHo9XqKi4uxsrIiJibmjNSoWgt6vZ6Kigo6OztJS0tb4TuqUCgIDQ1d1iW4iB//+Mc2jo6OXxcEIXyvrveThE/OXbCHEATBy87O7scPP/zwihLgYhfgWkRJlUpFRkYGGo2G/Pz8XZugdwOLWlfz8/NUVlZumFWZn59fIo7uhjXM4vXU1tauEK7bLcjlcqKiopakCHYDAQEBdHR0bHrwnpubo7a2luzsbObn59m/fz8JCQnLDFZlMhn29vab1+R64gk4+2xwdYWiIjh0CIBZwwJvTZbhJLHFgJEPp090Sx45YuIQffnL8JvfmJ292up3OTbdzYLegSPt9fgJAi+++D3mI4K52fksHGTLS842Vq7sj/wyc9oJigpfoO35EWTWEvy/6IhUYRrq1tOwsgtWEnKrMzJLCa3PjjBasnZTx6JH4jIezc9+BjExcOONcEpZXS6XIwgC3haOdL5cxPM3/pxLr/kcH/WUAytJ6xKJBE9PT9LT04mIiDBlFRoa0MfEMFdTw1xtLQAR3pacvc+O2u453q9aLsMwMTGBXq//OPjbYSwsLNDQ0EBMTMyelQA7OzuZnJzctXN6eXnh7e1NaWnphuPfwsIC+fn5eHh4nFarnK1gdHSUnJwc1Go1ycnJa5YuPTw8MBqNy5pj4H8lwY3wv8DqFAiCILi6ur70zDPPOJ3KFRodHWV6enpDgT2pVEpUVBQhISEUFhbS3d39icleLZbhrKys1k2L63Q6ioqKiIqK2jJxdDNQKBQkJiZSVla27e6yzcLJyQk7Ozva2tp25fhyuRwfHx/a21fygU7G7OwsFRUVFBUVYW9vz8GDBwkNDV1zENyUppVeD3feCbfdBmedBfn5EPix5ct/J8uYN2r5vGM6HpNWlM62fly2srWFxx4zZa+02k1nr5RK5YZmsKvBaDQwNDGLiITpe7/BI/m/ozs5lJucjmIvXT04crQPJN7nRixzMtDrF/C7Vo3c9uNxfyPVdYWTnOBbnbENUNDzxgQ9b04gGlY+u1NTU9ja2i6fTJVKePFFmJoyBVerPPOCIJB9PIvv3vt9al7L5eLEozz4t4fp6+9bkTFYhJ2dHbGxsaSnp6ONiGDexoaR119n4cRiIz3MhsRAK7LrZig7SYahvr6e8PDdSSgsWniFh4fvGZ9ocHBwydR8N4MYHx8f1Go1lZWVa47bMzMz5OfnExoa+onqCjcYDNTV1dHQ0EBycjI+Pj4bfpcxMTE0NDSsKAnGxcVx0003+To6On5vN6/5k4j/BVanQKlUXpKenh519OjRZXfbWiXA9eDk5ER6ejrDw8OUlJTsimbUbkAQBEJCQvD09CQ/P39Fp5zBYKCoqIjg4OBlHUy7BRsbG2JjYykuLt6z7zA8PJyenp5d48v5+fnR09OzaplscnKSkpISKioqcHd3JzMzEy8vrw3LDGq1mqmpqbUzYRMTcNFF8Ic/mMpW//43nBQUN8/3UznXwQHbCNwsHIhacEWGlHenKpcf58gRE/fq5OxVXt6a17VVAvu0pp85nQMLczMMSQaZ9HLmTreLsZWuHRgZFoxo3vJArlPRH/tXmidfWzY5bkZ1XWppynI5p9kwWjhL2/Oj6DXLsxdL/KpTERkJv/ylqRz42GOrHt/CwoKf/fhB8gsKcFCruffKr3Nc18C8sH7JVC6XExwaiucXv4ig1dL+wgvU1taysLDAhYkqAt0UvHFChmFkZASZTIZKpVr3mFtFd3c3CoUCN7fVNcN2GhMTE9TX129KAHQnEBQUhFwuX9Xnc3x8nOLiYuLi4vbcYHo7mJqaIjc3FwsLC9LS0jYtT7FeSfCHP/yhtY2NzZ2CIOxey+knEP8LrE6CIAiW9vb2jzz66KOqU1+rr6/Hz8/PbK0UuVxOfHw8np6e5Obm7rnh8Hbg7e1NaGgo+fn5zMzMAKaVamlpKZ6enmuusHcDarWakJCQXVeMX4RUKl0yat6NTk+pVIq/v/+yzsfR0VEKCgqor6/H39+f9PR0XF1dNx3IC4KAh4cHvb2ryA60tJhI6u+/D08+uURSX8SCUce/J4pxktlx0Nbks+bh4Eqk3o36+R46Fk7pGD01e5WRYcperVL63iqBfWKmi3m9I1XZf+fe869H2TCxZqYKQDSIdP5tjLl+HX6fd8IrIoy2vuO09L6/9J65ublNPcOCRMDjPHu8L1Mx27lA8xNDzA99HPgs41ediq9+FS64AL79bThRslsNyYlJNJbVcPcjP0Iaqebhwbeo1LRvmN1Wenhgd+gQtoOD2I2OUlhYSE11FRfHKZdkGEqqWwkL252OeI1GQ1tb255ZeM3OzlJeXk5SUtKeZccEQSAyMpK5uTlaW1uXtg8MDFBVVcX+/ft3NVO/kxBFkebm5iXx1qCgILMzfh4eHoiiuKIkqFQqeeyxx9Rubm5P7eQ1f9Lxv8DqJDg7O//47rvvdjx1FTY2Nsb09PS2bAk8PDxITU2lo6ODysrKPVUX3w5cXFyW7GZGR0epqqrC3t5+1/3GVoO7uzseHh57JiBqb2+Pq6vrkhnxTsPHx4fBwUGGh4cpKCigra2N8PBwUlJStsyL8fb2XtlJ+eGHJpL60JCJpP6lL63Y74OpaiYMs1yiSkZ2gjLh6OiI27AFthJL3pmsWP0730T2ytLScksZKxNx3YW+pgKsnVX4265dchFFkZ5/TzDdvIDXxSrswyyJCrgcD6c4atv+Se9wGWAKCszpXlPHWRN4oxNGrUjzk8NMNc4jiiKzs7Nry4oIAjz9NNjZwdVXwzplUKlUygWRmdzufB4jBa1ce911PDvwAZP69UV7bQ8cQO7mhqyggIzERFxdXampKiPBZRgBI1VjblhabU/2ZDUsGixHR0fvSffbwsLCUnZor3WhFi2vhoaG6OnpoaOjg9bWVlJTU7fsNbnXmJ2dJS8vD71eT0ZGxra4sNHR0TQ0NKzIsl9wwQWSyMjIZKlUeni71/tpwf8CqxMQBCFQpVJdf+eddy5rGRJFkZqamh0hSyqVSpKTk1GpVOTk5DA2Nrat4+0V7O3t2b9/PyUlJWg0mj33ATsZ/v7+WFtbU7tOJmAnERQUxMjIyK4IwM7NzSGVSikvLyc0NJSkpKRtr4ItLS2RSqVLGUYefxzOOQfc3JaR1E9Gj3aUgtkmkqyD8FV8rAlka2vL/KSGI7bR9OhGqZ1fQ/piMXv13nuwsLAie7XVUuDETDdagysdDUX4JIXgNL/2ZDb4wTRjZRpcD9nimGiagAVBQkLYDajtAilteJbRyRa0Wu2mbU8WYe2jIPg2ZxRqGe0vjtL9/gg21jbrjweurvDMMybC//fXFqru7e3F09MTFwsVPt0Kqv+Rwy9u+C6/636dktmWNRcQglRq8hLUaJh8+23c3Nw4cOAA3m4qvGVtzGhl5DdszVNwPbS2tqJSqXaNEH8yDAYDxcXFhIeH71pJcyMsdifX1tbS3d1NSkqK2ffP6YAoinR2di59f+Hh4dvuWFQoFAQGBtLY2LjitT//+c9qJyenpwVBWMPS4f8v/C+wOgFXV9fnnnrqKadTV2EdHR04OTltW/RyEYIg4OvrS1JSEvX19dTV1X0iREUHBwdRqVQYDIYtSQXsJMLDw9FqtctS9LuFRePqncwyLiwsUFVVRWlpKSEhISiVyh0tcfj4+NDV1gZf/7opk3T22StI6oswiEZeHy/EVqLkbLvYZa/NtC3gkBeEY5YdLjJ73pusRC+uU4Y9etSUvbrttmXZq62orxuNBiame+jrnWZqbIh9CTHIjasPV6PFswx+NI063grXw8slP6QSOSmRt2GlVFNQ+ycMTG1pgWRhLyPwZifsIywZz9JiWe6Kpm8Dvt8FF8Add5jKru+8s+pbenp6lqQK7rzzTh599FEa3inh7zf/jn/05/LsyAeM6WdW3Vfu5obtwYPMVVUxV1+PIAim5pMAFZ72Rj6snqSmoXXHSudTU1P09fXtWonxZCxSDry9vU+r157RaKS6uhpXV1cMBsMnQqNwfn5+yU0jIyMDtVq9Y8f29vZmYmKCqanlQbufnx+33nqrs1qt/s6OnewTjP8FVoBCobgkLS0t/MCBA8u2Lyws0NHRsSsZGmtra9LS0rCwsCAnJ2fFjXomob+/n76+PhITE0lNTV0ynz5dnY6LFjSDg4Or84l2GDY2Nvj5+VFXV7et4+j1ehoaGsjPz8fR0ZEDBw7g6upKSEjIqqvALUEUcWtpwf2GG0yaSt/4xgqS+snImalnUD/JRapElJKPV+JjFRranh9F0AtMlixwtjyWMcMMJbMbqOHb2sIf/7gse6X4wQ/QmXl/T2n6WDBY0l5fCsB5h85Z9X2T9XP0/GcC22AFXherVg2aLOQ2pEbdgYCEGcmHlDU+R+dAPrNzI2bdw1ILCb6fd8AQOYU4IqX5T8O0vzCKpnedAOsXvzAR2q+/Hk7RY5uenkYmky0rTX7lK1/hqaeeovZ4Ce/d/Cc6pvp5dOgt8mYaMIorF2CLJcGJf/8b/cwMzc3NhISEcHm6G0aklHVLycrK2nZnstFopKKigtjY2F0nj4uiSHV1NXZ2dtuiX2wXOp2OwsJC7Ozs2LdvH0lJSZSXl++ot+pOo6+vj/z8fPz8/IiNjd3xcq0gCERFRa1qOfaDH/zA2tbW9n9Edv4XWCEIgqWDg8Ojjz322Aq3zLq6OkJDQ3eNSyAIAkFBQUsk6ZaWtVP/pwuTk5M0NjaSnJyMVCpFKpWSmJiIXq+nvLz8tGXbJBIJSUlJtLa2MjIysuvn8/X1RaPRbMn2Z5H0mZ2djYWFBZmZmXh6ei4FAa6urszOzm5vNTw7ayKlx8UhPXQIu+Zmpn79a1PmaI2JcFg3xfGpGiItvQmz9Fq61sGPpun+5zg2vha4XWWFqAe7MhsCFK4cn65hzriJzsyTslfCb35D4i23IBYUbPrjTEx3Ma9zxDskiXO/exsXpZ678iN3LdD56hhWHnJ8r1QjSNfORFlbOhHlez2WMg8Gxmoob3qed4vv553CH1DS8Awd/TlMawY39fxNugwQ/k033I7YMtu9QPPjw7S9MLJ6gGVpaZJgGBuDm29eJsFwqnbVIm666Saef/55ogPDucvnUvwsXPnvZDlPjbzPsG65npsgk6G67DKMGg39//wnrq6uKJVKnO3lJAdb0zoqJyhyP+Pj4+Tl5W15AdfY2Ii7u/ueELZbWlowGo2Ehobu+rnWwvz8PPn5+fj4+BAUFASYFsNxcXGUlJTsqGnzTkCn01FWVkZvb+9S08tuQaVSYWtru8KhQqlU8uijjzq6urr+f09k/8QEVoIgSAVBKBcE4T+nbP+2IAiiIAhb6vt3dnZ+4O6771avRlifn5/fk843Ozs7MjIy0Gq15OXl7Zle00ZYWFigvLychISEJZsDMAWE0dHR2Nvb77gzvDmQy+UkJSVRU1Oz6xm/xSxZbW2tWZIPMzMzFBYW0t/fT2pqKgEBASu4DoIgEBYWRkNDg/kX1tJi8vHz9IRbbzVN3I8/zlR9PU2ZmWvuZhRF3pgoQi5IucA+ATB11fX8e4KB96dQxVjif60TLmEOaJ1nGCmc5WyLWDRGLTnTm8zcnZS9kuj16MwIgCdmutAZ3XBw9eWia89HZbG8FD8/rKP9r6PI7aQmAVCLjYcyKSr8nC7h/JSHOJJwLzFBV6K2D2B4vJGK5hd5v+RH/LfwexTX/5m2vo+Ymu1DPCVLNDs7i7W1NTJLKa6H7Aj/hhtuR+3QdGtNAdbzI2h6Trk/YmLg5z83ZQ4ffxwwZYCGhobWnACvueYann76aRzkNhzU+HOWGMaIborHhv7LR9O1GE66Lgt3d6wzMpC0tOB90kLncLQdlnIJ71bPEh0dTVRUFFVVVVRXV5v1zI6NjTE2NrYUYOwmuru7GR0d3VPR0VMxPT1NQUEBEREReHp6LntNpVIRFBS0Zw00m8Hw8DA5OTm4uLiQlJS0JxywsLAwWlpaVtxHF1544SKR/ZC5xxQE4WlBEIYEQag5aZtaEIR3BUFoPvHfFQmQMxHCmXJzbARBEL4JJAJ2oihedGKbN/BnIAxIEEXRrNSFIAiBQUFBhfX19Y4nZ6VEUSQ7O5u4uLgdtWnZDMbGxqiqqsLf339T4m27BaPRSH5+PsHBwetqtfT29tLa2kpycvIKq5C9wqJX4f79+3fdr6y3t5eBgQESEhLWfZ9er6e5uZnh4WGioqI2xXPIz8/fHFHXYIC334ZHHoFjx0yyCZ/9rKnNPz0dBAFRFMnKyiI1NXXVgbZ4toV/TxRzqSqZeOtADAtGOl8dY7ppAZcDNridZYcgCAwPD3PBeWdznvsX+Oq3bic3tpbauW7udL0Qe9nmu7Qqi4rwCQ7GwWFz4+LxsocoaYogv7Cb628O5jNR53D8+HEOHTqEbtpA85PDiDqRoFtMpPLNoLm5GUtLyxX2K6IoMjs3xMhkMyOTzYxONDOnnQDAQmaNo30QjvbBOKmCGR/WYTSKBJ7CVzPMGxkpnGU4bxrDnIhtsALXQ3ZYe5/47o1GOP98yM6G0lIG1WoGBweJiYlZ95oNBsNSSedf/32DInkXtfPduMsduFS1H3cL0/fZ2tSExX/+g8xoxPWOO5CceBaLmmf4T8kkV2aoifS2RBRFuru7aW1tJSgoCC8vr3XHGL1eT05ODklJSbvelTc8PExDQwOpqamnzW9vdHSU6urqDd0kFqkQERERe3h1y2EwGKivr2d6epp9+/btmVfjIjo7O5menl4hu9HR0cH+/fs7hoaGQkRR3HQELwhCJjADPCeKYtSJbb8AxkRRfEgQhO8CDqIo3rPecc4EfCIyVoIgeAEXYgqiTsZvge8AW4oOXV1dn3v66acd1yKs73VQBSa9poyMDCYmJigqKlohzrkXWDQ5dXNz21AAz9PTk4iICAoKCk4bsdPW1pbo6GiKi4t3PXu2uIJdj9s1MDBAdnY2CoWCAwcObJo8Gh4evn7WanTUxNkJCoKLLzZ1nP3oR9DVBS+9ZOrGOzFJCoKAp6fnqtc5ZdDwzmQF/gpX4qwC0M0YaH1mZEmqwP1s+6XJNr/0NUrKKvnJm9+l/p02DiuiAZH3p6o29ZkWobS33zSB3WjUMzXbR3VlG//83R1Ihj/OwhjmjbQ9P4pBY8T/i46bDqpgbdV1QRCwsXLFzz2DxLAbOWf/g5yd9ABxIdfi5hjN5GwPNW1/53jZz6jq/gNj87nMzi1fw0mVElwP2ppKhGfZoenV0fLkMG3PjTDbrQWJxGTUbG0NV19Nd0vLqmXAUyGVSvnNb35DY2MjFx09n0xtIFepM5g2zPH48DHem6piTjtPV28vTldcgXF6mql3313aPyHQGhd7GcfKJ9EZTAbUPj4+ZGRkbKo8WFtbu9SJu5uYnJyktrb2tJoY9/X1UVNTw/79+zeUJQgLC2N6enpXDdvXw8TEBDk5OVhZWZGSkrLnQRWYmmQ2ILLfbc7xRFHMAk5tlb8E+MuJv/8CXLrFy91TfCICK+B3mAKopRFWEITPAL2iKFautdN6UCgUn9lrwvpmIZPJiI2Nxc/Pj7y8vBWibLuNjo4OjEYjAQEBm3q/k5MT8fHxlJSUbN6rbofh6OhIUFAQxcXFu877io6OpqmpaYVNi1arpbS0lJ6eHtLS0ggICDAr46hSqZBKpSu/w5ISk0WKlxfccw/4+sLf/gadnXD//bBGuXo1TStRFPnPRAkG0chnVEksjOppeXKYhWE9/lercUyyXvosY1PtiNZVPPHi15DJpDx87Bfoy0T224RQOddBv3bzEhTmSC5MzfZhFPU019Yilcs5K/WQ6QUjdLw8xvyQDt8r1Vh5mlfy2IzqOpgCLWtLJ3zdUokPvY5zkn/MOck/IT70emRGN/rGinm3+IcU1/+Z8enlHbJShQTXTFvCv+FqCrD6TgqwdGp46imoqMD9V79CtUlNoXPOOYe3336bzs5ODh48iO0I3OF6ATGWvmRN1/LYwNuo/Fyw9PXFJjWV2eJiFk7YJUklAufH2zMxayC/4ePuQrlcTkxMDFFRUVRUVNDU1LTiuRkaGmJ+fn5TAeB2oNFoKCsrIzEx8bRlvdva2ujo6CAtLW1TQYogCMTHx9Pa2srExMTuX+AJGI1GGhsbl7Jq5o4xO4mNiOw2Njbf2AEiu6soiv0AJ/77iZC6P+MDK0EQLgKGRFEsPWmbFfAD4P4tHlPm4ODwh0ceeWRFXaK+vn5XCevmwNXVlbS0NHp6eigrK9sTLtPw8DC9vb3Exsaa9cDa2dmRkpJCTU0NfX19u3iFa8PDwwNXV9ddNVAGkyVJZGQkFRUfi2YODAyQm5uLu7s7iYmJW5ZPWORaiXNz8PzzkJICSUnw6qtwww0mQvjx4/C5z4F8fckYhUKBQqFYtqKsm++hYb6XI3bRKHstaHlyGKNWJPAmJ+xCTRPK1NQUBw6kc88PvoSlhYrrrvgpF1+WzmsVL5P19wIyFBEoBQvemarY9OcyR3JhYqaLBazoqi/FPzwSpVKJYc6IbZkXM20LeF+iwi7Y/Al4fn5+yxO3lVKNo00UTpaHOSf5xwR7n83gWB0flf+cnMrfMjBWs+yeOznAcj/7RID15xFax9MY//wNeL72mongv5G34wkcOnSId955h8HBQe666y6sJAouV6dylV06c6KWY8pG+rVj2B45gtTBgfHXX0c8MV4EuikJ91KSVTfNlGa59IK9vT0ZGRkYjUZyc3OX7hWtVkttba3Z44C50Gq1FBcXExsbu2OSNuZAFEVqa2sZHx8nJSVlGZd0I8jlchITEykvL9+SF6a5mJmZIfeE8Xl6evppqaicCpVKhY2NzYrMuFKp5He/+53azc3tt6fp0k4rzvjACkgHPiMIQgfwMnAEeB7wBypPbPcCygRB2JRxla2t7ZeuueYaRw+P5cH02NgYc3Nze2rVshEWTYidnZ3JycnZ1Q642dlZampqSExM3FJLtaWlJWlpaUsKxacDgYGBKBSKVT2+dhIuLi5YWVnR2tpKaWkp3d3dpKWlceo9ZS5s9XoCnnsO0csLrrvO5O/3+99Db6+JCG6mjcjJxsxzRi1vTpTgLncgosuH1r+MILWSEHSL81L2Z2ZmhgsuuIDSsjKc3ZUkR9yCwsKGW2/+Nj7eLgwODzBbpuWgXSStCwO0zG8um2pOxmpiuosBnQ/97dXsT80AoPXZEWRTlqhiLFHHbb0stZ0gYdHGxlKhItL/Us7d/yCRAZczOzdMQc1jfFj6IF0DBRiNH+udSRUSXA58HGDN9evoCvkxY3f9AbGkxERsf/HFTZ0/LS2N48eP88QTTyxtE7umuUTYh1yQ8szIB/QyhcMll2AYG2Pqgw+W3nfuPnsMRpH3qlaW/SQSCWFhYcTExFBRUUFzczOVlZWEhobuagZpUQA0JCRkR7WWzDl/aalpvR4fH78lAU1ra2uioqIoKSnZNastURRpb2+npKSEqKgoQkNDty32uZMIDw+nubl5xcL/0ksvlTg7Ox8RBGE77Z2DgiC4A5z4r/lt2acBZ86vswZEUfyeKIpeoij6AVcBH4iieIUoii6iKPqd2N4DxIuiOLDR8QRBsLS2tr7/vvvuW7Y8Wly5REVFnbbU6loQBAFvb29SUlJoamqipqZmxx9ivV5PSUkJcXFx2xpM5XI5KSkpTExMUFtbe1o6ZyIjI9FoNLSfKIfsFhwdHamvr0elUm3fx2x0FO69F3x9cX/iCcbDwhDfeQfq601Cn1tsc3d1dWV4eBij0cg7kxVojAuc3RhP998msHS3IPhLH5O/Z2dnufDCCykoyOeb953FrTd+H5WtqQxkoY7k18+9QkJSAIPZEyRaBOEgtebYZMWq+kqnQqlUbnpVPzHTRV29BqNBzwVHzgJAbmsK9H2u2FpTkE6nMysbsRpONV6WyywJ9jqLs5MfID70OgDKmp7jnaL7ae5+F53+4wzdYoDlebMlBl8N3baX0/ez44jhEXDNNfCFL8Am1P3j4uJwdHRkYWGBa6+91jTZeodws9NZWEoU/GXkQ/o9bbBKSGAmLw/tiUyC2lZGaqgNFe0aekdX72pdzF6Nj48zMjKyqxmRRWscDw+P07KQXdSoUqvVREZGbmvMd3Z2xtPTk6oq83iHm8Hc3BwFBQXMzMxw4MCBTTd/7CUsLCwICAhYYf0lCAKPPPKIk5ub2+pu5JvDG8D1J/6+Hnh9G8faM5zxgdVOQ61W333nnXeqTu286uvrw97e/oxIr64FS0vLJZ+qnJycHa3tL3Yi7oR1hEQiIT4+HoDS0tI9MU0+GYseX319fbvCTzMYDFRWVtLb20tycjL9/f1bDyCHh+G73wU/P/jpT+G886Cykt4//pG+iIglMvpWIZFIcHZ2pmyggdLZVs4pTmD2XR324UoCb3BCZm0KWIxGI5deeik5OTnc+f0jfOGqa/FzT8dgFHm7bILjLQoq+wIZ823lX3l/Z6R4krPsYhnUT1Cp6djUdWzmOzIYdYxp+nGJzuRrv8vm4gvOQjSKzHYvsOC2NdV0MN8jcDVMTk6uquMkkcjwcU3hcMIPSI36KjZWrtS2/4tjhT+gpu2fzC1MLL23Z6Ab9wttcTvLjpEhN1pv+gfG+x+Av//dlL06Kcu0Hvr6+jh27Bh33XUXRUVFqGTW3Ox8FDupFc+PHmfk8D4kNjaMv/Ya4gnHgMxIW2yUEt4qm1zzt1hYWGB2dpbk5GTKysro6OjYlcVRbW0tVlZW+Pv77/ixN8Lc3Bx5eXn4+fltmke6Efz8/BBFcSk7vBPo6emhoKCAoKAgoqOjd12YdTvw8fFhZGRkRVY6MzOT4ODgWEEQkjY6hiAILwH5QKggCD2CINwMPAScLQhCM3D2if8/4/GJCqxEUTy+KLVwyna/zUgtCIKgsrKy+updd921bIQ1Go00NzefVkG6zUIQBAICAoiPj6e6unpV0qm5WBwMdpKkuugOr1arT4vWlVQqJTk5maamph31ZJyeniY3Nxc7OzuSkpJwdXXFycmJ5uZm8w40OAh3320KqH7xC7joIhN/6m9/g5gYQkJCaG5u3hEivpu3Bx9o6jjwfjTWZVY4pVjj+3k1EvnHQYpEIuHiS87lzu+fw0WXHiEm6Eqm5ww8+8EI+Y2zJARaIRVEPmyBH77xTf7wi4eJkHvjKVfz/lQVOnFjux+ZTLbhfTA928+kpT3CgjW+/r7Y2lij6dVhmBPROW5d8XqzxPX19re0tFw3sBMEAVd1JBkxd3Io7ru4qiNp6Xmfd4ruo6zxOSamexkZGcHV1RXXTFt8rnBA02ekyelWdMeywMrKxLv61rfWNW4GUyn64YcfxtHRkSNHjnDs2DHspFbc5HQUtdSWl6YLGL40E/3gINM5OQAo5RLOirGje0RLdedKvpsoilRUVBAVFYWjo+NSd3JpaemOPr+tra0sLCwQHh6+Y8fcLKampigoKCAqKmrbZfuTIQgCMTExtLe3b7s7WqvVUlJSwtDQEBkZGTg7O2+802nGelp8jzzyiKOrq+vjwgarIlEUvyCKorsoivITVaqnRFEcFUXxqCiKwSf++4kw2P1EBVbbhYuLy4/vv/9+1amlrs7OTtzc3HbUr223YWtrS3p6Okajkby8vI9Nd83E9PQ0bW1tG+rpbBUBAQFL3Y3m+sVtF3K5nOTkZCorK7f8/ZyM7u5uSktLiY2Nxd/ff2mSDQkJYXBwkMnJyQ2OAPT1mWxm/P1NquiXXw51dSa5hMjIpbcplUpcXFxWdPWZC61Rz79nKoh/JwKXVgc8zrPH8wIVgsR07VqtlvLycvQGLVGpCxw9P5Lk8FvoHTPyp2ND9I3puCLVgUuSHfCzm0bpdYT42Fj+9O7vaT7exrn2cUwZ58if2diSZzME9vHpTkYVKt546AGmukwNv9Mt8yCAXr114dztZqwW+VWbhcrWh6Twmzk76Uf4ux+gd7iM4+UPYrCsQG8wfQ6HWCsCrnVCN22gqdSPubcK4PbbTfdFcrIp0F4DDQ0NHD58mNzcXEJCQrjooot49dVXsZEqudH5CC5yFf+0aqfnYCTTH32E7oRjwL4AKzzUct6pnEKrXx60t7e3Y2NjszSRS6VS9u3bh5ubG7m5uTuSIe/t7WVwcJC4uLg9p1yMjIwsdR/uhom0TCYjLi6OsrKyLWfph4aGyM3NxcPDg/j4+G2Xr/cSLi4uzM3NrZBfiImJITU11U8ikZx9mi5tz/H/TWAlCIKHjY3NVTfeeOOyHm29Xk9HR8cKwb9PAhZJp5GRkZSUlNDe3m5W2t5gMFBWVkZcXNyudkF6eHgQHR1NQUHBnnsiWlpakpCQQElJyZY7dxbte4aGhkhPT19RDlo0aq6oqFh7QO3pga99DQICTB5+n/88NDSYOv/WMLUNCgqira1ty4O01qjnr/1Z+L7mhtOgHYoDWpzTPqYW6nQ6rrzySjIyMng/949MzfaREHojtT1Knnl/BJlU4JaznYn1M2V64v1kWMjg8jt+ydT8JD954EF8Zc6EKT3Jnq5j1rD+97sZAvvYVAfNHRoqP/wn+llTMDDdsoCVhxxRvvXs3dzc3LYyVqOjo1uajK0tnYgJ+jzn7v8J1pIYZnVtfFD6IINjJvV6mwAFQTc7I0gEWl6aY+obv4E334ShIUhMNAVZp2Qtp6ammJ+fx9nZGVdXV44fP85FF120JBFjJVFwg9NhPC0ceSvMSHOoAxOvv45oNCIRTPILUxoDOfUfLzZmZmbo7u5eVfDSy8uLxMREqqqqaG1t3XJpcGRkhNbWVpKSkvacfN3T00NdXR0pKSm7SvdY9DesXicoXg16vZ7Kykra2tpITU3d0WzaXkEQBMLDw1dtHPrNb37j4Ozs/KggCP9fxBz/X3xIAG9v70e/+93vqk+tU7e1teHj4/OJWhmcCgcHBzIyMpbsUzabGaqpqcHX13dP/L/UajWJiYmUlZUxfIoZ7W7Dzs6OyMhIiouL0es3LlmdjKmpKXJzc1Gr1euuIG1tbfHy8lqZCu/qgq98BQID4U9/gi9+ERobTWKRwcHrntvCwgJPT086OjrMumYwBVUv9mfj+5objkN2eF1uz6BF19KkqNfrufrqq3nttdf4zg9uZY5GAj0vIK/Zg/+UTBLgpuDL57rg5vDx5/VwUhGsHGXBOoKLzr2IV/L+Ss4/szjbLhadaOD4dO2617SZwKpN00dHvunzHsw8gH7OiKZHi+0W5BVOxnZLgRMTE9viHxoNMpRiJAfjvoNcZkV+zSNUtryC3qDF0lVO8C3OWKhltP91lFG3g6Zs1fnnm8qCZ58NJ2Uu6+vrCQ8PX8r42Nvb869//YvY2FgA3n77bRSCnOscD+Fn4cIHGc5UWk8zW1QEgK+zgigfS3Lqp5mY1WM0GikvL1/XYNnGxob09HQ0Gg1FRUVmlwanpqaoqakhKSlpT8daURRpaWmhu7ub1NTUPdHJ8vX1Ra/Xb1o8dGxsjJycHOzt7dm/f/9p0/LaCSx2d55Kv/D29ubIkSOeVlZWV52O69pr/H8RWAmCEGJvb5+ZkpIiycrKYmBgAFEU0Wq19Pb24ufnd7ovcduQyWRER0cTEBBAQUHBusrgYErJa7XaPXWPt7W1JSUlhfr6+j1XLHZ2dsbf35+SkpJN85YGBgaWMnq+vr4bli4CAgKYnJw0SWK0t5u8+4KC4M9/NmlQNTeb/jYjOxoQEEBXV5dZAeFiUOX9uiuOQ3b4ft4Rp1hbrK2tmZiYwGAwcN111/H3v/+dn/z0XuIOGLCxTiSnOZGKdg2Homy5JtMRy5P897S9vehfeYXksn+jEAyc/aUHifSJpCtnGEeJLfFWgRTPNjOqX5tfslEp0GDU0a+U013YiMrZm6hQX2ZaF0AE26DtlenXUl3f7L5KpXJbWZbu7m68vb1R2XhzKP67BHoepb3vI46X/ZTx6Q7kdlKCbnLCxl9Bz2sTDFQrEP/5T9P9UlhoIra//PLShLWWPMGxY8e44IILuOWWW5AaBb7odJAgpTtZB93J7SlCf6Lz8Jx9JnHSdyumaG5uxsXFZcPAUSqVEh0djbe3N7m5uZsur8/NzVFWVkZ8fPyeKoSLorjkI7p///49C+gEQSA2NpaWlpZ1vyOj0Uh9fT11dXUkJSXh5+d3xnWkbwWLWStRFDEYDLS2tpKdnc1dd91laWtr+3NBED65WYxN4v+LwMrNze2xRx55RB0dHU1ycvKSmGNlZSVBQUFndLeFuXBxcSEjI4OBgQFKSkpWNQyenZ2lubmZffv27fmDrFQqSU1Npbu7m5aWlj2VY/Dy8sLR0ZHKysp1zyuKIk1NTbS1tZGWlrahvcUiBEEgztcX7Y03IoaEwF/+ArfcYjJKfvxxE1HdTMhkMnx9fTetC3ZyUOU0aAqqVJGmyWxR0+rpp5/mpZde4sGfPkDiESMafQTFHecxPmPgmkw1R6LtkJy4L0S9nsl332X4yScxLixgdLAlZrCUYa2apx5/jij7VNoLazlsF4VMkPLe5NpGCBtlrCame5iwcqC7rBbv0GSc7GRMt8wjVQpmq6yfClEUtxwYmcuvWu3cvb29S3ZIUomc6MArSI++E4NBS1b5r2jofAtBIRLwRUcc4qwYPD5N9+uTiDfcBJWVpnLxF76A/uqrCV8nMD/nnHO47777eOqpp/jsZz+Lfl7H1Y4HCJW6kpvqzPuV/0EURVTWMjLCbanumqOhe4rgDbKnJ8PDw4O4uLglgvV60Ol0FBcXEx0dvennaCdgMBgoKSlZ4j3tdelRLpcTGxu7Jt9qamqKnJwcZDIZ6enpu24ZtJews7PD0tKS6upqsrKyMBgMHDhwgOTkZG666SYHlUr11dN9jbuNT31gJQhCYmBg4L6DBw8CplXzvn37CAsLY3h4mO7ubsY3oR/zSYJcLichIQEPDw9yc3OXDX6LonixsbGnrfwpl8vZv38/09PT1NTU7GlwtRhINzauTrbW6/WUlpaysLBASkrK5p3iRRFefRXL+Hjc336bkSuugLY2ePRR2Ga3pZ+fH/39/asGySdDa9Tz0hpBFZh0t8bGxrj++ut5/fXXyLzAno6RSOoGLsLOUspt57oQ6vnx+7W9vQz98Y/MZGdjtW8frl/9KoazziJSOoDSME+1Qc2EtJs//PQZLAwi6TZh1M5307WweoPuRhmrxsEqpmZ02No5EhabilwqMNU8j02gEkG69QWAXq/f1uLpVP0qczE+Po6tre2K583ZIZTDiffi6ZJAQ+d/yK74NbPaYbwvVeF62Jbxcg1tL4xi8PSH7Gxm774bl2PHsPvxj9c8lyAIPPDAAzz88MO88cYbnHfeecxMTnOV6yHCNDbkBst4p/ldRFEkNcQSpVRH7YQnAxPmlcjt7e1JTU2lubl5zQWS0WikuLiYoKCgXSGLrwWtVktBQQHOzs7LSqZ7DQcHBzw9Pamrq1vaJooira2tS6XX4ODgT0WWahGLi4iJiQn6+vpIS0sjJCRkicP7ve99z9rS0vIeQRA+PZHkKvjUB1Zubm5/fPTRR1c81d3d3cTHxxMZGUljYyNFRUV7TqzebXh4eJCamkpbWxtVVVXo9XoaGxvx8PA47UJzi4RvuVxOcXHxnmldCYJAdHQ0U1NTdHYu93mbm5sjPz8fZ2dnoqOjN7/K7e2Fyy4zEdK9vKC4mI5vfYv+HVolSyQSAgIC1pV0WAyqvFYJqkRR5MUXXyQyMhKpVMrQ0BC+4VIK26LonTpItK8Vt5zjjKOtafBbylI98QTGhQUcv/hFHC69FImlJU5ubswkxRM320DbBORr8vnDm7/l1//3E9JswrCRKDk2tbqlkFQqXbcM26QdxFplzQ8e/YgLLr+O+SE9+mnjaS0Dwvb5VV1dXWtKmVjIrEgMu5HEsJuYmRvkw9Kf0tGfg+shW7wvUzHTvkDLU8NoZ6Hs4ovRfvWr8Ic/bKjWfscdd/Diiy9SWFhIXl4eUkHClQHnE96jJ9d6lGMjxTQ31XNRtIjSQsKzH4zQPbJ+4H4qFAoFqampzM7OUl5evuwZXhQAdXV13VMitkajIT8/n8DAwDOC4hEQEIBGo2FwcBCNRkNeXh7z8/NkZGTsCbd1ryCKIoODg2RnZzM6OkpaWhpeXl4rMpq2trZ8+9vfdnBycvreabrUPcGnOrASBCE5KirKf5HUuYipqSk0Gg2urq7Y29uTkpJCYGAg1dXVlJWVbdp645MApVK55NZ+/PhxhoaGzpgOyEXtExcXF/Lz8zfMyOzkeRMSEuju7mZwcBAwZRUKCgqIiIjYPO/MaIQnnoCICDh2zKRHVViIEBdHTEwMDQ0NLCws7Mg1e3t7Mzw8vGpn44qg6nOO2EcoEUUjVVWVHDp8iGuuuQZra2ssFFIqWsr4T4UPU/PBnBdnz2dTHbCQmYYCbU/Px1mquDhc77gD5UmG5CqVirG5OTIvikdpmEMVfpAo7xh+9+ifmRzr44hdNN3aEernV+fQSSSSVYNoURTps5Kjmp5hbBZc7OVMN5s+q23Q9si82wms5ufnsbCw2HIpSa/XMz4+vmHGy8slkSMJ96G2C6Cy5SUKah/DKlJPwBcd0U4YaPzTIHaTTkh/+ms4cAC+9CXYQOn7qquuoq2tjQsuuAAAnU7PFQHnEVE/QZ62lXJpD9Fhftx01AlLhYTnPhyhc9i8+1UikRAbG4uDgwP5+flL93t9fT0KhWJPx5rJyUkKCwuJiYnBzW1T7ma7jkV9q4qKCgoLC5e6uD9N9JPR0VHy8vLo7e0lMTGRmJgYlEolISEhtLS0rHjev/KVrygsLCxuOeH5+6nEpzqwcnd3/9XPfvazFdmqU7tqwFQmWYyyS0pKqKqq2hNjzb3AoiWORCJBEAQaGxt3RHhyp+Dn50dQUBB5eXl7FtQuCojW19fT2tpKVVUV+/fv33zJoqkJjhyB226DhARTF9fdd8OJlLdCoSA8PHyZUfN2IAgCLp5S3iv+IW/n38Nb+d/hzbxv83ret3m08Rm8XnfFcdCWoejXOD72bf710Ve45Mo44uLjKCsv5PZvHeT7v0qiYaKYkoEojKIV1x9WkxZmgyAIiDrdEpdKXFjA8dprTVmqUzqUpFIpcrkcqaMD6T4CfQpXvnHl7QxPDfODb95DnFUAzjI73p2sxLCK1c1a5cC+yR7mFUoe/ezPef/V3+JsJ2e6ZQGliwwL++1NQtvpCNyqzMIi+vv7cXd331S5x1KhIi36DqIDP8fwRBMflPyEaVUDgTc6oTfooMiOmt+M0H7pYxis7DFeegXiBjSGxWzRO++8Q1BQEDXd3ZwrCyOkcYI2u0n6deOorGXcfNQZG0spzx8fpX3I/MWAv78/oaGh5Ofn09DQgEajIfIkXbbdxtDQEOXl5SQlJZ32bPzJWFhYoLq6Gmtra+zs7Pa0JLrbmJiYoKCgYEkHMT4+ftlzZmFhgYeHx4quZqVSyR133GH7aeZafWoDK0EQIry9vcMTExOXbZ+YmEAUxVW7agRBwMXFhQMHDuDk5ERBQQF1dXV7lknZTTQ0NODr60tmZiYSiYTc3NxtKwTvJNzc3IiNjaWwsHBHrXrWw6KcQX19PTExMZubfHU6eOghU5dWRQU8+SS8/76p++8ULIrOblfkE8Bg0NI99l+MooiTfSSeTvG4uSTS65pMzIfpOA7aIT3YhmeCNyE+5xHudyFSozOf/8L5vJf1HHd9/fsIittoG/scdkod54XOEuBmojloe3oY+tOflrJULnfcgXIdMrOjo+OJdH8A1hI92pAEzok6n+dffo3aulzOsdvHqGGa0tmVhPu1COzlA6XMDI7TWteO3EKJo5WU2c6FbWerYHuB1XaJ64vdgJuFIEgI9DzM4fjvYqlUU1T3BKUDTyG5cJSgLznhkmGLztKFtov/iNDZwUzGlXT/a5TJ+jkMC2svlnx9fZFKpRw6dIhXGhpJ7bNEOafntd4PMYpG7Kyk3HTUCXsrKS8cH6V1wPxFpbOzM15eXrS0tBAQELBn3KGuri4aGxtJTU3FxsZm4x32CAMDA+Tl5eHj40N6ejp6vX4pQ/5JxszMDMXFxdTX1xMWFkZSUtKa2mCBgYF0dXWtyFrdcccdlgqF4huCIGyvK+UMxac2sHJ3d//5z372sxX59+bm5iUhvbUgCAIeHh5kZmZibW1Nbm4uTU1NZmsgnSkYGxtjYmJiabALCQkhJiaGsrKybQn+7TQcHBxITk6moqJiw26jnUBLSwujo6OkpqZSWVm5cdmurAz274fvfQ8uvNBkkPylL63r5xcVFUVbW9u2M3Etve8ztzBOuM9nkcxFEh74WWqtXAk9FoXToB1+n1NjdFTxlRt/i27Sh3C/i/jH397hpeffJC7ys1R2J1LR6UKMryW3nx/A7Pg4Rq2WyXfe2TBLdSqcnJwYHR1FLhPI3Kemz8aD28/5POkBh2koySdY4YafhQsfTlczb1yud7RWxqpZOsVQXgUAPmHJWI8ZEA1gG7x9N4TtlALHx8e3nAHRaDSIorilji9bK3cO7rubEO/zGJ2uoWv6BToN/0V9UELI7S74/f5iNN/6GbZ17yJ/7Bd0vDRG7UP9tD47wnDuNPPDumXPdWhoKHl5eXh4eHDXXXcxHBDCoU4ZAxZacurfN53TUsqNR51Q20j5a9Yozf3mBVdjY2P09vaSkZFBVVXVruvVLXbv9vf3k5qaesY4Z+h0OsrLy+nq6iItLQ03N7clCYa6uro9t/faKWg0GsrLy6moqMDf35/U1NQNuYcymQwPD48VHoq2trZcd911tjY2NtevsesnGp/KwEoQBD8HB4eUw4cPL9s+MzODVqtdUwPmVEgkkqUsj0wmIzs7e1tK2KcDBoOBqqoqYmNjl60gF53s5+fnyc/PP2N4ZdbW1qSmptLY2LijhqYn42R9m+TkZBwdHYmIiFhbQHRuDu65x2Qz0t9vMsz9xz/A3X3Dcy3qi5WXr07o3gzmFiZo6noHd6d9BPkmMbug4a+9x/F8zRXHQTtU50q47/F7iI+Pp7a2dkkjTCKRMKkx8PT7I9R0zXF2rB1XpDqgtJDhtLDAwKOPMpOTg1V8/IZZqpPh4OCw1EmbGGSDnaWEgdhEfnPV7/EZS6drMJ9z7fcxa1wgZ2a5CvNqGatx7RTjVnL682qxUFjiFxyNrkuHIBew9tn+ZLnVjNXCwoKp7LlFPsx6pPXNQCKRYUk0/k5X4+YYSVP3O7xTeB+17a9hVGqw/vm34OqrcX3/l4QEluOUYoN+xkDfsSkaHx6i4XeD9PxngqmmeYxaI46Ojvz0pz/Fw8ODz1x6Kd7BafiOinxkOUh/RSEANkopNxx1wslWzotZozT2bk5seGZmhsrKSpKTk1GpVEt6dX19fVv+/OvBaDRSVVXF3NwcSUlJu+ocYQ5GR0fJzc3F0dGRpKSkZcGeUqkkODiYmpqa03iF5mOxnFlSUoK7uzvp6elmdckGBATQ0dGxgn5y991321hbW98rCMKnh3B2Ap/KwMrNze3HP/nJT9SnpqKbm5vN0mtZhFQqJSAggAMHDqDX68nKyqKzs/OM4imthYaGBry9vVdNkUulUiIjIwkJCaGoqIju7u4zInu12G3U399PY2Pjjl6T0WikrKzMpDl1kr6Ni4sLPj4+lJaWLj/f8eOmst8vfmES+ayrgyuuMOucjo6OODg4bFqL6lTUd7yBKBqI8r+MBVFHh70en3974DhoR6HyGEmX7uOxxx7j9ttvp7GxkQsvvBCA7hEtjx8bYmRKzxcy1aQHyJktKmLo4YdxyM1FPz9vylJdcsmGWaqTIZVKkUqlpsBDKnAw0o4+uQM66wFGWuG+bz6Ak6Ak2tKX/JkGpgwfB1KrBVY1/aaJpqu8k4DwBNwcrZlumcfGz2KZUfRWYTAYtjTxbodfJYriEr9qq1i024oISSYp/EscSfgBbo7RNHe/yztF91Pb/hoLj/waISoKy29ej0foOKF3uBL+TVc8L1ahdJEzXq6h/YVRah7qp+7PPeyPSOftt9/mK1/5Ch7e3lwacgFGqYT/zlSiqagAwFoh5YYjTriq5LycM0Z9z/rB1fz8PCUlJcsEQBf16jo6Omhvb9/yd7DW91JcXIxSqSQmJmbPNapWg8FgoLa2lsbGRpKTk/Hx8Vm1FOrp6YlOp/tElAR1Oh319fXk5+fj4ODAgQMHlrJv5kAul+Pi4rJCtNrZ2ZnPfOYz9hYWFpfv5HWfCTj9d+QOQxAEVysrq/MuueSSZZ9tbm6O6enpbTmFy2QyQkJCSE9PZ3Z2lqysLPr6+s6IYGQ1nFwCXA9OTk6kp6czMjJCcXHxjnWybQcymYykpCTm5+epqqrakSB2UVfH3t6eyMjIFQOEj48PKpWKqqoqEyn41lvh8GFT99/775tUsLdYFgoLC6Ovr89sSY+J6S66BgsI8DjMbK+C/GdaiX0lBPWwLU7nK+id6yQ4OJiSkhIeeeSRpWxsRbuGZ94fRi4TuDFRilv5+wz86ldMvvkmgkKB6rLLaE9ORubvv6XPs8izAogLsEJlLaUsNJCC9vd54eV3eeyJ+znLLgajKPLB1Me+aauVAusWelDMz3DW0VSi0i/HXSZBO2rYto0NmH7zrXJ9tsOvGhkZwcHBYVuZlPb2dry9vZf0r+ysPUgKv4kjCffi7hhNc897vFP7EE2/uw3RYDAF/PPzWKhkOCVZ43+NI5HfdSfgOkfkoUakEwpGX9GjGvTgh/f9EIlEwtzIDOmKUNr9bSkvexfNCY87K4WEGw474e4g55WcMWq6Vg+uFoOcyMjIFfIBi3p1w8PD60qFmIOFhQXy8/Nxd3cnNDT0jNCAmpycJCcnZymYXC87utgleCaXBPV6Pc3NzeTk5GBpaUlmZiZeXl7b+q4DAwNpa2tbMVfee++99g4ODg8KZ8IPuYP41AVWLi4uP7jvvvtUp65iWltbCQwM3JEH0cLCgoiICFJSUhgZGSE7O5uhoaEzKsBaLAFuVl1dLpcTFxeHt7c3eXl5DAwM7MFVrg+JREJMTAyWlpZb8vk7GQaDgeLiYpydnQlahWi+iJCQEBQtLRhCQ+Gpp+Db3zZ1/B05suVzw3Kj5s0GiaIoUt38d1RDiQj/3U//c9NYDypp9ahjKL6eLmMz9913H9nZ2cTFxQFgNIocK5/knwXjeFrp+ezIe/DMo8yWlqKMiMD51ltxue02rOPicPPy2tD6aC0s8qwAZFKBg5G29MzC5V+4hkDnUH75k2cxTI2w3yaYck07g7oJwHSfnfw7zhrm6bPS46AZ4+4f3Et4+udxPtFTYbdN/SrYPr9qs7SBU7HdMqBOp6Onpwf/VQJfO2t3EsNv4mjifbg7xVInq6P4e5lQVob+9ltMYrUnIJELSNwNDLq2Evo1V+xClQy8N0Xzn4cZah0lOTmZp77xK5wEG3IzPRh6/Z/M1Zo8H5UWEq477ISXkwWv5o1R1bE802g0GikpKcHf33/NBatUKiUxMZHJyUmampq2/H2AyTEiPz+f0NDQbX23O4VFjldlZSVxcXGbnl8WS4LmGjXvNoxGI+3t7WRnZyORSMjMzMTPz29HMoJKpRKVSrUiU+fj40NmZqaTRCI5a9snOYPwqQqsBEGwt7CwuOqaa65ZtkzUarWMjIzsuFDdYio6ISGBnp4e8vLyliab042Wlha8vLzMJs66u7uTlpZGV1cXFRUVp52wv0i2d3d3X6aTYw4WgyoXF5cNs3cCEPrYY4haLQOvvw6//CVsw7z3ZNjZ2eHu7r6m6vuya5430vJOI1Zvn49D1blMLGiozmxj7EgHt977Bb753W8glUqZmJhYGvjmtUb++uEQuQ0zRM02cXbxM8jHBrE76yzcvv1t1JdfjoWX19I5fHx8tuzZ6ODgsMxodZ+/FQ42UkpUNnzrvB/QPzDGD++9lQM2ESgEGe9MViy9VxCEpeCyfrQZURDQtbQyM2vKBloNG7BwkGLhuH3ezFYDK61Wu1TyNBc6nY7p6elttf23tLTg7++/7vltrdxIDLuRo4n3I73kchqvS0D27Av0/PR25rWTgGnyr6ioMGkL2Vvgd5Ujvp9Xox03MPDCPDd95su8/NLLNP3ufWYsJZQd8mfs1VeZqzdx45RyCdcedMTX2YJ/FIxT3ja7dNzKykocHR3xOumeWg0SiYT4+Himp6c3de+vhvHxcYqKiti3bx8uLi5bOsZOYnZ2ltzcXAwGAxkZGWbb9SyWBEdGVncp2EuIokh3dzdZWVlotVoyMjIIDAzcca2toKCgVVX6H3jgAQcXF5df7ujJTjM+VYGVWq3+5re//W27U60j2tra8Pf337W0sbW1NfHx8URHR9Pa2kpBQQGTk5O7cq7NYHZ2loGBgQ2DiLWgUChISkpCrVaTk5NzRgSLPj4+Szo5s7Ozm95vMahyc3NbdfW/Am+/jfDBB0h++EOa7e13vDsxKCiIsbGxFe7vi9BO6un77yR1vxpAk2uLzm6O4vPryf9CLR72cM2Fn8XKyoo33niDyMhIGhoaEEWRgeYe/vSPVloHtRzoz+KIrBPnL1yJ6113YZuZiXSVANvS0hKJRLJpM92TIZPJkEgkS1IkUonA4Sg7eqb1ZFx+IemBh/jLc1k0vvcKmbaRNC/00zpvyoIqlcoljbjaqTaU8ws89eP/cvVnr0AQQezTYxuk3JHndavE9e3wq/r6+vDw8Njy9S8sLDA4OLjprIytlSsJYTfg+cgbTGZE4f6jJyl69laqW/9OfWMFarV6WeZNFWVJ6B0u2IVZ8lnnm7jywHU8+svfM/q3air95UyEeTH2t78xfyLDpJBL+OJBR/xdFLxWOEFp6yyNjY1IpdJ1s78nYzG4mpmZMTu4GhgYoLKykv37929LAX8nIIoiHR0dFBcXExERQXh4+JYyOoIgEBUVRW1t7Wnj6i7yALOyspiamiItLY3Q0NBdszqztrbG0tJyxXwSFhZGVFSUlyAI+3flxKcBn5rAShAESwsLi9tuueWWZfUDvV5Pf3+/WVoyW4WdnR3JycmEhoZSV1dHSUnJliat7aKmpobIyMhtpXAFQcDHx4fk5GQaGhqora097d2QLi4uxMXFUVRUtCl/x8VShaur6+bsLfR6+M53ICgI6Ve/SnJyMnV1dTsaJAuCwL59+5Yshhah6dPS+fcx6n87yHDBDIL3OA2Zr3Ls8iY0AfPs73Xhc+ddirW1NR9++CGBgYHY2NjgoNNR9PgrPFW4gMYg4QrrVg5dexZON9yAZXg4wgarTm9v7y3rbJ3MswKI9rXE0VZGrkTLt86/nwsSLqBlKofYYSkqqTXvTFVgFMUlntWCUUeHxSx240M01Q8QHJGIyzyIOnHbNjaL2GrGajv8KnO1q05FU1MTQUFBZj+/NrYe2L92HMHdk5T/e4+e2rdpHnoO/4CVGSW5jRS/K9X4XenI9877CRlBh3n8279gIK+Z7EOeSF1cGH35ZeZbWgCwkEm45qAjQe4KXi+aoLZHT3R0tFnB42LDyPT09KY5V52dnbS0tJCWlrZlLbKdwvz8PIWFhUxNTZGRkbHlMvEirK2tcXV13XFy/2YwPDxMTk4OQ0NDJCcnExkZuXlf1G0gODh41d/+zjvvdJTL5ccEQagXBKFWEIQ7AQRB+D9BEHoFQag48e+CxX0EQfieIAgtgiA0CoJw7knbEwRBqD7x2h8W+VuCICgEQXjlxPZCQRD8dutzfmoCKzs7u1u//OUv25768HV0dODj47OnnSMODg6kpqbi6+tLRUUFFRUV65rP7iQGBweRSqXbMo09GVZWVqSlpaFUKsnJyTmtmTgwyUTs37+fqqqqdXlgi0GVk5PT5jJVAM8+C7W18LOfgYUFCoWCxMTEHbc5sra2xt/fn9qaWqYa52l9ZpjmPw0z1TiPc4oNAV+1onjfa9SFueAmd+Bmp7N5/olnsLa25vjx40s2IfrJSYZqR3jLLh1bpZTbLnAn+pJDyM1o0HB3d2dgYGBL/MCTeVawmLWypW/WQOChGH5w8A9Y27jRlP0MhyUB9OvGqZ7rWOoMbJrpxiAVGK6sYWFeh3doMr5aASRgE7AzgdVWM1ZjY2Nbmjinp6eRyWRb5nVpNBrGx8fx9PTc0v44OiL512vIx2bZ/39FCAsa2vo+WPPtqihLIu/04I/3PsMXkm7ihu7PMzOspf3KA8idnBh98UUW2toAkEsFjobqcVTMUT3qQJeZ3oLwceZqYmJi3S5ZURRpaGhgcHCQ1NTUPZn010NfXx/5+fkEBAQQExOzY/IOwcHBdHd375nLx9jYGHl5eXR1dREXF0dsbOy2fDTNhZ2dHRKJZIUIdEJCAiEhISJwBZACfFUQhIgTL/9WFMV9J/69BSYBcOAqIBI4D3jsJNmGPwK3AsEn/p13YvvNwLgoikHAb4Gf79LH/HQEVoIgSCwtLb/1ta99bdkIajAY6O7u3rz32w7D2dmZ9PR03NzcKCoqoqamZlc77gwGA/X19TtuJSEIAoGBgcTFxVFZWUlzc/NpJepbWVmRmppKa2vrCrsEMA3KVVVV2Nvbb96rbHYW7r8fUlOXySnY2NgQGxtLcXHxjirwu9l5YPzAlva/jrIwqsf9HDsivuWGx3n2vD39Fu1OAfjKHbne8TDWUgWPPvro0sAOJqPkD/9ZyHGndFwsF7gwQYqj2vwAQiqVolartyTmeCrPCiDKxxJnOxl5Uh2CXMLAhx789O1jOL56DHepPe9NVWFhqUSj0VA71oRiQU9HqSkr4uyfiPM0WPtYIFXszNC0lcBKp9MhkUi2NHl2d3dvi1jd2NhISEjI9sqg8fH0/vCHOFTUcuj7x+ls/C/z2rW7UWXWUqKu9+Xhp36Prc6etJfCqfx3G7KrP4dMrWb0r39loaOD8fFxmhobuOEcL1RWUl7JGWNy1nwOpkQiISEhgeHh4VWzpUajkYqKCnQ6HUlJSafVV0+n01FaWkpfXx/p6ek7zu+SSqWEhoZSe6JhYLcwNTVFYWEhzc3NREZGkpCQcNpU6lfLWrm7u/OrX/1K5e7ufr8oitNAPbDe6uIS4GVRFBdEUWwHWoBkQRDcATtRFPNF0yT1HHDpSfv85cTffweO7lY34qcisAKOHj161ObUFWZPTw8eHh6nVTxOEATc3NzIzMxEpVIteWntRqvtImF9t1YgdnZ2ZGRkoNfrycvLM4vrtNOwsLAgJSWFoaEh6uvrlwV6DQ0NSCSSDRX2l+E3vzGJf/7qVyuU1NVqNaGhoRQXF+9IOXSqaZ7mPw0jm1MyEzZA4FfVuGTYIlEIvDGcRY1CgrdBQnSvI2cfOsrg4CByuXwpiyGKIm+/XkG2MpJQex03nOtFd2frlrkaPj4+WxJjXeRinHwvSyQCh6Pt6JszIIZaUF3Wwz9fKeefffmkFA4zadDQKB9idk5DqzCO68gU9VX9BAYFIpWoUU6LO2JjswidTmc2Z2R0dHRL2Sqj0cjg4CCurq5m7wumbNfs7OyW91/E6OgonZmZ8Ne/YlvRRurX/k5b+Ssb7qeKtCT0q858+99f4jffuYeyJ/uwufBapPb2jLzwAg1ZWSQlJWFvo+TqTEd0epGXcsbQ6c1fZEkkEhITE+no6FjWKabX6yksLMTW1paoqKjTKqewWC5zc3MjMTFx17Jmbm5u6HS6XeGyzs7OUlpaSk1NDcHBwezfv3+FLMZeQ61Wo9VqV9BkzjnnHCwsLI4KghADxAGFJ166QxCEKkEQnhYEYbEjxBM4OSrvObHN88Tfp25fto8oinpgEtgV88ZPRWDl7u7+o3vuuWdZC84iyXDTZaBdhiAIeHl5kZmZuVRWW835e6vQaDTbIqxvFhKJhPDwcMLDwykuLqazs/O0Za+kUilJSUno9XrKy8sxGo20tbUxOztrHv9jcNAkAHr55ZCWtupb3Nzc8PT0pKysbMufVzSK9L8/RfsLo8jtZYR82QX/Q+5U11ZjEI28Nl5IibYX1+lhoga8OPesc+jq6lpWhjSKIm8ca6FA606kxThXneeLtZUSNze3LSvVq1QqZmdnt5SRc3R0XJG1ivBW4qqSkSfTcU3KTXg4efD7V46jbKjHf1JKkb6NNoZZkIGTbo4v3pzJjx78DS6LMgs7YGMDLP1O5k7Oo6OjWyqlDw8P4+jouOUMS2NjI2FhYdsKJnQ6HdXV1cTFxSF84QsI//43tr1T+FxxN3ONFRvuL7eR8cBv76dttIUfPHEH9U+Powv6PFpBim97O1YnhGRd7OVckeZA/5iO14vGt/RMyGSyJSP0sbEx5ufnycvLw9vbm6CgoNMWVBkMBqqrq2lpaSElJWXrZdlNQhAEoqOjqamp2TEi+9zcHJWVlZSVleHt7U1qauq2OWE7iaCgINpOlJgXIZFIuO2222wFQXgLuEsUxSlMZb1AYB/QD/z6xNtXuznEdbavt8+O48zwAdgGBEEI2LdvX1BMTMyy7SMjI9jZ2Z322vypkEgk+Pn54e3tTXt7O1lZWfj7+2+bB1ZdXU1ERMSeccnUajUZGRnU1tYyMDBAbGwsSjPUu3cKi901ra2tfPTRR0uZLLMG5f/7P5ifN5krrwM/Pz/m5uaoqakhOjrarOvUzRjoenWcmfYF1PFWeF6oQiIX8MCDnoE+nu19j05hFPexTjx7Hbnw6ouxs7Pjww8/XFocGIwi//qon6pxK/bpO7jkc/uRSkyfMzAwkJycHLy9vc2e2AVBwNPTk97eXrMXIo6OjoyMjCzLskgEgSPRdryUPYY8wo47D93HPX+/nadGqrnumA0dnwukVj2KTGdEYRglMjIKnT4cXRcYLAwUNuTBKo1j09PTHD9+fNXrVyqVKBQKlErl0j8wZdWMRqNZz8Xo6Kh52c4T6Orq2pKzA5jM4XU63ba5kbW1tQQEBHxc/jzvPHRvvY7FZy6FzCPwQTZsQBU466yzePzJx/nSTTfzg4/u4uc8gnXQJVi0vsxsSQk2+03NW2GelhyJseP9qincHORkhK9uxLseFAoFycnJ5OfnAxATE7MtEeftYnx8nMrKSnx9ffc0Y3YykX3T9IVVoNVqaW5uZmRkhODgYGJiYs4IEdVT4eLiQn19/bKMsk6n491331VYW1vbzMzMvAYgiuJSOlMQhCeB/5z43x7g5A4RL6DvxHavVbafvE+PIAgywB5YvT17m9jzwOoEwawE6BVF8SJBEH6MqfZpBIaAG0RR3LTBlIuLy3e+//3vr0jntbW1ERYWtlOXveNYbFX29fWltbWVrKwsAgMDt6Rwu0hY3+sBSSaTERsby9DQ0JJw305rhW0GgiBgb29PR0cHer0enU63+eCioQGefBJuvx02MSmGhYVRXl5OS0vLplvNZzoX6PzbGIY5I96XqlDHfyx9MKAbJ99jgFH9NAHj/Wirurnha7/Azs6O48ePL3Uz6g0if8sepmFAJGmyivOvyUB6UolbLpcvBeubva6T4e3tTWFh4ZYCq9WEH8M8lbg7yMie0nJOxIX8NTCGp57+kAt/Fk9IwwSN4Sr8O2eorGmCBW/Ck5S4z4J9mCVxhw6u+gwcP36cQ4cOrdhuNBpZWFhgfn5+6d/4+DhTU1PMzs6SnZ2NKIrIZDLs7e2xt7dHpVJha2u74jyLZU1zy4darRaNRrNlOYCGhgbCw8O3tO8iBgYG0Gq1KzoSlYfOo/Hln+B73Q8RD2QgvPU2pKSse6ybb7yJqpY6/vDTX+PrHsgd8m9i5xPO1AcfYBUdjeRE4JYZYcPAuI53K6ZwtZcT7GH+4mp+fh5RFBEE4bTxfoxGI83NzQwPD5OYmHhariM4OJisrCw8PT3NXqTqdDra2tro6+sjMDCQiIiIMzKgWoQgCHh7e9PV1UVgYCCiKHLzzTcTExODr6+v+Nxzz50HvCUIgrsoiv0ndrsMWDRafAN4URCE3wDPA2cBnqIoRgmCMC0IwveBa4AI4M6T9rkeyAc+C3wg7lK55XRkrO7ERExbVFT7pSiK9wEIgvB14H7gy5s5kCAIVp6enpdddtlly5ajGo0GnU532mvJm4FcLicsLAx/f3+am5tpa2sjJCRk055Mi90zycnJe3C1q8PFxWXJCmZgYIDo6Ohd00JZDVNTU9TW1nLgwAGmp6cpKCggISEBW9tNrKDvucckAHr//Zs616JcQmFhIZaWluuWCURRZDh3hv73prBQSQm41gVLN/nSawWzTbwzWYFSkLFvbBjJRAuB8VeSktLOY489thRULeiMvJQ9StugjvTBPA5dvh/ZKp/N39+frKwsfH19zf7+FQoFCoWCqakps8QOF88zPz+PRqNhYmKCiYkJpqencZVYU2FwZ84LvnPkp+QqnmQmXMv+FpF+Dy3+E1r+8loNdZUf8eTTP0Bh0KIOtzZ7QpBIJFhaWq7gFvb09KBWq5eySDqdjsnJSSYmJmhqamJmZgapVLoUaKlUKjQazZZkFnp6ejYUylwLo6OjSCSSbWk0LSwsUF9fT1pa2qrfn+/RW8h5rIaMu99GefQo/OtfcM45ax5PFEVu/NwXGZwcQX1JMIZcI9PWGVh2NzB1/DiqC0xd74IgcFmKitFpPa/mjXHrOc442W3+3uvr66O5uZn09HQ0Gg3FxcWkpqbu6fgxPT1NRUUFLi4upKWlnTbvQalUSkhICI2NjcTGxm5qH4PBQEdHB11dXfj5+XHw4MEzwjtxM/Dx8SE3N5eAgAByc3N5/vnniY6ORqvVqgRBeFUQhM8BXxAEYR+mkl0HcBuAKIq1giD8DagD5JjiisW44XbgJUCBKVuVd2L7U8DzgiC0YMpUXbVbn21PAytBELyAC4EHgW8CnKijLsIaM2qelpaWV994443Wp5LT29vbzxhu1WahUCiIiopibm6OxsZGWlpaCAsL2zAL1d3djZOT0562zK4GCwsLEhMT6enpIScnh6ioqD3JoC0sLFBWVkZCQsJScBAfH09JSQkxMTHrT5JZWfDGG/Dgg2DGtS4Sb/Pz81EoFKuWbwxzRrpeG2eqfh77CCXelzogVZoGvBnDPP8aL6R5oQ9PoxSnrlzKc9o4cuBzWCu8eeutt5aOo1kw8sJHI/SOajnc9yFJ6cEo1ug6k0ql+Pv709rauqVs7SKJPSoqasP3iqLI2NgYAwMDaDQacnNzcXJywt7enoCAAOzs7BAEgZF3hymXGkh338f++N9TI/4cbZorn3ujjYn9DtRX95ORcQShT48I2AbuDL8KVmpYyeVynJyclv1eJwdbixkLCwsLLCwscHNz21xwjimw2r/ffH3DxYXRqVQGc49RWVlJeHg4CsXq359SYY9b4mf48PcC59xfhPSii+CFF+Dzn1/1/YtdWy89/AzNC/1Uj3Uzc2yA/Z9JhaICrJOSlmQ9LGQSrs5U86djw7yYZQqulBYbT+5tbW309/eTlpaGXC7H0tKSgIAAysrKSE5O3vWMiyiKtLe3093dTWxs7GkXHwXw8PCgra2NmZmZdbNmRqOR7u5u2tra8PLy4sCBA6e1SWsrkMvlODg4MDw8TEZGxjKeXkJCwmxZWVmDKIrXrrW/KIoPYoolOKFJ9eUT20swySwgCMLxk94/D3xuFz7KCux1aPs74DuYyn5LEAThQUEQujGl7jaXOgDs7e2/ffvtty+TlDYYDAwNDW3LVf50wtLSkn379hEXF0dnZyd5eXlrimEaDAZaW1u3zOvYDXh5eZGSkkJLSwvV1dW7Kiq6qFUVHh6+bAK0s7MjJSWFmpoa+vrWqCobjSYfQE9PuOsus88tl8tJTk6mpqZmhbHyXL+WpseHmGqcx+M8e3yvVC8FVS3z/Tw29DZtC/0ETgyganiPv/6hjJ9893XK8gfo7u5metrE4p6eM/DM+8P0j2k5u+cdYn2UWG8wefv4+DAwMLAlWQ9XV1eGh4fXJNDq9Xr6+vooKyvj+PHjdHd34+joSFRUFO7u7sTGxuLn54dKpUIikSCc4FoNGIwY/OVoquTU5ML37v8JMxcdpmV2iKGBaQ4cOITNqBGdSoLMeuda6zcjtbAYbAUFBZGQkIC1tTXJyclYWFhQV1fH8ePHqampYWRkZM3vZXJyconjZS6GhoawtLTcdAC3Gnp6epDL5bi5ua37vhDvczA4O1D+xC2mUuBVV8Gf/rTifd3d3YyNjS3xc0KUHtS2f8BNz17O88dq6fG1Y/K//122j8paxpUZasZm9Pw9fwyjce31sSiK1NbWMjY2RkpKyrLslJeXF7a2tjQ0NJj5LZiHubk58vPz0Wg0ZGRknBFBFZgygGFhYWt+flEU6e3tJSsra+nag4ODP3FB1SL8/f1XkNgBvvOd7zi6uLh84zRc0o5gzwIrQRAuAoZEUSw99TVRFH8giqI38Ffgjk0eb19kZKTjqZye3t5e3N3dPzHp0LVgY2NDYmIikZGRNDU1UVRUtGIC7+jowNPT84wj6FtaWpKSkoKNjQ3Z2dkrxOB2CtXV1bi6uq7anm5paUlaWhrt7e2rPri8+ioUF8NPfrJlL0ClUklCQgKlpaXMzc0hiiKjpbM0PzmMqBcJuskJ5zQbBEFALxo4NlnOc6PHEXQaQrpLkDR38OC3c/jX3z7innvu4c477yQ2NpaKigpGp7U89d4wYzN6Lhh4j2BLDapLLtlwFS+RSAgKCtq0svWp+zo7Oy9rf5+bm6O9vZ38/Hxyc3OZnJzE39+fQ4cOsW/fPtzc3HBxcVmzVTzQTYGPkwUFSj2iTmSwUsEbf6sgq+gliotLAIiJTsFBA1LvnS3/mKu6rtfrMRqN2NjY4Ovry/79+zlw4ADOzs709vby0UcfUVpaSm9v7zKJia0aLouiuNQJuFVoNBpaW1s3lWW0kNsQ6HmEHm0TE3//M1x4oYlb+OCDS8bNQ0NDdHR0kJiYuGwM/fbX7yQhKplfPPE9np2eoVw2zPwp95i/i4ILEuxp6lvg/erVdbOMRiNlZWWASRRyNS5keHg4U1NTWzYIXw+LvngFBQWEhIQQFRV1WnWyVoOzszM6nW7ZuCmKIoODg2RnZy8FpOHh4XtaMt0N2NnZYTAYVggwX3bZZRKpVPp5QRDOrMltk9jL6CMd+IwgCB3Ay8ARQRBeOOU9L2JSXt0Q7u7u93znO99ZUYPp6uo6bYKgu4FFpfGgoCCqq6spLS1ldnYWnU5HV1fXrssrbBWCIODv709iYiLV1dU0NjbuqCdWe3s7BoNh3Q4auVxOSkoKY2Nj1NbWfpxqXliA730PYmLg2jUzzZuCra0tMTExFOUX0/nPMXpen8DaV0HI7S5Y+5gyGKP6af48/C65Mw24TA0R3FWMpsWBr93wF7q7+nnjjTd46KGHkMlkqFQqFLauPHFskLkFI5dM5eA524v6qquQbDKA9vT0ZHR0dEtq/z4+PnR0dNDW1kZWVhbl5eWIokhsbCwHDx4kPDwcBweHZQGehYUFRqNxVcNuQRA4EmPHgCii95XzxeCv4OTswB9+9SL1tW1YWVviIg1GAtiF7GxX6fz8vFkk4NXU1qVSKa6ursTGxnLo0CECAwOZnp4mPz+f/Px8enp6GB4e3pJwZF9fHyqVastWLYsGy+ZwGoO8jiKXWVM3+A7885+m+//ee+Fb32JyfJy6ujqSk5NXZECsrKw49v5bBLuF8sy3f8ZfFZO83Z2F4ZTfPCnImsRAK7LrZqjuXD5Z6nQ6CgoKUKlUREZGrrlIEASB+Ph4WlpadnRRptVqKSkpWSo97ZQ7xW4gPDyc+hNG2KOjo+Tm5tLX10diYiLR0dGnpQN7t+Dr60tnZ+eybRYWFlx11VWWcrn8stN0WdvCngVWoih+TxRFL1EU/TCRxj4QRfGLgiCcXMf6DLBhDlgQBFuZTHb0rLPOWrZ9ampqqVb/aYNarSYtLQ1vb2/KysrIzc3Fy8vrjE8B29jYkJ6eDkBubu6OeCeOjIzQ09NDbGzshhkcqVRKQkICAGVlZabS5GOPQXs7/PKXsAOrVUdHR1z7ApmonMPloA0B1zois5YiiiLls208NvgWQwsjBPTXEacTOCvh+6QlXE5cXBxlZWVcfPHFS8fqGlngvVYbDAYjl4gVOHbV4nDZZcjNmAQEQSA0NNQss1tRFBkZGaG5uZnR0VF0Oh0pKSmkpaUtb99fA2q1es2SdYCrAj8XCwot9SgFK7577f/RUDNAcLgLWfmvs9BpQCsBtx0MrLaiYbWRfpUgCKhUKsLCwsjMzCQ6Opre3t4l4rg59/ZiF9pWZB0W0dbWhr29vVlke7nMkmDvsxkar2NU02mycbrrLvjtb9FcfTWJJ7iKq8HB2YF/PvsGbrYevP6lhyn0lvBy+1voxI+DK0EQuCBBhY+zBa8VTtA3ZtJGm5ubIy8vDz8/v03JCcjlchITEykvL98Ru5fBwUFyc3Px9PQkPj7+jM/0qFQqRFHko48+oq2tjdjYWOLi4k67X+JuYNFW69SF9x133GHr5OT0vdN0WdvCmVAve0gQhBpBEKqAc/i4NXJN2NjYXH/rrbfanFru6+jo2JzZ7icUgiDg4uJCYmIiOp2Onp4eamtrd9RqZTcgkUgIDQ0lOjqa0tJS2tratiyyOTc3R3V1NYmJiZtO4QuCQGRkJA4ODpS8+y7ij39s6ohapyvKHEw1z7PQBIpYA32qFhBg3qjlb2M5/GuiEMXcODEDjUTKUsh6cxZrpTPh4eHLNKoAmvrm+csHo1hZSPiCVRP21QVYp6VhGRGxztlXh6urKzMzMxtO9nq9nvb2dj766CO6urrw9/cnIiICqVRqVol5Uc9qLRyJtmNAENF7yTjqcBnh4SE8/3ghwX5xCL16xmzBxnLnFglbVVw3J0ixsbFBFEXS0tJwcHCgurqavLw8+vv7N7y/u7u7cXFx2XLmYXp6mp6eni2VEQM8DqKQ21HX8QaiIKB96CE6r7sO9//+F5tf/WrdfUOP+PHMna/y26uf5EinjEbLGZ4ZfI9Zw8fBj0wqcFW6GiuFhJeyx+gfnqCgoICoqCiz5Fisra2JioqitLR0y9luvV5PZWUlHR0dpKamnhY5GHMxPT295PJgNBpJTEzcFgfvTIdUKsXFxWWF92tAQAC+vr6egiCErre/IAgvYZJQCBUEoUcQhJsFQbhMEIQeIBV4UxCEY7v2AVbBaQmsRFE8LoriRSf+vkIUxShRFGNEUbxYFMUNC+u2trZfu+WWW5alpfR6PaOjozvu5XQmorm5mYiICA4dOoStrS25ubk0NjauWoo5k6BSqcjIyGB2dpaCggKzS1VGo5HS0lJiYmK2lJUMCAgg4q23YGKC+QceMHv/1WBYMNLz7wkUTjJCL/FBqVSS1VDMw/2vUzvXjftoJ+figGJ0PxecfQMPPvjgqpyvynYNL2aN4mQr4YrpbJTF2RhCQujeYhPGRiRYjUZDTU0N2dnZ6PV60tLSiI+PR61W4+XlRW9vr1nBr6Oj47qWHH4uCgLdFBRZGRC0Eh66/WG+9tW7kWvskM2LzLnsLM/FXI9Ag8GAwWAwK5icn59fknXx8PAgNTWVmJgYhoeH+eijj2htbV3VuspgMNDW1rYlvTEwPQfl5eXs27dvS/wgmVRBiM+5jE62MDhWR3FJCYqHHoKbboIHHoDnnltzX0EqEP/5cOLUKcRyFOmDb9HQ3sQTw+8yrPuYV2VjKeULB9TMzhv4e84AiYmJW5KxcHZ2xtnZeUtk9rGxMXJyclCpVCQnJ5/x5TONRkN5eTmVlZX4+/tz4MAB1Go1/f39G+/8CYevr++qvq/f+ta31K6url9fb19RFL8giqK7KIryE1Wxp0RR/NeJvxWiKLqKonjubl37ajgTMlZmQRCEYG9vby+9Xr+s46y3txdPT88zWhRtJzA7O8vExAQeHh4IgoCPjw+ZmZnI5XKys7NpbW3d1U687UIqlRIdHU1QUBCFhYX09PRsvNMJNDQ04OLisqUBGoCxMWyffRbtZz5DvkazohlgKxj4YArdhAHvS1RIZAJuQe4ct2lmQTdDwvgAn/P5PP96oZ4LL/gMrq6ulJSUrCiF5DXM8I+CcXwcJFzU9jqSxhrsL7gAr6uvZkaj2ZJBMoCTk9OSnMAiZmZmKC4upqysDLVazcGDBwkODl4WUFhYWGBtbW0Wv0WhUHDqM3kqjkTb0S8V0bnLCJiN5vCBI0w2mYJrmc/OE9fNCazGxsZwcHDY+I0nobu7e4UYp42NDTExMcvK36dmlbfbdNLU1ISbm9u2dPr83DOwVDhQUvciDk4SXN3cTB2CR4/Cl74EqyjcL8IuVIm1jwWtOZP87oXX+cclDzA6MMSfh9+lfWFo6X3i3DDWsjksbRy2lXEJDg5mcnKSoaGhjd+MKfCsq6ujvr6epKQkfH19z+h5YX5+nurqakpKSvDw8CA9PX2pJB0aGkpTU9OO8lPPRCxKS5ycYV9YWCAiIkIilUq/IAjCJypW+URdLICTk9Ott956q3JycpKsrCyqqqqYmJjYcmfOJw1NTU2EhoYuGyikUikBAQEcOHAAg8FAVlYWnZ2dZ/TD6OzsTHp6OkNDQ5SUlGxYzhwaGmJycnJ70hJ/+ANMT6N44AESExMpKytbt3y1EWa7tYwUzOKYbI21r4LZ+VH+2vMPjIjEDBhIVH+er972PX70ox9x7bXXUlhYuKx0I4oi71RM8t/yScIcjZxT/jzSyVEcr70Wm5QUJBIJ+/bto6amZsum3WFhYdTX1zM3N0dFRQUVFRX4+/uTkZGBh4fHmt2zWzFmXo9nBeDtZEGwh4Jiaz0GjRGrATVjDRqmLMDBdWebfzQajVlZTXP9ARfb3tcSiJXL5QQGBnLw4MGlrHJzczMLCwvbajoZHx9fsivZDqQSOXayJAziJE2Dz/N+yQM09r/H7AtPQFAQXHaZyZVgFQiCgPs5dlgb7Xj2Ry8zPDHFPy99AMmMnudGPqRS005raytdXV2IUmvUttv7bQVBIC4ujtra2g35VlNTU+Tk5GBhYUFaWhrW1tbrvv90QqfTUV9fT0FBAWq1mgMHDuDq6rpsbFcqlUtdqZ92+Pr60tXVxcDAAEVFRRQWFqJQKDhw4IAAHDjd12cOPlGBlSAIglQq/cJVV10lWSyFubq6Ul9fv9SeuxX9nk8K5ubmmJ6eXrPcKZPJCAkJIT09ndnZWbKysswu6ewl5HI58fHxeHh4kJubu6zN/2TMz89TW1trMpbd6spzchJ+/3u49FKIicHW1paUlBTq6uq2NGgZ9SI9b4wjt5XgfpYdIxNN/KvhT4wobUix8OL8hOtpaWnlkksu4cknn+TZZ59dNsgbjCKvF02QUz/DPnsNB/KfQWapwPnWW1GeVCKytLQkODiYqqqqLX1sa2trZmZmyMvLw9XVddlqeD04OzszNjZmVvZzI54VwJEoO/rloHORImm1RttrZMAGnM1Q694MzC0FmsuvGh8fx9bWdkMe18lZZUEQ+PDDD7G1td2SHMwiX2hbz8EJtLS0oBB8OC/l5+wLvhqFhS31Hf/m3aZfUfSryzHIBMQLzoc1sqXWPgrsI5QEaOJ4/oGf09Ldwz+/8HNcddb8Y7yAuvkeEpOSmZ43Ym+1/TKvUqkkKipqTRN0URRpaWmhoqKCffv2nVYT542g1+tpamoiJycHKysrMjMz1622BAYGbouX+knA9PQ0Y2NjtLa2MjQ0RGhoKJmZmQQGBvLlL39Z5eHhsSkZpjMFn6jACkhOSUlRLk5QgiDg6uqKWq1e8kYqLCykqKho1S6DTzoW/ek2GjAsLCyIiIggJSWF0dFRsrOzGRwcPGMfzEV+SkdHB5WVlcu4YqIoUlZWRlRU1PY4Eo88AhMTptbyE1AqlaSmptLV1UVLS4tZhxvOnWF+UI/nRSq6xnLJqnmUDrU3zlIbIrQBvPrqqyQnJ+Pu7s6VV1657DfT6UVeyRmjrE1DqnKQ5ILnsfT1weXWW1ft/vPy8kIUxbXFTleBwWCgubmZ3NxcvL29USgUm7ZJAtOz5ebmZha/YyOeFYCnowVhnkpKbAwwL0EwwqA1ONvtbHerORpWBoMBnU5nlsCnuRlyqVSKj48PFhYWWFpakpWVRV9fn1nPZF1dHX5+ftvOwvT29jI8PMy+fftQWFjj557Bgdhvcnbyjwn3+wxTznKyf3IYY28302fvp6+7AKNxJX/T7Sw7jHqR/ZHX89i111JSXsHAsyXYGhQMu+iYmRcRRVDtkOirs7MzarV6hTelRqMhLy8PrVZLRkaGWZZMewmj0UhbWxvZ2dlIpVIyMzPx9fXdMMhWKpWoVKoV5O5POnQ6HR0dHWRnZ1NbW4ujoyMeHh54enouK3NnZmYCHBQE4cwmyZ2ET1Rg5ebm9tXbb7992bJSFEX6+/vx8vIiICCAzMxMQkNDlwiktbW1O8KlOd1YWFhgdHTULEV5pVJJTEwMiYmJ9Pb2kpeXt+HEd7qgVCpJTk5GpVKRk5PD2JjJdLypqQkHB4ft2ePMzMBvf2sSRDwhvbAIuVzO/v37mZqaorq6elMT3fywjsHjU9hHKumQvk5ly0uMu+9DK5WTMu/P2UfP4itf+Qqzs7NLAqKLJYw5rZHnjo/Q0DvPQUMjMeWvYbN/P47XXotknUAgJiaGxsbGDUshRqORzs5OsrKyEARh6XmwsrIym6vl7e1Nd3f3pt+vVCrR6XQbZrkOR9vSZwHzDmCUiEzagv0OKq6DeYHV+Pi4WfwqvV7P+Pi42TpIzc3NBAUFERkZSUpKCsPDw+Tk5GzqdxkaGkKj0Wxbo29kZITW1tYVAqAA1kpHQn3O42ji/ey7+rd0/+ZObKraEa/7Im/nfZeK5pcYnWxdekaUTnIcE6wZLZ3j8lvv5t1bb+WmqCiSHULp0A7TM23iy+xUYAUmztHIyAgjIyOIokhnZydFRUWEh4cTERFxRgpDi6JIV1cXWVlZ6HQ6MjIyCAwMNKvxIDg4mJaWljN2cbxZiKLI8PAwpaWl5ObmotPpSExMJCUlBQ8PD3x8fFbwbiUSCZ/73OcUEonkgtN02WbjzLsL14AgCHJBEM49evTosu2Tk5PY2NgsS8nb29sTHR3NwYMHcXBwoK6ujuzsbDo6OrbMVTndWPQ/3Ep628rKivj4eGJiYmhra6OgoGDX1NC3A0EQ8PX1JSkpibq6OsrLy5fSwtvCH/8Io6Nw332rviyRSIiLi0Mmk1FSUrJuYCAaRXremECQC/T6vUJ7fxZq76N0KZUEz6q57vzP0d/fz9tvv42TkxN2dnZERkZSVFTE2NQ8T783TPeIlnOmCglryUJ18cWoLrwQYYNB1sLCgsjISCoqKtYcXMfGxsjOzmZ2dpaMjAyCgoKWBu/Q0FAaGhrMGphtbGwwGo1mdW86ODhseG+5rMKntAABAABJREFUO1gQ4aMkxwXKA/Q42MuR7HDZRhTFTU+y5vKr+vv7cXd3N+tZnJ+fZ3h4eInsrlQql7SJOjs7KSwsXPN71mq11NbWsm/fvm2Vt6ampqipqSE5OXndEqYgCKhsffD76q8Rf/5zPI+3Ev+XeroHC8iu/DXvFv+Q+o5/MzM3hOshWwQptJZJCTt0CGlVFS6lpmC8ZtxENt+JUuDJ1xYfH09VVdXSOJaRkbFC2PVMwGKWOSsri+npadLS0ggNDd2ShpaVlRVWVlarLoy7u7s5fPgw4eHhREZG8vvf/x4wjQdnn302wcHBnH322cv4jz/72c8ICgoiNDSUY8c+ViIoLS1dai76+te/vjReLCwscOWVVxIUFMT+/ftX7eBbDxqNhoaGBo4fP05vby/+/v5LjTMnL4CcnJwYGxtbUW26+eab7dzd3TeUYjpT8IkJrICzL774YsWpgpjd3d1ruspLJBI8PDxISUkhKSkJnU5Hbm4upaWlDA0NfWKif51OR39//4oOJHNha2tLUlLSEqG5uLh4RwQ7dxrW1takpqYyNDSEXq/f3jVqNPCrX8HZZ8M6PnuCIBAeHo6zszMFBQVrkunHSjXMdmoZD/mAUW0DcSHXUWNthTCu4+dXfIuuri7efPNNUlNTl/ZxdnbG2imAx48NMjat4/z+dwkYa8TpuuuwTkra9EdxcXHB0tJyBancYDBQW1tLfX09iYmJRERErBi8ra2tUalUZrdue3l5mUVi3wzPCuBwlB2TEuiQy3e8DKjX683KBpjLr1qtG3AjNDY2EhISsiIwWrSuCggIoKCgwET4PmVcqq6uJjQ0dFul8Lm5OUpLS0lISDDrOJJv3w233Yb7n9/i/Now4kOuw1rpRGPXf3mv+P/IbvwFM+49WAzZoj7rMp7r6CDp3EtwHoWOKVM3qr3Vzv6+ExMT6HQ6BEEgNjb2jBNJFkWRoaGhpWxkcnIykZGR27YeCw4OXtWqSiaT8etf/3qJCP/oo49SV1fHQw89xNGjR2lububo0aM89NBDgKmk/PLLL1NbW8t///tfvvKVrywtJm+//XaeeOIJmpubaW5u5r8nPCGfeuopHBwcaGlp4Rvf+Ab33HPPhter1+vp7u4mNzeXiooKrK2tOXDgAPv27UOtVq+6SBAEYYWtFrCoNh8uCIJ5rbunCZ+YwMrT0/PrX/rSl5b1FxuNRkZGRjalXaVUKgkODubgwYP4+/vT39/P8ePHqa+vZ3Z2dteueyfQ2dmJj4/PjqW5VSoVqamp+Pv7U1FRQXl5+QqvptONpqYmAgMDiY+Pp6KigtbW1q0Fwk88AUNDcP/mvL0XlaEXDVpPhm7KQO+xMebVnWg8azkQ+026re0Z0E0gzRmitaWVf//734ucAAD0BpF3Kyd5o0pAYjByYdtr+Mmmcbn1VhRb6AyLjIykvb196Z5dzFIteiOux78JCQkxu3Xb09NzU4KXi9gMzwrAVSUn2se0UnWy39mJ0RziutFoRKvVbjrY0Gg0iKJoFs9pdnaWycnJdcv4zs7OZGRkMD4+vix7tdhYsR1hS51OR1FRETEnmjbMgiCY+InnnYfsq1/Dp3qa9Jivc+7+B/F1PpuZ2TEm/d8CCYwWz3Hky19mVqul7ff/ZG5OQKkAuWxnspE6nY7y8nJ6eno4ePAgwJalSHYLY2Nj5OXl0d3dTXx8PLGxsTvmBGJnZ4dEIlmREXZ3dyc+Ph4wLZ7Dw8Pp7e3l9ddf5/rrrwfg+uuv57XXXgPg9ddf56qrrkKhUODv709QUBBFRUX09/czNTVFamoqgiBw3XXXLdtn8Vif/exnef/999dsIhgbG6OiomIpex4XF7fkGrKZINjLy2tVGZ6bbrrJxsrK6srNfl+nE5+IwOqEhU18YmLisu0jIyM4OjqaFXAIgoBarSY2NpbMzExsbW2prKwkNzeXrq6uM05k02Aw0N3dvSv+h05OTqSnp+Pu7k5JSQnV1dVnRFflxMQEo6OjBAYGYm9vT3p6OvPz8+Tl5ZkXAM7Pwy9+AYcOQUbGpndzc3MjJiaGwsLCJQ0oo9FIw98aMegNLCSUczD+HrBy4sPpakKVntx727doaGjgyJEjS8cZGNfx+DtDZNfNECEM8fmGF3BQSRk/eBDZFrW4ZDIZMTExlJWVLWWpkpKSCAgI2LBMpFQqcXFxMUs7TCaTYW9vv8R52wiWlpZotdpNBW+Ho22RCQa81aePuD4xMYFKpdr0sbu7u82WdVk0Wt7o95HL5cTGxi5lr1pbW2lsbCQmJsas850Mo9FIcXExwcHBW9d/k8nglVcgIgI++1moqWFkaJqZEScO7PsGRksNC+5tjJVpSIjfT3RkJB+8V4Qwr0BisX07GjCN9bm5uTg5OZGYmLhUSq2trT0j6B1TU1MUFhbS3NxMdHQ0CQkJuyL1EBwcvIK8fzI6OjooLy9n//79DA4OLgXz7u7uSzpgvb29yzKui4LAvb29y6o/i9tP3WdxTDh5ATU3N0dzczMfffQR7e3teHp6cujQIcLCwsy24bG3t1/ywz0Z1157raW9vf1XzTrYacInIrCysLC4/Itf/KLVqQPTemXAzUAqleLl5UVaWhpxcXHMzc2RnZ1NeXk5o6OjZ0SpsLu7Gw8Pj11Ldy92fx04cAAHBwfy8/Opr68/bYOV0WiksrJymQ+gVColMjKSsLAwioqKVi2XrIqnn4b+/jW5VevBwcGBpKQkysvL6R/ooezdtzB22SPGtpOedgtKC3te7f6I57/4M9waxSV+GJikFD6qnebxd4aYndNz4UwhGbX/wvFgBr633srU/LzZHIVTMTs7u8TbMGcADwoKMltE1lxNK3t7+01x+Jzs5JwfOISr7c4K2pqTsVpcnG0Gi40y5jSQTE1NMTc3Z1bzhYuLC+np6bS2tiKTyba82BNFkfLyclxdXbdv5WJnB2++iWhtje7ccxmqqiI1NRUHew+Swm9m1CML44LIeLmGL916K1VdXQzXtDInm2Z+bOsNMwaDgZqaGpqamti/fz/e3t5L44KlpSUBAQHU1dVt77NtAzMzM5SWllJTU0NwcDD79+/f1a5EtVqNTqdjenp61Wu54oor+N3vfrfuNaw2dgqCsOb2tfYxGo309fVRUFBAaWkpcrmc9PR0EhIScHZ23jIfUBAEPDw8VnRBe3t74+bm5ioIwhkvWPmJCKwcHR2/duONNy6bPfR6PdPT02arJa8FKysrQkNDOXToEN7e3nR2dvLRRx/R1NRktvXKTkEURTo6Opb5ye0WBEHAy8uLzMxMrKysyMnJobm5ec8zeI2NjXh6eq5asnB0dCQ9PZ2xsTGKi4vXz65ptfDQQ5CeDocPb+labGxsSE1NpaLmZYTiYASnOfZdfBCp1IKi4Xp+cuU3acuuYWZ4Ymmf4Skdf353mPerpghV6fls8yt4DzegvuYa7A4fRnLCFLqnp8fs9umTuVTp6elotVqzO14tLCzw9PRc4Sa/HtRqNZOTk5u+F5ycnDbdfWplZbnjz5c5GStziOujo6OoVCqzFjkNDQ2Eh4ebPcn09vbi7u5OWFgYBQUFdHd3m73Qq6urQ6lUbsr0eDMQvbxo/s1vkIyNEf/TnyI7EZy7OIQRtC+Zebte+nOHuebqa1AoFJS89xqi1QKlH7yKYQt0i4mJiSWtp9TU1FV/U29v76XGgL3E3NwclZWVlJeX4+PjQ1pa2p4R6Bc7BE+GTqfjiiuu4JprruHyyy8HTH6hi5zK/v7+JcqMl5fXsm7fnp4ePDw8VpTgFrefus/IyAhjY2PU1NQwPj5OZGQkGRkZ+Pn57Zi59cnZspNx++23Ozg4ONy4IyfZRZzxgZUgCK4ODg4+pw4OAwMDZunymHE+nJyciI+PJz09HYVCQWlpKfn5+fT29u6pXczg4CBqtXrbpEdzIJFI8PX1JTMzE4lEQnZ2Nu3t7XuiCTY5OblUAlwLcrmcffv24ePjs2R4uyr+8hfo7jZlq7Zxj2j1EzjU7Eeqs8Qi2eSVNjozwdWXXUlvWQsvvvhXLrnkEoyiSF7DDH/87xDjMwY+ox7gQN7TWFtb4HLbbVie1NkolUpJTk6moaFhXaXykzE3N0dubi5KpZK0tDRsbW3Zt28fFRUVZt+TAQEBdHZ2bjpQEgQBd3f3TQupbpbADqYFzU7z+zabsTIajczPz286CFvkOm4W4+PjiKJo9oQ7MzNDZ2cnERERuLi4kJGRwcjICGVlZZv+rdva2pibmyNiCwbeq0Gv11NUVIQYF4fkL39ByMuD22+HE8FekNdZyKJGEKcUzHSM8NwLL5Nx6Z1YKHQ0eEgZfeEFjJukGRiNRpqamqiuriY+Pn7dMrcgCMTExFBbW7sni8CFhQVq/h977x3eVn5e+X8uOkAQBAH23ntvIilKI8+4ju0ZO3H3usROXLKb7DplM7Y3bZOsnc0m6xSvE//Wccb2JuPYiWvisR1PkUSJYhG72HsnAXYQHff3B3XvECRIghQlcbR7nkfPaCCUC+Difs/3fc97Tl8fra2t8ndzT1Ywp0BsbCybm5vygI0oinz0ox+lsLCQX/u1X5Pv99RTT/Hss88C8Oyzz/L000/Ltz/33HO43W4mJiYYGRmRPfciIyNpaWlBFEW+9rWvyY958skn+cu//Etefvll/uZv/oZLly5x5coViouL70tAtMFgCDmR/M53vlOl1Wo/fOYveMY498RKq9U+/cEPfvDANzc7O3tPbcBwoFarSU9Pp6mpidLSUvbH6NzvVqFksfAwoFQqyc7OpqmpCY/Hw9WrV0+1aw4XoijS19dHaWlpWGQ5ISGBxsZGZmZm6OzsDG5der3wuc9BbS28/vX3dFzj359Bv5pF/JN6XLrdnL0n3vIGJlr6+Yu//RLveue7WN328dWf2Xi+c4PsOA3v89wgsfl76EtKiP3Yx0LqqTQaDXV1dXR1dR079bi6ukpLSwslJSVkZ2fLn4/JZCIlJeXEAbUqlYr09PSQYdCHIZS/zGEwGAy4XK6wyLjBYHhoFauT6Kuk9stJKuQDAwNBEUbhIBAI0NXVRXl5uTzZqFarqaysxGKxcOPGjWM/r/n5eRYXF8/EoR12yURLSwsJCQm7cVrvetfuMMhXv7obE8VdgvP44/h1Dhab7VRdbMBojiPLHM1MmpHN1SVWv/lNxGOIoZQSEAgEuHjxYliLtl6vJy0tLeTE3FnB6/UyODjIzZs3iYqK4vLlyye23DgrSG7+UtW5ubmZr3/967zwwgtUVFRQUVHBv/7rv/LMM8/w05/+lNzcXH7605/yzDPPALsDMO9617soKirijW98I1/84hflc+1LX/oSv/iLv0hOTg5ZWVlUVlbS2tpKUVERa2trfOQjH+F73/seX/jCF+67Z1ioqpXZbCYrKytCEITTZUI9KIiieK7/JCcnNw8NDYl74Xa7xZdffll8GAgEAuLi4qLY2toqvvTSS+Lo6KjocrnO/HW2trbE5ubmM3/e08Ltdot9fX3iSy+9JM7Pz4uBQOBMn396elrs7u4+8eMCgYA4PT0tvvjii+LKysrujV/9qiiCKP7gB/d0TMtt62LXb8+KHd+4Lr/WT/tviAVP1omf+uLviYFAQGwd2Rb/4B/nxD/81pzY1rUgLvz5n4uzv/u74lZzc1if0dramvjiiy8eeg5NTk6KL7/8srizsxPy3wOBgNjc3CzabLYTvTefzye+8MILotvtDvsxN27cELe2tsK6b0dHh7i6unrs/TY2NsT29vawnvPFF1880/sNDw+LU1NTYd13cnJS3H8dOgrLy8tiW1tb2PeXMDQ0JA4MDBz67ysrK+ILL7xw6Gdrt9vFl156SfR4PCd+7VDY3t4WX3zxRXFpaSn4H/x+UXz720VRoRDFH/9Yvnn63xbErt+eFf/pB98W3/Obz4of/MQnxd+e/Xvx5Ts/FWd/+7dF+7e/HfJ3EQgExPHxcfHFF18M67zZD7/fL7788sthn5/hwufziSMjI+ILL7wgjo+Pi36//0yf/7Twer3iCy+8cObXYVEUxc3NTbGvr0984YUXxJ6eHnF9ff3MXyMcHLbO/6//9b+8kZGRvymeA35y2J9zXbESBEGvUqly8/Lygm5fWloiPj7+YR0T8fHx1NbWymOp9yNG52FWq0JBMqisq6sL8mg5C3i9XkZHRyksLDzxYwVBIDU1lbq6OoaHh+nv6UH8b/8NKit3ndZPCceUm/kfbuG0jJP6pl1twmbASUf0Ar/418/whpLX8uwLK/ygbZ0Uq4ZfzN0k6YdfQXQ6ifngBzE2Noa1mzWbzRQVFdHa2hrUyggEAvT29rKyskJjY+OhFRhBEKioqKC3t/dEAwdScPdJonxO4sQers7qrFuBgUAg7CrCSfRVJ/GuEkVRngQ8CdbX11laWmL/9W4vYmJiqKuro6en58B3sbW1RXd397EGoOFibW2N1tZWKioqDlraKBTwta9BcTG8+91wd1ItsSEWlCKRkyksTQ/wtb/+EoppB3esfiIffxxndzebP/1p0FM5nU5u3brF9vY2TU1Np9LNKhQKiouL6evrO5OqeiAQYHJykqtXryKKIpcuXSIzM/PcOLurVCpiYmLOLOZmf7xMdHQ0ly9fprS0NChe5kFCo9GgUqkOVGifeuopVWRk5L97KAcVJs7HWXI4nnjrW996IMBL0lc9bGg0mvsSo+Pz+bDZbOfiPe6HXq+XHaOnp6e5ceNG2KP4h2FwcJDs7Ox7WgwkgWt0VxfCyAiO//gfT62t8mz4mHxuFb9+i526G8RE5zA1O039ay4yPzLDe2MeZ2gjg8kVN68r0fE2fxe+f/p7VDExxH7iEyf2p4qLiyM9PZ2Ojg7ZV0lKdq+urj5WLG0wGMjKyqK/v/9Er5uamsry8vKxMTkSEhMTWVxcDGvhCldnpVKpzlS3GG4bUBRFnE5nWFqsra0tVCpV2FqsxcVFjEYjRqMxrPvD7mBCd3c3FRUVxy7eERERXLx4kYWFBfr7+xFFEZfLJRuAnoVv0tLSkkzSDm2XGo3w/e/v2jE89RRsbKAyKLFURBBjS6bu4tMolQrGvnWLee8qzsYKIurq2L5+ne0bN4BdkX5LSwtZWVmUlpbe0/Sz1WpFo9HcE9kQRZHZ2VmuXr2K0+mkqamJ3Nzcc2dCCpCZmcnExMSpHy+GiJepra2V42VOYrJ7vxAfH3/g+0xOTsZoNCYKgmB+OEd1PM41sUpOTv7Qu971rqC50UAgwPb29rkL2twfozMwMCALv09qXTA3N3dk2vl5gNFopLq6muLiYkZGRrh169apyOTGxgYbGxv37CoPd8d071oPDN4VwJ509xrwBJj8+1X8Xj8LZX9PRkY9oijytg+8k7H2AV5vruBqhw+7A56q0hP70t/juHYVQ3U1sR/5CKpT7u7S0tIwm810dHRw48YNMjIyQjp1H4bU1FQ8Hs+JFhWFQiGbhoYDpVKJxWIJq1IpaafC+fwFQTizSm+4wvWNjY2wd+InrVYNDw+fOIZpYGCA1NTUsIXAKpWK2tpalEolLS0t3Lp1i+Li4jO5Lk5NTTEyMhKelUdGBnz72zA2Bu99L/j9xNQbUQQEqlVxVNWn8fz/+Q6i10+Pc5KoJ59EV1TExvPP0//977O4uEhTU1NYJs/hoKioiKGhoRML2UVRZHFxkatXr7K2tkZDQwOFhYVnNuV2PyAR95MmUzgcjkPjZe4p6P4+ICEhIeQ17Z3vfKdBqVS+6SEcUlg4t8RKEASF3++/tDcaBF7xnTmvpEOK0blw4QK1tbX4/X6am5tpb28PO0bnpNNHDxNRUVFcuHCB3Nxc+vr66OjoCNvJXjyhYD0s3F2gK6urCQQCNDc3n+h4Zr63jnPRi6+hm0DkNqlxdfzW//g9ul5q5ZOf/w30QiV3Zly8vsJE7uIdIldWWMnOxlNfj3CPF2Gz2YzNZsNisZzIKwmQ4z0GBgZOZPKamJjI+vp62J9RuJ5WgiBgMplkg9WjoNPpwq6aHYednZ2wKjbh+leJosjS0lLY1ePZ2VmsVuuJqkY2m42tra0Tt/4FQSAvLw+Xy4XH4zmxEeN+iKLI4OAgS0tLNDQ0hD+N/Nhju+7sP/oRfPrT6OPVrEcJZKxqeernmrAt29l4aZRu5xSiAL7Ll3GaTJj7+6kqKztT8qLT6U4sZJfMRxcXF6mtraW0tBSt9kCj5FwiIyMjLOuUvfEy3d3dYcXLnAdERETg8XgOEOV3vOMdEYmJiefWduHcEiug+sKFC8r9Jdjz0gYMBzqdjpycHB577DGysrLCitFZX19Hr9efu53DcbBYLDQ0NJCamsrt27fp7u4+dnppYWEBo9F4tj38u8RKoVJRUFBAcXExbW1tTE5OHktql69ts97rJPY1Oma1PyE1vo7mntt84Xc+T8UbG/jIU8/wUt8WlZkGqrV2Nl94AX1JCYXveQ8jIyMn8obaj/n5eYaHh3nNa16D0+k8kSGnBK1WS2FhId3d3WFX6gRBoKCggKGhobDubzabcTgch2Yp7sXD0FmF294LV1+1vLyM1WoNqy0SCAQYGxsjNzc3rGOFXW1LX1/fqQKWRVGku7ub1NRUamtraW1tDWkcGQ6kaUSPxyNXwk6Ej38cfvmX4U/+BL7+dUYtoHHDhy9+noqaNDRbM2z6d/jZQAsT09PEv/nN4HSy0919quM9ChkZGSwvLx97/VlfX+fmzZtMTk5SXl5ORUXFPZPTB42EhASWl5dDttPFM4iXOQ+IjY2VXeMllJeXEwgEKgRBOJclxXNLrGJjY9/z/ve/P2hLKYriiZPozwNOEqMzOTl5X+JrHgQEQZC9XeLi4mhtbaW/vz/kIix51Zy0ZXIspJbS3YUhOjqapqYmOXLisMrIxqCTxZ9tYi7V48juIhDwkpTQwK//4WfQmSL46//5f/h+6yapMRqeLFSx9u1voYyOxvzUU2i1WhoaGlhaWmJwcPDE7cfZ2VnGx8epr69Hp9NRXV3N1NTUgYtJOEhISECtVp8otiY2Nhan0xlWK1cQBJKTk8PytApXZ3WWxCqcVqAoimG3DKenp8OuHk9PT5OQkHCiakdfXx/Z2dmn0kUNDQ3Jtihms5nq6mra29tP3JKXPKqMRuO9VY+/8AV4zWsQf+mX8M904DcqcHar+fFPnqexQo/SH2AucpsLFy5gLChAnZjIVnMz4hl75CkUCvLz8w+1Idna2qK1tZXBwUGKioqoqam5L15MDwIKhSLICBR2NxfDw8NnEi9zHpCQkHAglFkQBF73utepgPCzyh4gzi2xUiqVb3/jG98Y9Avf2trCaDSem8mM0+CoGJ3l5WXW1tYeuOHcWUMylLx8+TImk4kbN24wNDQUpDWbnp4mPj7+7Ctz0s5tzzki5etlZWVx8+bNA1EJrmUv0/+0hj5RTcpTUUwuXMViyuZnnhne9Ccf5Rvf+w7XhvQYtArec9HM1nf/mYDTieVd70Jx9/iVSiW1tbV4PB66urrC1gxNTU0xPT1NfX293BJRqVTU1dVx586dsKJh9qOkpISxsbGwyYpUtQrXD+uwkNT9iIiIkEOLj4Jef3bu6+GI1zc3NzGZTMcSCI/Hw87OTlgVVb/fz8TExIlczhcWFvD5fKfy45ucnGRzczOICJlMJmpra+no6Aj7vHG5XNy8eZOUlBRyc3PvrSWkVsO3vkUgIYn3/M9fQhtvZ2fWi61fidqTybXf/f/oX5vEEXAjCALGS5fw2+24BgZO/5qHID4+Xo59krCzs8Pt27fp6ekhOzub+vr6hzbxdpaQ2oF742W0Wu2ZxMucB0RHR4f0jXzve98bnZiY+IGHdFhH4lwyFEEQ0tPS0oz7dxGvpjZgONgfozM0NITb7WZkZOShxeicJSQrhMuXL6PRaLh+/TpjY2N4PB4mJibIyck5+xeVCE0I8i1lsC0sLNDR0YHX68W3E2Di7+0o1AIZ77VidwzhcK3QY4+ga2WY11vrWNoqwukO8L7LFmi7gXtsDPOTT6LZp4MSBIHS0lKMRuMB+4RQkC6GdXV1B8ryWq1Wzio8aTVHrVZTWlpKV1dX2NUzq9VKIBAIywlep9Oh0WiOrYwIgkBkZOSx7amzrFh5vd5jNTvh6qskE+JwFqWJiQlSU1PD1gu53W4GBweDMjHDxeLiIrOzs1RXVx94rNFolI1njyNX29vbtLS0UFBQcHZmy1Yrc1/9FlrXNln/4wMgOvDf0RKtK+fq31/n2Xf9IT+bagNAX1SE0mJh6/r1MzceFgSBwsJCBgYGcLlc9PT00N7eTnJyMo2NjacPpD5nWF9fZ3R0lLW1NVZWVuR4mfT09HMtvD8JBEHAbDYfuDZduXKFQCDwBuEcssZz2WSNiIh4+/vf/37z/tuXlpa4cOHCQzii+wspRketVnPhwgU2Nzfp6OhAqVSSlpZGQkLCuRh9PS0UCgWZmZmkpqYyMTHBCy+8ELZu5cQ4gljBrkVGdXU1c3NzXL92nYSxfLwbItm/EIMmSsl4/1VWAlF89gOfJaMgh7o/ejuzdifvabJgWZ/D9sIL6EtLMVRXh3x+QRDIzc1Fr9dz48YN6urqQlblpqenmZub48KFC4d+DhEREVRUVNDa2kpjY+OJoo2sVitRUVGMj4+HXUUpLCzkzp077B8YCQVJxF5SUnLk/WJiYrDZbEdOq51VxUpanI+7ztrt9rCiXmZnZ8O63ni9XmZmZrh8+XLYx9nV1UVRUdGJ46rW1tYYHByksbHxyPNG0lxVVVWFrMqsrq7S3d196L/fC5ZS87n27/+S9//pR7Am/wl24ffw5VbzqT/4HP/zd36bj732w/j+9sdYY+LwFr4B9+AAEc3TqCwWBAEEAAEEBBSC9Hfu/puw7/9fcVURBOGV2wUQRA3rG5tcv36dwsLCsx2SeYhwu93Mzs4yOzuLwWAgLS2NyMhI/H7/q7aleRyk6cC98VBarZbS0lL10tJSIfDwkrhD4FwSq6ioqA8+/fTTQXTb5XKhUCgeaG7eg4Tb7cbr9RIdHU10dDTp6elsb28zPT3N8PAwVquVtLQ0oqKiXrUXBylKZWZmBoPBwNWrV8nNzSUpKenMpwI5hrQlJydjcJuYfmkTocKBLjmBHdcqU2uD/OWf3WJ7ZYNf/sLn6Z508nhpJPnRfpb/17dQWSyYn3rq2ONNSUlBq9XS0tJCdXV10AVvbm6OmZmZI0mVhOjoaAoKCmhtbaWhoeFEZLSgoIDr168TGxsb1hh+VFQUarUam812rI4xPj6ewcFBAoHAka15q9XKwMAAWUd4e2k0mrDE8MfB5XId21oWRRGHw3GsjcDGxgY6nS4svdTY2BiZmZlhfzfT09PodLoTmxw7HA66urq4cOHCsddBiVy1tbUd0BAtLCwwPDzMhQsXzlxz43Q6mZscYaz2dbS+/kPU/fh/s5XwOny3LqJNey/v/o10nvuTD/HJD7yFD3z2m0RExUDcBZgBZk7v/XcYmjIy0AeWzvYa8xAQCARYXl5menoal8tFSkpK0OSmx+Ph5s2b96cLcA4QGxvL0NDQgQ3R+9//fktHR8e7gd99OEcWGmdGrARBUALtwJwoim8RBOFPgLcCHmAM+AVRFNfDeJ6IrKyslP0C7ofptv4gMDc3JyeJSzAajRQVFVFYWMjy8jIjIyPs7OyQkpIiL9yvNoyMjJCTk0NaWhoul4uRkRHGxsbIz88nLi7u3i9+x1SsgrC9uxAaMjRcu3YNY/wS37m1Se8PWvjEb3yGeX8eJWl6LhdGsPr1rxNwuYj54AdRhPm5x8bGUllZSXt7O+Xl5VgsFubn55mYmODChQthT+UkJCTIBpC1tbVhf0ZKpVIOam5qagpLm1hQUEBXVxcXL1488nUUCgWxsbEsLS0daQ1hNBpxOByIonhkkC5w5H3CQTgTgVtbW0RGRh77OuGK1t1uN4uLi2FXq3Z2dpiYmKCp6WSaW7fbTVtbG5WVlWGTIclrrr29ndraWoxGIxMTE8zPz5/MTiEMSMaaY2NjNFWU8LaYGHjLF6Gimbwf/ya++J/w6z+fSnNWN6riT/HdT32Zd1d7qapKYuvaVTZffInYj30MZVz83ecDUf7v7v8E37b7l73/7/f7mZubZ25ujviEJL7fp0VljEPv3WR5eflVuX5sbW0xPT3N0tISsbGx5Ofnh6wwajQadDqdrB981KBSqdDpdAc2RW95y1uUn/nMZ95JmMRKEIS/Bd4CLIuiWHL3tlNxlaNwlhqr/wjsVSH+FCgRRbEMGAY+HebzNL7+9a8/0Bx+1PRV+yGZgobCYTE6t27dYmFh4czMFe833G43KysrstmiTqejtLSUmpoa5ufnaW5uDms8/0iEEK8fejx2HwiQVZpOdXUVLyz0893ff47S2hqSaj5BQrSat10ws331Ku7xccxvfjPqE56DUVFR1NfX09vby/DwMKOjo1y4cOHE+oeMjAwiIyNPHNkRFRVFYmJi2HYKkmP4/imcUAjH00oQBIxG47E6K61WeyL/rVAIx8MqHH1VIBDAZrOFZVopbRTCIa2iKNLZ2UlZWdmJRt2lqb2ioqKwQ6MlmEwmqqqqaGtro6enB7vdTn19/ZmSKrfbTXt7OzabjYsXL75S7YyIgGefRbE8S8rVP2Dp37bJTGiktjSKT1z/U/IqC1EpBdSlJajVSlw3m9GqFWjVCnQaBXqNAoNWQYRWSYROiVGvJFKvxGRQEmVQEhWhwhyhwhyhZHt1nr7bN9ArPbzhNfXUlGYRHaHEtumjoKDgVGbBDwuh4mWuXLlybLxMamrqiaaBX20IZRYaExNDREREjCAIxzjZyvg74I37bjstVzkUZ0KsBEFIAd4M/G/pNlEUfyKKoqTebQHCUkfGx8e/9U1vepN5722BQICdnZ0TRUS8mrC9vS0z8uOwN0anoKAAm812JjE6DwLj4+NkZmYeqBYYDAYqKyspLy9nfHycmzdvnmoaDjhRxcqz6kNtUqJQC3gCKyz5VZS+rpbH3/1f0aiVvO+yFXF6kq2XXkJfXo6hqupUh6TX66msrGR4eFi2QzgNCgoK8Pl8jI2NnehxOTk52O32sKOH8vPzGRoaOnYhMplMuN3uYwmR1Wo9ljCfhYA9HAsFu91+LLFaXFwkLi7uWLLkdDqx2+2Hboj2Y2xsjOjo6CCdyHEIBAJ0dHSQnp5+anfyyMhINBoNCwsLVFZWnqm2cXFxkRs3bpCSkkJlZeXBc7uxEeE3foPolv+D6urzWNcuELu5hEanod0xyp/92Z9Rd+kSjuxsnH19+MIYnpAgiiLz8/O8/PLLbG1tcfHiRfLz82XSajWpsG36MBgMGAyGkNYfH/nIR4iLiwvSCv7e7/0eycnJVFRUUFFRwb/+67/K//a5z32OnJwc8vPz+fGPfyzf3tHRQWlpKTk5Ofzqr/6q/Ntxu928+93vJicnhwsXLjA5OXnoezkqXiYc4h4fH8/S0tKrhkCeFHFxcSFTHx5//HE1cLwwFBBF8Sqwuu+2U3GVo3BWFasvAP8ZOKx08hHgR2EdkELx+kuXLgXdtrGxceKd2qsJc3Nzp5rKOcsYnfsNr9fL4uLikdEgkZGR1NbWUlhYyODgIG1tbSc3PAxTYwW7FSutZfciPGnvIqIwh//25T/HlFRGgsaGfXyA1W9/G5XVivktbzl1m8rn89HV1UV9fT2bm5tyvttJIbmrr6ysnGhnKggClZWV9PT0hBX1odfrsVqtYXlVhRPMHI5R6FkI2I+zWhBFke3t7WMFvuG2AYeGhsjPzw/rvNjc3GR+fv5EwcyiKNLb24vZbD51EoPX66WlpYWEhARycnLo7e09k4VXOqenp6dpbGw8Oingv/5XxOJi0v71P7P2ryukmQoxOzfo2BmjoqqCqakpnv7932d5e1vOEDwKoiiyvLzMtWvXsNls1NfXU1xcfKAKF2tSYd/yERBFcnNzQwaOf/jDH+b5558/cPunPvUpurq66Orq4sknnwTgzp07PPfcc/T39/P888/zy7/8y7Ix5yc/+Um+/OUvMzIywsjIiPycX/nKV4iOjmZ0dJRPfepT/NZv/VbQ65xlvIxSqcRsNt9zdut5hRSTtb9D8+STT5rj4uLeekYvEzZXOQr3TKwEQZD6lR2H/PtnAR/wf8J4LqPRaLTsTzcPR0z7aoUoiiwsLJw4wmQvziJG535DiukJZ+dlNpupr68nKyuL7u7uk1kOnKBi5V71o7UqEUWRIccEmwurpKp2dW4FuZnQ1oZvZwfD294Wtq5qP6T2T0ZGBjExMVRXVyOKIrdv3z5VC1ehUFBTU8P4+HhYmX0SIiIiyMjI4M6d8IZnpIXouGOUzEKPOscky4Wj7vMgKlbb29tEREQcSYRcLhder/dY8rW9vc329nZYuh3J1TycgOW9GBkZQRRF8vLywn7MXjidTm7evEl6ejrZ2dlkZWUhiuI9BffCbtXv+vXrWCwWamtrj9d6arUIX/sayh07cc99hjj7a7BszOAIuImty+Zf//VfmZqZ4d3PPcfkyy/jPyJeaXV1lRs3bsh2E2VlZYcSkJhINV6/yNaOH5PJhEKhOFAJv3z5ctgVxO9973u85z3vQavVkpmZSU5ODq2trSwsLLC5uSnLND74wQ/y3e9+V37Mhz70IQDe8Y538LOf/UyeIr0f8TIpKSnHbnRezTCbzQdisi5fvoxKpXrDvT73SbjKcTiLitVF4ClBECaB54DHBUH4BoAgCB9iVyj2fjG81b3xta997YE+Sbi+M69GrK+vExkZeWbxAntjdLKzs8OK0bnf8Pv9zMzMnNhR3mq1cvHiRZKSkmhvb6e3t/f4TLkwNVY+ZwD/TgCNRcXmzjyzbh9/Uf+rPPs//hoAnQp08/Oo8vPpGB9nZmbmVAR1eHhYHomG3epRSUkJZrOZlpaWU1UW1Wo1dXV1J27/pqens7OzE5aju1arJSEh4VgNlUajISIi4sjWrSAIREREHHn+nQWxcrvdRy7y4aQ2hBu4PDg4SEFBQViL4ODgIElJSScSFU9PT7O2tkZZWdmpFtrNzU1aWlooLi6WW5WCIFBWVsb8/PyJSLkEv99Pf38/g4OD1NXVkZaWFv6xVVXBf/kvRPd9F9X/fpFErxa930ebY5THHnuMH/3oR8yvrfGur36V1WvXDjx8Y2ODlpYWRkdHKS0tpaqq6tjJTqtp95pq29qt0ubm5oYdOP5Xf/VXlJWV8ZGPfET2T5qbmws6N1JSUpibmzvQcZBu3/sYURTZ3NxEr9fzL//yL/ctXiYmJoa1tbWQETePAkKlOURHR2MwGCwn0FkdwCm4ypG4Z2IliuKnRVFMEUUxA3gP8IIoiv9OEIQ3Ar8FPCWKYlhXzMP0VS6X61VpxR8O5ufnw9ZonASCIBAdHR1WjM79xszMDElJSae6eEjC/UuXLmGxWGhpaWFgYOBwQhJmxcqzuvv+tVYV87YuBkfXEAMiRSUVu6+7soDodhNdU8PFixex2Wy0t7efyBZgfn6etbW1kJ5J2dnZZGRkcPPmzVO1wKTom46OjrAfLwgCFRUVh8YMhTrGiYmJYy/S4YjYj4u3uddWYDgeVsdt0ERRPHKIRMLGxgYejyesKvrq6ipra2sncmRfXl5mamqK6urqU6VM2Gw2Ojo6qK6uPvB+lUolNTU19PX1nWijtbm56wel0+lobGw81fVY+Mxn8JdVk/hPv0X6SAPR6zNMepZZ9m5w+fJlfvT88/z7t70NX1cXgbvn5/b2Nu3t7fT395Ofn09dXV3YBDUm8i6x2tz9rVssFrxe77Hygk9+8pOMjY3R1dVFYmIiv/7rvw4QcmMlCMKht8Pu+jU+Pi7HyyiVSpqamu5bvIwgCMTGxoYVJfVqxGGygieeeEINNJ7mOU/DVY7D/XRe/ysgEvipIAhdgiD89XEPUKlUby4tLQ1qPzzq+qqVlZX7HmFzVIyO3W6/r63CQCDA5OQkmZmZ9/Q8Ukbd5cuXMRgMXL9+neHh4YMEMUyNldv+CrEaX7vDZPdugHJRWc3uHSbHUEREoM3KQq1WU1lZSUpKCs3NzWFNzG1sbDA8PBzSHVtCUlISxcXFtLS0nGrwIDIykvLyclpbW8OufOl0OvLz8+np6Tn2vmq1mpSUlGNbR7Gxsayurh5JwI7TWel0uuOrkUfA4/EcOekmiiJbW1tHLspra2tERkYeO1wwMDBAYWHhscfk8/no6emhsrIy7MrO+vo6d+7cCenGHw7m5ua4c+cO9fX1h75XnU4n24Acd96IosjIyAhdXV1UVlaSnZ19+laVWo3yH76GwrdD4uf+B/H2TRQitDl2tU+XLl3iE//lvxDY2eFHf/M3vPDCC3R2dpKenk5jYyP7JSLHIVKvQKMS5IoV7FatRkZGjnxcfHw8SqUShULBL/3SL9Ha2gocbLPNzs6SlJR0IOJpenqaqKgoWlpaMBqN8rRkeXk529vb9737Emp67lFBKJ2Vz+ejsbHRnJSU9LbjHi8Iwj8AN4F8QRBmBUH4KKfgKsfhTImVKIoviaL4lrt/zxFFMVUUxYq7fz5x1GMFQTAaDAbz2toaV69e5ebNmwwPDzM9PX2iKZpXE7a2ttDr9Q/UVX1/jM7U1BQvv/wyw8PD9yVGZ3FxkZiYmDMb71YoFKSnp3P58mWUSiXXrl1jfHz8lR9amBUryWrBq19nDhdzt0fJyc9Fb9y9eIuTY+iLixH2fDeJiYk0NjYyOTlJd3f3oVU/t9tNZ2cnNTU1xy7SVquVmpoaOjo6TrXLtFgs5Obm0traGnb5XzJLDEecnpWVxczMzJELsCAIx17MTSYTm5ubh5L4vV5Wp8FxwnWHw4HBYDiSFMzMzBwrErfb7SgUirAW+f7+fjIzM8OuTOzs7NDZ2RmebikExsbGmJqaoqGh4VjbCbPZTE5ODrdv3z70M3c4HNy4cQOfz0dTU9PZ+CMVFeH/zH/FNPgTKr+lItphp2tnHHfg7vmVkMB6RAQ/92u/xs9+9jOamppOvfEUBIGYu5OBEmJjY9ne3j6SxO8NNP7Od74jTww+9dRTPPfcc7jdbiYmJhgZGaGuro7ExEQiIyP56U9/Snd3N3/xF39BU1MTxcXFfOhDH+InP/kJarWab3/72zz++OP33ajUYrGwurp6LrS19wMmk4mJiQn6+/u5du0azc3NEuE/VmcliuJ7RVFMFEVRfbfT9pWTcpVwcJ6c1xtf+9rXCpWVlcDuhdJmszExMYHdbmdubg6r1UpMTAxms/lVHfEiYWlp6aF5c0kxOjExMXi9Xubn5+9LjM7ExAQVFRX3fsD7oFQqyc7OJi0tjfHxca5evUpWVhapfv9uJEYYrUC1ScnSRg+bejPzHSP8/Fvejtu7S8w0Xif60tIDj9NqtdTV1TE9Pc3169cpKysLIv6SML2oqChse5DIyEjq6+tpa2sjOzv7xK3hpKQkXC4XnZ2dR1bI9qKsrEwWIB+1CCuVSjIyMhgbGztyoi01NZXe3t4jvdgkHdVh2hi1Wo3X6z0VCT9OuH6cvsrn87G6ukpZWdmh9xFFkcHBQUpDnBf7sbS0hMvlCnuaz+Px0NraSkVFxbHaoVDH1d/fj9vtpr6+Puz2YXJyslxZzc/PD3q+6elpJiYmDpzfZwH1b/86rn/8Lqlf/UsyX/NLtDda6doeJ2peZHFxkZyMDOKNRsbGxu6ZhMREqpi2vdL2FgRBDi3Oz8/nve99Ly+99BI2m42UlBR+//d/n5deeomuri75vn/zN38DQHFxMe9617soKipCpVLxxS9+EZ/Px+TkJL/4i7/IJz7xCfx+P29+85v5+Mc/jiAIfPSjH+UDH/gAOTk5WCwWnnvuuXt6P+FAoVBgMpkemW6P1+vFbrdjs9lYXV3F7XbjdDrJyckhLy9P3rzq9XqTIAgRoig+HDHxHpwbYrVfX6XX60lOTmZsbIwrV67InjGzs7P09vaiVqtlohUdHf2qJFpLS0tUH5I59yChVqtJT08/8xidzc1NVCrViReKk0CtVpOfn09mZiYjIyNMjo2RCYh3c8MOg2S1MGvrZsscyy//j2d4Ou8x3L7dXZ7OqENziIhZEATS09OJjY2ls7NTjp1RKBRMTk5iNBpP7Dmk1+tpaGigvb0dl8t1Ik0O7FaWnE4nd+7cobi4+Nj7q9VqSkpKZBuIo77f9PR0rl69SmZm5qGVFKPRSCAQOLJyJOmsDjsfJJ3VaYjVcRUrm8125GcqTeYe9TmsrKyg1+uPrdx4PB7u3LlDY2NjWL8bv99PW1sbBQUFJ253+f1+Ojs7MRgMVFVVnfh3WlBQQHNzMwkJCURFReFyueju7kan09HU1HRmouogKJUI3/gq1Fdx+fde4s4Pirnm7OUduhouX76M49o1iuLj6ersvOeXsppU9Ew58fgCaFS7hDM5OVmO0/qHf/iHA4/56Ec/eujzffazn+XTn/60HC9z69YtUlJS+IVf+AU+/vGPH7i/TqfjW9/61j2/j5NCqiC/GomVx+MJIlIKhQKr1So7z3u9Xrq7uw8UJZ544gn16OhoI7uGnw8V91NjdSKE8q9aX1+XnWb1ej0pKSmUl5dz5coVOX9tfn6e69evc/36dQYGBlheXn6gwuzTwuPxEAgETuxVcr8hxehcuXKF+Ph4RkZGuHr1KmNjYyd2xp6YmLhnbVW40Gg0FBcXk7q2hjcmhuu3bh1pNeFe9aOMDjDjWUFUq/jQu/8djY2NOB2779FUVIBwzM7fYDDI4cjXr19naWmJqampsPQ3oSCFcG9sbJzYYR2gqKgIl8vF+Ph4WPePjY3FaDQealooQaFQkJ2dfaw2JSUl5UgR+3E6q3uZDDyqYiVNZB3lWn3cNKBUrdpb2Tnsft3d3RQUFITVzhNFkY6ODpKTk09cvfZ4PLS0tGC1WikqKjrV5kehUFBeXk53dzezs7PcvHmTzMxMysvL7w+pugt1RS7LH/gs5jsdVD/3Ml69SEZGBgqFAoXRSFF8PMMjI/c8ySwJ2Fe3XmmTK5VK4uPjmZ+fP9FzbW1t0d/fz8svv8zKygr5+flcvnyZrKysc5dhGxcXF9b073mA2+1mfn6enp4eXn75ZVpbW1lfXyc+Pp6LFy9y6dIlioqKiI+PR61WYzAYcLlcB6xg3vzmN5+ln9U94VxUrARBMObm5kbvZ9dHle91Oh3Jycly68HtdmO321laWmJgYEBmuVJF67Ru1/cL5z37UJrGi4+Px+PxMDs7y61bt9BqtaSlpREfH39ky8Hr9crj4g8MHg+qf/s3eOc7qaquZnBwkJGREQoLC4PaGZLVglu7wqbezNSNO6xlZEJtKo5FG8qAjsiykiNe6BUIgkBOTg6xsbFcv36d1NTUe6qeKhQKKisrGRgYoL29naqqqrCfTzICbWlpQafTHcieDIWioiKuXbsmk6zDkJKSwvj4+JGVoeTkZK5fv05eXl7IRT4qKuqAB81e3C9iJUXdHEY8dnZ2EEXxyMrqwsICZrP52Orr3NwcSqUyLF86URTp6+sjMjKSjIyMY++/F06nk9bWVvLy8u7JAw92N62BQIDh4WGampruK0mQJi9HR0eJe9/PY/7hN6j/X8/T/L4n8Il+VIIShdFIcXy8/PlcuHDh1K8XI1sueEmIfmUNyMjIoLOz81hjZq/XK4emq9Vq0tLSKCwsPNW05oOEWq1GpVIdW8l9GHC5XHJFam1tTe4+JSYmUlxcHNb1TvKz2lvhvXTpEkql8p79rM4C54JYAfV3bemDYLPZwtbnaLVakpKS5MXE4/GwurrK8vIyg4ODwG4rQvrzsInW4uLisbvf8wIpRicrK4vNzU2mp6cZHBwkNjaWtLS0kK2R2dlZkpOTH2yi/LVrsLkJb30rERERVFdXs7m5ycDAboRlYWEhJpMJz92JwA1hBIcxhpf/298yE93MCy+8wM7KKhplHOqEkzldr66ukpaWhlKp5MaNG6fSykgQBIGioiImJiZoaWmhtrY27MVOoVBQW1vLjRs30Gq1x04gKZVKysvL6erqorGx8dAFQxAE8vLyGBoaOvQ3qVKpMJlMrK6uhnxdQRDQ6/WHkiC9Xn/qWCaXy3Vo9fc4fdVx1SqJdNTX1x95DE6nk9HRUS5evBjWMY+NjeH1eoPiVMLBxsYGt2/floO97wUrKyv09fWRk5PD5OTkqVuxx0EURZaWlhgaGsJqtdLQ0IDCo2L2ym+S+Y8foeJb11j65GWSjekojUYupKXxT1/60omc6kPBus9yQYLBYECpVMqh3PuP1WazMT09zdbWFsnJydTW1p677sJxkNqBD6prcBgkvbTdbmd9fR2NRoPVaiUlJYWSkpJTbURjYmKw2WxBxMpsNmMwGMyCIOhFUTz7SawT4FwQq6ioqIuXL18OqtNL/lWnZdsajYaEhAS5vO71elldXcVms8mOxhaLRSZaD7KU6/f7w4rWOI8wmUyUlJQQCATk6qDH4yElJYWUlBTUarUsfj1uITpz/PCHoNXCa18bdLwXLlxgdXWVvr6+XQLu373QLAkDrPpSme0b532/+fP4NzZw7XjQWhQnIoQOh4OpqSlZk7K6ukpbWxuZmZknM1Hch8zMTHQ6HTdv3qS2tjbs6TLJQLSlpYWamppjz7Po6GhiY2MZGRk5kuwnJCQwOjrK9vb2odUtydPqMEIn6axCibrvpWIliuKhpNBmsx26uEh5c/tlCHsxOztLXFzckQur5LBfUlIS1qZtdnaWlZUVLly4cKLzY2Vlhf7+fmpra+8pO9Xv93Pnzh22t7epr69Hr9cTFRVFV1cXTU1NZ1qRWVlZYWhoCKPRSF1dnXxNFzUijoo3sHO7nCtf+Gduv+USyYUfQBERQbTBwBtqaog4on0bDjQqBVEG5QFiBbvawcnJSXkYweFwMDMzw8LCAtHR0WRmZhIdHf1gN4dniISEBLq7ux84sdrZ2QkiUjqdTtbrlpWVncm5ZbVa6e7uJjc3N+j22tpaxdjYWBlw655f5B5wLohVZGTka2pqaoLO3rMmHmq1Wm5twStTQDabjbGxMfx+fxDROs24c7iQdtCv1h8s7FZGEhMTSUxMxOVyMTs7S3NzM0ajEYvFQkRExH39DA9AFOEHP4DHH4cQlSKLxUJjYyMrKytM/HAeDWbs0T4W+sbx+3zU19ez09eHR6FGbwj/uCVNTWlpqaxJsVgsNDU10d/fz+LiIhUVFaf+LBITE9Fqtdy6dYuqqqojdUJ7odfrZQPR+vr6Y3fbubm5NDc3Ex8ff6jgVRAECgoKGBoaOnTowmq10tfXh8/nC6nRsVqtcrxRqGM+jeWH1+s9Ug+0sbFx6Odmt9sxm82HPt7v9zM2NnZsFWpiYgKTyRSWaajNZmN8fHy3anOCRWZ2dpaJiYmwvs+jsL6+Tnd3N6mpqZSUlMjXIZPJREJCwrEEO1ysra0xMDCARqOhoqLiABEUBAFdvJqVN3+a9D9/DxFf/Qc8f/RzqO/+fts6OpgbGuL973//PR1HjEkV5GUlIT4+noGBASYnJ5mbm0MQBFJTU7l06dJ91Zc9KBgMBjweD16v9751aERRDCJSGxsbctZoRkYGUVFR96VtKumsRFEMWkcvX75s/u53v1vH/yNW4PP5cnNycoJuW19fv68TDSqViri4OHl6y+fzsba2Jl/0fD4f0dHRxMTEYLVaz7QMvLy8fK71VSeFFKOTnZ3N+vo6nZ2d+P1+BgYGSEtLu69TgTKGhmBsDO66JB+G2NhYVp0BHNYVNo1mFjraAaivr8f5z/+ML6IRrT78i9Dk5CQmk+lAhUalUlFeXs7S0hI3btygoKDg1FoYKZOtvb2d4uLisH19pOpia2srDQ0NR15cFQoFFRUV3L59m6ampkPL81Jl6zCyIggCiYmJzM/PhyRPZrP5UHNShUJxKu+do3QkTqcTnU536MV9enr6yKilqakpkpOTj6xob21tMTMzQ1NT07HHurm5SV9fH/X19WEvdqIoMjo6it1up6Gh4dSLfiAQYGRkhOXlZaqrq0NWvHJycoKmBE+Dzc1NBgcHCQQCFBcXH/k8ung1q9YmJhqKKP3KVaY+8lNyC96GoNPx3L/8C9944QXe+9733tPiHBOpomtiR16ERVFkdXWV6elp3G43NpuNysrKRzLdQxoYOStbHynI3G63Y7fb2dzcxGAwYLVaycrKOvUE+Wmg1+sPdLVqa2tVMTExTwB/+UAO4hA8dGIlCIKlrKxMtf+Hs7Gx8UA9nlQqFbGxsfKi5ff7WVtbw263Mzk5idfrxWw2y0TrXgSBq6ur96wdOI8QBEH+YV25coWlpSW6u7sRRZHU1NRTx9qEhR/8YPe/b37zkXdzr/pwLfrwl8+yHWFhuXWMlJQU1iYnMc7P4y2LxKQO7yIutQCPaiPFx8cTHR1Nd3c3CwsLlJaWnmr3aDQaZa8rl8sVVp4d7F5Ys7OzaW9v58KFC0cuUJGRkaSmpjIwMHCk7qewsJDBwcFDRcVpaWncvn07JLFSKBRoNJpDyZBSqTy02nUYjhKuHxVj4/V62dzcPFSn5PP5jv1+pYDl8vLyY7UiTqeTjo4Oampqwt6oiaJIb28vfr+furq6UxOM7e1tOjs7iYuL4+LFi4c+jzQleJqWoMPhYGhoCKfTSUFBQVgO4/p4NaIXbv6HD/C+93+awF/+OYG/fAtKo5Hi5GQcDgdjY2MHWj4nQYxJhdsnYlvfYW1ljvn5eSIjI0lPTyczM1PO83wUERsby/Ly8qnXUimxQBKbS0HmVquVnJwcTCbTQ+u8REVFsb6+HnQdKS0txefzlT+UA9qDh06sgKrGxsYDK836+vpDJR9KpVI20MzPzycQCMhEa3p6Go/HQ1RUlEy0wv1hejweBEF4JErNobCyskJMTIwch5KSksLOzg4zMzNcv36dqKgo0tLS7jnF/QB++EMoL4djDBk3+ndbTbaEYVyqWL7wjb/GuqxEPzSECDhRognzq+nv7w9LfKnRaKipqWFubo7m5mZKSkrCahnth06nk72unE4nubm5YX2GycnJOJ1OOZbkqMdkZmbS0tKCzWY79Bglwejq6mpIUqLX61EoFDgcjpDVSkl4GoocSu3Ak8gAjqpY2Wy2QytS8/Pzsgt9KIyPj5OWlnbkb3V4ePjI9qkEr9dLa2sr5eXlYb83v99PR0cHJpOJ/Pz8U/1eRFFkcnKS6elpysvLw+oCmEwm4uPjmZycJCsr69j7u1wuhoeH5Wt2bGxs2Meqi9v9bP1ZDcw9XkPm128y959eQhcRQdHdTW5XV9epiZXf7yfg3p1Ebbl9h7KcXWK5d3PjdDrva7vsYcJiscjDW+FAsiaRiJTD4cBoNMrrYGRk5LmRsJjNZtbX14M6AVqtloiICIMgCDpRFE+fkXWPeOire1RUVOPFixfNe28TRRG/33+uTnTJvsFqtZKXl0cgEGB9fR273U53dzcul4uoqCjZ4uGw+Ay73X7fs6IeJmZnZw9cjKUYnby8POx2O1NTU/T29pKUlERqauq9jwOvrkJzM3z608fedf2OE32SmnnjNhBLiSULi9XA4o9+xHZOKQ6vgk3bHJOTW6SlpR26Y5ciI8IlSIIgkJKSgtVqpbOzk8XFRQoLC088EaNSqairq6Onp4eenh7KysrCutBlZ2fT19fH4ODgkT5bUlDzrVu3DixAe1FYWEhvb++hJpipqalMT0+HfK2YmBimp6eDiJUoirhcLgRBYHZ2Fq1Wi8vlwu124/f7EUURh8NBW1sbgiCgVqvR6XRotVqZzIfKCzzKfXpmZuZQrZjH42Fubo7Lly8f9lHJ0oHGxqOzX/1+P62treTm5oY9xSc5saemph7ZqjwKEpk2Go1HtndDITs7m2vXrpGamnroOeDxeBgdHWV5eZm8vDxKS0tPvOjq4naf27Jmou0zH+Ftr/1lfH/y31A88TFyTCZUKhXd3d28853vDPs5RVFkY2OD6enpXd2PIhXQc7m+kqiIg0teUlIS8/Pzp/6czzNUKhWCIBxKHKXPSiJSOzs7REZGEhMTQ2FhIUaj8dwQqf0wm80hPfiqq6slAXvrAz+ou3joxCqUcH1ra+ueJl4eBBQKBRaLRc5qCwQC8gna19fHzs6OLGa1Wq1EREQgCAJ2u/3ErtyvFvh8Pra2to4UP9+XGJ3nnwe/H97yliPv5ln34ZzzEvMaDeu6SG78yT9hyVji4298I4GtLXrLa1CuCbztSh5LcxNcvXqVnJycA7YRoigyMDAQVrTJfkgO6xMTE1y/fj3sKsJeSO2a4eFh2traqK6uPvZzEwSBkpIS2tvbmZycPNI3Sa/Xk5OTQ29vL1VVVSHvYzKZ0Ol0rKyshDyfExMTGRkZoaCg4MCF2Ww209XVxdzcHOvr62xsbOB2u9Hr9fh8Pnw+HwkJCfIQibQ4bG1tUVRURCAQwOfz4XK5cLlcbG9vA7teUx6Ph4iICKKiojAYDKhUqpDkeHt7G5VKdSipHx0dJSsr69DP1e/3093dTU1NzZHtMmlaMDExMSxfMUAmkIWFhafWYs7OzjI6OnoiTd5eqFSqQ6OMfD4fY2NjzM/Pk52dLacOnAZKnQJ1lBLTagQdT6TgePMVUr5xnfknfg61x0NhYSHd3d1hPZfb7WZ2dpbZ2VkMBgNpaWmUlJTwTy3rmAyekKQKdj3abt++/UgSK9gdGJF0VnvXKZvNhtPplNep4uJieZ16NUAKbg8lYP/+979fx//NxMrn8+Xl5eUF3XbUFM95hRTMGh0dTU5OTtBOoL+/X94JrK6ukpycfOBkeBQQTiyIhMNidCwWC2lpaZjN5vA/nx/8AOLioLb2yLtt3NmtDCsyt1j3Gbnxtz8i/Z1R7MTE4IyKpXdNQ2WWAYtJh8VUSFZWFsPDw4yNjZGfn098fDyCILC8vBxWtMlhEASBrKwsYmNj6erqIi4ujtzc3BMtToIgkJ+fz9TUlGzHcNzkoSAIVFVVyQaiR+kukpOTWVhYkL/TUCgoKOD27dshWz9KpRKLxSITL6mVvri4yMrKCm63m/X1dVkDJmmOlpaWsNvtIRc5hUIRsrUoVZ6USqVc2drY2GBmZoadnR2uXbtGQkIC8fHxcitjf8VsL1wuF8vLy0dWq+7cuUN6evqxG8A7d+6g1+vDaqkB8vBHRUXFieNtYLeK1NPTg0KhOLLiGA72Rxn5/X65rbg3CP1eoYtXobdr2fQ70X7uCyjLK1B+5znEvMf5/j//MwlHmHgGAgE5XsblcpGSkkJDQ0NQ5XLG5iEt5vDhA4lcn0czzXtFIBBAq9UyMjLCxMSE3FmJiYmhrKzsVa0tEwRBJlchBOyPA3/1sI7toRIrQRDMJSUlB4Tr6+vrDy2c+KwgCAJmsxmz2Ux2drY8ibK2thbkBSS1Ds9T7/q0mJ2dPVUVR4rRKSwsZGVlhbGxMRwOB8nJyaSmph5NGLze3YrV299+bPDyxh0nungVc7pxJl4cwbm1w1te+1pcg4MMVP4cARdcLHhF/6LVaiktLWVnZ4fh4WFGR0fJz89ncHCQ2mNIXDiIjIzk4sWLjIyMyKaiJ63UpqenB3ldHTeBqVQqZQNRjUZzaGtKEATKy8tpbm7GYrGE/A4iIiIwmUwsLCyErMZIQvjZ2VnW19exWCwkJCRQUFDA6OgoRqPxQEXmNJYLgUBAXuAFQcBoNGI0GrHZbOTm5mI0GllaWmJwcBCHw0FsbOyRBr3Dw8Pk5eUdSnRXVlbY3t4+1thzfHwcl8t1aNVvPyRfuLq6ulNN0i4vL9Pf309+fn7Y1bGjoFAoyMnJYWhoiKioKMbHx0lOTpbtCD7ykY/wwx/+kLi4OPr6+oDdFvm73/1uuSr6j//4jzJB/NznPsdXvvIVlEolf/EXf8Eb3rBrkr0RsCOs6PD7A/z615/lvz79GhK/c5XpX6/ij3/3d/m3W7ewWq1885vflCutW1tbTE9Ps7y8LOt/Qm3GN3f8rDv81Ocd7VOYkpLC7OzsPYnkzwP8fj/r6+uy/YHH48FkMuFyuWhqanrkiKOks9r7vsrKyvD5fBUP76geflZgSOH6o5LKvReCIODxeGQX3ytXrshtkuHhYV566SVaW1sZGxtjY2PjVGPnDxNerxev13tPLVxBEIiLi6OmpoaGhgaUSiW3bt3i1q1bLCwsHMiGAna1Vevr8NajI6K8W34cMx6iivRMeG0MPd+2m/UXHY1bUNPjjaE4VS87Ne+FwWCgoqKC8vJyBgYGcLvdeDyeU7/PvVAoFOTn51NcXEx7ezsTExMn/u7j4+OpqKiQM7aOg0ajoa6uju7ubrmNdtj9ioqK6OrqOvSY8vPzGR4eDvp3SXvT3d3N5uYmycnJvOY1r6GiokJu90pGoftxUpNQv99/KAFaW1vDbDbLMUx1dXVylSUQCHDz5k1mZ2eDzqudnZ0Dgti98Hq99PX1UVFRceRGaH5+XvYwC2fDNDU1xcjICA0NDScmVT6fj+7ubiYmJmhoaDgTUgXI3+n09DTr6+tcvHiRvLw8Wcz/4Q9/mOeffz7oMZ///Od54oknGBkZ4YknnuDzn/88sFu5e+655+jv7+f555/nl3/5l/H7d/P7/vaf/j9Uggrjhp6Z1QU63/pOBL+Irv0qkRoNTz/9NE8//TS/+Zu/yeTkJNeuXaO/v5/o6Ggee+wxSktLD+1wzNh2f6dpsUcTq8TERBYXF0//YT0k+P1+bDYbg4ODNDc3c+3aNWZnZ4mIiKCyspIrV65QVVWFTqd7JAemJGK1FzqdDoPBYBQE4QEaKQbjoX7SUVFRjU1NTea9t4miiM/nO1fC9bPCXn2VIAhERkYSGRlJZmam3MKw2WyMjo4G+YNYrdb7ZrR2VlheXj5T7ZhGoyEzM5PMzMyjY3R++EPQaOB1rzvy+TYGnCCCuVjPjHOH4Z+084bXvx6xv5/h7CbcPmgqPJoURkREEAgEqKysZHBwEIVCQWFh4ZkY2UZHR3Pp0iXu3LnDrVu3KC8vP9Hu0mw2U1dXF7Y2x2AwUFVVRXt7Ow0NDYdWBePj41lcXDzU70mn0xEbG8vMzIzscSXF+zQ1NTE1NcXOzs4BchEdHS1XOfZCpVLJC244OKx943K5UKvVB1pVSqWS7e1t6urq0Gg0TExMMDIyQmpqKpmZmXLQ8mFkqKenh7y8vCO/G7vdzsjICI2Njce2ykRRlCfq6uvrT7z4ra6u0tPTc88u//uPaXl5maGhIcxmMxUVFSwtLR0YDLh8+fIB8fD3vvc9XnrpJQA+9KEPceXKFf74j/+Y733ve7znPe9Bq9WSmZlJTk4Ora2tZGRkMLx4B8ohajWCN73jKf7hOy9R/LaLxH+vmac+/x4u/8an+ZVf+RV+8pOf8Ed/9EcnipeZsXlQKSHBfPR6otFoUCgUR0YjnQdIxtaSj5Tf7yc6Olo25Dzs2PfqrB4lmM1mpqamDtxeXV0tjI+PlwLtD/6oHjKxMplMIR3XH4ih5EOA3W4/1EJibwsjIyMjyNF2YmIiyNHWarViNpvPFdFaXFwkOzv7vjz3UTE6Gd//PsJrXgPHVMo27rjQxqgIWAMsDOyQVZjK2y5fxr2+SXdaNtkxWpIsR+9qJycnSUxMlP3O7HY7PT096PV6CgoK7lmvoFQqKS0tZWVlhZaWFvLy8uSQ8XAQERFBQ0OD7HV1nBg3KiqKoqIi2UD0sEW9uLiY69evExMTE/K3mZGRwdWrV9Hr9Qemw1JSUuR4n/3vVa1W43a7D5A6QRAIBAJhnd+HeVgdNn3r8XjY2dmR/daKi4vJz89ncnKSF198UW6BhsL8/DzAkd/J1tYWPT09YRmABgIBenp6EASBurq6E5GiQCDA0NAQq6urYbWAw4XdbmdwcBC9Xk9NTQ0Gg0GOqApH+7q0tCRX+xITE1leXgZ2w6n3RlylpKQwNze3+xmZAiCAaTUCMn3Mzc3h/+xnEX/wZpJ//B0AeeTfYrGciPhM29wkWzSolMd/tvHx8SwtLZ0rEfvehBC73U4gEJATQrKyssJOdIiJibknP6vzCp1Oh9PpPEzAXsv/jcTK6/UeEK7fb8f1hwWv14tCoQh7RyoIAhEREURERMg/dIloTU1N0dPTg0ajkacOo6OjHxrRCgQCbG5u3veBg/0xOgtdXQgjI8y85S1ol5cP9c/xOfxsT7qJazIy4VlGH23k83/9KWo6dHRq0nH4FFwqPLrq5PV6D5hFWq1WGhsbWV5epr29HbPZTF5e3j3veGNjY2lqaqKnp4eFhQXKysrCzrLUarXU19fT0dGB0+k81v8oLi4Ot9tNe3v7oQaUKpWKsrIyOahZej6/38/4+Dizs7NYLBZiYmIOtKF0Oh0ajYbNzc0DYn9pF73/MZLOKhyycFjFKtTzwq4OMCUlJegzUalU5OTkYLPZ0Gg0XLt2jby8vKBBDJfLxdDQ0JHRNi6Xi46ODqqrq4+tNvp8Ptrb2+Wp4pOQqs3NTbq6ukhMTDzU7uKk2NjYYGBgAIVCQWlpadB3JQgChYWFDAwMnDr/M1QrWXJB94s+tDFKolYNjCdOs7a2Rr97kuq0aAzLWwCybcdJ3qvXL7Kw5qUhPzx5QkJCAv39/Q+VWHm9XrkaZbfbAWQilZOTc+pM25P6Wb1acJiAvaamRhUbG/s48KWHcVwPjVgJgqDOysrS7i+Vb2xsPJJ2BGcx6SiNEEuO1k6nE7vdzszMDL29vajV6iCidRYTO+FAMop8kOJ7nU5H5l0CHl1UxNjCAv39/SQkJByI0dkYdEEAoor0tLoG2Vm0kRgRy87QED2FHyDZrCYz/vhqVXp6+gFiLAgC8fHxxMXFMT8/T0tLC3Fxcfd0EYTdqcnq6mrm5+dpbm6muLg47N/FXq+r7u7uY4NPU1NTcTqd9PT0UF5eHvJ7tFgsREdHMzY2Rk5ODna7nd7eXpKTk7l8+TKiKHLt2rWQn5EUzLxf7G21WkMK3yWdVTjEamdnJ+T03OrqKsXFxQdun52dDekYv7a2BkBVVRUul4vBwUGmpqaoqKhAp9PR1dVFcXHxod+pZABaUlJy7LSo2+2W22DhOujDLjkZHx9nbm6O8vLyM9nIbG9vMzg4iNfrpaCg4NBJRGnjtra2duS0Ynx8vDxJurCwIJ+zKSkpzMzMyPebnZ0lKSmJ5ORkpqamcGkcRK1GsOrZorS8AJd6GNQa/GsOYPcc3djYCNsHDGB+1YM/AKlHTATuhdFoxOl04vf7H9i10+PxyCRqdXUVQRDkTUpeXt6ZSWJUKhWBQCDsSvCrCVFRUXJHR8JdU++ih3VMD7NilZmTk3NgG+NwOM40fPm84H5YSOj1etndHHZ3zHa7nbm5Ofr6+lCr1XLrMDo6+r6JFxcXFx9OiXlzEwBjYiLl5eX4/X4WFhbo6ekhEAjIMTobd5xozEp0CSputnTwpxd/ldjPfJQGcxPrAS1vLDp6IjMQCDA7O3tktIkgCCQnJ5OYmMjMzAzNzc0kJyeTlZV1T597UlISFouFrq4uFhcXKSoqCuv5BEGgrKyM0dFRWltbqampOfJxubm59PT0MDw8fOi0XEFBAdeuXZN9p+rq6oLacGlpaYyPj7O/Ch0fHy9nx+29qEdHR3Pnzp0Dr3OSyUCn03mAmLndblQq1YHFcWNjQzYV3Y/BwUGKinavwzqdjoqKClZWVrh16xaRkZHo9fpDiW0gEKC9vZ2srKxjDWO3t7dpb2+nqKjoRBvInZ0dOjs7MZvNXLx48Z4XfqfTydDQENvb2xQUFIRldJuTk8PY2Bg1NTWH3uepp57i2Wef5ZlnnuHZZ5/l6aeflm9/3/vex6/92q8xPz/P8PAwZrOZ4eFhNBoN28IGxu04Vp1bPPlz+Xj9U6j9OrwbdrRaLf39/Tz++OMn2rxJwvVwiRXsVotXVlbu2/XM7XYHESnJeDouLo6CgoL7KjCPjIxka2vrVWdldByMRiMOhyPotrvkP3wWfsZ4mMQqr7y8/EC9XApNfdSwvr7O/qDps4ZOpyM5OVnWgEg/4oWFBe7cuSN7C0lahbP6EdtstiPdvO8btnbbBNwl4kql8kCMTvOLN4gazSKyUsWqf5uO528AUB0ZRXfSBayRKgqSjz7fpJ13OJ+XQqEgPT2dlJQUeYJJ8us67WKo0+m4cOECU1NTXL9+nbKysrB27oIgkJubG2THcNhvSyJira2tTE9Ph8z5W19fx+fzYbfbeeKJJw68H0lrlZmZGbTTVigUxMbGBulvAJn87HdMNxgMbGxsHPv+ILTG6jB91WHvy2azoVarDyw4sbGxVFZWcuPGDaKiokK2HUVRpKuri9jYWHmDcxhWV1fp7u6mqqoq7MVNFEVmZmYYHx+ntLT0nlMb3G43w8PDrK6uBnmzhYPo6GicTqf8Obz3ve/lpZdewmazkZKSwu///u/zzDPP8K53vYuvfOUrpKWl8a1vfQvY1em94x3vID8/H1EU+ZVf+RUMBgMXL17k2Wef5cu//VX+fe0zJEQmIfqvkR7bgKB8kai7G5a/+7u/45vf/OaJ3uuMzYPFqMSoC/93l5CQwMzMzJkRK2mza7PZWFtbQ6VSYbVaSUhIoLCw8IFO6kkTdI8isdpbDZUQFRWlFATBKIri4aPP9wkPjVgZjcaS0tLSoNKUNPb8avdzCoWtra0HXonTarUkJSXJO3qp7Ly8vMzg4GBQ2dlisZyq7Ly9vY1er39gpfMg3K1YEaL1IsXomGYTWBa32TAv0dw/w9CP20nPiUWry2FFYeLpQiMKxdHn28TERNheRBKUSiXZ2dmkp6czNjbG1atXyc7OJjU19VTntyAIZGRkEBsbS2dnJ1arlfz8/LDK+qmpqeh0OlpaWqipqTnUEkMQBKqrq2UD0b0VlYmJCWZnZ6mvr2dhYYGhoSG5wrP3PWdlZTEyMnLg39LS0hgYGDhgYyDprPbertfrwx59DzVBHGr6KRAIYLPZDrQHRVFkcHCQioqKA88tBSDX19fj8/loaWmhrKwsiNwMDg6iVquPHdxYWFhgeHiYCxcuhD3k4Ha76e7uRqPR3LPZp9frZXR0lKWlJXJycigpKTnxeSidg5OTkxQWFvIP//APIe/3s5/9TP67KIqsr68zPT1NU1MTP//zP09aWlrQOVhTU0PR/y5j5G9WMPvNKBQaClLfREDzP4hSqxkbGzvx+xVFkRmbh+yEk03cR0dH09PTc2oDZ0meYbfbWVtbk+UZycnJYeWK3k+YzWZmZ2fPlTj/LGA0GkPaxhQVFQkDAwO5QOeDPqaH1myNjo6u3t8yCFdX8WqDz+dDqVQ+9N62RqMhMTGRkpISLl++TH19vewndPPmTa5evUpfXx+Li4t4vd6wntNut58qUPhMsK9itR9+VwD7LQdRRTpKHyuhb2uKmdYhmh7LotdUi0EjUpJ69IV3bW0NjUZz6ok/lUpFfn4+Fy9eZGtri5dffpn5+flT+5RFRERw8eJFVCoVzc3NbEmfwTGQqi9tbW2srq4eeby1tbXcuXOH9fV1AoEA3d3drK2t0djYSEREBNnZ2aytrYV8ntTUVJaXl3G5gvNPTSYTHo8Ht9sddHsoP6twvawO+wxXV1cP6IAWFxeJi4s78BtcWlqSp3H3Y2RkhJiYGKKjo4mNjaW+vp7+/n55vHtyclI2Cj1qEZ6YmGB8fJyGhoawz6PFxUVu3LhBWloaFRUVpyZVPp+PkZERrl+/jl6v5/LlywfE+ydBcnIyi4uLx1piuN1ueUMxMjJCfHw8V65coaioKORnrbXu7vEjNiJISXsdOo0JUaPBub7On/7pn574ONccfrZdAdJiTkasFArFibzUpMp4Z2cnL730Ep2dnTgcDlJSUrh06RIXL14kPz+fmJiYh0qq4BUt0qMGjUYTcr2qqKiIAPIOPuL+46FVrPx+f+F+l1uHw/FIEquNjY1Tx5/cT6jVahISEuTdvdfrlT1SRkZGgkZ7Y2JiQgp3bTbbfW9xHgqJVBzy2dpaHfhdInGXI+lwjPHysz9EpVbyROM7mNAnUh3r5EbztSNjdCYmJsKOIzkKGo2G4uJiXC6X7OJeUFBw6CTjUZBafHFxcdy+fZuUlBSysrKOfZ6oqCguXLhAW1ubPPUWClqtltraWlpaWlCr1SQlJZGdnS0/vyAIVFZW0traSlNTU1A7Q6FQkJuby/DwMGVlZUHPKwmY954vFouFgYGBoPup1eqwiP3+SSDYrcqGmr6dnp4OWa0aGhqirq7uwHNvbGywtLQUNAWo1+tpbGyU9W5er5eGhoZDP3cpU9LhcFBfXx/WwioZkHq9XhobG8Mep9+PQCDA1NQUk5OTpKamnln8jDSZOzc3d6CtGk68zKHPqwWfzknkhp6omCwQBESNBq3Xy0AIHd5xOI2+SkJMTAw2m+3AWrTXAsdut8uavZiYGNLT08+dBc5+PMoCdqVSic/nC/rdFxUV6WNjYyuBk/WQzwAPU2Nl2a8TkWJeHjW8Wiwk1Go18fHxsrnkXjO68fFx2YxOmjw8bIz+gUFqBYaoWPk9AVZubBOZq0WVoODqUj/v/E/v5bU5SlbUb8KidPGWpmwUQvahMTper5fNzc171rXshU6no6ysDIfDwdDQECMjIxQWFp5o2klCVFQUTU1NDA4OcvPmTSoqKo6tiBgMhiCvq/3+UhIksuB2u0MaTxoMBjIzM+nv7z/g+5SUlMTY2NgB/VNycjI3b94MImlSSLLX65WrMtK/HdeO2dnZOUCsQumrXC4XXq/3QCt+bm4Oq9V64Dn8fj9dXV1UVVUdWIBUKhVZWVm0trYeed4HAgG6urpQq9XU1NSERZ6lScvs7OxTV5VEUWR2dpaxsTESEhJoamo6c7Pl9PR0Ojo6ZGK1ubnJzMzMsfEyR2F6qQW3QYFx3cRGwAWCgEelIhLIOcHkpIQZmweNSiAu6uRLXExMDKOjo6SlpeFwOGSN1ObmJnq9npiYGDIzM8+9aXMoPKoC9oiICBwOR9D7umvkW/EwjufEZ50gCEp2TbfmRFF8iyAI7wR+DygE6kRRPNaQSxAEY2Fh4YHX3t7ePtH48asFD0K4fj+gUqmIi4uTtTZ+v18mWlKgZyAQYG5ujpiYmAc/dLC1BWo1hNjVr7Y58O8EiH8sklbHCNsBFzXCBqsVH2R8zcw7kzdR3tVWSe/R4/EwNzfHrVu30Gq1aLVakpOT74vmLyIigqqqKjY3N+WJucLCwhNf8JRKJcXFxdjtdlpbW8NalDUaDfX19dy+fRun00lhYWHQ/be3t2lra6OqqgqPxyMbiO6veKSlpbG4uMjS0lKQ07sUED00NERlZWXQ60ZERLC+vh7UqrNYLAd0UaG8afbjMOH6/mm7mZmZA9eVQCDA6OgoDQ0NB553cHCQlJSUkJrI7e1turu7uXz5MsvLy9y6dYu6urqgnbLX66W9vZ24uLiwTHP9fj+Dg4NsbGwcmLQMF6Iosri4yPDwMFar9Ug3/XuFXq9HoVAwODjIysoKGo2G1NRUCgsLT0U0fH4Xdya/j8X0RiIXE1jzb4EgsOr3YwVyTiEkn17xkGLVHKuf3AtRFNne3sZut7O4uMiLL75IRESEHBQumcq+mvEoC9i3t7eD3ld2djZerzeshVcQhL8F3gIsi6JYcve2PwCeBgLAMvBhURTnw3m+01Ss/iMwAEjbtT7g54C/OcFz5BQWFh44Qx/VitXDEK7fDyiVStl1HHZDZh0OBw6Hg+npaTweD2azWW4d3vfAz83N3WrVvotdwCuy3LyNMVOLKkXBtcV+fvIrX8ZfF40u889I3Z6mIOdge29/jM6NGzdkd/CgGJ0zhMlkoq6ubtcUsb8fjUZDQUHBiX8HVquVixcv0tfXx8LCAuXl5UcurEqlkpqaGvr7+7l9+zaVlZUoFAocDodMqqSLlGR8WVtbG7SwCIJARUUFN27ckDP5JMTFxTE6Onrg3Jc8rfYSK6n1spdYSZYLR51DTqfzwOckTbtJEEWRubm5A8ae09PTxMfHH/iMbDYbGxsbB8T3gGykWlVVhcFgICMjA4VCQWtrKxcuXECpVOJ0OmlrayM7Ozss1/yNjQ26urpISUmhqKjoVAv3ysoKg4OD8rl0v353oiiysrLCzMwMDoeDQCBwoniZwzAy81Pcnk3i0zPZmFQxv+2ESIEVr5dcIOOEGk63N8DShpfLRUdfc0VRZGtrS27tSeuPlGxRVlb2SFy39yIqKkpOEHiUYDQaD+hN7w5VRQqCIIjHi1r/Dvgr4Gt7bvsTURR/G0AQhF8Ffgf4RDjHcyJiJQhCCvBm4I+AXwMQRXHg7r+d5KnyysvLD4ipvF7vPZkqnkdIIbGvtpJxOFhbWyMnJ0degAOBgJys3tXVhcvlCiJa9xr5cgBbWyH1VaudDnzbAeLfEUmLY5g717u49Z2XyEn7j2Snq2iwtaKy1h751IFAAKvVSnV19YEYneTk5DM/T6Ojo2lsbGRlZYXOzk4iIyPJz88/0SKpVquprKyUhc+FhYVHjo0LgkBJSQljY2O0tLRQUlJCR0cHlZWVQTu/9PR0nE4nvb29QXE1sKvHKigooKenJ6jlJQgCBQUFDA4OUlv7ymcdGxtLf39/kAmjxWJhaGgo6NgkAfFRLdKdnR2Z5AOyLmtv62ttbY3IyMig2/x+PxMTEzQ1NQU9n6RvChUv4/P5aG1tpaioKOizSUtLQxRF+d9u375NaWnpsQMdoigyMjLC4uIiVVVVp1rAV1dXGRwcRKvVUllZed82pdLGaXFxEYvFQmZmJhUVFVy9evWe24w7rlVGZ/+NlNgaLIo4NljFZfMiJAm4754faSdsk8/ZvYgipO3TV4miyObmpkykJM9EacI2MjIyqA29urr6SBKr/ZrGRwEREREhJ4nj4+OZnZ2NAVaOerwoilcFQcjYd9vm3pcAwp44OmnF6gvAfwbu6WyLiYmpKC4uDloxfD7fI0k+HlVBvnSR2lvFUSgUWCwWeTEMBAJsbGxgs9no6enB6XRiMpmIiYmRidY9ldalitUeBHwiy9e2MaRqUKRD89IAg1+7SmSUgfTKf09pYJZYkwrhGP+Yubk5UlNTD8TozM7OcvPmTSIiIkhLSzuV+PwoxMbGEhMTw9LSEq2trVitVnJzc0/U1klISCA6Opru7m4WFxcpLi4+cgHMzs5GrVZz9epVqqurQ+oB8/Pz6erqYnR0lP1DJ4mJiSwuLjI7OxvUcrNarYyMjARpDCWn+sXFRbmiIx3bXp2VwWA4YPq3H/tbgaurqwf0VaHagBMTE6SkpBz4TPr6+sjOzj6wAZAMQDMyMkKaeqanp7O5uUlzczMXL148ts3icDjo7OwkJiaGpqamE1/3Njc35cWxuLj4vrR1fD4f8/PzzMzMIAgCaWlp5OXlBbWDY2NjsdlsxwZ+H4U7k99HFEWKMp9Gub37mwys7q5fpRkZcOMGcSfckE3bdidPk61qeaNnt9vZ2dnBZDJhtVopKioiIiLi0N+upLN61KwJ1Gr1iULOXy2IiIgIablQWlqq6ujoyOMYYnUYBEH4I+CDwAbwmnAfFzaxEgRB6j92CIJw5aQHuBcGg6Fyv9WCw+F4JNuAj2p7U2rTHEUqFAoF0dHRREdHk5ubiyiKbGxsYLfb6evrC7rQWa1WjEbjyUhKiIrVWs8O3g0/KU+ZuekYYml2gds/auaxp9+L3qCjZqYNdVroabi9WFlZORCYrdPpyMnJITs7W/bmkWJ0UlNTz+x7FgSBhIQE4uPjmZub4+bNmyQkJMgEKBxIk32SC/xR5pKiKLKwsEB2djaDg4NEREQcaHtK4cStra2y4/9elJSU0NzcfKAFXFBQwMDAQJCWKS0tTY7DkWC1WlldXZUXab1ef8CGYT/2G4vabLagSpGkCdw7nej1epmZmTngor+wsIDX6z3wvkRRpKenB4vFcqj+c35+Xj72lZWVQ4mOKIrypF55efmR0TCh4HA4GBwcxOVynXrg4ShIVZrp6WnW19dJSkqisrLy0EpzQkICc3NzpyZWa1uTzC63kpf6Bgw6K6JaRFSIqFaV+EQ/orSZCNNSJBAIYFtdo3vMgVEd4NaNq0RFRWG1WikpKTnRRs5kMoVtZfJqg1qtPvDbebVDmnjcj/Ly8kilUpkPNJ/meUVR/CzwWUEQPg38B+B3wzqeE7zGReApQRCeBHSASRCEb4ii+O9OerA+ny9v/07gUa3sPKrE6jSTjoIgYDabMZvNZGdnB5XmpbF0KcXearUGleZDYmsL9iwuol9k+eoW+iQ1ikxoWR5i6h9aASi58itcydej7l1BXVtx5HFubW0daXoqCIJMGKUYnd7eXgKBgNwqPAtHZUEQSElJISkpienpaa5fv05qaiqZmZlhjc5LlYaYmBg5DqWgoODAYwcGBjCZTBQWFpKcnExHR8cBI0zYJco1NTXcuHEDrVYb1IZTq9WUlJTQ2dkZZEFgNptRqVRBpMdoNOL3+4M0VJKflbRIH+clJEkm9p4fq6urQXE6CwsLJCQkBN1nbGyMjIyMoO/H7XYzODgYMtB4eHhYtrcIhbGxMZaWlmhsbESpVHLz5k0iIyMPkA2Xy0VXVxcGg+GARcVxkAKgNzc3yc/PP/MqqdPpZGZmhvn5eUwmk+ydddxrWCwWent7T2WmKYoifWP/hFYdSW7q6wEQlAKYRYwbejb9O/zByy/zFwAhKhGwS6TW1tbkqT2X28PQdhr2HS1vrozkQkHYBYYDEAQBlUr1yBEQeEXofdbE/GFjP2EURZGsrCx1fHx8LfC39/j0fw/8C2dNrERR/DTwaYC7FavfOA2pAlAqlVE9PT34fD5gd3fq8XgwGAzMz8+j1+sxGAxoNJpX/RTG9vb2PZXKzys2Njbu2UJCEASioqKIioqSidbW1hZ2u52hoSG2traCiJbJZAo+HzY3ISND/t/1PieeVT8Z743ihmMQj+jjteUN2N+iIiXVSpVxmzVAfcz3sbS0FHakxd4YHafTKROgqKgo0tLSziScWqFQyIG9ExMTcmxMWlpaWG0kg8FAY2Mj4+PjXL9+nYqKCrmqMjs7y9bWluzlZDKZqK+vp62tjZycnAM5fFLAc0tLywEtVkxMDIuLiwe8vwoKCuju7ubixYvyZ5GamsrMzIxMhKS2oQStVnvATHQv9i94Xq8XURSDKnrT09NBVhBut5vFxUUuX74s3yaKIt3d3RQWFh5ot0qVm1CaK1EU6e/vx+12U19fL38PNTU13Lx5E4PBIOtz5ufnGRoaOlGQtvQeR0ZGsNls5ObmUlZWdmbXQ7/fz+LiItPT0/j9flJTU0/s7q5QKDCZTKe6FszburBvjlGR+z7UqlcqnGqrEqPNwJrPQcvCwu6Nd4mV3+8PIlJerxez2UxMTAzlFRX8S6eLhW0nb66O4kLevW9mJUPNvRuIRwGPCrESRRGXy8XOzg47Ozv4fD46OzsJBALytWNzcxOtVnsqk1BBEHJFUZQuSk8Bg+E+9p631YIgvB34SyAW+BdBELpEUXzDEfdXZGZmBiThaCAQwOVy0dfXh8FgYGtri+XlZXZ2dvB4dk3etFqtTLak/xoMBnQ63bknXo9qJW59fZ2MPaTmLCAIAiaTCZPJRGZmZtD488jICFtbWxgMBploRW1tIdxdvMSAyNLVLXRxKhS5IreWhynVp6MtzOc12qd5XRkEVmaB44nV4uLikUGzh0Gv15Ofn09eXp7cUunt7SUxMZG0tLR7ntZSKpXk5OQExeTk5OSEZQkhCALZ2dnExsbS1dUl68ZGR0eDCI/0PiSvK6fTecAyQKfTUVNTQ1tbG/X19UHvq7CwkOvXrxMbGysTi8jISCIiIoIIa3JyMtevXyc3NxdBEFCr1QQCAdnk7zgvq/36qrW1taCFYmdnB1EUg357IyMjZGdnB5HRmZkZNBrNASItGV3W19cfeH2/309nZycGg4GqqqoDYv7Kykpu375NfX09fX19AFy8eDHsyofX62V8fJyFhQWysrJOPS24H1Irfnp6GrvdTnx8PKWlpfdUUU9ISGBxcfFExMof8NI/8R1MhiTSEoLtLvQxaozjehY2Vpi+G8S9ODLCWHMzXq9X9tFLT0+XpxEDosh3W9bom3by+grTmZAqeMWa4FEjVhEREaytrT3swzgWUlXb6XTK5En6+96izF5OYDabZR9CQRCw2+0888wzx46VCoLwD8AVIEYQhFl2K1NPCoKQz67dwhRhTgTCKYmVKIovAS/d/ft3gO+c4OExVqtVVtdLEQKCIITUqYiiiNvtlj9Qp9PJ2tqa/IHDbglwP/GSPvCHHSPg9/sfaNDmg4C0U7jfvlWCIBAZGUlkZCQZGRmIoigb9o2NjVG6tcWa3c7myAiGNTPuFR9p74zm+vYgfjHAwnf7WRDqiLMsUJFVzXp/B4Jej+II2wSPx4Moivf03gRBkHVjPp+Pubk5bt++jUKhIDU1lcTExHs6L9VqNQUFBWRmZjIyMsLY2Bh5eXkH2l6hYDKZZFPRq1evHhqXolarqa+vp7Ozk76+PoqLi4Oe22g0ypqrxsZG+TmUSiUVFRV0dXVx8eJFmcTk5+fT1tYmh/6qVCpMJlOQ4NxisbC6uipXdSQH9lCEZL8Vg81mC2pd7hetSxlue93Xd3Z2GB8fPzAduL6+zp07d2hoaDjw2/V6vbS2tpKYmHioI79UhX3hhRcoKysLy3YBdq8Vk5OTTE9Pk56ezuXLl89koMftdjM7O8vs7CwGg4G0tLQD052nRVxcHGNjYwf0iEdhfP5ldlw2Gkv+Awrhld+Bz+cDrRelX8GNF1uwAzs6HeYbN6j57GdDDnCIosgP29bpmnTyeGkkTYVnN8UXFRXF0tLSmT3fecFhocUPGl6vN2hd3/tfyR1+73oeHR1NUlISBoMh5DVrcnLywLXbYrHg9/uPLc2JovjeEDd/5bTv7WGs+IlpaWkHftGHLdSCIKDT6dDpdIeKPb1ebxCjXVpakomX9AXtr3ZJf7+fpMfj8Zy56/F5gPRdPehqoSAIcq5beno6lJYSs7SEW6tluWsDNGq6Hbe5tT2LqneDX/3oJ3jjh/+AP/z0axEEAd/SEuq4uCOPe7/Z5b1CpVKRnp5Oeno629vbzMzMMDIycmSMTrjQarWUlJTgdDoZGhpibGxM1uAcBYVCgVarJT4+nuHhYbxeb0h3dYVCQVVVFQMDA7INw15CaLFYyMvLo7W1NSiyJSoqSn5uacE1GAxYLBbm5uZkgbjkaSURopiYmCCDT0lnFYpY7a9Y2e122YRXEuPvJUxDQ0Pk5eUFVcI6OzspLS0Nugbs7OzQ2dlJXV3dgYXc6XTS2tp6ZByQ3+/nzp078vEdVq3OyMggMjISpVKJSqXin/7pn+jq6uK///f/zvLyMhkZGfzjP/6jfM373Oc+x1e+8hWUSiV/8Rd/wRvesNsU6Ojo4MMf/jBOp5Mnn3ySP//zP0cQhHuKlzkJ1Go1KpXqWM8xCW7vNkNTPyLeUkx0ZC5LS0vYbDZWV1cJBAKY1xKBCLxuFz5gtq6OvJ/9DIaGYF9EkiiK/Oj2Bu1jO1wqMvJY8dlaI0RGRoacNHu14yRZiKeFKIp4PJ4DhGlnZweXy4UoiqhUqiDiFBsbK///aTaeOp3uQCXu7ibugS/CD4VYpaenH9h63EtlR61Wy7vEUPD5fEElRbvdLv/d7/fL5G0/6ZKY8WkXvv8nXL/PqKlB+eUvk5aURCByA7fXh6IwkcD2DL3/eA2lSsOV1+ej9xt2NRlLSxj2OIGHwuLiYpDB5FnCaDRSWFhIQUHBoTE6p4Fer6eiooLt7W0GBwflmJzDNiISwbt06ZKsFVpcXKS8vPzA5kYQBIqKipiYmKClpYW6urqgzYJkQ9HZ2Ul1dbX8W8nJyeHGjRusra3Jx5GXl8fNmzdJSkpCoVBgtVrp6+uT239Wq5WxsTH5uaUFINS5trOzIz+vz+cjEAjIpMFutxMVFSVfT7a3t9na2grSW42Pj8seaxIkl/mKiooDhGhzc5OOjg7Ky8sP1aasra3R3d1Neno6JSUlbG9vc/v2bS5duhSy8vTCCy/IOqqdnR2uXr3KW9/6Vp555hk+//nP8/nPf54//uM/5s6dOzz33HP09/czPz/Pa1/7WoaHh1EqlXzyk5/ky1/+MvX19Tz55JP88z//MwUFBfcUL3NSSO3Aw+KRJHi9XroG/xmf34lrNY2bN2/Kld28vDzUajVj315hxbBFlNXEpZISfHV1cPs2fP7z8Pd/Lz+XKIr8tHuTlmEHDfkRvLbMdOYbPUEQUCqVQTYgjwIUCgWiKJ5q6ECC1LUI1aaT9E0ajSaIOCUmJsoSnvthrSSlNexHRESEQhAEnSiKB//xPuGBEytBEJLS09OD5nePN0W9N6hUKrmlFAqSzks6Qba2tlhaWmJnZ0c2HdRqtSGrXkdVbra3tx9JfdXGxsb5iESorYU//3O4c4eAPwlBKbCh2P3trC2uYUnMJDHWhynSwmJfH9EeD1Pb2ywODhITE0N0dHTQzsjv97O9vX3fTQEFQTgQo9Pa2opGoyEtLY34+PhTXXiMRiM1NTVsbGwwMDCAQqGgoKAgyDpBsg8oKyuT33t5eTnLy8vcvHmT/Pz8A4J1gMzMTHQ6HTdu3Djg7p2ZmYnT6aS/v5+SkhJg9+JdUVFBe3u7PAUnVclmZmZIT09HEAQSExOZn58nLS0NjUaD3++XzUMl9/VQ2Fsh2a+vklppEoaGhigoKJB/p5ubm8zOzgZVtPx+P62trSEJ6crKCv39/dTU1IQ8NwKBAMPDw9hsNmpqauTNVGRkJElJSYyMjBxwg/f7/dy8eZPMzEzq6+vR6XT88Ic/5KWXXgLgQx/6EFeuXOGP//iP+d73vsd73vMetFotmZmZ5OTk0NraSkZGBpubm9TU1DA5OUldXR3f+MY3+OIXv3jqeJnTICEhge7u7gPEyuPxyELz1dXV3QVdt+uhlJYVRXbK5QPP5Vr0smF18NjjV/jQ/8pi86c/RfzoRxH+8i/hD/8Q7rZfX+rb4vrANrU5Ebyx8v5FzZjNZjY2No41fH214bjIqEAgEJI0OZ1OeU3U6XTyeihF/xgMBlnf9KCh0+lCDrwkJSWJQ0NDicDEgzqWB06sLBZLdnJyctDr+ny+h7ojkFqFh/m1SDqvvSeYVPWSGLJarT6g8VpbW3vkhI+wa0ew3+/noUBy9G5vR1Q+haAUsHk3iVToGR0ZJiYxnwitgpSUFAytrbg0GnLf8AbWHA7m5+fp7+9HqVTKu2a/309MTMwDvSjsj9GZnp5mcHCQ2NjYU8foREVFUV9fz+rqKr29vbKoPiIiguXlZXQ63YGqS1xcHGazmZ6eHhYXFyktLT3wm0xMTESr1dLS0kJ1dXXQsRUWFnL79m3GxsZksbvUsh0YGKC0tBTYrWRdv36dlJQUlEolaWlp3L59Ww70jY6OZnV1ldjYWAwGAwvSZNg+7JUO7NVXScHZ0vvb2NjA7XbLv0MpHLmiokImlqIo0tHRQWpq6oE28OzsLOPj4zL52Y+trS26urqIj4+nsbHxAJnJzs7m6tWrZGRkoNVqsdvtDAwMEAgE+J3f+R2USiUf//jH+djHPsbS0pLcYkxMTGR5eRnYNautr6+XnzMlJUWe5jSZTDQ3N5OSksKlS5fo6OgISYzvJwwGAx6PB4fDIRsCr62tyb+t+Ph4CgsLUalUiOJFbvY56Jv4FubIZKxRrwxGBLwiPpvIevk2uco4VHe/M+/734/mS1+CP/kT+NKXuHZnixf7tqjMNPDmmvub3yeFFj9qxMpgMLC0tIRerz9AnKQuzt61LCoqisTERPR6/T11ce4nDpskTk1NVQGPNrHS6/WZ+/UJLpfrvgWGngX26rxCQRRFWeclnaCbm5ssLS1ht9vlsn0ojZder3/VidtDhd8+FOTk7BqEtrUh1r4VQQkrvk2iRT3TkxM0lD6JUa/Cv7WFs7eXiJoaDGYzBrNZFhS73W7sdjtLS0vMzc2hVqu5c+eOXNF6kITfZDJRUlJCIBCQY3TcbjepqamnitGxWCxyTE5HRwdRUVGsra3J1gr7odFoqKmpYXZ2lubmZoqLiw9sDCwWC7W1tbS3twf9uyAIVFZW0tLSgl6vlxf3jIwMbt26xfLyMnFxcajValJSUpicnCQ7O1s2mZWmZyWdlUSsDqtYiaIokxi73S4Lyefn50lKSpIv/IODgxQWFsqPGxoaIjExUa64iqJIb28vJpMpqMoliiKjo6PY7XYaGxsP/EZFUWRiYoKZmRnKy8sPbY0rFApycnLo7e3F6/WiUqkoLy+nra2NpKQklpeXed3rXnek+HtvRd/hcMji+pycHAwGA4899hiCILCwsPBAFzyXyyVXpHZ2dmRRf2JiIsXFxSF1MoKgoKbgI7zc9d9pvfNlHqv8LQy6XRLsWvFCANat27zz8luoKSrhd1JT8apUaD70IfjqV2l//2/w0xkdpel6nq4zo7jP71eaZn01IdR6tPe/0r+vr6/LVSar1Upqauqrcj2SIAhCyO5XRkaGjl1i9cDwMFqBaft3VA9iwux+QhAENBoNGo0m6AK7ublJdXU1Wq1W1nlJpVW73c7MzMyhO4S9/z1POwSpN38u4ocUCqip2SVWVaDQCNh8m5TrM/hR8xDPd24TqZ/G0dYGfj/GPbt+CVqtlqSkJJKSktja2qK0tBSHw8Hy8jKDg7u2JVJFy2q1PhCitTdGx+12MzMzc+oYHantGBsbS19fH06nk8nJSXJycg4laikpKVitVrq6ulhcXKSoqChokTQajbLXldvtlquXCoWC2tpa2UDUarXKQc03b96UiWpmZibXrl0jLS0NtVoti9gLCwuxWq1MTOxuLHU6XUhiJREU2G3h+Xw+eWM2MzNDdXU1sGsYCsitvdXVVVZXV2lsbJSfa3R0FL/ff6BV19vbi9/vp66u7sC57nQ66erqIjIykqampiOFtltbW8zPz7OyskJ1dbVs6yC1FOPi4nj7299Oa2sr8fHxLCwskJiYyMLCgiziT0pKore3l+bmZgRBwGaz8cQTT5Cdnc0f/MEfyOfC7Ozsfa1WOZ1OOR5mfX0djUaD1WolJSWF6OhoXC4X+xM1QkGjNlBf/HFe7vwTbt35Gy6V/zoqpQbnwm6Lad26xfCdQS5eaACFAp/NBr/5m4hf+QrO//5nFP3mf+Xn6qNRKO7/NdFoNAbp/s4D9nZQ9pOmwzooJpNJ/n+FQsHc3BwOhyOs7+vVBGlwY+9vNj093aDVakPHJtwnPHBi5fP54kNVrF7NxOow7DUxDEfntfcHsrGxweLiYpDOa29Pe++P5kH2tM/dd1VbC3/2Z+By4ddpcYs+4tRmXEYrEVE6TNpFHG1taPPyUB0S6QKvXKyk70haAL1eL6urq9hsNkZGRhBFEYvFIhOt++3KrNVqzyRGRxRF7HY7V65cYWVlhebmZpKSksjOzg65Q9Xr9dTX1zM5Ocn169cPVGV0Oh0NDQ20t7fjdDrJycmR/ajq6uq4desW1dXVREZGotPpyMvLo6enh+rqalQqFRkZGYyPj5Ofn09iYiIjIyMUFBSg1Wrxer2yzirUDnRvxXSvvmp7e1uuDIuiGNSC9Pl89PT0UFtbG0RE7HZ7kAGo3++no6MDk8lEfn5+0O9KFEVmZ2cZGxujpKTkyPbQzs4OQ0NDOBwOCgoKyMjIYGZmhoSEBBwOB4FAgMjISBwOBz/5yU/4nd/5HZ566imeffZZnnnmGf7u7/6O17/+9XR2dpKYmMjXv/51nnnmGdbX15mZmaGhoQGlUklkZCQtLS1cuHCBr33ta/zKr/xKWOdDONjZ2QkiUjqdDqvVSlpaGmVlZUGLl1ar5c6dO2E/d6QhkZqCX6Cl/6/pGv4G1QW/gHPRi6gWWfGvsL29TVZWFqq7xKozuxFV3Zu58LOvofjqH6J8AKQKDhdE309Ia0Goibr9ml9pHbBarcdqfvdCp9Nht9vv91t54JDagXu1Y4mJiVgslpwHeRwPo+YXsX9hdrvd52uxPkOES3gUCgURERGHit33T2E4HA65BH/YFMZeI9WzqjCdu0nHmhrwetHM9LMVvbuI9v7bLV7+ST8ZFz+Gxr5OwOEIWa3aC6fTGbK9qVariY+Pl7U3Pp9PJlpjY2P4/f4gonW/Wtr3GqMzOztLfHw8er2etLQ0kpOTmZqakitHGRkZByovgiCQmZlJbGwsnZ2dxMXFkZubK59Lkgt7d3c3vb29sjeSXq+nqqqKjo4OLly4gF6vJzk5mcXFRblVl56eLjvIazQaLBYLKysrxMXFER0dzdraGjExMSiVSnlqUMJe4fpefdX09LSs1VpZWUGn08k6sP7+fjIzM+Xf18rKCuPj40G6KGkqMDU19UD4rsfjobu7G6VSeaRDudvtZnh4mLW1NfLz84m7a+8hiiLDw8M4HA6WlpZ4+9vfDuyeT+973/t44xvfSG1tLe94xzv467/+aywWC3/6p39KamoqFRUVLCwsUFNTg0ql4otf/KL8XX3pS1+S7Rbe9KY38aY3vem4UykkRFEMIlIbGxvygp2RkUFUVNSR15CIiIhjQ7P3I8FaSlHGW7kz+X2ijCkIC5W4Yz04Z9cBdomVw8HAppaftq5T/eH/ROknfgB/8yX4zGdO9T5PCkEQQlZB7gX7p9T3kqe93QvpGi5FJJ1l9+JhEMYHAUnAvp9YqdXqjAd5HA+UWAmCIKSlpR14TZfLdT6mzM4Qfr//TNtle39soca99/bVpR/qwsJCkG+IUqk81M8rXN+Qc+ckf1fArp3owlaxq6V58bs/5l9++BN+7coHEIenUMXGot3nHr4f6+vrYZ2DKpVKnuiD3Yvk2toaNpuN8fFxfD6f7A5ttVrvy4bhsBgdKedNasFJEEVRnhrb+xxZWVmkpaUxPj7O1atXycrKIjU19cB5azQauXjxIiMjIzQ3N1NZWSmTa2n6b2hoiLa2Nqqrq1EqlbJerK2tjYaGBtRqNaWlpTQ3N2OxWNDpdGRnZzMyMkJxcTFpaWmMjY0RFxcn66wk/YcU1i1hb8XKbrfL5rFLS0vk5+cjiiJDQ0NUVVUBuy7qLpdLJl0bGxv09/dTX18vEzZJI1RYWHhAwL60tMSdO3coKCg41L/K6/UyOjrK0tISubm5lJSUBH0HgiCQlZXFxMQEJSUldHd3y//m9/uZm5tjenqaP/iDPyA1NZWkpKQg8vbZz36Wz372swdet6amRnZ3Pwn2phrY7XY2NzdlrU1WVhZRUScThUtyiJNm6+WmvoENxxz9498ja6EIZ6GbndndFm5mZiYTU9v8VEwhzarmje+4At99I3zhC/CpT8E9JhmEC+kcDHdDuf86vPfv0nV4L3GSqk3321dxL46LjHq1QqvVHiCMiYmJ+P3+8Fx6zwgPumJlsVgsB2r75669dAZwu90PVJB/mM5rLySnW+nHvrKyEtLpNlTVS7rIn7vsw7Q0iI1FN92NW/h5dIKasaFR4lOyUCt2UCysY3z88WMXifX19VNlZ6lUKmJjY2UR9948s8nJyaA8M+kCepYIFaPT19cXFKOzurpKREREyN+YSqUiLy+PjIwMRkdHuXr1Krm5uUECcNglUPn5+cTHx8sTdJmZmfKOvqCggKmpKW7evEldXR0ajYaYmBiys7Pl6BuNRkNxcTFdXV1cuHCBlJQUrl69itPpxGw243A48Hq9WK1Wpqam5PfndDqDiJXT6SQ2Nha/34/X60Wn07G0tITVakWpVMphwhEREXg8Hvr7++VgaKfTye3bt6mpqZE/j/X1dTo7O6moqAiyWvD5fPT39+NyuWhsbAz5e/b5fExMTDA7O0tWVtaRbumJiYkMDQ3h8/lQKpVnHi9zFPbmcNpsNtkKxmq1kpOTczCH8xSIiopifX39RHmIgiBQmfcBdlaciF6Bdesm8dpEPvjBD+LTJfLDLRexzmXeXZqKRqWAZ56BK1fgb/8W/v2/v6fjDRdStp7RaAw5IS79d6++ae81VKo26XS6h54EIkGlUuH3+x/2YZw5QlXiYmNj8fl8h+tA7gMeOLEKZT/woEnIg8B5JItqtRq1Wn3oCP/+bKaNjQ0WFhaCvEtcLhdut1tuFUgXj4flXYIgQE0Nus4unIIHqzKSoaEhiurfhErhQK0woN/n2BwKGxsbh0aUnARKpZKYmBjZnDEQCMhEa3p6Go/HQ1RUlEy0zmq6cn+Mzvz8vByj4/P5jo0c0Wg0FBUVkZWVxfDwsOziHrfPqd5sNtPU1MTAwAAtLS1UVFTIZFHKb7tx4wa1tbVERESQnJwsG4hWVVURFxfH4uIiU1NTZGRkkJeXx/DwMOXl5SQnJzM7O0tmZiYej4dAIBDSJVqqWK2vr8tEaHp6mtzcXLnlJtkT9PT0kJ+fj06nk+NoysvLZa3j8vIyd+7coa6uLqgSu7q6Sk9Pjxx2vf/cDgQCTE1NMTk5SVpaGpcvXz520RQEgfj4eLq6unA4HGceL7MXoiiyubkpEymHwyEHmufn5xMZGXnmryl5Pp2EWAGolBoKIt/NIh7mI+coK63gl2o/wf952U5cBLxx6F9Rrr8DEmLh8mVoaNi1XvjYx+CMh0n2ehrutdaZm5uTh1n2expaLJZXTXbtftyLSeh5hFarZWtrK+g2hUKB6gGPOj5oYmWMioo6sJ3br6F4FHAeidVxUCqVcmRMKIiiyEsvvURaWhoulwuHwyFXvfbqvA4zUr1vk4S1tWif/zFu9zqajd2KkTk+C5XCgbm8DsUxrYn7mX0oOYxL7tKBQID19XXsdjvd3d1yG9xqtcqtr3u90KlUKtLS0khLS2NtbY1bt27R29srC4+PitHR6XSUlZWxs7PD4OAgo6OjFBQUBDmUK5VKSkpKWFlZoaWlhdzcXHkyMD4+Ho1GQ2trK5WVlZjNZrKzs+nr62NgYICioiKKiorkoOaEhARGR0dxOBykpKTQ1tZGZmamHIBrMBhYWVkJOkZJYzU3N4fVasXj8bCzs0NUVBQzMzPExsai0+mYnZ1FoVCQlJQkG4Dm5eXJlcnp6WmmpqZoaGiQN3aBQIDBwUHZlmI/8d0rYE9MTKSpqenYSVHJPmN6elrepDz22GNnOvggBSzvtT+IjIwkJiaGwsJCjEbjfV9Ao6KiDvUdOw4BuxYEN6uWHRyDTv7PnB1LpIoPXjSy0e7ZnQyE3Y3Upz8NTz0F3/wm/Lt/d6LXkTaPodp0Pp8vKIVDr9cTGRmJWq1me3v7vhDgh4mjsjhfrVCpVHJA814oHvAY+4NmM5Fms/nAtu7cjO+fIV6NxOo4SG2fw0xPpXyovRctKTA7VD7UfmuJU5fJa2sRxAD6qT78GZbddmh8DhqcGOtee+zDw805OwsoFAosFgsWi4Xc3FwCgYC8IPb19cl6IqmiFRERcU8X862tLbKyssjNzT0Qo5OSknLoOWowGKiqqmJra4uBgQE5JmevDi02NpampiZ6e3tZXFykrKwMjUZDdHQ0dXV1tLW1UVRURFxcHMXFxbS3tzMxMUFmZibl5eV0dnZy8eJFCgoKGBwcpLq6Go1Gw+bmJlarFZvNRmJi4gHLhUAggFKpxG63k5aWxuzsLCkpKYiiKAvSnU4nIyMjNDU1ybmASUlJJCYmylWt9fX1oKDlzc1Nurq6SEpKorGx8YBObWFhgZGREWJiYmhsbDx2Qdrc3GRmZobl5WViY2MpLCzEZDJx48YNfD7fPS1oe88bm80mt0tjYmIoLi6+5/PmNDAajScWsEtwLnjQxqrxuM382Tv+A5kFlbz8o29j1CvZioh4hVgBvPnNUFy8G3Pzvvft2q7cxVH+TYcF+yYnJ8vGl6GwubnJ2traI0Wq4JW22f8lxEopCIIg3u+YF+k4HsSL7EGk2Wx+tEpTh8DlcgXt8h8FHHdOCoKAVqtFq9UeGZi9d6e4srJy5IVvLwE7tDJQUwNA9Pgdmn7zP2NbsvHHP1xFr7yBKgxB+sPMPlQoFPK0X05OTlDlob+/X648SBWtk1YeFhcX5TiX/TE6bW1tx8boREZGUldXx9raGnfu3EGtVlNQUCBXNdVqNVVVVczPz9Pc3ExRURHx8fFERETQ0NBAa2urLByvqqqipaUFnU5HYmIiMTExjIyMkJeXx8jICJubm7KnVXZ2Nl1dXWRlZQURK2koJBAI4PF40Ov1zM7OcuHCBSYnJ6UJIDo6OigpKUGtVtPX14fBYCAzM5NAIEBPTw+CIFBbWyvnpo2NjTE/P09FRcWBVvny8jJDQ0OYTKYDcT774fV6mZ2dZXZ2Vv5s98fLSNl6J2k9S5VOaWpPqnTGxMRQVlZ2Lgx77wbenljADuBc9EKSkkBPIRu2OdKSE1nb7MCor0MVE4PPZgvauPHxjxP9q7/K+hvewGpNDbbiYnaSk1Ht82+SjGbvZeP2KE/QuVyuU6U7nFccRqz0er0I6IH7mz4tHceDeJE9MJrN5kcnzfIInObict7h8XjuWQsXrs5LIltra2vMzc3JpXogpJFqhCmR6PEBjGoT6x1DKJSJRBjCO9WkaJDzAEEQMJvNcgtNEh3bbDYGBwdlEa1EtI7Syvj9fpmY7cVpYnSio6NpaGjAZrPR1dWF0WgkPz9fJhlJSUlYLBa6u7tZXFykuLgYrVZLQ0MDHR0dOJ1O8vLyqK2t5ebNm2i1WvLy8mhubiY+Pp6CggIGBgaora1lcHCQoqIiXC4XCoUiSGQrVRelKc6NjQ1ZFDw1NUVTUxOTk5MYjUZiY2MZGxvD7XZTVVWFz+ejo6OD6OhocnNzEQSBnZ0dOjs7iY6OpqmpKYgAra6uMjg4iFarpaqq6kgrlJWVFaanp9ne3iYlJYXa2tpDq4EJCQkyaTwMfr8/iEh5PB45NHqvru28wWQysbW1daJNpXfbj28rwJ3NAJvCHAG/j8z0RG4PfZ35iSXi7Hbw++l/+eVXpAaPP476/e/H9JOfYP63fyMLICEBHntsV4f12GO7gy1nUGWSWmaPGrRaLR6P52EfxpniMGIVGRkpAkYeUWIVaTabg9jGA6rMPXA87PzD+4EHET10nM5LEpdK5Gtra4vl5WWyrZkYF+b49Y/9KuqFNRI/+EUUigAzMzNBfl6hSIjL5Tqx4PZBQRAETCYTJpOJrKwseUzeZrMxPDzM1taWPN0VExMTNN0leTwdVeE6aYxOTEwMFy9eZGlpidbWViwWC3l5eWi1WnQ6HXV1dbL9Q1lZmRyB09vbS3d3N2VlZdTW1nLr1i1qa2upqKjg9u3bciDy+vo6sbGxLC0tyToryUcIXhGu22w2YmJiZO+q8fFx0tLScLvdTE9P09TUxPz8PEtLS9TX18seVenp6aSlpSGKIlNTU0xMTMjHKWFzc5OBgQEASkpKDiXdDoeD6elpFhcXsVgsZGdnH6lfk2AwGPB6vXi9XvkaIU2TSkTK6/USHR0t6+LOK5HaD71ef2h1Z/9wjOwWPu8ngiTWleBL3v3c46Kq0Sp3WHL+mCi1ibQn30fm3YBvGd/4BogiDA3B1avw8su7f775zd1/j4l5hWRdvgxlZUFtw3DxqLUAJRxGQl7NOOw93ZUwRALLD+Q4HsSLSIiIiIiOjIwMOrMlvcSjhv8nyL8/2BuYvXdX7HIs40hJR6lV8c2Xf8p//IBIAB9ut1vWeUktpf3j0BsbG/j9ftnt+zxDEATZHT4zMxNRFGWz2NHR0SA/otXVVTIyMsJ63pPE6AiCQEJCAvHx8czNzXHz5k3i4+PJyclBrVaTnp5OTEwMXV1dWCwW8vPzKSsrY2RkhNbWVmpqaqiqqqK9vZ36+npSUlLkTL++vj5KSkoYGBggMTERu90elBkoGblKmq7R0VHy8vIYGBigqamJlpYWysvLWV9fZ3R0lIaGBnZ2dmhvb5f1Xm63m66uLnQ6HU1NTfLv1OFwMDg4iNvtpqCgIKT9hjRxOTMzgyAIpKWlkZeXd+LzJiYmhtHRUWDXi8vv98tEKiMj46H/zk4Dr9eLKIosLy8f0Foepm9KSkpCk6ljuNVGpBei/XUolUo2l1cp6kzgTs4mIzUOYlP1hGx2CgIUFOz++djHdonWxMQrJOvll+Gf/3n3vmYzXLr0CtGqrIQwr9FS5fS8Xx9OApVK9ci1OA+zkTCZTAK7FasHcxwP6oUADAaDdX9b4lEkIIDsVfMo4TwQq5AQRTRrM3iLLpOSl8GWcwfHxgoOq4vs7OwDO85QBn7j4+O4XC55ATjMSPW8nauCIMgVPskoU3LQlvyKJKJltVoxm83HDoocFqMTHx9PWlqaXE0UBIGUlBSSkpLkKlVKSorscN7Y2Mjo6CjXr1+noqKCvLw8mbDV1dVRXFwse1y1tbURHx8vG/y53W5MJhODg4MYjUbZcmFnZwez2YzL5ZJH+8fGxsjKymJ8fJy4uDiUSqXslbW9vU1XVxdVVVXy1JrUapT82JxOJ8PDw2xublJQUHBgOEMURdkjbGNjg8TERCorK0+ka9rr2C+19iRvsKysrHNvNyPpm0JN1O0dTBEEQSaJsbGxYRsQq00KsvR+hh1xvPcXf52KrTXU27E0Fvwyt1a+yc2+L9JY+h+wmI7RpQkCZGXt/vmFX9i9bXo6uKL1gx/s3h4ZCRcvvkK0amrgEPmGpEc6V+bI9wgp1eBRgqS/3I+7Q3Oh8+TuAx7oKqHRaKL3t3geZWL1qL0vt9t9Pi8si4sovG5EQyYJ2bvu2ra5ETxpKnZcdiL0wZluarWaqKgoecJteno6yJVc0ibt9bHZHzkhjWSHMlJ9mK0DQRCIiIhAq9UyNTXF5cuXZaI1NTVFT0+PbN5ptVqJjo4+lGjtj9FZXFwMGaOjUCjIyMggNTWViYkJrl27RkZGBunp6eTm5hIXFydP22VnZ6PVarl58yY1NTVkZGTQ0dFBeXk5bW1tVFRU0NvbS0pKivy5x8bGBhGryMhI2VpBsnIoKytjenqa6upqOadwY2ODwcFBLly4gFqt5vbt2/j9fi5evCi7hI+MjGCz2cjLy6OsrCzou3M6nczMzMiGo2lpaVRUVIT1/Xq9XtnVXMpkk6KPpFzFlpaW+xqafBLsj8zae/4fFpmVmJh4IDJrc3OTkZGRsCulEvSJGjy2HchcJPOxXyXd9hIx73k96thYmhL/E9e7/yc3ev+KxtJfwWLKPNmbS0vbtWWQrBnm5+HatVeI1qc/vXu7wbDrkfXYY7t/6urg7kZScio/l9e/U+JRbAUehqioKBWPasVKoVCY/2+pWMGj15v3+/3n87uamADAZ0rDGr8bOWKfH8EXyGN9e/oAsdqLUBo/Kdz2qMBsyURQ0nktLS2FDEkN5ef1IM6LjY0NmThKRpRSpIvT6cRutzMzM0Nvby9qtTqIaIWqLiiVSpKTk0lOTpYJx/4YHaVSSU5ODunp6YyNjXH16lWys7NJSUnh4sWLDA0NcePGDSorK6msrKStrY3y8nIsFgvDw8Ny5IvJZEKtVjM+Po7JZEIUxaBWoMPhICoqivn5eRYWFsjOzqa3t5fy8nLa29spLS1ldXWVubk5Ghsb2dzcpK+vj5ycHJKTk/H5fAwNDcmPLSoqCgphXlxcZHp6Gr/fT2pq6pHZgBI8Ho9MolZXVxEEAYvFQkxMDHl5eSEf7/f7zzSD7ijsDXnfb0MQKuQ9IiJC9lU7ifnvaSfo9IlqNoYElGkT6CcEvuGKJUdrwgrotWaayv8T17u/wI3e/5+9946PKyHP/b9nelMZzaj3Xi3JliXbctlCCYFd2sJSsiQQUoH0exMuN4Hcm0sSEtK4/AK5IVxCIJCFsCwElrLFa8tNki3J6r3X0YykGWmKppzfH+NzdkYaVcuy7Nzn89HHu9LMmdPmnOe87/M+z//eH7mKREYGvOc94R8Amy2aaH3qU+GWolYLp07BI4+QkJtLMCEB9pHOcFTxn4lY3RmaezgrVoIgJMQiVg9by+xhxZElwSMjAKybczGp4igrK0MZWicY1LO8OkFm8okt37qf6c1InVcsxIq9kKovkbEXGycbpX8P4ka7nYWEXq+XswYh3OKV3KW7urpQq9Vy69BsNm865nq9npKSEoqLi7eM0SkrKyM/P1+OySkpKaG8vByHw0FzczMFBQWy11Vpaam8nwKBACkpKYyMjMj72Ov1ytNLUjZjfHw8qampzM3NAZCZmUlPTw8FBQXYbDZcLhf19fVyi+/UqVNoNBpGRkaYmJggLy9Pjp8RRVFuee42Xsbn80URKckINiUlhbKysl19T+Li4lhdXT2QidRAILClf1NksK90jiUkJJCeni7bmBwU2d/vBJ3CO4lAIonLBkLO63z+9z9GavINPv6BelRKAb3WHEWuzh77TczxeQeyziQnwzvfGf4BWFqCpqbXiNanP01eKISoUoWzSaWKVmMjHJFp4v3gYY21gc2O8neG5h5OYiWKYtx/llbgw4gjS4LvVKzWE7MILi3T29vL331rBNE/xtLK7W3fei90Y1KrcKvlRgZmSzdAp9MZM6g1lpHqbr4ve4no0el0cjUKXiMNs7Oz9PT0oFQq5epLUlKS/PlbxehIou709HQqKytlDZPk4n7u3Dm6urqYm5ujrq6O27dvk5GRgc1mw2KxMDIyIlfA3G63HG8jXSyl9pTJZCItLY3FxUXW19dJSUlhYWEBtVpNSUkJ165dIzs7m/LyciYnJxkdHSUrK4vz58+jUqnw+Xyy55Qk0t/KXVsin4uLiywtLaFSqbBYLKSlpVFeXr6va5iUrbcTsYp1vkT+Gytg3WKxkJ2dvevz5aCwH4LmamrCe70J+ACJiyaK6msB6O7p40dtJTxxMhEAvdbM2erfoun233Kl839ztvo3MMflHdi6yzCb4cknwz8ATicz3/42pps3iW9rg89+NmxOqlDAiROvEa1z58LvfUDwsFasJJ1V5L0qPj5eqdPpdjY1PCAcKqMJhUJx/xlagQ+zhcSRPFajo4jp6QSMGgRHuNpj0KtZdRpYcY1vm4d1PwT5uwnMDgQCUTdPqXW3VQUi8l8pgmOrVuZO0Gq1ZGRkyPofqc21sLBAX19fVJsrKSkJtVodFaMj2RAMDg6SlJRETk4O1dXVrK2t0d/fz+DgIGVlZayvr9Pa2kpJSQkzMzMYjUZmZ2dJT0+XJzklSJUltVqNUqmUCZbk0g5gs9mwWq2EQiE6Ozs5fvw4TqeTy5cvk5qayrlz51AqlXK8jM/nIysrizNnzmyqWkr73G63s7S0JLdLMzMzqaqqOpAHjPj4eGw2W1SFcyNp2qrCmZCQIAemH7XUit1O0ImiiPMnP2H1yhWMlVUsjgaxLMZTdjLcsjYFJmgeXCPHqqE6L1wdNuiSOFf92zTd/huu3L6H5CoS8fGsP/449sceIz4/H9bW4Nq11wTxn/88/NVfhYXz1dWvEa3z58PVsCOKh5VYSdsVef7FxcVhNBq31oQc9Doc1gcBhEIh/cb2ycM2wgpHWIt0lzjKxErIzydkDqFZUvNv33qWP/4vf8iv/+FX8Iu+mAJ2CUd10lGlUu2o84q8Aa+srDA3NyfrvFwuFy0tLTGrXnsNzNZoNLIVA7wmzF5cXKS/vx9AJlpSDE95eTllZWWbYnQqKyvx+XxyoO2xY8cYGRmRL4ZarZa5uTn0ej0mk4lgMEggEJCrVhD+fklTaNLE4Pr6OhkZGczNzckC8fb2dtnY1Ofz0d/fj81mi4qXkSC1axcXF1lZWUGj0WCxWMjKyrprIiUdq43VJqfTKedtSpo86ThZLJZD1eQdJHYzQScGgyx/73u429ow1teT8Ja3MPCVURJtYfPb5ORkcI2TY9XwvZZl0s1qkhPCOrUwufqdCHL1m5jjcu/pNqlUqteIvtEIr399+AfA64UbN14jWv/4j/C5z4X/VlHxGtG6cAHufIeOAh7GqUAIb9fGFuedB85D69seditQsfEC9TDmBB7Zltld4igTK86fR2URiBvXM2cJMDMxyOz8PFWlbCtgf1AnfRQKBUajMea6i6LIq6++Sk1NjXwTl7yuIqe8pCrIRpH9ToHZarWatLQ00tLSgDDRcjgc2O12BgcHCYVC8gSc1WrdMkZHrVbT39+PVqslPj6eqakpzGYzPp+P1dVVAFncLZmE+nw+gsGgXGFyOp0Eg0GSk5OZmpoiNzeX6elpvF4vNTU1sqZL+kxJqO52uxkfH8dut8vu7Varldzc3F1ZUkRCqi7GEodHVhelfRwXF0dqaioqlYqOjg7Onj276896ELDTBJ3o9+P41rfw9vUR9+ijxD32GIIg4EnxkjSeQMgvUlZWRn9/P391Nokv/GiBbzY5+JU3JqNV36lIS5Wrjr/laufnOHvst0iMy7ln27RtdUene408/dEfwfo6tLa+RrT+5V/gC18Iv7a4+LXXPvIIZGffs3XeCVIV+GFDrO1SKpUoFIpDuynv+i4pCIISaAWmRVF8QhCEJODfgDxgDHhaFMWlHRazKWT6YTywDyNZhCNaXfT7YXIS8vPRWdUI3UpS88Oi7NmZcQjC0vLIlgL2h7G6KAnypZt5LKPLSN2ORARmZ2ejfIk26nYi/zvyPFCr1aSmpsq+UJJnk91uZ2RkRPY1slqtNDQ0yO7oUusuLi6OyclJ4uLicLlcsv5JqlAFAgEEQSAQCMjHy+fzyesg3cg1Gg02m43s7GxsNhvt7e1kZmZy8uRJgsEgdrudtrY2nE4ner0eq9VKfn4+CQkJ235fI/fTVvqmSOIkVZt28j2TjsHDhu1E0SGvF/vXv876xAQJb3kLplOn5L+tJnuwiIl45/186lOfQqVSEW9Q8q5GM1+9aOf7Lcs8dcYsV/AMOgtna8JWDFc6P8fZY795z8jVntpmGk1Y2N7YCB//OAQC0Nb2GtH69rfhS18KvzYvL5po5ecfSAzPf3Zs5BV3Hs52vHkJgvBl4AlgQRTFqg1/+y/AXwLJoiguxnq/hL3cUX4L6AWkctrHgZdEUfxzQRA+fuf//2C7BYiiKMS6gD1ope6dsJ2m50HHkduuiQkIhSA/n7hkHT7cJMalolSpWJgeRruqY8k+BMWx3x4KhY7eNt0ldtPe3K3OK5JI2Gy2mE7asUKzpcBnCJNXiWiNjo7KcS1S6PTs7KwsNvX7/QiCgCiKhEIhQqGQfJOOPFaCIET9SK2n5eVllpaWSE9Pl7VhUqyR1WqlsLCQhIQEeTmxJjilfyP1TZHbmJqaKlf27uZB42E77yRIx28jgqur2L/6VfwLC5ifegpDdXXU353WNQDcM+u87nWvk39fmKbj8WPxvHTbSW6ylvri1yphRp2FczW/c8/J1VbGk7uCNE1YXw+/93sQDEJn52tE6wc/gH/+5/BrMzOjiVZJyf8jWntErO/VHd6xm2rHV4DPA1/dsMxs4A3AxG7WYVfEShCELOAtwKeB373z67cBj975738GLrIDsQovKnqjH8bqzsNYhTuyuDMRSH4+CckGFnHjWw6RnVvA4uwQqtUGVuJntyS7DyMJPoiwbAg/pUs5hbGwMfttZWWF2dnZTd5IEtmSWmBarVbWNEku5HFxcQQCAURRlOOFIv9bgiiKcpVIoVCgUCjw+/0olUpEUcRoNLK0tITf75e1Vmq1Wl7P+fl5xsbGZF0WbPYcS0pK2jZb8iAhkZCH6RyMzHaUEFhaYvGf/5mQy4Xl534OXfHmJ51Vk5eALohn1s/q6ioXL16ktrY2PMlZYWLC5uOHt5bJSFKTaXlt2MCos9wRtP9tmFxV/xaJpoNtsW1FFvcFpRJqa8M/v/mb4QfD3t4wybp0CV5+Gf71X8OvTU19Le/wkUfCmq2H7H550Ih1rHZbsRJF8ZIgCHkx/vQ3wO8Dz+9mHXZbsfrbOwuNVNKmiqI4e2dlZgVB2E2K7aarx8NKQh6mC+WRhkSsCgowWMLiVr89xBve9FZ6p9fRCGmsCbYtBewPI7E/LNPJnQKzJTdvqYUmCbU9Hk+Um7dkZBoIBFAoFHi9XpRKpRwxFGu5EumSBLhqtZpQKIRGo0GpVOLxeJiYmGByclImd3q9nri4OFJSUjAYDGg0mvv+PY01Gv6gY6PGxT8/z+JXv4oYCGD94AfRbKErWieAL2Udz4wf35ydJ598ki9/+ct86EMfQiEIPHXGzBd+ZOPfrjj4tZ9JwaB97Rw36q0R04Kf42z1bx4oubqn54lCAZWV4Z+PfCRsTjo4+BrRevVV+Na3wq+1WF7LO3zkkfAU4kN07hwUYhErYF87ShCEtxKWQHXs9jzYkVgJgiD1G28KgvDoflYscnFbfMZdLvZo4WF7Aj3SGB0NX1gyM1EoFayb/OCAT3zyf/HllxbRmDqBTpZWRrYkVg/bsToq2xQp2o4MzJYg5c9Ftt+katba2hoqlUoO9o0FlUolk7tYWrCd3NKPAhwOx9HULt4FnE6nTOwDDge2f/onBI2G5A9/GHVK7Odvd8iHO+TFn+LH2+anLCsXjUYjT48CGLRK3nMuiX960ca/X3Pw/gsWlIrXzvMwufodmVy9/uQn0WoOxhPS7/djs9kOZFk7QhDCLcCSEvjlXw4TrbGxaKL13e+GX5uQAO94B3zxi2Gn+D1iZWXlQFf9KMBut5ObGz0larPZsNvt9XtdliAIBuC/A2/cy/t2U7E6C7xVEIQ3AzogXhCErwHzgiCk36lWpQMLu/nAa9euyU+rEJ7KEgSBkTvu2Q8DgsEgPp+Pixcv3u9VOVC4XK4jt03pXi+lwSDtn/scy8ePgykF1aKKga4bEMqj164nWSdwu/enDPW5N73f4/GwsLDwUAnY/X6/HM1y1BGppdr4I1WmYkFqQ0r6KKktGPlzFMjlbtDU1PRQVU3dbrccKaR2u8lZX8en0TDQ1YUYYzuXdD560pZZV4XwBlYQg/Fcf+UGKSkpNDc3b7rmFJni6Z9N5Uvf76Ek3hZDglSAX3GTpqsvoSTxQLYpEAjg9Xrv7/UvLy/88/M/j9ZmI6G9HfOtW6R/5SvMT03R+4lP7EuPddSu6XcLr9dLe3t71DW9q6sL1f4u8oVAPiBVq7KAW4IgNIiiuOUFdscPEkXxvwH/DeBOxeq/iKL4jCAIfwn8AvDnd/7dTe9RPHPmTNQvRkZGUCqVmxjmg4y1tTV6enqor98zQT7SuHjxIo8++uj9Xo1onD4Nzz5L7XPPwW//Ntddw2huackrzOPtT1bys8/8Eb9zQY8jZ57G0w1o1NE+ap2dnWRkZMSsqDyomJ+fx+FwUF5efl/XY2MrMLIyFalv0uv1CIIgT99JD1t+v1/WXW2EQqFAqVSi0WgQRVGujEmtQa/XK08TRmbgRVa2jkIr8PLlyzQ2Nj5UFav+/n7i4+Nl3zNPTg6OZ5/l2PIy5ne847VcRjHEq65u2l3dmJVGPpjUSNwxI6Ptduoq6ykqKsLv98e85vykfYWmXigvzuFCRXRV6lb/JLN2I4+feSuCcDCEdXl5mbGxMWpraw9keQeCd787/O+nP03qH/4hqQ0N8OlP72kRR/Kafpe4efMmxcXFUdpQhULBl770pWt7XZYoip2AXGYVBGEMOHmQU4Eb8efAs4IgfJiwUv7du1nPjb+43xe2e4WHVTt25KDThdPpP/YxeOUVNKn5KIMKtCoDSqWC8ZFufFXnCGW3MW1rJT/jQtTbYwltH3Tc1QTTHiBVjWJN1Emj6Rv9m1JSUtBqtaytreFwOGRDzri4OPlYaLVavF4vgiDILt4bt0+hUMhPpJK+ShAE1tfXWVtbw2g0kpGRITvDSwTP5XKxsLAQk9zF8vO619enw9LDHSY2Ttrqq6qIs9lwvfIK6uRk4s6fZyWwxreXrjG+bqNGn8cTiSfRKtR4TOFj4l8NkZmZyZUrV2J+xutr4llxB3mxw0mCQUnNHWd2URSxLfeTnFhyYKRKWu6RxSc+AePj8Kd/Crm58Cu/cr/X6L5j4/f2zvVwx2BEQRC+QXgozyoIwhTwKVEU/2mvn78nYiWK4kXC03+IomgHXrfd62MvIlr/caDTFkcEDytZPLL48Ifhz/4M/viPMf3LN/AAznkfdXUnGB5tZ0z3K+Qb55mYvx6TWD1s559Go4lqt+8Xfr9/S+IUabcgERKz2UxGRoYcqyNhK7uFpKQksrKymJubY21tTX7ClLRTkZCOkUS2pOMmObBLf1tbW8NsNpOcnMz6+jpDQ0O4XC7ZbiE1NTWm3ULk9klxOpLTtkqlipnZKFXI7gZHRQ93kIg1EBL36KMEFhdxvvgiw2kqXjDOECTEO82nqTXky69TmcL7M7Aa5I/+6I+29PlSCALvOGXG5Qny3RtLxOmUFKRpcXvteHwOirPfcODbdGSPkyDA3/992M/vIx+BrCx485vv91rdN8Q6VnekBTsSK1EU37fD3/N2sw6HKiwRBEGMNQHzsN3YHsabtYQjeYGJqFol995kTHEcz1yQ+pMnuXrlc4xq02gwn2N46lmca7PEG1+LlXgY3YelSJHtIAnHY7mFSwahKpUqikgkJyfL/70doQgEAiwsLLC4uCiLsyWD0Pz8fNkgdGhoSCY7ExMTsvmnlAUoCAIqlUr+b6kKJ920pddJ2+zxeDCZTJjNZubm5nC5XGRlZVFZWSkbhA4PD8sGoZIzfEJCAjqdDvMWAbobA5Dn5+dl4iURzFiZjTsJ6B+2805CrGuEIAiY3vYkL2a46TKMkS7G8XTqI1hU0W08lUEBAgRWQ5Q2lG77OSqlwPvOW/inF218o8nOL70+GY8nHLGUnLj9e/eKI19ZVKng2WfDk4JPPx0WuNfV3e+1ui+I9b26c+04tNbEYSt2QxuJ1cNIQh7G9hK8lsF0JIXed6pWCZ/+C5zv/BLGBR11dXX4/evMTw9hX6tDEL7NxPw1qgreKb/tYczL0mg0UaRp47+RVgeRra/ExMRdRdpshBRpIxEpKdLGarVSVFQkr8/09DQ3btxAq9WSk5NDWloa/f39cs7f5OQkSUlJuFwuIHxsQqEQarVa1lxJrt5S8HMoFGJ9fZ3ExERWV1dJT09ncnISo9HIiRMncDgctLa2otFoyM7O5vjx4ygUCtxuN4uLi4yOjsqRNhLR2hhpo1arSUhIkG0hNiIYDEbt36WlJaanp6MibSL9vCLd6x+EycW9Ilak14J/hWeXrrCQp6Gm18XpzhkSf+mRaAMfQFAKqAwK/KtBZmZmeP7553nb294mB4JvhF6j4JlHLPzjT238y6t2TuWNodMkYNKnHvg2HcnrXiTi4sJmo6dPwxNPhIOi8/Lu91rdF+y3YnVQOOyKVUi6KEb87qEjIdtFOjzIkGIdjuQFRqeDT3wCxUc/iu7cqwj+n+Xs+87ye089RYI6yO2JIPW5VUzON1OR/zYUQnQcyoOGyBDmjeRJCmHu6OiQb+RGoxGr1bqvEOaNiAxhdjgcAFgsFiwWCyUlJfL3WxRFbDYbExMTcgjzqVOn8Hq99PX1IQgCpaWljIyM4HK5SEpKYn19Hb/fj8lkioqxWV9fR6FQRBmfKpVKdDodPp8Pu91OVlYW09PTWCwWEhMT5RBmKUZncnKS/v5+rFYrOTk58g+Ep0MXFxeZmJjg9u3bcgizRLS2q9AplcodA7MjRfwul4v5+XlcLpdshLnRpFT67wcxhNnn88nHSRRFbrqHeWHlFhpBxQcsj5BbKbB47UvYv/ENkj/0IYQN5FJlUhBYDTE1Ps5HPvIRcnNztyRWAIlGFc88YuHLLy5yZbCKR8oOPk3hyF73NiI9HV54Ac6eDbcDr1yBLSqxD2PqBMTermAwSCgUejiJlUKh8Ljd7qi4DckI8GHCw1gFgT3mZd0PfPjD8Kd/StH3v8jUO95CuiWD//aud3HbGeAVZwCd7jw+x20WHD2kWY4B4RaS3W6/zyu+GRvjZKT/9ng8UcG+0g04ISGB9PR0Wd906dIl6uvrD2TaTIqGkYiUQqHAYrGQnJxMaWnppqrL6uoqk5OTzM3NkZSURGFhIYmJiaytrdHZ2cn6+jrl5eX4fD46OzspLS1lenoag8GA0+kkPT2d5eVl1tbW5GVG2idILUC/38/y8rKczWez2UhNTSUUCjE0NERtbS0ul4tr166RmppKSUkJ5eXlLCws0N/fj9frJSsri6ysLPR6PdnZ2WTfMa/0eDzY7Xampqbo7OxErVbLRMtsNu9pv0qtQoMheiJ1YWEBm81GRUXFplgdu92Ox+PZMlYnknwdtRaVFKnkCa3zvaVmur2TFGrTeKf5NHFKPaSD+amncHzzmyw9/zzmp56KuhGqTEoCriCZmZkATE9P7/iZ6WYNT56Eb1830z55hvpyEZXy4EjDA0OsIOzO/t3vwhvfCG9/O/zkJzE9ro5s9+EuEcsXzu124/f7nYe1DodNrFzSk6m8Akf9Zr0PPIxPAfAAHCutFj7xCSwf/SjLtU1459+By+nEM9qF5sRJxu3paNQmxuevRRGrwyb2sQKQI4lTrADk5ORkWTC9m4uhyWTC5XJtmQO4HaQK0OLiIktLSyiVSiwWC6mpqZSXl8f8/EAgwPT0NFNTUygUCrKzsykpKZFd0Ds6OnC5XJSVlWE2m+nq6mJ9fZ2TJ09y+/ZtMjIyWFhYICMjg4mJCSwWC3FxcXi9XtbX1wmFQrI/l5QnKFWJ7HY7Go0Gq9WKy+VCrVZz7Ngx2trayM7O5vz580xNTdHU1ERWVhb5+fmkpaXh8/mYmpri2rVrGAwGcnJySElJkUmrRLogTBbsdjszMzN0d3fL+8RisZCUlLSvG5TT6ZSnIXU63Zb5jtL5Ekmy5+fnYwZBx9J6HfbNMxQKMRVw8O2lq7iCHt4YX0ujqQxF5KRgRQXxr3sdzpdeCk8KPvKI/Dd1nILVxQB56ekIgrArYgVg0gyQm9jL+PJbeb55iXeeNh/YtTgQCBxITNSh4ZFH4Ctfgfe/Hz74Qfj61zdF4TxQZHEPiLVdLpeLtbW1bS0SDhKH3Qp0ra6uRq/AUb9Z/z/IeCBanB/+MN4/+R+kXfpr3HNv4bPPPcc/vvgi//Lyb9A14eUtNaeZmH8Fn38Vrdp0T4iV5N8US+MUWYGIrDqkp6fLxOkgKhAJCQmsrKzsilhJpEEiUlJ1Jj09ncrKyi2rM6IoYrfbmZiYkCtNJ06cQK/XA2GC1tvbi91up6SkhJqaGhwOB01NTRQUFGCxWGhpaaG0tJSFhQUSEhKw2+0UFBQwNjaGwWDAZDKh1WrlFqHkWRUfH49KpWJubg6z2YzBYGBhYYHs7GxcLhcDAwOcOXOGwcFBbty4wfHjx8nKymJsbIzLly+Tl5dHbm4uhYWFFBQUsLKywsTEBD09PaSmppKTkxMV1aPT6cjMzJSrKBL5nJ+fp7e3V67iSRWt3WinVlZWKI6RmbcRkYHZW+m8AoFA1HkmVbwidV5bES9Jw3YQCIaCjJpdXFx8iQSlkV9KfgNZmtgecaYLF/DbbDhfeglVcjL6igrgTsVqNVxNSUlJ2TWxsi33k500Q2F2HC93ukgwqnh9deycyz1v14NY3Xnf+8Ih9R//eNiG4c//POrPDyuxijVo4HQ6g16v99Bs5g91r4qiuCIJU+UVeBBu1v8PwANCgrVapv7rr1L0e3+C68c/pTori/VAAOP6KOuBbDzBU4jii0wttFCY+ZgsrN4LJH3TRuJ0p9wMEGVKKU2gHaZmJjExkampqZjGu5KeyG63s7y8LOuJMjMzqaqq2rHNJeXwzc7OkpCQQG5uLklJSfJ2+f1+hoeHmZubo7CwkMrKSkKhED09PSwvL9PQ0IDf76e5uZna2lpsNhuiKGIwGPB4PCwvL1NQUMDIyAgKhYKEhARUKhVOpxOVSoXZbEalUjEzM4PZbCYxMZGRkRGqq6vp7OykoqICvV5Pc3MzDQ0NOJ1Obty4IZOonJwcRkZGuHTpEoWFhWRlZZGYmEhiYqLsWN/Z2UkwGCQ7O5uMjIxNREmr1ZKRkSFrf6R26cLCghzDIlW0LBZLTKLlcrm2zFncK1Qq1Y46r8jzdWVlhbm5uS3P2UjitVtNnjPo5lv2q4xbVzmmz+XJxHp0iq0JpiAImN/2NgIOB0v//u8ozWY06emoTUrEIIS8IpmZmbsiVqIYYnFlkHRLDcdL4lhxB7nU7SLRoORkkXHH9++EB5aE/P7vhz2uPvOZMLn69V+X/xRryOBhwcbzdXl5eR1wxX71weNQz5RQKLQci1gd+Zv1PnEkrQnuAg+Kdsz7oWfw/q//Q/y//Bk1z4T9XKaHb2PJyKN3WklhUg4Tc9cozHws5vHZ+PQf+W/k079044mPjyc1NfXAn/7vBgkJCXR3dwPIE3ASkZIm4HJycqiurt5VhSwYDDI7O8vk5CShUIjs7GzOnTsXdbMJBoOMjo4yOTlJXl4eFy5cQKFQsLKyQnt7O1lZWTQ2NmKz2eRkgqWlJRwOB8eOHaOlpYXjx49z+/ZtTCYTWVlZTExMkJiYKFfBJCH+wsICGo2G9PR0urq6qKmpoauri7q6Opqbm6mrq0On03H16lUaGho4e/YsXV1dzM3NUVNTQ2lpKfn5+QwODnLp0iWKi4tJT09HqVTKlSmPx8Pk5CRXrlwhPj6enJwcLBZLzOMrrYvkNh45KTk4OIgoiiQlJclESxAElErloemjFAoFRqMRozE2ydhYZZXOmcgp0o1V1kg/rwHfLM8tXScgBjm+nMrbM87s6nsgqNVY3vc+bP/n/+D4+tdJ/tVflb2s/KtBnnvuuSgH7a2wsjqFP+AmObEUQRB44mQiTk+Q77cuE6dXUpoZu826WzywJEQQ4HOfC3tcfexjYY+rJ58EHmCyuA8sLy/7eViJ1fr6+tJ/llagtF0P0zj1gzJBF28w0/3Uz1P3pb+kaP4kCUYjN2/e5OfOvY8XO5zUZDcyNf9NhsbaEILxeL1ebty4Ifs3bdSrSNWm+6FX2StEUZRviqurq7z88ssYDAYsFgt5eXkkJCTs+mYuiiLLy8tMTEzgcDhIS0vj2LFjm6osoVCIiYkJRkdHyc7O5sKFCyiVSkRRZHBwkNnZWY4fP058fDwTExOMj49z5swZnE4nY2NjnD59mpaWFo4dO8bQ0BClpaX09fVRXV2NzWbD4/GQmhoen5dsClZWVigtLWV+fp6UlBScTicpKSlMTU1x8uRJWltbOX36NDU1NXIr8Pjx48zOznLlyhUqKipITU2lsrISj8fDwMAAw8PDlJaWknInKFiv11NSUkJxcTEOh4OJiQm6urpIT08nOzt7kxg9Emq1mtTUVHm9A4GATLSGh4fx+XwoFApmZmawWCz3Xb8T+bAQqYGVEEsXODs7i8fjYdW7xqsFc2iCSk7NpaDzKRgfH48iXtt9b5RxcVh+7uewfelL2P/1X9E/9gwQ9rLKyc/Z1frblsP+VdbEkvAyFQJPNybxf19e5NkrDn7xdVYyLZq97hYZkZOODxxUKvjmN8O6q/e+Fy5ehPr6/1TEamVlJQCs7vjCA8Kh7lW3223/z1KxivTbeVhwVCfoIiGKIrqAio53PcaxZ7+G8Uc/pTInh1deeYV3Pt0OFNA7HEecSWB2sYOc5McwGAwUFRVhNpuP3ITVThBFkdXVVex2O3a7HafTKROp5ORk8vLySE5O3tMyvV4vU1NTTE9PYzQa5crWxgqEKIpMT08zNDREWloa586dk8/3tbU12tvbSUpK4ty5cwiCwMDAAEtLS5w5c4a1tTW6u7s5c+YMExMTJCQkoFar8fl86HQ6tFotTqcTi8XC8vKyTGIMBoM8dZaQkEB/fz+NjY1cvXqVc+fOcf36dVJTU6murqa5uZnGxkbq6+tpbW2loqKC9PR0kpKSaG9vZ3Z2lqqqKvR6PTU1NaytrdHX18fQ0BBlZWUywRAEQa40BQIBZmZmaGtrQxAEcnJy5ErXdpD0QhJp6+7ulqt5IyMjBAIB2UTVYrFsKWS/X4jUecXS7S0vXafDPYbJkoBhVZCtNraaZN043ahOS5MnBcUbrwDH8a8GaW1t5Tvf+Q6f/OQnt90ni8sDmPSp6LWvrZtWreDnLoQ9rr72qp1ffmMySab93fKkc+6BhdEI//EfcOaM7HEV1GgeOmK1lZHr8vJykIe1YrW2trbkcrlCgLzlsbLAHgY8jITxfkzQbUSkJ9BGKwJJK6XRaljO8GOv+3nSX/kMn3jf+0j6pV/i9GPn6PjuHHGWPBI1OYiCndzcXJaXl+X8uaMOURRxuVyy2Hx1dRWj0YjFYqGoqIj4+HiZAM3PzzM3N7crYhUKhZifn2diYoL19XWysrI4c+YMGs3mp3xRFJmfn6e/vx+LxcKZM2eifIuk6lV1dTVJSUmEQiFu376NKIrU19fj9Xq5desW9fX1rK+vMzU1xblz52htbaWsrIyJiQlycnKYm5sjNzeXmZmZqFagzWbDYrHgcDiwWq0sLS2RmZnJxMQEx48f5+bNm5w7d47i4mJaWlo4ffo0Z86cobm5Ga/XS05ODg0NDUxOTtLU1CSvp9FopK6uDqfTSW9vLwDl5eVRrSiVSiX7X62trTExMcHg4CBJSUlkZ2djNu9uEm1xcZHGxkaZiAaDQZaWlrDb7YyNjcmxPxKhk7b/qOJnE04w4pvnqnaMd+vryM3cXGkKBoNRfl4rKyty1UvSeSWXlGDsHwWOY59a4trQNf7sz/6MD3/4wxQWFsb87FAoyOLKEDmppzb9LU6v5AOPWvjST238y0U7v/wGKwbt3lt6sRJDHjikpYU9rhob4c1vJvSNb6DawuPqQcVWLVun0ynysFasANcdEZlM/Y+CHuVeQKVSbZlz9aBCMmO8l9joYh35byAQ2ORiHRcXR2pqKnq9Ho1GI59P044rLFTXk/4KnPH7EVZWEAQBa7wKmzNASVEZg1M/xR/wynEoW0Wa3E+IoojT6ZSJ1NraGiaTCavVSmlpqTyuHwtWq5Xe3t5ttX5Op5OJiQlsNhvJycmbiMRGLC4u0tfXh8lkoqGhIeqG7/V66ejoQKfTyfqrQCDAzZs3SUxMpKSkBL/fT0tLCzU1NRgMBq5cuUJtbS0rK+GBncTERDo6OqioqKCvr4+ampqo7DmDwYDb7aawsJDx8XEKCgro7+/nxIkTXL58WSY9PT09HDt2DI/HQ1tbGydOnODMmTPcvHkTj8dDSUkJOTk5WK1W2traMJvNlJWVoVAoiI+P59SpUzgcDrq6utBqtZSVlW3SJxmNRsrLyykrK8NmszE6Osrt27fJzMwkOzt7ywqH2+1GrVZHVbOVSiVWq1U+rqFQiKWlJdm0dH19nYSEBLmitV0b8n5Ar9DwjsRT/LP9FW4pp8hlM7FSKpXb6ryC/hCzF5ewD7gRRC9BVuTz4tKlS0xOTqLRaDZpvNZDCwRDPqxbxNgkx6t5/wUL//zyIl+/5OCDj1lRq3Z/33mokkHKyuD55+ENbyD5V34F+ze+cb/X6ECxVXvzznn0cFasgNU7IrIHuKa6O+xn2uyo4yDCfTfmrkX+Gyt3zWw2k5mZuWPu2kaU6jLpOxui6gsmDKse/uO732Xg5k2q3vZ7dE94SE4sZWDyx9hXBomLs+B0Ord1dz4siKLIysqKTKTcbjdxcXFYrVbKy8tlR/LdQPLCcrlcUWRJipeZnJyU42UqKiq2rdgtLS3R19eHWq2mtrZ2k85qZmaG/v5+Kisr5XaXz+ejubmZ3NxccnJyCAaDtLS0UFJSQlJSEn19fXIo8tWrV6mqqmJ+fp7k5GS5JbixUqDX6/F4PCQmJnL79m0SEhLwer0Eg0Fyc3MZGRmhpKSE69evY7PZKCwspKuri97eXioqKqivr6ezs5Pbt29z7NgxDAYDjY2NDA8P09TURG1trbyvkpKSZLH9rVu3iI+Pp6SkZFP1SBAEuc3n9/uZnp6mpaVFjtFJS0uL2rdzc3OkpaVte+wk+waLJWxVEAqFWF5exm6309HRgdfrJSEhQbZ4MBgM9/0htVCXRrbTRFv8OLW+IvK1Kbt+79rkOlPPL+FdCJBQrkU98V1UwwLTU1PExcXxgQ98AKVSyfr6etR1Y3l5mdmVl0EU6O9eYFTVFLPdmJWk56nGJJ5tcvDv1xw8fTYJhWJ3+8vv9z9Ukg7On4evfhX9e96D9fd+D557bpPH1YOKrYiVy+USeMgrVg9Xf2wLHIW22UFjpwu3FOy7lWM4hCt5G40vdxPsu1cU6zJ4pbCb1dzTmHr6aPLl8PmvfY3n3/JLeNbV6HT5KBRqbMv9FKa/mYmJiQP77L0gFApFESmPx0N8fDxWq5XKykqMRuNd3TDT0tKYm5sjLi4uZrzMToJcp9NJX18foVCIioqKTT5Kfr+fzs5OQqEQZ8+elVuHa2trtLS0UFFRQUpKCqIocuvWLTIyMkhPT5erMWfPnsVms6HVaomPj6e3t5fy8nIWFxexWCx4PJ4oIiPlByoUCjQaDR6Ph6ysLKampsjPz+fSpUvk5+dTW1vL9evXOXfuHJWVldy8eZPR0VHy8/Oprq5mYGCAlpYW6urqUKlUFBUVkZKSQnt7OxkZGRQWFsr7PTk5GavVytzcHM3NzVitVoqLi2O2SdVqNXl5eeTl5eF0OjfF6CQkJDA3N0dtbe2ejqNCoSApKYmkpCSKi4ujzpuuri7cbrd83lgslrs+b/YDURTJXzCyZobvLl3nIyk/i3YbuwWAoC/E3EtOFm+soY5Tkvf+JBLK9HgHfgb7177GpR//mDNnzsg3S61Wi1arlavLbq+D0ZZh8tLPUlvyM5uMVG02W9SDW16chZ6pJL53eYjqbGUUAduKPD3w+qpYePpppq5eJevv/g7+4A/gL//yfq/RgWArYuXxeATAc1jrcT+I1SZBlZQX+CBoXHYLnU7HRqH+gw5RFGVR6kadk6xvulOqly5WknnjYWee6RUa4rN0LJecJuEHL/K+3/oIf/fKK9z6wTeg8udxrIIlvgDbch9VBU/JxO9eQ6o8SPYHUuXBarXKFZSD3E9xcXH09PQwNTWFxWKR42V2+gy3201fXx8ej4eysjK5chIJm81GV1cXxcXFskM5hKtb7e3tHD9+XBY6d3d3YzQayc/PJxAI0NHRQX19PQB9fX2cOHFCdlmPj49nZGSEnJycTcQKXtNlWiwWOSPw2rVrFBQUUFBQwODgIJWVlRQXF9PZ2cmJEyc4fvw4169fR6fTkZ6eTmlpKRMTE1y7do2GhgaZ2J07d46+vj6uXr1KbW2t3LYSBIH09HTS0tKYmpri6tWrpKenU1BQsOUNOT4+nsrKyqgYHck36m5FwwqFArPZjNlspqioKKrS2d3dLVc6pYrWXiqd+8Xq6ioJhjjeYT7Glxdf5Mcr7bzVXL/l652DXqa+v4x/OYilwUj66+NR6sL3AF1JCcqaGmx//de86x3v2HIZA5M/RkSkJOdNAHKLNVY7e27JT/PFRXRqkZKseJRKL0tLS8zMzOB2u6OkBpFVL6/Xi1qtfujsc8bf9S7S19dRfvazYY+rj33sfq/SXWMrYhUKhYLiIfZ0D70VuLKysilxWdJixHoCfFCh0+mw2Wz3ezX2hGAwuKV/k3TR8fl88hRXXFwcKSkpGAyGKH3TUUGpIZOh82Xk/gBOxieSaTbzyvPf5Fzlz7PoDJCcWEbP2PP4/C65wnjQT6bBYDCKSK2vr5OYmIjFYqG2tvaeiJI3xsuYTCZKS0t3JWL3er0MDAywvLxMWVkZycnJMQNNe3p6WF1d5fTp01HbIDmRnzp1StYBDQ8Ps76+zvHjxwHo6ekhLy8Po9HI7Ows8fHxGI1GhoaGZIK2vLxMdXU1ExMTm/REUjvQarUyNTVFVlYWBoOBlZUVsrOzefXVV+VK1tzcHDMzM2RkZNDQ0MDVq1fRarUkJSWRk5ODTqfj2rVr1NfXYzQaUSgUVFRU4HA4aGlpIT8/n5ycHHkfCIJAdnY2mZmZjI+P09TURE5ODnl5eVtWXBUKBWlpaaSlpdHT04Pb7Y4Zo3M3EARBNjktLCyUhxwkTdzq6iomk0kmWttp8/YLyek/V5tMo6mMK6t9lOszKdZFt9gDa0FmfrTCUocHrVVF0YetGHM3V05TnniCjj/5E3zr64R8PhQbqqtur53xuavkpjVi0G22iIjEuM3H11+1o1EJ/NIbkklJiE2GpeEY6brncrnkB8lXX30VCFfNYuU2PmiB2f5AAMXnPgczM/CbvwnZ2fC2t93v1borbEOsNvGOe4nDJlaOWGRD8kd62IjVUWsFRpbJN/4rVQwjLxhms5mMjAzZ+BKgq6uL1NTUPY/w3w+U6TL51/MjPKI3E/rBK7z9rW/lS1/7Gqc9LhadJgqKSmEMFpf7SUhIYHl5eUfty06QprskIhU53ZWTk3PPprs2xstkZGTI8TLSpNl2x2x9fZ2hoSEWFhYoKSnh2LFjMW8Sy8vLdHR0kJOTQ1VVVdRrxsfHmZycpLGxUf4uT09PMz8/z+nTpxEEgYWFBdxuN8eOHUMURQYGBmhoaJCtGxobG/F6vWg0GhQKBW63e1O1TBKwWywWOjs7AcjJyWFiYoLq6mpKSkoYGBigpqaG6upqrly5QlJSEjqdjoaGBq5fv87JkyflBwONRiO7wEstJskmoru7WzYVjSTdCoWC/Px8srOzGR0dlVuQOTk5W1bepcnL8+fPy15c28Xo3A0EQSA+Pp74+HgKCgpkW47FxUUGBgZwuVzyNKnVao2aJt0vlpeXZX3d4/HVDHhn+O5SMx9LfTN6hSbsi9bpYfqHK4R8IVIfjSPlQhyKLYTkCq2WpHe+k8Uvf5mVH/0I84ab/sDEjxEQKMn+mW3Xa2DGy781OYg3KPmFxywkGre+7UUGZkfq28xmM2lpaYiiiM/ni7p+Li0tbSt3iPTzOmqThYJKBf/6r/DYY+EInFdegVObpysfFMTyGwuFQgQOeUT/0ImVw+HY9C2SSMhWcQwPIg7bTFPSN23UNrndbtn4UqVSRRGn/eibTCYTq6urDwSxSlLFIeQJuArOENf0Ck9/++t853vfY33qNrY8M4mmHNQqPQtLfaQlvm5fxEoyfpR8pILBoEyk8vLy7rk2Y6d4GQiThO7u7pgVuUAgwMjICNPT0xQUFMhu6RsRCoUYHBxkYWGBurq6KAIgiiL9/f04nU7OnDkjn0uSGeaZM2dQKBSsr6/L3lWCIDA5OYnVakWv17O0tITRaEStVrOwsCDf1GK1AqWKlVKpRK1W4/V6SUlJoaenh2AwSHp6OsPDw6ytrWE0GqmsrKSjo0OeYqyrq+PmzZucPn0anU5HYmIip06dorm5mbKyMvkcUKlU1NTUMD8/z7Vr1ygrK5Od1SWoVCqKi4vJy8tjaGiIS5cuUVRURGZm5iaiIllfSE/UG2N0urq6CAQCW8bo3A0iQ6vz8/MRRZG1tTUWFxcZGhqK8j+zWq0kJCTsmWitrKxQUhI26FQLSp4yn+H/2H7CD5dv8qSinqnvL+Ma9GHIUpP1Niv61O237xd+4RcoKSnhY+fOsXr5MrqyMvSl4cm/Nc8i4/NXyUs/v2216vaYm+9cXyI1Uc0HHrVg0u2d2KyurpKdnQ0QFZi91RTxxgEd6WFiqwGdyH8PSyQfZUtgMMD3vx/2uHrySbh2Dbawtjjq8Hq9m46LzWZDpVIdqgHjYWcFihkZGZuY42GM8R82JJHtQUGKnIhVbZL23cZR5MTERLlEfVD6NaPRyPz8/IEs6zBQYsxgqq6GY1/9IWdT0xjt6eEbzw+ysLCKIKRiTSjBttxPadY7mZyc3HF5kQ7adrudUCgkR5UUFBQcijuzFC8zMTGBKIox42UiIQgCeXl5jI6OUl5eLi9jfHyc8fFxcnNzZbf0WFhdXaWtrY2UlBTOnj0bdS6FQiE6OjpQKpXU19fLN2On00lXVxenTp2SbxadnZ2UlpbK037Dw8M0NjYCyN5VECZkUtix2+3e1Ao0GAwsLS0ByDqrzMxMUlNTmZubIzMzU3Zvr6urIyUlRd5fubm5svZJMhCVKgyNjY00Nzfj8/miMhZTU1Mxm810dHQwOzvLsWPHNt0A1Wo15eXlFBQUMDAwIE8npqamIghhw8yRkRG5HRqJ/cbo3A0EQcBkMmEymcjLy4ty7B8ZGWFlZUVOHbBYLCQmJm57DZEe7CK7DhmaJC4YK5m87qC3ZQ6FoCDjzQlYG4wIO0zkra+v8+yzz/Lrv/7rxD/2GN6BAZaffx7NRz+K0mhkYPJHCCi2rVbdGFjlBzdXyEvR8P4LFnTq/V0DY52D20GtVpOQkLBlYPZGS5mlpSWmp6e3tJSJJF4HJbnYVNlJSXnN4+pnfxauXgWr9a4/57AhTRNHYnZ2FqVSubsk7wPCoduuiqLo3vgUqtVqj1zb7KCwW8FjZEjqRvIUGZIqfcGMRqM8Zr3bkNSDgMlkYnh4+FA+6yBQps/kyhuKOPZV8H/nRXSf+CiWpEmGfUq8c/Mkm8uYtXcQElZxu92b3u/3++VqlOQ6LxGpoqKiQ2tfx4qXqamp2dITaCOysrK4dOkSeXl5LCwsMDIyQmZmJufPn9+SkImiKGf/1dTUbHLcDgQCtLa2yvtCOgc9Hg83b97k5MmT8vdcCtKVLC3Gx8dJT09Ho9EQDAZxOBxUV1cDYfF7VVUVEL4JbVw/vV7PzMwMEPbqmpmZITMzk5ycHDo7O8nMzCQ5OZnBwUGcTqdMpJqamrBarRiNRtnSobW1lYaGBnnKMNLrqrS0VN4mjUbDyZMnmZ6e5sqVK1RVVWGNcePRarUcO3YMt9tNf3+/7OIeCoXk7+12iBWj09nZSUZGxo4xOncDQRBkjymJVEpEa3x8nNu3b6PRaOSpw40pBVJ1MBKeeT9Zz6dimUrClr1M3TvzMFt2d77eunULr9fL2bNnEVQqkp56ioV/+AeWv/99tG99nIm56+RnXIhyWpcgiiKvdLm42OWiPEvHuxqTUCv3d32UBnYOcrBKqVTuGJgdaaTqcrmYn5+PMkHWarUx24271XnF1JOWlMD3vgePPw5vfSu89BIccWPajfB6vZsebmdnZ/H7/WOHuR6HTqzUavXc3NxcYX5+vvw7nU4nG8E9TJC8rLRaLYFAYEsbgo1xD3q9noSEBNLT06P0TUcBR1E7th0y1RamzplZj0sl9OOX6H7bo/ziR5/kDR/6SyZEA+lPnQPCkRharRaXyyVHxDgcDgRBICkpCavVSklJyaEfi93Gy+wEKZbl4sWL5ObmRlkjxILH46G9vZ24uDjOnTu3qZrl9Xppbm6moKAgaiLQ7/fT3NxMdXW1fOOQBPHnzoX3dSAQYGxsTP7/2dlZ0tLS5OEItVotV3xjbaeksQIwm810dXUBYdIvDWDo9XrKy8tlIb1KpaK6upr29nYaGxsRBIGsrCw8Hg8dHR3U1tbKwcj19fV0dXXR3t5OTU2NfFOV3mOxWGhvb2dubo7y8vKYlT6DwcDx48dxuVz09vZis9moq6vb8/G6mxidu4UkrpcqiR6PB7vdzuTkJJ2dnajVaploud1umXiHAiILr7pYaHKh0CpIeLuW76Z0YcPBe8Vzuzp3m5qaADh79iwA6rQ04h9/HOdPf8pw7hyCQhmzWhUSRV64ucKNwTWO5xt4a0Miyl36VcXC/bBaiNR5xYKk84q8n9jtdjwej3xtVqvVMQX2er0ehUKx9XY1NsLXvw7vfjc88ww8+ywcMV3YdoilsZqdncXhcAwd5nrcj4rVxMzMzNmNxOpBullvRKyAUrfbzerqKleuXEGhUMhmjZH+TbsJKD1qEAThgbLHUAgCRQkZLFbWk3LrEoUFBXg9bvpaXmDB+nrSRhfRqOIYGr9B0FlFc3Mz6enppKSkUFZWdl+OzV7iZXaCZI/R19dHQkICer2evLy8bZc1NTXF0NAQlZWVMbV0LpeLmzdvbvp7KBSipaWF4uJiWSMliiLt7e1UVVXJpHR0dJScnBz5/ycmJqipqQHAbrfL7/V6vTHF/mq1Wo6LUiqVqFQq+YKanZ3N5OSkbEIK4QqY2WyWfaCGhoYoLi4GoKioiM7OTvr7+ykrKwPC53hVVRXDw8PcuHGD+vr6qPNAr9dz+vRpRkdHaWpqilnNkxAXF0dGRgYKhYKxsTEmJiYoLy/fk550Y4zO5OQkly5d2nOMzt1Cr9eTlZUlE2mv14vdbmd6epqZmRl0Oh1Bl0jokonAEphr9GS8KQGVUcnjrmP81NnBbc8YNYb8HT4Jrly5QmFhYZTm0XT2LEsjHcys95CffBadNrrVFgiKPHdjic5xD2fLTLyx9u4F+dI05VFCpM4rFqT7UeRD/Pz8vHxvkv6u0WgIBAKbCJjqqafgr/8afud34L/+1/B/PyCIVV0cHx93+3y+nXUeB4hDv2t4PJ7R2dnZqN8ddY2VpG+KNVEX+YQQ+VSQnp5OKBQiOTn5SDh6HySkisFRu+BshTJdJsNny8m4/h+4mzp59LHHefnVn7Dwzvcy/+KLaE6lEGSFmpoaFhcXqaiouC/rudd4mZ1gt9vp6+uTBduSPk7yjdqI9fV1bt++jUKh4OzZszGrcw6Hg46ODurq6qLWTRRF2traSE1NjTrfx8bG5NYbhCtaU1NTXLhwAQi3m0RRlNtIi4uLskDc7XZvOUUZSe4lnVVGRgYZGRlcuXKF4uJiBEGgrKyM7u5uWctVWlpKU1MTKSkpskD72LFjtLS0yHozaflFRUXodDquXr1KQ0ND1I1MEAQKCgpITk6mvb2dlJQUiouLN13UQ6EQQ0NDcp6i3W7n9u3b6PV6ysrK9tzaMxqNlJWVUVpayuLi4q5jdO4FdDqdrA1bXl7m5MmT2LqXWVkCb+4SE6mjrI6Hq72nzMX0eaf5wfJN8rSpJCi33+6ioqJN30NBoWDhuAaFXSD55hpiWQjhzv5eD4T4tyYHg7M+3lATz/mKgxmEitXiPOqIDMzeSuclpRZIcV5Sxcvtdoc7KMePU/qe95D2N3/DolaL/zd/UyZearX6SNpKbCW7GRsb8wKzm99x73DoxMrhcAxPT08HIj/7fufqSfqmjcRJMvMDokzjJFHnTj1taRkPG+Li4nA6nQ8EsfJ4POjsQbp/JofzfwX2b/yQC+fP8h/ff55Wl59GtZ+0lHxGpl8lOdlKX1/foRoB7ideZiesrKzQ29uLQqHg2LFjUQQoJSWF4eFhHA6HXNGBsP9UT08PpaWlWz4IzM7OMjAwsMm7CqC3txetVhsVlLu6usr4+Ljc8gMYGhqioKBAbmNNTk7KE1cQri5VVlYC24uGpSq3wWCQXdGlSbr4+HgcDgcWi4WEhAS0Wq1MVhUKBbW1tbS1tcktTkEQqKur49q1a+h0OlJTU+XPycrKQqvVcv36derq6jZVmuLi4jh79iyDg4OyqWjk92J4eJj09HS5PWGxWGhsbGRhYYHW1lY5Q3GvhEgQBJKTk0lOTo6K0VGr1eTk5GyK0bmXcLvdaDQajEYjhpMGBloW0LqTya8P68QWFhbo6+sjR61iJjvAt+ab+IXkx7Ztq/9lDCdwl3ueqeUOcrWViINTrLW0YDp1Cs96iK+9amfKvs7bGhKpKzw4IuRyuTZNgj4McLvdFBcXb/ngEgqF8Bw/jtfjwfrnf86swcDoE09se0+UCguHqfmNRKw2IMDk5GSAh51YiaI4Mz4+7gbkq/29PgiBQGBL/6ZIfZN0csTHx5OamnrX7NxkMu1q0uxBg+T5dBQrcZLeYHFxkZWVFTQaDRaLheTscPvB5FPy/ve/n9///d+npbsdV7EBvSqRkBjAHwwHHG/M1jtoSO05KV4mKytrV/EyO2F1dZW+vj78fj9lZWUxx8EFQaC6uprW1lbOnz+PKIqyFcOZM2e2vMGPjo4yMzNDY2Pjphvi6Ogobrc7SkMUCoVkjZLURvP5fMzPz8vVKlEUmZ2dlYnX+vo6SqVSJl0ej2fLlplkuSDlSfb09Mh/kzytpJZiaWkpbW1tWK1W2d8pKyuLvr4+mcQplUrZQFSj0UTtu+TkZE6cOEFrays1NTVRhBTCmpjS0lJSUlJobW0lNzeXvLw8VldXmZmZ4fz585uOQWpqKikpKczMzHD9+nVSUlL2PQyxmxide4nI7ENBIZByPo6Jby/hHQmRXp4uExO/349oa+OqOMwP2i6S5NXK+kWLxSKfV6urqzEjefonfohSoaa87hlWh5/H+ZOfsJ5VwL92hLC7Ajx9NonK7IMVW0tGuQ8bdtKOKRQKjPHx8K1vwdvfTvqnPkV6SQm85z1A7C6O3W6PmlLf2MWJ9PO6F6Q/lnAdYGZmRuCoEitBEHTAJUB7533fFkXxU4Ig1ABfBEzAGPBzoig6t1nU7Pj4+Ka+n1Kp3NI1dTvE6idHHmxRFFEqlTGrTQaD4Z5qaCTPp4cNiYmJjI2N3e/VkEfEI4mUTqfDarWSm5sbNSJuWQ4TpXW7h4z0DP7rf/ski9o6xuNWKVsP38zcXrucrXcviNXq6ioTExPMz8+TlJS063iZneDxeOjv72d1dZWysrKY02qRMJlMZGdn097ejsvl2uQuHglRFOnp6cHj8XD69OlNgunZ2VlmZmZkA1AJQ0NDWK3WKIIyMDBAUVGRfEzsdjsJCQnydzBSXwVhkhxZPYpEpEmoSqWSfbIkIi15QqlUKkwmE3FxcczNzck3+YKCAq5duxb1mRqNhoaGBm7cuEFDQ0NUCyg+Pp7Tp0/T3NxMcXFxzIcKs9nM+fPn6enp4dq1a/j9/ijx+0YIgkBmZibp6emyxUJmZiYFBQX7vi7FitHxer2yNupeTLHOzc1F2UgkVuqZe8nJwiUX8WWvVfTVajWvSz9B59wMjnwFb0k8I3vADQ4OytYln/70p2lvb6evr09epss9y9RCK8VZr0enjUf99rcz8MWv8K8Xl/BqTDzziIXCtINtg4qiSDAYPFLDQwcBaShkV9cdjQa+/e2wBcMzz4DRCE88EVWM2PigAbF1x7Ozs3JnSLovb2Wkup/zfyuyuLa2FhJFcVsRtyAIXwaeABZEUay687s/Bn4ZkFzNPyGK4g93sy57WXsf8LgoiquCIKiBJkEQXgD+N/BfRFF8VRCEXwT+K/BH2yxndmJiYlNmj1Ta39heijUBEWl8CZsnIKRq071ixruFRqO5ry3OewXpWB12dpZkaigRKafTiV6vx2q1kp+fT0JCwpbH22oMkw2FL4Bz3sNnPv3H/O13ZxhdnKBmNXyM3N5FUlOPc+PGDdno8G7h9/uZmZlhcnISpVJJTk4OpaWlBzLR5fP5GBwcxG63U1paKnsm7YRQKCRXj2pra7esPIZCIdra2tBqtdTV1W1atsPhYGBggMbGxqjtWV5eZn5+Xp7oAmS/HslGAZB9pSQsLi5GEantWoEGgyEqi1PSWaWnp8u5fjMzM/JEW2lpKc3NzfL0oSAI1NbW0tzcHKUnk6b5WlpaZF2UBL1eL3tdeb1eCgoKNq2XUqnk2LFjtLe3Mzs7y9ra2pbCdgkKhYLc3FyysrIYGxvj8uXLctVrv9evyBgdn8/H1NTUgcfoQPj8lgTQEgSlQPK5OKa/v8zq6DpxBa/tQ7Wg4lxcOS+s3GIq5CA/NVU+5oFAALvdzquvvkpJSQmvvvoqZrMZq9XK5NIPUCo0FGW/AQBbQMf38t5O0Ovj3QnjFKYdfPXc5XI9EHKHvWKvvlyygejrXgfvelfY7+qxx7Z9S6TOa6vzf+OkvM1m23JSfiMBi0V2YxErURQJBAK7uQl/Bfg88NUNv/8bURQ/u4v3R2HXxOpOgKFUflHf+RGBUsKVLICfAj9me2K1aLfb5W+05NkhiiITExMolUp5Z2/l2bEbfdNRwX4rcUcZ0lTKVlNbB4XIGA673Y7L5ZI1NYWFhXtzh76z/4XgOr1DM9Sn5KNw9tDjieNJewDUsOa1ywZ8dzNmHStepq6u7sD2ld/vZ3h4mLm5OYqKiqisrNz1fnA6nbS3t5Oens6FCxdobW0lOTl504XK7/fT0tJCampqlG5KwurqKh0dHZw+fTrqvcFgkI6ODk6cOBFFCvr7+ykpKZHXMxAI4HQ6o552HQ6HbGAqrcNW1QK9Xs/CwoL8/1arlYWFBbkilZ2dTVtbm0yspEr11NSUrOkyGAwUFBTQ3d1NbW2tvKzExEQqKipoaWnh9OnTUd9dtVrN6dOnaWtrw+PxUFFRsWnfr6yssLKywuOPP05XVxezs7NUV1fvWC1SKpUUFhaSm5vL8PAwly5doqCggOzs7Lu6zknat4KCggOP0VlYWJBjbCKRVGtg/pVw1SqSWAGcNBZy2dXDK84u8pNfI9IqlYqJiQnm5ub4zGc+w7lz53A4HIzP3GR2pQ2tWE5fzzA+pYWf9inQatQ8RQf6q62sV+WiOWBpwsrKyj1vo94P7GvSMT4efvQjeOSRsMfViy/edfSNSqWSY5diIRgMRvl5raysyFWvWN6Oy8vLJCQkyC1BQRBwOBwolUrHTusiiuIlQRDy7mqDIrdtLy8WBEEJ3ASKgP9PFMUbgiB0AW8FngfeDWRvswhEUQzl5OQompqaolxmJX1Feno6qampB+oyez9hNBpZW1t76L6giYmJLC8vHyixigyOlYhUXFwcFouFkpKSuwuOFQRErRZR8OIYX2W+dIHf/uAbeezpP2As9Y3ochNwexcBSEtLY35+PqqashvsJl7mbhAMBhkZGWFqaor8/Pwt42diQRRFhoeHmZmZoaamRj4fi4qKuHXrFg0NDVEGny0tLRQVFcWsZnm9XlpbW2OSxd7eXrKzs6O0US6Xi7W1tahq1PT0NBkZGfJn+v1+FAqFTGKkIPqt9l2klxWE23CRrSODwYAgCFFTXcXFxVy7do3MzEx5v2VnZzM3NxelE4KwyN/r9XLz5k3q6+uj9rNSqaSuro6enh5u3brF8ePH5b/7fD7a2tqoq6uTK30zMzNcuXKFysrKmCRkI1QqFaWlpeTn5zM4OChXcKRq3H4RGdR8UDE6c3NzMYm3Qi2Q3Ghi9idO3NPrGDJfI5VqQcX5uApeWLnFqG+BfO1r++S5555DqVTyxBNPoFQqMcWrWBh8iXhjJmerPszFThdXe/wYVOtUmaZYi0tBN6zD/q1vkfaRjyAcYNvuILJDjyL2PeloscBPfwrnz4dbgxcvwh1T33sBpVIpm9bGwsY0kpmZGfmhVtJ5TU1NodFoFu9iNT4mCMLPA63A74miuLSbN+2JWImiGARqBUFIBJ4TBKEK+EXgc4IgfBL4HrC+03KCweDKsWPHLJFkY2ZmBpfLdSQF0XcDSWf1sBGrhIQEVlZW7mpiRhRFnE6nTKTW1tZkIlVaWnp3RCoGBI0GjT5IwpyJKcMq1dXVTHRfZvDN7yBXZ2HNG3ZWT0tLo7u7e1fEaq/xMvtBKBRifHycsbExsrOzt42fiQW3201bWxtms5mzZ89GvTcrKwun00lfXx/l5eU4nU5u3rxJdXX1pvBjCFeampubqays3PSkKbVnJUG4hL6+PsrKyqKO5eTkZJTY3W63R1WvtprwkSCZ70qQCEFklUsSsUtVMK1WS1paGuPj40g+eoIgUFNTw9WrVzGbzVGfmZOTg8fjobOzc5MpqyAIVFZWMjw8zPXr16mvr0epVNLa2rrJpyojI4OkpCTZVLSiomJX54dGo6GyshKv1xvl4p6cnHzX34uDiNEJhUI4nc4tr22WeiMLl1wsXHKR977oc0mqWl10dpKf/Dr598899xyPPvooSUlJhMQgrb1fJiQGqCr8MN+67mFgJkBltoG3nUpEo8zBMT6OR60maLdz5Sc/wZiRIecd3q1L/crKCqV3sgkfJkRmH+4Z6enhatW5c/DGN8Lly3DHE+6wEanzgnCaQ21trVwZFkWR73//+/h8voF9fsQXgD8h3Jn7E+CvCPOdHbGvq78oisuCIFwE3nSn//hGAEEQSoC37PihKtXAxMREwbFjx+TfGY1G5ubm9rM6RxrSlNnDhsTERCYmJvb0HlEUWVlZkYmU2+0mPj4ei8VCRUVFzEmgA4VGg94AJqeeywsdPProo3zhC//AcCiBUrWVpdWwOa/JZJL7/LEIzN3Gy+wWoigyNTXF8PAwaWlpnDt3bk8VBVEUmZycZGRkhGPHjsUkSgDl5eU0NzfT29vL3NwcJ0+ejDmNFwqFaG1tlf2bIuH3++VswMhjuLy8TCAQiBLUr66uygMlEux2e9RrdtKBSJ8RqfOzWCw4HA65Mpaens7g4GAUqSssLKSpqYns7GyZ3Gi1WsrLy+no6IjKOwQoKSmho6ODwcHBmLq7wsJC9Ho9V69exWQykRqhGYqETqfj1KlTjI+P09TURHV1dUzRbyzodDpqampYW1ujr6+PwcFBysvLd/3+nRAZo7O0tLTrGB3JsmOr76xSq8B6ysT8qy68Nj+65NfOXUlr9aOVNsZ8C+RpUxBFkb/5m7+RW/B9Y/+B3TlMTsav8LVL4PJ4eUtdAg3F4euEd3CQ9W9/GyWQ9IEPkFFYKF9fbt++jcfjISEhIYpo7fb6ckebc2iRVYeJuzY9zcsLk6sLF+D1rw+Tqzst9/sJyfRUgiAIjIyM+Ofn51v2szxRFOVQXEEQ/hH4j92+dy9TgcmA/w6p0gOvBz4jCEKKKIoLgiAogD8kPCG4Ldxud9vAwMCbNhKrh3GCzmQysdEQ9WGANO6+nYA9FAqxvLws5+xFXuiqqqr2dKE7EGg0qLVBAFTTKgrOVeH/nI/R0S6cVZl4fC2EQkEUCiXJycnYbLaoVoAULzM1NYXJZNp3vMxOEEWRubk5BgYGsFgsm0TUu4HP56OjowONRrOl2acESex9+/btmF5N0jp1dHRgsViiImwkdHV1ySQjElIlLBKRgcsS7HZ7FHHZmCcaC5GRURDWWUUK4JVKJUlJSdhsNrkFp1aryc7OZnR0VHZfh3CVcnZ2NkqDJe2b6upqWlpaYq43hCtSUtRLUVHRlusr3AnDTk5Opq2tTa7M7radazQaqaurkyuMoihSVlZ2YNVwKb4pKSlpU4yO1CqMfNDY2D6NBetpI7arqyxcXiXnndH2H/XGIppcvbzi6uJD2scRBIE3velNAMw7euif+AlB5dN8/2YycXr48OuTybJoEEMhXJcu4Xz5ZdSpqSS9972o7pBMs9mM2WymuLg46kGuq6sr6kHOYrFgMpm2/O46nc49ueM/SNhIQPaFsjL4yU/g0UdfI1dbTPAeBgKBQMzvUUdHhysYDPbvZ5mCIKSLoijdvN8BdO32vXupWKUD/3xHZ6UAnhVF8T8EQfgtQRA+euc13wH+704LWlxcbO/u7vY89dRT8pVTpVIRCoX2sDoPBiSN1cMGyQ8oshUQCoVYWlqSp/bW19dlIlVdXX3PAmR3Da0WlSqIoILshWS6a5ZRKBSMd11m7uwHMelFPD4HRn0ymZmZDA4OkpKSsileZieicjeQ4mfi4uJoaGjYl4ZtdnZWJjS70YgMDw+zsLDAhQsXuHXrFnq9ftMkT39/P0qlMiZxmJ2dJRAIbCJcdrsdpVIZtSxRFJmfn49qsUhC1Mh9upvJJUlnJRGrpKQkBgaiq/4SiYrUNuXn58uB1JGfWVVVxZUrV7BYLFGfrVAoogxEN+qkxsfHWV1d5ezZs9y6dYtjx45ta3lhNBo5e/YsQ0NDNDU1UVtbuyd7j/j4eBoaGlhaWqK7uxuNRkNZWdmBTrBtFaNjNptlbyybzbaJNG9ajlFJUp2BxeY10h6PQ5MYMQiwoWr1gy99i0cffZSCokyae7/OlPO92FYLKMnQ8s7TSRi0CkJeL0vf+Q7evj701dUkvvWtKLYgCZGasqKioijpQW9vL2trYd86yUcrUnqwuLi4o23Jgwi/339wGZO1tfDDH8Ib3hD+uXgRDqiKuldIx3IjOjs7A8COrUBBEL4BPApYBUGYAj4FPCoIQi3hVuAY8Ku7XZ+9TAXeBo7H+P3fAX+32+XcwUBHR8caEHXXUKvVshfNwwIpTPZBydbbC8xmM+Pj42i1WhYXF/H7/SQmJmK1Wjl+/Pg9nRjcFzQaBL8PQ4aGLJuVG8Y+vv7Cv+HsT2BqJZFSXXgy0KgPO3Tb7XZeeeUVUlNT7zpeZicsLS3J7uXHjx/f101Sasf5/X4aGxt3rHKJoii//tSpUygUCurr62lububEiRMyYR4fH8fpdG5qk0G4MtbX18fZs2ej/iaKIn19fVRvELfabDaSkpKiLu6SS3okJI+q7WAwGPB4PLJXllqtlv1zJMJkNpu5fft21O+USiX5+fkMDQ1FEQO1Wi1bJZw5cyZqe1QqFQ0NDVy7dg2tVivvm4mJCaanpzl16hRKpZIzZ87Q3NxMYWEhmZmZW667IAgUFxeTkpJCW1sbWVlZFBQU7Kn6aTabaWxsxGaz0dbWRlxcHKWlpQf+vYsVo+NwONDpdLu6USefNWFvWWPhyipZb0mM+ptUtfr3/lf4Lx/7GJ/+9P+i9nXpdM68F18wiTfUxHO23IRCEPAvLOD4xjcILC2R8OY3Y9zQdt4JgiCQkJBAQkIChYWF8rCM3W6XfeCMRqPs5L/x3H0YcOCTjo2N8Pzz8Ja3wJvfHBa334dK31aC/Pn5eYAdxeuiKL4vxq//ab/rc788AIZ6e3s3eVlJQu+D0g4cFcTFxeFyuR54AXswGJQN/ex2O16vl1AoREVFBbm5uYeeAr9naDSwvo4hR4P72jpJoglXrZaSHhsvBytw+zMYn+ylr3NBFjobjcaoltFBw+l00tvbC0BlZeW+zxGp3VFYWEhWVtaON5xgMMitW7cwGo1UVVXJrzcajdTX19PS0kJtbS3r6+tMTk5uIhrwWsByRUXFpoehhYUFDAbDpnbKxMTEpimyxcXFTSRqN61AvV6/KTIqKSmJpaUluaokmXBOT0+Tl5cnvy4nJ0e2M4gkoFIMzsjIyKb11Gq1nDx5kpaWFk6dOsXCwgIzMzM0NDTI5EKn03HmzBlaW1vxeDzbtgYhPARy7tw5+vr6uHbtGrW1tXuu7CYnJ8tkoLm5GYvFQnFx8V07+W9EZIzO1atXSUpK2lWMjiZBhbnGgOPmGqmPxKE2vUbEpKrVn/zTnwOQVJTPjdFG9GoFH3rESl5KeBs83d0sPfccglqN9YMfRBtxLO9me6Rx//z8/Ch7l+XlZVpaWmSiJZ0XD/qU+j2xkHj96+HZZ+Gpp+BtbwtXsQ75XhBLN3ZHJ+sSpRHjQ8R9IVaiKK5mZmYGNv7+YSVWkjXBg0asAoEADoeDxcVFHA4HwWBQNuzLz89Ho9Fw8eLFqLH5I407xMqYo8HWBGddFTwbfJnLF7+LqlZPqrEUn2uGhoaflZ/Gr1y5QlFR0YFvnyRE9nq9dyVEDgaD9PX1sbKywqlTp3ZVrVhfX6elpYWMjAx5Oi4SJpOJU6dOce3aNUKhEI888kjMqsTExMSmbD0IE67+/n5Onjy56XNjGWY6HI5NwvDd+IgZDAaWlqKnny0WC4uLi1HtuuzsbFpaWqKIlUKhoKioiMHBwSjTUoCysjI5qHkjMTSZTNTU1HDp0iXi4+PlSlUk1Go1p06dor29nc7OzijiGgtKpZLKykrsdjvNzc378q6SdHJpaWmyGWhaWhqFhYUH3rb2eDyEQiHKysooKyvD5XIxMTGxbYxO8jkTjjY3i9dXSX999N9OGooY/NEtknPymQk+gjXOwS++rgKTXokYCuF88UVWm5pQZ2Vhee97Ud6jyrEgCMTFxREKhUhLS+PEiROyIfHw8LBsSCyJ4bczJD6qWF5e3pHs7wtvext85Svw8z8P7343fOc7cIiO9aurq5uuQ8PDw6jV6qFDW4kI3E/XSofD4UiPvKGYTCbsdvt9XKV7g8TERKampvbsi3TY8Pv9UURKipiwWq1b5pht1FkdaUjEKju8HZruELoqLd+9fAVL5zjFpV/BK15m6W//Fm1+PtqCAswKBYuLi5um4PYLaXTe6XRSWlp6V6PzKysrtLe3k5WVFdOoMhbcbjctLS2yL9JWkB7ytFqtXGWKXL7b7WZ0dDQqYFnCzMwMiYmJmyov09PTZGZmRi0nEAgQCoWibv47eVhJkFqBkbBYLAwNRV9LdTodarVa9kWTkJmZyfDw8KbqmFKpjApqjrx5BgIBRkZGMJvN26YqKBQKjh8/Tl9fH62trZw4cWLHlpnFYuHs2bN0d3czNzdHTU3NnqtOktA8MzNTnkDMzs4mPz//wLQ14+PjUSL+uLi4HWN0dFY1CRV6FpvXSDkXh1L32j4dm1hk9FoPZ574NVKtnfzyo4+iUSsJrq2x9K1v4RsZwVhfT8LP/izCIRgtS/oqQRAwmUyYTCb52u12u+V2qBShJRGtyAito4qN34EDxTPPwOoq/PqvhwnW174GB6Xn2gGxWoEDAwN4PJ72Q1mBDbhvxEqpVPYODg5WnopwbzUajXse4X8QkJCQEBUSe1Tg9/tlobnDETanlSZmSkpKdvWkK01iPQjEKqTREBwYYOxP/jsmWzGiO4NHy5IZ+NTP8exv/T2v/vgFin8hDk1JEb6RMTzd3VgBd1MTS2VlaAsK0Obno9zHtq6vrzM4OIjNZqOkpOSupglFUWRwcJD5+XlOnDix6wvlysoKt27dihkkHAmfz0dLSwt1dXXEx8fT2dlJW1sbNTU1KJVKRFGkra2N6urqTX5MoVCIwcFBTp8+vWm5U1NTNDQ0RP1OGtmPxHaO65HQ6XSbiJVGoyEUCm1KO5A8rSI9tgRBoLS0lP7+/ijndQh/Z9PS0hgYGJBDeCXj1NzcXHJzcxkbG+PWrVucPHky5rEUBIHy8nLGxsZkr6ud9KNqtZra2lrm5ua4evXqrgcQNkKhUMgZkKOjo1y6dEn+/7u5+YdCIWZnZ+Ug7Y2fuW2MznkzK90eFpvXSL0QPme7Jtz89f+9jFKtofzpArTVIhq1jvWZGRzf/CbB1VUS3/52jCdO7Hud94rFxcVNVUwJ0rZIxNLj8bC4uMjExAS3b9+WsyolonVgQvEDgDQ5d0/J36/9Gjid8Ad/ENZa/cM/wCF0M4LB4KZrUU9Pj8dms7Xd8w+PgftGrJaWlm4ODAy8K5JYGQyGh3KCTqVSEQwG77uAfX19PYpIKRQKLBYLycnJlJaW7qtlYLFY6O7ujum+fBQQGS+TkpxM1qVLFH/mM/Lfi/4KXgd8Ua1i+qufwtRaSNyxPtSZ+YTi4/ELAra5OfwLC3ivXiWk16OyWsMkq6AATV4eym38qwKBgOx4XlhYuOvK0lZYW1ujra0Nq9XK2bNnd30+LSws0NPTQ319/bbC+EAgQEtLCxUVFXLLrqamhtHRUa5evcqJEyeYnZ3FbDbHJGeTk5OkpKRsauM5nU40Gs2mCsxG/yrYfZbZVvtR0llFVhnT0tLo7++nvLw8ap+lpqYyNDQUU6NRXFzMlStXWFpaIhAI0NXVFWWcmpeXh8fjoaura9t2X15eHjqdjmvXrlFfX7+rbUtLS8NsNtPR0cHc3ByVlZX7+n5Kk5yRMTlFRUWbKoe7xfT0NGlpaTsSBilGp7CwUPZ867H3YEnLx3bVhbnByE+7nNwYXKO2vobHn/s1EqrLaQks0991BdN3XkJpNJL84Q+j2WYI4KARCoX2lKWn1+vJzs6WLTo8Hg92u52pqSk6OztRq9Uy0TKbzfeVaB1aRM/v/36YXH3602Fy9dnP3lNytb6+HvO70d7evsYuJgLvBe4bsVpdXe3q7Ox0AfLjtnTBO+xw38PA/RCw+3w+mUgtLS2hVCqxWCzylNtBuIPvZKZ5v+B2u5mcnIyOl/nWt8Dng/l5gpMzTP1DH0bdEiPmWyhGZpn6zkXyxhfIdF1DWPghSq8XJdEZTaJKRSg+nqBeT8hgwGs0Qloaivx8lKWlqI4dQ5GTQzAjg7E7juy5ubl7dkvfCFEUZff1mpoaeRJuN5icnGRsbIzTp09vq1sKhULcvHlTDumNhBRyff36dYLBIK973es2vV+K3InVHtzKA8put28i5bsRrktQqVSbKlySziqSWCkUCjlPMLICJAgCZWVl9PX1bdKECYLAsWPHuHr1KgkJCZw+fXrTepWVldHW1sbw8PC22pW0tDQ0Gg03btyImrjcDlqtlvr6etkVfTuT152gVqspKyuTY3KGh4f3FNwN4XNwdHSU+vr6PX12ZIzOhGEO5w9EvvWNMfp1WqqzPSiD/5uc1JNUJj9K98zzXFzr4ansbMxPP73tQ8u9wNLSEmazed/3H71eL7dAIdz6t9vtzMzM0N3dLV+DLRYLSUlJh5ohu7y8vGMg+IHhT/4kTK7++q8hIQE++cl79lFbGZ729PSIwOA9++BtcD81VgMdHR0eIogVhE/Mex3uez9wGAJ26UssESnpaSk9PZ3Kysp7Rnw2GjPeL+wqXkang9xclLm5qNcqmL62SvBX38J/hG7hOvE+XtLn86GfXeBE6XvB5YK5OUIzM/S88grliYkobTaUc3MoZmcRJydhchKhowNhw+CJLzub4Isvcv78+bu+eHq9Xtrb2zEYDHuKy5Fahg6HgzNnzmz7PlEU6ezsJDExMSYBgvA5rFKpMJvN3LhxY5Pb/NjYGJmZmZueHkOhEDabjYqKiqjfBwIBgsHgpvbYXioGkpdV5PfKYrEwMjKy6bU5OTn09/dvaq1ZrVYGBwc3PdHbbDa6u7tJSUlBpVLFvCYJgkBtbS03btxAp9PFNE+VkJSURH19Pa2trVRUVOwqN1AQBHJycrBarbS1tZGYmEhZWdm+v8tarZaqqio8Hk9UTM5uPJuWlpbkwNv9QKlUkncyg9s/ncHo0JJfdZPnv/pnXHllhH/78jtxXv4aNYlrXGtMZa36caz6wyVVsDvT071Ap9PJ0UHw2sPu/Pw8vb29ctdAqmjdK388uIfC9VgQBPjbvw1fQz/1qXCI82//9j35qK2I1crKSlAUxfviOn4/idXo0NDQpscCo9GIy+V66IhVQkICMzMzB7pMqb9vt9tZXl6W+/uZmZlUVVUdWgUpLS2N6enp+0Ks7iZextIQdoXO6LSiqBRoeFcjvTcTGLONU10URBUfD/HxKEpK0GZmMq5UUlBQAIBw5weAYJDQ7Cy2V1/Fd/Uqmf/8z2hTUmJGoOwVMzMz9Pf37zrAV4Ioity+fRtRFGloaNixZTg4OIgoituuc19fH5mZmRQVFWG322lpaSEzM5OCggJEUWRiYoLz589vet/8/DzJycmb1kGqDmyEx+PZtWeYlAAQSYi0Wq1M2iK/AwkJCXi93pg5hGVlZfT29nL69Gm8Xi99fX14PB5OnTqFTqfjxo0bLCwsxDwGCoWCkydPygai25EUk8kke135fL5dZ7YZDAYaGxsZGRmRTUXv5iFNr9dTW1vL6uoqfX19DAwMUF5evm0ldGhoaN/WI6FQkIWlHibmm3EYLpC+quOnP/0iX/vH6/zMG1+H9WozPo+HgrwzdAhrXFzr4Rf0h389sdlssqbuXkCr1ZKRkSFn4kryjIWFBTlEXKpoWSyWAyVa91S4HgsKBfzjP4bJ1e/8Trgt+OEPH/jHxHISuDMt7DjwD9sl7huxEkXRn56e7ot18VtZWdnTTeRBQEJCguxXtF9IEykSkZImUqRolful30pKSqKzs/NQW7gHES+jNauIL9XhurVOcXUGU/ohBLGG//Xxf+Sn1Tf4whf+QX5tfn4+ly9fJicnJ6ryI4oiC4uL9I+MYK6uJsvrRfn3f4/4nvfc1fb5/X5u374NwNmzZ/dkmhsIBLh58yaJiYmUlJTsuE8mJydZWlqKaQAqweFwsLS0RGNjIxC++J8/f14WRkui3lhVscgg5EjE0lfB/ipWGyHprDYuPysri6mpqU3tR4lQ3Lx5E5fLJU9NSvujtraWa9eukZiYGPNYqNVqGhoauH79OidOnNiWGGq12iivq+Li4l2dt4IgUFhYSHJyMu3t7aSnp9+1FYjJZOLkyZOsrKzIFZSysrJN67+0tEQoFNpTC1oURRzOEaYWWpi23WQ9sIbbX45bb+Dyi1/l7194gSefeII/fc9bmRCduM8/wpTKhy+4zrBvju7JQUrT8w+tXSY90B+mpEGj0ZCeni5P6EZOZksPO0lJSTLR2q959qEI12NBpYKvfx3W1uCXfxlMJrjLa+NGrKysbLKN6e/vR6FQ3LeJsftZsUKtVg8MDAxkRV50ExMTZeb+MEGtVsecVtoKoihGEamVlRXZQyUvL+9IeagoFAri4+NZWVm5pz38UCjE3Nwck5OTBxYvYz1lxNnn5dh4Pv1ZTVgtfvSJhXzxi/+HZ575ec6ePQuEtTySAFiKY7Hb7fT19aHX6zl58iQGg4HV//k/ARDe9a59r9PCwgLd3d2UlJRs694dC9JEX3Z29q7sPRYWFhgbG+PMmTNbnk+BQIDbt29vIl6SMDo9PZ1Lly7J2qhIQuL1ellfX49JNOx2e0wfrb1orPR6PTabbdPvJZ1VLGJ17dq1KJfzQCDA2NgYq6urCILAo48+uunmqtPpKC0tpbOzk7q6upjrotPpqKuro7W1NaYeKxKSk/vt27e5ffv2nh4K4uPjOXfuHP39/Vy5coXjx4/fdQC4pCGz2+10dnai1+spKyvDYDAgiiK9vb1RE5XbweWeZ2qhmcmFFtzeRRQKNemWalKsdXz/VjLX+77L11/4BA0NF6j9m6d5Vq8CTCiYJ1mVQJU6l1TiEBYCXL58WY7RuRvt024wPz9/oG3A/UCtVkcFeUd6CQ4PDxMMBqOI1m7tOGJN3x4atFr493+HN70pbMlgMoWd2g8AoijG9LxrbW0N2Gy2lw/kQ/aB+0qsnE7nK62trY+Vl5fL3xaTyfRQTgZC+GLvcDhiVuMk11/J1dzpdGIwGLBYLBQUFBx519+0tDTm5ubuCbFyOp1MTEzIYboHGS9jKtCiTVYhtIEuS43Susr5d32SkfYX+ZVf+RXa2trkp8S8vDwuXbpEUlISw8PDKJVKqqur5fK66PejvnGDYGEhyhiEYScEAgF6enpwu9073phjYW1tjZaWFsrLy3fVll1ZWaGnp2dH/VV3dzf5+flb3rzHxsaorKwkOTmZwcFBBgYGyMnJITs7m6mpqZi6o2AwiN/vj3ljEEVx1w8NW1WsLBYLY2Njm36v0WgwGAysrKyg0WgYHR1lYWGB7OxsHnvsMTo6OrbUC2ZkZDA7Oyv7ccVCXFwc1dXVNDc309jYuC3pVygU1NTUMDAwQHNzM3V1dbuuzigUCsrLy3E4HLL5aW5u7l1fIywWixyT09raSmJiIklJSVExPrHgXXcybWtlcr6ZpdUJ/CodanMJiqwzrGoMXAk4cczNgSOZ1Ldk8q7bv8CvP/m72AcvkZVWSF7laZLV8aiECEKbBOWlZbJv1O3bt8nMzCQ7O/uepDzMz89vSZrvF1QqFSkpKfI9IxAIsLS0xOLiIiMjIwQCAdm02WKxbLlf7nv2ocEA//Ef8Pjj8K53wQsvhAOc7xKSHnvjeX/p0qVln8/XctcfsE/cV2K1srJytampafkDH/iAXF8WBCHmpM/DgEhX6MicqsXFRTmnymKxUFRURHx8/DItpbcAAQAASURBVJEmUhuRkpLC8PDwgekT1tfX5VafTqcjJyeHioqKA6/SCYKA9ZSR6f9Y4cRyEc0Jk2h0J/jgb32MP/+DP+Iv/uIv+MM//EMgTFwEQaCtrY2GhoZNJHL91i00k5MEfuM32GszYWlpiY6ODvLy8jh27Niej/3y8jJtbW0cP358V+TW7XZz69Yt6uvrt33qnZ+fx+v1bilo93g8sjBdEASqq6vx+/2yOaXX6+XEiROb2sRb6asCgcCeWjGSxmojJOf8jVKDYDCIyWSiubkZo9FIXl5elAVDWVkZra2tpKSkxDwG1dXVNDU1kZSUtCXxlSJlpOib7bZH8tIaHx+Xva72YgqalJTEuXPn6Onpobm5mZqamrsmHYIgkJKSQnJyMjMzM7S1tZGdnb0pxzUQ9DJpa6ff0ca0bwG3xojfnII7JY914c4wh7hMUiBAmspM9/dGyS1Z57ceeT1rC6UsDcRR7c7HUvumLc/3yBgdv9/P9PT0rmJ09or19XVCodCRj+VSqVTy/oDw+SwF34+NjeH3+zGbzXJFSzpH7Xb7PY3m2hXi4+FHP4JHHoEnn4SXXoINvnZ7xVYDYTdv3hSBzrta+F3gvhIr4NbVq1c32RcnJCSwvLx8YG7XRwGiKKJWq5menmZ1dVVO47ZYLJSWlkYlqz+IUKvVqNXqLSc0dgNRFFlYWGBiYgK3201WVhanTp068MyzjTDXGJh90UlOZypXz/Wi0bhJKn2Mp59+mn/4h3/gIx/5COPj46ytrVFRUUFPT09MrYP4b/+GACh//ud3/dmhUIiBgQEWFxc5efLkvvadNGHU0NCwq5bQ+vq6fBPe7vPW19fp6emhsbFxy3NzYGBgk45LrVZTVFREUlISvb29TE9P093dTVJSEmlpaVit1gPRV8FrIeexYDabWV5exmQyMTc3x/z8PG63G6vVikKh4PTp05tIj8FgIDExkdnZWVlgHAm1Wk1VVRXt7e2cPn16y/2SkZGB1+ulra2Nurq6Hb/bubm56PV62etqL609lUpFdXU1CwsLXLt2jdLS0pjrvlcIgoAoiuTk5JCYmMiVK1ewZqYyFT/PpGcaOz48ah0kJAKJqFCQpjZTpDaTpk4kTZ1IqjoRrULNn/31P/ClP/w1PvK7f4yx+r24Bl4C3oGi8JFdX/fUajV5eXnk5eXtKkZnL5idnb3vbcD9QKlUYrVasVqtlJaWEgwGWV5elk1L19fXiYuLw+v1Ho1ihdUaDmo+fz7cGnz1VTh2bN+Li2Uh4fV6cbvdq6Io+u5ybfeN+0qsRFFcTk9PD2w0zpSsCR5kYiWKIisrK3JFyu12yy2j4uJiEhMTH2giFQtZWVlMT0/LGqTdYnV1lYmJCebn5+Wn/cNsfSq1CpKOG1i8sUZ6vZllywrLcxn8rz/7n8xOzdPZ2UkoFJIDWSXfoxMb3KAVP/0pgeRkVLtsJ7hcLtrb20lNTaWxsXFfT97j4+NySPJuCGgwGKSlpYWysrJtNReiKNLR0UFZWdmWy11bW8PpdFJdXR3z75OTkxQXF8sVWofDwdzcnDxxl52djVKpJDExUa4U7EVfJUGhUMiVKVEUWVtbY3l5GY/Hw82bNzEYDLJ3m8lkQhAEFAoFc3NzMVt6JSUlXL9+fctqSHJyMnNzc4yNjcXUiEkoKCjA4/HQ09OzK31SSkoKGo2G5uZmamtr9yQUl96fmJjI7du3mZ2dpbq6+q5upKFQiKGhIfncyszM5Pvjr3AraEOlCGFBT6Umg3xTHunqJJJUJhTC5v315S9/mf/+X36d0uOP8r9+7Rkc3/xX9OnJrK4IuIbWSard+7rtJkZnL5iamtr0fX4QEemTBeFjODo6itvtpqOjA6/XS0JCgmzxYDAYDv8+lJEBL74YJldveANcvgz7rKYtLy9HZYAC3L59G5VK1X73K7p/3O+KFSqVamBgYCAjsoWUkJDA/Pz8fVyrvSMUCkURKWlk3Gq1UllZidFoRBAEurq68Pv9Dx2pAkhPT6epqWlXk2h+v5+ZmRkmJydRKpXk5ORQWlp630xGrQ0mFq+vcXygiB9mDsNsOt++5cSkjSPBqOGfPvMJLv3ke+QXlfLU089QU1NLenYBqZYEFAoB0W5H3dOD7x3vQLXDtktGi5OTk9TU1OxLlyYFHTudTs6cObOr/SaKIrdu3SIzM3PHp/Pp6WmUSuW2eYJ9fX2UlpbGPNbBYBCHwyGTLkEQ5At+KBTi4sWLJCUl4XA4GBkZwefzodfrCQQCqNVqxsfH0el0aLValEolCoWCUCjE6uoqoiji9/tl6wRpCtLv97O+vo7RaCQxMZHMzEwCgUBMw9KcnBy6urpiEiudTkdKSgqTk5NbDgBUVFTQ1NREcnLytlW/iooKbt68ycjIiGzVsR0SExNpaGjYk1YuEhqNhpMnTzI1NcWVK1dk7dt+MD4+TlpamkyslUolZ7NOcsv2Atlr6+TNZ1NQkE+2NXvLh4KvfOUr/NIv/RL5VRf4P1/8Z7zPfROF0Yj1mZ/D91M/zgEfYkhEUOzverhTjE4sm4+NkFrJD5vFD4T3j8/no7i4mLS0tKj7VFdXF263W75PWSwW+T51z5GfH65cXbgAr389NDXBLq1HJGwlXG9paQksLi7eN+E6HAFi5XK5XmltbX2krKxMPppxcXGsrt4XX69dIxQKySVXu90uPwlYrVaOHTu25ZNApM7qYYNKpSIuLo7l5eWYT9uR8TJOp5OMjAzq6uqOxAVNa1FhKtIg3gpR6YlnRenAKahxBAUWHWpOPf2nxOWc5falb/PZP/0jEARqzr+bt/7aX6HXwImmf+dnQiEuNb6fwM1ljDolJp0Co1aBUafEqFNg0ikI+n20tbXJk137IZKhUIjbt2+jUCi2tUiIhCiKdHV1YTKZNj3hbYTH42FoaEieiIwFp9OJ1+vd8qYttVZirdvy8jJJSUlRfj7SRbKnpweDwUAoFMLhcOD1egkGg4iiiMfjkS0BVCoVOp0OnU6HyWTCarXGrFQMDw/HjJIymUwEAoEtK2RFRUVcuXKFrKysmMdIGlxob2/fttooCALHjx/n+vXr6HS6XbXojEYjjY2NNDc34/V69xXenpWVhcViob29nbm5OSoqKvZ0rkmTkhtJabImEWtQZMag5D2nTzI2OsmlS5c22VNAWEf3u7/7u5TVnucDf/BPFF1/HjEYxPqhD6GMiyOu2M1Suwf31DrGnLtv98eM0enpISUlhZycnC09nLYasHhYEKmvUigUmM1mzGYzRUVFUZ2V7u5uubMiVbSkCu89QXk5/OQn8NhjYXJ16RLs4UFCIlWxhOter7f5oFd3L7jvxGplZeXqlStXlp955pkoAbtSqTwaPeE7iOxd2+121tfXSUxMxGKxUFtbu2tyYLFYGBoausdre/8g+QRFEispXmZmZobExMRwvExS0pGp2oVCIcbHx5lOmCVRl01ZRw5I2ltBxJPoYykhwImfvYDz3acZWRrjxk9+hMFowpjSiegW0H3jMyzFJdKSUURwaJlAKPZ5m6Z38vS5kn1P6AQCAVpbW+Uhh93uw+HhYfx+/5bhshJEUaS9vZ2qqqptv3u9vb2Ul5dv+fmTk5NbtggXFxc3RbMIgoBer0cURbKysmLeBC9evBgzTiUUCiEIQsz2j6TXjNX2zM7OZnJyMqYpqkajITMzk7GxsS1zMKVprKGhoW2NVZVKJQ0NDVy9ehWtVrurWBqNRsOZM2e4efMmHo9ny8rgdtDr9Zw+fZqxsTGampr2VB0dHh4mNzc35jlQo8/lpfUJel2d1FU0UlBQwMDAgOzinpycjCAImM1mvvrtn3BlIpHT3mHEJQfWX/gF1HfIeFyRDhTgHPQdCLGKRGSMzvz8PN3d3QQCAbKysjalA8zMzMj+bA8bAoGArO+NBUEQ5H1VWFgoD1UtLi7S19cna2YlonXgWuDjx+EHP4A3vhF+5mfglVdgly3wrSJ6bt68GQJuH9xK7h33nVixhYD9fuuspGkLiUhFTlvk5OTsu8qi0WgQRXHXflYPGpKTk+np6cHv9zM/Px8VL3MQ8S4HCVEUmZqaYnh4mPT0dM78bD3qt6oJ+UV89gDeBT/ehQBem5/EBSPr40EQ4RSFvDfrcTwJPpbGV+mzt1A/P8s/AX/9+6+n/q31nHlTFRlWMyqvgLCuQgwlMeN8HFOCdd+kyuv1yqP1u3XshnBbz2azcerUqR0viqOjo8TFxW27jndcjbfUaLndblmTFguLi4scP3485t/2o7HS6/XyOm2EFLcUa10zMjK4cuXKlgadBQUFXL58mdzc3C3P25KSEq5cuSLrm7ZCpIHoyZMnd+WArVQqqa+vp7Ozk/b2dmpqavaswxMEgfz8fJKTk2lrayMlJYXi4uJtl+N0Opmfn4/ZQgU4lXSSV2ZGubU2TB2N6HQ6qqurWVtbo7+/n7/7u79Do9HwyU9+kplADklaF4W9VzG/+ym0EdVSlV6BMVuDa8BL+usOxj5lI5RKpVwZ9Xg8cos0Li6OnJwc1Go1er3+yDzAHzT26l8lCALx8fHEx8fLiQrS9PrAwAAul0ueXrdarQczvX72LHz3u/DEE/DmN4dbhLsY4olFrHw+H2tra25RFL13t1J3h/t+lxNF0RFLwC45sB8WsYr0B7Hb7QSDQZlISen0BwVJW/KwtQOleBlRFLl48SJZWVm7jpc5TIiiyNzcHAMDA1itVhobG6OqHQq1gD5NjT5tQ+ZdJOGyBfAt+DHOaChvFTEASY0fpXj2Nj/5+xf48f/3Q/7kM18i8ZEM1rJnKZ1uYW7tjSSa9veVW11dpbW1dc+aGclYcDsDUAkul4vJycktb6gSdjKLnJyc3JL4hUIh1tfXtyRPwWBwz+TbYDAwPT0d829Wq5X29vaYf1Or1cTHx+NwOGJWkSRT2JGRkS0rUgqFgtraWm7durVja1ev11NXV8fNmzd3DMSWIAVBDw0N0dzczMmTJ/f1cGIymTh79iyDg4NcuXKF2tramOQuFArR0dGxLYnTKbVkBxVMqkJ4/G70agP+gIg3qOFr//Zd/uYv/pSq46dJr3wbU/5kzs82Y37D6zDEmP6KK9Yx96ITvyuIOu7e6iv1ej3FxcUUFRWxtLTExMQEs7OzWK3WPU+jPiiw2Wx35V8VSbTy8/Pl4ZDFxUWGhoai/BatVuv+h47e8Ab45jfh3e+Gt70tXMXa4fuxsrKySdbQ2dmJSqXq2PsKHCzuO7ECUKlUg0NDQxmRF6/ExEQGBgbu2WdGOtra7XZCoZDsaFtQUHBPR/xTUlKYn59/aIiV1+tlcnKS6elp4uLiyMvLw+FwxIwxud+w2Wz09fURHx9PQ0PDnqojsQiXKCZhf8OzBPUGHv+dD/M6cyGjfeM8/+JzvHn1DQg/FHj5Q0uoVVY865Bg2PtXzuFw0NHRwYkTJ/Y0Uu50Ounq6uL06dM7PpGHQiG5KrIdObDZbNuaRYqiyOzs7JbkbLsgcqmlt1ds5WUl/c3r9cbUWUFYxD4xMbFley43N5dLly6Rl5e35aRZXFwc2dnZ9Pb27thqjY+Pp6qqiubmZs6cObOrSokgCBQXF0fZMeznQU+hUFBaWkpqaiq3bt0iOzub/Pz8qH0+NDRESkqKfIwCQZFVbxCnJ4jLE8LlCeJyB2G5npDHx9+1zRFa17Hm8fGDL32cjkvPUn3h3TzxS59h1qcgyz1JltkHtbWx90dJmFg5B71YThzOA5ggCCQlJZGYmCg/4La1tSEIAtnZ2aSnpx+pyvrdYHFxcc9T2ttBEARMJpOs1YxMCBkZGYlKCLFYLCQmJu6+yvqOd8BXvgIf+AA8/XTYrX2b74fH49lKuP7SXWzigeBInD13BOwXSkpKohzYXS7XgX2G3++XXc3tdjuATKSKior2ncG0H1gsFrq7uw81W++gsTFeJjs7W46XEUWRycnJmGG39wsOh4O+vj60Wi3Hjx/ft9fWRgh+P0k3ruMpKcbcmIouIx7N8UzeVHmB7hvXeOV7lzjx1lq02rB4NNGwt6fy2dlZBgYGOHXq1J6eqCWrgZMnT+7qJjw4OLhjO0sURfr6+rZs40FYKJuQkLDljclut29JYvbTBoRw5SkQCGz5d6n6HWugwmKx0NnZuWVrXqlUUlhYyNDQEBUVFVt+Rn5+PtevX9+Vw7XVaqWgoIDW1lZOnTq16xtPVlYWWq1Wbifu9xxOTEzk3Llz9Pb2cu3adcxZlaz6lNiW3UzMBDEkJPPiyDwuTwi3b7NHmEIAo1KDoFvHr16ieGqRv/zf/42OvjZ+6Y1v5Xff/Q7M5n5MGaloM/NZVhTS0dGByWSitLQ06hjrUlWo45W4Bg6PWEmQwsFzc3PJzc1lbW2NycnJQ43RuZdwu91oNJp7ShIFQcBoNGI0GuUhC4lojY+Pc/v2bTQajTx1aDabtz/fn3kGnE746Efhgx+Er34VYjzoud3uIytchyNCrFZWVq5cunRp5f3vf3+i9DuFQoFOp9v3xVZKDbfb7TgcDvkpxWq1UlJScl976kqlUiaOBxXNclhYWVlhYmJCnmyMFS8jCIJcCbjfbr9Op1MOv66qqjr4/X3xIorVVTxVVcwuLqJcXmZpaYmGhgZeeu4v+b9X/54zy3+Lyhq2E4k37p5YjY6OMjMzw5kzZ/ZE/P1+P83NzVFxO9thaWkJm822o4B3bm6OuLi4bW/oExMT206x2e32LUXtd9OOEQRhy6qUZEgai1gJgkBGRgYzMzNbustnZWVx6dIlCgoKtiSpgiBQW1vLjRs3dpVfmZWVhdfrpb29nePHj+/65p2cnMzx48dpaWmhpqZm3/lvSqWSqqoqekfn+cYV6QFWxKRNAF8Is1FFthkMQTcG9zI65yK6xWk0C1Po/G4E4JU3xjOQn0m91siH3v0EH0n+EL/40Y8ibDgGyYSPwfz8PM3NzbJXnVarRRAE4kq0LHd6EIMigvLwSMz4+HhUS9toNFJWVkZpaemhxejcS8zNzd0X01PJ6kL6Pnk8Hux2O5OTk3R2dqJWq6OI1qYK+Uc+Ai4XfPzjYa3VF78IG74fWxkMt7S03HfhOhwRYgVcf/nllzcJ2CXh6W6Euj6fL4pIKRQKLBYLKSkplJWVHbnSrpSt9yAQq1jxMpWVlds+eWRlZXHlypU9Ta4dJNbW1ujr68Pn8+1ohnlX+M53CGk0BB55hInJSbKysmSnco8ibPxr8oIohC9wu6lYSaG3UmbgXsbkQ6EQLS0tFBcX72r6LBgM0tHRwcmTJ7c9nqIoMjAwQMM2ERSBQACn07nlvpYsE7YiT/t9iIKw95TX6425bKkqVVRUFPO92dnZtLW1bUmsFAoFJSUlDAwMbEkKIdx2LCoqorOzc1dmk4WFhXR1ddHX17entrkUmNzc3CzbHOwXBVnJCMySZVyiSDvDcYOe0MIC/oEZAouLIIbHYxUGA+r0dNSn69BkZKBOT8d8+yWGXm6h4/Wv42OP/89tP0cQBNLS0khNTWV6eppr166RlpZGYWEh8cU6HK1u1ibWMeUfToXb7XYTDAZjPngcVozOvcbc3Ny21eXDgl6vl41bISwdsdvtTE9P09XVhVqtlluHZrM5fK/+gz8IV67+9E/DUTh/8RdR5GpxcXGTvmp5eRm3270simJsXcAh4kiwDVEUVzMyMpaWl5eTI1sRFouF8fHxmMRKOjiLi4ssLS2hUqmwWCykpaVRXl5+5IjURqSmpnLjxo1tx7TvJ+42XkatVmM2m+Xg5MOCx+NhYGAAp9NJaWmpPPp9TxAMIj73HN7CQhbuGDP29vbKAmyPECZWBq+CQCgRgXXi9NuTpFAoRFtbG1qtdldRKJEQRZG2tjbS0tJ2HWnS09NDbm7ujm2lqampqOyxWJient7kZRSJlZWVbTVibrd737EkUhhzLGJlMBjweDxbtt4lz7m1tbUtBy3S09MZGhra9jUAmZmZzM7OMjs7uyPhEQSBqqoqWltbGRsb29FfLBJ6vT7K62o7B/jtoFUrSI5XsObTUqyDtZ/+FAwGtJnZ6MqrUKeloc5IR5lwZ/pLCK/3Cy+8wHuf/kUMKSbKzlXxdjEU03U91jZnZWWRkZHBxMQETU1NZKZmISgMOAe8h0asxsbGduUPdi9jdO4l/H4/gUDgSHgEboROpyMzM1M255WKIrOzs/T09KBUKsPdpd/8TazLyyg++1lISIA7ma0QW6t5+fJlgsHgjw91Y7bAkWEfoVDoJ5cvXy558skn5d9J8QzwWjnRbreztLQklxMzMzOpqqq6b47d+4VGo0GhUMR0jr2fOMh4mfz8fHp7ew+FWK2vrzM4OMji4iIlJSVUV1ff80qZ5/p19AsLeC5cIM3jIdlqxZ2bS29vL8eOHWNVCD84JQQTWfKqMOkDqLZpdfj9fjkAeCvvpO3Q09ODTqfblcM3hIXoq6urOwquQ6GQPFm4HXaKBYnlXxUJt9u97+qLRKxiQZpsWllZ2VJDJnlabRUiLggCZWVl9Pf3b7uNgiBQU1PDlStXSEpK2vFBRBAETpw4IRuI7qV1o1arOX36NG1tbXg8nm19xbZCKBRCE1xiOZiApagYR1MTttTzCIN5MCi9au3OTxjfvvU1/uyH/52i1DI+97b/S/I/p9EpzNwhXgICgHDnhzuFBmm1BOG1woOgJYUyvMEgIVHE3usk7Q1x97waJHlb7TUwfqsYHalVeJg63Z2wsLDwwAxHabXaKLNgScazYLPR+653UTY8TOof/RErZjOGX/kV/H4/Op1u03nygx/8YHlhYeH792MbNuKuiZUgCDrgEqC9s7xvi6L4KUEQaoEvAjogAHxEFMUtRWXz8/Pff+GFF5558sknEyF8kbXb7fh8Pl5++WV0Oh0Wi4WsrKwHkkjFQmpqKvPz8/tyVj5I3Kt4mfj4eAKBwI5P+XcDv9/PyMgIs7OzFBYWUlFRcc8JlSiKTExMMDM5yRkgrrQU28wMq9evk9fYyPXr11lYWMBFmFjFKTMYcwdJ2KYN6PF4aGlpobCwMGbMyk4YGRnB4/FQt8ucQr/fL08M7rS/NkabxMLq6ioKhWLbJ2S73b4tibubVqBer9922EXSWW1FrNLT07l8+fK2RpzJyckMDg7idDq3beFrNBoqKipob2+noaFhx/0r+VVJBqJ7yQhUKpXU1dXR3d3NrVu3OH78+J6ISV9fH9lWLVPjsGwM23hY1QbsgDdnidSsZPS68DEJhUT+9Ev/g8//4G94vOENfPG//18ExTptvgniBR3HTEVhY13JXFcU5f9GlLuKd14jhv905/WhUIhVzTKXLl2isLCQrKyse/Y9np6eJiMjY98EbqsYHb1eT05ODikpKfe9VTg3N7evh7OjAI1GQ3p6uvyQFRBF+PGPWZubo+PaNXw+Hzqdjrm5OSwWi6xnfOmll/zA1e2WLQjCl4EngAVRFKsifv8bwMcIc5UfiKL4+3ezDQdRsfIBj4uiuCoIghpoEgThBeB/Av9DFMUXBEF4M/AXwKPbLOfqiy++KN66dYuVlRV0Oh1Wq5W0tDTZrfthQ1paGt3d3fdl2w4rXiY/P5/R0dEdqyJ7RTAYZGxsjImJCfLy8rhw4cKhXMy8Xi8dHR3odDrqn3oKUlNRT0yge9ObcL38Mvryck6cOMG1a9c4/dtP8HHDf0cnrrHiDpBujv1E63Q6uXnzJseOHduX58zMzAyzs7O7IkkSbt++TUlJyY7HW9rPO3lbTU5ObqlRAuSx7O3E6XeTtGAwGLbNF5Umcbe62ahUKpKSklhcXNzSJ0yqWvX19W2rNYPwQ9Pc3NyOYn4JGo2GhoYGbty4QX19/Z4m/qSW4vDwMNevX6e+vn5X+3F6ehqXy0V9VTHXxheYdglkW6343fNACoXns+lf7MJsNlNWVoYgCAS+5eFXf/VX+fznP49KpUIUQ/y0//t0maycS6/CqLybVp4Fny+LwcFB2Ttsq1ik/UIURcbGxnY8frtFrBgdqUq/XYzOvUQoFMLpdB7ZNuVeofq7vwOLhYyPf5wMo5GbN2/KVhmDg4OEQqGw9MLjcYqiuLbD4r4CfB74qvQLQRAeA94GVIui6BME4a5LfXd9JxLDkIL91Hd+pOcW6bEuAZjZYTmrbrd7OSkpiUceeYQzZ85QXFxMTk4ODofjblfzSMJkMuHxeAgGg4f2mW63m/7+fi5evCiHzD7yyCO7usnuB2lpaSwuLrK+vn4gy5PiZy5dukQoFOL8+fPk5+cfCqmanZ3l2rVr5OXlUVNTg0qthtOnEW7cIPGJJ0ChYPn559FoNFTWHmNVsY6gF1EH41nZomJlt9u5efMmdXV1+yJV0sWloaFh1xXGmZkZRFHcVWVsZGSE7OzsbW/UkuHqdm0sqcqz1U1SvFPO2O9NdDsvKwhPfLndbvlzYiE7O5uJiYltP0cKkd7K6T0SlZWVjI6Obtmi3AiDwcCJEydobW3F5/Pt6j2RKCwsJDc3l2vXrm27LyCsURkaGuLEiRNY4lQYtAomF9dRZ2YiOsYBUHrVsnluU1MTLpeLz3/+83zhC1+QNayCoKBKnYooCLSv3X1Ul1arpaqqioaGBubn52lqasJms931ciXYbDZMJtM9kV8kJiZSXV3NhQsXMJvNdHd309TUxNjYGH7/ptmsewbJbf1BtYmIQk8PfO978Bu/AXe6Hk6nk/z8fCoqKjh//jxnz55leHgYURR31FeJongJ2Egofh34c1EUfXdes3C3q30gdyNBEJSCILQDC8BPRVG8Afw28JeCIEwCnwX+207LCQQCP+js7NzkwL68vHwQq3kkkZycfKAXjlgIBoNMTU1x9epV2tra0Ov1nD9/nuPHj2OxWO7pF1ChUJCXl8fo6OhdLUcURaanp7l06RJut5tz585RXFx8KEMKfr+fW7duMTU1xdmzZ0mNDAo9dQoGBlAGAiS88Y34Rkdxt7WxboC+H7Xw2Rf+B/gMBIJsIlYzMzN0d3dz+vTpfU2HulwuOjo6aGho2HWlx+v10t/fv+10mwS/38/U1NSOwmibzUZSUtK2xG4nfdXdag01Gs225F0QBOLi4nA6nVu+xmw243K5drwJlpeXyxYe20GlUlFdXU1bW9u2hC4SCQkJVFRU0NzcvK0311bIzMyksrKS69evb7mtXq/3/2fvveMby8vr//dVseXee++99zKzS11aIBBIgCSEpSQhbBJIgIQESAIB8mPhC0sJCb1tqIHQNgvswozHvdvj3nsvsi1bXZ/fHxpp7bE9lizJ9mw4r5deOytLV1fS1b3n8zznOYeenh7Ky8tRKpVWY8xwL+Y3DHjFxiIdrABg2DYhSRKRkZE8/PDDfPrTnz7xd5wbXoavbo/OvRGn9/c0+Pj4UFxcTElJCXNzczQ3NztEZs/C+Pi4xy1gbDE61dXVlJWVYTQaaWpqoquri/X1dYePhfPismwWPIKPfxx8fKy+VlgLAz4+Pkc4gkKhoLm5Wb20tPQ/53yVTOCaJEltkiTdlCTpeCCpk3ALsRJCmIUQxUA8UClJUj5WFvhOIUQC8E7gy2dt547OSn1kB+/4WTm66rvfEBsbe2ochysQQtgduxsaGtjb26OoqIi6ujoSExMvdGoyISGBpaWlc10obNWQW7dusbW1RXV1NTk5ORfmQ7axsWHPgisvLz8uUK2utv63vR3fsjK8kpLYefJJVvZWWegc58dtP2BvyxpbFXTIw2pycpKZmRlqamrOVSnU6XT2Spejz7cFLOfl5TkktJ2cnCQlJeXMStjc3Nw924Bwuu+MDa7oq+CZSte9Llo2ndW9thEXF3fm7zEoKAgvLy+HFkShoaGEhIQwOTl55mNtiIyMJCkpia6uLiyW4wadZyEsLMwenbOxsXHkb2azmc7OTvLz84/oHhPCvdjYM2GMjEPCjFxlwaC2VtI7OzuZmpqitLQUg8FAc3PzkfNxaGAqUdpdNjGwbHBvd8Hf35+ysjLy8vIYGxujra3tnuT4Xtja2kKpVF5oe84Wo/PAAw+QkpLC4uIiN27cYGRkxCPXNCGEyzE2VwaLi/Ctb8Gb3wx33s9pCzRH9FX3gAIIAaqBdwPfk1ysNri1fyKEUAM3gBcBfwL88M6fvg840tRufuqpp070s7rXCfF+RnBwMHt7e+ciHSdBp9MxPj7OzZs3mZ6eJiYmhgcffJCcnJxLy+yTy+UkJCQwOzvr1PNspGZ5eZny8nIKCgoubILSbDYzMDBgdz0/VUxbXm4de2prQ5LJCH7FKxAmEwvjfQizGZlMhuVOHGiQrxwhBAMDA6jVaoeiZk6CzQDUWcPT2dlZfH19HZoW0uv1rKysnEmYDAYD+/v7Zzq2nzXA4I6sNm9v73u20MLCwo4Rjbthmw48C7YJQUeqD9nZ2SwtLTlFCGyu3/39/eeqcAQGBlJdXc3Q0JCdKAoh6OvrIzY29piOLCHcSrRXFSEgSSi8dBi2reektrY2AGpqasjNzSU7O5v29nZ7wLokySj0SUKyWOjUeCaGLCgoiKqqKjIyMrh9+zZdXV3s758lpzmK8fHxS7O3sRlUFxcXc+3aNfz8/Ojp6aGpqYn5+Xm3nf83NjZONt28H/HYY2A2w9/8jf2ukxZo29vbHBwcbDmgrzoNC8AP78ia2gEL4BIzdZlYSZIUIUlS8J1/+wDPB0awaqoeuPOw53JoePc0CCE0Go1m6+6Sr80o9NkISZKIiYlheXn53NuwWCwsLS3R2tpqN7Krq6ujrKyMyMjIK9FrT0pKYm5uzqEVuFqtpqWlhenpaYqKiigpKbnQgFS1Wk1jYyO+vr5nV5QCAiA/H1pbAVCGhxP44IOsiT3kJgNymRyFxUqezLodurq6kMlklJaWnksXZrFY6OzsJDU11alV6f7+PjMzM/eMZTmM8fFx0tPTz9zHxcVF4uLi7nmM7e3tERAQcM/HuINY3ctyAazVj/39/XsSFZVKhVKpPDNOy5aXdi/BvA22oObe3l6nKlAZGRlIknTuzFQfHx9qamqYnZ1lcnKSqakpZDLZia3duFAlMgkWdgSKyEhkll0M29aKlc1vzzatGBYWRn19PVtbW7S3t6PX60mJKCN4f4N+7SxG4TnNaGhoKLW1tSQkJNDd3U1fXx86ne7M5+3u7mKxWO65ALgoKBQKewRYcXEx+/v73Lp1i97eXra2tlxqFS4sLDhkqH3lsbNjdVz//d+HQ8frSf5VDQ0NmEwmV/yr/gcrR0GSpEzAC3CJcLijYhUD/EaSpH6gA6vG6mfAW4FPSJLUB3wE+FNHNnbHz+rIfc92nVVcXBwLCwtOP29nZ4fbt29z8+ZNtre37WK+5OTkS43sOQlKpZLo6Oh7VgP29vbo6OiwO1FXVFRcaNneYrEwOjpqd85OTU11jJRWVUFbm32e3L+ujq0IH2QmIzKZDEkvUEjQ29VGYGDguS0hbK28iIgIu4uxo8/r6emxCu4daAHbPOMcEbfPz8+feSI/S19le01XhyfOErDbAmTPIk22OKazkJWV5XDVKjAwkNjYWEZGHNchSZJEQUGBfdrsPLB5Xa2srDAxMUFBQcGJx56XQkZUsNKqs4qLQ9KtY9g1YzFZaG1tpaqq6sjjFQoFxcXFJCUl0dzcjE6jIla3jx4Lo1r3SxsOw6b7qq+vJyIigtbWVgYHB++psbMtFK4abDE6Dz74IHFxcUxPT3Pz5k3Gx8fPHEC4G2azGbVa7bmUiYvEf/6nNdbm3e+233WSvgrgiSeecNi/SpKkbwMtQJYkSQuSJL0Z+AqQKknSAPAd4E+Ei0I4d0wF9gshSoQQhUKIfCHEB+/c3yiEKBNCFAkhqoQQXY5s7zSdla+vLxqN5pRn3d/w9/fHZDI5tPIyGAxMTU3R0NDA6OgoERERPPDAA+Tl5V35eJzU1FSmp6ePXYgODg7o6emhr6+P1NRUqqurL3xlqdFoaG62tujr6uqcI3TV1bC9DePWoqxBsrDvo0ApzHjLlUgCvIWRzMxMVlZWzj0hNDIyglKpdNqfZmJiwh4X4QhGR0fv6edkw+7uLt7e3meaYN4reNmGi6hYgbXacpasIDo6mrW1tTOrSz4+PoSFhTmskUxLS2N7e9upKWeZTEZZWRmzs7OsrZ1vWGlvbw+DwUBMTAzd3d2nTiEnhHuxuGlAHhOLzLQJFthbP+DlL385h42bDyM6Opra2loWFxcJ04bgZdLTtX9mc8ItsOU8PvDAAwQEBNDU1MTo6Oixttr+/j4HBwdXWndki9EpKyuzZ012dXXR2trK0tKSQ5Pjq6urREVFXYkOhUvQ6+FTn4LnPx8OmfGura2daIVyJw6vxZFNCyFeJ4SIEUIohRDxQogvCyEMQog/usNfSoUQv3b1LVzFwKPmX/7yl8euPLZsvWcr7iWaFUKwurpKR0cHLS0tCCGoqqqisrLyvsmtAqsGJiIiwl610ul03L59m87OTmJjY6mrq3Mo386dEEIwPT1NZ2cneXl5ZGVlOf952lbzd7QoGyarlubNf/USWv76kwAEaJT0roeRnJpOW1ub0+RqZmbG7pLuzIlzZ2eHlZUVsrKyHHq8RqNBo9EcnXw8BY6I1oUQaDSaM4mqXq93OC7pNNiia+4FR/SaMpmM8PBwh4hMRkYGExMTDrX4JEmipKSE/v5+pzQ1CoWCyspKhoaGnK7c7+7u0t3dTUVFBYWFhYSHh9Pa2npidSch3AuDSbATHIcMa1VPdqDgC1/4Aq95zWtOfQ0vLy+S0vxBvkPo7iqT+jV2zBc3bGQLfb9+/TpKpZJbt24xOTlpJyOjo6NkZmbeN4TDFqNTX19PXl4e29vbNDQ0cPv2bXZ2dk593vydrNL7Ho8/DsvL8J6jHp0nTTtubGywv7+/4YK+yiO4cldkIcS+TqdbuFvobHMpf7YiLi6OpaWjVl8ajYahoSFu3LjB6uoqGRkZXL9+nbS0NJcvQpcF24VocHCQ1tZWQkNDuXbt2qWstLRaLa2trWg0Gq5du+aU4/UR5ORYtVZ3dFZrRuvJL9w7DL1ykfnNHmpWBLOTOp4YVBAZm+LUOP3KygqLi4uUlpY69RmZzWZ6e3spLi52mCyOjIzYzSDvBYvFwvr6+pkETKPR4Ofnd8/tuephZYOPj8+ZFauAgAD29vbObN852g709vYmOjra4Vadr68vKSkpDA4OOvT4w69TUVFBT0+Pw9NkGo2Grq4uysvL7YajKSkppKam0tLScmw7NgH7EgHIZdbr1NL0yqmk0WjSMbV0k6c7P0jzwGfYYw9jUBJI0DXef6H+fGAdkklNTeXatWuYzWYaGhoYGRlBq9XeN/Eud8MWo/PAAw8QERHB6OgoDQ0NTE5OHhnUMBgM6HS6K9+1OBMWizVwuaTEWrG6A1tH5+4BmJ/97GdmnU73/YvezbNw5YgVwM7Ozjd+/OMfH1nSq1QqLBaL24wmrxq8vb1RKpVsb28zOztLY2MjAwMDBAUFcf36dQoLCwkODr5vVl0nwWQyMTMzg8Fg4ODggOvXr58pfPYUFhcXaW1tJT09nYKCAtemaORyqKiwV6yW9WtIwoJQCz41PcYffuX36Rq/wUNrgu1tIz/ul+ETmkhHR8eZF5/t7W1GRkaoqKhweh9HRkaIj493uK25s7OD0Wh0qGWyurpKRETEmYTtLJsFsF4U3JGzplKpzmynS5KEn5/fmRNlQUFB6HQ6h4w609LSmJ6edphIJCYmotPpnF4o+vn5UVxcTHt7+5nnwf39fTo6OigtLT32/cfExFBQUEBbW9uRCkiInxw/bxkLWya8o/wBC3/016/loYceOvL8vYMV+ia+yy/a/oH+ie+iVPgQlvFqRuJL2VPIeXVwDUnKCBobG+9ZYfEUFAoFmZmZ1NXVsbCwgFartZvi3q+wxehUVlba9W5tbW20t7fbF17nicK6cvjpT2F01FqtOnRdWF9fP5EcP/7441vb29vfvchddARXkljt7+//6PHHH1ffff+ztWolhGBjYwOj0UhbWxt6vZ6ysjKqq6uJi4u770dnLRYLU1NT3Lp1C7lcznOf+1w0Gs2Fr2jBehHv7OxkZWXFLn51C6qroa8PcXDAyu4mkhBsqmZ49cOVxCUn8hf/9UZ+1vQDXrFjQQb8/LYcvVfcPStXGo3GnjfnLPHY3NxkZ2fH4UBmgOHhYYeDaR1pA4K1VH8WsXKHcB0c87ICx2wXAOLj4x0aKlEqlSQkJDhsgitJEsXFxQwNDTm9ULTFy7S3t5/6+7GRqpKSklNjTUJDQ+0VMJsf12GjUO/4WMwWNbfH+ygoKEAIC8sbfTT1f5qnOz/I7HITMWFF1Be9i4OU5/MryyrBCj/eFvkiCv2SSUtLo7S0lP7+fsbGxi6F1Ozt7REYGGifYLx16xarq6v3NcGCZ2J0rl+/TlZWFuvr6wwODrK/v3/mYMaVx8c+BsnJ8OpXH7n7pDagXq/n9u3bRuBst94LxpUkVkKI2bm5uf27fV+ebTqru+NlsrKy8Pb2JiMjwyPxMhcNW1hxQ0MDRqOR+vp60tLS8PLyIiUlhYkJ1yMwnMHa2hpNTU32XES3Tk5WVYHJxOT3v0/abhiBCn/GYguZ91vlg59+MeWVhbzvx+/ks99+jN/VG4gOUfLrMTlrlnja2o6TK71eT2dnJ6WlpU6Luo1GI7dv36a4uNjhauDm5iYymcyhdqhOp8NgMJzZdhBC2K0W7gV3CNdtUCqVZ+rXHPXFsxErRy7EKSkpzM/PO6yd8/b2Jjs7m76+Pqcv9NHR0SQkJNDV1XXsuXt7e7S3t1NcXHzmAIi/vz/V1dWMjIzYCWRCuBdbGjPGyDgmV7vRG3Ukpqn4ZfsHaBv6TzQHK+Qkv5yHqj5MSvqr+IF+nJb9Uar8MnlrxAsIUzzzXQcEBFBXV4fFYqGpqelCh4+EEAwPD5OTk4NKpaKgoIDy8nKWlpZobm5+1vgiBgUFkZqaSkhICBEREQwODnLr1q0Lj9FxC5qaoLkZ/vZv4dD0shACtVp97Nx048YNZDLZL1yd4PMEriSxAjCbzT/8xS9+ceQDCwgIQKPRnMuN+KrAbDYzPz9/YrxMZGQkISEhHo+48TSEECwtLdkd32tra8nKyjpCZBITE1ldXXVoEtJVmEwm+vv7mZqaoqamhtjYWLe/hrm8HCFJxD36KNe39fx55ItJ8o5iNiqT7eRs3vGhCh56aSmPt3+BqdYNfkd2QGGSD11zMia1iTS1PCNoN5lMtLe3k5ube64g1YGBAdLS0hwmK0IIu7bKESwsLDgkkt3f38fX1/dMcueuihWcbbkAVuuD3d3dMwmNl5cXvr6+DrWz5HI5KSkpTjmsx8TEoFAozmW1kpSURGBgILdv37a/j93dXTo7OykrK3N4qlalUlFTU8PCwgLj4+MkhFl/o9NKLzq32gHwDZ/DTxVOZe5beUHVh8hKfBHjpm0+v/YLtkx7vDa0npcGl6GQjlfWZTIZ2dnZ5OXl0dnZyczMzIVUjFZXV/Hz8ztC6n19fSkpKaGwsJCpqSlaW1ufFTY+s7OzJCUl2WN0ysvLLzxGxy342McgLAwefvjI3dvb2yfKYL797W9vLy8vf/Mid9FRXFlitb6+/p3HH3/8yLJCkiSHy/hXCbZ4md7eXhoaGtjf3z81XiY5Odlph/KrAiEEa2tr9uDUysrKU+NTZDIZmZmZjI6OenSftra2aGxsJDAwkKqqKo84txsMBlqmptj41Kfw2d5GevBBfH/nlbxhMZQqvwzmfQPZzn4Rb/vHF/CxL7+SsGjByg1BjWmF5xUGMrEuMbCTzM2mDntUTVJS0rkEtzY7B2emg9bX1/Hx8XFI+GrLbHREz+GIvgrcW7FyxHJBkiSHHgeOi9htj11ZWXEqQDk/P5/JyUmnPYvA6qNlNpuZnJxErVbbherOCphtU4cajYaF2V8iYaFjcYjelX5C/cJ5zQv/jfqidxAbXoIZwU/VHXxvu4kIRSBvi3wRuT5nG1KGhIRQX1/P7u4ubW1tHl1Q2fzoTlsoBAQEUFFRQXZ2NsPDw3R0dNy3LTSLxcLq6ioxMTH2+y46RsctGB62hi0/8og9bNmGlZWVY0MyQgh+9atfmYDGC9xLh3FxgXHOo6utrc1sMpmOEA9bO/B+mPLQ6XTMz8+zuLhIQEAAiYmJFBUV3XMFHxwcjFardTmU9qKxtbXF8PAwKpWK0tJSh+JzYmJimJ6eZmdn51yVmXvBdnLd3NykoqLCY3E+Nj1LTk4OEfX18Na3wmc/Cx/9KPKSUl76+teT8N4386OQdbQptZRHalkM/x5PfszAL7/wBD95/Mv8QX05P2zZptuQhPqpFjITwxzSL90NvV7P8PAwtbW1DrcAbdWq8vJyhx6vVqvx8/NzSPO1sbHhkOeWO4mVI5OB8IzO6qzjIjIykqGhIcxm85laR5lMRlpaGuPj4+Tn5zu0v0qlkvz8fLq7u6isqkCpcHzaV5IkioqK7PFVtbW15z7OLcKAxaefjb02fJTxICvhjaUv5nrEq/ExWi9q68ZdvrfVxKpJTb1/Ds8LLEQuOb42t4VSr62t0dLSQmZmpkcE1zMzM0RGRp5ZBQ0ODqampoaNjQ36+vrw8/MjKyvrQlMeXIXtWnjSsWmL0QkNDcVkMrG8vExvby9CCBITE+0V0yuBu8KWD2N9ff1YFFFfXx8ymaxXCHEl+51XtmIlhLDI5fJbLS1Hfb9s+oirWtq8V7xMRESEQxc8W/zL/YCdnR3a2toYHx+noKCAsrIyh0/ukiSRn59/pJ3hDuzu7tLY2IhCoaCurs5jpEqtVtPe3k5RUdEzKyofH6tb8NQUvPe98KMfUVjyEO/811+iWF3npo+c+Io/JvMhBSs7K1x/1atYbP02b35+OGaLhdGDNNY21E5HHNly4HJycpyy4lheXiY4ONjhi4mjonUhBLu7uw4RZncuIhzxsgLHdVaSJBEVFeWwtjM+Pp7NzU2nKlDh4eFo5R080fwuWgc+z9xKKwbj2eRQCMHo6CgqlQovL69zVyPUmnludP8bMyu9GKSHMZgj2d1X8mBtNS8rfDX6LSO9B9P85/ov2LNo+aOwB3hhULFTpOowIiMjqaurY2Vlha6uLrdOeut0Oubm5sjIyHD4OeHh4dTV1RETE0NHRwe3b992qup4mZiZmSEpKenMx9lidGpraykpKXFrjI7LWFyEb34T3vQmuGuYaH9/Hy8vr2ME8Ac/+MH+8vLyVy9yN53BlSVWAIuLi1//3ve+d0TBLpPJ8Pf3P3fCuafgzngZm1noVSWP8IxHzuDgIJmZmVRVVZ3LQyUoKIigoCCHgm/PghCCyclJe3yLLWvNE1hbW7NP7J0o+A4Oho98BCYm4C1vIfCLX+fttX/FQx//b/53uZ2SP30T3/n3L6GQvPjdP3473/rSX1ASsYTBImffL4+ZmRmH41LAag7o5eV1bHLmXrBYLIyNjTkcTGs2m9na2nJoktIWP+HI5y+EcJvJraMtvqCgIIetABITEx0+PiVJOleL21sFZrOKmTUL7SPf439b30Pz7c8ys9yE3nC8TWUymejo6EAIQXV1NVVVVQwODjp1XhRCMLn4a250/z/mt7IY2/wbBhZiifHT0vStv+Hng00AtM+N8sPtVmKUIfxF5IvIVLmuUfTy8qKsrIzo6GiamprO7Sp/N4aGhsjKynK6EiNJEtHR0Vy/fp2QkBBaWloYHh6+0gJw2zCAzaPMUfj6+rotRsctsIUt/+3fHvvTSdOAAN///vcPzGbz/17E7p0HV6QOeCqe/ulPf6r/zGc+c+ROWzvQ3e0jZ2EwGFhYWGBhYQGVSkViYiJ5eXkuXyQUCgXh4eGsrKwc6Z1fBWi1WsbGxtjd3SU7O9stdgXZ2dk0NjYSExNz7km9g4MDent7CQoKor6+3qMWFXNzc8zNzVFTU3N2dSg2Fj7/efibv0H6wAco/+R3KPjaE/zmkd9B/+dv5seyn/En730D7/vHr/PNb6koT/pHOqd0vOl5JeytTdDV1UVxcfE9LxQHBwdMTU1RV1fn1PuYn58nMjLS4WrR8vIy0dHRDpElR/VVJpPJrd+VI+J1sF5IbW3Ds6p1tsgpR0X20dHRTE5OotFonLjoCfZMDzK5XszOyjQ7a72UVMYRtNSBv/cPiQ5NJDa8mNiwYswmBZ2dnaSlpdm1dCqVirKyMjo7O6murj5zP/VGDd0j32RoUbCmeRtaox8pkV6IlVv841vfzubmJkWxkVREwvaejgcD8nkgIO/cVarTEBcXR1hYGL29vaysrJCbm3vu9tTm5iYGg8GpxcXdkCSJ+Ph4YmNjmZ+fp7Gxkfj4eFJSUq5O2+wOpqenTwzUdhS2GJ2IiAiMRiOLi4t0dXWhUChITEwkKirK81Y/p4Qt27C6ukpJScmR+xYXF9FoNMtCCLVnd+78uNIVKyGE1mQyjd+d7n6ZflYXFS+TkpLisC/ORUCv1zMwMEB7e/uRAFR3QKlUkp6ezvCw83YkNkuH9vZ2srKyyMvL89jJwNZ6WV5eprq62jn3+4wM+Pa3oasLr8oaXvShx3le+avRbH6dz73zP/h/r/4yCeuvQLH+GXzQ8dMONTm5eURERNDc3HwqWbAFLBcUFDhFSs1mM1NTU04F0zoSuGyDI8HL4F59FVgr2o5W+ZwZhElISHCqapWVleVU4LLAjFn4UrxqwfCTH/H1/+8vefdrX89H//FJvvndeH7ZXcLPO7f59o2v84u2xwiN1RAafvRzCwgIoKioiPb29ntWWta2x/jvW49zY7Sa2e1XEOwfzCtLFTR86z28+Y9+j7AAfx792D/zspT3YFSa8PPTk6eNdDupskGlUtkr3o2NjWxvbzu9DYvFwsDAgNORT6dBJpORlJTE9evXkclk3Lp1i+np6SszkW4ymdjY2HCJRB7GaTE6/f39np2cPCFs2QaDwYDJZDq2SPjJT35i2tvb+5bndsp1XC0KfgI2Nja+/qMf/aj07/7u7+zLai8vL7y8vJxcEboGjUbD3Nwcq6urhIWFkZGRQVBQkMdaTf7+/kiS5JAPkCdhNBqZnJxkZWWFtLQ08vLyPPKe4+PjmZubc0rIrtfr6evrs+vY3OpLdRcsFgv9/f1IkkRlZeX5P4PSUqQnn4Tf/AbFu9/Jc9/1GHsRXyP5ea9BO/5mWtqj+FLT83npO77LjV/v8NznZhAQEEBraytFRUXHkuunpqYIDg52OmNxdnaWuLg4h41HtVotFovF4d+bo9+jVqt1u1hYLpdz99DLSQgLC2N2dtYhzVhsbCxNTU0Ot5cjIiIYHx93+HMQQjA2MMJ3H30b//K7j1KQWsatgV/x69En+UnXL/jl1/x41xd7WZdXYDRoGdncI2D4FlFBWrLjI0mLLcTPJ5zQ0FAyMjJob2+nurr6yCLDIsw03r5Jy7gv+4aXEewreFlFCHmJPvzH5z/PN7/5Td78yhdT9vaHKW+tQCaXSH9zJAVh0XR0WCdWHdHznAeSJJGcnEx4eDi9vb2Eh4eTmZnp8ELVJlh39/VALpeTlpZGYmIiU1NTNDQ02CuFl5mCYcsF9MQ+2GJ0cnJyWF9fZ3x8nIODA+Lj44mPj3dfnNopYcs2LC0tnWiN861vfWt7b2/vv92zE57BlSdWer3+x9/4xjf+9TCxgmfM+xz13jkPjEYjS0tLzM/P28V/WVlZF+aEbqtaFRYWXsjrHYbZbGZ6epr5+XmSk5PtKzdP4bCQva6u7swTxsrKit0A0F2rttNgMpno7Oy0X7TccTIz1NXR8egnyd9YQXz1P0n+3leQxJfxiSukaWWFr//DQ+y+4z9InGgh4QXXqK6upqOjg7i4OFJTU5Ekid3dXRYWFqivr3f6/czOznLt2jWHnzM3N+ewhcPBwQEqlcqh48WmxXInbO3AsxYkwcHB9PX1ObRNpVJJQEAA29vbx8jtacjJyWFkZMQeQXIvCGFhR73HzMooB0F6Ql8VwhvNf8XDt/+G9Y45Ztcnubau5cB3hrf/29sxKbxIL3sxGeUvYWApA5VigVD/flIifShMSSEmJoaenh7KysqQJImZ1Q1+0j7FhiYLb4Wel5T6kR0tY3xsEBGazSuiwtF85j34FV+n6pe5KALlZL0xCu8Q6yWiurqarq4udDqdRwON/f39qa2tZWJigqamJoqLi8/8HrVaLXNzc07/DpyBUqkkKyuLlJQUxsfHaWhoIDMz0+HWuDthq9LX1NR49HVkMhlRUVFERUWh1+tZWFigra3NLnuJjIx07ZpgC1v++tdP/PPCwgJlZWVH7lOr1UxNTe0LIabO/8Kex5UnVkKI1djY2LnJycmIw6Pb0dHRNDY2kpWV5dYD2xYvMzc3x97ent2l+zKc0KOiohgZGXFblpojsFgszM3NMT09TXx8PNeuXbswbUFQUBBhYWFMTk6e2qIyGo0MDg5iMBiora31eBi1Xq+nvb2d5ORkh9tgZ8FsNtPe3k52Tg7h0c+B17wO/cwka597lKivfZcfmnTMH5j4/Idfz6O/9+e8f3ESn8xMKp//fCa3tmhubqawsNAesOws0Z+amiIpKcnh71UIwfLyssMXLkf1VWAlVm6LFboDm4D9rAuyTCZDpVI5rJ2yTes6SqxCQkKQJImtra0zn2MRFrQHVvd9b19vKiOy2NfsE/GKSNoz1qjSPIBizIfIhSxenP4qfjX5U57+7qM8/d1HiY9P4vm//+ckV76WJbWSpjEzPkotoT4mFht62BNBjC17I5fCqEjd4aGybFqablH64ofZ297mvz/yHtqeE0dI6POo+EUWqkglaW8IR+n/zHFl87rq7++nr6+PwsJCjy20bB53UVFRdHd3k7qzQ7zJhFRaCklJRzLkbNOweXl5F3Ke8vLyIi8vz641nZiYcJvW1FGsr68TGBh4YdcEeCZGJy0tjZ2dHebm5hgeHiYyMpLExETnuyoWCzz6KBQXHwlbtuHg4ACZTHbsd/n973/fpNfrv3b+d3IxuPLECmBzc/MzX/3qVz/3r//6r/a5eYVC4fQK8l44ODhgfn6epaUlQkJCSElJsZ8YLwu28vj09DRZWVkefS2b8ePExARRUVHU19d7tLV2GrKysrh16xZRUVHHfqybm5vcvn2b1NRUEhISPP7daDQaOjs7yc3NdZtvmhCCrq4uEhISjlTavJPTSHj0PzD96yeZ+vaX8P+3r/CR0V4MP/h3hotLia5cZXN8nNiyMqJLS2lqaiI4ONjpSUyDwcDi4iLXr193+DlbW1sEBQU5fOHa2NhwuGXkTtd1GxwVsMMzOitHSHNYWBgDAwMOtRltyM7O5vbt22d7iwkLWq11xN9XpSI+Lp4bN26wvb3NC2vqUKlU1kSDaTVvKPpTHh5+Gxubqzw5+3OemvwZ/uZxXmT5X3ZNwXzyv39ASvlzOUh+Hou7AUgYSQwd5BXVxfgpY3jPu/6Gxx57jKSIcP7iAw/z1MuTKepPIb0lAf8UL5JfF4ZcdZw0SZJEYWEhExMTtLe3U15e7lEyYxtE0ZeWIvX3W+8MCbFejEtKoKSElehofO7EuVwkfHx8KCoqQqPRMDo6yvj4ONnZ2W65Fp2F8fHxS+li2BAUFERBQQFms5nV1VUGBwcxGo0kJCQQFxfn2HXjpz+FkRH4r/86QpRtWFhYONHj7POf//z29vb2lbVZsOG+IFYGg+G/v/Wtbz36oQ99yO/wySkhIYGFhYVzH8w207T5+XmEECQkJFxohcYRJCQk2Pv6ntgvmxh/dHSUsLAwxybdPAiZTEZRURF9fX32lqDZbGZkZAS1Wk1lZeWFGPhtbW3R19dHaWmp26ZPhRDcvn2bwMDAU4mHwtuH1Df+JZY/eYTb3/w5hn/9JEUjnSh6u9lLTUDf242hvYjElBRkvr40NzVRVFzssLZkYmKCtLQ0p6pcjnpX2bCzs+NwpIq7xetgrVg5mgUXHh7O3NycQ8RKkiRiYmJYXl52uHoZGBiIj48P6+vr9yTnAgu6O8TK38uLpqYm0tLSmJ2dtX9XkiQRlxpCXGoIFoOF1cEgIrui+JO5tyIQrO2q+d+N/+HpJ3+K4cc/JMjfj9r6Kspq83nw9Y8gNyspKS9ibGKC33uwhqJPvQlTqB8P9ZTh3+5HUK6KxN8LRaY8nQBKkkRGRgYqlYqWlhYqKys9er6Qy+X4pqZiXl1l8vWvJ3Z1Fb/xcaTPfQ70emKAaJUKCgvtZIuSEigosHrKeRj+/v6UlZWxu7trH77Jyck5l/WMI9ja2rK3pS8bcrmc2NhYYmNj7WbYTU1NdjPs8PDw0xcTtrDl17zm2J9skWh3TznPz8+zsrKyKoS48iaPV4dB3ANCCE18fHx3Z2fnQxUVFfb7w8PDGRwcxGKxOFyWFkKwvb3N3Nwc29vbxMTEUFRU5DETSVchl8tJSEhgdnbWIRdrZ7CxscHIyAj+/v5UVlZemeBnmxh7cnKSiIgIent7iY+Pd8pR3BWsrKwwOjpKVVWVWy/6k5OTmM1mh6qPMkmi4A0vY7SolM4faJDf+gJezZ+maGoe49NP4/Xgg+hLyggMCWF6dBS/oiJS7uhpToNOp2Ntbc0pXaLJZGJnZ8fhxYtWq8XLy8vh36PFYnG7ZtGZilVwcDD9tmqIA0hISKCnp8eptnBWVhZdXV33NAi2CAv+IdGUp9bhI1dQXV2Kj48PKpWK/v7+Y1oTmZeMmJIgYkqC0G+b2OjWIPXCG/UP83vveTU/1fyE34w9yc2GVv73yV9T5xNJcVoudVGRvOrPX4bytZUES4E8v6UUQ5+FsHJf4l4WjCRz7PeVkJBgJ1fl5eWeHSLKzET+xBOkfOQjDAwPYzKZKMjJYfTHPyZFrSZwchJ6euA737FOmQHI5ZCdfZRsFRdbK14egC0ya2tri4GBAXvItruvK+Pj4x7vXpwHKpWKjIwM0tPT7dfXgYEBYmJiSEhIOPo52MKWP/OZI2HLNuzs7ODn53es8vXNb35Tu7Oz8zlPvxd34L4gVgCLi4uf/uIXv1hVUVERbLtPJpMRHh7O2tramQLm88TLXBUkJSXR2NhISkqKW3QNarWa4eFhlEolxU5UOy4SmZmZPPXUU8zPz1NWVuaxFeDdmJmZYXFxkZqaGrdqGBYWFlhfX6eqqsqpYy6rKJaf7y2zuP8SPtT/A+J3F/hURBBVTzzJ3vw0xt//Q0J3d2F2lplf/5rAkhKCSktRnDAlaDMDdeYYWlxcJCYmxuF93tzcdHhC0Ww2e0Sn46hJKFjPIV5eXg67v9tCpff39x2+aPr5+REUFMTy8vKpAeAmk5HsqpfxjqDXgNeyfZETFxfHysrKqRNSAN4hCuKeF0zsc4LQzBjY6vbh9UN/yOtL/5CdB3b5tbyBrt8JY/RATdY33s6Bt4xr3jmk/jKOvRE9UQ8EEPXcAKfPhREREZSUlNDR0XHixKrbkJkJBgPK5WVKSkpYXl7mZlMTgampBB4WcAsBMzNWkmW7/frX8K1Dk/lJSUfJVkkJxMWd2I46D0JDQ6mtrWVtbY3u7m4CAwPJzMx0y6J1d3cXi8XicDX4MnBSjE5fX9/RGJ1TwpZtOC3k/Stf+Yrm4ODgO55+D+7AfUOsgF/97Gc/M9ytb0hISGBiYuJEYmWxWFhZWWFubs7eA/b0WL4noFQqiYmJYX5+3qVx5729PYaHh7FYLOTm5l66wepp2N/fp6enh8jIyAuz1LBl5mk0mmNj6q5ifX2dqakpamtrz0Uknl8VxWfWLXwo6gd8+xsfpHropzwc4McnpucI/ud/RjzyFrxf+Xr2hofR3bqF7tYtFLGx+BYU4JufjzwoiP39fdRqNQUFBU699sLCAqUnjEKfhs3NTYenBz2hrwKr/tJsNjv8+LCwMDY3Nx3OrbN5WjlT+cvKyqK1tfUYSdVoNIyMjGAyGrCgRG6RUFiO7ntBQQFNTU2Ehobek/xJMomAVG8CUr2J11lQD2jx7fHilfMvQ3xLoE7YZS5lhbqCbMSPlezN6Yl7aRDhVef/fQUFBVFVVUVHRweZmZmeMTS2xdOMj0NKCsHBwfZzeG9vL/n5+dZrgiRZTSZTUuBVr3rm+WtrVpLV2/sM4frxj61EDCA8/DjZysgAF0h/ZGQkERERrKys0N7eTnh4OBkZGS4t1sbHx52K6rlsKHZ2SFhaImF6GsPwMNr+fvYnJggaHkb7nveg8vXlbjorhGB9fZ3c3Nwj99++fRudTjd8lU1BD+O+IVZCCGNMTMwvnn766T9+6KGH7PcHBQWh0WgwGo32H5ttamFjY4PIyEjy8vKuRE/aFaSmptLc3ExiYqLTK8uDgwNGRkbQarVkZ2c77Xl0URBCMDs7y8zMDIWFhYSGhjI6Osro6Cg5OTkee12LxUJvby9KpZLy8nK3VjF3d3cZHBykurr63Bo5b6WMF5cG8l0dvOadn+Z1rQ/z6ac+wt9Xp/CXsm3yH/sCe//zU1Sf/xz+f/AHLDc1oRsexvSLX7D7i1/glZTERkgIWTU1Tr03jUZz4mTOvbC9ve1wALGniBVYV86OSgTCwsJYXFx0mFjFxMRw69YtpyaSVSoVERERzM/Pk5iYiE6nY3R01J5gsDGp5ImvfJCfDg/zX+/5xJHn2ibRent7Ha54ylUywsr9CCv3Q7duZKvnAGWfnJC5IPZuWpBkBhJfHUJIgeutbl9fX2pqauxeV664gZ8IW+TS2BiW5z+f7u5uCgsLCQsLs7ujFxQUnH5ei4yEhx6y3mzY24P+/qPVrU9+EmzGqn5+UFR0lGzl5YETejKbJi86OpqFhQWam5uJiYkhNTXV6cX9/v4+Wq32ap27hYDNTSvhnZiw3g7/+5DRq5ck4ZWQgEhP5+D6dUZf+lJ2bt4kNjaWhIQE+3lgY2OD0NDQY7/bL3/5y7vLy8uPXej7cwH3DbECWFlZ+dznP//5lzz00EP2o8t28C4sLCCEcHu8zFWBl5cXYWFh92wn3A2dTsfY2BhqtZqsrCwiIyOvbOtTp9PR19eHSqWivr7eTkIyMzNpaWlhfX3dI5M/RqORzs5OIiMj3a5h02q1dHV1UV5e7nLIsHZ9lJcXxTC46s+qopJPJf8QH60RdeEE307PoupjXyD1Ja9i/g9eTOhj/4nPi1/MdG8v+/39hG5uEjg7i5ifR/fiF6NyMBvQGad1sH6HSqXS4WqfJ4TrNth0Vo6060JCQhgYGHB42wqFgpCQEDY2Npw6JjMyMmhsbGRvb4/19XUyMzMpLCy0DmhMwN7WKgatGi+OO8dHRkaysrLC7OwsycnJDr8mgCpCSewLg4h5XiB7k3qWOjbZCVwlKM991SUvLy+qq6vp7u5Gq9WSk5PjvnNNVBQEBMDYGGNjY4SHh9vtPGwi6Z6eHkJCQsjOznbsnB8QAHV11psNBgMMDR0lW1//OnzujqxHobCSK5tey/bfM2QKkiTZJ+ZmZ2dpbGwkMTGR5ORkh38rtqGTCz9/CwHr60cJ02ECdThvU5Ksrdb0dHjta63/TU+3Vv9SUkClQgJ8gRKe8Yk8HKOzvLx87Pi2WCx8//vf11sslicu8J27hPuKWAHtra2tOpu+wWKxsL6+ztbWFltbW2RnZ1NVVXWpU22eRHp6Oh0dHWdqXgwGAxMTE6ytrZGZmUlBQcGVJVRgddgdHR0lLy/v2OSUJEmUlpbS0tJCTU2NywTlMHQ6He3t7aSlpTlcrXAURqOR9vZ2ioqKXK6WLiwsIEkSZblxlOfC0paBpv5d/Dok4gbzGFsc4V3+/vy5fpu//96T6P83h/FH/5G0t7wLCgu5eeMG/tvbJMzPs/mtb+GdmUnwi198og7LBiEEKysrDgc0g3P6KrAST0+1o50hVnK5HKVSiV6vd/jckZiYyPT0tMPEymw2Mzc3h8FgQKvVHjPcNZvlGLUH+Hr5IslOjk3Jzc2lsbGRiIiIc4miJblEYKaKwMw4Jia09Pb2UlJS4rZzg1wup7y8nMHBQXp6eiguLnbPwlaSIDMTw8AAW1tbx4wxfX19qa2tZXJyksbGRoqLi8+nyfTyshKl4uJn9D8WC9jE8bbbE0/A1772zPPS0o63Ek+QpshkMlJSUkhISGB6epqGhga7dcy9PiedTodarfacxYIQsLp6vOJk+/feoRBwmcw6zZeeDlVVVtJkI1ApKU5V9JRKJUlJSSQlJbG3t8fMzAxLS0soFArkcrldS9bQ0ABwUwihc+fb9iTuK2IlhBARERHf/va3v/3Ompoa+draGmFhYeTk5DAwMEBcXNyzllSB9WIREBDA2toaUVFRx/5uMpmYmppicXGR1NRUj7uluwqj0Uh/fz9CCOrq6k7VH6hUKvLy8uju7qbGyXbWadjb26Orq4v8/HyHzSwdhc0ANCMjw2VBr1arZXx8/Ig5Z2yoF695MJyNUiP9P93kFbyKmr94Ef8+9nFqf/JNHtvdp/bP/oHZx7/L5qMfxS8gmKL6esZGRpAGBwmbnmb1s5/Fv6aGgAceQHbCb2Z9fZ3Q0FCntGabm5sOV1PBWrHyVMi4MwJ2eEZn5ej+h4SE0N/ff0SCcBJsLtlTU1PEx8fznOc8h+bm5mNtSpNFjlG3T5iXH7JTiJVCoaCoqIienh6H0gnuhfT0dG7fvs3IyIhb2+y2BIXJyUna2tooLy93i6bVnJqKubGR0tLSE9+3JEmkp6cTGRlJb28vMTExpKenu36ukMms5CEjwxoUbMPy8lGy1d0NP/jBM3+Pjj5OtlJTQZJQKBRkZGSQnJzMxMQEDQ0NZGRkEBsbe+L+Tk5O2tMWzg0hrPt8N3my3TSaZx4rl1tJUnq6taJ3mDwlJ1sJqJsREBBgP9+EhYUdidH5j//4D/XS0tJn3f6iHoTkaGCpW15MklRAA+CNldT9QAjxT5IkfRewzZAGA2ohRPEp28iorKzs/eEPf+gbHR1tP/HPzs6i1+udWmHfj9jf36erq4tr167Zf2hms5nZ2Vl77pkzJebLwvr6OoODg6Snpzssdh4aGkKhULj8HW9ubtpH2N09bWgzAA0NDSU1NdXlbbW2tpKenn7Pysja8AELP9jCYoZfB2zxxG8+zCNyLS//9VNIRhNDLyjH/CevJ/6lr8PX7M1Yby++AwMELC0h8/cn6IUvxKewEOnQhb6zs5O0tDRCnBhPv3HjBteuXXP42GtqaqKystLhC++NGzd48MEHHXrs8vIyu7u7Do+mr6+vs7y87FRVYHx83B5eezeMRiNzc3PMz88TERFxRLhss904fBx/98aHeecb/ossnwS++a73EP/W5576uiMjI3Z3clcghKCzs5OIiAin24uOYHFxkcnJSSoqKlzS0gkhWHjLW4j/2teQDg7OrIpYLBZGR0fZ2tqiuLj44qx0dnaOCuR7eqytRdsgRWDgEXNTSkogJwed2cz4+Djb29t2x3nbuV2n09Ha2urYItligaWlk/VOExNweKGhUFjJ02HSZPt3UhJcwoCXLVHCNqxkMBiYnJzk+c9//vbS0lK4EOLEFYckSV8BXgasCSHy79znMKfwBC66YqUHniuE0EiSpAQaJUn6XyHEH9geIEnSJ4Cd0zYghBiPjY1dUCgUmYdP4HFxcdy6dcttWW5XFX5+fgQHB7O0tGTXlk1OThIXF3flzE1PgtlsZmhoCI1GQ1VVlVMn3OzsbJqbmwkLCzu3iHNpaYnx8XGqq6s9IpweGhrCx8fHZVIFVusHf3//M9tNkTm+BP+lF1P/tclDK2Ekv/Df6A/3YuvlY2R8+m8o/lkLIT9rYS/4vUy/6jkoX/96wv7w99nsGUDR1oblhz9kr62NkJe9DK+4OAwGA/v7+06Ndev1ensJ31GcVe1xBT4+PqysrDj8+NDQUIaGhpx6jYSEBDo6Oo6QEo1Gw9TUFFtbW6dOIScnJ9PQ0EBycrKdbGklXzKy6ygjBkl+csXKhszMTJqamoiKinKplWprs7e2tqJSqdyeuWnrILS2tlJeXn7ulvj4+Di+WVlIFgtMTcEZFTaZTEZOTg5bW1t0dHSQkpJyrqEfpxEUBA88YL3ZoNPBwMBRsvXFLz5Dcry9UeXnU1BSgiE3l5mpKabi4sgsKSE8PJzR0dGjFikWCywuntyym5yEw/5tSqW1SpaRAc997lHylJh4oofUZUFzp2J2eALcy8uLwcFBi9ls/vZppOoOvgZ8FviG7Q5nOIUncKGfrLCWx2w1R+Wdm71kJlmP/N8HTl+uAXt7e5/54he/+LH3ve999iujQqEgLCzs1DbZswk2EezY2BhRUVH3bKNdJajVanp7e0lKSiI/P9/pE51MJqOsrIzW1tZzEaPJyUlWV1epra31yAV9amoKnU7nlD3BadBoNE4Fy3oFK8h8ayQLP1OT1QMJ7NMQHsn3//hT/MPPPktM4//wWrWGl3/t56i+8lO2EyMx/t4Lsbz+j5G2BYq2Dtb/8z+R5+ZyUFBAXFycU9+Ps/oqT1fKnW0FyuVy5HK5U7mcKpUKpVLJzs4O+/v7zM7OIoQgNTX1nrpGuVxOamoqExMT9rFyrcyX3/uDf+KBWZBkg/d8XZlMRom/P/LcXCzXryN761vhwQfPZQ8gl8upqKigpaUFLy8vt3tRhYeHU1ZWRmdnp32Szxmsr6+zvr5OjY2sjI2dSaxsCA0Npb6+nsHBQVZWVigqKnKrRtMhqFRQXm692WA2W9/H4erWj36E15e+RCaQIUnoEhNZS08nICmJmOBgK2kaH7f+V69/ZlteXlaNV3o6vPCFR6tPCQnWtt59gNOGMj7xiU9sra6ufvpezxVCNEiSdPzJOM4p3I0Lp6ySJMmBLiAd+JwQou3Qn68Bq0KI8XttQ6PRfP0LX/jCB/7hH/7B53B5NDk5meHh4WctsbJ5fIyMjODl5UVsbOx94WtisVgYHx9nbW3NZZdmHx8fCgoK6OzspLa21qEKiRCCoaEhdDod1dXVHtGdLS0tsbKyQnV1tcsrY5v9Q1FRkVMVIJlSIuF3g/GL92Lh5/CQ2sxemJaaN7yb/lf/HZ9+6hv89dPf4E+Cg3hXWix5j/0Xsk9+i5W8ZNZ/7yWIvGJChoZRjIxgSUpiT6vFLysLmQNEY3Nz06mKh06n86jTv1KpxGgbnXcQNp2Vo7ovjUaDJEl2G5SCggKHj21bVFVqaioqlQq95Ivyzppckp1NOv0/+lEsW1uIJ56wOo6npsKb3wxvfCM4oXMDa2WgoqKCtrY2Kioq3O4bFxgYSHV1tV136KiOTaPRMDAwQE1NDTLdHd3y2JhTr23Tpa2urtLS0kJWVpZTOkCPQC63ksOcHHjd66z3CQELC9DTg9TTg09PD7LWViKffhqLtzeW1FTkmZnwkpccJU9xcfcNeToNZrOZtbW1Y1q/qakpZmdnF4UQoy5s3iFO4W5cOLESQpiBYkmSgoEfSZKUL4SwzTq/Dvi2A9vYi42Nffqpp5567Qtf+EL7/YGBgRiNRo/641wWtra2GB4exsfHh7KyMry8vOxu7Fe5/be3t0dvby+RkZHU1dW5hdSEh4eTkJBAb2/vqWJWG8xmMz09Pfj4+Jz52PNic3OT8fHxcxuA3o3x8XEiIiLO5bAsSRKh5b4Mr9wmzpCOYjyWwFVBvszESx54C+PP/3MGtZt8OS2dnEfmuf3I7/L6PT0FH/x3LJLEQlUOW2XFRKi32J2aQq1QIOLiCCgsJKigANkpv6utrS2nRNAHBwce/Y3avmchhMPfeVhYGKurq6cSKyEEarWa1dVVVldX8fb2Jj4+nv39fXJycpz67mUyGRkZGYyNjVFYWIhOePPev8rmz+r+ir/POqNK2dkJ3/8+0vvfT/tznkPe6CgB3/0u/OM/wgc+AC99KbzlLfDiFzvc7vH19aW0tJTOzk6P5IX6+PhQW1tLR0cHWq32TGsTo9FIV1cXJSUl1iqTSgUREdaqzTkQFRVFSEgIfX19rKysUFBQcLWMoiXJWmFKSICXv9yejlFTUMC2Vsvw6Ch+fn5kZWVdSFbqRWJ5eZno6Ohjv5/PfvazexsbGx91cfMOcQp349KuyEIItSRJN4AXAQOSJCmAVwFl93ziHSwvL/9/H/vYx57/whe+8MhIV2JiIrOzs065Il9l7OzsMDw8jEwmo6Cg4IjYOjExkampqSsp2BdCMD09zfz8PEVFRW6PYUhOTmZnZ4fJyUnS09NPfIzN8sBmyucJ7O3t0d/fT3V1tVtO1Gq1mrW1tWMBpM5gcXGR4BR/UvLDEWbB/pyBjf5tGPKlatuHSimAvVkzDVsaPq+K5H3TfZQGBfPPhdnUzs2S+Ln/AsAYHoo5KwdtRAT6nh6WwsIwRUfjm5tLaGkpijvHosFgQCaTOUXwPelhZYNKpXKqMhYaGmoP0rXBbDazvr7O6uoqW1tbBAYGEh0dTVpamv373t7edihW627ExsYyOTnJ/r4GrUGBTqdBQjp1KtCOv/97CA9Hete7KFQoaJck6n75S5QzM/CVr8BXvwo/+Ym1cvXww/CmN1krWmcgKCiI3Nxc2tvbqampcfuCTalUUl1dTU9PDwMDA+Tl5Z1IeoUQdHd3k56efvS8kZnpdMXqMLy8vCgvL2dxcdFuKuruiWB3YXh42LpQ8fcnzN+fujvRbZ2dnYSEhNiDsJ8NmJ2dpaSk5Mh9BoOB73znO1qj0fij827XWU7hTlwosZIkKQIw3iFVPsDzgf/vzp+fD4wIIRYc2ZYQojcmJmZzaWkp/HBpNy4ujoaGBqcz0a4abFEXBoOBnJycE6ezThLBXgVotVaPnICAAOrr6z02oVhQUEBLSwsBAQHH2r9ardbp1oOz0Ol0dHV1UVZW5pbqi9lspq+vj7KysnMfuxaLhYmJCbvXjySX8E/xxj8lmsSXWZgd7GexaxaflTReJmXxkj/8GQ3rbXyt6T95+a1fofTy5un/fRLj8JOE3eogvWWEkKYm67bDw9ElJaGPi2M9ORldSgreWVlYkpKc1s446jHlCmxeVo5+NwqFAplMhkajYXNzk5WVFbRaLREREcTFxVFQUHDi95KYmMjo6KjTxEqSJLKyshgZGWFfayVTvl5+SPJ7tAKfegqeftrqEh4YiC+QlpbGwMCA9eL00Y/CBz8IP/85fOlL1v//8Ifhec+zVrFe+cp7TtVFRkai1+vp7OyksrLS7edQmUxGaWkpw8PD9orU3eeH4eFhAgMDj3vLZWbCk0+69PqSJBEfH09YWBi9vb2srKyQk5Nzpaao19fXUSqVR0ilJElERUURGRnJ0tISra2tREZGkpGRcbUqb05id3cXuVx+bJH1ox/9yGI2m78nhDC4sHmnOIU7cdEVqxjg63d0VjLge0KIn93522txsmS3s7Pz8c9//vOf+tCHPmQ/Q8vlciIjI1leXna76eNFQKvVMjo6ikajISsr654TYXK5nLS0NMbHx8nLy7vAvTwdCwsLjI+Pk5+f7xGn9MOQyWSUl5fT0tKCr6+vfepod3eXrq4ujwbD2qph+fn5brNsGB4eJiEhwSWNy9zcHNHR0Se2cmRyGSmFxcTlZDA49SMWJyYI2irheeEVPBhZzVT9OE/P/ob1oXz2gwr4gOYv0dUE8NzrKbzW5EdB2xQ+Nxrw7eoCwBQWhj4xEX1SEkRFMZWVhVdhIQGJifjHxiL39T013Pbg4MDjx4dNwH6vY8BoNLKzs4NarUatVrO/v097ezuJiYnk5uY6NMkWFBSETqdzymDUhsjISEYmhtEdWImVj9IXmXRKxcpisVarEhPhbW+z3x0fH8/y8jLLy8vWNqZSCb/7u9bbwoK1gvXlL1v1PKGh8IY3WEnWKeeMhIQEtFot/f39HgmqlySJ3NxcpqamaG1tPWK5sbCwgEajoaKi4vgTMzOt72Vvz+qc7gJ8fHyorq5menqaxsZGj1TVzwMhBMPDw6cOwEiSRFxcnD07trGxkbi4OFJTU6+0JOQ0TE9Pn9hN+NjHPra5trb2SUe2IUnSt4EHgXBJkhaAfxJCfJlzcAp34UJ9rNwNSZJ84+LipmdmZiIPH1QHBwd0d3c7PFF1FaDX6xkfH2dzc5OsrKwjXib3ghCChoYGKisrL1VXZjAY6O/vt7csL3IVtbu7S3d3N9XV1ezt7TE4OEhZWZnH8iEtFgttbW0kJia6jbyvr68zMTHhkvjdbDbT0NBAfX29Q5//hnqM3vFvo9GuEq96ADGWjb8uCsOyGWEQ/MvP3sUvBn+K1nhAaEg0JS94Hq9/22t4Q2gSihsN8OtfI27cQNo5eZLZolBg8fdH+PsjBQUhDw5GCgqCwEBW9HpC3/pWvF70olPJ191wxscKrBdprVZrH/AwGo2o1Wo7kdJoNCgUCoKCgggKCiI4OJiDgwM2NzcdXqjojBYmV/R0ja6zq5MIC/LF11tmv/l5y+/8V4aPl4RMaWafPXZMu6iNu+yYNCxrt2h9epcvvukNfOLVX+CNr4sk9FWvOP5i3/se/MEfWF2//+RPjvxJr9fT3NxMbW3tyeTOYrFWur70JfjRj6yZeNXV8Na3Wo0v7yLzQgj6+/tRqVQOe4GdB8vLy4yNjVFZWcnBwQGDg4PU1taeTBL++7/h1a+2mnHe1TpyBYd1oBkZGZfa6VhcXGRjY4OioiKHHm82m5mZmWFubo6kpCSSk5Pvm06N0WikqamJBx544Mg5b3h4mOc973kdS0tLlZe4ey7hviZWAFFRUf/x2c9+9q2vec1rjhxNbW1tZGdneywyw10wGo1MTk6ysrJCenq602PuAKurq8zPz1N+eKT3ArG6usrQ0NClTtysr6/T19eHUqmkqqrKY/oDIQQ9PT0EBgaequ1yFkajkcbGRpe9tSYmJgCc2i+zxcjY3C8Ym/8FQkgkRpUTH16FvyEZzayRmYENfvXUE/yy+0c0T97gLdf/mte85C8xR5gIjNBTWJ3M4E++S1lSEqaJCfS3b2OamkLSalF4eyP5+mI2mzHv7CB2dlDs7yM/OEC5uYlSq0WXm8ven/0Zlle9Cm9/f1QqFd7e3if+Bk4jVhaLBZ1OZ68a2f69s7PD7u4u3t7eCCHsJCo4OJigoCACAgKOvY7RaKSlpYXr16+f+plt7BoZXdIxtqRnbl2P2QLeSlBK25glBTvbGszCG5mkRCZXIMlkyOXKZwxYJQsojfabpNCzPbXF0De+yp/lv5HnvVhL6O/eRayMxmdCgHt7T5wEW1lZYW5ujoqKinufQ9bX4ZvftJKs4WErqXrd66wkq7zcTnSFELS3txMdHU1SUtLp23MRW1tbdHd3I0kStbW1p/8Gbt+GwkLrFOQf/MHJjzknbJPL6+vrFBcXu30y0hHYFkbnie4yGo1MTU2xtLREWloaCQkJV97PcXJyEuDYIMPDDz+s/sY3vvGHZrP5vskGvBv3PbGSJCm1uLi4taen50hfYX19nYWFhWOiuKsCs9lsF3fbDOxcWWm0tbWRmprq8fbKYZhMJgYHB9HpdJfjEXMHQggmJyeZn5+3h8F6SjMxPDyMyWSioKDAbdvs7u4mMjLSYQf6k2AjZ9evXz/Xex8YbmPzoIs93QQmsw4fr2DioypJiKwk0C8W/a6J/pYFFic0BGmC6Or8X979gz+jJKGS55a8jJe88nepfmk2vhFKzPv7HPT0sN/VhXlzE8nHB9+iIvwqKlBGRGAymWh86inKx8bw/sxnUE5MYIyOZvX1r2fxxS9Ge0pLY29v78QqpCRJqFQqOymz/VuSJLvezJnflu3iZqv6mcyCmTU9Y0s6xpZ0bGmsTtohfkaEppvetu8RlZ9AUczvsDo0z7v+7o+ObfPh9/wdtQ+9lInhYT7xzkeQZFbfLJlMgSST88q3fYLXxj9IwhoklPUR8oq7iNV//if8+Z9bRem/8zun7ntvby+hoaEkJiae/UaFgJYWq2Hl975nNa0sLLS2Cf/wDyE0FJPJRGtrKxkZGR6zsTk4OKClpQWAwsLC089hWi34+lo1ZO9/v0f2ZXt7m76+Pnv15yLJycjICEql0qUweIPBYCeImZmZZ+bKXhaEENy8efOYge7Ozg5ZWVkLq6urSWeYgl5p3PfECiA2Nrb5ySefrDkcR2FrkdXU1FwpYbfFYmFubo7p6WkSEhJISUlxCwk4ODigo6ODa9euXUgpeGtri/7+/otzNT4FQggGBgYwmUwUFRUxMzPD5uYm5eXlbt+nmZkZ1tfX3brtpaUllpaWXK42joyMoFKpzhVNcvi3IpPDymY/82ttrG0NI7AQ5J9AQmQl8ZHlqLyCMAsLP+hs4luf+w49v/wli8vWSll2dD6f/LNvE1ESQ2KFP+ExXhimp9nv7EQ7PAxmM15JSXgVFzN4cEDttWvWFtUTT8DHPw43b1rdq//sz+Cv/srq0XMIzrYCbSdvZ54DMDg4iE9AGNvGAMaWdEyu6DGYBHKZINx/i42Z/6W/9Sd0NY8zO7UOwJtq385fPe+9bOpW+dXtJzBbzFiEBZPFhNli5oGM55MRlcOiep7/7voWZsmMRTIjZBYskpnXPe8NxCtTkR0YSSgfIuTlL39mhw4OrL5Fqalw69Y9W6cmk4nGxkYqKyudm7rc2bFWgr74RejqslbGfu/34K1vRV9dTUtrK8XFxW7XIen1elpaWigqKsLHx4f29nZSU1NPX2QkJcH169aKm4dwOB2iuLj4QiQW+/v7dHZ2uu38rdVqGRsbs8c6RUREXCmCZbMsuTtC6v/9v/+n/+AHP/jParX63y5nz9yDZwWxkiTpBa9//eu/+/jjjx8ZnZudnUWn03lUI+AohBAsLi4yMTFxbFzbXRgdHUUul7utRXUSLBYLIyMjbG9vX2wO1wkwm810dXURGBhIVlaW/cQxPDyM0Wi8p/u1s1hZWWFyctKt1TCdTkdLS4vLzvm2i9N5Q7e3t7eZnJw8Ru50hl0W1zuZX21HrZlDQkZESDYJUVXEhBVhQPDtkV8yuDbP8H/3sdU+y7+98ouEamV85tf/H1tij7rnvIQXvu4FpMfJMd3utVaxtrawKBT4pqfjnZ6OKj0dRWgodHTAJz4B3/++1UX89a+Hv/1baxWFM4iVyWSN9Rgast4GB2FoCPPYGLLoaKS0NCsxOXxLS4OQEA70Fpa3DSxvG1neMjK/rkV9JxnER6nHXzHK7toNsjN1KMyCP3vt46xvqilOrODBjBdSXVRLTrCBQMMokmwfyWJBoETghcD7zn+9sOANCj+E0g8UviBTYZFUCOGFEArMJjky7TTRZXtHidW//Ru8971WUuWAbnRzc5ORkRFqa2vPd/z39FjF7t/6lpVwpadj+OM/piMvj+IXvchtv3mTyURLS4s9H892X2dnJ2FhYSeHKD//+dbA4NZWt+zDvbC+vs7AwAAZGRkuVZPPghCCtrY2MjIyzh3VdRr29/cZGRlBp9ORk5PjsWEeZ9HU1ERRUdGRlqvFYiE1NXVjdnY2Qwihvry9cx3PFmIli4qKmh4aGko8fODYetaXmaEnhGBlZYWxsTHCwsLIyMhwu/meDWazmVu3bjmdwecodnd33Zsc7wIMBgPt7e3Ex8cfq9IIIejr68PHx8ctpHpra4vbt2+7tfpp068kJye73GIZGBggKCiIhISEcz2/r6+PmJgYIiMjT33M3sEy86vtzK+1o9Vvo5B7Ex1ahHrdm8qK57OEnn7tLMMHC6jWAvnl336Zpqafozfq8PcOoDzruVx7wat54R++jEDNFAHTA/hsbGBWqwGQh4binZqBPDYNhdaM/Eufx+v7X0PS7qMrfS67L3s7MxHZpFfGEihfQDE9coRAMTpq1SHZkJwMubks+foSJZcjn5mx5sytrx95Xzq/QLYiktiKTGQ7Kom9qEi0sX5shRzQv9xNd9sAve1zqBTe/OrdP0CyZDE4N0B4bDSKLEFKlImY2CAUoSEoQkIYmZoiKCCA6KAgLAcHmPf3sRwcPHO76//Nd+6zB/UCUkkJsa98pfV/trasJPDaNfjpTx3+TgcHB1GpVC61ldBqrYLxL34RGhoQcjkbNTWE/PmfoygttVbRzrk4tFgstLe3ExcXd+y4tVgs9PX1IZfLjy+O/uIv4Nvftn4uF3D+MRqN9Pf3I4SgsLDQI92P5eVllpaWKCvznN3S7u6u3aPtsrXHW1tb9nDuw3jyySd505ve9N2lpaXXXtKuuQ3PCmIFEBQU9Nd/8zd/85F/+qd/OlL/npiYQJIk104w58T6+jqjo6P4+/uTlZV1ISVlTwjZbRqmpaUlioqKLn0g4ODggPb2drKzs0/1DrJYLPaVryvfvUajoaOjg6qqKrcaWs7OzqJWqx2e/jkNNr+u69evn4vo2hYfDz74oINTqBY2diaYX21jcb0bs8WaWyaXeeHvG4XKN4YtvxDm5DB3sM3yE+Ms/c8onR03eSjnZbznRf/KjHyXr/36/xHo7Ye/3AdfmTd+Mh+K4ipIj8xCazhgeOU2gWYT2eNPkXb7h6gONjH4R6A82EaymKz7IknoYyPQZ8Siy0hAn5GAISUBTXwCWlkAer2czU09OimAbVMAO8YQxAH4L4yhmuwhaKGP0LUJwjZXiNzZIU5vRG5+RtZhBhYlGXt+4UgRmQQmlbGWFcJ+eTQZD9QSnZp7TERui2Gprq52+DsQQiAMBiwHB2i3t+mdnaXe9n285z3WNmlfHzih6zObzTQ2NlJSUuIeO5CxMfjylzF/5SvINzas9ymVVguE3Nxnbnl51qiVexAQi8VCV1cXoaGhp/42hRCMjo6yu7tLWVnZM1XiT30K3vlOK0G+QHPPpaUlRkdHycvLu+cCxFnYFsPV1dUXolHd3t5meHgYb29vsrKyLkWk39bWRlZW1rG2clVV1UZ7e/sDQgjn0tCvIJ41xEqSJJ/o6OjpycnJqMMXQJPJxK1bt84t6j0PbAevl5cX2dnZF37wtrW1kZaW5hZX4YODA3p6eggJCSErK+vSjfTUajU9PT0UFxefaJp6GBaLhY6ODiIiIs7lvG5rsZWUlLiVTO7v79PR0UF9fb3LldTe3l6ioqIczre7GwsLC+zt7TkVR2PDwGA/Sh8t3j5Gdg+W0RyssLe/jNagBkCv8GY7IJrtwGj2UeC3IKdkORtdh4Y/euzFaA0HWA7pU9/w6g/xwHMeZnJlgI986EX2+72A1wN/kZVEQH4ZM/oQPvzL7zCn9MPi5YPCywuZtzcv+MP3EFnwACszIzT/9N9ReqtQKFUY9Qdotud51VvfSmZqEN2/+hmff+xr9u1LkkRURCQ//dJPSNL5M/TET1nqbCBf7k+sxYhMO4NyZx6/jU2kw+dLpdLqKZWcDCkp1ltyMn27u2Q+73n4JCefq6Jz+/ZtQkJCiAcrSXnNa+Ab33B6Ozs7O/T19VFfX+8+3aXRyPKTT3LQ1UWqTodka71OTVnF8GAlmxkZzxAtG+nKzMTi5UV3dzdBQUEO5ZzOzs4yPz9PZWWltVr0xBPWyJ6mJqitdc97chA6nY7e3l58fX3Jzc11SxfEHYL188CWORsQEHBhi36wVs4GBwftBsY2dHZ28vKXv7xxaWnp2oXsiIfxrCFWAGFhYf/ygQ984O/++q//+kivbWRkBB8fH4+ODIP1oBkZGcFisZCTk3NplR13CNmFEMzPzzM1NUVBQYHbe//nwdraGkNDQ1RUVDis8zCbzXR0dBAdHe2UsNum/8jKynLrClUIQXNzs1v0DhqNhp6eHurr68/dlm1paXEqPPgwbG3nu9sjRpOWvYOVO7dldg9WWDaqWfT2Zts/ArPcSjaEEJgNJowHeow74K0IwVsehn7LzGLPBMY9C8Y9MyadAaNeS0r+NcLj0tlamab9F1+xWjpotcgP9Fj0ev702jtIyi7gqZ1f8x/f+GcMRh1GvR6FSklgbCgv+uCfEFucxsHINtvNiyR4JZAiSybNlEKA9pn3rwsycBCmZTlmk6n0FaIDg3leYCEpBMPsLMzMwPT08f+urR3/kMLDITr67FtoqL21ZSP0D3zrW0jf+Ia1WnSOoQSw5k6aTKZzEed7wZYKYW/VabXWdqytNWu7TUxYBxQAIZOhj4/HlJmJf2XlM8QrKwvucWFfXV1leHjYKshfXHzGKPSNb3Tre3IEQghmZ2eZmZmhsLDQpd+wuwXrzuIiZSo2dHV1kZSUdGzR/4IXvGDzqaeeeqkQos2jO3BBeFYRK0mSguLj48enpqYiDgvDDQYDzc3Nx4zI3IX9/X1GR0fRarVXRiDoipBdr9fT29uLt7c3+fn5V8LRd25ujtnZWSorK53+8dvIVVRUFCkpKWc+/l76D1fhzgtdZ2cnSUlJ57bY0Gq1dHd3nyuX0GQy2c39HH6OWc/O/jJPjzYSm5iMt1cA3l7+yGSnV3WEAIMBNBrBxOgs6elJ+Pgq8FWBt0JCLpMhQ4ZFDeYxC4YRgWneeiGXh0jIks3sqdSEyCMwrJgxLwvYv+PThMASakEfYUAXZWA/Qstu+AE6LwM6iwH9npaXxleT4e3gyPrBAczMYBofZ/LmTTIDA5FWV2Fl5ehNpzv+XKUSoqLsREutVBL04x8jPfIIPPaYw5/x8c/PfUT+7u329vbi7+9/78qTTgdjY1gGBlj5zW8ImJsjYG7OGqZs05VJklVHdridmJsL2dlwZwG1vb1Nb28vJfn5BMfGWlukH/6w296Ps9jf36enp4ewsDCysrKcJkY2jWV6evqlL1qFECwsLDA5OemxwSp45jOrq6s78nsaGRnhOc95Tt/y8nKx21/0knD5V0w3QgixExUV9Z3HH3/8bW984xvt783Ly4vw8HCWlpbcGnOj0+kYHR1lZ2eH7OzsKzXSmp6ezq1bt4iJiXFqimd5eZmRkRFycnKczj7zBIQQjI2NoVarzx0MK5fLqaiooLOzEyHEPduCNsfp0NBQt5OqnZ0dlpeX3ZIIsLOzg8FgcMm3bG5u7tzTTtvb205fqBVyb8ICk4ncn6E+yonPwBcIBjExzQOnVZ2j7tyugVFjZndEx86Qlr0+PSpLKFrJjCpCQWCGEp8YL3xilPjEKJF7n35BvDlyk7QUxxIQrPvpC7m5KHJz0cTHs52ScvwzEsIayXI32Tp8W1wkaGUFXUQEXn//97jSfJckieLiYre1ng9vt6ioiPb2dnx8fE4/jlQqLPn5dOn1BJWXE2sLjDcYrOTqrilOnnzy+BBCXh4hubnUpqUxMDJCcUwMchfCmN0BPz8/6urqmJiYoLGxkeLiYqe0bIuLiyiVyksnVWD9LhMSEoiLi2N2dpbGxka3WgHZMDExceLQ0wc+8IHttbW1d7vtha4AnlUVKwBJkiJTU1MHx8fHww+vIrRarb095ir5uV9M2La2thgeHnZo7NpoNDIwMIDRaKSoqMjjJWFHYLFYuH37NsCpAbjObq+jo8M+yn0SRkdH0el0FBYWuvU7NZvNNDU1OX0CPg1tbW1kZmaeqTM7DTaPp/NebIeHhwkKCnLaad9oNNLW1nYucumsjxWAcd9E2687qX2oEpmXc8dPf38/MTEx5yKv6+vrLC4uUlxc7PRzbRgfH0eSJLfYp7hrWOJu2FrmtoXl3bBZooSEhDikqcJohMnJ4y3FkRErGbsDfUEB3v397nwr58bOzg69vb3Ex8eTmpp65nnDZrPiaPTURcNkMjE9Pc3CwoJbzKvB+p7b2tqODdnMzc1RWVk5vrq6miWeRWTk/ggVcgJCiLWDg4Mnf/zjHx9xbfXx8SEgIID1u8atnYHJZGJ0dJSmpiYCAgK4fv06sbGxV5JUAYSGhhIcHMzU1NQ9H7exsUFTUxPh4eFUVFRcCVJlMpno6OjAx8eHwsJCt2gQZDIZFRUV7OzsMDg4yN2/Y9vFx92kCqyELTY21i2kamtrC0mSzk2qbNsIDAw8dwVjc3PzXKttrVZ7oZmWSj8FpgCd06QKIDw8nM3NzXO9bnh4ONvb25hMpnM9HyAlJYX5+XmMhys450RiYiI6nY61k3RgLkChUFBRUcHg4CA7d2VG2kh0RESEY6QKrC3R7GyrOen732+1Vujrg/19q4brRz/C/MEPMvvHf8zo6Oix3/BlICgoiPr6ejthOjg4OPWxtop4bm7ulSRVYP1OMzIyqK+vR6vV0tDQwMLCgkuf9eTk5Imk81//9V93tre3//HZRKrgWUisAFZWVt73vve9b+vu7yojI4Px8XGnt2c2m5mcnOTWrVsolUquX7/uFhZ/EcjOzmZ+fh6NRnPsb2azmYGBAcbGxqiqqroy+VI28W5MTAyZmZlu3SeZTEZpaak9889yR1i7trbG/Pw8ZWVlbv8MNjc32d7edsvkjxCC4eFhsrOzXdrO3NycY7EnJ8BsNmM2m89FwA8ODtxqW+EI5HL5uQhOWFjYuYmVJEnExMSwvLx8rueD9QKXnJx85sLI0f0pKipicHAQw6HKjzugUqkoLy+nu7sbrdbqrGojGcnJyQ7pGs+EQmEVrf/u7yJ///tJ/9u/RafT0dfXZ/8NXybkcjl5eXlkZWXR3t7O3NzciUTE1gL0VDyQO6FUKsnJyaGmpga1Wk1DQwMrKytOEyyj0cja2toxGc76+jo/+clPdgwGw3+7c7+vAq4+MzgHhBCz29vbLb/5zW+O3O/v74+XlxdbW1sObcdisTA7O0tDQwNms5lr166Rmpp66ZYDzkAul1NYWEhfX9+RH8TOzg6NjY34+PhQU1NzoVWEe2F/f98+jXfeC/9ZkCSJ/Px8AgMDaW9vZ3Nz0z5t6G6hvtFo5Pbt25SUlLiFsK2vr6NSqVyqfJlMJnZ2ds6t79je3j53tewyiJWvr+89qwinwdvbG6PRiPmQeaczSExMZG5u7lzPtSEpKYnl5WX0er1L2wErAcrKyqLfAy00f39/u+ZKrVbT2tpKTk6Ox0LZZTIZhYWF+Pr60tHR4VJl0J0ICwujrq6Ora0tOjo6jnxvOp2O8fFx8vPzL3EPnYdtiKmyspKVlRWamprYsHmZOYCpqSmSk5OPFSIeffRRjUaj+dD9nAl4Gp6VxApgeXn579/73vce+/YzMjIYO0P4aIufaWhoYH9/n7q6OjIzM6/EdNx5cLglaBOD9/f3U1paSlpa2pWoUoH1gt3e3k5JSYlbLQ5OQ3p6OuHh4fasMk+0QAcHB0lNTXULmRBCMDIy4nK1amlpySVd4MbGxrlJ2UW3AsEqA7BVUpxFSEgI29vb53qur68vkiSxv79/rueDlUCkpaUxMTFx7m0cRmxsLDKZjIWFBbds7zBCQ0OJi4ujsbHx3mHKboIkSWRmZhIbG0tLS4tbyKc7oFQqKS4uJjExkebmZnuVp6+v70q3AM+Cj48PxcXFFBcXMzMzQ0tLy5m/DZPJxNLS0rFF8u7uLt/4xjf29vf3nTdouw/wrCVWQoih+fn54c7OziP3BwcHI0nSiSV+IQSrq6vcunWLzc1Nqquryc3NvVIhzudFdna2vfpmsVioq6sjICDgsnfLjpWVFfr7+6mqqrow/y+DwcDCwgI5OTn09/efq6pxL6ysrKDX6902Xbi8vExQUJDLWW3z8/MuVQPPq6+C+6tiBa7prAASEhKYn58/9/MB4uPj2djYODc5vBsFBQWMj4+7bXs2rK+vs7CwQHp6un0RdxFISEggKyuLlpaWEyUPl4Xo6Ghqa2uZm5ujqakJhUJxX7QAz4K/vz/l5eXk5uYyOjpKe3s7e3t7Jz52cnKSxMTEY12ez33uc1q9Xv9JIYR7+9JXBM9aYgWwvLz8rve+973Hzoo5OTmMjIwc+eFvbm7S3NzM4uIi5eXlFBYWXkjEwEXAZvZpsVgQQpzLd8WTmJmZYXJykpqamgu76JrNZtrb28nJySEtLY3CwkLa2tpcuogehl6vZ3h4mOLiYrdUBG2VRlezDzUaDTKZ7NxVI7PZjNFoPPdv4zIqVq4QK1d0VoBdZ+UKybBVZs6qtDsKpVJJfn4+vb29biM/09PTjI6OUlNTQ3Z2Nr6+vgwODrpl244gMjKSkpISOjo6zl1h9AS8vb0pKChgf3+f3d1dt51frgKCgoKorq4mLS2N/v5+uru7j/zODAYDS0tLx4yZdTodn/3sZ/fUavXnLniXLwxX5+rqAQgh2gcGBqZ7e3uP3B8YGIivry+rq6t2PcDk5CSFhYWUlpZe+Irak7CNue7u7vLggw8SGRnJ5OTkZe8W8IwQe21tjerq6gurDAoh6OrqIiEhwb6CDAkJobq6mqGhIWZnZ13efn9/P9nZ2W5rL87PzxMREeEy2Z+fn3epgqZWq12aRrRYLBeuUXSlFahSqTAYDOcWSCsUCkJCQpzSpJyE6Ohodnd33VaRiYiIwN/fn5mZGZe2YwtM3t7epqamxn685+TkoNfrL/RcExQURFVVFf39/aysrFzY694LtnNBSUkJVVVVjIyMMDg4eG7d3lVEWFgYtbW1xMXF0dnZSX9/PzqdjrGxMdLT04/93v/93/9dZzAYviiEcG+L4ArhWU2sAFZWVt72yCOPHFsmJCQk0N3dzdDQEFlZWVRWVl6p1pg7sLi4SEtLC6mpqRQWFqJQKMjKymJpaenSV3UWi4Wenh5MJhMVFRUXdrEVQnD79m0CAwOPRRz5+PhQW1vL+vo6t2/fPvfFdGFhAYVCce78vrthNpuZmppyfGT9FNgiLFzZL1f0VWaz+VIqpa4QK7DKB9Rq9bmf7w4RuyRJZGdnMzo66tJ2DiM3N5e5ublzkzXb9K6/vz8lJSVHfsOSJFFSUsLq6ipLS0vu2uUz4evrS01NDZOTky6TRndgamoKX19fIiMj8fX1pba2FpVKRWNj4zF7ivsZkiQRFRXFtWvXCA8Pp7m5mYWFhWNa2b29PT7+8Y+rNzY2PnpJu3oheNYTKyFE5+TkZO/NmzcBayuit7eXkZERIiIiSEhIcGkFfhVhMBjo6upiZWWFurq6Iwe3XC6nrKyMvr4+t/jjnAc2f5vAwEDy8/MvVDw/MTGB2Ww+taVm+3xUKhWtra1Oj6ZrtVomJyfdOvkzOztLTEyMyxW99fV1QkNDXSKxruirLqMNCNaqkSsVgrCwMJcqTiEhIezt7bn8e4uIiECv17O7u+vSdmyQy+UUFRUdsR1xFDs7O7S0tJCRkXHqAIzNN25iYuJCW2BeXl5UV1ezvr7O8PDwpXldbW9vs7i4SG5urv0+SZJIS0ujpKSEvr4+xsbGroQXl7sgSRKxsbEEBwcTGxtLc3MzY2Nj9qnNj370o/v7+/v/JoQ4/0THfYBnPbECWFlZ+YtHHnlkq7+/n/b2dqKjo6mrq6OoqMh+oX22YG1tjaamJqKjoykrKzvxYuzn50dGRoZbNRaOwuZvk5CQcGK8gSexsLDA5uYmRUVF93xdSZLIyMggNTWV5uZmhy9kNm+s/Px8t03+mEwmZmdn3eKB5Yp3FVirjAaD4dzk6DKE6zZIknTuCqSrAnZJkoiLi2NxcfHc27AhOzub4eFhl7djQ3BwMJGRkU75+y0tLdHT00N5efmZ07tKpZKKigpu377tNkLoCORyOeXl5ZhMpnMRR1dhNBrp6+ujtLT0xIVMYGAg9fX19kQGVyZHrxp2d3fRarUUFBRw/fp15HI5t27dor29na985Svbu7u7/37Z++hp/J8gVkKIsZ2dnYa2tjbL9evXiY6ORpIkvLy8iIuLuxIlY1dhMpno7+9namqK6urqMzMR4+Li8PLycllP5Az29vZobW0lNzf33Bl158X6+jrT09OUl5c73I6Kjo6mtLSUnp4eZmdnzyShU1NTBAUFHUtudwVTU1MkJia6bPVhMBjY398nODj43NtQq9UuPf+yKlbgWjvQx8cHnU7n0sXZHdOBgD170FEvPkeQkZHB2trame1Os9lMf38/8/Pz1NXV4e/v79D2fXx8KC0tPWIgehGQJImCggICAwNpa2u7sAq9zVohPT39np+RTCYjJyeH3NxcOjo6mJmZeVZUr4aHh8nJyUGSJORyOWlpaVy7do1PfepT2r29vb8TQlxOq+QC8X+CWAHMz8+//aMf/ejW3dWp1NRU5ubmLq0t5g5sb2/T2NhIYGAgVVVVDl+88vPzmZ2dvZBe/+bmJp2dnZSWlrqVeDgCW4TNeQxAAwMD7YZ/3d3dpx4ne3t7LCwsuOwxdRgGg4HFxcVjUzXnweLiInFxcS5VCF3RV8HlVqxcmQwE13VWKpUKpVJ56li6M8jJyXFri0smk9lbU6dV7zUaDU1NTfj7+1NZWel0RTYwMJCCggI6Ojou/Fybnp5OYmIiLS0t6HQ6j7/e7OwsCoXC4cVjaGgo9fX17O7u0tbWdiH76CnYCP/d4eNzc3P8+te/Xjw4OPjOZezXReO+IFaSJKkkSWqXJKlPkqRBSZL+5dDf/lKSpNE793/stG0IIZb29/e/89WvfvWIaMYWG3FVJuWcgcVisU+ZlJeXk5yc7NSFUy6X2ysynnQuXlpaYmBggOrqardk5TkDrVZLd3c35eXl556oUygUdtPSpqamY0TUYrHQ29tLcXGx29Pg3eX0v7Cw4HKVcHNz0yVSfJnEysfHxyVi5artArhHxA5WkqJSqVzKPb0b/v7+JCQkMDQ0dOxvCwsLdHZ2UlhY6FDI8GkICwsjLS2Njo6OC2/NxcXFkZubS2trq1vI7WnY3d1ldnaWgoICp56nUCjsn29LS8uFCv7dBduUd05OzrG//e3f/u32+vr62+/lsi5J0lckSVqTJGng0H3FkiS1SpLUK0lSpyRJlR7afbfiviBWgB54rhCiCCgGXiRJUrUkSc8BXgEUCiHygI/fayNra2vv/5d/+Zedu8vRSUlJdjPH+wV7e3s0NTUhk8mora11uCx/NwICAkhNTfVIzAVYW1kzMzPU1tZeeBvIaDTS3t5OUVHRuT+fw0hISKC8vJy+vj6mp6ftFYOxsTGioqLcamxqC8x1h7no7u4uXl5eLlk1WCwWdDqdS9/hZbYCfX19XWpDuaqzAmtreW1tzS2kwjYh6M7WUUpKChqNxk7YTCYTvb299iEYV9rANsTFxREVFUVPT8+Ft73Cw8MpLS2lq6vLI2J6m57rNF2VI4iMjKSuro6lpSW6urruq07K2toaPj4+xxbP/f39tLS0zFgsll+dsYmvAS+6676PAf8ihCgGPnDn/6887gtiJaywzQQr79wE8Dbg34QQ+juPu2d0uxBCrdVqP/vYY48dOcPKZDIyMjLcOsrsKQghmJycpLu7m8LCQjIzM10eYbcJmt2xmrZBCMHg4CBbW1tUVVVdeIyDzQA0MzPzWFnaFfj7+1NXV8fu7i4dHR2srq6ysbHhshXC3RgbGyMjI8Mt9gSuitbB2k51lTiaTKZLi/NwtRVoI2aukAGZTEZ4eDhra/c8TTkEPz8/AgMDXQp5vhuSJFFcXMzAwACbm5s0NTUREhJCWVmZW7+3tLQ0vL293SrCdxQ2ucTAwIBbq0I2v6qUlBSXbXu8vLwoLy8nOjqaxsZGt1YmPYV7xW098sgjm6urq38mzvjxCCEagLvFgwKwMbUg4L4o5d0XxApAkiS5JEm9wBrwKyFEG5AJXJMkqU2SpJuSJFWctZ2tra1HH3vsMfXdeonY2Fh2dnY8WiZ2FVqtlpaWFrRaLfX19W6tkBQWFjI9Pe2SjsQGs9lMd3c3AGVlZRduCGmbzouNjXWbl9Rh2MbU4+LiaG9vdyl37yQcHBygVqvdEmBrsVhYX193OUrD1TagxWK51ExKVytWYDWgdFWP6K52IEBmZibj4+Nurfx4e3vj5+dHe3s7paWlJCUleeR7y8vL4+DggOnpabdv+yzY/OpmZmaYmppyyzZnZmaQJMmtwfFxcXFUV1czMTHB7du3r/T0+tzcHOHh4cda/Q0NDYyPj/cJITrOuel3AI9KkjSPtSP1Xtf29GJw3xArIYT5TjkwHqiUJCkfUAAhQDXwbuB70hlnASGEdn9//4Mf+tCHjjAoSZLIy8vj9u3bV24ywxZJ09raSmZmJvn5+W4nKwqFgvLycnp6elwST9o8qkJCQsjLy7uUi+ng4CC+vr6kpKR49HU2NzfJyclBrVYfS7J3BSMjI2RlZbnls1tdXSUiIsLlyperwnWdTnepEVFKpdLltoqrflZgJWc6nc4tx4qPjw/h4eFumTYEa1WysbGRkJAQwsPDPbrItBmILi0tubXq5iiUSiVVVVVsbW0xODjo0jl/fX2dxcVFCgsL3biHVvj4+FBdXY2/vz+3bt26dGPnk2AwGJiamiIzM/PI/UIIHnnkkY2VlZW3ubD5twHvFEIkAO8EvuzCti4M9w2xskEIoQZuYO3FLgA/vNMqbAcswJnL6r29vS89/vjjW3eXgkNDQ/H19b2UH/pp0Ov1dHZ2srGxQX19vUcn6vz8/MjPz6ezs/NcqyOtVktzczPJycmkpqZ6YA/PxuTkJHq9/kQBpTuxtrbGwcEBaWlplJWVkZCQQHNzs8vthb29PbRa7Zn+QI7CHW1AIQRardYl4fllCtcPw5ULqDt0VmANVV5YWHB5O2C1SpicnHRJt2Ubgunv76e4uJiMjAyKiooYHR316ISaXC6noqKCsbExt9pHOPP6ZWVlAHR3d5/rnLe/v8/AwADl5eUeq8xLkkRKSgrl5eUMDAwwOjp64eL/e2F4eJiMjIxj7eL/+Z//sayvr/9aCOFKyOWfAD+88+/vA78Vr7sLkiRFSJIUfOffPsDzgRHgf4Dn3rk/E/ACzlxSCiFM29vbf/X2t7/9GP3PyclhdHTUo1NyjmJlZYXm5mbi4+MpKSm5EH1KREQEcXFx9PX1OXUR2t3dpbW1lfz8fLe0sM6DpaUlVldXKSkp8WilzGAwMDg4eCRg2WY6u7y87FL1yqZTcMf+6/V69Hq9y5OYOzs7BAYGurRPlylct0GlUrlEFGw6LVcr2u4kVl5eXsTGxp7bj06tVtPY2IhcLqeurs5+rHh5eZGXl+f0ecBZeHl5UVlZSV9fn9tyEJ2BrVMREhLitNeV0Wiks7OTkpKSC6nG2vSdAE1NTVdCtqJWq9FoNMd8E3U6He94xzu2VlZW3uniSywBD9z593MBx51sLxH3BbECYoDfSJLUD3Rg1Vj9DPgKkHpnPPM7wJ+cJZCzQa/X/6SlpWW4oaHhyP3e3t4kJye7LUn+PLBN48zOzlJbW+sRndC9kJycjFwud1h/sLGxYbc0cKVd5Ao2NzeZmJigoqLC43l0t2/fJjMz89jJ1MvLy169amlpYWpqyqmVpVqtxmw2u+0zdDVw2QZX9VVwNSpWrgrYJUkiMDDQZQdxLy8vfH193aJnBKsX38zMjFOLQaPRSH9/v32BcNKgRGRkJCqVyq1DLSfBZiDa2dl5aR5OqampJCcn09zc7JAWTwhBd3c3aWlpbpmWdBQymYysrCwKCgro7u5mamrq0qQrQggGBgYoKCg4tuj68Ic/vK/RaD4phHC4hC9J0reBFiBLkqQFSZLeDLwV+IQkSX3AR4A/deNb8BjuC2IlhOgXQpQIIQqFEPlCiA/eud8ghPijO/eVCiF+7cx2V1dX//jNb37z5t0npOTkZDY2Ni5lRbC1tUVjYyOhoaFUVlba0+IvEjbH4pWVlTMnmBYXFxkaGqK6uvrSQqx3d3e5ffs2FRUVHq/q2WJJ7uVsHx0dTX19PXq9nsbGRofbR8PDw24zGBVC2E1BXYWr+iq4GhUrV8OYwT06K3CviF2pVJKYmOiQEFwIwezsrF1LVVtbe8+KZl5eHtPT0x6PXAkKCiIvL4+Ojo5L6xbExsaSn59Pa2vrmeR5ZGSEgICAC0+QsCE4OJj6+noODg5obW29UEd7G+bm5ggODj52/ExPT/OFL3xhfWtr61FntieEeJ0QIkYIoRRCxAshviyEaBRClAkhioQQVUKILre+CQ/hviBWnoIQYmpnZ+erd9svSJJEfn4+AwMDF7YasFgsDA0NMTw8TGVlJYmJiZc6RSWTySgvL2doaOhUgjkxMcHc3Bw1NTWXJky2GYCWlpZ6/MKt0+kYGxtzSKSqUCjIycmhtLSU8fFxuru777ka39jYQKFQuG31q1ar8fPzczm4WQjBwcEBfn5+Lm3n2VCxAvfprCIiItjc3HTbpFdycjILCwv3bGWp1Wp7C6m+vp6EhIQzzzE248qLyBWNiIggJSWFzs7OS9MQhYWFUV5eTnd396kEemFhgd3dXY/rOM+CXC4nPz+fjIwM2traWFhYuLDrlU2wflKY/Vve8patjY2Nh/8vRNechv/TxApgfX39A48++ujWysrKkftDQ0NRqVQXImTf3d2lsbERLy8vamtrL/0CZIO3tzclJSXHjOqEEPZQ1cvwqLLBaDTS0dFBfn6+xx3dhRD09vaSl5fn1Pv19/enqqqKmJgYWltbTxQa2zxg3HmidodoHazHZkBAgMsk32AwuEzyXIU7KlZ+fn7s7++7fAGTyWRERkayurrq0nZskMvlpKamMjExcexvBoPB3vYrLCx0OiQ8NDSU0NDQE7ftbsTHxxMWFuZxbde9EBAQQHV1NUNDQ8e0cGq1msnJSUpLSy914XsY4eHh1NXVsba2RmdnJwaD4ewnuYiRkRHS09OPHUc///nPLYODg+1ms/mGx3fiCuP/PLESQmi3t7ff/hd/8RfHhOy5ubkeFbILIRgfH7fHoaSnp1+ZH6sNQUFBZGVl0d7ejtlsxmw209nZaY958bSe6TRYLBY6OjpIS0u7kOzB2dlZfH19zzWtJ0kSMTEx1NfXYzQaaWhoYHFx0X7hWF1dxc/Pzy3u8GD1Edva2iIiIsLlbblDX2V7n5d9bLujYiVJEgEBAW6RCbizHQjWZIDV1VV7ZdRkMjE2NkZTUxOhoaFntv3uhaysLJaXly8kVzQ9PR25XH6phs0qlYqamhrm5+eZmJhACMH+/j49PT2Ul5df2mLyNCiVSkpLS4mLi6OpqclthP0kqNVq9vb2jrVBdTodb3/72zdXV1ff7LEXv0/wf55YAej1+h83NzcP37p168j9nhSy7+/v09zcjNFopL6+/sIz9JxBTEwMcXFxdHR00NLSQkREhD29/DJgMwCNiopyi4boLGg0GmZmZsjNzXVpOwqFguzsbGpqatjc3OTWrVusrq4yOjp6Ykn9vFhZWSEqKsot34879FV6vf5StIJ3w9vb2y3+Ue7SWQUEBGAymdymj7ElSIyNjTE9Pc2tW7eQy+Vcv36d+Ph4l44HmUxGcXHxPYOa3QWbxtOWu3dZsHld7e7u0tfXR0dHByUlJS63xT2J2NhYampqmJmZoa+vz+1FgbME63t7e485I1h/tuK3xOoOVldX3/DmN7954zQhu7tGgW3i0Y6ODnJycsjNzb20qo8ziIyMZGdnB7lcTlJS0qXuy/DwMN7e3qSlpXn8tWwBy0VFRSgUCrds09vbm8LCQsrKyhgbG7PbIrgL7moD2lbprlbSroJwHZ6pmLnaYnJHILMN7rReEEIghGBubg6NRkN9fT1paWlu81cKDAwkNjaWkZERt2zvXpAkibKyMubn5z1afTkLMpmMgoICVldXkcvllzag4wxUKhWVlZUEBwfT2NjoVo+w+fn5EwXrMzMzNsH6fZHl52lc/Sv6BUEIMalWq7/+2GOPHVEY24Ts/f39Lp+QdTod7e3tqNVq6uvr3Zph50ns7OzQ1tZGRUUFvr6+l2pFYZtQysvLu5DXm5iYIDw8nJCQELdv28fHB7PZTElJCaOjo7S3t7vcatFqtZjNZre0Fff29vD393e58nUVhOs2eHl5uaxBCQgIQKPRuEUDFBcXd6QtfB4IIVheXubWrVtsbW1RVFTksVzGtLQ01Gq1R0KM74ZcLqeyspLh4eFLcxy3WCx0dnaSl5dHQkICra2tF6JhchWSJJGUlERFRQXDw8MMDQ25PBCg1+uZnJz8rWDdAfyWWB3C+vr6+x999NHNk4TsAQEBLpWll5aWaGlpITk52a3VD09jbW2Nnp4eKioqCA0NpbCwkJ2dHWZmZi58X5aXl1laWrow4aharWZ1dfVYVIO7MDc3R1RUFBEREVRXV5OWlsbw8DCtra3nvnC5y7sKrPoqd3hquera7k64IzNQkiT8/PzcUsVWKpUEBAScizhYLBbm5+dpaGhgbW2N8vJyCgsLiY+PZ39/3yN2MbYomtu3b7scEeQIvLy8qKiooLe31+OWD3fDJjmIjIwkPj6e5ORk0tLSaGlpcVmrd1Hw8/OjtrYWLy8vGhsbXfJgu337NtnZ2ScK1gcGBv7PC9YP47fE6hDuCNkfefvb366++285OTnMzMw4/YMyGo10d3ezuLhIXV2dy2G4F4n5+XlGR0epqamxV0BsJfrFxUW3psOfha2tLcbGxqioqLiQUGez2UxfXx/FxcUeadWazWamp6dJT0+33xcWFkZ1dTU5OTlMT0/T2NjIysqKw9UMIQRLS0tu0525Q7gO1orVVWgFgrVK6I6LortsF8B5Ebvt2Ll58yZ7e3tUVVVRVFRkJ6+SJJGTk+Oxlp2vry+pqakMDg56ZPt3w8/Pj5KSErfmcZ4Fm5bIx8fniOQgOjqawsJC2traLkTI7w5IkkR6ejrFxcX09vbaxfjOYGlpyT6Ecxh3BOtbvxWsH8VvidVdMBgMP25qahp4+umnjxx5CoWCgoICp/xcNjY2aGpqIjIykvLy8ksfN3cUQgjGxsZYWlqipqbmmPDYVqKfmJhwi4j3LGg0Gvr6+qisrLywz3B4eJj4+HiPaSpmZmaIj48/sV0TFBREeXk5JSUlrK6u0tDQwMLCwpml/K2tLQIDA91SDRVCsLe355b3f5Vage6YDAT3CdjBStK2t7fPFBobjUbGx8dpaGiwD73k5uae6CEXFhaGyWRym7v73UhISMBgMHB3dd9TCA4OJicn58IMRCcmJjCZTCdaoISEhFBRUUFPT8+ZBspXCYGBgdTV1WEwGGhubnb4d6DX6xkdHaWgoODY3/75n/9Zo9FofitYvwu/JVZ3QQghVldXX/fwww9v3F3qDwsLIyAg4Mw2mNlsZmBggPHxcaqqqlyeyLlICCHo7+/n4OCAioqKUy/SSqWSyspKBgYGPLpy0+l0dHZ2XogBqA0bGxvs7u56LEjaaDQyNzdHSkrKPR/n5+dHUVERVVVV7OzscPPmzXsG47pLtA5WMuvn5+eW41an012agezdcIeXFVgvUnt7e27RWdkqAad55tmm0pqampDL5Vy7do3MzMwzNVQ5OTkMDw+7vH8nQZIkioqKGB4evrAqUlRUFAkJCXR1dXnU42pubs6uVTvt+Pf396empobR0VGPR/64E3K5nNzcXLKzs2lvb2d2dvbMz7K/v5/s7Oxji9qenh6++tWvzm1ubn7Uk/t8P+K3xOoECCEWdnd33/+Xf/mXxxhDTk4Os7Ozp7J9W6ipr68v1dXVV6YF4ghMJhPt7e2oVCqKiorObIGpVCq7S7Gr+Wmn7U9HRwd5eXkEBQW5ffsnwWg0MjAw4NEg56mpKZKTkx2uLKlUKvLy8rh27RoqlYr29na6urrY3Ny0nxRNJhM7Oztuyxl0l77KhquysHBXxUqSJHx9fd2m+7m7HWixWFhcXKSpqYmhoSFiYmJ44IEHSE1Ndfi4CQ4ORqFQeKyq7O3tTXZ29oWaeSYlJREcHOyWYaKTsLCwwPz8PGVlZWee/7y9vampqWF5eZmxsbFLMzQ9D8LCwqivr2d7e5v29vZTyfHS0hIymexYC9BgMPDa1752c21t7feEEJ7137gP8VtidQp2dna+8MQTTww+/fTTR/ovp7UELRYLo6Oj3L59m9LSUlJTU6/MxcQR6PV6WltbiYmJISsry+F99/f3p7y8nK6uLreKZW3TOMnJyW4xunQUAwMDpKWleYwQGwwGlpeXz2VZoVAoSEpK4tq1a6SkpDA7O0tDQwNTU1PMzc0RExPjtmPOXfoqo9F4pcwUVSqV24J+3amz8vX1RZIk1tfXGRoa4ubNm+zs7FBcXEx1dTWRkZHn+m6zs7MZGRnx2EU/JiYGpVLpNssIR5CZmWk3V3YnFhcXmZ2dpaqqymHyqlAoqKioQKvV0t/ff2lRPOeBQqGguLiYpKQkmpubj1VM79UCfP/736/Z3Nz8tBDC894b9yF+S6xOgRBCrK2t/f7DDz+8eTdhCAsLIzAw0N4S1Gg0NDc3A1BXV3dfeJ0cxv7+Pi0tLWRmZp6rlRQQEEBZWRmdnZ1uIVdCCPr6+ggLC3PbhJsjWF5exmQyeTRYdXx8nLS0NJcE8ZIkERoaSmlpKTU1NQghGB4eZnNzk6WlJZcNHIUQ7O7uusW09ioJ18HqS+QukuEunZVer2dqaoqDgwP6+voICgrigQceIDc312UzyoCAAPz8/DyqBcrPz2dycvLCgoAlSaKwsJCtrS3m5+fdss2lpSWmp6eprKx0WqMok8koLCxEpVJdaoj0eREdHU1tbS0LCwv09PTYpz37+/vJyck51gLs7u7ma1/72uzm5uaHL2N/7wf8lljdA0KIxZ2dnX985JFHjrUEs7OzmZ2dZXR01O5zkpWVdV+YfR6GrRRcXFx8rrgWGwIDA91GrsbGxpDL5Ucm5jwNvV7PyMgIhYWFHqs0arVaNjY23ErcvLy8iI6OJiQkhPz8fNRqNQ0NDfT09LC+vn4uEmETm7vjc7hKwnUbFAqFW6wCgoKC2N3dPddnbDKZWFhYoLW1lfb2doQQ1NTUIJfLiY2Ndet5JCsri9HRUY9VrZRKJfn5+fT09FxYO8wWEj8zM+MyaVxaWmJyctKl3FNJksjKyiImJoaWlpYL0525C97e3pSXlxMeHk5jYyMjIyPIZDKio6OPPO5QC/DVv20Bno77iwVcAnZ3d7/0i1/8YuCpp546UuM1Go1IksTs7Cz19fUeMZD0NFZXV+nr66Oqqorg4GCXt+cOcjU7O8vOzs6JkQmegi1gOScnx6PRK2NjY2RmZrr9fdlE64GBgeTm5vLggw+SmJjI0tISN27cYGBggI2NDYfbFO6IsbHhqriuH4a7BOySJDll32AymVhaWqKrq4vGxkY0Gg35+flcu3aNtLQ0/Pz8CAkJcbsmytfXl5CQEI/ao4SHhxMUFMTU1JTHXuNuKBQKKisrGRoaOvcAzeLiIlNTU1RXV7ulZZ2YmEhWVhYtLS0X7rvlKiRJIiEhgZKSEiYmJlAoFMeq3+973/s0m5ubj/22BXhv/JZYnYE7U4J/8KY3vcneErStNHNzc4mNjXVbOfoiMTs7y/j4OLW1tW6tKBwmV84K2ldXV+3C0YvUp83NzeHt7X1sdeZOaDQadnd33f4aQghWVlaOiEslSSIsLIyioiKuX79OREQEi4uL3Lx5k66uLhYXF+9ZsXGXvgquZsXKXQJ2OFtnpdVqmZ6epqWlhaamJnZ2dkhNTeWBBx4gOzv7mEO+u4OZbcjIyGB8fNyjGqDs7GwWFhY8Ykx6GmyVlu7ubqe/04WFBaanp12qVJ2EyMhIiouLaW9vvzTHeFcwPj5OWVkZ/v7+NDY22i07urq6+PrXvz67tbX1kcvdw6uP+8P++5IhhFgMCgr6h7e97W0ff8c73hEkSRL19fUolUpCQ0O5desW4eHh94W2SgjB6Ogou7u79taDuxEYGEh5eTmdnZ2UlZU5pNXZ3t5meHiY2traCzEAteHg4IDp6Wnq6+s9+jqjo6NkZ2e7nTCur68TGhp66mcml8uJiooiKioKIQQ7OzusrKwwOTmJQqEgOjqaiIiII9E1Ozs7bpvCfDZXrMCqs5qenrZrEy0WC2q1mrW1NdbW1uyf8WEDz3shJCSE/v5+t4v+VSoVUVFRzM/PeyzrUy6XU1xcTE9PD/X19Rcmi/D396eoqIiOjg5qamoc8rqbn59nbm6O6upqj6RgBAcHU1VVRXt7O9nZ2R5dtLkT8/PzyOVy+0ItMjKS3t5eQkJCfjsF6AR+W7FyELu7u1++cePG+MTEhKWsrMx+0pPL5ZSUlNDd3e3x1HdXYQsUNhgMHncwDwgIoKKigq6urjNDQPf39+nt7aWiouJCTVRtkRUFBQUejRja3d1Fr9d7ZLrRGe8qSZIIDg4mOzub69ev2y0lRkZGuHHjBp2dnYyNjbn1gn4ViZU7K1YBAQFsbm4yPj5OS0sLDQ0NzM3NERAQQE1NDbW1taSmpjpctZMkyZ4f6G6kp6czNTXl0fNUUFAQ0dHRF54nGhoaSlZWFh0dHWe+v+npaebn552a/jsPfH19qa2tZWJiwqU4tIvC3t4ek5OTR6YAAwICqKur49Of/rR+Z2fn00KI0UvcxfsGv61YOQghhJAk6RXvfve7e1/ykpdEHK7CBAUFkZiYyMDAAEVFRZe4l6fDZDLR2dlJWFgY6enpF9Jq8/f3p7q62r5qOynOR6/X09HRQUlJicsTUM5icnKSkJAQt/o1nYTh4WGys7Pdvl2DwYBGozm3Ps7Hx4eUlBRSUlLsTuvj4+MYDAZu3LhBQEAAYWFh9jT78xBxi8VyoRVIR+AKsTIajajVara3t9nc3ESv12OxWJDJZBQXF7uFRCYkJNDR0UFycrLL2zoMpVJJfHw8MzMzR2Ja3I2MjAyamprY3t6+UO1pdHQ0Op2O7u5uysvLj53jbNV6WwzQRRyXXl5e1NTU0NXVhVardcrK5iJhNpvp7u6mpKTk2MKqu7ubH//4x+Pr6+u/nQJ0EL+tWDkBIcTSzs7O3//pn/6p+u6/JScnYzAYPLLSdBU6nY7m5mbi4+PJyMi40B+2j48PNTU1jI+PH9OO2AxAc3Jy3CKedwa7u7ssLS15hPAchq1aFxoa6vZtLy4uus3VX5IkAgMDkclklJSU8OCDD9rDp2dmZmhsbOTmzZv09PQwPT3N1tbWmZUBk8l05UgVON4KNBgMrK2tMT4+TkdHBzdu3KCtrY2VlRV8fHwoLi7mwQcfJDU1FS8vL7dV5lQqFUql0iNapZSUFObm5jwaoGwLau7r67tw64Hk5GT8/f2P5RjaEiX0ej3l5eUXelzK5XIqKiowGo309vZeSa+rgYEBEhMTj0kADg4OeO1rX7vx2ylA5/B/qmIlSZIKaAC8sb73Hwgh/kmSpH8G3gqs33noPwghnjhpG3t7e1/9zW9+86pvfOMbL3jDG95g71tJkkRxcTFNTU0EBwdfePXlNOzt7dHV1UVeXt6FGm0ehpeXF9XV1XR2dqLX6+02Cl1dXSQkJFx4MLWtJeqpgGUbhBCMjIyQn5/vke0vLCxQUVHh1m2q1WqCgoLsROtwZdZsNrO7u4tarWZubo6dnR2EEPj4+ODv72+/+fn54e3tfSXbgGC90NkubkIIDg4O2N/fR6PR2G96vR6lUklwcDBBQUF2oflJJDYsLIzZ2Vm3eq7ZROx5eXlu2yY8YzI7NTVFVlaWW7d9GH5+fiQnJzM0NERhYaHHXuckZGdn09PTw+TkJGlpaZjNZrq6uggKCvLIVK4jkCTJ7vfV1tZ2z7iwi8bS0hJ6vf7ECulb3vIW9ebm5gfu1QKUJOkrwMuANSFE/p37ioD/APyBGeAPhRDuj+e4opDuJxt+VyFZf1F+QgiNJElKoBH4a+BFgEYI8XEHtxMQGRk5cOvWrUTbqt6G7e1tBgYGqKuru3RPq62tLfr6+hwWkHsaNkKjVCoxm834+Ph49OR+GoaGhlAqlWRkZHj0ddbW1uxTju7G7u4uw8PDVFVVuW2bWq2W3t5eampqHH6OEAKtVmsnJDaCotfrMZvNCCGIiIhApVIduXl7e+Pt7e3URe7GjRs8+OCDDj/eYrGg0+nQ6XTo9foj/15cXLQvfnx9ffHz8ztCDr28vBzeN4vFQkNDg1P75sg2b968yQMPPOD284htf2traz2qaRRC0NbWRmpqqkseeeeBxWKhra2N2NhYFhYWiIuLc3tr9bxYWFhgamqKysrKS8/Q3N/fp6Ojg7q6umMtwG9+85vGd73rXb9cW1v7HXEPoiBJ0nVAA3zjELHqAN4lhLgpSdKbgBQhxPs9+FauFK4GZb4g3Dk4bMnKyjs3p5mlEGJPkqRXvPzlL3+qt7c37PCPIyQkhNjYWIaGhjxWqXAEtvyqq5RXaGszNTU1odPpeM5znnPh+7C1tcX29ja1tbUefR2bnqO0tNQj23dn4LIN5/GvsmXm+fr6Hrt4Tk1NYTQaiYiIsJOazc1NO7m520RRkiQUCoX9JpfLkSTJfrPFhoD18xVCYDKZjtzu3t5hIqdSqQgJCbHH2uTl5bllklcmk+Hl5eXWCp1MJiM8PJy1tTW3T5TJZDJSU1MZHx93e0XsMGxV/JaWFoKDgy90MEX2/7d33uGRluX+/z5T0uukt930Xje7STZbYCmeBRVREOUo6k9UOApHRdCjKNjl2EA8eDzYFURARIRFBXXdbMumZ9N7z/SUmZTJtPv3xxSzyaTP+0529/lc11ybnZm8z5PJ5J3ve5fvLZGgsLAQp06dQlZW1q4RVQCQnJwMf39/1NbWory83Gfd5Ha7HU1NTSgpKVklqvr6+vDQQw8pNRrNneuJKgAgohrGWOqKu3PgyA4BwJsA/gqAC6srFcaYFEAjgEwATxHRBcbYTQDuY4x9AEADgM8Q0boGJETUEhUV9a1PfOITX/rZz352SWI6PT0ddXV1UCqVq4ZXisHQ0BAmJydRXV29q+a0AY6rNZlMhtTUVNTV1YkaErdarbh48SIOHDggeDpAqVQiLCxMkJSw3W6HVqtFfn6+V4+r1+u9KtZMJhOioqI2XV9mt9svEUmuiBfgEFJqtRpJSUnu351EIoFUKr1EjG329xoaGorFxUWvfahFRUVBr9d71VV/z5496OnpEaRVPyUlBTU1NYKnawMCApCTk4O2tjZBIrdrMTc3h8bGRuzbtw+9vb1ISEjYFVF7FzExMdi3bx8aGhpQUlIiSA3mRriGe69sMDCZTLjlllv0arX6ViLabqFfO4BbALwC4N0AxJtNtgu46orXichGRKUAkgFUMMYKAfwvgAwApQCUAL63mWNNTU19/7XXXmt88cUXL7lUdhVvdnd3e62tezMQETo7O6HX673mJOxNtFothoeHsX//fmRmZiIlJQXnzp0TbcZYR0cH0tLSBK9/cw2IXZkm9hZqtRoxMTFeTxHNzMx4tYlgqx/arshPUFAQwsLCEBkZCYVCAYVCgaioKMhkMrdQUygUiIiIQGhoKAIDAyGXy7cklr3pZQV4dyCzi/DwcHd0z9swxpCVlSWKLUJiYiIAiNbYo9PpUF9fj3379iExMRHl5eVoamoS7TyzWcLCwlBVVYW2trZVA5CFRqVSYX5+3mN36H333WdQq9WPEVHzDpb4MIBPMMYaAYQCMO/gWJcdV52wckFEMwD+CeA4EamdgssO4CcAKjZ5DNJoNLfdf//96qGhoUse8/PzQ3FxMZqamkTpAnGFdYkI5eXlu64ba3Z2Fh0dHZcMOU1OTkZhYSFqa2s39LraKWq1GiaTyevpM0+MjY0hOjpasEiAEGlAk8kEPz8/r4q13ei67sKbXlaAwxBSCJftpKQkjI+Pe/24AJCQkACDwSDK6JXi4mL09vYKLm6GhobQ1dWFgwcPuiNUoaGhKCoqQl1dnaDdkNshMDAQ1dXVGBwcxMrPEKFYXFxEV1eX28duOb///e+tr776asP09PSmggtrQUTdRPQWIioH8ByAgZ0c73LjqhJWjLEYxliE8+tAADcA6GaMLc/XvROOMOamIKIZtVp92y233DJlNl8qyqOiohAbG4vubmHHKlksFtTW1iIiIgIFBQW7zidlYWHB7S2zchafQqFAVVUV2tvbBTPRM5vN6OzsRElJieCvjd1ux8DAgGCF8a7aJG+nNfR6vdf9vGw2267pfFqJtyNWUqkUcrkcJpPJa8cEHBcfQkV6XIODhT4/Af8a1Nza2irIoGa73Y7W1lZMTU2hurp6VVF4VFQUsrKyUF9fv+vsDuRyOaqqqqDX69HR0SHoIGvXBXhxcfGqmrehoSHcd999aqe1wo42wRiLdf4rAfBFODoErxquKmEFIAHAScbYRQD1AN4kotcAfJsx1ua8/xiAT2/loER0QalUPv7AAw+saifNysqC0WgU7OS4uLiI8+fPIzU1VVDTv+1iNptRX1+PkpKSVXPRXLiu2jQaDdrb27164iMitLa2IicnR5QOnJGRESQmJgpWqDs+Pu7VOh4X3hy8DDhO4LtN4C/H2xEr4F91Vt7EVXS/3SHDG+FqLNjqXM/trhUcHIzh4WGvHndpaQnnz59HcHAw9u3bt2a0PjExEXFxcWhubhZUvGwHqVTqrkETMsvR1taGuLi4VX/rZrMZ73jHO6bUavXtG9UXr4Qx9hyA8wByGGPjjLG7AdzJGOsF0A1gEsAvvPQjXBZcVcKKiC4SURkRFRNRIRF91Xn/XURU5Lz/FiLacsJbr9d/88UXX2x79dVXLzFRY4xh37596O/vdw+z9BYGgwEXLlxAQUGBu45hN2Gz2VBfX4+cnJwNizNlMhn2798PuVyOCxcuYGX0b7tMTExAKpWK8vpYrVYMDw8jPT1dkOMTkWDCytsu2SaTyeet5Oshl8u9bl4pRJ0VINxgZsBxfsrLy0NXV5cgx19JXl4eRkZGMDc3t/GTN4HBYMD58+eRmZm5qYkSGRkZCAgIEO3n3QqMMRQUFCAyMhK1tbVeT1sODQ3BZrN5vAD/zGc+Y5ycnHyCiGq3elwiupOIEohITkTJRPQzIvoBEWU7b/+10wjY5cZVJayEhIjsGo3m1o997GOalTURcrkc+/fvR3Nzs9dSBTqdDk1NTSgvLxd8JMt2ICI0NTUhKSlp011NrtREamoqzp07t2Pn6cXFRfT19V0y+0pIXMN4hWoamJmZQXBwsNejYS4zTG/W5e3m+ioXjDGvRgYiIyMFqbOKjY2FTqcTbMaf66JH6DpHwHEBVVJS4hUHcqVS6T4HbsVkOD8/3z18fTeSnp6O1NRUnD9/3mvpap1Oh/HxcY/lEK+99prthRdeaNPr9XxkjZfgwsqLEJFOq9W+5+abb55aKaCCg4NRWFiIhoaGHZ8gJyYm0NnZicrKSp95oGxER0eH2315qyQkJGDfvn1obGyESqXa1vrLByyL0R1psVgwPj4uqF+OEEXrgDD1VZeDsHL5WXkLqVQKqVTq9S4+iUSC2NhYqNVqrx53Obm5uaLUWgEOARodHY3+/v5tfb/LI254eBjV1dVbPge6urYnJydF78bbLImJiSgoKEBtbe2O07Tz8/Noa2vDgQMHVl089ff34yMf+Yhao9Hc6mze4ngBLqy8jNVqPT0+Pv6V973vfTMro58xMTFITEzExYsXt53jHxgYwOjoKA4ePLhrjD9XMjAwALPZjLy8vG0fIywsDAcPHsTQ0BA6Ojq2fHU7NDSEsLAwREdHb3sPW6G/vx/p6emCdWPabDZMTU0JMpbI2/VVwNatFnyBtwvYAWHqrABh04GAw9rB398fWq124yd7gezsbKjV6i2XRywtLaG2thZWqxWVlZXbjt5KpVJUVFSgt7dXlEjddoiKisL+/fvR1NQEnU63rWNYLBY0NDSgtLR0VWreYDDg+PHjerVa/TYiEucXf5XAhZUATE1NPXnmzJnXHnvssVXVsWlpaWCMYXBwcEvHJCK0t7djdnYWlZWVu86jysXExAQ0Gg1KS0t3XLzs7++Pqqoq+Pn54dy5c5suNjYajRgbG9uRsNsKJpMJarXaq7PiVqJSqRAXFydIQfj09LTXDQovh4iVEAXsQtVZhYaGwmq1CmpX4OoQFKMcRiKRoLS0FK2trZuO4Ot0Opw7dw7p6ekoKCjYsTWIXC5HRUUFWltbBRl47Q1CQ0NRVVWFzs7OLTdAucoxMjIyVtVP2mw2vOMd75jWaDT379CviuMBLqwEQqPRfPjxxx/vPnHixKpi9uLiYqhUKmg0mk0dy2azoaGhwT0SxtczCNdCp9NhYGAA+/fv99oeXUaG+fn5bjf79XDNIywpKRHNy6uvrw9ZWVmC/l6ESgOazWZ3CsubXK3CKjIyUrAISHJysmCeVgAQEhKCsLCwbafft0poaChSUlI2LCR3DTPv6elBVVWVV4e2BwYGory8HI2NjV63yvAWAQEBOHjwIEZHRzEwsHk7qO7uboSGhnpsdnnooYeMHR0dvzAYDM95c68cB7vzE/oKgIgsWq323+6++27lytoFiUSC/fv3o7Ozc8PuGLPZjNraWkRHRyM/P3/XtrAbDAa0t7ejoqJCkGiaQqFAdXU1RkdH0dbWtuZVbl9fH2JjY73qIL4eCwsLmJ6eFrTrcHFxETabbU27ip0gRH0V4EhB7NaoqgshUoEymQwSicRrXa3LSUpKwsTEhKARpezsbPT29opmR5CWlgaDwbBmqmtxcRHnzp0DAFRXVwuSXg4LC0NBQQHq6uq83inqLeRyOSorKzE7O4u2trYNfz8TExMwGAweo/bPPPOM+dlnn23QarUPCbXfqx0urASEiHRqtfqmm2++WbeyW8jf3x9lZWVoaGhYs612YWEB58+fR3p6OtLS0sTY8rZYXFxEY2MjysvLBW2x9/PzQ0VFBYKCgnD27NlVonR6ehparVYwc05P9PT0ICcnR1DBOzY2JliaUYj6KtdJf7deBLgQImIFCFdnJZfLERoaKkjnoYvAwEBER0cLGhlbjquQvL29fdV5UKPRoLa2FtnZ2cjNzRX0/RQTE4P09HQ0NDTsOgNRF66MhUwmW7cJamZmBv39/di3b9+q16y+vh6f+cxnxjQazS28WF04uLASGCJqV6vVH3vb2942vfJqKDw8HNnZ2WhsbFz1xzw7O4sLFy6gqKjIJ4OcN4vFYkFdXR2Ki4tF6VBkjCEjIwNFRUVoaGhwfwDYbDa0traitLRUtFSp0WjE/Pw8YmNjBVuDiDA5OSlYRGxqasrr9VVLS0urHPZ3I35+foJEloSqswKEL2IHgMzMTAwMDIgmMAIDA5GRkYH2dsfAC7vdjo6ODgwMDKC6ulqQhg1PJCcnIyoqSjB3eG/g8h2LiYlBbW3tqvevyWRCS0sLysvLV0WMJycn8c53vlOj0WhuICLvGIlxPMKFlQjMz8+/3NfX96P7779/Vd9sYmIiFArFJZ2CWq0Wzc3NOHDggE+mnm8Wu92O+vp6ZGVlie6lFRkZiUOHDkGtVqOhoQFtbW3Yu3evIOmyteju7kZeXp6gV9JTU1MICwsTJK1msVggkUi8PnbmcqivAv4VUfP2h6iQdVbR0dGYnp4WNGXl7++PhIQEwUZMeSI5ORlWqxUDAwM4c+aMe8yL2AI9MzMTUqkUPT09oq67VVyTNs6fP++OuroucgsKCladB00mE44fPz6l0WjeQ0TDPtjyVQUXViKh1Wq/9Ic//OHcT37yk1UmN67C5+7uboyNjaG7uxtVVVWiioSt4vKJiouL85nru1wuR3l5OUJCQjAxMSHqSXhmZgZWq1VwQSlU0TrgqK8SQrhfDlYLLoSIWrlEsBADfxljSEhIENx/KT09HcPDw6LVHBERgoOD0dXVhfz8fGRnZ/sklcwYQ1FREQwGg6jCcjvEx8ejqKgIFy5cwPT0NOrr65GZmbkqwkdEeP/73z87Pj7+FbPZ/E/f7PbqggsrkSAi0mg0tz388MPDZ86cueQSmTGGwsJCqFQq9PX14eDBg7t6HAgAdHV1ISAgwOfzCS0WC5RKJQ4fPozJyUk0NjYKkt5ZSVdXl+B2DlarFTMzM4KJN71eL4jP1+USsQKErbMSKmqVkpIieDpQLpcjJSVFFHdyg8GAM2fOuOflDQwM+DQVxxhDeXk5xsbGBDVl9QYKhQL79+/H+fPnERIS4vEi97HHHls4ffr0q1NTU0/6YItXJVxYiQgRLWi12hvvuOMO9fK2WSJCW1sbIiIi4O/vv+v/mIeGhrCwsID8/HxfbwUXL15EdnY2wsPDsX//fiQkJODs2bOCXtHrdDrIZDLBOw9dtVVCXbkLFbG63ISVEN5Q0dHR2zZ13Ijg4GAADkdtIUlLS8P4+LggkTfAUUrQ29vrtkfJyclBQkICAgICBBeOG+EyEO3q6hK0WWCnEJF7lNbs7CzGxsYuefzll1+2PvHEE10ajebDPtriVQkXViJDRGNKpfLm66+/XqdWq92DigMCAlBaWoqKigoMDAyI5oC8VZRKJSYnJ1FWVubzrq/JyUkQEZKSktz3JSYmorq6GuPj44JEr1yeOrm5uV49rieE7AZ0fVgKUbt1OaUCAwMDBYlYKRQKQR299+zZs+pD1NtIpVKkpaVte/TMehgMBpw9exZEhMOHDyM8PNz9WEFBgfvizZe4upBbWloEF7Hbpbe3F3a7HQUFBTh48CAmJibcdhk1NTV0zz33DDuL1YVRxxyPcGHlA4ioeXJy8r3XXnvt9N/+9jfExcW5W/ZdbsAdHR1bHvcgNFNTU+jt7UVFRYVo5ptrYTKZ0NPTg+Li4lWP+fv748CBA4JErzQaDYKDgwXvgJyfnwdjTLDIz9TUlGApRpPJtOtT2S6ESgXK5XIQkWDRHledldApsz179kCtVntt/uHyKFVxcTFycnJWdfHKZDIUFxejubnZ5915QUFBKCsrQ319vddnQO6UkZERzM7Oori4GIwxyGQyVFRUYGFhAS+99BLuuOOOSa1Wew0Rzfh6r1cbXFj5CLPZ/HelUnn/l770JWN8fPwljwUEBODAgQNobm7eNVdKc3NzaG1tFcwAdCsQEVpaWlBQULDurDBX9GpychIXLlzY8WvpGv6ak5Ozo+NsBiGL1gFh/KuAy8fDyoVQqUDAEbUSKo0kk8kQGRkpWLrRhUQiQWZmJnp7e3d8LK1Wi9OnT3uMUq1EoVAgMjJyS07jQhEREYH8/HzU19fvGgNRpVKJ8fFxlJeXXyJMJRIJIiIi8OlPf3parVZfT0STPtzmVQsXVj5kZmbm2YGBga/efvvtMys9Y4KDg91XSr4etWAymdDQ0IDy8vJdkeIZGRlBUFDQpvyj/P39UV5ejoyMDDQ0NKC7u3vTs8lWMjk5icjISMHrh4gIKpVKUP8yoSJWl4Pj+nICAgIEE1ZRUVGCCh8xPK0Ah+P71NTUtiN7i4uLaGhowNDQEA4cOOAxSuWJ3NxcTE5OwmBY5VIjOrGxsdizZ49Hz0Gx0ev1a2YOdDodrr/+et34+PhxItrdnhFXMFxY+Ri9Xv/dCxcu/PKee+4xrAx7R0REuEctCJVS2Air1er2RgkLC/PJHpYzPz+P4eHhLRfOR0dH48iRI5DL5Th9+vSW56HZ7Xb3TECh0Wq1UCgUgqVbrVYr7Ha7IALocipcB4SNrAnlwO4iMjISRqNR8HMDYww5OTlb9nay2+3o7+/HhQsXkJKS4p6asFlcg5pbWlp8LmYAh5CNiIjY1EgZoTAYDGhra/OYOZifn8d11103NTEx8UEiqvPJBjkAuLDaFWi12gdeeeWVv3z1q19dlauKiYlBRkYG6uvrtx1p2S52ux0NDQ1IT08Xzf14PVzeWcXFxdsytZRIJMjIyEBVVRUmJiZQW1u76fTg2NgY4uLiRKkdEjoNKITbuovLqXDdhUwmE0Sc+Pn5wW63C5Y+Yoy55wcKTVxcHObn52E0Gjf1fK1Wi5qaGthsNhw5cmTbg5PDwsKQmJiIlfNWfUV2djaICH19faKvPT8/7x4dtvJvzGKx4KabbpoeHR190GQyvS765jiXwIXVLoCISKvVvu+pp56qf/rpp1dVSCYlJSEpKQl1dXWiiSsiQmtrK6KiojxOR/cF/f39iIqK2rEoCAgIQHl5ObKysjaVHrTZbBgcHERmZuaO1t0MFosFc3Nzglo5COVfBVx+EStAuAJ2QNg6K8DhWC7GXD/GGHJzczeMWi1P+1VUVCAnJ2fHkdeMjAxMT08L2mW5WRhjKC4uxvT0tKiWEAsLC6ivr0dZWdmqxhm73Y4777xztrOz83szMzO/EG1TnDXhwmqHMMYCGGN1jLFWxlgHY+wrKx5/kDFGjLF1P8mIyKrVam/+4he/2P3KK6+susTdu3cvEhISRItc9fT0QCqViiImNsPs7CyUSqVXC8ejoqLc6cGamhqMjo56DPEPDw8jOTlZlNqh8fFxJCcnC5qi0uv1gnUEXo4Rq8DAwMu2ziowMBAymWzTkaSdEB0dDYvF4rFb2WKxoKura9tpv/VgjKG0tBQXL17cFcXjEokE5eXlGBkZgUajEXy9hYUF1NXVoaSkxOMF16c+9SljTU3Nb3U63Tc2OhZjLIUxdpIx1uX8vPqk834FY+xNxlif899I7/8kVw9cWO2cJQDXEVEJgFIAxxljVYDjTQzgRgCburQhokWtVnvsox/96MhKd3bAMR8qLi5O8AnsIyMjMBgMKCoq2hXdXTabDS0tLYIMWHalBw8dOgSj0YiamhqoVCq3wLJYLBgdHUVaWppX110Ll7ASCqvVCpvNtm435U7gEatLEbrOChCviB0A8vLyLknL2Ww293y/gIAAHD16dNtpv/UIDg5GWloaOjo6vH7s7eCyNujs7MTs7Kxg6ywuLrqH3EdGrtY6jz322MLzzz//D61We98mD2kF8BkiygNQBeATjLF8AP8F4O9ElAXg787/c7YJF1Y7hBy4JoXLnTeXKHocwGeX/X8zx5vWarXX3H777RNNTU2rHk9LS0N0dLRg4kqtVmNsbAzl5eW7QlQBjmHHycnJghbP+/n5oaCgABUVFVAqlTh79iz0ej0GBwexd+9erw8q9oTBYICfn5+gdVzT09MeT9DegkesLsXf398tZoUiLi4OGo1GlALviIgISCQS6HQ6jI6OXlJHlZaW5vULn+Xs2bMHJpNp10ym8Pf3x/79+9HU1CSIMF9cXMSFCxdQXFzssfzh6aefXvr+97/frNFo3k1Em/rlE5GSiJqcXxsBdAFIAvAOAL9yPu1XAG71xs9wtcKFlRdgjEkZYy0ANADeJKILjLFbAEwQUetWj0dEE2q1+pqbb755sqWlZdXjGRkZUCgUXhdX09PT6Orq2hUGoC70ej1mZ2eRnp4uynqBgYEoKytDSUkJ+vr60N/fL1ih90pGR0cFc1p3IWR9FeCozRPyw1UIhIxYAcLXWUmlUkRFRYmSliIixMTE4MKFCzAYDDh06BCys7NFufBgjKGkpASdnZ2izAPdDCEhISgtLUV9fb1X9+QSVUVFRR7PPz/72c+WvvjFL7Zqtdobt+uqzhhLBVAG4AKAOCJSAg7xBWBjLxvOmlxeZ8BdChHZiKgUQDKACsZYMYCHATyyg2MOqtXqa2666SZlW1vbqsczMzMRFRXltZqr+fl5tLS0oKKiQrA00VaxWCxoa2tDaWmp6NGz0NBQhIaGIj09HR0dHYJdlbqw2+3QarVYaRbrbYSsr7JarbtGkG8FISNWgPB1VoCjBlPodKBer8fZs2cxMzODmJgYxMTEiH6uCAgIQG5uLlpbW33uyu4iMjISOTk5XjsXLxdVnv5Wf/WrXy19/vOfb9NqtceIaFtvXMZYCICXAHyKiHxvFHaFwYWVF3GODvgnHGHVNACtjLFhOARXE2NsS5+aRNSvUqmu/bd/+zdVZ2fnqsczMjIQExOz4z/opaUld8fJbqqP6ejoQHp6uk/2tLi4CJ1Oh9zcXFRXVyMpKQkNDQ1obm7G3NzcxgfYImq1GjExMYJGe2w2GywWC/z9/QU5/uLi4q56/2wWqVQqaBpNjDqr8PBwmEwmr49dISJotVqcP38eAwMDKCkpQVlZGQoLC9HT0+MTcZOQkACpVCqKzcRmiY+PR1JSEpqamnb0miwsLLjTf55E1bPPPmt+6KGHOrVa7bVEtK0rPcaYHA5R9SwR/cF5t5oxluB8PAGO7Atnm3BhtUMYYzGMsQjn14EAbgDQTESxRJRKRKkAxgHsI6KtuVICIKJepVJ57MYbb1R78nJJT09HXFzctsWV1WpFfX098vPzBW3x3yoqlQpms1nw1Nha9Pb2IisrC4wxMMYQFxeHI0eOIDExEa2traivr/fqLEehvasA4eurFhYWLrv6KhcSiUSwOqiAgABYLBbBu3mTkpK8Zr1ARFAqlThz5gxGR0fd9YeuVv+goCBERERgctI3E1OKiorQ398vaKRxq6SmpiIkJATt7e3bElfz8/Pu7j9P6b/nn3/e8ulPf7pLq9UeJaJtzedijtD/zwB0EdH3lz30JwAfdH79QQCvbOf4HAdcWO2cBAAnGWMXAdTDUWP1mjcXIKLuycnJ666//nq1p8hVWloaEhISUFdXt6V2ZLvdjsbGRuzZs2dT42HEYmlpCV1dXSgpKfFJAf38/DwMBsOqkTIugXXo0CFkZGSgp6cH58+fh06n29FV6tLSEpaWlgR3the6vupy7Ah0IXSdVWRkpOBD1ZOTk3ccxbHb7RgbG0NNTQ00Gg3Ky8tRXl7u8b2ZnZ2Nvr4+n7iiy+VyFBYW7opBzcvJzc2FxWLZ8ozDubk51NXVobS01OPFz+9+9zvL/fff363Vao8sa5baDocA3AXgOsZYi/N2M4DHANzIGOuDo5P9sR2scdUjfMXhFQ4RXYSjAHC956R6YZ1OxtixG2644R9vvPFGfGFh4SWP7927FxKJBLW1tZuqkyIitLW1ISIiQvBIyVZwGZPm5eUJlrLaiO7ubuTk5Kwr6hQKBSorKzE7O4u+vj50d3cjMzMTcXFxWxaDQlssuNDr9di7d69gx19cXBSsfktoXHVWK80XvYWrzkrI18ff3x8BAQGYnZ1dd8CxJ2w2G0ZHRzE8PIy4uDhUVlZu2J0aEBCA2NhYjI2NCfq+Wovo6GioVCoMDQ2J1tyyES7PrQsXLiAgIGBTf9czMzNobm7Gvn37PP7ennnmGfMDDzzQ6YxU7ciwjIjOAFjrBHX9To7N+Rc8YnUZQURdSqXy2re85S3K1tbVzYYpKSnIysrC+fPnN7z67uvrAxEhOztbqO1ui7GxMfj5+QlexL0WBoMBJpNp0yN8wsPDsX//fpSVlUGtVruNRjeb9iEiUYSV3W6H2WwW1MqBR6zWRow6K2DrnlZLS0vo7e1FTU0NLBYLDh8+jPz8/E2/TzIzMzE4OCj6uC0XeXl5GBsbE8UgdbNIJBLs378fg4ODGzYtaLVad9OQJ1H1y1/+cumBBx5o12q1h3cqqjjiwYXVZQYR9SiVyqPHjx+fbG5uXvV4XFwcioqK3O3QnhgbG8P09DSKi4t3jVcV4PhgHhwcREFBgc/20NXVhby8vC2/LsHBwSgpKUFlZSUWFhZQU1ODzs7ODWtAZmdnERQUJHh31czMjOA1dJejh5ULoTsDAwMDYTabBU+bxcbGQqfTbbjO9PQ0mpqaUFtbCz8/Pxw9ehTZ2dlbni7g5+eHpKQkDA8P72DX20cqlaKkpGTXDGp2IZfLUVFRgfb29jXPwxMTE+jq6sLBgwcRHBy86vGf/vSnps997nMXnem/bdVUcXwDF1aXIc5uwSM33XTTRF3d6iHmCoXCbVy38ipZo9FgeHgY5eXlu8pvyDVguaioSJTRMZ5wzSLbiW+Vqx38mmuuQVhYGBoaGlBXVwetVuuxFkSMonUAgqehAEc6SQw/IyEQOmIFOKKbQtdZSSQSxMbGQqVa3Sdjs9kwNjaG06dPo7+/H3v27MHRo0eRmpq6I5uM9PR0jI6O+mzcTEREBGJjY9Hb2+uT9dfCNZO0sbFxlWgfHBzEyMgIDh486LHk4Uc/+pHpC1/4QqtGo7lmu91/HN+xez5ZOVvC6XN16O1vf/vwX/7yl1WXaqGhoaisrER7ezuUSiUAR3Sks7MTFRUVu+4DcHBwEBERET6t0enu7kZubq5XjiWRSJCcnIwjR44gOzsbExMTOHXqFPr7+91GgjabDXq9XpTGAZ1OJ2jhut1u31XRz60idMQKcNQECe1nBaxOBxqNRrS3t6Ompgbz8/PYv38/Dhw4gOjoaK/8zmQyGfbu3bvlgm1vkpWVBZ1OJ6gR63YIDQ1FcXEx6urqYLFYQETo7OzE1NQUqqqqVl1EEhEeeeSR+S9/+cvnnZYKu6ftkbNpdtenK2dLENEIY+zABz7wgVPf+973Mu+6665L8kmBgYE4ePAg6uvrMTc3h/HxcRw4cMBnReFrYTAYMD4+jsOHD/tsD1qtFv7+/lsu+t0MERERKC0thcViwdjYGM6fP4+QkBAEBQUhNjZWcEHiqq8SMk13OacBAUfqRuiIS3R0NDxNUvA2oaGhMJvNGBwchFKphEQiwd69e5Gfny9YlHrv3r04ffo00tLSfGIwLJFIUFpaioaGBhw5cmRXGdVGRUUhKysLdXV1CAoKgkwm8zgyzGaz4WMf+5jhtddee12r1b6fiHxTuMbZMTxidZlDRDqtVlvxmc98puHb3/72qpCxn58f9u3bh76+PigUCo+5fF9it9vdA5Z9dTIkIncnoJDI5XKkp6fj6NGjSEtLw9jYGJRKJdrb2zEzMyNY2/jMzIwggnE5l3PhugvGmKB1OoGBgTCZTIKtYbfboVar3aknlUqF0tJSHDx4EImJiYKm/qVSKdLT09HX1yfYGhsREhKCvXv3wpMlja+JjY3F0tISZmZmUFBQsEpULS0t4ZZbbpl59dVXf6LRaP6di6rLGy6srgCIaF6r1V773e9+9++f/OQnjcs/oG02G5qamlBWVua2WNhNvi89PT1ISEgQ/IN/PVQqFcLCwhASEiLKeowxBAYGIigoCNdddx2io6PR19eHU6dOobe31+u1PkKOsXFxuUesAEdNjMlkEnSN8PBwzM7Oeu14RITp6Wm0tbXh1KlTUKvVSE9Px7Fjx2A2m0UVuykpKdBqtYK/huuRmpqKubk5UeYmbhaz2Yza2lpkZGQgNjYWXV1dlzxuMBhw9OjR6dra2q9qNJoHaTedoDnbggurKwQismi12lufe+65597znvfMuvL5TU1NSEpKQkJCAkpKSiCXy9HQ0OCzQtPlTE1NQa/XIzMz02d7ICL09vaKbjsxNjaGlJQUSCQSxMfH48CBAzh06BACAgLQ0tKCM2fOYHh42CuDXYU2BgWujIiVGAXs0dHRXrFdmJ+fR09PD06dOoXBwUHExsbimmuuQXFxMSIjI+Hn54fQ0FBRa44YY8jOzkZPT49oa3raQ2lpKTo6OmCxbGs2sVdZWFjA+fPnkZmZ6U7HLi4uYnBwEIDjoq6ysnKqq6vr43q9/nEfb5fjJbiwuoIgIrtGo7nnH//4x/duuOGG6bq6OoSEhCA1NRWA46STl5eH2NhYnDt3zqfjIKxWKy5evIiysjKfFj2Pj48jOjpa1GgLEWFychKJiYmX3C+Xy7Fnzx5UV1ejvLwcVqsVtbW1OHfuHAYGBjA/v/WOayISZYYfF1abY7sDmV2Rqa6uLpw6dQoXL15EUFAQDh8+jPLycsTFxa1K9W3V08obJCQkYHZ2dlvvVW8RGBiI7OxsXLx40Wd7ABwNI665fy5fPsYYysrKoFKpcPbsWVRVVekGBgbebTAYfufTzXK8Ci9evwLR6XRfi4yMVH7kIx/5wcmTJ1d92u3duxchISGora1dcy6V0HR0dCA1NdWnNV92ux0DAwM4ePCgqOtOTU0hLCxsXVuJwMBAZGZmIjMz010vc/HiRZjNZsTExCA+Ph6RkZEbitLtuHBvhyshFRgYGCi40WRQUBAWFxdBRBv+7mw2G7RaLVQqFaanpxEWFoaEhARkZmZuypIkOjoa7e3tsFqtonUBM8aQm5uLnp4e7Nu3T5Q1PZGUlASlUunxAkYMhoeHMTY2hqqqqlV/F1KpFDKZDLfddtvM+Pj4jUTUIvoGOYLChdUVyvT09E+DgoKUVVVVv/zHP/4RvdIrKSoqCpWVlWhoaEBqaqqoY200Gg0WFxdRXFws2pqeGBkZQXx8vOhdklv1rgoMDERaWhrS0tJgtVrdXmStra2IiIhAfHw8YmJiPH54iuFfBQAWi8Vn/mPeIigoCGq1WtA1GGMICwvD7OysR8NWk8kEtVoNlUqFxcVFxMTEICUlBcXFxVsuPmeMISEhAUqlUtRh5jExMejr64PBYBB8/uV6FBcX4+zZs1AoFIJOHFiO3W5He3s7LBYLqqurPTbk/O1vf7O/733vG9doNMeIaFCUjXFEhQurK5iFhYUTjLG3VVdX/+nEiROxJSUllzweFBSE6upqNDc3w2AweOxW8TZmsxkdHR04ePCgT1OAVqsVw8PDols8WK1WzM7OorS0dFvfL5PJkJiYiMTERHd6SKlUore3FzKZDFFRUYiOjkZkZCSkUin0ej1WzpX0Nq5a28vZxwoQx8sK+FedVUREBMxmM/R6PXQ6HaampiCVShEfH4/8/HyvzC1MSUlBa2urqMLKVXLQ3d2NiooK0dZdiZ+fHwoKCtDS0oLKykpRzm0NDQ2IiYlBUVGRx/WeffZZywMPPDDgNP7cPRX2HK/ChdUVDhFdYIwdectb3vLXp556Kvn222+/5Hcuk8mwf/9+9Pb2ora2Fvv37xc08nDx4kXk5OSIdgW5FkNDQ0hJSRE9yjI5OYmEhASvnOQZY1AoFO5U7tLSEnQ6HSYmJtDe3g65XA6j0YjFxUUEBAQIZmdhMpl8/vv0Bn5+fl5pFlgP11ibwcFBjI+PQyKRICoqCnFxccjLy/N6yi44OBhEJHoNnEKhgN1ux/T0NCIjI0VbdyUuF/qRkRF3rakQGAwGNDU1IS8vD3Fxcaset9vt+OxnPzv361//ulGr1b6dz/27suHC6iqAiHoZY2Uf//jHT7S0tBR/9atfDVmeVmCMIScnB5OTkzh79izKy8u9crW8kvHxcTDGfFLzsByLxYLx8XEcPXpU9LXHxsZQVlYmyLH9/f2RlJSEpKQkAA7T0+7u7kuEVnR0NCIiIhAREeG1FOiVUF8F/Cvitpn6p83gEjSzs7PuDliXkAKA6upqUYS9q4jdW1MFNkteXh46OjpQXV0t6roryc/Px5kzZxATEyNITadKpUJ3d/ea502DwYB3vvOdM21tbb/SarUPENHuGWrIEQQurK4SiGiGMXb0Jz/5yVONjY3v+f3vfx+x8iSTmJiIkJAQNDY2Ij8/36ujVhYXF9HX1+dTd3UX/f39SEtLE92QdH5+Howx0SIHBoMBKSkp7it1k8nkTju5RusEBQW5hVZ4ePi2Ik9XQkegC39/fywtLW35dXCJqJmZGfdt+esbGxuL3Nxcd0RqYWEBCwsLojQWJCQk4PTp08jJyRE1XRseHg4/Pz9otVrExMSItu5KZDIZiouL0dzcjEOHDnntNSAi9PX1Qa/Xo7q62qPj/MDAAI4fP67XaDSfmp2dfcYrC3N2PVxY7XIYYwEAagD4w/H7+j0RPcoY+xqAdwCwA9AA+BARTa53LKeb772RkZEN5eXlj/31r3+N2rt37yXPCQsLw8GDB9HQ0ACDwYCMjIwdn4iICC0tLSgsLPR5gfPS0hLUarVPolViDVx2odfrkZ+f7/5/QEDAJRGt5WJAp9NhYGAAS0tLbjEQGhqKkJAQBAcHrytCFxYWdp2j/3ZxWS6sJ6wsFgvm5uYwNzcHg8HgFlHBwcEIDw9HdHQ0MjMz140IuuqsxBBWMpkMkZGR0Ol0oguc3NxctLS0eG0u4XZRKBSIiopCX1+fVzzrrFYrWlpa4O/vj8rKSo+NBX//+9/t73//+1UqleoWImrc6JiMsRQAvwYQD8d5/Wki+gFj7N0AvgwgD0AFETXs+AfgCAoXVrufJQDXEdEcY0wO4Axj7M8AvkNEXwIAxth/AngEwL2bOeD09PRPGWPtBw8efPn555+PO3LkyCVnPH9/fxw8eBAdHR2oq6tDWVnZjuZ/DQ8PIyQkxKdXrS56e3uRmZkp6HgPTxARVCqVaEakRIT5+fl1BQ9jDMHBwQgODl4ltmZnZ2E0GqFUKjE/Pw+bzQZ/f3+EhIS4b8HBwW77AKENSMXCVcBus9kwPz+Pubk5979zc3Ow2WyQyWTunz8mJmZDEeWJqKgodHV1IT09XaCf5FL27NmDoaEh0f8GXe8VlUqFhIQEUddeSU5ODs6cOYO4uLgdCVqDwYDm5makpaV5vFAiIjz55JOmb3zjG/1arfZGIlJt8tBWAJ8hoibGWCiARsbYmwDaAbwLwP9te9McUeHCapfjHG8w5/yv3HkjIjIse1owgC2NQSCiWsbY/ttuu+1vX/va19LuueeeSz4ZJBIJioqKoFQqce7cORQXF2/L72pubg4jIyM4cuTIlr/X2ywsLGBqakrwLjlPaLVaKBQK0dKPRqMRoaGhW44SLBdbyyEimM1mt8DQarUYHh7GwsIC5ufnMTs7i+DgYPj7+yMgIMB9c/3f15FKF66fY2lpCSaTadXNYDDAarWiv7/fLZ5cFwXBwcFe+zlCQkIwPz/vtXqujYiMjMTFixd9YouRk5ODuro6xMfH+zRqJZFIUFZWhqamJhw+fHjLf4tEhNHRUQwPD6OsrMyjlYTZbMbdd989+8Ybb/xDq9XeSURLWzi+EoDS+bWRMdYFIImI3gQu/67bqwkurC4DGGNSAI0AMgE8RUQXnPd/A8AHAMwCOLbV4xLRBGNs3yOPPPJiY2PjkR/96EdhK7uSXHP8mpqaEBcXh8zMzE3/gdvtdjQ3N6OkpGRXTJvv7e0Vvc7ExejoKDIyMkRbz9v+VYwx+Pv7w9/ff9VxT548iaqqKphMJrdgWVxcxMzMjFuwuEYoMcYgk8ncJomeblKpFFKp1P17YoyBMQaLxQK1Wg0icls8EBGsVitsNhusVqvHm+sxF35+fpeIvuDgYERFRSEgIADz8/NQqVSCe6wxxhASEgKj0SiK1xNjDElJSZiYmBC0O84TgYGBiIqKwsTEBJKTk0VdeyWhoaFITk5Gd3c3CgoKNv19FosFra2tkMlkOHTokMfuTa1Wi5tuumlqZGTkuzqd7rGdzPxjjKUCKANwYbvH4PgOLqwuA5y1UaWMsQgALzPGComonYgeBvAwY+zzAO4D8Og2jr3IGHv7H//4xy+3tbXdf+LEiciVkSmX31VXVxcuXLiAsrKyTaU++vr6EBsb69N2axeuSIunVmihcdXkeDKEFAq9Xo+cnBzB13FFXPz8/DaVLnYJobXEj9VqxdLSEmw2m/v5rs8nm82GqampSwQXALcgCwoKukScrRRrmxHUEonEPcdNaKKioqDX60Uz0UxOTkZjY6PowgoAsrKycP78eSQmJoqehl9Jeno6zp8/D51Ot6kU9szMDFpaWpCZmbmmMGxtbcXb3/52rUaj+YDJZPrLTvbHGAsB8BKAT63ITHAuE7iwuoxwdvb9E8BxOPLuLn4L4AS2IaycxyUAj4aEhDSVlpb+5MUXX4yprKy85DkSiQQFBQVQq9U4d+4cioqK1j0pzczMQKPR4NChQ9vZktfp7u5Gbm6uT6JV4+PjSE5OFm1tIsLc3JwglhkrMZvNW6q/Y4xBLpdvKx2lVquRl5e35e/bCgEBATCZTIKu4SI6Ohq9vb1IS0sTZb3AwEDIZDJ3mlhM/P39ER8fj9HRUZ8Iu+W4BjXX1dXh0KFDa74XiQhDQ0MYHx/H/v37ERIS4vE5P/3pT5e++MUvTmo0muNE1LvDvcnhEFXPEtEfdnIsju/gQ5h3OYyxGGekCoyxQAA3AOhmjGUte9otALp3utbc3NwrY2NjlbfcckvXt771rUW7fbXdSlxcHKqqqtDT04Pu7m54inbbbDa0traitLTU51engEPkWSwWnxVYu4SVWMzNzSE4OFgUIXeleFi5WO5lJTShoaEwGo2irOXCF4OZXWRkZGBoaMgdjfQlQUFBSE9PR3t7u8fHzWYz6uvrMTc3h0OHDnkUVUajEe9617tmvvSlL53QaDRFXhBVDMDPAHQR0fd3ciyOb/H9px5nIxIAnGSMXQRQD+BNInoNwGOMsXbn/W8B8ElvLEZEQxqNpvSJJ574zbFjx6Z1Ot2q5wQGBroHF587d27VGJCuri6kpKSIflW8Ft3d3YJHOtbCYDC4a3rEQq/XiyYiryQPKxdyuRwWi0XwdVyNAvPz84Kv5SIuLg4ajQaeLpqERi6XIyUlBUNDQ6Kv7YmUlBRYLBYolcpL7p+amsK5c+eQnJyM4uJij/WhLS0tKCkp0Z08efIBlUp1GxF545d4CMBdAK5jjLU4bzczxt7JGBsHcBDACcbYX72wFkdAeCpwl0NEF+EoYlx5/20CrmkGcE9QUNBrpaWlP3322WdjrrnmmkvCHxKJBLm5udBqtaitrUVeXh7i4+Oh1WphNBq3VBgqJC63azHrm5YzNjYm6pw2wFG4Lpatw5UWsQL+ZbmwE4uRzRIVFQWdTucxIiIEUqkUUVFR0Gq1Pqk3TEtLQ01NDfbu3evzTlHGGEpKSnDu3DkoFAr4+fmhr68ParUaFRUVHi8YXFYK3/zmN8c1Gs1bdxqlWnHsMwDWCjO/7K11OMLDI1acNVlYWHh1YmKi/N3vfnfbI488Mu8phB8TE4Pq6mqMjo6ioaEBbW1tKC0t3RWtwUTk02iV3W6HRqNBfHy8aGsSkag1NFdixMplEioGLqNQMfFlOlAqlSItLQ0DAwM+WX8l/v7+yMvLQ2NjI86cOQO73Y5Dhw55fE/PzMzgpptumv7mN7/5e2+k/jhXLlxYcdaFiMa1Wm35j3/8458cOnRoSqVa7XXn7++PAwcOuNvqDYbd0cii0WgQGBjos5SkRqNBdHS0qHVm8/PzCAoKEk3YXonCKjAwUDRhFRYWBoPBIGqdVUREBBYWFgQfOL0We/bsgUqlwtLSpi2eBMN1ITI7O4uYmBjk5uZ6/Hu9cOECiouLtWfOnPm4Wq2+i4jE6XDgXJZwYcXZECKyajSaTzc1Nb1337596jfeeGNVgYZSqYS/vz+OHDmCkZERNDU1iVKnshZEhJ6eHtEHzy5H7BE2gLj1VYBj/qCY9WNi4HKTFwPX7EixhJyL5ORkjI+Pi7qmC4lEgszMTPT19flkfRdGoxFnz56F1WrFddddB5VKter3YLfb8dhjjy3ecsstXWNjY1Vzc3O/89F2OZcRXFhxNo3ZbH5TqVSW3nXXXY0PPvjgnMt00WQyoaenByUlJQgMDMSBAwcQGxuLM2fOQK1W+2Svk5OTiIiI8Fk0xWWUKcYsuOV42xh0I4hoV3R+ehOxhY6rzkpMfCmsACApKQl6vV40Absc1/DkpqYmFBYWIi8vD/7+/igqKkJzc7M7eqjT6XDddddNP/7447/RaDSlRCSOwRnnsufKOiNyBIeIVBqNpupXv/rVEyUlJfr29na0trYiPz/fXezLGENycjIOHjyIkZERNDc3ixq9stvtXhu2ul3EtlgAHB8YBoNBNDFntVp3haO+t3EVr4uFL+qsXK7zs7Ozoq7rgjGGnJwc9PT0iLru8ijVkSNHLmlqiYqKQkREBAYHB/HHP/7RWlxcrK6rq/uQWq2+x9nQw+FsCi6sOFuGiOxarfZLnZ2d1914441DzzzzjMVTlCQgIAAHDhxATEyMqNGrsbExxMbG+ixFRUQ+EVYLCwsIDAzk9VU7RCKRiFrzFB4e7hOB48sidsBh/eCaiCA0RIT+/v5LolSeIq0xMTG45557zPfee+8/lEpl4cLCwp8E3xznioMLK862IaKLKpUq53e/+93jJSUl+s7OzlXPWR69Gh4eFjx6ZbPZMDg4iMzMTMHW2IjZ2VkEBQWJ0q6/HLHrqxYXF69IYQU4uteWzxcUEsaYqAXzLmJjY6HT6XziaQU4fu7c3Fx0d+/Y23hdXFEqi8WCw4cPr2m98sc//tFWWlqqPnfu3F0qlerfiEjc/CznioELK86OICKLVqv9XGdn5/XHjh3r/9rXvrbg6QMpICAAFRUV7ujV6OioIFGB4eFhJCUliS5qluOLonVA/PoqV4TsSkTsdKAv6qwkEgliY2PhqdNXLKKjo2E2mwWJ2FmtVnR2dqK5udkdpfKUup6amsK73vWumXvvvffvSqWyaGFh4QWvb4ZzVcGFFccrEFGrRqPJ/+EPf/hUaWnputGrw4cPw2Aw4OzZs5iZmfHaHqxWK0ZHR5Genu61Y24Vm80GvV6P2NhY0deenZ0VtVj+Sk0FAr4pYBe7zgrwfToQAPLy8tDV1eW14xERJicncfr0aQQFBa2qpVrOn/70J1tRUZHmjTfe+A9nlErrtY1wrlq4sOJ4DSKyaDSaz3Z0dNxw7Nix/q9//eseo1dyuRyFhYUoLi5GR0cHLl686BVPnYGBAezduxcyme8GCqhUKsTFxYlukLqwsICAgABRO/SuRNd1F2JHrCIiIrx6kbFZQkNDYbFYRBs87YnIyEhIJBKvCEuj0Yjz589Do9GguroaqampHv8WXVGqj33sYycnJycLuY0Cx5twYcXxOkTUotFoCp588skflZWV6de6Gg0LC0N1dTUiIyNx9uxZjIyMbDs9aDabMTk5ib179+5k6zvGV2lAseurAB6x8iYSiQQBAQE+sR9ISUnB2NiY6Osux1Vrtd2/f6vVio6ODrS0tCAvLw+lpaXw9/f3+NxlUaqPq1SqG3mUiuNtuLDiCAIRmTUazUPt7e03HDt2rP+RRx6Z93RVzBhDSkoKDh8+7C4y3c6Ve19fHzIyMnza/r+4uAibzSba3LfliF1fBThsLa5EuwVA/IgV4Js6K8DhKTUxMSFqJ+RKwsLCEBgYCK12axqHiDAxMYHTp08jODgYhw8fRmRkpMfnKpVKvPOd75z56Ec/enJycrJobm7uOW/sncNZCRdWHDeMsQDGWB1jrJUx1sEY+4rz/u8wxroZYxcZYy8zxiI2e0wialGr1fk/+tGPHsvNzdW9/vrrHluQdpIeNJlM0Gq1og87XokvBi67mJ2dFXXQtM1mu+KMQZfjCzd0X/hZAY6/vdDQUExPT4u+9nJycnK2FLVypf20Wu26aT+r1Yrvfve7prKysonXX3/9Q2q1+kYi0mxmDcZYCmPsJGOsy3lO/KTz/m2fEzlXPlfumZGzHZYAXEdEJQBKARxnjFUBeBNAIREVA+gF8PmtHJSILDqd7usjIyOld9999xs33HDD1PDwsMfnrkwPDg8Pb9gO3tvbi+zsbJ8OfnYVzCYmJoq+9uLiIvz8/Hh9lReRyWTwNHRcSHxVZwXsjiL24OBgREREQKlUrvs8s9m86bTfqVOnKC8vT/ftb3/7h2q1OmtpaemVLW7LCuAzRJQHoArAJxhj+djhOZFzZcOFFccNOXC59cmdNyKiN4jIVYVeC2BbzpdENKFUKm86efLk7VVVVcNf+tKXNkwPLi4uoqamBpOTkx6vZOfn5zEzM4OEhITtbMlrTE1NISwsDHK5XPS19Xq96GnAK11YAY73oZgeTxKJBH5+fj4pJI+Ojsb09LRo3l1rkZ2djd7eXo+vu9VqRV9fH86ePYvQ0NBNpf3e8573nOvv76/UaDSfJaIt53aJSElETc6vjQC6ACR565zIuTLhwopzCYwxKWOsBYAGwJtEdGHFUz4M4M87WcNms51Uq9XZ//u///tYTk6O7sSJE2umB/Py8lBVVQWdToczZ86sqsFwDVr2ZbQK8F3ROsAL14XCV3VWvkgHMsaQkJCwYbRIaAICAhAbG3vJHEO73Y7h4WGcPn0ajDEcPXoUe/bs8fg3b7FY8J3vfMed9lOpVIe9NeOPMZYKoAyA18+JnCsLLqw4l0BENiIqheMKrIIxVuh6jDH2MByh8We9sI5Fp9N9fXR0tPTuu+9+4/rrr18zPRgQEIDi4mLs27cPIyMjOH/+PGZmZmAwGLC4uIiYmJidbmdHWK1WzMzMiB41cjE9PS1qfRVwdUSsrqYCdsDRHejrdCAAZGZmYmBgAFarFZOTk6ipqcHi4iIOHz6MzMzMNRsmTp06Rfn5+brvfOc72037rQljLATASwA+RUSGZfd77ZzIuXLwneEPZ1dDRDOMsX8COA6gnTH2QQBvA3A9ebF9iIgmANwklUqPVVZW/vxjH/tYzMMPPxzsac5fcHAw9u/fj5mZGXR1dcFgMKCwsNDn0SpXbZUv9mEymSCXy0XvzltYWPB5+lVofFHAHhkZifb2dlHXdBEcHAzA99FIPz8/RERE4OTJk4iNjUVVVdW6cz+VSiX+4z/+Y7q2trZDrVZ/0FsRKheMMTkcoupZIvrDsvsFOSdyLn94xIrjhjEW4+puYYwFArgBQDdj7DiAzwG4hYgE+aSx2WwnNRpN9o9+9KNvZWdna5955hnrWvUtERERyM3NRWBgIAYHB9Ha2upTg0NfdgP6or4KuLLnBLoICgoSPWIllUohl8uxtLQk6roufF3EPjMzg/Pnz8NqtUIikaCgoGBNUTU3N4dHHnlkvqysbPzPf/7z/1OpVEcEEFUMwM8AdBHR95fdL/g5kXP5woUVZzkJAE4yxi4CqIejxuo1AP8DIBTAm4yxFsbYj4VYnIgser3+G2NjYwUPPvjgr/Py8nR//vOf7Z4uBru6ulBSUoLDhw8jJiYGtbW16Ozs9IqD+1aYn58HY8xnIkOn04leXwU4all8UagvJr4YjAz4rs4KgLvOSuwAjNFoRENDA7q6upCXl4cDBw4gNTUVg4OrdZLZbMaTTz65lJ2drf7hD3/4qFqtzvBm2m8FhwDcBeA657mvhTF2M0Q6J3IuT3gqkOOGiC7CUZy58v5MkfehBXA3Yyz1wx/+8JNJSUnVTz31VFRlZSUAQKvVws/Pzz0XLzExEfHx8RgbG8O5c+cQFRWFzMxMUWqAfFm0DjjqqwoLCzd+ohe5WrIevkgFAg5hpVQqfWLdIZPJEBkZCZ1OJ0rt4vT0NPr6+mC1WpGVlXXJmqmpqaipqUFqair8/Pxgt9vx3HPPWb/whS9MLyws/EKn033d2aknGER0BoCnHP/rQq7LubzhwoqzayGiYQC3MMaKbr311v8tLCzMe/LJJxU6nQ5lZZfqP4lEgr1792LPnj2YnJxEfX09QkNDkZWVJZgTOhFBpVIhOztbkONvxNLSEmQymej1VSaT6YovXAccXakWi0X0dRUKBTwNMReLPXv2YGhoSDBhRUTQ6XTo6+uDVCpFdna2R9sEqVSK9PR09PX1YWxsjD71qU/pZ2ZmXlWr1Z/jY2g4uxkurDi7HiJqA3CYMXb4+uuv/8mBAwdSn3rqqQBPgokxhqSkJCQmJkKr1aK1tRV+fn7IysryeuecVquFQqHw2VgXX9VXLSwsXBXCytWMQESiNiZIpVJIpVKYzWb4+fmJtq6LyMhIXLx40evpXteFSH9/P4KDg1FYWIiwsLB1v2dychIf//jHTWq1+m9KpfJ+58UWh7Or4cKKc9lARGcYY/l/+ctfbikvL3/iPe95T9SXv/zlUIVCseq5jDHExsYiNjYWU1NT6Onpgd1uR1ZWFqKiorzyQTk2Noa0tLQdH2e76PV6xMfHi76ur7vGxCQgIMAnETpXnZUvOi8ZY0hMTPTaUHO73Y7x8XEMDg5CoVCgvLx8w/dPd3c3/vM//3Oqra2tW6VS3eu8uOJwLgt48TrnsoKIaGlp6RWNRpP5i1/84oH8/PzJRx99dGG9OWcKhQKVlZUoKCjAyMgIzp49C5VKtaNaIYvFAqPRuKbzsxhMTU35ZP2rwcPKhS+8rADf+lkBDk+rsbGxHR3DZrNhcHAQp06dwtzcHA4ePIji4uJ1RVV/fz/uvPPOmWuvvbbjzTffvFWpVB7ioopzucGFFeeyhIhsRqPxp2q1OuPxxx//r7y8vIlPfvKTRpVKteb3hIWFoby8HGVlZVCr1aipqcHw8PC2xnhMTEwgKSnJZx5aZrMZEokEMpn4QeerKWLlqwJ2hUKBqakp0dd1ERgYCJlMBqNx67Xhi4uL6O7uRk1NDaxWKw4fPoz8/Pw15/kBQEtLC9761rdOHTlypP2FF174d7VaXUREp3fyM3A4voILK85lDRGZDAbDD9VqderTTz/9idLS0qEPfvCDM57atF0EBwejpKQEVVVVMJvNOH36NNrb2zE/P7/pdX3pXQX4rr4K4BErMZDJZJBIJD4pnnexFSd2IoJer0dDQwMaGhoQHByMo0ePIjs7e906rdOnT+Pw4cP6m2++ufb1119/h1KpLLLZbH/mhpucyxleY8W5InAORP0NY+yZ3/72t2974403HquoqIj/+te/rigqKvL4Pf7+/sjOzkZmZiZUKhVaWloglUqRlpaG2NjYNaNRBoMBcrl8XTdoodHr9YiNjfXJ2ktLS+tGH64kgoKCfOYppVAofFZHBwDx8fHo6elBXl4eJBLP1+BWqxUTExMYGRlBcHAwMjIyNkxPExFOnDhBDz/8sF6r1TYqlcrPOq1eOJwrAi6sOFcUzivdVxljr/3pT386Ul9f/92srKz0b33rW1HV1dUev0cikSAxMRGJiYkwGAwYGhpCV1cXEhMTsWfPnlUCamxszKfeVYCjvionJ0f0dV2BBF+PERILX0WsACA6Oho6nc5nwkoqlSI6OhparRZxcXGXPGYwGDA8PAy9Xo/ExERUVFRseKFhtVrx4osv2h599NFpo9H4D5VK9TAR9Qv5M3A4voALK84ViVNg1cAxSHrf7bff/u34+PiSb3zjG1HHjx9nawmDsLAwlJSUwGq1Ynx8HHV1dQgMDERqaiqio6NBRNBoNMjLyxP151mOxWIBY8wnzue+sgDwFa6uQF+gUCjQ09Pjk7Vd7NmzB319fYiLi4PNZsPk5CRGRkYgl8uxd+9eFBUVbSiyTSYTfv7zn1v++7//e8ZkMv1Bo9F8lYgmRfoROBzR4cKK43MYYwFwiCB/ON6TvyeiRxlj7wbwZQB5ACqIqGE7xyeiJgA3MMay77777m8FBwcffeihh8Lf//73y9cqwpbJZEhNTUVqaiqmp6cxPDyMjo4OhIaGIjw8fM3UiBjo9Xp4spgQg6upcB3wnZcVALdw9uX4oPDwcBgMBjQ3N2NmZgbx8fHYt2/fpt4DSqUS//M//zP/i1/8Yt5isfxcp9N9h4i2XZHPGEsB8GsA8QDsAJ4moh8wxr4G4B3O+zQAPsSFG8eXMF4jyPE1zvBRMBHNOSfJnwHwSQCzcJws/w/Ag9sVVh7Wi4uKivqkTCb7f3fccUfQpz/96bDN+FFZLBacPXsWEokEEonEbUQqdr1RR0cHoqOjV6VnxGBychJGo9Enach//vOfuPbaa0Vf9+zZszhw4IBPInW++l3Pzc1hfHwcKpUKjDFERESgqKhowwsKIkJtbS2++c1v6hsaGqaNRuN/z8/PP0tEO86nMsYSACQQURNjLBRAI4BbAYwTkcH5nP8EkE9E9+50PQ5nu/CIFcfnONN2c87/yp03IqIuwPv1PESkBvAFxtijP/7xj9/14osvfjEnJyf+4Ycfjr7++uvX/PCw2+2QSCQ4evQoTCYTJiYmcOHCBfj5+SElJQVxcXGi2B9MTU35bIzO1RaxAv5lueALYeXysxJDWLne0xMTE/Dz80NycjIOHz4Mm82GCxcurCuqFhcX8dxzz1m//e1vzxiNxsbJycmvAKj1ZncfESkBKJ1fGxljXQCSiGj5/J9gADxawPEpXFhxdgWMMSkcV6CZAJ4iogtCr0lEFgDPA3ieMVbS29v7Bblcfuzee+8N+chHPhK4clba+Pg4kpOTAThqbzIyMpCRkQGj0Yjx8XH09vYiPDwcycnJiImJESR1ZLFYQEQ+Sw0tLCz41BTVF7iElbdHIm2GqKgo9PX1CXZ8q9UKpVKJ8fFxWK1WJCUlobKy8pIorEwmQ0BAAGZnZ92Dz110d3fjiSeemH3llVcWrFbrMzqd7nGnABIUxlgqHAPjLzj//w0AH4Ajyn1M6PU5nPXgwoqzKyAiG4BSxlgEgJcZY4VE1C7i+q0A3sMYC/vmN7/5wR/84AefOnDgQPiDDz4YdfToUQAOYXXw4MFV3xsaGoq8vDzk5uZienoaY2Nj6OjoQExMDBITExEZGek1kTU9Pe2z+irg6vKwcuHLzkC5XA673Q6r1eq1aKjVaoVOp8PExASMRiMSEhJQVFS07rDyPXv2YHR0FEVFRVhaWsJLL71k+853vjOl0WiGVCrVN+x2++tOyxPBYYyFAHgJwKdcKUAiehjAw4yxzwO4D8CjYuyFw/EEF1acXQURzTDG/gngOADRhNWy9Q0AfsgY+5/XXnutsqmp6fN+fn7V//7v/x5aWVnpv146iDEGhUIBhUIBu90OjUaDkZERtLS0IDIyEvHx8YiJidnRB6ROp/OZMSjgSBf50r/LFwQFBUGpFDwIsyYuF/ad+JaZTCao1WqoVCosLi4iJiYG6enpiIiI2JToj4mJwcsvv4wf/vCHs6+++qrJZrM9r9VqHxd7KLKzBvMlAM8S0R88POW3AE6ACyuOD+HCiuNzGGMxACxOURUI4AYA/+3LPTlrQ2oBvIMxFv7EE0/cERkZ+Z+PPPJI3L333htxxx13yNeLHEkkEsTHxyM+Ph5EhOnpaahUKvT29sLf3x/x8fGIi4vbcvRHr9cjMzNzZz/cDiAin3ZE+gJfRqwAh5/VVg1hiQgGgwEqlQoajQYSiQRxcXEoKChYNzK1koGBAfzyl79c+M1vfjNPRO2jo6PfBfCmM40uKs4ml58B6CKi7y+7P4uIXPnSWwB0i703Dmc5XFhxdgMJAH7lrLOSAHiBiF5jjL0TwA8BxAA4wRhrIaJ/E3tzRDQL4CcAfsIYS/r85z///77yla98OC8vL/TjH/+44m1ve5tkvSjO8kgWAMzPz0OlUqG5uRlWqxWxsbGIj49HeHj4utEDq9UKu93uMx8pi8Xik9mEvsbXwioqKgoDAwMbPs9ut0On00GlUkGv1yMkJATx8fGorKzc0ntGq9XiueeeMz/99NOz09PTYzqd7gdms/kPRDS38XcLyiEAdwFoY4y1OO/7AoC7GWM5cHQQjwDgHYEcn3L1nSU5uw7nOIsyD/e/DOBl8Xe0NkQ0AeDrAL7OGCvs6Oi457777rvt2muv9b/nnnsU11xzzYYRHdfoj4yMDFgsFqjVagwMDMBgMEChUCA6OhpRUVGrUm68vso3SCQSt+O8L/Dz84PNZoPNZoNUKnXfT0SYn5+HTqeDVqvF3NwcoqKiEB8fj8LCwi1FFhcWFvDKK6/Yn3rqKf3AwMDswsLC0waD4TdEtPZUc5EhojMAPF15vC72Xjic9eDCisPZJs7i+vsZY598/vnnD58+ffo+ANfedttt/h/60IfCysrKNqxfkcvlSE5ORnJyMux2O6anp6HT6TA8PAyLxYLIyEhER0e7x5v4sr7qarRacCGVSr1aQL5VIiMjodfrERQUBJ1OB51OB6PRiODgYERHRyMnJwehoaFbapIwm804efIk/u///k9/7ty5Jbvd/jutVvs0EfnW7p3DuczhBqEcjhdhjPlLJJKbExIS/oOISm+44QbZe9/73shjx45tuejbZrNhZmbG/UE6PT2NpKQkxMbGIjo6WnRj0sHBQUilUuzdu1fUdV34yiAUABobG5GVlYWwsDDR1lwekRobG8P8/Lw7ohkdHb1lIQU4avRef/11+zPPPKNvbW21SCSSvymVyh/Dy55THM7VDBdWHI5AODuYDsXHx99FRMcLCgrk73//+xVve9vbpCs9sjbCZrPh9OnTKCwshF6vh06nc0e0FAoFIiIiEBISIujYFZeFxE6603aCL4VVZ2cnoqKiBDXqtNlsMBgMmJmZwdTUFAwGA4KDgxEVFYXw8HB0d3fj8OHDWz5ub28vXn75ZdNvf/tbo0ajmTGbzc9PTU29AKCdiykOx/vwVCCHIxDOzql/AvgnY4yp1erc5ubmOx5++OH3KhSKqDvvvDPkXe96V2Bubu6GgshVX+WKVuTk5MBms2F6ehrT09Po7u7G/Pw8ZDIZwsPDERER4XWxdTWnAl0mod5iuYiamZmBwWAA4BgCHh4ejszMTISFhV3yu7NaravqrDxhtVpx/vx5vPDCC4ZXX311yWq19k9NTf1ycXHxT7upZorDuVLhESsOxwcwxmL9/PzeFhsb+yHGWN5b3/pW+a233hp+6NAhj+3w3d3dCA0NRVJS0rrHNZvNmJ2ddX9grxRb4eHh20ohAUBNTQ0OHTq04Qe7UPgyYqXRaKDValFQULDl77XZbJidnXX/XpaLKJcADgsL2/B1bW1tRVJSEqKjo1c9plKpcPLkSXrhhRemamtrrVKp9MzExMQvAfzdG3P6OBzO5uERK85VDWMsAEANAH84/h5+T0SPMsYUcIy7SQUwDOAOIpr21rpEpAHwcwA/Z4wF/PjHPz72yiuvvAvAdREREaHHjx8POH78eGh1dTVCQkKg1+uRmpq64XH9/PwQExOD5alGi8XiFlpqtRpzc3NgjCE4OBghISEICQlxf73eqBy73e4zUeVrNrJcICIsLS1hbm4O8/PzmJubw9zcHBYXF8EYQ3h4OMLDw5GamropEeUJl59VdHQ01Go1Tp48SSdOnJg+ffq0zWKxqJaWlk7o9fo/AGgkIvsOflyPMMZSAPwaQDwc1gZPE9EPlj3+IIDvAIghIp231+dwLhe4sOJc7SwBuI6I5pw1UWcYY38G8C44rvYfY4z9F4D/AvA5ITZARCYAf3bewBiL6OrqOvK73/3uHUR0LDIyMnTfvn2RH/jAB2SHDh1CcHDwlo4vl8tXiS2bzYaFhQW3ANDpdJibm3N3vq0UXQEBAVedMehyXMLKYrGsEk/z8/MgIvj7+7tfr5iYGKSlpSEwMNArqViXkHrppZfMzc3NhmVC6gSAeiJa2vlPuSFWAJ8hoibGWCiARsbYm0TU6RRdNwIYFWEfHM6uhqcCORwnjLEgAGcA/AccV+bXEpGSMZYA4J9ElOOjfUUAOJKQkPAOIjqmUChCjh8/Hnj8+PHQioqKVYNxd4rFYlklHAwGAxYXFxEcHAx/f3/4+/sjICDAfVv+f6EEmJCpQKvVCpPJhKWlJZhMplU3i8UCo9GIyMjISyJ8ISEhCAoK8nokb3JyEmfOnKETJ05Mnzp1anlE6nUAdSIJqXVhjL0C4H+I6E3G2O8BfA3AKwD284gV52qGCyvOVY/T8b0RQCaAp4joc4yxGSKKWPacaSKK9NUel8MYi4RTaAGolsvlivz8fFxzzTXhlZWV/vv27fO62HLVGOXn568SH8v/v7S0BLvdkYXy8/ODXC6HTCbzeJNKpR7vdwkzxpg72sMYcwsr1zmLiNw316Bi181ms13yf083i8UCi8UxmUUqlXoUia6bXC5HTU0Njhw54lXhSESYnJxEY2Mjzp07N3f69OmFoaEhkkgk44uLi3+fmpo6AeDCbhBSy2GMpcKRQi8EcC2A64nok4yxYXBhxbnK4cKKw3HijAy9DOB+AGd2q7BaiVMY5jDGyhMSEq4nokqZTKbIy8vDNddcE1ZZWRmwb98+REZuf/sjIyOw2WxIT0/f1POJCGazGRaLZUtix2q1usWS6zium9FodPtIrRRdEolkXQHnEnjLxZyfnx9kMtmmU3V1dXUoKCjYcip2+WsyPj7uElHG06dPL46MjJBEIhkzm81ntFrtKTgE/vhutkFgjIUAOAXgGwDnJTEOAAAHXElEQVT+AuAkgLcQ0SwXVhwOF1YcziUwxh4FMA/go9glqcDt4BRbWS6xBaBKKpVG5ebmoqKiIriwsDA4OzsbWVlZCA0N3fB4XV1diIyMRHx8vOB7XwtfdgUCQHt7O+Li4rCRBxkRQavVore3Fz09PdTW1masra01jY6OklQqHV1aWqrRarU1AJoATOxmEbUSZx3iawD+SkTfZ4wVAfg7AJcXRTKASQAV3NqBc7XCi9c5VzWMsRgAFiKaYYwFArgBwH8D+BOADwJ4zPnvK77b5dYhIhuAbuftWQBgjEnGxsay3nzzzfzIyMjikJCQfVarNUcikYQrFAppQUGBpLS0NCQvL88/Ozsb6enp7uG9CwsLG1o9XOkEBgZe4mVlNBrR19eH3t5etLe3z7e2ti709PRgbm7OIpFINIyxzqmpqYaFhYUuABeJaNJ3u985zBHa+xmALiL6PgAQURuA2GXPGQaPWHGucnjEinNVwxgrBvArAFIAEgAvENFXGWNRAF4AsAeOTqd3E9GU73YqLM40aBaA7Li4uH1+fn6lFoslXS6XByUlJSE+Pj68oKDAlpqaGpiYmMgSEhKQmJiImJgY0boFxYxYmc1mqFQqKJVKKJVKTE5O2ru7u5eGh4dtw8PDi1NTUza73T4rk8l65ubmmqanpy8C6AUw4OzyvOJgjB0GcBpAGxx2CwDwBSJ6fdlzhsGFFecqhwsrDoezJs4oRTwcfl4JAQEByREREVlyuTyViBKtVmu0TCbz8/f3l8bHx9OePXskqampgXv27AmKj49noaGhcN1CQkLc/25nmPF2hZXLX8poNMJoNLq/np2dxeTkpHVkZGRheHjYPDY2ZtfpdMxsNlvtdrtJLperAYybTKbBqampAZvNNglHmmuQiGa2vBEOh3NVwIUVh8PZMYwxPwBxABIAJMhkskSFQpEul8sjJRJJOGMsgohCbTZbiM1mC2aMyaRSqVQikUikUqkkMDAQISEhFBYWBrlcDqlUColEwlxF6RKJhC0sLIQGBgYa7XY72Ww22O12uL42mUwwGAwwGo0Ss9lMNpvNbrfbbXa73QbALJVK5yUSiZExZiSiWZvNNr20tKSbmpoaIiIlHIJJCUAnhLkmh8O5euDCisPxMWs5WjPGSgD8GEAIHO7v7yMig882KhDOqFggHD9nKP6VlpWs+FoCwAbHa7TyZgZgBGAkIrPIP4LgrPMe+TIcjRZa51MvSc1xOBzx4cKKw/Exzq7DhOWO1gBuhaP260EiOsUY+zCANCL6kg+3yvER67xH7gAwR0Tf9eX+OBzOv7h6Z1RwOLsEIlISUZPzayOALgBJAHLgMGEEgDcB3OabHXJ8zTrvEQ6Hs8vgworD2UU4Ha3LAFwA0A7gFudD7waQ4qNtcXYRK94jAHAfY+wiY+znTld+DofjQ7iw4nB2CU5H65cAfMpZS/VhAJ9gjDXCUXt0xdUOcbaGh/fI/wLIAFAKR/H993y3Ow6HA/AaKw5nV7DS0drD49kAniGiCtE3x9kVbOI9kgrgNSIqFHtvHA7nX/CIFYfjYzw5Wjvvj3X+KwHwRTg6BDlXIeu8RxKWPe2dcKSPORyOD+HCisPxPYcA3AXgOsZYi/N2M4A7GWO9cIylmQTwCyE3wRhLYYydZIx1McY6GGOfdN5fyhirde6rgTF21UTN1npNnI/dzxjrcd7/bYG3stZ75NuMsTbG2EUAxwB8WuB9cDicDeCpQA6HA2Ddlv4nADxORH92fph/loiu9dlGRWSd1yQOwMMA3kpES4yxWCLS+HCrHA5nl8CHMHM4HACOln44CqBBREbGmKulnwCEOZ8WDkf0TFDWMcR8Hg4bCgCIADBDRKVC7WOd1+SjAB4joiXnY1xUcTgcADxixeFwPOAshK4BUAiHkPgrAAZH+UA1EY0IvL7HSBERdS57zvcAzBLRV4Xcy7L1UvGv16QGwCsAjgMwwWHkWi/GPjgczu6G11hxOJxL8NDS/x8APk1EKXDU8PxM6D1sZIjpLOa+A8BzQu/Fud7K10QGIBJAFYCHALzg3BOHw7nK4cKKw+G4cbb0vwTgWSL6g/PuDwJwff0iAFGL1z0YYgLAEQBqIuoTYX1Pr8k4gD+Qgzo40pXRQu+Fw+Hsfriw4nA4ANZu6Yejpuoa59fXARBczCzb08pIkYs7IUK0ap3X5I9wvBYujzE/ADqh98PhcHY/vMaKw+EAABhjhwGcBtAGRwQGAL4AwADgB3Ckv0wAPk5EjSLsx6MhJmNMBmACQDkRjQu8h7Vek78B+DkcjudmOGqs/iHkXjgczuUBF1YcDmfX4YwU/QrAFBF9asVjxwF8noiu8fS9HA6H40t4KpDD4exG1jLEBID3QqSidQ6Hw9kqPGLF4XA4HA6H4yV4xIrD4XA4HA7HS3BhxeFwOBwOh+MluLDicDgcDofD8RJcWHE4HA6Hw+F4CS6sOBwOh8PhcLwEF1YcDofD4XA4XoILKw6Hw+FwOBwvwYUVh8PhcDgcjpf4/53fw6rnv/D7AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 720x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#\n",
+    "\n",
+    "dhna = deaths_headlines.dropna()\n",
+    "\n",
+    "fig = plt.figure(figsize=(10, 10))\n",
+    "ax = fig.add_subplot(111, projection=\"polar\")\n",
+    "\n",
+    "theta = np.roll(\n",
+    "    np.flip(\n",
+    "        np.arange(len(dhna))/float(len(dhna))*2.*np.pi),\n",
+    "    14)\n",
+    "# l15, = ax.plot(theta, deaths_headlines['total_2015'], color=\"#b56363\", label=\"2015\") # 0\n",
+    "# l16, = ax.plot(theta, deaths_headlines['total_2016'], color=\"#a4b563\", label=\"2016\") # 72\n",
+    "# l17, = ax.plot(theta, deaths_headlines['total_2017'], color=\"#63b584\", label=\"2017\") # 144\n",
+    "# l18, = ax.plot(theta, deaths_headlines['total_2018'], color=\"#6384b5\", label=\"2018\") # 216\n",
+    "# l19, = ax.plot(theta, deaths_headlines['total_2019'], color=\"#a4635b\", label=\"2019\") # 288\n",
+    "l15, = ax.plot(theta, dhna[2015], color=\"#e47d7d\", label=\"2015\") # 0\n",
+    "l16, = ax.plot(theta, dhna[2016], color=\"#afc169\", label=\"2016\") # 72 , d0e47d\n",
+    "l17, = ax.plot(theta, dhna[2017], color=\"#7de4a6\", label=\"2017\") # 144\n",
+    "l18, = ax.plot(theta, dhna[2018], color=\"#7da6e4\", label=\"2018\") # 216\n",
+    "l19, = ax.plot(theta, dhna[2019], color=\"#d07de4\", label=\"2019\") # 288\n",
+    "\n",
+    "lmean, = ax.plot(theta, dhna['previous_mean'], color=\"black\", linestyle='dashed', label=\"mean\")\n",
+    "\n",
+    "l20, = ax.plot(theta, dhna[2020], color=\"red\", label=\"2020\")\n",
+    "\n",
+    "# deaths_headlines.total_2019.plot(ax=ax)\n",
+    "\n",
+    "def _closeline(line):\n",
+    "    x, y = line.get_data()\n",
+    "    x = np.concatenate((x, [x[0]]))\n",
+    "    y = np.concatenate((y, [y[0]]))\n",
+    "    line.set_data(x, y)\n",
+    "\n",
+    "[_closeline(l) for l in [l19, l18, l17, l16, l15, lmean]]\n",
+    "\n",
+    "\n",
+    "ax.set_xticks(theta)\n",
+    "ax.set_xticklabels(dhna.index)\n",
+    "plt.legend()\n",
+    "plt.title(\"Deaths by week over years, all UK\")\n",
+    "plt.savefig('deaths-radar.png')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "source": [
+    "# Plots for UK nations"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 584,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 720x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#\n",
+    "\n",
+    "fig = plt.figure(figsize=(10, 10))\n",
+    "ax = fig.add_subplot(111, projection=\"polar\")\n",
+    "\n",
+    "theta = np.roll(\n",
+    "    np.flip(\n",
+    "        np.arange(len(deaths_headlines_e))/float(len(deaths_headlines_e))*2.*np.pi),\n",
+    "    14)\n",
+    "l15, = ax.plot(theta, deaths_headlines_e[2015], color=\"#e47d7d\", label=\"2015\") # 0\n",
+    "l16, = ax.plot(theta, deaths_headlines_e[2016], color=\"#afc169\", label=\"2016\") # 72 , d0e47d\n",
+    "l17, = ax.plot(theta, deaths_headlines_e[2017], color=\"#7de4a6\", label=\"2017\") # 144\n",
+    "l18, = ax.plot(theta, deaths_headlines_e[2018], color=\"#7da6e4\", label=\"2018\") # 216\n",
+    "l19, = ax.plot(theta, deaths_headlines_e[2019], color=\"#d07de4\", label=\"2019\") # 288\n",
+    "\n",
+    "lmean, = ax.plot(theta, deaths_headlines_e['previous_mean'], color=\"black\", linestyle='dashed', label=\"mean\")\n",
+    "\n",
+    "l20, = ax.plot(theta, deaths_headlines_e[2020], color=\"red\", label=\"2020\")\n",
+    "\n",
+    "# deaths_headlines.total_2019.plot(ax=ax)\n",
+    "\n",
+    "def _closeline(line):\n",
+    "    x, y = line.get_data()\n",
+    "    x = np.concatenate((x, [x[0]]))\n",
+    "    y = np.concatenate((y, [y[0]]))\n",
+    "    line.set_data(x, y)\n",
+    "\n",
+    "[_closeline(l) for l in [l19, l18, l17, l16, l15, lmean]]\n",
+    "\n",
+    "\n",
+    "ax.set_xticks(theta)\n",
+    "ax.set_xticklabels(deaths_headlines_e.index)\n",
+    "plt.legend()\n",
+    "plt.title(\"Deaths by week over years, England\")\n",
+    "plt.savefig('deaths-radar_england.png')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 585,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#\n",
+    "\n",
+    "fig = plt.figure(figsize=(10, 10))\n",
+    "ax = fig.add_subplot(111, projection=\"polar\")\n",
+    "\n",
+    "theta = np.roll(\n",
+    "    np.flip(\n",
+    "        np.arange(len(deaths_headlines_w))/float(len(deaths_headlines_w))*2.*np.pi),\n",
+    "    14)\n",
+    "l15, = ax.plot(theta, deaths_headlines_w[2015], color=\"#e47d7d\", label=\"2015\") # 0\n",
+    "l16, = ax.plot(theta, deaths_headlines_w[2016], color=\"#afc169\", label=\"2016\") # 72 , d0e47d\n",
+    "l17, = ax.plot(theta, deaths_headlines_w[2017], color=\"#7de4a6\", label=\"2017\") # 144\n",
+    "l18, = ax.plot(theta, deaths_headlines_w[2018], color=\"#7da6e4\", label=\"2018\") # 216\n",
+    "l19, = ax.plot(theta, deaths_headlines_w[2019], color=\"#d07de4\", label=\"2019\") # 288\n",
+    "\n",
+    "lmean, = ax.plot(theta, deaths_headlines_w['previous_mean'], color=\"black\", linestyle='dashed', label=\"mean\")\n",
+    "\n",
+    "l20, = ax.plot(theta, deaths_headlines_w[2020], color=\"red\", label=\"2020\")\n",
+    "\n",
+    "\n",
+    "def _closeline(line):\n",
+    "    x, y = line.get_data()\n",
+    "    x = np.concatenate((x, [x[0]]))\n",
+    "    y = np.concatenate((y, [y[0]]))\n",
+    "    line.set_data(x, y)\n",
+    "\n",
+    "[_closeline(l) for l in [l19, l18, l17, l16, l15, lmean]]\n",
+    "\n",
+    "\n",
+    "ax.set_xticks(theta)\n",
+    "ax.set_xticklabels(deaths_headlines_w.index)\n",
+    "plt.legend()\n",
+    "plt.title(\"Deaths by week over years, Wales\")\n",
+    "plt.savefig('deaths-radar_wales.png')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 586,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#\n",
+    "\n",
+    "fig = plt.figure(figsize=(10, 10))\n",
+    "ax = fig.add_subplot(111, projection=\"polar\")\n",
+    "\n",
+    "theta = np.roll(\n",
+    "    np.flip(\n",
+    "        np.arange(len(deaths_headlines_s))/float(len(deaths_headlines_s))*2.*np.pi),\n",
+    "    14)\n",
+    "l15, = ax.plot(theta, deaths_headlines_s[2015], color=\"#e47d7d\", label=\"2015\") # 0\n",
+    "l16, = ax.plot(theta, deaths_headlines_s[2016], color=\"#afc169\", label=\"2016\") # 72 , d0e47d\n",
+    "l17, = ax.plot(theta, deaths_headlines_s[2017], color=\"#7de4a6\", label=\"2017\") # 144\n",
+    "l18, = ax.plot(theta, deaths_headlines_s[2018], color=\"#7da6e4\", label=\"2018\") # 216\n",
+    "l19, = ax.plot(theta, deaths_headlines_s[2019], color=\"#d07de4\", label=\"2019\") # 288\n",
+    "\n",
+    "lmean, = ax.plot(theta, deaths_headlines_s['previous_mean'], color=\"black\", linestyle='dashed', label=\"mean\")\n",
+    "\n",
+    "l20, = ax.plot(theta, deaths_headlines_s[2020], color=\"red\", label=\"2020\")\n",
+    "\n",
+    "\n",
+    "def _closeline(line):\n",
+    "    x, y = line.get_data()\n",
+    "    x = np.concatenate((x, [x[0]]))\n",
+    "    y = np.concatenate((y, [y[0]]))\n",
+    "    line.set_data(x, y)\n",
+    "\n",
+    "[_closeline(l) for l in [l19, l18, l17, l16, l15, lmean]]\n",
+    "\n",
+    "\n",
+    "ax.set_xticks(theta)\n",
+    "ax.set_xticklabels(deaths_headlines_s.index)\n",
+    "plt.legend()\n",
+    "plt.title(\"Deaths by week over years, Scotland\")\n",
+    "plt.savefig('deaths-radar_scotland.png')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 587,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 720x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#\n",
+    "\n",
+    "fig = plt.figure(figsize=(10, 10))\n",
+    "ax = fig.add_subplot(111, projection=\"polar\")\n",
+    "\n",
+    "theta = np.roll(\n",
+    "    np.flip(\n",
+    "        np.arange(len(deaths_headlines_i))/float(len(deaths_headlines_i))*2.*np.pi),\n",
+    "    14)\n",
+    "l15, = ax.plot(theta, deaths_headlines_i[2015], color=\"#e47d7d\", label=\"2015\") # 0\n",
+    "l16, = ax.plot(theta, deaths_headlines_i[2016], color=\"#afc169\", label=\"2016\") # 72 , d0e47d\n",
+    "l17, = ax.plot(theta, deaths_headlines_i[2017], color=\"#7de4a6\", label=\"2017\") # 144\n",
+    "l18, = ax.plot(theta, deaths_headlines_i[2018], color=\"#7da6e4\", label=\"2018\") # 216\n",
+    "l19, = ax.plot(theta, deaths_headlines_i[2019], color=\"#d07de4\", label=\"2019\") # 288\n",
+    "\n",
+    "lmean, = ax.plot(theta, deaths_headlines_i['previous_mean'], color=\"black\", linestyle='dashed', label=\"mean\")\n",
+    "\n",
+    "l20, = ax.plot(theta, deaths_headlines_i[2020], color=\"red\", label=\"2020\")\n",
+    "\n",
+    "\n",
+    "def _closeline(line):\n",
+    "    x, y = line.get_data()\n",
+    "    x = np.concatenate((x, [x[0]]))\n",
+    "    y = np.concatenate((y, [y[0]]))\n",
+    "    line.set_data(x, y)\n",
+    "\n",
+    "[_closeline(l) for l in [l19, l18, l17, l16, l15, lmean]]\n",
+    "\n",
+    "\n",
+    "ax.set_xticks(theta)\n",
+    "ax.set_xticklabels(deaths_headlines_i.index)\n",
+    "plt.legend()\n",
+    "plt.title(\"Deaths by week over years, Northern Ireland\")\n",
+    "plt.savefig('deaths-radar_northern_ireland.png')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "jupytext": {
+   "formats": "ipynb,md"
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/deaths_import.md b/deaths_import.md

new file mode 100644 (file)

index 0000000..f704518
--- /dev/null
+++ b/deaths_import.md
@@ -0,0 +1,1017 @@
+---
+jupyter:
+  jupytext:
+    formats: ipynb,md
+    text_representation:
+      extension: .md
+      format_name: markdown
+      format_version: '1.2'
+      jupytext_version: 1.9.1
+  kernelspec:
+    display_name: Python 3
+    language: python
+    name: python3
+---
+
+<!-- #region Collapsed="false" -->
+Data from:
+
+* [Office of National Statistics](https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/weeklyprovisionalfiguresondeathsregisteredinenglandandwales) (Endland and Wales) Weeks start on a Saturday.
+* [Northern Ireland Statistics and Research Agency](https://www.nisra.gov.uk/publications/weekly-deaths) (Northern Ireland). Weeks start on a Saturday. Note that the week numbers don't match the England and Wales data.
+* [National Records of Scotland](https://www.nrscotland.gov.uk/statistics-and-data/statistics/statistics-by-theme/vital-events/general-publications/weekly-and-monthly-data-on-births-and-deaths/weekly-data-on-births-and-deaths) (Scotland). Note that Scotland uses ISO8601 week numbers, which start on a Monday.
+
+<!-- #endregion -->
+
+```python Collapsed="false"
+import itertools
+import collections
+import json
+import pandas as pd
+import numpy as np
+from scipy.stats import gmean
+import datetime
+
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+%matplotlib inline
+
+from sqlalchemy.types import Integer, Text, String, DateTime, Float
+from sqlalchemy import create_engine
+%load_ext sql
+```
+
+```python Collapsed="false"
+connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'
+```
+
+```python Collapsed="false"
+%sql $connection_string
+```
+
+```python Collapsed="false"
+conn = create_engine(connection_string)
+```
+
+```python Collapsed="false"
+england_wales_filename = 'uk-deaths-data/publishedweek532020.xlsx'
+```
+
+```sql Collapsed="false"
+drop table if exists all_causes_deaths;
+create table all_causes_deaths (
+    week integer,
+    year integer,
+    date_up_to date,
+    nation varchar(20),
+    deaths integer,
+    CONSTRAINT week_nation PRIMARY KEY(year, week, nation)
+);
+```
+
+```python Collapsed="false"
+raw_data_2015 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2015.csv', 
+                       parse_dates=[1, 2], dayfirst=True,
+#                       index_col=0,
+                      header=[0, 1]
+                           )
+dh15i = raw_data_2015.iloc[:, [0, 3]]
+dh15i.set_index(dh15i.columns[0], inplace=True)
+dh15i.columns = ['total_2015']
+dh15i.tail()
+```
+
+```python Collapsed="false"
+raw_data_2015.head()
+```
+
+```python Collapsed="false"
+rd = raw_data_2015.iloc[:, [0, 2, 3]].droplevel(1, axis=1).rename(
+    columns={'Week Ends (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2015P)': 'deaths',
+            'Registration Week': 'week'}
+    )
+rd['year'] = 2015
+rd['nation'] = 'Northern Ireland'
+rd.head()
+```
+
+```python Collapsed="false"
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python Collapsed="false"
+%sql select * from all_causes_deaths limit 10
+```
+
+```python Collapsed="false"
+raw_data_2016 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2016.csv', 
+                        parse_dates=[1, 2], dayfirst=True,
+#                       index_col=0,
+                      header=[0, 1]
+                           )
+raw_data_2016.head()
+# dh16i = raw_data_2016.iloc[:, [2]]
+# dh16i.columns = ['total_2016']
+# # dh16i.head()
+dh16i = raw_data_2016.iloc[:, [0, 3]]
+dh16i.set_index(dh16i.columns[0], inplace=True)
+dh16i.columns = ['total_2016']
+dh16i.tail()
+```
+
+```python Collapsed="false"
+rd = raw_data_2016.iloc[:, [0, 2, 3]].droplevel(1, axis=1).rename(
+    columns={'Week Ends (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2016P)': 'deaths',
+            'Registration Week': 'week'}
+    )
+rd['year'] = 2016
+rd['nation'] = 'Northern Ireland'
+rd.head()
+```
+
+```python Collapsed="false"
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python Collapsed="false"
+%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation)
+```
+
+```python Collapsed="false"
+raw_data_2017 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2017.csv', 
+                        parse_dates=[1, 2], dayfirst=True,
+#                       index_col=0,
+                      header=[0, 1]
+                           )
+raw_data_2017.head()
+dh17i = raw_data_2017.iloc[:, [0, 3]]
+dh17i.set_index(dh17i.columns[0], inplace=True)
+dh17i.columns = ['total_2017']
+dh17i.tail()
+```
+
+```python Collapsed="false"
+rd = raw_data_2017.iloc[:, [0, 2, 3]].droplevel(1, axis=1).rename(
+    columns={'Week Ends (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2017P)': 'deaths',
+            'Registration Week': 'week'}
+    )
+rd['year'] = 2017
+rd['nation'] = 'Northern Ireland'
+rd.head()
+```
+
+```python Collapsed="false"
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python Collapsed="false"
+%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation)
+```
+
+```python Collapsed="false"
+raw_data_2018 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2018.csv', 
+                        parse_dates=[1, 2], dayfirst=True,
+#                       index_col=0,
+                      header=[0, 1]
+                           )
+raw_data_2018.head()
+dh18i = raw_data_2018.iloc[:, [0, 3]]
+dh18i.set_index(dh18i.columns[0], inplace=True)
+dh18i.columns = ['total_2018']
+dh18i.tail()
+```
+
+```python Collapsed="false"
+rd = raw_data_2018.iloc[:, [0, 2, 3]].droplevel(1, axis=1).rename(
+    columns={'Week Ends (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2018P)': 'deaths',
+            'Registration Week': 'week'}
+    )
+rd['year'] = 2018
+rd['nation'] = 'Northern Ireland'
+rd.head()
+```
+
+```python Collapsed="false"
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python Collapsed="false"
+%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation)
+```
+
+```python Collapsed="false"
+raw_data_2019 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2019.csv', 
+                        parse_dates=[1, 2], dayfirst=True,
+#                       index_col=0,
+                      header=[0, 1]
+                           )
+raw_data_2019.head()
+dh19i = raw_data_2019.iloc[:, [0, 3]]
+dh19i.set_index(dh19i.columns[0], inplace=True)
+dh19i.columns = ['total_2019']
+dh19i.tail()
+```
+
+```python Collapsed="false"
+rd = raw_data_2019.iloc[:, [0, 2, 3]].droplevel(1, axis=1).rename(
+    columns={'Week Ends (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2019P)': 'deaths',
+            'Registration Week': 'week'}
+    )
+rd['year'] = 2019
+rd['nation'] = 'Northern Ireland'
+rd.head()
+```
+
+```python Collapsed="false"
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python Collapsed="false"
+%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation)
+```
+
+```python Collapsed="false"
+raw_data_2020_i = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2020.csv', 
+                        parse_dates=[1], dayfirst=True,
+                      header=[0, 1]
+                           )
+raw_data_2020_i.head()
+```
+
+```python Collapsed="false"
+rd = raw_data_2020_i.iloc[:, [0, 1, 2]].droplevel(1, axis=1).rename(
+    columns={'Week Ending (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2020P)': 'deaths',
+            'Registration Week': 'week'}
+    )
+rd['year'] = 2020
+rd['nation'] = 'Northern Ireland'
+rd.head()
+```
+
+```python Collapsed="false"
+rd.tail()
+```
+
+```python Collapsed="false"
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python Collapsed="false"
+%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year
+```
+
+```python
+raw_data_2020_i.set_index(raw_data_2020_i.columns[0], inplace=True)
+raw_data_2020_i.tail()
+```
+
+```python Collapsed="false"
+datetime.datetime.now().isocalendar()
+```
+
+```python Collapsed="false"
+datetime.datetime.fromisocalendar(2021, 3, 1)
+```
+
+```python Collapsed="false"
+
+```
+
+```python Collapsed="false"
+raw_data_s = pd.read_csv('uk-deaths-data/weekly-deaths-scotland.csv', 
+                      index_col=0,
+                      header=0,
+                        skiprows=2
+                           )
+# raw_data_s
+```
+
+```python Collapsed="false"
+deaths_headlines_s = raw_data_s[reversed('2015 2016 2017 2018 2019 2020'.split())]
+deaths_headlines_s.columns = ['total_' + c for c in deaths_headlines_s.columns]
+deaths_headlines_s.reset_index(drop=True, inplace=True)
+deaths_headlines_s.index = deaths_headlines_s.index + 1
+deaths_headlines_s
+```
+
+```python
+%sql select * from all_causes_deaths limit 5
+```
+
+```python Collapsed="false"
+for year, ser in deaths_headlines_s.items():
+    year_i = int(year[-4:])
+#     print(year_i)
+    for week, deaths in ser.dropna().iteritems():
+#         print(datetime.date.fromisocalendar(year_i, week, 7), deaths)
+        dut = datetime.date.fromisocalendar(year_i, week, 7)
+        %sql insert into all_causes_deaths(week, year, date_up_to, nation, deaths) values ({week}, {year_i}, :dut, 'Scotland', {deaths})
+```
+
+```python
+%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year
+```
+
+```python
+%sql select year, nation, date_up_to from all_causes_deaths where week=3 order by year, nation
+```
+
+```python Collapsed="false"
+eng_xls = pd.read_excel(england_wales_filename, 
+                        sheet_name="Weekly figures 2020",
+                        skiprows=[0, 1, 2, 3],
+                        header=0,
+                        index_col=[1]
+                       ).iloc[:91].T
+eng_xls
+```
+
+```python Collapsed="false"
+# eng_xls_columns
+```
+
+```python Collapsed="false"
+eng_xls_columns = list(eng_xls.columns)
+
+for i, c in enumerate(eng_xls_columns):
+#     print(i, c, type(c), isinstance(c, float))
+    if isinstance(c, float) and np.isnan(c):
+        if eng_xls.iloc[0].iloc[i] is not pd.NaT:
+            eng_xls_columns[i] = eng_xls.iloc[0].iloc[i]
+
+# np.isnan(eng_xls_columns[0])
+# eng_xls_columns
+
+eng_xls.columns = eng_xls_columns
+# eng_xls.columns
+```
+
+```python
+eng_xls
+```
+
+```python
+rd = eng_xls.iloc[1:][['Week ended', 'Wales']].reset_index(level=0).rename(
+    columns={'Week ended': 'date_up_to', 'Wales': 'deaths',
+            'index': 'week'}
+    )
+rd['year'] = 2020
+rd['nation'] = 'Wales'
+rd.head()
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python Collapsed="false"
+eng_xls = eng_xls.iloc[1:]
+eng_xls['England deaths'] = eng_xls.loc[:, 'Total deaths, all ages'] - eng_xls.loc[:, 'Wales']
+```
+
+```python
+eng_xls.head()
+```
+
+```python
+rd = eng_xls[['Week ended', 'England deaths']].reset_index(level=0).rename(
+    columns={'Week ended': 'date_up_to', 'England deaths': 'deaths',
+            'index': 'week'}
+    )
+rd['year'] = 2020
+rd['nation'] = 'England'
+rd.head()
+```
+
+```python
+%sql delete from all_causes_deaths where nation = 'England'
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python
+rd.tail()
+```
+
+```python
+%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year
+```
+
+```python Collapsed="false"
+# raw_data_2020 = pd.read_csv('uk-deaths-data/publishedweek272020.csv', 
+#                        parse_dates=[1], dayfirst=True,
+#                       index_col=0,
+#                       header=[0, 1])
+```
+
+```python Collapsed="false"
+
+```
+
+```python Collapsed="false"
+# raw_data_2020.head()
+```
+
+```python Collapsed="false"
+# raw_data_2020['W92000004', 'Wales']
+```
+
+```python Collapsed="false"
+raw_data_2019 = pd.read_csv('uk-deaths-data/publishedweek522019.csv', 
+                       parse_dates=[1], dayfirst=True,
+#                       index_col=0,
+                      header=[0, 1])
+# raw_data_2019.head()
+```
+
+```python
+rdew = raw_data_2019.iloc[:, [0, 1, 2, -1]].droplevel(axis=1, level=1)
+rdew.head()
+```
+
+```python
+rd = rdew.drop(columns=['Total deaths, all ages']).rename(
+    columns={'Week ended': 'date_up_to', 'W92000004': 'deaths',
+            'Week number': 'week'}
+    )
+rd['year'] = 2019
+rd['nation'] = 'Wales'
+rd.head()
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python
+rd = rdew.loc[:, ['Week ended','Week number']]
+rd['deaths'] = rdew['Total deaths, all ages'] - rdew['W92000004']
+rd = rd.rename(
+    columns={'Week ended': 'date_up_to', 'Week number': 'week'}
+    )
+rd['year'] = 2019
+rd['nation'] = 'England'
+rd.head()
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python
+%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year
+```
+
+```python Collapsed="false"
+raw_data_2018 = pd.read_csv('uk-deaths-data/publishedweek522018.csv', 
+                       parse_dates=[1], dayfirst=True,
+#                       index_col=0,
+                      header=[0, 1])
+# raw_data_2018.head()
+```
+
+```python
+rdew = raw_data_2018.iloc[:, [0, 1, 2, -1]].droplevel(axis=1, level=1)
+rdew.head()
+```
+
+```python
+rd = rdew.drop(columns=['Total deaths, all ages']).rename(
+    columns={'Week ended': 'date_up_to', 'W92000004': 'deaths',
+            'Week number': 'week'}
+    )
+rd['year'] = 2018
+rd['nation'] = 'Wales'
+rd.head()
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python
+rd = rdew.loc[:, ['Week ended','Week number']]
+rd['deaths'] = rdew['Total deaths, all ages'] - rdew['W92000004']
+rd = rd.rename(
+    columns={'Week ended': 'date_up_to', 'Week number': 'week'}
+    )
+rd['year'] = 2018
+rd['nation'] = 'England'
+rd.head()
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python
+%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year
+```
+
+```python Collapsed="false"
+raw_data_2017 = pd.read_csv('uk-deaths-data/publishedweek522017.csv', 
+                       parse_dates=[1], dayfirst=True,
+#                       index_col=0,
+                      header=[0, 1])
+# raw_data_2017.head()
+```
+
+```python
+rdew = raw_data_2017.iloc[:, [0, 1, 2, -1]].droplevel(axis=1, level=1)
+rdew.head()
+```
+
+```python
+rd = rdew.drop(columns=['Total deaths, all ages']).rename(
+    columns={'Week ended': 'date_up_to', 'W92000004': 'deaths',
+            'Week number': 'week'}
+    )
+rd['year'] = 2017
+rd['nation'] = 'Wales'
+rd.head()
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python
+rd = rdew.loc[:, ['Week ended','Week number']]
+rd['deaths'] = rdew['Total deaths, all ages'] - rdew['W92000004']
+rd = rd.rename(
+    columns={'Week ended': 'date_up_to', 'Week number': 'week'}
+    )
+rd['year'] = 2017
+rd['nation'] = 'England'
+rd.head()
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python
+%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year
+```
+
+```python
+
+```
+
+```python Collapsed="false"
+raw_data_2016 = pd.read_csv('uk-deaths-data/publishedweek522016.csv', 
+                       parse_dates=[1], dayfirst=True,
+#                       index_col=0,
+                      header=[0, 1])
+# raw_data_2016.head()
+```
+
+```python
+raw_data_2016.head()
+```
+
+```python
+rdew = raw_data_2016.iloc[:, [0, 1, 2, -1]].droplevel(axis=1, level=1)
+rdew.head()
+```
+
+```python
+rd = rdew.drop(columns=['Total deaths, all ages']).rename(
+    columns={'Week ended': 'date_up_to', 'W92000004': 'deaths',
+            'Week number': 'week'}
+    )
+rd['year'] = 2016
+rd['nation'] = 'Wales'
+rd.head()
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python
+rd = rdew.loc[:, ['Week ended','Week number']]
+rd['deaths'] = rdew['Total deaths, all ages'] - rdew['W92000004']
+rd = rd.rename(
+    columns={'Week ended': 'date_up_to', 'Week number': 'week'}
+    )
+rd['year'] = 2016
+rd['nation'] = 'England'
+rd.head()
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python
+ %sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year
+```
+
+```python Collapsed="false"
+raw_data_2015 = pd.read_csv('uk-deaths-data/publishedweek2015.csv', 
+                       parse_dates=[1], dayfirst=True,
+#                       index_col=0,
+                      header=[0, 1])
+# raw_data_2015.head()
+```
+
+```python
+rdew = raw_data_2015.iloc[:, [0, 1, 2, -1]].droplevel(axis=1, level=1)
+rdew.head()
+```
+
+```python
+rd = rdew.drop(columns=['Total deaths, all ages']).rename(
+    columns={'Week ended': 'date_up_to', 'W92000004': 'deaths',
+            'Week number': 'week'}
+    )
+rd['year'] = 2015
+rd['nation'] = 'Wales'
+rd.head()
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python
+rd = rdew.loc[:, ['Week ended','Week number']]
+rd['deaths'] = rdew['Total deaths, all ages'] - rdew['W92000004']
+rd = rd.rename(
+    columns={'Week ended': 'date_up_to', 'Week number': 'week'}
+    )
+rd['year'] = 2015
+rd['nation'] = 'England'
+rd.head()
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python
+%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by year, nation
+```
+
+```sql magic_args="res << select week, year, deaths"
+from all_causes_deaths
+where nation = 'England'
+```
+
+```python
+deaths_headlines_e = res.DataFrame().pivot(index='week', columns='year', values='deaths')
+deaths_headlines_e
+```
+
+```python
+
+```
+
+```sql magic_args="res << select week, year, deaths"
+from all_causes_deaths
+where nation = 'Scotland'
+```
+
+```python
+deaths_headlines_s = res.DataFrame().pivot(index='week', columns='year', values='deaths')
+deaths_headlines_s
+```
+
+```sql magic_args="res << select week, year, deaths"
+from all_causes_deaths
+where nation = 'Wales'
+```
+
+```python
+deaths_headlines_w = res.DataFrame().pivot(index='week', columns='year', values='deaths')
+deaths_headlines_w
+```
+
+```sql magic_args="res << select week, year, deaths"
+from all_causes_deaths
+where nation = 'Northern Ireland'
+```
+
+```python
+deaths_headlines_i = res.DataFrame().pivot(index='week', columns='year', values='deaths')
+deaths_headlines_i
+```
+
+```python Collapsed="false"
+deaths_headlines = deaths_headlines_e + deaths_headlines_w + deaths_headlines_i + deaths_headlines_s
+deaths_headlines
+```
+
+```python
+deaths_headlines_e.columns
+```
+
+```python
+deaths_headlines_e['previous_mean'] = deaths_headlines_e[[int(y) for y in '2019 2018 2017 2016 2015'.split()]].apply(np.mean, axis=1)
+deaths_headlines_w['previous_mean'] = deaths_headlines_w[[int(y) for y in '2019 2018 2017 2016 2015'.split()]].apply(np.mean, axis=1)
+deaths_headlines_s['previous_mean'] = deaths_headlines_s[[int(y) for y in '2019 2018 2017 2016 2015'.split()]].apply(np.mean, axis=1)
+deaths_headlines_i['previous_mean'] = deaths_headlines_i[[int(y) for y in '2019 2018 2017 2016 2015'.split()]].apply(np.mean, axis=1)
+deaths_headlines['previous_mean'] = deaths_headlines[[int(y) for y in '2019 2018 2017 2016 2015'.split()]].apply(np.mean, axis=1)
+deaths_headlines
+```
+
+```python Collapsed="false"
+deaths_headlines[[2020, 2019, 2018, 2017, 2016, 2015]].plot(figsize=(14, 8))
+```
+
+```python Collapsed="false"
+deaths_headlines[[2020, 'previous_mean']].plot(figsize=(10, 8))
+```
+
+```python Collapsed="false"
+deaths_headlines_i.plot()
+```
+
+```python
+deaths_headlines[2020].sum() - deaths_headlines.previous_mean.sum()
+```
+
+```python Collapsed="false"
+# Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#
+
+dhna = deaths_headlines.dropna()
+
+fig = plt.figure(figsize=(10, 10))
+ax = fig.add_subplot(111, projection="polar")
+
+theta = np.roll(
+    np.flip(
+        np.arange(len(dhna))/float(len(dhna))*2.*np.pi),
+    14)
+# l15, = ax.plot(theta, deaths_headlines['total_2015'], color="#b56363", label="2015") # 0
+# l16, = ax.plot(theta, deaths_headlines['total_2016'], color="#a4b563", label="2016") # 72
+# l17, = ax.plot(theta, deaths_headlines['total_2017'], color="#63b584", label="2017") # 144
+# l18, = ax.plot(theta, deaths_headlines['total_2018'], color="#6384b5", label="2018") # 216
+# l19, = ax.plot(theta, deaths_headlines['total_2019'], color="#a4635b", label="2019") # 288
+l15, = ax.plot(theta, dhna[2015], color="#e47d7d", label="2015") # 0
+l16, = ax.plot(theta, dhna[2016], color="#afc169", label="2016") # 72 , d0e47d
+l17, = ax.plot(theta, dhna[2017], color="#7de4a6", label="2017") # 144
+l18, = ax.plot(theta, dhna[2018], color="#7da6e4", label="2018") # 216
+l19, = ax.plot(theta, dhna[2019], color="#d07de4", label="2019") # 288
+
+lmean, = ax.plot(theta, dhna['previous_mean'], color="black", linestyle='dashed', label="mean")
+
+l20, = ax.plot(theta, dhna[2020], color="red", label="2020")
+
+# deaths_headlines.total_2019.plot(ax=ax)
+
+def _closeline(line):
+    x, y = line.get_data()
+    x = np.concatenate((x, [x[0]]))
+    y = np.concatenate((y, [y[0]]))
+    line.set_data(x, y)
+
+[_closeline(l) for l in [l19, l18, l17, l16, l15, lmean]]
+
+
+ax.set_xticks(theta)
+ax.set_xticklabels(dhna.index)
+plt.legend()
+plt.title("Deaths by week over years, all UK")
+plt.savefig('deaths-radar.png')
+plt.show()
+```
+
+<!-- #region Collapsed="false" -->
+# Plots for UK nations
+<!-- #endregion -->
+
+```python Collapsed="false"
+# Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#
+
+fig = plt.figure(figsize=(10, 10))
+ax = fig.add_subplot(111, projection="polar")
+
+theta = np.roll(
+    np.flip(
+        np.arange(len(deaths_headlines_e))/float(len(deaths_headlines_e))*2.*np.pi),
+    14)
+l15, = ax.plot(theta, deaths_headlines_e[2015], color="#e47d7d", label="2015") # 0
+l16, = ax.plot(theta, deaths_headlines_e[2016], color="#afc169", label="2016") # 72 , d0e47d
+l17, = ax.plot(theta, deaths_headlines_e[2017], color="#7de4a6", label="2017") # 144
+l18, = ax.plot(theta, deaths_headlines_e[2018], color="#7da6e4", label="2018") # 216
+l19, = ax.plot(theta, deaths_headlines_e[2019], color="#d07de4", label="2019") # 288
+
+lmean, = ax.plot(theta, deaths_headlines_e['previous_mean'], color="black", linestyle='dashed', label="mean")
+
+l20, = ax.plot(theta, deaths_headlines_e[2020], color="red", label="2020")
+
+# deaths_headlines.total_2019.plot(ax=ax)
+
+def _closeline(line):
+    x, y = line.get_data()
+    x = np.concatenate((x, [x[0]]))
+    y = np.concatenate((y, [y[0]]))
+    line.set_data(x, y)
+
+[_closeline(l) for l in [l19, l18, l17, l16, l15, lmean]]
+
+
+ax.set_xticks(theta)
+ax.set_xticklabels(deaths_headlines_e.index)
+plt.legend()
+plt.title("Deaths by week over years, England")
+plt.savefig('deaths-radar_england.png')
+plt.show()
+```
+
+```python Collapsed="false"
+# Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#
+
+fig = plt.figure(figsize=(10, 10))
+ax = fig.add_subplot(111, projection="polar")
+
+theta = np.roll(
+    np.flip(
+        np.arange(len(deaths_headlines_w))/float(len(deaths_headlines_w))*2.*np.pi),
+    14)
+l15, = ax.plot(theta, deaths_headlines_w[2015], color="#e47d7d", label="2015") # 0
+l16, = ax.plot(theta, deaths_headlines_w[2016], color="#afc169", label="2016") # 72 , d0e47d
+l17, = ax.plot(theta, deaths_headlines_w[2017], color="#7de4a6", label="2017") # 144
+l18, = ax.plot(theta, deaths_headlines_w[2018], color="#7da6e4", label="2018") # 216
+l19, = ax.plot(theta, deaths_headlines_w[2019], color="#d07de4", label="2019") # 288
+
+lmean, = ax.plot(theta, deaths_headlines_w['previous_mean'], color="black", linestyle='dashed', label="mean")
+
+l20, = ax.plot(theta, deaths_headlines_w[2020], color="red", label="2020")
+
+
+def _closeline(line):
+    x, y = line.get_data()
+    x = np.concatenate((x, [x[0]]))
+    y = np.concatenate((y, [y[0]]))
+    line.set_data(x, y)
+
+[_closeline(l) for l in [l19, l18, l17, l16, l15, lmean]]
+
+
+ax.set_xticks(theta)
+ax.set_xticklabels(deaths_headlines_w.index)
+plt.legend()
+plt.title("Deaths by week over years, Wales")
+plt.savefig('deaths-radar_wales.png')
+plt.show()
+```
+
+```python Collapsed="false"
+# Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#
+
+fig = plt.figure(figsize=(10, 10))
+ax = fig.add_subplot(111, projection="polar")
+
+theta = np.roll(
+    np.flip(
+        np.arange(len(deaths_headlines_s))/float(len(deaths_headlines_s))*2.*np.pi),
+    14)
+l15, = ax.plot(theta, deaths_headlines_s[2015], color="#e47d7d", label="2015") # 0
+l16, = ax.plot(theta, deaths_headlines_s[2016], color="#afc169", label="2016") # 72 , d0e47d
+l17, = ax.plot(theta, deaths_headlines_s[2017], color="#7de4a6", label="2017") # 144
+l18, = ax.plot(theta, deaths_headlines_s[2018], color="#7da6e4", label="2018") # 216
+l19, = ax.plot(theta, deaths_headlines_s[2019], color="#d07de4", label="2019") # 288
+
+lmean, = ax.plot(theta, deaths_headlines_s['previous_mean'], color="black", linestyle='dashed', label="mean")
+
+l20, = ax.plot(theta, deaths_headlines_s[2020], color="red", label="2020")
+
+
+def _closeline(line):
+    x, y = line.get_data()
+    x = np.concatenate((x, [x[0]]))
+    y = np.concatenate((y, [y[0]]))
+    line.set_data(x, y)
+
+[_closeline(l) for l in [l19, l18, l17, l16, l15, lmean]]
+
+
+ax.set_xticks(theta)
+ax.set_xticklabels(deaths_headlines_s.index)
+plt.legend()
+plt.title("Deaths by week over years, Scotland")
+plt.savefig('deaths-radar_scotland.png')
+plt.show()
+```
+
+```python Collapsed="false"
+# Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#
+
+fig = plt.figure(figsize=(10, 10))
+ax = fig.add_subplot(111, projection="polar")
+
+theta = np.roll(
+    np.flip(
+        np.arange(len(deaths_headlines_i))/float(len(deaths_headlines_i))*2.*np.pi),
+    14)
+l15, = ax.plot(theta, deaths_headlines_i[2015], color="#e47d7d", label="2015") # 0
+l16, = ax.plot(theta, deaths_headlines_i[2016], color="#afc169", label="2016") # 72 , d0e47d
+l17, = ax.plot(theta, deaths_headlines_i[2017], color="#7de4a6", label="2017") # 144
+l18, = ax.plot(theta, deaths_headlines_i[2018], color="#7da6e4", label="2018") # 216
+l19, = ax.plot(theta, deaths_headlines_i[2019], color="#d07de4", label="2019") # 288
+
+lmean, = ax.plot(theta, deaths_headlines_i['previous_mean'], color="black", linestyle='dashed', label="mean")
+
+l20, = ax.plot(theta, deaths_headlines_i[2020], color="red", label="2020")
+
+
+def _closeline(line):
+    x, y = line.get_data()
+    x = np.concatenate((x, [x[0]]))
+    y = np.concatenate((y, [y[0]]))
+    line.set_data(x, y)
+
+[_closeline(l) for l in [l19, l18, l17, l16, l15, lmean]]
+
+
+ax.set_xticks(theta)
+ax.set_xticklabels(deaths_headlines_i.index)
+plt.legend()
+plt.title("Deaths by week over years, Northern Ireland")
+plt.savefig('deaths-radar_northern_ireland.png')
+plt.show()
+```
+
+```python Collapsed="false"
+
+```
+
+```python Collapsed="false"
+
+```
diff --git a/estimated_total_deaths.js b/estimated_total_deaths.js

deleted file mode 100644 (file)

index 834fee0..0000000
--- a/estimated_total_deaths.js
+++ /dev/null
@@ -1 +0,0 @@
-document.write('65583');
-\ No newline at end of file
diff --git a/excess_death_accuracy.ipynb b/excess_death_accuracy.ipynb

index 56bb293496572a31aacfc698b004d5cc88fd1ecc..eb372ebb2df5c3cfddcacb9067fd5b870e274439 100644 (file)
--- a/excess_death_accuracy.ipynb
+++ b/excess_death_accuracy.ipynb
@@ -2,8 +2,10 @@
   "cells": [
    {
     "cell_type": "code",
   "cells": [
    {
     "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {},
+   "execution_count": 23,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "import itertools\n",
     "outputs": [],
     "source": [
      "import itertools\n",
@@ -21,8 +23,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
+   "execution_count": 66,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
@@ -51,6 +55,12 @@
         "      <th>deaths_culm</th>\n",
         "      <th>cases_diff</th>\n",
         "      <th>deaths_diff</th>\n",
         "      <th>deaths_culm</th>\n",
         "      <th>cases_diff</th>\n",
         "      <th>deaths_diff</th>\n",
+       "      <th>cases_m7</th>\n",
+       "      <th>deaths_m7</th>\n",
+       "      <th>deaths_g4</th>\n",
+       "      <th>deaths_g7</th>\n",
+       "      <th>doubling_time</th>\n",
+       "      <th>doubling_time_7</th>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>dateRep</th>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>dateRep</th>\n",
@@ -60,6 +70,12 @@
         "      <th></th>\n",
         "      <th></th>\n",
         "      <th></th>\n",
         "      <th></th>\n",
         "      <th></th>\n",
         "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
         "    </tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
         "    </tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
@@ -71,6 +87,12 @@
         "      <td>0</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
         "      <td>0</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-01-01</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-01-01</td>\n",
@@ -80,6 +102,12 @@
         "      <td>0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-01-02</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-01-02</td>\n",
@@ -89,6 +117,12 @@
         "      <td>0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-01-03</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-01-03</td>\n",
@@ -98,6 +132,12 @@
         "      <td>0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-01-04</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-01-04</td>\n",
@@ -107,6 +147,12 @@
         "      <td>0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>...</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>...</td>\n",
@@ -116,76 +162,140 @@
         "      <td>...</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2020-08-08</td>\n",
-       "      <td>871</td>\n",
-       "      <td>98</td>\n",
-       "      <td>309005</td>\n",
-       "      <td>46511</td>\n",
-       "      <td>-79.0</td>\n",
-       "      <td>49.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-09</td>\n",
-       "      <td>758</td>\n",
-       "      <td>55</td>\n",
-       "      <td>309763</td>\n",
-       "      <td>46566</td>\n",
-       "      <td>-113.0</td>\n",
-       "      <td>-43.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-10</td>\n",
-       "      <td>1062</td>\n",
-       "      <td>8</td>\n",
-       "      <td>310825</td>\n",
-       "      <td>46574</td>\n",
-       "      <td>304.0</td>\n",
-       "      <td>-47.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-11</td>\n",
-       "      <td>816</td>\n",
-       "      <td>-48</td>\n",
-       "      <td>311641</td>\n",
-       "      <td>46526</td>\n",
-       "      <td>-246.0</td>\n",
-       "      <td>-56.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-12</td>\n",
-       "      <td>1148</td>\n",
-       "      <td>0</td>\n",
-       "      <td>312789</td>\n",
-       "      <td>46526</td>\n",
-       "      <td>332.0</td>\n",
-       "      <td>48.0</td>\n",
+       "      <td>2020-12-06</td>\n",
+       "      <td>15539</td>\n",
+       "      <td>397</td>\n",
+       "      <td>1705971</td>\n",
+       "      <td>61014</td>\n",
+       "      <td>-759.0</td>\n",
+       "      <td>-107.0</td>\n",
+       "      <td>14399.857143</td>\n",
+       "      <td>426.285714</td>\n",
+       "      <td>481.336835</td>\n",
+       "      <td>391.619248</td>\n",
+       "      <td>88.209086</td>\n",
+       "      <td>108.338041</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-07</td>\n",
+       "      <td>17271</td>\n",
+       "      <td>231</td>\n",
+       "      <td>1723242</td>\n",
+       "      <td>61245</td>\n",
+       "      <td>1732.0</td>\n",
+       "      <td>-166.0</td>\n",
+       "      <td>15130.714286</td>\n",
+       "      <td>428.571429</td>\n",
+       "      <td>371.927543</td>\n",
+       "      <td>395.655665</td>\n",
+       "      <td>114.486195</td>\n",
+       "      <td>107.641011</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-08</td>\n",
+       "      <td>14718</td>\n",
+       "      <td>189</td>\n",
+       "      <td>1737960</td>\n",
+       "      <td>61434</td>\n",
+       "      <td>-2553.0</td>\n",
+       "      <td>-42.0</td>\n",
+       "      <td>15471.857143</td>\n",
+       "      <td>426.571429</td>\n",
+       "      <td>305.719899</td>\n",
+       "      <td>391.637191</td>\n",
+       "      <td>139.633275</td>\n",
+       "      <td>109.076442</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-09</td>\n",
+       "      <td>12281</td>\n",
+       "      <td>599</td>\n",
+       "      <td>1750241</td>\n",
+       "      <td>62033</td>\n",
+       "      <td>-2437.0</td>\n",
+       "      <td>410.0</td>\n",
+       "      <td>15307.857143</td>\n",
+       "      <td>426.000000</td>\n",
+       "      <td>319.207273</td>\n",
+       "      <td>391.264999</td>\n",
+       "      <td>135.048719</td>\n",
+       "      <td>110.241037</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-10</td>\n",
+       "      <td>16578</td>\n",
+       "      <td>533</td>\n",
+       "      <td>1766819</td>\n",
+       "      <td>62566</td>\n",
+       "      <td>4297.0</td>\n",
+       "      <td>-66.0</td>\n",
+       "      <td>15366.142857</td>\n",
+       "      <td>409.571429</td>\n",
+       "      <td>343.603005</td>\n",
+       "      <td>380.495816</td>\n",
+       "      <td>126.560073</td>\n",
+       "      <td>114.322369</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
-       "<p>226 rows × 6 columns</p>\n",
+       "<p>346 rows × 12 columns</p>\n",
         "</div>"
        ],
        "text/plain": [
         "</div>"
        ],
        "text/plain": [
-       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff\n",
-       "dateRep                                                                    \n",
-       "2019-12-31      0       0           0            0         NaN          NaN\n",
-       "2020-01-01      0       0           0            0         0.0          0.0\n",
-       "2020-01-02      0       0           0            0         0.0          0.0\n",
-       "2020-01-03      0       0           0            0         0.0          0.0\n",
-       "2020-01-04      0       0           0            0         0.0          0.0\n",
-       "...           ...     ...         ...          ...         ...          ...\n",
-       "2020-08-08    871      98      309005        46511       -79.0         49.0\n",
-       "2020-08-09    758      55      309763        46566      -113.0        -43.0\n",
-       "2020-08-10   1062       8      310825        46574       304.0        -47.0\n",
-       "2020-08-11    816     -48      311641        46526      -246.0        -56.0\n",
-       "2020-08-12   1148       0      312789        46526       332.0         48.0\n",
+       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff  \\\n",
+       "dateRep                                                                       \n",
+       "2019-12-31      0       0           0            0         NaN          NaN   \n",
+       "2020-01-01      0       0           0            0         0.0          0.0   \n",
+       "2020-01-02      0       0           0            0         0.0          0.0   \n",
+       "2020-01-03      0       0           0            0         0.0          0.0   \n",
+       "2020-01-04      0       0           0            0         0.0          0.0   \n",
+       "...           ...     ...         ...          ...         ...          ...   \n",
+       "2020-12-06  15539     397     1705971        61014      -759.0       -107.0   \n",
+       "2020-12-07  17271     231     1723242        61245      1732.0       -166.0   \n",
+       "2020-12-08  14718     189     1737960        61434     -2553.0        -42.0   \n",
+       "2020-12-09  12281     599     1750241        62033     -2437.0        410.0   \n",
+       "2020-12-10  16578     533     1766819        62566      4297.0        -66.0   \n",
+       "\n",
+       "                cases_m7   deaths_m7   deaths_g4   deaths_g7  doubling_time  \\\n",
+       "dateRep                                                                       \n",
+       "2019-12-31      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-01      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-02      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-03      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-04      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "...                  ...         ...         ...         ...            ...   \n",
+       "2020-12-06  14399.857143  426.285714  481.336835  391.619248      88.209086   \n",
+       "2020-12-07  15130.714286  428.571429  371.927543  395.655665     114.486195   \n",
+       "2020-12-08  15471.857143  426.571429  305.719899  391.637191     139.633275   \n",
+       "2020-12-09  15307.857143  426.000000  319.207273  391.264999     135.048719   \n",
+       "2020-12-10  15366.142857  409.571429  343.603005  380.495816     126.560073   \n",
         "\n",
         "\n",
-       "[226 rows x 6 columns]"
+       "            doubling_time_7  \n",
+       "dateRep                      \n",
+       "2019-12-31              NaN  \n",
+       "2020-01-01              NaN  \n",
+       "2020-01-02              NaN  \n",
+       "2020-01-03              NaN  \n",
+       "2020-01-04              NaN  \n",
+       "...                     ...  \n",
+       "2020-12-06       108.338041  \n",
+       "2020-12-07       107.641011  \n",
+       "2020-12-08       109.076442  \n",
+       "2020-12-09       110.241037  \n",
+       "2020-12-10       114.322369  \n",
+       "\n",
+       "[346 rows x 12 columns]"
        ]
       },
        ]
       },
-     "execution_count": 18,
+     "execution_count": 66,
       "metadata": {},
       "output_type": "execute_result"
      }
       "metadata": {},
       "output_type": "execute_result"
      }
@@ -197,8 +307,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {},
+   "execution_count": 67,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
@@ -553,7 +665,7 @@
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-08-07</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-08-07</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>10236.0</td>\n",
         "      <td>10406.0</td>\n",
         "      <td>10542.0</td>\n",
         "      <td>10278.0</td>\n",
         "      <td>10406.0</td>\n",
         "      <td>10542.0</td>\n",
         "      <td>10278.0</td>\n",
@@ -563,7 +675,7 @@
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-08-14</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-08-14</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>10592.0</td>\n",
         "      <td>10405.0</td>\n",
         "      <td>10091.0</td>\n",
         "      <td>10569.0</td>\n",
         "      <td>10405.0</td>\n",
         "      <td>10091.0</td>\n",
         "      <td>10569.0</td>\n",
@@ -573,7 +685,7 @@
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-08-21</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-08-21</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>10990.0</td>\n",
         "      <td>10279.0</td>\n",
         "      <td>10199.0</td>\n",
         "      <td>10698.0</td>\n",
         "      <td>10279.0</td>\n",
         "      <td>10199.0</td>\n",
         "      <td>10698.0</td>\n",
@@ -583,7 +695,7 @@
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-08-28</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-08-28</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>10364.0</td>\n",
         "      <td>9478.0</td>\n",
         "      <td>9046.0</td>\n",
         "      <td>9372.0</td>\n",
         "      <td>9478.0</td>\n",
         "      <td>9046.0</td>\n",
         "      <td>9372.0</td>\n",
@@ -593,7 +705,7 @@
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-09-04</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-09-04</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>9023.0</td>\n",
         "      <td>10918.0</td>\n",
         "      <td>10680.0</td>\n",
         "      <td>10781.0</td>\n",
         "      <td>10918.0</td>\n",
         "      <td>10680.0</td>\n",
         "      <td>10781.0</td>\n",
@@ -603,7 +715,7 @@
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-09-11</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-09-11</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>11176.0</td>\n",
         "      <td>10892.0</td>\n",
         "      <td>10496.0</td>\n",
         "      <td>10692.0</td>\n",
         "      <td>10892.0</td>\n",
         "      <td>10496.0</td>\n",
         "      <td>10692.0</td>\n",
@@ -613,7 +725,7 @@
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-09-18</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-09-18</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>10797.0</td>\n",
         "      <td>10792.0</td>\n",
         "      <td>10498.0</td>\n",
         "      <td>10875.0</td>\n",
         "      <td>10792.0</td>\n",
         "      <td>10498.0</td>\n",
         "      <td>10875.0</td>\n",
@@ -623,7 +735,7 @@
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-09-25</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-09-25</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>10890.0</td>\n",
         "      <td>10954.0</td>\n",
         "      <td>10463.0</td>\n",
         "      <td>11027.0</td>\n",
         "      <td>10954.0</td>\n",
         "      <td>10463.0</td>\n",
         "      <td>11027.0</td>\n",
@@ -633,7 +745,7 @@
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-10-02</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-10-02</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>11468.0</td>\n",
         "      <td>11113.0</td>\n",
         "      <td>10869.0</td>\n",
         "      <td>11101.0</td>\n",
         "      <td>11113.0</td>\n",
         "      <td>10869.0</td>\n",
         "      <td>11101.0</td>\n",
@@ -643,7 +755,7 @@
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-10-09</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-10-09</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>11373.0</td>\n",
         "      <td>11403.0</td>\n",
         "      <td>11048.0</td>\n",
         "      <td>11357.0</td>\n",
         "      <td>11403.0</td>\n",
         "      <td>11048.0</td>\n",
         "      <td>11357.0</td>\n",
@@ -653,7 +765,7 @@
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-10-16</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-10-16</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>11943.0</td>\n",
         "      <td>11625.0</td>\n",
         "      <td>11177.0</td>\n",
         "      <td>11389.0</td>\n",
         "      <td>11625.0</td>\n",
         "      <td>11177.0</td>\n",
         "      <td>11389.0</td>\n",
@@ -663,7 +775,7 @@
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-10-23</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-10-23</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>12317.0</td>\n",
         "      <td>11415.0</td>\n",
         "      <td>10885.0</td>\n",
         "      <td>11152.0</td>\n",
         "      <td>11415.0</td>\n",
         "      <td>10885.0</td>\n",
         "      <td>11152.0</td>\n",
@@ -673,7 +785,7 @@
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-10-30</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-10-30</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>12517.0</td>\n",
         "      <td>11567.0</td>\n",
         "      <td>10866.0</td>\n",
         "      <td>11366.0</td>\n",
         "      <td>11567.0</td>\n",
         "      <td>10866.0</td>\n",
         "      <td>11366.0</td>\n",
@@ -683,7 +795,7 @@
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-11-06</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-11-06</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>13448.0</td>\n",
         "      <td>12177.0</td>\n",
         "      <td>11588.0</td>\n",
         "      <td>11767.0</td>\n",
         "      <td>12177.0</td>\n",
         "      <td>11588.0</td>\n",
         "      <td>11767.0</td>\n",
@@ -693,7 +805,7 @@
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-11-13</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-11-13</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>13798.0</td>\n",
         "      <td>12146.0</td>\n",
         "      <td>11552.0</td>\n",
         "      <td>11773.0</td>\n",
         "      <td>12146.0</td>\n",
         "      <td>11552.0</td>\n",
         "      <td>11773.0</td>\n",
@@ -703,7 +815,7 @@
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-11-20</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-11-20</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>14291.0</td>\n",
         "      <td>12472.0</td>\n",
         "      <td>11289.0</td>\n",
         "      <td>12102.0</td>\n",
         "      <td>12472.0</td>\n",
         "      <td>11289.0</td>\n",
         "      <td>12102.0</td>\n",
@@ -713,7 +825,7 @@
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-11-27</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-11-27</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>14132.0</td>\n",
         "      <td>12455.0</td>\n",
         "      <td>11392.0</td>\n",
         "      <td>12046.0</td>\n",
         "      <td>12455.0</td>\n",
         "      <td>11392.0</td>\n",
         "      <td>12046.0</td>\n",
@@ -799,23 +911,23 @@
         "2020-07-17     10096.0     10324.0     10353.0     10426.0     10672.0   \n",
         "2020-07-24     10159.0     10422.0     10356.0     10147.0     10612.0   \n",
         "2020-07-31     10262.0     10564.0     10408.0     10239.0     10433.0   \n",
         "2020-07-17     10096.0     10324.0     10353.0     10426.0     10672.0   \n",
         "2020-07-24     10159.0     10422.0     10356.0     10147.0     10612.0   \n",
         "2020-07-31     10262.0     10564.0     10408.0     10239.0     10433.0   \n",
-       "2020-08-07         NaN     10406.0     10542.0     10278.0     10439.0   \n",
-       "2020-08-14         NaN     10405.0     10091.0     10569.0     10312.0   \n",
-       "2020-08-21         NaN     10279.0     10199.0     10698.0     10637.0   \n",
-       "2020-08-28         NaN      9478.0      9046.0      9372.0      9226.0   \n",
-       "2020-09-04         NaN     10918.0     10680.0     10781.0     10681.0   \n",
-       "2020-09-11         NaN     10892.0     10496.0     10692.0     10401.0   \n",
-       "2020-09-18         NaN     10792.0     10498.0     10875.0     10183.0   \n",
-       "2020-09-25         NaN     10954.0     10463.0     11027.0     10278.0   \n",
-       "2020-10-02         NaN     11113.0     10869.0     11101.0     10671.0   \n",
-       "2020-10-09         NaN     11403.0     11048.0     11357.0     11016.0   \n",
-       "2020-10-16         NaN     11625.0     11177.0     11389.0     11134.0   \n",
-       "2020-10-23         NaN     11415.0     10885.0     11152.0     11048.0   \n",
-       "2020-10-30         NaN     11567.0     10866.0     11366.0     11463.0   \n",
-       "2020-11-06         NaN     12177.0     11588.0     11767.0     11803.0   \n",
-       "2020-11-13         NaN     12146.0     11552.0     11773.0     12209.0   \n",
-       "2020-11-20         NaN     12472.0     11289.0     12102.0     12064.0   \n",
-       "2020-11-27         NaN     12455.0     11392.0     12046.0     11901.0   \n",
+       "2020-08-07     10236.0     10406.0     10542.0     10278.0     10439.0   \n",
+       "2020-08-14     10592.0     10405.0     10091.0     10569.0     10312.0   \n",
+       "2020-08-21     10990.0     10279.0     10199.0     10698.0     10637.0   \n",
+       "2020-08-28     10364.0      9478.0      9046.0      9372.0      9226.0   \n",
+       "2020-09-04      9023.0     10918.0     10680.0     10781.0     10681.0   \n",
+       "2020-09-11     11176.0     10892.0     10496.0     10692.0     10401.0   \n",
+       "2020-09-18     10797.0     10792.0     10498.0     10875.0     10183.0   \n",
+       "2020-09-25     10890.0     10954.0     10463.0     11027.0     10278.0   \n",
+       "2020-10-02     11468.0     11113.0     10869.0     11101.0     10671.0   \n",
+       "2020-10-09     11373.0     11403.0     11048.0     11357.0     11016.0   \n",
+       "2020-10-16     11943.0     11625.0     11177.0     11389.0     11134.0   \n",
+       "2020-10-23     12317.0     11415.0     10885.0     11152.0     11048.0   \n",
+       "2020-10-30     12517.0     11567.0     10866.0     11366.0     11463.0   \n",
+       "2020-11-06     13448.0     12177.0     11588.0     11767.0     11803.0   \n",
+       "2020-11-13     13798.0     12146.0     11552.0     11773.0     12209.0   \n",
+       "2020-11-20     14291.0     12472.0     11289.0     12102.0     12064.0   \n",
+       "2020-11-27     14132.0     12455.0     11392.0     12046.0     11901.0   \n",
         "2020-12-04         NaN     12275.0     11687.0     12342.0     12733.0   \n",
         "2020-12-11         NaN     12853.0     12078.0     12924.0     12076.0   \n",
         "2020-12-18         NaN     13566.0     12649.0     14308.0     13137.0   \n",
         "2020-12-04         NaN     12275.0     11687.0     12342.0     12733.0   \n",
         "2020-12-11         NaN     12853.0     12078.0     12924.0     12076.0   \n",
         "2020-12-18         NaN     13566.0     12649.0     14308.0     13137.0   \n",
@@ -877,7 +989,7 @@
         "2020-12-25        9806         9231.2  "
        ]
       },
         "2020-12-25        9806         9231.2  "
        ]
       },
-     "execution_count": 19,
+     "execution_count": 67,
       "metadata": {},
       "output_type": "execute_result"
      }
       "metadata": {},
       "output_type": "execute_result"
      }
@@ -889,8 +1001,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {},
+   "execution_count": 68,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
@@ -919,6 +1033,12 @@
         "      <th>deaths_culm</th>\n",
         "      <th>cases_diff</th>\n",
         "      <th>deaths_diff</th>\n",
         "      <th>deaths_culm</th>\n",
         "      <th>cases_diff</th>\n",
         "      <th>deaths_diff</th>\n",
+       "      <th>cases_m7</th>\n",
+       "      <th>deaths_m7</th>\n",
+       "      <th>deaths_g4</th>\n",
+       "      <th>deaths_g7</th>\n",
+       "      <th>doubling_time</th>\n",
+       "      <th>doubling_time_7</th>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>dateRep</th>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>dateRep</th>\n",
@@ -928,6 +1048,12 @@
         "      <th></th>\n",
         "      <th></th>\n",
         "      <th></th>\n",
         "      <th></th>\n",
         "      <th></th>\n",
         "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
         "    </tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
         "    </tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
@@ -939,6 +1065,12 @@
         "      <td>0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.000000e+00</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-01-10</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-01-10</td>\n",
@@ -948,6 +1080,12 @@
         "      <td>0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.000000e+00</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-01-17</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-01-17</td>\n",
@@ -957,6 +1095,12 @@
         "      <td>0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.000000e+00</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-01-24</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-01-24</td>\n",
@@ -966,6 +1110,12 @@
         "      <td>0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.000000e+00</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-01-31</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-01-31</td>\n",
@@ -975,6 +1125,12 @@
         "      <td>0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.000000e+00</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-02-07</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-02-07</td>\n",
@@ -984,6 +1140,12 @@
         "      <td>0</td>\n",
         "      <td>1.0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0</td>\n",
         "      <td>1.0</td>\n",
         "      <td>0.0</td>\n",
+       "      <td>2.571429</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.000000e+00</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-02-14</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-02-14</td>\n",
@@ -993,6 +1155,12 @@
         "      <td>0</td>\n",
         "      <td>-1.0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0</td>\n",
         "      <td>-1.0</td>\n",
         "      <td>0.0</td>\n",
+       "      <td>5.142857</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.000000e+00</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-02-21</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-02-21</td>\n",
@@ -1002,6 +1170,12 @@
         "      <td>0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0.0</td>\n",
+       "      <td>2.285714</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.000000e+00</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-02-28</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-02-28</td>\n",
@@ -1011,6 +1185,12 @@
         "      <td>0</td>\n",
         "      <td>4.0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0</td>\n",
         "      <td>4.0</td>\n",
         "      <td>0.0</td>\n",
+       "      <td>3.714286</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.000000e+00</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-03-06</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-03-06</td>\n",
@@ -1020,6 +1200,12 @@
         "      <td>0</td>\n",
         "      <td>52.0</td>\n",
         "      <td>0.0</td>\n",
         "      <td>0</td>\n",
         "      <td>52.0</td>\n",
         "      <td>0.0</td>\n",
+       "      <td>83.571429</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.000000e+00</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-03-13</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-03-13</td>\n",
@@ -1029,248 +1215,764 @@
         "      <td>31</td>\n",
         "      <td>350.0</td>\n",
         "      <td>2.0</td>\n",
         "      <td>31</td>\n",
         "      <td>350.0</td>\n",
         "      <td>2.0</td>\n",
+       "      <td>514.000000</td>\n",
+       "      <td>4.428571</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>inf</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-03-20</td>\n",
         "      <td>4144</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-03-20</td>\n",
         "      <td>4144</td>\n",
-       "      <td>149</td>\n",
+       "      <td>153</td>\n",
         "      <td>23173</td>\n",
         "      <td>23173</td>\n",
-       "      <td>500</td>\n",
+       "      <td>507</td>\n",
         "      <td>593.0</td>\n",
         "      <td>593.0</td>\n",
-       "      <td>41.0</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>2699.142857</td>\n",
+       "      <td>68.000000</td>\n",
+       "      <td>79.504887</td>\n",
+       "      <td>24.257733</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>inf</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-03-27</td>\n",
         "      <td>12291</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-03-27</td>\n",
         "      <td>12291</td>\n",
-       "      <td>720</td>\n",
+       "      <td>722</td>\n",
         "      <td>78855</td>\n",
         "      <td>78855</td>\n",
-       "      <td>3169</td>\n",
+       "      <td>3197</td>\n",
         "      <td>1693.0</td>\n",
         "      <td>1693.0</td>\n",
-       "      <td>140.0</td>\n",
+       "      <td>135.0</td>\n",
+       "      <td>7954.571429</td>\n",
+       "      <td>384.285714</td>\n",
+       "      <td>464.807614</td>\n",
+       "      <td>327.583287</td>\n",
+       "      <td>3.577040e+01</td>\n",
+       "      <td>4.797282e+01</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-03</td>\n",
         "      <td>25664</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-03</td>\n",
         "      <td>25664</td>\n",
-       "      <td>2870</td>\n",
+       "      <td>2898</td>\n",
         "      <td>217112</td>\n",
         "      <td>217112</td>\n",
-       "      <td>15602</td>\n",
+       "      <td>15722</td>\n",
         "      <td>2221.0</td>\n",
         "      <td>2221.0</td>\n",
-       "      <td>469.0</td>\n",
+       "      <td>476.0</td>\n",
+       "      <td>19751.000000</td>\n",
+       "      <td>1789.285714</td>\n",
+       "      <td>2153.720503</td>\n",
+       "      <td>1633.574291</td>\n",
+       "      <td>3.702651e+01</td>\n",
+       "      <td>4.931862e+01</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-10</td>\n",
         "      <td>33254</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-10</td>\n",
         "      <td>33254</td>\n",
-       "      <td>5868</td>\n",
+       "      <td>5909</td>\n",
         "      <td>433554</td>\n",
         "      <td>433554</td>\n",
-       "      <td>47578</td>\n",
+       "      <td>47916</td>\n",
         "      <td>218.0</td>\n",
         "      <td>218.0</td>\n",
-       "      <td>458.0</td>\n",
+       "      <td>459.0</td>\n",
+       "      <td>30920.285714</td>\n",
+       "      <td>4599.142857</td>\n",
+       "      <td>5088.524097</td>\n",
+       "      <td>4416.476344</td>\n",
+       "      <td>4.749914e+01</td>\n",
+       "      <td>5.457682e+01</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-17</td>\n",
         "      <td>29808</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-17</td>\n",
         "      <td>29808</td>\n",
-       "      <td>6340</td>\n",
+       "      <td>6338</td>\n",
         "      <td>654431</td>\n",
         "      <td>654431</td>\n",
-       "      <td>92676</td>\n",
+       "      <td>92954</td>\n",
         "      <td>-66.0</td>\n",
         "      <td>-66.0</td>\n",
-       "      <td>-81.0</td>\n",
+       "      <td>-80.0</td>\n",
+       "      <td>31553.857143</td>\n",
+       "      <td>6434.000000</td>\n",
+       "      <td>6392.991495</td>\n",
+       "      <td>6269.311492</td>\n",
+       "      <td>7.441501e+01</td>\n",
+       "      <td>7.427834e+01</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-24</td>\n",
         "      <td>33923</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-24</td>\n",
         "      <td>33923</td>\n",
-       "      <td>5845</td>\n",
+       "      <td>5773</td>\n",
         "      <td>880467</td>\n",
         "      <td>880467</td>\n",
-       "      <td>135580</td>\n",
+       "      <td>135712</td>\n",
         "      <td>422.0</td>\n",
         "      <td>422.0</td>\n",
-       "      <td>-302.0</td>\n",
+       "      <td>-354.0</td>\n",
+       "      <td>32290.857143</td>\n",
+       "      <td>6108.285714</td>\n",
+       "      <td>5745.091557</td>\n",
+       "      <td>5865.493228</td>\n",
+       "      <td>1.196415e+02</td>\n",
+       "      <td>1.151654e+02</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-01</td>\n",
         "      <td>32226</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-01</td>\n",
         "      <td>32226</td>\n",
-       "      <td>4987</td>\n",
+       "      <td>4881</td>\n",
         "      <td>1110138</td>\n",
         "      <td>1110138</td>\n",
-       "      <td>173156</td>\n",
+       "      <td>172753</td>\n",
         "      <td>-45.0</td>\n",
         "      <td>-45.0</td>\n",
-       "      <td>-53.0</td>\n",
+       "      <td>-48.0</td>\n",
+       "      <td>32810.142857</td>\n",
+       "      <td>5291.571429</td>\n",
+       "      <td>4695.525928</td>\n",
+       "      <td>4919.730986</td>\n",
+       "      <td>1.890979e+02</td>\n",
+       "      <td>1.744465e+02</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-08</td>\n",
         "      <td>26812</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-08</td>\n",
         "      <td>26812</td>\n",
-       "      <td>3850</td>\n",
+       "      <td>3638</td>\n",
         "      <td>1320759</td>\n",
         "      <td>1320759</td>\n",
-       "      <td>203075</td>\n",
+       "      <td>201454</td>\n",
         "      <td>-1615.0</td>\n",
         "      <td>-1615.0</td>\n",
-       "      <td>-134.0</td>\n",
+       "      <td>-176.0</td>\n",
+       "      <td>30088.714286</td>\n",
+       "      <td>4100.142857</td>\n",
+       "      <td>3669.542328</td>\n",
+       "      <td>3786.175573</td>\n",
+       "      <td>2.839767e+02</td>\n",
+       "      <td>2.627153e+02</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-15</td>\n",
         "      <td>21611</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-15</td>\n",
         "      <td>21611</td>\n",
-       "      <td>3006</td>\n",
+       "      <td>2671</td>\n",
         "      <td>1481545</td>\n",
         "      <td>1481545</td>\n",
-       "      <td>226425</td>\n",
+       "      <td>222871</td>\n",
         "      <td>-520.0</td>\n",
         "      <td>-520.0</td>\n",
-       "      <td>-112.0</td>\n",
+       "      <td>-106.0</td>\n",
+       "      <td>22969.428571</td>\n",
+       "      <td>3059.571429</td>\n",
+       "      <td>2677.524456</td>\n",
+       "      <td>2785.255471</td>\n",
+       "      <td>4.329725e+02</td>\n",
+       "      <td>3.948088e+02</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-22</td>\n",
         "      <td>17430</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-22</td>\n",
         "      <td>17430</td>\n",
-       "      <td>2449</td>\n",
+       "      <td>2075</td>\n",
         "      <td>1614993</td>\n",
         "      <td>1614993</td>\n",
-       "      <td>245286</td>\n",
+       "      <td>239208</td>\n",
         "      <td>-589.0</td>\n",
         "      <td>-589.0</td>\n",
-       "      <td>-90.0</td>\n",
+       "      <td>-79.0</td>\n",
+       "      <td>19064.000000</td>\n",
+       "      <td>2333.857143</td>\n",
+       "      <td>1947.928544</td>\n",
+       "      <td>2022.217125</td>\n",
+       "      <td>6.541432e+02</td>\n",
+       "      <td>5.836862e+02</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-29</td>\n",
         "      <td>12658</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-29</td>\n",
         "      <td>12658</td>\n",
-       "      <td>2199</td>\n",
+       "      <td>1890</td>\n",
         "      <td>1722647</td>\n",
         "      <td>1722647</td>\n",
-       "      <td>261258</td>\n",
+       "      <td>252717</td>\n",
         "      <td>-883.0</td>\n",
         "      <td>-883.0</td>\n",
-       "      <td>78.0</td>\n",
+       "      <td>70.0</td>\n",
+       "      <td>15379.142857</td>\n",
+       "      <td>1929.857143</td>\n",
+       "      <td>1732.798698</td>\n",
+       "      <td>1728.444472</td>\n",
+       "      <td>7.391467e+02</td>\n",
+       "      <td>7.173609e+02</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-05</td>\n",
         "      <td>9772</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-05</td>\n",
         "      <td>9772</td>\n",
-       "      <td>1697</td>\n",
+       "      <td>1207</td>\n",
         "      <td>1797791</td>\n",
         "      <td>1797791</td>\n",
-       "      <td>274939</td>\n",
+       "      <td>263570</td>\n",
         "      <td>-479.0</td>\n",
         "      <td>-479.0</td>\n",
-       "      <td>-239.0</td>\n",
+       "      <td>-213.0</td>\n",
+       "      <td>10734.857143</td>\n",
+       "      <td>1550.428571</td>\n",
+       "      <td>1257.247277</td>\n",
+       "      <td>1322.817820</td>\n",
+       "      <td>1.135760e+03</td>\n",
+       "      <td>9.930720e+02</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-12</td>\n",
         "      <td>7341</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-12</td>\n",
         "      <td>7341</td>\n",
-       "      <td>1388</td>\n",
+       "      <td>937</td>\n",
         "      <td>1855247</td>\n",
         "      <td>1855247</td>\n",
-       "      <td>285795</td>\n",
+       "      <td>271259</td>\n",
         "      <td>-157.0</td>\n",
         "      <td>-157.0</td>\n",
-       "      <td>-25.0</td>\n",
+       "      <td>-54.0</td>\n",
+       "      <td>8208.000000</td>\n",
+       "      <td>1098.428571</td>\n",
+       "      <td>916.682753</td>\n",
+       "      <td>940.775215</td>\n",
+       "      <td>1.593893e+03</td>\n",
+       "      <td>1.416581e+03</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-19</td>\n",
         "      <td>6939</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-19</td>\n",
         "      <td>6939</td>\n",
-       "      <td>1018</td>\n",
+       "      <td>591</td>\n",
         "      <td>1905027</td>\n",
         "      <td>1905027</td>\n",
-       "      <td>293710</td>\n",
+       "      <td>276164</td>\n",
         "      <td>-186.0</td>\n",
         "      <td>-186.0</td>\n",
-       "      <td>-15.0</td>\n",
+       "      <td>-9.0</td>\n",
+       "      <td>7111.428571</td>\n",
+       "      <td>700.714286</td>\n",
+       "      <td>563.512973</td>\n",
+       "      <td>593.415144</td>\n",
+       "      <td>2.647618e+03</td>\n",
+       "      <td>2.299498e+03</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-26</td>\n",
         "      <td>5899</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-26</td>\n",
         "      <td>5899</td>\n",
-       "      <td>835</td>\n",
+       "      <td>480</td>\n",
         "      <td>1950419</td>\n",
         "      <td>1950419</td>\n",
-       "      <td>300001</td>\n",
+       "      <td>279624</td>\n",
         "      <td>-235.0</td>\n",
         "      <td>-235.0</td>\n",
-       "      <td>12.0</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>6484.571429</td>\n",
+       "      <td>494.285714</td>\n",
+       "      <td>416.381335</td>\n",
+       "      <td>421.990143</td>\n",
+       "      <td>3.585584e+03</td>\n",
+       "      <td>3.235524e+03</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-03</td>\n",
         "      <td>4485</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-03</td>\n",
         "      <td>4485</td>\n",
-       "      <td>765</td>\n",
+       "      <td>360</td>\n",
         "      <td>1985555</td>\n",
         "      <td>1985555</td>\n",
-       "      <td>305684</td>\n",
+       "      <td>282616</td>\n",
         "      <td>-127.0</td>\n",
         "      <td>-127.0</td>\n",
-       "      <td>-60.0</td>\n",
+       "      <td>-58.0</td>\n",
+       "      <td>5019.428571</td>\n",
+       "      <td>427.428571</td>\n",
+       "      <td>376.617800</td>\n",
+       "      <td>366.017611</td>\n",
+       "      <td>4.038218e+03</td>\n",
+       "      <td>3.764706e+03</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-10</td>\n",
         "      <td>4131</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-10</td>\n",
         "      <td>4131</td>\n",
-       "      <td>607</td>\n",
+       "      <td>253</td>\n",
         "      <td>2014685</td>\n",
         "      <td>2014685</td>\n",
-       "      <td>310295</td>\n",
+       "      <td>284705</td>\n",
         "      <td>42.0</td>\n",
         "      <td>42.0</td>\n",
-       "      <td>-4.0</td>\n",
+       "      <td>-10.0</td>\n",
+       "      <td>4161.428571</td>\n",
+       "      <td>298.428571</td>\n",
+       "      <td>248.675598</td>\n",
+       "      <td>258.540406</td>\n",
+       "      <td>6.117937e+03</td>\n",
+       "      <td>5.408341e+03</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-17</td>\n",
         "      <td>4266</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-17</td>\n",
         "      <td>4266</td>\n",
-       "      <td>517</td>\n",
+       "      <td>164</td>\n",
         "      <td>2044059</td>\n",
         "      <td>2044059</td>\n",
-       "      <td>314237</td>\n",
+       "      <td>286128</td>\n",
         "      <td>79.0</td>\n",
         "      <td>79.0</td>\n",
-       "      <td>-19.0</td>\n",
+       "      <td>-7.0</td>\n",
+       "      <td>4196.285714</td>\n",
+       "      <td>203.285714</td>\n",
+       "      <td>166.283290</td>\n",
+       "      <td>171.181184</td>\n",
+       "      <td>9.430925e+03</td>\n",
+       "      <td>8.243797e+03</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-24</td>\n",
         "      <td>4496</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-24</td>\n",
         "      <td>4496</td>\n",
-       "      <td>435</td>\n",
+       "      <td>107</td>\n",
         "      <td>2074665</td>\n",
         "      <td>2074665</td>\n",
-       "      <td>317595</td>\n",
+       "      <td>287092</td>\n",
         "      <td>1.0</td>\n",
         "      <td>1.0</td>\n",
-       "      <td>-13.0</td>\n",
+       "      <td>-15.0</td>\n",
+       "      <td>4372.285714</td>\n",
+       "      <td>137.714286</td>\n",
+       "      <td>118.278798</td>\n",
+       "      <td>120.912224</td>\n",
+       "      <td>1.271636e+04</td>\n",
+       "      <td>1.165442e+04</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-31</td>\n",
         "      <td>3869</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-31</td>\n",
         "      <td>3869</td>\n",
-       "      <td>445</td>\n",
+       "      <td>113</td>\n",
         "      <td>2104314</td>\n",
         "      <td>2104314</td>\n",
-       "      <td>320764</td>\n",
+       "      <td>287889</td>\n",
         "      <td>73.0</td>\n",
         "      <td>73.0</td>\n",
-       "      <td>-15.0</td>\n",
+       "      <td>-9.0</td>\n",
+       "      <td>4235.571429</td>\n",
+       "      <td>113.857143</td>\n",
+       "      <td>79.927160</td>\n",
+       "      <td>82.049806</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>inf</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-08-07</td>\n",
         "      <td>5833</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-08-07</td>\n",
         "      <td>5833</td>\n",
-       "      <td>414</td>\n",
+       "      <td>89</td>\n",
         "      <td>2139062</td>\n",
         "      <td>2139062</td>\n",
-       "      <td>323799</td>\n",
+       "      <td>288530</td>\n",
         "      <td>104.0</td>\n",
         "      <td>104.0</td>\n",
-       "      <td>11.0</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>4964.000000</td>\n",
+       "      <td>91.571429</td>\n",
+       "      <td>26.017737</td>\n",
+       "      <td>9.273227</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>inf</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-08-14</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-08-14</td>\n",
-       "      <td>4655</td>\n",
-       "      <td>113</td>\n",
-       "      <td>1554023</td>\n",
-       "      <td>232703</td>\n",
-       "      <td>198.0</td>\n",
-       "      <td>-49.0</td>\n",
+       "      <td>6793</td>\n",
+       "      <td>89</td>\n",
+       "      <td>2182748</td>\n",
+       "      <td>289102</td>\n",
+       "      <td>179.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>6240.857143</td>\n",
+       "      <td>81.714286</td>\n",
+       "      <td>77.224731</td>\n",
+       "      <td>64.479846</td>\n",
+       "      <td>2.011138e+04</td>\n",
+       "      <td>2.245319e+04</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-08-21</td>\n",
+       "      <td>7353</td>\n",
+       "      <td>56</td>\n",
+       "      <td>2235156</td>\n",
+       "      <td>289635</td>\n",
+       "      <td>53.0</td>\n",
+       "      <td>-12.0</td>\n",
+       "      <td>7486.857143</td>\n",
+       "      <td>76.142857</td>\n",
+       "      <td>57.415692</td>\n",
+       "      <td>61.994254</td>\n",
+       "      <td>2.822494e+04</td>\n",
+       "      <td>2.333077e+04</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-08-28</td>\n",
+       "      <td>8088</td>\n",
+       "      <td>74</td>\n",
+       "      <td>2287182</td>\n",
+       "      <td>290081</td>\n",
+       "      <td>340.0</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>7432.285714</td>\n",
+       "      <td>63.714286</td>\n",
+       "      <td>54.517208</td>\n",
+       "      <td>49.287140</td>\n",
+       "      <td>2.710076e+04</td>\n",
+       "      <td>2.908195e+04</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-09-04</td>\n",
+       "      <td>10043</td>\n",
+       "      <td>50</td>\n",
+       "      <td>2350991</td>\n",
+       "      <td>290529</td>\n",
+       "      <td>213.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>9115.571429</td>\n",
+       "      <td>64.000000</td>\n",
+       "      <td>45.709346</td>\n",
+       "      <td>49.612299</td>\n",
+       "      <td>4.258905e+04</td>\n",
+       "      <td>3.069208e+04</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-09-11</td>\n",
+       "      <td>17727</td>\n",
+       "      <td>81</td>\n",
+       "      <td>2449684</td>\n",
+       "      <td>290979</td>\n",
+       "      <td>1184.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>14099.000000</td>\n",
+       "      <td>64.285714</td>\n",
+       "      <td>55.103648</td>\n",
+       "      <td>46.741257</td>\n",
+       "      <td>2.723477e+04</td>\n",
+       "      <td>3.156956e+04</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-09-18</td>\n",
+       "      <td>23476</td>\n",
+       "      <td>97</td>\n",
+       "      <td>2600541</td>\n",
+       "      <td>291555</td>\n",
+       "      <td>476.0</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>21551.000000</td>\n",
+       "      <td>82.285714</td>\n",
+       "      <td>76.375361</td>\n",
+       "      <td>65.232921</td>\n",
+       "      <td>2.020206e+04</td>\n",
+       "      <td>2.224637e+04</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-09-25</td>\n",
+       "      <td>34749</td>\n",
+       "      <td>197</td>\n",
+       "      <td>2798819</td>\n",
+       "      <td>292645</td>\n",
+       "      <td>3239.0</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>28325.428571</td>\n",
+       "      <td>155.714286</td>\n",
+       "      <td>161.214801</td>\n",
+       "      <td>143.205548</td>\n",
+       "      <td>8.901465e+03</td>\n",
+       "      <td>1.026870e+04</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-02</td>\n",
+       "      <td>43815</td>\n",
+       "      <td>300</td>\n",
+       "      <td>3086093</td>\n",
+       "      <td>294313</td>\n",
+       "      <td>280.0</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>41039.142857</td>\n",
+       "      <td>238.285714</td>\n",
+       "      <td>230.060916</td>\n",
+       "      <td>211.544534</td>\n",
+       "      <td>6.473932e+03</td>\n",
+       "      <td>6.827996e+03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-09</td>\n",
+       "      <td>101637</td>\n",
+       "      <td>390</td>\n",
+       "      <td>3601915</td>\n",
+       "      <td>296856</td>\n",
+       "      <td>10626.0</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>73688.857143</td>\n",
+       "      <td>363.285714</td>\n",
+       "      <td>349.704548</td>\n",
+       "      <td>322.563025</td>\n",
+       "      <td>4.291457e+03</td>\n",
+       "      <td>4.498907e+03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-16</td>\n",
+       "      <td>111807</td>\n",
+       "      <td>701</td>\n",
+       "      <td>4351113</td>\n",
+       "      <td>300605</td>\n",
+       "      <td>1438.0</td>\n",
+       "      <td>61.0</td>\n",
+       "      <td>107028.285714</td>\n",
+       "      <td>535.571429</td>\n",
+       "      <td>577.496284</td>\n",
+       "      <td>499.621044</td>\n",
+       "      <td>2.571463e+03</td>\n",
+       "      <td>3.038155e+03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-23</td>\n",
+       "      <td>136845</td>\n",
+       "      <td>1054</td>\n",
+       "      <td>5220544</td>\n",
+       "      <td>306852</td>\n",
+       "      <td>2260.0</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>124204.428571</td>\n",
+       "      <td>892.428571</td>\n",
+       "      <td>903.798899</td>\n",
+       "      <td>829.790586</td>\n",
+       "      <td>1.681682e+03</td>\n",
+       "      <td>1.816643e+03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-30</td>\n",
+       "      <td>154873</td>\n",
+       "      <td>1608</td>\n",
+       "      <td>6278688</td>\n",
+       "      <td>316205</td>\n",
+       "      <td>1827.0</td>\n",
+       "      <td>91.0</td>\n",
+       "      <td>151163.428571</td>\n",
+       "      <td>1336.142857</td>\n",
+       "      <td>1363.375912</td>\n",
+       "      <td>1244.302740</td>\n",
+       "      <td>1.144987e+03</td>\n",
+       "      <td>1.253041e+03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-06</td>\n",
+       "      <td>157857</td>\n",
+       "      <td>2165</td>\n",
+       "      <td>7386321</td>\n",
+       "      <td>329466</td>\n",
+       "      <td>1073.0</td>\n",
+       "      <td>98.0</td>\n",
+       "      <td>158233.285714</td>\n",
+       "      <td>1894.428571</td>\n",
+       "      <td>1869.072858</td>\n",
+       "      <td>1756.119532</td>\n",
+       "      <td>8.748452e+02</td>\n",
+       "      <td>9.175873e+02</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-13</td>\n",
+       "      <td>166998</td>\n",
+       "      <td>2808</td>\n",
+       "      <td>8503996</td>\n",
+       "      <td>346708</td>\n",
+       "      <td>9332.0</td>\n",
+       "      <td>185.0</td>\n",
+       "      <td>159667.857143</td>\n",
+       "      <td>2463.142857</td>\n",
+       "      <td>2401.361299</td>\n",
+       "      <td>2249.701288</td>\n",
+       "      <td>7.273019e+02</td>\n",
+       "      <td>7.528714e+02</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-20</td>\n",
+       "      <td>163061</td>\n",
+       "      <td>2847</td>\n",
+       "      <td>9716180</td>\n",
+       "      <td>366945</td>\n",
+       "      <td>-10555.0</td>\n",
+       "      <td>-62.0</td>\n",
+       "      <td>173169.142857</td>\n",
+       "      <td>2891.000000</td>\n",
+       "      <td>2708.892132</td>\n",
+       "      <td>2619.031072</td>\n",
+       "      <td>6.907600e+02</td>\n",
+       "      <td>6.823344e+02</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-27</td>\n",
+       "      <td>121306</td>\n",
+       "      <td>3256</td>\n",
+       "      <td>10676794</td>\n",
+       "      <td>388295</td>\n",
+       "      <td>-5360.0</td>\n",
+       "      <td>-3.0</td>\n",
+       "      <td>137230.571429</td>\n",
+       "      <td>3050.000000</td>\n",
+       "      <td>2934.861534</td>\n",
+       "      <td>2753.026893</td>\n",
+       "      <td>6.765205e+02</td>\n",
+       "      <td>6.882603e+02</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-04</td>\n",
+       "      <td>99572</td>\n",
+       "      <td>3082</td>\n",
+       "      <td>11417933</td>\n",
+       "      <td>411137</td>\n",
+       "      <td>-2677.0</td>\n",
+       "      <td>-84.0</td>\n",
+       "      <td>105877.000000</td>\n",
+       "      <td>3263.142857</td>\n",
+       "      <td>2966.168647</td>\n",
+       "      <td>2988.661808</td>\n",
+       "      <td>7.059253e+02</td>\n",
+       "      <td>6.717400e+02</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-11</td>\n",
+       "      <td>92685</td>\n",
+       "      <td>2453</td>\n",
+       "      <td>10374665</td>\n",
+       "      <td>368909</td>\n",
+       "      <td>1700.0</td>\n",
+       "      <td>119.0</td>\n",
+       "      <td>90123.714286</td>\n",
+       "      <td>2555.000000</td>\n",
+       "      <td>2356.150688</td>\n",
+       "      <td>2352.938908</td>\n",
+       "      <td>6.829136e+02</td>\n",
+       "      <td>6.544146e+02</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "</div>"
        ],
        "text/plain": [
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "</div>"
        ],
        "text/plain": [
-       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff\n",
-       "dateRep                                                                    \n",
-       "2020-01-03      0       0           0            0         0.0          0.0\n",
-       "2020-01-10      0       0           0            0         0.0          0.0\n",
-       "2020-01-17      0       0           0            0         0.0          0.0\n",
-       "2020-01-24      0       0           0            0         0.0          0.0\n",
-       "2020-01-31      0       0           0            0         0.0          0.0\n",
-       "2020-02-07      4       0          18            0         1.0          0.0\n",
-       "2020-02-14      6       0          54            0        -1.0          0.0\n",
-       "2020-02-21      0       0          70            0         0.0          0.0\n",
-       "2020-02-28     12       0          96            0         4.0          0.0\n",
-       "2020-03-06    198       0         681            0        52.0          0.0\n",
-       "2020-03-13   1062       9        4279           31       350.0          2.0\n",
-       "2020-03-20   4144     149       23173          500       593.0         41.0\n",
-       "2020-03-27  12291     720       78855         3169      1693.0        140.0\n",
-       "2020-04-03  25664    2870      217112        15602      2221.0        469.0\n",
-       "2020-04-10  33254    5868      433554        47578       218.0        458.0\n",
-       "2020-04-17  29808    6340      654431        92676       -66.0        -81.0\n",
-       "2020-04-24  33923    5845      880467       135580       422.0       -302.0\n",
-       "2020-05-01  32226    4987     1110138       173156       -45.0        -53.0\n",
-       "2020-05-08  26812    3850     1320759       203075     -1615.0       -134.0\n",
-       "2020-05-15  21611    3006     1481545       226425      -520.0       -112.0\n",
-       "2020-05-22  17430    2449     1614993       245286      -589.0        -90.0\n",
-       "2020-05-29  12658    2199     1722647       261258      -883.0         78.0\n",
-       "2020-06-05   9772    1697     1797791       274939      -479.0       -239.0\n",
-       "2020-06-12   7341    1388     1855247       285795      -157.0        -25.0\n",
-       "2020-06-19   6939    1018     1905027       293710      -186.0        -15.0\n",
-       "2020-06-26   5899     835     1950419       300001      -235.0         12.0\n",
-       "2020-07-03   4485     765     1985555       305684      -127.0        -60.0\n",
-       "2020-07-10   4131     607     2014685       310295        42.0         -4.0\n",
-       "2020-07-17   4266     517     2044059       314237        79.0        -19.0\n",
-       "2020-07-24   4496     435     2074665       317595         1.0        -13.0\n",
-       "2020-07-31   3869     445     2104314       320764        73.0        -15.0\n",
-       "2020-08-07   5833     414     2139062       323799       104.0         11.0\n",
-       "2020-08-14   4655     113     1554023       232703       198.0        -49.0"
+       "             cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff  \\\n",
+       "dateRep                                                                        \n",
+       "2020-01-03       0       0           0            0         0.0          0.0   \n",
+       "2020-01-10       0       0           0            0         0.0          0.0   \n",
+       "2020-01-17       0       0           0            0         0.0          0.0   \n",
+       "2020-01-24       0       0           0            0         0.0          0.0   \n",
+       "2020-01-31       0       0           0            0         0.0          0.0   \n",
+       "2020-02-07       4       0          18            0         1.0          0.0   \n",
+       "2020-02-14       6       0          54            0        -1.0          0.0   \n",
+       "2020-02-21       0       0          70            0         0.0          0.0   \n",
+       "2020-02-28      12       0          96            0         4.0          0.0   \n",
+       "2020-03-06     198       0         681            0        52.0          0.0   \n",
+       "2020-03-13    1062       9        4279           31       350.0          2.0   \n",
+       "2020-03-20    4144     153       23173          507       593.0         44.0   \n",
+       "2020-03-27   12291     722       78855         3197      1693.0        135.0   \n",
+       "2020-04-03   25664    2898      217112        15722      2221.0        476.0   \n",
+       "2020-04-10   33254    5909      433554        47916       218.0        459.0   \n",
+       "2020-04-17   29808    6338      654431        92954       -66.0        -80.0   \n",
+       "2020-04-24   33923    5773      880467       135712       422.0       -354.0   \n",
+       "2020-05-01   32226    4881     1110138       172753       -45.0        -48.0   \n",
+       "2020-05-08   26812    3638     1320759       201454     -1615.0       -176.0   \n",
+       "2020-05-15   21611    2671     1481545       222871      -520.0       -106.0   \n",
+       "2020-05-22   17430    2075     1614993       239208      -589.0        -79.0   \n",
+       "2020-05-29   12658    1890     1722647       252717      -883.0         70.0   \n",
+       "2020-06-05    9772    1207     1797791       263570      -479.0       -213.0   \n",
+       "2020-06-12    7341     937     1855247       271259      -157.0        -54.0   \n",
+       "2020-06-19    6939     591     1905027       276164      -186.0         -9.0   \n",
+       "2020-06-26    5899     480     1950419       279624      -235.0         32.0   \n",
+       "2020-07-03    4485     360     1985555       282616      -127.0        -58.0   \n",
+       "2020-07-10    4131     253     2014685       284705        42.0        -10.0   \n",
+       "2020-07-17    4266     164     2044059       286128        79.0         -7.0   \n",
+       "2020-07-24    4496     107     2074665       287092         1.0        -15.0   \n",
+       "2020-07-31    3869     113     2104314       287889        73.0         -9.0   \n",
+       "2020-08-07    5833      89     2139062       288530       104.0         18.0   \n",
+       "2020-08-14    6793      89     2182748       289102       179.0          0.0   \n",
+       "2020-08-21    7353      56     2235156       289635        53.0        -12.0   \n",
+       "2020-08-28    8088      74     2287182       290081       340.0          6.0   \n",
+       "2020-09-04   10043      50     2350991       290529       213.0          1.0   \n",
+       "2020-09-11   17727      81     2449684       290979      1184.0          1.0   \n",
+       "2020-09-18   23476      97     2600541       291555       476.0          7.0   \n",
+       "2020-09-25   34749     197     2798819       292645      3239.0         19.0   \n",
+       "2020-10-02   43815     300     3086093       294313       280.0         19.0   \n",
+       "2020-10-09  101637     390     3601915       296856     10626.0         18.0   \n",
+       "2020-10-16  111807     701     4351113       300605      1438.0         61.0   \n",
+       "2020-10-23  136845    1054     5220544       306852      2260.0         51.0   \n",
+       "2020-10-30  154873    1608     6278688       316205      1827.0         91.0   \n",
+       "2020-11-06  157857    2165     7386321       329466      1073.0         98.0   \n",
+       "2020-11-13  166998    2808     8503996       346708      9332.0        185.0   \n",
+       "2020-11-20  163061    2847     9716180       366945    -10555.0        -62.0   \n",
+       "2020-11-27  121306    3256    10676794       388295     -5360.0         -3.0   \n",
+       "2020-12-04   99572    3082    11417933       411137     -2677.0        -84.0   \n",
+       "2020-12-11   92685    2453    10374665       368909      1700.0        119.0   \n",
+       "\n",
+       "                 cases_m7    deaths_m7    deaths_g4    deaths_g7  \\\n",
+       "dateRep                                                            \n",
+       "2020-01-03       0.000000     0.000000     0.000000     0.000000   \n",
+       "2020-01-10       0.000000     0.000000     0.000000     0.000000   \n",
+       "2020-01-17       0.000000     0.000000     0.000000     0.000000   \n",
+       "2020-01-24       0.000000     0.000000     0.000000     0.000000   \n",
+       "2020-01-31       0.000000     0.000000     0.000000     0.000000   \n",
+       "2020-02-07       2.571429     0.000000     0.000000     0.000000   \n",
+       "2020-02-14       5.142857     0.000000     0.000000     0.000000   \n",
+       "2020-02-21       2.285714     0.000000     0.000000     0.000000   \n",
+       "2020-02-28       3.714286     0.000000     0.000000     0.000000   \n",
+       "2020-03-06      83.571429     0.000000     0.000000     0.000000   \n",
+       "2020-03-13     514.000000     4.428571     0.000000     0.000000   \n",
+       "2020-03-20    2699.142857    68.000000    79.504887    24.257733   \n",
+       "2020-03-27    7954.571429   384.285714   464.807614   327.583287   \n",
+       "2020-04-03   19751.000000  1789.285714  2153.720503  1633.574291   \n",
+       "2020-04-10   30920.285714  4599.142857  5088.524097  4416.476344   \n",
+       "2020-04-17   31553.857143  6434.000000  6392.991495  6269.311492   \n",
+       "2020-04-24   32290.857143  6108.285714  5745.091557  5865.493228   \n",
+       "2020-05-01   32810.142857  5291.571429  4695.525928  4919.730986   \n",
+       "2020-05-08   30088.714286  4100.142857  3669.542328  3786.175573   \n",
+       "2020-05-15   22969.428571  3059.571429  2677.524456  2785.255471   \n",
+       "2020-05-22   19064.000000  2333.857143  1947.928544  2022.217125   \n",
+       "2020-05-29   15379.142857  1929.857143  1732.798698  1728.444472   \n",
+       "2020-06-05   10734.857143  1550.428571  1257.247277  1322.817820   \n",
+       "2020-06-12    8208.000000  1098.428571   916.682753   940.775215   \n",
+       "2020-06-19    7111.428571   700.714286   563.512973   593.415144   \n",
+       "2020-06-26    6484.571429   494.285714   416.381335   421.990143   \n",
+       "2020-07-03    5019.428571   427.428571   376.617800   366.017611   \n",
+       "2020-07-10    4161.428571   298.428571   248.675598   258.540406   \n",
+       "2020-07-17    4196.285714   203.285714   166.283290   171.181184   \n",
+       "2020-07-24    4372.285714   137.714286   118.278798   120.912224   \n",
+       "2020-07-31    4235.571429   113.857143    79.927160    82.049806   \n",
+       "2020-08-07    4964.000000    91.571429    26.017737     9.273227   \n",
+       "2020-08-14    6240.857143    81.714286    77.224731    64.479846   \n",
+       "2020-08-21    7486.857143    76.142857    57.415692    61.994254   \n",
+       "2020-08-28    7432.285714    63.714286    54.517208    49.287140   \n",
+       "2020-09-04    9115.571429    64.000000    45.709346    49.612299   \n",
+       "2020-09-11   14099.000000    64.285714    55.103648    46.741257   \n",
+       "2020-09-18   21551.000000    82.285714    76.375361    65.232921   \n",
+       "2020-09-25   28325.428571   155.714286   161.214801   143.205548   \n",
+       "2020-10-02   41039.142857   238.285714   230.060916   211.544534   \n",
+       "2020-10-09   73688.857143   363.285714   349.704548   322.563025   \n",
+       "2020-10-16  107028.285714   535.571429   577.496284   499.621044   \n",
+       "2020-10-23  124204.428571   892.428571   903.798899   829.790586   \n",
+       "2020-10-30  151163.428571  1336.142857  1363.375912  1244.302740   \n",
+       "2020-11-06  158233.285714  1894.428571  1869.072858  1756.119532   \n",
+       "2020-11-13  159667.857143  2463.142857  2401.361299  2249.701288   \n",
+       "2020-11-20  173169.142857  2891.000000  2708.892132  2619.031072   \n",
+       "2020-11-27  137230.571429  3050.000000  2934.861534  2753.026893   \n",
+       "2020-12-04  105877.000000  3263.142857  2966.168647  2988.661808   \n",
+       "2020-12-11   90123.714286  2555.000000  2356.150688  2352.938908   \n",
+       "\n",
+       "            doubling_time  doubling_time_7  \n",
+       "dateRep                                     \n",
+       "2020-01-03   0.000000e+00     0.000000e+00  \n",
+       "2020-01-10   0.000000e+00     0.000000e+00  \n",
+       "2020-01-17   0.000000e+00     0.000000e+00  \n",
+       "2020-01-24   0.000000e+00     0.000000e+00  \n",
+       "2020-01-31   0.000000e+00     0.000000e+00  \n",
+       "2020-02-07   0.000000e+00     0.000000e+00  \n",
+       "2020-02-14   0.000000e+00     0.000000e+00  \n",
+       "2020-02-21   0.000000e+00     0.000000e+00  \n",
+       "2020-02-28   0.000000e+00     0.000000e+00  \n",
+       "2020-03-06   0.000000e+00     0.000000e+00  \n",
+       "2020-03-13            inf              inf  \n",
+       "2020-03-20            inf              inf  \n",
+       "2020-03-27   3.577040e+01     4.797282e+01  \n",
+       "2020-04-03   3.702651e+01     4.931862e+01  \n",
+       "2020-04-10   4.749914e+01     5.457682e+01  \n",
+       "2020-04-17   7.441501e+01     7.427834e+01  \n",
+       "2020-04-24   1.196415e+02     1.151654e+02  \n",
+       "2020-05-01   1.890979e+02     1.744465e+02  \n",
+       "2020-05-08   2.839767e+02     2.627153e+02  \n",
+       "2020-05-15   4.329725e+02     3.948088e+02  \n",
+       "2020-05-22   6.541432e+02     5.836862e+02  \n",
+       "2020-05-29   7.391467e+02     7.173609e+02  \n",
+       "2020-06-05   1.135760e+03     9.930720e+02  \n",
+       "2020-06-12   1.593893e+03     1.416581e+03  \n",
+       "2020-06-19   2.647618e+03     2.299498e+03  \n",
+       "2020-06-26   3.585584e+03     3.235524e+03  \n",
+       "2020-07-03   4.038218e+03     3.764706e+03  \n",
+       "2020-07-10   6.117937e+03     5.408341e+03  \n",
+       "2020-07-17   9.430925e+03     8.243797e+03  \n",
+       "2020-07-24   1.271636e+04     1.165442e+04  \n",
+       "2020-07-31            inf              inf  \n",
+       "2020-08-07            inf              inf  \n",
+       "2020-08-14   2.011138e+04     2.245319e+04  \n",
+       "2020-08-21   2.822494e+04     2.333077e+04  \n",
+       "2020-08-28   2.710076e+04     2.908195e+04  \n",
+       "2020-09-04   4.258905e+04     3.069208e+04  \n",
+       "2020-09-11   2.723477e+04     3.156956e+04  \n",
+       "2020-09-18   2.020206e+04     2.224637e+04  \n",
+       "2020-09-25   8.901465e+03     1.026870e+04  \n",
+       "2020-10-02   6.473932e+03     6.827996e+03  \n",
+       "2020-10-09   4.291457e+03     4.498907e+03  \n",
+       "2020-10-16   2.571463e+03     3.038155e+03  \n",
+       "2020-10-23   1.681682e+03     1.816643e+03  \n",
+       "2020-10-30   1.144987e+03     1.253041e+03  \n",
+       "2020-11-06   8.748452e+02     9.175873e+02  \n",
+       "2020-11-13   7.273019e+02     7.528714e+02  \n",
+       "2020-11-20   6.907600e+02     6.823344e+02  \n",
+       "2020-11-27   6.765205e+02     6.882603e+02  \n",
+       "2020-12-04   7.059253e+02     6.717400e+02  \n",
+       "2020-12-11   6.829136e+02     6.544146e+02  "
        ]
       },
        ]
       },
-     "execution_count": 20,
+     "execution_count": 68,
       "metadata": {},
       "output_type": "execute_result"
      }
       "metadata": {},
       "output_type": "execute_result"
      }
@@ -1282,8 +1984,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
+   "execution_count": 69,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
@@ -1316,121 +2020,223 @@
         "      <td>2020-03-20</td>\n",
         "      <td>12112.0</td>\n",
         "      <td>12007.4</td>\n",
         "      <td>2020-03-20</td>\n",
         "      <td>12112.0</td>\n",
         "      <td>12007.4</td>\n",
-       "      <td>149</td>\n",
+       "      <td>153</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-03-27</td>\n",
         "      <td>12507.0</td>\n",
         "      <td>11549.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-03-27</td>\n",
         "      <td>12507.0</td>\n",
         "      <td>11549.6</td>\n",
-       "      <td>720</td>\n",
+       "      <td>722</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-03</td>\n",
         "      <td>18565.0</td>\n",
         "      <td>11681.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-03</td>\n",
         "      <td>18565.0</td>\n",
         "      <td>11681.4</td>\n",
-       "      <td>2870</td>\n",
+       "      <td>2898</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-10</td>\n",
         "      <td>20929.0</td>\n",
         "      <td>11919.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-10</td>\n",
         "      <td>20929.0</td>\n",
         "      <td>11919.4</td>\n",
-       "      <td>5868</td>\n",
+       "      <td>5909</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-17</td>\n",
         "      <td>24691.0</td>\n",
         "      <td>11850.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-17</td>\n",
         "      <td>24691.0</td>\n",
         "      <td>11850.6</td>\n",
-       "      <td>6340</td>\n",
+       "      <td>6338</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-24</td>\n",
         "      <td>24303.0</td>\n",
         "      <td>11844.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-24</td>\n",
         "      <td>24303.0</td>\n",
         "      <td>11844.4</td>\n",
-       "      <td>5845</td>\n",
+       "      <td>5773</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-01</td>\n",
         "      <td>20059.0</td>\n",
         "      <td>11318.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-01</td>\n",
         "      <td>20059.0</td>\n",
         "      <td>11318.4</td>\n",
-       "      <td>4987</td>\n",
+       "      <td>4881</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-08</td>\n",
         "      <td>14428.0</td>\n",
         "      <td>10887.2</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-08</td>\n",
         "      <td>14428.0</td>\n",
         "      <td>10887.2</td>\n",
-       "      <td>3850</td>\n",
+       "      <td>3638</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-15</td>\n",
         "      <td>16390.0</td>\n",
         "      <td>11547.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-15</td>\n",
         "      <td>16390.0</td>\n",
         "      <td>11547.0</td>\n",
-       "      <td>3006</td>\n",
+       "      <td>2671</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-22</td>\n",
         "      <td>13839.0</td>\n",
         "      <td>11281.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-22</td>\n",
         "      <td>13839.0</td>\n",
         "      <td>11281.0</td>\n",
-       "      <td>2449</td>\n",
+       "      <td>2075</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-29</td>\n",
         "      <td>11265.0</td>\n",
         "      <td>9448.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-29</td>\n",
         "      <td>11265.0</td>\n",
         "      <td>9448.0</td>\n",
-       "      <td>2199</td>\n",
+       "      <td>1890</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-05</td>\n",
         "      <td>12106.0</td>\n",
         "      <td>11325.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-05</td>\n",
         "      <td>12106.0</td>\n",
         "      <td>11325.6</td>\n",
-       "      <td>1697</td>\n",
+       "      <td>1207</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-12</td>\n",
         "      <td>11302.0</td>\n",
         "      <td>10703.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-12</td>\n",
         "      <td>11302.0</td>\n",
         "      <td>10703.6</td>\n",
-       "      <td>1388</td>\n",
+       "      <td>937</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-19</td>\n",
         "      <td>10694.0</td>\n",
         "      <td>10698.2</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-19</td>\n",
         "      <td>10694.0</td>\n",
         "      <td>10698.2</td>\n",
-       "      <td>1018</td>\n",
+       "      <td>591</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-26</td>\n",
         "      <td>10282.0</td>\n",
         "      <td>10605.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-26</td>\n",
         "      <td>10282.0</td>\n",
         "      <td>10605.6</td>\n",
-       "      <td>835</td>\n",
+       "      <td>480</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-03</td>\n",
         "      <td>10412.0</td>\n",
         "      <td>10483.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-03</td>\n",
         "      <td>10412.0</td>\n",
         "      <td>10483.0</td>\n",
-       "      <td>765</td>\n",
+       "      <td>360</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-10</td>\n",
         "      <td>9941.0</td>\n",
         "      <td>10509.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-10</td>\n",
         "      <td>9941.0</td>\n",
         "      <td>10509.4</td>\n",
-       "      <td>607</td>\n",
+       "      <td>253</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-17</td>\n",
         "      <td>10096.0</td>\n",
         "      <td>10360.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-17</td>\n",
         "      <td>10096.0</td>\n",
         "      <td>10360.6</td>\n",
-       "      <td>517</td>\n",
+       "      <td>164</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-24</td>\n",
         "      <td>10159.0</td>\n",
         "      <td>10311.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-24</td>\n",
         "      <td>10159.0</td>\n",
         "      <td>10311.6</td>\n",
-       "      <td>435</td>\n",
+       "      <td>107</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-31</td>\n",
         "      <td>10262.0</td>\n",
         "      <td>10307.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-31</td>\n",
         "      <td>10262.0</td>\n",
         "      <td>10307.4</td>\n",
-       "      <td>445</td>\n",
+       "      <td>113</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-08-07</td>\n",
+       "      <td>10236.0</td>\n",
+       "      <td>10363.6</td>\n",
+       "      <td>89</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-08-14</td>\n",
+       "      <td>10592.0</td>\n",
+       "      <td>10345.8</td>\n",
+       "      <td>89</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-08-21</td>\n",
+       "      <td>10990.0</td>\n",
+       "      <td>10433.4</td>\n",
+       "      <td>56</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-08-28</td>\n",
+       "      <td>10364.0</td>\n",
+       "      <td>9472.2</td>\n",
+       "      <td>74</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-09-04</td>\n",
+       "      <td>9023.0</td>\n",
+       "      <td>10430.4</td>\n",
+       "      <td>50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-09-11</td>\n",
+       "      <td>11176.0</td>\n",
+       "      <td>10610.8</td>\n",
+       "      <td>81</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-09-18</td>\n",
+       "      <td>10797.0</td>\n",
+       "      <td>10545.8</td>\n",
+       "      <td>97</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-09-25</td>\n",
+       "      <td>10890.0</td>\n",
+       "      <td>10709.6</td>\n",
+       "      <td>197</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-02</td>\n",
+       "      <td>11468.0</td>\n",
+       "      <td>10890.8</td>\n",
+       "      <td>300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-09</td>\n",
+       "      <td>11373.0</td>\n",
+       "      <td>11186.4</td>\n",
+       "      <td>390</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-16</td>\n",
+       "      <td>11943.0</td>\n",
+       "      <td>11224.8</td>\n",
+       "      <td>701</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-23</td>\n",
+       "      <td>12317.0</td>\n",
+       "      <td>11093.2</td>\n",
+       "      <td>1054</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-30</td>\n",
+       "      <td>12517.0</td>\n",
+       "      <td>11257.6</td>\n",
+       "      <td>1608</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-06</td>\n",
+       "      <td>13448.0</td>\n",
+       "      <td>11729.4</td>\n",
+       "      <td>2165</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-13</td>\n",
+       "      <td>13798.0</td>\n",
+       "      <td>11803.6</td>\n",
+       "      <td>2808</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-20</td>\n",
+       "      <td>14291.0</td>\n",
+       "      <td>11821.0</td>\n",
+       "      <td>2847</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-27</td>\n",
+       "      <td>14132.0</td>\n",
+       "      <td>11802.0</td>\n",
+       "      <td>3256</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
@@ -1438,29 +2244,46 @@
        ],
        "text/plain": [
         "            total_2020  previous_mean  covid_deaths\n",
        ],
        "text/plain": [
         "            total_2020  previous_mean  covid_deaths\n",
-       "2020-03-20     12112.0        12007.4           149\n",
-       "2020-03-27     12507.0        11549.6           720\n",
-       "2020-04-03     18565.0        11681.4          2870\n",
-       "2020-04-10     20929.0        11919.4          5868\n",
-       "2020-04-17     24691.0        11850.6          6340\n",
-       "2020-04-24     24303.0        11844.4          5845\n",
-       "2020-05-01     20059.0        11318.4          4987\n",
-       "2020-05-08     14428.0        10887.2          3850\n",
-       "2020-05-15     16390.0        11547.0          3006\n",
-       "2020-05-22     13839.0        11281.0          2449\n",
-       "2020-05-29     11265.0         9448.0          2199\n",
-       "2020-06-05     12106.0        11325.6          1697\n",
-       "2020-06-12     11302.0        10703.6          1388\n",
-       "2020-06-19     10694.0        10698.2          1018\n",
-       "2020-06-26     10282.0        10605.6           835\n",
-       "2020-07-03     10412.0        10483.0           765\n",
-       "2020-07-10      9941.0        10509.4           607\n",
-       "2020-07-17     10096.0        10360.6           517\n",
-       "2020-07-24     10159.0        10311.6           435\n",
-       "2020-07-31     10262.0        10307.4           445"
+       "2020-03-20     12112.0        12007.4           153\n",
+       "2020-03-27     12507.0        11549.6           722\n",
+       "2020-04-03     18565.0        11681.4          2898\n",
+       "2020-04-10     20929.0        11919.4          5909\n",
+       "2020-04-17     24691.0        11850.6          6338\n",
+       "2020-04-24     24303.0        11844.4          5773\n",
+       "2020-05-01     20059.0        11318.4          4881\n",
+       "2020-05-08     14428.0        10887.2          3638\n",
+       "2020-05-15     16390.0        11547.0          2671\n",
+       "2020-05-22     13839.0        11281.0          2075\n",
+       "2020-05-29     11265.0         9448.0          1890\n",
+       "2020-06-05     12106.0        11325.6          1207\n",
+       "2020-06-12     11302.0        10703.6           937\n",
+       "2020-06-19     10694.0        10698.2           591\n",
+       "2020-06-26     10282.0        10605.6           480\n",
+       "2020-07-03     10412.0        10483.0           360\n",
+       "2020-07-10      9941.0        10509.4           253\n",
+       "2020-07-17     10096.0        10360.6           164\n",
+       "2020-07-24     10159.0        10311.6           107\n",
+       "2020-07-31     10262.0        10307.4           113\n",
+       "2020-08-07     10236.0        10363.6            89\n",
+       "2020-08-14     10592.0        10345.8            89\n",
+       "2020-08-21     10990.0        10433.4            56\n",
+       "2020-08-28     10364.0         9472.2            74\n",
+       "2020-09-04      9023.0        10430.4            50\n",
+       "2020-09-11     11176.0        10610.8            81\n",
+       "2020-09-18     10797.0        10545.8            97\n",
+       "2020-09-25     10890.0        10709.6           197\n",
+       "2020-10-02     11468.0        10890.8           300\n",
+       "2020-10-09     11373.0        11186.4           390\n",
+       "2020-10-16     11943.0        11224.8           701\n",
+       "2020-10-23     12317.0        11093.2          1054\n",
+       "2020-10-30     12517.0        11257.6          1608\n",
+       "2020-11-06     13448.0        11729.4          2165\n",
+       "2020-11-13     13798.0        11803.6          2808\n",
+       "2020-11-20     14291.0        11821.0          2847\n",
+       "2020-11-27     14132.0        11802.0          3256"
        ]
       },
        ]
       },
-     "execution_count": 21,
+     "execution_count": 69,
       "metadata": {},
       "output_type": "execute_result"
      }
       "metadata": {},
       "output_type": "execute_result"
      }
@@ -1473,10 +2296,21 @@
      "excess_deaths"
     ]
    },
      "excess_deaths"
     ]
    },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "source": [
+    "## Correction for the dip in deaths being in week 36, not the usual week 35"
+   ]
+  },
    {
     "cell_type": "code",
    {
     "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {},
+   "execution_count": 70,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
@@ -1502,206 +2336,572 @@
         "      <th>total_2020</th>\n",
         "      <th>previous_mean</th>\n",
         "      <th>covid_deaths</th>\n",
         "      <th>total_2020</th>\n",
         "      <th>previous_mean</th>\n",
         "      <th>covid_deaths</th>\n",
-       "      <th>excess</th>\n",
         "    </tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
         "    </tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
-       "      <td>2020-03-20</td>\n",
-       "      <td>12112.0</td>\n",
-       "      <td>12007.4</td>\n",
-       "      <td>149</td>\n",
-       "      <td>104.6</td>\n",
+       "      <td>2020-08-14</td>\n",
+       "      <td>10592.0</td>\n",
+       "      <td>10345.8</td>\n",
+       "      <td>89</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2020-03-27</td>\n",
-       "      <td>12507.0</td>\n",
-       "      <td>11549.6</td>\n",
-       "      <td>720</td>\n",
-       "      <td>957.4</td>\n",
+       "      <td>2020-08-21</td>\n",
+       "      <td>10990.0</td>\n",
+       "      <td>10433.4</td>\n",
+       "      <td>56</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2020-04-03</td>\n",
-       "      <td>18565.0</td>\n",
-       "      <td>11681.4</td>\n",
-       "      <td>2870</td>\n",
-       "      <td>6883.6</td>\n",
+       "      <td>2020-08-28</td>\n",
+       "      <td>9023.0</td>\n",
+       "      <td>9472.2</td>\n",
+       "      <td>74</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2020-04-10</td>\n",
-       "      <td>20929.0</td>\n",
-       "      <td>11919.4</td>\n",
-       "      <td>5868</td>\n",
-       "      <td>9009.6</td>\n",
+       "      <td>2020-09-04</td>\n",
+       "      <td>10364.0</td>\n",
+       "      <td>10430.4</td>\n",
+       "      <td>50</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2020-04-17</td>\n",
-       "      <td>24691.0</td>\n",
-       "      <td>11850.6</td>\n",
-       "      <td>6340</td>\n",
-       "      <td>12840.4</td>\n",
+       "      <td>2020-09-11</td>\n",
+       "      <td>11176.0</td>\n",
+       "      <td>10610.8</td>\n",
+       "      <td>81</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2020-04-24</td>\n",
-       "      <td>24303.0</td>\n",
-       "      <td>11844.4</td>\n",
-       "      <td>5845</td>\n",
-       "      <td>12458.6</td>\n",
+       "      <td>2020-09-18</td>\n",
+       "      <td>10797.0</td>\n",
+       "      <td>10545.8</td>\n",
+       "      <td>97</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2020-05-01</td>\n",
-       "      <td>20059.0</td>\n",
-       "      <td>11318.4</td>\n",
-       "      <td>4987</td>\n",
-       "      <td>8740.6</td>\n",
+       "      <td>2020-09-25</td>\n",
+       "      <td>10890.0</td>\n",
+       "      <td>10709.6</td>\n",
+       "      <td>197</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2020-05-08</td>\n",
-       "      <td>14428.0</td>\n",
-       "      <td>10887.2</td>\n",
-       "      <td>3850</td>\n",
-       "      <td>3540.8</td>\n",
+       "      <td>2020-10-02</td>\n",
+       "      <td>11468.0</td>\n",
+       "      <td>10890.8</td>\n",
+       "      <td>300</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2020-05-15</td>\n",
-       "      <td>16390.0</td>\n",
-       "      <td>11547.0</td>\n",
-       "      <td>3006</td>\n",
+       "      <td>2020-10-09</td>\n",
+       "      <td>11373.0</td>\n",
+       "      <td>11186.4</td>\n",
+       "      <td>390</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-16</td>\n",
+       "      <td>11943.0</td>\n",
+       "      <td>11224.8</td>\n",
+       "      <td>701</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-23</td>\n",
+       "      <td>12317.0</td>\n",
+       "      <td>11093.2</td>\n",
+       "      <td>1054</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-30</td>\n",
+       "      <td>12517.0</td>\n",
+       "      <td>11257.6</td>\n",
+       "      <td>1608</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-06</td>\n",
+       "      <td>13448.0</td>\n",
+       "      <td>11729.4</td>\n",
+       "      <td>2165</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-13</td>\n",
+       "      <td>13798.0</td>\n",
+       "      <td>11803.6</td>\n",
+       "      <td>2808</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-20</td>\n",
+       "      <td>14291.0</td>\n",
+       "      <td>11821.0</td>\n",
+       "      <td>2847</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-27</td>\n",
+       "      <td>14132.0</td>\n",
+       "      <td>11802.0</td>\n",
+       "      <td>3256</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            total_2020  previous_mean  covid_deaths\n",
+       "2020-08-14     10592.0        10345.8            89\n",
+       "2020-08-21     10990.0        10433.4            56\n",
+       "2020-08-28      9023.0         9472.2            74\n",
+       "2020-09-04     10364.0        10430.4            50\n",
+       "2020-09-11     11176.0        10610.8            81\n",
+       "2020-09-18     10797.0        10545.8            97\n",
+       "2020-09-25     10890.0        10709.6           197\n",
+       "2020-10-02     11468.0        10890.8           300\n",
+       "2020-10-09     11373.0        11186.4           390\n",
+       "2020-10-16     11943.0        11224.8           701\n",
+       "2020-10-23     12317.0        11093.2          1054\n",
+       "2020-10-30     12517.0        11257.6          1608\n",
+       "2020-11-06     13448.0        11729.4          2165\n",
+       "2020-11-13     13798.0        11803.6          2808\n",
+       "2020-11-20     14291.0        11821.0          2847\n",
+       "2020-11-27     14132.0        11802.0          3256"
+      ]
+     },
+     "execution_count": 70,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "temp1 = excess_deaths.loc['2020-08-28'].total_2020\n",
+    "temp2 = excess_deaths.loc['2020-09-04'].total_2020\n",
+    "excess_deaths.loc['2020-08-28', 'total_2020'] = temp2\n",
+    "excess_deaths.loc['2020-09-04', 'total_2020'] = temp1\n",
+    "excess_deaths.loc['2020-08-14':]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(10364.0, 9023.0)"
+      ]
+     },
+     "execution_count": 71,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "temp1, temp2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>total_2020</th>\n",
+       "      <th>previous_mean</th>\n",
+       "      <th>covid_deaths</th>\n",
+       "      <th>excess</th>\n",
+       "      <th>attributable</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>2020-03-20</td>\n",
+       "      <td>12112.0</td>\n",
+       "      <td>12007.4</td>\n",
+       "      <td>153</td>\n",
+       "      <td>104.6</td>\n",
+       "      <td>153.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-03-27</td>\n",
+       "      <td>12507.0</td>\n",
+       "      <td>11549.6</td>\n",
+       "      <td>722</td>\n",
+       "      <td>957.4</td>\n",
+       "      <td>957.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-04-03</td>\n",
+       "      <td>18565.0</td>\n",
+       "      <td>11681.4</td>\n",
+       "      <td>2898</td>\n",
+       "      <td>6883.6</td>\n",
+       "      <td>6883.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-04-10</td>\n",
+       "      <td>20929.0</td>\n",
+       "      <td>11919.4</td>\n",
+       "      <td>5909</td>\n",
+       "      <td>9009.6</td>\n",
+       "      <td>9009.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-04-17</td>\n",
+       "      <td>24691.0</td>\n",
+       "      <td>11850.6</td>\n",
+       "      <td>6338</td>\n",
+       "      <td>12840.4</td>\n",
+       "      <td>12840.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-04-24</td>\n",
+       "      <td>24303.0</td>\n",
+       "      <td>11844.4</td>\n",
+       "      <td>5773</td>\n",
+       "      <td>12458.6</td>\n",
+       "      <td>12458.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-05-01</td>\n",
+       "      <td>20059.0</td>\n",
+       "      <td>11318.4</td>\n",
+       "      <td>4881</td>\n",
+       "      <td>8740.6</td>\n",
+       "      <td>8740.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-05-08</td>\n",
+       "      <td>14428.0</td>\n",
+       "      <td>10887.2</td>\n",
+       "      <td>3638</td>\n",
+       "      <td>3540.8</td>\n",
+       "      <td>3638.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-05-15</td>\n",
+       "      <td>16390.0</td>\n",
+       "      <td>11547.0</td>\n",
+       "      <td>2671</td>\n",
+       "      <td>4843.0</td>\n",
         "      <td>4843.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-22</td>\n",
         "      <td>13839.0</td>\n",
         "      <td>11281.0</td>\n",
         "      <td>4843.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-22</td>\n",
         "      <td>13839.0</td>\n",
         "      <td>11281.0</td>\n",
-       "      <td>2449</td>\n",
+       "      <td>2075</td>\n",
+       "      <td>2558.0</td>\n",
         "      <td>2558.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-29</td>\n",
         "      <td>11265.0</td>\n",
         "      <td>9448.0</td>\n",
         "      <td>2558.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-29</td>\n",
         "      <td>11265.0</td>\n",
         "      <td>9448.0</td>\n",
-       "      <td>2199</td>\n",
+       "      <td>1890</td>\n",
         "      <td>1817.0</td>\n",
         "      <td>1817.0</td>\n",
+       "      <td>1890.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-05</td>\n",
         "      <td>12106.0</td>\n",
         "      <td>11325.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-05</td>\n",
         "      <td>12106.0</td>\n",
         "      <td>11325.6</td>\n",
-       "      <td>1697</td>\n",
+       "      <td>1207</td>\n",
         "      <td>780.4</td>\n",
         "      <td>780.4</td>\n",
+       "      <td>1207.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-12</td>\n",
         "      <td>11302.0</td>\n",
         "      <td>10703.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-12</td>\n",
         "      <td>11302.0</td>\n",
         "      <td>10703.6</td>\n",
-       "      <td>1388</td>\n",
+       "      <td>937</td>\n",
         "      <td>598.4</td>\n",
         "      <td>598.4</td>\n",
+       "      <td>937.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-19</td>\n",
         "      <td>10694.0</td>\n",
         "      <td>10698.2</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-19</td>\n",
         "      <td>10694.0</td>\n",
         "      <td>10698.2</td>\n",
-       "      <td>1018</td>\n",
+       "      <td>591</td>\n",
         "      <td>-4.2</td>\n",
         "      <td>-4.2</td>\n",
+       "      <td>591.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-26</td>\n",
         "      <td>10282.0</td>\n",
         "      <td>10605.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-26</td>\n",
         "      <td>10282.0</td>\n",
         "      <td>10605.6</td>\n",
-       "      <td>835</td>\n",
+       "      <td>480</td>\n",
         "      <td>-323.6</td>\n",
         "      <td>-323.6</td>\n",
+       "      <td>480.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-03</td>\n",
         "      <td>10412.0</td>\n",
         "      <td>10483.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-03</td>\n",
         "      <td>10412.0</td>\n",
         "      <td>10483.0</td>\n",
-       "      <td>765</td>\n",
+       "      <td>360</td>\n",
         "      <td>-71.0</td>\n",
         "      <td>-71.0</td>\n",
+       "      <td>360.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-10</td>\n",
         "      <td>9941.0</td>\n",
         "      <td>10509.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-10</td>\n",
         "      <td>9941.0</td>\n",
         "      <td>10509.4</td>\n",
-       "      <td>607</td>\n",
+       "      <td>253</td>\n",
         "      <td>-568.4</td>\n",
         "      <td>-568.4</td>\n",
+       "      <td>253.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-17</td>\n",
         "      <td>10096.0</td>\n",
         "      <td>10360.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-17</td>\n",
         "      <td>10096.0</td>\n",
         "      <td>10360.6</td>\n",
-       "      <td>517</td>\n",
+       "      <td>164</td>\n",
         "      <td>-264.6</td>\n",
         "      <td>-264.6</td>\n",
+       "      <td>164.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-24</td>\n",
         "      <td>10159.0</td>\n",
         "      <td>10311.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-24</td>\n",
         "      <td>10159.0</td>\n",
         "      <td>10311.6</td>\n",
-       "      <td>435</td>\n",
+       "      <td>107</td>\n",
         "      <td>-152.6</td>\n",
         "      <td>-152.6</td>\n",
+       "      <td>107.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-31</td>\n",
         "      <td>10262.0</td>\n",
         "      <td>10307.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-31</td>\n",
         "      <td>10262.0</td>\n",
         "      <td>10307.4</td>\n",
-       "      <td>445</td>\n",
+       "      <td>113</td>\n",
         "      <td>-45.4</td>\n",
         "      <td>-45.4</td>\n",
+       "      <td>113.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-08-07</td>\n",
+       "      <td>10236.0</td>\n",
+       "      <td>10363.6</td>\n",
+       "      <td>89</td>\n",
+       "      <td>-127.6</td>\n",
+       "      <td>89.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-08-14</td>\n",
+       "      <td>10592.0</td>\n",
+       "      <td>10345.8</td>\n",
+       "      <td>89</td>\n",
+       "      <td>246.2</td>\n",
+       "      <td>246.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-08-21</td>\n",
+       "      <td>10990.0</td>\n",
+       "      <td>10433.4</td>\n",
+       "      <td>56</td>\n",
+       "      <td>556.6</td>\n",
+       "      <td>556.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-08-28</td>\n",
+       "      <td>9023.0</td>\n",
+       "      <td>9472.2</td>\n",
+       "      <td>74</td>\n",
+       "      <td>-449.2</td>\n",
+       "      <td>74.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-09-04</td>\n",
+       "      <td>10364.0</td>\n",
+       "      <td>10430.4</td>\n",
+       "      <td>50</td>\n",
+       "      <td>-66.4</td>\n",
+       "      <td>50.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-09-11</td>\n",
+       "      <td>11176.0</td>\n",
+       "      <td>10610.8</td>\n",
+       "      <td>81</td>\n",
+       "      <td>565.2</td>\n",
+       "      <td>565.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-09-18</td>\n",
+       "      <td>10797.0</td>\n",
+       "      <td>10545.8</td>\n",
+       "      <td>97</td>\n",
+       "      <td>251.2</td>\n",
+       "      <td>251.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-09-25</td>\n",
+       "      <td>10890.0</td>\n",
+       "      <td>10709.6</td>\n",
+       "      <td>197</td>\n",
+       "      <td>180.4</td>\n",
+       "      <td>197.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-02</td>\n",
+       "      <td>11468.0</td>\n",
+       "      <td>10890.8</td>\n",
+       "      <td>300</td>\n",
+       "      <td>577.2</td>\n",
+       "      <td>577.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-09</td>\n",
+       "      <td>11373.0</td>\n",
+       "      <td>11186.4</td>\n",
+       "      <td>390</td>\n",
+       "      <td>186.6</td>\n",
+       "      <td>390.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-16</td>\n",
+       "      <td>11943.0</td>\n",
+       "      <td>11224.8</td>\n",
+       "      <td>701</td>\n",
+       "      <td>718.2</td>\n",
+       "      <td>718.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-23</td>\n",
+       "      <td>12317.0</td>\n",
+       "      <td>11093.2</td>\n",
+       "      <td>1054</td>\n",
+       "      <td>1223.8</td>\n",
+       "      <td>1223.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-30</td>\n",
+       "      <td>12517.0</td>\n",
+       "      <td>11257.6</td>\n",
+       "      <td>1608</td>\n",
+       "      <td>1259.4</td>\n",
+       "      <td>1608.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-06</td>\n",
+       "      <td>13448.0</td>\n",
+       "      <td>11729.4</td>\n",
+       "      <td>2165</td>\n",
+       "      <td>1718.6</td>\n",
+       "      <td>2165.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-13</td>\n",
+       "      <td>13798.0</td>\n",
+       "      <td>11803.6</td>\n",
+       "      <td>2808</td>\n",
+       "      <td>1994.4</td>\n",
+       "      <td>2808.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-20</td>\n",
+       "      <td>14291.0</td>\n",
+       "      <td>11821.0</td>\n",
+       "      <td>2847</td>\n",
+       "      <td>2470.0</td>\n",
+       "      <td>2847.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-27</td>\n",
+       "      <td>14132.0</td>\n",
+       "      <td>11802.0</td>\n",
+       "      <td>3256</td>\n",
+       "      <td>2330.0</td>\n",
+       "      <td>3256.0</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "</div>"
        ],
        "text/plain": [
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "</div>"
        ],
        "text/plain": [
-       "            total_2020  previous_mean  covid_deaths   excess\n",
-       "2020-03-20     12112.0        12007.4           149    104.6\n",
-       "2020-03-27     12507.0        11549.6           720    957.4\n",
-       "2020-04-03     18565.0        11681.4          2870   6883.6\n",
-       "2020-04-10     20929.0        11919.4          5868   9009.6\n",
-       "2020-04-17     24691.0        11850.6          6340  12840.4\n",
-       "2020-04-24     24303.0        11844.4          5845  12458.6\n",
-       "2020-05-01     20059.0        11318.4          4987   8740.6\n",
-       "2020-05-08     14428.0        10887.2          3850   3540.8\n",
-       "2020-05-15     16390.0        11547.0          3006   4843.0\n",
-       "2020-05-22     13839.0        11281.0          2449   2558.0\n",
-       "2020-05-29     11265.0         9448.0          2199   1817.0\n",
-       "2020-06-05     12106.0        11325.6          1697    780.4\n",
-       "2020-06-12     11302.0        10703.6          1388    598.4\n",
-       "2020-06-19     10694.0        10698.2          1018     -4.2\n",
-       "2020-06-26     10282.0        10605.6           835   -323.6\n",
-       "2020-07-03     10412.0        10483.0           765    -71.0\n",
-       "2020-07-10      9941.0        10509.4           607   -568.4\n",
-       "2020-07-17     10096.0        10360.6           517   -264.6\n",
-       "2020-07-24     10159.0        10311.6           435   -152.6\n",
-       "2020-07-31     10262.0        10307.4           445    -45.4"
+       "            total_2020  previous_mean  covid_deaths   excess  attributable\n",
+       "2020-03-20     12112.0        12007.4           153    104.6         153.0\n",
+       "2020-03-27     12507.0        11549.6           722    957.4         957.4\n",
+       "2020-04-03     18565.0        11681.4          2898   6883.6        6883.6\n",
+       "2020-04-10     20929.0        11919.4          5909   9009.6        9009.6\n",
+       "2020-04-17     24691.0        11850.6          6338  12840.4       12840.4\n",
+       "2020-04-24     24303.0        11844.4          5773  12458.6       12458.6\n",
+       "2020-05-01     20059.0        11318.4          4881   8740.6        8740.6\n",
+       "2020-05-08     14428.0        10887.2          3638   3540.8        3638.0\n",
+       "2020-05-15     16390.0        11547.0          2671   4843.0        4843.0\n",
+       "2020-05-22     13839.0        11281.0          2075   2558.0        2558.0\n",
+       "2020-05-29     11265.0         9448.0          1890   1817.0        1890.0\n",
+       "2020-06-05     12106.0        11325.6          1207    780.4        1207.0\n",
+       "2020-06-12     11302.0        10703.6           937    598.4         937.0\n",
+       "2020-06-19     10694.0        10698.2           591     -4.2         591.0\n",
+       "2020-06-26     10282.0        10605.6           480   -323.6         480.0\n",
+       "2020-07-03     10412.0        10483.0           360    -71.0         360.0\n",
+       "2020-07-10      9941.0        10509.4           253   -568.4         253.0\n",
+       "2020-07-17     10096.0        10360.6           164   -264.6         164.0\n",
+       "2020-07-24     10159.0        10311.6           107   -152.6         107.0\n",
+       "2020-07-31     10262.0        10307.4           113    -45.4         113.0\n",
+       "2020-08-07     10236.0        10363.6            89   -127.6          89.0\n",
+       "2020-08-14     10592.0        10345.8            89    246.2         246.2\n",
+       "2020-08-21     10990.0        10433.4            56    556.6         556.6\n",
+       "2020-08-28      9023.0         9472.2            74   -449.2          74.0\n",
+       "2020-09-04     10364.0        10430.4            50    -66.4          50.0\n",
+       "2020-09-11     11176.0        10610.8            81    565.2         565.2\n",
+       "2020-09-18     10797.0        10545.8            97    251.2         251.2\n",
+       "2020-09-25     10890.0        10709.6           197    180.4         197.0\n",
+       "2020-10-02     11468.0        10890.8           300    577.2         577.2\n",
+       "2020-10-09     11373.0        11186.4           390    186.6         390.0\n",
+       "2020-10-16     11943.0        11224.8           701    718.2         718.2\n",
+       "2020-10-23     12317.0        11093.2          1054   1223.8        1223.8\n",
+       "2020-10-30     12517.0        11257.6          1608   1259.4        1608.0\n",
+       "2020-11-06     13448.0        11729.4          2165   1718.6        2165.0\n",
+       "2020-11-13     13798.0        11803.6          2808   1994.4        2808.0\n",
+       "2020-11-20     14291.0        11821.0          2847   2470.0        2847.0\n",
+       "2020-11-27     14132.0        11802.0          3256   2330.0        3256.0"
        ]
       },
        ]
       },
-     "execution_count": 22,
+     "execution_count": 72,
       "metadata": {},
       "output_type": "execute_result"
      }
     ],
     "source": [
      "excess_deaths['excess'] = excess_deaths.total_2020 - excess_deaths.previous_mean\n",
       "metadata": {},
       "output_type": "execute_result"
      }
     ],
     "source": [
      "excess_deaths['excess'] = excess_deaths.total_2020 - excess_deaths.previous_mean\n",
+    "excess_deaths['attributable'] = excess_deaths[['covid_deaths', 'excess']].max(axis=1)\n",
      "excess_deaths"
     ]
    },
    {
     "cell_type": "code",
      "excess_deaths"
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {},
+   "execution_count": 73,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
        "text/plain": [
     "outputs": [
      {
       "data": {
        "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f249a3ad790>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f41c44a9610>"
        ]
       },
        ]
       },
-     "execution_count": 23,
+     "execution_count": 73,
       "metadata": {},
       "output_type": "execute_result"
      },
      {
       "data": {
       "metadata": {},
       "output_type": "execute_result"
      },
      {
       "data": {
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\n",
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\n",
        "text/plain": [
         "<Figure size 432x288 with 1 Axes>"
        ]
        "text/plain": [
         "<Figure size 432x288 with 1 Axes>"
        ]
@@ -1718,16 +2918,18 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {},
+   "execution_count": 74,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
        "text/plain": [
     "outputs": [
      {
       "data": {
        "text/plain": [
-       "1.385140247879974"
+       "1.3562695100136786"
        ]
       },
        ]
       },
-     "execution_count": 24,
+     "execution_count": 74,
       "metadata": {},
       "output_type": "execute_result"
      }
       "metadata": {},
       "output_type": "execute_result"
      }
@@ -1738,8 +2940,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {},
+   "execution_count": 75,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
@@ -1766,6 +2970,7 @@
         "      <th>previous_mean</th>\n",
         "      <th>covid_deaths</th>\n",
         "      <th>excess</th>\n",
         "      <th>previous_mean</th>\n",
         "      <th>covid_deaths</th>\n",
         "      <th>excess</th>\n",
+       "      <th>attributable</th>\n",
         "      <th>accounted_fraction</th>\n",
         "    </tr>\n",
         "  </thead>\n",
         "      <th>accounted_fraction</th>\n",
         "    </tr>\n",
         "  </thead>\n",
@@ -1774,213 +2979,420 @@
         "      <td>2020-03-20</td>\n",
         "      <td>12112.0</td>\n",
         "      <td>12007.4</td>\n",
         "      <td>2020-03-20</td>\n",
         "      <td>12112.0</td>\n",
         "      <td>12007.4</td>\n",
-       "      <td>149</td>\n",
+       "      <td>153</td>\n",
         "      <td>104.6</td>\n",
         "      <td>104.6</td>\n",
-       "      <td>1.424474</td>\n",
+       "      <td>153.0</td>\n",
+       "      <td>1.462715</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-03-27</td>\n",
         "      <td>12507.0</td>\n",
         "      <td>11549.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-03-27</td>\n",
         "      <td>12507.0</td>\n",
         "      <td>11549.6</td>\n",
-       "      <td>720</td>\n",
+       "      <td>722</td>\n",
         "      <td>957.4</td>\n",
         "      <td>957.4</td>\n",
-       "      <td>0.752037</td>\n",
+       "      <td>957.4</td>\n",
+       "      <td>0.754126</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-03</td>\n",
         "      <td>18565.0</td>\n",
         "      <td>11681.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-03</td>\n",
         "      <td>18565.0</td>\n",
         "      <td>11681.4</td>\n",
-       "      <td>2870</td>\n",
+       "      <td>2898</td>\n",
+       "      <td>6883.6</td>\n",
         "      <td>6883.6</td>\n",
         "      <td>6883.6</td>\n",
-       "      <td>0.416933</td>\n",
+       "      <td>0.421001</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-10</td>\n",
         "      <td>20929.0</td>\n",
         "      <td>11919.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-10</td>\n",
         "      <td>20929.0</td>\n",
         "      <td>11919.4</td>\n",
-       "      <td>5868</td>\n",
+       "      <td>5909</td>\n",
+       "      <td>9009.6</td>\n",
         "      <td>9009.6</td>\n",
         "      <td>9009.6</td>\n",
-       "      <td>0.651305</td>\n",
+       "      <td>0.655856</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-17</td>\n",
         "      <td>24691.0</td>\n",
         "      <td>11850.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-17</td>\n",
         "      <td>24691.0</td>\n",
         "      <td>11850.6</td>\n",
-       "      <td>6340</td>\n",
+       "      <td>6338</td>\n",
         "      <td>12840.4</td>\n",
         "      <td>12840.4</td>\n",
-       "      <td>0.493754</td>\n",
+       "      <td>12840.4</td>\n",
+       "      <td>0.493598</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-24</td>\n",
         "      <td>24303.0</td>\n",
         "      <td>11844.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-24</td>\n",
         "      <td>24303.0</td>\n",
         "      <td>11844.4</td>\n",
-       "      <td>5845</td>\n",
+       "      <td>5773</td>\n",
+       "      <td>12458.6</td>\n",
         "      <td>12458.6</td>\n",
         "      <td>12458.6</td>\n",
-       "      <td>0.469154</td>\n",
+       "      <td>0.463375</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-01</td>\n",
         "      <td>20059.0</td>\n",
         "      <td>11318.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-01</td>\n",
         "      <td>20059.0</td>\n",
         "      <td>11318.4</td>\n",
-       "      <td>4987</td>\n",
+       "      <td>4881</td>\n",
         "      <td>8740.6</td>\n",
         "      <td>8740.6</td>\n",
-       "      <td>0.570556</td>\n",
+       "      <td>8740.6</td>\n",
+       "      <td>0.558428</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-08</td>\n",
         "      <td>14428.0</td>\n",
         "      <td>10887.2</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-08</td>\n",
         "      <td>14428.0</td>\n",
         "      <td>10887.2</td>\n",
-       "      <td>3850</td>\n",
+       "      <td>3638</td>\n",
         "      <td>3540.8</td>\n",
         "      <td>3540.8</td>\n",
-       "      <td>1.087325</td>\n",
+       "      <td>3638.0</td>\n",
+       "      <td>1.027451</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-15</td>\n",
         "      <td>16390.0</td>\n",
         "      <td>11547.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-15</td>\n",
         "      <td>16390.0</td>\n",
         "      <td>11547.0</td>\n",
-       "      <td>3006</td>\n",
+       "      <td>2671</td>\n",
+       "      <td>4843.0</td>\n",
         "      <td>4843.0</td>\n",
         "      <td>4843.0</td>\n",
-       "      <td>0.620690</td>\n",
+       "      <td>0.551518</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-22</td>\n",
         "      <td>13839.0</td>\n",
         "      <td>11281.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-22</td>\n",
         "      <td>13839.0</td>\n",
         "      <td>11281.0</td>\n",
-       "      <td>2449</td>\n",
+       "      <td>2075</td>\n",
         "      <td>2558.0</td>\n",
         "      <td>2558.0</td>\n",
-       "      <td>0.957389</td>\n",
+       "      <td>2558.0</td>\n",
+       "      <td>0.811181</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-29</td>\n",
         "      <td>11265.0</td>\n",
         "      <td>9448.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-29</td>\n",
         "      <td>11265.0</td>\n",
         "      <td>9448.0</td>\n",
-       "      <td>2199</td>\n",
+       "      <td>1890</td>\n",
         "      <td>1817.0</td>\n",
         "      <td>1817.0</td>\n",
-       "      <td>1.210237</td>\n",
+       "      <td>1890.0</td>\n",
+       "      <td>1.040176</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-05</td>\n",
         "      <td>12106.0</td>\n",
         "      <td>11325.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-05</td>\n",
         "      <td>12106.0</td>\n",
         "      <td>11325.6</td>\n",
-       "      <td>1697</td>\n",
+       "      <td>1207</td>\n",
         "      <td>780.4</td>\n",
         "      <td>780.4</td>\n",
-       "      <td>2.174526</td>\n",
+       "      <td>1207.0</td>\n",
+       "      <td>1.546643</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-12</td>\n",
         "      <td>11302.0</td>\n",
         "      <td>10703.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-12</td>\n",
         "      <td>11302.0</td>\n",
         "      <td>10703.6</td>\n",
-       "      <td>1388</td>\n",
+       "      <td>937</td>\n",
         "      <td>598.4</td>\n",
         "      <td>598.4</td>\n",
-       "      <td>2.319519</td>\n",
+       "      <td>937.0</td>\n",
+       "      <td>1.565842</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-19</td>\n",
         "      <td>10694.0</td>\n",
         "      <td>10698.2</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-19</td>\n",
         "      <td>10694.0</td>\n",
         "      <td>10698.2</td>\n",
-       "      <td>1018</td>\n",
+       "      <td>591</td>\n",
         "      <td>-4.2</td>\n",
         "      <td>-4.2</td>\n",
-       "      <td>-242.380952</td>\n",
+       "      <td>591.0</td>\n",
+       "      <td>-140.714286</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-26</td>\n",
         "      <td>10282.0</td>\n",
         "      <td>10605.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-26</td>\n",
         "      <td>10282.0</td>\n",
         "      <td>10605.6</td>\n",
-       "      <td>835</td>\n",
+       "      <td>480</td>\n",
         "      <td>-323.6</td>\n",
         "      <td>-323.6</td>\n",
-       "      <td>-2.580346</td>\n",
+       "      <td>480.0</td>\n",
+       "      <td>-1.483313</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-03</td>\n",
         "      <td>10412.0</td>\n",
         "      <td>10483.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-03</td>\n",
         "      <td>10412.0</td>\n",
         "      <td>10483.0</td>\n",
-       "      <td>765</td>\n",
+       "      <td>360</td>\n",
         "      <td>-71.0</td>\n",
         "      <td>-71.0</td>\n",
-       "      <td>-10.774648</td>\n",
+       "      <td>360.0</td>\n",
+       "      <td>-5.070423</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-10</td>\n",
         "      <td>9941.0</td>\n",
         "      <td>10509.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-10</td>\n",
         "      <td>9941.0</td>\n",
         "      <td>10509.4</td>\n",
-       "      <td>607</td>\n",
+       "      <td>253</td>\n",
         "      <td>-568.4</td>\n",
         "      <td>-568.4</td>\n",
-       "      <td>-1.067910</td>\n",
+       "      <td>253.0</td>\n",
+       "      <td>-0.445109</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-17</td>\n",
         "      <td>10096.0</td>\n",
         "      <td>10360.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-17</td>\n",
         "      <td>10096.0</td>\n",
         "      <td>10360.6</td>\n",
-       "      <td>517</td>\n",
+       "      <td>164</td>\n",
         "      <td>-264.6</td>\n",
         "      <td>-264.6</td>\n",
-       "      <td>-1.953893</td>\n",
+       "      <td>164.0</td>\n",
+       "      <td>-0.619803</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-24</td>\n",
         "      <td>10159.0</td>\n",
         "      <td>10311.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-24</td>\n",
         "      <td>10159.0</td>\n",
         "      <td>10311.6</td>\n",
-       "      <td>435</td>\n",
+       "      <td>107</td>\n",
         "      <td>-152.6</td>\n",
         "      <td>-152.6</td>\n",
-       "      <td>-2.850590</td>\n",
+       "      <td>107.0</td>\n",
+       "      <td>-0.701180</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-31</td>\n",
         "      <td>10262.0</td>\n",
         "      <td>10307.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-31</td>\n",
         "      <td>10262.0</td>\n",
         "      <td>10307.4</td>\n",
-       "      <td>445</td>\n",
+       "      <td>113</td>\n",
         "      <td>-45.4</td>\n",
         "      <td>-45.4</td>\n",
-       "      <td>-9.801762</td>\n",
+       "      <td>113.0</td>\n",
+       "      <td>-2.488987</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-08-07</td>\n",
+       "      <td>10236.0</td>\n",
+       "      <td>10363.6</td>\n",
+       "      <td>89</td>\n",
+       "      <td>-127.6</td>\n",
+       "      <td>89.0</td>\n",
+       "      <td>-0.697492</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-08-14</td>\n",
+       "      <td>10592.0</td>\n",
+       "      <td>10345.8</td>\n",
+       "      <td>89</td>\n",
+       "      <td>246.2</td>\n",
+       "      <td>246.2</td>\n",
+       "      <td>0.361495</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-08-21</td>\n",
+       "      <td>10990.0</td>\n",
+       "      <td>10433.4</td>\n",
+       "      <td>56</td>\n",
+       "      <td>556.6</td>\n",
+       "      <td>556.6</td>\n",
+       "      <td>0.100611</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-08-28</td>\n",
+       "      <td>9023.0</td>\n",
+       "      <td>9472.2</td>\n",
+       "      <td>74</td>\n",
+       "      <td>-449.2</td>\n",
+       "      <td>74.0</td>\n",
+       "      <td>-0.164737</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-09-04</td>\n",
+       "      <td>10364.0</td>\n",
+       "      <td>10430.4</td>\n",
+       "      <td>50</td>\n",
+       "      <td>-66.4</td>\n",
+       "      <td>50.0</td>\n",
+       "      <td>-0.753012</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-09-11</td>\n",
+       "      <td>11176.0</td>\n",
+       "      <td>10610.8</td>\n",
+       "      <td>81</td>\n",
+       "      <td>565.2</td>\n",
+       "      <td>565.2</td>\n",
+       "      <td>0.143312</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-09-18</td>\n",
+       "      <td>10797.0</td>\n",
+       "      <td>10545.8</td>\n",
+       "      <td>97</td>\n",
+       "      <td>251.2</td>\n",
+       "      <td>251.2</td>\n",
+       "      <td>0.386146</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-09-25</td>\n",
+       "      <td>10890.0</td>\n",
+       "      <td>10709.6</td>\n",
+       "      <td>197</td>\n",
+       "      <td>180.4</td>\n",
+       "      <td>197.0</td>\n",
+       "      <td>1.092018</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-02</td>\n",
+       "      <td>11468.0</td>\n",
+       "      <td>10890.8</td>\n",
+       "      <td>300</td>\n",
+       "      <td>577.2</td>\n",
+       "      <td>577.2</td>\n",
+       "      <td>0.519751</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-09</td>\n",
+       "      <td>11373.0</td>\n",
+       "      <td>11186.4</td>\n",
+       "      <td>390</td>\n",
+       "      <td>186.6</td>\n",
+       "      <td>390.0</td>\n",
+       "      <td>2.090032</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-16</td>\n",
+       "      <td>11943.0</td>\n",
+       "      <td>11224.8</td>\n",
+       "      <td>701</td>\n",
+       "      <td>718.2</td>\n",
+       "      <td>718.2</td>\n",
+       "      <td>0.976051</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-23</td>\n",
+       "      <td>12317.0</td>\n",
+       "      <td>11093.2</td>\n",
+       "      <td>1054</td>\n",
+       "      <td>1223.8</td>\n",
+       "      <td>1223.8</td>\n",
+       "      <td>0.861252</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-30</td>\n",
+       "      <td>12517.0</td>\n",
+       "      <td>11257.6</td>\n",
+       "      <td>1608</td>\n",
+       "      <td>1259.4</td>\n",
+       "      <td>1608.0</td>\n",
+       "      <td>1.276798</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-06</td>\n",
+       "      <td>13448.0</td>\n",
+       "      <td>11729.4</td>\n",
+       "      <td>2165</td>\n",
+       "      <td>1718.6</td>\n",
+       "      <td>2165.0</td>\n",
+       "      <td>1.259746</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-13</td>\n",
+       "      <td>13798.0</td>\n",
+       "      <td>11803.6</td>\n",
+       "      <td>2808</td>\n",
+       "      <td>1994.4</td>\n",
+       "      <td>2808.0</td>\n",
+       "      <td>1.407942</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-20</td>\n",
+       "      <td>14291.0</td>\n",
+       "      <td>11821.0</td>\n",
+       "      <td>2847</td>\n",
+       "      <td>2470.0</td>\n",
+       "      <td>2847.0</td>\n",
+       "      <td>1.152632</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-27</td>\n",
+       "      <td>14132.0</td>\n",
+       "      <td>11802.0</td>\n",
+       "      <td>3256</td>\n",
+       "      <td>2330.0</td>\n",
+       "      <td>3256.0</td>\n",
+       "      <td>1.397425</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "</div>"
        ],
        "text/plain": [
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "</div>"
        ],
        "text/plain": [
-       "            total_2020  previous_mean  covid_deaths   excess  \\\n",
-       "2020-03-20     12112.0        12007.4           149    104.6   \n",
-       "2020-03-27     12507.0        11549.6           720    957.4   \n",
-       "2020-04-03     18565.0        11681.4          2870   6883.6   \n",
-       "2020-04-10     20929.0        11919.4          5868   9009.6   \n",
-       "2020-04-17     24691.0        11850.6          6340  12840.4   \n",
-       "2020-04-24     24303.0        11844.4          5845  12458.6   \n",
-       "2020-05-01     20059.0        11318.4          4987   8740.6   \n",
-       "2020-05-08     14428.0        10887.2          3850   3540.8   \n",
-       "2020-05-15     16390.0        11547.0          3006   4843.0   \n",
-       "2020-05-22     13839.0        11281.0          2449   2558.0   \n",
-       "2020-05-29     11265.0         9448.0          2199   1817.0   \n",
-       "2020-06-05     12106.0        11325.6          1697    780.4   \n",
-       "2020-06-12     11302.0        10703.6          1388    598.4   \n",
-       "2020-06-19     10694.0        10698.2          1018     -4.2   \n",
-       "2020-06-26     10282.0        10605.6           835   -323.6   \n",
-       "2020-07-03     10412.0        10483.0           765    -71.0   \n",
-       "2020-07-10      9941.0        10509.4           607   -568.4   \n",
-       "2020-07-17     10096.0        10360.6           517   -264.6   \n",
-       "2020-07-24     10159.0        10311.6           435   -152.6   \n",
-       "2020-07-31     10262.0        10307.4           445    -45.4   \n",
+       "            total_2020  previous_mean  covid_deaths   excess  attributable  \\\n",
+       "2020-03-20     12112.0        12007.4           153    104.6         153.0   \n",
+       "2020-03-27     12507.0        11549.6           722    957.4         957.4   \n",
+       "2020-04-03     18565.0        11681.4          2898   6883.6        6883.6   \n",
+       "2020-04-10     20929.0        11919.4          5909   9009.6        9009.6   \n",
+       "2020-04-17     24691.0        11850.6          6338  12840.4       12840.4   \n",
+       "2020-04-24     24303.0        11844.4          5773  12458.6       12458.6   \n",
+       "2020-05-01     20059.0        11318.4          4881   8740.6        8740.6   \n",
+       "2020-05-08     14428.0        10887.2          3638   3540.8        3638.0   \n",
+       "2020-05-15     16390.0        11547.0          2671   4843.0        4843.0   \n",
+       "2020-05-22     13839.0        11281.0          2075   2558.0        2558.0   \n",
+       "2020-05-29     11265.0         9448.0          1890   1817.0        1890.0   \n",
+       "2020-06-05     12106.0        11325.6          1207    780.4        1207.0   \n",
+       "2020-06-12     11302.0        10703.6           937    598.4         937.0   \n",
+       "2020-06-19     10694.0        10698.2           591     -4.2         591.0   \n",
+       "2020-06-26     10282.0        10605.6           480   -323.6         480.0   \n",
+       "2020-07-03     10412.0        10483.0           360    -71.0         360.0   \n",
+       "2020-07-10      9941.0        10509.4           253   -568.4         253.0   \n",
+       "2020-07-17     10096.0        10360.6           164   -264.6         164.0   \n",
+       "2020-07-24     10159.0        10311.6           107   -152.6         107.0   \n",
+       "2020-07-31     10262.0        10307.4           113    -45.4         113.0   \n",
+       "2020-08-07     10236.0        10363.6            89   -127.6          89.0   \n",
+       "2020-08-14     10592.0        10345.8            89    246.2         246.2   \n",
+       "2020-08-21     10990.0        10433.4            56    556.6         556.6   \n",
+       "2020-08-28      9023.0         9472.2            74   -449.2          74.0   \n",
+       "2020-09-04     10364.0        10430.4            50    -66.4          50.0   \n",
+       "2020-09-11     11176.0        10610.8            81    565.2         565.2   \n",
+       "2020-09-18     10797.0        10545.8            97    251.2         251.2   \n",
+       "2020-09-25     10890.0        10709.6           197    180.4         197.0   \n",
+       "2020-10-02     11468.0        10890.8           300    577.2         577.2   \n",
+       "2020-10-09     11373.0        11186.4           390    186.6         390.0   \n",
+       "2020-10-16     11943.0        11224.8           701    718.2         718.2   \n",
+       "2020-10-23     12317.0        11093.2          1054   1223.8        1223.8   \n",
+       "2020-10-30     12517.0        11257.6          1608   1259.4        1608.0   \n",
+       "2020-11-06     13448.0        11729.4          2165   1718.6        2165.0   \n",
+       "2020-11-13     13798.0        11803.6          2808   1994.4        2808.0   \n",
+       "2020-11-20     14291.0        11821.0          2847   2470.0        2847.0   \n",
+       "2020-11-27     14132.0        11802.0          3256   2330.0        3256.0   \n",
         "\n",
         "            accounted_fraction  \n",
         "\n",
         "            accounted_fraction  \n",
-       "2020-03-20            1.424474  \n",
-       "2020-03-27            0.752037  \n",
-       "2020-04-03            0.416933  \n",
-       "2020-04-10            0.651305  \n",
-       "2020-04-17            0.493754  \n",
-       "2020-04-24            0.469154  \n",
-       "2020-05-01            0.570556  \n",
-       "2020-05-08            1.087325  \n",
-       "2020-05-15            0.620690  \n",
-       "2020-05-22            0.957389  \n",
-       "2020-05-29            1.210237  \n",
-       "2020-06-05            2.174526  \n",
-       "2020-06-12            2.319519  \n",
-       "2020-06-19         -242.380952  \n",
-       "2020-06-26           -2.580346  \n",
-       "2020-07-03          -10.774648  \n",
-       "2020-07-10           -1.067910  \n",
-       "2020-07-17           -1.953893  \n",
-       "2020-07-24           -2.850590  \n",
-       "2020-07-31           -9.801762  "
+       "2020-03-20            1.462715  \n",
+       "2020-03-27            0.754126  \n",
+       "2020-04-03            0.421001  \n",
+       "2020-04-10            0.655856  \n",
+       "2020-04-17            0.493598  \n",
+       "2020-04-24            0.463375  \n",
+       "2020-05-01            0.558428  \n",
+       "2020-05-08            1.027451  \n",
+       "2020-05-15            0.551518  \n",
+       "2020-05-22            0.811181  \n",
+       "2020-05-29            1.040176  \n",
+       "2020-06-05            1.546643  \n",
+       "2020-06-12            1.565842  \n",
+       "2020-06-19         -140.714286  \n",
+       "2020-06-26           -1.483313  \n",
+       "2020-07-03           -5.070423  \n",
+       "2020-07-10           -0.445109  \n",
+       "2020-07-17           -0.619803  \n",
+       "2020-07-24           -0.701180  \n",
+       "2020-07-31           -2.488987  \n",
+       "2020-08-07           -0.697492  \n",
+       "2020-08-14            0.361495  \n",
+       "2020-08-21            0.100611  \n",
+       "2020-08-28           -0.164737  \n",
+       "2020-09-04           -0.753012  \n",
+       "2020-09-11            0.143312  \n",
+       "2020-09-18            0.386146  \n",
+       "2020-09-25            1.092018  \n",
+       "2020-10-02            0.519751  \n",
+       "2020-10-09            2.090032  \n",
+       "2020-10-16            0.976051  \n",
+       "2020-10-23            0.861252  \n",
+       "2020-10-30            1.276798  \n",
+       "2020-11-06            1.259746  \n",
+       "2020-11-13            1.407942  \n",
+       "2020-11-20            1.152632  \n",
+       "2020-11-27            1.397425  "
        ]
       },
        ]
       },
-     "execution_count": 25,
+     "execution_count": 75,
       "metadata": {},
       "output_type": "execute_result"
      }
       "metadata": {},
       "output_type": "execute_result"
      }
@@ -1992,8 +3404,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {},
+   "execution_count": 76,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
@@ -2020,6 +3434,7 @@
         "      <th>previous_mean</th>\n",
         "      <th>covid_deaths</th>\n",
         "      <th>excess</th>\n",
         "      <th>previous_mean</th>\n",
         "      <th>covid_deaths</th>\n",
         "      <th>excess</th>\n",
+       "      <th>attributable</th>\n",
         "      <th>accounted_fraction</th>\n",
         "      <th>covid_deaths_m2</th>\n",
         "      <th>excess_m2</th>\n",
         "      <th>accounted_fraction</th>\n",
         "      <th>covid_deaths_m2</th>\n",
         "      <th>excess_m2</th>\n",
@@ -2031,295 +3446,570 @@
         "      <td>2020-03-20</td>\n",
         "      <td>12112.0</td>\n",
         "      <td>12007.4</td>\n",
         "      <td>2020-03-20</td>\n",
         "      <td>12112.0</td>\n",
         "      <td>12007.4</td>\n",
-       "      <td>149</td>\n",
+       "      <td>153</td>\n",
         "      <td>104.6</td>\n",
         "      <td>104.6</td>\n",
-       "      <td>1.424474</td>\n",
-       "      <td>149.0</td>\n",
+       "      <td>153.0</td>\n",
+       "      <td>1.462715</td>\n",
+       "      <td>153.0</td>\n",
         "      <td>104.6</td>\n",
         "      <td>104.6</td>\n",
-       "      <td>1.424474</td>\n",
+       "      <td>1.462715</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-03-27</td>\n",
         "      <td>12507.0</td>\n",
         "      <td>11549.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-03-27</td>\n",
         "      <td>12507.0</td>\n",
         "      <td>11549.6</td>\n",
-       "      <td>720</td>\n",
+       "      <td>722</td>\n",
+       "      <td>957.4</td>\n",
         "      <td>957.4</td>\n",
         "      <td>957.4</td>\n",
-       "      <td>0.752037</td>\n",
-       "      <td>434.5</td>\n",
+       "      <td>0.754126</td>\n",
+       "      <td>437.5</td>\n",
         "      <td>531.0</td>\n",
         "      <td>531.0</td>\n",
-       "      <td>0.818267</td>\n",
+       "      <td>0.823917</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-03</td>\n",
         "      <td>18565.0</td>\n",
         "      <td>11681.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-03</td>\n",
         "      <td>18565.0</td>\n",
         "      <td>11681.4</td>\n",
-       "      <td>2870</td>\n",
+       "      <td>2898</td>\n",
+       "      <td>6883.6</td>\n",
         "      <td>6883.6</td>\n",
         "      <td>6883.6</td>\n",
-       "      <td>0.416933</td>\n",
-       "      <td>1795.0</td>\n",
+       "      <td>0.421001</td>\n",
+       "      <td>1810.0</td>\n",
         "      <td>3920.5</td>\n",
         "      <td>3920.5</td>\n",
-       "      <td>0.457850</td>\n",
+       "      <td>0.461676</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-10</td>\n",
         "      <td>20929.0</td>\n",
         "      <td>11919.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-10</td>\n",
         "      <td>20929.0</td>\n",
         "      <td>11919.4</td>\n",
-       "      <td>5868</td>\n",
+       "      <td>5909</td>\n",
         "      <td>9009.6</td>\n",
         "      <td>9009.6</td>\n",
-       "      <td>0.651305</td>\n",
-       "      <td>4369.0</td>\n",
+       "      <td>9009.6</td>\n",
+       "      <td>0.655856</td>\n",
+       "      <td>4403.5</td>\n",
         "      <td>7946.6</td>\n",
         "      <td>7946.6</td>\n",
-       "      <td>0.549795</td>\n",
+       "      <td>0.554136</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-17</td>\n",
         "      <td>24691.0</td>\n",
         "      <td>11850.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-17</td>\n",
         "      <td>24691.0</td>\n",
         "      <td>11850.6</td>\n",
-       "      <td>6340</td>\n",
+       "      <td>6338</td>\n",
+       "      <td>12840.4</td>\n",
         "      <td>12840.4</td>\n",
         "      <td>12840.4</td>\n",
-       "      <td>0.493754</td>\n",
-       "      <td>6104.0</td>\n",
+       "      <td>0.493598</td>\n",
+       "      <td>6123.5</td>\n",
         "      <td>10925.0</td>\n",
         "      <td>10925.0</td>\n",
-       "      <td>0.558719</td>\n",
+       "      <td>0.560503</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-24</td>\n",
         "      <td>24303.0</td>\n",
         "      <td>11844.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-04-24</td>\n",
         "      <td>24303.0</td>\n",
         "      <td>11844.4</td>\n",
-       "      <td>5845</td>\n",
+       "      <td>5773</td>\n",
         "      <td>12458.6</td>\n",
         "      <td>12458.6</td>\n",
-       "      <td>0.469154</td>\n",
-       "      <td>6092.5</td>\n",
+       "      <td>12458.6</td>\n",
+       "      <td>0.463375</td>\n",
+       "      <td>6055.5</td>\n",
         "      <td>12649.5</td>\n",
         "      <td>12649.5</td>\n",
-       "      <td>0.481640</td>\n",
+       "      <td>0.478715</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-01</td>\n",
         "      <td>20059.0</td>\n",
         "      <td>11318.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-01</td>\n",
         "      <td>20059.0</td>\n",
         "      <td>11318.4</td>\n",
-       "      <td>4987</td>\n",
+       "      <td>4881</td>\n",
+       "      <td>8740.6</td>\n",
         "      <td>8740.6</td>\n",
         "      <td>8740.6</td>\n",
-       "      <td>0.570556</td>\n",
-       "      <td>5416.0</td>\n",
+       "      <td>0.558428</td>\n",
+       "      <td>5327.0</td>\n",
         "      <td>10599.6</td>\n",
         "      <td>10599.6</td>\n",
-       "      <td>0.510963</td>\n",
+       "      <td>0.502566</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-08</td>\n",
         "      <td>14428.0</td>\n",
         "      <td>10887.2</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-08</td>\n",
         "      <td>14428.0</td>\n",
         "      <td>10887.2</td>\n",
-       "      <td>3850</td>\n",
+       "      <td>3638</td>\n",
         "      <td>3540.8</td>\n",
         "      <td>3540.8</td>\n",
-       "      <td>1.087325</td>\n",
-       "      <td>4418.5</td>\n",
+       "      <td>3638.0</td>\n",
+       "      <td>1.027451</td>\n",
+       "      <td>4259.5</td>\n",
         "      <td>6140.7</td>\n",
         "      <td>6140.7</td>\n",
-       "      <td>0.719543</td>\n",
+       "      <td>0.693651</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-15</td>\n",
         "      <td>16390.0</td>\n",
         "      <td>11547.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-15</td>\n",
         "      <td>16390.0</td>\n",
         "      <td>11547.0</td>\n",
-       "      <td>3006</td>\n",
+       "      <td>2671</td>\n",
         "      <td>4843.0</td>\n",
         "      <td>4843.0</td>\n",
-       "      <td>0.620690</td>\n",
-       "      <td>3428.0</td>\n",
+       "      <td>4843.0</td>\n",
+       "      <td>0.551518</td>\n",
+       "      <td>3154.5</td>\n",
         "      <td>4191.9</td>\n",
         "      <td>4191.9</td>\n",
-       "      <td>0.817768</td>\n",
+       "      <td>0.752523</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-22</td>\n",
         "      <td>13839.0</td>\n",
         "      <td>11281.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-22</td>\n",
         "      <td>13839.0</td>\n",
         "      <td>11281.0</td>\n",
-       "      <td>2449</td>\n",
+       "      <td>2075</td>\n",
+       "      <td>2558.0</td>\n",
         "      <td>2558.0</td>\n",
         "      <td>2558.0</td>\n",
-       "      <td>0.957389</td>\n",
-       "      <td>2727.5</td>\n",
+       "      <td>0.811181</td>\n",
+       "      <td>2373.0</td>\n",
         "      <td>3700.5</td>\n",
         "      <td>3700.5</td>\n",
-       "      <td>0.737063</td>\n",
+       "      <td>0.641265</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-29</td>\n",
         "      <td>11265.0</td>\n",
         "      <td>9448.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-05-29</td>\n",
         "      <td>11265.0</td>\n",
         "      <td>9448.0</td>\n",
-       "      <td>2199</td>\n",
+       "      <td>1890</td>\n",
         "      <td>1817.0</td>\n",
         "      <td>1817.0</td>\n",
-       "      <td>1.210237</td>\n",
-       "      <td>2324.0</td>\n",
+       "      <td>1890.0</td>\n",
+       "      <td>1.040176</td>\n",
+       "      <td>1982.5</td>\n",
         "      <td>2187.5</td>\n",
         "      <td>2187.5</td>\n",
-       "      <td>1.062400</td>\n",
+       "      <td>0.906286</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-05</td>\n",
         "      <td>12106.0</td>\n",
         "      <td>11325.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-05</td>\n",
         "      <td>12106.0</td>\n",
         "      <td>11325.6</td>\n",
-       "      <td>1697</td>\n",
+       "      <td>1207</td>\n",
         "      <td>780.4</td>\n",
         "      <td>780.4</td>\n",
-       "      <td>2.174526</td>\n",
-       "      <td>1948.0</td>\n",
+       "      <td>1207.0</td>\n",
+       "      <td>1.546643</td>\n",
+       "      <td>1548.5</td>\n",
         "      <td>1298.7</td>\n",
         "      <td>1298.7</td>\n",
-       "      <td>1.499961</td>\n",
+       "      <td>1.192346</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-12</td>\n",
         "      <td>11302.0</td>\n",
         "      <td>10703.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-12</td>\n",
         "      <td>11302.0</td>\n",
         "      <td>10703.6</td>\n",
-       "      <td>1388</td>\n",
+       "      <td>937</td>\n",
         "      <td>598.4</td>\n",
         "      <td>598.4</td>\n",
-       "      <td>2.319519</td>\n",
-       "      <td>1542.5</td>\n",
+       "      <td>937.0</td>\n",
+       "      <td>1.565842</td>\n",
+       "      <td>1072.0</td>\n",
         "      <td>689.4</td>\n",
         "      <td>689.4</td>\n",
-       "      <td>2.237453</td>\n",
+       "      <td>1.554975</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-19</td>\n",
         "      <td>10694.0</td>\n",
         "      <td>10698.2</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-19</td>\n",
         "      <td>10694.0</td>\n",
         "      <td>10698.2</td>\n",
-       "      <td>1018</td>\n",
+       "      <td>591</td>\n",
         "      <td>-4.2</td>\n",
         "      <td>-4.2</td>\n",
-       "      <td>-242.380952</td>\n",
-       "      <td>1203.0</td>\n",
+       "      <td>591.0</td>\n",
+       "      <td>-140.714286</td>\n",
+       "      <td>764.0</td>\n",
         "      <td>297.1</td>\n",
         "      <td>297.1</td>\n",
-       "      <td>4.049142</td>\n",
+       "      <td>2.571525</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-26</td>\n",
         "      <td>10282.0</td>\n",
         "      <td>10605.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-06-26</td>\n",
         "      <td>10282.0</td>\n",
         "      <td>10605.6</td>\n",
-       "      <td>835</td>\n",
+       "      <td>480</td>\n",
         "      <td>-323.6</td>\n",
         "      <td>-323.6</td>\n",
-       "      <td>-2.580346</td>\n",
-       "      <td>926.5</td>\n",
+       "      <td>480.0</td>\n",
+       "      <td>-1.483313</td>\n",
+       "      <td>535.5</td>\n",
         "      <td>-163.9</td>\n",
         "      <td>-163.9</td>\n",
-       "      <td>-5.652837</td>\n",
+       "      <td>-3.267236</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-03</td>\n",
         "      <td>10412.0</td>\n",
         "      <td>10483.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-03</td>\n",
         "      <td>10412.0</td>\n",
         "      <td>10483.0</td>\n",
-       "      <td>765</td>\n",
+       "      <td>360</td>\n",
         "      <td>-71.0</td>\n",
         "      <td>-71.0</td>\n",
-       "      <td>-10.774648</td>\n",
-       "      <td>800.0</td>\n",
+       "      <td>360.0</td>\n",
+       "      <td>-5.070423</td>\n",
+       "      <td>420.0</td>\n",
         "      <td>-197.3</td>\n",
         "      <td>-197.3</td>\n",
-       "      <td>-4.054739</td>\n",
+       "      <td>-2.128738</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-10</td>\n",
         "      <td>9941.0</td>\n",
         "      <td>10509.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-10</td>\n",
         "      <td>9941.0</td>\n",
         "      <td>10509.4</td>\n",
-       "      <td>607</td>\n",
+       "      <td>253</td>\n",
         "      <td>-568.4</td>\n",
         "      <td>-568.4</td>\n",
-       "      <td>-1.067910</td>\n",
-       "      <td>686.0</td>\n",
+       "      <td>253.0</td>\n",
+       "      <td>-0.445109</td>\n",
+       "      <td>306.5</td>\n",
         "      <td>-319.7</td>\n",
         "      <td>-319.7</td>\n",
-       "      <td>-2.145762</td>\n",
+       "      <td>-0.958711</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-17</td>\n",
         "      <td>10096.0</td>\n",
         "      <td>10360.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-17</td>\n",
         "      <td>10096.0</td>\n",
         "      <td>10360.6</td>\n",
-       "      <td>517</td>\n",
+       "      <td>164</td>\n",
         "      <td>-264.6</td>\n",
         "      <td>-264.6</td>\n",
-       "      <td>-1.953893</td>\n",
-       "      <td>562.0</td>\n",
+       "      <td>164.0</td>\n",
+       "      <td>-0.619803</td>\n",
+       "      <td>208.5</td>\n",
         "      <td>-416.5</td>\n",
         "      <td>-416.5</td>\n",
-       "      <td>-1.349340</td>\n",
+       "      <td>-0.500600</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-24</td>\n",
         "      <td>10159.0</td>\n",
         "      <td>10311.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-24</td>\n",
         "      <td>10159.0</td>\n",
         "      <td>10311.6</td>\n",
-       "      <td>435</td>\n",
+       "      <td>107</td>\n",
         "      <td>-152.6</td>\n",
         "      <td>-152.6</td>\n",
-       "      <td>-2.850590</td>\n",
-       "      <td>476.0</td>\n",
+       "      <td>107.0</td>\n",
+       "      <td>-0.701180</td>\n",
+       "      <td>135.5</td>\n",
         "      <td>-208.6</td>\n",
         "      <td>-208.6</td>\n",
-       "      <td>-2.281879</td>\n",
+       "      <td>-0.649569</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-31</td>\n",
         "      <td>10262.0</td>\n",
         "      <td>10307.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>2020-07-31</td>\n",
         "      <td>10262.0</td>\n",
         "      <td>10307.4</td>\n",
-       "      <td>445</td>\n",
+       "      <td>113</td>\n",
         "      <td>-45.4</td>\n",
         "      <td>-45.4</td>\n",
-       "      <td>-9.801762</td>\n",
-       "      <td>440.0</td>\n",
+       "      <td>113.0</td>\n",
+       "      <td>-2.488987</td>\n",
+       "      <td>110.0</td>\n",
         "      <td>-99.0</td>\n",
         "      <td>-99.0</td>\n",
-       "      <td>-4.444444</td>\n",
+       "      <td>-1.111111</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-08-07</td>\n",
+       "      <td>10236.0</td>\n",
+       "      <td>10363.6</td>\n",
+       "      <td>89</td>\n",
+       "      <td>-127.6</td>\n",
+       "      <td>89.0</td>\n",
+       "      <td>-0.697492</td>\n",
+       "      <td>101.0</td>\n",
+       "      <td>-86.5</td>\n",
+       "      <td>-1.167630</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-08-14</td>\n",
+       "      <td>10592.0</td>\n",
+       "      <td>10345.8</td>\n",
+       "      <td>89</td>\n",
+       "      <td>246.2</td>\n",
+       "      <td>246.2</td>\n",
+       "      <td>0.361495</td>\n",
+       "      <td>89.0</td>\n",
+       "      <td>59.3</td>\n",
+       "      <td>1.500843</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-08-21</td>\n",
+       "      <td>10990.0</td>\n",
+       "      <td>10433.4</td>\n",
+       "      <td>56</td>\n",
+       "      <td>556.6</td>\n",
+       "      <td>556.6</td>\n",
+       "      <td>0.100611</td>\n",
+       "      <td>72.5</td>\n",
+       "      <td>401.4</td>\n",
+       "      <td>0.180618</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-08-28</td>\n",
+       "      <td>9023.0</td>\n",
+       "      <td>9472.2</td>\n",
+       "      <td>74</td>\n",
+       "      <td>-449.2</td>\n",
+       "      <td>74.0</td>\n",
+       "      <td>-0.164737</td>\n",
+       "      <td>65.0</td>\n",
+       "      <td>53.7</td>\n",
+       "      <td>1.210428</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-09-04</td>\n",
+       "      <td>10364.0</td>\n",
+       "      <td>10430.4</td>\n",
+       "      <td>50</td>\n",
+       "      <td>-66.4</td>\n",
+       "      <td>50.0</td>\n",
+       "      <td>-0.753012</td>\n",
+       "      <td>62.0</td>\n",
+       "      <td>-257.8</td>\n",
+       "      <td>-0.240497</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-09-11</td>\n",
+       "      <td>11176.0</td>\n",
+       "      <td>10610.8</td>\n",
+       "      <td>81</td>\n",
+       "      <td>565.2</td>\n",
+       "      <td>565.2</td>\n",
+       "      <td>0.143312</td>\n",
+       "      <td>65.5</td>\n",
+       "      <td>249.4</td>\n",
+       "      <td>0.262630</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-09-18</td>\n",
+       "      <td>10797.0</td>\n",
+       "      <td>10545.8</td>\n",
+       "      <td>97</td>\n",
+       "      <td>251.2</td>\n",
+       "      <td>251.2</td>\n",
+       "      <td>0.386146</td>\n",
+       "      <td>89.0</td>\n",
+       "      <td>408.2</td>\n",
+       "      <td>0.218030</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-09-25</td>\n",
+       "      <td>10890.0</td>\n",
+       "      <td>10709.6</td>\n",
+       "      <td>197</td>\n",
+       "      <td>180.4</td>\n",
+       "      <td>197.0</td>\n",
+       "      <td>1.092018</td>\n",
+       "      <td>147.0</td>\n",
+       "      <td>215.8</td>\n",
+       "      <td>0.681186</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-02</td>\n",
+       "      <td>11468.0</td>\n",
+       "      <td>10890.8</td>\n",
+       "      <td>300</td>\n",
+       "      <td>577.2</td>\n",
+       "      <td>577.2</td>\n",
+       "      <td>0.519751</td>\n",
+       "      <td>248.5</td>\n",
+       "      <td>378.8</td>\n",
+       "      <td>0.656019</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-09</td>\n",
+       "      <td>11373.0</td>\n",
+       "      <td>11186.4</td>\n",
+       "      <td>390</td>\n",
+       "      <td>186.6</td>\n",
+       "      <td>390.0</td>\n",
+       "      <td>2.090032</td>\n",
+       "      <td>345.0</td>\n",
+       "      <td>381.9</td>\n",
+       "      <td>0.903378</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-16</td>\n",
+       "      <td>11943.0</td>\n",
+       "      <td>11224.8</td>\n",
+       "      <td>701</td>\n",
+       "      <td>718.2</td>\n",
+       "      <td>718.2</td>\n",
+       "      <td>0.976051</td>\n",
+       "      <td>545.5</td>\n",
+       "      <td>452.4</td>\n",
+       "      <td>1.205791</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-23</td>\n",
+       "      <td>12317.0</td>\n",
+       "      <td>11093.2</td>\n",
+       "      <td>1054</td>\n",
+       "      <td>1223.8</td>\n",
+       "      <td>1223.8</td>\n",
+       "      <td>0.861252</td>\n",
+       "      <td>877.5</td>\n",
+       "      <td>971.0</td>\n",
+       "      <td>0.903708</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-10-30</td>\n",
+       "      <td>12517.0</td>\n",
+       "      <td>11257.6</td>\n",
+       "      <td>1608</td>\n",
+       "      <td>1259.4</td>\n",
+       "      <td>1608.0</td>\n",
+       "      <td>1.276798</td>\n",
+       "      <td>1331.0</td>\n",
+       "      <td>1241.6</td>\n",
+       "      <td>1.072004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-06</td>\n",
+       "      <td>13448.0</td>\n",
+       "      <td>11729.4</td>\n",
+       "      <td>2165</td>\n",
+       "      <td>1718.6</td>\n",
+       "      <td>2165.0</td>\n",
+       "      <td>1.259746</td>\n",
+       "      <td>1886.5</td>\n",
+       "      <td>1489.0</td>\n",
+       "      <td>1.266958</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-13</td>\n",
+       "      <td>13798.0</td>\n",
+       "      <td>11803.6</td>\n",
+       "      <td>2808</td>\n",
+       "      <td>1994.4</td>\n",
+       "      <td>2808.0</td>\n",
+       "      <td>1.407942</td>\n",
+       "      <td>2486.5</td>\n",
+       "      <td>1856.5</td>\n",
+       "      <td>1.339348</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-20</td>\n",
+       "      <td>14291.0</td>\n",
+       "      <td>11821.0</td>\n",
+       "      <td>2847</td>\n",
+       "      <td>2470.0</td>\n",
+       "      <td>2847.0</td>\n",
+       "      <td>1.152632</td>\n",
+       "      <td>2827.5</td>\n",
+       "      <td>2232.2</td>\n",
+       "      <td>1.266688</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-27</td>\n",
+       "      <td>14132.0</td>\n",
+       "      <td>11802.0</td>\n",
+       "      <td>3256</td>\n",
+       "      <td>2330.0</td>\n",
+       "      <td>3256.0</td>\n",
+       "      <td>1.397425</td>\n",
+       "      <td>3051.5</td>\n",
+       "      <td>2400.0</td>\n",
+       "      <td>1.271458</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "</div>"
        ],
        "text/plain": [
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "</div>"
        ],
        "text/plain": [
-       "            total_2020  previous_mean  covid_deaths   excess  \\\n",
-       "2020-03-20     12112.0        12007.4           149    104.6   \n",
-       "2020-03-27     12507.0        11549.6           720    957.4   \n",
-       "2020-04-03     18565.0        11681.4          2870   6883.6   \n",
-       "2020-04-10     20929.0        11919.4          5868   9009.6   \n",
-       "2020-04-17     24691.0        11850.6          6340  12840.4   \n",
-       "2020-04-24     24303.0        11844.4          5845  12458.6   \n",
-       "2020-05-01     20059.0        11318.4          4987   8740.6   \n",
-       "2020-05-08     14428.0        10887.2          3850   3540.8   \n",
-       "2020-05-15     16390.0        11547.0          3006   4843.0   \n",
-       "2020-05-22     13839.0        11281.0          2449   2558.0   \n",
-       "2020-05-29     11265.0         9448.0          2199   1817.0   \n",
-       "2020-06-05     12106.0        11325.6          1697    780.4   \n",
-       "2020-06-12     11302.0        10703.6          1388    598.4   \n",
-       "2020-06-19     10694.0        10698.2          1018     -4.2   \n",
-       "2020-06-26     10282.0        10605.6           835   -323.6   \n",
-       "2020-07-03     10412.0        10483.0           765    -71.0   \n",
-       "2020-07-10      9941.0        10509.4           607   -568.4   \n",
-       "2020-07-17     10096.0        10360.6           517   -264.6   \n",
-       "2020-07-24     10159.0        10311.6           435   -152.6   \n",
-       "2020-07-31     10262.0        10307.4           445    -45.4   \n",
+       "            total_2020  previous_mean  covid_deaths   excess  attributable  \\\n",
+       "2020-03-20     12112.0        12007.4           153    104.6         153.0   \n",
+       "2020-03-27     12507.0        11549.6           722    957.4         957.4   \n",
+       "2020-04-03     18565.0        11681.4          2898   6883.6        6883.6   \n",
+       "2020-04-10     20929.0        11919.4          5909   9009.6        9009.6   \n",
+       "2020-04-17     24691.0        11850.6          6338  12840.4       12840.4   \n",
+       "2020-04-24     24303.0        11844.4          5773  12458.6       12458.6   \n",
+       "2020-05-01     20059.0        11318.4          4881   8740.6        8740.6   \n",
+       "2020-05-08     14428.0        10887.2          3638   3540.8        3638.0   \n",
+       "2020-05-15     16390.0        11547.0          2671   4843.0        4843.0   \n",
+       "2020-05-22     13839.0        11281.0          2075   2558.0        2558.0   \n",
+       "2020-05-29     11265.0         9448.0          1890   1817.0        1890.0   \n",
+       "2020-06-05     12106.0        11325.6          1207    780.4        1207.0   \n",
+       "2020-06-12     11302.0        10703.6           937    598.4         937.0   \n",
+       "2020-06-19     10694.0        10698.2           591     -4.2         591.0   \n",
+       "2020-06-26     10282.0        10605.6           480   -323.6         480.0   \n",
+       "2020-07-03     10412.0        10483.0           360    -71.0         360.0   \n",
+       "2020-07-10      9941.0        10509.4           253   -568.4         253.0   \n",
+       "2020-07-17     10096.0        10360.6           164   -264.6         164.0   \n",
+       "2020-07-24     10159.0        10311.6           107   -152.6         107.0   \n",
+       "2020-07-31     10262.0        10307.4           113    -45.4         113.0   \n",
+       "2020-08-07     10236.0        10363.6            89   -127.6          89.0   \n",
+       "2020-08-14     10592.0        10345.8            89    246.2         246.2   \n",
+       "2020-08-21     10990.0        10433.4            56    556.6         556.6   \n",
+       "2020-08-28      9023.0         9472.2            74   -449.2          74.0   \n",
+       "2020-09-04     10364.0        10430.4            50    -66.4          50.0   \n",
+       "2020-09-11     11176.0        10610.8            81    565.2         565.2   \n",
+       "2020-09-18     10797.0        10545.8            97    251.2         251.2   \n",
+       "2020-09-25     10890.0        10709.6           197    180.4         197.0   \n",
+       "2020-10-02     11468.0        10890.8           300    577.2         577.2   \n",
+       "2020-10-09     11373.0        11186.4           390    186.6         390.0   \n",
+       "2020-10-16     11943.0        11224.8           701    718.2         718.2   \n",
+       "2020-10-23     12317.0        11093.2          1054   1223.8        1223.8   \n",
+       "2020-10-30     12517.0        11257.6          1608   1259.4        1608.0   \n",
+       "2020-11-06     13448.0        11729.4          2165   1718.6        2165.0   \n",
+       "2020-11-13     13798.0        11803.6          2808   1994.4        2808.0   \n",
+       "2020-11-20     14291.0        11821.0          2847   2470.0        2847.0   \n",
+       "2020-11-27     14132.0        11802.0          3256   2330.0        3256.0   \n",
         "\n",
         "            accounted_fraction  covid_deaths_m2  excess_m2  \\\n",
         "\n",
         "            accounted_fraction  covid_deaths_m2  excess_m2  \\\n",
-       "2020-03-20            1.424474            149.0      104.6   \n",
-       "2020-03-27            0.752037            434.5      531.0   \n",
-       "2020-04-03            0.416933           1795.0     3920.5   \n",
-       "2020-04-10            0.651305           4369.0     7946.6   \n",
-       "2020-04-17            0.493754           6104.0    10925.0   \n",
-       "2020-04-24            0.469154           6092.5    12649.5   \n",
-       "2020-05-01            0.570556           5416.0    10599.6   \n",
-       "2020-05-08            1.087325           4418.5     6140.7   \n",
-       "2020-05-15            0.620690           3428.0     4191.9   \n",
-       "2020-05-22            0.957389           2727.5     3700.5   \n",
-       "2020-05-29            1.210237           2324.0     2187.5   \n",
-       "2020-06-05            2.174526           1948.0     1298.7   \n",
-       "2020-06-12            2.319519           1542.5      689.4   \n",
-       "2020-06-19         -242.380952           1203.0      297.1   \n",
-       "2020-06-26           -2.580346            926.5     -163.9   \n",
-       "2020-07-03          -10.774648            800.0     -197.3   \n",
-       "2020-07-10           -1.067910            686.0     -319.7   \n",
-       "2020-07-17           -1.953893            562.0     -416.5   \n",
-       "2020-07-24           -2.850590            476.0     -208.6   \n",
-       "2020-07-31           -9.801762            440.0      -99.0   \n",
+       "2020-03-20            1.462715            153.0      104.6   \n",
+       "2020-03-27            0.754126            437.5      531.0   \n",
+       "2020-04-03            0.421001           1810.0     3920.5   \n",
+       "2020-04-10            0.655856           4403.5     7946.6   \n",
+       "2020-04-17            0.493598           6123.5    10925.0   \n",
+       "2020-04-24            0.463375           6055.5    12649.5   \n",
+       "2020-05-01            0.558428           5327.0    10599.6   \n",
+       "2020-05-08            1.027451           4259.5     6140.7   \n",
+       "2020-05-15            0.551518           3154.5     4191.9   \n",
+       "2020-05-22            0.811181           2373.0     3700.5   \n",
+       "2020-05-29            1.040176           1982.5     2187.5   \n",
+       "2020-06-05            1.546643           1548.5     1298.7   \n",
+       "2020-06-12            1.565842           1072.0      689.4   \n",
+       "2020-06-19         -140.714286            764.0      297.1   \n",
+       "2020-06-26           -1.483313            535.5     -163.9   \n",
+       "2020-07-03           -5.070423            420.0     -197.3   \n",
+       "2020-07-10           -0.445109            306.5     -319.7   \n",
+       "2020-07-17           -0.619803            208.5     -416.5   \n",
+       "2020-07-24           -0.701180            135.5     -208.6   \n",
+       "2020-07-31           -2.488987            110.0      -99.0   \n",
+       "2020-08-07           -0.697492            101.0      -86.5   \n",
+       "2020-08-14            0.361495             89.0       59.3   \n",
+       "2020-08-21            0.100611             72.5      401.4   \n",
+       "2020-08-28           -0.164737             65.0       53.7   \n",
+       "2020-09-04           -0.753012             62.0     -257.8   \n",
+       "2020-09-11            0.143312             65.5      249.4   \n",
+       "2020-09-18            0.386146             89.0      408.2   \n",
+       "2020-09-25            1.092018            147.0      215.8   \n",
+       "2020-10-02            0.519751            248.5      378.8   \n",
+       "2020-10-09            2.090032            345.0      381.9   \n",
+       "2020-10-16            0.976051            545.5      452.4   \n",
+       "2020-10-23            0.861252            877.5      971.0   \n",
+       "2020-10-30            1.276798           1331.0     1241.6   \n",
+       "2020-11-06            1.259746           1886.5     1489.0   \n",
+       "2020-11-13            1.407942           2486.5     1856.5   \n",
+       "2020-11-20            1.152632           2827.5     2232.2   \n",
+       "2020-11-27            1.397425           3051.5     2400.0   \n",
         "\n",
         "            accounted_fraction_m2  \n",
         "\n",
         "            accounted_fraction_m2  \n",
-       "2020-03-20               1.424474  \n",
-       "2020-03-27               0.818267  \n",
-       "2020-04-03               0.457850  \n",
-       "2020-04-10               0.549795  \n",
-       "2020-04-17               0.558719  \n",
-       "2020-04-24               0.481640  \n",
-       "2020-05-01               0.510963  \n",
-       "2020-05-08               0.719543  \n",
-       "2020-05-15               0.817768  \n",
-       "2020-05-22               0.737063  \n",
-       "2020-05-29               1.062400  \n",
-       "2020-06-05               1.499961  \n",
-       "2020-06-12               2.237453  \n",
-       "2020-06-19               4.049142  \n",
-       "2020-06-26              -5.652837  \n",
-       "2020-07-03              -4.054739  \n",
-       "2020-07-10              -2.145762  \n",
-       "2020-07-17              -1.349340  \n",
-       "2020-07-24              -2.281879  \n",
-       "2020-07-31              -4.444444  "
+       "2020-03-20               1.462715  \n",
+       "2020-03-27               0.823917  \n",
+       "2020-04-03               0.461676  \n",
+       "2020-04-10               0.554136  \n",
+       "2020-04-17               0.560503  \n",
+       "2020-04-24               0.478715  \n",
+       "2020-05-01               0.502566  \n",
+       "2020-05-08               0.693651  \n",
+       "2020-05-15               0.752523  \n",
+       "2020-05-22               0.641265  \n",
+       "2020-05-29               0.906286  \n",
+       "2020-06-05               1.192346  \n",
+       "2020-06-12               1.554975  \n",
+       "2020-06-19               2.571525  \n",
+       "2020-06-26              -3.267236  \n",
+       "2020-07-03              -2.128738  \n",
+       "2020-07-10              -0.958711  \n",
+       "2020-07-17              -0.500600  \n",
+       "2020-07-24              -0.649569  \n",
+       "2020-07-31              -1.111111  \n",
+       "2020-08-07              -1.167630  \n",
+       "2020-08-14               1.500843  \n",
+       "2020-08-21               0.180618  \n",
+       "2020-08-28               1.210428  \n",
+       "2020-09-04              -0.240497  \n",
+       "2020-09-11               0.262630  \n",
+       "2020-09-18               0.218030  \n",
+       "2020-09-25               0.681186  \n",
+       "2020-10-02               0.656019  \n",
+       "2020-10-09               0.903378  \n",
+       "2020-10-16               1.205791  \n",
+       "2020-10-23               0.903708  \n",
+       "2020-10-30               1.072004  \n",
+       "2020-11-06               1.266958  \n",
+       "2020-11-13               1.339348  \n",
+       "2020-11-20               1.266688  \n",
+       "2020-11-27               1.271458  "
        ]
       },
        ]
       },
-     "execution_count": 26,
+     "execution_count": 76,
       "metadata": {},
       "output_type": "execute_result"
      }
       "metadata": {},
       "output_type": "execute_result"
      }
@@ -2333,22 +4023,24 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 27,
-   "metadata": {},
+   "execution_count": 77,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
        "text/plain": [
     "outputs": [
      {
       "data": {
        "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f249a356990>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f41bf8727d0>"
        ]
       },
        ]
       },
-     "execution_count": 27,
+     "execution_count": 77,
       "metadata": {},
       "output_type": "execute_result"
      },
      {
       "data": {
       "metadata": {},
       "output_type": "execute_result"
      },
      {
       "data": {
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\n",
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\n",
        "text/plain": [
         "<Figure size 432x288 with 1 Axes>"
        ]
        "text/plain": [
         "<Figure size 432x288 with 1 Axes>"
        ]
@@ -2365,22 +4057,24 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {},
+   "execution_count": 78,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
        "text/plain": [
     "outputs": [
      {
       "data": {
        "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f249a26fb50>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f41bf7b8e10>"
        ]
       },
        ]
       },
-     "execution_count": 28,
+     "execution_count": 78,
       "metadata": {},
       "output_type": "execute_result"
      },
      {
       "data": {
       "metadata": {},
       "output_type": "execute_result"
      },
      {
       "data": {
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\n",
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\n",
        "text/plain": [
         "<Figure size 432x288 with 1 Axes>"
        ]
        "text/plain": [
         "<Figure size 432x288 with 1 Axes>"
        ]
@@ -2397,36 +4091,84 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {},
+   "execution_count": 79,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
        "text/plain": [
     "outputs": [
      {
       "data": {
        "text/plain": [
-       "1397"
+       "9772.4"
        ]
       },
        ]
       },
-     "execution_count": 29,
+     "execution_count": 79,
       "metadata": {},
       "output_type": "execute_result"
      }
     ],
     "source": [
       "metadata": {},
       "output_type": "execute_result"
      }
     ],
     "source": [
-    "excess_deaths.tail(3).covid_deaths.sum()"
+    "excess_deaths.tail(5).excess.sum()"
     ]
    },
    {
     "cell_type": "code",
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {},
+   "execution_count": 80,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
        "text/plain": [
     "outputs": [
      {
       "data": {
        "text/plain": [
-       "-0.3311381531853975"
+       "12684"
        ]
       },
        ]
       },
-     "execution_count": 30,
+     "execution_count": 80,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "excess_deaths.tail(5).covid_deaths.sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.7704509618416903"
+      ]
+     },
+     "execution_count": 81,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "excess_deaths.tail(5).excess.sum() / excess_deaths.tail(5).covid_deaths.sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.7624733475479744"
+      ]
+     },
+     "execution_count": 82,
       "metadata": {},
       "output_type": "execute_result"
      }
       "metadata": {},
       "output_type": "execute_result"
      }
@@ -2437,8 +4179,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {},
+   "execution_count": 83,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
@@ -2446,7 +4190,7 @@
         "1"
        ]
       },
         "1"
        ]
       },
-     "execution_count": 31,
+     "execution_count": 83,
       "metadata": {},
       "output_type": "execute_result"
      }
       "metadata": {},
       "output_type": "execute_result"
      }
@@ -2457,18 +4201,63 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {},
+   "execution_count": 84,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
     "outputs": [],
     "source": [
-    "with open('excess_death_accuracy.json', 'w') as f:\n",
-    "    json.dump(max(1, excess_deaths.tail(3).excess.sum() / excess_deaths.tail(3).covid_deaths.sum()), f)"
+    "# with open('excess_death_accuracy.json', 'w') as f:\n",
+    "# #     json.dump(max(1, excess_deaths.tail(3).excess.sum() / excess_deaths.tail(3).covid_deaths.sum()), f)\n",
+    "#     json.dump(1, f)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'85807'"
+      ]
+     },
+     "execution_count": 85,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "f'{excess_deaths.attributable.sum():.0f}'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "excess_death_data = {\n",
+    "    'start_date': str(excess_deaths.index[0]),\n",
+    "    'end_date': str(excess_deaths.index[-1]),\n",
+    "    'excess_deaths': f'{excess_deaths.attributable.sum():.0f}'\n",
+    "}\n",
+    "\n",
+    "with open('excess_deaths.json', 'w') as f:\n",
+    "    json.dump(excess_death_data, f)"
     ]
    },
    {
     "cell_type": "code",
     "execution_count": null,
     ]
    },
    {
     "cell_type": "code",
     "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": []
    }
     "outputs": [],
     "source": []
    }
@@ -2489,7 +4278,7 @@
     "name": "python",
     "nbconvert_exporter": "python",
     "pygments_lexer": "ipython3",
     "name": "python",
     "nbconvert_exporter": "python",
     "pygments_lexer": "ipython3",
-   "version": "3.7.4"
+   "version": "3.8.5"
    }
   },
   "nbformat": 4,
    }
   },
   "nbformat": 4,
diff --git a/excess_deaths.js b/excess_deaths.js

deleted file mode 100644 (file)

index cae0e6f..0000000
--- a/excess_deaths.js
+++ /dev/null
@@ -1 +0,0 @@
-document.write('64734');
-\ No newline at end of file
diff --git a/excess_deaths.json b/excess_deaths.json

deleted file mode 100644 (file)

index 695b2a8..0000000
--- a/excess_deaths.json
+++ /dev/null
@@ -1 +0,0 @@
-{"start_date": "2020-03-20 00:00:00", "end_date": "2020-07-03 00:00:00", "excess_deaths": 64733.6}
-\ No newline at end of file
diff --git a/excess_deaths_upto.js b/excess_deaths_upto.js

deleted file mode 100644 (file)

index 72a3148..0000000
--- a/excess_deaths_upto.js
+++ /dev/null
@@ -1 +0,0 @@
-document.write('03 July 2020');
-\ No newline at end of file
diff --git a/historical_deaths_import.ipynb b/historical_deaths_import.ipynb

new file mode 100644 (file)

index 0000000..3436ba2
--- /dev/null
+++ b/historical_deaths_import.ipynb
@@ -0,0 +1,15646 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "source": [
+    "Data from:\n",
+    "\n",
+    "* [Office of National Statistics](https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/weeklyprovisionalfiguresondeathsregisteredinenglandandwales) (Endland and Wales) Weeks start on a Saturday.\n",
+    "* [Northern Ireland Statistics and Research Agency](https://www.nisra.gov.uk/publications/weekly-deaths) (Northern Ireland). Weeks start on a Saturday. Note that the week numbers don't match the England and Wales data.\n",
+    "* [National Records of Scotland](https://www.nrscotland.gov.uk/statistics-and-data/statistics/statistics-by-theme/vital-events/general-publications/weekly-and-monthly-data-on-births-and-deaths/weekly-data-on-births-and-deaths) (Scotland). Note that Scotland uses ISO8601 week numbers, which start on a Monday.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "import itertools\n",
+    "import collections\n",
+    "import json\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "from scipy.stats import gmean\n",
+    "import datetime\n",
+    "\n",
+    "import matplotlib as mpl\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline\n",
+    "\n",
+    "from sqlalchemy.types import Integer, Text, String, DateTime, Float\n",
+    "from sqlalchemy import create_engine\n",
+    "%load_ext sql"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Connected: covid@covid'"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql $connection_string"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "conn = create_engine(connection_string)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "england_wales_filename = 'uk-deaths-data/publishedweek532020.xlsx'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "Done.\n",
+      "Done.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[]"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%sql\n",
+    "drop table if exists all_causes_deaths;\n",
+    "create table all_causes_deaths (\n",
+    "    week integer,\n",
+    "    year integer,\n",
+    "    date_up_to date,\n",
+    "    nation varchar(20),\n",
+    "    deaths integer,\n",
+    "    CONSTRAINT week_nation PRIMARY KEY(year, week, nation)\n",
+    ");"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>total_2015</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>(Registration Week, Unnamed: 0_level_1)</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>294</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>343</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>301</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>232</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>232</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                         total_2015\n",
+       "(Registration Week, Unnamed: 0_level_1)            \n",
+       "49                                              294\n",
+       "50                                              343\n",
+       "51                                              301\n",
+       "52                                              232\n",
+       "53                                              232"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data_2015 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2015.csv', \n",
+    "                       parse_dates=[1, 2], dayfirst=True,\n",
+    "#                       index_col=0,\n",
+    "                      header=[0, 1]\n",
+    "                           )\n",
+    "dh15i = raw_data_2015.iloc[:, [0, 3]]\n",
+    "dh15i.set_index(dh15i.columns[0], inplace=True)\n",
+    "dh15i.columns = ['total_2015']\n",
+    "dh15i.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead tr th {\n",
+       "        text-align: left;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th>Registration Week</th>\n",
+       "      <th>Week Starts (Saturday)</th>\n",
+       "      <th>Week Ends (Friday)</th>\n",
+       "      <th>Total Number of Deaths Registered in Week (2015P)</th>\n",
+       "      <th>Average number of deaths registered in corresponding week in previous 5 years (2010 to 2014P)</th>\n",
+       "      <th>Range</th>\n",
+       "      <th>Unnamed: 6_level_0</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th>Unnamed: 0_level_1</th>\n",
+       "      <th>Unnamed: 1_level_1</th>\n",
+       "      <th>Unnamed: 2_level_1</th>\n",
+       "      <th>Unnamed: 3_level_1</th>\n",
+       "      <th>Unnamed: 4_level_1</th>\n",
+       "      <th>Minimum in Previous 5 years</th>\n",
+       "      <th>Maximum in Previous 5 years</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2014-12-29</td>\n",
+       "      <td>2015-01-02</td>\n",
+       "      <td>319</td>\n",
+       "      <td>317.2</td>\n",
+       "      <td>248</td>\n",
+       "      <td>372</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2015-01-03</td>\n",
+       "      <td>2015-01-09</td>\n",
+       "      <td>373</td>\n",
+       "      <td>384.0</td>\n",
+       "      <td>344</td>\n",
+       "      <td>421</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2015-01-10</td>\n",
+       "      <td>2015-01-16</td>\n",
+       "      <td>383</td>\n",
+       "      <td>347.8</td>\n",
+       "      <td>319</td>\n",
+       "      <td>373</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2015-01-17</td>\n",
+       "      <td>2015-01-23</td>\n",
+       "      <td>397</td>\n",
+       "      <td>319.0</td>\n",
+       "      <td>282</td>\n",
+       "      <td>353</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2015-01-24</td>\n",
+       "      <td>2015-01-30</td>\n",
+       "      <td>374</td>\n",
+       "      <td>309.2</td>\n",
+       "      <td>284</td>\n",
+       "      <td>336</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Registration Week Week Starts (Saturday) Week Ends (Friday)  \\\n",
+       "  Unnamed: 0_level_1     Unnamed: 1_level_1 Unnamed: 2_level_1   \n",
+       "0                  1             2014-12-29         2015-01-02   \n",
+       "1                  2             2015-01-03         2015-01-09   \n",
+       "2                  3             2015-01-10         2015-01-16   \n",
+       "3                  4             2015-01-17         2015-01-23   \n",
+       "4                  5             2015-01-24         2015-01-30   \n",
+       "\n",
+       "  Total Number of Deaths Registered in Week (2015P)  \\\n",
+       "                                 Unnamed: 3_level_1   \n",
+       "0                                               319   \n",
+       "1                                               373   \n",
+       "2                                               383   \n",
+       "3                                               397   \n",
+       "4                                               374   \n",
+       "\n",
+       "  Average number of deaths registered in corresponding week in previous 5 years (2010 to 2014P)  \\\n",
+       "                                                                             Unnamed: 4_level_1   \n",
+       "0                                              317.2                                              \n",
+       "1                                              384.0                                              \n",
+       "2                                              347.8                                              \n",
+       "3                                              319.0                                              \n",
+       "4                                              309.2                                              \n",
+       "\n",
+       "                        Range          Unnamed: 6_level_0  \n",
+       "  Minimum in Previous 5 years Maximum in Previous 5 years  \n",
+       "0                         248                         372  \n",
+       "1                         344                         421  \n",
+       "2                         319                         373  \n",
+       "3                         282                         353  \n",
+       "4                         284                         336  "
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data_2015.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2015-01-02</td>\n",
+       "      <td>319</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2015-01-09</td>\n",
+       "      <td>373</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2015-01-16</td>\n",
+       "      <td>383</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2015-01-23</td>\n",
+       "      <td>397</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2015-01-30</td>\n",
+       "      <td>374</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week date_up_to  deaths  year            nation\n",
+       "0     1 2015-01-02     319  2015  Northern Ireland\n",
+       "1     2 2015-01-09     373  2015  Northern Ireland\n",
+       "2     3 2015-01-16     383  2015  Northern Ireland\n",
+       "3     4 2015-01-23     397  2015  Northern Ireland\n",
+       "4     5 2015-01-30     374  2015  Northern Ireland"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = raw_data_2015.iloc[:, [0, 2, 3]].droplevel(1, axis=1).rename(\n",
+    "    columns={'Week Ends (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2015P)': 'deaths',\n",
+    "            'Registration Week': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2015\n",
+    "rd['nation'] = 'Northern Ireland'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "10 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>week</th>\n",
+       "            <th>year</th>\n",
+       "            <th>date_up_to</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>deaths</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>1</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-01-02</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>319</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-01-09</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>373</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>3</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-01-16</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>383</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>4</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-01-23</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>397</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>5</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-01-30</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>374</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>6</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-02-06</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>347</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>7</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-02-13</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>328</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>8</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-02-20</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>317</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>9</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-02-27</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>401</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>10</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-03-06</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>346</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(1, 2015, datetime.date(2015, 1, 2), 'Northern Ireland', 319),\n",
+       " (2, 2015, datetime.date(2015, 1, 9), 'Northern Ireland', 373),\n",
+       " (3, 2015, datetime.date(2015, 1, 16), 'Northern Ireland', 383),\n",
+       " (4, 2015, datetime.date(2015, 1, 23), 'Northern Ireland', 397),\n",
+       " (5, 2015, datetime.date(2015, 1, 30), 'Northern Ireland', 374),\n",
+       " (6, 2015, datetime.date(2015, 2, 6), 'Northern Ireland', 347),\n",
+       " (7, 2015, datetime.date(2015, 2, 13), 'Northern Ireland', 328),\n",
+       " (8, 2015, datetime.date(2015, 2, 20), 'Northern Ireland', 317),\n",
+       " (9, 2015, datetime.date(2015, 2, 27), 'Northern Ireland', 401),\n",
+       " (10, 2015, datetime.date(2015, 3, 6), 'Northern Ireland', 346)]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select * from all_causes_deaths limit 10"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>total_2016</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>(Registration Week, Unnamed: 0_level_1)</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>303</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>322</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>324</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>360</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>199</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                         total_2016\n",
+       "(Registration Week, Unnamed: 0_level_1)            \n",
+       "48                                              303\n",
+       "49                                              322\n",
+       "50                                              324\n",
+       "51                                              360\n",
+       "52                                              199"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data_2016 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2016.csv', \n",
+    "                        parse_dates=[1, 2], dayfirst=True,\n",
+    "#                       index_col=0,\n",
+    "                      header=[0, 1]\n",
+    "                           )\n",
+    "raw_data_2016.head()\n",
+    "# dh16i = raw_data_2016.iloc[:, [2]]\n",
+    "# dh16i.columns = ['total_2016']\n",
+    "# # dh16i.head()\n",
+    "dh16i = raw_data_2016.iloc[:, [0, 3]]\n",
+    "dh16i.set_index(dh16i.columns[0], inplace=True)\n",
+    "dh16i.columns = ['total_2016']\n",
+    "dh16i.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2016-01-08</td>\n",
+       "      <td>424</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2016-01-15</td>\n",
+       "      <td>348</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2016-01-22</td>\n",
+       "      <td>372</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2016-01-29</td>\n",
+       "      <td>355</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2016-02-05</td>\n",
+       "      <td>314</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week date_up_to  deaths  year            nation\n",
+       "0     1 2016-01-08     424  2016  Northern Ireland\n",
+       "1     2 2016-01-15     348  2016  Northern Ireland\n",
+       "2     3 2016-01-22     372  2016  Northern Ireland\n",
+       "3     4 2016-01-29     355  2016  Northern Ireland\n",
+       "4     5 2016-02-05     314  2016  Northern Ireland"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = raw_data_2016.iloc[:, [0, 2, 3]].droplevel(1, axis=1).rename(\n",
+    "    columns={'Week Ends (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2016P)': 'deaths',\n",
+    "            'Registration Week': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2016\n",
+    "rd['nation'] = 'Northern Ireland'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "2 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2015, 'Northern Ireland', 53), (2016, 'Northern Ireland', 52)]"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>total_2017</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>(Registration Week, Unnamed: 0_level_1)</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>355</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>324</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>372</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>354</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>249</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                         total_2017\n",
+       "(Registration Week, Unnamed: 0_level_1)            \n",
+       "48                                              355\n",
+       "49                                              324\n",
+       "50                                              372\n",
+       "51                                              354\n",
+       "52                                              249"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data_2017 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2017.csv', \n",
+    "                        parse_dates=[1, 2], dayfirst=True,\n",
+    "#                       index_col=0,\n",
+    "                      header=[0, 1]\n",
+    "                           )\n",
+    "raw_data_2017.head()\n",
+    "dh17i = raw_data_2017.iloc[:, [0, 3]]\n",
+    "dh17i.set_index(dh17i.columns[0], inplace=True)\n",
+    "dh17i.columns = ['total_2017']\n",
+    "dh17i.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2017-01-06</td>\n",
+       "      <td>416</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2017-01-13</td>\n",
+       "      <td>434</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2017-01-20</td>\n",
+       "      <td>397</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2017-01-27</td>\n",
+       "      <td>387</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2017-02-03</td>\n",
+       "      <td>371</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week date_up_to  deaths  year            nation\n",
+       "0     1 2017-01-06     416  2017  Northern Ireland\n",
+       "1     2 2017-01-13     434  2017  Northern Ireland\n",
+       "2     3 2017-01-20     397  2017  Northern Ireland\n",
+       "3     4 2017-01-27     387  2017  Northern Ireland\n",
+       "4     5 2017-02-03     371  2017  Northern Ireland"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = raw_data_2017.iloc[:, [0, 2, 3]].droplevel(1, axis=1).rename(\n",
+    "    columns={'Week Ends (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2017P)': 'deaths',\n",
+    "            'Registration Week': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2017\n",
+    "rd['nation'] = 'Northern Ireland'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "3 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2015, 'Northern Ireland', 53),\n",
+       " (2017, 'Northern Ireland', 52),\n",
+       " (2016, 'Northern Ireland', 52)]"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>total_2018</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>(Registration Week, Unnamed: 0_level_1)</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>297</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>324</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>316</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>317</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>195</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                         total_2018\n",
+       "(Registration Week, Unnamed: 0_level_1)            \n",
+       "48                                              297\n",
+       "49                                              324\n",
+       "50                                              316\n",
+       "51                                              317\n",
+       "52                                              195"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data_2018 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2018.csv', \n",
+    "                        parse_dates=[1, 2], dayfirst=True,\n",
+    "#                       index_col=0,\n",
+    "                      header=[0, 1]\n",
+    "                           )\n",
+    "raw_data_2018.head()\n",
+    "dh18i = raw_data_2018.iloc[:, [0, 3]]\n",
+    "dh18i.set_index(dh18i.columns[0], inplace=True)\n",
+    "dh18i.columns = ['total_2018']\n",
+    "dh18i.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2018-01-05</td>\n",
+       "      <td>447</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2018-01-12</td>\n",
+       "      <td>481</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2018-01-19</td>\n",
+       "      <td>470</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2018-01-26</td>\n",
+       "      <td>426</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2018-02-02</td>\n",
+       "      <td>433</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week date_up_to  deaths  year            nation\n",
+       "0     1 2018-01-05     447  2018  Northern Ireland\n",
+       "1     2 2018-01-12     481  2018  Northern Ireland\n",
+       "2     3 2018-01-19     470  2018  Northern Ireland\n",
+       "3     4 2018-01-26     426  2018  Northern Ireland\n",
+       "4     5 2018-02-02     433  2018  Northern Ireland"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = raw_data_2018.iloc[:, [0, 2, 3]].droplevel(1, axis=1).rename(\n",
+    "    columns={'Week Ends (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2018P)': 'deaths',\n",
+    "            'Registration Week': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2018\n",
+    "rd['nation'] = 'Northern Ireland'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "4 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2015, 'Northern Ireland', 53),\n",
+       " (2018, 'Northern Ireland', 52),\n",
+       " (2017, 'Northern Ireland', 52),\n",
+       " (2016, 'Northern Ireland', 52)]"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>total_2019</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>(Registration Week, Unnamed: 0_level_1)</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>334</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>351</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>353</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>363</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>194</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                         total_2019\n",
+       "(Registration Week, Unnamed: 0_level_1)            \n",
+       "48                                              334\n",
+       "49                                              351\n",
+       "50                                              353\n",
+       "51                                              363\n",
+       "52                                              194"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data_2019 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2019.csv', \n",
+    "                        parse_dates=[1, 2], dayfirst=True,\n",
+    "#                       index_col=0,\n",
+    "                      header=[0, 1]\n",
+    "                           )\n",
+    "raw_data_2019.head()\n",
+    "dh19i = raw_data_2019.iloc[:, [0, 3]]\n",
+    "dh19i.set_index(dh19i.columns[0], inplace=True)\n",
+    "dh19i.columns = ['total_2019']\n",
+    "dh19i.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2019-01-04</td>\n",
+       "      <td>365</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2019-01-11</td>\n",
+       "      <td>371</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2019-01-18</td>\n",
+       "      <td>332</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2019-01-25</td>\n",
+       "      <td>335</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2019-02-01</td>\n",
+       "      <td>296</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week date_up_to  deaths  year            nation\n",
+       "0     1 2019-01-04     365  2019  Northern Ireland\n",
+       "1     2 2019-01-11     371  2019  Northern Ireland\n",
+       "2     3 2019-01-18     332  2019  Northern Ireland\n",
+       "3     4 2019-01-25     335  2019  Northern Ireland\n",
+       "4     5 2019-02-01     296  2019  Northern Ireland"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = raw_data_2019.iloc[:, [0, 2, 3]].droplevel(1, axis=1).rename(\n",
+    "    columns={'Week Ends (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2019P)': 'deaths',\n",
+    "            'Registration Week': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2019\n",
+    "rd['nation'] = 'Northern Ireland'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "5 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2015, 'Northern Ireland', 53),\n",
+       " (2018, 'Northern Ireland', 52),\n",
+       " (2019, 'Northern Ireland', 52),\n",
+       " (2017, 'Northern Ireland', 52),\n",
+       " (2016, 'Northern Ireland', 52)]"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead tr th {\n",
+       "        text-align: left;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th>Registration Week</th>\n",
+       "      <th>Week Ending (Friday)</th>\n",
+       "      <th>Total Number of Deaths Registered in Week (2020P)</th>\n",
+       "      <th>Average number of deaths registered in corresponding week over previous 5 years (2015 to 2019P)</th>\n",
+       "      <th>Range</th>\n",
+       "      <th>Unnamed: 5_level_0</th>\n",
+       "      <th>Respiratory2 deaths registered in week (2020P)</th>\n",
+       "      <th>Average number of respiratory2 deaths registered in corresponding week over previous 5 years (2015 to 2019P)</th>\n",
+       "      <th>Covid-193 deaths registered in week (2020P)</th>\n",
+       "      <th>Unnamed: 9_level_0</th>\n",
+       "      <th>Unnamed: 10_level_0</th>\n",
+       "      <th>Unnamed: 11_level_0</th>\n",
+       "      <th>Unnamed: 12_level_0</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th>Unnamed: 0_level_1</th>\n",
+       "      <th>Unnamed: 1_level_1</th>\n",
+       "      <th>Unnamed: 2_level_1</th>\n",
+       "      <th>Unnamed: 3_level_1</th>\n",
+       "      <th>Minimum in Previous 5 years</th>\n",
+       "      <th>Maximum in Previous 5 years</th>\n",
+       "      <th>Unnamed: 6_level_1</th>\n",
+       "      <th>Unnamed: 7_level_1</th>\n",
+       "      <th>Unnamed: 8_level_1</th>\n",
+       "      <th>Unnamed: 9_level_1</th>\n",
+       "      <th>Unnamed: 10_level_1</th>\n",
+       "      <th>Unnamed: 11_level_1</th>\n",
+       "      <th>Unnamed: 12_level_1</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-01-03</td>\n",
+       "      <td>353</td>\n",
+       "      <td>250.0</td>\n",
+       "      <td>199</td>\n",
+       "      <td>365</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2020-01-10</td>\n",
+       "      <td>395</td>\n",
+       "      <td>402.2</td>\n",
+       "      <td>319</td>\n",
+       "      <td>481</td>\n",
+       "      <td>131</td>\n",
+       "      <td>144</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2020-01-17</td>\n",
+       "      <td>411</td>\n",
+       "      <td>391.4</td>\n",
+       "      <td>332</td>\n",
+       "      <td>470</td>\n",
+       "      <td>116</td>\n",
+       "      <td>127.6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2020-01-24</td>\n",
+       "      <td>347</td>\n",
+       "      <td>382.6</td>\n",
+       "      <td>335</td>\n",
+       "      <td>426</td>\n",
+       "      <td>113</td>\n",
+       "      <td>123.8</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2020-01-31</td>\n",
+       "      <td>323</td>\n",
+       "      <td>373.6</td>\n",
+       "      <td>296</td>\n",
+       "      <td>433</td>\n",
+       "      <td>78</td>\n",
+       "      <td>124</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Registration Week Week Ending (Friday)  \\\n",
+       "  Unnamed: 0_level_1   Unnamed: 1_level_1   \n",
+       "0                  1           2020-01-03   \n",
+       "1                  2           2020-01-10   \n",
+       "2                  3           2020-01-17   \n",
+       "3                  4           2020-01-24   \n",
+       "4                  5           2020-01-31   \n",
+       "\n",
+       "  Total Number of Deaths Registered in Week (2020P)  \\\n",
+       "                                 Unnamed: 2_level_1   \n",
+       "0                                               353   \n",
+       "1                                               395   \n",
+       "2                                               411   \n",
+       "3                                               347   \n",
+       "4                                               323   \n",
+       "\n",
+       "  Average number of deaths registered in corresponding week over previous 5 years (2015 to 2019P)  \\\n",
+       "                                                                               Unnamed: 3_level_1   \n",
+       "0                                              250.0                                                \n",
+       "1                                              402.2                                                \n",
+       "2                                              391.4                                                \n",
+       "3                                              382.6                                                \n",
+       "4                                              373.6                                                \n",
+       "\n",
+       "                        Range          Unnamed: 5_level_0  \\\n",
+       "  Minimum in Previous 5 years Maximum in Previous 5 years   \n",
+       "0                         199                         365   \n",
+       "1                         319                         481   \n",
+       "2                         332                         470   \n",
+       "3                         335                         426   \n",
+       "4                         296                         433   \n",
+       "\n",
+       "  Respiratory2 deaths registered in week (2020P)  \\\n",
+       "                              Unnamed: 6_level_1   \n",
+       "0                                              0   \n",
+       "1                                            131   \n",
+       "2                                            116   \n",
+       "3                                            113   \n",
+       "4                                             78   \n",
+       "\n",
+       "  Average number of respiratory2 deaths registered in corresponding week over previous 5 years (2015 to 2019P)  \\\n",
+       "                                                                                            Unnamed: 7_level_1   \n",
+       "0                                                  0                                                             \n",
+       "1                                                144                                                             \n",
+       "2                                              127.6                                                             \n",
+       "3                                              123.8                                                             \n",
+       "4                                                124                                                             \n",
+       "\n",
+       "  Covid-193 deaths registered in week (2020P) Unnamed: 9_level_0  \\\n",
+       "                           Unnamed: 8_level_1 Unnamed: 9_level_1   \n",
+       "0                                           0                NaN   \n",
+       "1                                           0                NaN   \n",
+       "2                                           0                NaN   \n",
+       "3                                           0                NaN   \n",
+       "4                                           0                NaN   \n",
+       "\n",
+       "  Unnamed: 10_level_0 Unnamed: 11_level_0 Unnamed: 12_level_0  \n",
+       "  Unnamed: 10_level_1 Unnamed: 11_level_1 Unnamed: 12_level_1  \n",
+       "0                 NaN                 NaN                 NaN  \n",
+       "1                 NaN                 NaN                 NaN  \n",
+       "2                 NaN                 NaN                 NaN  \n",
+       "3                 NaN                 NaN                 NaN  \n",
+       "4                 NaN                 NaN                 NaN  "
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data_2020_i = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2020.csv', \n",
+    "                        parse_dates=[1], dayfirst=True,\n",
+    "                      header=[0, 1]\n",
+    "                           )\n",
+    "raw_data_2020_i.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-01-03</td>\n",
+       "      <td>353</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2020-01-10</td>\n",
+       "      <td>395</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2020-01-17</td>\n",
+       "      <td>411</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2020-01-24</td>\n",
+       "      <td>347</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2020-01-31</td>\n",
+       "      <td>323</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week date_up_to  deaths  year            nation\n",
+       "0     1 2020-01-03     353  2020  Northern Ireland\n",
+       "1     2 2020-01-10     395  2020  Northern Ireland\n",
+       "2     3 2020-01-17     411  2020  Northern Ireland\n",
+       "3     4 2020-01-24     347  2020  Northern Ireland\n",
+       "4     5 2020-01-31     323  2020  Northern Ireland"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = raw_data_2020_i.iloc[:, [0, 1, 2]].droplevel(1, axis=1).rename(\n",
+    "    columns={'Week Ending (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2020P)': 'deaths',\n",
+    "            'Registration Week': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2020\n",
+    "rd['nation'] = 'Northern Ireland'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>49</td>\n",
+       "      <td>2020-12-04</td>\n",
+       "      <td>387</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>50</td>\n",
+       "      <td>2020-12-11</td>\n",
+       "      <td>366</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>51</td>\n",
+       "      <td>2020-12-18</td>\n",
+       "      <td>350</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>52</td>\n",
+       "      <td>2020-12-25</td>\n",
+       "      <td>310</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>53</td>\n",
+       "      <td>2021-01-01</td>\n",
+       "      <td>333</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    week date_up_to  deaths  year            nation\n",
+       "48    49 2020-12-04     387  2020  Northern Ireland\n",
+       "49    50 2020-12-11     366  2020  Northern Ireland\n",
+       "50    51 2020-12-18     350  2020  Northern Ireland\n",
+       "51    52 2020-12-25     310  2020  Northern Ireland\n",
+       "52    53 2021-01-01     333  2020  Northern Ireland"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "6 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2015, 'Northern Ireland', 53),\n",
+       " (2016, 'Northern Ireland', 52),\n",
+       " (2017, 'Northern Ireland', 52),\n",
+       " (2018, 'Northern Ireland', 52),\n",
+       " (2019, 'Northern Ireland', 52),\n",
+       " (2020, 'Northern Ireland', 53)]"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead tr th {\n",
+       "        text-align: left;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead tr:last-of-type th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th>Week Ending (Friday)</th>\n",
+       "      <th>Total Number of Deaths Registered in Week (2020P)</th>\n",
+       "      <th>Average number of deaths registered in corresponding week over previous 5 years (2015 to 2019P)</th>\n",
+       "      <th>Range</th>\n",
+       "      <th>Unnamed: 5_level_0</th>\n",
+       "      <th>Respiratory2 deaths registered in week (2020P)</th>\n",
+       "      <th>Average number of respiratory2 deaths registered in corresponding week over previous 5 years (2015 to 2019P)</th>\n",
+       "      <th>Covid-193 deaths registered in week (2020P)</th>\n",
+       "      <th>Unnamed: 9_level_0</th>\n",
+       "      <th>Unnamed: 10_level_0</th>\n",
+       "      <th>Unnamed: 11_level_0</th>\n",
+       "      <th>Unnamed: 12_level_0</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th>Unnamed: 1_level_1</th>\n",
+       "      <th>Unnamed: 2_level_1</th>\n",
+       "      <th>Unnamed: 3_level_1</th>\n",
+       "      <th>Minimum in Previous 5 years</th>\n",
+       "      <th>Maximum in Previous 5 years</th>\n",
+       "      <th>Unnamed: 6_level_1</th>\n",
+       "      <th>Unnamed: 7_level_1</th>\n",
+       "      <th>Unnamed: 8_level_1</th>\n",
+       "      <th>Unnamed: 9_level_1</th>\n",
+       "      <th>Unnamed: 10_level_1</th>\n",
+       "      <th>Unnamed: 11_level_1</th>\n",
+       "      <th>Unnamed: 12_level_1</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>(Registration Week, Unnamed: 0_level_1)</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>2020-12-04</td>\n",
+       "      <td>387</td>\n",
+       "      <td>322.0</td>\n",
+       "      <td>279</td>\n",
+       "      <td>355</td>\n",
+       "      <td>-</td>\n",
+       "      <td>-</td>\n",
+       "      <td>-</td>\n",
+       "      <td>155.0</td>\n",
+       "      <td>87.0</td>\n",
+       "      <td>-</td>\n",
+       "      <td>98.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>2020-12-11</td>\n",
+       "      <td>366</td>\n",
+       "      <td>322.0</td>\n",
+       "      <td>294</td>\n",
+       "      <td>353</td>\n",
+       "      <td>-</td>\n",
+       "      <td>-</td>\n",
+       "      <td>-</td>\n",
+       "      <td>138.0</td>\n",
+       "      <td>93.0</td>\n",
+       "      <td>-</td>\n",
+       "      <td>87.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>2020-12-18</td>\n",
+       "      <td>350</td>\n",
+       "      <td>344.0</td>\n",
+       "      <td>317</td>\n",
+       "      <td>372</td>\n",
+       "      <td>-</td>\n",
+       "      <td>-</td>\n",
+       "      <td>-</td>\n",
+       "      <td>140.0</td>\n",
+       "      <td>102.0</td>\n",
+       "      <td>-</td>\n",
+       "      <td>82.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>2020-12-25</td>\n",
+       "      <td>310</td>\n",
+       "      <td>281.0</td>\n",
+       "      <td>194</td>\n",
+       "      <td>360</td>\n",
+       "      <td>-</td>\n",
+       "      <td>-</td>\n",
+       "      <td>-</td>\n",
+       "      <td>132.0</td>\n",
+       "      <td>92.0</td>\n",
+       "      <td>-</td>\n",
+       "      <td>88.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>2021-01-01</td>\n",
+       "      <td>333</td>\n",
+       "      <td>280.0</td>\n",
+       "      <td>199</td>\n",
+       "      <td>365</td>\n",
+       "      <td>-</td>\n",
+       "      <td>-</td>\n",
+       "      <td>-</td>\n",
+       "      <td>146.0</td>\n",
+       "      <td>97.0</td>\n",
+       "      <td>-</td>\n",
+       "      <td>94.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                        Week Ending (Friday)  \\\n",
+       "                                          Unnamed: 1_level_1   \n",
+       "(Registration Week, Unnamed: 0_level_1)                        \n",
+       "49                                                2020-12-04   \n",
+       "50                                                2020-12-11   \n",
+       "51                                                2020-12-18   \n",
+       "52                                                2020-12-25   \n",
+       "53                                                2021-01-01   \n",
+       "\n",
+       "                                        Total Number of Deaths Registered in Week (2020P)  \\\n",
+       "                                                                       Unnamed: 2_level_1   \n",
+       "(Registration Week, Unnamed: 0_level_1)                                                     \n",
+       "49                                                                                    387   \n",
+       "50                                                                                    366   \n",
+       "51                                                                                    350   \n",
+       "52                                                                                    310   \n",
+       "53                                                                                    333   \n",
+       "\n",
+       "                                        Average number of deaths registered in corresponding week over previous 5 years (2015 to 2019P)  \\\n",
+       "                                                                                                                     Unnamed: 3_level_1   \n",
+       "(Registration Week, Unnamed: 0_level_1)                                                                                                   \n",
+       "49                                                                                   322.0                                                \n",
+       "50                                                                                   322.0                                                \n",
+       "51                                                                                   344.0                                                \n",
+       "52                                                                                   281.0                                                \n",
+       "53                                                                                   280.0                                                \n",
+       "\n",
+       "                                                              Range  \\\n",
+       "                                        Minimum in Previous 5 years   \n",
+       "(Registration Week, Unnamed: 0_level_1)                               \n",
+       "49                                                              279   \n",
+       "50                                                              294   \n",
+       "51                                                              317   \n",
+       "52                                                              194   \n",
+       "53                                                              199   \n",
+       "\n",
+       "                                                 Unnamed: 5_level_0  \\\n",
+       "                                        Maximum in Previous 5 years   \n",
+       "(Registration Week, Unnamed: 0_level_1)                               \n",
+       "49                                                              355   \n",
+       "50                                                              353   \n",
+       "51                                                              372   \n",
+       "52                                                              360   \n",
+       "53                                                              365   \n",
+       "\n",
+       "                                        Respiratory2 deaths registered in week (2020P)  \\\n",
+       "                                                                    Unnamed: 6_level_1   \n",
+       "(Registration Week, Unnamed: 0_level_1)                                                  \n",
+       "49                                                                                   -   \n",
+       "50                                                                                   -   \n",
+       "51                                                                                   -   \n",
+       "52                                                                                   -   \n",
+       "53                                                                                   -   \n",
+       "\n",
+       "                                        Average number of respiratory2 deaths registered in corresponding week over previous 5 years (2015 to 2019P)  \\\n",
+       "                                                                                                                                  Unnamed: 7_level_1   \n",
+       "(Registration Week, Unnamed: 0_level_1)                                                                                                                \n",
+       "49                                                                                       -                                                             \n",
+       "50                                                                                       -                                                             \n",
+       "51                                                                                       -                                                             \n",
+       "52                                                                                       -                                                             \n",
+       "53                                                                                       -                                                             \n",
+       "\n",
+       "                                        Covid-193 deaths registered in week (2020P)  \\\n",
+       "                                                                 Unnamed: 8_level_1   \n",
+       "(Registration Week, Unnamed: 0_level_1)                                               \n",
+       "49                                                                                -   \n",
+       "50                                                                                -   \n",
+       "51                                                                                -   \n",
+       "52                                                                                -   \n",
+       "53                                                                                -   \n",
+       "\n",
+       "                                        Unnamed: 9_level_0  \\\n",
+       "                                        Unnamed: 9_level_1   \n",
+       "(Registration Week, Unnamed: 0_level_1)                      \n",
+       "49                                                   155.0   \n",
+       "50                                                   138.0   \n",
+       "51                                                   140.0   \n",
+       "52                                                   132.0   \n",
+       "53                                                   146.0   \n",
+       "\n",
+       "                                        Unnamed: 10_level_0  \\\n",
+       "                                        Unnamed: 10_level_1   \n",
+       "(Registration Week, Unnamed: 0_level_1)                       \n",
+       "49                                                     87.0   \n",
+       "50                                                     93.0   \n",
+       "51                                                    102.0   \n",
+       "52                                                     92.0   \n",
+       "53                                                     97.0   \n",
+       "\n",
+       "                                        Unnamed: 11_level_0  \\\n",
+       "                                        Unnamed: 11_level_1   \n",
+       "(Registration Week, Unnamed: 0_level_1)                       \n",
+       "49                                                        -   \n",
+       "50                                                        -   \n",
+       "51                                                        -   \n",
+       "52                                                        -   \n",
+       "53                                                        -   \n",
+       "\n",
+       "                                        Unnamed: 12_level_0  \n",
+       "                                        Unnamed: 12_level_1  \n",
+       "(Registration Week, Unnamed: 0_level_1)                      \n",
+       "49                                                     98.0  \n",
+       "50                                                     87.0  \n",
+       "51                                                     82.0  \n",
+       "52                                                     88.0  \n",
+       "53                                                     94.0  "
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data_2020_i.set_index(raw_data_2020_i.columns[0], inplace=True)\n",
+    "raw_data_2020_i.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(2021, 3, 3)"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "datetime.datetime.now().isocalendar()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "datetime.datetime(2021, 1, 18, 0, 0)"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "datetime.datetime.fromisocalendar(2021, 3, 1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {
+    "Collapsed": "false",
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "raw_data_s = pd.read_csv('uk-deaths-data/weekly-deaths-scotland.csv', \n",
+    "                      index_col=0,\n",
+    "                      header=0,\n",
+    "                        skiprows=2\n",
+    "                           )\n",
+    "# raw_data_s"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "Collapsed": "false",
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>total_2020</th>\n",
+       "      <th>total_2019</th>\n",
+       "      <th>total_2018</th>\n",
+       "      <th>total_2017</th>\n",
+       "      <th>total_2016</th>\n",
+       "      <th>total_2015</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1161</td>\n",
+       "      <td>1104.0</td>\n",
+       "      <td>1531.0</td>\n",
+       "      <td>1205.0</td>\n",
+       "      <td>1394.0</td>\n",
+       "      <td>1146</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1567</td>\n",
+       "      <td>1507.0</td>\n",
+       "      <td>1899.0</td>\n",
+       "      <td>1379.0</td>\n",
+       "      <td>1305.0</td>\n",
+       "      <td>1708</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1322</td>\n",
+       "      <td>1353.0</td>\n",
+       "      <td>1629.0</td>\n",
+       "      <td>1224.0</td>\n",
+       "      <td>1215.0</td>\n",
+       "      <td>1489</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1226</td>\n",
+       "      <td>1208.0</td>\n",
+       "      <td>1610.0</td>\n",
+       "      <td>1197.0</td>\n",
+       "      <td>1187.0</td>\n",
+       "      <td>1381</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>1188</td>\n",
+       "      <td>1206.0</td>\n",
+       "      <td>1369.0</td>\n",
+       "      <td>1332.0</td>\n",
+       "      <td>1205.0</td>\n",
+       "      <td>1286</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>1216</td>\n",
+       "      <td>1243.0</td>\n",
+       "      <td>1265.0</td>\n",
+       "      <td>1200.0</td>\n",
+       "      <td>1217.0</td>\n",
+       "      <td>1344</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>1162</td>\n",
+       "      <td>1181.0</td>\n",
+       "      <td>1315.0</td>\n",
+       "      <td>1231.0</td>\n",
+       "      <td>1209.0</td>\n",
+       "      <td>1360</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>1162</td>\n",
+       "      <td>1245.0</td>\n",
+       "      <td>1245.0</td>\n",
+       "      <td>1185.0</td>\n",
+       "      <td>1239.0</td>\n",
+       "      <td>1320</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>1171</td>\n",
+       "      <td>1125.0</td>\n",
+       "      <td>1022.0</td>\n",
+       "      <td>1219.0</td>\n",
+       "      <td>1150.0</td>\n",
+       "      <td>1308</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>1208</td>\n",
+       "      <td>1156.0</td>\n",
+       "      <td>1475.0</td>\n",
+       "      <td>1146.0</td>\n",
+       "      <td>1174.0</td>\n",
+       "      <td>1192</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>1156</td>\n",
+       "      <td>1108.0</td>\n",
+       "      <td>1220.0</td>\n",
+       "      <td>1141.0</td>\n",
+       "      <td>1175.0</td>\n",
+       "      <td>1201</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>1196</td>\n",
+       "      <td>1101.0</td>\n",
+       "      <td>1158.0</td>\n",
+       "      <td>1152.0</td>\n",
+       "      <td>1042.0</td>\n",
+       "      <td>1149</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>1079</td>\n",
+       "      <td>1086.0</td>\n",
+       "      <td>1050.0</td>\n",
+       "      <td>1112.0</td>\n",
+       "      <td>1172.0</td>\n",
+       "      <td>1171</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>1744</td>\n",
+       "      <td>1032.0</td>\n",
+       "      <td>1192.0</td>\n",
+       "      <td>1060.0</td>\n",
+       "      <td>1166.0</td>\n",
+       "      <td>1042</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>1978</td>\n",
+       "      <td>1069.0</td>\n",
+       "      <td>1192.0</td>\n",
+       "      <td>998.0</td>\n",
+       "      <td>1048.0</td>\n",
+       "      <td>1192</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>1916</td>\n",
+       "      <td>902.0</td>\n",
+       "      <td>1136.0</td>\n",
+       "      <td>1111.0</td>\n",
+       "      <td>1092.0</td>\n",
+       "      <td>1095</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>1836</td>\n",
+       "      <td>1121.0</td>\n",
+       "      <td>1008.0</td>\n",
+       "      <td>1121.0</td>\n",
+       "      <td>1076.0</td>\n",
+       "      <td>1108</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>1679</td>\n",
+       "      <td>1131.0</td>\n",
+       "      <td>1093.0</td>\n",
+       "      <td>1050.0</td>\n",
+       "      <td>1006.0</td>\n",
+       "      <td>1117</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>1435</td>\n",
+       "      <td>1018.0</td>\n",
+       "      <td>967.0</td>\n",
+       "      <td>1119.0</td>\n",
+       "      <td>1047.0</td>\n",
+       "      <td>1020</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>1421</td>\n",
+       "      <td>1115.0</td>\n",
+       "      <td>977.0</td>\n",
+       "      <td>1115.0</td>\n",
+       "      <td>1010.0</td>\n",
+       "      <td>1103</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>1226</td>\n",
+       "      <td>1061.0</td>\n",
+       "      <td>1070.0</td>\n",
+       "      <td>1063.0</td>\n",
+       "      <td>994.0</td>\n",
+       "      <td>1039</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>1125</td>\n",
+       "      <td>1029.0</td>\n",
+       "      <td>998.0</td>\n",
+       "      <td>1015.0</td>\n",
+       "      <td>999.0</td>\n",
+       "      <td>1043</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>1093</td>\n",
+       "      <td>1042.0</td>\n",
+       "      <td>1033.0</td>\n",
+       "      <td>1076.0</td>\n",
+       "      <td>1023.0</td>\n",
+       "      <td>1106</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>1034</td>\n",
+       "      <td>1028.0</td>\n",
+       "      <td>915.0</td>\n",
+       "      <td>1031.0</td>\n",
+       "      <td>988.0</td>\n",
+       "      <td>1038</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>1065</td>\n",
+       "      <td>1053.0</td>\n",
+       "      <td>993.0</td>\n",
+       "      <td>1032.0</td>\n",
+       "      <td>994.0</td>\n",
+       "      <td>1025</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>1008</td>\n",
+       "      <td>1051.0</td>\n",
+       "      <td>1046.0</td>\n",
+       "      <td>994.0</td>\n",
+       "      <td>1007.0</td>\n",
+       "      <td>1032</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>983</td>\n",
+       "      <td>981.0</td>\n",
+       "      <td>1041.0</td>\n",
+       "      <td>1040.0</td>\n",
+       "      <td>988.0</td>\n",
+       "      <td>1040</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>976</td>\n",
+       "      <td>1077.0</td>\n",
+       "      <td>1002.0</td>\n",
+       "      <td>1014.0</td>\n",
+       "      <td>1022.0</td>\n",
+       "      <td>1011</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>1033</td>\n",
+       "      <td>964.0</td>\n",
+       "      <td>928.0</td>\n",
+       "      <td>1025.0</td>\n",
+       "      <td>1041.0</td>\n",
+       "      <td>1023</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>961</td>\n",
+       "      <td>1041.0</td>\n",
+       "      <td>933.0</td>\n",
+       "      <td>978.0</td>\n",
+       "      <td>979.0</td>\n",
+       "      <td>956</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>1043</td>\n",
+       "      <td>1020.0</td>\n",
+       "      <td>969.0</td>\n",
+       "      <td>1011.0</td>\n",
+       "      <td>987.0</td>\n",
+       "      <td>985</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>1011</td>\n",
+       "      <td>1018.0</td>\n",
+       "      <td>953.0</td>\n",
+       "      <td>1002.0</td>\n",
+       "      <td>997.0</td>\n",
+       "      <td>1043</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>922</td>\n",
+       "      <td>1028.0</td>\n",
+       "      <td>978.0</td>\n",
+       "      <td>1004.0</td>\n",
+       "      <td>982.0</td>\n",
+       "      <td>969</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>1046</td>\n",
+       "      <td>1011.0</td>\n",
+       "      <td>941.0</td>\n",
+       "      <td>1045.0</td>\n",
+       "      <td>1017.0</td>\n",
+       "      <td>982</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>1029</td>\n",
+       "      <td>1013.0</td>\n",
+       "      <td>930.0</td>\n",
+       "      <td>980.0</td>\n",
+       "      <td>1039.0</td>\n",
+       "      <td>954</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>1050</td>\n",
+       "      <td>980.0</td>\n",
+       "      <td>970.0</td>\n",
+       "      <td>1006.0</td>\n",
+       "      <td>1007.0</td>\n",
+       "      <td>977</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>1069</td>\n",
+       "      <td>1074.0</td>\n",
+       "      <td>1020.0</td>\n",
+       "      <td>972.0</td>\n",
+       "      <td>983.0</td>\n",
+       "      <td>991</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>952</td>\n",
+       "      <td>1071.0</td>\n",
+       "      <td>946.0</td>\n",
+       "      <td>1049.0</td>\n",
+       "      <td>966.0</td>\n",
+       "      <td>1001</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>933</td>\n",
+       "      <td>1142.0</td>\n",
+       "      <td>1015.0</td>\n",
+       "      <td>1056.0</td>\n",
+       "      <td>1009.0</td>\n",
+       "      <td>1010</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>1195</td>\n",
+       "      <td>1051.0</td>\n",
+       "      <td>1042.0</td>\n",
+       "      <td>1016.0</td>\n",
+       "      <td>1072.0</td>\n",
+       "      <td>1008</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>1071</td>\n",
+       "      <td>1143.0</td>\n",
+       "      <td>1081.0</td>\n",
+       "      <td>1133.0</td>\n",
+       "      <td>1009.0</td>\n",
+       "      <td>1028</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>1131</td>\n",
+       "      <td>1153.0</td>\n",
+       "      <td>1031.0</td>\n",
+       "      <td>1067.0</td>\n",
+       "      <td>1070.0</td>\n",
+       "      <td>989</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>1187</td>\n",
+       "      <td>1115.0</td>\n",
+       "      <td>1019.0</td>\n",
+       "      <td>1095.0</td>\n",
+       "      <td>1052.0</td>\n",
+       "      <td>981</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>1262</td>\n",
+       "      <td>1101.0</td>\n",
+       "      <td>1085.0</td>\n",
+       "      <td>1062.0</td>\n",
+       "      <td>1032.0</td>\n",
+       "      <td>1116</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>1250</td>\n",
+       "      <td>1184.0</td>\n",
+       "      <td>1144.0</td>\n",
+       "      <td>1126.0</td>\n",
+       "      <td>1043.0</td>\n",
+       "      <td>1028</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>1138</td>\n",
+       "      <td>1160.0</td>\n",
+       "      <td>1084.0</td>\n",
+       "      <td>1175.0</td>\n",
+       "      <td>1174.0</td>\n",
+       "      <td>1103</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>1360</td>\n",
+       "      <td>1229.0</td>\n",
+       "      <td>1058.0</td>\n",
+       "      <td>1178.0</td>\n",
+       "      <td>1132.0</td>\n",
+       "      <td>1054</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>1328</td>\n",
+       "      <td>1163.0</td>\n",
+       "      <td>1062.0</td>\n",
+       "      <td>1153.0</td>\n",
+       "      <td>1159.0</td>\n",
+       "      <td>1115</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>1296</td>\n",
+       "      <td>1108.0</td>\n",
+       "      <td>1076.0</td>\n",
+       "      <td>1237.0</td>\n",
+       "      <td>1188.0</td>\n",
+       "      <td>1089</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>1284</td>\n",
+       "      <td>1312.0</td>\n",
+       "      <td>1212.0</td>\n",
+       "      <td>1335.0</td>\n",
+       "      <td>1219.0</td>\n",
+       "      <td>1101</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>1297</td>\n",
+       "      <td>1277.0</td>\n",
+       "      <td>1216.0</td>\n",
+       "      <td>1437.0</td>\n",
+       "      <td>1284.0</td>\n",
+       "      <td>1146</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>1205</td>\n",
+       "      <td>1000.0</td>\n",
+       "      <td>1058.0</td>\n",
+       "      <td>1168.0</td>\n",
+       "      <td>1133.0</td>\n",
+       "      <td>944</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>1178</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1018</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    total_2020  total_2019  total_2018  total_2017  total_2016  total_2015\n",
+       "1         1161      1104.0      1531.0      1205.0      1394.0        1146\n",
+       "2         1567      1507.0      1899.0      1379.0      1305.0        1708\n",
+       "3         1322      1353.0      1629.0      1224.0      1215.0        1489\n",
+       "4         1226      1208.0      1610.0      1197.0      1187.0        1381\n",
+       "5         1188      1206.0      1369.0      1332.0      1205.0        1286\n",
+       "6         1216      1243.0      1265.0      1200.0      1217.0        1344\n",
+       "7         1162      1181.0      1315.0      1231.0      1209.0        1360\n",
+       "8         1162      1245.0      1245.0      1185.0      1239.0        1320\n",
+       "9         1171      1125.0      1022.0      1219.0      1150.0        1308\n",
+       "10        1208      1156.0      1475.0      1146.0      1174.0        1192\n",
+       "11        1156      1108.0      1220.0      1141.0      1175.0        1201\n",
+       "12        1196      1101.0      1158.0      1152.0      1042.0        1149\n",
+       "13        1079      1086.0      1050.0      1112.0      1172.0        1171\n",
+       "14        1744      1032.0      1192.0      1060.0      1166.0        1042\n",
+       "15        1978      1069.0      1192.0       998.0      1048.0        1192\n",
+       "16        1916       902.0      1136.0      1111.0      1092.0        1095\n",
+       "17        1836      1121.0      1008.0      1121.0      1076.0        1108\n",
+       "18        1679      1131.0      1093.0      1050.0      1006.0        1117\n",
+       "19        1435      1018.0       967.0      1119.0      1047.0        1020\n",
+       "20        1421      1115.0       977.0      1115.0      1010.0        1103\n",
+       "21        1226      1061.0      1070.0      1063.0       994.0        1039\n",
+       "22        1125      1029.0       998.0      1015.0       999.0        1043\n",
+       "23        1093      1042.0      1033.0      1076.0      1023.0        1106\n",
+       "24        1034      1028.0       915.0      1031.0       988.0        1038\n",
+       "25        1065      1053.0       993.0      1032.0       994.0        1025\n",
+       "26        1008      1051.0      1046.0       994.0      1007.0        1032\n",
+       "27         983       981.0      1041.0      1040.0       988.0        1040\n",
+       "28         976      1077.0      1002.0      1014.0      1022.0        1011\n",
+       "29        1033       964.0       928.0      1025.0      1041.0        1023\n",
+       "30         961      1041.0       933.0       978.0       979.0         956\n",
+       "31        1043      1020.0       969.0      1011.0       987.0         985\n",
+       "32        1011      1018.0       953.0      1002.0       997.0        1043\n",
+       "33         922      1028.0       978.0      1004.0       982.0         969\n",
+       "34        1046      1011.0       941.0      1045.0      1017.0         982\n",
+       "35        1029      1013.0       930.0       980.0      1039.0         954\n",
+       "36        1050       980.0       970.0      1006.0      1007.0         977\n",
+       "37        1069      1074.0      1020.0       972.0       983.0         991\n",
+       "38         952      1071.0       946.0      1049.0       966.0        1001\n",
+       "39         933      1142.0      1015.0      1056.0      1009.0        1010\n",
+       "40        1195      1051.0      1042.0      1016.0      1072.0        1008\n",
+       "41        1071      1143.0      1081.0      1133.0      1009.0        1028\n",
+       "42        1131      1153.0      1031.0      1067.0      1070.0         989\n",
+       "43        1187      1115.0      1019.0      1095.0      1052.0         981\n",
+       "44        1262      1101.0      1085.0      1062.0      1032.0        1116\n",
+       "45        1250      1184.0      1144.0      1126.0      1043.0        1028\n",
+       "46        1138      1160.0      1084.0      1175.0      1174.0        1103\n",
+       "47        1360      1229.0      1058.0      1178.0      1132.0        1054\n",
+       "48        1328      1163.0      1062.0      1153.0      1159.0        1115\n",
+       "49        1296      1108.0      1076.0      1237.0      1188.0        1089\n",
+       "50        1284      1312.0      1212.0      1335.0      1219.0        1101\n",
+       "51        1297      1277.0      1216.0      1437.0      1284.0        1146\n",
+       "52        1205      1000.0      1058.0      1168.0      1133.0         944\n",
+       "53        1178         NaN         NaN         NaN         NaN        1018"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_headlines_s = raw_data_s[reversed('2015 2016 2017 2018 2019 2020'.split())]\n",
+    "deaths_headlines_s.columns = ['total_' + c for c in deaths_headlines_s.columns]\n",
+    "deaths_headlines_s.reset_index(drop=True, inplace=True)\n",
+    "deaths_headlines_s.index = deaths_headlines_s.index + 1\n",
+    "deaths_headlines_s"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "5 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>week</th>\n",
+       "            <th>year</th>\n",
+       "            <th>date_up_to</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>deaths</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>1</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-01-02</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>319</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-01-09</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>373</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>3</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-01-16</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>383</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>4</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-01-23</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>397</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>5</td>\n",
+       "            <td>2015</td>\n",
+       "            <td>2015-01-30</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>374</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(1, 2015, datetime.date(2015, 1, 2), 'Northern Ireland', 319),\n",
+       " (2, 2015, datetime.date(2015, 1, 9), 'Northern Ireland', 373),\n",
+       " (3, 2015, datetime.date(2015, 1, 16), 'Northern Ireland', 383),\n",
+       " (4, 2015, datetime.date(2015, 1, 23), 'Northern Ireland', 397),\n",
+       " (5, 2015, datetime.date(2015, 1, 30), 'Northern Ireland', 374)]"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select * from all_causes_deaths limit 5"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "Collapsed": "false",
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n"
+     ]
+    }
+   ],
+   "source": [
+    "for year, ser in deaths_headlines_s.items():\n",
+    "    year_i = int(year[-4:])\n",
+    "#     print(year_i)\n",
+    "    for week, deaths in ser.dropna().iteritems():\n",
+    "#         print(datetime.date.fromisocalendar(year_i, week, 7), deaths)\n",
+    "        dut = datetime.date.fromisocalendar(year_i, week, 7)\n",
+    "        %sql insert into all_causes_deaths(week, year, date_up_to, nation, deaths) values ({week}, {year_i}, :dut, 'Scotland', {deaths})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "12 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2015, 'Northern Ireland', 53),\n",
+       " (2016, 'Northern Ireland', 52),\n",
+       " (2017, 'Northern Ireland', 52),\n",
+       " (2018, 'Northern Ireland', 52),\n",
+       " (2019, 'Northern Ireland', 52),\n",
+       " (2020, 'Northern Ireland', 53),\n",
+       " (2015, 'Scotland', 53),\n",
+       " (2016, 'Scotland', 52),\n",
+       " (2017, 'Scotland', 52),\n",
+       " (2018, 'Scotland', 52),\n",
+       " (2019, 'Scotland', 52),\n",
+       " (2020, 'Scotland', 53)]"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "12 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>date_up_to</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>2015-01-16</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>2015-01-18</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>2016-01-22</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>2016-01-24</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>2017-01-20</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>2017-01-22</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>2018-01-19</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>2018-01-21</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>2019-01-18</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>2019-01-20</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>2020-01-17</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>2020-01-19</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2015, 'Northern Ireland', datetime.date(2015, 1, 16)),\n",
+       " (2015, 'Scotland', datetime.date(2015, 1, 18)),\n",
+       " (2016, 'Northern Ireland', datetime.date(2016, 1, 22)),\n",
+       " (2016, 'Scotland', datetime.date(2016, 1, 24)),\n",
+       " (2017, 'Northern Ireland', datetime.date(2017, 1, 20)),\n",
+       " (2017, 'Scotland', datetime.date(2017, 1, 22)),\n",
+       " (2018, 'Northern Ireland', datetime.date(2018, 1, 19)),\n",
+       " (2018, 'Scotland', datetime.date(2018, 1, 21)),\n",
+       " (2019, 'Northern Ireland', datetime.date(2019, 1, 18)),\n",
+       " (2019, 'Scotland', datetime.date(2019, 1, 20)),\n",
+       " (2020, 'Northern Ireland', datetime.date(2020, 1, 17)),\n",
+       " (2020, 'Scotland', datetime.date(2020, 1, 19))]"
+      ]
+     },
+     "execution_count": 42,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select year, nation, date_up_to from all_causes_deaths where week=3 order by year, nation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {
+    "Collapsed": "false",
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>...</th>\n",
+       "      <th>North East</th>\n",
+       "      <th>North West</th>\n",
+       "      <th>Yorkshire and The Humber</th>\n",
+       "      <th>East Midlands</th>\n",
+       "      <th>West Midlands</th>\n",
+       "      <th>East</th>\n",
+       "      <th>London</th>\n",
+       "      <th>South East</th>\n",
+       "      <th>South West</th>\n",
+       "      <th>Wales</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Week number</th>\n",
+       "      <td>Week ended</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Total deaths, all ages</td>\n",
+       "      <td>Total deaths: average of corresponding</td>\n",
+       "      <td>week over the previous 5 years 1, 10, 11 (Engl...</td>\n",
+       "      <td>Total deaths: average of corresponding</td>\n",
+       "      <td>week over the previous 5 years 1, 10, 11 (Engl...</td>\n",
+       "      <td>Total deaths: average of corresponding</td>\n",
+       "      <td>week over the previous 5 years 1, 10, 11 (Wales)</td>\n",
+       "      <td>...</td>\n",
+       "      <td>E12000001</td>\n",
+       "      <td>E12000002</td>\n",
+       "      <td>E12000003</td>\n",
+       "      <td>E12000004</td>\n",
+       "      <td>E12000005</td>\n",
+       "      <td>E12000006</td>\n",
+       "      <td>E12000007</td>\n",
+       "      <td>E12000008</td>\n",
+       "      <td>E12000009</td>\n",
+       "      <td>W92000004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2020-01-03 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12254</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12175</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11412</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>756</td>\n",
+       "      <td>...</td>\n",
+       "      <td>673</td>\n",
+       "      <td>1806</td>\n",
+       "      <td>1240</td>\n",
+       "      <td>1060</td>\n",
+       "      <td>1349</td>\n",
+       "      <td>1162</td>\n",
+       "      <td>1113</td>\n",
+       "      <td>1814</td>\n",
+       "      <td>1225</td>\n",
+       "      <td>787</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2020-01-10 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14058</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13822</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12933</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>856</td>\n",
+       "      <td>...</td>\n",
+       "      <td>707</td>\n",
+       "      <td>1932</td>\n",
+       "      <td>1339</td>\n",
+       "      <td>1195</td>\n",
+       "      <td>1450</td>\n",
+       "      <td>1573</td>\n",
+       "      <td>1272</td>\n",
+       "      <td>2132</td>\n",
+       "      <td>1487</td>\n",
+       "      <td>939</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2020-01-17 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12990</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13216</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12370</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>812</td>\n",
+       "      <td>...</td>\n",
+       "      <td>647</td>\n",
+       "      <td>1696</td>\n",
+       "      <td>1278</td>\n",
+       "      <td>1106</td>\n",
+       "      <td>1407</td>\n",
+       "      <td>1457</td>\n",
+       "      <td>1073</td>\n",
+       "      <td>2064</td>\n",
+       "      <td>1466</td>\n",
+       "      <td>767</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2020-01-24 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11856</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12760</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11933</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>802</td>\n",
+       "      <td>...</td>\n",
+       "      <td>612</td>\n",
+       "      <td>1529</td>\n",
+       "      <td>1187</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>1231</td>\n",
+       "      <td>1410</td>\n",
+       "      <td>1028</td>\n",
+       "      <td>1833</td>\n",
+       "      <td>1253</td>\n",
+       "      <td>723</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2020-01-31 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11612</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12206</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11419</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>760</td>\n",
+       "      <td>...</td>\n",
+       "      <td>561</td>\n",
+       "      <td>1461</td>\n",
+       "      <td>1136</td>\n",
+       "      <td>1015</td>\n",
+       "      <td>1262</td>\n",
+       "      <td>1286</td>\n",
+       "      <td>1092</td>\n",
+       "      <td>1820</td>\n",
+       "      <td>1233</td>\n",
+       "      <td>727</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2020-02-07 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10986</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11925</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11154</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>729</td>\n",
+       "      <td>...</td>\n",
+       "      <td>564</td>\n",
+       "      <td>1529</td>\n",
+       "      <td>1072</td>\n",
+       "      <td>922</td>\n",
+       "      <td>1052</td>\n",
+       "      <td>1259</td>\n",
+       "      <td>987</td>\n",
+       "      <td>1729</td>\n",
+       "      <td>1157</td>\n",
+       "      <td>690</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2020-02-14 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10944</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11627</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10876</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>722</td>\n",
+       "      <td>...</td>\n",
+       "      <td>573</td>\n",
+       "      <td>1427</td>\n",
+       "      <td>1059</td>\n",
+       "      <td>976</td>\n",
+       "      <td>1159</td>\n",
+       "      <td>1172</td>\n",
+       "      <td>967</td>\n",
+       "      <td>1688</td>\n",
+       "      <td>1169</td>\n",
+       "      <td>728</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2020-02-21 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10841</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11548</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10790</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>724</td>\n",
+       "      <td>...</td>\n",
+       "      <td>539</td>\n",
+       "      <td>1477</td>\n",
+       "      <td>1087</td>\n",
+       "      <td>924</td>\n",
+       "      <td>1116</td>\n",
+       "      <td>1167</td>\n",
+       "      <td>1032</td>\n",
+       "      <td>1675</td>\n",
+       "      <td>1118</td>\n",
+       "      <td>679</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2020-02-28 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10816</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11183</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10448</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>698</td>\n",
+       "      <td>...</td>\n",
+       "      <td>572</td>\n",
+       "      <td>1476</td>\n",
+       "      <td>1078</td>\n",
+       "      <td>919</td>\n",
+       "      <td>1174</td>\n",
+       "      <td>1115</td>\n",
+       "      <td>1085</td>\n",
+       "      <td>1587</td>\n",
+       "      <td>1133</td>\n",
+       "      <td>651</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>2020-03-06 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10895</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11498</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10745</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>720</td>\n",
+       "      <td>...</td>\n",
+       "      <td>568</td>\n",
+       "      <td>1490</td>\n",
+       "      <td>1112</td>\n",
+       "      <td>930</td>\n",
+       "      <td>1098</td>\n",
+       "      <td>1149</td>\n",
+       "      <td>982</td>\n",
+       "      <td>1726</td>\n",
+       "      <td>1170</td>\n",
+       "      <td>652</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>2020-03-13 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11019</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11205</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10447</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>727</td>\n",
+       "      <td>...</td>\n",
+       "      <td>590</td>\n",
+       "      <td>1472</td>\n",
+       "      <td>1053</td>\n",
+       "      <td>915</td>\n",
+       "      <td>1187</td>\n",
+       "      <td>1211</td>\n",
+       "      <td>964</td>\n",
+       "      <td>1751</td>\n",
+       "      <td>1174</td>\n",
+       "      <td>675</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>2020-03-20 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10645</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10573</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9841</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>677</td>\n",
+       "      <td>...</td>\n",
+       "      <td>522</td>\n",
+       "      <td>1443</td>\n",
+       "      <td>1012</td>\n",
+       "      <td>947</td>\n",
+       "      <td>1115</td>\n",
+       "      <td>1043</td>\n",
+       "      <td>1008</td>\n",
+       "      <td>1657</td>\n",
+       "      <td>1156</td>\n",
+       "      <td>719</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>2020-03-27 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11141</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10130</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9414</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>665</td>\n",
+       "      <td>...</td>\n",
+       "      <td>542</td>\n",
+       "      <td>1538</td>\n",
+       "      <td>982</td>\n",
+       "      <td>922</td>\n",
+       "      <td>1035</td>\n",
+       "      <td>1182</td>\n",
+       "      <td>1297</td>\n",
+       "      <td>1822</td>\n",
+       "      <td>1092</td>\n",
+       "      <td>719</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>2020-04-03 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>16387</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10305</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9601</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>667</td>\n",
+       "      <td>...</td>\n",
+       "      <td>770</td>\n",
+       "      <td>2137</td>\n",
+       "      <td>1436</td>\n",
+       "      <td>1246</td>\n",
+       "      <td>1812</td>\n",
+       "      <td>1717</td>\n",
+       "      <td>2511</td>\n",
+       "      <td>2294</td>\n",
+       "      <td>1520</td>\n",
+       "      <td>920</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>2020-04-10 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>18516</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10520</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9807</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>671</td>\n",
+       "      <td>...</td>\n",
+       "      <td>849</td>\n",
+       "      <td>2597</td>\n",
+       "      <td>1503</td>\n",
+       "      <td>1452</td>\n",
+       "      <td>2182</td>\n",
+       "      <td>1984</td>\n",
+       "      <td>2832</td>\n",
+       "      <td>2604</td>\n",
+       "      <td>1560</td>\n",
+       "      <td>928</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>2020-04-17 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>22351</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10497</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9787</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>661</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1155</td>\n",
+       "      <td>3195</td>\n",
+       "      <td>1960</td>\n",
+       "      <td>1632</td>\n",
+       "      <td>2536</td>\n",
+       "      <td>2466</td>\n",
+       "      <td>3275</td>\n",
+       "      <td>3084</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1169</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>2020-04-24 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>21997</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10458</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9768</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>662</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1103</td>\n",
+       "      <td>3109</td>\n",
+       "      <td>2095</td>\n",
+       "      <td>1711</td>\n",
+       "      <td>2481</td>\n",
+       "      <td>2299</td>\n",
+       "      <td>2785</td>\n",
+       "      <td>3334</td>\n",
+       "      <td>1924</td>\n",
+       "      <td>1124</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>2020-05-01 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>17953</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9941</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9289</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>624</td>\n",
+       "      <td>...</td>\n",
+       "      <td>922</td>\n",
+       "      <td>2503</td>\n",
+       "      <td>1844</td>\n",
+       "      <td>1418</td>\n",
+       "      <td>1975</td>\n",
+       "      <td>1982</td>\n",
+       "      <td>1953</td>\n",
+       "      <td>2853</td>\n",
+       "      <td>1554</td>\n",
+       "      <td>929</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>2020-05-08 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12657</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9576</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8937</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>612</td>\n",
+       "      <td>...</td>\n",
+       "      <td>769</td>\n",
+       "      <td>1790</td>\n",
+       "      <td>1328</td>\n",
+       "      <td>1094</td>\n",
+       "      <td>1326</td>\n",
+       "      <td>1321</td>\n",
+       "      <td>1213</td>\n",
+       "      <td>1887</td>\n",
+       "      <td>1218</td>\n",
+       "      <td>692</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>2020-05-15 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14573</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10188</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9526</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>635</td>\n",
+       "      <td>...</td>\n",
+       "      <td>845</td>\n",
+       "      <td>1992</td>\n",
+       "      <td>1589</td>\n",
+       "      <td>1283</td>\n",
+       "      <td>1502</td>\n",
+       "      <td>1543</td>\n",
+       "      <td>1329</td>\n",
+       "      <td>2251</td>\n",
+       "      <td>1449</td>\n",
+       "      <td>772</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>2020-05-22 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12288</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9940</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9299</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>614</td>\n",
+       "      <td>...</td>\n",
+       "      <td>718</td>\n",
+       "      <td>1636</td>\n",
+       "      <td>1236</td>\n",
+       "      <td>1041</td>\n",
+       "      <td>1319</td>\n",
+       "      <td>1397</td>\n",
+       "      <td>1125</td>\n",
+       "      <td>1937</td>\n",
+       "      <td>1177</td>\n",
+       "      <td>692</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>2020-05-29 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9824</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8171</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7607</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>546</td>\n",
+       "      <td>...</td>\n",
+       "      <td>550</td>\n",
+       "      <td>1337</td>\n",
+       "      <td>1046</td>\n",
+       "      <td>863</td>\n",
+       "      <td>970</td>\n",
+       "      <td>1095</td>\n",
+       "      <td>841</td>\n",
+       "      <td>1515</td>\n",
+       "      <td>1011</td>\n",
+       "      <td>587</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>2020-06-05 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10709</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9977</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9346</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>610</td>\n",
+       "      <td>...</td>\n",
+       "      <td>576</td>\n",
+       "      <td>1478</td>\n",
+       "      <td>1090</td>\n",
+       "      <td>931</td>\n",
+       "      <td>1172</td>\n",
+       "      <td>1131</td>\n",
+       "      <td>891</td>\n",
+       "      <td>1610</td>\n",
+       "      <td>1116</td>\n",
+       "      <td>700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>2020-06-12 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9976</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9417</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8803</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>588</td>\n",
+       "      <td>...</td>\n",
+       "      <td>478</td>\n",
+       "      <td>1374</td>\n",
+       "      <td>980</td>\n",
+       "      <td>967</td>\n",
+       "      <td>1096</td>\n",
+       "      <td>1048</td>\n",
+       "      <td>883</td>\n",
+       "      <td>1530</td>\n",
+       "      <td>1035</td>\n",
+       "      <td>574</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>2020-06-19 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9339</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9404</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8810</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>573</td>\n",
+       "      <td>...</td>\n",
+       "      <td>498</td>\n",
+       "      <td>1234</td>\n",
+       "      <td>952</td>\n",
+       "      <td>835</td>\n",
+       "      <td>973</td>\n",
+       "      <td>927</td>\n",
+       "      <td>896</td>\n",
+       "      <td>1411</td>\n",
+       "      <td>990</td>\n",
+       "      <td>617</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>2020-06-26 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8979</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9293</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8695</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>571</td>\n",
+       "      <td>...</td>\n",
+       "      <td>485</td>\n",
+       "      <td>1300</td>\n",
+       "      <td>922</td>\n",
+       "      <td>800</td>\n",
+       "      <td>946</td>\n",
+       "      <td>880</td>\n",
+       "      <td>791</td>\n",
+       "      <td>1311</td>\n",
+       "      <td>979</td>\n",
+       "      <td>552</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>2020-07-03 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9140</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9183</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8606</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>555</td>\n",
+       "      <td>...</td>\n",
+       "      <td>515</td>\n",
+       "      <td>1225</td>\n",
+       "      <td>875</td>\n",
+       "      <td>827</td>\n",
+       "      <td>949</td>\n",
+       "      <td>922</td>\n",
+       "      <td>837</td>\n",
+       "      <td>1454</td>\n",
+       "      <td>938</td>\n",
+       "      <td>584</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>2020-07-10 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8690</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9250</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8648</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>578</td>\n",
+       "      <td>...</td>\n",
+       "      <td>468</td>\n",
+       "      <td>1154</td>\n",
+       "      <td>848</td>\n",
+       "      <td>771</td>\n",
+       "      <td>902</td>\n",
+       "      <td>999</td>\n",
+       "      <td>803</td>\n",
+       "      <td>1228</td>\n",
+       "      <td>930</td>\n",
+       "      <td>572</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>2020-07-17 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8823</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9093</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8502</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>557</td>\n",
+       "      <td>...</td>\n",
+       "      <td>445</td>\n",
+       "      <td>1159</td>\n",
+       "      <td>843</td>\n",
+       "      <td>816</td>\n",
+       "      <td>956</td>\n",
+       "      <td>945</td>\n",
+       "      <td>806</td>\n",
+       "      <td>1339</td>\n",
+       "      <td>953</td>\n",
+       "      <td>550</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>2020-07-24 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8891</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9052</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8452</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>566</td>\n",
+       "      <td>...</td>\n",
+       "      <td>493</td>\n",
+       "      <td>1197</td>\n",
+       "      <td>817</td>\n",
+       "      <td>798</td>\n",
+       "      <td>964</td>\n",
+       "      <td>951</td>\n",
+       "      <td>816</td>\n",
+       "      <td>1340</td>\n",
+       "      <td>941</td>\n",
+       "      <td>565</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>2020-07-31 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8946</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9036</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8436</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>572</td>\n",
+       "      <td>...</td>\n",
+       "      <td>507</td>\n",
+       "      <td>1272</td>\n",
+       "      <td>837</td>\n",
+       "      <td>729</td>\n",
+       "      <td>902</td>\n",
+       "      <td>949</td>\n",
+       "      <td>773</td>\n",
+       "      <td>1447</td>\n",
+       "      <td>988</td>\n",
+       "      <td>531</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>2020-08-07 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8945</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9102</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8502</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>571</td>\n",
+       "      <td>...</td>\n",
+       "      <td>486</td>\n",
+       "      <td>1211</td>\n",
+       "      <td>851</td>\n",
+       "      <td>798</td>\n",
+       "      <td>933</td>\n",
+       "      <td>955</td>\n",
+       "      <td>832</td>\n",
+       "      <td>1370</td>\n",
+       "      <td>929</td>\n",
+       "      <td>563</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>2020-08-14 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9392</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9085</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8494</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>564</td>\n",
+       "      <td>...</td>\n",
+       "      <td>520</td>\n",
+       "      <td>1304</td>\n",
+       "      <td>853</td>\n",
+       "      <td>829</td>\n",
+       "      <td>923</td>\n",
+       "      <td>1006</td>\n",
+       "      <td>928</td>\n",
+       "      <td>1395</td>\n",
+       "      <td>1009</td>\n",
+       "      <td>617</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>2020-08-21 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9631</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9157</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8560</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>573</td>\n",
+       "      <td>...</td>\n",
+       "      <td>479</td>\n",
+       "      <td>1269</td>\n",
+       "      <td>870</td>\n",
+       "      <td>780</td>\n",
+       "      <td>1028</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>920</td>\n",
+       "      <td>1608</td>\n",
+       "      <td>1043</td>\n",
+       "      <td>594</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>2020-08-28 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9032</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8241</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7674</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>539</td>\n",
+       "      <td>...</td>\n",
+       "      <td>455</td>\n",
+       "      <td>1148</td>\n",
+       "      <td>922</td>\n",
+       "      <td>724</td>\n",
+       "      <td>945</td>\n",
+       "      <td>951</td>\n",
+       "      <td>810</td>\n",
+       "      <td>1511</td>\n",
+       "      <td>959</td>\n",
+       "      <td>591</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>2020-09-04 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7739</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9182</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8604</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>552</td>\n",
+       "      <td>...</td>\n",
+       "      <td>431</td>\n",
+       "      <td>1057</td>\n",
+       "      <td>780</td>\n",
+       "      <td>640</td>\n",
+       "      <td>770</td>\n",
+       "      <td>806</td>\n",
+       "      <td>737</td>\n",
+       "      <td>1208</td>\n",
+       "      <td>803</td>\n",
+       "      <td>488</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>2020-09-11 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9811</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9306</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8708</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>577</td>\n",
+       "      <td>...</td>\n",
+       "      <td>502</td>\n",
+       "      <td>1229</td>\n",
+       "      <td>952</td>\n",
+       "      <td>867</td>\n",
+       "      <td>1021</td>\n",
+       "      <td>1052</td>\n",
+       "      <td>898</td>\n",
+       "      <td>1610</td>\n",
+       "      <td>1084</td>\n",
+       "      <td>578</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>2020-09-18 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9523</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9264</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8663</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>575</td>\n",
+       "      <td>...</td>\n",
+       "      <td>465</td>\n",
+       "      <td>1287</td>\n",
+       "      <td>939</td>\n",
+       "      <td>795</td>\n",
+       "      <td>1051</td>\n",
+       "      <td>1023</td>\n",
+       "      <td>844</td>\n",
+       "      <td>1530</td>\n",
+       "      <td>1021</td>\n",
+       "      <td>555</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>2020-09-25 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9634</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9377</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8744</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>604</td>\n",
+       "      <td>...</td>\n",
+       "      <td>514</td>\n",
+       "      <td>1271</td>\n",
+       "      <td>965</td>\n",
+       "      <td>825</td>\n",
+       "      <td>1036</td>\n",
+       "      <td>963</td>\n",
+       "      <td>869</td>\n",
+       "      <td>1521</td>\n",
+       "      <td>1041</td>\n",
+       "      <td>617</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>2020-10-02 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9945</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9555</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8942</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>587</td>\n",
+       "      <td>...</td>\n",
+       "      <td>558</td>\n",
+       "      <td>1301</td>\n",
+       "      <td>978</td>\n",
+       "      <td>842</td>\n",
+       "      <td>1045</td>\n",
+       "      <td>1054</td>\n",
+       "      <td>899</td>\n",
+       "      <td>1577</td>\n",
+       "      <td>1003</td>\n",
+       "      <td>671</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>2020-10-09 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9954</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9811</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9168</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>615</td>\n",
+       "      <td>...</td>\n",
+       "      <td>544</td>\n",
+       "      <td>1367</td>\n",
+       "      <td>1067</td>\n",
+       "      <td>884</td>\n",
+       "      <td>1053</td>\n",
+       "      <td>1019</td>\n",
+       "      <td>902</td>\n",
+       "      <td>1462</td>\n",
+       "      <td>1010</td>\n",
+       "      <td>638</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>2020-10-16 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10534</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9865</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9215</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>630</td>\n",
+       "      <td>...</td>\n",
+       "      <td>606</td>\n",
+       "      <td>1553</td>\n",
+       "      <td>1001</td>\n",
+       "      <td>904</td>\n",
+       "      <td>1154</td>\n",
+       "      <td>1056</td>\n",
+       "      <td>923</td>\n",
+       "      <td>1462</td>\n",
+       "      <td>1174</td>\n",
+       "      <td>688</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>2020-10-23 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10739</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9759</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9104</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>628</td>\n",
+       "      <td>...</td>\n",
+       "      <td>600</td>\n",
+       "      <td>1714</td>\n",
+       "      <td>1111</td>\n",
+       "      <td>891</td>\n",
+       "      <td>1124</td>\n",
+       "      <td>1154</td>\n",
+       "      <td>922</td>\n",
+       "      <td>1510</td>\n",
+       "      <td>1044</td>\n",
+       "      <td>661</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>2020-10-30 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10887</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9891</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9248</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>616</td>\n",
+       "      <td>...</td>\n",
+       "      <td>591</td>\n",
+       "      <td>1754</td>\n",
+       "      <td>1168</td>\n",
+       "      <td>882</td>\n",
+       "      <td>1102</td>\n",
+       "      <td>1089</td>\n",
+       "      <td>888</td>\n",
+       "      <td>1563</td>\n",
+       "      <td>1129</td>\n",
+       "      <td>712</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>2020-11-06 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11812</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10331</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9675</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>625</td>\n",
+       "      <td>...</td>\n",
+       "      <td>675</td>\n",
+       "      <td>1900</td>\n",
+       "      <td>1294</td>\n",
+       "      <td>990</td>\n",
+       "      <td>1186</td>\n",
+       "      <td>1177</td>\n",
+       "      <td>952</td>\n",
+       "      <td>1614</td>\n",
+       "      <td>1174</td>\n",
+       "      <td>832</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>2020-11-13 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12254</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10350</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9662</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>658</td>\n",
+       "      <td>...</td>\n",
+       "      <td>711</td>\n",
+       "      <td>1950</td>\n",
+       "      <td>1350</td>\n",
+       "      <td>1099</td>\n",
+       "      <td>1317</td>\n",
+       "      <td>1172</td>\n",
+       "      <td>1112</td>\n",
+       "      <td>1616</td>\n",
+       "      <td>1168</td>\n",
+       "      <td>742</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>2020-11-20 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12535</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10380</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9701</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>653</td>\n",
+       "      <td>...</td>\n",
+       "      <td>691</td>\n",
+       "      <td>1935</td>\n",
+       "      <td>1441</td>\n",
+       "      <td>1105</td>\n",
+       "      <td>1385</td>\n",
+       "      <td>1186</td>\n",
+       "      <td>1086</td>\n",
+       "      <td>1687</td>\n",
+       "      <td>1159</td>\n",
+       "      <td>848</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>2020-11-27 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12456</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10357</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9690</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>646</td>\n",
+       "      <td>...</td>\n",
+       "      <td>679</td>\n",
+       "      <td>1791</td>\n",
+       "      <td>1501</td>\n",
+       "      <td>1218</td>\n",
+       "      <td>1358</td>\n",
+       "      <td>1159</td>\n",
+       "      <td>1012</td>\n",
+       "      <td>1655</td>\n",
+       "      <td>1272</td>\n",
+       "      <td>797</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>2020-12-04 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12303</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10695</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9995</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>679</td>\n",
+       "      <td>...</td>\n",
+       "      <td>645</td>\n",
+       "      <td>1679</td>\n",
+       "      <td>1403</td>\n",
+       "      <td>1121</td>\n",
+       "      <td>1340</td>\n",
+       "      <td>1229</td>\n",
+       "      <td>1029</td>\n",
+       "      <td>1720</td>\n",
+       "      <td>1284</td>\n",
+       "      <td>836</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>2020-12-11 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12292</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10750</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10034</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>693</td>\n",
+       "      <td>...</td>\n",
+       "      <td>661</td>\n",
+       "      <td>1691</td>\n",
+       "      <td>1326</td>\n",
+       "      <td>1199</td>\n",
+       "      <td>1432</td>\n",
+       "      <td>1224</td>\n",
+       "      <td>1065</td>\n",
+       "      <td>1706</td>\n",
+       "      <td>1156</td>\n",
+       "      <td>814</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>2020-12-18 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13011</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11548</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10804</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>718</td>\n",
+       "      <td>...</td>\n",
+       "      <td>689</td>\n",
+       "      <td>1718</td>\n",
+       "      <td>1380</td>\n",
+       "      <td>1199</td>\n",
+       "      <td>1385</td>\n",
+       "      <td>1317</td>\n",
+       "      <td>1167</td>\n",
+       "      <td>1947</td>\n",
+       "      <td>1311</td>\n",
+       "      <td>882</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>2020-12-25 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11520</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7954</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7421</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>518</td>\n",
+       "      <td>...</td>\n",
+       "      <td>669</td>\n",
+       "      <td>1463</td>\n",
+       "      <td>1130</td>\n",
+       "      <td>1097</td>\n",
+       "      <td>1217</td>\n",
+       "      <td>1198</td>\n",
+       "      <td>1090</td>\n",
+       "      <td>1701</td>\n",
+       "      <td>1115</td>\n",
+       "      <td>825</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>2021-01-01 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10069</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7954</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7421</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>518</td>\n",
+       "      <td>...</td>\n",
+       "      <td>547</td>\n",
+       "      <td>1346</td>\n",
+       "      <td>886</td>\n",
+       "      <td>842</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>997</td>\n",
+       "      <td>1159</td>\n",
+       "      <td>1595</td>\n",
+       "      <td>929</td>\n",
+       "      <td>727</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>54 rows × 91 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                             NaN  NaN  NaN                     NaN  \\\n",
+       "Week number           Week ended  NaN  NaN  Total deaths, all ages   \n",
+       "1            2020-01-03 00:00:00  NaN  NaN                   12254   \n",
+       "2            2020-01-10 00:00:00  NaN  NaN                   14058   \n",
+       "3            2020-01-17 00:00:00  NaN  NaN                   12990   \n",
+       "4            2020-01-24 00:00:00  NaN  NaN                   11856   \n",
+       "5            2020-01-31 00:00:00  NaN  NaN                   11612   \n",
+       "6            2020-02-07 00:00:00  NaN  NaN                   10986   \n",
+       "7            2020-02-14 00:00:00  NaN  NaN                   10944   \n",
+       "8            2020-02-21 00:00:00  NaN  NaN                   10841   \n",
+       "9            2020-02-28 00:00:00  NaN  NaN                   10816   \n",
+       "10           2020-03-06 00:00:00  NaN  NaN                   10895   \n",
+       "11           2020-03-13 00:00:00  NaN  NaN                   11019   \n",
+       "12           2020-03-20 00:00:00  NaN  NaN                   10645   \n",
+       "13           2020-03-27 00:00:00  NaN  NaN                   11141   \n",
+       "14           2020-04-03 00:00:00  NaN  NaN                   16387   \n",
+       "15           2020-04-10 00:00:00  NaN  NaN                   18516   \n",
+       "16           2020-04-17 00:00:00  NaN  NaN                   22351   \n",
+       "17           2020-04-24 00:00:00  NaN  NaN                   21997   \n",
+       "18           2020-05-01 00:00:00  NaN  NaN                   17953   \n",
+       "19           2020-05-08 00:00:00  NaN  NaN                   12657   \n",
+       "20           2020-05-15 00:00:00  NaN  NaN                   14573   \n",
+       "21           2020-05-22 00:00:00  NaN  NaN                   12288   \n",
+       "22           2020-05-29 00:00:00  NaN  NaN                    9824   \n",
+       "23           2020-06-05 00:00:00  NaN  NaN                   10709   \n",
+       "24           2020-06-12 00:00:00  NaN  NaN                    9976   \n",
+       "25           2020-06-19 00:00:00  NaN  NaN                    9339   \n",
+       "26           2020-06-26 00:00:00  NaN  NaN                    8979   \n",
+       "27           2020-07-03 00:00:00  NaN  NaN                    9140   \n",
+       "28           2020-07-10 00:00:00  NaN  NaN                    8690   \n",
+       "29           2020-07-17 00:00:00  NaN  NaN                    8823   \n",
+       "30           2020-07-24 00:00:00  NaN  NaN                    8891   \n",
+       "31           2020-07-31 00:00:00  NaN  NaN                    8946   \n",
+       "32           2020-08-07 00:00:00  NaN  NaN                    8945   \n",
+       "33           2020-08-14 00:00:00  NaN  NaN                    9392   \n",
+       "34           2020-08-21 00:00:00  NaN  NaN                    9631   \n",
+       "35           2020-08-28 00:00:00  NaN  NaN                    9032   \n",
+       "36           2020-09-04 00:00:00  NaN  NaN                    7739   \n",
+       "37           2020-09-11 00:00:00  NaN  NaN                    9811   \n",
+       "38           2020-09-18 00:00:00  NaN  NaN                    9523   \n",
+       "39           2020-09-25 00:00:00  NaN  NaN                    9634   \n",
+       "40           2020-10-02 00:00:00  NaN  NaN                    9945   \n",
+       "41           2020-10-09 00:00:00  NaN  NaN                    9954   \n",
+       "42           2020-10-16 00:00:00  NaN  NaN                   10534   \n",
+       "43           2020-10-23 00:00:00  NaN  NaN                   10739   \n",
+       "44           2020-10-30 00:00:00  NaN  NaN                   10887   \n",
+       "45           2020-11-06 00:00:00  NaN  NaN                   11812   \n",
+       "46           2020-11-13 00:00:00  NaN  NaN                   12254   \n",
+       "47           2020-11-20 00:00:00  NaN  NaN                   12535   \n",
+       "48           2020-11-27 00:00:00  NaN  NaN                   12456   \n",
+       "49           2020-12-04 00:00:00  NaN  NaN                   12303   \n",
+       "50           2020-12-11 00:00:00  NaN  NaN                   12292   \n",
+       "51           2020-12-18 00:00:00  NaN  NaN                   13011   \n",
+       "52           2020-12-25 00:00:00  NaN  NaN                   11520   \n",
+       "53           2021-01-01 00:00:00  NaN  NaN                   10069   \n",
+       "\n",
+       "                                                NaN  \\\n",
+       "Week number  Total deaths: average of corresponding   \n",
+       "1                                               NaN   \n",
+       "2                                               NaN   \n",
+       "3                                               NaN   \n",
+       "4                                               NaN   \n",
+       "5                                               NaN   \n",
+       "6                                               NaN   \n",
+       "7                                               NaN   \n",
+       "8                                               NaN   \n",
+       "9                                               NaN   \n",
+       "10                                              NaN   \n",
+       "11                                              NaN   \n",
+       "12                                              NaN   \n",
+       "13                                              NaN   \n",
+       "14                                              NaN   \n",
+       "15                                              NaN   \n",
+       "16                                              NaN   \n",
+       "17                                              NaN   \n",
+       "18                                              NaN   \n",
+       "19                                              NaN   \n",
+       "20                                              NaN   \n",
+       "21                                              NaN   \n",
+       "22                                              NaN   \n",
+       "23                                              NaN   \n",
+       "24                                              NaN   \n",
+       "25                                              NaN   \n",
+       "26                                              NaN   \n",
+       "27                                              NaN   \n",
+       "28                                              NaN   \n",
+       "29                                              NaN   \n",
+       "30                                              NaN   \n",
+       "31                                              NaN   \n",
+       "32                                              NaN   \n",
+       "33                                              NaN   \n",
+       "34                                              NaN   \n",
+       "35                                              NaN   \n",
+       "36                                              NaN   \n",
+       "37                                              NaN   \n",
+       "38                                              NaN   \n",
+       "39                                              NaN   \n",
+       "40                                              NaN   \n",
+       "41                                              NaN   \n",
+       "42                                              NaN   \n",
+       "43                                              NaN   \n",
+       "44                                              NaN   \n",
+       "45                                              NaN   \n",
+       "46                                              NaN   \n",
+       "47                                              NaN   \n",
+       "48                                              NaN   \n",
+       "49                                              NaN   \n",
+       "50                                              NaN   \n",
+       "51                                              NaN   \n",
+       "52                                              NaN   \n",
+       "53                                              NaN   \n",
+       "\n",
+       "                                                           NaN  \\\n",
+       "Week number  week over the previous 5 years 1, 10, 11 (Engl...   \n",
+       "1                                                        12175   \n",
+       "2                                                        13822   \n",
+       "3                                                        13216   \n",
+       "4                                                        12760   \n",
+       "5                                                        12206   \n",
+       "6                                                        11925   \n",
+       "7                                                        11627   \n",
+       "8                                                        11548   \n",
+       "9                                                        11183   \n",
+       "10                                                       11498   \n",
+       "11                                                       11205   \n",
+       "12                                                       10573   \n",
+       "13                                                       10130   \n",
+       "14                                                       10305   \n",
+       "15                                                       10520   \n",
+       "16                                                       10497   \n",
+       "17                                                       10458   \n",
+       "18                                                        9941   \n",
+       "19                                                        9576   \n",
+       "20                                                       10188   \n",
+       "21                                                        9940   \n",
+       "22                                                        8171   \n",
+       "23                                                        9977   \n",
+       "24                                                        9417   \n",
+       "25                                                        9404   \n",
+       "26                                                        9293   \n",
+       "27                                                        9183   \n",
+       "28                                                        9250   \n",
+       "29                                                        9093   \n",
+       "30                                                        9052   \n",
+       "31                                                        9036   \n",
+       "32                                                        9102   \n",
+       "33                                                        9085   \n",
+       "34                                                        9157   \n",
+       "35                                                        8241   \n",
+       "36                                                        9182   \n",
+       "37                                                        9306   \n",
+       "38                                                        9264   \n",
+       "39                                                        9377   \n",
+       "40                                                        9555   \n",
+       "41                                                        9811   \n",
+       "42                                                        9865   \n",
+       "43                                                        9759   \n",
+       "44                                                        9891   \n",
+       "45                                                       10331   \n",
+       "46                                                       10350   \n",
+       "47                                                       10380   \n",
+       "48                                                       10357   \n",
+       "49                                                       10695   \n",
+       "50                                                       10750   \n",
+       "51                                                       11548   \n",
+       "52                                                        7954   \n",
+       "53                                                        7954   \n",
+       "\n",
+       "                                                NaN  \\\n",
+       "Week number  Total deaths: average of corresponding   \n",
+       "1                                               NaN   \n",
+       "2                                               NaN   \n",
+       "3                                               NaN   \n",
+       "4                                               NaN   \n",
+       "5                                               NaN   \n",
+       "6                                               NaN   \n",
+       "7                                               NaN   \n",
+       "8                                               NaN   \n",
+       "9                                               NaN   \n",
+       "10                                              NaN   \n",
+       "11                                              NaN   \n",
+       "12                                              NaN   \n",
+       "13                                              NaN   \n",
+       "14                                              NaN   \n",
+       "15                                              NaN   \n",
+       "16                                              NaN   \n",
+       "17                                              NaN   \n",
+       "18                                              NaN   \n",
+       "19                                              NaN   \n",
+       "20                                              NaN   \n",
+       "21                                              NaN   \n",
+       "22                                              NaN   \n",
+       "23                                              NaN   \n",
+       "24                                              NaN   \n",
+       "25                                              NaN   \n",
+       "26                                              NaN   \n",
+       "27                                              NaN   \n",
+       "28                                              NaN   \n",
+       "29                                              NaN   \n",
+       "30                                              NaN   \n",
+       "31                                              NaN   \n",
+       "32                                              NaN   \n",
+       "33                                              NaN   \n",
+       "34                                              NaN   \n",
+       "35                                              NaN   \n",
+       "36                                              NaN   \n",
+       "37                                              NaN   \n",
+       "38                                              NaN   \n",
+       "39                                              NaN   \n",
+       "40                                              NaN   \n",
+       "41                                              NaN   \n",
+       "42                                              NaN   \n",
+       "43                                              NaN   \n",
+       "44                                              NaN   \n",
+       "45                                              NaN   \n",
+       "46                                              NaN   \n",
+       "47                                              NaN   \n",
+       "48                                              NaN   \n",
+       "49                                              NaN   \n",
+       "50                                              NaN   \n",
+       "51                                              NaN   \n",
+       "52                                              NaN   \n",
+       "53                                              NaN   \n",
+       "\n",
+       "                                                           NaN  \\\n",
+       "Week number  week over the previous 5 years 1, 10, 11 (Engl...   \n",
+       "1                                                        11412   \n",
+       "2                                                        12933   \n",
+       "3                                                        12370   \n",
+       "4                                                        11933   \n",
+       "5                                                        11419   \n",
+       "6                                                        11154   \n",
+       "7                                                        10876   \n",
+       "8                                                        10790   \n",
+       "9                                                        10448   \n",
+       "10                                                       10745   \n",
+       "11                                                       10447   \n",
+       "12                                                        9841   \n",
+       "13                                                        9414   \n",
+       "14                                                        9601   \n",
+       "15                                                        9807   \n",
+       "16                                                        9787   \n",
+       "17                                                        9768   \n",
+       "18                                                        9289   \n",
+       "19                                                        8937   \n",
+       "20                                                        9526   \n",
+       "21                                                        9299   \n",
+       "22                                                        7607   \n",
+       "23                                                        9346   \n",
+       "24                                                        8803   \n",
+       "25                                                        8810   \n",
+       "26                                                        8695   \n",
+       "27                                                        8606   \n",
+       "28                                                        8648   \n",
+       "29                                                        8502   \n",
+       "30                                                        8452   \n",
+       "31                                                        8436   \n",
+       "32                                                        8502   \n",
+       "33                                                        8494   \n",
+       "34                                                        8560   \n",
+       "35                                                        7674   \n",
+       "36                                                        8604   \n",
+       "37                                                        8708   \n",
+       "38                                                        8663   \n",
+       "39                                                        8744   \n",
+       "40                                                        8942   \n",
+       "41                                                        9168   \n",
+       "42                                                        9215   \n",
+       "43                                                        9104   \n",
+       "44                                                        9248   \n",
+       "45                                                        9675   \n",
+       "46                                                        9662   \n",
+       "47                                                        9701   \n",
+       "48                                                        9690   \n",
+       "49                                                        9995   \n",
+       "50                                                       10034   \n",
+       "51                                                       10804   \n",
+       "52                                                        7421   \n",
+       "53                                                        7421   \n",
+       "\n",
+       "                                                NaN  \\\n",
+       "Week number  Total deaths: average of corresponding   \n",
+       "1                                               NaN   \n",
+       "2                                               NaN   \n",
+       "3                                               NaN   \n",
+       "4                                               NaN   \n",
+       "5                                               NaN   \n",
+       "6                                               NaN   \n",
+       "7                                               NaN   \n",
+       "8                                               NaN   \n",
+       "9                                               NaN   \n",
+       "10                                              NaN   \n",
+       "11                                              NaN   \n",
+       "12                                              NaN   \n",
+       "13                                              NaN   \n",
+       "14                                              NaN   \n",
+       "15                                              NaN   \n",
+       "16                                              NaN   \n",
+       "17                                              NaN   \n",
+       "18                                              NaN   \n",
+       "19                                              NaN   \n",
+       "20                                              NaN   \n",
+       "21                                              NaN   \n",
+       "22                                              NaN   \n",
+       "23                                              NaN   \n",
+       "24                                              NaN   \n",
+       "25                                              NaN   \n",
+       "26                                              NaN   \n",
+       "27                                              NaN   \n",
+       "28                                              NaN   \n",
+       "29                                              NaN   \n",
+       "30                                              NaN   \n",
+       "31                                              NaN   \n",
+       "32                                              NaN   \n",
+       "33                                              NaN   \n",
+       "34                                              NaN   \n",
+       "35                                              NaN   \n",
+       "36                                              NaN   \n",
+       "37                                              NaN   \n",
+       "38                                              NaN   \n",
+       "39                                              NaN   \n",
+       "40                                              NaN   \n",
+       "41                                              NaN   \n",
+       "42                                              NaN   \n",
+       "43                                              NaN   \n",
+       "44                                              NaN   \n",
+       "45                                              NaN   \n",
+       "46                                              NaN   \n",
+       "47                                              NaN   \n",
+       "48                                              NaN   \n",
+       "49                                              NaN   \n",
+       "50                                              NaN   \n",
+       "51                                              NaN   \n",
+       "52                                              NaN   \n",
+       "53                                              NaN   \n",
+       "\n",
+       "                                                          NaN  ... North East  \\\n",
+       "Week number  week over the previous 5 years 1, 10, 11 (Wales)  ...  E12000001   \n",
+       "1                                                         756  ...        673   \n",
+       "2                                                         856  ...        707   \n",
+       "3                                                         812  ...        647   \n",
+       "4                                                         802  ...        612   \n",
+       "5                                                         760  ...        561   \n",
+       "6                                                         729  ...        564   \n",
+       "7                                                         722  ...        573   \n",
+       "8                                                         724  ...        539   \n",
+       "9                                                         698  ...        572   \n",
+       "10                                                        720  ...        568   \n",
+       "11                                                        727  ...        590   \n",
+       "12                                                        677  ...        522   \n",
+       "13                                                        665  ...        542   \n",
+       "14                                                        667  ...        770   \n",
+       "15                                                        671  ...        849   \n",
+       "16                                                        661  ...       1155   \n",
+       "17                                                        662  ...       1103   \n",
+       "18                                                        624  ...        922   \n",
+       "19                                                        612  ...        769   \n",
+       "20                                                        635  ...        845   \n",
+       "21                                                        614  ...        718   \n",
+       "22                                                        546  ...        550   \n",
+       "23                                                        610  ...        576   \n",
+       "24                                                        588  ...        478   \n",
+       "25                                                        573  ...        498   \n",
+       "26                                                        571  ...        485   \n",
+       "27                                                        555  ...        515   \n",
+       "28                                                        578  ...        468   \n",
+       "29                                                        557  ...        445   \n",
+       "30                                                        566  ...        493   \n",
+       "31                                                        572  ...        507   \n",
+       "32                                                        571  ...        486   \n",
+       "33                                                        564  ...        520   \n",
+       "34                                                        573  ...        479   \n",
+       "35                                                        539  ...        455   \n",
+       "36                                                        552  ...        431   \n",
+       "37                                                        577  ...        502   \n",
+       "38                                                        575  ...        465   \n",
+       "39                                                        604  ...        514   \n",
+       "40                                                        587  ...        558   \n",
+       "41                                                        615  ...        544   \n",
+       "42                                                        630  ...        606   \n",
+       "43                                                        628  ...        600   \n",
+       "44                                                        616  ...        591   \n",
+       "45                                                        625  ...        675   \n",
+       "46                                                        658  ...        711   \n",
+       "47                                                        653  ...        691   \n",
+       "48                                                        646  ...        679   \n",
+       "49                                                        679  ...        645   \n",
+       "50                                                        693  ...        661   \n",
+       "51                                                        718  ...        689   \n",
+       "52                                                        518  ...        669   \n",
+       "53                                                        518  ...        547   \n",
+       "\n",
+       "            North West Yorkshire and The Humber East Midlands West Midlands  \\\n",
+       "Week number  E12000002                E12000003     E12000004     E12000005   \n",
+       "1                 1806                     1240          1060          1349   \n",
+       "2                 1932                     1339          1195          1450   \n",
+       "3                 1696                     1278          1106          1407   \n",
+       "4                 1529                     1187          1024          1231   \n",
+       "5                 1461                     1136          1015          1262   \n",
+       "6                 1529                     1072           922          1052   \n",
+       "7                 1427                     1059           976          1159   \n",
+       "8                 1477                     1087           924          1116   \n",
+       "9                 1476                     1078           919          1174   \n",
+       "10                1490                     1112           930          1098   \n",
+       "11                1472                     1053           915          1187   \n",
+       "12                1443                     1012           947          1115   \n",
+       "13                1538                      982           922          1035   \n",
+       "14                2137                     1436          1246          1812   \n",
+       "15                2597                     1503          1452          2182   \n",
+       "16                3195                     1960          1632          2536   \n",
+       "17                3109                     2095          1711          2481   \n",
+       "18                2503                     1844          1418          1975   \n",
+       "19                1790                     1328          1094          1326   \n",
+       "20                1992                     1589          1283          1502   \n",
+       "21                1636                     1236          1041          1319   \n",
+       "22                1337                     1046           863           970   \n",
+       "23                1478                     1090           931          1172   \n",
+       "24                1374                      980           967          1096   \n",
+       "25                1234                      952           835           973   \n",
+       "26                1300                      922           800           946   \n",
+       "27                1225                      875           827           949   \n",
+       "28                1154                      848           771           902   \n",
+       "29                1159                      843           816           956   \n",
+       "30                1197                      817           798           964   \n",
+       "31                1272                      837           729           902   \n",
+       "32                1211                      851           798           933   \n",
+       "33                1304                      853           829           923   \n",
+       "34                1269                      870           780          1028   \n",
+       "35                1148                      922           724           945   \n",
+       "36                1057                      780           640           770   \n",
+       "37                1229                      952           867          1021   \n",
+       "38                1287                      939           795          1051   \n",
+       "39                1271                      965           825          1036   \n",
+       "40                1301                      978           842          1045   \n",
+       "41                1367                     1067           884          1053   \n",
+       "42                1553                     1001           904          1154   \n",
+       "43                1714                     1111           891          1124   \n",
+       "44                1754                     1168           882          1102   \n",
+       "45                1900                     1294           990          1186   \n",
+       "46                1950                     1350          1099          1317   \n",
+       "47                1935                     1441          1105          1385   \n",
+       "48                1791                     1501          1218          1358   \n",
+       "49                1679                     1403          1121          1340   \n",
+       "50                1691                     1326          1199          1432   \n",
+       "51                1718                     1380          1199          1385   \n",
+       "52                1463                     1130          1097          1217   \n",
+       "53                1346                      886           842          1024   \n",
+       "\n",
+       "                  East     London South East South West      Wales  \n",
+       "Week number  E12000006  E12000007  E12000008  E12000009  W92000004  \n",
+       "1                 1162       1113       1814       1225        787  \n",
+       "2                 1573       1272       2132       1487        939  \n",
+       "3                 1457       1073       2064       1466        767  \n",
+       "4                 1410       1028       1833       1253        723  \n",
+       "5                 1286       1092       1820       1233        727  \n",
+       "6                 1259        987       1729       1157        690  \n",
+       "7                 1172        967       1688       1169        728  \n",
+       "8                 1167       1032       1675       1118        679  \n",
+       "9                 1115       1085       1587       1133        651  \n",
+       "10                1149        982       1726       1170        652  \n",
+       "11                1211        964       1751       1174        675  \n",
+       "12                1043       1008       1657       1156        719  \n",
+       "13                1182       1297       1822       1092        719  \n",
+       "14                1717       2511       2294       1520        920  \n",
+       "15                1984       2832       2604       1560        928  \n",
+       "16                2466       3275       3084       1854       1169  \n",
+       "17                2299       2785       3334       1924       1124  \n",
+       "18                1982       1953       2853       1554        929  \n",
+       "19                1321       1213       1887       1218        692  \n",
+       "20                1543       1329       2251       1449        772  \n",
+       "21                1397       1125       1937       1177        692  \n",
+       "22                1095        841       1515       1011        587  \n",
+       "23                1131        891       1610       1116        700  \n",
+       "24                1048        883       1530       1035        574  \n",
+       "25                 927        896       1411        990        617  \n",
+       "26                 880        791       1311        979        552  \n",
+       "27                 922        837       1454        938        584  \n",
+       "28                 999        803       1228        930        572  \n",
+       "29                 945        806       1339        953        550  \n",
+       "30                 951        816       1340        941        565  \n",
+       "31                 949        773       1447        988        531  \n",
+       "32                 955        832       1370        929        563  \n",
+       "33                1006        928       1395       1009        617  \n",
+       "34                1024        920       1608       1043        594  \n",
+       "35                 951        810       1511        959        591  \n",
+       "36                 806        737       1208        803        488  \n",
+       "37                1052        898       1610       1084        578  \n",
+       "38                1023        844       1530       1021        555  \n",
+       "39                 963        869       1521       1041        617  \n",
+       "40                1054        899       1577       1003        671  \n",
+       "41                1019        902       1462       1010        638  \n",
+       "42                1056        923       1462       1174        688  \n",
+       "43                1154        922       1510       1044        661  \n",
+       "44                1089        888       1563       1129        712  \n",
+       "45                1177        952       1614       1174        832  \n",
+       "46                1172       1112       1616       1168        742  \n",
+       "47                1186       1086       1687       1159        848  \n",
+       "48                1159       1012       1655       1272        797  \n",
+       "49                1229       1029       1720       1284        836  \n",
+       "50                1224       1065       1706       1156        814  \n",
+       "51                1317       1167       1947       1311        882  \n",
+       "52                1198       1090       1701       1115        825  \n",
+       "53                 997       1159       1595        929        727  \n",
+       "\n",
+       "[54 rows x 91 columns]"
+      ]
+     },
+     "execution_count": 43,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "eng_xls = pd.read_excel(england_wales_filename, \n",
+    "                        sheet_name=\"Weekly figures 2020\",\n",
+    "                        skiprows=[0, 1, 2, 3],\n",
+    "                        header=0,\n",
+    "                        index_col=[1]\n",
+    "                       ).iloc[:91].T\n",
+    "eng_xls"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# eng_xls_columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "eng_xls_columns = list(eng_xls.columns)\n",
+    "\n",
+    "for i, c in enumerate(eng_xls_columns):\n",
+    "#     print(i, c, type(c), isinstance(c, float))\n",
+    "    if isinstance(c, float) and np.isnan(c):\n",
+    "        if eng_xls.iloc[0].iloc[i] is not pd.NaT:\n",
+    "            eng_xls_columns[i] = eng_xls.iloc[0].iloc[i]\n",
+    "\n",
+    "# np.isnan(eng_xls_columns[0])\n",
+    "# eng_xls_columns\n",
+    "\n",
+    "eng_xls.columns = eng_xls_columns\n",
+    "# eng_xls.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Week ended</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>Total deaths, all ages</th>\n",
+       "      <th>Total deaths: average of corresponding</th>\n",
+       "      <th>week over the previous 5 years 1, 10, 11 (England and Wales)</th>\n",
+       "      <th>Total deaths: average of corresponding</th>\n",
+       "      <th>week over the previous 5 years 1, 10, 11 (England)</th>\n",
+       "      <th>Total deaths: average of corresponding</th>\n",
+       "      <th>week over the previous 5 years 1, 10, 11 (Wales)</th>\n",
+       "      <th>...</th>\n",
+       "      <th>North East</th>\n",
+       "      <th>North West</th>\n",
+       "      <th>Yorkshire and The Humber</th>\n",
+       "      <th>East Midlands</th>\n",
+       "      <th>West Midlands</th>\n",
+       "      <th>East</th>\n",
+       "      <th>London</th>\n",
+       "      <th>South East</th>\n",
+       "      <th>South West</th>\n",
+       "      <th>Wales</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Week number</th>\n",
+       "      <td>Week ended</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Total deaths, all ages</td>\n",
+       "      <td>Total deaths: average of corresponding</td>\n",
+       "      <td>week over the previous 5 years 1, 10, 11 (Engl...</td>\n",
+       "      <td>Total deaths: average of corresponding</td>\n",
+       "      <td>week over the previous 5 years 1, 10, 11 (Engl...</td>\n",
+       "      <td>Total deaths: average of corresponding</td>\n",
+       "      <td>week over the previous 5 years 1, 10, 11 (Wales)</td>\n",
+       "      <td>...</td>\n",
+       "      <td>E12000001</td>\n",
+       "      <td>E12000002</td>\n",
+       "      <td>E12000003</td>\n",
+       "      <td>E12000004</td>\n",
+       "      <td>E12000005</td>\n",
+       "      <td>E12000006</td>\n",
+       "      <td>E12000007</td>\n",
+       "      <td>E12000008</td>\n",
+       "      <td>E12000009</td>\n",
+       "      <td>W92000004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2020-01-03 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12254</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12175</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11412</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>756</td>\n",
+       "      <td>...</td>\n",
+       "      <td>673</td>\n",
+       "      <td>1806</td>\n",
+       "      <td>1240</td>\n",
+       "      <td>1060</td>\n",
+       "      <td>1349</td>\n",
+       "      <td>1162</td>\n",
+       "      <td>1113</td>\n",
+       "      <td>1814</td>\n",
+       "      <td>1225</td>\n",
+       "      <td>787</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2020-01-10 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14058</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13822</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12933</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>856</td>\n",
+       "      <td>...</td>\n",
+       "      <td>707</td>\n",
+       "      <td>1932</td>\n",
+       "      <td>1339</td>\n",
+       "      <td>1195</td>\n",
+       "      <td>1450</td>\n",
+       "      <td>1573</td>\n",
+       "      <td>1272</td>\n",
+       "      <td>2132</td>\n",
+       "      <td>1487</td>\n",
+       "      <td>939</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2020-01-17 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12990</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13216</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12370</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>812</td>\n",
+       "      <td>...</td>\n",
+       "      <td>647</td>\n",
+       "      <td>1696</td>\n",
+       "      <td>1278</td>\n",
+       "      <td>1106</td>\n",
+       "      <td>1407</td>\n",
+       "      <td>1457</td>\n",
+       "      <td>1073</td>\n",
+       "      <td>2064</td>\n",
+       "      <td>1466</td>\n",
+       "      <td>767</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2020-01-24 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11856</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12760</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11933</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>802</td>\n",
+       "      <td>...</td>\n",
+       "      <td>612</td>\n",
+       "      <td>1529</td>\n",
+       "      <td>1187</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>1231</td>\n",
+       "      <td>1410</td>\n",
+       "      <td>1028</td>\n",
+       "      <td>1833</td>\n",
+       "      <td>1253</td>\n",
+       "      <td>723</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2020-01-31 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11612</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12206</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11419</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>760</td>\n",
+       "      <td>...</td>\n",
+       "      <td>561</td>\n",
+       "      <td>1461</td>\n",
+       "      <td>1136</td>\n",
+       "      <td>1015</td>\n",
+       "      <td>1262</td>\n",
+       "      <td>1286</td>\n",
+       "      <td>1092</td>\n",
+       "      <td>1820</td>\n",
+       "      <td>1233</td>\n",
+       "      <td>727</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2020-02-07 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10986</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11925</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11154</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>729</td>\n",
+       "      <td>...</td>\n",
+       "      <td>564</td>\n",
+       "      <td>1529</td>\n",
+       "      <td>1072</td>\n",
+       "      <td>922</td>\n",
+       "      <td>1052</td>\n",
+       "      <td>1259</td>\n",
+       "      <td>987</td>\n",
+       "      <td>1729</td>\n",
+       "      <td>1157</td>\n",
+       "      <td>690</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2020-02-14 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10944</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11627</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10876</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>722</td>\n",
+       "      <td>...</td>\n",
+       "      <td>573</td>\n",
+       "      <td>1427</td>\n",
+       "      <td>1059</td>\n",
+       "      <td>976</td>\n",
+       "      <td>1159</td>\n",
+       "      <td>1172</td>\n",
+       "      <td>967</td>\n",
+       "      <td>1688</td>\n",
+       "      <td>1169</td>\n",
+       "      <td>728</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2020-02-21 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10841</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11548</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10790</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>724</td>\n",
+       "      <td>...</td>\n",
+       "      <td>539</td>\n",
+       "      <td>1477</td>\n",
+       "      <td>1087</td>\n",
+       "      <td>924</td>\n",
+       "      <td>1116</td>\n",
+       "      <td>1167</td>\n",
+       "      <td>1032</td>\n",
+       "      <td>1675</td>\n",
+       "      <td>1118</td>\n",
+       "      <td>679</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2020-02-28 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10816</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11183</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10448</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>698</td>\n",
+       "      <td>...</td>\n",
+       "      <td>572</td>\n",
+       "      <td>1476</td>\n",
+       "      <td>1078</td>\n",
+       "      <td>919</td>\n",
+       "      <td>1174</td>\n",
+       "      <td>1115</td>\n",
+       "      <td>1085</td>\n",
+       "      <td>1587</td>\n",
+       "      <td>1133</td>\n",
+       "      <td>651</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>2020-03-06 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10895</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11498</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10745</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>720</td>\n",
+       "      <td>...</td>\n",
+       "      <td>568</td>\n",
+       "      <td>1490</td>\n",
+       "      <td>1112</td>\n",
+       "      <td>930</td>\n",
+       "      <td>1098</td>\n",
+       "      <td>1149</td>\n",
+       "      <td>982</td>\n",
+       "      <td>1726</td>\n",
+       "      <td>1170</td>\n",
+       "      <td>652</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>2020-03-13 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11019</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11205</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10447</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>727</td>\n",
+       "      <td>...</td>\n",
+       "      <td>590</td>\n",
+       "      <td>1472</td>\n",
+       "      <td>1053</td>\n",
+       "      <td>915</td>\n",
+       "      <td>1187</td>\n",
+       "      <td>1211</td>\n",
+       "      <td>964</td>\n",
+       "      <td>1751</td>\n",
+       "      <td>1174</td>\n",
+       "      <td>675</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>2020-03-20 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10645</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10573</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9841</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>677</td>\n",
+       "      <td>...</td>\n",
+       "      <td>522</td>\n",
+       "      <td>1443</td>\n",
+       "      <td>1012</td>\n",
+       "      <td>947</td>\n",
+       "      <td>1115</td>\n",
+       "      <td>1043</td>\n",
+       "      <td>1008</td>\n",
+       "      <td>1657</td>\n",
+       "      <td>1156</td>\n",
+       "      <td>719</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>2020-03-27 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11141</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10130</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9414</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>665</td>\n",
+       "      <td>...</td>\n",
+       "      <td>542</td>\n",
+       "      <td>1538</td>\n",
+       "      <td>982</td>\n",
+       "      <td>922</td>\n",
+       "      <td>1035</td>\n",
+       "      <td>1182</td>\n",
+       "      <td>1297</td>\n",
+       "      <td>1822</td>\n",
+       "      <td>1092</td>\n",
+       "      <td>719</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>2020-04-03 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>16387</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10305</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9601</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>667</td>\n",
+       "      <td>...</td>\n",
+       "      <td>770</td>\n",
+       "      <td>2137</td>\n",
+       "      <td>1436</td>\n",
+       "      <td>1246</td>\n",
+       "      <td>1812</td>\n",
+       "      <td>1717</td>\n",
+       "      <td>2511</td>\n",
+       "      <td>2294</td>\n",
+       "      <td>1520</td>\n",
+       "      <td>920</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>2020-04-10 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>18516</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10520</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9807</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>671</td>\n",
+       "      <td>...</td>\n",
+       "      <td>849</td>\n",
+       "      <td>2597</td>\n",
+       "      <td>1503</td>\n",
+       "      <td>1452</td>\n",
+       "      <td>2182</td>\n",
+       "      <td>1984</td>\n",
+       "      <td>2832</td>\n",
+       "      <td>2604</td>\n",
+       "      <td>1560</td>\n",
+       "      <td>928</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>2020-04-17 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>22351</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10497</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9787</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>661</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1155</td>\n",
+       "      <td>3195</td>\n",
+       "      <td>1960</td>\n",
+       "      <td>1632</td>\n",
+       "      <td>2536</td>\n",
+       "      <td>2466</td>\n",
+       "      <td>3275</td>\n",
+       "      <td>3084</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1169</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>2020-04-24 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>21997</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10458</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9768</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>662</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1103</td>\n",
+       "      <td>3109</td>\n",
+       "      <td>2095</td>\n",
+       "      <td>1711</td>\n",
+       "      <td>2481</td>\n",
+       "      <td>2299</td>\n",
+       "      <td>2785</td>\n",
+       "      <td>3334</td>\n",
+       "      <td>1924</td>\n",
+       "      <td>1124</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>2020-05-01 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>17953</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9941</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9289</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>624</td>\n",
+       "      <td>...</td>\n",
+       "      <td>922</td>\n",
+       "      <td>2503</td>\n",
+       "      <td>1844</td>\n",
+       "      <td>1418</td>\n",
+       "      <td>1975</td>\n",
+       "      <td>1982</td>\n",
+       "      <td>1953</td>\n",
+       "      <td>2853</td>\n",
+       "      <td>1554</td>\n",
+       "      <td>929</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>2020-05-08 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12657</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9576</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8937</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>612</td>\n",
+       "      <td>...</td>\n",
+       "      <td>769</td>\n",
+       "      <td>1790</td>\n",
+       "      <td>1328</td>\n",
+       "      <td>1094</td>\n",
+       "      <td>1326</td>\n",
+       "      <td>1321</td>\n",
+       "      <td>1213</td>\n",
+       "      <td>1887</td>\n",
+       "      <td>1218</td>\n",
+       "      <td>692</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>2020-05-15 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14573</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10188</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9526</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>635</td>\n",
+       "      <td>...</td>\n",
+       "      <td>845</td>\n",
+       "      <td>1992</td>\n",
+       "      <td>1589</td>\n",
+       "      <td>1283</td>\n",
+       "      <td>1502</td>\n",
+       "      <td>1543</td>\n",
+       "      <td>1329</td>\n",
+       "      <td>2251</td>\n",
+       "      <td>1449</td>\n",
+       "      <td>772</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>2020-05-22 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12288</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9940</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9299</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>614</td>\n",
+       "      <td>...</td>\n",
+       "      <td>718</td>\n",
+       "      <td>1636</td>\n",
+       "      <td>1236</td>\n",
+       "      <td>1041</td>\n",
+       "      <td>1319</td>\n",
+       "      <td>1397</td>\n",
+       "      <td>1125</td>\n",
+       "      <td>1937</td>\n",
+       "      <td>1177</td>\n",
+       "      <td>692</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>2020-05-29 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9824</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8171</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7607</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>546</td>\n",
+       "      <td>...</td>\n",
+       "      <td>550</td>\n",
+       "      <td>1337</td>\n",
+       "      <td>1046</td>\n",
+       "      <td>863</td>\n",
+       "      <td>970</td>\n",
+       "      <td>1095</td>\n",
+       "      <td>841</td>\n",
+       "      <td>1515</td>\n",
+       "      <td>1011</td>\n",
+       "      <td>587</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>2020-06-05 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10709</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9977</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9346</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>610</td>\n",
+       "      <td>...</td>\n",
+       "      <td>576</td>\n",
+       "      <td>1478</td>\n",
+       "      <td>1090</td>\n",
+       "      <td>931</td>\n",
+       "      <td>1172</td>\n",
+       "      <td>1131</td>\n",
+       "      <td>891</td>\n",
+       "      <td>1610</td>\n",
+       "      <td>1116</td>\n",
+       "      <td>700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>2020-06-12 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9976</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9417</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8803</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>588</td>\n",
+       "      <td>...</td>\n",
+       "      <td>478</td>\n",
+       "      <td>1374</td>\n",
+       "      <td>980</td>\n",
+       "      <td>967</td>\n",
+       "      <td>1096</td>\n",
+       "      <td>1048</td>\n",
+       "      <td>883</td>\n",
+       "      <td>1530</td>\n",
+       "      <td>1035</td>\n",
+       "      <td>574</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>2020-06-19 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9339</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9404</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8810</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>573</td>\n",
+       "      <td>...</td>\n",
+       "      <td>498</td>\n",
+       "      <td>1234</td>\n",
+       "      <td>952</td>\n",
+       "      <td>835</td>\n",
+       "      <td>973</td>\n",
+       "      <td>927</td>\n",
+       "      <td>896</td>\n",
+       "      <td>1411</td>\n",
+       "      <td>990</td>\n",
+       "      <td>617</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>2020-06-26 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8979</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9293</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8695</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>571</td>\n",
+       "      <td>...</td>\n",
+       "      <td>485</td>\n",
+       "      <td>1300</td>\n",
+       "      <td>922</td>\n",
+       "      <td>800</td>\n",
+       "      <td>946</td>\n",
+       "      <td>880</td>\n",
+       "      <td>791</td>\n",
+       "      <td>1311</td>\n",
+       "      <td>979</td>\n",
+       "      <td>552</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>2020-07-03 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9140</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9183</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8606</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>555</td>\n",
+       "      <td>...</td>\n",
+       "      <td>515</td>\n",
+       "      <td>1225</td>\n",
+       "      <td>875</td>\n",
+       "      <td>827</td>\n",
+       "      <td>949</td>\n",
+       "      <td>922</td>\n",
+       "      <td>837</td>\n",
+       "      <td>1454</td>\n",
+       "      <td>938</td>\n",
+       "      <td>584</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>2020-07-10 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8690</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9250</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8648</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>578</td>\n",
+       "      <td>...</td>\n",
+       "      <td>468</td>\n",
+       "      <td>1154</td>\n",
+       "      <td>848</td>\n",
+       "      <td>771</td>\n",
+       "      <td>902</td>\n",
+       "      <td>999</td>\n",
+       "      <td>803</td>\n",
+       "      <td>1228</td>\n",
+       "      <td>930</td>\n",
+       "      <td>572</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>2020-07-17 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8823</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9093</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8502</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>557</td>\n",
+       "      <td>...</td>\n",
+       "      <td>445</td>\n",
+       "      <td>1159</td>\n",
+       "      <td>843</td>\n",
+       "      <td>816</td>\n",
+       "      <td>956</td>\n",
+       "      <td>945</td>\n",
+       "      <td>806</td>\n",
+       "      <td>1339</td>\n",
+       "      <td>953</td>\n",
+       "      <td>550</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>2020-07-24 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8891</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9052</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8452</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>566</td>\n",
+       "      <td>...</td>\n",
+       "      <td>493</td>\n",
+       "      <td>1197</td>\n",
+       "      <td>817</td>\n",
+       "      <td>798</td>\n",
+       "      <td>964</td>\n",
+       "      <td>951</td>\n",
+       "      <td>816</td>\n",
+       "      <td>1340</td>\n",
+       "      <td>941</td>\n",
+       "      <td>565</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>2020-07-31 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8946</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9036</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8436</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>572</td>\n",
+       "      <td>...</td>\n",
+       "      <td>507</td>\n",
+       "      <td>1272</td>\n",
+       "      <td>837</td>\n",
+       "      <td>729</td>\n",
+       "      <td>902</td>\n",
+       "      <td>949</td>\n",
+       "      <td>773</td>\n",
+       "      <td>1447</td>\n",
+       "      <td>988</td>\n",
+       "      <td>531</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>2020-08-07 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8945</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9102</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8502</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>571</td>\n",
+       "      <td>...</td>\n",
+       "      <td>486</td>\n",
+       "      <td>1211</td>\n",
+       "      <td>851</td>\n",
+       "      <td>798</td>\n",
+       "      <td>933</td>\n",
+       "      <td>955</td>\n",
+       "      <td>832</td>\n",
+       "      <td>1370</td>\n",
+       "      <td>929</td>\n",
+       "      <td>563</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>2020-08-14 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9392</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9085</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8494</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>564</td>\n",
+       "      <td>...</td>\n",
+       "      <td>520</td>\n",
+       "      <td>1304</td>\n",
+       "      <td>853</td>\n",
+       "      <td>829</td>\n",
+       "      <td>923</td>\n",
+       "      <td>1006</td>\n",
+       "      <td>928</td>\n",
+       "      <td>1395</td>\n",
+       "      <td>1009</td>\n",
+       "      <td>617</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>2020-08-21 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9631</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9157</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8560</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>573</td>\n",
+       "      <td>...</td>\n",
+       "      <td>479</td>\n",
+       "      <td>1269</td>\n",
+       "      <td>870</td>\n",
+       "      <td>780</td>\n",
+       "      <td>1028</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>920</td>\n",
+       "      <td>1608</td>\n",
+       "      <td>1043</td>\n",
+       "      <td>594</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>2020-08-28 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9032</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8241</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7674</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>539</td>\n",
+       "      <td>...</td>\n",
+       "      <td>455</td>\n",
+       "      <td>1148</td>\n",
+       "      <td>922</td>\n",
+       "      <td>724</td>\n",
+       "      <td>945</td>\n",
+       "      <td>951</td>\n",
+       "      <td>810</td>\n",
+       "      <td>1511</td>\n",
+       "      <td>959</td>\n",
+       "      <td>591</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>2020-09-04 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7739</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9182</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8604</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>552</td>\n",
+       "      <td>...</td>\n",
+       "      <td>431</td>\n",
+       "      <td>1057</td>\n",
+       "      <td>780</td>\n",
+       "      <td>640</td>\n",
+       "      <td>770</td>\n",
+       "      <td>806</td>\n",
+       "      <td>737</td>\n",
+       "      <td>1208</td>\n",
+       "      <td>803</td>\n",
+       "      <td>488</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>2020-09-11 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9811</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9306</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8708</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>577</td>\n",
+       "      <td>...</td>\n",
+       "      <td>502</td>\n",
+       "      <td>1229</td>\n",
+       "      <td>952</td>\n",
+       "      <td>867</td>\n",
+       "      <td>1021</td>\n",
+       "      <td>1052</td>\n",
+       "      <td>898</td>\n",
+       "      <td>1610</td>\n",
+       "      <td>1084</td>\n",
+       "      <td>578</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>2020-09-18 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9523</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9264</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8663</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>575</td>\n",
+       "      <td>...</td>\n",
+       "      <td>465</td>\n",
+       "      <td>1287</td>\n",
+       "      <td>939</td>\n",
+       "      <td>795</td>\n",
+       "      <td>1051</td>\n",
+       "      <td>1023</td>\n",
+       "      <td>844</td>\n",
+       "      <td>1530</td>\n",
+       "      <td>1021</td>\n",
+       "      <td>555</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>2020-09-25 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9634</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9377</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8744</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>604</td>\n",
+       "      <td>...</td>\n",
+       "      <td>514</td>\n",
+       "      <td>1271</td>\n",
+       "      <td>965</td>\n",
+       "      <td>825</td>\n",
+       "      <td>1036</td>\n",
+       "      <td>963</td>\n",
+       "      <td>869</td>\n",
+       "      <td>1521</td>\n",
+       "      <td>1041</td>\n",
+       "      <td>617</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>2020-10-02 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9945</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9555</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8942</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>587</td>\n",
+       "      <td>...</td>\n",
+       "      <td>558</td>\n",
+       "      <td>1301</td>\n",
+       "      <td>978</td>\n",
+       "      <td>842</td>\n",
+       "      <td>1045</td>\n",
+       "      <td>1054</td>\n",
+       "      <td>899</td>\n",
+       "      <td>1577</td>\n",
+       "      <td>1003</td>\n",
+       "      <td>671</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>2020-10-09 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9954</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9811</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9168</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>615</td>\n",
+       "      <td>...</td>\n",
+       "      <td>544</td>\n",
+       "      <td>1367</td>\n",
+       "      <td>1067</td>\n",
+       "      <td>884</td>\n",
+       "      <td>1053</td>\n",
+       "      <td>1019</td>\n",
+       "      <td>902</td>\n",
+       "      <td>1462</td>\n",
+       "      <td>1010</td>\n",
+       "      <td>638</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>2020-10-16 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10534</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9865</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9215</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>630</td>\n",
+       "      <td>...</td>\n",
+       "      <td>606</td>\n",
+       "      <td>1553</td>\n",
+       "      <td>1001</td>\n",
+       "      <td>904</td>\n",
+       "      <td>1154</td>\n",
+       "      <td>1056</td>\n",
+       "      <td>923</td>\n",
+       "      <td>1462</td>\n",
+       "      <td>1174</td>\n",
+       "      <td>688</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>2020-10-23 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10739</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9759</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9104</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>628</td>\n",
+       "      <td>...</td>\n",
+       "      <td>600</td>\n",
+       "      <td>1714</td>\n",
+       "      <td>1111</td>\n",
+       "      <td>891</td>\n",
+       "      <td>1124</td>\n",
+       "      <td>1154</td>\n",
+       "      <td>922</td>\n",
+       "      <td>1510</td>\n",
+       "      <td>1044</td>\n",
+       "      <td>661</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>2020-10-30 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10887</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9891</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9248</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>616</td>\n",
+       "      <td>...</td>\n",
+       "      <td>591</td>\n",
+       "      <td>1754</td>\n",
+       "      <td>1168</td>\n",
+       "      <td>882</td>\n",
+       "      <td>1102</td>\n",
+       "      <td>1089</td>\n",
+       "      <td>888</td>\n",
+       "      <td>1563</td>\n",
+       "      <td>1129</td>\n",
+       "      <td>712</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>2020-11-06 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11812</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10331</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9675</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>625</td>\n",
+       "      <td>...</td>\n",
+       "      <td>675</td>\n",
+       "      <td>1900</td>\n",
+       "      <td>1294</td>\n",
+       "      <td>990</td>\n",
+       "      <td>1186</td>\n",
+       "      <td>1177</td>\n",
+       "      <td>952</td>\n",
+       "      <td>1614</td>\n",
+       "      <td>1174</td>\n",
+       "      <td>832</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>2020-11-13 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12254</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10350</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9662</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>658</td>\n",
+       "      <td>...</td>\n",
+       "      <td>711</td>\n",
+       "      <td>1950</td>\n",
+       "      <td>1350</td>\n",
+       "      <td>1099</td>\n",
+       "      <td>1317</td>\n",
+       "      <td>1172</td>\n",
+       "      <td>1112</td>\n",
+       "      <td>1616</td>\n",
+       "      <td>1168</td>\n",
+       "      <td>742</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>2020-11-20 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12535</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10380</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9701</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>653</td>\n",
+       "      <td>...</td>\n",
+       "      <td>691</td>\n",
+       "      <td>1935</td>\n",
+       "      <td>1441</td>\n",
+       "      <td>1105</td>\n",
+       "      <td>1385</td>\n",
+       "      <td>1186</td>\n",
+       "      <td>1086</td>\n",
+       "      <td>1687</td>\n",
+       "      <td>1159</td>\n",
+       "      <td>848</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>2020-11-27 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12456</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10357</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9690</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>646</td>\n",
+       "      <td>...</td>\n",
+       "      <td>679</td>\n",
+       "      <td>1791</td>\n",
+       "      <td>1501</td>\n",
+       "      <td>1218</td>\n",
+       "      <td>1358</td>\n",
+       "      <td>1159</td>\n",
+       "      <td>1012</td>\n",
+       "      <td>1655</td>\n",
+       "      <td>1272</td>\n",
+       "      <td>797</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>2020-12-04 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12303</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10695</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9995</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>679</td>\n",
+       "      <td>...</td>\n",
+       "      <td>645</td>\n",
+       "      <td>1679</td>\n",
+       "      <td>1403</td>\n",
+       "      <td>1121</td>\n",
+       "      <td>1340</td>\n",
+       "      <td>1229</td>\n",
+       "      <td>1029</td>\n",
+       "      <td>1720</td>\n",
+       "      <td>1284</td>\n",
+       "      <td>836</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>2020-12-11 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12292</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10750</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10034</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>693</td>\n",
+       "      <td>...</td>\n",
+       "      <td>661</td>\n",
+       "      <td>1691</td>\n",
+       "      <td>1326</td>\n",
+       "      <td>1199</td>\n",
+       "      <td>1432</td>\n",
+       "      <td>1224</td>\n",
+       "      <td>1065</td>\n",
+       "      <td>1706</td>\n",
+       "      <td>1156</td>\n",
+       "      <td>814</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>2020-12-18 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13011</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11548</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10804</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>718</td>\n",
+       "      <td>...</td>\n",
+       "      <td>689</td>\n",
+       "      <td>1718</td>\n",
+       "      <td>1380</td>\n",
+       "      <td>1199</td>\n",
+       "      <td>1385</td>\n",
+       "      <td>1317</td>\n",
+       "      <td>1167</td>\n",
+       "      <td>1947</td>\n",
+       "      <td>1311</td>\n",
+       "      <td>882</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>2020-12-25 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11520</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7954</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7421</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>518</td>\n",
+       "      <td>...</td>\n",
+       "      <td>669</td>\n",
+       "      <td>1463</td>\n",
+       "      <td>1130</td>\n",
+       "      <td>1097</td>\n",
+       "      <td>1217</td>\n",
+       "      <td>1198</td>\n",
+       "      <td>1090</td>\n",
+       "      <td>1701</td>\n",
+       "      <td>1115</td>\n",
+       "      <td>825</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>2021-01-01 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10069</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7954</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7421</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>518</td>\n",
+       "      <td>...</td>\n",
+       "      <td>547</td>\n",
+       "      <td>1346</td>\n",
+       "      <td>886</td>\n",
+       "      <td>842</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>997</td>\n",
+       "      <td>1159</td>\n",
+       "      <td>1595</td>\n",
+       "      <td>929</td>\n",
+       "      <td>727</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>54 rows × 91 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                      Week ended  NaN  NaN  Total deaths, all ages  \\\n",
+       "Week number           Week ended  NaN  NaN  Total deaths, all ages   \n",
+       "1            2020-01-03 00:00:00  NaN  NaN                   12254   \n",
+       "2            2020-01-10 00:00:00  NaN  NaN                   14058   \n",
+       "3            2020-01-17 00:00:00  NaN  NaN                   12990   \n",
+       "4            2020-01-24 00:00:00  NaN  NaN                   11856   \n",
+       "5            2020-01-31 00:00:00  NaN  NaN                   11612   \n",
+       "6            2020-02-07 00:00:00  NaN  NaN                   10986   \n",
+       "7            2020-02-14 00:00:00  NaN  NaN                   10944   \n",
+       "8            2020-02-21 00:00:00  NaN  NaN                   10841   \n",
+       "9            2020-02-28 00:00:00  NaN  NaN                   10816   \n",
+       "10           2020-03-06 00:00:00  NaN  NaN                   10895   \n",
+       "11           2020-03-13 00:00:00  NaN  NaN                   11019   \n",
+       "12           2020-03-20 00:00:00  NaN  NaN                   10645   \n",
+       "13           2020-03-27 00:00:00  NaN  NaN                   11141   \n",
+       "14           2020-04-03 00:00:00  NaN  NaN                   16387   \n",
+       "15           2020-04-10 00:00:00  NaN  NaN                   18516   \n",
+       "16           2020-04-17 00:00:00  NaN  NaN                   22351   \n",
+       "17           2020-04-24 00:00:00  NaN  NaN                   21997   \n",
+       "18           2020-05-01 00:00:00  NaN  NaN                   17953   \n",
+       "19           2020-05-08 00:00:00  NaN  NaN                   12657   \n",
+       "20           2020-05-15 00:00:00  NaN  NaN                   14573   \n",
+       "21           2020-05-22 00:00:00  NaN  NaN                   12288   \n",
+       "22           2020-05-29 00:00:00  NaN  NaN                    9824   \n",
+       "23           2020-06-05 00:00:00  NaN  NaN                   10709   \n",
+       "24           2020-06-12 00:00:00  NaN  NaN                    9976   \n",
+       "25           2020-06-19 00:00:00  NaN  NaN                    9339   \n",
+       "26           2020-06-26 00:00:00  NaN  NaN                    8979   \n",
+       "27           2020-07-03 00:00:00  NaN  NaN                    9140   \n",
+       "28           2020-07-10 00:00:00  NaN  NaN                    8690   \n",
+       "29           2020-07-17 00:00:00  NaN  NaN                    8823   \n",
+       "30           2020-07-24 00:00:00  NaN  NaN                    8891   \n",
+       "31           2020-07-31 00:00:00  NaN  NaN                    8946   \n",
+       "32           2020-08-07 00:00:00  NaN  NaN                    8945   \n",
+       "33           2020-08-14 00:00:00  NaN  NaN                    9392   \n",
+       "34           2020-08-21 00:00:00  NaN  NaN                    9631   \n",
+       "35           2020-08-28 00:00:00  NaN  NaN                    9032   \n",
+       "36           2020-09-04 00:00:00  NaN  NaN                    7739   \n",
+       "37           2020-09-11 00:00:00  NaN  NaN                    9811   \n",
+       "38           2020-09-18 00:00:00  NaN  NaN                    9523   \n",
+       "39           2020-09-25 00:00:00  NaN  NaN                    9634   \n",
+       "40           2020-10-02 00:00:00  NaN  NaN                    9945   \n",
+       "41           2020-10-09 00:00:00  NaN  NaN                    9954   \n",
+       "42           2020-10-16 00:00:00  NaN  NaN                   10534   \n",
+       "43           2020-10-23 00:00:00  NaN  NaN                   10739   \n",
+       "44           2020-10-30 00:00:00  NaN  NaN                   10887   \n",
+       "45           2020-11-06 00:00:00  NaN  NaN                   11812   \n",
+       "46           2020-11-13 00:00:00  NaN  NaN                   12254   \n",
+       "47           2020-11-20 00:00:00  NaN  NaN                   12535   \n",
+       "48           2020-11-27 00:00:00  NaN  NaN                   12456   \n",
+       "49           2020-12-04 00:00:00  NaN  NaN                   12303   \n",
+       "50           2020-12-11 00:00:00  NaN  NaN                   12292   \n",
+       "51           2020-12-18 00:00:00  NaN  NaN                   13011   \n",
+       "52           2020-12-25 00:00:00  NaN  NaN                   11520   \n",
+       "53           2021-01-01 00:00:00  NaN  NaN                   10069   \n",
+       "\n",
+       "             Total deaths: average of corresponding  \\\n",
+       "Week number  Total deaths: average of corresponding   \n",
+       "1                                               NaN   \n",
+       "2                                               NaN   \n",
+       "3                                               NaN   \n",
+       "4                                               NaN   \n",
+       "5                                               NaN   \n",
+       "6                                               NaN   \n",
+       "7                                               NaN   \n",
+       "8                                               NaN   \n",
+       "9                                               NaN   \n",
+       "10                                              NaN   \n",
+       "11                                              NaN   \n",
+       "12                                              NaN   \n",
+       "13                                              NaN   \n",
+       "14                                              NaN   \n",
+       "15                                              NaN   \n",
+       "16                                              NaN   \n",
+       "17                                              NaN   \n",
+       "18                                              NaN   \n",
+       "19                                              NaN   \n",
+       "20                                              NaN   \n",
+       "21                                              NaN   \n",
+       "22                                              NaN   \n",
+       "23                                              NaN   \n",
+       "24                                              NaN   \n",
+       "25                                              NaN   \n",
+       "26                                              NaN   \n",
+       "27                                              NaN   \n",
+       "28                                              NaN   \n",
+       "29                                              NaN   \n",
+       "30                                              NaN   \n",
+       "31                                              NaN   \n",
+       "32                                              NaN   \n",
+       "33                                              NaN   \n",
+       "34                                              NaN   \n",
+       "35                                              NaN   \n",
+       "36                                              NaN   \n",
+       "37                                              NaN   \n",
+       "38                                              NaN   \n",
+       "39                                              NaN   \n",
+       "40                                              NaN   \n",
+       "41                                              NaN   \n",
+       "42                                              NaN   \n",
+       "43                                              NaN   \n",
+       "44                                              NaN   \n",
+       "45                                              NaN   \n",
+       "46                                              NaN   \n",
+       "47                                              NaN   \n",
+       "48                                              NaN   \n",
+       "49                                              NaN   \n",
+       "50                                              NaN   \n",
+       "51                                              NaN   \n",
+       "52                                              NaN   \n",
+       "53                                              NaN   \n",
+       "\n",
+       "            week over the previous 5 years 1, 10, 11 (England and Wales)  \\\n",
+       "Week number  week over the previous 5 years 1, 10, 11 (Engl...             \n",
+       "1                                                        12175             \n",
+       "2                                                        13822             \n",
+       "3                                                        13216             \n",
+       "4                                                        12760             \n",
+       "5                                                        12206             \n",
+       "6                                                        11925             \n",
+       "7                                                        11627             \n",
+       "8                                                        11548             \n",
+       "9                                                        11183             \n",
+       "10                                                       11498             \n",
+       "11                                                       11205             \n",
+       "12                                                       10573             \n",
+       "13                                                       10130             \n",
+       "14                                                       10305             \n",
+       "15                                                       10520             \n",
+       "16                                                       10497             \n",
+       "17                                                       10458             \n",
+       "18                                                        9941             \n",
+       "19                                                        9576             \n",
+       "20                                                       10188             \n",
+       "21                                                        9940             \n",
+       "22                                                        8171             \n",
+       "23                                                        9977             \n",
+       "24                                                        9417             \n",
+       "25                                                        9404             \n",
+       "26                                                        9293             \n",
+       "27                                                        9183             \n",
+       "28                                                        9250             \n",
+       "29                                                        9093             \n",
+       "30                                                        9052             \n",
+       "31                                                        9036             \n",
+       "32                                                        9102             \n",
+       "33                                                        9085             \n",
+       "34                                                        9157             \n",
+       "35                                                        8241             \n",
+       "36                                                        9182             \n",
+       "37                                                        9306             \n",
+       "38                                                        9264             \n",
+       "39                                                        9377             \n",
+       "40                                                        9555             \n",
+       "41                                                        9811             \n",
+       "42                                                        9865             \n",
+       "43                                                        9759             \n",
+       "44                                                        9891             \n",
+       "45                                                       10331             \n",
+       "46                                                       10350             \n",
+       "47                                                       10380             \n",
+       "48                                                       10357             \n",
+       "49                                                       10695             \n",
+       "50                                                       10750             \n",
+       "51                                                       11548             \n",
+       "52                                                        7954             \n",
+       "53                                                        7954             \n",
+       "\n",
+       "             Total deaths: average of corresponding  \\\n",
+       "Week number  Total deaths: average of corresponding   \n",
+       "1                                               NaN   \n",
+       "2                                               NaN   \n",
+       "3                                               NaN   \n",
+       "4                                               NaN   \n",
+       "5                                               NaN   \n",
+       "6                                               NaN   \n",
+       "7                                               NaN   \n",
+       "8                                               NaN   \n",
+       "9                                               NaN   \n",
+       "10                                              NaN   \n",
+       "11                                              NaN   \n",
+       "12                                              NaN   \n",
+       "13                                              NaN   \n",
+       "14                                              NaN   \n",
+       "15                                              NaN   \n",
+       "16                                              NaN   \n",
+       "17                                              NaN   \n",
+       "18                                              NaN   \n",
+       "19                                              NaN   \n",
+       "20                                              NaN   \n",
+       "21                                              NaN   \n",
+       "22                                              NaN   \n",
+       "23                                              NaN   \n",
+       "24                                              NaN   \n",
+       "25                                              NaN   \n",
+       "26                                              NaN   \n",
+       "27                                              NaN   \n",
+       "28                                              NaN   \n",
+       "29                                              NaN   \n",
+       "30                                              NaN   \n",
+       "31                                              NaN   \n",
+       "32                                              NaN   \n",
+       "33                                              NaN   \n",
+       "34                                              NaN   \n",
+       "35                                              NaN   \n",
+       "36                                              NaN   \n",
+       "37                                              NaN   \n",
+       "38                                              NaN   \n",
+       "39                                              NaN   \n",
+       "40                                              NaN   \n",
+       "41                                              NaN   \n",
+       "42                                              NaN   \n",
+       "43                                              NaN   \n",
+       "44                                              NaN   \n",
+       "45                                              NaN   \n",
+       "46                                              NaN   \n",
+       "47                                              NaN   \n",
+       "48                                              NaN   \n",
+       "49                                              NaN   \n",
+       "50                                              NaN   \n",
+       "51                                              NaN   \n",
+       "52                                              NaN   \n",
+       "53                                              NaN   \n",
+       "\n",
+       "            week over the previous 5 years 1, 10, 11 (England)  \\\n",
+       "Week number  week over the previous 5 years 1, 10, 11 (Engl...   \n",
+       "1                                                        11412   \n",
+       "2                                                        12933   \n",
+       "3                                                        12370   \n",
+       "4                                                        11933   \n",
+       "5                                                        11419   \n",
+       "6                                                        11154   \n",
+       "7                                                        10876   \n",
+       "8                                                        10790   \n",
+       "9                                                        10448   \n",
+       "10                                                       10745   \n",
+       "11                                                       10447   \n",
+       "12                                                        9841   \n",
+       "13                                                        9414   \n",
+       "14                                                        9601   \n",
+       "15                                                        9807   \n",
+       "16                                                        9787   \n",
+       "17                                                        9768   \n",
+       "18                                                        9289   \n",
+       "19                                                        8937   \n",
+       "20                                                        9526   \n",
+       "21                                                        9299   \n",
+       "22                                                        7607   \n",
+       "23                                                        9346   \n",
+       "24                                                        8803   \n",
+       "25                                                        8810   \n",
+       "26                                                        8695   \n",
+       "27                                                        8606   \n",
+       "28                                                        8648   \n",
+       "29                                                        8502   \n",
+       "30                                                        8452   \n",
+       "31                                                        8436   \n",
+       "32                                                        8502   \n",
+       "33                                                        8494   \n",
+       "34                                                        8560   \n",
+       "35                                                        7674   \n",
+       "36                                                        8604   \n",
+       "37                                                        8708   \n",
+       "38                                                        8663   \n",
+       "39                                                        8744   \n",
+       "40                                                        8942   \n",
+       "41                                                        9168   \n",
+       "42                                                        9215   \n",
+       "43                                                        9104   \n",
+       "44                                                        9248   \n",
+       "45                                                        9675   \n",
+       "46                                                        9662   \n",
+       "47                                                        9701   \n",
+       "48                                                        9690   \n",
+       "49                                                        9995   \n",
+       "50                                                       10034   \n",
+       "51                                                       10804   \n",
+       "52                                                        7421   \n",
+       "53                                                        7421   \n",
+       "\n",
+       "             Total deaths: average of corresponding  \\\n",
+       "Week number  Total deaths: average of corresponding   \n",
+       "1                                               NaN   \n",
+       "2                                               NaN   \n",
+       "3                                               NaN   \n",
+       "4                                               NaN   \n",
+       "5                                               NaN   \n",
+       "6                                               NaN   \n",
+       "7                                               NaN   \n",
+       "8                                               NaN   \n",
+       "9                                               NaN   \n",
+       "10                                              NaN   \n",
+       "11                                              NaN   \n",
+       "12                                              NaN   \n",
+       "13                                              NaN   \n",
+       "14                                              NaN   \n",
+       "15                                              NaN   \n",
+       "16                                              NaN   \n",
+       "17                                              NaN   \n",
+       "18                                              NaN   \n",
+       "19                                              NaN   \n",
+       "20                                              NaN   \n",
+       "21                                              NaN   \n",
+       "22                                              NaN   \n",
+       "23                                              NaN   \n",
+       "24                                              NaN   \n",
+       "25                                              NaN   \n",
+       "26                                              NaN   \n",
+       "27                                              NaN   \n",
+       "28                                              NaN   \n",
+       "29                                              NaN   \n",
+       "30                                              NaN   \n",
+       "31                                              NaN   \n",
+       "32                                              NaN   \n",
+       "33                                              NaN   \n",
+       "34                                              NaN   \n",
+       "35                                              NaN   \n",
+       "36                                              NaN   \n",
+       "37                                              NaN   \n",
+       "38                                              NaN   \n",
+       "39                                              NaN   \n",
+       "40                                              NaN   \n",
+       "41                                              NaN   \n",
+       "42                                              NaN   \n",
+       "43                                              NaN   \n",
+       "44                                              NaN   \n",
+       "45                                              NaN   \n",
+       "46                                              NaN   \n",
+       "47                                              NaN   \n",
+       "48                                              NaN   \n",
+       "49                                              NaN   \n",
+       "50                                              NaN   \n",
+       "51                                              NaN   \n",
+       "52                                              NaN   \n",
+       "53                                              NaN   \n",
+       "\n",
+       "             week over the previous 5 years 1, 10, 11 (Wales)  ... North East  \\\n",
+       "Week number  week over the previous 5 years 1, 10, 11 (Wales)  ...  E12000001   \n",
+       "1                                                         756  ...        673   \n",
+       "2                                                         856  ...        707   \n",
+       "3                                                         812  ...        647   \n",
+       "4                                                         802  ...        612   \n",
+       "5                                                         760  ...        561   \n",
+       "6                                                         729  ...        564   \n",
+       "7                                                         722  ...        573   \n",
+       "8                                                         724  ...        539   \n",
+       "9                                                         698  ...        572   \n",
+       "10                                                        720  ...        568   \n",
+       "11                                                        727  ...        590   \n",
+       "12                                                        677  ...        522   \n",
+       "13                                                        665  ...        542   \n",
+       "14                                                        667  ...        770   \n",
+       "15                                                        671  ...        849   \n",
+       "16                                                        661  ...       1155   \n",
+       "17                                                        662  ...       1103   \n",
+       "18                                                        624  ...        922   \n",
+       "19                                                        612  ...        769   \n",
+       "20                                                        635  ...        845   \n",
+       "21                                                        614  ...        718   \n",
+       "22                                                        546  ...        550   \n",
+       "23                                                        610  ...        576   \n",
+       "24                                                        588  ...        478   \n",
+       "25                                                        573  ...        498   \n",
+       "26                                                        571  ...        485   \n",
+       "27                                                        555  ...        515   \n",
+       "28                                                        578  ...        468   \n",
+       "29                                                        557  ...        445   \n",
+       "30                                                        566  ...        493   \n",
+       "31                                                        572  ...        507   \n",
+       "32                                                        571  ...        486   \n",
+       "33                                                        564  ...        520   \n",
+       "34                                                        573  ...        479   \n",
+       "35                                                        539  ...        455   \n",
+       "36                                                        552  ...        431   \n",
+       "37                                                        577  ...        502   \n",
+       "38                                                        575  ...        465   \n",
+       "39                                                        604  ...        514   \n",
+       "40                                                        587  ...        558   \n",
+       "41                                                        615  ...        544   \n",
+       "42                                                        630  ...        606   \n",
+       "43                                                        628  ...        600   \n",
+       "44                                                        616  ...        591   \n",
+       "45                                                        625  ...        675   \n",
+       "46                                                        658  ...        711   \n",
+       "47                                                        653  ...        691   \n",
+       "48                                                        646  ...        679   \n",
+       "49                                                        679  ...        645   \n",
+       "50                                                        693  ...        661   \n",
+       "51                                                        718  ...        689   \n",
+       "52                                                        518  ...        669   \n",
+       "53                                                        518  ...        547   \n",
+       "\n",
+       "            North West Yorkshire and The Humber East Midlands West Midlands  \\\n",
+       "Week number  E12000002                E12000003     E12000004     E12000005   \n",
+       "1                 1806                     1240          1060          1349   \n",
+       "2                 1932                     1339          1195          1450   \n",
+       "3                 1696                     1278          1106          1407   \n",
+       "4                 1529                     1187          1024          1231   \n",
+       "5                 1461                     1136          1015          1262   \n",
+       "6                 1529                     1072           922          1052   \n",
+       "7                 1427                     1059           976          1159   \n",
+       "8                 1477                     1087           924          1116   \n",
+       "9                 1476                     1078           919          1174   \n",
+       "10                1490                     1112           930          1098   \n",
+       "11                1472                     1053           915          1187   \n",
+       "12                1443                     1012           947          1115   \n",
+       "13                1538                      982           922          1035   \n",
+       "14                2137                     1436          1246          1812   \n",
+       "15                2597                     1503          1452          2182   \n",
+       "16                3195                     1960          1632          2536   \n",
+       "17                3109                     2095          1711          2481   \n",
+       "18                2503                     1844          1418          1975   \n",
+       "19                1790                     1328          1094          1326   \n",
+       "20                1992                     1589          1283          1502   \n",
+       "21                1636                     1236          1041          1319   \n",
+       "22                1337                     1046           863           970   \n",
+       "23                1478                     1090           931          1172   \n",
+       "24                1374                      980           967          1096   \n",
+       "25                1234                      952           835           973   \n",
+       "26                1300                      922           800           946   \n",
+       "27                1225                      875           827           949   \n",
+       "28                1154                      848           771           902   \n",
+       "29                1159                      843           816           956   \n",
+       "30                1197                      817           798           964   \n",
+       "31                1272                      837           729           902   \n",
+       "32                1211                      851           798           933   \n",
+       "33                1304                      853           829           923   \n",
+       "34                1269                      870           780          1028   \n",
+       "35                1148                      922           724           945   \n",
+       "36                1057                      780           640           770   \n",
+       "37                1229                      952           867          1021   \n",
+       "38                1287                      939           795          1051   \n",
+       "39                1271                      965           825          1036   \n",
+       "40                1301                      978           842          1045   \n",
+       "41                1367                     1067           884          1053   \n",
+       "42                1553                     1001           904          1154   \n",
+       "43                1714                     1111           891          1124   \n",
+       "44                1754                     1168           882          1102   \n",
+       "45                1900                     1294           990          1186   \n",
+       "46                1950                     1350          1099          1317   \n",
+       "47                1935                     1441          1105          1385   \n",
+       "48                1791                     1501          1218          1358   \n",
+       "49                1679                     1403          1121          1340   \n",
+       "50                1691                     1326          1199          1432   \n",
+       "51                1718                     1380          1199          1385   \n",
+       "52                1463                     1130          1097          1217   \n",
+       "53                1346                      886           842          1024   \n",
+       "\n",
+       "                  East     London South East South West      Wales  \n",
+       "Week number  E12000006  E12000007  E12000008  E12000009  W92000004  \n",
+       "1                 1162       1113       1814       1225        787  \n",
+       "2                 1573       1272       2132       1487        939  \n",
+       "3                 1457       1073       2064       1466        767  \n",
+       "4                 1410       1028       1833       1253        723  \n",
+       "5                 1286       1092       1820       1233        727  \n",
+       "6                 1259        987       1729       1157        690  \n",
+       "7                 1172        967       1688       1169        728  \n",
+       "8                 1167       1032       1675       1118        679  \n",
+       "9                 1115       1085       1587       1133        651  \n",
+       "10                1149        982       1726       1170        652  \n",
+       "11                1211        964       1751       1174        675  \n",
+       "12                1043       1008       1657       1156        719  \n",
+       "13                1182       1297       1822       1092        719  \n",
+       "14                1717       2511       2294       1520        920  \n",
+       "15                1984       2832       2604       1560        928  \n",
+       "16                2466       3275       3084       1854       1169  \n",
+       "17                2299       2785       3334       1924       1124  \n",
+       "18                1982       1953       2853       1554        929  \n",
+       "19                1321       1213       1887       1218        692  \n",
+       "20                1543       1329       2251       1449        772  \n",
+       "21                1397       1125       1937       1177        692  \n",
+       "22                1095        841       1515       1011        587  \n",
+       "23                1131        891       1610       1116        700  \n",
+       "24                1048        883       1530       1035        574  \n",
+       "25                 927        896       1411        990        617  \n",
+       "26                 880        791       1311        979        552  \n",
+       "27                 922        837       1454        938        584  \n",
+       "28                 999        803       1228        930        572  \n",
+       "29                 945        806       1339        953        550  \n",
+       "30                 951        816       1340        941        565  \n",
+       "31                 949        773       1447        988        531  \n",
+       "32                 955        832       1370        929        563  \n",
+       "33                1006        928       1395       1009        617  \n",
+       "34                1024        920       1608       1043        594  \n",
+       "35                 951        810       1511        959        591  \n",
+       "36                 806        737       1208        803        488  \n",
+       "37                1052        898       1610       1084        578  \n",
+       "38                1023        844       1530       1021        555  \n",
+       "39                 963        869       1521       1041        617  \n",
+       "40                1054        899       1577       1003        671  \n",
+       "41                1019        902       1462       1010        638  \n",
+       "42                1056        923       1462       1174        688  \n",
+       "43                1154        922       1510       1044        661  \n",
+       "44                1089        888       1563       1129        712  \n",
+       "45                1177        952       1614       1174        832  \n",
+       "46                1172       1112       1616       1168        742  \n",
+       "47                1186       1086       1687       1159        848  \n",
+       "48                1159       1012       1655       1272        797  \n",
+       "49                1229       1029       1720       1284        836  \n",
+       "50                1224       1065       1706       1156        814  \n",
+       "51                1317       1167       1947       1311        882  \n",
+       "52                1198       1090       1701       1115        825  \n",
+       "53                 997       1159       1595        929        727  \n",
+       "\n",
+       "[54 rows x 91 columns]"
+      ]
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "eng_xls"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-01-03 00:00:00</td>\n",
+       "      <td>787</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2020-01-10 00:00:00</td>\n",
+       "      <td>939</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2020-01-17 00:00:00</td>\n",
+       "      <td>767</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2020-01-24 00:00:00</td>\n",
+       "      <td>723</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2020-01-31 00:00:00</td>\n",
+       "      <td>727</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week           date_up_to deaths  year nation\n",
+       "0     1  2020-01-03 00:00:00    787  2020  Wales\n",
+       "1     2  2020-01-10 00:00:00    939  2020  Wales\n",
+       "2     3  2020-01-17 00:00:00    767  2020  Wales\n",
+       "3     4  2020-01-24 00:00:00    723  2020  Wales\n",
+       "4     5  2020-01-31 00:00:00    727  2020  Wales"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = eng_xls.iloc[1:][['Week ended', 'Wales']].reset_index(level=0).rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'Wales': 'deaths',\n",
+    "            'index': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2020\n",
+    "rd['nation'] = 'Wales'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "<ipython-input-49-7dd1e0e9987b>:2: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  eng_xls['England deaths'] = eng_xls.loc[:, 'Total deaths, all ages'] - eng_xls.loc[:, 'Wales']\n"
+     ]
+    }
+   ],
+   "source": [
+    "eng_xls = eng_xls.iloc[1:]\n",
+    "eng_xls['England deaths'] = eng_xls.loc[:, 'Total deaths, all ages'] - eng_xls.loc[:, 'Wales']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Week ended</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>Total deaths, all ages</th>\n",
+       "      <th>Total deaths: average of corresponding</th>\n",
+       "      <th>week over the previous 5 years 1, 10, 11 (England and Wales)</th>\n",
+       "      <th>Total deaths: average of corresponding</th>\n",
+       "      <th>week over the previous 5 years 1, 10, 11 (England)</th>\n",
+       "      <th>Total deaths: average of corresponding</th>\n",
+       "      <th>week over the previous 5 years 1, 10, 11 (Wales)</th>\n",
+       "      <th>...</th>\n",
+       "      <th>North West</th>\n",
+       "      <th>Yorkshire and The Humber</th>\n",
+       "      <th>East Midlands</th>\n",
+       "      <th>West Midlands</th>\n",
+       "      <th>East</th>\n",
+       "      <th>London</th>\n",
+       "      <th>South East</th>\n",
+       "      <th>South West</th>\n",
+       "      <th>Wales</th>\n",
+       "      <th>England deaths</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2020-01-03 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12254</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12175</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11412</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>756</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1806</td>\n",
+       "      <td>1240</td>\n",
+       "      <td>1060</td>\n",
+       "      <td>1349</td>\n",
+       "      <td>1162</td>\n",
+       "      <td>1113</td>\n",
+       "      <td>1814</td>\n",
+       "      <td>1225</td>\n",
+       "      <td>787</td>\n",
+       "      <td>11467</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2020-01-10 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14058</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13822</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12933</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>856</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1932</td>\n",
+       "      <td>1339</td>\n",
+       "      <td>1195</td>\n",
+       "      <td>1450</td>\n",
+       "      <td>1573</td>\n",
+       "      <td>1272</td>\n",
+       "      <td>2132</td>\n",
+       "      <td>1487</td>\n",
+       "      <td>939</td>\n",
+       "      <td>13119</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2020-01-17 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12990</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13216</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12370</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>812</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1696</td>\n",
+       "      <td>1278</td>\n",
+       "      <td>1106</td>\n",
+       "      <td>1407</td>\n",
+       "      <td>1457</td>\n",
+       "      <td>1073</td>\n",
+       "      <td>2064</td>\n",
+       "      <td>1466</td>\n",
+       "      <td>767</td>\n",
+       "      <td>12223</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2020-01-24 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11856</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12760</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11933</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>802</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1529</td>\n",
+       "      <td>1187</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>1231</td>\n",
+       "      <td>1410</td>\n",
+       "      <td>1028</td>\n",
+       "      <td>1833</td>\n",
+       "      <td>1253</td>\n",
+       "      <td>723</td>\n",
+       "      <td>11133</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2020-01-31 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11612</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12206</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11419</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>760</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1461</td>\n",
+       "      <td>1136</td>\n",
+       "      <td>1015</td>\n",
+       "      <td>1262</td>\n",
+       "      <td>1286</td>\n",
+       "      <td>1092</td>\n",
+       "      <td>1820</td>\n",
+       "      <td>1233</td>\n",
+       "      <td>727</td>\n",
+       "      <td>10885</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 92 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Week ended  NaN  NaN Total deaths, all ages  \\\n",
+       "1  2020-01-03 00:00:00  NaN  NaN                  12254   \n",
+       "2  2020-01-10 00:00:00  NaN  NaN                  14058   \n",
+       "3  2020-01-17 00:00:00  NaN  NaN                  12990   \n",
+       "4  2020-01-24 00:00:00  NaN  NaN                  11856   \n",
+       "5  2020-01-31 00:00:00  NaN  NaN                  11612   \n",
+       "\n",
+       "  Total deaths: average of corresponding  \\\n",
+       "1                                    NaN   \n",
+       "2                                    NaN   \n",
+       "3                                    NaN   \n",
+       "4                                    NaN   \n",
+       "5                                    NaN   \n",
+       "\n",
+       "  week over the previous 5 years 1, 10, 11 (England and Wales)  \\\n",
+       "1                                              12175             \n",
+       "2                                              13822             \n",
+       "3                                              13216             \n",
+       "4                                              12760             \n",
+       "5                                              12206             \n",
+       "\n",
+       "  Total deaths: average of corresponding  \\\n",
+       "1                                    NaN   \n",
+       "2                                    NaN   \n",
+       "3                                    NaN   \n",
+       "4                                    NaN   \n",
+       "5                                    NaN   \n",
+       "\n",
+       "  week over the previous 5 years 1, 10, 11 (England)  \\\n",
+       "1                                              11412   \n",
+       "2                                              12933   \n",
+       "3                                              12370   \n",
+       "4                                              11933   \n",
+       "5                                              11419   \n",
+       "\n",
+       "  Total deaths: average of corresponding  \\\n",
+       "1                                    NaN   \n",
+       "2                                    NaN   \n",
+       "3                                    NaN   \n",
+       "4                                    NaN   \n",
+       "5                                    NaN   \n",
+       "\n",
+       "  week over the previous 5 years 1, 10, 11 (Wales)  ... North West  \\\n",
+       "1                                              756  ...       1806   \n",
+       "2                                              856  ...       1932   \n",
+       "3                                              812  ...       1696   \n",
+       "4                                              802  ...       1529   \n",
+       "5                                              760  ...       1461   \n",
+       "\n",
+       "  Yorkshire and The Humber East Midlands West Midlands  East London  \\\n",
+       "1                     1240          1060          1349  1162   1113   \n",
+       "2                     1339          1195          1450  1573   1272   \n",
+       "3                     1278          1106          1407  1457   1073   \n",
+       "4                     1187          1024          1231  1410   1028   \n",
+       "5                     1136          1015          1262  1286   1092   \n",
+       "\n",
+       "  South East South West Wales England deaths  \n",
+       "1       1814       1225   787          11467  \n",
+       "2       2132       1487   939          13119  \n",
+       "3       2064       1466   767          12223  \n",
+       "4       1833       1253   723          11133  \n",
+       "5       1820       1233   727          10885  \n",
+       "\n",
+       "[5 rows x 92 columns]"
+      ]
+     },
+     "execution_count": 50,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "eng_xls.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-01-03 00:00:00</td>\n",
+       "      <td>11467</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2020-01-10 00:00:00</td>\n",
+       "      <td>13119</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2020-01-17 00:00:00</td>\n",
+       "      <td>12223</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2020-01-24 00:00:00</td>\n",
+       "      <td>11133</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2020-01-31 00:00:00</td>\n",
+       "      <td>10885</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week           date_up_to deaths  year   nation\n",
+       "0     1  2020-01-03 00:00:00  11467  2020  England\n",
+       "1     2  2020-01-10 00:00:00  13119  2020  England\n",
+       "2     3  2020-01-17 00:00:00  12223  2020  England\n",
+       "3     4  2020-01-24 00:00:00  11133  2020  England\n",
+       "4     5  2020-01-31 00:00:00  10885  2020  England"
+      ]
+     },
+     "execution_count": 51,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = eng_xls[['Week ended', 'England deaths']].reset_index(level=0).rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'England deaths': 'deaths',\n",
+    "            'index': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2020\n",
+    "rd['nation'] = 'England'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "0 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[]"
+      ]
+     },
+     "execution_count": 52,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql delete from all_causes_deaths where nation = 'England'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>49</td>\n",
+       "      <td>2020-12-04 00:00:00</td>\n",
+       "      <td>11467</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>50</td>\n",
+       "      <td>2020-12-11 00:00:00</td>\n",
+       "      <td>11478</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>51</td>\n",
+       "      <td>2020-12-18 00:00:00</td>\n",
+       "      <td>12129</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>52</td>\n",
+       "      <td>2020-12-25 00:00:00</td>\n",
+       "      <td>10695</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>53</td>\n",
+       "      <td>2021-01-01 00:00:00</td>\n",
+       "      <td>9342</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    week           date_up_to deaths  year   nation\n",
+       "48    49  2020-12-04 00:00:00  11467  2020  England\n",
+       "49    50  2020-12-11 00:00:00  11478  2020  England\n",
+       "50    51  2020-12-18 00:00:00  12129  2020  England\n",
+       "51    52  2020-12-25 00:00:00  10695  2020  England\n",
+       "52    53  2021-01-01 00:00:00   9342  2020  England"
+      ]
+     },
+     "execution_count": 54,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "14 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>England</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2020, 'England', 53),\n",
+       " (2015, 'Northern Ireland', 53),\n",
+       " (2016, 'Northern Ireland', 52),\n",
+       " (2017, 'Northern Ireland', 52),\n",
+       " (2018, 'Northern Ireland', 52),\n",
+       " (2019, 'Northern Ireland', 52),\n",
+       " (2020, 'Northern Ireland', 53),\n",
+       " (2015, 'Scotland', 53),\n",
+       " (2016, 'Scotland', 52),\n",
+       " (2017, 'Scotland', 52),\n",
+       " (2018, 'Scotland', 52),\n",
+       " (2019, 'Scotland', 52),\n",
+       " (2020, 'Scotland', 53),\n",
+       " (2020, 'Wales', 53)]"
+      ]
+     },
+     "execution_count": 55,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# raw_data_2020 = pd.read_csv('uk-deaths-data/publishedweek272020.csv', \n",
+    "#                        parse_dates=[1], dayfirst=True,\n",
+    "#                       index_col=0,\n",
+    "#                       header=[0, 1])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# raw_data_2020.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# raw_data_2020['W92000004', 'Wales']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "raw_data_2019 = pd.read_csv('uk-deaths-data/publishedweek522019.csv', \n",
+    "                       parse_dates=[1], dayfirst=True,\n",
+    "#                       index_col=0,\n",
+    "                      header=[0, 1])\n",
+    "# raw_data_2019.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Week number</th>\n",
+       "      <th>Week ended</th>\n",
+       "      <th>Total deaths, all ages</th>\n",
+       "      <th>W92000004</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2019-01-04</td>\n",
+       "      <td>10955</td>\n",
+       "      <td>718</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2019-01-11</td>\n",
+       "      <td>12609</td>\n",
+       "      <td>809</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2019-01-18</td>\n",
+       "      <td>11860</td>\n",
+       "      <td>683</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2019-01-25</td>\n",
+       "      <td>11740</td>\n",
+       "      <td>734</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2019-02-01</td>\n",
+       "      <td>11297</td>\n",
+       "      <td>745</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Week number Week ended  Total deaths, all ages  W92000004\n",
+       "0            1 2019-01-04                   10955        718\n",
+       "1            2 2019-01-11                   12609        809\n",
+       "2            3 2019-01-18                   11860        683\n",
+       "3            4 2019-01-25                   11740        734\n",
+       "4            5 2019-02-01                   11297        745"
+      ]
+     },
+     "execution_count": 60,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rdew = raw_data_2019.iloc[:, [0, 1, 2, -1]].droplevel(axis=1, level=1)\n",
+    "rdew.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2019-01-04</td>\n",
+       "      <td>718</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2019-01-11</td>\n",
+       "      <td>809</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2019-01-18</td>\n",
+       "      <td>683</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2019-01-25</td>\n",
+       "      <td>734</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2019-02-01</td>\n",
+       "      <td>745</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week date_up_to  deaths  year nation\n",
+       "0     1 2019-01-04     718  2019  Wales\n",
+       "1     2 2019-01-11     809  2019  Wales\n",
+       "2     3 2019-01-18     683  2019  Wales\n",
+       "3     4 2019-01-25     734  2019  Wales\n",
+       "4     5 2019-02-01     745  2019  Wales"
+      ]
+     },
+     "execution_count": 61,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = rdew.drop(columns=['Total deaths, all ages']).rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'W92000004': 'deaths',\n",
+    "            'Week number': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2019\n",
+    "rd['nation'] = 'Wales'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>week</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2019-01-04</td>\n",
+       "      <td>1</td>\n",
+       "      <td>10237</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2019-01-11</td>\n",
+       "      <td>2</td>\n",
+       "      <td>11800</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2019-01-18</td>\n",
+       "      <td>3</td>\n",
+       "      <td>11177</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2019-01-25</td>\n",
+       "      <td>4</td>\n",
+       "      <td>11006</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2019-02-01</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10552</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  date_up_to  week  deaths  year   nation\n",
+       "0 2019-01-04     1   10237  2019  England\n",
+       "1 2019-01-11     2   11800  2019  England\n",
+       "2 2019-01-18     3   11177  2019  England\n",
+       "3 2019-01-25     4   11006  2019  England\n",
+       "4 2019-02-01     5   10552  2019  England"
+      ]
+     },
+     "execution_count": 63,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = rdew.loc[:, ['Week ended','Week number']]\n",
+    "rd['deaths'] = rdew['Total deaths, all ages'] - rdew['W92000004']\n",
+    "rd = rd.rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'Week number': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2019\n",
+    "rd['nation'] = 'England'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "16 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>England</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2019, 'England', 52),\n",
+       " (2020, 'England', 53),\n",
+       " (2015, 'Northern Ireland', 53),\n",
+       " (2016, 'Northern Ireland', 52),\n",
+       " (2017, 'Northern Ireland', 52),\n",
+       " (2018, 'Northern Ireland', 52),\n",
+       " (2019, 'Northern Ireland', 52),\n",
+       " (2020, 'Northern Ireland', 53),\n",
+       " (2015, 'Scotland', 53),\n",
+       " (2016, 'Scotland', 52),\n",
+       " (2017, 'Scotland', 52),\n",
+       " (2018, 'Scotland', 52),\n",
+       " (2019, 'Scotland', 52),\n",
+       " (2020, 'Scotland', 53),\n",
+       " (2019, 'Wales', 52),\n",
+       " (2020, 'Wales', 53)]"
+      ]
+     },
+     "execution_count": 65,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "raw_data_2018 = pd.read_csv('uk-deaths-data/publishedweek522018.csv', \n",
+    "                       parse_dates=[1], dayfirst=True,\n",
+    "#                       index_col=0,\n",
+    "                      header=[0, 1])\n",
+    "# raw_data_2018.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Week number</th>\n",
+       "      <th>Week ended</th>\n",
+       "      <th>Total deaths, all ages</th>\n",
+       "      <th>W92000004</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2018-01-05</td>\n",
+       "      <td>12723</td>\n",
+       "      <td>783</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2018-01-12</td>\n",
+       "      <td>15050</td>\n",
+       "      <td>904</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2018-01-19</td>\n",
+       "      <td>14256</td>\n",
+       "      <td>885</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2018-01-26</td>\n",
+       "      <td>13935</td>\n",
+       "      <td>850</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2018-02-02</td>\n",
+       "      <td>13285</td>\n",
+       "      <td>815</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Week number Week ended  Total deaths, all ages  W92000004\n",
+       "0            1 2018-01-05                   12723        783\n",
+       "1            2 2018-01-12                   15050        904\n",
+       "2            3 2018-01-19                   14256        885\n",
+       "3            4 2018-01-26                   13935        850\n",
+       "4            5 2018-02-02                   13285        815"
+      ]
+     },
+     "execution_count": 67,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rdew = raw_data_2018.iloc[:, [0, 1, 2, -1]].droplevel(axis=1, level=1)\n",
+    "rdew.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2018-01-05</td>\n",
+       "      <td>783</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2018-01-12</td>\n",
+       "      <td>904</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2018-01-19</td>\n",
+       "      <td>885</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2018-01-26</td>\n",
+       "      <td>850</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2018-02-02</td>\n",
+       "      <td>815</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week date_up_to  deaths  year nation\n",
+       "0     1 2018-01-05     783  2018  Wales\n",
+       "1     2 2018-01-12     904  2018  Wales\n",
+       "2     3 2018-01-19     885  2018  Wales\n",
+       "3     4 2018-01-26     850  2018  Wales\n",
+       "4     5 2018-02-02     815  2018  Wales"
+      ]
+     },
+     "execution_count": 68,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = rdew.drop(columns=['Total deaths, all ages']).rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'W92000004': 'deaths',\n",
+    "            'Week number': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2018\n",
+    "rd['nation'] = 'Wales'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>week</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2018-01-05</td>\n",
+       "      <td>1</td>\n",
+       "      <td>11940</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2018-01-12</td>\n",
+       "      <td>2</td>\n",
+       "      <td>14146</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2018-01-19</td>\n",
+       "      <td>3</td>\n",
+       "      <td>13371</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2018-01-26</td>\n",
+       "      <td>4</td>\n",
+       "      <td>13085</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2018-02-02</td>\n",
+       "      <td>5</td>\n",
+       "      <td>12470</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  date_up_to  week  deaths  year   nation\n",
+       "0 2018-01-05     1   11940  2018  England\n",
+       "1 2018-01-12     2   14146  2018  England\n",
+       "2 2018-01-19     3   13371  2018  England\n",
+       "3 2018-01-26     4   13085  2018  England\n",
+       "4 2018-02-02     5   12470  2018  England"
+      ]
+     },
+     "execution_count": 70,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = rdew.loc[:, ['Week ended','Week number']]\n",
+    "rd['deaths'] = rdew['Total deaths, all ages'] - rdew['W92000004']\n",
+    "rd = rd.rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'Week number': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2018\n",
+    "rd['nation'] = 'England'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "18 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>England</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2018, 'England', 52),\n",
+       " (2019, 'England', 52),\n",
+       " (2020, 'England', 53),\n",
+       " (2015, 'Northern Ireland', 53),\n",
+       " (2016, 'Northern Ireland', 52),\n",
+       " (2017, 'Northern Ireland', 52),\n",
+       " (2018, 'Northern Ireland', 52),\n",
+       " (2019, 'Northern Ireland', 52),\n",
+       " (2020, 'Northern Ireland', 53),\n",
+       " (2015, 'Scotland', 53),\n",
+       " (2016, 'Scotland', 52),\n",
+       " (2017, 'Scotland', 52),\n",
+       " (2018, 'Scotland', 52),\n",
+       " (2019, 'Scotland', 52),\n",
+       " (2020, 'Scotland', 53),\n",
+       " (2018, 'Wales', 52),\n",
+       " (2019, 'Wales', 52),\n",
+       " (2020, 'Wales', 53)]"
+      ]
+     },
+     "execution_count": 72,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "raw_data_2017 = pd.read_csv('uk-deaths-data/publishedweek522017.csv', \n",
+    "                       parse_dates=[1], dayfirst=True,\n",
+    "#                       index_col=0,\n",
+    "                      header=[0, 1])\n",
+    "# raw_data_2017.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Week number</th>\n",
+       "      <th>Week ended</th>\n",
+       "      <th>Total deaths, all ages</th>\n",
+       "      <th>W92000004</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2017-01-06</td>\n",
+       "      <td>11991</td>\n",
+       "      <td>744</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2017-01-13</td>\n",
+       "      <td>13715</td>\n",
+       "      <td>825</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2017-01-20</td>\n",
+       "      <td>13610</td>\n",
+       "      <td>835</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2017-01-27</td>\n",
+       "      <td>12877</td>\n",
+       "      <td>881</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2017-02-03</td>\n",
+       "      <td>12485</td>\n",
+       "      <td>749</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Week number Week ended  Total deaths, all ages  W92000004\n",
+       "0            1 2017-01-06                   11991        744\n",
+       "1            2 2017-01-13                   13715        825\n",
+       "2            3 2017-01-20                   13610        835\n",
+       "3            4 2017-01-27                   12877        881\n",
+       "4            5 2017-02-03                   12485        749"
+      ]
+     },
+     "execution_count": 74,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rdew = raw_data_2017.iloc[:, [0, 1, 2, -1]].droplevel(axis=1, level=1)\n",
+    "rdew.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2017-01-06</td>\n",
+       "      <td>744</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2017-01-13</td>\n",
+       "      <td>825</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2017-01-20</td>\n",
+       "      <td>835</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2017-01-27</td>\n",
+       "      <td>881</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2017-02-03</td>\n",
+       "      <td>749</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week date_up_to  deaths  year nation\n",
+       "0     1 2017-01-06     744  2017  Wales\n",
+       "1     2 2017-01-13     825  2017  Wales\n",
+       "2     3 2017-01-20     835  2017  Wales\n",
+       "3     4 2017-01-27     881  2017  Wales\n",
+       "4     5 2017-02-03     749  2017  Wales"
+      ]
+     },
+     "execution_count": 75,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = rdew.drop(columns=['Total deaths, all ages']).rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'W92000004': 'deaths',\n",
+    "            'Week number': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2017\n",
+    "rd['nation'] = 'Wales'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>week</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2017-01-06</td>\n",
+       "      <td>1</td>\n",
+       "      <td>11247</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2017-01-13</td>\n",
+       "      <td>2</td>\n",
+       "      <td>12890</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2017-01-20</td>\n",
+       "      <td>3</td>\n",
+       "      <td>12775</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2017-01-27</td>\n",
+       "      <td>4</td>\n",
+       "      <td>11996</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2017-02-03</td>\n",
+       "      <td>5</td>\n",
+       "      <td>11736</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  date_up_to  week  deaths  year   nation\n",
+       "0 2017-01-06     1   11247  2017  England\n",
+       "1 2017-01-13     2   12890  2017  England\n",
+       "2 2017-01-20     3   12775  2017  England\n",
+       "3 2017-01-27     4   11996  2017  England\n",
+       "4 2017-02-03     5   11736  2017  England"
+      ]
+     },
+     "execution_count": 77,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = rdew.loc[:, ['Week ended','Week number']]\n",
+    "rd['deaths'] = rdew['Total deaths, all ages'] - rdew['W92000004']\n",
+    "rd = rd.rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'Week number': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2017\n",
+    "rd['nation'] = 'England'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "20 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>England</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2017, 'England', 52),\n",
+       " (2018, 'England', 52),\n",
+       " (2019, 'England', 52),\n",
+       " (2020, 'England', 53),\n",
+       " (2015, 'Northern Ireland', 53),\n",
+       " (2016, 'Northern Ireland', 52),\n",
+       " (2017, 'Northern Ireland', 52),\n",
+       " (2018, 'Northern Ireland', 52),\n",
+       " (2019, 'Northern Ireland', 52),\n",
+       " (2020, 'Northern Ireland', 53),\n",
+       " (2015, 'Scotland', 53),\n",
+       " (2016, 'Scotland', 52),\n",
+       " (2017, 'Scotland', 52),\n",
+       " (2018, 'Scotland', 52),\n",
+       " (2019, 'Scotland', 52),\n",
+       " (2020, 'Scotland', 53),\n",
+       " (2017, 'Wales', 52),\n",
+       " (2018, 'Wales', 52),\n",
+       " (2019, 'Wales', 52),\n",
+       " (2020, 'Wales', 53)]"
+      ]
+     },
+     "execution_count": 79,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "raw_data_2016 = pd.read_csv('uk-deaths-data/publishedweek522016.csv', \n",
+    "                       parse_dates=[1], dayfirst=True,\n",
+    "#                       index_col=0,\n",
+    "                      header=[0, 1])\n",
+    "# raw_data_2016.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead tr th {\n",
+       "        text-align: left;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th>Week number</th>\n",
+       "      <th>Week ended</th>\n",
+       "      <th>Total deaths, all ages</th>\n",
+       "      <th>Total deaths: average of corresponding</th>\n",
+       "      <th>Unnamed: 4_level_0</th>\n",
+       "      <th>Unnamed: 5_level_0</th>\n",
+       "      <th>Persons</th>\n",
+       "      <th>Unnamed: 7_level_0</th>\n",
+       "      <th>Unnamed: 8_level_0</th>\n",
+       "      <th>Unnamed: 9_level_0</th>\n",
+       "      <th>...</th>\n",
+       "      <th>E12000001</th>\n",
+       "      <th>E12000002</th>\n",
+       "      <th>E12000003</th>\n",
+       "      <th>E12000004</th>\n",
+       "      <th>E12000005</th>\n",
+       "      <th>E12000006</th>\n",
+       "      <th>E12000007</th>\n",
+       "      <th>E12000008</th>\n",
+       "      <th>E12000009</th>\n",
+       "      <th>W92000004</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th>Unnamed: 0_level_1</th>\n",
+       "      <th>Unnamed: 1_level_1</th>\n",
+       "      <th>Unnamed: 2_level_1</th>\n",
+       "      <th>Unnamed: 3_level_1</th>\n",
+       "      <th>Deaths by underlying cause</th>\n",
+       "      <th>All respiratory diseases (ICD-10 J00-J99)\\nICD-10 v 2013 (IRIS)</th>\n",
+       "      <th>Deaths by age group</th>\n",
+       "      <th>Under 1 year</th>\n",
+       "      <th>01-14</th>\n",
+       "      <th>15-44</th>\n",
+       "      <th>...</th>\n",
+       "      <th>North East</th>\n",
+       "      <th>North West</th>\n",
+       "      <th>Yorkshire and The Humber</th>\n",
+       "      <th>East Midlands</th>\n",
+       "      <th>West Midlands</th>\n",
+       "      <th>East</th>\n",
+       "      <th>London</th>\n",
+       "      <th>South East</th>\n",
+       "      <th>South West</th>\n",
+       "      <th>Wales</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2016-01-08</td>\n",
+       "      <td>13045</td>\n",
+       "      <td>11701.4</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2046</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>49</td>\n",
+       "      <td>17</td>\n",
+       "      <td>299</td>\n",
+       "      <td>...</td>\n",
+       "      <td>705</td>\n",
+       "      <td>1748</td>\n",
+       "      <td>1284</td>\n",
+       "      <td>1067</td>\n",
+       "      <td>1396</td>\n",
+       "      <td>1401</td>\n",
+       "      <td>1226</td>\n",
+       "      <td>1951</td>\n",
+       "      <td>1424</td>\n",
+       "      <td>809</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2016-01-15</td>\n",
+       "      <td>11501</td>\n",
+       "      <td>13016.4</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1835</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>64</td>\n",
+       "      <td>24</td>\n",
+       "      <td>326</td>\n",
+       "      <td>...</td>\n",
+       "      <td>600</td>\n",
+       "      <td>1532</td>\n",
+       "      <td>1148</td>\n",
+       "      <td>956</td>\n",
+       "      <td>1208</td>\n",
+       "      <td>1237</td>\n",
+       "      <td>1048</td>\n",
+       "      <td>1771</td>\n",
+       "      <td>1263</td>\n",
+       "      <td>711</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2016-01-22</td>\n",
+       "      <td>11473</td>\n",
+       "      <td>11765.4</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1775</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>50</td>\n",
+       "      <td>18</td>\n",
+       "      <td>345</td>\n",
+       "      <td>...</td>\n",
+       "      <td>612</td>\n",
+       "      <td>1602</td>\n",
+       "      <td>1119</td>\n",
+       "      <td>929</td>\n",
+       "      <td>1209</td>\n",
+       "      <td>1253</td>\n",
+       "      <td>1068</td>\n",
+       "      <td>1710</td>\n",
+       "      <td>1219</td>\n",
+       "      <td>720</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2016-01-29</td>\n",
+       "      <td>11317</td>\n",
+       "      <td>11289.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1810</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>47</td>\n",
+       "      <td>14</td>\n",
+       "      <td>324</td>\n",
+       "      <td>...</td>\n",
+       "      <td>631</td>\n",
+       "      <td>1516</td>\n",
+       "      <td>1131</td>\n",
+       "      <td>858</td>\n",
+       "      <td>1195</td>\n",
+       "      <td>1236</td>\n",
+       "      <td>1065</td>\n",
+       "      <td>1730</td>\n",
+       "      <td>1207</td>\n",
+       "      <td>717</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2016-02-05</td>\n",
+       "      <td>11052</td>\n",
+       "      <td>10965.6</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1748</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>60</td>\n",
+       "      <td>22</td>\n",
+       "      <td>314</td>\n",
+       "      <td>...</td>\n",
+       "      <td>620</td>\n",
+       "      <td>1459</td>\n",
+       "      <td>1109</td>\n",
+       "      <td>954</td>\n",
+       "      <td>1197</td>\n",
+       "      <td>1160</td>\n",
+       "      <td>1059</td>\n",
+       "      <td>1604</td>\n",
+       "      <td>1169</td>\n",
+       "      <td>690</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 41 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         Week number         Week ended Total deaths, all ages  \\\n",
+       "  Unnamed: 0_level_1 Unnamed: 1_level_1     Unnamed: 2_level_1   \n",
+       "0                  1         2016-01-08                  13045   \n",
+       "1                  2         2016-01-15                  11501   \n",
+       "2                  3         2016-01-22                  11473   \n",
+       "3                  4         2016-01-29                  11317   \n",
+       "4                  5         2016-02-05                  11052   \n",
+       "\n",
+       "  Total deaths: average of corresponding         Unnamed: 4_level_0  \\\n",
+       "                      Unnamed: 3_level_1 Deaths by underlying cause   \n",
+       "0                                11701.4                        NaN   \n",
+       "1                                13016.4                        NaN   \n",
+       "2                                11765.4                        NaN   \n",
+       "3                                11289.0                        NaN   \n",
+       "4                                10965.6                        NaN   \n",
+       "\n",
+       "                                               Unnamed: 5_level_0  \\\n",
+       "  All respiratory diseases (ICD-10 J00-J99)\\nICD-10 v 2013 (IRIS)   \n",
+       "0                                               2046                \n",
+       "1                                               1835                \n",
+       "2                                               1775                \n",
+       "3                                               1810                \n",
+       "4                                               1748                \n",
+       "\n",
+       "              Persons Unnamed: 7_level_0 Unnamed: 8_level_0  \\\n",
+       "  Deaths by age group       Under 1 year              01-14   \n",
+       "0                 NaN                 49                 17   \n",
+       "1                 NaN                 64                 24   \n",
+       "2                 NaN                 50                 18   \n",
+       "3                 NaN                 47                 14   \n",
+       "4                 NaN                 60                 22   \n",
+       "\n",
+       "  Unnamed: 9_level_0  ...  E12000001  E12000002                E12000003  \\\n",
+       "               15-44  ... North East North West Yorkshire and The Humber   \n",
+       "0                299  ...        705       1748                     1284   \n",
+       "1                326  ...        600       1532                     1148   \n",
+       "2                345  ...        612       1602                     1119   \n",
+       "3                324  ...        631       1516                     1131   \n",
+       "4                314  ...        620       1459                     1109   \n",
+       "\n",
+       "      E12000004     E12000005 E12000006 E12000007  E12000008  E12000009  \\\n",
+       "  East Midlands West Midlands      East    London South East South West   \n",
+       "0          1067          1396      1401      1226       1951       1424   \n",
+       "1           956          1208      1237      1048       1771       1263   \n",
+       "2           929          1209      1253      1068       1710       1219   \n",
+       "3           858          1195      1236      1065       1730       1207   \n",
+       "4           954          1197      1160      1059       1604       1169   \n",
+       "\n",
+       "  W92000004  \n",
+       "      Wales  \n",
+       "0       809  \n",
+       "1       711  \n",
+       "2       720  \n",
+       "3       717  \n",
+       "4       690  \n",
+       "\n",
+       "[5 rows x 41 columns]"
+      ]
+     },
+     "execution_count": 81,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data_2016.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Week number</th>\n",
+       "      <th>Week ended</th>\n",
+       "      <th>Total deaths, all ages</th>\n",
+       "      <th>W92000004</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2016-01-08</td>\n",
+       "      <td>13045</td>\n",
+       "      <td>809</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2016-01-15</td>\n",
+       "      <td>11501</td>\n",
+       "      <td>711</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2016-01-22</td>\n",
+       "      <td>11473</td>\n",
+       "      <td>720</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2016-01-29</td>\n",
+       "      <td>11317</td>\n",
+       "      <td>717</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2016-02-05</td>\n",
+       "      <td>11052</td>\n",
+       "      <td>690</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Week number Week ended  Total deaths, all ages  W92000004\n",
+       "0            1 2016-01-08                   13045        809\n",
+       "1            2 2016-01-15                   11501        711\n",
+       "2            3 2016-01-22                   11473        720\n",
+       "3            4 2016-01-29                   11317        717\n",
+       "4            5 2016-02-05                   11052        690"
+      ]
+     },
+     "execution_count": 82,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rdew = raw_data_2016.iloc[:, [0, 1, 2, -1]].droplevel(axis=1, level=1)\n",
+    "rdew.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 83,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2016-01-08</td>\n",
+       "      <td>809</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2016-01-15</td>\n",
+       "      <td>711</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2016-01-22</td>\n",
+       "      <td>720</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2016-01-29</td>\n",
+       "      <td>717</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2016-02-05</td>\n",
+       "      <td>690</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week date_up_to  deaths  year nation\n",
+       "0     1 2016-01-08     809  2016  Wales\n",
+       "1     2 2016-01-15     711  2016  Wales\n",
+       "2     3 2016-01-22     720  2016  Wales\n",
+       "3     4 2016-01-29     717  2016  Wales\n",
+       "4     5 2016-02-05     690  2016  Wales"
+      ]
+     },
+     "execution_count": 83,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = rdew.drop(columns=['Total deaths, all ages']).rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'W92000004': 'deaths',\n",
+    "            'Week number': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2016\n",
+    "rd['nation'] = 'Wales'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>week</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2016-01-08</td>\n",
+       "      <td>1</td>\n",
+       "      <td>12236</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2016-01-15</td>\n",
+       "      <td>2</td>\n",
+       "      <td>10790</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2016-01-22</td>\n",
+       "      <td>3</td>\n",
+       "      <td>10753</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2016-01-29</td>\n",
+       "      <td>4</td>\n",
+       "      <td>10600</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2016-02-05</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10362</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  date_up_to  week  deaths  year   nation\n",
+       "0 2016-01-08     1   12236  2016  England\n",
+       "1 2016-01-15     2   10790  2016  England\n",
+       "2 2016-01-22     3   10753  2016  England\n",
+       "3 2016-01-29     4   10600  2016  England\n",
+       "4 2016-02-05     5   10362  2016  England"
+      ]
+     },
+     "execution_count": 85,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = rdew.loc[:, ['Week ended','Week number']]\n",
+    "rd['deaths'] = rdew['Total deaths, all ages'] - rdew['W92000004']\n",
+    "rd = rd.rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'Week number': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2016\n",
+    "rd['nation'] = 'England'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "22 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>England</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2016, 'England', 52),\n",
+       " (2017, 'England', 52),\n",
+       " (2018, 'England', 52),\n",
+       " (2019, 'England', 52),\n",
+       " (2020, 'England', 53),\n",
+       " (2015, 'Northern Ireland', 53),\n",
+       " (2016, 'Northern Ireland', 52),\n",
+       " (2017, 'Northern Ireland', 52),\n",
+       " (2018, 'Northern Ireland', 52),\n",
+       " (2019, 'Northern Ireland', 52),\n",
+       " (2020, 'Northern Ireland', 53),\n",
+       " (2015, 'Scotland', 53),\n",
+       " (2016, 'Scotland', 52),\n",
+       " (2017, 'Scotland', 52),\n",
+       " (2018, 'Scotland', 52),\n",
+       " (2019, 'Scotland', 52),\n",
+       " (2020, 'Scotland', 53),\n",
+       " (2016, 'Wales', 52),\n",
+       " (2017, 'Wales', 52),\n",
+       " (2018, 'Wales', 52),\n",
+       " (2019, 'Wales', 52),\n",
+       " (2020, 'Wales', 53)]"
+      ]
+     },
+     "execution_count": 87,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    " %sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "raw_data_2015 = pd.read_csv('uk-deaths-data/publishedweek2015.csv', \n",
+    "                       parse_dates=[1], dayfirst=True,\n",
+    "#                       index_col=0,\n",
+    "                      header=[0, 1])\n",
+    "# raw_data_2015.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Week number</th>\n",
+       "      <th>Week ended</th>\n",
+       "      <th>Total deaths, all ages</th>\n",
+       "      <th>W92000004</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2015-01-02</td>\n",
+       "      <td>12286</td>\n",
+       "      <td>725</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2015-01-09</td>\n",
+       "      <td>16237</td>\n",
+       "      <td>1031</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2015-01-16</td>\n",
+       "      <td>14866</td>\n",
+       "      <td>936</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2015-01-23</td>\n",
+       "      <td>13934</td>\n",
+       "      <td>828</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2015-01-30</td>\n",
+       "      <td>12900</td>\n",
+       "      <td>801</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Week number Week ended  Total deaths, all ages  W92000004\n",
+       "0            1 2015-01-02                   12286        725\n",
+       "1            2 2015-01-09                   16237       1031\n",
+       "2            3 2015-01-16                   14866        936\n",
+       "3            4 2015-01-23                   13934        828\n",
+       "4            5 2015-01-30                   12900        801"
+      ]
+     },
+     "execution_count": 89,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rdew = raw_data_2015.iloc[:, [0, 1, 2, -1]].droplevel(axis=1, level=1)\n",
+    "rdew.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 90,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2015-01-02</td>\n",
+       "      <td>725</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2015-01-09</td>\n",
+       "      <td>1031</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2015-01-16</td>\n",
+       "      <td>936</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2015-01-23</td>\n",
+       "      <td>828</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2015-01-30</td>\n",
+       "      <td>801</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week date_up_to  deaths  year nation\n",
+       "0     1 2015-01-02     725  2015  Wales\n",
+       "1     2 2015-01-09    1031  2015  Wales\n",
+       "2     3 2015-01-16     936  2015  Wales\n",
+       "3     4 2015-01-23     828  2015  Wales\n",
+       "4     5 2015-01-30     801  2015  Wales"
+      ]
+     },
+     "execution_count": 90,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = rdew.drop(columns=['Total deaths, all ages']).rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'W92000004': 'deaths',\n",
+    "            'Week number': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2015\n",
+    "rd['nation'] = 'Wales'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 92,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>week</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2015-01-02</td>\n",
+       "      <td>1</td>\n",
+       "      <td>11561</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2015-01-09</td>\n",
+       "      <td>2</td>\n",
+       "      <td>15206</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2015-01-16</td>\n",
+       "      <td>3</td>\n",
+       "      <td>13930</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2015-01-23</td>\n",
+       "      <td>4</td>\n",
+       "      <td>13106</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2015-01-30</td>\n",
+       "      <td>5</td>\n",
+       "      <td>12099</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>England</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  date_up_to  week  deaths  year   nation\n",
+       "0 2015-01-02     1   11561  2015  England\n",
+       "1 2015-01-09     2   15206  2015  England\n",
+       "2 2015-01-16     3   13930  2015  England\n",
+       "3 2015-01-23     4   13106  2015  England\n",
+       "4 2015-01-30     5   12099  2015  England"
+      ]
+     },
+     "execution_count": 92,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = rdew.loc[:, ['Week ended','Week number']]\n",
+    "rd['deaths'] = rdew['Total deaths, all ages'] - rdew['W92000004']\n",
+    "rd = rd.rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'Week number': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2015\n",
+    "rd['nation'] = 'England'\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 93,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    conn,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 94,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "24 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>year</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>England</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2015</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2016</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2017</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2018</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>England</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2019</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>52</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>England</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2020</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>53</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(2015, 'England', 53),\n",
+       " (2015, 'Northern Ireland', 53),\n",
+       " (2015, 'Scotland', 53),\n",
+       " (2015, 'Wales', 53),\n",
+       " (2016, 'England', 52),\n",
+       " (2016, 'Northern Ireland', 52),\n",
+       " (2016, 'Scotland', 52),\n",
+       " (2016, 'Wales', 52),\n",
+       " (2017, 'England', 52),\n",
+       " (2017, 'Northern Ireland', 52),\n",
+       " (2017, 'Scotland', 52),\n",
+       " (2017, 'Wales', 52),\n",
+       " (2018, 'England', 52),\n",
+       " (2018, 'Northern Ireland', 52),\n",
+       " (2018, 'Scotland', 52),\n",
+       " (2018, 'Wales', 52),\n",
+       " (2019, 'England', 52),\n",
+       " (2019, 'Northern Ireland', 52),\n",
+       " (2019, 'Scotland', 52),\n",
+       " (2019, 'Wales', 52),\n",
+       " (2020, 'England', 53),\n",
+       " (2020, 'Northern Ireland', 53),\n",
+       " (2020, 'Scotland', 53),\n",
+       " (2020, 'Wales', 53)]"
+      ]
+     },
+     "execution_count": 94,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by year, nation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "314 rows affected.\n",
+      "Returning data to local variable res\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%sql res << select week, year, deaths\n",
+    "from all_causes_deaths\n",
+    "where nation = 'England'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 96,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>year</th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>2017</th>\n",
+       "      <th>2018</th>\n",
+       "      <th>2019</th>\n",
+       "      <th>2020</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>week</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>11561.0</td>\n",
+       "      <td>12236.0</td>\n",
+       "      <td>11247.0</td>\n",
+       "      <td>11940.0</td>\n",
+       "      <td>10237.0</td>\n",
+       "      <td>11467.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>15206.0</td>\n",
+       "      <td>10790.0</td>\n",
+       "      <td>12890.0</td>\n",
+       "      <td>14146.0</td>\n",
+       "      <td>11800.0</td>\n",
+       "      <td>13119.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>13930.0</td>\n",
+       "      <td>10753.0</td>\n",
+       "      <td>12775.0</td>\n",
+       "      <td>13371.0</td>\n",
+       "      <td>11177.0</td>\n",
+       "      <td>12223.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>13106.0</td>\n",
+       "      <td>10600.0</td>\n",
+       "      <td>11996.0</td>\n",
+       "      <td>13085.0</td>\n",
+       "      <td>11006.0</td>\n",
+       "      <td>11133.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>12099.0</td>\n",
+       "      <td>10362.0</td>\n",
+       "      <td>11736.0</td>\n",
+       "      <td>12470.0</td>\n",
+       "      <td>10552.0</td>\n",
+       "      <td>10885.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>11319.0</td>\n",
+       "      <td>10470.0</td>\n",
+       "      <td>11546.0</td>\n",
+       "      <td>11694.0</td>\n",
+       "      <td>10959.0</td>\n",
+       "      <td>10296.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>11112.0</td>\n",
+       "      <td>9933.0</td>\n",
+       "      <td>10954.0</td>\n",
+       "      <td>11443.0</td>\n",
+       "      <td>11076.0</td>\n",
+       "      <td>10216.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>10695.0</td>\n",
+       "      <td>10360.0</td>\n",
+       "      <td>11093.0</td>\n",
+       "      <td>11353.0</td>\n",
+       "      <td>10600.0</td>\n",
+       "      <td>10162.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>10736.0</td>\n",
+       "      <td>10564.0</td>\n",
+       "      <td>10533.0</td>\n",
+       "      <td>10220.0</td>\n",
+       "      <td>10360.0</td>\n",
+       "      <td>10165.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>10757.0</td>\n",
+       "      <td>10276.0</td>\n",
+       "      <td>10443.0</td>\n",
+       "      <td>12101.0</td>\n",
+       "      <td>10276.0</td>\n",
+       "      <td>10243.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>10290.0</td>\n",
+       "      <td>10284.0</td>\n",
+       "      <td>10044.0</td>\n",
+       "      <td>11870.0</td>\n",
+       "      <td>9901.0</td>\n",
+       "      <td>10344.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>9888.0</td>\n",
+       "      <td>8967.0</td>\n",
+       "      <td>9690.0</td>\n",
+       "      <td>11139.0</td>\n",
+       "      <td>9774.0</td>\n",
+       "      <td>9926.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>9827.0</td>\n",
+       "      <td>9574.0</td>\n",
+       "      <td>9369.0</td>\n",
+       "      <td>9308.0</td>\n",
+       "      <td>9213.0</td>\n",
+       "      <td>10422.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>8482.0</td>\n",
+       "      <td>10857.0</td>\n",
+       "      <td>9297.0</td>\n",
+       "      <td>10064.0</td>\n",
+       "      <td>9484.0</td>\n",
+       "      <td>15467.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>9429.0</td>\n",
+       "      <td>10679.0</td>\n",
+       "      <td>7916.0</td>\n",
+       "      <td>11558.0</td>\n",
+       "      <td>9654.0</td>\n",
+       "      <td>17588.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>10968.0</td>\n",
+       "      <td>10211.0</td>\n",
+       "      <td>8990.0</td>\n",
+       "      <td>10535.0</td>\n",
+       "      <td>8445.0</td>\n",
+       "      <td>21182.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>9937.0</td>\n",
+       "      <td>9784.0</td>\n",
+       "      <td>10181.0</td>\n",
+       "      <td>9692.0</td>\n",
+       "      <td>9381.0</td>\n",
+       "      <td>20873.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>9506.0</td>\n",
+       "      <td>8568.0</td>\n",
+       "      <td>8464.0</td>\n",
+       "      <td>9520.0</td>\n",
+       "      <td>10519.0</td>\n",
+       "      <td>17024.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>8273.0</td>\n",
+       "      <td>9985.0</td>\n",
+       "      <td>10006.0</td>\n",
+       "      <td>8094.0</td>\n",
+       "      <td>8455.0</td>\n",
+       "      <td>11965.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>9668.0</td>\n",
+       "      <td>9342.0</td>\n",
+       "      <td>9673.0</td>\n",
+       "      <td>9474.0</td>\n",
+       "      <td>9614.0</td>\n",
+       "      <td>13801.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>9391.0</td>\n",
+       "      <td>9115.0</td>\n",
+       "      <td>9438.0</td>\n",
+       "      <td>9033.0</td>\n",
+       "      <td>9657.0</td>\n",
+       "      <td>11596.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>7625.0</td>\n",
+       "      <td>7409.0</td>\n",
+       "      <td>7746.0</td>\n",
+       "      <td>7609.0</td>\n",
+       "      <td>7742.0</td>\n",
+       "      <td>9237.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>9509.0</td>\n",
+       "      <td>9289.0</td>\n",
+       "      <td>9182.0</td>\n",
+       "      <td>9343.0</td>\n",
+       "      <td>9514.0</td>\n",
+       "      <td>10009.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>8942.0</td>\n",
+       "      <td>8808.0</td>\n",
+       "      <td>8768.0</td>\n",
+       "      <td>8782.0</td>\n",
+       "      <td>8847.0</td>\n",
+       "      <td>9402.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>8717.0</td>\n",
+       "      <td>8807.0</td>\n",
+       "      <td>9019.0</td>\n",
+       "      <td>8694.0</td>\n",
+       "      <td>8916.0</td>\n",
+       "      <td>8722.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>8593.0</td>\n",
+       "      <td>8679.0</td>\n",
+       "      <td>8788.0</td>\n",
+       "      <td>8613.0</td>\n",
+       "      <td>8947.0</td>\n",
+       "      <td>8427.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>8670.0</td>\n",
+       "      <td>8614.0</td>\n",
+       "      <td>8707.0</td>\n",
+       "      <td>8633.0</td>\n",
+       "      <td>8528.0</td>\n",
+       "      <td>8556.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>8461.0</td>\n",
+       "      <td>8789.0</td>\n",
+       "      <td>8812.0</td>\n",
+       "      <td>8710.0</td>\n",
+       "      <td>8591.0</td>\n",
+       "      <td>8118.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>8228.0</td>\n",
+       "      <td>8790.0</td>\n",
+       "      <td>8562.0</td>\n",
+       "      <td>8579.0</td>\n",
+       "      <td>8527.0</td>\n",
+       "      <td>8273.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>8262.0</td>\n",
+       "      <td>8725.0</td>\n",
+       "      <td>8296.0</td>\n",
+       "      <td>8581.0</td>\n",
+       "      <td>8569.0</td>\n",
+       "      <td>8326.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>8071.0</td>\n",
+       "      <td>8602.0</td>\n",
+       "      <td>8351.0</td>\n",
+       "      <td>8587.0</td>\n",
+       "      <td>8701.0</td>\n",
+       "      <td>8415.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>8298.0</td>\n",
+       "      <td>8531.0</td>\n",
+       "      <td>8466.0</td>\n",
+       "      <td>8782.0</td>\n",
+       "      <td>8580.0</td>\n",
+       "      <td>8382.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>8600.0</td>\n",
+       "      <td>8496.0</td>\n",
+       "      <td>8707.0</td>\n",
+       "      <td>8312.0</td>\n",
+       "      <td>8504.0</td>\n",
+       "      <td>8775.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>8564.0</td>\n",
+       "      <td>8700.0</td>\n",
+       "      <td>8812.0</td>\n",
+       "      <td>8413.0</td>\n",
+       "      <td>8441.0</td>\n",
+       "      <td>9037.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>8423.0</td>\n",
+       "      <td>7453.0</td>\n",
+       "      <td>7594.0</td>\n",
+       "      <td>7354.0</td>\n",
+       "      <td>7684.0</td>\n",
+       "      <td>8441.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>7389.0</td>\n",
+       "      <td>8847.0</td>\n",
+       "      <td>8955.0</td>\n",
+       "      <td>8851.0</td>\n",
+       "      <td>9113.0</td>\n",
+       "      <td>7251.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>8704.0</td>\n",
+       "      <td>8548.0</td>\n",
+       "      <td>8845.0</td>\n",
+       "      <td>8612.0</td>\n",
+       "      <td>8946.0</td>\n",
+       "      <td>9233.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>8542.0</td>\n",
+       "      <td>8382.0</td>\n",
+       "      <td>8949.0</td>\n",
+       "      <td>8707.0</td>\n",
+       "      <td>8868.0</td>\n",
+       "      <td>8968.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>8865.0</td>\n",
+       "      <td>8402.0</td>\n",
+       "      <td>9096.0</td>\n",
+       "      <td>8590.0</td>\n",
+       "      <td>8906.0</td>\n",
+       "      <td>9017.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>8858.0</td>\n",
+       "      <td>8729.0</td>\n",
+       "      <td>9147.0</td>\n",
+       "      <td>8908.0</td>\n",
+       "      <td>9202.0</td>\n",
+       "      <td>9274.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>9124.0</td>\n",
+       "      <td>9132.0</td>\n",
+       "      <td>9300.0</td>\n",
+       "      <td>9043.0</td>\n",
+       "      <td>9383.0</td>\n",
+       "      <td>9316.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>8899.0</td>\n",
+       "      <td>9144.0</td>\n",
+       "      <td>9381.0</td>\n",
+       "      <td>9224.0</td>\n",
+       "      <td>9534.0</td>\n",
+       "      <td>9846.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>9104.0</td>\n",
+       "      <td>9100.0</td>\n",
+       "      <td>9131.0</td>\n",
+       "      <td>8970.0</td>\n",
+       "      <td>9351.0</td>\n",
+       "      <td>10078.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>9025.0</td>\n",
+       "      <td>9508.0</td>\n",
+       "      <td>9389.0</td>\n",
+       "      <td>8925.0</td>\n",
+       "      <td>9522.0</td>\n",
+       "      <td>10175.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>9388.0</td>\n",
+       "      <td>9844.0</td>\n",
+       "      <td>9748.0</td>\n",
+       "      <td>9509.0</td>\n",
+       "      <td>10044.0</td>\n",
+       "      <td>10980.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>9325.0</td>\n",
+       "      <td>10013.0</td>\n",
+       "      <td>9609.0</td>\n",
+       "      <td>9537.0</td>\n",
+       "      <td>9976.0</td>\n",
+       "      <td>11512.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>9219.0</td>\n",
+       "      <td>9942.0</td>\n",
+       "      <td>9982.0</td>\n",
+       "      <td>9300.0</td>\n",
+       "      <td>10183.0</td>\n",
+       "      <td>11687.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>9233.0</td>\n",
+       "      <td>9796.0</td>\n",
+       "      <td>9902.0</td>\n",
+       "      <td>9360.0</td>\n",
+       "      <td>10269.0</td>\n",
+       "      <td>11659.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>9706.0</td>\n",
+       "      <td>10530.0</td>\n",
+       "      <td>10151.0</td>\n",
+       "      <td>9613.0</td>\n",
+       "      <td>10079.0</td>\n",
+       "      <td>11467.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>9581.0</td>\n",
+       "      <td>9870.0</td>\n",
+       "      <td>10509.0</td>\n",
+       "      <td>9842.0</td>\n",
+       "      <td>10489.0</td>\n",
+       "      <td>11478.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>10043.0</td>\n",
+       "      <td>10802.0</td>\n",
+       "      <td>11755.0</td>\n",
+       "      <td>10392.0</td>\n",
+       "      <td>11159.0</td>\n",
+       "      <td>12129.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>8095.0</td>\n",
+       "      <td>7445.0</td>\n",
+       "      <td>7946.0</td>\n",
+       "      <td>6670.0</td>\n",
+       "      <td>7037.0</td>\n",
+       "      <td>10695.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>7008.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9342.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "year     2015     2016     2017     2018     2019     2020\n",
+       "week                                                      \n",
+       "1     11561.0  12236.0  11247.0  11940.0  10237.0  11467.0\n",
+       "2     15206.0  10790.0  12890.0  14146.0  11800.0  13119.0\n",
+       "3     13930.0  10753.0  12775.0  13371.0  11177.0  12223.0\n",
+       "4     13106.0  10600.0  11996.0  13085.0  11006.0  11133.0\n",
+       "5     12099.0  10362.0  11736.0  12470.0  10552.0  10885.0\n",
+       "6     11319.0  10470.0  11546.0  11694.0  10959.0  10296.0\n",
+       "7     11112.0   9933.0  10954.0  11443.0  11076.0  10216.0\n",
+       "8     10695.0  10360.0  11093.0  11353.0  10600.0  10162.0\n",
+       "9     10736.0  10564.0  10533.0  10220.0  10360.0  10165.0\n",
+       "10    10757.0  10276.0  10443.0  12101.0  10276.0  10243.0\n",
+       "11    10290.0  10284.0  10044.0  11870.0   9901.0  10344.0\n",
+       "12     9888.0   8967.0   9690.0  11139.0   9774.0   9926.0\n",
+       "13     9827.0   9574.0   9369.0   9308.0   9213.0  10422.0\n",
+       "14     8482.0  10857.0   9297.0  10064.0   9484.0  15467.0\n",
+       "15     9429.0  10679.0   7916.0  11558.0   9654.0  17588.0\n",
+       "16    10968.0  10211.0   8990.0  10535.0   8445.0  21182.0\n",
+       "17     9937.0   9784.0  10181.0   9692.0   9381.0  20873.0\n",
+       "18     9506.0   8568.0   8464.0   9520.0  10519.0  17024.0\n",
+       "19     8273.0   9985.0  10006.0   8094.0   8455.0  11965.0\n",
+       "20     9668.0   9342.0   9673.0   9474.0   9614.0  13801.0\n",
+       "21     9391.0   9115.0   9438.0   9033.0   9657.0  11596.0\n",
+       "22     7625.0   7409.0   7746.0   7609.0   7742.0   9237.0\n",
+       "23     9509.0   9289.0   9182.0   9343.0   9514.0  10009.0\n",
+       "24     8942.0   8808.0   8768.0   8782.0   8847.0   9402.0\n",
+       "25     8717.0   8807.0   9019.0   8694.0   8916.0   8722.0\n",
+       "26     8593.0   8679.0   8788.0   8613.0   8947.0   8427.0\n",
+       "27     8670.0   8614.0   8707.0   8633.0   8528.0   8556.0\n",
+       "28     8461.0   8789.0   8812.0   8710.0   8591.0   8118.0\n",
+       "29     8228.0   8790.0   8562.0   8579.0   8527.0   8273.0\n",
+       "30     8262.0   8725.0   8296.0   8581.0   8569.0   8326.0\n",
+       "31     8071.0   8602.0   8351.0   8587.0   8701.0   8415.0\n",
+       "32     8298.0   8531.0   8466.0   8782.0   8580.0   8382.0\n",
+       "33     8600.0   8496.0   8707.0   8312.0   8504.0   8775.0\n",
+       "34     8564.0   8700.0   8812.0   8413.0   8441.0   9037.0\n",
+       "35     8423.0   7453.0   7594.0   7354.0   7684.0   8441.0\n",
+       "36     7389.0   8847.0   8955.0   8851.0   9113.0   7251.0\n",
+       "37     8704.0   8548.0   8845.0   8612.0   8946.0   9233.0\n",
+       "38     8542.0   8382.0   8949.0   8707.0   8868.0   8968.0\n",
+       "39     8865.0   8402.0   9096.0   8590.0   8906.0   9017.0\n",
+       "40     8858.0   8729.0   9147.0   8908.0   9202.0   9274.0\n",
+       "41     9124.0   9132.0   9300.0   9043.0   9383.0   9316.0\n",
+       "42     8899.0   9144.0   9381.0   9224.0   9534.0   9846.0\n",
+       "43     9104.0   9100.0   9131.0   8970.0   9351.0  10078.0\n",
+       "44     9025.0   9508.0   9389.0   8925.0   9522.0  10175.0\n",
+       "45     9388.0   9844.0   9748.0   9509.0  10044.0  10980.0\n",
+       "46     9325.0  10013.0   9609.0   9537.0   9976.0  11512.0\n",
+       "47     9219.0   9942.0   9982.0   9300.0  10183.0  11687.0\n",
+       "48     9233.0   9796.0   9902.0   9360.0  10269.0  11659.0\n",
+       "49     9706.0  10530.0  10151.0   9613.0  10079.0  11467.0\n",
+       "50     9581.0   9870.0  10509.0   9842.0  10489.0  11478.0\n",
+       "51    10043.0  10802.0  11755.0  10392.0  11159.0  12129.0\n",
+       "52     8095.0   7445.0   7946.0   6670.0   7037.0  10695.0\n",
+       "53     7008.0      NaN      NaN      NaN      NaN   9342.0"
+      ]
+     },
+     "execution_count": 96,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_headlines_e = res.DataFrame().pivot(index='week', columns='year', values='deaths')\n",
+    "deaths_headlines_e"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 97,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "314 rows affected.\n",
+      "Returning data to local variable res\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%sql res << select week, year, deaths\n",
+    "from all_causes_deaths\n",
+    "where nation = 'Scotland'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 98,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>year</th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>2017</th>\n",
+       "      <th>2018</th>\n",
+       "      <th>2019</th>\n",
+       "      <th>2020</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>week</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1146.0</td>\n",
+       "      <td>1394.0</td>\n",
+       "      <td>1205.0</td>\n",
+       "      <td>1531.0</td>\n",
+       "      <td>1104.0</td>\n",
+       "      <td>1161.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1708.0</td>\n",
+       "      <td>1305.0</td>\n",
+       "      <td>1379.0</td>\n",
+       "      <td>1899.0</td>\n",
+       "      <td>1507.0</td>\n",
+       "      <td>1567.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1489.0</td>\n",
+       "      <td>1215.0</td>\n",
+       "      <td>1224.0</td>\n",
+       "      <td>1629.0</td>\n",
+       "      <td>1353.0</td>\n",
+       "      <td>1322.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1381.0</td>\n",
+       "      <td>1187.0</td>\n",
+       "      <td>1197.0</td>\n",
+       "      <td>1610.0</td>\n",
+       "      <td>1208.0</td>\n",
+       "      <td>1226.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>1286.0</td>\n",
+       "      <td>1205.0</td>\n",
+       "      <td>1332.0</td>\n",
+       "      <td>1369.0</td>\n",
+       "      <td>1206.0</td>\n",
+       "      <td>1188.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>1344.0</td>\n",
+       "      <td>1217.0</td>\n",
+       "      <td>1200.0</td>\n",
+       "      <td>1265.0</td>\n",
+       "      <td>1243.0</td>\n",
+       "      <td>1216.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>1360.0</td>\n",
+       "      <td>1209.0</td>\n",
+       "      <td>1231.0</td>\n",
+       "      <td>1315.0</td>\n",
+       "      <td>1181.0</td>\n",
+       "      <td>1162.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>1320.0</td>\n",
+       "      <td>1239.0</td>\n",
+       "      <td>1185.0</td>\n",
+       "      <td>1245.0</td>\n",
+       "      <td>1245.0</td>\n",
+       "      <td>1162.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>1308.0</td>\n",
+       "      <td>1150.0</td>\n",
+       "      <td>1219.0</td>\n",
+       "      <td>1022.0</td>\n",
+       "      <td>1125.0</td>\n",
+       "      <td>1171.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>1192.0</td>\n",
+       "      <td>1174.0</td>\n",
+       "      <td>1146.0</td>\n",
+       "      <td>1475.0</td>\n",
+       "      <td>1156.0</td>\n",
+       "      <td>1208.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>1201.0</td>\n",
+       "      <td>1175.0</td>\n",
+       "      <td>1141.0</td>\n",
+       "      <td>1220.0</td>\n",
+       "      <td>1108.0</td>\n",
+       "      <td>1156.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>1149.0</td>\n",
+       "      <td>1042.0</td>\n",
+       "      <td>1152.0</td>\n",
+       "      <td>1158.0</td>\n",
+       "      <td>1101.0</td>\n",
+       "      <td>1196.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>1171.0</td>\n",
+       "      <td>1172.0</td>\n",
+       "      <td>1112.0</td>\n",
+       "      <td>1050.0</td>\n",
+       "      <td>1086.0</td>\n",
+       "      <td>1079.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>1042.0</td>\n",
+       "      <td>1166.0</td>\n",
+       "      <td>1060.0</td>\n",
+       "      <td>1192.0</td>\n",
+       "      <td>1032.0</td>\n",
+       "      <td>1744.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>1192.0</td>\n",
+       "      <td>1048.0</td>\n",
+       "      <td>998.0</td>\n",
+       "      <td>1192.0</td>\n",
+       "      <td>1069.0</td>\n",
+       "      <td>1978.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>1095.0</td>\n",
+       "      <td>1092.0</td>\n",
+       "      <td>1111.0</td>\n",
+       "      <td>1136.0</td>\n",
+       "      <td>902.0</td>\n",
+       "      <td>1916.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>1108.0</td>\n",
+       "      <td>1076.0</td>\n",
+       "      <td>1121.0</td>\n",
+       "      <td>1008.0</td>\n",
+       "      <td>1121.0</td>\n",
+       "      <td>1836.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>1117.0</td>\n",
+       "      <td>1006.0</td>\n",
+       "      <td>1050.0</td>\n",
+       "      <td>1093.0</td>\n",
+       "      <td>1131.0</td>\n",
+       "      <td>1679.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>1020.0</td>\n",
+       "      <td>1047.0</td>\n",
+       "      <td>1119.0</td>\n",
+       "      <td>967.0</td>\n",
+       "      <td>1018.0</td>\n",
+       "      <td>1435.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>1103.0</td>\n",
+       "      <td>1010.0</td>\n",
+       "      <td>1115.0</td>\n",
+       "      <td>977.0</td>\n",
+       "      <td>1115.0</td>\n",
+       "      <td>1421.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>1039.0</td>\n",
+       "      <td>994.0</td>\n",
+       "      <td>1063.0</td>\n",
+       "      <td>1070.0</td>\n",
+       "      <td>1061.0</td>\n",
+       "      <td>1226.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>1043.0</td>\n",
+       "      <td>999.0</td>\n",
+       "      <td>1015.0</td>\n",
+       "      <td>998.0</td>\n",
+       "      <td>1029.0</td>\n",
+       "      <td>1125.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>1106.0</td>\n",
+       "      <td>1023.0</td>\n",
+       "      <td>1076.0</td>\n",
+       "      <td>1033.0</td>\n",
+       "      <td>1042.0</td>\n",
+       "      <td>1093.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>1038.0</td>\n",
+       "      <td>988.0</td>\n",
+       "      <td>1031.0</td>\n",
+       "      <td>915.0</td>\n",
+       "      <td>1028.0</td>\n",
+       "      <td>1034.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>1025.0</td>\n",
+       "      <td>994.0</td>\n",
+       "      <td>1032.0</td>\n",
+       "      <td>993.0</td>\n",
+       "      <td>1053.0</td>\n",
+       "      <td>1065.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>1032.0</td>\n",
+       "      <td>1007.0</td>\n",
+       "      <td>994.0</td>\n",
+       "      <td>1046.0</td>\n",
+       "      <td>1051.0</td>\n",
+       "      <td>1008.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>1040.0</td>\n",
+       "      <td>988.0</td>\n",
+       "      <td>1040.0</td>\n",
+       "      <td>1041.0</td>\n",
+       "      <td>981.0</td>\n",
+       "      <td>983.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>1011.0</td>\n",
+       "      <td>1022.0</td>\n",
+       "      <td>1014.0</td>\n",
+       "      <td>1002.0</td>\n",
+       "      <td>1077.0</td>\n",
+       "      <td>976.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>1023.0</td>\n",
+       "      <td>1041.0</td>\n",
+       "      <td>1025.0</td>\n",
+       "      <td>928.0</td>\n",
+       "      <td>964.0</td>\n",
+       "      <td>1033.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>956.0</td>\n",
+       "      <td>979.0</td>\n",
+       "      <td>978.0</td>\n",
+       "      <td>933.0</td>\n",
+       "      <td>1041.0</td>\n",
+       "      <td>961.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>985.0</td>\n",
+       "      <td>987.0</td>\n",
+       "      <td>1011.0</td>\n",
+       "      <td>969.0</td>\n",
+       "      <td>1020.0</td>\n",
+       "      <td>1043.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>1043.0</td>\n",
+       "      <td>997.0</td>\n",
+       "      <td>1002.0</td>\n",
+       "      <td>953.0</td>\n",
+       "      <td>1018.0</td>\n",
+       "      <td>1011.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>969.0</td>\n",
+       "      <td>982.0</td>\n",
+       "      <td>1004.0</td>\n",
+       "      <td>978.0</td>\n",
+       "      <td>1028.0</td>\n",
+       "      <td>922.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>982.0</td>\n",
+       "      <td>1017.0</td>\n",
+       "      <td>1045.0</td>\n",
+       "      <td>941.0</td>\n",
+       "      <td>1011.0</td>\n",
+       "      <td>1046.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>954.0</td>\n",
+       "      <td>1039.0</td>\n",
+       "      <td>980.0</td>\n",
+       "      <td>930.0</td>\n",
+       "      <td>1013.0</td>\n",
+       "      <td>1029.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>977.0</td>\n",
+       "      <td>1007.0</td>\n",
+       "      <td>1006.0</td>\n",
+       "      <td>970.0</td>\n",
+       "      <td>980.0</td>\n",
+       "      <td>1050.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>991.0</td>\n",
+       "      <td>983.0</td>\n",
+       "      <td>972.0</td>\n",
+       "      <td>1020.0</td>\n",
+       "      <td>1074.0</td>\n",
+       "      <td>1069.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>1001.0</td>\n",
+       "      <td>966.0</td>\n",
+       "      <td>1049.0</td>\n",
+       "      <td>946.0</td>\n",
+       "      <td>1071.0</td>\n",
+       "      <td>952.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>1010.0</td>\n",
+       "      <td>1009.0</td>\n",
+       "      <td>1056.0</td>\n",
+       "      <td>1015.0</td>\n",
+       "      <td>1142.0</td>\n",
+       "      <td>933.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>1008.0</td>\n",
+       "      <td>1072.0</td>\n",
+       "      <td>1016.0</td>\n",
+       "      <td>1042.0</td>\n",
+       "      <td>1051.0</td>\n",
+       "      <td>1195.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>1028.0</td>\n",
+       "      <td>1009.0</td>\n",
+       "      <td>1133.0</td>\n",
+       "      <td>1081.0</td>\n",
+       "      <td>1143.0</td>\n",
+       "      <td>1071.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>989.0</td>\n",
+       "      <td>1070.0</td>\n",
+       "      <td>1067.0</td>\n",
+       "      <td>1031.0</td>\n",
+       "      <td>1153.0</td>\n",
+       "      <td>1131.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>981.0</td>\n",
+       "      <td>1052.0</td>\n",
+       "      <td>1095.0</td>\n",
+       "      <td>1019.0</td>\n",
+       "      <td>1115.0</td>\n",
+       "      <td>1187.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>1116.0</td>\n",
+       "      <td>1032.0</td>\n",
+       "      <td>1062.0</td>\n",
+       "      <td>1085.0</td>\n",
+       "      <td>1101.0</td>\n",
+       "      <td>1262.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>1028.0</td>\n",
+       "      <td>1043.0</td>\n",
+       "      <td>1126.0</td>\n",
+       "      <td>1144.0</td>\n",
+       "      <td>1184.0</td>\n",
+       "      <td>1250.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>1103.0</td>\n",
+       "      <td>1174.0</td>\n",
+       "      <td>1175.0</td>\n",
+       "      <td>1084.0</td>\n",
+       "      <td>1160.0</td>\n",
+       "      <td>1138.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>1054.0</td>\n",
+       "      <td>1132.0</td>\n",
+       "      <td>1178.0</td>\n",
+       "      <td>1058.0</td>\n",
+       "      <td>1229.0</td>\n",
+       "      <td>1360.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>1115.0</td>\n",
+       "      <td>1159.0</td>\n",
+       "      <td>1153.0</td>\n",
+       "      <td>1062.0</td>\n",
+       "      <td>1163.0</td>\n",
+       "      <td>1328.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>1089.0</td>\n",
+       "      <td>1188.0</td>\n",
+       "      <td>1237.0</td>\n",
+       "      <td>1076.0</td>\n",
+       "      <td>1108.0</td>\n",
+       "      <td>1296.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>1101.0</td>\n",
+       "      <td>1219.0</td>\n",
+       "      <td>1335.0</td>\n",
+       "      <td>1212.0</td>\n",
+       "      <td>1312.0</td>\n",
+       "      <td>1284.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>1146.0</td>\n",
+       "      <td>1284.0</td>\n",
+       "      <td>1437.0</td>\n",
+       "      <td>1216.0</td>\n",
+       "      <td>1277.0</td>\n",
+       "      <td>1297.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>944.0</td>\n",
+       "      <td>1133.0</td>\n",
+       "      <td>1168.0</td>\n",
+       "      <td>1058.0</td>\n",
+       "      <td>1000.0</td>\n",
+       "      <td>1205.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>1018.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1178.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "year    2015    2016    2017    2018    2019    2020\n",
+       "week                                                \n",
+       "1     1146.0  1394.0  1205.0  1531.0  1104.0  1161.0\n",
+       "2     1708.0  1305.0  1379.0  1899.0  1507.0  1567.0\n",
+       "3     1489.0  1215.0  1224.0  1629.0  1353.0  1322.0\n",
+       "4     1381.0  1187.0  1197.0  1610.0  1208.0  1226.0\n",
+       "5     1286.0  1205.0  1332.0  1369.0  1206.0  1188.0\n",
+       "6     1344.0  1217.0  1200.0  1265.0  1243.0  1216.0\n",
+       "7     1360.0  1209.0  1231.0  1315.0  1181.0  1162.0\n",
+       "8     1320.0  1239.0  1185.0  1245.0  1245.0  1162.0\n",
+       "9     1308.0  1150.0  1219.0  1022.0  1125.0  1171.0\n",
+       "10    1192.0  1174.0  1146.0  1475.0  1156.0  1208.0\n",
+       "11    1201.0  1175.0  1141.0  1220.0  1108.0  1156.0\n",
+       "12    1149.0  1042.0  1152.0  1158.0  1101.0  1196.0\n",
+       "13    1171.0  1172.0  1112.0  1050.0  1086.0  1079.0\n",
+       "14    1042.0  1166.0  1060.0  1192.0  1032.0  1744.0\n",
+       "15    1192.0  1048.0   998.0  1192.0  1069.0  1978.0\n",
+       "16    1095.0  1092.0  1111.0  1136.0   902.0  1916.0\n",
+       "17    1108.0  1076.0  1121.0  1008.0  1121.0  1836.0\n",
+       "18    1117.0  1006.0  1050.0  1093.0  1131.0  1679.0\n",
+       "19    1020.0  1047.0  1119.0   967.0  1018.0  1435.0\n",
+       "20    1103.0  1010.0  1115.0   977.0  1115.0  1421.0\n",
+       "21    1039.0   994.0  1063.0  1070.0  1061.0  1226.0\n",
+       "22    1043.0   999.0  1015.0   998.0  1029.0  1125.0\n",
+       "23    1106.0  1023.0  1076.0  1033.0  1042.0  1093.0\n",
+       "24    1038.0   988.0  1031.0   915.0  1028.0  1034.0\n",
+       "25    1025.0   994.0  1032.0   993.0  1053.0  1065.0\n",
+       "26    1032.0  1007.0   994.0  1046.0  1051.0  1008.0\n",
+       "27    1040.0   988.0  1040.0  1041.0   981.0   983.0\n",
+       "28    1011.0  1022.0  1014.0  1002.0  1077.0   976.0\n",
+       "29    1023.0  1041.0  1025.0   928.0   964.0  1033.0\n",
+       "30     956.0   979.0   978.0   933.0  1041.0   961.0\n",
+       "31     985.0   987.0  1011.0   969.0  1020.0  1043.0\n",
+       "32    1043.0   997.0  1002.0   953.0  1018.0  1011.0\n",
+       "33     969.0   982.0  1004.0   978.0  1028.0   922.0\n",
+       "34     982.0  1017.0  1045.0   941.0  1011.0  1046.0\n",
+       "35     954.0  1039.0   980.0   930.0  1013.0  1029.0\n",
+       "36     977.0  1007.0  1006.0   970.0   980.0  1050.0\n",
+       "37     991.0   983.0   972.0  1020.0  1074.0  1069.0\n",
+       "38    1001.0   966.0  1049.0   946.0  1071.0   952.0\n",
+       "39    1010.0  1009.0  1056.0  1015.0  1142.0   933.0\n",
+       "40    1008.0  1072.0  1016.0  1042.0  1051.0  1195.0\n",
+       "41    1028.0  1009.0  1133.0  1081.0  1143.0  1071.0\n",
+       "42     989.0  1070.0  1067.0  1031.0  1153.0  1131.0\n",
+       "43     981.0  1052.0  1095.0  1019.0  1115.0  1187.0\n",
+       "44    1116.0  1032.0  1062.0  1085.0  1101.0  1262.0\n",
+       "45    1028.0  1043.0  1126.0  1144.0  1184.0  1250.0\n",
+       "46    1103.0  1174.0  1175.0  1084.0  1160.0  1138.0\n",
+       "47    1054.0  1132.0  1178.0  1058.0  1229.0  1360.0\n",
+       "48    1115.0  1159.0  1153.0  1062.0  1163.0  1328.0\n",
+       "49    1089.0  1188.0  1237.0  1076.0  1108.0  1296.0\n",
+       "50    1101.0  1219.0  1335.0  1212.0  1312.0  1284.0\n",
+       "51    1146.0  1284.0  1437.0  1216.0  1277.0  1297.0\n",
+       "52     944.0  1133.0  1168.0  1058.0  1000.0  1205.0\n",
+       "53    1018.0     NaN     NaN     NaN     NaN  1178.0"
+      ]
+     },
+     "execution_count": 98,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_headlines_s = res.DataFrame().pivot(index='week', columns='year', values='deaths')\n",
+    "deaths_headlines_s"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 99,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "314 rows affected.\n",
+      "Returning data to local variable res\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%sql res << select week, year, deaths\n",
+    "from all_causes_deaths\n",
+    "where nation = 'Wales'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 100,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>year</th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>2017</th>\n",
+       "      <th>2018</th>\n",
+       "      <th>2019</th>\n",
+       "      <th>2020</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>week</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>725.0</td>\n",
+       "      <td>809.0</td>\n",
+       "      <td>744.0</td>\n",
+       "      <td>783.0</td>\n",
+       "      <td>718.0</td>\n",
+       "      <td>787.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1031.0</td>\n",
+       "      <td>711.0</td>\n",
+       "      <td>825.0</td>\n",
+       "      <td>904.0</td>\n",
+       "      <td>809.0</td>\n",
+       "      <td>939.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>936.0</td>\n",
+       "      <td>720.0</td>\n",
+       "      <td>835.0</td>\n",
+       "      <td>885.0</td>\n",
+       "      <td>683.0</td>\n",
+       "      <td>767.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>828.0</td>\n",
+       "      <td>717.0</td>\n",
+       "      <td>881.0</td>\n",
+       "      <td>850.0</td>\n",
+       "      <td>734.0</td>\n",
+       "      <td>723.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>801.0</td>\n",
+       "      <td>690.0</td>\n",
+       "      <td>749.0</td>\n",
+       "      <td>815.0</td>\n",
+       "      <td>745.0</td>\n",
+       "      <td>727.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>720.0</td>\n",
+       "      <td>700.0</td>\n",
+       "      <td>723.0</td>\n",
+       "      <td>801.0</td>\n",
+       "      <td>701.0</td>\n",
+       "      <td>690.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>710.0</td>\n",
+       "      <td>657.0</td>\n",
+       "      <td>690.0</td>\n",
+       "      <td>803.0</td>\n",
+       "      <td>748.0</td>\n",
+       "      <td>728.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>739.0</td>\n",
+       "      <td>696.0</td>\n",
+       "      <td>701.0</td>\n",
+       "      <td>789.0</td>\n",
+       "      <td>695.0</td>\n",
+       "      <td>679.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>736.0</td>\n",
+       "      <td>721.0</td>\n",
+       "      <td>715.0</td>\n",
+       "      <td>634.0</td>\n",
+       "      <td>684.0</td>\n",
+       "      <td>651.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>712.0</td>\n",
+       "      <td>734.0</td>\n",
+       "      <td>634.0</td>\n",
+       "      <td>896.0</td>\n",
+       "      <td>622.0</td>\n",
+       "      <td>652.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>661.0</td>\n",
+       "      <td>738.0</td>\n",
+       "      <td>653.0</td>\n",
+       "      <td>918.0</td>\n",
+       "      <td>666.0</td>\n",
+       "      <td>675.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>680.0</td>\n",
+       "      <td>668.0</td>\n",
+       "      <td>635.0</td>\n",
+       "      <td>774.0</td>\n",
+       "      <td>628.0</td>\n",
+       "      <td>719.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>666.0</td>\n",
+       "      <td>712.0</td>\n",
+       "      <td>658.0</td>\n",
+       "      <td>633.0</td>\n",
+       "      <td>654.0</td>\n",
+       "      <td>719.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>580.0</td>\n",
+       "      <td>742.0</td>\n",
+       "      <td>642.0</td>\n",
+       "      <td>730.0</td>\n",
+       "      <td>642.0</td>\n",
+       "      <td>920.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>660.0</td>\n",
+       "      <td>738.0</td>\n",
+       "      <td>577.0</td>\n",
+       "      <td>743.0</td>\n",
+       "      <td>637.0</td>\n",
+       "      <td>928.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>671.0</td>\n",
+       "      <td>714.0</td>\n",
+       "      <td>654.0</td>\n",
+       "      <td>688.0</td>\n",
+       "      <td>580.0</td>\n",
+       "      <td>1169.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>662.0</td>\n",
+       "      <td>629.0</td>\n",
+       "      <td>727.0</td>\n",
+       "      <td>614.0</td>\n",
+       "      <td>678.0</td>\n",
+       "      <td>1124.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>628.0</td>\n",
+       "      <td>569.0</td>\n",
+       "      <td>600.0</td>\n",
+       "      <td>633.0</td>\n",
+       "      <td>688.0</td>\n",
+       "      <td>929.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>589.0</td>\n",
+       "      <td>652.0</td>\n",
+       "      <td>687.0</td>\n",
+       "      <td>530.0</td>\n",
+       "      <td>600.0</td>\n",
+       "      <td>692.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>622.0</td>\n",
+       "      <td>611.0</td>\n",
+       "      <td>615.0</td>\n",
+       "      <td>667.0</td>\n",
+       "      <td>658.0</td>\n",
+       "      <td>772.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>614.0</td>\n",
+       "      <td>624.0</td>\n",
+       "      <td>602.0</td>\n",
+       "      <td>603.0</td>\n",
+       "      <td>627.0</td>\n",
+       "      <td>692.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>588.0</td>\n",
+       "      <td>500.0</td>\n",
+       "      <td>586.0</td>\n",
+       "      <td>538.0</td>\n",
+       "      <td>518.0</td>\n",
+       "      <td>587.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>648.0</td>\n",
+       "      <td>584.0</td>\n",
+       "      <td>584.0</td>\n",
+       "      <td>607.0</td>\n",
+       "      <td>626.0</td>\n",
+       "      <td>700.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>606.0</td>\n",
+       "      <td>578.0</td>\n",
+       "      <td>599.0</td>\n",
+       "      <td>561.0</td>\n",
+       "      <td>598.0</td>\n",
+       "      <td>574.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>595.0</td>\n",
+       "      <td>558.0</td>\n",
+       "      <td>608.0</td>\n",
+       "      <td>562.0</td>\n",
+       "      <td>542.0</td>\n",
+       "      <td>617.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>597.0</td>\n",
+       "      <td>549.0</td>\n",
+       "      <td>546.0</td>\n",
+       "      <td>599.0</td>\n",
+       "      <td>564.0</td>\n",
+       "      <td>552.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>535.0</td>\n",
+       "      <td>524.0</td>\n",
+       "      <td>556.0</td>\n",
+       "      <td>625.0</td>\n",
+       "      <td>534.0</td>\n",
+       "      <td>584.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>554.0</td>\n",
+       "      <td>599.0</td>\n",
+       "      <td>564.0</td>\n",
+       "      <td>583.0</td>\n",
+       "      <td>588.0</td>\n",
+       "      <td>572.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>574.0</td>\n",
+       "      <td>560.0</td>\n",
+       "      <td>551.0</td>\n",
+       "      <td>548.0</td>\n",
+       "      <td>553.0</td>\n",
+       "      <td>550.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>529.0</td>\n",
+       "      <td>610.0</td>\n",
+       "      <td>586.0</td>\n",
+       "      <td>560.0</td>\n",
+       "      <td>543.0</td>\n",
+       "      <td>565.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>546.0</td>\n",
+       "      <td>580.0</td>\n",
+       "      <td>590.0</td>\n",
+       "      <td>574.0</td>\n",
+       "      <td>570.0</td>\n",
+       "      <td>531.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>564.0</td>\n",
+       "      <td>641.0</td>\n",
+       "      <td>572.0</td>\n",
+       "      <td>537.0</td>\n",
+       "      <td>542.0</td>\n",
+       "      <td>563.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>548.0</td>\n",
+       "      <td>574.0</td>\n",
+       "      <td>592.0</td>\n",
+       "      <td>518.0</td>\n",
+       "      <td>589.0</td>\n",
+       "      <td>617.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>557.0</td>\n",
+       "      <td>619.0</td>\n",
+       "      <td>570.0</td>\n",
+       "      <td>565.0</td>\n",
+       "      <td>553.0</td>\n",
+       "      <td>594.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>603.0</td>\n",
+       "      <td>470.0</td>\n",
+       "      <td>555.0</td>\n",
+       "      <td>511.0</td>\n",
+       "      <td>558.0</td>\n",
+       "      <td>591.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>489.0</td>\n",
+       "      <td>552.0</td>\n",
+       "      <td>542.0</td>\n",
+       "      <td>594.0</td>\n",
+       "      <td>582.0</td>\n",
+       "      <td>488.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>554.0</td>\n",
+       "      <td>576.0</td>\n",
+       "      <td>609.0</td>\n",
+       "      <td>579.0</td>\n",
+       "      <td>567.0</td>\n",
+       "      <td>578.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>555.0</td>\n",
+       "      <td>563.0</td>\n",
+       "      <td>585.0</td>\n",
+       "      <td>598.0</td>\n",
+       "      <td>572.0</td>\n",
+       "      <td>555.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>664.0</td>\n",
+       "      <td>592.0</td>\n",
+       "      <td>593.0</td>\n",
+       "      <td>560.0</td>\n",
+       "      <td>611.0</td>\n",
+       "      <td>617.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>552.0</td>\n",
+       "      <td>562.0</td>\n",
+       "      <td>631.0</td>\n",
+       "      <td>595.0</td>\n",
+       "      <td>597.0</td>\n",
+       "      <td>671.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>652.0</td>\n",
+       "      <td>587.0</td>\n",
+       "      <td>640.0</td>\n",
+       "      <td>606.0</td>\n",
+       "      <td>590.0</td>\n",
+       "      <td>638.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>612.0</td>\n",
+       "      <td>624.0</td>\n",
+       "      <td>650.0</td>\n",
+       "      <td>640.0</td>\n",
+       "      <td>622.0</td>\n",
+       "      <td>688.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>607.0</td>\n",
+       "      <td>624.0</td>\n",
+       "      <td>608.0</td>\n",
+       "      <td>633.0</td>\n",
+       "      <td>670.0</td>\n",
+       "      <td>661.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>593.0</td>\n",
+       "      <td>644.0</td>\n",
+       "      <td>595.0</td>\n",
+       "      <td>604.0</td>\n",
+       "      <td>642.0</td>\n",
+       "      <td>712.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>606.0</td>\n",
+       "      <td>626.0</td>\n",
+       "      <td>598.0</td>\n",
+       "      <td>642.0</td>\n",
+       "      <td>653.0</td>\n",
+       "      <td>832.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>613.0</td>\n",
+       "      <td>681.0</td>\n",
+       "      <td>666.0</td>\n",
+       "      <td>656.0</td>\n",
+       "      <td>674.0</td>\n",
+       "      <td>742.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>611.0</td>\n",
+       "      <td>661.0</td>\n",
+       "      <td>639.0</td>\n",
+       "      <td>657.0</td>\n",
+       "      <td>699.0</td>\n",
+       "      <td>848.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>589.0</td>\n",
+       "      <td>643.0</td>\n",
+       "      <td>636.0</td>\n",
+       "      <td>673.0</td>\n",
+       "      <td>689.0</td>\n",
+       "      <td>797.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>659.0</td>\n",
+       "      <td>693.0</td>\n",
+       "      <td>630.0</td>\n",
+       "      <td>674.0</td>\n",
+       "      <td>737.0</td>\n",
+       "      <td>836.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>688.0</td>\n",
+       "      <td>663.0</td>\n",
+       "      <td>708.0</td>\n",
+       "      <td>708.0</td>\n",
+       "      <td>699.0</td>\n",
+       "      <td>814.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>646.0</td>\n",
+       "      <td>691.0</td>\n",
+       "      <td>762.0</td>\n",
+       "      <td>724.0</td>\n",
+       "      <td>767.0</td>\n",
+       "      <td>882.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>535.0</td>\n",
+       "      <td>558.0</td>\n",
+       "      <td>541.0</td>\n",
+       "      <td>461.0</td>\n",
+       "      <td>496.0</td>\n",
+       "      <td>825.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>516.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>727.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "year    2015   2016   2017   2018   2019    2020\n",
+       "week                                            \n",
+       "1      725.0  809.0  744.0  783.0  718.0   787.0\n",
+       "2     1031.0  711.0  825.0  904.0  809.0   939.0\n",
+       "3      936.0  720.0  835.0  885.0  683.0   767.0\n",
+       "4      828.0  717.0  881.0  850.0  734.0   723.0\n",
+       "5      801.0  690.0  749.0  815.0  745.0   727.0\n",
+       "6      720.0  700.0  723.0  801.0  701.0   690.0\n",
+       "7      710.0  657.0  690.0  803.0  748.0   728.0\n",
+       "8      739.0  696.0  701.0  789.0  695.0   679.0\n",
+       "9      736.0  721.0  715.0  634.0  684.0   651.0\n",
+       "10     712.0  734.0  634.0  896.0  622.0   652.0\n",
+       "11     661.0  738.0  653.0  918.0  666.0   675.0\n",
+       "12     680.0  668.0  635.0  774.0  628.0   719.0\n",
+       "13     666.0  712.0  658.0  633.0  654.0   719.0\n",
+       "14     580.0  742.0  642.0  730.0  642.0   920.0\n",
+       "15     660.0  738.0  577.0  743.0  637.0   928.0\n",
+       "16     671.0  714.0  654.0  688.0  580.0  1169.0\n",
+       "17     662.0  629.0  727.0  614.0  678.0  1124.0\n",
+       "18     628.0  569.0  600.0  633.0  688.0   929.0\n",
+       "19     589.0  652.0  687.0  530.0  600.0   692.0\n",
+       "20     622.0  611.0  615.0  667.0  658.0   772.0\n",
+       "21     614.0  624.0  602.0  603.0  627.0   692.0\n",
+       "22     588.0  500.0  586.0  538.0  518.0   587.0\n",
+       "23     648.0  584.0  584.0  607.0  626.0   700.0\n",
+       "24     606.0  578.0  599.0  561.0  598.0   574.0\n",
+       "25     595.0  558.0  608.0  562.0  542.0   617.0\n",
+       "26     597.0  549.0  546.0  599.0  564.0   552.0\n",
+       "27     535.0  524.0  556.0  625.0  534.0   584.0\n",
+       "28     554.0  599.0  564.0  583.0  588.0   572.0\n",
+       "29     574.0  560.0  551.0  548.0  553.0   550.0\n",
+       "30     529.0  610.0  586.0  560.0  543.0   565.0\n",
+       "31     546.0  580.0  590.0  574.0  570.0   531.0\n",
+       "32     564.0  641.0  572.0  537.0  542.0   563.0\n",
+       "33     548.0  574.0  592.0  518.0  589.0   617.0\n",
+       "34     557.0  619.0  570.0  565.0  553.0   594.0\n",
+       "35     603.0  470.0  555.0  511.0  558.0   591.0\n",
+       "36     489.0  552.0  542.0  594.0  582.0   488.0\n",
+       "37     554.0  576.0  609.0  579.0  567.0   578.0\n",
+       "38     555.0  563.0  585.0  598.0  572.0   555.0\n",
+       "39     664.0  592.0  593.0  560.0  611.0   617.0\n",
+       "40     552.0  562.0  631.0  595.0  597.0   671.0\n",
+       "41     652.0  587.0  640.0  606.0  590.0   638.0\n",
+       "42     612.0  624.0  650.0  640.0  622.0   688.0\n",
+       "43     607.0  624.0  608.0  633.0  670.0   661.0\n",
+       "44     593.0  644.0  595.0  604.0  642.0   712.0\n",
+       "45     606.0  626.0  598.0  642.0  653.0   832.0\n",
+       "46     613.0  681.0  666.0  656.0  674.0   742.0\n",
+       "47     611.0  661.0  639.0  657.0  699.0   848.0\n",
+       "48     589.0  643.0  636.0  673.0  689.0   797.0\n",
+       "49     659.0  693.0  630.0  674.0  737.0   836.0\n",
+       "50     688.0  663.0  708.0  708.0  699.0   814.0\n",
+       "51     646.0  691.0  762.0  724.0  767.0   882.0\n",
+       "52     535.0  558.0  541.0  461.0  496.0   825.0\n",
+       "53     516.0    NaN    NaN    NaN    NaN   727.0"
+      ]
+     },
+     "execution_count": 100,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_headlines_w = res.DataFrame().pivot(index='week', columns='year', values='deaths')\n",
+    "deaths_headlines_w"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 101,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "314 rows affected.\n",
+      "Returning data to local variable res\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%sql res << select week, year, deaths\n",
+    "from all_causes_deaths\n",
+    "where nation = 'Northern Ireland'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 102,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>year</th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>2017</th>\n",
+       "      <th>2018</th>\n",
+       "      <th>2019</th>\n",
+       "      <th>2020</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>week</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>319.0</td>\n",
+       "      <td>424.0</td>\n",
+       "      <td>416.0</td>\n",
+       "      <td>447.0</td>\n",
+       "      <td>365.0</td>\n",
+       "      <td>353.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>373.0</td>\n",
+       "      <td>348.0</td>\n",
+       "      <td>434.0</td>\n",
+       "      <td>481.0</td>\n",
+       "      <td>371.0</td>\n",
+       "      <td>395.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>383.0</td>\n",
+       "      <td>372.0</td>\n",
+       "      <td>397.0</td>\n",
+       "      <td>470.0</td>\n",
+       "      <td>332.0</td>\n",
+       "      <td>411.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>397.0</td>\n",
+       "      <td>355.0</td>\n",
+       "      <td>387.0</td>\n",
+       "      <td>426.0</td>\n",
+       "      <td>335.0</td>\n",
+       "      <td>347.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>374.0</td>\n",
+       "      <td>314.0</td>\n",
+       "      <td>371.0</td>\n",
+       "      <td>433.0</td>\n",
+       "      <td>296.0</td>\n",
+       "      <td>323.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>347.0</td>\n",
+       "      <td>310.0</td>\n",
+       "      <td>336.0</td>\n",
+       "      <td>351.0</td>\n",
+       "      <td>319.0</td>\n",
+       "      <td>332.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>328.0</td>\n",
+       "      <td>217.0</td>\n",
+       "      <td>337.0</td>\n",
+       "      <td>364.0</td>\n",
+       "      <td>342.0</td>\n",
+       "      <td>306.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>317.0</td>\n",
+       "      <td>423.0</td>\n",
+       "      <td>351.0</td>\n",
+       "      <td>366.0</td>\n",
+       "      <td>337.0</td>\n",
+       "      <td>297.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>401.0</td>\n",
+       "      <td>298.0</td>\n",
+       "      <td>352.0</td>\n",
+       "      <td>314.0</td>\n",
+       "      <td>310.0</td>\n",
+       "      <td>347.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>346.0</td>\n",
+       "      <td>309.0</td>\n",
+       "      <td>357.0</td>\n",
+       "      <td>387.0</td>\n",
+       "      <td>342.0</td>\n",
+       "      <td>312.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>323.0</td>\n",
+       "      <td>292.0</td>\n",
+       "      <td>251.0</td>\n",
+       "      <td>359.0</td>\n",
+       "      <td>343.0</td>\n",
+       "      <td>324.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>310.0</td>\n",
+       "      <td>306.0</td>\n",
+       "      <td>356.0</td>\n",
+       "      <td>326.0</td>\n",
+       "      <td>294.0</td>\n",
+       "      <td>271.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>323.0</td>\n",
+       "      <td>280.0</td>\n",
+       "      <td>314.0</td>\n",
+       "      <td>319.0</td>\n",
+       "      <td>307.0</td>\n",
+       "      <td>287.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>221.0</td>\n",
+       "      <td>295.0</td>\n",
+       "      <td>306.0</td>\n",
+       "      <td>286.0</td>\n",
+       "      <td>287.0</td>\n",
+       "      <td>434.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>294.0</td>\n",
+       "      <td>292.0</td>\n",
+       "      <td>270.0</td>\n",
+       "      <td>350.0</td>\n",
+       "      <td>301.0</td>\n",
+       "      <td>435.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>327.0</td>\n",
+       "      <td>293.0</td>\n",
+       "      <td>245.0</td>\n",
+       "      <td>280.0</td>\n",
+       "      <td>316.0</td>\n",
+       "      <td>424.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>316.0</td>\n",
+       "      <td>306.0</td>\n",
+       "      <td>327.0</td>\n",
+       "      <td>282.0</td>\n",
+       "      <td>272.0</td>\n",
+       "      <td>470.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>335.0</td>\n",
+       "      <td>258.0</td>\n",
+       "      <td>258.0</td>\n",
+       "      <td>292.0</td>\n",
+       "      <td>357.0</td>\n",
+       "      <td>427.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>256.0</td>\n",
+       "      <td>318.0</td>\n",
+       "      <td>302.0</td>\n",
+       "      <td>230.0</td>\n",
+       "      <td>288.0</td>\n",
+       "      <td>336.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>299.0</td>\n",
+       "      <td>259.0</td>\n",
+       "      <td>315.0</td>\n",
+       "      <td>268.0</td>\n",
+       "      <td>330.0</td>\n",
+       "      <td>396.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>290.0</td>\n",
+       "      <td>280.0</td>\n",
+       "      <td>328.0</td>\n",
+       "      <td>268.0</td>\n",
+       "      <td>308.0</td>\n",
+       "      <td>325.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>258.0</td>\n",
+       "      <td>284.0</td>\n",
+       "      <td>256.0</td>\n",
+       "      <td>252.0</td>\n",
+       "      <td>245.0</td>\n",
+       "      <td>316.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>340.0</td>\n",
+       "      <td>275.0</td>\n",
+       "      <td>292.0</td>\n",
+       "      <td>276.0</td>\n",
+       "      <td>279.0</td>\n",
+       "      <td>304.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>272.0</td>\n",
+       "      <td>299.0</td>\n",
+       "      <td>300.0</td>\n",
+       "      <td>277.0</td>\n",
+       "      <td>281.0</td>\n",
+       "      <td>292.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>292.0</td>\n",
+       "      <td>252.0</td>\n",
+       "      <td>271.0</td>\n",
+       "      <td>265.0</td>\n",
+       "      <td>296.0</td>\n",
+       "      <td>290.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>303.0</td>\n",
+       "      <td>291.0</td>\n",
+       "      <td>296.0</td>\n",
+       "      <td>271.0</td>\n",
+       "      <td>262.0</td>\n",
+       "      <td>295.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>300.0</td>\n",
+       "      <td>286.0</td>\n",
+       "      <td>262.0</td>\n",
+       "      <td>266.0</td>\n",
+       "      <td>285.0</td>\n",
+       "      <td>289.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>252.0</td>\n",
+       "      <td>237.0</td>\n",
+       "      <td>253.0</td>\n",
+       "      <td>172.0</td>\n",
+       "      <td>256.0</td>\n",
+       "      <td>275.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>203.0</td>\n",
+       "      <td>281.0</td>\n",
+       "      <td>288.0</td>\n",
+       "      <td>298.0</td>\n",
+       "      <td>280.0</td>\n",
+       "      <td>240.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>274.0</td>\n",
+       "      <td>298.0</td>\n",
+       "      <td>287.0</td>\n",
+       "      <td>282.0</td>\n",
+       "      <td>269.0</td>\n",
+       "      <td>307.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>291.0</td>\n",
+       "      <td>264.0</td>\n",
+       "      <td>287.0</td>\n",
+       "      <td>278.0</td>\n",
+       "      <td>273.0</td>\n",
+       "      <td>273.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>248.0</td>\n",
+       "      <td>270.0</td>\n",
+       "      <td>238.0</td>\n",
+       "      <td>270.0</td>\n",
+       "      <td>266.0</td>\n",
+       "      <td>280.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>235.0</td>\n",
+       "      <td>260.0</td>\n",
+       "      <td>266.0</td>\n",
+       "      <td>283.0</td>\n",
+       "      <td>284.0</td>\n",
+       "      <td>278.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>251.0</td>\n",
+       "      <td>301.0</td>\n",
+       "      <td>271.0</td>\n",
+       "      <td>280.0</td>\n",
+       "      <td>274.0</td>\n",
+       "      <td>313.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>259.0</td>\n",
+       "      <td>264.0</td>\n",
+       "      <td>243.0</td>\n",
+       "      <td>251.0</td>\n",
+       "      <td>223.0</td>\n",
+       "      <td>303.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>237.0</td>\n",
+       "      <td>275.0</td>\n",
+       "      <td>278.0</td>\n",
+       "      <td>265.0</td>\n",
+       "      <td>243.0</td>\n",
+       "      <td>234.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>324.0</td>\n",
+       "      <td>294.0</td>\n",
+       "      <td>266.0</td>\n",
+       "      <td>285.0</td>\n",
+       "      <td>305.0</td>\n",
+       "      <td>296.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>283.0</td>\n",
+       "      <td>272.0</td>\n",
+       "      <td>292.0</td>\n",
+       "      <td>247.0</td>\n",
+       "      <td>281.0</td>\n",
+       "      <td>322.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>287.0</td>\n",
+       "      <td>275.0</td>\n",
+       "      <td>282.0</td>\n",
+       "      <td>298.0</td>\n",
+       "      <td>295.0</td>\n",
+       "      <td>323.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>282.0</td>\n",
+       "      <td>308.0</td>\n",
+       "      <td>307.0</td>\n",
+       "      <td>324.0</td>\n",
+       "      <td>263.0</td>\n",
+       "      <td>328.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>304.0</td>\n",
+       "      <td>288.0</td>\n",
+       "      <td>284.0</td>\n",
+       "      <td>318.0</td>\n",
+       "      <td>287.0</td>\n",
+       "      <td>348.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>299.0</td>\n",
+       "      <td>296.0</td>\n",
+       "      <td>291.0</td>\n",
+       "      <td>282.0</td>\n",
+       "      <td>316.0</td>\n",
+       "      <td>278.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>274.0</td>\n",
+       "      <td>272.0</td>\n",
+       "      <td>318.0</td>\n",
+       "      <td>263.0</td>\n",
+       "      <td>279.0</td>\n",
+       "      <td>391.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>292.0</td>\n",
+       "      <td>279.0</td>\n",
+       "      <td>320.0</td>\n",
+       "      <td>252.0</td>\n",
+       "      <td>302.0</td>\n",
+       "      <td>368.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>290.0</td>\n",
+       "      <td>290.0</td>\n",
+       "      <td>295.0</td>\n",
+       "      <td>293.0</td>\n",
+       "      <td>296.0</td>\n",
+       "      <td>386.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>297.0</td>\n",
+       "      <td>341.0</td>\n",
+       "      <td>323.0</td>\n",
+       "      <td>275.0</td>\n",
+       "      <td>336.0</td>\n",
+       "      <td>406.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>294.0</td>\n",
+       "      <td>329.0</td>\n",
+       "      <td>303.0</td>\n",
+       "      <td>274.0</td>\n",
+       "      <td>361.0</td>\n",
+       "      <td>396.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>279.0</td>\n",
+       "      <td>303.0</td>\n",
+       "      <td>355.0</td>\n",
+       "      <td>297.0</td>\n",
+       "      <td>334.0</td>\n",
+       "      <td>348.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>294.0</td>\n",
+       "      <td>322.0</td>\n",
+       "      <td>324.0</td>\n",
+       "      <td>324.0</td>\n",
+       "      <td>351.0</td>\n",
+       "      <td>387.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>343.0</td>\n",
+       "      <td>324.0</td>\n",
+       "      <td>372.0</td>\n",
+       "      <td>316.0</td>\n",
+       "      <td>353.0</td>\n",
+       "      <td>366.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>301.0</td>\n",
+       "      <td>360.0</td>\n",
+       "      <td>354.0</td>\n",
+       "      <td>317.0</td>\n",
+       "      <td>363.0</td>\n",
+       "      <td>350.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>232.0</td>\n",
+       "      <td>199.0</td>\n",
+       "      <td>249.0</td>\n",
+       "      <td>195.0</td>\n",
+       "      <td>194.0</td>\n",
+       "      <td>310.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>232.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>333.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "year   2015   2016   2017   2018   2019   2020\n",
+       "week                                          \n",
+       "1     319.0  424.0  416.0  447.0  365.0  353.0\n",
+       "2     373.0  348.0  434.0  481.0  371.0  395.0\n",
+       "3     383.0  372.0  397.0  470.0  332.0  411.0\n",
+       "4     397.0  355.0  387.0  426.0  335.0  347.0\n",
+       "5     374.0  314.0  371.0  433.0  296.0  323.0\n",
+       "6     347.0  310.0  336.0  351.0  319.0  332.0\n",
+       "7     328.0  217.0  337.0  364.0  342.0  306.0\n",
+       "8     317.0  423.0  351.0  366.0  337.0  297.0\n",
+       "9     401.0  298.0  352.0  314.0  310.0  347.0\n",
+       "10    346.0  309.0  357.0  387.0  342.0  312.0\n",
+       "11    323.0  292.0  251.0  359.0  343.0  324.0\n",
+       "12    310.0  306.0  356.0  326.0  294.0  271.0\n",
+       "13    323.0  280.0  314.0  319.0  307.0  287.0\n",
+       "14    221.0  295.0  306.0  286.0  287.0  434.0\n",
+       "15    294.0  292.0  270.0  350.0  301.0  435.0\n",
+       "16    327.0  293.0  245.0  280.0  316.0  424.0\n",
+       "17    316.0  306.0  327.0  282.0  272.0  470.0\n",
+       "18    335.0  258.0  258.0  292.0  357.0  427.0\n",
+       "19    256.0  318.0  302.0  230.0  288.0  336.0\n",
+       "20    299.0  259.0  315.0  268.0  330.0  396.0\n",
+       "21    290.0  280.0  328.0  268.0  308.0  325.0\n",
+       "22    258.0  284.0  256.0  252.0  245.0  316.0\n",
+       "23    340.0  275.0  292.0  276.0  279.0  304.0\n",
+       "24    272.0  299.0  300.0  277.0  281.0  292.0\n",
+       "25    292.0  252.0  271.0  265.0  296.0  290.0\n",
+       "26    303.0  291.0  296.0  271.0  262.0  295.0\n",
+       "27    300.0  286.0  262.0  266.0  285.0  289.0\n",
+       "28    252.0  237.0  253.0  172.0  256.0  275.0\n",
+       "29    203.0  281.0  288.0  298.0  280.0  240.0\n",
+       "30    274.0  298.0  287.0  282.0  269.0  307.0\n",
+       "31    291.0  264.0  287.0  278.0  273.0  273.0\n",
+       "32    248.0  270.0  238.0  270.0  266.0  280.0\n",
+       "33    235.0  260.0  266.0  283.0  284.0  278.0\n",
+       "34    251.0  301.0  271.0  280.0  274.0  313.0\n",
+       "35    259.0  264.0  243.0  251.0  223.0  303.0\n",
+       "36    237.0  275.0  278.0  265.0  243.0  234.0\n",
+       "37    324.0  294.0  266.0  285.0  305.0  296.0\n",
+       "38    283.0  272.0  292.0  247.0  281.0  322.0\n",
+       "39    287.0  275.0  282.0  298.0  295.0  323.0\n",
+       "40    282.0  308.0  307.0  324.0  263.0  328.0\n",
+       "41    304.0  288.0  284.0  318.0  287.0  348.0\n",
+       "42    299.0  296.0  291.0  282.0  316.0  278.0\n",
+       "43    274.0  272.0  318.0  263.0  279.0  391.0\n",
+       "44    292.0  279.0  320.0  252.0  302.0  368.0\n",
+       "45    290.0  290.0  295.0  293.0  296.0  386.0\n",
+       "46    297.0  341.0  323.0  275.0  336.0  406.0\n",
+       "47    294.0  329.0  303.0  274.0  361.0  396.0\n",
+       "48    279.0  303.0  355.0  297.0  334.0  348.0\n",
+       "49    294.0  322.0  324.0  324.0  351.0  387.0\n",
+       "50    343.0  324.0  372.0  316.0  353.0  366.0\n",
+       "51    301.0  360.0  354.0  317.0  363.0  350.0\n",
+       "52    232.0  199.0  249.0  195.0  194.0  310.0\n",
+       "53    232.0    NaN    NaN    NaN    NaN  333.0"
+      ]
+     },
+     "execution_count": 102,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_headlines_i = res.DataFrame().pivot(index='week', columns='year', values='deaths')\n",
+    "deaths_headlines_i"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 103,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>year</th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>2017</th>\n",
+       "      <th>2018</th>\n",
+       "      <th>2019</th>\n",
+       "      <th>2020</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>week</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>13751.0</td>\n",
+       "      <td>14863.0</td>\n",
+       "      <td>13612.0</td>\n",
+       "      <td>14701.0</td>\n",
+       "      <td>12424.0</td>\n",
+       "      <td>13768.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>18318.0</td>\n",
+       "      <td>13154.0</td>\n",
+       "      <td>15528.0</td>\n",
+       "      <td>17430.0</td>\n",
+       "      <td>14487.0</td>\n",
+       "      <td>16020.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>16738.0</td>\n",
+       "      <td>13060.0</td>\n",
+       "      <td>15231.0</td>\n",
+       "      <td>16355.0</td>\n",
+       "      <td>13545.0</td>\n",
+       "      <td>14723.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>15712.0</td>\n",
+       "      <td>12859.0</td>\n",
+       "      <td>14461.0</td>\n",
+       "      <td>15971.0</td>\n",
+       "      <td>13283.0</td>\n",
+       "      <td>13429.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>14560.0</td>\n",
+       "      <td>12571.0</td>\n",
+       "      <td>14188.0</td>\n",
+       "      <td>15087.0</td>\n",
+       "      <td>12799.0</td>\n",
+       "      <td>13123.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>13730.0</td>\n",
+       "      <td>12697.0</td>\n",
+       "      <td>13805.0</td>\n",
+       "      <td>14111.0</td>\n",
+       "      <td>13222.0</td>\n",
+       "      <td>12534.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>13510.0</td>\n",
+       "      <td>12016.0</td>\n",
+       "      <td>13212.0</td>\n",
+       "      <td>13925.0</td>\n",
+       "      <td>13347.0</td>\n",
+       "      <td>12412.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>13071.0</td>\n",
+       "      <td>12718.0</td>\n",
+       "      <td>13330.0</td>\n",
+       "      <td>13753.0</td>\n",
+       "      <td>12877.0</td>\n",
+       "      <td>12300.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>13181.0</td>\n",
+       "      <td>12733.0</td>\n",
+       "      <td>12819.0</td>\n",
+       "      <td>12190.0</td>\n",
+       "      <td>12479.0</td>\n",
+       "      <td>12334.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>13007.0</td>\n",
+       "      <td>12493.0</td>\n",
+       "      <td>12580.0</td>\n",
+       "      <td>14859.0</td>\n",
+       "      <td>12396.0</td>\n",
+       "      <td>12415.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>12475.0</td>\n",
+       "      <td>12489.0</td>\n",
+       "      <td>12089.0</td>\n",
+       "      <td>14367.0</td>\n",
+       "      <td>12018.0</td>\n",
+       "      <td>12499.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>12027.0</td>\n",
+       "      <td>10983.0</td>\n",
+       "      <td>11833.0</td>\n",
+       "      <td>13397.0</td>\n",
+       "      <td>11797.0</td>\n",
+       "      <td>12112.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>11987.0</td>\n",
+       "      <td>11738.0</td>\n",
+       "      <td>11453.0</td>\n",
+       "      <td>11310.0</td>\n",
+       "      <td>11260.0</td>\n",
+       "      <td>12507.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>10325.0</td>\n",
+       "      <td>13060.0</td>\n",
+       "      <td>11305.0</td>\n",
+       "      <td>12272.0</td>\n",
+       "      <td>11445.0</td>\n",
+       "      <td>18565.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>11575.0</td>\n",
+       "      <td>12757.0</td>\n",
+       "      <td>9761.0</td>\n",
+       "      <td>13843.0</td>\n",
+       "      <td>11661.0</td>\n",
+       "      <td>20929.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>13061.0</td>\n",
+       "      <td>12310.0</td>\n",
+       "      <td>11000.0</td>\n",
+       "      <td>12639.0</td>\n",
+       "      <td>10243.0</td>\n",
+       "      <td>24691.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>12023.0</td>\n",
+       "      <td>11795.0</td>\n",
+       "      <td>12356.0</td>\n",
+       "      <td>11596.0</td>\n",
+       "      <td>11452.0</td>\n",
+       "      <td>24303.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>11586.0</td>\n",
+       "      <td>10401.0</td>\n",
+       "      <td>10372.0</td>\n",
+       "      <td>11538.0</td>\n",
+       "      <td>12695.0</td>\n",
+       "      <td>20059.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>10138.0</td>\n",
+       "      <td>12002.0</td>\n",
+       "      <td>12114.0</td>\n",
+       "      <td>9821.0</td>\n",
+       "      <td>10361.0</td>\n",
+       "      <td>14428.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>11692.0</td>\n",
+       "      <td>11222.0</td>\n",
+       "      <td>11718.0</td>\n",
+       "      <td>11386.0</td>\n",
+       "      <td>11717.0</td>\n",
+       "      <td>16390.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>11334.0</td>\n",
+       "      <td>11013.0</td>\n",
+       "      <td>11431.0</td>\n",
+       "      <td>10974.0</td>\n",
+       "      <td>11653.0</td>\n",
+       "      <td>13839.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>9514.0</td>\n",
+       "      <td>9192.0</td>\n",
+       "      <td>9603.0</td>\n",
+       "      <td>9397.0</td>\n",
+       "      <td>9534.0</td>\n",
+       "      <td>11265.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>11603.0</td>\n",
+       "      <td>11171.0</td>\n",
+       "      <td>11134.0</td>\n",
+       "      <td>11259.0</td>\n",
+       "      <td>11461.0</td>\n",
+       "      <td>12106.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>10858.0</td>\n",
+       "      <td>10673.0</td>\n",
+       "      <td>10698.0</td>\n",
+       "      <td>10535.0</td>\n",
+       "      <td>10754.0</td>\n",
+       "      <td>11302.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>10629.0</td>\n",
+       "      <td>10611.0</td>\n",
+       "      <td>10930.0</td>\n",
+       "      <td>10514.0</td>\n",
+       "      <td>10807.0</td>\n",
+       "      <td>10694.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>10525.0</td>\n",
+       "      <td>10526.0</td>\n",
+       "      <td>10624.0</td>\n",
+       "      <td>10529.0</td>\n",
+       "      <td>10824.0</td>\n",
+       "      <td>10282.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>10545.0</td>\n",
+       "      <td>10412.0</td>\n",
+       "      <td>10565.0</td>\n",
+       "      <td>10565.0</td>\n",
+       "      <td>10328.0</td>\n",
+       "      <td>10412.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>10278.0</td>\n",
+       "      <td>10647.0</td>\n",
+       "      <td>10643.0</td>\n",
+       "      <td>10467.0</td>\n",
+       "      <td>10512.0</td>\n",
+       "      <td>9941.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>10028.0</td>\n",
+       "      <td>10672.0</td>\n",
+       "      <td>10426.0</td>\n",
+       "      <td>10353.0</td>\n",
+       "      <td>10324.0</td>\n",
+       "      <td>10096.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>10021.0</td>\n",
+       "      <td>10612.0</td>\n",
+       "      <td>10147.0</td>\n",
+       "      <td>10356.0</td>\n",
+       "      <td>10422.0</td>\n",
+       "      <td>10159.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>9893.0</td>\n",
+       "      <td>10433.0</td>\n",
+       "      <td>10239.0</td>\n",
+       "      <td>10408.0</td>\n",
+       "      <td>10564.0</td>\n",
+       "      <td>10262.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>10153.0</td>\n",
+       "      <td>10439.0</td>\n",
+       "      <td>10278.0</td>\n",
+       "      <td>10542.0</td>\n",
+       "      <td>10406.0</td>\n",
+       "      <td>10236.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>10352.0</td>\n",
+       "      <td>10312.0</td>\n",
+       "      <td>10569.0</td>\n",
+       "      <td>10091.0</td>\n",
+       "      <td>10405.0</td>\n",
+       "      <td>10592.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>10354.0</td>\n",
+       "      <td>10637.0</td>\n",
+       "      <td>10698.0</td>\n",
+       "      <td>10199.0</td>\n",
+       "      <td>10279.0</td>\n",
+       "      <td>10990.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>10239.0</td>\n",
+       "      <td>9226.0</td>\n",
+       "      <td>9372.0</td>\n",
+       "      <td>9046.0</td>\n",
+       "      <td>9478.0</td>\n",
+       "      <td>10364.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>9092.0</td>\n",
+       "      <td>10681.0</td>\n",
+       "      <td>10781.0</td>\n",
+       "      <td>10680.0</td>\n",
+       "      <td>10918.0</td>\n",
+       "      <td>9023.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>10573.0</td>\n",
+       "      <td>10401.0</td>\n",
+       "      <td>10692.0</td>\n",
+       "      <td>10496.0</td>\n",
+       "      <td>10892.0</td>\n",
+       "      <td>11176.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>10381.0</td>\n",
+       "      <td>10183.0</td>\n",
+       "      <td>10875.0</td>\n",
+       "      <td>10498.0</td>\n",
+       "      <td>10792.0</td>\n",
+       "      <td>10797.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>10826.0</td>\n",
+       "      <td>10278.0</td>\n",
+       "      <td>11027.0</td>\n",
+       "      <td>10463.0</td>\n",
+       "      <td>10954.0</td>\n",
+       "      <td>10890.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>10700.0</td>\n",
+       "      <td>10671.0</td>\n",
+       "      <td>11101.0</td>\n",
+       "      <td>10869.0</td>\n",
+       "      <td>11113.0</td>\n",
+       "      <td>11468.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>11108.0</td>\n",
+       "      <td>11016.0</td>\n",
+       "      <td>11357.0</td>\n",
+       "      <td>11048.0</td>\n",
+       "      <td>11403.0</td>\n",
+       "      <td>11373.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>10799.0</td>\n",
+       "      <td>11134.0</td>\n",
+       "      <td>11389.0</td>\n",
+       "      <td>11177.0</td>\n",
+       "      <td>11625.0</td>\n",
+       "      <td>11943.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>10966.0</td>\n",
+       "      <td>11048.0</td>\n",
+       "      <td>11152.0</td>\n",
+       "      <td>10885.0</td>\n",
+       "      <td>11415.0</td>\n",
+       "      <td>12317.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>11026.0</td>\n",
+       "      <td>11463.0</td>\n",
+       "      <td>11366.0</td>\n",
+       "      <td>10866.0</td>\n",
+       "      <td>11567.0</td>\n",
+       "      <td>12517.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>11312.0</td>\n",
+       "      <td>11803.0</td>\n",
+       "      <td>11767.0</td>\n",
+       "      <td>11588.0</td>\n",
+       "      <td>12177.0</td>\n",
+       "      <td>13448.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>11338.0</td>\n",
+       "      <td>12209.0</td>\n",
+       "      <td>11773.0</td>\n",
+       "      <td>11552.0</td>\n",
+       "      <td>12146.0</td>\n",
+       "      <td>13798.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>11178.0</td>\n",
+       "      <td>12064.0</td>\n",
+       "      <td>12102.0</td>\n",
+       "      <td>11289.0</td>\n",
+       "      <td>12472.0</td>\n",
+       "      <td>14291.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>11216.0</td>\n",
+       "      <td>11901.0</td>\n",
+       "      <td>12046.0</td>\n",
+       "      <td>11392.0</td>\n",
+       "      <td>12455.0</td>\n",
+       "      <td>14132.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>11748.0</td>\n",
+       "      <td>12733.0</td>\n",
+       "      <td>12342.0</td>\n",
+       "      <td>11687.0</td>\n",
+       "      <td>12275.0</td>\n",
+       "      <td>13986.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>11713.0</td>\n",
+       "      <td>12076.0</td>\n",
+       "      <td>12924.0</td>\n",
+       "      <td>12078.0</td>\n",
+       "      <td>12853.0</td>\n",
+       "      <td>13942.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>12136.0</td>\n",
+       "      <td>13137.0</td>\n",
+       "      <td>14308.0</td>\n",
+       "      <td>12649.0</td>\n",
+       "      <td>13566.0</td>\n",
+       "      <td>14658.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>9806.0</td>\n",
+       "      <td>9335.0</td>\n",
+       "      <td>9904.0</td>\n",
+       "      <td>8384.0</td>\n",
+       "      <td>8727.0</td>\n",
+       "      <td>13035.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>8774.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11580.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "year     2015     2016     2017     2018     2019     2020\n",
+       "week                                                      \n",
+       "1     13751.0  14863.0  13612.0  14701.0  12424.0  13768.0\n",
+       "2     18318.0  13154.0  15528.0  17430.0  14487.0  16020.0\n",
+       "3     16738.0  13060.0  15231.0  16355.0  13545.0  14723.0\n",
+       "4     15712.0  12859.0  14461.0  15971.0  13283.0  13429.0\n",
+       "5     14560.0  12571.0  14188.0  15087.0  12799.0  13123.0\n",
+       "6     13730.0  12697.0  13805.0  14111.0  13222.0  12534.0\n",
+       "7     13510.0  12016.0  13212.0  13925.0  13347.0  12412.0\n",
+       "8     13071.0  12718.0  13330.0  13753.0  12877.0  12300.0\n",
+       "9     13181.0  12733.0  12819.0  12190.0  12479.0  12334.0\n",
+       "10    13007.0  12493.0  12580.0  14859.0  12396.0  12415.0\n",
+       "11    12475.0  12489.0  12089.0  14367.0  12018.0  12499.0\n",
+       "12    12027.0  10983.0  11833.0  13397.0  11797.0  12112.0\n",
+       "13    11987.0  11738.0  11453.0  11310.0  11260.0  12507.0\n",
+       "14    10325.0  13060.0  11305.0  12272.0  11445.0  18565.0\n",
+       "15    11575.0  12757.0   9761.0  13843.0  11661.0  20929.0\n",
+       "16    13061.0  12310.0  11000.0  12639.0  10243.0  24691.0\n",
+       "17    12023.0  11795.0  12356.0  11596.0  11452.0  24303.0\n",
+       "18    11586.0  10401.0  10372.0  11538.0  12695.0  20059.0\n",
+       "19    10138.0  12002.0  12114.0   9821.0  10361.0  14428.0\n",
+       "20    11692.0  11222.0  11718.0  11386.0  11717.0  16390.0\n",
+       "21    11334.0  11013.0  11431.0  10974.0  11653.0  13839.0\n",
+       "22     9514.0   9192.0   9603.0   9397.0   9534.0  11265.0\n",
+       "23    11603.0  11171.0  11134.0  11259.0  11461.0  12106.0\n",
+       "24    10858.0  10673.0  10698.0  10535.0  10754.0  11302.0\n",
+       "25    10629.0  10611.0  10930.0  10514.0  10807.0  10694.0\n",
+       "26    10525.0  10526.0  10624.0  10529.0  10824.0  10282.0\n",
+       "27    10545.0  10412.0  10565.0  10565.0  10328.0  10412.0\n",
+       "28    10278.0  10647.0  10643.0  10467.0  10512.0   9941.0\n",
+       "29    10028.0  10672.0  10426.0  10353.0  10324.0  10096.0\n",
+       "30    10021.0  10612.0  10147.0  10356.0  10422.0  10159.0\n",
+       "31     9893.0  10433.0  10239.0  10408.0  10564.0  10262.0\n",
+       "32    10153.0  10439.0  10278.0  10542.0  10406.0  10236.0\n",
+       "33    10352.0  10312.0  10569.0  10091.0  10405.0  10592.0\n",
+       "34    10354.0  10637.0  10698.0  10199.0  10279.0  10990.0\n",
+       "35    10239.0   9226.0   9372.0   9046.0   9478.0  10364.0\n",
+       "36     9092.0  10681.0  10781.0  10680.0  10918.0   9023.0\n",
+       "37    10573.0  10401.0  10692.0  10496.0  10892.0  11176.0\n",
+       "38    10381.0  10183.0  10875.0  10498.0  10792.0  10797.0\n",
+       "39    10826.0  10278.0  11027.0  10463.0  10954.0  10890.0\n",
+       "40    10700.0  10671.0  11101.0  10869.0  11113.0  11468.0\n",
+       "41    11108.0  11016.0  11357.0  11048.0  11403.0  11373.0\n",
+       "42    10799.0  11134.0  11389.0  11177.0  11625.0  11943.0\n",
+       "43    10966.0  11048.0  11152.0  10885.0  11415.0  12317.0\n",
+       "44    11026.0  11463.0  11366.0  10866.0  11567.0  12517.0\n",
+       "45    11312.0  11803.0  11767.0  11588.0  12177.0  13448.0\n",
+       "46    11338.0  12209.0  11773.0  11552.0  12146.0  13798.0\n",
+       "47    11178.0  12064.0  12102.0  11289.0  12472.0  14291.0\n",
+       "48    11216.0  11901.0  12046.0  11392.0  12455.0  14132.0\n",
+       "49    11748.0  12733.0  12342.0  11687.0  12275.0  13986.0\n",
+       "50    11713.0  12076.0  12924.0  12078.0  12853.0  13942.0\n",
+       "51    12136.0  13137.0  14308.0  12649.0  13566.0  14658.0\n",
+       "52     9806.0   9335.0   9904.0   8384.0   8727.0  13035.0\n",
+       "53     8774.0      NaN      NaN      NaN      NaN  11580.0"
+      ]
+     },
+     "execution_count": 103,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_headlines = deaths_headlines_e + deaths_headlines_w + deaths_headlines_i + deaths_headlines_s\n",
+    "deaths_headlines"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 104,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Int64Index([2015, 2016, 2017, 2018, 2019, 2020], dtype='int64', name='year')"
+      ]
+     },
+     "execution_count": 104,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_headlines_e.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 105,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>year</th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>2017</th>\n",
+       "      <th>2018</th>\n",
+       "      <th>2019</th>\n",
+       "      <th>2020</th>\n",
+       "      <th>previous_mean</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>week</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>13751.0</td>\n",
+       "      <td>14863.0</td>\n",
+       "      <td>13612.0</td>\n",
+       "      <td>14701.0</td>\n",
+       "      <td>12424.0</td>\n",
+       "      <td>13768.0</td>\n",
+       "      <td>13870.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>18318.0</td>\n",
+       "      <td>13154.0</td>\n",
+       "      <td>15528.0</td>\n",
+       "      <td>17430.0</td>\n",
+       "      <td>14487.0</td>\n",
+       "      <td>16020.0</td>\n",
+       "      <td>15783.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>16738.0</td>\n",
+       "      <td>13060.0</td>\n",
+       "      <td>15231.0</td>\n",
+       "      <td>16355.0</td>\n",
+       "      <td>13545.0</td>\n",
+       "      <td>14723.0</td>\n",
+       "      <td>14985.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>15712.0</td>\n",
+       "      <td>12859.0</td>\n",
+       "      <td>14461.0</td>\n",
+       "      <td>15971.0</td>\n",
+       "      <td>13283.0</td>\n",
+       "      <td>13429.0</td>\n",
+       "      <td>14457.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>14560.0</td>\n",
+       "      <td>12571.0</td>\n",
+       "      <td>14188.0</td>\n",
+       "      <td>15087.0</td>\n",
+       "      <td>12799.0</td>\n",
+       "      <td>13123.0</td>\n",
+       "      <td>13841.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>13730.0</td>\n",
+       "      <td>12697.0</td>\n",
+       "      <td>13805.0</td>\n",
+       "      <td>14111.0</td>\n",
+       "      <td>13222.0</td>\n",
+       "      <td>12534.0</td>\n",
+       "      <td>13513.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>13510.0</td>\n",
+       "      <td>12016.0</td>\n",
+       "      <td>13212.0</td>\n",
+       "      <td>13925.0</td>\n",
+       "      <td>13347.0</td>\n",
+       "      <td>12412.0</td>\n",
+       "      <td>13202.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>13071.0</td>\n",
+       "      <td>12718.0</td>\n",
+       "      <td>13330.0</td>\n",
+       "      <td>13753.0</td>\n",
+       "      <td>12877.0</td>\n",
+       "      <td>12300.0</td>\n",
+       "      <td>13149.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>13181.0</td>\n",
+       "      <td>12733.0</td>\n",
+       "      <td>12819.0</td>\n",
+       "      <td>12190.0</td>\n",
+       "      <td>12479.0</td>\n",
+       "      <td>12334.0</td>\n",
+       "      <td>12680.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>13007.0</td>\n",
+       "      <td>12493.0</td>\n",
+       "      <td>12580.0</td>\n",
+       "      <td>14859.0</td>\n",
+       "      <td>12396.0</td>\n",
+       "      <td>12415.0</td>\n",
+       "      <td>13067.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>12475.0</td>\n",
+       "      <td>12489.0</td>\n",
+       "      <td>12089.0</td>\n",
+       "      <td>14367.0</td>\n",
+       "      <td>12018.0</td>\n",
+       "      <td>12499.0</td>\n",
+       "      <td>12687.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>12027.0</td>\n",
+       "      <td>10983.0</td>\n",
+       "      <td>11833.0</td>\n",
+       "      <td>13397.0</td>\n",
+       "      <td>11797.0</td>\n",
+       "      <td>12112.0</td>\n",
+       "      <td>12007.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>11987.0</td>\n",
+       "      <td>11738.0</td>\n",
+       "      <td>11453.0</td>\n",
+       "      <td>11310.0</td>\n",
+       "      <td>11260.0</td>\n",
+       "      <td>12507.0</td>\n",
+       "      <td>11549.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>10325.0</td>\n",
+       "      <td>13060.0</td>\n",
+       "      <td>11305.0</td>\n",
+       "      <td>12272.0</td>\n",
+       "      <td>11445.0</td>\n",
+       "      <td>18565.0</td>\n",
+       "      <td>11681.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>11575.0</td>\n",
+       "      <td>12757.0</td>\n",
+       "      <td>9761.0</td>\n",
+       "      <td>13843.0</td>\n",
+       "      <td>11661.0</td>\n",
+       "      <td>20929.0</td>\n",
+       "      <td>11919.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>13061.0</td>\n",
+       "      <td>12310.0</td>\n",
+       "      <td>11000.0</td>\n",
+       "      <td>12639.0</td>\n",
+       "      <td>10243.0</td>\n",
+       "      <td>24691.0</td>\n",
+       "      <td>11850.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>12023.0</td>\n",
+       "      <td>11795.0</td>\n",
+       "      <td>12356.0</td>\n",
+       "      <td>11596.0</td>\n",
+       "      <td>11452.0</td>\n",
+       "      <td>24303.0</td>\n",
+       "      <td>11844.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>11586.0</td>\n",
+       "      <td>10401.0</td>\n",
+       "      <td>10372.0</td>\n",
+       "      <td>11538.0</td>\n",
+       "      <td>12695.0</td>\n",
+       "      <td>20059.0</td>\n",
+       "      <td>11318.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>10138.0</td>\n",
+       "      <td>12002.0</td>\n",
+       "      <td>12114.0</td>\n",
+       "      <td>9821.0</td>\n",
+       "      <td>10361.0</td>\n",
+       "      <td>14428.0</td>\n",
+       "      <td>10887.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>11692.0</td>\n",
+       "      <td>11222.0</td>\n",
+       "      <td>11718.0</td>\n",
+       "      <td>11386.0</td>\n",
+       "      <td>11717.0</td>\n",
+       "      <td>16390.0</td>\n",
+       "      <td>11547.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>11334.0</td>\n",
+       "      <td>11013.0</td>\n",
+       "      <td>11431.0</td>\n",
+       "      <td>10974.0</td>\n",
+       "      <td>11653.0</td>\n",
+       "      <td>13839.0</td>\n",
+       "      <td>11281.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>9514.0</td>\n",
+       "      <td>9192.0</td>\n",
+       "      <td>9603.0</td>\n",
+       "      <td>9397.0</td>\n",
+       "      <td>9534.0</td>\n",
+       "      <td>11265.0</td>\n",
+       "      <td>9448.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>11603.0</td>\n",
+       "      <td>11171.0</td>\n",
+       "      <td>11134.0</td>\n",
+       "      <td>11259.0</td>\n",
+       "      <td>11461.0</td>\n",
+       "      <td>12106.0</td>\n",
+       "      <td>11325.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>10858.0</td>\n",
+       "      <td>10673.0</td>\n",
+       "      <td>10698.0</td>\n",
+       "      <td>10535.0</td>\n",
+       "      <td>10754.0</td>\n",
+       "      <td>11302.0</td>\n",
+       "      <td>10703.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>10629.0</td>\n",
+       "      <td>10611.0</td>\n",
+       "      <td>10930.0</td>\n",
+       "      <td>10514.0</td>\n",
+       "      <td>10807.0</td>\n",
+       "      <td>10694.0</td>\n",
+       "      <td>10698.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>10525.0</td>\n",
+       "      <td>10526.0</td>\n",
+       "      <td>10624.0</td>\n",
+       "      <td>10529.0</td>\n",
+       "      <td>10824.0</td>\n",
+       "      <td>10282.0</td>\n",
+       "      <td>10605.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>10545.0</td>\n",
+       "      <td>10412.0</td>\n",
+       "      <td>10565.0</td>\n",
+       "      <td>10565.0</td>\n",
+       "      <td>10328.0</td>\n",
+       "      <td>10412.0</td>\n",
+       "      <td>10483.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>10278.0</td>\n",
+       "      <td>10647.0</td>\n",
+       "      <td>10643.0</td>\n",
+       "      <td>10467.0</td>\n",
+       "      <td>10512.0</td>\n",
+       "      <td>9941.0</td>\n",
+       "      <td>10509.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>10028.0</td>\n",
+       "      <td>10672.0</td>\n",
+       "      <td>10426.0</td>\n",
+       "      <td>10353.0</td>\n",
+       "      <td>10324.0</td>\n",
+       "      <td>10096.0</td>\n",
+       "      <td>10360.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>10021.0</td>\n",
+       "      <td>10612.0</td>\n",
+       "      <td>10147.0</td>\n",
+       "      <td>10356.0</td>\n",
+       "      <td>10422.0</td>\n",
+       "      <td>10159.0</td>\n",
+       "      <td>10311.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>9893.0</td>\n",
+       "      <td>10433.0</td>\n",
+       "      <td>10239.0</td>\n",
+       "      <td>10408.0</td>\n",
+       "      <td>10564.0</td>\n",
+       "      <td>10262.0</td>\n",
+       "      <td>10307.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>10153.0</td>\n",
+       "      <td>10439.0</td>\n",
+       "      <td>10278.0</td>\n",
+       "      <td>10542.0</td>\n",
+       "      <td>10406.0</td>\n",
+       "      <td>10236.0</td>\n",
+       "      <td>10363.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>10352.0</td>\n",
+       "      <td>10312.0</td>\n",
+       "      <td>10569.0</td>\n",
+       "      <td>10091.0</td>\n",
+       "      <td>10405.0</td>\n",
+       "      <td>10592.0</td>\n",
+       "      <td>10345.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>10354.0</td>\n",
+       "      <td>10637.0</td>\n",
+       "      <td>10698.0</td>\n",
+       "      <td>10199.0</td>\n",
+       "      <td>10279.0</td>\n",
+       "      <td>10990.0</td>\n",
+       "      <td>10433.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>10239.0</td>\n",
+       "      <td>9226.0</td>\n",
+       "      <td>9372.0</td>\n",
+       "      <td>9046.0</td>\n",
+       "      <td>9478.0</td>\n",
+       "      <td>10364.0</td>\n",
+       "      <td>9472.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>9092.0</td>\n",
+       "      <td>10681.0</td>\n",
+       "      <td>10781.0</td>\n",
+       "      <td>10680.0</td>\n",
+       "      <td>10918.0</td>\n",
+       "      <td>9023.0</td>\n",
+       "      <td>10430.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>10573.0</td>\n",
+       "      <td>10401.0</td>\n",
+       "      <td>10692.0</td>\n",
+       "      <td>10496.0</td>\n",
+       "      <td>10892.0</td>\n",
+       "      <td>11176.0</td>\n",
+       "      <td>10610.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>10381.0</td>\n",
+       "      <td>10183.0</td>\n",
+       "      <td>10875.0</td>\n",
+       "      <td>10498.0</td>\n",
+       "      <td>10792.0</td>\n",
+       "      <td>10797.0</td>\n",
+       "      <td>10545.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>10826.0</td>\n",
+       "      <td>10278.0</td>\n",
+       "      <td>11027.0</td>\n",
+       "      <td>10463.0</td>\n",
+       "      <td>10954.0</td>\n",
+       "      <td>10890.0</td>\n",
+       "      <td>10709.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>10700.0</td>\n",
+       "      <td>10671.0</td>\n",
+       "      <td>11101.0</td>\n",
+       "      <td>10869.0</td>\n",
+       "      <td>11113.0</td>\n",
+       "      <td>11468.0</td>\n",
+       "      <td>10890.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>11108.0</td>\n",
+       "      <td>11016.0</td>\n",
+       "      <td>11357.0</td>\n",
+       "      <td>11048.0</td>\n",
+       "      <td>11403.0</td>\n",
+       "      <td>11373.0</td>\n",
+       "      <td>11186.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>10799.0</td>\n",
+       "      <td>11134.0</td>\n",
+       "      <td>11389.0</td>\n",
+       "      <td>11177.0</td>\n",
+       "      <td>11625.0</td>\n",
+       "      <td>11943.0</td>\n",
+       "      <td>11224.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>10966.0</td>\n",
+       "      <td>11048.0</td>\n",
+       "      <td>11152.0</td>\n",
+       "      <td>10885.0</td>\n",
+       "      <td>11415.0</td>\n",
+       "      <td>12317.0</td>\n",
+       "      <td>11093.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>11026.0</td>\n",
+       "      <td>11463.0</td>\n",
+       "      <td>11366.0</td>\n",
+       "      <td>10866.0</td>\n",
+       "      <td>11567.0</td>\n",
+       "      <td>12517.0</td>\n",
+       "      <td>11257.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>11312.0</td>\n",
+       "      <td>11803.0</td>\n",
+       "      <td>11767.0</td>\n",
+       "      <td>11588.0</td>\n",
+       "      <td>12177.0</td>\n",
+       "      <td>13448.0</td>\n",
+       "      <td>11729.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>11338.0</td>\n",
+       "      <td>12209.0</td>\n",
+       "      <td>11773.0</td>\n",
+       "      <td>11552.0</td>\n",
+       "      <td>12146.0</td>\n",
+       "      <td>13798.0</td>\n",
+       "      <td>11803.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>11178.0</td>\n",
+       "      <td>12064.0</td>\n",
+       "      <td>12102.0</td>\n",
+       "      <td>11289.0</td>\n",
+       "      <td>12472.0</td>\n",
+       "      <td>14291.0</td>\n",
+       "      <td>11821.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>11216.0</td>\n",
+       "      <td>11901.0</td>\n",
+       "      <td>12046.0</td>\n",
+       "      <td>11392.0</td>\n",
+       "      <td>12455.0</td>\n",
+       "      <td>14132.0</td>\n",
+       "      <td>11802.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>11748.0</td>\n",
+       "      <td>12733.0</td>\n",
+       "      <td>12342.0</td>\n",
+       "      <td>11687.0</td>\n",
+       "      <td>12275.0</td>\n",
+       "      <td>13986.0</td>\n",
+       "      <td>12157.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>11713.0</td>\n",
+       "      <td>12076.0</td>\n",
+       "      <td>12924.0</td>\n",
+       "      <td>12078.0</td>\n",
+       "      <td>12853.0</td>\n",
+       "      <td>13942.0</td>\n",
+       "      <td>12328.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>12136.0</td>\n",
+       "      <td>13137.0</td>\n",
+       "      <td>14308.0</td>\n",
+       "      <td>12649.0</td>\n",
+       "      <td>13566.0</td>\n",
+       "      <td>14658.0</td>\n",
+       "      <td>13159.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>9806.0</td>\n",
+       "      <td>9335.0</td>\n",
+       "      <td>9904.0</td>\n",
+       "      <td>8384.0</td>\n",
+       "      <td>8727.0</td>\n",
+       "      <td>13035.0</td>\n",
+       "      <td>9231.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>8774.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11580.0</td>\n",
+       "      <td>8774.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "year     2015     2016     2017     2018     2019     2020  previous_mean\n",
+       "week                                                                     \n",
+       "1     13751.0  14863.0  13612.0  14701.0  12424.0  13768.0        13870.2\n",
+       "2     18318.0  13154.0  15528.0  17430.0  14487.0  16020.0        15783.4\n",
+       "3     16738.0  13060.0  15231.0  16355.0  13545.0  14723.0        14985.8\n",
+       "4     15712.0  12859.0  14461.0  15971.0  13283.0  13429.0        14457.2\n",
+       "5     14560.0  12571.0  14188.0  15087.0  12799.0  13123.0        13841.0\n",
+       "6     13730.0  12697.0  13805.0  14111.0  13222.0  12534.0        13513.0\n",
+       "7     13510.0  12016.0  13212.0  13925.0  13347.0  12412.0        13202.0\n",
+       "8     13071.0  12718.0  13330.0  13753.0  12877.0  12300.0        13149.8\n",
+       "9     13181.0  12733.0  12819.0  12190.0  12479.0  12334.0        12680.4\n",
+       "10    13007.0  12493.0  12580.0  14859.0  12396.0  12415.0        13067.0\n",
+       "11    12475.0  12489.0  12089.0  14367.0  12018.0  12499.0        12687.6\n",
+       "12    12027.0  10983.0  11833.0  13397.0  11797.0  12112.0        12007.4\n",
+       "13    11987.0  11738.0  11453.0  11310.0  11260.0  12507.0        11549.6\n",
+       "14    10325.0  13060.0  11305.0  12272.0  11445.0  18565.0        11681.4\n",
+       "15    11575.0  12757.0   9761.0  13843.0  11661.0  20929.0        11919.4\n",
+       "16    13061.0  12310.0  11000.0  12639.0  10243.0  24691.0        11850.6\n",
+       "17    12023.0  11795.0  12356.0  11596.0  11452.0  24303.0        11844.4\n",
+       "18    11586.0  10401.0  10372.0  11538.0  12695.0  20059.0        11318.4\n",
+       "19    10138.0  12002.0  12114.0   9821.0  10361.0  14428.0        10887.2\n",
+       "20    11692.0  11222.0  11718.0  11386.0  11717.0  16390.0        11547.0\n",
+       "21    11334.0  11013.0  11431.0  10974.0  11653.0  13839.0        11281.0\n",
+       "22     9514.0   9192.0   9603.0   9397.0   9534.0  11265.0         9448.0\n",
+       "23    11603.0  11171.0  11134.0  11259.0  11461.0  12106.0        11325.6\n",
+       "24    10858.0  10673.0  10698.0  10535.0  10754.0  11302.0        10703.6\n",
+       "25    10629.0  10611.0  10930.0  10514.0  10807.0  10694.0        10698.2\n",
+       "26    10525.0  10526.0  10624.0  10529.0  10824.0  10282.0        10605.6\n",
+       "27    10545.0  10412.0  10565.0  10565.0  10328.0  10412.0        10483.0\n",
+       "28    10278.0  10647.0  10643.0  10467.0  10512.0   9941.0        10509.4\n",
+       "29    10028.0  10672.0  10426.0  10353.0  10324.0  10096.0        10360.6\n",
+       "30    10021.0  10612.0  10147.0  10356.0  10422.0  10159.0        10311.6\n",
+       "31     9893.0  10433.0  10239.0  10408.0  10564.0  10262.0        10307.4\n",
+       "32    10153.0  10439.0  10278.0  10542.0  10406.0  10236.0        10363.6\n",
+       "33    10352.0  10312.0  10569.0  10091.0  10405.0  10592.0        10345.8\n",
+       "34    10354.0  10637.0  10698.0  10199.0  10279.0  10990.0        10433.4\n",
+       "35    10239.0   9226.0   9372.0   9046.0   9478.0  10364.0         9472.2\n",
+       "36     9092.0  10681.0  10781.0  10680.0  10918.0   9023.0        10430.4\n",
+       "37    10573.0  10401.0  10692.0  10496.0  10892.0  11176.0        10610.8\n",
+       "38    10381.0  10183.0  10875.0  10498.0  10792.0  10797.0        10545.8\n",
+       "39    10826.0  10278.0  11027.0  10463.0  10954.0  10890.0        10709.6\n",
+       "40    10700.0  10671.0  11101.0  10869.0  11113.0  11468.0        10890.8\n",
+       "41    11108.0  11016.0  11357.0  11048.0  11403.0  11373.0        11186.4\n",
+       "42    10799.0  11134.0  11389.0  11177.0  11625.0  11943.0        11224.8\n",
+       "43    10966.0  11048.0  11152.0  10885.0  11415.0  12317.0        11093.2\n",
+       "44    11026.0  11463.0  11366.0  10866.0  11567.0  12517.0        11257.6\n",
+       "45    11312.0  11803.0  11767.0  11588.0  12177.0  13448.0        11729.4\n",
+       "46    11338.0  12209.0  11773.0  11552.0  12146.0  13798.0        11803.6\n",
+       "47    11178.0  12064.0  12102.0  11289.0  12472.0  14291.0        11821.0\n",
+       "48    11216.0  11901.0  12046.0  11392.0  12455.0  14132.0        11802.0\n",
+       "49    11748.0  12733.0  12342.0  11687.0  12275.0  13986.0        12157.0\n",
+       "50    11713.0  12076.0  12924.0  12078.0  12853.0  13942.0        12328.8\n",
+       "51    12136.0  13137.0  14308.0  12649.0  13566.0  14658.0        13159.2\n",
+       "52     9806.0   9335.0   9904.0   8384.0   8727.0  13035.0         9231.2\n",
+       "53     8774.0      NaN      NaN      NaN      NaN  11580.0         8774.0"
+      ]
+     },
+     "execution_count": 105,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_headlines_e['previous_mean'] = deaths_headlines_e[[int(y) for y in '2019 2018 2017 2016 2015'.split()]].apply(np.mean, axis=1)\n",
+    "deaths_headlines_w['previous_mean'] = deaths_headlines_w[[int(y) for y in '2019 2018 2017 2016 2015'.split()]].apply(np.mean, axis=1)\n",
+    "deaths_headlines_s['previous_mean'] = deaths_headlines_s[[int(y) for y in '2019 2018 2017 2016 2015'.split()]].apply(np.mean, axis=1)\n",
+    "deaths_headlines_i['previous_mean'] = deaths_headlines_i[[int(y) for y in '2019 2018 2017 2016 2015'.split()]].apply(np.mean, axis=1)\n",
+    "deaths_headlines['previous_mean'] = deaths_headlines[[int(y) for y in '2019 2018 2017 2016 2015'.split()]].apply(np.mean, axis=1)\n",
+    "deaths_headlines"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 106,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='week'>"
+      ]
+     },
+     "execution_count": 106,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1008x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "deaths_headlines[[2020, 2019, 2018, 2017, 2016, 2015]].plot(figsize=(14, 8))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 107,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='week'>"
+      ]
+     },
+     "execution_count": 107,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "deaths_headlines[[2020, 'previous_mean']].plot(figsize=(10, 8))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 108,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='week'>"
+      ]
+     },
+     "execution_count": 108,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "deaths_headlines_i.plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 109,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "83207.6000000001"
+      ]
+     },
+     "execution_count": 109,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_headlines[2020].sum() - deaths_headlines.previous_mean.sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 115,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
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996twLGm/bIXV9CqzGAAxKpUqg8fjpVoslvCQkBBRcHAw1Gq1f1JSkl2r1QoCAwOJRqNBYGAg5HI5WKz1vbiYx+NBKpVCKpXO9zAbgPjiO6emptDf3x/e29uL3t5e9PT02Ovq6sxtbW22tra2yeDgYGq320c5HE7D+Ph46cjISCWABgDNlFKjm3dpXUAICQawA8DTAL7r5ekwMKwbGGHFwPCZ6zkFsI9S+icAqukUESilvdPGnZc0hBAWHOIpISAgIMXPzy/DarXGsFgs/5SUFJKYmMhOS0vzjY+P58fExCA8PBw8Hg8AUFpaiujoaIjFczTIZQmPx0NISAhCQkKcd7Gam5uFHA4HWq3WFwAMBoOqsbExpqGh4Ybq6urJ8vLyifr6egQGBlpZLNYAIaRGr9eXTE5O1sDRuLnnMqv9ehHAowD8vDwPBoZ1BSOsGBjmcT339oTWynTtSwwhJEOj0VxNKc0OCQmRxcXFkU2bNvkkJiaKYmJiEBUVBT+/pc+LIpEIk5OTV4ywmg+j0QiVSjXzf19fX2zYsAEbNmwAHMX3IgCglGJoaEjT0NCQWl9fv6uysnL89OnTpvb2dhocHNxpsVhODAwMHANwDkDXpSi2CCE3ABiglJYSQgq8PB0GhnUFU2PFwDALQsgeOBrc3g+gYDpapQFwlFIa69XJLcC0iIqbLaI4HI4kISGBbN261S87O1uQnp6OgICAVY/R3t4Om82GiIiIZT2fUoqpqSlYLBZYrdY5N5vNNu/9VqsVlNKZm3NblFKMj4/Dz88PhJCZxtTOv1ksFjgczgU3Nps9577ZNx6PBw6Hs+wm12fOnEFiYiJ8fHxW9R5SStHd3Y3S0lKcOnXKcOLEicm2tjbKYrG6LBbLyWmxVQqgc72LLULI/wL4MgArAAEc6dR/UUrv8urEGAAApaWlSg6H8xKAJFxZRuB2AOetVut9GRkZA96aBCOsGK5opp3OWZTS8em/jwB4EsDVAHSzitellNJHvTlXJ4QQCYAtarX6ZkJILpfLlSQmJmLr1q3+2dnZ/A0bNsDf39+lYw4MDGBwcBDx8fEwm80wm80wmUwzt9n/dx5TeDzejHhZTOQ4H5teDQgWizVHOAHAsWPHsHXrVgC4QHxRSmG325cUbBeLOqfwAwA2mw2BQAA+nw+BQHDBjc/ng8fj4fjx49i8ebPLa8p6enouEFutra2UENJtMpn+q9PpDgEoppSaXTqoC5mOWD3CFK+vHyoqKg6q1ep4hUIxxmKxrpiTvN1uJ4ODg/59fX01qampN3lrHkwqkOFKZyHX87MA3iKE/D8AHQB2emuC00Jqs0aj+QKltCAxMdHnuuuuE2zfvl2cnZ3t8vScxWKBwWDAxMQEDAbDzCo6o9GIoaGhGfHh/Nff3/8CEeLOYvbZguti+Hz+qrdrtVrniMXx8fGZ+6ampjA+Po5Tp07Bx8cHvr6+8PX1hY+PD3x8fMBms1c9dmBgIAIDA3HjjTc6fbzQ09OjKiws3HDo0KH7jh49agsKCuo3m83vTwut0+tZaDGsC5IUCsXwlSSqAIDFYlGFQjHa19eX5M15MBErBoZ1xsVCSiqV+qanp0vuvvtuTm5u7qpTUbOx2WyYmJi4QDxNTEzAarWCw+HMiAangODz+SguLsaWLVvWvoOrZLV2C67AarWiqKgImzZtmvOeTUxMwG63g8/nzxFdIpFo2anGxejv78d///tf+s9//nOqrKxsbGpqyim03gdwhhFaDLOpqKhoS01NHVr6mZcnFRUV8tTU1DBvjc9ErBgYvAwhRABgW2Bg4BcppQUJCQl+1113neC6667zcwqpwsJCZGRkQCAQrHj7U1NTGB0dxcjICEZGRjAxMQEWizUTbfH19YVCoYCPjw+4XO6C27Hbr1zfTKPRCKFQCC6Xi4CAgDn1apRSmM3mGdE1ODiI1tZWGI1GEEIgFotnXicWi1cc4VKpVCgoKCCZmZn82NhYRX9/v+Lo0aOJhw4duv/48eO2oKCgvmmh9S6AEsbklMHbNDU1ce+8887wwcFBLovFwj333DP405/+dKC/v599yy23RHR3d/ODgoLM//73v1sUCoWtr6+PffPNN0dWVVX5fPGLX9S99tprHc5tZWVlxQ4MDHAFAoEdAD7++OOGoKAgq/f2bnEYYcXA4AUIIUo+n3+TXC6/JzQ0NHbHjh28m2++2T8vLw++vr5zni+TyaDT6RAUFLTodqempjAyMjIjpAwGA7hcLvz9/REQEIC4uDj4+vquKorCYrFgs9nWlPa6VHEKq4UghMykQ2Uy2QWP2Ww2jI2NYWRkBG1tbRgbGwOAGbHl7+8Pf3//Jd/XoaGhmc9fpVLhtttuI7fddpsUAPr7+xWffvpp0ltvvXV/UVGRNTg4uLC7u/sVAB9TSifXsOsMDKuCy+Xi+eef78rPz58cHh5mbdiwIeH6668f+/Of/ywvKCgYf+aZZxp/9KMfqR9//HH1H/7wh26RSESffPLJnoqKCuH58+fn/Nhee+21li1btlwS32VGWDEweIBpB/P4gICALwmFwl1JSUnS22+/3e/WW28VxMbGLil05HI5enp6LhBWNpsNw8PD0Ov1GB0dnRFRzpP1WkTUfAiFQhiNxnmF3+XO5OQkRCLRql7LZrMhkUggkUhm7psttjo6OjA6OgoA8PPzQ0BAAGQyGcRi8QWf3fDwMJKS5i8dUalU2LVrF9m1a5fMZrOhqKjo1rfeeuua9957zxwcHNys0+leMZlM/6aU9q1qJxgYVohWq7VotVoLAEgkEntkZKSxo6OD9+GHHwYcO3asHgB2796t27p1ayyAbrFYbN++fbuhvr5+9cWS6wRGWDEwuAlCCBdAvlqt/rJKpdqenJzMvfPOO6U7duxgKxSKFW1LIpHg/PnzGBoawtDQEHQ6HSwWy4yjuEajcamImg+nl9WVKqwujkSthYXE1vj4OEZGRtDU1ISxsTGIRCLI5XKIxeKZFZTL2XZ+fj7y8/PFv/71r9HY2Kh49913N/z9739/KjAwcMRsNr+l1+vfAlC13m0dGC4P6uvreTU1NaKtW7cadDodxym4tFqtRa/XL0uH3HfffWEsFgs33njj8P/93//1rueOD4ywYmBwIYQQPovF2qHRaB4IDAxM+9znPsfZtWuXpKCgYMX1Uc6IlFNIGQwGdHZ2QqVSITw8fE2r4FaDM2J1JbJUKtAVsNnsmTqssLAwUEoxMTEBnU6Huro6TExM4MyZM5DJZDNiazlCOjo6Go8++ij/0UcfVej1esWhQ4d++MYbb3ytvLzcGhgYeKS3t3cfgCJGZF2eDL/7bohlYGB14dYF4CqVk5JbbulcznNHR0dZt956a+Szzz7bKZVKV1X7t3///pbw8HDL8PAw64Ybboj8/e9/L/vmN7+pW822PAEjrBjWDdNGlyUAuimlNxBCUgH8EY4l6G0A7qSUjnlxivMy3Spmc2Bg4DcDAwO3fvGLX+Tfe++94rS0tBVFkOx2O/R6PXQ6HYaGhmCxWCCRSKBQKBAeHo6Wlhb4+/sjMDDQfTuzCCKRCMPDV2bv4bWkAlcLIWRmheHo6ChiY2MhEokwNDQ0E9Hy8fGBTCaDQqGYMU9dDKlUirvuuot11113KaampnD06NG79+3bt6OwsNCsUCj2Dw0N/YlSekl0Hphunj4OwAbASinN9O6MGC7GbDaTHTt2RO7cuVN/zz33jACATCaztre3c7VaraW9vZ0rlUqXLEIPDw+fSSnedttt+jNnzvgAYIQVA8MyeAhALT5rivsSHMaDxwghXwXwfQA/9dbkLoYQkqRUKh9UqVS3bNu2jb97927pli1bVuTjZLFY0N/fj76+PoyPj0MqlUIul0Or1c6JcMnlcvT19XlVWHV3d3tlbG9js9nA4XjvcDk8PIzExESw2Wz4+vpeENEaGhpCfX09DAYDZDIZ1Gr1sppj83g8XHvttbj22mtlk5OTOHjw4EO/+93v7tJoNGNGo/HPo6Ojr14CNVnbKKVXrK3AclhuZMnV2O127Nq1SxsTE2Pas2dPv/P+7du3j+zbt0/2zDPP9O3bt0923XXXjSy2HYvFgqGhIY5Go7GazWZy6NAh/6uuumrc7TuwBhhhxbAuIIQEA9gB4GkA352+OxbA8em/jwA4DC8LK0JIcEBAwFcEAsFXrrrqKr+vf/3r0h07drBWkuabmJhAX18f+vr6YLPZoFKpZhocLxZxkEgkqKmpccVurIorNRVot9vdWru2FFNTU2Cz2XPqq2ZHtMLCwmC32zE0NIT+/n5UV1fD19cXarUaKpVqppn2QohEIuzatYu1a9cuxdDQkOLNN9986k9/+tP3goKCuvR6/a9NJtM/KaXr+mTGsL44cuSI74EDB2TR0dHGuLi4BADYu3dv9969e3tvueWWSK1WKw8MDJw6cOBAs/M1QUFByQaDgW2xWMjhw4cDDh061BAdHT11zTXXRFssFmK328nmzZvHvvvd7w56b8+WhhFWDOuFFwE8CmB2R+DzAG4C8G84nM9DPD8tgBDiLxQKb5NKpd9OTU1VPvjgg5IvfelLnNmFx4tBKcXw8DD6+vowMDAAgUAAtVqN9PT0FdXtcDgcsFgsTE1NLXmidAdcLhdW67q1jnEbnqivWgydTreswnkWiwWlUgmlUjnTW7Gvrw+nT58GIQRqtRpqtXrJxQdyuRzf+ta3uN/61rcUzc3NildfffV3r7322s/DwsLOt7e3/wLAR5RSi4t2by1QAB8RQiiAfZTSP3l7QgyfsX37dgOltHS+x4qKihrmu7+7u7tqvvurq6trXTk3d8MIKwavQwi5AcAApbR0uu+Yk68C+DUh5HEABwFMeXBOBMCmwMDAH4aFheXceeedfllZWfybblpe+ym73Y6BgQH09vZieHgYEokEarUaMTExa0opOf2sNBrNqrexFgghsNvtbm1bs97wtrAaGhqCSqVa0WucpqRisRgxMTEwmUwzkSyj0QiFQgGNRgOJRLJoNC4yMhJPPvmk6IknnhD9+c9/LigrK9tw8OBBs1Kp3D84OPhLSmnrWvdvDeRRSnsIIUoARwghdZTS40u+ioHBzTDCimE9kAfgJkLI9QAEAMSEkDcopXcBuBYACCExcKQK3QohROzn53evSqX6TlZWlviRRx6Rbd68GQBw/PjxRaNFlFLo9Xp0dXVBr9dDoVBAq9VipUXsiyGXyzEwMOA1YSUQCGAymTxeyO1NvFG4Phu9Xo/4+Pg1bUMgEECr1UKr1cJms804w1dWVkKtViM4OHjRSNbg4CDy8vLwwAMP+P/617/Gv/71r6///Oc/3xUUFNTW19f3tN1uf59S6tFwJqW0Z/rfAULIuwCy8FnpAAOD12CEFYPXoZT+EMAPAWA6YvUIpfQuQohy+qDJAvATOFYIugVCSKparf5xaGhowYMPPuh73333CeVy+QXPCQ4ORldXFyIiIi64f3x8HF1dXejr64O/vz+Cg4ORkpLilrociUSCujrvLdpy1lldScLKaDTCz89v6Se6AYvFAhaL5dLCeTabPZMWtFqt6O3tRVVVFaxWK4KCghAUFDTHyqOjowOxsbEAHM2ub7/9dvbtt9+uqKurU/zqV7969cCBA0aFQvH60NDQLymlvS6b7AIQQnwAsCil49N/XwvgSXePy8CwHBhhxbCeuZ0Q8o3pv/8F4K+u3DghhMvlcm+Vy+U/KSgoUP/4xz+WX3XVVQumuYKDg3H69GlERETAZDKhu7sb3d3d4PP5CA4ORkxMjNvbvTh7+VkslkX7+rkLp0moK80y1zuTk5MrTsW5Cp1OB6lU6rbtczgchISEICQkZOY7febMGXC5XAQHB0OtVsNms8FkMsHf33/O6+Pi4vCHP/zB/4UXXvD/xz/+8fBzzz13b1BQUHlPT88euNcbSwXg3emLFw6Av1NKP3TTWAwMK4IRVgzrCkrpUQBHp//+FYBfuXoMQohKJpN9R6VS3Xvbbbf5PPzww35hYWFLvo7FYsFut+P48eNgsVgICgpCdna2x406ZTIZ9Hq9V072IpEI4+NX1uIwb6YCdTodLo6cuguBQIDIyEhERkbCYDCgq6sLJ0+eBOCIlC5WWycUCvGVr3yFc++99ypOnz79uWeeeSb97Nmzwz4+Ps9NTk6+QSl16XJSSmkLgFRXbpOBwVUwworhioEQEqNWq5+Njo7e/P3vfz/gzjvv5Cx1wqSUzjTPHR0dnTFhTE9P99Cs5yKTyVZV0OwKhEIhBgYGPD6uN/FWdBBwCKuYmBiPj+vr64u4uDjExsbik08+AaUUx44dg1qthlarXVBoEkKwadMmHDx4UNbX1yf77W9/+8u//OUvP1MoFK8MDQ39H6VU7+FdYWDwOFfO0h6GKxZCSHpgYODH6enphX/961+/UF9fL7///vsXFVUWiwVtbW04ceIEmpubERISgq1bt2LDhg0YHR2F3b6qzgwuwRmx8gbOVOCVgjOT5Q0fK4vF4WjgLVEHAKOjoxCLxUhLS8OWLVvg6+uLsrIyFBcXo6+vD4tl+tRqNX72s5/5tLa2Kp988snvhIaG1qvV6j8RQrzjcMvgUZqamrjZ2dkxERERiVFRUYlPPfWUEgD6+/vZubm50VqtNik3Nzd6cHCQDQB9fX3s7OzsGJFItOHuu+8Onb0tk8lEbr/9dm1YWFhSeHh44iuvvBLghV1aNoywYrgsIQ62ajSas1u3bv3on//851WlpaXy6667jix2khwbG0NFRQUKCwthsViQnZ2NzMxMyOVyEEJmvIL6+rxnSM3lckEpnTnxehIej4epKY+5Xngdk8m04h6PrkKv13u9lq2jowOhoY5zHJvNRkhICPLy8pCQkIDBwUEcPXoU9fX1MJlMC26Dz+fjwQcf5LW0tMhffPHFr0ZHR1doNJq3CCFRntoPBs/D5XLx/PPPd7W0tFSfPXu29uWXX1aWlpYKnnjiCU1BQcF4e3v7+YKCgvHHH39cDQAikYg++eSTPXv27Om6eFs//OEPNQqFwtLW1na+qampevv27QbP79HyYVKBDJcVhBAWh8O5Qa1WP5udna166qmnpMnJyYu+xm63o6+vD62treBwOAgPD190VV9ISAhqamq81loGcPR8Gx4ehlKp9Oi4zveEUupVN3JP4U0Pq6GhIa8KK5vNhqGhISQlJc15TCwWIzk5GVardabg3cfHB+Hh4QsW27PZbOzatYt92223yQ8dOvTFH//4x9sCAwPP9fb2PkoprXD3/jB4Fq1Wa9FqtTM9/iIjI40dHR28Dz/8MODYsWP1ALB7927d1q1bYwF0i8Vi+/bt2w319fVzilbffPNNeUNDw3nA8T3SaDTr2qmYiVgxXBYQQjhCofBulUrVdOedd75aWFgYf+DAgUVFldlsRkNDA44dOwa9Xo+0tDRkZ2dDqVQuKhrEYjEsFsuiV+nuxlln5Q34fD7MZrNXxvY03ixc93bEqq+vDyqValEzWA6HA61Wi82bNyMsLAwtLS04ceIEOjo6YLPZ5n0NIQQ7duwg5eXl8rfeeuva/Pz8jwMDA4sJIfnu2hcG71JfX8+rqakRbd261aDT6ThOwaXVai16vX7RAM/Q0BAbAL773e8GJiQkxH/+85+P6OzsXNdBoXU9OQaGpSCECMRi8W6VSvXorl27/H7wgx/4qdXqRV8zMTGBpqYmjIyMzJwUVuoTFBISgs7OTkRHR69l+qtGJpOhqanJK2M7vay8lSLzJN6KWFmtVtjtdq/WV3V2diIxMXFZzyWEQCaTQSaTwWg0or29HcePH0dQUBDCw8MX3I/8/HycOHFCVlFRIfvxj3/8b41G0zswMPCo3W7/wI1WDVcU5+pfDxmb7HHp1YFYFDiZHvvlZTV3Hh0dZd16662Rzz77bKdUKl1xcarFYiH9/f3c/Px8w0svvdS1Z88e1be+9a2QAwcOeNP1f1GYiBXDJQkhhO3n53e/SqVq+c53vvNMXV1d4IsvvrioqBobG0NpaSnKysqgUqmwZcsWhIWFrcp8MSgoCN3d3YsW77oTHo8Hu93uld59V1IBu7ciVnq93q3+VUthNBphtVpXZYwqFAoRFxeHLVu2gMvl4uTJk6ipqVk0ypmamor//Oc/0hMnTiR+6Utf+ptarT5PCNm8ln1g8D5ms5ns2LEjcufOnfp77rlnBABkMpm1vb2dCwDt7e1cqVS66EFMpVJZBQKB/ctf/vIIANx111368+fPr2uHYiZixXBJQQghPB7vZpVK9cvbbrtN9sQTT/gtdQLS6/VobGyE3W5HdHQ0ZDLZmuuDuFwu/Pz8MDw87LUToLPOSqFQeHRcZ8TqSsBbEStP+lfNR2dnJ0JC1tbznM1mIzw8HFqtFt3d3SguLoZEIkFUVNSCYjUqKgpvvvlmQF1dXcBDDz10QKPR1Pf19e2mlM7bnJdhaZYbWXI1drsdu3bt0sbExJj27NnT77x/+/btI/v27ZM988wzffv27ZNdd911I4tth8Vi4eqrrx59//33/W666abxQ4cOiaOjo9f1AYgRVgyXDISQfI1G89LGjRu1v/vd7wTBwcELPpdSisHBQTQ2NoLH4yE2NhYBAQEunY8zHegtYeWss/K0sBKJRBgeHvbomN7CW6sCdTodIiMjPT4u4Pjt9PT0IC8vzyXbY7FYCAkJQXBwMPr6+lBaWgqRSITo6GiIxeJ5XxMXF4fDhw9Li4uLcx588MEzgYGBH/f29n6TUtrmkkkxuJ0jR474HjhwQBYdHW2Mi4tLAIC9e/d27927t/eWW26J1Gq18sDAwKkDBw40O18TFBSUbDAY2BaLhRw+fDjg0KFDDRkZGaYXXnih64477gh/5JFH2DKZzPraa6+1eW3HlgEjrBjmQAhhAygB0E0pvYEQkgZHnz4BACuAr1NKz3hwPslqtfqPn/vc5+J+9atfSYeGhhYUSc6TQnNzM/z8/JCamrpoc9m1oFAoUF1dDZvN5vZWNvMhk8nQ0tLi8XFFItEVEbHyloeVzWaDzWZbsNm3uxkeHoafn5/L67sIIdBoNFCr1RgaGsL58+fBZrMRHR294MWJRqPBG2+8Iejq6rr+oYceOqtWq//T39//KKV00KWTWyaEkAAALwFIAkABfJVSWuSNuax3tm/fbqCUls73WFFRUcN893d3d88bmYyJiZkqKSmpd+X83AlTY8UwHw8BqJ31/+cA7KWUpgF4fPr/bocQEqbRaN7LzMz89N///nfuRx99JI2Pj0dcXNycRsR2ux3t7e04duwYhoeHsXHjRmzYsMFtomp6flCr1ejtdXvP2Xnh8/mwWq0Lrr5yFwKB4IoQVt5yXNfr9ZBIJB4f18ls7yp3QAiBQqFAbm4uYmJi0NTUhMLCQgwOXqiVbDYbWlpaEB0dje3bt5Oamhr5Cy+88GWtVlutUCieI4R4ozP2rwB8SCmNg6OlTu0Sz2e4AmGEFcMFEEKCAeyA46rMCQXgjNn7A+hx8xwUarX6LzExMWf/+te/7jhz5owsKytr5nGFQoGpqSmMjo7ORKiOHz+OiYkJ5ObmIikpyWN1MaGhoejo6PDIWPMhkUg8npa7EvyrAO8VrnuzvspqtWJ4eNhj40skEmRlZSElJQXt7e0oKirCyMgIAKCtrQ1BQUEzkTsWi4U77riD3dDQoHj88ce/rdFoGiUSySOEEI+E9gghYgBbALwMAJTSKUrpiCfGZri0YIQVw8W8COBRALOXxX4HwM8JIZ0AfgHgh+4YmBDClUqlPwkNDa1+/vnnv1xbW7ugU3p8fDwqKipw8uRJDA4OYtOmTUhISPB4+sTHxweUUq+tkpPL5V7xs+JyuV5xfvckRqPRa8LKW/5Vvb290Gg0HhfPfn5+yMzMRHx8PGpra3HmzBm0tbUhIiJiznN5PB6+9a1v8RsaGlQPPfTQXpVK1czn82/2wDQjAAwC+CshpIwQ8hIhxMcD4zJcYjDCimEGQsgNAAbmyYs/COBhSmkIgIcxfcXmSths9jaVStXwzW9+8wf19fWKO++8k7OQMeHIyAjq6upgNBoRERGB1NRUr3oqOYvYvYFMJoNOp/P4uEKh8LK3XJicnPT4ikCbzQaLxQI+f475tEdwdxpwKQICApCTkwMulwu73Y7q6uoFjXh9fX2xZ88eUVlZWfD111//V7VaXUgImavEXAcHQDqAP1BKNwCYAPADN47HcInCCCuG2eQBuIkQ0gbgHwCuIoS8AeAeAP+afs7bALLmf/nKIYQEqdXqD7dt2/ZOcXFx2JNPPumzkEgyGAwoKSlBbW0t4uPjkZOTg7a2Nq95STkJDAxET0+PV+YhEAhgsVg8Xmd1JXhZeSMVODw87LX6qomJCQDwmtO8k6mpKYyMjGDbtm1QKBQoLi5GbW3tghFSjUaDd999V/LWW2/lRkVFnVEqlT8nhLhDEXcB6KKUnp7+/ztwCC0GhgtghBXDDJTSH1JKgymlYQB2AfiEUnoXHDVVW6efdhWAxrWORQjhymSyn2q12vK//OUvn/vvf/8rDQsLm/e5JpMJFRUVKCsrg1arRU5ODgICAiAWiyEUCucUvXoaDoeDgIAAr0SOAEedirMuxVNcCV5W3vCw8mZ9VWdnp1ejVU6ampoQGRkJDoeDwMBAbNmyBSKRCCdPnkRTU9OCFxFbtmxBTU2N7NFHH/2mSqVqdHV6kFLaB6CTEBI7fdfVAGpcOQbD5QEjrBiWw/0AnieEVAB4BsDX1rIxZ9rvG9/4xmN1dXXy66+/ft7vocViQW1tLYqLi6FQKJCfnz/Hsyk2NhZ1dXVej1p5s4jdG30Dr4SIlbeElTfqqyilM/VV3sRkMmFgYACzPepYLBa0Wi22bNkCSimOHz+O9vb2eX/zXC4XjzzyiKCsrCxox44d7kgPfgvA3wghlQDS4DgeMsxDU1MTNzs7OyYiIiIxKioq8amnnlICQH9/Pzs3Nzdaq9Um5ebmRg8ODrIBoK+vj52dnR0jEok23H333TMKf3h4mBUXF5fgvEkkktSvfvWra3OvdTOMsGKYF0rpUUrpDdN/n6SUZlBKUyml2Qt5kywFISRIo9EsmfajlKKzsxMnT56EUCjEli1bEBgYOG9BrY+PDwICArxmeeBEKpVibGzMKwXd3qizuhIiVpTSRRsQuxq73Y6pqSmv1AsODQ1BIpGsqr2TK2loaEBMTMy877vT8yovLw8GgwEnTpyAXq+fdzsajQb/+te/XJ4epJSWU0ozKaUplNIvUEqvDKfcVcDlcvH88893tbS0VJ89e7b25ZdfVpaWlgqeeOIJTUFBwXh7e/v5goKC8ccff1wNACKRiD755JM9e/bs6Zq9HYlEYq+rq6tx3gIDA6d27ty5rt93RlgxuJ3Zab+XX3550bTf2NgYTp06heHhYeTl5SEsLGzJk1tMTAwaGhq8GrUihMzUWnkaoVCIqakp2O0r7m+6pjEvZ2FltVo9bvo6MjLi8u4Ay8XbReuAo8ZrZGRkyagZj8dDYmIiNmzYgLq6OpSXly/Yh3DLli2ora2VPfbYY99wR3qQYWG0Wq0lPz9/EnCIo8jISGNHRwfvww8/DNi9e7cOAHbv3q374IMPJAAgFovt27dvNwgEggUPZFVVVXydTsfdvn27wTN7sToYYcXgVgghG5RKZe03v/nNHyyV9quqqkJlZSWSkpKQkpKybOsEgUAAhULhtZV5Try5OtDf39+jdVZsNtujQs7TeKNwfWhoyCtpQIvFgvHxca+akgJAfX094uLilm314Ofnh5ycHCiVSpw6dQqtra3zXlxxOBx873vfE5aXlwddf/31r6jV6v8SQpSunj/DwtTX1/NqampEW7duNeh0Oo5Wq7UADvGl1+uXHSZ99dVXpTfddJPek5Hk1cC0tGFwC4QQnkKheCY5Ofne/fv3y+Lj4+d9HqUUXV1dMwWrSUlJq/LQiY6ORmFhIYKCgrzSXgZwRHHYbDYMBoNbHd/nQy6XQ6fTebRvIYvF8lo7H3fjrfqqtLQ0j44JAN3d3QgKCvKq8evY2BiMRuOK+146I8VKpRINDQ04efIkEhMT5/0dqNVqvPvuuwHvvfdewYMPPljp6+v7sMFgeNNV+7BeeXf4dMiAZcSlVwlKbsDkLZLsZV1Fjo6Osm699dbIZ599tlMqla7pauzdd9+VvvLKK61r2YYnWN+yj+GShBCSplQqqx966KEHz507t6Comp32y8/PR2ho6KoP7jweD4GBgWhvb1/L1NeMt4rYmQJ21+LpiJXdbofJZPK4mAMcqwFDQrxbC1xXV7eiaNXFcDgcJCQkIC0tDfX19YumB2+88UZ2VVWVavv27b9XqVRHCCGe7WJ+BWE2m8mOHTsid+7cqb/nnntGAEAmk1nb29u5ANDe3s6VSqXW5WyrqKhIaLPZyObNm9f9QYeJWDG4jOko1dNJSUlf3b9/vzQhIWHe51ksFtTV1WF0dBTJycnw9/d3yfiRkZE4ceIEQkNDvVaEq1ar0dDQgPj4eI9GAEQiEUwmE+x2u8cKrp11Vn5+3mjZ5l6MRqNH03Leqq8aHx8Hl8v1qsHu8PAw7Ha7S95vPz8/bNq0Cb29vTh16hTCwsIQFhY257cokUjwz3/+M+DgwYPbHnzwwfO+vr7fuVyjV8uNLLkau92OXbt2aWNiYkx79uzpd96/ffv2kX379smeeeaZvn379smuu+66keVs7/XXX5fecsst869WWGcwESsGl+CMUn3729/+ellZ2byiypn2O3nyJPz9/ZGXl+cyUQU4rlpDQ0PR0tLism2uFDabDZlMhoGBAY+P7e/vj9HRUY+Nx0SsXIe3bBbWQ9G60/DXVTjTg5s3b4bRaMSJEycW7Kd50003sauqqpTbt2//vVqtPsxEr1zHkSNHfA8cOCA7efKkn9MqYf/+/f579+7t/fTTT8VarTbp008/Fe/du3dmSXdQUFDyT3/605B33nlHplKpUkpLS2cU/8GDB6V33333JSGsmIgVw5oghHDlcvnTiYmJX33rrbdkC0WpnCafPB4P+fn54HK5bplPWFgYjh8/jrCwMI/3DXQSGhqKxsZGqFQqj47rrLPyVBGySCRacLn7pY6na6x0Oh1SUlI8Nh7giCgMDAy4VNSslMHBQfB4PJdeYDlxpgfHx8dRUVEBqVSK2NjYOTWBUqkU//znPwP+/e9/X/31r3+9SiQSPTQ5Obnf5RO6wti+fbthIWueoqKihvnu7+7urlpoe11dXQs+tt5gIlYMq4YQkqpWqxtuv/3275SXl88rqpxRqqKiIoSFhWHDhg1uE1WAI2IUERGBpqYmt42xFP7+/picnMTU1JRHx/V0ndXl3C/QZrN5LJ1MKfVKw+eBgQHI5XKPenXNhlI6sxLQnfj5+SEvLw88Hg8nT55ccPXszTffzC4vL1fl5eW9plarjxBCvGOBz3DJwwgrhhVDCGErFIqfJSQkfHzkyJGwO++8kzufQaXJZMLZs2cxODiI/Px8j0VwQkJCMDAwsGDzVndDCEFwcDC6urqWfrILEYlEMBqNHvPzulxTgXa73aP1caOjo26J2CyFt9OA/f398PX19cgKWkIIoqKikJ6ejvPnz6O2tnbe1jgDAwP44x//yPvjH/+4TaPRnBeJRDe5fXIMlx2MsGJYEYQQtVKpLLr33nu/XVFRIUtKSkJqaipqampmIjSzo1RardbtUaqLYbFYiI6ORkPDvNFmj+ANYUUIgVgs9lidFYfD8XjzZ0/g6TSgN/yrzGYzTCaTVwQd8Fm0KjY2duknuxBn9IrL5c6JXul0OoyMjCAiIgJf+MIX2JWVlaqsrKxXVCrVnwgh3qkrYLgkYYQVw7Lh8Xif02g05a+//nrGz3/+cz9nqkQgECA2NhYVFRUwGo1eiVJdTGBgIEZGRrwWUeHz+RAIBB4tJgc+q7PyFISQy84o1BuF655uvNzV1XVBPz5P093dDZlM5hV7ifmiV2azGVVVVdiwYcNMtFIul+PTTz+VfPe7371LoVBUuLjnIMNlDCOsGJaEEMJRKpUvpqen/+PcuXOqa6+9ds73RqPRwGQy4cSJE16JUl0MIWSmQbO38IanlafrrAQCgddSru5icnLSYyd8SqlXXN69KazsdjuampoQHR3tlfGdzI5effLJJ1Cr1XM+B0IIHnvsMeF//vOfuNDQ0GJfX99dXpouwyUEI6wuEQghbEJIGSHkP9P/308IKZ++tRFCyt00brBCoSh98MEH7yssLJSq1eo5zzGbzTh79iyEQiE4HA7EYrE7prJilEoljEYjxsbGvDb+0NCQRyM6Pj4+mJycZOqs1oAnC8nHxsYgFos9WtM1MjICkUjktVWzHR0dUKvV4PP5Xhl/NoQQ+Pr6wt/fH4ODg6itrZ3395qVlYWKigpFfn7+71Uq1RuEELcbfxFCYmcd48sJIWOEkO+4e1yGtcMIq0uHhwDUOv9DKb2NUppGKU0D8E8A/3L1gCKR6MagoKDSt99+O3nv3r0+87UuGRwcxKlTpxAaGorMzEwkJyejrKzMqw2RnRBCEBcX57WoFYvFglKpRF9fn8fGJITAz88P4+PjHhnvchRWnowgeaO+yptF6zabDa2trYiMjPTK+BdjNptRW1uLjIwM5Ofng81mo7CwcN7vdEBAAD744APJj3/84/9RKpVVhBC3FohRSutnHeMzAEwCeNedY7qSpqYmbnZ2dkxERERiVFRU4lNPPaUEgP7+fnZubm60VqtNys3NjR4cHGQDQF9fHzs7OztGJBJtuPvuuy/4gu7bt08aExOTEBMTk7B58+bo3t7edW0VxQirSwBCSDCAHQBemucxAuBLAFzmGkwI4alUqj9lZWW9Wl5erty6deucy2m73Y7a2lo0NjYiJycHzkiWQqGAWCxGa+v6aOckk8lgt9sXNAh0N95ozCyXyz2WDnS6r19OeLJ43dP1VTabDTqdbsU9+VxFa2srQkJCvFom4IRSioqKCsTHx4PP54MQgpiYGCQmJuLMmTPo6emZ8xpCCL797W8LDh8+HBUeHn7S39//qx6a7tUAmiml3u3ZtQK4XC6ef/75rpaWluqzZ8/Wvvzyy8rS0lLBE088oSkoKBhvb28/X1BQMP7444+rAUAkEtEnn3yyZ8+ePRes+rFYLPjhD38YcuzYsYaGhoaaxMRE489//vN13USbEVaXBi8CeBTAfDmlzQD6KaWNrhiIEBKuVCrLH3744bs++eQTyXwHfaPRiKKiIrBYLOTk5MxphxEfH4/Ozk6PRU2WwptRK7FYjKmpKY/WIXmyzupyjFhZLBaPnPgppZiYmICPj4/bx3LS398PpVLpFe8qi8WCzs5OhIeHe3zs+ejs7ASXy8XF5Q1SqRS5ubno6upCZWXlvCtf09LSUFFRIb/qqqueV6lU/yKEuPtD3AUXXjx7Aq1Wa8nPz58EAIlEYo+MjDR2dHTwPvzww4Ddu3frAGD37t26Dz74QAIAYrHYvn37doNAILjgPGe32wmlFOPj4yy73Y6xsTFWYGCgZ00CVwgjrNY5hJAbAAws5GAL4Ha46Afn6+t7c0hIyOmDBw/G/+AHPxDOd/Dt7+9HcXExYmNjERsbO29tCJvNRmpqKsrLy9fFirGAgABwuVyPNyl24mnrBV9fX0xMTHgkHXu5Rayc75knap7Gx8fh5+fn0foqb6YBm5ubER4ePsf53BtMTk6ipaUFSUlJ8z7O4/GwceNG+Pr6orCwEAaDYc5z/Pz88K9//Svg6aef3jGdGoxxx1ynrR5uAvC2O7bvCerr63k1NTWirVu3GnQ6HUer1VoAh/jS6/WLpvX4fD594YUXOtLT0xNVKlVKQ0OD8Dvf+Y53DubLZF3nKRkAAHkAbiKEXA9AAEBMCHmDUnoXIYQD4FY48u+rhhBC5HL53uTk5G++//77EqlUOuc5ztTf+Pg4cnNzlyw8DQgIgFKpRGNjo8e9auYjLi4O5eXlyMvL8+iJDHAIq8LCQkRGRnpkbGdB7vj4uNsXEvB4vBU5zFNKYbVaF7zZbLaZf53Pd95MJhNqax1lhoSQmfeSw+GAw+GAzWbP/H3xjc1mL+u9N5lMHmtI7On6KqPRCKvV6pWm2WazGX19fdiyZYvHx74YSinKy8uRnJy8aGSSEIKIiAhIpVKUlJQgKipqzkpKQgjuu+8+XlZWVviNN954UiAQ3GMymT5w8ZQ/D+AcpbR/yWfOw7unh0MGRiwuLRpUBnAnb8mWLKvGYXR0lHXrrbdGPvvss51SqXTFV9pms5n86U9/Upw+fbomPj7efO+994b+6Ec/0jz33HO9S7/aOzDCap1DKf0hgB8CACGkAMAjlNK7ph++BkAdpXTV4RBCiFCpVL7zhS98If93v/udeL42HpOTkzh37hxUKhWys7OXLQ6io6Nx6tQpKJVKj/WvWwinw3N/f/+c0L+74XK58PX1xcjIiMfeB5lMBp1O53ZhRQgBpRRms3nGdNL5r/NmNpthtVpnnn+x4LlYBAkEArBYrBnx5Py+dXd3QyqVzkSVnILLKcampqbmFWnOmxMulwuBQDDnxufzPVq4rtPpPHrR4U2LhcbGRkRFRXmtfc5sWlpa4O/vv2xRGxAQgLy8PFRUVGBwcBDJyclz2h2lpKSgpKRE8fnPf/4NuVz+vE6n+1/qupCxy7ISnsZsNpMdO3ZE7ty5U3/PPfeMAIBMJrO2t7dztVqtpb29nSuVSq2LbaO4uFgIAImJiWYAuP322/XPPvusZw/iK4QRVpc2a8q7E0KClUrlkSeffDJ89+7d84agenp60NDQgJSUFMwXyVoMFouFtLQ0lJSUYPPmzV5PAcTGxuLMmTNQqVQej1o5Pa08JazkcjkaGhpcVs/iFE8TExMwGAwzN6PRiMnJSZw5cwYikWhGoAiFQkgkkpn/u6JmicvlrtlwllIKi8VygfCbmJiAXq+HyWTC6OgorFYrhoeH4ePjMyPInX+7qvaKUgqDweCx6BGlFN3d3cjLy/PIeLMxGo3Q6XRITEz0+NgXMzY2hq6uLuTn56/odVwuFxkZGejo6EBhYSE2bNgw56JFoVDg1KlT0vvuu++xw4cPZxJCbqeUmtcyX0KICMDnAOxe7TaWG1lyNXa7Hbt27dLGxMSY9uzZMxNt2759+8i+fftkzzzzTN++fftk11133chi29FqtZampiZBT08PJzAw0Prhhx+KY2Ji1rV5HiOsLiEopUcBHJ31/3tXuy0Oh7MpMDDw3X/84x+qzZs3z7vq7/z58zCZTMjNzV21542vry+0Wi1qamqQnJy82um6BKFQCKlUiu7ubo9fuSsUClRXV8Nms3lEYDotFyilKxKRTsPK0dFRjI2NzQgpSin4fP6MwFAoFAgPD4dQKERlZSVCQkJWLLy9ASEEPB4PPB5v3mheQ0MDfHx8oFarMTExMbP/g4ODmJiYgNVqBYfDmRFbYrEYAQEBK/ZkMhgM8PHx8ZjAHx4ehp+fn1dW49XX1yMmJsbjFzMXY7fbUV5ejrS0tFX9Bgkh0Gq1kEgkKCsrQ3h4+Jx6NR6Ph1dffVX8m9/85vM/+9nPSgkh11BKV+23QimdBOBZPw4XceTIEd8DBw7IoqOjjXFxcQkAsHfv3u69e/f23nLLLZFarVYeGBg4deDAgWbna4KCgpINBgPbYrGQw4cPBxw6dKghIyPD9P3vf783Pz8/lsPh0ODg4Km///3v62PZ+QKQ9eA3xOBZAgIC7tdoNP97+PBh2XyFrGazGSUlJVCpVC6pC6KUori4GFFRUV5b5u3EbDajqKgIW7Zs8Xhaora2Fn5+fh4TdWfOnEFCQsKCTW6dq9JGR0cxMjKCkZERTE1NQSQSISAgAGKxGD4+PvDx8Vn0ROQUI0FBQe7aFQDA0aNHUVBQ4NYxKioqlhSJFotlJmI3NjY2530LCAiAv7//orVabW1tsNvtiIjwTJeU8vJyBAUFefz3ZzAYvFbbeDG1tbVgs9mIiVl7jbnVakV5eTn4fD4SExPnPZZ8/PHH9rvuuqu/r6/vxkUWH7mFioqKttTU1HVd4O1OKioq5KmpqWHeGp+JWF1BEELYCoXi97m5uV96++23A+Zb5j06OoqysjIkJCRAqXSNVQghBGlpaSguLkZ+fr5XPWz4fD5UKhU6OjoQFhbm0bFDQ0NRUVHhMWHltF1wCiuTyTTTaNYpBnx8fODv7w+5XI6oqKhVuWFfTpYLy6mx4nK5kEgkF6R1nZG+kZERDA0Nobm5GWazeUZsSSQSSKXSmdqcoaEhj7V0caY2U1NTPTLebOrq6hZcPexJ9Ho9dDqdy1KhHA4HGRkZaGxsxOnTp5GRkTEnqn/11VezCgsLNdddd91hf3//h0dHR193yeAM6x5GWF0hEEICFArFB7t3705+8sknfeY70DnrqTIzMxeMcqwWoVCImJgYVFZWIiNjTYsY10xUVBROnjyJkJAQj9Z9+fj4eLQ3nFgsRl1dHUZHRzE8PAwulwu5XA6FQrFqETUfIpHIo42f3YnZbF7V+0IImYnuOSN3s9OqAwMDqKurAyEEMpkMw8PDHiuS7+3thUaj8bi4GR0dxdTUlNej1FarFZWVldi4caNL3wOnoWhfXx9OnTqFjIyMOTVzERERKC0tld1yyy2/UiqVmYODgw9TSr3vQcPgVhhhdQVACIlRKpWHf//73wf/z//8z5zPnFKKhoYGDA8PzzQldQdBQUHo7e1FT08PAgMD3TLGcuByuQgODkZrayuioqI8OrbTid0dq8GcEamhoaEZITUxMYH4+HgkJSW5TUReLl5Wrvawmi22nN/3qakpdHd3AwBOnToFFosFmUwGuVx+QUTLlXR0dGDDhg0u3+5S1NbWIj4+3uPjXkxNTQ3CwsLcZsTqbN5cWlqKuLi4OauO/fz88NFHH0kee+yxr7z66quphJAbKaXrwz2ZwS0wwuoyhxCSHRQUdPDQoUPKlJSUOY9brVaUlZVBJBKtyEphtaSkpKCwsBBSqdRjfkHzER4ejhMnTkCr1Xo0NRkYGIgTJ064pJiXUgq9Xo++vj4MDQ2Bw+FALpcjKChoRkidPn0aQqHQrZE5gUDgUWd5dzE1NeX2xsQ8Hg8sFgsRERGIjIzE1NQUdDodBgYGZmqAVCoV1Gq1S1YMTkxMgBDiseiYE71eDxaL5XWblYGBAUxOTrp94YxYLEZubi5KSkowPj6OqKioC37fLBYLP//5z/3S0tJyH3744bOEkC2U0gG3TorBazDC6jJGJBLtiIyMfPWTTz6Zt0h9cnISJSUlCAsL85gbM4/HQ2JiIsrLyz0i5BaCw+EgLCwMzc3NiIuL8+i4AQEBq+4RZ7VaMTAwgL6+PoyOjiIgIABqtRqxsbHzRjucdVbubJvi/AxXugJxveGpHoFDQ0MzTYh5PB40Gg00Gg0AR9Sxv78fNTU1MBqNkMvlUKvVkEqlq1ps0dnZiZCQEJfOfykopaitrfX6KuCpqSlUV1cjJyfHI99LHo+HTZs24fz58zh37ty8qw/vvPNOrkqlir7rrrvOEkK2UUpb3D4xBo/jfbc2BrcgkUjui4yMfKu4uHheUaXT6XD69GkkJSV5vMWFUqmEUChEe7t3+4lqtVr09fXBbF6T1cyKcXpaLRej0YjW1lYUFRWhsLAQo6OjCAsLQ0FBATZs2ACNRrNgCkkul3uk/onL5cJisbh9HHfiido3SinGxsbg7+8/7+MCgQBarRbZ2dnYvHkz5HI5uru7cezYMZSWlqK7u3vZ7zOldKa+ypMMDg5CKBS63Zx2KSorKxEbG+vRyDiLxUJKSgpkMhlOnTo1b4r8mmuuYR08eDA0ODj4HCEkzWOTY/AYjLC6DJHL5T9NTU197qWXXhINDg7Oeby9vR01NTXYtGmT17yHEhMT0dbWhomJCa+MDzgOgpGRkWhqavLouFKpFGNjY4ueII1GI5qamnD8+HGUlZWBUorU1FRs3boV8fHxkEqly7oK9/f3x+joqCunPy+XQ52VJyJWk5OTEAqFy/rs2Gw21Go1UlNTUVBQgMjISIyPj6OoqAhFRUXo7Oy8wFH+YoaGhiCRSNxSt7UQlNKZlYDepLu7G4QQr9VyhoWFIT4+HsXFxdDr9Rc85uwIsH//fn+tVnuEx+Nd5ZVJupmmpiZudnZ2TERERGJUVFTiU089pQSA/v5+dm5ubrRWq03Kzc2NHhwcZANAX18fOzs7O0YkEm24++67L7ja//Of/yyJiYlJiIqKSnzggQe80z5gBTDC6jKCEMJSKpX7rrrqqu8dOXJEkpWVBYPBgLa2NgCfhegHBgaQm5vrkbTHQnA4HKSkpMyIBm8RHByMoaEhj4oC5wG/p6fngvstFgva29tx6tQpnDt3DhwOB5s2bUJubi4iIiJWFU0hhEAoFLrdDuFysFzwRMRqtSlgQggCAgIQFxeHLVu2ICUlBZOTkzh58iRKS0vR398/p+G5Nxou9/b2wt/f362p56UwGo0z3SK8iVwuR3Z2NqqqqtDX5/AIpZSirKwMarUaubm5OH36tDwqKuptsVi8y6uTdQNcLhfPP/98V0tLS/XZs2drX375ZWVpaangiSee0BQUFIy3t7efLygoGH/88cfVACASieiTTz7Zs2fPngtatPX19bEff/zx4KNHjzY0NTVVDwwMcP797397vuHlCmCE1WUCIYSrVCoP3HHHHbfv37/fn8vlghCC9PR0dHd3o7e3F+Xl5bBYLMjMzPR6exnAEbmRyWQejxjNxrlkuqGhwaPjOlcH2u129Pb24uzZsygsLITZbEZaWhry8vIQFhbmkmJqZ52VO2GE1fJwVeNlHx8fxMbGYuvWrYiIiMDAwACOHTuGyspK6PV6TE1NYXx83KPF487Vxd6MVjkbLCclJXnVL8+JSCRCTk4OmpqaZjIFQqFwxhhWpVKhuLhYmpCQ8HuZTPZdL0/XpWi1Wkt+fv4kAEgkEntkZKSxo6OD9+GHHwbs3r1bBwC7d+/WffDBBxIAEIvF9u3btxsEAsEFVwj19fX88PBwc2BgoBUArr766rG3337bu6siloARVpcBhBBfhUJx/JFHHrn6xRdf9JudZmCz2UhPT8e5c+fAYrGQnJy8rgqMY2Nj0dvb65F01UKo1WqMjY3BYDB4ZDxK6UyPvU8++QQ6nQ4xMTHYunUrYmJiXH5ydzZkdieXQyrQZDK5vR5ndHR0wfqq1UAIgUQiQXJyMrZu3QqVSoXW1lZ8+umn4HK5HhW7nZ2dUCgUXl3t29bWNtNyab3A4/GQk5ODlpYWDAwMzLGgEIvFOHbsmGTTpk0/VSqVz5P1dIB2EfX19byamhrR1q1bDTqdjqPVai2AQ3zp9fpFc9UJCQnm5uZmQX19Pc9iseDgwYOSnp4e9y7fXSPMqsBLHEKIXKFQHHvhhRei7rrrrjlftqmpKZSWliImJgZdXV2YmJhwufnnWnA2ai4rK0N+fr5XImmEEMTFxaG+vt6t5qUWiwWdnZ3o7OyEr68vQkJCYLfb3d6cNiAgAJWVlW4d43KIWFFK3drmyGg0QiAQuG0MFosFlUoFlUqF48ePQ6PRoLy8HCwWC1qtFmq12m1j22w2tLS0IDc31y3bXw4GgwHt7e3YvHmz1+awEP39/eDxeBCJRKiurkZSUtIFF7h8Ph/vvfdewNe+9rX73nvvvUBCyJcppQsX0K2AjneHQ0wDFpderQmU3MnQW5bX3Hl0dJR16623Rj777LOdUql0xeaoCoXC9stf/rJ9586dESwWCxs3bjS0tbW5xt3YTTARq0sYQohWqVSeff311+PmE1VGoxFFRUWIjIxEdHQ00tPTUVJS4vFVcEshFosRHByMuro6r81BoVDAbDa7JXI2PDyMsrIyFBYWwm63IycnBxkZGYiJicHAwIDba8xYLBZ4PJ5bI0qXesTKYrG4vcjbVWnApRgfHwePx0NERATy8vKQnJwMvV6PY8eOoba21i2fU3t7OzQajdt9wBbCbrejrKwMqamp66LMYTY6nQ6NjY3IyspCWloaOBwOSktLYbPZLngei8XCn//8Z/EDDzxwo0Kh+IgQ4r3Qn4swm81kx44dkTt37tTfc889IwAgk8ms7e3tXABob2/nSqXSJQXkHXfcMVpZWVlXXl5eFxsba4qMjFxfJ7GLYCJWlyiEkAiVSnX84MGDQVlZWXMeHx8fR0lJyczSX8CxQiwhIQFnzpxBTk6OR1cLLUVERASKioqg0+k8cvKZj7i4ONTV1SE7O3vN27LZbOjp6UFbWxsEAgHCw8ORlpaGi9O0MpkMAwMDUKlUax5zMeRyOYaGhtzmacRisby6CGGteGJF4NDQELRarVvHAOYWrfv6+iIpKWnmO1laWjojvGQy2ZpLA6xWq9cjRY2NjVAoFF43JL2Y8fFxVFZWYtOmTTM1X/Hx8WhpacHp06excePGC2rBCCHYu3evj0qlytmzZ8/Raa+rNSnh5UaWXI3dbseuXbu0MTExpj179vQ779++ffvIvn37ZM8880zfvn37ZNddd93IUtvq7u7mBAUFWQcHB9kvvfSS8q233mp26+TXyPo5szIsG0JItFqtPnro0KHA+VpV6PV6VFRUICMjY46XjFKphNlsRmlpKTZu3OjW1MdKcDZqPnPmjFvb6iyG03pCr9ev2obCZDKhtbUVfX19UKvVyMzMXPSEHRoaisbGRo8Iq46ODreaRbLZbFit1nUl2JeLJwrXnYau7sRut89bxwM4Pp+QkBCEhIRgZGQELS0tqK6uhlarRXBw8Ko/t5aWFoSGhnrtcx8ZGcHAwIDLGiy7CpPJhNLSUmRkZMw5BkRERIDP56OoqAjZ2dlz+lN+/etfF/B4vLQf/ehHxwkhWymll1ye/ciRI74HDhyQRUdHG+Pi4hIAYO/evd179+7tveWWWyK1Wq08MDBw6sCBAzMiKSgoKNlgMLAtFgs5fPhwwKFDhxoyMjJMDzzwQEhNTY0IAB577LGelJQUJmJ1JUAIYQMoAdBNKb1h+r5vAfgmACuA9ymlj7pgnFiNRvPpBx98oJmvW31/f/9M1GWhE0VISAiMRiMqKyuRmpq6borZRSIRIiIiUF1djbS0NK/MIT4+HlVVVcjNzV3R+zIxMYHGxkaMjo4iIiICW7ZsWVZKwt/fH5OTk25vp+KJOitnOtAVrVg8jamxESI3Fl0bjcaZdjbuZGBgAHK5fMlxAgICkJ6eDrPZjPb2dpw4cQJBQUEIDw9f0UWNs/fhli1b1jr1VWGz2VBRUYH09PR1c5EIOFLLZ86cQVJS0oJGqUFBQeDxeCgqKsLGjRvnWFTcd999fA6Hk/zoo4+emBZXLl9d09PTo9TpdAoAEAgEkxEREW1sNtsloeft27cbKKWl8z1WVFQ07zLs7u7uqvnuf++991pdMSdPsX6+iZc+DwGodf6HELINwM0AUiiliQB+sdYBCCHxGo3m6EcffTSvqOrs7ERjYyNycnKWvPqOjo4GIcTjNgNLERISgqmpqRnfF08jFoshEAgwn7HqfIyOjqKkpARlZWXQaDTYsmULQkJCll3nQQhBcHAwurq6ln7yGnDWWbmzp9+lWsBuGxsD5+OPwfngA5jd1A3AUynulXpX8fl8xMTEYMuWLeByuTh58iSqq6uX/T1pampCRESE1+qaamtrERISsq7EvN1uR0lJCSIjI5f0LFMoFDOR+vnqO++9917+L3/5yySFQnGCEOLSnTSbzdzBwUFVQkJCTXJycjUAMjQ05B3H6MsMRli5AEJIMIAdAF6adfeDAJ6llJoBYK0NNwkhCYGBgZ9+/PHH6qSkpDmPt7W1obOzE5s2bVpW5IMQgpSUFIyMjKyovYq7IYQgNTUVtbW1Xiuyd64QXKxmSKfTobi4GLW1tQgPD0d+fj5UKtWqon+eEFaA+20XLtUC9vETJwBKQXx8oPvb32Bxg6hfrTHoSjCbzTCZTKuyc2Cz2QgPD8fWrVshFotx+vRpVFRULNoZwWQyYWBgwOO9CJ0MDQ1hbGwM4eHhXhl/Ppw+WgqFAkFBQct6TUBAADZu3Ihz585heHh4zuN33nkn79e//nWiQqEoJIS4tE8QpZTY7XaW3W6H3W5n8Xi8S7sv1TqBEVau4UUAjwKYvZQ0BsBmQshpQsgxQsjG1W6cEBIXGBj4yccff6yar3bCWdOTnZ29ojoHQggyMjLQ0dGBgYH102idz+cjPj4eFRUVXimI9vHxgVgsRm9v7wX3U0rR39+PwsJCtLa2Ij4+Hps2bVpzJILP54PP52NsbGxN21kKdxuFXooRK9vYGCZKSzGu0UB+771g8XgYeu01WF0sQIeHh91eX9XV1bXsk/lCsFgshISEYMuWLVAqlTh37hxKS0vn/W42NDQgOjraKyk4i8WC8+fPY8OGDeumlAEA6urqwOVyZ5psLxdfX19kZWWhoqJiXnG1a9cu7m9/+9s4hUJxnBDiEr8cPp9vUSqVfVVVVSkVFRWpbDbbJpFI3HsQukJghNUaIYTcAGBgnlwyB4AEwCYA3wfw1mqM3wghMRqN5tMjR46o4uLi5jzuNJ3buHHjqsLxHA4HGzduRE1NDUZGRlb8enehVqvB4/HQ2emVBS2IiYlBY2MjKKUzgurEiRPo7e1FamoqMjMzXWr0uNLGzKtBIpHMe9B2FSKR6JKLWI2fOAHY7dBpteDJZJDdcw9gt2Po1Vdhc5HQNZlM4HK5bk+XdXd3IzjYNW3UCCHQaDTIz8+HVqtFdXU1zpw5MyOwJicnMTIy4rVefFVVVYiKivJqW66LaWtrg8FgmONRtVx8fHxmxNXF/QUB4Etf+hL3xRdfTJgWV2vuGWSxWNijo6MBSUlJVampqZU2m401MDDApAJdACOs1k4egJsIIW0A/gHgKkLIGwC6APyLOjgDRzRrRbkAQkiUWq0+evjwYXVCQsKcx5ubmzE4OLhqUeWEz+dj48aNKCsrW1cRh8TERLS0tHhlTkKhEHK5HHV1dTh16hS6u7uRmZmJtLQ0txisqlQqDA4Ozun35krYbDa4XK7bUqye6EnoSpzRKmFKCuzThcNchQKyu++G3Wh0iCsXNAn3RH3VyMgIBALBnNVla4UQArlcjpycHERGRqKqqgplZWU4f/48YmNjvRIt6u3thc1mW3N0zpX09fWhu7sb6enpa3pPRCIRsrOzUVlZOW/a/o477uD+/Oc/T1AoFMcIIWtaxjo6Oirm8XhmHo9nZbFYVCKRjBgMhvXjHn0JwwirNUIp/SGlNJhSGgZgF4BPKKV3ATgA4CrAEXUCwAOw7DzMtE/VsQ8//FCTnJw85/GmpibodDqXWSb4+PjMFFFOTU2teXuugMvlIjk52SuNmsfHxzE+Po6WlhYkJiYiPT3drcvxWSwWFAqF24v23VlnxeFw5pgermfGT54E7HZwsrIuiHzwAgMhu+MOWIeHoXvjDdjXKEQ9UV/liYbLMpkMubm5CAgIwODgIAYHBz1+rDCZTKirq1tXq5mHh4dRX1+/5gtcJ0KhcKZ583y/1XvuuYf/7LPPJikUik8JIasO2fF4vKnJyUlfm83GopRibGzMTygUum91yxUEI6zcx18ARBBCzsMRybqHLlMdEEKCVCrVsUOHDgXOt/qvubkZer0emZmZLq1vkEgkiI+Px5kzZ9bNCVImkyEgIAAtLS0eGc9oNKKsrAwVFRWIjo5GVFTUvGF5dxAaGur21Ke766wIIW6NurkK2/g4JkpKIEpNhWm61chs+OHhkH7pS7D09kL/97+DWlZf06vX691qXGmz2aDT6aBUKt02hhNCCAYHB5GdnQ1/f38UFhaioaEBVqtLuq8sCqUUFRUVSEhI8JrD+8UYDAaUl5dj48aNLp3TbHE13/Hnq1/9Kv9nP/tZqkKhOEIIWZXpn1gsnvD39x+urq6OP3/+fCIAolKplrccmmFRGGHlQiilR50eVpTSKUrpXZTSJEppOqX0k+VsgxAiUSgUx955552g9PT0OY+3tLRgaGjI5aLKiUqlQkhICEpLS9eNk3ZcXBy6urrcWtw9NTU1U0ei0WiQl5cHmUyGiIgItLe3e+TEIRaLMTU15VZLBHfXWV0qKwOdtVV+W7cu6LoujIuD5JZbYG5thf6dd0BXcbFhNpvB4XDcWl/V398PpVLpkSLy4eFh2O12yOXymSJ3NpuNEydOoLW11a2iuqOjAwKBwO1musvFbDajpKTEbdFsp7iqrKycV1x97Wtf43/ve9/boFAo3iGErOrDDw0N7UlJSalOTk6ujoqKamWxWOvjoH+JwwirdQQhRKhQKD596aWXtPn5+XPi3G1tbRgYGHCbqHKi1WohFotRVVW1LsQVm81GWloaysvLXX7gttvtaG5uRmFhIfz8/LBlyxao1eqZNAOXy0VoaChaWz3jT+du6wXnSd5dKZxLYWXg7GgVRyrF2PjkgkXQotRU+F9/PUy1tRg5eBB0hd8/T9RXeSIN6KSurg6zF9Gw2WxERkYiPz8fZrMZx48fR39//yJbWB0TExNobW11e8Py5WK1WnHmzBkkJCS4dBHLxQiFQmRlZaGysnLeC6LHHntMtGvXrm0KheK3bpvEKqmvr+eFh4cn3nbbbdro6OjEm266KfzAgQN+6enpcVqtNunTTz8VjY2NsXbu3BmWlJQUHx8fn/DGG28EOF+bkZERm5CQEJ+QkBB/5MgRHwD4z3/+45eVlRV73XXXRYSHhyfedNNN4esxQs4Iq3UCIYSjUCg+ePrpp2NvuummOZ4J7e3t6O3tdVkefyliY2Nhs9nQ1NTk9rGWg7+/PzQaDerr6122zaGhIZw4cQIWiwVbtmxBaGjovHUbYWFh6OrqgmUN6aDl4hRW7hS07qyzuhQiVs7aKr8tWzAwasG71b74TyWBwTR/RMp30yb4bduGybIyjB4+vKLPxt31VUajEVar1SMGmUNDQ+ByufPaRnC5XMTFxSE7OxudnZ04ffq0ywS20xsqJSVlXbRLstvtKC0tRVhYmEfSryKRCFlZWSgvL5935faLL77ot2XLljvkcvlP3D6ZFdLZ2Sn43ve+N1BXV1fd3Nws+Nvf/iYrKSmpe/rpp7uefvppzY9+9CPNtm3bxs6fP1974sSJ+p/85CfBY2NjrMDAQOuJEycaampqavfv39/y8MMPz1w51NbWCn/3u991NjU1VXd0dPCPHDmy7gruvf8tZQAhhCgUir994xvfyLz//vvn9NXo7u5Gd3c3srOzPeZw7DTqPHPmDIRCocuWca+FqKgoFBYWrqmXH+AogK2urobFYkFmZuacVhIXw2azERERgaampnl7sLkSLpcLX19fjIyMuK0uRyaTob+/HxqNxuXbFolE8zpIrxds4+OYOHsWopQUWPwk+PvhARBQ9I7Y8McPB3Bbvgwh8rm1Mn4FBbAbjZgoKgJLKIS4oGBZ4+n1erd+Z7q6ujzy26SUoq6ubslWU0KhEJmZmRgcHJxJq0dFRa3puNXc3AyJRLKm37yroJSisrISEonEo8aoTnF15swZZGZmXiCkWSwW3nzzTf9rrrnmuwEBAd0jIyN/vfj1WVlZsRffd+utt+p/8IMfDI6Pj7Ouvvrq6Isfv+uuu4a+/e1v63p7ezk333zzBcZcZ86cWdYVblBQkDkrK8sIADExMcarrrpqjMViIT09ffJnP/tZYF9fH+/w4cMBv/71r9UAYDabSVNTE0+r1Vr+3//7f9qamhohi8VCe3v7zHLX5OTkicjISAsAJCYmTjY3N6+PgrtZMBGrdYBCoXjhlltuue7xxx+fc4YfHBxEc3OzxyJVs2GxWMjMzERLS8uyW7y4E0IINmzYgMrKylXVPDnTfsXFxQgKCsKmTZuWFFVOQkJC0N/f79b6Jyfu9rSSSqVuK8hf7xErZ7TKZ8sWvH1Kj9FJG5IlPbj/WgXYLIK/fDyIs40Tc6JShBD4X3cdhGlpGP/kExhOn15yrKmpKbBYLLdFWSil6O7u9ojtQH9/P3x8fJZtNaJQKC6ov1ptenBsbAw9PT2Yz8PPGzQ0NIAQgujoOTrE7fj4+CAjIwOlpaVzfmNcLheHDh2SaLXaX4hEous9PrkF4PF4Mz8kFosFgUBAAcfFqs1mI5RSvPPOO011dXU1dXV1Nb29vVXp6emmp59+WqVUKi21tbU1VVVVNRaLZUar8Pn8mW1ON35fH8tDZ8FErLyMTCZ7JDc3994//OEP4ovTUCMjI6iursamTZtW1BjVlXA4HGRlZaG4uBjp6ekLNhT1FD4+PggLC0NNTQ1SUlKW/bqhoSFUV1dDpVJh8+bNKxapLBYL0dHRaGxsxHz2F65EoVCguroaNpvNLWKaw+GAxWLBYrG4/Hu1nmusbOPjmCwpgTAlBUe7uGjqNeDGTH9MdDdCI+Fh93Yl3inS472SEXTppnBDZgC4nM9+k4TFguTmm0FNJoy+/z5YAgFE86zadeLu+qrh4WH4+fm5/dhAKUV9fT2ysrJW9DoWi4WoqCgEBQWhuroabW1tSE5OXnaht91uR3l5OdLS0tZFg+WOjg6MjIwgKyvLa1YPYrEYycnJOHPmDHJzcy/47H18fPDxxx9Ls7OzX5uamrqgbmGxCJOfn599scc1Go11uRGqlbJt27ax559/XvXKK690sFgsFBYWCvPy8oyjo6Ps4ODgKTabjd/+9rey9bJKfbl4/9t6BRMQEHBnZGTk4++8807AxQeOiYkJlJWVYePGjRAI5mQHPYpAIEBmZua8V0reQKvVYnJycllteMxmM0pLS9Hc3IzMzEzExcWtWqwEBgZieHjY7cKBEAK1Wj2npY4rkUqlbqmz4nK5HqlFWw2GwkJQqxUdMfk4WWtAZpQIScHsmcJ1EZ+Fu7bIUJDkh7LWSbz030EMGy6MjBI2G9KdO8ELD8fwu+/CuEjNn7vrqzxVtN7d3Q2pVLpql3NnejAyMhJnz55FfX39shah1NXVITAw0OsXcwAwMDCAjo4OZGRkeN0/SyaTISYmZl5bHLlcjo8//lg2NjamnJycdK1brBt49tlne6xWK4mLi0uIjo5O/MlPfhIEAN/5zncG3nzzTVlqampcQ0ODQCgUrr8K9UUg62HV15UIj8e7Jioq6q1f/vKXkri4OGi12pnHTCYTiouLkZaW5vb+YitBr9ejqqpqzpWSNzCZTCgqKkJeXt6C/jHd3d1oaGhAXFycy+qJ+vv70dPTgw0bNrhkewsxMTGBiooK5ObmumX7/f39GBoacssqq6NHj2Lr1q0uPwEdPXoUBcusbboYm8GA/l/+EmNxmXibpkIj5eLebXKMjujR3d09J/pZ323EP4uGQQiwM1eKKM2FFzd2sxlDf/0rLAMDkN99N/hhYXPGPH78OHJyctzyW7FarThx4gQKCgrceqK32+0z++EKV3e73Y6mpib09fUhNTV1wRV1er0etbW1yM3N9bqQGRkZQXl5ucveA1fR3t6Ovr6+C0yi7XY7KisrYbPZIBAILFFRUbV8Pn99Xum4kYqKCnlqamqYt8ZnIlZegBCyISgo6M1PP/1Ucs0116C/vx91dXWglMJiseDMmTNITExcV6IKcEQ5FrpS8jQCgQCxsbGorKyc85jZbMbZs2fR19eHvLw8lxZpK5VKTExMYHx83GXbnA8fHx9QSt0WHXNXxApwfDaeqEVbCYaTJzFJOXifkwIhj2BXnhQcNsHk5OS8qanYICF2b1dCLGTj9aM6HKseh33WRSiLz4fsy18GJyAAur/9DVM9PRe83hm1c9cFSG9vLzQajdtFR0dHB1QqlcsEBYvFQkxMDNLS0lBZWYm6uro50Sur1YrKysp10WB5cnJyJnOwnkQV4IjcBwQEoLKyEpTSGQsIHx8fiEQihIaGcpubm2OtVqtni3MZGGHlaQghIRqN5tB///tfuUqlApvNxsaNGzE1NYXy8nKcOXMGkZGRUCgU3p7qvGg0GgQGBnqlzczFBAYGghByge9TT08PTp06heDgYGRkZLjcoZkQgvj4eNTV1bl0u/MREhLiNid25wnfHWm79VbAbjMYMHa2BJ/E3IyJKeD2zTL4Ch3nGqPRuGDNj8yPg/uvVSBZK8THlWP4xwk9TFOfiQC2jw/k99wDlkAA3WuvwTJrgYder3drfVVHR4fbV6XZbDa0trYiKirK5dsWi8XIy8sDi8XCyZMnL1hJWl1djfDwcLe2kFoOU1NTOHPmDNLS0pa9yMXTxMTEgMViobq6GkVFRQgKCpoprPfz84NGo+E1NTXF2O32dVfgfTnDCCsPQggRKRSKI2+//bYqMjJy9v1ISkrCyMgIzGbzunEWXgjnQa+mpsbbU0FKSgoaGxsxOjqKs2fPore31+VRqouRyWSwWq3zesq4ksDAQPT09LhNwMpkMresDlxvBeyGwkIUSTeii/rjpiwJgmSfie3JyYXNQQGAx2Hhf3IkuD7dHw09Juz7aAD9I5+JUba/P2T33AMQAt1rr8E6/Z0YGhpyW33VxHRjaHef7FtbWxEcHOy2qNvF0av6+nr09vbCZDJ5zPB0IWw2G86cOYP4+Hi3tiNaK4QQhIeHo6OjA/7+/nPEtkQiIQEBAYL29vYw78zwyoQRVh6CEEKUSuW/nn766bC8vLwLrh4opTh//jzUajWio6NRVFS07lIpFxMfHw+TyYTm5mavzoPL5UKj0eDkyZMICgpyS5RqPuLj41FbW+vWMTgcDgICAtyWsnNX38D1JKxsBgNKa4dxXpqEnFgfpIVfGAVZKBU4G0IINsX64itXy2G2UPzpo0FUtX+2f1y5HLK774bdZILu1VdhMxjW7LW2GJ2dnW4XHhaLBZ2dnQgPD3frOMBn0SubzYbS0lJERkZ6NQVIKUVpaSlCQkLW/UWuXq9HSUkJcnJyYDAY0HNRShoAVCoVi1Lq39fX5343UwYAjLDyGAqF4qlbb7015/7775+TqG9sbITdbkdcXBxCQkIQFxeH4uJiGAwGb0x1WTg9pZzF3N7AYrGgtLQUExMTCAoKgtls9tjYAQEB4HA4bm1oDLjX08pdEav1lApsPHYOxxW5CJcSXJs2t1B6ampq2UJcq+DjweuU0Ei4ePvUMD44NwKb3RFN5Gk0kN11F2xjYxh67TUQN1hZAI6TvrO+yp20tLQgLCzMY07nhBBMTEwgPj4eNTU1aGho8EqpAaUUVVVVEIvFFywoWo/09vaiqqoK2dnZkEgk2LhxI5qamuZ4DhJCEBYWxh4eHg4cHR11v0U/AyOsPIGPj8+t0dHRX//Nb34zZ91wT08P9Ho9UlJSZq7SFAoFNmzYgLNnz7rNyNEVsFismR+zu6IqCzE8PIzCwkKoVCpkZGQgOTkZ7e3tHhWjcXFxM4sO3IVUKsXY2JhbaqG4XC7sdrvLG0yvl4jViG4cB/Rq+LIsuK1ABTbrwiiI83NbSXTET8jGV66WY1OMD4rqJ/DKJ0MwGB0LOfhaLaS33QbrwACCz5+H3Q1Cf2hoCBKJxK2Cx2w2o7e316PCoqurCxwOZ6bvoNVqRXFxsccj901NTbDZbIiNnWNUvq5obW1FS0sLcnJyZiKuXC4XWVlZqK6unrMggMViITIykt3V1RVhNBrXnVP55QYjrNwMISRJpVLt+89//iO5+GA4OjqKhoYGZGRkzDHA8/f3R3Z2NqqqqtzqZ7RWuFwuNm7ciKqqKrevlAMcJ8Pm5mZUVVUhMzNzpp0Hm81GamoqysrKXN6oeSH8/Pzg4+OzLD+t1UIImam1cgfucGHn8/kejR7Oh9VG8eYnfZhi8bAr2xci/tyFUSuJVs2GzSK4PiMA/5MjQY/egj8cHkDHoGN/BTExmNy0CVydDro33nC5uPKEd1VTUxMiIyM9ZsppNBrR3NyMpKQkAA4RkJCQgMjISBQVFXms60NXVxd0Oh1SU1O9vhpxISilqKmpwdDQEDZt2jTn+ysQCJCWloapqak5x0Eej4ewsDBOa2trjNVqdfuH29TUxM3Ozo6JiIhIjIqKSnzqqaeUANDf38/Ozc2N1mq1Sbm5udGDg4NsAHj33XfFiYmJ8TExMQmJiYnxBw8enImunThxQhQTE5MQGhqadO+994asx8bLs2GElRshhMhVKtUHhw4dkl9cAGk2m1FWVobMzMwFUwYikQg5OTloaWlBa2urJ6a8KoRCIdLT091uIOpcpTM5OYm8vLw57TUkEgmUSiUaGxvdNoeLiY2NRX19vVujVu5cHSiXy10ebXSelLy1apRSiveKh9BrFWE7pwXBEfPXySynvmoxUsNEuP9zCnDZBH/9ZAinGwyglKLPxwd+t9yCqc5O6F5/3WXiymKxYHx83K3F1EajEUNDQx7rDUopRVlZGZKSkuYcB5VKJTZt2oSGhga3R4YHBwfR0tKCzMzMdeHyPh92u33mwjEzM3NBo2NnmcLk5OSc98zHxwcqlYrX0tIS5e7fJ5fLxfPPP9/V0tJSffbs2dqXX35ZWVpaKnjiiSc0BQUF4+3t7ecLCgrGH3/8cTUAKJVKy/vvv9/U0NBQ88orr7Ted999MwV+X//617W///3v29va2s63tLQI3nnnHe+7xi7C+vwGXQYQQrgKheLwX/7yF83Ffa7sdjtKSkqQkJCwZO8tHo+HTZs2QafToaamxusWBwshFouRlJSEs2fPuiVtpdfrUVhYiNDQUCQnJy94UImOjsbAwIDbV+w5EYlEkEgkbq0zEwqFYLPZbklzymSyy86B/WzTBMo6prBhqAzpVy3cfsjU2wvRGq981RIudm9XIlLNx/ulo/hnkR4WK4U4LQ3SL34RU11dLhNXzr6A7oymNDQ0ICYmxmMRm9bWVojF4gVXUAqFwhmT0FOnTrnlwm1sbAzV1dXIysryWE3ZSrFYLDh9+jT8/f2RlJS05OfD4XDAZrPnTaXKZDIiEol8urq63KqetVqtJT8/fxIAJBKJPTIy0tjR0cH78MMPA3bv3q0DgN27d+s++OADCQDk5eUZw8LCLACQkZFhmpqaYhmNRtLe3s41GAysa665ZoLFYuHOO+/UHThwYP0u1QQjrNyGUqn8y8MPPxx3/fXXX6AAnN3R1Wo1lMrlLdJgs9nIyMiA3W7HuXPnPJbqWilyuRyRkZEoKSlx2RwppWhsbERNTQ2ys7OXLNplsVhIS0tDRUWFx0xMnT0E3fm5uKuIncfjwWazufy98ladVduAGYdKRxE60YktKiO4C/nBtbRAUVCAiC98AVhjNFDIY+GOLTJsS/ZDZbsJpfow1HYZIUhMdKm46urqcmskyWAwYGxsDGq12m1jzGZ8fBydnZ2Ij49f9HmEEMTGxiI2NhbFxcWrbug8H0ajEaWlpcjMzPR667CFMBqNKCoqQmhoKGbb9CyFQCCA3W7H1NTUnMeCgoJYJpNJPjQ05J6lqxdRX1/Pq6mpEW3dutWg0+k4Wq3WAjjEl16vn6NmX331VUlCQsKkUCik7e3tXI1GM3OVptVqp3p7e73b+mMJ1qc8v8SRSqUPXXXVVTf+4Ac/mJNnaG1tBaUUERERK9qm0+uqubkZp0+fXjSF6E2CgoJgMplQXl6+Zudks9mMc+fOwd/fH7m5ucsO0fv5+SEkJAS1tbUzdRvuRCAQQKVSobOz020Fv2q1Gg0NDYiPj3d5NEEikUCv17vUlNYprDzZPWBkwor9J/XwZ5lxVfd/Ib7pa/M/cWAA2L4dMJvBMpmAbduAo0eBNYgWFiHYliQGnehDea8P3jyhR6iCh2tTo6HYuRP6t9+G7rXXIPvyl8FaxQl8fHwcHA5n1f36lkN9fT3i4uI8Eq1yNlhOTU1ddu9OuVyO3NxcnDt3DkNDQ4iPj19T2s7Z5SI1NXXJzIG3GB8fR2lpKZKSklbsi0YIgUgkguUb3wCtrr7gcyUAoihlT05OhtkAFZuQlV0VJiVN4i9/WdYVyejoKOvWW2+NfPbZZzulUumS45SUlAgef/zxoA8//LARmL+kYL3WwDlhIlYuhsPhbA4ODn78jTfe8L/4wx8cHERPT88FKwBXSmRkJEJDQ1FUVLRulrRfTGRkJHg83pp8nsbGxlBUVISIiAgkJCSs+AAaHh6O8fFxjxW+RkVFoaWlxW1RMjabDalU6pb9cUedlactF6asdrx5Qg+rzY7trf9BQEIsuPNFhMfHgR07QLu78cPkZBz94Q8dQuuqq4Du7jXPg2cZwIPbZbhxYwD041a89N8hHNCrQW+8DVPd3Y7I1SpWurm7aH10dBRms9ljHR8aGhqgUqlWLLz5fD42bdoEDoeD06dPzxuNWQ5OA9CYmBi3+Y2tFZ1Oh5KSEqSnp6/abJYQAg6XC5vdjovlCSEEQqGQmCgV2h1ay+WYzWayY8eOyJ07d+rvueeeEQCQyWTW9vZ2LgC0t7dzpVLpzLLk5uZm7he/+MWol19+uTUxMdEMAGFhYZbZEar29naeWq1e1/0Pr7iIFSGEDaAEQDel9AZCyB4A9wNwnrF+RCk9tMpty9Vq9f5Dhw5JLw4rT0xM4Pz588jJyVn2FdpCBAUFQSAQ4PTp08jIyICf3/qzJklMTERJSQlaW1tXbDLY29uL+vr6Ne0bIQRpaWkoLi5Gfn6+26N7XC4XwcHBaGtrW1G4fiWEhoaiubl52Snk5SKTyVy+OEIkEnlsNSulFAfPjKBv2IKbxZ3wn9TBb+uuuU+cmgL+539Ay8rwdY0GfywsxK/PnkXnW29BedddDnF19CiwSo8oZ0pVKBRgYxSQGibEqToDCmsNqLOJkZpzN5LOvAO8/vqKIld2ux0DAwO4uFbTldTV1bl1+7MZHh7G0NDQqhuMO1ODvb29OHXq1IqPE86C+cDAQLf7ga2Wnp4eNDU1YdOmTWuOUrJ+9SvYLBYYTCb4+vpecFHPAmAZGSFd/f2IiYmpd0UkqKenR6nT6RSUUvzkJz+xxcTETOzZs2cmf7t9+/aRffv2yZ555pm+ffv2ya677roRABgaGmJff/310Xv27Om69tprJ5zP12q1Fh8fH/vHH3/ss23btom//e1vsm984xvuW4rtAq7EiNVDAC4OpfySUpo2fVutqGIplcoDf/7zn5UX10FYLBaUlJRgw4YNLsvjy2SymZV4nvaQWg6EEKSnp6Onp2fZJ1hKKerr69HW1obc3Nw1C0ahUIjo6GhUVVWtaTvLxdlawl1F2wEBAZiYmFj1VfpC8Pl8WCwWl0bbPFljdarOgMp2IwriBFCX/RfCxMS50Sq7HfjKV4AjR/CYRIK/jY7iF7/4BY4cOQLlzTcDH34IW2enIy3Y17eqeQwPD1+wYo/HYaEgSYzv3KhCdrQPqkb4+Ef0HThp1qDn9TeXHbkaGBiAXC5f8wXZQjjtNjwRubFaraioqEBaWtqaV99pNJqZY+BK6q5qamogEok84iq/Gpqbm9HW1oacnByXpX65XC54PN68KwUDAgIgEomEPT09a1aZExMTAp1Op0hISKjt7u5uf++993xOnjwpjouLS4iLi0vYv3+//969e3s//fRTsVarTfr000/Fe/fu7QWA5557TtnR0cF/9tlnA53P7+7u5gDA73//+/YHHnggTKvVJoWFhZl37tw5uvhMvMsVFbEihAQD2AHgaQDfdeW25XL5j3bu3Jl8ww03zClWP3fuHKKiolxebyIWi5GdnY2zZ88iKioKgYGBLt3+WnE2mC4qKgKfz1/0wG21WlFWVgahUIjs7GyXLXkOCgpCb28venp63P7+cDgchIWFoaWlxS0Gg4QQBAcHo6ura8U1ekshkUgwPDzssv52AoHAI+aOTb0mfFQxhsQQAdKHymCwWOBXUHDhkygFHnkE+PvfcbigAC9XVuKZd/8AfQwbAz4cNJh60GwYxzNGI440N4OzZQs4J04AK2xnMjQ0NG/jZR8BG9dnBGBTrC8+rhxDGd2AWqsJmW8eR8GXNoPns/jJs6Ojw22GlZRS1NbWIjl54dWTrqS2thZardZlNU1isRg5OTkoKSnB+Pj4ku1wmpubYTKZkJ6e7pLxXYnTo8pkMmHTpk0ut33g8/mw2Wwwm81zLvCDgoJY9fX1Kj8/vzGxWDyxwCaWxGg0CkUikYHNZts///nPGzo6OnpYLJY9KCjoAuVbVFTUcPFrn3vuud7nnntu3qvwLVu2TDY2Nlavdl6e5kqLWL0I4FEAFxfQfZMQUkkI+QshZMXLOAkh2Wq1+uEXXnhhjrdGY2Mj/Pz8EBQUtLoZL4FQKEROTg7a2tq83rdvPng8HjZu3IiKiooF7QKMRiNOnToFpVKJpKQklx5QCCFITU1FfX29R070Wq0Wvb29Lo8qOXEKK1fj6jorFovldmsQ/bgVb5/SQynm4KYUASbOnJ4/WvWLXwC//CXw7W/jmiNH8MKnr2IgjgV/qwCNpl68oTuG0rhRhP7ga/g8pZhqbMTYxo2O2qsVoNPp5hVWTqS+HOzMleKB7QqoA9g4KUjErw50obxxFPYF3iuz2QyTyQR//7nteFzB4OAgBAIBxGL32wINDAxgYmICYWFhLt0un89HTk4OJiYmcO7cuQUjrz09Pejv71/zohp34OyT6Iz0u8tLSygUwmq1zum2wGKxEBERwe7s7Iy0WCyrDo0KhULjxMSEn8ViYdtsNtbY2Jj/1NTUFef0fsUIK0LIDQAGKKWlFz30BwCRANIA9AJ4foXblahUqn8ePHhQerELrk6nc3ttBOAI827atAkjIyM4f/78uvO6EolESE9PR0lJyRxxo9frUVxcjKSkJLetqOPxeEhISEBFRYXb35vpA5TbTEr5fD74fD7GxsZcul13+Fmx2WyXt8txYrbY8fcTjvnevkUGy9liULMZflu3XvjE114DHn0UH/j7o/Whh3DIUIZm2TiSSTA+Z4rB9zVfwB3SLYjxC0bct65G9Ac/w91hanA6O9EVFwssc7GAzWaDxWJZVqo/UMrDV28Mw20RE+BNTeJfJQb88YN+NPXOFf5dXV1uuyhzpt49UVtlsVhQXV3tNldzFouF1NRUSKXSef2udDodmpqasHHjxnVnAGqxWFBcXAyZTIaEhAS3ij7nSsHJyck59jB8Ph+BgYGc1tbWyNUeJ318fEwqlaqvvr4+pr6+PlooFE6uNxHrCdbXN8y95AG4iRDSBuAfAK4ihLxBKe2nlNoopXYAfwaQtdwNEkKIUql85ze/+Y3q4nz91NQUKisr521X4w5YLNbMlU5paanHPJyWi7+/PxITE3H27NmZk21XVxfOnz+PTZs2ub2+Q6VSQSAQuK2h8WxCQkIwNDTktlVx7vC0EggE87bBWAvuqrOyU4p/FQ9jcMyKL+VJEcCagqG42BGtmp2+O3QI9q98BZ+wWPi+QoH/TlTh7EQT8n3jkW4KhI/IBxzCRpwwCF+S5uFR9S34et5tuP7U6/jpl7ZCYTBgaGsWTrWexIh18ezIyMjIih3RE7NjcH82D1f1fIKJ4XG8dlSHVz4ZQo/+s2hnd3e327yrent7IRaL4ePj45btz6ayshIxMTFutYsAHHWO8fHxKC4uxuioowxnfHwcVVVV2Lhx47qzqHFG6yMiIjxW88VisSAUCuett5JIJITP54v6+vpWlgefhUqlGkpKSqpNSEioZ7PZNj6f79mGj+uAK0ZYUUp/SCkNppSGAdgF4BNK6V2EkNkFe7cAOL/cbUql0u/ecMMNGTt37rygVs256iQ+Pt7tB5LZEEKQkJAAmUyG4uJirzlfL4RCoUBYWBhKSkrQ1NSEzs5O5Obmeuw9SkxMRGtrKyYmVl1CsCwIIYiOjkZDw5wyApegUqkwODjockPSgIAAlzrWr9RywWlmODk5ibGxMQwPD0Ov10On00Gn08FqtUKn0+FwyQBqu0zYEsuF0seC4RMnQM1m+M6OVp0+Deutt6KcUvw0IQEPvfcCOqWT2OaXjM+JU2EymuZ87/gsLtJE4fiq5hrs/fuHaPnXSwho7YE69yZcf8NWvFj7Ds5ONGLSNtfoc6H6qqUQJcQj+/pM3Nb8D+SbqtE7PIU/Hh7E26f0aO8dhkAgAJ/PX/F2l8JpvBsTE+PybV9M97SNhbsibxcjl8uxceNGlJWVoaenB6WlpUhPT/fosXg5jI2Nobi4GMnJyW5ZnbhY1InL5YLNZs/b0zMkJIQ9MjKiHh8fX1W/p6mpKQ4AmEwm3ujoaIBcLndtM9IlsNvtBHPLfTzKFVW8vgDPEULSAFAAbQB2L+dFhJC0uLi4H/7ud7+bU/zQ0tICHx8fjzkYX0x4eDgEAgFOnTqFrKysdXVACQ4ORnt7O9ra2rBt2za3rXSaDw6Hg5SUFJSXl8+0yXAXGo0Gzc3NmJiYcHlEgMViQaFQoL+/36UHZJlMhqGhIZdFDwUCAUZGRsDlcmEymebcLq5DI4SAw+FccHN+RnY6BZO9HWdrg1DUKUaovwlSDKKhahLK06dhVKnQVF8PWlcHUUcHkh58ED1mMx6Oi8Wtr/0YnX4GbLSFIn5SjhHbCMbHxxf1hfJlCxB/wz3AwUCEXn89fn+4FDflfRUn//crSLohB1ECDVKEWsQJgsFjcaDT6VbtMyWMj4fiSzvB3r8f8epO1GV+AcXNJpzvsKMg1j3Rqs7OTsjlcrcfG0wmExoaGpCXl+fWcS7G19cXGRkZOHbsGKKjoz1SQ7YSBgcHUV1djczMTLfY5QgEgpmav4WOcwKBAAaDYea35oTFYiE8PJzT3NwcGRsbW83hcFYkUpqamiJtNhuHEEJDQ0M7uFyux9IndrudDA4O+mMFARJ3QNZbPc6lACHET6lUnj9x4kToxVd8w8PDOH/+PPLy8ryey9fr9aioqEBGRsa6OLA43Za5XO6034/QbaudFqOmpgZcLhfR0dFuHWdgYACdnZ3IyMhw+bbHxsZQW1uL7Oxsl23TaDSivLwcOTk5y34NpRSTk5OYmJiAwWCAwWDAxMQEzGYzbDYbKKVQKpXg8/kQCAQX3Hg83rLF7dFzz6J3eAJNuvuh8Bfg/12tAJdDMPbJJxg/ehTKb3zDkQbs7gZyc2E3GrH3umuh2Xs7enhjyCdRiDbLZ4rBe3p6ZhowC4VC+Pr6ztx8fHzA5/M/m9vhw7DfdBMaOBzkTE4i6eZrcPVTd8Iu5YNHOIjlB4HTNI5bsrev+D2fjbGuDvr9+8FVqcDdeSdeOdqLEYsPvrxVhiiN69qt2O12HDt2DHl5ebi4LtSVUEpx+vRpREREuNx7bSnsdjtOnz6NwMDAmTo1VxfNr5auri60tLQgKyvLbW10LBYLurq6llyw44wSX/B9n2b6N22USCTr2jPqIuwAzlut1vsyMjK8Nm8mYrVCpuuq3vzFL36hvlhUWSwWVFRUrJsCSalUio0bN6KkpASJiYkec1WeD6vVipKSEsjlckRFRYFSirNnz6K9vd1tResLERcXh5MnT0KlUrlVcCoUCjQ1NWFsbMzl44jFYkxNTcFkMrns4CwUCmEymWC32+f9/tpsNoyNjWFkZAQjIyMYGxsDpfQCYRIUFARfX1/weDwYDAbU19cjJSVlzXOzIQ61AxtBYMOODSZwOQR2oxGGoiIIEhIcompkBCObNsF/ZATWTz9GmHYcbVMDuDkgCxk+F5q2joyMoKCgAJRSGI3GGVHY3d2NiYkJmEwmcLlc+Pv7IyAhAbK//x2xd9yBmqAgpH1wHI9/8zFExSSjcrId5yfbYQ62QjpejS2+qy8+FsbFQXrbbdDv3w/L31/BVTmbcXLAH/sL9bj/cwoo/V1TH9TW1obAwEC3iioAaG9vh0gk8rioopSivLwcSqUSWq0WwcHBKC0thdls9miD6fnm1dTUBJ1Oh9zcXLc2fOZyucuu2erp6UFXVxc2btw457254447zB988MH/DQ8P/8Ed87xc8f7Z/xLDz8/vK9u2bcv78pe/fMFRyfljjo6O9kgx6HLx9fXFpk2bUFdX55Zl+sthamoKxcXFCAwMRFRUFABH2icjIwOdnZ0ubaq6HJyNmsvLy91a5E8IQVxc3Jpa+yyGO6wXAgICMDo6CkopxsbG0NrairKyMhw7dgwnT55EW1sbACAsLAz5+fkoKChAdnY2EhMTodVqIZPJZq5+XdnWpqTNEV2MVn6C882/x4RJB0NREajZDHFBAejkJFpTUiDq6sKbt9+G17SjaJ8axK2SnDmiymazzQhH5yoppVKJiIgIpKSkICcnB9u2bUNWVhbUajVMJhNqtFpU7d0L1cAAGsPDEa9WQ20XY/LDZmztCEQUVeDjsUocGDkNK139d0oYFwfprl2gQ0NQ11Tiji1ScNkEbxzTwWBc+3fVarWivb3d5T5oFzMxMYG2tjYkJCS4dZz5qKurA4/Hm+mA4PTTM5lMqKys9MqqaUopqqqqYDAYkJWV5VZRtVICAwPB5/NnftuzeemllwJkMtmThBDPpxYuYRhhtQIIIYH+/v7P/ulPfwq4+LG2tjbweDyPFWiuBIFAgJycHHR1daGxsdGjBxZnZ/bo6Og5NSjOA15tba1Li6aXg1gsRmBgIOrr6906jrNeyelu7UqCgoLQ1dXlks/TKaTsdjvKyspw9OjRmeJ7p4jaunUrNmzYgPDwcEgkkiXr4zgcjkuEq53a4MN1eLTdmH0t7NSCosrfYKTkFAQJCWDLZKhMToa2sxMvb9uKkb23omtKh53SPKSKwuZsz2g0Lqu2iMfjQaFQIDo6GpmZmUj5wQ9gf+st+LW0QHbXXTj5/vv46le/iuu3fx66d6qQJ4hF2WQrXhs6ikn73KLgZRMaCn1UFKxNTeC31uHOLTJMmOz42wkdpqxrq8ltbW1FaGioW1fHORfvpKamelxAtLW1wWAwIDEx8YL7CSFISUkBn89HSUmJR1dN22w2nD17FjwezyWO8+4gKSkJHR0dMyspnYhEIuzfv1+uVCrfmW4Hx7AM1t8nvE4hhJCgoKB/P/fcc7KL0zqjo6Po6OhAUlKSl2a3NBwOB1lZWTAYDKiqqvKIuDIYDDh9+jSSk5OhWsDFms/nz6zgcfdqvYuJjIzE8PCw21sCxcfHo66uzuXb5fF48PX1XbUoNRqNaG1txZkzZ2aElJ+fH3g8HgoKCpCZmblsEbUQLBZrzScxw2Q/jBYJfLmj8PcNRHbCbkwYh9AQOwB+TjaOJSUhtaUF/yzYCtvfH8WQfRy3yzYjURgy7/YmJydn6qtWCucLXwB55x0Ia2rwueefR8knnyAoKAjfffi7ePaL30NQDdBhHsQfej9Av3F4VWN0dXVBnJcHblAQRt9/H2r+FL6YK0GPzoJ/FQ8vaCa6FM66G3fXGjU2NkIul6/YfmKt9Pb2oru7G+np6fOm+5wRZLlcjtOnT7vNY202U1NTKCoqgkqlQlxc3LozJnXCZrORnp6OsrKyOavJN2zYgJtvvjlaoVD82EvTu+RghNUyEYvF/6+goCA6OjqaVVpaOvPls9lsKCsrQ3p6ukdXuK0GZwqMx+Ph7Nmzbr1qGx8fx9mzZ5Genr7kKjMfHx9s2LABZ8+enXf5r7sghGDDhg2oqqpy60FWLBaDz+djcJlmkythJZ5WlFIMDw+jrq4Ox44dQ1lZGSilSEhImBFSMTExLrXpcEU6cHi8HSaLHD4cx2ck5Ycgoj4ABokV3T+9H9saGnA0Pxe9bz6CYbsBd8q2IlYwf+TYbqEY+KcZ9JgYlvFVfv9vugl46y2gpASx3/kOXv/97/F///d/OHXqFJ689xHssCfDZJ/CnwY/wvuln8ysDl0OlFJ0d3cjKCQEkltvhX1qCiP/+Q/iggS4doMYNZ0m/LdideawTU1NiIiIcOtxanR0FP2Ohr5uG2M+9Ho9GhoasHHjxiX3Lzw8HCEhITh9+rRbLWkmJydx6tQpREdHe7yOdDX4+fkhMjLygt6q4+PjKCwsxLe//W2+v7//t5iU4PJghNUyIIQE+fv7P/OHP/zBPzMzE2q1GidPnsTg4OBM7yt3LJl1B86rNpVKhaKiIre0XhkbG0NJScmKViMGBAQgPj7+AgNRT+Bsxnr+vHtX58bGxqKurs7lkUKFQgG9Xr+gSLbZbOjr60N5eTmOHj2KlpYWiMVi5ObmIjc3FxEREXM63qt7emA4dswl83OFsBoc7YbFLoaI43jvDMXF8GmzI/u/VsS+/jG6bsxH+VuPYcxuxJdlBYgUzG9zQu0U7W/rYeslsA2y0LhvEJO9q/z+f+ELwP79YJeWIvHJJ/HoI4+grKwM//u//4uNoYl4QPN58CwEJepBtHL0qKysxLFjx1BTU4Ph4eEFvwfDw8Pw8/MDl8sFV6GAeNs2mGpqYKyuRm6sLzZG+eBkrQGlzSuL7ppMJvT39yMkZP4oniuw2WwoLy/3eLrLYDDMLBpabkF+SEgIwsLC3CauRkZGcPr0aaSmpi4YrV+PhISEwGazobe3F83NzTh37hz+P3tnHR5Zeb7/zxnJTHwycXe3jW5ss4ZLsbZQKF6gtLRQoVSAfktLS12QFihSoEipAC3QRZe4u7u7yyQZO78/ZhM2G53YLvx6X9dehDNzZGbOed/nfZ77ue+YmBiioqJ4+eWXnVxcXP7xv5LgxvhfYLUBTnQB/u3pp592XAyePD09SUlJoa6ujr6+vl0drHYLvr6+BAcHk5eXt6MluKmpKUpLS0lMTDS7E87V1RVvb2/Kysr2lAfm4+PDwsICAwMDu3YOGxsb7OzsdvwcgiDg5uZGf//H3qWiKDIyMkJFRQVZWVmMjIzg7e3NwYMHSUhIwMPDY22OzZNPEnbDDdgcOQLf/CZsUzl9J9TX+0dNvA8bmRbj/Dz9H37Ik3/5C64/fpKxw3H85TfXM2PUcL3TYfwUq3egiaJI75uTTDXMY4iexuNqKxCg5c8jTNRsMfC7/HI6vvlNLI8fh4cfJiIiguuuuw6AnDc/4FepdzB4rI4sWQvzkTakpaWhUqloa2vjo48+or6+nunp6WWH7OrqWsZFtElLM5UE//MfjLOzXJBgT5Cbgn8XT9A6sHlB6+bmZoKDg3c14GloaMDLy2tPF5kLCwuUlJQQHx9vdnnX09OTgICAHQ+uhoaGqKioIDk5ec/LoTuB4OBgSktLmZ2dJSMjY8mnMiEhgeuvv95XrVZ//zRf4hmP/wVWG8DOzu5L5513XuRZZ5217LuSy+WIooivry85OTmMj2+NT3E64erqSmxsLEVFRTtCHl8MqpKSkrY8uPr6+mJvb79nPDAwBSf79u2jvr5+V0uRISEhNDU17fjnWiwHTk1NUVdXx/Hjx+nu7sbLy4tDhw4RFRWFo6Pj+pOqXg/f+AbceiuGQ4cYuuwyk3Hxvn2Qm7vla9tuxsooGhiZNmUwraRauo4d4xePPsr/9fUxHBzIX568B6PCkoDuMmRTvWseZyhrhtHiWZwzbNC4j6LysyH4Nmcs3eR0/m2MgfenEI3m/S6iKNJx3nmIF18M3/kOVFUtvRYYGIiPtzd/vPkBPvj6M7zZlc/r08W4uLuSkJBARkYGtra21NbWkpWVtVQuHB8fx8nJaek4glSKw2WXYVxYYPLNN5FKBD6focbJTsYrOWMMTW4cEGg0GsbHx/Hw8DDr85mDkZERJicnd73b8GTo9XqKioqIjIzcskm1h4cHAQEBO+ZU0dXVRVNTE6mpqWdUd/hmIIoi3d3dVFRUEBQUhE6nW1FW/clPfmLj6Oh4pyAIu28w+QnG/wKrdXCiBPjgI488suKpbWhowNfXl9DQUBITE6mtraWhoWHHbUZ2Gw4ODiQnJ1NRUcHQ0Nb11E7OVNnY2GzrmkJCQjAajbS0tGzrOOZAoVAQFha2q+3YlpaWODk57ahEglarZWBgYEmYVqVSkZmZSVxcHE5OTpsjy05OwsUXw+9+B3fdhfStt6i74w7E994DnQ4OHNhy9mq7Gavp2X40WgcEQWR+tIc7b7yR34yNMeflycuv3YfOyoKbnc/FU+FEScPTjE21rzjGWPksA+9P4RBriftZduj1elOpzUZK4I1OqOOtGPxoms5XxjAsbP75nZycxM7eHuGpp0CthmuugRNBZFRUFAUFBfz4xz+m6N/Hefro9/n7v//FsyMfMmtYQCaT4eXlRUpKCvv370cikVBQUIDBYKCvr2/ZOCJ3ccHu8GHmamuZq6lBKZfwxYOOyDYpw9DY2EhoaOiuEad1Oh01NTXExcXtGTnbaDRSUlKCn5/ftvX5PDw8CAwM3FbmatHQur+/n5SUlF2xIdpNLGb+RkZGSE9PJywsDKPRuCLDbmFhwcsvv+z4vy7B9fG/wGoNLJYAn3nmGcdTsy+jo6NMTU0tddfY2NgsWaTk5uauSO+f6bC2tiY1NZWmpqYtmftOT08vBVU7UQZYbI0eHR2lu7t728fbLNzd3ZHJZLuq9xUcHExra+u2AnBRFBkbG6OsrIz8/HwEQSA8PBxHR0c8PDzMIye3tkJqKrz3HjzxhClLJZPR7bFAYaw7VFfD7bdvOXtlZWW1rYzVxEw383pHbC10/PZrd/D4+DgyRzUv/PM+dGoVNzkdxUPpRErk7Sgs7Cmo/SMzcx8vEKaa5ul+fQKbQAVelzggIi6b/CUyAa9LVHicZ89kwzwtfx5GO745jt/o6Kgpu+TsDM8+CzU1cM89S6/L5XLuvfdeSkpK8PXwJkbnQZ92lCeH32FE9zEBXaFQ4O/vj6WlJbGxsUxOTi7xsRbL9Dbp6cg9PJh4800Ms7OorGVLMgwvZo+i06++GJienkaj0eyqSGdNTQ2BgYF7Zp0liiJVVVWo1eodo2F4eHjg7+9PUVGR2RxPo9FIZWUl8/PzJCUlnVEaVZvBwMAAeXl5eHl5ERcXt0QTiImJob6+fgUPNz4+nhtuuMHX0dHxf12Ca+B/gdUasLe3v/WCCy6IPHr06LLvSK/XU11dzb59+5YP0BIJoaGhREdHU1ZWRltb22kRotsqFAoFKSkp9Pf309jYuOlrn5mZWSKq7yS3QiKRkJiYSEdHx650062FqKgoWltbd0zY8lRYWFjg7u5OZ2en2fsuijtmZ2fT3t6Or68vmZmZBAQE4OPjQ39/v3n33PHjkJwMg4Pw7rtwyy0AVM910mIzzjvz1cxYSuHRR+H99z/OXn3rW5vOXsnl8m2VWCamO1nQO9Py2iM8NTKCg1LJC6/ei9bbnZudjuIkN/H4FBa2pEV9FUSR/OpHWdBOo+nV0vnKGJaucvyuUiORCasq1QuCgHOaDf5fdEQ7aaDp8WFmOjYuCS8zXj73XLjrLnj4YXjrrWXvi4mJoaioiO/dfBc3OB0l72/v8s2//pT2hY+FcTUaDaIo4uzsTEREBAcPHsTe3p6KigoKCgoYGhlBdemlGOfnmXzzTQA8HS24ItWB3nVkGBoaGna1zb+/vx+9Xo+X1+54Gq6GpqamJaPznYSnpye+vr5mSTHo9XqKi4uxsrIiJibmjNSoWgt6vZ6Kigo6OztJS0tb4TuqUCgIDQ1d1iW4iB//+Mc2jo6OXxcEIXyvrveThE/OXbCHEATBy87O7scPP/zwihLgYhfgWkRJlUpFRkYGGo2G/Pz8XZugdwOLWlfz8/NUVlZumFWZn59fIo7uhjXM4vXU1tauEK7bLcjlcqKiopakCHYDAQEBdHR0bHrwnpubo7a2luzsbObn59m/fz8JCQnLDFZlMhn29vab1+R64gk4+2xwdYWiIjh0CIBZwwJvTZbhJLHFgJEPp090Sx45YuIQffnL8JvfmJ292up3OTbdzYLegSPt9fgJAi+++D3mI4K52fksHGTLS842Vq7sj/wyc9oJigpfoO35EWTWEvy/6IhUYRrq1tOwsgtWEnKrMzJLCa3PjjBasnZTx6JH4jIezc9+BjExcOONcEpZXS6XIwgC3haOdL5cxPM3/pxLr/kcH/WUAytJ6xKJBE9PT9LT04mIiDBlFRoa0MfEMFdTw1xtLQAR3pacvc+O2u453q9aLsMwMTGBXq//OPjbYSwsLNDQ0EBMTMyelQA7OzuZnJzctXN6eXnh7e1NaWnphuPfwsIC+fn5eHh4nFarnK1gdHSUnJwc1Go1ycnJa5YuPTw8MBqNy5pj4H8lwY3wv8DqFAiCILi6ur70zDPPOJ3KFRodHWV6enpDgT2pVEpUVBQhISEUFhbS3d39icleLZbhrKys1k2L63Q6ioqKiIqK2jJxdDNQKBQkJiZSVla27e6yzcLJyQk7Ozva2tp25fhyuRwfHx/a21fygU7G7OwsFRUVFBUVYW9vz8GDBwkNDV1zENyUppVeD3feCbfdBmedBfn5EPix5ct/J8uYN2r5vGM6HpNWlM62fly2srWFxx4zZa+02k1nr5RK5YZmsKvBaDQwNDGLiITpe7/BI/m/ozs5lJucjmIvXT04crQPJN7nRixzMtDrF/C7Vo3c9uNxfyPVdYWTnOBbnbENUNDzxgQ9b04gGlY+u1NTU9ja2i6fTJVKePFFmJoyBVerPPOCIJB9PIvv3vt9al7L5eLEozz4t4fp6+9bkTFYhJ2dHbGxsaSnp6ONiGDexoaR119n4cRiIz3MhsRAK7LrZig7SYahvr6e8PDdSSgsWniFh4fvGZ9ocHBwydR8N4MYHx8f1Go1lZWVa47bMzMz5OfnExoa+onqCjcYDNTV1dHQ0EBycjI+Pj4bfpcxMTE0NDSsKAnGxcVx0003+To6On5vN6/5k4j/BVanQKlUXpKenh519OjRZXfbWiXA9eDk5ER6ejrDw8OUlJTsimbUbkAQBEJCQvD09CQ/P39Fp5zBYKCoqIjg4OBlHUy7BRsbG2JjYykuLt6z7zA8PJyenp5d48v5+fnR09OzaplscnKSkpISKioqcHd3JzMzEy8vrw3LDGq1mqmpqbUzYRMTcNFF8Ic/mMpW//43nBQUN8/3UznXwQHbCNwsHIhacEWGlHenKpcf58gRE/fq5OxVXt6a17VVAvu0pp85nQMLczMMSQaZ9HLmTreLsZWuHRgZFoxo3vJArlPRH/tXmidfWzY5bkZ1XWppynI5p9kwWjhL2/Oj6DXLsxdL/KpTERkJv/ylqRz42GOrHt/CwoKf/fhB8gsKcFCruffKr3Nc18C8sH7JVC6XExwaiucXv4ig1dL+wgvU1taysLDAhYkqAt0UvHFChmFkZASZTIZKpVr3mFtFd3c3CoUCN7fVNcN2GhMTE9TX129KAHQnEBQUhFwuX9Xnc3x8nOLiYuLi4vbcYHo7mJqaIjc3FwsLC9LS0jYtT7FeSfCHP/yhtY2NzZ2CIOxey+knEP8LrE6CIAiW9vb2jzz66KOqU1+rr6/Hz8/PbK0UuVxOfHw8np6e5Obm7rnh8Hbg7e1NaGgo+fn5zMzMAKaVamlpKZ6enmuusHcDarWakJCQXVeMX4RUKl0yat6NTk+pVIq/v/+yzsfR0VEKCgqor6/H39+f9PR0XF1dNx3IC4KAh4cHvb2ryA60tJhI6u+/D08+uURSX8SCUce/J4pxktlx0Nbks+bh4Eqk3o36+R46Fk7pGD01e5WRYcperVL63iqBfWKmi3m9I1XZf+fe869H2TCxZqYKQDSIdP5tjLl+HX6fd8IrIoy2vuO09L6/9J65ublNPcOCRMDjPHu8L1Mx27lA8xNDzA99HPgs41ediq9+FS64AL79bThRslsNyYlJNJbVcPcjP0Iaqebhwbeo1LRvmN1Wenhgd+gQtoOD2I2OUlhYSE11FRfHKZdkGEqqWwkL252OeI1GQ1tb255ZeM3OzlJeXk5SUtKeZccEQSAyMpK5uTlaW1uXtg8MDFBVVcX+/ft3NVO/kxBFkebm5iXx1qCgILMzfh4eHoiiuKIkqFQqeeyxx9Rubm5P7eQ1f9Lxv8DqJDg7O//47rvvdjx1FTY2Nsb09PS2bAk8PDxITU2lo6ODysrKPVUX3w5cXFyW7GZGR0epqqrC3t5+1/3GVoO7uzseHh57JiBqb2+Pq6vrkhnxTsPHx4fBwUGGh4cpKCigra2N8PBwUlJStsyL8fb2XtlJ+eGHJpL60JCJpP6lL63Y74OpaiYMs1yiSkZ2gjLh6OiI27AFthJL3pmsWP0730T2ytLScksZKxNx3YW+pgKsnVX4265dchFFkZ5/TzDdvIDXxSrswyyJCrgcD6c4atv+Se9wGWAKCszpXlPHWRN4oxNGrUjzk8NMNc4jiiKzs7Nry4oIAjz9NNjZwdVXwzplUKlUygWRmdzufB4jBa1ce911PDvwAZP69UV7bQ8cQO7mhqyggIzERFxdXampKiPBZRgBI1VjblhabU/2ZDUsGixHR0fvSffbwsLCUnZor3WhFi2vhoaG6OnpoaOjg9bWVlJTU7fsNbnXmJ2dJS8vD71eT0ZGxra4sNHR0TQ0NKzIsl9wwQWSyMjIZKlUeni71/tpwf8CqxMQBCFQpVJdf+eddy5rGRJFkZqamh0hSyqVSpKTk1GpVOTk5DA2Nrat4+0V7O3t2b9/PyUlJWg0mj33ATsZ/v7+WFtbU7tOJmAnERQUxMjIyK4IwM7NzSGVSikvLyc0NJSkpKRtr4ItLS2RSqVLGUYefxzOOQfc3JaR1E9Gj3aUgtkmkqyD8FV8rAlka2vL/KSGI7bR9OhGqZ1fQ/piMXv13nuwsLAie7XVUuDETDdagysdDUX4JIXgNL/2ZDb4wTRjZRpcD9nimGiagAVBQkLYDajtAilteJbRyRa0Wu2mbU8WYe2jIPg2ZxRqGe0vjtL9/gg21jbrjweurvDMMybC//fXFqru7e3F09MTFwsVPt0Kqv+Rwy9u+C6/636dktmWNRcQglRq8hLUaJh8+23c3Nw4cOAA3m4qvGVtzGhl5DdszVNwPbS2tqJSqXaNEH8yDAYDxcXFhIeH71pJcyMsdifX1tbS3d1NSkqK2ffP6YAoinR2di59f+Hh4dvuWFQoFAQGBtLY2LjitT//+c9qJyenpwVBWMPS4f8v/C+wOgFXV9fnnnrqKadTV2EdHR04OTltW/RyEYIg4OvrS1JSEvX19dTV1X0iREUHBwdRqVQYDIYtSQXsJMLDw9FqtctS9LuFRePqncwyLiwsUFVVRWlpKSEhISiVyh0tcfj4+NDV1gZf/7opk3T22StI6oswiEZeHy/EVqLkbLvYZa/NtC3gkBeEY5YdLjJ73pusRC+uU4Y9etSUvbrttmXZq62orxuNBiame+jrnWZqbIh9CTHIjasPV6PFswx+NI063grXw8slP6QSOSmRt2GlVFNQ+ycMTG1pgWRhLyPwZifsIywZz9JiWe6Kpm8Dvt8FF8Add5jKru+8s+pbenp6lqQK7rzzTh599FEa3inh7zf/jn/05/LsyAeM6WdW3Vfu5obtwYPMVVUxV1+PIAim5pMAFZ72Rj6snqSmoXXHSudTU1P09fXtWonxZCxSDry9vU+r157RaKS6uhpXV1cMBsMnQqNwfn5+yU0jIyMDtVq9Y8f29vZmYmKCqanlQbufnx+33nqrs1qt/s6OnewTjP8FVoBCobgkLS0t/MCBA8u2Lyws0NHRsSsZGmtra9LS0rCwsCAnJ2fFjXomob+/n76+PhITE0lNTV0ynz5dnY6LFjSDg4Or84l2GDY2Nvj5+VFXV7et4+j1ehoaGsjPz8fR0ZEDBw7g6upKSEjIqqvALUEUcWtpwf2GG0yaSt/4xgqS+snImalnUD/JRapElJKPV+JjFRranh9F0AtMlixwtjyWMcMMJbMbqOHb2sIf/7gse6X4wQ/QmXl/T2n6WDBY0l5fCsB5h85Z9X2T9XP0/GcC22AFXherVg2aLOQ2pEbdgYCEGcmHlDU+R+dAPrNzI2bdw1ILCb6fd8AQOYU4IqX5T8O0vzCKpnedAOsXvzAR2q+/Hk7RY5uenkYmky0rTX7lK1/hqaeeovZ4Ce/d/Cc6pvp5dOgt8mYaMIorF2CLJcGJf/8b/cwMzc3NhISEcHm6G0aklHVLycrK2nZnstFopKKigtjY2F0nj4uiSHV1NXZ2dtuiX2wXOp2OwsJC7Ozs2LdvH0lJSZSXl++ot+pOo6+vj/z8fPz8/IiNjd3xcq0gCERFRa1qOfaDH/zA2tbW9n9Edv4XWCEIgqWDg8Ojjz322Aq3zLq6OkJDQ3eNSyAIAkFBQUsk6ZaWtVP/pwuTk5M0NjaSnJyMVCpFKpWSmJiIXq+nvLz8tGXbJBIJSUlJtLa2MjIysuvn8/X1RaPRbMn2Z5H0mZ2djYWFBZmZmXh6ei4FAa6urszOzm5vNTw7ayKlx8UhPXQIu+Zmpn79a1PmaI2JcFg3xfGpGiItvQmz9Fq61sGPpun+5zg2vha4XWWFqAe7MhsCFK4cn65hzriJzsyTslfCb35D4i23IBYUbPrjTEx3Ma9zxDskiXO/exsXpZ678iN3LdD56hhWHnJ8r1QjSNfORFlbOhHlez2WMg8Gxmoob3qed4vv553CH1DS8Awd/TlMawY39fxNugwQ/k033I7YMtu9QPPjw7S9MLJ6gGVpaZJgGBuDm29eJsFwqnbVIm666Saef/55ogPDucvnUvwsXPnvZDlPjbzPsG65npsgk6G67DKMGg39//wnrq6uKJVKnO3lJAdb0zoqJyhyP+Pj4+Tl5W15AdfY2Ii7u/ueELZbWlowGo2Ehobu+rnWwvz8PPn5+fj4+BAUFASYFsNxcXGUlJTsqGnzTkCn01FWVkZvb+9S08tuQaVSYWtru8KhQqlU8uijjzq6urr+f09k/8QEVoIgSAVBKBcE4T+nbP+2IAiiIAhb6vt3dnZ+4O6771avRlifn5/fk843Ozs7MjIy0Gq15OXl7Zle00ZYWFigvLychISEJZsDMAWE0dHR2Nvb77gzvDmQy+UkJSVRU1Oz6xm/xSxZbW2tWZIPMzMzFBYW0t/fT2pqKgEBASu4DoIgEBYWRkNDg/kX1tJi8vHz9IRbbzVN3I8/zlR9PU2ZmWvuZhRF3pgoQi5IucA+ATB11fX8e4KB96dQxVjif60TLmEOaJ1nGCmc5WyLWDRGLTnTm8zcnZS9kuj16MwIgCdmutAZ3XBw9eWia89HZbG8FD8/rKP9r6PI7aQmAVCLjYcyKSr8nC7h/JSHOJJwLzFBV6K2D2B4vJGK5hd5v+RH/LfwexTX/5m2vo+Ymu1DPCVLNDs7i7W1NTJLKa6H7Aj/hhtuR+3QdGtNAdbzI2h6Trk/YmLg5z83ZQ4ffxwwZYCGhobWnACvueYann76aRzkNhzU+HOWGMaIborHhv7LR9O1GE66Lgt3d6wzMpC0tOB90kLncLQdlnIJ71bPEh0dTVRUFFVVVVRXV5v1zI6NjTE2NrYUYOwmuru7GR0d3VPR0VMxPT1NQUEBEREReHp6LntNpVIRFBS0Zw00m8Hw8DA5OTm4uLiQlJS0JxywsLAwWlpaVtxHF1544SKR/ZC5xxQE4WlBEIYEQag5aZtaEIR3BUFoPvHfFQmQMxHCmXJzbARBEL4JJAJ2oihedGKbN/BnIAxIEEXRrNSFIAiBQUFBhfX19Y4nZ6VEUSQ7O5u4uLgdtWnZDMbGxqiqqsLf339T4m27BaPRSH5+PsHBwetqtfT29tLa2kpycvIKq5C9wqJX4f79+3fdr6y3t5eBgQESEhLWfZ9er6e5uZnh4WGioqI2xXPIz8/fHFHXYIC334ZHHoFjx0yyCZ/9rKnNPz0dBAFRFMnKyiI1NXXVgbZ4toV/TxRzqSqZeOtADAtGOl8dY7ppAZcDNridZYcgCAwPD3PBeWdznvsX+Oq3bic3tpbauW7udL0Qe9nmu7Qqi4rwCQ7GwWFz4+LxsocoaYogv7Cb628O5jNR53D8+HEOHTqEbtpA85PDiDqRoFtMpPLNoLm5GUtLyxX2K6IoMjs3xMhkMyOTzYxONDOnnQDAQmaNo30QjvbBOKmCGR/WYTSKBJ7CVzPMGxkpnGU4bxrDnIhtsALXQ3ZYe5/47o1GOP98yM6G0lIG1WoGBweJiYlZ95oNBsNSSedf/32DInkXtfPduMsduFS1H3cL0/fZ2tSExX/+g8xoxPWOO5CceBaLmmf4T8kkV2aoifS2RBRFuru7aW1tJSgoCC8vr3XHGL1eT05ODklJSbvelTc8PExDQwOpqamnzW9vdHSU6urqDd0kFqkQERERe3h1y2EwGKivr2d6epp9+/btmVfjIjo7O5menl4hu9HR0cH+/fs7hoaGQkRR3HQELwhCJjADPCeKYtSJbb8AxkRRfEgQhO8CDqIo3rPecc4EfCIyVoIgeAEXYgqiTsZvge8AW4oOXV1dn3v66acd1yKs73VQBSa9poyMDCYmJigqKlohzrkXWDQ5dXNz21AAz9PTk4iICAoKCk4bsdPW1pbo6GiKi4t3PXu2uIJdj9s1MDBAdnY2CoWCAwcObJo8Gh4evn7WanTUxNkJCoKLLzZ1nP3oR9DVBS+9ZOrGOzFJCoKAp6fnqtc5ZdDwzmQF/gpX4qwC0M0YaH1mZEmqwP1s+6XJNr/0NUrKKvnJm9+l/p02DiuiAZH3p6o29ZkWobS33zSB3WjUMzXbR3VlG//83R1Ihj/OwhjmjbQ9P4pBY8T/i46bDqpgbdV1QRCwsXLFzz2DxLAbOWf/g5yd9ABxIdfi5hjN5GwPNW1/53jZz6jq/gNj87nMzi1fw0mVElwP2ppKhGfZoenV0fLkMG3PjTDbrQWJxGTUbG0NV19Nd0vLqmXAUyGVSvnNb35DY2MjFx09n0xtIFepM5g2zPH48DHem6piTjtPV28vTldcgXF6mql3313aPyHQGhd7GcfKJ9EZTAbUPj4+ZGRkbKo8WFtbu9SJu5uYnJyktrb2tJoY9/X1UVNTw/79+zeUJQgLC2N6enpXDdvXw8TEBDk5OVhZWZGSkrLnQRWYmmQ2ILLfbc7xRFHMAk5tlb8E+MuJv/8CXLrFy91TfCICK+B3mAKopRFWEITPAL2iKFautdN6UCgUn9lrwvpmIZPJiI2Nxc/Pj7y8vBWibLuNjo4OjEYjAQEBm3q/k5MT8fHxlJSUbN6rbofh6OhIUFAQxcXFu877io6OpqmpaYVNi1arpbS0lJ6eHtLS0ggICDAr46hSqZBKpSu/w5ISk0WKlxfccw/4+sLf/gadnXD//bBGuXo1TStRFPnPRAkG0chnVEksjOppeXKYhWE9/lercUyyXvosY1PtiNZVPPHi15DJpDx87Bfoy0T224RQOddBv3bzEhTmSC5MzfZhFPU019Yilcs5K/WQ6QUjdLw8xvyQDt8r1Vh5mlfy2IzqOpgCLWtLJ3zdUokPvY5zkn/MOck/IT70emRGN/rGinm3+IcU1/+Z8enlHbJShQTXTFvCv+FqCrD6TgqwdGp46imoqMD9V79CtUlNoXPOOYe3336bzs5ODh48iO0I3OF6ATGWvmRN1/LYwNuo/Fyw9PXFJjWV2eJiFk7YJUklAufH2zMxayC/4ePuQrlcTkxMDFFRUVRUVNDU1LTiuRkaGmJ+fn5TAeB2oNFoKCsrIzEx8bRlvdva2ujo6CAtLW1TQYogCMTHx9Pa2srExMTuX+AJGI1GGhsbl7Jq5o4xO4mNiOw2Njbf2AEiu6soiv0AJ/77iZC6P+MDK0EQLgKGRFEsPWmbFfAD4P4tHlPm4ODwh0ceeWRFXaK+vn5XCevmwNXVlbS0NHp6eigrK9sTLtPw8DC9vb3Exsaa9cDa2dmRkpJCTU0NfX19u3iFa8PDwwNXV9ddNVAGkyVJZGQkFRUfi2YODAyQm5uLu7s7iYmJW5ZPWORaiXNz8PzzkJICSUnw6qtwww0mQvjx4/C5z4F8fckYhUKBQqFYtqKsm++hYb6XI3bRKHstaHlyGKNWJPAmJ+xCTRPK1NQUBw6kc88PvoSlhYrrrvgpF1+WzmsVL5P19wIyFBEoBQvemarY9OcyR3JhYqaLBazoqi/FPzwSpVKJYc6IbZkXM20LeF+iwi7Y/Al4fn5+yxO3lVKNo00UTpaHOSf5xwR7n83gWB0flf+cnMrfMjBWs+yeOznAcj/7RID15xFax9MY//wNeL72mongv5G34wkcOnSId955h8HBQe666y6sJAouV6dylV06c6KWY8pG+rVj2B45gtTBgfHXX0c8MV4EuikJ91KSVTfNlGa59IK9vT0ZGRkYjUZyc3OX7hWtVkttba3Z44C50Gq1FBcXExsbu2OSNuZAFEVqa2sZHx8nJSVlGZd0I8jlchITEykvL9+SF6a5mJmZIfeE8Xl6evppqaicCpVKhY2NzYrMuFKp5He/+53azc3tt6fp0k4rzvjACkgHPiMIQgfwMnAEeB7wBypPbPcCygRB2JRxla2t7ZeuueYaRw+P5cH02NgYc3Nze2rVshEWTYidnZ3JycnZ1Q642dlZampqSExM3FJLtaWlJWlpaUsKxacDgYGBKBSKVT2+dhIuLi5YWVnR2tpKaWkp3d3dpKWlceo9ZS5s9XoCnnsO0csLrrvO5O/3+99Db6+JCG6mjcjJxsxzRi1vTpTgLncgosuH1r+MILWSEHSL81L2Z2ZmhgsuuIDSsjKc3ZUkR9yCwsKGW2/+Nj7eLgwODzBbpuWgXSStCwO0zG8um2pOxmpiuosBnQ/97dXsT80AoPXZEWRTlqhiLFHHbb0stZ0gYdHGxlKhItL/Us7d/yCRAZczOzdMQc1jfFj6IF0DBRiNH+udSRUSXA58HGDN9evoCvkxY3f9AbGkxERsf/HFTZ0/LS2N48eP88QTTyxtE7umuUTYh1yQ8szIB/QyhcMll2AYG2Pqgw+W3nfuPnsMRpH3qlaW/SQSCWFhYcTExFBRUUFzczOVlZWEhobuagZpUQA0JCRkR7WWzDl/aalpvR4fH78lAU1ra2uioqIoKSnZNastURRpb2+npKSEqKgoQkNDty32uZMIDw+nubl5xcL/0ksvlTg7Ox8RBGE77Z2DgiC4A5z4r/lt2acBZ86vswZEUfyeKIpeoij6AVcBH4iieIUoii6iKPqd2N4DxIuiOLDR8QRBsLS2tr7/vvvuW7Y8Wly5REVFnbbU6loQBAFvb29SUlJoamqipqZmxx9ivV5PSUkJcXFx2xpM5XI5KSkpTExMUFtbe1o6ZyIjI9FoNLSfKIfsFhwdHamvr0elUm3fx2x0FO69F3x9cX/iCcbDwhDfeQfq601Cn1tsc3d1dWV4eBij0cg7kxVojAuc3RhP998msHS3IPhLH5O/Z2dnufDCCykoyOeb953FrTd+H5WtqQxkoY7k18+9QkJSAIPZEyRaBOEgtebYZMWq+kqnQqlUbnpVPzHTRV29BqNBzwVHzgJAbmsK9H2u2FpTkE6nMysbsRpONV6WyywJ9jqLs5MfID70OgDKmp7jnaL7ae5+F53+4wzdYoDlebMlBl8N3baX0/ez44jhEXDNNfCFL8Am1P3j4uJwdHRkYWGBa6+91jTZeodws9NZWEoU/GXkQ/o9bbBKSGAmLw/tiUyC2lZGaqgNFe0aekdX72pdzF6Nj48zMjKyqxmRRWscDw+P07KQXdSoUqvVREZGbmvMd3Z2xtPTk6oq83iHm8Hc3BwFBQXMzMxw4MCBTTd/7CUsLCwICAhYYf0lCAKPPPKIk5ub2+pu5JvDG8D1J/6+Hnh9G8faM5zxgdVOQ61W333nnXeqTu286uvrw97e/oxIr64FS0vLJZ+qnJycHa3tL3Yi7oR1hEQiIT4+HoDS0tI9MU0+GYseX319fbvCTzMYDFRWVtLb20tycjL9/f1bDyCHh+G73wU/P/jpT+G886Cykt4//pG+iIglMvpWIZFIcHZ2pmyggdLZVs4pTmD2XR324UoCb3BCZm0KWIxGI5deeik5OTnc+f0jfOGqa/FzT8dgFHm7bILjLQoq+wIZ823lX3l/Z6R4krPsYhnUT1Cp6djUdWzmOzIYdYxp+nGJzuRrv8vm4gvOQjSKzHYvsOC2NdV0MN8jcDVMTk6uquMkkcjwcU3hcMIPSI36KjZWrtS2/4tjhT+gpu2fzC1MLL23Z6Ab9wttcTvLjpEhN1pv+gfG+x+Av//dlL06Kcu0Hvr6+jh27Bh33XUXRUVFqGTW3Ox8FDupFc+PHmfk8D4kNjaMv/Ya4gnHgMxIW2yUEt4qm1zzt1hYWGB2dpbk5GTKysro6OjYlcVRbW0tVlZW+Pv77/ixN8Lc3Bx5eXn4+fltmke6Efz8/BBFcSk7vBPo6emhoKCAoKAgoqOjd12YdTvw8fFhZGRkRVY6MzOT4ODgWEEQkjY6hiAILwH5QKggCD2CINwMPAScLQhCM3D2if8/4/GJCqxEUTy+KLVwyna/zUgtCIKgsrKy+updd921bIQ1Go00NzefVkG6zUIQBAICAoiPj6e6unpV0qm5WBwMdpKkuugOr1arT4vWlVQqJTk5maamph31ZJyeniY3Nxc7OzuSkpJwdXXFycmJ5uZm8w40OAh3320KqH7xC7joIhN/6m9/g5gYQkJCaG5u3hEivpu3Bx9o6jjwfjTWZVY4pVjj+3k1EvnHQYpEIuHiS87lzu+fw0WXHiEm6Eqm5ww8+8EI+Y2zJARaIRVEPmyBH77xTf7wi4eJkHvjKVfz/lQVOnFjux+ZTLbhfTA928+kpT3CgjW+/r7Y2lij6dVhmBPROW5d8XqzxPX19re0tFw3sBMEAVd1JBkxd3Io7ru4qiNp6Xmfd4ruo6zxOSamexkZGcHV1RXXTFt8rnBA02ekyelWdMeywMrKxLv61rfWNW4GUyn64YcfxtHRkSNHjnDs2DHspFbc5HQUtdSWl6YLGL40E/3gINM5OQAo5RLOirGje0RLdedKvpsoilRUVBAVFYWjo+NSd3JpaemOPr+tra0sLCwQHh6+Y8fcLKampigoKCAqKmrbZfuTIQgCMTExtLe3b7s7WqvVUlJSwtDQEBkZGTg7O2+802nGelp8jzzyiKOrq+vjwgarIlEUvyCKorsoivITVaqnRFEcFUXxqCiKwSf++4kw2P1EBVbbhYuLy4/vv/9+1amlrs7OTtzc3HbUr223YWtrS3p6Okajkby8vI9Nd83E9PQ0bW1tG+rpbBUBAQFL3Y3m+sVtF3K5nOTkZCorK7f8/ZyM7u5uSktLiY2Nxd/ff2mSDQkJYXBwkMnJyQ2OAPT1mWxm/P1NquiXXw51dSa5hMjIpbcplUpcXFxWdPWZC61Rz79nKoh/JwKXVgc8zrPH8wIVgsR07VqtlvLycvQGLVGpCxw9P5Lk8FvoHTPyp2ND9I3puCLVgUuSHfCzm0bpdYT42Fj+9O7vaT7exrn2cUwZ58if2diSZzME9vHpTkYVKt546AGmukwNv9Mt8yCAXr114dztZqwW+VWbhcrWh6Twmzk76Uf4ux+gd7iM4+UPYrCsQG8wfQ6HWCsCrnVCN22gqdSPubcK4PbbTfdFcrIp0F4DDQ0NHD58mNzcXEJCQrjooot49dVXsZEqudH5CC5yFf+0aqfnYCTTH32E7oRjwL4AKzzUct6pnEKrXx60t7e3Y2NjszSRS6VS9u3bh5ubG7m5uTuSIe/t7WVwcJC4uLg9p1yMjIwsdR/uhom0TCYjLi6OsrKyLWfph4aGyM3NxcPDg/j4+G2Xr/cSLi4uzM3NrZBfiImJITU11U8ikZx9mi5tz/H/TWAlCIKHjY3NVTfeeOOyHm29Xk9HR8cKwb9PAhZJp5GRkZSUlNDe3m5W2t5gMFBWVkZcXNyudkF6eHgQHR1NQUHBnnsiWlpakpCQQElJyZY7dxbte4aGhkhPT19RDlo0aq6oqFh7QO3pga99DQICTB5+n/88NDSYOv/WMLUNCgqira1ty4O01qjnr/1Z+L7mhtOgHYoDWpzTPqYW6nQ6rrzySjIyMng/949MzfaREHojtT1Knnl/BJlU4JaznYn1M2V64v1kWMjg8jt+ydT8JD954EF8Zc6EKT3Jnq5j1rD+97sZAvvYVAfNHRoqP/wn+llTMDDdsoCVhxxRvvXs3dzc3LYyVqOjo1uajK0tnYgJ+jzn7v8J1pIYZnVtfFD6IINjJvV6mwAFQTc7I0gEWl6aY+obv4E334ShIUhMNAVZp2Qtp6ammJ+fx9nZGVdXV44fP85FF120JBFjJVFwg9NhPC0ceSvMSHOoAxOvv45oNCIRTPILUxoDOfUfLzZmZmbo7u5eVfDSy8uLxMREqqqqaG1t3XJpcGRkhNbWVpKSkvacfN3T00NdXR0pKSm7SvdY9DesXicoXg16vZ7Kykra2tpITU3d0WzaXkEQBMLDw1dtHPrNb37j4Ozs/KggCP9fxBz/X3xIAG9v70e/+93vqk+tU7e1teHj4/OJWhmcCgcHBzIyMpbsUzabGaqpqcHX13dP/L/UajWJiYmUlZUxfIoZ7W7Dzs6OyMhIiouL0es3LlmdjKmpKXJzc1Gr1euuIG1tbfHy8lqZCu/qgq98BQID4U9/gi9+ERobTWKRwcHrntvCwgJPT086OjrMumYwBVUv9mfj+5objkN2eF1uz6BF19KkqNfrufrqq3nttdf4zg9uZY5GAj0vIK/Zg/+UTBLgpuDL57rg5vDx5/VwUhGsHGXBOoKLzr2IV/L+Ss4/szjbLhadaOD4dO2617SZwKpN00dHvunzHsw8gH7OiKZHi+0W5BVOxnZLgRMTE9viHxoNMpRiJAfjvoNcZkV+zSNUtryC3qDF0lVO8C3OWKhltP91lFG3g6Zs1fnnm8qCZ58NJ2Uu6+vrCQ8PX8r42Nvb869//YvY2FgA3n77bRSCnOscD+Fn4cIHGc5UWk8zW1QEgK+zgigfS3Lqp5mY1WM0GikvL1/XYNnGxob09HQ0Gg1FRUVmlwanpqaoqakhKSlpT8daURRpaWmhu7ub1NTUPdHJ8vX1Ra/Xb1o8dGxsjJycHOzt7dm/f/9p0/LaCSx2d55Kv/D29ubIkSOeVlZWV52O69pr/H8RWAmCEGJvb5+ZkpIiycrKYmBgAFEU0Wq19Pb24ufnd7ovcduQyWRER0cTEBBAQUHBusrgYErJa7XaPXWPt7W1JSUlhfr6+j1XLHZ2dsbf35+SkpJN85YGBgaWMnq+vr4bli4CAgKYnJw0SWK0t5u8+4KC4M9/NmlQNTeb/jYjOxoQEEBXV5dZAeFiUOX9uiuOQ3b4ft4Rp1hbrK2tmZiYwGAwcN111/H3v/+dn/z0XuIOGLCxTiSnOZGKdg2Homy5JtMRy5P897S9vehfeYXksn+jEAyc/aUHifSJpCtnGEeJLfFWgRTPNjOqX5tfslEp0GDU0a+U013YiMrZm6hQX2ZaF0AE26DtlenXUl3f7L5KpXJbWZbu7m68vb1R2XhzKP67BHoepb3vI46X/ZTx6Q7kdlKCbnLCxl9Bz2sTDFQrEP/5T9P9UlhoIra//PLShLWWPMGxY8e44IILuOWWW5AaBb7odJAgpTtZB93J7SlCf6Lz8Jx9JnHSdyumaG5uxsXFZcPAUSqVEh0djbe3N7m5uZsur8/NzVFWVkZ8fPyeKoSLorjkI7p///49C+gEQSA2NpaWlpZ1vyOj0Uh9fT11dXUkJSXh5+d3xnWkbwWLWStRFDEYDLS2tpKdnc1dd91laWtr+3NBED65WYxN4v+LwMrNze2xRx55RB0dHU1ycvKSmGNlZSVBQUFndLeFuXBxcSEjI4OBgQFKSkpWNQyenZ2lubmZffv27fmDrFQqSU1Npbu7m5aWlj2VY/Dy8sLR0ZHKysp1zyuKIk1NTbS1tZGWlrahvcUiBEEgztcX7Y03IoaEwF/+ArfcYjJKfvxxE1HdTMhkMnx9fTetC3ZyUOU0aAqqVJGmyWxR0+rpp5/mpZde4sGfPkDiESMafQTFHecxPmPgmkw1R6LtkJy4L0S9nsl332X4yScxLixgdLAlZrCUYa2apx5/jij7VNoLazlsF4VMkPLe5NpGCBtlrCame5iwcqC7rBbv0GSc7GRMt8wjVQpmq6yfClEUtxwYmcuvWu3cvb29S3ZIUomc6MArSI++E4NBS1b5r2jofAtBIRLwRUcc4qwYPD5N9+uTiDfcBJWVpnLxF76A/uqrCV8nMD/nnHO47777eOqpp/jsZz+Lfl7H1Y4HCJW6kpvqzPuV/0EURVTWMjLCbanumqOhe4rgDbKnJ8PDw4O4uLglgvV60Ol0FBcXEx0dvennaCdgMBgoKSlZ4j3tdelRLpcTGxu7Jt9qamqKnJwcZDIZ6enpu24ZtJews7PD0tKS6upqsrKyMBgMHDhwgOTkZG666SYHlUr11dN9jbuNT31gJQhCYmBg4L6DBw8CplXzvn37CAsLY3h4mO7ubsY3oR/zSYJcLichIQEPDw9yc3OXDX6LonixsbGnrfwpl8vZv38/09PT1NTU7GlwtRhINzauTrbW6/WUlpaysLBASkrK5p3iRRFefRXL+Hjc336bkSuugLY2ePRR2Ga3pZ+fH/39/asGySdDa9Tz0hpBFZh0t8bGxrj++ut5/fXXyLzAno6RSOoGLsLOUspt57oQ6vnx+7W9vQz98Y/MZGdjtW8frl/9KoazziJSOoDSME+1Qc2EtJs//PQZLAwi6TZh1M5307WweoPuRhmrxsEqpmZ02No5EhabilwqMNU8j02gEkG69QWAXq/f1uLpVP0qczE+Po6tre2K583ZIZTDiffi6ZJAQ+d/yK74NbPaYbwvVeF62Jbxcg1tL4xi8PSH7Gxm774bl2PHsPvxj9c8lyAIPPDAAzz88MO88cYbnHfeecxMTnOV6yHCNDbkBst4p/ldRFEkNcQSpVRH7YQnAxPmlcjt7e1JTU2lubl5zQWS0WikuLiYoKCgXSGLrwWtVktBQQHOzs7LSqZ7DQcHBzw9Pamrq1vaJooira2tS6XX4ODgT0WWahGLi4iJiQn6+vpIS0sjJCRkicP7ve99z9rS0vIeQRA+PZHkKvjUB1Zubm5/fPTRR1c81d3d3cTHxxMZGUljYyNFRUV7TqzebXh4eJCamkpbWxtVVVXo9XoaGxvx8PA47UJzi4RvuVxOcXHxnmldCYJAdHQ0U1NTdHYu93mbm5sjPz8fZ2dnoqOjN7/K7e2Fyy4zEdK9vKC4mI5vfYv+HVolSyQSAgIC1pV0WAyqvFYJqkRR5MUXXyQyMhKpVMrQ0BC+4VIK26LonTpItK8Vt5zjjKOtafBbylI98QTGhQUcv/hFHC69FImlJU5ubswkxRM320DbBORr8vnDm7/l1//3E9JswrCRKDk2tbqlkFQqXbcM26QdxFplzQ8e/YgLLr+O+SE9+mnjaS0Dwvb5VV1dXWtKmVjIrEgMu5HEsJuYmRvkw9Kf0tGfg+shW7wvUzHTvkDLU8NoZ6Hs4ovRfvWr8Ic/bKjWfscdd/Diiy9SWFhIXl4eUkHClQHnE96jJ9d6lGMjxTQ31XNRtIjSQsKzH4zQPbJ+4H4qFAoFqampzM7OUl5evuwZXhQAdXV13VMitkajIT8/n8DAwDOC4hEQEIBGo2FwcBCNRkNeXh7z8/NkZGTsCbd1ryCKIoODg2RnZzM6OkpaWhpeXl4rMpq2trZ8+9vfdnBycvreabrUPcGnOrASBCE5KirKf5HUuYipqSk0Gg2urq7Y29uTkpJCYGAg1dXVlJWVbdp645MApVK55NZ+/PhxhoaGzpgOyEXtExcXF/Lz8zfMyOzkeRMSEuju7mZwcBAwZRUKCgqIiIjYPO/MaIQnnoCICDh2zKRHVViIEBdHTEwMDQ0NLCws7Mg1e3t7Mzw8vGpn44qg6nOO2EcoEUUjVVWVHDp8iGuuuQZra2ssFFIqWsr4T4UPU/PBnBdnz2dTHbCQmYYCbU/Px1mquDhc77gD5UmG5CqVirG5OTIvikdpmEMVfpAo7xh+9+ifmRzr44hdNN3aEernV+fQSSSSVYNoURTps5Kjmp5hbBZc7OVMN5s+q23Q9si82wms5ufnsbCw2HIpSa/XMz4+vmHGy8slkSMJ96G2C6Cy5SUKah/DKlJPwBcd0U4YaPzTIHaTTkh/+ms4cAC+9CXYQOn7qquuoq2tjQsuuAAAnU7PFQHnEVE/QZ62lXJpD9Fhftx01AlLhYTnPhyhc9i8+1UikRAbG4uDgwP5+flL93t9fT0KhWJPx5rJyUkKCwuJiYnBzW1T7ma7jkV9q4qKCgoLC5e6uD9N9JPR0VHy8vLo7e0lMTGRmJgYlEolISEhtLS0rHjev/KVrygsLCxuOeH5+6nEpzqwcnd3/9XPfvazFdmqU7tqwFQmWYyyS0pKqKqq2hNjzb3AoiWORCJBEAQaGxt3RHhyp+Dn50dQUBB5eXl7FtQuCojW19fT2tpKVVUV+/fv33zJoqkJjhyB226DhARTF9fdd8OJlLdCoSA8PHyZUfN2IAgCLp5S3iv+IW/n38Nb+d/hzbxv83ret3m08Rm8XnfFcdCWoejXOD72bf710Ve45Mo44uLjKCsv5PZvHeT7v0qiYaKYkoEojKIV1x9WkxZmgyAIiDrdEpdKXFjA8dprTVmqUzqUpFIpcrkcqaMD6T4CfQpXvnHl7QxPDfODb95DnFUAzjI73p2sxLCK1c1a5cC+yR7mFUoe/ezPef/V3+JsJ2e6ZQGliwwL++1NQtvpCNyqzMIi+vv7cXd331S5x1KhIi36DqIDP8fwRBMflPyEaVUDgTc6oTfooMiOmt+M0H7pYxis7DFeegXiBjSGxWzRO++8Q1BQEDXd3ZwrCyOkcYI2u0n6deOorGXcfNQZG0spzx8fpX3I/MWAv78/oaGh5Ofn09DQgEajIfIkXbbdxtDQEOXl5SQlJZ32bPzJWFhYoLq6Gmtra+zs7Pa0JLrbmJiYoKCgYEkHMT4+ftlzZmFhgYeHx4quZqVSyR133GH7aeZafWoDK0EQIry9vcMTExOXbZ+YmEAUxVW7agRBwMXFhQMHDuDk5ERBQQF1dXV7lknZTTQ0NODr60tmZiYSiYTc3NxtKwTvJNzc3IiNjaWwsHBHrXrWw6KcQX19PTExMZubfHU6eOghU5dWRQU8+SS8/76p++8ULIrOblfkE8Bg0NI99l+MooiTfSSeTvG4uSTS65pMzIfpOA7aIT3YhmeCNyE+5xHudyFSozOf/8L5vJf1HHd9/fsIittoG/scdkod54XOEuBmojloe3oY+tOflrJULnfcgXIdMrOjo+OJdH8A1hI92pAEzok6n+dffo3aulzOsdvHqGGa0tmVhPu1COzlA6XMDI7TWteO3EKJo5WU2c6FbWerYHuB1XaJ64vdgJuFIEgI9DzM4fjvYqlUU1T3BKUDTyG5cJSgLznhkmGLztKFtov/iNDZwUzGlXT/a5TJ+jkMC2svlnx9fZFKpRw6dIhXGhpJ7bNEOafntd4PMYpG7Kyk3HTUCXsrKS8cH6V1wPxFpbOzM15eXrS0tBAQELBn3KGuri4aGxtJTU3FxsZm4x32CAMDA+Tl5eHj40N6ejp6vX4pQ/5JxszMDMXFxdTX1xMWFkZSUtKa2mCBgYF0dXWtyFrdcccdlgqF4huCIGyvK+UMxac2sHJ3d//5z372sxX59+bm5iUhvbUgCAIeHh5kZmZibW1Nbm4uTU1NZmsgnSkYGxtjYmJiabALCQkhJiaGsrKybQn+7TQcHBxITk6moqJiw26jnUBLSwujo6OkpqZSWVm5cdmurAz274fvfQ8uvNBkkPylL63r5xcVFUVbW9u2M3Etve8ztzBOuM9nkcxFEh74WWqtXAk9FoXToB1+n1NjdFTxlRt/i27Sh3C/i/jH397hpeffJC7ys1R2J1LR6UKMryW3nx/A7Pg4Rq2WyXfe2TBLdSqcnJwYHR1FLhPI3Kemz8aD28/5POkBh2koySdY4YafhQsfTlczb1yud7RWxqpZOsVQXgUAPmHJWI8ZEA1gG7x9N4TtlALHx8e3nAHRaDSIorilji9bK3cO7rubEO/zGJ2uoWv6BToN/0V9UELI7S74/f5iNN/6GbZ17yJ/7Bd0vDRG7UP9tD47wnDuNPPDumXPdWhoKHl5eXh4eHDXXXcxHBDCoU4ZAxZacurfN53TUsqNR51Q20j5a9Yozf3mBVdjY2P09vaSkZFBVVXVruvVLXbv9vf3k5qaesY4Z+h0OsrLy+nq6iItLQ03N7clCYa6uro9t/faKWg0GsrLy6moqMDf35/U1NQNuYcymQwPD48VHoq2trZcd911tjY2NtevsesnGp/KwEoQBD8HB4eUw4cPL9s+MzODVqtdUwPmVEgkkqUsj0wmIzs7e1tK2KcDBoOBqqoqYmNjl60gF53s5+fnyc/PP2N4ZdbW1qSmptLY2LijhqYn42R9m+TkZBwdHYmIiFhbQHRuDu65x2Qz0t9vMsz9xz/A3X3Dcy3qi5WXr07o3gzmFiZo6noHd6d9BPkmMbug4a+9x/F8zRXHQTtU50q47/F7iI+Pp7a2dkkjTCKRMKkx8PT7I9R0zXF2rB1XpDqgtJDhtLDAwKOPMpOTg1V8/IZZqpPh4OCw1EmbGGSDnaWEgdhEfnPV7/EZS6drMJ9z7fcxa1wgZ2a5CvNqGatx7RTjVnL682qxUFjiFxyNrkuHIBew9tn+ZLnVjNXCwoKp7LlFPsx6pPXNQCKRYUk0/k5X4+YYSVP3O7xTeB+17a9hVGqw/vm34OqrcX3/l4QEluOUYoN+xkDfsSkaHx6i4XeD9PxngqmmeYxaI46Ojvz0pz/Fw8ODz1x6Kd7BafiOinxkOUh/RSEANkopNxx1wslWzotZozT2bk5seGZmhsrKSpKTk1GpVEt6dX19fVv+/OvBaDRSVVXF3NwcSUlJu+ocYQ5GR0fJzc3F0dGRpKSkZcGeUqkkODiYmpqa03iF5mOxnFlSUoK7uzvp6elmdckGBATQ0dGxgn5y991321hbW98rCMKnh3B2Ap/KwMrNze3HP/nJT9SnpqKbm5vN0mtZhFQqJSAggAMHDqDX68nKyqKzs/OM4imthYaGBry9vVdNkUulUiIjIwkJCaGoqIju7u4zInu12G3U399PY2Pjjl6T0WikrKzMpDl1kr6Ni4sLPj4+lJaWLj/f8eOmst8vfmES+ayrgyuuMOucjo6OODg4bFqL6lTUd7yBKBqI8r+MBVFHh70en3974DhoR6HyGEmX7uOxxx7j9ttvp7GxkQsvvBCA7hEtjx8bYmRKzxcy1aQHyJktKmLo4YdxyM1FPz9vylJdcsmGWaqTIZVKkUqlpsBDKnAw0o4+uQM66wFGWuG+bz6Ak6Ak2tKX/JkGpgwfB1KrBVY1/aaJpqu8k4DwBNwcrZlumcfGz2KZUfRWYTAYtjTxbodfJYriEr9qq1i024oISSYp/EscSfgBbo7RNHe/yztF91Pb/hoLj/waISoKy29ej0foOKF3uBL+TVc8L1ahdJEzXq6h/YVRah7qp+7PPeyPSOftt9/mK1/5Ch7e3lwacgFGqYT/zlSiqagAwFoh5YYjTriq5LycM0Z9z/rB1fz8PCUlJcsEQBf16jo6Omhvb9/yd7DW91JcXIxSqSQmJmbPNapWg8FgoLa2lsbGRpKTk/Hx8Vm1FOrp6YlOp/tElAR1Oh319fXk5+fj4ODAgQMHlrJv5kAul+Pi4rJCtNrZ2ZnPfOYz9hYWFpfv5HWfCTj9d+QOQxAEVysrq/MuueSSZZ9tbm6O6enpbTmFy2QyQkJCSE9PZ3Z2lqysLPr6+s6IYGQ1nFwCXA9OTk6kp6czMjJCcXHxjnWybQcymYykpCTm5+epqqrakSB2UVfH3t6eyMjIFQOEj48PKpWKqqoqEyn41lvh8GFT99/775tUsLdYFgoLC6Ovr89sSY+J6S66BgsI8DjMbK+C/GdaiX0lBPWwLU7nK+id6yQ4OJiSkhIeeeSRpWxsRbuGZ94fRi4TuDFRilv5+wz86ldMvvkmgkKB6rLLaE9ORubvv6XPs8izAogLsEJlLaUsNJCC9vd54eV3eeyJ+znLLgajKPLB1Me+aauVAusWelDMz3DW0VSi0i/HXSZBO2rYto0NmH7zrXJ9tsOvGhkZwcHBYVuZlPb2dry9vZf0r+ysPUgKv4kjCffi7hhNc897vFP7EE2/uw3RYDAF/PPzWKhkOCVZ43+NI5HfdSfgOkfkoUakEwpGX9GjGvTgh/f9EIlEwtzIDOmKUNr9bSkvexfNCY87K4WEGw474e4g55WcMWq6Vg+uFoOcyMjIFfIBi3p1w8PD60qFmIOFhQXy8/Nxd3cnNDT0jNCAmpycJCcnZymYXC87utgleCaXBPV6Pc3NzeTk5GBpaUlmZiZeXl7b+q4DAwNpa2tbMVfee++99g4ODg8KZ8IPuYP41AVWLi4uP7jvvvtUp65iWltbCQwM3JEH0cLCgoiICFJSUhgZGSE7O5uhoaEzKsBaLAFuVl1dLpcTFxeHt7c3eXl5DAwM7MFVrg+JREJMTAyWlpZb8vk7GQaDgeLiYpydnQlahWi+iJCQEBQtLRhCQ+Gpp+Db3zZ1/B05suVzw3Kj5s0GiaIoUt38d1RDiQj/3U//c9NYDypp9ahjKL6eLmMz9913H9nZ2cTFxQFgNIocK5/knwXjeFrp+ezIe/DMo8yWlqKMiMD51ltxue02rOPicPPy2tD6aC0s8qwAZFKBg5G29MzC5V+4hkDnUH75k2cxTI2w3yaYck07g7oJwHSfnfw7zhrm6bPS46AZ4+4f3Et4+udxPtFTYbdN/SrYPr9qs7SBU7HdMqBOp6Onpwf/VQJfO2t3EsNv4mjifbg7xVInq6P4e5lQVob+9ltMYrUnIJELSNwNDLq2Evo1V+xClQy8N0Xzn4cZah0lOTmZp77xK5wEG3IzPRh6/Z/M1Zo8H5UWEq477ISXkwWv5o1R1bE802g0GikpKcHf33/NBatUKiUxMZHJyUmampq2/H2AyTEiPz+f0NDQbX23O4VFjldlZSVxcXGbnl8WS4LmGjXvNoxGI+3t7WRnZyORSMjMzMTPz29HMoJKpRKVSrUiU+fj40NmZqaTRCI5a9snOYPwqQqsBEGwt7CwuOqaa65ZtkzUarWMjIzsuFDdYio6ISGBnp4e8vLyliab042Wlha8vLzMJs66u7uTlpZGV1cXFRUVp52wv0i2d3d3X6aTYw4WgyoXF5cNs3cCEPrYY4haLQOvvw6//CVsw7z3ZNjZ2eHu7r6m6vuya5430vJOI1Zvn49D1blMLGiozmxj7EgHt977Bb753W8glUqZmJhYGvjmtUb++uEQuQ0zRM02cXbxM8jHBrE76yzcvv1t1JdfjoWX19I5fHx8tuzZ6ODgsMxodZ+/FQ42UkpUNnzrvB/QPzDGD++9lQM2ESgEGe9MViy9VxCEpeCyfrQZURDQtbQyM2vKBloNG7BwkGLhuH3ezFYDK61Wu1TyNBc6nY7p6elttf23tLTg7++/7vltrdxIDLuRo4n3I73kchqvS0D27Av0/PR25rWTgGnyr6ioMGkL2Vvgd5Ujvp9Xox03MPDCPDd95su8/NLLNP3ufWYsJZQd8mfs1VeZqzdx45RyCdcedMTX2YJ/FIxT3ja7dNzKykocHR3xOumeWg0SiYT4+Himp6c3de+vhvHxcYqKiti3bx8uLi5bOsZOYnZ2ltzcXAwGAxkZGWbb9SyWBEdGVncp2EuIokh3dzdZWVlotVoyMjIIDAzcca2toKCgVVX6H3jgAQcXF5df7ujJTjM+VYGVWq3+5re//W27U60j2tra8Pf337W0sbW1NfHx8URHR9Pa2kpBQQGTk5O7cq7NYHZ2loGBgQ2DiLWgUChISkpCrVaTk5NzRgSLPj4+Szo5s7Ozm95vMahyc3NbdfW/Am+/jfDBB0h++EOa7e13vDsxKCiIsbGxFe7vi9BO6un77yR1vxpAk2uLzm6O4vPryf9CLR72cM2Fn8XKyoo33niDyMhIGhoaEEWRgeYe/vSPVloHtRzoz+KIrBPnL1yJ6113YZuZiXSVANvS0hKJRLJpM92TIZPJkEgkS1IkUonA4Sg7eqb1ZFx+IemBh/jLc1k0vvcKmbaRNC/00zpvyoIqlcoljbjaqTaU8ws89eP/cvVnr0AQQezTYxuk3JHndavE9e3wq/r6+vDw8Njy9S8sLDA4OLjprIytlSsJYTfg+cgbTGZE4f6jJyl69laqW/9OfWMFarV6WeZNFWVJ6B0u2IVZ8lnnm7jywHU8+svfM/q3air95UyEeTH2t78xfyLDpJBL+OJBR/xdFLxWOEFp6yyNjY1IpdJ1s78nYzG4mpmZMTu4GhgYoLKykv37929LAX8nIIoiHR0dFBcXExERQXh4+JYyOoIgEBUVRW1t7Wnj6i7yALOyspiamiItLY3Q0NBdszqztrbG0tJyxXwSFhZGVFSUlyAI+3flxKcBn5rAShAESwsLi9tuueWWZfUDvV5Pf3+/WVoyW4WdnR3JycmEhoZSV1dHSUnJliat7aKmpobIyMhtpXAFQcDHx4fk5GQaGhqora097d2QLi4uxMXFUVRUtCl/x8VShaur6+bsLfR6+M53ICgI6Ve/SnJyMnV1dTsaJAuCwL59+5Yshhah6dPS+fcx6n87yHDBDIL3OA2Zr3Ls8iY0AfPs73Xhc+ddirW1NR9++CGBgYHY2NjgoNNR9PgrPFW4gMYg4QrrVg5dexZON9yAZXg4wgarTm9v7y3rbJ3MswKI9rXE0VZGrkTLt86/nwsSLqBlKofYYSkqqTXvTFVgFMUlntWCUUeHxSx240M01Q8QHJGIyzyIOnHbNjaL2GrGajv8KnO1q05FU1MTQUFBZj+/NrYe2L92HMHdk5T/e4+e2rdpHnoO/4CVGSW5jRS/K9X4XenI9877CRlBh3n8279gIK+Z7EOeSF1cGH35ZeZbWgCwkEm45qAjQe4KXi+aoLZHT3R0tFnB42LDyPT09KY5V52dnbS0tJCWlrZlLbKdwvz8PIWFhUxNTZGRkbHlMvEirK2tcXV13XFy/2YwPDxMTk4OQ0NDJCcnExkZuXlf1G0gODh41d/+zjvvdJTL5ccEQagXBKFWEIQ7AQRB+D9BEHoFQag48e+CxX0EQfieIAgtgiA0CoJw7knbEwRBqD7x2h8W+VuCICgEQXjlxPZCQRD8dutzfmoCKzs7u1u//OUv25768HV0dODj47OnnSMODg6kpqbi6+tLRUUFFRUV65rP7iQGBweRSqXbMo09GVZWVqSlpaFUKsnJyTmtmTgwyUTs37+fqqqqdXlgi0GVk5PT5jJVAM8+C7W18LOfgYUFCoWCxMTEHbc5sra2xt/fn9qaWqYa52l9ZpjmPw0z1TiPc4oNAV+1onjfa9SFueAmd+Bmp7N5/olnsLa25vjx40s2IfrJSYZqR3jLLh1bpZTbLnAn+pJDyM1o0HB3d2dgYGBL/MCTeVawmLWypW/WQOChGH5w8A9Y27jRlP0MhyUB9OvGqZ7rWOoMbJrpxiAVGK6sYWFeh3doMr5aASRgE7AzgdVWM1ZjY2Nbmjinp6eRyWRb5nVpNBrGx8fx9PTc0v44OiL512vIx2bZ/39FCAsa2vo+WPPtqihLIu/04I/3PsMXkm7ihu7PMzOspf3KA8idnBh98UUW2toAkEsFjobqcVTMUT3qQJeZ3oLwceZqYmJi3S5ZURRpaGhgcHCQ1NTUPZn010NfXx/5+fkEBAQQExOzY/IOwcHBdHd375nLx9jYGHl5eXR1dREXF0dsbOy2fDTNhZ2dHRKJZIUIdEJCAiEhISJwBZACfFUQhIgTL/9WFMV9J/69BSYBcOAqIBI4D3jsJNmGPwK3AsEn/p13YvvNwLgoikHAb4Gf79LH/HQEVoIgSCwtLb/1ta99bdkIajAY6O7u3rz32w7D2dmZ9PR03NzcKCoqoqamZlc77gwGA/X19TtuJSEIAoGBgcTFxVFZWUlzc/NpJepbWVmRmppKa2vrCrsEMA3KVVVV2Nvbb96rbHYW7r8fUlOXySnY2NgQGxtLcXHxjirwu9l5YPzAlva/jrIwqsf9HDsivuWGx3n2vD39Fu1OAfjKHbne8TDWUgWPPvro0sAOJqPkD/9ZyHGndFwsF7gwQYqj2vwAQiqVolartyTmeCrPCiDKxxJnOxl5Uh2CXMLAhx789O1jOL56DHepPe9NVWFhqUSj0VA71oRiQU9HqSkr4uyfiPM0WPtYIFXszNC0lcBKp9MhkUi2NHl2d3dvi1jd2NhISEjI9sqg8fH0/vCHOFTUcuj7x+ls/C/z2rW7UWXWUqKu9+Xhp36Prc6etJfCqfx3G7KrP4dMrWb0r39loaOD8fFxmhobuOEcL1RWUl7JGWNy1nwOpkQiISEhgeHh4VWzpUajkYqKCnQ6HUlJSafVV0+n01FaWkpfXx/p6ek7zu+SSqWEhoZSe6JhYLcwNTVFYWEhzc3NREZGkpCQcNpU6lfLWrm7u/OrX/1K5e7ufr8oitNAPbDe6uIS4GVRFBdEUWwHWoBkQRDcATtRFPNF0yT1HHDpSfv85cTffweO7lY34qcisAKOHj161ObUFWZPTw8eHh6nVTxOEATc3NzIzMxEpVIteWntRqvtImF9t1YgdnZ2ZGRkoNfrycvLM4vrtNOwsLAgJSWFoaEh6uvrlwV6DQ0NSCSSDRX2l+E3vzGJf/7qVyuU1NVqNaGhoRQXF+9IOXSqaZ7mPw0jm1MyEzZA4FfVuGTYIlEIvDGcRY1CgrdBQnSvI2cfOsrg4CByuXwpiyGKIm+/XkG2MpJQex03nOtFd2frlrkaPj4+WxJjXeRinHwvSyQCh6Pt6JszIIZaUF3Wwz9fKeefffmkFA4zadDQKB9idk5DqzCO68gU9VX9BAYFIpWoUU6LO2JjswidTmc2Z2R0dHRL2Sqj0cjg4CCurq5m7wumbNfs7OyW91/E6OgonZmZ8Ne/YlvRRurX/k5b+Ssb7qeKtCT0q858+99f4jffuYeyJ/uwufBapPb2jLzwAg1ZWSQlJWFvo+TqTEd0epGXcsbQ6c1fZEkkEhITE+no6FjWKabX6yksLMTW1paoqKjTKqewWC5zc3MjMTFx17Jmbm5u6HS6XeGyzs7OUlpaSk1NDcHBwezfv3+FLMZeQ61Wo9VqV9BkzjnnHCwsLI4KghADxAGFJ166QxCEKkEQnhYEYbEjxBM4OSrvObHN88Tfp25fto8oinpgEtgV88ZPRWDl7u7+o3vuuWdZC84iyXDTZaBdhiAIeHl5kZmZuVRWW835e6vQaDTbIqxvFhKJhPDwcMLDwykuLqazs/O0Za+kUilJSUno9XrKy8sxGo20tbUxOztrHv9jcNAkAHr55ZCWtupb3Nzc8PT0pKysbMufVzSK9L8/RfsLo8jtZYR82QX/Q+5U11ZjEI28Nl5IibYX1+lhoga8OPesc+jq6lpWhjSKIm8ca6FA606kxThXneeLtZUSNze3LSvVq1QqZmdnt5SRc3R0XJG1ivBW4qqSkSfTcU3KTXg4efD7V46jbKjHf1JKkb6NNoZZkIGTbo4v3pzJjx78DS6LMgs7YGMDLP1O5k7Oo6OjWyqlDw8P4+jouOUMS2NjI2FhYdsKJnQ6HdXV1cTFxSF84QsI//43tr1T+FxxN3ONFRvuL7eR8cBv76dttIUfPHEH9U+Powv6PFpBim97O1YnhGRd7OVckeZA/5iO14vGt/RMyGSyJSP0sbEx5ufnycvLw9vbm6CgoNMWVBkMBqqrq2lpaSElJWXrZdlNQhAEoqOjqamp2TEi+9zcHJWVlZSVleHt7U1qauq2OWE7iaCgINpOlJgXIZFIuO2222wFQXgLuEsUxSlMZb1AYB/QD/z6xNtXuznEdbavt8+O48zwAdgGBEEI2LdvX1BMTMyy7SMjI9jZ2Z322vypkEgk+Pn54e3tTXt7O1lZWfj7+2+bB1ZdXU1ERMSeccnUajUZGRnU1tYyMDBAbGwsSjPUu3cKi901ra2tfPTRR0uZLLMG5f/7P5ifN5krrwM/Pz/m5uaoqakhOjrarOvUzRjoenWcmfYF1PFWeF6oQiIX8MCDnoE+nu19j05hFPexTjx7Hbnw6ouxs7Pjww8/XFocGIwi//qon6pxK/bpO7jkc/uRSkyfMzAwkJycHLy9vc2e2AVBwNPTk97eXrMXIo6OjoyMjCzLskgEgSPRdryUPYY8wo47D93HPX+/nadGqrnumA0dnwukVj2KTGdEYRglMjIKnT4cXRcYLAwUNuTBKo1j09PTHD9+fNXrVyqVKBQKlErl0j8wZdWMRqNZz8Xo6Kh52c4T6Orq2pKzA5jM4XU63ba5kbW1tQQEBHxc/jzvPHRvvY7FZy6FzCPwQTZsQBU466yzePzJx/nSTTfzg4/u4uc8gnXQJVi0vsxsSQk2+03NW2GelhyJseP9qincHORkhK9uxLseFAoFycnJ5OfnAxATE7MtEeftYnx8nMrKSnx9ffc0Y3YykX3T9IVVoNVqaW5uZmRkhODgYGJiYs4IEdVT4eLiQn19/bKMsk6n491331VYW1vbzMzMvAYgiuJSOlMQhCeB/5z43x7g5A4RL6DvxHavVbafvE+PIAgywB5YvT17m9jzwOoEwawE6BVF8SJBEH6MqfZpBIaAG0RR3LTBlIuLy3e+//3vr0jntbW1ERYWtlOXveNYbFX29fWltbWVrKwsAgMDt6Rwu0hY3+sBSSaTERsby9DQ0JJw305rhW0GgiBgb29PR0cHer0enU63+eCioQGefBJuvx02MSmGhYVRXl5OS0vLplvNZzoX6PzbGIY5I96XqlDHfyx9MKAbJ99jgFH9NAHj/Wirurnha7/Azs6O48ePL3Uz6g0if8sepmFAJGmyivOvyUB6UolbLpcvBeubva6T4e3tTWFh4ZYCq9WEH8M8lbg7yMie0nJOxIX8NTCGp57+kAt/Fk9IwwSN4Sr8O2eorGmCBW/Ck5S4z4J9mCVxhw6u+gwcP36cQ4cOrdhuNBpZWFhgfn5+6d/4+DhTU1PMzs6SnZ2NKIrIZDLs7e2xt7dHpVJha2u74jyLZU1zy4darRaNRrNlOYCGhgbCw8O3tO8iBgYG0Gq1KzoSlYfOo/Hln+B73Q8RD2QgvPU2pKSse6ybb7yJqpY6/vDTX+PrHsgd8m9i5xPO1AcfYBUdjeRE4JYZYcPAuI53K6ZwtZcT7GH+4mp+fh5RFBEE4bTxfoxGI83NzQwPD5OYmHhariM4OJisrCw8PT3NXqTqdDra2tro6+sjMDCQiIiIMzKgWoQgCHh7e9PV1UVgYCCiKHLzzTcTExODr6+v+Nxzz50HvCUIgrsoiv0ndrsMWDRafAN4URCE3wDPA2cBnqIoRgmCMC0IwveBa4AI4M6T9rkeyAc+C3wg7lK55XRkrO7ERExbVFT7pSiK9wEIgvB14H7gy5s5kCAIVp6enpdddtlly5ajGo0GnU532mvJm4FcLicsLAx/f3+am5tpa2sjJCRk055Mi90zycnJe3C1q8PFxWXJCmZgYIDo6Ohd00JZDVNTU9TW1nLgwAGmp6cpKCggISEBW9tNrKDvucckAHr//Zs616JcQmFhIZaWluuWCURRZDh3hv73prBQSQm41gVLN/nSawWzTbwzWYFSkLFvbBjJRAuB8VeSktLOY489thRULeiMvJQ9StugjvTBPA5dvh/ZKp/N39+frKwsfH19zf7+FQoFCoWCqakps8QOF88zPz+PRqNhYmKCiYkJpqencZVYU2FwZ84LvnPkp+QqnmQmXMv+FpF+Dy3+E1r+8loNdZUf8eTTP0Bh0KIOtzZ7QpBIJFhaWq7gFvb09KBWq5eySDqdjsnJSSYmJmhqamJmZgapVLoUaKlUKjQazZZkFnp6ejYUylwLo6OjSCSSbWk0LSwsUF9fT1pa2qrfn+/RW8h5rIaMu99GefQo/OtfcM45ax5PFEVu/NwXGZwcQX1JMIZcI9PWGVh2NzB1/DiqC0xd74IgcFmKitFpPa/mjXHrOc442W3+3uvr66O5uZn09HQ0Gg3FxcWkpqbu6fgxPT1NRUUFLi4upKWlnTbvQalUSkhICI2NjcTGxm5qH4PBQEdHB11dXfj5+XHw4MEzwjtxM/Dx8SE3N5eAgAByc3N5/vnniY6ORqvVqgRBeFUQhM8BXxAEYR+mkl0HcBuAKIq1giD8DagD5JjiisW44XbgJUCBKVuVd2L7U8DzgiC0YMpUXbVbn21PAytBELyAC4EHgW8CnKijLsIaM2qelpaWV994443Wp5LT29vbzxhu1WahUCiIiopibm6OxsZGWlpaCAsL2zAL1d3djZOT0562zK4GCwsLEhMT6enpIScnh6ioqD3JoC0sLFBWVkZCQsJScBAfH09JSQkxMTHrT5JZWfDGG/Dgg2DGtS4Sb/Pz81EoFKuWbwxzRrpeG2eqfh77CCXelzogVZoGvBnDPP8aL6R5oQ9PoxSnrlzKc9o4cuBzWCu8eeutt5aOo1kw8sJHI/SOajnc9yFJ6cEo1ug6k0ql+Pv709rauqVs7SKJPSoqasP3iqLI2NgYAwMDaDQacnNzcXJywt7enoCAAOzs7BAEgZF3hymXGkh338f++N9TI/4cbZorn3ujjYn9DtRX95ORcQShT48I2AbuDL8KVmpYyeVynJyclv1eJwdbixkLCwsLLCwscHNz21xwjimw2r/ffH3DxYXRqVQGc49RWVlJeHg4CsXq359SYY9b4mf48PcC59xfhPSii+CFF+Dzn1/1/YtdWy89/AzNC/1Uj3Uzc2yA/Z9JhaICrJOSlmQ9LGQSrs5U86djw7yYZQqulBYbT+5tbW309/eTlpaGXC7H0tKSgIAAysrKSE5O3vWMiyiKtLe3093dTWxs7GkXHwXw8PCgra2NmZmZdbNmRqOR7u5u2tra8PLy4sCBA6e1SWsrkMvlODg4MDw8TEZGxjKeXkJCwmxZWVmDKIrXrrW/KIoPYoolOKFJ9eUT20swySwgCMLxk94/D3xuFz7KCux1aPs74DuYyn5LEAThQUEQujGl7jaXOgDs7e2/ffvtty+TlDYYDAwNDW3LVf50wtLSkn379hEXF0dnZyd5eXlrimEaDAZaW1u3zOvYDXh5eZGSkkJLSwvV1dW7Kiq6qFUVHh6+bAK0s7MjJSWFmpoa+vrWqCobjSYfQE9PuOsus88tl8tJTk6mpqZmhbHyXL+WpseHmGqcx+M8e3yvVC8FVS3z/Tw29DZtC/0ETgyganiPv/6hjJ9893XK8gfo7u5metrE4p6eM/DM+8P0j2k5u+cdYn2UWG8wefv4+DAwMLAlWQ9XV1eGh4fXJNDq9Xr6+vooKyvj+PHjdHd34+joSFRUFO7u7sTGxuLn54dKpUIikSCc4FoNGIwY/OVoquTU5ML37v8JMxcdpmV2iKGBaQ4cOITNqBGdSoLMeuda6zcjtbAYbAUFBZGQkIC1tTXJyclYWFhQV1fH8ePHqampYWRkZM3vZXJyconjZS6GhoawtLTcdAC3Gnp6epDL5bi5ua37vhDvczA4O1D+xC2mUuBVV8Gf/rTifd3d3YyNjS3xc0KUHtS2f8BNz17O88dq6fG1Y/K//122j8paxpUZasZm9Pw9fwyjce31sSiK1NbWMjY2RkpKyrLslJeXF7a2tjQ0NJj5LZiHubk58vPz0Wg0ZGRknBFBFZgygGFhYWt+flEU6e3tJSsra+nag4ODP3FB1SL8/f1XkNgBvvOd7zi6uLh84zRc0o5gzwIrQRAuAoZEUSw99TVRFH8giqI38Ffgjk0eb19kZKTjqZye3t5e3N3dPzHp0LVgY2NDYmIikZGRNDU1UVRUtGIC7+jowNPT84wj6FtaWpKSkoKNjQ3Z2dkrxOB2CtXV1bi6uq7anm5paUlaWhrt7e2rPri8+ioUF8NPfrJlL0ClUklCQgKlpaXMzc0hiiKjpbM0PzmMqBcJuskJ5zQbBEFALxo4NlnOc6PHEXQaQrpLkDR38OC3c/jX3z7innvu4c477yQ2NpaKigpGp7U89d4wYzN6Lhh4j2BLDapLLtlwFS+RSAgKCtq0svWp+zo7Oy9rf5+bm6O9vZ38/Hxyc3OZnJzE39+fQ4cOsW/fPtzc3HBxcVmzVTzQTYGPkwUFSj2iTmSwUsEbf6sgq+gliotLAIiJTsFBA1LvnS3/mKu6rtfrMRqN2NjY4Ovry/79+zlw4ADOzs709vby0UcfUVpaSm9v7zKJia0aLouiuNQJuFVoNBpaW1s3lWW0kNsQ6HmEHm0TE3//M1x4oYlb+OCDS8bNQ0NDdHR0kJiYuGwM/fbX7yQhKplfPPE9np2eoVw2zPwp95i/i4ILEuxp6lvg/erVdbOMRiNlZWWASRRyNS5keHg4U1NTWzYIXw+LvngFBQWEhIQQFRV1WnWyVoOzszM6nW7ZuCmKIoODg2RnZy8FpOHh4XtaMt0N2NnZYTAYVggwX3bZZRKpVPp5QRDOrMltk9jL6CMd+IwgCB3Ay8ARQRBeOOU9L2JSXt0Q7u7u93znO99ZUYPp6uo6bYKgu4FFpfGgoCCqq6spLS1ldnYWnU5HV1fXrssrbBWCIODv709iYiLV1dU0NjbuqCdWe3s7BoNh3Q4auVxOSkoKY2Nj1NbWfpxqXliA730PYmLg2jUzzZuCra0tMTExFOUX0/nPMXpen8DaV0HI7S5Y+5gyGKP6af48/C65Mw24TA0R3FWMpsWBr93wF7q7+nnjjTd46KGHkMlkqFQqFLauPHFskLkFI5dM5eA524v6qquQbDKA9vT0ZHR0dEtq/z4+PnR0dNDW1kZWVhbl5eWIokhsbCwHDx4kPDwcBweHZQGehYUFRqNxVcNuQRA4EmPHgCii95XzxeCv4OTswB9+9SL1tW1YWVviIg1GAtiF7GxX6fz8vFkk4NXU1qVSKa6ursTGxnLo0CECAwOZnp4mPz+f/Px8enp6GB4e3pJwZF9fHyqVastWLYsGy+ZwGoO8jiKXWVM3+A7885+m+//ee+Fb32JyfJy6ujqSk5NXZECsrKw49v5bBLuF8sy3f8ZfFZO83Z2F4ZTfPCnImsRAK7LrZqjuXD5Z6nQ6CgoKUKlUREZGrrlIEASB+Ph4WlpadnRRptVqKSkpWSo97ZQ7xW4gPDyc+hNG2KOjo+Tm5tLX10diYiLR0dGnpQN7t+Dr60tnZ+eybRYWFlx11VWWcrn8stN0WdvCngVWoih+TxRFL1EU/TCRxj4QRfGLgiCcXMf6DLBhDlgQBFuZTHb0rLPOWrZ9ampqqVb/aYNarSYtLQ1vb2/KysrIzc3Fy8vrjE8B29jYkJ6eDkBubu6OeCeOjIzQ09NDbGzshhkcqVRKQkICAGVlZabS5GOPQXs7/PKXsAOrVUdHR1z7ApmonMPloA0B1zois5YiiiLls208NvgWQwsjBPTXEacTOCvh+6QlXE5cXBxlZWVcfPHFS8fqGlngvVYbDAYjl4gVOHbV4nDZZcjNmAQEQSA0NNQss1tRFBkZGaG5uZnR0VF0Oh0pKSmkpaUtb99fA2q1es2SdYCrAj8XCwot9SgFK7577f/RUDNAcLgLWfmvs9BpQCsBtx0MrLaiYbWRfpUgCKhUKsLCwsjMzCQ6Opre3t4l4rg59/ZiF9pWZB0W0dbWhr29vVlke7nMkmDvsxkar2NU02mycbrrLvjtb9FcfTWJJ7iKq8HB2YF/PvsGbrYevP6lhyn0lvBy+1voxI+DK0EQuCBBhY+zBa8VTtA3ZtJGm5ubIy8vDz8/v03JCcjlchITEykvL98Ru5fBwUFyc3Px9PQkPj7+jM/0qFQqRFHko48+oq2tjdjYWOLi4k67X+JuYNFW69SF9x133GHr5OT0vdN0WdvCmVAve0gQhBpBEKqAc/i4NXJN2NjYXH/rrbfanFru6+jo2JzZ7icUgiDg4uJCYmIiOp2Onp4eamtrd9RqZTcgkUgIDQ0lOjqa0tJS2tratiyyOTc3R3V1NYmJiZtO4QuCQGRkJA4ODpS8+y7ij39s6ohapyvKHEw1z7PQBIpYA32qFhBg3qjlb2M5/GuiEMXcODEDjUTKUsh6cxZrpTPh4eHLNKoAmvrm+csHo1hZSPiCVRP21QVYp6VhGRGxztlXh6urKzMzMxtO9nq9nvb2dj766CO6urrw9/cnIiICqVRqVol5Uc9qLRyJtmNAENF7yTjqcBnh4SE8/3ghwX5xCL16xmzBxnLnFglbVVw3J0ixsbFBFEXS0tJwcHCgurqavLw8+vv7N7y/u7u7cXFx2XLmYXp6mp6eni2VEQM8DqKQ21HX8QaiIKB96CE6r7sO9//+F5tf/WrdfUOP+PHMna/y26uf5EinjEbLGZ4ZfI9Zw8fBj0wqcFW6GiuFhJeyx+gfnqCgoICoqCiz5Fisra2JioqitLR0y9luvV5PZWUlHR0dpKamnhY5GHMxPT295PJgNBpJTEzcFgfvTIdUKsXFxWWF92tAQAC+vr6egiCErre/IAgvYZJQCBUEoUcQhJsFQbhMEIQeIBV4UxCEY7v2AVbBaQmsRFE8LoriRSf+vkIUxShRFGNEUbxYFMUNC+u2trZfu+WWW5alpfR6PaOjozvu5XQmorm5mYiICA4dOoStrS25ubk0NjauWoo5k6BSqcjIyGB2dpaCggKzS1VGo5HS0lJiYmK2lJUMCAgg4q23YGKC+QceMHv/1WBYMNLz7wkUTjJCL/FBqVSS1VDMw/2vUzvXjftoJ+figGJ0PxecfQMPPvjgqpyvynYNL2aN4mQr4YrpbJTF2RhCQujeYhPGRiRYjUZDTU0N2dnZ6PV60tLSiI+PR61W4+XlRW9vr1nBr6Oj47qWHH4uCgLdFBRZGRC0Eh66/WG+9tW7kWvskM2LzLnsLM/FXI9Ag8GAwWAwK5icn59fknXx8PAgNTWVmJgYhoeH+eijj2htbV3VuspgMNDW1rYlvTEwPQfl5eXs27dvS/wgmVRBiM+5jE62MDhWR3FJCYqHHoKbboIHHoDnnltzX0EqEP/5cOLUKcRyFOmDb9HQ3sQTw+8yrPuYV2VjKeULB9TMzhv4e84AiYmJW5KxcHZ2xtnZeUtk9rGxMXJyclCpVCQnJ5/x5TONRkN5eTmVlZX4+/tz4MAB1Go1/f39G+/8CYevr++qvq/f+ta31K6url9fb19RFL8giqK7KIryE1Wxp0RR/NeJvxWiKLqKonjubl37ajgTMlZmQRCEYG9vby+9Xr+s46y3txdPT88zWhRtJzA7O8vExAQeHh4IgoCPjw+ZmZnI5XKys7NpbW3d1U687UIqlRIdHU1QUBCFhYX09PRsvNMJNDQ04OLisqUBGoCxMWyffRbtZz5DvkazohlgKxj4YArdhAHvS1RIZAJuQe4ct2lmQTdDwvgAn/P5PP96oZ4LL/gMrq6ulJSUrCiF5DXM8I+CcXwcJFzU9jqSxhrsL7gAr6uvZkaj2ZJBMoCTk9OSnMAiZmZmKC4upqysDLVazcGDBwkODl4WUFhYWGBtbW0Wv0WhUHDqM3kqjkTb0S8V0bnLCJiN5vCBI0w2mYJrmc/OE9fNCazGxsZwcHDY+I0nobu7e4UYp42NDTExMcvK36dmlbfbdNLU1ISbm9u2dPr83DOwVDhQUvciDk4SXN3cTB2CR4/Cl74EqyjcL8IuVIm1jwWtOZP87oXX+cclDzA6MMSfh9+lfWFo6X3i3DDWsjksbRy2lXEJDg5mcnKSoaGhjd+MKfCsq6ujvr6epKQkfH19z+h5YX5+nurqakpKSvDw8CA9PX2pJB0aGkpTU9OO8lPPRCxKS5ycYV9YWCAiIkIilUq/IAjCJypW+URdLICTk9Ott956q3JycpKsrCyqqqqYmJjYcmfOJw1NTU2EhoYuGyikUikBAQEcOHAAg8FAVlYWnZ2dZ/TD6OzsTHp6OkNDQ5SUlGxYzhwaGmJycnJ70hJ/+ANMT6N44AESExMpKytbt3y1EWa7tYwUzOKYbI21r4LZ+VH+2vMPjIjEDBhIVH+er972PX70ox9x7bXXUlhYuKx0I4oi71RM8t/yScIcjZxT/jzSyVEcr70Wm5QUJBIJ+/bto6amZsum3WFhYdTX1zM3N0dFRQUVFRX4+/uTkZGBh4fHmt2zWzFmXo9nBeDtZEGwh4Jiaz0GjRGrATVjDRqmLMDBdWebfzQajVlZTXP9ARfb3tcSiJXL5QQGBnLw4MGlrHJzczMLCwvbajoZHx9fsivZDqQSOXayJAziJE2Dz/N+yQM09r/H7AtPQFAQXHaZyZVgFQiCgPs5dlgb7Xj2Ry8zPDHFPy99AMmMnudGPqRS005raytdXV2IUmvUttv7bQVBIC4ujtra2g35VlNTU+Tk5GBhYUFaWhrW1tbrvv90QqfTUV9fT0FBAWq1mgMHDuDq6rpsbFcqlUtdqZ92+Pr60tXVxcDAAEVFRRQWFqJQKDhw4IAAHDjd12cOPlGBlSAIglQq/cJVV10lWSyFubq6Ul9fv9SeuxX9nk8K5ubmmJ6eXrPcKZPJCAkJIT09ndnZWbKysswu6ewl5HI58fHxeHh4kJubu6zN/2TMz89TW1trMpbd6spzchJ+/3u49FKIicHW1paUlBTq6uq2NGgZ9SI9b4wjt5XgfpYdIxNN/KvhT4wobUix8OL8hOtpaWnlkksu4cknn+TZZ59dNsgbjCKvF02QUz/DPnsNB/KfQWapwPnWW1GeVCKytLQkODiYqqqqLX1sa2trZmZmyMvLw9XVddlqeD04OzszNjZmVvZzI54VwJEoO/rloHORImm1RttrZMAGnM1Q694MzC0FmsuvGh8fx9bWdkMe18lZZUEQ+PDDD7G1td2SHMwiX2hbz8EJtLS0oBB8OC/l5+wLvhqFhS31Hf/m3aZfUfSryzHIBMQLzoc1sqXWPgrsI5QEaOJ4/oGf09Ldwz+/8HNcddb8Y7yAuvkeEpOSmZ43Ym+1/TKvUqkkKipqTRN0URRpaWmhoqKCffv2nVYT542g1+tpamoiJycHKysrMjMz1622BAYGbouX+knA9PQ0Y2NjtLa2MjQ0RGhoKJmZmQQGBvLlL39Z5eHhsSkZpjMFn6jACkhOSUlRLk5QgiDg6uqKWq1e8kYqLCykqKho1S6DTzoW/ek2GjAsLCyIiIggJSWF0dFRsrOzGRwcPGMfzEV+SkdHB5WVlcu4YqIoUlZWRlRU1PY4Eo88AhMTptbyE1AqlaSmptLV1UVLS4tZhxvOnWF+UI/nRSq6xnLJqnmUDrU3zlIbIrQBvPrqqyQnJ+Pu7s6VV1657DfT6UVeyRmjrE1DqnKQ5ILnsfT1weXWW1ft/vPy8kIUxbXFTleBwWCgubmZ3NxcvL29USgUm7ZJAtOz5ebmZha/YyOeFYCnowVhnkpKbAwwL0EwwqA1ONvtbHerORpWBoMBnU5nlsCnuRlyqVSKj48PFhYWWFpakpWVRV9fn1nPZF1dHX5+ftvOwvT29jI8PMy+fftQWFjj557Bgdhvcnbyjwn3+wxTznKyf3IYY28302fvp6+7AKNxJX/T7Sw7jHqR/ZHX89i111JSXsHAsyXYGhQMu+iYmRcRRVDtkOirs7MzarV6hTelRqMhLy8PrVZLRkaGWZZMewmj0UhbWxvZ2dlIpVIyMzPx9fXdMMhWKpWoVKoV5O5POnQ6HR0dHWRnZ1NbW4ujoyMeHh54enouK3NnZmYCHBQE4cwmyZ2ET1Rg5ebm9tXbb7992bJSFEX6+/vx8vIiICCAzMxMQkNDlwiktbW1O8KlOd1YWFhgdHTULEV5pVJJTEwMiYmJ9Pb2kpeXt+HEd7qgVCpJTk5GpVKRk5PD2JjJdLypqQkHB4ft2ePMzMBvf2sSRDwhvbAIuVzO/v37mZqaorq6elMT3fywjsHjU9hHKumQvk5ly0uMu+9DK5WTMu/P2UfP4itf+Qqzs7NLAqKLJYw5rZHnjo/Q0DvPQUMjMeWvYbN/P47XXotknUAgJiaGxsbGDUshRqORzs5OsrKyEARh6XmwsrIym6vl7e1Nd3f3pt+vVCrR6XQbZrkOR9vSZwHzDmCUiEzagv0OKq6DeYHV+Pi4WfwqvV7P+Pi42TpIzc3NBAUFERkZSUpKCsPDw+Tk5GzqdxkaGkKj0Wxbo29kZITW1tYVAqAA1kpHQn3O42ji/ey7+rd0/+ZObKraEa/7Im/nfZeK5pcYnWxdekaUTnIcE6wZLZ3j8lvv5t1bb+WmqCiSHULp0A7TM23iy+xUYAUmztHIyAgjIyOIokhnZydFRUWEh4cTERFxRgpDi6JIV1cXWVlZ6HQ6MjIyCAwMNKvxIDg4mJaWljN2cbxZiKLI8PAwpaWl5ObmotPpSExMJCUlBQ8PD3x8fFbwbiUSCZ/73OcUEonkgtN02WbjzLsL14AgCHJBEM49evTosu2Tk5PY2NgsS8nb29sTHR3NwYMHcXBwoK6ujuzsbDo6OrbMVTndWPQ/3Ep628rKivj4eGJiYmhra6OgoGDX1NC3A0EQ8PX1JSkpibq6OsrLy5fSwtvCH/8Io6Nw332rviyRSIiLi0Mmk1FSUrJuYCAaRXremECQC/T6vUJ7fxZq76N0KZUEz6q57vzP0d/fz9tvv42TkxN2dnZERkZSVFTE2NQ8T783TPeIlnOmCglryUJ18cWoLrwQYYNB1sLCgsjISCoqKtYcXMfGxsjOzmZ2dpaMjAyCgoKWBu/Q0FAaGhrMGphtbGwwGo1mdW86ODhseG+5rMKntAABAABJREFUO1gQ4aMkxwXKA/Q42MuR7HDZRhTFTU+y5vKr+vv7cXd3N+tZnJ+fZ3h4eInsrlQql7SJOjs7KSwsXPN71mq11NbWsm/fvm2Vt6ampqipqSE5OXndEqYgCKhsffD76q8Rf/5zPI+3Ev+XeroHC8iu/DXvFv+Q+o5/MzM3hOshWwQptJZJCTt0CGlVFS6lpmC8ZtxENt+JUuDJ1xYfH09VVdXSOJaRkbFC2PVMwGKWOSsri+npadLS0ggNDd2ShpaVlRVWVlarLoy7u7s5fPgw4eHhREZG8vvf/x4wjQdnn302wcHBnH322cv4jz/72c8ICgoiNDSUY8c+ViIoLS1dai76+te/vjReLCwscOWVVxIUFMT+/ftX7eBbDxqNhoaGBo4fP05vby/+/v5LjTMnL4CcnJwYGxtbUW26+eab7dzd3TeUYjpT8IkJrICzL774YsWpgpjd3d1ruspLJBI8PDxISUkhKSkJnU5Hbm4upaWlDA0NfWKif51OR39//4oOJHNha2tLUlLSEqG5uLh4RwQ7dxrW1takpqYyNDSEXq/f3jVqNPCrX8HZZ8M6PnuCIBAeHo6zszMFBQVrkunHSjXMdmoZD/mAUW0DcSHXUWNthTCu4+dXfIuuri7efPNNUlNTl/ZxdnbG2imAx48NMjat4/z+dwkYa8TpuuuwTkra9EdxcXHB0tJyBancYDBQW1tLfX09iYmJRERErBi8ra2tUalUZrdue3l5mUVi3wzPCuBwlB2TEuiQy3e8DKjX683KBpjLr1qtG3AjNDY2EhISsiIwWrSuCggIoKCgwET4PmVcqq6uJjQ0dFul8Lm5OUpLS0lISDDrOJJv3w233Yb7n9/i/Now4kOuw1rpRGPXf3mv+P/IbvwFM+49WAzZoj7rMp7r6CDp3EtwHoWOKVM3qr3Vzv6+ExMT6HQ6BEEgNjb2jBNJFkWRoaGhpWxkcnIykZGR27YeCw4OXtWqSiaT8etf/3qJCP/oo49SV1fHQw89xNGjR2lububo0aM89NBDgKmk/PLLL1NbW8t///tfvvKVrywtJm+//XaeeOIJmpubaW5u5r8nPCGfeuopHBwcaGlp4Rvf+Ab33HPPhter1+vp7u4mNzeXiooKrK2tOXDgAPv27UOtVq+6SBAEYYWtFrCoNh8uCIJ5rbunCZ+YwMrT0/PrX/rSl5b1FxuNRkZGRjalXaVUKgkODubgwYP4+/vT39/P8ePHqa+vZ3Z2dteueyfQ2dmJj4/PjqW5VSoVqamp+Pv7U1FRQXl5+QqvptONpqYmAgMDiY+Pp6KigtbW1q0Fwk88AUNDcP/mvL0XlaEXDVpPhm7KQO+xMebVnWg8azkQ+026re0Z0E0gzRmitaWVf//734ucAAD0BpF3Kyd5o0pAYjByYdtr+Mmmcbn1VhRb6AyLjIykvb196Z5dzFIteiOux78JCQkxu3Xb09NzU4KXi9gMzwrAVSUn2se0UnWy39mJ0RziutFoRKvVbjrY0Gg0iKJoFs9pdnaWycnJdcv4zs7OZGRkMD4+vix7tdhYsR1hS51OR1FRETEnmjbMgiCY+InnnYfsq1/Dp3qa9Jivc+7+B/F1PpuZ2TEm/d8CCYwWz3Hky19mVqul7ff/ZG5OQKkAuWxnspE6nY7y8nJ6eno4ePAgwJalSHYLY2Nj5OXl0d3dTXx8PLGxsTvmBGJnZ4dEIlmREXZ3dyc+Ph4wLZ7Dw8Pp7e3l9ddf5/rrrwfg+uuv57XXXgPg9ddf56qrrkKhUODv709QUBBFRUX09/czNTVFamoqgiBw3XXXLdtn8Vif/exnef/999dsIhgbG6OiomIpex4XF7fkGrKZINjLy2tVGZ6bbrrJxsrK6srNfl+nE5+IwOqEhU18YmLisu0jIyM4OjqaFXAIgoBarSY2NpbMzExsbW2prKwkNzeXrq6uM05k02Aw0N3dvSv+h05OTqSnp+Pu7k5JSQnV1dVnRFflxMQEo6OjBAYGYm9vT3p6OvPz8+Tl5ZkXAM7Pwy9+AYcOQUbGpndzc3MjJiaGwsLCJQ0oo9FIw98aMegNLCSUczD+HrBy4sPpakKVntx727doaGjgyJEjS8cZGNfx+DtDZNfNECEM8fmGF3BQSRk/eBDZFrW4ZDIZMTExlJWVLWWpkpKSCAgI2LBMpFQqcXFxMUs7TCaTYW9vv8R52wiWlpZotdpNBW+Ho22RCQa81aePuD4xMYFKpdr0sbu7u82WdVk0Wt7o95HL5cTGxi5lr1pbW2lsbCQmJsas850Mo9FIcXExwcHBW9d/k8nglVcgIgI++1moqWFkaJqZEScO7PsGRksNC+5tjJVpSIjfT3RkJB+8V4Qwr0BisX07GjCN9bm5uTg5OZGYmLhUSq2trT0j6B1TU1MUFhbS3NxMdHQ0CQkJuyL1EBwcvIK8fzI6OjooLy9n//79DA4OLgXz7u7uSzpgvb29yzKui4LAvb29y6o/i9tP3WdxTDh5ATU3N0dzczMfffQR7e3teHp6cujQIcLCwsy24bG3t1/ywz0Z1157raW9vf1XzTrYacInIrCysLC4/Itf/KLVqQPTemXAzUAqleLl5UVaWhpxcXHMzc2RnZ1NeXk5o6OjZ0SpsLu7Gw8Pj11Ldy92fx04cAAHBwfy8/Opr68/bYOV0WiksrJymQ+gVColMjKSsLAwioqKVi2XrIqnn4b+/jW5VevBwcGBpKQkysvL6R/ooezdtzB22SPGtpOedgtKC3te7f6I57/4M9waxSV+GJikFD6qnebxd4aYndNz4UwhGbX/wvFgBr633srU/LzZHIVTMTs7u8TbMGcADwoKMltE1lxNK3t7+01x+Jzs5JwfOISr7c4K2pqTsVpcnG0Gi40y5jSQTE1NMTc3Z1bzhYuLC+np6bS2tiKTyba82BNFkfLyclxdXbdv5WJnB2++iWhtje7ccxmqqiI1NRUHew+Swm9m1CML44LIeLmGL916K1VdXQzXtDInm2Z+bOsNMwaDgZqaGpqamti/fz/e3t5L44KlpSUBAQHU1dVt77NtAzMzM5SWllJTU0NwcDD79+/f1a5EtVqNTqdjenp61Wu54oor+N3vfrfuNaw2dgqCsOb2tfYxGo309fVRUFBAaWkpcrmc9PR0EhIScHZ23jIfUBAEPDw8VnRBe3t74+bm5ioIwhkvWPmJCKwcHR2/duONNy6bPfR6PdPT02arJa8FKysrQkNDOXToEN7e3nR2dvLRRx/R1NRktvXKTkEURTo6Opb5ye0WBEHAy8uLzMxMrKysyMnJobm5ec8zeI2NjXh6eq5asnB0dCQ9PZ2xsTGKi4vXz65ptfDQQ5CeDocPb+labGxsSE1NpaLmZYTiYASnOfZdfBCp1IKi4Xp+cuU3acuuYWZ4Ymmf4Skdf353mPerpghV6fls8yt4DzegvuYa7A4fRnLCFLqnp8fs9umTuVTp6elotVqzO14tLCzw9PRc4Sa/HtRqNZOTk5u+F5ycnDbdfWplZbnjz5c5GStziOujo6OoVCqzFjkNDQ2Eh4ebPcn09vbi7u5OWFgYBQUFdHd3m73Qq6urQ6lUbsr0eDMQvbxo/s1vkIyNEf/TnyI7EZy7OIQRtC+Zebte+nOHuebqa1AoFJS89xqi1QKlH7yKYQt0i4mJiSWtp9TU1FV/U29v76XGgL3E3NwclZWVlJeX4+PjQ1pa2p4R6Bc7BE+GTqfjiiuu4JprruHyyy8HTH6hi5zK/v7+JcqMl5fXsm7fnp4ePDw8VpTgFrefus/IyAhjY2PU1NQwPj5OZGQkGRkZ+Pn57Zi59cnZspNx++23Ozg4ONy4IyfZRZzxgZUgCK4ODg4+pw4OAwMDZunymHE+nJyciI+PJz09HYVCQWlpKfn5+fT29u6pXczg4CBqtXrbpEdzIJFI8PX1JTMzE4lEQnZ2Nu3t7XuiCTY5OblUAlwLcrmcffv24ePjs2R4uyr+8hfo7jZlq7Zxj2j1EzjU7Eeqs8Qi2eSVNjozwdWXXUlvWQsvvvhXLrnkEoyiSF7DDH/87xDjMwY+ox7gQN7TWFtb4HLbbVie1NkolUpJTk6moaFhXaXykzE3N0dubi5KpZK0tDRsbW3Zt28fFRUVZt+TAQEBdHZ2bjpQEgQBd3f3TQupbpbADqYFzU7z+zabsTIajczPz286CFvkOm4W4+PjiKJo9oQ7MzNDZ2cnERERuLi4kJGRwcjICGVlZZv+rdva2pibmyNiCwbeq0Gv11NUVIQYF4fkL39ByMuD22+HE8FekNdZyKJGEKcUzHSM8NwLL5Nx6Z1YKHQ0eEgZfeEFjJukGRiNRpqamqiuriY+Pn7dMrcgCMTExFBbW7sni8CFhQVq/h977x3eVn5e+X8uOkAQBAH23ntvIilKI8+4ju0ZO3H3usROXLKb7DplM7Y3bZOsnc0m6xSvE//Wccb2JuPYiWvisR1PkUSJYhG72HsnAXYQHff3B3XvECRIghQlcbR7nkfPaCCUC+Difs/3fc97Tl8fra2t8ndzT1Ywp0BsbCybm5vygI0oinz0ox+lsLCQX/u1X5Pv99RTT/Hss88C8Oyzz/L000/Ltz/33HO43W4mJiYYGRmRPfciIyNpaWlBFEW+9rWvyY958skn+cu//Etefvll/uZv/oZLly5x5coViouL70tAtMFgCDmR/M53vlOl1Wo/fOYveMY498RKq9U+/cEPfvDANzc7O3tPbcBwoFarSU9Pp6mpidLSUvbH6NzvVqFksfAwoFQqyc7OpqmpCY/Hw9WrV0+1aw4XoijS19dHaWlpWGQ5ISGBxsZGZmZm6OzsDG5der3wuc9BbS28/vX3dFzj359Bv5pF/JN6XLrdnL0n3vIGJlr6+Yu//RLveue7WN328dWf2Xi+c4PsOA3v89wgsfl76EtKiP3Yx0LqqTQaDXV1dXR1dR079bi6ukpLSwslJSVkZ2fLn4/JZCIlJeXEAbUqlYr09PSQYdCHIZS/zGEwGAy4XK6wyLjBYHhoFauT6Kuk9stJKuQDAwNBEUbhIBAI0NXVRXl5uTzZqFarqaysxGKxcOPGjWM/r/n5eRYXF8/EoR12yURLSwsJCQm7cVrvetfuMMhXv7obE8VdgvP44/h1Dhab7VRdbMBojiPLHM1MmpHN1SVWv/lNxGOIoZQSEAgEuHjxYliLtl6vJy0tLeTE3FnB6/UyODjIzZs3iYqK4vLlyye23DgrSG7+UtW5ubmZr3/967zwwgtUVFRQUVHBv/7rv/LMM8/w05/+lNzcXH7605/yzDPPALsDMO9617soKirijW98I1/84hflc+1LX/oSv/iLv0hOTg5ZWVlUVlbS2tpKUVERa2trfOQjH+F73/seX/jCF+67Z1ioqpXZbCYrKytCEITTZUI9KIiieK7/JCcnNw8NDYl74Xa7xZdffll8GAgEAuLi4qLY2toqvvTSS+Lo6KjocrnO/HW2trbE5ubmM3/e08Ltdot9fX3iSy+9JM7Pz4uBQOBMn396elrs7u4+8eMCgYA4PT0tvvjii+LKysrujV/9qiiCKP7gB/d0TMtt62LXb8+KHd+4Lr/WT/tviAVP1omf+uLviYFAQGwd2Rb/4B/nxD/81pzY1rUgLvz5n4uzv/u74lZzc1if0dramvjiiy8eeg5NTk6KL7/8srizsxPy3wOBgNjc3CzabLYTvTefzye+8MILotvtDvsxN27cELe2tsK6b0dHh7i6unrs/TY2NsT29vawnvPFF1880/sNDw+LU1NTYd13cnJS3H8dOgrLy8tiW1tb2PeXMDQ0JA4MDBz67ysrK+ILL7xw6Gdrt9vFl156SfR4PCd+7VDY3t4WX3zxRXFpaSn4H/x+UXz720VRoRDFH/9Yvnn63xbErt+eFf/pB98W3/Obz4of/MQnxd+e/Xvx5Ts/FWd/+7dF+7e/HfJ3EQgExPHxcfHFF18M67zZD7/fL7788sthn5/hwufziSMjI+ILL7wgjo+Pi36//0yf/7Twer3iCy+8cObXYVEUxc3NTbGvr0984YUXxJ6eHnF9ff3MXyMcHLbO/6//9b+8kZGRvymeA35y2J9zXbESBEGvUqly8/Lygm5fWloiPj7+YR0T8fHx1NbWymOp9yNG52FWq0JBMqisq6sL8mg5C3i9XkZHRyksLDzxYwVBIDU1lbq6OoaHh+nv6UH8b/8NKit3ndZPCceUm/kfbuG0jJP6pl1twmbASUf0Ar/418/whpLX8uwLK/ygbZ0Uq4ZfzN0k6YdfQXQ6ifngBzE2Noa1mzWbzRQVFdHa2hrUyggEAvT29rKyskJjY+OhFRhBEKioqKC3t/dEAwdScPdJonxO4sQers7qrFuBgUAg7CrCSfRVJ/GuEkVRngQ8CdbX11laWmL/9W4vYmJiqKuro6en58B3sbW1RXd397EGoOFibW2N1tZWKioqDlraKBTwta9BcTG8+91wd1ItsSEWlCKRkyksTQ/wtb/+EoppB3esfiIffxxndzebP/1p0FM5nU5u3brF9vY2TU1Np9LNKhQKiouL6evrO5OqeiAQYHJykqtXryKKIpcuXSIzM/PcOLurVCpiYmLOLOZmf7xMdHQ0ly9fprS0NChe5kFCo9GgUqkOVGifeuopVWRk5L97KAcVJs7HWXI4nnjrW996IMBL0lc9bGg0mvsSo+Pz+bDZbOfiPe6HXq+XHaOnp6e5ceNG2KP4h2FwcJDs7Ox7WgwkgWt0VxfCyAiO//gfT62t8mz4mHxuFb9+i526G8RE5zA1O039ay4yPzLDe2MeZ2gjg8kVN68r0fE2fxe+f/p7VDExxH7iEyf2p4qLiyM9PZ2Ojg7ZV0lKdq+urj5WLG0wGMjKyqK/v/9Er5uamsry8vKxMTkSEhMTWVxcDGvhCldnpVKpzlS3GG4bUBRFnE5nWFqsra0tVCpV2FqsxcVFjEYjRqMxrPvD7mBCd3c3FRUVxy7eERERXLx4kYWFBfr7+xFFEZfLJRuAnoVv0tLSkkzSDm2XGo3w/e/v2jE89RRsbKAyKLFURBBjS6bu4tMolQrGvnWLee8qzsYKIurq2L5+ne0bN4BdkX5LSwtZWVmUlpbe0/Sz1WpFo9HcE9kQRZHZ2VmuXr2K0+mkqamJ3Nzcc2dCCpCZmcnExMSpHy+GiJepra2V42VOYrJ7vxAfH3/g+0xOTsZoNCYKgmB+OEd1PM41sUpOTv7Qu971rqC50UAgwPb29rkL2twfozMwMCALv09qXTA3N3dk2vl5gNFopLq6muLiYkZGRrh169apyOTGxgYbGxv37CoPd8d071oPDN4VwJ509xrwBJj8+1X8Xj8LZX9PRkY9oijytg+8k7H2AV5vruBqhw+7A56q0hP70t/juHYVQ3U1sR/5CKpT7u7S0tIwm810dHRw48YNMjIyQjp1H4bU1FQ8Hs+JFhWFQiGbhoYDpVKJxWIJq1IpaafC+fwFQTizSm+4wvWNjY2wd+InrVYNDw+fOIZpYGCA1NTUsIXAKpWK2tpalEolLS0t3Lp1i+Li4jO5Lk5NTTEyMhKelUdGBnz72zA2Bu99L/j9xNQbUQQEqlVxVNWn8fz/+Q6i10+Pc5KoJ59EV1TExvPP0//977O4uEhTU1NYJs/hoKioiKGhoRML2UVRZHFxkatXr7K2tkZDQwOFhYVnNuV2PyAR95MmUzgcjkPjZe4p6P4+ICEhIeQ17Z3vfKdBqVS+6SEcUlg4t8RKEASF3++/tDcaBF7xnTmvpEOK0blw4QK1tbX4/X6am5tpb28PO0bnpNNHDxNRUVFcuHCB3Nxc+vr66OjoCNvJXjyhYD0s3F2gK6urCQQCNDc3n+h4Zr63jnPRi6+hm0DkNqlxdfzW//g9ul5q5ZOf/w30QiV3Zly8vsJE7uIdIldWWMnOxlNfj3CPF2Gz2YzNZsNisZzIKwmQ4z0GBgZOZPKamJjI+vp62J9RuJ5WgiBgMplkg9WjoNPpwq6aHYednZ2wKjbh+leJosjS0lLY1ePZ2VmsVuuJqkY2m42tra0Tt/4FQSAvLw+Xy4XH4zmxEeN+iKLI4OAgS0tLNDQ0hD+N/Nhju+7sP/oRfPrT6OPVrEcJZKxqeernmrAt29l4aZRu5xSiAL7Ll3GaTJj7+6kqKztT8qLT6U4sZJfMRxcXF6mtraW0tBSt9kCj5FwiIyMjLOuUvfEy3d3dYcXLnAdERETg8XgOEOV3vOMdEYmJiefWduHcEiug+sKFC8r9Jdjz0gYMBzqdjpycHB577DGysrLCitFZX19Hr9efu53DcbBYLDQ0NJCamsrt27fp7u4+dnppYWEBo9F4tj38u8RKoVJRUFBAcXExbW1tTE5OHktql69ts97rJPY1Oma1PyE1vo7mntt84Xc+T8UbG/jIU8/wUt8WlZkGqrV2Nl94AX1JCYXveQ8jIyMn8obaj/n5eYaHh3nNa16D0+k8kSGnBK1WS2FhId3d3WFX6gRBoKCggKGhobDubzabcTgch2Yp7sXD0FmF294LV1+1vLyM1WoNqy0SCAQYGxsjNzc3rGOFXW1LX1/fqQKWRVGku7ub1NRUamtraW1tDWkcGQ6kaUSPxyNXwk6Ej38cfvmX4U/+BL7+dUYtoHHDhy9+noqaNDRbM2z6d/jZQAsT09PEv/nN4HSy0919quM9ChkZGSwvLx97/VlfX+fmzZtMTk5SXl5ORUXFPZPTB42EhASWl5dDttPFM4iXOQ+IjY2VXeMllJeXEwgEKgRBOJclxXNLrGJjY9/z/ve/P2hLKYriiZPozwNOEqMzOTl5X+JrHgQEQZC9XeLi4mhtbaW/vz/kIix51Zy0ZXIspJbS3YUhOjqapqYmOXLisMrIxqCTxZ9tYi7V48juIhDwkpTQwK//4WfQmSL46//5f/h+6yapMRqeLFSx9u1voYyOxvzUU2i1WhoaGlhaWmJwcPDE7cfZ2VnGx8epr69Hp9NRXV3N1NTUgYtJOEhISECtVp8otiY2Nhan0xlWK1cQBJKTk8PytApXZ3WWxCqcVqAoimG3DKenp8OuHk9PT5OQkHCiakdfXx/Z2dmn0kUNDQ3Jtihms5nq6mra29tP3JKXPKqMRuO9VY+/8AV4zWsQf+mX8M904DcqcHar+fFPnqexQo/SH2AucpsLFy5gLChAnZjIVnMz4hl75CkUCvLz8w+1Idna2qK1tZXBwUGKioqoqam5L15MDwIKhSLICBR2NxfDw8NnEi9zHpCQkHAglFkQBF73utepgPCzyh4gzi2xUiqVb3/jG98Y9Avf2trCaDSem8mM0+CoGJ3l5WXW1tYeuOHcWUMylLx8+TImk4kbN24wNDQUpDWbnp4mPj7+7Ctz0s5tzzki5etlZWVx8+bNA1EJrmUv0/+0hj5RTcpTUUwuXMViyuZnnhne9Ccf5Rvf+w7XhvQYtArec9HM1nf/mYDTieVd70Jx9/iVSiW1tbV4PB66urrC1gxNTU0xPT1NfX293BJRqVTU1dVx586dsKJh9qOkpISxsbGwyYpUtQrXD+uwkNT9iIiIkEOLj4Jef3bu6+GI1zc3NzGZTMcSCI/Hw87OTlgVVb/fz8TExIlczhcWFvD5fKfy45ucnGRzczOICJlMJmpra+no6Aj7vHG5XNy8eZOUlBRyc3PvrSWkVsO3vkUgIYn3/M9fQhtvZ2fWi61fidqTybXf/f/oX5vEEXAjCALGS5fw2+24BgZO/5qHID4+Xo59krCzs8Pt27fp6ekhOzub+vr6hzbxdpaQ2oF742W0Wu2ZxMucB0RHR4f0jXzve98bnZiY+IGHdFhH4lwyFEEQ0tPS0oz7dxGvpjZgONgfozM0NITb7WZkZOShxeicJSQrhMuXL6PRaLh+/TpjY2N4PB4mJibIyck5+xeVCE0I8i1lsC0sLNDR0YHX68W3E2Di7+0o1AIZ77VidwzhcK3QY4+ga2WY11vrWNoqwukO8L7LFmi7gXtsDPOTT6LZp4MSBIHS0lKMRuMB+4RQkC6GdXV1B8ryWq1Wzio8aTVHrVZTWlpKV1dX2NUzq9VKIBAIywlep9Oh0WiOrYwIgkBkZOSx7amzrFh5vd5jNTvh6qskE+JwFqWJiQlSU1PD1gu53W4GBweDMjHDxeLiIrOzs1RXVx94rNFolI1njyNX29vbtLS0UFBQcHZmy1Yrc1/9FlrXNln/4wMgOvDf0RKtK+fq31/n2Xf9IT+bagNAX1SE0mJh6/r1MzceFgSBwsJCBgYGcLlc9PT00N7eTnJyMo2NjacPpD5nWF9fZ3R0lLW1NVZWVuR4mfT09HMtvD8JBEHAbDYfuDZduXKFQCDwBuEcssZz2WSNiIh4+/vf/37z/tuXlpa4cOHCQzii+wspRketVnPhwgU2Nzfp6OhAqVSSlpZGQkLCuRh9PS0UCgWZmZmkpqYyMTHBCy+8ELZu5cQ4gljBrkVGdXU1c3NzXL92nYSxfLwbItm/EIMmSsl4/1VWAlF89gOfJaMgh7o/ejuzdifvabJgWZ/D9sIL6EtLMVRXh3x+QRDIzc1Fr9dz48YN6urqQlblpqenmZub48KFC4d+DhEREVRUVNDa2kpjY+OJoo2sVitRUVGMj4+HXUUpLCzkzp077B8YCQVJxF5SUnLk/WJiYrDZbEdOq51VxUpanI+7ztrt9rCiXmZnZ8O63ni9XmZmZrh8+XLYx9nV1UVRUdGJ46rW1tYYHByksbHxyPNG0lxVVVWFrMqsrq7S3d196L/fC5ZS87n27/+S9//pR7Am/wl24ffw5VbzqT/4HP/zd36bj732w/j+9sdYY+LwFr4B9+AAEc3TqCwWBAEEAAEEBBSC9Hfu/puw7/9fcVURBOGV2wUQRA3rG5tcv36dwsLCsx2SeYhwu93Mzs4yOzuLwWAgLS2NyMhI/H7/q7aleRyk6cC98VBarZbS0lL10tJSIfDwkrhD4FwSq6ioqA8+/fTTQXTb5XKhUCgeaG7eg4Tb7cbr9RIdHU10dDTp6elsb28zPT3N8PAwVquVtLQ0oqKiXrUXBylKZWZmBoPBwNWrV8nNzSUpKenMpwI5hrQlJydjcJuYfmkTocKBLjmBHdcqU2uD/OWf3WJ7ZYNf/sLn6Z508nhpJPnRfpb/17dQWSyYn3rq2ONNSUlBq9XS0tJCdXV10AVvbm6OmZmZI0mVhOjoaAoKCmhtbaWhoeFEZLSgoIDr168TGxsb1hh+VFQUarUam812rI4xPj6ewcFBAoHAka15q9XKwMAAWUd4e2k0mrDE8MfB5XId21oWRRGHw3GsjcDGxgY6nS4svdTY2BiZmZlhfzfT09PodLoTmxw7HA66urq4cOHCsddBiVy1tbUd0BAtLCwwPDzMhQsXzlxz43Q6mZscYaz2dbS+/kPU/fh/s5XwOny3LqJNey/v/o10nvuTD/HJD7yFD3z2m0RExUDcBZgBZk7v/XcYmjIy0AeWzvYa8xAQCARYXl5menoal8tFSkpK0OSmx+Ph5s2b96cLcA4QGxvL0NDQgQ3R+9//fktHR8e7gd99OEcWGmdGrARBUALtwJwoim8RBOFPgLcCHmAM+AVRFNfDeJ6IrKyslP0C7ofptv4gMDc3JyeJSzAajRQVFVFYWMjy8jIjIyPs7OyQkpIiL9yvNoyMjJCTk0NaWhoul4uRkRHGxsbIz88nLi7u3i9+x1SsgrC9uxAaMjRcu3YNY/wS37m1Se8PWvjEb3yGeX8eJWl6LhdGsPr1rxNwuYj54AdRhPm5x8bGUllZSXt7O+Xl5VgsFubn55mYmODChQthT+UkJCTIBpC1tbVhf0ZKpVIOam5qagpLm1hQUEBXVxcXL1488nUUCgWxsbEsLS0daQ1hNBpxOByIonhkkC5w5H3CQTgTgVtbW0RGRh77OuGK1t1uN4uLi2FXq3Z2dpiYmKCp6WSaW7fbTVtbG5WVlWGTIclrrr29ndraWoxGIxMTE8zPz5/MTiEMSMaaY2NjNFWU8LaYGHjLF6Gimbwf/ya++J/w6z+fSnNWN6riT/HdT32Zd1d7qapKYuvaVTZffInYj30MZVz83ecDUf7v7v8E37b7l73/7/f7mZubZ25ujviEJL7fp0VljEPv3WR5eflVuX5sbW0xPT3N0tISsbGx5Ofnh6wwajQadDqdrB981KBSqdDpdAc2RW95y1uUn/nMZ95JmMRKEIS/Bd4CLIuiWHL3tlNxlaNwlhqr/wjsVSH+FCgRRbEMGAY+HebzNL7+9a8/0Bx+1PRV+yGZgobCYTE6t27dYmFh4czMFe833G43KysrstmiTqejtLSUmpoa5ufnaW5uDms8/0iEEK8fejx2HwiQVZpOdXUVLyz0893ff47S2hqSaj5BQrSat10ws331Ku7xccxvfjPqE56DUVFR1NfX09vby/DwMKOjo1y4cOHE+oeMjAwiIyNPHNkRFRVFYmJi2HYKkmP4/imcUAjH00oQBIxG47E6K61WeyL/rVAIx8MqHH1VIBDAZrOFZVopbRTCIa2iKNLZ2UlZWdmJRt2lqb2ioqKwQ6MlmEwmqqqqaGtro6enB7vdTn19/ZmSKrfbTXt7OzabjYsXL75S7YyIgGefRbE8S8rVP2Dp37bJTGiktjSKT1z/U/IqC1EpBdSlJajVSlw3m9GqFWjVCnQaBXqNAoNWQYRWSYROiVGvJFKvxGRQEmVQEhWhwhyhwhyhZHt1nr7bN9ArPbzhNfXUlGYRHaHEtumjoKDgVGbBDwuh4mWuXLlybLxMamrqiaaBX20IZRYaExNDREREjCAIxzjZyvg74I37bjstVzkUZ0KsBEFIAd4M/G/pNlEUfyKKoqTebQHCUkfGx8e/9U1vepN5722BQICdnZ0TRUS8mrC9vS0z8uOwN0anoKAAm812JjE6DwLj4+NkZmYeqBYYDAYqKyspLy9nfHycmzdvnmoaDjhRxcqz6kNtUqJQC3gCKyz5VZS+rpbH3/1f0aiVvO+yFXF6kq2XXkJfXo6hqupUh6TX66msrGR4eFi2QzgNCgoK8Pl8jI2NnehxOTk52O32sKOH8vPzGRoaOnYhMplMuN3uYwmR1Wo9ljCfhYA9HAsFu91+LLFaXFwkLi7uWLLkdDqx2+2Hboj2Y2xsjOjo6CCdyHEIBAJ0dHSQnp5+anfyyMhINBoNCwsLVFZWnqm2cXFxkRs3bpCSkkJlZeXBc7uxEeE3foPolv+D6urzWNcuELu5hEanod0xyp/92Z9Rd+kSjuxsnH19+MIYnpAgiiLz8/O8/PLLbG1tcfHiRfLz82XSajWpsG36MBgMGAyGkNYfH/nIR4iLiwvSCv7e7/0eycnJVFRUUFFRwb/+67/K//a5z32OnJwc8vPz+fGPfyzf3tHRQWlpKTk5Ofzqr/6q/Ntxu928+93vJicnhwsXLjA5OXnoezkqXiYc4h4fH8/S0tKrhkCeFHFxcSFTHx5//HE1cLwwFBBF8Sqwuu+2U3GVo3BWFasvAP8ZOKx08hHgR2EdkELx+kuXLgXdtrGxceKd2qsJc3Nzp5rKOcsYnfsNr9fL4uLikdEgkZGR1NbWUlhYyODgIG1tbSc3PAxTYwW7FSutZfciPGnvIqIwh//25T/HlFRGgsaGfXyA1W9/G5XVivktbzl1m8rn89HV1UV9fT2bm5tyvttJIbmrr6ysnGhnKggClZWV9PT0hBX1odfrsVqtYXlVhRPMHI5R6FkI2I+zWhBFke3t7WMFvuG2AYeGhsjPzw/rvNjc3GR+fv5EwcyiKNLb24vZbD51EoPX66WlpYWEhARycnLo7e09k4VXOqenp6dpbGw8Oingv/5XxOJi0v71P7P2ryukmQoxOzfo2BmjoqqCqakpnv7932d5e1vOEDwKoiiyvLzMtWvXsNls1NfXU1xcfKAKF2tSYd/yERBFcnNzQwaOf/jDH+b5558/cPunPvUpurq66Orq4sknnwTgzp07PPfcc/T39/P888/zy7/8y7Ix5yc/+Um+/OUvMzIywsjIiPycX/nKV4iOjmZ0dJRPfepT/NZv/VbQ65xlvIxSqcRsNt9zdut5hRSTtb9D8+STT5rj4uLeekYvEzZXOQr3TKwEQZD6lR2H/PtnAR/wf8J4LqPRaLTsTzcPR0z7aoUoiiwsLJw4wmQvziJG535DiukJZ+dlNpupr68nKyuL7u7uk1kOnKBi5V71o7UqEUWRIccEmwurpKp2dW4FuZnQ1oZvZwfD294Wtq5qP6T2T0ZGBjExMVRXVyOKIrdv3z5VC1ehUFBTU8P4+HhYmX0SIiIiyMjI4M6d8IZnpIXouGOUzEKPOscky4Wj7vMgKlbb29tEREQcSYRcLhder/dY8rW9vc329nZYuh3J1TycgOW9GBkZQRRF8vLywn7MXjidTm7evEl6ejrZ2dlkZWUhiuI9BffCbtXv+vXrWCwWamtrj9d6arUIX/sayh07cc99hjj7a7BszOAIuImty+Zf//VfmZqZ4d3PPcfkyy/jPyJeaXV1lRs3bsh2E2VlZYcSkJhINV6/yNaOH5PJhEKhOFAJv3z5ctgVxO9973u85z3vQavVkpmZSU5ODq2trSwsLLC5uSnLND74wQ/y3e9+V37Mhz70IQDe8Y538LOf/UyeIr0f8TIpKSnHbnRezTCbzQdisi5fvoxKpXrDvT73SbjKcTiLitVF4ClBECaB54DHBUH4BoAgCB9iVyj2fjG81b3xta997YE+Sbi+M69GrK+vExkZeWbxAntjdLKzs8OK0bnf8Pv9zMzMnNhR3mq1cvHiRZKSkmhvb6e3t/f4TLkwNVY+ZwD/TgCNRcXmzjyzbh9/Uf+rPPs//hoAnQp08/Oo8vPpGB9nZmbmVAR1eHhYHomG3epRSUkJZrOZlpaWU1UW1Wo1dXV1J27/pqens7OzE5aju1arJSEh4VgNlUajISIi4sjWrSAIREREHHn+nQWxcrvdRy7y4aQ2hBu4PDg4SEFBQViL4ODgIElJSScSFU9PT7O2tkZZWdmpFtrNzU1aWlooLi6WW5WCIFBWVsb8/PyJSLkEv99Pf38/g4OD1NXVkZaWFv6xVVXBf/kvRPd9F9X/fpFErxa930ebY5THHnuMH/3oR8yvrfGur36V1WvXDjx8Y2ODlpYWRkdHKS0tpaqq6tjJTqtp95pq29qt0ubm5oYdOP5Xf/VXlJWV8ZGPfET2T5qbmws6N1JSUpibmzvQcZBu3/sYURTZ3NxEr9fzL//yL/ctXiYmJoa1tbWQETePAkKlOURHR2MwGCwn0FkdwCm4ypG4Z2IliuKnRVFMEUUxA3gP8IIoiv9OEIQ3Ar8FPCWKYlhXzMP0VS6X61VpxR8O5ufnw9ZonASCIBAdHR1WjM79xszMDElJSae6eEjC/UuXLmGxWGhpaWFgYOBwQhJmxcqzuvv+tVYV87YuBkfXEAMiRSUVu6+7soDodhNdU8PFixex2Wy0t7efyBZgfn6etbW1kJ5J2dnZZGRkcPPmzVO1wKTom46OjrAfLwgCFRUVh8YMhTrGiYmJYy/S4YjYj4u3uddWYDgeVsdt0ERRPHKIRMLGxgYejyesKvrq6ipra2sncmRfXl5mamqK6urqU6VM2Gw2Ojo6qK6uPvB+lUolNTU19PX1nWijtbm56wel0+lobGw81fVY+Mxn8JdVk/hPv0X6SAPR6zNMepZZ9m5w+fJlfvT88/z7t70NX1cXgbvn5/b2Nu3t7fT395Ofn09dXV3YBDUm8i6x2tz9rVssFrxe77Hygk9+8pOMjY3R1dVFYmIiv/7rvw4QcmMlCMKht8Pu+jU+Pi7HyyiVSpqamu5bvIwgCMTGxoYVJfVqxGGygieeeEINNJ7mOU/DVY7D/XRe/ysgEvipIAhdgiD89XEPUKlUby4tLQ1qPzzq+qqVlZX7HmFzVIyO3W6/r63CQCDA5OQkmZmZ9/Q8Ukbd5cuXMRgMXL9+neHh4YMEMUyNldv+CrEaX7vDZPdugHJRWc3uHSbHUEREoM3KQq1WU1lZSUpKCs3NzWFNzG1sbDA8PBzSHVtCUlISxcXFtLS0nGrwIDIykvLyclpbW8OufOl0OvLz8+np6Tn2vmq1mpSUlGNbR7Gxsayurh5JwI7TWel0uuOrkUfA4/EcOekmiiJbW1tHLspra2tERkYeO1wwMDBAYWHhscfk8/no6emhsrIy7MrO+vo6d+7cCenGHw7m5ua4c+cO9fX1h75XnU4n24Acd96IosjIyAhdXV1UVlaSnZ19+laVWo3yH76GwrdD4uf+B/H2TRQitDl2tU+XLl3iE//lvxDY2eFHf/M3vPDCC3R2dpKenk5jYyP7JSLHIVKvQKMS5IoV7FatRkZGjnxcfHw8SqUShULBL/3SL9Ha2gocbLPNzs6SlJR0IOJpenqaqKgoWlpaMBqN8rRkeXk529vb9737Emp67lFBKJ2Vz+ejsbHRnJSU9LbjHi8Iwj8AN4F8QRBmBUH4KKfgKsfhTImVKIoviaL4lrt/zxFFMVUUxYq7fz5x1GMFQTAaDAbz2toaV69e5ebNmwwPDzM9PX2iKZpXE7a2ttDr9Q/UVX1/jM7U1BQvv/wyw8PD9yVGZ3FxkZiYmDMb71YoFKSnp3P58mWUSiXXrl1jfHz8lR9amBUryWrBq19nDhdzt0fJyc9Fb9y9eIuTY+iLixH2fDeJiYk0NjYyOTlJd3f3oVU/t9tNZ2cnNTU1xy7SVquVmpoaOjo6TrXLtFgs5Obm0traGnb5XzJLDEecnpWVxczMzJELsCAIx17MTSYTm5ubh5L4vV5Wp8FxwnWHw4HBYDiSFMzMzBwrErfb7SgUirAW+f7+fjIzM8OuTOzs7NDZ2RmebikExsbGmJqaoqGh4VjbCbPZTE5ODrdv3z70M3c4HNy4cQOfz0dTU9PZ+CMVFeH/zH/FNPgTKr+lItphp2tnHHfg7vmVkMB6RAQ/92u/xs9+9jOamppOvfEUBIGYu5OBEmJjY9ne3j6SxO8NNP7Od74jTww+9dRTPPfcc7jdbiYmJhgZGaGuro7ExEQiIyP56U9/Snd3N3/xF39BU1MTxcXFfOhDH+InP/kJarWab3/72zz++OP33ajUYrGwurp6LrS19wMmk4mJiQn6+/u5du0azc3NEuE/VmcliuJ7RVFMFEVRfbfT9pWTcpVwcJ6c1xtf+9rXCpWVlcDuhdJmszExMYHdbmdubg6r1UpMTAxms/lVHfEiYWlp6aF5c0kxOjExMXi9Xubn5+9LjM7ExAQVFRX3fsD7oFQqyc7OJi0tjfHxca5evUpWVhapfv9uJEYYrUC1ScnSRg+bejPzHSP8/Fvejtu7S8w0Xif60tIDj9NqtdTV1TE9Pc3169cpKysLIv6SML2oqChse5DIyEjq6+tpa2sjOzv7xK3hpKQkXC4XnZ2dR1bI9qKsrEwWIB+1CCuVSjIyMhgbGztyoi01NZXe3t4jvdgkHdVh2hi1Wo3X6z0VCT9OuH6cvsrn87G6ukpZWdmh9xFFkcHBQUpDnBf7sbS0hMvlCnuaz+Px0NraSkVFxbHaoVDH1d/fj9vtpr6+Puz2YXJyslxZzc/PD3q+6elpJiYmDpzfZwH1b/86rn/8Lqlf/UsyX/NLtDda6doeJ2peZHFxkZyMDOKNRsbGxu6ZhMREqpi2vdL2FgRBDi3Oz8/nve99Ly+99BI2m42UlBR+//d/n5deeomuri75vn/zN38DQHFxMe9617soKipCpVLxxS9+EZ/Px+TkJL/4i7/IJz7xCfx+P29+85v5+Mc/jiAIfPSjH+UDH/gAOTk5WCwWnnvuuXt6P+FAoVBgMpkemW6P1+vFbrdjs9lYXV3F7XbjdDrJyckhLy9P3rzq9XqTIAgRoig+HDHxHpwbYrVfX6XX60lOTmZsbIwrV67InjGzs7P09vaiVqtlohUdHf2qJFpLS0tUH5I59yChVqtJT08/8xidzc1NVCrViReKk0CtVpOfn09mZiYjIyNMjo2RCYh3c8MOg2S1MGvrZsscyy//j2d4Ou8x3L7dXZ7OqENziIhZEATS09OJjY2ls7NTjp1RKBRMTk5iNBpP7Dmk1+tpaGigvb0dl8t1Ik0O7FaWnE4nd+7cobi4+Nj7q9VqSkpKZBuIo77f9PR0rl69SmZm5qGVFKPRSCAQOLJyJOmsDjsfJJ3VaYjVcRUrm8125GcqTeYe9TmsrKyg1+uPrdx4PB7u3LlDY2NjWL8bv99PW1sbBQUFJ253+f1+Ojs7MRgMVFVVnfh3WlBQQHNzMwkJCURFReFyueju7kan09HU1HRmouogKJUI3/gq1Fdx+fde4s4Pirnm7OUduhouX76M49o1iuLj6ersvOeXsppU9Ew58fgCaFS7hDM5OVmO0/qHf/iHA4/56Ec/eujzffazn+XTn/60HC9z69YtUlJS+IVf+AU+/vGPH7i/TqfjW9/61j2/j5NCqiC/GomVx+MJIlIKhQKr1So7z3u9Xrq7uw8UJZ544gn16OhoI7uGnw8V91NjdSKE8q9aX1+XnWb1ej0pKSmUl5dz5coVOX9tfn6e69evc/36dQYGBlheXn6gwuzTwuPxEAgETuxVcr8hxehcuXKF+Ph4RkZGuHr1KmNjYyd2xp6YmLhnbVW40Gg0FBcXk7q2hjcmhuu3bh1pNeFe9aOMDjDjWUFUq/jQu/8djY2NOB2779FUVIBwzM7fYDDI4cjXr19naWmJqampsPQ3oSCFcG9sbJzYYR2gqKgIl8vF+Ph4WPePjY3FaDQealooQaFQkJ2dfaw2JSUl5UgR+3E6q3uZDDyqYiVNZB3lWn3cNKBUrdpb2Tnsft3d3RQUFITVzhNFkY6ODpKTk09cvfZ4PLS0tGC1WikqKjrV5kehUFBeXk53dzezs7PcvHmTzMxMysvL7w+pugt1RS7LH/gs5jsdVD/3Ml69SEZGBgqFAoXRSFF8PMMjI/c8ySwJ2Fe3XmmTK5VK4uPjmZ+fP9FzbW1t0d/fz8svv8zKygr5+flcvnyZrKysc5dhGxcXF9b073mA2+1mfn6enp4eXn75ZVpbW1lfXyc+Pp6LFy9y6dIlioqKiI+PR61WYzAYcLlcB6xg3vzmN5+ln9U94VxUrARBMObm5kbvZ9dHle91Oh3Jycly68HtdmO321laWmJgYEBmuVJF67Ru1/cL5z37UJrGi4+Px+PxMDs7y61bt9BqtaSlpREfH39ky8Hr9crj4g8MHg+qf/s3eOc7qaquZnBwkJGREQoLC4PaGZLVglu7wqbezNSNO6xlZEJtKo5FG8qAjsiykiNe6BUIgkBOTg6xsbFcv36d1NTUe6qeKhQKKisrGRgYoL29naqqqrCfTzICbWlpQafTHcieDIWioiKuXbsmk6zDkJKSwvj4+JGVoeTkZK5fv05eXl7IRT4qKuqAB81e3C9iJUXdHEY8dnZ2EEXxyMrqwsICZrP52Orr3NwcSqUyLF86URTp6+sjMjKSjIyMY++/F06nk9bWVvLy8u7JAw92N62BQIDh4WGampruK0mQJi9HR0eJe9/PY/7hN6j/X8/T/L4n8Il+VIIShdFIcXy8/PlcuHDh1K8XI1sueEmIfmUNyMjIoLOz81hjZq/XK4emq9Vq0tLSKCwsPNW05oOEWq1GpVIdW8l9GHC5XHJFam1tTe4+JSYmUlxcHNb1TvKz2lvhvXTpEkql8p79rM4C54JYAfV3bemDYLPZwtbnaLVakpKS5MXE4/GwurrK8vIyg4ODwG4rQvrzsInW4uLisbvf8wIpRicrK4vNzU2mp6cZHBwkNjaWtLS0kK2R2dlZkpOTH2yi/LVrsLkJb30rERERVFdXs7m5ycDAboRlYWEhJpMJz92JwA1hBIcxhpf/298yE93MCy+8wM7KKhplHOqEkzldr66ukpaWhlKp5MaNG6fSykgQBIGioiImJiZoaWmhtrY27MVOoVBQW1vLjRs30Gq1x04gKZVKysvL6erqorGx8dAFQxAE8vLyGBoaOvQ3qVKpMJlMrK6uhnxdQRDQ6/WHkiC9Xn/qWCaXy3Vo9fc4fdVx1SqJdNTX1x95DE6nk9HRUS5evBjWMY+NjeH1eoPiVMLBxsYGt2/floO97wUrKyv09fWRk5PD5OTkqVuxx0EURZaWlhgaGsJqtdLQ0IDCo2L2ym+S+Y8foeJb11j65GWSjekojUYupKXxT1/60omc6kPBus9yQYLBYECpVMqh3PuP1WazMT09zdbWFsnJydTW1p677sJxkNqBD6prcBgkvbTdbmd9fR2NRoPVaiUlJYWSkpJTbURjYmKw2WxBxMpsNmMwGMyCIOhFUTz7SawT4FwQq6ioqIuXL18OqtNL/lWnZdsajYaEhAS5vO71elldXcVms8mOxhaLRSZaD7KU6/f7w4rWOI8wmUyUlJQQCATk6qDH4yElJYWUlBTUarUsfj1uITpz/PCHoNXCa18bdLwXLlxgdXWVvr6+XQLu373QLAkDrPpSme0b532/+fP4NzZw7XjQWhQnIoQOh4OpqSlZk7K6ukpbWxuZmZknM1Hch8zMTHQ6HTdv3qS2tjbs6TLJQLSlpYWamppjz7Po6GhiY2MZGRk5kuwnJCQwOjrK9vb2odUtydPqMEIn6axCibrvpWIliuKhpNBmsx26uEh5c/tlCHsxOztLXFzckQur5LBfUlIS1qZtdnaWlZUVLly4cKLzY2Vlhf7+fmpra+8pO9Xv93Pnzh22t7epr69Hr9cTFRVFV1cXTU1NZ1qRWVlZYWhoCKPRSF1dnXxNFzUijoo3sHO7nCtf+Gduv+USyYUfQBERQbTBwBtqaog4on0bDjQqBVEG5QFiBbvawcnJSXkYweFwMDMzw8LCAtHR0WRmZhIdHf1gN4dniISEBLq7ux84sdrZ2QkiUjqdTtbrlpWVncm5ZbVa6e7uJjc3N+j22tpaxdjYWBlw655f5B5wLohVZGTka2pqaoLO3rMmHmq1Wm5twStTQDabjbGxMfx+fxDROs24c7iQdtCv1h8s7FZGEhMTSUxMxOVyMTs7S3NzM0ajEYvFQkRExH39DA9AFOEHP4DHH4cQlSKLxUJjYyMrKytM/HAeDWbs0T4W+sbx+3zU19ez09eHR6FGbwj/uCVNTWlpqaxJsVgsNDU10d/fz+LiIhUVFaf+LBITE9Fqtdy6dYuqqqojdUJ7odfrZQPR+vr6Y3fbubm5NDc3Ex8ff6jgVRAECgoKGBoaOnTowmq10tfXh8/nC6nRsVqtcrxRqGM+jeWH1+s9Ug+0sbFx6Odmt9sxm82HPt7v9zM2NnZsFWpiYgKTyRSWaajNZmN8fHy3anOCRWZ2dpaJiYmwvs+jsL6+Tnd3N6mpqZSUlMjXIZPJREJCwrEEO1ysra0xMDCARqOhoqLiABEUBAFdvJqVN3+a9D9/DxFf/Qc8f/RzqO/+fts6OpgbGuL973//PR1HjEkV5GUlIT4+noGBASYnJ5mbm0MQBFJTU7l06dJ91Zc9KBgMBjweD16v9751aERRDCJSGxsbctZoRkYGUVFR96VtKumsRFEMWkcvX75s/u53v1vH/yNW4PP5cnNycoJuW19fv68TDSqViri4OHl6y+fzsba2Jl/0fD4f0dHRxMTEYLVaz7QMvLy8fK71VSeFFKOTnZ3N+vo6nZ2d+P1+BgYGSEtLu69TgTKGhmBsDO66JB+G2NhYVp0BHNYVNo1mFjraAaivr8f5z/+ML6IRrT78i9Dk5CQmk+lAhUalUlFeXs7S0hI3btygoKDg1FoYKZOtvb2d4uLisH19pOpia2srDQ0NR15cFQoFFRUV3L59m6ampkPL81Jl6zCyIggCiYmJzM/PhyRPZrP5UHNShUJxKu+do3QkTqcTnU536MV9enr6yKilqakpkpOTj6xob21tMTMzQ1NT07HHurm5SV9fH/X19WEvdqIoMjo6it1up6Gh4dSLfiAQYGRkhOXlZaqrq0NWvHJycoKmBE+Dzc1NBgcHCQQCFBcXH/k8ung1q9YmJhqKKP3KVaY+8lNyC96GoNPx3L/8C9944QXe+9733tPiHBOpomtiR16ERVFkdXWV6elp3G43NpuNysrKRzLdQxoYOStbHynI3G63Y7fb2dzcxGAwYLVaycrKOvUE+Wmg1+sPdLVqa2tVMTExTwB/+UAO4hA8dGIlCIKlrKxMtf+Hs7Gx8UA9nlQqFbGxsfKi5ff7WVtbw263Mzk5idfrxWw2y0TrXgSBq6ur96wdOI8QBEH+YV25coWlpSW6u7sRRZHU1NRTx9qEhR/8YPe/b37zkXdzr/pwLfrwl8+yHWFhuXWMlJQU1iYnMc7P4y2LxKQO7yIutQCPaiPFx8cTHR1Nd3c3CwsLlJaWnmr3aDQaZa8rl8sVVp4d7F5Ys7OzaW9v58KFC0cuUJGRkaSmpjIwMHCk7qewsJDBwcFDRcVpaWncvn07JLFSKBRoNJpDyZBSqTy02nUYjhKuHxVj4/V62dzcPFSn5PP5jv1+pYDl8vLyY7UiTqeTjo4Oampqwt6oiaJIb28vfr+furq6UxOM7e1tOjs7iYuL4+LFi4c+jzQleJqWoMPhYGhoCKfTSUFBQVgO4/p4NaIXbv6HD/C+93+awF/+OYG/fAtKo5Hi5GQcDgdjY2MHWj4nQYxJhdsnYlvfYW1ljvn5eSIjI0lPTyczM1PO83wUERsby/Ly8qnXUimxQBKbS0HmVquVnJwcTCbTQ+u8REVFsb6+HnQdKS0txefzlT+UA9qDh06sgKrGxsYDK836+vpDJR9KpVI20MzPzycQCMhEa3p6Go/HQ1RUlEy0wv1hejweBEF4JErNobCyskJMTIwch5KSksLOzg4zMzNcv36dqKgo0tLS7jnF/QB++EMoL4djDBk3+ndbTbaEYVyqWL7wjb/GuqxEPzSECDhRognzq+nv7w9LfKnRaKipqWFubo7m5mZKSkrCahnth06nk72unE4nubm5YX2GycnJOJ1OOZbkqMdkZmbS0tKCzWY79Bglwejq6mpIUqLX61EoFDgcjpDVSkl4GoocSu3Ak8gAjqpY2Wy2QytS8/Pzsgt9KIyPj5OWlnbkb3V4ePjI9qkEr9dLa2sr5eXlYb83v99PR0cHJpOJ/Pz8U/1eRFFkcnKS6elpysvLw+oCmEwm4uPjmZycJCsr69j7u1wuhoeH5Wt2bGxs2Meqi9v9bP1ZDcw9XkPm128y959eQhcRQdHdTW5XV9epiZXf7yfg3p1Ebbl9h7KcXWK5d3PjdDrva7vsYcJiscjDW+FAsiaRiJTD4cBoNMrrYGRk5LmRsJjNZtbX14M6AVqtloiICIMgCDpRFE+fkXWPeOire1RUVOPFixfNe28TRRG/33+uTnTJvsFqtZKXl0cgEGB9fR273U53dzcul4uoqCjZ4uGw+Ay73X7fs6IeJmZnZw9cjKUYnby8POx2O1NTU/T29pKUlERqauq9jwOvrkJzM3z608fedf2OE32SmnnjNhBLiSULi9XA4o9+xHZOKQ6vgk3bHJOTW6SlpR26Y5ciI8IlSIIgkJKSgtVqpbOzk8XFRQoLC088EaNSqairq6Onp4eenh7KysrCutBlZ2fT19fH4ODgkT5bUlDzrVu3DixAe1FYWEhvb++hJpipqalMT0+HfK2YmBimp6eDiJUoirhcLgRBYHZ2Fq1Wi8vlwu124/f7EUURh8NBW1sbgiCgVqvR6XRotVqZzIfKCzzKfXpmZuZQrZjH42Fubo7Lly8f9lHJ0oHGxqOzX/1+P62treTm5oY9xSc5saemph7ZqjwKEpk2Go1HtndDITs7m2vXrpGamnroOeDxeBgdHWV5eZm8vDxKS0tPvOjq4naf27Jmou0zH+Ftr/1lfH/y31A88TFyTCZUKhXd3d28853vDPs5RVFkY2OD6enpXd2PIhXQc7m+kqiIg0teUlIS8/Pzp/6czzNUKhWCIBxKHKXPSiJSOzs7REZGEhMTQ2FhIUaj8dwQqf0wm80hPfiqq6slAXvrAz+ou3joxCqUcH1ra+ueJl4eBBQKBRaLRc5qCwQC8gna19fHzs6OLGa1Wq1EREQgCAJ2u/3ErtyvFvh8Pra2to4UP9+XGJ3nnwe/H97yliPv5ln34ZzzEvMaDeu6SG78yT9hyVji4298I4GtLXrLa1CuCbztSh5LcxNcvXqVnJycA7YRoigyMDAQVrTJfkgO6xMTE1y/fj3sKsJeSO2a4eFh2traqK6uPvZzEwSBkpIS2tvbmZycPNI3Sa/Xk5OTQ29vL1VVVSHvYzKZ0Ol0rKyshDyfExMTGRkZoaCg4MCF2Ww209XVxdzcHOvr62xsbOB2u9Hr9fh8Pnw+HwkJCfIQibQ4bG1tUVRURCAQwOfz4XK5cLlcbG9vA7teUx6Ph4iICKKiojAYDKhUqpDkeHt7G5VKdSipHx0dJSsr69DP1e/3093dTU1NzZHtMmlaMDExMSxfMUAmkIWFhafWYs7OzjI6OnoiTd5eqFSqQ6OMfD4fY2NjzM/Pk52dLacOnAZKnQJ1lBLTagQdT6TgePMVUr5xnfknfg61x0NhYSHd3d1hPZfb7WZ2dpbZ2VkMBgNpaWmUlJTwTy3rmAyekKQKdj3abt++/UgSK9gdGJF0VnvXKZvNhtPplNep4uJieZ16NUAKbg8lYP/+979fx//NxMrn8+Xl5eUF3XbUFM95hRTMGh0dTU5OTtBOoL+/X94JrK6ukpycfOBkeBQQTiyIhMNidCwWC2lpaZjN5vA/nx/8AOLioLb2yLtt3NmtDCsyt1j3Gbnxtz8i/Z1R7MTE4IyKpXdNQ2WWAYtJh8VUSFZWFsPDw4yNjZGfn098fDyCILC8vBxWtMlhEASBrKwsYmNj6erqIi4ujtzc3BMtToIgkJ+fz9TUlGzHcNzkoSAIVFVVyQaiR+kukpOTWVhYkL/TUCgoKOD27dshWz9KpRKLxSITL6mVvri4yMrKCm63m/X1dVkDJmmOlpaWsNvtIRc5hUIRsrUoVZ6USqVc2drY2GBmZoadnR2uXbtGQkIC8fHxcitjf8VsL1wuF8vLy0dWq+7cuUN6evqxG8A7d+6g1+vDaqkB8vBHRUXFieNtYLeK1NPTg0KhOLLiGA72Rxn5/X65rbg3CP1eoYtXobdr2fQ70X7uCyjLK1B+5znEvMf5/j//MwlHmHgGAgE5XsblcpGSkkJDQ0NQ5XLG5iEt5vDhA4lcn0czzXtFIBBAq9UyMjLCxMSE3FmJiYmhrKzsVa0tEwRBJlchBOyPA3/1sI7toRIrQRDMJSUlB4Tr6+vrDy2c+KwgCAJmsxmz2Ux2drY8ibK2thbkBSS1Ds9T7/q0mJ2dPVUVR4rRKSwsZGVlhbGxMRwOB8nJyaSmph5NGLze3YrV299+bPDyxh0nungVc7pxJl4cwbm1w1te+1pcg4MMVP4cARdcLHhF/6LVaiktLWVnZ4fh4WFGR0fJz89ncHCQ2mNIXDiIjIzk4sWLjIyMyKaiJ63UpqenB3ldHTeBqVQqZQNRjUZzaGtKEATKy8tpbm7GYrGE/A4iIiIwmUwsLCyErMZIQvjZ2VnW19exWCwkJCRQUFDA6OgoRqPxQEXmNJYLgUBAXuAFQcBoNGI0GrHZbOTm5mI0GllaWmJwcBCHw0FsbOyRBr3Dw8Pk5eUdSnRXVlbY3t4+1thzfHwcl8t1aNVvPyRfuLq6ulNN0i4vL9Pf309+fn7Y1bGjoFAoyMnJYWhoiKioKMbHx0lOTpbtCD7ykY/wwx/+kLi4OPr6+oDdFvm73/1uuSr6j//4jzJB/NznPsdXvvIVlEolf/EXf8Eb3rBrkr0RsCOs6PD7A/z615/lvz79GhK/c5XpX6/ij3/3d/m3W7ewWq1885vflCutW1tbTE9Ps7y8LOt/Qm3GN3f8rDv81Ocd7VOYkpLC7OzsPYnkzwP8fj/r6+uy/YHH48FkMuFyuWhqanrkiKOks9r7vsrKyvD5fBUP76geflZgSOH6o5LKvReCIODxeGQX3ytXrshtkuHhYV566SVaW1sZGxtjY2PjVGPnDxNerxev13tPLVxBEIiLi6OmpoaGhgaUSiW3bt3i1q1bLCwsHMiGAna1Vevr8NajI6K8W34cMx6iivRMeG0MPd+2m/UXHY1bUNPjjaE4VS87Ne+FwWCgoqKC8vJyBgYGcLvdeDyeU7/PvVAoFOTn51NcXEx7ezsTExMn/u7j4+OpqKiQM7aOg0ajoa6uju7ubrmNdtj9ioqK6OrqOvSY8vPzGR4eDvp3SXvT3d3N5uYmycnJvOY1r6GiokJu90pGoftxUpNQv99/KAFaW1vDbDbLMUx1dXVylSUQCHDz5k1mZ2eDzqudnZ0Dgti98Hq99PX1UVFRceRGaH5+XvYwC2fDNDU1xcjICA0NDScmVT6fj+7ubiYmJmhoaDgTUgXI3+n09DTr6+tcvHiRvLw8Wcz/4Q9/mOeffz7oMZ///Od54oknGBkZ4YknnuDzn/88sFu5e+655+jv7+f555/nl3/5l/H7d/P7/vaf/j9Uggrjhp6Z1QU63/pOBL+Irv0qkRoNTz/9NE8//TS/+Zu/yeTkJNeuXaO/v5/o6Ggee+wxSktLD+1wzNh2f6dpsUcTq8TERBYXF0//YT0k+P1+bDYbg4ODNDc3c+3aNWZnZ4mIiKCyspIrV65QVVWFTqd7JAemJGK1FzqdDoPBYBQE4QEaKQbjoX7SUVFRjU1NTea9t4miiM/nO1fC9bPCXn2VIAhERkYSGRlJZmam3MKw2WyMjo4G+YNYrdb7ZrR2VlheXj5T7ZhGoyEzM5PMzMyjY3R++EPQaOB1rzvy+TYGnCCCuVjPjHOH4Z+084bXvx6xv5/h7CbcPmgqPJoURkREEAgEqKysZHBwEIVCQWFh4ZkY2UZHR3Pp0iXu3LnDrVu3KC8vP9Hu0mw2U1dXF7Y2x2AwUFVVRXt7Ow0NDYdWBePj41lcXDzU70mn0xEbG8vMzIzscSXF+zQ1NTE1NcXOzs4BchEdHS1XOfZCpVLJC244OKx943K5UKvVB1pVSqWS7e1t6urq0Gg0TExMMDIyQmpqKpmZmXLQ8mFkqKenh7y8vCO/G7vdzsjICI2Njce2ykRRlCfq6uvrT7z4ra6u0tPTc88u//uPaXl5maGhIcxmMxUVFSwtLR0YDLh8+fIB8fD3vvc9XnrpJQA+9KEPceXKFf74j/+Y733ve7znPe9Bq9WSmZlJTk4Ora2tZGRkMLx4B8ohajWCN73jKf7hOy9R/LaLxH+vmac+/x4u/8an+ZVf+RV+8pOf8Ed/9EcnipeZsXlQKSHBfPR6otFoUCgUR0YjnQdIxtaSj5Tf7yc6Olo25Dzs2PfqrB4lmM1mpqamDtxeXV0tjI+PlwLtD/6oHjKxMplMIR3XH4ih5EOA3W4/1EJibwsjIyMjyNF2YmIiyNHWarViNpvPFdFaXFwkOzv7vjz3UTE6Gd//PsJrXgPHVMo27rjQxqgIWAMsDOyQVZjK2y5fxr2+SXdaNtkxWpIsR+9qJycnSUxMlP3O7HY7PT096PV6CgoK7lmvoFQqKS0tZWVlhZaWFvLy8uSQ8XAQERFBQ0OD7HV1nBg3KiqKoqIi2UD0sEW9uLiY69evExMTE/K3mZGRwdWrV9Hr9Qemw1JSUuR4n/3vVa1W43a7D5A6QRAIBAJhnd+HeVgdNn3r8XjY2dmR/daKi4vJz89ncnKSF198UW6BhsL8/DzAkd/J1tYWPT09YRmABgIBenp6EASBurq6E5GiQCDA0NAQq6urYbWAw4XdbmdwcBC9Xk9NTQ0Gg0GOqApH+7q0tCRX+xITE1leXgZ2w6n3RlylpKQwNze3+xmZAiCAaTUCMn3Mzc3h/+xnEX/wZpJ//B0AeeTfYrGciPhM29wkWzSolMd/tvHx8SwtLZ0rEfvehBC73U4gEJATQrKyssJOdIiJibknP6vzCp1Oh9PpPEzAXsv/jcTK6/UeEK7fb8f1hwWv14tCoQh7RyoIAhEREURERMg/dIloTU1N0dPTg0ajkacOo6OjHxrRCgQCbG5u3veBg/0xOgtdXQgjI8y85S1ol5cP9c/xOfxsT7qJazIy4VlGH23k83/9KWo6dHRq0nH4FFwqPLrq5PV6D5hFWq1WGhsbWV5epr29HbPZTF5e3j3veGNjY2lqaqKnp4eFhQXKysrCzrLUarXU19fT0dGB0+k81v8oLi4Ot9tNe3v7oQaUKpWKsrIyOahZej6/38/4+Dizs7NYLBZiYmIOtKF0Oh0ajYbNzc0DYn9pF73/MZLOKhyycFjFKtTzwq4OMCUlJegzUalU5OTkYLPZ0Gg0XLt2jby8vKBBDJfLxdDQ0JHRNi6Xi46ODqqrq4+tNvp8Ptrb2+Wp4pOQqs3NTbq6ukhMTDzU7uKk2NjYYGBgAIVCQWlpadB3JQgChYWFDAwMnDr/M1QrWXJB94s+tDFKolYNjCdOs7a2Rr97kuq0aAzLWwCybcdJ3qvXL7Kw5qUhPzx5QkJCAv39/Q+VWHm9XrkaZbfbAWQilZOTc+pM25P6Wb1acJiAvaamRhUbG/s48KWHcVwPjVgJgqDOysrS7i+Vb2xsPJJ2BGcx6SiNEEuO1k6nE7vdzszMDL29vajV6iCidRYTO+FAMop8kOJ7nU5H5l0CHl1UxNjCAv39/SQkJByI0dkYdEEAoor0tLoG2Vm0kRgRy87QED2FHyDZrCYz/vhqVXp6+gFiLAgC8fHxxMXFMT8/T0tLC3Fxcfd0EYTdqcnq6mrm5+dpbm6muLg47N/FXq+r7u7uY4NPU1NTcTqd9PT0UF5eHvJ7tFgsREdHMzY2Rk5ODna7nd7eXpKTk7l8+TKiKHLt2rWQn5EUzLxf7G21WkMK3yWdVTjEamdnJ+T03OrqKsXFxQdun52dDekYv7a2BkBVVRUul4vBwUGmpqaoqKhAp9PR1dVFcXHxod+pZABaUlJy7LSo2+2W22DhOujDLjkZHx9nbm6O8vLyM9nIbG9vMzg4iNfrpaCg4NBJRGnjtra2duS0Ynx8vDxJurCwIJ+zKSkpzMzMyPebnZ0lKSmJ5ORkpqamcGkcRK1GsOrZorS8AJd6GNQa/GsOYPcc3djYCNsHDGB+1YM/AKlHTATuhdFoxOl04vf7H9i10+PxyCRqdXUVQRDkTUpeXt6ZSWJUKhWBQCDsSvCrCVFRUXJHR8JdU++ih3VMD7NilZmTk3NgG+NwOM40fPm84H5YSOj1etndHHZ3zHa7nbm5Ofr6+lCr1XLrMDo6+r6JFxcXFx9OiXlzEwBjYiLl5eX4/X4WFhbo6ekhEAjIMTobd5xozEp0CSputnTwpxd/ldjPfJQGcxPrAS1vLDp6IjMQCDA7O3tktIkgCCQnJ5OYmMjMzAzNzc0kJyeTlZV1T597UlISFouFrq4uFhcXKSoqCuv5BEGgrKyM0dFRWltbqampOfJxubm59PT0MDw8fOi0XEFBAdeuXZN9p+rq6oLacGlpaYyPj7O/Ch0fHy9nx+29qEdHR3Pnzp0Dr3OSyUCn03mAmLndblQq1YHFcWNjQzYV3Y/BwUGKinavwzqdjoqKClZWVrh16xaRkZHo9fpDiW0gEKC9vZ2srKxjDWO3t7dpb2+nqKjoRBvInZ0dOjs7MZvNXLx48Z4XfqfTydDQENvb2xQUFIRldJuTk8PY2Bg1NTWH3uepp57i2Wef5ZlnnuHZZ5/l6aeflm9/3/vex6/92q8xPz/P8PAwZrOZ4eFhNBoN28IGxu04Vp1bPPlz+Xj9U6j9OrwbdrRaLf39/Tz++OMn2rxJwvVwiRXsVotXVlbu2/XM7XYHESnJeDouLo6CgoL7KjCPjIxka2vrVWdldByMRiMOhyPotrvkP3wWfsZ4mMQqr7y8/EC9XApNfdSwvr7O/qDps4ZOpyM5OVnWgEg/4oWFBe7cuSN7C0lahbP6EdtstiPdvO8btnbbBNwl4kql8kCMTvOLN4gazSKyUsWqf5uO528AUB0ZRXfSBayRKgqSjz7fpJ13OJ+XQqEgPT2dlJQUeYJJ8us67WKo0+m4cOECU1NTXL9+nbKysrB27oIgkJubG2THcNhvSyJira2tTE9Ph8z5W19fx+fzYbfbeeKJJw68H0lrlZmZGbTTVigUxMbGBulvAJn87HdMNxgMbGxsHPv+ILTG6jB91WHvy2azoVarDyw4sbGxVFZWcuPGDaKiokK2HUVRpKuri9jYWHmDcxhWV1fp7u6mqqoq7MVNFEVmZmYYHx+ntLT0nlMb3G43w8PDrK6uBnmzhYPo6GicTqf8Obz3ve/lpZdewmazkZKSwu///u/zzDPP8K53vYuvfOUrpKWl8a1vfQvY1em94x3vID8/H1EU+ZVf+RUMBgMXL17k2Wef5cu//VX+fe0zJEQmIfqvkR7bgKB8kai7G5a/+7u/45vf/OaJ3uuMzYPFqMSoC/93l5CQwMzMzJkRK2mza7PZWFtbQ6VSYbVaSUhIoLCw8IFO6kkTdI8isdpbDZUQFRWlFATBKIri4aPP9wkPjVgZjcaS0tLSoNKUNPb8avdzCoWtra0HXonTarUkJSXJO3qp7Ly8vMzg4GBQ2dlisZyq7Ly9vY1er39gpfMg3K1YEaL1IsXomGYTWBa32TAv0dw/w9CP20nPiUWry2FFYeLpQiMKxdHn28TERNheRBKUSiXZ2dmkp6czNjbG1atXyc7OJjU19VTntyAIZGRkEBsbS2dnJ1arlfz8/LDK+qmpqeh0OlpaWqipqTnUEkMQBKqrq2UD0b0VlYmJCWZnZ6mvr2dhYYGhoSG5wrP3PWdlZTEyMnLg39LS0hgYGDhgYyDprPbertfrwx59DzVBHGr6KRAIYLPZDrQHRVFkcHCQioqKA88tBSDX19fj8/loaWmhrKwsiNwMDg6iVquPHdxYWFhgeHiYCxcuhD3k4Ha76e7uRqPR3LPZp9frZXR0lKWlJXJycigpKTnxeSidg5OTkxQWFvIP//APIe/3s5/9TP67KIqsr68zPT1NU1MTP//zP09aWlrQOVhTU0PR/y5j5G9WMPvNKBQaClLfREDzP4hSqxkbGzvx+xVFkRmbh+yEk03cR0dH09PTc2oDZ0meYbfbWVtbk+UZycnJYeWK3k+YzWZmZ2fPlTj/LGA0GkPaxhQVFQkDAwO5QOeDPqaH1myNjo6u3t8yCFdX8WqDz+dDqVQ+9N62RqMhMTGRkpISLl++TH19vewndPPmTa5evUpfXx+Li4t4vd6wntNut58qUPhMsK9itR9+VwD7LQdRRTpKHyuhb2uKmdYhmh7LotdUi0EjUpJ69IV3bW0NjUZz6ok/lUpFfn4+Fy9eZGtri5dffpn5+flT+5RFRERw8eJFVCoVzc3NbEmfwTGQqi9tbW2srq4eeby1tbXcuXOH9fV1AoEA3d3drK2t0djYSEREBNnZ2aytrYV8ntTUVJaXl3G5gvNPTSYTHo8Ht9sddHsoP6twvawO+wxXV1cP6IAWFxeJi4s78BtcWlqSp3H3Y2RkhJiYGKKjo4mNjaW+vp7+/n55vHtyclI2Cj1qEZ6YmGB8fJyGhoawz6PFxUVu3LhBWloaFRUVpyZVPp+PkZERrl+/jl6v5/LlywfE+ydBcnIyi4uLx1piuN1ueUMxMjJCfHw8V65coaioKORnrbXu7vEjNiJISXsdOo0JUaPBub7On/7pn574ONccfrZdAdJiTkasFArFibzUpMp4Z2cnL730Ep2dnTgcDlJSUrh06RIXL14kPz+fmJiYh0qq4BUt0qMGjUYTcr2qqKiIAPIOPuL+46FVrPx+f+F+l1uHw/FIEquNjY1Tx5/cT6jVahISEuTdvdfrlT1SRkZGgkZ7Y2JiQgp3bTbbfW9xHgqJVBzy2dpaHfhdInGXI+lwjPHysz9EpVbyROM7mNAnUh3r5EbztSNjdCYmJsKOIzkKGo2G4uJiXC6X7OJeUFBw6CTjUZBafHFxcdy+fZuUlBSysrKOfZ6oqCguXLhAW1ubPPUWClqtltraWlpaWlCr1SQlJZGdnS0/vyAIVFZW0traSlNTU1A7Q6FQkJuby/DwMGVlZUHPKwmY954vFouFgYGBoPup1eqwiP3+SSDYrcqGmr6dnp4OWa0aGhqirq7uwHNvbGywtLQUNAWo1+tpbGyU9W5er5eGhoZDP3cpU9LhcFBfXx/WwioZkHq9XhobG8Mep9+PQCDA1NQUk5OTpKamnln8jDSZOzc3d6CtGk68zKHPqwWfzknkhp6omCwQBESNBq3Xy0AIHd5xOI2+SkJMTAw2m+3AWrTXAsdut8uavZiYGNLT08+dBc5+PMoCdqVSic/nC/rdFxUV6WNjYyuBk/WQzwAPU2Nl2a8TkWJeHjW8Wiwk1Go18fHxsrnkXjO68fFx2YxOmjw8bIz+gUFqBYaoWPk9AVZubBOZq0WVoODqUj/v/E/v5bU5SlbUb8KidPGWpmwUQvahMTper5fNzc171rXshU6no6ysDIfDwdDQECMjIxQWFp5o2klCVFQUTU1NDA4OcvPmTSoqKo6tiBgMhiCvq/3+UhIksuB2u0MaTxoMBjIzM+nv7z/g+5SUlMTY2NgB/VNycjI3b94MImlSSLLX65WrMtK/HdeO2dnZOUCsQumrXC4XXq/3QCt+bm4Oq9V64Dn8fj9dXV1UVVUdWIBUKhVZWVm0trYeed4HAgG6urpQq9XU1NSERZ6lScvs7OxTV5VEUWR2dpaxsTESEhJoamo6c7Pl9PR0Ojo6ZGK1ubnJzMzMsfEyR2F6qQW3QYFx3cRGwAWCgEelIhLIOcHkpIQZmweNSiAu6uRLXExMDKOjo6SlpeFwOGSN1ObmJnq9npiYGDIzM8+9aXMoPKoC9oiICBwOR9D7umvkW/EwjufEZ50gCEp2TbfmRFF8iyAI7wR+DygE6kRRPNaQSxAEY2Fh4YHX3t7ePtH48asFD0K4fj+gUqmIi4uTtTZ+v18mWlKgZyAQYG5ujpiYmAc/dLC1BWo1hNjVr7Y58O8EiH8sklbHCNsBFzXCBqsVH2R8zcw7kzdR3tVWSe/R4/EwNzfHrVu30Gq1aLVakpOT74vmLyIigqqqKjY3N+WJucLCwhNf8JRKJcXFxdjtdlpbW8NalDUaDfX19dy+fRun00lhYWHQ/be3t2lra6OqqgqPxyMbiO6veKSlpbG4uMjS0lKQ07sUED00NERlZWXQ60ZERLC+vh7UqrNYLAd0UaG8afbjMOH6/mm7mZmZA9eVQCDA6OgoDQ0NB553cHCQlJSUkJrI7e1turu7uXz5MsvLy9y6dYu6urqgnbLX66W9vZ24uLiwTHP9fj+Dg4NsbGwcmLQMF6Iosri4yPDwMFar9Ug3/XuFXq9HoVAwODjIysoKGo2G1NRUCgsLT0U0fH4Xdya/j8X0RiIXE1jzb4EgsOr3YwVyTiEkn17xkGLVHKuf3AtRFNne3sZut7O4uMiLL75IRESEHBQumcq+mvEoC9i3t7eD3ld2djZerzeshVcQhL8F3gIsi6JYcve2PwCeBgLAMvBhURTnw3m+01Ss/iMwAEjbtT7g54C/OcFz5BQWFh44Qx/VitXDEK7fDyiVStl1HHZDZh0OBw6Hg+npaTweD2azWW4d3vfAz83N3WrVvotdwCuy3LyNMVOLKkXBtcV+fvIrX8ZfF40u889I3Z6mIOdge29/jM6NGzdkd/CgGJ0zhMlkoq6ubtcUsb8fjUZDQUHBiX8HVquVixcv0tfXx8LCAuXl5UcurEqlkpqaGvr7+7l9+zaVlZUoFAocDodMqqSLlGR8WVtbG7SwCIJARUUFN27ckDP5JMTFxTE6Onrg3Jc8rfYSK6n1spdYSZYLR51DTqfzwOckTbtJEEWRubm5A8ae09PTxMfHH/iMbDYbGxsbB8T3gGykWlVVhcFgICMjA4VCQWtrKxcuXECpVOJ0OmlrayM7Ozss1/yNjQ26urpISUmhqKjoVAv3ysoKg4OD8rl0v353oiiysrLCzMwMDoeDQCBwoniZwzAy81Pcnk3i0zPZmFQxv+2ESIEVr5dcIOOEGk63N8DShpfLRUdfc0VRZGtrS27tSeuPlGxRVlb2SFy39yIqKkpOEHiUYDQaD+hN7w5VRQqCIIjHi1r/Dvgr4Gt7bvsTURR/G0AQhF8Ffgf4RDjHcyJiJQhCCvBm4I+AXwMQRXHg7r+d5KnyysvLD4ipvF7vPZkqnkdIIbGvtpJxOFhbWyMnJ0degAOBgJys3tXVhcvlCiJa9xr5cgBbWyH1VaudDnzbAeLfEUmLY5g717u49Z2XyEn7j2Snq2iwtaKy1h751IFAAKvVSnV19YEYneTk5DM/T6Ojo2lsbGRlZYXOzk4iIyPJz88/0SKpVquprKyUhc+FhYVHjo0LgkBJSQljY2O0tLRQUlJCR0cHlZWVQTu/9PR0nE4nvb29QXE1sKvHKigooKenJ6jlJQgCBQUFDA4OUlv7ymcdGxtLf39/kAmjxWJhaGgo6NgkAfFRLdKdnR2Z5AOyLmtv62ttbY3IyMig2/x+PxMTEzQ1NQU9n6RvChUv4/P5aG1tpaioKOizSUtLQxRF+d9u375NaWnpsQMdoigyMjLC4uIiVVVVp1rAV1dXGRwcRKvVUllZed82pdLGaXFxEYvFQmZmJhUVFVy9evWe24w7rlVGZ/+NlNgaLIo4NljFZfMiJAm4754faSdsk8/ZvYgipO3TV4miyObmpkykJM9EacI2MjIyqA29urr6SBKr/ZrGRwEREREhJ4nj4+OZnZ2NAVaOerwoilcFQcjYd9vm3pcAwp44OmnF6gvAfwbu6WyLiYmpKC4uDloxfD7fI0k+HlVBvnSR2lvFUSgUWCwWeTEMBAJsbGxgs9no6enB6XRiMpmIiYmRidY9ldalitUeBHwiy9e2MaRqUKRD89IAg1+7SmSUgfTKf09pYJZYkwrhGP+Yubk5UlNTD8TozM7OcvPmTSIiIkhLSzuV+PwoxMbGEhMTw9LSEq2trVitVnJzc0/U1klISCA6Opru7m4WFxcpLi4+cgHMzs5GrVZz9epVqqurQ+oB8/Pz6erqYnR0lP1DJ4mJiSwuLjI7OxvUcrNarYyMjARpDCWn+sXFRbmiIx3bXp2VwWA4YPq3H/tbgaurqwf0VaHagBMTE6SkpBz4TPr6+sjOzj6wAZAMQDMyMkKaeqanp7O5uUlzczMXL148ts3icDjo7OwkJiaGpqamE1/3Njc35cWxuLj4vrR1fD4f8/PzzMzMIAgCaWlp5OXlBbWDY2NjsdlsxwZ+H4U7k99HFEWKMp9Gub37mwys7q5fpRkZcOMGcSfckE3bdidPk61qeaNnt9vZ2dnBZDJhtVopKioiIiLi0N+upLN61KwJ1Gr1iULOXy2IiIgIablQWlqq6ujoyOMYYnUYBEH4I+CDwAbwmnAfFzaxEgRB6j92CIJw5aQHuBcGg6Fyv9WCw+F4JNuAj2p7U2rTHEUqFAoF0dHRREdHk5ubiyiKbGxsYLfb6evrC7rQWa1WjEbjyUhKiIrVWs8O3g0/KU+ZuekYYml2gds/auaxp9+L3qCjZqYNdVroabi9WFlZORCYrdPpyMnJITs7W/bmkWJ0UlNTz+x7FgSBhIQE4uPjmZub4+bNmyQkJMgEKBxIk32SC/xR5pKiKLKwsEB2djaDg4NEREQcaHtK4cStra2y4/9elJSU0NzcfKAFXFBQwMDAQJCWKS0tTY7DkWC1WlldXZUXab1ef8CGYT/2G4vabLagSpGkCdw7nej1epmZmTngor+wsIDX6z3wvkRRpKenB4vFcqj+c35+Xj72lZWVQ4mOKIrypF55efmR0TCh4HA4GBwcxOVynXrg4ShIVZrp6WnW19dJSkqisrLy0EpzQkICc3NzpyZWa1uTzC63kpf6Bgw6K6JaRFSIqFaV+EQ/orSZCNNSJBAIYFtdo3vMgVEd4NaNq0RFRWG1WikpKTnRRs5kMoVtZfJqg1qtPvDbebVDmnjcj/Ly8kilUpkPNJ/meUVR/CzwWUEQPg38B+B3wzqeE7zGReApQRCeBHSASRCEb4ii+O9OerA+ny9v/07gUa3sPKrE6jSTjoIgYDabMZvNZGdnB5XmpbF0KcXearUGleZDYmsL9iwuol9k+eoW+iQ1ikxoWR5i6h9aASi58itcydej7l1BXVtx5HFubW0daXoqCIJMGKUYnd7eXgKBgNwqPAtHZUEQSElJISkpienpaa5fv05qaiqZmZlhjc5LlYaYmBg5DqWgoODAYwcGBjCZTBQWFpKcnExHR8cBI0zYJco1NTXcuHEDrVYb1IZTq9WUlJTQ2dkZZEFgNptRqVRBpMdoNOL3+4M0VJKflbRIH+clJEkm9p4fq6urQXE6CwsLJCQkBN1nbGyMjIyMoO/H7XYzODgYMtB4eHhYtrcIhbGxMZaWlmhsbESpVHLz5k0iIyMPkA2Xy0VXVxcGg+GARcVxkAKgNzc3yc/PP/MqqdPpZGZmhvn5eUwmk+ydddxrWCwWent7T2WmKYoifWP/hFYdSW7q6wEQlAKYRYwbejb9O/zByy/zFwAhKhGwS6TW1tbkqT2X28PQdhr2HS1vrozkQkHYBYYDEAQBlUr1yBEQeEXofdbE/GFjP2EURZGsrCx1fHx8LfC39/j0fw/8C2dNrERR/DTwaYC7FavfOA2pAlAqlVE9PT34fD5gd3fq8XgwGAzMz8+j1+sxGAxoNJpX/RTG9vb2PZXKzys2Njbu2UJCEASioqKIioqSidbW1hZ2u52hoSG2traCiJbJZAo+HzY3ISND/t/1PieeVT8Z743ihmMQj+jjteUN2N+iIiXVSpVxmzVAfcz3sbS0FHakxd4YHafTKROgqKgo0tLSziScWqFQyIG9ExMTcmxMWlpaWG0kg8FAY2Mj4+PjXL9+nYqKCrmqMjs7y9bWluzlZDKZqK+vp62tjZycnAM5fFLAc0tLywEtVkxMDIuLiwe8vwoKCuju7ubixYvyZ5GamsrMzIxMhKS2oQStVnvATHQv9i94Xq8XURSDKnrT09NBVhBut5vFxUUuX74s3yaKIt3d3RQWFh5ot0qVm1CaK1EU6e/vx+12U19fL38PNTU13Lx5E4PBIOtz5ufnGRoaOlGQtvQeR0ZGsNls5ObmUlZWdmbXQ7/fz+LiItPT0/j9flJTU0/s7q5QKDCZTKe6FszburBvjlGR+z7UqlcqnGqrEqPNwJrPQcvCwu6Nd4mV3+8PIlJerxez2UxMTAzlFRX8S6eLhW0nb66O4kLevW9mJUPNvRuIRwGPCrESRRGXy8XOzg47Ozv4fD46OzsJBALytWNzcxOtVnsqk1BBEHJFUZQuSk8Bg+E+9p631YIgvB34SyAW+BdBELpEUXzDEfdXZGZmBiThaCAQwOVy0dfXh8FgYGtri+XlZXZ2dvB4dk3etFqtTLak/xoMBnQ63bknXo9qJW59fZ2MPaTmLCAIAiaTCZPJRGZmZtD488jICFtbWxgMBploRW1tIdxdvMSAyNLVLXRxKhS5IreWhynVp6MtzOc12qd5XRkEVmaB44nV4uLikUGzh0Gv15Ofn09eXp7cUunt7SUxMZG0tLR7ntZSKpXk5OQExeTk5OSEZQkhCALZ2dnExsbS1dUl68ZGR0eDCI/0PiSvK6fTecAyQKfTUVNTQ1tbG/X19UHvq7CwkOvXrxMbGysTi8jISCIiIoIIa3JyMtevXyc3NxdBEFCr1QQCAdnk7zgvq/36qrW1taCFYmdnB1EUg357IyMjZGdnB5HRmZkZNBrNASItGV3W19cfeH2/309nZycGg4GqqqoDYv7Kykpu375NfX09fX19AFy8eDHsyofX62V8fJyFhQWysrJOPS24H1Irfnp6GrvdTnx8PKWlpfdUUU9ISGBxcfFExMof8NI/8R1MhiTSEoLtLvQxaozjehY2Vpi+G8S9ODLCWHMzXq9X9tFLT0+XpxEDosh3W9bom3by+grTmZAqeMWa4FEjVhEREaytrT3swzgWUlXb6XTK5En6+96izF5OYDabZR9CQRCw2+0888wzx46VCoLwD8AVIEYQhFl2K1NPCoKQz67dwhRhTgTCKYmVKIovAS/d/ft3gO+c4OExVqtVVtdLEQKCIITUqYiiiNvtlj9Qp9PJ2tqa/IHDbglwP/GSPvCHHSPg9/sfaNDmg4C0U7jfvlWCIBAZGUlkZCQZGRmIoigb9o2NjVG6tcWa3c7myAiGNTPuFR9p74zm+vYgfjHAwnf7WRDqiLMsUJFVzXp/B4Jej+II2wSPx4Moivf03gRBkHVjPp+Pubk5bt++jUKhIDU1lcTExHs6L9VqNQUFBWRmZjIyMsLY2Bh5eXkH2l6hYDKZZFPRq1evHhqXolarqa+vp7Ozk76+PoqLi4Oe22g0ypqrxsZG+TmUSiUVFRV0dXVx8eJFmcTk5+fT1tYmh/6qVCpMJlOQ4NxisbC6uipXdSQH9lCEZL8Vg81mC2pd7hetSxlue93Xd3Z2GB8fPzAduL6+zp07d2hoaDjw2/V6vbS2tpKYmHioI79UhX3hhRcoKysLy3YBdq8Vk5OTTE9Pk56ezuXLl89koMftdjM7O8vs7CwGg4G0tLQD052nRVxcHGNjYwf0iEdhfP5ldlw2Gkv+Awrhld+Bz+cDrRelX8GNF1uwAzs6HeYbN6j57GdDDnCIosgP29bpmnTyeGkkTYVnN8UXFRXF0tLSmT3fecFhocUPGl6vN2hd3/tfyR1+73oeHR1NUlISBoMh5DVrcnLywLXbYrHg9/uPLc2JovjeEDd/5bTv7WGs+IlpaWkHftGHLdSCIKDT6dDpdIeKPb1ebxCjXVpakomX9AXtr3ZJf7+fpMfj8Zy56/F5gPRdPehqoSAIcq5beno6lJYSs7SEW6tluWsDNGq6Hbe5tT2LqneDX/3oJ3jjh/+AP/z0axEEAd/SEuq4uCOPe7/Z5b1CpVKRnp5Oeno629vbzMzMMDIycmSMTrjQarWUlJTgdDoZGhpibGxM1uAcBYVCgVarJT4+nuHhYbxeb0h3dYVCQVVVFQMDA7INw15CaLFYyMvLo7W1NSiyJSoqSn5uacE1GAxYLBbm5uZkgbjkaSURopiYmCCDT0lnFYpY7a9Y2e122YRXEuPvJUxDQ0Pk5eUFVcI6OzspLS0Nugbs7OzQ2dlJXV3dgYXc6XTS2tp6ZByQ3+/nzp078vEdVq3OyMggMjISpVKJSqXin/7pn+jq6uK///f/zvLyMhkZGfzjP/6jfM373Oc+x1e+8hWUSiV/8Rd/wRvesNsU6Ojo4MMf/jBOp5Mnn3ySP//zP0cQhHuKlzkJ1Go1KpXqWM8xCW7vNkNTPyLeUkx0ZC5LS0vYbDZWV1cJBAKY1xKBCLxuFz5gtq6OvJ/9DIaGYF9EkiiK/Oj2Bu1jO1wqMvJY8dlaI0RGRoacNHu14yRZiKeFKIp4PJ4DhGlnZweXy4UoiqhUqiDiFBsbK///aTaeOp3uQCXu7ibugS/CD4VYpaenH9h63EtlR61Wy7vEUPD5fEElRbvdLv/d7/fL5G0/6ZKY8WkXvv8nXL/PqKlB+eUvk5aURCByA7fXh6IwkcD2DL3/eA2lSsOV1+ej9xt2NRlLSxj2OIGHwuLiYpDB5FnCaDRSWFhIQUHBoTE6p4Fer6eiooLt7W0GBwflmJzDNiISwbt06ZKsFVpcXKS8vPzA5kYQBIqKipiYmKClpYW6urqgzYJkQ9HZ2Ul1dbX8W8nJyeHGjRusra3Jx5GXl8fNmzdJSkpCoVBgtVrp6+uT239Wq5WxsTH5uaUFINS5trOzIz+vz+cjEAjIpMFutxMVFSVfT7a3t9na2grSW42Pj8seaxIkl/mKiooDhGhzc5OOjg7Ky8sP1aasra3R3d1Neno6JSUlbG9vc/v2bS5duhSy8vTCCy/IOqqdnR2uXr3KW9/6Vp555hk+//nP8/nPf54//uM/5s6dOzz33HP09/czPz/Pa1/7WoaHh1EqlXzyk5/ky1/+MvX19Tz55JP88z//MwUFBfcUL3NSSO3Aw+KRJHi9XroG/xmf34lrNY2bN2/Kld28vDzUajVj315hxbBFlNXEpZISfHV1cPs2fP7z8Pd/Lz+XKIr8tHuTlmEHDfkRvLbMdOYbPUEQUCqVQTYgjwIUCgWiKJ5q6ECC1LUI1aaT9E0ajSaIOCUmJsoSnvthrSSlNexHRESEQhAEnSiKB//xPuGBEytBEJLS09OD5nePN0W9N6hUKrmlFAqSzks6Qba2tlhaWmJnZ0c2HdRqtSGrXkdVbra3tx9JfdXGxsb5iESorYU//3O4c4eAPwlBKbCh2P3trC2uYUnMJDHWhynSwmJfH9EeD1Pb2ywODhITE0N0dHTQzsjv97O9vX3fTQEFQTgQo9Pa2opGoyEtLY34+PhTXXiMRiM1NTVsbGwwMDCAQqGgoKAgyDpBsg8oKyuT33t5eTnLy8vcvHmT/Pz8A4J1gMzMTHQ6HTdu3Djg7p2ZmYnT6aS/v5+SkhJg9+JdUVFBe3u7PAUnVclmZmZIT09HEAQSExOZn58nLS0NjUaD3++XzUMl9/VQ2Fsh2a+vklppEoaGhigoKJB/p5ubm8zOzgZVtPx+P62trSEJ6crKCv39/dTU1IQ8NwKBAMPDw9hsNmpqauTNVGRkJElJSYyMjBxwg/f7/dy8eZPMzEzq6+vR6XT88Ic/5KWXXgLgQx/6EFeuXOGP//iP+d73vsd73vMetFotmZmZ5OTk0NraSkZGBpubm9TU1DA5OUldXR3f+MY3+OIXv3jqeJnTICEhge7u7gPEyuPxyELz1dXV3QVdt+uhlJYVRXbK5QPP5Vr0smF18NjjV/jQ/8pi86c/RfzoRxH+8i/hD/8Q7rZfX+rb4vrANrU5Ebyx8v5FzZjNZjY2No41fH214bjIqEAgEJI0OZ1OeU3U6XTyeihF/xgMBlnf9KCh0+lCDrwkJSWJQ0NDicDEgzqWB06sLBZLdnJyctDr+ny+h7ojkFqFh/m1SDqvvSeYVPWSGLJarT6g8VpbW3vkhI+wa0ew3+/noUBy9G5vR1Q+haAUsHk3iVToGR0ZJiYxnwitgpSUFAytrbg0GnLf8AbWHA7m5+fp7+9HqVTKu2a/309MTMwDvSjsj9GZnp5mcHCQ2NjYU8foREVFUV9fz+rqKr29vbKoPiIiguXlZXQ63YGqS1xcHGazmZ6eHhYXFyktLT3wm0xMTESr1dLS0kJ1dXXQsRUWFnL79m3GxsZksbvUsh0YGKC0tBTYrWRdv36dlJQUlEolaWlp3L59Ww70jY6OZnV1ldjYWAwGAwvSZNg+7JUO7NVXScHZ0vvb2NjA7XbLv0MpHLmiokImlqIo0tHRQWpq6oE28OzsLOPj4zL52Y+trS26urqIj4+nsbHxAJnJzs7m6tWrZGRkoNVqsdvtDAwMEAgE+J3f+R2USiUf//jH+djHPsbS0pLcYkxMTGR5eRnYNautr6+XnzMlJUWe5jSZTDQ3N5OSksKlS5fo6OgISYzvJwwGAx6PB4fDIRsCr62tyb+t+Ph4CgsLUalUiOJFbvY56Jv4FubIZKxRrwxGBLwiPpvIevk2uco4VHe/M+/734/mS1+CP/kT+NKXuHZnixf7tqjMNPDmmvub3yeFFj9qxMpgMLC0tIRerz9AnKQuzt61LCoqisTERPR6/T11ce4nDpskTk1NVQGPNrHS6/WZ+/UJLpfrvgWGngX26rxCQRRFWeclnaCbm5ssLS1ht9vlsn0ojZder3/VidtDhd8+FOTk7BqEtrUh1r4VQQkrvk2iRT3TkxM0lD6JUa/Cv7WFs7eXiJoaDGYzBrNZFhS73W7sdjtLS0vMzc2hVqu5c+eOXNF6kITfZDJRUlJCIBCQY3TcbjepqamnitGxWCxyTE5HRwdRUVGsra3J1gr7odFoqKmpYXZ2lubmZoqLiw9sDCwWC7W1tbS3twf9uyAIVFZW0tLSgl6vlxf3jIwMbt26xfLyMnFxcajValJSUpicnCQ7O1s2mZWmZyWdlUSsDqtYiaIokxi73S4Lyefn50lKSpIv/IODgxQWFsqPGxoaIjExUa64iqJIb28vJpMpqMoliiKjo6PY7XYaGxsP/EZFUWRiYoKZmRnKy8sPbY0rFApycnLo7e3F6/WiUqkoLy+nra2NpKQklpeXed3rXnek+HtvRd/hcMji+pycHAwGA4899hiCILCwsPBAFzyXyyVXpHZ2dmRRf2JiIsXFxSF1MoKgoKbgI7zc9d9pvfNlHqv8LQy6XRLsWvFCANat27zz8luoKSrhd1JT8apUaD70IfjqV2l//2/w0xkdpel6nq4zo7jP71eaZn01IdR6tPe/0r+vr6/LVSar1Upqauqrcj2SIAhCyO5XRkaGjl1i9cDwMFqBaft3VA9iwux+QhAENBoNGo0m6AK7ublJdXU1Wq1W1nlJpVW73c7MzMyhO4S9/z1POwSpN38u4ocUCqip2SVWVaDQCNh8m5TrM/hR8xDPd24TqZ/G0dYGfj/GPbt+CVqtlqSkJJKSktja2qK0tBSHw8Hy8jKDg7u2JVJFy2q1PhCitTdGx+12MzMzc+oYHantGBsbS19fH06nk8nJSXJycg4laikpKVitVrq6ulhcXKSoqChokTQajbLXldvtlquXCoWC2tpa2UDUarXKQc03b96UiWpmZibXrl0jLS0NtVoti9gLCwuxWq1MTOxuLHU6XUhiJREU2G3h+Xw+eWM2MzNDdXU1sGsYCsitvdXVVVZXV2lsbJSfa3R0FL/ff6BV19vbi9/vp66u7sC57nQ66erqIjIykqampiOFtltbW8zPz7OyskJ1dbVs6yC1FOPi4nj7299Oa2sr8fHxLCwskJiYyMLCgiziT0pKore3l+bmZgRBwGaz8cQTT5Cdnc0f/MEfyOfC7Ozsfa1WOZ1OOR5mfX0djUaD1WolJSWF6OhoXC4X+xM1QkGjNlBf/HFe7vwTbt35Gy6V/zoqpQbnwm6Lad26xfCdQS5eaACFAp/NBr/5m4hf+QrO//5nFP3mf+Xn6qNRKO7/NdFoNAbp/s4D9nZQ9pOmwzooJpNJ/n+FQsHc3BwOhyOs7+vVBGlwY+9vNj093aDVakPHJtwnPHBi5fP54kNVrF7NxOow7DUxDEfntfcHsrGxweLiYpDOa29Pe++P5kH2tM/dd1VbC3/2Z+By4ddpcYs+4tRmXEYrEVE6TNpFHG1taPPyUB0S6QKvXKyk70haAL1eL6urq9hsNkZGRhBFEYvFIhOt++3KrNVqzyRGRxRF7HY7V65cYWVlhebmZpKSksjOzg65Q9Xr9dTX1zM5Ocn169cPVGV0Oh0NDQ20t7fjdDrJycmR/ajq6uq4desW1dXVREZGotPpyMvLo6enh+rqalQqFRkZGYyPj5Ofn09iYiIjIyMUFBSg1Wrxer2yzirUDnRvxXSvvmp7e1uuDIuiGNSC9Pl89PT0UFtbG0RE7HZ7kAGo3++no6MDk8lEfn5+0O9KFEVmZ2cZGxujpKTkyPbQzs4OQ0NDOBwOCgoKyMjIYGZmhoSEBBwOB4FAgMjISBwOBz/5yU/4nd/5HZ566imeffZZnnnmGf7u7/6O17/+9XR2dpKYmMjXv/51nnnmGdbX15mZmaGhoQGlUklkZCQtLS1cuHCBr33ta/zKr/xKWOdDONjZ2QkiUjqdDqvVSlpaGmVlZUGLl1ar5c6dO2E/d6QhkZqCX6Cl/6/pGv4G1QW/gHPRi6gWWfGvsL29TVZWFqq7xKozuxFV3Zu58LOvofjqH6J8AKQKDhdE309Ia0Goibr9ml9pHbBarcdqfvdCp9Nht9vv91t54JDagXu1Y4mJiVgslpwHeRwPo+YXsX9hdrvd52uxPkOES3gUCgURERGHit33T2E4HA65BH/YFMZeI9WzqjCdu0nHmhrwetHM9LMVvbuI9v7bLV7+ST8ZFz+Gxr5OwOEIWa3aC6fTGbK9qVariY+Pl7U3Pp9PJlpjY2P4/f4gonW/Wtr3GqMzOztLfHw8er2etLQ0kpOTmZqakitHGRkZByovgiCQmZlJbGwsnZ2dxMXFkZubK59Lkgt7d3c3vb29sjeSXq+nqqqKjo4OLly4gF6vJzk5mcXFRblVl56eLjvIazQaLBYLKysrxMXFER0dzdraGjExMSiVSnlqUMJe4fpefdX09LSs1VpZWUGn08k6sP7+fjIzM+Xf18rKCuPj40G6KGkqMDU19UD4rsfjobu7G6VSeaRDudvtZnh4mLW1NfLz84m7a+8hiiLDw8M4HA6WlpZ4+9vfDuyeT+973/t44xvfSG1tLe94xzv467/+aywWC3/6p39KamoqFRUVLCwsUFNTg0ql4otf/KL8XX3pS1+S7Rbe9KY38aY3vem4UykkRFEMIlIbGxvygp2RkUFUVNSR15CIiIhjQ7P3I8FaSlHGW7kz+X2ijCkIC5W4Yz04Z9cBdomVw8HAppaftq5T/eH/ROknfgB/8yX4zGdO9T5PCkEQQlZB7gX7p9T3kqe93QvpGi5FJJ1l9+JhEMYHAUnAvp9YqdXqjAd5HA+UWAmCIKSlpR14TZfLdT6mzM4Qfr//TNtle39soca99/bVpR/qwsJCkG+IUqk81M8rXN+Qc+ckf1fArp3owlaxq6V58bs/5l9++BN+7coHEIenUMXGot3nHr4f6+vrYZ2DKpVKnuiD3Yvk2toaNpuN8fFxfD6f7A5ttVrvy4bhsBgdKedNasFJEEVRnhrb+xxZWVmkpaUxPj7O1atXycrKIjU19cB5azQauXjxIiMjIzQ3N1NZWSmTa2n6b2hoiLa2Nqqrq1EqlbJerK2tjYaGBtRqNaWlpTQ3N2OxWNDpdGRnZzMyMkJxcTFpaWmMjY0RFxcn66wk/YcU1i1hb8XKbrfL5rFLS0vk5+cjiiJDQ0NUVVUBuy7qLpdLJl0bGxv09/dTX18vEzZJI1RYWHhAwL60tMSdO3coKCg41L/K6/UyOjrK0tISubm5lJSUBH0HgiCQlZXFxMQEJSUldHd3y//m9/uZm5tjenqaP/iDPyA1NZWkpKQg8vbZz36Wz372swdet6amRnZ3Pwn2phrY7XY2NzdlrU1WVhZRUScThUtyiJNm6+WmvoENxxz9498ja6EIZ6GbndndFm5mZiYTU9v8VEwhzarmje+4At99I3zhC/CpT8E9JhmEC+kcDHdDuf86vPfv0nV4L3GSqk3321dxL46LjHq1QqvVHiCMiYmJ+P3+8Fx6zwgPumJlsVgsB2r75669dAZwu90PVJB/mM5rLySnW+nHvrKyEtLpNlTVS7rIn7vsw7Q0iI1FN92NW/h5dIKasaFR4lOyUCt2UCysY3z88WMXifX19VNlZ6lUKmJjY2UR9948s8nJyaA8M+kCepYIFaPT19cXFKOzurpKREREyN+YSqUiLy+PjIwMRkdHuXr1Krm5uUECcNglUPn5+cTHx8sTdJmZmfKOvqCggKmpKW7evEldXR0ajYaYmBiys7Pl6BuNRkNxcTFdXV1cuHCBlJQUrl69itPpxGw243A48Hq9WK1Wpqam5PfndDqDiJXT6SQ2Nha/34/X60Wn07G0tITVakWpVMphwhEREXg8Hvr7++VgaKfTye3bt6mpqZE/j/X1dTo7O6moqAiyWvD5fPT39+NyuWhsbAz5e/b5fExMTDA7O0tWVtaRbumJiYkMDQ3h8/lQKpVnHi9zFPbmcNpsNtkKxmq1kpOTczCH8xSIiopifX39RHmIgiBQmfcBdlaciF6Bdesm8dpEPvjBD+LTJfLDLRexzmXeXZqKRqWAZ56BK1fgb/8W/v2/v6fjDRdStp7RaAw5IS79d6++ae81VKo26XS6h54EIkGlUuH3+x/2YZw5QlXiYmNj8fl8h+tA7gMeOLEKZT/woEnIg8B5JItqtRq1Wn3oCP/+bKaNjQ0WFhaCvEtcLhdut1tuFUgXj4flXYIgQE0Nus4unIIHqzKSoaEhiurfhErhQK0woN/n2BwKGxsbh0aUnARKpZKYmBjZnDEQCMhEa3p6Go/HQ1RUlEy0zmq6cn+Mzvz8vByj4/P5jo0c0Wg0FBUVkZWVxfDwsOziHrfPqd5sNtPU1MTAwAAtLS1UVFTIZFHKb7tx4wa1tbVERESQnJwsG4hWVVURFxfH4uIiU1NTZGRkkJeXx/DwMOXl5SQnJzM7O0tmZiYej4dAIBDSJVqqWK2vr8tEaHp6mtzcXLnlJtkT9PT0kJ+fj06nk+NoysvLZa3j8vIyd+7coa6uLqgSu7q6Sk9Pjxx2vf/cDgQCTE1NMTk5SVpaGpcvXz520RQEgfj4eLq6unA4HGceL7MXoiiyubkpEymHwyEHmufn5xMZGXnmryl5Pp2EWAGolBoKIt/NIh7mI+coK63gl2o/wf952U5cBLxx6F9Rrr8DEmLh8mVoaNi1XvjYx+CMh0n2ehrutdaZm5uTh1n2expaLJZXTXbtftyLSeh5hFarZWtrK+g2hUKB6gGPOj5oYmWMioo6sJ3br6F4FHAeidVxUCqVcmRMKIiiyEsvvURaWhoulwuHwyFXvfbqvA4zUr1vk4S1tWif/zFu9zqajd2KkTk+C5XCgbm8DsUxrYn7mX0oOYxL7tKBQID19XXsdjvd3d1yG9xqtcqtr3u90KlUKtLS0khLS2NtbY1bt27R29srC4+PitHR6XSUlZWxs7PD4OAgo6OjFBQUBDmUK5VKSkpKWFlZoaWlhdzcXHkyMD4+Ho1GQ2trK5WVlZjNZrKzs+nr62NgYICioiKKiorkoOaEhARGR0dxOBykpKTQ1tZGZmamHIBrMBhYWVkJOkZJYzU3N4fVasXj8bCzs0NUVBQzMzPExsai0+mYnZ1FoVCQlJQkG4Dm5eXJlcnp6WmmpqZoaGiQN3aBQIDBwUHZlmI/8d0rYE9MTKSpqenYSVHJPmN6elrepDz22GNnOvggBSzvtT+IjIwkJiaGwsJCjEbjfV9Ao6KiDvUdOw4BuxYEN6uWHRyDTv7PnB1LpIoPXjSy0e7ZnQyE3Y3Upz8NTz0F3/wm/Lt/d6LXkTaPodp0Pp8vKIVDr9cTGRmJWq1me3v7vhDgh4mjsjhfrVCpVHJA814oHvAY+4NmM5Fms/nAtu7cjO+fIV6NxOo4SG2fw0xPpXyovRctKTA7VD7UfmuJU5fJa2sRxAD6qT78GZbddmh8DhqcGOtee+zDw805OwsoFAosFgsWi4Xc3FwCgYC8IPb19cl6IqmiFRERcU8X862tLbKyssjNzT0Qo5OSknLoOWowGKiqqmJra4uBgQE5JmevDi02NpampiZ6e3tZXFykrKwMjUZDdHQ0dXV1tLW1UVRURFxcHMXFxbS3tzMxMUFmZibl5eV0dnZy8eJFCgoKGBwcpLq6Go1Gw+bmJlarFZvNRmJi4gHLhUAggFKpxG63k5aWxuzsLCkpKYiiKAvSnU4nIyMjNDU1ybmASUlJJCYmylWt9fX1oKDlzc1Nurq6SEpKorGx8YBObWFhgZGREWJiYmhsbDx2Qdrc3GRmZobl5WViY2MpLCzEZDJx48YNfD7fPS1oe88bm80mt0tjYmIoLi6+5/PmNDAajScWsEtwLnjQxqrxuM382Tv+A5kFlbz8o29j1CvZioh4hVgBvPnNUFy8G3Pzvvft2q7cxVH+TYcF+yYnJ8vGl6GwubnJ2traI0Wq4JW22f8lxEopCIIg3u+YF+k4HsSL7EGk2Wx+tEpTh8DlcgXt8h8FHHdOCoKAVqtFq9UeGZi9d6e4srJy5IVvLwE7tDJQUwNA9Pgdmn7zP2NbsvHHP1xFr7yBKgxB+sPMPlQoFPK0X05OTlDlob+/X648SBWtk1YeFhcX5TiX/TE6bW1tx8boREZGUldXx9raGnfu3EGtVlNQUCBXNdVqNVVVVczPz9Pc3ExRURHx8fFERETQ0NBAa2urLByvqqqipaUFnU5HYmIiMTExjIyMkJeXx8jICJubm7KnVXZ2Nl1dXWRlZQURK2koJBAI4PF40Ov1zM7OcuHCBSYnJ6UJIDo6OigpKUGtVtPX14fBYCAzM5NAIEBPTw+CIFBbWyvnpo2NjTE/P09FRcWBVvny8jJDQ0OYTKYDcT774fV6mZ2dZXZ2Vv5s98fLSNl6J2k9S5VOaWpPqnTGxMRQVlZ2Lgx77wbenljADuBc9EKSkkBPIRu2OdKSE1nb7MCor0MVE4PPZgvauPHxjxP9q7/K+hvewGpNDbbiYnaSk1Ht82+SjGbvZeP2KE/QuVyuU6U7nFccRqz0er0I6IH7mz4tHceDeJE9MJrN5kcnzfIInObict7h8XjuWQsXrs5LIltra2vMzc3JpXogpJFqhCmR6PEBjGoT6x1DKJSJRBjCO9WkaJDzAEEQMJvNcgtNEh3bbDYGBwdlEa1EtI7Syvj9fpmY7cVpYnSio6NpaGjAZrPR1dWF0WgkPz9fJhlJSUlYLBa6u7tZXFykuLgYrVZLQ0MDHR0dOJ1O8vLyqK2t5ebNm2i1WvLy8mhubiY+Pp6CggIGBgaora1lcHCQoqIiXC4XCoUiSGQrVRelKc6NjQ1ZFDw1NUVTUxOTk5MYjUZiY2MZGxvD7XZTVVWFz+ejo6OD6OhocnNzEQSBnZ0dOjs7iY6OpqmpKYgAra6uMjg4iFarpaqq6kgrlJWVFaanp9ne3iYlJYXa2tpDq4EJCQkyaTwMfr8/iEh5PB45NHqvru28wWQysbW1daJNpXfbj28rwJ3NAJvCHAG/j8z0RG4PfZ35iSXi7Hbw++l/+eVXpAaPP476/e/H9JOfYP63fyMLICEBHntsV4f12GO7gy1nUGWSWmaPGrRaLR6P52EfxpniMGIVGRkpAkYeUWIVaTabg9jGA6rMPXA87PzD+4EHET10nM5LEpdK5Gtra4vl5WWyrZkYF+b49Y/9KuqFNRI/+EUUigAzMzNBfl6hSIjL5Tqx4PZBQRAETCYTJpOJrKwseUzeZrMxPDzM1taWPN0VExMTNN0leTwdVeE6aYxOTEwMFy9eZGlpidbWViwWC3l5eWi1WnQ6HXV1dbL9Q1lZmRyB09vbS3d3N2VlZdTW1nLr1i1qa2upqKjg9u3bciDy+vo6sbGxLC0tyToryUcIXhGu22w2YmJiZO+q8fFx0tLScLvdTE9P09TUxPz8PEtLS9TX18seVenp6aSlpSGKIlNTU0xMTMjHKWFzc5OBgQEASkpKDiXdDoeD6elpFhcXsVgsZGdnH6lfk2AwGPB6vXi9XvkaIU2TSkTK6/USHR0t6+LOK5HaD71ef2h1Z/9wjOwWPu8ngiTWleBL3v3c46Kq0Sp3WHL+mCi1ibQn30fm3YBvGd/4BogiDA3B1avw8su7f775zd1/j4l5hWRdvgxlZUFtw3DxqLUAJRxGQl7NOOw93ZUwRALLD+Q4HsSLSIiIiIiOjIwMOrMlvcSjhv8nyL8/2BuYvXdX7HIs40hJR6lV8c2Xf8p//IBIAB9ut1vWeUktpf3j0BsbG/j9ftnt+zxDEATZHT4zMxNRFGWz2NHR0SA/otXVVTIyMsJ63pPE6AiCQEJCAvHx8czNzXHz5k3i4+PJyclBrVaTnp5OTEwMXV1dWCwW8vPzKSsrY2RkhNbWVmpqaqiqqqK9vZ36+npSUlLkTL++vj5KSkoYGBggMTERu90elBkoGblKmq7R0VHy8vIYGBigqamJlpYWysvLWV9fZ3R0lIaGBnZ2dmhvb5f1Xm63m66uLnQ6HU1NTfLv1OFwMDg4iNvtpqCgIKT9hjRxOTMzgyAIpKWlkZeXd+LzJiYmhtHRUWDXi8vv98tEKiMj46H/zk4Dr9eLKIosLy8f0Foepm9KSkpCk6ljuNVGpBei/XUolUo2l1cp6kzgTs4mIzUOYlP1hGx2CgIUFOz++djHdonWxMQrJOvll+Gf/3n3vmYzXLr0CtGqrIQwr9FS5fS8Xx9OApVK9ci1OA+zkTCZTAK7FasHcxwP6oUADAaDdX9b4lEkIIDsVfMo4TwQq5AQRTRrM3iLLpOSl8GWcwfHxgoOq4vs7OwDO85QBn7j4+O4XC55ATjMSPW8nauCIMgVPskoU3LQlvyKJKJltVoxm83HDoocFqMTHx9PWlqaXE0UBIGUlBSSkpLkKlVKSorscN7Y2Mjo6CjXr1+noqKCvLw8mbDV1dVRXFwse1y1tbURHx8vG/y53W5MJhODg4MYjUbZcmFnZwez2YzL5ZJH+8fGxsjKymJ8fJy4uDiUSqXslbW9vU1XVxdVVVXy1JrUapT82JxOJ8PDw2xublJQUHBgOEMURdkjbGNjg8TERCorK0+ka9rr2C+19iRvsKysrHNvNyPpm0JN1O0dTBEEQSaJsbGxYRsQq00KsvR+hh1xvPcXf52KrTXU27E0Fvwyt1a+yc2+L9JY+h+wmI7RpQkCZGXt/vmFX9i9bXo6uKL1gx/s3h4ZCRcvvkK0amrgEPmGpEc6V+bI9wgp1eBRgqS/3I+7Q3Oh8+TuAx7oKqHRaKL3t3geZWL1qL0vt9t9Pi8si4sovG5EQyYJ2bvu2ra5ETxpKnZcdiL0wZluarWaqKgoecJteno6yJVc0ibt9bHZHzkhjWSHMlJ9mK0DQRCIiIhAq9UyNTXF5cuXZaI1NTVFT0+PbN5ptVqJjo4+lGjtj9FZXFwMGaOjUCjIyMggNTWViYkJrl27RkZGBunp6eTm5hIXFydP22VnZ6PVarl58yY1NTVkZGTQ0dFBeXk5bW1tVFRU0NvbS0pKivy5x8bGBhGryMhI2VpBsnIoKytjenqa6upqOadwY2ODwcFBLly4gFqt5vbt2/j9fi5evCi7hI+MjGCz2cjLy6OsrCzou3M6nczMzMiGo2lpaVRUVIT1/Xq9XtnVXMpkk6KPpFzFlpaW+xqafBLsj8zae/4fFpmVmJh4IDJrc3OTkZGRsCulEvSJGjy2HchcJPOxXyXd9hIx73k96thYmhL/E9e7/yc3ev+KxtJfwWLKPNmbS0vbtWWQrBnm5+HatVeI1qc/vXu7wbDrkfXYY7t/6urg7kZScio/l9e/U+JRbAUehqioKBWPasVKoVCY/2+pWMGj15v3+/3n87uamADAZ0rDGr8bOWKfH8EXyGN9e/oAsdqLUBo/Kdz2qMBsyURQ0nktLS2FDEkN5ef1IM6LjY0NmThKRpRSpIvT6cRutzMzM0Nvby9qtTqIaIWqLiiVSpKTk0lOTpYJx/4YHaVSSU5ODunp6YyNjXH16lWys7NJSUnh4sWLDA0NcePGDSorK6msrKStrY3y8nIsFgvDw8Ny5IvJZEKtVjM+Po7JZEIUxaBWoMPhICoqivn5eRYWFsjOzqa3t5fy8nLa29spLS1ldXWVubk5Ghsb2dzcpK+vj5ycHJKTk/H5fAwNDcmPLSoqCgphXlxcZHp6Gr/fT2pq6pHZgBI8Ho9MolZXVxEEAYvFQkxMDHl5eSEf7/f7zzSD7ijsDXnfb0MQKuQ9IiJC9lU7ifnvaSfo9IlqNoYElGkT6CcEvuGKJUdrwgrotWaayv8T17u/wI3e/5+9946PKyHP/b9nelMZzaj3Xi3JliXbctlCCYFd2sJSsiQQUoH0exMuN4Hcm0sSEtK4/AK5IVxCIJCFsCwElrLFa8tNki3J6r3X0YykGWmKppzfH+NzdkYaVcuy7Nzn89HHu9LMmdPmnOe87/M+z//eH7mKREYGvOc94R8Amy2aaH3qU+GWolYLp07BI4+QkJtLMCEB9pHOcFTxn4lY3RmaezgrVoIgJMQiVg9by+xhxZElwSMjAKybczGp4igrK0MZWicY1LO8OkFm8okt37qf6c1InVcsxIq9kKovkbEXGycbpX8P4ka7nYWEXq+XswYh3OKV3KW7urpQq9Vy69BsNm865nq9npKSEoqLi7eM0SkrKyM/P1+OySkpKaG8vByHw0FzczMFBQWy11Vpaam8nwKBACkpKYyMjMj72Ov1ytNLUjZjfHw8qampzM3NAZCZmUlPTw8FBQXYbDZcLhf19fVyi+/UqVNoNBpGRkaYmJggLy9Pjp8RRVFuee42Xsbn80URKckINiUlhbKysl19T+Li4lhdXT2QidRAILClf1NksK90jiUkJJCeni7bmBwU2d/vBJ3CO4lAIonLBkLO63z+9z9GavINPv6BelRKAb3WHEWuzh77TczxeQeyziQnwzvfGf4BWFqCpqbXiNanP01eKISoUoWzSaWKVmMjHJFp4v3gYY21gc2O8neG5h5OYiWKYtx/llbgw4gjS4LvVKzWE7MILi3T29vL331rBNE/xtLK7W3fei90Y1KrcKvlRgZmSzdAp9MZM6g1lpHqbr4ve4no0el0cjUKXiMNs7Oz9PT0oFQq5epLUlKS/PlbxehIou709HQqKytlDZPk4n7u3Dm6urqYm5ujrq6O27dvk5GRgc1mw2KxMDIyIlfA3G63HG8jXSyl9pTJZCItLY3FxUXW19dJSUlhYWEBtVpNSUkJ165dIzs7m/LyciYnJxkdHSUrK4vz58+jUqnw+Xyy55Qk0t/KXVsin4uLiywtLaFSqbBYLKSlpVFeXr6va5iUrbcTsYp1vkT+Gytg3WKxkJ2dvevz5aCwH4LmamrCe70J+ACJiyaK6msB6O7p40dtJTxxMhEAvdbM2erfoun233Kl839ztvo3MMflHdi6yzCb4cknwz8ATicz3/42pps3iW9rg89+NmxOqlDAiROvEa1z58LvfUDwsFasJJ1V5L0qPj5eqdPpdjY1PCAcKqMJhUJx/xlagQ+zhcSRPFajo4jp6QSMGgRHuNpj0KtZdRpYcY1vm4d1PwT5uwnMDgQCUTdPqXW3VQUi8l8pgmOrVuZO0Gq1ZGRkyPofqc21sLBAX19fVJsrKSkJtVodFaMj2RAMDg6SlJRETk4O1dXVrK2t0d/fz+DgIGVlZayvr9Pa2kpJSQkzMzMYjUZmZ2dJT0+XJzklSJUltVqNUqmUCZbk0g5gs9mwWq2EQiE6Ozs5fvw4TqeTy5cvk5qayrlz51AqlXK8jM/nIysrizNnzmyqWkr73G63s7S0JLdLMzMzqaqqOpAHjPj4eGw2W1SFcyNp2qrCmZCQIAemH7XUit1O0ImiiPMnP2H1yhWMlVUsjgaxLMZTdjLcsjYFJmgeXCPHqqE6L1wdNuiSOFf92zTd/huu3L6H5CoS8fGsP/449sceIz4/H9bW4Nq11wTxn/88/NVfhYXz1dWvEa3z58PVsCOKh5VYSdsVef7FxcVhNBq31oQc9Doc1gcBhEIh/cb2ycM2wgpHWIt0lzjKxErIzydkDqFZUvNv33qWP/4vf8iv/+FX8Iu+mAJ2CUd10lGlUu2o84q8Aa+srDA3NyfrvFwuFy0tLTGrXnsNzNZoNLIVA7wmzF5cXKS/vx9AJlpSDE95eTllZWWbYnQqKyvx+XxyoO2xY8cYGRmRL4ZarZa5uTn0ej0mk4lgMEggEJCrVhD+fklTaNLE4Pr6OhkZGczNzckC8fb2dtnY1Ofz0d/fj81mi4qXkSC1axcXF1lZWUGj0WCxWMjKyrprIiUdq43VJqfTKedtSpo86ThZLJZD1eQdJHYzQScGgyx/73u429ow1teT8Ja3MPCVURJtYfPb5ORkcI2TY9XwvZZl0s1qkhPCOrUwufqdCHL1m5jjcu/pNqlUqteIvtEIr399+AfA64UbN14jWv/4j/C5z4X/VlHxGtG6cAHufIeOAh7GqUAIb9fGFuedB85D69seditQsfEC9TDmBB7Zltld4igTK86fR2URiBvXM2cJMDMxyOz8PFWlbCtgf1AnfRQKBUajMea6i6LIq6++Sk1NjXwTl7yuIqe8pCrIRpH9ToHZarWatLQ00tLSgDDRcjgc2O12BgcHCYVC8gSc1WrdMkZHrVbT39+PVqslPj6eqakpzGYzPp+P1dVVAFncLZmE+nw+gsGgXGFyOp0Eg0GSk5OZmpoiNzeX6elpvF4vNTU1sqZL+kxJqO52uxkfH8dut8vu7Varldzc3F1ZUkRCqi7GEodHVhelfRwXF0dqaioqlYqOjg7Onj276896ELDTBJ3o9+P41rfw9vUR9+ijxD32GIIg4EnxkjSeQMgvUlZWRn9/P391Nokv/GiBbzY5+JU3JqNV36lIS5Wrjr/laufnOHvst0iMy7ln27RtdUene408/dEfwfo6tLa+RrT+5V/gC18Iv7a4+LXXPvIIZGffs3XeCVIV+GFDrO1SKpUoFIpDuynv+i4pCIISaAWmRVF8QhCEJODfgDxgDHhaFMWlHRazKWT6YTywDyNZhCNaXfT7YXIS8vPRWdUI3UpS88Oi7NmZcQjC0vLIlgL2h7G6KAnypZt5LKPLSN2ORARmZ2ejfIk26nYi/zvyPFCr1aSmpsq+UJJnk91uZ2RkRPY1slqtNDQ0yO7oUusuLi6OyclJ4uLicLlcsv5JqlAFAgEEQSAQCMjHy+fzyesg3cg1Gg02m43s7GxsNhvt7e1kZmZy8uRJgsEgdrudtrY2nE4ner0eq9VKfn4+CQkJ235fI/fTVvqmSOIkVZt28j2TjsHDhu1E0SGvF/vXv876xAQJb3kLplOn5L+tJnuwiIl45/186lOfQqVSEW9Q8q5GM1+9aOf7Lcs8dcYsV/AMOgtna8JWDFc6P8fZY795z8jVntpmGk1Y2N7YCB//OAQC0Nb2GtH69rfhS18KvzYvL5po5ecfSAzPf3Zs5BV3Hs52vHkJgvBl4AlgQRTFqg1/+y/AXwLJoiguxnq/hL3cUX4L6AWkctrHgZdEUfxzQRA+fuf//2C7BYiiKMS6gD1ope6dsJ2m50HHkduuiQkIhSA/n7hkHT7cJMalolSpWJgeRruqY8k+BMWx3x4KhY7eNt0ldtPe3K3OK5JI2Gy2mE7asUKzpcBnCJNXiWiNjo7KcS1S6PTs7KwsNvX7/QiCgCiKhEIhQqGQfJOOPFaCIET9SK2n5eVllpaWSE9Pl7VhUqyR1WqlsLCQhIQEeTmxJjilfyP1TZHbmJqaKlf27uZB42E77yRIx28jgqur2L/6VfwLC5ifegpDdXXU353WNQDcM+u87nWvk39fmKbj8WPxvHTbSW6ylvri1yphRp2FczW/c8/J1VbGk7uCNE1YXw+/93sQDEJn52tE6wc/gH/+5/BrMzOjiVZJyf8jWntErO/VHd6xm2rHV4DPA1/dsMxs4A3AxG7WYVfEShCELOAtwKeB373z67cBj975738GLrIDsQovKnqjH8bqzsNYhTuyuDMRSH4+CckGFnHjWw6RnVvA4uwQqtUGVuJntyS7DyMJPoiwbAg/pUs5hbGwMfttZWWF2dnZTd5IEtmSWmBarVbWNEku5HFxcQQCAURRlOOFIv9bgiiKcpVIoVCgUCjw+/0olUpEUcRoNLK0tITf75e1Vmq1Wl7P+fl5xsbGZF0WbPYcS0pK2jZb8iAhkZCH6RyMzHaUEFhaYvGf/5mQy4Xl534OXfHmJ51Vk5eALohn1s/q6ioXL16ktrY2PMlZYWLC5uOHt5bJSFKTaXlt2MCos9wRtP9tmFxV/xaJpoNtsW1FFvcFpRJqa8M/v/mb4QfD3t4wybp0CV5+Gf71X8OvTU19Le/wkUfCmq2H7H550Ih1rHZbsRJF8ZIgCHkx/vQ3wO8Dz+9mHXZbsfrbOwuNVNKmiqI4e2dlZgVB2E2K7aarx8NKQh6mC+WRhkSsCgowWMLiVr89xBve9FZ6p9fRCGmsCbYtBewPI7E/LNPJnQKzJTdvqYUmCbU9Hk+Um7dkZBoIBFAoFHi9XpRKpRwxFGu5EumSBLhqtZpQKIRGo0GpVOLxeJiYmGByclImd3q9nri4OFJSUjAYDGg0mvv+PY01Gv6gY6PGxT8/z+JXv4oYCGD94AfRbKErWieAL2Udz4wf35ydJ598ki9/+ct86EMfQiEIPHXGzBd+ZOPfrjj4tZ9JwaB97Rw36q0R04Kf42z1bx4oubqn54lCAZWV4Z+PfCRsTjo4+BrRevVV+Na3wq+1WF7LO3zkkfAU4kN07hwUYhErYF87ShCEtxKWQHXs9jzYkVgJgiD1G28KgvDoflYscnFbfMZdLvZo4WF7Aj3SGB0NX1gyM1EoFayb/OCAT3zyf/HllxbRmDqBTpZWRrYkVg/bsToq2xQp2o4MzJYg5c9Ftt+katba2hoqlUoO9o0FlUolk7tYWrCd3NKPAhwOx9HULt4FnE6nTOwDDge2f/onBI2G5A9/GHVK7Odvd8iHO+TFn+LH2+anLCsXjUYjT48CGLRK3nMuiX960ca/X3Pw/gsWlIrXzvMwufodmVy9/uQn0WoOxhPS7/djs9kOZFk7QhDCLcCSEvjlXw4TrbGxaKL13e+GX5uQAO94B3zxi2Gn+D1iZWXlQFf9KMBut5ObGz0larPZsNvt9XtdliAIBuC/A2/cy/t2U7E6C7xVEIQ3AzogXhCErwHzgiCk36lWpQMLu/nAa9euyU+rEJ7KEgSBkTvu2Q8DgsEgPp+Pixcv3u9VOVC4XK4jt03pXi+lwSDtn/scy8ePgykF1aKKga4bEMqj164nWSdwu/enDPW5N73f4/GwsLDwUAnY/X6/HM1y1BGppdr4I1WmYkFqQ0r6KKktGPlzFMjlbtDU1PRQVU3dbrccKaR2u8lZX8en0TDQ1YUYYzuXdD560pZZV4XwBlYQg/Fcf+UGKSkpNDc3b7rmFJni6Z9N5Uvf76Ek3hZDglSAX3GTpqsvoSTxQLYpEAjg9Xrv7/UvLy/88/M/j9ZmI6G9HfOtW6R/5SvMT03R+4lP7EuPddSu6XcLr9dLe3t71DW9q6sL1f4u8oVAPiBVq7KAW4IgNIiiuOUFdscPEkXxvwH/DeBOxeq/iKL4jCAIfwn8AvDnd/7dTe9RPHPmTNQvRkZGUCqVmxjmg4y1tTV6enqor98zQT7SuHjxIo8++uj9Xo1onD4Nzz5L7XPPwW//Ntddw2huackrzOPtT1bys8/8Eb9zQY8jZ57G0w1o1NE+ap2dnWRkZMSsqDyomJ+fx+FwUF5efl/XY2MrMLIyFalv0uv1CIIgT99JD1t+v1/WXW2EQqFAqVSi0WgQRVGujEmtQa/XK08TRmbgRVa2jkIr8PLlyzQ2Nj5UFav+/n7i4+Nl3zNPTg6OZ5/l2PIy5ne847VcRjHEq65u2l3dmJVGPpjUSNwxI6Ptduoq6ykqKsLv98e85vykfYWmXigvzuFCRXRV6lb/JLN2I4+feSuCcDCEdXl5mbGxMWpraw9keQeCd787/O+nP03qH/4hqQ0N8OlP72kRR/Kafpe4efMmxcXFUdpQhULBl770pWt7XZYoip2AXGYVBGEMOHmQU4Eb8efAs4IgfJiwUv7du1nPjb+43xe2e4WHVTt25KDThdPpP/YxeOUVNKn5KIMKtCoDSqWC8ZFufFXnCGW3MW1rJT/jQtTbYwltH3Tc1QTTHiBVjWJN1Emj6Rv9m1JSUtBqtaytreFwOGRDzri4OPlYaLVavF4vgiDILt4bt0+hUMhPpJK+ShAE1tfXWVtbw2g0kpGRITvDSwTP5XKxsLAQk9zF8vO619enw9LDHSY2Ttrqq6qIs9lwvfIK6uRk4s6fZyWwxreXrjG+bqNGn8cTiSfRKtR4TOFj4l8NkZmZyZUrV2J+xutr4llxB3mxw0mCQUnNHWd2URSxLfeTnFhyYKRKWu6RxSc+AePj8Kd/Crm58Cu/cr/X6L5j4/f2zvVwx2BEQRC+QXgozyoIwhTwKVEU/2mvn78nYiWK4kXC03+IomgHXrfd62MvIlr/caDTFkcEDytZPLL48Ifhz/4M/viPMf3LN/AAznkfdXUnGB5tZ0z3K+Qb55mYvx6TWD1s559Go4lqt+8Xfr9/S+IUabcgERKz2UxGRoYcqyNhK7uFpKQksrKymJubY21tTX7ClLRTkZCOkUS2pOMmObBLf1tbW8NsNpOcnMz6+jpDQ0O4XC7ZbiE1NTWm3ULk9klxOpLTtkqlipnZKFXI7gZHRQ93kIg1EBL36KMEFhdxvvgiw2kqXjDOECTEO82nqTXky69TmcL7M7Aa5I/+6I+29PlSCALvOGXG5Qny3RtLxOmUFKRpcXvteHwOirPfcODbdGSPkyDA3/992M/vIx+BrCx485vv91rdN8Q6VnekBTsSK1EU37fD3/N2sw6HKiwRBEGMNQHzsN3YHsabtYQjeYGJqFol995kTHEcz1yQ+pMnuXrlc4xq02gwn2N46lmca7PEG1+LlXgY3YelSJHtIAnHY7mFSwahKpUqikgkJyfL/70doQgEAiwsLLC4uCiLsyWD0Pz8fNkgdGhoSCY7ExMTsvmnlAUoCAIqlUr+b6kKJ920pddJ2+zxeDCZTJjNZubm5nC5XGRlZVFZWSkbhA4PD8sGoZIzfEJCAjqdDvMWAbobA5Dn5+dl4iURzFiZjTsJ6B+2805CrGuEIAiY3vYkL2a46TKMkS7G8XTqI1hU0W08lUEBAgRWQ5Q2lG77OSqlwPvOW/inF218o8nOL70+GY8nHLGUnLj9e/eKI19ZVKng2WfDk4JPPx0WuNfV3e+1ui+I9b26c+04tNbEYSt2QxuJ1cNIQh7G9hK8lsF0JIXed6pWCZ/+C5zv/BLGBR11dXX4/evMTw9hX6tDEL7NxPw1qgreKb/tYczL0mg0UaRp47+RVgeRra/ExMRdRdpshBRpIxEpKdLGarVSVFQkr8/09DQ3btxAq9WSk5NDWloa/f39cs7f5OQkSUlJuFwuIHxsQqEQarVa1lxJrt5S8HMoFGJ9fZ3ExERWV1dJT09ncnISo9HIiRMncDgctLa2otFoyM7O5vjx4ygUCtxuN4uLi4yOjsqRNhLR2hhpo1arSUhIkG0hNiIYDEbt36WlJaanp6MibSL9vCLd6x+EycW9Ilak14J/hWeXrrCQp6Gm18XpzhkSf+mRaAMfQFAKqAwK/KtBZmZmeP7553nb294mB4JvhF6j4JlHLPzjT238y6t2TuWNodMkYNKnHvg2HcnrXiTi4sJmo6dPwxNPhIOi8/Lu91rdF+y3YnVQOOyKVUi6KEb87qEjIdtFOjzIkGIdjuQFRqeDT3wCxUc/iu7cqwj+n+Xs+87ye089RYI6yO2JIPW5VUzON1OR/zYUQnQcyoOGyBDmjeRJCmHu6OiQb+RGoxGr1bqvEOaNiAxhdjgcAFgsFiwWCyUlJfL3WxRFbDYbExMTcgjzqVOn8Hq99PX1IQgCpaWljIyM4HK5SEpKYn19Hb/fj8lkioqxWV9fR6FQRBmfKpVKdDodPp8Pu91OVlYW09PTWCwWEhMT5RBmKUZncnKS/v5+rFYrOTk58g+Ep0MXFxeZmJjg9u3bcgizRLS2q9AplcodA7MjRfwul4v5+XlcLpdshLnRpFT67wcxhNnn88nHSRRFbrqHeWHlFhpBxQcsj5BbKbB47UvYv/ENkj/0IYQN5FJlUhBYDTE1Ps5HPvIRcnNztyRWAIlGFc88YuHLLy5yZbCKR8oOPk3hyF73NiI9HV54Ac6eDbcDr1yBLSqxD2PqBMTermAwSCgUejiJlUKh8Ljd7qi4DckI8GHCw1gFgT3mZd0PfPjD8Kd/StH3v8jUO95CuiWD//aud3HbGeAVZwCd7jw+x20WHD2kWY4B4RaS3W6/zyu+GRvjZKT/9ng8UcG+0g04ISGB9PR0Wd906dIl6uvrD2TaTIqGkYiUQqHAYrGQnJxMaWnppqrL6uoqk5OTzM3NkZSURGFhIYmJiaytrdHZ2cn6+jrl5eX4fD46OzspLS1lenoag8GA0+kkPT2d5eVl1tbW5GVG2idILUC/38/y8rKczWez2UhNTSUUCjE0NERtbS0ul4tr166RmppKSUkJ5eXlLCws0N/fj9frJSsri6ysLPR6PdnZ2WTfMa/0eDzY7Xampqbo7OxErVbLRMtsNu9pv0qtQoMheiJ1YWEBm81GRUXFplgdu92Ox+PZMlYnknwdtRaVFKnkCa3zvaVmur2TFGrTeKf5NHFKPaSD+amncHzzmyw9/zzmp56KuhGqTEoCriCZmZkATE9P7/iZ6WYNT56Eb1830z55hvpyEZXy4EjDA0OsIOzO/t3vwhvfCG9/O/zkJzE9ro5s9+EuEcsXzu124/f7nYe1DodNrFzSk6m8Akf9Zr0PPIxPAfAAHCutFj7xCSwf/SjLtU1459+By+nEM9qF5sRJxu3paNQmxuevRRGrwyb2sQKQI4lTrADk5ORkWTC9m4uhyWTC5XJtmQO4HaQK0OLiIktLSyiVSiwWC6mpqZSXl8f8/EAgwPT0NFNTUygUCrKzsykpKZFd0Ds6OnC5XJSVlWE2m+nq6mJ9fZ2TJ09y+/ZtMjIyWFhYICMjg4mJCSwWC3FxcXi9XtbX1wmFQrI/l5QnKFWJ7HY7Go0Gq9WKy+VCrVZz7Ngx2trayM7O5vz580xNTdHU1ERWVhb5+fmkpaXh8/mYmpri2rVrGAwGcnJySElJkUmrRLogTBbsdjszMzN0d3fL+8RisZCUlLSvG5TT6ZSnIXU63Zb5jtL5Ekmy5+fnYwZBx9J6HfbNMxQKMRVw8O2lq7iCHt4YX0ujqQxF5KRgRQXxr3sdzpdeCk8KPvKI/Dd1nILVxQB56ekIgrArYgVg0gyQm9jL+PJbeb55iXeeNh/YtTgQCBxITNSh4ZFH4Ctfgfe/Hz74Qfj61zdF4TxQZHEPiLVdLpeLtbW1bS0SDhKH3Qp0ra6uRq/AUb9Z/z/IeCBanB/+MN4/+R+kXfpr3HNv4bPPPcc/vvgi//Lyb9A14eUtNaeZmH8Fn38Vrdp0T4iV5N8US+MUWYGIrDqkp6fLxOkgKhAJCQmsrKzsilhJpEEiUlJ1Jj09ncrKyi2rM6IoYrfbmZiYkCtNJ06cQK/XA2GC1tvbi91up6SkhJqaGhwOB01NTRQUFGCxWGhpaaG0tJSFhQUSEhKw2+0UFBQwNjaGwWDAZDKh1WrlFqHkWRUfH49KpWJubg6z2YzBYGBhYYHs7GxcLhcDAwOcOXOGwcFBbty4wfHjx8nKymJsbIzLly+Tl5dHbm4uhYWFFBQUsLKywsTEBD09PaSmppKTkxMV1aPT6cjMzJSrKBL5nJ+fp7e3V67iSRWt3WinVlZWKI6RmbcRkYHZW+m8AoFA1HkmVbwidV5bES9Jw3YQCIaCjJpdXFx8iQSlkV9KfgNZmtgecaYLF/DbbDhfeglVcjL6igrgTsVqNVxNSUlJ2TWxsi33k500Q2F2HC93ukgwqnh9deycyz1v14NY3Xnf+8Ih9R//eNiG4c//POrPDyuxijVo4HQ6g16v99Bs5g91r4qiuCIJU+UVeBBu1v8PwANCgrVapv7rr1L0e3+C68c/pTori/VAAOP6KOuBbDzBU4jii0wttFCY+ZgsrN4LJH3TRuJ0p9wMEGVKKU2gHaZmJjExkampqZjGu5KeyG63s7y8LOuJMjMzqaqq2rHNJeXwzc7OkpCQQG5uLklJSfJ2+f1+hoeHmZubo7CwkMrKSkKhED09PSwvL9PQ0IDf76e5uZna2lpsNhuiKGIwGPB4PCwvL1NQUMDIyAgKhYKEhARUKhVOpxOVSoXZbEalUjEzM4PZbCYxMZGRkRGqq6vp7OykoqICvV5Pc3MzDQ0NOJ1Obty4IZOonJwcRkZGuHTpEoWFhWRlZZGYmEhiYqLsWN/Z2UkwGCQ7O5uMjIxNREmr1ZKRkSFrf6R26cLCghzDIlW0LBZLTKLlcrm2zFncK1Qq1Y46r8jzdWVlhbm5uS3P2UjitVtNnjPo5lv2q4xbVzmmz+XJxHp0iq0JpiAImN/2NgIOB0v//u8ozWY06emoTUrEIIS8IpmZmbsiVqIYYnFlkHRLDcdL4lhxB7nU7SLRoORkkXHH9++EB5aE/P7vhz2uPvOZMLn69V+X/xRryOBhwcbzdXl5eR1wxX71weNQz5RQKLQci1gd+Zv1PnEkrQnuAg+Kdsz7oWfw/q//Q/y//Bk1z4T9XKaHb2PJyKN3WklhUg4Tc9cozHws5vHZ+PQf+W/k079044mPjyc1NfXAn/7vBgkJCXR3dwPIE3ASkZIm4HJycqiurt5VhSwYDDI7O8vk5CShUIjs7GzOnTsXdbMJBoOMjo4yOTlJXl4eFy5cQKFQsLKyQnt7O1lZWTQ2NmKz2eRkgqWlJRwOB8eOHaOlpYXjx49z+/ZtTCYTWVlZTExMkJiYKFfBJCH+wsICGo2G9PR0urq6qKmpoauri7q6Opqbm6mrq0On03H16lUaGho4e/YsXV1dzM3NUVNTQ2lpKfn5+QwODnLp0iWKi4tJT09HqVTKlSmPx8Pk5CRXrlwhPj6enJwcLBZLzOMrrYvkNh45KTk4OIgoiiQlJclESxAElErloemjFAoFRqMRozE2ydhYZZXOmcgp0o1V1kg/rwHfLM8tXScgBjm+nMrbM87s6nsgqNVY3vc+bP/n/+D4+tdJ/tVflb2s/KtBnnvuuSgH7a2wsjqFP+AmObEUQRB44mQiTk+Q77cuE6dXUpoZu826WzywJEQQ4HOfC3tcfexjYY+rJ58EHmCyuA8sLy/7eViJ1fr6+tJ/llagtF0P0zj1gzJBF28w0/3Uz1P3pb+kaP4kCUYjN2/e5OfOvY8XO5zUZDcyNf9NhsbaEILxeL1ebty4Ifs3bdSrSNWm+6FX2StEUZRviqurq7z88ssYDAYsFgt5eXkkJCTs+mYuiiLLy8tMTEzgcDhIS0vj2LFjm6osoVCIiYkJRkdHyc7O5sKFCyiVSkRRZHBwkNnZWY4fP058fDwTExOMj49z5swZnE4nY2NjnD59mpaWFo4dO8bQ0BClpaX09fVRXV2NzWbD4/GQmhoen5dsClZWVigtLWV+fp6UlBScTicpKSlMTU1x8uRJWltbOX36NDU1NXIr8Pjx48zOznLlyhUqKipITU2lsrISj8fDwMAAw8PDlJaWknInKFiv11NSUkJxcTEOh4OJiQm6urpIT08nOzt7kxg9Emq1mtTUVHm9A4GATLSGh4fx+XwoFApmZmawWCz3Xb8T+bAQqYGVEEsXODs7i8fjYdW7xqsFc2iCSk7NpaDzKRgfH48iXtt9b5RxcVh+7uewfelL2P/1X9E/9gwQ9rLKyc/Z1frblsP+VdbEkvAyFQJPNybxf19e5NkrDn7xdVYyLZq97hYZkZOODxxUKvjmN8O6q/e+Fy5ehPr6/1TEamVlJQCs7vjCA8Kh7lW3223/z1KxivTbeVhwVCfoIiGKIrqAio53PcaxZ7+G8Uc/pTInh1deeYV3Pt0OFNA7HEecSWB2sYOc5McwGAwUFRVhNpuP3ITVThBFkdXVVex2O3a7HafTKROp5ORk8vLySE5O3tMyvV4vU1NTTE9PYzQa5crWxgqEKIpMT08zNDREWloa586dk8/3tbU12tvbSUpK4ty5cwiCwMDAAEtLS5w5c4a1tTW6u7s5c+YMExMTJCQkoFar8fl86HQ6tFotTqcTi8XC8vKyTGIMBoM8dZaQkEB/fz+NjY1cvXqVc+fOcf36dVJTU6murqa5uZnGxkbq6+tpbW2loqKC9PR0kpKSaG9vZ3Z2lqqqKvR6PTU1NaytrdHX18fQ0BBlZWUywRAEQa40BQIBZmZmaGtrQxAEcnJy5ErXdpD0QhJp6+7ulqt5IyMjBAIB2UTVYrFsKWS/X4jUecXS7S0vXafDPYbJkoBhVZCtNraaZN043ahOS5MnBcUbrwDH8a8GaW1t5Tvf+Q6f/OQnt90ni8sDmPSp6LWvrZtWreDnLoQ9rr72qp1ffmMySab93fKkc+6BhdEI//EfcOaM7HEV1GgeOmK1lZHr8vJykIe1YrW2trbkcrlCgLzlsbLAHgY8jITxfkzQbUSkJ9BGKwJJK6XRaljO8GOv+3nSX/kMn3jf+0j6pV/i9GPn6PjuHHGWPBI1OYiCndzcXJaXl+X8uaMOURRxuVyy2Hx1dRWj0YjFYqGoqIj4+HiZAM3PzzM3N7crYhUKhZifn2diYoL19XWysrI4c+YMGs3mp3xRFJmfn6e/vx+LxcKZM2eifIuk6lV1dTVJSUmEQiFu376NKIrU19fj9Xq5desW9fX1rK+vMzU1xblz52htbaWsrIyJiQlycnKYm5sjNzeXmZmZqFagzWbDYrHgcDiwWq0sLS2RmZnJxMQEx48f5+bNm5w7d47i4mJaWlo4ffo0Z86cobm5Ga/XS05ODg0NDUxOTtLU1CSvp9FopK6uDqfTSW9vLwDl5eVRrSiVSiX7X62trTExMcHg4CBJSUlkZ2djNu9uEm1xcZHGxkaZiAaDQZaWlrDb7YyNjcmxPxKhk7b/qOJnE04w4pvnqnaMd+vryM3cXGkKBoNRfl4rKyty1UvSeSWXlGDsHwWOY59a4trQNf7sz/6MD3/4wxQWFsb87FAoyOLKEDmppzb9LU6v5AOPWvjST238y0U7v/wGKwbt3lt6sRJDHjikpYU9rhob4c1vJvSNb6DawuPqQcVWLVun0ynysFasANcdEZlM/Y+CHuVeQKVSbZlz9aBCMmO8l9joYh35byAQ2ORiHRcXR2pqKnq9Ho1GI59P044rLFTXk/4KnPH7EVZWEAQBa7wKmzNASVEZg1M/xR/wynEoW0Wa3E+IoojT6ZSJ1NraGiaTCavVSmlpqTyuHwtWq5Xe3t5ttX5Op5OJiQlsNhvJycmbiMRGLC4u0tfXh8lkoqGhIeqG7/V66ejoQKfTyfqrQCDAzZs3SUxMpKSkBL/fT0tLCzU1NRgMBq5cuUJtbS0rK+GBncTERDo6OqioqKCvr4+ampqo7DmDwYDb7aawsJDx8XEKCgro7+/nxIkTXL58WSY9PT09HDt2DI/HQ1tbGydOnODMmTPcvHkTj8dDSUkJOTk5WK1W2traMJvNlJWVoVAoiI+P59SpUzgcDrq6utBqtZSVlW3SJxmNRsrLyykrK8NmszE6Osrt27fJzMwkOzt7ywqH2+1GrVZHVbOVSiVWq1U+rqFQiKWlJdm0dH19nYSEBLmitV0b8n5Ar9DwjsRT/LP9FW4pp8hlM7FSKpXb6ryC/hCzF5ewD7gRRC9BVuTz4tKlS0xOTqLRaDZpvNZDCwRDPqxbxNgkx6t5/wUL//zyIl+/5OCDj1lRq3Z/33mokkHKyuD55+ENbyD5V34F+ze+cb/X6ECxVXvzznn0cFasgNU7IrIHuKa6O+xn2uyo4yDCfTfmrkX+Gyt3zWw2k5mZuWPu2kaU6jLpOxui6gsmDKse/uO732Xg5k2q3vZ7dE94SE4sZWDyx9hXBomLs+B0Ord1dz4siKLIysqKTKTcbjdxcXFYrVbKy8tlR/LdQPLCcrlcUWRJipeZnJyU42UqKiq2rdgtLS3R19eHWq2mtrZ2k85qZmaG/v5+Kisr5XaXz+ejubmZ3NxccnJyCAaDtLS0UFJSQlJSEn19fXIo8tWrV6mqqmJ+fp7k5GS5JbixUqDX6/F4PCQmJnL79m0SEhLwer0Eg0Fyc3MZGRmhpKSE69evY7PZKCwspKuri97eXioqKqivr6ezs5Pbt29z7NgxDAYDjY2NDA8P09TURG1trbyvkpKSZLH9rVu3iI+Pp6SkZFP1SBAEuc3n9/uZnp6mpaVFjtFJS0uL2rdzc3OkpaVte+wk+waLJWxVEAqFWF5exm6309HRgdfrJSEhQbZ4MBgM9/0htVCXRrbTRFv8OLW+IvK1Kbt+79rkOlPPL+FdCJBQrkU98V1UwwLTU1PExcXxgQ98AKVSyfr6etR1Y3l5mdmVl0EU6O9eYFTVFLPdmJWk56nGJJ5tcvDv1xw8fTYJhWJ3+8vv9z9Ukg7On4evfhX9e96D9fd+D557bpPH1YOKrYiVy+USeMgrVg9Xf2wLHIW22UFjpwu3FOy7lWM4hCt5G40vdxPsu1cU6zJ4pbCb1dzTmHr6aPLl8PmvfY3n3/JLeNbV6HT5KBRqbMv9FKa/mYmJiQP77L0gFApFESmPx0N8fDxWq5XKykqMRuNd3TDT0tKYm5sjLi4uZrzMToJcp9NJX18foVCIioqKTT5Kfr+fzs5OQqEQZ8+elVuHa2trtLS0UFFRQUpKCqIocuvWLTIyMkhPT5erMWfPnsVms6HVaomPj6e3t5fy8nIWFxexWCx4PJ4oIiPlByoUCjQaDR6Ph6ysLKampsjPz+fSpUvk5+dTW1vL9evXOXfuHJWVldy8eZPR0VHy8/Oprq5mYGCAlpYW6urqUKlUFBUVkZKSQnt7OxkZGRQWFsr7PTk5GavVytzcHM3NzVitVoqLi2O2SdVqNXl5eeTl5eF0OjfF6CQkJDA3N0dtbe2ejqNCoSApKYmkpCSKi4ujzpuuri7cbrd83lgslrs+b/YDURTJXzCyZobvLl3nIyk/i3YbuwWAoC/E3EtOFm+soY5Tkvf+JBLK9HgHfgb7177GpR//mDNnzsg3S61Wi1arlavLbq+D0ZZh8tLPUlvyM5uMVG02W9SDW16chZ6pJL53eYjqbGUUAduKPD3w+qpYePpppq5eJevv/g7+4A/gL//yfq/RgWArYuXxeATAc1jrcT+I1SZBlZQX+CBoXHYLnU7HRqH+gw5RFGVR6kadk6xvulOqly5WknnjYWee6RUa4rN0LJecJuEHL/K+3/oIf/fKK9z6wTeg8udxrIIlvgDbch9VBU/JxO9eQ6o8SPYHUuXBarXKFZSD3E9xcXH09PQwNTWFxWKR42V2+gy3201fXx8ej4eysjK5chIJm81GV1cXxcXFskM5hKtb7e3tHD9+XBY6d3d3YzQayc/PJxAI0NHRQX19PQB9fX2cOHFCdlmPj49nZGSEnJycTcQKXtNlWiwWOSPw2rVrFBQUUFBQwODgIJWVlRQXF9PZ2cmJEyc4fvw4169fR6fTkZ6eTmlpKRMTE1y7do2GhgaZ2J07d46+vj6uXr1KbW2t3LYSBIH09HTS0tKYmpri6tWrpKenU1BQsOUNOT4+nsrKyqgYHck36m5FwwqFArPZjNlspqioKKrS2d3dLVc6pYrWXiqd+8Xq6ioJhjjeYT7Glxdf5Mcr7bzVXL/l652DXqa+v4x/OYilwUj66+NR6sL3AF1JCcqaGmx//de86x3v2HIZA5M/RkSkJOdNAHKLNVY7e27JT/PFRXRqkZKseJRKL0tLS8zMzOB2u6OkBpFVL6/Xi1qtfujsc8bf9S7S19dRfvazYY+rj33sfq/SXWMrYhUKhYLiIfZ0D70VuLKysilxWdJixHoCfFCh0+mw2Wz3ezX2hGAwuKV/k3TR8fl88hRXXFwcKSkpGAyGKH3TUUGpIZOh82Xk/gBOxieSaTbzyvPf5Fzlz7PoDJCcWEbP2PP4/C65wnjQT6bBYDCKSK2vr5OYmIjFYqG2tvaeiJI3xsuYTCZKS0t3JWL3er0MDAywvLxMWVkZycnJMQNNe3p6WF1d5fTp01HbIDmRnzp1StYBDQ8Ps76+zvHjxwHo6ekhLy8Po9HI7Ows8fHxGI1GhoaGZIK2vLxMdXU1ExMTm/REUjvQarUyNTVFVlYWBoOBlZUVsrOzefXVV+VK1tzcHDMzM2RkZNDQ0MDVq1fRarUkJSWRk5ODTqfj2rVr1NfXYzQaUSgUVFRU4HA4aGlpIT8/n5ycHHkfCIJAdnY2mZmZjI+P09TURE5ODnl5eVtWXBUKBWlpaaSlpdHT04Pb7Y4Zo3M3EARBNjktLCyUhxwkTdzq6iomk0kmWttp8/YLyek/V5tMo6mMK6t9lOszKdZFt9gDa0FmfrTCUocHrVVF0YetGHM3V05TnniCjj/5E3zr64R8PhQbqqtur53xuavkpjVi0G22iIjEuM3H11+1o1EJ/NIbkklJiE2GpeEY6brncrnkB8lXX30VCFfNYuU2PmiB2f5AAMXnPgczM/CbvwnZ2fC2t93v1borbEOsNvGOe4nDJlaOWGRD8kd62IjVUWsFRpbJN/4rVQwjLxhms5mMjAzZ+BKgq6uL1NTUPY/w3w+U6TL51/MjPKI3E/rBK7z9rW/lS1/7Gqc9LhadJgqKSmEMFpf7SUhIYHl5eUfty06QprskIhU53ZWTk3PPprs2xstkZGTI8TLSpNl2x2x9fZ2hoSEWFhYoKSnh2LFjMW8Sy8vLdHR0kJOTQ1VVVdRrxsfHmZycpLGxUf4uT09PMz8/z+nTpxEEgYWFBdxuN8eOHUMURQYGBmhoaJCtGxobG/F6vWg0GhQKBW63e1O1TBKwWywWOjs7AcjJyWFiYoLq6mpKSkoYGBigpqaG6upqrly5QlJSEjqdjoaGBq5fv87JkyflBwONRiO7wEstJskmoru7WzYVjSTdCoWC/Px8srOzGR0dlVuQOTk5W1bepcnL8+fPy15c28Xo3A0EQSA+Pp74+HgKCgpkW47FxUUGBgZwuVzyNKnVao2aJt0vlpeXZX3d4/HVDHhn+O5SMx9LfTN6hSbsi9bpYfqHK4R8IVIfjSPlQhyKLYTkCq2WpHe+k8Uvf5mVH/0I84ab/sDEjxEQKMn+mW3Xa2DGy781OYg3KPmFxywkGre+7UUGZkfq28xmM2lpaYiiiM/ni7p+Li0tbSt3iPTzOmqThYJKBf/6r/DYY+EInFdegVObpysfFMTyGwuFQgQOeUT/0ImVw+HY9C2SSMhWcQwPIg7bTFPSN23UNrndbtn4UqVSRRGn/eibTCYTq6urDwSxSlLFIeQJuArOENf0Ck9/++t853vfY33qNrY8M4mmHNQqPQtLfaQlvm5fxEoyfpR8pILBoEyk8vLy7rk2Y6d4GQiThO7u7pgVuUAgwMjICNPT0xQUFMhu6RsRCoUYHBxkYWGBurq6KAIgiiL9/f04nU7OnDkjn0uSGeaZM2dQKBSsr6/L3lWCIDA5OYnVakWv17O0tITRaEStVrOwsCDf1GK1AqWKlVKpRK1W4/V6SUlJoaenh2AwSHp6OsPDw6ytrWE0GqmsrKSjo0OeYqyrq+PmzZucPn0anU5HYmIip06dorm5mbKyMvkcUKlU1NTUMD8/z7Vr1ygrK5Od1SWoVCqKi4vJy8tjaGiIS5cuUVRURGZm5iaiIllfSE/UG2N0urq6CAQCW8bo3A0iQ6vz8/MRRZG1tTUWFxcZGhqK8j+zWq0kJCTsmWitrKxQUhI26FQLSp4yn+H/2H7CD5dv8qSinqnvL+Ma9GHIUpP1Niv61O237xd+4RcoKSnhY+fOsXr5MrqyMvSl4cm/Nc8i4/NXyUs/v2216vaYm+9cXyI1Uc0HHrVg0u2d2KyurpKdnQ0QFZi91RTxxgEd6WFiqwGdyH8PSyQfZUtgMMD3vx/2uHrySbh2Dbawtjjq8Hq9m46LzWZDpVIdqgHjYWcFihkZGZuY42GM8R82JJHtQUGKnIhVbZL23cZR5MTERLlEfVD6NaPRyPz8/IEs6zBQYsxgqq6GY1/9IWdT0xjt6eEbzw+ysLCKIKRiTSjBttxPadY7mZyc3HF5kQ7adrudUCgkR5UUFBQcijuzFC8zMTGBKIox42UiIQgCeXl5jI6OUl5eLi9jfHyc8fFxcnNzZbf0WFhdXaWtrY2UlBTOnj0bdS6FQiE6OjpQKpXU19fLN2On00lXVxenTp2SbxadnZ2UlpbK037Dw8M0NjYCyN5VECZkUtix2+3e1Ao0GAwsLS0ByDqrzMxMUlNTmZubIzMzU3Zvr6urIyUlRd5fubm5svZJMhCVKgyNjY00Nzfj8/miMhZTU1Mxm810dHQwOzvLsWPHNt0A1Wo15eXlFBQUMDAwIE8npqamIghhw8yRkRG5HRqJ/cbo3A0EQcBkMmEymcjLy4ty7B8ZGWFlZUVOHbBYLCQmJm57DZEe7CK7DhmaJC4YK5m87qC3ZQ6FoCDjzQlYG4wIO0zkra+v8+yzz/Lrv/7rxD/2GN6BAZaffx7NRz+K0mhkYPJHCCi2rVbdGFjlBzdXyEvR8P4LFnTq/V0DY52D20GtVpOQkLBlYPZGS5mlpSWmp6e3tJSJJF4HJbnYVNlJSXnN4+pnfxauXgWr9a4/57AhTRNHYnZ2FqVSubsk7wPCoduuiqLo3vgUqtVqj1zb7KCwW8FjZEjqRvIUGZIqfcGMRqM8Zr3bkNSDgMlkYnh4+FA+6yBQps/kyhuKOPZV8H/nRXSf+CiWpEmGfUq8c/Mkm8uYtXcQElZxu92b3u/3++VqlOQ6LxGpoqKiQ2tfx4qXqamp2dITaCOysrK4dOkSeXl5LCwsMDIyQmZmJufPn9+SkImiKGf/1dTUbHLcDgQCtLa2yvtCOgc9Hg83b97k5MmT8vdcCtKVLC3Gx8dJT09Ho9EQDAZxOBxUV1cDYfF7VVUVEL4JbVw/vV7PzMwMEPbqmpmZITMzk5ycHDo7O8nMzCQ5OZnBwUGcTqdMpJqamrBarRiNRtnSobW1lYaGBnnKMNLrqrS0VN4mjUbDyZMnmZ6e5sqVK1RVVWGNcePRarUcO3YMt9tNf3+/7OIeCoXk7+12iBWj09nZSUZGxo4xOncDQRBkjymJVEpEa3x8nNu3b6PRaOSpw40pBVJ1MBKeeT9Zz6dimUrClr1M3TvzMFt2d77eunULr9fL2bNnEVQqkp56ioV/+AeWv/99tG99nIm56+RnXIhyWpcgiiKvdLm42OWiPEvHuxqTUCv3d32UBnYOcrBKqVTuGJgdaaTqcrmYn5+PMkHWarUx24271XnF1JOWlMD3vgePPw5vfSu89BIccWPajfB6vZsebmdnZ/H7/WOHuR6HTqzUavXc3NxcYX5+vvw7nU4nG8E9TJC8rLRaLYFAYEsbgo1xD3q9noSEBNLT06P0TUcBR1E7th0y1RamzplZj0sl9OOX6H7bo/ziR5/kDR/6SyZEA+lPnQPCkRharRaXyyVHxDgcDgRBICkpCavVSklJyaEfi93Gy+wEKZbl4sWL5ObmRlkjxILH46G9vZ24uDjOnTu3qZrl9Xppbm6moKAgaiLQ7/fT3NxMdXW1fOOQBPHnzoX3dSAQYGxsTP7/2dlZ0tLS5OEItVotV3xjbaeksQIwm810dXUBYdIvDWDo9XrKy8tlIb1KpaK6upr29nYaGxsRBIGsrCw8Hg8dHR3U1tbKwcj19fV0dXXR3t5OTU2NfFOV3mOxWGhvb2dubo7y8vKYlT6DwcDx48dxuVz09vZis9moq6vb8/G6mxidu4UkrpcqiR6PB7vdzuTkJJ2dnajVaploud1umXiHAiILr7pYaHKh0CpIeLuW76Z0YcPBe8Vzuzp3m5qaADh79iwA6rQ04h9/HOdPf8pw7hyCQhmzWhUSRV64ucKNwTWO5xt4a0Miyl36VcXC/bBaiNR5xYKk84q8n9jtdjwej3xtVqvVMQX2er0ehUKx9XY1NsLXvw7vfjc88ww8+ywcMV3YdoilsZqdncXhcAwd5nrcj4rVxMzMzNmNxOpBullvRKyAUrfbzerqKleuXEGhUMhmjZH+TbsJKD1qEAThgbLHUAgCRQkZLFbWk3LrEoUFBXg9bvpaXmDB+nrSRhfRqOIYGr9B0FlFc3Mz6enppKSkUFZWdl+OzV7iZXaCZI/R19dHQkICer2evLy8bZc1NTXF0NAQlZWVMbV0LpeLmzdvbvp7KBSipaWF4uJiWSMliiLt7e1UVVXJpHR0dJScnBz5/ycmJqipqQHAbrfL7/V6vTHF/mq1Wo6LUiqVqFQq+YKanZ3N5OSkbEIK4QqY2WyWfaCGhoYoLi4GoKioiM7OTvr7+ykrKwPC53hVVRXDw8PcuHGD+vr6qPNAr9dz+vRpRkdHaWpqilnNkxAXF0dGRgYKhYKxsTEmJiYoLy/fk550Y4zO5OQkly5d2nOMzt1Cr9eTlZUlE2mv14vdbmd6epqZmRl0Oh1Bl0jokonAEphr9GS8KQGVUcnjrmP81NnBbc8YNYb8HT4Jrly5QmFhYZTm0XT2LEsjHcys95CffBadNrrVFgiKPHdjic5xD2fLTLyx9u4F+dI05VFCpM4rFqT7UeRD/Pz8vHxvkv6u0WgIBAKbCJjqqafgr/8afud34L/+1/B/PyCIVV0cHx93+3y+nXUeB4hDv2t4PJ7R2dnZqN8ddY2VpG+KNVEX+YQQ+VSQnp5OKBQiOTn5SDh6HySkisFRu+BshTJdJsNny8m4/h+4mzp59LHHefnVn7Dwzvcy/+KLaE6lEGSFmpoaFhcXqaiouC/rudd4mZ1gt9vp6+uTBduSPk7yjdqI9fV1bt++jUKh4OzZszGrcw6Hg46ODurq6qLWTRRF2traSE1NjTrfx8bG5NYbhCtaU1NTXLhwAQi3m0RRlNtIi4uLskDc7XZvOUUZSe4lnVVGRgYZGRlcuXKF4uJiBEGgrKyM7u5uWctVWlpKU1MTKSkpskD72LFjtLS0yHozaflFRUXodDquXr1KQ0ND1I1MEAQKCgpITk6mvb2dlJQUiouLN13UQ6EQQ0NDcp6i3W7n9u3b6PV6ysrK9tzaMxqNlJWVUVpayuLi4q5jdO4FdDqdrA1bXl7m5MmT2LqXWVkCb+4SE6mjrI6Hq72nzMX0eaf5wfJN8rSpJCi33+6ioqJN30NBoWDhuAaFXSD55hpiWQjhzv5eD4T4tyYHg7M+3lATz/mKgxmEitXiPOqIDMzeSuclpRZIcV5Sxcvtdoc7KMePU/qe95D2N3/DolaL/zd/UyZearX6SNpKbCW7GRsb8wKzm99x73DoxMrhcAxPT08HIj/7fufqSfqmjcRJMvMDokzjJFHnTj1taRkPG+Li4nA6nQ8EsfJ4POjsQbp/JofzfwX2b/yQC+fP8h/ff55Wl59GtZ+0lHxGpl8lOdlKX1/foRoB7ideZiesrKzQ29uLQqHg2LFjUQQoJSWF4eFhHA6HXNGBsP9UT08PpaWlWz4IzM7OMjAwsMm7CqC3txetVhsVlLu6usr4+Ljc8gMYGhqioKBAbmNNTk7KE1cQri5VVlYC24uGpSq3wWCQXdGlSbr4+HgcDgcWi4WEhAS0Wq1MVhUKBbW1tbS1tcktTkEQqKur49q1a+h0OlJTU+XPycrKQqvVcv36derq6jZVmuLi4jh79iyDg4OyqWjk92J4eJj09HS5PWGxWGhsbGRhYYHW1lY5Q3GvhEgQBJKTk0lOTo6K0VGr1eTk5GyK0bmXcLvdaDQajEYjhpMGBloW0LqTya8P68QWFhbo6+sjR61iJjvAt+ab+IXkx7Ztq/9lDCdwl3ueqeUOcrWViINTrLW0YDp1Cs96iK+9amfKvs7bGhKpKzw4IuRyuTZNgj4McLvdFBcXb/ngEgqF8Bw/jtfjwfrnf86swcDoE09se0+UCguHqfmNRKw2IMDk5GSAh51YiaI4Mz4+7gbkq/29PgiBQGBL/6ZIfZN0csTHx5OamnrX7NxkMu1q0uxBg+T5dBQrcZLeYHFxkZWVFTQaDRaLheTscPvB5FPy/ve/n9///d+npbsdV7EBvSqRkBjAHwwHHG/M1jtoSO05KV4mKytrV/EyO2F1dZW+vj78fj9lZWUxx8EFQaC6uprW1lbOnz+PKIqyFcOZM2e2vMGPjo4yMzNDY2Pjphvi6Ogobrc7SkMUCoVkjZLURvP5fMzPz8vVKlEUmZ2dlYnX+vo6SqVSJl0ej2fLlplkuSDlSfb09Mh/kzytpJZiaWkpbW1tWK1W2d8pKyuLvr4+mcQplUrZQFSj0UTtu+TkZE6cOEFrays1NTVRhBTCmpjS0lJSUlJobW0lNzeXvLw8VldXmZmZ4fz585uOQWpqKikpKczMzHD9+nVSUlL2PQyxmxide4nI7ENBIZByPo6Jby/hHQmRXp4uExO/349oa+OqOMwP2i6S5NXK+kWLxSKfV6urqzEjefonfohSoaa87hlWh5/H+ZOfsJ5VwL92hLC7Ajx9NonK7IMVW0tGuQ8bdtKOKRQKjPHx8K1vwdvfTvqnPkV6SQm85z1A7C6O3W6PmlLf2MWJ9PO6F6Q/lnAdYGZmRuCoEitBEHTAJUB7533fFkXxU4Ig1ABfBEzAGPBzoig6t1nU7Pj4+Ka+n1Kp3NI1dTvE6idHHmxRFFEqlTGrTQaD4Z5qaCTPp4cNiYmJjI2N3e/VkEfEI4mUTqfDarWSm5sbNSJuWQ4TpXW7h4z0DP7rf/ski9o6xuNWKVsP38zcXrucrXcviNXq6ioTExPMz8+TlJS063iZneDxeOjv72d1dZWysrKY02qRMJlMZGdn097ejsvl2uQuHglRFOnp6cHj8XD69OlNgunZ2VlmZmZkA1AJQ0NDWK3WKIIyMDBAUVGRfEzsdjsJCQnydzBSXwVhkhxZPYpEpEmoSqWSfbIkIi15QqlUKkwmE3FxcczNzck3+YKCAq5duxb1mRqNhoaGBm7cuEFDQ0NUCyg+Pp7Tp0/T3NxMcXFxzIcKs9nM+fPn6enp4dq1a/j9/ijx+0YIgkBmZibp6emyxUJmZiYFBQX7vi7FitHxer2yNupeTLHOzc1F2UgkVuqZe8nJwiUX8WWvVfTVajWvSz9B59wMjnwFb0k8I3vADQ4OytYln/70p2lvb6evr09epss9y9RCK8VZr0enjUf99rcz8MWv8K8Xl/BqTDzziIXCtINtg4qiSDAYPFLDQwcBaShkV9cdjQa+/e2wBcMzz4DRCE88EVWM2PigAbF1x7Ozs3JnSLovb2Wkup/zfyuyuLa2FhJFcVsRtyAIXwaeABZEUay687s/Bn4ZkFzNPyGK4g93sy57WXsf8LgoiquCIKiBJkEQXgD+N/BfRFF8VRCEXwT+K/BH2yxndmJiYlNmj1Ta39heijUBEWl8CZsnIKRq071ixruFRqO5ry3OewXpWB12dpZkaigRKafTiV6vx2q1kp+fT0JCwpbH22oMkw2FL4Bz3sNnPv3H/O13ZxhdnKBmNXyM3N5FUlOPc+PGDdno8G7h9/uZmZlhcnISpVJJTk4OpaWlBzLR5fP5GBwcxG63U1paKnsm7YRQKCRXj2pra7esPIZCIdra2tBqtdTV1W1atsPhYGBggMbGxqjtWV5eZn5+Xp7oAmS/HslGAZB9pSQsLi5GEantWoEGgyEqi1PSWaWnp8u5fjMzM/JEW2lpKc3NzfL0oSAI1NbW0tzcHKUnk6b5WlpaZF2UBL1eL3tdeb1eCgoKNq2XUqnk2LFjtLe3Mzs7y9ra2pbCdgkKhYLc3FyysrIYGxvj8uXLctVrv9evyBgdn8/H1NTUgcfoQPj8lgTQEgSlQPK5OKa/v8zq6DpxBa/tQ7Wg4lxcOS+s3GIq5CA/NVU+5oFAALvdzquvvkpJSQmvvvoqZrMZq9XK5NIPUCo0FGW/AQBbQMf38t5O0Ovj3QnjFKYdfPXc5XI9EHKHvWKvvlyygejrXgfvelfY7+qxx7Z9S6TOa6vzf+OkvM1m23JSfiMBi0V2YxErURQJBAK7uQl/Bfg88NUNv/8bURQ/u4v3R2HXxOpOgKFUflHf+RGBUsKVLICfAj9me2K1aLfb5W+05NkhiiITExMolUp5Z2/l2bEbfdNRwX4rcUcZ0lTKVlNbB4XIGA673Y7L5ZI1NYWFhXtzh76z/4XgOr1DM9Sn5KNw9tDjieNJewDUsOa1ywZ8dzNmHStepq6u7sD2ld/vZ3h4mLm5OYqKiqisrNz1fnA6nbS3t5Oens6FCxdobW0lOTl504XK7/fT0tJCampqlG5KwurqKh0dHZw+fTrqvcFgkI6ODk6cOBFFCvr7+ykpKZHXMxAI4HQ6o552HQ6HbGAqrcNW1QK9Xs/CwoL8/1arlYWFBbkilZ2dTVtbm0yspEr11NSUrOkyGAwUFBTQ3d1NbW2tvKzExEQqKipoaWnh9OnTUd9dtVrN6dOnaWtrw+PxUFFRsWnfr6yssLKywuOPP05XVxezs7NUV1fvWC1SKpUUFhaSm5vL8PAwly5doqCggOzs7Lu6zknat4KCggOP0VlYWJBjbCKRVGtg/pVw1SqSWAGcNBZy2dXDK84u8pNfI9IqlYqJiQnm5ub4zGc+w7lz53A4HIzP3GR2pQ2tWE5fzzA+pYWf9inQatQ8RQf6q62sV+WiOWBpwsrKyj1vo94P7GvSMT4efvQjeOSRsMfViy/edfSNSqWSY5diIRgMRvl5raysyFWvWN6Oy8vLJCQkyC1BQRBwOBwolUrHTusiiuIlQRDy7mqDIrdtLy8WBEEJ3ASKgP9PFMUbgiB0AW8FngfeDWRvswhEUQzl5OQompqaolxmJX1Feno6qampB+oyez9hNBpZW1t76L6giYmJLC8vHyixigyOlYhUXFwcFouFkpKSuwuOFQRErRZR8OIYX2W+dIHf/uAbeezpP2As9Y3ochNwexcBSEtLY35+PqqashvsJl7mbhAMBhkZGWFqaor8/Pwt42diQRRFhoeHmZmZoaamRj4fi4qKuHXrFg0NDVEGny0tLRQVFcWsZnm9XlpbW2OSxd7eXrKzs6O0US6Xi7W1tahq1PT0NBkZGfJn+v1+FAqFTGKkIPqt9l2klxWE23CRrSODwYAgCFFTXcXFxVy7do3MzEx5v2VnZzM3NxelE4KwyN/r9XLz5k3q6+uj9rNSqaSuro6enh5u3brF8ePH5b/7fD7a2tqoq6uTK30zMzNcuXKFysrKmCRkI1QqFaWlpeTn5zM4OChXcKRq3H4RGdR8UDE6c3NzMYm3Qi2Q3Ghi9idO3NPrGDJfI5VqQcX5uApeWLnFqG+BfO1r++S5555DqVTyxBNPoFQqMcWrWBh8iXhjJmerPszFThdXe/wYVOtUmaZYi0tBN6zD/q1vkfaRjyAcYNvuILJDjyL2PeloscBPfwrnz4dbgxcvwh1T33sBpVIpm9bGwsY0kpmZGfmhVtJ5TU1NodFoFu9iNT4mCMLPA63A74miuLSbN+2JWImiGARqBUFIBJ4TBKEK+EXgc4IgfBL4HrC+03KCweDKsWPHLJFkY2ZmBpfLdSQF0XcDSWf1sBGrhIQEVlZW7mpiRhRFnE6nTKTW1tZkIlVaWnp3RCoGBI0GjT5IwpyJKcMq1dXVTHRfZvDN7yBXZ2HNG3ZWT0tLo7u7e1fEaq/xMvtBKBRifHycsbExsrOzt42fiQW3201bWxtms5mzZ89GvTcrKwun00lfXx/l5eU4nU5u3rxJdXX1pvBjCFeampubqays3PSkKbVnJUG4hL6+PsrKyqKO5eTkZJTY3W63R1WvtprwkSCZ70qQCEFklUsSsUtVMK1WS1paGuPj40g+eoIgUFNTw9WrVzGbzVGfmZOTg8fjobOzc5MpqyAIVFZWMjw8zPXr16mvr0epVNLa2rrJpyojI4OkpCTZVLSiomJX54dGo6GyshKv1xvl4p6cnHzX34uDiNEJhUI4nc4tr22WeiMLl1wsXHKR977oc0mqWl10dpKf/Dr598899xyPPvooSUlJhMQgrb1fJiQGqCr8MN+67mFgJkBltoG3nUpEo8zBMT6OR60maLdz5Sc/wZiRIecd3q1L/crKCqV3sgkfJkRmH+4Z6enhatW5c/DGN8Lly3DHE+6wEanzgnCaQ21trVwZFkWR73//+/h8voF9fsQXgD8h3Jn7E+CvCPOdHbGvq78oisuCIFwE3nSn//hGAEEQSoC37PihKtXAxMREwbFjx+TfGY1G5ubm9rM6RxrSlNnDhsTERCYmJvb0HlEUWVlZkYmU2+0mPj4ei8VCRUVFzEmgA4VGg94AJqeeywsdPProo3zhC//AcCiBUrWVpdWwOa/JZJL7/LEIzN3Gy+wWoigyNTXF8PAwaWlpnDt3bk8VBVEUmZycZGRkhGPHjsUkSgDl5eU0NzfT29vL3NwcJ0+ejDmNFwqFaG1tlf2bIuH3++VswMhjuLy8TCAQiBLUr66uygMlEux2e9RrdtKBSJ8RqfOzWCw4HA65Mpaens7g4GAUqSssLKSpqYns7GyZ3Gi1WsrLy+no6IjKOwQoKSmho6ODwcHBmLq7wsJC9Ho9V69exWQykRqhGYqETqfj1KlTjI+P09TURHV1dUzRbyzodDpqampYW1ujr6+PwcFBysvLd/3+nRAZo7O0tLTrGB3JsmOr76xSq8B6ysT8qy68Nj+65NfOXUlr9aOVNsZ8C+RpUxBFkb/5m7+RW/B9Y/+B3TlMTsav8LVL4PJ4eUtdAg3F4euEd3CQ9W9/GyWQ9IEPkFFYKF9fbt++jcfjISEhIYpo7fb6ckebc2iRVYeJuzY9zcsLk6sLF+D1rw+Tqzst9/sJyfRUgiAIjIyM+Ofn51v2szxRFOVQXEEQ/hH4j92+dy9TgcmA/w6p0gOvBz4jCEKKKIoLgiAogD8kPCG4Ldxud9vAwMCbNhKrh3GCzmQysdEQ9WGANO6+nYA9FAqxvLws5+xFXuiqqqr2dKE7EGg0qLVBAFTTKgrOVeH/nI/R0S6cVZl4fC2EQkEUCiXJycnYbLaoVoAULzM1NYXJZNp3vMxOEEWRubk5BgYGsFgsm0TUu4HP56OjowONRrOl2acESex9+/btmF5N0jp1dHRgsViiImwkdHV1ySQjElIlLBKRgcsS7HZ7FHHZmCcaC5GRURDWWUUK4JVKJUlJSdhsNrkFp1aryc7OZnR0VHZfh3CVcnZ2NkqDJe2b6upqWlpaYq43hCtSUtRLUVHRlusr3AnDTk5Opq2tTa7M7radazQaqaurkyuMoihSVlZ2YNVwKb4pKSlpU4yO1CqMfNDY2D6NBetpI7arqyxcXiXnndH2H/XGIppcvbzi6uJD2scRBIE3velNAMw7euif+AlB5dN8/2YycXr48OuTybJoEEMhXJcu4Xz5ZdSpqSS9972o7pBMs9mM2WymuLg46kGuq6sr6kHOYrFgMpm2/O46nc49ueM/SNhIQPaFsjL4yU/g0UdfI1dbTPAeBgKBQMzvUUdHhysYDPbvZ5mCIKSLoijdvN8BdO32vXupWKUD/3xHZ6UAnhVF8T8EQfgtQRA+euc13wH+704LWlxcbO/u7vY89dRT8pVTpVIRCoX2sDoPBiSN1cMGyQ8oshUQCoVYWlqSp/bW19dlIlVdXX3PAmR3Da0WlSqIoILshWS6a5ZRKBSMd11m7uwHMelFPD4HRn0ymZmZDA4OkpKSsileZieicjeQ4mfi4uJoaGjYl4ZtdnZWJjS70YgMDw+zsLDAhQsXuHXrFnq9ftMkT39/P0qlMiZxmJ2dJRAIbCJcdrsdpVIZtSxRFJmfn49qsUhC1Mh9upvJJUlnJRGrpKQkBgaiq/4SiYrUNuXn58uB1JGfWVVVxZUrV7BYLFGfrVAoogxEN+qkxsfHWV1d5ezZs9y6dYtjx45ta3lhNBo5e/YsQ0NDNDU1UVtbuyd7j/j4eBoaGlhaWqK7uxuNRkNZWdmBTrBtFaNjNptlbyybzbaJNG9ajlFJUp2BxeY10h6PQ5MYMQiwoWr1gy99i0cffZSCokyae7/OlPO92FYLKMnQ8s7TSRi0CkJeL0vf+Q7evj701dUkvvWtKLYgCZGasqKioijpQW9vL2trYd86yUcrUnqwuLi4o23Jgwi/339wGZO1tfDDH8Ib3hD+uXgRDqiKuldIx3IjOjs7A8COrUBBEL4BPApYBUGYAj4FPCoIQi3hVuAY8Ku7XZ+9TAXeBo7H+P3fAX+32+XcwUBHR8caEHXXUKvVshfNwwIpTPZBydbbC8xmM+Pj42i1WhYXF/H7/SQmJmK1Wjl+/Pg9nRjcFzQaBL8PQ4aGLJuVG8Y+vv7Cv+HsT2BqJZFSXXgy0KgPO3Tb7XZeeeUVUlNT7zpeZicsLS3J7uXHjx/f101Sasf5/X4aGxt3rHKJoii//tSpUygUCurr62lububEiRMyYR4fH8fpdG5qk0G4MtbX18fZs2ej/iaKIn19fVRvELfabDaSkpKiLu6SS3okJI+q7WAwGPB4PLJXllqtlv1zJMJkNpu5fft21O+USiX5+fkMDQ1FEQO1Wi1bJZw5cyZqe1QqFQ0NDVy7dg2tVivvm4mJCaanpzl16hRKpZIzZ87Q3NxMYWEhmZmZW667IAgUFxeTkpJCW1sbWVlZFBQU7Kn6aTabaWxsxGaz0dbWRlxcHKWlpQf+vYsVo+NwONDpdLu6USefNWFvWWPhyipZb0mM+ptUtfr3/lf4Lx/7GJ/+9P+i9nXpdM68F18wiTfUxHO23IRCEPAvLOD4xjcILC2R8OY3Y9zQdt4JgiCQkJBAQkIChYWF8rCM3W6XfeCMRqPs5L/x3H0YcOCTjo2N8Pzz8Ja3wJvfHBa334dK31aC/Pn5eYAdxeuiKL4vxq//ab/rc788AIZ6e3s3eVlJQu+D0g4cFcTFxeFyuR54AXswGJQN/ex2O16vl1AoREVFBbm5uYeeAr9naDSwvo4hR4P72jpJoglXrZaSHhsvBytw+zMYn+ylr3NBFjobjcaoltFBw+l00tvbC0BlZeW+zxGp3VFYWEhWVtaON5xgMMitW7cwGo1UVVXJrzcajdTX19PS0kJtbS3r6+tMTk5uIhrwWsByRUXFpoehhYUFDAbDpnbKxMTEpimyxcXFTSRqN61AvV6/KTIqKSmJpaUluaokmXBOT0+Tl5cnvy4nJ0e2M4gkoFIMzsjIyKb11Gq1nDx5kpaWFk6dOsXCwgIzMzM0NDTI5EKn03HmzBlaW1vxeDzbtgYhPARy7tw5+vr6uHbtGrW1tXuu7CYnJ8tkoLm5GYvFQnFx8V07+W9EZIzO1atXSUpK2lWMjiZBhbnGgOPmGqmPxKE2vUbEpKrVn/zTnwOQVJTPjdFG9GoFH3rESl5KeBs83d0sPfccglqN9YMfRBtxLO9me6Rx//z8/Ch7l+XlZVpaWmSiJZ0XD/qU+j2xkHj96+HZZ+Gpp+BtbwtXsQ75XhBLN3ZHJ+sSpRHjQ8R9IVaiKK5mZmYGNv7+YSVWkjXBg0asAoEADoeDxcVFHA4HwWBQNuzLz89Ho9Fw8eLFqLH5I407xMqYo8HWBGddFTwbfJnLF7+LqlZPqrEUn2uGhoaflZ/Gr1y5QlFR0YFvnyRE9nq9dyVEDgaD9PX1sbKywqlTp3ZVrVhfX6elpYWMjAx5Oi4SJpOJU6dOce3aNUKhEI888kjMqsTExMSmbD0IE67+/n5Onjy56XNjGWY6HI5NwvDd+IgZDAaWlqKnny0WC4uLi1HtuuzsbFpaWqKIlUKhoKioiMHBwSjTUoCysjI5qHkjMTSZTNTU1HDp0iXi4+PlSlUk1Go1p06dor29nc7OzijiGgtKpZLKykrsdjvNzc378q6SdHJpaWmyGWhaWhqFhYUH3rb2eDyEQiHKysooKyvD5XIxMTGxbYxO8jkTjjY3i9dXSX999N9OGooY/NEtknPymQk+gjXOwS++rgKTXokYCuF88UVWm5pQZ2Vhee97Ud6jyrEgCMTFxREKhUhLS+PEiROyIfHw8LBsSCyJ4bczJD6qWF5e3pHs7wtvext85Svw8z8P7343fOc7cIiO9aurq5uuQ8PDw6jV6qFDW4kI3E/XSofD4UiPvKGYTCbsdvt9XKV7g8TERKampvbsi3TY8Pv9UURKipiwWq1b5pht1FkdaUjEKju8HZruELoqLd+9fAVL5zjFpV/BK15m6W//Fm1+PtqCAswKBYuLi5um4PYLaXTe6XRSWlp6V6PzKysrtLe3k5WVFdOoMhbcbjctLS2yL9JWkB7ytFqtXGWKXL7b7WZ0dDQqYFnCzMwMiYmJmyov09PTZGZmRi0nEAgQCoWibv47eVhJkFqBkbBYLAwNRV9LdTodarVa9kWTkJmZyfDw8KbqmFKpjApqjrx5BgIBRkZGMJvN26YqKBQKjh8/Tl9fH62trZw4cWLHlpnFYuHs2bN0d3czNzdHTU3NnqtOktA8MzNTnkDMzs4mPz//wLQ14+PjUSL+uLi4HWN0dFY1CRV6FpvXSDkXh1L32j4dm1hk9FoPZ574NVKtnfzyo4+iUSsJrq2x9K1v4RsZwVhfT8LP/izCIRgtS/oqQRAwmUyYTCb52u12u+V2qBShJRGtyAito4qN34EDxTPPwOoq/PqvhwnW174GB6Xn2gGxWoEDAwN4PJ72Q1mBDbhvxEqpVPYODg5WnopwbzUajXse4X8QkJCQEBUSe1Tg9/tlobnDETanlSZmSkpKdvWkK01iPQjEKqTREBwYYOxP/jsmWzGiO4NHy5IZ+NTP8exv/T2v/vgFin8hDk1JEb6RMTzd3VgBd1MTS2VlaAsK0Obno9zHtq6vrzM4OIjNZqOkpOSupglFUWRwcJD5+XlOnDix6wvlysoKt27dihkkHAmfz0dLSwt1dXXEx8fT2dlJW1sbNTU1KJVKRFGkra2N6urqTX5MoVCIwcFBTp8+vWm5U1NTNDQ0RP1OGtmPxHaO65HQ6XSbiJVGoyEUCm1KO5A8rSI9tgRBoLS0lP7+/ijndQh/Z9PS0hgYGJBDeCXj1NzcXHJzcxkbG+PWrVucPHky5rEUBIHy8nLGxsZkr6ud9KNqtZra2lrm5ua4evXqrgcQNkKhUMgZkKOjo1y6dEn+/7u5+YdCIWZnZ+Ug7Y2fuW2MznkzK90eFpvXSL0QPme7Jtz89f+9jFKtofzpArTVIhq1jvWZGRzf/CbB1VUS3/52jCdO7Hud94rFxcVNVUwJ0rZIxNLj8bC4uMjExAS3b9+WsyolonVgQvEDgDQ5d0/J36/9Gjid8Ad/ENZa/cM/wCF0M4LB4KZrUU9Pj8dms7Xd8w+PgftGrJaWlm4ODAy8K5JYGQyGh3KCTqVSEQwG77uAfX19PYpIKRQKLBYLycnJlJaW7qtlYLFY6O7ujum+fBQQGS+TkpxM1qVLFH/mM/Lfi/4KXgd8Ua1i+qufwtRaSNyxPtSZ+YTi4/ELAra5OfwLC3ivXiWk16OyWsMkq6AATV4eym38qwKBgOx4XlhYuOvK0lZYW1ujra0Nq9XK2bNnd30+LSws0NPTQ319/bbC+EAgQEtLCxUVFXLLrqamhtHRUa5evcqJEyeYnZ3FbDbHJGeTk5OkpKRsauM5nU40Gs2mCsxG/yrYfZbZVvtR0llFVhnT0tLo7++nvLw8ap+lpqYyNDQUU6NRXFzMlStXWFpaIhAI0NXVFWWcmpeXh8fjoaura9t2X15eHjqdjmvXrlFfX7+rbUtLS8NsNtPR0cHc3ByVlZX7+n5Kk5yRMTlFRUWbKoe7xfT0NGlpaTsSBilGp7CwUPZ867H3YEnLx3bVhbnByE+7nNwYXKO2vobHn/s1EqrLaQks0991BdN3XkJpNJL84Q+j2WYI4KARCoX2lKWn1+vJzs6WLTo8Hg92u52pqSk6OztRq9Uy0TKbzfeVaB1aRM/v/36YXH3602Fy9dnP3lNytb6+HvO70d7evsYuJgLvBe4bsVpdXe3q7Ox0AfLjtnTBO+xw38PA/RCw+3w+mUgtLS2hVCqxWCzylNtBuIPvZKZ5v+B2u5mcnIyOl/nWt8Dng/l5gpMzTP1DH0bdEiPmWyhGZpn6zkXyxhfIdF1DWPghSq8XJdEZTaJKRSg+nqBeT8hgwGs0Qloaivx8lKWlqI4dQ5GTQzAjg7E7juy5ubl7dkvfCFEUZff1mpoaeRJuN5icnGRsbIzTp09vq1sKhULcvHlTDumNhBRyff36dYLBIK973es2vV+K3InVHtzKA8put28i5bsRrktQqVSbKlySziqSWCkUCjlPMLICJAgCZWVl9PX1bdKECYLAsWPHuHr1KgkJCZw+fXrTepWVldHW1sbw8PC22pW0tDQ0Gg03btyImrjcDlqtlvr6etkVfTuT152gVqspKyuTY3KGh4f3FNwN4XNwdHSU+vr6PX12ZIzOhGEO5w9EvvWNMfp1WqqzPSiD/5uc1JNUJj9K98zzXFzr4ansbMxPP73tQ8u9wNLSEmazed/3H71eL7dAIdz6t9vtzMzM0N3dLV+DLRYLSUlJh5ohu7y8vGMg+IHhT/4kTK7++q8hIQE++cl79lFbGZ729PSIwOA9++BtcD81VgMdHR0eIogVhE/Mex3uez9wGAJ26UssESnpaSk9PZ3Kysp7Rnw2GjPeL+wqXkang9xclLm5qNcqmL62SvBX38J/hG7hOvE+XtLn86GfXeBE6XvB5YK5OUIzM/S88grliYkobTaUc3MoZmcRJydhchKhowNhw+CJLzub4Isvcv78+bu+eHq9Xtrb2zEYDHuKy5Fahg6HgzNnzmz7PlEU6ezsJDExMSYBgvA5rFKpMJvN3LhxY5Pb/NjYGJmZmZueHkOhEDabjYqKiqjfBwIBgsHgpvbYXioGkpdV5PfKYrEwMjKy6bU5OTn09/dvaq1ZrVYGBwc3PdHbbDa6u7tJSUlBpVLFvCYJgkBtbS03btxAp9PFNE+VkJSURH19Pa2trVRUVOwqN1AQBHJycrBarbS1tZGYmEhZWdm+v8tarZaqqio8Hk9UTM5uPJuWlpbkwNv9QKlUkncyg9s/ncHo0JJfdZPnv/pnXHllhH/78jtxXv4aNYlrXGtMZa36caz6wyVVsDvT071Ap9PJ0UHw2sPu/Pw8vb29ctdAqmjdK388uIfC9VgQBPjbvw1fQz/1qXCI82//9j35qK2I1crKSlAUxfviOn4/idXo0NDQpscCo9GIy+V66IhVQkICMzMzB7pMqb9vt9tZXl6W+/uZmZlUVVUdWgUpLS2N6enp+0Ks7iZextIQdoXO6LSiqBRoeFcjvTcTGLONU10URBUfD/HxKEpK0GZmMq5UUlBQAIBw5weAYJDQ7Cy2V1/Fd/Uqmf/8z2hTUmJGoOwVMzMz9Pf37zrAV4Ioity+fRtRFGloaNixZTg4OIgoituuc19fH5mZmRQVFWG322lpaSEzM5OCggJEUWRiYoLz589vet/8/DzJycmb1kGqDmyEx+PZtWeYlAAQSYi0Wq1M2iK/AwkJCXi93pg5hGVlZfT29nL69Gm8Xi99fX14PB5OnTqFTqfjxo0bLCwsxDwGCoWCkydPygai25EUk8kke135fL5dZ7YZDAYaGxsZGRmRTUXv5iFNr9dTW1vL6uoqfX19DAwMUF5evm0ldGhoaN/WI6FQkIWlHibmm3EYLpC+quOnP/0iX/vH6/zMG1+H9WozPo+HgrwzdAhrXFzr4Rf0h389sdlssqbuXkCr1ZKRkSFn4kryjIWFBTlEXKpoWSyWAyVa91S4HgsKBfzjP4bJ1e/8Trgt+OEPH/jHxHISuDMt7DjwD9sl7huxEkXRn56e7ot18VtZWdnTTeRBQEJCguxXtF9IEykSkZImUqRolful30pKSqKzs/NQW7gHES+jNauIL9XhurVOcXUGU/ohBLGG//Xxf+Sn1Tf4whf+QX5tfn4+ly9fJicnJ6ryI4oiC4uL9I+MYK6uJsvrRfn3f4/4nvfc1fb5/X5u374NwNmzZ/dkmhsIBLh58yaJiYmUlJTsuE8mJydZWlqKaQAqweFwsLS0RGNjIxC++J8/f14WRkui3lhVscgg5EjE0lfB/ipWGyHprDYuPysri6mpqU3tR4lQ3Lx5E5fLJU9NSvujtraWa9eukZiYGPNYqNVqGhoauH79OidOnNiWGGq12iivq+Li4l2dt4IgUFhYSHJyMu3t7aSnp9+1FYjJZOLkyZOsrKzIFZSysrJN67+0tEQoFNpTC1oURRzOEaYWWpi23WQ9sIbbX45bb+Dyi1/l7194gSefeII/fc9bmRCduM8/wpTKhy+4zrBvju7JQUrT8w+tXSY90B+mpEGj0ZCeni5P6EZOZksPO0lJSTLR2q959qEI12NBpYKvfx3W1uCXfxlMJrjLa+NGrKysbLKN6e/vR6FQ3LeJsftZsUKtVg8MDAxkRV50ExMTZeb+MEGtVsecVtoKoihGEamVlRXZQyUvL+9IeagoFAri4+NZWVm5pz38UCjE3Nwck5OTBxYvYz1lxNnn5dh4Pv1ZTVgtfvSJhXzxi/+HZ575ec6ePQuEtTySAFiKY7Hb7fT19aHX6zl58iQGg4HV//k/ARDe9a59r9PCwgLd3d2UlJRs694dC9JEX3Z29q7sPRYWFhgbG+PMmTNbnk+BQIDbt29vIl6SMDo9PZ1Lly7J2qhIQuL1ellfX49JNOx2e0wfrb1orPR6PTabbdPvJZ1VLGJ17dq1KJfzQCDA2NgYq6urCILAo48+uunmqtPpKC0tpbOzk7q6upjrotPpqKuro7W1NaYeKxKSk/vt27e5ffv2nh4K4uPjOXfuHP39/Vy5coXjx4/fdQC4pCGz2+10dnai1+spKyvDYDAgiiK9vb1RE5XbweWeZ2qhmcmFFtzeRRQKNemWalKsdXz/VjLX+77L11/4BA0NF6j9m6d5Vq8CTCiYJ1mVQJU6l1TiEBYCXL58WY7RuRvt024wPz9/oG3A/UCtVkcFeUd6CQ4PDxMMBqOI1m7tOGJN3x4atFr493+HN70pbMlgMoWd2g8AoijG9LxrbW0N2Gy2lw/kQ/aB+0qsnE7nK62trY+Vl5fL3xaTyfRQTgZC+GLvcDhiVuMk11/J1dzpdGIwGLBYLBQUFBx519+0tDTm5ubuCbFyOp1MTEzIYboHGS9jKtCiTVYhtIEuS43Susr5d32SkfYX+ZVf+RXa2trkp8S8vDwuXbpEUlISw8PDKJVKqqur5fK66PejvnGDYGEhyhiEYScEAgF6enpwu9073phjYW1tjZaWFsrLy3fVll1ZWaGnp2dH/VV3dzf5+flb3rzHxsaorKwkOTmZwcFBBgYGyMnJITs7m6mpqZi6o2AwiN/vj3ljEEVx1w8NW1WsLBYLY2Njm36v0WgwGAysrKyg0WgYHR1lYWGB7OxsHnvsMTo6OrbUC2ZkZDA7Oyv7ccVCXFwc1dXVNDc309jYuC3pVygU1NTUMDAwQHNzM3V1dbuuzigUCsrLy3E4HLL5aW5u7l1fIywWixyT09raSmJiIklJSVExPrHgXXcybWtlcr6ZpdUJ/CodanMJiqwzrGoMXAk4cczNgSOZ1Ldk8q7bv8CvP/m72AcvkZVWSF7laZLV8aiECEKbBOWlZbJv1O3bt8nMzCQ7O/uepDzMz89vSZrvF1QqFSkpKfI9IxAIsLS0xOLiIiMjIwQCAdm02WKxbLlf7nv2ocEA//Ef8Pjj8K53wQsvhAOc7xKSHnvjeX/p0qVln8/XctcfsE/cV2K1srJytampafkDH/iAXF8WBCHmpM/DgEhX6MicqsXFRTmnymKxUFRURHx8/DItpbcAAQAASURBVJEmUhuRkpLC8PDwgekT1tfX5VafTqcjJyeHioqKA6/SCYKA9ZSR6f9Y4cRyEc0Jk2h0J/jgb32MP/+DP+Iv/uIv+MM//EMgTFwEQaCtrY2GhoZNJHL91i00k5MEfuM32GszYWlpiY6ODvLy8jh27Niej/3y8jJtbW0cP358V+TW7XZz69Yt6uvrt33qnZ+fx+v1bilo93g8sjBdEASqq6vx+/2yOaXX6+XEiROb2sRb6asCgcCeWjGSxmojJOf8jVKDYDCIyWSiubkZo9FIXl5elAVDWVkZra2tpKSkxDwG1dXVNDU1kZSUtCXxlSJlpOib7bZH8tIaHx+Xva72YgqalJTEuXPn6Onpobm5mZqamrsmHYIgkJKSQnJyMjMzM7S1tZGdnb0pxzUQ9DJpa6ff0ca0bwG3xojfnII7JY914c4wh7hMUiBAmspM9/dGyS1Z57ceeT1rC6UsDcRR7c7HUvumLc/3yBgdv9/P9PT0rmJ09or19XVCodCRj+VSqVTy/oDw+SwF34+NjeH3+zGbzXJFSzpH7Xb7PY3m2hXi4+FHP4JHHoEnn4SXXoINvnZ7xVYDYTdv3hSBzrta+F3gvhIr4NbVq1c32RcnJCSwvLx8YG7XRwGiKKJWq5menmZ1dVVO47ZYLJSWlkYlqz+IUKvVqNXqLSc0dgNRFFlYWGBiYgK3201WVhanTp068MyzjTDXGJh90UlOZypXz/Wi0bhJKn2Mp59+mn/4h3/gIx/5COPj46ytrVFRUUFPT09MrYP4b/+GACh//ud3/dmhUIiBgQEWFxc5efLkvvadNGHU0NCwq5bQ+vq6fBPe7vPW19fp6emhsbFxy3NzYGBgk45LrVZTVFREUlISvb29TE9P093dTVJSEmlpaVit1gPRV8FrIeexYDabWV5exmQyMTc3x/z8PG63G6vVikKh4PTp05tIj8FgIDExkdnZWVlgHAm1Wk1VVRXt7e2cPn16y/2SkZGB1+ulra2Nurq6Hb/bubm56PV62etqL609lUpFdXU1CwsLXLt2jdLS0pjrvlcIgoAoiuTk5JCYmMiVK1ewZqYyFT/PpGcaOz48ah0kJAKJqFCQpjZTpDaTpk4kTZ1IqjoRrULNn/31P/ClP/w1PvK7f4yx+r24Bl4C3oGi8JFdX/fUajV5eXnk5eXtKkZnL5idnb3vbcD9QKlUYrVasVqtlJaWEgwGWV5elk1L19fXiYuLw+v1Ho1ihdUaDmo+fz7cGnz1VTh2bN+Li2Uh4fV6cbvdq6Io+u5ybfeN+0qsRFFcTk9PD2w0zpSsCR5kYiWKIisrK3JFyu12yy2j4uJiEhMTH2giFQtZWVlMT0/LGqTdYnV1lYmJCebn5+Wn/cNsfSq1CpKOG1i8sUZ6vZllywrLcxn8rz/7n8xOzdPZ2UkoFJIDWSXfoxMb3KAVP/0pgeRkVLtsJ7hcLtrb20lNTaWxsXFfT97j4+NySPJuCGgwGKSlpYWysrJtNReiKNLR0UFZWdmWy11bW8PpdFJdXR3z75OTkxQXF8sVWofDwdzcnDxxl52djVKpJDExUa4U7EVfJUGhUMiVKVEUWVtbY3l5GY/Hw82bNzEYDLJ3m8lkQhAEFAoFc3NzMVt6JSUlXL9+fctqSHJyMnNzc4yNjcXUiEkoKCjA4/HQ09OzK31SSkoKGo2G5uZmamtr9yQUl96fmJjI7du3mZ2dpbq6+q5upKFQiKGhIfncyszM5Pvjr3AraEOlCGFBT6Umg3xTHunqJJJUJhTC5v315S9/mf/+X36d0uOP8r9+7Rkc3/xX9OnJrK4IuIbWSard+7rtJkZnL5iamtr0fX4QEemTBeFjODo6itvtpqOjA6/XS0JCgmzxYDAYDv8+lJEBL74YJldveANcvgz7rKYtLy9HZYAC3L59G5VK1X73K7p/3O+KFSqVamBgYCAjsoWUkJDA/Pz8fVyrvSMUCkURKWlk3Gq1UllZidFoRBAEurq68Pv9Dx2pAkhPT6epqWlXk2h+v5+ZmRkmJydRKpXk5ORQWlp630xGrQ0mFq+vcXygiB9mDsNsOt++5cSkjSPBqOGfPvMJLv3ke+QXlfLU089QU1NLenYBqZYEFAoB0W5H3dOD7x3vQLXDtktGi5OTk9TU1OxLlyYFHTudTs6cObOr/SaKIrdu3SIzM3PHp/Pp6WmUSuW2eYJ9fX2UlpbGPNbBYBCHwyGTLkEQ5At+KBTi4sWLJCUl4XA4GBkZwefzodfrCQQCqNVqxsfH0el0aLValEolCoWCUCjE6uoqoiji9/tl6wRpCtLv97O+vo7RaCQxMZHMzEwCgUBMw9KcnBy6urpiEiudTkdKSgqTk5NbDgBUVFTQ1NREcnLytlW/iooKbt68ycjIiGzVsR0SExNpaGjYk1YuEhqNhpMnTzI1NcWVK1dk7dt+MD4+TlpamkyslUolZ7NOcsv2Atlr6+TNZ1NQkE+2NXvLh4KvfOUr/NIv/RL5VRf4P1/8Z7zPfROF0Yj1mZ/D91M/zgEfYkhEUOzverhTjE4sm4+NkFrJD5vFD4T3j8/no7i4mLS0tKj7VFdXF263W75PWSwW+T51z5GfH65cXbgAr389NDXBLq1HJGwlXG9paQksLi7eN+E6HAFi5XK5XmltbX2krKxMPppxcXGsrt4XX69dIxQKySVXu90uPwlYrVaOHTu25ZNApM7qYYNKpSIuLo7l5eWYT9uR8TJOp5OMjAzq6uqOxAVNa1FhKtIg3gpR6YlnRenAKahxBAUWHWpOPf2nxOWc5falb/PZP/0jEARqzr+bt/7aX6HXwImmf+dnQiEuNb6fwM1ljDolJp0Co1aBUafEqFNg0ikI+n20tbXJk137IZKhUIjbt2+jUCi2tUiIhCiKdHV1YTKZNj3hbYTH42FoaEieiIwFp9OJ1+vd8qYttVZirdvy8jJJSUlRfj7SRbKnpweDwUAoFMLhcOD1egkGg4iiiMfjkS0BVCoVOp0OnU6HyWTCarXGrFQMDw/HjJIymUwEAoEtK2RFRUVcuXKFrKysmMdIGlxob2/fttooCALHjx/n+vXr6HS6XbXojEYjjY2NNDc34/V69xXenpWVhcViob29nbm5OSoqKvZ0rkmTkhtJabImEWtQZMag5D2nTzI2OsmlS5c22VNAWEf3u7/7u5TVnucDf/BPFF1/HjEYxPqhD6GMiyOu2M1Suwf31DrGnLtv98eM0enpISUlhZycnC09nLYasHhYEKmvUigUmM1mzGYzRUVFUZ2V7u5uubMiVbSkCu89QXk5/OQn8NhjYXJ16RLs4UFCIlWxhOter7f5oFd3L7jvxGplZeXqlStXlp955pkoAbtSqTwaPeE7iOxd2+121tfXSUxMxGKxUFtbu2tyYLFYGBoausdre/8g+QRFEispXmZmZobExMRwvExS0pGp2oVCIcbHx5lOmCVRl01ZRw5I2ltBxJPoYykhwImfvYDz3acZWRrjxk9+hMFowpjSiegW0H3jMyzFJdKSUURwaJlAKPZ5m6Z38vS5kn1P6AQCAVpbW+Uhh93uw+HhYfx+/5bhshJEUaS9vZ2qqqptv3u9vb2Ul5dv+fmTk5NbtggXFxc3RbMIgoBer0cURbKysmLeBC9evBgzTiUUCiEIQsz2j6TXjNX2zM7OZnJyMqYpqkajITMzk7GxsS1zMKVprKGhoW2NVZVKJQ0NDVy9ehWtVrurWBqNRsOZM2e4efMmHo9ny8rgdtDr9Zw+fZqxsTGampr2VB0dHh4mNzc35jlQo8/lpfUJel2d1FU0UlBQwMDAgOzinpycjCAImM1mvvrtn3BlIpHT3mHEJQfWX/gF1HfIeFyRDhTgHPQdCLGKRGSMzvz8PN3d3QQCAbKysjalA8zMzMj+bA8bAoGArO+NBUEQ5H1VWFgoD1UtLi7S19cna2YlonXgWuDjx+EHP4A3vhF+5mfglVdgly3wrSJ6bt68GQJuH9xK7h33nVixhYD9fuuspGkLiUhFTlvk5OTsu8qi0WgQRXHXflYPGpKTk+np6cHv9zM/Px8VL3MQ8S4HCVEUmZqaYnh4mPT0dM78bD3qt6oJ+UV89gDeBT/ehQBem5/EBSPr40EQ4RSFvDfrcTwJPpbGV+mzt1A/P8s/AX/9+6+n/q31nHlTFRlWMyqvgLCuQgwlMeN8HFOCdd+kyuv1yqP1u3XshnBbz2azcerUqR0viqOjo8TFxW27jndcjbfUaLndblmTFguLi4scP3485t/2o7HS6/XyOm2EFLcUa10zMjK4cuXKlgadBQUFXL58mdzc3C3P25KSEq5cuSLrm7ZCpIHoyZMnd+WArVQqqa+vp7Ozk/b2dmpqavaswxMEgfz8fJKTk2lrayMlJYXi4uJtl+N0Opmfn4/ZQgU4lXSSV2ZGubU2TB2N6HQ6qqurWVtbo7+/n7/7u79Do9HwyU9+kplADklaF4W9VzG/+ym0EdVSlV6BMVuDa8BL+usOxj5lI5RKpVwZ9Xg8cos0Li6OnJwc1Go1er3+yDzAHzT26l8lCALx8fHEx8fLiQrS9PrAwAAul0ueXrdarQczvX72LHz3u/DEE/DmN4dbhLsY4olFrHw+H2tra25RFL13t1J3h/t+lxNF0RFLwC45sB8WsYr0B7Hb7QSDQZlISen0BwVJW/KwtQOleBlRFLl48SJZWVm7jpc5TIiiyNzcHAMDA1itVhobG6OqHQq1gD5NjT5tQ+ZdJOGyBfAt+DHOaChvFTEASY0fpXj2Nj/5+xf48f/3Q/7kM18i8ZEM1rJnKZ1uYW7tjSSa9veVW11dpbW1dc+aGclYcDsDUAkul4vJycktb6gSdjKLnJyc3JL4hUIh1tfXtyRPwWBwz+TbYDAwPT0d829Wq5X29vaYf1Or1cTHx+NwOGJWkSRT2JGRkS0rUgqFgtraWm7durVja1ev11NXV8fNmzd3DMSWIAVBDw0N0dzczMmTJ/f1cGIymTh79iyDg4NcuXKF2tramOQuFArR0dGxLYnTKbVkBxVMqkJ4/G70agP+gIg3qOFr//Zd/uYv/pSq46dJr3wbU/5kzs82Y37D6zDEmP6KK9Yx96ITvyuIOu7e6iv1ej3FxcUUFRWxtLTExMQEs7OzWK3WPU+jPiiw2Wx35V8VSbTy8/Pl4ZDFxUWGhoai/BatVuv+h47e8Ab45jfh3e+Gt70tXMXa4fuxsrKySdbQ2dmJSqXq2PsKHCzuO7ECUKlUg0NDQxmRF6/ExEQGBgbu2WdGOtra7XZCoZDsaFtQUHBPR/xTUlKYn59/aIiV1+tlcnKS6elp4uLiyMvLw+FwxIwxud+w2Wz09fURHx9PQ0PDnqojsQiXKCZhf8OzBPUGHv+dD/M6cyGjfeM8/+JzvHn1DQg/FHj5Q0uoVVY865Bg2PtXzuFw0NHRwYkTJ/Y0Uu50Ounq6uL06dM7PpGHQiG5KrIdObDZbNuaRYqiyOzs7JbkbLsgcqmlt1ds5WUl/c3r9cbUWUFYxD4xMbFley43N5dLly6Rl5e35aRZXFwc2dnZ9Pb27thqjY+Pp6qqiubmZs6cObOrSokgCBQXF0fZMeznQU+hUFBaWkpqaiq3bt0iOzub/Pz8qH0+NDRESkqKfIwCQZFVbxCnJ4jLE8LlCeJyB2G5npDHx9+1zRFa17Hm8fGDL32cjkvPUn3h3TzxS59h1qcgyz1JltkHtbWx90dJmFg5B71YThzOA5ggCCQlJZGYmCg/4La1tSEIAtnZ2aSnpx+pyvrdYHFxcc9T2ttBEARMJpOs1YxMCBkZGYlKCLFYLCQmJu6+yvqOd8BXvgIf+AA8/XTYrX2b74fH49lKuP7SXWzigeBInD13BOwXSkpKohzYXS7XgX2G3++XXc3tdjuATKSKior2ncG0H1gsFrq7uw81W++gsTFeJjs7W46XEUWRycnJmGG39wsOh4O+vj60Wi3Hjx/ft9fWRgh+P0k3ruMpKcbcmIouIx7N8UzeVHmB7hvXeOV7lzjx1lq02rB4NNGwt6fy2dlZBgYGOHXq1J6eqCWrgZMnT+7qJjw4OLhjO0sURfr6+rZs40FYKJuQkLDljclut29JYvbTBoRw5SkQCGz5d6n6HWugwmKx0NnZuWVrXqlUUlhYyNDQEBUVFVt+Rn5+PtevX9+Vw7XVaqWgoIDW1lZOnTq16xtPVlYWWq1Wbifu9xxOTEzk3Llz9Pb2cu3adcxZlaz6lNiW3UzMBDEkJPPiyDwuTwi3b7NHmEIAo1KDoFvHr16ieGqRv/zf/42OvjZ+6Y1v5Xff/Q7M5n5MGaloM/NZVhTS0dGByWSitLQ06hjrUlWo45W4Bg6PWEmQwsFzc3PJzc1lbW2NycnJQ43RuZdwu91oNJp7ShIFQcBoNGI0GuUhC4lojY+Pc/v2bTQajTx1aDabtz/fn3kGnE746Efhgx+Er34VYjzoud3uIytchyNCrFZWVq5cunRp5f3vf3+i9DuFQoFOp9v3xVZKDbfb7TgcDvkpxWq1UlJScl976kqlUiaOBxXNclhYWVlhYmJCnmyMFS8jCIJcCbjfbr9Op1MOv66qqjr4/X3xIorVVTxVVcwuLqJcXmZpaYmGhgZeeu4v+b9X/54zy3+Lyhq2E4k37p5YjY6OMjMzw5kzZ/ZE/P1+P83NzVFxO9thaWkJm822o4B3bm6OuLi4bW/oExMT206x2e32LUXtd9OOEQRhy6qUZEgai1gJgkBGRgYzMzNbustnZWVx6dIlCgoKtiSpgiBQW1vLjRs3dpVfmZWVhdfrpb29nePHj+/65p2cnMzx48dpaWmhpqZm3/lvSqWSqqoqekfn+cYV6QFWxKRNAF8Is1FFthkMQTcG9zI65yK6xWk0C1Po/G4E4JU3xjOQn0m91siH3v0EH0n+EL/40Y8ibDgGyYSPwfz8PM3NzbJXnVarRRAE4kq0LHd6EIMigvLwSMz4+HhUS9toNFJWVkZpaemhxejcS8zNzd0X01PJ6kL6Pnk8Hux2O5OTk3R2dqJWq6OI1qYK+Uc+Ai4XfPzjYa3VF78IG74fWxkMt7S03HfhOhwRYgVcf/nllzcJ2CXh6W6Euj6fL4pIKRQKLBYLKSkplJWVHbnSrpSt9yAQq1jxMpWVlds+eWRlZXHlypU9Ta4dJNbW1ujr68Pn8+1ohnlX+M53CGk0BB55hInJSbKysmSnco8ibPxr8oIohC9wu6lYSaG3UmbgXsbkQ6EQLS0tFBcX72r6LBgM0tHRwcmTJ7c9nqIoMjAwQMM2ERSBQACn07nlvpYsE7YiT/t9iIKw95TX6425bKkqVVRUFPO92dnZtLW1bUmsFAoFJSUlDAwMbEkKIdx2LCoqorOzc1dmk4WFhXR1ddHX17entrkUmNzc3CzbHOwXBVnJCMySZVyiSDvDcYOe0MIC/oEZAouLIIbHYxUGA+r0dNSn69BkZKBOT8d8+yWGXm6h4/Wv42OP/89tP0cQBNLS0khNTWV6eppr166RlpZGYWEh8cU6HK1u1ibWMeUfToXb7XYTDAZjPngcVozOvcbc3Ny21eXDgl6vl41bISwdsdvtTE9P09XVhVqtlluHZrM5fK/+gz8IV67+9E/DUTh/8RdR5GpxcXGTvmp5eRm3270simJsXcAh4kiwDVEUVzMyMpaWl5eTI1sRFouF8fHxmMRKOjiLi4ssLS2hUqmwWCykpaVRXl5+5IjURqSmpnLjxo1tx7TvJ+42XkatVmM2m+Xg5MOCx+NhYGAAp9NJaWmpPPp9TxAMIj73HN7CQhbuGDP29vbKAmyPECZWBq+CQCgRgXXi9NuTpFAoRFtbG1qtdldRKJEQRZG2tjbS0tJ2HWnS09NDbm7ujm2lqampqOyxWJient7kZRSJlZWVbTVibrd737EkUhhzLGJlMBjweDxbtt4lz7m1tbUtBy3S09MZGhra9jUAmZmZzM7OMjs7uyPhEQSBqqoqWltbGRsb29FfLBJ6vT7K62o7B/jtoFUrSI5XsObTUqyDtZ/+FAwGtJnZ6MqrUKeloc5IR5lwZ/pLCK/3Cy+8wHuf/kUMKSbKzlXxdjEU03U91jZnZWWRkZHBxMQETU1NZKZmISgMOAe8h0asxsbGduUPdi9jdO4l/H4/gUDgSHgEboROpyMzM1M255WKIrOzs/T09KBUKsPdpd/8TazLyyg++1lISIA7ma0QW6t5+fJlgsHgjw91Y7bAkWEfoVDoJ5cvXy558skn5d9J8QzwWjnRbreztLQklxMzMzOpqqq6b47d+4VGo0GhUMR0jr2fOMh4mfz8fHp7ew+FWK2vrzM4OMji4iIlJSVUV1ff80qZ5/p19AsLeC5cIM3jIdlqxZ2bS29vL8eOHWNVCD84JQQTWfKqMOkDqLZpdfj9fjkAeCvvpO3Q09ODTqfblcM3hIXoq6urOwquQ6GQPFm4HXaKBYnlXxUJt9u97+qLRKxiQZpsWllZ2VJDJnlabRUiLggCZWVl9Pf3b7uNgiBQU1PDlStXSEpK2vFBRBAETpw4IRuI7qV1o1arOX36NG1tbXg8nm19xbZCKBRCE1xiOZiApagYR1MTttTzCIN5MCi9au3OTxjfvvU1/uyH/52i1DI+97b/S/I/p9EpzNwhXgICgHDnhzuFBmm1BOG1woOgJYUyvMEgIVHE3usk7Q1x97waJHlb7TUwfqsYHalVeJg63Z2wsLDwwAxHabXaKLNgScazYLPR+653UTY8TOof/RErZjOGX/kV/H4/Op1u03nygx/8YHlhYeH792MbNuKuiZUgCDrgEqC9s7xvi6L4KUEQaoEvAjogAHxEFMUtRWXz8/Pff+GFF5558sknEyF8kbXb7fh8Pl5++WV0Oh0Wi4WsrKwHkkjFQmpqKvPz8/tyVj5I3Kt4mfj4eAKBwI5P+XcDv9/PyMgIs7OzFBYWUlFRcc8JlSiKTExMMDM5yRkgrrQU28wMq9evk9fYyPXr11lYWMBFmFjFKTMYcwdJ2KYN6PF4aGlpobCwMGbMyk4YGRnB4/FQt8ucQr/fL08M7rS/NkabxMLq6ioKhWLbJ2S73b4tibubVqBer9922EXSWW1FrNLT07l8+fK2RpzJyckMDg7idDq3beFrNBoqKipob2+noaFhx/0r+VVJBqJ7yQhUKpXU1dXR3d3NrVu3OH78+J6ISV9fH9lWLVPjsGwM23hY1QbsgDdnidSsZPS68DEJhUT+9Ev/g8//4G94vOENfPG//18ExTptvgniBR3HTEVhY13JXFcU5f9GlLuKd14jhv905/WhUIhVzTKXLl2isLCQrKyse/Y9np6eJiMjY98EbqsYHb1eT05ODikpKfe9VTg3N7evh7OjAI1GQ3p6uvyQFRBF+PGPWZubo+PaNXw+Hzqdjrm5OSwWi6xnfOmll/zA1e2WLQjCl4EngAVRFKsifv8bwMcIc5UfiKL4+3ezDQdRsfIBj4uiuCoIghpoEgThBeB/Av9DFMUXBEF4M/AXwKPbLOfqiy++KN66dYuVlRV0Oh1Wq5W0tDTZrfthQ1paGt3d3fdl2w4rXiY/P5/R0dEdqyJ7RTAYZGxsjImJCfLy8rhw4cKhXMy8Xi8dHR3odDrqn3oKUlNRT0yge9ObcL38Mvryck6cOMG1a9c4/dtP8HHDf0cnrrHiDpBujv1E63Q6uXnzJseOHduX58zMzAyzs7O7IkkSbt++TUlJyY7HW9rPO3lbTU5ObqlRAuSx7O3E6XeTtGAwGLbNF5Umcbe62ahUKpKSklhcXNzSJ0yqWvX19W2rNYPwQ9Pc3NyOYn4JGo2GhoYGbty4QX19/Z4m/qSW4vDwMNevX6e+vn5X+3F6ehqXy0V9VTHXxheYdglkW6343fNACoXns+lf7MJsNlNWVoYgCAS+5eFXf/VX+fznP49KpUIUQ/y0//t0maycS6/CqLybVp4Fny+LwcFB2Ttsq1ik/UIURcbGxnY8frtFrBgdqUq/XYzOvUQoFMLpdB7ZNuVeofq7vwOLhYyPf5wMo5GbN2/KVhmDg4OEQqGw9MLjcYqiuLbD4r4CfB74qvQLQRAeA94GVIui6BME4a5LfXd9JxLDkIL91Hd+pOcW6bEuAZjZYTmrbrd7OSkpiUceeYQzZ85QXFxMTk4ODofjblfzSMJkMuHxeAgGg4f2mW63m/7+fi5evCiHzD7yyCO7usnuB2lpaSwuLrK+vn4gy5PiZy5dukQoFOL8+fPk5+cfCqmanZ3l2rVr5OXlUVNTg0qthtOnEW7cIPGJJ0ChYPn559FoNFTWHmNVsY6gF1EH41nZomJlt9u5efMmdXV1+yJV0sWloaFh1xXGmZkZRFHcVWVsZGSE7OzsbW/UkuHqdm0sqcqz1U1SvFPO2O9NdDsvKwhPfLndbvlzYiE7O5uJiYltP0cKkd7K6T0SlZWVjI6Obtmi3AiDwcCJEydobW3F5/Pt6j2RKCwsJDc3l2vXrm27LyCsURkaGuLEiRNY4lQYtAomF9dRZ2YiOsYBUHrVsnluU1MTLpeLz3/+83zhC1+QNayCoKBKnYooCLSv3X1Ul1arpaqqioaGBubn52lqasJms931ciXYbDZMJtM9kV8kJiZSXV3NhQsXMJvNdHd309TUxNjYGH7/ptmsewbJbf1BtYmIQk8PfO978Bu/AXe6Hk6nk/z8fCoqKjh//jxnz55leHgYURR31FeJongJ2Egofh34c1EUfXdes3C3q30gdyNBEJSCILQDC8BPRVG8Afw28JeCIEwCnwX+207LCQQCP+js7NzkwL68vHwQq3kkkZycfKAXjlgIBoNMTU1x9epV2tra0Ov1nD9/nuPHj2OxWO7pF1ChUJCXl8fo6OhdLUcURaanp7l06RJut5tz585RXFx8KEMKfr+fW7duMTU1xdmzZ0mNDAo9dQoGBlAGAiS88Y34Rkdxt7WxboC+H7Xw2Rf+B/gMBIJsIlYzMzN0d3dz+vTpfU2HulwuOjo6aGho2HWlx+v10t/fv+10mwS/38/U1NSOwmibzUZSUtK2xG4nfdXdag01Gs225F0QBOLi4nA6nVu+xmw243K5drwJlpeXyxYe20GlUlFdXU1bW9u2hC4SCQkJVFRU0NzcvK0311bIzMyksrKS69evb7mtXq/3/2fvveMby8vr//dVseXee++99zKzS11aIBBIgCSEpSQhbBJIgIQESAIB8mPhC0sJCb1tqIHQNgvswozHvdvj3nsvsi1bXZ/fHxpp7bE9lizJ9mw4r5deOytLV1fS1b3n8zznOYeenh7Ky8tRKpVWY8xwL+Y3DHjFxiIdrABg2DYhSRKRkZE8/PDDfPrTnz7xd5wbXoavbo/OvRGn9/c0+Pj4UFxcTElJCXNzczQ3NztEZs/C+Pi4xy1gbDE61dXVlJWVYTQaaWpqoquri/X1dYePhfPismwWPIKPfxx8fKy+VlgLAz4+Pkc4gkKhoLm5Wb20tPQ/53yVTOCaJEltkiTdlCTpeCCpk3ALsRJCmIUQxUA8UClJUj5WFvhOIUQC8E7gy2dt547OSn1kB+/4WTm66rvfEBsbe2ochysQQtgduxsaGtjb26OoqIi6ujoSExMvdGoyISGBpaWlc10obNWQW7dusbW1RXV1NTk5ORfmQ7axsWHPgisvLz8uUK2utv63vR3fsjK8kpLYefJJVvZWWegc58dtP2BvyxpbFXTIw2pycpKZmRlqamrOVSnU6XT2Spejz7cFLOfl5TkktJ2cnCQlJeXMStjc3Nw924Bwuu+MDa7oq+CZSte9Llo2ndW9thEXF3fm7zEoKAgvLy+HFkShoaGEhIQwOTl55mNtiIyMJCkpia6uLiyW4wadZyEsLMwenbOxsXHkb2azmc7OTvLz84/oHhPCvdjYM2GMjEPCjFxlwaC2VtI7OzuZmpqitLQUg8FAc3PzkfNxaGAqUdpdNjGwbHBvd8Hf35+ysjLy8vIYGxujra3tnuT4Xtja2kKpVF5oe84Wo/PAAw+QkpLC4uIiN27cYGRkxCPXNCGEyzE2VwaLi/Ctb8Gb3wx33s9pCzRH9FX3gAIIAaqBdwPfk1ysNri1fyKEUAM3gBcBfwL88M6fvg840tRufuqpp070s7rXCfF+RnBwMHt7e+ciHSdBp9MxPj7OzZs3mZ6eJiYmhgcffJCcnJxLy+yTy+UkJCQwOzvr1PNspGZ5eZny8nIKCgoubILSbDYzMDBgdz0/VUxbXm4de2prQ5LJCH7FKxAmEwvjfQizGZlMhuVOHGiQrxwhBAMDA6jVaoeiZk6CzQDUWcPT2dlZfH19HZoW0uv1rKysnEmYDAYD+/v7Zzq2nzXA4I6sNm9v73u20MLCwo4Rjbthmw48C7YJQUeqD9nZ2SwtLTlFCGyu3/39/eeqcAQGBlJdXc3Q0JCdKAoh6OvrIzY29piOLCHcSrRXFSEgSSi8dBi2reektrY2AGpqasjNzSU7O5v29nZ7wLokySj0SUKyWOjUeCaGLCgoiKqqKjIyMrh9+zZdXV3s758lpzmK8fHxS7O3sRlUFxcXc+3aNfz8/Ojp6aGpqYn5+Xm3nf83NjZONt28H/HYY2A2w9/8jf2ukxZo29vbHBwcbDmgrzoNC8AP78ia2gEL4BIzdZlYSZIUIUlS8J1/+wDPB0awaqoeuPOw53JoePc0CCE0Go1m6+6Sr80o9NkISZKIiYlheXn53NuwWCwsLS3R2tpqN7Krq6ujrKyMyMjIK9FrT0pKYm5uzqEVuFqtpqWlhenpaYqKiigpKbnQgFS1Wk1jYyO+vr5nV5QCAiA/H1pbAVCGhxP44IOsiT3kJgNymRyFxUqezLodurq6kMlklJaWnksXZrFY6OzsJDU11alV6f7+PjMzM/eMZTmM8fFx0tPTz9zHxcVF4uLi7nmM7e3tERAQcM/HuINY3ctyAazVj/39/XsSFZVKhVKpPDNOy5aXdi/BvA22oObe3l6nKlAZGRlIknTuzFQfHx9qamqYnZ1lcnKSqakpZDLZia3duFAlMgkWdgSKyEhkll0M29aKlc1vzzatGBYWRn19PVtbW7S3t6PX60mJKCN4f4N+7SxG4TnNaGhoKLW1tSQkJNDd3U1fXx86ne7M5+3u7mKxWO65ALgoKBQKewRYcXEx+/v73Lp1i97eXra2tlxqFS4sLDhkqH3lsbNjdVz//d+HQ8frSf5VDQ0NmEwmV/yr/gcrR0GSpEzAC3CJcLijYhUD/EaSpH6gA6vG6mfAW4FPSJLUB3wE+FNHNnbHz+rIfc92nVVcXBwLCwtOP29nZ4fbt29z8+ZNtre37WK+5OTkS43sOQlKpZLo6Oh7VgP29vbo6OiwO1FXVFRcaNneYrEwOjpqd85OTU11jJRWVUFbm32e3L+ujq0IH2QmIzKZDEkvUEjQ29VGYGDguS0hbK28iIgIu4uxo8/r6emxCu4daAHbPOMcEbfPz8+feSI/S19le01XhyfOErDbAmTPIk22OKazkJWV5XDVKjAwkNjYWEZGHNchSZJEQUGBfdrsPLB5Xa2srDAxMUFBQcGJx56XQkZUsNKqs4qLQ9KtY9g1YzFZaG1tpaqq6sjjFQoFxcXFJCUl0dzcjE6jIla3jx4Lo1r3SxsOw6b7qq+vJyIigtbWVgYHB++psbMtFK4abDE6Dz74IHFxcUxPT3Pz5k3Gx8fPHEC4G2azGbVa7bmUiYvEf/6nNdbm3e+233WSvgrgiSeecNi/SpKkbwMtQJYkSQuSJL0Z+AqQKknSAPAd4E+Ei0I4d0wF9gshSoQQhUKIfCHEB+/c3yiEKBNCFAkhqoQQXY5s7zSdla+vLxqN5pRn3d/w9/fHZDI5tPIyGAxMTU3R0NDA6OgoERERPPDAA+Tl5V35eJzU1FSmp6ePXYgODg7o6emhr6+P1NRUqqurL3xlqdFoaG62tujr6uqcI3TV1bC9DePWoqxBsrDvo0ApzHjLlUgCvIWRzMxMVlZWzj0hNDIyglKpdNqfZmJiwh4X4QhGR0fv6edkw+7uLt7e3meaYN4reNmGi6hYgbXacpasIDo6mrW1tTOrSz4+PoSFhTmskUxLS2N7e9upKWeZTEZZWRmzs7OsrZ1vWGlvbw+DwUBMTAzd3d2nTiEnhHuxuGlAHhOLzLQJFthbP+DlL385h42bDyM6Opra2loWFxcJ04bgZdLTtX9mc8ItsOU8PvDAAwQEBNDU1MTo6Oixttr+/j4HBwdXWndki9EpKyuzZ012dXXR2trK0tKSQ5Pjq6urREVFXYkOhUvQ6+FTn4LnPx8OmfGura2daIVyJw6vxZFNCyFeJ4SIEUIohRDxQogvCyEMQog/usNfSoUQv3b1LVzFwKPmX/7yl8euPLZsvWcr7iWaFUKwurpKR0cHLS0tCCGoqqqisrLyvsmtAqsGJiIiwl610ul03L59m87OTmJjY6mrq3Mo386dEEIwPT1NZ2cneXl5ZGVlOf952lbzd7QoGyarlubNf/USWv76kwAEaJT0roeRnJpOW1ub0+RqZmbG7pLuzIlzZ2eHlZUVsrKyHHq8RqNBo9EcnXw8BY6I1oUQaDSaM4mqXq93OC7pNNiia+4FR/SaMpmM8PBwh4hMRkYGExMTDrX4JEmipKSE/v5+pzQ1CoWCyspKhoaGnK7c7+7u0t3dTUVFBYWFhYSHh9Pa2npidSch3AuDSbATHIcMa1VPdqDgC1/4Aq95zWtOfQ0vLy+S0vxBvkPo7iqT+jV2zBc3bGQLfb9+/TpKpZJbt24xOTlpJyOjo6NkZmbeN4TDFqNTX19PXl4e29vbNDQ0cPv2bXZ2dk593vydrNL7Ho8/DsvL8J6jHp0nTTtubGywv7+/4YK+yiO4cldkIcS+TqdbuFvobHMpf7YiLi6OpaWjVl8ajYahoSFu3LjB6uoqGRkZXL9+nbS0NJcvQpcF24VocHCQ1tZWQkNDuXbt2qWstLRaLa2trWg0Gq5du+aU4/UR5ORYtVZ3dFZrRuvJL9w7DL1ykfnNHmpWBLOTOp4YVBAZm+LUOP3KygqLi4uUlpY69RmZzWZ6e3spLi52mCyOjIzYzSDvBYvFwvr6+pkETKPR4Ofnd8/tuephZYOPj8+ZFauAgAD29vbObN852g709vYmOjra4Vadr68vKSkpDA4OOvT4w69TUVFBT0+Pw9NkGo2Grq4uysvL7YajKSkppKam0tLScmw7NgH7EgHIZdbr1NL0yqmk0WjSMbV0k6c7P0jzwGfYYw9jUBJI0DXef6H+fGAdkklNTeXatWuYzWYaGhoYGRlBq9XeN/Eud8MWo/PAAw8QERHB6OgoDQ0NTE5OHhnUMBgM6HS6K9+1OBMWizVwuaTEWrG6A1tH5+4BmJ/97GdmnU73/YvezbNw5YgVwM7Ozjd+/OMfH1nSq1QqLBaL24wmrxq8vb1RKpVsb28zOztLY2MjAwMDBAUFcf36dQoLCwkODr5vVl0nwWQyMTMzg8Fg4ODggOvXr58pfPYUFhcXaW1tJT09nYKCAtemaORyqKiwV6yW9WtIwoJQCz41PcYffuX36Rq/wUNrgu1tIz/ul+ETmkhHR8eZF5/t7W1GRkaoqKhweh9HRkaIj493uK25s7OD0Wh0qGWyurpKRETEmYTtLJsFsF4U3JGzplKpzmynS5KEn5/fmRNlQUFB6HQ6h4w609LSmJ6edphIJCYmotPpnF4o+vn5UVxcTHt7+5nnwf39fTo6OigtLT32/cfExFBQUEBbW9uRCkiInxw/bxkLWya8o/wBC3/016/loYceOvL8vYMV+ia+yy/a/oH+ie+iVPgQlvFqRuJL2VPIeXVwDUnKCBobG+9ZYfEUFAoFmZmZ1NXVsbCwgFartZvi3q+wxehUVlba9W5tbW20t7fbF17nicK6cvjpT2F01FqtOnRdWF9fP5EcP/7441vb29vfvchddARXkljt7+//6PHHH1ffff+ztWolhGBjYwOj0UhbWxt6vZ6ysjKqq6uJi4u770dnLRYLU1NT3Lp1C7lcznOf+1w0Gs2Fr2jBehHv7OxkZWXFLn51C6qroa8PcXDAyu4mkhBsqmZ49cOVxCUn8hf/9UZ+1vQDXrFjQQb8/LYcvVfcPStXGo3GnjfnLPHY3NxkZ2fH4UBmgOHhYYeDaR1pA4K1VH8WsXKHcB0c87ICx2wXAOLj4x0aKlEqlSQkJDhsgitJEsXFxQwNDTm9ULTFy7S3t5/6+7GRqpKSklNjTUJDQ+0VMJsf12GjUO/4WMwWNbfH+ygoKEAIC8sbfTT1f5qnOz/I7HITMWFF1Be9i4OU5/MryyrBCj/eFvkiCv2SSUtLo7S0lP7+fsbGxi6F1Ozt7REYGGifYLx16xarq6v3NcGCZ2J0rl+/TlZWFuvr6wwODrK/v3/mYMaVx8c+BsnJ8OpXH7n7pDagXq/n9u3bRuBst94LxpUkVkKI2bm5uf27fV+ebTqru+NlsrKy8Pb2JiMjwyPxMhcNW1hxQ0MDRqOR+vp60tLS8PLyIiUlhYkJ1yMwnMHa2hpNTU32XES3Tk5WVYHJxOT3v0/abhiBCn/GYguZ91vlg59+MeWVhbzvx+/ks99+jN/VG4gOUfLrMTlrlnja2o6TK71eT2dnJ6WlpU6Luo1GI7dv36a4uNjhauDm5iYymcyhdqhOp8NgMJzZdhBC2K0W7gV3CNdtUCqVZ+rXHPXFsxErRy7EKSkpzM/PO6yd8/b2Jjs7m76+Pqcv9NHR0SQkJNDV1XXsuXt7e7S3t1NcXHzmAIi/vz/V1dWMjIzYCWRCuBdbGjPGyDgmV7vRG3Ukpqn4ZfsHaBv6TzQHK+Qkv5yHqj5MSvqr+IF+nJb9Uar8MnlrxAsIUzzzXQcEBFBXV4fFYqGpqelCh4+EEAwPD5OTk4NKpaKgoIDy8nKWlpZobm5+1vgiBgUFkZqaSkhICBEREQwODnLr1q0Lj9FxC5qaoLkZ/vZv4dD0shACtVp97Nx048YNZDLZL1yd4PMEriSxAjCbzT/8xS9+ceQDCwgIQKPRnMuN+KrAbDYzPz9/YrxMZGQkISEhHo+48TSEECwtLdkd32tra8nKyjpCZBITE1ldXXVoEtJVmEwm+vv7mZqaoqamhtjYWLe/hrm8HCFJxD36KNe39fx55ItJ8o5iNiqT7eRs3vGhCh56aSmPt3+BqdYNfkd2QGGSD11zMia1iTS1PCNoN5lMtLe3k5ube64g1YGBAdLS0hwmK0IIu7bKESwsLDgkkt3f38fX1/dMcueuihWcbbkAVuuD3d3dMwmNl5cXvr6+DrWz5HI5KSkpTjmsx8TEoFAozmW1kpSURGBgILdv37a/j93dXTo7OykrK3N4qlalUlFTU8PCwgLj4+MkhFl/o9NKLzq32gHwDZ/DTxVOZe5beUHVh8hKfBHjpm0+v/YLtkx7vDa0npcGl6GQjlfWZTIZ2dnZ5OXl0dnZyczMzIVUjFZXV/Hz8ztC6n19fSkpKaGwsJCpqSlaW1ufFTY+s7OzJCUl2WN0ysvLLzxGxy342McgLAwefvjI3dvb2yfKYL797W9vLy8vf/Mid9FRXFlitb6+/p3HH3/8yLJCkiSHy/hXCbZ4md7eXhoaGtjf3z81XiY5Odlph/KrAiEEa2tr9uDUysrKU+NTZDIZmZmZjI6OenSftra2aGxsJDAwkKqqKo84txsMBlqmptj41Kfw2d5GevBBfH/nlbxhMZQqvwzmfQPZzn4Rb/vHF/CxL7+SsGjByg1BjWmF5xUGMrEuMbCTzM2mDntUTVJS0rkEtzY7B2emg9bX1/Hx8XFI+GrLbHREz+GIvgrcW7FyxHJBkiSHHgeOi9htj11ZWXEqQDk/P5/JyUmnPYvA6qNlNpuZnJxErVbbherOCphtU4cajYaF2V8iYaFjcYjelX5C/cJ5zQv/jfqidxAbXoIZwU/VHXxvu4kIRSBvi3wRuT5nG1KGhIRQX1/P7u4ubW1tHl1Q2fzoTlsoBAQEUFFRQXZ2NsPDw3R0dNy3LTSLxcLq6ioxMTH2+y46RsctGB62hi0/8og9bNmGlZWVY0MyQgh+9atfmYDGC9xLh3FxgXHOo6utrc1sMpmOEA9bO/B+mPLQ6XTMz8+zuLhIQEAAiYmJFBUV3XMFHxwcjFardTmU9qKxtbXF8PAwKpWK0tJSh+JzYmJimJ6eZmdn51yVmXvBdnLd3NykoqLCY3E+Nj1LTk4OEfX18Na3wmc/Cx/9KPKSUl76+teT8N4386OQdbQptZRHalkM/x5PfszAL7/wBD95/Mv8QX05P2zZptuQhPqpFjITwxzSL90NvV7P8PAwtbW1DrcAbdWq8vJyhx6vVqvx8/NzSPO1sbHhkOeWO4mVI5OB8IzO6qzjIjIykqGhIcxm85laR5lMRlpaGuPj4+Tn5zu0v0qlkvz8fLq7u6isqkCpcHzaV5IkioqK7PFVtbW15z7OLcKAxaefjb02fJTxICvhjaUv5nrEq/ExWi9q68ZdvrfVxKpJTb1/Ds8LLEQuOb42t4VSr62t0dLSQmZmpkcE1zMzM0RGRp5ZBQ0ODqampoaNjQ36+vrw8/MjKyvrQlMeXIXtWnjSsWmL0QkNDcVkMrG8vExvby9CCBITE+0V0yuBu8KWD2N9ff1YFFFfXx8ymaxXCHEl+51XtmIlhLDI5fJbLS1Hfb9s+oirWtq8V7xMRESEQxc8W/zL/YCdnR3a2toYHx+noKCAsrIyh0/ukiSRn59/pJ3hDuzu7tLY2IhCoaCurs5jpEqtVtPe3k5RUdEzKyofH6tb8NQUvPe98KMfUVjyEO/811+iWF3npo+c+Io/JvMhBSs7K1x/1atYbP02b35+OGaLhdGDNNY21E5HHNly4HJycpyy4lheXiY4ONjhi4mjonUhBLu7uw4RZncuIhzxsgLHdVaSJBEVFeWwtjM+Pp7NzU2nKlDh4eFo5R080fwuWgc+z9xKKwbj2eRQCMHo6CgqlQovL69zVyPUmnludP8bMyu9GKSHMZgj2d1X8mBtNS8rfDX6LSO9B9P85/ov2LNo+aOwB3hhULFTpOowIiMjqaurY2Vlha6uLrdOeut0Oubm5sjIyHD4OeHh4dTV1RETE0NHRwe3b992qup4mZiZmSEpKenMx9lidGpraykpKXFrjI7LWFyEb34T3vQmuGuYaH9/Hy8vr2ME8Ac/+MH+8vLyVy9yN53BlSVWAIuLi1//3ve+d0TBLpPJ8Pf3P3fCuafgzngZm1noVSWP8IxHzuDgIJmZmVRVVZ3LQyUoKIigoCCHgm/PghCCyclJe3yLLWvNE1hbW7NP7J0o+A4Oho98BCYm4C1vIfCLX+fttX/FQx//b/53uZ2SP30T3/n3L6GQvPjdP3473/rSX1ASsYTBImffL4+ZmRmH41LAag7o5eV1bHLmXrBYLIyNjTkcTGs2m9na2nJoktIWP+HI5y+EcJvJraMtvqCgIIetABITEx0+PiVJOleL21sFZrOKmTUL7SPf439b30Pz7c8ys9yE3nC8TWUymejo6EAIQXV1NVVVVQwODjp1XhRCMLn4a250/z/mt7IY2/wbBhZiifHT0vStv+Hng00AtM+N8sPtVmKUIfxF5IvIVLmuUfTy8qKsrIzo6GiamprO7Sp/N4aGhsjKynK6EiNJEtHR0Vy/fp2QkBBaWloYHh6+0gJw2zCAzaPMUfj6+rotRsctsIUt/+3fHvvTSdOAAN///vcPzGbz/17E7p0HV6QOeCqe/ulPf6r/zGc+c+ROWzvQ3e0jZ2EwGFhYWGBhYQGVSkViYiJ5eXkuXyQUCgXh4eGsrKwc6Z1fBWi1WsbGxtjd3SU7O9stdgXZ2dk0NjYSExNz7km9g4MDent7CQoKor6+3qMWFXNzc8zNzVFTU3N2dSg2Fj7/efibv0H6wAco/+R3KPjaE/zmkd9B/+dv5seyn/En730D7/vHr/PNb6koT/pHOqd0vOl5JeytTdDV1UVxcfE9LxQHBwdMTU1RV1fn1PuYn58nMjLS4WrR8vIy0dHRDpElR/VVJpPJrd+VI+J1sF5IbW3Ds6p1tsgpR0X20dHRTE5OotFonLjoCfZMDzK5XszOyjQ7a72UVMYRtNSBv/cPiQ5NJDa8mNiwYswmBZ2dnaSlpdm1dCqVirKyMjo7O6murj5zP/VGDd0j32RoUbCmeRtaox8pkV6IlVv841vfzubmJkWxkVREwvaejgcD8nkgIO/cVarTEBcXR1hYGL29vaysrJCbm3vu9tTm5iYGg8GpxcXdkCSJ+Ph4YmNjmZ+fp7Gxkfj4eFJSUq5O2+wOpqenTwzUdhS2GJ2IiAiMRiOLi4t0dXWhUChITEwkKirK81Y/p4Qt27C6ukpJScmR+xYXF9FoNMtCCLVnd+78uNIVKyGE1mQyjd+d7n6ZflYXFS+TkpLisC/ORUCv1zMwMEB7e/uRAFR3QKlUkp6ezvCw83YkNkuH9vZ2srKyyMvL89jJwNZ6WV5eprq62jn3+4wM+Pa3oasLr8oaXvShx3le+avRbH6dz73zP/h/r/4yCeuvQLH+GXzQ8dMONTm5eURERNDc3HwqWbAFLBcUFDhFSs1mM1NTU04F0zoSuGyDI8HL4F59FVgr2o5W+ZwZhElISHCqapWVleVU4LLAjFn4UrxqwfCTH/H1/+8vefdrX89H//FJvvndeH7ZXcLPO7f59o2v84u2xwiN1RAafvRzCwgIoKioiPb29ntWWta2x/jvW49zY7Sa2e1XEOwfzCtLFTR86z28+Y9+j7AAfx792D/zspT3YFSa8PPTk6eNdDupskGlUtkr3o2NjWxvbzu9DYvFwsDAgNORT6dBJpORlJTE9evXkclk3Lp1i+np6SszkW4ymdjY2HCJRB7GaTE6/f39np2cPCFs2QaDwYDJZDq2SPjJT35i2tvb+5bndsp1XC0KfgI2Nja+/qMf/aj07/7u7+zLai8vL7y8vJxcEboGjUbD3Nwcq6urhIWFkZGRQVBQkMdaTf7+/kiS5JAPkCdhNBqZnJxkZWWFtLQ08vLyPPKe4+PjmZubc0rIrtfr6evrs+vY3OpLdRcsFgv9/f1IkkRlZeX5P4PSUqQnn4Tf/AbFu9/Jc9/1GHsRXyP5ea9BO/5mWtqj+FLT83npO77LjV/v8NznZhAQEEBraytFRUXHkuunpqYIDg52OmNxdnaWuLg4h41HtVotFovF4d+bo9+jVqt1u1hYLpdz99DLSQgLC2N2dtYhzVhsbCxNTU0Ot5cjIiIYHx93+HMQQjA2MMJ3H30b//K7j1KQWsatgV/x69En+UnXL/jl1/x41xd7WZdXYDRoGdncI2D4FlFBWrLjI0mLLcTPJ5zQ0FAyMjJob2+nurr6yCLDIsw03r5Jy7gv+4aXEewreFlFCHmJPvzH5z/PN7/5Td78yhdT9vaHKW+tQCaXSH9zJAVh0XR0WCdWHdHznAeSJJGcnEx4eDi9vb2Eh4eTmZnp8ELVJlh39/VALpeTlpZGYmIiU1NTNDQ02CuFl5mCYcsF9MQ+2GJ0cnJyWF9fZ3x8nIODA+Lj44mPj3dfnNopYcs2LC0tnWiN861vfWt7b2/vv92zE57BlSdWer3+x9/4xjf+9TCxgmfM+xz13jkPjEYjS0tLzM/P28V/WVlZF+aEbqtaFRYWXsjrHYbZbGZ6epr5+XmSk5PtKzdP4bCQva6u7swTxsrKit0A0F2rttNgMpno7Oy0X7TccTIz1NXR8egnyd9YQXz1P0n+3leQxJfxiSukaWWFr//DQ+y+4z9InGgh4QXXqK6upqOjg7i4OFJTU5Ekid3dXRYWFqivr3f6/czOznLt2jWHnzM3N+ewhcPBwQEqlcqh48WmxXInbO3AsxYkwcHB9PX1ObRNpVJJQEAA29vbx8jtacjJyWFkZMQeQXIvCGFhR73HzMooB0F6Ql8VwhvNf8XDt/+G9Y45Ztcnubau5cB3hrf/29sxKbxIL3sxGeUvYWApA5VigVD/flIifShMSSEmJoaenh7KysqQJImZ1Q1+0j7FhiYLb4Wel5T6kR0tY3xsEBGazSuiwtF85j34FV+n6pe5KALlZL0xCu8Q6yWiurqarq4udDqdRwON/f39qa2tZWJigqamJoqLi8/8HrVaLXNzc07/DpyBUqkkKyuLlJQUxsfHaWhoIDMz0+HWuDthq9LX1NR49HVkMhlRUVFERUWh1+tZWFigra3NLnuJjIx07ZpgC1v++tdP/PPCwgJlZWVH7lOr1UxNTe0LIabO/8Kex5UnVkKI1djY2LnJycmIw6Pb0dHRNDY2kpWV5dYD2xYvMzc3x97ent2l+zKc0KOiohgZGXFblpojsFgszM3NMT09TXx8PNeuXbswbUFQUBBhYWFMTk6e2qIyGo0MDg5iMBiora31eBi1Xq+nvb2d5ORkh9tgZ8FsNtPe3k52Tg7h0c+B17wO/cwka597lKivfZcfmnTMH5j4/Idfz6O/9+e8f3ESn8xMKp//fCa3tmhubqawsNAesOws0Z+amiIpKcnh71UIwfLyssMXLkf1VWAlVm6LFboDm4D9rAuyTCZDpVI5rJ2yTes6SqxCQkKQJImtra0zn2MRFrQHVvd9b19vKiOy2NfsE/GKSNoz1qjSPIBizIfIhSxenP4qfjX5U57+7qM8/d1HiY9P4vm//+ckV76WJbWSpjEzPkotoT4mFht62BNBjC17I5fCqEjd4aGybFqablH64ofZ297mvz/yHtqeE0dI6POo+EUWqkglaW8IR+n/zHFl87rq7++nr6+PwsJCjy20bB53UVFRdHd3k7qzQ7zJhFRaCklJRzLkbNOweXl5F3Ke8vLyIi8vz641nZiYcJvW1FGsr68TGBh4YdcEeCZGJy0tjZ2dHebm5hgeHiYyMpLExETnuyoWCzz6KBQXHwlbtuHg4ACZTHbsd/n973/fpNfrv3b+d3IxuPLECmBzc/MzX/3qVz/3r//6r/a5eYVC4fQK8l44ODhgfn6epaUlQkJCSElJsZ8YLwu28vj09DRZWVkefS2b8ePExARRUVHU19d7tLV2GrKysrh16xZRUVHHfqybm5vcvn2b1NRUEhISPP7daDQaOjs7yc3NdZtvmhCCrq4uEhISjlTavJPTSHj0PzD96yeZ+vaX8P+3r/CR0V4MP/h3hotLia5cZXN8nNiyMqJLS2lqaiI4ONjpSUyDwcDi4iLXr193+DlbW1sEBQU5fOHa2NhwuGXkTtd1GxwVsMMzOitHSHNYWBgDAwMOtRltyM7O5vbt22d7iwkLWq11xN9XpSI+Lp4bN26wvb3NC2vqUKlU1kSDaTVvKPpTHh5+Gxubqzw5+3OemvwZ/uZxXmT5X3ZNwXzyv39ASvlzOUh+Hou7AUgYSQwd5BXVxfgpY3jPu/6Gxx57jKSIcP7iAw/z1MuTKepPIb0lAf8UL5JfF4ZcdZw0SZJEYWEhExMTtLe3U15e7lEyYxtE0ZeWIvX3W+8MCbFejEtKoKSElehofO7EuVwkfHx8KCoqQqPRMDo6yvj4ONnZ2W65Fp2F8fHxS+li2BAUFERBQQFms5nV1VUGBwcxGo0kJCQQFxfn2HXjpz+FkRH4r/86QpRtWFhYONHj7POf//z29vb2lbVZsOG+IFYGg+G/v/Wtbz36oQ99yO/wySkhIYGFhYVzH8w207T5+XmEECQkJFxohcYRJCQk2Pv6ntgvmxh/dHSUsLAwxybdPAiZTEZRURF9fX32lqDZbGZkZAS1Wk1lZeWFGPhtbW3R19dHaWmp26ZPhRDcvn2bwMDAU4mHwtuH1Df+JZY/eYTb3/w5hn/9JEUjnSh6u9lLTUDf242hvYjElBRkvr40NzVRVFzssLZkYmKCtLQ0p6pcjnpX2bCzs+NwpIq7xetgrVg5mgUXHh7O3NycQ8RKkiRiYmJYXl52uHoZGBiIj48P6+vr9yTnAgu6O8TK38uLpqYm0tLSmJ2dtX9XkiQRlxpCXGoIFoOF1cEgIrui+JO5tyIQrO2q+d+N/+HpJ3+K4cc/JMjfj9r6Kspq83nw9Y8gNyspKS9ibGKC33uwhqJPvQlTqB8P9ZTh3+5HUK6KxN8LRaY8nQBKkkRGRgYqlYqWlhYqKys9er6Qy+X4pqZiXl1l8vWvJ3Z1Fb/xcaTPfQ70emKAaJUKCgvtZIuSEigosHrKeRj+/v6UlZWxu7trH77Jyck5l/WMI9ja2rK3pS8bcrmc2NhYYmNj7WbYTU1NdjPs8PDw0xcTtrDl17zm2J9skWh3TznPz8+zsrKyKoS48iaPV4dB3ANCCE18fHx3Z2fnQxUVFfb7w8PDGRwcxGKxOFyWFkKwvb3N3Nwc29vbxMTEUFRU5DETSVchl8tJSEhgdnbWIRdrZ7CxscHIyAj+/v5UVlZemeBnmxh7cnKSiIgIent7iY+Pd8pR3BWsrKwwOjpKVVWVWy/6k5OTmM1mh6qPMkmi4A0vY7SolM4faJDf+gJezZ+maGoe49NP4/Xgg+hLyggMCWF6dBS/oiJS7uhpToNOp2Ntbc0pXaLJZGJnZ8fhxYtWq8XLy8vh36PFYnG7ZtGZilVwcDD9tmqIA0hISKCnp8eptnBWVhZdXV33NAi2CAv+IdGUp9bhI1dQXV2Kj48PKpWK/v7+Y1oTmZeMmJIgYkqC0G+b2OjWIPXCG/UP83vveTU/1fyE34w9yc2GVv73yV9T5xNJcVoudVGRvOrPX4bytZUES4E8v6UUQ5+FsHJf4l4WjCRz7PeVkJBgJ1fl5eWeHSLKzET+xBOkfOQjDAwPYzKZKMjJYfTHPyZFrSZwchJ6euA737FOmQHI5ZCdfZRsFRdbK14egC0ya2tri4GBAXvItruvK+Pj4x7vXpwHKpWKjIwM0tPT7dfXgYEBYmJiSEhIOPo52MKWP/OZI2HLNuzs7ODn53es8vXNb35Tu7Oz8zlPvxd34L4gVgCLi4uf/uIXv1hVUVERbLtPJpMRHh7O2tramQLm88TLXBUkJSXR2NhISkqKW3QNarWa4eFhlEolxU5UOy4SmZmZPPXUU8zPz1NWVuaxFeDdmJmZYXFxkZqaGrdqGBYWFlhfX6eqqsqpYy6rKJaf7y2zuP8SPtT/A+J3F/hURBBVTzzJ3vw0xt//Q0J3d2F2lplf/5rAkhKCSktRnDAlaDMDdeYYWlxcJCYmxuF93tzcdHhC0Ww2e0Sn46hJKFjPIV5eXg67v9tCpff39x2+aPr5+REUFMTy8vKpAeAmk5HsqpfxjqDXgNeyfZETFxfHysrKqRNSAN4hCuKeF0zsc4LQzBjY6vbh9UN/yOtL/5CdB3b5tbyBrt8JY/RATdY33s6Bt4xr3jmk/jKOvRE9UQ8EEPXcAKfPhREREZSUlNDR0XHixKrbkJkJBgPK5WVKSkpYXl7mZlMTgampBB4WcAsBMzNWkmW7/frX8K1Dk/lJSUfJVkkJxMWd2I46D0JDQ6mtrWVtbY3u7m4CAwPJzMx0y6J1d3cXi8XicDX4MnBSjE5fX9/RGJ1TwpZtOC3k/Stf+Yrm4ODgO55+D+7AfUOsgF/97Gc/M9ytb0hISGBiYuJEYmWxWFhZWWFubs7eA/b0WL4noFQqiYmJYX5+3qVx5729PYaHh7FYLOTm5l66wepp2N/fp6enh8jIyAuz1LBl5mk0mmNj6q5ifX2dqakpamtrz0Uknl8VxWfWLXwo6gd8+xsfpHropzwc4McnpucI/ud/RjzyFrxf+Xr2hofR3bqF7tYtFLGx+BYU4JufjzwoiP39fdRqNQUFBU699sLCAqUnjEKfhs3NTYenBz2hrwKr/tJsNjv8+LCwMDY3Nx3OrbN5WjlT+cvKyqK1tfUYSdVoNIyMjGAyGrCgRG6RUFiO7ntBQQFNTU2Ehobek/xJMomAVG8CUr2J11lQD2jx7fHilfMvQ3xLoE7YZS5lhbqCbMSPlezN6Yl7aRDhVef/fQUFBVFVVUVHRweZmZmeMTS2xdOMj0NKCsHBwfZzeG9vL/n5+dZrgiRZTSZTUuBVr3rm+WtrVpLV2/sM4frxj61EDCA8/DjZysgAF0h/ZGQkERERrKys0N7eTnh4OBkZGS4t1sbHx52K6rlsKHZ2SFhaImF6GsPwMNr+fvYnJggaHkb7nveg8vXlbjorhGB9fZ3c3Nwj99++fRudTjd8lU1BD+O+IVZCCGNMTMwvnn766T9+6KGH7PcHBQWh0WgwGo32H5ttamFjY4PIyEjy8vKuRE/aFaSmptLc3ExiYqLTK8uDgwNGRkbQarVkZ2c77Xl0URBCMDs7y8zMDIWFhYSGhjI6Osro6Cg5OTkee12LxUJvby9KpZLy8nK3VjF3d3cZHBykurr63Bo5b6WMF5cG8l0dvOadn+Z1rQ/z6ac+wt9Xp/CXsm3yH/sCe//zU1Sf/xz+f/AHLDc1oRsexvSLX7D7i1/glZTERkgIWTU1Tr03jUZz4mTOvbC9ve1wALGniBVYV86OSgTCwsJYXFx0mFjFxMRw69YtpyaSVSoVERERzM/Pk5iYiE6nY3R01J5gsDGp5ImvfJCfDg/zX+/5xJHn2ibRent7Ha54ylUywsr9CCv3Q7duZKvnAGWfnJC5IPZuWpBkBhJfHUJIgeutbl9fX2pqauxeV664gZ8IW+TS2BiW5z+f7u5uCgsLCQsLs7ujFxQUnH5ei4yEhx6y3mzY24P+/qPVrU9+EmzGqn5+UFR0lGzl5YETejKbJi86OpqFhQWam5uJiYkhNTXV6cX9/v4+Wq32ap27hYDNTSvhnZiw3g7/+5DRq5ck4ZWQgEhP5+D6dUZf+lJ2bt4kNjaWhIQE+3lgY2OD0NDQY7/bL3/5y7vLy8uPXej7cwH3DbECWFlZ+dznP//5lzz00EP2o8t28C4sLCCEcHu8zFWBl5cXYWFh92wn3A2dTsfY2BhqtZqsrCwiIyOvbOtTp9PR19eHSqWivr7eTkIyMzNpaWlhfX3dI5M/RqORzs5OIiMj3a5h02q1dHV1UV5e7nLIsHZ9lJcXxTC46s+qopJPJf8QH60RdeEE307PoupjXyD1Ja9i/g9eTOhj/4nPi1/MdG8v+/39hG5uEjg7i5ifR/fiF6NyMBvQGad1sH6HSqXS4WqfJ4TrNth0Vo6060JCQhgYGHB42wqFgpCQEDY2Npw6JjMyMmhsbGRvb4/19XUyMzMpLCy0DmhMwN7WKgatGi+OO8dHRkaysrLC7OwsycnJDr8mgCpCSewLg4h5XiB7k3qWOjbZCVwlKM991SUvLy+qq6vp7u5Gq9WSk5PjvnNNVBQEBMDYGGNjY4SHh9vtPGwi6Z6eHkJCQsjOznbsnB8QAHV11psNBgMMDR0lW1//OnzujqxHobCSK5tey/bfM2QKkiTZJ+ZmZ2dpbGwkMTGR5ORkh38rtqGTCz9/CwHr60cJ02ECdThvU5Ksrdb0dHjta63/TU+3Vv9SUkClQgJ8gRKe8Yk8HKOzvLx87Pi2WCx8//vf11sslicu8J27hPuKWAHtra2tOpu+wWKxsL6+ztbWFltbW2RnZ1NVVXWpU22eRHp6Oh0dHWdqXgwGAxMTE6ytrZGZmUlBQcGVJVRgddgdHR0lLy/v2OSUJEmUlpbS0tJCTU2NywTlMHQ6He3t7aSlpTlcrXAURqOR9vZ2ioqKXK6WLiwsIEkSZblxlOfC0paBpv5d/Dok4gbzGFsc4V3+/vy5fpu//96T6P83h/FH/5G0t7wLCgu5eeMG/tvbJMzPs/mtb+GdmUnwi198og7LBiEEKysrDgc0g3P6KrAST0+1o50hVnK5HKVSiV6vd/jckZiYyPT0tMPEymw2Mzc3h8FgQKvVHjPcNZvlGLUH+Hr5IslOjk3Jzc2lsbGRiIiIc4miJblEYKaKwMw4Jia09Pb2UlJS4rZzg1wup7y8nMHBQXp6eiguLnbPwlaSIDMTw8AAW1tbx4wxfX19qa2tZXJyksbGRoqLi8+nyfTyshKl4uJn9D8WC9jE8bbbE0/A1772zPPS0o63Ek+QpshkMlJSUkhISGB6epqGhga7dcy9PiedTodarfacxYIQsLp6vOJk+/feoRBwmcw6zZeeDlVVVtJkI1ApKU5V9JRKJUlJSSQlJbG3t8fMzAxLS0soFArkcrldS9bQ0ABwUwihc+fb9iTuK2IlhBARERHf/va3v/3Ompoa+draGmFhYeTk5DAwMEBcXNyzllSB9WIREBDA2toaUVFRx/5uMpmYmppicXGR1NRUj7uluwqj0Uh/fz9CCOrq6k7VH6hUKvLy8uju7qbGyXbWadjb26Orq4v8/HyHzSwdhc0ANCMjw2VBr1arZXx8/Ig5Z2yoF695MJyNUiP9P93kFbyKmr94Ef8+9nFqf/JNHtvdp/bP/oHZx7/L5qMfxS8gmKL6esZGRpAGBwmbnmb1s5/Fv6aGgAceQHbCb2Z9fZ3Q0FCntGabm5sOV1PBWrHyVMi4MwJ2eEZn5ej+h4SE0N/ff0SCcBJsLtlTU1PEx8fznOc8h+bm5mNtSpNFjlG3T5iXH7JTiJVCoaCoqIienh6H0gnuhfT0dG7fvs3IyIhb2+y2BIXJyUna2tooLy93i6bVnJqKubGR0tLSE9+3JEmkp6cTGRlJb28vMTExpKenu36ukMms5CEjwxoUbMPy8lGy1d0NP/jBM3+Pjj5OtlJTQZJQKBRkZGSQnJzMxMQEDQ0NZGRkEBsbe+L+Tk5O2tMWzg0hrPt8N3my3TSaZx4rl1tJUnq6taJ3mDwlJ1sJqJsREBBgP9+EhYUdidH5j//4D/XS0tJn3f6iHoTkaGCpW15MklRAA+CNldT9QAjxT5IkfRewzZAGA2ohRPEp28iorKzs/eEPf+gbHR1tP/HPzs6i1+udWmHfj9jf36erq4tr167Zf2hms5nZ2Vl77pkzJebLwvr6OoODg6Snpzssdh4aGkKhULj8HW9ubtpH2N09bWgzAA0NDSU1NdXlbbW2tpKenn7Pysja8AELP9jCYoZfB2zxxG8+zCNyLS//9VNIRhNDLyjH/CevJ/6lr8PX7M1Yby++AwMELC0h8/cn6IUvxKewEOnQhb6zs5O0tDRCnBhPv3HjBteuXXP42GtqaqKystLhC++NGzd48MEHHXrs8vIyu7u7Do+mr6+vs7y87FRVYHx83B5eezeMRiNzc3PMz88TERFxRLhss904fBx/98aHeecb/ossnwS++a73EP/W5576uiMjI3Z3clcghKCzs5OIiAin24uOYHFxkcnJSSoqKlzS0gkhWHjLW4j/2teQDg7OrIpYLBZGR0fZ2tqiuLj44qx0dnaOCuR7eqytRdsgRWDgEXNTSkogJwed2cz4+Djb29t2x3nbuV2n09Ha2urYItligaWlk/VOExNweKGhUFjJ02HSZPt3UhJcwoCXLVHCNqxkMBiYnJzk+c9//vbS0lK4EOLEFYckSV8BXgasCSHy79znMKfwBC66YqUHniuE0EiSpAQaJUn6XyHEH9geIEnSJ4Cd0zYghBiPjY1dUCgUmYdP4HFxcdy6dcttWW5XFX5+fgQHB7O0tGTXlk1OThIXF3flzE1PgtlsZmhoCI1GQ1VVlVMn3OzsbJqbmwkLCzu3iHNpaYnx8XGqq6s9IpweGhrCx8fHZVIFVusHf3//M9tNkTm+BP+lF1P/tclDK2Ekv/Df6A/3YuvlY2R8+m8o/lkLIT9rYS/4vUy/6jkoX/96wv7w99nsGUDR1oblhz9kr62NkJe9DK+4OAwGA/v7+06Ndev1ensJ31GcVe1xBT4+PqysrDj8+NDQUIaGhpx6jYSEBDo6Oo6QEo1Gw9TUFFtbW6dOIScnJ9PQ0EBycrKdbGklXzKy6ygjBkl+csXKhszMTJqamoiKinKplWprs7e2tqJSqdyeuWnrILS2tlJeXn7ulvj4+Di+WVlIFgtMTcEZFTaZTEZOTg5bW1t0dHSQkpJyrqEfpxEUBA88YL3ZoNPBwMBRsvXFLz5Dcry9UeXnU1BSgiE3l5mpKabi4sgsKSE8PJzR0dGjFikWCywuntyym5yEw/5tSqW1SpaRAc997lHylJh4oofUZUFzp2J2eALcy8uLwcFBi9ls/vZppOoOvgZ8FviG7Q5nOIUncKGfrLCWx2w1R+Wdm71kJlmP/N8HTl+uAXt7e5/54he/+LH3ve999iujQqEgLCzs1DbZswk2EezY2BhRUVH3bKNdJajVanp7e0lKSiI/P9/pE51MJqOsrIzW1tZzEaPJyUlWV1epra31yAV9amoKnU7nlD3BadBoNE4Fy3oFK8h8ayQLP1OT1QMJ7NMQHsn3//hT/MPPPktM4//wWrWGl3/t56i+8lO2EyMx/t4Lsbz+j5G2BYq2Dtb/8z+R5+ZyUFBAXFycU9+Ps/oqT1fKnW0FyuVy5HK5U7mcKpUKpVLJzs4O+/v7zM7OIoQgNTX1nrpGuVxOamoqExMT9rFyrcyX3/uDf+KBWZBkg/d8XZlMRom/P/LcXCzXryN761vhwQfPZQ8gl8upqKigpaUFLy8vt3tRhYeHU1ZWRmdnp32Szxmsr6+zvr5OjY2sjI2dSaxsCA0Npb6+nsHBQVZWVigqKnKrRtMhqFRQXm692WA2W9/H4erWj36E15e+RCaQIUnoEhNZS08nICmJmOBgK2kaH7f+V69/ZlteXlaNV3o6vPCFR6tPCQnWtt59gNOGMj7xiU9sra6ufvpezxVCNEiSdPzJOM4p3I0Lp6ySJMmBLiAd+JwQou3Qn68Bq0KI8XttQ6PRfP0LX/jCB/7hH/7B53B5NDk5meHh4WctsbJ5fIyMjODl5UVsbOx94WtisVgYHx9nbW3NZZdmHx8fCgoK6OzspLa21qEKiRCCoaEhdDod1dXVHtGdLS0tsbKyQnV1tcsrY5v9Q1FRkVMVIJlSIuF3g/GL92Lh5/CQ2sxemJaaN7yb/lf/HZ9+6hv89dPf4E+Cg3hXWix5j/0Xsk9+i5W8ZNZ/7yWIvGJChoZRjIxgSUpiT6vFLysLmQNEY3Nz06mKh06n86jTv1KpxGgbnXcQNp2Vo7ovjUaDJEl2G5SCggKHj21bVFVqaioqlQq95Ivyzppckp1NOv0/+lEsW1uIJ56wOo6npsKb3wxvfCM4oXMDa2WgoqKCtrY2Kioq3O4bFxgYSHV1tV136KiOTaPRMDAwQE1NDTLdHd3y2JhTr23Tpa2urtLS0kJWVpZTOkCPQC63ksOcHHjd66z3CQELC9DTg9TTg09PD7LWViKffhqLtzeW1FTkmZnwkpccJU9xcfcNeToNZrOZtbW1Y1q/qakpZmdnF4UQoy5s3iFO4W5cOLESQpiBYkmSgoEfSZKUL4SwzTq/Dvi2A9vYi42Nffqpp5567Qtf+EL7/YGBgRiNRo/641wWtra2GB4exsfHh7KyMry8vOxu7Fe5/be3t0dvby+RkZHU1dW5hdSEh4eTkJBAb2/vqWJWG8xmMz09Pfj4+Jz52PNic3OT8fHxcxuA3o3x8XEiIiLO5bAsSRKh5b4Mr9wmzpCOYjyWwFVBvszESx54C+PP/3MGtZt8OS2dnEfmuf3I7/L6PT0FH/x3LJLEQlUOW2XFRKi32J2aQq1QIOLiCCgsJKigANkpv6utrS2nRNAHBwce/Y3avmchhMPfeVhYGKurq6cSKyEEarWa1dVVVldX8fb2Jj4+nv39fXJycpz67mUyGRkZGYyNjVFYWIhOePPev8rmz+r+ir/POqNK2dkJ3/8+0vvfT/tznkPe6CgB3/0u/OM/wgc+AC99KbzlLfDiFzvc7vH19aW0tJTOzk6P5IX6+PhQW1tLR0cHWq32TGsTo9FIV1cXJSUl1iqTSgUREdaqzTkQFRVFSEgIfX19rKysUFBQcLWMoiXJWmFKSICXv9yejlFTUMC2Vsvw6Ch+fn5kZWVdSFbqRWJ5eZno6Ohjv5/PfvazexsbGx91cfMOcQp349KuyEIItSRJN4AXAQOSJCmAVwFl93ziHSwvL/9/H/vYx57/whe+8MhIV2JiIrOzs065Il9l7OzsMDw8jEwmo6Cg4IjYOjExkampqSsp2BdCMD09zfz8PEVFRW6PYUhOTmZnZ4fJyUnS09NPfIzN8sBmyucJ7O3t0d/fT3V1tVtO1Gq1mrW1tWMBpM5gcXGR4BR/UvLDEWbB/pyBjf5tGPKlatuHSimAvVkzDVsaPq+K5H3TfZQGBfPPhdnUzs2S+Ln/AsAYHoo5KwdtRAT6nh6WwsIwRUfjm5tLaGkpijvHosFgQCaTOUXwPelhZYNKpXKqMhYaGmoP0rXBbDazvr7O6uoqW1tbBAYGEh0dTVpamv373t7edihW627ExsYyOTnJ/r4GrUGBTqdBQjp1KtCOv/97CA9Hete7KFQoaJck6n75S5QzM/CVr8BXvwo/+Ym1cvXww/CmN1krWmcgKCiI3Nxc2tvbqampcfuCTalUUl1dTU9PDwMDA+Tl5Z1IeoUQdHd3k56efvS8kZnpdMXqMLy8vCgvL2dxcdFuKuruiWB3YXh42LpQ8fcnzN+fujvRbZ2dnYSEhNiDsJ8NmJ2dpaSk5Mh9BoOB73znO1qj0fij827XWU7hTlwosZIkKQIw3iFVPsDzgf/vzp+fD4wIIRYc2ZYQojcmJmZzaWkp/HBpNy4ujoaGBqcz0a4abFEXBoOBnJycE6ezThLBXgVotVaPnICAAOrr6z02oVhQUEBLSwsBAQHH2r9ardbp1oOz0Ol0dHV1UVZW5pbqi9lspq+vj7KysnMfuxaLhYmJCbvXjySX8E/xxj8lmsSXWZgd7GexaxaflTReJmXxkj/8GQ3rbXyt6T95+a1fofTy5un/fRLj8JOE3eogvWWEkKYm67bDw9ElJaGPi2M9ORldSgreWVlYkpKc1s446jHlCmxeVo5+NwqFAplMhkajYXNzk5WVFbRaLREREcTFxVFQUHDi95KYmMjo6KjTxEqSJLKyshgZGWFfayVTvl5+SPJ7tAKfegqeftrqEh4YiC+QlpbGwMCA9eL00Y/CBz8IP/85fOlL1v//8Ifhec+zVrFe+cp7TtVFRkai1+vp7OyksrLS7edQmUxGaWkpw8PD9orU3eeH4eFhAgMDj3vLZWbCk0+69PqSJBEfH09YWBi9vb2srKyQk5Nzpaao19fXUSqVR0ilJElERUURGRnJ0tISra2tREZGkpGRcbUqb05id3cXuVx+bJH1ox/9yGI2m78nhDC4sHmnOIU7cdEVqxjg63d0VjLge0KIn93522txsmS3s7Pz8c9//vOf+tCHPmQ/Q8vlciIjI1leXna76eNFQKvVMjo6ikajISsr654TYXK5nLS0NMbHx8nLy7vAvTwdCwsLjI+Pk5+f7xGn9MOQyWSUl5fT0tKCr6+vfepod3eXrq4ujwbD2qph+fn5brNsGB4eJiEhwSWNy9zcHNHR0Se2cmRyGSmFxcTlZDA49SMWJyYI2irheeEVPBhZzVT9OE/P/ob1oXz2gwr4gOYv0dUE8NzrKbzW5EdB2xQ+Nxrw7eoCwBQWhj4xEX1SEkRFMZWVhVdhIQGJifjHxiL39T013Pbg4MDjx4dNwH6vY8BoNLKzs4NarUatVrO/v097ezuJiYnk5uY6NMkWFBSETqdzymDUhsjISEYmhtEdWImVj9IXmXRKxcpisVarEhPhbW+z3x0fH8/y8jLLy8vWNqZSCb/7u9bbwoK1gvXlL1v1PKGh8IY3WEnWKeeMhIQEtFot/f39HgmqlySJ3NxcpqamaG1tPWK5sbCwgEajoaKi4vgTMzOt72Vvz+qc7gJ8fHyorq5menqaxsZGj1TVzwMhBMPDw6cOwEiSRFxcnD07trGxkbi4OFJTU6+0JOQ0TE9Pn9hN+NjHPra5trb2SUe2IUnSt4EHgXBJkhaAfxJCfJlzcAp34UJ9rNwNSZJ84+LipmdmZiIPH1QHBwd0d3c7PFF1FaDX6xkfH2dzc5OsrKwjXib3ghCChoYGKisrL1VXZjAY6O/vt7csL3IVtbu7S3d3N9XV1ezt7TE4OEhZWZnH8iEtFgttbW0kJia6jbyvr68zMTHhkvjdbDbT0NBAfX29Q5//hnqM3vFvo9GuEq96ADGWjb8uCsOyGWEQ/MvP3sUvBn+K1nhAaEg0JS94Hq9/22t4Q2gSihsN8OtfI27cQNo5eZLZolBg8fdH+PsjBQUhDw5GCgqCwEBW9HpC3/pWvF70olPJ191wxscKrBdprVZrH/AwGo2o1Wo7kdJoNCgUCoKCgggKCiI4OJiDgwM2NzcdXqjojBYmV/R0ja6zq5MIC/LF11tmv/l5y+/8V4aPl4RMaWafPXZMu6iNu+yYNCxrt2h9epcvvukNfOLVX+CNr4sk9FWvOP5i3/se/MEfWF2//+RPjvxJr9fT3NxMbW3tyeTOYrFWur70JfjRj6yZeNXV8Na3Wo0v7yLzQgj6+/tRqVQOe4GdB8vLy4yNjVFZWcnBwQGDg4PU1taeTBL++7/h1a+2mnHe1TpyBYd1oBkZGZfa6VhcXGRjY4OioiKHHm82m5mZmWFubo6kpCSSk5Pvm06N0WikqamJBx544Mg5b3h4mOc973kdS0tLlZe4ey7hviZWAFFRUf/x2c9+9q2vec1rjhxNbW1tZGdneywyw10wGo1MTk6ysrJCenq602PuAKurq8zPz1N+eKT3ArG6usrQ0NClTtysr6/T19eHUqmkqqrKY/oDIQQ9PT0EBgaequ1yFkajkcbGRpe9tSYmJgCc2i+zxcjY3C8Ym/8FQkgkRpUTH16FvyEZzayRmYENfvXUE/yy+0c0T97gLdf/mte85C8xR5gIjNBTWJ3M4E++S1lSEqaJCfS3b2OamkLSalF4eyP5+mI2mzHv7CB2dlDs7yM/OEC5uYlSq0WXm8ven/0Zlle9Cm9/f1QqFd7e3if+Bk4jVhaLBZ1OZ68a2f69s7PD7u4u3t7eCCHsJCo4OJigoCACAgKOvY7RaKSlpYXr16+f+plt7BoZXdIxtqRnbl2P2QLeSlBK25glBTvbGszCG5mkRCZXIMlkyOXKZwxYJQsojfabpNCzPbXF0De+yp/lv5HnvVhL6O/eRayMxmdCgHt7T5wEW1lZYW5ujoqKinufQ9bX4ZvftJKs4WErqXrd66wkq7zcTnSFELS3txMdHU1SUtLp23MRW1tbdHd3I0kStbW1p/8Gbt+GwkLrFOQf/MHJjzknbJPL6+vrFBcXu30y0hHYFkbnie4yGo1MTU2xtLREWloaCQkJV97PcXJyEuDYIMPDDz+s/sY3vvGHZrP5vskGvBv3PbGSJCm1uLi4taen50hfYX19nYWFhWOiuKsCs9lsF3fbDOxcWWm0tbWRmprq8fbKYZhMJgYHB9HpdJfjEXMHQggmJyeZn5+3h8F6SjMxPDyMyWSioKDAbdvs7u4mMjLSYQf6k2AjZ9evXz/Xex8YbmPzoIs93QQmsw4fr2DioypJiKwk0C8W/a6J/pYFFic0BGmC6Or8X979gz+jJKGS55a8jJe88nepfmk2vhFKzPv7HPT0sN/VhXlzE8nHB9+iIvwqKlBGRGAymWh86inKx8bw/sxnUE5MYIyOZvX1r2fxxS9Ge0pLY29v78QqpCRJqFQqOymz/VuSJLvezJnflu3iZqv6mcyCmTU9Y0s6xpZ0bGmsTtohfkaEppvetu8RlZ9AUczvsDo0z7v+7o+ObfPh9/wdtQ+9lInhYT7xzkeQZFbfLJlMgSST88q3fYLXxj9IwhoklPUR8oq7iNV//if8+Z9bRem/8zun7ntvby+hoaEkJiae/UaFgJYWq2Hl975nNa0sLLS2Cf/wDyE0FJPJRGtrKxkZGR6zsTk4OKClpQWAwsLC089hWi34+lo1ZO9/v0f2ZXt7m76+Pnv15yLJycjICEql0qUweIPBYCeImZmZZ+bKXhaEENy8efOYge7Ozg5ZWVkLq6urSWeYgl5p3PfECiA2Nrb5ySefrDkcR2FrkdXU1FwpYbfFYmFubo7p6WkSEhJISUlxCwk4ODigo6ODa9euXUgpeGtri/7+/otzNT4FQggGBgYwmUwUFRUxMzPD5uYm5eXlbt+nmZkZ1tfX3brtpaUllpaWXK42joyMoFKpzhVNcvi3IpPDymY/82ttrG0NI7AQ5J9AQmQl8ZHlqLyCMAsLP+hs4luf+w49v/wli8vWSll2dD6f/LNvE1ESQ2KFP+ExXhimp9nv7EQ7PAxmM15JSXgVFzN4cEDttWvWFtUTT8DHPw43b1rdq//sz+Cv/srq0XMIzrYCbSdvZ54DMDg4iE9AGNvGAMaWdEyu6DGYBHKZINx/i42Z/6W/9Sd0NY8zO7UOwJtq385fPe+9bOpW+dXtJzBbzFiEBZPFhNli5oGM55MRlcOiep7/7voWZsmMRTIjZBYskpnXPe8NxCtTkR0YSSgfIuTlL39mhw4OrL5Fqalw69Y9W6cmk4nGxkYqKyudm7rc2bFWgr74RejqslbGfu/34K1vRV9dTUtrK8XFxW7XIen1elpaWigqKsLHx4f29nZSU1NPX2QkJcH169aKm4dwOB2iuLj4QiQW+/v7dHZ2uu38rdVqGRsbs8c6RUREXCmCZbMsuTtC6v/9v/+n/+AHP/jParX63y5nz9yDZwWxkiTpBa9//eu/+/jjjx8ZnZudnUWn03lUI+AohBAsLi4yMTFxbFzbXRgdHUUul7utRXUSLBYLIyMjbG9vX2wO1wkwm810dXURGBhIVlaW/cQxPDyM0Wi8p/u1s1hZWWFyctKt1TCdTkdLS4vLzvm2i9N5Q7e3t7eZnJw8Ru50hl0W1zuZX21HrZlDQkZESDYJUVXEhBVhQPDtkV8yuDbP8H/3sdU+y7+98ouEamV85tf/H1tij7rnvIQXvu4FpMfJMd3utVaxtrawKBT4pqfjnZ6OKj0dRWgodHTAJz4B3/++1UX89a+Hv/1baxWFM4iVyWSN9Rgast4GB2FoCPPYGLLoaKS0NCsxOXxLS4OQEA70Fpa3DSxvG1neMjK/rkV9JxnER6nHXzHK7toNsjN1KMyCP3vt46xvqilOrODBjBdSXVRLTrCBQMMokmwfyWJBoETghcD7zn+9sOANCj+E0g8UviBTYZFUCOGFEArMJjky7TTRZXtHidW//Ru8971WUuWAbnRzc5ORkRFqa2vPd/z39FjF7t/6lpVwpadj+OM/piMvj+IXvchtv3mTyURLS4s9H892X2dnJ2FhYSeHKD//+dbA4NZWt+zDvbC+vs7AwAAZGRkuVZPPghCCtrY2MjIyzh3VdRr29/cZGRlBp9ORk5PjsWEeZ9HU1ERRUdGRlqvFYiE1NXVjdnY2Qwihvry9cx3PFmIli4qKmh4aGko8fODYetaXmaEnhGBlZYWxsTHCwsLIyMhwu/meDWazmVu3bjmdwecodnd33Zsc7wIMBgPt7e3Ex8cfq9IIIejr68PHx8ctpHpra4vbt2+7tfpp068kJye73GIZGBggKCiIhISEcz2/r6+PmJgYIiMjT33M3sEy86vtzK+1o9Vvo5B7Ex1ahHrdm8qK57OEnn7tLMMHC6jWAvnl336Zpqafozfq8PcOoDzruVx7wat54R++jEDNFAHTA/hsbGBWqwGQh4binZqBPDYNhdaM/Eufx+v7X0PS7qMrfS67L3s7MxHZpFfGEihfQDE9coRAMTpq1SHZkJwMubks+foSJZcjn5mx5sytrx95Xzq/QLYiktiKTGQ7Kom9qEi0sX5shRzQv9xNd9sAve1zqBTe/OrdP0CyZDE4N0B4bDSKLEFKlImY2CAUoSEoQkIYmZoiKCCA6KAgLAcHmPf3sRwcPHO76//Nd+6zB/UCUkkJsa98pfV/trasJPDaNfjpTx3+TgcHB1GpVC61ldBqrYLxL34RGhoQcjkbNTWE/PmfoygttVbRzrk4tFgstLe3ExcXd+y4tVgs9PX1IZfLjy+O/uIv4Nvftn4uF3D+MRqN9Pf3I4SgsLDQI92P5eVllpaWKCvznN3S7u6u3aPtsrXHW1tb9nDuw3jyySd505ve9N2lpaXXXtKuuQ3PCmIFEBQU9Nd/8zd/85F/+qd/OlL/npiYQJIk104w58T6+jqjo6P4+/uTlZV1ISVlTwjZbRqmpaUlioqKLn0g4ODggPb2drKzs0/1DrJYLPaVryvfvUajoaOjg6qqKrcaWs7OzqJWqx2e/jkNNr+u69evn4vo2hYfDz74oINTqBY2diaYX21jcb0bs8WaWyaXeeHvG4XKN4YtvxDm5DB3sM3yE+Ms/c8onR03eSjnZbznRf/KjHyXr/36/xHo7Ye/3AdfmTd+Mh+K4ipIj8xCazhgeOU2gWYT2eNPkXb7h6gONjH4R6A82EaymKz7IknoYyPQZ8Siy0hAn5GAISUBTXwCWlkAer2czU09OimAbVMAO8YQxAH4L4yhmuwhaKGP0LUJwjZXiNzZIU5vRG5+RtZhBhYlGXt+4UgRmQQmlbGWFcJ+eTQZD9QSnZp7TERui2Gprq52+DsQQiAMBiwHB2i3t+mdnaXe9n285z3WNmlfHzih6zObzTQ2NlJSUuIeO5CxMfjylzF/5SvINzas9ymVVguE3Nxnbnl51qiVexAQi8VCV1cXoaGhp/42hRCMjo6yu7tLWVnZM1XiT30K3vlOK0G+QHPPpaUlRkdHycvLu+cCxFnYFsPV1dUXolHd3t5meHgYb29vsrKyLkWk39bWRlZW1rG2clVV1UZ7e/sDQgjn0tCvIJ41xEqSJJ/o6OjpycnJqMMXQJPJxK1bt84t6j0PbAevl5cX2dnZF37wtrW1kZaW5hZX4YODA3p6eggJCSErK+vSjfTUajU9PT0UFxefaJp6GBaLhY6ODiIiIs7lvG5rsZWUlLiVTO7v79PR0UF9fb3LldTe3l6ioqIczre7GwsLC+zt7TkVR2PDwGA/Sh8t3j5Gdg+W0RyssLe/jNagBkCv8GY7IJrtwGj2UeC3IKdkORtdh4Y/euzFaA0HWA7pU9/w6g/xwHMeZnJlgI986EX2+72A1wN/kZVEQH4ZM/oQPvzL7zCn9MPi5YPCywuZtzcv+MP3EFnwACszIzT/9N9ReqtQKFUY9Qdotud51VvfSmZqEN2/+hmff+xr9u1LkkRURCQ//dJPSNL5M/TET1nqbCBf7k+sxYhMO4NyZx6/jU2kw+dLpdLqKZWcDCkp1ltyMn27u2Q+73n4JCefq6Jz+/ZtQkJCiAcrSXnNa+Ab33B6Ozs7O/T19VFfX+8+3aXRyPKTT3LQ1UWqTodka71OTVnF8GAlmxkZzxAtG+nKzMTi5UV3dzdBQUEO5ZzOzs4yPz9PZWWltVr0xBPWyJ6mJqitdc97chA6nY7e3l58fX3Jzc11SxfEHYL188CWORsQEHBhi36wVs4GBwftBsY2dHZ28vKXv7xxaWnp2oXsiIfxrCFWAGFhYf/ygQ984O/++q//+kivbWRkBB8fH4+ODIP1oBkZGcFisZCTk3NplR13CNmFEMzPzzM1NUVBQYHbe//nwdraGkNDQ1RUVDis8zCbzXR0dBAdHe2UsNum/8jKynLrClUIQXNzs1v0DhqNhp6eHurr68/dlm1paXEqPPgwbG3nu9sjRpOWvYOVO7dldg9WWDaqWfT2Zts/ArPcSjaEEJgNJowHeow74K0IwVsehn7LzGLPBMY9C8Y9MyadAaNeS0r+NcLj0tlamab9F1+xWjpotcgP9Fj0ev702jtIyi7gqZ1f8x/f+GcMRh1GvR6FSklgbCgv+uCfEFucxsHINtvNiyR4JZAiSybNlEKA9pn3rwsycBCmZTlmk6n0FaIDg3leYCEpBMPsLMzMwPT08f+urR3/kMLDITr67FtoqL21ZSP0D3zrW0jf+Ia1WnSOoQSw5k6aTKZzEed7wZYKYW/VabXWdqytNWu7TUxYBxQAIZOhj4/HlJmJf2XlM8QrKwvucWFfXV1leHjYKshfXHzGKPSNb3Tre3IEQghmZ2eZmZmhsLDQpd+wuwXrzuIiZSo2dHV1kZSUdGzR/4IXvGDzqaeeeqkQos2jO3BBeFYRK0mSguLj48enpqYiDgvDDQYDzc3Nx4zI3IX9/X1GR0fRarVXRiDoipBdr9fT29uLt7c3+fn5V8LRd25ujtnZWSorK53+8dvIVVRUFCkpKWc+/l76D1fhzgtdZ2cnSUlJ57bY0Gq1dHd3nyuX0GQy2c39HH6OWc/O/jJPjzYSm5iMt1cA3l7+yGSnV3WEAIMBNBrBxOgs6elJ+Pgq8FWBt0JCLpMhQ4ZFDeYxC4YRgWneeiGXh0jIks3sqdSEyCMwrJgxLwvYv+PThMASakEfYUAXZWA/Qstu+AE6LwM6iwH9npaXxleT4e3gyPrBAczMYBofZ/LmTTIDA5FWV2Fl5ehNpzv+XKUSoqLsREutVBL04x8jPfIIPPaYw5/x8c/PfUT+7u329vbi7+9/78qTTgdjY1gGBlj5zW8ImJsjYG7OGqZs05VJklVHdridmJsL2dlwZwG1vb1Nb28vJfn5BMfGWlukH/6w296Ps9jf36enp4ewsDCysrKcJkY2jWV6evqlL1qFECwsLDA5OemxwSp45jOrq6s78nsaGRnhOc95Tt/y8nKx21/0knD5V0w3QgixExUV9Z3HH3/8bW984xvt783Ly4vw8HCWlpbcGnOj0+kYHR1lZ2eH7OzsKzXSmp6ezq1bt4iJiXFqimd5eZmRkRFycnKczj7zBIQQjI2NoVarzx0MK5fLqaiooLOzEyHEPduCNsfp0NBQt5OqnZ0dlpeX3ZIIsLOzg8FgcMm3bG5u7tzTTtvb205fqBVyb8ICk4ncn6E+yonPwBcIBjExzQOnVZ2j7tyugVFjZndEx86Qlr0+PSpLKFrJjCpCQWCGEp8YL3xilPjEKJF7n35BvDlyk7QUxxIQrPvpC7m5KHJz0cTHs52ScvwzEsIayXI32Tp8W1wkaGUFXUQEXn//97jSfJckieLiYre1ng9vt6ioiPb2dnx8fE4/jlQqLPn5dOn1BJWXE2sLjDcYrOTqrilOnnzy+BBCXh4hubnUpqUxMDJCcUwMchfCmN0BPz8/6urqmJiYoLGxkeLiYqe0bIuLiyiVyksnVWD9LhMSEoiLi2N2dpbGxka3WgHZMDExceLQ0wc+8IHttbW1d7vtha4AnlUVKwBJkiJTU1MHx8fHww+vIrRarb095ir5uV9M2La2thgeHnZo7NpoNDIwMIDRaKSoqMjjJWFHYLFYuH37NsCpAbjObq+jo8M+yn0SRkdH0el0FBYWuvU7NZvNNDU1OX0CPg1tbW1kZmaeqTM7DTaPp/NebIeHhwkKCnLaad9oNNLW1nYucumsjxWAcd9E2687qX2oEpmXc8dPf38/MTEx5yKv6+vrLC4uUlxc7PRzbRgfH0eSJLfYp7hrWOJu2FrmtoXl3bBZooSEhDikqcJohMnJ4y3FkRErGbsDfUEB3v397nwr58bOzg69vb3Ex8eTmpp65nnDZrPiaPTURcNkMjE9Pc3CwoJbzKvB+p7b2tqODdnMzc1RWVk5vrq6miWeRWTk/ggVcgJCiLWDg4Mnf/zjHx9xbfXx8SEgIID1u8atnYHJZGJ0dJSmpiYCAgK4fv06sbGxV5JUAYSGhhIcHMzU1NQ9H7exsUFTUxPh4eFUVFRcCVJlMpno6OjAx8eHwsJCt2gQZDIZFRUV7OzsMDg4yN2/Y9vFx92kCqyELTY21i2kamtrC0mSzk2qbNsIDAw8dwVjc3PzXKttrVZ7oZmWSj8FpgCd06QKIDw8nM3NzXO9bnh4ONvb25hMpnM9HyAlJYX5+XmMhys450RiYiI6nY61k3RgLkChUFBRUcHg4CA7d2VG2kh0RESEY6QKrC3R7GyrOen732+1Vujrg/19q4brRz/C/MEPMvvHf8zo6Oix3/BlICgoiPr6ejthOjg4OPWxtop4bm7ulSRVYP1OMzIyqK+vR6vV0tDQwMLCgkuf9eTk5Imk81//9V93tre3//HZRKrgWUisAFZWVt73vve9b+vu7yojI4Px8XGnt2c2m5mcnOTWrVsolUquX7/uFhZ/EcjOzmZ+fh6NRnPsb2azmYGBAcbGxqiqqroy+VI28W5MTAyZmZlu3SeZTEZpaak9889yR1i7trbG/Pw8ZWVlbv8MNjc32d7edsvkjxCC4eFhsrOzXdrO3NycY7EnJ8BsNmM2m89FwA8ODtxqW+EI5HL5uQhOWFjYuYmVJEnExMSwvLx8rueD9QKXnJx85sLI0f0pKipicHAQw6HKjzugUqkoLy+nu7sbrdbqrGojGcnJyQ7pGs+EQmEVrf/u7yJ///tJ/9u/RafT0dfXZ/8NXybkcjl5eXlkZWXR3t7O3NzciUTE1gL0VDyQO6FUKsnJyaGmpga1Wk1DQwMrKytOEyyj0cja2toxGc76+jo/+clPdgwGw3+7c7+vAq4+MzgHhBCz29vbLb/5zW+O3O/v74+XlxdbW1sObcdisTA7O0tDQwNms5lr166Rmpp66ZYDzkAul1NYWEhfX9+RH8TOzg6NjY34+PhQU1NzoVWEe2F/f98+jXfeC/9ZkCSJ/Px8AgMDaW9vZ3Nz0z5t6G6hvtFo5Pbt25SUlLiFsK2vr6NSqVyqfJlMJnZ2ds6t79je3j53tewyiJWvr+89qwinwdvbG6PRiPmQeaczSExMZG5u7lzPtSEpKYnl5WX0er1L2wErAcrKyqLfAy00f39/u+ZKrVbT2tpKTk6Ox0LZZTIZhYWF+Pr60tHR4VJl0J0ICwujrq6Ora0tOjo6jnxvOp2O8fFx8vPzL3EPnYdtiKmyspKVlRWamprYsHmZOYCpqSmSk5OPFSIeffRRjUaj+dD9nAl4Gp6VxApgeXn579/73vce+/YzMjIYO0P4aIufaWhoYH9/n7q6OjIzM6/EdNx5cLglaBOD9/f3U1paSlpa2pWoUoH1gt3e3k5JSYlbLQ5OQ3p6OuHh4fasMk+0QAcHB0lNTXULmRBCMDIy4nK1amlpySVd4MbGxrlJ2UW3AsEqA7BVUpxFSEgI29vb53qur68vkiSxv79/rueDlUCkpaUxMTFx7m0cRmxsLDKZjIWFBbds7zBCQ0OJi4ujsbHx3mHKboIkSWRmZhIbG0tLS4tbyKc7oFQqKS4uJjExkebmZnuVp6+v70q3AM+Cj48PxcXFFBcXMzMzQ0tLy5m/DZPJxNLS0rFF8u7uLt/4xjf29vf3nTdouw/wrCVWQoih+fn54c7OziP3BwcHI0nSiSV+IQSrq6vcunWLzc1Nqquryc3NvVIhzudFdna2vfpmsVioq6sjICDgsnfLjpWVFfr7+6mqqrow/y+DwcDCwgI5OTn09/efq6pxL6ysrKDX6902Xbi8vExQUJDLWW3z8/MuVQPPq6+C+6tiBa7prAASEhKYn58/9/MB4uPj2djYODc5vBsFBQWMj4+7bXs2rK+vs7CwQHp6un0RdxFISEggKyuLlpaWEyUPl4Xo6Ghqa2uZm5ujqakJhUJxX7QAz4K/vz/l5eXk5uYyOjpKe3s7e3t7Jz52cnKSxMTEY12ez33uc1q9Xv9JIYR7+9JXBM9aYgWwvLz8rve+973Hzoo5OTmMjIwc+eFvbm7S3NzM4uIi5eXlFBYWXkjEwEXAZvZpsVgQQpzLd8WTmJmZYXJykpqamgu76JrNZtrb28nJySEtLY3CwkLa2tpcuogehl6vZ3h4mOLiYrdUBG2VRlezDzUaDTKZ7NxVI7PZjNFoPPdv4zIqVq4QK1d0VoBdZ+UKybBVZs6qtDsKpVJJfn4+vb29biM/09PTjI6OUlNTQ3Z2Nr6+vgwODrpl244gMjKSkpISOjo6zl1h9AS8vb0pKChgf3+f3d1dt51frgKCgoKorq4mLS2N/v5+uru7j/zODAYDS0tLx4yZdTodn/3sZ/fUavXnLniXLwxX5+rqAQgh2gcGBqZ7e3uP3B8YGIivry+rq6t2PcDk5CSFhYWUlpZe+Irak7CNue7u7vLggw8SGRnJ5OTkZe8W8IwQe21tjerq6gurDAoh6OrqIiEhwb6CDAkJobq6mqGhIWZnZ13efn9/P9nZ2W5rL87PzxMREeEy2Z+fn3epgqZWq12aRrRYLBeuUXSlFahSqTAYDOcWSCsUCkJCQpzSpJyE6Ohodnd33VaRiYiIwN/fn5mZGZe2YwtM3t7epqamxn685+TkoNfrL/RcExQURFVVFf39/aysrFzY694LtnNBSUkJVVVVjIyMMDg4eG7d3lVEWFgYtbW1xMXF0dnZSX9/PzqdjrGxMdLT04/93v/93/9dZzAYviiEcG+L4ArhWU2sAFZWVt72yCOPHFsmJCQk0N3dzdDQEFlZWVRWVl6p1pg7sLi4SEtLC6mpqRQWFqJQKMjKymJpaenSV3UWi4Wenh5MJhMVFRUXdrEVQnD79m0CAwOPRRz5+PhQW1vL+vo6t2/fPvfFdGFhAYVCce78vrthNpuZmppyfGT9FNgiLFzZL1f0VWaz+VIqpa4QK7DKB9Rq9bmf7w4RuyRJZGdnMzo66tJ2DiM3N5e5ublzkzXb9K6/vz8lJSVHfsOSJFFSUsLq6ipLS0vu2uUz4evrS01NDZOTky6TRndgamoKX19fIiMj8fX1pba2FpVKRWNj4zF7ivsZkiQRFRXFtWvXCA8Pp7m5mYWFhWNa2b29PT7+8Y+rNzY2PnpJu3oheNYTKyFE5+TkZO/NmzcBayuit7eXkZERIiIiSEhIcGkFfhVhMBjo6upiZWWFurq6Iwe3XC6nrKyMvr4+t/jjnAc2f5vAwEDy8/MvVDw/MTGB2Ww+taVm+3xUKhWtra1Oj6ZrtVomJyfdOvkzOztLTEyMyxW99fV1QkNDXSKxruirLqMNCNaqkSsVgrCwMJcqTiEhIezt7bn8e4uIiECv17O7u+vSdmyQy+UUFRUdsR1xFDs7O7S0tJCRkXHqAIzNN25iYuJCW2BeXl5UV1ezvr7O8PDwpXldbW9vs7i4SG5urv0+SZJIS0ujpKSEvr4+xsbGroQXl7sgSRKxsbEEBwcTGxtLc3MzY2Nj9qnNj370o/v7+/v/JoQ4/0THfYBnPbECWFlZ+YtHHnlkq7+/n/b2dqKjo6mrq6OoqMh+oX22YG1tjaamJqKjoykrKzvxYuzn50dGRoZbNRaOwuZvk5CQcGK8gSexsLDA5uYmRUVF93xdSZLIyMggNTWV5uZmhy9kNm+s/Px8t03+mEwmZmdn3eKB5Yp3FVirjAaD4dzk6DKE6zZIknTuCqSrAnZJkoiLi2NxcfHc27AhOzub4eFhl7djQ3BwMJGRkU75+y0tLdHT00N5efmZ07tKpZKKigpu377tNkLoCORyOeXl5ZhMpnMRR1dhNBrp6+ujtLT0xIVMYGAg9fX19kQGVyZHrxp2d3fRarUUFBRw/fp15HI5t27dor29na985Svbu7u7/37Z++hp/J8gVkKIsZ2dnYa2tjbL9evXiY6ORpIkvLy8iIuLuxIlY1dhMpno7+9namqK6urqMzMR4+Li8PLycllP5Az29vZobW0lNzf33Bl158X6+jrT09OUl5c73I6Kjo6mtLSUnp4eZmdnzyShU1NTBAUFHUtudwVTU1MkJia6bPVhMBjY398nODj43NtQq9UuPf+yKlbgWjvQx8cHnU7n0sXZHdOBgD170FEvPkeQkZHB2trame1Os9lMf38/8/Pz1NXV4e/v79D2fXx8KC0tPWIgehGQJImCggICAwNpa2u7sAq9zVohPT39np+RTCYjJyeH3NxcOjo6mJmZeVZUr4aHh8nJyUGSJORyOWlpaVy7do1PfepT2r29vb8TQlxOq+QC8X+CWAHMz8+//aMf/ejW3dWp1NRU5ubmLq0t5g5sb2/T2NhIYGAgVVVVDl+88vPzmZ2dvZBe/+bmJp2dnZSWlrqVeDgCW4TNeQxAAwMD7YZ/3d3dpx4ne3t7LCwsuOwxdRgGg4HFxcVjUzXnweLiInFxcS5VCF3RV8HlVqxcmQwE13VWKpUKpVJ56li6M8jJyXFri0smk9lbU6dV7zUaDU1NTfj7+1NZWel0RTYwMJCCggI6Ojou/Fybnp5OYmIiLS0t6HQ6j7/e7OwsCoXC4cVjaGgo9fX17O7u0tbWdiH76CnYCP/d4eNzc3P8+te/Xjw4OPjOZezXReO+IFaSJKkkSWqXJKlPkqRBSZL+5dDf/lKSpNE793/stG0IIZb29/e/89WvfvWIaMYWG3FVJuWcgcVisU+ZlJeXk5yc7NSFUy6X2ysynnQuXlpaYmBggOrqardk5TkDrVZLd3c35eXl556oUygUdtPSpqamY0TUYrHQ29tLcXGx29Pg3eX0v7Cw4HKVcHNz0yVSfJnEysfHxyVi5artArhHxA5WkqJSqVzKPb0b/v7+JCQkMDQ0dOxvCwsLdHZ2UlhY6FDI8GkICwsjLS2Njo6OC2/NxcXFkZubS2trq1vI7WnY3d1ldnaWgoICp56nUCjsn29LS8uFCv7dBduUd05OzrG//e3f/u32+vr62+/lsi5J0lckSVqTJGng0H3FkiS1SpLUK0lSpyRJlR7afbfiviBWgB54rhCiCCgGXiRJUrUkSc8BXgEUCiHygI/fayNra2vv/5d/+Zedu8vRSUlJdjPH+wV7e3s0NTUhk8mora11uCx/NwICAkhNTfVIzAVYW1kzMzPU1tZeeBvIaDTS3t5OUVHRuT+fw0hISKC8vJy+vj6mp6ftFYOxsTGioqLcamxqC8x1h7no7u4uXl5eLlk1WCwWdDqdS9/hZbYCfX19XWpDuaqzAmtreW1tzS2kwjYh6M7WUUpKChqNxk7YTCYTvb299iEYV9rANsTFxREVFUVPT8+Ft73Cw8MpLS2lq6vLI2J6m57rNF2VI4iMjKSuro6lpSW6urruq07K2toaPj4+xxbP/f39tLS0zFgsll+dsYmvAS+6676PAf8ihCgGPnDn/6887gtiJaywzQQr79wE8Dbg34QQ+juPu2d0uxBCrdVqP/vYY48dOcPKZDIyMjLcOsrsKQghmJycpLu7m8LCQjIzM10eYbcJmt2xmrZBCMHg4CBbW1tUVVVdeIyDzQA0MzPzWFnaFfj7+1NXV8fu7i4dHR2srq6ysbHhshXC3RgbGyMjI8Mt9gSuitbB2k51lTiaTKZLi/NwtRVoI2aukAGZTEZ4eDhra/c8TTkEPz8/AgMDXQp5vhuSJFFcXMzAwACbm5s0NTUREhJCWVmZW7+3tLQ0vL293SrCdxQ2ucTAwIBbq0I2v6qUlBSXbXu8vLwoLy8nOjqaxsZGt1YmPYV7xW098sgjm6urq38mzvjxCCEagLvFgwKwMbUg4L4o5d0XxApAkiS5JEm9wBrwKyFEG5AJXJMkqU2SpJuSJFWctZ2tra1HH3vsMfXdeonY2Fh2dnY8WiZ2FVqtlpaWFrRaLfX19W6tkBQWFjI9Pe2SjsQGs9lMd3c3AGVlZRduCGmbzouNjXWbl9Rh2MbU4+LiaG9vdyl37yQcHBygVqvdEmBrsVhYX193OUrD1TagxWK51ExKVytWYDWgdFWP6K52IEBmZibj4+Nurfx4e3vj5+dHe3s7paWlJCUleeR7y8vL4+DggOnpabdv+yzY/OpmZmaYmppyyzZnZmaQJMmtwfFxcXFUV1czMTHB7du3r/T0+tzcHOHh4cda/Q0NDYyPj/cJITrOuel3AI9KkjSPtSP1Xtf29GJw3xArIYT5TjkwHqiUJCkfUAAhQDXwbuB70hlnASGEdn9//4Mf+tCHjjAoSZLIy8vj9u3bV24ywxZJ09raSmZmJvn5+W4nKwqFgvLycnp6elwST9o8qkJCQsjLy7uUi+ng4CC+vr6kpKR49HU2NzfJyclBrVYfS7J3BSMjI2RlZbnls1tdXSUiIsLlyperwnWdTnepEVFKpdLltoqrflZgJWc6nc4tx4qPjw/h4eFumTYEa1WysbGRkJAQwsPDPbrItBmILi0tubXq5iiUSiVVVVVsbW0xODjo0jl/fX2dxcVFCgsL3biHVvj4+FBdXY2/vz+3bt26dGPnk2AwGJiamiIzM/PI/UIIHnnkkY2VlZW3ubD5twHvFEIkAO8EvuzCti4M9w2xskEIoQZuYO3FLgA/vNMqbAcswJnL6r29vS89/vjjW3eXgkNDQ/H19b2UH/pp0Ov1dHZ2srGxQX19vUcn6vz8/MjPz6ezs/NcqyOtVktzczPJycmkpqZ6YA/PxuTkJHq9/kQBpTuxtrbGwcEBaWlplJWVkZCQQHNzs8vthb29PbRa7Zn+QI7CHW1AIQRardYl4fllCtcPw5ULqDt0VmANVV5YWHB5O2C1SpicnHRJt2Ubgunv76e4uJiMjAyKiooYHR316ISaXC6noqKCsbExt9pHOPP6ZWVlAHR3d5/rnLe/v8/AwADl5eUeq8xLkkRKSgrl5eUMDAwwOjp64eL/e2F4eJiMjIxj7eL/+Z//sayvr/9aCOFKyOWfAD+88+/vA78Vr7sLkiRFSJIUfOffPsDzgRHgf4Dn3rk/E/ACzlxSCiFM29vbf/X2t7/9GP3PyclhdHTUo1NyjmJlZYXm5mbi4+MpKSm5EH1KREQEcXFx9PX1OXUR2t3dpbW1lfz8fLe0sM6DpaUlVldXKSkp8WilzGAwMDg4eCRg2WY6u7y87FL1yqZTcMf+6/V69Hq9y5OYOzs7BAYGurRPlylct0GlUrlEFGw6LVcr2u4kVl5eXsTGxp7bj06tVtPY2IhcLqeurs5+rHh5eZGXl+f0ecBZeHl5UVlZSV9fn9tyEJ2BrVMREhLitNeV0Wiks7OTkpKSC6nG2vSdAE1NTVdCtqJWq9FoNMd8E3U6He94xzu2VlZW3uniSywBD9z593MBx51sLxH3BbECYoDfSJLUD3Rg1Vj9DPgKkHpnPPM7wJ+cJZCzQa/X/6SlpWW4oaHhyP3e3t4kJye7LUn+PLBN48zOzlJbW+sRndC9kJycjFwud1h/sLGxYbc0cKVd5Ao2NzeZmJigoqLC43l0t2/fJjMz89jJ1MvLy169amlpYWpqyqmVpVqtxmw2u+0zdDVw2QZX9VVwNSpWrgrYJUkiMDDQZQdxLy8vfH193aJnBKsX38zMjFOLQaPRSH9/v32BcNKgRGRkJCqVyq1DLSfBZiDa2dl5aR5OqampJCcn09zc7JAWTwhBd3c3aWlpbpmWdBQymYysrCwKCgro7u5mamrq0qQrQggGBgYoKCg4tuj68Ic/vK/RaD4phHC4hC9J0reBFiBLkqQFSZLeDLwV+IQkSX3AR4A/deNb8BjuC2IlhOgXQpQIIQqFEPlCiA/eud8ghPijO/eVCiF+7cx2V1dX//jNb37z5t0npOTkZDY2Ni5lRbC1tUVjYyOhoaFUVlba0+IvEjbH4pWVlTMnmBYXFxkaGqK6uvrSQqx3d3e5ffs2FRUVHq/q2WJJ7uVsHx0dTX19PXq9nsbGRofbR8PDw24zGBVC2E1BXYWr+iq4GhUrV8OYwT06K3CviF2pVJKYmOiQEFwIwezsrF1LVVtbe8+KZl5eHtPT0x6PXAkKCiIvL4+Ojo5L6xbExsaSn59Pa2vrmeR5ZGSEgICAC0+QsCE4OJj6+noODg5obW29UEd7G+bm5ggODj52/ExPT/OFL3xhfWtr61FntieEeJ0QIkYIoRRCxAshviyEaBRClAkhioQQVUKILre+CQ/hviBWnoIQYmpnZ+erd9svSJJEfn4+AwMDF7YasFgsDA0NMTw8TGVlJYmJiZc6RSWTySgvL2doaOhUgjkxMcHc3Bw1NTWXJky2GYCWlpZ6/MKt0+kYGxtzSKSqUCjIycmhtLSU8fFxuru777ka39jYQKFQuG31q1ar8fPzczm4WQjBwcEBfn5+Lm3n2VCxAvfprCIiItjc3HTbpFdycjILCwv3bGWp1Wp7C6m+vp6EhIQzzzE248qLyBWNiIggJSWFzs7OS9MQhYWFUV5eTnd396kEemFhgd3dXY/rOM+CXC4nPz+fjIwM2traWFhYuLDrlU2wflKY/Vve8patjY2Nh/8vRNechv/TxApgfX39A48++ujWysrKkftDQ0NRqVQXImTf3d2lsbERLy8vamtrL/0CZIO3tzclJSXHjOqEEPZQ1cvwqLLBaDTS0dFBfn6+xx3dhRD09vaSl5fn1Pv19/enqqqKmJgYWltbTxQa2zxg3HmidodoHazHZkBAgMsk32AwuEzyXIU7KlZ+fn7s7++7fAGTyWRERkayurrq0nZskMvlpKamMjExcexvBoPB3vYrLCx0OiQ8NDSU0NDQE7ftbsTHxxMWFuZxbde9EBAQQHV1NUNDQ8e0cGq1msnJSUpLSy914XsY4eHh1NXVsba2RmdnJwaD4ewnuYiRkRHS09OPHUc///nPLYODg+1ms/mGx3fiCuP/PLESQmi3t7ff/hd/8RfHhOy5ubkeFbILIRgfH7fHoaSnp1+ZH6sNQUFBZGVl0d7ejtlsxmw209nZaY958bSe6TRYLBY6OjpIS0u7kOzB2dlZfH19zzWtJ0kSMTEx1NfXYzQaaWhoYHFx0X7hWF1dxc/Pzy3u8GD1Edva2iIiIsLlbblDX2V7n5d9bLujYiVJEgEBAW6RCbizHQjWZIDV1VV7ZdRkMjE2NkZTUxOhoaFntv3uhaysLJaXly8kVzQ9PR25XH6phs0qlYqamhrm5+eZmJhACMH+/j49PT2Ul5df2mLyNCiVSkpLS4mLi6OpqclthP0kqNVq9vb2jrVBdTodb3/72zdXV1ff7LEXv0/wf55YAej1+h83NzcP37p168j9nhSy7+/v09zcjNFopL6+/sIz9JxBTEwMcXFxdHR00NLSQkREhD29/DJgMwCNiopyi4boLGg0GmZmZsjNzXVpOwqFguzsbGpqatjc3OTWrVusrq4yOjp6Ykn9vFhZWSEqKsot34879FV6vf5StIJ3w9vb2y3+Ue7SWQUEBGAymdymj7ElSIyNjTE9Pc2tW7eQy+Vcv36d+Ph4l44HmUxGcXHxPYOa3QWbxtOWu3dZsHld7e7u0tfXR0dHByUlJS63xT2J2NhYampqmJmZoa+vz+1FgbME63t7e485I1h/tuK3xOoOVldX3/DmN7954zQhu7tGgW3i0Y6ODnJycsjNzb20qo8ziIyMZGdnB7lcTlJS0qXuy/DwMN7e3qSlpXn8tWwBy0VFRSgUCrds09vbm8LCQsrKyhgbG7PbIrgL7moD2lbprlbSroJwHZ6pmLnaYnJHILMN7rReEEIghGBubg6NRkN9fT1paWlu81cKDAwkNjaWkZERt2zvXpAkibKyMubn5z1afTkLMpmMgoICVldXkcvllzag4wxUKhWVlZUEBwfT2NjoVo+w+fn5EwXrMzMzNsH6fZHl52lc/Sv6BUEIMalWq7/+2GOPHVEY24Ts/f39Lp+QdTod7e3tqNVq6uvr3Zph50ns7OzQ1tZGRUUFvr6+l2pFYZtQysvLu5DXm5iYIDw8nJCQELdv28fHB7PZTElJCaOjo7S3t7vcatFqtZjNZre0Fff29vD393e58nUVhOs2eHl5uaxBCQgIQKPRuEUDFBcXd6QtfB4IIVheXubWrVtsbW1RVFTksVzGtLQ01Gq1R0KM74ZcLqeyspLh4eFLcxy3WCx0dnaSl5dHQkICra2tF6JhchWSJJGUlERFRQXDw8MMDQ25PBCg1+uZnJz8rWDdAfyWWB3C+vr6+x999NHNk4TsAQEBLpWll5aWaGlpITk52a3VD09jbW2Nnp4eKioqCA0NpbCwkJ2dHWZmZi58X5aXl1laWrow4aharWZ1dfVYVIO7MDc3R1RUFBEREVRXV5OWlsbw8DCtra3nvnC5y7sKrPoqd3hquera7k64IzNQkiT8/PzcUsVWKpUEBAScizhYLBbm5+dpaGhgbW2N8vJyCgsLiY+PZ39/3yN2MbYomtu3b7scEeQIvLy8qKiooLe31+OWD3fDJjmIjIwkPj6e5ORk0tLSaGlpcVmrd1Hw8/OjtrYWLy8vGhsbXfJgu337NtnZ2ScK1gcGBv7PC9YP47fE6hDuCNkfefvb366++285OTnMzMw4/YMyGo10d3ezuLhIXV2dy2G4F4n5+XlGR0epqamxV0BsJfrFxUW3psOfha2tLcbGxqioqLiQUGez2UxfXx/FxcUeadWazWamp6dJT0+33xcWFkZ1dTU5OTlMT0/T2NjIysqKw9UMIQRLS0tu0525Q7gO1orVVWgFgrVK6I6LortsF8B5Ebvt2Ll58yZ7e3tUVVVRVFRkJ6+SJJGTk+Oxlp2vry+pqakMDg56ZPt3w8/Pj5KSErfmcZ4Fm5bIx8fniOQgOjqawsJC2traLkTI7w5IkkR6ejrFxcX09vbaxfjOYGlpyT6Ecxh3BOtbvxWsH8VvidVdMBgMP25qahp4+umnjxx5CoWCgoICp/xcNjY2aGpqIjIykvLy8ksfN3cUQgjGxsZYWlqipqbmmPDYVqKfmJhwi4j3LGg0Gvr6+qisrLywz3B4eJj4+HiPaSpmZmaIj48/sV0TFBREeXk5JSUlrK6u0tDQwMLCwpml/K2tLQIDA91SDRVCsLe355b3f5Vage6YDAT3CdjBStK2t7fPFBobjUbGx8dpaGiwD73k5uae6CEXFhaGyWRym7v73UhISMBgMHB3dd9TCA4OJicn58IMRCcmJjCZTCdaoISEhFBRUUFPT8+ZBspXCYGBgdTV1WEwGGhubnb4d6DX6xkdHaWgoODY3/75n/9Zo9FofitYvwu/JVZ3QQghVldXX/fwww9v3F3qDwsLIyAg4Mw2mNlsZmBggPHxcaqqqlyeyLlICCHo7+/n4OCAioqKUy/SSqWSyspKBgYGPLpy0+l0dHZ2XogBqA0bGxvs7u56LEjaaDQyNzdHSkrKPR/n5+dHUVERVVVV7OzscPPmzXsG47pLtA5WMuvn5+eW41an012agezdcIeXFVgvUnt7e27RWdkqAad55tmm0pqampDL5Vy7do3MzMwzNVQ5OTkMDw+7vH8nQZIkioqKGB4evrAqUlRUFAkJCXR1dXnU42pubs6uVTvt+Pf396empobR0VGPR/64E3K5nNzcXLKzs2lvb2d2dvbMz7K/v5/s7Oxji9qenh6++tWvzm1ubn7Uk/t8P+K3xOoECCEWdnd33/+Xf/mXxxhDTk4Os7Ozp7J9W6ipr68v1dXVV6YF4ghMJhPt7e2oVCqKiorObIGpVCq7S7Gr+Wmn7U9HRwd5eXkEBQW5ffsnwWg0MjAw4NEg56mpKZKTkx2uLKlUKvLy8rh27RoqlYr29na6urrY3Ny0nxRNJhM7Oztuyxl0l77KhquysHBXxUqSJHx9fd2m+7m7HWixWFhcXKSpqYmhoSFiYmJ44IEHSE1Ndfi4CQ4ORqFQeKyq7O3tTXZ29oWaeSYlJREcHOyWYaKTsLCwwPz8PGVlZWee/7y9vampqWF5eZmxsbFLMzQ9D8LCwqivr2d7e5v29vZTyfHS0hIymexYC9BgMPDa1752c21t7feEEJ7137gP8VtidQp2dna+8MQTTww+/fTTR/ovp7UELRYLo6Oj3L59m9LSUlJTU6/MxcQR6PV6WltbiYmJISsry+F99/f3p7y8nK6uLreKZW3TOMnJyW4xunQUAwMDpKWleYwQGwwGlpeXz2VZoVAoSEpK4tq1a6SkpDA7O0tDQwNTU1PMzc0RExPjtmPOXfoqo9F4pcwUVSqV24J+3amz8vX1RZIk1tfXGRoa4ubNm+zs7FBcXEx1dTWRkZHn+m6zs7MZGRnx2EU/JiYGpVLpNssIR5CZmWk3V3YnFhcXmZ2dpaqqymHyqlAoqKioQKvV0t/ff2lRPOeBQqGguLiYpKQkmpubj1VM79UCfP/736/Z3Nz8tBDC894b9yF+S6xOgRBCrK2t/f7DDz+8eTdhCAsLIzAw0N4S1Gg0NDc3A1BXV3dfeJ0cxv7+Pi0tLWRmZp6rlRQQEEBZWRmdnZ1uIVdCCPr6+ggLC3PbhJsjWF5exmQyeTRYdXx8nLS0NJcE8ZIkERoaSmlpKTU1NQghGB4eZnNzk6WlJZcNHIUQ7O7uusW09ioJ18HqS+QukuEunZVer2dqaoqDgwP6+voICgrigQceIDc312UzyoCAAPz8/DyqBcrPz2dycvLCgoAlSaKwsJCtrS3m5+fdss2lpSWmp6eprKx0WqMok8koLCxEpVJdaoj0eREdHU1tbS0LCwv09PTYpz37+/vJyck51gLs7u7ma1/72uzm5uaHL2N/7wf8lljdA0KIxZ2dnX985JFHjrUEs7OzmZ2dZXR01O5zkpWVdV+YfR6GrRRcXFx8rrgWGwIDA91GrsbGxpDL5Ucm5jwNvV7PyMgIhYWFHqs0arVaNjY23ErcvLy8iI6OJiQkhPz8fNRqNQ0NDfT09LC+vn4uEmETm7vjc7hKwnUbFAqFW6wCgoKC2N3dPddnbDKZWFhYoLW1lfb2doQQ1NTUIJfLiY2Ndet5JCsri9HRUY9VrZRKJfn5+fT09FxYO8wWEj8zM+MyaVxaWmJyctKl3FNJksjKyiImJoaWlpYL0525C97e3pSXlxMeHk5jYyMjIyPIZDKio6OPPO5QC/DVv20Bno77iwVcAnZ3d7/0i1/8YuCpp546UuM1Go1IksTs7Cz19fUeMZD0NFZXV+nr66Oqqorg4GCXt+cOcjU7O8vOzs6JkQmegi1gOScnx6PRK2NjY2RmZrr9fdlE64GBgeTm5vLggw+SmJjI0tISN27cYGBggI2NDYfbFO6IsbHhqriuH4a7BOySJDll32AymVhaWqKrq4vGxkY0Gg35+flcu3aNtLQ0/Pz8CAkJcbsmytfXl5CQEI/ao4SHhxMUFMTU1JTHXuNuKBQKKisrGRoaOvcAzeLiIlNTU1RXV7ulZZ2YmEhWVhYtLS0X7rvlKiRJIiEhgZKSEiYmJlAoFMeq3+973/s0m5ubj/22BXhv/JZYnYE7U4J/8KY3vcneErStNHNzc4mNjXVbOfoiMTs7y/j4OLW1tW6tKBwmV84K2ldXV+3C0YvUp83NzeHt7X1sdeZOaDQadnd33f4aQghWVlaOiEslSSIsLIyioiKuX79OREQEi4uL3Lx5k66uLhYXF+9ZsXGXvgquZsXKXQJ2OFtnpdVqmZ6epqWlhaamJnZ2dkhNTeWBBx4gOzv7mEO+u4OZbcjIyGB8fNyjGqDs7GwWFhY8Ykx6GmyVlu7ubqe/04WFBaanp12qVJ2EyMhIiouLaW9vvzTHeFcwPj5OWVkZ/v7+NDY22i07urq6+PrXvz67tbX1kcvdw6uP+8P++5IhhFgMCgr6h7e97W0ff8c73hEkSRL19fUolUpCQ0O5desW4eHh94W2SgjB6Ogou7u79taDuxEYGEh5eTmdnZ2UlZU5pNXZ3t5meHiY2traCzEAteHg4IDp6Wnq6+s9+jqjo6NkZ2e7nTCur68TGhp66mcml8uJiooiKioKIQQ7OzusrKwwOTmJQqEgOjqaiIiII9E1Ozs7bpvCfDZXrMCqs5qenrZrEy0WC2q1mrW1NdbW1uyf8WEDz3shJCSE/v5+t4v+VSoVUVFRzM/PeyzrUy6XU1xcTE9PD/X19Rcmi/D396eoqIiOjg5qamoc8rqbn59nbm6O6upqj6RgBAcHU1VVRXt7O9nZ2R5dtLkT8/PzyOVy+0ItMjKS3t5eQkJCfjsF6AR+W7FyELu7u1++cePG+MTEhKWsrMx+0pPL5ZSUlNDd3e3x1HdXYQsUNhgMHncwDwgIoKKigq6urjNDQPf39+nt7aWiouJCTVRtkRUFBQUejRja3d1Fr9d7ZLrRGe8qSZIIDg4mOzub69ev2y0lRkZGuHHjBp2dnYyNjbn1gn4ViZU7K1YBAQFsbm4yPj5OS0sLDQ0NzM3NERAQQE1NDbW1taSmpjpctZMkyZ4f6G6kp6czNTXl0fNUUFAQ0dHRF54nGhoaSlZWFh0dHWe+v+npaebn552a/jsPfH19qa2tZWJiwqU4tIvC3t4ek5OTR6YAAwICqKur49Of/rR+Z2fn00KI0UvcxfsGv61YOQghhJAk6RXvfve7e1/ykpdEHK7CBAUFkZiYyMDAAEVFRZe4l6fDZDLR2dlJWFgY6enpF9Jq8/f3p7q62r5qOynOR6/X09HRQUlJicsTUM5icnKSkJAQt/o1nYTh4WGys7Pdvl2DwYBGozm3Ps7Hx4eUlBRSUlLsTuvj4+MYDAZu3LhBQEAAYWFh9jT78xBxi8VyoRVIR+AKsTIajajVara3t9nc3ESv12OxWJDJZBQXF7uFRCYkJNDR0UFycrLL2zoMpVJJfHw8MzMzR2Ja3I2MjAyamprY3t6+UO1pdHQ0Op2O7u5uysvLj53jbNV6WwzQRRyXXl5e1NTU0NXVhVardcrK5iJhNpvp7u6mpKTk2MKqu7ubH//4x+Pr6+u/nQJ0EL+tWDkBIcTSzs7O3//pn/6p+u6/JScnYzAYPLLSdBU6nY7m5mbi4+PJyMi40B+2j48PNTU1jI+PH9OO2AxAc3Jy3CKedwa7u7ssLS15hPAchq1aFxoa6vZtLy4uus3VX5IkAgMDkclklJSU8OCDD9rDp2dmZmhsbOTmzZv09PQwPT3N1tbWmZUBk8l05UgVON4KNBgMrK2tMT4+TkdHBzdu3KCtrY2VlRV8fHwoLi7mwQcfJDU1FS8vL7dV5lQqFUql0iNapZSUFObm5jwaoGwLau7r67tw64Hk5GT8/f2P5RjaEiX0ej3l5eUXelzK5XIqKiowGo309vZeSa+rgYEBEhMTj0kADg4OeO1rX7vx2ylA5/B/qmIlSZIKaAC8sb73Hwgh/kmSpH8G3gqs33noPwghnjhpG3t7e1/9zW9+86pvfOMbL3jDG95g71tJkkRxcTFNTU0EBwdfePXlNOzt7dHV1UVeXt6FGm0ehpeXF9XV1XR2dqLX6+02Cl1dXSQkJFx4MLWtJeqpgGUbhBCMjIyQn5/vke0vLCxQUVHh1m2q1WqCgoLsROtwZdZsNrO7u4tarWZubo6dnR2EEPj4+ODv72+/+fn54e3tfSXbgGC90NkubkIIDg4O2N/fR6PR2G96vR6lUklwcDBBQUF2oflJJDYsLIzZ2Vm3eq7ZROx5eXlu2yY8YzI7NTVFVlaWW7d9GH5+fiQnJzM0NERhYaHHXuckZGdn09PTw+TkJGlpaZjNZrq6uggKCvLIVK4jkCTJ7vfV1tZ2z7iwi8bS0hJ6vf7ECulb3vIW9ebm5gfu1QKUJOkrwMuANSFE/p37ioD/APyBGeAPhRDuj+e4opDuJxt+VyFZf1F+QgiNJElKoBH4a+BFgEYI8XEHtxMQGRk5cOvWrUTbqt6G7e1tBgYGqKuru3RPq62tLfr6+hwWkHsaNkKjVCoxm834+Ph49OR+GoaGhlAqlWRkZHj0ddbW1uxTju7G7u4uw8PDVFVVuW2bWq2W3t5eampqHH6OEAKtVmsnJDaCotfrMZvNCCGIiIhApVIduXl7e+Pt7e3URe7GjRs8+OCDDj/eYrGg0+nQ6XTo9foj/15cXLQvfnx9ffHz8ztCDr28vBzeN4vFQkNDg1P75sg2b968yQMPPOD284htf2traz2qaRRC0NbWRmpqqkseeeeBxWKhra2N2NhYFhYWiIuLc3tr9bxYWFhgamqKysrKS8/Q3N/fp6Ojg7q6umMtwG9+85vGd73rXb9cW1v7HXEPoiBJ0nVAA3zjELHqAN4lhLgpSdKbgBQhxPs9+FauFK4GZb4g3Dk4bMnKyjs3p5mlEGJPkqRXvPzlL3+qt7c37PCPIyQkhNjYWIaGhjxWqXAEtvyqq5RXaGszNTU1odPpeM5znnPh+7C1tcX29ja1tbUefR2bnqO0tNQj23dn4LIN5/GvsmXm+fr6Hrt4Tk1NYTQaiYiIsJOazc1NO7m520RRkiQUCoX9JpfLkSTJfrPFhoD18xVCYDKZjtzu3t5hIqdSqQgJCbHH2uTl5bllklcmk+Hl5eXWCp1MJiM8PJy1tTW3T5TJZDJSU1MZHx93e0XsMGxV/JaWFoKDgy90MEX2/7d33uGRluX+/z5T0uukt930Xje7STZbYCmeBRVREOUo6k9UOApHRdCjKNjl2EA8eDzYFURARIRFBXXdbMumZ9N7z/SUmZTJtPv3xxSzyaTP+0529/lc11ybnZm8z5PJ5J3ve5fvLZGgsLAQp06dQlZW1q4RVQCQnJwMf39/1NbWory83Gfd5Ha7HU1NTSgpKVklqvr6+vDQQw8pNRrNneuJKgAgohrGWOqKu3PgyA4BwJsA/gqAC6srFcaYFEAjgEwATxHRBcbYTQDuY4x9AEADgM8Q0boGJETUEhUV9a1PfOITX/rZz352SWI6PT0ddXV1UCqVq4ZXisHQ0BAmJydRXV29q+a0AY6rNZlMhtTUVNTV1YkaErdarbh48SIOHDggeDpAqVQiLCxMkJSw3W6HVqtFfn6+V4+r1+u9KtZMJhOioqI2XV9mt9svEUmuiBfgEFJqtRpJSUnu351EIoFUKr1EjG329xoaGorFxUWvfahFRUVBr9d71VV/z5496OnpEaRVPyUlBTU1NYKnawMCApCTk4O2tjZBIrdrMTc3h8bGRuzbtw+9vb1ISEjYFVF7FzExMdi3bx8aGhpQUlIiSA3mRriGe69sMDCZTLjlllv0arX6ViLabqFfO4BbALwC4N0AxJtNtgu46orXichGRKUAkgFUMMYKAfwvgAwApQCUAL63mWNNTU19/7XXXmt88cUXL7lUdhVvdnd3e62tezMQETo7O6HX673mJOxNtFothoeHsX//fmRmZiIlJQXnzp0TbcZYR0cH0tLSBK9/cw2IXZkm9hZqtRoxMTFeTxHNzMx4tYlgqx/arshPUFAQwsLCEBkZCYVCAYVCgaioKMhkMrdQUygUiIiIQGhoKAIDAyGXy7cklr3pZQV4dyCzi/DwcHd0z9swxpCVlSWKLUJiYiIAiNbYo9PpUF9fj3379iExMRHl5eVoamoS7TyzWcLCwlBVVYW2trZVA5CFRqVSYX5+3mN36H333WdQq9WPEVHzDpb4MIBPMMYaAYQCMO/gWJcdV52wckFEMwD+CeA4EamdgssO4CcAKjZ5DNJoNLfdf//96qGhoUse8/PzQ3FxMZqamkTpAnGFdYkI5eXlu64ba3Z2Fh0dHZcMOU1OTkZhYSFqa2s39LraKWq1GiaTyevpM0+MjY0hOjpasEiAEGlAk8kEPz8/r4q13ei67sKbXlaAwxBSCJftpKQkjI+Pe/24AJCQkACDwSDK6JXi4mL09vYKLm6GhobQ1dWFgwcPuiNUoaGhKCoqQl1dnaDdkNshMDAQ1dXVGBwcxMrPEKFYXFxEV1eX28duOb///e+tr776asP09PSmggtrQUTdRPQWIioH8ByAgZ0c73LjqhJWjLEYxliE8+tAADcA6GaMLc/XvROOMOamIKIZtVp92y233DJlNl8qyqOiohAbG4vubmHHKlksFtTW1iIiIgIFBQW7zidlYWHB7S2zchafQqFAVVUV2tvbBTPRM5vN6OzsRElJieCvjd1ux8DAgGCF8a7aJG+nNfR6vdf9vGw2267pfFqJtyNWUqkUcrkcJpPJa8cEHBcfQkV6XIODhT4/Af8a1Nza2irIoGa73Y7W1lZMTU2hurp6VVF4VFQUsrKyUF9fv+vsDuRyOaqqqqDX69HR0SHoIGvXBXhxcfGqmrehoSHcd999aqe1wo42wRiLdf4rAfBFODoErxquKmEFIAHAScbYRQD1AN4kotcAfJsx1ua8/xiAT2/loER0QalUPv7AAw+saifNysqC0WgU7OS4uLiI8+fPIzU1VVDTv+1iNptRX1+PkpKSVXPRXLiu2jQaDdrb27164iMitLa2IicnR5QOnJGRESQmJgpWqDs+Pu7VOh4X3hy8DDhO4LtN4C/H2xEr4F91Vt7EVXS/3SHDG+FqLNjqXM/trhUcHIzh4WGvHndpaQnnz59HcHAw9u3bt2a0PjExEXFxcWhubhZUvGwHqVTqrkETMsvR1taGuLi4VX/rZrMZ73jHO6bUavXtG9UXr4Qx9hyA8wByGGPjjLG7AdzJGOsF0A1gEsAvvPQjXBZcVcKKiC4SURkRFRNRIRF91Xn/XURU5Lz/FiLacsJbr9d/88UXX2x79dVXLzFRY4xh37596O/vdw+z9BYGgwEXLlxAQUGBu45hN2Gz2VBfX4+cnJwNizNlMhn2798PuVyOCxcuYGX0b7tMTExAKpWK8vpYrVYMDw8jPT1dkOMTkWDCytsu2SaTyeet5Oshl8u9bl4pRJ0VINxgZsBxfsrLy0NXV5cgx19JXl4eRkZGMDc3t/GTN4HBYMD58+eRmZm5qYkSGRkZCAgIEO3n3QqMMRQUFCAyMhK1tbVeT1sODQ3BZrN5vAD/zGc+Y5ycnHyCiGq3elwiupOIEohITkTJRPQzIvoBEWU7b/+10wjY5cZVJayEhIjsGo3m1o997GOalTURcrkc+/fvR3Nzs9dSBTqdDk1NTSgvLxd8JMt2ICI0NTUhKSlp011NrtREamoqzp07t2Pn6cXFRfT19V0y+0pIXMN4hWoamJmZQXBwsNejYS4zTG/W5e3m+ioXjDGvRgYiIyMFqbOKjY2FTqcTbMaf66JH6DpHwHEBVVJS4hUHcqVS6T4HbsVkOD8/3z18fTeSnp6O1NRUnD9/3mvpap1Oh/HxcY/lEK+99prthRdeaNPr9XxkjZfgwsqLEJFOq9W+5+abb55aKaCCg4NRWFiIhoaGHZ8gJyYm0NnZicrKSp95oGxER0eH2315qyQkJGDfvn1obGyESqXa1vrLByyL0R1psVgwPj4uqF+OEEXrgDD1VZeDsHL5WXkLqVQKqVTq9S4+iUSC2NhYqNVqrx53Obm5uaLUWgEOARodHY3+/v5tfb/LI254eBjV1dVbPge6urYnJydF78bbLImJiSgoKEBtbe2O07Tz8/Noa2vDgQMHVl089ff34yMf+Yhao9Hc6mze4ngBLqy8jNVqPT0+Pv6V973vfTMro58xMTFITEzExYsXt53jHxgYwOjoKA4ePLhrjD9XMjAwALPZjLy8vG0fIywsDAcPHsTQ0BA6Ojq2fHU7NDSEsLAwREdHb3sPW6G/vx/p6emCdWPabDZMTU0JMpbI2/VVwNatFnyBtwvYAWHqrABh04GAw9rB398fWq124yd7gezsbKjV6i2XRywtLaG2thZWqxWVlZXbjt5KpVJUVFSgt7dXlEjddoiKisL+/fvR1NQEnU63rWNYLBY0NDSgtLR0VWreYDDg+PHjerVa/TYiEucXf5XAhZUATE1NPXnmzJnXHnvssVXVsWlpaWCMYXBwcEvHJCK0t7djdnYWlZWVu86jysXExAQ0Gg1KS0t3XLzs7++Pqqoq+Pn54dy5c5suNjYajRgbG9uRsNsKJpMJarXaq7PiVqJSqRAXFydIQfj09LTXDQovh4iVEAXsQtVZhYaGwmq1CmpX4OoQFKMcRiKRoLS0FK2trZuO4Ot0Opw7dw7p6ekoKCjYsTWIXC5HRUUFWltbBRl47Q1CQ0NRVVWFzs7OLTdAucoxMjIyVtVP2mw2vOMd75jWaDT379CviuMBLqwEQqPRfPjxxx/vPnHixKpi9uLiYqhUKmg0mk0dy2azoaGhwT0SxtczCNdCp9NhYGAA+/fv99oeXUaG+fn5bjf79XDNIywpKRHNy6uvrw9ZWVmC/l6ESgOazWZ3CsubXK3CKjIyUrAISHJysmCeVgAQEhKCsLCwbafft0poaChSUlI2LCR3DTPv6elBVVWVV4e2BwYGory8HI2NjV63yvAWAQEBOHjwIEZHRzEwsHk7qO7uboSGhnpsdnnooYeMHR0dvzAYDM95c68cB7vzE/oKgIgsWq323+6++27lytoFiUSC/fv3o7Ozc8PuGLPZjNraWkRHRyM/P3/XtrAbDAa0t7ejoqJCkGiaQqFAdXU1RkdH0dbWtuZVbl9fH2JjY73qIL4eCwsLmJ6eFrTrcHFxETabbU27ip0gRH0V4EhB7NaoqgshUoEymQwSicRrXa3LSUpKwsTEhKARpezsbPT29opmR5CWlgaDwbBmqmtxcRHnzp0DAFRXVwuSXg4LC0NBQQHq6uq83inqLeRyOSorKzE7O4u2trYNfz8TExMwGAweo/bPPPOM+dlnn23QarUPCbXfqx0urASEiHRqtfqmm2++WbeyW8jf3x9lZWVoaGhYs612YWEB58+fR3p6OtLS0sTY8rZYXFxEY2MjysvLBW2x9/PzQ0VFBYKCgnD27NlVonR6ehparVYwc05P9PT0ICcnR1DBOzY2JliaUYj6KtdJf7deBLgQImIFCFdnJZfLERoaKkjnoYvAwEBER0cLGhlbjquQvL29fdV5UKPRoLa2FtnZ2cjNzRX0/RQTE4P09HQ0NDTsOgNRF66MhUwmW7cJamZmBv39/di3b9+q16y+vh6f+cxnxjQazS28WF04uLASGCJqV6vVH3vb2942vfJqKDw8HNnZ2WhsbFz1xzw7O4sLFy6gqKjIJ4OcN4vFYkFdXR2Ki4tF6VBkjCEjIwNFRUVoaGhwfwDYbDa0traitLRUtFSp0WjE/Pw8YmNjBVuDiDA5OSlYRGxqasrr9VVLS0urHPZ3I35+foJEloSqswKEL2IHgMzMTAwMDIgmMAIDA5GRkYH2dsfAC7vdjo6ODgwMDKC6ulqQhg1PJCcnIyoqSjB3eG/g8h2LiYlBbW3tqvevyWRCS0sLysvLV0WMJycn8c53vlOj0WhuICLvGIlxPMKFlQjMz8+/3NfX96P7779/Vd9sYmIiFArFJZ2CWq0Wzc3NOHDggE+mnm8Wu92O+vp6ZGVlie6lFRkZiUOHDkGtVqOhoQFtbW3Yu3evIOmyteju7kZeXp6gV9JTU1MICwsTJK1msVggkUi8PnbmcqivAv4VUfP2h6iQdVbR0dGYnp4WNGXl7++PhIQEwUZMeSI5ORlWqxUDAwM4c+aMe8yL2AI9MzMTUqkUPT09oq67VVyTNs6fP++OuroucgsKCladB00mE44fPz6l0WjeQ0TDPtjyVQUXViKh1Wq/9Ic//OHcT37yk1UmN67C5+7uboyNjaG7uxtVVVWiioSt4vKJiouL85nru1wuR3l5OUJCQjAxMSHqSXhmZgZWq1VwQSlU0TrgqK8SQrhfDlYLLoSIWrlEsBADfxljSEhIENx/KT09HcPDw6LVHBERgoOD0dXVhfz8fGRnZ/sklcwYQ1FREQwGg6jCcjvEx8ejqKgIFy5cwPT0NOrr65GZmbkqwkdEeP/73z87Pj7+FbPZ/E/f7PbqggsrkSAi0mg0tz388MPDZ86cueQSmTGGwsJCqFQq9PX14eDBg7t6HAgAdHV1ISAgwOfzCS0WC5RKJQ4fPozJyUk0NjYKkt5ZSVdXl+B2DlarFTMzM4KJN71eL4jP1+USsQKErbMSKmqVkpIieDpQLpcjJSVFFHdyg8GAM2fOuOflDQwM+DQVxxhDeXk5xsbGBDVl9QYKhQL79+/H+fPnERIS4vEi97HHHls4ffr0q1NTU0/6YItXJVxYiQgRLWi12hvvuOMO9fK2WSJCW1sbIiIi4O/vv+v/mIeGhrCwsID8/HxfbwUXL15EdnY2wsPDsX//fiQkJODs2bOCXtHrdDrIZDLBOw9dtVVCXbkLFbG63ISVEN5Q0dHR2zZ13Ijg4GAADkdtIUlLS8P4+LggkTfAUUrQ29vrtkfJyclBQkICAgICBBeOG+EyEO3q6hK0WWCnEJF7lNbs7CzGxsYuefzll1+2PvHEE10ajebDPtriVQkXViJDRGNKpfLm66+/XqdWq92DigMCAlBaWoqKigoMDAyI5oC8VZRKJSYnJ1FWVubzrq/JyUkQEZKSktz3JSYmorq6GuPj44JEr1yeOrm5uV49rieE7AZ0fVgKUbt1OaUCAwMDBYlYKRQKQR299+zZs+pD1NtIpVKkpaVte/TMehgMBpw9exZEhMOHDyM8PNz9WEFBgfvizZe4upBbWloEF7Hbpbe3F3a7HQUFBTh48CAmJibcdhk1NTV0zz33DDuL1YVRxxyPcGHlA4ioeXJy8r3XXnvt9N/+9jfExcW5W/ZdbsAdHR1bHvcgNFNTU+jt7UVFRYVo5ptrYTKZ0NPTg+Li4lWP+fv748CBA4JErzQaDYKDgwXvgJyfnwdjTLDIz9TUlGApRpPJtOtT2S6ESgXK5XIQkWDRHledldApsz179kCtVntt/uHyKFVxcTFycnJWdfHKZDIUFxejubnZ5915QUFBKCsrQ319vddnQO6UkZERzM7Oori4GIwxyGQyVFRUYGFhAS+99BLuuOOOSa1Wew0Rzfh6r1cbXFj5CLPZ/HelUnn/l770JWN8fPwljwUEBODAgQNobm7eNVdKc3NzaG1tFcwAdCsQEVpaWlBQULDurDBX9GpychIXLlzY8WvpGv6ak5Ozo+NsBiGL1gFh/KuAy8fDyoVQqUDAEbUSKo0kk8kQGRkpWLrRhUQiQWZmJnp7e3d8LK1Wi9OnT3uMUq1EoVAgMjJyS07jQhEREYH8/HzU19fvGgNRpVKJ8fFxlJeXXyJMJRIJIiIi8OlPf3parVZfT0STPtzmVQsXVj5kZmbm2YGBga/efvvtMys9Y4KDg91XSr4etWAymdDQ0IDy8vJdkeIZGRlBUFDQpvyj/P39UV5ejoyMDDQ0NKC7u3vTs8lWMjk5icjISMHrh4gIKpVKUP8yoSJWl4Pj+nICAgIEE1ZRUVGCCh8xPK0Ah+P71NTUtiN7i4uLaGhowNDQEA4cOOAxSuWJ3NxcTE5OwmBY5VIjOrGxsdizZ49Hz0Gx0ev1a2YOdDodrr/+et34+PhxItrdnhFXMFxY+Ri9Xv/dCxcu/PKee+4xrAx7R0REuEctCJVS2Air1er2RgkLC/PJHpYzPz+P4eHhLRfOR0dH48iRI5DL5Th9+vSW56HZ7Xb3TECh0Wq1UCgUgqVbrVYr7Ha7IALocipcB4SNrAnlwO4iMjISRqNR8HMDYww5OTlb9nay2+3o7+/HhQsXkJKS4p6asFlcg5pbWlp8LmYAh5CNiIjY1EgZoTAYDGhra/OYOZifn8d11103NTEx8UEiqvPJBjkAuLDaFWi12gdeeeWVv3z1q19dlauKiYlBRkYG6uvrtx1p2S52ux0NDQ1IT08Xzf14PVzeWcXFxdsytZRIJMjIyEBVVRUmJiZQW1u76fTg2NgY4uLiRKkdEjoNKITbuovLqXDdhUwmE0Sc+Pn5wW63C5Y+Yoy55wcKTVxcHObn52E0Gjf1fK1Wi5qaGthsNhw5cmTbg5PDwsKQmJiIlfNWfUV2djaICH19faKvPT8/7x4dtvJvzGKx4KabbpoeHR190GQyvS765jiXwIXVLoCISKvVvu+pp56qf/rpp1dVSCYlJSEpKQl1dXWiiSsiQmtrK6KiojxOR/cF/f39iIqK2rEoCAgIQHl5ObKysjaVHrTZbBgcHERmZuaO1t0MFosFc3Nzglo5COVfBVx+EStAuAJ2QNg6K8DhWC7GXD/GGHJzczeMWi1P+1VUVCAnJ2fHkdeMjAxMT08L2mW5WRhjKC4uxvT0tKiWEAsLC6ivr0dZWdmqxhm73Y4777xztrOz83szMzO/EG1TnDXhwmqHMMYCGGN1jLFWxlgHY+wrKx5/kDFGjLF1P8mIyKrVam/+4he/2P3KK6+susTdu3cvEhISRItc9fT0QCqViiImNsPs7CyUSqVXC8ejoqLc6cGamhqMjo56DPEPDw8jOTlZlNqh8fFxJCcnC5qi0uv1gnUEXo4Rq8DAwMu2ziowMBAymWzTkaSdEB0dDYvF4rFb2WKxoKura9tpv/VgjKG0tBQXL17cFcXjEokE5eXlGBkZgUajEXy9hYUF1NXVoaSkxOMF16c+9SljTU3Nb3U63Tc2OhZjLIUxdpIx1uX8vPqk834FY+xNxlif899I7/8kVw9cWO2cJQDXEVEJgFIAxxljVYDjTQzgRgCburQhokWtVnvsox/96MhKd3bAMR8qLi5O8AnsIyMjMBgMKCoq2hXdXTabDS0tLYIMWHalBw8dOgSj0YiamhqoVCq3wLJYLBgdHUVaWppX110Ll7ASCqvVCpvNtm435U7gEatLEbrOChCviB0A8vLyLknL2Ww293y/gIAAHD16dNtpv/UIDg5GWloaOjo6vH7s7eCyNujs7MTs7Kxg6ywuLrqH3EdGrtY6jz322MLzzz//D61We98mD2kF8BkiygNQBeATjLF8AP8F4O9ElAXg787/c7YJF1Y7hBy4JoXLnTeXKHocwGeX/X8zx5vWarXX3H777RNNTU2rHk9LS0N0dLRg4kqtVmNsbAzl5eW7QlQBjmHHycnJghbP+/n5oaCgABUVFVAqlTh79iz0ej0GBwexd+9erw8q9oTBYICfn5+gdVzT09MeT9DegkesLsXf398tZoUiLi4OGo1GlALviIgISCQS6HQ6jI6OXlJHlZaW5vULn+Xs2bMHJpNp10ym8Pf3x/79+9HU1CSIMF9cXMSFCxdQXFzssfzh6aefXvr+97/frNFo3k1Em/rlE5GSiJqcXxsBdAFIAvAOAL9yPu1XAG71xs9wtcKFlRdgjEkZYy0ANADeJKILjLFbAEwQUetWj0dEE2q1+pqbb755sqWlZdXjGRkZUCgUXhdX09PT6Orq2hUGoC70ej1mZ2eRnp4uynqBgYEoKytDSUkJ+vr60N/fL1ih90pGR0cFc1p3IWR9FeCozRPyw1UIhIxYAcLXWUmlUkRFRYmSliIixMTE4MKFCzAYDDh06BCys7NFufBgjKGkpASdnZ2izAPdDCEhISgtLUV9fb1X9+QSVUVFRR7PPz/72c+WvvjFL7Zqtdobt+uqzhhLBVAG4AKAOCJSAg7xBWBjLxvOmlxeZ8BdChHZiKgUQDKACsZYMYCHATyyg2MOqtXqa2666SZlW1vbqsczMzMRFRXltZqr+fl5tLS0oKKiQrA00VaxWCxoa2tDaWmp6NGz0NBQhIaGIj09HR0dHYJdlbqw2+3QarVYaRbrbYSsr7JarbtGkG8FISNWgPB1VoCjBlPodKBer8fZs2cxMzODmJgYxMTEiH6uCAgIQG5uLlpbW33uyu4iMjISOTk5XjsXLxdVnv5Wf/WrXy19/vOfb9NqtceIaFtvXMZYCICXAHyKiHxvFHaFwYWVF3GODvgnHGHVNACtjLFhOARXE2NsS5+aRNSvUqmu/bd/+zdVZ2fnqsczMjIQExOz4z/opaUld8fJbqqP6ejoQHp6uk/2tLi4CJ1Oh9zcXFRXVyMpKQkNDQ1obm7G3NzcxgfYImq1GjExMYJGe2w2GywWC/z9/QU5/uLi4q56/2wWqVQqaBpNjDqr8PBwmEwmr49dISJotVqcP38eAwMDKCkpQVlZGQoLC9HT0+MTcZOQkACpVCqKzcRmiY+PR1JSEpqamnb0miwsLLjTf55E1bPPPmt+6KGHOrVa7bVEtK0rPcaYHA5R9SwR/cF5t5oxluB8PAGO7Atnm3BhtUMYYzGMsQjn14EAbgDQTESxRJRKRKkAxgHsI6KtuVICIKJepVJ57MYbb1R78nJJT09HXFzctsWV1WpFfX098vPzBW3x3yoqlQpms1nw1Nha9Pb2IisrC4wxMMYQFxeHI0eOIDExEa2traivr/fqLEehvasA4eurFhYWLrv6KhcSiUSwOqiAgABYLBbBu3mTkpK8Zr1ARFAqlThz5gxGR0fd9YeuVv+goCBERERgctI3E1OKiorQ398vaKRxq6SmpiIkJATt7e3bElfz8/Pu7j9P6b/nn3/e8ulPf7pLq9UeJaJtzedijtD/zwB0EdH3lz30JwAfdH79QQCvbOf4HAdcWO2cBAAnGWMXAdTDUWP1mjcXIKLuycnJ666//nq1p8hVWloaEhISUFdXt6V2ZLvdjsbGRuzZs2dT42HEYmlpCV1dXSgpKfFJAf38/DwMBsOqkTIugXXo0CFkZGSgp6cH58+fh06n29FV6tLSEpaWlgR3the6vupy7Ah0IXSdVWRkpOBD1ZOTk3ccxbHb7RgbG0NNTQ00Gg3Ky8tRXl7u8b2ZnZ2Nvr4+n7iiy+VyFBYW7opBzcvJzc2FxWLZ8ozDubk51NXVobS01OPFz+9+9zvL/fff363Vao8sa5baDocA3AXgOsZYi/N2M4DHANzIGOuDo5P9sR2scdUjfMXhFQ4RXYSjAHC956R6YZ1OxtixG2644R9vvPFGfGFh4SWP7927FxKJBLW1tZuqkyIitLW1ISIiQvBIyVZwGZPm5eUJlrLaiO7ubuTk5Kwr6hQKBSorKzE7O4u+vj50d3cjMzMTcXFxWxaDQlssuNDr9di7d69gx19cXBSsfktoXHVWK80XvYWrzkrI18ff3x8BAQGYnZ1dd8CxJ2w2G0ZHRzE8PIy4uDhUVlZu2J0aEBCA2NhYjI2NCfq+Wovo6GioVCoMDQ2J1tyyES7PrQsXLiAgIGBTf9czMzNobm7Gvn37PP7ennnmGfMDDzzQ6YxU7ciwjIjOAFjrBHX9To7N+Rc8YnUZQURdSqXy2re85S3K1tbVzYYpKSnIysrC+fPnN7z67uvrAxEhOztbqO1ui7GxMfj5+QlexL0WBoMBJpNp0yN8wsPDsX//fpSVlUGtVruNRjeb9iEiUYSV3W6H2WwW1MqBR6zWRow6K2DrnlZLS0vo7e1FTU0NLBYLDh8+jPz8/E2/TzIzMzE4OCj6uC0XeXl5GBsbE8UgdbNIJBLs378fg4ODGzYtaLVad9OQJ1H1y1/+cumBBx5o12q1h3cqqjjiwYXVZQYR9SiVyqPHjx+fbG5uXvV4XFwcioqK3O3QnhgbG8P09DSKi4t3jVcV4PhgHhwcREFBgc/20NXVhby8vC2/LsHBwSgpKUFlZSUWFhZQU1ODzs7ODWtAZmdnERQUJHh31czMjOA1dJejh5ULoTsDAwMDYTabBU+bxcbGQqfTbbjO9PQ0mpqaUFtbCz8/Pxw9ehTZ2dlbni7g5+eHpKQkDA8P72DX20cqlaKkpGTXDGp2IZfLUVFRgfb29jXPwxMTE+jq6sLBgwcRHBy86vGf/vSnps997nMXnem/bdVUcXwDF1aXIc5uwSM33XTTRF3d6iHmCoXCbVy38ipZo9FgeHgY5eXlu8pvyDVguaioSJTRMZ5wzSLbiW+Vqx38mmuuQVhYGBoaGlBXVwetVuuxFkSMonUAgqehAEc6SQw/IyEQOmIFOKKbQtdZSSQSxMbGQqVa3Sdjs9kwNjaG06dPo7+/H3v27MHRo0eRmpq6I5uM9PR0jI6O+mzcTEREBGJjY9Hb2+uT9dfCNZO0sbFxlWgfHBzEyMgIDh486LHk4Uc/+pHpC1/4QqtGo7lmu91/HN+xez5ZOVvC6XN16O1vf/vwX/7yl1WXaqGhoaisrER7ezuUSiUAR3Sks7MTFRUVu+4DcHBwEBERET6t0enu7kZubq5XjiWRSJCcnIwjR44gOzsbExMTOHXqFPr7+91GgjabDXq9XpTGAZ1OJ2jhut1u31XRz60idMQKcNQECe1nBaxOBxqNRrS3t6Ompgbz8/PYv38/Dhw4gOjoaK/8zmQyGfbu3bvlgm1vkpWVBZ1OJ6gR63YIDQ1FcXEx6urqYLFYQETo7OzE1NQUqqqqVl1EEhEeeeSR+S9/+cvnnZYKu6ftkbNpdtenK2dLENEIY+zABz7wgVPf+973Mu+6665L8kmBgYE4ePAg6uvrMTc3h/HxcRw4cMBnReFrYTAYMD4+jsOHD/tsD1qtFv7+/lsu+t0MERERKC0thcViwdjYGM6fP4+QkBAEBQUhNjZWcEHiqq8SMk13OacBAUfqRuiIS3R0NDxNUvA2oaGhMJvNGBwchFKphEQiwd69e5Gfny9YlHrv3r04ffo00tLSfGIwLJFIUFpaioaGBhw5cmRXGdVGRUUhKysLdXV1CAoKgkwm8zgyzGaz4WMf+5jhtddee12r1b6fiHxTuMbZMTxidZlDRDqtVlvxmc98puHb3/72qpCxn58f9u3bh76+PigUCo+5fF9it9vdA5Z9dTIkIncnoJDI5XKkp6fj6NGjSEtLw9jYGJRKJdrb2zEzMyNY2/jMzIwggnE5l3PhugvGmKB1OoGBgTCZTIKtYbfboVar3aknlUqF0tJSHDx4EImJiYKm/qVSKdLT09HX1yfYGhsREhKCvXv3wpMlja+JjY3F0tISZmZmUFBQsEpULS0t4ZZbbpl59dVXf6LRaP6di6rLGy6srgCIaF6r1V773e9+9++f/OQnjcs/oG02G5qamlBWVua2WNhNvi89PT1ISEgQ/IN/PVQqFcLCwhASEiLKeowxBAYGIigoCNdddx2io6PR19eHU6dOobe31+u1PkKOsXFxuUesAEdNjMlkEnSN8PBwzM7Oeu14RITp6Wm0tbXh1KlTUKvVSE9Px7Fjx2A2m0UVuykpKdBqtYK/huuRmpqKubk5UeYmbhaz2Yza2lpkZGQgNjYWXV1dlzxuMBhw9OjR6dra2q9qNJoHaTedoDnbggurKwQismi12lufe+65597znvfMuvL5TU1NSEpKQkJCAkpKSiCXy9HQ0OCzQtPlTE1NQa/XIzMz02d7ICL09vaKbjsxNjaGlJQUSCQSxMfH48CBAzh06BACAgLQ0tKCM2fOYHh42CuDXYU2BgWujIiVGAXs0dHRXrFdmJ+fR09PD06dOoXBwUHExsbimmuuQXFxMSIjI+Hn54fQ0FBRa44YY8jOzkZPT49oa3raQ2lpKTo6OmCxbGs2sVdZWFjA+fPnkZmZ6U7HLi4uYnBwEIDjoq6ysnKqq6vr43q9/nEfb5fjJbiwuoIgIrtGo7nnH//4x/duuOGG6bq6OoSEhCA1NRWA46STl5eH2NhYnDt3zqfjIKxWKy5evIiysjKfFj2Pj48jOjpa1GgLEWFychKJiYmX3C+Xy7Fnzx5UV1ejvLwcVqsVtbW1OHfuHAYGBjA/v/WOayISZYYfF1abY7sDmV2Rqa6uLpw6dQoXL15EUFAQDh8+jPLycsTFxa1K9W3V08obJCQkYHZ2dlvvVW8RGBiI7OxsXLx40Wd7ABwNI665fy5fPsYYysrKoFKpcPbsWVRVVekGBgbebTAYfufTzXK8Ci9evwLR6XRfi4yMVH7kIx/5wcmTJ1d92u3duxchISGora1dcy6V0HR0dCA1NdWnNV92ux0DAwM4ePCgqOtOTU0hLCxsXVuJwMBAZGZmIjMz010vc/HiRZjNZsTExCA+Ph6RkZEbitLtuHBvhyshFRgYGCi40WRQUBAWFxdBRBv+7mw2G7RaLVQqFaanpxEWFoaEhARkZmZuypIkOjoa7e3tsFqtonUBM8aQm5uLnp4e7Nu3T5Q1PZGUlASlUunxAkYMhoeHMTY2hqqqqlV/F1KpFDKZDLfddtvM+Pj4jUTUIvoGOYLChdUVyvT09E+DgoKUVVVVv/zHP/4RvdIrKSoqCpWVlWhoaEBqaqqoY200Gg0WFxdRXFws2pqeGBkZQXx8vOhdklv1rgoMDERaWhrS0tJgtVrdXmStra2IiIhAfHw8YmJiPH54iuFfBQAWi8Vn/mPeIigoCGq1WtA1GGMICwvD7OysR8NWk8kEtVoNlUqFxcVFxMTEICUlBcXFxVsuPmeMISEhAUqlUtRh5jExMejr64PBYBB8/uV6FBcX4+zZs1AoFIJOHFiO3W5He3s7LBYLqqurPTbk/O1vf7O/733vG9doNMeIaFCUjXFEhQurK5iFhYUTjLG3VVdX/+nEiROxJSUllzweFBSE6upqNDc3w2AweOxW8TZmsxkdHR04ePCgT1OAVqsVw8PDols8WK1WzM7OorS0dFvfL5PJkJiYiMTERHd6SKlUore3FzKZDFFRUYiOjkZkZCSkUin0ej1WzpX0Nq5a28vZxwoQx8sK+FedVUREBMxmM/R6PXQ6HaampiCVShEfH4/8/HyvzC1MSUlBa2urqMLKVXLQ3d2NiooK0dZdiZ+fHwoKCtDS0oLKykpRzm0NDQ2IiYlBUVGRx/WeffZZywMPPDDgNP7cPRX2HK/ChdUVDhFdYIwdectb3vLXp556Kvn222+/5Hcuk8mwf/9+9Pb2ora2Fvv37xc08nDx4kXk5OSIdgW5FkNDQ0hJSRE9yjI5OYmEhASvnOQZY1AoFO5U7tLSEnQ6HSYmJtDe3g65XA6j0YjFxUUEBAQIZmdhMpl8/vv0Bn5+fl5pFlgP11ibwcFBjI+PQyKRICoqCnFxccjLy/N6yi44OBhEJHoNnEKhgN1ux/T0NCIjI0VbdyUuF/qRkRF3rakQGAwGNDU1IS8vD3Fxcaset9vt+OxnPzv361//ulGr1b6dz/27suHC6iqAiHoZY2Uf//jHT7S0tBR/9atfDVmeVmCMIScnB5OTkzh79izKy8u9crW8kvHxcTDGfFLzsByLxYLx8XEcPXpU9LXHxsZQVlYmyLH9/f2RlJSEpKQkAA7T0+7u7kuEVnR0NCIiIhAREeG1FOiVUF8F/Cvitpn6p83gEjSzs7PuDliXkAKA6upqUYS9q4jdW1MFNkteXh46OjpQXV0t6roryc/Px5kzZxATEyNITadKpUJ3d/ea502DwYB3vvOdM21tbb/SarUPENHuGWrIEQQurK4SiGiGMXb0Jz/5yVONjY3v+f3vfx+x8iSTmJiIkJAQNDY2Ij8/36ujVhYXF9HX1+dTd3UX/f39SEtLE92QdH5+Howx0SIHBoMBKSkp7it1k8nkTju5RusEBQW5hVZ4ePi2Ik9XQkegC39/fywtLW35dXCJqJmZGfdt+esbGxuL3Nxcd0RqYWEBCwsLojQWJCQk4PTp08jJyRE1XRseHg4/Pz9otVrExMSItu5KZDIZiouL0dzcjEOHDnntNSAi9PX1Qa/Xo7q62qPj/MDAAI4fP67XaDSfmp2dfcYrC3N2PVxY7XIYYwEAagD4w/H7+j0RPcoY+xqAdwCwA9AA+BARTa53LKeb772RkZEN5eXlj/31r3+N2rt37yXPCQsLw8GDB9HQ0ACDwYCMjIwdn4iICC0tLSgsLPR5gfPS0hLUarVPolViDVx2odfrkZ+f7/5/QEDAJRGt5WJAp9NhYGAAS0tLbjEQGhqKkJAQBAcHrytCFxYWdp2j/3ZxWS6sJ6wsFgvm5uYwNzcHg8HgFlHBwcEIDw9HdHQ0MjMz140IuuqsxBBWMpkMkZGR0Ol0oguc3NxctLS0eG0u4XZRKBSIiopCX1+fVzzrrFYrWlpa4O/vj8rKSo+NBX//+9/t73//+1UqleoWImrc6JiMsRQAvwYQD8d5/Wki+gFj7N0AvgwgD0AFETXs+AfgCAoXVrufJQDXEdEcY0wO4Axj7M8AvkNEXwIAxth/AngEwL2bOeD09PRPGWPtBw8efPn555+PO3LkyCVnPH9/fxw8eBAdHR2oq6tDWVnZjuZ/DQ8PIyQkxKdXrS56e3uRmZkp6HgPTxARVCqVaEakRIT5+fl1BQ9jDMHBwQgODl4ltmZnZ2E0GqFUKjE/Pw+bzQZ/f3+EhIS4b8HBwW77AKENSMXCVcBus9kwPz+Pubk5979zc3Ow2WyQyWTunz8mJmZDEeWJqKgodHV1IT09XaCf5FL27NmDoaEh0f8GXe8VlUqFhIQEUddeSU5ODs6cOYO4uLgdCVqDwYDm5makpaV5vFAiIjz55JOmb3zjG/1arfZGIlJt8tBWAJ8hoibGWCiARsbYmwDaAbwLwP9te9McUeHCapfjHG8w5/yv3HkjIjIse1owgC2NQSCiWsbY/ttuu+1vX/va19LuueeeSz4ZJBIJioqKoFQqce7cORQXF2/L72pubg4jIyM4cuTIlr/X2ywsLGBqakrwLjlPaLVaKBQK0dKPRqMRoaGhW44SLBdbyyEimM1mt8DQarUYHh7GwsIC5ufnMTs7i+DgYPj7+yMgIMB9c/3f15FKF66fY2lpCSaTadXNYDDAarWiv7/fLZ5cFwXBwcFe+zlCQkIwPz/vtXqujYiMjMTFixd9YouRk5ODuro6xMfH+zRqJZFIUFZWhqamJhw+fHjLf4tEhNHRUQwPD6OsrMyjlYTZbMbdd989+8Ybb/xDq9XeSURLWzi+EoDS+bWRMdYFIImI3gQu/67bqwkurC4DGGNSAI0AMgE8RUQXnPd/A8AHAMwCOLbV4xLRBGNs3yOPPPJiY2PjkR/96EdhK7uSXHP8mpqaEBcXh8zMzE3/gdvtdjQ3N6OkpGRXTJvv7e0Vvc7ExejoKDIyMkRbz9v+VYwx+Pv7w9/ff9VxT548iaqqKphMJrdgWVxcxMzMjFuwuEYoMcYgk8ncJomeblKpFFKp1P17YoyBMQaLxQK1Wg0icls8EBGsVitsNhusVqvHm+sxF35+fpeIvuDgYERFRSEgIADz8/NQqVSCe6wxxhASEgKj0SiK1xNjDElJSZiYmBC0O84TgYGBiIqKwsTEBJKTk0VdeyWhoaFITk5Gd3c3CgoKNv19FosFra2tkMlkOHTokMfuTa1Wi5tuumlqZGTkuzqd7rGdzPxjjKUCKANwYbvH4PgOLqwuA5y1UaWMsQgALzPGComonYgeBvAwY+zzAO4D8Og2jr3IGHv7H//4xy+3tbXdf+LEiciVkSmX31VXVxcuXLiAsrKyTaU++vr6EBsb69N2axeuSIunVmihcdXkeDKEFAq9Xo+cnBzB13FFXPz8/DaVLnYJobXEj9VqxdLSEmw2m/v5rs8nm82GqampSwQXALcgCwoKukScrRRrmxHUEonEPcdNaKKioqDX60Uz0UxOTkZjY6PowgoAsrKycP78eSQmJoqehl9Jeno6zp8/D51Ot6kU9szMDFpaWpCZmbmmMGxtbcXb3/52rUaj+YDJZPrLTvbHGAsB8BKAT63ITHAuE7iwuoxwdvb9E8BxOPLuLn4L4AS2IaycxyUAj4aEhDSVlpb+5MUXX4yprKy85DkSiQQFBQVQq9U4d+4cioqK1j0pzczMQKPR4NChQ9vZktfp7u5Gbm6uT6JV4+PjSE5OFm1tIsLc3JwglhkrMZvNW6q/Y4xBLpdvKx2lVquRl5e35e/bCgEBATCZTIKu4SI6Ohq9vb1IS0sTZb3AwEDIZDJ3mlhM/P39ER8fj9HRUZ8Iu+W4BjXX1dXh0KFDa74XiQhDQ0MYHx/H/v37ERIS4vE5P/3pT5e++MUvTmo0muNE1LvDvcnhEFXPEtEfdnIsju/gQ5h3OYyxGGekCoyxQAA3AOhmjGUte9otALp3utbc3NwrY2NjlbfcckvXt771rUW7fbXdSlxcHKqqqtDT04Pu7m54inbbbDa0traitLTU51engEPkWSwWnxVYu4SVWMzNzSE4OFgUIXeleFi5WO5lJTShoaEwGo2irOXCF4OZXWRkZGBoaMgdjfQlQUFBSE9PR3t7u8fHzWYz6uvrMTc3h0OHDnkUVUajEe9617tmvvSlL53QaDRFXhBVDMDPAHQR0fd3ciyOb/H9px5nIxIAnGSMXQRQD+BNInoNwGOMsXbn/W8B8ElvLEZEQxqNpvSJJ574zbFjx6Z1Ot2q5wQGBroHF587d27VGJCuri6kpKSIflW8Ft3d3YJHOtbCYDC4a3rEQq/XiyYiryQPKxdyuRwWi0XwdVyNAvPz84Kv5SIuLg4ajQaeLpqERi6XIyUlBUNDQ6Kv7YmUlBRYLBYolcpL7p+amsK5c+eQnJyM4uJij/WhLS0tKCkp0Z08efIBlUp1GxF545d4CMBdAK5jjLU4bzczxt7JGBsHcBDACcbYX72wFkdAeCpwl0NEF+EoYlx5/20CrmkGcE9QUNBrpaWlP3322WdjrrnmmkvCHxKJBLm5udBqtaitrUVeXh7i4+Oh1WphNBq3VBgqJC63azHrm5YzNjYm6pw2wFG4Lpatw5UWsQL+ZbmwE4uRzRIVFQWdTucxIiIEUqkUUVFR0Gq1Pqk3TEtLQ01NDfbu3evzTlHGGEpKSnDu3DkoFAr4+fmhr68ParUaFRUVHi8YXFYK3/zmN8c1Gs1bdxqlWnHsMwDWCjO/7K11OMLDI1acNVlYWHh1YmKi/N3vfnfbI488Mu8phB8TE4Pq6mqMjo6ioaEBbW1tKC0t3RWtwUTk02iV3W6HRqNBfHy8aGsSkag1NFdixMplEioGLqNQMfFlOlAqlSItLQ0DAwM+WX8l/v7+yMvLQ2NjI86cOQO73Y5Dhw55fE/PzMzgpptumv7mN7/5e2+k/jhXLlxYcdaFiMa1Wm35j3/8458cOnRoSqVa7XXn7++PAwcOuNvqDYbd0cii0WgQGBjos5SkRqNBdHS0qHVm8/PzCAoKEk3YXonCKjAwUDRhFRYWBoPBIGqdVUREBBYWFgQfOL0We/bsgUqlwtLSpi2eBMN1ITI7O4uYmBjk5uZ6/Hu9cOECiouLtWfOnPm4Wq2+i4jE6XDgXJZwYcXZECKyajSaTzc1Nb1337596jfeeGNVgYZSqYS/vz+OHDmCkZERNDU1iVKnshZEhJ6eHtEHzy5H7BE2gLj1VYBj/qCY9WNi4HKTFwPX7EixhJyL5ORkjI+Pi7qmC4lEgszMTPT19flkfRdGoxFnz56F1WrFddddB5VKter3YLfb8dhjjy3ecsstXWNjY1Vzc3O/89F2OZcRXFhxNo3ZbH5TqVSW3nXXXY0PPvjgnMt00WQyoaenByUlJQgMDMSBAwcQGxuLM2fOQK1W+2Svk5OTiIiI8Fk0xWWUKcYsuOV42xh0I4hoV3R+ehOxhY6rzkpMfCmsACApKQl6vV40Absc1/DkpqYmFBYWIi8vD/7+/igqKkJzc7M7eqjT6XDddddNP/7447/RaDSlRCSOwRnnsufKOiNyBIeIVBqNpupXv/rVEyUlJfr29na0trYiPz/fXezLGENycjIOHjyIkZERNDc3ixq9stvtXhu2ul3EtlgAHB8YBoNBNDFntVp3haO+t3EVr4uFL+qsXK7zs7Ozoq7rgjGGnJwc9PT0iLru8ijVkSNHLmlqiYqKQkREBAYHB/HHP/7RWlxcrK6rq/uQWq2+x9nQw+FsCi6sOFuGiOxarfZLnZ2d1914441DzzzzjMVTlCQgIAAHDhxATEyMqNGrsbExxMbG+ixFRUQ+EVYLCwsIDAzk9VU7RCKRiFrzFB4e7hOB48sidsBh/eCaiCA0RIT+/v5LolSeIq0xMTG45557zPfee+8/lEpl4cLCwp8E3xznioMLK862IaKLKpUq53e/+93jJSUl+s7OzlXPWR69Gh4eFjx6ZbPZMDg4iMzMTMHW2IjZ2VkEBQWJ0q6/HLHrqxYXF69IYQU4uteWzxcUEsaYqAXzLmJjY6HT6XziaQU4fu7c3Fx0d+/Y23hdXFEqi8WCw4cPr2m98sc//tFWWlqqPnfu3F0qlerfiEjc/CznioELK86OICKLVqv9XGdn5/XHjh3r/9rXvrbg6QMpICAAFRUV7ujV6OioIFGB4eFhJCUliS5qluOLonVA/PoqV4TsSkTsdKAv6qwkEgliY2PhqdNXLKKjo2E2mwWJ2FmtVnR2dqK5udkdpfKUup6amsK73vWumXvvvffvSqWyaGFh4QWvb4ZzVcGFFccrEFGrRqPJ/+EPf/hUaWnputGrw4cPw2Aw4OzZs5iZmfHaHqxWK0ZHR5Genu61Y24Vm80GvV6P2NhY0deenZ0VtVj+Sk0FAr4pYBe7zgrwfToQAPLy8tDV1eW14xERJicncfr0aQQFBa2qpVrOn/70J1tRUZHmjTfe+A9nlErrtY1wrlq4sOJ4DSKyaDSaz3Z0dNxw7Nix/q9//eseo1dyuRyFhYUoLi5GR0cHLl686BVPnYGBAezduxcyme8GCqhUKsTFxYlukLqwsICAgABRO/SuRNd1F2JHrCIiIrx6kbFZQkNDYbFYRBs87YnIyEhIJBKvCEuj0Yjz589Do9GguroaqampHv8WXVGqj33sYycnJycLuY0Cx5twYcXxOkTUotFoCp588skflZWV6de6Gg0LC0N1dTUiIyNx9uxZjIyMbDs9aDabMTk5ib179+5k6zvGV2lAseurAB6x8iYSiQQBAQE+sR9ISUnB2NiY6Osux1Vrtd2/f6vVio6ODrS0tCAvLw+lpaXw9/f3+NxlUaqPq1SqG3mUiuNtuLDiCAIRmTUazUPt7e03HDt2rP+RRx6Z93RVzBhDSkoKDh8+7C4y3c6Ve19fHzIyMnza/r+4uAibzSba3LfliF1fBThsLa5EuwVA/IgV4Js6K8DhKTUxMSFqJ+RKwsLCEBgYCK12axqHiDAxMYHTp08jODgYhw8fRmRkpMfnKpVKvPOd75z56Ec/enJycrJobm7uOW/sncNZCRdWHDeMsQDGWB1jrJUx1sEY+4rz/u8wxroZYxcZYy8zxiI2e0wialGr1fk/+tGPHsvNzdW9/vrrHluQdpIeNJlM0Gq1og87XokvBi67mJ2dFXXQtM1mu+KMQZfjCzd0X/hZAY6/vdDQUExPT4u+9nJycnK2FLVypf20Wu26aT+r1Yrvfve7prKysonXX3/9Q2q1+kYi0mxmDcZYCmPsJGOsy3lO/KTz/m2fEzlXPlfumZGzHZYAXEdEJQBKARxnjFUBeBNAIREVA+gF8PmtHJSILDqd7usjIyOld9999xs33HDD1PDwsMfnrkwPDg8Pb9gO3tvbi+zsbJ8OfnYVzCYmJoq+9uLiIvz8/Hh9lReRyWTwNHRcSHxVZwXsjiL24OBgREREQKlUrvs8s9m86bTfqVOnKC8vT/ftb3/7h2q1OmtpaemVLW7LCuAzRJQHoArAJxhj+djhOZFzZcOFFccNOXC59cmdNyKiN4jIVYVeC2BbzpdENKFUKm86efLk7VVVVcNf+tKXNkwPLi4uoqamBpOTkx6vZOfn5zEzM4OEhITtbMlrTE1NISwsDHK5XPS19Xq96GnAK11YAY73oZgeTxKJBH5+fj4pJI+Ojsb09LRo3l1rkZ2djd7eXo+vu9VqRV9fH86ePYvQ0NBNpf3e8573nOvv76/UaDSfJaIt53aJSElETc6vjQC6ACR565zIuTLhwopzCYwxKWOsBYAGwJtEdGHFUz4M4M87WcNms51Uq9XZ//u///tYTk6O7sSJE2umB/Py8lBVVQWdToczZ86sqsFwDVr2ZbQK8F3ROsAL14XCV3VWvkgHMsaQkJCwYbRIaAICAhAbG3vJHEO73Y7h4WGcPn0ajDEcPXoUe/bs8fg3b7FY8J3vfMed9lOpVIe9NeOPMZYKoAyA18+JnCsLLqw4l0BENiIqheMKrIIxVuh6jDH2MByh8We9sI5Fp9N9fXR0tPTuu+9+4/rrr18zPRgQEIDi4mLs27cPIyMjOH/+PGZmZmAwGLC4uIiYmJidbmdHWK1WzMzMiB41cjE9PS1qfRVwdUSsrqYCdsDRHejrdCAAZGZmYmBgAFarFZOTk6ipqcHi4iIOHz6MzMzMNRsmTp06Rfn5+brvfOc72037rQljLATASwA+RUSGZfd77ZzIuXLwneEPZ1dDRDOMsX8COA6gnTH2QQBvA3A9ebF9iIgmANwklUqPVVZW/vxjH/tYzMMPPxzsac5fcHAw9u/fj5mZGXR1dcFgMKCwsNDn0SpXbZUv9mEymSCXy0XvzltYWPB5+lVofFHAHhkZifb2dlHXdBEcHAzA99FIPz8/RERE4OTJk4iNjUVVVdW6cz+VSiX+4z/+Y7q2trZDrVZ/0FsRKheMMTkcoupZIvrDsvsFOSdyLn94xIrjhjEW4+puYYwFArgBQDdj7DiAzwG4hYgE+aSx2WwnNRpN9o9+9KNvZWdna5955hnrWvUtERERyM3NRWBgIAYHB9Ha2upTg0NfdgP6or4KuLLnBLoICgoSPWIllUohl8uxtLQk6roufF3EPjMzg/Pnz8NqtUIikaCgoGBNUTU3N4dHHnlkvqysbPzPf/7z/1OpVEcEEFUMwM8AdBHR95fdL/g5kXP5woUVZzkJAE4yxi4CqIejxuo1AP8DIBTAm4yxFsbYj4VYnIgser3+G2NjYwUPPvjgr/Py8nR//vOf7Z4uBru6ulBSUoLDhw8jJiYGtbW16Ozs9IqD+1aYn58HY8xnIkOn04leXwU4all8UagvJr4YjAz4rs4KgLvOSuwAjNFoRENDA7q6upCXl4cDBw4gNTUVg4OrdZLZbMaTTz65lJ2drf7hD3/4qFqtzvBm2m8FhwDcBeA657mvhTF2M0Q6J3IuT3gqkOOGiC7CUZy58v5MkfehBXA3Yyz1wx/+8JNJSUnVTz31VFRlZSUAQKvVws/Pzz0XLzExEfHx8RgbG8O5c+cQFRWFzMxMUWqAfFm0DjjqqwoLCzd+ohe5WrIevkgFAg5hpVQqfWLdIZPJEBkZCZ1OJ0rt4vT0NPr6+mC1WpGVlXXJmqmpqaipqUFqair8/Pxgt9vx3HPPWb/whS9MLyws/EKn033d2aknGER0BoCnHP/rQq7LubzhwoqzayGiYQC3MMaKbr311v8tLCzMe/LJJxU6nQ5lZZfqP4lEgr1792LPnj2YnJxEfX09QkNDkZWVJZgTOhFBpVIhOztbkONvxNLSEmQymej1VSaT6YovXAccXakWi0X0dRUKBTwNMReLPXv2YGhoSDBhRUTQ6XTo6+uDVCpFdna2R9sEqVSK9PR09PX1YWxsjD71qU/pZ2ZmXlWr1Z/jY2g4uxkurDi7HiJqA3CYMXb4+uuv/8mBAwdSn3rqqQBPgokxhqSkJCQmJkKr1aK1tRV+fn7IysryeuecVquFQqHw2VgXX9VXLSwsXBXCytWMQESiNiZIpVJIpVKYzWb4+fmJtq6LyMhIXLx40evpXteFSH9/P4KDg1FYWIiwsLB1v2dychIf//jHTWq1+m9KpfJ+58UWh7Or4cKKc9lARGcYY/l/+ctfbikvL3/iPe95T9SXv/zlUIVCseq5jDHExsYiNjYWU1NT6Onpgd1uR1ZWFqKiorzyQTk2Noa0tLQdH2e76PV6xMfHi76ur7vGxCQgIMAnETpXnZUvOi8ZY0hMTPTaUHO73Y7x8XEMDg5CoVCgvLx8w/dPd3c3/vM//3Oqra2tW6VS3eu8uOJwLgt48TrnsoKIaGlp6RWNRpP5i1/84oH8/PzJRx99dGG9OWcKhQKVlZUoKCjAyMgIzp49C5VKtaNaIYvFAqPRuKbzsxhMTU35ZP2rwcPKhS+8rADf+lkBDk+rsbGxHR3DZrNhcHAQp06dwtzcHA4ePIji4uJ1RVV/fz/uvPPOmWuvvbbjzTffvFWpVB7ioopzucGFFeeyhIhsRqPxp2q1OuPxxx//r7y8vIlPfvKTRpVKteb3hIWFoby8HGVlZVCr1aipqcHw8PC2xnhMTEwgKSnJZx5aZrMZEokEMpn4QeerKWLlqwJ2hUKBqakp0dd1ERgYCJlMBqNx67Xhi4uL6O7uRk1NDaxWKw4fPoz8/Pw15/kBQEtLC9761rdOHTlypP2FF174d7VaXUREp3fyM3A4voILK85lDRGZDAbDD9VqderTTz/9idLS0qEPfvCDM57atF0EBwejpKQEVVVVMJvNOH36NNrb2zE/P7/pdX3pXQX4rr4K4BErMZDJZJBIJD4pnnexFSd2IoJer0dDQwMaGhoQHByMo0ePIjs7e906rdOnT+Pw4cP6m2++ufb1119/h1KpLLLZbH/mhpucyxleY8W5InAORP0NY+yZ3/72t2974403HquoqIj/+te/rigqKvL4Pf7+/sjOzkZmZiZUKhVaWloglUqRlpaG2NjYNaNRBoMBcrl8XTdoodHr9YiNjfXJ2ktLS+tGH64kgoKCfOYppVAofFZHBwDx8fHo6elBXl4eJBLP1+BWqxUTExMYGRlBcHAwMjIyNkxPExFOnDhBDz/8sF6r1TYqlcrPOq1eOJwrAi6sOFcUzivdVxljr/3pT386Ul9f/92srKz0b33rW1HV1dUev0cikSAxMRGJiYkwGAwYGhpCV1cXEhMTsWfPnlUCamxszKfeVYCjvionJ0f0dV2BBF+PERILX0WsACA6Oho6nc5nwkoqlSI6OhparRZxcXGXPGYwGDA8PAy9Xo/ExERUVFRseKFhtVrx4osv2h599NFpo9H4D5VK9TAR9Qv5M3A4voALK84ViVNg1cAxSHrf7bff/u34+PiSb3zjG1HHjx9nawmDsLAwlJSUwGq1Ynx8HHV1dQgMDERqaiqio6NBRNBoNMjLyxP151mOxWIBY8wnzue+sgDwFa6uQF+gUCjQ09Pjk7Vd7NmzB319fYiLi4PNZsPk5CRGRkYgl8uxd+9eFBUVbSiyTSYTfv7zn1v++7//e8ZkMv1Bo9F8lYgmRfoROBzR4cKK43MYYwFwiCB/ON6TvyeiRxlj7wbwZQB5ACqIqGE7xyeiJgA3MMay77777m8FBwcffeihh8Lf//73y9cqwpbJZEhNTUVqaiqmp6cxPDyMjo4OhIaGIjw8fM3UiBjo9Xp4spgQg6upcB3wnZcVALdw9uX4oPDwcBgMBjQ3N2NmZgbx8fHYt2/fpt4DSqUS//M//zP/i1/8Yt5isfxcp9N9h4i2XZHPGEsB8GsA8QDsAJ4moh8wxr4G4B3O+zQAPsSFG8eXMF4jyPE1zvBRMBHNOSfJnwHwSQCzcJws/w/Ag9sVVh7Wi4uKivqkTCb7f3fccUfQpz/96bDN+FFZLBacPXsWEokEEonEbUQqdr1RR0cHoqOjV6VnxGBychJGo9Enach//vOfuPbaa0Vf9+zZszhw4IBPInW++l3Pzc1hfHwcKpUKjDFERESgqKhowwsKIkJtbS2++c1v6hsaGqaNRuN/z8/PP0tEO86nMsYSACQQURNjLBRAI4BbAYwTkcH5nP8EkE9E9+50PQ5nu/CIFcfnONN2c87/yp03IqIuwPv1PESkBvAFxtijP/7xj9/14osvfjEnJyf+4Ycfjr7++uvX/PCw2+2QSCQ4evQoTCYTJiYmcOHCBfj5+SElJQVxcXGi2B9MTU35bIzO1RaxAv5lueALYeXysxJDWLne0xMTE/Dz80NycjIOHz4Mm82GCxcurCuqFhcX8dxzz1m//e1vzxiNxsbJycmvAKj1ZncfESkBKJ1fGxljXQCSiGj5/J9gADxawPEpXFhxdgWMMSkcV6CZAJ4iogtCr0lEFgDPA3ieMVbS29v7Bblcfuzee+8N+chHPhK4clba+Pg4kpOTAThqbzIyMpCRkQGj0Yjx8XH09vYiPDwcycnJiImJESR1ZLFYQEQ+Sw0tLCz41BTVF7iElbdHIm2GqKgo9PX1CXZ8q9UKpVKJ8fFxWK1WJCUlobKy8pIorEwmQ0BAAGZnZ92Dz110d3fjiSeemH3llVcWrFbrMzqd7nGnABIUxlgqHAPjLzj//w0AH4Ajyn1M6PU5nPXgwoqzKyAiG4BSxlgEgJcZY4VE1C7i+q0A3sMYC/vmN7/5wR/84AefOnDgQPiDDz4YdfToUQAOYXXw4MFV3xsaGoq8vDzk5uZienoaY2Nj6OjoQExMDBITExEZGek1kTU9Pe2z+irg6vKwcuHLzkC5XA673Q6r1eq1aKjVaoVOp8PExASMRiMSEhJQVFS07rDyPXv2YHR0FEVFRVhaWsJLL71k+853vjOl0WiGVCrVN+x2++tOyxPBYYyFAHgJwKdcKUAiehjAw4yxzwO4D8CjYuyFw/EEF1acXQURzTDG/gngOADRhNWy9Q0AfsgY+5/XXnutsqmp6fN+fn7V//7v/x5aWVnpv146iDEGhUIBhUIBu90OjUaDkZERtLS0IDIyEvHx8YiJidnRB6ROp/OZMSjgSBf50r/LFwQFBUGpFDwIsyYuF/ad+JaZTCao1WqoVCosLi4iJiYG6enpiIiI2JToj4mJwcsvv4wf/vCHs6+++qrJZrM9r9VqHxd7KLKzBvMlAM8S0R88POW3AE6ACyuOD+HCiuNzGGMxACxOURUI4AYA/+3LPTlrQ2oBvIMxFv7EE0/cERkZ+Z+PPPJI3L333htxxx13yNeLHEkkEsTHxyM+Ph5EhOnpaahUKvT29sLf3x/x8fGIi4vbcvRHr9cjMzNzZz/cDiAin3ZE+gJfRqwAh5/VVg1hiQgGgwEqlQoajQYSiQRxcXEoKChYNzK1koGBAfzyl79c+M1vfjNPRO2jo6PfBfCmM40uKs4ml58B6CKi7y+7P4uIXPnSWwB0i703Dmc5XFhxdgMJAH7lrLOSAHiBiF5jjL0TwA8BxAA4wRhrIaJ/E3tzRDQL4CcAfsIYS/r85z///77yla98OC8vL/TjH/+44m1ve5tkvSjO8kgWAMzPz0OlUqG5uRlWqxWxsbGIj49HeHj4utEDq9UKu93uMx8pi8Xik9mEvsbXwioqKgoDAwMbPs9ut0On00GlUkGv1yMkJATx8fGorKzc0ntGq9XiueeeMz/99NOz09PTYzqd7gdms/kPRDS38XcLyiEAdwFoY4y1OO/7AoC7GWM5cHQQjwDgHYEcn3L1nSU5uw7nOIsyD/e/DOBl8Xe0NkQ0AeDrAL7OGCvs6Oi457777rvt2muv9b/nnnsU11xzzYYRHdfoj4yMDFgsFqjVagwMDMBgMEChUCA6OhpRUVGrUm68vso3SCQSt+O8L/Dz84PNZoPNZoNUKnXfT0SYn5+HTqeDVqvF3NwcoqKiEB8fj8LCwi1FFhcWFvDKK6/Yn3rqKf3AwMDswsLC0waD4TdEtPZUc5EhojMAPF15vC72Xjic9eDCisPZJs7i+vsZY598/vnnD58+ffo+ANfedttt/h/60IfCysrKNqxfkcvlSE5ORnJyMux2O6anp6HT6TA8PAyLxYLIyEhER0e7x5v4sr7qarRacCGVSr1aQL5VIiMjodfrERQUBJ1OB51OB6PRiODgYERHRyMnJwehoaFbapIwm804efIk/u///k9/7ty5Jbvd/jutVvs0EfnW7p3DuczhBqEcjhdhjPlLJJKbExIS/oOISm+44QbZe9/73shjx45tuejbZrNhZmbG/UE6PT2NpKQkxMbGIjo6WnRj0sHBQUilUuzdu1fUdV34yiAUABobG5GVlYWwsDDR1lwekRobG8P8/Lw7ohkdHb1lIQU4avRef/11+zPPPKNvbW21SCSSvymVyh/Dy55THM7VDBdWHI5AODuYDsXHx99FRMcLCgrk73//+xVve9vbpCs9sjbCZrPh9OnTKCwshF6vh06nc0e0FAoFIiIiEBISIujYFZeFxE6603aCL4VVZ2cnoqKiBDXqtNlsMBgMmJmZwdTUFAwGA4KDgxEVFYXw8HB0d3fj8OHDWz5ub28vXn75ZdNvf/tbo0ajmTGbzc9PTU29AKCdiykOx/vwVCCHIxDOzql/AvgnY4yp1erc5ubmOx5++OH3KhSKqDvvvDPkXe96V2Bubu6GgshVX+WKVuTk5MBms2F6ehrT09Po7u7G/Pw8ZDIZwsPDERER4XWxdTWnAl0mod5iuYiamZmBwWAA4BgCHh4ejszMTISFhV3yu7NaravqrDxhtVpx/vx5vPDCC4ZXX311yWq19k9NTf1ycXHxT7upZorDuVLhESsOxwcwxmL9/PzeFhsb+yHGWN5b3/pW+a233hp+6NAhj+3w3d3dCA0NRVJS0rrHNZvNmJ2ddX9grxRb4eHh20ohAUBNTQ0OHTq04Qe7UPgyYqXRaKDValFQULDl77XZbJidnXX/XpaLKJcADgsL2/B1bW1tRVJSEqKjo1c9plKpcPLkSXrhhRemamtrrVKp9MzExMQvAfzdG3P6OBzO5uERK85VDWMsAEANAH84/h5+T0SPMsYUcIy7SQUwDOAOIpr21rpEpAHwcwA/Z4wF/PjHPz72yiuvvAvAdREREaHHjx8POH78eGh1dTVCQkKg1+uRmpq64XH9/PwQExOD5alGi8XiFlpqtRpzc3NgjCE4OBghISEICQlxf73eqBy73e4zUeVrNrJcICIsLS1hbm4O8/PzmJubw9zcHBYXF8EYQ3h4OMLDw5GamropEeUJl59VdHQ01Go1Tp48SSdOnJg+ffq0zWKxqJaWlk7o9fo/AGgkIvsOflyPMMZSAPwaQDwc1gZPE9EPlj3+IIDvAIghIp231+dwLhe4sOJc7SwBuI6I5pw1UWcYY38G8C44rvYfY4z9F4D/AvA5ITZARCYAf3bewBiL6OrqOvK73/3uHUR0LDIyMnTfvn2RH/jAB2SHDh1CcHDwlo4vl8tXiS2bzYaFhQW3ANDpdJibm3N3vq0UXQEBAVedMehyXMLKYrGsEk/z8/MgIvj7+7tfr5iYGKSlpSEwMNArqViXkHrppZfMzc3NhmVC6gSAeiJa2vlPuSFWAJ8hoibGWCiARsbYm0TU6RRdNwIYFWEfHM6uhqcCORwnjLEgAGcA/AccV+bXEpGSMZYA4J9ElOOjfUUAOJKQkPAOIjqmUChCjh8/Hnj8+PHQioqKVYNxd4rFYlklHAwGAxYXFxEcHAx/f3/4+/sjICDAfVv+f6EEmJCpQKvVCpPJhKWlJZhMplU3i8UCo9GIyMjISyJ8ISEhCAoK8nokb3JyEmfOnKETJ05Mnzp1anlE6nUAdSIJqXVhjL0C4H+I6E3G2O8BfA3AKwD284gV52qGCyvOVY/T8b0RQCaAp4joc4yxGSKKWPacaSKK9NUel8MYi4RTaAGolsvlivz8fFxzzTXhlZWV/vv27fO62HLVGOXn568SH8v/v7S0BLvdkYXy8/ODXC6HTCbzeJNKpR7vdwkzxpg72sMYcwsr1zmLiNw316Bi181ms13yf083i8UCi8UxmUUqlXoUia6bXC5HTU0Njhw54lXhSESYnJxEY2Mjzp07N3f69OmFoaEhkkgk44uLi3+fmpo6AeDCbhBSy2GMpcKRQi8EcC2A64nok4yxYXBhxbnK4cKKw3HijAy9DOB+AGd2q7BaiVMY5jDGyhMSEq4nokqZTKbIy8vDNddcE1ZZWRmwb98+REZuf/sjIyOw2WxIT0/f1POJCGazGRaLZUtix2q1usWS6zium9FodPtIrRRdEolkXQHnEnjLxZyfnx9kMtmmU3V1dXUoKCjYcip2+WsyPj7uElHG06dPL46MjJBEIhkzm81ntFrtKTgE/vhutkFgjIUAOAXgGwDnJTEOAAAHXElEQVT+AuAkgLcQ0SwXVhwOF1YcziUwxh4FMA/go9glqcDt4BRbWS6xBaBKKpVG5ebmoqKiIriwsDA4OzsbWVlZCA0N3fB4XV1diIyMRHx8vOB7XwtfdgUCQHt7O+Li4rCRBxkRQavVore3Fz09PdTW1masra01jY6OklQqHV1aWqrRarU1AJoATOxmEbUSZx3iawD+SkTfZ4wVAfg7AJcXRTKASQAV3NqBc7XCi9c5VzWMsRgAFiKaYYwFArgBwH8D+BOADwJ4zPnvK77b5dYhIhuAbuftWQBgjEnGxsay3nzzzfzIyMjikJCQfVarNUcikYQrFAppQUGBpLS0NCQvL88/Ozsb6enp7uG9CwsLG1o9XOkEBgZe4mVlNBrR19eH3t5etLe3z7e2ti709PRgbm7OIpFINIyxzqmpqYaFhYUuABeJaNJ3u985zBHa+xmALiL6PgAQURuA2GXPGQaPWHGucnjEinNVwxgrBvArAFIAEgAvENFXGWNRAF4AsAeOTqd3E9GU73YqLM40aBaA7Li4uH1+fn6lFoslXS6XByUlJSE+Pj68oKDAlpqaGpiYmMgSEhKQmJiImJgY0boFxYxYmc1mqFQqKJVKKJVKTE5O2ru7u5eGh4dtw8PDi1NTUza73T4rk8l65ubmmqanpy8C6AUw4OzyvOJgjB0GcBpAGxx2CwDwBSJ6fdlzhsGFFecqhwsrDoezJs4oRTwcfl4JAQEByREREVlyuTyViBKtVmu0TCbz8/f3l8bHx9OePXskqampgXv27AmKj49noaGhcN1CQkLc/25nmPF2hZXLX8poNMJoNLq/np2dxeTkpHVkZGRheHjYPDY2ZtfpdMxsNlvtdrtJLperAYybTKbBqampAZvNNglHmmuQiGa2vBEOh3NVwIUVh8PZMYwxPwBxABIAJMhkskSFQpEul8sjJRJJOGMsgohCbTZbiM1mC2aMyaRSqVQikUikUqkkMDAQISEhFBYWBrlcDqlUColEwlxF6RKJhC0sLIQGBgYa7XY72Ww22O12uL42mUwwGAwwGo0Ss9lMNpvNbrfbbXa73QbALJVK5yUSiZExZiSiWZvNNr20tKSbmpoaIiIlHIJJCUAnhLkmh8O5euDCisPxMWs5WjPGSgD8GEAIHO7v7yMig882KhDOqFggHD9nKP6VlpWs+FoCwAbHa7TyZgZgBGAkIrPIP4LgrPMe+TIcjRZa51MvSc1xOBzx4cKKw/Exzq7DhOWO1gBuhaP260EiOsUY+zCANCL6kg+3yvER67xH7gAwR0Tf9eX+OBzOv7h6Z1RwOLsEIlISUZPzayOALgBJAHLgMGEEgDcB3OabHXJ8zTrvEQ6Hs8vgworD2UU4Ha3LAFwA0A7gFudD7waQ4qNtcXYRK94jAHAfY+wiY+znTld+DofjQ7iw4nB2CU5H65cAfMpZS/VhAJ9gjDXCUXt0xdUOcbaGh/fI/wLIAFAKR/H993y3Ow6HA/AaKw5nV7DS0drD49kAniGiCtE3x9kVbOI9kgrgNSIqFHtvHA7nX/CIFYfjYzw5Wjvvj3X+KwHwRTg6BDlXIeu8RxKWPe2dcKSPORyOD+HCisPxPYcA3AXgOsZYi/N2M4A7GWO9cIylmQTwCyE3wRhLYYydZIx1McY6GGOfdN5fyhirde6rgTF21UTN1npNnI/dzxjrcd7/bYG3stZ75NuMsTbG2EUAxwB8WuB9cDicDeCpQA6HA2Ddlv4nADxORH92fph/loiu9dlGRWSd1yQOwMMA3kpES4yxWCLS+HCrHA5nl8CHMHM4HACOln44CqBBREbGmKulnwCEOZ8WDkf0TFDWMcR8Hg4bCgCIADBDRKVC7WOd1+SjAB4joiXnY1xUcTgcADxixeFwPOAshK4BUAiHkPgrAAZH+UA1EY0IvL7HSBERdS57zvcAzBLRV4Xcy7L1UvGv16QGwCsAjgMwwWHkWi/GPjgczu6G11hxOJxL8NDS/x8APk1EKXDU8PxM6D1sZIjpLOa+A8BzQu/Fud7K10QGIBJAFYCHALzg3BOHw7nK4cKKw+G4cbb0vwTgWSL6g/PuDwJwff0iAFGL1z0YYgLAEQBqIuoTYX1Pr8k4gD+Qgzo40pXRQu+Fw+Hsfriw4nA4ANZu6Yejpuoa59fXARBczCzb08pIkYs7IUK0ap3X5I9wvBYujzE/ADqh98PhcHY/vMaKw+EAABhjhwGcBtAGRwQGAL4AwADgB3Ckv0wAPk5EjSLsx6MhJmNMBmACQDkRjQu8h7Vek78B+DkcjudmOGqs/iHkXjgczuUBF1YcDmfX4YwU/QrAFBF9asVjxwF8noiu8fS9HA6H40t4KpDD4exG1jLEBID3QqSidQ6Hw9kqPGLF4XA4HA6H4yV4xIrD4XA4HA7HS3BhxeFwOBwOh+MluLDicDgcDofD8RJcWHE4HA6Hw+F4CS6sOBwOh8PhcLwEF1YcDofD4XA4XoILKw6Hw+FwOBwvwYUVh8PhcDgcjpf4/53fw6rnv/D7AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 720x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#\n",
+    "\n",
+    "dhna = deaths_headlines.dropna()\n",
+    "\n",
+    "fig = plt.figure(figsize=(10, 10))\n",
+    "ax = fig.add_subplot(111, projection=\"polar\")\n",
+    "\n",
+    "theta = np.roll(\n",
+    "    np.flip(\n",
+    "        np.arange(len(dhna))/float(len(dhna))*2.*np.pi),\n",
+    "    14)\n",
+    "# l15, = ax.plot(theta, deaths_headlines['total_2015'], color=\"#b56363\", label=\"2015\") # 0\n",
+    "# l16, = ax.plot(theta, deaths_headlines['total_2016'], color=\"#a4b563\", label=\"2016\") # 72\n",
+    "# l17, = ax.plot(theta, deaths_headlines['total_2017'], color=\"#63b584\", label=\"2017\") # 144\n",
+    "# l18, = ax.plot(theta, deaths_headlines['total_2018'], color=\"#6384b5\", label=\"2018\") # 216\n",
+    "# l19, = ax.plot(theta, deaths_headlines['total_2019'], color=\"#a4635b\", label=\"2019\") # 288\n",
+    "l15, = ax.plot(theta, dhna[2015], color=\"#e47d7d\", label=\"2015\") # 0\n",
+    "l16, = ax.plot(theta, dhna[2016], color=\"#afc169\", label=\"2016\") # 72 , d0e47d\n",
+    "l17, = ax.plot(theta, dhna[2017], color=\"#7de4a6\", label=\"2017\") # 144\n",
+    "l18, = ax.plot(theta, dhna[2018], color=\"#7da6e4\", label=\"2018\") # 216\n",
+    "l19, = ax.plot(theta, dhna[2019], color=\"#d07de4\", label=\"2019\") # 288\n",
+    "\n",
+    "lmean, = ax.plot(theta, dhna['previous_mean'], color=\"black\", linestyle='dashed', label=\"mean\")\n",
+    "\n",
+    "l20, = ax.plot(theta, dhna[2020], color=\"red\", label=\"2020\")\n",
+    "\n",
+    "# deaths_headlines.total_2019.plot(ax=ax)\n",
+    "\n",
+    "def _closeline(line):\n",
+    "    x, y = line.get_data()\n",
+    "    x = np.concatenate((x, [x[0]]))\n",
+    "    y = np.concatenate((y, [y[0]]))\n",
+    "    line.set_data(x, y)\n",
+    "\n",
+    "[_closeline(l) for l in [l19, l18, l17, l16, l15, lmean]]\n",
+    "\n",
+    "\n",
+    "ax.set_xticks(theta)\n",
+    "ax.set_xticklabels(dhna.index)\n",
+    "plt.legend()\n",
+    "plt.title(\"Deaths by week over years, all UK\")\n",
+    "plt.savefig('deaths-radar-2020.png')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "source": [
+    "# Plots for UK nations"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 116,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 720x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#\n",
+    "\n",
+    "fig = plt.figure(figsize=(10, 10))\n",
+    "ax = fig.add_subplot(111, projection=\"polar\")\n",
+    "\n",
+    "theta = np.roll(\n",
+    "    np.flip(\n",
+    "        np.arange(len(deaths_headlines_e))/float(len(deaths_headlines_e))*2.*np.pi),\n",
+    "    14)\n",
+    "l15, = ax.plot(theta, deaths_headlines_e[2015], color=\"#e47d7d\", label=\"2015\") # 0\n",
+    "l16, = ax.plot(theta, deaths_headlines_e[2016], color=\"#afc169\", label=\"2016\") # 72 , d0e47d\n",
+    "l17, = ax.plot(theta, deaths_headlines_e[2017], color=\"#7de4a6\", label=\"2017\") # 144\n",
+    "l18, = ax.plot(theta, deaths_headlines_e[2018], color=\"#7da6e4\", label=\"2018\") # 216\n",
+    "l19, = ax.plot(theta, deaths_headlines_e[2019], color=\"#d07de4\", label=\"2019\") # 288\n",
+    "\n",
+    "lmean, = ax.plot(theta, deaths_headlines_e['previous_mean'], color=\"black\", linestyle='dashed', label=\"mean\")\n",
+    "\n",
+    "l20, = ax.plot(theta, deaths_headlines_e[2020], color=\"red\", label=\"2020\")\n",
+    "\n",
+    "# deaths_headlines.total_2019.plot(ax=ax)\n",
+    "\n",
+    "def _closeline(line):\n",
+    "    x, y = line.get_data()\n",
+    "    x = np.concatenate((x, [x[0]]))\n",
+    "    y = np.concatenate((y, [y[0]]))\n",
+    "    line.set_data(x, y)\n",
+    "\n",
+    "[_closeline(l) for l in [l19, l18, l17, l16, l15, lmean]]\n",
+    "\n",
+    "\n",
+    "ax.set_xticks(theta)\n",
+    "ax.set_xticklabels(deaths_headlines_e.index)\n",
+    "plt.legend()\n",
+    "plt.title(\"Deaths by week over years, England\")\n",
+    "plt.savefig('deaths-radar-2020-england.png')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 117,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#\n",
+    "\n",
+    "fig = plt.figure(figsize=(10, 10))\n",
+    "ax = fig.add_subplot(111, projection=\"polar\")\n",
+    "\n",
+    "theta = np.roll(\n",
+    "    np.flip(\n",
+    "        np.arange(len(deaths_headlines_w))/float(len(deaths_headlines_w))*2.*np.pi),\n",
+    "    14)\n",
+    "l15, = ax.plot(theta, deaths_headlines_w[2015], color=\"#e47d7d\", label=\"2015\") # 0\n",
+    "l16, = ax.plot(theta, deaths_headlines_w[2016], color=\"#afc169\", label=\"2016\") # 72 , d0e47d\n",
+    "l17, = ax.plot(theta, deaths_headlines_w[2017], color=\"#7de4a6\", label=\"2017\") # 144\n",
+    "l18, = ax.plot(theta, deaths_headlines_w[2018], color=\"#7da6e4\", label=\"2018\") # 216\n",
+    "l19, = ax.plot(theta, deaths_headlines_w[2019], color=\"#d07de4\", label=\"2019\") # 288\n",
+    "\n",
+    "lmean, = ax.plot(theta, deaths_headlines_w['previous_mean'], color=\"black\", linestyle='dashed', label=\"mean\")\n",
+    "\n",
+    "l20, = ax.plot(theta, deaths_headlines_w[2020], color=\"red\", label=\"2020\")\n",
+    "\n",
+    "\n",
+    "def _closeline(line):\n",
+    "    x, y = line.get_data()\n",
+    "    x = np.concatenate((x, [x[0]]))\n",
+    "    y = np.concatenate((y, [y[0]]))\n",
+    "    line.set_data(x, y)\n",
+    "\n",
+    "[_closeline(l) for l in [l19, l18, l17, l16, l15, lmean]]\n",
+    "\n",
+    "\n",
+    "ax.set_xticks(theta)\n",
+    "ax.set_xticklabels(deaths_headlines_w.index)\n",
+    "plt.legend()\n",
+    "plt.title(\"Deaths by week over years, Wales\")\n",
+    "plt.savefig('deaths-radar-2020-wales.png')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 118,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#\n",
+    "\n",
+    "fig = plt.figure(figsize=(10, 10))\n",
+    "ax = fig.add_subplot(111, projection=\"polar\")\n",
+    "\n",
+    "theta = np.roll(\n",
+    "    np.flip(\n",
+    "        np.arange(len(deaths_headlines_s))/float(len(deaths_headlines_s))*2.*np.pi),\n",
+    "    14)\n",
+    "l15, = ax.plot(theta, deaths_headlines_s[2015], color=\"#e47d7d\", label=\"2015\") # 0\n",
+    "l16, = ax.plot(theta, deaths_headlines_s[2016], color=\"#afc169\", label=\"2016\") # 72 , d0e47d\n",
+    "l17, = ax.plot(theta, deaths_headlines_s[2017], color=\"#7de4a6\", label=\"2017\") # 144\n",
+    "l18, = ax.plot(theta, deaths_headlines_s[2018], color=\"#7da6e4\", label=\"2018\") # 216\n",
+    "l19, = ax.plot(theta, deaths_headlines_s[2019], color=\"#d07de4\", label=\"2019\") # 288\n",
+    "\n",
+    "lmean, = ax.plot(theta, deaths_headlines_s['previous_mean'], color=\"black\", linestyle='dashed', label=\"mean\")\n",
+    "\n",
+    "l20, = ax.plot(theta, deaths_headlines_s[2020], color=\"red\", label=\"2020\")\n",
+    "\n",
+    "\n",
+    "def _closeline(line):\n",
+    "    x, y = line.get_data()\n",
+    "    x = np.concatenate((x, [x[0]]))\n",
+    "    y = np.concatenate((y, [y[0]]))\n",
+    "    line.set_data(x, y)\n",
+    "\n",
+    "[_closeline(l) for l in [l19, l18, l17, l16, l15, lmean]]\n",
+    "\n",
+    "\n",
+    "ax.set_xticks(theta)\n",
+    "ax.set_xticklabels(deaths_headlines_s.index)\n",
+    "plt.legend()\n",
+    "plt.title(\"Deaths by week over years, Scotland\")\n",
+    "plt.savefig('deaths-radar-2020-scotland.png')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 119,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 720x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#\n",
+    "\n",
+    "fig = plt.figure(figsize=(10, 10))\n",
+    "ax = fig.add_subplot(111, projection=\"polar\")\n",
+    "\n",
+    "theta = np.roll(\n",
+    "    np.flip(\n",
+    "        np.arange(len(deaths_headlines_i))/float(len(deaths_headlines_i))*2.*np.pi),\n",
+    "    14)\n",
+    "l15, = ax.plot(theta, deaths_headlines_i[2015], color=\"#e47d7d\", label=\"2015\") # 0\n",
+    "l16, = ax.plot(theta, deaths_headlines_i[2016], color=\"#afc169\", label=\"2016\") # 72 , d0e47d\n",
+    "l17, = ax.plot(theta, deaths_headlines_i[2017], color=\"#7de4a6\", label=\"2017\") # 144\n",
+    "l18, = ax.plot(theta, deaths_headlines_i[2018], color=\"#7da6e4\", label=\"2018\") # 216\n",
+    "l19, = ax.plot(theta, deaths_headlines_i[2019], color=\"#d07de4\", label=\"2019\") # 288\n",
+    "\n",
+    "lmean, = ax.plot(theta, deaths_headlines_i['previous_mean'], color=\"black\", linestyle='dashed', label=\"mean\")\n",
+    "\n",
+    "l20, = ax.plot(theta, deaths_headlines_i[2020], color=\"red\", label=\"2020\")\n",
+    "\n",
+    "\n",
+    "def _closeline(line):\n",
+    "    x, y = line.get_data()\n",
+    "    x = np.concatenate((x, [x[0]]))\n",
+    "    y = np.concatenate((y, [y[0]]))\n",
+    "    line.set_data(x, y)\n",
+    "\n",
+    "[_closeline(l) for l in [l19, l18, l17, l16, l15, lmean]]\n",
+    "\n",
+    "\n",
+    "ax.set_xticks(theta)\n",
+    "ax.set_xticklabels(deaths_headlines_i.index)\n",
+    "plt.legend()\n",
+    "plt.title(\"Deaths by week over years, Northern Ireland\")\n",
+    "plt.savefig('deaths-radar-2020-northern-ireland.png')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "jupytext": {
+   "formats": "ipynb,md"
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/historical_deaths_import.md b/historical_deaths_import.md

new file mode 100644 (file)

index 0000000..9a7acd8
--- /dev/null
+++ b/historical_deaths_import.md
@@ -0,0 +1,1017 @@
+---
+jupyter:
+  jupytext:
+    formats: ipynb,md
+    text_representation:
+      extension: .md
+      format_name: markdown
+      format_version: '1.2'
+      jupytext_version: 1.9.1
+  kernelspec:
+    display_name: Python 3
+    language: python
+    name: python3
+---
+
+<!-- #region Collapsed="false" -->
+Data from:
+
+* [Office of National Statistics](https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/weeklyprovisionalfiguresondeathsregisteredinenglandandwales) (Endland and Wales) Weeks start on a Saturday.
+* [Northern Ireland Statistics and Research Agency](https://www.nisra.gov.uk/publications/weekly-deaths) (Northern Ireland). Weeks start on a Saturday. Note that the week numbers don't match the England and Wales data.
+* [National Records of Scotland](https://www.nrscotland.gov.uk/statistics-and-data/statistics/statistics-by-theme/vital-events/general-publications/weekly-and-monthly-data-on-births-and-deaths/weekly-data-on-births-and-deaths) (Scotland). Note that Scotland uses ISO8601 week numbers, which start on a Monday.
+
+<!-- #endregion -->
+
+```python Collapsed="false"
+import itertools
+import collections
+import json
+import pandas as pd
+import numpy as np
+from scipy.stats import gmean
+import datetime
+
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+%matplotlib inline
+
+from sqlalchemy.types import Integer, Text, String, DateTime, Float
+from sqlalchemy import create_engine
+%load_ext sql
+```
+
+```python Collapsed="false"
+connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'
+```
+
+```python Collapsed="false"
+%sql $connection_string
+```
+
+```python Collapsed="false"
+conn = create_engine(connection_string)
+```
+
+```python Collapsed="false"
+england_wales_filename = 'uk-deaths-data/publishedweek532020.xlsx'
+```
+
+```sql Collapsed="false"
+drop table if exists all_causes_deaths;
+create table all_causes_deaths (
+    week integer,
+    year integer,
+    date_up_to date,
+    nation varchar(20),
+    deaths integer,
+    CONSTRAINT week_nation PRIMARY KEY(year, week, nation)
+);
+```
+
+```python Collapsed="false"
+raw_data_2015 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2015.csv', 
+                       parse_dates=[1, 2], dayfirst=True,
+#                       index_col=0,
+                      header=[0, 1]
+                           )
+dh15i = raw_data_2015.iloc[:, [0, 3]]
+dh15i.set_index(dh15i.columns[0], inplace=True)
+dh15i.columns = ['total_2015']
+dh15i.tail()
+```
+
+```python Collapsed="false"
+raw_data_2015.head()
+```
+
+```python Collapsed="false"
+rd = raw_data_2015.iloc[:, [0, 2, 3]].droplevel(1, axis=1).rename(
+    columns={'Week Ends (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2015P)': 'deaths',
+            'Registration Week': 'week'}
+    )
+rd['year'] = 2015
+rd['nation'] = 'Northern Ireland'
+rd.head()
+```
+
+```python Collapsed="false"
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python Collapsed="false"
+%sql select * from all_causes_deaths limit 10
+```
+
+```python Collapsed="false"
+raw_data_2016 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2016.csv', 
+                        parse_dates=[1, 2], dayfirst=True,
+#                       index_col=0,
+                      header=[0, 1]
+                           )
+raw_data_2016.head()
+# dh16i = raw_data_2016.iloc[:, [2]]
+# dh16i.columns = ['total_2016']
+# # dh16i.head()
+dh16i = raw_data_2016.iloc[:, [0, 3]]
+dh16i.set_index(dh16i.columns[0], inplace=True)
+dh16i.columns = ['total_2016']
+dh16i.tail()
+```
+
+```python Collapsed="false"
+rd = raw_data_2016.iloc[:, [0, 2, 3]].droplevel(1, axis=1).rename(
+    columns={'Week Ends (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2016P)': 'deaths',
+            'Registration Week': 'week'}
+    )
+rd['year'] = 2016
+rd['nation'] = 'Northern Ireland'
+rd.head()
+```
+
+```python Collapsed="false"
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python Collapsed="false"
+%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation)
+```
+
+```python Collapsed="false"
+raw_data_2017 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2017.csv', 
+                        parse_dates=[1, 2], dayfirst=True,
+#                       index_col=0,
+                      header=[0, 1]
+                           )
+raw_data_2017.head()
+dh17i = raw_data_2017.iloc[:, [0, 3]]
+dh17i.set_index(dh17i.columns[0], inplace=True)
+dh17i.columns = ['total_2017']
+dh17i.tail()
+```
+
+```python Collapsed="false"
+rd = raw_data_2017.iloc[:, [0, 2, 3]].droplevel(1, axis=1).rename(
+    columns={'Week Ends (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2017P)': 'deaths',
+            'Registration Week': 'week'}
+    )
+rd['year'] = 2017
+rd['nation'] = 'Northern Ireland'
+rd.head()
+```
+
+```python Collapsed="false"
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python Collapsed="false"
+%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation)
+```
+
+```python Collapsed="false"
+raw_data_2018 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2018.csv', 
+                        parse_dates=[1, 2], dayfirst=True,
+#                       index_col=0,
+                      header=[0, 1]
+                           )
+raw_data_2018.head()
+dh18i = raw_data_2018.iloc[:, [0, 3]]
+dh18i.set_index(dh18i.columns[0], inplace=True)
+dh18i.columns = ['total_2018']
+dh18i.tail()
+```
+
+```python Collapsed="false"
+rd = raw_data_2018.iloc[:, [0, 2, 3]].droplevel(1, axis=1).rename(
+    columns={'Week Ends (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2018P)': 'deaths',
+            'Registration Week': 'week'}
+    )
+rd['year'] = 2018
+rd['nation'] = 'Northern Ireland'
+rd.head()
+```
+
+```python Collapsed="false"
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python Collapsed="false"
+%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation)
+```
+
+```python Collapsed="false"
+raw_data_2019 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2019.csv', 
+                        parse_dates=[1, 2], dayfirst=True,
+#                       index_col=0,
+                      header=[0, 1]
+                           )
+raw_data_2019.head()
+dh19i = raw_data_2019.iloc[:, [0, 3]]
+dh19i.set_index(dh19i.columns[0], inplace=True)
+dh19i.columns = ['total_2019']
+dh19i.tail()
+```
+
+```python Collapsed="false"
+rd = raw_data_2019.iloc[:, [0, 2, 3]].droplevel(1, axis=1).rename(
+    columns={'Week Ends (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2019P)': 'deaths',
+            'Registration Week': 'week'}
+    )
+rd['year'] = 2019
+rd['nation'] = 'Northern Ireland'
+rd.head()
+```
+
+```python Collapsed="false"
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python Collapsed="false"
+%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation)
+```
+
+```python Collapsed="false"
+raw_data_2020_i = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2020.csv', 
+                        parse_dates=[1], dayfirst=True,
+                      header=[0, 1]
+                           )
+raw_data_2020_i.head()
+```
+
+```python Collapsed="false"
+rd = raw_data_2020_i.iloc[:, [0, 1, 2]].droplevel(1, axis=1).rename(
+    columns={'Week Ending (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2020P)': 'deaths',
+            'Registration Week': 'week'}
+    )
+rd['year'] = 2020
+rd['nation'] = 'Northern Ireland'
+rd.head()
+```
+
+```python Collapsed="false"
+rd.tail()
+```
+
+```python Collapsed="false"
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python Collapsed="false"
+%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year
+```
+
+```python
+raw_data_2020_i.set_index(raw_data_2020_i.columns[0], inplace=True)
+raw_data_2020_i.tail()
+```
+
+```python Collapsed="false"
+datetime.datetime.now().isocalendar()
+```
+
+```python Collapsed="false"
+datetime.datetime.fromisocalendar(2021, 3, 1)
+```
+
+```python Collapsed="false"
+
+```
+
+```python Collapsed="false"
+raw_data_s = pd.read_csv('uk-deaths-data/weekly-deaths-scotland.csv', 
+                      index_col=0,
+                      header=0,
+                        skiprows=2
+                           )
+# raw_data_s
+```
+
+```python Collapsed="false"
+deaths_headlines_s = raw_data_s[reversed('2015 2016 2017 2018 2019 2020'.split())]
+deaths_headlines_s.columns = ['total_' + c for c in deaths_headlines_s.columns]
+deaths_headlines_s.reset_index(drop=True, inplace=True)
+deaths_headlines_s.index = deaths_headlines_s.index + 1
+deaths_headlines_s
+```
+
+```python
+%sql select * from all_causes_deaths limit 5
+```
+
+```python Collapsed="false"
+for year, ser in deaths_headlines_s.items():
+    year_i = int(year[-4:])
+#     print(year_i)
+    for week, deaths in ser.dropna().iteritems():
+#         print(datetime.date.fromisocalendar(year_i, week, 7), deaths)
+        dut = datetime.date.fromisocalendar(year_i, week, 7)
+        %sql insert into all_causes_deaths(week, year, date_up_to, nation, deaths) values ({week}, {year_i}, :dut, 'Scotland', {deaths})
+```
+
+```python
+%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year
+```
+
+```python
+%sql select year, nation, date_up_to from all_causes_deaths where week=3 order by year, nation
+```
+
+```python Collapsed="false"
+eng_xls = pd.read_excel(england_wales_filename, 
+                        sheet_name="Weekly figures 2020",
+                        skiprows=[0, 1, 2, 3],
+                        header=0,
+                        index_col=[1]
+                       ).iloc[:91].T
+eng_xls
+```
+
+```python Collapsed="false"
+# eng_xls_columns
+```
+
+```python Collapsed="false"
+eng_xls_columns = list(eng_xls.columns)
+
+for i, c in enumerate(eng_xls_columns):
+#     print(i, c, type(c), isinstance(c, float))
+    if isinstance(c, float) and np.isnan(c):
+        if eng_xls.iloc[0].iloc[i] is not pd.NaT:
+            eng_xls_columns[i] = eng_xls.iloc[0].iloc[i]
+
+# np.isnan(eng_xls_columns[0])
+# eng_xls_columns
+
+eng_xls.columns = eng_xls_columns
+# eng_xls.columns
+```
+
+```python
+eng_xls
+```
+
+```python
+rd = eng_xls.iloc[1:][['Week ended', 'Wales']].reset_index(level=0).rename(
+    columns={'Week ended': 'date_up_to', 'Wales': 'deaths',
+            'index': 'week'}
+    )
+rd['year'] = 2020
+rd['nation'] = 'Wales'
+rd.head()
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python Collapsed="false"
+eng_xls = eng_xls.iloc[1:]
+eng_xls['England deaths'] = eng_xls.loc[:, 'Total deaths, all ages'] - eng_xls.loc[:, 'Wales']
+```
+
+```python
+eng_xls.head()
+```
+
+```python
+rd = eng_xls[['Week ended', 'England deaths']].reset_index(level=0).rename(
+    columns={'Week ended': 'date_up_to', 'England deaths': 'deaths',
+            'index': 'week'}
+    )
+rd['year'] = 2020
+rd['nation'] = 'England'
+rd.head()
+```
+
+```python
+%sql delete from all_causes_deaths where nation = 'England'
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python
+rd.tail()
+```
+
+```python
+%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year
+```
+
+```python Collapsed="false"
+# raw_data_2020 = pd.read_csv('uk-deaths-data/publishedweek272020.csv', 
+#                        parse_dates=[1], dayfirst=True,
+#                       index_col=0,
+#                       header=[0, 1])
+```
+
+```python Collapsed="false"
+
+```
+
+```python Collapsed="false"
+# raw_data_2020.head()
+```
+
+```python Collapsed="false"
+# raw_data_2020['W92000004', 'Wales']
+```
+
+```python Collapsed="false"
+raw_data_2019 = pd.read_csv('uk-deaths-data/publishedweek522019.csv', 
+                       parse_dates=[1], dayfirst=True,
+#                       index_col=0,
+                      header=[0, 1])
+# raw_data_2019.head()
+```
+
+```python
+rdew = raw_data_2019.iloc[:, [0, 1, 2, -1]].droplevel(axis=1, level=1)
+rdew.head()
+```
+
+```python
+rd = rdew.drop(columns=['Total deaths, all ages']).rename(
+    columns={'Week ended': 'date_up_to', 'W92000004': 'deaths',
+            'Week number': 'week'}
+    )
+rd['year'] = 2019
+rd['nation'] = 'Wales'
+rd.head()
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python
+rd = rdew.loc[:, ['Week ended','Week number']]
+rd['deaths'] = rdew['Total deaths, all ages'] - rdew['W92000004']
+rd = rd.rename(
+    columns={'Week ended': 'date_up_to', 'Week number': 'week'}
+    )
+rd['year'] = 2019
+rd['nation'] = 'England'
+rd.head()
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python
+%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year
+```
+
+```python Collapsed="false"
+raw_data_2018 = pd.read_csv('uk-deaths-data/publishedweek522018.csv', 
+                       parse_dates=[1], dayfirst=True,
+#                       index_col=0,
+                      header=[0, 1])
+# raw_data_2018.head()
+```
+
+```python
+rdew = raw_data_2018.iloc[:, [0, 1, 2, -1]].droplevel(axis=1, level=1)
+rdew.head()
+```
+
+```python
+rd = rdew.drop(columns=['Total deaths, all ages']).rename(
+    columns={'Week ended': 'date_up_to', 'W92000004': 'deaths',
+            'Week number': 'week'}
+    )
+rd['year'] = 2018
+rd['nation'] = 'Wales'
+rd.head()
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python
+rd = rdew.loc[:, ['Week ended','Week number']]
+rd['deaths'] = rdew['Total deaths, all ages'] - rdew['W92000004']
+rd = rd.rename(
+    columns={'Week ended': 'date_up_to', 'Week number': 'week'}
+    )
+rd['year'] = 2018
+rd['nation'] = 'England'
+rd.head()
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python
+%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year
+```
+
+```python Collapsed="false"
+raw_data_2017 = pd.read_csv('uk-deaths-data/publishedweek522017.csv', 
+                       parse_dates=[1], dayfirst=True,
+#                       index_col=0,
+                      header=[0, 1])
+# raw_data_2017.head()
+```
+
+```python
+rdew = raw_data_2017.iloc[:, [0, 1, 2, -1]].droplevel(axis=1, level=1)
+rdew.head()
+```
+
+```python
+rd = rdew.drop(columns=['Total deaths, all ages']).rename(
+    columns={'Week ended': 'date_up_to', 'W92000004': 'deaths',
+            'Week number': 'week'}
+    )
+rd['year'] = 2017
+rd['nation'] = 'Wales'
+rd.head()
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python
+rd = rdew.loc[:, ['Week ended','Week number']]
+rd['deaths'] = rdew['Total deaths, all ages'] - rdew['W92000004']
+rd = rd.rename(
+    columns={'Week ended': 'date_up_to', 'Week number': 'week'}
+    )
+rd['year'] = 2017
+rd['nation'] = 'England'
+rd.head()
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python
+%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year
+```
+
+```python
+
+```
+
+```python Collapsed="false"
+raw_data_2016 = pd.read_csv('uk-deaths-data/publishedweek522016.csv', 
+                       parse_dates=[1], dayfirst=True,
+#                       index_col=0,
+                      header=[0, 1])
+# raw_data_2016.head()
+```
+
+```python
+raw_data_2016.head()
+```
+
+```python
+rdew = raw_data_2016.iloc[:, [0, 1, 2, -1]].droplevel(axis=1, level=1)
+rdew.head()
+```
+
+```python
+rd = rdew.drop(columns=['Total deaths, all ages']).rename(
+    columns={'Week ended': 'date_up_to', 'W92000004': 'deaths',
+            'Week number': 'week'}
+    )
+rd['year'] = 2016
+rd['nation'] = 'Wales'
+rd.head()
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python
+rd = rdew.loc[:, ['Week ended','Week number']]
+rd['deaths'] = rdew['Total deaths, all ages'] - rdew['W92000004']
+rd = rd.rename(
+    columns={'Week ended': 'date_up_to', 'Week number': 'week'}
+    )
+rd['year'] = 2016
+rd['nation'] = 'England'
+rd.head()
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python
+ %sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by nation, year
+```
+
+```python Collapsed="false"
+raw_data_2015 = pd.read_csv('uk-deaths-data/publishedweek2015.csv', 
+                       parse_dates=[1], dayfirst=True,
+#                       index_col=0,
+                      header=[0, 1])
+# raw_data_2015.head()
+```
+
+```python
+rdew = raw_data_2015.iloc[:, [0, 1, 2, -1]].droplevel(axis=1, level=1)
+rdew.head()
+```
+
+```python
+rd = rdew.drop(columns=['Total deaths, all ages']).rename(
+    columns={'Week ended': 'date_up_to', 'W92000004': 'deaths',
+            'Week number': 'week'}
+    )
+rd['year'] = 2015
+rd['nation'] = 'Wales'
+rd.head()
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python
+rd = rdew.loc[:, ['Week ended','Week number']]
+rd['deaths'] = rdew['Total deaths, all ages'] - rdew['W92000004']
+rd = rd.rename(
+    columns={'Week ended': 'date_up_to', 'Week number': 'week'}
+    )
+rd['year'] = 2015
+rd['nation'] = 'England'
+rd.head()
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    conn,
+    if_exists='append',
+    index=False)
+```
+
+```python
+%sql select year, nation, count(date_up_to) from all_causes_deaths group by (year, nation) order by year, nation
+```
+
+```sql magic_args="res << select week, year, deaths"
+from all_causes_deaths
+where nation = 'England'
+```
+
+```python
+deaths_headlines_e = res.DataFrame().pivot(index='week', columns='year', values='deaths')
+deaths_headlines_e
+```
+
+```python
+
+```
+
+```sql magic_args="res << select week, year, deaths"
+from all_causes_deaths
+where nation = 'Scotland'
+```
+
+```python
+deaths_headlines_s = res.DataFrame().pivot(index='week', columns='year', values='deaths')
+deaths_headlines_s
+```
+
+```sql magic_args="res << select week, year, deaths"
+from all_causes_deaths
+where nation = 'Wales'
+```
+
+```python
+deaths_headlines_w = res.DataFrame().pivot(index='week', columns='year', values='deaths')
+deaths_headlines_w
+```
+
+```sql magic_args="res << select week, year, deaths"
+from all_causes_deaths
+where nation = 'Northern Ireland'
+```
+
+```python
+deaths_headlines_i = res.DataFrame().pivot(index='week', columns='year', values='deaths')
+deaths_headlines_i
+```
+
+```python Collapsed="false"
+deaths_headlines = deaths_headlines_e + deaths_headlines_w + deaths_headlines_i + deaths_headlines_s
+deaths_headlines
+```
+
+```python
+deaths_headlines_e.columns
+```
+
+```python
+deaths_headlines_e['previous_mean'] = deaths_headlines_e[[int(y) for y in '2019 2018 2017 2016 2015'.split()]].apply(np.mean, axis=1)
+deaths_headlines_w['previous_mean'] = deaths_headlines_w[[int(y) for y in '2019 2018 2017 2016 2015'.split()]].apply(np.mean, axis=1)
+deaths_headlines_s['previous_mean'] = deaths_headlines_s[[int(y) for y in '2019 2018 2017 2016 2015'.split()]].apply(np.mean, axis=1)
+deaths_headlines_i['previous_mean'] = deaths_headlines_i[[int(y) for y in '2019 2018 2017 2016 2015'.split()]].apply(np.mean, axis=1)
+deaths_headlines['previous_mean'] = deaths_headlines[[int(y) for y in '2019 2018 2017 2016 2015'.split()]].apply(np.mean, axis=1)
+deaths_headlines
+```
+
+```python Collapsed="false"
+deaths_headlines[[2020, 2019, 2018, 2017, 2016, 2015]].plot(figsize=(14, 8))
+```
+
+```python Collapsed="false"
+deaths_headlines[[2020, 'previous_mean']].plot(figsize=(10, 8))
+```
+
+```python Collapsed="false"
+deaths_headlines_i.plot()
+```
+
+```python
+deaths_headlines[2020].sum() - deaths_headlines.previous_mean.sum()
+```
+
+```python Collapsed="false"
+# Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#
+
+dhna = deaths_headlines.dropna()
+
+fig = plt.figure(figsize=(10, 10))
+ax = fig.add_subplot(111, projection="polar")
+
+theta = np.roll(
+    np.flip(
+        np.arange(len(dhna))/float(len(dhna))*2.*np.pi),
+    14)
+# l15, = ax.plot(theta, deaths_headlines['total_2015'], color="#b56363", label="2015") # 0
+# l16, = ax.plot(theta, deaths_headlines['total_2016'], color="#a4b563", label="2016") # 72
+# l17, = ax.plot(theta, deaths_headlines['total_2017'], color="#63b584", label="2017") # 144
+# l18, = ax.plot(theta, deaths_headlines['total_2018'], color="#6384b5", label="2018") # 216
+# l19, = ax.plot(theta, deaths_headlines['total_2019'], color="#a4635b", label="2019") # 288
+l15, = ax.plot(theta, dhna[2015], color="#e47d7d", label="2015") # 0
+l16, = ax.plot(theta, dhna[2016], color="#afc169", label="2016") # 72 , d0e47d
+l17, = ax.plot(theta, dhna[2017], color="#7de4a6", label="2017") # 144
+l18, = ax.plot(theta, dhna[2018], color="#7da6e4", label="2018") # 216
+l19, = ax.plot(theta, dhna[2019], color="#d07de4", label="2019") # 288
+
+lmean, = ax.plot(theta, dhna['previous_mean'], color="black", linestyle='dashed', label="mean")
+
+l20, = ax.plot(theta, dhna[2020], color="red", label="2020")
+
+# deaths_headlines.total_2019.plot(ax=ax)
+
+def _closeline(line):
+    x, y = line.get_data()
+    x = np.concatenate((x, [x[0]]))
+    y = np.concatenate((y, [y[0]]))
+    line.set_data(x, y)
+
+[_closeline(l) for l in [l19, l18, l17, l16, l15, lmean]]
+
+
+ax.set_xticks(theta)
+ax.set_xticklabels(dhna.index)
+plt.legend()
+plt.title("Deaths by week over years, all UK")
+plt.savefig('deaths-radar-2020.png')
+plt.show()
+```
+
+<!-- #region Collapsed="false" -->
+# Plots for UK nations
+<!-- #endregion -->
+
+```python Collapsed="false"
+# Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#
+
+fig = plt.figure(figsize=(10, 10))
+ax = fig.add_subplot(111, projection="polar")
+
+theta = np.roll(
+    np.flip(
+        np.arange(len(deaths_headlines_e))/float(len(deaths_headlines_e))*2.*np.pi),
+    14)
+l15, = ax.plot(theta, deaths_headlines_e[2015], color="#e47d7d", label="2015") # 0
+l16, = ax.plot(theta, deaths_headlines_e[2016], color="#afc169", label="2016") # 72 , d0e47d
+l17, = ax.plot(theta, deaths_headlines_e[2017], color="#7de4a6", label="2017") # 144
+l18, = ax.plot(theta, deaths_headlines_e[2018], color="#7da6e4", label="2018") # 216
+l19, = ax.plot(theta, deaths_headlines_e[2019], color="#d07de4", label="2019") # 288
+
+lmean, = ax.plot(theta, deaths_headlines_e['previous_mean'], color="black", linestyle='dashed', label="mean")
+
+l20, = ax.plot(theta, deaths_headlines_e[2020], color="red", label="2020")
+
+# deaths_headlines.total_2019.plot(ax=ax)
+
+def _closeline(line):
+    x, y = line.get_data()
+    x = np.concatenate((x, [x[0]]))
+    y = np.concatenate((y, [y[0]]))
+    line.set_data(x, y)
+
+[_closeline(l) for l in [l19, l18, l17, l16, l15, lmean]]
+
+
+ax.set_xticks(theta)
+ax.set_xticklabels(deaths_headlines_e.index)
+plt.legend()
+plt.title("Deaths by week over years, England")
+plt.savefig('deaths-radar-2020-england.png')
+plt.show()
+```
+
+```python Collapsed="false"
+# Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#
+
+fig = plt.figure(figsize=(10, 10))
+ax = fig.add_subplot(111, projection="polar")
+
+theta = np.roll(
+    np.flip(
+        np.arange(len(deaths_headlines_w))/float(len(deaths_headlines_w))*2.*np.pi),
+    14)
+l15, = ax.plot(theta, deaths_headlines_w[2015], color="#e47d7d", label="2015") # 0
+l16, = ax.plot(theta, deaths_headlines_w[2016], color="#afc169", label="2016") # 72 , d0e47d
+l17, = ax.plot(theta, deaths_headlines_w[2017], color="#7de4a6", label="2017") # 144
+l18, = ax.plot(theta, deaths_headlines_w[2018], color="#7da6e4", label="2018") # 216
+l19, = ax.plot(theta, deaths_headlines_w[2019], color="#d07de4", label="2019") # 288
+
+lmean, = ax.plot(theta, deaths_headlines_w['previous_mean'], color="black", linestyle='dashed', label="mean")
+
+l20, = ax.plot(theta, deaths_headlines_w[2020], color="red", label="2020")
+
+
+def _closeline(line):
+    x, y = line.get_data()
+    x = np.concatenate((x, [x[0]]))
+    y = np.concatenate((y, [y[0]]))
+    line.set_data(x, y)
+
+[_closeline(l) for l in [l19, l18, l17, l16, l15, lmean]]
+
+
+ax.set_xticks(theta)
+ax.set_xticklabels(deaths_headlines_w.index)
+plt.legend()
+plt.title("Deaths by week over years, Wales")
+plt.savefig('deaths-radar-2020-wales.png')
+plt.show()
+```
+
+```python Collapsed="false"
+# Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#
+
+fig = plt.figure(figsize=(10, 10))
+ax = fig.add_subplot(111, projection="polar")
+
+theta = np.roll(
+    np.flip(
+        np.arange(len(deaths_headlines_s))/float(len(deaths_headlines_s))*2.*np.pi),
+    14)
+l15, = ax.plot(theta, deaths_headlines_s[2015], color="#e47d7d", label="2015") # 0
+l16, = ax.plot(theta, deaths_headlines_s[2016], color="#afc169", label="2016") # 72 , d0e47d
+l17, = ax.plot(theta, deaths_headlines_s[2017], color="#7de4a6", label="2017") # 144
+l18, = ax.plot(theta, deaths_headlines_s[2018], color="#7da6e4", label="2018") # 216
+l19, = ax.plot(theta, deaths_headlines_s[2019], color="#d07de4", label="2019") # 288
+
+lmean, = ax.plot(theta, deaths_headlines_s['previous_mean'], color="black", linestyle='dashed', label="mean")
+
+l20, = ax.plot(theta, deaths_headlines_s[2020], color="red", label="2020")
+
+
+def _closeline(line):
+    x, y = line.get_data()
+    x = np.concatenate((x, [x[0]]))
+    y = np.concatenate((y, [y[0]]))
+    line.set_data(x, y)
+
+[_closeline(l) for l in [l19, l18, l17, l16, l15, lmean]]
+
+
+ax.set_xticks(theta)
+ax.set_xticklabels(deaths_headlines_s.index)
+plt.legend()
+plt.title("Deaths by week over years, Scotland")
+plt.savefig('deaths-radar-2020-scotland.png')
+plt.show()
+```
+
+```python Collapsed="false"
+# Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#
+
+fig = plt.figure(figsize=(10, 10))
+ax = fig.add_subplot(111, projection="polar")
+
+theta = np.roll(
+    np.flip(
+        np.arange(len(deaths_headlines_i))/float(len(deaths_headlines_i))*2.*np.pi),
+    14)
+l15, = ax.plot(theta, deaths_headlines_i[2015], color="#e47d7d", label="2015") # 0
+l16, = ax.plot(theta, deaths_headlines_i[2016], color="#afc169", label="2016") # 72 , d0e47d
+l17, = ax.plot(theta, deaths_headlines_i[2017], color="#7de4a6", label="2017") # 144
+l18, = ax.plot(theta, deaths_headlines_i[2018], color="#7da6e4", label="2018") # 216
+l19, = ax.plot(theta, deaths_headlines_i[2019], color="#d07de4", label="2019") # 288
+
+lmean, = ax.plot(theta, deaths_headlines_i['previous_mean'], color="black", linestyle='dashed', label="mean")
+
+l20, = ax.plot(theta, deaths_headlines_i[2020], color="red", label="2020")
+
+
+def _closeline(line):
+    x, y = line.get_data()
+    x = np.concatenate((x, [x[0]]))
+    y = np.concatenate((y, [y[0]]))
+    line.set_data(x, y)
+
+[_closeline(l) for l in [l19, l18, l17, l16, l15, lmean]]
+
+
+ax.set_xticks(theta)
+ax.set_xticklabels(deaths_headlines_i.index)
+plt.legend()
+plt.title("Deaths by week over years, Northern Ireland")
+plt.savefig('deaths-radar-2020-northern-ireland.png')
+plt.show()
+```
+
+```python Collapsed="false"
+
+```
+
+```python Collapsed="false"
+
+```
diff --git a/hospital_data-Copy1.ipynb b/hospital_data-Copy1.ipynb

new file mode 100644 (file)

index 0000000..245d6ec
--- /dev/null
+++ b/hospital_data-Copy1.ipynb
@@ -0,0 +1,3975 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "import itertools\n",
+    "import collections\n",
+    "import json\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "from scipy.stats import gmean\n",
+    "import datetime\n",
+    "\n",
+    "import matplotlib as mpl\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline\n",
+    "%load_ext sql"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Connected: covid@covid'"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql $connection_string"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "normalisation_date = '2020-08-01' # '2020-05-15'\n",
+    "\n",
+    "hospital_normalisation_date = {\n",
+    "    'hospital_normalisation_date': normalisation_date\n",
+    "}\n",
+    "\n",
+    "with open('hospital_normalisation_date.json', 'w') as f:\n",
+    "    json.dump(hospital_normalisation_date, f)\n",
+    "    \n",
+    "hnd = pd.to_datetime(normalisation_date).strftime(\"%d %B %Y\")\n",
+    "with open('hospital_normalisation_date.js', 'w') as f:\n",
+    "    f.write(f\"document.write('{hnd}');\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "377 rows affected.\n",
+      "Returning data to local variable res\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%sql res << select uk_data.date, uk_data.new_admissions, uk_data_7.new_admissions as admissions7\n",
+    "    from uk_data join uk_data_7 using (date)\n",
+    "    order by uk_data.date"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date</th>\n",
+       "      <th>new_admissions</th>\n",
+       "      <th>admissions7</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>2020-01-03</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-01-04</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>2020-01-05</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>2020-01-06</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>2020-01-07</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>372</td>\n",
+       "      <td>2021-01-09</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4042.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>373</td>\n",
+       "      <td>2021-01-10</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4148.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>374</td>\n",
+       "      <td>2021-01-11</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4231.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>375</td>\n",
+       "      <td>2021-01-12</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4310.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>376</td>\n",
+       "      <td>2021-01-13</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4253.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>377 rows × 3 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           date  new_admissions  admissions7\n",
+       "0    2020-01-03             NaN          NaN\n",
+       "1    2020-01-04             NaN          NaN\n",
+       "2    2020-01-05             NaN          NaN\n",
+       "3    2020-01-06             NaN          NaN\n",
+       "4    2020-01-07             NaN          NaN\n",
+       "..          ...             ...          ...\n",
+       "372  2021-01-09             NaN       4042.8\n",
+       "373  2021-01-10             NaN       4148.0\n",
+       "374  2021-01-11             NaN       4231.0\n",
+       "375  2021-01-12             NaN       4310.0\n",
+       "376  2021-01-13             NaN       4253.0\n",
+       "\n",
+       "[377 rows x 3 columns]"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "hospital_data = res.DataFrame()\n",
+    "hospital_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 475,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>areaName</th>\n",
+       "      <th>areaType</th>\n",
+       "      <th>newAdmissions</th>\n",
+       "      <th>cumAdmissions</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>date</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>2020-03-23</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>1271</td>\n",
+       "      <td>4860</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-03-24</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>1719</td>\n",
+       "      <td>6579</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-03-25</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>2084</td>\n",
+       "      <td>8663</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-03-26</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>1929</td>\n",
+       "      <td>10592</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-03-27</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>2224</td>\n",
+       "      <td>12816</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-07</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>1626</td>\n",
+       "      <td>233132</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-08</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>1729</td>\n",
+       "      <td>234861</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-09</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>1705</td>\n",
+       "      <td>236566</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-10</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>1707</td>\n",
+       "      <td>238273</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-11</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>1637</td>\n",
+       "      <td>239910</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>264 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  areaName  areaType  newAdmissions  cumAdmissions\n",
+       "date                                                              \n",
+       "2020-03-23  United Kingdom  overview           1271           4860\n",
+       "2020-03-24  United Kingdom  overview           1719           6579\n",
+       "2020-03-25  United Kingdom  overview           2084           8663\n",
+       "2020-03-26  United Kingdom  overview           1929          10592\n",
+       "2020-03-27  United Kingdom  overview           2224          12816\n",
+       "...                    ...       ...            ...            ...\n",
+       "2020-12-07  United Kingdom  overview           1626         233132\n",
+       "2020-12-08  United Kingdom  overview           1729         234861\n",
+       "2020-12-09  United Kingdom  overview           1705         236566\n",
+       "2020-12-10  United Kingdom  overview           1707         238273\n",
+       "2020-12-11  United Kingdom  overview           1637         239910\n",
+       "\n",
+       "[264 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 475,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "hospital_data = raw_data.dropna().set_index('date').astype({'newAdmissions': np.int64, 'cumAdmissions': np.int64}).sort_index()\n",
+    "hospital_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 476,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f41899bac50>"
+      ]
+     },
+     "execution_count": 476,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "hospital_data.newAdmissions.plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 477,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# data_by_day.newAdmissions.dropna()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 478,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cases</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>cases_culm</th>\n",
+       "      <th>deaths_culm</th>\n",
+       "      <th>cases_diff</th>\n",
+       "      <th>deaths_diff</th>\n",
+       "      <th>cases_m7</th>\n",
+       "      <th>deaths_m7</th>\n",
+       "      <th>deaths_g4</th>\n",
+       "      <th>deaths_g7</th>\n",
+       "      <th>doubling_time</th>\n",
+       "      <th>doubling_time_7</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dateRep</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>2019-12-31</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-01</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-02</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-03</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-04</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-10</td>\n",
+       "      <td>16578</td>\n",
+       "      <td>533</td>\n",
+       "      <td>1766819</td>\n",
+       "      <td>62566</td>\n",
+       "      <td>4297.0</td>\n",
+       "      <td>-66.0</td>\n",
+       "      <td>15366.142857</td>\n",
+       "      <td>409.571429</td>\n",
+       "      <td>343.603005</td>\n",
+       "      <td>380.495816</td>\n",
+       "      <td>126.560073</td>\n",
+       "      <td>114.322369</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-11</td>\n",
+       "      <td>20964</td>\n",
+       "      <td>516</td>\n",
+       "      <td>1787783</td>\n",
+       "      <td>63082</td>\n",
+       "      <td>4386.0</td>\n",
+       "      <td>-17.0</td>\n",
+       "      <td>16235.571429</td>\n",
+       "      <td>424.142857</td>\n",
+       "      <td>420.064891</td>\n",
+       "      <td>392.657665</td>\n",
+       "      <td>104.437514</td>\n",
+       "      <td>111.703039</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-12</td>\n",
+       "      <td>21672</td>\n",
+       "      <td>424</td>\n",
+       "      <td>1809455</td>\n",
+       "      <td>63506</td>\n",
+       "      <td>708.0</td>\n",
+       "      <td>-92.0</td>\n",
+       "      <td>17003.285714</td>\n",
+       "      <td>412.714286</td>\n",
+       "      <td>514.093837</td>\n",
+       "      <td>383.080949</td>\n",
+       "      <td>85.970563</td>\n",
+       "      <td>115.254067</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-13</td>\n",
+       "      <td>21501</td>\n",
+       "      <td>520</td>\n",
+       "      <td>1830956</td>\n",
+       "      <td>64026</td>\n",
+       "      <td>-171.0</td>\n",
+       "      <td>96.0</td>\n",
+       "      <td>17855.000000</td>\n",
+       "      <td>430.285714</td>\n",
+       "      <td>496.234012</td>\n",
+       "      <td>398.139480</td>\n",
+       "      <td>89.778614</td>\n",
+       "      <td>111.813286</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-14</td>\n",
+       "      <td>18447</td>\n",
+       "      <td>144</td>\n",
+       "      <td>1849403</td>\n",
+       "      <td>64170</td>\n",
+       "      <td>-3054.0</td>\n",
+       "      <td>-376.0</td>\n",
+       "      <td>18023.000000</td>\n",
+       "      <td>417.857143</td>\n",
+       "      <td>357.762938</td>\n",
+       "      <td>372.146458</td>\n",
+       "      <td>124.672307</td>\n",
+       "      <td>119.867072</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>350 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff  \\\n",
+       "dateRep                                                                       \n",
+       "2019-12-31      0       0           0            0         NaN          NaN   \n",
+       "2020-01-01      0       0           0            0         0.0          0.0   \n",
+       "2020-01-02      0       0           0            0         0.0          0.0   \n",
+       "2020-01-03      0       0           0            0         0.0          0.0   \n",
+       "2020-01-04      0       0           0            0         0.0          0.0   \n",
+       "...           ...     ...         ...          ...         ...          ...   \n",
+       "2020-12-10  16578     533     1766819        62566      4297.0        -66.0   \n",
+       "2020-12-11  20964     516     1787783        63082      4386.0        -17.0   \n",
+       "2020-12-12  21672     424     1809455        63506       708.0        -92.0   \n",
+       "2020-12-13  21501     520     1830956        64026      -171.0         96.0   \n",
+       "2020-12-14  18447     144     1849403        64170     -3054.0       -376.0   \n",
+       "\n",
+       "                cases_m7   deaths_m7   deaths_g4   deaths_g7  doubling_time  \\\n",
+       "dateRep                                                                       \n",
+       "2019-12-31      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-01      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-02      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-03      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-04      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "...                  ...         ...         ...         ...            ...   \n",
+       "2020-12-10  15366.142857  409.571429  343.603005  380.495816     126.560073   \n",
+       "2020-12-11  16235.571429  424.142857  420.064891  392.657665     104.437514   \n",
+       "2020-12-12  17003.285714  412.714286  514.093837  383.080949      85.970563   \n",
+       "2020-12-13  17855.000000  430.285714  496.234012  398.139480      89.778614   \n",
+       "2020-12-14  18023.000000  417.857143  357.762938  372.146458     124.672307   \n",
+       "\n",
+       "            doubling_time_7  \n",
+       "dateRep                      \n",
+       "2019-12-31              NaN  \n",
+       "2020-01-01              NaN  \n",
+       "2020-01-02              NaN  \n",
+       "2020-01-03              NaN  \n",
+       "2020-01-04              NaN  \n",
+       "...                     ...  \n",
+       "2020-12-10       114.322369  \n",
+       "2020-12-11       111.703039  \n",
+       "2020-12-12       115.254067  \n",
+       "2020-12-13       111.813286  \n",
+       "2020-12-14       119.867072  \n",
+       "\n",
+       "[350 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 478,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_by_day = pd.read_csv('data_by_day_uk.csv', index_col='dateRep', parse_dates=True)\n",
+    "data_by_day"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 479,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cases</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>cases_culm</th>\n",
+       "      <th>deaths_culm</th>\n",
+       "      <th>cases_diff</th>\n",
+       "      <th>deaths_diff</th>\n",
+       "      <th>cases_m7</th>\n",
+       "      <th>deaths_m7</th>\n",
+       "      <th>deaths_g4</th>\n",
+       "      <th>deaths_g7</th>\n",
+       "      <th>doubling_time</th>\n",
+       "      <th>doubling_time_7</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dateRep</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>2019-12-31</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-01</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-02</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-03</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-04</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-10</td>\n",
+       "      <td>16578</td>\n",
+       "      <td>533</td>\n",
+       "      <td>1766819</td>\n",
+       "      <td>62566</td>\n",
+       "      <td>4297.0</td>\n",
+       "      <td>-66.0</td>\n",
+       "      <td>15366.142857</td>\n",
+       "      <td>409.571429</td>\n",
+       "      <td>343.603005</td>\n",
+       "      <td>380.495816</td>\n",
+       "      <td>126.560073</td>\n",
+       "      <td>114.322369</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-11</td>\n",
+       "      <td>20964</td>\n",
+       "      <td>516</td>\n",
+       "      <td>1787783</td>\n",
+       "      <td>63082</td>\n",
+       "      <td>4386.0</td>\n",
+       "      <td>-17.0</td>\n",
+       "      <td>16235.571429</td>\n",
+       "      <td>424.142857</td>\n",
+       "      <td>420.064891</td>\n",
+       "      <td>392.657665</td>\n",
+       "      <td>104.437514</td>\n",
+       "      <td>111.703039</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-12</td>\n",
+       "      <td>21672</td>\n",
+       "      <td>424</td>\n",
+       "      <td>1809455</td>\n",
+       "      <td>63506</td>\n",
+       "      <td>708.0</td>\n",
+       "      <td>-92.0</td>\n",
+       "      <td>17003.285714</td>\n",
+       "      <td>412.714286</td>\n",
+       "      <td>514.093837</td>\n",
+       "      <td>383.080949</td>\n",
+       "      <td>85.970563</td>\n",
+       "      <td>115.254067</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-13</td>\n",
+       "      <td>21501</td>\n",
+       "      <td>520</td>\n",
+       "      <td>1830956</td>\n",
+       "      <td>64026</td>\n",
+       "      <td>-171.0</td>\n",
+       "      <td>96.0</td>\n",
+       "      <td>17855.000000</td>\n",
+       "      <td>430.285714</td>\n",
+       "      <td>496.234012</td>\n",
+       "      <td>398.139480</td>\n",
+       "      <td>89.778614</td>\n",
+       "      <td>111.813286</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-14</td>\n",
+       "      <td>18447</td>\n",
+       "      <td>144</td>\n",
+       "      <td>1849403</td>\n",
+       "      <td>64170</td>\n",
+       "      <td>-3054.0</td>\n",
+       "      <td>-376.0</td>\n",
+       "      <td>18023.000000</td>\n",
+       "      <td>417.857143</td>\n",
+       "      <td>357.762938</td>\n",
+       "      <td>372.146458</td>\n",
+       "      <td>124.672307</td>\n",
+       "      <td>119.867072</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>350 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff  \\\n",
+       "dateRep                                                                       \n",
+       "2019-12-31      0       0           0            0         NaN          NaN   \n",
+       "2020-01-01      0       0           0            0         0.0          0.0   \n",
+       "2020-01-02      0       0           0            0         0.0          0.0   \n",
+       "2020-01-03      0       0           0            0         0.0          0.0   \n",
+       "2020-01-04      0       0           0            0         0.0          0.0   \n",
+       "...           ...     ...         ...          ...         ...          ...   \n",
+       "2020-12-10  16578     533     1766819        62566      4297.0        -66.0   \n",
+       "2020-12-11  20964     516     1787783        63082      4386.0        -17.0   \n",
+       "2020-12-12  21672     424     1809455        63506       708.0        -92.0   \n",
+       "2020-12-13  21501     520     1830956        64026      -171.0         96.0   \n",
+       "2020-12-14  18447     144     1849403        64170     -3054.0       -376.0   \n",
+       "\n",
+       "                cases_m7   deaths_m7   deaths_g4   deaths_g7  doubling_time  \\\n",
+       "dateRep                                                                       \n",
+       "2019-12-31      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-01      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-02      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-03      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-04      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "...                  ...         ...         ...         ...            ...   \n",
+       "2020-12-10  15366.142857  409.571429  343.603005  380.495816     126.560073   \n",
+       "2020-12-11  16235.571429  424.142857  420.064891  392.657665     104.437514   \n",
+       "2020-12-12  17003.285714  412.714286  514.093837  383.080949      85.970563   \n",
+       "2020-12-13  17855.000000  430.285714  496.234012  398.139480      89.778614   \n",
+       "2020-12-14  18023.000000  417.857143  357.762938  372.146458     124.672307   \n",
+       "\n",
+       "            doubling_time_7  \n",
+       "dateRep                      \n",
+       "2019-12-31              NaN  \n",
+       "2020-01-01              NaN  \n",
+       "2020-01-02              NaN  \n",
+       "2020-01-03              NaN  \n",
+       "2020-01-04              NaN  \n",
+       "...                     ...  \n",
+       "2020-12-10       114.322369  \n",
+       "2020-12-11       111.703039  \n",
+       "2020-12-12       115.254067  \n",
+       "2020-12-13       111.813286  \n",
+       "2020-12-14       119.867072  \n",
+       "\n",
+       "[350 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 479,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_by_day.loc['2020-07-03', 'cases'] = 576\n",
+    "data_by_day"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 480,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_day = data_by_day.merge(hospital_data[['newAdmissions', 'cumAdmissions']], how='outer',\n",
+    "    left_index=True, right_index=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 481,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_day['deaths_m7'] = data_by_day.deaths.transform(lambda x: x.rolling(7, 1).mean())\n",
+    "data_by_day['cases_m7'] = data_by_day.cases.transform(lambda x: x.rolling(7, 1).mean())\n",
+    "data_by_day['admissions_m7'] = data_by_day.newAdmissions.transform(lambda x: x.rolling(7).mean())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 482,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cases</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>cases_culm</th>\n",
+       "      <th>deaths_culm</th>\n",
+       "      <th>cases_diff</th>\n",
+       "      <th>deaths_diff</th>\n",
+       "      <th>cases_m7</th>\n",
+       "      <th>deaths_m7</th>\n",
+       "      <th>deaths_g4</th>\n",
+       "      <th>deaths_g7</th>\n",
+       "      <th>doubling_time</th>\n",
+       "      <th>doubling_time_7</th>\n",
+       "      <th>newAdmissions</th>\n",
+       "      <th>cumAdmissions</th>\n",
+       "      <th>admissions_m7</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>2019-12-31</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-01</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-02</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-03</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-04</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-10</td>\n",
+       "      <td>16578</td>\n",
+       "      <td>533</td>\n",
+       "      <td>1766819</td>\n",
+       "      <td>62566</td>\n",
+       "      <td>4297.0</td>\n",
+       "      <td>-66.0</td>\n",
+       "      <td>15366.142857</td>\n",
+       "      <td>409.571429</td>\n",
+       "      <td>343.603005</td>\n",
+       "      <td>380.495816</td>\n",
+       "      <td>126.560073</td>\n",
+       "      <td>114.322369</td>\n",
+       "      <td>1707.0</td>\n",
+       "      <td>238273.0</td>\n",
+       "      <td>1568.428571</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-11</td>\n",
+       "      <td>20964</td>\n",
+       "      <td>516</td>\n",
+       "      <td>1787783</td>\n",
+       "      <td>63082</td>\n",
+       "      <td>4386.0</td>\n",
+       "      <td>-17.0</td>\n",
+       "      <td>16235.571429</td>\n",
+       "      <td>424.142857</td>\n",
+       "      <td>420.064891</td>\n",
+       "      <td>392.657665</td>\n",
+       "      <td>104.437514</td>\n",
+       "      <td>111.703039</td>\n",
+       "      <td>1637.0</td>\n",
+       "      <td>239910.0</td>\n",
+       "      <td>1601.714286</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-12</td>\n",
+       "      <td>21672</td>\n",
+       "      <td>424</td>\n",
+       "      <td>1809455</td>\n",
+       "      <td>63506</td>\n",
+       "      <td>708.0</td>\n",
+       "      <td>-92.0</td>\n",
+       "      <td>17003.285714</td>\n",
+       "      <td>412.714286</td>\n",
+       "      <td>514.093837</td>\n",
+       "      <td>383.080949</td>\n",
+       "      <td>85.970563</td>\n",
+       "      <td>115.254067</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-13</td>\n",
+       "      <td>21501</td>\n",
+       "      <td>520</td>\n",
+       "      <td>1830956</td>\n",
+       "      <td>64026</td>\n",
+       "      <td>-171.0</td>\n",
+       "      <td>96.0</td>\n",
+       "      <td>17855.000000</td>\n",
+       "      <td>430.285714</td>\n",
+       "      <td>496.234012</td>\n",
+       "      <td>398.139480</td>\n",
+       "      <td>89.778614</td>\n",
+       "      <td>111.813286</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-14</td>\n",
+       "      <td>18447</td>\n",
+       "      <td>144</td>\n",
+       "      <td>1849403</td>\n",
+       "      <td>64170</td>\n",
+       "      <td>-3054.0</td>\n",
+       "      <td>-376.0</td>\n",
+       "      <td>18023.000000</td>\n",
+       "      <td>417.857143</td>\n",
+       "      <td>357.762938</td>\n",
+       "      <td>372.146458</td>\n",
+       "      <td>124.672307</td>\n",
+       "      <td>119.867072</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>350 rows × 15 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff  \\\n",
+       "2019-12-31      0       0           0            0         NaN          NaN   \n",
+       "2020-01-01      0       0           0            0         0.0          0.0   \n",
+       "2020-01-02      0       0           0            0         0.0          0.0   \n",
+       "2020-01-03      0       0           0            0         0.0          0.0   \n",
+       "2020-01-04      0       0           0            0         0.0          0.0   \n",
+       "...           ...     ...         ...          ...         ...          ...   \n",
+       "2020-12-10  16578     533     1766819        62566      4297.0        -66.0   \n",
+       "2020-12-11  20964     516     1787783        63082      4386.0        -17.0   \n",
+       "2020-12-12  21672     424     1809455        63506       708.0        -92.0   \n",
+       "2020-12-13  21501     520     1830956        64026      -171.0         96.0   \n",
+       "2020-12-14  18447     144     1849403        64170     -3054.0       -376.0   \n",
+       "\n",
+       "                cases_m7   deaths_m7   deaths_g4   deaths_g7  doubling_time  \\\n",
+       "2019-12-31      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-01      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-02      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-03      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-04      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "...                  ...         ...         ...         ...            ...   \n",
+       "2020-12-10  15366.142857  409.571429  343.603005  380.495816     126.560073   \n",
+       "2020-12-11  16235.571429  424.142857  420.064891  392.657665     104.437514   \n",
+       "2020-12-12  17003.285714  412.714286  514.093837  383.080949      85.970563   \n",
+       "2020-12-13  17855.000000  430.285714  496.234012  398.139480      89.778614   \n",
+       "2020-12-14  18023.000000  417.857143  357.762938  372.146458     124.672307   \n",
+       "\n",
+       "            doubling_time_7  newAdmissions  cumAdmissions  admissions_m7  \n",
+       "2019-12-31              NaN            NaN            NaN            NaN  \n",
+       "2020-01-01              NaN            NaN            NaN            NaN  \n",
+       "2020-01-02              NaN            NaN            NaN            NaN  \n",
+       "2020-01-03              NaN            NaN            NaN            NaN  \n",
+       "2020-01-04              NaN            NaN            NaN            NaN  \n",
+       "...                     ...            ...            ...            ...  \n",
+       "2020-12-10       114.322369         1707.0       238273.0    1568.428571  \n",
+       "2020-12-11       111.703039         1637.0       239910.0    1601.714286  \n",
+       "2020-12-12       115.254067            NaN            NaN            NaN  \n",
+       "2020-12-13       111.813286            NaN            NaN            NaN  \n",
+       "2020-12-14       119.867072            NaN            NaN            NaN  \n",
+       "\n",
+       "[350 rows x 15 columns]"
+      ]
+     },
+     "execution_count": 482,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_by_day"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 483,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "cases                 687.000000\n",
+       "deaths                 31.000000\n",
+       "cases_culm         277855.000000\n",
+       "deaths_culm         39878.000000\n",
+       "cases_diff           -299.000000\n",
+       "deaths_diff           -40.000000\n",
+       "cases_m7              954.285714\n",
+       "deaths_m7              73.142857\n",
+       "deaths_g4              59.325790\n",
+       "deaths_g7              64.691830\n",
+       "doubling_time         466.270719\n",
+       "doubling_time_7       427.623359\n",
+       "newAdmissions         393.000000\n",
+       "cumAdmissions      124711.000000\n",
+       "admissions_m7         366.000000\n",
+       "Name: 2020-06-22 00:00:00, dtype: float64"
+      ]
+     },
+     "execution_count": 483,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_by_day.loc['2020-06-22']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 484,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f41899ed7d0>"
+      ]
+     },
+     "execution_count": 484,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data_by_day[['cases_culm', 'cumAdmissions', 'deaths_culm']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 485,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f418c0c2250>"
+      ]
+     },
+     "execution_count": 485,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data_by_day.loc['2020-04-01':, ['cases_culm', 'cumAdmissions', 'deaths_culm']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 486,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f418b055e90>"
+      ]
+     },
+     "execution_count": 486,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data_by_day.loc['2020-03-01':'2020-07-02', ['cases', 'newAdmissions', 'deaths']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 487,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f4189834d90>"
+      ]
+     },
+     "execution_count": 487,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data_by_day.loc['2020-03-01':'2020-07-02', ['cases_m7', 'admissions_m7', 'deaths_m7']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 488,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_day['cases_m7n'] = data_by_day.cases_m7 / data_by_day.cases_m7.max()\n",
+    "data_by_day['deaths_m7n'] = data_by_day.deaths_m7 / data_by_day.deaths_m7.max()\n",
+    "data_by_day['admissions_m7n'] = data_by_day.admissions_m7 / data_by_day.admissions_m7.max()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 489,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_day['cases_m7nd'] = data_by_day.cases_m7 / data_by_day.cases_m7.loc[normalisation_date]\n",
+    "data_by_day['deaths_m7nd'] = data_by_day.deaths_m7 / data_by_day.deaths_m7.loc[normalisation_date]\n",
+    "data_by_day['admissions_m7nd'] = data_by_day.admissions_m7 / data_by_day.admissions_m7.loc[normalisation_date]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 490,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_day['cases_nd'] = data_by_day.cases / data_by_day.cases_m7.loc[normalisation_date]\n",
+    "data_by_day['deaths_nd'] = data_by_day.deaths / data_by_day.deaths_m7.loc[normalisation_date]\n",
+    "data_by_day['admissions_nd'] = data_by_day.newAdmissions / data_by_day.admissions_m7.loc[normalisation_date]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 491,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f4189772650>"
+      ]
+     },
+     "execution_count": 491,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data_by_day.loc['2020-03-01':'2020-07-02', ['cases_m7n', 'admissions_m7n', 'deaths_m7n']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 492,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cases</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>cases_culm</th>\n",
+       "      <th>deaths_culm</th>\n",
+       "      <th>cases_diff</th>\n",
+       "      <th>deaths_diff</th>\n",
+       "      <th>cases_m7</th>\n",
+       "      <th>deaths_m7</th>\n",
+       "      <th>deaths_g4</th>\n",
+       "      <th>deaths_g7</th>\n",
+       "      <th>...</th>\n",
+       "      <th>admissions_m7</th>\n",
+       "      <th>cases_m7n</th>\n",
+       "      <th>deaths_m7n</th>\n",
+       "      <th>admissions_m7n</th>\n",
+       "      <th>cases_m7nd</th>\n",
+       "      <th>deaths_m7nd</th>\n",
+       "      <th>admissions_m7nd</th>\n",
+       "      <th>cases_nd</th>\n",
+       "      <th>deaths_nd</th>\n",
+       "      <th>admissions_nd</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>2019-12-31</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-01</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-02</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-03</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-04</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-10</td>\n",
+       "      <td>16578</td>\n",
+       "      <td>533</td>\n",
+       "      <td>1766819</td>\n",
+       "      <td>62566</td>\n",
+       "      <td>4297.0</td>\n",
+       "      <td>-66.0</td>\n",
+       "      <td>15366.142857</td>\n",
+       "      <td>409.571429</td>\n",
+       "      <td>343.603005</td>\n",
+       "      <td>380.495816</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1568.428571</td>\n",
+       "      <td>0.606611</td>\n",
+       "      <td>0.434591</td>\n",
+       "      <td>0.503370</td>\n",
+       "      <td>26.770284</td>\n",
+       "      <td>28.386139</td>\n",
+       "      <td>12.796037</td>\n",
+       "      <td>28.881533</td>\n",
+       "      <td>36.940594</td>\n",
+       "      <td>13.926573</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-11</td>\n",
+       "      <td>20964</td>\n",
+       "      <td>516</td>\n",
+       "      <td>1787783</td>\n",
+       "      <td>63082</td>\n",
+       "      <td>4386.0</td>\n",
+       "      <td>-17.0</td>\n",
+       "      <td>16235.571429</td>\n",
+       "      <td>424.142857</td>\n",
+       "      <td>420.064891</td>\n",
+       "      <td>392.657665</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1601.714286</td>\n",
+       "      <td>0.640933</td>\n",
+       "      <td>0.450053</td>\n",
+       "      <td>0.514053</td>\n",
+       "      <td>28.284968</td>\n",
+       "      <td>29.396040</td>\n",
+       "      <td>13.067599</td>\n",
+       "      <td>36.522648</td>\n",
+       "      <td>35.762376</td>\n",
+       "      <td>13.355478</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-12</td>\n",
+       "      <td>21672</td>\n",
+       "      <td>424</td>\n",
+       "      <td>1809455</td>\n",
+       "      <td>63506</td>\n",
+       "      <td>708.0</td>\n",
+       "      <td>-92.0</td>\n",
+       "      <td>17003.285714</td>\n",
+       "      <td>412.714286</td>\n",
+       "      <td>514.093837</td>\n",
+       "      <td>383.080949</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.671240</td>\n",
+       "      <td>0.437926</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>29.622449</td>\n",
+       "      <td>28.603960</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>37.756098</td>\n",
+       "      <td>29.386139</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-13</td>\n",
+       "      <td>21501</td>\n",
+       "      <td>520</td>\n",
+       "      <td>1830956</td>\n",
+       "      <td>64026</td>\n",
+       "      <td>-171.0</td>\n",
+       "      <td>96.0</td>\n",
+       "      <td>17855.000000</td>\n",
+       "      <td>430.285714</td>\n",
+       "      <td>496.234012</td>\n",
+       "      <td>398.139480</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.704864</td>\n",
+       "      <td>0.456571</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>31.106272</td>\n",
+       "      <td>29.821782</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>37.458188</td>\n",
+       "      <td>36.039604</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-14</td>\n",
+       "      <td>18447</td>\n",
+       "      <td>144</td>\n",
+       "      <td>1849403</td>\n",
+       "      <td>64170</td>\n",
+       "      <td>-3054.0</td>\n",
+       "      <td>-376.0</td>\n",
+       "      <td>18023.000000</td>\n",
+       "      <td>417.857143</td>\n",
+       "      <td>357.762938</td>\n",
+       "      <td>372.146458</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.711496</td>\n",
+       "      <td>0.443383</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>31.398955</td>\n",
+       "      <td>28.960396</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>32.137631</td>\n",
+       "      <td>9.980198</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>350 rows × 24 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff  \\\n",
+       "2019-12-31      0       0           0            0         NaN          NaN   \n",
+       "2020-01-01      0       0           0            0         0.0          0.0   \n",
+       "2020-01-02      0       0           0            0         0.0          0.0   \n",
+       "2020-01-03      0       0           0            0         0.0          0.0   \n",
+       "2020-01-04      0       0           0            0         0.0          0.0   \n",
+       "...           ...     ...         ...          ...         ...          ...   \n",
+       "2020-12-10  16578     533     1766819        62566      4297.0        -66.0   \n",
+       "2020-12-11  20964     516     1787783        63082      4386.0        -17.0   \n",
+       "2020-12-12  21672     424     1809455        63506       708.0        -92.0   \n",
+       "2020-12-13  21501     520     1830956        64026      -171.0         96.0   \n",
+       "2020-12-14  18447     144     1849403        64170     -3054.0       -376.0   \n",
+       "\n",
+       "                cases_m7   deaths_m7   deaths_g4   deaths_g7  ...  \\\n",
+       "2019-12-31      0.000000    0.000000    0.000000    0.000000  ...   \n",
+       "2020-01-01      0.000000    0.000000    0.000000    0.000000  ...   \n",
+       "2020-01-02      0.000000    0.000000    0.000000    0.000000  ...   \n",
+       "2020-01-03      0.000000    0.000000    0.000000    0.000000  ...   \n",
+       "2020-01-04      0.000000    0.000000    0.000000    0.000000  ...   \n",
+       "...                  ...         ...         ...         ...  ...   \n",
+       "2020-12-10  15366.142857  409.571429  343.603005  380.495816  ...   \n",
+       "2020-12-11  16235.571429  424.142857  420.064891  392.657665  ...   \n",
+       "2020-12-12  17003.285714  412.714286  514.093837  383.080949  ...   \n",
+       "2020-12-13  17855.000000  430.285714  496.234012  398.139480  ...   \n",
+       "2020-12-14  18023.000000  417.857143  357.762938  372.146458  ...   \n",
+       "\n",
+       "            admissions_m7  cases_m7n  deaths_m7n  admissions_m7n  cases_m7nd  \\\n",
+       "2019-12-31            NaN   0.000000    0.000000             NaN    0.000000   \n",
+       "2020-01-01            NaN   0.000000    0.000000             NaN    0.000000   \n",
+       "2020-01-02            NaN   0.000000    0.000000             NaN    0.000000   \n",
+       "2020-01-03            NaN   0.000000    0.000000             NaN    0.000000   \n",
+       "2020-01-04            NaN   0.000000    0.000000             NaN    0.000000   \n",
+       "...                   ...        ...         ...             ...         ...   \n",
+       "2020-12-10    1568.428571   0.606611    0.434591        0.503370   26.770284   \n",
+       "2020-12-11    1601.714286   0.640933    0.450053        0.514053   28.284968   \n",
+       "2020-12-12            NaN   0.671240    0.437926             NaN   29.622449   \n",
+       "2020-12-13            NaN   0.704864    0.456571             NaN   31.106272   \n",
+       "2020-12-14            NaN   0.711496    0.443383             NaN   31.398955   \n",
+       "\n",
+       "            deaths_m7nd  admissions_m7nd   cases_nd  deaths_nd  admissions_nd  \n",
+       "2019-12-31     0.000000              NaN   0.000000   0.000000            NaN  \n",
+       "2020-01-01     0.000000              NaN   0.000000   0.000000            NaN  \n",
+       "2020-01-02     0.000000              NaN   0.000000   0.000000            NaN  \n",
+       "2020-01-03     0.000000              NaN   0.000000   0.000000            NaN  \n",
+       "2020-01-04     0.000000              NaN   0.000000   0.000000            NaN  \n",
+       "...                 ...              ...        ...        ...            ...  \n",
+       "2020-12-10    28.386139        12.796037  28.881533  36.940594      13.926573  \n",
+       "2020-12-11    29.396040        13.067599  36.522648  35.762376      13.355478  \n",
+       "2020-12-12    28.603960              NaN  37.756098  29.386139            NaN  \n",
+       "2020-12-13    29.821782              NaN  37.458188  36.039604            NaN  \n",
+       "2020-12-14    28.960396              NaN  32.137631   9.980198            NaN  \n",
+       "\n",
+       "[350 rows x 24 columns]"
+      ]
+     },
+     "execution_count": 492,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_by_day"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 493,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f41898eded0>"
+      ]
+     },
+     "execution_count": 493,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data_by_day.loc['2020-10-01':, ['cases_m7n', 'admissions_m7n', 'deaths_m7n']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 494,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cases</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>cases_culm</th>\n",
+       "      <th>deaths_culm</th>\n",
+       "      <th>cases_diff</th>\n",
+       "      <th>deaths_diff</th>\n",
+       "      <th>cases_m7</th>\n",
+       "      <th>deaths_m7</th>\n",
+       "      <th>deaths_g4</th>\n",
+       "      <th>deaths_g7</th>\n",
+       "      <th>...</th>\n",
+       "      <th>admissions_m7</th>\n",
+       "      <th>cases_m7n</th>\n",
+       "      <th>deaths_m7n</th>\n",
+       "      <th>admissions_m7n</th>\n",
+       "      <th>cases_m7nd</th>\n",
+       "      <th>deaths_m7nd</th>\n",
+       "      <th>admissions_m7nd</th>\n",
+       "      <th>cases_nd</th>\n",
+       "      <th>deaths_nd</th>\n",
+       "      <th>admissions_nd</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>2019-12-31</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-01</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-02</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-03</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-04</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-10</td>\n",
+       "      <td>16578</td>\n",
+       "      <td>533</td>\n",
+       "      <td>1766819</td>\n",
+       "      <td>62566</td>\n",
+       "      <td>4297.0</td>\n",
+       "      <td>-66.0</td>\n",
+       "      <td>15366.142857</td>\n",
+       "      <td>409.571429</td>\n",
+       "      <td>343.603005</td>\n",
+       "      <td>380.495816</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1568.428571</td>\n",
+       "      <td>0.606611</td>\n",
+       "      <td>0.434591</td>\n",
+       "      <td>0.503370</td>\n",
+       "      <td>26.770284</td>\n",
+       "      <td>28.386139</td>\n",
+       "      <td>12.796037</td>\n",
+       "      <td>28.881533</td>\n",
+       "      <td>36.940594</td>\n",
+       "      <td>13.926573</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-11</td>\n",
+       "      <td>20964</td>\n",
+       "      <td>516</td>\n",
+       "      <td>1787783</td>\n",
+       "      <td>63082</td>\n",
+       "      <td>4386.0</td>\n",
+       "      <td>-17.0</td>\n",
+       "      <td>16235.571429</td>\n",
+       "      <td>424.142857</td>\n",
+       "      <td>420.064891</td>\n",
+       "      <td>392.657665</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1601.714286</td>\n",
+       "      <td>0.640933</td>\n",
+       "      <td>0.450053</td>\n",
+       "      <td>0.514053</td>\n",
+       "      <td>28.284968</td>\n",
+       "      <td>29.396040</td>\n",
+       "      <td>13.067599</td>\n",
+       "      <td>36.522648</td>\n",
+       "      <td>35.762376</td>\n",
+       "      <td>13.355478</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-12</td>\n",
+       "      <td>21672</td>\n",
+       "      <td>424</td>\n",
+       "      <td>1809455</td>\n",
+       "      <td>63506</td>\n",
+       "      <td>708.0</td>\n",
+       "      <td>-92.0</td>\n",
+       "      <td>17003.285714</td>\n",
+       "      <td>412.714286</td>\n",
+       "      <td>514.093837</td>\n",
+       "      <td>383.080949</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.671240</td>\n",
+       "      <td>0.437926</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>29.622449</td>\n",
+       "      <td>28.603960</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>37.756098</td>\n",
+       "      <td>29.386139</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-13</td>\n",
+       "      <td>21501</td>\n",
+       "      <td>520</td>\n",
+       "      <td>1830956</td>\n",
+       "      <td>64026</td>\n",
+       "      <td>-171.0</td>\n",
+       "      <td>96.0</td>\n",
+       "      <td>17855.000000</td>\n",
+       "      <td>430.285714</td>\n",
+       "      <td>496.234012</td>\n",
+       "      <td>398.139480</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.704864</td>\n",
+       "      <td>0.456571</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>31.106272</td>\n",
+       "      <td>29.821782</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>37.458188</td>\n",
+       "      <td>36.039604</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-14</td>\n",
+       "      <td>18447</td>\n",
+       "      <td>144</td>\n",
+       "      <td>1849403</td>\n",
+       "      <td>64170</td>\n",
+       "      <td>-3054.0</td>\n",
+       "      <td>-376.0</td>\n",
+       "      <td>18023.000000</td>\n",
+       "      <td>417.857143</td>\n",
+       "      <td>357.762938</td>\n",
+       "      <td>372.146458</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.711496</td>\n",
+       "      <td>0.443383</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>31.398955</td>\n",
+       "      <td>28.960396</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>32.137631</td>\n",
+       "      <td>9.980198</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>350 rows × 24 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff  \\\n",
+       "2019-12-31      0       0           0            0         NaN          NaN   \n",
+       "2020-01-01      0       0           0            0         0.0          0.0   \n",
+       "2020-01-02      0       0           0            0         0.0          0.0   \n",
+       "2020-01-03      0       0           0            0         0.0          0.0   \n",
+       "2020-01-04      0       0           0            0         0.0          0.0   \n",
+       "...           ...     ...         ...          ...         ...          ...   \n",
+       "2020-12-10  16578     533     1766819        62566      4297.0        -66.0   \n",
+       "2020-12-11  20964     516     1787783        63082      4386.0        -17.0   \n",
+       "2020-12-12  21672     424     1809455        63506       708.0        -92.0   \n",
+       "2020-12-13  21501     520     1830956        64026      -171.0         96.0   \n",
+       "2020-12-14  18447     144     1849403        64170     -3054.0       -376.0   \n",
+       "\n",
+       "                cases_m7   deaths_m7   deaths_g4   deaths_g7  ...  \\\n",
+       "2019-12-31      0.000000    0.000000    0.000000    0.000000  ...   \n",
+       "2020-01-01      0.000000    0.000000    0.000000    0.000000  ...   \n",
+       "2020-01-02      0.000000    0.000000    0.000000    0.000000  ...   \n",
+       "2020-01-03      0.000000    0.000000    0.000000    0.000000  ...   \n",
+       "2020-01-04      0.000000    0.000000    0.000000    0.000000  ...   \n",
+       "...                  ...         ...         ...         ...  ...   \n",
+       "2020-12-10  15366.142857  409.571429  343.603005  380.495816  ...   \n",
+       "2020-12-11  16235.571429  424.142857  420.064891  392.657665  ...   \n",
+       "2020-12-12  17003.285714  412.714286  514.093837  383.080949  ...   \n",
+       "2020-12-13  17855.000000  430.285714  496.234012  398.139480  ...   \n",
+       "2020-12-14  18023.000000  417.857143  357.762938  372.146458  ...   \n",
+       "\n",
+       "            admissions_m7  cases_m7n  deaths_m7n  admissions_m7n  cases_m7nd  \\\n",
+       "2019-12-31            NaN   0.000000    0.000000             NaN    0.000000   \n",
+       "2020-01-01            NaN   0.000000    0.000000             NaN    0.000000   \n",
+       "2020-01-02            NaN   0.000000    0.000000             NaN    0.000000   \n",
+       "2020-01-03            NaN   0.000000    0.000000             NaN    0.000000   \n",
+       "2020-01-04            NaN   0.000000    0.000000             NaN    0.000000   \n",
+       "...                   ...        ...         ...             ...         ...   \n",
+       "2020-12-10    1568.428571   0.606611    0.434591        0.503370   26.770284   \n",
+       "2020-12-11    1601.714286   0.640933    0.450053        0.514053   28.284968   \n",
+       "2020-12-12            NaN   0.671240    0.437926             NaN   29.622449   \n",
+       "2020-12-13            NaN   0.704864    0.456571             NaN   31.106272   \n",
+       "2020-12-14            NaN   0.711496    0.443383             NaN   31.398955   \n",
+       "\n",
+       "            deaths_m7nd  admissions_m7nd   cases_nd  deaths_nd  admissions_nd  \n",
+       "2019-12-31     0.000000              NaN   0.000000   0.000000            NaN  \n",
+       "2020-01-01     0.000000              NaN   0.000000   0.000000            NaN  \n",
+       "2020-01-02     0.000000              NaN   0.000000   0.000000            NaN  \n",
+       "2020-01-03     0.000000              NaN   0.000000   0.000000            NaN  \n",
+       "2020-01-04     0.000000              NaN   0.000000   0.000000            NaN  \n",
+       "...                 ...              ...        ...        ...            ...  \n",
+       "2020-12-10    28.386139        12.796037  28.881533  36.940594      13.926573  \n",
+       "2020-12-11    29.396040        13.067599  36.522648  35.762376      13.355478  \n",
+       "2020-12-12    28.603960              NaN  37.756098  29.386139            NaN  \n",
+       "2020-12-13    29.821782              NaN  37.458188  36.039604            NaN  \n",
+       "2020-12-14    28.960396              NaN  32.137631   9.980198            NaN  \n",
+       "\n",
+       "[350 rows x 24 columns]"
+      ]
+     },
+     "execution_count": 494,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_by_day"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 495,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cases</th>\n",
+       "      <th>cases_culm</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>deaths_culm</th>\n",
+       "      <th>newAdmissions</th>\n",
+       "      <th>cumAdmissions</th>\n",
+       "      <th>deaths_m7</th>\n",
+       "      <th>cases_m7</th>\n",
+       "      <th>admissions_m7</th>\n",
+       "      <th>cases_m7n</th>\n",
+       "      <th>deaths_m7n</th>\n",
+       "      <th>admissions_m7n</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>2019-12-31</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-01</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-02</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-03</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-04</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-10</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>533</td>\n",
+       "      <td>62566</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>409.571429</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>28.386139</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-11</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>516</td>\n",
+       "      <td>63082</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>424.142857</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>29.396040</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-12</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>424</td>\n",
+       "      <td>63506</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>412.714286</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>28.603960</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-13</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>520</td>\n",
+       "      <td>64026</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>430.285714</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>29.821782</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-14</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>144</td>\n",
+       "      <td>64170</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>417.857143</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>28.960396</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>350 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            cases  cases_culm  deaths  deaths_culm  newAdmissions  \\\n",
+       "2019-12-31    0.0         0.0       0            0            NaN   \n",
+       "2020-01-01    0.0         0.0       0            0            NaN   \n",
+       "2020-01-02    0.0         0.0       0            0            NaN   \n",
+       "2020-01-03    0.0         0.0       0            0            NaN   \n",
+       "2020-01-04    0.0         0.0       0            0            NaN   \n",
+       "...           ...         ...     ...          ...            ...   \n",
+       "2020-12-10    NaN         NaN     533        62566            NaN   \n",
+       "2020-12-11    NaN         NaN     516        63082            NaN   \n",
+       "2020-12-12    NaN         NaN     424        63506            NaN   \n",
+       "2020-12-13    NaN         NaN     520        64026            NaN   \n",
+       "2020-12-14    NaN         NaN     144        64170            NaN   \n",
+       "\n",
+       "            cumAdmissions   deaths_m7  cases_m7  admissions_m7  cases_m7n  \\\n",
+       "2019-12-31            NaN         NaN       NaN            NaN        NaN   \n",
+       "2020-01-01            NaN         NaN       NaN            NaN        NaN   \n",
+       "2020-01-02            NaN         NaN       NaN            NaN        NaN   \n",
+       "2020-01-03            NaN         NaN       NaN            NaN        NaN   \n",
+       "2020-01-04            NaN         NaN       NaN            NaN        NaN   \n",
+       "...                   ...         ...       ...            ...        ...   \n",
+       "2020-12-10            NaN  409.571429       NaN            NaN        NaN   \n",
+       "2020-12-11            NaN  424.142857       NaN            NaN        NaN   \n",
+       "2020-12-12            NaN  412.714286       NaN            NaN        NaN   \n",
+       "2020-12-13            NaN  430.285714       NaN            NaN        NaN   \n",
+       "2020-12-14            NaN  417.857143       NaN            NaN        NaN   \n",
+       "\n",
+       "            deaths_m7n  admissions_m7n  \n",
+       "2019-12-31         NaN             NaN  \n",
+       "2020-01-01         NaN             NaN  \n",
+       "2020-01-02         NaN             NaN  \n",
+       "2020-01-03         NaN             NaN  \n",
+       "2020-01-04         NaN             NaN  \n",
+       "...                ...             ...  \n",
+       "2020-12-10   28.386139             NaN  \n",
+       "2020-12-11   29.396040             NaN  \n",
+       "2020-12-12   28.603960             NaN  \n",
+       "2020-12-13   29.821782             NaN  \n",
+       "2020-12-14   28.960396             NaN  \n",
+       "\n",
+       "[350 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 495,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dbds = pd.read_csv('data_by_day_uk.csv', index_col='dateRep', parse_dates=True)\n",
+    "# dbds.loc['2020-07-03', 'cases'] = 576\n",
+    "\n",
+    "dbds = dbds[['cases', 'cases_culm']].shift(-25).merge(dbds[['deaths', 'deaths_culm']], left_index=True, right_index=True, how='outer')\n",
+    "dbds = dbds.merge(hospital_data[['newAdmissions', 'cumAdmissions']].shift(-14), how='outer',\n",
+    "    left_index=True, right_index=True)\n",
+    "\n",
+    "dbds['deaths_m7'] = dbds.deaths.transform(lambda x: x.rolling(7).mean())\n",
+    "dbds['cases_m7'] = dbds.cases.transform(lambda x: x.rolling(7).mean())\n",
+    "dbds['admissions_m7'] = dbds.newAdmissions.transform(lambda x: x.rolling(7).mean())\n",
+    "\n",
+    "dbds['cases_m7n'] = dbds.cases_m7 / dbds.cases_m7.loc[normalisation_date]\n",
+    "dbds['deaths_m7n'] = dbds.deaths_m7 / dbds.deaths_m7.loc[normalisation_date]\n",
+    "dbds['admissions_m7n'] = dbds.admissions_m7 / dbds.admissions_m7.loc[normalisation_date]\n",
+    "\n",
+    "dbds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 496,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f418958dd50>"
+      ]
+     },
+     "execution_count": 496,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "dbds.loc['2020-03-01':, ['cases_m7n', 'admissions_m7n', 'deaths_m7n']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 497,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Timestamp('2020-12-14 00:00:00')"
+      ]
+     },
+     "execution_count": 497,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dbds.last_valid_index()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 498,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "34.6"
+      ]
+     },
+     "execution_count": 498,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(int(dbds.loc[normalisation_date:, ['cases_m7n', 'admissions_m7n', 'deaths_m7n']].max().max() * 10) + 1) / 10.0"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 499,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7f41893f0890>"
+      ]
+     },
+     "execution_count": 499,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 720x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ymax = (int(dbds.loc[normalisation_date:, ['cases_m7n', 'admissions_m7n', 'deaths_m7n']].max().max() * 10) + 1) / 10.0\n",
+    "ax = dbds.loc[normalisation_date:, ['cases_m7n', 'admissions_m7n', 'deaths_m7n']].plot(ylim=(0, ymax), \n",
+    "#                                                                                  xlim=('2020-05-15', dbds.last_valid_index()), \n",
+    "                                                                                 figsize=(10, 8),\n",
+    "                                                                                 title=\"Cases, hospital admissions, and deaths\\n(7-day moving averages, time-shifted data)\")\n",
+    "\n",
+    "lvi = dbds.cases_m7n.last_valid_index()\n",
+    "ax.text(x = lvi + pd.Timedelta(days=1), y = dbds.cases_m7n[lvi], s = f'{dbds.cases_m7n[lvi]:.2f}')\n",
+    "\n",
+    "lvi = dbds.admissions_m7n.last_valid_index()\n",
+    "ax.text(x = lvi + pd.Timedelta(days=1), y = dbds.admissions_m7n[lvi], s = f'{dbds.admissions_m7n[lvi]:.2f}')\n",
+    "\n",
+    "lvi = dbds.deaths_m7n.last_valid_index()\n",
+    "ax.text(x = lvi + pd.Timedelta(days=1), y = dbds.deaths_m7n[lvi], s = f'{dbds.deaths_m7n[lvi]:.2f}')\n",
+    "\n",
+    "\n",
+    "ax.set_xlabel(\"Date\")\n",
+    "ax.set_ylabel(f'Normalised units, scaled from {normalisation_date}')\n",
+    "ax.legend(['Cases', 'Admissions', 'Deaths'])\n",
+    "# for c in COUNTRIES_FRIENDS:\n",
+    "#     lvi = cases_m7[c].last_valid_index()\n",
+    "#     ax.text(x = lvi + 1, y = cases_m7[c][lvi], s = f\"{c}: {cases_m7[c][lvi]:.0f}\")\n",
+    "\n",
+    "# plt.savefig('cases_admissions_deaths.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 500,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['#1f77b4', '#ff7f0e', '#2ca02c']"
+      ]
+     },
+     "execution_count": 500,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "[l.get_color() for l in ax.lines]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 501,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 720x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ymax = (int(data_by_day.loc[normalisation_date:, ['cases_m7nd', 'admissions_m7nd', 'deaths_m7nd']].max().max() * 10) + 1) / 10.0\n",
+    "# ymax = (int(data_by_day.loc[normalisation_date:, ['cases_m7nd', 'admissions_m7nd', 'deaths_m7nd',\n",
+    "#                                                  'cases_nd', 'admissions_nd', 'deaths_nd']].max().max() * 10) + 1) / 10.0\n",
+    "ax = data_by_day.loc[normalisation_date:, ['cases_m7nd', 'admissions_m7nd', 'deaths_m7nd']].plot(\n",
+    "# ax = data_by_day.loc[normalisation_date:, ['cases_m7nd', 'admissions_m7nd', 'deaths_m7nd',\n",
+    "#                                           'cases_nd', 'admissions_nd', 'deaths_nd']].plot(\n",
+    "    ylim=(0, ymax), \n",
+    "#     xlim=('2020-05-15', dbds.last_valid_index()), \n",
+    "#     style={'cases_nd': '#1f77b4', 'admissions_nd': '#ff7f0e', 'deaths_nd': '#2ca02c'},\n",
+    "#     style={'cases_nd': ':', 'admissions_nd': ':', 'deaths_nd': ':'},\n",
+    "    figsize=(10, 8),\n",
+    "    title=\"Cases, hospital admissions, and deaths\\n(7-day moving averages)\")\n",
+    "\n",
+    "lvi = data_by_day.cases_m7nd.last_valid_index()\n",
+    "ax.text(x = lvi + pd.Timedelta(days=1), y = data_by_day.cases_m7nd[lvi], s = f'{data_by_day.cases_m7nd[lvi]:.2f}')\n",
+    "\n",
+    "lvi = data_by_day.admissions_m7nd.last_valid_index()\n",
+    "ax.text(x = lvi + pd.Timedelta(days=1), y = data_by_day.admissions_m7nd[lvi], s = f'{data_by_day.admissions_m7nd[lvi]:.2f}')\n",
+    "\n",
+    "lvi = data_by_day.deaths_m7nd.last_valid_index()\n",
+    "ax.text(x = lvi + pd.Timedelta(days=1), y = data_by_day.deaths_m7nd[lvi], s = f'{data_by_day.deaths_m7nd[lvi]:.2f}')\n",
+    "\n",
+    "\n",
+    "ax.set_xlabel(\"Date\")\n",
+    "ax.set_ylabel(f'Normalised units, scaled from {normalisation_date}')\n",
+    "ax.legend(['Cases', 'Admissions', 'Deaths'])\n",
+    "# for c in COUNTRIES_FRIENDS:\n",
+    "#     lvi = cases_m7[c].last_valid_index()\n",
+    "#     ax.text(x = lvi + 1, y = cases_m7[c][lvi], s = f\"{c}: {cases_m7[c][lvi]:.0f}\")\n",
+    "\n",
+    "plt.savefig('cases_admissions_deaths.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 502,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cases</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>cases_culm</th>\n",
+       "      <th>deaths_culm</th>\n",
+       "      <th>cases_diff</th>\n",
+       "      <th>deaths_diff</th>\n",
+       "      <th>cases_m7</th>\n",
+       "      <th>deaths_m7</th>\n",
+       "      <th>deaths_g4</th>\n",
+       "      <th>deaths_g7</th>\n",
+       "      <th>...</th>\n",
+       "      <th>admissions_m7</th>\n",
+       "      <th>cases_m7n</th>\n",
+       "      <th>deaths_m7n</th>\n",
+       "      <th>admissions_m7n</th>\n",
+       "      <th>cases_m7nd</th>\n",
+       "      <th>deaths_m7nd</th>\n",
+       "      <th>admissions_m7nd</th>\n",
+       "      <th>cases_nd</th>\n",
+       "      <th>deaths_nd</th>\n",
+       "      <th>admissions_nd</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>2019-12-31</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-01</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-02</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-03</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-04</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-10</td>\n",
+       "      <td>16578</td>\n",
+       "      <td>533</td>\n",
+       "      <td>1766819</td>\n",
+       "      <td>62566</td>\n",
+       "      <td>4297.0</td>\n",
+       "      <td>-66.0</td>\n",
+       "      <td>15366.142857</td>\n",
+       "      <td>409.571429</td>\n",
+       "      <td>343.603005</td>\n",
+       "      <td>380.495816</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1568.428571</td>\n",
+       "      <td>0.606611</td>\n",
+       "      <td>0.434591</td>\n",
+       "      <td>0.503370</td>\n",
+       "      <td>26.770284</td>\n",
+       "      <td>28.386139</td>\n",
+       "      <td>12.796037</td>\n",
+       "      <td>28.881533</td>\n",
+       "      <td>36.940594</td>\n",
+       "      <td>13.926573</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-11</td>\n",
+       "      <td>20964</td>\n",
+       "      <td>516</td>\n",
+       "      <td>1787783</td>\n",
+       "      <td>63082</td>\n",
+       "      <td>4386.0</td>\n",
+       "      <td>-17.0</td>\n",
+       "      <td>16235.571429</td>\n",
+       "      <td>424.142857</td>\n",
+       "      <td>420.064891</td>\n",
+       "      <td>392.657665</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1601.714286</td>\n",
+       "      <td>0.640933</td>\n",
+       "      <td>0.450053</td>\n",
+       "      <td>0.514053</td>\n",
+       "      <td>28.284968</td>\n",
+       "      <td>29.396040</td>\n",
+       "      <td>13.067599</td>\n",
+       "      <td>36.522648</td>\n",
+       "      <td>35.762376</td>\n",
+       "      <td>13.355478</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-12</td>\n",
+       "      <td>21672</td>\n",
+       "      <td>424</td>\n",
+       "      <td>1809455</td>\n",
+       "      <td>63506</td>\n",
+       "      <td>708.0</td>\n",
+       "      <td>-92.0</td>\n",
+       "      <td>17003.285714</td>\n",
+       "      <td>412.714286</td>\n",
+       "      <td>514.093837</td>\n",
+       "      <td>383.080949</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.671240</td>\n",
+       "      <td>0.437926</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>29.622449</td>\n",
+       "      <td>28.603960</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>37.756098</td>\n",
+       "      <td>29.386139</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-13</td>\n",
+       "      <td>21501</td>\n",
+       "      <td>520</td>\n",
+       "      <td>1830956</td>\n",
+       "      <td>64026</td>\n",
+       "      <td>-171.0</td>\n",
+       "      <td>96.0</td>\n",
+       "      <td>17855.000000</td>\n",
+       "      <td>430.285714</td>\n",
+       "      <td>496.234012</td>\n",
+       "      <td>398.139480</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.704864</td>\n",
+       "      <td>0.456571</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>31.106272</td>\n",
+       "      <td>29.821782</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>37.458188</td>\n",
+       "      <td>36.039604</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-14</td>\n",
+       "      <td>18447</td>\n",
+       "      <td>144</td>\n",
+       "      <td>1849403</td>\n",
+       "      <td>64170</td>\n",
+       "      <td>-3054.0</td>\n",
+       "      <td>-376.0</td>\n",
+       "      <td>18023.000000</td>\n",
+       "      <td>417.857143</td>\n",
+       "      <td>357.762938</td>\n",
+       "      <td>372.146458</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.711496</td>\n",
+       "      <td>0.443383</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>31.398955</td>\n",
+       "      <td>28.960396</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>32.137631</td>\n",
+       "      <td>9.980198</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>350 rows × 24 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff  \\\n",
+       "2019-12-31      0       0           0            0         NaN          NaN   \n",
+       "2020-01-01      0       0           0            0         0.0          0.0   \n",
+       "2020-01-02      0       0           0            0         0.0          0.0   \n",
+       "2020-01-03      0       0           0            0         0.0          0.0   \n",
+       "2020-01-04      0       0           0            0         0.0          0.0   \n",
+       "...           ...     ...         ...          ...         ...          ...   \n",
+       "2020-12-10  16578     533     1766819        62566      4297.0        -66.0   \n",
+       "2020-12-11  20964     516     1787783        63082      4386.0        -17.0   \n",
+       "2020-12-12  21672     424     1809455        63506       708.0        -92.0   \n",
+       "2020-12-13  21501     520     1830956        64026      -171.0         96.0   \n",
+       "2020-12-14  18447     144     1849403        64170     -3054.0       -376.0   \n",
+       "\n",
+       "                cases_m7   deaths_m7   deaths_g4   deaths_g7  ...  \\\n",
+       "2019-12-31      0.000000    0.000000    0.000000    0.000000  ...   \n",
+       "2020-01-01      0.000000    0.000000    0.000000    0.000000  ...   \n",
+       "2020-01-02      0.000000    0.000000    0.000000    0.000000  ...   \n",
+       "2020-01-03      0.000000    0.000000    0.000000    0.000000  ...   \n",
+       "2020-01-04      0.000000    0.000000    0.000000    0.000000  ...   \n",
+       "...                  ...         ...         ...         ...  ...   \n",
+       "2020-12-10  15366.142857  409.571429  343.603005  380.495816  ...   \n",
+       "2020-12-11  16235.571429  424.142857  420.064891  392.657665  ...   \n",
+       "2020-12-12  17003.285714  412.714286  514.093837  383.080949  ...   \n",
+       "2020-12-13  17855.000000  430.285714  496.234012  398.139480  ...   \n",
+       "2020-12-14  18023.000000  417.857143  357.762938  372.146458  ...   \n",
+       "\n",
+       "            admissions_m7  cases_m7n  deaths_m7n  admissions_m7n  cases_m7nd  \\\n",
+       "2019-12-31            NaN   0.000000    0.000000             NaN    0.000000   \n",
+       "2020-01-01            NaN   0.000000    0.000000             NaN    0.000000   \n",
+       "2020-01-02            NaN   0.000000    0.000000             NaN    0.000000   \n",
+       "2020-01-03            NaN   0.000000    0.000000             NaN    0.000000   \n",
+       "2020-01-04            NaN   0.000000    0.000000             NaN    0.000000   \n",
+       "...                   ...        ...         ...             ...         ...   \n",
+       "2020-12-10    1568.428571   0.606611    0.434591        0.503370   26.770284   \n",
+       "2020-12-11    1601.714286   0.640933    0.450053        0.514053   28.284968   \n",
+       "2020-12-12            NaN   0.671240    0.437926             NaN   29.622449   \n",
+       "2020-12-13            NaN   0.704864    0.456571             NaN   31.106272   \n",
+       "2020-12-14            NaN   0.711496    0.443383             NaN   31.398955   \n",
+       "\n",
+       "            deaths_m7nd  admissions_m7nd   cases_nd  deaths_nd  admissions_nd  \n",
+       "2019-12-31     0.000000              NaN   0.000000   0.000000            NaN  \n",
+       "2020-01-01     0.000000              NaN   0.000000   0.000000            NaN  \n",
+       "2020-01-02     0.000000              NaN   0.000000   0.000000            NaN  \n",
+       "2020-01-03     0.000000              NaN   0.000000   0.000000            NaN  \n",
+       "2020-01-04     0.000000              NaN   0.000000   0.000000            NaN  \n",
+       "...                 ...              ...        ...        ...            ...  \n",
+       "2020-12-10    28.386139        12.796037  28.881533  36.940594      13.926573  \n",
+       "2020-12-11    29.396040        13.067599  36.522648  35.762376      13.355478  \n",
+       "2020-12-12    28.603960              NaN  37.756098  29.386139            NaN  \n",
+       "2020-12-13    29.821782              NaN  37.458188  36.039604            NaN  \n",
+       "2020-12-14    28.960396              NaN  32.137631   9.980198            NaN  \n",
+       "\n",
+       "[350 rows x 24 columns]"
+      ]
+     },
+     "execution_count": 502,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_by_day"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 503,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Timestamp('2020-12-15 00:00:00')"
+      ]
+     },
+     "execution_count": 503,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lvi + pd.Timedelta(days=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 504,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f41892fdd10>"
+      ]
+     },
+     "execution_count": 504,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "dbds.loc['2020-03-01':'2020-07-02', ['cases_m7', 'admissions_m7', 'deaths_m7']].plot(ylim=(0, 6000))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 505,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>areaType</th>\n",
+       "      <th>areaName</th>\n",
+       "      <th>newCasesByPublishDate</th>\n",
+       "      <th>cumCasesByPublishDate</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>date</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>2020-03-10</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>373</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-03-11</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>83.0</td>\n",
+       "      <td>456</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-03-12</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>134.0</td>\n",
+       "      <td>590</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-03-13</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>207.0</td>\n",
+       "      <td>797</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-03-14</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>264.0</td>\n",
+       "      <td>1061</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-06-29</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>815.0</td>\n",
+       "      <td>311965</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-06-30</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>689.0</td>\n",
+       "      <td>312654</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-07-01</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>829.0</td>\n",
+       "      <td>313483</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-07-02</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>576.0</td>\n",
+       "      <td>283757</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-07-03</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>544.0</td>\n",
+       "      <td>284276</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>116 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            areaType        areaName  newCasesByPublishDate  \\\n",
+       "date                                                          \n",
+       "2020-03-10  overview  United Kingdom                    NaN   \n",
+       "2020-03-11  overview  United Kingdom                   83.0   \n",
+       "2020-03-12  overview  United Kingdom                  134.0   \n",
+       "2020-03-13  overview  United Kingdom                  207.0   \n",
+       "2020-03-14  overview  United Kingdom                  264.0   \n",
+       "...              ...             ...                    ...   \n",
+       "2020-06-29  overview  United Kingdom                  815.0   \n",
+       "2020-06-30  overview  United Kingdom                  689.0   \n",
+       "2020-07-01  overview  United Kingdom                  829.0   \n",
+       "2020-07-02  overview  United Kingdom                  576.0   \n",
+       "2020-07-03  overview  United Kingdom                  544.0   \n",
+       "\n",
+       "            cumCasesByPublishDate  \n",
+       "date                               \n",
+       "2020-03-10                    373  \n",
+       "2020-03-11                    456  \n",
+       "2020-03-12                    590  \n",
+       "2020-03-13                    797  \n",
+       "2020-03-14                   1061  \n",
+       "...                           ...  \n",
+       "2020-06-29                 311965  \n",
+       "2020-06-30                 312654  \n",
+       "2020-07-01                 313483  \n",
+       "2020-07-02                 283757  \n",
+       "2020-07-03                 284276  \n",
+       "\n",
+       "[116 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 505,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dbd = pd.read_csv('data_cases_2020-Jul-05.csv', index_col='date', parse_dates=True).sort_index()\n",
+    "dbd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 506,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "date\n",
+       "2020-03-10         NaN\n",
+       "2020-03-11       456.0\n",
+       "2020-03-12       590.0\n",
+       "2020-03-13       797.0\n",
+       "2020-03-14      1061.0\n",
+       "                ...   \n",
+       "2020-06-29    313091.0\n",
+       "2020-06-30    313780.0\n",
+       "2020-07-01    314609.0\n",
+       "2020-07-02    315185.0\n",
+       "2020-07-03    315729.0\n",
+       "Name: newCasesByPublishDate, Length: 116, dtype: float64"
+      ]
+     },
+     "execution_count": 506,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dbd.newCasesByPublishDate.cumsum() + dbd.loc['2020-03-10', 'cumCasesByPublishDate']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 507,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cases</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>cases_culm</th>\n",
+       "      <th>deaths_culm</th>\n",
+       "      <th>cases_diff</th>\n",
+       "      <th>deaths_diff</th>\n",
+       "      <th>cases_m7</th>\n",
+       "      <th>deaths_m7</th>\n",
+       "      <th>deaths_g4</th>\n",
+       "      <th>deaths_g7</th>\n",
+       "      <th>...</th>\n",
+       "      <th>admissions_m7</th>\n",
+       "      <th>cases_m7n</th>\n",
+       "      <th>deaths_m7n</th>\n",
+       "      <th>admissions_m7n</th>\n",
+       "      <th>cases_m7nd</th>\n",
+       "      <th>deaths_m7nd</th>\n",
+       "      <th>admissions_m7nd</th>\n",
+       "      <th>cases_nd</th>\n",
+       "      <th>deaths_nd</th>\n",
+       "      <th>admissions_nd</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>2019-12-31</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-01</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-02</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-03</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-04</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-10</td>\n",
+       "      <td>16578</td>\n",
+       "      <td>533</td>\n",
+       "      <td>1766819</td>\n",
+       "      <td>62566</td>\n",
+       "      <td>4297.0</td>\n",
+       "      <td>-66.0</td>\n",
+       "      <td>15366.142857</td>\n",
+       "      <td>409.571429</td>\n",
+       "      <td>343.603005</td>\n",
+       "      <td>380.495816</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1568.428571</td>\n",
+       "      <td>0.606611</td>\n",
+       "      <td>0.434591</td>\n",
+       "      <td>0.503370</td>\n",
+       "      <td>26.770284</td>\n",
+       "      <td>28.386139</td>\n",
+       "      <td>12.796037</td>\n",
+       "      <td>28.881533</td>\n",
+       "      <td>36.940594</td>\n",
+       "      <td>13.926573</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-11</td>\n",
+       "      <td>20964</td>\n",
+       "      <td>516</td>\n",
+       "      <td>1787783</td>\n",
+       "      <td>63082</td>\n",
+       "      <td>4386.0</td>\n",
+       "      <td>-17.0</td>\n",
+       "      <td>16235.571429</td>\n",
+       "      <td>424.142857</td>\n",
+       "      <td>420.064891</td>\n",
+       "      <td>392.657665</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1601.714286</td>\n",
+       "      <td>0.640933</td>\n",
+       "      <td>0.450053</td>\n",
+       "      <td>0.514053</td>\n",
+       "      <td>28.284968</td>\n",
+       "      <td>29.396040</td>\n",
+       "      <td>13.067599</td>\n",
+       "      <td>36.522648</td>\n",
+       "      <td>35.762376</td>\n",
+       "      <td>13.355478</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-12</td>\n",
+       "      <td>21672</td>\n",
+       "      <td>424</td>\n",
+       "      <td>1809455</td>\n",
+       "      <td>63506</td>\n",
+       "      <td>708.0</td>\n",
+       "      <td>-92.0</td>\n",
+       "      <td>17003.285714</td>\n",
+       "      <td>412.714286</td>\n",
+       "      <td>514.093837</td>\n",
+       "      <td>383.080949</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.671240</td>\n",
+       "      <td>0.437926</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>29.622449</td>\n",
+       "      <td>28.603960</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>37.756098</td>\n",
+       "      <td>29.386139</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-13</td>\n",
+       "      <td>21501</td>\n",
+       "      <td>520</td>\n",
+       "      <td>1830956</td>\n",
+       "      <td>64026</td>\n",
+       "      <td>-171.0</td>\n",
+       "      <td>96.0</td>\n",
+       "      <td>17855.000000</td>\n",
+       "      <td>430.285714</td>\n",
+       "      <td>496.234012</td>\n",
+       "      <td>398.139480</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.704864</td>\n",
+       "      <td>0.456571</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>31.106272</td>\n",
+       "      <td>29.821782</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>37.458188</td>\n",
+       "      <td>36.039604</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-14</td>\n",
+       "      <td>18447</td>\n",
+       "      <td>144</td>\n",
+       "      <td>1849403</td>\n",
+       "      <td>64170</td>\n",
+       "      <td>-3054.0</td>\n",
+       "      <td>-376.0</td>\n",
+       "      <td>18023.000000</td>\n",
+       "      <td>417.857143</td>\n",
+       "      <td>357.762938</td>\n",
+       "      <td>372.146458</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.711496</td>\n",
+       "      <td>0.443383</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>31.398955</td>\n",
+       "      <td>28.960396</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>32.137631</td>\n",
+       "      <td>9.980198</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>350 rows × 24 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff  \\\n",
+       "2019-12-31      0       0           0            0         NaN          NaN   \n",
+       "2020-01-01      0       0           0            0         0.0          0.0   \n",
+       "2020-01-02      0       0           0            0         0.0          0.0   \n",
+       "2020-01-03      0       0           0            0         0.0          0.0   \n",
+       "2020-01-04      0       0           0            0         0.0          0.0   \n",
+       "...           ...     ...         ...          ...         ...          ...   \n",
+       "2020-12-10  16578     533     1766819        62566      4297.0        -66.0   \n",
+       "2020-12-11  20964     516     1787783        63082      4386.0        -17.0   \n",
+       "2020-12-12  21672     424     1809455        63506       708.0        -92.0   \n",
+       "2020-12-13  21501     520     1830956        64026      -171.0         96.0   \n",
+       "2020-12-14  18447     144     1849403        64170     -3054.0       -376.0   \n",
+       "\n",
+       "                cases_m7   deaths_m7   deaths_g4   deaths_g7  ...  \\\n",
+       "2019-12-31      0.000000    0.000000    0.000000    0.000000  ...   \n",
+       "2020-01-01      0.000000    0.000000    0.000000    0.000000  ...   \n",
+       "2020-01-02      0.000000    0.000000    0.000000    0.000000  ...   \n",
+       "2020-01-03      0.000000    0.000000    0.000000    0.000000  ...   \n",
+       "2020-01-04      0.000000    0.000000    0.000000    0.000000  ...   \n",
+       "...                  ...         ...         ...         ...  ...   \n",
+       "2020-12-10  15366.142857  409.571429  343.603005  380.495816  ...   \n",
+       "2020-12-11  16235.571429  424.142857  420.064891  392.657665  ...   \n",
+       "2020-12-12  17003.285714  412.714286  514.093837  383.080949  ...   \n",
+       "2020-12-13  17855.000000  430.285714  496.234012  398.139480  ...   \n",
+       "2020-12-14  18023.000000  417.857143  357.762938  372.146458  ...   \n",
+       "\n",
+       "            admissions_m7  cases_m7n  deaths_m7n  admissions_m7n  cases_m7nd  \\\n",
+       "2019-12-31            NaN   0.000000    0.000000             NaN    0.000000   \n",
+       "2020-01-01            NaN   0.000000    0.000000             NaN    0.000000   \n",
+       "2020-01-02            NaN   0.000000    0.000000             NaN    0.000000   \n",
+       "2020-01-03            NaN   0.000000    0.000000             NaN    0.000000   \n",
+       "2020-01-04            NaN   0.000000    0.000000             NaN    0.000000   \n",
+       "...                   ...        ...         ...             ...         ...   \n",
+       "2020-12-10    1568.428571   0.606611    0.434591        0.503370   26.770284   \n",
+       "2020-12-11    1601.714286   0.640933    0.450053        0.514053   28.284968   \n",
+       "2020-12-12            NaN   0.671240    0.437926             NaN   29.622449   \n",
+       "2020-12-13            NaN   0.704864    0.456571             NaN   31.106272   \n",
+       "2020-12-14            NaN   0.711496    0.443383             NaN   31.398955   \n",
+       "\n",
+       "            deaths_m7nd  admissions_m7nd   cases_nd  deaths_nd  admissions_nd  \n",
+       "2019-12-31     0.000000              NaN   0.000000   0.000000            NaN  \n",
+       "2020-01-01     0.000000              NaN   0.000000   0.000000            NaN  \n",
+       "2020-01-02     0.000000              NaN   0.000000   0.000000            NaN  \n",
+       "2020-01-03     0.000000              NaN   0.000000   0.000000            NaN  \n",
+       "2020-01-04     0.000000              NaN   0.000000   0.000000            NaN  \n",
+       "...                 ...              ...        ...        ...            ...  \n",
+       "2020-12-10    28.386139        12.796037  28.881533  36.940594      13.926573  \n",
+       "2020-12-11    29.396040        13.067599  36.522648  35.762376      13.355478  \n",
+       "2020-12-12    28.603960              NaN  37.756098  29.386139            NaN  \n",
+       "2020-12-13    29.821782              NaN  37.458188  36.039604            NaN  \n",
+       "2020-12-14    28.960396              NaN  32.137631   9.980198            NaN  \n",
+       "\n",
+       "[350 rows x 24 columns]"
+      ]
+     },
+     "execution_count": 507,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_by_day"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 508,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_day['cases_m7n_date'] = data_by_day.cases_m7 / data_by_day.cases_m7.loc[normalisation_date]\n",
+    "data_by_day['deaths_m7n_date'] = data_by_day.deaths_m7 / data_by_day.deaths_m7.loc[normalisation_date]\n",
+    "data_by_day['admissions_m7n_date'] = data_by_day.admissions_m7 / data_by_day.admissions_m7.loc[normalisation_date]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 509,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f418923ee50>"
+      ]
+     },
+     "execution_count": 509,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data_by_day.loc[normalisation_date:, ['cases_m7n_date', 'admissions_m7n_date', 'deaths_m7n_date']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/hospital_data.ipynb b/hospital_data.ipynb

index b5ea101d36beae0de2a97ddce38cb405868a5bd0..d42d43c493970569df7027d99804570a7123e1a5 100644 (file)
--- a/hospital_data.ipynb
+++ b/hospital_data.ipynb
@@ -2,9 +2,20 @@
   "cells": [
    {
     "cell_type": "code",
   "cells": [
    {
     "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 91,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The sql extension is already loaded. To reload it, use:\n",
+      "  %reload_ext sql\n"
+     ]
+    }
+   ],
     "source": [
      "import itertools\n",
      "import collections\n",
     "source": [
      "import itertools\n",
      "import collections\n",
@@ -14,69 +25,81 @@
      "from scipy.stats import gmean\n",
      "import datetime\n",
      "\n",
      "from scipy.stats import gmean\n",
      "import datetime\n",
      "\n",
+    "import sqlalchemy\n",
+    "\n",
      "import matplotlib as mpl\n",
      "import matplotlib.pyplot as plt\n",
      "import matplotlib as mpl\n",
      "import matplotlib.pyplot as plt\n",
-    "%matplotlib inline"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
-      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
-      "100  1292    0  1292    0     0   1196      0 --:--:--  0:00:01 --:--:--  1196\n"
-     ]
-    }
-   ],
-   "source": [
-    "!curl \"https://api.coronavirus-staging.data.gov.uk/v1/data?filters=areaName=United%2520Kingdom;areaType=overview&structure=%7B%22date%22:%22date%22,%22areaName%22:%22areaName%22,%22areaType%22:%22areaType%22,%22newAdmissions%22:%22newAdmissions%22,%22cumAdmissions%22:%22cumAdmissions%22%7D&format=csv\" | gunzip > hospital_admissions.csv"
+    "%matplotlib inline\n",
+    "%load_ext sql"
     ]
    },
    {
     "cell_type": "code",
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
+   "execution_count": 92,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
     "outputs": [],
     "source": [
-    "raw_data = pd.read_csv('hospital_admissions.csv', \n",
-    "                       parse_dates=[0], dayfirst=True,\n",
-    "                      )"
+    "connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'"
     ]
    },
    {
     "cell_type": "code",
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
+   "execution_count": 93,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
        "text/plain": [
     "outputs": [
      {
       "data": {
        "text/plain": [
-       "date             datetime64[ns]\n",
-       "areaName                 object\n",
-       "areaType                 object\n",
-       "newAdmissions             int64\n",
-       "cumAdmissions             int64\n",
-       "dtype: object"
+       "'Connected: covid@covid'"
        ]
       },
        ]
       },
-     "execution_count": 5,
+     "execution_count": 93,
       "metadata": {},
       "output_type": "execute_result"
      }
     ],
     "source": [
       "metadata": {},
       "output_type": "execute_result"
      }
     ],
     "source": [
-    "raw_data.dtypes"
+    "%sql $connection_string"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 94,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "conn = sqlalchemy.create_engine(connection_string)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "normalisation_date = '2020-08-01' # '2020-05-15'\n",
+    "\n",
+    "hospital_normalisation_date = {\n",
+    "    'hospital_normalisation_date': normalisation_date\n",
+    "}\n",
+    "\n",
+    "with open('hospital_normalisation_date.json', 'w') as f:\n",
+    "    json.dump(hospital_normalisation_date, f)\n",
+    "    \n",
+    "hnd = pd.to_datetime(normalisation_date).strftime(\"%d %B %Y\")\n",
+    "with open('hospital_normalisation_date.js', 'w') as f:\n",
+    "    f.write(f\"document.write('{hnd}');\")"
     ]
    },
    {
     "cell_type": "code",
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 109,
     "metadata": {},
     "outputs": [
      {
     "metadata": {},
     "outputs": [
      {
@@ -100,10 +123,16 @@
         "  <thead>\n",
         "    <tr style=\"text-align: right;\">\n",
         "      <th></th>\n",
         "  <thead>\n",
         "    <tr style=\"text-align: right;\">\n",
         "      <th></th>\n",
-       "      <th>areaName</th>\n",
-       "      <th>areaType</th>\n",
-       "      <th>newAdmissions</th>\n",
-       "      <th>cumAdmissions</th>\n",
+       "      <th>new_admissions</th>\n",
+       "      <th>new_admissions_7</th>\n",
+       "      <th>new_cases</th>\n",
+       "      <th>new_cases_7</th>\n",
+       "      <th>new_deaths</th>\n",
+       "      <th>new_deaths_7</th>\n",
+       "      <th>hospital_cases</th>\n",
+       "      <th>hospital_cases_7</th>\n",
+       "      <th>ventilator_beds</th>\n",
+       "      <th>ventilator_beds_7</th>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>date</th>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>date</th>\n",
@@ -111,164 +140,164 @@
         "      <th></th>\n",
         "      <th></th>\n",
         "      <th></th>\n",
         "      <th></th>\n",
         "      <th></th>\n",
         "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
         "    </tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
         "    </tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
-       "      <td>2020-03-23</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>1687</td>\n",
-       "      <td>6794</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-24</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>1931</td>\n",
-       "      <td>8725</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-25</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>1968</td>\n",
-       "      <td>10693</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-26</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>2222</td>\n",
-       "      <td>12915</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-27</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>2165</td>\n",
-       "      <td>15080</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-01</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>133</td>\n",
-       "      <td>132672</td>\n",
+       "      <th>2021-01-22</th>\n",
+       "      <td>3341.0</td>\n",
+       "      <td>3771.7500</td>\n",
+       "      <td>29094.0</td>\n",
+       "      <td>24870.428</td>\n",
+       "      <td>1401</td>\n",
+       "      <td>1238.7142</td>\n",
+       "      <td>38144.0</td>\n",
+       "      <td>38057.168</td>\n",
+       "      <td>4076.0</td>\n",
+       "      <td>4015.8572</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2020-08-02</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>109</td>\n",
-       "      <td>132781</td>\n",
+       "      <th>2021-01-23</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3651.6667</td>\n",
+       "      <td>20495.0</td>\n",
+       "      <td>22463.666</td>\n",
+       "      <td>1348</td>\n",
+       "      <td>1241.7142</td>\n",
+       "      <td>37266.0</td>\n",
+       "      <td>37915.600</td>\n",
+       "      <td>4066.0</td>\n",
+       "      <td>4027.3333</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2020-08-03</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>89</td>\n",
-       "      <td>132870</td>\n",
+       "      <th>2021-01-24</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14266.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>610</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>37561.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4077.0</td>\n",
+       "      <td>NaN</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2020-08-04</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>126</td>\n",
-       "      <td>132996</td>\n",
+       "      <th>2021-01-25</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4482.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>592</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4032.0</td>\n",
+       "      <td>NaN</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2020-08-05</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>128</td>\n",
-       "      <td>133124</td>\n",
+       "      <th>2021-01-26</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1631</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
-       "<p>136 rows × 4 columns</p>\n",
         "</div>"
        ],
        "text/plain": [
         "</div>"
        ],
        "text/plain": [
-       "                  areaName  areaType  newAdmissions  cumAdmissions\n",
-       "date                                                              \n",
-       "2020-03-23  United Kingdom  overview           1687           6794\n",
-       "2020-03-24  United Kingdom  overview           1931           8725\n",
-       "2020-03-25  United Kingdom  overview           1968          10693\n",
-       "2020-03-26  United Kingdom  overview           2222          12915\n",
-       "2020-03-27  United Kingdom  overview           2165          15080\n",
-       "...                    ...       ...            ...            ...\n",
-       "2020-08-01  United Kingdom  overview            133         132672\n",
-       "2020-08-02  United Kingdom  overview            109         132781\n",
-       "2020-08-03  United Kingdom  overview             89         132870\n",
-       "2020-08-04  United Kingdom  overview            126         132996\n",
-       "2020-08-05  United Kingdom  overview            128         133124\n",
+       "            new_admissions  new_admissions_7  new_cases  new_cases_7  \\\n",
+       "date                                                                   \n",
+       "2021-01-22          3341.0         3771.7500    29094.0    24870.428   \n",
+       "2021-01-23             NaN         3651.6667    20495.0    22463.666   \n",
+       "2021-01-24             NaN               NaN    14266.0          NaN   \n",
+       "2021-01-25             NaN               NaN     4482.0          NaN   \n",
+       "2021-01-26             NaN               NaN        NaN          NaN   \n",
+       "\n",
+       "            new_deaths  new_deaths_7  hospital_cases  hospital_cases_7  \\\n",
+       "date                                                                     \n",
+       "2021-01-22        1401     1238.7142         38144.0         38057.168   \n",
+       "2021-01-23        1348     1241.7142         37266.0         37915.600   \n",
+       "2021-01-24         610           NaN         37561.0               NaN   \n",
+       "2021-01-25         592           NaN             NaN               NaN   \n",
+       "2021-01-26        1631           NaN             NaN               NaN   \n",
         "\n",
         "\n",
-       "[136 rows x 4 columns]"
+       "            ventilator_beds  ventilator_beds_7  \n",
+       "date                                            \n",
+       "2021-01-22           4076.0          4015.8572  \n",
+       "2021-01-23           4066.0          4027.3333  \n",
+       "2021-01-24           4077.0                NaN  \n",
+       "2021-01-25           4032.0                NaN  \n",
+       "2021-01-26              NaN                NaN  "
        ]
       },
        ]
       },
-     "execution_count": 6,
+     "execution_count": 109,
       "metadata": {},
       "output_type": "execute_result"
      }
     ],
     "source": [
       "metadata": {},
       "output_type": "execute_result"
      }
     ],
     "source": [
-    "hospital_data = raw_data.dropna().set_index('date').astype({'newAdmissions': np.int64, 'cumAdmissions': np.int64}).sort_index()\n",
-    "hospital_data"
+    "qstr = '''select uk_data.date\n",
+    "    , uk_data.new_admissions, uk_data_7.new_admissions as new_admissions_7\n",
+    "    , uk_data.new_cases, uk_data_7.new_cases as new_cases_7\n",
+    "    , uk_data.new_deaths, uk_data_7.new_deaths as new_deaths_7\n",
+    "    , uk_data.hospital_cases, uk_data_7.hospital_cases as hospital_cases_7\n",
+    "    , uk_data.ventilator_beds, uk_data_7.ventilator_beds as ventilator_beds_7\n",
+    "    from uk_data left outer join uk_data_7 using (date)\n",
+    "    order by uk_data.date'''\n",
+    "hd2 = pd.read_sql_query(qstr, conn)\n",
+    "hd2['date'] = hd2.date.astype('datetime64[ns]')\n",
+    "hd2.set_index('date', inplace=True)\n",
+    "hd2.tail()"
     ]
    },
    {
     "cell_type": "code",
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
+   "execution_count": 111,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
     "outputs": [
      {
-     "data": {
-      "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f01c8fcb5d0>"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "390 rows affected.\n",
+      "Returning data to local variable res\n"
+     ]
      }
     ],
     "source": [
      }
     ],
     "source": [
-    "hospital_data.newAdmissions.plot()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# data_by_day.newAdmissions.dropna()"
+    "%%sql res << select uk_data.date\n",
+    "    , uk_data.new_admissions, uk_data_7.new_admissions as new_admissions_7\n",
+    "    , uk_data.new_cases, uk_data_7.new_cases as new_cases_7\n",
+    "    , uk_data.new_deaths, uk_data_7.new_deaths as new_deaths_7\n",
+    "    , uk_data.hospital_cases, uk_data_7.hospital_cases as hospital_cases_7\n",
+    "    , uk_data.ventilator_beds, uk_data_7.ventilator_beds as ventilator_beds_7\n",
+    "    from uk_data left outer join uk_data_7 using (date)\n",
+    "    order by uk_data.date"
     ]
    },
    {
     "cell_type": "code",
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
+   "execution_count": 112,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
@@ -291,15 +320,23 @@
         "  <thead>\n",
         "    <tr style=\"text-align: right;\">\n",
         "      <th></th>\n",
         "  <thead>\n",
         "    <tr style=\"text-align: right;\">\n",
         "      <th></th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
+       "      <th>new_admissions</th>\n",
+       "      <th>new_admissions_7</th>\n",
+       "      <th>new_cases</th>\n",
+       "      <th>new_cases_7</th>\n",
+       "      <th>new_deaths</th>\n",
+       "      <th>new_deaths_7</th>\n",
+       "      <th>hospital_cases</th>\n",
+       "      <th>hospital_cases_7</th>\n",
+       "      <th>ventilator_beds</th>\n",
+       "      <th>ventilator_beds_7</th>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <th>dateRep</th>\n",
+       "      <th>date</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
         "      <th></th>\n",
         "      <th></th>\n",
         "      <th></th>\n",
         "      <th></th>\n",
         "      <th></th>\n",
         "      <th></th>\n",
@@ -310,140 +347,195 @@
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
-       "      <td>2019-12-31</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-01</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <th>2021-01-17</th>\n",
+       "      <td>3725.0</td>\n",
+       "      <td>3939.0000</td>\n",
+       "      <td>28875.0</td>\n",
+       "      <td>37337.855</td>\n",
+       "      <td>671</td>\n",
+       "      <td>1217.5714</td>\n",
+       "      <td>38095.0</td>\n",
+       "      <td>38292.285</td>\n",
+       "      <td>3871.0</td>\n",
+       "      <td>3857.4285</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2020-01-02</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <th>2021-01-18</th>\n",
+       "      <td>4054.0</td>\n",
+       "      <td>3872.8572</td>\n",
+       "      <td>44732.0</td>\n",
+       "      <td>35766.570</td>\n",
+       "      <td>599</td>\n",
+       "      <td>1223.5714</td>\n",
+       "      <td>39181.0</td>\n",
+       "      <td>38338.145</td>\n",
+       "      <td>3916.0</td>\n",
+       "      <td>3898.5715</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2020-01-03</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <th>2021-01-19</th>\n",
+       "      <td>4132.0</td>\n",
+       "      <td>3825.8572</td>\n",
+       "      <td>39311.0</td>\n",
+       "      <td>34143.285</td>\n",
+       "      <td>1610</td>\n",
+       "      <td>1240.8572</td>\n",
+       "      <td>38765.0</td>\n",
+       "      <td>38348.430</td>\n",
+       "      <td>3947.0</td>\n",
+       "      <td>3939.5715</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2020-01-04</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <th>2021-01-20</th>\n",
+       "      <td>4016.0</td>\n",
+       "      <td>3811.0000</td>\n",
+       "      <td>35015.0</td>\n",
+       "      <td>32707.428</td>\n",
+       "      <td>1820</td>\n",
+       "      <td>1248.4286</td>\n",
+       "      <td>38650.0</td>\n",
+       "      <td>38294.000</td>\n",
+       "      <td>3953.0</td>\n",
+       "      <td>3969.8572</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
+       "      <th>2021-01-21</th>\n",
+       "      <td>3598.0</td>\n",
+       "      <td>3828.2000</td>\n",
+       "      <td>31430.0</td>\n",
+       "      <td>30620.428</td>\n",
+       "      <td>1290</td>\n",
+       "      <td>1239.7142</td>\n",
+       "      <td>37957.0</td>\n",
+       "      <td>38217.715</td>\n",
+       "      <td>3960.0</td>\n",
+       "      <td>3999.2856</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2020-08-14</td>\n",
-       "      <td>1129</td>\n",
-       "      <td>-5359</td>\n",
-       "      <td>314927</td>\n",
-       "      <td>41347</td>\n",
-       "      <td>120.0</td>\n",
-       "      <td>-5539.0</td>\n",
+       "      <th>2021-01-22</th>\n",
+       "      <td>3341.0</td>\n",
+       "      <td>3771.7500</td>\n",
+       "      <td>29094.0</td>\n",
+       "      <td>24870.428</td>\n",
+       "      <td>1401</td>\n",
+       "      <td>1238.7142</td>\n",
+       "      <td>38144.0</td>\n",
+       "      <td>38057.168</td>\n",
+       "      <td>4076.0</td>\n",
+       "      <td>4015.8572</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>1440</td>\n",
-       "      <td>10</td>\n",
-       "      <td>316367</td>\n",
-       "      <td>41357</td>\n",
-       "      <td>311.0</td>\n",
-       "      <td>5369.0</td>\n",
+       "      <th>2021-01-23</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3651.6667</td>\n",
+       "      <td>20495.0</td>\n",
+       "      <td>22463.666</td>\n",
+       "      <td>1348</td>\n",
+       "      <td>1241.7142</td>\n",
+       "      <td>37266.0</td>\n",
+       "      <td>37915.600</td>\n",
+       "      <td>4066.0</td>\n",
+       "      <td>4027.3333</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>1077</td>\n",
-       "      <td>4</td>\n",
-       "      <td>317444</td>\n",
-       "      <td>41361</td>\n",
-       "      <td>-363.0</td>\n",
-       "      <td>-6.0</td>\n",
+       "      <th>2021-01-24</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14266.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>610</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>37561.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4077.0</td>\n",
+       "      <td>NaN</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>1040</td>\n",
-       "      <td>5</td>\n",
-       "      <td>318484</td>\n",
-       "      <td>41366</td>\n",
-       "      <td>-37.0</td>\n",
-       "      <td>1.0</td>\n",
+       "      <th>2021-01-25</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4482.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>592</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4032.0</td>\n",
+       "      <td>NaN</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>713</td>\n",
-       "      <td>3</td>\n",
-       "      <td>319197</td>\n",
-       "      <td>41369</td>\n",
-       "      <td>-327.0</td>\n",
-       "      <td>-2.0</td>\n",
+       "      <th>2021-01-26</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1631</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
-       "<p>232 rows × 6 columns</p>\n",
         "</div>"
        ],
        "text/plain": [
         "</div>"
        ],
        "text/plain": [
-       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff\n",
-       "dateRep                                                                    \n",
-       "2019-12-31      0       0           0            0         NaN          NaN\n",
-       "2020-01-01      0       0           0            0         0.0          0.0\n",
-       "2020-01-02      0       0           0            0         0.0          0.0\n",
-       "2020-01-03      0       0           0            0         0.0          0.0\n",
-       "2020-01-04      0       0           0            0         0.0          0.0\n",
-       "...           ...     ...         ...          ...         ...          ...\n",
-       "2020-08-14   1129   -5359      314927        41347       120.0      -5539.0\n",
-       "2020-08-15   1440      10      316367        41357       311.0       5369.0\n",
-       "2020-08-16   1077       4      317444        41361      -363.0         -6.0\n",
-       "2020-08-17   1040       5      318484        41366       -37.0          1.0\n",
-       "2020-08-18    713       3      319197        41369      -327.0         -2.0\n",
+       "            new_admissions  new_admissions_7  new_cases  new_cases_7  \\\n",
+       "date                                                                   \n",
+       "2021-01-17          3725.0         3939.0000    28875.0    37337.855   \n",
+       "2021-01-18          4054.0         3872.8572    44732.0    35766.570   \n",
+       "2021-01-19          4132.0         3825.8572    39311.0    34143.285   \n",
+       "2021-01-20          4016.0         3811.0000    35015.0    32707.428   \n",
+       "2021-01-21          3598.0         3828.2000    31430.0    30620.428   \n",
+       "2021-01-22          3341.0         3771.7500    29094.0    24870.428   \n",
+       "2021-01-23             NaN         3651.6667    20495.0    22463.666   \n",
+       "2021-01-24             NaN               NaN    14266.0          NaN   \n",
+       "2021-01-25             NaN               NaN     4482.0          NaN   \n",
+       "2021-01-26             NaN               NaN        NaN          NaN   \n",
+       "\n",
+       "            new_deaths  new_deaths_7  hospital_cases  hospital_cases_7  \\\n",
+       "date                                                                     \n",
+       "2021-01-17         671     1217.5714         38095.0         38292.285   \n",
+       "2021-01-18         599     1223.5714         39181.0         38338.145   \n",
+       "2021-01-19        1610     1240.8572         38765.0         38348.430   \n",
+       "2021-01-20        1820     1248.4286         38650.0         38294.000   \n",
+       "2021-01-21        1290     1239.7142         37957.0         38217.715   \n",
+       "2021-01-22        1401     1238.7142         38144.0         38057.168   \n",
+       "2021-01-23        1348     1241.7142         37266.0         37915.600   \n",
+       "2021-01-24         610           NaN         37561.0               NaN   \n",
+       "2021-01-25         592           NaN             NaN               NaN   \n",
+       "2021-01-26        1631           NaN             NaN               NaN   \n",
         "\n",
         "\n",
-       "[232 rows x 6 columns]"
+       "            ventilator_beds  ventilator_beds_7  \n",
+       "date                                            \n",
+       "2021-01-17           3871.0          3857.4285  \n",
+       "2021-01-18           3916.0          3898.5715  \n",
+       "2021-01-19           3947.0          3939.5715  \n",
+       "2021-01-20           3953.0          3969.8572  \n",
+       "2021-01-21           3960.0          3999.2856  \n",
+       "2021-01-22           4076.0          4015.8572  \n",
+       "2021-01-23           4066.0          4027.3333  \n",
+       "2021-01-24           4077.0                NaN  \n",
+       "2021-01-25           4032.0                NaN  \n",
+       "2021-01-26              NaN                NaN  "
        ]
       },
        ]
       },
-     "execution_count": 9,
+     "execution_count": 112,
       "metadata": {},
       "output_type": "execute_result"
      }
     ],
     "source": [
       "metadata": {},
       "output_type": "execute_result"
      }
     ],
     "source": [
-    "data_by_day = pd.read_csv('data_by_day_uk.csv', index_col='dateRep', parse_dates=True)\n",
-    "data_by_day"
+    "hospital_data = res.DataFrame()\n",
+    "hospital_data['date'] = hospital_data.date.astype('datetime64[ns]')\n",
+    "hospital_data.set_index('date', inplace=True)\n",
+    "hospital_data.tail(10)"
     ]
    },
    {
     "cell_type": "code",
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 113,
     "metadata": {},
     "outputs": [
      {
     "metadata": {},
     "outputs": [
      {
@@ -467,15 +559,23 @@
         "  <thead>\n",
         "    <tr style=\"text-align: right;\">\n",
         "      <th></th>\n",
         "  <thead>\n",
         "    <tr style=\"text-align: right;\">\n",
         "      <th></th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
+       "      <th>new_admissions</th>\n",
+       "      <th>new_admissions_7</th>\n",
+       "      <th>new_cases</th>\n",
+       "      <th>new_cases_7</th>\n",
+       "      <th>new_deaths</th>\n",
+       "      <th>new_deaths_7</th>\n",
+       "      <th>hospital_cases</th>\n",
+       "      <th>hospital_cases_7</th>\n",
+       "      <th>ventilator_beds</th>\n",
+       "      <th>ventilator_beds_7</th>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <th>dateRep</th>\n",
+       "      <th>date</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
         "      <th></th>\n",
         "      <th></th>\n",
         "      <th></th>\n",
         "      <th></th>\n",
         "      <th></th>\n",
         "      <th></th>\n",
@@ -486,458 +586,290 @@
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
-       "      <td>2019-12-31</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-01</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-02</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-03</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-04</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-14</td>\n",
-       "      <td>1129</td>\n",
-       "      <td>-5359</td>\n",
-       "      <td>314927</td>\n",
-       "      <td>41347</td>\n",
-       "      <td>120.0</td>\n",
-       "      <td>-5539.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>1440</td>\n",
-       "      <td>10</td>\n",
-       "      <td>316367</td>\n",
-       "      <td>41357</td>\n",
-       "      <td>311.0</td>\n",
-       "      <td>5369.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>1077</td>\n",
-       "      <td>4</td>\n",
-       "      <td>317444</td>\n",
-       "      <td>41361</td>\n",
-       "      <td>-363.0</td>\n",
-       "      <td>-6.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>1040</td>\n",
-       "      <td>5</td>\n",
-       "      <td>318484</td>\n",
-       "      <td>41366</td>\n",
-       "      <td>-37.0</td>\n",
-       "      <td>1.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>713</td>\n",
-       "      <td>3</td>\n",
-       "      <td>319197</td>\n",
-       "      <td>41369</td>\n",
-       "      <td>-327.0</td>\n",
-       "      <td>-2.0</td>\n",
+       "      <th>2020-01-03</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-04</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-05</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-06</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-07</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-22</th>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-23</th>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-24</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-25</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-26</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
-       "<p>232 rows × 6 columns</p>\n",
+       "<p>390 rows × 10 columns</p>\n",
         "</div>"
        ],
        "text/plain": [
         "</div>"
        ],
        "text/plain": [
-       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff\n",
-       "dateRep                                                                    \n",
-       "2019-12-31      0       0           0            0         NaN          NaN\n",
-       "2020-01-01      0       0           0            0         0.0          0.0\n",
-       "2020-01-02      0       0           0            0         0.0          0.0\n",
-       "2020-01-03      0       0           0            0         0.0          0.0\n",
-       "2020-01-04      0       0           0            0         0.0          0.0\n",
-       "...           ...     ...         ...          ...         ...          ...\n",
-       "2020-08-14   1129   -5359      314927        41347       120.0      -5539.0\n",
-       "2020-08-15   1440      10      316367        41357       311.0       5369.0\n",
-       "2020-08-16   1077       4      317444        41361      -363.0         -6.0\n",
-       "2020-08-17   1040       5      318484        41366       -37.0          1.0\n",
-       "2020-08-18    713       3      319197        41369      -327.0         -2.0\n",
+       "            new_admissions  new_admissions_7  new_cases  new_cases_7  \\\n",
+       "date                                                                   \n",
+       "2020-01-03           False             False      False        False   \n",
+       "2020-01-04           False             False      False        False   \n",
+       "2020-01-05           False             False      False        False   \n",
+       "2020-01-06           False             False      False        False   \n",
+       "2020-01-07           False             False      False        False   \n",
+       "...                    ...               ...        ...          ...   \n",
+       "2021-01-22            True              True       True         True   \n",
+       "2021-01-23           False              True       True         True   \n",
+       "2021-01-24           False             False       True        False   \n",
+       "2021-01-25           False             False       True        False   \n",
+       "2021-01-26           False             False      False        False   \n",
         "\n",
         "\n",
-       "[232 rows x 6 columns]"
+       "            new_deaths  new_deaths_7  hospital_cases  hospital_cases_7  \\\n",
+       "date                                                                     \n",
+       "2020-01-03        True         False           False             False   \n",
+       "2020-01-04        True         False           False             False   \n",
+       "2020-01-05        True         False           False             False   \n",
+       "2020-01-06        True          True           False             False   \n",
+       "2020-01-07        True          True           False             False   \n",
+       "...                ...           ...             ...               ...   \n",
+       "2021-01-22        True          True            True              True   \n",
+       "2021-01-23        True          True            True              True   \n",
+       "2021-01-24        True         False            True             False   \n",
+       "2021-01-25        True         False           False             False   \n",
+       "2021-01-26        True         False           False             False   \n",
+       "\n",
+       "            ventilator_beds  ventilator_beds_7  \n",
+       "date                                            \n",
+       "2020-01-03            False              False  \n",
+       "2020-01-04            False              False  \n",
+       "2020-01-05            False              False  \n",
+       "2020-01-06            False              False  \n",
+       "2020-01-07            False              False  \n",
+       "...                     ...                ...  \n",
+       "2021-01-22             True               True  \n",
+       "2021-01-23             True               True  \n",
+       "2021-01-24             True              False  \n",
+       "2021-01-25             True              False  \n",
+       "2021-01-26            False              False  \n",
+       "\n",
+       "[390 rows x 10 columns]"
        ]
       },
        ]
       },
-     "execution_count": 10,
+     "execution_count": 113,
       "metadata": {},
       "output_type": "execute_result"
      }
     ],
     "source": [
       "metadata": {},
       "output_type": "execute_result"
      }
     ],
     "source": [
-    "data_by_day.loc['2020-07-03', 'cases'] = 576\n",
-    "data_by_day"
+    "hospital_data == hd2"
     ]
    },
    {
     "cell_type": "code",
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 114,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "new_admissions       float64\n",
+       "new_admissions_7     float64\n",
+       "new_cases            float64\n",
+       "new_cases_7          float64\n",
+       "new_deaths             int64\n",
+       "new_deaths_7         float64\n",
+       "hospital_cases       float64\n",
+       "hospital_cases_7     float64\n",
+       "ventilator_beds      float64\n",
+       "ventilator_beds_7    float64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 114,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
     "source": [
     "source": [
-    "data_by_day = data_by_day.merge(hospital_data[['newAdmissions', 'cumAdmissions']], how='outer',\n",
-    "    left_index=True, right_index=True)"
+    "hospital_data.dtypes"
     ]
    },
    {
     "cell_type": "code",
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 115,
     "metadata": {},
     "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "new_admissions       float64\n",
+       "new_admissions_7     float64\n",
+       "new_cases            float64\n",
+       "new_cases_7          float64\n",
+       "new_deaths             int64\n",
+       "new_deaths_7         float64\n",
+       "hospital_cases       float64\n",
+       "hospital_cases_7     float64\n",
+       "ventilator_beds      float64\n",
+       "ventilator_beds_7    float64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 115,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
     "source": [
     "source": [
-    "data_by_day['deaths_m7'] = data_by_day.deaths.transform(lambda x: x.rolling(7, 1).mean())\n",
-    "data_by_day['cases_m7'] = data_by_day.cases.transform(lambda x: x.rolling(7, 1).mean())\n",
-    "data_by_day['admissions_m7'] = data_by_day.newAdmissions.transform(lambda x: x.rolling(7, 1).mean())"
+    "hd2.dtypes"
     ]
    },
    {
     "cell_type": "code",
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "      <th>newAdmissions</th>\n",
-       "      <th>cumAdmissions</th>\n",
-       "      <th>deaths_m7</th>\n",
-       "      <th>cases_m7</th>\n",
-       "      <th>admissions_m7</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>2019-12-31</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-01</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-02</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-03</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-04</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-14</td>\n",
-       "      <td>1129</td>\n",
-       "      <td>-5359</td>\n",
-       "      <td>314927</td>\n",
-       "      <td>41347</td>\n",
-       "      <td>120.0</td>\n",
-       "      <td>-5539.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-723.714286</td>\n",
-       "      <td>970.428571</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>1440</td>\n",
-       "      <td>10</td>\n",
-       "      <td>316367</td>\n",
-       "      <td>41357</td>\n",
-       "      <td>311.0</td>\n",
-       "      <td>5369.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-736.285714</td>\n",
-       "      <td>1051.714286</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>1077</td>\n",
-       "      <td>4</td>\n",
-       "      <td>317444</td>\n",
-       "      <td>41361</td>\n",
-       "      <td>-363.0</td>\n",
-       "      <td>-6.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-743.571429</td>\n",
-       "      <td>1097.285714</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>1040</td>\n",
-       "      <td>5</td>\n",
-       "      <td>318484</td>\n",
-       "      <td>41366</td>\n",
-       "      <td>-37.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-744.000000</td>\n",
-       "      <td>1094.142857</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>713</td>\n",
-       "      <td>3</td>\n",
-       "      <td>319197</td>\n",
-       "      <td>41369</td>\n",
-       "      <td>-327.0</td>\n",
-       "      <td>-2.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-736.714286</td>\n",
-       "      <td>1079.428571</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>232 rows × 11 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff  \\\n",
-       "2019-12-31      0       0           0            0         NaN          NaN   \n",
-       "2020-01-01      0       0           0            0         0.0          0.0   \n",
-       "2020-01-02      0       0           0            0         0.0          0.0   \n",
-       "2020-01-03      0       0           0            0         0.0          0.0   \n",
-       "2020-01-04      0       0           0            0         0.0          0.0   \n",
-       "...           ...     ...         ...          ...         ...          ...   \n",
-       "2020-08-14   1129   -5359      314927        41347       120.0      -5539.0   \n",
-       "2020-08-15   1440      10      316367        41357       311.0       5369.0   \n",
-       "2020-08-16   1077       4      317444        41361      -363.0         -6.0   \n",
-       "2020-08-17   1040       5      318484        41366       -37.0          1.0   \n",
-       "2020-08-18    713       3      319197        41369      -327.0         -2.0   \n",
-       "\n",
-       "            newAdmissions  cumAdmissions   deaths_m7     cases_m7  \\\n",
-       "2019-12-31            NaN            NaN    0.000000     0.000000   \n",
-       "2020-01-01            NaN            NaN    0.000000     0.000000   \n",
-       "2020-01-02            NaN            NaN    0.000000     0.000000   \n",
-       "2020-01-03            NaN            NaN    0.000000     0.000000   \n",
-       "2020-01-04            NaN            NaN    0.000000     0.000000   \n",
-       "...                   ...            ...         ...          ...   \n",
-       "2020-08-14            NaN            NaN -723.714286   970.428571   \n",
-       "2020-08-15            NaN            NaN -736.285714  1051.714286   \n",
-       "2020-08-16            NaN            NaN -743.571429  1097.285714   \n",
-       "2020-08-17            NaN            NaN -744.000000  1094.142857   \n",
-       "2020-08-18            NaN            NaN -736.714286  1079.428571   \n",
-       "\n",
-       "            admissions_m7  \n",
-       "2019-12-31            NaN  \n",
-       "2020-01-01            NaN  \n",
-       "2020-01-02            NaN  \n",
-       "2020-01-03            NaN  \n",
-       "2020-01-04            NaN  \n",
-       "...                   ...  \n",
-       "2020-08-14            NaN  \n",
-       "2020-08-15            NaN  \n",
-       "2020-08-16            NaN  \n",
-       "2020-08-17            NaN  \n",
-       "2020-08-18            NaN  \n",
-       "\n",
-       "[232 rows x 11 columns]"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_by_day"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "cases               687.000000\n",
-       "deaths               43.000000\n",
-       "cases_culm       277855.000000\n",
-       "deaths_culm       42741.000000\n",
-       "cases_diff         -299.000000\n",
-       "deaths_diff         -87.000000\n",
-       "newAdmissions       347.000000\n",
-       "cumAdmissions    125307.000000\n",
-       "deaths_m7           134.428571\n",
-       "cases_m7            954.285714\n",
-       "admissions_m7       353.714286\n",
-       "Name: 2020-06-22 00:00:00, dtype: float64"
-      ]
-     },
-     "execution_count": 14,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_by_day.loc['2020-06-22']"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {},
+   "execution_count": 116,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
        "text/plain": [
     "outputs": [
      {
       "data": {
        "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f01f6713410>"
+       "<AxesSubplot:xlabel='date'>"
        ]
       },
        ]
       },
-     "execution_count": 15,
+     "execution_count": 116,
       "metadata": {},
       "output_type": "execute_result"
      },
      {
       "data": {
       "metadata": {},
       "output_type": "execute_result"
      },
      {
       "data": {
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\n",
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\n",
        "text/plain": [
         "<Figure size 432x288 with 1 Axes>"
        ]
        "text/plain": [
         "<Figure size 432x288 with 1 Axes>"
        ]
@@ -949,27 +881,29 @@
      }
     ],
     "source": [
      }
     ],
     "source": [
-    "data_by_day[['cases_culm', 'cumAdmissions', 'deaths_culm']].plot()"
+    "hospital_data[['new_admissions', 'new_admissions_7']].plot()"
     ]
    },
    {
     "cell_type": "code",
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {},
+   "execution_count": 117,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
        "text/plain": [
     "outputs": [
      {
       "data": {
        "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f01c41f2850>"
+       "<AxesSubplot:xlabel='date'>"
        ]
       },
        ]
       },
-     "execution_count": 16,
+     "execution_count": 117,
       "metadata": {},
       "output_type": "execute_result"
      },
      {
       "data": {
       "metadata": {},
       "output_type": "execute_result"
      },
      {
       "data": {
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\n",
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\n",
        "text/plain": [
         "<Figure size 432x288 with 1 Axes>"
        ]
        "text/plain": [
         "<Figure size 432x288 with 1 Axes>"
        ]
@@ -981,27 +915,29 @@
      }
     ],
     "source": [
      }
     ],
     "source": [
-    "data_by_day.loc['2020-04-01':, ['cases_culm', 'cumAdmissions', 'deaths_culm']].plot()"
+    "hospital_data[['hospital_cases', 'hospital_cases_7']].plot()"
     ]
    },
    {
     "cell_type": "code",
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {},
+   "execution_count": 118,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
        "text/plain": [
     "outputs": [
      {
       "data": {
        "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f01c40cbdd0>"
+       "<AxesSubplot:xlabel='date'>"
        ]
       },
        ]
       },
-     "execution_count": 17,
+     "execution_count": 118,
       "metadata": {},
       "output_type": "execute_result"
      },
      {
       "data": {
       "metadata": {},
       "output_type": "execute_result"
      },
      {
       "data": {
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\n",
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\n",
        "text/plain": [
         "<Figure size 432x288 with 1 Axes>"
        ]
        "text/plain": [
         "<Figure size 432x288 with 1 Axes>"
        ]
@@ -1013,29 +949,28 @@
      }
     ],
     "source": [
      }
     ],
     "source": [
-    "data_by_day.loc['2020-03-01':'2020-07-02', ['cases', 'newAdmissions', 'deaths']].plot()"
+    "hospital_data[['ventilator_beds', 'ventilator_beds_7']].plot()"
     ]
    },
    {
     "cell_type": "code",
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 119,
     "metadata": {},
     "outputs": [
      {
       "data": {
        "text/plain": [
     "metadata": {},
     "outputs": [
      {
       "data": {
        "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f01c4070190>"
+       "<Figure size 720x576 with 0 Axes>"
        ]
       },
        ]
       },
-     "execution_count": 18,
       "metadata": {},
       "metadata": {},
-     "output_type": "execute_result"
+     "output_type": "display_data"
      },
      {
       "data": {
      },
      {
       "data": {
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\n",
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\n",
        "text/plain": [
        "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+       "<Figure size 720x576 with 2 Axes>"
        ]
       },
       "metadata": {
        ]
       },
       "metadata": {
@@ -1045,72 +980,62 @@
      }
     ],
     "source": [
      }
     ],
     "source": [
-    "data_by_day.loc['2020-03-01':'2020-07-02', ['cases_m7', 'admissions_m7', 'deaths_m7']].plot()"
+    "fig = plt.figure(figsize=(10, 8))\n",
+    "ax = hospital_data.loc['2020-03-20':, ['hospital_cases', 'ventilator_beds']].plot(\n",
+    "    secondary_y='ventilator_beds',\n",
+    "    figsize=(10, 8),\n",
+    "    title=\"People in hospital, and on mechanical ventilation\")\n",
+    "# axl.legend(['Number in hospital', 'Number on ventilator'])\n",
+    "plt.savefig('people_in_hospital.png')"
     ]
    },
    {
     "cell_type": "code",
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {},
+   "execution_count": 120,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
     "outputs": [],
     "source": [
-    "data_by_day['cases_m7n'] = data_by_day.cases_m7 / data_by_day.cases_m7.max()\n",
-    "data_by_day['deaths_m7n'] = data_by_day.deaths_m7 / data_by_day.deaths_m7.max()\n",
-    "data_by_day['admissions_m7n'] = data_by_day.admissions_m7 / data_by_day.admissions_m7.max()"
+    "hospital_data['cases_m7nd'] = hospital_data.new_cases_7 / hospital_data.new_cases_7.loc[normalisation_date]\n",
+    "hospital_data['deaths_m7nd'] = hospital_data.new_deaths_7 / hospital_data.new_deaths_7.loc[normalisation_date]\n",
+    "hospital_data['admissions_m7nd'] = hospital_data.new_admissions_7 / hospital_data.new_admissions_7.loc[normalisation_date]"
     ]
    },
    {
     "cell_type": "code",
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {},
+   "execution_count": 121,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
        "text/plain": [
     "outputs": [
      {
       "data": {
        "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f01c3fa8790>"
+       "96.1"
        ]
       },
        ]
       },
-     "execution_count": 20,
+     "execution_count": 121,
       "metadata": {},
       "output_type": "execute_result"
       "metadata": {},
       "output_type": "execute_result"
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
      }
     ],
     "source": [
      }
     ],
     "source": [
-    "data_by_day.loc['2020-03-01':'2020-07-02', ['cases_m7n', 'admissions_m7n', 'deaths_m7n']].plot()"
+    "(int(hospital_data.loc[normalisation_date:, ['cases_m7nd', 'admissions_m7nd', 'deaths_m7nd']].max().max() * 10) + 1) / 10.0"
     ]
    },
    {
     "cell_type": "code",
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
+   "execution_count": 122,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
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\n",
        "text/plain": [
        "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f01c8407f90>"
-      ]
-     },
-     "execution_count": 21,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+       "<Figure size 720x576 with 1 Axes>"
        ]
       },
       "metadata": {
        ]
       },
       "metadata": {
@@ -1120,838 +1045,35 @@
      }
     ],
     "source": [
      }
     ],
     "source": [
-    "data_by_day.loc['2020-03-01':, ['cases_m7n', 'admissions_m7n', 'deaths_m7n']].plot()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "      <th>newAdmissions</th>\n",
-       "      <th>cumAdmissions</th>\n",
-       "      <th>deaths_m7</th>\n",
-       "      <th>cases_m7</th>\n",
-       "      <th>admissions_m7</th>\n",
-       "      <th>cases_m7n</th>\n",
-       "      <th>deaths_m7n</th>\n",
-       "      <th>admissions_m7n</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>2019-12-31</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-01</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-02</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-03</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-04</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-14</td>\n",
-       "      <td>1129</td>\n",
-       "      <td>-5359</td>\n",
-       "      <td>314927</td>\n",
-       "      <td>41347</td>\n",
-       "      <td>120.0</td>\n",
-       "      <td>-5539.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-723.714286</td>\n",
-       "      <td>970.428571</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.200248</td>\n",
-       "      <td>-0.766067</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>1440</td>\n",
-       "      <td>10</td>\n",
-       "      <td>316367</td>\n",
-       "      <td>41357</td>\n",
-       "      <td>311.0</td>\n",
-       "      <td>5369.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-736.285714</td>\n",
-       "      <td>1051.714286</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.217021</td>\n",
-       "      <td>-0.779374</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>1077</td>\n",
-       "      <td>4</td>\n",
-       "      <td>317444</td>\n",
-       "      <td>41361</td>\n",
-       "      <td>-363.0</td>\n",
-       "      <td>-6.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-743.571429</td>\n",
-       "      <td>1097.285714</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.226425</td>\n",
-       "      <td>-0.787086</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>1040</td>\n",
-       "      <td>5</td>\n",
-       "      <td>318484</td>\n",
-       "      <td>41366</td>\n",
-       "      <td>-37.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-744.000000</td>\n",
-       "      <td>1094.142857</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.225776</td>\n",
-       "      <td>-0.787540</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>713</td>\n",
-       "      <td>3</td>\n",
-       "      <td>319197</td>\n",
-       "      <td>41369</td>\n",
-       "      <td>-327.0</td>\n",
-       "      <td>-2.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-736.714286</td>\n",
-       "      <td>1079.428571</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.222740</td>\n",
-       "      <td>-0.779828</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>232 rows × 14 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff  \\\n",
-       "2019-12-31      0       0           0            0         NaN          NaN   \n",
-       "2020-01-01      0       0           0            0         0.0          0.0   \n",
-       "2020-01-02      0       0           0            0         0.0          0.0   \n",
-       "2020-01-03      0       0           0            0         0.0          0.0   \n",
-       "2020-01-04      0       0           0            0         0.0          0.0   \n",
-       "...           ...     ...         ...          ...         ...          ...   \n",
-       "2020-08-14   1129   -5359      314927        41347       120.0      -5539.0   \n",
-       "2020-08-15   1440      10      316367        41357       311.0       5369.0   \n",
-       "2020-08-16   1077       4      317444        41361      -363.0         -6.0   \n",
-       "2020-08-17   1040       5      318484        41366       -37.0          1.0   \n",
-       "2020-08-18    713       3      319197        41369      -327.0         -2.0   \n",
-       "\n",
-       "            newAdmissions  cumAdmissions   deaths_m7     cases_m7  \\\n",
-       "2019-12-31            NaN            NaN    0.000000     0.000000   \n",
-       "2020-01-01            NaN            NaN    0.000000     0.000000   \n",
-       "2020-01-02            NaN            NaN    0.000000     0.000000   \n",
-       "2020-01-03            NaN            NaN    0.000000     0.000000   \n",
-       "2020-01-04            NaN            NaN    0.000000     0.000000   \n",
-       "...                   ...            ...         ...          ...   \n",
-       "2020-08-14            NaN            NaN -723.714286   970.428571   \n",
-       "2020-08-15            NaN            NaN -736.285714  1051.714286   \n",
-       "2020-08-16            NaN            NaN -743.571429  1097.285714   \n",
-       "2020-08-17            NaN            NaN -744.000000  1094.142857   \n",
-       "2020-08-18            NaN            NaN -736.714286  1079.428571   \n",
-       "\n",
-       "            admissions_m7  cases_m7n  deaths_m7n  admissions_m7n  \n",
-       "2019-12-31            NaN   0.000000    0.000000             NaN  \n",
-       "2020-01-01            NaN   0.000000    0.000000             NaN  \n",
-       "2020-01-02            NaN   0.000000    0.000000             NaN  \n",
-       "2020-01-03            NaN   0.000000    0.000000             NaN  \n",
-       "2020-01-04            NaN   0.000000    0.000000             NaN  \n",
-       "...                   ...        ...         ...             ...  \n",
-       "2020-08-14            NaN   0.200248   -0.766067             NaN  \n",
-       "2020-08-15            NaN   0.217021   -0.779374             NaN  \n",
-       "2020-08-16            NaN   0.226425   -0.787086             NaN  \n",
-       "2020-08-17            NaN   0.225776   -0.787540             NaN  \n",
-       "2020-08-18            NaN   0.222740   -0.779828             NaN  \n",
-       "\n",
-       "[232 rows x 14 columns]"
-      ]
-     },
-     "execution_count": 22,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_by_day"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>cases</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>newAdmissions</th>\n",
-       "      <th>cumAdmissions</th>\n",
-       "      <th>deaths_m7</th>\n",
-       "      <th>cases_m7</th>\n",
-       "      <th>admissions_m7</th>\n",
-       "      <th>cases_m7n</th>\n",
-       "      <th>deaths_m7n</th>\n",
-       "      <th>admissions_m7n</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>2019-12-31</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-01</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-02</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-03</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-04</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-14</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-5359</td>\n",
-       "      <td>41347</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-723.714286</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-1.685296</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>10</td>\n",
-       "      <td>41357</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-736.285714</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-1.714571</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>4</td>\n",
-       "      <td>41361</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-743.571429</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-1.731537</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>5</td>\n",
-       "      <td>41366</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-744.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-1.732535</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>3</td>\n",
-       "      <td>41369</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-736.714286</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-1.715569</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>232 rows × 12 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "            cases  cases_culm  deaths  deaths_culm  newAdmissions  \\\n",
-       "2019-12-31    0.0         0.0       0            0            NaN   \n",
-       "2020-01-01    0.0         0.0       0            0            NaN   \n",
-       "2020-01-02    0.0         0.0       0            0            NaN   \n",
-       "2020-01-03    0.0         0.0       0            0            NaN   \n",
-       "2020-01-04    0.0         0.0       0            0            NaN   \n",
-       "...           ...         ...     ...          ...            ...   \n",
-       "2020-08-14    NaN         NaN   -5359        41347            NaN   \n",
-       "2020-08-15    NaN         NaN      10        41357            NaN   \n",
-       "2020-08-16    NaN         NaN       4        41361            NaN   \n",
-       "2020-08-17    NaN         NaN       5        41366            NaN   \n",
-       "2020-08-18    NaN         NaN       3        41369            NaN   \n",
-       "\n",
-       "            cumAdmissions   deaths_m7  cases_m7  admissions_m7  cases_m7n  \\\n",
-       "2019-12-31            NaN    0.000000       0.0            NaN        0.0   \n",
-       "2020-01-01            NaN    0.000000       0.0            NaN        0.0   \n",
-       "2020-01-02            NaN    0.000000       0.0            NaN        0.0   \n",
-       "2020-01-03            NaN    0.000000       0.0            NaN        0.0   \n",
-       "2020-01-04            NaN    0.000000       0.0            NaN        0.0   \n",
-       "...                   ...         ...       ...            ...        ...   \n",
-       "2020-08-14            NaN -723.714286       NaN            NaN        NaN   \n",
-       "2020-08-15            NaN -736.285714       NaN            NaN        NaN   \n",
-       "2020-08-16            NaN -743.571429       NaN            NaN        NaN   \n",
-       "2020-08-17            NaN -744.000000       NaN            NaN        NaN   \n",
-       "2020-08-18            NaN -736.714286       NaN            NaN        NaN   \n",
-       "\n",
-       "            deaths_m7n  admissions_m7n  \n",
-       "2019-12-31    0.000000             NaN  \n",
-       "2020-01-01    0.000000             NaN  \n",
-       "2020-01-02    0.000000             NaN  \n",
-       "2020-01-03    0.000000             NaN  \n",
-       "2020-01-04    0.000000             NaN  \n",
-       "...                ...             ...  \n",
-       "2020-08-14   -1.685296             NaN  \n",
-       "2020-08-15   -1.714571             NaN  \n",
-       "2020-08-16   -1.731537             NaN  \n",
-       "2020-08-17   -1.732535             NaN  \n",
-       "2020-08-18   -1.715569             NaN  \n",
-       "\n",
-       "[232 rows x 12 columns]"
-      ]
-     },
-     "execution_count": 23,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "dbds = pd.read_csv('data_by_day_uk.csv', index_col='dateRep', parse_dates=True)\n",
-    "dbds.loc['2020-07-03', 'cases'] = 576\n",
-    "\n",
-    "dbds = dbds[['cases', 'cases_culm']].shift(-25).merge(dbds[['deaths', 'deaths_culm']], left_index=True, right_index=True, how='outer')\n",
-    "dbds = dbds.merge(hospital_data[['newAdmissions', 'cumAdmissions']].shift(-14), how='outer',\n",
-    "    left_index=True, right_index=True)\n",
-    "\n",
-    "dbds['deaths_m7'] = dbds.deaths.transform(lambda x: x.rolling(7, 1).mean())\n",
-    "dbds['cases_m7'] = dbds.cases.transform(lambda x: x.rolling(7, 1).mean())\n",
-    "dbds['admissions_m7'] = dbds.newAdmissions.transform(lambda x: x.rolling(7, 1).mean())\n",
-    "\n",
-    "dbds['cases_m7n'] = dbds.cases_m7 / dbds.cases_m7.loc['2020-05-15']\n",
-    "dbds['deaths_m7n'] = dbds.deaths_m7 / dbds.deaths_m7.loc['2020-05-15']\n",
-    "dbds['admissions_m7n'] = dbds.admissions_m7 / dbds.admissions_m7.loc['2020-05-15']\n",
-    "\n",
-    "dbds"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f01c3e41e90>"
-      ]
-     },
-     "execution_count": 24,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 720x576 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "dbds.loc['2020-03-01':, ['cases_m7n', 'admissions_m7n', 'deaths_m7n']].plot(ylim=(0, 1.5), figsize=(10, 8))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f01c3b7bb90>"
-      ]
-     },
-     "execution_count": 25,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "dbds.loc['2020-03-01':'2020-07-02', ['cases_m7', 'admissions_m7', 'deaths_m7']].plot(ylim=(0, 6000))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 50,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>areaType</th>\n",
-       "      <th>areaName</th>\n",
-       "      <th>newCasesByPublishDate</th>\n",
-       "      <th>cumCasesByPublishDate</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>date</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>2020-03-10</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>373</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-11</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>83.0</td>\n",
-       "      <td>456</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-12</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>134.0</td>\n",
-       "      <td>590</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-13</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>207.0</td>\n",
-       "      <td>797</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-14</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>264.0</td>\n",
-       "      <td>1061</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-06-29</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>815.0</td>\n",
-       "      <td>311965</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-06-30</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>689.0</td>\n",
-       "      <td>312654</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-07-01</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>829.0</td>\n",
-       "      <td>313483</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-07-02</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>576.0</td>\n",
-       "      <td>283757</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-07-03</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>544.0</td>\n",
-       "      <td>284276</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>116 rows × 4 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "            areaType        areaName  newCasesByPublishDate  \\\n",
-       "date                                                          \n",
-       "2020-03-10  overview  United Kingdom                    NaN   \n",
-       "2020-03-11  overview  United Kingdom                   83.0   \n",
-       "2020-03-12  overview  United Kingdom                  134.0   \n",
-       "2020-03-13  overview  United Kingdom                  207.0   \n",
-       "2020-03-14  overview  United Kingdom                  264.0   \n",
-       "...              ...             ...                    ...   \n",
-       "2020-06-29  overview  United Kingdom                  815.0   \n",
-       "2020-06-30  overview  United Kingdom                  689.0   \n",
-       "2020-07-01  overview  United Kingdom                  829.0   \n",
-       "2020-07-02  overview  United Kingdom                  576.0   \n",
-       "2020-07-03  overview  United Kingdom                  544.0   \n",
-       "\n",
-       "            cumCasesByPublishDate  \n",
-       "date                               \n",
-       "2020-03-10                    373  \n",
-       "2020-03-11                    456  \n",
-       "2020-03-12                    590  \n",
-       "2020-03-13                    797  \n",
-       "2020-03-14                   1061  \n",
-       "...                           ...  \n",
-       "2020-06-29                 311965  \n",
-       "2020-06-30                 312654  \n",
-       "2020-07-01                 313483  \n",
-       "2020-07-02                 283757  \n",
-       "2020-07-03                 284276  \n",
-       "\n",
-       "[116 rows x 4 columns]"
-      ]
-     },
-     "execution_count": 50,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "dbd = pd.read_csv('data_cases_2020-Jul-05.csv', index_col='date', parse_dates=True).sort_index()\n",
-    "dbd"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 51,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "date\n",
-       "2020-03-10         NaN\n",
-       "2020-03-11       456.0\n",
-       "2020-03-12       590.0\n",
-       "2020-03-13       797.0\n",
-       "2020-03-14      1061.0\n",
-       "                ...   \n",
-       "2020-06-29    313091.0\n",
-       "2020-06-30    313780.0\n",
-       "2020-07-01    314609.0\n",
-       "2020-07-02    315185.0\n",
-       "2020-07-03    315729.0\n",
-       "Name: newCasesByPublishDate, Length: 116, dtype: float64"
-      ]
-     },
-     "execution_count": 51,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "dbd.newCasesByPublishDate.cumsum() + dbd.loc['2020-03-10', 'cumCasesByPublishDate']"
+    "ymax = (int(hospital_data.loc[normalisation_date:, ['cases_m7nd', 'admissions_m7nd', 'deaths_m7nd']].max().max() * 10) + 1) / 10.0\n",
+    "ax = hospital_data.loc[normalisation_date:, ['cases_m7nd', 'admissions_m7nd', 'deaths_m7nd']].plot(\n",
+    "    ylim=(0, ymax), \n",
+    "    figsize=(10, 8),\n",
+    "    title=\"Cases, hospital admissions, and deaths\\n(7-day moving averages)\")\n",
+    "\n",
+    "lvi = hospital_data.cases_m7nd.last_valid_index()\n",
+    "ax.text(x = lvi + pd.Timedelta(days=1), y = hospital_data.cases_m7nd[lvi], s = f'{hospital_data.cases_m7nd[lvi]:.2f}')\n",
+    "\n",
+    "lvi = hospital_data.admissions_m7nd.last_valid_index()\n",
+    "ax.text(x = lvi + pd.Timedelta(days=1), y = hospital_data.admissions_m7nd[lvi], s = f'{hospital_data.admissions_m7nd[lvi]:.2f}')\n",
+    "\n",
+    "lvi = hospital_data.deaths_m7nd.last_valid_index()\n",
+    "ax.text(x = lvi + pd.Timedelta(days=1), y = hospital_data.deaths_m7nd[lvi], s = f'{hospital_data.deaths_m7nd[lvi]:.2f}')\n",
+    "\n",
+    "\n",
+    "ax.set_xlabel(\"Date\")\n",
+    "ax.set_ylabel(f'Normalised units, scaled from {normalisation_date}')\n",
+    "ax.legend(['Cases', 'Admissions', 'Deaths'])\n",
+    "\n",
+    "plt.savefig('cases_admissions_deaths.png')"
     ]
    },
    {
     "cell_type": "code",
     "execution_count": null,
     ]
    },
    {
     "cell_type": "code",
     "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": []
    }
     "outputs": [],
     "source": []
    }
@@ -1972,7 +1094,7 @@
     "name": "python",
     "nbconvert_exporter": "python",
     "pygments_lexer": "ipython3",
     "name": "python",
     "nbconvert_exporter": "python",
     "pygments_lexer": "ipython3",
-   "version": "3.7.4"
+   "version": "3.8.5"
    }
   },
   "nbformat": 4,
    }
   },
   "nbformat": 4,
diff --git a/hospital_data.py b/hospital_data.py

new file mode 100644 (file)

index 0000000..3771cfa
--- /dev/null
+++ b/hospital_data.py
@@ -0,0 +1,100 @@
+#!/usr/bin/env python
+# coding: utf-8
+# %%
+import itertools
+import collections
+import json
+import pandas as pd
+import numpy as np
+from scipy.stats import gmean
+import datetime
+
+import sqlalchemy
+
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+plt.ioff()
+
+
+# %%
+connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'
+
+
+# %%
+engine = sqlalchemy.create_engine(connection_string)
+
+
+# %%
+normalisation_date = '2020-08-01' # '2020-05-15'
+
+hospital_normalisation_date = {
+    'hospital_normalisation_date': normalisation_date
+}
+
+with open('hospital_normalisation_date.json', 'w') as f:
+    json.dump(hospital_normalisation_date, f)
+    
+hnd = pd.to_datetime(normalisation_date).strftime("%d %B %Y")
+with open('hospital_normalisation_date.js', 'w') as f:
+    f.write(f"document.write('{hnd}');")
+
+
+# %%
+qstr = '''select uk_data.date
+    , uk_data.new_admissions, uk_data_7.new_admissions as new_admissions_7
+    , uk_data.new_cases, uk_data_7.new_cases as new_cases_7
+    , uk_data.new_deaths, uk_data_7.new_deaths as new_deaths_7
+    , uk_data.hospital_cases, uk_data_7.hospital_cases as hospital_cases_7
+    , uk_data.ventilator_beds, uk_data_7.ventilator_beds as ventilator_beds_7
+    from uk_data left outer join uk_data_7 using (date)
+    order by uk_data.date'''
+hospital_data = pd.read_sql_query(qstr, engine,
+    index_col='date',
+    parse_dates = ['date'])
+
+
+# %%
+fig = plt.figure(figsize=(10, 8))
+ax = hospital_data.loc['2020-03-20':, ['hospital_cases', 'ventilator_beds']].plot(
+    secondary_y='ventilator_beds',
+    figsize=(10, 8),
+    title="People in hospital, and on mechanical ventilation")
+# axl.legend(['Number in hospital', 'Number on ventilator'])
+plt.savefig('people_in_hospital.png')
+
+
+# %%
+hospital_data['cases_m7nd'] = hospital_data.new_cases_7 / hospital_data.new_cases_7.loc[normalisation_date]
+hospital_data['deaths_m7nd'] = hospital_data.new_deaths_7 / hospital_data.new_deaths_7.loc[normalisation_date]
+hospital_data['admissions_m7nd'] = hospital_data.new_admissions_7 / hospital_data.new_admissions_7.loc[normalisation_date]
+
+
+# %%
+ymax = (int(hospital_data.loc[normalisation_date:, ['cases_m7nd', 'admissions_m7nd', 'deaths_m7nd']].max().max() * 10) + 1) / 10.0
+ax = hospital_data.loc[normalisation_date:, ['cases_m7nd', 'admissions_m7nd', 'deaths_m7nd']].plot(
+    ylim=(0, ymax), 
+    figsize=(10, 8),
+    title="Cases, hospital admissions, and deaths\n(7-day moving averages)")
+
+lvi = hospital_data.cases_m7nd.last_valid_index()
+ax.text(x = lvi + pd.Timedelta(days=1), y = hospital_data.cases_m7nd[lvi], s = f'{hospital_data.cases_m7nd[lvi]:.2f}')
+
+lvi = hospital_data.admissions_m7nd.last_valid_index()
+ax.text(x = lvi + pd.Timedelta(days=1), y = hospital_data.admissions_m7nd[lvi], s = f'{hospital_data.admissions_m7nd[lvi]:.2f}')
+
+lvi = hospital_data.deaths_m7nd.last_valid_index()
+ax.text(x = lvi + pd.Timedelta(days=1), y = hospital_data.deaths_m7nd[lvi], s = f'{hospital_data.deaths_m7nd[lvi]:.2f}')
+
+
+ax.set_xlabel("Date")
+ax.set_ylabel(f'Normalised units, scaled from {normalisation_date}')
+ax.legend(['Cases', 'Admissions', 'Deaths'])
+
+plt.savefig('cases_admissions_deaths.png')
+
+
+# %%
+
+
+
+
diff --git a/international_comparison.ipynb b/international_comparison.ipynb

new file mode 100644 (file)

index 0000000..8f21f53
--- /dev/null
+++ b/international_comparison.ipynb
@@ -0,0 +1,1032 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "source": [
+    "Data from [European Centre for Disease Prevention and Control](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 94,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The sql extension is already loaded. To reload it, use:\n",
+      "  %reload_ext sql\n"
+     ]
+    }
+   ],
+   "source": [
+    "import itertools\n",
+    "import collections\n",
+    "import json\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "from scipy.stats import gmean\n",
+    "import datetime\n",
+    "\n",
+    "from sqlalchemy.types import Integer, Text, String, DateTime, Date, Float\n",
+    "from sqlalchemy import create_engine\n",
+    "\n",
+    "import matplotlib as mpl\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline\n",
+    "%load_ext sql"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 96,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Connected: covid@covid'"
+      ]
+     },
+     "execution_count": 96,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql $connection_string"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 97,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "engine = create_engine(connection_string)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 98,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "DEATH_COUNT_THRESHOLD = 10\n",
+    "COUNTRIES_CORE = tuple(sorted('IT DE UK ES IE FR BE'.split()))\n",
+    "COUNTRIES_NORDIC = tuple('SE NO DK FI UK'.split())\n",
+    "COUNTRIES_FRIENDS = tuple('IT UK ES BE SI MX'.split())\n",
+    "# COUNTRIES_FRIENDS = 'IT UK ES BE SI PT'.split()\n",
+    "\n",
+    "COUNTRIES_AMERICAS = ('AG', 'AR', 'AW', 'BS', 'BB', 'BZ', 'BM', 'BO', 'BR', 'VG', 'KY', # excluding Canada and USA\n",
+    "       'CL', 'CO', 'CR', 'CU', 'CW', 'DM', 'DO', 'EC', 'SV', 'GL', 'GD', 'GT',\n",
+    "       'GY', 'HT', 'HN', 'JM', 'MX', 'MS', 'NI', 'PA', 'PY', 'PE', 'PR', 'KN',\n",
+    "       'LC', 'VC', 'SX', 'SR', 'TT', 'TC', 'VI', 'UY', 'VE')\n",
+    "COUNTRIES_OF_INTEREST = tuple(set(COUNTRIES_CORE + COUNTRIES_FRIENDS))\n",
+    "COUNTRIES_ALL = tuple(set(COUNTRIES_CORE + COUNTRIES_FRIENDS + COUNTRIES_NORDIC + COUNTRIES_AMERICAS))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# res = %sql select report_date, geo_id, deaths_weekly, culm_deaths from weekly_cases where geo_id in $COUNTRIES_CORE order by report_date, geo_id"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# country_data = res.DataFrame()\n",
+    "# country_data['report_date'] = country_data.report_date.astype('datetime64[ns]')\n",
+    "# country_data.set_index('report_date', inplace=True)\n",
+    "# country_data.tail(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "query_string = f'''select report_date, geo_id, deaths_weekly, culm_deaths \n",
+    "from weekly_cases \n",
+    "where geo_id in {COUNTRIES_CORE} \n",
+    "order by report_date, geo_id'''\n",
+    "\n",
+    "country_data = pd.read_sql_query(query_string,\n",
+    "                  engine,\n",
+    "                  index_col = 'report_date',\n",
+    "                  parse_dates = ['report_date']\n",
+    "                 )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>geo_id</th>\n",
+       "      <th>BE</th>\n",
+       "      <th>DE</th>\n",
+       "      <th>ES</th>\n",
+       "      <th>FR</th>\n",
+       "      <th>IE</th>\n",
+       "      <th>IT</th>\n",
+       "      <th>UK</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>report_date</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2020-12-21</th>\n",
+       "      <td>18789</td>\n",
+       "      <td>26275</td>\n",
+       "      <td>49260</td>\n",
+       "      <td>60549</td>\n",
+       "      <td>2158</td>\n",
+       "      <td>68799</td>\n",
+       "      <td>67401</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-12-28</th>\n",
+       "      <td>19319</td>\n",
+       "      <td>30126</td>\n",
+       "      <td>50122</td>\n",
+       "      <td>63109</td>\n",
+       "      <td>2204</td>\n",
+       "      <td>71925</td>\n",
+       "      <td>71109</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-04</th>\n",
+       "      <td>19774</td>\n",
+       "      <td>34574</td>\n",
+       "      <td>51078</td>\n",
+       "      <td>65037</td>\n",
+       "      <td>2259</td>\n",
+       "      <td>75332</td>\n",
+       "      <td>75024</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-11</th>\n",
+       "      <td>20156</td>\n",
+       "      <td>40686</td>\n",
+       "      <td>52275</td>\n",
+       "      <td>67750</td>\n",
+       "      <td>2344</td>\n",
+       "      <td>78755</td>\n",
+       "      <td>81431</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-18</th>\n",
+       "      <td>20491</td>\n",
+       "      <td>46633</td>\n",
+       "      <td>53769</td>\n",
+       "      <td>70283</td>\n",
+       "      <td>2608</td>\n",
+       "      <td>82177</td>\n",
+       "      <td>89261</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "geo_id          BE     DE     ES     FR    IE     IT     UK\n",
+       "report_date                                                \n",
+       "2020-12-21   18789  26275  49260  60549  2158  68799  67401\n",
+       "2020-12-28   19319  30126  50122  63109  2204  71925  71109\n",
+       "2021-01-04   19774  34574  51078  65037  2259  75332  75024\n",
+       "2021-01-11   20156  40686  52275  67750  2344  78755  81431\n",
+       "2021-01-18   20491  46633  53769  70283  2608  82177  89261"
+      ]
+     },
+     "execution_count": 87,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_culm = country_data.pivot(columns='geo_id', values='culm_deaths')\n",
+    "deaths_culm.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='report_date'>"
+      ]
+     },
+     "execution_count": 88,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "deaths_culm.plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax = deaths_culm.loc['2020-03-15':].plot(figsize=(10, 6), title=\"Total deaths, linear\")\n",
+    "ax.set_xlabel(f\"Date\")\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = deaths_culm[c].last_valid_index()\n",
+    "    ax.text(x = lvi + pd.Timedelta(days=1), y = deaths_culm[c][lvi], s = f\"{c}: {deaths_culm[c][lvi]:.0f}\")\n",
+    "plt.savefig('covid_deaths_total_linear.png')    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 90,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>geo_id</th>\n",
+       "      <th>BE</th>\n",
+       "      <th>DE</th>\n",
+       "      <th>ES</th>\n",
+       "      <th>FR</th>\n",
+       "      <th>IE</th>\n",
+       "      <th>IT</th>\n",
+       "      <th>UK</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>report_date</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2020-12-21</th>\n",
+       "      <td>653</td>\n",
+       "      <td>4300</td>\n",
+       "      <td>1247</td>\n",
+       "      <td>2638</td>\n",
+       "      <td>34</td>\n",
+       "      <td>4279</td>\n",
+       "      <td>3231</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-12-28</th>\n",
+       "      <td>530</td>\n",
+       "      <td>3851</td>\n",
+       "      <td>862</td>\n",
+       "      <td>2560</td>\n",
+       "      <td>46</td>\n",
+       "      <td>3126</td>\n",
+       "      <td>3708</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-04</th>\n",
+       "      <td>455</td>\n",
+       "      <td>4448</td>\n",
+       "      <td>956</td>\n",
+       "      <td>1928</td>\n",
+       "      <td>55</td>\n",
+       "      <td>3407</td>\n",
+       "      <td>3915</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-11</th>\n",
+       "      <td>382</td>\n",
+       "      <td>6112</td>\n",
+       "      <td>1197</td>\n",
+       "      <td>2713</td>\n",
+       "      <td>85</td>\n",
+       "      <td>3423</td>\n",
+       "      <td>6407</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-18</th>\n",
+       "      <td>335</td>\n",
+       "      <td>5947</td>\n",
+       "      <td>1494</td>\n",
+       "      <td>2533</td>\n",
+       "      <td>264</td>\n",
+       "      <td>3422</td>\n",
+       "      <td>7830</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "geo_id        BE    DE    ES    FR   IE    IT    UK\n",
+       "report_date                                        \n",
+       "2020-12-21   653  4300  1247  2638   34  4279  3231\n",
+       "2020-12-28   530  3851   862  2560   46  3126  3708\n",
+       "2021-01-04   455  4448   956  1928   55  3407  3915\n",
+       "2021-01-11   382  6112  1197  2713   85  3423  6407\n",
+       "2021-01-18   335  5947  1494  2533  264  3422  7830"
+      ]
+     },
+     "execution_count": 90,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_weekly = country_data.pivot(columns='geo_id', values='deaths_weekly')\n",
+    "deaths_weekly.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='report_date'>"
+      ]
+     },
+     "execution_count": 91,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "deaths_weekly.plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 92,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax = deaths_weekly.loc['2020-03-01':, COUNTRIES_CORE].plot(figsize=(10, 6), title=\"Deaths per week\")\n",
+    "ax.set_xlabel('Date')\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = deaths_weekly[c].last_valid_index()\n",
+    "    ax.text(x = lvi + pd.Timedelta(days=1), y = deaths_weekly[c][lvi], s = c)\n",
+    "plt.savefig('covid_deaths_per_week.png') "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 93,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax = deaths_weekly.iloc[-6:].plot(figsize=(10, 6), title=\"Deaths per week\")#, ylim=(-10, 100))\n",
+    "ax.set_xlabel(\"Date\")\n",
+    "\n",
+    "text_x_pos = deaths_weekly.last_valid_index() + pd.Timedelta(days=0.5)\n",
+    "\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = deaths_weekly[c].last_valid_index()\n",
+    "#     if c != 'ES':\n",
+    "    ax.text(x = text_x_pos, y = deaths_weekly[c][lvi], s = f\"{c}: {deaths_weekly[c][lvi]:.0f}\")\n",
+    "plt.savefig('deaths_by_date_last_6_weeks.png') "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 109,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>geo_id</th>\n",
+       "      <th>deaths_weekly_pc</th>\n",
+       "      <th>culm_deaths_pc</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>report_date</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2021-01-18</th>\n",
+       "      <td>ES</td>\n",
+       "      <td>0.000032</td>\n",
+       "      <td>0.001146</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-18</th>\n",
+       "      <td>FR</td>\n",
+       "      <td>0.000038</td>\n",
+       "      <td>0.001049</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-18</th>\n",
+       "      <td>IE</td>\n",
+       "      <td>0.000054</td>\n",
+       "      <td>0.000532</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-18</th>\n",
+       "      <td>IT</td>\n",
+       "      <td>0.000057</td>\n",
+       "      <td>0.001361</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-18</th>\n",
+       "      <td>UK</td>\n",
+       "      <td>0.000117</td>\n",
+       "      <td>0.001339</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            geo_id  deaths_weekly_pc  culm_deaths_pc\n",
+       "report_date                                         \n",
+       "2021-01-18      ES          0.000032        0.001146\n",
+       "2021-01-18      FR          0.000038        0.001049\n",
+       "2021-01-18      IE          0.000054        0.000532\n",
+       "2021-01-18      IT          0.000057        0.001361\n",
+       "2021-01-18      UK          0.000117        0.001339"
+      ]
+     },
+     "execution_count": 109,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "query_string = f'''select report_date, geo_id, \n",
+    "(cast(deaths_weekly as float) / population_2019) deaths_weekly_pc,\n",
+    "(cast(culm_deaths as float) / population_2019) as culm_deaths_pc\n",
+    "from weekly_cases join countries using (geo_id)\n",
+    "where  geo_id in {COUNTRIES_CORE} \n",
+    "order by report_date, geo_id'''\n",
+    "\n",
+    "deaths_pc_data = pd.read_sql_query(query_string,\n",
+    "                  engine,\n",
+    "                  index_col = 'report_date',\n",
+    "                  parse_dates = ['report_date']\n",
+    "                 )\n",
+    "deaths_pc_data.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 110,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>geo_id</th>\n",
+       "      <th>BE</th>\n",
+       "      <th>DE</th>\n",
+       "      <th>ES</th>\n",
+       "      <th>FR</th>\n",
+       "      <th>IE</th>\n",
+       "      <th>IT</th>\n",
+       "      <th>UK</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>report_date</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2020-12-21</th>\n",
+       "      <td>0.001640</td>\n",
+       "      <td>0.000316</td>\n",
+       "      <td>0.001049</td>\n",
+       "      <td>0.000904</td>\n",
+       "      <td>0.000440</td>\n",
+       "      <td>0.001140</td>\n",
+       "      <td>0.001011</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-12-28</th>\n",
+       "      <td>0.001686</td>\n",
+       "      <td>0.000363</td>\n",
+       "      <td>0.001068</td>\n",
+       "      <td>0.000942</td>\n",
+       "      <td>0.000449</td>\n",
+       "      <td>0.001192</td>\n",
+       "      <td>0.001067</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-04</th>\n",
+       "      <td>0.001726</td>\n",
+       "      <td>0.000416</td>\n",
+       "      <td>0.001088</td>\n",
+       "      <td>0.000971</td>\n",
+       "      <td>0.000461</td>\n",
+       "      <td>0.001248</td>\n",
+       "      <td>0.001126</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-11</th>\n",
+       "      <td>0.001760</td>\n",
+       "      <td>0.000490</td>\n",
+       "      <td>0.001114</td>\n",
+       "      <td>0.001011</td>\n",
+       "      <td>0.000478</td>\n",
+       "      <td>0.001305</td>\n",
+       "      <td>0.001222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-18</th>\n",
+       "      <td>0.001789</td>\n",
+       "      <td>0.000562</td>\n",
+       "      <td>0.001146</td>\n",
+       "      <td>0.001049</td>\n",
+       "      <td>0.000532</td>\n",
+       "      <td>0.001361</td>\n",
+       "      <td>0.001339</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "geo_id             BE        DE        ES        FR        IE        IT  \\\n",
+       "report_date                                                               \n",
+       "2020-12-21   0.001640  0.000316  0.001049  0.000904  0.000440  0.001140   \n",
+       "2020-12-28   0.001686  0.000363  0.001068  0.000942  0.000449  0.001192   \n",
+       "2021-01-04   0.001726  0.000416  0.001088  0.000971  0.000461  0.001248   \n",
+       "2021-01-11   0.001760  0.000490  0.001114  0.001011  0.000478  0.001305   \n",
+       "2021-01-18   0.001789  0.000562  0.001146  0.001049  0.000532  0.001361   \n",
+       "\n",
+       "geo_id             UK  \n",
+       "report_date            \n",
+       "2020-12-21   0.001011  \n",
+       "2020-12-28   0.001067  \n",
+       "2021-01-04   0.001126  \n",
+       "2021-01-11   0.001222  \n",
+       "2021-01-18   0.001339  "
+      ]
+     },
+     "execution_count": 110,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_pc_culm = deaths_pc_data.pivot(columns='geo_id', values='culm_deaths_pc')\n",
+    "deaths_pc_culm.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 115,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax = deaths_pc_culm.loc['2020-03-15':].plot(figsize=(10, 6), title=\"Deaths per million, linear\")\n",
+    "ax.set_xlabel(f\"Date\")\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = deaths_pc_culm[c].last_valid_index()\n",
+    "    ax.text(x = lvi + pd.Timedelta(days=1), y = deaths_pc_culm[c][lvi], s = f\"{c}: {deaths_pc_culm[c][lvi]*10**6:.0f}\")\n",
+    "# plt.savefig('covid_deaths_total_linear.png')    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 117,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>geo_id</th>\n",
+       "      <th>BE</th>\n",
+       "      <th>DE</th>\n",
+       "      <th>ES</th>\n",
+       "      <th>FR</th>\n",
+       "      <th>IE</th>\n",
+       "      <th>IT</th>\n",
+       "      <th>UK</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>report_date</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2020-12-21</th>\n",
+       "      <td>0.000057</td>\n",
+       "      <td>0.000052</td>\n",
+       "      <td>0.000027</td>\n",
+       "      <td>0.000039</td>\n",
+       "      <td>0.000007</td>\n",
+       "      <td>0.000071</td>\n",
+       "      <td>0.000048</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-12-28</th>\n",
+       "      <td>0.000046</td>\n",
+       "      <td>0.000046</td>\n",
+       "      <td>0.000018</td>\n",
+       "      <td>0.000038</td>\n",
+       "      <td>0.000009</td>\n",
+       "      <td>0.000052</td>\n",
+       "      <td>0.000056</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-04</th>\n",
+       "      <td>0.000040</td>\n",
+       "      <td>0.000054</td>\n",
+       "      <td>0.000020</td>\n",
+       "      <td>0.000029</td>\n",
+       "      <td>0.000011</td>\n",
+       "      <td>0.000056</td>\n",
+       "      <td>0.000059</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-11</th>\n",
+       "      <td>0.000033</td>\n",
+       "      <td>0.000074</td>\n",
+       "      <td>0.000026</td>\n",
+       "      <td>0.000040</td>\n",
+       "      <td>0.000017</td>\n",
+       "      <td>0.000057</td>\n",
+       "      <td>0.000096</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-18</th>\n",
+       "      <td>0.000029</td>\n",
+       "      <td>0.000072</td>\n",
+       "      <td>0.000032</td>\n",
+       "      <td>0.000038</td>\n",
+       "      <td>0.000054</td>\n",
+       "      <td>0.000057</td>\n",
+       "      <td>0.000117</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "geo_id             BE        DE        ES        FR        IE        IT  \\\n",
+       "report_date                                                               \n",
+       "2020-12-21   0.000057  0.000052  0.000027  0.000039  0.000007  0.000071   \n",
+       "2020-12-28   0.000046  0.000046  0.000018  0.000038  0.000009  0.000052   \n",
+       "2021-01-04   0.000040  0.000054  0.000020  0.000029  0.000011  0.000056   \n",
+       "2021-01-11   0.000033  0.000074  0.000026  0.000040  0.000017  0.000057   \n",
+       "2021-01-18   0.000029  0.000072  0.000032  0.000038  0.000054  0.000057   \n",
+       "\n",
+       "geo_id             UK  \n",
+       "report_date            \n",
+       "2020-12-21   0.000048  \n",
+       "2020-12-28   0.000056  \n",
+       "2021-01-04   0.000059  \n",
+       "2021-01-11   0.000096  \n",
+       "2021-01-18   0.000117  "
+      ]
+     },
+     "execution_count": 117,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_pc = deaths_pc_data.pivot(columns='geo_id', values='deaths_weekly_pc')\n",
+    "deaths_pc.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 118,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax = deaths_pc.loc['2020-03-15':].plot(figsize=(10, 6), title=\"Deaths per million, linear\")\n",
+    "ax.set_xlabel(f\"Date\")\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = deaths_pc[c].last_valid_index()\n",
+    "    ax.text(x = lvi + pd.Timedelta(days=1), y = deaths_pc[c][lvi], s = f\"{c}: {deaths_pc[c][lvi]*10**6:.0f}\")\n",
+    "# plt.savefig('covid_deaths_total_linear.png')    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 123,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax = deaths_pc.iloc[-6:].plot(figsize=(10, 6), title=\"Deaths per million, linear\")\n",
+    "ax.set_xlabel(f\"Date\")\n",
+    "for c in COUNTRIES_CORE:\n",
+    "    lvi = deaths_pc[c].last_valid_index()\n",
+    "    ax.text(x = lvi, y = deaths_pc[c][lvi], s = f\"{c}: {deaths_pc[c][lvi]*10**6:.0f}\")\n",
+    "# plt.savefig('covid_deaths_total_linear.png')    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "jupytext": {
+   "formats": "ipynb,md"
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/international_comparison.md b/international_comparison.md

new file mode 100644 (file)

index 0000000..801ee4c
--- /dev/null
+++ b/international_comparison.md
@@ -0,0 +1,193 @@
+---
+jupyter:
+  jupytext:
+    formats: ipynb,md
+    text_representation:
+      extension: .md
+      format_name: markdown
+      format_version: '1.2'
+      jupytext_version: 1.9.1
+  kernelspec:
+    display_name: Python 3
+    language: python
+    name: python3
+---
+
+<!-- #region Collapsed="false" -->
+Data from [European Centre for Disease Prevention and Control](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide)
+<!-- #endregion -->
+
+```python Collapsed="false"
+import itertools
+import collections
+import json
+import pandas as pd
+import numpy as np
+from scipy.stats import gmean
+import datetime
+
+from sqlalchemy.types import Integer, Text, String, DateTime, Date, Float
+from sqlalchemy import create_engine
+
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+%matplotlib inline
+%load_ext sql
+```
+
+```python Collapsed="false"
+connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'
+```
+
+```python Collapsed="false"
+%sql $connection_string
+```
+
+```python
+engine = create_engine(connection_string)
+```
+
+```python Collapsed="false"
+DEATH_COUNT_THRESHOLD = 10
+COUNTRIES_CORE = tuple(sorted('IT DE UK ES IE FR BE'.split()))
+COUNTRIES_NORDIC = tuple('SE NO DK FI UK'.split())
+COUNTRIES_FRIENDS = tuple('IT UK ES BE SI MX'.split())
+# COUNTRIES_FRIENDS = 'IT UK ES BE SI PT'.split()
+
+COUNTRIES_AMERICAS = ('AG', 'AR', 'AW', 'BS', 'BB', 'BZ', 'BM', 'BO', 'BR', 'VG', 'KY', # excluding Canada and USA
+       'CL', 'CO', 'CR', 'CU', 'CW', 'DM', 'DO', 'EC', 'SV', 'GL', 'GD', 'GT',
+       'GY', 'HT', 'HN', 'JM', 'MX', 'MS', 'NI', 'PA', 'PY', 'PE', 'PR', 'KN',
+       'LC', 'VC', 'SX', 'SR', 'TT', 'TC', 'VI', 'UY', 'VE')
+COUNTRIES_OF_INTEREST = tuple(set(COUNTRIES_CORE + COUNTRIES_FRIENDS))
+COUNTRIES_ALL = tuple(set(COUNTRIES_CORE + COUNTRIES_FRIENDS + COUNTRIES_NORDIC + COUNTRIES_AMERICAS))
+```
+
+```python Collapsed="false"
+# res = %sql select report_date, geo_id, deaths_weekly, culm_deaths from weekly_cases where geo_id in $COUNTRIES_CORE order by report_date, geo_id
+```
+
+```python Collapsed="false"
+# country_data = res.DataFrame()
+# country_data['report_date'] = country_data.report_date.astype('datetime64[ns]')
+# country_data.set_index('report_date', inplace=True)
+# country_data.tail(10)
+```
+
+```python
+query_string = f'''select report_date, geo_id, deaths_weekly, culm_deaths 
+from weekly_cases 
+where geo_id in {COUNTRIES_CORE} 
+order by report_date, geo_id'''
+
+country_data = pd.read_sql_query(query_string,
+                  engine,
+                  index_col = 'report_date',
+                  parse_dates = ['report_date']
+                 )
+```
+
+```python Collapsed="false"
+deaths_culm = country_data.pivot(columns='geo_id', values='culm_deaths')
+deaths_culm.tail()
+```
+
+```python Collapsed="false"
+deaths_culm.plot()
+```
+
+```python Collapsed="false"
+ax = deaths_culm.loc['2020-03-15':].plot(figsize=(10, 6), title="Total deaths, linear")
+ax.set_xlabel(f"Date")
+for c in COUNTRIES_CORE:
+    lvi = deaths_culm[c].last_valid_index()
+    ax.text(x = lvi + pd.Timedelta(days=1), y = deaths_culm[c][lvi], s = f"{c}: {deaths_culm[c][lvi]:.0f}")
+plt.savefig('covid_deaths_total_linear.png')    
+```
+
+```python Collapsed="false"
+deaths_weekly = country_data.pivot(columns='geo_id', values='deaths_weekly')
+deaths_weekly.tail()
+```
+
+```python Collapsed="false"
+deaths_weekly.plot()
+```
+
+```python Collapsed="false"
+ax = deaths_weekly.loc['2020-03-01':, COUNTRIES_CORE].plot(figsize=(10, 6), title="Deaths per week")
+ax.set_xlabel('Date')
+for c in COUNTRIES_CORE:
+    lvi = deaths_weekly[c].last_valid_index()
+    ax.text(x = lvi + pd.Timedelta(days=1), y = deaths_weekly[c][lvi], s = c)
+plt.savefig('covid_deaths_per_week.png') 
+```
+
+```python Collapsed="false"
+ax = deaths_weekly.iloc[-6:].plot(figsize=(10, 6), title="Deaths per week")#, ylim=(-10, 100))
+ax.set_xlabel("Date")
+
+text_x_pos = deaths_weekly.last_valid_index() + pd.Timedelta(days=0.5)
+
+for c in COUNTRIES_CORE:
+    lvi = deaths_weekly[c].last_valid_index()
+#     if c != 'ES':
+    ax.text(x = text_x_pos, y = deaths_weekly[c][lvi], s = f"{c}: {deaths_weekly[c][lvi]:.0f}")
+plt.savefig('deaths_by_date_last_6_weeks.png') 
+```
+
+```python
+query_string = f'''select report_date, geo_id, 
+(cast(deaths_weekly as float) / population_2019) deaths_weekly_pc,
+(cast(culm_deaths as float) / population_2019) as culm_deaths_pc
+from weekly_cases join countries using (geo_id)
+where  geo_id in {COUNTRIES_CORE} 
+order by report_date, geo_id'''
+
+deaths_pc_data = pd.read_sql_query(query_string,
+                  engine,
+                  index_col = 'report_date',
+                  parse_dates = ['report_date']
+                 )
+deaths_pc_data.tail()
+```
+
+```python Collapsed="false"
+deaths_pc_culm = deaths_pc_data.pivot(columns='geo_id', values='culm_deaths_pc')
+deaths_pc_culm.tail()
+```
+
+```python
+ax = deaths_pc_culm.loc['2020-03-15':].plot(figsize=(10, 6), title="Deaths per million, linear")
+ax.set_xlabel(f"Date")
+for c in COUNTRIES_CORE:
+    lvi = deaths_pc_culm[c].last_valid_index()
+    ax.text(x = lvi + pd.Timedelta(days=1), y = deaths_pc_culm[c][lvi], s = f"{c}: {deaths_pc_culm[c][lvi]*10**6:.0f}")
+# plt.savefig('covid_deaths_total_linear.png')    
+```
+
+```python Collapsed="false"
+deaths_pc = deaths_pc_data.pivot(columns='geo_id', values='deaths_weekly_pc')
+deaths_pc.tail()
+```
+
+```python
+ax = deaths_pc.loc['2020-03-15':].plot(figsize=(10, 6), title="Deaths per million, linear")
+ax.set_xlabel(f"Date")
+for c in COUNTRIES_CORE:
+    lvi = deaths_pc[c].last_valid_index()
+    ax.text(x = lvi + pd.Timedelta(days=1), y = deaths_pc[c][lvi], s = f"{c}: {deaths_pc[c][lvi]*10**6:.0f}")
+# plt.savefig('covid_deaths_total_linear.png')    
+```
+
+```python
+ax = deaths_pc.iloc[-6:].plot(figsize=(10, 6), title="Deaths per million, linear")
+ax.set_xlabel(f"Date")
+for c in COUNTRIES_CORE:
+    lvi = deaths_pc[c].last_valid_index()
+    ax.text(x = lvi, y = deaths_pc[c][lvi], s = f"{c}: {deaths_pc[c][lvi]*10**6:.0f}")
+# plt.savefig('covid_deaths_total_linear.png')    
+```
+
+```python
+
+```
diff --git a/international_comparison.py b/international_comparison.py

new file mode 100644 (file)

index 0000000..2135609
--- /dev/null
+++ b/international_comparison.py
@@ -0,0 +1,102 @@
+#!/usr/bin/env python
+# coding: utf-8
+# %%
+# Data from [European Centre for Disease Prevention and Control](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide)
+
+# %%
+import itertools
+import collections
+import json
+import pandas as pd
+import numpy as np
+from scipy.stats import gmean
+import datetime
+
+from sqlalchemy.types import Integer, Text, String, DateTime, Date, Float
+from sqlalchemy import create_engine
+
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+plt.ioff()
+
+
+# %%
+connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'
+
+
+# %%
+engine = create_engine(connection_string)
+
+
+# %%
+DEATH_COUNT_THRESHOLD = 10
+COUNTRIES_CORE = tuple(sorted('IT DE UK ES IE FR BE'.split()))
+COUNTRIES_NORDIC = tuple('SE NO DK FI UK'.split())
+COUNTRIES_FRIENDS = tuple('IT UK ES BE SI MX'.split())
+# COUNTRIES_FRIENDS = 'IT UK ES BE SI PT'.split()
+
+COUNTRIES_AMERICAS = ('AG', 'AR', 'AW', 'BS', 'BB', 'BZ', 'BM', 'BO', 'BR', 'VG', 'KY', # excluding Canada and USA
+       'CL', 'CO', 'CR', 'CU', 'CW', 'DM', 'DO', 'EC', 'SV', 'GL', 'GD', 'GT',
+       'GY', 'HT', 'HN', 'JM', 'MX', 'MS', 'NI', 'PA', 'PY', 'PE', 'PR', 'KN',
+       'LC', 'VC', 'SX', 'SR', 'TT', 'TC', 'VI', 'UY', 'VE')
+COUNTRIES_OF_INTEREST = tuple(set(COUNTRIES_CORE + COUNTRIES_FRIENDS))
+COUNTRIES_ALL = tuple(set(COUNTRIES_CORE + COUNTRIES_FRIENDS + COUNTRIES_NORDIC + COUNTRIES_AMERICAS))
+
+
+# %%
+query_string = f'''select report_date, geo_id, deaths_weekly, culm_deaths 
+from weekly_cases 
+where geo_id in {COUNTRIES_CORE} 
+order by report_date, geo_id'''
+
+country_data = pd.read_sql_query(query_string,
+                  engine,
+                  index_col = 'report_date',
+                  parse_dates = ['report_date']
+                 )
+
+
+# %%
+deaths_culm = country_data.pivot(columns='geo_id', values='culm_deaths')
+
+
+# %%
+ax = deaths_culm.loc['2020-03-15':].plot(figsize=(10, 6), title="Total deaths, linear")
+ax.set_xlabel(f"Date")
+for c in COUNTRIES_CORE:
+    lvi = deaths_culm[c].last_valid_index()
+    ax.text(x = lvi + pd.Timedelta(days=1), y = deaths_culm[c][lvi], s = f"{c}: {deaths_culm[c][lvi]:.0f}")
+plt.savefig('covid_deaths_total_linear.png')    
+
+
+# %%
+deaths_weekly = country_data.pivot(columns='geo_id', values='deaths_weekly')
+
+
+# %%
+ax = deaths_weekly.loc['2020-03-01':, COUNTRIES_CORE].plot(figsize=(10, 6), title="Deaths per week")
+ax.set_xlabel('Date')
+for c in COUNTRIES_CORE:
+    lvi = deaths_weekly[c].last_valid_index()
+    ax.text(x = lvi + pd.Timedelta(days=1), y = deaths_weekly[c][lvi], s = c)
+plt.savefig('covid_deaths_per_week.png') 
+
+
+# %%
+ax = deaths_weekly.iloc[-6:].plot(figsize=(10, 6), title="Deaths per week")#, ylim=(-10, 100))
+ax.set_xlabel("Date")
+
+text_x_pos = deaths_weekly.last_valid_index() + pd.Timedelta(days=0.5)
+
+for c in COUNTRIES_CORE:
+    lvi = deaths_weekly[c].last_valid_index()
+#     if c != 'ES':
+    ax.text(x = text_x_pos, y = deaths_weekly[c][lvi], s = f"{c}: {deaths_weekly[c][lvi]:.0f}")
+plt.savefig('deaths_by_date_last_6_weeks.png') 
+
+
+# %%
+
+
+
+
diff --git a/last_uk_date.js b/last_uk_date.js

deleted file mode 100644 (file)

index 35cb802..0000000
--- a/last_uk_date.js
+++ /dev/null
@@ -1 +0,0 @@
-document.write('19 August 2020');
-\ No newline at end of file
diff --git a/projected_deaths.js b/projected_deaths.js

deleted file mode 100644 (file)

index 10ec4e1..0000000
--- a/projected_deaths.js
+++ /dev/null
@@ -1 +0,0 @@
-document.write('41684');
-\ No newline at end of file
diff --git a/projected_excess_deaths.js b/projected_excess_deaths.js

deleted file mode 100644 (file)

index a50c533..0000000
--- a/projected_excess_deaths.js
+++ /dev/null
@@ -1 +0,0 @@
-document.write('65981');
-\ No newline at end of file
diff --git a/projection_date.js b/projection_date.js

deleted file mode 100644 (file)

index 90f9557..0000000
--- a/projection_date.js
+++ /dev/null
@@ -1 +0,0 @@
-document.write('13 September 2020');
-\ No newline at end of file
diff --git a/projection_length.js b/projection_length.js

deleted file mode 100644 (file)

index 96a356b..0000000
--- a/projection_length.js
+++ /dev/null
@@ -1 +0,0 @@
-document.write('24');
-\ No newline at end of file
diff --git a/publish.ipynb b/publish.ipynb

new file mode 100644 (file)

index 0000000..99b4bef
--- /dev/null
+++ b/publish.ipynb
@@ -0,0 +1,823 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "source": [
+    "Data from [European Centre for Disease Prevention and Control](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 192,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The sql extension is already loaded. To reload it, use:\n",
+      "  %reload_ext sql\n"
+     ]
+    }
+   ],
+   "source": [
+    "import itertools\n",
+    "import collections\n",
+    "import json\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "from scipy.stats import gmean\n",
+    "import datetime\n",
+    "\n",
+    "import matplotlib as mpl\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline\n",
+    "%load_ext sql"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 193,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 194,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Connected: covid@covid'"
+      ]
+     },
+     "execution_count": 194,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql $connection_string"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 195,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# DEATH_COUNT_THRESHOLD = 10\n",
+    "COUNTRIES_CORE = tuple('IT DE UK ES IE FR BE'.split())\n",
+    "# COUNTRIES_NORDIC = 'SE NO DK FI UK'.split()\n",
+    "# COUNTRIES_FRIENDS = 'IT UK ES BE SI MX'.split()\n",
+    "# # COUNTRIES_FRIENDS = 'IT UK ES BE SI PT'.split()\n",
+    "\n",
+    "# COUNTRIES_AMERICAS = ['AG', 'AR', 'AW', 'BS', 'BB', 'BZ', 'BM', 'BO', 'BR', 'VG', 'KY', # excluding Canada and USA\n",
+    "#        'CL', 'CO', 'CR', 'CU', 'CW', 'DM', 'DO', 'EC', 'SV', 'GL', 'GD', 'GT',\n",
+    "#        'GY', 'HT', 'HN', 'JM', 'MX', 'MS', 'NI', 'PA', 'PY', 'PE', 'PR', 'KN',\n",
+    "#        'LC', 'VC', 'SX', 'SR', 'TT', 'TC', 'VI', 'UY', 'VE']\n",
+    "# COUNTRIES_OF_INTEREST = list(set(COUNTRIES_CORE + COUNTRIES_FRIENDS))\n",
+    "# COUNTRIES_ALL = list(set(COUNTRIES_CORE + COUNTRIES_FRIENDS + COUNTRIES_NORDIC + COUNTRIES_AMERICAS))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "source": [
+    "# Write results to summary file"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 196,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "datetime.date(2021, 1, 26)"
+      ]
+     },
+     "execution_count": 196,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "last_uk_date = %sql select date from uk_data order by date desc limit 1\n",
+    "last_uk_date = last_uk_date[0][0]\n",
+    "last_uk_date"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 197,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "datetime.date(2021, 1, 18)"
+      ]
+     },
+     "execution_count": 197,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "last_intl_date = %sql select report_date from weekly_cases order by report_date desc limit 1\n",
+    "last_intl_date = last_intl_date[0][0]\n",
+    "last_intl_date"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 198,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "390 rows affected.\n",
+      "Returning data to local variable results\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%sql results << select date, new_cases, new_deaths \n",
+    "from uk_data \n",
+    "order by date"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 199,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>new_cases</th>\n",
+       "      <th>new_deaths</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>date</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2021-01-17</th>\n",
+       "      <td>28875.0</td>\n",
+       "      <td>671</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-18</th>\n",
+       "      <td>44732.0</td>\n",
+       "      <td>599</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-19</th>\n",
+       "      <td>39311.0</td>\n",
+       "      <td>1610</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-20</th>\n",
+       "      <td>35015.0</td>\n",
+       "      <td>1820</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-21</th>\n",
+       "      <td>31430.0</td>\n",
+       "      <td>1290</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-22</th>\n",
+       "      <td>29094.0</td>\n",
+       "      <td>1401</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-23</th>\n",
+       "      <td>20495.0</td>\n",
+       "      <td>1348</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-24</th>\n",
+       "      <td>14266.0</td>\n",
+       "      <td>610</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-25</th>\n",
+       "      <td>4482.0</td>\n",
+       "      <td>592</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-26</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1631</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            new_cases  new_deaths\n",
+       "date                             \n",
+       "2021-01-17    28875.0         671\n",
+       "2021-01-18    44732.0         599\n",
+       "2021-01-19    39311.0        1610\n",
+       "2021-01-20    35015.0        1820\n",
+       "2021-01-21    31430.0        1290\n",
+       "2021-01-22    29094.0        1401\n",
+       "2021-01-23    20495.0        1348\n",
+       "2021-01-24    14266.0         610\n",
+       "2021-01-25     4482.0         592\n",
+       "2021-01-26        NaN        1631"
+      ]
+     },
+     "execution_count": 199,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "uk_data = results.DataFrame()\n",
+    "uk_data['date'] = uk_data.date.astype('datetime64[ns]')\n",
+    "uk_data.set_index('date', inplace=True)\n",
+    "uk_data.tail(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 200,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "datetime.date(2021, 1, 26)"
+      ]
+     },
+     "execution_count": 200,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "most_recent_uk_date = %sql select max(date) from uk_data\n",
+    "most_recent_uk_date = most_recent_uk_date[0][0]\n",
+    "most_recent_uk_date"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 201,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "7 rows affected.\n",
+      "Returning data to local variable results\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%sql results << select geo_id, country_name, culm_deaths \n",
+    "from weekly_cases join countries using (geo_id)\n",
+    "where geo_id in :COUNTRIES_CORE \n",
+    "    and (geo_id, report_date) in (select geo_id, max(report_date) from weekly_cases group by geo_id)\n",
+    "order by geo_id"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 202,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "datetime.date(2020, 12, 27)"
+      ]
+     },
+     "execution_count": 202,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "thirty_days_ago = most_recent_uk_date - datetime.timedelta(days=30)\n",
+    "thirty_days_ago"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 203,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n",
+      " * postgresql://covid:***@localhost/covid\n",
+      "1 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "(100184, 29366, 1283174)"
+      ]
+     },
+     "execution_count": 203,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# thirty_days_ago = most_recent_uk_date - datetime.interval(days=30)\n",
+    "total_uk_deaths = %sql select sum(new_deaths) from uk_data\n",
+    "total_uk_deaths = total_uk_deaths[0][0]\n",
+    "deaths_in_past_month = %sql select sum(new_deaths) from uk_data where date > :thirty_days_ago\n",
+    "deaths_in_past_month = deaths_in_past_month[0][0]\n",
+    "cases_in_past_month = %sql select sum(new_cases) from uk_data where date > :thirty_days_ago\n",
+    "cases_in_past_month = cases_in_past_month[0][0]\n",
+    "total_uk_deaths, deaths_in_past_month, cases_in_past_month"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 204,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "with open('covid_summary.md', 'w') as f:\n",
+    "    f.write('% Covid death data summary\\n')\n",
+    "    f.write('% Neil Smith\\n')\n",
+    "    f.write(f'% Created on {datetime.datetime.now().strftime(\"%Y-%m-%d\")}\\n')\n",
+    "    f.write('\\n')       \n",
+    "    f.write(f'> Last UK data from {last_uk_date.strftime(\"%d %b %Y\")}. ')\n",
+    "    f.write(f' Last international data from {last_intl_date.strftime(\"%d %b %Y\")}.\\n')\n",
+    "    f.write('\\n')    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 205,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "with open('covid_summary.md', 'a') as f:\n",
+    "    f.write('## Headlines (UK data)\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('| []() | |\\n')\n",
+    "    f.write('|:---|---:|\\n')\n",
+    "    f.write(f'| Deaths reported so far | {total_uk_deaths} | \\n')\n",
+    "    f.write(f'| Deaths in last 30 days | {deaths_in_past_month} | \\n')\n",
+    "    f.write(f'| Cases in last 30 days  | {cases_in_past_month} | \\n')\n",
+    "#     f.write(f'| Total Covid deaths to date (estimated) | {uk_deaths_to_date:.0f} |\\n')\n",
+    "    f.write('\\n')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 206,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "with open('covid_summary.md', 'a') as f:\n",
+    "    f.write('## International comparison\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write(f'Based on weekly data. Last data from {last_intl_date.strftime(\"%d %b %Y\")}\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('### Total deaths\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('![Total deaths](covid_deaths_total_linear.png)\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('| Country ID | Country name | Total deaths |\\n')\n",
+    "    f.write('|:-----------|:-------------|-------------:|\\n')\n",
+    "    for c_id, c_name, t_deaths in results:\n",
+    "        f.write(f'| {c_id} | {c_name} | {t_deaths} |\\n')\n",
+    "    f.write('\\n')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 207,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# with open('covid_summary.md', 'a') as f:\n",
+    "#     f.write('## All-causes deaths, UK\\n')\n",
+    "#     f.write('\\n')\n",
+    "#     f.write('![All-causes deaths](deaths-radar.png)\\n')\n",
+    "#     f.write('\\n')\n",
+    "#     f.write('### True deaths\\n')\n",
+    "#     f.write('\\n')\n",
+    "#     f.write(f'The number of deaths reported in official statistics, {uk_covid_deaths}, is an underestimate '\n",
+    "#             'of the true number of Covid deaths.\\n'\n",
+    "#             'This is especially true early in the pandemic, approximately March to May 2020.\\n')\n",
+    "#     f.write('We can get a better understanding of the impact of Covid by looking at the number of deaths, '\n",
+    "#             'over and above what would be expected at each week of the year.\\n')\n",
+    "#     f.write(f'The ONS (and other bodies in Scotland and Northern Ireland) have released data on the number of deaths '\n",
+    "#             f'up to {pd.to_datetime(excess_deaths_data[\"end_date\"]).strftime(\"%d %B %Y\")}.\\n\\n')\n",
+    "#     f.write('If, for each of those weeks, I take the largest of the excess deaths or the reported Covid deaths, ')\n",
+    "#     f.write(f'I estimate there have been **{uk_deaths_to_date}** total deaths so far.\\n')\n",
+    "#     f.write('\\n')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 208,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "with open('covid_summary.md', 'a') as f:\n",
+    "    f.write('### Deaths per week\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('![Deaths per week](covid_deaths_per_week.png)\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('![Deaths per week, last 6 weeks](deaths_by_date_last_6_weeks.png)\\n')\n",
+    "    f.write('\\n')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 209,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "with open('covid_summary.md', 'a') as f:\n",
+    "    f.write('## UK data\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('### Total deaths\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write(f'Deaths reported up to {last_uk_date.strftime(\"%d %b %Y\")}: {total_uk_deaths}\\n')\n",
+    "    f.write('\\n')    \n",
+    "    f.write('![Total deaths](cases_and_deaths.png)\\n')\n",
+    "    f.write('\\n')    \n",
+    "    f.write('![Cases and deaths in last 60 days](cases_and_deaths_last_60_days.png)\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('![Deaths compared to past five years](deaths-radar-2020.png)\\n')\n",
+    "    f.write('\\n')\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 210,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "with open('hospital_normalisation_date.json') as f:\n",
+    "    hospital_normalisation_date_data = json.load(f)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 211,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "with open('covid_summary.md', 'a') as f:\n",
+    "    f.write('### Hospital care\\n')\n",
+    "    f.write(f'Based on a 7-day moving average\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('![Cases, admissions, deaths](cases_admissions_deaths.png)\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('Due to the large scale differences between the three '\n",
+    "            'measures, they are all normalised to show changes ')\n",
+    "    f.write(f'since {pd.to_datetime(hospital_normalisation_date_data[\"hospital_normalisation_date\"]).strftime(\"%d %B %Y\")}.\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('People in hospital, and on mechanical ventilators\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('![People in hospital and on mechancial ventilators](people_in_hospital.png)\\n')\n",
+    "    f.write('\\n')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 212,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "with open('covid_summary.md', 'a') as f:\n",
+    "    f.write('### Testing effectiveness\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('A question about testing is whether more detected cases is a result of more tests being '\n",
+    "            'done or is because the number of cases is increasing. One way of telling the differeence '\n",
+    "            'is by looking at the fraction of tests that are positive.\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('![Positive tests and cases](tests_and_cases.png)\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('Numbers of positive tests and cases, '\n",
+    "            '7-day moving average.\\n'\n",
+    "            'Note the different y-axes\\n')\n",
+    "    f.write('\\n')    \n",
+    "    f.write('![Fraction of tests with positive result](fraction_positive_tests.png)\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('Fraction of tests with a positive result, both daily figures and '\n",
+    "            '7-day moving average.\\n')\n",
+    "    f.write('\\n')    \n",
+    "    f.write('\\n')\n",
+    "    f.write('![Tests against fraction positive, trajectory](fraction_positive_tests_vs_tests.png)\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('The trajectory of tests done vs fraction positive tests.\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('Points higher indicate more tests; points to the right indicate more positive tests.'\n",
+    "            'More tests being done with the same infection prevelance will move the point up '\n",
+    "            'and to the left.\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('![Tests against fraction positive, trajectory](tests_vs_fraction_positive_animation.png)\\n')\n",
+    "    f.write('\\n')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 213,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "with open('covid_summary.md', 'a') as f:\n",
+    "    f.write('# Data sources\\n')\n",
+    "    f.write('\\n')\n",
+    "    f.write('> Covid data from [European Centre for Disease Prevention and Control](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide)\\n')\n",
+    "    f.write('\\n')    \n",
+    "    f.write(\"\"\"> Population data from:\n",
+    "\n",
+    "* [Office of National Statistics](https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/weeklyprovisionalfiguresondeathsregisteredinenglandandwales) (Endland and Wales) Weeks start on a Saturday.\n",
+    "* [Northern Ireland Statistics and Research Agency](https://www.nisra.gov.uk/publications/weekly-deaths) (Northern Ireland). Weeks start on a Saturday. Note that the week numbers don't match the England and Wales data.\n",
+    "* [National Records of Scotland](https://www.nrscotland.gov.uk/statistics-and-data/statistics/statistics-by-theme/vital-events/general-publications/weekly-and-monthly-data-on-births-and-deaths/weekly-data-on-births-and-deaths) (Scotland). Note that Scotland uses ISO8601 week numbers, which start on a Monday.\"\"\")\n",
+    "    \n",
+    "    f.write('\\n\\n')\n",
+    "    f.write('> [Source code available](https://git.njae.me.uk/?p=covid19.git;a=tree)\\n')\n",
+    "    f.write('\\n') \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 214,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "!pandoc --toc -s covid_summary.md > covid_summary.html"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 215,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "covid_summary.html                            100%   10KB 287.3KB/s   00:00    \n",
+      "covid_deaths_total_linear.png                 100%   45KB   1.8MB/s   00:00    \n",
+      "cases_and_deaths.png                          100%   62KB   5.3MB/s   00:00    \n",
+      "cases_and_deaths_last_60_days.png             100%   62KB   8.4MB/s   00:00    \n",
+      "deaths-radar-2020.png                         100%  199KB   5.4MB/s   00:00    \n",
+      "covid_deaths_per_week.png                     100%   61KB   8.0MB/s   00:00    \n",
+      "fraction_positive_tests.png                   100%   59KB   2.8MB/s   00:00    \n",
+      "tests_and_cases.png                           100%   40KB   5.4MB/s   00:00    \n",
+      "deaths_by_date_last_6_weeks.png               100%   33KB   5.4MB/s   00:00    \n",
+      "fraction_positive_tests_vs_tests.png          100%   41KB   7.7MB/s   00:00    \n",
+      "tests_vs_fraction_positive_animation.png      100% 1982KB  10.3MB/s   00:00    \n",
+      "people_in_hospital.png                        100%   42KB   8.0MB/s   00:00    \n",
+      "cases_admissions_deaths.png                   100%   44KB   2.3MB/s   00:00    \n"
+     ]
+    }
+   ],
+   "source": [
+    "!scp covid_summary.html neil@ogedei:/var/www/scripts.njae.me.uk/covid/index.html\n",
+    "!scp covid_deaths_total_linear.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp cases_and_deaths.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp cases_and_deaths_last_60_days.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "# !scp deaths-radar.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp deaths-radar-2020.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp covid_deaths_per_week.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp fraction_positive_tests.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/    \n",
+    "!scp tests_and_cases.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp deaths_by_date_last_6_weeks.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp fraction_positive_tests_vs_tests.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp tests_vs_fraction_positive_animation.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/   \n",
+    "!scp people_in_hospital.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp cases_admissions_deaths.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 216,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "with open('uk_covid_deaths.js', 'w') as f:\n",
+    "    f.write(f\"document.write('{total_uk_deaths}');\")\n",
+    "    \n",
+    "with open('uk_deaths_30_days.js', 'w') as f:\n",
+    "    f.write(f\"document.write('{deaths_in_past_month}');\")\n",
+    "\n",
+    "with open('uk_cases_30_days.js', 'w') as f:\n",
+    "    f.write(f\"document.write('{cases_in_past_month}');\")    \n",
+    "    \n",
+    "# with open('estimated_total_deaths.js', 'w') as f:\n",
+    "#     f.write(f\"document.write('{uk_deaths_to_date:.0f}');\")\n",
+    "\n",
+    "# edut = pd.to_datetime(excess_deaths_data[\"end_date\"]).strftime('%d %B %Y')\n",
+    "# with open('excess_deaths_upto.js', 'w') as f:\n",
+    "#     f.write(f\"document.write('{edut}');\")\n",
+    "    \n",
+    "with open('last_uk_date.js', 'w') as f:\n",
+    "    f.write(f\"document.write('{pd.to_datetime(last_uk_date).strftime('%d %B %Y')}');\")\n",
+    "\n",
+    "with open('last_intl_date.js', 'w') as f:\n",
+    "    f.write(f\"document.write('{pd.to_datetime(last_intl_date).strftime('%d %B %Y')}');\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 217,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# pd.to_datetime(excess_deaths_upto).strftime('%d %B %Y')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 218,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "uk_covid_deaths.js                            100%   25     2.0KB/s   00:00    \n",
+      "uk_deaths_30_days.js                          100%   24     1.2KB/s   00:00    \n",
+      "uk_cases_30_days.js                           100%   26    21.3KB/s   00:00    \n",
+      "last_uk_date.js                               100%   34     2.4KB/s   00:00    \n",
+      "last_intl_date.js                             100%   34     3.8KB/s   00:00    \n",
+      "hospital_normalisation_date.js                100%   33    29.1KB/s   00:00    \n"
+     ]
+    }
+   ],
+   "source": [
+    "!scp uk_covid_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp uk_deaths_30_days.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp uk_cases_30_days.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "# !scp estimated_total_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "# !scp excess_deaths_upto.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp last_uk_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp last_intl_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/\n",
+    "!scp hospital_normalisation_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "jupytext": {
+   "formats": "ipynb,md"
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/publish.md b/publish.md

new file mode 100644 (file)

index 0000000..6b4ed59
--- /dev/null
+++ b/publish.md
@@ -0,0 +1,343 @@
+---
+jupyter:
+  jupytext:
+    formats: ipynb,md
+    text_representation:
+      extension: .md
+      format_name: markdown
+      format_version: '1.2'
+      jupytext_version: 1.9.1
+  kernelspec:
+    display_name: Python 3
+    language: python
+    name: python3
+---
+
+<!-- #region Collapsed="false" -->
+Data from [European Centre for Disease Prevention and Control](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide)
+<!-- #endregion -->
+
+```python Collapsed="false"
+import itertools
+import collections
+import json
+import pandas as pd
+import numpy as np
+from scipy.stats import gmean
+import datetime
+
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+%matplotlib inline
+%load_ext sql
+```
+
+```python Collapsed="false"
+connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'
+```
+
+```python Collapsed="false"
+%sql $connection_string
+```
+
+```python Collapsed="false"
+# DEATH_COUNT_THRESHOLD = 10
+COUNTRIES_CORE = tuple('IT DE UK ES IE FR BE'.split())
+# COUNTRIES_NORDIC = 'SE NO DK FI UK'.split()
+# COUNTRIES_FRIENDS = 'IT UK ES BE SI MX'.split()
+# # COUNTRIES_FRIENDS = 'IT UK ES BE SI PT'.split()
+
+# COUNTRIES_AMERICAS = ['AG', 'AR', 'AW', 'BS', 'BB', 'BZ', 'BM', 'BO', 'BR', 'VG', 'KY', # excluding Canada and USA
+#        'CL', 'CO', 'CR', 'CU', 'CW', 'DM', 'DO', 'EC', 'SV', 'GL', 'GD', 'GT',
+#        'GY', 'HT', 'HN', 'JM', 'MX', 'MS', 'NI', 'PA', 'PY', 'PE', 'PR', 'KN',
+#        'LC', 'VC', 'SX', 'SR', 'TT', 'TC', 'VI', 'UY', 'VE']
+# COUNTRIES_OF_INTEREST = list(set(COUNTRIES_CORE + COUNTRIES_FRIENDS))
+# COUNTRIES_ALL = list(set(COUNTRIES_CORE + COUNTRIES_FRIENDS + COUNTRIES_NORDIC + COUNTRIES_AMERICAS))
+```
+
+<!-- #region Collapsed="false" -->
+# Write results to summary file
+<!-- #endregion -->
+
+```python Collapsed="false"
+last_uk_date = %sql select date from uk_data order by date desc limit 1
+last_uk_date = last_uk_date[0][0]
+last_uk_date
+```
+
+```python Collapsed="false"
+last_intl_date = %sql select report_date from weekly_cases order by report_date desc limit 1
+last_intl_date = last_intl_date[0][0]
+last_intl_date
+```
+
+```sql magic_args="results << select date, new_cases, new_deaths "
+from uk_data 
+order by date
+```
+
+```python
+uk_data = results.DataFrame()
+uk_data['date'] = uk_data.date.astype('datetime64[ns]')
+uk_data.set_index('date', inplace=True)
+uk_data.tail(10)
+```
+
+```python
+most_recent_uk_date = %sql select max(date) from uk_data
+most_recent_uk_date = most_recent_uk_date[0][0]
+most_recent_uk_date
+```
+
+```sql Collapsed="false" magic_args="results << select geo_id, country_name, culm_deaths "
+from weekly_cases join countries using (geo_id)
+where geo_id in :COUNTRIES_CORE 
+    and (geo_id, report_date) in (select geo_id, max(report_date) from weekly_cases group by geo_id)
+order by geo_id
+```
+
+```python
+thirty_days_ago = most_recent_uk_date - datetime.timedelta(days=30)
+thirty_days_ago
+```
+
+```python
+# thirty_days_ago = most_recent_uk_date - datetime.interval(days=30)
+total_uk_deaths = %sql select sum(new_deaths) from uk_data
+total_uk_deaths = total_uk_deaths[0][0]
+deaths_in_past_month = %sql select sum(new_deaths) from uk_data where date > :thirty_days_ago
+deaths_in_past_month = deaths_in_past_month[0][0]
+cases_in_past_month = %sql select sum(new_cases) from uk_data where date > :thirty_days_ago
+cases_in_past_month = cases_in_past_month[0][0]
+total_uk_deaths, deaths_in_past_month, cases_in_past_month
+```
+
+```python Collapsed="false"
+with open('covid_summary.md', 'w') as f:
+    f.write('% Covid death data summary\n')
+    f.write('% Neil Smith\n')
+    f.write(f'% Created on {datetime.datetime.now().strftime("%Y-%m-%d")}\n')
+    f.write('\n')       
+    f.write(f'> Last UK data from {last_uk_date.strftime("%d %b %Y")}. ')
+    f.write(f' Last international data from {last_intl_date.strftime("%d %b %Y")}.\n')
+    f.write('\n')    
+```
+
+```python Collapsed="false"
+with open('covid_summary.md', 'a') as f:
+    f.write('## Headlines (UK data)\n')
+    f.write('\n')
+    f.write('| []() | |\n')
+    f.write('|:---|---:|\n')
+    f.write(f'| Deaths reported so far | {total_uk_deaths} | \n')
+    f.write(f'| Deaths in last 30 days | {deaths_in_past_month} | \n')
+    f.write(f'| Cases in last 30 days  | {cases_in_past_month} | \n')
+#     f.write(f'| Total Covid deaths to date (estimated) | {uk_deaths_to_date:.0f} |\n')
+    f.write('\n')
+```
+
+```python Collapsed="false"
+with open('covid_summary.md', 'a') as f:
+    f.write('## International comparison\n')
+    f.write('\n')
+    f.write(f'Based on weekly data. Last data from {last_intl_date.strftime("%d %b %Y")}\n')
+    f.write('\n')
+    f.write('### Total deaths\n')
+    f.write('\n')
+    f.write('![Total deaths](covid_deaths_total_linear.png)\n')
+    f.write('\n')
+    f.write('| Country ID | Country name | Total deaths |\n')
+    f.write('|:-----------|:-------------|-------------:|\n')
+    for c_id, c_name, t_deaths in results:
+        f.write(f'| {c_id} | {c_name} | {t_deaths} |\n')
+    f.write('\n')
+```
+
+```python Collapsed="false"
+# with open('covid_summary.md', 'a') as f:
+#     f.write('## All-causes deaths, UK\n')
+#     f.write('\n')
+#     f.write('![All-causes deaths](deaths-radar.png)\n')
+#     f.write('\n')
+#     f.write('### True deaths\n')
+#     f.write('\n')
+#     f.write(f'The number of deaths reported in official statistics, {uk_covid_deaths}, is an underestimate '
+#             'of the true number of Covid deaths.\n'
+#             'This is especially true early in the pandemic, approximately March to May 2020.\n')
+#     f.write('We can get a better understanding of the impact of Covid by looking at the number of deaths, '
+#             'over and above what would be expected at each week of the year.\n')
+#     f.write(f'The ONS (and other bodies in Scotland and Northern Ireland) have released data on the number of deaths '
+#             f'up to {pd.to_datetime(excess_deaths_data["end_date"]).strftime("%d %B %Y")}.\n\n')
+#     f.write('If, for each of those weeks, I take the largest of the excess deaths or the reported Covid deaths, ')
+#     f.write(f'I estimate there have been **{uk_deaths_to_date}** total deaths so far.\n')
+#     f.write('\n')
+```
+
+```python Collapsed="false"
+with open('covid_summary.md', 'a') as f:
+    f.write('### Deaths per week\n')
+    f.write('\n')
+    f.write('![Deaths per week](covid_deaths_per_week.png)\n')
+    f.write('\n')
+    f.write('![Deaths per week, last 6 weeks](deaths_by_date_last_6_weeks.png)\n')
+    f.write('\n')
+```
+
+```python
+with open('covid_summary.md', 'a') as f:
+    f.write('## UK data\n')
+    f.write('\n')
+    f.write('### Total deaths\n')
+    f.write('\n')
+    f.write(f'Deaths reported up to {last_uk_date.strftime("%d %b %Y")}: {total_uk_deaths}\n')
+    f.write('\n')    
+    f.write('![Total deaths](cases_and_deaths.png)\n')
+    f.write('\n')    
+    f.write('![Cases and deaths in last 60 days](cases_and_deaths_last_60_days.png)\n')
+    f.write('\n')
+    f.write('![Deaths compared to past five years](deaths-radar-2020.png)\n')
+    f.write('\n')
+    
+```
+
+```python Collapsed="false"
+with open('hospital_normalisation_date.json') as f:
+    hospital_normalisation_date_data = json.load(f)
+```
+
+```python Collapsed="false"
+with open('covid_summary.md', 'a') as f:
+    f.write('### Hospital care\n')
+    f.write(f'Based on a 7-day moving average\n')
+    f.write('\n')
+    f.write('![Cases, admissions, deaths](cases_admissions_deaths.png)\n')
+    f.write('\n')
+    f.write('Due to the large scale differences between the three '
+            'measures, they are all normalised to show changes ')
+    f.write(f'since {pd.to_datetime(hospital_normalisation_date_data["hospital_normalisation_date"]).strftime("%d %B %Y")}.\n')
+    f.write('\n')
+    f.write('People in hospital, and on mechanical ventilators\n')
+    f.write('\n')
+    f.write('![People in hospital and on mechancial ventilators](people_in_hospital.png)\n')
+    f.write('\n')
+```
+
+```python Collapsed="false"
+with open('covid_summary.md', 'a') as f:
+    f.write('### Testing effectiveness\n')
+    f.write('\n')
+    f.write('A question about testing is whether more detected cases is a result of more tests being '
+            'done or is because the number of cases is increasing. One way of telling the differeence '
+            'is by looking at the fraction of tests that are positive.\n')
+    f.write('\n')
+    f.write('![Positive tests and cases](tests_and_cases.png)\n')
+    f.write('\n')
+    f.write('Numbers of positive tests and cases, '
+            '7-day moving average.\n'
+            'Note the different y-axes\n')
+    f.write('\n')    
+    f.write('![Fraction of tests with positive result](fraction_positive_tests.png)\n')
+    f.write('\n')
+    f.write('Fraction of tests with a positive result, both daily figures and '
+            '7-day moving average.\n')
+    f.write('\n')    
+    f.write('\n')
+    f.write('![Tests against fraction positive, trajectory](fraction_positive_tests_vs_tests.png)\n')
+    f.write('\n')
+    f.write('The trajectory of tests done vs fraction positive tests.\n')
+    f.write('\n')
+    f.write('Points higher indicate more tests; points to the right indicate more positive tests.'
+            'More tests being done with the same infection prevelance will move the point up '
+            'and to the left.\n')
+    f.write('\n')
+    f.write('\n')
+    f.write('![Tests against fraction positive, trajectory](tests_vs_fraction_positive_animation.png)\n')
+    f.write('\n')
+```
+
+```python Collapsed="false"
+
+```
+
+```python Collapsed="false"
+with open('covid_summary.md', 'a') as f:
+    f.write('# Data sources\n')
+    f.write('\n')
+    f.write('> Covid data from [European Centre for Disease Prevention and Control](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide)\n')
+    f.write('\n')    
+    f.write("""> Population data from:
+
+* [Office of National Statistics](https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/weeklyprovisionalfiguresondeathsregisteredinenglandandwales) (Endland and Wales) Weeks start on a Saturday.
+* [Northern Ireland Statistics and Research Agency](https://www.nisra.gov.uk/publications/weekly-deaths) (Northern Ireland). Weeks start on a Saturday. Note that the week numbers don't match the England and Wales data.
+* [National Records of Scotland](https://www.nrscotland.gov.uk/statistics-and-data/statistics/statistics-by-theme/vital-events/general-publications/weekly-and-monthly-data-on-births-and-deaths/weekly-data-on-births-and-deaths) (Scotland). Note that Scotland uses ISO8601 week numbers, which start on a Monday.""")
+    
+    f.write('\n\n')
+    f.write('> [Source code available](https://git.njae.me.uk/?p=covid19.git;a=tree)\n')
+    f.write('\n') 
+
+```
+
+```python Collapsed="false"
+!pandoc --toc -s covid_summary.md > covid_summary.html
+```
+
+```python Collapsed="false"
+!scp covid_summary.html neil@ogedei:/var/www/scripts.njae.me.uk/covid/index.html
+!scp covid_deaths_total_linear.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp cases_and_deaths.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp cases_and_deaths_last_60_days.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+# !scp deaths-radar.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp deaths-radar-2020.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp covid_deaths_per_week.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp fraction_positive_tests.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/    
+!scp tests_and_cases.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp deaths_by_date_last_6_weeks.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp fraction_positive_tests_vs_tests.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp tests_vs_fraction_positive_animation.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/   
+!scp people_in_hospital.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp cases_admissions_deaths.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+```
+
+```python Collapsed="false"
+with open('uk_covid_deaths.js', 'w') as f:
+    f.write(f"document.write('{total_uk_deaths}');")
+    
+with open('uk_deaths_30_days.js', 'w') as f:
+    f.write(f"document.write('{deaths_in_past_month}');")
+
+with open('uk_cases_30_days.js', 'w') as f:
+    f.write(f"document.write('{cases_in_past_month}');")    
+    
+# with open('estimated_total_deaths.js', 'w') as f:
+#     f.write(f"document.write('{uk_deaths_to_date:.0f}');")
+
+# edut = pd.to_datetime(excess_deaths_data["end_date"]).strftime('%d %B %Y')
+# with open('excess_deaths_upto.js', 'w') as f:
+#     f.write(f"document.write('{edut}');")
+    
+with open('last_uk_date.js', 'w') as f:
+    f.write(f"document.write('{pd.to_datetime(last_uk_date).strftime('%d %B %Y')}');")
+
+with open('last_intl_date.js', 'w') as f:
+    f.write(f"document.write('{pd.to_datetime(last_intl_date).strftime('%d %B %Y')}');")
+
+```
+
+```python Collapsed="false"
+# pd.to_datetime(excess_deaths_upto).strftime('%d %B %Y')
+```
+
+```python Collapsed="false"
+!scp uk_covid_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp uk_deaths_30_days.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp uk_cases_30_days.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+# !scp estimated_total_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+# !scp excess_deaths_upto.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp last_uk_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp last_intl_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+!scp hospital_normalisation_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+```
+
+```python Collapsed="false"
+
+```
diff --git a/publish.py b/publish.py

new file mode 100644 (file)

index 0000000..8ed4adb
--- /dev/null
+++ b/publish.py
@@ -0,0 +1,273 @@
+#!/usr/bin/env python
+# coding: utf-8
+# %%
+# Data from [European Centre for Disease Prevention and Control](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide)
+
+# %%
+import itertools
+import collections
+import json
+import pandas as pd
+import numpy as np
+from scipy.stats import gmean
+import datetime
+import sqlalchemy
+import os
+
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+
+
+# %%
+connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'
+
+
+# %%
+engine = sqlalchemy.create_engine(connection_string)
+
+
+# %%
+# DEATH_COUNT_THRESHOLD = 10
+COUNTRIES_CORE = tuple('IT DE UK ES IE FR BE'.split())
+# COUNTRIES_NORDIC = 'SE NO DK FI UK'.split()
+# COUNTRIES_FRIENDS = 'IT UK ES BE SI MX'.split()
+# # COUNTRIES_FRIENDS = 'IT UK ES BE SI PT'.split()
+
+# COUNTRIES_AMERICAS = ['AG', 'AR', 'AW', 'BS', 'BB', 'BZ', 'BM', 'BO', 'BR', 'VG', 'KY', # excluding Canada and USA
+#        'CL', 'CO', 'CR', 'CU', 'CW', 'DM', 'DO', 'EC', 'SV', 'GL', 'GD', 'GT',
+#        'GY', 'HT', 'HN', 'JM', 'MX', 'MS', 'NI', 'PA', 'PY', 'PE', 'PR', 'KN',
+#        'LC', 'VC', 'SX', 'SR', 'TT', 'TC', 'VI', 'UY', 'VE']
+# COUNTRIES_OF_INTEREST = list(set(COUNTRIES_CORE + COUNTRIES_FRIENDS))
+# COUNTRIES_ALL = list(set(COUNTRIES_CORE + COUNTRIES_FRIENDS + COUNTRIES_NORDIC + COUNTRIES_AMERICAS))
+
+
+# # Write results to summary file
+
+# %%
+def singleton_sql_value(engine, query_string):
+    with engine.connect() as conn: 
+        result = conn.execute(query_string)
+    return result.next()[0]
+
+
+# %%
+last_uk_date = singleton_sql_value(engine, 'select max(date) from uk_data')
+
+
+# %%
+last_intl_date = singleton_sql_value(engine, 'select max(report_date) from weekly_cases')
+
+
+# %%
+thirty_days_ago = last_uk_date - datetime.timedelta(days=30)
+
+
+# %%
+total_uk_deaths = singleton_sql_value(engine, 'select sum(new_deaths) from uk_data')
+deaths_in_past_month = singleton_sql_value(engine, f"select sum(new_deaths) from uk_data where date > '{thirty_days_ago.isoformat()}'")
+cases_in_past_month = singleton_sql_value(engine, f"select sum(new_cases) from uk_data where date > '{thirty_days_ago.isoformat()}'")
+total_uk_deaths, deaths_in_past_month, cases_in_past_month
+
+
+# %%
+with open('covid_summary.md', 'w') as f:
+    f.write('% Covid death data summary\n')
+    f.write('% Neil Smith\n')
+    f.write(f'% Created on {datetime.datetime.now().strftime("%Y-%m-%d")}\n')
+    f.write('\n')       
+    f.write(f'> Last UK data from {last_uk_date.strftime("%d %b %Y")}. ')
+    f.write(f' Last international data from {last_intl_date.strftime("%d %b %Y")}.\n')
+    f.write('\n')    
+
+
+# %%
+with open('covid_summary.md', 'a') as f:
+    f.write('## Headlines (UK data)\n')
+    f.write('\n')
+    f.write('| []() | |\n')
+    f.write('|:---|---:|\n')
+    f.write(f'| Deaths reported so far | {total_uk_deaths} | \n')
+    f.write(f'| Deaths in last 30 days | {deaths_in_past_month} | \n')
+    f.write(f'| Cases in last 30 days  | {cases_in_past_month} | \n')
+#     f.write(f'| Total Covid deaths to date (estimated) | {uk_deaths_to_date:.0f} |\n')
+    f.write('\n')
+
+
+# %%
+query_string = f'''select geo_id, country_name, culm_deaths 
+from weekly_cases join countries using (geo_id)
+where geo_id in {COUNTRIES_CORE} 
+    and report_date = '{last_intl_date.isoformat()}'
+order by geo_id'''
+
+with engine.connect() as conn: 
+    results = list(conn.execute(query_string))
+results
+
+# %%
+with open('covid_summary.md', 'a') as f:
+    f.write('## International comparison\n')
+    f.write('\n')
+    f.write(f'Based on weekly data. Last data from {last_intl_date.strftime("%d %b %Y")}\n')
+    f.write('\n')
+    f.write('### Total deaths\n')
+    f.write('\n')
+    f.write('![Total deaths](covid_deaths_total_linear.png)\n')
+    f.write('\n')
+    f.write('| Country ID | Country name | Total deaths |\n')
+    f.write('|:-----------|:-------------|-------------:|\n')
+    for c_id, c_name, t_deaths in results:
+        f.write(f'| {c_id} | {c_name} | {t_deaths} |\n')
+    f.write('\n')
+
+
+# %%
+with open('covid_summary.md', 'a') as f:
+    f.write('### Deaths per week\n')
+    f.write('\n')
+    f.write('![Deaths per week](covid_deaths_per_week.png)\n')
+    f.write('\n')
+    f.write('![Deaths per week, last 6 weeks](deaths_by_date_last_6_weeks.png)\n')
+    f.write('\n')
+
+
+# %%
+with open('covid_summary.md', 'a') as f:
+    f.write('## UK data\n')
+    f.write('\n')
+    f.write('### Total deaths\n')
+    f.write('\n')
+    f.write(f'Deaths reported up to {last_uk_date.strftime("%d %b %Y")}: {total_uk_deaths}\n')
+    f.write('\n')    
+    f.write('![Total deaths](cases_and_deaths.png)\n')
+    f.write('\n')    
+    f.write('![Cases and deaths in last 60 days](cases_and_deaths_last_60_days.png)\n')
+    f.write('\n')
+    f.write('![Deaths compared to past five years](deaths-radar-2021.png)\n')
+    f.write('\n')
+
+# %%
+with open('hospital_normalisation_date.json') as f:
+    hospital_normalisation_date_data = json.load(f)
+
+
+# %%
+with open('covid_summary.md', 'a') as f:
+    f.write('### Hospital care\n')
+    f.write(f'Based on a 7-day moving average\n')
+    f.write('\n')
+    f.write('![Cases, admissions, deaths](cases_admissions_deaths.png)\n')
+    f.write('\n')
+    f.write('Due to the large scale differences between the three '
+            'measures, they are all normalised to show changes ')
+    f.write(f'since {pd.to_datetime(hospital_normalisation_date_data["hospital_normalisation_date"]).strftime("%d %B %Y")}.\n')
+    f.write('\n')
+    f.write('People in hospital, and on mechanical ventilators\n')
+    f.write('\n')
+    f.write('![People in hospital and on mechancial ventilators](people_in_hospital.png)\n')
+    f.write('\n')
+
+
+# %%
+with open('covid_summary.md', 'a') as f:
+    f.write('### Testing effectiveness\n')
+    f.write('\n')
+    f.write('A question about testing is whether more detected cases is a result of more tests being '
+            'done or is because the number of cases is increasing. One way of telling the differeence '
+            'is by looking at the fraction of tests that are positive.\n')
+    f.write('\n')
+    f.write('![Positive tests and cases](tests_and_cases.png)\n')
+    f.write('\n')
+    f.write('Numbers of positive tests and cases, '
+            '7-day moving average.\n'
+            'Note the different y-axes\n')
+    f.write('\n')    
+    f.write('![Fraction of tests with positive result](fraction_positive_tests.png)\n')
+    f.write('\n')
+    f.write('Fraction of tests with a positive result, both daily figures and '
+            '7-day moving average.\n')
+    f.write('\n')    
+    f.write('\n')
+    f.write('![Tests against fraction positive, trajectory](fraction_positive_tests_vs_tests.png)\n')
+    f.write('\n')
+    f.write('The trajectory of tests done vs fraction positive tests.\n')
+    f.write('\n')
+    f.write('Points higher indicate more tests; points to the right indicate more positive tests.'
+            'More tests being done with the same infection prevelance will move the point up '
+            'and to the left.\n')
+    f.write('\n')
+    f.write('\n')
+    f.write('![Tests against fraction positive, trajectory](tests_vs_fraction_positive_animation.png)\n')
+    f.write('\n')
+
+
+# %%
+with open('covid_summary.md', 'a') as f:
+    f.write('# Data sources\n')
+    f.write('\n')
+    f.write('> Covid data from [European Centre for Disease Prevention and Control](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide)\n')
+    f.write('\n')    
+    f.write("""> Population data from:
+
+* [Office of National Statistics](https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/weeklyprovisionalfiguresondeathsregisteredinenglandandwales) (Endland and Wales) Weeks start on a Saturday.
+* [Northern Ireland Statistics and Research Agency](https://www.nisra.gov.uk/publications/weekly-deaths) (Northern Ireland). Weeks start on a Saturday. Note that the week numbers don't match the England and Wales data.
+* [National Records of Scotland](https://www.nrscotland.gov.uk/statistics-and-data/statistics/statistics-by-theme/vital-events/general-publications/weekly-and-monthly-data-on-births-and-deaths/weekly-data-on-births-and-deaths) (Scotland). Note that Scotland uses ISO8601 week numbers, which start on a Monday.""")
+    
+    f.write('\n\n')
+    f.write('> [Source code available](https://git.njae.me.uk/?p=covid19.git;a=tree)\n')
+    f.write('\n') 
+
+
+# %%
+os.system('pandoc --toc -s covid_summary.md > covid_summary.html')
+
+
+# %%
+os.system('scp covid_summary.html neil@ogedei:/var/www/scripts.njae.me.uk/covid/index.html')
+os.system('scp covid_deaths_total_linear.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp cases_and_deaths.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp cases_and_deaths_last_60_days.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp deaths-radar-2021.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp covid_deaths_per_week.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp fraction_positive_tests.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/    ')
+os.system('scp tests_and_cases.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp deaths_by_date_last_6_weeks.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp fraction_positive_tests_vs_tests.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp tests_vs_fraction_positive_animation.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/   ')
+os.system('scp people_in_hospital.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp cases_admissions_deaths.png neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+
+
+# %%
+with open('uk_covid_deaths.js', 'w') as f:
+    f.write(f"document.write('{total_uk_deaths}');")
+    
+with open('uk_deaths_30_days.js', 'w') as f:
+    f.write(f"document.write('{deaths_in_past_month}');")
+
+with open('uk_cases_30_days.js', 'w') as f:
+    f.write(f"document.write('{cases_in_past_month}');")    
+
+with open('last_uk_date.js', 'w') as f:
+    f.write(f"document.write('{pd.to_datetime(last_uk_date).strftime('%d %B %Y')}');")
+
+with open('last_intl_date.js', 'w') as f:
+    f.write(f"document.write('{pd.to_datetime(last_intl_date).strftime('%d %B %Y')}');")
+
+
+# %%
+os.system('scp uk_covid_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp uk_deaths_30_days.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp uk_cases_30_days.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+# # !scp estimated_total_deaths.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+# # !scp excess_deaths_upto.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/
+os.system('scp last_uk_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp last_intl_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+os.system('scp hospital_normalisation_date.js neil@ogedei:/var/www/scripts.njae.me.uk/covid/')
+
+
+# %%
+
+
+
+
diff --git a/reported_deaths.js b/reported_deaths.js

deleted file mode 100644 (file)

index 0b140b7..0000000
--- a/reported_deaths.js
+++ /dev/null
@@ -1 +0,0 @@
-document.write('40532');
-\ No newline at end of file
diff --git a/run_daily_covid_update b/run_daily_covid_update

new file mode 100755 (executable)

index 0000000..72fc7a9
--- /dev/null
+++ b/run_daily_covid_update
@@ -0,0 +1,13 @@
+#!/usr/bin/bash
+
+eval "$(/home/neil/anaconda3/bin/conda shell.bash hook)"
+
+/home/neil/anaconda3/bin/conda init bash
+/home/neil/anaconda3/bin/conda activate base
+
+python /home/neil/Programming/covid19/data_import.py
+python /home/neil/Programming/covid19/international_comparison.py
+python /home/neil/Programming/covid19/hospital_data.py
+python /home/neil/Programming/covid19/uk_cases_and_deaths.py
+python /home/neil/Programming/covid19/test_and_case_data.py
+python /home/neil/Programming/covid19/publish.py
diff --git a/s_end.js b/s_end.js

deleted file mode 100644 (file)

index 20f4738..0000000
--- a/s_end.js
+++ /dev/null
@@ -1 +0,0 @@
-document.write('175');
-\ No newline at end of file
diff --git a/s_start_date.js b/s_start_date.js

deleted file mode 100644 (file)

index e2b7590..0000000
--- a/s_start_date.js
+++ /dev/null
@@ -1 +0,0 @@
-document.write('25 May 2020');
-\ No newline at end of file
diff --git a/scaling_factor.js b/scaling_factor.js

deleted file mode 100644 (file)

index e122139..0000000
--- a/scaling_factor.js
+++ /dev/null
@@ -1 +0,0 @@
-document.write('1.00');
-\ No newline at end of file
diff --git a/school_reopenings.png b/school_reopenings.png

deleted file mode 100644 (file)

index 787e841..0000000

Binary files a/school_reopenings.png and /dev/null differ
diff --git a/school_reopenings_detail.png b/school_reopenings_detail.png

deleted file mode 100644 (file)

index ef3ee25..0000000

Binary files a/school_reopenings_detail.png and /dev/null differ
diff --git a/test_and_case_data-Copy1.ipynb b/test_and_case_data-Copy1.ipynb

new file mode 100644 (file)

index 0000000..593eedc
--- /dev/null
+++ b/test_and_case_data-Copy1.ipynb
@@ -0,0 +1,2242 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "import itertools\n",
+    "import collections\n",
+    "import json\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "from scipy.stats import gmean\n",
+    "import datetime\n",
+    "\n",
+    "import matplotlib as mpl\n",
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib.animation as ani\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 372,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
+      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
+      "100   175    0   175    0     0   1367      0 --:--:-- --:--:-- --:--:--  1367\n"
+     ]
+    }
+   ],
+   "source": [
+    "# !curl \"https://api.coronavirus.data.gov.uk/v1/data?filters=areaName=United%2520Kingdom;areaType=overview&structure=%7B%22areaType%22:%22areaType%22,%22areaName%22:%22areaName%22,%22areaCode%22:%22areaCode%22,%22date%22:%22date%22,%22plannedCapacityByPublishDate%22:%22plannedCapacityByPublishDate%22,%22capacityPillarOne%22:%22capacityPillarOne%22,%22capacityPillarTwo%22:%22capacityPillarTwo%22,%22capacityPillarThree%22:%22capacityPillarThree%22,%22capacityPillarFour%22:%22capacityPillarFour%22,%22capacityPillarOneTwo%22:%22capacityPillarOneTwo%22,%22newTestsByPublishDate%22:%22newTestsByPublishDate%22,%22newPillarOneTestsByPublishDate%22:%22newPillarOneTestsByPublishDate%22,%22newPillarTwoTestsByPublishDate%22:%22newPillarTwoTestsByPublishDate%22,%22newPillarThreeTestsByPublishDate%22:%22newPillarThreeTestsByPublishDate%22,%22newPillarFourTestsByPublishDate%22:%22newPillarFourTestsByPublishDate%22,%22newPillarOneTwoTestsByPublishDate%22:%22newPillarOneTwoTestsByPublishDate%22,%22cumTestsByPublishDate%22:%22cumTestsByPublishDate%22,%22cumPillarOneTwoTestsByPublishDate%22:%22cumPillarOneTwoTestsByPublishDate%22%7D&format=csv\" | gunzip > tests_and_cases.csv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "https://coronavirus.data.gov.uk/api/v1/data?filters=areaName=United%2520Kingdom;areaType=overview&structure=%7B%22areaType%22:%22areaType%22,%22areaName%22:%22areaName%22,%22areaCode%22:%22areaCode%22,%22date%22:%22date%22,%22newVirusTests%22:%22newVirusTests%22,%22cumVirusTests%22:%22cumVirusTests%22%7D&format=csv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 413,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
+      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
+      "100 20547  100 20547    0     0  98783      0 --:--:-- --:--:-- --:--:-- 98783\n"
+     ]
+    }
+   ],
+   "source": [
+    "!curl \"https://api.coronavirus.data.gov.uk/v2/data?areaType=overview&metric=newTestsByPublishDate&metric=cumTestsByPublishDate&format=csv\" > tests_and_cases.csv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 414,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# !curl \"https://api.coronavirus-staging.data.gov.uk/v1/data?filters=areaName=United%2520Kingdom;areaType=overview&structure=%7B%22areaType%22:%22areaType%22,%22areaName%22:%22areaName%22,%22areaCode%22:%22areaCode%22,%22date%22:%22date%22,%22plannedCapacityByPublishDate%22:%22plannedCapacityByPublishDate%22,%22newTestsByPublishDate%22:%22newTestsByPublishDate%22,%22cumTestsByPublishDate%22:%22cumTestsByPublishDate%22%7D&format=csv\" | gunzip > tests_and_cases.csv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 415,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "chart_start_date = '2020-09-15'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 416,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "date,areaType,areaCode,areaName,newTestsByPublishDate,cumTestsByPublishDate\n",
+      "\"2020-12-15\",overview,K02000001,United Kingdom,,\n",
+      "\"2020-12-14\",overview,K02000001,United Kingdom,277944,48488168\n",
+      "\"2020-12-13\",overview,K02000001,United Kingdom,312638,48209087\n",
+      "\"2020-12-12\",overview,K02000001,United Kingdom,359457,47209531\n",
+      "\"2020-12-11\",overview,K02000001,United Kingdom,395510,47536955\n",
+      "\"2020-12-10\",overview,K02000001,United Kingdom,404236,47141344\n",
+      "\"2020-12-09\",overview,K02000001,United Kingdom,372446,46730999\n",
+      "\"2020-12-08\",overview,K02000001,United Kingdom,297220,46344703\n",
+      "\"2020-12-07\",overview,K02000001,United Kingdom,218055,46047237\n"
+     ]
+    }
+   ],
+   "source": [
+    "!head tests_and_cases.csv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 417,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "raw_data = pd.read_csv('tests_and_cases.csv', \n",
+    "                       parse_dates=[3], dayfirst=True,\n",
+    "                      )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 418,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "date                      object\n",
+       "areaType                  object\n",
+       "areaCode                  object\n",
+       "areaName                  object\n",
+       "newTestsByPublishDate    float64\n",
+       "cumTestsByPublishDate    float64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 418,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 419,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>areaType</th>\n",
+       "      <th>areaCode</th>\n",
+       "      <th>areaName</th>\n",
+       "      <th>newTestsByPublishDate</th>\n",
+       "      <th>cumTestsByPublishDate</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>date</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>2020-03-31</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>11896</td>\n",
+       "      <td>155174</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-04-01</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>11947</td>\n",
+       "      <td>167237</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-04-02</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>13623</td>\n",
+       "      <td>182352</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-04-03</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>14629</td>\n",
+       "      <td>223578</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-04-04</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>16080</td>\n",
+       "      <td>239658</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-10</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>404236</td>\n",
+       "      <td>47141344</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-11</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>395510</td>\n",
+       "      <td>47536955</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-12</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>359457</td>\n",
+       "      <td>47209531</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-13</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>312638</td>\n",
+       "      <td>48209087</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-14</td>\n",
+       "      <td>overview</td>\n",
+       "      <td>K02000001</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>277944</td>\n",
+       "      <td>48488168</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>259 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            areaType   areaCode        areaName  newTestsByPublishDate  \\\n",
+       "date                                                                     \n",
+       "2020-03-31  overview  K02000001  United Kingdom                  11896   \n",
+       "2020-04-01  overview  K02000001  United Kingdom                  11947   \n",
+       "2020-04-02  overview  K02000001  United Kingdom                  13623   \n",
+       "2020-04-03  overview  K02000001  United Kingdom                  14629   \n",
+       "2020-04-04  overview  K02000001  United Kingdom                  16080   \n",
+       "...              ...        ...             ...                    ...   \n",
+       "2020-12-10  overview  K02000001  United Kingdom                 404236   \n",
+       "2020-12-11  overview  K02000001  United Kingdom                 395510   \n",
+       "2020-12-12  overview  K02000001  United Kingdom                 359457   \n",
+       "2020-12-13  overview  K02000001  United Kingdom                 312638   \n",
+       "2020-12-14  overview  K02000001  United Kingdom                 277944   \n",
+       "\n",
+       "            cumTestsByPublishDate  \n",
+       "date                               \n",
+       "2020-03-31                 155174  \n",
+       "2020-04-01                 167237  \n",
+       "2020-04-02                 182352  \n",
+       "2020-04-03                 223578  \n",
+       "2020-04-04                 239658  \n",
+       "...                           ...  \n",
+       "2020-12-10               47141344  \n",
+       "2020-12-11               47536955  \n",
+       "2020-12-12               47209531  \n",
+       "2020-12-13               48209087  \n",
+       "2020-12-14               48488168  \n",
+       "\n",
+       "[259 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 419,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tests_data = raw_data.dropna().astype({'newTestsByPublishDate': np.int64, 'cumTestsByPublishDate': np.int64}).set_index('date').sort_index()\n",
+    "tests_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 420,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f488e22a1d0>"
+      ]
+     },
+     "execution_count": 420,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "tests_data.newTestsByPublishDate.plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 421,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# data_by_day.newAdmissions.dropna()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 422,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cases</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>cases_culm</th>\n",
+       "      <th>deaths_culm</th>\n",
+       "      <th>cases_diff</th>\n",
+       "      <th>deaths_diff</th>\n",
+       "      <th>cases_m7</th>\n",
+       "      <th>deaths_m7</th>\n",
+       "      <th>deaths_g4</th>\n",
+       "      <th>deaths_g7</th>\n",
+       "      <th>doubling_time</th>\n",
+       "      <th>doubling_time_7</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dateRep</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>2019-12-31</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-01</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-02</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-03</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-04</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-10</td>\n",
+       "      <td>16578</td>\n",
+       "      <td>533</td>\n",
+       "      <td>1766819</td>\n",
+       "      <td>62566</td>\n",
+       "      <td>4297.0</td>\n",
+       "      <td>-66.0</td>\n",
+       "      <td>15366.142857</td>\n",
+       "      <td>409.571429</td>\n",
+       "      <td>343.603005</td>\n",
+       "      <td>380.495816</td>\n",
+       "      <td>126.560073</td>\n",
+       "      <td>114.322369</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-11</td>\n",
+       "      <td>20964</td>\n",
+       "      <td>516</td>\n",
+       "      <td>1787783</td>\n",
+       "      <td>63082</td>\n",
+       "      <td>4386.0</td>\n",
+       "      <td>-17.0</td>\n",
+       "      <td>16235.571429</td>\n",
+       "      <td>424.142857</td>\n",
+       "      <td>420.064891</td>\n",
+       "      <td>392.657665</td>\n",
+       "      <td>104.437514</td>\n",
+       "      <td>111.703039</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-12</td>\n",
+       "      <td>21672</td>\n",
+       "      <td>424</td>\n",
+       "      <td>1809455</td>\n",
+       "      <td>63506</td>\n",
+       "      <td>708.0</td>\n",
+       "      <td>-92.0</td>\n",
+       "      <td>17003.285714</td>\n",
+       "      <td>412.714286</td>\n",
+       "      <td>514.093837</td>\n",
+       "      <td>383.080949</td>\n",
+       "      <td>85.970563</td>\n",
+       "      <td>115.254067</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-13</td>\n",
+       "      <td>21501</td>\n",
+       "      <td>520</td>\n",
+       "      <td>1830956</td>\n",
+       "      <td>64026</td>\n",
+       "      <td>-171.0</td>\n",
+       "      <td>96.0</td>\n",
+       "      <td>17855.000000</td>\n",
+       "      <td>430.285714</td>\n",
+       "      <td>496.234012</td>\n",
+       "      <td>398.139480</td>\n",
+       "      <td>89.778614</td>\n",
+       "      <td>111.813286</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-14</td>\n",
+       "      <td>18447</td>\n",
+       "      <td>144</td>\n",
+       "      <td>1849403</td>\n",
+       "      <td>64170</td>\n",
+       "      <td>-3054.0</td>\n",
+       "      <td>-376.0</td>\n",
+       "      <td>18023.000000</td>\n",
+       "      <td>417.857143</td>\n",
+       "      <td>357.762938</td>\n",
+       "      <td>372.146458</td>\n",
+       "      <td>124.672307</td>\n",
+       "      <td>119.867072</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>350 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff  \\\n",
+       "dateRep                                                                       \n",
+       "2019-12-31      0       0           0            0         NaN          NaN   \n",
+       "2020-01-01      0       0           0            0         0.0          0.0   \n",
+       "2020-01-02      0       0           0            0         0.0          0.0   \n",
+       "2020-01-03      0       0           0            0         0.0          0.0   \n",
+       "2020-01-04      0       0           0            0         0.0          0.0   \n",
+       "...           ...     ...         ...          ...         ...          ...   \n",
+       "2020-12-10  16578     533     1766819        62566      4297.0        -66.0   \n",
+       "2020-12-11  20964     516     1787783        63082      4386.0        -17.0   \n",
+       "2020-12-12  21672     424     1809455        63506       708.0        -92.0   \n",
+       "2020-12-13  21501     520     1830956        64026      -171.0         96.0   \n",
+       "2020-12-14  18447     144     1849403        64170     -3054.0       -376.0   \n",
+       "\n",
+       "                cases_m7   deaths_m7   deaths_g4   deaths_g7  doubling_time  \\\n",
+       "dateRep                                                                       \n",
+       "2019-12-31      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-01      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-02      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-03      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-04      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "...                  ...         ...         ...         ...            ...   \n",
+       "2020-12-10  15366.142857  409.571429  343.603005  380.495816     126.560073   \n",
+       "2020-12-11  16235.571429  424.142857  420.064891  392.657665     104.437514   \n",
+       "2020-12-12  17003.285714  412.714286  514.093837  383.080949      85.970563   \n",
+       "2020-12-13  17855.000000  430.285714  496.234012  398.139480      89.778614   \n",
+       "2020-12-14  18023.000000  417.857143  357.762938  372.146458     124.672307   \n",
+       "\n",
+       "            doubling_time_7  \n",
+       "dateRep                      \n",
+       "2019-12-31              NaN  \n",
+       "2020-01-01              NaN  \n",
+       "2020-01-02              NaN  \n",
+       "2020-01-03              NaN  \n",
+       "2020-01-04              NaN  \n",
+       "...                     ...  \n",
+       "2020-12-10       114.322369  \n",
+       "2020-12-11       111.703039  \n",
+       "2020-12-12       115.254067  \n",
+       "2020-12-13       111.813286  \n",
+       "2020-12-14       119.867072  \n",
+       "\n",
+       "[350 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 422,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_by_day = pd.read_csv('data_by_day_uk.csv', index_col='dateRep', parse_dates=True)\n",
+    "data_by_day"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 423,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "cases                 651.000000\n",
+       "deaths                 41.000000\n",
+       "cases_culm         285539.000000\n",
+       "deaths_culm         40532.000000\n",
+       "cases_diff             34.000000\n",
+       "deaths_diff           -56.000000\n",
+       "cases_m7              640.714286\n",
+       "deaths_m7              51.428571\n",
+       "deaths_g4              45.868305\n",
+       "deaths_g7              45.798566\n",
+       "doubling_time         612.853155\n",
+       "doubling_time_7       613.785835\n",
+       "Name: 2020-07-03 00:00:00, dtype: float64"
+      ]
+     },
+     "execution_count": 423,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_by_day.loc['2020-07-03']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 424,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cases</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>cases_culm</th>\n",
+       "      <th>deaths_culm</th>\n",
+       "      <th>cases_diff</th>\n",
+       "      <th>deaths_diff</th>\n",
+       "      <th>cases_m7</th>\n",
+       "      <th>deaths_m7</th>\n",
+       "      <th>deaths_g4</th>\n",
+       "      <th>deaths_g7</th>\n",
+       "      <th>doubling_time</th>\n",
+       "      <th>doubling_time_7</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dateRep</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>2019-12-31</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-01</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-02</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-03</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-04</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-10</td>\n",
+       "      <td>16578</td>\n",
+       "      <td>533</td>\n",
+       "      <td>1766819</td>\n",
+       "      <td>62566</td>\n",
+       "      <td>4297.0</td>\n",
+       "      <td>-66.0</td>\n",
+       "      <td>15366.142857</td>\n",
+       "      <td>409.571429</td>\n",
+       "      <td>343.603005</td>\n",
+       "      <td>380.495816</td>\n",
+       "      <td>126.560073</td>\n",
+       "      <td>114.322369</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-11</td>\n",
+       "      <td>20964</td>\n",
+       "      <td>516</td>\n",
+       "      <td>1787783</td>\n",
+       "      <td>63082</td>\n",
+       "      <td>4386.0</td>\n",
+       "      <td>-17.0</td>\n",
+       "      <td>16235.571429</td>\n",
+       "      <td>424.142857</td>\n",
+       "      <td>420.064891</td>\n",
+       "      <td>392.657665</td>\n",
+       "      <td>104.437514</td>\n",
+       "      <td>111.703039</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-12</td>\n",
+       "      <td>21672</td>\n",
+       "      <td>424</td>\n",
+       "      <td>1809455</td>\n",
+       "      <td>63506</td>\n",
+       "      <td>708.0</td>\n",
+       "      <td>-92.0</td>\n",
+       "      <td>17003.285714</td>\n",
+       "      <td>412.714286</td>\n",
+       "      <td>514.093837</td>\n",
+       "      <td>383.080949</td>\n",
+       "      <td>85.970563</td>\n",
+       "      <td>115.254067</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-13</td>\n",
+       "      <td>21501</td>\n",
+       "      <td>520</td>\n",
+       "      <td>1830956</td>\n",
+       "      <td>64026</td>\n",
+       "      <td>-171.0</td>\n",
+       "      <td>96.0</td>\n",
+       "      <td>17855.000000</td>\n",
+       "      <td>430.285714</td>\n",
+       "      <td>496.234012</td>\n",
+       "      <td>398.139480</td>\n",
+       "      <td>89.778614</td>\n",
+       "      <td>111.813286</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-14</td>\n",
+       "      <td>18447</td>\n",
+       "      <td>144</td>\n",
+       "      <td>1849403</td>\n",
+       "      <td>64170</td>\n",
+       "      <td>-3054.0</td>\n",
+       "      <td>-376.0</td>\n",
+       "      <td>18023.000000</td>\n",
+       "      <td>417.857143</td>\n",
+       "      <td>357.762938</td>\n",
+       "      <td>372.146458</td>\n",
+       "      <td>124.672307</td>\n",
+       "      <td>119.867072</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>350 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff  \\\n",
+       "dateRep                                                                       \n",
+       "2019-12-31      0       0           0            0         NaN          NaN   \n",
+       "2020-01-01      0       0           0            0         0.0          0.0   \n",
+       "2020-01-02      0       0           0            0         0.0          0.0   \n",
+       "2020-01-03      0       0           0            0         0.0          0.0   \n",
+       "2020-01-04      0       0           0            0         0.0          0.0   \n",
+       "...           ...     ...         ...          ...         ...          ...   \n",
+       "2020-12-10  16578     533     1766819        62566      4297.0        -66.0   \n",
+       "2020-12-11  20964     516     1787783        63082      4386.0        -17.0   \n",
+       "2020-12-12  21672     424     1809455        63506       708.0        -92.0   \n",
+       "2020-12-13  21501     520     1830956        64026      -171.0         96.0   \n",
+       "2020-12-14  18447     144     1849403        64170     -3054.0       -376.0   \n",
+       "\n",
+       "                cases_m7   deaths_m7   deaths_g4   deaths_g7  doubling_time  \\\n",
+       "dateRep                                                                       \n",
+       "2019-12-31      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-01      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-02      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-03      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-04      0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "...                  ...         ...         ...         ...            ...   \n",
+       "2020-12-10  15366.142857  409.571429  343.603005  380.495816     126.560073   \n",
+       "2020-12-11  16235.571429  424.142857  420.064891  392.657665     104.437514   \n",
+       "2020-12-12  17003.285714  412.714286  514.093837  383.080949      85.970563   \n",
+       "2020-12-13  17855.000000  430.285714  496.234012  398.139480      89.778614   \n",
+       "2020-12-14  18023.000000  417.857143  357.762938  372.146458     124.672307   \n",
+       "\n",
+       "            doubling_time_7  \n",
+       "dateRep                      \n",
+       "2019-12-31              NaN  \n",
+       "2020-01-01              NaN  \n",
+       "2020-01-02              NaN  \n",
+       "2020-01-03              NaN  \n",
+       "2020-01-04              NaN  \n",
+       "...                     ...  \n",
+       "2020-12-10       114.322369  \n",
+       "2020-12-11       111.703039  \n",
+       "2020-12-12       115.254067  \n",
+       "2020-12-13       111.813286  \n",
+       "2020-12-14       119.867072  \n",
+       "\n",
+       "[350 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 424,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# data_by_day.loc['2020-07-03', 'cases'] = 576\n",
+    "data_by_day"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 425,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_day = data_by_day.merge(tests_data[['newTestsByPublishDate', 'cumTestsByPublishDate']], how='outer',\n",
+    "    left_index=True, right_index=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 426,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_day['deaths_m7'] = data_by_day.deaths.transform(lambda x: x.rolling(7).mean())\n",
+    "data_by_day['cases_m7'] = data_by_day.cases.transform(lambda x: x.rolling(7).mean())\n",
+    "data_by_day['tests_m7'] = data_by_day.newTestsByPublishDate.transform(lambda x: x.rolling(7).mean())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 427,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cases</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>cases_culm</th>\n",
+       "      <th>deaths_culm</th>\n",
+       "      <th>cases_diff</th>\n",
+       "      <th>deaths_diff</th>\n",
+       "      <th>cases_m7</th>\n",
+       "      <th>deaths_m7</th>\n",
+       "      <th>deaths_g4</th>\n",
+       "      <th>deaths_g7</th>\n",
+       "      <th>doubling_time</th>\n",
+       "      <th>doubling_time_7</th>\n",
+       "      <th>newTestsByPublishDate</th>\n",
+       "      <th>cumTestsByPublishDate</th>\n",
+       "      <th>tests_m7</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>2019-12-31</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-01</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-02</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-03</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-04</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-10</td>\n",
+       "      <td>16578</td>\n",
+       "      <td>533</td>\n",
+       "      <td>1766819</td>\n",
+       "      <td>62566</td>\n",
+       "      <td>4297.0</td>\n",
+       "      <td>-66.0</td>\n",
+       "      <td>15366.142857</td>\n",
+       "      <td>409.571429</td>\n",
+       "      <td>343.603005</td>\n",
+       "      <td>380.495816</td>\n",
+       "      <td>126.560073</td>\n",
+       "      <td>114.322369</td>\n",
+       "      <td>404236.0</td>\n",
+       "      <td>47141344.0</td>\n",
+       "      <td>329487.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-11</td>\n",
+       "      <td>20964</td>\n",
+       "      <td>516</td>\n",
+       "      <td>1787783</td>\n",
+       "      <td>63082</td>\n",
+       "      <td>4386.0</td>\n",
+       "      <td>-17.0</td>\n",
+       "      <td>16235.571429</td>\n",
+       "      <td>424.142857</td>\n",
+       "      <td>420.064891</td>\n",
+       "      <td>392.657665</td>\n",
+       "      <td>104.437514</td>\n",
+       "      <td>111.703039</td>\n",
+       "      <td>395510.0</td>\n",
+       "      <td>47536955.0</td>\n",
+       "      <td>330972.142857</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-12</td>\n",
+       "      <td>21672</td>\n",
+       "      <td>424</td>\n",
+       "      <td>1809455</td>\n",
+       "      <td>63506</td>\n",
+       "      <td>708.0</td>\n",
+       "      <td>-92.0</td>\n",
+       "      <td>17003.285714</td>\n",
+       "      <td>412.714286</td>\n",
+       "      <td>514.093837</td>\n",
+       "      <td>383.080949</td>\n",
+       "      <td>85.970563</td>\n",
+       "      <td>115.254067</td>\n",
+       "      <td>359457.0</td>\n",
+       "      <td>47209531.0</td>\n",
+       "      <td>331435.142857</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-13</td>\n",
+       "      <td>21501</td>\n",
+       "      <td>520</td>\n",
+       "      <td>1830956</td>\n",
+       "      <td>64026</td>\n",
+       "      <td>-171.0</td>\n",
+       "      <td>96.0</td>\n",
+       "      <td>17855.000000</td>\n",
+       "      <td>430.285714</td>\n",
+       "      <td>496.234012</td>\n",
+       "      <td>398.139480</td>\n",
+       "      <td>89.778614</td>\n",
+       "      <td>111.813286</td>\n",
+       "      <td>312638.0</td>\n",
+       "      <td>48209087.0</td>\n",
+       "      <td>337080.285714</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-14</td>\n",
+       "      <td>18447</td>\n",
+       "      <td>144</td>\n",
+       "      <td>1849403</td>\n",
+       "      <td>64170</td>\n",
+       "      <td>-3054.0</td>\n",
+       "      <td>-376.0</td>\n",
+       "      <td>18023.000000</td>\n",
+       "      <td>417.857143</td>\n",
+       "      <td>357.762938</td>\n",
+       "      <td>372.146458</td>\n",
+       "      <td>124.672307</td>\n",
+       "      <td>119.867072</td>\n",
+       "      <td>277944.0</td>\n",
+       "      <td>48488168.0</td>\n",
+       "      <td>345635.857143</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>350 rows × 15 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff  \\\n",
+       "2019-12-31      0       0           0            0         NaN          NaN   \n",
+       "2020-01-01      0       0           0            0         0.0          0.0   \n",
+       "2020-01-02      0       0           0            0         0.0          0.0   \n",
+       "2020-01-03      0       0           0            0         0.0          0.0   \n",
+       "2020-01-04      0       0           0            0         0.0          0.0   \n",
+       "...           ...     ...         ...          ...         ...          ...   \n",
+       "2020-12-10  16578     533     1766819        62566      4297.0        -66.0   \n",
+       "2020-12-11  20964     516     1787783        63082      4386.0        -17.0   \n",
+       "2020-12-12  21672     424     1809455        63506       708.0        -92.0   \n",
+       "2020-12-13  21501     520     1830956        64026      -171.0         96.0   \n",
+       "2020-12-14  18447     144     1849403        64170     -3054.0       -376.0   \n",
+       "\n",
+       "                cases_m7   deaths_m7   deaths_g4   deaths_g7  doubling_time  \\\n",
+       "2019-12-31           NaN         NaN    0.000000    0.000000            NaN   \n",
+       "2020-01-01           NaN         NaN    0.000000    0.000000            NaN   \n",
+       "2020-01-02           NaN         NaN    0.000000    0.000000            NaN   \n",
+       "2020-01-03           NaN         NaN    0.000000    0.000000            NaN   \n",
+       "2020-01-04           NaN         NaN    0.000000    0.000000            NaN   \n",
+       "...                  ...         ...         ...         ...            ...   \n",
+       "2020-12-10  15366.142857  409.571429  343.603005  380.495816     126.560073   \n",
+       "2020-12-11  16235.571429  424.142857  420.064891  392.657665     104.437514   \n",
+       "2020-12-12  17003.285714  412.714286  514.093837  383.080949      85.970563   \n",
+       "2020-12-13  17855.000000  430.285714  496.234012  398.139480      89.778614   \n",
+       "2020-12-14  18023.000000  417.857143  357.762938  372.146458     124.672307   \n",
+       "\n",
+       "            doubling_time_7  newTestsByPublishDate  cumTestsByPublishDate  \\\n",
+       "2019-12-31              NaN                    NaN                    NaN   \n",
+       "2020-01-01              NaN                    NaN                    NaN   \n",
+       "2020-01-02              NaN                    NaN                    NaN   \n",
+       "2020-01-03              NaN                    NaN                    NaN   \n",
+       "2020-01-04              NaN                    NaN                    NaN   \n",
+       "...                     ...                    ...                    ...   \n",
+       "2020-12-10       114.322369               404236.0             47141344.0   \n",
+       "2020-12-11       111.703039               395510.0             47536955.0   \n",
+       "2020-12-12       115.254067               359457.0             47209531.0   \n",
+       "2020-12-13       111.813286               312638.0             48209087.0   \n",
+       "2020-12-14       119.867072               277944.0             48488168.0   \n",
+       "\n",
+       "                 tests_m7  \n",
+       "2019-12-31            NaN  \n",
+       "2020-01-01            NaN  \n",
+       "2020-01-02            NaN  \n",
+       "2020-01-03            NaN  \n",
+       "2020-01-04            NaN  \n",
+       "...                   ...  \n",
+       "2020-12-10  329487.000000  \n",
+       "2020-12-11  330972.142857  \n",
+       "2020-12-12  331435.142857  \n",
+       "2020-12-13  337080.285714  \n",
+       "2020-12-14  345635.857143  \n",
+       "\n",
+       "[350 rows x 15 columns]"
+      ]
+     },
+     "execution_count": 427,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_by_day"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 428,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "cases                    6.870000e+02\n",
+       "deaths                   3.100000e+01\n",
+       "cases_culm               2.778550e+05\n",
+       "deaths_culm              3.987800e+04\n",
+       "cases_diff              -2.990000e+02\n",
+       "deaths_diff             -4.000000e+01\n",
+       "cases_m7                 9.542857e+02\n",
+       "deaths_m7                7.314286e+01\n",
+       "deaths_g4                5.932579e+01\n",
+       "deaths_g7                6.469183e+01\n",
+       "doubling_time            4.662707e+02\n",
+       "doubling_time_7          4.276234e+02\n",
+       "newTestsByPublishDate    1.029570e+05\n",
+       "cumTestsByPublishDate    6.384549e+06\n",
+       "tests_m7                 1.172710e+05\n",
+       "Name: 2020-06-22 00:00:00, dtype: float64"
+      ]
+     },
+     "execution_count": 428,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_by_day.loc['2020-06-22']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 429,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f488e16b710>"
+      ]
+     },
+     "execution_count": 429,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data_by_day[['cases_culm', 'cumTestsByPublishDate']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 430,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f488e143310>"
+      ]
+     },
+     "execution_count": 430,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data_by_day.loc['2020-04-01':, ['cases_culm', 'cumTestsByPublishDate']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 431,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f488d327a50>"
+      ]
+     },
+     "execution_count": 431,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data_by_day.loc['2020-04-15':'2020-08-26', ['cases', 'newTestsByPublishDate']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 432,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f488dadc250>"
+      ]
+     },
+     "execution_count": 432,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data_by_day.loc['2020-04-15':'2020-08-26', ['cases_m7', 'tests_m7']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 433,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_day['fraction_positive'] = data_by_day.cases / data_by_day.newTestsByPublishDate\n",
+    "data_by_day['fraction_positive_m7'] = data_by_day.cases_m7 / data_by_day.tests_m7"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 434,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f488db37590>"
+      ]
+     },
+     "execution_count": 434,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data_by_day[['fraction_positive', 'fraction_positive_m7']].dropna().plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 435,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# ax = data_by_day.dropna().loc['2020-06-15': , ['fraction_positive', 'fraction_positive_m7']].plot(figsize=(10, 8), title='Fraction of tests with positive results')\n",
+    "# ax.legend(['Fraction positive per day', 'Fraction positive, 7 day moving average'])\n",
+    "# ax.set_ylabel('Fraction positive')\n",
+    "# plt.savefig('fraction_positive_tests.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 436,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'New cases')"
+      ]
+     },
+     "execution_count": 436,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x576 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "pri_y_max = int((data_by_day.dropna().loc['2020-06-15': , 'tests_m7'].max() * 1.1) / 100 ) * 100\n",
+    "ax = data_by_day.dropna().loc['2020-06-15': , 'tests_m7'].plot(figsize=(10, 8), \n",
+    "                                                               style=['k-'], \n",
+    "                                                               legend=False,\n",
+    "                                                               ylim=(0, pri_y_max))\n",
+    "ax.set_title('Tests done and new cases (7 day moving average)')\n",
+    "ax.legend(['Tests, 7 day moving average'], loc='lower left')\n",
+    "ax.set_ylabel('Tests')\n",
+    "sec_y_max = int((data_by_day.dropna().loc['2020-06-15':, 'cases_m7'].max() * 1.1) / 100) * 100\n",
+    "ax = data_by_day.dropna().loc['2020-06-15':, 'cases_m7'].plot(ax=ax, secondary_y=True, style='r--')\n",
+    "ax.set_ylim((0, sec_y_max))\n",
+    "ax.legend(['Cases (7 day moving average)'], loc='lower right')\n",
+    "ax.set_ylabel('New cases')\n",
+    "# plt.savefig('tests_and_cases.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 437,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x576 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "pri_y_max = int((data_by_day.loc[chart_start_date: , 'tests_m7'].max() * 1.1) / 100 ) * 100\n",
+    "ax = data_by_day.loc[chart_start_date: , 'tests_m7'].plot(figsize=(10, 8), \n",
+    "                                                               style=['k-'], \n",
+    "                                                               legend=False,\n",
+    "                                                               ylim=(0, pri_y_max))\n",
+    "ax.set_title('Tests done and new cases (7 day moving average)')\n",
+    "ax.legend(['Tests, 7 day moving average'], loc='lower left')\n",
+    "ax.set_ylabel('Tests')\n",
+    "sec_y_max = int((data_by_day.loc[chart_start_date:, 'cases_m7'].max() * 1.1) / 100) * 100\n",
+    "ax = data_by_day.loc[chart_start_date:, 'cases_m7'].plot(ax=ax, secondary_y=True, style='r--')\n",
+    "ax.set_ylim((0, sec_y_max))\n",
+    "ax.legend(['Cases (7 day moving average)'], loc='lower right')\n",
+    "ax.set_ylabel('New cases')\n",
+    "plt.savefig('tests_and_cases.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 438,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cases_m7</th>\n",
+       "      <th>cases</th>\n",
+       "      <th>tests_m7</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>2020-12-05</td>\n",
+       "      <td>14447.285714</td>\n",
+       "      <td>16298</td>\n",
+       "      <td>320410.142857</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-06</td>\n",
+       "      <td>14399.857143</td>\n",
+       "      <td>15539</td>\n",
+       "      <td>327945.142857</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-07</td>\n",
+       "      <td>15130.714286</td>\n",
+       "      <td>17271</td>\n",
+       "      <td>328166.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-08</td>\n",
+       "      <td>15471.857143</td>\n",
+       "      <td>14718</td>\n",
+       "      <td>325637.285714</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-09</td>\n",
+       "      <td>15307.857143</td>\n",
+       "      <td>12281</td>\n",
+       "      <td>327912.714286</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-10</td>\n",
+       "      <td>15366.142857</td>\n",
+       "      <td>16578</td>\n",
+       "      <td>329487.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-11</td>\n",
+       "      <td>16235.571429</td>\n",
+       "      <td>20964</td>\n",
+       "      <td>330972.142857</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-12</td>\n",
+       "      <td>17003.285714</td>\n",
+       "      <td>21672</td>\n",
+       "      <td>331435.142857</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-13</td>\n",
+       "      <td>17855.000000</td>\n",
+       "      <td>21501</td>\n",
+       "      <td>337080.285714</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-12-14</td>\n",
+       "      <td>18023.000000</td>\n",
+       "      <td>18447</td>\n",
+       "      <td>345635.857143</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                cases_m7  cases       tests_m7\n",
+       "2020-12-05  14447.285714  16298  320410.142857\n",
+       "2020-12-06  14399.857143  15539  327945.142857\n",
+       "2020-12-07  15130.714286  17271  328166.000000\n",
+       "2020-12-08  15471.857143  14718  325637.285714\n",
+       "2020-12-09  15307.857143  12281  327912.714286\n",
+       "2020-12-10  15366.142857  16578  329487.000000\n",
+       "2020-12-11  16235.571429  20964  330972.142857\n",
+       "2020-12-12  17003.285714  21672  331435.142857\n",
+       "2020-12-13  17855.000000  21501  337080.285714\n",
+       "2020-12-14  18023.000000  18447  345635.857143"
+      ]
+     },
+     "execution_count": 438,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_by_day[['cases_m7', 'cases', 'tests_m7']].tail(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 439,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# ax = (data_by_day.dropna().loc[chart_start_date: , ['fraction_positive', 'fraction_positive_m7']] * 100).plot(figsize=(10, 8), \n",
+    "#                                                                                                   style=['b:', 'k-'], legend=False)\n",
+    "# ax.set_title('Fraction of tests with positive results')\n",
+    "# ax.legend(['Fraction positive (%)', 'Fraction positive (%), 7 day moving average'], loc='upper left')\n",
+    "# ax.set_ylabel('Fraction positive')\n",
+    "# cases_axis_max = 1.0 * data_by_day.dropna().loc[chart_start_date:].cases_m7.max() * data_by_day.dropna().loc[chart_start_date:].fraction_positive.max() / data_by_day.dropna().loc[chart_start_date:].fraction_positive_m7.max()\n",
+    "\n",
+    "# ax2 = ax.twinx()\n",
+    "# ax2 = data_by_day.dropna().loc[chart_start_date:, 'cases_m7'].plot(ax=ax2, secondary_y=True, style='r--')\n",
+    "# ax2.set_ylim(-1000, cases_axis_max)\n",
+    "# ax2.legend(['Cases (7 day moving average)'], loc='center left')\n",
+    "# ax2.set_ylabel('New cases')\n",
+    "# plt.savefig('fraction_positive_tests.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 440,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 720x576 with 3 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax = (data_by_day.loc[chart_start_date: , ['fraction_positive', 'fraction_positive_m7']] * 100).plot(figsize=(10, 8), \n",
+    "                                                                                                  style=['b:', 'k-'], legend=False)\n",
+    "ax.set_title('Fraction of tests with positive results')\n",
+    "ax.legend(['Fraction positive (%)', 'Fraction positive (%), 7 day moving average'], loc='upper left')\n",
+    "ax.set_ylabel('Fraction positive')\n",
+    "cases_axis_max = 1.0 * data_by_day.loc[chart_start_date:].cases_m7.max() * data_by_day.loc[chart_start_date:].fraction_positive.max() / data_by_day.loc[chart_start_date:].fraction_positive_m7.max()\n",
+    "\n",
+    "ax2 = ax.twinx()\n",
+    "ax2 = data_by_day.loc[chart_start_date:, 'cases_m7'].plot(ax=ax2, secondary_y=True, style='r--')\n",
+    "ax2.set_ylim(-1000, cases_axis_max)\n",
+    "ax2.legend(['Cases (7 day moving average)'], loc='center left')\n",
+    "ax2.set_ylabel('New cases')\n",
+    "plt.savefig('fraction_positive_tests.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 441,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 576x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax = data_by_day.dropna().loc[chart_start_date:].plot(x='fraction_positive_m7', y='tests_m7', \n",
+    "                                                  figsize=(8, 8),\n",
+    "                                                  legend=None)\n",
+    "ax.set_xlabel(\"Fraction of tests that are positive\")\n",
+    "ax.set_ylabel(\"Number of tests\")\n",
+    "for d in data_by_day.dropna().loc[chart_start_date::15].index:\n",
+    "    ax.plot(data_by_day.loc[d, 'fraction_positive_m7'], data_by_day.loc[d, 'tests_m7'], 'o', \n",
+    "                        markersize=8)#, markerfacecolor=marker_col, markeredgecolor=marker_col)\n",
+    "    ax.text(data_by_day.loc[d, 'fraction_positive_m7'] + 0.0002, data_by_day.loc[d, 'tests_m7'], \n",
+    "            s = d.strftime(\"%d %B %Y\"))\n",
+    "plt.savefig('fraction_positive_tests_vs_tests.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 442,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cases</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>cases_culm</th>\n",
+       "      <th>deaths_culm</th>\n",
+       "      <th>cases_diff</th>\n",
+       "      <th>deaths_diff</th>\n",
+       "      <th>cases_m7</th>\n",
+       "      <th>deaths_m7</th>\n",
+       "      <th>deaths_g4</th>\n",
+       "      <th>deaths_g7</th>\n",
+       "      <th>doubling_time</th>\n",
+       "      <th>doubling_time_7</th>\n",
+       "      <th>newTestsByPublishDate</th>\n",
+       "      <th>cumTestsByPublishDate</th>\n",
+       "      <th>tests_m7</th>\n",
+       "      <th>fraction_positive</th>\n",
+       "      <th>fraction_positive_m7</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>2020-06-15</td>\n",
+       "      <td>890</td>\n",
+       "      <td>27</td>\n",
+       "      <td>271175</td>\n",
+       "      <td>39366</td>\n",
+       "      <td>-162.0</td>\n",
+       "      <td>-80.0</td>\n",
+       "      <td>1019.428571</td>\n",
+       "      <td>106.714286</td>\n",
+       "      <td>73.233216</td>\n",
+       "      <td>88.710020</td>\n",
+       "      <td>372.942855</td>\n",
+       "      <td>307.937760</td>\n",
+       "      <td>101337.0</td>\n",
+       "      <td>5552801.0</td>\n",
+       "      <td>125823.571429</td>\n",
+       "      <td>0.008783</td>\n",
+       "      <td>0.008102</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-06-16</td>\n",
+       "      <td>822</td>\n",
+       "      <td>29</td>\n",
+       "      <td>271997</td>\n",
+       "      <td>39395</td>\n",
+       "      <td>-68.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1033.857143</td>\n",
+       "      <td>104.142857</td>\n",
+       "      <td>57.557803</td>\n",
+       "      <td>82.797182</td>\n",
+       "      <td>474.765799</td>\n",
+       "      <td>330.146725</td>\n",
+       "      <td>122435.0</td>\n",
+       "      <td>5675283.0</td>\n",
+       "      <td>124299.714286</td>\n",
+       "      <td>0.006714</td>\n",
+       "      <td>0.008317</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff  \\\n",
+       "2020-06-15    890      27      271175        39366      -162.0        -80.0   \n",
+       "2020-06-16    822      29      271997        39395       -68.0          2.0   \n",
+       "\n",
+       "               cases_m7   deaths_m7  deaths_g4  deaths_g7  doubling_time  \\\n",
+       "2020-06-15  1019.428571  106.714286  73.233216  88.710020     372.942855   \n",
+       "2020-06-16  1033.857143  104.142857  57.557803  82.797182     474.765799   \n",
+       "\n",
+       "            doubling_time_7  newTestsByPublishDate  cumTestsByPublishDate  \\\n",
+       "2020-06-15       307.937760               101337.0              5552801.0   \n",
+       "2020-06-16       330.146725               122435.0              5675283.0   \n",
+       "\n",
+       "                 tests_m7  fraction_positive  fraction_positive_m7  \n",
+       "2020-06-15  125823.571429           0.008783              0.008102  \n",
+       "2020-06-16  124299.714286           0.006714              0.008317  "
+      ]
+     },
+     "execution_count": 442,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_by_day.dropna().loc['2020-06-15':][:2]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 443,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 576x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize=(8, 8))\n",
+    "plt.ylabel('Number of tests')\n",
+    "plt.xlabel('Fraction of tests that are positive')\n",
+    "all_data = data_by_day.dropna().loc[chart_start_date:]\n",
+    "\n",
+    "\n",
+    "minx = all_data.fraction_positive_m7.min() * 0.9\n",
+    "maxx = all_data.fraction_positive_m7.max() * 1.1\n",
+    "miny = all_data.tests_m7.min() * 0.9\n",
+    "maxy = all_data.tests_m7.max() * 1.1\n",
+    "\n",
+    "plt.xlim(minx, maxx)\n",
+    "plt.ylim(miny, maxy)\n",
+    "# plt.legend(None)\n",
+    "\n",
+    "def build_state_frame(i):\n",
+    "    this_data = all_data[:i]\n",
+    "    plt.clf()\n",
+    "    plt.ylabel('Number of tests')\n",
+    "    plt.xlabel('Fraction of tests that are positive')\n",
+    "    plt.xlim(minx, maxx)\n",
+    "    plt.ylim(miny, maxy)\n",
+    "    p = plt.plot(this_data.fraction_positive_m7, this_data.tests_m7)\n",
+    "    p[0].set_color('r')\n",
+    "    for d in this_data[::15].index:\n",
+    "        plt.plot(this_data.loc[d, 'fraction_positive_m7'], \n",
+    "                this_data.loc[d, 'tests_m7'], 'o', \n",
+    "                markersize=8, markerfacecolor='r', markeredgecolor='r')\n",
+    "        plt.text(this_data.loc[d, 'fraction_positive_m7'] + 0.0002, \n",
+    "                this_data.loc[d, 'tests_m7'], \n",
+    "            s = d.strftime(\"%d %B %Y\"))\n",
+    "\n",
+    "animator = ani.FuncAnimation(fig, build_state_frame, \n",
+    "                             frames=all_data.shape[0]+1,\n",
+    "                             interval=100,\n",
+    "                             repeat_delay=200,\n",
+    "                             repeat=True)\n",
+    "animator.save('tests_vs_fraction_positive.mp4')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 444,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ffmpeg version 4.2.4-1ubuntu0.1 Copyright (c) 2000-2020 the FFmpeg developers\n",
+      "  built with gcc 9 (Ubuntu 9.3.0-10ubuntu2)\n",
+      "  configuration: --prefix=/usr --extra-version=1ubuntu0.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-avresample --disable-filter=resample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librsvg --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-nvenc --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared\n",
+      "  WARNING: library configuration mismatch\n",
+      "  avcodec     configuration: --prefix=/usr --extra-version=1ubuntu0.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-avresample --disable-filter=resample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librsvg --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-nvenc --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared --enable-version3 --disable-doc --disable-programs --enable-libaribb24 --enable-liblensfun --enable-libopencore_amrnb --enable-libopencore_amrwb --enable-libtesseract --enable-libvo_amrwbenc\n",
+      "  libavutil      56. 31.100 / 56. 31.100\n",
+      "  libavcodec     58. 54.100 / 58. 54.100\n",
+      "  libavformat    58. 29.100 / 58. 29.100\n",
+      "  libavdevice    58.  8.100 / 58.  8.100\n",
+      "  libavfilter     7. 57.100 /  7. 57.100\n",
+      "  libavresample   4.  0.  0 /  4.  0.  0\n",
+      "  libswscale      5.  5.100 /  5.  5.100\n",
+      "  libswresample   3.  5.100 /  3.  5.100\n",
+      "  libpostproc    55.  5.100 / 55.  5.100\n",
+      "Input #0, mov,mp4,m4a,3gp,3g2,mj2, from 'tests_vs_fraction_positive.mp4':\n",
+      "  Metadata:\n",
+      "    major_brand     : isom\n",
+      "    minor_version   : 512\n",
+      "    compatible_brands: isomiso2avc1mp41\n",
+      "    encoder         : Lavf58.29.100\n",
+      "  Duration: 00:00:09.20, start: 0.000000, bitrate: 25 kb/s\n",
+      "    Stream #0:0(und): Video: h264 (High) (avc1 / 0x31637661), yuv420p, 576x576, 23 kb/s, 10 fps, 10 tbr, 10240 tbn, 20 tbc (default)\n",
+      "    Metadata:\n",
+      "      handler_name    : VideoHandler\n",
+      "Stream mapping:\n",
+      "  Stream #0:0 -> #0:0 (h264 (native) -> apng (native))\n",
+      "Press [q] to stop, [?] for help\n",
+      "Output #0, apng, to 'tests_vs_fraction_positive_animation.png':\n",
+      "  Metadata:\n",
+      "    major_brand     : isom\n",
+      "    minor_version   : 512\n",
+      "    compatible_brands: isomiso2avc1mp41\n",
+      "    encoder         : Lavf58.29.100\n",
+      "    Stream #0:0(und): Video: apng, rgb24, 576x576, q=2-31, 200 kb/s, 10 fps, 10 tbn, 10 tbc (default)\n",
+      "    Metadata:\n",
+      "      handler_name    : VideoHandler\n",
+      "      encoder         : Lavc58.54.100 apng\n",
+      "frame=   92 fps= 48 q=-0.0 Lsize=    1714kB time=00:00:09.20 bitrate=1526.4kbits/s speed=4.82x    \n",
+      "video:1714kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.004900%\n"
+     ]
+    }
+   ],
+   "source": [
+    "!rm tests_vs_fraction_positive_animation.png\n",
+    "!ffmpeg -i tests_vs_fraction_positive.mp4 -plays 0 -final_delay 1 -f apng tests_vs_fraction_positive_animation.png"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 445,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 576x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize=(8, 8))\n",
+    "plt.ylabel('Number of tests')\n",
+    "plt.xlabel('Fraction of tests that are positive')\n",
+    "\n",
+    "all_data = data_by_day.dropna().loc[chart_start_date:]\n",
+    "\n",
+    "minx = all_data.fraction_positive_m7.min() * 0.9\n",
+    "maxx = all_data.fraction_positive_m7.max() * 1.1\n",
+    "miny = all_data.tests_m7.min() * 0.9\n",
+    "maxy = all_data.tests_m7.max() * 1.1\n",
+    "\n",
+    "plt.xlim(minx, maxx)\n",
+    "plt.ylim(miny, maxy)\n",
+    "# plt.legend(None)\n",
+    "\n",
+    "def build_state_frame(i):\n",
+    "    this_data = all_data[:i]\n",
+    "    p = plt.plot(this_data.fraction_positive_m7, this_data.tests_m7)\n",
+    "    p[0].set_color('r')\n",
+    "    for d in this_data[::15].index:\n",
+    "        plt.plot(this_data.loc[d, 'fraction_positive_m7'], \n",
+    "                this_data.loc[d, 'tests_m7'], 'o', \n",
+    "                markersize=8, markerfacecolor='r', markeredgecolor='r')\n",
+    "        plt.text(this_data.loc[d, 'fraction_positive_m7'] + 0.0002, \n",
+    "                this_data.loc[d, 'tests_m7'], \n",
+    "            s = d.strftime(\"%d %B %Y\"))\n",
+    "\n",
+    "# animator = ani.FuncAnimation(fig, build_state_frame, interval=200)\n",
+    "# animator.save('myfirstAnimation.mp4')\n",
+    "build_state_frame(103)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 446,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "91"
+      ]
+     },
+     "execution_count": 446,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "all_data.shape[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 447,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(0.011172239552450438, 0.08499906334209148)"
+      ]
+     },
+     "execution_count": 447,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "minx, maxx"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/test_and_case_data-be.ipynb b/test_and_case_data-be.ipynb

new file mode 100644 (file)

index 0000000..8917cae
--- /dev/null
+++ b/test_and_case_data-be.ipynb
@@ -0,0 +1,1699 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "import itertools\n",
+    "import collections\n",
+    "import json\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "from scipy.stats import gmean\n",
+    "import datetime\n",
+    "\n",
+    "import matplotlib as mpl\n",
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib.animation as ani\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "source": [
+    "Belgian data from https://epistat.wiv-isp.be/covid/"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
+      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
+      "100  126k  100  126k    0     0   337k      0 --:--:-- --:--:-- --:--:--  337k\n"
+     ]
+    }
+   ],
+   "source": [
+    "!curl \"https://epistat.sciensano.be/Data/COVID19BE_tests.csv\" > COVID19BE_tests.csv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "raw_data = pd.read_csv('COVID19BE_tests.csv', \n",
+    "                       parse_dates=[0], dayfirst=True,\n",
+    "                       keep_default_na=False, na_values = ['']\n",
+    "                      )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "DATE             datetime64[ns]\n",
+       "PROVINCE                 object\n",
+       "REGION                   object\n",
+       "TESTS_ALL                 int64\n",
+       "TESTS_ALL_POS             int64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 80,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>TESTS_ALL</th>\n",
+       "      <th>TESTS_ALL_POS</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>DATE</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>2020-03-01</td>\n",
+       "      <td>82</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-03-02</td>\n",
+       "      <td>317</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-03-03</td>\n",
+       "      <td>538</td>\n",
+       "      <td>21</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-03-04</td>\n",
+       "      <td>701</td>\n",
+       "      <td>37</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-03-05</td>\n",
+       "      <td>773</td>\n",
+       "      <td>65</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-08</td>\n",
+       "      <td>13284</td>\n",
+       "      <td>2785</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-09</td>\n",
+       "      <td>21947</td>\n",
+       "      <td>4480</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-10</td>\n",
+       "      <td>38400</td>\n",
+       "      <td>8086</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-11</td>\n",
+       "      <td>31388</td>\n",
+       "      <td>6091</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-12</td>\n",
+       "      <td>26443</td>\n",
+       "      <td>4665</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>257 rows × 2 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            TESTS_ALL  TESTS_ALL_POS\n",
+       "DATE                                \n",
+       "2020-03-01         82              0\n",
+       "2020-03-02        317             10\n",
+       "2020-03-03        538             21\n",
+       "2020-03-04        701             37\n",
+       "2020-03-05        773             65\n",
+       "...               ...            ...\n",
+       "2020-11-08      13284           2785\n",
+       "2020-11-09      21947           4480\n",
+       "2020-11-10      38400           8086\n",
+       "2020-11-11      31388           6091\n",
+       "2020-11-12      26443           4665\n",
+       "\n",
+       "[257 rows x 2 columns]"
+      ]
+     },
+     "execution_count": 81,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tests_data = raw_data.set_index('DATE').sort_index().groupby('DATE').sum()[:-1]\n",
+    "tests_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f46895e23d0>"
+      ]
+     },
+     "execution_count": 82,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "tests_data.plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 83,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# data_by_day.newAdmissions.dropna()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cases</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>cases_culm</th>\n",
+       "      <th>deaths_culm</th>\n",
+       "      <th>cases_diff</th>\n",
+       "      <th>deaths_diff</th>\n",
+       "      <th>cases_m7</th>\n",
+       "      <th>deaths_m7</th>\n",
+       "      <th>deaths_g4</th>\n",
+       "      <th>deaths_g7</th>\n",
+       "      <th>doubling_time</th>\n",
+       "      <th>doubling_time_7</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dateRep</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>2019-12-31</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-01</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-02</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-03</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-01-04</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-10</td>\n",
+       "      <td>8320</td>\n",
+       "      <td>189</td>\n",
+       "      <td>513491</td>\n",
+       "      <td>13591</td>\n",
+       "      <td>6875.0</td>\n",
+       "      <td>-16.0</td>\n",
+       "      <td>6909.571429</td>\n",
+       "      <td>196.571429</td>\n",
+       "      <td>203.540082</td>\n",
+       "      <td>196.032323</td>\n",
+       "      <td>46.629293</td>\n",
+       "      <td>48.401920</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-11</td>\n",
+       "      <td>7217</td>\n",
+       "      <td>199</td>\n",
+       "      <td>520708</td>\n",
+       "      <td>13790</td>\n",
+       "      <td>-1103.0</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>6213.285714</td>\n",
+       "      <td>201.000000</td>\n",
+       "      <td>199.875596</td>\n",
+       "      <td>200.832476</td>\n",
+       "      <td>48.167987</td>\n",
+       "      <td>47.940131</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-12</td>\n",
+       "      <td>1819</td>\n",
+       "      <td>177</td>\n",
+       "      <td>522527</td>\n",
+       "      <td>13967</td>\n",
+       "      <td>-5398.0</td>\n",
+       "      <td>-22.0</td>\n",
+       "      <td>5158.571429</td>\n",
+       "      <td>199.000000</td>\n",
+       "      <td>192.203150</td>\n",
+       "      <td>198.660293</td>\n",
+       "      <td>50.715337</td>\n",
+       "      <td>49.078127</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-13</td>\n",
+       "      <td>2385</td>\n",
+       "      <td>124</td>\n",
+       "      <td>524912</td>\n",
+       "      <td>14091</td>\n",
+       "      <td>566.0</td>\n",
+       "      <td>-53.0</td>\n",
+       "      <td>4407.142857</td>\n",
+       "      <td>187.857143</td>\n",
+       "      <td>169.503027</td>\n",
+       "      <td>185.282927</td>\n",
+       "      <td>57.968081</td>\n",
+       "      <td>53.060535</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-14</td>\n",
+       "      <td>4</td>\n",
+       "      <td>15</td>\n",
+       "      <td>524916</td>\n",
+       "      <td>14106</td>\n",
+       "      <td>-2381.0</td>\n",
+       "      <td>-109.0</td>\n",
+       "      <td>3459.571429</td>\n",
+       "      <td>159.428571</td>\n",
+       "      <td>89.967328</td>\n",
+       "      <td>126.745394</td>\n",
+       "      <td>109.024927</td>\n",
+       "      <td>77.489169</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>320 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff  \\\n",
+       "dateRep                                                                       \n",
+       "2019-12-31      0       0           0            0         NaN          NaN   \n",
+       "2020-01-01      0       0           0            0         0.0          0.0   \n",
+       "2020-01-02      0       0           0            0         0.0          0.0   \n",
+       "2020-01-03      0       0           0            0         0.0          0.0   \n",
+       "2020-01-04      0       0           0            0         0.0          0.0   \n",
+       "...           ...     ...         ...          ...         ...          ...   \n",
+       "2020-11-10   8320     189      513491        13591      6875.0        -16.0   \n",
+       "2020-11-11   7217     199      520708        13790     -1103.0         10.0   \n",
+       "2020-11-12   1819     177      522527        13967     -5398.0        -22.0   \n",
+       "2020-11-13   2385     124      524912        14091       566.0        -53.0   \n",
+       "2020-11-14      4      15      524916        14106     -2381.0       -109.0   \n",
+       "\n",
+       "               cases_m7   deaths_m7   deaths_g4   deaths_g7  doubling_time  \\\n",
+       "dateRep                                                                      \n",
+       "2019-12-31     0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-01     0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-02     0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-03     0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "2020-01-04     0.000000    0.000000    0.000000    0.000000            NaN   \n",
+       "...                 ...         ...         ...         ...            ...   \n",
+       "2020-11-10  6909.571429  196.571429  203.540082  196.032323      46.629293   \n",
+       "2020-11-11  6213.285714  201.000000  199.875596  200.832476      48.167987   \n",
+       "2020-11-12  5158.571429  199.000000  192.203150  198.660293      50.715337   \n",
+       "2020-11-13  4407.142857  187.857143  169.503027  185.282927      57.968081   \n",
+       "2020-11-14  3459.571429  159.428571   89.967328  126.745394     109.024927   \n",
+       "\n",
+       "            doubling_time_7  \n",
+       "dateRep                      \n",
+       "2019-12-31              NaN  \n",
+       "2020-01-01              NaN  \n",
+       "2020-01-02              NaN  \n",
+       "2020-01-03              NaN  \n",
+       "2020-01-04              NaN  \n",
+       "...                     ...  \n",
+       "2020-11-10        48.401920  \n",
+       "2020-11-11        47.940131  \n",
+       "2020-11-12        49.078127  \n",
+       "2020-11-13        53.060535  \n",
+       "2020-11-14        77.489169  \n",
+       "\n",
+       "[320 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 84,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_by_day = pd.read_csv('data_by_day_be.csv', index_col='dateRep', parse_dates=True)\n",
+    "data_by_day"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "cases                 93.000000\n",
+       "deaths                 5.000000\n",
+       "cases_culm         62214.000000\n",
+       "deaths_culm         9647.000000\n",
+       "cases_diff           -42.000000\n",
+       "deaths_diff            3.000000\n",
+       "cases_m7              90.428571\n",
+       "deaths_m7              4.714286\n",
+       "deaths_g4              3.935979\n",
+       "deaths_g7              4.091666\n",
+       "doubling_time       1699.235256\n",
+       "doubling_time_7     1634.593051\n",
+       "Name: 2020-07-03 00:00:00, dtype: float64"
+      ]
+     },
+     "execution_count": 85,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_by_day.loc['2020-07-03']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_day = data_by_day.merge(tests_data[['TESTS_ALL']], how='outer',\n",
+    "    left_index=True, right_index=True).dropna()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cases</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>cases_culm</th>\n",
+       "      <th>deaths_culm</th>\n",
+       "      <th>cases_diff</th>\n",
+       "      <th>deaths_diff</th>\n",
+       "      <th>cases_m7</th>\n",
+       "      <th>deaths_m7</th>\n",
+       "      <th>deaths_g4</th>\n",
+       "      <th>deaths_g7</th>\n",
+       "      <th>doubling_time</th>\n",
+       "      <th>doubling_time_7</th>\n",
+       "      <th>TESTS_ALL</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>2020-03-10</td>\n",
+       "      <td>94</td>\n",
+       "      <td>1</td>\n",
+       "      <td>501</td>\n",
+       "      <td>1</td>\n",
+       "      <td>30.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>66.142857</td>\n",
+       "      <td>0.142857</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>804.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-03-11</td>\n",
+       "      <td>99</td>\n",
+       "      <td>0</td>\n",
+       "      <td>600</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>75.428571</td>\n",
+       "      <td>0.142857</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>1108.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-03-12</td>\n",
+       "      <td>174</td>\n",
+       "      <td>3</td>\n",
+       "      <td>774</td>\n",
+       "      <td>4</td>\n",
+       "      <td>75.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>92.714286</td>\n",
+       "      <td>0.571429</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>1438.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-03-13</td>\n",
+       "      <td>250</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>5</td>\n",
+       "      <td>76.0</td>\n",
+       "      <td>-2.0</td>\n",
+       "      <td>116.857143</td>\n",
+       "      <td>0.714286</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>2524.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-03-14</td>\n",
+       "      <td>338</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1362</td>\n",
+       "      <td>8</td>\n",
+       "      <td>88.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>149.428571</td>\n",
+       "      <td>1.142857</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>2171.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-08</td>\n",
+       "      <td>3027</td>\n",
+       "      <td>207</td>\n",
+       "      <td>503726</td>\n",
+       "      <td>13197</td>\n",
+       "      <td>-3610.0</td>\n",
+       "      <td>-7.0</td>\n",
+       "      <td>7873.571429</td>\n",
+       "      <td>192.428571</td>\n",
+       "      <td>203.325671</td>\n",
+       "      <td>191.422569</td>\n",
+       "      <td>45.334910</td>\n",
+       "      <td>48.132496</td>\n",
+       "      <td>13284.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-09</td>\n",
+       "      <td>1445</td>\n",
+       "      <td>205</td>\n",
+       "      <td>505171</td>\n",
+       "      <td>13402</td>\n",
+       "      <td>-1582.0</td>\n",
+       "      <td>-2.0</td>\n",
+       "      <td>7699.285714</td>\n",
+       "      <td>198.857143</td>\n",
+       "      <td>206.953291</td>\n",
+       "      <td>198.321322</td>\n",
+       "      <td>45.232911</td>\n",
+       "      <td>47.186672</td>\n",
+       "      <td>21947.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-10</td>\n",
+       "      <td>8320</td>\n",
+       "      <td>189</td>\n",
+       "      <td>513491</td>\n",
+       "      <td>13591</td>\n",
+       "      <td>6875.0</td>\n",
+       "      <td>-16.0</td>\n",
+       "      <td>6909.571429</td>\n",
+       "      <td>196.571429</td>\n",
+       "      <td>203.540082</td>\n",
+       "      <td>196.032323</td>\n",
+       "      <td>46.629293</td>\n",
+       "      <td>48.401920</td>\n",
+       "      <td>38400.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-11</td>\n",
+       "      <td>7217</td>\n",
+       "      <td>199</td>\n",
+       "      <td>520708</td>\n",
+       "      <td>13790</td>\n",
+       "      <td>-1103.0</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>6213.285714</td>\n",
+       "      <td>201.000000</td>\n",
+       "      <td>199.875596</td>\n",
+       "      <td>200.832476</td>\n",
+       "      <td>48.167987</td>\n",
+       "      <td>47.940131</td>\n",
+       "      <td>31388.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-12</td>\n",
+       "      <td>1819</td>\n",
+       "      <td>177</td>\n",
+       "      <td>522527</td>\n",
+       "      <td>13967</td>\n",
+       "      <td>-5398.0</td>\n",
+       "      <td>-22.0</td>\n",
+       "      <td>5158.571429</td>\n",
+       "      <td>199.000000</td>\n",
+       "      <td>192.203150</td>\n",
+       "      <td>198.660293</td>\n",
+       "      <td>50.715337</td>\n",
+       "      <td>49.078127</td>\n",
+       "      <td>26443.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>248 rows × 13 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff  \\\n",
+       "2020-03-10     94       1         501            1        30.0          1.0   \n",
+       "2020-03-11     99       0         600            1         5.0         -1.0   \n",
+       "2020-03-12    174       3         774            4        75.0          3.0   \n",
+       "2020-03-13    250       1        1024            5        76.0         -2.0   \n",
+       "2020-03-14    338       3        1362            8        88.0          2.0   \n",
+       "...           ...     ...         ...          ...         ...          ...   \n",
+       "2020-11-08   3027     207      503726        13197     -3610.0         -7.0   \n",
+       "2020-11-09   1445     205      505171        13402     -1582.0         -2.0   \n",
+       "2020-11-10   8320     189      513491        13591      6875.0        -16.0   \n",
+       "2020-11-11   7217     199      520708        13790     -1103.0         10.0   \n",
+       "2020-11-12   1819     177      522527        13967     -5398.0        -22.0   \n",
+       "\n",
+       "               cases_m7   deaths_m7   deaths_g4   deaths_g7  doubling_time  \\\n",
+       "2020-03-10    66.142857    0.142857    0.000000    0.000000            inf   \n",
+       "2020-03-11    75.428571    0.142857    0.000000    0.000000            inf   \n",
+       "2020-03-12    92.714286    0.571429    0.000000    0.000000            inf   \n",
+       "2020-03-13   116.857143    0.714286    0.000000    0.000000            inf   \n",
+       "2020-03-14   149.428571    1.142857    0.000000    0.000000            inf   \n",
+       "...                 ...         ...         ...         ...            ...   \n",
+       "2020-11-08  7873.571429  192.428571  203.325671  191.422569      45.334910   \n",
+       "2020-11-09  7699.285714  198.857143  206.953291  198.321322      45.232911   \n",
+       "2020-11-10  6909.571429  196.571429  203.540082  196.032323      46.629293   \n",
+       "2020-11-11  6213.285714  201.000000  199.875596  200.832476      48.167987   \n",
+       "2020-11-12  5158.571429  199.000000  192.203150  198.660293      50.715337   \n",
+       "\n",
+       "            doubling_time_7  TESTS_ALL  \n",
+       "2020-03-10              inf      804.0  \n",
+       "2020-03-11              inf     1108.0  \n",
+       "2020-03-12              inf     1438.0  \n",
+       "2020-03-13              inf     2524.0  \n",
+       "2020-03-14              inf     2171.0  \n",
+       "...                     ...        ...  \n",
+       "2020-11-08        48.132496    13284.0  \n",
+       "2020-11-09        47.186672    21947.0  \n",
+       "2020-11-10        48.401920    38400.0  \n",
+       "2020-11-11        47.940131    31388.0  \n",
+       "2020-11-12        49.078127    26443.0  \n",
+       "\n",
+       "[248 rows x 13 columns]"
+      ]
+     },
+     "execution_count": 87,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_by_day"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_day['deaths_m7'] = data_by_day.deaths.transform(lambda x: x.rolling(7, 1).mean())\n",
+    "data_by_day['cases_m7'] = data_by_day.cases.transform(lambda x: x.rolling(7, 1).mean())\n",
+    "data_by_day['tests_m7'] = data_by_day.TESTS_ALL.transform(lambda x: x.rolling(7, 1).mean())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cases</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>cases_culm</th>\n",
+       "      <th>deaths_culm</th>\n",
+       "      <th>cases_diff</th>\n",
+       "      <th>deaths_diff</th>\n",
+       "      <th>cases_m7</th>\n",
+       "      <th>deaths_m7</th>\n",
+       "      <th>deaths_g4</th>\n",
+       "      <th>deaths_g7</th>\n",
+       "      <th>doubling_time</th>\n",
+       "      <th>doubling_time_7</th>\n",
+       "      <th>TESTS_ALL</th>\n",
+       "      <th>tests_m7</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>2020-03-10</td>\n",
+       "      <td>94</td>\n",
+       "      <td>1</td>\n",
+       "      <td>501</td>\n",
+       "      <td>1</td>\n",
+       "      <td>30.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>94.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>804.0</td>\n",
+       "      <td>804.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-03-11</td>\n",
+       "      <td>99</td>\n",
+       "      <td>0</td>\n",
+       "      <td>600</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>96.500000</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>1108.0</td>\n",
+       "      <td>956.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-03-12</td>\n",
+       "      <td>174</td>\n",
+       "      <td>3</td>\n",
+       "      <td>774</td>\n",
+       "      <td>4</td>\n",
+       "      <td>75.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>122.333333</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>1438.0</td>\n",
+       "      <td>1116.666667</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-03-13</td>\n",
+       "      <td>250</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>5</td>\n",
+       "      <td>76.0</td>\n",
+       "      <td>-2.0</td>\n",
+       "      <td>154.250000</td>\n",
+       "      <td>1.250000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>2524.0</td>\n",
+       "      <td>1468.500000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-03-14</td>\n",
+       "      <td>338</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1362</td>\n",
+       "      <td>8</td>\n",
+       "      <td>88.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>191.000000</td>\n",
+       "      <td>1.600000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>2171.0</td>\n",
+       "      <td>1609.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-08</td>\n",
+       "      <td>3027</td>\n",
+       "      <td>207</td>\n",
+       "      <td>503726</td>\n",
+       "      <td>13197</td>\n",
+       "      <td>-3610.0</td>\n",
+       "      <td>-7.0</td>\n",
+       "      <td>7873.571429</td>\n",
+       "      <td>192.428571</td>\n",
+       "      <td>203.325671</td>\n",
+       "      <td>191.422569</td>\n",
+       "      <td>45.334910</td>\n",
+       "      <td>48.132496</td>\n",
+       "      <td>13284.0</td>\n",
+       "      <td>36906.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-09</td>\n",
+       "      <td>1445</td>\n",
+       "      <td>205</td>\n",
+       "      <td>505171</td>\n",
+       "      <td>13402</td>\n",
+       "      <td>-1582.0</td>\n",
+       "      <td>-2.0</td>\n",
+       "      <td>7699.285714</td>\n",
+       "      <td>198.857143</td>\n",
+       "      <td>206.953291</td>\n",
+       "      <td>198.321322</td>\n",
+       "      <td>45.232911</td>\n",
+       "      <td>47.186672</td>\n",
+       "      <td>21947.0</td>\n",
+       "      <td>35916.142857</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-10</td>\n",
+       "      <td>8320</td>\n",
+       "      <td>189</td>\n",
+       "      <td>513491</td>\n",
+       "      <td>13591</td>\n",
+       "      <td>6875.0</td>\n",
+       "      <td>-16.0</td>\n",
+       "      <td>6909.571429</td>\n",
+       "      <td>196.571429</td>\n",
+       "      <td>203.540082</td>\n",
+       "      <td>196.032323</td>\n",
+       "      <td>46.629293</td>\n",
+       "      <td>48.401920</td>\n",
+       "      <td>38400.0</td>\n",
+       "      <td>33588.857143</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-11</td>\n",
+       "      <td>7217</td>\n",
+       "      <td>199</td>\n",
+       "      <td>520708</td>\n",
+       "      <td>13790</td>\n",
+       "      <td>-1103.0</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>6213.285714</td>\n",
+       "      <td>201.000000</td>\n",
+       "      <td>199.875596</td>\n",
+       "      <td>200.832476</td>\n",
+       "      <td>48.167987</td>\n",
+       "      <td>47.940131</td>\n",
+       "      <td>31388.0</td>\n",
+       "      <td>31691.428571</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-11-12</td>\n",
+       "      <td>1819</td>\n",
+       "      <td>177</td>\n",
+       "      <td>522527</td>\n",
+       "      <td>13967</td>\n",
+       "      <td>-5398.0</td>\n",
+       "      <td>-22.0</td>\n",
+       "      <td>5158.571429</td>\n",
+       "      <td>199.000000</td>\n",
+       "      <td>192.203150</td>\n",
+       "      <td>198.660293</td>\n",
+       "      <td>50.715337</td>\n",
+       "      <td>49.078127</td>\n",
+       "      <td>26443.0</td>\n",
+       "      <td>28969.857143</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>248 rows × 14 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff  \\\n",
+       "2020-03-10     94       1         501            1        30.0          1.0   \n",
+       "2020-03-11     99       0         600            1         5.0         -1.0   \n",
+       "2020-03-12    174       3         774            4        75.0          3.0   \n",
+       "2020-03-13    250       1        1024            5        76.0         -2.0   \n",
+       "2020-03-14    338       3        1362            8        88.0          2.0   \n",
+       "...           ...     ...         ...          ...         ...          ...   \n",
+       "2020-11-08   3027     207      503726        13197     -3610.0         -7.0   \n",
+       "2020-11-09   1445     205      505171        13402     -1582.0         -2.0   \n",
+       "2020-11-10   8320     189      513491        13591      6875.0        -16.0   \n",
+       "2020-11-11   7217     199      520708        13790     -1103.0         10.0   \n",
+       "2020-11-12   1819     177      522527        13967     -5398.0        -22.0   \n",
+       "\n",
+       "               cases_m7   deaths_m7   deaths_g4   deaths_g7  doubling_time  \\\n",
+       "2020-03-10    94.000000    1.000000    0.000000    0.000000            inf   \n",
+       "2020-03-11    96.500000    0.500000    0.000000    0.000000            inf   \n",
+       "2020-03-12   122.333333    1.333333    0.000000    0.000000            inf   \n",
+       "2020-03-13   154.250000    1.250000    0.000000    0.000000            inf   \n",
+       "2020-03-14   191.000000    1.600000    0.000000    0.000000            inf   \n",
+       "...                 ...         ...         ...         ...            ...   \n",
+       "2020-11-08  7873.571429  192.428571  203.325671  191.422569      45.334910   \n",
+       "2020-11-09  7699.285714  198.857143  206.953291  198.321322      45.232911   \n",
+       "2020-11-10  6909.571429  196.571429  203.540082  196.032323      46.629293   \n",
+       "2020-11-11  6213.285714  201.000000  199.875596  200.832476      48.167987   \n",
+       "2020-11-12  5158.571429  199.000000  192.203150  198.660293      50.715337   \n",
+       "\n",
+       "            doubling_time_7  TESTS_ALL      tests_m7  \n",
+       "2020-03-10              inf      804.0    804.000000  \n",
+       "2020-03-11              inf     1108.0    956.000000  \n",
+       "2020-03-12              inf     1438.0   1116.666667  \n",
+       "2020-03-13              inf     2524.0   1468.500000  \n",
+       "2020-03-14              inf     2171.0   1609.000000  \n",
+       "...                     ...        ...           ...  \n",
+       "2020-11-08        48.132496    13284.0  36906.000000  \n",
+       "2020-11-09        47.186672    21947.0  35916.142857  \n",
+       "2020-11-10        48.401920    38400.0  33588.857143  \n",
+       "2020-11-11        47.940131    31388.0  31691.428571  \n",
+       "2020-11-12        49.078127    26443.0  28969.857143  \n",
+       "\n",
+       "[248 rows x 14 columns]"
+      ]
+     },
+     "execution_count": 89,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_by_day = data_by_day.dropna()\n",
+    "data_by_day"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 90,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "cases                 20.000000\n",
+       "deaths                 9.000000\n",
+       "cases_culm         61152.000000\n",
+       "deaths_culm         9590.000000\n",
+       "cases_diff           -30.000000\n",
+       "deaths_diff            6.000000\n",
+       "cases_m7              95.428571\n",
+       "deaths_m7              6.142857\n",
+       "deaths_g4              4.820571\n",
+       "deaths_g7              5.765161\n",
+       "doubling_time       1379.287366\n",
+       "doubling_time_7     1153.355452\n",
+       "TESTS_ALL          11129.000000\n",
+       "tests_m7           12589.285714\n",
+       "Name: 2020-06-22 00:00:00, dtype: float64"
+      ]
+     },
+     "execution_count": 90,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_by_day.loc['2020-06-22']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f4689458910>"
+      ]
+     },
+     "execution_count": 91,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data_by_day.loc['2020-04-15':'2020-08-26', ['cases_m7', 'tests_m7']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 92,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "data_by_day['fraction_positive'] = data_by_day.cases / data_by_day.TESTS_ALL\n",
+    "data_by_day['fraction_positive_m7'] = data_by_day.cases_m7 / data_by_day.tests_m7"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 93,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f46894496d0>"
+      ]
+     },
+     "execution_count": 93,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data_by_day[['fraction_positive', 'fraction_positive_m7']].dropna().plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 94,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# ax = data_by_day.dropna().loc['2020-06-15': , ['fraction_positive', 'fraction_positive_m7']].plot(figsize=(10, 8), title='Fraction of tests with positive results')\n",
+    "# ax.legend(['Fraction positive per day', 'Fraction positive, 7 day moving average'])\n",
+    "# ax.set_ylabel('Fraction positive')\n",
+    "# plt.savefig('fraction_positive_tests.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x576 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "pri_y_max = int((data_by_day.dropna().loc['2020-06-15': , 'tests_m7'].max() * 1.1) / 100 ) * 100\n",
+    "ax = data_by_day.dropna().loc['2020-06-15': , 'tests_m7'].plot(figsize=(10, 8), \n",
+    "                                                               style=['k-'], \n",
+    "                                                               legend=False,\n",
+    "                                                               ylim=(0, pri_y_max))\n",
+    "ax.set_title('Tests done and new cases (7 day moving average)')\n",
+    "ax.legend(['Tests, 7 day moving average'], loc='lower left')\n",
+    "ax.set_ylabel('Tests')\n",
+    "sec_y_max = int((data_by_day.dropna().loc['2020-06-15':, 'cases_m7'].max() * 1.1) / 100) * 100\n",
+    "ax = data_by_day.dropna().loc['2020-06-15':, 'cases_m7'].plot(ax=ax, secondary_y=True, style='r--')\n",
+    "ax.set_ylim((0, sec_y_max))\n",
+    "ax.legend(['Cases (7 day moving average)'], loc='lower right')\n",
+    "ax.set_ylabel('New cases')\n",
+    "plt.savefig('tests_and_cases_be.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 96,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "19400"
+      ]
+     },
+     "execution_count": 96,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "int((sec_y_max * 1.1) / 100) * 100"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 97,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x576 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax = (data_by_day.dropna().loc['2020-06-15': , ['fraction_positive', 'fraction_positive_m7']] * 100).plot(figsize=(10, 8), \n",
+    "                                                                                                  style=['b:', 'k-'], legend=False)\n",
+    "ax.set_title('Fraction of tests with positive results')\n",
+    "ax.legend(['Fraction positive (%)', 'Fraction positive (%), 7 day moving average'], loc='lower left')\n",
+    "ax.set_ylabel('Fraction positive')\n",
+    "ax = data_by_day.dropna().loc['2020-06-15':, 'cases_m7'].plot(ax=ax, secondary_y=True, style='r--')\n",
+    "ax.legend(['Cases (7 day moving average)'], loc='lower right')\n",
+    "ax.set_ylabel('New cases')\n",
+    "plt.savefig('fraction_positive_tests_be.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 98,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 576x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax = data_by_day.dropna().loc['2020-06-15':].plot(x='fraction_positive_m7', y='tests_m7', \n",
+    "                                                  figsize=(8, 8),\n",
+    "                                                  legend=None)\n",
+    "ax.set_xlabel(\"Fraction of tests that are positive\")\n",
+    "ax.set_ylabel(\"Number of tests\")\n",
+    "for d in data_by_day.dropna().loc['2020-06-15'::15].index:\n",
+    "    ax.plot(data_by_day.loc[d, 'fraction_positive_m7'], data_by_day.loc[d, 'tests_m7'], 'o', \n",
+    "                        markersize=8)#, markerfacecolor=marker_col, markeredgecolor=marker_col)\n",
+    "    ax.text(data_by_day.loc[d, 'fraction_positive_m7'] + 0.0002, data_by_day.loc[d, 'tests_m7'], \n",
+    "            s = d.strftime(\"%d %B %Y\"))\n",
+    "plt.savefig('fraction_positive_tests_vs_tests_be.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 99,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cases</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>cases_culm</th>\n",
+       "      <th>deaths_culm</th>\n",
+       "      <th>cases_diff</th>\n",
+       "      <th>deaths_diff</th>\n",
+       "      <th>cases_m7</th>\n",
+       "      <th>deaths_m7</th>\n",
+       "      <th>deaths_g4</th>\n",
+       "      <th>deaths_g7</th>\n",
+       "      <th>doubling_time</th>\n",
+       "      <th>doubling_time_7</th>\n",
+       "      <th>TESTS_ALL</th>\n",
+       "      <th>tests_m7</th>\n",
+       "      <th>fraction_positive</th>\n",
+       "      <th>fraction_positive_m7</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>2020-06-15</td>\n",
+       "      <td>22</td>\n",
+       "      <td>3</td>\n",
+       "      <td>60484</td>\n",
+       "      <td>9547</td>\n",
+       "      <td>-27.0</td>\n",
+       "      <td>-2.0</td>\n",
+       "      <td>95.857143</td>\n",
+       "      <td>8.285714</td>\n",
+       "      <td>5.692425</td>\n",
+       "      <td>7.520666</td>\n",
+       "      <td>1162.852153</td>\n",
+       "      <td>880.252074</td>\n",
+       "      <td>11905.0</td>\n",
+       "      <td>12538.000000</td>\n",
+       "      <td>0.001848</td>\n",
+       "      <td>0.007645</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2020-06-16</td>\n",
+       "      <td>147</td>\n",
+       "      <td>8</td>\n",
+       "      <td>60631</td>\n",
+       "      <td>9555</td>\n",
+       "      <td>125.0</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>95.142857</td>\n",
+       "      <td>8.142857</td>\n",
+       "      <td>5.885662</td>\n",
+       "      <td>7.395181</td>\n",
+       "      <td>1125.627162</td>\n",
+       "      <td>895.932593</td>\n",
+       "      <td>15194.0</td>\n",
+       "      <td>12553.571429</td>\n",
+       "      <td>0.009675</td>\n",
+       "      <td>0.007579</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff  \\\n",
+       "2020-06-15     22       3       60484         9547       -27.0         -2.0   \n",
+       "2020-06-16    147       8       60631         9555       125.0          5.0   \n",
+       "\n",
+       "             cases_m7  deaths_m7  deaths_g4  deaths_g7  doubling_time  \\\n",
+       "2020-06-15  95.857143   8.285714   5.692425   7.520666    1162.852153   \n",
+       "2020-06-16  95.142857   8.142857   5.885662   7.395181    1125.627162   \n",
+       "\n",
+       "            doubling_time_7  TESTS_ALL      tests_m7  fraction_positive  \\\n",
+       "2020-06-15       880.252074    11905.0  12538.000000           0.001848   \n",
+       "2020-06-16       895.932593    15194.0  12553.571429           0.009675   \n",
+       "\n",
+       "            fraction_positive_m7  \n",
+       "2020-06-15              0.007645  \n",
+       "2020-06-16              0.007579  "
+      ]
+     },
+     "execution_count": 99,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_by_day.dropna().loc['2020-06-15':][:2]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 100,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 576x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize=(8, 8))\n",
+    "plt.ylabel('Number of tests')\n",
+    "plt.xlabel('Fraction of tests that are positive')\n",
+    "all_data = data_by_day.dropna().loc['2020-06-15':]\n",
+    "\n",
+    "\n",
+    "minx = all_data.fraction_positive_m7.min() * 0.9\n",
+    "maxx = all_data.fraction_positive_m7.max() * 1.1\n",
+    "miny = all_data.tests_m7.min() * 0.9\n",
+    "maxy = all_data.tests_m7.max() * 1.1\n",
+    "\n",
+    "plt.xlim(minx, maxx)\n",
+    "plt.ylim(miny, maxy)\n",
+    "# plt.legend(None)\n",
+    "\n",
+    "def build_state_frame(i):\n",
+    "    this_data = all_data[:i]\n",
+    "    plt.clf()\n",
+    "    plt.ylabel('Number of tests')\n",
+    "    plt.xlabel('Fraction of tests that are positive')\n",
+    "    plt.xlim(minx, maxx)\n",
+    "    plt.ylim(miny, maxy)\n",
+    "    p = plt.plot(this_data.fraction_positive_m7, this_data.tests_m7)\n",
+    "    p[0].set_color('r')\n",
+    "    for d in this_data[::15].index:\n",
+    "        plt.plot(this_data.loc[d, 'fraction_positive_m7'], \n",
+    "                this_data.loc[d, 'tests_m7'], 'o', \n",
+    "                markersize=8, markerfacecolor='r', markeredgecolor='r')\n",
+    "        plt.text(this_data.loc[d, 'fraction_positive_m7'] + 0.0002, \n",
+    "                this_data.loc[d, 'tests_m7'], \n",
+    "            s = d.strftime(\"%d %B %Y\"))\n",
+    "\n",
+    "animator = ani.FuncAnimation(fig, build_state_frame, \n",
+    "                             frames=all_data.shape[0]+1,\n",
+    "                             interval=100,\n",
+    "                             repeat_delay=200,\n",
+    "                             repeat=True)\n",
+    "animator.save('tests_vs_fraction_positive_be.mp4')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 101,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ffmpeg version 4.2.4-1ubuntu0.1 Copyright (c) 2000-2020 the FFmpeg developers\n",
+      "  built with gcc 9 (Ubuntu 9.3.0-10ubuntu2)\n",
+      "  configuration: --prefix=/usr --extra-version=1ubuntu0.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-avresample --disable-filter=resample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librsvg --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-nvenc --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared\n",
+      "  WARNING: library configuration mismatch\n",
+      "  avcodec     configuration: --prefix=/usr --extra-version=1ubuntu0.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-avresample --disable-filter=resample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librsvg --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-nvenc --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared --enable-version3 --disable-doc --disable-programs --enable-libaribb24 --enable-liblensfun --enable-libopencore_amrnb --enable-libopencore_amrwb --enable-libtesseract --enable-libvo_amrwbenc\n",
+      "  libavutil      56. 31.100 / 56. 31.100\n",
+      "  libavcodec     58. 54.100 / 58. 54.100\n",
+      "  libavformat    58. 29.100 / 58. 29.100\n",
+      "  libavdevice    58.  8.100 / 58.  8.100\n",
+      "  libavfilter     7. 57.100 /  7. 57.100\n",
+      "  libavresample   4.  0.  0 /  4.  0.  0\n",
+      "  libswscale      5.  5.100 /  5.  5.100\n",
+      "  libswresample   3.  5.100 /  3.  5.100\n",
+      "  libpostproc    55.  5.100 / 55.  5.100\n",
+      "Input #0, mov,mp4,m4a,3gp,3g2,mj2, from 'tests_vs_fraction_positive_be.mp4':\n",
+      "  Metadata:\n",
+      "    major_brand     : isom\n",
+      "    minor_version   : 512\n",
+      "    compatible_brands: isomiso2avc1mp41\n",
+      "    encoder         : Lavf58.29.100\n",
+      "  Duration: 00:00:15.20, start: 0.000000, bitrate: 15 kb/s\n",
+      "    Stream #0:0(und): Video: h264 (High) (avc1 / 0x31637661), yuv420p, 576x576, 14 kb/s, 10 fps, 10 tbr, 10240 tbn, 20 tbc (default)\n",
+      "    Metadata:\n",
+      "      handler_name    : VideoHandler\n",
+      "Stream mapping:\n",
+      "  Stream #0:0 -> #0:0 (h264 (native) -> apng (native))\n",
+      "Press [q] to stop, [?] for help\n",
+      "Output #0, apng, to 'tests_vs_fraction_positive_animation_be.png':\n",
+      "  Metadata:\n",
+      "    major_brand     : isom\n",
+      "    minor_version   : 512\n",
+      "    compatible_brands: isomiso2avc1mp41\n",
+      "    encoder         : Lavf58.29.100\n",
+      "    Stream #0:0(und): Video: apng, rgb24, 576x576, q=2-31, 200 kb/s, 10 fps, 10 tbn, 10 tbc (default)\n",
+      "    Metadata:\n",
+      "      handler_name    : VideoHandler\n",
+      "      encoder         : Lavc58.54.100 apng\n",
+      "frame=  152 fps= 66 q=-0.0 Lsize=    1438kB time=00:00:15.20 bitrate= 774.8kbits/s speed=6.65x    \n",
+      "video:1438kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.005842%\n"
+     ]
+    }
+   ],
+   "source": [
+    "!rm tests_vs_fraction_positive_animation_be.png\n",
+    "!ffmpeg -i tests_vs_fraction_positive_be.mp4 -plays 0 -final_delay 1 -f apng tests_vs_fraction_positive_animation_be.png"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/test_and_case_data.ipynb b/test_and_case_data.ipynb

new file mode 100644 (file)

index 0000000..1ba0be4
--- /dev/null
+++ b/test_and_case_data.ipynb
@@ -0,0 +1,824 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The sql extension is already loaded. To reload it, use:\n",
+      "  %reload_ext sql\n"
+     ]
+    }
+   ],
+   "source": [
+    "import itertools\n",
+    "import collections\n",
+    "import json\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "from scipy.stats import gmean\n",
+    "import datetime\n",
+    "\n",
+    "import matplotlib as mpl\n",
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib.animation as ani\n",
+    "%matplotlib inline\n",
+    "%load_ext sql"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 92,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "chart_start_date = '2020-09-15'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 93,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 94,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Connected: covid@covid'"
+      ]
+     },
+     "execution_count": 94,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql $connection_string"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 109,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "390 rows affected.\n",
+      "Returning data to local variable res\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%sql res << select uk_data.date, \n",
+    "    uk_data.new_cases, uk_data_7.new_cases as new_cases_7,\n",
+    "    uk_data.new_tests, uk_data_7.new_tests as new_tests_7,\n",
+    "    uk_data.new_pcr_tests, uk_data_7.new_pcr_tests as new_pcr_7,\n",
+    "    uk_data.new_pillar_1_2_tests as new_pillar_12, uk_data_7.new_pillar_1_2_tests as new_pillar_12_7,\n",
+    "     uk_data.new_cases::float / uk_data.new_tests as fraction_positive,\n",
+    "        uk_data_7.new_cases / uk_data_7.new_tests as fraction_positive_7\n",
+    "    from uk_data left outer join uk_data_7 using (date)\n",
+    "    order by uk_data.date"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 110,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>new_cases</th>\n",
+       "      <th>new_cases_7</th>\n",
+       "      <th>new_tests</th>\n",
+       "      <th>new_tests_7</th>\n",
+       "      <th>new_pcr_tests</th>\n",
+       "      <th>new_pcr_7</th>\n",
+       "      <th>new_pillar_12</th>\n",
+       "      <th>new_pillar_12_7</th>\n",
+       "      <th>fraction_positive</th>\n",
+       "      <th>fraction_positive_7</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>date</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2021-01-17</th>\n",
+       "      <td>28875.0</td>\n",
+       "      <td>37337.855</td>\n",
+       "      <td>417965.0</td>\n",
+       "      <td>571242.56</td>\n",
+       "      <td>320122.0</td>\n",
+       "      <td>389469.84</td>\n",
+       "      <td>395737.0</td>\n",
+       "      <td>545088.10</td>\n",
+       "      <td>0.069085</td>\n",
+       "      <td>0.065363</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-18</th>\n",
+       "      <td>44732.0</td>\n",
+       "      <td>35766.570</td>\n",
+       "      <td>559939.0</td>\n",
+       "      <td>566901.10</td>\n",
+       "      <td>262499.0</td>\n",
+       "      <td>377019.28</td>\n",
+       "      <td>537028.0</td>\n",
+       "      <td>542617.90</td>\n",
+       "      <td>0.079887</td>\n",
+       "      <td>0.063091</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-19</th>\n",
+       "      <td>39311.0</td>\n",
+       "      <td>34143.285</td>\n",
+       "      <td>582938.0</td>\n",
+       "      <td>571336.56</td>\n",
+       "      <td>357850.0</td>\n",
+       "      <td>374771.16</td>\n",
+       "      <td>559061.0</td>\n",
+       "      <td>547402.44</td>\n",
+       "      <td>0.067436</td>\n",
+       "      <td>0.059760</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-20</th>\n",
+       "      <td>35015.0</td>\n",
+       "      <td>32707.428</td>\n",
+       "      <td>645050.0</td>\n",
+       "      <td>570458.10</td>\n",
+       "      <td>434099.0</td>\n",
+       "      <td>372037.44</td>\n",
+       "      <td>617221.0</td>\n",
+       "      <td>546806.30</td>\n",
+       "      <td>0.054283</td>\n",
+       "      <td>0.057335</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-21</th>\n",
+       "      <td>31430.0</td>\n",
+       "      <td>30620.428</td>\n",
+       "      <td>668989.0</td>\n",
+       "      <td>569716.70</td>\n",
+       "      <td>439408.0</td>\n",
+       "      <td>363750.16</td>\n",
+       "      <td>644537.0</td>\n",
+       "      <td>546626.56</td>\n",
+       "      <td>0.046981</td>\n",
+       "      <td>0.053747</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-22</th>\n",
+       "      <td>29094.0</td>\n",
+       "      <td>24870.428</td>\n",
+       "      <td>631901.0</td>\n",
+       "      <td>567830.30</td>\n",
+       "      <td>401075.0</td>\n",
+       "      <td>354323.16</td>\n",
+       "      <td>608829.0</td>\n",
+       "      <td>545780.30</td>\n",
+       "      <td>0.046042</td>\n",
+       "      <td>0.043799</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-23</th>\n",
+       "      <td>20495.0</td>\n",
+       "      <td>22463.666</td>\n",
+       "      <td>486425.0</td>\n",
+       "      <td>565312.30</td>\n",
+       "      <td>389209.0</td>\n",
+       "      <td>353735.34</td>\n",
+       "      <td>465231.0</td>\n",
+       "      <td>543566.80</td>\n",
+       "      <td>0.042134</td>\n",
+       "      <td>0.039737</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-24</th>\n",
+       "      <td>14266.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>412775.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>262111.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>394479.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.034561</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-25</th>\n",
+       "      <td>4482.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>546734.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>196510.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>531104.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.008198</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-26</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            new_cases  new_cases_7  new_tests  new_tests_7  new_pcr_tests  \\\n",
+       "date                                                                        \n",
+       "2021-01-17    28875.0    37337.855   417965.0    571242.56       320122.0   \n",
+       "2021-01-18    44732.0    35766.570   559939.0    566901.10       262499.0   \n",
+       "2021-01-19    39311.0    34143.285   582938.0    571336.56       357850.0   \n",
+       "2021-01-20    35015.0    32707.428   645050.0    570458.10       434099.0   \n",
+       "2021-01-21    31430.0    30620.428   668989.0    569716.70       439408.0   \n",
+       "2021-01-22    29094.0    24870.428   631901.0    567830.30       401075.0   \n",
+       "2021-01-23    20495.0    22463.666   486425.0    565312.30       389209.0   \n",
+       "2021-01-24    14266.0          NaN   412775.0          NaN       262111.0   \n",
+       "2021-01-25     4482.0          NaN   546734.0          NaN       196510.0   \n",
+       "2021-01-26        NaN          NaN        NaN          NaN            NaN   \n",
+       "\n",
+       "            new_pcr_7  new_pillar_12  new_pillar_12_7  fraction_positive  \\\n",
+       "date                                                                       \n",
+       "2021-01-17  389469.84       395737.0        545088.10           0.069085   \n",
+       "2021-01-18  377019.28       537028.0        542617.90           0.079887   \n",
+       "2021-01-19  374771.16       559061.0        547402.44           0.067436   \n",
+       "2021-01-20  372037.44       617221.0        546806.30           0.054283   \n",
+       "2021-01-21  363750.16       644537.0        546626.56           0.046981   \n",
+       "2021-01-22  354323.16       608829.0        545780.30           0.046042   \n",
+       "2021-01-23  353735.34       465231.0        543566.80           0.042134   \n",
+       "2021-01-24        NaN       394479.0              NaN           0.034561   \n",
+       "2021-01-25        NaN       531104.0              NaN           0.008198   \n",
+       "2021-01-26        NaN            NaN              NaN                NaN   \n",
+       "\n",
+       "            fraction_positive_7  \n",
+       "date                             \n",
+       "2021-01-17             0.065363  \n",
+       "2021-01-18             0.063091  \n",
+       "2021-01-19             0.059760  \n",
+       "2021-01-20             0.057335  \n",
+       "2021-01-21             0.053747  \n",
+       "2021-01-22             0.043799  \n",
+       "2021-01-23             0.039737  \n",
+       "2021-01-24                  NaN  \n",
+       "2021-01-25                  NaN  \n",
+       "2021-01-26                  NaN  "
+      ]
+     },
+     "execution_count": 110,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tests_data = res.DataFrame()\n",
+    "tests_data['date'] = tests_data.date.astype('datetime64[ns]')\n",
+    "tests_data.set_index('date', inplace=True)\n",
+    "tests_data.tail(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 111,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='date'>"
+      ]
+     },
+     "execution_count": 111,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "tests_data[['new_tests', 'new_cases']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 112,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='date'>"
+      ]
+     },
+     "execution_count": 112,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "tests_data[['fraction_positive', 'fraction_positive_7']].dropna().plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 113,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# ax = data_by_day.dropna().loc['2020-06-15': , ['fraction_positive', 'fraction_positive_m7']].plot(figsize=(10, 8), title='Fraction of tests with positive results')\n",
+    "# ax.legend(['Fraction positive per day', 'Fraction positive, 7 day moving average'])\n",
+    "# ax.set_ylabel('Fraction positive')\n",
+    "# plt.savefig('fraction_positive_tests.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 114,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'New cases')"
+      ]
+     },
+     "execution_count": 114,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x576 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "pri_y_max = int((tests_data.dropna().loc['2020-06-15': , 'new_tests_7'].max() * 1.1) / 100 ) * 100\n",
+    "ax = tests_data.dropna().loc['2020-06-15': , 'new_tests_7'].plot(figsize=(10, 8), \n",
+    "                                                               style=['k-'], \n",
+    "                                                               legend=False,\n",
+    "                                                               ylim=(0, pri_y_max))\n",
+    "ax.set_title('Tests done and new cases (7 day moving average)')\n",
+    "ax.legend(['Tests, 7 day moving average'], loc='lower left')\n",
+    "ax.set_ylabel('Tests')\n",
+    "sec_y_max = int((tests_data.dropna().loc['2020-06-15':, 'new_cases_7'].max() * 1.1) / 100) * 100\n",
+    "ax = tests_data.dropna().loc['2020-06-15':, 'new_cases_7'].plot(ax=ax, secondary_y=True, style='r--')\n",
+    "ax.set_ylim((0, sec_y_max))\n",
+    "ax.legend(['Cases (7 day moving average)'], loc='lower right')\n",
+    "ax.set_ylabel('New cases')\n",
+    "# plt.savefig('tests_and_cases.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 115,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x576 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "pri_y_max = int((tests_data.dropna().loc[chart_start_date: , 'new_tests_7'].max() * 1.1) / 100 ) * 100\n",
+    "ax = tests_data.dropna().loc[chart_start_date: , 'new_tests_7'].plot(figsize=(10, 8), \n",
+    "                                                               style=['k-'], \n",
+    "                                                               legend=False,\n",
+    "                                                               ylim=(0, pri_y_max))\n",
+    "ax.set_title('Tests done and new cases (7 day moving average)')\n",
+    "ax.legend(['Tests, 7 day moving average'], loc='lower left')\n",
+    "ax.set_ylabel('Tests')\n",
+    "sec_y_max = int((tests_data.dropna().loc[chart_start_date:, 'new_cases_7'].max() * 1.1) / 100) * 100\n",
+    "ax = tests_data.dropna().loc[chart_start_date:, 'new_cases_7'].plot(ax=ax, secondary_y=True, style='r--')\n",
+    "ax.set_ylim((0, sec_y_max))\n",
+    "ax.legend(['Cases (7 day moving average)'], loc='lower right')\n",
+    "ax.set_ylabel('New cases')\n",
+    "plt.savefig('tests_and_cases.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 116,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x576 with 3 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax = (tests_data.loc[chart_start_date: , ['fraction_positive', 'fraction_positive_7']] * 100).plot(figsize=(10, 8), \n",
+    "                                                                                                  style=['b:', 'k-'], legend=False)\n",
+    "ax.set_title('Fraction of tests with positive results')\n",
+    "ax.legend(['Fraction positive (%)', 'Fraction positive (%), 7 day moving average'], loc='upper left')\n",
+    "ax.set_ylabel('Fraction positive')\n",
+    "cases_axis_max = (1.0 * tests_data.loc[chart_start_date:].new_cases_7.max() \n",
+    "                  * tests_data.loc[chart_start_date:].fraction_positive.max() \n",
+    "                  / tests_data.loc[chart_start_date:].fraction_positive_7.max()\n",
+    "                  )\n",
+    "\n",
+    "ax2 = ax.twinx()\n",
+    "ax2 = tests_data.loc[chart_start_date:, 'new_cases_7'].plot(ax=ax2, secondary_y=True, style='r--')\n",
+    "ax2.set_ylim(-1000, cases_axis_max)\n",
+    "ax2.legend(['Cases (7 day moving average)'], loc='center left')\n",
+    "ax2.set_ylabel('New cases')\n",
+    "plt.savefig('fraction_positive_tests.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 117,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 576x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax = tests_data.dropna().loc[chart_start_date:].plot(x='fraction_positive_7', y='new_tests_7', \n",
+    "                                                  figsize=(8, 8),\n",
+    "                                                  legend=None)\n",
+    "ax.set_xlabel(\"Fraction of tests that are positive\")\n",
+    "ax.set_ylabel(\"Number of tests\")\n",
+    "for d in tests_data.dropna().loc[chart_start_date::15].index:\n",
+    "    ax.plot(tests_data.loc[d, 'fraction_positive_7'], tests_data.loc[d, 'new_tests_7'], 'o', \n",
+    "                        markersize=8)#, markerfacecolor=marker_col, markeredgecolor=marker_col)\n",
+    "    ax.text(tests_data.loc[d, 'fraction_positive_7'] + 0.0002, tests_data.loc[d, 'new_tests_7'], \n",
+    "            s = d.strftime(\"%d %B %Y\"))\n",
+    "plt.savefig('fraction_positive_tests_vs_tests.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 118,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 576x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize=(8, 8))\n",
+    "plt.ylabel('Number of tests')\n",
+    "plt.xlabel('Fraction of tests that are positive')\n",
+    "all_data = tests_data.dropna().loc[chart_start_date:]\n",
+    "\n",
+    "\n",
+    "minx = all_data.fraction_positive_7.min() * 0.9\n",
+    "maxx = all_data.fraction_positive_7.max() * 1.1\n",
+    "miny = all_data.new_tests_7.min() * 0.9\n",
+    "maxy = all_data.new_tests_7.max() * 1.1\n",
+    "\n",
+    "plt.xlim(minx, maxx)\n",
+    "plt.ylim(miny, maxy)\n",
+    "# plt.legend(None)\n",
+    "\n",
+    "def build_state_frame(i):\n",
+    "    this_data = all_data[:i]\n",
+    "    plt.clf()\n",
+    "    plt.ylabel('Number of tests')\n",
+    "    plt.xlabel('Fraction of tests that are positive')\n",
+    "    plt.xlim(minx, maxx)\n",
+    "    plt.ylim(miny, maxy)\n",
+    "    p = plt.plot(this_data.fraction_positive_7, this_data.new_tests_7)\n",
+    "    p[0].set_color('r')\n",
+    "    for d in this_data[::15].index:\n",
+    "        plt.plot(this_data.loc[d, 'fraction_positive_7'], \n",
+    "                this_data.loc[d, 'new_tests_7'], 'o', \n",
+    "                markersize=8, markerfacecolor='r', markeredgecolor='r')\n",
+    "        plt.text(this_data.loc[d, 'fraction_positive_7'] + 0.0002, \n",
+    "                this_data.loc[d, 'new_tests_7'], \n",
+    "            s = d.strftime(\"%d %B %Y\"))\n",
+    "\n",
+    "animator = ani.FuncAnimation(fig, build_state_frame, \n",
+    "                             frames=all_data.shape[0]+1,\n",
+    "                             interval=100,\n",
+    "                             repeat_delay=200,\n",
+    "                             repeat=True)\n",
+    "animator.save('tests_vs_fraction_positive.mp4')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 119,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ffmpeg version 4.2.4-1ubuntu0.1 Copyright (c) 2000-2020 the FFmpeg developers\n",
+      "  built with gcc 9 (Ubuntu 9.3.0-10ubuntu2)\n",
+      "  configuration: --prefix=/usr --extra-version=1ubuntu0.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-avresample --disable-filter=resample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librsvg --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-nvenc --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared\n",
+      "  WARNING: library configuration mismatch\n",
+      "  avcodec     configuration: --prefix=/usr --extra-version=1ubuntu0.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-avresample --disable-filter=resample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librsvg --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-nvenc --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared --enable-version3 --disable-doc --disable-programs --enable-libaribb24 --enable-liblensfun --enable-libopencore_amrnb --enable-libopencore_amrwb --enable-libtesseract --enable-libvo_amrwbenc\n",
+      "  libavutil      56. 31.100 / 56. 31.100\n",
+      "  libavcodec     58. 54.100 / 58. 54.100\n",
+      "  libavformat    58. 29.100 / 58. 29.100\n",
+      "  libavdevice    58.  8.100 / 58.  8.100\n",
+      "  libavfilter     7. 57.100 /  7. 57.100\n",
+      "  libavresample   4.  0.  0 /  4.  0.  0\n",
+      "  libswscale      5.  5.100 /  5.  5.100\n",
+      "  libswresample   3.  5.100 /  3.  5.100\n",
+      "  libpostproc    55.  5.100 / 55.  5.100\n",
+      "Input #0, mov,mp4,m4a,3gp,3g2,mj2, from 'tests_vs_fraction_positive.mp4':\n",
+      "  Metadata:\n",
+      "    major_brand     : isom\n",
+      "    minor_version   : 512\n",
+      "    compatible_brands: isomiso2avc1mp41\n",
+      "    encoder         : Lavf58.29.100\n",
+      "  Duration: 00:00:13.20, start: 0.000000, bitrate: 20 kb/s\n",
+      "    Stream #0:0(und): Video: h264 (High) (avc1 / 0x31637661), yuv420p, 576x576, 19 kb/s, 10 fps, 10 tbr, 10240 tbn, 20 tbc (default)\n",
+      "    Metadata:\n",
+      "      handler_name    : VideoHandler\n",
+      "Stream mapping:\n",
+      "  Stream #0:0 -> #0:0 (h264 (native) -> apng (native))\n",
+      "Press [q] to stop, [?] for help\n",
+      "Output #0, apng, to 'tests_vs_fraction_positive_animation.png':\n",
+      "  Metadata:\n",
+      "    major_brand     : isom\n",
+      "    minor_version   : 512\n",
+      "    compatible_brands: isomiso2avc1mp41\n",
+      "    encoder         : Lavf58.29.100\n",
+      "    Stream #0:0(und): Video: apng, rgb24, 576x576, q=2-31, 200 kb/s, 10 fps, 10 tbn, 10 tbc (default)\n",
+      "    Metadata:\n",
+      "      handler_name    : VideoHandler\n",
+      "      encoder         : Lavc58.54.100 apng\n",
+      "frame=  132 fps= 54 q=-0.0 Lsize=    1982kB time=00:00:13.20 bitrate=1230.1kbits/s speed= 5.4x    \n",
+      "video:1982kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.004237%\n"
+     ]
+    }
+   ],
+   "source": [
+    "!rm tests_vs_fraction_positive_animation.png\n",
+    "!ffmpeg -i tests_vs_fraction_positive.mp4 -plays 0 -final_delay 1 -f apng tests_vs_fraction_positive_animation.png"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 120,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# fig = plt.figure(figsize=(8, 8))\n",
+    "# plt.ylabel('Number of tests')\n",
+    "# plt.xlabel('Fraction of tests that are positive')\n",
+    "\n",
+    "# all_data = data_by_day.dropna().loc[chart_start_date:]\n",
+    "\n",
+    "# minx = all_data.fraction_positive_m7.min() * 0.9\n",
+    "# maxx = all_data.fraction_positive_m7.max() * 1.1\n",
+    "# miny = all_data.tests_m7.min() * 0.9\n",
+    "# maxy = all_data.tests_m7.max() * 1.1\n",
+    "\n",
+    "# plt.xlim(minx, maxx)\n",
+    "# plt.ylim(miny, maxy)\n",
+    "# # plt.legend(None)\n",
+    "\n",
+    "# def build_state_frame(i):\n",
+    "#     this_data = all_data[:i]\n",
+    "#     p = plt.plot(this_data.fraction_positive_m7, this_data.tests_m7)\n",
+    "#     p[0].set_color('r')\n",
+    "#     for d in this_data[::15].index:\n",
+    "#         plt.plot(this_data.loc[d, 'fraction_positive_m7'], \n",
+    "#                 this_data.loc[d, 'tests_m7'], 'o', \n",
+    "#                 markersize=8, markerfacecolor='r', markeredgecolor='r')\n",
+    "#         plt.text(this_data.loc[d, 'fraction_positive_m7'] + 0.0002, \n",
+    "#                 this_data.loc[d, 'tests_m7'], \n",
+    "#             s = d.strftime(\"%d %B %Y\"))\n",
+    "\n",
+    "# # animator = ani.FuncAnimation(fig, build_state_frame, interval=200)\n",
+    "# # animator.save('myfirstAnimation.mp4')\n",
+    "# build_state_frame(103)\n",
+    "# plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 121,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "131"
+      ]
+     },
+     "execution_count": 121,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "all_data.shape[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 122,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(0.0127848996, 0.15778081000000002)"
+      ]
+     },
+     "execution_count": 122,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "minx, maxx"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/test_and_case_data.py b/test_and_case_data.py

new file mode 100644 (file)

index 0000000..7de6bf0
--- /dev/null
+++ b/test_and_case_data.py
@@ -0,0 +1,146 @@
+#!/usr/bin/env python
+# coding: utf-8
+# %%
+import itertools
+import collections
+import json
+import pandas as pd
+import numpy as np
+from scipy.stats import gmean
+import datetime
+import os
+import sqlalchemy
+
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+import matplotlib.animation as ani
+plt.ioff()
+
+
+# %%
+chart_start_date = '2020-09-15'
+
+
+# %%
+connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'
+
+
+# %%
+engine = sqlalchemy.create_engine(connection_string)
+
+# %%
+query_string = '''select uk_data.date, 
+    uk_data.new_cases, uk_data_7.new_cases as new_cases_7,
+    uk_data.new_tests, uk_data_7.new_tests as new_tests_7,
+    uk_data.new_pcr_tests, uk_data_7.new_pcr_tests as new_pcr_7,
+    uk_data.new_pillar_1_2_tests as new_pillar_12, uk_data_7.new_pillar_1_2_tests as new_pillar_12_7,
+     uk_data.new_cases::float / uk_data.new_tests as fraction_positive,
+        uk_data_7.new_cases / uk_data_7.new_tests as fraction_positive_7
+    from uk_data left outer join uk_data_7 using (date)
+    order by uk_data.date'''
+tests_data = pd.read_sql_query(query_string, engine,
+    index_col='date',
+    parse_dates = ['date'])
+
+# %%
+pri_y_max = int((tests_data.dropna().loc[chart_start_date: , 'new_tests_7'].max() * 1.1) / 100 ) * 100
+ax = tests_data.dropna().loc[chart_start_date: , 'new_tests_7'].plot(figsize=(10, 8), 
+                                                               style=['k-'], 
+                                                               legend=False,
+                                                               ylim=(0, pri_y_max))
+ax.set_title('Tests done and new cases (7 day moving average)')
+ax.legend(['Tests, 7 day moving average'], loc='lower left')
+ax.set_ylabel('Tests')
+sec_y_max = int((tests_data.dropna().loc[chart_start_date:, 'new_cases_7'].max() * 1.1) / 100) * 100
+ax = tests_data.dropna().loc[chart_start_date:, 'new_cases_7'].plot(ax=ax, secondary_y=True, style='r--')
+ax.set_ylim((0, sec_y_max))
+ax.legend(['Cases (7 day moving average)'], loc='lower right')
+ax.set_ylabel('New cases')
+plt.savefig('tests_and_cases.png')
+
+
+# %%
+ax = (tests_data.loc[chart_start_date: , ['fraction_positive', 'fraction_positive_7']] * 100).plot(figsize=(10, 8), 
+                                                                                                  style=['b:', 'k-'], legend=False)
+ax.set_title('Fraction of tests with positive results')
+ax.legend(['Fraction positive (%)', 'Fraction positive (%), 7 day moving average'], loc='upper left')
+ax.set_ylabel('Fraction positive')
+cases_axis_max = (1.0 * tests_data.loc[chart_start_date:].new_cases_7.max() 
+                  * tests_data.loc[chart_start_date:].fraction_positive.max() 
+                  / tests_data.loc[chart_start_date:].fraction_positive_7.max()
+                  )
+
+ax2 = ax.twinx()
+ax2 = tests_data.loc[chart_start_date:, 'new_cases_7'].plot(ax=ax2, secondary_y=True, style='r--')
+ax2.set_ylim(-1000, cases_axis_max)
+ax2.legend(['Cases (7 day moving average)'], loc='center left')
+ax2.set_ylabel('New cases')
+plt.savefig('fraction_positive_tests.png')
+
+
+# %%
+ax = tests_data.dropna().loc[chart_start_date:].plot(x='fraction_positive_7', y='new_tests_7', 
+                                                  figsize=(8, 8),
+                                                  legend=None)
+ax.set_xlabel("Fraction of tests that are positive")
+ax.set_ylabel("Number of tests")
+for d in tests_data.dropna().loc[chart_start_date::15].index:
+    ax.plot(tests_data.loc[d, 'fraction_positive_7'], tests_data.loc[d, 'new_tests_7'], 'o', 
+                        markersize=8)#, markerfacecolor=marker_col, markeredgecolor=marker_col)
+    ax.text(tests_data.loc[d, 'fraction_positive_7'] + 0.0002, tests_data.loc[d, 'new_tests_7'], 
+            s = d.strftime("%d %B %Y"))
+plt.savefig('fraction_positive_tests_vs_tests.png')
+
+
+# %%
+fig = plt.figure(figsize=(8, 8))
+plt.ylabel('Number of tests')
+plt.xlabel('Fraction of tests that are positive')
+all_data = tests_data.dropna().loc[chart_start_date:]
+
+
+minx = all_data.fraction_positive_7.min() * 0.9
+maxx = all_data.fraction_positive_7.max() * 1.1
+miny = all_data.new_tests_7.min() * 0.9
+maxy = all_data.new_tests_7.max() * 1.1
+
+plt.xlim(minx, maxx)
+plt.ylim(miny, maxy)
+# plt.legend(None)
+
+def build_state_frame(i):
+    this_data = all_data[:i]
+    plt.clf()
+    plt.ylabel('Number of tests')
+    plt.xlabel('Fraction of tests that are positive')
+    plt.xlim(minx, maxx)
+    plt.ylim(miny, maxy)
+    p = plt.plot(this_data.fraction_positive_7, this_data.new_tests_7)
+    p[0].set_color('r')
+    for d in this_data[::15].index:
+        plt.plot(this_data.loc[d, 'fraction_positive_7'], 
+                this_data.loc[d, 'new_tests_7'], 'o', 
+                markersize=8, markerfacecolor='r', markeredgecolor='r')
+        plt.text(this_data.loc[d, 'fraction_positive_7'] + 0.0002, 
+                this_data.loc[d, 'new_tests_7'], 
+            s = d.strftime("%d %B %Y"))
+
+animator = ani.FuncAnimation(fig, build_state_frame, 
+                             frames=all_data.shape[0]+1,
+                             interval=100,
+                             repeat_delay=200,
+                             repeat=True)
+animator.save('tests_vs_fraction_positive.mp4')
+# plt.show()
+
+
+# %%
+os.system('rm tests_vs_fraction_positive_animation.png')
+os.system('ffmpeg -i tests_vs_fraction_positive.mp4 -plays 0 -final_delay 1 -f apng tests_vs_fraction_positive_animation.png')
+
+
+# %%
+
+
+
+
diff --git a/uk-deaths-data/Weekly_Deaths_NI_2020.csv b/uk-deaths-data/Weekly_Deaths_NI_2020.csv

deleted file mode 100644 (file)

index 778a52d..0000000
--- a/uk-deaths-data/Weekly_Deaths_NI_2020.csv
+++ /dev/null
@@ -1,33 +0,0 @@
-Registration Week,Week Ending (Friday),Total Number of Deaths Registered in Week (2020P),Average number of deaths registered in corresponding week over previous 5 years (2015 to 2019P),Range,,Respiratory2 deaths registered in week (2020P),Average number of respiratory2 deaths registered in corresponding week over previous 5 years (2015 to 2019P),Covid-193 deaths registered in week (2020P)
-,,,,Minimum in Previous 5 years,Maximum in Previous 5 years,,,
-1,03/01/2020,353,250,199,365,0,0,0
-2,10/01/20,395,402.2,319,481,131,144,0
-3,17/01/20,411,391.4,332,470,116,127.6,0
-4,24/01/20,347,382.6,335,426,113,123.8,0
-5,31/01/20,323,373.6,296,433,78,124,0
-6,07/02/20,332,345.8,314,374,81,110.6,0
-7,14/02/20,306,339.8,310,364,94,112,0
-8,21/02/20,297,317,217,366,80,97.2,0
-9,28/02/20,347,343,310,423,94,109.8,0
-10,06/03/20,312,356,298,401,81,105,0
-11,13/03/20,324,342.8,309,359,90,106.8,0
-12,20/03/20,271,297.2,251,326,84,95.2,1
-13,27/03/20,287,319.6,306,356,77,98,9
-14,03/04/20,434,298,280,323,129,90.6,55
-15,10/04/20,435,294.6,221,350,162,86.8,76
-16,17/04/20,424,290.4,270,316,179,81.2,101
-17,24/04/2020,470,284,245,327,206,78,128
-18,01/05/2020,427,320,292,357,180,88,124
-19,08/05/2020,336,274,230,335,130,80,84
-20,15/05/2020,396,295,256,330,136,74,74
-21,22/05/2020,325,290,259,315,90,80,53
-22,29/05/2020,316,279,245,328,105,79,49
-23,05/06/2020,304,271,256,284,64,71,20
-24,12/06/2020,292,293,275,340,69,78,21
-25,19/06/2020,290,286,265,300,68,71,17
-26,26/06/2020,295,270,252,292,79,75,12
-27,03/07/2020,289,288,266,303,63,71,11
-28,10/07/20,275,255,172,300,61,62,9
-29,17/07/2020,240,264,237,298,51,70,2
-30,24/07/2020,307,265,203,288,60,61,7
-31,31/07/2020,273,282,273,298,44,71,1
diff --git a/uk-deaths-data/Weekly_Deaths_NI_2020.xls b/uk-deaths-data/Weekly_Deaths_NI_2020.xls

deleted file mode 100644 (file)

index 34391c9..0000000

Binary files a/uk-deaths-data/Weekly_Deaths_NI_2020.xls and /dev/null differ
diff --git a/uk-deaths-data/weekly-deaths-april-20-scotland.csv b/uk-deaths-data/weekly-deaths-april-20-scotland.csv

deleted file mode 100644 (file)

index 6e876e6..0000000
--- a/uk-deaths-data/weekly-deaths-april-20-scotland.csv
+++ /dev/null
@@ -1,56 +0,0 @@
-"Table 2: Weekly death registrations, Scotland, 1974 - 2020",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
-,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
-Week Number,1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,Week Number
-W01,906,1577,1308,1514,1389,1541,1502,1268,1898,1545,1265,1303,1557,1239,1621,1457,1784,1375,1256,1556,1514,1318,1845,1483,1178,1838,2275,1308,1256,1177,1242,1244,1246,1345,1164,1245,1516,1344,1184,1201,1090,1146,1394,1205,1531,1104,1161,W01
-W02,1425,1612,1555,1370,1353,1618,1476,1657,1834,1511,1353,1346,1924,1673,1361,1352,1551,1467,1473,1482,1457,1333,1728,1911,1655,1525,1930,1270,1417,1570,1857,1308,1297,1517,1334,1844,1387,1372,1298,1425,1313,1708,1305,1379,1899,1507,1567,W02
-W03,1432,1437,1311,1337,1405,1469,1326,1317,1657,1403,1390,1451,1660,1371,1261,1270,1303,1291,1367,1369,1335,1304,1396,1712,1222,1541,1587,1319,1280,1354,1306,1181,1229,1452,1292,1333,1202,1244,1106,1265,1189,1489,1215,1224,1629,1353,1322,W03
-W04,1345,1432,1286,1314,1473,1494,1446,1442,1513,1301,1388,1441,1625,1354,1347,1226,1332,1315,1274,1346,1279,1207,1308,1460,1168,1515,1329,1244,1207,1296,1282,1204,1068,1271,1180,1241,1132,1143,1075,1212,1137,1381,1187,1197,1610,1208,1226,W04
-W05,1368,1435,1319,1335,1425,1408,1347,1325,1481,1331,1405,1460,1610,1260,1277,1229,1344,1272,1321,1198,1228,1228,1244,1388,1144,1493,1205,1205,1236,1256,1146,1168,1081,1252,1123,1176,1126,1099,1085,1282,1054,1286,1205,1332,1369,1206,1188,W05
-W06,1292,1320,1481,1305,1414,1513,1390,1253,1382,1407,1317,1283,1466,1310,1231,1238,1210,1231,1354,1192,1232,1266,1238,1257,1235,1440,1130,1200,1226,1236,1208,1185,1113,1134,1195,1090,1129,1012,1059,1194,1107,1344,1217,1200,1265,1243,1216,W06
-W07,1376,1397,1477,1311,1501,1471,1316,1296,1451,1399,1287,1335,1436,1305,1217,1218,1241,1372,1335,1260,1178,1256,1234,1276,1209,1408,1148,1217,1203,1224,1110,1218,1112,1178,1131,1183,1104,1089,1063,1113,1073,1360,1209,1231,1315,1181,1162,W07
-W08,1315,1261,1645,1343,1684,1467,1248,1327,1514,1429,1255,1400,1490,1351,1245,1209,1199,1303,1259,1263,1233,1203,1225,1288,1281,1334,1135,1125,1178,1188,1097,1185,1074,1184,1078,1122,1122,1118,1121,1228,1081,1320,1239,1185,1245,1245,1162,W08
-W09,1289,1330,1760,1291,1780,1417,1224,1397,1447,1519,1280,1363,1372,1232,1209,1287,1270,1283,1282,1260,1271,1204,1166,1252,1159,1244,1131,1138,1184,1202,1082,1209,1098,1085,1085,1104,1136,1021,1091,1108,1057,1308,1150,1219,1022,1125,1171,W09
-W10,1305,1361,1770,1300,1620,1350,1201,1437,1523,1526,1286,1417,1421,1375,1216,1229,1194,1258,1172,1326,1167,1224,1129,1146,1259,1283,1146,1230,1209,1178,1083,1255,1188,1154,1118,1114,1079,1030,1034,1131,1044,1192,1174,1146,1475,1156,1208,W10
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-W36,1037,1035,1051,1053,1144,1133,1066,1079,1105,1137,1050,1101,1121,1055,1131,1059,1016,1026,1089,1089,1095,1051,998,987,1072,1020,1039,1040,1074,1011,1057,1012,979,1016,899,921,963,1024,972,951,1026,977,1007,1006,970,980,,W36
-W37,1081,1067,1102,1044,1143,1086,1072,1091,1062,1067,1104,1106,1097,1092,1040,1111,1058,1084,1101,1076,1107,1035,1128,951,1106,999,1007,1056,1115,1051,1024,915,1027,955,959,941,998,965,1003,916,981,991,983,972,1020,1074,,W37
-W38,1117,1062,1054,1077,1070,1069,1105,1044,995,1072,1041,1142,1148,1043,1042,1068,986,1080,1027,1079,1067,1032,999,1007,1059,1025,961,1006,1070,1048,1015,926,950,922,965,962,971,943,951,971,934,1001,966,1049,946,1071,,W38
-W39,1194,1135,1135,1165,1200,1226,1050,1071,1189,1142,1181,1084,1103,1089,1147,1201,1108,1020,1121,1184,1181,1089,1048,1038,969,1041,1095,1079,1008,987,992,1050,1019,1039,949,962,1020,989,1071,928,950,1010,1009,1056,1015,1142,,W39
-W40,1201,1221,1131,1078,1110,1149,1192,1165,1129,1172,1157,1197,1105,1204,1148,1059,1102,1193,1107,1126,1137,1108,1128,1140,1066,1041,981,1082,1062,1136,1038,1004,991,1039,1042,1006,1000,977,1054,1040,994,1008,1072,1016,1042,1051,,W40
-W41,1176,1166,1024,1103,1127,1105,1123,1206,1150,1126,1059,1104,1034,1168,1118,1226,1084,1154,1098,1107,1120,1129,1045,1182,1055,1036,1072,1064,1087,1065,1066,971,1006,1047,1050,1005,999,1034,1033,918,1068,1028,1009,1133,1081,1143,,W41
-W42,1185,1179,1086,1146,1164,1074,1085,1159,1127,1183,1135,1064,1037,1192,1130,1125,1113,1168,1070,1172,1035,1124,1126,1069,1113,1023,1109,1051,1085,1133,1054,1026,1026,988,1017,994,1014,1034,1098,995,1013,989,1070,1067,1031,1153,,W42
-W43,1112,1109,1123,1075,1136,1151,1150,1198,1147,1205,1159,1109,1085,1212,1083,1124,1099,1105,1178,1321,1137,1113,1075,1057,1088,1062,1033,1012,1176,1080,1059,1058,1015,1000,988,968,1024,1035,1015,1047,1111,981,1052,1095,1019,1115,,W43
-W44,1251,1166,1174,1120,1152,1170,1169,1242,1144,1174,1127,1186,1155,1179,1200,1207,1196,1161,1260,1408,1134,1111,1084,1168,1177,1123,1068,1053,1119,1133,1037,1027,1022,1002,1029,1069,1028,1020,1074,1008,1021,1116,1032,1062,1085,1101,,W44
-W45,1213,1097,1230,1142,1149,1181,1164,1197,1137,1079,1113,1269,1128,1195,1246,1159,1128,1152,1189,1498,1090,1077,1107,1145,1170,1067,1102,1015,1138,1173,1041,971,1027,1048,1044,1000,1034,964,1034,1049,1087,1028,1043,1126,1144,1184,,W45
-W46,1308,1153,1167,1194,1143,1292,1213,1169,1171,1224,1145,1226,1222,1182,1191,1173,1141,1220,1129,1449,1079,1178,1082,1134,1191,1119,1137,1063,1111,1191,1027,1013,1048,1066,1074,1045,1115,973,1074,1016,1128,1103,1174,1175,1084,1160,,W46
-W47,1322,1138,1264,1226,1179,1363,1187,1135,1241,1168,1178,1244,1168,1194,1236,1376,1165,1243,1169,1462,1082,1212,1106,1109,1109,1142,1076,1059,1131,1186,1090,1035,1029,1033,1016,1005,1026,1038,1056,1030,1032,1054,1132,1178,1058,1229,,W47
-W48,1290,1249,1214,1298,1345,1278,1216,1172,1271,1256,1179,1338,1125,1188,1264,1571,1166,1199,1203,1441,1115,1300,1156,1098,1119,1150,1043,1111,1126,1220,1090,1154,1046,1107,1074,1112,1025,956,1003,1039,1008,1115,1159,1153,1062,1163,,W48
-W49,1223,1284,1183,1442,1300,1201,1357,1322,1299,1240,1238,1359,1164,1220,1274,1933,1196,1176,1221,1340,1159,1308,1208,1125,1132,1241,1059,1131,1102,1122,1095,1058,1086,1063,1113,1074,1188,1136,1088,1071,1076,1089,1188,1237,1076,1108,,W49
-W50,1333,1231,1388,1267,1321,1282,1294,1315,1371,1270,1243,1352,1148,1258,1270,2125,1263,1198,1226,1354,1176,1361,1193,1187,1178,1310,1053,1147,1215,1194,1100,1079,1017,1081,1128,1105,1098,1180,1083,1064,1170,1101,1219,1335,1212,1312,,W50
-W51,1455,1351,1412,1248,1374,1367,1268,1526,1413,1320,1271,1376,1220,1360,1314,2400,1318,1300,1262,1467,1258,1465,1266,1208,1198,1466,1185,1194,1176,1274,1096,1155,1171,1194,1300,1078,1164,1188,1207,1059,1265,1146,1284,1437,1216,1277,,W51
-W52,1564,1181,1461,1235,1491,1419,1078,1451,1543,1391,1291,1331,1009,1096,1394,1809,1299,1277,1099,1372,1276,1505,1250,943,1103,1614,1126,1147,1180,891,1123,1094,1122,1122,932,996,1075,1002,1103,901,886,944,1133,1168,1058,1000,,W52
-W53,,,1443,,,,,1608,,,,,,1299,,,,,1282,,,,,,1258,,,,,,1184,,,,,1064,,,,,,1018,,,,,,W53
diff --git a/uk_cases_and_deaths.ipynb b/uk_cases_and_deaths.ipynb

new file mode 100644 (file)

index 0000000..a2f3724
--- /dev/null
+++ b/uk_cases_and_deaths.ipynb
@@ -0,0 +1,426 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The sql extension is already loaded. To reload it, use:\n",
+      "  %reload_ext sql\n"
+     ]
+    }
+   ],
+   "source": [
+    "import itertools\n",
+    "import collections\n",
+    "import json\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "from scipy.stats import gmean\n",
+    "import datetime\n",
+    "\n",
+    "import sqlalchemy\n",
+    "\n",
+    "import matplotlib as mpl\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline\n",
+    "%load_ext sql"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Connected: covid@covid'"
+      ]
+     },
+     "execution_count": 58,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql $connection_string"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "conn = sqlalchemy.create_engine(connection_string)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "390 rows affected.\n",
+      "Returning data to local variable res\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%sql res << select uk_data.date\n",
+    "    , uk_data.new_cases, uk_data_7.new_cases as new_cases_7\n",
+    "    , uk_data.new_deaths, uk_data_7.new_deaths as new_deaths_7\n",
+    "    from uk_data left outer join uk_data_7 using (date)\n",
+    "    order by uk_data.date"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>new_cases</th>\n",
+       "      <th>new_cases_7</th>\n",
+       "      <th>new_deaths</th>\n",
+       "      <th>new_deaths_7</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>date</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2021-01-17</th>\n",
+       "      <td>28875.0</td>\n",
+       "      <td>37337.855</td>\n",
+       "      <td>671</td>\n",
+       "      <td>1217.5714</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-18</th>\n",
+       "      <td>44732.0</td>\n",
+       "      <td>35766.570</td>\n",
+       "      <td>599</td>\n",
+       "      <td>1223.5714</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-19</th>\n",
+       "      <td>39311.0</td>\n",
+       "      <td>34143.285</td>\n",
+       "      <td>1610</td>\n",
+       "      <td>1240.8572</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-20</th>\n",
+       "      <td>35015.0</td>\n",
+       "      <td>32707.428</td>\n",
+       "      <td>1820</td>\n",
+       "      <td>1248.4286</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-21</th>\n",
+       "      <td>31430.0</td>\n",
+       "      <td>30620.428</td>\n",
+       "      <td>1290</td>\n",
+       "      <td>1239.7142</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-22</th>\n",
+       "      <td>29094.0</td>\n",
+       "      <td>24870.428</td>\n",
+       "      <td>1401</td>\n",
+       "      <td>1238.7142</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-23</th>\n",
+       "      <td>20495.0</td>\n",
+       "      <td>22463.666</td>\n",
+       "      <td>1348</td>\n",
+       "      <td>1241.7142</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-24</th>\n",
+       "      <td>14266.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>610</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-25</th>\n",
+       "      <td>4482.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>592</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-26</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1631</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            new_cases  new_cases_7  new_deaths  new_deaths_7\n",
+       "date                                                        \n",
+       "2021-01-17    28875.0    37337.855         671     1217.5714\n",
+       "2021-01-18    44732.0    35766.570         599     1223.5714\n",
+       "2021-01-19    39311.0    34143.285        1610     1240.8572\n",
+       "2021-01-20    35015.0    32707.428        1820     1248.4286\n",
+       "2021-01-21    31430.0    30620.428        1290     1239.7142\n",
+       "2021-01-22    29094.0    24870.428        1401     1238.7142\n",
+       "2021-01-23    20495.0    22463.666        1348     1241.7142\n",
+       "2021-01-24    14266.0          NaN         610           NaN\n",
+       "2021-01-25     4482.0          NaN         592           NaN\n",
+       "2021-01-26        NaN          NaN        1631           NaN"
+      ]
+     },
+     "execution_count": 70,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "uk_data = res.DataFrame()\n",
+    "uk_data['date'] = uk_data.date.astype('datetime64[ns]')\n",
+    "uk_data.set_index('date', inplace=True)\n",
+    "uk_data.tail(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "new_cases       float64\n",
+       "new_cases_7     float64\n",
+       "new_deaths        int64\n",
+       "new_deaths_7    float64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 71,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "uk_data.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 720x576 with 3 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax = uk_data.loc['2020-03-10':, ['new_cases', 'new_cases_7']].plot(\n",
+    "    style={'new_cases': \"#e4e4e4\", \n",
+    "           'new_cases_7': 'k'},\n",
+    "    figsize=(10, 8),\n",
+    "    legend=False,\n",
+    "    title=\"New cases and new deaths\")\n",
+    "\n",
+    "# ax.set_title('Fraction of tests with positive results')\n",
+    "ax.legend(['New cases', 'New cases, 7 day moving average'], loc='upper left')\n",
+    "ax.set_ylabel('New cases')\n",
+    "\n",
+    "ax2 = ax.twinx()\n",
+    "ax2 = uk_data.loc['2020-03-10':, ['new_deaths','new_deaths_7']].plot(\n",
+    "    ax=ax2,\n",
+    "    secondary_y=['new_deaths', 'new_deaths_7'],\n",
+    "    style={'new_deaths': \"#ffe4e4\",\n",
+    "           'new_deaths_7': 'r'},\n",
+    "    legend=False)\n",
+    "ax2.legend(['New deaths', 'New deaths, 7 day moving average'], loc='best')\n",
+    "ax2.set_ylabel('New cases')\n",
+    "plt.savefig('cases_and_deaths.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# fig = plt.figure(figsize=(10, 8))\n",
+    "# axl = uk_data.loc['2020-03-10':, ['new_cases', 'new_deaths', 'new_cases_7', 'new_deaths_7']].plot(\n",
+    "#     secondary_y=['new_deaths', 'new_deaths_7'],\n",
+    "#     style={'new_cases': \"#e4e4e4\", \n",
+    "#            'new_deaths': \"#ffe4e4\",\n",
+    "#            'new_cases_7': 'k',\n",
+    "#            'new_deaths_7': 'r'},\n",
+    "#     figsize=(10, 8),\n",
+    "#     title=\"New cases and new deaths\")\n",
+    "# # axl.legend(['Number in hospital', 'Number on ventilator'])\n",
+    "# plt.savefig('cases_and_deaths.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x576 with 3 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax = uk_data.iloc[-60:][['new_cases', 'new_cases_7']].plot(\n",
+    "    style={'new_cases': \"#e4e4e4\", \n",
+    "           'new_cases_7': 'k'},\n",
+    "    figsize=(10, 8),\n",
+    "    legend=False,\n",
+    "    title=\"New cases and new deaths\")\n",
+    "\n",
+    "# ax.set_title('Fraction of tests with positive results')\n",
+    "ax.legend(['New cases', 'New cases, 7 day moving average'], loc='upper left')\n",
+    "ax.set_ylabel('New cases')\n",
+    "\n",
+    "\n",
+    "ax2 = ax.twinx()\n",
+    "ax2 = uk_data.iloc[-60:][['new_deaths','new_deaths_7']].plot(\n",
+    "    ax=ax2,\n",
+    "    secondary_y=['new_deaths', 'new_deaths_7'],\n",
+    "    style={'new_deaths': \"#ffe4e4\",\n",
+    "           'new_deaths_7': 'r'},\n",
+    "    legend=False)\n",
+    "ax2.legend(['New deaths', 'New deaths, 7 day moving average'], loc='best')\n",
+    "ax2.set_ylabel('New cases')\n",
+    "plt.savefig('cases_and_deaths_last_60_days.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# fig = plt.figure(figsize=(10, 8))\n",
+    "# axl = uk_data.iloc[-60:][['new_cases', 'new_deaths', 'new_cases_7', 'new_deaths_7']].plot(\n",
+    "#     secondary_y=['new_deaths', 'new_deaths_7'],\n",
+    "#     style={'new_cases': \"#e4e4e4\", \n",
+    "#            'new_deaths': \"#ffe4e4\",\n",
+    "#            'new_cases_7': 'k',\n",
+    "#            'new_deaths_7': 'r'},\n",
+    "#     figsize=(10, 8),\n",
+    "#     title=\"New cases and new deaths, last 60 days\")\n",
+    "# # axl.legend(['Number in hospital', 'Number on ventilator'])\n",
+    "# plt.savefig('cases_and_deaths_last_60_days.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/uk_cases_and_deaths.py b/uk_cases_and_deaths.py

new file mode 100644 (file)

index 0000000..bb57ed6
--- /dev/null
+++ b/uk_cases_and_deaths.py
@@ -0,0 +1,90 @@
+#!/usr/bin/env python
+# coding: utf-8
+# %%
+import itertools
+import collections
+import json
+import pandas as pd
+import numpy as np
+from scipy.stats import gmean
+import datetime
+
+import sqlalchemy
+
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+plt.ioff()
+
+
+# %%
+connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'
+
+
+# %%
+engine = sqlalchemy.create_engine(connection_string)
+
+
+# %%
+qstr = '''select uk_data.date
+    , uk_data.new_cases, uk_data_7.new_cases as new_cases_7
+    , uk_data.new_deaths, uk_data_7.new_deaths as new_deaths_7
+    from uk_data left outer join uk_data_7 using (date)
+    order by uk_data.date'''
+uk_data = pd.read_sql_query(qstr, engine,
+    index_col='date',
+    parse_dates = ['date'])
+
+# %%
+ax = uk_data.loc['2020-03-10':, ['new_cases', 'new_cases_7']].plot(
+    style={'new_cases': "#e4e4e4", 
+           'new_cases_7': 'k'},
+    figsize=(10, 8),
+    legend=False,
+    title="New cases and new deaths")
+
+# ax.set_title('Fraction of tests with positive results')
+ax.legend(['New cases', 'New cases, 7 day moving average'], loc='upper left')
+ax.set_ylabel('New cases')
+
+ax2 = ax.twinx()
+ax2 = uk_data.loc['2020-03-10':, ['new_deaths','new_deaths_7']].plot(
+    ax=ax2,
+    secondary_y=['new_deaths', 'new_deaths_7'],
+    style={'new_deaths': "#ffe4e4",
+           'new_deaths_7': 'r'},
+    legend=False)
+ax2.legend(['New deaths', 'New deaths, 7 day moving average'], loc='best')
+ax2.set_ylabel('New cases')
+plt.savefig('cases_and_deaths.png')
+
+
+# %%
+ax = uk_data.iloc[-60:][['new_cases', 'new_cases_7']].plot(
+    style={'new_cases': "#e4e4e4", 
+           'new_cases_7': 'k'},
+    figsize=(10, 8),
+    legend=False,
+    title="New cases and new deaths")
+
+# ax.set_title('Fraction of tests with positive results')
+ax.legend(['New cases', 'New cases, 7 day moving average'], loc='upper left')
+ax.set_ylabel('New cases')
+
+
+ax2 = ax.twinx()
+ax2 = uk_data.iloc[-60:][['new_deaths','new_deaths_7']].plot(
+    ax=ax2,
+    secondary_y=['new_deaths', 'new_deaths_7'],
+    style={'new_deaths': "#ffe4e4",
+           'new_deaths_7': 'r'},
+    legend=False)
+ax2.legend(['New deaths', 'New deaths, 7 day moving average'], loc='best')
+ax2.set_ylabel('New cases')
+plt.savefig('cases_and_deaths_last_60_days.png')
+
+
+# %%
+
+
+
+
diff --git a/uk_covid_deaths.js b/uk_covid_deaths.js

deleted file mode 100644 (file)

index 583cb0d..0000000
--- a/uk_covid_deaths.js
+++ /dev/null
@@ -1 +0,0 @@
-document.write('41381');
-\ No newline at end of file
diff --git a/uk_deaths.ipynb b/uk_deaths.ipynb

index 9cf1f8631f978f6f349150b70a72cd7581fcfcc1..2f6888c005cf753a4406abf04d29f53a3380717b 100644 (file)
--- a/uk_deaths.ipynb
+++ b/uk_deaths.ipynb
@@ -2,7 +2,9 @@
   "cells": [
    {
     "cell_type": "markdown",
   "cells": [
    {
     "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "Collapsed": "false"
+   },
     "source": [
      "Data from:\n",
      "\n",
     "source": [
      "Data from:\n",
      "\n",
@@ -13,8 +15,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 76,
-   "metadata": {},
+   "execution_count": 1,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "import itertools\n",
     "outputs": [],
     "source": [
      "import itertools\n",
@@ -31,94 +35,21 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 77,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      " covid-deaths-data-scotland-week-21.xlsx\n",
-      " covid-deaths-data-scotland-week-31.xlsx\n",
-      " covid-deaths-data-week-23.xlsx\n",
-      " covid-deaths-data-week-24-scotland.xlsx\n",
-      " covid-deaths-data-week-25-scotland.xlsx\n",
-      " covid-deaths-data-week-27-scotland.xlsx\n",
-      " covid-deaths-data-week-28-scotland.xlsx\n",
-      " covid-deaths-data-week-32.xlsx\n",
-      " publishedweek1620201.xlsx\n",
-      " publishedweek172020.csv\n",
-      " publishedweek172020.ods\n",
-      " publishedweek172020.xlsx\n",
-      " publishedweek182020.csv\n",
-      " publishedweek182020.ods\n",
-      " publishedweek182020.xlsx\n",
-      " publishedweek192020.csv\n",
-      " publishedweek192020.ods\n",
-      " publishedweek192020.xlsx\n",
-      " publishedweek2015.csv\n",
-      " publishedweek2015.ods\n",
-      " publishedweek2015.xls\n",
-      " publishedweek202020.csv\n",
-      " publishedweek202020.ods\n",
-      " publishedweek202020.xlsx\n",
-      " publishedweek212020.csv\n",
-      " publishedweek212020.ods\n",
-      " publishedweek212020.xlsx\n",
-      " publishedweek222020.csv\n",
-      " publishedweek222020.xlsx\n",
-      " publishedweek232020.csv\n",
-      " publishedweek232020.xlsx\n",
-      " publishedweek242020.csv\n",
-      " publishedweek242020.xlsx\n",
-      " publishedweek252020.csv\n",
-      " publishedweek252020.xlsx\n",
-      " publishedweek262020.csv\n",
-      " publishedweek262020.xlsx\n",
-      " publishedweek272020.csv\n",
-      " publishedweek272020.xlsx\n",
-      " publishedweek282020.xlsx\n",
-      " publishedweek292020.xlsx\n",
-      " publishedweek302020.xlsx\n",
-      " publishedweek312020.xlsx\n",
-      " publishedweek522016.csv\n",
-      " publishedweek522016.ods\n",
-      " publishedweek522016.xls\n",
-      " publishedweek522017.csv\n",
-      " publishedweek522017.ods\n",
-      " publishedweek522017.xls\n",
-      " publishedweek522018.csv\n",
-      " publishedweek522018.ods\n",
-      " publishedweek522018withupdatedrespiratoryrow.xls\n",
-      " publishedweek522019.csv\n",
-      " publishedweek522019.ods\n",
-      " publishedweek522019.xls\n",
-      " scotland-deaths-2020.csv\n",
-      " weekly-april-20-tab2_Sheet.csv\n",
-      " weekly-april-20-tab2.xlsx\n",
-      " weekly-deaths-april-20-scotland.csv\n",
-      " weekly-deaths-april-20-scotland.xlsx\n",
-      " weekly-deaths-april-20-scotland.zip\n",
-      "'Weekly_Deaths - Historical_NI.xls'\n",
-      " Weekly_Deaths_NI_2015.csv\n",
-      " Weekly_Deaths_NI_2016.csv\n",
-      " Weekly_Deaths_NI_2017.csv\n",
-      " Weekly_Deaths_NI_2018.csv\n",
-      " Weekly_Deaths_NI_2019.csv\n",
-      " Weekly_Deaths_NI_2020.csv\n",
-      " Weekly_Deaths_NI_2020.xls\n",
-      " weekly-march-20-scotland.zip\n"
-     ]
-    }
-   ],
+   "execution_count": 2,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
     "source": [
     "source": [
-    "!ls uk-deaths-data"
+    "england_wales_filename = 'uk-deaths-data/publishedweek532020.xlsx'"
     ]
    },
    {
     "cell_type": "code",
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 78,
-   "metadata": {},
+   "execution_count": 3,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "raw_data_2015 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2015.csv', \n",
     "outputs": [],
     "source": [
      "raw_data_2015 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2015.csv', \n",
@@ -133,8 +64,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 79,
-   "metadata": {},
+   "execution_count": 4,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "raw_data_2016 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2016.csv', \n",
     "outputs": [],
     "source": [
      "raw_data_2016 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2016.csv', \n",
@@ -149,8 +82,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 80,
-   "metadata": {},
+   "execution_count": 5,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "raw_data_2017 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2017.csv', \n",
     "outputs": [],
     "source": [
      "raw_data_2017 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2017.csv', \n",
@@ -165,8 +100,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 81,
-   "metadata": {},
+   "execution_count": 6,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "raw_data_2018 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2018.csv', \n",
     "outputs": [],
     "source": [
      "raw_data_2018 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2018.csv', \n",
@@ -181,8 +118,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 82,
-   "metadata": {},
+   "execution_count": 7,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "raw_data_2019 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2019.csv', \n",
     "outputs": [],
     "source": [
      "raw_data_2019 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2019.csv', \n",
@@ -197,8 +136,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 83,
-   "metadata": {},
+   "execution_count": 8,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
@@ -226,39 +167,39 @@
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
-       "      <td>1</td>\n",
-       "      <td>353</td>\n",
+       "      <th>49</th>\n",
+       "      <td>387</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2</td>\n",
-       "      <td>395</td>\n",
+       "      <th>50</th>\n",
+       "      <td>366</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>3</td>\n",
-       "      <td>411</td>\n",
+       "      <th>51</th>\n",
+       "      <td>350</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>4</td>\n",
-       "      <td>347</td>\n",
+       "      <th>52</th>\n",
+       "      <td>310</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>5</td>\n",
-       "      <td>323</td>\n",
+       "      <th>53</th>\n",
+       "      <td>333</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "</div>"
        ],
        "text/plain": [
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "</div>"
        ],
        "text/plain": [
-       "   total_2020\n",
-       "1         353\n",
-       "2         395\n",
-       "3         411\n",
-       "4         347\n",
-       "5         323"
+       "    total_2020\n",
+       "49         387\n",
+       "50         366\n",
+       "51         350\n",
+       "52         310\n",
+       "53         333"
        ]
       },
        ]
       },
-     "execution_count": 83,
+     "execution_count": 8,
       "metadata": {},
       "output_type": "execute_result"
      }
       "metadata": {},
       "output_type": "execute_result"
      }
@@ -271,44 +212,14 @@
      "                           )\n",
      "deaths_headlines_i = raw_data_2020_i.iloc[:, [1]]\n",
      "deaths_headlines_i.columns = ['total_2020']\n",
      "                           )\n",
      "deaths_headlines_i = raw_data_2020_i.iloc[:, [1]]\n",
      "deaths_headlines_i.columns = ['total_2020']\n",
-    "deaths_headlines_i.head()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 84,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [],
-   "source": [
-    "raw_data_s = pd.read_csv('uk-deaths-data/weekly-deaths-april-20-scotland.csv', \n",
-    "                      index_col=0,\n",
-    "                      header=0,\n",
-    "                        skiprows=2\n",
-    "                           )\n",
-    "# raw_data_s"
+    "deaths_headlines_i.tail()"
     ]
    },
    {
     "cell_type": "code",
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 85,
+   "execution_count": 9,
     "metadata": {
     "metadata": {
-    "scrolled": true
+    "Collapsed": "false"
     },
     "outputs": [
      {
     },
     "outputs": [
      {
@@ -324,585 +235,766 @@
         "        vertical-align: top;\n",
         "    }\n",
         "\n",
         "        vertical-align: top;\n",
         "    }\n",
         "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
+       "    .dataframe thead tr th {\n",
+       "        text-align: left;\n",
         "    }\n",
         "</style>\n",
         "<table border=\"1\" class=\"dataframe\">\n",
         "  <thead>\n",
         "    }\n",
         "</style>\n",
         "<table border=\"1\" class=\"dataframe\">\n",
         "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
+       "    <tr>\n",
+       "      <th>Registration Week</th>\n",
+       "      <th>Week Starts (Saturday)</th>\n",
+       "      <th>Week Ends (Friday)</th>\n",
+       "      <th>Total Number of Deaths Registered in Week (2019P)</th>\n",
+       "      <th>Average number of deaths registered in corresponding week in previous 5 years (2014 to 2018P)</th>\n",
+       "      <th>Range</th>\n",
+       "      <th>Unnamed: 6_level_0</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
         "      <th></th>\n",
         "      <th></th>\n",
-       "      <th>total_2020</th>\n",
-       "      <th>total_2019</th>\n",
-       "      <th>total_2018</th>\n",
-       "      <th>total_2017</th>\n",
-       "      <th>total_2016</th>\n",
-       "      <th>total_2015</th>\n",
+       "      <th>Unnamed: 1_level_1</th>\n",
+       "      <th>Unnamed: 2_level_1</th>\n",
+       "      <th>Unnamed: 3_level_1</th>\n",
+       "      <th>Unnamed: 4_level_1</th>\n",
+       "      <th>Minimum in Previous 5 years</th>\n",
+       "      <th>Maximum in Previous 5 years</th>\n",
         "    </tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
         "    </tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
-       "      <td>1</td>\n",
-       "      <td>1161.0</td>\n",
-       "      <td>1104.0</td>\n",
-       "      <td>1531.0</td>\n",
-       "      <td>1205.0</td>\n",
-       "      <td>1394.0</td>\n",
-       "      <td>1146</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2</td>\n",
-       "      <td>1567.0</td>\n",
-       "      <td>1507.0</td>\n",
-       "      <td>1899.0</td>\n",
-       "      <td>1379.0</td>\n",
-       "      <td>1305.0</td>\n",
-       "      <td>1708</td>\n",
+       "      <th>1</th>\n",
+       "      <td>2018-12-29</td>\n",
+       "      <td>2019-01-04</td>\n",
+       "      <td>365</td>\n",
+       "      <td>212</td>\n",
+       "      <td>178</td>\n",
+       "      <td>249</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>3</td>\n",
-       "      <td>1322.0</td>\n",
-       "      <td>1353.0</td>\n",
-       "      <td>1629.0</td>\n",
-       "      <td>1224.0</td>\n",
-       "      <td>1215.0</td>\n",
-       "      <td>1489</td>\n",
+       "      <th>2</th>\n",
+       "      <td>2019-01-05</td>\n",
+       "      <td>2019-01-11</td>\n",
+       "      <td>371</td>\n",
+       "      <td>387</td>\n",
+       "      <td>294</td>\n",
+       "      <td>481</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>4</td>\n",
-       "      <td>1226.0</td>\n",
-       "      <td>1208.0</td>\n",
-       "      <td>1610.0</td>\n",
-       "      <td>1197.0</td>\n",
-       "      <td>1187.0</td>\n",
-       "      <td>1381</td>\n",
+       "      <th>3</th>\n",
+       "      <td>2019-01-12</td>\n",
+       "      <td>2019-01-18</td>\n",
+       "      <td>332</td>\n",
+       "      <td>401</td>\n",
+       "      <td>348</td>\n",
+       "      <td>470</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>5</td>\n",
-       "      <td>1188.0</td>\n",
-       "      <td>1206.0</td>\n",
-       "      <td>1369.0</td>\n",
-       "      <td>1332.0</td>\n",
-       "      <td>1205.0</td>\n",
-       "      <td>1286</td>\n",
+       "      <th>4</th>\n",
+       "      <td>2019-01-19</td>\n",
+       "      <td>2019-01-25</td>\n",
+       "      <td>335</td>\n",
+       "      <td>382</td>\n",
+       "      <td>331</td>\n",
+       "      <td>426</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>6</td>\n",
-       "      <td>1216.0</td>\n",
-       "      <td>1243.0</td>\n",
-       "      <td>1265.0</td>\n",
-       "      <td>1200.0</td>\n",
-       "      <td>1217.0</td>\n",
-       "      <td>1344</td>\n",
+       "      <th>5</th>\n",
+       "      <td>2019-01-26</td>\n",
+       "      <td>2019-02-01</td>\n",
+       "      <td>296</td>\n",
+       "      <td>385</td>\n",
+       "      <td>353</td>\n",
+       "      <td>433</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>7</td>\n",
-       "      <td>1162.0</td>\n",
-       "      <td>1181.0</td>\n",
-       "      <td>1315.0</td>\n",
-       "      <td>1231.0</td>\n",
-       "      <td>1209.0</td>\n",
-       "      <td>1360</td>\n",
+       "      <th>6</th>\n",
+       "      <td>2019-02-02</td>\n",
+       "      <td>2019-02-08</td>\n",
+       "      <td>319</td>\n",
+       "      <td>349</td>\n",
+       "      <td>314</td>\n",
+       "      <td>374</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>8</td>\n",
-       "      <td>1162.0</td>\n",
-       "      <td>1245.0</td>\n",
-       "      <td>1245.0</td>\n",
-       "      <td>1185.0</td>\n",
-       "      <td>1239.0</td>\n",
-       "      <td>1320</td>\n",
+       "      <th>7</th>\n",
+       "      <td>2019-02-09</td>\n",
+       "      <td>2019-02-15</td>\n",
+       "      <td>342</td>\n",
+       "      <td>327</td>\n",
+       "      <td>280</td>\n",
+       "      <td>364</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>9</td>\n",
-       "      <td>1171.0</td>\n",
-       "      <td>1125.0</td>\n",
-       "      <td>1022.0</td>\n",
-       "      <td>1219.0</td>\n",
-       "      <td>1150.0</td>\n",
-       "      <td>1308</td>\n",
+       "      <th>8</th>\n",
+       "      <td>2019-02-16</td>\n",
+       "      <td>2019-02-22</td>\n",
+       "      <td>337</td>\n",
+       "      <td>309</td>\n",
+       "      <td>217</td>\n",
+       "      <td>366</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>10</td>\n",
-       "      <td>1208.0</td>\n",
-       "      <td>1156.0</td>\n",
-       "      <td>1475.0</td>\n",
-       "      <td>1146.0</td>\n",
-       "      <td>1174.0</td>\n",
-       "      <td>1192</td>\n",
+       "      <th>9</th>\n",
+       "      <td>2019-02-23</td>\n",
+       "      <td>2019-03-01</td>\n",
+       "      <td>310</td>\n",
+       "      <td>347</td>\n",
+       "      <td>314</td>\n",
+       "      <td>423</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>11</td>\n",
-       "      <td>1156.0</td>\n",
-       "      <td>1108.0</td>\n",
-       "      <td>1220.0</td>\n",
-       "      <td>1141.0</td>\n",
-       "      <td>1175.0</td>\n",
-       "      <td>1201</td>\n",
+       "      <th>10</th>\n",
+       "      <td>2019-03-02</td>\n",
+       "      <td>2019-03-08</td>\n",
+       "      <td>342</td>\n",
+       "      <td>345</td>\n",
+       "      <td>285</td>\n",
+       "      <td>401</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>12</td>\n",
-       "      <td>1196.0</td>\n",
-       "      <td>1101.0</td>\n",
-       "      <td>1158.0</td>\n",
-       "      <td>1152.0</td>\n",
-       "      <td>1042.0</td>\n",
-       "      <td>1149</td>\n",
+       "      <th>11</th>\n",
+       "      <td>2019-03-09</td>\n",
+       "      <td>2019-03-15</td>\n",
+       "      <td>343</td>\n",
+       "      <td>338</td>\n",
+       "      <td>309</td>\n",
+       "      <td>359</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>13</td>\n",
-       "      <td>1079.0</td>\n",
-       "      <td>1086.0</td>\n",
-       "      <td>1050.0</td>\n",
-       "      <td>1112.0</td>\n",
-       "      <td>1172.0</td>\n",
-       "      <td>1171</td>\n",
+       "      <th>12</th>\n",
+       "      <td>2019-03-16</td>\n",
+       "      <td>2019-03-22</td>\n",
+       "      <td>294</td>\n",
+       "      <td>304</td>\n",
+       "      <td>251</td>\n",
+       "      <td>327</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>14</td>\n",
-       "      <td>1744.0</td>\n",
-       "      <td>1032.0</td>\n",
-       "      <td>1192.0</td>\n",
-       "      <td>1060.0</td>\n",
-       "      <td>1166.0</td>\n",
-       "      <td>1042</td>\n",
+       "      <th>13</th>\n",
+       "      <td>2019-03-23</td>\n",
+       "      <td>2019-03-29</td>\n",
+       "      <td>307</td>\n",
+       "      <td>310</td>\n",
+       "      <td>261</td>\n",
+       "      <td>356</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>15</td>\n",
-       "      <td>1978.0</td>\n",
-       "      <td>1069.0</td>\n",
-       "      <td>1192.0</td>\n",
-       "      <td>998.0</td>\n",
-       "      <td>1048.0</td>\n",
-       "      <td>1192</td>\n",
+       "      <th>14</th>\n",
+       "      <td>2019-03-30</td>\n",
+       "      <td>2019-04-05</td>\n",
+       "      <td>287</td>\n",
+       "      <td>301</td>\n",
+       "      <td>280</td>\n",
+       "      <td>323</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>16</td>\n",
-       "      <td>1916.0</td>\n",
-       "      <td>902.0</td>\n",
-       "      <td>1136.0</td>\n",
-       "      <td>1111.0</td>\n",
-       "      <td>1092.0</td>\n",
-       "      <td>1095</td>\n",
+       "      <th>15</th>\n",
+       "      <td>2019-04-06</td>\n",
+       "      <td>2019-04-12</td>\n",
+       "      <td>301</td>\n",
+       "      <td>292</td>\n",
+       "      <td>221</td>\n",
+       "      <td>350</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>17</td>\n",
-       "      <td>1836.0</td>\n",
-       "      <td>1121.0</td>\n",
-       "      <td>1008.0</td>\n",
-       "      <td>1121.0</td>\n",
-       "      <td>1076.0</td>\n",
-       "      <td>1108</td>\n",
+       "      <th>16</th>\n",
+       "      <td>2019-04-13</td>\n",
+       "      <td>2019-04-19</td>\n",
+       "      <td>316</td>\n",
+       "      <td>290</td>\n",
+       "      <td>270</td>\n",
+       "      <td>316</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>18</td>\n",
-       "      <td>1679.0</td>\n",
-       "      <td>1131.0</td>\n",
-       "      <td>1093.0</td>\n",
-       "      <td>1050.0</td>\n",
-       "      <td>1006.0</td>\n",
-       "      <td>1117</td>\n",
+       "      <th>17</th>\n",
+       "      <td>2019-04-20</td>\n",
+       "      <td>2019-04-26</td>\n",
+       "      <td>272</td>\n",
+       "      <td>279</td>\n",
+       "      <td>245</td>\n",
+       "      <td>327</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>19</td>\n",
-       "      <td>1435.0</td>\n",
-       "      <td>1018.0</td>\n",
-       "      <td>967.0</td>\n",
-       "      <td>1119.0</td>\n",
-       "      <td>1047.0</td>\n",
-       "      <td>1020</td>\n",
+       "      <th>18</th>\n",
+       "      <td>2019-04-27</td>\n",
+       "      <td>2019-05-03</td>\n",
+       "      <td>357</td>\n",
+       "      <td>298</td>\n",
+       "      <td>251</td>\n",
+       "      <td>327</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>20</td>\n",
-       "      <td>1421.0</td>\n",
-       "      <td>1115.0</td>\n",
-       "      <td>977.0</td>\n",
-       "      <td>1115.0</td>\n",
-       "      <td>1010.0</td>\n",
-       "      <td>1103</td>\n",
+       "      <th>19</th>\n",
+       "      <td>2019-05-04</td>\n",
+       "      <td>2019-05-10</td>\n",
+       "      <td>288</td>\n",
+       "      <td>279</td>\n",
+       "      <td>230</td>\n",
+       "      <td>335</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>21</td>\n",
-       "      <td>1226.0</td>\n",
-       "      <td>1061.0</td>\n",
-       "      <td>1070.0</td>\n",
-       "      <td>1063.0</td>\n",
-       "      <td>994.0</td>\n",
-       "      <td>1039</td>\n",
+       "      <th>20</th>\n",
+       "      <td>2019-05-11</td>\n",
+       "      <td>2019-05-17</td>\n",
+       "      <td>330</td>\n",
+       "      <td>279</td>\n",
+       "      <td>249</td>\n",
+       "      <td>318</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>22</td>\n",
-       "      <td>1125.0</td>\n",
-       "      <td>1029.0</td>\n",
-       "      <td>998.0</td>\n",
-       "      <td>1015.0</td>\n",
-       "      <td>999.0</td>\n",
-       "      <td>1043</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>23</td>\n",
-       "      <td>1093.0</td>\n",
-       "      <td>1042.0</td>\n",
-       "      <td>1033.0</td>\n",
-       "      <td>1076.0</td>\n",
-       "      <td>1023.0</td>\n",
-       "      <td>1106</td>\n",
+       "      <th>21</th>\n",
+       "      <td>2019-05-18</td>\n",
+       "      <td>2019-05-24</td>\n",
+       "      <td>308</td>\n",
+       "      <td>278</td>\n",
+       "      <td>250</td>\n",
+       "      <td>315</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>24</td>\n",
-       "      <td>1034.0</td>\n",
-       "      <td>1028.0</td>\n",
-       "      <td>915.0</td>\n",
-       "      <td>1031.0</td>\n",
-       "      <td>988.0</td>\n",
-       "      <td>1038</td>\n",
+       "      <th>22</th>\n",
+       "      <td>2019-05-25</td>\n",
+       "      <td>2019-05-31</td>\n",
+       "      <td>245</td>\n",
+       "      <td>278</td>\n",
+       "      <td>241</td>\n",
+       "      <td>328</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>25</td>\n",
-       "      <td>1065.0</td>\n",
-       "      <td>1053.0</td>\n",
-       "      <td>993.0</td>\n",
-       "      <td>1032.0</td>\n",
-       "      <td>994.0</td>\n",
-       "      <td>1025</td>\n",
+       "      <th>23</th>\n",
+       "      <td>2019-06-01</td>\n",
+       "      <td>2019-06-07</td>\n",
+       "      <td>279</td>\n",
+       "      <td>263</td>\n",
+       "      <td>241</td>\n",
+       "      <td>284</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>26</td>\n",
-       "      <td>1008.0</td>\n",
-       "      <td>1051.0</td>\n",
-       "      <td>1046.0</td>\n",
-       "      <td>994.0</td>\n",
-       "      <td>1007.0</td>\n",
-       "      <td>1032</td>\n",
+       "      <th>24</th>\n",
+       "      <td>2019-06-08</td>\n",
+       "      <td>2019-06-14</td>\n",
+       "      <td>281</td>\n",
+       "      <td>286</td>\n",
+       "      <td>246</td>\n",
+       "      <td>340</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>27</td>\n",
-       "      <td>983.0</td>\n",
-       "      <td>981.0</td>\n",
-       "      <td>1041.0</td>\n",
-       "      <td>1040.0</td>\n",
-       "      <td>988.0</td>\n",
-       "      <td>1040</td>\n",
+       "      <th>25</th>\n",
+       "      <td>2019-06-15</td>\n",
+       "      <td>2019-06-21</td>\n",
+       "      <td>296</td>\n",
+       "      <td>284</td>\n",
+       "      <td>265</td>\n",
+       "      <td>300</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>28</td>\n",
-       "      <td>976.0</td>\n",
-       "      <td>1077.0</td>\n",
-       "      <td>1002.0</td>\n",
-       "      <td>1014.0</td>\n",
-       "      <td>1022.0</td>\n",
-       "      <td>1011</td>\n",
+       "      <th>26</th>\n",
+       "      <td>2019-06-22</td>\n",
+       "      <td>2019-06-28</td>\n",
+       "      <td>262</td>\n",
+       "      <td>259</td>\n",
+       "      <td>211</td>\n",
+       "      <td>292</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>29</td>\n",
-       "      <td>1033.0</td>\n",
-       "      <td>964.0</td>\n",
-       "      <td>928.0</td>\n",
-       "      <td>1025.0</td>\n",
-       "      <td>1041.0</td>\n",
-       "      <td>1023</td>\n",
+       "      <th>27</th>\n",
+       "      <td>2019-06-29</td>\n",
+       "      <td>2019-07-05</td>\n",
+       "      <td>285</td>\n",
+       "      <td>278</td>\n",
+       "      <td>235</td>\n",
+       "      <td>303</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>30</td>\n",
-       "      <td>961.0</td>\n",
-       "      <td>1041.0</td>\n",
-       "      <td>933.0</td>\n",
-       "      <td>978.0</td>\n",
-       "      <td>979.0</td>\n",
-       "      <td>956</td>\n",
+       "      <th>28</th>\n",
+       "      <td>2019-07-06</td>\n",
+       "      <td>2019-07-12</td>\n",
+       "      <td>256</td>\n",
+       "      <td>254</td>\n",
+       "      <td>172</td>\n",
+       "      <td>300</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>31</td>\n",
-       "      <td>1043.0</td>\n",
-       "      <td>1020.0</td>\n",
-       "      <td>969.0</td>\n",
-       "      <td>1011.0</td>\n",
-       "      <td>987.0</td>\n",
-       "      <td>985</td>\n",
+       "      <th>29</th>\n",
+       "      <td>2019-07-13</td>\n",
+       "      <td>2019-07-19</td>\n",
+       "      <td>280</td>\n",
+       "      <td>256</td>\n",
+       "      <td>237</td>\n",
+       "      <td>298</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>32</td>\n",
-       "      <td>1002.0</td>\n",
-       "      <td>1018.0</td>\n",
-       "      <td>953.0</td>\n",
-       "      <td>1002.0</td>\n",
-       "      <td>997.0</td>\n",
-       "      <td>1043</td>\n",
+       "      <th>30</th>\n",
+       "      <td>2019-07-20</td>\n",
+       "      <td>2019-07-26</td>\n",
+       "      <td>269</td>\n",
+       "      <td>255</td>\n",
+       "      <td>203</td>\n",
+       "      <td>288</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>33</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1028.0</td>\n",
-       "      <td>978.0</td>\n",
-       "      <td>1004.0</td>\n",
-       "      <td>982.0</td>\n",
-       "      <td>969</td>\n",
+       "      <th>31</th>\n",
+       "      <td>2019-07-27</td>\n",
+       "      <td>2019-08-02</td>\n",
+       "      <td>273</td>\n",
+       "      <td>280</td>\n",
+       "      <td>261</td>\n",
+       "      <td>298</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>34</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1011.0</td>\n",
-       "      <td>941.0</td>\n",
-       "      <td>1045.0</td>\n",
-       "      <td>1017.0</td>\n",
-       "      <td>982</td>\n",
+       "      <th>32</th>\n",
+       "      <td>2019-08-03</td>\n",
+       "      <td>2019-08-09</td>\n",
+       "      <td>266</td>\n",
+       "      <td>281</td>\n",
+       "      <td>264</td>\n",
+       "      <td>292</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>35</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1013.0</td>\n",
-       "      <td>930.0</td>\n",
-       "      <td>980.0</td>\n",
-       "      <td>1039.0</td>\n",
-       "      <td>954</td>\n",
+       "      <th>33</th>\n",
+       "      <td>2019-08-10</td>\n",
+       "      <td>2019-08-16</td>\n",
+       "      <td>284</td>\n",
+       "      <td>260</td>\n",
+       "      <td>238</td>\n",
+       "      <td>283</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>36</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>980.0</td>\n",
-       "      <td>970.0</td>\n",
-       "      <td>1006.0</td>\n",
-       "      <td>1007.0</td>\n",
-       "      <td>977</td>\n",
+       "      <th>34</th>\n",
+       "      <td>2019-08-17</td>\n",
+       "      <td>2019-08-23</td>\n",
+       "      <td>274</td>\n",
+       "      <td>260</td>\n",
+       "      <td>235</td>\n",
+       "      <td>280</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>37</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1074.0</td>\n",
-       "      <td>1020.0</td>\n",
-       "      <td>972.0</td>\n",
-       "      <td>983.0</td>\n",
-       "      <td>991</td>\n",
+       "      <th>35</th>\n",
+       "      <td>2019-08-24</td>\n",
+       "      <td>2019-08-30</td>\n",
+       "      <td>223</td>\n",
+       "      <td>271</td>\n",
+       "      <td>251</td>\n",
+       "      <td>301</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>38</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1071.0</td>\n",
-       "      <td>946.0</td>\n",
-       "      <td>1049.0</td>\n",
-       "      <td>966.0</td>\n",
-       "      <td>1001</td>\n",
+       "      <th>36</th>\n",
+       "      <td>2019-08-31</td>\n",
+       "      <td>2019-09-06</td>\n",
+       "      <td>243</td>\n",
+       "      <td>258</td>\n",
+       "      <td>243</td>\n",
+       "      <td>265</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>39</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1142.0</td>\n",
-       "      <td>1015.0</td>\n",
-       "      <td>1056.0</td>\n",
-       "      <td>1009.0</td>\n",
-       "      <td>1010</td>\n",
+       "      <th>37</th>\n",
+       "      <td>2019-09-07</td>\n",
+       "      <td>2019-09-13</td>\n",
+       "      <td>305</td>\n",
+       "      <td>275</td>\n",
+       "      <td>237</td>\n",
+       "      <td>301</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>40</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1051.0</td>\n",
-       "      <td>1042.0</td>\n",
-       "      <td>1016.0</td>\n",
-       "      <td>1072.0</td>\n",
-       "      <td>1008</td>\n",
+       "      <th>38</th>\n",
+       "      <td>2019-09-14</td>\n",
+       "      <td>2019-09-20</td>\n",
+       "      <td>281</td>\n",
+       "      <td>285</td>\n",
+       "      <td>247</td>\n",
+       "      <td>324</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>41</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1143.0</td>\n",
-       "      <td>1081.0</td>\n",
-       "      <td>1133.0</td>\n",
-       "      <td>1009.0</td>\n",
-       "      <td>1028</td>\n",
+       "      <th>39</th>\n",
+       "      <td>2019-09-21</td>\n",
+       "      <td>2019-09-27</td>\n",
+       "      <td>295</td>\n",
+       "      <td>281</td>\n",
+       "      <td>259</td>\n",
+       "      <td>298</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>42</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1153.0</td>\n",
-       "      <td>1031.0</td>\n",
-       "      <td>1067.0</td>\n",
-       "      <td>1070.0</td>\n",
-       "      <td>989</td>\n",
+       "      <th>40</th>\n",
+       "      <td>2019-09-28</td>\n",
+       "      <td>2019-10-04</td>\n",
+       "      <td>263</td>\n",
+       "      <td>292</td>\n",
+       "      <td>275</td>\n",
+       "      <td>324</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>43</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1115.0</td>\n",
-       "      <td>1019.0</td>\n",
-       "      <td>1095.0</td>\n",
-       "      <td>1052.0</td>\n",
-       "      <td>981</td>\n",
+       "      <th>41</th>\n",
+       "      <td>2019-10-05</td>\n",
+       "      <td>2019-10-11</td>\n",
+       "      <td>287</td>\n",
+       "      <td>298</td>\n",
+       "      <td>277</td>\n",
+       "      <td>318</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>44</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1101.0</td>\n",
-       "      <td>1085.0</td>\n",
-       "      <td>1062.0</td>\n",
-       "      <td>1032.0</td>\n",
-       "      <td>1116</td>\n",
+       "      <th>42</th>\n",
+       "      <td>2019-10-12</td>\n",
+       "      <td>2019-10-18</td>\n",
+       "      <td>316</td>\n",
+       "      <td>295</td>\n",
+       "      <td>282</td>\n",
+       "      <td>317</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>45</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1184.0</td>\n",
-       "      <td>1144.0</td>\n",
-       "      <td>1126.0</td>\n",
-       "      <td>1043.0</td>\n",
-       "      <td>1028</td>\n",
+       "      <th>43</th>\n",
+       "      <td>2019-10-19</td>\n",
+       "      <td>2019-10-25</td>\n",
+       "      <td>279</td>\n",
+       "      <td>287</td>\n",
+       "      <td>263</td>\n",
+       "      <td>299</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>46</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1160.0</td>\n",
-       "      <td>1084.0</td>\n",
-       "      <td>1175.0</td>\n",
-       "      <td>1174.0</td>\n",
-       "      <td>1103</td>\n",
+       "      <th>44</th>\n",
+       "      <td>2019-10-26</td>\n",
+       "      <td>2019-11-01</td>\n",
+       "      <td>302</td>\n",
+       "      <td>283</td>\n",
+       "      <td>252</td>\n",
+       "      <td>318</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>47</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1229.0</td>\n",
-       "      <td>1058.0</td>\n",
-       "      <td>1178.0</td>\n",
-       "      <td>1132.0</td>\n",
-       "      <td>1054</td>\n",
+       "      <th>45</th>\n",
+       "      <td>2019-11-02</td>\n",
+       "      <td>2019-11-08</td>\n",
+       "      <td>296</td>\n",
+       "      <td>290</td>\n",
+       "      <td>267</td>\n",
+       "      <td>320</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>48</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1163.0</td>\n",
-       "      <td>1062.0</td>\n",
-       "      <td>1153.0</td>\n",
-       "      <td>1159.0</td>\n",
-       "      <td>1115</td>\n",
+       "      <th>46</th>\n",
+       "      <td>2019-11-09</td>\n",
+       "      <td>2019-11-15</td>\n",
+       "      <td>336</td>\n",
+       "      <td>286</td>\n",
+       "      <td>275</td>\n",
+       "      <td>295</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>49</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1108.0</td>\n",
-       "      <td>1076.0</td>\n",
-       "      <td>1237.0</td>\n",
-       "      <td>1188.0</td>\n",
-       "      <td>1089</td>\n",
+       "      <th>47</th>\n",
+       "      <td>2019-11-16</td>\n",
+       "      <td>2019-11-22</td>\n",
+       "      <td>361</td>\n",
+       "      <td>305</td>\n",
+       "      <td>274</td>\n",
+       "      <td>341</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>50</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1312.0</td>\n",
-       "      <td>1212.0</td>\n",
-       "      <td>1335.0</td>\n",
-       "      <td>1219.0</td>\n",
-       "      <td>1101</td>\n",
+       "      <th>48</th>\n",
+       "      <td>2019-11-23</td>\n",
+       "      <td>2019-11-29</td>\n",
+       "      <td>334</td>\n",
+       "      <td>304</td>\n",
+       "      <td>294</td>\n",
+       "      <td>329</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>51</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1277.0</td>\n",
-       "      <td>1216.0</td>\n",
-       "      <td>1437.0</td>\n",
-       "      <td>1284.0</td>\n",
-       "      <td>1146</td>\n",
+       "      <th>49</th>\n",
+       "      <td>2019-11-30</td>\n",
+       "      <td>2019-12-06</td>\n",
+       "      <td>351</td>\n",
+       "      <td>310</td>\n",
+       "      <td>279</td>\n",
+       "      <td>355</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>52</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1000.0</td>\n",
-       "      <td>1058.0</td>\n",
-       "      <td>1168.0</td>\n",
-       "      <td>1133.0</td>\n",
-       "      <td>944</td>\n",
+       "      <th>50</th>\n",
+       "      <td>2019-12-07</td>\n",
+       "      <td>2019-12-13</td>\n",
+       "      <td>353</td>\n",
+       "      <td>306</td>\n",
+       "      <td>275</td>\n",
+       "      <td>324</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>53</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1018</td>\n",
+       "      <th>51</th>\n",
+       "      <td>2019-12-14</td>\n",
+       "      <td>2019-12-20</td>\n",
+       "      <td>363</td>\n",
+       "      <td>331</td>\n",
+       "      <td>298</td>\n",
+       "      <td>372</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>2019-12-21</td>\n",
+       "      <td>2019-12-27</td>\n",
+       "      <td>194</td>\n",
+       "      <td>298</td>\n",
+       "      <td>195</td>\n",
+       "      <td>360</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "</div>"
        ],
        "text/plain": [
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "</div>"
        ],
        "text/plain": [
-       "    total_2020  total_2019  total_2018  total_2017  total_2016  total_2015\n",
-       "1       1161.0      1104.0      1531.0      1205.0      1394.0        1146\n",
-       "2       1567.0      1507.0      1899.0      1379.0      1305.0        1708\n",
-       "3       1322.0      1353.0      1629.0      1224.0      1215.0        1489\n",
-       "4       1226.0      1208.0      1610.0      1197.0      1187.0        1381\n",
-       "5       1188.0      1206.0      1369.0      1332.0      1205.0        1286\n",
-       "6       1216.0      1243.0      1265.0      1200.0      1217.0        1344\n",
-       "7       1162.0      1181.0      1315.0      1231.0      1209.0        1360\n",
-       "8       1162.0      1245.0      1245.0      1185.0      1239.0        1320\n",
-       "9       1171.0      1125.0      1022.0      1219.0      1150.0        1308\n",
-       "10      1208.0      1156.0      1475.0      1146.0      1174.0        1192\n",
-       "11      1156.0      1108.0      1220.0      1141.0      1175.0        1201\n",
-       "12      1196.0      1101.0      1158.0      1152.0      1042.0        1149\n",
-       "13      1079.0      1086.0      1050.0      1112.0      1172.0        1171\n",
-       "14      1744.0      1032.0      1192.0      1060.0      1166.0        1042\n",
-       "15      1978.0      1069.0      1192.0       998.0      1048.0        1192\n",
-       "16      1916.0       902.0      1136.0      1111.0      1092.0        1095\n",
-       "17      1836.0      1121.0      1008.0      1121.0      1076.0        1108\n",
-       "18      1679.0      1131.0      1093.0      1050.0      1006.0        1117\n",
-       "19      1435.0      1018.0       967.0      1119.0      1047.0        1020\n",
-       "20      1421.0      1115.0       977.0      1115.0      1010.0        1103\n",
-       "21      1226.0      1061.0      1070.0      1063.0       994.0        1039\n",
-       "22      1125.0      1029.0       998.0      1015.0       999.0        1043\n",
-       "23      1093.0      1042.0      1033.0      1076.0      1023.0        1106\n",
-       "24      1034.0      1028.0       915.0      1031.0       988.0        1038\n",
-       "25      1065.0      1053.0       993.0      1032.0       994.0        1025\n",
-       "26      1008.0      1051.0      1046.0       994.0      1007.0        1032\n",
-       "27       983.0       981.0      1041.0      1040.0       988.0        1040\n",
-       "28       976.0      1077.0      1002.0      1014.0      1022.0        1011\n",
-       "29      1033.0       964.0       928.0      1025.0      1041.0        1023\n",
-       "30       961.0      1041.0       933.0       978.0       979.0         956\n",
-       "31      1043.0      1020.0       969.0      1011.0       987.0         985\n",
-       "32      1002.0      1018.0       953.0      1002.0       997.0        1043\n",
-       "33         NaN      1028.0       978.0      1004.0       982.0         969\n",
-       "34         NaN      1011.0       941.0      1045.0      1017.0         982\n",
-       "35         NaN      1013.0       930.0       980.0      1039.0         954\n",
-       "36         NaN       980.0       970.0      1006.0      1007.0         977\n",
-       "37         NaN      1074.0      1020.0       972.0       983.0         991\n",
-       "38         NaN      1071.0       946.0      1049.0       966.0        1001\n",
-       "39         NaN      1142.0      1015.0      1056.0      1009.0        1010\n",
-       "40         NaN      1051.0      1042.0      1016.0      1072.0        1008\n",
-       "41         NaN      1143.0      1081.0      1133.0      1009.0        1028\n",
-       "42         NaN      1153.0      1031.0      1067.0      1070.0         989\n",
-       "43         NaN      1115.0      1019.0      1095.0      1052.0         981\n",
-       "44         NaN      1101.0      1085.0      1062.0      1032.0        1116\n",
-       "45         NaN      1184.0      1144.0      1126.0      1043.0        1028\n",
-       "46         NaN      1160.0      1084.0      1175.0      1174.0        1103\n",
-       "47         NaN      1229.0      1058.0      1178.0      1132.0        1054\n",
-       "48         NaN      1163.0      1062.0      1153.0      1159.0        1115\n",
-       "49         NaN      1108.0      1076.0      1237.0      1188.0        1089\n",
-       "50         NaN      1312.0      1212.0      1335.0      1219.0        1101\n",
-       "51         NaN      1277.0      1216.0      1437.0      1284.0        1146\n",
-       "52         NaN      1000.0      1058.0      1168.0      1133.0         944\n",
-       "53         NaN         NaN         NaN         NaN         NaN        1018"
+       "Registration Week Week Starts (Saturday) Week Ends (Friday)  \\\n",
+       "                      Unnamed: 1_level_1 Unnamed: 2_level_1   \n",
+       "1                             2018-12-29         2019-01-04   \n",
+       "2                             2019-01-05         2019-01-11   \n",
+       "3                             2019-01-12         2019-01-18   \n",
+       "4                             2019-01-19         2019-01-25   \n",
+       "5                             2019-01-26         2019-02-01   \n",
+       "6                             2019-02-02         2019-02-08   \n",
+       "7                             2019-02-09         2019-02-15   \n",
+       "8                             2019-02-16         2019-02-22   \n",
+       "9                             2019-02-23         2019-03-01   \n",
+       "10                            2019-03-02         2019-03-08   \n",
+       "11                            2019-03-09         2019-03-15   \n",
+       "12                            2019-03-16         2019-03-22   \n",
+       "13                            2019-03-23         2019-03-29   \n",
+       "14                            2019-03-30         2019-04-05   \n",
+       "15                            2019-04-06         2019-04-12   \n",
+       "16                            2019-04-13         2019-04-19   \n",
+       "17                            2019-04-20         2019-04-26   \n",
+       "18                            2019-04-27         2019-05-03   \n",
+       "19                            2019-05-04         2019-05-10   \n",
+       "20                            2019-05-11         2019-05-17   \n",
+       "21                            2019-05-18         2019-05-24   \n",
+       "22                            2019-05-25         2019-05-31   \n",
+       "23                            2019-06-01         2019-06-07   \n",
+       "24                            2019-06-08         2019-06-14   \n",
+       "25                            2019-06-15         2019-06-21   \n",
+       "26                            2019-06-22         2019-06-28   \n",
+       "27                            2019-06-29         2019-07-05   \n",
+       "28                            2019-07-06         2019-07-12   \n",
+       "29                            2019-07-13         2019-07-19   \n",
+       "30                            2019-07-20         2019-07-26   \n",
+       "31                            2019-07-27         2019-08-02   \n",
+       "32                            2019-08-03         2019-08-09   \n",
+       "33                            2019-08-10         2019-08-16   \n",
+       "34                            2019-08-17         2019-08-23   \n",
+       "35                            2019-08-24         2019-08-30   \n",
+       "36                            2019-08-31         2019-09-06   \n",
+       "37                            2019-09-07         2019-09-13   \n",
+       "38                            2019-09-14         2019-09-20   \n",
+       "39                            2019-09-21         2019-09-27   \n",
+       "40                            2019-09-28         2019-10-04   \n",
+       "41                            2019-10-05         2019-10-11   \n",
+       "42                            2019-10-12         2019-10-18   \n",
+       "43                            2019-10-19         2019-10-25   \n",
+       "44                            2019-10-26         2019-11-01   \n",
+       "45                            2019-11-02         2019-11-08   \n",
+       "46                            2019-11-09         2019-11-15   \n",
+       "47                            2019-11-16         2019-11-22   \n",
+       "48                            2019-11-23         2019-11-29   \n",
+       "49                            2019-11-30         2019-12-06   \n",
+       "50                            2019-12-07         2019-12-13   \n",
+       "51                            2019-12-14         2019-12-20   \n",
+       "52                            2019-12-21         2019-12-27   \n",
+       "\n",
+       "Registration Week Total Number of Deaths Registered in Week (2019P)  \\\n",
+       "                                                 Unnamed: 3_level_1   \n",
+       "1                                                               365   \n",
+       "2                                                               371   \n",
+       "3                                                               332   \n",
+       "4                                                               335   \n",
+       "5                                                               296   \n",
+       "6                                                               319   \n",
+       "7                                                               342   \n",
+       "8                                                               337   \n",
+       "9                                                               310   \n",
+       "10                                                              342   \n",
+       "11                                                              343   \n",
+       "12                                                              294   \n",
+       "13                                                              307   \n",
+       "14                                                              287   \n",
+       "15                                                              301   \n",
+       "16                                                              316   \n",
+       "17                                                              272   \n",
+       "18                                                              357   \n",
+       "19                                                              288   \n",
+       "20                                                              330   \n",
+       "21                                                              308   \n",
+       "22                                                              245   \n",
+       "23                                                              279   \n",
+       "24                                                              281   \n",
+       "25                                                              296   \n",
+       "26                                                              262   \n",
+       "27                                                              285   \n",
+       "28                                                              256   \n",
+       "29                                                              280   \n",
+       "30                                                              269   \n",
+       "31                                                              273   \n",
+       "32                                                              266   \n",
+       "33                                                              284   \n",
+       "34                                                              274   \n",
+       "35                                                              223   \n",
+       "36                                                              243   \n",
+       "37                                                              305   \n",
+       "38                                                              281   \n",
+       "39                                                              295   \n",
+       "40                                                              263   \n",
+       "41                                                              287   \n",
+       "42                                                              316   \n",
+       "43                                                              279   \n",
+       "44                                                              302   \n",
+       "45                                                              296   \n",
+       "46                                                              336   \n",
+       "47                                                              361   \n",
+       "48                                                              334   \n",
+       "49                                                              351   \n",
+       "50                                                              353   \n",
+       "51                                                              363   \n",
+       "52                                                              194   \n",
+       "\n",
+       "Registration Week Average number of deaths registered in corresponding week in previous 5 years (2014 to 2018P)  \\\n",
+       "                                                                                             Unnamed: 4_level_1   \n",
+       "1                                                                212                                              \n",
+       "2                                                                387                                              \n",
+       "3                                                                401                                              \n",
+       "4                                                                382                                              \n",
+       "5                                                                385                                              \n",
+       "6                                                                349                                              \n",
+       "7                                                                327                                              \n",
+       "8                                                                309                                              \n",
+       "9                                                                347                                              \n",
+       "10                                                               345                                              \n",
+       "11                                                               338                                              \n",
+       "12                                                               304                                              \n",
+       "13                                                               310                                              \n",
+       "14                                                               301                                              \n",
+       "15                                                               292                                              \n",
+       "16                                                               290                                              \n",
+       "17                                                               279                                              \n",
+       "18                                                               298                                              \n",
+       "19                                                               279                                              \n",
+       "20                                                               279                                              \n",
+       "21                                                               278                                              \n",
+       "22                                                               278                                              \n",
+       "23                                                               263                                              \n",
+       "24                                                               286                                              \n",
+       "25                                                               284                                              \n",
+       "26                                                               259                                              \n",
+       "27                                                               278                                              \n",
+       "28                                                               254                                              \n",
+       "29                                                               256                                              \n",
+       "30                                                               255                                              \n",
+       "31                                                               280                                              \n",
+       "32                                                               281                                              \n",
+       "33                                                               260                                              \n",
+       "34                                                               260                                              \n",
+       "35                                                               271                                              \n",
+       "36                                                               258                                              \n",
+       "37                                                               275                                              \n",
+       "38                                                               285                                              \n",
+       "39                                                               281                                              \n",
+       "40                                                               292                                              \n",
+       "41                                                               298                                              \n",
+       "42                                                               295                                              \n",
+       "43                                                               287                                              \n",
+       "44                                                               283                                              \n",
+       "45                                                               290                                              \n",
+       "46                                                               286                                              \n",
+       "47                                                               305                                              \n",
+       "48                                                               304                                              \n",
+       "49                                                               310                                              \n",
+       "50                                                               306                                              \n",
+       "51                                                               331                                              \n",
+       "52                                                               298                                              \n",
+       "\n",
+       "Registration Week                       Range          Unnamed: 6_level_0  \n",
+       "                  Minimum in Previous 5 years Maximum in Previous 5 years  \n",
+       "1                                         178                         249  \n",
+       "2                                         294                         481  \n",
+       "3                                         348                         470  \n",
+       "4                                         331                         426  \n",
+       "5                                         353                         433  \n",
+       "6                                         314                         374  \n",
+       "7                                         280                         364  \n",
+       "8                                         217                         366  \n",
+       "9                                         314                         423  \n",
+       "10                                        285                         401  \n",
+       "11                                        309                         359  \n",
+       "12                                        251                         327  \n",
+       "13                                        261                         356  \n",
+       "14                                        280                         323  \n",
+       "15                                        221                         350  \n",
+       "16                                        270                         316  \n",
+       "17                                        245                         327  \n",
+       "18                                        251                         327  \n",
+       "19                                        230                         335  \n",
+       "20                                        249                         318  \n",
+       "21                                        250                         315  \n",
+       "22                                        241                         328  \n",
+       "23                                        241                         284  \n",
+       "24                                        246                         340  \n",
+       "25                                        265                         300  \n",
+       "26                                        211                         292  \n",
+       "27                                        235                         303  \n",
+       "28                                        172                         300  \n",
+       "29                                        237                         298  \n",
+       "30                                        203                         288  \n",
+       "31                                        261                         298  \n",
+       "32                                        264                         292  \n",
+       "33                                        238                         283  \n",
+       "34                                        235                         280  \n",
+       "35                                        251                         301  \n",
+       "36                                        243                         265  \n",
+       "37                                        237                         301  \n",
+       "38                                        247                         324  \n",
+       "39                                        259                         298  \n",
+       "40                                        275                         324  \n",
+       "41                                        277                         318  \n",
+       "42                                        282                         317  \n",
+       "43                                        263                         299  \n",
+       "44                                        252                         318  \n",
+       "45                                        267                         320  \n",
+       "46                                        275                         295  \n",
+       "47                                        274                         341  \n",
+       "48                                        294                         329  \n",
+       "49                                        279                         355  \n",
+       "50                                        275                         324  \n",
+       "51                                        298                         372  \n",
+       "52                                        195                         360  "
        ]
       },
        ]
       },
-     "execution_count": 85,
+     "execution_count": 9,
       "metadata": {},
       "output_type": "execute_result"
      }
     ],
     "source": [
       "metadata": {},
       "output_type": "execute_result"
      }
     ],
     "source": [
-    "deaths_headlines_s = raw_data_s[reversed('2015 2016 2017 2018 2019 2020'.split())]\n",
-    "deaths_headlines_s.columns = ['total_' + c for c in deaths_headlines_s.columns]\n",
-    "deaths_headlines_s.reset_index(drop=True, inplace=True)\n",
-    "deaths_headlines_s.index = deaths_headlines_s.index + 1\n",
-    "deaths_headlines_s"
+    "raw_data_2019"
     ]
    },
    {
     "cell_type": "code",
     "execution_count": null,
     ]
    },
    {
     "cell_type": "code",
     "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": []
    },
    {
     "cell_type": "code",
     "outputs": [],
     "source": []
    },
    {
     "cell_type": "code",
-   "execution_count": 86,
+   "execution_count": 10,
+   "metadata": {
+    "Collapsed": "false",
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "raw_data_s = pd.read_csv('uk-deaths-data/weekly-deaths-scotland.csv', \n",
+    "                      index_col=0,\n",
+    "                      header=0,\n",
+    "                        skiprows=2\n",
+    "                           )\n",
+    "# raw_data_s"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
     "metadata": {
     "metadata": {
+    "Collapsed": "false",
      "scrolled": true
     },
     "outputs": [
      "scrolled": true
     },
     "outputs": [
@@ -927,1325 +1019,1923 @@
         "  <thead>\n",
         "    <tr style=\"text-align: right;\">\n",
         "      <th></th>\n",
         "  <thead>\n",
         "    <tr style=\"text-align: right;\">\n",
         "      <th></th>\n",
-       "      <th>NaN</th>\n",
-       "      <th>NaN</th>\n",
-       "      <th>NaN</th>\n",
-       "      <th>NaN</th>\n",
-       "      <th>NaN</th>\n",
-       "      <th>NaN</th>\n",
-       "      <th>NaN</th>\n",
-       "      <th>NaN</th>\n",
-       "      <th>NaN</th>\n",
-       "      <th>NaN</th>\n",
-       "      <th>...</th>\n",
-       "      <th>North East</th>\n",
-       "      <th>North West</th>\n",
-       "      <th>Yorkshire and The Humber</th>\n",
-       "      <th>East Midlands</th>\n",
-       "      <th>West Midlands</th>\n",
-       "      <th>East</th>\n",
-       "      <th>London</th>\n",
-       "      <th>South East</th>\n",
-       "      <th>South West</th>\n",
-       "      <th>Wales</th>\n",
+       "      <th>total_2020</th>\n",
+       "      <th>total_2019</th>\n",
+       "      <th>total_2018</th>\n",
+       "      <th>total_2017</th>\n",
+       "      <th>total_2016</th>\n",
+       "      <th>total_2015</th>\n",
         "    </tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
         "    </tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
-       "      <td>Week number</td>\n",
-       "      <td>Week ended</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>Total deaths, all ages</td>\n",
-       "      <td>Total deaths: average of corresponding</td>\n",
-       "      <td>week over the previous 5 years 1 (England and ...</td>\n",
-       "      <td>Total deaths: average of corresponding</td>\n",
-       "      <td>week over the previous 5 years 1 (England)</td>\n",
-       "      <td>Total deaths: average of corresponding</td>\n",
-       "      <td>week over the previous 5 years 1 (Wales)</td>\n",
-       "      <td>...</td>\n",
-       "      <td>E12000001</td>\n",
-       "      <td>E12000002</td>\n",
-       "      <td>E12000003</td>\n",
-       "      <td>E12000004</td>\n",
-       "      <td>E12000005</td>\n",
-       "      <td>E12000006</td>\n",
-       "      <td>E12000007</td>\n",
-       "      <td>E12000008</td>\n",
-       "      <td>E12000009</td>\n",
-       "      <td>W92000004</td>\n",
+       "      <th>1</th>\n",
+       "      <td>1161</td>\n",
+       "      <td>1104.0</td>\n",
+       "      <td>1531.0</td>\n",
+       "      <td>1205.0</td>\n",
+       "      <td>1394.0</td>\n",
+       "      <td>1146</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>1</td>\n",
-       "      <td>2020-01-03 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>12254</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>12175</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>11412</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>756</td>\n",
-       "      <td>...</td>\n",
-       "      <td>673</td>\n",
-       "      <td>1806</td>\n",
-       "      <td>1240</td>\n",
-       "      <td>1060</td>\n",
-       "      <td>1349</td>\n",
-       "      <td>1162</td>\n",
-       "      <td>1113</td>\n",
-       "      <td>1814</td>\n",
-       "      <td>1225</td>\n",
-       "      <td>787</td>\n",
+       "      <th>2</th>\n",
+       "      <td>1567</td>\n",
+       "      <td>1507.0</td>\n",
+       "      <td>1899.0</td>\n",
+       "      <td>1379.0</td>\n",
+       "      <td>1305.0</td>\n",
+       "      <td>1708</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2</td>\n",
-       "      <td>2020-01-10 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>14058</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>13822</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>12933</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>856</td>\n",
-       "      <td>...</td>\n",
-       "      <td>707</td>\n",
-       "      <td>1932</td>\n",
-       "      <td>1339</td>\n",
-       "      <td>1195</td>\n",
-       "      <td>1450</td>\n",
-       "      <td>1573</td>\n",
-       "      <td>1272</td>\n",
-       "      <td>2132</td>\n",
-       "      <td>1487</td>\n",
-       "      <td>939</td>\n",
+       "      <th>3</th>\n",
+       "      <td>1322</td>\n",
+       "      <td>1353.0</td>\n",
+       "      <td>1629.0</td>\n",
+       "      <td>1224.0</td>\n",
+       "      <td>1215.0</td>\n",
+       "      <td>1489</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>3</td>\n",
-       "      <td>2020-01-17 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>12990</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>13216</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>12370</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>812</td>\n",
-       "      <td>...</td>\n",
-       "      <td>647</td>\n",
-       "      <td>1696</td>\n",
-       "      <td>1278</td>\n",
-       "      <td>1106</td>\n",
-       "      <td>1407</td>\n",
-       "      <td>1457</td>\n",
-       "      <td>1073</td>\n",
-       "      <td>2064</td>\n",
-       "      <td>1466</td>\n",
-       "      <td>767</td>\n",
+       "      <th>4</th>\n",
+       "      <td>1226</td>\n",
+       "      <td>1208.0</td>\n",
+       "      <td>1610.0</td>\n",
+       "      <td>1197.0</td>\n",
+       "      <td>1187.0</td>\n",
+       "      <td>1381</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>4</td>\n",
-       "      <td>2020-01-24 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>11856</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>12760</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>11933</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>802</td>\n",
-       "      <td>...</td>\n",
-       "      <td>612</td>\n",
-       "      <td>1529</td>\n",
-       "      <td>1187</td>\n",
-       "      <td>1024</td>\n",
-       "      <td>1231</td>\n",
-       "      <td>1410</td>\n",
-       "      <td>1028</td>\n",
-       "      <td>1833</td>\n",
-       "      <td>1253</td>\n",
-       "      <td>723</td>\n",
+       "      <th>5</th>\n",
+       "      <td>1188</td>\n",
+       "      <td>1206.0</td>\n",
+       "      <td>1369.0</td>\n",
+       "      <td>1332.0</td>\n",
+       "      <td>1205.0</td>\n",
+       "      <td>1286</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>5</td>\n",
-       "      <td>2020-01-31 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>11612</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>12206</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>11419</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>760</td>\n",
-       "      <td>...</td>\n",
-       "      <td>561</td>\n",
-       "      <td>1461</td>\n",
-       "      <td>1136</td>\n",
-       "      <td>1015</td>\n",
-       "      <td>1262</td>\n",
-       "      <td>1286</td>\n",
-       "      <td>1092</td>\n",
-       "      <td>1820</td>\n",
-       "      <td>1233</td>\n",
-       "      <td>727</td>\n",
+       "      <th>6</th>\n",
+       "      <td>1216</td>\n",
+       "      <td>1243.0</td>\n",
+       "      <td>1265.0</td>\n",
+       "      <td>1200.0</td>\n",
+       "      <td>1217.0</td>\n",
+       "      <td>1344</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>6</td>\n",
-       "      <td>2020-02-07 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>10986</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>11925</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>11154</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>729</td>\n",
-       "      <td>...</td>\n",
+       "      <th>7</th>\n",
+       "      <td>1162</td>\n",
+       "      <td>1181.0</td>\n",
+       "      <td>1315.0</td>\n",
+       "      <td>1231.0</td>\n",
+       "      <td>1209.0</td>\n",
+       "      <td>1360</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>1162</td>\n",
+       "      <td>1245.0</td>\n",
+       "      <td>1245.0</td>\n",
+       "      <td>1185.0</td>\n",
+       "      <td>1239.0</td>\n",
+       "      <td>1320</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>1171</td>\n",
+       "      <td>1125.0</td>\n",
+       "      <td>1022.0</td>\n",
+       "      <td>1219.0</td>\n",
+       "      <td>1150.0</td>\n",
+       "      <td>1308</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>1208</td>\n",
+       "      <td>1156.0</td>\n",
+       "      <td>1475.0</td>\n",
+       "      <td>1146.0</td>\n",
+       "      <td>1174.0</td>\n",
+       "      <td>1192</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>1156</td>\n",
+       "      <td>1108.0</td>\n",
+       "      <td>1220.0</td>\n",
+       "      <td>1141.0</td>\n",
+       "      <td>1175.0</td>\n",
+       "      <td>1201</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>1196</td>\n",
+       "      <td>1101.0</td>\n",
+       "      <td>1158.0</td>\n",
+       "      <td>1152.0</td>\n",
+       "      <td>1042.0</td>\n",
+       "      <td>1149</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>1079</td>\n",
+       "      <td>1086.0</td>\n",
+       "      <td>1050.0</td>\n",
+       "      <td>1112.0</td>\n",
+       "      <td>1172.0</td>\n",
+       "      <td>1171</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>1744</td>\n",
+       "      <td>1032.0</td>\n",
+       "      <td>1192.0</td>\n",
+       "      <td>1060.0</td>\n",
+       "      <td>1166.0</td>\n",
+       "      <td>1042</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>1978</td>\n",
+       "      <td>1069.0</td>\n",
+       "      <td>1192.0</td>\n",
+       "      <td>998.0</td>\n",
+       "      <td>1048.0</td>\n",
+       "      <td>1192</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>1916</td>\n",
+       "      <td>902.0</td>\n",
+       "      <td>1136.0</td>\n",
+       "      <td>1111.0</td>\n",
+       "      <td>1092.0</td>\n",
+       "      <td>1095</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>1836</td>\n",
+       "      <td>1121.0</td>\n",
+       "      <td>1008.0</td>\n",
+       "      <td>1121.0</td>\n",
+       "      <td>1076.0</td>\n",
+       "      <td>1108</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>1679</td>\n",
+       "      <td>1131.0</td>\n",
+       "      <td>1093.0</td>\n",
+       "      <td>1050.0</td>\n",
+       "      <td>1006.0</td>\n",
+       "      <td>1117</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>1435</td>\n",
+       "      <td>1018.0</td>\n",
+       "      <td>967.0</td>\n",
+       "      <td>1119.0</td>\n",
+       "      <td>1047.0</td>\n",
+       "      <td>1020</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>1421</td>\n",
+       "      <td>1115.0</td>\n",
+       "      <td>977.0</td>\n",
+       "      <td>1115.0</td>\n",
+       "      <td>1010.0</td>\n",
+       "      <td>1103</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>1226</td>\n",
+       "      <td>1061.0</td>\n",
+       "      <td>1070.0</td>\n",
+       "      <td>1063.0</td>\n",
+       "      <td>994.0</td>\n",
+       "      <td>1039</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>1125</td>\n",
+       "      <td>1029.0</td>\n",
+       "      <td>998.0</td>\n",
+       "      <td>1015.0</td>\n",
+       "      <td>999.0</td>\n",
+       "      <td>1043</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>1093</td>\n",
+       "      <td>1042.0</td>\n",
+       "      <td>1033.0</td>\n",
+       "      <td>1076.0</td>\n",
+       "      <td>1023.0</td>\n",
+       "      <td>1106</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>1034</td>\n",
+       "      <td>1028.0</td>\n",
+       "      <td>915.0</td>\n",
+       "      <td>1031.0</td>\n",
+       "      <td>988.0</td>\n",
+       "      <td>1038</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>1065</td>\n",
+       "      <td>1053.0</td>\n",
+       "      <td>993.0</td>\n",
+       "      <td>1032.0</td>\n",
+       "      <td>994.0</td>\n",
+       "      <td>1025</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>1008</td>\n",
+       "      <td>1051.0</td>\n",
+       "      <td>1046.0</td>\n",
+       "      <td>994.0</td>\n",
+       "      <td>1007.0</td>\n",
+       "      <td>1032</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>983</td>\n",
+       "      <td>981.0</td>\n",
+       "      <td>1041.0</td>\n",
+       "      <td>1040.0</td>\n",
+       "      <td>988.0</td>\n",
+       "      <td>1040</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>976</td>\n",
+       "      <td>1077.0</td>\n",
+       "      <td>1002.0</td>\n",
+       "      <td>1014.0</td>\n",
+       "      <td>1022.0</td>\n",
+       "      <td>1011</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>1033</td>\n",
+       "      <td>964.0</td>\n",
+       "      <td>928.0</td>\n",
+       "      <td>1025.0</td>\n",
+       "      <td>1041.0</td>\n",
+       "      <td>1023</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>961</td>\n",
+       "      <td>1041.0</td>\n",
+       "      <td>933.0</td>\n",
+       "      <td>978.0</td>\n",
+       "      <td>979.0</td>\n",
+       "      <td>956</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>1043</td>\n",
+       "      <td>1020.0</td>\n",
+       "      <td>969.0</td>\n",
+       "      <td>1011.0</td>\n",
+       "      <td>987.0</td>\n",
+       "      <td>985</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>1011</td>\n",
+       "      <td>1018.0</td>\n",
+       "      <td>953.0</td>\n",
+       "      <td>1002.0</td>\n",
+       "      <td>997.0</td>\n",
+       "      <td>1043</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>922</td>\n",
+       "      <td>1028.0</td>\n",
+       "      <td>978.0</td>\n",
+       "      <td>1004.0</td>\n",
+       "      <td>982.0</td>\n",
+       "      <td>969</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>1046</td>\n",
+       "      <td>1011.0</td>\n",
+       "      <td>941.0</td>\n",
+       "      <td>1045.0</td>\n",
+       "      <td>1017.0</td>\n",
+       "      <td>982</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>1029</td>\n",
+       "      <td>1013.0</td>\n",
+       "      <td>930.0</td>\n",
+       "      <td>980.0</td>\n",
+       "      <td>1039.0</td>\n",
+       "      <td>954</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>1050</td>\n",
+       "      <td>980.0</td>\n",
+       "      <td>970.0</td>\n",
+       "      <td>1006.0</td>\n",
+       "      <td>1007.0</td>\n",
+       "      <td>977</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>1069</td>\n",
+       "      <td>1074.0</td>\n",
+       "      <td>1020.0</td>\n",
+       "      <td>972.0</td>\n",
+       "      <td>983.0</td>\n",
+       "      <td>991</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>952</td>\n",
+       "      <td>1071.0</td>\n",
+       "      <td>946.0</td>\n",
+       "      <td>1049.0</td>\n",
+       "      <td>966.0</td>\n",
+       "      <td>1001</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>933</td>\n",
+       "      <td>1142.0</td>\n",
+       "      <td>1015.0</td>\n",
+       "      <td>1056.0</td>\n",
+       "      <td>1009.0</td>\n",
+       "      <td>1010</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>1195</td>\n",
+       "      <td>1051.0</td>\n",
+       "      <td>1042.0</td>\n",
+       "      <td>1016.0</td>\n",
+       "      <td>1072.0</td>\n",
+       "      <td>1008</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>1071</td>\n",
+       "      <td>1143.0</td>\n",
+       "      <td>1081.0</td>\n",
+       "      <td>1133.0</td>\n",
+       "      <td>1009.0</td>\n",
+       "      <td>1028</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>1131</td>\n",
+       "      <td>1153.0</td>\n",
+       "      <td>1031.0</td>\n",
+       "      <td>1067.0</td>\n",
+       "      <td>1070.0</td>\n",
+       "      <td>989</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>1187</td>\n",
+       "      <td>1115.0</td>\n",
+       "      <td>1019.0</td>\n",
+       "      <td>1095.0</td>\n",
+       "      <td>1052.0</td>\n",
+       "      <td>981</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>1262</td>\n",
+       "      <td>1101.0</td>\n",
+       "      <td>1085.0</td>\n",
+       "      <td>1062.0</td>\n",
+       "      <td>1032.0</td>\n",
+       "      <td>1116</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>1250</td>\n",
+       "      <td>1184.0</td>\n",
+       "      <td>1144.0</td>\n",
+       "      <td>1126.0</td>\n",
+       "      <td>1043.0</td>\n",
+       "      <td>1028</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>1138</td>\n",
+       "      <td>1160.0</td>\n",
+       "      <td>1084.0</td>\n",
+       "      <td>1175.0</td>\n",
+       "      <td>1174.0</td>\n",
+       "      <td>1103</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>1360</td>\n",
+       "      <td>1229.0</td>\n",
+       "      <td>1058.0</td>\n",
+       "      <td>1178.0</td>\n",
+       "      <td>1132.0</td>\n",
+       "      <td>1054</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>1328</td>\n",
+       "      <td>1163.0</td>\n",
+       "      <td>1062.0</td>\n",
+       "      <td>1153.0</td>\n",
+       "      <td>1159.0</td>\n",
+       "      <td>1115</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>1296</td>\n",
+       "      <td>1108.0</td>\n",
+       "      <td>1076.0</td>\n",
+       "      <td>1237.0</td>\n",
+       "      <td>1188.0</td>\n",
+       "      <td>1089</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>1284</td>\n",
+       "      <td>1312.0</td>\n",
+       "      <td>1212.0</td>\n",
+       "      <td>1335.0</td>\n",
+       "      <td>1219.0</td>\n",
+       "      <td>1101</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>1297</td>\n",
+       "      <td>1277.0</td>\n",
+       "      <td>1216.0</td>\n",
+       "      <td>1437.0</td>\n",
+       "      <td>1284.0</td>\n",
+       "      <td>1146</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>1205</td>\n",
+       "      <td>1000.0</td>\n",
+       "      <td>1058.0</td>\n",
+       "      <td>1168.0</td>\n",
+       "      <td>1133.0</td>\n",
+       "      <td>944</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>1178</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1018</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    total_2020  total_2019  total_2018  total_2017  total_2016  total_2015\n",
+       "1         1161      1104.0      1531.0      1205.0      1394.0        1146\n",
+       "2         1567      1507.0      1899.0      1379.0      1305.0        1708\n",
+       "3         1322      1353.0      1629.0      1224.0      1215.0        1489\n",
+       "4         1226      1208.0      1610.0      1197.0      1187.0        1381\n",
+       "5         1188      1206.0      1369.0      1332.0      1205.0        1286\n",
+       "6         1216      1243.0      1265.0      1200.0      1217.0        1344\n",
+       "7         1162      1181.0      1315.0      1231.0      1209.0        1360\n",
+       "8         1162      1245.0      1245.0      1185.0      1239.0        1320\n",
+       "9         1171      1125.0      1022.0      1219.0      1150.0        1308\n",
+       "10        1208      1156.0      1475.0      1146.0      1174.0        1192\n",
+       "11        1156      1108.0      1220.0      1141.0      1175.0        1201\n",
+       "12        1196      1101.0      1158.0      1152.0      1042.0        1149\n",
+       "13        1079      1086.0      1050.0      1112.0      1172.0        1171\n",
+       "14        1744      1032.0      1192.0      1060.0      1166.0        1042\n",
+       "15        1978      1069.0      1192.0       998.0      1048.0        1192\n",
+       "16        1916       902.0      1136.0      1111.0      1092.0        1095\n",
+       "17        1836      1121.0      1008.0      1121.0      1076.0        1108\n",
+       "18        1679      1131.0      1093.0      1050.0      1006.0        1117\n",
+       "19        1435      1018.0       967.0      1119.0      1047.0        1020\n",
+       "20        1421      1115.0       977.0      1115.0      1010.0        1103\n",
+       "21        1226      1061.0      1070.0      1063.0       994.0        1039\n",
+       "22        1125      1029.0       998.0      1015.0       999.0        1043\n",
+       "23        1093      1042.0      1033.0      1076.0      1023.0        1106\n",
+       "24        1034      1028.0       915.0      1031.0       988.0        1038\n",
+       "25        1065      1053.0       993.0      1032.0       994.0        1025\n",
+       "26        1008      1051.0      1046.0       994.0      1007.0        1032\n",
+       "27         983       981.0      1041.0      1040.0       988.0        1040\n",
+       "28         976      1077.0      1002.0      1014.0      1022.0        1011\n",
+       "29        1033       964.0       928.0      1025.0      1041.0        1023\n",
+       "30         961      1041.0       933.0       978.0       979.0         956\n",
+       "31        1043      1020.0       969.0      1011.0       987.0         985\n",
+       "32        1011      1018.0       953.0      1002.0       997.0        1043\n",
+       "33         922      1028.0       978.0      1004.0       982.0         969\n",
+       "34        1046      1011.0       941.0      1045.0      1017.0         982\n",
+       "35        1029      1013.0       930.0       980.0      1039.0         954\n",
+       "36        1050       980.0       970.0      1006.0      1007.0         977\n",
+       "37        1069      1074.0      1020.0       972.0       983.0         991\n",
+       "38         952      1071.0       946.0      1049.0       966.0        1001\n",
+       "39         933      1142.0      1015.0      1056.0      1009.0        1010\n",
+       "40        1195      1051.0      1042.0      1016.0      1072.0        1008\n",
+       "41        1071      1143.0      1081.0      1133.0      1009.0        1028\n",
+       "42        1131      1153.0      1031.0      1067.0      1070.0         989\n",
+       "43        1187      1115.0      1019.0      1095.0      1052.0         981\n",
+       "44        1262      1101.0      1085.0      1062.0      1032.0        1116\n",
+       "45        1250      1184.0      1144.0      1126.0      1043.0        1028\n",
+       "46        1138      1160.0      1084.0      1175.0      1174.0        1103\n",
+       "47        1360      1229.0      1058.0      1178.0      1132.0        1054\n",
+       "48        1328      1163.0      1062.0      1153.0      1159.0        1115\n",
+       "49        1296      1108.0      1076.0      1237.0      1188.0        1089\n",
+       "50        1284      1312.0      1212.0      1335.0      1219.0        1101\n",
+       "51        1297      1277.0      1216.0      1437.0      1284.0        1146\n",
+       "52        1205      1000.0      1058.0      1168.0      1133.0         944\n",
+       "53        1178         NaN         NaN         NaN         NaN        1018"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_headlines_s = raw_data_s[reversed('2015 2016 2017 2018 2019 2020'.split())]\n",
+    "deaths_headlines_s.columns = ['total_' + c for c in deaths_headlines_s.columns]\n",
+    "deaths_headlines_s.reset_index(drop=True, inplace=True)\n",
+    "deaths_headlines_s.index = deaths_headlines_s.index + 1\n",
+    "deaths_headlines_s"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "Collapsed": "false",
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>...</th>\n",
+       "      <th>North East</th>\n",
+       "      <th>North West</th>\n",
+       "      <th>Yorkshire and The Humber</th>\n",
+       "      <th>East Midlands</th>\n",
+       "      <th>West Midlands</th>\n",
+       "      <th>East</th>\n",
+       "      <th>London</th>\n",
+       "      <th>South East</th>\n",
+       "      <th>South West</th>\n",
+       "      <th>Wales</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Week number</th>\n",
+       "      <td>Week ended</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Total deaths, all ages</td>\n",
+       "      <td>Total deaths: average of corresponding</td>\n",
+       "      <td>week over the previous 5 years 1, 10, 11 (Engl...</td>\n",
+       "      <td>Total deaths: average of corresponding</td>\n",
+       "      <td>week over the previous 5 years 1, 10, 11 (Engl...</td>\n",
+       "      <td>Total deaths: average of corresponding</td>\n",
+       "      <td>week over the previous 5 years 1, 10, 11 (Wales)</td>\n",
+       "      <td>...</td>\n",
+       "      <td>E12000001</td>\n",
+       "      <td>E12000002</td>\n",
+       "      <td>E12000003</td>\n",
+       "      <td>E12000004</td>\n",
+       "      <td>E12000005</td>\n",
+       "      <td>E12000006</td>\n",
+       "      <td>E12000007</td>\n",
+       "      <td>E12000008</td>\n",
+       "      <td>E12000009</td>\n",
+       "      <td>W92000004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2020-01-03 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12254</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12175</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11412</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>756</td>\n",
+       "      <td>...</td>\n",
+       "      <td>673</td>\n",
+       "      <td>1806</td>\n",
+       "      <td>1240</td>\n",
+       "      <td>1060</td>\n",
+       "      <td>1349</td>\n",
+       "      <td>1162</td>\n",
+       "      <td>1113</td>\n",
+       "      <td>1814</td>\n",
+       "      <td>1225</td>\n",
+       "      <td>787</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2020-01-10 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14058</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13822</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12933</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>856</td>\n",
+       "      <td>...</td>\n",
+       "      <td>707</td>\n",
+       "      <td>1932</td>\n",
+       "      <td>1339</td>\n",
+       "      <td>1195</td>\n",
+       "      <td>1450</td>\n",
+       "      <td>1573</td>\n",
+       "      <td>1272</td>\n",
+       "      <td>2132</td>\n",
+       "      <td>1487</td>\n",
+       "      <td>939</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2020-01-17 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12990</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13216</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12370</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>812</td>\n",
+       "      <td>...</td>\n",
+       "      <td>647</td>\n",
+       "      <td>1696</td>\n",
+       "      <td>1278</td>\n",
+       "      <td>1106</td>\n",
+       "      <td>1407</td>\n",
+       "      <td>1457</td>\n",
+       "      <td>1073</td>\n",
+       "      <td>2064</td>\n",
+       "      <td>1466</td>\n",
+       "      <td>767</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2020-01-24 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11856</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12760</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11933</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>802</td>\n",
+       "      <td>...</td>\n",
+       "      <td>612</td>\n",
+       "      <td>1529</td>\n",
+       "      <td>1187</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>1231</td>\n",
+       "      <td>1410</td>\n",
+       "      <td>1028</td>\n",
+       "      <td>1833</td>\n",
+       "      <td>1253</td>\n",
+       "      <td>723</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2020-01-31 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11612</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12206</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11419</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>760</td>\n",
+       "      <td>...</td>\n",
+       "      <td>561</td>\n",
+       "      <td>1461</td>\n",
+       "      <td>1136</td>\n",
+       "      <td>1015</td>\n",
+       "      <td>1262</td>\n",
+       "      <td>1286</td>\n",
+       "      <td>1092</td>\n",
+       "      <td>1820</td>\n",
+       "      <td>1233</td>\n",
+       "      <td>727</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2020-02-07 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10986</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11925</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11154</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>729</td>\n",
+       "      <td>...</td>\n",
         "      <td>564</td>\n",
         "      <td>1529</td>\n",
         "      <td>1072</td>\n",
         "      <td>922</td>\n",
         "      <td>564</td>\n",
         "      <td>1529</td>\n",
         "      <td>1072</td>\n",
         "      <td>922</td>\n",
-       "      <td>1052</td>\n",
-       "      <td>1259</td>\n",
-       "      <td>987</td>\n",
-       "      <td>1729</td>\n",
-       "      <td>1157</td>\n",
-       "      <td>690</td>\n",
+       "      <td>1052</td>\n",
+       "      <td>1259</td>\n",
+       "      <td>987</td>\n",
+       "      <td>1729</td>\n",
+       "      <td>1157</td>\n",
+       "      <td>690</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2020-02-14 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10944</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11627</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10876</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>722</td>\n",
+       "      <td>...</td>\n",
+       "      <td>573</td>\n",
+       "      <td>1427</td>\n",
+       "      <td>1059</td>\n",
+       "      <td>976</td>\n",
+       "      <td>1159</td>\n",
+       "      <td>1172</td>\n",
+       "      <td>967</td>\n",
+       "      <td>1688</td>\n",
+       "      <td>1169</td>\n",
+       "      <td>728</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2020-02-21 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10841</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11548</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10790</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>724</td>\n",
+       "      <td>...</td>\n",
+       "      <td>539</td>\n",
+       "      <td>1477</td>\n",
+       "      <td>1087</td>\n",
+       "      <td>924</td>\n",
+       "      <td>1116</td>\n",
+       "      <td>1167</td>\n",
+       "      <td>1032</td>\n",
+       "      <td>1675</td>\n",
+       "      <td>1118</td>\n",
+       "      <td>679</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2020-02-28 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10816</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11183</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10448</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>698</td>\n",
+       "      <td>...</td>\n",
+       "      <td>572</td>\n",
+       "      <td>1476</td>\n",
+       "      <td>1078</td>\n",
+       "      <td>919</td>\n",
+       "      <td>1174</td>\n",
+       "      <td>1115</td>\n",
+       "      <td>1085</td>\n",
+       "      <td>1587</td>\n",
+       "      <td>1133</td>\n",
+       "      <td>651</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>2020-03-06 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10895</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11498</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10745</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>720</td>\n",
+       "      <td>...</td>\n",
+       "      <td>568</td>\n",
+       "      <td>1490</td>\n",
+       "      <td>1112</td>\n",
+       "      <td>930</td>\n",
+       "      <td>1098</td>\n",
+       "      <td>1149</td>\n",
+       "      <td>982</td>\n",
+       "      <td>1726</td>\n",
+       "      <td>1170</td>\n",
+       "      <td>652</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>2020-03-13 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11019</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11205</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10447</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>727</td>\n",
+       "      <td>...</td>\n",
+       "      <td>590</td>\n",
+       "      <td>1472</td>\n",
+       "      <td>1053</td>\n",
+       "      <td>915</td>\n",
+       "      <td>1187</td>\n",
+       "      <td>1211</td>\n",
+       "      <td>964</td>\n",
+       "      <td>1751</td>\n",
+       "      <td>1174</td>\n",
+       "      <td>675</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>2020-03-20 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10645</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10573</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9841</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>677</td>\n",
+       "      <td>...</td>\n",
+       "      <td>522</td>\n",
+       "      <td>1443</td>\n",
+       "      <td>1012</td>\n",
+       "      <td>947</td>\n",
+       "      <td>1115</td>\n",
+       "      <td>1043</td>\n",
+       "      <td>1008</td>\n",
+       "      <td>1657</td>\n",
+       "      <td>1156</td>\n",
+       "      <td>719</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>2020-03-27 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11141</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10130</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9414</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>665</td>\n",
+       "      <td>...</td>\n",
+       "      <td>542</td>\n",
+       "      <td>1538</td>\n",
+       "      <td>982</td>\n",
+       "      <td>922</td>\n",
+       "      <td>1035</td>\n",
+       "      <td>1182</td>\n",
+       "      <td>1297</td>\n",
+       "      <td>1822</td>\n",
+       "      <td>1092</td>\n",
+       "      <td>719</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>2020-04-03 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>16387</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10305</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9601</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>667</td>\n",
+       "      <td>...</td>\n",
+       "      <td>770</td>\n",
+       "      <td>2137</td>\n",
+       "      <td>1436</td>\n",
+       "      <td>1246</td>\n",
+       "      <td>1812</td>\n",
+       "      <td>1717</td>\n",
+       "      <td>2511</td>\n",
+       "      <td>2294</td>\n",
+       "      <td>1520</td>\n",
+       "      <td>920</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>2020-04-10 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>18516</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10520</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9807</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>671</td>\n",
+       "      <td>...</td>\n",
+       "      <td>849</td>\n",
+       "      <td>2597</td>\n",
+       "      <td>1503</td>\n",
+       "      <td>1452</td>\n",
+       "      <td>2182</td>\n",
+       "      <td>1984</td>\n",
+       "      <td>2832</td>\n",
+       "      <td>2604</td>\n",
+       "      <td>1560</td>\n",
+       "      <td>928</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>2020-04-17 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>22351</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10497</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9787</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>661</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1155</td>\n",
+       "      <td>3195</td>\n",
+       "      <td>1960</td>\n",
+       "      <td>1632</td>\n",
+       "      <td>2536</td>\n",
+       "      <td>2466</td>\n",
+       "      <td>3275</td>\n",
+       "      <td>3084</td>\n",
+       "      <td>1854</td>\n",
+       "      <td>1169</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>2020-04-24 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>21997</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10458</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9768</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>662</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1103</td>\n",
+       "      <td>3109</td>\n",
+       "      <td>2095</td>\n",
+       "      <td>1711</td>\n",
+       "      <td>2481</td>\n",
+       "      <td>2299</td>\n",
+       "      <td>2785</td>\n",
+       "      <td>3334</td>\n",
+       "      <td>1924</td>\n",
+       "      <td>1124</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>2020-05-01 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>17953</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9941</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9289</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>624</td>\n",
+       "      <td>...</td>\n",
+       "      <td>922</td>\n",
+       "      <td>2503</td>\n",
+       "      <td>1844</td>\n",
+       "      <td>1418</td>\n",
+       "      <td>1975</td>\n",
+       "      <td>1982</td>\n",
+       "      <td>1953</td>\n",
+       "      <td>2853</td>\n",
+       "      <td>1554</td>\n",
+       "      <td>929</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>2020-05-08 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12657</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9576</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8937</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>612</td>\n",
+       "      <td>...</td>\n",
+       "      <td>769</td>\n",
+       "      <td>1790</td>\n",
+       "      <td>1328</td>\n",
+       "      <td>1094</td>\n",
+       "      <td>1326</td>\n",
+       "      <td>1321</td>\n",
+       "      <td>1213</td>\n",
+       "      <td>1887</td>\n",
+       "      <td>1218</td>\n",
+       "      <td>692</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>2020-05-15 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14573</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10188</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9526</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>635</td>\n",
+       "      <td>...</td>\n",
+       "      <td>845</td>\n",
+       "      <td>1992</td>\n",
+       "      <td>1589</td>\n",
+       "      <td>1283</td>\n",
+       "      <td>1502</td>\n",
+       "      <td>1543</td>\n",
+       "      <td>1329</td>\n",
+       "      <td>2251</td>\n",
+       "      <td>1449</td>\n",
+       "      <td>772</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>2020-05-22 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12288</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9940</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9299</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>614</td>\n",
+       "      <td>...</td>\n",
+       "      <td>718</td>\n",
+       "      <td>1636</td>\n",
+       "      <td>1236</td>\n",
+       "      <td>1041</td>\n",
+       "      <td>1319</td>\n",
+       "      <td>1397</td>\n",
+       "      <td>1125</td>\n",
+       "      <td>1937</td>\n",
+       "      <td>1177</td>\n",
+       "      <td>692</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>2020-05-29 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9824</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8171</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7607</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>546</td>\n",
+       "      <td>...</td>\n",
+       "      <td>550</td>\n",
+       "      <td>1337</td>\n",
+       "      <td>1046</td>\n",
+       "      <td>863</td>\n",
+       "      <td>970</td>\n",
+       "      <td>1095</td>\n",
+       "      <td>841</td>\n",
+       "      <td>1515</td>\n",
+       "      <td>1011</td>\n",
+       "      <td>587</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>2020-06-05 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10709</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9977</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9346</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>610</td>\n",
+       "      <td>...</td>\n",
+       "      <td>576</td>\n",
+       "      <td>1478</td>\n",
+       "      <td>1090</td>\n",
+       "      <td>931</td>\n",
+       "      <td>1172</td>\n",
+       "      <td>1131</td>\n",
+       "      <td>891</td>\n",
+       "      <td>1610</td>\n",
+       "      <td>1116</td>\n",
+       "      <td>700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>2020-06-12 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9976</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9417</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8803</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>588</td>\n",
+       "      <td>...</td>\n",
+       "      <td>478</td>\n",
+       "      <td>1374</td>\n",
+       "      <td>980</td>\n",
+       "      <td>967</td>\n",
+       "      <td>1096</td>\n",
+       "      <td>1048</td>\n",
+       "      <td>883</td>\n",
+       "      <td>1530</td>\n",
+       "      <td>1035</td>\n",
+       "      <td>574</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>7</td>\n",
-       "      <td>2020-02-14 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>10944</td>\n",
+       "      <th>25</th>\n",
+       "      <td>2020-06-19 00:00:00</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>11627</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>10876</td>\n",
+       "      <td>9339</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9404</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8810</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>722</td>\n",
-       "      <td>...</td>\n",
         "      <td>573</td>\n",
         "      <td>573</td>\n",
-       "      <td>1427</td>\n",
-       "      <td>1059</td>\n",
-       "      <td>976</td>\n",
-       "      <td>1159</td>\n",
-       "      <td>1172</td>\n",
-       "      <td>967</td>\n",
-       "      <td>1688</td>\n",
-       "      <td>1169</td>\n",
-       "      <td>728</td>\n",
+       "      <td>...</td>\n",
+       "      <td>498</td>\n",
+       "      <td>1234</td>\n",
+       "      <td>952</td>\n",
+       "      <td>835</td>\n",
+       "      <td>973</td>\n",
+       "      <td>927</td>\n",
+       "      <td>896</td>\n",
+       "      <td>1411</td>\n",
+       "      <td>990</td>\n",
+       "      <td>617</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>8</td>\n",
-       "      <td>2020-02-21 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>10841</td>\n",
+       "      <th>26</th>\n",
+       "      <td>2020-06-26 00:00:00</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>11548</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>10790</td>\n",
+       "      <td>8979</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>724</td>\n",
+       "      <td>9293</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8695</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>571</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>539</td>\n",
-       "      <td>1477</td>\n",
-       "      <td>1087</td>\n",
-       "      <td>924</td>\n",
-       "      <td>1116</td>\n",
-       "      <td>1167</td>\n",
-       "      <td>1032</td>\n",
-       "      <td>1675</td>\n",
-       "      <td>1118</td>\n",
-       "      <td>679</td>\n",
+       "      <td>485</td>\n",
+       "      <td>1300</td>\n",
+       "      <td>922</td>\n",
+       "      <td>800</td>\n",
+       "      <td>946</td>\n",
+       "      <td>880</td>\n",
+       "      <td>791</td>\n",
+       "      <td>1311</td>\n",
+       "      <td>979</td>\n",
+       "      <td>552</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>9</td>\n",
-       "      <td>2020-02-28 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>10816</td>\n",
+       "      <th>27</th>\n",
+       "      <td>2020-07-03 00:00:00</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>11183</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>10448</td>\n",
+       "      <td>9140</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>698</td>\n",
+       "      <td>9183</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8606</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>555</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>572</td>\n",
-       "      <td>1476</td>\n",
-       "      <td>1078</td>\n",
-       "      <td>919</td>\n",
-       "      <td>1174</td>\n",
-       "      <td>1115</td>\n",
-       "      <td>1085</td>\n",
-       "      <td>1587</td>\n",
-       "      <td>1133</td>\n",
-       "      <td>651</td>\n",
+       "      <td>515</td>\n",
+       "      <td>1225</td>\n",
+       "      <td>875</td>\n",
+       "      <td>827</td>\n",
+       "      <td>949</td>\n",
+       "      <td>922</td>\n",
+       "      <td>837</td>\n",
+       "      <td>1454</td>\n",
+       "      <td>938</td>\n",
+       "      <td>584</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>10</td>\n",
-       "      <td>2020-03-06 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>10895</td>\n",
+       "      <th>28</th>\n",
+       "      <td>2020-07-10 00:00:00</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>11498</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>10745</td>\n",
+       "      <td>8690</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>720</td>\n",
+       "      <td>9250</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8648</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>578</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>568</td>\n",
-       "      <td>1490</td>\n",
-       "      <td>1112</td>\n",
+       "      <td>468</td>\n",
+       "      <td>1154</td>\n",
+       "      <td>848</td>\n",
+       "      <td>771</td>\n",
+       "      <td>902</td>\n",
+       "      <td>999</td>\n",
+       "      <td>803</td>\n",
+       "      <td>1228</td>\n",
         "      <td>930</td>\n",
         "      <td>930</td>\n",
-       "      <td>1098</td>\n",
-       "      <td>1149</td>\n",
-       "      <td>982</td>\n",
-       "      <td>1726</td>\n",
-       "      <td>1170</td>\n",
-       "      <td>652</td>\n",
+       "      <td>572</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>11</td>\n",
-       "      <td>2020-03-13 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>11019</td>\n",
+       "      <th>29</th>\n",
+       "      <td>2020-07-17 00:00:00</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>11205</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>10447</td>\n",
+       "      <td>8823</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>727</td>\n",
+       "      <td>9093</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8502</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>557</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>590</td>\n",
-       "      <td>1472</td>\n",
-       "      <td>1053</td>\n",
-       "      <td>915</td>\n",
-       "      <td>1187</td>\n",
-       "      <td>1211</td>\n",
+       "      <td>445</td>\n",
+       "      <td>1159</td>\n",
+       "      <td>843</td>\n",
+       "      <td>816</td>\n",
+       "      <td>956</td>\n",
+       "      <td>945</td>\n",
+       "      <td>806</td>\n",
+       "      <td>1339</td>\n",
+       "      <td>953</td>\n",
+       "      <td>550</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>2020-07-24 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8891</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9052</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8452</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>566</td>\n",
+       "      <td>...</td>\n",
+       "      <td>493</td>\n",
+       "      <td>1197</td>\n",
+       "      <td>817</td>\n",
+       "      <td>798</td>\n",
         "      <td>964</td>\n",
         "      <td>964</td>\n",
-       "      <td>1751</td>\n",
-       "      <td>1174</td>\n",
-       "      <td>675</td>\n",
+       "      <td>951</td>\n",
+       "      <td>816</td>\n",
+       "      <td>1340</td>\n",
+       "      <td>941</td>\n",
+       "      <td>565</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>12</td>\n",
-       "      <td>2020-03-20 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>10645</td>\n",
+       "      <th>31</th>\n",
+       "      <td>2020-07-31 00:00:00</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>10573</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>9841</td>\n",
+       "      <td>8946</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>677</td>\n",
+       "      <td>9036</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8436</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>572</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>522</td>\n",
-       "      <td>1443</td>\n",
-       "      <td>1012</td>\n",
-       "      <td>947</td>\n",
-       "      <td>1115</td>\n",
-       "      <td>1043</td>\n",
-       "      <td>1008</td>\n",
-       "      <td>1657</td>\n",
-       "      <td>1156</td>\n",
-       "      <td>719</td>\n",
+       "      <td>507</td>\n",
+       "      <td>1272</td>\n",
+       "      <td>837</td>\n",
+       "      <td>729</td>\n",
+       "      <td>902</td>\n",
+       "      <td>949</td>\n",
+       "      <td>773</td>\n",
+       "      <td>1447</td>\n",
+       "      <td>988</td>\n",
+       "      <td>531</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>13</td>\n",
-       "      <td>2020-03-27 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>11141</td>\n",
+       "      <th>32</th>\n",
+       "      <td>2020-08-07 00:00:00</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>10130</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>9414</td>\n",
+       "      <td>8945</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>665</td>\n",
+       "      <td>9102</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8502</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>571</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>542</td>\n",
-       "      <td>1538</td>\n",
-       "      <td>982</td>\n",
-       "      <td>922</td>\n",
-       "      <td>1035</td>\n",
-       "      <td>1182</td>\n",
-       "      <td>1297</td>\n",
-       "      <td>1822</td>\n",
-       "      <td>1092</td>\n",
-       "      <td>719</td>\n",
+       "      <td>486</td>\n",
+       "      <td>1211</td>\n",
+       "      <td>851</td>\n",
+       "      <td>798</td>\n",
+       "      <td>933</td>\n",
+       "      <td>955</td>\n",
+       "      <td>832</td>\n",
+       "      <td>1370</td>\n",
+       "      <td>929</td>\n",
+       "      <td>563</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>14</td>\n",
-       "      <td>2020-04-03 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>16387</td>\n",
+       "      <th>33</th>\n",
+       "      <td>2020-08-14 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>10305</td>\n",
+       "      <td>9392</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>9601</td>\n",
+       "      <td>9085</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>667</td>\n",
+       "      <td>8494</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>564</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>770</td>\n",
-       "      <td>2137</td>\n",
-       "      <td>1436</td>\n",
-       "      <td>1246</td>\n",
-       "      <td>1812</td>\n",
-       "      <td>1717</td>\n",
-       "      <td>2511</td>\n",
-       "      <td>2294</td>\n",
-       "      <td>1520</td>\n",
-       "      <td>920</td>\n",
+       "      <td>520</td>\n",
+       "      <td>1304</td>\n",
+       "      <td>853</td>\n",
+       "      <td>829</td>\n",
+       "      <td>923</td>\n",
+       "      <td>1006</td>\n",
+       "      <td>928</td>\n",
+       "      <td>1395</td>\n",
+       "      <td>1009</td>\n",
+       "      <td>617</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>15</td>\n",
-       "      <td>2020-04-10 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>18516</td>\n",
+       "      <th>34</th>\n",
+       "      <td>2020-08-21 00:00:00</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>10520</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>9807</td>\n",
+       "      <td>9631</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>671</td>\n",
+       "      <td>9157</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8560</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>573</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>849</td>\n",
-       "      <td>2597</td>\n",
-       "      <td>1503</td>\n",
-       "      <td>1452</td>\n",
-       "      <td>2182</td>\n",
-       "      <td>1984</td>\n",
-       "      <td>2832</td>\n",
-       "      <td>2604</td>\n",
-       "      <td>1560</td>\n",
-       "      <td>928</td>\n",
+       "      <td>479</td>\n",
+       "      <td>1269</td>\n",
+       "      <td>870</td>\n",
+       "      <td>780</td>\n",
+       "      <td>1028</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>920</td>\n",
+       "      <td>1608</td>\n",
+       "      <td>1043</td>\n",
+       "      <td>594</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>16</td>\n",
-       "      <td>2020-04-17 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>22351</td>\n",
+       "      <th>35</th>\n",
+       "      <td>2020-08-28 00:00:00</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>10497</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>9787</td>\n",
+       "      <td>9032</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>661</td>\n",
+       "      <td>8241</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7674</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>539</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>1155</td>\n",
-       "      <td>3195</td>\n",
-       "      <td>1960</td>\n",
-       "      <td>1632</td>\n",
-       "      <td>2536</td>\n",
-       "      <td>2466</td>\n",
-       "      <td>3275</td>\n",
-       "      <td>3084</td>\n",
-       "      <td>1854</td>\n",
-       "      <td>1169</td>\n",
+       "      <td>455</td>\n",
+       "      <td>1148</td>\n",
+       "      <td>922</td>\n",
+       "      <td>724</td>\n",
+       "      <td>945</td>\n",
+       "      <td>951</td>\n",
+       "      <td>810</td>\n",
+       "      <td>1511</td>\n",
+       "      <td>959</td>\n",
+       "      <td>591</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>17</td>\n",
-       "      <td>2020-04-24 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>21997</td>\n",
+       "      <th>36</th>\n",
+       "      <td>2020-09-04 00:00:00</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>10458</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>9768</td>\n",
+       "      <td>7739</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>662</td>\n",
+       "      <td>9182</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8604</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>552</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>1103</td>\n",
-       "      <td>3109</td>\n",
-       "      <td>2095</td>\n",
-       "      <td>1711</td>\n",
-       "      <td>2481</td>\n",
-       "      <td>2299</td>\n",
-       "      <td>2785</td>\n",
-       "      <td>3334</td>\n",
-       "      <td>1924</td>\n",
-       "      <td>1124</td>\n",
+       "      <td>431</td>\n",
+       "      <td>1057</td>\n",
+       "      <td>780</td>\n",
+       "      <td>640</td>\n",
+       "      <td>770</td>\n",
+       "      <td>806</td>\n",
+       "      <td>737</td>\n",
+       "      <td>1208</td>\n",
+       "      <td>803</td>\n",
+       "      <td>488</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>18</td>\n",
-       "      <td>2020-05-01 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>17953</td>\n",
+       "      <th>37</th>\n",
+       "      <td>2020-09-11 00:00:00</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>9941</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>9289</td>\n",
+       "      <td>9811</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>624</td>\n",
+       "      <td>9306</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8708</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>577</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>922</td>\n",
-       "      <td>2503</td>\n",
-       "      <td>1844</td>\n",
-       "      <td>1418</td>\n",
-       "      <td>1975</td>\n",
-       "      <td>1982</td>\n",
-       "      <td>1953</td>\n",
-       "      <td>2853</td>\n",
-       "      <td>1554</td>\n",
-       "      <td>929</td>\n",
+       "      <td>502</td>\n",
+       "      <td>1229</td>\n",
+       "      <td>952</td>\n",
+       "      <td>867</td>\n",
+       "      <td>1021</td>\n",
+       "      <td>1052</td>\n",
+       "      <td>898</td>\n",
+       "      <td>1610</td>\n",
+       "      <td>1084</td>\n",
+       "      <td>578</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>19</td>\n",
-       "      <td>2020-05-08 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>12657</td>\n",
+       "      <th>38</th>\n",
+       "      <td>2020-09-18 00:00:00</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>9576</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>8937</td>\n",
+       "      <td>9523</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>612</td>\n",
+       "      <td>9264</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8663</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>575</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>769</td>\n",
-       "      <td>1790</td>\n",
-       "      <td>1328</td>\n",
-       "      <td>1094</td>\n",
-       "      <td>1326</td>\n",
-       "      <td>1321</td>\n",
-       "      <td>1213</td>\n",
-       "      <td>1887</td>\n",
-       "      <td>1218</td>\n",
-       "      <td>692</td>\n",
+       "      <td>465</td>\n",
+       "      <td>1287</td>\n",
+       "      <td>939</td>\n",
+       "      <td>795</td>\n",
+       "      <td>1051</td>\n",
+       "      <td>1023</td>\n",
+       "      <td>844</td>\n",
+       "      <td>1530</td>\n",
+       "      <td>1021</td>\n",
+       "      <td>555</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>20</td>\n",
-       "      <td>2020-05-15 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>14573</td>\n",
+       "      <th>39</th>\n",
+       "      <td>2020-09-25 00:00:00</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>10188</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>9526</td>\n",
+       "      <td>9634</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>635</td>\n",
+       "      <td>9377</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8744</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>604</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>845</td>\n",
-       "      <td>1992</td>\n",
-       "      <td>1589</td>\n",
-       "      <td>1283</td>\n",
-       "      <td>1502</td>\n",
-       "      <td>1543</td>\n",
-       "      <td>1329</td>\n",
-       "      <td>2251</td>\n",
-       "      <td>1449</td>\n",
-       "      <td>772</td>\n",
+       "      <td>514</td>\n",
+       "      <td>1271</td>\n",
+       "      <td>965</td>\n",
+       "      <td>825</td>\n",
+       "      <td>1036</td>\n",
+       "      <td>963</td>\n",
+       "      <td>869</td>\n",
+       "      <td>1521</td>\n",
+       "      <td>1041</td>\n",
+       "      <td>617</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>21</td>\n",
-       "      <td>2020-05-22 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>12288</td>\n",
+       "      <th>40</th>\n",
+       "      <td>2020-10-02 00:00:00</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>9940</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>9299</td>\n",
+       "      <td>9945</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>614</td>\n",
+       "      <td>9555</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8942</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>587</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>718</td>\n",
-       "      <td>1636</td>\n",
-       "      <td>1236</td>\n",
-       "      <td>1041</td>\n",
-       "      <td>1319</td>\n",
-       "      <td>1397</td>\n",
-       "      <td>1125</td>\n",
-       "      <td>1937</td>\n",
-       "      <td>1177</td>\n",
-       "      <td>692</td>\n",
+       "      <td>558</td>\n",
+       "      <td>1301</td>\n",
+       "      <td>978</td>\n",
+       "      <td>842</td>\n",
+       "      <td>1045</td>\n",
+       "      <td>1054</td>\n",
+       "      <td>899</td>\n",
+       "      <td>1577</td>\n",
+       "      <td>1003</td>\n",
+       "      <td>671</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>22</td>\n",
-       "      <td>2020-05-29 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>9824</td>\n",
+       "      <th>41</th>\n",
+       "      <td>2020-10-09 00:00:00</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>8171</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>7607</td>\n",
+       "      <td>9954</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>546</td>\n",
+       "      <td>9811</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9168</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>615</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>550</td>\n",
-       "      <td>1337</td>\n",
-       "      <td>1046</td>\n",
-       "      <td>863</td>\n",
-       "      <td>970</td>\n",
-       "      <td>1095</td>\n",
-       "      <td>841</td>\n",
-       "      <td>1515</td>\n",
-       "      <td>1011</td>\n",
-       "      <td>587</td>\n",
+       "      <td>544</td>\n",
+       "      <td>1367</td>\n",
+       "      <td>1067</td>\n",
+       "      <td>884</td>\n",
+       "      <td>1053</td>\n",
+       "      <td>1019</td>\n",
+       "      <td>902</td>\n",
+       "      <td>1462</td>\n",
+       "      <td>1010</td>\n",
+       "      <td>638</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>23</td>\n",
-       "      <td>2020-06-05 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>10709</td>\n",
+       "      <th>42</th>\n",
+       "      <td>2020-10-16 00:00:00</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>9977</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>9346</td>\n",
+       "      <td>10534</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>610</td>\n",
+       "      <td>9865</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9215</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>630</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>576</td>\n",
-       "      <td>1478</td>\n",
-       "      <td>1090</td>\n",
-       "      <td>931</td>\n",
-       "      <td>1172</td>\n",
-       "      <td>1131</td>\n",
-       "      <td>891</td>\n",
-       "      <td>1610</td>\n",
-       "      <td>1116</td>\n",
-       "      <td>700</td>\n",
+       "      <td>606</td>\n",
+       "      <td>1553</td>\n",
+       "      <td>1001</td>\n",
+       "      <td>904</td>\n",
+       "      <td>1154</td>\n",
+       "      <td>1056</td>\n",
+       "      <td>923</td>\n",
+       "      <td>1462</td>\n",
+       "      <td>1174</td>\n",
+       "      <td>688</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>24</td>\n",
-       "      <td>2020-06-12 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>9976</td>\n",
+       "      <th>43</th>\n",
+       "      <td>2020-10-23 00:00:00</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>9417</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>8803</td>\n",
+       "      <td>10739</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>588</td>\n",
+       "      <td>9759</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9104</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>628</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>478</td>\n",
-       "      <td>1374</td>\n",
-       "      <td>980</td>\n",
-       "      <td>967</td>\n",
-       "      <td>1096</td>\n",
-       "      <td>1048</td>\n",
-       "      <td>883</td>\n",
-       "      <td>1530</td>\n",
-       "      <td>1035</td>\n",
-       "      <td>574</td>\n",
+       "      <td>600</td>\n",
+       "      <td>1714</td>\n",
+       "      <td>1111</td>\n",
+       "      <td>891</td>\n",
+       "      <td>1124</td>\n",
+       "      <td>1154</td>\n",
+       "      <td>922</td>\n",
+       "      <td>1510</td>\n",
+       "      <td>1044</td>\n",
+       "      <td>661</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>25</td>\n",
-       "      <td>2020-06-19 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>9339</td>\n",
+       "      <th>44</th>\n",
+       "      <td>2020-10-30 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>9404</td>\n",
+       "      <td>10887</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>8810</td>\n",
+       "      <td>9891</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>573</td>\n",
+       "      <td>9248</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>616</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>498</td>\n",
-       "      <td>1234</td>\n",
-       "      <td>952</td>\n",
-       "      <td>835</td>\n",
-       "      <td>973</td>\n",
-       "      <td>927</td>\n",
-       "      <td>896</td>\n",
-       "      <td>1411</td>\n",
-       "      <td>990</td>\n",
-       "      <td>617</td>\n",
+       "      <td>591</td>\n",
+       "      <td>1754</td>\n",
+       "      <td>1168</td>\n",
+       "      <td>882</td>\n",
+       "      <td>1102</td>\n",
+       "      <td>1089</td>\n",
+       "      <td>888</td>\n",
+       "      <td>1563</td>\n",
+       "      <td>1129</td>\n",
+       "      <td>712</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>26</td>\n",
-       "      <td>2020-06-26 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>8979</td>\n",
+       "      <th>45</th>\n",
+       "      <td>2020-11-06 00:00:00</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>9293</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>8695</td>\n",
+       "      <td>11812</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>571</td>\n",
+       "      <td>10331</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9675</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>625</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>485</td>\n",
-       "      <td>1300</td>\n",
-       "      <td>922</td>\n",
-       "      <td>800</td>\n",
-       "      <td>946</td>\n",
-       "      <td>880</td>\n",
-       "      <td>791</td>\n",
-       "      <td>1311</td>\n",
-       "      <td>979</td>\n",
-       "      <td>552</td>\n",
+       "      <td>675</td>\n",
+       "      <td>1900</td>\n",
+       "      <td>1294</td>\n",
+       "      <td>990</td>\n",
+       "      <td>1186</td>\n",
+       "      <td>1177</td>\n",
+       "      <td>952</td>\n",
+       "      <td>1614</td>\n",
+       "      <td>1174</td>\n",
+       "      <td>832</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>27</td>\n",
-       "      <td>2020-07-03 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>9140</td>\n",
+       "      <th>46</th>\n",
+       "      <td>2020-11-13 00:00:00</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>9183</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>8606</td>\n",
+       "      <td>12254</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>555</td>\n",
+       "      <td>10350</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9662</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>658</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>515</td>\n",
-       "      <td>1225</td>\n",
-       "      <td>875</td>\n",
-       "      <td>827</td>\n",
-       "      <td>949</td>\n",
-       "      <td>922</td>\n",
-       "      <td>837</td>\n",
-       "      <td>1454</td>\n",
-       "      <td>938</td>\n",
-       "      <td>584</td>\n",
+       "      <td>711</td>\n",
+       "      <td>1950</td>\n",
+       "      <td>1350</td>\n",
+       "      <td>1099</td>\n",
+       "      <td>1317</td>\n",
+       "      <td>1172</td>\n",
+       "      <td>1112</td>\n",
+       "      <td>1616</td>\n",
+       "      <td>1168</td>\n",
+       "      <td>742</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>28</td>\n",
-       "      <td>2020-07-10 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>8690</td>\n",
+       "      <th>47</th>\n",
+       "      <td>2020-11-20 00:00:00</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>9250</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>8648</td>\n",
+       "      <td>12535</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>578</td>\n",
+       "      <td>10380</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9701</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>653</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>468</td>\n",
-       "      <td>1154</td>\n",
+       "      <td>691</td>\n",
+       "      <td>1935</td>\n",
+       "      <td>1441</td>\n",
+       "      <td>1105</td>\n",
+       "      <td>1385</td>\n",
+       "      <td>1186</td>\n",
+       "      <td>1086</td>\n",
+       "      <td>1687</td>\n",
+       "      <td>1159</td>\n",
         "      <td>848</td>\n",
         "      <td>848</td>\n",
-       "      <td>771</td>\n",
-       "      <td>902</td>\n",
-       "      <td>999</td>\n",
-       "      <td>803</td>\n",
-       "      <td>1228</td>\n",
-       "      <td>930</td>\n",
-       "      <td>572</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>29</td>\n",
-       "      <td>2020-07-17 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>8823</td>\n",
+       "      <th>48</th>\n",
+       "      <td>2020-11-27 00:00:00</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>9093</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>8502</td>\n",
+       "      <td>12456</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>557</td>\n",
+       "      <td>10357</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9690</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>646</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>445</td>\n",
+       "      <td>679</td>\n",
+       "      <td>1791</td>\n",
+       "      <td>1501</td>\n",
+       "      <td>1218</td>\n",
+       "      <td>1358</td>\n",
         "      <td>1159</td>\n",
         "      <td>1159</td>\n",
-       "      <td>843</td>\n",
-       "      <td>816</td>\n",
-       "      <td>956</td>\n",
-       "      <td>945</td>\n",
-       "      <td>806</td>\n",
-       "      <td>1339</td>\n",
-       "      <td>953</td>\n",
-       "      <td>550</td>\n",
+       "      <td>1012</td>\n",
+       "      <td>1655</td>\n",
+       "      <td>1272</td>\n",
+       "      <td>797</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>30</td>\n",
-       "      <td>2020-07-24 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>8891</td>\n",
+       "      <th>49</th>\n",
+       "      <td>2020-12-04 00:00:00</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>9052</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>8452</td>\n",
+       "      <td>12303</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>566</td>\n",
+       "      <td>10695</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9995</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>679</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>493</td>\n",
-       "      <td>1197</td>\n",
-       "      <td>817</td>\n",
-       "      <td>798</td>\n",
-       "      <td>964</td>\n",
-       "      <td>951</td>\n",
-       "      <td>816</td>\n",
+       "      <td>645</td>\n",
+       "      <td>1679</td>\n",
+       "      <td>1403</td>\n",
+       "      <td>1121</td>\n",
         "      <td>1340</td>\n",
         "      <td>1340</td>\n",
-       "      <td>941</td>\n",
-       "      <td>565</td>\n",
+       "      <td>1229</td>\n",
+       "      <td>1029</td>\n",
+       "      <td>1720</td>\n",
+       "      <td>1284</td>\n",
+       "      <td>836</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>31</td>\n",
-       "      <td>2020-07-31 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>8946</td>\n",
+       "      <th>50</th>\n",
+       "      <td>2020-12-11 00:00:00</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>9036</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>8436</td>\n",
+       "      <td>12292</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>572</td>\n",
+       "      <td>10750</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10034</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>693</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>507</td>\n",
-       "      <td>1272</td>\n",
-       "      <td>837</td>\n",
-       "      <td>729</td>\n",
-       "      <td>902</td>\n",
-       "      <td>949</td>\n",
-       "      <td>773</td>\n",
-       "      <td>1447</td>\n",
-       "      <td>988</td>\n",
-       "      <td>531</td>\n",
+       "      <td>661</td>\n",
+       "      <td>1691</td>\n",
+       "      <td>1326</td>\n",
+       "      <td>1199</td>\n",
+       "      <td>1432</td>\n",
+       "      <td>1224</td>\n",
+       "      <td>1065</td>\n",
+       "      <td>1706</td>\n",
+       "      <td>1156</td>\n",
+       "      <td>814</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>32</td>\n",
-       "      <td>2020-08-07 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>33</td>\n",
-       "      <td>2020-08-14 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>34</td>\n",
-       "      <td>2020-08-21 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>35</td>\n",
-       "      <td>2020-08-28 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>36</td>\n",
-       "      <td>2020-09-04 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>37</td>\n",
-       "      <td>2020-09-11 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>38</td>\n",
-       "      <td>2020-09-18 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>39</td>\n",
-       "      <td>2020-09-25 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>40</td>\n",
-       "      <td>2020-10-02 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>41</td>\n",
-       "      <td>2020-10-09 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>42</td>\n",
-       "      <td>2020-10-16 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>43</td>\n",
-       "      <td>2020-10-23 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>44</td>\n",
-       "      <td>2020-10-30 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>45</td>\n",
-       "      <td>2020-11-06 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>46</td>\n",
-       "      <td>2020-11-13 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>47</td>\n",
-       "      <td>2020-11-20 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>48</td>\n",
-       "      <td>2020-11-27 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>49</td>\n",
-       "      <td>2020-12-04 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>50</td>\n",
-       "      <td>2020-12-11 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>51</td>\n",
+       "      <th>51</th>\n",
         "      <td>2020-12-18 00:00:00</td>\n",
         "      <td>2020-12-18 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13011</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11548</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10804</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>718</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>52</td>\n",
+       "      <td>689</td>\n",
+       "      <td>1718</td>\n",
+       "      <td>1380</td>\n",
+       "      <td>1199</td>\n",
+       "      <td>1385</td>\n",
+       "      <td>1317</td>\n",
+       "      <td>1167</td>\n",
+       "      <td>1947</td>\n",
+       "      <td>1311</td>\n",
+       "      <td>882</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
         "      <td>2020-12-25 00:00:00</td>\n",
         "      <td>2020-12-25 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11520</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7954</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7421</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>518</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>53</td>\n",
+       "      <td>669</td>\n",
+       "      <td>1463</td>\n",
+       "      <td>1130</td>\n",
+       "      <td>1097</td>\n",
+       "      <td>1217</td>\n",
+       "      <td>1198</td>\n",
+       "      <td>1090</td>\n",
+       "      <td>1701</td>\n",
+       "      <td>1115</td>\n",
+       "      <td>825</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
         "      <td>2021-01-01 00:00:00</td>\n",
         "      <td>2021-01-01 00:00:00</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10069</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7954</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7421</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>518</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
-       "      <td>NaT</td>\n",
+       "      <td>547</td>\n",
+       "      <td>1346</td>\n",
+       "      <td>886</td>\n",
+       "      <td>842</td>\n",
+       "      <td>1024</td>\n",
+       "      <td>997</td>\n",
+       "      <td>1159</td>\n",
+       "      <td>1595</td>\n",
+       "      <td>929</td>\n",
+       "      <td>727</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
@@ -2253,61 +2943,61 @@
         "</div>"
        ],
        "text/plain": [
         "</div>"
        ],
        "text/plain": [
-       "                             NaN NaN NaN                     NaN  \\\n",
-       "Week number           Week ended NaT NaT  Total deaths, all ages   \n",
-       "1            2020-01-03 00:00:00 NaT NaT                   12254   \n",
-       "2            2020-01-10 00:00:00 NaT NaT                   14058   \n",
-       "3            2020-01-17 00:00:00 NaT NaT                   12990   \n",
-       "4            2020-01-24 00:00:00 NaT NaT                   11856   \n",
-       "5            2020-01-31 00:00:00 NaT NaT                   11612   \n",
-       "6            2020-02-07 00:00:00 NaT NaT                   10986   \n",
-       "7            2020-02-14 00:00:00 NaT NaT                   10944   \n",
-       "8            2020-02-21 00:00:00 NaT NaT                   10841   \n",
-       "9            2020-02-28 00:00:00 NaT NaT                   10816   \n",
-       "10           2020-03-06 00:00:00 NaT NaT                   10895   \n",
-       "11           2020-03-13 00:00:00 NaT NaT                   11019   \n",
-       "12           2020-03-20 00:00:00 NaT NaT                   10645   \n",
-       "13           2020-03-27 00:00:00 NaT NaT                   11141   \n",
-       "14           2020-04-03 00:00:00 NaT NaT                   16387   \n",
-       "15           2020-04-10 00:00:00 NaT NaT                   18516   \n",
-       "16           2020-04-17 00:00:00 NaT NaT                   22351   \n",
-       "17           2020-04-24 00:00:00 NaT NaT                   21997   \n",
-       "18           2020-05-01 00:00:00 NaT NaT                   17953   \n",
-       "19           2020-05-08 00:00:00 NaT NaT                   12657   \n",
-       "20           2020-05-15 00:00:00 NaT NaT                   14573   \n",
-       "21           2020-05-22 00:00:00 NaT NaT                   12288   \n",
-       "22           2020-05-29 00:00:00 NaT NaT                    9824   \n",
-       "23           2020-06-05 00:00:00 NaT NaT                   10709   \n",
-       "24           2020-06-12 00:00:00 NaT NaT                    9976   \n",
-       "25           2020-06-19 00:00:00 NaT NaT                    9339   \n",
-       "26           2020-06-26 00:00:00 NaT NaT                    8979   \n",
-       "27           2020-07-03 00:00:00 NaT NaT                    9140   \n",
-       "28           2020-07-10 00:00:00 NaT NaT                    8690   \n",
-       "29           2020-07-17 00:00:00 NaT NaT                    8823   \n",
-       "30           2020-07-24 00:00:00 NaT NaT                    8891   \n",
-       "31           2020-07-31 00:00:00 NaT NaT                    8946   \n",
-       "32           2020-08-07 00:00:00 NaT NaT                     NaT   \n",
-       "33           2020-08-14 00:00:00 NaT NaT                     NaT   \n",
-       "34           2020-08-21 00:00:00 NaT NaT                     NaT   \n",
-       "35           2020-08-28 00:00:00 NaT NaT                     NaT   \n",
-       "36           2020-09-04 00:00:00 NaT NaT                     NaT   \n",
-       "37           2020-09-11 00:00:00 NaT NaT                     NaT   \n",
-       "38           2020-09-18 00:00:00 NaT NaT                     NaT   \n",
-       "39           2020-09-25 00:00:00 NaT NaT                     NaT   \n",
-       "40           2020-10-02 00:00:00 NaT NaT                     NaT   \n",
-       "41           2020-10-09 00:00:00 NaT NaT                     NaT   \n",
-       "42           2020-10-16 00:00:00 NaT NaT                     NaT   \n",
-       "43           2020-10-23 00:00:00 NaT NaT                     NaT   \n",
-       "44           2020-10-30 00:00:00 NaT NaT                     NaT   \n",
-       "45           2020-11-06 00:00:00 NaT NaT                     NaT   \n",
-       "46           2020-11-13 00:00:00 NaT NaT                     NaT   \n",
-       "47           2020-11-20 00:00:00 NaT NaT                     NaT   \n",
-       "48           2020-11-27 00:00:00 NaT NaT                     NaT   \n",
-       "49           2020-12-04 00:00:00 NaT NaT                     NaT   \n",
-       "50           2020-12-11 00:00:00 NaT NaT                     NaT   \n",
-       "51           2020-12-18 00:00:00 NaT NaT                     NaT   \n",
-       "52           2020-12-25 00:00:00 NaT NaT                     NaT   \n",
-       "53           2021-01-01 00:00:00 NaT NaT                     NaT   \n",
+       "                             NaN  NaN  NaN                     NaN  \\\n",
+       "Week number           Week ended  NaN  NaN  Total deaths, all ages   \n",
+       "1            2020-01-03 00:00:00  NaN  NaN                   12254   \n",
+       "2            2020-01-10 00:00:00  NaN  NaN                   14058   \n",
+       "3            2020-01-17 00:00:00  NaN  NaN                   12990   \n",
+       "4            2020-01-24 00:00:00  NaN  NaN                   11856   \n",
+       "5            2020-01-31 00:00:00  NaN  NaN                   11612   \n",
+       "6            2020-02-07 00:00:00  NaN  NaN                   10986   \n",
+       "7            2020-02-14 00:00:00  NaN  NaN                   10944   \n",
+       "8            2020-02-21 00:00:00  NaN  NaN                   10841   \n",
+       "9            2020-02-28 00:00:00  NaN  NaN                   10816   \n",
+       "10           2020-03-06 00:00:00  NaN  NaN                   10895   \n",
+       "11           2020-03-13 00:00:00  NaN  NaN                   11019   \n",
+       "12           2020-03-20 00:00:00  NaN  NaN                   10645   \n",
+       "13           2020-03-27 00:00:00  NaN  NaN                   11141   \n",
+       "14           2020-04-03 00:00:00  NaN  NaN                   16387   \n",
+       "15           2020-04-10 00:00:00  NaN  NaN                   18516   \n",
+       "16           2020-04-17 00:00:00  NaN  NaN                   22351   \n",
+       "17           2020-04-24 00:00:00  NaN  NaN                   21997   \n",
+       "18           2020-05-01 00:00:00  NaN  NaN                   17953   \n",
+       "19           2020-05-08 00:00:00  NaN  NaN                   12657   \n",
+       "20           2020-05-15 00:00:00  NaN  NaN                   14573   \n",
+       "21           2020-05-22 00:00:00  NaN  NaN                   12288   \n",
+       "22           2020-05-29 00:00:00  NaN  NaN                    9824   \n",
+       "23           2020-06-05 00:00:00  NaN  NaN                   10709   \n",
+       "24           2020-06-12 00:00:00  NaN  NaN                    9976   \n",
+       "25           2020-06-19 00:00:00  NaN  NaN                    9339   \n",
+       "26           2020-06-26 00:00:00  NaN  NaN                    8979   \n",
+       "27           2020-07-03 00:00:00  NaN  NaN                    9140   \n",
+       "28           2020-07-10 00:00:00  NaN  NaN                    8690   \n",
+       "29           2020-07-17 00:00:00  NaN  NaN                    8823   \n",
+       "30           2020-07-24 00:00:00  NaN  NaN                    8891   \n",
+       "31           2020-07-31 00:00:00  NaN  NaN                    8946   \n",
+       "32           2020-08-07 00:00:00  NaN  NaN                    8945   \n",
+       "33           2020-08-14 00:00:00  NaN  NaN                    9392   \n",
+       "34           2020-08-21 00:00:00  NaN  NaN                    9631   \n",
+       "35           2020-08-28 00:00:00  NaN  NaN                    9032   \n",
+       "36           2020-09-04 00:00:00  NaN  NaN                    7739   \n",
+       "37           2020-09-11 00:00:00  NaN  NaN                    9811   \n",
+       "38           2020-09-18 00:00:00  NaN  NaN                    9523   \n",
+       "39           2020-09-25 00:00:00  NaN  NaN                    9634   \n",
+       "40           2020-10-02 00:00:00  NaN  NaN                    9945   \n",
+       "41           2020-10-09 00:00:00  NaN  NaN                    9954   \n",
+       "42           2020-10-16 00:00:00  NaN  NaN                   10534   \n",
+       "43           2020-10-23 00:00:00  NaN  NaN                   10739   \n",
+       "44           2020-10-30 00:00:00  NaN  NaN                   10887   \n",
+       "45           2020-11-06 00:00:00  NaN  NaN                   11812   \n",
+       "46           2020-11-13 00:00:00  NaN  NaN                   12254   \n",
+       "47           2020-11-20 00:00:00  NaN  NaN                   12535   \n",
+       "48           2020-11-27 00:00:00  NaN  NaN                   12456   \n",
+       "49           2020-12-04 00:00:00  NaN  NaN                   12303   \n",
+       "50           2020-12-11 00:00:00  NaN  NaN                   12292   \n",
+       "51           2020-12-18 00:00:00  NaN  NaN                   13011   \n",
+       "52           2020-12-25 00:00:00  NaN  NaN                   11520   \n",
+       "53           2021-01-01 00:00:00  NaN  NaN                   10069   \n",
         "\n",
         "                                                NaN  \\\n",
         "Week number  Total deaths: average of corresponding   \n",
         "\n",
         "                                                NaN  \\\n",
         "Week number  Total deaths: average of corresponding   \n",
@@ -2342,31 +3032,31 @@
         "29                                              NaN   \n",
         "30                                              NaN   \n",
         "31                                              NaN   \n",
         "29                                              NaN   \n",
         "30                                              NaN   \n",
         "31                                              NaN   \n",
-       "32                                              NaT   \n",
-       "33                                              NaT   \n",
-       "34                                              NaT   \n",
-       "35                                              NaT   \n",
-       "36                                              NaT   \n",
-       "37                                              NaT   \n",
-       "38                                              NaT   \n",
-       "39                                              NaT   \n",
-       "40                                              NaT   \n",
-       "41                                              NaT   \n",
-       "42                                              NaT   \n",
-       "43                                              NaT   \n",
-       "44                                              NaT   \n",
-       "45                                              NaT   \n",
-       "46                                              NaT   \n",
-       "47                                              NaT   \n",
-       "48                                              NaT   \n",
-       "49                                              NaT   \n",
-       "50                                              NaT   \n",
-       "51                                              NaT   \n",
-       "52                                              NaT   \n",
-       "53                                              NaT   \n",
+       "32                                              NaN   \n",
+       "33                                              NaN   \n",
+       "34                                              NaN   \n",
+       "35                                              NaN   \n",
+       "36                                              NaN   \n",
+       "37                                              NaN   \n",
+       "38                                              NaN   \n",
+       "39                                              NaN   \n",
+       "40                                              NaN   \n",
+       "41                                              NaN   \n",
+       "42                                              NaN   \n",
+       "43                                              NaN   \n",
+       "44                                              NaN   \n",
+       "45                                              NaN   \n",
+       "46                                              NaN   \n",
+       "47                                              NaN   \n",
+       "48                                              NaN   \n",
+       "49                                              NaN   \n",
+       "50                                              NaN   \n",
+       "51                                              NaN   \n",
+       "52                                              NaN   \n",
+       "53                                              NaN   \n",
         "\n",
         "                                                           NaN  \\\n",
         "\n",
         "                                                           NaN  \\\n",
-       "Week number  week over the previous 5 years 1 (England and ...   \n",
+       "Week number  week over the previous 5 years 1, 10, 11 (Engl...   \n",
         "1                                                        12175   \n",
         "2                                                        13822   \n",
         "3                                                        13216   \n",
         "1                                                        12175   \n",
         "2                                                        13822   \n",
         "3                                                        13216   \n",
@@ -2398,28 +3088,28 @@
         "29                                                        9093   \n",
         "30                                                        9052   \n",
         "31                                                        9036   \n",
         "29                                                        9093   \n",
         "30                                                        9052   \n",
         "31                                                        9036   \n",
-       "32                                                         NaT   \n",
-       "33                                                         NaT   \n",
-       "34                                                         NaT   \n",
-       "35                                                         NaT   \n",
-       "36                                                         NaT   \n",
-       "37                                                         NaT   \n",
-       "38                                                         NaT   \n",
-       "39                                                         NaT   \n",
-       "40                                                         NaT   \n",
-       "41                                                         NaT   \n",
-       "42                                                         NaT   \n",
-       "43                                                         NaT   \n",
-       "44                                                         NaT   \n",
-       "45                                                         NaT   \n",
-       "46                                                         NaT   \n",
-       "47                                                         NaT   \n",
-       "48                                                         NaT   \n",
-       "49                                                         NaT   \n",
-       "50                                                         NaT   \n",
-       "51                                                         NaT   \n",
-       "52                                                         NaT   \n",
-       "53                                                         NaT   \n",
+       "32                                                        9102   \n",
+       "33                                                        9085   \n",
+       "34                                                        9157   \n",
+       "35                                                        8241   \n",
+       "36                                                        9182   \n",
+       "37                                                        9306   \n",
+       "38                                                        9264   \n",
+       "39                                                        9377   \n",
+       "40                                                        9555   \n",
+       "41                                                        9811   \n",
+       "42                                                        9865   \n",
+       "43                                                        9759   \n",
+       "44                                                        9891   \n",
+       "45                                                       10331   \n",
+       "46                                                       10350   \n",
+       "47                                                       10380   \n",
+       "48                                                       10357   \n",
+       "49                                                       10695   \n",
+       "50                                                       10750   \n",
+       "51                                                       11548   \n",
+       "52                                                        7954   \n",
+       "53                                                        7954   \n",
         "\n",
         "                                                NaN  \\\n",
         "Week number  Total deaths: average of corresponding   \n",
         "\n",
         "                                                NaN  \\\n",
         "Week number  Total deaths: average of corresponding   \n",
@@ -2454,84 +3144,84 @@
         "29                                              NaN   \n",
         "30                                              NaN   \n",
         "31                                              NaN   \n",
         "29                                              NaN   \n",
         "30                                              NaN   \n",
         "31                                              NaN   \n",
-       "32                                              NaT   \n",
-       "33                                              NaT   \n",
-       "34                                              NaT   \n",
-       "35                                              NaT   \n",
-       "36                                              NaT   \n",
-       "37                                              NaT   \n",
-       "38                                              NaT   \n",
-       "39                                              NaT   \n",
-       "40                                              NaT   \n",
-       "41                                              NaT   \n",
-       "42                                              NaT   \n",
-       "43                                              NaT   \n",
-       "44                                              NaT   \n",
-       "45                                              NaT   \n",
-       "46                                              NaT   \n",
-       "47                                              NaT   \n",
-       "48                                              NaT   \n",
-       "49                                              NaT   \n",
-       "50                                              NaT   \n",
-       "51                                              NaT   \n",
-       "52                                              NaT   \n",
-       "53                                              NaT   \n",
+       "32                                              NaN   \n",
+       "33                                              NaN   \n",
+       "34                                              NaN   \n",
+       "35                                              NaN   \n",
+       "36                                              NaN   \n",
+       "37                                              NaN   \n",
+       "38                                              NaN   \n",
+       "39                                              NaN   \n",
+       "40                                              NaN   \n",
+       "41                                              NaN   \n",
+       "42                                              NaN   \n",
+       "43                                              NaN   \n",
+       "44                                              NaN   \n",
+       "45                                              NaN   \n",
+       "46                                              NaN   \n",
+       "47                                              NaN   \n",
+       "48                                              NaN   \n",
+       "49                                              NaN   \n",
+       "50                                              NaN   \n",
+       "51                                              NaN   \n",
+       "52                                              NaN   \n",
+       "53                                              NaN   \n",
         "\n",
         "\n",
-       "                                                    NaN  \\\n",
-       "Week number  week over the previous 5 years 1 (England)   \n",
-       "1                                                 11412   \n",
-       "2                                                 12933   \n",
-       "3                                                 12370   \n",
-       "4                                                 11933   \n",
-       "5                                                 11419   \n",
-       "6                                                 11154   \n",
-       "7                                                 10876   \n",
-       "8                                                 10790   \n",
-       "9                                                 10448   \n",
-       "10                                                10745   \n",
-       "11                                                10447   \n",
-       "12                                                 9841   \n",
-       "13                                                 9414   \n",
-       "14                                                 9601   \n",
-       "15                                                 9807   \n",
-       "16                                                 9787   \n",
-       "17                                                 9768   \n",
-       "18                                                 9289   \n",
-       "19                                                 8937   \n",
-       "20                                                 9526   \n",
-       "21                                                 9299   \n",
-       "22                                                 7607   \n",
-       "23                                                 9346   \n",
-       "24                                                 8803   \n",
-       "25                                                 8810   \n",
-       "26                                                 8695   \n",
-       "27                                                 8606   \n",
-       "28                                                 8648   \n",
-       "29                                                 8502   \n",
-       "30                                                 8452   \n",
-       "31                                                 8436   \n",
-       "32                                                  NaT   \n",
-       "33                                                  NaT   \n",
-       "34                                                  NaT   \n",
-       "35                                                  NaT   \n",
-       "36                                                  NaT   \n",
-       "37                                                  NaT   \n",
-       "38                                                  NaT   \n",
-       "39                                                  NaT   \n",
-       "40                                                  NaT   \n",
-       "41                                                  NaT   \n",
-       "42                                                  NaT   \n",
-       "43                                                  NaT   \n",
-       "44                                                  NaT   \n",
-       "45                                                  NaT   \n",
-       "46                                                  NaT   \n",
-       "47                                                  NaT   \n",
-       "48                                                  NaT   \n",
-       "49                                                  NaT   \n",
-       "50                                                  NaT   \n",
-       "51                                                  NaT   \n",
-       "52                                                  NaT   \n",
-       "53                                                  NaT   \n",
+       "                                                           NaN  \\\n",
+       "Week number  week over the previous 5 years 1, 10, 11 (Engl...   \n",
+       "1                                                        11412   \n",
+       "2                                                        12933   \n",
+       "3                                                        12370   \n",
+       "4                                                        11933   \n",
+       "5                                                        11419   \n",
+       "6                                                        11154   \n",
+       "7                                                        10876   \n",
+       "8                                                        10790   \n",
+       "9                                                        10448   \n",
+       "10                                                       10745   \n",
+       "11                                                       10447   \n",
+       "12                                                        9841   \n",
+       "13                                                        9414   \n",
+       "14                                                        9601   \n",
+       "15                                                        9807   \n",
+       "16                                                        9787   \n",
+       "17                                                        9768   \n",
+       "18                                                        9289   \n",
+       "19                                                        8937   \n",
+       "20                                                        9526   \n",
+       "21                                                        9299   \n",
+       "22                                                        7607   \n",
+       "23                                                        9346   \n",
+       "24                                                        8803   \n",
+       "25                                                        8810   \n",
+       "26                                                        8695   \n",
+       "27                                                        8606   \n",
+       "28                                                        8648   \n",
+       "29                                                        8502   \n",
+       "30                                                        8452   \n",
+       "31                                                        8436   \n",
+       "32                                                        8502   \n",
+       "33                                                        8494   \n",
+       "34                                                        8560   \n",
+       "35                                                        7674   \n",
+       "36                                                        8604   \n",
+       "37                                                        8708   \n",
+       "38                                                        8663   \n",
+       "39                                                        8744   \n",
+       "40                                                        8942   \n",
+       "41                                                        9168   \n",
+       "42                                                        9215   \n",
+       "43                                                        9104   \n",
+       "44                                                        9248   \n",
+       "45                                                        9675   \n",
+       "46                                                        9662   \n",
+       "47                                                        9701   \n",
+       "48                                                        9690   \n",
+       "49                                                        9995   \n",
+       "50                                                       10034   \n",
+       "51                                                       10804   \n",
+       "52                                                        7421   \n",
+       "53                                                        7421   \n",
         "\n",
         "                                                NaN  \\\n",
         "Week number  Total deaths: average of corresponding   \n",
         "\n",
         "                                                NaN  \\\n",
         "Week number  Total deaths: average of corresponding   \n",
@@ -2566,84 +3256,84 @@
         "29                                              NaN   \n",
         "30                                              NaN   \n",
         "31                                              NaN   \n",
         "29                                              NaN   \n",
         "30                                              NaN   \n",
         "31                                              NaN   \n",
-       "32                                              NaT   \n",
-       "33                                              NaT   \n",
-       "34                                              NaT   \n",
-       "35                                              NaT   \n",
-       "36                                              NaT   \n",
-       "37                                              NaT   \n",
-       "38                                              NaT   \n",
-       "39                                              NaT   \n",
-       "40                                              NaT   \n",
-       "41                                              NaT   \n",
-       "42                                              NaT   \n",
-       "43                                              NaT   \n",
-       "44                                              NaT   \n",
-       "45                                              NaT   \n",
-       "46                                              NaT   \n",
-       "47                                              NaT   \n",
-       "48                                              NaT   \n",
-       "49                                              NaT   \n",
-       "50                                              NaT   \n",
-       "51                                              NaT   \n",
-       "52                                              NaT   \n",
-       "53                                              NaT   \n",
+       "32                                              NaN   \n",
+       "33                                              NaN   \n",
+       "34                                              NaN   \n",
+       "35                                              NaN   \n",
+       "36                                              NaN   \n",
+       "37                                              NaN   \n",
+       "38                                              NaN   \n",
+       "39                                              NaN   \n",
+       "40                                              NaN   \n",
+       "41                                              NaN   \n",
+       "42                                              NaN   \n",
+       "43                                              NaN   \n",
+       "44                                              NaN   \n",
+       "45                                              NaN   \n",
+       "46                                              NaN   \n",
+       "47                                              NaN   \n",
+       "48                                              NaN   \n",
+       "49                                              NaN   \n",
+       "50                                              NaN   \n",
+       "51                                              NaN   \n",
+       "52                                              NaN   \n",
+       "53                                              NaN   \n",
         "\n",
         "\n",
-       "                                                  NaN  ... North East  \\\n",
-       "Week number  week over the previous 5 years 1 (Wales)  ...  E12000001   \n",
-       "1                                                 756  ...        673   \n",
-       "2                                                 856  ...        707   \n",
-       "3                                                 812  ...        647   \n",
-       "4                                                 802  ...        612   \n",
-       "5                                                 760  ...        561   \n",
-       "6                                                 729  ...        564   \n",
-       "7                                                 722  ...        573   \n",
-       "8                                                 724  ...        539   \n",
-       "9                                                 698  ...        572   \n",
-       "10                                                720  ...        568   \n",
-       "11                                                727  ...        590   \n",
-       "12                                                677  ...        522   \n",
-       "13                                                665  ...        542   \n",
-       "14                                                667  ...        770   \n",
-       "15                                                671  ...        849   \n",
-       "16                                                661  ...       1155   \n",
-       "17                                                662  ...       1103   \n",
-       "18                                                624  ...        922   \n",
-       "19                                                612  ...        769   \n",
-       "20                                                635  ...        845   \n",
-       "21                                                614  ...        718   \n",
-       "22                                                546  ...        550   \n",
-       "23                                                610  ...        576   \n",
-       "24                                                588  ...        478   \n",
-       "25                                                573  ...        498   \n",
-       "26                                                571  ...        485   \n",
-       "27                                                555  ...        515   \n",
-       "28                                                578  ...        468   \n",
-       "29                                                557  ...        445   \n",
-       "30                                                566  ...        493   \n",
-       "31                                                572  ...        507   \n",
-       "32                                                NaT  ...        NaT   \n",
-       "33                                                NaT  ...        NaT   \n",
-       "34                                                NaT  ...        NaT   \n",
-       "35                                                NaT  ...        NaT   \n",
-       "36                                                NaT  ...        NaT   \n",
-       "37                                                NaT  ...        NaT   \n",
-       "38                                                NaT  ...        NaT   \n",
-       "39                                                NaT  ...        NaT   \n",
-       "40                                                NaT  ...        NaT   \n",
-       "41                                                NaT  ...        NaT   \n",
-       "42                                                NaT  ...        NaT   \n",
-       "43                                                NaT  ...        NaT   \n",
-       "44                                                NaT  ...        NaT   \n",
-       "45                                                NaT  ...        NaT   \n",
-       "46                                                NaT  ...        NaT   \n",
-       "47                                                NaT  ...        NaT   \n",
-       "48                                                NaT  ...        NaT   \n",
-       "49                                                NaT  ...        NaT   \n",
-       "50                                                NaT  ...        NaT   \n",
-       "51                                                NaT  ...        NaT   \n",
-       "52                                                NaT  ...        NaT   \n",
-       "53                                                NaT  ...        NaT   \n",
+       "                                                          NaN  ... North East  \\\n",
+       "Week number  week over the previous 5 years 1, 10, 11 (Wales)  ...  E12000001   \n",
+       "1                                                         756  ...        673   \n",
+       "2                                                         856  ...        707   \n",
+       "3                                                         812  ...        647   \n",
+       "4                                                         802  ...        612   \n",
+       "5                                                         760  ...        561   \n",
+       "6                                                         729  ...        564   \n",
+       "7                                                         722  ...        573   \n",
+       "8                                                         724  ...        539   \n",
+       "9                                                         698  ...        572   \n",
+       "10                                                        720  ...        568   \n",
+       "11                                                        727  ...        590   \n",
+       "12                                                        677  ...        522   \n",
+       "13                                                        665  ...        542   \n",
+       "14                                                        667  ...        770   \n",
+       "15                                                        671  ...        849   \n",
+       "16                                                        661  ...       1155   \n",
+       "17                                                        662  ...       1103   \n",
+       "18                                                        624  ...        922   \n",
+       "19                                                        612  ...        769   \n",
+       "20                                                        635  ...        845   \n",
+       "21                                                        614  ...        718   \n",
+       "22                                                        546  ...        550   \n",
+       "23                                                        610  ...        576   \n",
+       "24                                                        588  ...        478   \n",
+       "25                                                        573  ...        498   \n",
+       "26                                                        571  ...        485   \n",
+       "27                                                        555  ...        515   \n",
+       "28                                                        578  ...        468   \n",
+       "29                                                        557  ...        445   \n",
+       "30                                                        566  ...        493   \n",
+       "31                                                        572  ...        507   \n",
+       "32                                                        571  ...        486   \n",
+       "33                                                        564  ...        520   \n",
+       "34                                                        573  ...        479   \n",
+       "35                                                        539  ...        455   \n",
+       "36                                                        552  ...        431   \n",
+       "37                                                        577  ...        502   \n",
+       "38                                                        575  ...        465   \n",
+       "39                                                        604  ...        514   \n",
+       "40                                                        587  ...        558   \n",
+       "41                                                        615  ...        544   \n",
+       "42                                                        630  ...        606   \n",
+       "43                                                        628  ...        600   \n",
+       "44                                                        616  ...        591   \n",
+       "45                                                        625  ...        675   \n",
+       "46                                                        658  ...        711   \n",
+       "47                                                        653  ...        691   \n",
+       "48                                                        646  ...        679   \n",
+       "49                                                        679  ...        645   \n",
+       "50                                                        693  ...        661   \n",
+       "51                                                        718  ...        689   \n",
+       "52                                                        518  ...        669   \n",
+       "53                                                        518  ...        547   \n",
         "\n",
         "            North West Yorkshire and The Humber East Midlands West Midlands  \\\n",
         "Week number  E12000002                E12000003     E12000004     E12000005   \n",
         "\n",
         "            North West Yorkshire and The Humber East Midlands West Midlands  \\\n",
         "Week number  E12000002                E12000003     E12000004     E12000005   \n",
@@ -2678,28 +3368,28 @@
         "29                1159                      843           816           956   \n",
         "30                1197                      817           798           964   \n",
         "31                1272                      837           729           902   \n",
         "29                1159                      843           816           956   \n",
         "30                1197                      817           798           964   \n",
         "31                1272                      837           729           902   \n",
-       "32                 NaT                      NaT           NaT           NaT   \n",
-       "33                 NaT                      NaT           NaT           NaT   \n",
-       "34                 NaT                      NaT           NaT           NaT   \n",
-       "35                 NaT                      NaT           NaT           NaT   \n",
-       "36                 NaT                      NaT           NaT           NaT   \n",
-       "37                 NaT                      NaT           NaT           NaT   \n",
-       "38                 NaT                      NaT           NaT           NaT   \n",
-       "39                 NaT                      NaT           NaT           NaT   \n",
-       "40                 NaT                      NaT           NaT           NaT   \n",
-       "41                 NaT                      NaT           NaT           NaT   \n",
-       "42                 NaT                      NaT           NaT           NaT   \n",
-       "43                 NaT                      NaT           NaT           NaT   \n",
-       "44                 NaT                      NaT           NaT           NaT   \n",
-       "45                 NaT                      NaT           NaT           NaT   \n",
-       "46                 NaT                      NaT           NaT           NaT   \n",
-       "47                 NaT                      NaT           NaT           NaT   \n",
-       "48                 NaT                      NaT           NaT           NaT   \n",
-       "49                 NaT                      NaT           NaT           NaT   \n",
-       "50                 NaT                      NaT           NaT           NaT   \n",
-       "51                 NaT                      NaT           NaT           NaT   \n",
-       "52                 NaT                      NaT           NaT           NaT   \n",
-       "53                 NaT                      NaT           NaT           NaT   \n",
+       "32                1211                      851           798           933   \n",
+       "33                1304                      853           829           923   \n",
+       "34                1269                      870           780          1028   \n",
+       "35                1148                      922           724           945   \n",
+       "36                1057                      780           640           770   \n",
+       "37                1229                      952           867          1021   \n",
+       "38                1287                      939           795          1051   \n",
+       "39                1271                      965           825          1036   \n",
+       "40                1301                      978           842          1045   \n",
+       "41                1367                     1067           884          1053   \n",
+       "42                1553                     1001           904          1154   \n",
+       "43                1714                     1111           891          1124   \n",
+       "44                1754                     1168           882          1102   \n",
+       "45                1900                     1294           990          1186   \n",
+       "46                1950                     1350          1099          1317   \n",
+       "47                1935                     1441          1105          1385   \n",
+       "48                1791                     1501          1218          1358   \n",
+       "49                1679                     1403          1121          1340   \n",
+       "50                1691                     1326          1199          1432   \n",
+       "51                1718                     1380          1199          1385   \n",
+       "52                1463                     1130          1097          1217   \n",
+       "53                1346                      886           842          1024   \n",
         "\n",
         "                  East     London South East South West      Wales  \n",
         "Week number  E12000006  E12000007  E12000008  E12000009  W92000004  \n",
         "\n",
         "                  East     London South East South West      Wales  \n",
         "Week number  E12000006  E12000007  E12000008  E12000009  W92000004  \n",
@@ -2734,39 +3424,39 @@
         "29                 945        806       1339        953        550  \n",
         "30                 951        816       1340        941        565  \n",
         "31                 949        773       1447        988        531  \n",
         "29                 945        806       1339        953        550  \n",
         "30                 951        816       1340        941        565  \n",
         "31                 949        773       1447        988        531  \n",
-       "32                 NaT        NaT        NaT        NaT        NaT  \n",
-       "33                 NaT        NaT        NaT        NaT        NaT  \n",
-       "34                 NaT        NaT        NaT        NaT        NaT  \n",
-       "35                 NaT        NaT        NaT        NaT        NaT  \n",
-       "36                 NaT        NaT        NaT        NaT        NaT  \n",
-       "37                 NaT        NaT        NaT        NaT        NaT  \n",
-       "38                 NaT        NaT        NaT        NaT        NaT  \n",
-       "39                 NaT        NaT        NaT        NaT        NaT  \n",
-       "40                 NaT        NaT        NaT        NaT        NaT  \n",
-       "41                 NaT        NaT        NaT        NaT        NaT  \n",
-       "42                 NaT        NaT        NaT        NaT        NaT  \n",
-       "43                 NaT        NaT        NaT        NaT        NaT  \n",
-       "44                 NaT        NaT        NaT        NaT        NaT  \n",
-       "45                 NaT        NaT        NaT        NaT        NaT  \n",
-       "46                 NaT        NaT        NaT        NaT        NaT  \n",
-       "47                 NaT        NaT        NaT        NaT        NaT  \n",
-       "48                 NaT        NaT        NaT        NaT        NaT  \n",
-       "49                 NaT        NaT        NaT        NaT        NaT  \n",
-       "50                 NaT        NaT        NaT        NaT        NaT  \n",
-       "51                 NaT        NaT        NaT        NaT        NaT  \n",
-       "52                 NaT        NaT        NaT        NaT        NaT  \n",
-       "53                 NaT        NaT        NaT        NaT        NaT  \n",
+       "32                 955        832       1370        929        563  \n",
+       "33                1006        928       1395       1009        617  \n",
+       "34                1024        920       1608       1043        594  \n",
+       "35                 951        810       1511        959        591  \n",
+       "36                 806        737       1208        803        488  \n",
+       "37                1052        898       1610       1084        578  \n",
+       "38                1023        844       1530       1021        555  \n",
+       "39                 963        869       1521       1041        617  \n",
+       "40                1054        899       1577       1003        671  \n",
+       "41                1019        902       1462       1010        638  \n",
+       "42                1056        923       1462       1174        688  \n",
+       "43                1154        922       1510       1044        661  \n",
+       "44                1089        888       1563       1129        712  \n",
+       "45                1177        952       1614       1174        832  \n",
+       "46                1172       1112       1616       1168        742  \n",
+       "47                1186       1086       1687       1159        848  \n",
+       "48                1159       1012       1655       1272        797  \n",
+       "49                1229       1029       1720       1284        836  \n",
+       "50                1224       1065       1706       1156        814  \n",
+       "51                1317       1167       1947       1311        882  \n",
+       "52                1198       1090       1701       1115        825  \n",
+       "53                 997       1159       1595        929        727  \n",
         "\n",
         "[54 rows x 91 columns]"
        ]
       },
         "\n",
         "[54 rows x 91 columns]"
        ]
       },
-     "execution_count": 86,
+     "execution_count": 12,
       "metadata": {},
       "output_type": "execute_result"
      }
     ],
     "source": [
       "metadata": {},
       "output_type": "execute_result"
      }
     ],
     "source": [
-    "eng_xls = pd.read_excel('uk-deaths-data/publishedweek312020.xlsx', \n",
+    "eng_xls = pd.read_excel(england_wales_filename, \n",
      "                        sheet_name=\"Weekly figures 2020\",\n",
      "                        skiprows=[0, 1, 2, 3],\n",
      "                        header=0,\n",
      "                        sheet_name=\"Weekly figures 2020\",\n",
      "                        skiprows=[0, 1, 2, 3],\n",
      "                        header=0,\n",
@@ -2777,8 +3467,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 87,
-   "metadata": {},
+   "execution_count": 13,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "# eng_xls_columns"
     "outputs": [],
     "source": [
      "# eng_xls_columns"
@@ -2786,8 +3478,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 88,
-   "metadata": {},
+   "execution_count": 14,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "eng_xls_columns = list(eng_xls.columns)\n",
     "outputs": [],
     "source": [
      "eng_xls_columns = list(eng_xls.columns)\n",
@@ -2807,8 +3501,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 89,
-   "metadata": {},
+   "execution_count": 15,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
@@ -2845,32 +3541,32 @@
         "29                               8823\n",
         "30                               8891\n",
         "31                               8946\n",
         "29                               8823\n",
         "30                               8891\n",
         "31                               8946\n",
-       "32                                NaT\n",
-       "33                                NaT\n",
-       "34                                NaT\n",
-       "35                                NaT\n",
-       "36                                NaT\n",
-       "37                                NaT\n",
-       "38                                NaT\n",
-       "39                                NaT\n",
-       "40                                NaT\n",
-       "41                                NaT\n",
-       "42                                NaT\n",
-       "43                                NaT\n",
-       "44                                NaT\n",
-       "45                                NaT\n",
-       "46                                NaT\n",
-       "47                                NaT\n",
-       "48                                NaT\n",
-       "49                                NaT\n",
-       "50                                NaT\n",
-       "51                                NaT\n",
-       "52                                NaT\n",
-       "53                                NaT\n",
+       "32                               8945\n",
+       "33                               9392\n",
+       "34                               9631\n",
+       "35                               9032\n",
+       "36                               7739\n",
+       "37                               9811\n",
+       "38                               9523\n",
+       "39                               9634\n",
+       "40                               9945\n",
+       "41                               9954\n",
+       "42                              10534\n",
+       "43                              10739\n",
+       "44                              10887\n",
+       "45                              11812\n",
+       "46                              12254\n",
+       "47                              12535\n",
+       "48                              12456\n",
+       "49                              12303\n",
+       "50                              12292\n",
+       "51                              13011\n",
+       "52                              11520\n",
+       "53                              10069\n",
         "Name: Total deaths, all ages, dtype: object"
        ]
       },
         "Name: Total deaths, all ages, dtype: object"
        ]
       },
-     "execution_count": 89,
+     "execution_count": 15,
       "metadata": {},
       "output_type": "execute_result"
      }
       "metadata": {},
       "output_type": "execute_result"
      }
@@ -2881,8 +3577,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 90,
-   "metadata": {},
+   "execution_count": 16,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
@@ -2918,32 +3616,32 @@
         "29     550\n",
         "30     565\n",
         "31     531\n",
         "29     550\n",
         "30     565\n",
         "31     531\n",
-       "32     NaT\n",
-       "33     NaT\n",
-       "34     NaT\n",
-       "35     NaT\n",
-       "36     NaT\n",
-       "37     NaT\n",
-       "38     NaT\n",
-       "39     NaT\n",
-       "40     NaT\n",
-       "41     NaT\n",
-       "42     NaT\n",
-       "43     NaT\n",
-       "44     NaT\n",
-       "45     NaT\n",
-       "46     NaT\n",
-       "47     NaT\n",
-       "48     NaT\n",
-       "49     NaT\n",
-       "50     NaT\n",
-       "51     NaT\n",
-       "52     NaT\n",
-       "53     NaT\n",
+       "32     563\n",
+       "33     617\n",
+       "34     594\n",
+       "35     591\n",
+       "36     488\n",
+       "37     578\n",
+       "38     555\n",
+       "39     617\n",
+       "40     671\n",
+       "41     638\n",
+       "42     688\n",
+       "43     661\n",
+       "44     712\n",
+       "45     832\n",
+       "46     742\n",
+       "47     848\n",
+       "48     797\n",
+       "49     836\n",
+       "50     814\n",
+       "51     882\n",
+       "52     825\n",
+       "53     727\n",
         "Name: Wales, dtype: object"
        ]
       },
         "Name: Wales, dtype: object"
        ]
       },
-     "execution_count": 90,
+     "execution_count": 16,
       "metadata": {},
       "output_type": "execute_result"
      }
       "metadata": {},
       "output_type": "execute_result"
      }
@@ -2954,8 +3652,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 91,
-   "metadata": {},
+   "execution_count": 17,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "# raw_data_2020 = pd.read_csv('uk-deaths-data/publishedweek272020.csv', \n",
     "outputs": [],
     "source": [
      "# raw_data_2020 = pd.read_csv('uk-deaths-data/publishedweek272020.csv', \n",
@@ -2967,14 +3667,18 @@
    {
     "cell_type": "code",
     "execution_count": null,
    {
     "cell_type": "code",
     "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": []
    },
    {
     "cell_type": "code",
     "outputs": [],
     "source": []
    },
    {
     "cell_type": "code",
-   "execution_count": 92,
-   "metadata": {},
+   "execution_count": 18,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "# raw_data_2020.head()"
     "outputs": [],
     "source": [
      "# raw_data_2020.head()"
@@ -2982,8 +3686,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 93,
-   "metadata": {},
+   "execution_count": 19,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "# raw_data_2020['W92000004', 'Wales']"
     "outputs": [],
     "source": [
      "# raw_data_2020['W92000004', 'Wales']"
@@ -2991,8 +3697,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 94,
-   "metadata": {},
+   "execution_count": 20,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "raw_data_2019 = pd.read_csv('uk-deaths-data/publishedweek522019.csv', \n",
     "outputs": [],
     "source": [
      "raw_data_2019 = pd.read_csv('uk-deaths-data/publishedweek522019.csv', \n",
@@ -3004,8 +3712,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 95,
-   "metadata": {},
+   "execution_count": 21,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "raw_data_2018 = pd.read_csv('uk-deaths-data/publishedweek522018.csv', \n",
     "outputs": [],
     "source": [
      "raw_data_2018 = pd.read_csv('uk-deaths-data/publishedweek522018.csv', \n",
@@ -3017,8 +3727,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 96,
-   "metadata": {},
+   "execution_count": 22,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "raw_data_2017 = pd.read_csv('uk-deaths-data/publishedweek522017.csv', \n",
     "outputs": [],
     "source": [
      "raw_data_2017 = pd.read_csv('uk-deaths-data/publishedweek522017.csv', \n",
@@ -3030,8 +3742,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 97,
-   "metadata": {},
+   "execution_count": 23,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "raw_data_2016 = pd.read_csv('uk-deaths-data/publishedweek522016.csv', \n",
     "outputs": [],
     "source": [
      "raw_data_2016 = pd.read_csv('uk-deaths-data/publishedweek522016.csv', \n",
@@ -3043,8 +3757,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 98,
-   "metadata": {},
+   "execution_count": 24,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "raw_data_2015 = pd.read_csv('uk-deaths-data/publishedweek2015.csv', \n",
     "outputs": [],
     "source": [
      "raw_data_2015 = pd.read_csv('uk-deaths-data/publishedweek2015.csv', \n",
@@ -3056,8 +3772,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 99,
-   "metadata": {},
+   "execution_count": 25,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "dhw = eng_xls['Wales'].iloc[1:]\n",
     "outputs": [],
     "source": [
      "dhw = eng_xls['Wales'].iloc[1:]\n",
@@ -3068,8 +3786,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 100,
-   "metadata": {},
+   "execution_count": 26,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "# deaths_headlines_e = raw_data_2020.iloc[:, [1]].copy()\n",
     "outputs": [],
     "source": [
      "# deaths_headlines_e = raw_data_2020.iloc[:, [1]].copy()\n",
@@ -3084,9 +3804,23 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 101,
-   "metadata": {},
+   "execution_count": 27,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
     "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/neil/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5489: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  self[name] = value\n"
+     ]
+    },
      {
       "data": {
        "text/html": [
      {
       "data": {
        "text/html": [
@@ -3113,23 +3847,23 @@
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
-       "      <td>48</td>\n",
+       "      <th>48</th>\n",
         "      <td>10269</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>10269</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>49</td>\n",
+       "      <th>49</th>\n",
         "      <td>10079</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>10079</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>50</td>\n",
+       "      <th>50</th>\n",
         "      <td>10489</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>10489</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>51</td>\n",
+       "      <th>51</th>\n",
         "      <td>11159</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>11159</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>52</td>\n",
+       "      <th>52</th>\n",
         "      <td>7037</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "      <td>7037</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
@@ -3145,7 +3879,7 @@
         "52        7037"
        ]
       },
         "52        7037"
        ]
       },
-     "execution_count": 101,
+     "execution_count": 27,
       "metadata": {},
       "output_type": "execute_result"
      }
       "metadata": {},
       "output_type": "execute_result"
      }
@@ -3161,8 +3895,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 102,
-   "metadata": {},
+   "execution_count": 28,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
@@ -3190,23 +3926,23 @@
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
-       "      <td>1</td>\n",
+       "      <th>1</th>\n",
         "      <td>718</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>718</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2</td>\n",
+       "      <th>2</th>\n",
         "      <td>809</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>809</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>3</td>\n",
+       "      <th>3</th>\n",
         "      <td>683</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>683</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>4</td>\n",
+       "      <th>4</th>\n",
         "      <td>734</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>734</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>5</td>\n",
+       "      <th>5</th>\n",
         "      <td>745</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "      <td>745</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
@@ -3222,7 +3958,7 @@
         "5         745"
        ]
       },
         "5         745"
        ]
       },
-     "execution_count": 102,
+     "execution_count": 28,
       "metadata": {},
       "output_type": "execute_result"
      }
       "metadata": {},
       "output_type": "execute_result"
      }
@@ -3233,9 +3969,24 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 103,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 29,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/neil/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py:5489: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  self[name] = value\n"
+     ]
+    }
+   ],
     "source": [
      "dh18e = raw_data_2018.iloc[:, [1]]\n",
      "dh18w = raw_data_2018['W92000004']\n",
     "source": [
      "dh18e = raw_data_2018.iloc[:, [1]]\n",
      "dh18w = raw_data_2018['W92000004']\n",
@@ -3247,8 +3998,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 104,
-   "metadata": {},
+   "execution_count": 30,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "dh17e = raw_data_2017.iloc[:, [1]]\n",
     "outputs": [],
     "source": [
      "dh17e = raw_data_2017.iloc[:, [1]]\n",
@@ -3261,8 +4014,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 105,
-   "metadata": {},
+   "execution_count": 31,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "dh16e = raw_data_2016.iloc[:, [1]]\n",
     "outputs": [],
     "source": [
      "dh16e = raw_data_2016.iloc[:, [1]]\n",
@@ -3275,8 +4030,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 106,
-   "metadata": {},
+   "execution_count": 32,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "dh15e = raw_data_2015.iloc[:, [1]]\n",
     "outputs": [],
     "source": [
      "dh15e = raw_data_2015.iloc[:, [1]]\n",
@@ -3289,19 +4046,614 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 107,
-   "metadata": {},
+   "execution_count": 33,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
     "outputs": [],
     "source": [
-    "# dh18 = raw_data_2018.iloc[:, [1, 2]]\n",
-    "# dh18.columns = ['total_2018', 'total_previous']\n",
-    "# # dh18.head()"
+    "# dh18 = raw_data_2018.iloc[:, [1, 2]]\n",
+    "# dh18.columns = ['total_2018', 'total_previous']\n",
+    "# # dh18.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>total_2020</th>\n",
+       "      <th>total_2019</th>\n",
+       "      <th>total_2018</th>\n",
+       "      <th>total_2017</th>\n",
+       "      <th>total_2016</th>\n",
+       "      <th>total_2015</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>11467</td>\n",
+       "      <td>10237.0</td>\n",
+       "      <td>11940.0</td>\n",
+       "      <td>11247.0</td>\n",
+       "      <td>12236.0</td>\n",
+       "      <td>11561</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>13119</td>\n",
+       "      <td>11800.0</td>\n",
+       "      <td>14146.0</td>\n",
+       "      <td>12890.0</td>\n",
+       "      <td>10790.0</td>\n",
+       "      <td>15206</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>12223</td>\n",
+       "      <td>11177.0</td>\n",
+       "      <td>13371.0</td>\n",
+       "      <td>12775.0</td>\n",
+       "      <td>10753.0</td>\n",
+       "      <td>13930</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>11133</td>\n",
+       "      <td>11006.0</td>\n",
+       "      <td>13085.0</td>\n",
+       "      <td>11996.0</td>\n",
+       "      <td>10600.0</td>\n",
+       "      <td>13106</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>10885</td>\n",
+       "      <td>10552.0</td>\n",
+       "      <td>12470.0</td>\n",
+       "      <td>11736.0</td>\n",
+       "      <td>10362.0</td>\n",
+       "      <td>12099</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>10296</td>\n",
+       "      <td>10959.0</td>\n",
+       "      <td>11694.0</td>\n",
+       "      <td>11546.0</td>\n",
+       "      <td>10470.0</td>\n",
+       "      <td>11319</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>10216</td>\n",
+       "      <td>11076.0</td>\n",
+       "      <td>11443.0</td>\n",
+       "      <td>10954.0</td>\n",
+       "      <td>9933.0</td>\n",
+       "      <td>11112</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>10162</td>\n",
+       "      <td>10600.0</td>\n",
+       "      <td>11353.0</td>\n",
+       "      <td>11093.0</td>\n",
+       "      <td>10360.0</td>\n",
+       "      <td>10695</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>10165</td>\n",
+       "      <td>10360.0</td>\n",
+       "      <td>10220.0</td>\n",
+       "      <td>10533.0</td>\n",
+       "      <td>10564.0</td>\n",
+       "      <td>10736</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>10243</td>\n",
+       "      <td>10276.0</td>\n",
+       "      <td>12101.0</td>\n",
+       "      <td>10443.0</td>\n",
+       "      <td>10276.0</td>\n",
+       "      <td>10757</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>10344</td>\n",
+       "      <td>9901.0</td>\n",
+       "      <td>11870.0</td>\n",
+       "      <td>10044.0</td>\n",
+       "      <td>10284.0</td>\n",
+       "      <td>10290</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>9926</td>\n",
+       "      <td>9774.0</td>\n",
+       "      <td>11139.0</td>\n",
+       "      <td>9690.0</td>\n",
+       "      <td>8967.0</td>\n",
+       "      <td>9888</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>10422</td>\n",
+       "      <td>9213.0</td>\n",
+       "      <td>9308.0</td>\n",
+       "      <td>9369.0</td>\n",
+       "      <td>9574.0</td>\n",
+       "      <td>9827</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>15467</td>\n",
+       "      <td>9484.0</td>\n",
+       "      <td>10064.0</td>\n",
+       "      <td>9297.0</td>\n",
+       "      <td>10857.0</td>\n",
+       "      <td>8482</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>17588</td>\n",
+       "      <td>9654.0</td>\n",
+       "      <td>11558.0</td>\n",
+       "      <td>7916.0</td>\n",
+       "      <td>10679.0</td>\n",
+       "      <td>9429</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>21182</td>\n",
+       "      <td>8445.0</td>\n",
+       "      <td>10535.0</td>\n",
+       "      <td>8990.0</td>\n",
+       "      <td>10211.0</td>\n",
+       "      <td>10968</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>20873</td>\n",
+       "      <td>9381.0</td>\n",
+       "      <td>9692.0</td>\n",
+       "      <td>10181.0</td>\n",
+       "      <td>9784.0</td>\n",
+       "      <td>9937</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>17024</td>\n",
+       "      <td>10519.0</td>\n",
+       "      <td>9520.0</td>\n",
+       "      <td>8464.0</td>\n",
+       "      <td>8568.0</td>\n",
+       "      <td>9506</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>11965</td>\n",
+       "      <td>8455.0</td>\n",
+       "      <td>8094.0</td>\n",
+       "      <td>10006.0</td>\n",
+       "      <td>9985.0</td>\n",
+       "      <td>8273</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>13801</td>\n",
+       "      <td>9614.0</td>\n",
+       "      <td>9474.0</td>\n",
+       "      <td>9673.0</td>\n",
+       "      <td>9342.0</td>\n",
+       "      <td>9668</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>11596</td>\n",
+       "      <td>9657.0</td>\n",
+       "      <td>9033.0</td>\n",
+       "      <td>9438.0</td>\n",
+       "      <td>9115.0</td>\n",
+       "      <td>9391</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>9237</td>\n",
+       "      <td>7742.0</td>\n",
+       "      <td>7609.0</td>\n",
+       "      <td>7746.0</td>\n",
+       "      <td>7409.0</td>\n",
+       "      <td>7625</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>10009</td>\n",
+       "      <td>9514.0</td>\n",
+       "      <td>9343.0</td>\n",
+       "      <td>9182.0</td>\n",
+       "      <td>9289.0</td>\n",
+       "      <td>9509</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>9402</td>\n",
+       "      <td>8847.0</td>\n",
+       "      <td>8782.0</td>\n",
+       "      <td>8768.0</td>\n",
+       "      <td>8808.0</td>\n",
+       "      <td>8942</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>8722</td>\n",
+       "      <td>8916.0</td>\n",
+       "      <td>8694.0</td>\n",
+       "      <td>9019.0</td>\n",
+       "      <td>8807.0</td>\n",
+       "      <td>8717</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>8427</td>\n",
+       "      <td>8947.0</td>\n",
+       "      <td>8613.0</td>\n",
+       "      <td>8788.0</td>\n",
+       "      <td>8679.0</td>\n",
+       "      <td>8593</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>8556</td>\n",
+       "      <td>8528.0</td>\n",
+       "      <td>8633.0</td>\n",
+       "      <td>8707.0</td>\n",
+       "      <td>8614.0</td>\n",
+       "      <td>8670</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>8118</td>\n",
+       "      <td>8591.0</td>\n",
+       "      <td>8710.0</td>\n",
+       "      <td>8812.0</td>\n",
+       "      <td>8789.0</td>\n",
+       "      <td>8461</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>8273</td>\n",
+       "      <td>8527.0</td>\n",
+       "      <td>8579.0</td>\n",
+       "      <td>8562.0</td>\n",
+       "      <td>8790.0</td>\n",
+       "      <td>8228</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>8326</td>\n",
+       "      <td>8569.0</td>\n",
+       "      <td>8581.0</td>\n",
+       "      <td>8296.0</td>\n",
+       "      <td>8725.0</td>\n",
+       "      <td>8262</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>8415</td>\n",
+       "      <td>8701.0</td>\n",
+       "      <td>8587.0</td>\n",
+       "      <td>8351.0</td>\n",
+       "      <td>8602.0</td>\n",
+       "      <td>8071</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>8382</td>\n",
+       "      <td>8580.0</td>\n",
+       "      <td>8782.0</td>\n",
+       "      <td>8466.0</td>\n",
+       "      <td>8531.0</td>\n",
+       "      <td>8298</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>8775</td>\n",
+       "      <td>8504.0</td>\n",
+       "      <td>8312.0</td>\n",
+       "      <td>8707.0</td>\n",
+       "      <td>8496.0</td>\n",
+       "      <td>8600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>9037</td>\n",
+       "      <td>8441.0</td>\n",
+       "      <td>8413.0</td>\n",
+       "      <td>8812.0</td>\n",
+       "      <td>8700.0</td>\n",
+       "      <td>8564</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>8441</td>\n",
+       "      <td>7684.0</td>\n",
+       "      <td>7354.0</td>\n",
+       "      <td>7594.0</td>\n",
+       "      <td>7453.0</td>\n",
+       "      <td>8423</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>7251</td>\n",
+       "      <td>9113.0</td>\n",
+       "      <td>8851.0</td>\n",
+       "      <td>8955.0</td>\n",
+       "      <td>8847.0</td>\n",
+       "      <td>7389</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>9233</td>\n",
+       "      <td>8946.0</td>\n",
+       "      <td>8612.0</td>\n",
+       "      <td>8845.0</td>\n",
+       "      <td>8548.0</td>\n",
+       "      <td>8704</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>8968</td>\n",
+       "      <td>8868.0</td>\n",
+       "      <td>8707.0</td>\n",
+       "      <td>8949.0</td>\n",
+       "      <td>8382.0</td>\n",
+       "      <td>8542</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>9017</td>\n",
+       "      <td>8906.0</td>\n",
+       "      <td>8590.0</td>\n",
+       "      <td>9096.0</td>\n",
+       "      <td>8402.0</td>\n",
+       "      <td>8865</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>9274</td>\n",
+       "      <td>9202.0</td>\n",
+       "      <td>8908.0</td>\n",
+       "      <td>9147.0</td>\n",
+       "      <td>8729.0</td>\n",
+       "      <td>8858</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>9316</td>\n",
+       "      <td>9383.0</td>\n",
+       "      <td>9043.0</td>\n",
+       "      <td>9300.0</td>\n",
+       "      <td>9132.0</td>\n",
+       "      <td>9124</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>9846</td>\n",
+       "      <td>9534.0</td>\n",
+       "      <td>9224.0</td>\n",
+       "      <td>9381.0</td>\n",
+       "      <td>9144.0</td>\n",
+       "      <td>8899</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>10078</td>\n",
+       "      <td>9351.0</td>\n",
+       "      <td>8970.0</td>\n",
+       "      <td>9131.0</td>\n",
+       "      <td>9100.0</td>\n",
+       "      <td>9104</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>10175</td>\n",
+       "      <td>9522.0</td>\n",
+       "      <td>8925.0</td>\n",
+       "      <td>9389.0</td>\n",
+       "      <td>9508.0</td>\n",
+       "      <td>9025</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>10980</td>\n",
+       "      <td>10044.0</td>\n",
+       "      <td>9509.0</td>\n",
+       "      <td>9748.0</td>\n",
+       "      <td>9844.0</td>\n",
+       "      <td>9388</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>11512</td>\n",
+       "      <td>9976.0</td>\n",
+       "      <td>9537.0</td>\n",
+       "      <td>9609.0</td>\n",
+       "      <td>10013.0</td>\n",
+       "      <td>9325</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>11687</td>\n",
+       "      <td>10183.0</td>\n",
+       "      <td>9300.0</td>\n",
+       "      <td>9982.0</td>\n",
+       "      <td>9942.0</td>\n",
+       "      <td>9219</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>11659</td>\n",
+       "      <td>10269.0</td>\n",
+       "      <td>9360.0</td>\n",
+       "      <td>9902.0</td>\n",
+       "      <td>9796.0</td>\n",
+       "      <td>9233</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>11467</td>\n",
+       "      <td>10079.0</td>\n",
+       "      <td>9613.0</td>\n",
+       "      <td>10151.0</td>\n",
+       "      <td>10530.0</td>\n",
+       "      <td>9706</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>11478</td>\n",
+       "      <td>10489.0</td>\n",
+       "      <td>9842.0</td>\n",
+       "      <td>10509.0</td>\n",
+       "      <td>9870.0</td>\n",
+       "      <td>9581</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>12129</td>\n",
+       "      <td>11159.0</td>\n",
+       "      <td>10392.0</td>\n",
+       "      <td>11755.0</td>\n",
+       "      <td>10802.0</td>\n",
+       "      <td>10043</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>10695</td>\n",
+       "      <td>7037.0</td>\n",
+       "      <td>6670.0</td>\n",
+       "      <td>7946.0</td>\n",
+       "      <td>7445.0</td>\n",
+       "      <td>8095</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>9342</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7008</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   total_2020  total_2019  total_2018  total_2017  total_2016  total_2015\n",
+       "1       11467     10237.0     11940.0     11247.0     12236.0       11561\n",
+       "2       13119     11800.0     14146.0     12890.0     10790.0       15206\n",
+       "3       12223     11177.0     13371.0     12775.0     10753.0       13930\n",
+       "4       11133     11006.0     13085.0     11996.0     10600.0       13106\n",
+       "5       10885     10552.0     12470.0     11736.0     10362.0       12099\n",
+       "6       10296     10959.0     11694.0     11546.0     10470.0       11319\n",
+       "7       10216     11076.0     11443.0     10954.0      9933.0       11112\n",
+       "8       10162     10600.0     11353.0     11093.0     10360.0       10695\n",
+       "9       10165     10360.0     10220.0     10533.0     10564.0       10736\n",
+       "10      10243     10276.0     12101.0     10443.0     10276.0       10757\n",
+       "11      10344      9901.0     11870.0     10044.0     10284.0       10290\n",
+       "12       9926      9774.0     11139.0      9690.0      8967.0        9888\n",
+       "13      10422      9213.0      9308.0      9369.0      9574.0        9827\n",
+       "14      15467      9484.0     10064.0      9297.0     10857.0        8482\n",
+       "15      17588      9654.0     11558.0      7916.0     10679.0        9429\n",
+       "16      21182      8445.0     10535.0      8990.0     10211.0       10968\n",
+       "17      20873      9381.0      9692.0     10181.0      9784.0        9937\n",
+       "18      17024     10519.0      9520.0      8464.0      8568.0        9506\n",
+       "19      11965      8455.0      8094.0     10006.0      9985.0        8273\n",
+       "20      13801      9614.0      9474.0      9673.0      9342.0        9668\n",
+       "21      11596      9657.0      9033.0      9438.0      9115.0        9391\n",
+       "22       9237      7742.0      7609.0      7746.0      7409.0        7625\n",
+       "23      10009      9514.0      9343.0      9182.0      9289.0        9509\n",
+       "24       9402      8847.0      8782.0      8768.0      8808.0        8942\n",
+       "25       8722      8916.0      8694.0      9019.0      8807.0        8717\n",
+       "26       8427      8947.0      8613.0      8788.0      8679.0        8593\n",
+       "27       8556      8528.0      8633.0      8707.0      8614.0        8670\n",
+       "28       8118      8591.0      8710.0      8812.0      8789.0        8461\n",
+       "29       8273      8527.0      8579.0      8562.0      8790.0        8228\n",
+       "30       8326      8569.0      8581.0      8296.0      8725.0        8262\n",
+       "31       8415      8701.0      8587.0      8351.0      8602.0        8071\n",
+       "32       8382      8580.0      8782.0      8466.0      8531.0        8298\n",
+       "33       8775      8504.0      8312.0      8707.0      8496.0        8600\n",
+       "34       9037      8441.0      8413.0      8812.0      8700.0        8564\n",
+       "35       8441      7684.0      7354.0      7594.0      7453.0        8423\n",
+       "36       7251      9113.0      8851.0      8955.0      8847.0        7389\n",
+       "37       9233      8946.0      8612.0      8845.0      8548.0        8704\n",
+       "38       8968      8868.0      8707.0      8949.0      8382.0        8542\n",
+       "39       9017      8906.0      8590.0      9096.0      8402.0        8865\n",
+       "40       9274      9202.0      8908.0      9147.0      8729.0        8858\n",
+       "41       9316      9383.0      9043.0      9300.0      9132.0        9124\n",
+       "42       9846      9534.0      9224.0      9381.0      9144.0        8899\n",
+       "43      10078      9351.0      8970.0      9131.0      9100.0        9104\n",
+       "44      10175      9522.0      8925.0      9389.0      9508.0        9025\n",
+       "45      10980     10044.0      9509.0      9748.0      9844.0        9388\n",
+       "46      11512      9976.0      9537.0      9609.0     10013.0        9325\n",
+       "47      11687     10183.0      9300.0      9982.0      9942.0        9219\n",
+       "48      11659     10269.0      9360.0      9902.0      9796.0        9233\n",
+       "49      11467     10079.0      9613.0     10151.0     10530.0        9706\n",
+       "50      11478     10489.0      9842.0     10509.0      9870.0        9581\n",
+       "51      12129     11159.0     10392.0     11755.0     10802.0       10043\n",
+       "52      10695      7037.0      6670.0      7946.0      7445.0        8095\n",
+       "53       9342         NaN         NaN         NaN         NaN        7008"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths_headlines_e = deaths_headlines_e.merge(dh19e['total_2019'], how='outer', left_index=True, right_index=True)\n",
+    "deaths_headlines_e = deaths_headlines_e.merge(dh18e['total_2018'], how='outer', left_index=True, right_index=True)\n",
+    "deaths_headlines_e = deaths_headlines_e.merge(dh17e['total_2017'], how='outer', left_index=True, right_index=True)\n",
+    "deaths_headlines_e = deaths_headlines_e.merge(dh16e['total_2016'], how='outer', left_index=True, right_index=True)\n",
+    "# deaths_headlines = deaths_headlines.merge(dh15['total_2015'], how='outer', left_index=True, right_index=True)\n",
+    "deaths_headlines_e = deaths_headlines_e.merge(dh15e['total_2015'], how='left', left_index=True, right_index=True)\n",
+    "deaths_headlines_e"
     ]
    },
    {
     "cell_type": "code",
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 108,
-   "metadata": {},
+   "execution_count": 35,
+   "metadata": {
+    "Collapsed": "false",
+    "scrolled": true
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
@@ -3334,553 +4686,573 @@
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
-       "      <td>1</td>\n",
-       "      <td>11467</td>\n",
-       "      <td>10237</td>\n",
-       "      <td>11940</td>\n",
-       "      <td>11247</td>\n",
-       "      <td>12236</td>\n",
-       "      <td>11561</td>\n",
+       "      <th>1</th>\n",
+       "      <td>1161</td>\n",
+       "      <td>1104.0</td>\n",
+       "      <td>1531.0</td>\n",
+       "      <td>1205.0</td>\n",
+       "      <td>1394.0</td>\n",
+       "      <td>1146</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2</td>\n",
-       "      <td>13119</td>\n",
-       "      <td>11800</td>\n",
-       "      <td>14146</td>\n",
-       "      <td>12890</td>\n",
-       "      <td>10790</td>\n",
-       "      <td>15206</td>\n",
+       "      <th>2</th>\n",
+       "      <td>1567</td>\n",
+       "      <td>1507.0</td>\n",
+       "      <td>1899.0</td>\n",
+       "      <td>1379.0</td>\n",
+       "      <td>1305.0</td>\n",
+       "      <td>1708</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>3</td>\n",
-       "      <td>12223</td>\n",
-       "      <td>11177</td>\n",
-       "      <td>13371</td>\n",
-       "      <td>12775</td>\n",
-       "      <td>10753</td>\n",
-       "      <td>13930</td>\n",
+       "      <th>3</th>\n",
+       "      <td>1322</td>\n",
+       "      <td>1353.0</td>\n",
+       "      <td>1629.0</td>\n",
+       "      <td>1224.0</td>\n",
+       "      <td>1215.0</td>\n",
+       "      <td>1489</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>4</td>\n",
-       "      <td>11133</td>\n",
-       "      <td>11006</td>\n",
-       "      <td>13085</td>\n",
-       "      <td>11996</td>\n",
-       "      <td>10600</td>\n",
-       "      <td>13106</td>\n",
+       "      <th>4</th>\n",
+       "      <td>1226</td>\n",
+       "      <td>1208.0</td>\n",
+       "      <td>1610.0</td>\n",
+       "      <td>1197.0</td>\n",
+       "      <td>1187.0</td>\n",
+       "      <td>1381</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>5</td>\n",
-       "      <td>10885</td>\n",
-       "      <td>10552</td>\n",
-       "      <td>12470</td>\n",
-       "      <td>11736</td>\n",
-       "      <td>10362</td>\n",
-       "      <td>12099</td>\n",
+       "      <th>5</th>\n",
+       "      <td>1188</td>\n",
+       "      <td>1206.0</td>\n",
+       "      <td>1369.0</td>\n",
+       "      <td>1332.0</td>\n",
+       "      <td>1205.0</td>\n",
+       "      <td>1286</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>6</td>\n",
-       "      <td>10296</td>\n",
-       "      <td>10959</td>\n",
-       "      <td>11694</td>\n",
-       "      <td>11546</td>\n",
-       "      <td>10470</td>\n",
-       "      <td>11319</td>\n",
+       "      <th>6</th>\n",
+       "      <td>1216</td>\n",
+       "      <td>1243.0</td>\n",
+       "      <td>1265.0</td>\n",
+       "      <td>1200.0</td>\n",
+       "      <td>1217.0</td>\n",
+       "      <td>1344</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>7</td>\n",
-       "      <td>10216</td>\n",
-       "      <td>11076</td>\n",
-       "      <td>11443</td>\n",
-       "      <td>10954</td>\n",
-       "      <td>9933</td>\n",
-       "      <td>11112</td>\n",
+       "      <th>7</th>\n",
+       "      <td>1162</td>\n",
+       "      <td>1181.0</td>\n",
+       "      <td>1315.0</td>\n",
+       "      <td>1231.0</td>\n",
+       "      <td>1209.0</td>\n",
+       "      <td>1360</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>8</td>\n",
-       "      <td>10162</td>\n",
-       "      <td>10600</td>\n",
-       "      <td>11353</td>\n",
-       "      <td>11093</td>\n",
-       "      <td>10360</td>\n",
-       "      <td>10695</td>\n",
+       "      <th>8</th>\n",
+       "      <td>1162</td>\n",
+       "      <td>1245.0</td>\n",
+       "      <td>1245.0</td>\n",
+       "      <td>1185.0</td>\n",
+       "      <td>1239.0</td>\n",
+       "      <td>1320</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>9</td>\n",
-       "      <td>10165</td>\n",
-       "      <td>10360</td>\n",
-       "      <td>10220</td>\n",
-       "      <td>10533</td>\n",
-       "      <td>10564</td>\n",
-       "      <td>10736</td>\n",
+       "      <th>9</th>\n",
+       "      <td>1171</td>\n",
+       "      <td>1125.0</td>\n",
+       "      <td>1022.0</td>\n",
+       "      <td>1219.0</td>\n",
+       "      <td>1150.0</td>\n",
+       "      <td>1308</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>10</td>\n",
-       "      <td>10243</td>\n",
-       "      <td>10276</td>\n",
-       "      <td>12101</td>\n",
-       "      <td>10443</td>\n",
-       "      <td>10276</td>\n",
-       "      <td>10757</td>\n",
+       "      <th>10</th>\n",
+       "      <td>1208</td>\n",
+       "      <td>1156.0</td>\n",
+       "      <td>1475.0</td>\n",
+       "      <td>1146.0</td>\n",
+       "      <td>1174.0</td>\n",
+       "      <td>1192</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>11</td>\n",
-       "      <td>10344</td>\n",
-       "      <td>9901</td>\n",
-       "      <td>11870</td>\n",
-       "      <td>10044</td>\n",
-       "      <td>10284</td>\n",
-       "      <td>10290</td>\n",
+       "      <th>11</th>\n",
+       "      <td>1156</td>\n",
+       "      <td>1108.0</td>\n",
+       "      <td>1220.0</td>\n",
+       "      <td>1141.0</td>\n",
+       "      <td>1175.0</td>\n",
+       "      <td>1201</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>12</td>\n",
-       "      <td>9926</td>\n",
-       "      <td>9774</td>\n",
-       "      <td>11139</td>\n",
-       "      <td>9690</td>\n",
-       "      <td>8967</td>\n",
-       "      <td>9888</td>\n",
+       "      <th>12</th>\n",
+       "      <td>1196</td>\n",
+       "      <td>1101.0</td>\n",
+       "      <td>1158.0</td>\n",
+       "      <td>1152.0</td>\n",
+       "      <td>1042.0</td>\n",
+       "      <td>1149</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>13</td>\n",
-       "      <td>10422</td>\n",
-       "      <td>9213</td>\n",
-       "      <td>9308</td>\n",
-       "      <td>9369</td>\n",
-       "      <td>9574</td>\n",
-       "      <td>9827</td>\n",
+       "      <th>13</th>\n",
+       "      <td>1079</td>\n",
+       "      <td>1086.0</td>\n",
+       "      <td>1050.0</td>\n",
+       "      <td>1112.0</td>\n",
+       "      <td>1172.0</td>\n",
+       "      <td>1171</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>14</td>\n",
-       "      <td>15467</td>\n",
-       "      <td>9484</td>\n",
-       "      <td>10064</td>\n",
-       "      <td>9297</td>\n",
-       "      <td>10857</td>\n",
-       "      <td>8482</td>\n",
+       "      <th>14</th>\n",
+       "      <td>1744</td>\n",
+       "      <td>1032.0</td>\n",
+       "      <td>1192.0</td>\n",
+       "      <td>1060.0</td>\n",
+       "      <td>1166.0</td>\n",
+       "      <td>1042</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>15</td>\n",
-       "      <td>17588</td>\n",
-       "      <td>9654</td>\n",
-       "      <td>11558</td>\n",
-       "      <td>7916</td>\n",
-       "      <td>10679</td>\n",
-       "      <td>9429</td>\n",
+       "      <th>15</th>\n",
+       "      <td>1978</td>\n",
+       "      <td>1069.0</td>\n",
+       "      <td>1192.0</td>\n",
+       "      <td>998.0</td>\n",
+       "      <td>1048.0</td>\n",
+       "      <td>1192</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>16</td>\n",
-       "      <td>21182</td>\n",
-       "      <td>8445</td>\n",
-       "      <td>10535</td>\n",
-       "      <td>8990</td>\n",
-       "      <td>10211</td>\n",
-       "      <td>10968</td>\n",
+       "      <th>16</th>\n",
+       "      <td>1916</td>\n",
+       "      <td>902.0</td>\n",
+       "      <td>1136.0</td>\n",
+       "      <td>1111.0</td>\n",
+       "      <td>1092.0</td>\n",
+       "      <td>1095</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>17</td>\n",
-       "      <td>20873</td>\n",
-       "      <td>9381</td>\n",
-       "      <td>9692</td>\n",
-       "      <td>10181</td>\n",
-       "      <td>9784</td>\n",
-       "      <td>9937</td>\n",
+       "      <th>17</th>\n",
+       "      <td>1836</td>\n",
+       "      <td>1121.0</td>\n",
+       "      <td>1008.0</td>\n",
+       "      <td>1121.0</td>\n",
+       "      <td>1076.0</td>\n",
+       "      <td>1108</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>18</td>\n",
-       "      <td>17024</td>\n",
-       "      <td>10519</td>\n",
-       "      <td>9520</td>\n",
-       "      <td>8464</td>\n",
-       "      <td>8568</td>\n",
-       "      <td>9506</td>\n",
+       "      <th>18</th>\n",
+       "      <td>1679</td>\n",
+       "      <td>1131.0</td>\n",
+       "      <td>1093.0</td>\n",
+       "      <td>1050.0</td>\n",
+       "      <td>1006.0</td>\n",
+       "      <td>1117</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>19</td>\n",
-       "      <td>11965</td>\n",
-       "      <td>8455</td>\n",
-       "      <td>8094</td>\n",
-       "      <td>10006</td>\n",
-       "      <td>9985</td>\n",
-       "      <td>8273</td>\n",
+       "      <th>19</th>\n",
+       "      <td>1435</td>\n",
+       "      <td>1018.0</td>\n",
+       "      <td>967.0</td>\n",
+       "      <td>1119.0</td>\n",
+       "      <td>1047.0</td>\n",
+       "      <td>1020</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>20</td>\n",
-       "      <td>13801</td>\n",
-       "      <td>9614</td>\n",
-       "      <td>9474</td>\n",
-       "      <td>9673</td>\n",
-       "      <td>9342</td>\n",
-       "      <td>9668</td>\n",
+       "      <th>20</th>\n",
+       "      <td>1421</td>\n",
+       "      <td>1115.0</td>\n",
+       "      <td>977.0</td>\n",
+       "      <td>1115.0</td>\n",
+       "      <td>1010.0</td>\n",
+       "      <td>1103</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>21</td>\n",
-       "      <td>11596</td>\n",
-       "      <td>9657</td>\n",
-       "      <td>9033</td>\n",
-       "      <td>9438</td>\n",
-       "      <td>9115</td>\n",
-       "      <td>9391</td>\n",
+       "      <th>21</th>\n",
+       "      <td>1226</td>\n",
+       "      <td>1061.0</td>\n",
+       "      <td>1070.0</td>\n",
+       "      <td>1063.0</td>\n",
+       "      <td>994.0</td>\n",
+       "      <td>1039</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>22</td>\n",
-       "      <td>9237</td>\n",
-       "      <td>7742</td>\n",
-       "      <td>7609</td>\n",
-       "      <td>7746</td>\n",
-       "      <td>7409</td>\n",
-       "      <td>7625</td>\n",
+       "      <th>22</th>\n",
+       "      <td>1125</td>\n",
+       "      <td>1029.0</td>\n",
+       "      <td>998.0</td>\n",
+       "      <td>1015.0</td>\n",
+       "      <td>999.0</td>\n",
+       "      <td>1043</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>23</td>\n",
-       "      <td>10009</td>\n",
-       "      <td>9514</td>\n",
-       "      <td>9343</td>\n",
-       "      <td>9182</td>\n",
-       "      <td>9289</td>\n",
-       "      <td>9509</td>\n",
+       "      <th>23</th>\n",
+       "      <td>1093</td>\n",
+       "      <td>1042.0</td>\n",
+       "      <td>1033.0</td>\n",
+       "      <td>1076.0</td>\n",
+       "      <td>1023.0</td>\n",
+       "      <td>1106</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>24</td>\n",
-       "      <td>9402</td>\n",
-       "      <td>8847</td>\n",
-       "      <td>8782</td>\n",
-       "      <td>8768</td>\n",
-       "      <td>8808</td>\n",
-       "      <td>8942</td>\n",
+       "      <th>24</th>\n",
+       "      <td>1034</td>\n",
+       "      <td>1028.0</td>\n",
+       "      <td>915.0</td>\n",
+       "      <td>1031.0</td>\n",
+       "      <td>988.0</td>\n",
+       "      <td>1038</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>25</td>\n",
-       "      <td>8722</td>\n",
-       "      <td>8916</td>\n",
-       "      <td>8694</td>\n",
-       "      <td>9019</td>\n",
-       "      <td>8807</td>\n",
-       "      <td>8717</td>\n",
+       "      <th>25</th>\n",
+       "      <td>1065</td>\n",
+       "      <td>1053.0</td>\n",
+       "      <td>993.0</td>\n",
+       "      <td>1032.0</td>\n",
+       "      <td>994.0</td>\n",
+       "      <td>1025</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>26</td>\n",
-       "      <td>8427</td>\n",
-       "      <td>8947</td>\n",
-       "      <td>8613</td>\n",
-       "      <td>8788</td>\n",
-       "      <td>8679</td>\n",
-       "      <td>8593</td>\n",
+       "      <th>26</th>\n",
+       "      <td>1008</td>\n",
+       "      <td>1051.0</td>\n",
+       "      <td>1046.0</td>\n",
+       "      <td>994.0</td>\n",
+       "      <td>1007.0</td>\n",
+       "      <td>1032</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>27</td>\n",
-       "      <td>8556</td>\n",
-       "      <td>8528</td>\n",
-       "      <td>8633</td>\n",
-       "      <td>8707</td>\n",
-       "      <td>8614</td>\n",
-       "      <td>8670</td>\n",
+       "      <th>27</th>\n",
+       "      <td>983</td>\n",
+       "      <td>981.0</td>\n",
+       "      <td>1041.0</td>\n",
+       "      <td>1040.0</td>\n",
+       "      <td>988.0</td>\n",
+       "      <td>1040</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>28</td>\n",
-       "      <td>8118</td>\n",
-       "      <td>8591</td>\n",
-       "      <td>8710</td>\n",
-       "      <td>8812</td>\n",
-       "      <td>8789</td>\n",
-       "      <td>8461</td>\n",
+       "      <th>28</th>\n",
+       "      <td>976</td>\n",
+       "      <td>1077.0</td>\n",
+       "      <td>1002.0</td>\n",
+       "      <td>1014.0</td>\n",
+       "      <td>1022.0</td>\n",
+       "      <td>1011</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>29</td>\n",
-       "      <td>8273</td>\n",
-       "      <td>8527</td>\n",
-       "      <td>8579</td>\n",
-       "      <td>8562</td>\n",
-       "      <td>8790</td>\n",
-       "      <td>8228</td>\n",
+       "      <th>29</th>\n",
+       "      <td>1033</td>\n",
+       "      <td>964.0</td>\n",
+       "      <td>928.0</td>\n",
+       "      <td>1025.0</td>\n",
+       "      <td>1041.0</td>\n",
+       "      <td>1023</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>30</td>\n",
-       "      <td>8326</td>\n",
-       "      <td>8569</td>\n",
-       "      <td>8581</td>\n",
-       "      <td>8296</td>\n",
-       "      <td>8725</td>\n",
-       "      <td>8262</td>\n",
+       "      <th>30</th>\n",
+       "      <td>961</td>\n",
+       "      <td>1041.0</td>\n",
+       "      <td>933.0</td>\n",
+       "      <td>978.0</td>\n",
+       "      <td>979.0</td>\n",
+       "      <td>956</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>31</td>\n",
-       "      <td>8415</td>\n",
-       "      <td>8701</td>\n",
-       "      <td>8587</td>\n",
-       "      <td>8351</td>\n",
-       "      <td>8602</td>\n",
-       "      <td>8071</td>\n",
+       "      <th>31</th>\n",
+       "      <td>1043</td>\n",
+       "      <td>1020.0</td>\n",
+       "      <td>969.0</td>\n",
+       "      <td>1011.0</td>\n",
+       "      <td>987.0</td>\n",
+       "      <td>985</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>32</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>8580</td>\n",
-       "      <td>8782</td>\n",
-       "      <td>8466</td>\n",
-       "      <td>8531</td>\n",
-       "      <td>8298</td>\n",
+       "      <th>32</th>\n",
+       "      <td>1011</td>\n",
+       "      <td>1018.0</td>\n",
+       "      <td>953.0</td>\n",
+       "      <td>1002.0</td>\n",
+       "      <td>997.0</td>\n",
+       "      <td>1043</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>33</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>8504</td>\n",
-       "      <td>8312</td>\n",
-       "      <td>8707</td>\n",
-       "      <td>8496</td>\n",
-       "      <td>8600</td>\n",
+       "      <th>33</th>\n",
+       "      <td>922</td>\n",
+       "      <td>1028.0</td>\n",
+       "      <td>978.0</td>\n",
+       "      <td>1004.0</td>\n",
+       "      <td>982.0</td>\n",
+       "      <td>969</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>34</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>8441</td>\n",
-       "      <td>8413</td>\n",
-       "      <td>8812</td>\n",
-       "      <td>8700</td>\n",
-       "      <td>8564</td>\n",
+       "      <th>34</th>\n",
+       "      <td>1046</td>\n",
+       "      <td>1011.0</td>\n",
+       "      <td>941.0</td>\n",
+       "      <td>1045.0</td>\n",
+       "      <td>1017.0</td>\n",
+       "      <td>982</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>35</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>7684</td>\n",
-       "      <td>7354</td>\n",
-       "      <td>7594</td>\n",
-       "      <td>7453</td>\n",
-       "      <td>8423</td>\n",
+       "      <th>35</th>\n",
+       "      <td>1029</td>\n",
+       "      <td>1013.0</td>\n",
+       "      <td>930.0</td>\n",
+       "      <td>980.0</td>\n",
+       "      <td>1039.0</td>\n",
+       "      <td>954</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>36</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>9113</td>\n",
-       "      <td>8851</td>\n",
-       "      <td>8955</td>\n",
-       "      <td>8847</td>\n",
-       "      <td>7389</td>\n",
+       "      <th>36</th>\n",
+       "      <td>1050</td>\n",
+       "      <td>980.0</td>\n",
+       "      <td>970.0</td>\n",
+       "      <td>1006.0</td>\n",
+       "      <td>1007.0</td>\n",
+       "      <td>977</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>37</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>8946</td>\n",
-       "      <td>8612</td>\n",
-       "      <td>8845</td>\n",
-       "      <td>8548</td>\n",
-       "      <td>8704</td>\n",
+       "      <th>37</th>\n",
+       "      <td>1069</td>\n",
+       "      <td>1074.0</td>\n",
+       "      <td>1020.0</td>\n",
+       "      <td>972.0</td>\n",
+       "      <td>983.0</td>\n",
+       "      <td>991</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>38</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>8868</td>\n",
-       "      <td>8707</td>\n",
-       "      <td>8949</td>\n",
-       "      <td>8382</td>\n",
-       "      <td>8542</td>\n",
+       "      <th>38</th>\n",
+       "      <td>952</td>\n",
+       "      <td>1071.0</td>\n",
+       "      <td>946.0</td>\n",
+       "      <td>1049.0</td>\n",
+       "      <td>966.0</td>\n",
+       "      <td>1001</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>39</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>8906</td>\n",
-       "      <td>8590</td>\n",
-       "      <td>9096</td>\n",
-       "      <td>8402</td>\n",
-       "      <td>8865</td>\n",
+       "      <th>39</th>\n",
+       "      <td>933</td>\n",
+       "      <td>1142.0</td>\n",
+       "      <td>1015.0</td>\n",
+       "      <td>1056.0</td>\n",
+       "      <td>1009.0</td>\n",
+       "      <td>1010</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>40</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>9202</td>\n",
-       "      <td>8908</td>\n",
-       "      <td>9147</td>\n",
-       "      <td>8729</td>\n",
-       "      <td>8858</td>\n",
+       "      <th>40</th>\n",
+       "      <td>1195</td>\n",
+       "      <td>1051.0</td>\n",
+       "      <td>1042.0</td>\n",
+       "      <td>1016.0</td>\n",
+       "      <td>1072.0</td>\n",
+       "      <td>1008</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>41</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>9383</td>\n",
-       "      <td>9043</td>\n",
-       "      <td>9300</td>\n",
-       "      <td>9132</td>\n",
-       "      <td>9124</td>\n",
+       "      <th>41</th>\n",
+       "      <td>1071</td>\n",
+       "      <td>1143.0</td>\n",
+       "      <td>1081.0</td>\n",
+       "      <td>1133.0</td>\n",
+       "      <td>1009.0</td>\n",
+       "      <td>1028</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>42</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>9534</td>\n",
-       "      <td>9224</td>\n",
-       "      <td>9381</td>\n",
-       "      <td>9144</td>\n",
-       "      <td>8899</td>\n",
+       "      <th>42</th>\n",
+       "      <td>1131</td>\n",
+       "      <td>1153.0</td>\n",
+       "      <td>1031.0</td>\n",
+       "      <td>1067.0</td>\n",
+       "      <td>1070.0</td>\n",
+       "      <td>989</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>43</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>9351</td>\n",
-       "      <td>8970</td>\n",
-       "      <td>9131</td>\n",
-       "      <td>9100</td>\n",
-       "      <td>9104</td>\n",
+       "      <th>43</th>\n",
+       "      <td>1187</td>\n",
+       "      <td>1115.0</td>\n",
+       "      <td>1019.0</td>\n",
+       "      <td>1095.0</td>\n",
+       "      <td>1052.0</td>\n",
+       "      <td>981</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>44</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>9522</td>\n",
-       "      <td>8925</td>\n",
-       "      <td>9389</td>\n",
-       "      <td>9508</td>\n",
-       "      <td>9025</td>\n",
+       "      <th>44</th>\n",
+       "      <td>1262</td>\n",
+       "      <td>1101.0</td>\n",
+       "      <td>1085.0</td>\n",
+       "      <td>1062.0</td>\n",
+       "      <td>1032.0</td>\n",
+       "      <td>1116</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>45</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>10044</td>\n",
-       "      <td>9509</td>\n",
-       "      <td>9748</td>\n",
-       "      <td>9844</td>\n",
-       "      <td>9388</td>\n",
+       "      <th>45</th>\n",
+       "      <td>1250</td>\n",
+       "      <td>1184.0</td>\n",
+       "      <td>1144.0</td>\n",
+       "      <td>1126.0</td>\n",
+       "      <td>1043.0</td>\n",
+       "      <td>1028</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>46</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>9976</td>\n",
-       "      <td>9537</td>\n",
-       "      <td>9609</td>\n",
-       "      <td>10013</td>\n",
-       "      <td>9325</td>\n",
+       "      <th>46</th>\n",
+       "      <td>1138</td>\n",
+       "      <td>1160.0</td>\n",
+       "      <td>1084.0</td>\n",
+       "      <td>1175.0</td>\n",
+       "      <td>1174.0</td>\n",
+       "      <td>1103</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>47</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>10183</td>\n",
-       "      <td>9300</td>\n",
-       "      <td>9982</td>\n",
-       "      <td>9942</td>\n",
-       "      <td>9219</td>\n",
+       "      <th>47</th>\n",
+       "      <td>1360</td>\n",
+       "      <td>1229.0</td>\n",
+       "      <td>1058.0</td>\n",
+       "      <td>1178.0</td>\n",
+       "      <td>1132.0</td>\n",
+       "      <td>1054</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>48</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>10269</td>\n",
-       "      <td>9360</td>\n",
-       "      <td>9902</td>\n",
-       "      <td>9796</td>\n",
-       "      <td>9233</td>\n",
+       "      <th>48</th>\n",
+       "      <td>1328</td>\n",
+       "      <td>1163.0</td>\n",
+       "      <td>1062.0</td>\n",
+       "      <td>1153.0</td>\n",
+       "      <td>1159.0</td>\n",
+       "      <td>1115</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>49</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>10079</td>\n",
-       "      <td>9613</td>\n",
-       "      <td>10151</td>\n",
-       "      <td>10530</td>\n",
-       "      <td>9706</td>\n",
+       "      <th>49</th>\n",
+       "      <td>1296</td>\n",
+       "      <td>1108.0</td>\n",
+       "      <td>1076.0</td>\n",
+       "      <td>1237.0</td>\n",
+       "      <td>1188.0</td>\n",
+       "      <td>1089</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>50</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>10489</td>\n",
-       "      <td>9842</td>\n",
-       "      <td>10509</td>\n",
-       "      <td>9870</td>\n",
-       "      <td>9581</td>\n",
+       "      <th>50</th>\n",
+       "      <td>1284</td>\n",
+       "      <td>1312.0</td>\n",
+       "      <td>1212.0</td>\n",
+       "      <td>1335.0</td>\n",
+       "      <td>1219.0</td>\n",
+       "      <td>1101</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>51</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>11159</td>\n",
-       "      <td>10392</td>\n",
-       "      <td>11755</td>\n",
-       "      <td>10802</td>\n",
-       "      <td>10043</td>\n",
+       "      <th>51</th>\n",
+       "      <td>1297</td>\n",
+       "      <td>1277.0</td>\n",
+       "      <td>1216.0</td>\n",
+       "      <td>1437.0</td>\n",
+       "      <td>1284.0</td>\n",
+       "      <td>1146</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>52</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>7037</td>\n",
-       "      <td>6670</td>\n",
-       "      <td>7946</td>\n",
-       "      <td>7445</td>\n",
-       "      <td>8095</td>\n",
+       "      <th>52</th>\n",
+       "      <td>1205</td>\n",
+       "      <td>1000.0</td>\n",
+       "      <td>1058.0</td>\n",
+       "      <td>1168.0</td>\n",
+       "      <td>1133.0</td>\n",
+       "      <td>944</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "</div>"
        ],
        "text/plain": [
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "</div>"
        ],
        "text/plain": [
-       "   total_2020  total_2019  total_2018  total_2017  total_2016  total_2015\n",
-       "1       11467       10237       11940       11247       12236       11561\n",
-       "2       13119       11800       14146       12890       10790       15206\n",
-       "3       12223       11177       13371       12775       10753       13930\n",
-       "4       11133       11006       13085       11996       10600       13106\n",
-       "5       10885       10552       12470       11736       10362       12099\n",
-       "6       10296       10959       11694       11546       10470       11319\n",
-       "7       10216       11076       11443       10954        9933       11112\n",
-       "8       10162       10600       11353       11093       10360       10695\n",
-       "9       10165       10360       10220       10533       10564       10736\n",
-       "10      10243       10276       12101       10443       10276       10757\n",
-       "11      10344        9901       11870       10044       10284       10290\n",
-       "12       9926        9774       11139        9690        8967        9888\n",
-       "13      10422        9213        9308        9369        9574        9827\n",
-       "14      15467        9484       10064        9297       10857        8482\n",
-       "15      17588        9654       11558        7916       10679        9429\n",
-       "16      21182        8445       10535        8990       10211       10968\n",
-       "17      20873        9381        9692       10181        9784        9937\n",
-       "18      17024       10519        9520        8464        8568        9506\n",
-       "19      11965        8455        8094       10006        9985        8273\n",
-       "20      13801        9614        9474        9673        9342        9668\n",
-       "21      11596        9657        9033        9438        9115        9391\n",
-       "22       9237        7742        7609        7746        7409        7625\n",
-       "23      10009        9514        9343        9182        9289        9509\n",
-       "24       9402        8847        8782        8768        8808        8942\n",
-       "25       8722        8916        8694        9019        8807        8717\n",
-       "26       8427        8947        8613        8788        8679        8593\n",
-       "27       8556        8528        8633        8707        8614        8670\n",
-       "28       8118        8591        8710        8812        8789        8461\n",
-       "29       8273        8527        8579        8562        8790        8228\n",
-       "30       8326        8569        8581        8296        8725        8262\n",
-       "31       8415        8701        8587        8351        8602        8071\n",
-       "32        NaN        8580        8782        8466        8531        8298\n",
-       "33        NaN        8504        8312        8707        8496        8600\n",
-       "34        NaN        8441        8413        8812        8700        8564\n",
-       "35        NaN        7684        7354        7594        7453        8423\n",
-       "36        NaN        9113        8851        8955        8847        7389\n",
-       "37        NaN        8946        8612        8845        8548        8704\n",
-       "38        NaN        8868        8707        8949        8382        8542\n",
-       "39        NaN        8906        8590        9096        8402        8865\n",
-       "40        NaN        9202        8908        9147        8729        8858\n",
-       "41        NaN        9383        9043        9300        9132        9124\n",
-       "42        NaN        9534        9224        9381        9144        8899\n",
-       "43        NaN        9351        8970        9131        9100        9104\n",
-       "44        NaN        9522        8925        9389        9508        9025\n",
-       "45        NaN       10044        9509        9748        9844        9388\n",
-       "46        NaN        9976        9537        9609       10013        9325\n",
-       "47        NaN       10183        9300        9982        9942        9219\n",
-       "48        NaN       10269        9360        9902        9796        9233\n",
-       "49        NaN       10079        9613       10151       10530        9706\n",
-       "50        NaN       10489        9842       10509        9870        9581\n",
-       "51        NaN       11159       10392       11755       10802       10043\n",
-       "52        NaN        7037        6670        7946        7445        8095"
+       "    total_2020  total_2019  total_2018  total_2017  total_2016  total_2015\n",
+       "1         1161      1104.0      1531.0      1205.0      1394.0        1146\n",
+       "2         1567      1507.0      1899.0      1379.0      1305.0        1708\n",
+       "3         1322      1353.0      1629.0      1224.0      1215.0        1489\n",
+       "4         1226      1208.0      1610.0      1197.0      1187.0        1381\n",
+       "5         1188      1206.0      1369.0      1332.0      1205.0        1286\n",
+       "6         1216      1243.0      1265.0      1200.0      1217.0        1344\n",
+       "7         1162      1181.0      1315.0      1231.0      1209.0        1360\n",
+       "8         1162      1245.0      1245.0      1185.0      1239.0        1320\n",
+       "9         1171      1125.0      1022.0      1219.0      1150.0        1308\n",
+       "10        1208      1156.0      1475.0      1146.0      1174.0        1192\n",
+       "11        1156      1108.0      1220.0      1141.0      1175.0        1201\n",
+       "12        1196      1101.0      1158.0      1152.0      1042.0        1149\n",
+       "13        1079      1086.0      1050.0      1112.0      1172.0        1171\n",
+       "14        1744      1032.0      1192.0      1060.0      1166.0        1042\n",
+       "15        1978      1069.0      1192.0       998.0      1048.0        1192\n",
+       "16        1916       902.0      1136.0      1111.0      1092.0        1095\n",
+       "17        1836      1121.0      1008.0      1121.0      1076.0        1108\n",
+       "18        1679      1131.0      1093.0      1050.0      1006.0        1117\n",
+       "19        1435      1018.0       967.0      1119.0      1047.0        1020\n",
+       "20        1421      1115.0       977.0      1115.0      1010.0        1103\n",
+       "21        1226      1061.0      1070.0      1063.0       994.0        1039\n",
+       "22        1125      1029.0       998.0      1015.0       999.0        1043\n",
+       "23        1093      1042.0      1033.0      1076.0      1023.0        1106\n",
+       "24        1034      1028.0       915.0      1031.0       988.0        1038\n",
+       "25        1065      1053.0       993.0      1032.0       994.0        1025\n",
+       "26        1008      1051.0      1046.0       994.0      1007.0        1032\n",
+       "27         983       981.0      1041.0      1040.0       988.0        1040\n",
+       "28         976      1077.0      1002.0      1014.0      1022.0        1011\n",
+       "29        1033       964.0       928.0      1025.0      1041.0        1023\n",
+       "30         961      1041.0       933.0       978.0       979.0         956\n",
+       "31        1043      1020.0       969.0      1011.0       987.0         985\n",
+       "32        1011      1018.0       953.0      1002.0       997.0        1043\n",
+       "33         922      1028.0       978.0      1004.0       982.0         969\n",
+       "34        1046      1011.0       941.0      1045.0      1017.0         982\n",
+       "35        1029      1013.0       930.0       980.0      1039.0         954\n",
+       "36        1050       980.0       970.0      1006.0      1007.0         977\n",
+       "37        1069      1074.0      1020.0       972.0       983.0         991\n",
+       "38         952      1071.0       946.0      1049.0       966.0        1001\n",
+       "39         933      1142.0      1015.0      1056.0      1009.0        1010\n",
+       "40        1195      1051.0      1042.0      1016.0      1072.0        1008\n",
+       "41        1071      1143.0      1081.0      1133.0      1009.0        1028\n",
+       "42        1131      1153.0      1031.0      1067.0      1070.0         989\n",
+       "43        1187      1115.0      1019.0      1095.0      1052.0         981\n",
+       "44        1262      1101.0      1085.0      1062.0      1032.0        1116\n",
+       "45        1250      1184.0      1144.0      1126.0      1043.0        1028\n",
+       "46        1138      1160.0      1084.0      1175.0      1174.0        1103\n",
+       "47        1360      1229.0      1058.0      1178.0      1132.0        1054\n",
+       "48        1328      1163.0      1062.0      1153.0      1159.0        1115\n",
+       "49        1296      1108.0      1076.0      1237.0      1188.0        1089\n",
+       "50        1284      1312.0      1212.0      1335.0      1219.0        1101\n",
+       "51        1297      1277.0      1216.0      1437.0      1284.0        1146\n",
+       "52        1205      1000.0      1058.0      1168.0      1133.0         944"
        ]
       },
        ]
       },
-     "execution_count": 108,
+     "execution_count": 35,
       "metadata": {},
       "output_type": "execute_result"
      }
     ],
     "source": [
       "metadata": {},
       "output_type": "execute_result"
      }
     ],
     "source": [
-    "deaths_headlines_e = deaths_headlines_e.merge(dh19e['total_2019'], how='outer', left_index=True, right_index=True)\n",
-    "deaths_headlines_e = deaths_headlines_e.merge(dh18e['total_2018'], how='outer', left_index=True, right_index=True)\n",
-    "deaths_headlines_e = deaths_headlines_e.merge(dh17e['total_2017'], how='outer', left_index=True, right_index=True)\n",
-    "deaths_headlines_e = deaths_headlines_e.merge(dh16e['total_2016'], how='outer', left_index=True, right_index=True)\n",
-    "# deaths_headlines = deaths_headlines.merge(dh15['total_2015'], how='outer', left_index=True, right_index=True)\n",
-    "deaths_headlines_e = deaths_headlines_e.merge(dh15e['total_2015'], how='left', left_index=True, right_index=True)\n",
-    "deaths_headlines_e"
+    "deaths_headlines_s = raw_data_s[reversed('2015 2016 2017 2018 2019 2020'.split())]\n",
+    "deaths_headlines_s.columns = ['total_' + c for c in deaths_headlines_s.columns]\n",
+    "deaths_headlines_s.reset_index(drop=True, inplace=True)\n",
+    "deaths_headlines_s.index = deaths_headlines_s.index + 1\n",
+    "deaths_headlines_s = deaths_headlines_s.loc[1:52]\n",
+    "deaths_headlines_s"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "source": [
+    "# Correction for missing data"
     ]
    },
    {
     "cell_type": "code",
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 109,
+   "execution_count": 36,
     "metadata": {
     "metadata": {
-    "scrolled": true
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# deaths_headlines_s.loc[20, 'total_2020'] = 1000\n",
+    "# deaths_headlines_s"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {
+    "Collapsed": "false"
     },
     "outputs": [
      {
     },
     "outputs": [
      {
@@ -3914,568 +5286,564 @@
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
-       "      <td>1</td>\n",
-       "      <td>1161.0</td>\n",
-       "      <td>1104.0</td>\n",
-       "      <td>1531.0</td>\n",
-       "      <td>1205.0</td>\n",
-       "      <td>1394.0</td>\n",
-       "      <td>1146</td>\n",
+       "      <th>1</th>\n",
+       "      <td>787</td>\n",
+       "      <td>718.0</td>\n",
+       "      <td>783.0</td>\n",
+       "      <td>744.0</td>\n",
+       "      <td>809.0</td>\n",
+       "      <td>725</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2</td>\n",
-       "      <td>1567.0</td>\n",
-       "      <td>1507.0</td>\n",
-       "      <td>1899.0</td>\n",
-       "      <td>1379.0</td>\n",
-       "      <td>1305.0</td>\n",
-       "      <td>1708</td>\n",
+       "      <th>2</th>\n",
+       "      <td>939</td>\n",
+       "      <td>809.0</td>\n",
+       "      <td>904.0</td>\n",
+       "      <td>825.0</td>\n",
+       "      <td>711.0</td>\n",
+       "      <td>1031</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>3</td>\n",
-       "      <td>1322.0</td>\n",
-       "      <td>1353.0</td>\n",
-       "      <td>1629.0</td>\n",
-       "      <td>1224.0</td>\n",
-       "      <td>1215.0</td>\n",
-       "      <td>1489</td>\n",
+       "      <th>3</th>\n",
+       "      <td>767</td>\n",
+       "      <td>683.0</td>\n",
+       "      <td>885.0</td>\n",
+       "      <td>835.0</td>\n",
+       "      <td>720.0</td>\n",
+       "      <td>936</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>4</td>\n",
-       "      <td>1226.0</td>\n",
-       "      <td>1208.0</td>\n",
-       "      <td>1610.0</td>\n",
-       "      <td>1197.0</td>\n",
-       "      <td>1187.0</td>\n",
-       "      <td>1381</td>\n",
+       "      <th>4</th>\n",
+       "      <td>723</td>\n",
+       "      <td>734.0</td>\n",
+       "      <td>850.0</td>\n",
+       "      <td>881.0</td>\n",
+       "      <td>717.0</td>\n",
+       "      <td>828</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>5</td>\n",
-       "      <td>1188.0</td>\n",
-       "      <td>1206.0</td>\n",
-       "      <td>1369.0</td>\n",
-       "      <td>1332.0</td>\n",
-       "      <td>1205.0</td>\n",
-       "      <td>1286</td>\n",
+       "      <th>5</th>\n",
+       "      <td>727</td>\n",
+       "      <td>745.0</td>\n",
+       "      <td>815.0</td>\n",
+       "      <td>749.0</td>\n",
+       "      <td>690.0</td>\n",
+       "      <td>801</td>\n",
         "    </tr>\n",
         "    </tr>\n",
-       "    <tr>\n",
-       "      <td>6</td>\n",
-       "      <td>1216.0</td>\n",
-       "      <td>1243.0</td>\n",
-       "      <td>1265.0</td>\n",
-       "      <td>1200.0</td>\n",
-       "      <td>1217.0</td>\n",
-       "      <td>1344</td>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>690</td>\n",
+       "      <td>701.0</td>\n",
+       "      <td>801.0</td>\n",
+       "      <td>723.0</td>\n",
+       "      <td>700.0</td>\n",
+       "      <td>720</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>7</td>\n",
-       "      <td>1162.0</td>\n",
-       "      <td>1181.0</td>\n",
-       "      <td>1315.0</td>\n",
-       "      <td>1231.0</td>\n",
-       "      <td>1209.0</td>\n",
-       "      <td>1360</td>\n",
+       "      <th>7</th>\n",
+       "      <td>728</td>\n",
+       "      <td>748.0</td>\n",
+       "      <td>803.0</td>\n",
+       "      <td>690.0</td>\n",
+       "      <td>657.0</td>\n",
+       "      <td>710</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>8</td>\n",
-       "      <td>1162.0</td>\n",
-       "      <td>1245.0</td>\n",
-       "      <td>1245.0</td>\n",
-       "      <td>1185.0</td>\n",
-       "      <td>1239.0</td>\n",
-       "      <td>1320</td>\n",
+       "      <th>8</th>\n",
+       "      <td>679</td>\n",
+       "      <td>695.0</td>\n",
+       "      <td>789.0</td>\n",
+       "      <td>701.0</td>\n",
+       "      <td>696.0</td>\n",
+       "      <td>739</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>9</td>\n",
-       "      <td>1171.0</td>\n",
-       "      <td>1125.0</td>\n",
-       "      <td>1022.0</td>\n",
-       "      <td>1219.0</td>\n",
-       "      <td>1150.0</td>\n",
-       "      <td>1308</td>\n",
+       "      <th>9</th>\n",
+       "      <td>651</td>\n",
+       "      <td>684.0</td>\n",
+       "      <td>634.0</td>\n",
+       "      <td>715.0</td>\n",
+       "      <td>721.0</td>\n",
+       "      <td>736</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>10</td>\n",
-       "      <td>1208.0</td>\n",
-       "      <td>1156.0</td>\n",
-       "      <td>1475.0</td>\n",
-       "      <td>1146.0</td>\n",
-       "      <td>1174.0</td>\n",
-       "      <td>1192</td>\n",
+       "      <th>10</th>\n",
+       "      <td>652</td>\n",
+       "      <td>622.0</td>\n",
+       "      <td>896.0</td>\n",
+       "      <td>634.0</td>\n",
+       "      <td>734.0</td>\n",
+       "      <td>712</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>11</td>\n",
-       "      <td>1156.0</td>\n",
-       "      <td>1108.0</td>\n",
-       "      <td>1220.0</td>\n",
-       "      <td>1141.0</td>\n",
-       "      <td>1175.0</td>\n",
-       "      <td>1201</td>\n",
+       "      <th>11</th>\n",
+       "      <td>675</td>\n",
+       "      <td>666.0</td>\n",
+       "      <td>918.0</td>\n",
+       "      <td>653.0</td>\n",
+       "      <td>738.0</td>\n",
+       "      <td>661</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>12</td>\n",
-       "      <td>1196.0</td>\n",
-       "      <td>1101.0</td>\n",
-       "      <td>1158.0</td>\n",
-       "      <td>1152.0</td>\n",
-       "      <td>1042.0</td>\n",
-       "      <td>1149</td>\n",
+       "      <th>12</th>\n",
+       "      <td>719</td>\n",
+       "      <td>628.0</td>\n",
+       "      <td>774.0</td>\n",
+       "      <td>635.0</td>\n",
+       "      <td>668.0</td>\n",
+       "      <td>680</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>13</td>\n",
-       "      <td>1079.0</td>\n",
-       "      <td>1086.0</td>\n",
-       "      <td>1050.0</td>\n",
-       "      <td>1112.0</td>\n",
-       "      <td>1172.0</td>\n",
-       "      <td>1171</td>\n",
+       "      <th>13</th>\n",
+       "      <td>719</td>\n",
+       "      <td>654.0</td>\n",
+       "      <td>633.0</td>\n",
+       "      <td>658.0</td>\n",
+       "      <td>712.0</td>\n",
+       "      <td>666</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>14</td>\n",
-       "      <td>1744.0</td>\n",
-       "      <td>1032.0</td>\n",
-       "      <td>1192.0</td>\n",
-       "      <td>1060.0</td>\n",
-       "      <td>1166.0</td>\n",
-       "      <td>1042</td>\n",
+       "      <th>14</th>\n",
+       "      <td>920</td>\n",
+       "      <td>642.0</td>\n",
+       "      <td>730.0</td>\n",
+       "      <td>642.0</td>\n",
+       "      <td>742.0</td>\n",
+       "      <td>580</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>15</td>\n",
-       "      <td>1978.0</td>\n",
-       "      <td>1069.0</td>\n",
-       "      <td>1192.0</td>\n",
-       "      <td>998.0</td>\n",
-       "      <td>1048.0</td>\n",
-       "      <td>1192</td>\n",
+       "      <th>15</th>\n",
+       "      <td>928</td>\n",
+       "      <td>637.0</td>\n",
+       "      <td>743.0</td>\n",
+       "      <td>577.0</td>\n",
+       "      <td>738.0</td>\n",
+       "      <td>660</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>16</td>\n",
-       "      <td>1916.0</td>\n",
-       "      <td>902.0</td>\n",
-       "      <td>1136.0</td>\n",
-       "      <td>1111.0</td>\n",
-       "      <td>1092.0</td>\n",
-       "      <td>1095</td>\n",
+       "      <th>16</th>\n",
+       "      <td>1169</td>\n",
+       "      <td>580.0</td>\n",
+       "      <td>688.0</td>\n",
+       "      <td>654.0</td>\n",
+       "      <td>714.0</td>\n",
+       "      <td>671</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>17</td>\n",
-       "      <td>1836.0</td>\n",
-       "      <td>1121.0</td>\n",
-       "      <td>1008.0</td>\n",
-       "      <td>1121.0</td>\n",
-       "      <td>1076.0</td>\n",
-       "      <td>1108</td>\n",
+       "      <th>17</th>\n",
+       "      <td>1124</td>\n",
+       "      <td>678.0</td>\n",
+       "      <td>614.0</td>\n",
+       "      <td>727.0</td>\n",
+       "      <td>629.0</td>\n",
+       "      <td>662</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>18</td>\n",
-       "      <td>1679.0</td>\n",
-       "      <td>1131.0</td>\n",
-       "      <td>1093.0</td>\n",
-       "      <td>1050.0</td>\n",
-       "      <td>1006.0</td>\n",
-       "      <td>1117</td>\n",
+       "      <th>18</th>\n",
+       "      <td>929</td>\n",
+       "      <td>688.0</td>\n",
+       "      <td>633.0</td>\n",
+       "      <td>600.0</td>\n",
+       "      <td>569.0</td>\n",
+       "      <td>628</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>19</td>\n",
-       "      <td>1435.0</td>\n",
-       "      <td>1018.0</td>\n",
-       "      <td>967.0</td>\n",
-       "      <td>1119.0</td>\n",
-       "      <td>1047.0</td>\n",
-       "      <td>1020</td>\n",
+       "      <th>19</th>\n",
+       "      <td>692</td>\n",
+       "      <td>600.0</td>\n",
+       "      <td>530.0</td>\n",
+       "      <td>687.0</td>\n",
+       "      <td>652.0</td>\n",
+       "      <td>589</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>20</td>\n",
-       "      <td>1421.0</td>\n",
-       "      <td>1115.0</td>\n",
-       "      <td>977.0</td>\n",
-       "      <td>1115.0</td>\n",
-       "      <td>1010.0</td>\n",
-       "      <td>1103</td>\n",
+       "      <th>20</th>\n",
+       "      <td>772</td>\n",
+       "      <td>658.0</td>\n",
+       "      <td>667.0</td>\n",
+       "      <td>615.0</td>\n",
+       "      <td>611.0</td>\n",
+       "      <td>622</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>21</td>\n",
-       "      <td>1226.0</td>\n",
-       "      <td>1061.0</td>\n",
-       "      <td>1070.0</td>\n",
-       "      <td>1063.0</td>\n",
-       "      <td>994.0</td>\n",
-       "      <td>1039</td>\n",
+       "      <th>21</th>\n",
+       "      <td>692</td>\n",
+       "      <td>627.0</td>\n",
+       "      <td>603.0</td>\n",
+       "      <td>602.0</td>\n",
+       "      <td>624.0</td>\n",
+       "      <td>614</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>22</td>\n",
-       "      <td>1125.0</td>\n",
-       "      <td>1029.0</td>\n",
-       "      <td>998.0</td>\n",
-       "      <td>1015.0</td>\n",
-       "      <td>999.0</td>\n",
-       "      <td>1043</td>\n",
+       "      <th>22</th>\n",
+       "      <td>587</td>\n",
+       "      <td>518.0</td>\n",
+       "      <td>538.0</td>\n",
+       "      <td>586.0</td>\n",
+       "      <td>500.0</td>\n",
+       "      <td>588</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>23</td>\n",
-       "      <td>1093.0</td>\n",
-       "      <td>1042.0</td>\n",
-       "      <td>1033.0</td>\n",
-       "      <td>1076.0</td>\n",
-       "      <td>1023.0</td>\n",
-       "      <td>1106</td>\n",
+       "      <th>23</th>\n",
+       "      <td>700</td>\n",
+       "      <td>626.0</td>\n",
+       "      <td>607.0</td>\n",
+       "      <td>584.0</td>\n",
+       "      <td>584.0</td>\n",
+       "      <td>648</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>24</td>\n",
-       "      <td>1034.0</td>\n",
-       "      <td>1028.0</td>\n",
-       "      <td>915.0</td>\n",
-       "      <td>1031.0</td>\n",
-       "      <td>988.0</td>\n",
-       "      <td>1038</td>\n",
+       "      <th>24</th>\n",
+       "      <td>574</td>\n",
+       "      <td>598.0</td>\n",
+       "      <td>561.0</td>\n",
+       "      <td>599.0</td>\n",
+       "      <td>578.0</td>\n",
+       "      <td>606</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>25</td>\n",
-       "      <td>1065.0</td>\n",
-       "      <td>1053.0</td>\n",
-       "      <td>993.0</td>\n",
-       "      <td>1032.0</td>\n",
-       "      <td>994.0</td>\n",
-       "      <td>1025</td>\n",
+       "      <th>25</th>\n",
+       "      <td>617</td>\n",
+       "      <td>542.0</td>\n",
+       "      <td>562.0</td>\n",
+       "      <td>608.0</td>\n",
+       "      <td>558.0</td>\n",
+       "      <td>595</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>26</td>\n",
-       "      <td>1008.0</td>\n",
-       "      <td>1051.0</td>\n",
-       "      <td>1046.0</td>\n",
-       "      <td>994.0</td>\n",
-       "      <td>1007.0</td>\n",
-       "      <td>1032</td>\n",
+       "      <th>26</th>\n",
+       "      <td>552</td>\n",
+       "      <td>564.0</td>\n",
+       "      <td>599.0</td>\n",
+       "      <td>546.0</td>\n",
+       "      <td>549.0</td>\n",
+       "      <td>597</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>27</td>\n",
-       "      <td>983.0</td>\n",
-       "      <td>981.0</td>\n",
-       "      <td>1041.0</td>\n",
-       "      <td>1040.0</td>\n",
-       "      <td>988.0</td>\n",
-       "      <td>1040</td>\n",
+       "      <th>27</th>\n",
+       "      <td>584</td>\n",
+       "      <td>534.0</td>\n",
+       "      <td>625.0</td>\n",
+       "      <td>556.0</td>\n",
+       "      <td>524.0</td>\n",
+       "      <td>535</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>28</td>\n",
-       "      <td>976.0</td>\n",
-       "      <td>1077.0</td>\n",
-       "      <td>1002.0</td>\n",
-       "      <td>1014.0</td>\n",
-       "      <td>1022.0</td>\n",
-       "      <td>1011</td>\n",
+       "      <th>28</th>\n",
+       "      <td>572</td>\n",
+       "      <td>588.0</td>\n",
+       "      <td>583.0</td>\n",
+       "      <td>564.0</td>\n",
+       "      <td>599.0</td>\n",
+       "      <td>554</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>29</td>\n",
-       "      <td>1033.0</td>\n",
-       "      <td>964.0</td>\n",
-       "      <td>928.0</td>\n",
-       "      <td>1025.0</td>\n",
-       "      <td>1041.0</td>\n",
-       "      <td>1023</td>\n",
+       "      <th>29</th>\n",
+       "      <td>550</td>\n",
+       "      <td>553.0</td>\n",
+       "      <td>548.0</td>\n",
+       "      <td>551.0</td>\n",
+       "      <td>560.0</td>\n",
+       "      <td>574</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>30</td>\n",
-       "      <td>961.0</td>\n",
-       "      <td>1041.0</td>\n",
-       "      <td>933.0</td>\n",
-       "      <td>978.0</td>\n",
-       "      <td>979.0</td>\n",
-       "      <td>956</td>\n",
+       "      <th>30</th>\n",
+       "      <td>565</td>\n",
+       "      <td>543.0</td>\n",
+       "      <td>560.0</td>\n",
+       "      <td>586.0</td>\n",
+       "      <td>610.0</td>\n",
+       "      <td>529</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>31</td>\n",
-       "      <td>1043.0</td>\n",
-       "      <td>1020.0</td>\n",
-       "      <td>969.0</td>\n",
-       "      <td>1011.0</td>\n",
-       "      <td>987.0</td>\n",
-       "      <td>985</td>\n",
+       "      <th>31</th>\n",
+       "      <td>531</td>\n",
+       "      <td>570.0</td>\n",
+       "      <td>574.0</td>\n",
+       "      <td>590.0</td>\n",
+       "      <td>580.0</td>\n",
+       "      <td>546</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>32</td>\n",
-       "      <td>1002.0</td>\n",
-       "      <td>1018.0</td>\n",
-       "      <td>953.0</td>\n",
-       "      <td>1002.0</td>\n",
-       "      <td>997.0</td>\n",
-       "      <td>1043</td>\n",
+       "      <th>32</th>\n",
+       "      <td>563</td>\n",
+       "      <td>542.0</td>\n",
+       "      <td>537.0</td>\n",
+       "      <td>572.0</td>\n",
+       "      <td>641.0</td>\n",
+       "      <td>564</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>33</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1028.0</td>\n",
-       "      <td>978.0</td>\n",
-       "      <td>1004.0</td>\n",
-       "      <td>982.0</td>\n",
-       "      <td>969</td>\n",
+       "      <th>33</th>\n",
+       "      <td>617</td>\n",
+       "      <td>589.0</td>\n",
+       "      <td>518.0</td>\n",
+       "      <td>592.0</td>\n",
+       "      <td>574.0</td>\n",
+       "      <td>548</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>34</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1011.0</td>\n",
-       "      <td>941.0</td>\n",
-       "      <td>1045.0</td>\n",
-       "      <td>1017.0</td>\n",
-       "      <td>982</td>\n",
+       "      <th>34</th>\n",
+       "      <td>594</td>\n",
+       "      <td>553.0</td>\n",
+       "      <td>565.0</td>\n",
+       "      <td>570.0</td>\n",
+       "      <td>619.0</td>\n",
+       "      <td>557</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>35</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1013.0</td>\n",
-       "      <td>930.0</td>\n",
-       "      <td>980.0</td>\n",
-       "      <td>1039.0</td>\n",
-       "      <td>954</td>\n",
+       "      <th>35</th>\n",
+       "      <td>591</td>\n",
+       "      <td>558.0</td>\n",
+       "      <td>511.0</td>\n",
+       "      <td>555.0</td>\n",
+       "      <td>470.0</td>\n",
+       "      <td>603</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>36</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>980.0</td>\n",
-       "      <td>970.0</td>\n",
-       "      <td>1006.0</td>\n",
-       "      <td>1007.0</td>\n",
-       "      <td>977</td>\n",
+       "      <th>36</th>\n",
+       "      <td>488</td>\n",
+       "      <td>582.0</td>\n",
+       "      <td>594.0</td>\n",
+       "      <td>542.0</td>\n",
+       "      <td>552.0</td>\n",
+       "      <td>489</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>37</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1074.0</td>\n",
-       "      <td>1020.0</td>\n",
-       "      <td>972.0</td>\n",
-       "      <td>983.0</td>\n",
-       "      <td>991</td>\n",
+       "      <th>37</th>\n",
+       "      <td>578</td>\n",
+       "      <td>567.0</td>\n",
+       "      <td>579.0</td>\n",
+       "      <td>609.0</td>\n",
+       "      <td>576.0</td>\n",
+       "      <td>554</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>38</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1071.0</td>\n",
-       "      <td>946.0</td>\n",
-       "      <td>1049.0</td>\n",
-       "      <td>966.0</td>\n",
-       "      <td>1001</td>\n",
+       "      <th>38</th>\n",
+       "      <td>555</td>\n",
+       "      <td>572.0</td>\n",
+       "      <td>598.0</td>\n",
+       "      <td>585.0</td>\n",
+       "      <td>563.0</td>\n",
+       "      <td>555</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>39</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1142.0</td>\n",
-       "      <td>1015.0</td>\n",
-       "      <td>1056.0</td>\n",
-       "      <td>1009.0</td>\n",
-       "      <td>1010</td>\n",
+       "      <th>39</th>\n",
+       "      <td>617</td>\n",
+       "      <td>611.0</td>\n",
+       "      <td>560.0</td>\n",
+       "      <td>593.0</td>\n",
+       "      <td>592.0</td>\n",
+       "      <td>664</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>40</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1051.0</td>\n",
-       "      <td>1042.0</td>\n",
-       "      <td>1016.0</td>\n",
-       "      <td>1072.0</td>\n",
-       "      <td>1008</td>\n",
+       "      <th>40</th>\n",
+       "      <td>671</td>\n",
+       "      <td>597.0</td>\n",
+       "      <td>595.0</td>\n",
+       "      <td>631.0</td>\n",
+       "      <td>562.0</td>\n",
+       "      <td>552</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>41</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1143.0</td>\n",
-       "      <td>1081.0</td>\n",
-       "      <td>1133.0</td>\n",
-       "      <td>1009.0</td>\n",
-       "      <td>1028</td>\n",
+       "      <th>41</th>\n",
+       "      <td>638</td>\n",
+       "      <td>590.0</td>\n",
+       "      <td>606.0</td>\n",
+       "      <td>640.0</td>\n",
+       "      <td>587.0</td>\n",
+       "      <td>652</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>42</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1153.0</td>\n",
-       "      <td>1031.0</td>\n",
-       "      <td>1067.0</td>\n",
-       "      <td>1070.0</td>\n",
-       "      <td>989</td>\n",
+       "      <th>42</th>\n",
+       "      <td>688</td>\n",
+       "      <td>622.0</td>\n",
+       "      <td>640.0</td>\n",
+       "      <td>650.0</td>\n",
+       "      <td>624.0</td>\n",
+       "      <td>612</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>43</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1115.0</td>\n",
-       "      <td>1019.0</td>\n",
-       "      <td>1095.0</td>\n",
-       "      <td>1052.0</td>\n",
-       "      <td>981</td>\n",
+       "      <th>43</th>\n",
+       "      <td>661</td>\n",
+       "      <td>670.0</td>\n",
+       "      <td>633.0</td>\n",
+       "      <td>608.0</td>\n",
+       "      <td>624.0</td>\n",
+       "      <td>607</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>44</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1101.0</td>\n",
-       "      <td>1085.0</td>\n",
-       "      <td>1062.0</td>\n",
-       "      <td>1032.0</td>\n",
-       "      <td>1116</td>\n",
+       "      <th>44</th>\n",
+       "      <td>712</td>\n",
+       "      <td>642.0</td>\n",
+       "      <td>604.0</td>\n",
+       "      <td>595.0</td>\n",
+       "      <td>644.0</td>\n",
+       "      <td>593</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>45</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1184.0</td>\n",
-       "      <td>1144.0</td>\n",
-       "      <td>1126.0</td>\n",
-       "      <td>1043.0</td>\n",
-       "      <td>1028</td>\n",
+       "      <th>45</th>\n",
+       "      <td>832</td>\n",
+       "      <td>653.0</td>\n",
+       "      <td>642.0</td>\n",
+       "      <td>598.0</td>\n",
+       "      <td>626.0</td>\n",
+       "      <td>606</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>46</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1160.0</td>\n",
-       "      <td>1084.0</td>\n",
-       "      <td>1175.0</td>\n",
-       "      <td>1174.0</td>\n",
-       "      <td>1103</td>\n",
+       "      <th>46</th>\n",
+       "      <td>742</td>\n",
+       "      <td>674.0</td>\n",
+       "      <td>656.0</td>\n",
+       "      <td>666.0</td>\n",
+       "      <td>681.0</td>\n",
+       "      <td>613</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>47</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1229.0</td>\n",
-       "      <td>1058.0</td>\n",
-       "      <td>1178.0</td>\n",
-       "      <td>1132.0</td>\n",
-       "      <td>1054</td>\n",
+       "      <th>47</th>\n",
+       "      <td>848</td>\n",
+       "      <td>699.0</td>\n",
+       "      <td>657.0</td>\n",
+       "      <td>639.0</td>\n",
+       "      <td>661.0</td>\n",
+       "      <td>611</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>48</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1163.0</td>\n",
-       "      <td>1062.0</td>\n",
-       "      <td>1153.0</td>\n",
-       "      <td>1159.0</td>\n",
-       "      <td>1115</td>\n",
+       "      <th>48</th>\n",
+       "      <td>797</td>\n",
+       "      <td>689.0</td>\n",
+       "      <td>673.0</td>\n",
+       "      <td>636.0</td>\n",
+       "      <td>643.0</td>\n",
+       "      <td>589</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>49</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1108.0</td>\n",
-       "      <td>1076.0</td>\n",
-       "      <td>1237.0</td>\n",
-       "      <td>1188.0</td>\n",
-       "      <td>1089</td>\n",
+       "      <th>49</th>\n",
+       "      <td>836</td>\n",
+       "      <td>737.0</td>\n",
+       "      <td>674.0</td>\n",
+       "      <td>630.0</td>\n",
+       "      <td>693.0</td>\n",
+       "      <td>659</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>50</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1312.0</td>\n",
-       "      <td>1212.0</td>\n",
-       "      <td>1335.0</td>\n",
-       "      <td>1219.0</td>\n",
-       "      <td>1101</td>\n",
+       "      <th>50</th>\n",
+       "      <td>814</td>\n",
+       "      <td>699.0</td>\n",
+       "      <td>708.0</td>\n",
+       "      <td>708.0</td>\n",
+       "      <td>663.0</td>\n",
+       "      <td>688</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>51</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1277.0</td>\n",
-       "      <td>1216.0</td>\n",
-       "      <td>1437.0</td>\n",
-       "      <td>1284.0</td>\n",
-       "      <td>1146</td>\n",
+       "      <th>51</th>\n",
+       "      <td>882</td>\n",
+       "      <td>767.0</td>\n",
+       "      <td>724.0</td>\n",
+       "      <td>762.0</td>\n",
+       "      <td>691.0</td>\n",
+       "      <td>646</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>825</td>\n",
+       "      <td>496.0</td>\n",
+       "      <td>461.0</td>\n",
+       "      <td>541.0</td>\n",
+       "      <td>558.0</td>\n",
+       "      <td>535</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>52</td>\n",
+       "      <th>53</th>\n",
+       "      <td>727</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>1000.0</td>\n",
-       "      <td>1058.0</td>\n",
-       "      <td>1168.0</td>\n",
-       "      <td>1133.0</td>\n",
-       "      <td>944</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>516</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "</div>"
        ],
        "text/plain": [
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "</div>"
        ],
        "text/plain": [
-       "    total_2020  total_2019  total_2018  total_2017  total_2016  total_2015\n",
-       "1       1161.0      1104.0      1531.0      1205.0      1394.0        1146\n",
-       "2       1567.0      1507.0      1899.0      1379.0      1305.0        1708\n",
-       "3       1322.0      1353.0      1629.0      1224.0      1215.0        1489\n",
-       "4       1226.0      1208.0      1610.0      1197.0      1187.0        1381\n",
-       "5       1188.0      1206.0      1369.0      1332.0      1205.0        1286\n",
-       "6       1216.0      1243.0      1265.0      1200.0      1217.0        1344\n",
-       "7       1162.0      1181.0      1315.0      1231.0      1209.0        1360\n",
-       "8       1162.0      1245.0      1245.0      1185.0      1239.0        1320\n",
-       "9       1171.0      1125.0      1022.0      1219.0      1150.0        1308\n",
-       "10      1208.0      1156.0      1475.0      1146.0      1174.0        1192\n",
-       "11      1156.0      1108.0      1220.0      1141.0      1175.0        1201\n",
-       "12      1196.0      1101.0      1158.0      1152.0      1042.0        1149\n",
-       "13      1079.0      1086.0      1050.0      1112.0      1172.0        1171\n",
-       "14      1744.0      1032.0      1192.0      1060.0      1166.0        1042\n",
-       "15      1978.0      1069.0      1192.0       998.0      1048.0        1192\n",
-       "16      1916.0       902.0      1136.0      1111.0      1092.0        1095\n",
-       "17      1836.0      1121.0      1008.0      1121.0      1076.0        1108\n",
-       "18      1679.0      1131.0      1093.0      1050.0      1006.0        1117\n",
-       "19      1435.0      1018.0       967.0      1119.0      1047.0        1020\n",
-       "20      1421.0      1115.0       977.0      1115.0      1010.0        1103\n",
-       "21      1226.0      1061.0      1070.0      1063.0       994.0        1039\n",
-       "22      1125.0      1029.0       998.0      1015.0       999.0        1043\n",
-       "23      1093.0      1042.0      1033.0      1076.0      1023.0        1106\n",
-       "24      1034.0      1028.0       915.0      1031.0       988.0        1038\n",
-       "25      1065.0      1053.0       993.0      1032.0       994.0        1025\n",
-       "26      1008.0      1051.0      1046.0       994.0      1007.0        1032\n",
-       "27       983.0       981.0      1041.0      1040.0       988.0        1040\n",
-       "28       976.0      1077.0      1002.0      1014.0      1022.0        1011\n",
-       "29      1033.0       964.0       928.0      1025.0      1041.0        1023\n",
-       "30       961.0      1041.0       933.0       978.0       979.0         956\n",
-       "31      1043.0      1020.0       969.0      1011.0       987.0         985\n",
-       "32      1002.0      1018.0       953.0      1002.0       997.0        1043\n",
-       "33         NaN      1028.0       978.0      1004.0       982.0         969\n",
-       "34         NaN      1011.0       941.0      1045.0      1017.0         982\n",
-       "35         NaN      1013.0       930.0       980.0      1039.0         954\n",
-       "36         NaN       980.0       970.0      1006.0      1007.0         977\n",
-       "37         NaN      1074.0      1020.0       972.0       983.0         991\n",
-       "38         NaN      1071.0       946.0      1049.0       966.0        1001\n",
-       "39         NaN      1142.0      1015.0      1056.0      1009.0        1010\n",
-       "40         NaN      1051.0      1042.0      1016.0      1072.0        1008\n",
-       "41         NaN      1143.0      1081.0      1133.0      1009.0        1028\n",
-       "42         NaN      1153.0      1031.0      1067.0      1070.0         989\n",
-       "43         NaN      1115.0      1019.0      1095.0      1052.0         981\n",
-       "44         NaN      1101.0      1085.0      1062.0      1032.0        1116\n",
-       "45         NaN      1184.0      1144.0      1126.0      1043.0        1028\n",
-       "46         NaN      1160.0      1084.0      1175.0      1174.0        1103\n",
-       "47         NaN      1229.0      1058.0      1178.0      1132.0        1054\n",
-       "48         NaN      1163.0      1062.0      1153.0      1159.0        1115\n",
-       "49         NaN      1108.0      1076.0      1237.0      1188.0        1089\n",
-       "50         NaN      1312.0      1212.0      1335.0      1219.0        1101\n",
-       "51         NaN      1277.0      1216.0      1437.0      1284.0        1146\n",
-       "52         NaN      1000.0      1058.0      1168.0      1133.0         944"
+       "   total_2020  total_2019  total_2018  total_2017  total_2016  total_2015\n",
+       "1         787       718.0       783.0       744.0       809.0         725\n",
+       "2         939       809.0       904.0       825.0       711.0        1031\n",
+       "3         767       683.0       885.0       835.0       720.0         936\n",
+       "4         723       734.0       850.0       881.0       717.0         828\n",
+       "5         727       745.0       815.0       749.0       690.0         801\n",
+       "6         690       701.0       801.0       723.0       700.0         720\n",
+       "7         728       748.0       803.0       690.0       657.0         710\n",
+       "8         679       695.0       789.0       701.0       696.0         739\n",
+       "9         651       684.0       634.0       715.0       721.0         736\n",
+       "10        652       622.0       896.0       634.0       734.0         712\n",
+       "11        675       666.0       918.0       653.0       738.0         661\n",
+       "12        719       628.0       774.0       635.0       668.0         680\n",
+       "13        719       654.0       633.0       658.0       712.0         666\n",
+       "14        920       642.0       730.0       642.0       742.0         580\n",
+       "15        928       637.0       743.0       577.0       738.0         660\n",
+       "16       1169       580.0       688.0       654.0       714.0         671\n",
+       "17       1124       678.0       614.0       727.0       629.0         662\n",
+       "18        929       688.0       633.0       600.0       569.0         628\n",
+       "19        692       600.0       530.0       687.0       652.0         589\n",
+       "20        772       658.0       667.0       615.0       611.0         622\n",
+       "21        692       627.0       603.0       602.0       624.0         614\n",
+       "22        587       518.0       538.0       586.0       500.0         588\n",
+       "23        700       626.0       607.0       584.0       584.0         648\n",
+       "24        574       598.0       561.0       599.0       578.0         606\n",
+       "25        617       542.0       562.0       608.0       558.0         595\n",
+       "26        552       564.0       599.0       546.0       549.0         597\n",
+       "27        584       534.0       625.0       556.0       524.0         535\n",
+       "28        572       588.0       583.0       564.0       599.0         554\n",
+       "29        550       553.0       548.0       551.0       560.0         574\n",
+       "30        565       543.0       560.0       586.0       610.0         529\n",
+       "31        531       570.0       574.0       590.0       580.0         546\n",
+       "32        563       542.0       537.0       572.0       641.0         564\n",
+       "33        617       589.0       518.0       592.0       574.0         548\n",
+       "34        594       553.0       565.0       570.0       619.0         557\n",
+       "35        591       558.0       511.0       555.0       470.0         603\n",
+       "36        488       582.0       594.0       542.0       552.0         489\n",
+       "37        578       567.0       579.0       609.0       576.0         554\n",
+       "38        555       572.0       598.0       585.0       563.0         555\n",
+       "39        617       611.0       560.0       593.0       592.0         664\n",
+       "40        671       597.0       595.0       631.0       562.0         552\n",
+       "41        638       590.0       606.0       640.0       587.0         652\n",
+       "42        688       622.0       640.0       650.0       624.0         612\n",
+       "43        661       670.0       633.0       608.0       624.0         607\n",
+       "44        712       642.0       604.0       595.0       644.0         593\n",
+       "45        832       653.0       642.0       598.0       626.0         606\n",
+       "46        742       674.0       656.0       666.0       681.0         613\n",
+       "47        848       699.0       657.0       639.0       661.0         611\n",
+       "48        797       689.0       673.0       636.0       643.0         589\n",
+       "49        836       737.0       674.0       630.0       693.0         659\n",
+       "50        814       699.0       708.0       708.0       663.0         688\n",
+       "51        882       767.0       724.0       762.0       691.0         646\n",
+       "52        825       496.0       461.0       541.0       558.0         535\n",
+       "53        727         NaN         NaN         NaN         NaN         516"
        ]
       },
        ]
       },
-     "execution_count": 109,
+     "execution_count": 37,
       "metadata": {},
       "output_type": "execute_result"
      }
     ],
     "source": [
       "metadata": {},
       "output_type": "execute_result"
      }
     ],
     "source": [
-    "deaths_headlines_s = raw_data_s[reversed('2015 2016 2017 2018 2019 2020'.split())]\n",
-    "deaths_headlines_s.columns = ['total_' + c for c in deaths_headlines_s.columns]\n",
-    "deaths_headlines_s.reset_index(drop=True, inplace=True)\n",
-    "deaths_headlines_s.index = deaths_headlines_s.index + 1\n",
-    "deaths_headlines_s = deaths_headlines_s.loc[1:52]\n",
-    "deaths_headlines_s"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Correction for missing data"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 110,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# deaths_headlines_s.loc[20, 'total_2020'] = 1000\n",
-    "# deaths_headlines_s"
+    "deaths_headlines_w = deaths_headlines_w.merge(dh19w['total_2019'], how='outer', left_index=True, right_index=True)\n",
+    "deaths_headlines_w = deaths_headlines_w.merge(dh18w['total_2018'], how='outer', left_index=True, right_index=True)\n",
+    "deaths_headlines_w = deaths_headlines_w.merge(dh17w['total_2017'], how='outer', left_index=True, right_index=True)\n",
+    "deaths_headlines_w = deaths_headlines_w.merge(dh16w['total_2016'], how='outer', left_index=True, right_index=True)\n",
+    "# deaths_headlines = deaths_headlines.merge(dh15['total_2015'], how='outer', left_index=True, right_index=True)\n",
+    "deaths_headlines_w = deaths_headlines_w.merge(dh15w['total_2015'], how='left', left_index=True, right_index=True)\n",
+    "deaths_headlines_w"
     ]
    },
    {
     "cell_type": "code",
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 111,
-   "metadata": {},
+   "execution_count": 38,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
@@ -4508,552 +5876,563 @@
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
-       "      <td>1</td>\n",
-       "      <td>787</td>\n",
-       "      <td>718</td>\n",
-       "      <td>783</td>\n",
-       "      <td>744</td>\n",
-       "      <td>809</td>\n",
-       "      <td>725</td>\n",
+       "      <th>1</th>\n",
+       "      <td>353</td>\n",
+       "      <td>365.0</td>\n",
+       "      <td>447.0</td>\n",
+       "      <td>416.0</td>\n",
+       "      <td>424.0</td>\n",
+       "      <td>319</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2</td>\n",
-       "      <td>939</td>\n",
-       "      <td>809</td>\n",
-       "      <td>904</td>\n",
-       "      <td>825</td>\n",
-       "      <td>711</td>\n",
-       "      <td>1031</td>\n",
+       "      <th>2</th>\n",
+       "      <td>395</td>\n",
+       "      <td>371.0</td>\n",
+       "      <td>481.0</td>\n",
+       "      <td>434.0</td>\n",
+       "      <td>348.0</td>\n",
+       "      <td>373</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>3</td>\n",
-       "      <td>767</td>\n",
-       "      <td>683</td>\n",
-       "      <td>885</td>\n",
-       "      <td>835</td>\n",
-       "      <td>720</td>\n",
-       "      <td>936</td>\n",
+       "      <th>3</th>\n",
+       "      <td>411</td>\n",
+       "      <td>332.0</td>\n",
+       "      <td>470.0</td>\n",
+       "      <td>397.0</td>\n",
+       "      <td>372.0</td>\n",
+       "      <td>383</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>4</td>\n",
-       "      <td>723</td>\n",
-       "      <td>734</td>\n",
-       "      <td>850</td>\n",
-       "      <td>881</td>\n",
-       "      <td>717</td>\n",
-       "      <td>828</td>\n",
+       "      <th>4</th>\n",
+       "      <td>347</td>\n",
+       "      <td>335.0</td>\n",
+       "      <td>426.0</td>\n",
+       "      <td>387.0</td>\n",
+       "      <td>355.0</td>\n",
+       "      <td>397</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>5</td>\n",
-       "      <td>727</td>\n",
-       "      <td>745</td>\n",
-       "      <td>815</td>\n",
-       "      <td>749</td>\n",
-       "      <td>690</td>\n",
-       "      <td>801</td>\n",
+       "      <th>5</th>\n",
+       "      <td>323</td>\n",
+       "      <td>296.0</td>\n",
+       "      <td>433.0</td>\n",
+       "      <td>371.0</td>\n",
+       "      <td>314.0</td>\n",
+       "      <td>374</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>6</td>\n",
-       "      <td>690</td>\n",
-       "      <td>701</td>\n",
-       "      <td>801</td>\n",
-       "      <td>723</td>\n",
-       "      <td>700</td>\n",
-       "      <td>720</td>\n",
+       "      <th>6</th>\n",
+       "      <td>332</td>\n",
+       "      <td>319.0</td>\n",
+       "      <td>351.0</td>\n",
+       "      <td>336.0</td>\n",
+       "      <td>310.0</td>\n",
+       "      <td>347</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>7</td>\n",
-       "      <td>728</td>\n",
-       "      <td>748</td>\n",
-       "      <td>803</td>\n",
-       "      <td>690</td>\n",
-       "      <td>657</td>\n",
-       "      <td>710</td>\n",
+       "      <th>7</th>\n",
+       "      <td>306</td>\n",
+       "      <td>342.0</td>\n",
+       "      <td>364.0</td>\n",
+       "      <td>337.0</td>\n",
+       "      <td>217.0</td>\n",
+       "      <td>328</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>8</td>\n",
-       "      <td>679</td>\n",
-       "      <td>695</td>\n",
-       "      <td>789</td>\n",
-       "      <td>701</td>\n",
-       "      <td>696</td>\n",
-       "      <td>739</td>\n",
+       "      <th>8</th>\n",
+       "      <td>297</td>\n",
+       "      <td>337.0</td>\n",
+       "      <td>366.0</td>\n",
+       "      <td>351.0</td>\n",
+       "      <td>423.0</td>\n",
+       "      <td>317</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>9</td>\n",
-       "      <td>651</td>\n",
-       "      <td>684</td>\n",
-       "      <td>634</td>\n",
-       "      <td>715</td>\n",
-       "      <td>721</td>\n",
-       "      <td>736</td>\n",
+       "      <th>9</th>\n",
+       "      <td>347</td>\n",
+       "      <td>310.0</td>\n",
+       "      <td>314.0</td>\n",
+       "      <td>352.0</td>\n",
+       "      <td>298.0</td>\n",
+       "      <td>401</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>10</td>\n",
-       "      <td>652</td>\n",
-       "      <td>622</td>\n",
-       "      <td>896</td>\n",
-       "      <td>634</td>\n",
-       "      <td>734</td>\n",
-       "      <td>712</td>\n",
+       "      <th>10</th>\n",
+       "      <td>312</td>\n",
+       "      <td>342.0</td>\n",
+       "      <td>387.0</td>\n",
+       "      <td>357.0</td>\n",
+       "      <td>309.0</td>\n",
+       "      <td>346</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>11</td>\n",
-       "      <td>675</td>\n",
-       "      <td>666</td>\n",
-       "      <td>918</td>\n",
-       "      <td>653</td>\n",
-       "      <td>738</td>\n",
-       "      <td>661</td>\n",
+       "      <th>11</th>\n",
+       "      <td>324</td>\n",
+       "      <td>343.0</td>\n",
+       "      <td>359.0</td>\n",
+       "      <td>251.0</td>\n",
+       "      <td>292.0</td>\n",
+       "      <td>323</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>12</td>\n",
-       "      <td>719</td>\n",
-       "      <td>628</td>\n",
-       "      <td>774</td>\n",
-       "      <td>635</td>\n",
-       "      <td>668</td>\n",
-       "      <td>680</td>\n",
+       "      <th>12</th>\n",
+       "      <td>271</td>\n",
+       "      <td>294.0</td>\n",
+       "      <td>326.0</td>\n",
+       "      <td>356.0</td>\n",
+       "      <td>306.0</td>\n",
+       "      <td>310</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>13</td>\n",
-       "      <td>719</td>\n",
-       "      <td>654</td>\n",
-       "      <td>633</td>\n",
-       "      <td>658</td>\n",
-       "      <td>712</td>\n",
-       "      <td>666</td>\n",
+       "      <th>13</th>\n",
+       "      <td>287</td>\n",
+       "      <td>307.0</td>\n",
+       "      <td>319.0</td>\n",
+       "      <td>314.0</td>\n",
+       "      <td>280.0</td>\n",
+       "      <td>323</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>14</td>\n",
-       "      <td>920</td>\n",
-       "      <td>642</td>\n",
-       "      <td>730</td>\n",
-       "      <td>642</td>\n",
-       "      <td>742</td>\n",
-       "      <td>580</td>\n",
+       "      <th>14</th>\n",
+       "      <td>434</td>\n",
+       "      <td>287.0</td>\n",
+       "      <td>286.0</td>\n",
+       "      <td>306.0</td>\n",
+       "      <td>295.0</td>\n",
+       "      <td>221</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>15</td>\n",
-       "      <td>928</td>\n",
-       "      <td>637</td>\n",
-       "      <td>743</td>\n",
-       "      <td>577</td>\n",
-       "      <td>738</td>\n",
-       "      <td>660</td>\n",
+       "      <th>15</th>\n",
+       "      <td>435</td>\n",
+       "      <td>301.0</td>\n",
+       "      <td>350.0</td>\n",
+       "      <td>270.0</td>\n",
+       "      <td>292.0</td>\n",
+       "      <td>294</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>16</td>\n",
-       "      <td>1169</td>\n",
-       "      <td>580</td>\n",
-       "      <td>688</td>\n",
-       "      <td>654</td>\n",
-       "      <td>714</td>\n",
-       "      <td>671</td>\n",
+       "      <th>16</th>\n",
+       "      <td>424</td>\n",
+       "      <td>316.0</td>\n",
+       "      <td>280.0</td>\n",
+       "      <td>245.0</td>\n",
+       "      <td>293.0</td>\n",
+       "      <td>327</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>17</td>\n",
-       "      <td>1124</td>\n",
-       "      <td>678</td>\n",
-       "      <td>614</td>\n",
-       "      <td>727</td>\n",
-       "      <td>629</td>\n",
-       "      <td>662</td>\n",
+       "      <th>17</th>\n",
+       "      <td>470</td>\n",
+       "      <td>272.0</td>\n",
+       "      <td>282.0</td>\n",
+       "      <td>327.0</td>\n",
+       "      <td>306.0</td>\n",
+       "      <td>316</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>18</td>\n",
-       "      <td>929</td>\n",
-       "      <td>688</td>\n",
-       "      <td>633</td>\n",
-       "      <td>600</td>\n",
-       "      <td>569</td>\n",
-       "      <td>628</td>\n",
+       "      <th>18</th>\n",
+       "      <td>427</td>\n",
+       "      <td>357.0</td>\n",
+       "      <td>292.0</td>\n",
+       "      <td>258.0</td>\n",
+       "      <td>258.0</td>\n",
+       "      <td>335</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>19</td>\n",
-       "      <td>692</td>\n",
-       "      <td>600</td>\n",
-       "      <td>530</td>\n",
-       "      <td>687</td>\n",
-       "      <td>652</td>\n",
-       "      <td>589</td>\n",
+       "      <th>19</th>\n",
+       "      <td>336</td>\n",
+       "      <td>288.0</td>\n",
+       "      <td>230.0</td>\n",
+       "      <td>302.0</td>\n",
+       "      <td>318.0</td>\n",
+       "      <td>256</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>396</td>\n",
+       "      <td>330.0</td>\n",
+       "      <td>268.0</td>\n",
+       "      <td>315.0</td>\n",
+       "      <td>259.0</td>\n",
+       "      <td>299</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>20</td>\n",
-       "      <td>772</td>\n",
-       "      <td>658</td>\n",
-       "      <td>667</td>\n",
-       "      <td>615</td>\n",
-       "      <td>611</td>\n",
-       "      <td>622</td>\n",
+       "      <th>21</th>\n",
+       "      <td>325</td>\n",
+       "      <td>308.0</td>\n",
+       "      <td>268.0</td>\n",
+       "      <td>328.0</td>\n",
+       "      <td>280.0</td>\n",
+       "      <td>290</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>21</td>\n",
-       "      <td>692</td>\n",
-       "      <td>627</td>\n",
-       "      <td>603</td>\n",
-       "      <td>602</td>\n",
-       "      <td>624</td>\n",
-       "      <td>614</td>\n",
+       "      <th>22</th>\n",
+       "      <td>316</td>\n",
+       "      <td>245.0</td>\n",
+       "      <td>252.0</td>\n",
+       "      <td>256.0</td>\n",
+       "      <td>284.0</td>\n",
+       "      <td>258</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>22</td>\n",
-       "      <td>587</td>\n",
-       "      <td>518</td>\n",
-       "      <td>538</td>\n",
-       "      <td>586</td>\n",
-       "      <td>500</td>\n",
-       "      <td>588</td>\n",
+       "      <th>23</th>\n",
+       "      <td>304</td>\n",
+       "      <td>279.0</td>\n",
+       "      <td>276.0</td>\n",
+       "      <td>292.0</td>\n",
+       "      <td>275.0</td>\n",
+       "      <td>340</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>23</td>\n",
-       "      <td>700</td>\n",
-       "      <td>626</td>\n",
-       "      <td>607</td>\n",
-       "      <td>584</td>\n",
-       "      <td>584</td>\n",
-       "      <td>648</td>\n",
+       "      <th>24</th>\n",
+       "      <td>292</td>\n",
+       "      <td>281.0</td>\n",
+       "      <td>277.0</td>\n",
+       "      <td>300.0</td>\n",
+       "      <td>299.0</td>\n",
+       "      <td>272</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>24</td>\n",
-       "      <td>574</td>\n",
-       "      <td>598</td>\n",
-       "      <td>561</td>\n",
-       "      <td>599</td>\n",
-       "      <td>578</td>\n",
-       "      <td>606</td>\n",
+       "      <th>25</th>\n",
+       "      <td>290</td>\n",
+       "      <td>296.0</td>\n",
+       "      <td>265.0</td>\n",
+       "      <td>271.0</td>\n",
+       "      <td>252.0</td>\n",
+       "      <td>292</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>25</td>\n",
-       "      <td>617</td>\n",
-       "      <td>542</td>\n",
-       "      <td>562</td>\n",
-       "      <td>608</td>\n",
-       "      <td>558</td>\n",
-       "      <td>595</td>\n",
+       "      <th>26</th>\n",
+       "      <td>295</td>\n",
+       "      <td>262.0</td>\n",
+       "      <td>271.0</td>\n",
+       "      <td>296.0</td>\n",
+       "      <td>291.0</td>\n",
+       "      <td>303</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>26</td>\n",
-       "      <td>552</td>\n",
-       "      <td>564</td>\n",
-       "      <td>599</td>\n",
-       "      <td>546</td>\n",
-       "      <td>549</td>\n",
-       "      <td>597</td>\n",
+       "      <th>27</th>\n",
+       "      <td>289</td>\n",
+       "      <td>285.0</td>\n",
+       "      <td>266.0</td>\n",
+       "      <td>262.0</td>\n",
+       "      <td>286.0</td>\n",
+       "      <td>300</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>27</td>\n",
-       "      <td>584</td>\n",
-       "      <td>534</td>\n",
-       "      <td>625</td>\n",
-       "      <td>556</td>\n",
-       "      <td>524</td>\n",
-       "      <td>535</td>\n",
+       "      <th>28</th>\n",
+       "      <td>275</td>\n",
+       "      <td>256.0</td>\n",
+       "      <td>172.0</td>\n",
+       "      <td>253.0</td>\n",
+       "      <td>237.0</td>\n",
+       "      <td>252</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>28</td>\n",
-       "      <td>572</td>\n",
-       "      <td>588</td>\n",
-       "      <td>583</td>\n",
-       "      <td>564</td>\n",
-       "      <td>599</td>\n",
-       "      <td>554</td>\n",
+       "      <th>29</th>\n",
+       "      <td>240</td>\n",
+       "      <td>280.0</td>\n",
+       "      <td>298.0</td>\n",
+       "      <td>288.0</td>\n",
+       "      <td>281.0</td>\n",
+       "      <td>203</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>29</td>\n",
-       "      <td>550</td>\n",
-       "      <td>553</td>\n",
-       "      <td>548</td>\n",
-       "      <td>551</td>\n",
-       "      <td>560</td>\n",
-       "      <td>574</td>\n",
+       "      <th>30</th>\n",
+       "      <td>307</td>\n",
+       "      <td>269.0</td>\n",
+       "      <td>282.0</td>\n",
+       "      <td>287.0</td>\n",
+       "      <td>298.0</td>\n",
+       "      <td>274</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>30</td>\n",
-       "      <td>565</td>\n",
-       "      <td>543</td>\n",
-       "      <td>560</td>\n",
-       "      <td>586</td>\n",
-       "      <td>610</td>\n",
-       "      <td>529</td>\n",
+       "      <th>31</th>\n",
+       "      <td>273</td>\n",
+       "      <td>273.0</td>\n",
+       "      <td>278.0</td>\n",
+       "      <td>287.0</td>\n",
+       "      <td>264.0</td>\n",
+       "      <td>291</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>31</td>\n",
-       "      <td>531</td>\n",
-       "      <td>570</td>\n",
-       "      <td>574</td>\n",
-       "      <td>590</td>\n",
-       "      <td>580</td>\n",
-       "      <td>546</td>\n",
+       "      <th>32</th>\n",
+       "      <td>280</td>\n",
+       "      <td>266.0</td>\n",
+       "      <td>270.0</td>\n",
+       "      <td>238.0</td>\n",
+       "      <td>270.0</td>\n",
+       "      <td>248</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>32</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>542</td>\n",
-       "      <td>537</td>\n",
-       "      <td>572</td>\n",
-       "      <td>641</td>\n",
-       "      <td>564</td>\n",
+       "      <th>33</th>\n",
+       "      <td>278</td>\n",
+       "      <td>284.0</td>\n",
+       "      <td>283.0</td>\n",
+       "      <td>266.0</td>\n",
+       "      <td>260.0</td>\n",
+       "      <td>235</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>33</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>589</td>\n",
-       "      <td>518</td>\n",
-       "      <td>592</td>\n",
-       "      <td>574</td>\n",
-       "      <td>548</td>\n",
+       "      <th>34</th>\n",
+       "      <td>313</td>\n",
+       "      <td>274.0</td>\n",
+       "      <td>280.0</td>\n",
+       "      <td>271.0</td>\n",
+       "      <td>301.0</td>\n",
+       "      <td>251</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>34</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>553</td>\n",
-       "      <td>565</td>\n",
-       "      <td>570</td>\n",
-       "      <td>619</td>\n",
-       "      <td>557</td>\n",
+       "      <th>35</th>\n",
+       "      <td>303</td>\n",
+       "      <td>223.0</td>\n",
+       "      <td>251.0</td>\n",
+       "      <td>243.0</td>\n",
+       "      <td>264.0</td>\n",
+       "      <td>259</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>35</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>558</td>\n",
-       "      <td>511</td>\n",
-       "      <td>555</td>\n",
-       "      <td>470</td>\n",
-       "      <td>603</td>\n",
+       "      <th>36</th>\n",
+       "      <td>234</td>\n",
+       "      <td>243.0</td>\n",
+       "      <td>265.0</td>\n",
+       "      <td>278.0</td>\n",
+       "      <td>275.0</td>\n",
+       "      <td>237</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>36</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>582</td>\n",
-       "      <td>594</td>\n",
-       "      <td>542</td>\n",
-       "      <td>552</td>\n",
-       "      <td>489</td>\n",
+       "      <th>37</th>\n",
+       "      <td>296</td>\n",
+       "      <td>305.0</td>\n",
+       "      <td>285.0</td>\n",
+       "      <td>266.0</td>\n",
+       "      <td>294.0</td>\n",
+       "      <td>324</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>37</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>567</td>\n",
-       "      <td>579</td>\n",
-       "      <td>609</td>\n",
-       "      <td>576</td>\n",
-       "      <td>554</td>\n",
+       "      <th>38</th>\n",
+       "      <td>322</td>\n",
+       "      <td>281.0</td>\n",
+       "      <td>247.0</td>\n",
+       "      <td>292.0</td>\n",
+       "      <td>272.0</td>\n",
+       "      <td>283</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>38</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>572</td>\n",
-       "      <td>598</td>\n",
-       "      <td>585</td>\n",
-       "      <td>563</td>\n",
-       "      <td>555</td>\n",
+       "      <th>39</th>\n",
+       "      <td>323</td>\n",
+       "      <td>295.0</td>\n",
+       "      <td>298.0</td>\n",
+       "      <td>282.0</td>\n",
+       "      <td>275.0</td>\n",
+       "      <td>287</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>39</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>611</td>\n",
-       "      <td>560</td>\n",
-       "      <td>593</td>\n",
-       "      <td>592</td>\n",
-       "      <td>664</td>\n",
+       "      <th>40</th>\n",
+       "      <td>328</td>\n",
+       "      <td>263.0</td>\n",
+       "      <td>324.0</td>\n",
+       "      <td>307.0</td>\n",
+       "      <td>308.0</td>\n",
+       "      <td>282</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>40</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>597</td>\n",
-       "      <td>595</td>\n",
-       "      <td>631</td>\n",
-       "      <td>562</td>\n",
-       "      <td>552</td>\n",
+       "      <th>41</th>\n",
+       "      <td>348</td>\n",
+       "      <td>287.0</td>\n",
+       "      <td>318.0</td>\n",
+       "      <td>284.0</td>\n",
+       "      <td>288.0</td>\n",
+       "      <td>304</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>41</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>590</td>\n",
-       "      <td>606</td>\n",
-       "      <td>640</td>\n",
-       "      <td>587</td>\n",
-       "      <td>652</td>\n",
+       "      <th>42</th>\n",
+       "      <td>278</td>\n",
+       "      <td>316.0</td>\n",
+       "      <td>282.0</td>\n",
+       "      <td>291.0</td>\n",
+       "      <td>296.0</td>\n",
+       "      <td>299</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>42</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>622</td>\n",
-       "      <td>640</td>\n",
-       "      <td>650</td>\n",
-       "      <td>624</td>\n",
-       "      <td>612</td>\n",
+       "      <th>43</th>\n",
+       "      <td>391</td>\n",
+       "      <td>279.0</td>\n",
+       "      <td>263.0</td>\n",
+       "      <td>318.0</td>\n",
+       "      <td>272.0</td>\n",
+       "      <td>274</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>43</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>670</td>\n",
-       "      <td>633</td>\n",
-       "      <td>608</td>\n",
-       "      <td>624</td>\n",
-       "      <td>607</td>\n",
+       "      <th>44</th>\n",
+       "      <td>368</td>\n",
+       "      <td>302.0</td>\n",
+       "      <td>252.0</td>\n",
+       "      <td>320.0</td>\n",
+       "      <td>279.0</td>\n",
+       "      <td>292</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>44</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>642</td>\n",
-       "      <td>604</td>\n",
-       "      <td>595</td>\n",
-       "      <td>644</td>\n",
-       "      <td>593</td>\n",
+       "      <th>45</th>\n",
+       "      <td>386</td>\n",
+       "      <td>296.0</td>\n",
+       "      <td>293.0</td>\n",
+       "      <td>295.0</td>\n",
+       "      <td>290.0</td>\n",
+       "      <td>290</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>45</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>653</td>\n",
-       "      <td>642</td>\n",
-       "      <td>598</td>\n",
-       "      <td>626</td>\n",
-       "      <td>606</td>\n",
+       "      <th>46</th>\n",
+       "      <td>406</td>\n",
+       "      <td>336.0</td>\n",
+       "      <td>275.0</td>\n",
+       "      <td>323.0</td>\n",
+       "      <td>341.0</td>\n",
+       "      <td>297</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>46</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>674</td>\n",
-       "      <td>656</td>\n",
-       "      <td>666</td>\n",
-       "      <td>681</td>\n",
-       "      <td>613</td>\n",
+       "      <th>47</th>\n",
+       "      <td>396</td>\n",
+       "      <td>361.0</td>\n",
+       "      <td>274.0</td>\n",
+       "      <td>303.0</td>\n",
+       "      <td>329.0</td>\n",
+       "      <td>294</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>47</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>699</td>\n",
-       "      <td>657</td>\n",
-       "      <td>639</td>\n",
-       "      <td>661</td>\n",
-       "      <td>611</td>\n",
+       "      <th>48</th>\n",
+       "      <td>348</td>\n",
+       "      <td>334.0</td>\n",
+       "      <td>297.0</td>\n",
+       "      <td>355.0</td>\n",
+       "      <td>303.0</td>\n",
+       "      <td>279</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>48</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>689</td>\n",
-       "      <td>673</td>\n",
-       "      <td>636</td>\n",
-       "      <td>643</td>\n",
-       "      <td>589</td>\n",
+       "      <th>49</th>\n",
+       "      <td>387</td>\n",
+       "      <td>351.0</td>\n",
+       "      <td>324.0</td>\n",
+       "      <td>324.0</td>\n",
+       "      <td>322.0</td>\n",
+       "      <td>294</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>49</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>737</td>\n",
-       "      <td>674</td>\n",
-       "      <td>630</td>\n",
-       "      <td>693</td>\n",
-       "      <td>659</td>\n",
+       "      <th>50</th>\n",
+       "      <td>366</td>\n",
+       "      <td>353.0</td>\n",
+       "      <td>316.0</td>\n",
+       "      <td>372.0</td>\n",
+       "      <td>324.0</td>\n",
+       "      <td>343</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>50</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>699</td>\n",
-       "      <td>708</td>\n",
-       "      <td>708</td>\n",
-       "      <td>663</td>\n",
-       "      <td>688</td>\n",
+       "      <th>51</th>\n",
+       "      <td>350</td>\n",
+       "      <td>363.0</td>\n",
+       "      <td>317.0</td>\n",
+       "      <td>354.0</td>\n",
+       "      <td>360.0</td>\n",
+       "      <td>301</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>51</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>767</td>\n",
-       "      <td>724</td>\n",
-       "      <td>762</td>\n",
-       "      <td>691</td>\n",
-       "      <td>646</td>\n",
+       "      <th>52</th>\n",
+       "      <td>310</td>\n",
+       "      <td>194.0</td>\n",
+       "      <td>195.0</td>\n",
+       "      <td>249.0</td>\n",
+       "      <td>199.0</td>\n",
+       "      <td>232</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>52</td>\n",
+       "      <th>53</th>\n",
+       "      <td>333</td>\n",
         "      <td>NaN</td>\n",
         "      <td>NaN</td>\n",
-       "      <td>496</td>\n",
-       "      <td>461</td>\n",
-       "      <td>541</td>\n",
-       "      <td>558</td>\n",
-       "      <td>535</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>232</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "</div>"
        ],
        "text/plain": [
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "</div>"
        ],
        "text/plain": [
-       "   total_2020  total_2019  total_2018  total_2017  total_2016  total_2015\n",
-       "1         787         718         783         744         809         725\n",
-       "2         939         809         904         825         711        1031\n",
-       "3         767         683         885         835         720         936\n",
-       "4         723         734         850         881         717         828\n",
-       "5         727         745         815         749         690         801\n",
-       "6         690         701         801         723         700         720\n",
-       "7         728         748         803         690         657         710\n",
-       "8         679         695         789         701         696         739\n",
-       "9         651         684         634         715         721         736\n",
-       "10        652         622         896         634         734         712\n",
-       "11        675         666         918         653         738         661\n",
-       "12        719         628         774         635         668         680\n",
-       "13        719         654         633         658         712         666\n",
-       "14        920         642         730         642         742         580\n",
-       "15        928         637         743         577         738         660\n",
-       "16       1169         580         688         654         714         671\n",
-       "17       1124         678         614         727         629         662\n",
-       "18        929         688         633         600         569         628\n",
-       "19        692         600         530         687         652         589\n",
-       "20        772         658         667         615         611         622\n",
-       "21        692         627         603         602         624         614\n",
-       "22        587         518         538         586         500         588\n",
-       "23        700         626         607         584         584         648\n",
-       "24        574         598         561         599         578         606\n",
-       "25        617         542         562         608         558         595\n",
-       "26        552         564         599         546         549         597\n",
-       "27        584         534         625         556         524         535\n",
-       "28        572         588         583         564         599         554\n",
-       "29        550         553         548         551         560         574\n",
-       "30        565         543         560         586         610         529\n",
-       "31        531         570         574         590         580         546\n",
-       "32        NaN         542         537         572         641         564\n",
-       "33        NaN         589         518         592         574         548\n",
-       "34        NaN         553         565         570         619         557\n",
-       "35        NaN         558         511         555         470         603\n",
-       "36        NaN         582         594         542         552         489\n",
-       "37        NaN         567         579         609         576         554\n",
-       "38        NaN         572         598         585         563         555\n",
-       "39        NaN         611         560         593         592         664\n",
-       "40        NaN         597         595         631         562         552\n",
-       "41        NaN         590         606         640         587         652\n",
-       "42        NaN         622         640         650         624         612\n",
-       "43        NaN         670         633         608         624         607\n",
-       "44        NaN         642         604         595         644         593\n",
-       "45        NaN         653         642         598         626         606\n",
-       "46        NaN         674         656         666         681         613\n",
-       "47        NaN         699         657         639         661         611\n",
-       "48        NaN         689         673         636         643         589\n",
-       "49        NaN         737         674         630         693         659\n",
-       "50        NaN         699         708         708         663         688\n",
-       "51        NaN         767         724         762         691         646\n",
-       "52        NaN         496         461         541         558         535"
+       "    total_2020  total_2019  total_2018  total_2017  total_2016  total_2015\n",
+       "1          353       365.0       447.0       416.0       424.0         319\n",
+       "2          395       371.0       481.0       434.0       348.0         373\n",
+       "3          411       332.0       470.0       397.0       372.0         383\n",
+       "4          347       335.0       426.0       387.0       355.0         397\n",
+       "5          323       296.0       433.0       371.0       314.0         374\n",
+       "6          332       319.0       351.0       336.0       310.0         347\n",
+       "7          306       342.0       364.0       337.0       217.0         328\n",
+       "8          297       337.0       366.0       351.0       423.0         317\n",
+       "9          347       310.0       314.0       352.0       298.0         401\n",
+       "10         312       342.0       387.0       357.0       309.0         346\n",
+       "11         324       343.0       359.0       251.0       292.0         323\n",
+       "12         271       294.0       326.0       356.0       306.0         310\n",
+       "13         287       307.0       319.0       314.0       280.0         323\n",
+       "14         434       287.0       286.0       306.0       295.0         221\n",
+       "15         435       301.0       350.0       270.0       292.0         294\n",
+       "16         424       316.0       280.0       245.0       293.0         327\n",
+       "17         470       272.0       282.0       327.0       306.0         316\n",
+       "18         427       357.0       292.0       258.0       258.0         335\n",
+       "19         336       288.0       230.0       302.0       318.0         256\n",
+       "20         396       330.0       268.0       315.0       259.0         299\n",
+       "21         325       308.0       268.0       328.0       280.0         290\n",
+       "22         316       245.0       252.0       256.0       284.0         258\n",
+       "23         304       279.0       276.0       292.0       275.0         340\n",
+       "24         292       281.0       277.0       300.0       299.0         272\n",
+       "25         290       296.0       265.0       271.0       252.0         292\n",
+       "26         295       262.0       271.0       296.0       291.0         303\n",
+       "27         289       285.0       266.0       262.0       286.0         300\n",
+       "28         275       256.0       172.0       253.0       237.0         252\n",
+       "29         240       280.0       298.0       288.0       281.0         203\n",
+       "30         307       269.0       282.0       287.0       298.0         274\n",
+       "31         273       273.0       278.0       287.0       264.0         291\n",
+       "32         280       266.0       270.0       238.0       270.0         248\n",
+       "33         278       284.0       283.0       266.0       260.0         235\n",
+       "34         313       274.0       280.0       271.0       301.0         251\n",
+       "35         303       223.0       251.0       243.0       264.0         259\n",
+       "36         234       243.0       265.0       278.0       275.0         237\n",
+       "37         296       305.0       285.0       266.0       294.0         324\n",
+       "38         322       281.0       247.0       292.0       272.0         283\n",
+       "39         323       295.0       298.0       282.0       275.0         287\n",
+       "40         328       263.0       324.0       307.0       308.0         282\n",
+       "41         348       287.0       318.0       284.0       288.0         304\n",
+       "42         278       316.0       282.0       291.0       296.0         299\n",
+       "43         391       279.0       263.0       318.0       272.0         274\n",
+       "44         368       302.0       252.0       320.0       279.0         292\n",
+       "45         386       296.0       293.0       295.0       290.0         290\n",
+       "46         406       336.0       275.0       323.0       341.0         297\n",
+       "47         396       361.0       274.0       303.0       329.0         294\n",
+       "48         348       334.0       297.0       355.0       303.0         279\n",
+       "49         387       351.0       324.0       324.0       322.0         294\n",
+       "50         366       353.0       316.0       372.0       324.0         343\n",
+       "51         350       363.0       317.0       354.0       360.0         301\n",
+       "52         310       194.0       195.0       249.0       199.0         232\n",
+       "53         333         NaN         NaN         NaN         NaN         232"
        ]
       },
        ]
       },
-     "execution_count": 111,
+     "execution_count": 38,
       "metadata": {},
       "output_type": "execute_result"
      }
     ],
     "source": [
       "metadata": {},
       "output_type": "execute_result"
      }
     ],
     "source": [
-    "deaths_headlines_w = deaths_headlines_w.merge(dh19w['total_2019'], how='outer', left_index=True, right_index=True)\n",
-    "deaths_headlines_w = deaths_headlines_w.merge(dh18w['total_2018'], how='outer', left_index=True, right_index=True)\n",
-    "deaths_headlines_w = deaths_headlines_w.merge(dh17w['total_2017'], how='outer', left_index=True, right_index=True)\n",
-    "deaths_headlines_w = deaths_headlines_w.merge(dh16w['total_2016'], how='outer', left_index=True, right_index=True)\n",
-    "# deaths_headlines = deaths_headlines.merge(dh15['total_2015'], how='outer', left_index=True, right_index=True)\n",
-    "deaths_headlines_w = deaths_headlines_w.merge(dh15w['total_2015'], how='left', left_index=True, right_index=True)\n",
-    "deaths_headlines_w"
+    "deaths_headlines_i = deaths_headlines_i.merge(dh19i['total_2019'], how='outer', left_index=True, right_index=True)\n",
+    "deaths_headlines_i = deaths_headlines_i.merge(dh18i['total_2018'], how='outer', left_index=True, right_index=True)\n",
+    "deaths_headlines_i = deaths_headlines_i.merge(dh17i['total_2017'], how='outer', left_index=True, right_index=True)\n",
+    "deaths_headlines_i = deaths_headlines_i.merge(dh16i['total_2016'], how='outer', left_index=True, right_index=True)\n",
+    "deaths_headlines_i = deaths_headlines_i.merge(dh15i['total_2015'], how='left', left_index=True, right_index=True)\n",
+    "deaths_headlines_i"
     ]
    },
    {
     "cell_type": "code",
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 112,
-   "metadata": {},
+   "execution_count": 39,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
@@ -5086,472 +6465,472 @@
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
-       "      <td>1</td>\n",
-       "      <td>353.0</td>\n",
-       "      <td>365</td>\n",
-       "      <td>447</td>\n",
-       "      <td>416</td>\n",
-       "      <td>424</td>\n",
-       "      <td>319</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2</td>\n",
-       "      <td>395.0</td>\n",
-       "      <td>371</td>\n",
-       "      <td>481</td>\n",
-       "      <td>434</td>\n",
-       "      <td>348</td>\n",
-       "      <td>373</td>\n",
+       "      <th>1</th>\n",
+       "      <td>1161</td>\n",
+       "      <td>1104.0</td>\n",
+       "      <td>1531.0</td>\n",
+       "      <td>1205.0</td>\n",
+       "      <td>1394.0</td>\n",
+       "      <td>1146</td>\n",
         "    </tr>\n",
         "    </tr>\n",
-       "    <tr>\n",
-       "      <td>3</td>\n",
-       "      <td>411.0</td>\n",
-       "      <td>332</td>\n",
-       "      <td>470</td>\n",
-       "      <td>397</td>\n",
-       "      <td>372</td>\n",
-       "      <td>383</td>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1567</td>\n",
+       "      <td>1507.0</td>\n",
+       "      <td>1899.0</td>\n",
+       "      <td>1379.0</td>\n",
+       "      <td>1305.0</td>\n",
+       "      <td>1708</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>4</td>\n",
-       "      <td>347.0</td>\n",
-       "      <td>335</td>\n",
-       "      <td>426</td>\n",
-       "      <td>387</td>\n",
-       "      <td>355</td>\n",
-       "      <td>397</td>\n",
+       "      <th>3</th>\n",
+       "      <td>1322</td>\n",
+       "      <td>1353.0</td>\n",
+       "      <td>1629.0</td>\n",
+       "      <td>1224.0</td>\n",
+       "      <td>1215.0</td>\n",
+       "      <td>1489</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>5</td>\n",
-       "      <td>323.0</td>\n",
-       "      <td>296</td>\n",
-       "      <td>433</td>\n",
-       "      <td>371</td>\n",
-       "      <td>314</td>\n",
-       "      <td>374</td>\n",
+       "      <th>4</th>\n",
+       "      <td>1226</td>\n",
+       "      <td>1208.0</td>\n",
+       "      <td>1610.0</td>\n",
+       "      <td>1197.0</td>\n",
+       "      <td>1187.0</td>\n",
+       "      <td>1381</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>6</td>\n",
-       "      <td>332.0</td>\n",
-       "      <td>319</td>\n",
-       "      <td>351</td>\n",
-       "      <td>336</td>\n",
-       "      <td>310</td>\n",
-       "      <td>347</td>\n",
+       "      <th>5</th>\n",
+       "      <td>1188</td>\n",
+       "      <td>1206.0</td>\n",
+       "      <td>1369.0</td>\n",
+       "      <td>1332.0</td>\n",
+       "      <td>1205.0</td>\n",
+       "      <td>1286</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>7</td>\n",
-       "      <td>306.0</td>\n",
-       "      <td>342</td>\n",
-       "      <td>364</td>\n",
-       "      <td>337</td>\n",
-       "      <td>217</td>\n",
-       "      <td>328</td>\n",
+       "      <th>6</th>\n",
+       "      <td>1216</td>\n",
+       "      <td>1243.0</td>\n",
+       "      <td>1265.0</td>\n",
+       "      <td>1200.0</td>\n",
+       "      <td>1217.0</td>\n",
+       "      <td>1344</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>8</td>\n",
-       "      <td>297.0</td>\n",
-       "      <td>337</td>\n",
-       "      <td>366</td>\n",
-       "      <td>351</td>\n",
-       "      <td>423</td>\n",
-       "      <td>317</td>\n",
+       "      <th>7</th>\n",
+       "      <td>1162</td>\n",
+       "      <td>1181.0</td>\n",
+       "      <td>1315.0</td>\n",
+       "      <td>1231.0</td>\n",
+       "      <td>1209.0</td>\n",
+       "      <td>1360</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>9</td>\n",
-       "      <td>347.0</td>\n",
-       "      <td>310</td>\n",
-       "      <td>314</td>\n",
-       "      <td>352</td>\n",
-       "      <td>298</td>\n",
-       "      <td>401</td>\n",
+       "      <th>8</th>\n",
+       "      <td>1162</td>\n",
+       "      <td>1245.0</td>\n",
+       "      <td>1245.0</td>\n",
+       "      <td>1185.0</td>\n",
+       "      <td>1239.0</td>\n",
+       "      <td>1320</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>10</td>\n",
-       "      <td>312.0</td>\n",
-       "      <td>342</td>\n",
-       "      <td>387</td>\n",
-       "      <td>357</td>\n",
-       "      <td>309</td>\n",
-       "      <td>346</td>\n",
+       "      <th>9</th>\n",
+       "      <td>1171</td>\n",
+       "      <td>1125.0</td>\n",
+       "      <td>1022.0</td>\n",
+       "      <td>1219.0</td>\n",
+       "      <td>1150.0</td>\n",
+       "      <td>1308</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>11</td>\n",
-       "      <td>324.0</td>\n",
-       "      <td>343</td>\n",
-       "      <td>359</td>\n",
-       "      <td>251</td>\n",
-       "      <td>292</td>\n",
-       "      <td>323</td>\n",
+       "      <th>10</th>\n",
+       "      <td>1208</td>\n",
+       "      <td>1156.0</td>\n",
+       "      <td>1475.0</td>\n",
+       "      <td>1146.0</td>\n",
+       "      <td>1174.0</td>\n",
+       "      <td>1192</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>12</td>\n",
-       "      <td>271.0</td>\n",
-       "      <td>294</td>\n",
-       "      <td>326</td>\n",
-       "      <td>356</td>\n",
-       "      <td>306</td>\n",
-       "      <td>310</td>\n",
+       "      <th>11</th>\n",
+       "      <td>1156</td>\n",
+       "      <td>1108.0</td>\n",
+       "      <td>1220.0</td>\n",
+       "      <td>1141.0</td>\n",
+       "      <td>1175.0</td>\n",
+       "      <td>1201</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>13</td>\n",
-       "      <td>287.0</td>\n",
-       "      <td>307</td>\n",
-       "      <td>319</td>\n",
-       "      <td>314</td>\n",
-       "      <td>280</td>\n",
-       "      <td>323</td>\n",
+       "      <th>12</th>\n",
+       "      <td>1196</td>\n",
+       "      <td>1101.0</td>\n",
+       "      <td>1158.0</td>\n",
+       "      <td>1152.0</td>\n",
+       "      <td>1042.0</td>\n",
+       "      <td>1149</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>14</td>\n",
-       "      <td>434.0</td>\n",
-       "      <td>287</td>\n",
-       "      <td>286</td>\n",
-       "      <td>306</td>\n",
-       "      <td>295</td>\n",
-       "      <td>221</td>\n",
+       "      <th>13</th>\n",
+       "      <td>1079</td>\n",
+       "      <td>1086.0</td>\n",
+       "      <td>1050.0</td>\n",
+       "      <td>1112.0</td>\n",
+       "      <td>1172.0</td>\n",
+       "      <td>1171</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>15</td>\n",
-       "      <td>435.0</td>\n",
-       "      <td>301</td>\n",
-       "      <td>350</td>\n",
-       "      <td>270</td>\n",
-       "      <td>292</td>\n",
-       "      <td>294</td>\n",
+       "      <th>14</th>\n",
+       "      <td>1744</td>\n",
+       "      <td>1032.0</td>\n",
+       "      <td>1192.0</td>\n",
+       "      <td>1060.0</td>\n",
+       "      <td>1166.0</td>\n",
+       "      <td>1042</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>16</td>\n",
-       "      <td>424.0</td>\n",
-       "      <td>316</td>\n",
-       "      <td>280</td>\n",
-       "      <td>245</td>\n",
-       "      <td>293</td>\n",
-       "      <td>327</td>\n",
+       "      <th>15</th>\n",
+       "      <td>1978</td>\n",
+       "      <td>1069.0</td>\n",
+       "      <td>1192.0</td>\n",
+       "      <td>998.0</td>\n",
+       "      <td>1048.0</td>\n",
+       "      <td>1192</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>17</td>\n",
-       "      <td>470.0</td>\n",
-       "      <td>272</td>\n",
-       "      <td>282</td>\n",
-       "      <td>327</td>\n",
-       "      <td>306</td>\n",
-       "      <td>316</td>\n",
+       "      <th>16</th>\n",
+       "      <td>1916</td>\n",
+       "      <td>902.0</td>\n",
+       "      <td>1136.0</td>\n",
+       "      <td>1111.0</td>\n",
+       "      <td>1092.0</td>\n",
+       "      <td>1095</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>18</td>\n",
-       "      <td>427.0</td>\n",
-       "      <td>357</td>\n",
-       "      <td>292</td>\n",
-       "      <td>258</td>\n",
-       "      <td>258</td>\n",
-       "      <td>335</td>\n",
+       "      <th>17</th>\n",
+       "      <td>1836</td>\n",
+       "      <td>1121.0</td>\n",
+       "      <td>1008.0</td>\n",
+       "      <td>1121.0</td>\n",
+       "      <td>1076.0</td>\n",
+       "      <td>1108</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>19</td>\n",
-       "      <td>336.0</td>\n",
-       "      <td>288</td>\n",
-       "      <td>230</td>\n",
-       "      <td>302</td>\n",
-       "      <td>318</td>\n",
-       "      <td>256</td>\n",
+       "      <th>18</th>\n",
+       "      <td>1679</td>\n",
+       "      <td>1131.0</td>\n",
+       "      <td>1093.0</td>\n",
+       "      <td>1050.0</td>\n",
+       "      <td>1006.0</td>\n",
+       "      <td>1117</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>20</td>\n",
-       "      <td>396.0</td>\n",
-       "      <td>330</td>\n",
-       "      <td>268</td>\n",
-       "      <td>315</td>\n",
-       "      <td>259</td>\n",
-       "      <td>299</td>\n",
+       "      <th>19</th>\n",
+       "      <td>1435</td>\n",
+       "      <td>1018.0</td>\n",
+       "      <td>967.0</td>\n",
+       "      <td>1119.0</td>\n",
+       "      <td>1047.0</td>\n",
+       "      <td>1020</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>21</td>\n",
-       "      <td>325.0</td>\n",
-       "      <td>308</td>\n",
-       "      <td>268</td>\n",
-       "      <td>328</td>\n",
-       "      <td>280</td>\n",
-       "      <td>290</td>\n",
+       "      <th>20</th>\n",
+       "      <td>1421</td>\n",
+       "      <td>1115.0</td>\n",
+       "      <td>977.0</td>\n",
+       "      <td>1115.0</td>\n",
+       "      <td>1010.0</td>\n",
+       "      <td>1103</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>22</td>\n",
-       "      <td>316.0</td>\n",
-       "      <td>245</td>\n",
-       "      <td>252</td>\n",
-       "      <td>256</td>\n",
-       "      <td>284</td>\n",
-       "      <td>258</td>\n",
+       "      <th>21</th>\n",
+       "      <td>1226</td>\n",
+       "      <td>1061.0</td>\n",
+       "      <td>1070.0</td>\n",
+       "      <td>1063.0</td>\n",
+       "      <td>994.0</td>\n",
+       "      <td>1039</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>23</td>\n",
-       "      <td>304.0</td>\n",
-       "      <td>279</td>\n",
-       "      <td>276</td>\n",
-       "      <td>292</td>\n",
-       "      <td>275</td>\n",
-       "      <td>340</td>\n",
+       "      <th>22</th>\n",
+       "      <td>1125</td>\n",
+       "      <td>1029.0</td>\n",
+       "      <td>998.0</td>\n",
+       "      <td>1015.0</td>\n",
+       "      <td>999.0</td>\n",
+       "      <td>1043</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>24</td>\n",
-       "      <td>292.0</td>\n",
-       "      <td>281</td>\n",
-       "      <td>277</td>\n",
-       "      <td>300</td>\n",
-       "      <td>299</td>\n",
-       "      <td>272</td>\n",
+       "      <th>23</th>\n",
+       "      <td>1093</td>\n",
+       "      <td>1042.0</td>\n",
+       "      <td>1033.0</td>\n",
+       "      <td>1076.0</td>\n",
+       "      <td>1023.0</td>\n",
+       "      <td>1106</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>25</td>\n",
-       "      <td>290.0</td>\n",
-       "      <td>296</td>\n",
-       "      <td>265</td>\n",
-       "      <td>271</td>\n",
-       "      <td>252</td>\n",
-       "      <td>292</td>\n",
+       "      <th>24</th>\n",
+       "      <td>1034</td>\n",
+       "      <td>1028.0</td>\n",
+       "      <td>915.0</td>\n",
+       "      <td>1031.0</td>\n",
+       "      <td>988.0</td>\n",
+       "      <td>1038</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>26</td>\n",
-       "      <td>295.0</td>\n",
-       "      <td>262</td>\n",
-       "      <td>271</td>\n",
-       "      <td>296</td>\n",
-       "      <td>291</td>\n",
-       "      <td>303</td>\n",
+       "      <th>25</th>\n",
+       "      <td>1065</td>\n",
+       "      <td>1053.0</td>\n",
+       "      <td>993.0</td>\n",
+       "      <td>1032.0</td>\n",
+       "      <td>994.0</td>\n",
+       "      <td>1025</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>27</td>\n",
-       "      <td>289.0</td>\n",
-       "      <td>285</td>\n",
-       "      <td>266</td>\n",
-       "      <td>262</td>\n",
-       "      <td>286</td>\n",
-       "      <td>300</td>\n",
+       "      <th>26</th>\n",
+       "      <td>1008</td>\n",
+       "      <td>1051.0</td>\n",
+       "      <td>1046.0</td>\n",
+       "      <td>994.0</td>\n",
+       "      <td>1007.0</td>\n",
+       "      <td>1032</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>28</td>\n",
-       "      <td>275.0</td>\n",
-       "      <td>256</td>\n",
-       "      <td>172</td>\n",
-       "      <td>253</td>\n",
-       "      <td>237</td>\n",
-       "      <td>252</td>\n",
+       "      <th>27</th>\n",
+       "      <td>983</td>\n",
+       "      <td>981.0</td>\n",
+       "      <td>1041.0</td>\n",
+       "      <td>1040.0</td>\n",
+       "      <td>988.0</td>\n",
+       "      <td>1040</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>29</td>\n",
-       "      <td>240.0</td>\n",
-       "      <td>280</td>\n",
-       "      <td>298</td>\n",
-       "      <td>288</td>\n",
-       "      <td>281</td>\n",
-       "      <td>203</td>\n",
+       "      <th>28</th>\n",
+       "      <td>976</td>\n",
+       "      <td>1077.0</td>\n",
+       "      <td>1002.0</td>\n",
+       "      <td>1014.0</td>\n",
+       "      <td>1022.0</td>\n",
+       "      <td>1011</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>30</td>\n",
-       "      <td>307.0</td>\n",
-       "      <td>269</td>\n",
-       "      <td>282</td>\n",
-       "      <td>287</td>\n",
-       "      <td>298</td>\n",
-       "      <td>274</td>\n",
+       "      <th>29</th>\n",
+       "      <td>1033</td>\n",
+       "      <td>964.0</td>\n",
+       "      <td>928.0</td>\n",
+       "      <td>1025.0</td>\n",
+       "      <td>1041.0</td>\n",
+       "      <td>1023</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>31</td>\n",
-       "      <td>273.0</td>\n",
-       "      <td>273</td>\n",
-       "      <td>278</td>\n",
-       "      <td>287</td>\n",
-       "      <td>264</td>\n",
-       "      <td>291</td>\n",
+       "      <th>30</th>\n",
+       "      <td>961</td>\n",
+       "      <td>1041.0</td>\n",
+       "      <td>933.0</td>\n",
+       "      <td>978.0</td>\n",
+       "      <td>979.0</td>\n",
+       "      <td>956</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>32</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>266</td>\n",
-       "      <td>270</td>\n",
-       "      <td>238</td>\n",
-       "      <td>270</td>\n",
-       "      <td>248</td>\n",
+       "      <th>31</th>\n",
+       "      <td>1043</td>\n",
+       "      <td>1020.0</td>\n",
+       "      <td>969.0</td>\n",
+       "      <td>1011.0</td>\n",
+       "      <td>987.0</td>\n",
+       "      <td>985</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>33</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>284</td>\n",
-       "      <td>283</td>\n",
-       "      <td>266</td>\n",
-       "      <td>260</td>\n",
-       "      <td>235</td>\n",
+       "      <th>32</th>\n",
+       "      <td>1011</td>\n",
+       "      <td>1018.0</td>\n",
+       "      <td>953.0</td>\n",
+       "      <td>1002.0</td>\n",
+       "      <td>997.0</td>\n",
+       "      <td>1043</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>34</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>274</td>\n",
-       "      <td>280</td>\n",
-       "      <td>271</td>\n",
-       "      <td>301</td>\n",
-       "      <td>251</td>\n",
+       "      <th>33</th>\n",
+       "      <td>922</td>\n",
+       "      <td>1028.0</td>\n",
+       "      <td>978.0</td>\n",
+       "      <td>1004.0</td>\n",
+       "      <td>982.0</td>\n",
+       "      <td>969</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>35</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>223</td>\n",
-       "      <td>251</td>\n",
-       "      <td>243</td>\n",
-       "      <td>264</td>\n",
-       "      <td>259</td>\n",
+       "      <th>34</th>\n",
+       "      <td>1046</td>\n",
+       "      <td>1011.0</td>\n",
+       "      <td>941.0</td>\n",
+       "      <td>1045.0</td>\n",
+       "      <td>1017.0</td>\n",
+       "      <td>982</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>36</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>243</td>\n",
-       "      <td>265</td>\n",
-       "      <td>278</td>\n",
-       "      <td>275</td>\n",
-       "      <td>237</td>\n",
+       "      <th>35</th>\n",
+       "      <td>1029</td>\n",
+       "      <td>1013.0</td>\n",
+       "      <td>930.0</td>\n",
+       "      <td>980.0</td>\n",
+       "      <td>1039.0</td>\n",
+       "      <td>954</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>37</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>305</td>\n",
-       "      <td>285</td>\n",
-       "      <td>266</td>\n",
-       "      <td>294</td>\n",
-       "      <td>324</td>\n",
+       "      <th>36</th>\n",
+       "      <td>1050</td>\n",
+       "      <td>980.0</td>\n",
+       "      <td>970.0</td>\n",
+       "      <td>1006.0</td>\n",
+       "      <td>1007.0</td>\n",
+       "      <td>977</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>38</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>281</td>\n",
-       "      <td>247</td>\n",
-       "      <td>292</td>\n",
-       "      <td>272</td>\n",
-       "      <td>283</td>\n",
+       "      <th>37</th>\n",
+       "      <td>1069</td>\n",
+       "      <td>1074.0</td>\n",
+       "      <td>1020.0</td>\n",
+       "      <td>972.0</td>\n",
+       "      <td>983.0</td>\n",
+       "      <td>991</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>39</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>295</td>\n",
-       "      <td>298</td>\n",
-       "      <td>282</td>\n",
-       "      <td>275</td>\n",
-       "      <td>287</td>\n",
+       "      <th>38</th>\n",
+       "      <td>952</td>\n",
+       "      <td>1071.0</td>\n",
+       "      <td>946.0</td>\n",
+       "      <td>1049.0</td>\n",
+       "      <td>966.0</td>\n",
+       "      <td>1001</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>40</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>263</td>\n",
-       "      <td>324</td>\n",
-       "      <td>307</td>\n",
-       "      <td>308</td>\n",
-       "      <td>282</td>\n",
+       "      <th>39</th>\n",
+       "      <td>933</td>\n",
+       "      <td>1142.0</td>\n",
+       "      <td>1015.0</td>\n",
+       "      <td>1056.0</td>\n",
+       "      <td>1009.0</td>\n",
+       "      <td>1010</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>41</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>287</td>\n",
-       "      <td>318</td>\n",
-       "      <td>284</td>\n",
-       "      <td>288</td>\n",
-       "      <td>304</td>\n",
+       "      <th>40</th>\n",
+       "      <td>1195</td>\n",
+       "      <td>1051.0</td>\n",
+       "      <td>1042.0</td>\n",
+       "      <td>1016.0</td>\n",
+       "      <td>1072.0</td>\n",
+       "      <td>1008</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>42</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>316</td>\n",
-       "      <td>282</td>\n",
-       "      <td>291</td>\n",
-       "      <td>296</td>\n",
-       "      <td>299</td>\n",
+       "      <th>41</th>\n",
+       "      <td>1071</td>\n",
+       "      <td>1143.0</td>\n",
+       "      <td>1081.0</td>\n",
+       "      <td>1133.0</td>\n",
+       "      <td>1009.0</td>\n",
+       "      <td>1028</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>43</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>279</td>\n",
-       "      <td>263</td>\n",
-       "      <td>318</td>\n",
-       "      <td>272</td>\n",
-       "      <td>274</td>\n",
+       "      <th>42</th>\n",
+       "      <td>1131</td>\n",
+       "      <td>1153.0</td>\n",
+       "      <td>1031.0</td>\n",
+       "      <td>1067.0</td>\n",
+       "      <td>1070.0</td>\n",
+       "      <td>989</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>44</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>302</td>\n",
-       "      <td>252</td>\n",
-       "      <td>320</td>\n",
-       "      <td>279</td>\n",
-       "      <td>292</td>\n",
+       "      <th>43</th>\n",
+       "      <td>1187</td>\n",
+       "      <td>1115.0</td>\n",
+       "      <td>1019.0</td>\n",
+       "      <td>1095.0</td>\n",
+       "      <td>1052.0</td>\n",
+       "      <td>981</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>45</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>296</td>\n",
-       "      <td>293</td>\n",
-       "      <td>295</td>\n",
-       "      <td>290</td>\n",
-       "      <td>290</td>\n",
+       "      <th>44</th>\n",
+       "      <td>1262</td>\n",
+       "      <td>1101.0</td>\n",
+       "      <td>1085.0</td>\n",
+       "      <td>1062.0</td>\n",
+       "      <td>1032.0</td>\n",
+       "      <td>1116</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>46</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>336</td>\n",
-       "      <td>275</td>\n",
-       "      <td>323</td>\n",
-       "      <td>341</td>\n",
-       "      <td>297</td>\n",
+       "      <th>45</th>\n",
+       "      <td>1250</td>\n",
+       "      <td>1184.0</td>\n",
+       "      <td>1144.0</td>\n",
+       "      <td>1126.0</td>\n",
+       "      <td>1043.0</td>\n",
+       "      <td>1028</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>47</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>361</td>\n",
-       "      <td>274</td>\n",
-       "      <td>303</td>\n",
-       "      <td>329</td>\n",
-       "      <td>294</td>\n",
+       "      <th>46</th>\n",
+       "      <td>1138</td>\n",
+       "      <td>1160.0</td>\n",
+       "      <td>1084.0</td>\n",
+       "      <td>1175.0</td>\n",
+       "      <td>1174.0</td>\n",
+       "      <td>1103</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>48</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>334</td>\n",
-       "      <td>297</td>\n",
-       "      <td>355</td>\n",
-       "      <td>303</td>\n",
-       "      <td>279</td>\n",
+       "      <th>47</th>\n",
+       "      <td>1360</td>\n",
+       "      <td>1229.0</td>\n",
+       "      <td>1058.0</td>\n",
+       "      <td>1178.0</td>\n",
+       "      <td>1132.0</td>\n",
+       "      <td>1054</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>49</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>351</td>\n",
-       "      <td>324</td>\n",
-       "      <td>324</td>\n",
-       "      <td>322</td>\n",
-       "      <td>294</td>\n",
+       "      <th>48</th>\n",
+       "      <td>1328</td>\n",
+       "      <td>1163.0</td>\n",
+       "      <td>1062.0</td>\n",
+       "      <td>1153.0</td>\n",
+       "      <td>1159.0</td>\n",
+       "      <td>1115</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>50</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>353</td>\n",
-       "      <td>316</td>\n",
-       "      <td>372</td>\n",
-       "      <td>324</td>\n",
-       "      <td>343</td>\n",
+       "      <th>49</th>\n",
+       "      <td>1296</td>\n",
+       "      <td>1108.0</td>\n",
+       "      <td>1076.0</td>\n",
+       "      <td>1237.0</td>\n",
+       "      <td>1188.0</td>\n",
+       "      <td>1089</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>51</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>363</td>\n",
-       "      <td>317</td>\n",
-       "      <td>354</td>\n",
-       "      <td>360</td>\n",
-       "      <td>301</td>\n",
+       "      <th>50</th>\n",
+       "      <td>1284</td>\n",
+       "      <td>1312.0</td>\n",
+       "      <td>1212.0</td>\n",
+       "      <td>1335.0</td>\n",
+       "      <td>1219.0</td>\n",
+       "      <td>1101</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>52</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>194</td>\n",
-       "      <td>195</td>\n",
-       "      <td>249</td>\n",
-       "      <td>199</td>\n",
-       "      <td>232</td>\n",
+       "      <th>51</th>\n",
+       "      <td>1297</td>\n",
+       "      <td>1277.0</td>\n",
+       "      <td>1216.0</td>\n",
+       "      <td>1437.0</td>\n",
+       "      <td>1284.0</td>\n",
+       "      <td>1146</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>1205</td>\n",
+       "      <td>1000.0</td>\n",
+       "      <td>1058.0</td>\n",
+       "      <td>1168.0</td>\n",
+       "      <td>1133.0</td>\n",
+       "      <td>944</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
@@ -5559,78 +6938,75 @@
        ],
        "text/plain": [
         "    total_2020  total_2019  total_2018  total_2017  total_2016  total_2015\n",
        ],
        "text/plain": [
         "    total_2020  total_2019  total_2018  total_2017  total_2016  total_2015\n",
-       "1        353.0         365         447         416         424         319\n",
-       "2        395.0         371         481         434         348         373\n",
-       "3        411.0         332         470         397         372         383\n",
-       "4        347.0         335         426         387         355         397\n",
-       "5        323.0         296         433         371         314         374\n",
-       "6        332.0         319         351         336         310         347\n",
-       "7        306.0         342         364         337         217         328\n",
-       "8        297.0         337         366         351         423         317\n",
-       "9        347.0         310         314         352         298         401\n",
-       "10       312.0         342         387         357         309         346\n",
-       "11       324.0         343         359         251         292         323\n",
-       "12       271.0         294         326         356         306         310\n",
-       "13       287.0         307         319         314         280         323\n",
-       "14       434.0         287         286         306         295         221\n",
-       "15       435.0         301         350         270         292         294\n",
-       "16       424.0         316         280         245         293         327\n",
-       "17       470.0         272         282         327         306         316\n",
-       "18       427.0         357         292         258         258         335\n",
-       "19       336.0         288         230         302         318         256\n",
-       "20       396.0         330         268         315         259         299\n",
-       "21       325.0         308         268         328         280         290\n",
-       "22       316.0         245         252         256         284         258\n",
-       "23       304.0         279         276         292         275         340\n",
-       "24       292.0         281         277         300         299         272\n",
-       "25       290.0         296         265         271         252         292\n",
-       "26       295.0         262         271         296         291         303\n",
-       "27       289.0         285         266         262         286         300\n",
-       "28       275.0         256         172         253         237         252\n",
-       "29       240.0         280         298         288         281         203\n",
-       "30       307.0         269         282         287         298         274\n",
-       "31       273.0         273         278         287         264         291\n",
-       "32         NaN         266         270         238         270         248\n",
-       "33         NaN         284         283         266         260         235\n",
-       "34         NaN         274         280         271         301         251\n",
-       "35         NaN         223         251         243         264         259\n",
-       "36         NaN         243         265         278         275         237\n",
-       "37         NaN         305         285         266         294         324\n",
-       "38         NaN         281         247         292         272         283\n",
-       "39         NaN         295         298         282         275         287\n",
-       "40         NaN         263         324         307         308         282\n",
-       "41         NaN         287         318         284         288         304\n",
-       "42         NaN         316         282         291         296         299\n",
-       "43         NaN         279         263         318         272         274\n",
-       "44         NaN         302         252         320         279         292\n",
-       "45         NaN         296         293         295         290         290\n",
-       "46         NaN         336         275         323         341         297\n",
-       "47         NaN         361         274         303         329         294\n",
-       "48         NaN         334         297         355         303         279\n",
-       "49         NaN         351         324         324         322         294\n",
-       "50         NaN         353         316         372         324         343\n",
-       "51         NaN         363         317         354         360         301\n",
-       "52         NaN         194         195         249         199         232"
+       "1         1161      1104.0      1531.0      1205.0      1394.0        1146\n",
+       "2         1567      1507.0      1899.0      1379.0      1305.0        1708\n",
+       "3         1322      1353.0      1629.0      1224.0      1215.0        1489\n",
+       "4         1226      1208.0      1610.0      1197.0      1187.0        1381\n",
+       "5         1188      1206.0      1369.0      1332.0      1205.0        1286\n",
+       "6         1216      1243.0      1265.0      1200.0      1217.0        1344\n",
+       "7         1162      1181.0      1315.0      1231.0      1209.0        1360\n",
+       "8         1162      1245.0      1245.0      1185.0      1239.0        1320\n",
+       "9         1171      1125.0      1022.0      1219.0      1150.0        1308\n",
+       "10        1208      1156.0      1475.0      1146.0      1174.0        1192\n",
+       "11        1156      1108.0      1220.0      1141.0      1175.0        1201\n",
+       "12        1196      1101.0      1158.0      1152.0      1042.0        1149\n",
+       "13        1079      1086.0      1050.0      1112.0      1172.0        1171\n",
+       "14        1744      1032.0      1192.0      1060.0      1166.0        1042\n",
+       "15        1978      1069.0      1192.0       998.0      1048.0        1192\n",
+       "16        1916       902.0      1136.0      1111.0      1092.0        1095\n",
+       "17        1836      1121.0      1008.0      1121.0      1076.0        1108\n",
+       "18        1679      1131.0      1093.0      1050.0      1006.0        1117\n",
+       "19        1435      1018.0       967.0      1119.0      1047.0        1020\n",
+       "20        1421      1115.0       977.0      1115.0      1010.0        1103\n",
+       "21        1226      1061.0      1070.0      1063.0       994.0        1039\n",
+       "22        1125      1029.0       998.0      1015.0       999.0        1043\n",
+       "23        1093      1042.0      1033.0      1076.0      1023.0        1106\n",
+       "24        1034      1028.0       915.0      1031.0       988.0        1038\n",
+       "25        1065      1053.0       993.0      1032.0       994.0        1025\n",
+       "26        1008      1051.0      1046.0       994.0      1007.0        1032\n",
+       "27         983       981.0      1041.0      1040.0       988.0        1040\n",
+       "28         976      1077.0      1002.0      1014.0      1022.0        1011\n",
+       "29        1033       964.0       928.0      1025.0      1041.0        1023\n",
+       "30         961      1041.0       933.0       978.0       979.0         956\n",
+       "31        1043      1020.0       969.0      1011.0       987.0         985\n",
+       "32        1011      1018.0       953.0      1002.0       997.0        1043\n",
+       "33         922      1028.0       978.0      1004.0       982.0         969\n",
+       "34        1046      1011.0       941.0      1045.0      1017.0         982\n",
+       "35        1029      1013.0       930.0       980.0      1039.0         954\n",
+       "36        1050       980.0       970.0      1006.0      1007.0         977\n",
+       "37        1069      1074.0      1020.0       972.0       983.0         991\n",
+       "38         952      1071.0       946.0      1049.0       966.0        1001\n",
+       "39         933      1142.0      1015.0      1056.0      1009.0        1010\n",
+       "40        1195      1051.0      1042.0      1016.0      1072.0        1008\n",
+       "41        1071      1143.0      1081.0      1133.0      1009.0        1028\n",
+       "42        1131      1153.0      1031.0      1067.0      1070.0         989\n",
+       "43        1187      1115.0      1019.0      1095.0      1052.0         981\n",
+       "44        1262      1101.0      1085.0      1062.0      1032.0        1116\n",
+       "45        1250      1184.0      1144.0      1126.0      1043.0        1028\n",
+       "46        1138      1160.0      1084.0      1175.0      1174.0        1103\n",
+       "47        1360      1229.0      1058.0      1178.0      1132.0        1054\n",
+       "48        1328      1163.0      1062.0      1153.0      1159.0        1115\n",
+       "49        1296      1108.0      1076.0      1237.0      1188.0        1089\n",
+       "50        1284      1312.0      1212.0      1335.0      1219.0        1101\n",
+       "51        1297      1277.0      1216.0      1437.0      1284.0        1146\n",
+       "52        1205      1000.0      1058.0      1168.0      1133.0         944"
        ]
       },
        ]
       },
-     "execution_count": 112,
+     "execution_count": 39,
       "metadata": {},
       "output_type": "execute_result"
      }
     ],
     "source": [
       "metadata": {},
       "output_type": "execute_result"
      }
     ],
     "source": [
-    "deaths_headlines_i = deaths_headlines_i.merge(dh19i['total_2019'], how='outer', left_index=True, right_index=True)\n",
-    "deaths_headlines_i = deaths_headlines_i.merge(dh18i['total_2018'], how='outer', left_index=True, right_index=True)\n",
-    "deaths_headlines_i = deaths_headlines_i.merge(dh17i['total_2017'], how='outer', left_index=True, right_index=True)\n",
-    "deaths_headlines_i = deaths_headlines_i.merge(dh16i['total_2016'], how='outer', left_index=True, right_index=True)\n",
-    "deaths_headlines_i = deaths_headlines_i.merge(dh15i['total_2015'], how='left', left_index=True, right_index=True)\n",
-    "deaths_headlines_i"
+    "deaths_headlines_s"
     ]
    },
    {
     "cell_type": "code",
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 113,
-   "metadata": {},
+   "execution_count": 40,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
@@ -5663,472 +7039,481 @@
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
-       "      <td>1</td>\n",
-       "      <td>13768</td>\n",
+       "      <th>1</th>\n",
+       "      <td>13768.0</td>\n",
         "      <td>12424.0</td>\n",
         "      <td>14701.0</td>\n",
         "      <td>13612.0</td>\n",
         "      <td>14863.0</td>\n",
         "      <td>12424.0</td>\n",
         "      <td>14701.0</td>\n",
         "      <td>13612.0</td>\n",
         "      <td>14863.0</td>\n",
-       "      <td>13751</td>\n",
+       "      <td>13751.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2</td>\n",
-       "      <td>16020</td>\n",
+       "      <th>2</th>\n",
+       "      <td>16020.0</td>\n",
         "      <td>14487.0</td>\n",
         "      <td>17430.0</td>\n",
         "      <td>15528.0</td>\n",
         "      <td>13154.0</td>\n",
         "      <td>14487.0</td>\n",
         "      <td>17430.0</td>\n",
         "      <td>15528.0</td>\n",
         "      <td>13154.0</td>\n",
-       "      <td>18318</td>\n",
+       "      <td>18318.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>3</td>\n",
-       "      <td>14723</td>\n",
+       "      <th>3</th>\n",
+       "      <td>14723.0</td>\n",
         "      <td>13545.0</td>\n",
         "      <td>16355.0</td>\n",
         "      <td>15231.0</td>\n",
         "      <td>13060.0</td>\n",
         "      <td>13545.0</td>\n",
         "      <td>16355.0</td>\n",
         "      <td>15231.0</td>\n",
         "      <td>13060.0</td>\n",
-       "      <td>16738</td>\n",
+       "      <td>16738.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>4</td>\n",
-       "      <td>13429</td>\n",
+       "      <th>4</th>\n",
+       "      <td>13429.0</td>\n",
         "      <td>13283.0</td>\n",
         "      <td>15971.0</td>\n",
         "      <td>14461.0</td>\n",
         "      <td>12859.0</td>\n",
         "      <td>13283.0</td>\n",
         "      <td>15971.0</td>\n",
         "      <td>14461.0</td>\n",
         "      <td>12859.0</td>\n",
-       "      <td>15712</td>\n",
+       "      <td>15712.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>5</td>\n",
-       "      <td>13123</td>\n",
+       "      <th>5</th>\n",
+       "      <td>13123.0</td>\n",
         "      <td>12799.0</td>\n",
         "      <td>15087.0</td>\n",
         "      <td>14188.0</td>\n",
         "      <td>12571.0</td>\n",
         "      <td>12799.0</td>\n",
         "      <td>15087.0</td>\n",
         "      <td>14188.0</td>\n",
         "      <td>12571.0</td>\n",
-       "      <td>14560</td>\n",
+       "      <td>14560.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>6</td>\n",
-       "      <td>12534</td>\n",
+       "      <th>6</th>\n",
+       "      <td>12534.0</td>\n",
         "      <td>13222.0</td>\n",
         "      <td>14111.0</td>\n",
         "      <td>13805.0</td>\n",
         "      <td>12697.0</td>\n",
         "      <td>13222.0</td>\n",
         "      <td>14111.0</td>\n",
         "      <td>13805.0</td>\n",
         "      <td>12697.0</td>\n",
-       "      <td>13730</td>\n",
+       "      <td>13730.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>7</td>\n",
-       "      <td>12412</td>\n",
+       "      <th>7</th>\n",
+       "      <td>12412.0</td>\n",
         "      <td>13347.0</td>\n",
         "      <td>13925.0</td>\n",
         "      <td>13212.0</td>\n",
         "      <td>12016.0</td>\n",
         "      <td>13347.0</td>\n",
         "      <td>13925.0</td>\n",
         "      <td>13212.0</td>\n",
         "      <td>12016.0</td>\n",
-       "      <td>13510</td>\n",
+       "      <td>13510.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>8</td>\n",
-       "      <td>12300</td>\n",
+       "      <th>8</th>\n",
+       "      <td>12300.0</td>\n",
         "      <td>12877.0</td>\n",
         "      <td>13753.0</td>\n",
         "      <td>13330.0</td>\n",
         "      <td>12718.0</td>\n",
         "      <td>12877.0</td>\n",
         "      <td>13753.0</td>\n",
         "      <td>13330.0</td>\n",
         "      <td>12718.0</td>\n",
-       "      <td>13071</td>\n",
+       "      <td>13071.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>9</td>\n",
-       "      <td>12334</td>\n",
+       "      <th>9</th>\n",
+       "      <td>12334.0</td>\n",
         "      <td>12479.0</td>\n",
         "      <td>12190.0</td>\n",
         "      <td>12819.0</td>\n",
         "      <td>12733.0</td>\n",
         "      <td>12479.0</td>\n",
         "      <td>12190.0</td>\n",
         "      <td>12819.0</td>\n",
         "      <td>12733.0</td>\n",
-       "      <td>13181</td>\n",
+       "      <td>13181.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>10</td>\n",
-       "      <td>12415</td>\n",
+       "      <th>10</th>\n",
+       "      <td>12415.0</td>\n",
         "      <td>12396.0</td>\n",
         "      <td>14859.0</td>\n",
         "      <td>12580.0</td>\n",
         "      <td>12493.0</td>\n",
         "      <td>12396.0</td>\n",
         "      <td>14859.0</td>\n",
         "      <td>12580.0</td>\n",
         "      <td>12493.0</td>\n",
-       "      <td>13007</td>\n",
+       "      <td>13007.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>11</td>\n",
-       "      <td>12499</td>\n",
+       "      <th>11</th>\n",
+       "      <td>12499.0</td>\n",
         "      <td>12018.0</td>\n",
         "      <td>14367.0</td>\n",
         "      <td>12089.0</td>\n",
         "      <td>12489.0</td>\n",
         "      <td>12018.0</td>\n",
         "      <td>14367.0</td>\n",
         "      <td>12089.0</td>\n",
         "      <td>12489.0</td>\n",
-       "      <td>12475</td>\n",
+       "      <td>12475.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>12</td>\n",
-       "      <td>12112</td>\n",
+       "      <th>12</th>\n",
+       "      <td>12112.0</td>\n",
         "      <td>11797.0</td>\n",
         "      <td>13397.0</td>\n",
         "      <td>11833.0</td>\n",
         "      <td>10983.0</td>\n",
         "      <td>11797.0</td>\n",
         "      <td>13397.0</td>\n",
         "      <td>11833.0</td>\n",
         "      <td>10983.0</td>\n",
-       "      <td>12027</td>\n",
+       "      <td>12027.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>13</td>\n",
-       "      <td>12507</td>\n",
+       "      <th>13</th>\n",
+       "      <td>12507.0</td>\n",
         "      <td>11260.0</td>\n",
         "      <td>11310.0</td>\n",
         "      <td>11453.0</td>\n",
         "      <td>11738.0</td>\n",
         "      <td>11260.0</td>\n",
         "      <td>11310.0</td>\n",
         "      <td>11453.0</td>\n",
         "      <td>11738.0</td>\n",
-       "      <td>11987</td>\n",
+       "      <td>11987.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>14</td>\n",
-       "      <td>18565</td>\n",
+       "      <th>14</th>\n",
+       "      <td>18565.0</td>\n",
         "      <td>11445.0</td>\n",
         "      <td>12272.0</td>\n",
         "      <td>11305.0</td>\n",
         "      <td>13060.0</td>\n",
         "      <td>11445.0</td>\n",
         "      <td>12272.0</td>\n",
         "      <td>11305.0</td>\n",
         "      <td>13060.0</td>\n",
-       "      <td>10325</td>\n",
+       "      <td>10325.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>15</td>\n",
-       "      <td>20929</td>\n",
+       "      <th>15</th>\n",
+       "      <td>20929.0</td>\n",
         "      <td>11661.0</td>\n",
         "      <td>13843.0</td>\n",
         "      <td>9761.0</td>\n",
         "      <td>12757.0</td>\n",
         "      <td>11661.0</td>\n",
         "      <td>13843.0</td>\n",
         "      <td>9761.0</td>\n",
         "      <td>12757.0</td>\n",
-       "      <td>11575</td>\n",
+       "      <td>11575.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>16</td>\n",
-       "      <td>24691</td>\n",
+       "      <th>16</th>\n",
+       "      <td>24691.0</td>\n",
         "      <td>10243.0</td>\n",
         "      <td>12639.0</td>\n",
         "      <td>11000.0</td>\n",
         "      <td>12310.0</td>\n",
         "      <td>10243.0</td>\n",
         "      <td>12639.0</td>\n",
         "      <td>11000.0</td>\n",
         "      <td>12310.0</td>\n",
-       "      <td>13061</td>\n",
+       "      <td>13061.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>17</td>\n",
-       "      <td>24303</td>\n",
+       "      <th>17</th>\n",
+       "      <td>24303.0</td>\n",
         "      <td>11452.0</td>\n",
         "      <td>11596.0</td>\n",
         "      <td>12356.0</td>\n",
         "      <td>11795.0</td>\n",
         "      <td>11452.0</td>\n",
         "      <td>11596.0</td>\n",
         "      <td>12356.0</td>\n",
         "      <td>11795.0</td>\n",
-       "      <td>12023</td>\n",
+       "      <td>12023.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>18</td>\n",
-       "      <td>20059</td>\n",
+       "      <th>18</th>\n",
+       "      <td>20059.0</td>\n",
         "      <td>12695.0</td>\n",
         "      <td>11538.0</td>\n",
         "      <td>10372.0</td>\n",
         "      <td>10401.0</td>\n",
         "      <td>12695.0</td>\n",
         "      <td>11538.0</td>\n",
         "      <td>10372.0</td>\n",
         "      <td>10401.0</td>\n",
-       "      <td>11586</td>\n",
+       "      <td>11586.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>19</td>\n",
-       "      <td>14428</td>\n",
+       "      <th>19</th>\n",
+       "      <td>14428.0</td>\n",
         "      <td>10361.0</td>\n",
         "      <td>9821.0</td>\n",
         "      <td>12114.0</td>\n",
         "      <td>12002.0</td>\n",
         "      <td>10361.0</td>\n",
         "      <td>9821.0</td>\n",
         "      <td>12114.0</td>\n",
         "      <td>12002.0</td>\n",
-       "      <td>10138</td>\n",
+       "      <td>10138.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>20</td>\n",
-       "      <td>16390</td>\n",
+       "      <th>20</th>\n",
+       "      <td>16390.0</td>\n",
         "      <td>11717.0</td>\n",
         "      <td>11386.0</td>\n",
         "      <td>11718.0</td>\n",
         "      <td>11222.0</td>\n",
         "      <td>11717.0</td>\n",
         "      <td>11386.0</td>\n",
         "      <td>11718.0</td>\n",
         "      <td>11222.0</td>\n",
-       "      <td>11692</td>\n",
+       "      <td>11692.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>21</td>\n",
-       "      <td>13839</td>\n",
+       "      <th>21</th>\n",
+       "      <td>13839.0</td>\n",
         "      <td>11653.0</td>\n",
         "      <td>10974.0</td>\n",
         "      <td>11431.0</td>\n",
         "      <td>11013.0</td>\n",
         "      <td>11653.0</td>\n",
         "      <td>10974.0</td>\n",
         "      <td>11431.0</td>\n",
         "      <td>11013.0</td>\n",
-       "      <td>11334</td>\n",
+       "      <td>11334.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>22</td>\n",
-       "      <td>11265</td>\n",
+       "      <th>22</th>\n",
+       "      <td>11265.0</td>\n",
         "      <td>9534.0</td>\n",
         "      <td>9397.0</td>\n",
         "      <td>9603.0</td>\n",
         "      <td>9192.0</td>\n",
         "      <td>9534.0</td>\n",
         "      <td>9397.0</td>\n",
         "      <td>9603.0</td>\n",
         "      <td>9192.0</td>\n",
-       "      <td>9514</td>\n",
+       "      <td>9514.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>23</td>\n",
-       "      <td>12106</td>\n",
+       "      <th>23</th>\n",
+       "      <td>12106.0</td>\n",
         "      <td>11461.0</td>\n",
         "      <td>11259.0</td>\n",
         "      <td>11134.0</td>\n",
         "      <td>11171.0</td>\n",
         "      <td>11461.0</td>\n",
         "      <td>11259.0</td>\n",
         "      <td>11134.0</td>\n",
         "      <td>11171.0</td>\n",
-       "      <td>11603</td>\n",
+       "      <td>11603.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>24</td>\n",
-       "      <td>11302</td>\n",
+       "      <th>24</th>\n",
+       "      <td>11302.0</td>\n",
         "      <td>10754.0</td>\n",
         "      <td>10535.0</td>\n",
         "      <td>10698.0</td>\n",
         "      <td>10673.0</td>\n",
         "      <td>10754.0</td>\n",
         "      <td>10535.0</td>\n",
         "      <td>10698.0</td>\n",
         "      <td>10673.0</td>\n",
-       "      <td>10858</td>\n",
+       "      <td>10858.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>25</td>\n",
-       "      <td>10694</td>\n",
+       "      <th>25</th>\n",
+       "      <td>10694.0</td>\n",
         "      <td>10807.0</td>\n",
         "      <td>10514.0</td>\n",
         "      <td>10930.0</td>\n",
         "      <td>10611.0</td>\n",
         "      <td>10807.0</td>\n",
         "      <td>10514.0</td>\n",
         "      <td>10930.0</td>\n",
         "      <td>10611.0</td>\n",
-       "      <td>10629</td>\n",
+       "      <td>10629.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>26</td>\n",
-       "      <td>10282</td>\n",
+       "      <th>26</th>\n",
+       "      <td>10282.0</td>\n",
         "      <td>10824.0</td>\n",
         "      <td>10529.0</td>\n",
         "      <td>10624.0</td>\n",
         "      <td>10526.0</td>\n",
         "      <td>10824.0</td>\n",
         "      <td>10529.0</td>\n",
         "      <td>10624.0</td>\n",
         "      <td>10526.0</td>\n",
-       "      <td>10525</td>\n",
+       "      <td>10525.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>27</td>\n",
-       "      <td>10412</td>\n",
+       "      <th>27</th>\n",
+       "      <td>10412.0</td>\n",
         "      <td>10328.0</td>\n",
         "      <td>10565.0</td>\n",
         "      <td>10565.0</td>\n",
         "      <td>10412.0</td>\n",
         "      <td>10328.0</td>\n",
         "      <td>10565.0</td>\n",
         "      <td>10565.0</td>\n",
         "      <td>10412.0</td>\n",
-       "      <td>10545</td>\n",
+       "      <td>10545.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>28</td>\n",
-       "      <td>9941</td>\n",
+       "      <th>28</th>\n",
+       "      <td>9941.0</td>\n",
         "      <td>10512.0</td>\n",
         "      <td>10467.0</td>\n",
         "      <td>10643.0</td>\n",
         "      <td>10647.0</td>\n",
         "      <td>10512.0</td>\n",
         "      <td>10467.0</td>\n",
         "      <td>10643.0</td>\n",
         "      <td>10647.0</td>\n",
-       "      <td>10278</td>\n",
+       "      <td>10278.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>29</td>\n",
-       "      <td>10096</td>\n",
+       "      <th>29</th>\n",
+       "      <td>10096.0</td>\n",
         "      <td>10324.0</td>\n",
         "      <td>10353.0</td>\n",
         "      <td>10426.0</td>\n",
         "      <td>10672.0</td>\n",
         "      <td>10324.0</td>\n",
         "      <td>10353.0</td>\n",
         "      <td>10426.0</td>\n",
         "      <td>10672.0</td>\n",
-       "      <td>10028</td>\n",
+       "      <td>10028.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>30</td>\n",
-       "      <td>10159</td>\n",
+       "      <th>30</th>\n",
+       "      <td>10159.0</td>\n",
         "      <td>10422.0</td>\n",
         "      <td>10356.0</td>\n",
         "      <td>10147.0</td>\n",
         "      <td>10612.0</td>\n",
         "      <td>10422.0</td>\n",
         "      <td>10356.0</td>\n",
         "      <td>10147.0</td>\n",
         "      <td>10612.0</td>\n",
-       "      <td>10021</td>\n",
+       "      <td>10021.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>31</td>\n",
-       "      <td>10262</td>\n",
+       "      <th>31</th>\n",
+       "      <td>10262.0</td>\n",
         "      <td>10564.0</td>\n",
         "      <td>10408.0</td>\n",
         "      <td>10239.0</td>\n",
         "      <td>10433.0</td>\n",
         "      <td>10564.0</td>\n",
         "      <td>10408.0</td>\n",
         "      <td>10239.0</td>\n",
         "      <td>10433.0</td>\n",
-       "      <td>9893</td>\n",
+       "      <td>9893.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>32</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>32</th>\n",
+       "      <td>10236.0</td>\n",
         "      <td>10406.0</td>\n",
         "      <td>10542.0</td>\n",
         "      <td>10278.0</td>\n",
         "      <td>10439.0</td>\n",
         "      <td>10406.0</td>\n",
         "      <td>10542.0</td>\n",
         "      <td>10278.0</td>\n",
         "      <td>10439.0</td>\n",
-       "      <td>10153</td>\n",
+       "      <td>10153.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>33</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>33</th>\n",
+       "      <td>10592.0</td>\n",
         "      <td>10405.0</td>\n",
         "      <td>10091.0</td>\n",
         "      <td>10569.0</td>\n",
         "      <td>10312.0</td>\n",
         "      <td>10405.0</td>\n",
         "      <td>10091.0</td>\n",
         "      <td>10569.0</td>\n",
         "      <td>10312.0</td>\n",
-       "      <td>10352</td>\n",
+       "      <td>10352.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>34</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>34</th>\n",
+       "      <td>10990.0</td>\n",
         "      <td>10279.0</td>\n",
         "      <td>10199.0</td>\n",
         "      <td>10698.0</td>\n",
         "      <td>10637.0</td>\n",
         "      <td>10279.0</td>\n",
         "      <td>10199.0</td>\n",
         "      <td>10698.0</td>\n",
         "      <td>10637.0</td>\n",
-       "      <td>10354</td>\n",
+       "      <td>10354.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>35</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>35</th>\n",
+       "      <td>10364.0</td>\n",
         "      <td>9478.0</td>\n",
         "      <td>9046.0</td>\n",
         "      <td>9372.0</td>\n",
         "      <td>9226.0</td>\n",
         "      <td>9478.0</td>\n",
         "      <td>9046.0</td>\n",
         "      <td>9372.0</td>\n",
         "      <td>9226.0</td>\n",
-       "      <td>10239</td>\n",
+       "      <td>10239.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>36</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>36</th>\n",
+       "      <td>9023.0</td>\n",
         "      <td>10918.0</td>\n",
         "      <td>10680.0</td>\n",
         "      <td>10781.0</td>\n",
         "      <td>10681.0</td>\n",
         "      <td>10918.0</td>\n",
         "      <td>10680.0</td>\n",
         "      <td>10781.0</td>\n",
         "      <td>10681.0</td>\n",
-       "      <td>9092</td>\n",
+       "      <td>9092.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>37</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>37</th>\n",
+       "      <td>11176.0</td>\n",
         "      <td>10892.0</td>\n",
         "      <td>10496.0</td>\n",
         "      <td>10692.0</td>\n",
         "      <td>10401.0</td>\n",
         "      <td>10892.0</td>\n",
         "      <td>10496.0</td>\n",
         "      <td>10692.0</td>\n",
         "      <td>10401.0</td>\n",
-       "      <td>10573</td>\n",
+       "      <td>10573.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>38</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>38</th>\n",
+       "      <td>10797.0</td>\n",
         "      <td>10792.0</td>\n",
         "      <td>10498.0</td>\n",
         "      <td>10875.0</td>\n",
         "      <td>10183.0</td>\n",
         "      <td>10792.0</td>\n",
         "      <td>10498.0</td>\n",
         "      <td>10875.0</td>\n",
         "      <td>10183.0</td>\n",
-       "      <td>10381</td>\n",
+       "      <td>10381.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>39</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>39</th>\n",
+       "      <td>10890.0</td>\n",
         "      <td>10954.0</td>\n",
         "      <td>10463.0</td>\n",
         "      <td>11027.0</td>\n",
         "      <td>10278.0</td>\n",
         "      <td>10954.0</td>\n",
         "      <td>10463.0</td>\n",
         "      <td>11027.0</td>\n",
         "      <td>10278.0</td>\n",
-       "      <td>10826</td>\n",
+       "      <td>10826.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>40</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>40</th>\n",
+       "      <td>11468.0</td>\n",
         "      <td>11113.0</td>\n",
         "      <td>10869.0</td>\n",
         "      <td>11101.0</td>\n",
         "      <td>10671.0</td>\n",
         "      <td>11113.0</td>\n",
         "      <td>10869.0</td>\n",
         "      <td>11101.0</td>\n",
         "      <td>10671.0</td>\n",
-       "      <td>10700</td>\n",
+       "      <td>10700.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>41</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>41</th>\n",
+       "      <td>11373.0</td>\n",
         "      <td>11403.0</td>\n",
         "      <td>11048.0</td>\n",
         "      <td>11357.0</td>\n",
         "      <td>11016.0</td>\n",
         "      <td>11403.0</td>\n",
         "      <td>11048.0</td>\n",
         "      <td>11357.0</td>\n",
         "      <td>11016.0</td>\n",
-       "      <td>11108</td>\n",
+       "      <td>11108.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>42</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>42</th>\n",
+       "      <td>11943.0</td>\n",
         "      <td>11625.0</td>\n",
         "      <td>11177.0</td>\n",
         "      <td>11389.0</td>\n",
         "      <td>11134.0</td>\n",
         "      <td>11625.0</td>\n",
         "      <td>11177.0</td>\n",
         "      <td>11389.0</td>\n",
         "      <td>11134.0</td>\n",
-       "      <td>10799</td>\n",
+       "      <td>10799.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>43</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>43</th>\n",
+       "      <td>12317.0</td>\n",
         "      <td>11415.0</td>\n",
         "      <td>10885.0</td>\n",
         "      <td>11152.0</td>\n",
         "      <td>11048.0</td>\n",
         "      <td>11415.0</td>\n",
         "      <td>10885.0</td>\n",
         "      <td>11152.0</td>\n",
         "      <td>11048.0</td>\n",
-       "      <td>10966</td>\n",
+       "      <td>10966.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>44</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>44</th>\n",
+       "      <td>12517.0</td>\n",
         "      <td>11567.0</td>\n",
         "      <td>10866.0</td>\n",
         "      <td>11366.0</td>\n",
         "      <td>11463.0</td>\n",
         "      <td>11567.0</td>\n",
         "      <td>10866.0</td>\n",
         "      <td>11366.0</td>\n",
         "      <td>11463.0</td>\n",
-       "      <td>11026</td>\n",
+       "      <td>11026.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>45</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>45</th>\n",
+       "      <td>13448.0</td>\n",
         "      <td>12177.0</td>\n",
         "      <td>11588.0</td>\n",
         "      <td>11767.0</td>\n",
         "      <td>11803.0</td>\n",
         "      <td>12177.0</td>\n",
         "      <td>11588.0</td>\n",
         "      <td>11767.0</td>\n",
         "      <td>11803.0</td>\n",
-       "      <td>11312</td>\n",
+       "      <td>11312.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>46</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>46</th>\n",
+       "      <td>13798.0</td>\n",
         "      <td>12146.0</td>\n",
         "      <td>11552.0</td>\n",
         "      <td>11773.0</td>\n",
         "      <td>12209.0</td>\n",
         "      <td>12146.0</td>\n",
         "      <td>11552.0</td>\n",
         "      <td>11773.0</td>\n",
         "      <td>12209.0</td>\n",
-       "      <td>11338</td>\n",
+       "      <td>11338.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>47</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>47</th>\n",
+       "      <td>14291.0</td>\n",
         "      <td>12472.0</td>\n",
         "      <td>11289.0</td>\n",
         "      <td>12102.0</td>\n",
         "      <td>12064.0</td>\n",
         "      <td>12472.0</td>\n",
         "      <td>11289.0</td>\n",
         "      <td>12102.0</td>\n",
         "      <td>12064.0</td>\n",
-       "      <td>11178</td>\n",
+       "      <td>11178.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>48</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>48</th>\n",
+       "      <td>14132.0</td>\n",
         "      <td>12455.0</td>\n",
         "      <td>11392.0</td>\n",
         "      <td>12046.0</td>\n",
         "      <td>11901.0</td>\n",
         "      <td>12455.0</td>\n",
         "      <td>11392.0</td>\n",
         "      <td>12046.0</td>\n",
         "      <td>11901.0</td>\n",
-       "      <td>11216</td>\n",
+       "      <td>11216.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>49</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>49</th>\n",
+       "      <td>13986.0</td>\n",
         "      <td>12275.0</td>\n",
         "      <td>11687.0</td>\n",
         "      <td>12342.0</td>\n",
         "      <td>12733.0</td>\n",
         "      <td>12275.0</td>\n",
         "      <td>11687.0</td>\n",
         "      <td>12342.0</td>\n",
         "      <td>12733.0</td>\n",
-       "      <td>11748</td>\n",
+       "      <td>11748.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>50</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>50</th>\n",
+       "      <td>13942.0</td>\n",
         "      <td>12853.0</td>\n",
         "      <td>12078.0</td>\n",
         "      <td>12924.0</td>\n",
         "      <td>12076.0</td>\n",
         "      <td>12853.0</td>\n",
         "      <td>12078.0</td>\n",
         "      <td>12924.0</td>\n",
         "      <td>12076.0</td>\n",
-       "      <td>11713</td>\n",
+       "      <td>11713.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>51</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>51</th>\n",
+       "      <td>14658.0</td>\n",
         "      <td>13566.0</td>\n",
         "      <td>12649.0</td>\n",
         "      <td>14308.0</td>\n",
         "      <td>13137.0</td>\n",
         "      <td>13566.0</td>\n",
         "      <td>12649.0</td>\n",
         "      <td>14308.0</td>\n",
         "      <td>13137.0</td>\n",
-       "      <td>12136</td>\n",
+       "      <td>12136.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>52</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>52</th>\n",
+       "      <td>13035.0</td>\n",
         "      <td>8727.0</td>\n",
         "      <td>8384.0</td>\n",
         "      <td>9904.0</td>\n",
         "      <td>9335.0</td>\n",
         "      <td>8727.0</td>\n",
         "      <td>8384.0</td>\n",
         "      <td>9904.0</td>\n",
         "      <td>9335.0</td>\n",
-       "      <td>9806</td>\n",
+       "      <td>9806.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
@@ -6136,61 +7521,62 @@
        ],
        "text/plain": [
         "   total_2020  total_2019  total_2018  total_2017  total_2016  total_2015\n",
        ],
        "text/plain": [
         "   total_2020  total_2019  total_2018  total_2017  total_2016  total_2015\n",
-       "1       13768     12424.0     14701.0     13612.0     14863.0       13751\n",
-       "2       16020     14487.0     17430.0     15528.0     13154.0       18318\n",
-       "3       14723     13545.0     16355.0     15231.0     13060.0       16738\n",
-       "4       13429     13283.0     15971.0     14461.0     12859.0       15712\n",
-       "5       13123     12799.0     15087.0     14188.0     12571.0       14560\n",
-       "6       12534     13222.0     14111.0     13805.0     12697.0       13730\n",
-       "7       12412     13347.0     13925.0     13212.0     12016.0       13510\n",
-       "8       12300     12877.0     13753.0     13330.0     12718.0       13071\n",
-       "9       12334     12479.0     12190.0     12819.0     12733.0       13181\n",
-       "10      12415     12396.0     14859.0     12580.0     12493.0       13007\n",
-       "11      12499     12018.0     14367.0     12089.0     12489.0       12475\n",
-       "12      12112     11797.0     13397.0     11833.0     10983.0       12027\n",
-       "13      12507     11260.0     11310.0     11453.0     11738.0       11987\n",
-       "14      18565     11445.0     12272.0     11305.0     13060.0       10325\n",
-       "15      20929     11661.0     13843.0      9761.0     12757.0       11575\n",
-       "16      24691     10243.0     12639.0     11000.0     12310.0       13061\n",
-       "17      24303     11452.0     11596.0     12356.0     11795.0       12023\n",
-       "18      20059     12695.0     11538.0     10372.0     10401.0       11586\n",
-       "19      14428     10361.0      9821.0     12114.0     12002.0       10138\n",
-       "20      16390     11717.0     11386.0     11718.0     11222.0       11692\n",
-       "21      13839     11653.0     10974.0     11431.0     11013.0       11334\n",
-       "22      11265      9534.0      9397.0      9603.0      9192.0        9514\n",
-       "23      12106     11461.0     11259.0     11134.0     11171.0       11603\n",
-       "24      11302     10754.0     10535.0     10698.0     10673.0       10858\n",
-       "25      10694     10807.0     10514.0     10930.0     10611.0       10629\n",
-       "26      10282     10824.0     10529.0     10624.0     10526.0       10525\n",
-       "27      10412     10328.0     10565.0     10565.0     10412.0       10545\n",
-       "28       9941     10512.0     10467.0     10643.0     10647.0       10278\n",
-       "29      10096     10324.0     10353.0     10426.0     10672.0       10028\n",
-       "30      10159     10422.0     10356.0     10147.0     10612.0       10021\n",
-       "31      10262     10564.0     10408.0     10239.0     10433.0        9893\n",
-       "32        NaN     10406.0     10542.0     10278.0     10439.0       10153\n",
-       "33        NaN     10405.0     10091.0     10569.0     10312.0       10352\n",
-       "34        NaN     10279.0     10199.0     10698.0     10637.0       10354\n",
-       "35        NaN      9478.0      9046.0      9372.0      9226.0       10239\n",
-       "36        NaN     10918.0     10680.0     10781.0     10681.0        9092\n",
-       "37        NaN     10892.0     10496.0     10692.0     10401.0       10573\n",
-       "38        NaN     10792.0     10498.0     10875.0     10183.0       10381\n",
-       "39        NaN     10954.0     10463.0     11027.0     10278.0       10826\n",
-       "40        NaN     11113.0     10869.0     11101.0     10671.0       10700\n",
-       "41        NaN     11403.0     11048.0     11357.0     11016.0       11108\n",
-       "42        NaN     11625.0     11177.0     11389.0     11134.0       10799\n",
-       "43        NaN     11415.0     10885.0     11152.0     11048.0       10966\n",
-       "44        NaN     11567.0     10866.0     11366.0     11463.0       11026\n",
-       "45        NaN     12177.0     11588.0     11767.0     11803.0       11312\n",
-       "46        NaN     12146.0     11552.0     11773.0     12209.0       11338\n",
-       "47        NaN     12472.0     11289.0     12102.0     12064.0       11178\n",
-       "48        NaN     12455.0     11392.0     12046.0     11901.0       11216\n",
-       "49        NaN     12275.0     11687.0     12342.0     12733.0       11748\n",
-       "50        NaN     12853.0     12078.0     12924.0     12076.0       11713\n",
-       "51        NaN     13566.0     12649.0     14308.0     13137.0       12136\n",
-       "52        NaN      8727.0      8384.0      9904.0      9335.0        9806"
+       "1     13768.0     12424.0     14701.0     13612.0     14863.0     13751.0\n",
+       "2     16020.0     14487.0     17430.0     15528.0     13154.0     18318.0\n",
+       "3     14723.0     13545.0     16355.0     15231.0     13060.0     16738.0\n",
+       "4     13429.0     13283.0     15971.0     14461.0     12859.0     15712.0\n",
+       "5     13123.0     12799.0     15087.0     14188.0     12571.0     14560.0\n",
+       "6     12534.0     13222.0     14111.0     13805.0     12697.0     13730.0\n",
+       "7     12412.0     13347.0     13925.0     13212.0     12016.0     13510.0\n",
+       "8     12300.0     12877.0     13753.0     13330.0     12718.0     13071.0\n",
+       "9     12334.0     12479.0     12190.0     12819.0     12733.0     13181.0\n",
+       "10    12415.0     12396.0     14859.0     12580.0     12493.0     13007.0\n",
+       "11    12499.0     12018.0     14367.0     12089.0     12489.0     12475.0\n",
+       "12    12112.0     11797.0     13397.0     11833.0     10983.0     12027.0\n",
+       "13    12507.0     11260.0     11310.0     11453.0     11738.0     11987.0\n",
+       "14    18565.0     11445.0     12272.0     11305.0     13060.0     10325.0\n",
+       "15    20929.0     11661.0     13843.0      9761.0     12757.0     11575.0\n",
+       "16    24691.0     10243.0     12639.0     11000.0     12310.0     13061.0\n",
+       "17    24303.0     11452.0     11596.0     12356.0     11795.0     12023.0\n",
+       "18    20059.0     12695.0     11538.0     10372.0     10401.0     11586.0\n",
+       "19    14428.0     10361.0      9821.0     12114.0     12002.0     10138.0\n",
+       "20    16390.0     11717.0     11386.0     11718.0     11222.0     11692.0\n",
+       "21    13839.0     11653.0     10974.0     11431.0     11013.0     11334.0\n",
+       "22    11265.0      9534.0      9397.0      9603.0      9192.0      9514.0\n",
+       "23    12106.0     11461.0     11259.0     11134.0     11171.0     11603.0\n",
+       "24    11302.0     10754.0     10535.0     10698.0     10673.0     10858.0\n",
+       "25    10694.0     10807.0     10514.0     10930.0     10611.0     10629.0\n",
+       "26    10282.0     10824.0     10529.0     10624.0     10526.0     10525.0\n",
+       "27    10412.0     10328.0     10565.0     10565.0     10412.0     10545.0\n",
+       "28     9941.0     10512.0     10467.0     10643.0     10647.0     10278.0\n",
+       "29    10096.0     10324.0     10353.0     10426.0     10672.0     10028.0\n",
+       "30    10159.0     10422.0     10356.0     10147.0     10612.0     10021.0\n",
+       "31    10262.0     10564.0     10408.0     10239.0     10433.0      9893.0\n",
+       "32    10236.0     10406.0     10542.0     10278.0     10439.0     10153.0\n",
+       "33    10592.0     10405.0     10091.0     10569.0     10312.0     10352.0\n",
+       "34    10990.0     10279.0     10199.0     10698.0     10637.0     10354.0\n",
+       "35    10364.0      9478.0      9046.0      9372.0      9226.0     10239.0\n",
+       "36     9023.0     10918.0     10680.0     10781.0     10681.0      9092.0\n",
+       "37    11176.0     10892.0     10496.0     10692.0     10401.0     10573.0\n",
+       "38    10797.0     10792.0     10498.0     10875.0     10183.0     10381.0\n",
+       "39    10890.0     10954.0     10463.0     11027.0     10278.0     10826.0\n",
+       "40    11468.0     11113.0     10869.0     11101.0     10671.0     10700.0\n",
+       "41    11373.0     11403.0     11048.0     11357.0     11016.0     11108.0\n",
+       "42    11943.0     11625.0     11177.0     11389.0     11134.0     10799.0\n",
+       "43    12317.0     11415.0     10885.0     11152.0     11048.0     10966.0\n",
+       "44    12517.0     11567.0     10866.0     11366.0     11463.0     11026.0\n",
+       "45    13448.0     12177.0     11588.0     11767.0     11803.0     11312.0\n",
+       "46    13798.0     12146.0     11552.0     11773.0     12209.0     11338.0\n",
+       "47    14291.0     12472.0     11289.0     12102.0     12064.0     11178.0\n",
+       "48    14132.0     12455.0     11392.0     12046.0     11901.0     11216.0\n",
+       "49    13986.0     12275.0     11687.0     12342.0     12733.0     11748.0\n",
+       "50    13942.0     12853.0     12078.0     12924.0     12076.0     11713.0\n",
+       "51    14658.0     13566.0     12649.0     14308.0     13137.0     12136.0\n",
+       "52    13035.0      8727.0      8384.0      9904.0      9335.0      9806.0\n",
+       "53        NaN         NaN         NaN         NaN         NaN         NaN"
        ]
       },
        ]
       },
-     "execution_count": 113,
+     "execution_count": 40,
       "metadata": {},
       "output_type": "execute_result"
      }
       "metadata": {},
       "output_type": "execute_result"
      }
@@ -6202,8 +7588,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 114,
-   "metadata": {},
+   "execution_count": 41,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
@@ -6237,583 +7625,594 @@
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
-       "      <td>1</td>\n",
-       "      <td>13768</td>\n",
+       "      <th>1</th>\n",
+       "      <td>13768.0</td>\n",
         "      <td>12424.0</td>\n",
         "      <td>14701.0</td>\n",
         "      <td>13612.0</td>\n",
         "      <td>14863.0</td>\n",
         "      <td>12424.0</td>\n",
         "      <td>14701.0</td>\n",
         "      <td>13612.0</td>\n",
         "      <td>14863.0</td>\n",
-       "      <td>13751</td>\n",
+       "      <td>13751.0</td>\n",
         "      <td>13870.2</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>13870.2</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>2</td>\n",
-       "      <td>16020</td>\n",
+       "      <th>2</th>\n",
+       "      <td>16020.0</td>\n",
         "      <td>14487.0</td>\n",
         "      <td>17430.0</td>\n",
         "      <td>15528.0</td>\n",
         "      <td>13154.0</td>\n",
         "      <td>14487.0</td>\n",
         "      <td>17430.0</td>\n",
         "      <td>15528.0</td>\n",
         "      <td>13154.0</td>\n",
-       "      <td>18318</td>\n",
+       "      <td>18318.0</td>\n",
         "      <td>15783.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>15783.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>3</td>\n",
-       "      <td>14723</td>\n",
+       "      <th>3</th>\n",
+       "      <td>14723.0</td>\n",
         "      <td>13545.0</td>\n",
         "      <td>16355.0</td>\n",
         "      <td>15231.0</td>\n",
         "      <td>13060.0</td>\n",
         "      <td>13545.0</td>\n",
         "      <td>16355.0</td>\n",
         "      <td>15231.0</td>\n",
         "      <td>13060.0</td>\n",
-       "      <td>16738</td>\n",
+       "      <td>16738.0</td>\n",
         "      <td>14985.8</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>14985.8</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>4</td>\n",
-       "      <td>13429</td>\n",
+       "      <th>4</th>\n",
+       "      <td>13429.0</td>\n",
         "      <td>13283.0</td>\n",
         "      <td>15971.0</td>\n",
         "      <td>14461.0</td>\n",
         "      <td>12859.0</td>\n",
         "      <td>13283.0</td>\n",
         "      <td>15971.0</td>\n",
         "      <td>14461.0</td>\n",
         "      <td>12859.0</td>\n",
-       "      <td>15712</td>\n",
+       "      <td>15712.0</td>\n",
         "      <td>14457.2</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>14457.2</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>5</td>\n",
-       "      <td>13123</td>\n",
+       "      <th>5</th>\n",
+       "      <td>13123.0</td>\n",
         "      <td>12799.0</td>\n",
         "      <td>15087.0</td>\n",
         "      <td>14188.0</td>\n",
         "      <td>12571.0</td>\n",
         "      <td>12799.0</td>\n",
         "      <td>15087.0</td>\n",
         "      <td>14188.0</td>\n",
         "      <td>12571.0</td>\n",
-       "      <td>14560</td>\n",
+       "      <td>14560.0</td>\n",
         "      <td>13841.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>13841.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>6</td>\n",
-       "      <td>12534</td>\n",
+       "      <th>6</th>\n",
+       "      <td>12534.0</td>\n",
         "      <td>13222.0</td>\n",
         "      <td>14111.0</td>\n",
         "      <td>13805.0</td>\n",
         "      <td>12697.0</td>\n",
         "      <td>13222.0</td>\n",
         "      <td>14111.0</td>\n",
         "      <td>13805.0</td>\n",
         "      <td>12697.0</td>\n",
-       "      <td>13730</td>\n",
+       "      <td>13730.0</td>\n",
         "      <td>13513.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>13513.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>7</td>\n",
-       "      <td>12412</td>\n",
+       "      <th>7</th>\n",
+       "      <td>12412.0</td>\n",
         "      <td>13347.0</td>\n",
         "      <td>13925.0</td>\n",
         "      <td>13212.0</td>\n",
         "      <td>12016.0</td>\n",
         "      <td>13347.0</td>\n",
         "      <td>13925.0</td>\n",
         "      <td>13212.0</td>\n",
         "      <td>12016.0</td>\n",
-       "      <td>13510</td>\n",
+       "      <td>13510.0</td>\n",
         "      <td>13202.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>13202.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>8</td>\n",
-       "      <td>12300</td>\n",
+       "      <th>8</th>\n",
+       "      <td>12300.0</td>\n",
         "      <td>12877.0</td>\n",
         "      <td>13753.0</td>\n",
         "      <td>13330.0</td>\n",
         "      <td>12718.0</td>\n",
         "      <td>12877.0</td>\n",
         "      <td>13753.0</td>\n",
         "      <td>13330.0</td>\n",
         "      <td>12718.0</td>\n",
-       "      <td>13071</td>\n",
+       "      <td>13071.0</td>\n",
         "      <td>13149.8</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>13149.8</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>9</td>\n",
-       "      <td>12334</td>\n",
+       "      <th>9</th>\n",
+       "      <td>12334.0</td>\n",
         "      <td>12479.0</td>\n",
         "      <td>12190.0</td>\n",
         "      <td>12819.0</td>\n",
         "      <td>12733.0</td>\n",
         "      <td>12479.0</td>\n",
         "      <td>12190.0</td>\n",
         "      <td>12819.0</td>\n",
         "      <td>12733.0</td>\n",
-       "      <td>13181</td>\n",
+       "      <td>13181.0</td>\n",
         "      <td>12680.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>12680.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>10</td>\n",
-       "      <td>12415</td>\n",
+       "      <th>10</th>\n",
+       "      <td>12415.0</td>\n",
         "      <td>12396.0</td>\n",
         "      <td>14859.0</td>\n",
         "      <td>12580.0</td>\n",
         "      <td>12493.0</td>\n",
         "      <td>12396.0</td>\n",
         "      <td>14859.0</td>\n",
         "      <td>12580.0</td>\n",
         "      <td>12493.0</td>\n",
-       "      <td>13007</td>\n",
+       "      <td>13007.0</td>\n",
         "      <td>13067.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>13067.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>11</td>\n",
-       "      <td>12499</td>\n",
+       "      <th>11</th>\n",
+       "      <td>12499.0</td>\n",
         "      <td>12018.0</td>\n",
         "      <td>14367.0</td>\n",
         "      <td>12089.0</td>\n",
         "      <td>12489.0</td>\n",
         "      <td>12018.0</td>\n",
         "      <td>14367.0</td>\n",
         "      <td>12089.0</td>\n",
         "      <td>12489.0</td>\n",
-       "      <td>12475</td>\n",
+       "      <td>12475.0</td>\n",
         "      <td>12687.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>12687.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>12</td>\n",
-       "      <td>12112</td>\n",
+       "      <th>12</th>\n",
+       "      <td>12112.0</td>\n",
         "      <td>11797.0</td>\n",
         "      <td>13397.0</td>\n",
         "      <td>11833.0</td>\n",
         "      <td>10983.0</td>\n",
         "      <td>11797.0</td>\n",
         "      <td>13397.0</td>\n",
         "      <td>11833.0</td>\n",
         "      <td>10983.0</td>\n",
-       "      <td>12027</td>\n",
+       "      <td>12027.0</td>\n",
         "      <td>12007.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>12007.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>13</td>\n",
-       "      <td>12507</td>\n",
+       "      <th>13</th>\n",
+       "      <td>12507.0</td>\n",
         "      <td>11260.0</td>\n",
         "      <td>11310.0</td>\n",
         "      <td>11453.0</td>\n",
         "      <td>11738.0</td>\n",
         "      <td>11260.0</td>\n",
         "      <td>11310.0</td>\n",
         "      <td>11453.0</td>\n",
         "      <td>11738.0</td>\n",
-       "      <td>11987</td>\n",
+       "      <td>11987.0</td>\n",
         "      <td>11549.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>11549.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>14</td>\n",
-       "      <td>18565</td>\n",
+       "      <th>14</th>\n",
+       "      <td>18565.0</td>\n",
         "      <td>11445.0</td>\n",
         "      <td>12272.0</td>\n",
         "      <td>11305.0</td>\n",
         "      <td>13060.0</td>\n",
         "      <td>11445.0</td>\n",
         "      <td>12272.0</td>\n",
         "      <td>11305.0</td>\n",
         "      <td>13060.0</td>\n",
-       "      <td>10325</td>\n",
+       "      <td>10325.0</td>\n",
         "      <td>11681.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>11681.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>15</td>\n",
-       "      <td>20929</td>\n",
+       "      <th>15</th>\n",
+       "      <td>20929.0</td>\n",
         "      <td>11661.0</td>\n",
         "      <td>13843.0</td>\n",
         "      <td>9761.0</td>\n",
         "      <td>12757.0</td>\n",
         "      <td>11661.0</td>\n",
         "      <td>13843.0</td>\n",
         "      <td>9761.0</td>\n",
         "      <td>12757.0</td>\n",
-       "      <td>11575</td>\n",
+       "      <td>11575.0</td>\n",
         "      <td>11919.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>11919.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>16</td>\n",
-       "      <td>24691</td>\n",
+       "      <th>16</th>\n",
+       "      <td>24691.0</td>\n",
         "      <td>10243.0</td>\n",
         "      <td>12639.0</td>\n",
         "      <td>11000.0</td>\n",
         "      <td>12310.0</td>\n",
         "      <td>10243.0</td>\n",
         "      <td>12639.0</td>\n",
         "      <td>11000.0</td>\n",
         "      <td>12310.0</td>\n",
-       "      <td>13061</td>\n",
+       "      <td>13061.0</td>\n",
         "      <td>11850.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>11850.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>17</td>\n",
-       "      <td>24303</td>\n",
+       "      <th>17</th>\n",
+       "      <td>24303.0</td>\n",
         "      <td>11452.0</td>\n",
         "      <td>11596.0</td>\n",
         "      <td>12356.0</td>\n",
         "      <td>11795.0</td>\n",
         "      <td>11452.0</td>\n",
         "      <td>11596.0</td>\n",
         "      <td>12356.0</td>\n",
         "      <td>11795.0</td>\n",
-       "      <td>12023</td>\n",
+       "      <td>12023.0</td>\n",
         "      <td>11844.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>11844.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>18</td>\n",
-       "      <td>20059</td>\n",
+       "      <th>18</th>\n",
+       "      <td>20059.0</td>\n",
         "      <td>12695.0</td>\n",
         "      <td>11538.0</td>\n",
         "      <td>10372.0</td>\n",
         "      <td>10401.0</td>\n",
         "      <td>12695.0</td>\n",
         "      <td>11538.0</td>\n",
         "      <td>10372.0</td>\n",
         "      <td>10401.0</td>\n",
-       "      <td>11586</td>\n",
+       "      <td>11586.0</td>\n",
         "      <td>11318.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>11318.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>19</td>\n",
-       "      <td>14428</td>\n",
+       "      <th>19</th>\n",
+       "      <td>14428.0</td>\n",
         "      <td>10361.0</td>\n",
         "      <td>9821.0</td>\n",
         "      <td>12114.0</td>\n",
         "      <td>12002.0</td>\n",
         "      <td>10361.0</td>\n",
         "      <td>9821.0</td>\n",
         "      <td>12114.0</td>\n",
         "      <td>12002.0</td>\n",
-       "      <td>10138</td>\n",
+       "      <td>10138.0</td>\n",
         "      <td>10887.2</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>10887.2</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>20</td>\n",
-       "      <td>16390</td>\n",
+       "      <th>20</th>\n",
+       "      <td>16390.0</td>\n",
         "      <td>11717.0</td>\n",
         "      <td>11386.0</td>\n",
         "      <td>11718.0</td>\n",
         "      <td>11222.0</td>\n",
         "      <td>11717.0</td>\n",
         "      <td>11386.0</td>\n",
         "      <td>11718.0</td>\n",
         "      <td>11222.0</td>\n",
-       "      <td>11692</td>\n",
+       "      <td>11692.0</td>\n",
         "      <td>11547.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>11547.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>21</td>\n",
-       "      <td>13839</td>\n",
+       "      <th>21</th>\n",
+       "      <td>13839.0</td>\n",
         "      <td>11653.0</td>\n",
         "      <td>10974.0</td>\n",
         "      <td>11431.0</td>\n",
         "      <td>11013.0</td>\n",
         "      <td>11653.0</td>\n",
         "      <td>10974.0</td>\n",
         "      <td>11431.0</td>\n",
         "      <td>11013.0</td>\n",
-       "      <td>11334</td>\n",
+       "      <td>11334.0</td>\n",
         "      <td>11281.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>11281.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>22</td>\n",
-       "      <td>11265</td>\n",
+       "      <th>22</th>\n",
+       "      <td>11265.0</td>\n",
         "      <td>9534.0</td>\n",
         "      <td>9397.0</td>\n",
         "      <td>9603.0</td>\n",
         "      <td>9192.0</td>\n",
         "      <td>9534.0</td>\n",
         "      <td>9397.0</td>\n",
         "      <td>9603.0</td>\n",
         "      <td>9192.0</td>\n",
-       "      <td>9514</td>\n",
+       "      <td>9514.0</td>\n",
         "      <td>9448.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>9448.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>23</td>\n",
-       "      <td>12106</td>\n",
+       "      <th>23</th>\n",
+       "      <td>12106.0</td>\n",
         "      <td>11461.0</td>\n",
         "      <td>11259.0</td>\n",
         "      <td>11134.0</td>\n",
         "      <td>11171.0</td>\n",
         "      <td>11461.0</td>\n",
         "      <td>11259.0</td>\n",
         "      <td>11134.0</td>\n",
         "      <td>11171.0</td>\n",
-       "      <td>11603</td>\n",
+       "      <td>11603.0</td>\n",
         "      <td>11325.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>11325.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>24</td>\n",
-       "      <td>11302</td>\n",
+       "      <th>24</th>\n",
+       "      <td>11302.0</td>\n",
         "      <td>10754.0</td>\n",
         "      <td>10535.0</td>\n",
         "      <td>10698.0</td>\n",
         "      <td>10673.0</td>\n",
         "      <td>10754.0</td>\n",
         "      <td>10535.0</td>\n",
         "      <td>10698.0</td>\n",
         "      <td>10673.0</td>\n",
-       "      <td>10858</td>\n",
+       "      <td>10858.0</td>\n",
         "      <td>10703.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>10703.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>25</td>\n",
-       "      <td>10694</td>\n",
+       "      <th>25</th>\n",
+       "      <td>10694.0</td>\n",
         "      <td>10807.0</td>\n",
         "      <td>10514.0</td>\n",
         "      <td>10930.0</td>\n",
         "      <td>10611.0</td>\n",
         "      <td>10807.0</td>\n",
         "      <td>10514.0</td>\n",
         "      <td>10930.0</td>\n",
         "      <td>10611.0</td>\n",
-       "      <td>10629</td>\n",
+       "      <td>10629.0</td>\n",
         "      <td>10698.2</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>10698.2</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>26</td>\n",
-       "      <td>10282</td>\n",
+       "      <th>26</th>\n",
+       "      <td>10282.0</td>\n",
         "      <td>10824.0</td>\n",
         "      <td>10529.0</td>\n",
         "      <td>10624.0</td>\n",
         "      <td>10526.0</td>\n",
         "      <td>10824.0</td>\n",
         "      <td>10529.0</td>\n",
         "      <td>10624.0</td>\n",
         "      <td>10526.0</td>\n",
-       "      <td>10525</td>\n",
+       "      <td>10525.0</td>\n",
         "      <td>10605.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>10605.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>27</td>\n",
-       "      <td>10412</td>\n",
+       "      <th>27</th>\n",
+       "      <td>10412.0</td>\n",
         "      <td>10328.0</td>\n",
         "      <td>10565.0</td>\n",
         "      <td>10565.0</td>\n",
         "      <td>10412.0</td>\n",
         "      <td>10328.0</td>\n",
         "      <td>10565.0</td>\n",
         "      <td>10565.0</td>\n",
         "      <td>10412.0</td>\n",
-       "      <td>10545</td>\n",
+       "      <td>10545.0</td>\n",
         "      <td>10483.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>10483.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>28</td>\n",
-       "      <td>9941</td>\n",
+       "      <th>28</th>\n",
+       "      <td>9941.0</td>\n",
         "      <td>10512.0</td>\n",
         "      <td>10467.0</td>\n",
         "      <td>10643.0</td>\n",
         "      <td>10647.0</td>\n",
         "      <td>10512.0</td>\n",
         "      <td>10467.0</td>\n",
         "      <td>10643.0</td>\n",
         "      <td>10647.0</td>\n",
-       "      <td>10278</td>\n",
+       "      <td>10278.0</td>\n",
         "      <td>10509.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>10509.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>29</td>\n",
-       "      <td>10096</td>\n",
+       "      <th>29</th>\n",
+       "      <td>10096.0</td>\n",
         "      <td>10324.0</td>\n",
         "      <td>10353.0</td>\n",
         "      <td>10426.0</td>\n",
         "      <td>10672.0</td>\n",
         "      <td>10324.0</td>\n",
         "      <td>10353.0</td>\n",
         "      <td>10426.0</td>\n",
         "      <td>10672.0</td>\n",
-       "      <td>10028</td>\n",
+       "      <td>10028.0</td>\n",
         "      <td>10360.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>10360.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>30</td>\n",
-       "      <td>10159</td>\n",
+       "      <th>30</th>\n",
+       "      <td>10159.0</td>\n",
         "      <td>10422.0</td>\n",
         "      <td>10356.0</td>\n",
         "      <td>10147.0</td>\n",
         "      <td>10612.0</td>\n",
         "      <td>10422.0</td>\n",
         "      <td>10356.0</td>\n",
         "      <td>10147.0</td>\n",
         "      <td>10612.0</td>\n",
-       "      <td>10021</td>\n",
+       "      <td>10021.0</td>\n",
         "      <td>10311.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>10311.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>31</td>\n",
-       "      <td>10262</td>\n",
+       "      <th>31</th>\n",
+       "      <td>10262.0</td>\n",
         "      <td>10564.0</td>\n",
         "      <td>10408.0</td>\n",
         "      <td>10239.0</td>\n",
         "      <td>10433.0</td>\n",
         "      <td>10564.0</td>\n",
         "      <td>10408.0</td>\n",
         "      <td>10239.0</td>\n",
         "      <td>10433.0</td>\n",
-       "      <td>9893</td>\n",
+       "      <td>9893.0</td>\n",
         "      <td>10307.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>10307.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>32</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>32</th>\n",
+       "      <td>10236.0</td>\n",
         "      <td>10406.0</td>\n",
         "      <td>10542.0</td>\n",
         "      <td>10278.0</td>\n",
         "      <td>10439.0</td>\n",
         "      <td>10406.0</td>\n",
         "      <td>10542.0</td>\n",
         "      <td>10278.0</td>\n",
         "      <td>10439.0</td>\n",
-       "      <td>10153</td>\n",
+       "      <td>10153.0</td>\n",
         "      <td>10363.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>10363.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>33</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>33</th>\n",
+       "      <td>10592.0</td>\n",
         "      <td>10405.0</td>\n",
         "      <td>10091.0</td>\n",
         "      <td>10569.0</td>\n",
         "      <td>10312.0</td>\n",
         "      <td>10405.0</td>\n",
         "      <td>10091.0</td>\n",
         "      <td>10569.0</td>\n",
         "      <td>10312.0</td>\n",
-       "      <td>10352</td>\n",
+       "      <td>10352.0</td>\n",
         "      <td>10345.8</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>10345.8</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>34</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>34</th>\n",
+       "      <td>10990.0</td>\n",
         "      <td>10279.0</td>\n",
         "      <td>10199.0</td>\n",
         "      <td>10698.0</td>\n",
         "      <td>10637.0</td>\n",
         "      <td>10279.0</td>\n",
         "      <td>10199.0</td>\n",
         "      <td>10698.0</td>\n",
         "      <td>10637.0</td>\n",
-       "      <td>10354</td>\n",
+       "      <td>10354.0</td>\n",
         "      <td>10433.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>10433.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>35</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>35</th>\n",
+       "      <td>10364.0</td>\n",
         "      <td>9478.0</td>\n",
         "      <td>9046.0</td>\n",
         "      <td>9372.0</td>\n",
         "      <td>9226.0</td>\n",
         "      <td>9478.0</td>\n",
         "      <td>9046.0</td>\n",
         "      <td>9372.0</td>\n",
         "      <td>9226.0</td>\n",
-       "      <td>10239</td>\n",
+       "      <td>10239.0</td>\n",
         "      <td>9472.2</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>9472.2</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>36</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>36</th>\n",
+       "      <td>9023.0</td>\n",
         "      <td>10918.0</td>\n",
         "      <td>10680.0</td>\n",
         "      <td>10781.0</td>\n",
         "      <td>10681.0</td>\n",
         "      <td>10918.0</td>\n",
         "      <td>10680.0</td>\n",
         "      <td>10781.0</td>\n",
         "      <td>10681.0</td>\n",
-       "      <td>9092</td>\n",
+       "      <td>9092.0</td>\n",
         "      <td>10430.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>10430.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>37</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>37</th>\n",
+       "      <td>11176.0</td>\n",
         "      <td>10892.0</td>\n",
         "      <td>10496.0</td>\n",
         "      <td>10692.0</td>\n",
         "      <td>10401.0</td>\n",
         "      <td>10892.0</td>\n",
         "      <td>10496.0</td>\n",
         "      <td>10692.0</td>\n",
         "      <td>10401.0</td>\n",
-       "      <td>10573</td>\n",
+       "      <td>10573.0</td>\n",
         "      <td>10610.8</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>10610.8</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>38</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>38</th>\n",
+       "      <td>10797.0</td>\n",
         "      <td>10792.0</td>\n",
         "      <td>10498.0</td>\n",
         "      <td>10875.0</td>\n",
         "      <td>10183.0</td>\n",
         "      <td>10792.0</td>\n",
         "      <td>10498.0</td>\n",
         "      <td>10875.0</td>\n",
         "      <td>10183.0</td>\n",
-       "      <td>10381</td>\n",
+       "      <td>10381.0</td>\n",
         "      <td>10545.8</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>10545.8</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>39</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>39</th>\n",
+       "      <td>10890.0</td>\n",
         "      <td>10954.0</td>\n",
         "      <td>10463.0</td>\n",
         "      <td>11027.0</td>\n",
         "      <td>10278.0</td>\n",
         "      <td>10954.0</td>\n",
         "      <td>10463.0</td>\n",
         "      <td>11027.0</td>\n",
         "      <td>10278.0</td>\n",
-       "      <td>10826</td>\n",
+       "      <td>10826.0</td>\n",
         "      <td>10709.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>10709.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>40</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>40</th>\n",
+       "      <td>11468.0</td>\n",
         "      <td>11113.0</td>\n",
         "      <td>10869.0</td>\n",
         "      <td>11101.0</td>\n",
         "      <td>10671.0</td>\n",
         "      <td>11113.0</td>\n",
         "      <td>10869.0</td>\n",
         "      <td>11101.0</td>\n",
         "      <td>10671.0</td>\n",
-       "      <td>10700</td>\n",
+       "      <td>10700.0</td>\n",
         "      <td>10890.8</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>10890.8</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>41</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>41</th>\n",
+       "      <td>11373.0</td>\n",
         "      <td>11403.0</td>\n",
         "      <td>11048.0</td>\n",
         "      <td>11357.0</td>\n",
         "      <td>11016.0</td>\n",
         "      <td>11403.0</td>\n",
         "      <td>11048.0</td>\n",
         "      <td>11357.0</td>\n",
         "      <td>11016.0</td>\n",
-       "      <td>11108</td>\n",
+       "      <td>11108.0</td>\n",
         "      <td>11186.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>11186.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>42</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>42</th>\n",
+       "      <td>11943.0</td>\n",
         "      <td>11625.0</td>\n",
         "      <td>11177.0</td>\n",
         "      <td>11389.0</td>\n",
         "      <td>11134.0</td>\n",
         "      <td>11625.0</td>\n",
         "      <td>11177.0</td>\n",
         "      <td>11389.0</td>\n",
         "      <td>11134.0</td>\n",
-       "      <td>10799</td>\n",
+       "      <td>10799.0</td>\n",
         "      <td>11224.8</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>11224.8</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>43</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>43</th>\n",
+       "      <td>12317.0</td>\n",
         "      <td>11415.0</td>\n",
         "      <td>10885.0</td>\n",
         "      <td>11152.0</td>\n",
         "      <td>11048.0</td>\n",
         "      <td>11415.0</td>\n",
         "      <td>10885.0</td>\n",
         "      <td>11152.0</td>\n",
         "      <td>11048.0</td>\n",
-       "      <td>10966</td>\n",
+       "      <td>10966.0</td>\n",
         "      <td>11093.2</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>11093.2</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>44</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>44</th>\n",
+       "      <td>12517.0</td>\n",
         "      <td>11567.0</td>\n",
         "      <td>10866.0</td>\n",
         "      <td>11366.0</td>\n",
         "      <td>11463.0</td>\n",
         "      <td>11567.0</td>\n",
         "      <td>10866.0</td>\n",
         "      <td>11366.0</td>\n",
         "      <td>11463.0</td>\n",
-       "      <td>11026</td>\n",
+       "      <td>11026.0</td>\n",
         "      <td>11257.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>11257.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>45</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>45</th>\n",
+       "      <td>13448.0</td>\n",
         "      <td>12177.0</td>\n",
         "      <td>11588.0</td>\n",
         "      <td>11767.0</td>\n",
         "      <td>11803.0</td>\n",
         "      <td>12177.0</td>\n",
         "      <td>11588.0</td>\n",
         "      <td>11767.0</td>\n",
         "      <td>11803.0</td>\n",
-       "      <td>11312</td>\n",
+       "      <td>11312.0</td>\n",
         "      <td>11729.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>11729.4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>46</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>46</th>\n",
+       "      <td>13798.0</td>\n",
         "      <td>12146.0</td>\n",
         "      <td>11552.0</td>\n",
         "      <td>11773.0</td>\n",
         "      <td>12209.0</td>\n",
         "      <td>12146.0</td>\n",
         "      <td>11552.0</td>\n",
         "      <td>11773.0</td>\n",
         "      <td>12209.0</td>\n",
-       "      <td>11338</td>\n",
+       "      <td>11338.0</td>\n",
         "      <td>11803.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>11803.6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>47</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>47</th>\n",
+       "      <td>14291.0</td>\n",
         "      <td>12472.0</td>\n",
         "      <td>11289.0</td>\n",
         "      <td>12102.0</td>\n",
         "      <td>12064.0</td>\n",
         "      <td>12472.0</td>\n",
         "      <td>11289.0</td>\n",
         "      <td>12102.0</td>\n",
         "      <td>12064.0</td>\n",
-       "      <td>11178</td>\n",
+       "      <td>11178.0</td>\n",
         "      <td>11821.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>11821.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>48</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>48</th>\n",
+       "      <td>14132.0</td>\n",
         "      <td>12455.0</td>\n",
         "      <td>11392.0</td>\n",
         "      <td>12046.0</td>\n",
         "      <td>11901.0</td>\n",
         "      <td>12455.0</td>\n",
         "      <td>11392.0</td>\n",
         "      <td>12046.0</td>\n",
         "      <td>11901.0</td>\n",
-       "      <td>11216</td>\n",
+       "      <td>11216.0</td>\n",
         "      <td>11802.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>11802.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>49</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>49</th>\n",
+       "      <td>13986.0</td>\n",
         "      <td>12275.0</td>\n",
         "      <td>11687.0</td>\n",
         "      <td>12342.0</td>\n",
         "      <td>12733.0</td>\n",
         "      <td>12275.0</td>\n",
         "      <td>11687.0</td>\n",
         "      <td>12342.0</td>\n",
         "      <td>12733.0</td>\n",
-       "      <td>11748</td>\n",
+       "      <td>11748.0</td>\n",
         "      <td>12157.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>12157.0</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>50</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>50</th>\n",
+       "      <td>13942.0</td>\n",
         "      <td>12853.0</td>\n",
         "      <td>12078.0</td>\n",
         "      <td>12924.0</td>\n",
         "      <td>12076.0</td>\n",
         "      <td>12853.0</td>\n",
         "      <td>12078.0</td>\n",
         "      <td>12924.0</td>\n",
         "      <td>12076.0</td>\n",
-       "      <td>11713</td>\n",
+       "      <td>11713.0</td>\n",
         "      <td>12328.8</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>12328.8</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>51</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>51</th>\n",
+       "      <td>14658.0</td>\n",
         "      <td>13566.0</td>\n",
         "      <td>12649.0</td>\n",
         "      <td>14308.0</td>\n",
         "      <td>13137.0</td>\n",
         "      <td>13566.0</td>\n",
         "      <td>12649.0</td>\n",
         "      <td>14308.0</td>\n",
         "      <td>13137.0</td>\n",
-       "      <td>12136</td>\n",
+       "      <td>12136.0</td>\n",
         "      <td>13159.2</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <td>13159.2</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-       "      <td>52</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>52</th>\n",
+       "      <td>13035.0</td>\n",
         "      <td>8727.0</td>\n",
         "      <td>8384.0</td>\n",
         "      <td>9904.0</td>\n",
         "      <td>9335.0</td>\n",
         "      <td>8727.0</td>\n",
         "      <td>8384.0</td>\n",
         "      <td>9904.0</td>\n",
         "      <td>9335.0</td>\n",
-       "      <td>9806</td>\n",
+       "      <td>9806.0</td>\n",
         "      <td>9231.2</td>\n",
         "    </tr>\n",
         "      <td>9231.2</td>\n",
         "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
         "</div>"
        ],
        "text/plain": [
         "   total_2020  total_2019  total_2018  total_2017  total_2016  total_2015  \\\n",
         "  </tbody>\n",
         "</table>\n",
         "</div>"
        ],
        "text/plain": [
         "   total_2020  total_2019  total_2018  total_2017  total_2016  total_2015  \\\n",
-       "1       13768     12424.0     14701.0     13612.0     14863.0       13751   \n",
-       "2       16020     14487.0     17430.0     15528.0     13154.0       18318   \n",
-       "3       14723     13545.0     16355.0     15231.0     13060.0       16738   \n",
-       "4       13429     13283.0     15971.0     14461.0     12859.0       15712   \n",
-       "5       13123     12799.0     15087.0     14188.0     12571.0       14560   \n",
-       "6       12534     13222.0     14111.0     13805.0     12697.0       13730   \n",
-       "7       12412     13347.0     13925.0     13212.0     12016.0       13510   \n",
-       "8       12300     12877.0     13753.0     13330.0     12718.0       13071   \n",
-       "9       12334     12479.0     12190.0     12819.0     12733.0       13181   \n",
-       "10      12415     12396.0     14859.0     12580.0     12493.0       13007   \n",
-       "11      12499     12018.0     14367.0     12089.0     12489.0       12475   \n",
-       "12      12112     11797.0     13397.0     11833.0     10983.0       12027   \n",
-       "13      12507     11260.0     11310.0     11453.0     11738.0       11987   \n",
-       "14      18565     11445.0     12272.0     11305.0     13060.0       10325   \n",
-       "15      20929     11661.0     13843.0      9761.0     12757.0       11575   \n",
-       "16      24691     10243.0     12639.0     11000.0     12310.0       13061   \n",
-       "17      24303     11452.0     11596.0     12356.0     11795.0       12023   \n",
-       "18      20059     12695.0     11538.0     10372.0     10401.0       11586   \n",
-       "19      14428     10361.0      9821.0     12114.0     12002.0       10138   \n",
-       "20      16390     11717.0     11386.0     11718.0     11222.0       11692   \n",
-       "21      13839     11653.0     10974.0     11431.0     11013.0       11334   \n",
-       "22      11265      9534.0      9397.0      9603.0      9192.0        9514   \n",
-       "23      12106     11461.0     11259.0     11134.0     11171.0       11603   \n",
-       "24      11302     10754.0     10535.0     10698.0     10673.0       10858   \n",
-       "25      10694     10807.0     10514.0     10930.0     10611.0       10629   \n",
-       "26      10282     10824.0     10529.0     10624.0     10526.0       10525   \n",
-       "27      10412     10328.0     10565.0     10565.0     10412.0       10545   \n",
-       "28       9941     10512.0     10467.0     10643.0     10647.0       10278   \n",
-       "29      10096     10324.0     10353.0     10426.0     10672.0       10028   \n",
-       "30      10159     10422.0     10356.0     10147.0     10612.0       10021   \n",
-       "31      10262     10564.0     10408.0     10239.0     10433.0        9893   \n",
-       "32        NaN     10406.0     10542.0     10278.0     10439.0       10153   \n",
-       "33        NaN     10405.0     10091.0     10569.0     10312.0       10352   \n",
-       "34        NaN     10279.0     10199.0     10698.0     10637.0       10354   \n",
-       "35        NaN      9478.0      9046.0      9372.0      9226.0       10239   \n",
-       "36        NaN     10918.0     10680.0     10781.0     10681.0        9092   \n",
-       "37        NaN     10892.0     10496.0     10692.0     10401.0       10573   \n",
-       "38        NaN     10792.0     10498.0     10875.0     10183.0       10381   \n",
-       "39        NaN     10954.0     10463.0     11027.0     10278.0       10826   \n",
-       "40        NaN     11113.0     10869.0     11101.0     10671.0       10700   \n",
-       "41        NaN     11403.0     11048.0     11357.0     11016.0       11108   \n",
-       "42        NaN     11625.0     11177.0     11389.0     11134.0       10799   \n",
-       "43        NaN     11415.0     10885.0     11152.0     11048.0       10966   \n",
-       "44        NaN     11567.0     10866.0     11366.0     11463.0       11026   \n",
-       "45        NaN     12177.0     11588.0     11767.0     11803.0       11312   \n",
-       "46        NaN     12146.0     11552.0     11773.0     12209.0       11338   \n",
-       "47        NaN     12472.0     11289.0     12102.0     12064.0       11178   \n",
-       "48        NaN     12455.0     11392.0     12046.0     11901.0       11216   \n",
-       "49        NaN     12275.0     11687.0     12342.0     12733.0       11748   \n",
-       "50        NaN     12853.0     12078.0     12924.0     12076.0       11713   \n",
-       "51        NaN     13566.0     12649.0     14308.0     13137.0       12136   \n",
-       "52        NaN      8727.0      8384.0      9904.0      9335.0        9806   \n",
+       "1     13768.0     12424.0     14701.0     13612.0     14863.0     13751.0   \n",
+       "2     16020.0     14487.0     17430.0     15528.0     13154.0     18318.0   \n",
+       "3     14723.0     13545.0     16355.0     15231.0     13060.0     16738.0   \n",
+       "4     13429.0     13283.0     15971.0     14461.0     12859.0     15712.0   \n",
+       "5     13123.0     12799.0     15087.0     14188.0     12571.0     14560.0   \n",
+       "6     12534.0     13222.0     14111.0     13805.0     12697.0     13730.0   \n",
+       "7     12412.0     13347.0     13925.0     13212.0     12016.0     13510.0   \n",
+       "8     12300.0     12877.0     13753.0     13330.0     12718.0     13071.0   \n",
+       "9     12334.0     12479.0     12190.0     12819.0     12733.0     13181.0   \n",
+       "10    12415.0     12396.0     14859.0     12580.0     12493.0     13007.0   \n",
+       "11    12499.0     12018.0     14367.0     12089.0     12489.0     12475.0   \n",
+       "12    12112.0     11797.0     13397.0     11833.0     10983.0     12027.0   \n",
+       "13    12507.0     11260.0     11310.0     11453.0     11738.0     11987.0   \n",
+       "14    18565.0     11445.0     12272.0     11305.0     13060.0     10325.0   \n",
+       "15    20929.0     11661.0     13843.0      9761.0     12757.0     11575.0   \n",
+       "16    24691.0     10243.0     12639.0     11000.0     12310.0     13061.0   \n",
+       "17    24303.0     11452.0     11596.0     12356.0     11795.0     12023.0   \n",
+       "18    20059.0     12695.0     11538.0     10372.0     10401.0     11586.0   \n",
+       "19    14428.0     10361.0      9821.0     12114.0     12002.0     10138.0   \n",
+       "20    16390.0     11717.0     11386.0     11718.0     11222.0     11692.0   \n",
+       "21    13839.0     11653.0     10974.0     11431.0     11013.0     11334.0   \n",
+       "22    11265.0      9534.0      9397.0      9603.0      9192.0      9514.0   \n",
+       "23    12106.0     11461.0     11259.0     11134.0     11171.0     11603.0   \n",
+       "24    11302.0     10754.0     10535.0     10698.0     10673.0     10858.0   \n",
+       "25    10694.0     10807.0     10514.0     10930.0     10611.0     10629.0   \n",
+       "26    10282.0     10824.0     10529.0     10624.0     10526.0     10525.0   \n",
+       "27    10412.0     10328.0     10565.0     10565.0     10412.0     10545.0   \n",
+       "28     9941.0     10512.0     10467.0     10643.0     10647.0     10278.0   \n",
+       "29    10096.0     10324.0     10353.0     10426.0     10672.0     10028.0   \n",
+       "30    10159.0     10422.0     10356.0     10147.0     10612.0     10021.0   \n",
+       "31    10262.0     10564.0     10408.0     10239.0     10433.0      9893.0   \n",
+       "32    10236.0     10406.0     10542.0     10278.0     10439.0     10153.0   \n",
+       "33    10592.0     10405.0     10091.0     10569.0     10312.0     10352.0   \n",
+       "34    10990.0     10279.0     10199.0     10698.0     10637.0     10354.0   \n",
+       "35    10364.0      9478.0      9046.0      9372.0      9226.0     10239.0   \n",
+       "36     9023.0     10918.0     10680.0     10781.0     10681.0      9092.0   \n",
+       "37    11176.0     10892.0     10496.0     10692.0     10401.0     10573.0   \n",
+       "38    10797.0     10792.0     10498.0     10875.0     10183.0     10381.0   \n",
+       "39    10890.0     10954.0     10463.0     11027.0     10278.0     10826.0   \n",
+       "40    11468.0     11113.0     10869.0     11101.0     10671.0     10700.0   \n",
+       "41    11373.0     11403.0     11048.0     11357.0     11016.0     11108.0   \n",
+       "42    11943.0     11625.0     11177.0     11389.0     11134.0     10799.0   \n",
+       "43    12317.0     11415.0     10885.0     11152.0     11048.0     10966.0   \n",
+       "44    12517.0     11567.0     10866.0     11366.0     11463.0     11026.0   \n",
+       "45    13448.0     12177.0     11588.0     11767.0     11803.0     11312.0   \n",
+       "46    13798.0     12146.0     11552.0     11773.0     12209.0     11338.0   \n",
+       "47    14291.0     12472.0     11289.0     12102.0     12064.0     11178.0   \n",
+       "48    14132.0     12455.0     11392.0     12046.0     11901.0     11216.0   \n",
+       "49    13986.0     12275.0     11687.0     12342.0     12733.0     11748.0   \n",
+       "50    13942.0     12853.0     12078.0     12924.0     12076.0     11713.0   \n",
+       "51    14658.0     13566.0     12649.0     14308.0     13137.0     12136.0   \n",
+       "52    13035.0      8727.0      8384.0      9904.0      9335.0      9806.0   \n",
+       "53        NaN         NaN         NaN         NaN         NaN         NaN   \n",
         "\n",
         "    previous_mean  \n",
         "1         13870.2  \n",
         "\n",
         "    previous_mean  \n",
         "1         13870.2  \n",
@@ -6867,10 +8266,11 @@
         "49        12157.0  \n",
         "50        12328.8  \n",
         "51        13159.2  \n",
         "49        12157.0  \n",
         "50        12328.8  \n",
         "51        13159.2  \n",
-       "52         9231.2  "
+       "52         9231.2  \n",
+       "53            NaN  "
        ]
       },
        ]
       },
-     "execution_count": 114,
+     "execution_count": 41,
       "metadata": {},
       "output_type": "execute_result"
      }
       "metadata": {},
       "output_type": "execute_result"
      }
@@ -6886,22 +8286,24 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 115,
-   "metadata": {},
+   "execution_count": 109,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
        "text/plain": [
     "outputs": [
      {
       "data": {
        "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f547de0af50>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f9b5d140cd0>"
        ]
       },
        ]
       },
-     "execution_count": 115,
+     "execution_count": 109,
       "metadata": {},
       "output_type": "execute_result"
      },
      {
       "data": {
       "metadata": {},
       "output_type": "execute_result"
      },
      {
       "data": {
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\n",
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9vbX2F9c5/xf0dIwrAVqArwJYa2uNMeuBE67zvmetrXV9fgz4CRAC7HP9EZGbxIcfX6G9s5sULwWhT0WFYoxmhERERMR3Bg1C1toj9P8eT99zEvt8tsAT1znveeD5fsZPAqmD1SIivuGscHWM89LSuOAAB9MjQ7ioGSERERHxEY/eERKRic1Z2RNYvDUjBJAYHcrFGs0IiYiIjIa6ujqeffbZAc8pLS3lhRdeGPRepaWlpKZefw4jPz+frKws0tLSyMrK4tChQ73HTp06RVpaGikpKaxZswb3nqa7d+9m9uzZ+Pn50Xev0I6ODlavXk1aWhqzZs1iw4YNg9bnKQUhERmUs6KR6ZHBTAoafsc4t6ToMC5WNfX+B1BERERGjjeD0GCio6N57bXXOHv2LNu3b2fVqlW9xx577DG2bduG0+nE6XSyf/9+AFJTU3nppZfIycm56l67d++mra2Ns2fPcurUKf7jP/6D0tLSYdcIQ9xHSEQmJmdlk9eWxbklRoXR0NrJxy0dTA0L9Oq9RUREbmZPv/0079W+59V73jH1DtbOX3vd4+vWreP8+fNkZmaydOlSAPbt24cxhqeeeooHHniAdevWUVRURGZmJqtXr2bFihWsWrWK5uaeTdC3bNnCokWLBq1lzpw5vZ9nz55Na2srbW1t1NbW0tDQwMKFCwF46KGHePnll8nLy2PWrFn93ssYQ3NzM52dnVy5coXAwEAiIiI8/l4GoiAkIgPq6raUVDaxcEaUV+/r7hx3sbpZQUhERGSEbdy4kXfffZeCggL27NnD1q1bOXPmDNXV1cybN4+cnBw2btzIM888w+uvvw5AS0sL+fn5BAcH43Q6Wbly5VXL1jyxZ88e5syZQ1BQEOXl5SQk/GHXnISEBMrLywe8/v777+eVV14hPj6elpYWNm/ezNSpU4f+BfRDQUhEBlT+8RXaOruZGeu994Og715CzWR9aopX7y0iInIzG2jmZjQcOXKElStX4nA4iI2NZfHixZw4ceKamZaOjg6efPJJCgoKcDgcFBcXD+k5hYWFrF27loMHDwL0uxy+Z/ec63v77bdxOBx89NFHfPzxx9x99918/vOfZ8aMGUOqpT8KQiIyIGdlT8e4lBjvLo27dWooDj/Dxepmr95XREREBubp+7mbN28mNjaWM2fO0N3dTXBwsMfPKCsrY8WKFezYsYPk5GSgZwaorKzsqnOmT58+4H1eeOEF7r33XgICAoiJiSE7O5uTJ096JQipWYKIDGgkOsYBBDj8uHVKCBdrFIRERERGWnh4OI2NPX+5mZOTw65du+jq6qKqqorDhw8zf/78q84BqK+vJz4+Hj8/P3bu3ElXV5dHz6qrq2PZsmVs2LCB7Ozs3vH4+HjCw8M5fvw41lp27NjB8uXLB7zXbbfdxqFDh7DW0tzczPHjx7njjjtu4Bu4loKQiAyouKKR2IggIkMCvH7vxOgwLlYpCImIiIy0qKgosrOzSU1N5dixY6Snp5ORkcGSJUvYtGkTcXFxpKen4+/vT0ZGBps3b+bxxx9n+/btLFiwgOLiYsLCwjx61pYtWygpKWH9+vVkZmaSmZlJZWUlAM899xyPPPIIKSkpJCcnk5eXB8DevXtJSEjg2LFjLFu2jNzcXACeeOIJmpqaSE1NZd68eXz1q18lPT3dK9+JGauta+fOnWuH+rKWiAzdl7YcITIkgJ1/+Rmv3/t/v1rI/5z8kMJ/yh10jbCIiMhYVlRUdN3OaOId/X3HxphT1tq5/Z2vGSERua5uV8c4by+Lc5sxLYyW9i6qGttG5P4iIiIi16NmCSJyXR/VX6GlvYuZXm6U4JYY1TPFfqG6mZgIz1/AFBEREd87cOAAa9de3QEvKSmJvXv3+qiioVEQEpHrcjdK8HbrbLe+LbQXeHmfIhERERlZubm5ve/yjEVaGici11VS4eoYN21kgtD0ySEEOvzUOU5ERERGnYKQiFxXcUUj0ZOCmBIWOCL3d/gZbosKVec4ERERGXUKQiJyXc7KJm4foWVxbolRYZRqRkhERERGmYKQiPTL2p6OcTNHqGOc24xpYZTWtNDdPTZb+YuIiMjYpCAkIv263NBKU1snKbEj0zHOLTEqjPbObj6qvzKizxEREZnI6urqePbZZwc8p7S0lBdeeGHQe5WWlpKamnrd4/n5+WRlZZGWlkZWVhaHDh3qPXbq1CnS0tJISUlhzZo1uPc03b17N7Nnz8bPz4++e4X+9Kc/7d2UNTMzEz8/PwoKCgat0RMKQiLSL6erUcJIzwj9oXNcy4g+R0REZCLzZhAaTHR0NK+99hpnz55l+/btrFq1qvfYY489xrZt23A6nTidTvbv3w9AamoqL730Ejk5OVfd6ytf+QoFBQUUFBSwc+dOEhMTyczMHHaNoPbZInIdva2zRykIXaxu4rMzo0f0WSIiIjeDy//8z7QVvefVewbNuoO4v//76x5ft24d58+fJzMzk6VLlwKwb98+jDE89dRTPPDAA6xbt46ioiIyMzNZvXo1K1asYNWqVTQ397zLu2XLFhYtWjRoLXPmzOn9PHv2bFpbW2lra6O2tpaGhgYWLlwIwEMPPcTLL79MXl4es2bNGvS+P/vZz1i5cuWg53lKQUhE+uWsaGRqWCBRk4JG9DmxEUGEBDi4qBkhERGREbNx40beffddCgoK2LNnD1u3buXMmTNUV1czb948cnJy2LhxI8888wyvv/46AC0tLeTn5xMcHIzT6WTlypVXLVvzxJ49e5gzZw5BQUGUl5eTkJDQeywhIYHy8nKP77Vr1y5eeeWVIT1/IApCItIv5yg0SgAwxpAYrc5xIiIycQw0czMajhw5wsqVK3E4HMTGxrJ48WJOnDhBRETEVed1dHTw5JNPUlBQgMPhoLi4eEjPKSwsZO3atRw8eBCg932gvowxHt3rrbfeIjQ0dMB3k4ZKQUhErmGtxVnRyJcyp4/K85KiQym61DgqzxIREZno+gsk/dm8eTOxsbGcOXOG7u5ugoODPX5GWVkZK1asYMeOHSQnJwM9M0BlZWVXnTN9ume/a7z44oteXRYHapYgIv2oamyjobWTmTEj2zHOLTEqjA9rW+jo6h6V54mIiEw04eHhNDb2/KVjTk4Ou3btoquri6qqKg4fPsz8+fOvOgegvr6e+Ph4/Pz82LlzJ11dXR49q66ujmXLlrFhwways7N7x+Pj4wkPD+f48eNYa9mxYwfLly8f9H7d3d3s3r2bBx98cIg/9cAUhETkGqPVKMEtKTqMzm5L2cdqoS0iIjISoqKiyM7OJjU1lWPHjpGenk5GRgZLlixh06ZNxMXFkZ6ejr+/PxkZGWzevJnHH3+c7du3s2DBAoqLiwkLC/PoWVu2bKGkpIT169f3tr2urKwE4LnnnuORRx4hJSWF5ORk8vLyANi7dy8JCQkcO3aMZcuWkZub23u/w4cPk5CQwIwZM7z6nRhPp8ZuNnPnzrVDfVlLRDzzk6MX+d+vnePtf7iHmHDPp8Fv1MnSWu7feowfPzyPz90RM+LPExERGW1FRUUedUaTG9ffd2yMOWWtndvf+ZoREpFrFFc2ERkSwLQR7hjn9ocW2mqYICIiIqNDzRJE5BolFU3cHjvJ404uwzU1LJDwYH8FIRERkTHkwIEDrF279qqxpKQk9u7d66OKhkZBSESuYq2luLKRvNT4UXumMYYktdAWEREZU3Jzc696l2es0dI4EblKTXM7dS0do9YowS0pOkwzQiIiIjJqFIRE5CrOClfHuNjRDUKJUWGU112htcOz1pwiIiIiw6EgJCJXKans2T9gtPYQckuKDsNa+LC2ZVSfKyIiIhOTgpCIXKW4oonwIH9iI0anY5ybu3PcBS2PExERkVGgICQiV3FWNjJzFDvGuSW6glCpgpCIiIjX1dXV8eyzzw54TmlpKS+88MKg9yotLSU1NfW6x/Pz88nKyiItLY2srCwOHTrUe+zUqVOkpaWRkpLCmjVrcO9punv3bmbPno2fnx+f3Cv0nXfeYeHChcyePZu0tDRaW1sHrdETCkIicpWSyqZRXxYHEBkSQFRYoDrHiYiIjABvBqHBREdH89prr3H27Fm2b9/OqlWreo899thjbNu2DafTidPpZP/+/QCkpqby0ksvkZOTc9W9Ojs7+Yu/+Au2bt1KYWEhv/71rwkICBh2jaD22SLSR21zO9VN7aPeKMEtMTqMC1UKQiIiMr799n+Kqf6wyav3jL51End/+fbrHl+3bh3nz58nMzOTpUuXArBv3z6MMTz11FM88MADrFu3jqKiIjIzM1m9ejUrVqxg1apVNDf3/H/zli1bWLRo0aC1zJkzp/fz7NmzaW1tpa2tjdraWhoaGli4cCEADz30EC+//DJ5eXnMmjWr33sdPHiQ9PR0MjIyAIiKivLsC/GAgpCI9Cqp7PmPcsoot852S4wK40hJlU+eLSIiMp5t3LiRd999l4KCAvbs2cPWrVs5c+YM1dXVzJs3j5ycHDZu3MgzzzzD66+/DkBLSwv5+fkEBwfjdDpZuXLlNcvWBrNnzx7mzJlDUFAQ5eXlJCQk9B5LSEigvLx8wOuLi4sxxpCbm0tVVRUPPvgg3/nOd4b+BfRDQUhEejndHeNiR39pHMCMaWHsOV1Gc1snYUH6z5OIiIxPA83cjIYjR46wcuVKHA4HsbGxLF68mBMnThAREXHVeR0dHTz55JMUFBTgcDgoLi4e0nMKCwtZu3YtBw8eBOh9H6ivwd5J7uzs5MiRI5w4cYLQ0FDuuecesrKyuOeee4ZUS3/0jpCI9HJWNBEW6GB6ZLBPnp8Y5WqYoPeERERERkx/gaQ/mzdvJjY2ljNnznDy5Ena29s9fkZZWRkrVqxgx44dJCcnAz0zQGVlZVedM3369AHvk5CQwOLFi4mOjiY0NJQvfvGLnD592uM6BqIgJCK9nJWNpMSGj3rHOLfE6FAASqu1l5CIiIg3hYeH09jYs/IjJyeHXbt20dXVRVVVFYcPH2b+/PlXnQNQX19PfHw8fn5+7Ny5k64uzzY9r6urY9myZWzYsIHs7Oze8fj4eMLDwzl+/DjWWnbs2MHy5csHvFdubi7vvPMOLS0tdHZ28pvf/IY777zzBr6Baw0ahIwxtxpjfmWMKTLGFBpjvuEa/xdjzHvGmHeMMXuNMZP7XPNdY0yJMeb3xpjcPuP3usZKjDHr+ownGWPeMsY4jTG7jDGBXvnpRGRInBVNzPTR+0Hwhxmhi9XefYFURERkoouKiiI7O5vU1FSOHTvW24BgyZIlbNq0ibi4ONLT0/H39ycjI4PNmzfz+OOPs337dhYsWEBxcTFhYWEePWvLli2UlJSwfv16MjMzyczMpLKyEoDnnnuORx55hJSUFJKTk8nLywNg7969JCQkcOzYMZYtW0Zubk+EmDJlCn/zN3/DvHnzyMzM5K677mLZsmVe+U7MYFNjxph4IN5ae9oYEw6cAu4DEoBD1tpOY8zTANbatcaYO4GfAfOB6cAvAfdCyGJgKVAGnABWWmvPGWP+B3jJWvuiMWYrcMZa+9xAdc2dO9cO9WUtEbm++pYOMr53kO/m3cH/vTjZZ3V85p9/yWdTpvGDL2f4rAYRERFvKyoqum5nNPGO/r5jY8wpa+3c/s4fdEbIWnvJWnva9bkRKAJusdYetNZ2uk47Tk8wAlgOvGitbbPWXgRK6AlF84ESa+0Fa2078CKw3PSswVkC/Nx1/XZ6gpaIjKKSKnejBN/NCAEkRYfpHSEREREZcUNqy2SMSQTmAG994tDXgF2uz7fQE4zcylxjAB9+YvwzQBRQ1ydU9T1fREaJs6JnOZovNlPtKyk6jAOFFT6tQURERAZ34MAB1q5de9VYUlISe/fu9VFFQ+NxEDLGTAL2AN+01jb0Gf8HoBP4qXuon8st/c8+2QHO76+GR4FHAW677TZPSxcRDzgrmwgJcHDL5BCf1pEYFUZtczv1VzqIDPHOztEiIiLifbm5ub3v8oxFHnWNM8YE0BOCfmqtfanP+Grgj4Gv2D+8bFQG3Nrn8gTgowHGq4HJxhj/T4xfw1q7zVo711o7d9q0aZ6ULiIeKq5oJCVmEn5+vukY55YU7WqhXa3lcSIiIjJyPOkaZ4D/AoqstT/sM9TEFw8AACAASURBVH4vsBb4krW2b6/bV4EHjTFBxpgkYCbwNj3NEWa6OsQFAg8Cr7oC1K+A+13XrwZeGf6PJiJDUVLp245xbu4gdFFBSEREREaQJ0vjsoFVwFljTIFr7O+BHwFBQL5rz5Hj1tqvW2sLXV3gztGzZO4Ja20XgDHmSeAA4ACet9YWuu63FnjRGPP/Ar+jJ3iJyChpbO3gUn0rKT5ulABw69RQjFEQEhERkZE1aBCy1h6h//d4fjHANd8Hvt/P+C/6u85ae4GernIi4gMllTdHowSAYNd7SgpCIiIiMpI8ekdIRMY3Z28Q8v2MEKiFtoiIiLfV1dXx7LPPDnhOaWkpL7zwwqD3Ki0tJTU19brH8/PzycrKIi0tjaysLA4dOtR77NSpU6SlpZGSksKaNWtwtxnYvXs3s2fPxs/Pj757hZaWlhISEtK7MevXv/71QevzlIKQiFBS2USQvx+3Tg31dSlATxC6WN2MHWTDZxEREfGMN4PQYKKjo3nttdc4e/Ys27dvZ9WqVb3HHnvsMbZt24bT6cTpdLJ//34AUlNTeemll8jJybnmfsnJyRQUFFBQUMDWrVuHXZ/bkPYREpHxqbiikeRpk3D4uGOcW2JUGI2tndQ0txM9KcjX5YiIiHjVr36yjcr3L3j1njGfmsHnHn70usfXrVvH+fPnyczMZOnSpQDs27cPYwxPPfUUDzzwAOvWraOoqIjMzExWr17NihUrWLVqFc3NPas0tmzZwqJFiwatZc6cOb2fZ8+eTWtrK21tbdTW1tLQ0MDChQsBeOihh3j55ZfJy8tj1qxZw/nxb4hmhEQEZ0UTM2+CRgluaqEtIiLiXRs3buydWVmwYAEFBQWcOXOGX/7yl3z729/m0qVLbNy4kbvvvpuCggK+9a1vERMTQ35+PqdPn2bXrl2sWbNmyM/ds2cPc+bMISgoiPLychISEnqPJSQkUF5ePug9Ll68yJw5c1i8eDG//e1vh1zD9WhGSGSCa27rpLzuCitjbh385FHSt4X23MSpPq5GRETEuwaauRkNR44cYeXKlTgcDmJjY1m8eDEnTpwgIiLiqvM6Ojp48sknKSgowOFwUFxcPKTnFBYWsnbtWg4ePAjQ75J3V/fp64qPj+eDDz4gKiqKU6dOcd9991FYWHhNrTdCQUhkgjtf1dMoIeUm6BjnljAlBH8/o85xIiIiI8DTd3A3b95MbGwsZ86cobu7m+DgYI+fUVZWxooVK9ixYwfJyclAzwxQWVnZVedMnz59wPsEBQURFNSzTD4rK4vk5GSKi4uZO3eux7Vcj5bGiUxwzgpXx7ibaGmcv6OncYM6x4mIiHhHeHg4jY2NAOTk5LBr1y66urqoqqri8OHDzJ8//6pzAOrr64mPj8fPz4+dO3fS1dXl0bPq6upYtmwZGzZsIDs7u3c8Pj6e8PBwjh8/jrWWHTt2sHz58gHvVVVV1fvcCxcu4HQ6mTFjxlB//H4pCIlMcM7KJgIdfnzqJukY55YUHcaFKgUhERERb4iKiiI7O5vU1FSOHTtGeno6GRkZLFmyhE2bNhEXF0d6ejr+/v5kZGSwefNmHn/8cbZv386CBQsoLi4mLCzMo2dt2bKFkpIS1q9f39v2urKyEoDnnnuORx55hJSUFJKTk8nLywNg7969JCQkcOzYMZYtW0Zubi4Ahw8f7q31/vvvZ+vWrUyd6p1l82astqedO3eu7dtjXERuzF/+5ATldVfY/81r21X60vdeO8fP3v6Ac9/LHXT9sIiIyM2uqKjIJ53RJpL+vmNjzClrbb/r6DQjJDLBOSubSLlJNlLtK2laGFc6uqhoaPN1KSIiIjIOKQiJTGBX2rv48OMWZt5EjRLckqJ6pt8vVDf5uBIRERHpz4EDB3qXvrn/rFixwtdleUxd40QmsPNVTVh7czVKcEuM7nlnqbS6hUXJPi5GRETEC6y142q5d25ubu+7PL52I6/7aEZIZAIrqXR1jLsJl8ZNjwwh0N9PneNERGRcCA4Opqam5oZ+YZeBWWupqakZUntv0IyQyITmrGzE38+QGO1ZF5jR5OdnSIwKVec4EREZF9x76FRVVfm6lHEpODiYhISEIV2jICQygRVXNJEUHUaA4+acHE6MCuOCNlUVEZFxICAggKSkJF+XIX3cnL/9iMioKKlsuinfD3JLmhbGBzUtdHVrGYGIiIh4l4KQyATV2tHF+zXNpNyEHePckqLCaO/q5qO6K74uRURERMYZBSGRCepidTPd9uZslODmfnfpopbHiYiIiJcpCIlMUE53x7ibeGncDAUhERERGSEKQiITVElFIw4/Q9JN2DHObVp4EGGBDgUhERER8ToFIZEJqriiiU9FhRLk7/B1KddlTE9rb+0lJCIiIt6mICQyAVlrOfl+Lem3RPq6lEElRodpRkhERES8TkFIZAL6fUUj1U3tLEqJ9nUpg0qKCqPs4yt0dHX7uhQREREZRxSERCagoyU1AGSPhSAUHUZXt+XD2hZflyIiIiLjiIKQyAT0Zkk1iVGh3DI5xNelDEottEVERGQkKAiJTDAdXd0cv1AzJmaDgN6udgpCIiIi4k0KQiITzDtldTS3d42ZIDQlNIDIkAAFIREREfEqBSGRCeZoSQ3GwMIZUb4uxSNqoS0iIiIjQUFIZII5WlLNnfERTAkL9HUpHpsRHUZptZoliIiIiPcoCIlMIFfau/jdB3VjZlmcW2JUGOV1V2jt6PJ1KSIiIjJOKAiJTCAnSmtp7+pmUfLYWBbnlhgdCsD7NZoVEhEREe9QEBKZQI6erybAYZifNNXXpQzJjOhJgDrHiYiIiPcoCIlMIG+W1DDn1imEBvr7upQhcc8IKQiJiIiItygIiUwQdS3tvPtR/Zh7PwggPDiA6EmBlCoIiYiIiJcoCIlMEMfO12AtZKeMrfeD3JKiwzQjJCIiIl6jICQyQRw9X01YoIOMWyf7upQbkhgVxkXtJSQiIiJeoiAkMkG8WVLD/KSpBDjG5r/2SdPCqGpso6mt09eliIiIyDgwNn8jEpEhuVR/hQvVzWPy/SC3pKgwAL0nJCIiIl6hICQyARwtqQFgUfLYDUKJ0T1BSO8JiYiIiDcoCIlMAG+WVDM1LJA74sJ9XcoNS9SMkIiIiHjRoEHIGHOrMeZXxpgiY0yhMeYbrvGpxph8Y4zT9b9TXOPGGPMjY0yJMeYdY8xdfe612nW+0xizus94ljHmrOuaHxljzEj8sCITkbWWo+erWZgchZ/f2P1XKyTQQXxksGaERERExCs8mRHqBP7WWjsLWAA8YYy5E1gHvGGtnQm84fpngDxgpuvPo8Bz0BOcgH8EPgPMB/7RHZ5c5zza57p7h/+jiQjA+apmKhrayB7Dy+LcEqPCuKAgJCIiIl4waBCy1l6y1p52fW4EioBbgOXAdtdp24H7XJ+XAztsj+PAZGNMPJAL5Ftra621HwP5wL2uYxHW2mPWWgvs6HMvERmmN89XA/DZMdwowe22qaGU113xdRkiIiIyDgzpHSFjTCIwB3gLiLXWXoKesATEuE67Bfiwz2VlrrGBxsv6Ge/v+Y8aY04aY05WVVUNpXSRCeuIs5qEKSHcFhXq61KGLS4ymOqmNto7u31dioiIiIxxHgchY8wkYA/wTWttw0Cn9jNmb2D82kFrt1lr51pr506bNm2wkkUmvK5uy/ELNeNiWRzA9MnBWAuVja2+LkVERETGOI+CkDEmgJ4Q9FNr7Uuu4QrXsjZc/1vpGi8Dbu1zeQLw0SDjCf2Mi8gwvVteT0NrJ4tSonxdilfERYYAcLleQUhERESGx5OucQb4L6DIWvvDPodeBdyd31YDr/QZf8jVPW4BUO9aOncA+IIxZoqrScIXgAOuY43GmAWuZz3U514iMgxHXe8HjeX9g/qKjwwG4JKCkIiIiAyTvwfnZAOrgLPGmALX2N8DG4H/Mcb8JfAB8OeuY78AvgiUAC3AVwGstbXGmPXACdd537PW1ro+Pwb8BAgB9rn+iMgwvVlSw6djw5kWHuTrUrwirjcIqWGCiIiIDM+gQchae4T+3+MBuKef8y3wxHXu9TzwfD/jJ4HUwWoREc+1dnRxorSW/+szt/m6FK8JD/InLNChGSEREREZtiF1jRORseP0Bx/T1tk9bholABhjiIsM1jtCIiIiMmwKQiLj1JslNTj8DJ+ZMdXXpXjV9MkhmhESERGRYVMQEhmnjp6vJiMhkvDgAF+X4lVxEZoREhERkeFTEBIZhxpaOzjzYR3ZKeNnWZxbfGQwlY2tdHZpU1URERG5cQpCIuPQWxdq6bbjp212X3GRIXRbqGxs83UpIiIiMoYpCImMQ0dLqgkO8OOuT032dSlep72ERERExBsUhETGoTfPVzMvcSpB/g5fl+J17r2E9J6QiIiIDIeCkMg4U9nYSnFF07hcFgcwPTIE0KaqIiIiMjwKQiLjzLHzNQBkp0T5uJKRERHiT0iAQzNCIiIiMiwKQiLjzNGSaiKC/Zk9PdLXpYwIYwzxkcF6R0hERESGRUFIZByx1nK0pIZFydE4/IyvyxkxcZHBWhonIiIiw6IgJDKOfFDbQnndlXG7LM4tLlKbqoqIiMjwKAiJjCNHSqoBWDQON1Lta3pkCBWNbXR1W1+XIiIiImOUgpDIOPJmSQ1xEcHMiA7zdSkjKi4ymK5uS3WTNlUVERGRG6MgJDJOdHdb3jxfzaKUKIwZv+8HgTZVFRERkeFTEBIZJ4ouN/BxSwfZ43T/oL7cm6peqlPDBBEREbkxCkIi48SbJe79g8Z/EIrv3VRVM0IiIiJyYxSERMaJo+ermTEtrHe2ZDybEhpAkL8flxsUhEREROTGKAiJjAPtnd28fbGWz06A2SDQpqoiIiIyfApCIuPAmbI6Wtq7WDQB3g9y69lLSO8IiYiIyI1REBIZB46WVONnYOGM8b2Ral/xkSGaERIREZEbpiAkMg4cLakm9ZZIIkMDfF3KqImLDKaioZVubaoqIiIiN0BBSGSMa27r5Hcf1E2oZXHQs5dQR5elulmbqoqIiMjQKQiJjHFvl9bS2W3JTpk4y+IA4iJ6uuNd1vI4ERERuQEKQiJj3Jsl1QQ6/Jj7qam+LmVUTZ+svYRERETkxikIiYxxR0tquOtTkwkJdPi6lFHl3i9JM0IiIiJyIxSERMaw2uZ2zl1qIHuCvR8EMDU0kECHHx+phbaIiIjcAAUhkTHs2PkaALJnTrwg5OdniI0M0oyQiIiI3BAFIZEx7Oj5asKD/Em/JdLXpfhEfIT2EhIREZEboyAkMoYVftRAxq2T8XdMzH+V4yKDNSMkIiIiN2Ri/vYkMk5UNrQS72oaMBHFT+4JQtZqU1UREREZGgUhkTGqq9tS2dhGbMQEDkIRwbR3dVPb3O7rUkRERGSMURASGaNqmtvo6rbERgT5uhSfiYvUXkIiIiJyYxSERMaoyoY2AGIm8oyQa1mggpCIiIgM1YQLQu+8cYCGqkpflyEybBUNPb/8xykIcVl7CYmIiMgQTagg1NJQT/62f+O3P9vu61JEhq3CNSM0kd8Rip4UhL+f0YyQiIiIDNmECkL1FZcBcL51lCuNDT6uRmR4Lje0YgxETwr0dSk+4+dniI1QC20REREZugkVhOoqe4JQV2cnRb/9lY+rERmeyobWnhmRCbqHkFt8ZLBmhERERGTIJtRvUPWXLwEw7bZEzh46qL1HZEyraGid0B3j3OIig7mkd4RERERkiAYNQsaY540xlcaYd/uMZRpjjhtjCowxJ40x813jxhjzI2NMiTHmHWPMXX2uWW2Mcbr+rO4znmWMOeu65kfGGOPtH9KtruIyk6ZMJfPeP6b6w/e55Pz9SD1KZMRVNLQRGz5x3w9yc88I6S82REREZCg8mRH6CXDvJ8Y2Af9krc0E/h/XPwPkATNdfx4FngMwxkwF/hH4DDAf+EdjzBTXNc+5znVf98lneU1dxSUiY+O5Y1EOAUHBnD10cKQeJTLiKhtbiY1UEIqLDKGts5u6lg5flyIiIiJjyKBByFp7GKj95DAQ4focCXzk+rwc2GF7HAcmG2PigVwg31pba639GMgH7nUdi7DWHrM9f527A7hv2D/VddRXXmZybByBIaF8etHd/P7Nw7RfaRmpx4mMmPbObqqb2jUjBEzXXkIiIiJyA270HaFvAv9ijPkQeAb4rmv8FuDDPueVucYGGi/rZ9zrOtrbaKqtITI2DoC0Jbl0tLXy3puHR+JxIiOqqsndOlvvCMW59xJq0HtCIiIi4rkbDUKPAd+y1t4KfAv4L9d4f+/32BsY75cx5lHXO0knq6qqhlRwQ2UFAJNj4wGIn/lpohJu0/I4GZPcm6lO5D2E3OIjQwDNCImIiMjQ3GgQWg285Pq8m573fqBnRufWPucl0LNsbqDxhH7G+2Wt3WatnWutnTtt2rQhFVxX0dMxzh2EjDGk35PL5ZJiqt6/OKR7ifhapSsIxWhGiGnhQTj8DJfqFIRERETEczcahD4CFrs+LwGcrs+vAg+5usctAOqttZeAA8AXjDFTXE0SvgAccB1rNMYscHWLewh45UZ/mIG4N1N1L40DmHX353D4+2tWSMacioaepXFxmhHC4WeICQ/SjJCIiIgMif9gJxhjfgb8ERBtjCmjp/vbXwH/aozxB1rp6foG8Avgi0AJ0AJ8FcBaW2uMWQ+ccJ33PWutuwHDY/R0pgsB9rn+eF1dxWUCQ0IICY/oHQsJjyBl/iLO/fYQd3/lYQIC9bfrMjZUNLQS4DBMCQ30dSk3hbjIYL0jJCIiIkMyaBCy1q68zqGsfs61wBPXuc/zwPP9jJ8EUgerY7jcrbM/uU1R+j25/P7Nw5S89Saz7v7cSJch4hWXG1qJCQ/Gz2/Ett0aU6ZHhlB0ucHXZYiIiMgYcqNL48acuoqe1tmfdOudaUTGxml5nIwplQ1tej+oj7jIYC5rU1UREREZggkRhGx3Nw2Vl4mMuTYIGT8/0j73BT48d5aPL5X7oDqRoatoaNUeQn3ERwbT0t5Fw5VOX5ciIiIiY8SECEKNtTV0dXb2doz7pNmL78H4+XH2V/mjXJnIjaloaNUeQn249xK6pPeERERExEMTIgjVf6J19idNmhrFjLvmUfjrX9LVqb9RlpvblfYuGlo7iY3UjJBbvDsIqXOciIiIeGhCBKG6flpnf1Laklxa6uu4cPrt0SpL5Ib0bqaqpXG93JuqXlYQEhEREQ9NiCBUX3kZP4eDiOjrb8KalJnFpClT1TRBbnq9QUh7CPWaFh6En9GMkIiIiHhuQgShusuXiIiOwc/huO45fg4Hs/9oKaUFp2morhrF6kSGpqKxZzNVvSP0BwEOP6aFB3G5Xu8IiYiIiGcmRhCquNy7LG6g9rppS5ZibTeFv/7laJUmMmSVrhmhGM0IXSUuMkQzQiIiIuKxCRGE6it79hBq72on76U8fvbez/o9LzImjtvSMjn7q4N0d3eNcpUinqloaCUkwEFE8KD7IU8o8RHBCkIiIiLisXEfhFqbm2htaiQyNp5zNecobyrnX0//K9VXqvs9P/2eXBqrq/jgnYJRrlTEMxUNbcRGBGGM8XUpNxX3pqoiIiIinhj3Qaje1TFucmwcBZU94aats41/+92/9Xt+8twFBIdHqGmC3LQuN7RqWVw/pk8Opqmtk8bWDl+XIiIiImPAuA9CdX32ECqoKuDW8Fv5izv/gr3OvRTWFF5zvn9AALNzPkfJybdoqa8b7XJFBlXZ0KqOcf2IUwttERERGYIJEIR6ZoQipsVQUFlA5rRMHk1/lCnBU3j67af7bZ6QtiSX7q5OCg8fGu1yRQZkre1ZGheujnGfpE1VRUREZCjGfRCqr7hEaORkKrtqqWmtITMmk/DAcNbMWcPvKn/HgdID11wTlXAb02+fxdlDBwfsMicy2hrbOrnS0aUZoX7ERbiDkFpoi4iIyODGfRByt852vx+UMS0DgPtS7mPW1Fn84NQPuNJ57S9Oaffk8vFHZZS/d+3yORFfcbfOjo1UEPqk2AjNCImIiIjnJkAQusTkmDjOVJ0hLCCMlMkpADj8HKydv5bLzZf5SeFPrrnu0ws+S2BIiJomyE3lcr1rM1UtjbtGoL8f0ZOC9I6QiIiIeGRcB6Guzg4aa6qJjI2noLKA9Oh0HH6O3uNZsVnkJuby/Nnnudx8+aprA4KDuSN7McXHj9La3DTapYv0q8I9I6Slcf2aPll7CYmIiIhnxnUQqq+sBGsJiZ6Cs85JZkzmNef8TdbfYLFsPrX5mmPp99xLZ3sb7x35zWiUKzKoisaeX/JjIjQj1J+4CO0lJCIiIp4Z30HI1Tq7MrCRbtvdbxCaPmk6D89+mF9c/AW/q/zdVcdikpKZljiDdw4dUNMEuSlUNrQRHuxPaKC/r0u5KcVHBvORmiWIiIiIB8Z1EHLvIXSBjzAY0qPT+z3va6lfIyY0ho1vb6TbdveOG2NIX5JLVekFKi+eH5WaRQZS0dDa2x1NrhUXGUJjaydNbZ2+LkVERERucuM6CNVXXsY/KIgzLUXMnDKTSYGT+j0vNCCUb2V9i3M153j1/KtXHbvjs4vxDwjk7KFr22yLjLYKbaY6IPdeQloeJyIiIoMZ10GoruIykTFxvFN9lsxp1y6L62tZ0jLSp6Xzr6f/leaO5t7x4LBJ3L4gm6Ijv6ajVb9ciW9VNLTp/aABxCkIiYiIiIfGdxC6fAn/qeE0dTT1+35QX8YY1s1bR/WVav7znf+86ljaPbm0X7nC748fGclyRQbU3W2pbNSM0ECmR4YA2lRVREREBjdug5C1lvrKCppDuwAGnRECSJuWxpeSv8SOczv4sOHD3vFb7pjNlPhbOPuGlseJ73zc0k5Hl9UeQgNwz5ZpRkhEREQGM26DUHPdx3S2t1ER2MDU4KkkhCd4dN037voG/n7+/ODUD3rHjDGkLfkCHxUXUVP2wUiVLDKgigbXZqqaEbqu4AAHUWGBfKQgJCIiIoMYt0HI3TGu2H5I5rRMjDEeXRcTGsOj6Y/yxgdvcPzS8d7x2Yvvwc/hz9uv/HxE6hUZjHsPodhIBaGBxEUGc1lL40RERGQQ4zYI1VdcBuCCucScmDlDunbVnau4ZdItPP3203R297ThDY2czNw/vo9zhw9R9l6h1+sVGUyFa5ZDM0IDi48M5pJmhERERGQQ4zYI1VVcBmNoDukctFHCJwU5gvi7uX9HSV0Je4r39I4v+NMHCY+axqH/eo7uri5vlywyIPfSuGmT9I7QQOIjQ7jcoCAkIiIiAxu3Qai+4hKEB+HwD2BW1KwhX3/PbfcwL24eWwq2UN9WD0BAcDCfW/1XVH1Qyu/2v+7tkkUGVNHYSlRYIIH+4/ZfW6+IiwymrqWDK+36ywoRERG5vnH7G1VdxSUawzq5M+pOghxD/xt0Ywxr562lob2BrWe29o6nzF9IYmYWb+7+b5o+rvVmySIDqmxoJUbL4gbVu6mqZoVERERkAOM6CFX4N3jUNvt6Pj3109w/835+9t7PuFB3AegJSEsefpSujg5+s/O/vFWuyKAqGtqI02aqg3JvqnqpTg0TRERE5PrGZRBqv9LClYYG6kPbhvx+0Cc9MecJQv1D2XRiE9ZaAKbE38K85ffz3tHf8GHhO94oWWRQFQ3aTNUT8b2bqmpGSERERK5vXAahOlfHuIbQoTdK+KSpwVN5LPMxjn50lN+W/7Z3fP59f07EtFjeeH4rXZ2dw3qGyGA6u7qpbmrT0jgPxEVoaZyIiIgMblwGIXfr7NDoqUSHRA/7fg/e8SCJEYlsOrGJjq4OAAICg1jy1UepKfuA0794ZdjPEBlIdVM73RZitTRuUCGBDqaEBnDJi3sJvVJQzvrXz3ntfiIiIuJ74zIIfezaTDUlMc0r9wvwC+A7877D+w3v890j36XmSg0AyVmfYUbWfI79/Gc01lR75Vki/alwzW7EhmtGyBNxkSFc9uLSuC2HSnj+6EUaWju8dk8RERHxrXEZhD4qO09rQBcZCVleu+fdCXfzROYTvPHBG3zp5S/x8+Kf0227WfLwo9jubn694/947Vkin9QbhLQ0ziPe3FT1QlUTzsomrIVTpR975Z4iIiLie+MyCF0qv0CjF94P+qSvZ3ydPX+yh5lTZvJPx/6Jh/c/TGVAI/NX/DnFx49Qeua0V58n4lbR2LOZamyklsZ5Is6LQejguQoAHH6Gty6qZb6IiMh4MS6DUFNVFVcmWVImp3j93jMmz+DHuT9mffZ6LtZf5MuvfZk3E8qIiInl0I//g84OLZ0R76uob8XhZ4gKUxDyRHxEMLXN7bR2DH9T1QOFl0m7JZLMWyfz9sUaL1QnIiIiN4NxF4S6OjsxDW2ERkfh8HOMyDOMMdyXch+v3vcqf5L8J/zkvR386tPlfHypnFOv7x2RZ8rEVtHQyrRJQTj8jK9LGRPcewlVDLNzXEVDK7/7oI4v3BnL/KSpvFNWz5X24YcrERER8b1xF4QqKz7AWIi7JWnEnzUleArfy/4eP879Mc0JQZTGNnP45zspeb9wxJ8tE0tFY5s6xg3B9Mne2UvIvSwuNzWO+UlT6ey2nP5A7wmJiIiMB4MGIWPM88aYSmPMu58Y/2tjzO+NMYXGmE19xr9rjClxHcvtM36va6zEGLOuz3iSMeYtY4zTGLPLGBM4nB+ooPgYALcnZgznNkMyN24uP/+Tn5P25RV02y7+/Yff5L/P/Ted3dpfSLyjsqFVewgNgXtGaLid4w4WXiYpOuz/Z+++w6OqtgYO/8609Ex67yT0ElrovUlRUEABC9gLiF7L9douKPbLZ6UoFsCKiIIgSi+h14QSaggBkpCZ9ElPZuZ8f0woIQmkTICB/T5PHuW0vRMUzpq99lpE+TjTMdQdhYTYJyQIgiAIt4jarAgtAO64/IAkSf2AkUBbWZZbATMrjrcExgGtow+BmgAAIABJREFUKu6ZI0mSUpIkJTAbGAq0BMZXXAvwIfCJLMtRQA7waEO+oZPJhwCIbtatIY+pM7VSzRM9p9J+5D0Epdvx48rPmLByAoczD1/7ZkG4Bp2h5GKjUOHaLvys0hrQSyivqJwdp7IY3MoXSZJwtVfTMsBV7BMSBEEQhFvENQMhWZZjgSs/An0a+ECW5dKKa/QVx0cCi2RZLpVl+TSQCMRUfCXKspwky3IZsAgYKUmSBPQHllTcvxAY1ZBvSJ+ajFkBfj4hVc4ZTWYeW7iXTcf11dxpHQNGT8Q9IJBhSVFkF2QyYeUE3t35Lvll+Y02pnBrKzWayCkqF6lxdeBkp8LVXtWgFaGNx/UYzTJDWvldPBYT5knc2VxKjWKfkCAIgiDYuvruEWoK9KpIadssSVLniuOBwLnLrkupOFbTcU8gV5Zl4xXHqyVJ0hOSJO2VJGlvRkZGlfNm2UxhZhZo7ZEUVb+1vWdyWHdUx7srj2I2y7X+ZutCqVIz4JGnKc828Ib0IOOaj+PX478yctlI9utEeW2h7vQGS+lskRpXN/5ahwbtEVqdkI6Pix3RQW4Xj3WJ8KDUaOZQSp41pigIgiAIwg1U30BIBbgDXYGXgcUVqzvVlbSS63G8WrIsz5NluZMsy528vb2rnD+VewrHAglnH59q719XsfH5pL6AtUd1NQ3TYKFtomnWrRfxfy3nmbBH+GX4LzioHHhp80vkluQ22rjCrUk0U60ffzf7eq8IlZSb2HQ8g8GtfFFcVqmvc5gHIPYJCYIgCMKtoL6BUArwh2yxGzADXhXHgy+7LghIu8rxTMBNkiTVFcfrJU4fh0uRioDAiCrnZFlm3VEdPSO9CPV0ZPbGRGS5cVaFAPo89CgKpYqNC76ipWdLZvaZSU5pDm/vfLtRxxVuPbqKFSGRGlc3/g1oqrrlZCbF5SYGt/SrdNzDSUNTX2cRCAmCIAjCLaC+gdAyLHt7kCSpKaDBEtQsB8ZJkmQnSVI4EAXsBvYAURUV4jRYCiosly0RwUZgTMVzJwJ/1vebOXh2H2qTgqCgqCrnTmUUkpxVxJBWvjzVpwkHU/LYmphZ36GuycXDi+5jxpO0fw+n9u6ihWcLpkRPYe2ZtSw/tbzRxhVuPRdWhESxhLrxc3Ugs6CUMqO5zveuTkjHxV5F1wjPKudiwj3Yl5yN0VT35wqCIAiCcPOoTfnsX4AdQDNJklIkSXoU+A6IqCipvQiYWLE6lAAsBo4Aq4DJsiybKvYATQFWA0eBxRXXArwCvCBJUiKWPUPf1vebSUq2PNLNz7/KuXUVqXADWvhyT4dA/Fztmb0xsb5D1Ur7oXfhGRTCxoXzKC8tYVKrSXTw6cD7u98nJT+lUccWbh26/BI0KgVaB/WNnopN8a9nU1Wjycz6ozoGNPdBo6r6R2RMuCeFZSaOnDdYZZ6CIAiCINwYtakaN16WZX9ZltWyLAfJsvytLMtlsiw/IMtya1mWO8iyvOGy69+VZbmJLMvNZFn+57Ljf8uy3LTi3LuXHU+SZTlGluVIWZbHXqhEV1dZxVkUZlhWeNx8qwmEjuhoFeBKgJsDdiolj/eOYGdSNvvONF6Ki1KlYsCjT2PI0LNr6W8oFUre6/UeEhKvbX0Nk1lUnhKuTZdXgq+rHZZteEJtXeglVNf0uN3J2eQUlVeqFne5LuGWfUK7RXqcIAiCINi0+qbG3XQOZBzApciy1cj1imIJWQWl7Dubw8AWvhePjY8Jxt1RzeyNpxp1XsEt29CiVz/2rvid7LRUAp0Dea3La8Tp45ifML9RxxZuDTpDKb4uIi2urvwvBkJ16yW0JkGHnUpBn2ZVC7KApWhFmKcjO5NEICQIgiAItuyWCYTiM+JxLVbj5OGBWlN5U/mGY3pkGQa1vBQIOWpUPNIjnA3H9CSkNW4p3D4PPIJSrSb2p+8AGBExgiFhQ5gdN5uErIRr3C3c7nT5JaJiXD34uzkA1KlynCzLrD2io1eUN44aVY3XxYR7sCc5u9HK8AuCIAiC0PhumUDogP4AvmWuuPsGVDm37qgOP1d7WgW4Vjr+UPcwnO1UzN3UuKtCTm7udL5rDKf27iL12BEkSeLNrm/i4eDBq1tepdhYt0+shduL3lCKj6gYV2fOdipc7FR1So07nGogNbeYwa18r3pdTLgnecXlnNCLRsmCIAiCYKtuiUCo3FTO4czDOBUq0fpWzusvKTcReyKTgS19quyx0DqoebBbKCsPnScpo6BR59hx2Eic3NyJ/XkBsiyjtdPyTo93OJ13mo/3ftyoYwu2q6DUSEGpUVSMqyc/bd16Ca1OSEchUSmNtjpin5AgCIIg2L5bIhA6mn0UU3k5UmEZbj6VA6Edp7IoLjfV+GLzSI9wNEoFX25u3FUhtb093cZMIO34EU7t2w1At4BuPNDiARYdX8SWlC2NOr5gm/SimWqD+Gnt67RHaHVCOjHhHng4aa56XZC7AwFae9FPSBAEQRBs2C0RCMXr4y8WStBeUTp73VEdjholXSM8kcvKSH7gAdJe+Q+lSUkAeLvYMT4mhD/2p5Ka27gpaq37DcLdP4CtvyzEXFEx7vmOzxPpFsl/t/+XnJKcRh1fsD3pFYGQSI2rn7o0VU3KKOCkvqDGanGXkySJmHAPdp/OFg2SBUEQBMFG3RqBUEY8YWbLio/bZalxsiyz7qiO3lHe2KuVFO7cSfHefeT99RdJw0eQMvU5So4c4fHeEQB8HZvUqPNUqlT0HPcQWSlnObLZUnHcTmnHB70+IK80j+nbp4uXKqESvcFSTV6sCNWPn9aBjIJSymvR/HTNEUuvscG1CITAsk8oI7+U05mFDZqjIAiCIAg3hs0HQrIsE6+PJ1IKBEB7WWrc4VQDOkMpAyuqxRnWrEHh5ETk+nV4PvEEhdu3c/qe0Zj+/RxPehTwy+6zZBbUq41RrUV16YFfZFO2/fYT5WWWsZp5NGNq+6lsOLeBZYnLGnV8wbboRGpcgwRo7ZFl0Odf+//r1QnptAnUElhRbe5aYsQ+IUEQBEGwaTYfCKUVppFRnIFvmSsaB0ccXC5Vhlt7VIdCgn7NvJGNRgrWrce5b1/Ufn74/Ot5Ijesx/v55yk5dJgR30xjxsZZrPhmaaOuykiSRO8JkyjIyiR+9cqLxx9q9RCd/Trzwe4POGc412jjC7ZFZyjF2U6Fs13NpZyFml1oqpp+jX1COkMJcWdzGdzy6kUSLtfE2wkvZ40IhARBEATBRtl8IBSvjwfAsVCBm69/pcpw647o6BjqjqezHUV792LKzcVl8OCL55Wurng99SSR69fh++p/CC/LoeuXb3Fq9Fjy161DNl87naY+glu1JSy6I7uXLqakwFKtTiEpeLfHuyglJa9ufRWj2dgoYwu2RZdfIvYHNYC/1rK6c619QhfS4oa0rl1aHFzaJyQKJgiCIAiCbbolAiFHlSPl2YZK+4NSc4s5ct5wsVpc/pq1SPb2OPfqWeUZCkdHPCZOxPG3P/ksegx5+ixSpjzL6ZEjyVuxAtlo/aCk1/iJlBQVsnv5kovH/J39eb3r6xzIOMC3h761+piC7dHlleDrItLi6uvCitD53GsEQgnphHs5EeXjXKfnx4R5kJpbTEpOUb3nKAiCIAjCjWHzgdCBjAO08WyNQa+v1ENo/VHLJ7wDW/oim83kr12Lc6+eKBwda3xWqzBvSofcyZODXsHr/Q8ASHv535waOoycXxdjLiuz2rx9wiJo0bMvcX8vJz878+Lx4RHDGRo+lC8PfMnhzMNWG0+wTbr8EnzFilC9udqrcNQor7oilFdUzo5TWQxu5Vul19i1xIR7AmKfkCAIgiDYIpsOhIrKiziec5x29s0xm4y4+V4qnb3uqJ4ILyeaeDtTHH8AY0ZGpbS4mkzpH0lmsYkV3m0J//NPgmbPQunmRvq0aZwaNJjC7dutNv8e996P2Wxmx28/Vzr+epfX8XTw5NUtr1JULj5pvl3JsozOUCoKJTSAJEmWpqqGmvcIbTyux2iWa1U2+0rN/FxwtVeJQEgQBEEQbJBNB0KHMg9hls1EEABwcUUov6ScHacyL1aLy1+zBtRqnPv2veYzO4Z60CXcg3mxSZSZZVwGDCBs8a8Ef/sNCmdnUp57ntLTp60yf62PH9GDh3F44zqyUi4VSNDaaXmv53ucMZzh430fW2UswfbkFZdTZjTjIwKhBgnQOlx1RWh1Qjo+LnZEB7nV+dlKhUTnMA8RCAmCIAiCDbLpQChOH4eEhHeZJa//worQlpOZlJtkBjT3QZZl8teuxal7N5QuLrV67uR+kaQbSli6PxWwfKrs3KMHIfO+QlKpSJnyLKaKIgcN1eWe+1Db27F10feVjsf4x/BQy4f49fivxKbEWmUswbboKnoI+YlAqEH8tPak1xAIlZSb2HQ8g8GtfFEo6pYWd0GXCA+SMgvR59eucasgCIIgCDcHmw6E4jPiaeLWhNLMHBRKJS6eXoClWpybo5qOoe6UHDlCeWoqrrVIi7ugV5QXbYO0zN18CuNljRjVgYEEfvIJZcnJpL3yH6tUlXN01dL5ztEk7tlB2omjlc5N7TCVKPco3tz2JlnFWQ0eS7Atl3oIiT1CDeGvtUdnKKn0//IFW05mUlxuYnDLuqfFXXBhn9Ce0zn1foYgCIIgCNefTQdCB/UHifaJJlevw9XbB4VSidFkZsNxPf2b+aBSKshfsxaUSpz796/1cyVJ4pm+kZzJKmLlofOVzjl17YLvK69QsH49mXPmWuX76Dh8FI5aN2J/WlCph5FGqeGDXh+QX5bPu7vetcpYgu1IF81UrcJPa49ZhoxqmiWvTkjHxV5F1wjPej+/VYArjholu0+LDysEQRAEwZbYbCBUaiolvzyfaO9o8nTnL6bF7TuTQ25RuaVanCyTv2YNjp07o3J3r9PzB7f0JcrHmTkbT2E2V26w6v7gA2hHjSJz1izy169v8Peitren25gJpB5L4HTc3krnmro35al2T7H2zFo2ndvU4LEE26GvCIS8XcSKUEP4XyihfUV6nNFkZv1RHQOa+6BR1f+PQrVSQcdQd9FPSBAEQRBsjM0GQheqqUX7RJOrO4+2IhBad1SHRqmgd1NvyhITKTt9GpfBg+r8fIVC4pl+TTiuy2fDMX2lc5Ik4ffWdOzbtCHt5X9TmpjY4O+nTf/BuPn5s+XnBZjNpkrnHm71MJFukbyz8x0KywsbPJZgG3SGUtwc1dirlTd6KjbtQlPVK/cJ7U7OJqeovF7V4q4UE+bBsfR8cousV2JfEARBEITGZbuBkLEIdzt3vCV3SgsLcfOxVIhbd1RP1yaeONupMKxdC5KEy8CB9RrjzrYBBLk7MGtjYqWUNQCFnR1BX3yO5OBAyuQpmAyGBn0/SpWKnuMmknnuDEe3bKp0Tq1UM737dPRFej7f/3mDxhFsh85QIgolWEFNK0JrEnTYqRT0aebd4DG6VKTW7UkW+4QEQRAEwVbYbCBUbCymnU87DHpL41Stnz+nMgo4nVnIoBY+AOSvWYtDdDRqH596jaFSKniqTxPiz+Wy41TV/H+1nx9Bn39GWWoqqS+9hGwyVfOU2mvatQe+EVFsW/wjxiuat7bzbse45uP45dgvHMw42KBxBNugyy8VpbOtQOugxl6tID3vUi8hWZZZe0RHryhvHDWqBo/RNkiLRqUQ+4QEQRAEwYbYbCBEqZJob0taHFhKZ687YgmKBrTwpezsWUqPHatVE9WrGdMxCB8XO2Zvqj79zbFjR/zeeJ3C2C1kfP5Fg8aSJIne908iPzOD+DUrq5yf2n4q3o7eTN8xnXJzeYPGulUtPr6YJSeWVFnBs0W6vBJ8xf6gBpMkCX+tA2mXrQgdTjWQmlvM4Fa+VhnDXq0kOthN9BMSBEEQBBtis4GQvdGJ9j7tydOlA6D18WXdUR0t/V0JcHOwNFEFXAbVfX9QpXHUSh7vFcG2xCzizlaf9uJ23324jR1L1ldfYVi1qkHjhbRuR1i7DuxaupjSosr7gZw1zrzR5Q1O5pxkYcLCBo1zKyo3lzNz70ze2vEW/9nyH4qNxde+6SZlMstkFJSKinFW4udauZfQ6oR0FBIMbGGdQAigS7gHh9MMFJQarfZMQRAEQRAaj80GQhqTPRF2UeTqzuOodSPfqGDfmRwGtrS82BjWrsW+VSs0QYENHmtClxDcHNXM3niq2vOSJOH75hs4REeT9uprlBw/3qDxeo6fSElBPnuW/17lXL+QfgwKHcTc+LmcMZxp0Di3mhPZJyg2FtM9oDv/nP6Hh/55iJT8lBs9rXrJKizFZJZFDyEr8ddWDYRiwj3wcNJYbYyYcA9MZpl9Z8Q+IUEQBEGwBTYbCCFLnIvPI0+XjpuvPxuPZ2CWYVALX8rT0yk5cLDBaXEXONmpeLh7OOuO6jiWXn1RBIVGQ+Dnn6F0drYUT8jNrfd4vuFNaN6jD/tW/klBdtU9B6/GvIqd0o63d7x9S6SAWUucPg6At7q/xewBs0ktSGXcynFsT91+g2dWd3qDpeeN2CNkHf5ulqaqJrNMUkYBJ/UFVqkWd7mOoe6oFJLYJyQIgiAINsJ2AyGVmeO70snVpePm68e6Izp8Xe1oHehqaaJKw9PiLjexeyhOGiVzalgVAlD7+BD0xecYdTpSX3gR2Vj/FJke9z2I2WRix5JfqpzzdvTm+Y7Pszt9N8sSl9V7jFvNfv1+/J388XPyo1dQLxYNX4SPow9Pr3+abw59Y1NBo66ih5CoGmcdfloHjGaZrIJS1lTsJRxs5UDIUaOidaBW7BMSBEEQBBths4GQxlFJelI2+dmZOHn5Ensyg4EtfJEkifw1a7CLisQuItxq47k5anigayh/HUwjObPmXj4O0dH4TZ9G4fbt6D/+pP7j+frRbvBQDm1cQ3Za1fSuMU3H0MGnAzP3ziSrWHwCLcsy8fp42vu0v3gsxDWEH4f+yODQwXy2/zNe3PyizfRhSq8IhMQeIevwd71UQnt1QjptArUEujlYfZwu4R4cOJdHSXnDKkgKgiAIwq2i1GjilSUHWXEg7UZPpQqbDYRcXZ2QZQPIMhmSM0VlJga29MWYmUnRvn24DLJOWtzlHu0Vjkqp4MvNNa8KAbiNHo37hAlkf/cdeSv+qvd4Xe++D5XGjq2Lvq9yTiEpmNZtGsXGYj7c82G9x7hVpBSkkFGcUSkQAnBUO/JR7494seOLrD+7nvtX3m8Te6t0hlIkCbycrbeH5XbmV9FL6EBKLnFncxlipWpxV4oJ96DMZCbubP1TYwVBEAThViHLMv/5/RC/7j3Hh6uOYTbfXNk5NhsIKZQSnv6WT10PGpQ4apR0i/Akf/0GkGVchlg/EPJxsee+TsH8vj+FtNyrVyTzffU/OHbqxPk33qA4IaFe4zlq3eh85z2c3LWdtBPHqpyPcIvg8TaP88/pf9iSsqVeY9wq4vXxAFUCIbAUs5jUehJfDfqKrJIsxv01js3nNl/vKdaJ3lCCl7MdKqXN/i96U7nQVPX7HZYg2NppcRd0CvNAkhDpcYIgCIIAfLLuJEvjUokJ9yAlp5idN9k+Wpt+y3L3s/TSOZQs0zvKG3u1kvw1a1CHhmDXtGmjjPlknwhkGb7eknTV6yS1msDPPkXp7k7Ks89izK7fi1HHEaNwcvdg9ZefUV5SUuX8o20eJUIbwTs736GovKheY9wK9uv346x2JtItssZruvp35dcRvxLsEsyUDVOYGz8Xs2y+jrOsPZ2hRFSMsyIPJw0alYJEfQHhXk5E+Tg3yjhaBzUt/FzZnXxz/UEvCIIgCNfbkn0pfL7+JGM6BvH9IzG42Kv4be/NVc3XpgMhtaYAJDWeBjsGtvTFlJdH4a5duA4ahCRJVW+QZVg7DVL313vMIHdHRrUP5JfdZ8ksKL3qtSpPT4JmzcKUlU3q8/9CLq97E1SNvQNDJ79AdloK67/7sup5pYZp3aaRVpjG7PjZdX7+rSJeH087n3YoFcqrXhfgHMD3Q7/nriZ3MefAHJ7b8Bz5ZfnXaZa1pzOUikIJVmRpqmr5eQ5u5Vv9nw9WEhPuwb4zOZQZb84gWxAEQRAa2/bETP7z+0F6RHry3t1tsFcrGRkdwN+HzmMoqfv7cGOx6UAoP1MHdu40M6ro3cST/A0bwWisuWz2+QOw7VNY8jCU1X/T/NN9m1BqNDN/2+lrXuvQuhX+b79F0e7dnL7vPvKWL0cuK6vTeKFtoul6z30kbF5Hwub1Vc538O3AvU3v5cejP5KQWb80PFuWV5pHYm4i7b2rpsVVx15lzzs93uHVmFfZmrqV8SvHcyr36vu+rjd9fokonW1lFwJLa5fNvlKXcA9Kys0cTstr1HEEQRAE4WZ0UpfPkz/uI9zLiTn3d0SjsoQb93YKptRovqmKJth0IJSn15GnccVBlsg/nU/+mjWo/P2xb9Om+htOrLb8MycZNrxT73GbeDszrLU/328/Q17xtaNa7ciRBHz4AXJJKWn/foXEgYPI/PIrjDm1b7zYbcx4glu2Yd23c8hKOVfl/PMdn8fT3pPpO6ZjNN9ene0PZBwAqt8fVBNJkpjQYgLfDPmG/LJ8JqycwNozaxtrinVSZjSTWVCGr4sIhKwpwtuZQDcHooPcGnWczuEegNgnJAiCINx+9PklTJq/B3u1kvkPd0broL54rk2glma+LjdVepxNB0K5uvMk4QT2So5tS6Vw2zZcBg2sOe3lxD8Q1Bk6PwY758LZnfUe++m+TcgvNfLjztpVINOOHEnEXysInvcVdpGRZHz6KYn9+nN+2nRKT117NUKhUDLs2ZdQ29mz4pP3KS+tvF/IRePCa11e41j2MX448kO9vidbFaePQyWpaO3Vus73dvTtyOIRi4l0i+SFTS+wMGFhI8ywbjIqUi7FHiHren14C5ZO7o5C0XhpcQBeznY08XZiV5LYJyQIgiDcPorKjDy2cC/ZhWV8O7ETQe6Olc5LksTYTkHEn8vlhO7m2JZgs4GQ2WjEVF5OntqV0PZenE3IpsysxrWmJqqG85AWB03vgIHTQRsMf06G8qtXf6tJ60At/Zp58+3W0xSV1W4FRlIocO7dm5DvviV8+Z+4jhhO3tKlJA0fwdnHn6Bg67arNv109vBk2JQXyUo9x4b586qcHxAygH7B/ZgTP4dz+VVXjW5V+3X7ae7RHEe147Uvroavky/z75jPgJABfLrvU07knLDyDOtGJ3oINQpnOxU+12mVrUuEJ3uTczDdZGVCBUEQBKExmMwyzy2K51BqHp+Pb0/bK7IvSk+dwpiTw93tA1EpJH7be3O8p9psIGQ0WlLSHDx9iOkXjFmWyAjviUOHDtXfcLIiLa7ZULBzgbs+g6xE2PRBvecwpX8k2YVl/LK77r+Z9k2bEvDOO0Ru3IDX1GcpOXqUc489xum77iLnt98wV1MhDiCsXQe6jBrL4Y1rOLplY6VzkiTxWpfXUCqUzNgx46pB1a2izFRGQlYC7X1rnxZXnQtFJ1w0Lry1/S1M5hvXEFNfEQj5iBUhm9Ul3IP8UiNHzxtu9FQEQRCEm8zR8wZGzd7G2C+38/Ga4+w4lWXzjbjfWXmEtUd0TBvRkkEtK/fqMxkMJN97Hxkff4Knsx0DW/iyNC6VctONLypku4FQmSUQim7ZBE9vNU5F6ejD+iApa6gadnyVZRXIp6Xl1036Q4eHYPvnkLqvXnPoGOpBl3APvo5NotRYv/+AVZ6eeD/zDJEb1uP//vugVJH+5n9J7Ncf/WefUa7XV7mn+9j7CWzeirVfzyY7rXKepZ+TH891eI4d53fwV1L9m7naiiNZRyg1ldZpf1BN3O3deSXmFQ5mHmTR8UVWmF396AyW1DhRNc52dQ4T+4QEQRCEqpYfSOOeOdtJyy2mzGhm1sZExn+9k3ZvrWHC1zuZteEk+87k3BRBQm3N33aa+duSebhHGJN6hFc5n7t4MebCQkqTLK1nxnYKIrOgjI3Hqr7jXm82GwgVl5RiRqJfx2YUbd+O3/mdZJdrycuoppdOeTEkbbKkxV2+f2jwO+DsB8smg/HqpbBrMqV/JOmGEv7Yn1q/b6SCQqPB7e5RhC/9g5AFC3Bo356sL78iccBA0l55hdKkSxXqFEolw6e+jFKj4a9PPqC8rPLc72t2H+282/G/Pf8jp6T2BRls0dUaqdbHsPBh9AjswWf7P+N8wXmrPLOu0g0lqJUS7o6aGzK+0HABbg4EeziIQEgQBEEAwGgy897fR5n6SxytAlz569me/DmlJ/HTBvPNQ524v0soOUXlzFxzgtFztxP91homzd/NvNhTHErJu2lTrdce0fH2X0cY1NKXN4a3rHJeLi8n+4cfASg7a9lX36epN94udiy+CYom2GwgVFZWRpHahc5NvMlfswb/4mMgwfFduqoXJ20GYzE0u6PycXst3PkpZByF2Jn1mkfPSC/aBmn5cvMpjFaI3iVJwqlrF4LnzKbJP3/jfu+9GNau4/TIkWR8/vnFlDkXTy+GTX6BjLPJbFr4daVnKCQF07tNJ788n5l76/d92Yo4fRzBLsF4OXhZ5XmSJPHfrv8FYMbOG5NeqDOU4ONi3+ib+oXGFRPmye7k7NsiRVUQBEGoWXZhGRPn72ZebBIPdg3l58e7XmyR4WqvZmBLX/57Z0v+ea4X+98cxJz7O3BPhyDOZRfx3t/HuHPWVtq/vYYnvt/L/G2nOZ6ef1P83XIwJZepv8TRJlDLZ+OiUVbz3mJYtQqjTodDx46YMjIxFxaiUioY3SGIjcf16POr3wpyvVwzEJIk6TtJkvSSJB2u5txLkiTJkiR5VfxakiTpc0mSEiVJOihJUofLrp0oSdLJiq+Jlx3vKEnSoYp7Ppdq2enQbCxH5eaF0mQkf8NGvHt2JLCpO8d3pVf9j+PEP6BxhrBeVR/UdAi0HQdbP4bzB2sz9JU/Ayb3i+T96EOMAAAgAElEQVRMVhErD1l3BUETFobfm28QuXoVLnfcQeacuSTdNZKCrdsACG/fic53jebgulUc27a50r2R7pE80voRlp9azsKEhWQUZVh1bjcDWZaJz4i32mrQBQHOATzb/lm2pG5hVfIqqz67NvSGUrE/6BbQJcKD7MIyEvUFN3oqgiAIwg1yODWPO7/Yyp7kHD4a05YZo1pf7KtTHQ8nDcPa+DNjVGvWv9iXXa8N4LNx0Qxt7c/RdANvrTjCkE9j6TBjLY8t3MtXm0+x/+z1b+KdklPEIwv24uGk4ZuJnXDUqKpcI8sy2fMXoImIwOP+CQCUnbPsqx/bKQiTWWZpAzOqGqo2K0ILgDuuPChJUjAwCDh72eGhQFTF1xPA3IprPYBpQBcgBpgmSZJ7xT1zK669cF+VsaqduNmEX1AQhbt2Yc7Px2XwYJp18cWQUYzu9GUblGXZ0j+oST9Q1fByecf74OBhqSJnqnu320EtfGnq68zsjYmYG2HpUuXtTeD/PiJk/ndIksS5xx4j9YUXKdfr6XHfgwQ0bcGaebPIOV/5P6Yn2j5BW6+2zNw7k/6/9WfcX+OYe2AuR7OO3hSfJDTUGcMZskuyrR4IAUxoPoHWnq35YPcH5JbkWv35V6MzlIgeQreALhX9hHaJ9DhBEITb0h/7Uxg9dztmWea3J7txb6fgOj/D19WekdGBfDimLVv+3Z8t/+7HR2PaMrCFL6cyCnj/n2PcM2c7baav5r6vdvB/a46z+UQG+SV1f5+trbzich5ZsIdSo4kFD3eusSJr0e49lBw5gsekiWjCwgAoO2MJG5p4O9Mx1J3f9qXc0HfSawZCsizHAtX9Tf4J8G/g8tmPBL6XLXYCbpIk+QNDgLWyLGfLspwDrAXuqDjnKsvyDtnyU/geGFW7ics0jQolf80aFI6OOPXoTpP2PijVCo7vSr904fkDkH8emg6t+WGOHjDiY0g/CNs+rc3wleeikHimbyQndAWsO1pNap6VOHXrRvjyP/GaMoX8tWtJGjacvMWLGTblRZQqFSs+/RBjWdnF6+2Udvw47Ed+v+t3prafilKhZG78XO79614GLRnEjB0ziE2JpcR4Y5cl6ytOHwdYb3/Q5ZQKJdO7T8dQarju6YU6Qwl+WhEI2boQD0d8Xe3EPiFBEITbTLnJzPTlCbyw+ADRwW6seLYn7YKt08w72MORezsF87+x7dj4Ul92vz6Aufd34P4uoRSVmZi9MZGJ3+2m3VtrGP75FqYvT+Cvg2kXW3M0VJnRzNM/7iMpo5CvHuhIlK9Ljddmz5+P0sMD7V13oQ4Jsdx/9lL/zXs7BZGoLyDu3PX9wPlyVdexakGSpLuAVFmWD1yRyRYIXF5LOqXi2NWOp1RzvFZ8/P3Jn/kZzn37orCzQwNEtPPi5F4dPcdGoVQp4MQqQIKowVd/WIs7odXdsPkjaD4CfFrUdhoAjGjrz8drTzB7YyKDWvrW3NS1gRR2dnhPmYzr8GHoZsxA9/YM7Jcuo/+Ee/l70QI2/fAtAx99+uL1kiTR1L0pTd2b8njbx8kqziI2JZbYlFhWJK1g8YnFOKgc6OLfhb5Bfekd1BtvR+9Gmbu1xenj0NppCddWrVBiDc08mvFw64f5+tDXDI8YTreAbo0yzuWKy0wYSowiNe4WIEkSMeGe7D5t2SfUWH8mCIIgCDePjPxSJv+8n92ns3mkRzivDmuOWtl4W/J9XOwZ2safoW38ASgoNRJ/Npc9ydnsSc7m1z3nWLA9GbB8QNcpzJ0wTyfcHNVoHdS4O2pwc1Tj5qBB66jG1V5V499Xsizz2tJDbD+Vxcyx7egeWfP+7NKk0xRs2oTX5Mko7C0f7io9PSk7cykQGt42gOnLj/Db3nN0CHGv6VGNqs6BkCRJjsDrQHWRRXU/Obkex2sa+wksaXQEuWuxz8qhKCcHl8GXptK0ix8n9+o5cziLiGhvOP4PBHUG51q83A+bCadjLSlyj64FRQ2luKuhUip4qk8TXlt6iG2JWfSMss7m/ZrYhYcT/O23GFb+je6DD+D1abTo34MDa1YS0qoNTbv2rPY+TwdP7o66m7uj7qbMVMae9D1sOreJzSmb2XRuEwCtPVvTO7g3fYP60tyj+U37AhenjyPaOxqF1Hh/wDzZ7knWnFnD2zve5o+Rf+Cgcmi0seCyZqoiNe6WEBPuwYoDaZzLLibEs34NfwVBEATbEH8ul6d+2EdOURmf3hfNqPa1/mzfapztVPSM8rr4HlpuMnMkzXAxMIo9kcEfBTXvy1EqJLQOatwc1GgdKwKlin/PKSxjWXwaUwdEMaZj0FXnkb1wIZJGg/uE8RePaUJCKD9zaUeNs52K4W39WXHgPP8d0QoHTe3fu62lPitCTYBw4MJqUBCwX5KkGCwrOpcnQAYBaRXH+15xfFPF8aBqrq+WLMvzgHkAwR5usrQvDsnODudel176Q1p64OCi5sSudCIijHA+Hgb8t3bfmZMXDP0Ifn8UdsyGHlNrd1+F0R0D+Xz9SWZtPNnogRBYPnHWjhiOc+9e6D/5hNBFv5LePJRVsz7GOzQCd/+Aq96vUWroEdiDHoE9eE1+jRM5J9icspnNKZuZGz+XOfFz8HbwpltAN3oG9qSbfzfc7K2ztNtQ2SXZJBuSGRVZq0zKerNT2jGt2zQeWf0Ic+Pn8kKnFxp1vIuBkOghdEvoWrFPaOfpLBEICYIg3MJ+3XOWN5cl4O1ix+9Pd6d1oPZGTwkAtVJBu2A32gW78VivCMASHOUVl5NbVEZuUbnlq+LXecXl5FQczysuJyO/lJP6fHKLyikoNTI+Jph/DYy66pjG7Gzyli1DO/IuVJ6eF49rQkIo3Lmz0rVjOwaxZF8K/xw+zz0drh5cNYY6B0KyLB8CfC78WpKkZKCTLMuZkiQtB6ZIkrQIS2GEPFmWz0uStBp477ICCYOBV2VZzpYkKV+SpK7ALuAh4ItaTUShoHTDRpx69UTh5HTpsFJBVGdfDsemUtJ6P/Zw9f1BV2o9GhKWwsZ3odkw8Iqs9a12KiWP945gxl9H2Hcmm46hHrUftwGUrq74T5uG26hRmKdPZ0NxMUtfnMz49z7GIax2aWOSJNHMoxnNPJrxRNsnyCzOZEvKFralbWPTuU0sP7UcCYlWnq3oHtidHgE9aOPdBrVC3cjfXfWs3T/oajr7dWZ01GgWHlnIHeF30NKzap18a9HlW3pC+V6H1DhZlpGRG3VF7XYX6eOMh5OG3aez67VJVhAEQbi5lRnNvLUigZ92naVnpBefj2+Ph9PN3QdQrVTg5WyHl3Pd3jVMZrnaEtlXylm0CLm0FI9JkyqPGxqC8c8/MRcXo3CwZNjEhHsQ5unI4r3nbkggVJvy2b8AO4BmkiSlSJL06FUu/xtIAhKBr4FnAGRZzgZmAHsqvt6uOAbwNPBNxT2ngH9qM3FJUmDU63EdXDVDr1kXP8xGmVM7T4M2pG77fSQJhv8fqOxh+RQw160c4fiYYDycNMzeeKpO91mDQ7t2tP7tN3rH9CLHVM7fTzxM5lfzkC8roFBbXg5e3B11NzP7zCT2vlh+GvYTT0c/jUqh4ptD3zBx1UR6L+rN8xufZ/HxxaReZZm1McTp41Ar1LTyanVdxnuh0wt42Hswfft0jGZjo42jr1gR8rkOK0Ivbn6RJ9Y+cUtUELxZSZJE5zB3dp3OutFTEQRBEKxMbyhh/Nc7+WnXWZ7sE8GChzvf9EFQQ9QmCDKXlpLz08849emNXZMmlc5pQkKBSyW0wfL35NhOwexMyuZsVpF1J1wLtakaN16WZX9ZltWyLAfJsvztFefDZFnOrPh3WZblybIsN5FluY0sy3svu+47WZYjK77mX3Z8ryzLrSvumSLX8q1MIcugVuPct2+Vc94hLrj72nP8jLeliWpd97i4+MEdH8DZHbDn62tffxlHjYpHeoSx4ZiehLS8uo1rBZJKRftXXiO6z0CS3Z059N08zj7+BObCwno/U6lQ0ta7LU+3e5ofhv3AlnFb+LjvxwwJG8KRrCPM2DmDO36/gzuX3sn7u94nNiWWovLG/Y85Th9HK89W2CmvT1EBV40rr3V5jaPZR/nhyA+NNo7OUIKDWomrfb3qmNRaWkEa686sY9f5XWxN3dqoY93uYsI9OZddTHqebVZnFARBECozmWUW7T7LsM+3cCTNwKwJ7Xl1aAtUjVgUwVYY/voLU1YWnlesBgFoQi2V48rPnq10/J4OgSgkWLLvXJV7GpvN/o4py8tx6toVpatrlXOSJNE0soDzZS0w+NaqLVFV7cZB5CBYNx1ykut064PdwnCxUzFn0/VfFbqg7xOT8Y2I4nBUCLpDBzj72OOYDIZr31gLrhpXBoUOYnr36awevZo/R/3JK51fIcgliD9O/sHk9ZPpuagni48vtsp4VyoxlpCQlUB738ZPi7vcwJCB9Avux5z4OZwzNM7/rOmGUnxd7Rq9QMXSxKUAeDt4Myt+llgVakQxYZYU2d3Jooy2IAiCrduWmMnwz7fwnz8OEerpxLLJPRjR9up7sm8XsiyTvWABds2b49i1a5XzmgsltM9UDoT8tQ70ivJmyb4UTI3Qj/NqbDYQUhlNuAweVOP5ppr1AJw4H1q/ASQJ7vwUJCUsf9bSmLWWtA5qHuwWyt+HznMq48Z0lVeq1Ix4/hUkjZotUYGsL8hg4yMPYTiTbNVxJEkiQhvBAy0fYO7AuWwdv5V5g+bR3KM5cw/Mpdxs/YZeCVkJGM1G2ntf30BIkiRe7/I6KoWKt3a+1SjBg85Q0uhpcSaziaUnl9I9oDtTO0zlSNYRNpzb0Khj3s5a+LvgbKdit0iPEwRBsFmnMgp4bOEe7v9mFwWlRmZNaM+Sp7rRzK/mPjq3m8KtWyk9mYjHpInVfqCr1GpRarWUXbEiBHBvp2DS8krYlph5PaZ6kc0GQmqzGZcBA6o/Kcu4nltGgNt5ju/JrP8LqzYIhrxjKam9b0Gdbn2kZzh2KgVf3sBVITdfPybOnE2vCZNQBAdxQGnkm5ensOStVzm6ZSNlJcVWH9NOaUe3gG4XCy7Enou1+hgXGqlG+0Rb/dnX4uvky/MdnmfX+V0sP7Xc6s/XG0oavWLctrRt6Ip0jG46mhERIwhzDWNW3CzMct32wwm1o1Iq6BjqLhqrCoIg2KDcojKmL09gyCex7EzK5pU7mrPuhT6MaBtw07YXuVGy5y9A5e2NdtiwGq9Rh4ZWaqp6wcCWPrg5qlm89/qmx9lsIKRwckLlUUNVtvPxUJBOs3aO5OqK0Cfn13+gDhMhvA+seRPyUq59fQUvZzvGdQ5haVwqKTnXf/PXBS4eXsSMHMPDc+Yz9sEnicgpQH/4IH/P+j/mPvEAKz//H0n792AyWrcAQM/Anvg4+LDk5BKrPhcsgVC4Nhx3+xvTfGtss7G092nP//b+j6xi633KL8syOkMpvi6Nu+9pyYkleNh70DeoLyqFimeinyExN5HVyasbddzbWUy4Byd0BeQU1r1wiSAIgnD9lRnNfLv1NH3+t4nvdyRzb+dgNr7Ul6f7NsFeff373dzsSo4fp3D7dtwfeABJU3PBiCt7CV1gp1IyKjqQNUd05BZdv78rbTcQqmZv0EXHVwESTQZ1R6lScHxXev0HkiS463OQzbDiuTqlyD3ROwJJgnmxSfUf34pCRtzJ4I8+oX9yBj1zS2nevjPJ8ftY+uFbfPXUQ6z7di6px49aJeVLpVBxd9TdbEvdRlpBja2h6swsm4nTx12Xstk1UUgKpnebTlF5ER/u+dBqz80vNVJcbsJP23grQhlFGcSmxDIyciRqpaX0+ZCwIUS6RTInfk6jVsS7ncVU9BPaI/YJCYIg3NRkWWbtER1DPo1lxl9HaBuk5e/nevHe3W3wbuQPKm1Z9oKFSA4OuN93b/UXpB+GggxLIHT+POZqKhqP7RREmdHM8gPWe2+8FpsNhFRuV2nseeIfCI7BzsuXsLZenNyrw2RqQNqPexgMnA6J6+DPKaA/WqvbAtwcuKd9EIv2nEOff3NUjHJs357QBfNxzysg4o+/efjf0xn58psEt25Hwsa1LPrvy3w79TG2LvqBrJSGLU/eE3UPcGljvjUk5SaRX5Z/QwMhgAi3CB5v+zj/nP6H2BTrpP9dj9LZyxKXYZJNjI4affGYQlIwJXoKyYZkViatbLSxb2dtg7RoVAqRHicIgnATS0jL4/5vdvH493tRSDB/Ume+fySG5n5X+fBdoFyvJ++vv3C75x6U1b2fn46FeX1hwwxL5ThZpjylapZVqwAtrQJcr2t6nM0GQihqmLohDc4fgKaWanHNuvpRUlDOuYQGvoB0fgxinoBDv8GcrrDwTji6AkxX/wT96b5NMJosy6s3C4dWrQj94XtkZFIefoQgJ1fufP4Vnpr3I3c88y/c/ALYvew3Frz4NMv+N4OivNx6jRPgHED3wO4sPbnUaisNcRmW/UE3OhACeKz1Y0S6RTJj5wwKy+tfnvyC9LyKZqqN9ImTWTbz+8nf6ezXmVDXykVE+of0p4VHC0uBC5P1C1zc7uxUSqKD3cSKkCAIwk1IbyjhlSUHGfHFVo6cN/DWXa1Y9Xxv+jX3EfuAaiHnp5/BaMTjoQerntQfg0UPgLkcsk6hvlg5ruo+IbAUTTicauBImnUqHV+L7QZCNTmxyvLPZkMBCGnlgb2zumHpcWAJvIb9D144alkdyj4Nvz4An7WDLf8HhdVXuQjzcmJE2wB+3HGGvKKb5wXTLiqKsB9+QLK358zESRQfOICdoyOt+gxgzOszePLLhfS470GS4/ex8OUpnI7be+2HVmNM1Bh0RTq2pW6zyrzjdHF42HsQ4hJilec1hFqpZlq3aegKdXwR90WDn6erWBFqrGIJu87vIrUgtdJq0AWSJPFs+2dJLUi16gqecEmXcA8OpxkoLBXph4IgCDcDWZb5avMp+s7cxB9xKTzaI5zNL/VjYvcw1KInUK2Yi4rIXbQIl4ED0IReUak5Xwc/jQWVHYT1gtwzaMLCgKq9hC4YGR2ARqngt+vUU+jW+10+vgrcQsG7OQBKpYKoTr6cPpBJabEVXkCcPKHnv2BqPNz3E3g2gfVvw8ctYOlTkLqvyi3P9GtCYZmJSQt2sy2xAVXsrEwTFkbYjz+gdHPj7MOPULh798VzTm7udL3nPu5/7xMcXbX88cF0Nsz/ivKy0jqN0Se4D572nlYrmnBhf9DN8glNtE8045qP4+ejP3Mg40CDnqXLv5Aa1zgrQr+f/B2tnZaBoQOrPd8zsCfR3tF8dfArSk11+30Wrq1zmAcms8z+szk3eiqCIAgCsPxAGu//c4xuEZ6s+Vcf3hjREq2j+kZPy6bkLluGKS8PjysbqJYVws/3QlEmTPgVQrqBIRWlixMKF5cqvYQucHPUMKiVL8viUik1mhp9/rdWIFRWBKc3W9LiLntRbtbFD5PRzKn9euuNpVRBixEwcTk8s8tSXe7oCvi6P3w9AA78CkbLy2RzP1c+GtOWtNxi7v9mF2O/3EHsiYybIiBSBwYS+sMPqPz9OffEkxRs2XrppCzjHRrO/e99QoehdxG3agU/vfov9Mm1L/6gVqgZFTmK2JRYdIW6Bs01oyiDlIKUmyIt7nLPdXgOb0dvZsXNatBz9IZSXOxVOGpUVprZJdkl2aw/u547I+7ETll9oCVJElPaT0FfpOe3479ZfQ63uw6h7igVktgnJAiCcBPIyC9l2vIEooPdmPdQJ8K9nG70lGyObDaTvXAh9m3b4tChw6UTZhMseRTSD8KY7yCwA7iHgmxGMqSiCQmptpfQBfd2CianqJz1R6343l6DWysQStoExhJodkelwz5hLmh9HDi+s4HpcTXxaQ7DZ1rS5oZ+BCW5sPQJ+LglrJ8Beanc2ymYzS/3Y8bIVqTmFvPQd7u5Z+52Nh7X3/CASO3rQ+iCb9EE+ZHy9FPkf3C/JaB71w9+HIOq3EC/SU8w+tW3KCnI5+fXX2DfymXI5soFKMxlZRQnJJD7++/o3v+A/I0bARgdNRqzbGZZ4rIGzfNC/6CbLRByUjsxImIEe9P3UlBW/wa6OkMJfo2UFrfi1AqMZmO1aXGX6+LfhRi/GL459A1F5Teu7PutyNlOResAV3aJQEgQBOGGkmWZN5YdoqjMxMyxbVEqbo4sE1tTsHEj5WfO4vnwpEuZOrIMq/5jKVw29KOLW1Vwq0ibyz2DJvTqgVDPSC/8tfbXpWjCrRUInVgFGhcI7VnpsCRJNOviR9rJXPKzG7F6m70rdHkSJu+BB5dCcIxl/9CnbWDxQ9jnJvJgtzA2vdyXd+9ujd5QysPz9zBq9jbWH9Vdv4DIZARdAsT9BCtfgm8GovqqLaFtd2CnLSZl4T7yTpqg7X2WSh9f9oIzOwiL7shD/5tFWHQnNn3/DYv/8zwp874i7dXXSBp1N8c7diJ59BjOv/4G2T/+SMrTz5DxxSyCnAPp4t+FP07+0aCmnXH6OOyV9rTwaGHFH4Z19Anqg1E2sj1te72fkd5IzVRlWWbJiSW0825HpHvkNa+f0n4KWSVZLDq+yOpzud11DvMg/lzudVnuFwRBEKq34uB5VifoeGFQUyJ9XG70dGxW1vz5qAMCcBk06NLBnXNg9zzoNgViHr903K1ib3fOGdQhIZSnpiKXV793XqmQGNMxiNgTGaTnNW7V5VsnEDKb4cRqiOwPqqqNnJp18QPgxO5GWhW6nEIBTfrD+F/guXjoNtmyWjWvHxz+HTuVkvu7hLLxpb58OLoN2UVlPLpwLyO+2MrqhHTrBkRmk6Xcd/wv8Pe/4ZtB8H4QzO0Ofz4DB34BpQY6P4Zy/DeE/LIUx04xpK3IILe8Dzy2jvIyOwreu5vMVyeS/cZ/abV2C63P6TmflMgfq5dxcs8OVN7eeE6aROAnH9Nk1T8027cX7d13kzl7NqnP/4uxIXeSVpjGjrQd9f5W4vRxtPZqfbH/zc2krXdbtHZaNqdsrvcz9IbSRtkftF+/n2RD8jVXgy5o79OenoE9+e7wdw1a4RKqign3oMxo5mBK3o2eiiAIwm0pI7+UaX8epl2wG4/1DL/R07FZxYcOUbx3H+4PPYikqkjpP/InrH4dWtwFg2ZUvsE1ECSlZUUoJBRMJsrTau4XNKZjEGYZft9ftcy2NVl/M8KNcj4eCtKh6dBqT7t6OeAfqeX4znQ6DAm9fpvt3cNg8Azo+gz8NgmWPAIpe2HQ22hUau7rHMI9HYJYFpfK7I2JPPnDPlr4uzK1fyRDWvmhaMhybeI6WD4VDKmWX6udwL8tdHoYAtqDfzR4RlYqRa4Egud9RcqzUzn/+hvoPT0xZZUC7sBu1O4aHDr2oGPrdrQK8GVj7Fr2njtDScfW9Jv0OBp7h4vP8n/vXeyiotDPnEnk2TNE3OHKkhNL6BHY46rTlmW5yu9PUXkRx7KP8UjrR+r/82hEKoWKnoE92Zq6FZPZhFJRt67TZrOMPr9xVoR+P/E7zmpnhoQNqfU9U6KnMG7lOH44+gNPt3va6nO6XXUOszRW3X06++K/C4IgCNeHLMu8uewwhaUmZo5pi0pUhqu37PkLUDg74zZmjOXAud3wxxMQ1AnumVe1zY1SBdogyDmDJnw4AGVnz1atNFch1NOJLuEe/Lb3HM/0bdJo7+23TiB0YhVICogaXOMlzbr4semn45zcoyOwqTuOWs31C4hc/WHiClj7pmXZMC0exi4AF1/USgVjOwVzd/tAlh9IY9aGRJ7+aT/NfF14dkAkw1r71y0gKi2ANW/AvvmW6nmj5kJAB/CKglq8oCscHAiaM5uMTz/DlJODfYsW2Ldojl3hDpSxb4PLFrjzUQjsyIRhw9n+28/s/nMJKUcPMezZl/CPbAZYUhI9H3kYu8gmpL7wIm99Z+T9kRvI7JqJl4MXAMX5BjLOJJN5LpnMs8lknE0m69xZHFxdCWvXgbDojoS0asehvEOYZNNNtz/ocn2C+rAyaSWHsw7Tzrtdne7NKSqj3CRbvYdQXmkea86sYWSTkTiqHWt9XyuvVvQP7s/3Cd8zofkEtHZaq87rduXupKGprzO7T2czud+Nno0gCMLt5a+D51mVkM4rdzQnylekxNVXeVoahtWr8XjoIZTOzpCdBL+MAxd/GL8I1A7V3+geCrln0VzsJXQWetU8zr2dgnnxtwPsPZPTaB8e3jqB0PF/ICjGUt66Bk06+LDzzyTWfncEALWdEjdfx4tf7hX/1Po4oLFvhB+NSgNDP4SgzrD8WfiqtyUYCu1mOa1UcE+HIEZGB/LXwTS+2JDIlJ/jiPI5yTujWtMloubv7aIz22HZ05BzxpKf2f9NUNd9lUGh0eD775evONoZIrtbVra+HQJD3kMZ8zi9xk8kvF1H/p79f/zy5st0H3s/MaPGoKgIupx79yb4px85NHUyj6zM48/M53HzjiDjbDKFOZc2jtu7uOIdEkbrfoPIz8rg6NbNHFy3CoVSCYFa2jhoCequrXbF6GbQPaA7SknJ5nOb6xwI6QyWCoN+WuuuCK1MWkmpqZTRTWuXFne5ye0ns3H5RhYmLGRqh6lWndftLCbcg2VxaZjMstigKwiCcJ1kFpTy34qUuMd7iZS4hsj+4UcAPB58AIqy4ccxIJvh/iXg5FXlerPJzIovDhAu9aNt+ZcovbyQHB0pO1t9U9ULhrbxY9ryBBbvOScCoavKS7WU6Bs4/aqX2TupuX96VzLO5ZOrK7r4lZ6Ux8m9Orhsa46Tm12l4OjCl6uXfcNfwtuMAZ+WloasC0fA4Hegy1MXS34rFRIjowMZ0TaAfw6fZ+bq4zz43W6+fKAD/Zv7Vv/M8hLY+A5sn2XZkDZpJYRdPQWtXoI6wZOxlmDrn5fhzDa46wuCWrbmoY++YP23c9n26w+cjt9HRPtOZJy1rPRkp6Ugu9mDmz2KlByknOhOMCsAACAASURBVOOEdorBKzQc75AwvELCcHJzr/SzNRnLSTtxjOT4fcRu/ZOOZ934443XcHJzJ7Rte8KiOxLaJhpH15tjtUJrp6W9T3tiU2LrHDhc6iFUt0DIbJaRAKmaF2pZlvn95O+08GjB/7N33mFRXGscfmc7LCy9dxCRXlTsYu81ajRqmqb33m5y02MSjYkmGtM0ajR2E3tXLKjYUEARlN57r1vuH2uNgKAY482+z+Ozy8yZs2fWYZjf+b7z+/ys/FrVL0B7i/YMcR/Cb+d+Y4rvFKyMrgpxrUaDTqdFLPnnrdf6p9PZ3ZLfjqRzLqecAKd/xrVrwIABA//PGFLi2g5NZSWlq1ejGjwYqY0lLB0DZZnw0J9g3bghU9z+LDITShDsPQkiD0Fdi8zVlYYmagldxlgmYUSQAxtOZ/P+KH9M5G0vW/4/hFDiNv1rE+uDrkVhIsXF1xIX3+uVpbpeQ1lBDSW5VwVSSV41icfyqL+mEKuppQLPUBu8Qm2w9zRr9AG0Rdj5wRN7Yf3TepvBzGMwci7ITa40EYsERgQ50sPLmocXRfPEkhPMmRTK8CCH6/vKPqUv5lqQAB0f1Qura/ppc4wtYdLvEDVXX0w2NxbuX4zCPpDhL7yOZ2gndv3yPdnnz6KyscPa1Y12nbth7epGvC6Z1Hlf0u2IDqVEhdNDjyNWqRr9GLFEiotfII4d/HidBQy3Hch90j6knj5J8qnjnN2/BwQBey9v3IM74hEShn279lciUXeDCOcIvjrxFblVudgr7Vt8XN4lV5TWrhHaPO8MRZkVhA5yw6+XI1LZ1XOPK4wjsSSRd7u826o+r+XpkKfZnradhXELeb3z1QjhpjlfUJafx5RPZ+sjdgZaTLiH/t5zNKXYIIQMGDBg4G9gc2wOW+NyeWOIjyEl7jYpXbMGbWUllo88rJ8UTz+srxV0Kbvpr9RU1hO9MQWA4golmHIlPa4uKemmnzehkwsrjmWw5UwO93d2actTAf6fhJCFO9j43HIXEpkYKycTrJyuFxA6nY6aigZK86opzqkiNbaQ2MhMTu/OwNhMhmeIXhQ5epsjau0Mg8IMJv4Gh76BPR9D3ln9z39R1BZKGcse68K0X4/x/O8nqaoP4v5OLqBp0Ntz758JShuYsha8B9zyd9AqRCLo+ZLeInzNNPh5gN4vPuwhfHv1xatzV3RaHXLj69eleGi60C/9J8x8neix8gipEyfhPH8eco+mw9RJpUlUNVQR6tkFf8/++Ef0R6vVkJd8gdSYk6ScPsHRdSs5svZ3FEoTQoeOpNu4BxD+ulDvb6C3S2++OvEV+zP3c7/P/S0+7nJqnI1Jy9cI5SaXkR5fhKmVgoOrkzixLZWQga4E9HZCppCwNmktRhIjhnkOa/V5XMbDzIMRniNYeX4lD/s/jK2xLaV5uSRFHwadjpjtmwgbNvqW+/834mBmhKulMdEpRUw3OBYZMGDAwB1FnxIXT7CzGU/08rzbw7mn0anVlCxZilGnjhjlr4P4dfpsrICm0++P/plMfa0Gny72nD+aS73SCFlpOjI3Vyr27kWn0SA0M6Ea5mqOl42Sw8lFd0QI3fuxwfoqSI6E9kOupJa1JYIgYKyS4ehtTkBvJ0Y8G8y0mb0YOM0Pe08zEqJy+PObGBa9eYg9S8+RFleERt2KWjkiEfR6Baaug6p8+LEPnNt0QzNThZTF08Lp0c6aN9ac4Y8du/XiY98M8L8Pnjn894mga3HrDk8eANeusPEFfWSqvgqZwugGEQQgF8sZ5TWKee5JWCz4Bk1JCakTJ1F56FCTH9FYIVWRSIxDOx+6jX+AyR/P4umflzHipbdw8Q/i8Jrf2TTnSxrq69r+fG+Ch8oDF1OXVtto51XUYqWUIZO0/Ffy5PY05EoJk94LZ+yrYVg7m3B43UWW/ucwUZsS2Zm0m0FugzCV3d7s11PBT6HRavjpzE8AnN65BUEQcPD24dCqZVSVltxW//9GOrtbciy15K4XUzZgwICB/3f++2cclbVqZk4INqTE3SYVO3bQkJ2NVS9XOPi1Pgupx0tNti9IryD+YDaBfZzwCrMBoFjtDCWpSF1doaGBhpzmy9oIgsCKJ7ox+/7Wrb1uKff+FZEcCZo6vRD6m5AbSWgfbs/QJwOZNqsXQ54IwMXXkgsn8tn03WkWvn6QnYviSY4pQF3fwsKJXn3hiUi9s9vKKbDrA33h02swlkn4+cFQZjpGMvTQRGoKUmDCYhj3ExhZtP2JthQTG72Q6/M2nFkJP/WDgvNNNh/nPQ61Vs12i0zc16xGamdHxhNPUrxkaaMPhqfyT2FrbIuj0rHJPo1MTPHp1pORr7xNxNRpJB49xOqP3qG6rLRNTrGlCIJAhHMER3OOUqOuafFx+eW1rVofVJxdRcrpQoL6OCNTSHD0NmfUi6GMe7Mjdp4qTm3KZFz0m4RnDqO2qvGCZS3FxdSFsd5jWZO0hvTiVOL27sS7czeGPPMy6vp6Diz/9bb6/zfSxcOS4qp6LhYY6jQZMGDAwJ1i85kctsTm8uIAb9obUuJuC211NYU//oTUwQaTnAXQbiAMm9VkEEKn03FgVSIKpZTwER5Y2CsBKNF6XK0lBDTcxDABwMZUfsdMsu59IZS4FeQqcLsDxgAtQCoX4xVmy6Dp/kyb2ZPhzwThGWJNWmwRWxfE8svrB9n+UxxJx/NuLorMXWDaNr3CPvg1/HYfVBVe3V+cgvy30Uwo/oFE03B6VX7OzMwO/4xZZZEY+rwFD67Tj/nHPnByCTQytnYW7QixCWFN4hqkTk64/f47Jn36kPfZZ+T+97/o6uuva38q/xShtqEt+iUQBIFOI+9j1CtvU5CWyvJ3X6UoM6OtzrJF9HbuTZ2mjuic6BYfk1deh30riqme2pGGRCYisK/zddvtPcwY8WwwMb3WU2qdTca+Wpb8J4rDf1ykprK+id5uzhNBTyAgsGTdTGorKwgZPBxLR2c6jhhDfORuss6fu+W+/41cXicUnWKIphkwYMDAnaCwso73/owjyNmMJ3sbUuJuB01ZGenTplOXeB5bnzQEez+YsEhfG6gJko7nkXOhjG5jvJAbS1FZKxBLRJSIffW1hNwuWWinN2+YcKe5t4WQVguJ28Grn96a+i4jkYpxD7Km/8N+PDqzJ6NeCMEn3I6sxBJ2/BzPkv9EcWxzSvMz9BI5jPwGRs+HjKN6i+3M43B8IXzfA/LiYMz3+L28iYHhAczbe5EPN55Fq/0HiCHQ/188dVBft2jD87BktN5f/i+Mbz+e1PJUTuSdQGyixPnbuVg9+SSlq9eQNm0aDfn5AORU5pBbldvq+kHe4d2Z+P4MGurq+P2910iPO90mp9cSOtl1wlhi3Kr0uNzylhdTrSiuJTE6D7+ejhiZ3Hjdny8+zxH1PrwnGjHpvXDc/K04uT2NJe9EcWhNElVlrU8ZtFfac7/P/VRFJ6FydMDZLxCArvdNxMTKmt0Lv0erbWH00wBuVsbYmMqJTim620MxYMCAgf9L3v8znspaNbMMKXG3hbqwkLSHHqY2Pg6nvmpU7ZUweTXIm46wNdRpiFp7ERtXUzp01xt8icQizO2MKda6Q2kaEltbBLlcX0voLnJvXxk5p6AyD3xu7hb3dyMWi3Dxs6TPlA488kVPRr0Ugo2riuiNKSx+J4qDq5OoKK5tuoPQKTB9hz7S8nN/2PSy3rr66SgImYxYLOKzsYFM7+nBr1GpvLn2DJp/ihi6XDx2+GzIOgnzu8Ohudel+g1yH4Sp1JQ1SWsAEEQibF9+CcdZs6iNjeNC/wFkvvAiCZuXI2h1t1RI1b5de6Z8OhsTSyvWfvZf4vbubLNTbA6pWEoPpx5EZka2KFqn1mgprKxrcWpczC79TSNkgGuj+9cmrUUqkjLScyRWTiYMfjyAB/7bBc9QG07vzmDpu4fZvzKRypJmrr9GGK3sh3WZjGxv4Up0TqYwos+D0ylITeb0zq2t6u/fjCAIhHtYEp1SfPPGBgwYMGCgVWw+k8Pm2BxDStxt0pCdTdqUqdSnpeDctxKVpwgeXK9/zmuGE9tSqSqto9f93oiucVe2dDCmpM4GStMRRCJkri6GiNBtcX4bCCLwHnS3R9IsIpGASwdLRj4fzMR3w/EMtubM3kx+e/cwu389S3F2VeMHOgTr1w2FPqjPw3zwD3363CUEQeDd4b680N+b1ScyeXHFKRo0rTBquJOIRNB5Ojx7VL/+aed7ekGXcwYAI4kRwz2Gszt5D4VlxdRWNlBVVofQrR+WC1dhNmkK1ceOYf/+z3w/X4vlkm3UZ7Q+xU1lY8sDH8/ExT+I7QvmcHDFUnTaO/8d9XbuTX51PudLml4rdZnCynp0OrBrQWpcTWU9Zw9m0z7cDlPLG4VTrbqWTcmbGOA2AHOF+ZXtlg5KBj7qz+QPuuLd2Y74yCyWvneYQ2uSUDe0LJKTuu8gSMVskB3lYunFK9vbd+2Ja0AQh1Yupbq8rEV9GYBwd0uyy2rJLKm+20MxYMCAgf8bii4VTg10MqTENUZ9rRpdCybO65JTSJ0yFXVhPq4RxZh4memXb9zEobmsoIaYnRm0D7fDoZ35dfssHJSUVxvTUF0FteVIXd1atEboTnJv22cnbgWXLvq6NvcI1s4mDJzmT5fRnpzelcHZQ9kkHMnFPcia0EGuOP7losHYEkZ/12R/giDwysD2mMjFfLYlgZp6DfOmhKGQimmo01CcU4Wlo/K6+jJ3Go1Gy4EVieSllqNR69CqX0BTOx3tmQo0MSloRHlokWCu6cYjdGPl4Zgb+pAZdcP72ZHsT5pBp9iLlPz0CyU//IRxeDjm48dhOmgQIkXLIihyYyVj33yf3Qu/5+j6lZTmZjPkmZeRyO5cOmVPp54ICERmRNLBskOzbfPKL9UQMr35+cTuzURdryV0kFuj+3em7aSivoLx3uMb3W9uZ0z/h3zpPMyd41tTidmVQca5EgZN98fSUdnk51aXl3H+8AF8e/dFaryCeTHzmN1nNqC/Bvs9+hRL3nieA8sXM/ip1hWTbRV1FaCua7Ry9b3G1XVCxThb3OiwaMCAAQMGWs9/N8RTYUiJa5TywhpWzziOrZspw54OQixt/PupPXeO9OmPgaYet97ZKLw99WvATW9eH/HQmiQEsUC3sTcWV9UbJgiUqp2wKU1D5upK1cGD6LTau1LyBO5lIaSph9wkGPDh3R7JLaGyMqLXxPZ0Gu5O7L4sYvdmsn7WSRy8zAgd7IZ7gFWrirVO6+qOtFTNhr0pfJZ0EB+pnLK8anQ6sHYxYewrYciM7vx/t06nY9+y8yRE5eDiZ4lMLkYkESGWmCHSNSDOPoq4MA6RkSniDgNZXXSUeuqYFvQoYokIsUSEIIKMc8UkHM3DquFRUnxrcXjYHbuMg1T/uYbsN95E9PEnqEYMx3zceBT+fjc1UhBLJAx8/Dks7B3Zv2wRFUWFjH79XYxVd6agpbWRNYHWgezP3M+TwU822/ayELI3a14I1deqObMvE49g6yZFy5rENbiautLZvnOzfamsjej3oC+eITbsWXKO1TOO0WOCN/69HBv9LuP27kTT0ED40LFMLZTww5kfSChOuCLyrJxdCR06ihOb1hPUfzAO3rde06tZVj4I5dnwXMuNKP6p+NiZolJIiE4p5r4w55sfYMCAAQMGmmVLbA6bz+Tw+mAffOwNKXHXolFr2f5zPOp6Delni9mxMJ7Bj/nfUAOz+uQpMp58EpFMwLVnCnLfEJi8qkVBh4yzxaScLqTrGE9MLK7PcqlV12LuYARAsdoFm0uGCbq6OtT5+UjtW16Evi25d4VQbbn+9R+4Pqg1GJnICB/hQehAV85FZROzM4Mt889g4aAkbJAr3p3tEP+ltoymQUtRdiX5aRXkp5WTn1ZBcXYVOq2OAcioqlVzwURH30GumKnkRK29wJYFZxj5XEiT6r+tOLYphYSoHDoPdyd8ZGMh6WC4uBc2vggXvyPDfxAfVCfwaMAoAmxDrrTq0NUBee9S5q1ZyuDaiURtzUUsaY/nxNl4WJZjFPUHZevWU/r7CuQ+PpiPG4dq5AgkFk3biAuCQOdR4zCztWPrd7NZ/u6r3PfWB1g63pmH0N7OvZkXM4/CmkKsjZqOYORV6M0LbG+SGnfuUA51VWrCBjceDUouS+Zk/kleCnupxTaT7oHWTHw3nN2LzxG5/DwZZ4vpO7UDChPplTZarYbTO7fi4heItYsbD9k9xPKE5cw9OZf5A+Zfadd9/AMkHIpk98LvmfzpV4hEbRyFTIuC5L369yWp+iLK9zAikUBnd0uiUw3rhAwYMGDgdimqrOO9PwwpcU1x5I+L5KeWM+SJACpL6ji4Ook9SxPo/5DvlYn3ykOHyHzueaQqOa7h55EG9oZJy0DWdMbIZTQaLQdWJaKyMSK4//WFT+OL4nlm1zOM9hiDkSiYErULlKYjc9U/99Wnpd81IXTvxgzrysDCA6zb3+2RtAlSuZigvi5M+bgrAx71QySC3YvP8dt7h4nZlc7Zg9nsW5bAqs+O8eNLkayecZzI5edJiSlEqZIRNtiVoU8F8vCM7gQ87ctvsmq+yMjBuYst/R72Jet8KTsXxd9Rd7mzh7I5tjmVDt0d6DzCo+mGXn31BWC7P8/Qc7sx1upYc+zrG5qdKT9FgsNhJr4Tzv3/6YxfT0f9LMaOWvYqxlD+/gpM3/wAQSIh77PPuNA7gsyXX6YmPr7Zcbbv2pP7359BQ20tv7/7GhnxZ2731BslwiUCHToOZh1stl1eWS1ikYCVsmkhpFFridmVjqO3OfaejUex1iWuQyJIGN1udKvGqTSTM/K5YHqMb0dqbCErPokm6/xVW+eUUycoL8gjeNBwAFQyFY8HPs6BrAPsz9x/pZ3MyJiIqdPIS75A7O4drRpDi9j3OchM9O+TW1ew9p9KuIclyQVVFFT8/cV/DRgwYOD/ifc3xFNe22BIiWuE1DOFxOzKIDDCCa8wW4L7uxA+0oPzR3I5sCoJnU5H+Y4dZD71NDIrBW7dEpB2Gg6TV7ZIBAHE7cuiJLeanuPbIZFenQiNzolm2rZpFNcWc7YkHjPbq85x0ku1hOrv4jqhe/dKqavUF1G9QwWW7hZisQifLvZMfDecEc8Fo7I24tCaC+z9LYGk4/nIjSWEDHBh8OMBPPhJN6bN6snIF0LoOtoLzxAbTCwUDAty5MeHOnEhv5KJPx6h0l5O+FhPLp4s4MCKxDtSdygtroh9y85fcsrzuXlEQqaEQZ9gPH0XwzQytucfp2LFZKi4WmE4Jj8GHwsflFIlNi6m9J7Unke+6MHA6X6YWhlxbEc2G6JtiOvzLsxcjmriA1RHHSZt0gOUrF7d7Mc7ePsw+ZNZGJtbsObT/xIfubstvobr8LHwwdbY9jqx0Bh55bXYmMgRN5MKmRidR2VJHWFDGo8G1Wvq2XBxA31c+jQbfWoKQSQQMsCV8W92QioX88c3pzjyx0U0Gi0xOzZjYmFJu85dr7Sf6jsVd5U7n0d/Tp3m6kN8hx4ROPsFcHDFEmoqyls9jiZJi4KUSH3RXlNHSN7Xdn3fRS6vEzpuiAoZMGDAwC2zNTaHTWdyeLG/tyEl7i9UFNeya/FZrF1M6D7+6rqdTsPcCRngQuy+TCJnbiPrpZdROJngFn4WSbfJMH6RvqRLC6ipqCd6Uwqufpa4B119Btmdtpundj2Fg9KBbg7dSKtIw8JBSYnWDUrSkDrYg1RKw110jrt3U+N0WvAZcrdHcccQBAG3ACvcAqwoyq5ELBFhZm3U4nVDfX1sWTwtnOm/HmPc91GIRQKjLI1gfxbnS6voONwdXwcVxrLbvwTy08rZ9lMcVk5KhjwRgLg1MzFOYYwftYg1W6eyOecQk+aFw6BPaAiexJnCM4xtN/a65hKpmPad7Wnf2Z6yghoSDudwLiqH9Pg6jEx74v38CKT71pM3dz3KY7mYTxiHSCpFEPTfKYL+oV8ABEFGt8lvcXDFXLbN/5q9kbGEjJtET/+2Cc8KgkCEcwSbkzfToGlAKpbe0Ka2QUNiXkWzjnE6rY5TO9KwcjbB1a/xHN09GXsoqSthXPtxtzVmG1dTJrzdiYOrkjixLY2UMxfJjj9Bt/GTEUuuXitSsZS3u7zNkzufZEn8Eh4PevzKOfd79CmWvvkCB1csYeDjz93WeK6w73NQ2kCnaZAXD0nb9XXE7tLiyrYiwMkMI6mYoynFDA1s3o7UgAEDBgxcRa3Rciy1hG1xOaw7lUWAk4onI7zu9rD+UWg0Wnb8HI9WrWPwYwHXRWoEQaD7uHZUxCYQn6xEGzScPl4/Iur9LAz6pFWBhiN/JqOu09Dzfu8rE+Hrk9bzweEPCLAOYH7/+SxPWM7hnMOY2slIOWWFpjgTsViMzNn5rtYSuneFkEgMrt3v9ij+FqwcTW7puK6eVkS+0ZfjqcXEZZUTl1VKUlwF3mdK+SgpmliFBi8bEwKczPB3VBHoZIafowpTxY0P7E1RXljDpnlnUCgljHguGJmi9ZeUv20wvpa+rFHVMLFUjbDheRL3fkCNtZLQ5CNQ8SFYeujXhFi4g8oJRGLMbIzoMsqTziM8yDhbzLlD2cQdLkQr6Qn+PaEc+CXhpp+v0w1BLJNQF7+LyKRU1g2ayDtjw7A2adlMSHNEOEewOnE1x/OO082x23X7jiQX8c66WJILq3hzSNPOcilnCinJrWbQdP8mI21rE9demXG5XWQKCf0e8sXFz5Jt8xcAIkyswm5o192xOwPdBvLjmR8Z4TkCBxP9g7yNqzuhg0dwcttGAvsNxt7L+/YGlHZYHw0a9CnIjMGzD5xeri8u7BB0e33fZaRiEWFu5oZ6QgYMGDDQAurVWqIuFrItLpcdZ/MorqpHLhER0d6G/wz3RXqvpMQl74ODX0N1EYjl+siLWPaXVzlIZE28KsA+AJzDQdz0c1f0hhRyk8sYNN0fc7vr3Ul1Oh1FCxbguvJbars8zjnzIdh6+hIw6JFWiaD8tHLOHsomuL/LJVc4WBi3kK9PfE0Pxx7M7jMbY6kx7ip3ADRmNegQUVpQj5VOh8zV9a7WErp3hZBcpb8gDDSLtYmcIQEODAnQP6Rq1Br+mHeGQedK6BtkSazQQNTFQtafyrpyjIe1kgAnMwIcVfg7mtHBwbRRUVBb2cDGb0+jVWsZ83JHlGa3LhzGtx/Px0c+Jn74MgJyznEycRVUJxJakApJB0F7tRgrIimYu+pFkaUHWjM3jKSO2ITaUeptS1qBhpzSWkzjTjIoegN1IikL/YeTbK43RbA0luFgpsDOVIG9SoG9So61yTNk795CXsJWzLfOYVLcEB4f348JHV2uKwbWWsIdwpGL5ezP3H9FCJXVNPD51nP8Hp2Bi6URS6eH08vbptHjdTodJ7alobJW4BXWeJuMigyO5BzhmZBnELehQYF7oBmC7ixKC18OrMomP01L7wfaXyd2X+v0GgcyDzDr+Cy+6vPVle3d759CQtR+9ixcwAMfz7w9W8zIa6JBAJ4R+tfkffe8EAIId7fim92JlNc2oGrFJIQBAwYM/BuoqdcQmVjA9vhcdp3Lo6JWjYlcQr8OtgwJsKePj02bZLf8LWQeh90f6Sf3VM5gHwiaOlDXQ32lXhhp6vVlIm54bWQtqcIMvPrr62m2GwAmV58T0uKLOLk9Db+ejnh3trvuMJ1OR/6XMyletAjzABNGuH7MdsViIo+7IQ3Iw6dLyzJjdDodB1YmYWQipfNwD3Q6HV+f+JpF8YsY4j6Ez3p+diUbxlWlLwJfoSwERJTUWWFVXYzUzZWqY8fQ6XQtNnpqS+6RK6cRFHfG9vj/HbFEzKing9g4J4a8EyV8+Fwwzh0sya+oJT6rnLisMmKzyjiZVsLG09lXjrM2kePrYIqvg4oO9qZ4W5lwfuUFyotqGP1iKJYOLVtM1xTDPIYx6/gs1lxYR0D3DzhVchTHwkrsHt6OTtNAUU4KxRmJVOVeQFOUgrQ8DZP0dGwuHkVFJbaALdAROKz14yfl05SGhREd6EbfZV/x7uG5iJ55CdfHHsFY3vhlXx0ynYWvmSFt2MaQ1LWs/TmVtccG8um4ILxvsTK1kcSILg5d2Jexj9c7vc62+Dze3xBPUWUdT/b25KUB7TFqpsZTdmIp+anlREz2ucHi8jLrk9YjEkQ3pBHeLglR+6mrrmLUq1PITTXl+OYUcpLLGDTNHzsPFQCOJo48FvgY38V8x5GcI3R10K8jkhsr6T3lUbbN/5q4fbsI7HeLRY/Tj+gFz6BP9NEg0NcxsOmg397jDtYs+pvo7GGBTgcnUkvo28H2bg/HgAEDBu46FbUN7EnIZ3t8LnsTCqhp0GBuLGWIvz1DA+3p7mWNQvr31Ue8bfLOwt5PIWETGFvDkM+h46MgbVk9RAB0OtA06AVRfTVkHIGkHZC0E+LXAQI4hYH3IKrs+7NrUS1WTkp63X99VoZOoyH3gw8oXb0GixAj7DpcRLhvAYN9h7Hpu9PsXnwOqVyMZ0jjk6/XkhidR25yGX0f7IBYDu9Hvc/6C+uZ6DORt8Pfvm5y1s1Uv8Y5V5oOuFGsdobSVGSubuiqq9EUFiKxuflntjX3rhAyatom2UDzSGVihj0TxPqvTrJlQSxjXwnD1tUU2w6K6x7EiqvqOZdTzrmcchJyKziXU86vh1JpUGsZVS2jfYOY444izp9IoUO2Cl8HFb72ptiYyptV9fVqLZV1aipr1VTUNVBZq6ayTo2vqhcbLmzGonY8BzKPodR2YODsSDJLaqhp0AAC4A14Y2sqx8XSGFdLY9qZNtBeVoSbqAD7+lS6xvxMt7qXwfk5iHgDzQM9yX7zLSq//YqStEQUH36IyMjohnEZq2R4hweRHmeDZ0gMQlQkeceyuT+1P1MHhPBs33a3dOONcI5gf+Z+Hly6mUPnRPg7qlj0SGcCnG4u1EilcwAAIABJREFU5k9uT8NIJaNDt8ZnZ9RaNX9c+IOeTj2xV7ad9aROpyNm+2asnF1x8Q/ENUDAuYMFOxfGs27mCcJHeRA2yA1BJPBIwCP8ceEPZhydwZpRa5CK9LM/fr37cWb3dg4s/5V24d0wMtGLyZwPP0Sdl4/L/Hk3H8i+v0SDLuPZB04s1s+StXAx5z+VUBcLpGKBoynFBiFkwICBfy2l1fXsOJvH9rhcDiQVUq/RYmMqZ1xHJ4YGOBDuYXnvpL5dpjhF/3fszEqQm0Lfd6HrU/r3rUUQ9JlQEpn+eL/R+n9aLeSe0QuipB1o937JjmJj1GpvBgfvRZKYBV79wMic+tRU8r6cSeWePVh1lmHjnYkwcRn4DEUCDHs6iA1zYtj+cxwjng3Gxbfp2kH1tWoOr7uArZspnuGWvBb5GrvTd/NU8FM8E/zMDc+BJjITLBWWZNSk0c7Ci5IaF7hUSwigPj3dIIQM/H0olFJGPh/C2pnH2fhtDPe93hFz2+vzRy2VMnq0s6ZHu6sOIA1qDduWniP9aD51ASpQajmaUswfMdnXHdfB3hRjmZiKSyLnqvBRU6/WNjomkaIdSo8dzDv1A3LrUhQ17rS3VhLR3uaK6HGxNMLZwrh5QdLradj1Phz6BuLWIh7yOc7fzqXwhx8o/PY76pIu4PztXGTON9YPCoxw4sLxfDw7TcEzrBM7f5rH5OzVbNmYx8bT2XwyJpCe3i13ZdNqdRTk6a3ETxUe4p1hjzOth0eLrD0L0itIP1tM1zGe1y1wvJb9mfspqCngXe93WzymlpB7IZH8lIv0n/b0lZuZYztzJv4nnH3LznPkj2Syzpcw6LEAFEo5b4W/xXN7nmP5ueU87P8woF+I2X/aU/z21ktErfqN/tOepj4zi9JVq0GjoSEvH6ldMw/+6Uf0dYMGfnyjfadnHzi6ADKiwaNXm577342RTEygkxnHDM5xBgwY+BdS26Dhh8hk5u+7QJ1ai5O5EQ92c2NogD1hrha3lZ5+16jIhf0z9RN2IjF0fx56vtyioqStRiQCxxD9v4jXObY2nuydefT3P4xF9iq4+AO1pXKKUl0pP1+NIBFj202ElXchPLD2ur+hMoV+vfcfs0+y5fszjHoxFAevxidtT2xLo6qsnt7TvHh2z7NE50bzVvhbTPGd0uRQ3VRupJalEu5oQvF5FyhNQ+baEdDXEjLu2LFtv5sWYBBC/2JMLOSMeiGEdTNPsnGuXgzdbJ1P/L4s0o/mE9zPhZ7XhFtLq+s5l1NBQm45CZdeS6sbMFFIsFcpMFFIMJFLMFFIMJXr35sqpFd/VkhQynrz8qEdpAsH0ejgl0kTaG9xC3WilNYweh6ETIXNr8DKKQjeg7GZ9AVG/v5kvf4GqePG4/jVV5j07HHdoQ7tzLF0VBK/P4sJb/fF0bsDm7+dybALO0jT5vDIT2WMCHPj3RF+NzVTSMqr4K11sZxIK8Gmgwve7XN4onfLHW1O7khDphATENF4wVedTseyc8uwMbKht3PvFvfbEmK2b0JmZIRf777XbVcopQx+3J+zBy3YvyKRNV8cZ/gzQUS4RNDbuTfzY+YzzGMYNsb6WR1bd0+CBw3j9I4tBPYbjHbZCv3sFVC5dy8WkyY2PYh9n+tTCDpPv3GfWw8QxPr0uHtcCAGEe1jxy8Fkahs091a6hwEDBgzcBnvP5/PBhnjSiqoZHuTAU729CHBS3ZW1Im1CTQkc/AaO/gDaBgh7CHq/DirHv+XjMxKKOb4rjw7d7Onw8H+oPjmEojkzqTx6GpGsGqsO5Vi2r0JiaQ5TN+pT6f6CQill5AshrP/qJJu+O82YV0Kxcbk+glVWUE3MrnTcO1nwVuKLJJUkMaPXDEZ4jmh2fG4qNw5mHcTCyYz0eEe0xbFIuziCWHzXagkZhNC/HAt7pV79f3OKjd+eZuyrYciNGr8sko7ncWjNBbzCbOhxjRc9gLmxjG5eVnTzsrqt8UzsMJ7Poz/HVGpKO/N2Nz+gOdy6wZP79TekfTNgfldMer2Gx4rfyHzpNTKeeAKbl17C6vHHrtx0BUHAv5cTB1Ymkpdajp27A5M+/JKoVb/BhrU83ZDH6uN96H++gLeHduD+TjeaKdSpNczfe5H5+y6glEv4akIwWcIQFsYtpKyuDDP5zVPiSvOruXgin9BBrk3+f2xK3kR0bjRvh7+NRNR2v8rV5WWcP3yAwP6DkRkZ37D/8ndk4aBk64JY1n55gsGPBfBm5zcZ8+cYZp+YzYxeM6607zFxKucPH2DXj98SujUSs1GjqI45RcXu3U0LofSjTUeDABQqcO6kF0L932ujM797dPGwZEHkRU6ll97275ABAwYM/NPJLKnmo41n2XE2Dy8bJcse63Jd9sm9gFarI/lUARKZCHtnCYrYn+HQXKgrh8AJ0OctsPr77LyryurYufAsFnbGhLkVk/bQw1RHRyM2M8P6heexnDIFsVClr8vn3ElvONUESjM5o18KZd3ME2ycG8PYV8OuOMIBHFx9AZFYYJHyC9LKUpjTb06LJmTdVG78ceEPlF4StEgpzy3FXCpF6uR012oJGYSQAew8VAx9MoDN351h6/dnGPF88A2pWNlJJez69SwO7cwY8Khfi+sZtZYRniP4+sTXBNkGIRLaIBdYLIXuz4H/WNj+Duz9BJnVCtxnfErOLzsomD2b2rg4HD77DLGJ/pfcp6s9h/+4SNz+LOzcVYglEnpNfgTXwBC2zpvNxJx1pCj68tbaetaezOSzsYFXzBSOpRbz9rpYLuRXMibEkfdG+GFlIud0QQQ/xf5EVHYUQz2G3nTYMTvTEYlFBPVzaXR/UU0RXxz7ghCbECZ1mHT739M1xO3diUatJmTQ8GbbObYzZ8Jbndg8/wwbvztNzwnePOL3CD/F/cT49uPpaKcPcSuUJvSa/DA7FszFRiHBY9o0xH/+SfHSpWgqKxGbNGIPH9lMNOgynn30qQc1pWBkfusn/A8gzM0CQYDolGKDEDJgwMD/LXVqDT8fSOHbPUkICLw5pAPTe3ogk9yltT/11bDnE6gu1E+6yUz0629kJvqf5SYgM730enV/cZGIPb+nkpd6tXC4pcQKB5s3cOjWFYeO/phaKvi74lparY5dC+Opr6qjU/pSclfsR2Jri+1bb2IxYQIi5WURYwaB41vUp6mlQi+GZp1gw5wYxr4WhsrKiPT4IlLPFBLbbjfZunR+GPgDYXY3RpYaw9VUvx6o1rQMgOICNeagt9C+S7WEDELIAACuflb0f8SXnQvPsnPhWQY/HnAl0lGcXcWW72MxszZi2NNBTa5XaQvM5GbM6TsHW+M2XjRu5gT3L4akXbDlNUSrJ+LY7T4U3k+T/+0P1CVfxPnbb5F7eCA3ktA+3I7zR3LpMa4dCqV+8b9bYAgPffkt2xfMQXtiJ6975rA0uyvD5h7gid6elFY3sOxoOk7mRvz6aGf6+Fw9hwCrACwVlkRmRt5UCFWV1XHucA6+3RyaTFX8IvoLqhuq+bD7h20jGC+h1Wo4vXMLLn6BWDm73rS9ytqIcW90ZOfCsxxYmYhfz344GG3ms6OfsXLEyiuRKr+uvYieO5vzbvb0cnbEdEB/ihcupGr/flTDhl3faUY0XNwDAz9qPBp0Gc8+EPkFpB4E3+bD8QC6hgZ0Gg0iRStcev4mzIyk+NqriE4tQm8IYsCAAQP/XxxIKuD9P+NJLqxiaIA9747ww8n8RuOiv436Klg+EdIO6Uty1FXqLazVtU0eotGJOVU1hmOVE5EJNQywWIKJkEuO8RByZBEkZUP8+nJYfxiluRyHdmY4eJnj0M4MKyeTO7LeSadWEzV3J5mJcjokLMNYmonVhx9iNnYMItntlZkxtzNm1Iuh/DH7JH9+E8OYl0PZ9XscFUZFJDkfZdGgRfhY+ty0n/qaao5tWIvSTb9GqkiRA8goLpPjqdUic3Wl7PTpu2KhfVMhJAjCQmAEkK/T6QIubZsJjATqgYvAozqdrvTSvreB6YAGeEGn022/tH0IMAcQAz/rdLrPL233AFYAlsBJ4EGdTlfflidpoGW0D7enpqKBg6uT2P/7eSIm+1BdVs/G72IQS0SMeC74iii4k/Rw6nHzRreK9wB45ggc+gbhwGysxDtRvPYwWT/tJXXC/di++QZmI0cS0NuJsweySTicQ8iAq4LAWGXGmNffI2bHZiKX/sKDRplkBo1m3t6LiASY3tODVwa2R/kXi26xSExPp55EZkai1qqbTWU7sycDnUZHyMDGhUhkRiRbU7fybMizeJp7ts33comUU8cpL8gnYuq0mze+hEwhYehTgRz9M5mT29OY5PYG823eYXXiah7o8AAA5Rs34p+aw6H2LkStXkbfBx9DbGVFxa7dNwqhfZ+DsRV0fqz5D3bqBFKlPj2uBUIo96OPKN+6DdvXXsP8/gm3V9voDhDuYcnKYxk0aLRt4oz04/6LbIvLZdGj4ZgZGeoTGTBg4O6QU1bDJ5vOsTk2B3cr4xsmCu8KdRWw7H69BfXYHyFowtV9mga9IKqr1Iul+kqoq6Agq5o92yUUVkpp51pCr+BEjMU+0O5ZnLz6gSCg1eoozq4k50IZORfLyLlQyoXj+QBIFWIcPM2w9zLDvCoN0YZFiGqrkVhZIba2QmJljcTaCrHV9e/F5uaNigNtXR1l6/8g6bftnHaajGPNOTq+ch9mw4YgSNouzmHtbMKI54L5c04Mv30YhbYOzoXs49dhi3BRNZ61ci0ZZ2PZNv8bygvycPTzB3fIrEvHROlOSb0DVOYic3NFW1GBprQUicXf6wrdkm/qV+A7YMk123YCb+t0OrUgCF8AbwNvCoLgB0wC/AFHYJcgCJdXu88DBgKZwDFBEDbodLqzwBfA1zqdboUgCAvQi6jvb//UDNwKwf1dqK6o5+S2NGQKCRkJxdRWqbnv1TBU1ndx5qYtkSr0ubuBE2DL6ygvfofHWD8yo+zIfe+/FMz6CrNx47B16kH8AX215GtvQoIgEDp4BM6+AWye8yXWBxfzRe+h+I2cRKBr02lNEc4RbLi4gTMFZ5oMI9fVqImLzMKro+0NLn4AlfWVfHzkY9qZt2N6QDNpY7dIzPbNmFhY4tWpa6uOE4kEuo31wtLBmD2/JTC58B0Ws5DB7oOxkJlTvOhX7DzaETSgHzHbNhPYdxCm/fpSvmUr2vr6q7NWGcfg4m4Y8GHz0SDQW4i699ALoZugraqibNNmBImE3A8+oGzTRhw++gi5Z9sKydsh3MOSX6NSicsqI9T19v4QRF0sZMbWBHQ6eHXVaX58sOO96bxkwICBe5Z6tZZFh1KYszsJjVbHqwPb83hvz7tvCFNbDsvG64ubjvsZAsZdv18s1ZdouVSmRdOg5diWFE5tT0dhImXokz54hjZu8ywSCVg7m2LtbEpgH73RUUVxLTkXSsm5UEZWXA7p8UUgCAjKqZgri7GsTsHiRDwmWZsRNTRSNFUiQWJpeY1YskZkYkLFtm1Ul9Zwptt/UZkKDPv6ceTGtxcBagoTZzGlfWJR7PCm1CaLWQ99cMUUqSka6us4tGIJJ7ZswNzWHs+wzqSdOYW9ty1p5Wl0tfGiJNMFStORuuonfhvS0v55Qkin0+0XBMH9L9t2XPPjEeBywuFoYIVOp6sDUgRBuACEX9p3QafTJQMIgrACGC0IwjmgHzD5UpvFwAcYhNBdpetoT2oq6jm1Mx1BJDD82SBsXG+toOg/GisvmLoWzm1AuvUt3IPPUt21DyWJCooXL8bKOo5zvg+TtGIv3vdHIIivv3nbuLozZcbXRC75hdM7t5C5fyv7jIyQK01QKE2QK5X6V2MTFCZK5HIZ/qlm7Nu+AjN/9ZX9CqUJSnMLBJGIuMhM6ms1hA1ya3TI35z8hvzqfGb3mX2lWnNbUZKbTerpk3SfMAXxLc4m+XR1wMzWmI3zTzH41BN8b7aUFywDqE9JwfGrWfSM6E3i0UNs+XYW/Xr2R7t6DdVHozHp1VPfQWQLo0GX8eyjLyhXlglmjbvrAVTs3k2NVo7lh19jVptD3hdfkDJ6DFZPP4X1Y48h3Gb6QFvQ2V2fMhCdUnxbQqiwso6XVsTgYa1kXJgzM7ef54f9yTzd5+9btGvAgIF/N1EXC/nvn/FcyK9kgK8d74/0w8Xyxsm9v53aMlh6H+TEwIRF+jo8zZCbUsaeJQmU5FTRoas9PSZ4tzozxtRSgdSsHKMDc7DduxetnTO6CU9Rbh9I1gULktNs0CnDkbQX4eCuxMFBjJ2qFpW2BG1xIerCItRFRaiLCtEUFlGXmIimuBhFWBjJXo+gzocxL3W8YyJod/puPjv6GQXVBUwe/zAvdX0CM+PmnwlzLySydd5sirMzCR40nIgpj5KVEE/yyWN0qLUnrTyNoY6mZKc6oytOQ+bWGdDXEjIKCbkj59EUbRE7mwasvPTeCb0wukzmpW0AGX/Z3gWwAkp1Op26kfY3IAjCE8ATAK6uN1+/YODWEASBPpN9kBtLsXNX4eb/f7x4WxD0N0KvfggHvkJ5cilK10IanC2wKC7lQm0VMWsSEX76BIv7J2I+fhwS66vONlKZnAGPPUO78G5knz9LXVUVtVWV1FVXUVtZSWlerv7nqioaamvojDm6s2f5Y/NH1w3Du0t3hj33Jqf3ZOLqZ9mo8DyRd4KV51cy1XcqQTZBbf5VnN6xBZFYTGD/wbfVj72nGZPe6cqvs3ah2u1PVNV+PJ2cUA0ejCCRMPy5V9k8dybr1i7D194Ks1079UIo4xhc2AUDPtAvTG0Jnn30r8mRENp07YKyjZs4G/wk5ZtqGP1yX7w29yLvs88onPstFVu34vDxx3/7zfev2JjK8bRWciy1mCcjbk20aLU6Xl11mtKaBhZPC6eDvSnncsqZuT2BEBdzgxGDAQMG7ih55bV8uvkcG05n42JpxC8Pd6K/r93dHpaemhK9CMqNhQmLm02pbqjXEL0hmdO7M1CayxnxXDBuAa2/f9ZnZlIwdy7lGzchMjHB5uWXsXxwKiLjq6KwrrqBrMRSMhNKyEwoJjqxAgCFUoWTjxvOnS1w8bVAZW10XXbKye1pZK+/SMRkH6yd236yOrcqlxlHZ7AnYw/tLdrzTZ9vCLQJbPYYjbqBI+tWcnT9KpTmFox75yPcg/UZME4d/BFLJDgWKjhtnISFqx3qqEoqsnIw8XMGQbgrhgm3JYQEQfgPoAaWXd7USDMd0FjCu66Z9o2i0+l+BH4E6NSpU5PtDNw+IrGIHuNu0776XkJuqn8A7/sfSN6H9MxK7BM241/kymnJKDTafRR88w0F8+ahGjQIiwcmYdSx45WbkntQKO5Boc1+hEat5reYX/kheh7f9/wWM50xddVVJB6NIunIIU7vSqCmvJ6wwTdGg+o0dXwQ9QFOJk48H/p8m59+Q10tcft20i68OyYWt1/wzdRSwdS3ezH/g6VcIAJtj454IkIMuId05KFZ37Ft3tfE1tdRcOoIY0pLUEZ+DkaW0Pnxln+QrR8obfTpcU0IIXVREfmnLlDaaRIiYNuPsdz/TjhOs2ejGjmS3A8/IvWByVhMmYLNSy9dcQ+8G4R7WLI1LhetVndLqWw/H0wmMrGAj8cE4OugAuCLcUGcyynn+d9PsvmFXtip/nlmEQYMGLj3ibpYyJNLT1Cn1vJCf2+e6eN199PgLlNdDEvHQP45mLgUfJo2LcpKLGHv0gTKCmrw7+1E97FeyJooY9EU6sJCCr9fQMmqVQgiEVbTp2H12GOIzW90OJUbS/EMscEzRJ9qVllSR9b5YjITSshIKOHiSf0aI1NLBc4dLHD2tUAml3Dkz2S8wmzx79W2NYo0Wg2rElcx5+QcNFoNL3d8mQf9HkQqaj4SVpieytZ5X5OfehG/Xn3p++iTKJRXJzWlCgWO7X3JzsqgxK4Eub3+Oy3OrkAlkyF1cKD+Llho37IQEgThYfQmCv11Ot1lUZIJXLtyyhnIvvS+se2FgLkgCJJLUaFr2xsw8PcjloL3QP2/ukoCorcRs0xMuZcjwR6HKM12o3TPTso3b0bu7Y3F5AdQjRzVoodnsURC3/aDmBU/h3hpOpN99RmhNm4eJB4+wPHN27Hz6I1j+xtvlD+c/oHU8lR+GPADxtK2Ty9IOLSfuqoqQm9imd0aLEzNGFgSSVZ+GskMZcOcGIY8GYCRiQxTS2vG/+djDs2awbFjUSx+6XGGWp/AY8yLLY8GgT6i59lHL4R0Ov3Pf6F8y1ZybLsgCDDyhWC2fB/Lth9jGftKGKZ9+2LcOZyCr7+mZNkyKnbvxv79/2Lap08bfQutI9zDkhXHMkjMr6CDvapVx55KL+HLbecZGmDP1C5XI+ZKuYQFUzsyet4hnlt+kuWPd20TMwYDBgwYuMy2uFxe+P0UblbG/PhQJzys796E0g1UFcHS0VCQCBOXQftBjTarr1VzeP1F4iKzUFkrGP1yKM4+rUtT1lRUULRwIcWLl6Crq8N8/Hisn3kaqV3Lo2ImFnJ8ujrg09UBnU5HaV71pWhRCckxBZyLygFAZa2g74Md2tRl7XzxeT46/BFnCs/Q3bE773Z9FxfT5g0RtFoNxzeuJ2rVb8iMlYx69R28w7s32tY1MISMlbHI60VUGBcBUFKgxh2QurnelaKqt/TX8JID3JvAKJ1OV33Nrg3AJEEQ5Jfc4LyBaOAY4C0IgocgCDL0hgobLgmovVxdY/Qw8OetnYoBA22M3ASzXuNx9bfkrGgKkgkzsOtvgffwNBw6lyKUp5H74Udc6N2bnA8/pC4l5aZduqpccVe5sz9z/5Vtlo7OWDh6UVV8mtBBrjfc1M4Xn2dR3CJGeY2iu1PjN5fbQafTEbN9M9Yubjj5+rdZv/WpqZgejqfI4ySHfdeQm1LGms+PU5RdCYAgEtHtyefonpyDvLaKdRkB7D4noaG+kcWizeHZB6ry9TN9jVCyaTO5Tj1wD7LGuYMl/R/xJS+lnP0rEwEQmyixf+9d3JYvQ6Q0JvOpp8l65VXURUW3cfa3xrXrhFpDWU0Dz/9+CjuVgs/vC7rhGvK2M2XGfYEcSy3hy20JbTZeAwYMGFh5LJ1nlp3A30nF6qe6/cNEUCEsHgmFSfDA8iZFUPrZIn7/6Chx+7MI7u/CpPe6tEoEaWtrKVq4iIsDBlL0/QJM+0TguWkjDh9+0CoR9FcEQcDCXklgH2eGPhXItFm9mPB2J3qMb8eI54KbLLjeWmrVtXxz4hsmbZpEZmUmM3rNYMGABTcVQSW52az84G0OLP8Vj9DOPDJrXpMiCPRlSAAcChVkqdMxktVQXKYvEyJzdaPhLqTG3VQICYLwO3AY8BEEIVMQhOnoXeRMgZ2CIMRccntDp9PFA6uAs8A24FmdTqe5FO15DtgOnANWXWoLekH1yiVjBSvglzY9QwMGbpOA3k5UlatJVYyFx/cgevkE5tNfxP0+AfeBBZjaF1O2eiXJI0eS//U3aGtqmu0vwjmC6Nxoqhv0cwg6nQ4dHdBpi1BeKjJ2GbVWzftR76OSq3ij8xt35Pxyks6Tn3qR4EHD23RmqejXXxEkEnq+8CmxFocoG3wGdb2WtV+e0LvmAGIzMxx8vOiVcoGOwS7E7NrOb2+9RF7KxZZ/kEeE/rUR97j6tDSysrTUi43x7aFPH/AKtSVsiBtnD2YTfyDrSlvj0FA8163D+vnnqNi5k+Rhwyldt56rAe87j7OFEY5mCo62QgjpdDreWRdLTlktcx8Ixcy48fSF0SFOPNzNjZ8OpLA1NqethmzAgIF/MQsiL/Lm2lh6etuw7LEumN+hBfu3RGU+/DoCipPhgRXQbsANTarK6ti9+Cwb555GKhMz7vWO9JzgjVTespQ+nVpN6Zo1XBwylPwvv0QRGIj72jU4zZ6N3MOjrc8IkUjA1k1FyABXLOzbRnBGZUcx9s+x/BL3CyO8RvDn6D8Z4Tmi2ecBnU5HzI4tLHnjeYoy0hj67CuMevUdjM2aL25u59UOmbExjkVGpJenY2lWR0m1BWjUyFxd0ZSWoikra7aPtqYlrnEPNLK5SbGi0+k+BT5tZPsWYEsj25O56ixnwMA/DrdAa0ws5Hpb61Bbvdtcn7cQIt7EKOskRrGrsI1eQ/4RLUU//ED5pk3Yvfduk+lVES4RLD67mMM5h+nv2p/0+GJqqtwQiSXE79+NfburBTWXnVtGfFE8MyNmYiY3uyPnF7NjMzIjI/x6NT7eW0FdVETZ+j8wGzMaB++uTCyeyO/nF7L46QEk/FbFjoXxPDyjB1KZGBPbIqpOSuh23zO4j1Czff7XLP/Pq/SYOJVOI8ciEt3kD5K5C1i10wuhbs9ct6ts0yayHbpjbCLBzf/q2qcuozz/x955h0V15f//NZ1hZui99yLd3sWOvXcTk5hkUzd9N8luet98UzfNmBhNorHEFnvDgh1FpCgiIB2kw8DAMMzM749rNAZQLJs1v53X89xnLnPPvffcAeac9/k0qgq1HFiZjaOnGrcA4bMVyeU4P/ooNgkJlL30MmUvvkj9pl9wf+015H9AghaRSERvfwcO51Z3ubDciuOFbEkv4+8JYfTwvfYK5j/GdeN0cT3P/ZxGqJuGAOcbcEO0YMGChUuYzWbe2ZbF1wfymBDjwQczYpBL7yCXW225YAmqL4Z5q8F/8FWHW1vaSN1VyKmdBRgNRoIMGQTnpNLyTwP5JhNmkwlMJswmI5jMYDRiNpvA+Ov7wqupqQljXR1WMdF4vPsuqr59/ksP3HVqy0poqqulRdLG0vM/sq10Fx4O3nw76lt6u19/Oq6trmLHV59QkHYK3+g4Rj/0BBpHp+ueByAWS/CJiKE+8zAF9flEOntxrsoLc30Rcl9hjG0tLEIZ9Z+Z73TE7au4ZMHC/6eIxSIiBnly7Jc86i7qsHO9FKMjEoFXD/DqgTT+BTxW34XtsaOUn7Gl+KFi7Dw2AAAgAElEQVSH0YwcgeuLLyJzd7/qerEusWhkGg4UH2CIWzxHN+aicbTFIbwfWYf2M+SuhUhlMooaivjs1GfEe8Uz2vfWMrl1hq6+juwjSUQNT0CuvH2xR7XLV2DW63G4914AHo19lB35O/gw6z3emfUJGz48xbmj5UQGlKORneIibmiTjuL3wAPc/f5n7Fr8GUkrlpKfepKER5/Cxuk6xfcC4iH1J6EQ3qW04mazmYqte6n2eojuAzwR/yYuRiwWMXJhBGveSWb7onRmvNgLla3i8nFFYCC+P/5A3erVVLz/f+RNmIBTQiT24wcjcQsAjRtoPMDaocO4pFuhl78DG1JLKajW4XcdF5Os8gZe33SGQcFO/GXw9WsiyaViPp/XnfGfJvHwjymsf7Q/1nLLMGDBgoWu02Y08fy6dH4+Wczd/Xx5dULEnVWnrKFUEEENZTDvZ6He3CVMRhNnDpVxfFMezVoDLtWpBJVsxyHAFcRikMkRicTCvkQs7EskiMQiEEtALLr6PYkUzbChqIcPv60eFf8p0vZsZ/c3XwhCDrAH5l4K4T+y8T1SrFXIldYorK1/9yq8LxJBytZfMBrbGL7wEWJGjrnh5/aNiiUn+Qg5pQXYe46h9YyZpqKCy7WEWgsLUEZF3tbnvhaWEdCChS4QPsCd5M0XyDhQwsAZwe0bKO1g3lpUtk8S4Lic6oYBVO0/SOO48Tg/+igOd9+FSCZM0GViGQM8B3Cg6AB7s7KoKmpkzENRiLAi+2gSF1KSCerdj9eOvIZELOEfff/xn/mC1WtJ37UZY1sbsbcxSYKpuZnaFStQDxt2uWCprcKWJ7s/ycuHX+Zk8EFcfN04vaeIiMIPkDnZYhURTuPuPTg98ABKjQ0TnnqBzP17SPxuEd8/9zgj7n+EsAFDOr9pQDwkfyMUyPPtB0BLRiaFBk8QiQnv797uFCuVjDEPRbH2vZPsWJzBpCfjkPxmRVMkFmM/ezbq+HgOPDSNwxnlhO77kmCPKuxDmpApTSCRXxJF7lc2G/f2P1+vOOxv6ON/KU4ov+aaQkjX2sZjK05ho5Tx4czYLk9EPO2UfDI7jgXfHeef6zP4YGbMn2IAt2DBwn+fFoORx1acYvfZizwxPJgnRwTfWd8f9cWCCGqsgLvWgY9QHNxsNnPhdBVHN+RSW67D3lBGt7Qf8ezpj9tnP9xSHM+fAbPJxIEVyzixaS1aTxmHPcoIVQcyxXsCdiI1ep0OfbOOVl0T+ubmS686mmprLr/fesnt3yO0GwmPPIm9281lq/O5FCdkuFCB/UhXoJzaggo8RwrWNMMfnDnOIoQsWOgCKlsFAXHOZB0po8+kAGTyDty1pHKY9Dkiez+c9r6FzT19uXjGh4r336d+40bcXn0F6+5CPv3BXoMpO9RKduFF+kz0JyDWGZPJAZW9A5kH9pDhcJFj5cd4qe9LuKncbt+DGJohezuk/4wpexenc3viHRGLo9e1AyJvhLp16zDW1eG48L6r3p8UNIk12Wv4KOVDPolfStKyXAr01fiNfQyNjYrKTz7FUFGBzMUFkUhEZPwIvMIi2Pr5B2z59H3yUpIZvvBhFNYdiAO/gSASC+5xl4RQ/aZNlLn3x91ffcWK9zucvDQMvTuMXd+e4dDPOQyeHdKujag+jXPWapqNMo6qvcivtyN8Zx3uvYJwGOyNwroJtGVwMRNy9kCrtv2NvPvCfdu7ZD0KdFbjoJJz/EINM3t2/nt59ZdMcisb+XFhH5w1ik7bdcTgEGeeHB7CR7uz6eFnz7w+HRfwtWDBgoVfaWgx8MCyExzPr+G1iREs6O93dQNjG5SmCK7K1rdehuGGqSsUYoKaa+Gu9eAtuHmVX6jn8NocynLq0cj1RJ35Hte2Qtxf+weaMTdu0fiz0apv5of3X6Qu/TxZPlpye4h5KO45podMRyzqujuj2WTCoG9BZqW8pc/M3t0DsY01DhebEHnbAeXUlDbgrVQidXP7w2sJWYSQBQtdJHKIJzknK8g5cZHw/p2shIhEMORvYOeLfOOjeEfXoh33CuUff03B3HnYTpuKy7PP4l8fRd9CJQQ00GOMHyD4zoYPjOfk1o1sct5OD7ceTA+Z3vF9bgSjQRAI6Wsgawu0NoLalTxlX7QtJuK73756UWajkZqly1DGxKC8JPp+RSwS82KfF5m7ZS5faN8lWj6a3a3T6OYTgoNSSEjQsGcPjnOuhCXaubkz+9X3OLZ+NUfW/kRxVibj/vo3PEPDr76x0h484oTnHPoC5rY28vefodm/D/2HXFvkhfRyo6JAy+ndRbj4aQjre7X1KHf9ZzQbZUx88m9Ul5ZybP1q9ttpCMitIODgWeyHD8Px/jdRxsQIJ+i1gn96Q6nwmrsH0lYJWYuc2wut3yMSiejlZ3/NzHEbU0tYfaKYx4YGMSCoY9/s4jMZZB8/xJD59yGRtk+g8PiwIFIKa3ntlzNEedoS7XXtIFcLFiz871Kp1bNgyXGyL2r5eFYsk2I9hQNmM5SkCN9xGWtBVwViKQQMhcipEDYOrP6AeI/afFg6AVrq4a4N4NWD+kodR9bnkZtSgZVSRLea3bikb8R+4nhcnv8Cqb0QU3mk9AjVLdVoZBrUcjVqmRqNXNhXSVVIrheneofSZmpjS/p6UhZ9j6baRHaMiRFTH+Gz4MkoJDe2eAaCl8TtcKEXiUQ4hAaiS9Vy0VyGQtxEbaURALmPzx9eS8gihCxY6CIewXbYu6vI2F/SuRD6lZhZYOMBq+ahyX4J1eKlVG04QvXSZZQfTOdE5F/R2dRyKmQDj4omXz4tYshwTmxah3uBmFenvHpDqzVXYTJB4RHI+BkyN0BzjTAYRU6FyOngN5BTb/wDtewUQdo9wH3XvWRX0O7ahaGoCJfnnu1wxSjSKZIHox/k+8ylNLnJ6Vs4iRe3/otq62I+tYPUH95gsWQxTkonHJWOOCmdhC3CCT+XqZSt3MOG91/nL18sQyr/XXaigHg4+DG0NNB0Ip1iZQQyqZnA7teJLwL6TwmkqkjLvuXncHBX4eJ7qYZPWRpp56qx0bgT2GcAwWIJEfEjSFqxlLMH91Hq4UxIZhrus2aj6tkTxwfuRzV4MCKnYHC65ELp20+YJJzf2SUhBNDb35EdmRcpr2/BzfbqAqj5VU28uC6dnr72PDmiAzfNSxxdv4qCtFO06fWMfPDxdr8PsVjEx7NiGf/vgzz8YwqbHx+IveoOyvhkwYKFO4KiGh13fXuM8oYWvlnQk/hQF6jOFRbX0lYJWdkkCqFIadh4KE8Txp0NDwvuw0EjIGIqhCYIxctvB2Yz1BVA/iEoOCR4OpiMsGAjzTYRnFiVTcaBEsQSEeE2xThv/QgrZ3vcF32JevCVxAmrz63mjaNvXPNW1lJr1HL1FaH0m32NXEM/9370de97x1iWWo2tbMzdyKqDS4g8YEbVKsVz/mieHPcIUvGdMe33j+5OVXI657NP4aBSUFMvjHNyXx+0e/f9oX25Mz4RCxb+BIhEIiIHe5C06jwVBQ1XJsud4T8IFu6C5dMRr5yGy/RvUYxaw7rPzkJzI31LV7DP+TwVugpcrIXJ+mlTDlW2enpV++Bn63djHTSboey0IH4y1kFDCcishcEpcjoEDQepsApUknWGwjMZDOkTgDh7pbCaZn+D92t3ezPV3y5B5uuDZvjwTts9FvcYj51NopadrJJP5hHxP7Ef2oz47AqitxxnmGM/yqmnqrmK87XnqW6ups3cBoBbkIKEY25kHdpP5NCRV184IB6SPoCCw1T9cpBKl0GE9Xbr2I3xd4glYkbfH8nqt5PZtiidmS/0QqmRU7vjIwp19gyYOv5y9jqNoxNjH3+WmFHj2Lv0a1Jb9ZQE+xKWV4ruLw+hCA7G8f6F2IwdK8SF2fmAczic3wH9H+vSZ9nb70qc0MSYK6Jb32bksZ9SkErEfDInDmknhVFbm3UUZaajdnQiPXEnjl6+9Bg3qV07e5WcL+Z1Z8ZXR3hqdSpLFvS6s4KeLViw8F/lXLmWu749hr7NxKr5wcTUbYDFq6DkBCASxrlBz0D4hCuWn+gZMPJ1IWYzc72wndsKUiuhWHnEVAgZfUOxk5jNgvgqOHhJ/ByGhmLhmNIefAfQNuDvnE6zIWX7EQx6I0GBYjx3fIS4KBv7efNwfuqpq4qfHyo5xNvH3maQ5yCe6/Ucja2NNBouba2NaFu1NBquvP56vL6lnhJtCdpWLQ2tDXyX8R3+tv7MCZvDxMCJqGT/nTpKOoOONdlrWJa5DGmRluGnXLGysmbGP9/AIyj0v9KnzojpGU/yt8sozcwk1jaSvDLBs0Hm44OxqgpjY1OXCtXfDixCyIKFGyC0r/vlytPD7r6OEAJwDoX798BPszH9dBf7JctokdkxvI8W4+JS/rXESHb1izj+82Oa5CbeOvYW3UJscUqupyI/Dxe/62cCoypHED/pa6A6B8QyQfSMfB1CEkDRPkXykbU/obSxJWb+c/DlKji+GEa3y3p/Q+iSk2lJT8ft1VcQSa4hPkpSIHs79sP+SbcyTzIPlDBuzmBEMx0o2Difv7YOxGbMmMvNTWYTDfoGqpqr2Fmwk9LMDRzevJqI+BFXr8B59QapElPWbnLTWjD5yeg2uOuxT0qNnDEPRbHu/RR2fJPJxLsdST9+CpHIi4iR49u19wwNZ95bH5B5IJGkFUtJcrAiuEcCQZnnKf3781R8/AmO9yzAbvp0xCGj4Mjn0NIAVtf/uwl316BWSDl+ofoqIfTutiwyShpYdFcPPO2UnZ5fkJaKydjG2PmzSDmcwv4fvsXBwxP/uJ7t2sZ42/HShG68tCGDz/fm8Pjwzq1MFixYuPNpbTOxLqUYhUxMgJOaAGcVGquO64tdi5MFNTzyXRKjJSn83TsN9cr9YDaCa5QwvkROB1vPjk8WicC7l7CNehOKjgmC6MwGOLtJWKQLSYCIKYI4kv3u+8xshsoswdrzq9Wn8aJwTOUMvgPA70nw7Y/ZKYzs5AqOfpFHY20VvmE2BJXuwPzNj8j9/XFf/iPWPXpcdfns2mye2f8MQXZBvD/k/ZsWL3qjnp35O1lxdgVvH3ubT1M+ZVLQJGaHzr7xxcybpF5fz4qzK1ietZx6fT2jGqLwPKHGwdObqc+/cv2sq/8FbB2c0dqakeeW4BASw5liDc01WuQ+QryqoagQSXj4da5ye7AIIQsWbgCFUkpIbzeyj5XTf1oQVqouDC5qF1iwmUPvfUNRiYqhsemE3PsobVMGseyvI+m/4RDZm/tR7WNDgnMdI8fOYl/KVs4c2NOxEDKZhIDUc9sEd4CLGYBISBjQ/3EIn3jNQNXS7LMUpJ1i8Lx7kbkEQMRkSPke4p+/JbeFmm+XIHFwwHby5Gs33PcuWNlB778Qo5WSvq+Y9H3F9Bkfi8TBAe3uPVcJIbFIjJ2VHXZWdrip3Lg/YCX2aWWUnjuLZ1i3K9eVWYFPXxoTEylxfBx7exEuvjf2PC6+NgyZG0ri92c59G0KmXUuBETHoHHoOA5HJBYTGT+C4N79ObZhNSlbNpDvoCTuwXvwPJnOxXfepfKLL3GeNw4HUxvk7YVu7S0zv0cqEdPD157kC7WX39t15iLfHcrnnv5+jI64dgKN3JTjKORiPHfOw3X6j6ysKGfzJ/9i7psfdJgYY34fH07m1/Dh7mxifewYFOx83T5asGDhzkPX2sZDP6ZwILvyqvddNAoCnFUEOKsJdBbEUaCTGk97JZLfW4GNbaQmbaQo8Tv2iZNRGlugzlMYX6JngmvEjXVKLBZchH37QcI7gjUncx2c+UV4lashdKwQT6QtF6w+BYdBJxTeRuMh1AHyHSBsTsGXE89oa1rY+3k6RWdqcPbV0K9bEyx6CmNtLY4P/QWnhx9GrLg6HqZSV8mjex5FJVXx2fDPbsmCo5AomBA4gQmBE0irTOOnrJ9YdW4Vy88uZ4DHAOaEzWGQ16Cbd3O/BhW6Cr7P/J7V2atpbmsm3msI8Rd8yD94AJ/oOCY89QIK69tXFuN20+atQXWmEZtBQh9rcvNx/LWWUEEhVhYhZMHCnUnkYE/OHCzl3NFyYoZ3zeJwJrmOtJJIogMK6Vb+Eqw6inTaYsofm8IrSet4XjeEyqRtjD0pRnLsY1x8XUnfvJHgvGLUPXtjHR2KrPEMZO8QXKyaKkEkAZ9+MPptYVXNpmupLI+sXYlSY3MlZXbfR4Qg19QV0OcvN/WZ6HNyaNy/H6fHH0NsZdV5w6Jkof/DXgIrG2ytwD/aiYwDJfQY44d62FC023dgbm1F9PsYIEAtV+PTpzetZ89wctvGq4UQQEA8hSvWovXzZeDwgJvy2Q7v705lXhWnErMxGOVEj5lMXn0eObU5jPAd0eGAprC2ZvDce4gaNor9Pyzh+LEkbF3d6Pf6Syg3buXiolXYTLdFmr2zS0IIoLe/A+/vOEdtUyvNBiPP/XyaCA8bXhgbds3zzCYTF1KS8VPVIsaI/JcHmHzPCpZ/vJgN/3qduW99gFJztVVKJBLx9tQozpQ18MTKVDY/PhCPa1icLFiwcOdR32xg4dJkUgpreXtKFL397cmpaCKvqpG8yibyKhvZklZGfbPh8jlyqRh/RxUBzirC7M0Mb9xMQN6PxOorCZKoEEVOxxw3C5NzHCZdM6amJkzp6cLrpc3Y2Hh539yix7pPb9SDBiGSdjDFFEsEdzr/QTDmfchPEsTQ2U2QvlpoY+cDwaOF+j++/cHev13GTbPZzNnDZRxacx6TycyAce447viCxmW7serWDZ/FX3c4kdYZdDyW+Bj1+nqWJiy9rVlZo52jiXaO5pmez/Bz9s+sObeGxxIfw0vtxeyw2UwOmnzThdHNZjMXdRfJrcslpy6HszVn2Zm/E6PZyBj/MdwTchfnV2wi++gBokckMOzeh5B09PnfQWiCfRBnnKFFJPw91uZfxH2skPX1j0yYcGd/ShYs3IE4+2hw9bch40AJ0cO8rjvZLsupY/+Kc3iF2TPg8Xg4oYftz8PScQwZ+gwrXVbykPQgTlH+rBm9AtGZ87Ts2EpiejK5u7bjvFIYHGSqNqzdzCgjw7Ae+gzyQTMRqRxvqO9lOefITz3JoLn3IPtVsHj1BK9ecPRL6PWAsHp3g1Qv+Q6RlRX2c+deu+Het8DaEfo8dPmt2BE+XDhdxbmj5fgOH079z2tpOp6MeuCADi8xPmwi33kdQ378MNrqqqsqWrc59iBXWo0YI6F9b67GAcAAr92kt6bSJtagdgzlmUOPklqZSh+3Prza/1W8NF4dnmfv5sHk5/5Jftop9i1bzPa1K/D0DyIgQ4xWF4H9+Z2CRa8Ln3HvS/WEjl2oZsnBfFrbTPx7ThwK6bVjnsrzzqNrqCfQowwS3oPD/8Zm64NM+svXrP7wIzZ9+A7T/vF6u0xy1nIpX87vwaTPDvHoihRWPdjvzqoUb8GChU6p1Oq5e8lxciq0fDa3O2OjhOyXQS5XW8XNZjM1Ta3kVQnCKLeyiaqyQnoVfMfYs9swFYo4n+9EqyEcG5kcfjmGSbdXcFW7HmIxIqmUmqVLkTg7YTd5MrZTpqII8O+4vUQKgUOFbdyHUHISbDzB7toLjI21Lez9MYvCzBpcnSG6aR+mlzfTZDLh8tyzOCxY0KEIM5qMPJ/0PFk1WXw69FO6OXbr4OpXYzabaTO00qbXY9C3YGjR09aqx9DSgkHfQltrKw6eXjh4el+eCzgpnXgo5iEWRi1kT+Eefjr7E/934v/4PPVzxgWMY07YHELsO06c86vgyanLIbcu98pWn0uToelyOwcrByYFTeK+iPtwNGvY8P4blOVkM3j+ffQcP+WOSdxwLTzDIigTZVJQUYpMZEdNWStilQqJsxOthQV/WD8sQsiChZsgcogne5aepeRcLV5hnbuhaWta2LYoHY2DFaMfiEQsEQtWF1tvWLuQXptfROmsoLmtmVf6vISqOgvqtxNtu50jEhtqw0T08rCiuS0EXYWUxrP51G/MhY2fInFcjnX37tjfNR9V795d6veRn3/CSmND7OjfFVDt+zD8fJ9grQkd0/HJnWC4WEH9pk3Yz5hxOR1phxQcFlzDRr5xVdySe5AtLr4aTu8pIvzvfRFZW6Pds7tTIdTPox/vhEiIuGDm9K5tDJx91+VjdSeLKXftja9tAVbqG/eJB6BNj/bgN7QY/FHaDWLzV6mcDchmkN8gUipSmPrLVJ7u8TQzQ2d26u7gFx3H3f/6N6d3beXQ6uVUhnjjnGvEXlUBZang2b3D835LtJctcqmYf27IpKpRz0ezYghwbh/v9XvyUpIRicDPVgdx8yFgCHw7Go+jf2PUfS+x7euvSFyyiBEPPNpusAx0VvOv6dE8sjyFN7ec4bWJEX+KAdWChf9limt1zP/mGBcb9HyzoBdDQjp3bRWJRDiqFTiqFfTS1EL5IvRnV1GbLaO8wAmT3ojE1xvXsBCkGjUSlQrx5U39m30VYrXqquMipRLa2mg8cIC6teuoXvId1Yu/Qdm9O3bTpqIZndB5ALxEdrn4aWeYzWbOHirl4KpzmAxGQou24LFvJ9jZYjthAo733Yvcz6/T8z88+SF7i/byfO/nGeItFOguzc7i9M4taGuqr4gdfQsGvR6DXk+bXo/ZbLru70BlZ493RDQ+kTH4REZj6+KGTCwjwS+BBL8Esmqy+CnrJzblbuLn7J/p6dqT2WGzUclU1xU8gXaBTAiYQKBd4OXNwUqYd1QXF7HivWdoqqtj4lMvENyn/3X7eqfg7xzEaTs9BeeycZDaUFspLGrKfXwx/IG1hCxCyIKFmyCohwsH15wnY39Jp0LIoDey9cs0jAYTY5+OvjqeKGws3LsVxYpZLKhrwewQQJ8f5wpprsVSJL796Rbty6m0IvjbDzhobHBAGAhaL+SjO3mC5hMnaTx4EF3qKYITE4UMZdegPCebC6dOMHD23citfuf2FD5RWIk7+uUNC6HaH38AoxGHe+/pvJHZDIlvgdoVet1/1SGRSETMCG92fXuGotwm1AMH0rgnEfNLLyHqwHIiE8sYEplAcepuTu/eRt+psy6n0s7edYY25VAiVVvAvLBLBUzbkbaa9FIpIpGIhIdmsnVxLiNy7ubZubMxmFp59cirvHXsLXYW7OS1/q/hrel49VIskRCXMAEbZ1c2/Ot1Cgsq8Q6WID2/q0tCSCGVEOttx/ELNUzv4cWUuI6tUL8n7+RxPFTNtIYM5EzdOXq49oBZP8CP0+hW9BXVE6ZwfNN6HL196D5mYrvzx0a5c/9Af745eAEbKxnPjAqxiCELFu5Qciq0zP/mOE2tbfx4f296+HahkGlpKuYDH6LdtZPaHBW6i3aIZFI0CWOwnzMbZVzczf/Py2Rohg9HM3w4bZWV1P/yC3Vr11H2j39S/tbb2Iwejd20qSh79OjyPcwmE1WHUjjwcwHlents63KIKPwZ10Hdsfn7V6j69bvu+LcqaxXfn/meuWFzmRs6h9yTx0n+ZS0lWZlYqdQ4evsgt7ZGZe+AzMoKmVyBzEqBTGGFVGGFTCHsyxSKq36WSKVU5OdRmHGaosw0sg7tB8DG2RWfyGh8IqLxjogmzCGM1/q/xtM9nmbd+XWsOreKZ/c/e7l/jlaOBNoFMjFwIoG2VwSPvVXni4uFGWn88uFbSKQyZr7yNu53WGa46+Fj40OZUwtuOWX4eVVSWi8k3pD7+NB0+PAf1g+LELJg4SaQyiSE9/fg9J4imur0qOyuDsY0m83sWXaWquJGxj0SjYN7B6tgHnFw/24eXTkPis5B8Cghi07gMFDa0S0/j5On/krWof3EJUwABNGgCPBHEeCP/YwZaPfupfjhR9Du3YvNqFHX7PORtT9hpVITO7p9BjQkMuj9AOx+FS5mdjkY1tjYRO3KVWhGjULufQ13hgv7hQDYMf8CefvgzcDuLhxZl0vq7iKGjhiOdudOWjIyUEZHd3i58QHjedp3Ld7HrTh3JImIIcMxlJSQ3+yGtaoJb+PeLhcwvQqTCePBf5PR4ElA9954RnuQHPQJvbMnkrG+kh5j/PhqxFesz1nP+8nvM+2XaTzZ/Ulmh83u3DoUE4fCSkmZrZoGbQgO53dA/N+71J0pccLA8NrErv0+tDVVVOTnMci5nHfULmzZfg/vDXqPsQFjYdLnsP5BBka6Ud2zD/uWfYODuyd+sT3aXefFseE0tbbx2d4cDCYTzyeEWcSQBQt3GOnF9Sz47jhikYhVD/ajm8c1MlKazXDhAIZt71OXmEpdnoq2Zntk7q44Pz0Pu2lTkTremKv19ZA6O+O4cCEO991Hc2oq9evW07B1K/Xr1yP39cV26lRsJ09C5uraQXfN6M+epW7zFs4dKibLaSQmsYpIRQax94ahGfLLteNRf0NScRJvH3+bIe6DGafrwbLnHqO6uBCNkzND73mQyKEj2y8O3gCuAUFEDRsluB2WFFOYeZqijDRyjh8hY+8uABw8vPC+ZC2a3W0ad3e7m+SLyUhFUoLsgrCz6rigtdlkorWlBb2uEX1TE3qdsFUVFXJ49Y/Yu3sy9flXsXG+8zLDXQ93lTsXXQxwHsySKnSt1uh1BuS+PtSvX4+puRmx8j8fq2oRQhYs3CQRgzxI3VXImUOl9Bp3tQ/0yW355KZU0G9qIH5RHWccA4Sg0IeShEHqdxNNF78AnP0CyNyfeFkI/R714MFI3d2pW7X6mkLoYl4OeSnJDJg5v/MsMt0XwL73BKvQpM867/NvqFuzBpNWi+PCaxRkNZsh8U3B4tR9QYdNJBIxUfFeHFmfS0tCL5BI0O7e06kQinCMQOHvSku2hFPbN9Ft8DBK1+6g1iGc7j2liArNkLfvxoXQ+Z3k5lehM7gQPSKB3QW7SXHYw7heU8hMKiUzqRS3AFuCevZiRfxq3st8i3eOv8Ougl283v91vG3ai0GJVEZQ3wGc27ub2v9y9a8AACAASURBVEIRDi4p0FgJ6utnZpvT24c5vX263P0LKScA8LKpJ6muCDu9Cy8degkPtQexMbOgvghR4huM7fskKyt82PzJv5jz5v/h6Hl1v8ViEW9NjkIiFrFofx5tRjP/HBduEUMW/ucwm80kZlXQJ8ARteLOmTIdzavm/mUnsFXK+PH+Pvg7deJyZjJhPrsJ3Yr3qD1WirbECtCgGtAft3nzUQ8efO1yB12k1djKuZpz5Nbn0sutF57qK2m1RSIR1nFxWMfF4frC8zTs3En92nVUfvQRlZ98gmrQQOymTkMzNJ7W4mIaNm+hYetWtKU1nAudS5X7JJztjQx/sDuO/gk31K9zNed4fvdzDLnoT7fDWnbVfoqzrz9jH3+WkL4Db2tCAZFIhKOXN45e3sSNHo/JZKSyIJ+ijNMUZqZx5kAip3duAZEIZ19/fCKikFlZk6I7SatOR0tT028Ej07Y1+k6jc/yjY5jwlPPo7D+79QtulWkYilKLxdMMtAZtADUluuw9rmUOa6wCKvQGxzDb6Yf//E7WLDw/yl2Ltb4dHMgM6mUHgm+QvwPkHeqkmO/XCCkjytxI7s4ie1kghkxeDj7vl9MVVEBTt6+7U+TSLCbPo2qf39Ga1FRp1aZI2t/QqFSETemY0EFCCm3Y+fAqeUw4lVQXUPAAWaDgZrvv8e6Vy+UUVGdNzy/C4qTYfxHQorrTug20IPkrfmkH6sluHcvtHv24PL0Ux22FYlEjA+cwC7PpVhlGik9d5aso+Wg8SVycm/43lcQQn0evOYztOPwp6Q1+qF2cMQvtjtv7LwfL40X06cOomF8CzkpFeScrODg6vMgglGBDzDQZwLfln/MtE3TeKL7E8wJm9POOhTWbxCZ+3ZTWKHFRydClrMLYq+TWOImyE05jo2ijbOh4XTP7k9Y1WCygpP4656/snzccrwHPQN1hciPfszkhLdYvqruUia5D1Gqrw6qFotFvDEpEqlYzLcHL2A0mXllQjeLGLLwP8XecxUsXHYCVxsFL4+PYGyU23/9f2DP2Ys8sjwFbwdrflzYBzfbDr5X2/QYDy+j/vvPqT2to1UrRaJ2wPGeWdjNnXttC/51MJqM5NXnkVGVQWZ1JulV6eRU56JpcsJe58Y3spXEBnfjrt6zCXW6eiIrtrbGbvJk7CZPprWggLr166nfsJGSJ55ApFRibm7GLBJR2282Z4L6Y0TCgMmBRA/zvuFiz/ml2Xzy1RNMyHNEZmjDMdKLhIeewDem+x/yOxSLJbj6B+LqH0jPCVMxtrVRnnv+sjBK3bkVo8GAwlqFQqVCobRGoVJj4+xyeV+hUgnHf21zad9KpcbW9b//t3ir+Nr6UeuST3WDFqRQU1iN7aVaQq2FBRYhZMHCnU7EYE+2fZVOflo1AXHOVJc0smvpGVz8bBg6/9bdicIHDuHA8iVk7t/DkPkdW13spk+n6vMvqFu9Bpdnnm53/OKFXHJPHKP/jHnXXznq8xCcWAInvoMhz12zacO2bbSVleH2ysudNzKbhUxxdj4QO/+a17NSyQjv707mgRLCB41C96/X0edd6DTj0LiAcXzl+Tn9clw5sXo5lfI43Bxa0ThYQUC8ULzP2CZkJuoKxSepP3+Cgvre9Js+mkJtEScunuCJ7k8ItYxcrek5xo+eY/yoLW8i56QgiuoTlUwXvUCjUwW/FO9jb3YSLw99ER+bKyLYOzIGK2sVZXZqGi664Ji947YLIUOrnsK0U0SqK9hlE0j4xVjEZj1h5wejrrbjcelfWTZxKbbjPgRtGTYHX2bizI9Y8916Nn/0DlNfeL3d6qhIJOKVCd2QSUQsTrqAwWjijUmRNzwhsWDhz0piVgXWcglOagWPrkhhcIgzr0+MwK8zC8x/mA2nSnhmjZBKf+m9vXFQyTEbjbRVVWHITsWQvh9D9mn053PQ5oPZKEYZ4o/HPx5GM2Zsu5o6v6ciP48Tm9bhEdqNyKEjkUillDSWkFGVIWzVGWRfzEHV4IhTkyduzX70bJnBIK0dItNvFoDOws5fCtiqysLFzQ4vT1dsnJXYXtpsnJXIfX1xefJJnB9/nKbDR9Du2oXJJ4RTjSEUZGlx87Fh2N3h2Lvd2GddU1rM0Y2ryTyQiL9JgmePWIZNuwe3wP9usWiJVIpnaDieoeH0nTYbk9GISCTqMBb2fwUfGx9S7E/jWGJGaVNJTYE1od2FbH6GPyiFtkUIWbBwC/hFOaK2V5BxoBj3YFu2fJGG3ErC2IeikMpu3d3A2tYO/7ienD24j0FzFiDuwIVB5uqKOj6eunXrcH78sXb1d46u/QmF9XWsQb/iHAqBwyF5MQx4AqTta/mA4C5S/e0S5EGBqAcP7vx6WVuELGmTPu/0Wr8lZpgX6fuKKVB0wx5oTNyDIuD+Dtt6abyI9oijyL8GUWYactveRCZcChYNiIeUZVB6Sqhs3hUOf0J6oy8ikYjIoSP55vwPSEVSJge1LxBr76ai1zh/eo3zp7q0kdyTFZw/aY36wkxMF0wsOryNwJ7OzEoYi0ojBNSG9BtE5u7t1Ja14JibCEaDEJt1myjKTKPNYMBbU8OFC/54S2yJqN9JU00LmMdjd8CR5yUv8emkD5BN/w6WjsXz2AuMnPkm21esY+/SRQxf+Eg78S4SiXhxbDhSiZgv9+ViNJl5e0qURQxZ+P8es9nM3qxK+gc68dX87vx4tIAPdmYz6uMDPDwkkIfjA7G6Dd/z18PU0oKhtIztiafYvieVv8mbSWgVoX3gc2qKCzBU1YHpavcpibUc2xG9sX/waawirh9j2GYwcGzdSo5v/BmzSMTZg/vYvnIR2X4GLqpVOLZ44dLkQ2TLJHo1XamFY6WW4eyjwdlbjZOXBgcPFfrmNspKqjl6LoWy4hLqyu2oKmxCarhahKnsFL8RRl5IBy/kxLZ82vRN9J8aRMyIG7MClWafJfmXteScOIZJDNneWmbMfZpRsV2r3fZH09F4/r+Gr40vGx209MQGK1M6tWUOSGxskNjb0/oHZY6zCCELFm4BsURMxCAPjv1ygU2fnkZX38qUZ7q3S55wK0QMHk7uiWMUpJ3CP65nh23sZ82kMTERbeJebBJGX36/Ij+PnOSj9Js+ByvV9VMvA0KB1eXTBItKzKwOmzQdOoz+3Dnc33qr89Uskwn2vg0OgRA9u0u3tnW2JiDGmTMptcRHxKDdvQfH+zsWQiBYhT7OexvvLC/M+lME9b8k9vyF1Kjk7euaEKrJw3hmMxkNQ/CPi0Vpb8fGPRsZ4j0EJ+W1XQQdPdQ4eqjpNd6fmtImUo/kYTjaRPMeDd8lHsQlWEWf0SGE9h9M2p7tFNYb8a1pQlZ4VCgqeJvISzmBTGymMMSP7idDEJmMxLx0P7I2HbYvf0Ga43gidozkvdaP+cesZxHNXQ3fjCTi/LtUj3qU5J3bcPTy6TAeTSQS8bfRocjEIj5NzKHNZOa9adHtK9JbsPD/EbmVjZTUNfPI0ECkEjH3DPBnbJQ7b245yyd7zrMxtYTXJ0Uy+Brpqm+Uttpamk+eRJd8Al3qKQxFxRhragAIubQhglaVCJlVC0qVEZsIKTJvf2Sh3ZFFxyONHIREo7nWba7i1On97F/8NcbKevI9WtHZRuJea4N9dTERmeVEiCRIrbyxc++BS4j9ZdHj5K1BZSfv0PPBI8iOHkMC0Rl0rD2/lmWZH1BXryVa0YMxDpPxNQehrWqhvrKZgoxqdA2tALj62zB8QXsrkNlkorlRS1NdLU21NTTV1dJYW0NTXQ1NdXXUlZVSkZ+LlUqNqY8Xq1WHeWrQ3xkVfmeKIAsCPjY+1KvakNuoMLUWUFsppCqX+/j8YUVVLULIgoVbJHyAB8mb86ks1DLi3m64+l8jc89NENCjF1YaGzL37+lUCKkGDkTq4U7d6lVXCaGj61YiV1rTfcwNDAaBw8ApBI5+AdEzO4xfql68GKmzMzYTOshA9ytnNkBFJkz9puvuaUDMcG/yUiupip2I7Yo3MVRUIHPpOCPOaL/RbK38GLHUH1NbJmaMgBhUjuAWLQih67j4AXDkc/KanGhqNhA9IoHEokRqWmqYFjyty/0WiUQ4eqoZPj2aoVMjWXt0C4l7T9BUEE3lFzoW/msg1hobyuwaaShS4Xh+520TQmazmbwTh/G1rma3vTtBLdFoZOXYdBsJQJ/lH+D01qccKvJGtDeOJZXLuO+xBYjmrYEloxioW0517Gj2LluMvYcXftFxHT7f06NCkYjFfLQ7G6PJzPvTo5FK/nfdOix0HaPJzA9H8ll9opg3Jkd0Lc3zf5m9WZUAxIde+f5xsbHi0zlxzOzpzcsbM7h7yXHGRbnz0vhuHcfqXIe26mpB9CQno0tORp+dDYBIoUAZ2Q11z1DKG8uRGwvxU1WgULUh1cgR+fcD/8HgNxjcY27oO1Zv1HOi/ARJ+fso3XkY7yxoVphoDA0jtHYsoosS7N2tcY7VIJWUUpi+jarCRFrqTuPmN4OooaMulyy4HtYya+7qdhezQ2ezOW8zSzKW8HrVM3hrvLm3/71MCpyEXCKnsVZLfmo6bYYKziado6m2lsa6GnR1tTTW1aKrq8VkNLa7vlypRGXngNregaELHuCMRx1fnf4/5ofPZ2747Y/DtHB78bPxAxFI/V3RpefT0iiltaUNma8PuhMn/pA+WISQBQu3iMpWQd8pgUikIkL7uN3260ukMsL6DyY9cQctjY1YqdtbdkQSCfYzZlD5yae0FhQg9/WlsjCf88cO03fa7A7P6RSxWIgV2vI0FB1rV+ROl5yM7tgxXF94HnFng6HJCPveAecwiJx6I497ucBqToOU7mZo3LsP+1kzO2xrq7BlWPEQ6qxCMDSu5dzhA0QMGS4cDIiHY19BaxPIr+Fj3lQNp5aTZhiI2kGFf2xP3t3zEO4qd/p73FxxOrFYzIz+Exgc05u3Nn5I6IHRZJwsJKT/YNK2b6b6opMghEa9cVPX/z1VRQVoa2rp5V7DztO26K1ciYkyXOmPSkXw2y/gsH0PO79LpyYzmp/+voIZb8xCNnsF4h+mMM4thZ88fNn80bvMfesDHDw6rlv0xIhgpBIR7+84R5vJzEczYy6LIbPZTEt6OobSUtTDhnX+92Hhf4rsi1qeX5tGSmEdSpmEBUuS+X5hb7r7XKMA8+2mvgTMJuG7QGYNUsV164ztPVdBiKsaT7v2KXwHBjux7clBfL0/j8/25rDvXAVPjQzhnv5+11wcMFysuCx6dMnJtOblASBSKrGOjcHm7klYO+mwMp9FdHEHIlMbjvZSSjVRWPeYjzhgCHj26JKr8W8paSzhYPFBkkqSOFZ2DE2VmUFpTvg2SVEEhuJgTKClQoJvpCP9pwbh4PHrd2YEZvMICjNOc+TnFSQu+Yrj61fTe/IMooaN7rIgkklkTAmewsTAiewt2ss3pxfz5dZ32VW/mAitO6bSuquEjtLGFrWdPSp7Bxy9fFBd2lfZOaCyt0dlZ4/aTqj58ysHig/wfuLLxHvF82zPZzvqhoU7DBdrFxQSBY0ecsSnTciNldRd1CH38aVh02ZMev1149puFYsQsmDhNtDl7HA3SWT8CFJ3bObckSRiRnZc8NR26jQqP/ucup9/xuWZZzi6diVypZLuY2/CNSBmNux5XbAK/U4IVX7+BRJnJ+xmdew2B0D6GqjKhhnLQHxjftC/LbBaHzoE9Z7dnQohY0sLxtYoxNJmlK6Ol1Npi0QiQQgd/hQKj0DQiM5vmLyYep2J/HI9/aZNoURXytGyozwS+wiSG+z773FVufLEmAdZc/QUyYd0TJgyiNQdmylsluKXdx55bQHYt88GeKPknTwOQGWwM7GHwmi1gbDp7UWcY8JwJkSHsuFvn1NrHs6Kx9cy8dkB2E/+EvnahUyOdmJ5kkTIJPfmh50K6EeHBiEVi3hnWxZtRhMfDvOgactm6tdvuDyxk7q64vjAA9jNmP4fH8gs3Jno24x8sTeXL/bloFZI+WhWDH0DHJn99VEWfHucH+7vQ6x3x/VTbisXDsCy37l8isQgU4FMKdQ2k6kuvQqbQaJkclEt/u7OsOcAOPgLCztOIWAlWP0VUgmPDw9mUqwnL/+SwZtbzrI2pYQ3J0fSw1cQeYbSUpqOH0d3QrD6GC7FPYhVKpTdu2M7rDcq52asTGcRlWyD1mbMZWLq7SI5pJnB8kp/+g5K4PGE6BtKvmMwGkipSCGpOImkkiTy6oX/Sx8rL6YXxyJNLcPa1hF14FgaapxReakZdU8Q3uHtLXUikQjfqFh8ImMoykzj8JoVJH63iOMb1tBr0gyih19fEJnNZurKSylIS6Up/RQDM0Gvc8cMlNuUUhVgIqL7QIIDorG2s0MhV6KQKFBIFMgl8sv7MrHs8r5UfGUKm1WTxXP7nyPUPpT3Br93y9/dFv4YxCIx3hpvSkRNeAOmtkJqy5pw8/UBsxlDcTGKwMD/aB8sQsiChT8BLv6BOHr5kLl/d6dCSObqgnpoPHXr1iOaMonsY4foM3lmu7TIXUKugh73CEKirlDI+sYla9DRo4I1qLNidkYD7HsXXKMgfOKN35srBVaLrEZjv+dljI2NSDqYlOdvOIDO2o1iu7UofRQ078+h7HwWHiHh4NMPJHLBPa4zIdSqg+Nfky4ZgAgjkUNHsvT8SsQiMVOCptxU39s9i30gjT5bUOWG4+ARiMrWjjK7JhqKlDid3ykUsr1F8pIP4mql5ajSFj+iUSma0Lh2/HtXe3gxdvFzfP3is0i001jzXgpDh9sSPOJVbHe/ysT4+1mzNZd1775Cv+lz8Y2ORdzBpOKBvl64nkyi4evF5L2VjdhsRtmjB25vvI7MxYWqrxdz8c03qV60CMcH7sdu5swuF0C08OfnZEEtz69N43xFI5NiPXh5fDcc1YIg/umBvsz++ih3fXuM5ff3IdrrPyyGjnwOKmcY9hIYdIKV2ND8m32d8POv+801tDZqGSyqx6mmDQ7qwPwbtyyNu5BYxikUnEPwcQ7juxkh7LjgxRu/ZPDKGz9wt6iEuJIM2i4tDIhtbbHu0R378cNROreAPhNZ8TZkjQ3QCMVSX46Yh7HTEMZRYzjaZmskYhEvjAnj/kEBXX5Us9nM2vNr+ejkRzS0NiATy+jp2pPpIdMJbXQl7YfV1FeUYe/ZF11TT4xGNcPuDiS0r9t1ExOIRCJ8ImPwjoimKDOdw2uWs3fpIpI3diyImrUNFGacpiDtFAXpqTRUVgBg4+xCSN8B+EbH4RMZQ05LAd9mfMu3hevg9LouP6sI0WWhpDfqsVPY8dnwz7CWdVIrz8Idia+NL3n1ecTYKqhryqemrAmfgEu1hAoKLULIggULwgAUET+CAz8uoaa0uFO3JftZs2jcvYeDiz5DprCix7hbCBTt/QAc/jcc/xpGvQl00Rp0+ieovQBzVgpudjeBRCImaqgXR9bpaVC40pSUhM2Y9gLw7P5ixCYPVKNc2Va0hTnWvpzavlkQQnJr8O4jCKFO+7oCY1MNGWUK/OPCUTrYsz5xPYM8B+Gmun1ujrH9AriYI2HfwRTCBsaTsmUDVSX2OGXvuGUhpGuopzQ3j97ONRQdM6G18adnv2tXiHdQOjDr1Zd4efHjDDozj137lZSrrOjXbwFemd+QkPAUifuyWPfOK6jsHQgfGE/E4GE4evvScvo0des30LB1K6FaLa32jmwP6YOsbyQPTwhC1lINzUWoFnZDN0BD1ZYMLr79DlWffoDjYE/suzsglhihTQ/G1kuvemhrFV5VLjDxU2GiaeFPR6O+jf/bcY5lR/Jxt7Hiu3t6MTTs6hg/DzslPz3Yl1mLjjD/m2OseKAvkZ62HV/wVqnOhewdMORv0KPjgs4d8ea6NDadLuPU8yMBE9QVQOU5qMwSrN2V5yB1ObQ20qYX0VRmRdRFDUtKZZj0ZkwiERdc3LCaMgWVtwwr41k0dduxq66Gaig2O3HI2J1DpghOy2KwsfUkwFlFhJOK8U4qVKWZFOxchzrxAPvyg3ELCMI1MBg7V/dOLUPF2mJePfIqx8qO0dO1J3d3u5s+7n2QtsGB5UtJ2rUKhcoRhe1MDEZf+kz0IXaEDzLFjVvtfSKj8Y6IoigznSM/r2Dv0kUc37iG7mMmom9qpCA9lYsXcsFsRq60xicyml4TpuEbHYudm8dVzxClieLjoR9TqaukTl9Hq7EVvVGP3qi/vN9qar2y/7vjrcZWTGYTc8Lm4GLdcTyphTsXHxsf9hfvx8e/HzWpJVQVViGLF77/WwsL/uP3twghCxb+JIQPjCdp+VLOHEhk4Oy7O2yj6t+fZm9P8vJz6D1pOkrNLSRusPWCbpPg5Pcw5Hl0aWevbw1qa4X97ws+7CE3VgH890QM9CB58wWKAxLw3JPYTgi1VNVSbHDD26ae3hHjWF20Buu4QLKPHmTI/PtQOzgK7nGJb0BTVfsCsSYjHP6MPHkvmrSNRA1P4EDxAaqaq24oSUJXGNt7GJ+u2cqZZBPz5g3i5JYNFBmt8T99CMVMnSDabpL81JMANHhbE74vnBJfCB4SdN3z/G39+ev8V/jr5sdZcPJe0nShVK3XMzwqnvALnxD80Efkleg4c/I0KZvXc2LTOmxbW/GobMBTq8XZx4Rt73qsnUqJEaWDfh38fOX6IkAllqLqr6ApxIqq02Yqtl6geu8FHHsosY/VILZWCq5JSjvBeidVCG5Mi4fD1EUQNu6mPxcLfzx7syr4x/p0yhpaWNDPj2dHh6JWdDzN8LRTXrYMzftGsAz9R8RQ8jcYmmWUfJmCZNXDyH19kfn6IPf1Re7rh8zdDdHv0hibzWb2natkYJATMokYEINjoLCFjcVsNqPPPk/j/n007t5Jc8YZMJmRqOVoguWonWtQOVQTISsBTkIFVJttSJFFU+TYi0aPATh4heDvrGaokwpnjeKyMDC0tJC49GtO792Jk48fxlYDqTs2YzQIMX8KlQpXf0EUuQUE4RoQjNrJiZXnVvJJyieIRWJe6vsS00OmIxaJyT+dws5F/0ZbXYVc1RORvB/dBvrSe4I/Kttbc1n9VRD5REZfdplLWrEUsUSCe3AY/WfMxTcqDrfA4C6lina2dsbZ+vZl4LPw58BX40ubqQ11oA+kFlKZn43Erg9iG5s/pJaQRQhZsPAnQW3vgF9MHJkHEuk/c16H7koiiYT8sAAkZcVEx3ScYe6G6PsIZK6D0z9R+cXh61uDTn0P9YUw4aPrBiJfD4W1jPABHmTsbaP60FY8WluvqpGUuSIJo1RNxChXfF3i8FR7ckpdgb/JxOnd2/l/7J13eBzVuf8/s71Iu9qVVl1adUuyimXLli33iiumF0MIPYFACLn3hpLO/d2EdAKYGgghGGyKwRgX3HtvklzUrN7rqm3Rlvn9sbJs44Jt7IBhPs8zz45mz5lzZiTt7nff93zfsbfcAQmT/UKocjNkfEHcFH8GnZUUuUcTYLKTkJPLXzc+Sqg2lPHRl8/WGvzOScpkO6qiCIQgM4bgEBq77XRXyrBUboEhly4aj+/Zil7RT6VTR3BgFoEBIqbwCxNWI8NH8uSkp/iF4pf8oPZBGsjikyIjE1W9RC/7CWENGjSVWuLadDQGBdIQGsixqBBKhBDiI7Wkp0aQkJqEwhjK5nqRP27rINEaxx/unIBWqx+MCOoHNvv+/bS99DIt27bTfkSD+Z47Md2yAHnAKWYWXXWw5HuweAFMfAImPnnJkUWJ/wztvS5+u/wonxY0kBQawIc/HHNBrnAxZh2LH/SLoTvf2M27948mPfIyum66euDgO7S3ZOI4Voo63k3frl2ITudgE0GpRBkbiyp2QBzFWWkKtOBpbGTylJMpOT6nE/vu3fRs2kTv5s14GhoB0KSnE/LDhwiYNBFNRsbJcgJ9bfhaiqmtKEYemUVY8nCmKM7/kau5opwVz/+JzqYGRl13M/k334FcocDr8dBeV0PT8TKaK8porihn/2ef4PN6APCoBZoD7UyPTuK6cd8jNWQk/XY7m95+gyOb1iJXBqMKvJW47Azyb0giOOoizHMukJihWdw6NIuOhjoCTGZUWik9TeLCsBr862SdiWEA9HRU4fX4/Bba/4FaQpIQkpC4ihg6aRqfPfcHag8XYc0adsbz7fW1VLY2ktDZg3PlKoxDM77agDEjIWoE9qUvYt/Vf/5okNsBW/4MMaP9RVkvA9lToinaWEdN0HAS9u4lYOzYwedKi/rQeV1YZ0xCJsiYHT+bNw6/wfisuRSuW0Xe9begiBwGaqM/Pe5UISSKsP15urVJVBbXM/qGW2l2tLCtfhsPZD1w2iLcy8WESTnsKWpl5fptDBk3iX3tH9JWE4ilbM0lCyGvx0NVwUGS9B107hPojBzCsNExF7Woen7SfGp6anhVeJXHUv4Hx8YoPu9/lLRNiwjsqUFv1hJ137Wk33gTqthY2mqqOLJlA8e2beL4+go0u1oYkj+BoROncneojp99VEjTO4d5/racM+yEdSNGEPvGP3AcOkTrSy/R+te/0vHGG5jvuRvTHXf4a58Yo+GeVX7Xws1/gMZCf3RIc4VSpy4SURTxun24+714+n14+r34fCK6QBUavRLhO1RbSRRFPj5Yz/9+dpRel4fHpibz8ORE1IqTX9L4XC5cx47hKCzCcbgIT3MLkX/8I8owfwpTjFnHew+M5tbXdnLHP3bx7gOjSYu4TGKoYDHenh46D3ZSN34+Sb9+gCGhMXhaWuivqqa/uor+6mrcNTX0V1XTt2MHossFwNsAm1Qcj41BYQ7GUViI6HQi6HTox4wh4KGHCJgwcfA6zkAfgix+HNb4cV86TdHnY9+KT9j23tvojEZu/sX/EZuRNfi8XKEgNC6B0LgEmOovj+B0OfjXpoVs2LsMS7eaIf3RuAs72XJoIVvwF+v0eX3INSMJS5jG2JtTiU0/f8rs5eBcthnPaAAAIABJREFUadsSEufihBCqV4mY1CI2dw22Zgeq2FgcRUVXfHxJCElIXEUkjshDrddzZPO6swqh3UuXoFCpyEzNomvpx1gee+yrWxiPfpjWf/8Mucly/mjQvn9CTyPc8NpXjgadwGjREZ9lptY9AdvajYNCqPVIDR3yMDIjmpENfAM7N3Eurxe9Tk+GEXuBjdKdW0mfMMVfq+f4Jr/4OTGvmp1Qv48i431AGZmTZ/BOuT+v64bki7P7vlBy0zPYpP+YzoJe5tw/jr3LPqRGMJCw+3PUc8RLumf1xUfp7/fQHykjvDiFzig5CcPDLvo8jwx7hNruWv5e9Sd+d/9f6HwvkMLMhwC/uZauWY1+UTM6ow19kBq9aTLjFkynt6Oc+mM7ObxpHQVrV2KKjObXybm8VNHL9L928at5Q7lpRPQZwkw7bBixr72Go6iItoUv0frc32l/85+Y77oL8/fuRG40wvyFEDEMPn/Knyp327tgSbnoazsXYn8/7qYmnDV1VBW00tgqA0sEokJ9mshxuwb23Sf3z4VMJqAzqtAZVOiManRGFfoT+wYV+oFjOoMKueLqjnLVdtj5+SeH2VLaSk5sEH+4MYvkYC2u4+XYiooGhY+rtAw8/sgFoRHY3AGo33iT8KefHDxXbLDutDS59x4YzZDwSzB5ORWfD3a/iq19CA1B6ZT6JnPkt0dpil5K+GgVEzPGkDXyxtPcxUSfD09zM794cRW6tkZ+mKiiv7oaT0sLQTfdRMDEiehGjbysLoi9nR2sWvhXaooOkTRyDDN+8OiXpjSXdpbyy+2/5Gj7UaaOncrP836ORWfB3e+ivriM3Z/sorG8CkNoNmNvHkvqmIgvNUKQkPi6CNGGoFPoqHG0kGtw0tnaTHNlCxZrLN2rVyN+IRvkciMJIQmJqwiFSkVq/gSObN6Ay25HrTuZftDRUE/x9i2MmHsd4dYUatdvoGftWoxzvto6C7s9CnuLmrBp6nNHg/r7YNtf/QX+4id8pfG+yLAZcVQWdlB6sJMonw9BJqPwg/0IYgBZt4wcbJdgTGBo8FDW+PYyKzKaA6uWkzZ+MkLCpME0OMwD7kvbn8enDeZwSSvx2cPRBwezdNNS8iPziQqIuqzzP4EgCIRkqOjbHUmN2ENQaBiNPQ66jzZgaTkGYekXfc6KPVuRCz7sHTJcIdlo9XLC4i7+23RBEPjfcf9LY18jvy1+mlcf/wem1ij6ulz02Vz0dfdjt7noaXfQVNGFs9d9Su/RKPQ5yNxl9LQfw9PwCbcCPpmKw8+ZOBoUTt7IoaRkpmCxxhFgDh4URtrMTGJeeRnHkSO0vfwybS++SNvChchNJhQWC4qQEBTa+SiKtqHYfQ3yifehyJ6BIsSCItSCTK8/Z/RLdLtxNzfjrqvHXV+Hu74ed309/fX1uOsb6OxV0BiWR3PYSNzKQOQeB8rKChQqOSqjHrXFhCZAQ2CwDIVKjlIlR6Ea2Fefsq+SgwCOnn76uvqxd7mwd/XT0+GkubILR68bxDPnp9Er0RlVBAZriEk1Y80Ixhiqvaho3teB1yfyrx1V/PnzYsJ723ghxkNuVxGux1+i5NgxRIcDAFlgINrMDALuvRfl0Axq+qM4sK0De1c/7vX/wvKwDXnQSbe4uBA97z04mtte28mC13fx3oOjSTmH8+EFcXwDYmsZ7UfSqEyZQo+uHVOcmqjioQjvC7yzbhPHrX8iLd3KxOiJ5EflY1AZcJhC+FAM5wfX5xM2M/Wr3q7zT3H/bj5/+e+4XS6mP/AImVOvOe/v3+1184+if/Ba0WsYVAb+PPHPzLDOQBAERFGkqtDG1iWdOPsSGTV/Erlz4lBppI95Et9sBEEg1hBLdXc1t0cJFLSKVBUWEBVrBZ8Pd0MDqri4Kza+9B8iIXGVkT5hKgVrV1G6axuZU2YMHt/98RLkSiW5c69HZzCijI7G9v4HX1kItb70KnKjlqCgAmg5BqFpZzba8zr0tcLkRV9prLMRkWjEbPRSbc/Fcfgw6qEZVNQrsHhrCMqYflrbuQlz+cPeP/DAhP+icPGHNJaVEJkw2f9kxSa/EGotgdJVVFgfoPdAMVPum8n2hu0025t5YtQTl33+pzJ9Sh7LdhexftNexo+fzK6WxbRUBxBSuhrhUoTQ3u1EaW1EHbRzaEQGacPDLjk1Sy1X8/cpf+eOFXfw0+2P8e6cd0kIOHuai9fjw97dT5/N/6HfL5hS6Ouejq2pkY76YuxdjQS52/C1lXFkZQFHVvr7yuQatIYwDKHRhETHEpEUT3R6EtEvvICrpISedevxtLb6t7Y2XJWteFrV4JbDvkXAyb8xr0pJv0mP3ailL1CFTyUnpNuDrq0PWWunPypwApkMX2QcrTFjqUu7iS6fAZkgEmtVkjomnCirmt41a+j+7DNcW0tBLkc/ZgyGuXMInDbtrPbtF4LX68PR7cbe7ToplLpPiqbOJjvVRWVs+6AMg0WLNSMYa0YwUclBKFRnWWAuin7Xstrd0FEJUcPBOhZ0X74m5/TTiBctunaUNLPsxXfJKNjMO911aJ19AHSp1WjS0gi66Sa0WZloMjJQWa2ICJTtbWbP8gq625qISDIieL3UWMaS9u67WB5++LTzx4foefeB0dz+2i4WvL6LxQ+OJin0EsXQ7lfoaQ+jvT8YlyqKwBFN/OCOm+nrcrFv/XHkWwQSDmbTdryGl8L/zVPBT5ETnkOoPAefIpBJQ/IA6LN1subV5wmJsZI0cgzhickn1wFdIu5+F5v//SYFa1ZgiUtgzo//h+ComPP2OdJ2hF/u+CVlnWXMjp/Nk6OexKTx1yrqbnewZXEp1UXtWGIDmfdoKpbYrxhRk5D4DxIbGEtxRzHRceEIBb00Hz+CasxsAPpraiQhJCEhcZKI5CGYIqM5snn9oBDqbGrg2LZNDJ91Lfog/5tj0M030/q3v+GqrEQdH39JY/Xt2YN9927C/uvHyJp/A7te9lsbn4qrB7b/3V+rJzbvq1zaWREEgZxZiaxfLKds2V40dSL9cj1Dhp75Rj8zfiZ/3vdnDoe3odLqOLh6OZGP/jcYov1CKPdevyW4QkNRgxq9yUxCzkhe2PJTgjXBTIqZdNnnfyrRVgvuoF7sJQpiH8pl10eLqZEbSdy+As34n17UuToa6uns6CYo0ItXlYIoqEkY9tUcl8waMwunLeTOlXdyy/JbBqt+D24KNRq5BpVchUauOfmzSYUm5OTPYbJo3N5wnN0e2hvcFBW2omztI8zjJtBtx97bRZ/tAI0l2ylaPzC4oEZUG/Bq1PTL7bgFO26LHV+wAlliOEqvgNIjoPAKyH0CMp+Av5LIwId5D+AW0Xtd+EL6aE8U6Q7WooyMxqQfTUDnUHzVgeCDkKgAxudHkjIqDI1eCd0N0FGB5p47CXnwAZylpXSvWEn3Z5/R+ORTNKl/Q8CkSRjmziFgwoSLSo2Sy2UEmNQEmM7dp7vNQfXhdqqPtHNsWwNFG+tQKGVEDTFhTTNgDa7H0LMbavf4BZCj88RNwx9uEiA882RENnbMYNFP8EcSijuKKWwrpLC1kKK2Itod7fx4+I9ZkLrgSwVRVWMnn/7pDdI2L+PuvjbcoRGEzJ2FNjMTbVYm6qQkBKVysL0oilQWtLH70wo6GvoIiQlg7iPZxA41U7C+lu0feqn+8CWC77kHmVZ72liJlgDeHUiTu+213QNi6CJFaFs5lK+lo3IY1YnTccnt3HCNf62O3qhm4g3p5M8ZwrEdjRxapyGkNBbR4KKkeyef6/9JQKKb3xz8gImtE4grEqk7sJfKQ/vZs+xD9CYzicNHkTRyNDEZ2ShOue4LobW6khXP/4n2uhpGzLmOcbd//7zncHqcvFzwMm8deYsQTQgvTHlh8HXK5xMp2ljHrk/9tYrG3ZxM5qQoZPKrO+1S4ruH1WBlfc16fKFZ6FX1dLeWoor9IcAVN0yQhJCExFWGIAgMnTCFbYvfxtbUSFB4BLuXvo9crmDktScNAYJuuJ7WF17A9v4HhD3xs0saq+1E3aDv3QNri6FgMUz9NehPWXS76xVwdMDkp7/qpZ2T5PFxbH/vCEePy1HbKlC5IPW2SWe0C9GGMCZyDCvrP+epSTdTsGYFE793HwEJE6Fkpf8Db+ESulNuo/LjIkZddzPt/R1sqdvC94d+H6Xs4j7UXAqJIywo1wews+MowZFRNPY56N5ThsbRCVrTBZ+ncu92ALSNXuois1Gq5USnXHj/c5FgTOCVaa+wuHgxDo8Dp9eJy+uiz9NHh7NjsH6Hy+vC6fE/5z212OTZiPFvoiiAKEejUGHEiKUnhJDOAIw2JbpeHyq7E0VPN0pRAYIBMINChqCWIdfLUOiVaAQb2u4jqDU6tCnT0Zqj0an1KNUabE2NFG1cg9sRgEFvRqdJQlaVjcoVSJ+il7KwTRRbdtMd2EJseygJK2TE97QR31FHgttNoqhEkzgFTcpMNA8swPKTx3AcOuQXRatW0fP558gCAgicMQPDnNno8/IQvsQJ7EIwhGjJnBRN5qRoPB0N1O86QPXhNqrL2qg+7I/0mOQWYoPSsCakEZmViDx+tL/Qcf1+qNwKVVthz2uIO1+kXqmiMDyZImMYhTI3x/oacPv86YwWrYUsSxZ9AX08u+dZdjXs4pmxzwxGF06lu6OLz599hYg1S5nu7KY7NonQZ57GPHPGGZbTJ6gt7mDXJxW0VHUTFKbjmgcySMyxDEYq08ZGsntZOVWGXBI+Wor5zjvOOEdSaACLH8zjtlMiQwmWixBDe17D0aHFVueiLXYotrhS4kLmntZEqZaTNTmajIlRVB5q5eDaGoQjk4iTTaAhshnXsL18eOx95m8KpSPUzYFcJ+HNSiIa++natIrC9atxy300hbmpD3fREOrCrRIRRX8epIg4GHXTKXToFXqSKjXEHnQjquT0zotjW1ITBUUvoVfqCVQGolcNPCr1BKoCaXe28/vdv6equ4obkm/gv3L/C4PKL3Bba3vY9E4xLdU9xA4NZuKCFAzB2jNuhYTE1YDVYMUreqnXmwjR1FHV1Um3x4NMp6P/CltoS0JIQuIqJH3CFLYt+TdHtmxg6IQpHN26gZyZ8wajQQAKi4XAKVPo+vhjLD957KIX+A5Gg044xeU9BPvfgv3/hAn/7W/k6PRHWIbM9tcOukLI5TJS4zwcqo6FXh9JymJU4Wd3a5qXMI8ntj6BYoQV32ofhetWkT9kkr/44bJHwOvmsHMIIlVkTpnBkvJP8Irey1476FyMn5DFovW72bO9mBvHTWJHQz3NlXos5esRMm+64PNU7FyHSWHHetxO5eQcEjODkSsvzzfBWZYssixZX95wAI/PMyiM+r39eHwelHIlCpkClVyFUqZEKVPS0OniiY+K2FnSTlpyCM8uyCIq6MwPb/buftrqemir7aWtrpf2+l46m+yINhEH4FZCsKcCTVkVwSPDCUnPIzg6AEQwR0/hwKo1dNbvhJY9CMojWEdOZfj8cbS11FJZHUBFaw2VPeWUq5RsVCjxhvprTMkRiOsrIGXnToZsfpohhniGJMwg7IEbCHviZ/Tt3kP3ihX0fP45XUuXIg8JwTBrFsZ5c9FkZl78+h6v25+qWbvLH+2p2YXCVo0VsCo0kD0cm2ki1c7hVDemUlQRQ8FeEWWhnOhUB1EpLbiFMBp68qlXxNEQPIWm3gYcHjdCs4CyUSDW62OkJ5EwpZHQQCs6UwK0RyIoFYwxHuStile4qe0mnp34LCPD/Wvu+tva2fmnl9Cv+piMfgf1CRkE/vRHpE6deM5rbKroYteyCupLOgkwqZn8vVRSR4efEZ1QaxWkj4umaIOXhn+9iOnWW06LJp0gKTRwME3u9td3sfjBMcSH6M9odwbObji0iI6mFOqsYwGBYZOt52wukwkkDg8lIcfCjt0NvL/oKCl1EcibrmNC1Ahq+5cQMS6bGXEGhFT/tYteEW9NF/Lj7USXtxPToEaUCRBtREi2QJIFwaAZDNjZu7uQrS5BXd1Ld7SSkjwZNnk5vVWH6O3vPe8XCZH6SF6d/ir5kfkAuPu97P2skkPratHoFcy4byhJuaHf+LVlEhLn44RzXI1KRazeRlUXlO3ah8VqveJFVSUhJCFxFRIYHII1cxhHt2ygp731jGjQCYJuvYWeNWvoWbsO49yLWys0GA064RQXmgqJU2DvPyD/x6BQwc6F4Oq6otGgE2TfmkvR7w/jlatJnxh7znaTYyejU+hY37ODYTm5FKxdRd60PyAHOL4e35B5FG3dR1z2cAItFpZuXUpeeB6xhnOf83ISFKZHZulHXx2Barp/XUCtykjSxqVoL1AIuex26qoaiBKddBrjEEUdCdlfXyFChUyBQqZArzz/B9XYYAWL7s9j0Z4afr/yGNf8bQs/n5PGbSNPt/zWGVTEpgefZvfrcXvpbLT7BVJdL+1VWo5XR3B0oxI2HgDAJ4BMBFPEcCbdPRudrIhj65dSsuNTynZ8QoqhjVFhXczPzvcX/E2ahltjoKanhnJbOaWdpZR2lHCw7TCrnO1AJ9QswVz5Lik+uV8YzR9PyiOvE17USN/Kz7EtWULnv/+NJjuL4HvuIXDatDOjRM5uaCuDthL/+p7WUv9jZyX4BhzVAsIgJg9GPYgYk4cjJJl2Tw+dzk46nR14nfUoujvoqfLSW6Wmr7SbyoK2UwaxEI6FcM50kwToADrxItCPQCU+FIiYuZWn6Vf08dGBPexTLienqgb1kWIsji58sWos46JIi/dA49/hnYG0WIUaQtMhMod2IZ3dG3upLGhDG6hk3C3JZIyPOq8oz5oSTeHGOqoUKcSsWoXx2mvP2i4lbEAMvb6L21/zR4bivkwMHXoXt82O7Wg3tePyqTeXct+we87fB3+k/aDdzjJ9PxseHEvtrmYOrHwPQWYkteVW0lOisGYEo1AORML8ugTR56OxvJTj+3ZRvncXHevLYH0ZIXEJJOXmERQWwebFb+Kyu5h4zw8Yds3c0/7WRVHE5XXR6+6lt7/X/ziw7/a5mRA9YfD/qvZoB5veLaa7zUlafgT5Nyb5UzslJK5yTrz/VgteZmjrQEimquAQUbGxuEpKrujYkhCSkLhKGTphCitf/AtHNjWTM2seAaYzF0vrx4xBGRODbcmSixJCZ0SDTjD6YVh0Exxd5hdFu16G9Ov86xOuMAEJMSQ7/kV3n0DktT85ZzutQss06zTWVK3hzhnPUfHsXkoPl5IWmg4tR6kMnkVv+3tMuftBdjXsor63nseGP3bF538qWaPj8C1XsbZ+D5ExVhrtTrq37EX7iBfOUij3i1Qf3INPBEuNk6MpOcjkArEZV75GyOVAJhP43mgrk1IsPPFRIU8tLWJlUSO/vyGTaNO5izD2eXyUuFwUuOwccnZT6OnDFtDPM/JFjPI1c8g3ns1iHnZZNT+2HmNo2U6EthJSNdCZm8YheyqHj2soLgslQjSTExFGitqAUq4kMSiRxKBErom7ZnC8LlcXpZ2llDTsoaR2KyW2ct6zV9BfUgklb6NEIHFcGENnTya3yE3UZwdw/uRxnCE66seF05ShwOPtQOxrh/4eRAR8gCjIELUmRJMZMWoKHm0QnSotHaKbDmcHnQ2f0lHxFi6v66z3QSPXYLaaMaeYCZNFMcQ8hPTgdNJCUjGoDX6bZMF/nwVBQJAx8CiAswuqd0LVVrx1hbTbzbT0hlHXHoq+LRS3IoX9AXLIA42sm/DAZhw00NfSSKiuAY3cQXufQF2bh76uSqqd9bR6jiIX3EQFNRIRLtBfGcGB9ihElf/DuyiKfoOHE79/uRxzVDTRKXLqPRNpef0NDPPmnTOiMSQ8kEX357HgdX9kaPmj4wgJOEd02+eDPa/S2ZxMS0gaPvQE5LjRKi4sZWxTSSuZUUYSEoIIkHWwb1k9CbnX01bbx+pXD6PSyEkYHkrKyDCihpj891gmIzIllciUVMYvuJuOhvpBUbTzo8UgigRHx3LTL/4flti4M8YUBAGNQoNGoSFEG3LWeTl6+9n+QTklu5swhmqZ/3gO0UO+ehqshMQ3BZPaRKAykGpPL2ZFPTLlVJorjqDMzKVnwwZEj+eypCGfDUkISUhcpSSNGoNKq8Xrdp81GgQgyGQE3XIzrX/5K66KCtQJCRd07jOiQSdInArBSbDrJWgu8ttmT3rqq17KBTPm8Vl4WluRB5z/W+G5CXP59PinHDd2YoqM5sDq5aTd8ANoOEThwXL0QSYSho/i5W0/I0gdxNTYy1MA9kLJzLNyaHkD5ftbmDB2HDtrq2mqVBBatx8hdtSX9q/YugI1HiydDo6YR2FNNKHWXl0v5zFmHYvuz+PdPTX8bsUxZj63ladnp3H7qBhcHh9HG7spqLVRWNdFQa2Nira+wb4JIXryE0PIik4kOXoi0fVLiF/7c64TfQiI9FfKKdUPI27a71CnzcQUnMhkYKzDzpHN6zm4ejkrX/gzm//9BtnTZ5M1beZpaaUARrWRkeEj/eliw38EgMdho+roR5QcX01JWxGl9ko29dbzUagc4W6R3DIZ83bbSf2kgrDVsDZHYPUIGZ2mkzbRAgKC4EPm64C+DhR2BSaNCZPGhFljJikoCbPGPPizWWPGpDZh1vofdcpzi8UvRWP0F+8dMhM5EHDgIPZXX8O6eTmhchVrU1PYn+dDJ8QyRTOHrvZwKhuSED3NeN1l4D2O190xcLIAoA6owwNU2KGiAaDywucjqNmggIrf/YbocROwWOMJjo5Brjg9ypEWYeDf9+Vx7YvbeGNbJU+cy9a6fC2+lko6jyRQPXwmNk0zs8dfmJ2/zd7PgZpOHpmcBMChNStQqNTMeuhWVFod9aU2Svc2U3GgheIdjegMKpJyQ0kZGU5oXOCgkDNHRmG+9kZGXnsjfbZOWiqPEz00E6Xq4msPiaJI6Z5mtn1QRr/dw4hZVnJnx52MSklIfEsQBAGrwUp1bx3KQCN6XTg9tmL6TAZwu3E3NaGKvjLFeq+ud04JCYlBlGoNE793H6JPJNB89m8SAYKuv57Wvz+Pbcn7hD315DnbneCc0SAAmQzyfggr/xuaCiHzZn/K3H8I3YgLW4c0KnwUodpQVlSt4N6Zc9nw5is0Gn6A3jqHykX3Meq6m+h029hYs5EFaQtQya9csbazYQjRoo+SEdOcTtNU/7flteogUta+i/a+8wshn89LxdESTE47teERCK5A4r+iW9zXhSAI3JFnZUKyhSeXFvL0x0Us3FhOc7cTj89/X0ID1WTHBHHjiGiyo4PIjDZi1H4hHcj6EEQNQzi6DF/saN6ss/LHTQ3E79bzcnIoJ8qwqrQ6cmbOY9iMOVQVHODA6uXs+GARuz9ewpAx48meMZuI5NRzRicU2iCSRtxH0oj7mOPz+o0KSlbiaCyEYCtCWgrCvUm4Gr3YPljJ9evWc/1eAcOc2ZjvuQdt6uX5XxFFkcYuJ/U2B2qFDK1SjlYlR6dSoBV8KJx2xJ4evN09+Hq68Xb7N98pxxzHinEePEiPWs8nqTPon3cjj984kgXyNp7c9ARvlz/JVHUWJsFLX087giBDZ0pAphiFxxND6uhYhs2wojOoBu6XgNDfBy1HEZoKoHFg6ziOcKKQUlAM3sg82tIeoKWpld2f7MFpq+ZY4X4OF+4HQCZXEBwdg8UaT2hcAhZrPBZrPBlRRmZlRPDOrmoenpRIoOYsKWG7X6GrMRybEEqfLIyGuI0MC7vtgu7plrI2fCJMHBKKs6+XY9s2kTp2IpoB2/SYNDMxaWYm3p5CdVE7pXubObKlgcINdRgsWlJGhpEyKgxT+MkvafRBJuJzci/49+pxe+lqcdDZZMfWbKeuuIP6Uhth8QYm35lKcNSlWbhLSFwNxBpiOdRyCExWQgLV9Nigqd+BCeivrpaEkISExJlkTZ35pW0UISEETptG1yefYPnp419qmnDOaNAJsm+HDf8Lrl6Y9OXC6utALpMzO2E27xx9h1/OewrVe1oOrl5OUHgkougjc8oMPjr+KR7R8x8zSfgi2WPi6fvQx5qqTxgXn0ijw0X3us1o7zt/v6bSYhwuH0OaHRwYPgmdD+Kzzy2ErwZizDreuS+PxXtrWXe0mfnDIsmKDmJYTBDhxnMU8f0i1jFgHYMM+OFQyEqM4ceLDzH/xe383/UZ3DD85JuoIJMRn5NLfE4uHQ11HFy9nCObN3B060ZCYuPImjaT9PGTUevOE3mUySFmFMSM4ouJV+okMIyfSX9tLR3/ehvb0qV0L/sUfX4+5nvuQT9u7AUtbj8heEqbeyhr7KKxrIqe8krE2hpCbM2E97UT4HagdzsIcDvRux1ovf3nPadPkOHS6OjSGvgkcz61Y6bz9A055EQHUnu4kNI9Oxi7Fxzd4XhlzVRHCEy96zbGTpyPNiBwcF5nnb9OB0ETIWXiyWPOLmgshIaD0HAQRfEyotwdRN3xAVrDCNb/6xjZBc8T/8xD9Oi1tFZV0FpdSU3RIY5u2TB4moDgEEZHJbC+L53Fe2p5YMIXotutJYjlG+goT6MufR79MifDxsddsInAppIWgnRKhsUEcWjVp3hcLoZdc2Y6sUIpJ3F4KInDQ3HZ3VQcaqV0TzP7V1Wxb2UVITEBpIwMJ3lkKAGmM/92RVHE3tVPZ7MdW1Of/3Fg6253nlZ8N9CsYcJtKQydEOVPeZSQ+BZjNVhZVbkKl3EEYapmquRmGpobMAHumhoYO/aKjCsJIQmJ7wCmW2+hZ/VqetaswThv3jnbnTcadAJ1AMz6EzhtEJx4hWb81ZmbMJe3jrzFhuYtZEyazqE1K9EGBmLNysFgCWPp9qUMDx1OQtCFpQtebpJHhLHjw+M4SpSE5qZTVHmchuP9hNrqEYKiztmvYtMnCKKIqdeOyjCGMJMBvfHi026+aQiCwO2jYrl91OUxrchPCmHlj8fx6HsH+en7Beyp7OAugF8IAAAgAElEQVQ31w5F84W0InNkNFPvfYjxt3+f4u1bKFi7ig1vvsKWRf8kNX8i2dNmEpaYfEmuXKqYGMJ/8XMsjz5C55L36fz3v6l94AHUycmY77kHw9w5yFQqRFGkoctJWVM3VeX1tBWX4aisQlFfi6WrmajeVkb1taM6YawAeDVafOGR+Cwm3Npo+rV6bGotTRo9DpWWPpWWXqWWHoWWbrkGm1yNTabGJipweHwoZAL3jY4mR9ZM+Wf/5OX9e3DZ+1BqtCTk5JKcl09rmJdf7vstazr+xn/XybltyG3+9UYXcS/65ArKAwyUW6IoU9rpUPTwdNF6grb8ieSxP2PH0nLq4q/BunQZqS+/RGr+yVQ2e3cXrVWVtFRX0FpVQfGOLVwb6eONbSa+nx+HSnGKIcOe1+hrDqC3w0dT2hBKQ7fz27SHLmiOPp/I5pJWJqZYkCFyaM1nRKSkEhZ//tc3tU5JWn4kafmR9HW5KN/XQuneZnYsLWfHx+VEJgWRMMxCv9ODrdnuj/S02HE7T7rEKVQygsJ0hMUZGDI6AlOYjqCBTamWUuAkvjvEGmIREakLDMbkLUGmSKH+eDHpGs0VrSUkCSEJie8Aurw8lNZYOpcsOa8Q+tJo0Amyv+T5bwApphSSgpL4rOIzXrjmDxxY9Sl9tk6m3PtD9jXvo7q7mh9k/eBrm1+ASUNIgo6kxuEU5fvtQes0BoasfAvdgp+fs1/FwQME2Z3sSzWisAWRMPnqTIv7TxBq0LDo/jz+tq6UhRuPU1DXxUt3DD+rDbNKqyNr2kwyp15D8/EyCtatpnjHZg5vXENoXCLZ02eROnYCKu3FrdERRZE+tQ7bdbfRMn4uzs9XY1j+Pq6nn6b8d3/kYFIu3s5OwrtaiOptJc/jHOzrlSvoD41AMTQZY/JMDMkJqOLiUMXFobBYLkmciT4fVQUHKNq4hsqX97Pc5UITEEjSqDEkj8rHmjkMhcqfKjoE+Cgyi19s+wW/2/07djbs5Jn8ZwjSBJ1xXrfPTVVXFWWdZZTbyinrLKPMVkZ9b/1gG61Ci8vrIjh5FE9sehZ5VC6ZkxLZs9xN8+4lhJaVoU5OHmyvMxixZg3DmuV3wlNptbB+DXZSWHaonptz/a6LOGxw6D066uNoTJ4KyFBn9xGqO7vF/hcpqu+iva+fyUNCqS48iK2pkfybFlzUfdUb1WRPjSF7agy2Fjtle5sH1/cABJjVmMJ0pI45XewEBKkHayxJSHyXsQb6LbSr1RrS5dXIFNNx9xXQa40m8ArWEvpSISQIwpvAXKBFFMWMgWNmYAkQB1QBt4ii2Cn4X5X/DswG7MDdoigeGOjzfeAXA6f9f6Io/mvg+AjgLUALrAQeE8VTLGYkJCS+MoJMhunmm2n5819wlZejTko6o80FRYOuIgRBYF7iPP62/2/06L0kjBhFS0U5iSPyeGrH0wSqAplunf61zjF9VDRti+2srviY25NSaHQW0b3683MKoe7WZlptLlK7+ticNQprx9WfFnelUchl/M81qeRazTz+/iHmvbCNP96UxezMiLO2FwSB8KQUwpNSmHTXfRzdupHCdatZ+/qLbPr3G6SNm0jWtFmD0YJel4cj9V0097ho7nLS3O3073c7ael20tztwuE+tU5MKOT+iPykCm48vpn8gvU4jMF4o2JQxY8kcEgSQUMSUcXFoYyMvGxOSY7eHo5sXEvB2lXYmhvRGYMYOnEayaPGEJ2Wgfwc45g1ZhZOXcg7x97hr/v/yo3Lb+SXo38JMCh2yjrLqOquwjMQsVIICuKMcWSGZHJD8g0kBSWRbEomKiCKZ3Y+w+Ljy7gjPI3opfczdMF69q8SqLNOI/IfbxD5h2fPeQ2jb7ydI1s2cI3jAK9tieLG4dH+lLGD7+BsddFT3kXNlDHUBhxjds60C743m0paEQSYkGJh88I30BqMJI8edxF393SCQnWMnBNP7uw4ejqcaANVKFVSdEdC4nwMWmjLYKyiFpkiGgSBdrOB4CtYS+hCXmHfAl4E3j7l2JPAelEUnxUE4cmBn58AZgHJA1se8DKQNyCcfg3k4s+A3S8IwqeiKHYOtHkQ2IVfCM0EVn31S5OQkDgV4/XX0/L357F98AFhT53p9HbB0aCriNnxs3lu/3OsqFjBvY/8F/1OBz2eXtZVr+PmlJvRKL5ewZc4PJQtS0qxNCQiG2qhp7yU+pImwlx2BPWZkYfKjUv9OzIH4arxmMJ1py3Oljg3k1ND+ezRcTzy7kEeXnSAu/PjeHp22unpVV9ArdOTc81chs2YQ2NZMYXrVnNk8wYK163GFxJDmTmTze4oXKe8lWqUMsIMGsICNWRGBzEtUE2YQUOowf8YZtAQGqhGr1YAP0b0+RBkl6cQ7tlorjzOoc9XULx9M55+F1Gp6Yy97XskjxpzhjvbuRAEge+lf48RYSP42Zaf8eiGRwefi9RHkmxKZmL0RJJNySQFJRFvjD+nAclD2Q/xWcVnLEwawe/3LkO38l5SchdS6s2j7fNfYHmsAWVk5Fn7BpjM5M65Ds/SJXSph7KxJJWpQ0Jgz2t0NiTQFpmB26uhImY/z8Q8cMH3aGNJC9nRQcj7Oqk4sJe8625BcZYirxeLIAgYgi/MultC4ruOUW3EpDZR7XOgltkJCFAiJ4YWj434mtor9lr5pUJIFMUtgiDEfeHwfGDSwP6/gE34hdB84O2BiM4uQRCCBEGIGGi7VhTFDgBBENYCMwVB2AQYRFHcOXD8beA6JCEkIXHZUQQHY5g+Ddsny7A8/vhpUZ9vWzToBOH6cEaFj+Kzis/4YfYPUev0vH3kbdw+NzemfD0mCaeiM6iISgmipyaXbVlrSQDqNIGkrngb/Q0/PKN92ZYN6FxutqYriWkJJn6GlBZ3MUSbdLz/gzH8ftUx/rm9ioO1NhYuyDlv/aJel4e9VR3sqoBd4ijKoqwkd5eQ0XWUIW0rGaLSYE4fgdEYiF6jRK1UIJPLkclk/vU0DhmCS4asXY4gk9Emk9EhkyEMbEqVGktcAiEx1nNGZS4Wr8dN6a7tHPp8BQ2lx1Co1aSPn0z2jNmExl36mrj04HTen/s+W+q3EK4LJykoiQDVxTmZhenDuDPtTt48/Cbfn/ErUpf/N9nJSzgmTqYhbAyhb71F+NPnLtCcO+9GDq1dxeTuPbyyKYWpwn48TbV0HYumfuI8uhVt5IxIvmAnyPZeFwV1Nn4yNYWCdasQEMia9uUmNBISEpefWEMsNa4OEGSYAnpwe6y0t9TS7/HgaW5GGXH2SP5X4VJfdcNEUWwEEEWxURCEE4m4UUDtKe3qBo6d73jdWY5LSEhcAYJuuZXulavo+fxzjPPnDx7/NkaDTjAnYQ6/2vErCtsKyQrJ4qOyj8gKySLFlPLlnf8DJOeGUV9i40h9LXlJKTS6+ulavuwMIeR2Oqhr6SOqt4898bnEVEBCtiSELhaVQsav5w1lZJyZn31YyJznt/G3W7OZkhoGnCp82tlV0cHh+i68PhGlXGBYTBD3TR3K6IQJ5MQE0VHhjxJVFRygz+vF5/Mh+nyIvpP7F4pCqcISF094YgrhicmEJSZjjoi6qG9Ae9rbKFy3isL1n2PvshEUHsGkux5g6KSpaPSXx3pZp9QxM+6rCYV7M+/lg9IPeK5zP6+M/QnB258jOiqfemEGsR/+ipCHHkJhOnvBULVOx5gbb8P51mvsOFZEt+xT+usi6FaH0+kJ4nDUx/wi5eELnsvWsjZEEcYnGNm5eA2JuXkYQqT/KwmJrwOrwcquxl1giMLkaKHeHYUoinQE+A0TvklC6FycbcWfeAnHz35yQXgQfxodsbGXx1lIQuK7hC5vFCqrlc4l7w8KoW9rNOgE063T+b/d/8dnxz/DJ/qo6Krgmfxnvu5pDZKQY2HzeyUktuXQmeTDXa6i/mgtEV+opF21fileQUab2cVQzyT0RhWh1sCvceZXN7MzI0iPMPDQogPc+9Y+5mRFUNfpOEP4PDwpkdEJwQyPNaH9wjoPXVoG0WkZ5x1H9PkQRXFAGHkRfb5TBJMPZ18fLZXlNB0vo+l4GYc3ruXg6uWA3xwgLD6JsMTkQYFksISeZpIgiiK1R4o4tOYzyvfuQhRFEnJyyblmLtasnCuadnepGFQGHsh8gL/s/wt7pr3GqPr9ZJf9nRXiz2gJSMXyziIsjz5yzv5Z02axb8UypnVtRV+7naayRJqG34pX7sab0k5acNoFz2VjSQvBehWqmiKcPd1ntcyWkJD4zxAbGMunxz/FERSN2VWFzzcFhVJFW4CW/ppq9KPzLvuYlyqEmgVBiBiIBkUALQPH64CYU9pFAw0Dxyd94fimgePRZ2l/VkRRfA14DSA3N1cyVJCQuEgEQSDollto+dOfcA04NH2bo0EAAaoAJsdMZnXVarr6u9Ar9VwTd83XPa1BtAEqYlLNuKpGszrhBaahpk4bQNraTwiYddNgu5LlHyP3+tiQ6WFKYyjxYyyS29RXJC5Ez8cP5/Pb5Uf55GA9GVGG8wqfS0GQyRAAmVwOnLnuRGcMwhwZRepYf+0dn89LR13toDBqrijj4KpP8Xr8RgRag5HwhCTCElPQ6PUUbVhDe10NmoBAcudeT/b0WRhDw7/yvK80t6fdzqLiRTx36AUW3fgG1lcmYuxpoT5tPhHv/IXg++5Fpjt7yqJCqWT87Xex8vk/sa8qBo1dRr0inuKQHcxNm33Bc/D6RDaXtjIlNZSCtW9jjowmNiP7cl2ihITERWI1+p3jagJDMdUdQRBmEBw7hPbePn8toSvApQqhT4HvA88OPC475fgjgiAsxm+W0DUglj4HficIwolY9wzgKVEUOwRB6BEEYTSwG7gLeOES5yQhIXEBGG+4ntbnnqPz/Q8InD7tWx0NOsHchLmsrlrNqspV3JJyCzrlxVkgX2mSckOpOdqBy6bCkBBBU7+brqXvDgohn89HTVsvxn4XmLLxNUL8MMkt7nKgUcr5/Q2Z/O76jEuyo77cyGRyQmLjCImNI2Oy39XQ43bTVlM1II5KaT5eRlXBQUTRR1hCEtc89BOG5I9Hqbp66kmp5Woezn6YX+34Fes6Cpl+61tkL3yeLf330ymasX34Iea77jpn/9RhGezT9LGvN5rwpBH4fALFETv4v4RzR5K+SEGdDZvdzehAO7XlpUy++wffiL8BCYnvKoMW2toAxrs3AWCwpNCsLqK3y8aFGeJfHBdin/0e/mhOiCAIdfjd354F3hcE4T6gBrh5oPlK/NbZ5fjts+8BGBA8/wvsHWj3zAnjBOAhTtpnr0IySpCQuKIoTCYCZ8yga9kynEeOfKujQSfIj8rHpDbR6er8RpgkfJH4bAsyeQlDu/KpjD2OuUJJXVElkf39CCoV9cvewSFX0BrexUjXVFRaBVEpZ19DIXFpfJM/ACuUSsITkwlPTMb/Fgv9Tgf2ri6MoWHf6Lmfj2sTr+Xto2/z/IHnmTR/KUPmjGf3e700pM4i+J9vYbr9doRzuLcJh95hpLKGFYo0qjUB2IIqyB6Siklz4f8Xm4pbkAmgKduJUq1h6MQpl+vSJCQkLoETFto1CjlaWRcanQy5yi+OHNMmX5ExvzR5WBTF20VRjBBFUSmKYrQoim+IotguiuJUURSTBx47BtqKoij+SBTFRFEUM0VR3HfKed4URTFpYPvnKcf3iaKYMdDnEamGkITElSfollvwdXfjOHCAkPvv/1ZHgwCUMiV3Db2LabHTSA9O/7qncwYavZLYdDMpHSNYpyxAJkC9Vk/f1o0AFC/9EID1mXYMjVFYM4KRn8f2WeLbj0qjJSgs/KoVQQBymZwf5/yYqu4qPi77GNX4H5IeU0WTNpXeDiddK1acvaPXA3teR99sItCtQnTtpzB4PdclXXdR428saWVUuJqKPdtInzAZtU6yopeQ+DrRK/WEaEOoph8As9mLsy8QrcFITdGhKzKm9E4qIfEdRDdqJKr4+O9ENOgE92fez98m/+3rnsY5ScoNQ+hTYXBEI48JpNGkp+uDt/F2d1Njs6MWXZgU6XjtkDBMcrWS+HYwKWYSOaE5vFLwCnaPg8x7FoAAjYkTaX/1lbM775Wuor+ugd5yO7qIuSA6Mba3kBk86oLHbe1xUVTfxWhvOV63m2EzJJMECYlvArGBsdS4uwAwBfTS2eTgmod+wqjrb7ki40lCSELiO4ggCEQvXIj1zTe/9dGgq4X47BDkShlj7NdwKKILp1JJTUEJjW+8jE2rpiLKRX7/DGQKgdih5q97uhISlwVBEHh8xOO0OlpZdGwRgREhJGboqbOMxV7TRO+G9Wd22v0qHdXh9AbG0OWNozMogPRqHUs2HbvgcTeXtiKIPlRlu4lOzyAkNu7yXZSEhMQlYzVYqe5rApkSk7oZl91DRFI2wVExX975EpCEkITEdxR1Qjzq5OSvexoSA6g0CqwZwUS0pFAQWI9MEKnXaihe+jEIAvvjejE3WolJNaPSXO7KBxISXx85oTlMipnEm4ffxOa0kT17KG5BR2vsSNr//BtOy5hvOoy3dBtdZQqa8xaA3MfWodXIRIGi5e/j8ngvaMyNJS1k0Yijo5VhM+ZeoSuTkJC4WKwGK+3OdnqDojHLKgHoaOy7YuNJQkhCQkLiG0LSiFB8fTJi3Rk4ohQ0mQJo0mkQZB702lj6bf7IkYTEt43Hch7D7rHzetHrhCcYCYs3UBc/C3tVJ44PTklp3fMqtuogXF4ldWIM9RHHiE5MIGL0FOI7jvDhugNfOpbH62NraSt5zmMEmMwkjRx9Ba9MQkLiYrAaBpzjjOGYPUcA6JSEkISEhMS3n7jMEBQqGeOdc9gb2opLoaDZqKcqwsV4zxwQIC5LEkIS3z6STElcm3gt7xW/R0NvA9lTYujxBdEZkUH7qy9Bawn0tSMeep/OCjOtI2/G64Ed5s+YnzSf6++5G59cyaFP3sXnO7/n0sFaG0JPO+qmMjKnzkSukCKsEhLfFAad4/RGdL1HUGnkkhCSkJCQ+C6gVMuJywohoC6S6mA7gkwEQaAsvI/QlkTC443ojVdPrRgJiYvhR8N+hIDAwkMLSRhuIcCkpiHndnrrlTgXLoBdL9FTDf2dTmpNI3GHddFraGdW/Cz0xiBC82cS3lnGp2t3nHecjcUtZPUcQZDLyZo28z90dRISEhdCTKB/LVC1So3gaMMUrqGjSRJCEhISEt8JkkeE4bb7yJNPoyXSiygTEYNCcDZJbnES327C9eEsSFvA8uPLOd5dTuakaFrsRnrNcbTvaoetf6ajOgpbykT67AK7glcyzTqNQFUgALfecwdOhY4DH73D+SpxbDnaQEZfCcmj8gkwScYjEhLfJLQKLWG6MGoE/3o/s8lHR6P9io0nCSEJCQmJbxCxGWaUGjm5vVNYP6SR1fmtTJDNA6T1QRLffu7PvJ8AZQDPH3ie9HGRKFQyWvLvprtGR3etBkedg4a0ecgDRI4F7jmtdpBOryd4/DyMXbWsWb3hrOdv6nLiO74fhcdJzjWSZbaExDeROEMc1Z5eAEwBPTi6+3H2ua/IWJIQkpCQkPgGoVDKic8OwVehR67V0WxwENk6BHOknqAw3dc9PQmJK4pRbeS+zPvYXLeZwz0FpI6OoNYRSr/GSMPeMBzB8TR3aaiLLSI8MJxR4afXDrrjrpvp/v/t3X1sXeV9wPHv7/racfwWJ6nz4jh20iRAQgpJFN4CdHkTYSvBqDCJsReEMjGpSIRp07Tun2rT1qnSRIq09Q80qqJ2K0RpUxitJhCla7SKdE5SCBlFZSN2GBCnJa/gxm/P/rgnLIBDZjvXvtf3+5Ein/Oc85zzu9JPOfd3z3OeU9NM165vMTz88RnkfvTaUa46dYjG+QtZcMWVE/WxJI1Ce1M73b8+BsDMaUeB4k2YYCEkSSVm2dq59PcN0TntHubmWnn/iHeDVDnuWX4Pc6bPYcf+HXxmQxtDQ4lf/cY2Uv8AvTf8Prmq4Nm6ndy+9HZy8eGvMY11tTTf3EntmWO88C8/+Nix9764n5b+X3Ld57YSERP1kSSNQkdTByf7T3Oypp5ZUdwptC2EJKnELFw+i2l1edacXs/fdvw9adjng1Q5puen84VVX+DlYy9zYOBFOlbO5nBuGfl16+k+O4+05CR91afpXNI5Yv8/uOd2emvnsG/3Ewz0n/2gfWBomLMH9zBcPY3lN2+YqI8jaZTaGwszx3XPbKWx/zXyNTmOF+k5IQshSSoxVfkcn17VQvfBd3nnpfdpmDmNlvbGyQ5LmjCdSztZPGMxj+x/hJUbWul7b4iXr/hDBgcSe2Y+xTXzrqGtsW3EvrMbplF/4x1U9Z3kx7t3f9D+k4OHWXTqdVpW30RN7fSJ+iiSRumDdwk1zCZOdLNk9RzqmmuKci4LIUkqQUvXzmHg10P0HPoVi69ucRiPKko+l2f76u28cfIN9lXvYVZrPe/890ka2qp4Jdf1oUkSRnLfXZvprmvnwDPfoe/MaQBe/NcfUMUwm+/8/ER8BElj1NbYRi5ydE+rhRM9bL5vBWtu6SjKuSyEJKkEtV0+k9qGagAWr/L5IFWeje0buarlKr720j+wfP1cAI50vEx9dT2b2zd/Yt+Fs+qovm4r9PexZ9eTDA8NMXjo3zk1azFti4rzhUrSpVFTVcP8+vn0VAWcPQl9x4t2LgshSSpBuaocl107l7qmGlqXNU92ONKEiwgeWvMQve/30tX8PLc8cAVPxzfZsmgLddUXn0Hxvq3r+HnD5Rx89hn+7Xu7qe0/zdzrNk1A5JLGq6Opg+7hvsLK8e6incdCSJJK1LrPL+V3vnQdVVX+V63KdM28a/hs22f5+qHH+EnuOfqG+i46LO6clQtmMLx6C0PDif07v8GpqgY2b1lf3IAlXRLtje309B8nAZywEJKkilOVz1FbXz3ZYUiTavua7ZzpP8PD+x5mUdMiVrWs+n/33XbrGl5qXAnAkbmrWDZvRrHClHQJdTR1cGawj3dzOTjRU7TzWAhJkqSSddnMy9i6ZCvDaZjOpZ2jmjhk3ZLZnFmxgf+YsYbWGzY56YhUJs7NHNdT31zUoXH5oh1ZkiTpEnhw9YOklLhz2Z2j6hcR3L/pSh44epY/utpJEqRyca4QOtzUwuoiDo2zEJIkSSVtbv1cvnzzl8fU97c+M4/vP3gTK+Y3XeKoJBVLa0Mr+cjTM73ByRIkSZLGIiK4snWGw+KkMpLP5VnQuIDufL7wjFBKRTmPhZAkSZKkktLe2E4PAzDYB+8dK8o5LIQkSZIklZSOpg56Bk4WptAu0vA4CyFJkiRJJaWjqYO+4QF6q6qK9i4hCyFJkiRJJaW9qR2Anuo8HD9clHNYCEmSJEkqKeem0O6un1m0l6o6fbYkSZKkkjKvbh7VuWp6Fq2By28ryjm8IyRJkiSppFTlqmhvbKe7vhkuu6Uo57AQkiRJklRy2pva6T7lC1UlSZIkVZCOpg6OnD7CcBouyvEthCRJkiSVnPamdvqH+3nnvXeKcnwLIUmSJEklp6MxmzmuSMPjLIQkSZIklZwP3iV0qjjTZ1sISZIkSSo5c+rmMD0/ne7T3hGSJEmSVCFykeOG+TfQWNNYlOP7QlVJkiRJJemRjY8U7djeEZIkSZJUcSyEJEmSJFUcCyFJkiRJFcdCSJIkSVLFGVchFBF/HBGHIuKViPh2RNRGxOKI2BsRv4iIJyOiJtt3Wrb+erZ90XnH+WLW/lpEbBnfR5IkSZKkTzbmQigiFgAPAmtTSiuBKuBu4CvAjpTSMuA4sC3rsg04nlJaCuzI9iMiVmT9rgRuBb4WEVVjjUuSJEmSLma8Q+PywPSIyAN1wNvARmBXtv1x4I5suTNbJ9u+KSIia38ipXQ2pfQG8Dpw7TjjkiRJkqQLGnMhlFL6H+DvgB4KBdBJYB9wIqU0mO32JrAgW14AHMn6Dmb7zz6/fYQ+HxIR90dEV0R0HTt2bKyhS5IkSapw4xkaN5PC3ZzFQCtQD/zmCLumc10usO1C7R9vTOnRlNLalNLalpaW0QctSZIkSYxvaNxm4I2U0rGU0gDwXWAd0JwNlQNoA97Klt8EFgJk22cA757fPkIfSZIkSbrkxlMI9QDXR0Rd9qzPJuA/gReAu7J97gWeypafztbJtv8wpZSy9ruzWeUWA8uAn44jLkmSJEn6RPmL7zKylNLeiNgF7AcGgQPAo8D3gSci4q+ztseyLo8B34yI1yncCbo7O86hiNhJoYgaBB5IKQ2NNS5JkiRJupgo3JQpP2vXrk1dXV2THYYkSZKkEhUR+1JKa0faNt7psyVJkiSp7FgISZIkSao4FkKSJEmSKo6FkCRJkqSKYyEkSZIkqeKU7axxEXEM6J7sOFSSPgX8crKD0JRjXqkYzCsVi7mlYijHvOpIKbWMtKFsCyHpQiKi60LTJEpjZV6pGMwrFYu5pWKYannl0DhJkiRJFcdCSJIkSVLFsRDSVPToZAegKcm8UjGYVyoWc0vFMKXyymeEJEmSJFUc7whJkiRJqjgWQiprEfH1iOiNiFfOa5sVEc9FxC+yvzMnM0aVn4hYGBEvRMSrEXEoIrZn7eaWxiwiaiPipxHxUpZXf5m1L46IvVlePRkRNZMdq8pPRFRFxIGIeCZbN680LhFxOCIORsTPIqIra5tS10ELIZW7bwC3fqTtz4HnU0rLgOezdWk0BoE/SSktB64HHoiIFZhbGp+zwMaU0tXAKuDWiLge+AqwI8ur48C2SYxR5Ws78Op56+aVLoUNKaVV502ZPaWugxZCKmsppR8D736kuRN4PFt+HLhjQoNS2UspvZ1S2p8tn6bw5WIB5pbGIRWcyVars38J2AjsytrNK41aRLQBnwP+MVsPzCsVx5S6DloIaSqam1J6GwpfaIE5kxyPylhELAJWA3sxtzRO2fClnwG9wHPAfwEnUkqD2S5vUgZjQy8AAAHXSURBVCi6pdH4KvBnwHC2PhvzSuOXgGcjYl9E3J+1TanrYH6yA5CkUhURDcB3gIdSSqcKP7JKY5dSGgJWRUQzsBtYPtJuExuVyllE3Ab0ppT2RcT6c80j7GpeabRuTCm9FRFzgOci4ueTHdCl5h0hTUVHI2I+QPa3d5LjURmKiGoKRdA/pZS+mzWbW7okUkongB9ReAatOSLO/TDZBrw1WXGpLN0I3B4Rh4EnKAyJ+yrmlcYppfRW9reXwg831zLFroMWQpqKngbuzZbvBZ6axFhUhrLx9Y8Br6aUHj5vk7mlMYuIluxOEBExHdhM4fmzF4C7st3MK41KSumLKaW2lNIi4G7ghyml38W80jhERH1ENJ5bBm4BXmGKXQd9oarKWkR8G1gPfAo4CnwJ+B6wE2gHeoDfTil9dEIF6YIi4iZgD3CQ/xtz/xcUnhMytzQmEXEVhYeLqyj8ELkzpfRXEfFpCr/kzwIOAL+XUjo7eZGqXGVD4/40pXSbeaXxyPJnd7aaB/45pfQ3ETGbKXQdtBCSJEmSVHEcGidJkiSp4lgISZIkSao4FkKSJEmSKo6FkCRJkqSKYyEkSZIkqeJYCEmSJEmqOBZCkiRJkiqOhZAkSZKkivO/gsbGJEbKEbEAAAAASUVORK5CYII=\n",
        "text/plain": [
         "<Figure size 1008x576 with 1 Axes>"
        ]
        "text/plain": [
         "<Figure size 1008x576 with 1 Axes>"
        ]
@@ -6918,22 +8320,24 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 116,
-   "metadata": {},
+   "execution_count": 110,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
        "text/plain": [
     "outputs": [
      {
       "data": {
        "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f547de478d0>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f9b6365e810>"
        ]
       },
        ]
       },
-     "execution_count": 116,
+     "execution_count": 110,
       "metadata": {},
       "output_type": "execute_result"
      },
      {
       "data": {
       "metadata": {},
       "output_type": "execute_result"
      },
      {
       "data": {
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\n",
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\n",
        "text/plain": [
         "<Figure size 720x576 with 1 Axes>"
        ]
        "text/plain": [
         "<Figure size 720x576 with 1 Axes>"
        ]
@@ -6950,22 +8354,24 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 117,
-   "metadata": {},
+   "execution_count": 111,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
        "text/plain": [
     "outputs": [
      {
       "data": {
        "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f54846e9f90>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f9b5d211050>"
        ]
       },
        ]
       },
-     "execution_count": 117,
+     "execution_count": 111,
       "metadata": {},
       "output_type": "execute_result"
      },
      {
       "data": {
       "metadata": {},
       "output_type": "execute_result"
      },
      {
       "data": {
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\n",
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\n",
        "text/plain": [
         "<Figure size 432x288 with 1 Axes>"
        ]
        "text/plain": [
         "<Figure size 432x288 with 1 Axes>"
        ]
@@ -6982,12 +8388,14 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 118,
-   "metadata": {},
+   "execution_count": 137,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
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\n",
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\n",
        "text/plain": [
         "<Figure size 720x720 with 1 Axes>"
        ]
        "text/plain": [
         "<Figure size 720x720 with 1 Axes>"
        ]
@@ -7001,27 +8409,29 @@
     "source": [
      "# Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#\n",
      "\n",
     "source": [
      "# Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#\n",
      "\n",
+    "dhna = deaths_headlines.dropna()\n",
+    "\n",
      "fig = plt.figure(figsize=(10, 10))\n",
      "ax = fig.add_subplot(111, projection=\"polar\")\n",
      "\n",
      "theta = np.roll(\n",
      "    np.flip(\n",
      "fig = plt.figure(figsize=(10, 10))\n",
      "ax = fig.add_subplot(111, projection=\"polar\")\n",
      "\n",
      "theta = np.roll(\n",
      "    np.flip(\n",
-    "        np.arange(len(deaths_headlines))/float(len(deaths_headlines))*2.*np.pi),\n",
+    "        np.arange(len(dhna))/float(len(dhna))*2.*np.pi),\n",
      "    14)\n",
      "# l15, = ax.plot(theta, deaths_headlines['total_2015'], color=\"#b56363\", label=\"2015\") # 0\n",
      "# l16, = ax.plot(theta, deaths_headlines['total_2016'], color=\"#a4b563\", label=\"2016\") # 72\n",
      "# l17, = ax.plot(theta, deaths_headlines['total_2017'], color=\"#63b584\", label=\"2017\") # 144\n",
      "# l18, = ax.plot(theta, deaths_headlines['total_2018'], color=\"#6384b5\", label=\"2018\") # 216\n",
      "# l19, = ax.plot(theta, deaths_headlines['total_2019'], color=\"#a4635b\", label=\"2019\") # 288\n",
      "    14)\n",
      "# l15, = ax.plot(theta, deaths_headlines['total_2015'], color=\"#b56363\", label=\"2015\") # 0\n",
      "# l16, = ax.plot(theta, deaths_headlines['total_2016'], color=\"#a4b563\", label=\"2016\") # 72\n",
      "# l17, = ax.plot(theta, deaths_headlines['total_2017'], color=\"#63b584\", label=\"2017\") # 144\n",
      "# l18, = ax.plot(theta, deaths_headlines['total_2018'], color=\"#6384b5\", label=\"2018\") # 216\n",
      "# l19, = ax.plot(theta, deaths_headlines['total_2019'], color=\"#a4635b\", label=\"2019\") # 288\n",
-    "l15, = ax.plot(theta, deaths_headlines['total_2015'], color=\"#e47d7d\", label=\"2015\") # 0\n",
-    "l16, = ax.plot(theta, deaths_headlines['total_2016'], color=\"#afc169\", label=\"2016\") # 72 , d0e47d\n",
-    "l17, = ax.plot(theta, deaths_headlines['total_2017'], color=\"#7de4a6\", label=\"2017\") # 144\n",
-    "l18, = ax.plot(theta, deaths_headlines['total_2018'], color=\"#7da6e4\", label=\"2018\") # 216\n",
-    "l19, = ax.plot(theta, deaths_headlines['total_2019'], color=\"#d07de4\", label=\"2019\") # 288\n",
+    "l15, = ax.plot(theta, dhna['total_2015'], color=\"#e47d7d\", label=\"2015\") # 0\n",
+    "l16, = ax.plot(theta, dhna['total_2016'], color=\"#afc169\", label=\"2016\") # 72 , d0e47d\n",
+    "l17, = ax.plot(theta, dhna['total_2017'], color=\"#7de4a6\", label=\"2017\") # 144\n",
+    "l18, = ax.plot(theta, dhna['total_2018'], color=\"#7da6e4\", label=\"2018\") # 216\n",
+    "l19, = ax.plot(theta, dhna['total_2019'], color=\"#d07de4\", label=\"2019\") # 288\n",
      "\n",
      "\n",
-    "lmean, = ax.plot(theta, deaths_headlines['previous_mean'], color=\"black\", linestyle='dashed', label=\"mean\")\n",
+    "lmean, = ax.plot(theta, dhna['previous_mean'], color=\"black\", linestyle='dashed', label=\"mean\")\n",
      "\n",
      "\n",
-    "l20, = ax.plot(theta, deaths_headlines['total_2020'], color=\"red\", label=\"2020\")\n",
+    "l20, = ax.plot(theta, dhna['total_2020'], color=\"red\", label=\"2020\")\n",
      "\n",
      "# deaths_headlines.total_2019.plot(ax=ax)\n",
      "\n",
      "\n",
      "# deaths_headlines.total_2019.plot(ax=ax)\n",
      "\n",
@@ -7035,7 +8445,7 @@
      "\n",
      "\n",
      "ax.set_xticks(theta)\n",
      "\n",
      "\n",
      "ax.set_xticks(theta)\n",
-    "ax.set_xticklabels(deaths_headlines.index)\n",
+    "ax.set_xticklabels(dhna.index)\n",
      "plt.legend()\n",
      "plt.title(\"Deaths by week over years, all UK\")\n",
      "plt.savefig('deaths-radar.png')\n",
      "plt.legend()\n",
      "plt.title(\"Deaths by week over years, all UK\")\n",
      "plt.savefig('deaths-radar.png')\n",
@@ -7044,15 +8454,19 @@
    },
    {
     "cell_type": "markdown",
    },
    {
     "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "Collapsed": "false"
+   },
     "source": [
      "# Excess deaths calculation"
     ]
    },
    {
     "cell_type": "code",
     "source": [
      "# Excess deaths calculation"
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 119,
-   "metadata": {},
+   "execution_count": 113,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "# raw_data_2020.loc[12, 'Week ended']"
     "outputs": [],
     "source": [
      "# raw_data_2020.loc[12, 'Week ended']"
@@ -7060,8 +8474,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 120,
-   "metadata": {},
+   "execution_count": 114,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
@@ -7069,7 +8485,7 @@
         "Timestamp('2020-03-20 00:00:00')"
        ]
       },
         "Timestamp('2020-03-20 00:00:00')"
        ]
       },
-     "execution_count": 120,
+     "execution_count": 114,
       "metadata": {},
       "output_type": "execute_result"
      }
       "metadata": {},
       "output_type": "execute_result"
      }
@@ -7080,8 +8496,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 121,
-   "metadata": {},
+   "execution_count": 115,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "# raw_data_2020.iloc[-1]['Week ended']"
     "outputs": [],
     "source": [
      "# raw_data_2020.iloc[-1]['Week ended']"
@@ -7089,16 +8507,18 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 122,
-   "metadata": {},
+   "execution_count": 116,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
        "text/plain": [
     "outputs": [
      {
       "data": {
        "text/plain": [
-       "31"
+       "53"
        ]
       },
        ]
       },
-     "execution_count": 122,
+     "execution_count": 116,
       "metadata": {},
       "output_type": "execute_result"
      }
       "metadata": {},
       "output_type": "execute_result"
      }
@@ -7109,16 +8529,18 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 123,
-   "metadata": {},
+   "execution_count": 117,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
        "text/plain": [
     "outputs": [
      {
       "data": {
        "text/plain": [
-       "Timestamp('2020-07-31 00:00:00')"
+       "Timestamp('2021-01-01 00:00:00')"
        ]
       },
        ]
       },
-     "execution_count": 123,
+     "execution_count": 117,
       "metadata": {},
       "output_type": "execute_result"
      }
       "metadata": {},
       "output_type": "execute_result"
      }
@@ -7129,8 +8551,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 124,
-   "metadata": {},
+   "execution_count": 118,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
@@ -7138,7 +8562,7 @@
         "Timestamp('2020-07-03 00:00:00')"
        ]
       },
         "Timestamp('2020-07-03 00:00:00')"
        ]
       },
-     "execution_count": 124,
+     "execution_count": 118,
       "metadata": {},
       "output_type": "execute_result"
      }
       "metadata": {},
       "output_type": "execute_result"
      }
@@ -7149,8 +8573,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 125,
-   "metadata": {},
+   "execution_count": 119,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "# raw_data_2020.loc[12].droplevel(1)['Week ended']"
     "outputs": [],
     "source": [
      "# raw_data_2020.loc[12].droplevel(1)['Week ended']"
@@ -7158,8 +8584,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 126,
-   "metadata": {},
+   "execution_count": 120,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "# raw_data_2020.iloc[-1].droplevel(1)['Week ended']"
     "outputs": [],
     "source": [
      "# raw_data_2020.iloc[-1].droplevel(1)['Week ended']"
@@ -7167,16 +8595,18 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 127,
-   "metadata": {},
+   "execution_count": 121,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
        "text/plain": [
     "outputs": [
      {
       "data": {
        "text/plain": [
-       "63702.6"
+       "86082.0"
        ]
       },
        ]
       },
-     "execution_count": 127,
+     "execution_count": 121,
       "metadata": {},
       "output_type": "execute_result"
      }
       "metadata": {},
       "output_type": "execute_result"
      }
@@ -7187,8 +8617,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 128,
-   "metadata": {},
+   "execution_count": 122,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
@@ -7196,7 +8628,7 @@
         "64733.6"
        ]
       },
         "64733.6"
        ]
       },
-     "execution_count": 128,
+     "execution_count": 122,
       "metadata": {},
       "output_type": "execute_result"
      }
       "metadata": {},
       "output_type": "execute_result"
      }
@@ -7207,16 +8639,18 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 129,
-   "metadata": {},
+   "execution_count": 123,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
        "text/plain": [
     "outputs": [
      {
       "data": {
        "text/plain": [
-       "604473.3999999999"
+       "618343.6"
        ]
       },
        ]
       },
-     "execution_count": 129,
+     "execution_count": 123,
       "metadata": {},
       "output_type": "execute_result"
      }
       "metadata": {},
       "output_type": "execute_result"
      }
@@ -7227,8 +8661,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 130,
-   "metadata": {},
+   "execution_count": 124,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "# excess_death_data = {\n",
     "outputs": [],
     "source": [
      "# excess_death_data = {\n",
@@ -7243,24 +8679,28 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 131,
-   "metadata": {},
+   "execution_count": 125,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
     "outputs": [],
     "source": [
-    "excess_death_data = {\n",
-    "    'start_date': str(eng_xls.loc[12, 'Week ended']),\n",
-    "    'end_date': str(eng_xls.loc[27, 'Week ended']),\n",
-    "    'excess_deaths': (deaths_headlines.loc[12:27].total_2020 - deaths_headlines.loc[12:27].previous_mean).sum()\n",
-    "}\n",
+    "# excess_death_data = {\n",
+    "#     'start_date': str(eng_xls.loc[12, 'Week ended']),\n",
+    "#     'end_date': str(eng_xls.loc[27, 'Week ended']),\n",
+    "#     'excess_deaths': (deaths_headlines.loc[12:27].total_2020 - deaths_headlines.loc[12:27].previous_mean).sum()\n",
+    "# }\n",
      "\n",
      "\n",
-    "with open('excess_deaths.json', 'w') as f:\n",
-    "    json.dump(excess_death_data, f)"
+    "# with open('excess_deaths.json', 'w') as f:\n",
+    "#     json.dump(excess_death_data, f)"
     ]
    },
    {
     "cell_type": "code",
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 132,
-   "metadata": {},
+   "execution_count": 126,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "# excess_death_data = {\n",
     "outputs": [],
     "source": [
      "# excess_death_data = {\n",
@@ -7275,8 +8715,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 133,
-   "metadata": {},
+   "execution_count": 127,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
@@ -7338,7 +8780,7 @@
         "Name: Week ended, dtype: object"
        ]
       },
         "Name: Week ended, dtype: object"
        ]
       },
-     "execution_count": 133,
+     "execution_count": 127,
       "metadata": {},
       "output_type": "execute_result"
      }
       "metadata": {},
       "output_type": "execute_result"
      }
@@ -7349,8 +8791,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 134,
-   "metadata": {},
+   "execution_count": 128,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "# raw_data_2020.droplevel(1, axis='columns')['Week ended']"
     "outputs": [],
     "source": [
      "# raw_data_2020.droplevel(1, axis='columns')['Week ended']"
@@ -7358,8 +8802,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 135,
-   "metadata": {},
+   "execution_count": 129,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "deaths_by_week = deaths_headlines.merge(eng_xls['Week ended'], left_index=True, right_index=True)\n",
     "outputs": [],
     "source": [
      "deaths_by_week = deaths_headlines.merge(eng_xls['Week ended'], left_index=True, right_index=True)\n",
@@ -7369,8 +8815,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 136,
-   "metadata": {},
+   "execution_count": 130,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "# deaths_by_week = deaths_headlines.merge(raw_data_2020.droplevel(1, axis='columns')['Week ended'], left_index=True, right_index=True)\n",
     "outputs": [],
     "source": [
      "# deaths_by_week = deaths_headlines.merge(raw_data_2020.droplevel(1, axis='columns')['Week ended'], left_index=True, right_index=True)\n",
@@ -7380,19 +8828,23 @@
    },
    {
     "cell_type": "markdown",
    },
    {
     "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "Collapsed": "false"
+   },
     "source": [
      "# Plots for UK nations"
     ]
    },
    {
     "cell_type": "code",
     "source": [
      "# Plots for UK nations"
     ]
    },
    {
     "cell_type": "code",
-   "execution_count": 137,
-   "metadata": {},
+   "execution_count": 131,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
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\n",
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RaIRGowEAOJ1ONDc3o6Wl5ZKfgX2bzeapqqpylJeXOysqKrxms5mSk5Pdbre7XSKR1BFRpcvlKq2vry92uVyV8ImvKgDV3DvG4XB6gwsrDqcf+L0xIsZYc6c6Us+H2ayg4W+FkgYgU6lUjouNjZ3kdruzRCKRYsyYMaKUlBSYTCZpampqVFJSksxgMCAxMRGJiYmIi4vDiRMnkJ6ejri4uLDY7/V6IRL9ey2OTCaDTCZDfHx8T28RA4j1bx14PB7U1taaqqurJ1dXV6OqqopVVFQ4ysrK2ioqKjwXL16kxMREl0QiqWKMnbVYLEfb29sL4WuAXckY83Y32XDDn+P1DXyfya3htofDERIurDic/tFTHalFAN4AkADgYyI6yRibH0Y7e4SIRABMADKjoqKy1Wr1dYyxbK/Xq83IyJBmZWVh/PjxUTk5OdGZmZnIyMhAbGxsX8MC8AmZtra2sAqrYHi/xGJxh2D0QwCi/RsAgDGG6upqw7lz564rKiq659SpU80nT54UVVVVuRMTE1ukUmmZy+U6ZTabjzHGzgEoZIxZh2zc1cUjAAoAhOeC4HDCCK9jxeFcg/hFVDqAyYmJiXOJaLpIJEpIS0vDhAkT5GPHjo3NysqizMxMJCQkDHlVY3FxMWQyGZKTk4Ni/0A5evQoRo8ejZiYmLDMf+zYMWRkZCAqKgplZWU4d+4cCgoKXKdOnWo6efKk12KxuKRSaXFzc/OXjY2NBwAcY4zVh8XYEENESfA1o34RwGPcY8UZbnCPFYdzleMXUZlENFmv188DMC0pKSk+KyuLcnNzY6dNmyafNGlSb2GxISOTydDe3h6y8fsiWB6rwdLS0oLo6GiIxWKkp6cjPT0dCxYskALQBOwrLi42HDt2bPb+/fttBw4ccCYmJnokEkmJ3W7/wmq1BsRWXdhOIni8BuBJdAmzcoTh2LFjWolE8g6AHAy/WpVeAHlut/vHkydPrg2XEVxYcThXGUQUDyA3MTFxIYDrk5OTNenp6ZHTpk2TzZs3L2LSpElQq9WC2iSTydDU1CTonJ3pmmMlJIwxMMZ6FXYikQiZmZnIzMzEXXfdpQB8NpeUlCQeO3Zspl9stev1eo9UKi2x2+2fWa3W/wfgG8ZY+BTrACGiWwHUMsaOEdGccNszHJFIJO/o9frRCQkJVpFINKxCUl6vlywWS3ZNTc07AG4Llx1cWHE4Vzh+ITXbaDQu8ng8s8aOHRu1cOHCqHnz5kVPnjwZKpUKNTU1sFqtGD16dFhslMlkcDqdYZkbCK+wcjqdkMlkA36fSCRCRkYGMjIysGzZsg6xdf78ef2RI0dm/POf/3xw//79XqPRWNna2vp3q9W6G1e+0LoBwG1EtACAHEAcEb3HGLsnzHYNJ3KGo6gCAJFIxBISEmw1NTU54bSDCysO5wojIKQMBsMir9c7a+zYsVELFiyInD9/fsz111+PyMjIy96jVCpx/vx54Y31E25h5fF4wias7HZ70HK7RCJRIJRIy5cv1wBAZWVlwpdffjn+448/fmD//v3epKSkSofDsauT0Lpiyj8wxp4G8DQA+D1Wj3NRJTii4SiqAvjPPawhUC6sOFcNPTRBVgP4E4BUAGUA7rjaVmD560TN83ukZufk5FwipKKiovocQy6Xw+l0gjEWlvY6ERERYc+xCpewCuRXhQqj0Yjly5d3J7QePHDggDcpKamyvb39nxaLZReAo7zkAyfcFBcXS5cvXz7CYrFIRSIRVqxYYVm3bl2t2WwWL1q0aGRlZaXMaDQ6d+7ceT4hIcFz4sQJ+cqVK1Pz8/OjVq9eXfn888+bA2MZjcax0dHRHpFIBIlEwvLy8grCeW79gQsrztXGjV0SfFcD+Iwx9hIRrfY/fio8pvUfIjLFxMQsjouL+2F6errx9ttvj7zlllv6LaS6Izo6Oqjek4EgEokQ7hXG4erX2NLSgoSEBMHm6yq0iouLE/74xz9OOH369KqDBw96kpKSDlZWVv4ewKeMMbtghnWBMfYlgC/DNT8nfEilUrzyyisXZ86c6bBaraKJEydmL1iwoOntt9+OnzNnTvOmTZu+XbNmjX79+vX6zZs3V2q1Wvfrr79esX37dlV34+3du/dcYmLiVdMZgQsrztXO9wDM8e+/C98f8itOWPlX7l2XkJBwt1gs/t60adOily9frvze974nTUlJCcocKpUKVqs1bCUHAITNYxZOWlpaMGLEiLDNL5VKcc899yAtLU3j8Xhw5MiR2//85z/P3bVrlzMpKem81Wr9g8Ph2BHoHMDhhBqTyeQymUwuAFCpVN60tLTWioqKiN27dyv37t1bBACrVq2qz83NzQJQaTQa3Uaj0b1z505lWA0PElxYca4mumuCrGOMVQMAY6za38fvioCIouAL8d2r1+tvmDFjhuSuu+5Sz58/n/pbeHMgqFQqVFdXh62WlFQqhcvlQkRERFjmDxetra3d5r0JRW1tLbKysgD4CpzOmDEDM2bMiHvttddQXFycsGPHjgnvv//+cwaDwdbe3r69vr7+QwCnWbhdjJxhQVFRUUR+fn5Ubm5uS319vSQguEwmk6uhoaFfGmTevHkZRISVK1daHn/88Su+JAkXVpyricuaIIfboK4QkSoyMnKpWq1emZqamnbbbbfJli5dGjd9+vSQ11lSKBQoKAhf+kEggX04CSuv15fOFC4vHWMMLS0tPVbIT09Px+OPPy57/PHHE6xWa8K//vWvp957770fHz9+3GU0Gr+oqqraBmAvY8wjrOUcIbB+9FGyq7Z2cLkFPSDVah2qRYsu9Oe1NptNtHjx4rSXXnrpglqtHlTu34EDBwpTU1NdlZWVkrlz52aOGTOm7ZZbbmkZzFhCwYUV56qhhybIZiJK9HurEgEIXhSOiOQikWhhcnLyU2lpaSPvu+++qKVLl0ZmZGQIaodUKoXH4wlbIndAWIXCG3el0traOuicuGDQ2NgIhULRL2GnUqlw991309133x3vcrmwb9++u3//+9/fsmfPHqder99lNps3AzjFPVmcYOB0OmnhwoVpS5cubVixYkUjAGg0Gnd5ebnUZDK5ysvLpWq1us+8qdTUVBcAGI1G98KFCxsPHToUzYUVhxMEemmCvAvACgAv+X/uFMgeEXwlER42Go2zlixZIl+wYEFsamoqMjMzhTChWxQKBZqamqBUCp+qEO6SC+GgpaUlrDlttbW10GoHHv2WSqWYN28e5s2bp3I6nfjXv/71k7feemvxmTNn7Gq1+l2r1bqNMVYRApM5AtJfz1Kw8Xq9WLZsmSkzM7Ptueee61jhN3/+/MYtW7ZoNm3aVLNlyxbNzTff3NjbOE1NTSKPxwOVSuVtamoSffHFF3Fr16694nMFubDiXC301AT5KIA/E9GPAFQAWBpKI4horFarvV+v199+4403ylatWqWeNWsWRCIRXC4XDh48GFZhpVQqYbVah5Ww8nq9YV0RGE5hZbFYkJqaOqQxZDIZbr/9drr99tvjbTZb/F/+8pc1mzdvvt9gMNTabLa3HA7HB1dbCRNOeNmzZ0/Mjh07NBkZGa2jRo3KBoANGzZUbtiwoXrRokVpJpMp3mAwtO/YsaMEACoqKiRTpkzJttvtYiJiW7Zs0RUUFOTV1NRIFi1alA4AHo+Hvv/979cvWbIkfC0e+glvwszh9AERJalUqvtkMtnKMWPGxDzwwAOahQsXUnfVtg8fPoycnJyw3WwbGxtx/vx5TJo0SfC5w1X93e124/Dhw5g5c6ag8wLAqVOnkJycLHgLIQBwuVw4dOgQZs+eHZLxL168iPfee69t27Ztza2trYVms/nXbrf7H4yxtpBMOES6q3MXXovCw6lTp8rGjx9/xSd4h5JTp07Fjx8/PjVc83OPFYfTDUQklUgkt2m12jUTJkxIvv/++1VLly6VqFTdllnpwGg0orKysmOVltDExcWFrWdfOD1W4SwOGi4RXVdXF9LG2klJSVi9erV89erV8ry8vIRt27ZN+Mtf/tJmMBj+VV1d/UvG2NmQTT54uta543AEZ7h1vuZweoWITFqt9lW9Xn/h/vvv/+2XX3456cSJEwk//elP+xRVAKDX61FTUyOApd0jEokgFovhcgnf5SRQ/V1owtnOJpzlJSwWi2CFSXNycvDqq6/GlpeXJ2zduvUHs2fP/tJgMJyNjIxcQURyQYzgcK4SuLDiDHuISCwWixcajcbD48ePP/rqq68+XFZWpvv1r38dN9CVfVKpFHK5PGxeI8CXZ2Wz2QSfNyIiYlh5rNxud8hLaPRGQ0OD4CFIsViMW2+9lfbu3Rt/5MiR7B/84AdbDQZDpV6vf5uI0gU15nICde6OEdFPw2wLZxjDhRVn2EJEKrVavVan05Xfe++97+3Zs2fayZMnE5YvXy7uLn+qvxiNRlRVhW/hSiCBXWjEYnFHXSch8Xg8YRE4drs9pD0C+5pbLpeHVdglJibirrvuiigrK1O/9dZb902ZMuWgwWA4IhaLb/GvmhWaGxhjkwDcAuBBIgpN8hmH0wdcWHGGHUQ0zmAw/CU1NfXcs88+u+7cuXPGbdu2KbOzs4MyfiAcGK6FIYHWNsOFcHmswplfJWQYsCcqKythNBohlUqxePFi0ddff53w6aefTv3hD3/4vl6vL1epVE8RkWDLUzvXuQMQqHPH4QgOT17nDAuIiEQi0XytVvvfs2fPNjzzzDPxN910U0iW6UskEkRHR6O5uRlxcXFBH78vAs2Yw4FEIoHb7YZE0vOfFq/XC7fbfdnGGANjDF6vt9t9wFfhXCQSXfLTbrfD6XTCYrFAIpFctoWqFENvFc9DTW1treCrL7tSXl6OqVMv1S7Z2dn43e9+p7TZbMpt27Zt+PWvf/2LxMTE3TU1NesYY+WhsqWXOnccjuBwYcW5piEisUwmW6rT6V6YO3euesOGDSohKqIbDAZUVlaGRVgREWQyGdra2iCXhzav2Ov1wul0dmwejwdFRUUAgLa2NrS3t6O9vf0S7x0RdYgeqVQKiUQCsVjcrWjqvA/4wn4BERYQXS0tLXA6nTCbzd0Kts6IxWJERERAJpP1uEml0n6JMbvdDr1eH8RPs394vV7Y7faw1s+yWq2IjIzs8fpSKBR47LHHZI8++mjCzp07l69du/YWg8FwqLq6ejVjLD8EJnVb5y4E83D6QXFxsXT58uUjLBaLVCQSYcWKFZZ169bVms1m8aJFi0ZWVlbKjEajc+fOnecTEhI8J06ckK9cuTI1Pz8/avXq1ZXPP/98R1HRuro68T333GMqKiqKJCJs3bq17KabbgrPf479hAsrzjUJEcliY2Pv0+l0T3//+99XrFmzJs5oNAo2v06nw7fffotRo0aFpXhlIByYmJg4pHE8Hg9aW1vhcDjgcDgu2fd4PB0iLrAFViVqNJqO5yIiIkL6GZjNZtTX16M/oVyPx3OJEHQ6nbDb7bBarXA6nWhra+tYUSmTyRAVFYXIyEhERUV17MvlchARWlpawpJj1djYCKVSGbaiqIDPW9WfwqQikQiLFi0S3X777fGff/75d59++unpBoOhoLq6+nHG2NfBsocxdh7A+GCNxxkaUqkUr7zyysWZM2c6rFaraOLEidkLFixoevvtt+PnzJnTvGnTpm/XrFmjX79+vX7z5s2VWq3W/frrr1ds3779sqXXP/3pT5O/853vNO3evft8W1sbtbS0XPEpTFxYcQYFEYkBfAOgkjF2KxHNBfAygAgAxwD8iDHWZx+oENgVo9FoHk1MTHz43nvvjf7FL34RrdFohDYDEokEMTExsNlsYamCPhBhxRhDe3s7mpub0dLS0vGzra0NYrH4EmGhUqlgNBoRFRXVbbivqKgIsbGxgub/eL3efidxi8XijnPpDcYYnE7nJWKyvr4era2taGvz1cd0OBwoLi5GTEwMYmNjERMTI0gyucViGVQbm2DhcrnQ2NiI8eP7r2OICPPmzcPXX38df/To0VlPP/30Pw0GQ0V1dfUTAD7n/QmvLUwmk8tkMrkAQKVSedPS0lorKioidu/erdy7d28RAKxatao+Nzc3C0Cl0Wh0G41G986dOy/5Y9nQ0CA6cuRI7Pbt28sAQC6XM7lcfsU3DOfCijNYHgFQACDOvwLoXQDzGKXcfbUAACAASURBVGPniOh5+Pr2bRPKGCJSx8fHrzYajStWrVqlmDFjhmzevHlCTd8tBoMBVVVVYRFWSqUS58+fv+x5t9uNpqYm2Gw22Gw2NDc3w+12QyaTdYiDxMRExMTEQCaTDdgrEo4ioaFIXiciyOXyHkNdra2tOHr0KBQKBZqbm1FbW4uWlhZ4PB7I5XLExcVBqVRCoVAgOjo6qN6lYLSxGQoXL15EUlLSoM9pypQp+PTTTzUFBQWadevW/eXAgQO1MplsbXt7+0eMMeGXlXJCSlFRUUR+fn5Ubm5uS319vSQguEwmk6uhoaFXDVJYWChTq9XupUuXpubn50eNGzfO/vbbb1+Ii4u7oq8TLqw4A4aIkgAsBPAigMcAaAA4GWPn/C/ZA+BpCCCsiMio0+meM5lMt69Zs0axYsUKqUwmw5EjR2C1WtGfop6hQqfToaioCKNHjxY8bCOXy9HW1gaLxYKmpiY0NjaiubkZIpEIcXFxUCgUSElJQWxsLKRSadDmlclkgtfwCkeB0NbWVigUCiQmJl7iFWSMoa2treMzr6yshN1uh1QqhUKh6BBbMTExg7LZ5XLB6/ViKOVAhgJjDBUVFbj++uuHPNbo0aOxfft2VXl5uWrjxo3b/vGPf7wSExOz0W63/4ExJnyF22uQ40X/l9zkqOrdPTtA4qIMjklZP+hXc2ebzSZavHhx2ksvvXRBrVYPWAy53W4qKCiIev311yvmzp1rX7lyZfK6dev0r7/++hXdiJkLK85geA3AkwACS6LqAEiJ6DrG2DcAlgBIDqUBRBSv1Wo3paenL9q4caNq6dKl4s5hmIyMDHz77beXrVoSErFYjLi4ODQ2NoZc4DHGYLfb0dDQgIaGBjQ2NqKtrQ0VFRVISEhAeno6YmNjQy5AAknzQjKQUGCw6KnUAhEhMjISkZGR0Ol0Hc+3t7d3eAm//fZbNDc3QyqVQq1Wd2z9EbihbmPTF1artcObGSxMJhPeeecdRW1treKXv/zla++9995z0dHRTzscjve5B+vqxel00sKFC9OWLl3asGLFikYA0Gg07vLycqnJZHKVl5dL1Wp1r+kiqamp7Tqdrn3u3Ll2ALjzzjutL730kvArRgYIF1acAUFEtwKoZYwdI6I5AMAYY0S0DMCrRCQD8AmAkORXEVG0RqNZm5yc/JMXXnhBuXz5ckl3N1W1Wt0R9grHyrwAgXBgsIWV1+tFY2Njh5Cy2+2IioqCRqNBSkoKxo4di/Pnz0MulyM5OaQa9xLCEQr0eDxB9br1h5aWFgwkdy8iIgIJCQmX5J45nU40NDSgrq4O586dg9frhVKp7BBaUVFRl3k6a2trIeQijK6UlpaGLAyp1Wrx8ssvxzz55JMxzzzzzG927dr1rFgsfsjr9X7Cc7AGR389S8HG6/Vi2bJlpszMzLbnnnuuY4Xf/PnzG7ds2aLZtGlTzZYtWzQ333xzY2/jpKSkuPV6ffupU6dk48ePd37yySdxWVlZV2QT8M5wYcUZKDcAuI2IFgCQw5dj9R5j7B4AswCAiL4DIDOYkxKRVKFQPKTX65964oknlA8++KCsr/+aMzIyUFxcjEmTJgXTlAGh1WpRWFiI7OzsIYUDGWNobm6GxWJBbW0tnE5nx004Ozu72zwelUqF6urqa15YhaNAaEtLC0wm05DGkMlkl4QSPR5Ph1jOy8uDw+GAUqmEVqtFfHw8ZDIZrFYrxo4dG4xTGDCBBQ6hbqOj1WqxdevWuDVr1sQ99thjHxw6dKiciFYFcxUhJ7Ts2bMnZseOHZqMjIzWUaNGZQPAhg0bKjds2FC9aNGiNJPJFG8wGNp37NhRAgAVFRWSKVOmZNvtdjERsS1btugKCgry1Gq194033qhYvnz5yPb2dkpJSXF+8MEHZeE8t/7AhRVnQDDGnoYvfwp+j9XjjLF7iEjLGKv1e6yegi//asgQkSgyMvIunU730o9+9CPV6tWro/tblDE+Ph6FhYVwOBx9rgILFWKxGAqFAlardcA3pNbWVlgslo48qcBqu/Hjx/frfBQKBQoKCgZr+qCQSCTweIRdtBOOUGAorqlAmYqAJyzglbRYLCgtLYXL5YLb7UZdXR00Go3g53zhwgWkpKQIli+YmpqKv/3tb6rTp0+rHn744X8lJiaeqqmpeYAxViiIAZxBM3/+/BbG2LHujh06dOhc1+dSUlLcZrP5dHevnzFjRmteXp6wf8iGCBdWnGDxhD9MKAKwmTH2+VAG81dK/w+dTveb2267LeGFF15QDHSJOREhPT0dxcXFGDdu3FDMGRJGoxGVlZV9CivGGBoaGlBTUwOLxdIRPkpLS4NCoRjwDU0qlcLj8YSt5YtQCJ283rkKfCgRiUQdYcGsrCyUlJSgubkZZrMZ+fn5iIiIgF6vh16vD/k/DowxXLhwATfccENI5+mOcePGYe/eveqvvvrqxoceemi/wWD4srq6+hHGWKXgxnA4/YALK86gYYx9CeBL//4TAJ4IxrhENFWn0/3vjBkzUl955RXViBEjBj2WXq/HuXPnBKlC3hMJCQnIz88HY+yym7Hb7YbFYkF1dTVsNhtUKhX0ej2ysrJ6bQvTXxQKBZqamgQt+SASiQRtjCy0cGxtbUVkZKRg8wWor6/H6NGjO9roOBwO1NTU4OTJk3C5XNDpdNDr9YMS4X1RV1cHhUIheC5bZ2bNmoWTJ09qXn311cVvvfXWXJ1O92Ftbe1axtjwaYzJuSrgwopzxUBESXq9ftusWbMmv/nmm5pgeJmICCNHjkRJSQnGjBkTBCsHjkgkglKpRENDAzQaDZxOJ6qrq1FTU4O2tjZotVqkpqZCpVIF/YaoVCphtVoFFVaBPCuhwq9ChwLD0Xy5uzY2UVFRGDlyJEaOHAmXy4Xa2lqUlJSgqakJarUaiYmJiI+PD4roLCsrQ3p6+pDHGSqNjY2YPn06PfLII6p33333x88+++wSjUbzSkNDwythKkisBPAOgBwADMB9jLFDQtvBubLgwooTdogoQqPRrBkxYsSDmzdvVs+fPz+o7gej0YiSkhK0t7cjIiIimEP3G51Oh8LCQhARPB4PDAYDxo4dG/KWKCqVCqWlpSGdoyvhEFZCeqzCIaz6amMjlUphNBphNBrh9XrR0NCA6upqnD17Fmq1GkajERqNZlDCva2tDa2trWEpdNsZxhjy8/ORk5MDsViM++67T3rXXXclbNy4cd22bdt+SkQrGWP7BDbrdQC7GWNLiCgCQHiSOTlXFFxYccJKRETEd7Ra7dsPPfRQ/JNPPhkVisKHIpEIqampKC0tRVZWVtDH7wm3242amhpUVlZ23JxmzZolaH+5uLg42Gw2weYDhF8ZKHSOVUtLi+AlD2pra/vdxkYkEiE+Ph7x8fFgjKG+vh6VlZU4c+YM4uPjYTQaB+QdraioEDRpvSfMZjOioqKgUCg6nouMjMSmTZuif/SjH4287777PtLr9QfNZvNPGWPVobaHiOIAzAZwLwAwxtoBtId6Xs6Vz7Wb0cq5oiGiZL1e/+ncuXM/PHr0aMq6detCIqoCJCcno6qqCm53aKMFXq8XNTU1OHr0KPbv34+WlhZkZ2cjNzcXer0era2tIZ2/K4GmyIHGwkIgtLASOhRot9sFb75ssVgG1X+RiBAfH4/x48cjNzcXWq0WZWVl+PLLL5Gfn4/m5uZe388YQ2VlJZKSkgZrelDwer0oLCzEqFGjuj2elpaGvXv3qrdu3bogJSXllFqtXk1EoXYcjARgAfA7IjpBRO8QkfBduTlXHFxYcQSFiCLi4+OfT01NPf7uu+/euHv3blVKSkrI5xWLxUhOTkZ5eXlIxm9ubsbZs2exd+9e1NXVITMzE7m5uRg1alRHsnFgdaDQKJVKQb1W4RBWQnqsnE6noC1lXC4XGGNDDmOLRCLodDpMmjQJs2fPhlKpxNmzZ7F//36Ul5d3K75ra2uhVquDspBiKFRUVECn0/W5aOC2224TFRYWJvzsZz97RqvVFkkkktkhNEsCYBJ8q6AnArADWB3C+a4aiouLpdOmTcscOXLkmPT09DEbN27UAoDZbBbPmDEjw2Qy5cyYMSPDYrGIAeDEiRPyCRMmjIqIiJi0fv36jpYFp06dko0aNSo7sMXExEx8/vnnw9eBvJ9wYcURjIiIiPlarfbbRx555BeFhYXxwc6l6ovU1FRUVFQErc6Sy+VCeXk59u/fj7Nnz0KlUiE3Nxc5OTndrszSaDRoaGiA1ytsl45AArtQXMuhwMBcQobFBuut6g2xWAyDwYDrr78ekydPhtPpxIEDB3D8+HHU19d3lJQoKysLa8NnwPd7Vlpa2u/k+UB48ODBgyNvuOGGj/R6/T+IKLHvdw6YiwAuMsaO+B9vh09oDXukUileeeWVi+fPnz979OjRgm3btmmPHTsmf/bZZxPnzJnTXF5enjdnzpzm9evX6wFAq9W6X3/99YpVq1aZO48zfvx4Z2FhYX5hYWF+Xl5evlwu9y5btqzXau1XAjzHihNyiChFp9P9bu7cuRO3bt0qiIeqOyQSCRITE3Hx4sVBV81mjMFqtaK8vBw2mw0GgwGTJ0/u1/L7QF2i+vr6oN8oe0OlUiE/P1+w+a7lUGC4woChzOmKjIxEZmYmMjIy0NDQgIqKCpw5cwZarRZtbW2X5DSFg+LiYqSmpg641EMgPLhr165bHn744VNqtfpVq9X6crAaPDPGaojoAhFlMcaKAMwDINwv2hWMyWRymUwmFwCoVCpvWlpaa0VFRcTu3buVe/fuLQKAVatW1efm5mYBqDQajW6j0ejeuXNnjyskdu3aFZeSkuLMzMy84vPYuMeKEzKISKRWqx9PTU3Ne/XVV+cIFfbrjZEjR6K0tHTAXiOPx4OKigp89dVXKC0tRXJyMnJzc5GZmTmgmkbhCAdGR0fDbrcLNt+17LEKx4rAhoaGkLeRAXz5WBqNBhMnTsQNN9yApqYmtLe349ixY2hoaAj5/N3R2toKs9k8pPZBgfDg/fffv0ar1eYT0YQgmvgwgD8S0WkAEwBsCuLY1wRFRUUR+fn5Ubm5uS319fWSgOAymUyuhoaGfjt3PvjgA/WSJUvqQ2dp8OAeK05IIKKRWq32r3fccUfaxo0bY0+cOAGXyxXWAoPAv5vhVlVV9Ssh1+FwoKysDGazGQaDAVOnTh1SoVGNRoMzZ84ImhdERJDJZIIVSZVKpYImy3dXeDVUCO2xCjTXFrpyvlgsRmtrK2688UbYbDacP38eZ8+ehclkgtFoFMxDWFhYiKysrCGff2RkJF588cWY5cuXp995552fabXa31oslrX+lXyDhjF2EsB1QzIuhHxkPZJc62oMagkIrVTpWKSa1q/mzjabTbR48eK0l1566YJarR50DkRbWxt9+umniv/5n/+5ONgxhIR7rDhBhYhEKpXqsREjRhzZsWPHhDfeeCNWqVQiLS1N0HBUb6SlpaGkpKQjj6QrjDFYLBZ8/fXXOH78OBQKBXJzc5GVlTVkYRLwCtTV1Q1pnIGiUqkEy7MKx7J8oeYU2mNVW1sraNg4gNlsRkJCAiQSCTQaDa677jpcd911cDgc2LdvHwoKCkK+wrWpqQkOhwN6vT5oY2ZnZ+PEiRPqn//85w9otdqzRDQ+aINzLsHpdNLChQvTli5d2rBixYpGANBoNO7y8nIpAJSXl0vVanW/lmlv375dkZ2d7UhOTha8COxg4B6rawgiEgP4BkAlY+xWIpoH4FfwCegWAPcyxopDOP8IrVb716VLl6b96le/iuscIktOTsbFixcFC2v0hlwuh1KphNlsvuSPttfrRWVlJc6fP4+4uDhkZmaGpCii0WhERUVFv+sSBQOlUonGxkYkJoYih/dyiOia7FEYDmEVjo4BZWVlyMnJueS5yMhIjBo1CpmZmaiqqsI333yDqKgopKenhyQPKz8/H9nZ2UEXzRKJBM8880zU4sWL0++4447PEhISfltXV7c2WLlXVxL99SwFG6/Xi2XLlpkyMzPbnnvuuY6E9Pnz5zdu2bJFs2nTppotW7Zobr755n4lon/44YfqO+64Izzx6EHAhdW1xSMACgDE+R9vBvA9xlgBET0A4Bn4i9kFE7+X6pERI0asee+99+JnzJjR3Wswbtw4HDt2DLNmzQr7DTc9PR0nTpyATqfryJ8qLy+HTqfDtGnTQhoyU6vVOH36tKDCQ+gK7DKZDO3t7WHrzxgqPB6PYKUHvF4vHA6H4MnydrsdXq+3o0xIV0QiEZKSkmA0GtHQ0ICCggIAvt+pwVZ370ptbS0kEglUKtWQx+qJ7OxsnDx5UvNf//VfD7755pu3E9ESxtjpkE04jNizZ0/Mjh07NBkZGa2jRo3KBoANGzZUbtiwoXrRokVpJpMp3mAwtO/YsaMEACoqKiRTpkzJttvtYiJiW7Zs0RUUFOSp1Wpvc3OzaP/+/XHvvvtuaGrlhAAurK4RiCgJwEIALwJ4zP80w79FlgJAVQjmTdVqtX9dsmRJ+ssvvxzXWyJ3TEwMEhMTUVxcjMzMzGCbMiCio6Mhk8lw8uRJNDY2IikpCTNnzhQkB4yIkJCQAIvFAp1O1/cbgoBcLofT6RQsHymQwH4tCav29nZBcwQbGxtD0j+yL8rLy/tVYiEQ1tZoNLDZbCguLkZhYSHS0tKg1+sHbTdjDIWFhZg8efKg3j8QJBIJ1q1bF7V48eKMO++883OtVvuOxWJZdy16r4Rk/vz5LYyxY90dO3To0Lmuz6WkpLjNZnO3ojY2Ntbb2Nh4Mtg2hpJry08/vHkNwJMAOicI/hjAP4noIoAfAHgpWJP5vVSPpqamHv3b3/426Te/+U2voipAeno6qqur0dLSEixTBkxrayvy8vLQ1NSEhoYGzJ49GxkZGYLeNA0GwzW9OjAiIkLQlYFCIHTi+kDa2AQLr9cLs9k84JCxQqHA5MmTMWnSJFgsFuzduxcVFRWDqtl24cIFqNVqQT/rMWPG4OTJk5qHHnroIa1Wm0dEYwWbnHPNwYXVNQAR3Qqgtpv/EP4TwALGWBKA3wH4nyDNl6TVao8sW7Zsw9mzZ+NvuOGGfr9XJBJh7NixOH36dI/J46Gira0NZ86cwddffw2VSoW5c+ciJiYGTU1NgtoB+EJzNpstaMVK+zunUAnscrkcbW1tIZ9HyGtI6Pwqi8WC+Ph4weYDgOrqauh0ukGHqKOiojBu3DhMnz4ddrsd+/btG5DA8ng8KCkpCYtHWyKRYP369dGfffZZZnZ29hdarfYFf94qhzMguLC6NrgBwG1EVAbgQwBziehjAOM7VQX+E4DLk58GSFRU1HeNRuOxP/3pT5M3b94cFxU18JW8arUaMTExuHBBmLxKp9OJvLw8HD58GGq1GrNnz4bRaAQRITMzE99++60gdnSGiKDValFbWyvYnCqVCo2NwhQtDuRYhRrG2DVZwypQrmKobWwGSllZ2ZBqRgWQyWQYPXo0pk+fjubmZuzbtw8XL17sUwiXlJQgOTlZ8PPuTE5ODk6dOqVZuXLlI1qt9nCIqrZzrmG4sLoGYIw9zRhLYoylAlgG4HMA3wOgIKLAv37/AV9i+6AgogidTrd16tSp7548eVI7Z86cISV+jB49GiUlJSENF7W3tyM/Px+HDh3qKJkQEFQBVCoV3G53WLxWBoMBVVVBT3vrEYVCIaiwEiIUeK0WBw2Ht6q5uRkikSioITiZTIYxY8Zg+vTpaGxsxN69e1FZWdmtwHI6naisrMSIESOCNv9gkUgk+O///u+YV199dXJSUtJZuVx+c7ht4lw9cGF1jcIYcwP4CYC/EtEp+HKsnhjMWEQ0IiEh4eR//ud/Lv/8889VwfiDL5VKkZWVhby8vCGP1RWXy4WCggIcOHAAMTExmD17NpKTk3tMps3IyEBxcciqUPSIUqlEU1OTYOFAqVQKj8cjSK/CQEHSUCPkykqHw4HBeGgHg8ViETy/qr9J64NBJpMhJycH119/Perr67Fv3z5UV1dfIrCKioqQkZEhWPHRvmhpaYHBYKDDhw+rJk2a9L5Wq/01EfEFX5w+4cLqGoMx9iVj7Fb//keMsbGMsfGMsTmMsfMDHS8mJmZZcnLykb///e+jV69eHRXMm5jBYIDb7Q5aOMzr9aK0tBT79+9HZGQkcnNzkZKS0ueNNz4+Hna7HQ6HIyh29Bcigk6ng9ls7vvFQSIuLk4Q75xQHiuh+gQyxgQLOzLG0NDQENJSA13xeDyCrFKVy+UYN24cpk6dipqaGhw8eBBWqxUtLS2w2Wwh7Yk4ELxeL44fP44JEybAaDRi//79qoceeug+rVZ7nIiSw20f58qGCytOtxCRXKfT/d/MmTPfOn36dMK0adNCMs+4ceOQn58Pt3vwBXUZY6iursa+ffvgdDoxa9YspKam9vsmSERIT08PS66V0WgUNBwoVAJ7RERErzlWXq8X7e3tcDgcHasza2trYTabUVNTg6qqKlRWVuLixYsdNcbKy8tx4cIFXLx4EVVVVaiurobZbEZ7ezssFgusViuam5vR1tYGt9sd1MR2odoBAeFpY1NVVYXExETB5oyMjMTEiRMxduxYFBUV4cCBAxgxYkRYqvZ3R0FBAQwGQ0eBYJFIhPXr10f/9a9/zUlKSvomMjLye2E28YqmuLhYOm3atMyRI0eOSU9PH7Nx40YtAJjNZvGMGTMyTCZTzowZMzIsFosYAE6cOCGfMGHCqIiIiEnr16+/RN1v2LBBm56ePiYjI2PMd7/73REOh+PKuEh6gbs1OZdBRJkJCQn/WLt2bfLDDz8sD+Ufu8jISKSkpODcuXPIzs4e8PutVivy8/MRFRWFadOmDaghcmf0ej3OnTsn6A0U8HmQWlpa4Ha7BSk8GapCoV6vF62trWhra4PT6YTT6URbWxtOnTrV8bhzyJOIIJFILtuICCKRCER02T4AuN1ueL3eDg9Sa2srXC4XzGYz3G73ZVtnIiIiIJPJIJPJLtmXyWSIiopCREREjzd2ofOrhG5jU15eLkjdqK7ExcUhIyMDZ8+eRUlJCWw2GzIzM8PaU9RiscBms2H69OmXHZs5cyadPHlSu3Tp0t/pdLq/1tbWPjjUfoPXIlKpFK+88srFmTNnOqxWq2jixInZCxYsaHr77bfj58yZ07xp06Zv16xZo1+/fr1+8+bNlVqt1v36669XbN++/RI3bWlpqXTr1q26oqKivJiYGLZgwYKR77zzjvrnP//5Fd2MmQsrziXExcWtHDFixC//9re/xU+YEMwm8D0zYsQI7N+/Hzabrd+tMRwOBwoKCtDe3o6cnJwht9Qgoo4egkK2EOkcDhQiDBIXFwebzTbg9zHG0NbWhubmZjgcDrS2tsLhcMDhcMDj8YCIEBkZCblcDplMBrlcDrFYjOTk5A7xEgrhGEjG79p+pTv7XS5Xh8gLbFarFU6nEw6Ho8PDFhBakZGRiIqKQnR0NGw2m2DCSug2NjabDVKpdND/lAwFxhgKCgowceLEjpXC+/fvR0pKCkaMGCF4h4b29nbk5eXh+uuv71FkazQafPbZZ6qXX3757l/96lcziehWxlhJqGwioiz4VnUHGAlgPWPstVDNOVRMJpPLZDK5AEClUnnT0tJaKyoqInbv3q3cu3dvEQCsWrWqPjc3NwtApdFodBuNRvfOnTsv6yHm8XjIbreLZDKZp7W1VZSUlHTFF2/lwooDwBf602q1/zdv3ryb/vCHPyh7amcRorkxbtw4nD59GjNnzuw1HODxeFBcXIyamhqMHj06qAm+BoMBxcXFaG9vF3S5t9FoRGFhoSDCSiQSQSwWw+VydesV8Hq9sNvtaG5uRnNzM1paWtDS0gLGGORyOWJiYhAdHQ2VSgWj0YioqKgeBVNlZWVHhftQ0d9VgUSEiIgIRERE9NiqBfDd6ANCKyAe6+rqYDabIRKJUFlZidjYWMTExCA2NhaxsbGQyWRBC2GFo41NWVlZyJLW+6K6urrjcwSAlJQUGAwGlJSU4KuvvkJ2drZg3jvGGE6cOIFRo0b1KTKJCE888UTUnDlzRi1ZsuRwbGzsA83NzX8JkV1FACb45xUDqATwUSjmCgVFRUUR+fn5Ubm5uS319fWSgOAymUyuhoaGXjXIiBEjXA8++GDNiBEjxslkMu+sWbOaFi9eLPwS7gHChRUHRJSYkJCwZ+3atWmhDv31hEKhgEajQWlpKUaOHNnta8xmMwoKCpCUlBSSfoMikQipqakoLS1FVlZWUMfujdjYWDgcDsHCgUqlEjabDSqVCk1NTbDZbB2b1+vtEA2BFkTR0dGDShAPJLCHUlgFO3mdiCCXyy8LBx8+fBjjx4+HSCRCS0sLmpubYTabUVxc3BE+VigUUCqVUCgUiIqKGpTYslqtgraxcbvdaGhowLhx4wSZrzNerxfnzp3D9ddff8nzEokEWVlZSE5ORl5eHsrLyzFmzJiQe9TKy8shl8sHVHV+ypQpOHXqVPxtt922JSEh4bq6urqnGWOhXHY7D0AJY6xfffM+OmJNrm10BXUpq1YpdSyapupXEUKbzSZavHhx2ksvvXRBrVYP+HOxWCzijz/+WFlcXHxGo9F4Fi5cOPKtt95SP/DAA1d0Q2YurIY5RHSdXq/f9cc//lE3d+7csC5myMrKwldffYXExMRL/og6HA6cOXMGYrF4SHlU/SE5ORn79u1DWlqaYM12iQh6vR41NTVISkoKyRyMMbS0tKChoQE2mw1VVVWQy+WIi4uDUqlEcnIyxowZE9RzFmJloFDlFgLiiYggk8mg0Wg6jgXCpAFxeuHCBTgcDkRERECpVEKj0UCtVvfLCyp0G5uLFy9eVttNKEpLS5GYmNhjTmNUVBSmTp0Ks9mMI0eOICkpCSNHjgzJ993c3Izy8nIMpItEAKVSiS+++EL16KOP3v/nP/95EhHdzhgLVe+oZQA+UGposQAAIABJREFUCNHYQcXpdNLChQvTli5d2rBixYpGANBoNO7y8nKpyWRylZeXS9Vqda+rlv7+97/HpaSkOA0GgxsAbr/99saDBw/GcGHFuWJRKpUrMjIyXtm9e7emJy+RkIjFYmRnZ+P06dOYNm3aJWE/oUICgbyg8vJypKWlhXy+AAaDocMbFww8Hg8aGxtRX1+PhoYGtLa2IiYmBmq1GiNHjsSFCxcQqpWeAYQQVkIUCPV6vZck0HclkF8WGRkJvV7f8bzT6ez4DoqLi+F2u6FQKKBWq6HRaBAdHX3ZmHV1dYJedxUVFZg6dapg8wVwuVyoqKjArFmz+nytTqdDfHw8iouLQxIe9Hg8OHHiBCZMmDDofyzEYjHeeOON2EmTJs1+6qmnThDRf/TXq9RfiCgCwG0Anu7ve/rrWQo2Xq8Xy5YtM2VmZrY999xzHfVk5s+f37hlyxbNpk2barZs2aK5+eabe61YnJqa2n78+PGY5uZmUXR0tPfzzz+PnTx5srB1cQYBF1bDECISJSQkvDZu3LifvPnmm/IrQVQF0Gq1uHDhAgoLCzs8OKEI+/VGamoqvvrqK6SmpgpWrDAuLg5tbW095j71BWMMVqsVFosFdXV1cLlcUKlUUKvVGDt27CWhKcYYioqKgn0KlyGUxyrU39Fgmy/LZDLodLqO2lBerxeNjY1oaGhAfn4+WlpaEBcXh4SEBGi12o7zECq/z2q1diw4EJpz585h5MiR/RYyYrH4kvBgRUUFcnJyghJmLigogNFoHPICGABYuXJlxOjRozO+//3vH5FIJEvcbvf+IQ/6b24BcJwxJlzhu0GyZ8+emB07dmgyMjJaR40alQ0AGzZsqNywYUP1okWL0kwmU7zBYGjfsWNHCQBUVFRIpkyZkm2328VExLZs2aIrKCjImzt3rv273/2uddy4caMlEgnGjBnjeOyxxyzhPbu+IaEb4XLCCxHFabXav69YsWLSiy++GHPkyBGMGjVK8PYZPeFyuXD69GnU1NRg1qxZiIuLC4sdRUVFkMlkgib1FhUVISoqCsnJfdcfZIzBbrfDYrHAYrHAbrdDqVQiISEB8fHxfd4sDx48iEmTJoX0pmo2m1FfXz+oMhr9pby8HB6Pp8e8vGBQU1MDq9WK0aNHB3VcxhiamppgsVhQW1sLu92OiIgIZGZmIj4+PuQlB06cOIGkpCTBSzs4HA4cPXoUs2fPHnQIsrq6GoWFhcjIyBhSKNNsNqO0tBTTpk0Laji0srIS8+fPb6iqqlrf0NDwm2CMSUQfAvh/jLHf9fa6U6dOlY0fP74uGHNerZw6dSp+/PjxqeGan3ushhFElKbVave89tprSXfddZcUAK677jocOnQI06ZNE6xdR0/U1NSgoKAAGRkZiI+PR1lZWViSagFfCYiDBw/2q3J7sDAajcjLy+tRWHm9XjQ0NKCmpgZ1dXWIjIxEQkICRo8ejZiYmAHdGAINmTuHroLNtZJjFaoaVkQEhUIBheL/s/fm0Y2e9d3399JmLd4kW7Il2ZYXyfu+L+MZT8gykBJISkoCSXmfAk9aoAVKD4f04QRCCE1Pn/QNaQtNSwKFhJC3WSaQhElCZvN43+3xvu+2ZEu2JGuXrvePGSmzeJHl+5aH1J9zfJKx7/u6r1u6l9/1W76/GGi1WvT09CA6Ohomkwnj4+PgcrlITExEYmIi41WCbrcbm5ubCJekyrUMDw8jOzv7QIaMUqlEfHw8BgcHsbCwgKKion3nXjqdTgwNDaGmpobxHDO1Wo2Ojg7Zgw8++GRCQkKFXq//0tU2YyFBCBHjSr/XR5ib5RFscWRY/Q9BIBDcnpSU9Os333xTXlpaGvi9UChEcXExOjs7UVtbG7aE7WtxOp0YGBgAANTW1iIiIgKUUrS0tMBoNEImk4V9TgKBAHK5HEtLS6wllN9IZGQkXC7XdXIPbrcber0eKysrMJvNkMlkSExMRE5OzoFCYLGxsTCZTB8Jw4ptz47Var0uWZ0NKKXY2NgIVB4CgN1ux+rqKgYGBuB0OiGXy5GYmMhI1eD8/DySkpLCnrS+sbEBp9PJSII+n89HcXExDAYD2traoNFokJqaGtQ5+aUVcnNzWfPaikQivPHGGzFPPvnk/c8++2weIeQuSmlISdeUUhsAdi/CIxjjyLD6iEMIITKZ7Ft5eXmPnjlzRrZdLzCpVIrU1FT09PSgvLw8bA9bSikWFhYwMTGB7Ozs68qc/dpWXV1dYc+x8pORkYG2trawVk0lJiZicXERXC4Xi4uLcLlcUCgUyMjIQExMDGPzYEuB/VrClbzOdo5QOFTXt2tjIxKJkJqaitTU1EBPzZmZGfT29iIuLg5qtRpxcXH7viYopZifn99WWZxNKKUYGhpCXl4eo/eTXC7HsWPHMDIygubmZhQVFe35fU1PT0MikbDeG5EQgu9+97vioqKiki9/+cu9hJCPU0oHWT3oEYfOkWH1EeZqkvp/NjQ0/OmvfvWrmN0SPVNSUrC5uYnx8XFkZmayPjen04ne3l5ERETg2LFj23od/DpKExMTYZnTjQiFQsTGxmJ1dZVVzw5wRU9odXUVa2trMJlM0Ol0KCwsZE0oUigUwul0glLKmtHI4XAY7de3HeEIBXo8Hta9YnvJLPB4PKhUKqhUKvh8Pqyvr2NhYQEDAwOQy+VQq9WIjY0N6rs0Go2IjIwMqwgucOUc/XpfTMPj8ZCfnw+j0Yiuri4kJyfv2HvQbDZjfn4ex44dY3weO/HJT36Se/bs2eSPf/zj5wQCwZ+5XK7zYTv4EWHnqAnzRxRCiEChUPzu4Ycf/rNXXnllV6PKT15eHtbW1rCyssLq3Pxd7TUaDYqLi3d9aWm1WiwvL8NqtbI6p92OPz4+zoqB4PP5sLKygs7OTly6dAlmsxn5+fmIiopCamoq6+rbEokEW1tsye18CJvGFdtVgW63OyzhcYPBEHR4jMPhQC6Xo7i4GCdOnEB8fDympqZw/vx5DA0NwWzeXZh6ZmYGaWlpTEw7aHw+H0ZGRhgvALgRmUyGY8eOYWtrC62trbDb7df93S+tUFJSEraKXz+5ublobW2Vp6envxYVFfVnYT34EWHlyGMVJq62IugEsEgp/RNCSCMAf28NBYB2SumnGTpWlFwu/8O3v/3tgm9961tBZ3RyOByUl5ejubkZEolk19YfoeDxeDA4OAiHwxHIpQpmTgUFBejv72clyXQvJBIJxGIx1tbWGKueslgsmJubw+rqKhQKBbRa7XVhPqVSieXlZWg0GkaOtxNSqRQmk4nVMBefz2fV48O2xypUqYX9cJA2NhwOJ5Dg7vd6+ntoJicnQ61WX/fZO51OWK1WSKXSXUZlnvn5ecjl8rD0I+RyuSgoKIBer0drayuysrKgUqkAAIODg0hJSTm0amOlUom2tjbZ7bff/u8ymSzRaDQ+eygTOYJVjjxW4ePrAIb9/6CU1lNKiymlxQBaALzOxEEIIQq5XN7+zDPPlOzHqPIjEAhQWlqKrq4uuN3M9bo0mUy4dOkSYmNjUVlZuS/9GZlMBolEgvn5Q9G6g06nw/j4+IHGcLvdmJ2dxaVLlzA4OAipVIqGhgbk5+ffFMJRq9VYXFw86LT3xF8ZyCZs51mxLRAajvwqk8nESIEGj8eDWq1GVVUVysvL4Xa70dTUhO7ubqytrQVyq5KTk8O6QPF4PJiamoJOpwvbMYErmnh1dXVYXFxEd3c3FhYWYLfbD60vop+YmBg0NjZKKysrH1coFP9IDkP2nmUmJib4VVVVmenp6XlarTbviSeeUADA6uoqt7a2VqfRaPJra2t1BoOBCwA9PT3C4uLibIFAUPrYY49dl/j2xBNPKHQ6XZ5Wq837wQ9+EL62BAfgyLAKA4SQJAB3A/jZNn+LAnAbgNMMHCdNoVB0vPjii5mf+9znQnYRREdHIzMzE11dXQcO4/h8PoyOjuLy5csoLy+HRqMJ6aGem5uLyclJ1pOhtyM6Oho8Hg8mk2nf+5pMJvT09KCpqQlOpxNlZWWorq6GSqXa0SAQi8Xwer2sn2tMTAzrhpVAIGD1PNgOBYbDsNLr9YxrSYlEIuh0Opw4cQIajQbz8/M4f/48JicnWU/YvpGJiQloNBrW89S2QyAQoLy8HLGxsejp6Qn5+cM0QqEQb7/9duwnPvGJv1QoFL+6GtH4yMDn8/H0008vTE1NDXZ0dAw///zziq6uLuH3vvc9ZUNDg2V2dvZyQ0OD5bHHHksEAIVC4fnxj38898gjj1wnftrR0SH85S9/Ke/u7h4eHh4ePHPmTOzAwAB7zUcZ4siwCg/PAPg2gO2aUN4L4ANK6YE6dhNCipRKZfPbb7+dcueddx74e1WpVIiNjcXQ0FDIY9jtdrS0tIBSirq6ugO9oPh8PrKysjA4eDgFNfvxWvl8PszPz6OxsRETExNITk7GiRMnkJmZGXQoRKVSYXl5+SBT3hM+nw+v1wufj72esWx7rD4KoUAmw8w3QghBXFwcSkpKkJOTA7FYjM7OTvT09LBuVANXeiyurKwcupdodXUVxcXFmJycxOjoKOtFFcHA5XLx85//PPqhhx66T6VSnSOEhF8CnyU0Go372LFjNgCQSqW+jIwM+9zcnODMmTOxjzzyyDoAPPLII+u///3vpQCgVqs9J06csPH5/Ou+mIGBAVFpaak1KirKx+fzUVdXZ3nllVdiw39G++PIsGIZQsifANBTSrt22ORBHLCppkAgaEhJSfnDhQsXEsvLyw8y1HVkZWVha2sLCwsL+9732vyG7OxsRl5+SqUyoOsUbqRSKTwez66JwXa7HcPDw7hw4QKsVivKy8tRUVGB+Pj4fa+SVSpVWMKB0dHReyY7HwShUAiHw8Ha+GyHAtk2rFwuFwCExZszPz+PgoICHD9+HElJSRgbG8OlS5ewsLDAmnE9MjKCzMzMQ5FL8TM5OYno6GgkJyejpqYGPp8Pra2th+L9vhGz2YxPfvKTor/7u7+rlMvlTYQQ5ksmD5nR0VHB0NCQ+MSJE9b19XWeRqNxA1eML6PRuGued3Fxsb2trS1qZWWFa7FYOO+//37M/Px8eMtZQ+AoeZ196gDcQwj5BAAhgGhCyIuU0ocIIXEAKnHFaxUS0dHRf5aenv7Tc+fOya7VgWICQghKSkrQ3NyMyMhIxMbuvVDwh/42NjaCTlDfz3wKCwvR1taGuLi4sFf1+L1WZWVl1/1+Y2MDExMTgfyN48ePH3huIpEIlFI4HA5WdZr8CezBfLehEBERwapnhM1QIKWU9VCjwWAIS0sZh8MBu90e+J7lcjnkcjlsNhtmZmYwPj4OlUqFtLQ0xmQYzGYzrFYrioqKGBkvFDY2NrC0tBSQVuBwOMjJyYFer0dzczMKCgoOrZ3X1tYWuru7UVFRgYaGhoikpKTCr371qx2EkBOUUkbc1XNvmJIdejejLTWECr4t5d7gmjtvbm5y7rvvvoynnnpqXiaT7dt6Ly0tdXz9619fue222zLFYrEvNzfXdhgi1vvlyGPFMpTSRymlSZTSVAAPADhLKX3o6p/vB/AWpTSkJX18fPzXs7Oz/72trY1xo8oPn89HeXk5ent791zhORwOtLS0gMPhoLq6mlGjyo9IJEJKSkpYmgjfSHx8PGw2G7a2tkApDTycR0dHkZ6ejvr6eiQnJzP2IlYqlVhaWmJkrJ1gO4H9jzl53el0snINX8t+ZBYOwtzc3LZVpmKxGLm5uTh+/DgiIiLQ3NyMy5cv3yRTEArDw8PIzc09tJwmj8eD3t5elJSU3HSNKBQKVFdXY3R0FGNjY2EPDTocDnR0dKCkpCSQInH//ffzXnnllYyEhIR2Qkh4M/1ZwOl0krvvvjvj/vvvN37hC1/YAIC4uDjP7OwsHwBmZ2f5MplszzY/3/zmN9eGhoaGOzs7R2UymVen07HnAmeIW9/0+2jzAICnQtlRLpd/t7S09Fu//e1vY9lWnpZIJMjNzUVnZydqamq2fZHp9XoMDg4iPz+f9RV4WlpaQPcpnGXThBBotVr09fXB4/EgMjISBQUFjMtS+FGpVOju7ma1wXB0dDQ2NzdZGz8iIoLVUCCbOVZsJ65TSmEymVjvh0kpxeLiIurr63fchsvlIjU1FRqNBktLS+jo6EBkZCR0Ol1I1/fa2ho4HM6htKPyc/nyZaSlpe04f5FIhJqaGgwPD6O1tRWlpaWsG9LAlQrh9vZ25OXl3eQpPnnyJOfdd99N+sQnPnGREPIxSmnoSa4AgvUsMY3P58MDDzygyczMdHz/+98PJKTfddddG88991zcj370o5Xnnnsu7tSpU3uu6hYXF3lqtdozPj4uePvtt2Pb29tH2J39wTkyrMIIpfQ8gPPX/LshlHEUCsXjlZWVf3P69OnYcFXaKBQKWCwWDAwMXOfap5RibGwM6+vrqKmpYb29CPBhSLCvrw/Hjh0Ly4rY5/Nhbm4O09PTcDqdqKqqYl0LyJ/obrfbWdP/4XA44HK5cLvdrOT5hCN5na1QHdv5VVarFRKJhPX8I71ej7i4uKCETgkhUKvVUKlUMBgMGBgYAJfLRWZmZtDXu791zbU9ScPN0tIS3G43UlJSdt2Ow+EgLy8vIFpcXFzM6n3t9XrR3t4OrVa74wK0qKgIf/jDHxJvv/32s4SQ2ymll1mbEEu8//77kadPn47T6XT27OzsXAB4/PHHFx9//PHle++9N0Oj0cSrVCrX6dOnJwFgbm6OV1FRkbu1tcUlhNDnnnsuYXh4+LJMJvPdc889GRsbGzwej0efeeaZOblc7j3cs9ubI8PqjwyFQvGjmpqar7z22msx4Y41p6eno7u7GzMzM4H+Zd3d3RCLxaiurg5rgmpMTAxkMhmmp6dZ9ej4K/ympqagVCpRV1cHvV6PpaWlsIgsqlQqLC0tISMjg7VjxMbGYnNzk5VcEy6Xy2rVIZsteaxWK6ve13DlV83MzOxb8ZwQAoVCAYVCAZPJFAiXZWdn75mPt7CwAKlUyrpMxU7Y7XaMjo6irq4u6GsjMTERUVFR6OrqQmpq6p4GWShQStHV1RUwXHcjJycHZ8+eTfjYxz72ASHkDkppP+MTYpG77rrLulPBVktLy9iNv0tJSfGsrq5ue45dXV3hz/s4IEc5Vn8kEEJIQkLCPx0/fvwrr7/+etiNqqtzQHFxMebn57G4uIimpiYolUrk5+cfStVPVlYW5ubmGMkHuRFKKebm5nDx4kXYbDbU1dUhOzsbAoEgsJr3V3SxiV+FnU1iY2ND0uj6qMN2KHCv/oBMYLfb4Xa7DxQyl0qlqKqqQlZWFkZGRtDe3r5j+Njr9R5ab0/gyn3b3d2NgoKCfSfhSyQS1NbWYnV1FQMDA4wuCCil6OvrQ0xMTNDSE1lZWTh//rwiOTn5fUJICWOTOYJ1jgyrPwIIIUQul/9zQ0PDl1955ZWYcFfDXQuXy0VaWhq6u7uRlZWF5OTkQ5sLj8dDbm4uBgYGGBuTUoqFhQVcuHABFosFNTU1yMnJue4hzeFwkJqaiunpacaOuxNCoRCEEFaMRz/+ykC24HK58Hj2zFG95WAzBOvz+WC321nXyJqdnWWsNZJUKkV1dTW0Wi0GBwfR0dFxk1TH1NQUkpKSwpKrtB3j4+OQyWQhe195PB7Ky8sRERGB1tZWxhZPw8PD4HA4+zY4tVqt37h6lxDCnJbOEaxyZFj9ESCXy//ptttu+18vv/zyoRpVlFJMTk5iZmYGFRUVGBsbO/QXpkKhAJfLZcSro9frcfHiRZhMJlRXVyMvL2/HF0RycjKWlpbCcv5st7hhuxkz23lWbOD3VrAVZjQajawndvt8PiwvL+8ZdtovMpkMtbW1SEtLw8DAAHp6emC32+FyubCwsMBqaH43TCYTVldXkZWVdaBxCCHIzMxEeno6mpubD6zzNjk5CZvNhoKCgpCup/T0dFy8eFGenJz8DiHk8BLXjgiaoxyrWxy5XP6PDQ0NX3rppZdiDlNkz+v1oq+vDxwOB7W1teBwOHA6nejr60NpaemhtonIz89Hc3Mz4uPjQ0rANpvNGBwchEAgQEVFBcTivWVfuFwuUlJSMDMzA61WG8q0g0apVAYSXtmAEBKo3mOj+MBvWLHtnWESu90e1HUQKuEIA66srEAul7OW3B8fH4+4uDisrKygra0NhBCkpaWFXV8OuFJp19fXh4qKCsbSEhITEyGRSNDV1YXMzMyQDNT5+Xno9XpUVVUd6BmZmpqKc+fOyRsaGs5czbnqC3mwbVhaWlKsr6/LAUAoFNrS09NnuFzu4cvT/5Fy5LG6hVGpVE/V1NT85W9+85tD9VS5XC60trYiNjYWxcXFgQeXv//XxMTEoc0NuPLizsjIwPDw8N4bX4PdbkdPTw8GBgaQnZ2NsrKyfb1M/T3YvF52i1QiIiLA5XJhs9lYOwabelZ/jB4rtvOr1tbWWBemZDIMuBOEECiVSpSVlcHlcmFqagozMzOsFixsx8DAADIyMhg33qOiolBXV4fZ2VlMTEzsS+9qdXU14N1nwtjLyMjA2bNn5Wq1+j1CSP6BB7yK0+nkGwyGhNzc3KGCgoJBAGRtbe3wdDI+AhwZVrcocrn8e8XFxX/1N3/zN9Fshmn2YmtrC83NzcjIyNjWxZ+fnw+9Xo/V1dVt9g4fycnJsFgsMBqNe27r8XgwMjKCtrY2JCYmora2NqQKPx6PB5VKhfl59qVi2A4HspnAzpZhxaaoI5uGldPpBIfDYbWNzdbWFnw+H2saazcyMjKC4uJi1NfXw2azobGxMWzPhIWFBVBKkZSUxMr4fD4fVVVVsFgs6O/vD8poNBqNGBkZQVVVVVAyF8Gi0+nwwQcfKFQq1R8IIblMjUspJT6fj+Pz+eDz+TgCgcDN1Nj/EzkyrG5B4uPjv11eXv6N3/72t9HV1dXo6uoKS8PUGzEajWhvb0dxcTESExO33YbD4aC8vBzDw8OwWq1hnuGHEEJQVFS0azUPpRRLS0tobGyEQCDA8ePHoVQqD+SiT0tLC8sKne3qQDYT2NkyrNgUB91aW2MtdMlm02U/fkmUcGA0GuH1eiGXy8Hn85Gbm4vKykrMz8+jra2N1fw9m82GiYkJFBYWspqOwOFwUFxcDKFQiI6Ojl1zK81mM/r6+lBZWclYe6BrycrKwh/+8IcEpVL5ASHkwPkBERERboVCsTIwMFDY19dXxOVyvVKplL0Gov8DODKsbjFiYmIezs7O/s6bb74Zy+PxEBkZicrKSvT29oa1JH5paQkDAwOoqqraU7cmIiICJSUl6OzshNt9eAudyMhIJCYmbhuatFqtaG1txerqKmpra5Gens7IS1kgEEAul7PeekYgEEAgELBmvAqFQjidTla8QDsZVj6fDy6XCzabDWazGUajMeD9XF5extLSEhYXFzE/P4+5uTnMzc1hYWEBi4uLWF5exvLyMrxeLwwGA0wmEywWCxwOBzwez4HOw72yAtk774CePcvK56HX61k1rLxeL1ZXV8FWm6tr8YuB5uZe7zwRiUQoLy9HRkYGOjs7MTo6ynjI3Ofzobu7G4WFhWFpYk0IQVZWFlQqFZqbm7ftKGCz2dDV1YXy8nLWKkqBKzpX77zzTmJCQsJZQsj2q94gcbvd3M3Nzdj8/PyBoqKifq/Xy9Hr9UehwANwlLx+CyEUCu/S6XTPnDlzRnrtSkcikaCyshLt7e0oKChAXFwcq/OYnJwMGCDBPrBiYmKg0+nQ3d2NysrKQ0tm1+l0aGxshFqthkQigcfjwdjYGNbW1pCfn89KJVZGRgba2tqgVqtZPW+/WChbGkH+6sCDhMD8MgI2mw12ux1OpxNWqxUGgwFWq/W68nVCCHg83k0/HA4HhBAQQq77f+DDxsiUUrhcLng8HqyursLj8dz044fD4SAiIuK6H6FQCJFIBLFYDIFAcN33tvneewAA58AAzLGxiLnjjpA/jxuhlGJjY4PVxsTLy8tITEwMi7bc8vIyIiMjd9TJio+PR319PaamptDY2IicnBwkJCQwcuzx8XHI5fKwt81JTk6GSCQKtMHxn7vT6Qx4+MMRgi0uLsbLL7+s/uxnP3uBEFJBKQ3Jy7S5uRktEAicAoHAAwBSqXTDarVGKhSKvfMqdmB0dFRw6tQpXWVlpbW7uzsyJyfH9hd/8RdrP/jBD9Tr6+u8X/ziF1NlZWWOL37xiynDw8Mir9dL/s//+T9LDz300Mbo6Kjgc5/7XJrdbucAwI9//OO5O+64Y+utt96K+sEPfqCSyWTu0dFRUUFBge306dPTh1nUtRNHhtUtAiGkPC0t7cWzZ8/KtnuxicViVFVVoa2tDXl5eayseCmluHz5Mtxud0hK6mq1GmazGSMjI/tWemYKDoeDgoIC9PX1ITU1FaOjo9BoNKivr2fN6BEKhYiNjcXKygqrXgKlUonm5mbWDCt/OHAvw8rj8WBrawsWiwVWqxVbW1uw2Wzwer0ghAQMFpFIBJFIhMjISGxubqKsrOwmI+Yg2Gw22Gw25Ofvnsfr9XrhdDrhdDrhcrngcDhgtVqh1+ths9kCxl5ERARiLBbETEzAkJ6OpOhoWBsbwY2ORmRVFSNzDkcbm9nZWRQXF7M2vh+fz4exsTFUV1fvuh2Hw4FWq4Varcbg4CBmZmZQUFBwoKrL9fV1GAwG1NbWhjzGQYiPj0dZWRm6urqQn5+PmJgYtLe3Izc3NywdGfycPHmS82//9m9pX/3qV88SQuoopfuOuQsEApfNZov0er0cDofjM5vNURKJ5MCVMvPz88JXXnllqqysbLawsDDnpZdeiuvs7Bz59a9/Hfvkk08qs7OzHSdPnjT/93//98za2hq3vLw855577jGrVCpPY2PjmFgspgMDAxEPPvhg+uXLl4cBYHh4WNTb2zuVmprqLisry37//fcj77rrrsPLQdmBI8PqFoAQolOr1W8gFlbJAAAgAElEQVSdPXs2fjeDSSQSobq6Gm1tbcjJyWG0XNvn86G3tzcQ1gv15ZednY329nYsLi5CrVYzNr/9IBaLsbW1hYmJCdTW1oZFrFCn06GrqwuJiYmsGXB8Ph9CoRAWi4WVFbHfOPSLvvp8PlitVmxubmJzcxMWiyWQeB0ZGYmoqCjExMRApVJBLBbvmKRLKcXo6Cjj30OwfQK5XC7EYvGuL3JKKRwOB0w/+xm8Egk2kpLgkkgQu7AA+vbbmNbrIcjMRGxsLGJiYkKWpWBbZsFisYDD4YRF2mJmZgaJiYlBfxb+8KDBYEB7eztSUlKQlpa27/vF7XZjYGAAlZWVh9LxwU9UVFTgeUwphVarZV1CYzvuv/9+/urqat4TTzzxO0LIx3t7e6/7e2Vl5U3CXvfdd5/xO9/5jsFisXBuv/32JJ/Px6GUFl39LnwPP/yw9etf/zqWl5d5n/rUp67rp9Xe3h5Uixm1Wu2srKy0A0BmZqb9tttuM3M4HJSWltp++MMfqlZWVgTvvvtu7LPPPpsIAE6nk0xMTAg0Go37i1/8omZoaEjE4XAwOzsbeHAUFBRsZWRkuAEgLy/PNjk5yXwSGwMcGVaHDCFEmZCQcPadd95JCCbZVCgUBm5mn8+3Y1L5fvB6vejs7IRMJoNOpzvQWIQQlJaWoqmpCZGRkYiJiTnw/IKFUor5+XlMTk4iNzcXY2M3taRiDbFYDIlEwnpisj8ceFARxBuhlILD4WBlZQU+nw+bm5uBqrKYmBgkJCRAq9UiIiJi3y9CtgxNr9fL2IuVEAI6NgZqMIBz221Qq1TIzMyEr6wMa7/4BWTd3YBSiXWvF1NTU3A4HBCJRIiJiQn0rQzGwDAYDCgoKGBkztsRrqR1t9uN2dlZ1NfX73tfuVyOY8eOYXR0FM3NzSgsLAx6oeBvDaPValnVGQuWiIgIiESiHVv8hIuvfe1rwsXFxZoXXnjh56Hsz+FwXAACcXpCyIGTCwUCQWAMDocDoVBIgSsLHa/XS7hcLn311VcnioqKrvOy/e3f/q1KoVC4X3vttWmfzweRSFTm/1tERERgzKsdHQ5PQHEXjgyrQ4QQEiOXyy/85je/URUWFga9X0RExHXG1UGUld1uNzo6OqBSqRh7IPP5fJSXl6OzsxM1NTVh8RjZbDb09fVBLBbj2LFj4PP5IIRgcHAQpaXhESvWarW4fPkyq4ZVYmIimpubD2xYeTwemEwmGI1GGI1GOBwOREdHw+fzQa1WIy8vj9EycQ6Hw3gVX7Aeq2CgbjfMH3wAvlIJU2Iioq6GQzkCAeI+/3ms/exn8L7/PnRf+hL4ubkBD9fGxgY2NjYwPT0Nl8uF6OhoxMXFQSaTISoq6jqj0uv1wuFwsOZN8nq9WFtbQ15eHivjX8v4+DjS0tJCvkZ4PB7y8vJgMpnQ3d0NpVIJrVa75/WxsLAADofDmrTCfqCUor+/H1FRUSgtLUVHRwfcbjfS0tIOZT4/+tGPIhcXFz9lsVgAYM3/+908TFFRUb7d/q5UKj3Beqj2y8mTJ81PP/10wi9+8Ys5DoeDpqYmUV1dnX1zc5OblJTk4nK5+Nd//dc4tnUC2eDWy/r6HwIhRKhQKM7+5Cc/SWtoaNj39yAQCFBdXY2pqSksLCyENAe/8KdGo2F8lRsZGYmcnBx0dnayKkVAKcXU1BTa29uh0+lQVFQUSLhXKpVwu90wGAysHf9aoqOjwePxWK3e5PP5EIlE+26z4X/pDg0NobGxEc3NzYHE4+LiYpw8eRJlZWWQy+WBJHImYUNygUlDzdreDu/GBqLvvBPWGxL4uRIJ4v78z0G4XKz/8pfwms2BXDKlUomcnBzU1dXhxIkTyMjICOQenT9/Hm1tbZiamoLVamW9jc3i4iKUSiXr4TG73Q69Xo+UlJQDjyWVSlFfXw9KKS5durSr52drawuTk5Osevz2w+joFXsjOzsbPB4PlZWVMBgMGB0dZVVjbScIIfj5z38e7fV6I1dWVtjV82CAp556asnj8ZDs7OxcnU6X993vflcNAN/4xjf0L7/8clxRUVH22NiYUCQShVdtlgHIYVwA/9MhhHDlcvm7jz32WN3Xvva1A/UQcbvdaG9vR3Jy8r4edHa7He3t7cjOzmasSmc7xsfHYbfbsR+PXLD4ldOjo6MDD7fttmlra0N9fX1YWm2YTCaMjY2hiqFk5+1YWFiA1WpFdnb2jttQSmGxWKDX62EwGOB0OiGVSqFQKHZt/eNvLM30qru3txepqal7SnfsB/+5HdRD47PbsfLMMxCo1Yj/8z/HxYsXUVdXd9P14lpawtoLL4ArlUL+xS+Cs0foj1KKra0tGAwG6PV6GI1GREdHQ6PRQC6XM+7JbWxsZL3MHwC6u7uhUqkYSUO4Fr/+U2JiIrRa7XXePp/Ph6amJuTn54c1OXwnpqensba2hvLy8pvm2dfXBz6fj7y8vEOpjh4aGgKHw/HK5fLZuLi48Gn03EL09fXFFxUVpR7W8Y88VmGGEEIUCsV/ffnLX646qFEFfKgKvLi4iJmZmaD2sdlsaGtrQ35+PqtGFXAlPOZyuTA7O8vouIuLi2htbYVOp0N+fv6OHhaRSITk5OSw5VtJpVJ4vd4DN27djcTERKysrNy0Kvb5fNDr9ejv78f58+cxOjoKPp+PoqIiNDQ0oKioCEqlclcJDbZa2wgEglvWY2W5eBHU4UDMnXeCUgqv17utES5QqSB74AF4DAYYX34ZdI8G3IQQREZGIi0tDVVVVRCLxdDpdNja2kJ7ezsuXbqEiYkJRrTJNjc3IRAIWDeqNjc3YbfbWXluREdHo66uDh6PB83Nzde1cBodHUVCQsItYVT5ddS265HqFxIFgL6+vkPzXGm1Wu7q6qpmc3OTvb5MR+zIkWF1A4QQLiGkhxDy1tV/E0LIk4SQMULIMCHkbw4yvlwuf+LUqVOf/OEPf8jYBe93Q6+srGBqamrXbW02G9rb21FUVMS6HhZw5SYvLi7G7OxsUO1m9sLtdqOrqwvLy8uoq6sLKp8pPT0da2trrBo715KZmYnx8XHWxufxeJBIJDCbzXC73VhYWEBnZycuXLiAlZUVJCYm4sSJE6ioqIBGo9lXkm90dDQribj+Js9MwkSOlWdjA9a2NoiLi8FPTITL5drVkyTUaiH99KfhnJ6G6fRp0CDD3E6nE1wuFwqFAllZWaivr0d5eTn4fD4GBwdx/vx5DA4Owmg0hvQynpmZCUtuz9DQEKueGA6Hg5ycnEB18fz8PAwGA4xG44ELa5hAr9djcnISFRUVO157hBDk5eVBIBAcmnHF4/Gg1Wq58/Pz2q2tLeY7qx+xK0eG1c18HcC13Xz/HwDJALIppTkAfhPqwBKJ5D6dTveV559/PprpBxOXy0VFRQUMBsOOTZGvNarCufLj8XgoLy9HX18f7HZ7yOOsra2hqakJCQkJKC8vD7pdBCEEhYWF6O/vD8tDLi4uDna7nbVWHl6vFyKRCJ2dnWhqaoLVaoVOp0NDQwMKCwuhUChC9uRwOBxwuVzGFfSFQuF14qBMwERVoPmDDwAAUbfdBuBKHs9eyeXi4mJE33477P39ML//flDHMRgMNy0ChEIhNBoNqqqqcOzYMcTFxWFmZiZgZG1sbAR1vbrdbhiNRtbb5Oj1eggEAkbDuTsRFxeHuro66PX6gDDyYYkO+zGZTBgaGkJVVdWewsmEEOTk5ByaceXz+eB0OpGcnMydmZnRud1u9vMgjghwZFhdAyEkCcDdAH52za//CsAPKKU+AKCU6kMcu0ChUPzHW2+9JWU6MdiP37jy5/lcy2EZVX7EYjEKCwvR2dm579YWlFIMDw9jdHQUVVVVIVUExcTEQCqVBh0uPQhXXfE7Grih4PP5sLKygq6uLly8eDHw++PHjyM7OxsxMTGMvXhiYmIY91rdisnrruVl2Pv7EVldDd5VWRCLxRKU8nxkfT0klZWwNjXB2tKy5/bbGVbXwuPxkJiYiNLSUhw/fhwymQwTExO4cOEChoeHd/W2+jXj2DQ8/PdgOIV/eTwefD4fUlNT0dXVhfX19bAd+0YsFgt6e3tRWVkZdG7cYRlXPp8PW1tbEAqFiImJgVqt5k9OTurY7md6xIccGVbX8wyAbwO49grMAPBZQkgnIeT3hJB9+6MJIfEJCQnvvPPOO3FsGzUcDgdlZWWwWCwYHh4GpfTQjSo/cXFxSE5ORm9vb9APGYfDgZaWFhBCUFtbe6AckqysLMzOzh7IaxYsCQkJ2NjYOHD4y2w24/Llyzh//jwMBgPS09PR0NAQUHtmI7zJRkNmtgyrg4QCze+9ByIUIuoaLaa1DRvE4r3lEAghiPnEJyDMycHmmTOwX76847b+NjbB3ntcLhdKpRLl5eU4duwYoqOjMTw8jMbGRszMzFznTaSUYm5ujpEKvd2Ym5tDfHx8WLWj5ubmAkng1dXVGB4exvj4eNi9P3a7HZ2dnSgrK9v3+YfbuFpbW4PL5YJYLA541WJjY0l0dLRobm5Ow+rBjwhwZFhdhRDyJwD0lNKuG/4UAcBBKS0H8J8AXtjnuHy5XP7u888/rwzXau+qui0cDgf6+vpuCaPKT2pqKng83p65YMCVVX5LSwt0Oh2ys7MPvCLn8XjIzc3FwMDAgcYJBkIIMjIyMDk5ue993W43ZmZm0NjYiOHhYcTFxaGhoQEFBQWQSqWBz0GtVmNxcZHpqbNmWDGdY3WQUKBjYgLOyUlEnzgBzlVjfXrVid8OReF0L7CxtXtiOgAQDgeyz3wGguRkGF97Dc6rFZU34veChXL98ng8qNVqVFVVoaKiAm63G01NTeju7sba2hpMJhPEYnHISvDB4PF4MDU1xVorpe2wWCyYnp4OtCsSiUSora2Fy+VCW1sb42HlnXC5XGhvb0dhYeGO/RD3IlzG1dzcHIaHhxEREXHTgkOpVHK8Xq90dXX1lpdh+ChwZFh9SB2AewghM7iSR3UbIeRFAAsAXru6zRsA9qUboFAoXvjGN76Rfffdd4c1xu3vxL68vAyJRBKWvIhgKSgowMrKCvT67aOqlFKMjIxgbGwMNTU1jOaOKBQKcLlcLC8vMzbmTqjVahgMhqBfApubm+jt7UVTUxPcbjfKy8tRVVW1ozaRQqGAXq9n/EHtb8bMJHw+n/G8rVA9VtTng/m998CVSiGprAQArFs8+M2ldURwPTBu+fDTM3qMLe1tCBI+H3Gf+xx4UinWX34Z7tXVm7bZKwwYLEKhEDqdDidOnEBqairm5+fR2toKPp/PqqExOTmJlJSUoBuyHxSfz4eenh4UFxdfV+3L4XCQl5eH1NRUNDU1MVIMsxsejwft7e3Iyso6cKEPm8aV/3m5vLyMmpqabQ14QghSU1O5RqNRbTabWe93NDExwa+qqspMT0/P02q1eU888YQCAFZXV7m1tbU6jUaTX1tbqzMYDFwA+OlPfyrLzMzMzczMzC0pKcluaWkJhCZeffXV6NTU1PyUlJT8v//7v2dW44Mljgyrq1BKH6WUJlFKUwE8AOAspfQhAKcB3HZ1sxMAgq7bl8lkX6+rq/vko48+GvbeC/5O65WVlRCJRGFL3A4Gf7hycHDwphe40+lES0sLKKWoqalhZSWen5+PkZERxl/0N0IIQVpa2q7eOZ/Ph8XFRVy6dAkjIyNQqVQ4ceIEdDrdnmFPLpeL6OhoxuURCCGMe5jYyP8JNcfK3t8P98oKoj/2MRAeD3aXDy9eWAcBQbFsEX95lwIxYh5evLCO9/s24fXtft9wxOIrAqJ8PtZ/9St4b8hPY7o/ICEEMpkM+fn5gSbXzc3N6O3tZTw07HA4sLy8HFY18eHhYahUqh0Xg4mJiaiqqsLg4CAmJiZYea75fD50dnYiJSWFMb0uv3HF4/EwNDTEyLy9Xi+6u7vhdrtRWVm5q7Avl8tFRkYGd25uTutwOFjtscfn8/H0008vTE1NDXZ0dAw///zziq6uLuH3vvc9ZUNDg2V2dvZyQ0OD5bHHHksEAK1W62xqahodGxsbevTRR5ceeeQRDXDFuP3mN7+Z8s4774yNjY0Nvvbaa7Kurq5bvsrxyLDam6cA/CkhZADAPwD4UjA7CQSChqSkpMd+/etfx4S7msXtdqOtrQ25ubmIi4tDXl4e+Hz+vnKb2EYoFKKkpASdnZ0BA2djYwMtLS3QarXIyclhTUE6IiIC6enpGBkZYWX8a0lKSsLy8vJNRpzT6cTo6CguXLiAjY0NlJaWoqqqCgqFYl9GCJvhQDYMNiavv1BCgYHWNSoVRPn58PoofnPJiI0tD+6tFCMuioe4KB6+fIccZRliNA5Z8V/n1mCx715wwYuNRfzDD8PndGLtV7+C72oen9frhdPpZCU3aX5+HikpKcjIyMCJEyegUqkwNDSEpqYmLC0tMfJZj46OQqfTha3ZsV6vh9lsRkZGxq7bicVi1NXVwWazoaurC549NMX2A6UUPT09iI+PZzx3zS/F4HK5DizJ4u+cIZVKg66aFAgESE1N5U1NTWV6vV7WvlSNRuM+duyYDQCkUqkvIyPDPjc3Jzhz5kzsI488sg4AjzzyyPrvf/97KQDccccdW3K53AsAJ0+e3FpZWREAwPnz5yUajcaZm5vrEgqF9L777jO++uqrt074ZQeODKttoJSep5T+ydX/36CU3k0pLaCU1lBK+/banxCSplAoXjlz5oyMzdyH7fB6vWhvb7+u07p/pSQSidDd3c1qi5n9EBsbi4yMDPT09GB+fh59fX2oqKgIS4f4lJQUmM1mVtvPAFdWiSkpKQGB1K2tLfT396OlpQVCoRD19fXIy8sL+cUrl8thMBgYN5hjY2MZ/2yYFgkNJRRobWuDd3MTMXfeCRCCtzs3ML3qxD0VsZBGOAMVgXwewacqpbivWorFdTd+ekaPqdXd585PTLwiILq+jvWrAqJstbHxJ60nJycDuHKPKxQKVFdXo7i4GOvr67hw4QJmZmb2XYXrx2KxwGw2H6gX6X5wOp0YHBxESUlJUEYCh8NBYWEh5HL5TYKioUIpxeXLlyESiaDVag883nYQQlBUVBToMRkKW1tbaG5uRkZGBtLT0/e1b2RkJBQKhWBqaiojHAvt0dFRwdDQkPjEiRPW9fV1nkajcQNXjC+j0XiTi+1f/uVf4k+ePLkJAPPz8wK1Wh2IcyclJbkWFxdZ9bYxwVETZoYhhETK5fL33njjDUW4Hkh+fD4fOjo6kJSUdNPDkBCC7OxsjI2NoaurC2VlZWFbhe6GWq3G5OQkxsbGcPz48bDlcfgfbl1dXaivr2f1s9BoNDh//jxMJhOcTicyMjIY0+XhcrmIiYmByWRi9AUulUpDfujvhL8ykKnFxn5DgT6bDZaLFxGh0yEiPR3NI1Z0TtpQnxuJknQJpqZWb5JaKE4TQyXj4zeXjPivc2u4rSAa9bmR4Ozw3QkzMiC9916YXn0Vptdfhz43l5WFgr89znZabhKJBAUFBXC5XJiensbFixeRlJSE1NTUfd1fQ0NDyM3NDYt+FKUUvb29yMnJ2ff1odFoEBUVhba2NhQUFCA+Pj7keYyPj8Pj8QSS5tnCnw7R1tYGPp+/LwkZo9GIvr4+lJSU7J07+41vAL29N/06HiCRDke0y+stiCBkfwl6+fk2vPDCfDCbbm5ucu67776Mp556al4mk+25ov/d734X9eKLL8Y3NzePANh2wUgIuTXCLrtw+G/WjxBX29W8+fTTT6dUVFSE9diUUnR3d0Mul0Oj2bmqNjMzEzKZDB0dHSGvZJnCX+GTkJAAsVgctmbJfiIjI5GYmBhS5V6wGI1GdHZ2ArhS2VRXVwelUsnoy4qNcKBQKITT6WTUE8a05MJ+Q4GWixdBnU7E3HknRhbteLdnE7lJQnys8Eq1l9Vq3VbDShHDxyN3ypGfIsIH/Wa8dGEdNufO9464sBDRd955RYKhpYUVj9XMzMyejdMFAkFA5Z3L5eLSpUsYHBwM6jtYX18HISQs3RmAK+cjEolCzmeSyWSorq7GyMgIpqenQ7puZ2dnYTKZUFRUFBZjksvlorKyEtPT01hZWQlqn8XFRQwMDKC6uvrABUkRQiG8hAjclLLiYHE6neTuu+/OuP/++41f+MIXNgAgLi7OMzs7yweA2dlZvkwmC8Rw29raRF/5ylc0p0+fnkhMTPQCQEpKynUeqoWFBYFKpWI3OZYBjjxWDCKTyb5z7733Vjz88MNhdVVSStHf3w+JRLJnbgIAZGRkgMPhoKOjY9fWDGxisVjQ1dWFrKwsKJXKQBl5ZGRkyGXNoaDT6dDY2AiVSrWn4vZ+MJlMGB0dDbToEIlEaGpqAqWU8Ye2XC4PJMMyOba/OjAYwcxgYNqw2k8o0GMyXWldU1KCdYEMr140QCnj474aacD7tJNhBQARfA4+UyNFqjwC73Rv4KdnDPizOhmS47e/1SPr6uAymRDb0QFHUxMEJ0+GdpLb4HQ6YbVag5ZP4fF4SE9PR2pqKhYWFtDS0oKEhARkZGRs6/GilGJoaAglJSWMzXk3zGYz5ubmcOzYsQONIxKJUFNTg/7+fvT19aGwsDBow3tpaQkLCwuorq4Oqyefx+OhqqoKLS0t4PF4O3rbKKUYHx/H+vo6amtrg/c8PvPMjn8iAAQeD0ZHR3kZGRnjQqGQsdJSn8+HBx54QJOZmen4/ve/HyiVveuuuzaee+65uB/96Ecrzz33XNypU6c2AGB8fFxw//33Z7zwwgvThYWFgYfEiRMntmZmZoQjIyOC1NRU9+uvvy576aWX9tbqOWSOPFYMQQgpT0xM/Nazzz4bFe5j+5Mgs7Ozg94nLS0NSqUSbW1tjCZ+BsP6+jq6urpQWloKpVIJ4EoVSVlZGbq7u8OmUQNcccnn5+czVjW5ubmJtrY2jI2NITs7G5WVlYiJiYFAIIBCoWAl0ZzD4SA2Npbx8nOm9awO02Nl/uADgBBwak/gpYvrEPIJPlcfBwHvw/1dLteubZIIIajQSfDlO+TgEOD5PxjQPGLdKVwBe3Ex3OnpsJw7B0tj4/5PcAf8Sev7NaI5HA5SUlJw/PhxiMViNDU1bVsdu7S0hJiYGMYM6t3wer3o6elBSUkJIws8LpeL4uJiREZGoq2tLajK37W1NUxMTKCysvJQFpkCgQBVVVW4fPnytlWdPp8v0A4smHY6+4HH40Gj0fCmp6d1Pp+PsVXZ+++/H3n69Om4S5cuRWVnZ+dmZ2fnvvLKKzGPP/748rlz56I1Gk3+uXPnoh9//PFlAPjud7+r3NjY4P31X/+1Jjs7Ozc/Pz8HCFQXzp06dSpTp9PlffrTnzaWl5czK4jHAuRWqRL7Y4YQEqNUKkefeeaZhHvuuYdVsb4bWVhYwMLCAiorK0Naac3Pz2Nubg6VlZVhyW9aWFjA1NQUKioqtpUT8DeSDvfKsa+vDzKZLJAMvF+sViuGh4fh8XiQnZ29rTfB4XCgra0Nx48fZ9xrpdfrsbKygsLCfcms7YrBYMDKygoKCgoYGU+v18NgMCAvL4+R8VpaWlBSUrLn/eZaWoLh3/8dEceO4zUUQr/hwRdvj4dK9qER5fV60dTUhOPHjwd1bLvLhzdaTRhZdCA3WYhPV0ohFFx/vXZ3dyNVowHOnYO9vx8xp04hsrZ2/yd6DZRSXLhwAXV1dQe+X30+H+bm5jA9PQ21Wh3wdl+8eBG1tbVBt245CAMDA5BIJPtOwA6GpaUljI+PByRntmNjYwO9vb2orq4O63N7O8xmM7q7u6+bi9vtRmdnJ+RyOTIyMoJ6boTSemh5ednncrnWNRrNXEiTv8Xo6+uLLyoqSj2s4x95rA7I1byq/++f//mfZQ0NDWhpacHa2lpYjr22toapqSmUl5eHbIQkJycjNTU16NVdqFBKMTY2hoWFBdTU1Oz4oEtMTER8fDyGhoZYm8t25ObmYmJiYt/eMqfTif7+fvT09CAtLQ01NTU7hmiEQiGkUmnQ+RT7IT4+Huvr64zmRMXGxjIquXAYoUBK6ZXWNWIxPhAWYWndjc/USq8zqoDgmi9fi0jAwYP1MtxZHI2RBQf+/V09lk0fXjuUUmxubkIqk0F6770Q5uZi88wZWNvb93eSN2AwGBAbG8vIIojD4SA1NRXHjx8Hh8PBxYsX0dPTA5VKFRajanV1FVtbW6xpZKlUKhQUFKC1tXXb3pdWqxU9PT2oqKg4dKMKAKKjo5GXl4eOjg54PB7YbDY0NzdDo9FAq9WymveVmJjIcTqdMqPRGMPEeEtLS4qBgYG8gYGBvKWlJfbLvG8xjgyrAyKVSv/6rrvuqnrggQf4/nLnkZER1ntaWSwWDAwMoKKiYldRuGDwr1ZbWlpYCcNd68oOxjOm0+lgt9sxNxe+xROfz0dmZiYGBweD2t7r9WJ8fBwtLS2Ii4vDsWPHgqpG8jdnZvra4HA4kMlkjDaq5fP58Hq9jMlzHEYo0DkxAefUFPqL7sHgogu3F0UjJ+lmo363/KqdIITgWE4U/tfH4uHxUvznewZ0TmyBUnpdGxvC5UL2mc9AmJWFzbfewlZ3976Ocy3BJK3vFy6XC61Wi4qKioCXku1CEofDEcjjYtNgkMlkqKioQE9PD1avUcV3OBzo7OxEaWkpo7mVB8VffNTa2orW1lYUFBSERe7iqpgxd3l5OdXpdB7Iat/a2hKur6/Lc3Nzh/Py8gY3NzdjbTYb+5b6LcSRYXUACCGFcrn8seeeey5g5ft7WvmVz9kwVBwOR0Ay4SBNia9FqVQiKysLra2tjL78/G0hJBJJ0MmkhBCUlJRgZmaGdZ2pa1GpVHC5XLu+VCilWFhYwMWLF0EIQX19PdRqddAvB7FYDIlEwopXU6VSMZ7DFR0dzZiat0AgYPR+2Etugfp82HzvPUwqi9C8EYOSNDGO5WxjPPl84P3kJ5D17SlRty0aeQT+6pQCGkiORTcAACAASURBVEUEftuxgddbTVhaMVwns0B4PMg++1lEaLXYePNN2EI4lsPhgNPpZK091czMDPLy8lBeXo6ZmRm0tbXBarUyfhy/tEJubm5YPGORkZGoqanB+Pg4ZmdnAwLK/kbmtxp8Ph9WqxUxMTFh7e/K5/ORkpLiz7cKeRy73S4Si8VWLpfr43A4iIyMtJhMplte1JNJjgyrECGERCYkJPz2zTffjLvRuPEnRCcnJ6O5uZnRcIrH40FHRwfy8vIYr55LSEhAdnY2WltbGWln4lcGVqvV0Ol0+1qZ8ng8lJeXo7e3l/HmvTtBCEFBQQEGBwe3laIwm81obm7G+vo66urqoNVqQ0p21el0B1Zd3o74+HgYjUZGBWCZTGDncDiMe+p2u6ZsfX1YMAPnpFXQyAX4ZEXszdt7vcCXvgTFk08i/vOfB156KaR5SIRcPHwiDifzo9A/Y8dv+zlwcq9/KRIeD3EPPghBaipMr79+RY5hH8zOzjKuBO5na2sLRqMRycnJkEgkqKiogE6nQ3d3N4aGhhgtcJmamkJkZCQSEhIYG3MvIiIiUFNTg+XlZZw/fx6ZmZkH0rtii8nJSUxNTeHkyZMghATVrH47Qr3PoqKiEB0dHbG4uBi8sNYNiEQi+9bWVpTb7eZ6vV6O2WyOcblcYauUv5qEf6gq2EeGVYgoFIoX/+Ef/kG5WyWeSqVCeXk5+vv7Q9ZWuRa/VpVGo2G0MfG1KBQK5OXlobW1FfarbTlCweFwoKWlBRkZGSEnhIvFYhQUFKCzszNsmltisRjJyckYG/uwJaTb7cbly5fR19eHvLw8FBUV7Vo9thdRUVHg8XiMV/H5e8gx6Q1jo7VNOApmqNuNxfOteC/l44iR8PBgvQw87g1GlcsFPPgg8POf4+XUVKzn5gIPPQQ8+2xIx+RwCE4WROPzx6VweTl4sdGCVy6tY93yoVFC+HzEff7zECQnw/jqq7APDwd3PpRiaWkJarU6pLntxfDwMLKzs68zPGUyGerr6yESidDY2MhIm5zNzU0sLi7uO7maCfznFhERAZPJdMu09wI+lMzZ3NxETU0NIiIiUFxcjNXV1X03jBcKhQfKt1QqlRybzRa/sbERUoW7RCJxJCQkrIyOjmaOjo7qRCKRLVxt3Xw+HzEYDDEA9rdqYZijqsAQiI2N/fLtt9/+T6+++mpQfmSv14uBgQF4vV4UFRWFnBM1MjICr9fLWFXVbhiNRvT396OysnLf7VZsNhva29uRl5fHiAE4NTWFzc1NFBcXh00F+tKlSygsLITFYsH4+DjS09NDKnHfCZPJhLGxMVRVVTEynp+1tTUsLCyguLiYkfF8Ph8uXryIhoYGRsZrampCRUXFgQxTP+fPn99xXmsXLuFXUzGwS6T48qkEyKNvSBux24HPfAZ45x08JhHjiS0bIgBcSFKhamEJeOwx4PvfB0L4vg0GAxaWVrDB1aBp2Aqvj6JSJ8GJvCiII654OH0OB9Z++Uu4l5cR9+CDEGZm7jrmysoK9Ho9o1WffkwmE0ZGRlBTU7PjNk6nE0NDQ3A4HCgoKAhJisHr9eLSpUsoLS1FVFR4VWn8/f+ioqKg1WoxMDAASikKCwvD8kzZDY/Hg66uLsTGxiIzM/O6+bhcLjQ3N6O0tDToCIXb7cbCwsKBPP1erxerq6temUy2zOFwDrSqNZvNsVwu1yuRSCwHGSdIfAAuezyeL5WVlenDcLztoZQe/ezjB0B2enq6wWKx0P0yOztLz58/Tzc3N/e979LSEm1ubqY+n2/f+4aK0Wik586do/s5183NTXr27FlqNBoZm4fP56Pd3d10cnKSsTH3Ynl5mb799tu0p6eHOp1OVo7R3Nwc0rWwGz6fj549e5Z6vV7Gxrxw4QJ1uVyMjNXZ2UnNZjMjY507d27b37ssVvofP2ulj700RyeW7TdvYDZT2tBAKSF0+PHv0OSyTPqVM/9Ij3/jPsrncejvtGpKAWr43w/RLZdt3/O6fPkyXV5evnIom4eebjPSx15eoE/+9yK9NGSmbs+Ve9hrs9HVn/yELjz+OLVPTOw6ZktLC+PXCqVXrpdLly7RjY2NoLZfX1+n58+fp6Ojo/u+xnp7e+n09HQIszw4ly9fpgMDA4Hnp8/no8PDw7Sjo4PRe2W/2Gw2euHCBTo3N7fjNpubm/TcuXOsPYd24ve//71XoVC0AuDQ/b8nFVf/mwJgBIB0v2P8Mf8chQL3ASEkQqFQ/O6NN96ID2XFlpKSgpKSEnR3d2NhYSHo/cxmM0ZHR1FWVhbW1ZVUKkVJSQk6Ojpgsey92NjY2Agk1TOZdEkIQWFhIZaWllivVqKUYnJyEiMjI1AoFAFxTzZgI9eKEIL4+HhGP6fY2Nhty9VDgenKwO14690JzIuT8IkcPjISbyijNxqB22+H7+JFLDz/DF75YjG+9eb/xZ8rP4YzT7+MV1rOYO2d/0TrX30K8f/xIoY/XofnF9/BBcsgll1G/0tjV9bW1gL5O1EiLj5VKcVXTimQHC/Au71mPPv2KgZmbSBCIeK+8AXw4uJg/PWv4ZyZ2XY8m80Gj8fDSkeClZUViMXioJO4/eFBALh06VLQYeLl5WU4nc5d222xxcTEBBwOB/Ly8gLPT3/vVKlUivb29kNp77W5uYnW1lbk5eXtmi4RHR2NrKwsdHV1BXX9McWpU6c4n//853Pj4+MfC2H31wghQwB+B+CrlNLwVSHdAhyFAveBQqF45pvf/Ob/fvTRRw9Uiud2u9Hb2wuBQID8/PxdE6BDcQUzjdlsDhhMO83BZDKhr68PFRUVrJUv+/O2KisrWTmGxWIJCIVmZWWB0ishwaqqKsaqL6+FUoqmpiaUlJQwej7r6+uYm5tjrCXJ/Pw8HA4HdDrdgccaGxuDRCIJ5ApRSuHxeOB2u+HxeODxeAISDz6fL7AC9Pl8V6QLCAGHwwEhBAMDAygpKQGPxwv8dA9v4MyIF6W8FXz6/rLrD766CnrnnfAODuJPvV6Q//cv8fHPfRq3OXUgTh+0Wm1gUx+l+Kk2HV+dmkF3RhJ+97vvwRstQRRHBJ1QiUyhChkRiYjgXB9i9Ffs1tXVbXv+E8sOvNdrxsqGG+o4Pk6VxCBJ5MbaCy/AazYj/gtfgOCGl+zw8DAiIyNDzlXcCX+YN9Tr23+/SKVSZGdn7/gcs9vtaG1tRV1dHWuLlJ2Ym5vD0tLSrgLKs7OzgW3Cpby+urqK4eFhlJeXBx1WHR0dhcfjCUsqiB+Xy4WCgoL1sbGx/5+9846PtCzX//edkkmmpPdkk2x6smmbZLPZ7C5LL2IDQQQ5gAcUxKP+PAoqNhT1oHjAigc9lgOoNBURkb4tyab3Xja990kyNTPP74/ZGTa76ZkJCl6fTz6zm5l555k37/s893Pf131dFwghdlZc8J8Y/wqsNghJkvKzsrJeqampCXTHzSeEoKenh8HBQfLy8lZcWO12O+Xl5cTFxbmsX94uzM/PU1VVtaKjujOo2gofa7OYmZmhsbGRoqKibet3OSGEw4fLqVx+9vcbGxujv78fT5lqj46OMjY2RnZ2ttuOKYTg2LFjHDlyxC3q9U5V+c2cA7vdjtFoxGAwYDAYMBqNmM1mZmZmsFqtLi0zSZKWBUbOH2fwdHYg5TyuM9Dq6+sjOjraFZCNzMupGgkmenGQlF167N4qlEolKpUK7fQ0u++8EzEwwPtsNmZvuZSPP/gFbgm7mJ72LgICAs4zAB4cHOT5972PT9bV0ahW0/nsY9gL4+gyjWIWVuTIiFWFkKSKJNk7kmCFjsHBQYxGI8lrcKbsdkF9r4HXG/TMG+2kR3tzcaIc+9O/xW4wEHzbbXid0S6y2+0cP36cCy64wO2Lfk9PDyaTaVtEcuc81t/fT1ZW1nmG00IITp06RVJSkscablbD6OgoXV1dFBYWrjtX7GRw1dvby+DgIPv27duU3IQQgsrKSiIiItweZK+Furo6rrjiitbx8fEsIcTO+p/9k+JfgdUGcKYE2HrixIndKSkpbj32zMwMdXV1pKamnhc8NTc3o1AocPdnbhWLi4tUVlaSnZ3tKvXtZFDlRH9/P2NjY+Tn52+7NLq4uEhtbS3BwcEkJyevGIhUVVURHR193sLrDgghOHHixJq2G1tBU1MTwcHBbhmzM1C76BwjYSEEJpOJ+fl5FhYWXI9WqxVJkvDx8UGtVrsevb290ev1LCwsbHvXvbS0xKlTp1xlqYk5K794ZRzN4hQ3R00SfPnFCCGwWq1YWlpQXX015rExrrDZ8P7SR3jfv19P5rA/ciHDbDYTFhZGUFAQWq0WrVbrCvyEEJR/8YvsfeghOoDp3/+eQx+5gX7LJJ2mYTpMw4wvOcqkAXItAfMKLgvKJSpwfSkBy5Kd0rYFilsXWLIJ8mOU7Cl/BpVpnpCPfQxleDjDw8PMzMy4PUthtVopLi7m0KFDblFxNxgM1NbWurK9zvuoq6sLs9m8o1kWcGRtm5qaOHDgwIazZJ4OroRwmFsbjcYteyMuLS1RUlJCdna2x/TMVsJ99923+Itf/OLhycnJrZQF33X4V2C1AYSGhv7oC1/4wsfvvfde99eDcKRba2pq0Ol0pKWlIZPJGBoaYmhoiH379r3tXStnw9nx5+ym2emgyommpiaUSuWWg04hhMsnbaWd9tlwliDdtQidi6GhIWZmZsjIyHDbMaenp+np6SEvL2/9F28AJSUlpKSkYDQamZubY25uDovFgo+PD1qtFp1O53pcayGbnZ2lt7d3212LC4YZyqpf4NLDt7JotvGLVyYwLxi4duhvJH7648icFiVNTXDZZVhNJo6YTYR9/3Y+dOP13BB4CKUkRwjB0aNHSUtLY3Fx0RUgLi0todVq8fPzw8/PD2VxMZqbbsIrIgLp9deZDgx0XTOzS4t0nAmyOo3DhHn587GQS/CRbWxBXzDaONo0T1X3Il5yyJ2qI2O2mfB/v43Kri6ysrLcbojc2tqKt7e3W+1knJnfsbExcnJyXN3QBw8e3FHfz7m5OWpra7dU4vRUcGWz2aiurkar1ZKWlratOd25wS0qKtqx0qrFYiErK2uqvb39iBBiY/YU72L8K7BaB5Ik5efk5LxcVVUV5MkUsXNSmpiYICUlhaamJrcYrXoCRqORkpISAIqKinY8qIK3yqS7d+/edFbGbDZTX1/v4rhtpKTY19eHXq93myHx2RDCYazrzonSmWXaagnJarUyMzPD1NQU09PTzM/Po9FoCA8Px8/PD39//y2N1Wg00tDQsG2ZiabuF+gaepmcpFt5ozmewUkz7zv9PMmX7EPrPHZVFfbLL0fm40PFnx/lGfUY+yLT+VDAARSS45w4z/25sg1CCBYXF5mdnWVubo7Z2VlUjY1kf/nLIJPxPoWC4Msu45FHHnGVuPR6PcW9tVQGjRLpFcgtQReex8FaC+NzVl6t09MxbEK3tEDBbB3eKYHsv/yybZ2rc2E0Gl1m4J4IeJzGxmazmaKioh2VVlhcXKSiooJ9+/ZtORh1d3BlMpmorKwkJibGbeT9kZER+vv7KSgo2JGNt8lk4rnnnuPee+/tGRkZSf5XSXBtyO+///63ewz/sDhTAjz20ksvRXmaHyBJEkFBQahUKioqKkhKSiIoKMijn7lVGI1GRkZGkCQJf3//t8VrS5IkwsLCqK2tdZ23jWBiYoLq6moSEhJISkra8MLi5+dHV1cXOp3O7UR2J5doYmLCbWrQkiRhMBiw2+0bWtiWlpaYmJigt7eX1tZWhoaGsNvtBAQEkJCQgJ+fHzKZjJSUFDQazZYXHJlMRk9Pz7YXGB+vCAZHGjnVHcTIXDCXzVcSywwBH/wgkkwGJ0+ydOmlDC4s8Ouvf4qGokDyA1O49qygChwLxtTUFNHRy4WmJUnCy8sLX19fQkNDiYmJISIvD+Nll6F45hk+PD3N/zQ2ct9jjyGXy9mzZw/j4+NEaIJICo7h1EI7g9Yp9vjEIJc2do1pvOVkxamJDVHRP2OjURGDfcZEZkY4Mrn7AqCmpibi4uI81gzj7e3N9PQ0MpmMyclJQkNDd4QUbjabKS8vZ+/evdv6bv7+/tjtdtrb24mMjNxW4DI/P09lZSVpaWluFXfV6XTMzs4yPz+/ZrZ9uxBCMDQ0RH19PQcOHMBisXi1traq7r333qMe+9B3AN4RcguSJMklSaqVJOnFM///rSRJPZIk1Z352VLdISQk5KEvfOELEWsRUd2N0dFRkpOTGR4epr29fUfbazeCxcVFqqurKSgo4ODBg7S1tS0zN91JeHl5kZubS3V19boedEII2tvb6ejooLCwcNPNAE7Jh8bGRrdaxjixa9cuRkZGsFqtbjtmVFQUw8PDKz4nhGB2dpb29naKi4spKSlxLYIHDx7k8OHDZGRkEBkZibe3t9usbeRyuXvOn5CYM13LlCGTXb5l7Bqtxu/SS5EUCnj5ZZYuvZROg4GPJMcxcNEu8tWJXBNQeF6QsxnzZUmS0ObloSwvxychgTcUCu4IC+Pee+/lyiuvpLa2ltHRUTTjdt6rzeW0eYxnp0uwic193/hwFZ+4MpRUqZdu71288Gq32+YBvV6PwWDwCF/QieHhYWw2G0VFRcTFxVFSUuJ2l4Fz4fT/27Nnj1u4R7GxsQQHB1NbW7vlc+/cxOXm5i7zjXQX0tPTGR0d9di5NZvNVFZWMjExwaFDhwgNDeUb3/iGJjg4+JOSJLmPt/AOxDsisAI+C5zrDXGPECLnzE/dZg8oSdK+qKioj/7nf/6nR3hVK2FwcBCr1UpSUhIHDhxgaWmJ8vJyjxg5bwVGo5HKykr27t2LVqtFpVJRWFhIR0fHpm0X3IWNaLyYzWZOnTqF3W7nwIEDW8446XQ6wsLC6O7u3s6QV4RMJiMmJoa+vj63HdPPz4/5+XmXRs8ZNWXq6+s5duwY3d3dLl+4I0eOsGfPHkJDQ1csjXp7e2M2m922wG/3OO3DFtqmAkkOXyJE/QY9+VZU6WmI557DdvXVNFos3F20lwue/wqXJxTyPv98ZCtkHjYTWLmwaxecPIksK4uHurt5/ZZbiIiIIDg4mNTUVCwWC5amCVIn/WkzDfHM+Els9s3pJI2OjrI3K4C8pR5q9VrerHXP4tnc3Ex6errHykdGo5H29nays7ORJInw8HD2799Pc3MzXV1dHtko2mw2KioqSExMdGvnYWJiImq1moaGhk2Pu7+/n7a2NgoLCz2WGZTJZOTm5lJfX+92bbihoSFKS0uJjY1l7969LkqKUqnk6aefDgoNDX1OkiT3tGW/A/FPH1hJkhQNXA38rxuP6R0aGvr0M8884xZphY1gfn6erq4u14Qkk8nYs2fPju341oPFYqGiooLMzMxlO0IvLy8KCwvp7u5maGjobRlbREQEgYGBtLScL7MyOTlJaWkpiYmJrsaA7SAxMZGhoSEWFxe3dZyVEBsby8DAgNvECp1ioW1tbVRVVXHy5EkmJiaIioriyJEj5OXlER0dveEyqkajccv3VigU2zb11RtsBPlYuVrWT2yHhlntPCOPfAFuuIFyu52vf+gyin73OS6L3MeVfntXDSS2FFgBBAfDG28gXXQRlzz+OI/v3UtISAh6vZ7vfOc7pKamcl3aJeyzx9K6NMwv216kuaWZubm5DS3SfX19xMbFcdXlSaTMtXO83URF58Lmx3kWxsfHUSqVbhXvPRtCOLxMs7KylvHv1Go1Bw8exGg0UlFR4daNohCC6upqIiMjiTwjUeFOOP0TWzfh6dja2sro6CgHDhzA29t7/TdtA2q1mrS0tG1l1s6G2WymqqqK0dFRDh48uKJRdlZWFp/4xCeig4OD79/2B75D8U8fWAE/BO7lfDfr70iS1CBJ0iOSJG1cLAQIDQ196J577gl3hyDiRmCz2aipqVm2M3AiPDycgoICmpub6e52X0lgM3Cm2VNTU1fkfSmVSvbv309vby8DAwM7Pj6A5ORkFhcXXYr2Qgi6urpcu0Z3peLlcjmZmZlb2sWuB4VCQWRkJP39/ds6jt1uZ2xsjJqaGkZHRxkdHSUpKYkjR46QkZFBcHDwlgJMd5UD3aG+nrVLxkVRkxiLT7BLl0Pu64tEfeGHmA/m8+oT/0XOD2/j8qBcLvVd2wtucXFx6xxBnQ5efBGuuw7dN75B7AsvUF5ezu9//3uys7MpKSnhfbuKOKxNZ9jPQJvfNO0d7Rw/fpz29vZV3Qz0ej1yuRy1Wo1XWBhXxZiJne/lxao5mvoNWxqqEIK2tjaPmh93dnYSGBi44hwhk8nIzMwkJiaG0tJStyj5CyGor6/Hz8/Prd2NZ0OSJDIzMzEajXR1da35Wuc8brPZ2Ldvn9t09tZDeHg4Op1u2y4OIyMjlJaWEhUVRV5e3prNKV//+tc1ISEhd/2rJLgy/qkDK0mS3guMCyGqz3nqy0AqsA8IBL64iWPmRUVF3biTJcCmpiZiYmJWtZXQaDQUFRWxsLBAVVWVW3k468Fms1FZWUl8fPyKuxcnnMHVwMCAW8tZG4UkSezdu5fu7m6mpqaoqalhcXGRoqIit5PNg4KC8PHx8UiGLj4+nt7e3i3xkPR6PU1NTRw/fpzx8XHi4uK4+OKLkcvlaDSabZd//P39N2xhshbcEVjZ7Xa07W0IiwV5ZRUxDzxO7944/ufRj2K/KJar/HM5oltbO8lmtmPrV+Cl2NS+azlUKnjqKSaLitB9+9tcl51NWVkZGo2GSy65hPvuu48jPmkUaJKoZxBDiiN7o9FoaG5u5uTJk/T29i67p/v6+oiLi3P93//ii7h89hSRtmn+eGqGrpHNm+sODAwQGBjosUaT6elpxsbG1pU/iYiIID8/n9ra2m3fP21tbchksjXFWN0B59wyNTW16txmsVgoKysjMDCQjIyMHZfISUtLY3x8fEuVDYvFQnV1NUNDQxQVFW2If3pOSXBnyjr/RPinDqyAg8D7JUnqBZ4CLpYk6UkhhMMBVQgz8BugYCMHkyRJFhoa+uSTTz4ZtFO6K2NjY5hMpmUT6UqQy+VkZ2cTERFBSUkJer3e42MTQlBXV0d4ePiGOloUCgX79+9nZGSEnp4ej4/vXCiVSjIyMjh16hS+vr5kZ2d7TD8nPT2dzs5Ot/PflEolYWFhG150rFYrvb29nDx5ktbWVoKCgjhy5AiZmZkEBgYik8kICwtzS4PBP1JgtTQ+jldHB/bycgJ++EOeVSj42T23M+0fTNLcOPu849Z8v81s5/QTk2ibIuj+9STm6a2XJk1WK6fvvRfJ2xvuuIPcnBxqamq4/fbb+a//+i+++93v8h6/PHJ84nhzvpFKczfR0dEUFhayb98+rFYrJSUlVFdXMzY2xsTExLJNjMzbm8DLLuHyrr8QqLTyVPE0Q1Mbv+5sNhvd3d0eC0CsVisNDQ3k5uZu6H7TarUcPHiQwcFBWlpatpT57e7uZnFxkczMzB0JYmQyGfn5+QwMDDA+Pr7suYWFBUpLS0lISPBY5mwj49u7dy8NDQ2bKrOPjo5SUlJCeHg4+fn5m1KCz8zM5Oabb4709/f/9FbG/E7GP3VgJYT4shAiWggRB3wEeFMIcbMkSREAkuOO+yDQtJHj+fr63vXhD384Mj093WNjPhtms5mWlhZycnI2PDlER0eTl5dHbW3ttktG66GtrQ2VSkV8fPyG3yOXy9m3bx/j4+MeIXmvhampKRoaGkhNTWV8fNwj3XtOeHl5kZycTHOz+7Xy4uPjOX369JoLjl6vp76+npKSEqxWK/v27WP//v1ERESct7hFRUUx1tAA2zwfSqXS5eO3HbgjsBJPP43x2WfZ9cor/M7Hh6aXfoT6gkQuU8Whm+ygtuOJVc+fzWyn54kpDANWbIkLWKaW6Pj5OLNNWyuzTUxM4J+WBg8/DCdOwGOPodFo+OUvf8nzzz/P5z73OWSSxIWyVNJUUbw8V0v1ouPe8Pb2dpVpd+/e7QrWe3p6lmWx1NnZaCNDuer0C6i9JJ44NsWEfmOZ6+7ubnbt2uUxMcnGxkYSEhI2lQ1TKpUuDaaKiopNZeGdwU1ubu6OZoacc1tLS4urlDk1NeVq6PFkp+VGoNFo2L17N01N6y93VqvVtYYUFRVtWQriW9/6lk6r1d4nSdLO+hX9g+OfOrBaA7+TJKkRaASCgW+v9wZJkgK1Wu03vvvd7+6I07GTH5CWlrapXQI4utMOHjzIxMQEtbW1HnFm7+vrY35+fktWFM4JaHp6mo6ODrePbSX09/fT0tJCYWEhiYmJhIeH09jY6NHPjIyMxGw2Mzk56dbjOuUNRkdHl/1eCOHiQbS0tBAeHs6RI0dISkpakyTr+9e/svfqq7EfPgwNDdsam6+v77azpdsOrIRg6emnSWpr47eBgfSd+DlSeiDXBxZxOKSIPbs/yPBkLV2Dr533VmdQtThowfcyCXWBIPmToXiHKOh7ZoaBF2awWzeXQRkfH3dw+G67DS6/HO69F86UjD7wgQ/g5+eHyWTioiMX8pdPP0qEScsLsxU0Gt4qK0mSRGBgIEIIioqKsNvtlJSU0NDQwPz8PJJMhv/VV+MzP8W1ilYkCR4/OsWcYe1732w2MzQ05LFMyuDgIEKILXnXSZJEWloau3btoqSkZEONEWNjY/T29rJv374dVXN3QqVSkZ+fT01NDT09PTQ3N1NYWLgqjWOnERMTg8ViWbNLe3x8nOLiYkJCQjbtV3guNBoNDz/8cEBYWNjPt3yQdyDeMYGVEOKYEOK9Z/59sRAiUwiRIYS4WQixbjtNWFjYTx966KHAnVIJ7u/vx8vLa8u7HIVCQW5uLgEBAZSUlLCwsL2OobMxPj5Of3//tnaEMpmMvLw85ufnaWtr8xjp3knKdXbhOPlU8fHx2Gw2j5YkndpWTU1Nbg9uExMTXe3pS0tLnD59mmPHjjE5OUlWVhaFhYWEhYWt//f561/hNfolPgAAIABJREFU1lsxp6UhWlshNxc+/3lYhTi9HtxBYN9uYGUzGHhxcpL7gYmSR7FGeHNj4GEyfGIASIy+lMjgXJp7/sL4TNtb7zsrqIq9LhBbuAGNRoNXgILE20MIOaRluspA52PjmMY3lkERQqDX6x0LqyTBY4+BEHDnnY7HM1AqlXz4wx/muWef43uXfBpz7Rh/nDlFu+mtku/s7CwqlQpfX18SExM5cuQIoaGhNDU1UVZWxry3N+rcXJSVJ7gxW4bJYufxo5MYzKtfe+3t7SQlJXlEoNNgMNB1xnJnO4iMjCQnJ4eKioo1r63p6WlaW1spKCjYMWL4StBoNAQEBNDa2kp+fr7bOZzbgSRJZGdn09bWhsm0nItntVqpq6ujp6eHAwcOEB0d7ZaM33XXXaeIj4+/SJKk7dkpvIPwjgmstgNJkvJiYmIuv/HGG3fkbl1cXKSnp2fb3nCSJBEXF0dWVhZVVVWrikFuBnq9npaWFrdMXk6dFaPRSGtrq9uDK7vdTk1NjasUdvZ4nRPM4OCg2zNKZ0OtVrNr1y63Z+acpsW1tbWcPHkSm83GoUOHyMzM3Lg8wLFjcP31sHcv1tdeo+6pp+D22x0lq9RUeOaZZYv/RuAOntV2A6uZjg4+MztL6Weuw+Qr8dGgC0jxeauUIUkSuSk3o1OHU9X6KwymqfOCKv8Mn2VSC5JcIvJyP3b/WxBLi3Y6H5tgqmZx3WtWr9ej0+neWqDi4uDBB+GVV+Dxx12vk8vlfOUrX6G4uBi5XM5DH/g8VT/6G78fO85ps4P/di5p3akDdeDAAdLS0hyq+DodKBT4nPw7Nx4OZHphiSePT2FZOr88u7CwwNzcnFsVv51w3ntZWVlusd3y9/dn//79NDQ0rJhtcZa+CwoKtpVh2S7sdjt1dXWuTVV9fb1HKQdbgUqlIj09nfr6etf1OzExQXFxMYGBgRQUFLhVBkKSJH7zm98EhoWFPf4vIrsD7/rASpIkWVhY2BO//e1vg3aiXm+326mtrSU7O9ttuy5/f3+KiooYGBjYljK4yWSiurqavLw8t01ekiSRk5OD1WqlqanJbcGV1WqlrKwMf3//VQmscrmc/Px8GhsbMRi2xp/ZCHbv3s3ExITbGgrMZjPNzc3o9XpmZma44IILSEpK2twCVlUF738/JCTA3/+OLjKSBZUK609/CqdOQWgo3HADXHEFbCIo9PPz23ar/HYDq/JjR7ELQVheIv8WdCGJ3ud3MSnk3uxP/wR2YaO8/tecfmJiWVAFK2tY+SZ5k/zJUNTRSgafn6X/jzPYzKvfTxMTE+dLedx9Nxw6BJ/7HJxTzi0sLKS2tpaPfvSj9L/agL+k4fdTJ+g1jDIzM7OqwKWfnx95eXnkFBaymJ6O5fRpvDoquL4ogKFpB6F9ybb83mppadm24e9q6OjoICQkxK12Kmq1mqKiIk6fPr2Mn2kwGKiuriY/P/9t8SV1wjnn6HQ6srKyiI6OJjg42OOUg60gLCwMHx8fTp8+TUNDA11dXRQWFhITE+OR6yElJYWbbropwt/f/z/cfvB/QrzrA6uAgIC7PvjBD+7aKcJ6d3c3wcHBbhfp8/LyoqCgAB8fH0pLSzEajZt6v91up6qqij179rjdNNW5uwPcov9kNBopLS1l9+7dJCQkrPlaHx8fsrOzqaqq2rYo5WqQyWRkZWVt+7tZLBZaWlo4deoUfn5+XHzxxeh0us0HMq2tcOWVEBQEr77qELMETNFe/HWsHLF/P1RWwo9/DOXlkJkJX/86bOCakclkyGSybUl+KBSKbZVOY+UKPnfb9dyR90HiVKvrk2nVYeyNvw11ySEWByzEXBfgCqrA4Y+4UrCq9JUTf2sw4RfrmG000vHzcQzDK3fhjY+Pnx8MyWTwv/8LBgN86lPnvcfX15fHH3+c4hMnuSPqcuQLNu773Q9Q7fJfd9FTq9UkfeADyENDsZeWMtlZxuFE6Box83z5DPYz19/U1BRCCLd5T56NqakppqamPNJlqFQqOXDgALOzszQ2NmIymaioqCA7O3tHzZzPhcFgoLS0lLi4OBITE11/p8TERJaWlujt7X3bxrYawsPDaWlpwdvbm8LCQo+XLB944AEnkd39F90/Gd7VgZUkSYFqtfqb11xzjba5udnj+lALCwsMDw97rO1ZkiSXwnhZWdl5bcFrobGxkYiICI94WjnHlpGRgUKhoK6ubssByMLCAmVlZWRmZm7Y7y8wMJDY2Nhtfe568Pf3x9/ff0saXlarldbWVkpLS9FqtVxwwQUu/kNycvLmhP96e+Gyy0ChgNdegzNlIIt9iWqfIeqkAVpMg47nP/1paGuD666DBx6APXvgpZc29F3dIfC4FQghCDIY+PSR95AaHLfma21mO8a/ReA9t4vxjD8zG1jles5qta6ZMZZkEmEX+pLwsWDEkqDrlxNMlC0su35sNhsWi2XlBSslBb71LfjTn+C551b8DF9fX3RyH+aebOAPn/hvvvLYdymZb3UFR6uOTS4n4L3vRW4wkLG0RJhqmgTdFA19Rv5eM4fdbqe1tRVPbBatViuNjY3s3bu6mv124aQQSJLE0aNHSUtL86jR8HqYmZmhvLycrKys89TdnRn5gYEBpqam3qYRLofNZqOpqYmuri7y8vI8SoU4GxqNhv/+7/8ODA8Pf9cT2d/VgVVYWNhPvve97/lffvnlaLVaiouLGRgY8Mji6+wCzMrK8ng3S1BQEEVFRS7l8fW+T29vLzabbVOyCluBJEmkp6fj4+NDTU3NpkuWs7OzVFZWkpeXt+mJNjY2FpVKta568naQmppKT0/PeaTR1WC32+nu7qa4uBi1Ws0FF1xATEzMsuvD398fu92+sTLj2JgjqFpcdGSqEhNdT9UYTmMSVlRWOX+brcJoP5OBiYiA3/0O3ngDvLzg6qvh2mthDSkPdxDYZTLZlrJWtpkZXqiqYkiINe8jh06Vg1MVc30AulQ5Dd3PMq0/DWxccV0bpyL5k6HoErwZfmmO3j9Ms2RwXLdTU1NrZ4T+8z8hL8+RtVpj0f3cpz7Lle+5iqMPPcs3vvcAT0wdY962dvZQFReHT2YmxrIy0qKiuP7iRBIDjZR3LPL8yT50Op3bMzzOOSwpKcnjJTkhBPPz84SEhLjmp7cDw8PDNDQ0sH///lWrDE7KQUNDw6YrBe7G9PQ0J0+eRKPRcODAASIjI9FqtR6X5nHi+uuvV8TFxV38bieyv2sDK0mS8nbt2nXFTTfdpJAkidjYWA4ePMjMzAwlJSVuEUI8G729vfj7+3vMp+tcqFQqDhw4gBCCU6dOrcppmZqaYmBgwOVR6GlIkkRqaio6nY7q6uoNB1dTU1PU1dVRUFCwZVPTPXv2MDEx4RaxzJWgUChIT09fl3MhhGB4eJgTJ06wtLTE4cOHiY2NXTVQSEpKWj9rNTvr4EsNDzuyTmd1atmEndKFNmK8grl4KYlFm4nX9fXL33/xxQ4phu9+F15+GdLS4PvfhxUEUAMCAt42AntPdTV3/fGPvFRXt+r5cgZVhjOcqoAMDXmpt+GjCqCi5ZeYLHOb8ghUaOTEfTSQyCv9mO800fHzcRb7zCuXAZe9UQG//jVMTzv4VqtgaGiI3/zq19xwww288Z0/8NTP/o9Hx/9Op2ntZhS/K65AksmYe/ll1Go1N1+eQFqkgrphL/qnhNv9LAcGBpDL5R4hw58Np+dgaGgo+fn5hIWFUV5evqOOE05LrN7eXoqKitYNJM+mHLwdQaDNZqO5uZnW1lb27dvH7t27XfN5Wloap0+f3vCGbztwEtlDQ0Pf1UT2d2VgtRph3cvLi6ysLLKysmhubqa+vt4tytoGg4G+vr517R7cDadOTEJCAqWlpeelqo1GIw0NDeTn53ukHXstJCcnExAQQGVl5boT0djYGE1NTezfv39blhxOCYjW1tZVfdq2C6cEwrkaVE7Mzs5SUlLCxMQEhYWFpKSkrNvEEBQUhNFoXH2hXFx0ZJpaWuDPf4YDB5Y93WIcYNa2yEFtGlkRycTO+1K52EWfeWL5cby84Mtfdhznssvgi1+EvXvh+PFlL9NoNNuW9/D29t5SYHXq2DEA0vPyVgyszg2qnJwqL6WG/emfwLpkoLLlV8zPz23KfFmSJEKKtCTeEYIkg67fTLJQZSfAb53MaVYW3HcfPPHEimVWi8WCXq8nLCyMJ554gmuuuYbax15BtmDjianjvDxXw5JY+f6Q+/qiO3IEU1sbps5OZJJEXuQCOpWd7oVQKquqaWpqcktAsrCwwOnTp8nMzNz2sdaCEILGxkY0Go2LPxkXF0dsbCxlZWVudzpYCXa73aUfVlhYuOGmkcDAQHbt2uVRysFKmJmZobi4GG9vb4qKis6bI5VKJenp6R7xN10JqampWyayS5L0a0mSxiVJajrrd4GSJL0mSVLnmcedyU5sA+/KwEqtVn/0/e9/f9Rq4pe+vr4UFRURHBxMSUkJPT09W74ghRA0NDS4+EVvB8LCwigsLKS1tdWljWSz2aiqqiI7O/tt02FJTEwkJCRkzeBqZGSEjo6OZRpV24FKpWLv3r1UV1d7bAeckZFBa2vrMrK8xWKhvr6e5uZmsrKyyM7O3nDLsyRJq2etLBb40IegrAx+/3uHQOVZEEJQvNBKsEJHincUGo2GuEkNfjI1L8xWrLxox8XB88/DCy84CNgXXgi33OIoNZ4Zj0ql2tYO2MvLa0uBVXlVFV4KBQkraDMtC6quD1xGVAfw00aTk3wzU/ouhmaObiqwckId5eUoDaZ44XM6iM6fTDJxamFtUdGvfMXBX7vzTjinpDswMMCuXbuQJAmlUslTTz1F+aky/l/iNRRokihdaOeXE68xaV25FKw9cAB5UBBzL72ExWRiaLCfq/ICmF4UqCNz8fX13TbFwROdzKuho6MDIQSpqanLfh8VFUVycvKa2Xd3wGq1UlFRgY+PDzk5OZumbcTFxaFQKDh9+rSHRvgWbDYbra2tNDc3k5eXR0JCwqpVh7CwMBQKxZrCoe7EAw88oPPx8blPkqTNlhd+C1x5zu++BLwhhEgC3jjz/39ovOsCK0mSvHQ63Xe/853vrPkHlySJqKgoDh8+jNFo5OTJk1siJw4ODuLj4+OR7pzNwMfHh6KiIoxGIxUVFTQ2NhIZGfm2kkLBIeQZHh5OeXn5eV17IyMjdHV1sX//frfacfj5+ZGcnEx1dbVHdnDe3t7Ex8e7tLv6+vooKSlxcd+2UsoMDQ1lbm5uOYfDZoObb3ZoJv3iFw4S+jnosYwxYp3hoDYN2ZlJNyYimgJLDBNLek7Ot67+oe97HzQ3OwKDp55yELIffRRstm3rWW2lFChsNqrb28lKSEChUCxb9M4LqvasHITvCt1HQtTFLCy1UNH+Q+o7/8DgeBVG88a/i9xbhrzIiOpSE6pABcN/n6P1kVHGi+dXlmbw8nKUBIeHHarszu8jhCuweuulXsTGxqJAzrFvP4X21Ulmlxb5n4lXqF083+ZIUijwv+oqlqam6H/xReLj49kToyE2xIujjfOERkRz6NAhZmZmKC0t3ZIkSFtbG+Hh4R6nMfT09KDX68nKyloxQAgLC3M15ngiuDIajZw6dYro6GiSk5O3TI3IyMhgeHh42zzEtTA7O0txcTFKpZKDBw9uaJOQkZFBe3v7jmT9tFot9913n19wcPDXN/M+IcQJ4Fwn6Q8A/3fm3/+Hw6buHxrvusDKz8/vP+64446ANbkRZ8HJm8nNzaWzs5Pq6uoN79TNZjNdXV0e6c7ZCmQyGZmZmWg0GoaGht72oMqJuLg4oqOjl/EoPBVUOREZGYmfnx+trWsEFttATEwM09PTHD9+nPn5eQ4dOrQtpWNnx6dL30cIuOsuePZZ+MEPHMKfK6B4vg2tzJssdZzrd0HKMNQvacix7ebEfDMTq2RDAFCr4dvfdvCv8vMdROz9+wnt69vWwuHt7b3pjJdpZISG4WH25eVht9tdGauNBlVOpMd9EG97Nj6qAAbGK6lq+zWvlN/HqxVfp6b9cfpGS1kwjq8ZdE9OThCeFUTi7SEkfCwY71AlI6/qaX1kjLET89hM5wRYBQUOntVjjzmEW3HwBn19fVe8vi0WCzU1NXz5jv9H5EkjkcpA/jxbznMzpZjsyxdG7+RklImJqJqbiQoMRJIkrsr1Y9Fs52TzPEqlkqysLDIyMmhoaKC5uXnD0iOTk5PMzs6SeFYjhCcwNDTEyMjIum4PoaGhHgmu5ubmKCsrY8+ePURHR2/rWHK5nNzcXLdRSc6G3W6nra2NxsZGcnNzl0k/rAenv+lGvATdgTvvvFOlVqtvlSQpbP1Xr4kwIcQIwJlHz7SuuxHvqsBKkiStj4/PvV/60pc2TdTRarUUFhYSFRVFWVkZnZ2d6xKvW1tbSUlJcYsysbuwuLjI5OQkRUVFNDQ00Nvbu6N8gNUQExNDXFwc5eXlDA4OejSociI1NZX5+XmGhobWf/EmYLfb6ejowG63Y7fbSU9Pd8s1EBkZyeTkpGOy/tKXHFpJX/mKw6JmBYxaZ+gyj7Bfm4zyDI/UOm9j5LlFFCMaMk/txktS8MJsxbot/qSmOuQb/vAHGBoi6OqrCfjKVxz8ri1ApVJtetGxjYxw7JOf5Atf/CJ2u93RWbjJoArAal3CT5VFUeZ/8J6ih7hw75fIiP8QfpooRqcaqe14ktcr7+eV8vuobP0Vp4ePM7c4hBCO+10IwdzcnMsfTrtbRcJtwSTeEYw6Ssno63paHxll9KieJeNZc8S3vuXo1LzjDjAY6O3tXaa0fu75eeGFFzhw4AB33PwxAkr0XOKbRbNxgEfHX2bAsryFfjg2FpkQLJzhw0UGepET58Op9gVmFhxBlJ+fHwcPHkStVlNcXLxuG77FYvG4tALgMmzft2/fhrie7g6uxsbGqK2tZd++fQQFBW37eODgIaakpFBbW+u2+VWv11NcXIxMJuPgwYNb6vqMjIzEYrHsiDSEUqnkwQcfDAgLC/u+xz/sHwzvqsAqODj4K1/84hf9tsKtcCI8PJzDhw8jhODEiROrakVNT09jNBo3rLW0E7DZbFRXV5OTk0NAQICrRFBTU+Mx8czNICoqisDAQOrr68nNzfVoUAVnrE9yc+nq6nKbLtPMzAwnT55EJpNx5MgRIiMj3ca3kCSJ3bt3M/vlLzs69u6+26E/tQpK5tvwkhQUaJIAsFsFvb+fwmawo4i1YWhe4oqFvfRZJqg1bGCMkgQf+Qi0tSF95jOE/eUviAsugC0EplspBVqHh4kOD2d3ZiY2mw1hZdNBFSxXXJdJcvx1MSRGX8L+PXdy1YHvcXHe18hOvJFgv2Sm57pp6Hqao9Xf4aVT91LW9HOaul5EreO8YEMToyL+34JJujMETayKsaPztD48ysjrepYMNkf273//F7q7WbrvPhYXF9csr2m1Wl566SXy8vK44cM3sHiyj38PvhSAX028zvH5ZuzCzuzsLAalEnVeHotVVSydWTQvyfZDkiRer38rI+m8hgoKCujq6qK+vn5FrqEQgrq6OlJTUz3KwZyZmaGlpYX9+/dvavNxdnC1naxQT08PXV1dFBUVbYlztxYiIiLQaDTLVOS3AudGra6ujpycHJKTk7cs2ePUE2xqatoRK54bbrhBHhAQ8B5Jkraj5TMmSVIEwJnHjQs0vk141wRWkiSFqNXq2+++++5tmyTJ5XKSk5PZv38//f39VFRULOvYEkLQ1NRERkbGjkgYbBRNTU1ER0fj7+8POL7H3r17XSR9T3XKbRQTExNMTEyQnZ1NdXW1R0mqTiiVSvLy8qitrd3W59ntdlpaWmhpaSEvL4+kpCRkMhlJSUkMDg66p/W9rY2YT32K0Icfxv6Rj8BPfuIIdlbA3NIijcY+8tQJ+Mi8EHZB/59mMAxbibkugLjrgrGrltAe1RKnDOWVudp1tZNc8PODH/6QjocectjhFBRATc2mvspWAqtfPfUUz3V3I0kSdotg4A9zmw6qYGUrGyckSYavJoLdkYfJT/sYl+//DpcVPEBuyi1EBuewYByje+TvjBqfo6Lll8zOn68PpI7yYvdNQSTfHYouUcX4yXlaHx5j+NU5rHmH4K67kP/kJ6T09a07P/j6+vLyyy+Tl5eH2WwmRhXM3aFXku6zizf0Dfx28ig17Q3s2bMH34suQlIo0L/+OgB+ajlFqVoa+40MTC4PPtRqNfv37ycwMJDi4mImJpZ3iPb396NSqTy6MZyfn3dJqGzFQis0NJTU1NQtSTE45+ipqSkKCws9tolLT09nZGSE6elzaUMbw/z8PCUlJQghOHTo0JalZs6GVqslNDR0R9TiZTIZP/rRj4LCw8N/so3DvADceubftwJ/2f7IPAwhxLviJyws7FdPPPGEVXgAExMT4tixY6K1tVVYrVZx+vRp0dzc7ImP2jKGhoZERUWFsNvtKz4/Ozsrjh49KgYGBnZ4ZA5MT0+Lo0ePCqPRKIQQYmxsTBw7dsz1f09jbGxMFBcXC5vNtun3zs3NiePHj4vOzs4Vz+/ExIQoLS1d9dyvi4kJIf7jP4SQy4Xw9RWT99wjOta5vv4+WyO+MfgHMWNdEEIIMfzarKj72qAYO6kXQgih1+tFXsZe8Y33PiR6KyfFNwefEk9PFW9qWB0dHWL01VeFiIkRQq0W4s9/3vB77Xa7OHr06IZfbzObRVJwsLiysFAsmWyi6gedou4bg2KmybCpMQshRFNTkxgbG9v0+5w4UfyaqO/4o/hr8efEn49/UpQ0/ERMznau+nrjmEX0PjMl6r4+KOq/NSSGnu0TCzGxwi6TCXH//UIsLa37mWdflzMzM8Jut4vqhW7xzcGnxAP9T4s+07gQQoi5N94Qg1/7mjCfuY9NFpv43p+GxS9eHV/1+jMYDKK0tFQ0NDSIpaUlodfrxbFjx4TV6pHp0vWZR48eFXNzc9s+1uDgoCgpKRFLGziPQghhtVpFeXm5aGlp2fo9uQksLi6KN998U1gslg2/x263i87OTnHs2DExMzPj9jFZrdZl862nUVBQMAlki3XWaeAPwAhgBQaB24EgHN2AnWceA9c7ztv9867IWEmSFOvn5/f+m266ySO9wsHBwRw+fBilUsmJEyfo7OwkKSnJEx+1JRiNRtrb29cUAXXyL0ZGRmhoaNhRkTu9Xu/auTolCEJDQ9mzZw9lZWU7omYcGhpKWFjYpoidQghOnz7takVfjUgaHByMj4/P5rlcZrODmJ6YCD//OXziE9DZid93v8vg2NiqfyOj3UL1YhcZPjH4KzRM1y4yfmKBwDw1IQcdmZqPf+I2qptqefDlr9LyTBsXqPbQZOyn3bTxMfr7+zMeHu7wG8zIcCi2f//7DmL9OthsJneyrY2uyUn279+PeXoJ2aLXpjNVTmxGHPRcLC0tYV9SkpV0LVfs/w7pce9ndqGfk/UPc7LuYcamW87j1HiHKom9PpDUT4fiv8eHiUY5p2/5O7Zrb4T773eIsw4Orvm5ztLPX//6V+Li4igtLSXHJ4683kA0Cm9+M/km9YZetAcPItNomHv1VYQQqJQyLs3yZWDSQvPAyveRj48PhYWFaDQaTp48SWVlJTk5OR6TVrBYLFRUVJCZmemWDExUVBSRkZFUVVWtW94ymUycOnXK1WG4ExUFtVpNcnIyDQ0NG3r9wsICJSUlWK1WDh8+7KowuBMKhYKUlBRaWlrcfuyV8LOf/SwoPDz8sfVeJ4S4UQgRIYRQCiGihRC/EkJMCSEuEUIknXncWvpvB/GuCKzCw8N//MMf/jDQk1YyMpmMhIQE/Pz80Gg0VFZWvu2lNXiLK5GRkbFuulupVJKfn49Go6G0tBSDweDx8Tmd6/Py8s5TNw4ODiYzM5Py8vIdGUtCQgJWq3VDfn9ms5mysjIMBgOHDh1yEZlXQ3p6Op2dnRvjgwjh8JdLS4N77oGDBx1deY8+CqGhKBQKoqKiVrWpqFrswiyWOKhNY6HHzOALs2jjVUS/12HyK4SdpEwvrr0xH4VK4mvPfIGE6khCFL68OFuF2b6xsopLciE83NHpdv31DlHR229fUbH9XEiStGGeR9mbbyKAwosvRh3hxVxR75aCKnBsNLbKG5qennYRnJUKH5JjruTygm+TmXA9BtMkp5p+yrHaBxmaqHWR3Z1QBSuJuTYAywVjSDo/2vIewvLjX0N1NWRnO3TD1kF+fj6hoaFcddVVvPDCC+wOiOLO0CvY5RXMH2dOcdTcjvbCI1h6ezGf0T3L2a0m3F/Jq3V6rLaVg15JkoiPj8fPz4+lpSUmJyc90tSytLRERUUFKSkpbiOKg6OzOCAgYE1xTr1eT1lZGampqcTGxrrtszcCp1r94BoBtBCC7u5uqqur2bNnD2lpaR61PwsPD98xInt+fj45OTlJkiQd8fiH/QPgHR9YSZKUERUVVXTllVd6/LtOT09jsVgoKioiLS2Nuro6tykfbxU9PT3odLq1rTfOgiRJJCQksGfPHsrLy1dVEHcHzGYzFRUV5OTkrLpzDQoKIjs7+zwemyfgNFTt6+tbkxMxNTVFaWkp8fHxZGRkbKiTydnq3NzcvPYLKyrg8GFHkKLRODSq/vY3OEeyY/fu3fT29p4XmCwJG2ULHSSowgnUa+l9agqvAAVxNwQiyR2BzMB4BXmHAnj44R/z8U99iJ7pdhpeauW9Yh96m4E39Wtb8jihVCqx2WyOMfj4ODoGv/Y1+M1vHEKl60zYTp6VEAKr1YrRaESv1zM9Pc34+DhjY2OMjIwwPDxMycmTAMQlJzM6OopVmF1SAAsLC5hMpg1lWZ3na6uZivHx8fOMyhVyLxKiLuKygm+Rk/RRlpZMVLb+kjerv03/WBl2+1vjMhqNmLwWSbo9FJlComPxSkyvlENsLHzgA/CZz8AaMhQRERG8+eabBAcH82//9m+OPEpCAAAgAElEQVRMTU2hlqu4JfhCctXxHJ9v5m8JVuwhgY6sld2OTCZxxV5fZhdtlLWvrpg/Pj6OyWTikksuwWAwUFFR4Va5ALvdTlVVFTExMYSHh7vtuE4kJyejUqlWvMcmJiaoqakhNzd3w3Ohu5GVlUVXV9eKGfjFxUVKS0sxmUwcOnRoR6zPJEkiMzNzx4jsjzzySGBERMQvpX8k4rGHIL///vvf7jF4FI899tgfn3jiidTtapOsByEE1dXVZGVloVKp8PHxISYmBpPJRH19PXK5HF9f3x0ls+v1etrb28lbxf5jLfj4+BAZGemyfwkKCnLr2G02G+Xl5aSmpq4rnurj44O/vz/V1dUEBwdviei6UchkMkJDQ6muriY8PHxZp5IQgs7OTvr6+igoKNh0il6n09HX14e3t/f53mP9/Y4uv89+1pHteeQRh+bRKiVluVyO0WjEbDYvy5bVGXppMPbyXlUeU0+aEEuQ8LFglL5yLBYLF110IQNj5eTk7CUr8XqS4rMoOKwmZu4CVHolXnsUVCx2kuwdga98faPd6elp1Gq1o4QrSXDRRY4x/+xn8OyziMsvx+Djw9zcHJOTk4yOjtLf309PTw+zs7MMDw/T39/P6OgoExMTywIlk8mE2WzGYrHwypNPYrDbuem22zAajczMzCCTyZienmZsbIzh4WF6e3vp6emht7fXdczp6Wn0er0r8DKbzSwsLGzZ784pobLS/SRJMvx1McRHHkGnDmda303vSDEDYxXIZAp8NZH09PQSFBREUEQgvinezDYYmer1Qfftu1BihB//2BFIX3QRrHJf+Pr6kpGRwWuvvcYvfvELPvKRjxAcGESKdxRekoJyQwdDSSFE1fTio/XDKyKCQK2CoWkrDX0G8uLVeCmWj99sNlNTU8O+ffvw8vIiLCwMmUxGXV0dfn5+2+4MFEJQW1tLYGAgu3fv3tax1kJISAiDg4OYTCZXcNLX10d3d/e2LbG2C7lcjlarpbm52aVpJ4Sgt7eXlpYWMjIy1vQM9QS8vLwwGo0YDAaPlBzB8bcfGhqiv7+f4eFhdVdXV+vXvvY1zwgI/oNA8kS69x8FkiQdvPTSS//y2muvuS/nvAqGhoaYmpoi6yzzWyesVittbW3Mzc2RkZHhsQv4bNjtdoqLi8nOzl63TLUWhBB0dHQwOTlJXl7ehm1Y1jtmVVUVoaGhm0rJ6/V6V9nQHdyMtTA1NUVLSwtFRUXI5XKXYKNOp9tWit6ZCTh8+LAj0zU/Dw8+CA8/7HjB5z/vKKdtQKPGZDJRVlbGkSNHHGU1IfjZ+Eso7HIu+3sehgELCbcFo4l1BKL33HMPP/jBD/jiA1fypc8+hr8uhqGJRZ4v6SZxoo36l6e4/Xs382vNG2jkKu4MuQK5tPb37OnpARylGKPRyOzsLHq9HlFcTMI99yAtLdH1ve9hu+ACfHx8UKvVrkCsq6uL4OBgwsLW1g+0LSww+v3v43PJJQQecVQSjh07xoUXXrj6e84EUUaj0bVwGAwGZmZmMJvNaLVatFotOp0OPz8//Pz81m33NxqN1NbWUlRUtObrnBBCMDrdSEf/y8zM96JS+iKZ47nk4G0olY6yvHlqie7fTGJfEiTcFoxP1Stw222OrNVPfwq33npe56fz756SksLTTz/NZz/72WWbnjbjIM/NnMLLYOGq45Nk3HI3klLJhN7Kz14aJz9Rw3vz/ZeNs6KigtjY2PMySYuLi1RXVxMdHb3M2HczEMLRgSeTyVjNRsydsNvtnDp1ivj4eGZnZ5mfnyc3N/dtsxQ7F83NzahUKiIjI6mrq8PX15e0tLQd92t1wmq1UlxczKFDh9yquSiEYGRkhM7OToKCgkhKSmJqaorc3Ny+sbGxBCFWMcF8B+AdnbF67LHH/vjkk08mrjdxbxc2m43a2tpVCZ9yuZywsDD8/f1pampienqagIAAj97ora2t+Pv7ExkZua3jSJLkIl87A4v1nN7XQ0tLC15eXpsm+KtUKoKDg6muriYwMNAtQd5qUKvVCCHo6elxceYSEhKIj4/fVuZOqVQ6OCyjowQ//zxccw28/DLccIPDn++aa2CDGTmFQuEIYoRAp9PRYR6mbKGDK0rysXbYiflQAL4pjkzDK6+8wt13382VH8jg/33uU8RFHGJ2cYknjs8yZfSmpO4NfvCbLxA0G87VH7qYckMHKklJjGrlsonFYnHJY/T39zM4OMjMzAySJOHn50dwbi7eH/0oipdeIuR3vyM0J4fASy9Fp9Ph7e2NQqFgfn4eIcS6gb+lpwdjYyP+F12E4symZC1xTXBkHpVKJWq1Gl9fX4KCgggPD8dutxMeHk5qaipqtRqr1crk5CTd3d309PQwMTGByWRy+SGe/bceGRlBpVJtmBskSRI6dRix4UUE+yUxNdvPoq2NmYUeQv3TUCi8UahlrszVdI0B3XuyUN55i8P78Uc/gq4uhyH2WddEU1MTMTExREZGUlhYiCRJNDY28vzzz5Ofn0+w0pckVSSN5gEa47zw7RsnIiIBjUrOoslOVdci6bt80HjLXefSbre7TI/PhpeXF9HR0a4MYGho6KY3FZ2dnZjNZjIzM3ckYy9JEiEhIZw6dQqVSvW2mMyvhcDAQGpraxkaGiIjI4O4uLgdzVKdC7lcjiRJjI+Pu6VMKoRwia7a7XaysrKIiopCoVCg0+no7u6WNTY2nv7qV7+6MxLwbwPesRwrSZJyk5OTd3vajR0cu/bIyMh1S1ROc+eQkBBKS0s5ffq0R2rbs7OzTE9PrzhRbhUhISEUFhbS3t7uMkrdCnp6ejCZTKSlpW3p/Tqdjn379lFbW+tRLy5wZGGcJPXc3Fz3aPoIQXxjI7ve/36HKW9SkqOr7sknISZm04dLTEx0GWsXz7eSXR8PTTLCLtQRkOUIgMfGxrjlllvYnRDOxz97Celx72fBaOP/jk5ittpJDrUTnX8LKYkp/Ndz9yOdNJPmHc3R+UamlxycHIvFwvDwMPX19Rw7doyKigqmp6eJiIjAy8uLiy66iP3795OamkpERAQ6nQ5ZQgKUlsIll8DHP+4g4p/Fg9qoltWfnn6aG598kqkzi4/dbt/yAu3sCFQqlQQEBBAbG0tWVhaHDx/myJEjpKamolAo6O3t5cSJE5SUlNDe3u7ifZ3Lr9oIJEkiJCAFn6XDpO76EDP607xZ8x3Gph1cIFWQgoSPBSNTSHT/dhKjPBTeeMOh1P6HP8DevVBVBTiytgsLC+ddiz/5yU+46667+OY3v4kQggivAO6KeA9BBonnQyc5MV2PEIILM3V4KSReqZtzHa+/v3/NTJJcLicnJwc/Pz9KS0s31aXbd8b6aK2OZHfDWdZMSEhAr9fvSFfxRmE0GqmsrMTf3x+lUvkPYysWExPD2NjYts6VEILx8XGKi4sZHR0lPz+frKys88rIX/3qV339/f2//U7mWv1DBFaSJMklSaqVJOnFc37/E0mSVmdbroHw8PDvP/jggx53PrZYLAwMDGw4iDnb3NlsNlNcXOzWrgy73U5DQ4NHJjIfHx8OHDiA1WqlvLx808TW8fFxhoeHycnJ2dbYtFotBQUF1NfXb1l4bz0IIWhra0OSJNRq9aZ97VbEG29AYSGya6/FWy6n7YEHECdOOAQ2twi1Wo1Go6FprIulVkFieTT+mT6EXfRWKfFvf/sb+vk5PvvVC9ibci1LdjX/d3QSvcHOzUeCuOZACFovG+//zE9ZsMzz+S9+nsu9cpAEPDV0jOMnjlNeXo5eryc6OprDhw9z6NAh0tPTiYiIQKFQrN6g4ecHL77o8Bj8wQ8ckgwLjlt6o4HV8ZISqgYHCTkTTJztE7hZrC0OKqHT6YiNjWXv3r1ceOGF5Ofno9Vq6evrY2RkhLa2Nnp6eja9ABkMBux2O6m7L+HC3C/h7eXLqaaf0XT6T9jtS+cHVxN2RyPAsWMO2Y2iInj4YVqamkhPTz/v/nn00Ue59dZbuf/++/nMZz6D3W5HJ/fhYwFHiD89z+vGFp6fLUflBUf2/H/uzjs6rrNa+78zRTMqo96b1btVrW7LTnE6aQ6EFGwgN1wCwQRCILSQS0gI5MIigdwPuCGQBEhIQgnpJLEtW7Jk9d57G7WRRjNqoynn+0OZwbIlWTMqTu6zltfyOjptzpx53/3u/eznUdE5YqBjeJ7a2loyMjIu+DytXYNWtfON/O7UajVDQ0Ps2bNnxzIys7OzlJWVERMTQ3x8POnp6VRWVl7UBiJYHk8GBgYoLy8nJiaG7Oxs/Pz8tsyVYbOQSCQkJCTQ1tbm0PGTk5OcPn2aoaEhMjMzSU9PX7OyERISwqWXXuotkUiu3Mw9f6RxsYW0Psx8fB34M/DGWdv2AC8Asw6cLy4zM3NC3AE0NjaKAwMDDh8/OzsrlpeXi1VVVeL8vP1ih+eivb1dbGtr2/R5LoSRkRHx2LFj4tTU1Ib21+v14vHjx8XFxcUtuweryODExNZ+1SaTSayoqBCbmppEi8UiLi4uisePHxf1er1jJywvF8XLLhNFEMXQUFF85hlRNBrFxsZGsbe3d9P3q9PpxD+U/kusfnhAbP/tmGheWil6aDQtiH/6573iserHxAWDUfzNu2Piwy8NiV3qZXFAi8Ui/uuPb4nf//OQeOttd4mA+NMv/Ux8peV98ftDfxardGuLX4qiKNbX12/sO/jlL0VRIhHF9HRRHBwUZ2ZmxKqqqnUPsVgsYmZYmJiXmGjbZjAYxNLS0gtfbxXYI0p6Nqanp8XKykpRr9eLXV1dYklJiVhcXCy2tbVtSOSypaVlhfiuyWQQ6zr+LP69+B7xeM3j4uz88vNbnDSKzU+oxcYfj4jz6g8FJTUaUbzxRlEEceLaa9e8htlsFu+//34REG+77TabIOXkX18V//7PX4rfH/qz+Mz4e6LWsCD+/J9q8b//2id2dnbb/Szm5ubE4uJicWhoaM19JiYmxOLiYrtEMTeLyclJ8dixY6JWq12xfWhoSCwvL98RMdDVsLCwIJaXl4u1tbUrnofJZBKPHz8uzs7OXpT7OhcWi0UsKSk57/mtB41GI5aWloqVlZWiTqfb8HEdHR1iYGBgg/gRiD+2499Fz1gJghAKXAs8c9Y2KfAE8E1HzhkYGPjYo48+uu2E9bm5Oaampjblhu7q6kpubi6hoaGcOXNmQ+bOa0Gv1zM6Oroj4qRBQUHk5OTQ2NhIT0/PuqVBo9FIdXU1GRkZW9rRZxU2bG5uXtOz0V4YDAbKysrw8/MjOTnZxrVJT0+nurravpVvU9MyZyovD+rrlzv9OjuXdZ5kMhISEmyl0c2gbWaMhOIYRFcLUbf7IJEvZzNqamooLS2lY+BdXDzMJEV8ihdLtIxMGflUoTfRgUrMJhPqv/yFpPYywvV9xF39IJdmHSDIEMtVXnmEyn14b7aBOfPamSUvL6+NlWXvvXe54627G3JyUDY1XTBjtTA2RvPICDmZmbZtZrPZoQyIyWRyONM1MTFBQEAAbm5uREdHU1hYaBPVbGtr48SJE7S3tzM7e36C3WKxMDo6uqJ8J5U6kRZ7G9mJdzM7P87xmscYGq86P3M1agRvb8S//pWBO+7A98034bXVHT0kEglPPPEEjz/+OBMTE7ZxxOPSy8iuneLqbjnDSxp+P/UeKRGLzBhktEx52V3Wd3FxIT8/n4GBATo7O887XqvV0tTURE5Ozo4Z0A8NDdHc3ExeXt55nL2QkBBUKhXt7e07ci9WiKLI0NAQZWVlREZGkp6evuJ5SKVSUlNTqa+vd5hasZUQBIHk5GSam5sveD9arZby8nK6urpISUlhz549dplCx8bGkpGRESwIwsY6QT5muOiBFfALlgOos6OJe4F/iqKotvdkgiCEenh47L/yyiu3vX7b0tKyZeq9AQEBK8ydx8bG7DpeFEXq6+tJTU3dsbS7q6srhYWF6PX6NYMOURSpqakhJiZmU92Ja0GpVJKXl0dra6vdz+xcWMsIsbGx5xGjPT09iY6Opqam5sKDYE8PfOYzkJoKx44tc2V6euC+++Aswr1MJiMpKckutfdzUTnahfFFAZkowZgxgcx1OXDQ6/Xceuut3HHHbbT0vkuIfz7vN3nSO2bgplwvQtyNNDU00PHrXyO2tCBkZpK52IxE4sRd3/sVyWFJ9LzWxw1eOSxalnhXV7vmPXh5eS0LhW4EV121zLtSKJBffjke77237u7Vx45hMJvJKyqybXO0FDg3N+dwu/1qxF4rsTsnJ4fCwkJcXFxoamri1KlT9Pb22n4PVtL3avcc4pfBJVnfwd01iKq2Z6nt+BNST8t5wdXQ8DAzX//68jv1pS/BGqbhgiDwrW99i7fffhuFQrEsN2Gx4JabS/gHjXxGmsGixUiZRzl7YuVUdc9zus1+toVcLic3N5e5uTkaGhpsQdzs7Cy1tbVkZ2dva3OJFaIo0t7eztDQEPn5+WvKQiQmJtrkPXYCBoOByspKJiYm2Lt375rcPG9vb1Qq1ZpivzsNT09PFArFed6RVuh0OioqKmhrayMhIYGcnByHO7QfffRRn6CgoCc2c78fVVzUwEoQhOuAcVEUq8/aFgx8EnDItDEgIODhH/7wh17bzYubmZnBaDRuqdjc2ebOg4ODnDlzZsOimL29vXh5ee2IlMPZkEqlpKWlERAQQGlpKTqdbsXf29vbUalUDusGbQQKhYL8/Hza29tRq+2OxYFlPabKykoyMjLWbP8PDQ1df+U7MrI86cXHLyunf+MbywHV97+/pnxCQEDAclu+A0KsVZouFl6yoFx0Iu5wAKKLkZkPJ9x7772Xnp4evvmDm1E4OdM9eQXtw4vkR5rRDVXT2tSEV3U17uPjuF9+OcE33ogxM4l0Yy9tC56MB3Xy6DNPcPK5d9irSqJuvpfuxdXv0dXVddVMzZpISYEzZxDS00l++OF1FccXx8bYGxVF4RVX2LY5mrFy1MrGZDJhMpnWDRTkcjlhYWHk5eWRnZ2N2WymtLSU6upqOjo6CF+nMcFV6cPe1K8TF3Yl/aOnKa79CQbl+L+Dq99P0Fc1RFxyMjzzDIyOwre/ve49y2QyRFHk5ptvZv/+/ehjYhAUClTvnSFz2AezVEQeM0RymDP/qtPRsobdzXqQSCSkpaXh4uJCRUUFs7OzVFVVkZGRsSN6URaLxWaefqHsmCAIZGVl0dHRcd4YtdUYGRnh9OnThIeHk5GRccGsXWJiokO8ve1CQkIC7e3tKxaQer2eqqoqmpqaiImJIS8vb9NzTUZGBpGRkXGCIJyvUfQxx8XOWBUC1wuC0Ae8BFwKNAMxQNeH210EQejayMkEQfBVKpU3HDp0aNt7a60R+3bA2dmZPXv2EB0dTVVVFa2trZhMpjX3X1xcZGBgYNvuZyMICwsjMzOTmpoaBgcHgWXyqlardbgD0B44OTmRn59Pd3e33Z584+PjNDQ0kJube8Gs2qorX41mWXsqJgb+93+XO+C6u5d98zbQmr979+4LfsfnokrbxcxfllBpXYi63QdVqJK4uDg6Ozv54x//yPPPP899999NUNQSU4YjtAyaiHKbIMbHwJ70dKK7uqC3F49rrkH1YTYoKDyc2Ewf3CwLNFo8Od1zjK8/+E0yLaH4SFW8rq3EKJ5/j9ZyqV0lTX9/OHaM3s9+FvHgwTV3S3dz42/f/jbhZ2UQLRbLjgZWGo3mgiK2Z0OpVBITE8P+/fsJDAxkcXGRmpoaent71/yOJRIpSZE3ULD7XpaMc5yo/QkjhjKiPuuDRTDjXhtO1y+m6O+LZuHTX1r2jiwpWfc+BEHgoYceoq+vj6KDBxmPjMTQ2Um4dok0l0gq57o4mK0kxEfOX8umGdbYr7IuCAKxsbEEBgZSXFxMQkLCjizujEYj5eXleHh4sHv37g29D3K5nKysLGpqaraFzL60tERVVRVqtZrCwsINq8tbM9cXdGXYIbi6uqJSqRgbG2Nubo6amhrq6+uJiIigoKBgSzsZf/zjH/sGBgb+ZMtO+BHBRQ2sRFH8trhstBgBfBo4JoqilyiKgaIoRny4fV4UxZiNnM/X1/fB7373ux7brVmi1WoRRXHbW2Wt5s4KhYJTp04xMjKyahmqubmZhISEi67V4u7uzt69exkfH6eyspK2tjYyMzN3rM3aWp7o6+uzBXcXwsjICG1tbeTn529In2vFynd4GH70I4iKgieegEOHoK1t2dPPDv0wpVJJZGTkhjtyqnXdTL46j8+oO+G3eOEZvXzfPj4+9Pf3c88997B3byEHrvNErbua7nEfMsLhyHVpRIeHM/vKKxi6u/G84Qbc8vJs5w0KCmJyWsNVOb7oPMI4evuXGdIM8vXPf4VPeGUzZZ7lhG71wd/mG2gPlErUd9/N0hqTomg2MzMwgPycbKejpUBHAytH9X0EQUCr1ZKamkpeXh5Go5FTp07R1NS0ZnbC3yuRS7K+g69HDPVdL1I3+iyajHZCrndHFaNgts9AV9hRDJ5hGA59jsGX1Uw3zGPUr661eOmll3L8+HH0ej1XfvWr1Ot0uFdUsHcxAAsWyhZaub3IB1elhD+d1KCd23hwb4XZbGZ4eJjIyEja29u3poN2HVjtXyIjI4mOjrZrfFGpVMTGxlJbW7ulvCa1Wk1paSkhISFkZWVd0Jf1XPj7+2OxWNYswe00wsPDqa2ttYnDFhYW2rW42Cj27duHn5/fHkEQtk4b6COAi52x2jIIgqBycnI6fOTIkW1nS7a1tREfH7/dlwGW0+1RUVEUFBQwPj5OWVnZilT25OQkJpNpW7y3HIFMJiM9Pd0WfO50m7M1uBocHLygmbLVWiU/P98uUr1cLidbFFGkpi6X+S65ZJmc/sIL4KB22K5du5iZmblgcFI9283wazMEDfgQ/AkPfFKWSy7WSSIvL4/Dhw/zhaNXMaTbzehsJjmxrtxYEIy4uMjkc8+xNDCA16FDuGZlnfe5lEolEQESInxlGHM/yU25N/DCP16i50QlGS6RlM62Mmo8n6i+YQL7OVhPcmG0rY3Exx7jz2fOrNjuaCnQUY6VRqNxyDDYbDYzPj5OYGAgCoWCuLg49u/fj5eXF5WVldTU1Kxq1K50cic/5cskR97I6FQjs65vMeV/muAbXUn6RiCx90ew+PBTKMa7UPz6pwy8Ok3LE6O0/XKM4Te1zLQuYF74N2V1z549HD9+HIso8oOTJ8HJCfMLr5AmDaFqrguzbJE79/tgMov8sVjDonHjzTNW/7/Q0FCSkpJITk62mZNvB6ampqioqCA1NdVhXbmQkBCUSqXNNWAzWFpaorq6muHhYQoKCjaldZeSkkJzc/OO+PathcXFRRoaGmhqasLT05OYmBj8/f23bXEsCAKPPvqod2Bg4I+25QIXCR+ZwEoUxROiKF63yvYNLTG9vLyO3nfffSp7Vwr2YmpqCkEQdsQk82xYO9MSExOpr6+nsbERg8FAc3MzKSkpO3ovF0JLSwtRUVFkZGRQWVnpMO/JUchkMnJzcxkZGVlz8Ozp6WFkZIS8vDz7O5f++U9cr70WqUpFw29+g+Vvf4NNCtEKgrDcIdRQx/ziNAsGLQuGaeYXpz78p6Fsup7etyfZ1RmAZ5GAS8oC+vkx/vX+a6Sl7+YvrzxHa0cl195QwKJrGGr9AdIjnLkmywPL/DyTv/89RrUa71tvxWUV6yVYnnTUajXXZntjkCq46bYv4evmz1e/+ACXq3bjLHHitelKLOLKwd/RwEqpVK4ZWJW//z4mi4W4jIwV2x0pBYqiiNlstjvTtbCwgJOTk0MZMrVaTWBg4Ip7lUgkNh270NBQGhsbqaiosHHjrBAECcHehbhzEF+PaFr6XuO9iofoHj6O3Ac8vnojfOYz+J36FXH7xwg66I7cXYqmZp6+F6doelxNx6/HGfnXDPquRcxLZp5//nlee+MN/A4fRjSZSHm9DhGRk7Mt+HvIuXWvN5M6Ey+XTGG2XDibY22YsQqtwnKW3WqabhfvbgMYGRmhsbGR3NzcTY+/ycnJDA8Pb0pkeGxsjNLSUgIDA9mzZ8+mO55dXFwIDg6mu7t7U+dxBAaDgaamJs6cOWOrlKSnp6/a9bnVuO666yRubm6XC4KwBQrMHw38n7C0EQRB4eHh8ecXXnjBc7sDq7q6OhITE3ek42U1WM2drV0n7u7uRERE7Ki583oYGRlBo9GQkpJiM3Jub29Hq9Xi6+u7Y/cpkUgIDg622WmcXbbt6elhYmKCnJwc+yfMp59e9nJLT0dy/DgzgYGo1eoL+t1tBAqFgu7Rf9A68Ardwx/QPXzM9q9C14K+KYTE2l1owyvo9fsD1Y1v8eADj/Cjh5/GIi4QnbqAV8gE6sUAhmauIC5Yyi0FvjCrZ/IPf8A0NYXP7bfjvE621dnZedkQNiGaeYOFRoMnN3n7c1P83Ug92omOTOPMXAcuEiWhTv/O4shkMrq6uux+F2dmZhAEYdXOoj/84hecbmnhl7/5zYpJS6/XYzQa7SpNLC0tMT4+TlhY2IaPgeX32dnZ2aGyf2NjIwkJCasG7oIg4OrqSlhYGM7OzrS2tjI6OopKpbJ91vr6euJjdxMfeQA/zwR082r61KcYGC1HKpHjcdWnkTz7e+S1Zbg+/EW8M9zwK3RDFa3AyUOKccaMtnmB6boFxF4FqYXJ+EV6g7Mzp/r7CR8axeDtRr2rjjSXCILdXVA5Sylrn2PeYCEuWLHud9nS0mITljx7P2dnZ7y8vKiursbPz8/usti5EEXRxp3My8vbkrFXIpHg6+tLTU0NwcHBdo0DRqORhoYGpqam2LNnz5ZSQqy2ZwEBATsiVbG0tER7ezvt7e0EBQWxe/du3N3dEQQBuVyOXq/HZDJtqzerIAh4e3srSktLVQ888MCb23ahHcRHJmO1GTg7O3/66quv9l1YWNjW6Fqj0SCVSrdFNsAeWL2wFAoFSpAW+eEAACAASURBVKWS0tLSbbd32Qjm5+fp6OggIyPDNtA6OTmRk5ODQqGw2w5js5BKpWRnZzM1NUVnZyfw76AqOzvbvqyHxbJMUL/3Xrj2Wjh+HPz9iY2NxWAwbEm79PyiBr2hE7kYStKuW0iPvZ302Dtwi7kRyWQRKZWRyOJmibgumNYKd44efoXS4z0c/twhTpS8xudu/wGLwtcYmrkSH4WWm7I9EWe0TPzud5hnZvD9zGdQXkDjzOqvp9PpuDTVHWeFBOlVNxHiG8hMhQduncPEKAJ5X1fPjGllx6qrq+uGu1itWK8UWNnQQGJo6HmDuiOlQEf5VRMTEw7xq3Q6HVKpdEO8PW9vbwoKCoiMjKSxsZHq6mrUajVms9l2bR+PaPamfpXC3V/FRelNfddLvN/7NBP/de+yJdLTTwMgkQm4RSgIvNSdmP/wI+ZrXuh3D6N0d6LvT1MM/H2ap5/6Hz5x5AgnPTxIKxlAMFso1i1LfmRFu7I30Y3KrjlOt6+dcerq6mJxcdGm9XYuPDw8yMzMpLKyclOZK6uThF6vdyy7vA5cXV2Ji4ujrq5uw/OG1bLFz89vWyQlpFLppiVYNgKj0Uh7ezunT5/G1dWVoqIiwsLCzvsuY2NjdyRr9elPf1oql8sPCYKw/e2kO4D/E4GVh4fHtx944AHZ4OAgJ0+epL+/H7N5642zOzo6Lmrn3dloaWkhKSmJ1NRUUlNTaW1tpa6ubkMWIdsBURSpra0lNTX1vBWqtXMoISGB8vLyLRPz3AgkEglZWVnodDrKy8sdC6oMBrjjjuUuvy99Cf7+d/iQqyMIAunp6fT19W3aXqdXfQqAtLhPMaV2YVdgIdPuQXR3C2ScisUt1omk2+LwdE5goGeG3bvTqKqq5rlnXyVq1wGOteyiZciFwgQ3rs90Y6ipgclnn8WysIDvkSMoIiM3dB8hISEMDw/j7CTh8lR3evUi5jQFj7/wS667+Q4uXwhFROSNmeoVA65delYfYq1SoHlxkdq+PvasUmJ1pBQ4OztrN79KFEV0Op1Dq/ULmUSvBl9fXwoKCggJCaG6uhqFQnEeR9HPK559afeTn/Jl5HIXSpNHmSyIwfLtBxH7Vpa9RVGkvrmO+AORxN0TgP8+N6br5ikyXE92eg5f+N730EXGk9gyTe18L5NLy+XIy9PcSQ5T8q9aHa1D5y+EBgYGmJycXLGAWg2bDa6MRiMVFRU4OzuTnp6+Lfp8Vo/XCy2MjEYj9fX1Nk5maGjotmXfrZpX20FkN5lMdHZ2UlJSgpOTE0VFRezatWvNZ6tUKvH19bW709peyGQyvvCFL7i6ubl9dlsvtEP42AdWgiBkp6Wl+SYlJZGZmUlubi4LCwsUFxfT1ta2ZYGGVqtFIpFsa0rUnntZWlqylZ/c3d3Jz8/H399/W82d10NnZyfe3t7rpsV9fX3Jz8+nq6uLtra2HVMblkgkeHt7MzMzg5ubm30D4vQ0XHEFvPQS/OQn8KtfwTllA5lMxp49e6ivr3c4I2c2L9GnLiXIN43QoBgUCgUnRmopbWon54MEZlXTfO/No/z0v39Kc3MzP/rRjygtLSU1NZUpvYn/fW+CvnEDN+Z6cnkUeHd14vzOO1iMRnw/9zmc7CiBBQQEMDY2hiiKZEa5EOwt54QopSAln9aefn72jS+zX4ikfXGYlsUh23Genp52Z07XyljN9/dz37593H7rref9zZGuQEcyVjMzM3h4eNg9gZpMJjQajUPlYUEQsFgshISE4O3tTUlJCf39/St+K4IgEOCdzIGMB8lJ/k/aH7wei2hEc8eVjEz8u9utq6sLT09P/Pz8kMgEgg56EHu3H0oXJT/a/zRKqTN3fO/7pImhSE0W3u94HwCJIHBznjchPnJePb1ShmF0dJSBgYEN+/95eHiQlZVFZWWlXYT2hYUFysrKCAsLIy4ublspBMnJyfT29q4Z/E1MTFBaWoqXlxc5OTk7QgNJSkqitbV1y8ZIs9lMd3c3p06dQiKRUFRURGRk5Ia+w+jo6Au6a2wF7rnnHhdXV9dv/F8wZ/7Yc6x++9vf/ubJJ59Mt5InZTIZvr6+hIeHs7CwQFNTE9PT07i6um6KXGgVRltL2XenYFUyT0lJWfF5rAayYWFhjI+P09raipub24ZKEZuFVqulp6fngitYWP5+QkNDmZycpKurC39/f2Qy2bbe3/DwMENDQ+zbt4+xsTEmJyfx8/O78GDd3w+XXgqNjcsdf1/8IqxxjFwuR6VS0dDQQGhoqN2r68HxMwxPVJMW82lclT6MuS1Q0ddL7lvxvNrwHEefvYumpkby8/O58847cXFxQRAE+sYNPHdcw5LJwqdilwiqP4b2jTdY6u9HDA5msbAQPzs7WCUSCRMTE7i5ueHsrMTfU0ZZxzx78zLpO1PH388Uc7uTC4vZ8bQYhsl0jUIuSHFycqKrq8tGZN4ohoeHz7OFWmprI9lgIPXuu5GckwHVaDTIZDK7SvJ9fX2EhobaxfcZGBjA09PT7tL/4OAgzs7ODrWnWywWampqyMjIwNfXl9DQUNRqNe3t7bi7u68YfwRBQOUSSFjcQfSCHu/n3qBN2U2n5whmoxz18Mx5cidydynema64yNyINCXx/InfMqQxcGV+Oo3eS0S2a/AMiUAqEYgPVtI4sEB93zzJ4c7M6adpbW21uySnUCjw9PSkpqaGwMDAC/7etVotVVVV7N69e0u4ixeCRCLBw8ODxsbGFZkok8lEU1MTY2Nj7NmzZ0c5ok5OTuj1epaWljZFPbFYLPT19VFfX49KpSItLQ1fX1+7xie5XM7U1BRSqXRbhV9dXV0pLy+3tLa2lj/88MPrt3R/xPGxDqwEQfAPDAx87L//+79dz33hJRIJnp6e7Nq1C6lUSkdHBwMDA8jlclxdXe36gczNzTE0NLRjEgvrYWxsDIPBsGaZQSKR4Ofnh5+fH+3t7YyOjuLl5bVtREiTyURFRQWZmZkbXslZOWJOTk7U1NTg4eGxbQHr2NgYXV1d5ObmIpfLCQgIYHx8nLGxsfXbiGtqloMqrXbZ3+668xpWz4OLi4ttIAsMDNzwOyaKIrUdf0QhdyM58kY6B0cZeHMa73dkfOH5T/F61V/Jy8vlzTff5JOf/KTtvLU9c/ylZAo3yRLXj72HW9UJLHNzuObk4HXoEKq8PBo7OwkPD7c70BMEwcYv8nCRMT1ronJskcPxubx87I9Ujfdxr08sDTFKFixG4p1DkEql9Pb2Eh4evuHPLpFI6OnpOe99LnvxRUwmEyFnKa5bodFoUCgUdmWPOzs7iY2Ntet339bWRkxMjN2Bf2NjI0lJSQ4tGHp7e3F2drbJp0ilUvz9/fHy8qK5uZnp6Wl8fHxWZOwEQUBZeBniu+8Q+E4jfVfHMThXTUxkBj6e5yu+C1IBVYySuMxolGov8r0vJTt4H60+fUxNDRE3I0ceGIiTXEJ0oILKrjnahuYxT7WRn+dYxsbZ2Rk3Nzfq6urWJYuPjo7S1NREdnb2jrpIODs7s7CwwNTUFL6+vmg0GqqqqggICCAlJWXHPA/PhqenJ/X19Q79fi0WCwMDA9TV1eHi4kJaWtpy5tLBcqqbmxttbW12N3/Yi+joaOc33ngj4v77739uWy+0zfhYlwJ9fHy+8o1vfMNzvcFSEAT8/f3Jy8tj9+7djI2NUVxcvK4K8rno6uoiJmZDGqXbCovFsmHFd6u5c1hYGGfOnKGjo2NbeGctLS3s2rXLLgNOKwICAsjNzaW5uZnu7u4tTzVrNBra2tpsQRUsvw8pKSlIpdK1zU/ffhuKisDJCUpLYf/+DV8zIiLCFixsFFO6HmbmhtilPEjbS6MsPGPBf9iLavMpxufV/O///i/FxcU2BXuLKPJO6Qh/P6MlaG6Y65v+iJfMiOdNNxF4//14XHEFMi8vZDIZISEhDhHr/f39GR8ftz2fg+keyCQCE4m7uO/g9+gf1DGi6Sa1bZaq+S76Dct8EHd3d7ssQyQSyarfwVd/9Su++te/rnqMvRwr6/ntCao2YmOzGrRara2pxF4YjUb6+/tXHWvc3d1tqtclJSXnS5hIpQjP/A6pbpa0p9pQynzoG3sPUVybEuAaruA7z32VS27Zh67aQM4LMWhdwug+8SaLXctmF/4ecm7a44pGb2bQEo+TwvEymK+vL7GxsZw5c2bVsbenp4fu7m4KCgocajTYLGJjYxkfH6eqqor29nZycnIuase1k5MT4eHhdskviKKIlWs8Pz9PYWEh8fHxmw4MVSoVMpls1VL/4OAgl1xyCYmJiSQnJ/Pkk08Cy9JEBw8eJDY2loMHD9qOFUWRo0ePEhMTQ2pqKjU1NbZzNTU1MTExsU8QhF5BEI5YtwuCkCUIQqMgCF2CIDz1US8XfmwDK0EQpDKZ7D/uvPPODb8x1lRoQUGBTQW5ubl5XV7M4uIiWq12R1LSF0J/fz+BgYF2ZXcCAgIoKipCEAROnTq1aaPiszE5Ocnc3JzdJN2z4eLiQmFhIXNzc1RWVm6ZoKhOp6OxsZGcnJxVyfRJSUkoFApqampW8tGeeQY+8QmIi4PyckhKsuu6Vj0qtVq9YfJpT2slAU23MPtyKPNdRnoyh9EUdPOZb36K5pZmYmJisFgsiCYT2vpGnv9jLacHRJK0rRzyGiH07s/h/5//iWtGBsI5A2hkZCR9fX12c+5kMhlubm42fSWVs5QDKSqatUt86rOf57X/LEWWEk5qwxiqOTOvacoxiWaH9azODq5mx8dpGRkh5xz9Kivs7QpcWFiwOyNqr42NFY6Q1q3o7OwkMjJyzUyXIAiEhYVRUFDA8PAwVVVVK/lpKSnovvIVfN56m8IXetHPqhkar1r3mhInCSFXe/IuL3Hop5cT9ZwHo+6XoHnxFZaGhzEYDIz31XJZsoLeCRPv1Kxu/rxRBAUFsWvXLqqqqmzvpCiKNspGXl7epuUZHIWVuzo1NUVOTs6O0CguhIiICEZGRi7IFRZFkeHhYYqLi9HpdOTn55OYmLilzzImJsbWXX02ZDIZP/vZz2htbaW8vJynn36alpYWHn/8cS677DI6Ozu57LLLePzxxwF4++236ezspLOzk9/+9rfcc889wHIg9l//9V889dRTeHt7vw38QBAEq2DZ/wO+AMR++O8q6/UFQXhWEIRxQRCaztr2SUEQmgVBsAiCsGfLHsIG8bENrCQSydXXXXedsyM1XycnJ5sKsoeHB1VVVVRVVa06IfT09BAVFXXRdaKMRiN9fX0OZc4kEgmxsbHk5uYyNDRkl7nzWjCbzTQ1NZGWlrbpZyORSEhNTSUkJITS0tLzxBLthdWbLSsra80JVRAEEhMTcXNzWw6uzGZ46KFln7+DB6G4GBxUUZZIJOzZs4empqZ1n/PihJGel0aRv7UX58kYejLVfPDpKv7x9q9Z0OuIiIggNDSU0OBg+v/2N7qe/H88V2OhV+rHZZ4abjmcj+/NN+K0jsG1tfzpSFePtTvQitw4N3zdZZyQmvD0cceteS9/WeiksHSMSXGWk5o6h6xt5HL5igxG5QcfYLJYyNu3b9X97c1YOUJcd8TGxmg0otVqHZJnWFhYYGJiYl2zZisUCgV79uwhJCSE06dP2wy85+fnqbnuOsxf/jKqX/+J3J+fob3nDSzihTPVtxy5CYkCvv7G3ag6/JgUb0L9h3eoOX6c5ORkilL9KEhw40znHOUdmxP+DAsLw9vbm8bGRlvnn0wmIzMz86LYcpnNZpqbm238saioKLq6NmRPu+2QSqXExsauaXcliiJqtZqTJ08yNTVFXl4eycnJmxYrXQ3e3t4YjcbzSP5BQUFkZmYCy8mLxMREhoeHee211zhyZDnpdOTIEf7xj38A8Nprr3H48GEEQSAvLw+tVotarebdd9/l4MGDfPazn5U6OTndDHwAXPWhcKi7KIpl4vIK7HngxrNu4Q+cFWh9iCbgZuDkFj+GDeFjG1gFBAR872tf+9qmBKUkEgmhoaHs3buXyMhIWxvqyMgIFosFo9HI2NgYIetMXDuF7u5uIiIiNkX0dnZ2Jisri5iYGKqrq+02/j0bbW1thIeHb+mqzuqzVVdXd14n1EZhMpmorKwkOTl5Q+XJ+Ph4PD080Nx0EzzyCNx1F/zzn+BAafNsKJVK0tPTqaqqOu8ZL04Y6X91ivZfjaPvWGI68gwlt9fTkNnF7D+aef63v+eDDz6w7e8/MoKuU81fg65F7+LDHft92H91KrINLiqio6MdKrWeWw6USQWuyfRgYsGCPlnJeyXlfP+7z1OtmSCmW8/J+XYWhUW7A+NzDZzLTy6PhQVXXrnq/vZ2BToSWDliYzM0NERISIhDC43W1lbi4+PtChiDgoIoKCiwcWlqamrYnZaG9Je/hIcfJuj1WpK++UcG+09d8FxRUVG8+OKLdA+0c7T2CxgUTmgNVxLYprMFilekuZMQouTtmhk6RjbnBxgbG4vRaOT48eMEBQWdJzK6U5ienqakpASlUklBQQGurq5ERUUxMTGx6QXeViE4OBidTrdikSaKImNjY5SUlDA+Pk5OTg67d+/e9o7FmJiYdYPOvr4+amtryc3NZWxszGbxExQUZJPZGR4eXsHVCg0NZXh42LZdqVRy6NAhZ0EQ3ICQD/8NnXWZoQ+3ASCK4klghdaNKIqtoii2b/bzOoqPZWAlCMIuPz+/6OTk5K06Hz4+PuTk5JCRkcHU1BTFxcXU1NQQEhKyLfop9mBpaQm1Wm13t9Va8PHxYe/evSiVSk6dOsXw8LBdk+709DRarZbIDeoi2QOVSkVhYSEajYba2lq7Aj9RFKmuriYiIsKurEFMaSl+r7/O8JEjmH/9a9gioqqXlxdRUVHU1NQgiiKGyX8HVLq2RXwLXBg+8Huq9uuZVMwS2STw+Hcf4fLLL+fnP/85AKbpaQbL6ngr4hNYZFL+4wp/4kLsC2YVCgXe3t52WwtJpVLc3d1XZKBigpQkhip5f26RQ1d8mpTQVL73o6fIUsYiN1n4R/97SE1Gu0q650ouVNTUEOrlRcga77u9pUB7A6uFhQUUCoVdwZsoigwMDGwo43QuZmZmWFxcdIhuoFAoyM7OxmAwMDs7u3zPggA/+AHik08SXNKL6pbPYtFeuDx71VVX8cgjj1D57nF+MPdDLAojC1PhGD60hZJIBG4p8CLQU87LpVOMTjtettfr9eh0Oruf81bBYrHQ2tpKc3MzWVlZK8ycJRIJaWlpNDQ0XFTfPisEQSA+Pp729uU4wSr/MDw8TGZmJmlpaTvWre7v78/MzMyqpcnZ2VkOHTrEL37xi3UbS1abawRBWLH96NGj7i4uLkWACKwWce+MVo+D+FgGVn5+fvc98MAD22LW5+rqSkpKCoWFhWi1WoaGhmhsbNx06Wwz6OrqIioqaksDPIlEQmRkJAUFBUxOTnL69OkNkY6tSsipqanbtsKUyWRkZGTg4+NDaWnphsUFm5ub8fT0tK9zZXgY7rsP9u3D+NBDVFRWOpzFWw1hYWG4OLnS9Fw/bb8cR9e6iF+BG4lfC2AhpYWWIF/0Tgry9WHcf+ReIiMjefnll5HJZIiiyMib/+KtkKuQKBRcEjWLQeeY76J1pWlv1urcciDAVRkeiAL0Rsh5+NqfMz+7xDce+Q6XC9GofeUszHahtUME9uzAShRFHiwq4jff+Maa+293KdCRMuD09DRubm4OlWCsYr+O/p6mp6cxGo0UFhbS0NBg0xwSjh5F++sf41k3gHF/PmyA8/fggw9y8Mor8PPxpiV1GCNhaN77N0/LSSbhjiIfFHKBP53UoF+wvyFmfHycmpoasrOzKSgooKura0edI2ZmZigpKUEul1NYWLjqu+Hu7o6fn59dTSjbCT8/P2ZmZiguLqa/v5+0tDQyMzO3Vf5gNQiCwK5du84zuDcajRw6dIg77riDm2++GVjm91oXc2q12iZ8GhoayuDgoO3YoaEhgoODV2yPi4tDqVR6AyaWM1Rn67GEAiPb9BG3BB+7wEoQBLlUKr3tlltu2dZlzvT0NIGBgVxyySX4+vpSV1fHmTNnmJyc3DFhS1g2x3TE42yjUCgUpKWlkZycTENDg433sBa6uroICgpyqAvQHlh/wNZy2oU4QgMDAywsLBAXF7fxi4jisjbV0hI8+ywRUVGEhISs2bXkCCxLFpTV/ph7ZTinQsLXAgi+0oOZRS1v6BvQuXhzvWc25a98gMlk4vXXX7cZzM40tfKPpXgWnVy584Av2enx9PT0rCibbRQuLi6oVCq71Zz9/f2ZmJhYqbDuJmNvoopK/RKJhWnctfcrvPNGOR1l1YSb3ahIVaF5/W+YN7gYOTuwMk9NEerszP41yoBgfylwaWnJLhLvxMSEbRLYKBwlrY+Pj+Pk5OSwtIDVty4jI8OW7dXr9VRVVWE0GvH4wrdo/tkRZO3diEX74KwJbTV0dHTwxE9+yu++8lNcM+UsskibJYTZ/n8HGO4uUu4o8mHeYOHPp5Y11DaK/v5+2tvbyc/PR6VSIZfLyc7Opq6uzqH32h5YLBba29tpaGggPT2dmJiYdYPZ2NhYhoeHL+qiGpbnovLycmQymY1ft93j73qwlu7Obj646667SExM5Otf/7ptv+uvv57nnltWTXjuuee44YYbbNuff/55RFGkvLwcDw8PgoKCuPLKK/nXv/7F9PQ009PTSCQSpY+Pz25RFNWAXhCEvA+7AQ8Dr+3wx7YLH7vASiKRXH3DDTcot7uW3NvbS2RkJIIgEBQUZGtb7e/v59SpUwwODu5Imrirq4vo6OhtL0d6enpSWFiIh4fHqmrPsEyOHRkZ2VHpCQ8PDwoLCxkeHl4zNT89PU1fX9+GBEpX4E9/gjfegMcegw8/U3h4OLt27aK8vHzTHYoWk0jfS1PMDSwReqM7Iz6dzJtn6ent4dWxD5hSeZKJG3vcYnjooYeora21BYbGhUVeqZpHo/ThU4XehPo4IZPJSExMdNhHbK2unvVgFU88N6OwN9ENDxcppSoTdxcd5bLMS5harOJa/1zMTjLKk5yYfOYZTBvIRJwdWFW8/z7PV1WxtE6gYU8p0LqvPZpier3erolraWkJnU5ntxmvKIq0trbaZDQcQUNDAzExMbbMhVQqJS0tjaCgIFu2N+DwNzn9xLWIw0NQWAjtq1NPenp6mJubIzU1FblEhvH0AJ965iCmLgV/0lShM/9bOT3Y24lbCrwY0Rj5e/k0lgssNkVRpKWlhfHxcQoKClZk9lxcXEhJSaGqqmpbJGFguUu4pKQEQRAoLCzckAaaVColOTl523371sLMzIxNKicxMZF9+/ZhNpvtkjPZDshkMvz8/GxNE6WlpbzwwgscO3aM9PR00tPTeeutt3jwwQd57733iI2N5b333uPBBx8E4JprriEqKoqYmBjuvvtu/ud//gdYJsd///vfJzs7m+zsbB599FHkcvknBEGQAfcAzwBdQDfw9sX47BuFsJPZl61AaGjosddff/2SjDVasbcCs7OzNDQ0UFBQsOrfFxYW6OvrY3R0lODgYCIiIralC2NxcZHy8nL279+/o8ROq0Hn9PQ0KSkptgxKRUUFkZGRDnU9bRaiKNLT08PIyAhZWVk20vzi4iJlZWXk5ubaR6RXqyE5GRIT4eTJ82xqRkZG6O7uJjc316GWZdEs0v/yFDOti4Te6IlPpitarZbTp08zHSWlXTVF4Iwa/RsGbrzh5hXis6Io8vLfmmle8uLaGAu52SuzlZWVlYSHhzvEyamsrCQ6OtquIGBsbIzx8XF2n+Pb1zywwF9Kp7herkDeYECd9QIBiWHMBKZxTN/INe+NsmvciO/hw8g/FLxcDdPT0/T395Oens79t97Kk6++yoxWi+sawc3p06fZs2fPhr4XnU5HZ2cnWVlZG/qs09PT9Pb22rqcNgKrzlB0dPSGj4Hl7M3s7CyOckUHBwcZHx9f87PpdDpqamqIj4+na+xFJPWNFHzzLQRRhHfegbM+49DQEIODg+Tm5tqC1urqaoqKiojyjOOBn/2Usb06bvc/QIjTv0n9pa163q3TUZTkxuVpq/cSmc1mamtrcXZ2Xrfk2d3djV6v35JOYyssFgtdXV2Mjo6Snp7ukCVZdXU1ISEhNtHW7YZer6etrQ2TyUR8fPyK36pGo6Gnp4fs7OwduZe1MDc3R11dHYWFhdt6nbvuukv77LPP3iaK4jtr7SMIwovAAcAXGAN+wDKZ/ZeAH6AF6kRRXDsNvsX4WGWsBEHwkMvlu9PT07f1Or29veum9Z2dnW0rCIVCQVlZGXV1dVu+krAKk+50t4xcLiclJYX09HRaW1upra1laGjIpup+MSAIAtHR0SQnJ3PmzBnGxsawWCxUVVWRkpJiX1AlinDPPbCwAM8+e15QBcudOLGxsZSXl9vtNylaRAb/Mc1M6yLBV3vgk+nK4uIijU2NTMfIaFdN4aMfZ/L1Th781nf43e9+t+L498rUNC95kScfPi+oAti9e7fDHZ2xsbF0dHTYdYyfn9+qJfCkMCWRAQo+EA3I3CV4tF3Jd775Y6ZOVBE37UncZTchSCRM/O53GNbhqpydsapsaCApNHTNoArs41jZy6+ytwxoFWS0t1RvMpno6emxr3R9Fubm5uju7iY1NXXNfayior29vbhK05iIdGbg1SfAxQUOHFiWFGE5cO7t7T3PnDwrK4s///nPNKvreeGRnyPOLvLs5Ac0zf9bcLYgwY2saBdOtsxS23N+ycxgMFBWVoavry/JycnrjmVRUVGIongef8dR6PV6SktLsVgs7N2712Gf1+TkZNra2rYtm2bF7Ows1dXVNDQ0EBUVRX5+/nkLIB8fH4xG40XvWHR1dUUqlW77fdx9992eISEhR9fbRxTF20RRDBJFUS6KYqgoir8TRfHvH/5fIYpiwE4GVfAxC6wUCsUnP/vZz55npYAcHwAAIABJREFUX7OVMJlMTE5Obmh1IpPJiIiIYP/+/QQHB9Pc3ExZWZnNwHYzMBgMTE5OXlSpB5VKRX5+Pn5+ftTW1uLm5nbRu2S8vb0pKCigp6eHkpIS/P397Q/2XnoJXnttWV5hHZuiwMBAEhISKC8v3zD/QxRFht+cYbp+gcBLVfjlu6HX6zlVcZqOqAXaXTUEzM0x934xP/r+77j88st57LHHbMdXdOgp6RdJ1HdyxdWrZzKUSiURERFratusByuXx54BUSKR4OXlhUajWbFdEASuzfJgwQzqGBmCVkVD+QRf+fLXiV/0ZEmuxPfuu5G6uzP5wgssrFFSsQZW5qUl6np7yTknM3Yu7CkFOhJY2fM+aTQaPDw87M5qdnd3Ex4e7pAitsVioba2drlkd4HjnZycyMvLQyb6oZAG0yxrxlT8AYSGwpVXov/Tn2htbSUnJ2dVKZcbbriBRx/8Me+3vEPnF/5CgMWVl6dLOaZrXCbICwLX7fEkKkDBPyu19I7/exGi1+spKysjLi5uQ/wzq7juwMCA3VpoZ0MURbq6upblJ3bvJiEhYVNUCqVSSVhYmN1l9I1ifn6e2tpaamtrbQKw60l9xMfHb9u92IOoqCh6P+wY3Q7odDrc3NyQSqVFgiDsLEt/k/hYBVY+Pj73HjlyZFv7SgcHB+020bXa5uTn55OcnIxaraa4uJi+vj6HVzlnc7wuJgRBYG5uzrayPnXqFJOTkxf1nhQKBRERESwtLTExMWEf6XVsDL7yFcjLg6997YK7+/v7k5SURHl5+boK/fChWN+/dGgq5/Db64b/fhWTk5MUN5bTGKNnUJwianqYmXff4sffeZewsDBbByBA69ACb1bPEK7v57os93V1qnbt2oVWq3VoAoqNjbV7YA4ODmZk5PxGHH8POblxrpyaX0K1S8UPr/slI0PTPPn0I0xPTyPz8MDvrrtwCglh6pVXmC0vP+8cUql0udv01Cn0BgMZWVlMTU0xMTHB2NgYarWakZERRkZGGB0dtalja7VaZmdnMRgMay5kZmdnN9w5ZTQaMZvNdpX1HSGtLy4uolarHZYr6ejowM/Pb8PlXJsAr1cRS0Y9XWInnDyJOTkZ18OHyZuaWvczf+tHD3Br4WEsZj8+cXyKdJdITuibeGX6NEsWE1KJwK17vfFyk/HSKQ0a/fLitKqqioyMDLsygFKplMzMTOrq6hziOM7OzlJaWorRaGTv3r1b5jcYGRnJ2NjYlhLZFxYWqK+vp6qqiqCgIPbu3bu+f+mH8PHxYXFx8aKT6v38/Gxq9VsFg8FAT08PJ0+epLW1FW9vb26//XYUCsVNW3aRHcDHJrASBCHE19c3eDP2KRvB4OCgQ1o0Vri7u5Oenk5+fj4Gg4GTJ0/S0tJywUn5bJhMJtRqNaGhoRfeeZthnQRiY2NJSEhgz5499PT0UFlZaddn2krMz8/T3t5OUVERsbGxlJWVbTzY+/KXYXZ2zRLgavDz82P37t2cOXOG+fn5NfcbL9YzUTqLT44rQQfdGR4e5nh/NbW7plm0zBMzXEfIvJ6Tb80QEhy2IlM1MGngldIp/AwarpG045axfrnburp3RGvHx8fHpnu0Ufj6+q7ZEXtJijsuSgl1/rAnpJBDl93Ii8+/w8nSNwGQuLjge+QITrGxzLz1FoN//Sttra3U1NRQUlLCiRMn0Ov1vP/PfwIQHBtr4w9NTU0xMzODXq9Hr9ej1Woxm82o1Wp6e3tpbW2lurqa4uJiTpw4wYkTJygvL6ehoWFFG/9GnpG9oqAGg4H5+Xm7J+/29nZiY2MdyqJoNBo0Go1DJcTUpCI8XKJo73+HCUycfuQRxN27UX7mM1C1tvWNRCLhV794mqOX/ZDFzjmung3hCvd0mhcGeHbyA3TmeZydJNxZ5IMgCPz+/VEampZVzD087NdwdnNzIzY2lrq6ug1n/kVRpLu7m6qqKpKTk0lMTNxSfSyJREJycjItLS2bPpfBYKCpqYmKigr8/PzYt2+fXabtsL5Q5+c//3n8/f1JSUmxbbv11lttxPKIiAisdJq+vj6cnZ1tf/viF79oO6a6uprdu3cTExPD0aNHbd+F1QMwLi6O119/3W5qwbmwWCyo1WrOnDnDmTNnEEWR3NxccnNzCQ4O5vOf/7yrj4/PuuXAjxo+NuR1Ly+v7zz22GMP33PPPdtmM67Vauns7NxSYqDFYmF4eHiZ5+DqSnR09AUHYqtK9kfB+Lmuro6AgACbgq4V4+PjtLS0EBwcTHR09I6J/FksFkpLS0lOTrat2BcWFqiuriYgIGB9Ttorr8CnPgWPPw7f+pbd156amqKhoYHs7OzzsiATp2cZeWcGr3Rnwm70oruvh5LFdno8ZnBfMhA+Uke4eyp7km5nfm4Jo9GIUqmkoqKCuJQcnj85g8K4wPWdr7DrC59DvkFiemtrK05OTnYTp62ZIHv4ivX19QQHB69aKqvpnuMfFVpuNjkx2zzJjc/k4Rvgyqsvv8Pc7ALz8/PIpVICu7pw7uuD+Hhcr74a1w9b7k+dOkXS+DjjDQ3EPfTQuu/TiRMnOHDgwKp/E0WRxcVF5ufnmZ+fp7m5GR8fH+bm5hAEAZVKhaenJ56ennh4eKy4TkNDA0FBQRsuBXZ2diKXy+3KWOn1eurq6ti7d6/d2Wij0UhpaSm5ubkOC0JO6/oorvspgiGCjIRbCZcrID8f5uehrAyiolY9zmIUafmZmvbe9/jum9/ltQ8+QAx349Xp0ygEObf77CNY7s275T2c7lPyuUu8iAzcnCtDfX09KpWKqDXuyQorkdrT05OEhIRtHYvOnDlDbGys3R2gsNw92tXVxfj4ODExMQ6r9MPye37y5Elyc3PPU1s/efIkbm5uHD58eNWOxvvvvx8PDw8eeugh+vr6uO6661bdLycnhyeffJK8vDyuueYajh49ytVXX803v/lNvL29efDBB3niiScICgrijjvusOuziKLIzMwMg4ODNl5jeHj4mjy4pKSkidbW1hRRFDcukHcR8bHJWCmVyv+49dZbty2oAhxWTl4PEomEsLAw9u3bx65du2hvb6e0tJSRkZFVV2MWi4WBgYEtU1nfDKw2Cqvxzfz9/SkqKkIikXDq1Clb6+12o729ncDAwBUDm7OzMwUFBRgMBioqKlZPTU9MwJe+BNnZcP/9Dl3b29ub9PR0KioqVmR7NNVzjLwzg0eSktDrPWnsbOFtsZEejxn8dOPEjTRz6mUd9939W5YMFtzd3fHx8cHV1ZWImGSeOz6BIFq4qvPv+OVkbDiogmUhvcHBwXUzaavB398fnU5nV9ZxrXIgQGKwBD83kfclC7g6u/HjO57ivu9fim6pFplMRnx8PHuLioj+3OdQHTgA7e2Y3nwT6Ye/AYVCwdLQEH6xsZuaGAVBwNnZGR8fHwICAlCpVGRnZ3PgwAH27dtHVFQUUqmUgYEBSkpKKCkpoaWlhYmJCTQazYYnTFEUbRY29sBRMVBRFKmvrycuLm5TKtsql1CciEBU9FHb80ta5hqwvPUGmExw1VVriohK5AK+OW44K+LRaGe45qqr8J1TcLffQaSChN9NfMCbLScxm5bLd67Omx+qU1JSGBoaWrMpSBRFent7qaysJDExkeTk5G1f4CUlJdHS0mIXh9ZoNNLW1sbp06dxc3OjqKiI0NDQTdE8BEEgMjJyVQHToqKiNd9jURR5+eWXue2229Y9v1qttpk5C4LA4cOHV3j9WT0A77zzTnp6ejbM2VxcXKSrq4uTJ0/S2dmJv78/Bw4cICUlZd3mgrvvvttDpVJ9ZkMX+QjgYxFYCYKQnJCQoHJklbBRmM1mNBqN3cKAG4UgCPj6+pKbm0t6ejoajYYTJ07Q3d29gkswNDREQECAQ6TWrUZzc/O6k4BEIiEmJobc3FyGh4cpLy+3q7xkLzQaDVNTU6tm8iQSCSkpKYSFhXH69OnzuUdf+QrodMslwE34LXp6epKVlUVlZSU6nY7pxnmG/qlFFaMg7JAXpzureUvZwqRinvDxTlLnLbz8/4b41VO/Jz09fQXJWTdv5rU6C2ZRxuXD/8LbRVgOOuyAVColJSWFhoYGuwZ7QRAu6Pt1Lnx9fZmamsJisSCKIhqNhubmZk6cOLFseh26iE4iZTZBQY7H5WR43o6vewrf/e53CQ0NZd++fTz11FPMxMbi+YlPYOjqYvIPf8A8N4dlcZE7f/Uryu1QbL8QziWuSyQSPD09bcKz+/fvJycnBy8vL1twWlFRQU9PzwUD1YmJCby9ve36nU5OTtrss+zF4OAgUqmU4OBgu4+1wmKxUFlZye7I28hL+RIqVx86hv/Bu9o/MvLsI4iDg/CJTyxnr1aBT44roT5h/OrTjzE8PMxNN92Ep8WZz3legrNBQpPHBL4By/QFZ6fNTy1SqZT09HTq6urO46rOz89TVlbG7Owse/fudSiD5AhUKhUqlWrNBcbZMJlMdHR02LwIi4qKCA8P3zJNwtDQUMbGxuziop06dYqAgABiY2Nt23p7e8nIyGD//v2cOrXsKzk8PLyCimIVBQXO8wB8//33GRgYYC2YzWbb/FBZWYlUKiU/P5/s7GwCAgI29Dxuv/32/0/de4fHdZbp/58zRSNp1EdlRr33ZvViWU5xekJJI6FlA1kg7LKbXWCX3YUltMD+KMv3C5ssIQmEQAKBkBAgAVJkS7J6sWT13rs0qqPRlPP7Q57BsqWZMyq2v/d1+fI17Zx3Rue87/M+z/3ct5uXl9ffSv6iVxn/TwRWwcHBn/jUpz51pHfO1NSUy3Xu/UKtVpORkcHx48cRRZGqqirOnz/P+vo6Q0NDTlPfVwKzs7MolUq7hpUj2MydExISaG5uprOz81BtYWB719fe3u5UBDQ0NJT8/Hza2toYGhraDjZeeQV++Uv40pfgIt7BfuHj40NeXh5tf+5i9DdLqCPdiLrfnz8NnuVtr35MGEiaPE+exzG+8W9v8POfv8RXv/pVnnzySTtRfdVg4SfvzLO2aeE9G3VoF4bZzM9Htg89tMDAQFQqlaTJ/mLodDoWFhZckpPw9PSkrq6OiooKxsbG7L6TpaWllByLJyfWk3ctJuR+cry6sthcc+N73/sejz/+OMvLy/zjP/4jkZGRfOappwi4/35M09PMP/MMAzU1vNPfj8lFs2RHkEJcd3NzQ6fTodFoSE5OJisrC9gugZ85c4be3t5dScKuktZtYqCpqakufQfY/h6Dg4OX6Yi5AlEUaW5uJjg4mIiICLQB6VyX+6/kJj6CeUtBvf95Wr58O2JDA+L9921nsC6B0kuOX6YnKeHv5bt3vp+qqio++tGP0lrTSLZ7NBuCicULjSSHEVjB9r0WGhpq74C1yTHU19eTmJhIRkbGgYzp94Pk5GT6+vr2bEyyWCz09/dTWVmJQqHgxIkTREdHH7rIs0wmIzIy0iV5ihdffHFHtkqn0zE6OkpLSwvf/e53efDBB1lZWdnTz283nD9/noWFhR2/hyiKLC4u2u+j5eVl0tLSKCsrIyYmxuUu2pCQEKKjo/0FQUhw/u6rjyO7IgVBkAONwIQoincIgvAMkMe2oWIv8JAoik7TG4IgyEJCQu658847jzQIHB0dtU+qVwpKpZL4+HhiY2OZnp62W6msr6+jUqmuWkegKIp0d3eTl5fn0uc0Gg1lZWUMDw9TWVlJQkLCgXgEF+P8+fPExcVJ0qtSq9WUlpbS3t7OuXfeIetTn0LIyYHPf/7A47DB002N32AERo9NfG9z58Wxt+j1WkRtWCZjZZHS1Ed55OF/4u233+GZZ57h4Ycftn92bXM7qFreMHOnvgrNZBe+d99N6+oqXvPzBAYGujyetLQ0qqurCQoKkjxpCYJAbGwsg4ODDtW/V1ZWGB0dZW5uDk9PTwRB4OTJk7v+XW/M8qFjzEB/hEBMOxjOWyn6YApf/OIX+eIXv0hvby+/+c1vCAsLwyM1Ffd77uG2227D40IJp9iBlQ3sbuC6F9bX1yVtDGB7I5GUlISnpyexsbHExsZiMpmYmpqira0Ns9lMeHg44eHhmM1mjEajS8TsiYkJfH19XZJ+gL9KK2RnZ+87gBBFkfb2djvH0wZBEIjQHkPjk0R1/evobxim7TOzZP33H1j+m/fj9dzLyBU7A/2gEi+WWja4KfNBviC3UjkxQWRkJN5BgVTO9jFjWEelUKKQH97cFRcXR01NDRMTE4yNjeHp6cnx48eveEBlg0qlIjQ0lOHh4R2/p8ViYWRkhJGRETv946jHGBkZSVVV1Q4T6b1gNpt55ZVXaGpqsj+nUqnsHaE2M+re3l7Cw8MZHx+3v8/m5wd/9QDU6XRMTU0RFBSEVqtlamqKgIAAxsbGmJqawtvbm8jIyEMTfH300Uc1fX19jwCHN5EfEY4yWPkHoOuix4+JopglimImMAr8ncTjlJ44cUJ1lO7dGxsbiKJ4xQ0tbZDJZISGhqJWq0lJSWFoaIiqqirGx8evim7U5OQk/v7+roluXoCt9l9aWsrCwoJkc2dHmJ6eti9sUmErI0S/8QbMzbH2f/8vHGJ5daZiFcuaSNR7A/jFwl/o9VgkcHmSm/Dj5qzP4usVzje+8Q1ef/31HUHVutHCT9+ZZ2nNzO0Lpwma7kHz4IN4ZWWRm5tLe3u7y3wp2M68JCQkuNy1FB4ezvT09GXlBLPZbLdv6urqIjAw0F46MxgMewY4Xu5yrkv3odlkRghToBrwZ2v1r9mPxMREvvCFL/CRj3wEgAWFAqu/P6cHB4kPDkbrhFsoiuKha1iJosja2tplNjZKpZLIyEiKi4spKCjAYrFQXV1NbW0tGo1GcpBnsVjo6+vboa4vFd3d3Wi12gPJBvT29mK1WklOTt71dU9PT44X3oWwVoDXP36HsYevx/eF1xn4u1P0j7+N2fJXzqJHiBKvWBUGWQaPJqfy+g9+QFxcHEEKHzxlKpY2jXioDn9ZCQ4Oprm5mejoaDIzM69aUGVDbGwso6OjmM1mrFYrw8PDnDlzBrPZzPHjx4mPj78iY1QqlWg0Gkkc17feeovk5OQd8+jc3Jw90zQ4OEhfXx+xsbF2P9ja2lpEUeT555/f4fV3sQfgnXfeiUKhoK2tza6wX1paSm5uLkFBQYeWIHjve98rk8vlDwpXW4NIAo4ksBIEIRy4nW1vHwBEUVy58JoAeACSZqXQ0NC/++QnP3mkZcCjIK27io2NDUwmExEREeTl5ZGXl8fKygqnT5+mt7f3ULVCHEEURfr6+nbU4PcDNze3HebObW1t+/oOJpOJrq4uMjMz93WD+nV2Yk1JoXFra4ej+kGwOWtirmaNgBxPui3tLPiLhCxNcatnCabFWD7/+S/YuzpvvfVW++c2jFZ++s62zs+tcxVoF4cI/MhHcL/QOu/h4UFWVhaNjY37KqWGhYVhMBguE/J0BJlMRlRUFMPDw9tj3Njg/PnzVFZWYjQayc/Pp7CwEK1Wa/fcCwwMdGjmXJioJshXQa2fFcEiY+zPe48nMTGRhpYWWuvreerZZ52O1xVx0I2NDUmbA71ej6+vr8PrS6VSER8fT1lZGWazmY2NDSorKxkZGXGqVTc0NERYWJjLtldzc3Po9foDdQcPDQ2xvLzsNGvg4eFBUWERY0Pr+HznN2zedxeJ/1vJyg+/zl/qv0jf2F8wW7b1wkzRy1hNbph88tj4/e/prK1lamqKaLcgVjfNh1YGhG2ys61ZJC0tzWUT8aOCQqEgIiKClpYWzpw5w+bmJsePHycxMfGK82MvFep84IEHKC4upqenh/DwcLuzw0svvXQZaf3MmTNkZmaSlZXFPffcw1NPPWXnqz355JN8/OMfJz4+nri4OPtcZvMAjI2N5ZVXXqGsrAyr1Yq3tzfHjh3bt/CtM3h5eVFQUOAOFBz6wQ8ZRyK3IAjCr4EnAG/gs6Io3nHh+eeA24BO4HZRFB1uzQVBkGm12qnx8fHgo+r2EEWRioqKK5K2dYSOjg78/Pwu6zIym82MjY0xMjKCv78/sbGxR+psPj4+jl6v36GBclDYOqj6+/uJjY0lMjJScpDU2tqKRqNx2TLkwokhMBDe9z5MTz7JuXPn7HY9+72eRFFk8CcLGKa2kN0+y7vKCmZ9gnnIPYdXf/YG//Ef/0FISAi1tbU7GiEMW1Z++u48M0smbpl9h8iNCTQf/jBuu3SVjY6O2j3gXA0m19fXaWhooKysTPJ3NJvNVFRU4Ovri9FoJDY21h5I7YbFxUWGh4cd+ukNThv5ybvzlIsWopKsxOdGOx13Z2enU6kTo9FIc3MzxcXFDt8niiKnT5/eU5bhYvT09KBWqyVlRKemppifnycjI4PNzU1GRkaYnJwkPDyc6OjoyxaUra0tqqurOXHihEvXnO1zRUVF++4CnJycZHh4mMLCQsnnXl9fp76+nvysLLzuvx+xooLO//Nx+tIE3BReeCky8Vakoa4Pw7xuhpWnOfb1r/LpT3+a+77+KH+ssBLpEcDHb3Ddx/JiiKLIxMQEfX19pKWlERwcjCiK1NTUkJSUtK8GgMPCxWPb3NykvLx8X9n9w0RNTQ3p6elHujbAdhZ4bGyM6elp/P39iYiIICAgAEEQGB0dxWAw7CszKxWvvfYan/jEJ/5nenr600d2kkPAoWesBEG4A5gVRbHp0tdEUfwbIJTtEuH9Eg5XUFpaKj/KFlq9Xo+Pj89VDarMZjOzs7OXaUXB9s4oJiaG8vJytFot7e3t1NbWMjs7e2DbnEthMyw9aLbqUgiCQEREBMePH2dtbY2qqioWFxedfs6mqr5vodT+flhchKIilEolubm5eHt7U11dvW/VYv15A2tDRmRZa/SuvMS8t4ZEZRAWvYKvfOUrBAcH89prr+0IqjZNVn5WMc/00hY3Tb9NpHGawIcf3jWogm3ehEql2pdthVqtJiwsTHK3n16vt3Mu3N3dKS0tJTQ01GFWyN/fn+XlZYeZmlitirQId6rlcmYszluxL/YLdASpPoGbm5uX6fvsBVdsbEZGRuykdXd3d5KSkuxBbFVVFd3d3TvKqr29vS7rvImiSGtrK8nJyfsOqubm5ujv7yc/P9+lc6vVanJycmg4dw7DCy8gpKeT9rmfUWY5BRYvFjfPIvfpI+SkF6ZlEc3xv+Hm5GSee+YZgrY8wazAqnTNW/NSGI1GGhoamJ2dtauRw/Y8kpWVRXt7+5H79u0GURSZnJzkzJkzLC0tUVxcTFJS0qFlwg+CmJiYI7OXMZlMDA8PU1VVRXt7O97e3pw4cYLs7Gw0Go1982fjXB0lbrzxRoA7j/Qkh4CjKAWWAncJgjAMvARcLwjCC7YXRVG0AL8E7nZ2oODg4AceeOCBIy0DTkxMXFU/PtsYnC1mgiAQEhJCSUkJqampTExMcObMGUmlCKkYHx8nODjY5ZKFVCiVStLS0sjOzqanp4eWlpY97WjMZjMdHR0HIz7a7FMKC4G/krUzMjKor693eRKwGK1M/WkZeaCVAa9nWfT1wSJTkC2L46677kImk/Hmm2+ytLRk5zwYTVZ+VrHA5OIWN02+TYy4QNDHP47SiaxHWloa8/Pz+9IHi4uLY2ZmhtXV1T3fs7KyQn19Pd3d3SQmJlJeXr6nsvqlEASBoKAgp2WZm4/5ggAtE86vJ7lcLqn8KbUUKJVfZTKZsFqtkq75jY0NLBbLZVkBhUJBbGws5eXluLu7U1VVRU9PDysrKywsLLicbR0ZGUGlUu260ZICvV5PR0cHhYWF+yrJ+Pr6kpWVRX13N6ZXX8UaEID33R8j2/1W4sKuZ3CyggF+jbtOwWKHG4/+/WfQr6/zxte+CyYlm/L9OzJMTk5y9uxZIiMjycnJuWz8arWaiIiIA6t9uwJRFJmZmaGyspK5uTkKCgrIyMjA3d2dqKgoJicn92W/c5gICQlhYWHh0MZh+86NjY12i6Dc3FyKi4sJDw/fNVhXKpV4enoemFPrCGq1mvj4eHdBEK6+erYDHHpgJYriFy64SkcDHwDeAT5s+yEucKzuBJw6yMpksvfcfPPNR0ZUE0XRZTf7oxjDyMiIS4KgPj4+HDt2jKKiIjY3Nzlz5gzd3d2ueeZdAqvVyuDg4BVRe/f29qaoqAitVkttbS0DAwOXkfT7+vqIiIg4kBgidXXg5QWXtLj7+/tTWlrKyMgIHR0dkhsEZk6vYlqxMh79G0T5JqtBqeiU/ix2TzA5OcnLL79MUlISRUVF9PX1MTI2wQunFxifN3LD5DvEua0S9PGPo5DQqSaTycjLy6O7u9thgLTXZzMyMnbVttrc3OTcuXO0tbURFxdHUVER/v7+KJVKQkJCdnQCOUJYWJhd12Yv+KkVlKV6M7vpTe+E4wyh1ODZarVKysBIDawWFhYkd2EODw87vE9lMhnR0dGcOHEChUJBZWWlyyWr1dVVRkZGSEvb3YDbGdbW1mhpaSE/P/9AG6SAgIBtu6iREeq//GWUW1uEPvYY6RF3kRx1O6OztazG17K1aCE//0GSIyP58S9/BWYFa4Jr1ytslz4bGxuZmpqitLR0V1FiG2JjY5mbm3P5vnAVoigyOztrF3TOy8sjKytrx5wkl8v3FOq8krBVBQ6aPVtZWbFr083MzBAXF0d5eTkJCQmS5mIp88JB8aEPfcjfx8fHaWLmauJK6VgJwE8FQWgH2gEd8BWHHxCEmOjoaE9X25NdwcLCAv7+/oeuL+IKlpeX8fDwkFy2uBgqlYqkpCROnDhh1xdqbm6WrIJ7MSYnJ11q1T8oBEFAp9PZycC23SBsLw6zs7P7Nqm1o7Z2W2l9l4XYzc3NvqOvqalxqkC+OWdi7uwaa7pOtvyHiEj5MAtWA4XqRLvExPXXX28/dkpmPr+u32R0zsj1k++QpDYQ+PDDyF3gQLi5uZGTk0NTU5PLO1F/f398fHzswn1Wq5W+vj5qa2sJCgqitLQPRwuXAAAgAElEQVT0skU/Li6OwcFBSVkrPz8/VlZWnGZLjyd74+VmYXDS+SIok8mcHu+wM1azs7OSyoBWq5Xp6WlJWSS5XE5AQAB+fn4IgkBlZaWkhgKLxXIgaQWDwUBjYyO5ubmH0uEsk8kwGAzI0tPh6aehuhrh3/6N5KjbSY+9m3G3P2Hx0zN7Zo1H/+mf6J6dQz83waZ8gxWL9M7WqakpqqurCQ0NJTc31+kcJAgC6enptLe3HzodwgZbR/PY2BjZ2dkcO3ZsTx5VREQEk5OTu2Zcd/Pt+/KXv0xYWJjdn++Pf/yj/bUnnniC+Ph4kpKS+NOf/mR//s033yQpKYn4+Hi++c1v2p8fGhqisLCQhIQEHn/8cUZHR13+TS41Pvb39+fEiRNkZmbi7+/vUsUgJCSE6enpI/u7ANx1110KLy+vDx7ZCQ4BRxpRiKJYIYriHaIoWkVRLBVFMUMUxXRRFD9o6xLcCz4+PvfcdNNNmr3Eyg4D10IZ0NVs1W6Qy+VERkZy4sQJIiIi6O7uprq6mqmpKUm/nSiKDA4OXhVhUrlcTlJSEvn5+QwNDVFfX09rayvp6ekHC3gNBjh3DoqK9nyLIAgkJiaSlJREbW3tnqUtURQZe30Bq2yTxcS3KUr/JN1sMPDHJmp/9ibAjnb4vqlNfvzWEgaTGzeO/4U4z3UCH3oI+T4Irj4+PiQmJtLU1OTyfZCcnMzg4KC9bCyKImVlZYSGhu46WapUKjQajaQSqSAIBAcHM+tEKV2pELg3VyDOz3lgpVKpnHaOSuVYSREHhW0ivhTV7qmpKUJCQiRly0RRpLOzk4yMDNLS0sjJyaGvr4/m5maHWeWuri7CwsL2ZVy8tbVFfX09GRkZDq1BpGJwcJCBgQFOnjyJu7s7/Xl52wbm3/kOvPIK8eE3kJ34QeYj32Jr0cKdeffQ2taLX1A4KE0M6fdW4r54zE1NTYyPj1NSUuKSqnxAQACenp4ui+I6w9LSEjU1NXZB1tzcXKcBulwuJzw8fFf18Yceeog333zzsucfe+wxWltbaW1t5bbbbgO27Y5eeuklOjo6ePPNN3n00UexWCxYLBY+/elP88Ybb9DZ2cmLL75ol1X5l3/5Fx577DH6+vpQq9VMT09L2ljbjI/r6+t3NT7eL69ZoVDg4+NzufPFISI0NBRvb2+tIAjSROquAq5Z5XUvL68P3X777bKenh4qKipob29nbm7u0HSdrFarS2WAo4DFYmFxcVEycdYZbNyXwsJCsrKymJub4/Tp0wwODjrkr8zNzeHj43OwstsB4enpSUFBAd7e3qysrDA/P38w7lhz87Z69AV+lSMEBgZSXFxMb28vPT09lwUwC+eW2Ri2sBR3mvzsD+LmHUlF81l+848/5IXnX7D/tlaryNttK7xQsYBa3OR9/b8iOUTOeEYGowcgdYaGhuLn50dXV5fzN18EURRRqVScP3+egoICEhMTnU6YNpsbKUGc1LR/oMZP0kSrUqmclrOllgKNRqPTLPDGxgbu7u6Sjncxad0Zpqen8fT0tAc4Xl5eFBYWotPpqKmp2TWrMDs7y9ra2r42N2azmfr6+kPplrOJiS4tLVFUVIRKpSI9PZ25uTlmPv95KCiAv/kb6OsjWldKSlkpW14zLFYvo7wQEArWTXq66xAdZFlnZmaorq5Gq9Xuu2yZkpJCb2/vobg8LC8vU1dXR29vL6mpqeTn57sUoEZHRzMyMnLZ+uTIt+9SvPbaa3zgAx9ApVIRExNDfHw89fX11NfX24Wk3dzc+MAHPsBrr72GKIq888473HPPPQB89KMf5a233tpTiV0URfR6Pe3t7VRUVLCwsEBycjInTpwgLi7u0Li1V6IceN9996nlcvltR3qSA+CaDKwEQfBVq9W6goIC8vPzOXHihF3t9fTp0zQ2NjIxMXEgot78BYXrq6k1dpQ2Ol5eXmRmZlJSUoLFYqGyspKOjo5dxSf7+vquCLfKGSwWC9PT01x33XXI5XIqKyslZ90uQ13d9v8SAivY7vAqLi7GYrFQV1dn71AzGjYZ/eMsRu9pkk7loNVk8NZoPb98+Nto/AP4zW9+g0KhYM1g4fmKBU53rJLmscyd7T9DGx9G4IMPkl9czMzMDAMDA65/jwtISkpidXVVMgfKVl6JiorC399fMh/Fw8MDb29vSXpBvr6+rK2tOV3YvLy8JHlISukMlFIKtFqtCILg9L6SWgZcW1tDEARJGTCr1UpPT89lYpy20vfx48dZWlqitrbWXn42Go10dHSQnZ3t8lxgtVppbGwkMjLSIS9JCmwBmlKpJCcnxx5wymQycnNz6RocZP2557a9Nu+5BzY2iAjJI6jcE/maL21/ruDZL91F56/+wLivyNLrr19275pMJlpaWhgeHqa4uPhAFQOVSkV0dPSBiOy2Jo7Ozk4SExMpLCzcV8bQxlGUGlD84Ac/IDMzk4cffpilpSVgu4JycaODzZ9vr+cXFhbw8/Ozl43Dw8Opq6tjcXFxx6b0UuPjoKAgScbH+0VwcDBzc3NHWg68++67PXU63UNHdoID4poMrORy+a333nuv50WPCQ4OJjMzk5MnTxIfH8/q6io1NTWcPXtWkmnqpbgWyoBXQpjUpshdXl6On58fTU1NNDQ02OUOlpaWUCqVLlttHAUGBwfthPX4+HiKioqYmpqirq7OdXPn2lqIigIXFhuZTEZqairR0dGcPXuWufkZWl6uRL6pJvAmBWHB2WxsbfIvH/57NuZWePW3r6LT6RieNfLkn2YZm9/iZq8JSptfwiczjYB770VQKJDL5eTn57OwsLAvCQXYXphzcnIYGBhwmP2xLVy28kpYWBgZGRku+TcmJCRIGqfUcqAgCJKyUVICKymlwPX1dUlBkNTGFWek9YsxMjJCSEjIntlfpVJJVlYWCQkJ1NbWMj4+TmtrK6mpqS7zLEVRpKWlhcDAwAPPI5ubm5w9e5bQ0FCSk5MvC/BUKhXHjh2jcW4O809+Au3t8Hfb5hlR+UkoAi2ETm0btp/99R9Y8lWy2N3O2tmz9mPMzs5SVVVFYGAgBQUF++KVXoro6Gjm5uZcnv/X1tZoamqivb2duLg4iouLJdsf7QWbPZSzgOJTn/oUAwMDtLa2otPp+Od//mdgd7smQRBceh5Aq9XaA7LdjI8dadQdBmxm51IkdfaLzMxMRFHMEgThyqqxSsQ1GVjpdLqH7r777l1nRkEQ8PPzs6cwbaa8586d4/Tp03R1dbG0tOTw4hZFkaWlpSvmiL4b1tfXr6iNjkwmIywsjLKyMuLi4hgYGKCystI+sVxtGI1GxsfHdxDW3d3dycnJITExkebmZjo6OqSn/evqJGerLoVWq6WwsJDmuldxH0hCkbhK7AUfyWf/8AsGz3bwxP98m9y8PCo7V/nJO/O4KQQ+4NFNdMPv8czLw/9970O4qMRk6/JbXl6mp6dnX+OyaXG1tLTsGoAsLi5SXV2NRqMhLy/Pntr38PAgOjpa8nm9vLxwc3OTRLiWmvb383NeDpQaWDkr3UkhrttsbJy9z2KxMDc3JykbZNP7kZL9DQwM5Pjx4wwMDLC2tubyXCSKIh0dHbi7ux8427yyskJNTQ2pqakOpSF8fX2JjY2lVadD/Pd/h+eeg2eeQZAJhN0QhLvBi1OlH2ZyaJSh6g7m8xNZ+fOfWe/u5ty5cwwODlJUVERERMShZekFQSA5OVlymXxjY4OWlhZaW1uJjIzctYljv3B3d8fPz8/pRsPG1ZPJZDzyyCPU19cD2xmni7v6bP58ez0fGBiIXq+3z4ljY2MEBQWxvr5OW1vbgY2PDwKdTrcvqRipEASBU6dOKYCyIzvJAXDNBVaCICisVuuxY8eOSXq/h4cHMTExFBcXU1JSgq+vL4ODg1RUVHDu3DlmZmYu4+osLS253O1w2BgbG7tqNjoBAQHk5+eTlpaGwWCgra2Nvr6+q6rF0tPTQ0JCwq6LZkBAAGVlZajVaiorKxkfH3e8K5yagtFRh8R1Z9gy6gk4X4ioNLMRvY7JZEIUReSlofzruz/gkw8+yi/OLPKXcyukhLtzv6kez4YK1MXF+N15J8IuO0JbSWV9fZ2urq59pcq9vLxIS0ujsbHRzucQRZGBgQE6OjrIz8/fVdk+OjqapaUlyaTSxMRESVkrHx8f1tfXnQa8/v7+9pLHXjisUqAU4vrS0pK9a88RJicnJe/w+/v7d1Vf3wu2UmBCQgLV1dUudfP29/djMplIvURKxFXMzs7S3NxMXl6eJL5pREQECoWCkYceghtv3Ca0t7bim+KO2UfGByPvwNvXg+bn/8JkRjCCRsPCr36Fv0pFYWHhkfA4g4ODMRqNDq9tg8HAuXPnaGxsJDQ0lNLS0kPjtl4MKUKdFzeH/Pa3v7V3DN5111289NJLGI1GhoaG6Ovrw0aH6evrY2hoiK2tLV566SXuuusuBEHguuuu4+c//zk9PT1885vfpKCgwF7+j4qKOnIl9r3gzPbqMPDAAw/463S6Dx/pSfaJay6wAkpvvPFGxX6CHqVSaW/ZLS8vJywsjLm5OSorK6mvr2d0dBSj0WjnNl0tiKIouXX7KDEzM0NqaqpdObq6upq2tjbXy24HxNraGsvLyw5Ls4IgEB0dvcPcec+FyEV+1aUQRZHeX46gXA8k8h4/dNEhPP3007zwh18xZVriuvhb+N8/zzEwvcltx7y5cepdLC2NeJeX43vLLQ4Xa0EQOHbsGEajkc7Ozn0FV8HBwYSEhNDe3o7JZKKhoYGNjQ1KS0v3DCgEQSAzM1Nyi7qNZ+JssbcJ187MzDh8n7+//6FlrKSUAp1loqSWAaV27RoMBmZmZiSXDG3SCjZvtdzcXFpbW/ckHl86psXFxYOJ57Jd4uzt7aW4uNilBTgjI4OR8XGWn3xy2zLq7rsRVpbRJyoJFN350F1/Q8+fm6kfbGEkNQq5KOLV3n5kG1lBEEhLS6Ojo2NX3bb29nbq6+sJDg6mrKyMkJCQIxuLj48PVqvVPofu5tv3+c9/noyMDDIzM3n33Xf53ve+B2yLAt93332kpqZyyy238MMf/hC5XI5CoeAHP/gBN998MykpKdx3330kJSUxOjrKvffey7e+9S1uvvlmlEoljz/+OEFBQURERBw5gdwRFAoFHh4eR6o1Vl5ejiiKp65FU+Yj8Qo8CLRa7Y+effbZR2wtqIcBW9p/enqamZkZ9Ho9CQkJhIWFXRVukV6vp7+/n7y8vCt+bhssFgtnzpyhvLzcvlDZ1HYHBgbsatJXguDf0NBATEyMSx2ay8vLnD9/Hm9vb5KTk3emuf/1X+G734XlZdjHDrnvLwNsVLpD1ihZdxezurpKRkYGBpmJT/z8Z8hGk/DxkHNvkS+eb7/KZlcXPjfeiPeJE5LPYeu+gu2FytXfWBRF6urqWFlZIS0tTTJfsKurCzc3N0nl34WFBYaGhpxepysrK3R3d1NQ4Ngb9d133+XkyZN7ftetrS0aGhooLS3d8xgDAwO4ubk5LFlVVVU5VR2vqqpy2o22srJCV1cXhRIC9JaWFrRareTNUltbG97e3jtK32azeYef5W4B5NTUlL2kdhC/y87OTjY2NnaQ1F3B2toajY2NHBcEFDfeCLffzsuf/TGhlUbWNsb4hfU5dA8VcbubhqwBL1YrKtB89KO4HyHtoLm5mbCwMEJCQjAajfT39zM3N0dCQsKeEiNHgYv9JA8ToiiysLDA6Ogoy8vL9jLhbpspk8nE2bNnKS8vP9QxuIKRkRFMJtORNkadOnVq7q233jopimLnkZ1kH7jmMlaCINx42BeDIAh4e3uTkJBAdnY2AQEBuLu72xVmOzo6WFhYONIuhosxMTGxf/+7Q8JuJQ5BENBqtZSWlpKcnMzY2BhnzpxhdHT0yLy5lpeXMZlMLste+Pr6UlJSQkBAANXV1QwPD//171dXB1lZ+wqqVkbXWa9WYtAMknD7tpnoY489xtjYGLd95TEYTiLIw8gjJ33wePNlNru68L3tNpeCKtj+rTMyMpDJZJw7d87la29ubg6DwYBSqXSJBJyYmMjY2Jgksq9Go8FoNDrNYPr4+LCxseG0lKxWqx16NCqVSqfHkFIKNJvNDoMqqTY2w8PDkiQWVlZW2NjYkJwFn56exmAwXHZshUJBTk4Onp6e1NTUXKbpNT8/by8P7TeoslgsNDY2IggCeXl5+z6Ol5cX0dHRdPj5wX/9F7z2GjEv/IC+IAtaIYJ/uuGreJr9+GNXH8rCIuQBASz//veIhyCNsBeSkpLo6emhs7OTmpoafHx87JWLK5nUCAkJYX5+/lBkIGA7iO3q6qKiooLx8XGioqI4efIkSUlJe2aobfPCUdrLOINNLPQo8f73v99frVbfLOW9giA8KwjCrCAI5y967v8TBKFbEIQ2QRB+KwiCn6NjSMU1FVgJguAfEBDgdZSE7unpacLCwoiKiqKwsJCysjI0Gg1jY2NUVFTQ3Ny8p4ruYcBmk3AU9X1X4GzR8PX1JScnh8LCQjY2Njhz5gw9PT2SjHJdQXd392Wt6VIhCALh4eEcP36c9fX1bXPnuTloaNgXv8pssDDwi1ksynVU103h6R7A7373O5555hmKP3UnCT734q+Wc3MKTD/7I4z9/fi95z147ZPLZSthqFQqWlpaJAdXIyMj9Pb2UlJSQlFREW1tbU6V422Qy+WkpaVJLglK7RCUQlZ1RmCXsvg5KwWaTCanquU2qRVHMJvNLCwsSCoXdnR0kJqaKmn8m5ubdHV17SmtIAgC8fHxxMfHc/bsWXsgasvQFhQU7Mv/D7YbRGpqaggKCpI8XkeIiopic3OTmQceYOvOO8l5+mtsTZ5jWQUrZ03o343me3d/haLbHuJp7fv5md8pnnp1mBdOL/Db2iX+1LJMZecqzYPr9EwYGJvfYnHVzOaW1eWNhslkYnx83C7/YRNLvhpVIplMdhnh3FVINT52hPDw8EMXUHUF7u7uiKJ46GvGxbj++usV/v7+75X49p8At1zy3F+AdFEUM4Fe4AuHMS7XfROOFmW33HLLwXtwHWBmZobc3Fz7Y7lcjlarRavV2rsFp6en6evrQ6VSodVqHbZPu4rFxUX8/Pz2vVM8DCwtLeHu7i7pO7m7u5OcnExCQgLj4+PU1tbi4+NDXFzcgTVQ9Ho9oigeuDvTZu68urrKwGuvEbC+ztaxY7jSAyOKIr0vTiEYFMzlvkpZwiPMz8/z8CMfIyQ1ivfd/58sjyu4/zo/AtvaWFtcZCY5GUGn4yDbAEEQSElJoaenh6amJnJycvYMHERRtHsHFhcX26+hrKwsGhsbKSkpkXRdBQUFMT4+ztTUlFO166CgILq7uzEYDA6vl9DQUDo7Ox2W6Pz9/ZmennaYrRUEwWHw5KwrUApxfXZ21mnp1CbHIkULS6lUSmrVt8kj2IJpRwgJCUGlUtmFP3t6esjPz9+3RMHq6ipNTU2kpqYemjeqLet6+vRpfD/1KYpaWvj4C59l/MdnWHrLzAMJwbR86P1U/OgnRGr9uP89n2RDv8aKuyfTehkbmxbMe+g9y2XgqZLhqZKhVskv/H/hsbvswmtyfNxhaXbUnsk5ceIEzc3NV7UxCSAyMpLa2lqio6Mlj8W26R4bG2NtbY2wsDByc3P3vfaEhITQ19dHUlLSVfs9tFotMzMzR9aolZiYiMViSRYEQSaKokP1cFEUzwiCEH3Jc3++6GEtcM9hjOuaCqx0Ot17b7nlliNrY9ja2sJqte45OQmCQEBAgH2hX19fZ3p6mubmZiwWCyEhIWi1Wnx8fPZ9oV4r+lmu2ujI5XKioqKIjIxkbm6Ozs5OrFYrcXFxBAcH7+v3OEi2ajd4e3uTdYHX0Dc6iqq/n9jYWEkdXVOVekzDAvrE0wQl6lB7BLLALLmfuIXcoutYnQgmO8aT0OURFquq8MzLI+PWW2lubmZhYYG0tLQDacMkJSXR19dHY2MjeXl5lx1LFEXa2toQBIH8/Pwdv3dAQAARERG0traSk5Mj6W+RlpZGdXU1QUFBDjMgtgxKf3+/Q86It7c3m5ubmEymPY/n5+dHd7dj73U3Nze2trb2vEedlQKlENeXlpac8l9GRkaccsZEUaSrq0syV3JwcBAfHx/JgY2fnx/Z2dlUV1eTmpq6bz7o/Pw87e3t5ObmHqogpF6v59y5c4SEhCCKIrLnnoNTp4h45QkM8V9A1QUf/vtjGIU5fv+/T5Me4cPf+/nhpopC86EPAbBlFtkwWtkwWlm3/b9p2fnYaGVqycSG0YJh69JMlsjdWTJOnDhhD7j9/Px23TQ8/PDD/P73vyc4OJjz57erQZ/73Od4/fXX7bzD5557Dj8/P4aHh0lJSSEpaZsOUFRUxFNPPQVAU1MTDz30EAaDgdtuu43vf//7CILA4uIi999/v70a8Pjjj6PX650G3SsrK4yNjTE7O4tGoyEuLk5Sx6ozKBQKvLy8WF5e3mG5dSWh1Wrp6uo6ssBKEASys7OFqampVOC80w84xsPALw9hWNdWKVAUxZMlJSVHdvy5uTmXSnBqtZq4uDhKS0spKipCrVbT19dHRUUFbW1tzM7OumSxYyMf/r9so2MThSwqKiIjI4Pp6WlOnz7N0NCQS+VTvV5v1yQ7TAgXJtMUf3+74ryztt/1sS1m317HGjqPPuIsiZE3M7+5zEv6am761L1EyG/Dw03GjTEiS6+8glKrxe/WW1EqlRQUFODh4cHZs2cll+P2QkJCAhqNhoaGhh2cNqvVSlNTEyqVak+iu63NX6q6u5ubG/Hx8XbPMUfQ6XQsLCw4TenrdDqHPoNKpRKLxeLwnnHWGeisFOhMm2p9fR13d3eHx9Dr9ZKM0cfGxtBoNJK06PR6PRMTE6SkpDh9rw0mk8keEI2Pj++rrDM2NkZnZyfFxcWHFlRZrVa6uro4f/48OTk55OTkYLFYmMnIgE9/GuH73ydM3Ypx3kzu9DFu+sK9XPeRO/jmd77DW6KIsa+Pzc7ObeFYpQx/LwVhGjcSQ93JjvGkNMWbU9m+vLfQnwdPaHjkVBD/cEcIX7g7lC/eq+UDOVsUaIYpi9kEBMwq7Y4sZkJCwq62TLv59p06dYrz58/T1tZGYmIiTzzxhP21uLg4u5+fLaiCbYHPH/3oR/T19dHX12c/5je/+U1uuOEG+vr6uOGGG6ioqNjVPxC2N/mHZXzsCFfCXsYRvLy8WF9fPzQrut1w5513+qvV6lMHOYYgCP8OmIGfH8aYrpnA6krwq1wNrC6Gm5sb4eHh5OXlUV5ejlartQcVjY2NjI+POyXeLiwsEBAQcKSqt84wOTmJTqc7lBvX29ubrKwsSkpKMJlMVFZW0tnZKSnA6O/vP5puEY0GFApkMzN2c+fh4WHq6+t3JWybNywMvjgHHmYmk18iNCib8akVkpOS6K1uI3OpmKlFC7dme7H56stgtRJw//0IF7IytoxOSkoKtbW1TsUBnSEuLo6QkBDq6+vtQUhDQwP+/v67KmJfjPT0dGZmZiSPITw8nI2NDadCoIIg2FWlHSE0NNTp4u/j4+OQUCslsHJWCnQUWEmZA6SQ1i0WCwMDAyQmJjp8H2zztVpbWzl27Jjke99isdg94nQ6HcXFxQwNDUleJG1l48nJSUpKSg5F5Ry2uV5VVVUoFApKS0vtMg2ZmZl0dnZi+trXID4e9eOfwMN3E8X5GLT6KUq/9gG++t/f4v7PfhalVov+jTewusC9sVqtjIyMUF1ViUw0cvN1BdxYGIu3h4zBmZ3H2cuWaTffvptuusnOySsqKnJqGTU1NcXKygrFxcUIgsBHPvIRXn31VWDb6++jH/0osO3b9/zzz++wl7nY+Li2tvbQjI8d4UrYyziCbfN8lKbMLvKsLoMgCB8F7gA+KB7SD3XNBFZA2a233nqk/CqbMOhBIZPJdljsJCQksL6+Tk1NDdXV1QwMDOza/TQ9PX1V9bPgaGx03NzcSExMpLy8HB8fHxoaGmhqatpTEHJ9fZ3Nzc1DUzzeAZkMQkK2RULZNnfOz88nJiaGhoYGenp67BOdaBUZ+fUilnUriuv7McmWiQ69gfd9+D5WF1e4J/E26jpMJOhURHRVYpqYwP9970Oxy7g1Gg0lJSX09/fvW/zThujoaEJDQ6mtraW+vp7AwEBJ8gg2dffOzk5JWmQ2bavz58873VGGh4czPT3tcPPg5eXF1tbWZd1sF8OZnpWzwEpKKdDT03PP12dnZx2W4kwmE3q93mlWeWBggIiICElq1h0dHcTExEjWirL5/4WHh9vLWbbs6PDwsNPgymKx0NzcjMlkoqCgwCmZX+qYenp6aGtrIzs7m4SEhB1Bvru7O7GxsXSPjcFPf4owNkZU7dcxLwokDupwA6I/WIjKwwNTSQlvNDay+u67Ts8riiLj4+OcOXOG9fV1SkpKSE5ORqlUIggCMcEqhmaMl91vtvK1K3j22We59dZb7Y+HhoY4duwY5eXlVFZWApd3dNt8+2Cbv2uT29DpdMzMzKDVaunv76e9vZ3Tp08fmfHxXpDL5ajV6iPVk3KGoKCgIxULTUxMxGq1JguC4HI8IwjCLcC/AHeJouiaL5IDXDOBVWho6JHyq2wT7mFniwRBwNfXl6SkJE6cOGEnH7e1te2w2LFarZK6kY4S6+vrCILgcOE5CGzdMGVlZURHR9PX10dVVRWTk5M7Jr4jy1bZoNPBJR1qQUFBlJWVoVAo7ObOs5WrrPVv4V5kZsT8J4ID0vnc//kePTVt/Nu3H2duaVtj6JTPLBt1taiLi/FwoHStUqnsO9mampoDdcNERERgNptZW1tzKRC2ebo1NTVJUtJXq9WEhoY67fyTyWRERUUxPDzs8H3OyoF+fn4OFdgPkrESRdHh61ar1SkHa3x8nPDwcIeZQaPRyMTExA4Nqr0wOTmJ0WiU/DcURZFz504MEQoAACAASURBVM7ZlbMvhi24Ghoa2jMzuLW1RW1tLf7+/vvSR9sNKysrVFVVAVBaWrpnSTEyMpLl5WWW09Lgs59F9evn0MyfRjNQQtDSBL3GSSa2Fvja//4vj7z8Mr989llMe3SSiqLI5OQkZ86cQa/XU1xcTGpq6mWBbKxWxdqmlbmVnTQEb29vFAqFU7V/G77+9a+jUCj44Ac/CGxfx6Ojo7S0tPDd736XBx98kJWVlT19+y7F5uamPUM1ODhIUFAQ5eXlR2Z87Ai26srVQlBQEPPz80d2fEEQyMrKEgCHNgSCILwI1ABJgiCMC4LwMeAHgDfwF0EQWgVBeMrRMaTimgmsrFbryeLi4iM7/pWSOLjYYqe0tBRfX1+GhoZ45513MJlMzM3NHZkmlDOMjY057No6LAiCgEajoaCggGPHjrG4uEhFRQX9/f2sra2h1+sJCQk5ugFotfaM1cWQyWTExcVtmzv3zTL19gpbIavI0voxmdc5t6Dm519/iuN33MB7b3qUvkkjJ+PkWN/4LcrwcHxPOS/j27zLbO3yUvz2LoVtcdXpdKSmplJbW+swC3QpfH19iY+Pp7m5WVLmLC4ujpmZGadZrqioKMbHxx1ev87Kgb6+vg7V3A/CsTIajQ5LXnq93iEpWBRFRkdHnd4jjuyXLobBYKCnp2dPaYXd0NXVhUKhICEhYdfXlUolhYWF9Pf3X1byXV9f5+zZs8TFxREbGyvpfI5gtVrp6+ujtbWVrKwskpKSHG5MbV2C58+fR3z8cUhLI/TX/4x8xkhMtzcqZFSsdvDtb3+booIC/u6VV/jNN76BeFG21OZKUVlZyfz8PAUFBaSnp++Z2YkN2X5+cPryayY+Pl6SVMhPf/pTfv/73/Pzn//c/ndSqVT2jHpubi5xcXH09vYSHh6+o1xo8+2D7S685uZmampqeOONN9BoNBw/fhxfX198fHyuGgVEijPCUUKlUmE2mw9VwshkMjEzM0NnZydVVVWkpqYGenl5OdSzEkXxAVEUdaIoKkVRDBdF8RlRFONFUYwQRTH7wr9PHsb4ronAShCEAI1Go75W+VX7hUKhIDQ0lJycHCIjIwkLC2NhYYHKykrq6uoYGRk5Uo2Pi3G1bHTUajXp6ekcP34cQRCoqqpCqVS67EbvEnS6XQMrG9zd3YnXJSIgsBG6QM/InzAFZ/KLV17F28+Hn/3PC7zZskKYv4L42t+ATEbAffchuFBSsRH8u7q6diXSOkJHRwdubm52xej4+HiXg6uwsDC8vb2dduHBdsCZkZHhVKhULpcTFhbm0HZFrVZjNpv3vK5lMhkymWzPbJpKpcJgMLCxsYFer2dubo7Z2Vn7P4PBgF6vZ2Vlhc3NzR1BnhR+laMy4NLSEl5eXg7LM1Lsl+Cv0goZGRmSzW/7+/sxGAykp6c7DMRswVVnZyeLi4vAtoxLfX092dnZh0I3WF1dpbq6GovFYg8OpMDX1xdvb2/GZmfh+ecRluaJrPhPNIPHiTGY6NmcYFlp5A9vvEFqQgIPPfkkf/rxj+1SA1VVVUxPT5OXl0dmZqZTqQE/tYIAL/llPCvY7pbd2tpyONe8+eabfOtb3+J3v/vdjkz+xRvgwcFB+vr6iI2NRafT4e3tbedIPf/881x//fWcO3eO7Oxsfvazn5Genk5PTw/33HMPbm5uV51A7ubmhkwmY3Nz86qNITAwcF+bTBuMRiOTk5P2kmptbS3z8/MEBARQUFDA3/7t3wp+fn7vOcQhHwjXitxC2a233nr47pwXIIqipDbso8TMzAwFBQX2SXt1dZXp6WkaGhoA7FIOXl5eR6I5srKygpeX16HwLfYDpVJJTEwMIyMjREZG0traikKhIC4uTrLgnWTodDA3B2Yz7PF9F6a3F6SkzDCqp4ycV/vwwGc/xu2f+z7N4yoMWxu8T2jHMj2N5kMfQrGP7kUPDw9KSkro6Oigvr6enJwcp+KOAwMDGI3GHbIJOp0OmUxGTU0NRUVFknkZKSkp1NXVMTk56VSvyt/fHx8fH6dSHDExMVRVVREdHb3nDtxWDtyLAO7n58fCwgJyuZyVlRXW19dZX1/HaNzmyhgMBqxWK0ql0s6lsWFra4uZmRnMZjMmk8kuoSIIAqIo4ubmxsjICH5+fnh7e+8Y49zcnMPynRTSemdnJykpKU6v1/7+fvz8/CSX/sfGxuwZGin3gkqloqCggLq6OqKiohgbG6OoqOjAens2Q++JiQmysrL21bWbkpJCVVUVoWVlKL74RXz+8z8JjLoJfbyC4RJfKlbP86DmBH8+fZqy7Gw+//jjeMfF4eHvT05OjqQuy4sRE6KiY9SAxSoil+387WymyGlpaTzwwANUVFQwPz9PeHg4jz/+OE888QRGo5FTF7LRNlmFM2fO8KUvfQmFQoFcLuepp56yE9+ffPJJPvKRj7C2tmbPZul0On74wx9y//332zfSL7/8MrB9P9TW1u6ZhbwSsGWtXJXZOSwEBQUxMzMjuVJhMBhYWFhgYWGBpaUllEolAQEBhISEkJKSctk6lpCQgMViSZKiZ3UlcE0EVqGhoe+9+eabj4xfpdfr8fX1vWoiaZubm9utxRctiN7e3nabHaPRyMzMDF1dXWxsbBAYGIhWqz3UDsLx8fGrrp9ls9EJDw8nPDwcvV7PwMAAnZ2dxMTEEBYWdjjfV6sFUYTZWdgloLBarUyNzaAmhHXzFAY3NVYB4lb9aZuco2VWTrFmA3VVFV5lZbhL6PzaC7Zs0OTkJNXV1WRnZ++5WE1NTTEzM0NRUdFl12pISAgymYza2lq7xIMzCIJAbm4u1dXVqNVqp1mH5ORkqqqq0Gq1ewZvSqUSrVbL+Pj4nryh0NBQWltbdwQpNpPixcVF5ufn7dlTX19fwsLCUKvV9nOePn16Tw2pubk5MjMzL/t9rFYrra2t9oxZf38/q6urKBQK/P398fPzw2Kx7Jk92traYnV11aFYrc32ylmwZBMZduR5eDGmp6cZGRmhqKjIpevfw8ODgIAAurq6OHny5IGDqrW1NTu/6/jx4/vuUlMqlURFRTEwMEDSF76A+LvfEf7mv7GU9GuyjkPd5gRTW4uoFAr++4kn0J47R5S/PwE5Ofs6X2yIiqaBDaaXTIRpdv59dTodvb29JCcn8+KLL1722Y997GO7HvPuu+/m7rvv3vGc2WxmamoKo9HI008/bW8uuHiz9Pbbb192LDc3N1QqFaurqy6ZXR8mtFotHR0dVy2w0mg0e0q72BIftkBqeXkZd3d3NBoN4eHhpKenO70WL5jbC1NTU2lA+xF8BZdwTQRWVqv1xFHyq642aXx2dtZhpK5SqYiMjCQyMhKLxcL8/Dzj4+O0t7fj6+uLVqt1KuToCLY0+2GKce4Hw8PD5Fw0efr5+ZGbm4vBYGBoaIjTp08TGhpKdHT0wbplbOXO6eldA6uhoSF81X6YgVXTGFvufvz4tn+nP6uED3/mezC7RUrtL1FGRuJz/fX7H8dFCA0NxcfHh+bmZiIjI4mKitoRHCwvL9PT00Npaemei2tQUBDp6enU1dVRWFgoaSFVKpXk5ubS1NREcXGxw99VqVSSnJzM+fPnd7gTXIrY2Fhqamr2tAzx9PTEbDYzOTnJ0tIS8/PzKJVKQkJCiI2NtfNV9mtSu9s5beXFiIiIHSWdra0tlpaWGB4exmAwUFNTQ3BwMDqdbsf7bPxDR/yrzs5OsrOzHY7NZqScn58vKUhaWFigp6eH4uJil7LJVquVtrY2AHJycjh37pzLgZkNoigyNDTE6OgoWVlZh9I5HR0dzZkzZ4iKisL9+eeRH8sh9tffwlr2OVQZCn47Ukneko7i665jfWAA1QE2vTHB29f0wIzxssBKJpMRGhpqV2Z3FRcbH6+srKDT6cjOznY5q2YrB16tOdjLywuDwYDFYrkqrh9yuRylUonRaMTNzY3V1VXm5+dZWFiwuyVoNBpiY2P3zUe74447/CsqKm7gGgisrjrHShAEd7Va7X2U/KrFxcWjae2XCFf4XXK5nJCQELKzszl58iQxMTEsLy9z9uxZampqGBoaclmIcmlpCV9f36tqo6PX63Fzc9u1I9HDw4PU1FTKyspQqVTU1NTQ2tq6/xZhW2C1C8/KZDIxOjpKgPd2ZmLZOILFM5CV8QV81d4XyM8CCvMW/cHBjIyNHZoGjJeXF6WlpSwtLdHc3GwncxqNRlpaWsjLy3MaPGs0GjIzM6mrq3NoaHwxvL29SUlJoampyamsgk6nw2KxONTCshF7d+v+W11dtWuZ9ff3o9FoKC0tpaSkxK4o7ePj45Qov5/ffDfbHTc3N0JCQnB3dycvL4+srCxkMhktLS1UV1czMjLC1taW08aOyclJfHx8nGYc2tvbiY2NlbTwrqys0N7eTkFBgWQeFmxfw3V1dajVarKystDpdAQFBdHR0SH5GDbYCO8Gg4GysrJDCapgO6BJTEzc5vilpsLXv4Zv75/wf7YOzbqKdbWVgoICvDUaftLQwMkPf3jf5/LykBPsq2BoF54VYO9mdeWa2s34uLy83KHxsSPYOvOulp4UbHPObJy8Kwmr1WrvzqytraWiooLe3l4EQSApKYmTJ09SUFBgnx/2W7UoKipSaDSaGw9z7PvFtZCxysjJyTmyGp0tzXhUEgNSzr+8vCyZ/HkxBEHA398ff39/UlJS2NjYYGpqipaWFsxms2SLnWvBRmdkZMQpf0WhUBAdHU1UVBSzs7N224m4uDiCgoKkl3Jt5N1dFv6BgQFiYmIQewQEBSwbxln1DmFjaZXw8HBsFA0RgfxTp+gbGqKyspL09PQDexrCduB87NgxRkdH7aXBjo4OUlJSJHMAAwICyM7Opr6+nvz8fEmfCwkJYWVlhY6ODqeZooyMDOrq6ggICNgzixIfH09DQwM6nc7eGj80NGQX0o2MjOTcuXO7EqltZfHNzc1du/jc3NwwmUwuBRu2gHGva8RmYyOTyYiJiSEmJoaNjQ27RhLAxsbGrveprTuuyInZ9sTEBBaLRVLn7cbGBk1NTeTl5blUwtvY2KChocHe2GBDfHw8TU1NknXqRFFkeHiYkZERMjMzD+XavhQ6nY6BgQFmZmYYKysjKS6NiDe+T+hXnqZF3Nq2wVGpsIgijR0dTE1N7bu5xlYONFtEFPKd14C7uztqtdqpvYzJZGJiYoLx8XHkcjkREREkJCQcCi9VoVCgVqtZWVnZ11pwGLDpSR11E5fFYmFpacle2tva2rJ3RlosFrKyso6ElpOWlobJZNpfGvyQcdUzVu7u7gUnTpw4MiMjW6fQ1eJXra6uHshb8GJ4enoSFxdHSUkJxcXFkix2RFFkfn7+indEXgyz2eySjY4gCISEhFBcXExaWhqTk5OcPn2a4eFhaVIVtsX8Eu2Wra0tpqamiIyMxLolIriB1WpiYm57NxUeHo7sQmQl+PmjvJBJy8nJobe3l6ampkPrrImMjOTYsWPU1NTYy2SuwM/Pj5ycHBoaGiRn9uLj4zEajQ67+mA7gxgVFUVPT4/D96jValpbWzl9+jQrKyvk5eVRWFhIWFgYXl5eiKK45+/lSI3ZFnS5go2NjT0zCevr63h4eFy2E/b09CQxMdFuKt7d3c3Zs2cvyywMDQ2h0+kcSjlsbGzQ19cnadEwGo32Dj5XODd6vZ66ujoyMjIua0a44JnG0NCQQ2V721hrampYW1vj+PHjRxJU2c4jl8tpaWkhOi4O8UvfR7k2S+z3nseClUf+/pOEhIaSeGFeaG1tZXFxkVOnTpGQkMCpU6fsmQ5RFPnMZz5DfHw8mZmZNDc328/z05/+lP/6z3/AZBH58c9/Z3++qamJjIwM4uPjef3113e97kVRZGZmhsbGRqqrqzGZTOTm5lJcXEx4ePihNvvodLqrqicVGBh4JHpSJpOJ2dlZurr+f/LePLqt/L7y/DysBIiF4AaC+05xE0WJq0QtFbviZXzkdiftcdw9do6Pt7IzcXqSSdsntvvYk3g5WTrT8cR2p5122d1xHU9P0s5JXLIrrtJGSVwlUtz3fSdIECBArG/+oN4rggC4iRQ8mXuOTpVICA/Le+93f9/v/d47yP3797l//z7z8/MYDAZqa2u5ceMGtbW1lJWV4XQ6z2wt1mg0GI1GnSAI8ami7EHciVVqauo76uvrz6xyFu824Fn5Z6nV6rCIHcnp986dO3R0dDA7O4vP55OnAeMZoyPtRE9yQZlMJi5cuEBzczNer1fO1jpw4dVqwWKJqFiN7QllDnpDoArgV6pZW9odA95bsVKkvK3JMxgMMmF49OgRY2Njp5J95fF4MBqNsm/Vcf3NzGYzly5dorOz89DFFN5efKenpw9tCeTn57OxsRHVc8rv9zM8PMzm5ibr6+tcvXqVioqKiMrLQZ5WFoslpnnjYV5W0SDpNKLhoGtwZ2eHnZ0d8vPzaWxs5Pz58ywvL3P37l2Wl5fx+XzMzMwc6Hy/11rhsFau3++nvb2dioqKY7XdFhcXefLkCQ0NDTGJkEqlora2NqzNvP91Tk9P097eTmlpKdXV1WcyJex2u3ny5And3d0UFRXJFhaK6y04yt5F2Q//Ef36Fh/4Nx/k1q1b5D57P0+ePInI2/vGN74BwOuvvy5n8/2n//SfeOWVV4Dd+/tXvvIVfvS9P0MAbt17Kp9XezP92tvbmZmZkT8XqXp7+/ZtlpeXKSoq4vr165SUlDz3EEAspKenx9VPSq1Wo1AojmXbEg3SBrWvr4+7d+/y8OFDVlZWSEpKoqGhgevXr1NTU0NWVlbYZ6nRaAgGg2fq41hfX68Aas7sAEfEiVdbQRCUgiA8FgThH579/b8JgjAsCEKfIAh/LQjCkZTWgUDgwvnz50/6Mg6F3W4/sx3ZUfAiSq8KhYK0tDSqq6u5ceMGZWVluN1uORJFoVAcWY9zFjiNGB2tVktZWRnXr1/HYDDQ3t5OV1dX7HiUfV5WXq+XlZUVuU0T8omElF68WhM6i5F//amPUlpa+jaxSg3/zgRBICMjg6tXrxIMBrl79+5z5QLu7OwwMDBAXV2d3M578ODBsf29TCYT9fX1B38We6BSqairq6Onp+dArZ4Ud9Pb2ytXb6R8vPv376PRaHjppZdISkqKafh5GLE6qGJ1XGJ1kJ3KQf5V0rkpkX6DwUBNTQ319fUsLCxw+/Zt0tPTDyQgIyMjpKSkHLqBCwaDdHR0UFhYeKCf1n6Mj48zMTHB5cuXD9X3mEwmCgsLZWG7BI/HQ1tbG5ubm7S0tJzJMM/Ozg69vb10dnaSkZFBS0sLVquVsrIyRkZG0JiVLP7KF1B6fdz487+j9EIFycnJKBUK8q1WHj9+HJG3tzeH7yMf+QiCINDU1MTm5iaLi4v87Gc/4+WXX8ZmTSEzRc25S+/g1q1bUTP9hoaG6OnpOfPg41jQaDQolcrnDmt/HpykauXxeJibm6Onp4c7d+7Q3t7O5uYm6enpNDc3c+3aNaqqqrDZbIe27w+LtHpeXLt2LUmn0zWe2QGOiOcpY3wOGNzz9/8GnAOqAR3w8cOeQBAErV6vN5zVDgE4sb7pNBAMBvF6vS9U3yUIAiaTSY7YUavVmM1mnj59yu3bt2VTwRclojztGB2FQkFOTg5Xr16V21Wtra0sLi6Gv6d9sTaTk5MUFBTIlbvgToiAwg0GG+ll2Xz7//r27gLr213QFcnRF0mlUklZWRmNjY3y7v+4ZEgURZ48eUJlZSVarRZBECgqKqKyspK2trZjtwsMBgMNDQ1yK+Uw6PV6qqur6ezsPHD3aDKZSE1NZWJigpWVFe7du0cwGOTq1avyZ1lSUhLT3TohIQFBEKIuJAkJCezs7EQ9D2MRq4PO2VjmoFKMTTRCIopiRPabBL1eT1lZGSqVCpfLRWdnZ9Qqqd1uZ3V19dAwZlEU6e7uxmazHVnvKIoivb29OBwOmpubj6w5y8nJIRQKyVFSs7OzPHr0iMLCQmpqak69SuX1eunr66OtrY3U1FSuXr1KRkaGTFTS0tLweDz4FDt404pZf8dN6v7rP+Ea3G3nbQcC3Kyvp7y8PCJvT9q8zM/Ph2nXpIy+vT8vtGrRmLKZW1iWv1cpVmZra4s333yTjY2NMw8+Pgi/DPEyB20IJU2yFOfz1ltv8fjxY7a3t8nOzqalpYWWlhbKy8tJT08/9qT6WQvo6+rqlCkpKe84swMcESciVoIgZAP/E/CfpZ+JovhT8RmAdiDybhWJ6tra2jPbJni9Xrn8GQ+cVujzSeHxeFCr1RQXF9PU1ERLSwsWi4Xp6Wlu377NkydPWFpaOtWogf2Ym5s7kxgdQRBITU2lsbGRCxcusLa2xp07dxgfH9919d4TayP5z+xdQEM+Eb/CiT8hCcHpJyG0u9iI27vTagrLwVVOnU4XFu48NDR05BL31NQUer0+omqRnJzMlStXmJqaYmBg4FjtxsTERBoaGujt7T2Sw3FqairZ2dmHuq1L5HV8fJzGxkZKS0vDFmZp03KSqlViYmLUSmosYnVQDmAsYiUJlqNVI1ZWVg4U6A8ODlJZWUljYyPZ2dk8fPgwbLrM7/fT29sr54PGgkSQjEbjkfIFYfecbW9vl7Mfj3MPk6qNQ0NDPHz4kPX1dVpaWo5VJTsKfD4fAwMDPHz4kKSkJK5du0ZmZmbUz7q4uJjxyXFUBgXbH/z3hFQqUr78RwC4/X6+ePMmX/nKV2IeK1ZG396fF1q1ICgIaNLY2trC5XLJwce5ubmo1Wp0Ot2ptPFPingTq/0VI1EU2draYnJyks7OTm7fvk1fXx8+n4/8/HyuX7/O5cuXKSsrIyUl5bmJ6FkTq6qqKgKBQNwF7CdlHH8O/D4QcYY+awH+L8Ctw55Eq9XWX79+/cyE6/EmNuvr63HVd0np6hJUKhU2m00WFObk5LC+vs79+/fliJ3TjD0QRZHFxcVTidg4CImJiVRXV3PlyhVEUeT+/fusqtWIS0vwTFeSk5MTdlMI7AQIKjxsq7X8w+/91dv+REckVhKkcGe1Ws29e/ciAqf3w+12Mz09TWVlZdTfazQaGhsbUSqVPHz48Fjfh16vp7GxkadPnx4pTb6goAClUsnExETU38/NzdHW1kZRUREKhSKmeLu0tJSRkZGovzuIWMUSsB9ErGIRDJ/PF7Wis7KyEpNQHOS0vrm5idfrlf+t1AZ2uVy0trayvb1Nb28vxcXFh1Zjh4eH5dHyo8Dj8fDgwQMyMzMpKys7dotK8q0LBoMEAgFqampO7IEXDX6/n6GhIdl49tq1a4cGV1utVjY3N1EZFQTV2Tz6xHvI/YeHKJ90sO33E/J6CYVCpKWlyTYei4uL8uefnZ3N7Oys/HxSRt/en6cbRULBAB7MeL1e1tbW5ODjzc1NMjMz4x4vk5iYiM/nO9PN7GFQKBQMDQ3R1tYmWx/A7nV848YNGhsbKS4uxmKxnHpRQq/X43a7z6xjotVqMRgMekEQzq4NdgQc+1MTBOF9wIooil0xHvKXwF1RFO8d9lxpaWnvPEvhuhS6Gi/8MgjnYy0qUlByZWUlN27ckEZV6ezs5N69e4yMjMRMcz8qnE4ner3+VG/qB0Gqzl2/fh09EBJF2h89YnJyMkLjFfQGCCl9OAjiWt6U2zOi85kIXH90rxop3Lm5uZnl5WUePXoUdVJPEqlXV1cfuPOTFuHS0lIePnx4LE2ETqejqamJgYGBI2nAqqurWVpaCntsIBCgu7ubpaUlWlpaKCsrQ61WR/Wtgrcz2aJ5U2m1WpRKZdR2aSwBeyxiFQwGo97oA4FAzKrT6upqVD2Rx+ORx8D3QxRF+vv7qaysDCMLKpWKqqoqKioqaG1txe12R20j7sXExAQul4vq6uojESSHw8GjR4+oqKg4UaXX6/XS2dnJysoKN27cwGg0nhqRCAQCjI6Ocv/+fbRaLdevXycvL+9Ii68gCBQUFOBVePBvBXn62X+F25KI6Wtfwe33s2a3YzKZyMvL49VXXwV2p/3e//7d+LebN2/ygx/8AFEUefToEWazGZvNxjvf+U5ef/11fv7zn3P79h0EQUF93UXe8573YLFYaG9vlzP93v/+92Oz2Q4MCX8ROKvpvGgIBoOsr68zMjLCw4cPuXv3rixRke79dXV1FBQUnNr0+kEQBAGdTnemOrO6urq4C9hPQkevADcFQZgCXgN+RRCE/wogCMK/B9KA/+0oTxQIBGpras7u/TscjrgRK2nU/Cz1Y4cd/zj5iAaDgeLiYlpaWmhoaCAhIYGhoSHu3LlDX18fa2trxy6hz83NHbrwnAUUCgWJ9++jfMc7SHqWQ9jW1sbc3Jz8HkJeCKqDeAmysbD6NrFy7RIikePfYKS2TVlZGU+ePKGvry8sbHh2dlZ2GD4K0tLSaGpqYnh4mJGRkSOT3ISEBJqamhgaGjq07aBQKLh06RL9/f1sb2+zubnJ/fv3SU1N5dKlSzIprqysZHh4OGZ48kFaq1hVq5NUrKIR0lgaKum1RqtkTU9Px3TiXl5eRqfTxdRmarVa1Go1Wq025gQe7J7/y8vLYbmPB2FlZYXHjx9TX19/InH5wsICDx48IDs7W86lrKqqYnR09LkmwaShhXv37qFQKLh27VqYXvGoyM7OxoMLvyOILsnK3Vfei7mjn4TBAZTPtJgZGRm88cYblJSU8MYbb/D5z38egPe+970UFhZSXFzMJz7xCb7+9a/T09NDX18fn/zkJ/n0pz/NH/3pdxAUCkpyd7sU3/72t/n4xz9OcXExRUVFvOc975G/u8MMas8Skp/UWSAQCMjWB62trdy7d4+5uTn0er1sOl1ZWYlCoYibDZHZbI4pHTgN/DII2I9dLRJF8QvAFwAEQbgB/J4oiv9GEISPA+8C3nGUEERBELQFBQVJwWAQURTP5At2u91xIzbxzIWCt6t1J/lco0XszM/P8/TpU0wmESCG6QAAIABJREFUExkZGYcKFyV/mKO2P04VY2O7f377t1ldXZWjPqSU+qysbAjoCem1hAJO7MtrMgEUtxyQDKHQySt1ycnJtLS0MDMzw/379ykuLiY9PZ3x8XFaWlqO9Vw6nY7m5mYGBwdpa2vj4sWLRxIxa7VampqaaGtrIxQKHRjCnJCQQG1tLQ8ePECtVlNXVxdByLVaLcXFxQwMDBBtM5SWlsbQ0FBU9/PMzEwePXpEcXFx2M/VajXBYDCixadQKKKSyFgVq1j6qljVKknQfO3atai/Gx4ejplVGAqF6O7uljMfJaPX+vr6sJbgysoKk5OTR46ZmZqaYm5u7tDYoWjw+Xz09vYiCAJXrlwJOz/UajWlpaVHiuPZj2AwyMzMDFNTU2RnZ3P16tXnEr4rFAoSU3UE50SSAnoGPvEBWl79Gf9yfZk1jYamxkaGhobo7OyM+LeCIPAnf/InfO5zn2NhYQGj0YjNZuP8+fO89NJLfPGLX+TRsIufdjvItOy+/7q6OtlkeC8k4Xtc7k0cnJt3XPh8Pux2u2zGCbv3HykeJtq5ZLFYdh3x4wRpkvikZrCHob6+XpmSkvIrwP95Jgc4Ak6zDfcdYBp4+Gwx/1tRFL96wOOrysvL1YODg2xvb6NQKDCZTGF/juO8vB9SJlG8jEHjbfNwWv5ZUsSO1WqVXeSXlpYYGxtDo9GQkZFBRkZGxGLqcDgwGo3xidH52c8AcLa0oPL55GpGZWUlZWVlTI/uajI8WgWuVQfBYJCsrCxCPh+4t3eJ1XNKAARBIC8vj8zMTIaGhujv76egoOBEbVGFQkFlZSWLi4s8ePDgyHluGo0mjFzFqh5KWji1Wi27VEeDpGeJdm4LgkBxcTFjY2MRzu4ajQa1Wh21smQymdja2opaWd6/4YqlsXK5XFE3Maurq1Hf8/LyMmlpaVHPzZmZGdLS0mJuyIaHh7FarfLnn5eXh9FopK2tjZqaGlmcOzAwQHNz86Hft5RB6PF4aG5uPvb1sri4yNDQEGVlZTHJc2ZmJtPT00fWnIZCIWZnZ5mYmCAzM5OWlpZTa+en56Ww+GQbkyeRbZ2Sic/8Kuf/4L+j6+3hwvnz/MVf/iV+v18+njR4MvssWio7O5srV65EfT0LG34MCQpM+oM/w4yMDB48eBA3YqVUKtFoNFE3IYdhZ2dHJlEbGxsolUqSk5NJTU2ltLT0SN+TWq1GFMUDW+hnCbPZfKhJ8fPgmYA9rq3A5/pURVG8Ddx+9v/Hei6VSnXx5Zdf1tbX1wO7F5DT6WRra4vFxUWGh4fx+XzodLowsnVUs8t4tgFhV7h+kKngWWNtbe3QCJnjQhAEkpKSSEpK4ty5c7jdbpaWluSInfT0dDIyMjCbzSwtLZ3ZjuRQ3LoFRUVMPIsv2QuVSkWayoaLdZxpXnRqLZ/+9KcpLy8nsLaG4lmx9XkqVnuhVqvJzc2Vx/J3dnYoLy8/0abBZrNhMpno6uoiOzubgoKCQzcOarU6jFxFaM2CQbq7u9Hr9Vy/fp2BgQFGRkaiLjqCIFBTU0NnZydXr16NuA5tNhsjIyN4vd6InXJmZibz8/MRtgTSlNL+a1WlUhEIBMIWilitQJfLFfVck2Js9mNqaoqqqqqInwcCASYnJ2NWFdfW1rDb7Vy+fDns58nJyTQ2NtLR0UFWVhazs7M0NjYeWnkKBoN0dXVhMBi4dOnSsTaBPp+Pvr4+gsEgly9fPvBYgiBQXV3NkydPaGlpOTBoem5ujvHxcaxWa0T16zSQmKYDttHYFfgzg2g/8lk2fnAH493b1L77PXi9XgYHB8nMzAwLPq6pqTnUw2vB7sOWfDRiodFocLvdcYs6S0tLY21t7UAdnSiKeDweOazY4XCg0WhISUkhMzOTysrKE29cpevuLPzMDsNZa6yebQ71giAkiKJ4etNYx0DcsgLT09Mbq6qq5KtApVLJuXgSJJ3S1tYWW1tbLC8vy5b4RqMxjHDtn1ja3NyMm38VvB1lEw8EAgECgcCxWwrHhV6vp7CwkMLCQjnWYHx8nK2tLXZ2dqipqXnxaeo7O/Dmm4Q++lHsdjvRzGc987t6k40MN3nmHL7wzQ8yPj7O03v3EHhmhnlKQyuSELqmpgaz2czCwgKtra3k5+eTn59/7IpqYmIiV65coa+vj66uriNNfKlUKnnhD4VCMuGWRvptNptMQCsqKnj06FHM3LbExEQyMzMZHR2NIF+CIFBYWMjExATl5eVhv7PZbDx69CiCWCUlJUWdzpN0VvuJVbRNVbRKWKwYm+3tbUKhUNQK19jYGHl5eVE/T5/Px9OnT2lqaor6nen1ei5evMjdu3cpKio6dMHe2dmho6OD3NzcmFqvWFheXmZgYIDS0tIje2IZjUaSkpKi+nZJWY+jo6OkpaWdqB15VKhNu/eCwJIfMsGcVsXwK9dp+p3/zktPn/KZz3xGthrJy8sjOTn5SNeILxBidStAefbRKkCS7UFhYeFzvZ+TIi0tjfHx8TBiJYoiLpdLrkhtbW2h1+tJTk4mLy/vuQKK9yMlJYX19fW4EKvDskJPA2VlZYyPjxcCp9NzPSbiRqwUCkXVYaZ60gSBTqcLy1ILBoO4XC62trZYXV1lbGxM3iVLRGttbS3mSPtZw+fzxdU/Kx5tSLVaTVZWFllZWWxvb9PR0cH6+jrDw8MYDAYyMjKwWq2nvgOOwP374HazXl8fM0bHveAnkLiBMyFIoHcWb81FamtrWenp4WnC7oI7Mz1FamLuc1/4KysrJCQkyBWZrKwsrFYrIyMj3Lt3j8rKymNPjiqVSmpqapibm6O1tZWLFy8eSuJVKhUNDQ0yucrJyaG9vZ3c3Nywm7sgCFy6dIkHDx6QmJgY9XmLioq4d++enAm4F9nZ2dy5c4fi4uIwgqLRaNBoNBF6KJPJFFXIKhGrvY+NprESRTFqJStWKzxWGPjOzg5LS0tRdVfSNGdZWVnM1o3P56O7u5vGxkbGxsYYHx+PWbF2Op10dXVRUVFxLG8pv98veww1Nzcf+9wsLS3lwYMH2Gw2lEoloiiytLTEyMgIDoeDL33pS/L1MjExwVe/+lU2Nzf5q7/6K/mz/NrXvsZ73/teAL7+9a/zve99D6VSyX/8j/+Rd73rXQDcunWLz33ucwSDQT7+8Y/LAnQAtVEJAggbuzuXrYCXYO0V1mpaSfrHf+ALrQ/IyMg4dotqeTOAKELmESpWsEusHj9+HDdiZTab2drakmOh1tfX5WGjlJQUiouLz3RKz2KxMDc3dybPfRRIAvazIlY1NTX6n/70p6X8/41Y+f3+7JNOjCmVSsxmc0RFyuv1ytWtzc1NHj9+DOxOvEmEy2w2y47QZ4V4V8t+GWwecnNzKSwsRBRFnE4nS0tLtLW1oVAosFqtZGRkHHli8Vi4dQs0GsZycqiJEaPjnvfhMy+zjchffvQPeHrtF/zgP/wH/BMTjNV8BItGSVZKAm1tbRiNRoqKik70fYqiyNDQUIQQWqVSUVFRgcvloq+vj6mpKSorK499k8nOzsZkMtHd3U1hYeGhsUFKpZKGhgba29sZHx+noqIiasVDo9Fw6dIlurq6uHz5cgQZVigUVFdX09vbK0eG7P1dXl4ek5OTEdUpyUNob6VLqVSiUCjCdDUQfTIwGoE6yL9q/8YqFAqxvLzMuXPnIh4/NDS0G2kUZTM0MzODWq2OqWEKBAK0tbVx7tw5UlNTSU5OprOzk1AoRElJSdhjV1dX6e/vPxIZ3v9++vv7KS4uPtQzKha0Wi3Z2dlMTk5iNBoZGRnBZDLR0NCATqfj5s2bALLm8AMf+AD/5b/8F/7tv/23/N7v/V7Ycw0MDPDaa6/R39/PwsIC73znO2U/pM9+9rO88cYbZGdnU19fz82bN6moqABAUAqojQoSfbsVxq6hLoziNEGdDqVLIBAInKjCvWDfrUJnWo5GrHQ6HYFAIOK8O0uEQiE2Nzfl1p7b7WZkZASr1UpFRQWJiYkvTBOs0+mOnRhxmpAE7McNnz8qqqqqEs1mczXwP87kAIcgLsRKEARVfn6+5rQrOlqtlrS0NCwWCwsLC1y9epVQKCRXt+x2O1NTU7Ij+X6x/GkJ+eIZowO7xOq09VXHwdLSkjw5JkXsmEwmSktL2dnZYXl5mf7+fjweD2lpadhsttPL6rp1i+CVK4h6fdR2jH8rSMAZwpO7xuainbWFFa5cuYKztZV1QwbzPh3vrjSQl2cgNzeHtbU12VW9sLAQq9V65Ne5sLBAcnJyzCqHwWCgqamJpaUlHj16RFZWlmzGeVSYTCZaWlro6enBbrcf6pEliiLBYJCEhIQDR86NRiPnzp2jq6uLxsbGiNeUnJyMwWBgdnY2gtDl5eVx9+5dCgsLw66pWKJh6Sa7ty0Ri1jtfx3RJgJDoRButzuiPbi4uIjVao14DsmlO9q0o8vlOlB3FQqF6OjoID8/X14kFAoFdXV1dHZ2hrU5Z2ZmmJ6epqmp6cgkOhAIyNdKU1PTc085G41GOjs7sdlsXLx4Mapu6Re/+AVFRUUHtih/8pOf8KEPfQitVktBQQHFxcW0t7cDuy7rUiXoQx/6ED/5yU+oqKhga2uL2dlZPGhRunfJjM7iJLjtw2AXWd52U1RUhNvtPnYrcsHuJ1F7uHB9L9LT01lZWTlyO/W4CAQCbGxsyBUpv99PUlISKSkpcsVZr9fHxZJGEAQ0Gk1UPeSLgMlkiumLdxooLS3FZDJdOrMDHIJ4Vazyi4qKziysbu/Ndu+04V74fD65uiWJJIPBoNz+kKpber3+2Au+w+E4c7fxWBBFEZ/Pd2Yl1sNwWD5iQkICeXl55OXlEQgEWF1dZXp6mp6eHpKSksjIyCAtLe1kJHd2Fvr7sb/vfTFvVu5n+ipX8gazHbs77Mbz5/G8+SZD1f8SdVCgtnD3tQuCQFpaGmlpabhcLiYmJhgaGpKtKA56jaIoMjo6SlNT06EvW3rP4+Pj3L1799gtIpVKxcWLF5mamqK1tZVLly7FzMbr7u4mMzOT/Px8uru7GRwc5Ny5c1HP8YyMDBwOBwMDA1HF3uXl5dy/fx+r1Rp2c1YqlWRnZzMzMxPWapGmDvdbkUhGofuJ1f4WYbRWoMvliniv0vTb/vc0NTUV1XJgYGCAioqKiMeHQiEeP37MhQsXon7X0ueZnp4eIUKW/MEePXqERqPB4XDIocBHPbfX1tbo6+ujoKCA8+fPP9fGY319naGhIRISEmTCG0sM/tprr/Ebv/Eb8t+/9a1v8YMf/IC6ujr+9E//FIvFwvz8fNi5LVkYAGGfRUZGBm+99RZ3795Fq9WSk5ODqTSBjaceEGHdMcZF7XlUO/+AIxCIaRFwGBY3/Ngs6mN9RmlpaczOzp4asfL7/TKJstvthEIh2fqgoKAg4n0lJyezsLAQF2IFb29oTjvq6CiIFWd1WigpKSEQCMRn7JP4EavS8+fPn9nKH8vXZi80Gg2pqalhN3PJVFMiXHNzc2xvb6NUKsPIlslkOrB8fJTjnxW2trbi6p91nBghKWLHZrMhiiIbGxssLS0xPDyMTqeTdVlHJom3dlOUpsrLuRBjItE97wMFbKU4me0YJtFgoNDpxKHQMBRIoaZAh04TWTEyGAycP38en8/H9PQ09+7dIz09ncLCwqhVhPn5eVJTU4/82pVKJaWlpeTk5NDf38/k5CRVVVWHTkJJkJytLRYLHR0dlJaWhrWuRFHk6dOnYXl1Fy9epKenJyaxgN2dX2dnJ7OzsxHkQa1Wc+7cOfr6+rh0KXxzmJ+fz/3798nPzw8jQ1I7cG87LikpKcJX56itQJfLFSHAXV1djVgsnE7nro/Svs9zdXVVHlnfj8HBQWw2W0wriKdPn5KYmBhTS6VUKrl06RJvvvkmaWlpNDQ0HGnhDwQCDA4O4nK5aGhoeK7JtY2NDYaGhlAqlVRXV2MymQgGg1ErirC74fz7v/97vv71rwPwyiuvyNqrL33pS/zu7/4uf/3Xfx0zuy8UCsn2HbOzs4yNjQGETUmuZ25j7/SQ6ExAodBRpK5F8Pux7+xEbdMeBn9QZMXhpzTzePdci8VCb2/vsY8nYWdnR/aQstvtKBSKY1kfJCUl0d/ff+LjPy8knVM8iJXkVXdWHpZmsxlBEOKWZxcXYpWYmFhZXV19Zqu/0+k8UUagIAgYDAYMBkPYohQIBGSyNT8/z+DgIH6/X7aCkMhWYmKiPAUXL/+seOcTHhSjcxAEQSA5OZnk5GRZf7S0tERXVxehUEjWZRmNxtif7a1bhLKzEc+di3lTc8/7SUhXs6NVMNs5QkNdHd7Hj5koe4lACBpLDifkJSUlFBUVsbi4SGdnJzqdjsLCQnlxFkWRiYkJJCuR40Cn01FXV8fa2hqdnZ1YrVaKi4uPXOVISkri8uXLPH78GLvdTkVFBQqFgqmpKYLBYFgbTrJPePr0KX19fVRVVUV8toIgyOahBoMh4rqy2WzMzs5GfO9qtZqMjAzm5ubCWoVWq5WxsbGwDDyDwRDRlkxISIggVtEmTLe3tyPa3qurqxGi5GiidVEUGRwcjCCF0nM4HA6am5sjfgcwMjJCKBQ6kAj4fD66urooKipiYWEBj8dzKElaX1/n6dOn5OfnR/0+jgqHwyGT1fLy8jByGKuiCPD6669z8eJFua25VwPziU98gve9731A9Ow+o9HIysqKHAReVlaGwWCgvLw8rFqjs+1em+Y1A2pDLsqgAH4/6273ibylVjb9hESwJR9vMEahUKDX62M69++H2+2WK1Kbm5uo1WpSUlLIyMigvLz82FV2lUqFIAgvVOe1F2az+UzbcYdBsl04K8sLi8WiEATBLIri2dm8x0BciJXFYqkrKys7M+bhcrlOlLMVCyqVSl70JUgeIxLhWlxcxOVyEQwGARgfH5erXC+yh72xsREhmH2RWFtbO5XjSxE7xcXF+Hw+lpeXGR4elisUGRkZpKSkvF0N8fvhn/4Jx7veRdYBRpieBR/mCh07Sg3/81/8Fr8+nkRoZoanmnxyjRoyjih+VSgU8hSk3W5nfHycgYEBOdjYaDQ+lx4mNTWVq1evMjU1xb179ygrK4s55bgfGo2GhoYGxsbGePDgAUVFRczNzXH58uWoxKm6upr+/n56e3ujtpxUKhWXLl2ivb096jRadXU1bW1tJCcnhy0uhYWFPHz4kJycHPk51Wo1er0+zI4k2vi1pP/Yi1AoFLEA7fcikqJb9grag8Egq6ursoBawtzcHBaLJWJRlTyi9gvzJUxNTeFwOKivr4/5fbhcLjo7Ozl37pzc6pWGAaJp4ILBIIODg/LzHrVSuR9Op5OhoSECgQBlZWUxp4NjVRR/9KMfhbUB99pu/N3f/Z3cEr558yYf/vCH+cxnPkN3d7ecylBRUcGXv/xlEhMT0el0vPbaa/zN3/xN2LEDxg1EIUTSeiIKs4h3y43S68V5CFGNhQX7bnTRUYXreyHFy+z/vKNZH+h0OlJSUsjNzeX8+fOnMvUt+UmdhpnzcWEwGM60HXcYjEajnCd7FqisrBT6+/tLgEgr/z0QBOGvASkDuerZz/4P4P1ACFgBflMUxSOHTMaFWImiWH6Y1cLzYHt7+8yN3wRBQP9MIL1XTzU2NibvQJaXlxkZGcHn86HVauXKlmR0ehb+Tk6nM25tSL/fjyAIp7770mg05OTkkJOTI4eKLiws0NfXJ0fsWEdGUG1tMX/+POdiTJr47EGCHhF9lgavSkN+UQrFnfPMF9ezsQPvvHiyxUwi3W63m8nJSSYnJykoKHjunahCoaCwsJCsrCwGBwdlY8ujTJMJgkBJSQmJiYl0dnZy4cKFmOebIAhUVlYyODjIkydPuHDhQgRhSExMpKqqis7OzgiHcJ1OR25uLsPDw2GTeFqtlpSUFBYXF8MqwFI7cO/7kHIDpWtJpVLJmxQJ+1uBUjtq72tdW1uLWKQWFhaw2WxhC2EwGGRsbIwrV66EPVYURR4/fsy5c+eitnEXFhZkfVEsUrW+vk5vby+1tbVypSg5OZmsrCz6+voiRPJ2u53e3l5yc3Mjgp+PCpfLxfDwMDvP2mmHVa3VajXp6elhGh+3280bb7zBd7/7Xflxv//7v8+TJ08QBIH8/Hy++93vEgwGSUpKorm5mYqKCrRaLd/5zndkzdW3vvUt3vWudxEMBvnYxz4Wdk6IosjTqddQJ75E0poBoVbJ1uQSplCIy7/yK6hffvnY731hw4dOI5CUePz7qRTFlJeXx9bWlkykJO3eWVsfSOd9PIiVIAgolcq4VcwMBgNOp/PMJgNramoMP/7xj0s5hFgB3we+Bfxgz8/+WBTFLwEIgvDbwJeBTx/12HEhVqFQKPWs2lVSyG68PKS2t7fJycmJqG7ttYIYGxvD5XIhimJUo9OTXsCBQACFQvHP2j9LqVSSnp5Oenp6WMSO/4c/JE8QWH+mg4pWlpeE6/osNU/+cQClfZsPujLpr6zB6FMc2VwwFvR6Pbm5uWxubqLT6WhtbSU5OZnCwsLnIrtarZYLFy6wsbFBT08PFouFsrKyI8WlTE1NUVtby8zMDNvb22EtuL0QBIHy8nJGRkbo7u6mtrY24jxKS0vD6XTS29sbQb4KCgpobW2NmIgtLi6mo6MjrNpmtVoZHR0NE81LAvaDhj72i9ejZYGurKxEVKunp6cj2n0TExNkZ2dHWDVMT0+TkJAQ1RxV8sw7KHpmfn6esbGxqBN8BQUFdHd3y3q1YDDI8PAwdrs9aj7jUeB2uxkeHmZ7e5vS0lLS0tKOfP+QXo9ErPR6vZw3J+GHP/whgKyBnJ2dZWhoCKvVyh//8R/zne98J+J53/ve98peV/sxu9LO6uYwhbZfJWlei2hW43IMo/D7KaqqQjimWSrsVqxsluPFl+21PlhZWeGtt97CbDaTkpLCuXPnXlhAsdlsZnl5+cyPEwtSG/4k0pnnhdFoPNNom4qKioS0tLSLwN8c9DhRFO8KgpC/72dbe/6aCBxr2O6FEytBEPSlpaWqszppo41Zv0hEE64LgkBCQgIJCQlhOpS9VhBra2tMTEyws7ODRqMJI1tGo/FI/futra242zy8SGPSvRE7GI0EDQYSMzPp6enB5/ORnp6OzWaThIy4530IKtCkqWj9wZv4F+38we/+ERMOJderElEpn/+cnJycpKioiIyMDAoKClhaWqKnpweVSkVRUREpKSknvmFbLJawcOeioqKwNlu012I2m8nOziYrK4uhoSEePXrExYsXo7anBUGgrKyM0dFRurq6uHTpUgS5Kigo4MmTJ0xOTobpcwRB4Pz58/T09ITFpkg6xJWVFXlnKk2k7T1fJQf2vVAqlWF5ZvvtFiRDRQnS4r/Xbd/hcKBWq8NIjs/nY25uLsIM1Ol0Mj09HdVaYXNzk/7+fpqamqISWmkKVIq8ifYY6TNqbW1Fo9EwNDREVlYWV65cOfY54fF4ZGPPsrIy0tPTj/0cer0ejUYTNVJo73FmZ2fl4OOcnJwTTyj6/C76Jv4fLMYCkvLTEUd38PtCEAiA38+Cw8Fx5/MCz4TrzWUHk9JgMChbH6ytrYVZH1gsliNF5pwFjEbjgbYnL+r48SBW0bSVp4nS0lISEhJOnBkoCMIfAR8BHMBLx/m38ahYFZ+kj35UxHMiD2IbFkbDXiuIvSO3khWEw+FgamoKp9NJKBQKs4IwmUwRVhC/DMak8XIyZnubgFZLZWUlOp0uImInOTkZ9VQqCRlqtkLbzHePce0dNQwXXEHYgLqi57+pBgIB1tfX5Xw6QRDkqUeHwyHrsPLz88nKyjpRK3h/uPPMzAxVVVURC6PL5WJmZoarV6/K/668vJzl5WU5yDkWCS4pKWF8fJyOjg7q6urCXqdEDh4+fIjJZAqbyDOZTKSkpESQruLiYnp6esJK/lI7UDpfdTodOzs7YVNCWq02rPq4vxW4/1qXJAB7yVe0uJzh4WGKi4vDnisYDMrWCtEmDx8/fkxDQ0PU9mAoFKKnpweFQkFDQ8OBFWNJf9fV1UVLS8uxY6+8Xi+jo6Osr69TUlLy3DYMBQUFETYUxwk+Pg76Jv4Of8DNhdIPs7O4+50KKwoS1WoUosg/3r7NJ4/5nCsOP8FQpOO63++XJ/bW19cJhUJYLBZSU1PJy8sL+x6l6b54EKtfhnac3W5/4ceF3Xa03+8/s+cvKirC7/efOLBXFMU/AP5AEIQvAL8F/Puj/tt4EKuSmpqaMzuD4xmseVoXx2FWEJubm8zMzOB2u1GpVDLRWl5ejptwPRQK4ff742I2BxByuQgmJKB/VpnYG7ETCoVYnV1nacmLM2eZN/6uDd/2DpXlefQ6E6nISTiWsWAsLCwskJmZGXWhM5vNXLx4kZ2dHSYnJ7l7967sJ3WSz0ytVlNdXc3W1hZ9fX3o9Xp5+koURZ48eUJNTU0ESbBarfLCnpmZSWFhYdTXKxmVdnR0UF9fH/Y8SqWSuro6Hj58SGNjY9j1VlZWxr1797DZbHKVyGAwoNVqwyZWpVif8vJy+fiSt41EliRBu/T8+1uBLpcrzINo/2RiIBCIyIvc3t5mY2MjwpdrcHCQrKysiI2Jx+Ohs7Mzppmm3++no6OD9PR0ioqKDiQ5DoeDnp4ebDYbKpUKu90ek1jl5+djNBpRKpWoVCoePHhAZ2cnv/3bv836+jrFxcX8+Mc/RhAERFHkc5/7HD/96U/R6/V8//vf5+LFiwC8+uqr/OEf/iEAX/ziF/noRz8adpzU1FT6+vrw+/04HI5jBx8fFaubI8wsP6Qk51cxJ2YRynhWqVhWkPjsMzOfwPtPEq6nJu5ef+vr62xsbMhTxpJG6qDNbnJyMnNzc6c68HQcmEwmtra24jLNbTQamZmZeeHHlSCFrZ+WOfdeaLVaVCpVoiAIghjNH+To+BvgH/llJlZ6vb6ouLj4zJiP2+0+MzEX/dtaAAAgAElEQVTcYdhvfHiaiGUF4ff7cTqdOBwONjc3GRgYIBgMotfrI6wgzlIzEG+3ef/GBkKMSqVCoUCc0ILoo+ZfnONPvvlnIAjkF78Tu18kS7+Jy6V57krn7OwstbW1Bz4mISGB8vJySktLmZub49GjR5hMJoqKik4U2m0ymWhubmZhYYEHDx7Ibtn7A833Qq/Xc+XKFfr7++no6KC2tjbqhqCgoACFQkFbWxsNDQ1hN7+EhAQuXLhAZ2cnly9fln+nVCqprKykt7eXxsZG+fElJSUMDg7Ki4dUudnc3JRfpyTk3Uus9k4GHlaxWl1dDSNM8/PzZGVlhZ33AwMDYWQOdkONXS5XRASOz+ejvb2d6urqqOe22+2mo6ODkpKSmHE30useHR1leXmZCxcuYDKZCAQCMgGNRawl3c/4+DgPHjzgtdde49d+7df4whe+wDe+8Q2+8Y1v8M1vfpPXX3+d0dFRRkdHaWtr45VXXqGtrQ273c5XvvIVOjs75QzImzdvhp0XbrcbtVrNm2++SXp6+rGCj4+KYMhPz+iP0CekUJa7q71S6ZRsG3ZIWFbh2dwEIPkYRp0ej4ellXVa+wKoBAVjg49JTT2Z9UFSUhJ9fX3He1OnCOm8jwex0uv1cY22kY5/kntfLAQCAdxuNx6Ph6SkJM3c3JyJ3XbekSEIQokoiqPP/noTGDro8fvxwolVUlJSUTRh6GkhnhWreEzkqdVqkpOTsVgsTE9Pc+3aNdkKQnJ7np+fZ3t7G4VCIYvlJcJ1WqHIexfIeMDvcKCJcXGKQZH1zm2MxVo8SV76BwcovlSI1/QOss0qsiyBsIidjIyMYy8ubrdbnhQ9CpRKJXl5eeTm5rK6usrAwAChUIiioqJj62UEQZDDnYeGhpicnAwjNdEg5f3Nz8/T2tpKbW1tVPKQl5cXRq72EjCLxUJ+fj6PHz+mrq5Ofs2So7VUwQPk596r58nMzGRhYUE+bywWC0tLS2RnZ8stwY2NDVQqFaIo4na72dra1ZRKPlfS+RstxmZ6ejosp9FutxMMBsMmsLxeLwMDAxFWFIFAgPb2dsrKyqIueBsbG/IE5UHn/dbWFj09PaSnp9PS0iJX3FQqFWVlZQwODkZ1g4fdCWOPx0NBQQHXrl3jU5/6FLdv3wbgox/9KDdu3OCb3/wmP/nJT/jIRz6CIAg0NTWxubnJ4uIit2/f5uWXX5Zbvi+//DK3bt3i13/911lYWGB2dhalUonNZmNxcfHQTcFJMTr7c1yeZZqrfguV8u37zWaqi8yVZKbnp8kDzDHWBalaL7X1HA4HSo2OnvVM7B41/6LRTG3hwTmZB0HyHTyryslhiGfVSDrno8VFvQhIXlZHJVbSIJjH45HJk/RfSUqgVCrR6/WSybTQ19dn4wBiJQjCj4AbQKogCHPsVqbeKwhCGbt2C9McYyIQ4kCsVCpV3kG7u+eFx+N57jytk8LlcsVlbBbCCeVeK4i9JDYQCOB0OmXfreHhYTn+Zi/ZMhgMx77IHA7HgdliZ43Q1hbqGP5VjkEPAWeI1JsG3nL28sHvfA5Lm5N1n5ZfrzGTn2ElP383YmdtbY3Z2Vl6e3sxm81kZGSQnp5+6A13bm7uRNEYgiDIU45Op5OJiQkGBwfJy8sjJyfnWDd6iYCcO3eOyclJZmdnqaioOPB6kNpfXV1d5Ofnk5ubG0HqcnJyZHLV2NgYRq5yc3PZ2tpidHQ0LHS5srKSBw8ekJaWJj++tLSU0dFR2Tg1PT2doaEhysvL2d7eZnNzk7m5uYjJNOmmv7Ozw8rKCsvLy3g8Hra3t2ltbSUpKQm1Wh1GDDc2NtDpdLKWRhRFBgYGwtqCkrWCZBmw93idnZ3k5uZGnVJcXFxkZGQkog26F6IoMjY2xuLiIjU1NVFJq81mY3JyMqzaGwgEmJqawuv18vGPfxytVsunPvUpPvnJT7K8vCxfzzabjZWVFWC3Mre3jSXFy+z9uSiKWCwWHj16hM1mIysri0uXLsnnxuLiYpiP2GnB6V5mZOZnZKfVYU0O9xHbTHWROZXCzNQuqdA9I7BScLsUVrzX+qCwsBCV1sB/vWtn3e3nX11Jpir3+e/3ZrNZ1mK+aMRbwC614OOR2LG/YhYMBvF4PGGESfp/SY+l1Wpl4qTT6bBYLPK1vn/dKi4uDv3TP/2TjQMqTqIo/kaUH3/ved7XCydWgUAg6ywrVqIoxtVqYb9Q9kXhKG1IlUoV0SISRZGdnR3ZCmJ5eRmn0ym3Hvd6b2m12piVFIfDcarl3OPA6/Wi3NmJ2Qpca9tGY1ESLAjQvTxGmtOOw/dOsnU+Cq1vL6gqlYqMjAwyMjLCInZGRkZISEiQI3aiEZXFxcWYLt1HhdFopKamBp/PJxuDWq1WCgoKjrRZcDqdbG5uylN5y8vLtLW1kZWVRWFhYUyxvMFg4MqVK7Jj9vnz5yMIXVZWFgqFgkePHtHY2BhW6ayoqKCtrY2lpSWZiGi1WoqKihgYGJB9m5KTk+WoFsmcMBQK8eabb2IymUhPT0ej0dDS0oJKpWJ9fZ35+Xm5vedwOKioqCAhIUEmc+fPn2djY0PeJLS2tpKVlcX6+nrYtbi4uIjBYAg7RycnJ0lMTAyTDkj6tNTU1IhwaclRf3l5Oebkn/Q9PHnyhLS0tLAq1X4IgkBVVRV9fX00NjbKIc05OTm0tbWRm5vLysoKL7/88oHGmbHiZaTdfX9/PysrKzidTjIyMrh+/XrEdZyZmcn8/HzMeJ6TQBRFekb/BqVSTVXRr4e/PsCR4kJA4GreBeDHBNRq2tra5NZQcnIyZWVlYWkLTk+Q77+1ht0Z4DeuJlOWdTqbaLPZzObmZlyI1VmLuA9DYmIibrf7zImVKIr4/f4w0iSZr87OzsobKIkw6XQ6eXOr1+tRq4+XBQmQn5+vB86ukhMDL5xYhUKhpLNqGQUCgTMx3Twq4l0tO0kbUhAE+STeu8CEQiG5urW6usr4+LhsBbGXbO296cXrs7fb7aT4fBBFaOtZ8rM97cP2qybuugb49jt/n5arV6h6xwe4ZnPFvFD3R+xsb2+ztLREd3c3wWBQjtgxmUxsb2+j1WpPra2q0WgoLS2luLiYhYUFOjs70ev1FBYWHth2Gh4eDtMPWa1WUlNTmZiY4N69e5SXl8fUH0pBztPT07S2tnLx4sWIG61ksimRK6nKIwUOP3jwgMTERPnf5eTkMDc3F2bDIU0IiqKIWq3GZrMRDAblSUq73Y7L5SIpKelAjZV0vktGl8PDw1y7do1AIMDMzAwLCwsolUoSEhJITExkZGQkLDRYygLdaxAqiiL9/f1otVqKi4vD3nsoFOLp06cEg0GampqikiWJeM3NzVFTUxPTwmAvjEYjwWCQt956i7y8PFpaWsIIW3p6Oh/4wAdob2/HarXKTuiLi4uyUH9/vMzs7Kysvezr68NisXDu3Dlee+01iouLo57zmZmZdHZ2niqxmll+xJpjlAslHyZB8zahDQaD2O0bOJM8AHhVqYiCQOqDB1h+53di6kEd2wG+/9Y6W+4g//p6CkUZp1ddM5vNEXYfLxIajeZYE+WnidPSWYVCIbxeb0SLzu12y9exZH0iVZysViuBQICGhoYzWT+ys7O1RqPxhbdS4tEKVJ+ViPosc4eOgnhWy5xOZ0QY7fNAoVBgNpsjWhh7jU4nJyfZ2toiEAgQCoUYGRmRCZdOp3theYl2ux3rzk5UYrXW5kJQgbIG/v7NW6yOzCO88xIZnnnyk49O8KWw3aKiIjliZ2RkBJfLJVcCT1unoFAoZA8qu93O6OgoPp+PwsLCiHgbp9OJ1+uNOAeUSiUlJSVkZ2fT398vu7fHmvbKy8sjKSmJrq4uSkpKItqbVqsVQRBkcrU3gubixYt0dXXJo/mSNYNkLbC6usrw8DAej4f6+npSUlIIhULcuXNH1lRJQt5oxGrvVODejYTP55Md/6U/586dw2Qy0dvbSyAQICUlRX6tkrVCbW1t2M18bGwMn88XoTXy+/10dXVhsVgoLS2Nel67XC7ZvLWlpeXQRSIUCjE3N8fExATJyck4HA65lSpV8oxGI9vb2/z85z/ny1/+Mjdv3uTVV1/l85//PK+++irvf//7gd14mb/4i7/g+vXrvP766yiVStLS0njllVe4fPkyOp2Ora0tfv7zn8vhyvshfTZer/dUJnu9Pid9E39LiqmIzJR6VlZWWFtbk3VuqhQ9lrVdAv7qTAcfq6qi6PXXcd+/j/Dud0c8n90V4PtvruHxhfjISynkpZ3u9LE0mRcvSC7k8RKwr66uHvq4QCAQVdvk8XgIBAKyX6NEnBITE0lNTUWv18fsdgSDQaamps5sU26z2TAajae3WzgiXiixEgRBV1ZWdmbMI5oT84tCvKtlL8q/S6vVkpaWFqYlm56elnUQGxsbTE9Py9NGe323TCbTmYhD7XY7gscD+95/wBNio9eD5byeB8Eh+v7HA9QaDcUXb1K//BaCJro79GHYG7EjEQO/38+dO3cwGo1yy/C0fGkEQSAlJYWUlBS2t7eZnJxkeHiY3NxccnNzUavVjI6OHmi1sT/cOT09nZKSkqjfh9ls5sqVKzx+/Jj19XWqqqrCCGN6enpY5Uq65kwmE6WlpXR1ddHY2Ci3k1NSUnjrrbdITk6moaGBjY0NFhYW5KzHpKSk3arjM7NGyXtKGsWWsJe4ulwuuWKztrYmE0pRFJmdnaW5uRmNRoPFYuHOnTusr68zMjJCcXEx/f395ObmhrUFp6ensdvtEfl/Ho+Hjo4OCgsLw7zmJIiiyOTkJDMzM5w/f/7QVpIoirI7e3p6OpcvX0aj0dDZ2Sm/j+XlZT7wgQ8Au/eVD3/4w7z73e+mvr6eD37wg3zve98jNzeXH//4x2xubpKTk0NCQgKNjY2YTCZ++MMfypWnL33pS7Km7ctf/vKBr89qtbK8vBzRAj0uvF4vnYOv4Q94CGyV8uhRW4T1waR3GXv3Apuina/96K/QvvQSX8jKQv3Zz0J/P+zReq1u+fn+m2sEgiK/+VIqWSmnX9VRKpWIohg3Ebeks4oHsdLpdLjdbnZ2diL0TdLP94vCpdxE6f9Peq9TKpVyWspZIDMzE5VK9c++YmXLzMx8Hj+JAxHPVlw8pxGBuE20AHIwstVqDatw+P1+ubo1OzsrV7f2G50+jxVEKBQi6PcjuN0RFauN7m1Ev4i2TkmHY5Thf2in5MINclJ8ZE4vojiFnbn0udfW1iKKIltbWywtLfHw4UNUKhVWqxWbzXZq54aU2ef3+2UHdrPZjNPpPNLgxP5w59LS0qjeW2q1mvr6eiYmJmhtbeXSpUth7yE1NZXz58/L04LS7zIzM9na2mJgYICKigpmZmZYW1tDEARKS0tlkenIyIhcHcnKypKJlslkwuHYHeCJFb0D4a7rKysrMhmw2+0YDAa5pTI2NkZJSQm5ubmMjY3x5ptvotPp5NYj7Oqv5ubmIlp8DoeD7u5uzp8/H3XBc7vdPH78GLPZzNWrVw/cWImiyOLiIqOjo6SkpNDU1BQmFC8tLaWvr4/U1FQKCwvp6emJeI6UlBR+8YtfsLOzw9zcnOxflpOTw9/+7d9GJQQf+9jH+NjHPhbzde1FRkYGg4ODxyZWklZG8pBSqVQEtSEgRFFpBrkZ9RH/ZsvvIWPWwoBiN8atJDMT94c+hPlTn4KvfQ2++lUAljb8vPrWGoIAH3tHGtakszPRlLRG8TCYNhgMR6oanRShUCiqINzj8eD1etne3iYQCMhESa/Xk5SUhF6vjyoKP00IgnBmhNZmsxEIBP7Za6xsubm5Z3ZMr9cbl8kGiC+piyepgl1iVVBQEPFztVotV1ok7B2bl3Qubrc7zIVe+nMUvYHT6cQsPW4PsRJDImsd2+hzNbQbRpi61Y9jbYOX/82v0Zyy65sjnIKeYW/oryAIcvu0rKxs12vnWaSNFLGTkZFBUlLSc7dJ1Wo1RUVFFBYW0t7eTjAYpKOjg6KiokOtIvaHO09PT0cNdxYEgaKiIiwWC21tbVRUVIRptJKTk6mpqaG9vT0s666srIz29nbu37+P0WikpaWFra0tent7aW5uRhAECgsLGR8fp6KigtTUVPr7++VdsUKhkM12Y910pXN+f4zNXqd1j8fD6uoqV69eRaFQkJuby8zMDD6fj/n5ebKzs1lbW2NkZITLly+HEaPl5WUGBwepr6+PWGhFUWR6epqpqSmqq6sPrDKIosjKygrDw8OYzWYaGhqi3idMJhMKhSLmEEowGGRpaUnWT2VnZ8tVudOCNFCw1/0+2vtxu91yW8/hcKDVaklOTiY7O5uqqiqUSiXBUCOtvX9Oz9h/w2ywYTaEV/vcs370Xj3T7hEAKqxWlI2NLL/8MtZvfAM++EHmbKX84K01NGoFv/lSCqmms3UmNxqNcQuxl6pGJ4EoimHeTfv/K10/CQkJcsXJZDJhtVplUfidO3eee/jmpJASFk57IhV2r6tQKPTCp6peOLEqKCg4/U/vGaJpTF4U4lmxine17DikUhAEEhMTSUxMjGkFsbCwwNDQEH6/X74JSH/2W0Fsbm5iiUKsnGNefPYg5pcS6Noep6monul/8QqXGosp0WhwcjrEanV1NWqLCHZvlgUFBRQUFOD3+1ldXZXH6y0WCxkZGaSlpT1XC1nyb7px4wZbW1uMj4/T399PQUGBPMkXC3vDnSV7iXPnzkWU9ZOTk7l8+TLd3d2sr69z7tw5+XktFgu1tbVy/I3RaMTr9eL1etnZ2aG6uhqVSkVycjIGg4HZ2Vlyc3PJzs7mzp07lJSUoFarsVgsrK+vk5qaSlJSEg6Hg9TUVFlntT/rTyIU29vbJCYmolAo8Hq9uFwuud01ODhIWVnZrkHsM2sFSVTe3d3N2toaGxsbNDc3h73nyclJ5ufnaW5ujtAbeTwenjx5gsFgkKcXo0EURVZXVxkZGSExMZG6urpDr9G8vDyZrEnPIQUf2+12rFYrlZWVZ2pCLE3HSUMSkvWBVJFyOp3o9XpSUlLIz8/HbDZHPceUCjUN5Z/k9uNv0tb/Xa5f/Hdo1W8TltC4SEgQGVkYxGazkZqYiLi1xdhnP0v648d4f/Pj/OB//7/R6dX85kupWAxnv1SddXbdQdDr9Xg8nqi/kya3o2mbdnZ2gEhReFpamvz/R7m/KBQKgsFgXOQs0jV+FsTqmfbyxWvJX+TBtFptdm5u7pkxAJ/PF7dIFY/HE5f+uHTseFXLQqEQgiA8dwXmMCsIh8PB0tISLtfuJJ9kdLq+vo5cK9tDrNbaXKgMCh5njyPuiBTrWrj+wXouFj9E8OwuoqdBrDY2NsLaSrGgVqvJzMwkMzOTUCjExsYGi4uLDA0NodfrZV3Wcc/fxcVFrFarrFW6dOkSHo+HyclJ7ty5Q1ZWFvn5+QdWNiwWC1euXGF2dpb79+9TWFgY4Wel1WppampiZGREDnKWboRms5lLly7R2dlJZWUlAwMDVFZWotfraW9v5/Lly2i1WsrLy7l//778PvPz85mcnJTbkfPz86SmpmKxWNjY2IhJrPbqCVdWVuSK4ezsrBxK7XA48Hg8coVtfHwck8kkP7ayspK7d++GfebSVODOzg7Nzc1hi4woiszMzDAxMUF1dfWBG7j19XWGhoZkd/qjVkAkg1eXy8XCwsKpBB8fF6mpqczMzMhEShrDT0lJobS0NGwK+DAkaM00Vn6Se0/+jI6B/8zl6v8VhWL3M1VPqHHYXEy8MU5NTQ0KvZ7Axga6nBxmPv9V8n7vM1x+64dc/LN/dypxU0eB0WiUvcFeJCRRuNfrZWpqKow87ReF63S6I4nCjwvJqDMe1br9QyqnDaPRqBAEwSCK4gtjzUcmVoIgKIFOYF4UxfcJgvBbwO8ARUCaKIprhz2HxWIpOUsPq9OaaPn/2rHjWbGSKgZngVhWEMFgUK5ubW5uMrOxQTowPjiIp6+PREw4R5WYr2rp2hkjccjHj966RXlNFmXZWYj9bvh/2Xvv+Mju8t7/faZ3TVPvZVddK622aouNbZoxxdhODBgChjR8Ey43wM0Nv9yb8grh5kIgYAIJIb8QwDaYhN4M2Gtvr9KutCqr3kdtNF2aeu4fs+dYbbWSVqMx9n1er3lpdGbmfOecOed8P+d5Ps/nIwgId0gul+QnNssNUCgUcolUFEUCgQAul4uLFy8CyFIOG8lMDA8Pr+pi0+v11NTUyLY5Z86cwWazUVZWdst1CoJAUVERubm59PT0cOrUKerq6pYBXUEQqKysZHp6mrNnzy4DGBaLhfr6es6ePUtDQ8MyAHPp0iU5K1RZWUlHRwfNzc0UFRXx0ksvUVZWJnvWJRIJrFYr3d1JPb+1LrpLgZVkYyOKoiyfIAGk2tpaBEGQlcglaYXFxUX5O01MTHDt2jVqampobW3FbDbT3NwsT1ajo6M89thjDA8Po1QqeeKJJ3jd617HX/zFX/DVr35V3s5PfepTHDp0iJ6eHr75zW/ys5/9DLVazRe+8AXe+MY3AvDzn/+cj3zkI8TjcT70oQ/xp3/6p/I2ScbHsViM8+fPU1FRsS3Gx7eLeDyOx+NZBqRisRhVVVXU1dWtMnrfbNjMJTTufjdXev6djoH/oKHit4h442hnNUy3zHP69Gl8Ph/hp58m7vHgzavnh3kP8Hjzs9z1rb9F+OR7wbAzHn5Go3HbM1aiKBKJRNYs0y0lhev1+iRfNB7HbreTn59/R6TwzYZ0nr0agVV+fr7Y2dmZC/Te9s3bFJvJWH0E6AKkeuVp4MfAiY2uQK1Wl6QSWEWj0bRxjdINrF4Jiu87FUqlEqvVKvuo7fvt34ZPfIKSzk7msrJwtwUBJRe0bcRI8P1PP0vruVN8+dn/SobhD0hEriBoNHd8p7dUn2mrIWXfzGYzu3btIhwO43K56OzsXGaxY7PZVgE4qXRwq/2vUqkoKSmhuLiY6elp2Q+tvLyczMzMNbdfrVZTV1e3prmzFFlZWbKRc3Z2NhUVFcRiMTo7O2lqaqKvrw+LxYLNZpMV5dvb29mzZw95eXmMjo7KhskFBQWMjIxQVlaGw+GQy4HSBHcrYGW322VCrtFoZGZmRlZgn5qaQqvVYrVaicVitLW1sW/fPpm7deHCBRk0Wq1WWltbeeGFF6isrFzmHiCKIlNTU7z73e/mwQcfRK/X09zczJtuygF89KMf5WMf+xgej4eenh56e3tRKBScOnWKrq4uJiYmuO+++7hxI8kjeuKJJ/jlL39JQUEB+/fv561vfSvZ2dmMjo7i8XjIzc2lqamJ3t7elLkYSMbUEpCKxWLYbDYcDgeFhYXo9XpeeOGFNRX4txpF2YfwBsbpH/81FmM+5vGkhU+0LCqXH+dsNro8ak70abDpY2R+86sIzQ3wxBPwgx/ADmTrVCrVpjvU1iOFRyIRIHkMb4QUfvHiRbKzs1+V4Ga90Gg0KR37Jq/7lQesBEEoAN4C/A3w3wBEUWy9+dqGBxNF0ZlqALBT2kkrI53A6rXaDSmXfgUBHnoI5Ze/TJZOhzrXxAjzOAqyUeFmZmKc3NJ6nKYFujsHyRgYwAAyr0gSOt0sKHe73XLL/3aFVquluLiY4uJi4vE4MzMzt7TYkcQibxeCIJCdnU12djY+n0+2zSkpKaGgoGBNXoVk7jw5OSmbO5eUlMgTgV6vp6Wlhc7OTs6fP08ikaCiooK8vDzsdjsXLlyQ5QfKyspobW1lcHCQ0tJSuZtQ4umcOnWKkpIS8vPzGRsbIzMzE41Gw+LiIlqtloWFhWWE6mAwSFFREW63W86oDQ0NsWvXLkRRpLu7W5YY6OjooLS0FJPJRDwe58KFC1RUVMiZNsnAXKfTLcsOLC4ucvXqVbRaLY8//rj8WnV1NePj4/J7pMaBqqoqbDYbf/u3f8ujjz6KVqultLSUiooKLly4ACTFUcvKyggGg9x77718/vOf58Mf/jBFRUU0NjbK29fZ2SmT9+80IpHIMiAFyNIHZWVla16zJBL3djop1Ja9A19wnKt9z1A1UEjIFOVq6zl+9Ol/4nOf+xxd+hKei+dTaFdRZRpDX3Uw2Rn4sY/Bd78Ljzyybd9lvVjJNYpGo2tym0KhkEyDWMptMpvNsjuDZpM3b5JQ52sNWGm12pRqiOXl5WmBHSVfb3Qm+TzwCeCOWJOJRMKcKuKldJCnK9IpDpoq4t9GIp3ZsmUdPA8/DJ//PPzkJwgN7wAgFo+jUagIeN04iosxm7I5WLePyeefR7N7N8ab0gDDw8P4fD4SiQQGg2GZsvx6pRCPx0NlZWXKtk+pVC6z2PF4PLhcLnp7e9FoNIRCIfbu3bupdVosFhobG2U+x0svvUROTg6lpaWrjiFBEMjLyyMrK4ve3l5OnjxJbW2tDEoUCgV1dXVcvnyZmZkZGdwbDAYOHjzI+fPnqaurw+l0smfPHs6cOYPFYsHhcFBUVERPTw81NTXk5OTIpPZr166RSCSw2Wx4PB60Wi0ej2eZOGgwGMRgMDA6OkpWVpasv2O1WhkeHpb5JxMTE0SjUYqKikgkEly+fJn8/HzZGHpmZobr16/LnnmnT5/GbDbj8/m4cePGqi7IoaEhWltbqa2t5dlnn+VHP/oRTz/9NAcPHuSzn/0skPTtW6rwLvn2SZmhU6dOyQbcPT09axofZ2dn43K5lvn/bTQWFxeXSR8olUrsdjuZmZns3r17Q2BN2vfbCawUgpL91R/kxUufJTSUYLLSTedLl/nxM9/lQx//HM8FCygIjvLYm6s5f/UmifsjH4Gnn4Y/+iO47z7YZscOicO5Unrg7Nmzsn6aRAqXwNNmSeGbCclYPB2h1WplmZN0jJ3K7bbZbBpgR9HqbYGVIAgPANOiKF4WBOHuOxksHo8bUsXHSZcdAKzt1bWTkc4SaLptfGSgfvgw5ObCd7+L0JgEVtF4DI2gwjitehsAACAASURBVDM/R1GDE43aQbi/H3FxEVNDAzqncxkJWRRFgsGgTJYfGRkhFAqhUqnWFDqNxWI7xoEQBEEm91dXVzM/P8+lS5fo6uoiFosts9jZyA2GVqulsrJSts25cOECJpOJ8vLyVWr7KpWK6upqioqK6OjoYGhoiNraWvR6PR6Ph1AoJAuKFhYWUlJSgl6v59ChQ5w/f57q6mqysrLYt2+fLCpaWlrKqVOn8Hq9lJWVcfbsWYqKinA6nczOzsoE9vz8fMLhsNwyLp1rCoWCmZkZKioqGBwcpLg4aaI9MDDA0aNHWVhYoKenR+ZVXb16FavVKksxDA8PMzIyskxPqqamhlOnTpGVlcWRI0eWXU8CgQAPPvggf/zHf8zAwAAf+chH+PKXv4wgCPz5n/85f/Inf8K//uu/LrsWiKLIwsICAwMDhEIh4vG4DOL6+vpuOTHn5eXR2dl5W2AlSR9IQMrr9aLRaHA4HOTl5VFbW7ulyT8jI4PJyclNf+52oVEbqTd9kKk4uIrcDHb0UlJRw8/bAuzOiHG8++co/ElNtXg8jlKlgn/5F9i3Dz7+8eTzTYRECl9LgkACTkslCAwGA3a7XS5R7/SNeqpLYutFujNWqRzbYrGo1Wr1ahf0FMZGZuMjwNsEQbgf0AEWQRC+KYriY5sdTKlUal0ul2w7oVKp5Od3mu2JRqNpA1bp1pGC9JVA06l2HwwGX86WKRTw0EPwL/+C8MkkPycWTyCEEyyEAhjMDlRKO6Hr1xF0OrRreKJJSuEmk0nOagCy75qku+Xz+QiHw8RiMbq6upZJQezU7xAMBikuLmb37t1EIhGmp6fp7e2VbTFycnJwOp23Pa+USiWFhYUUFBTI3WyxWIyysjJycnKWbY/RaOTgwYOyuXNubi4ul0v2FTxy5Ajt7e1cvnyZxsZGdDqdDK5EUSQ7O5s9e/Zw6dIlWlpaaGho4Nq1axw9ehSn08nExAT5+fmMjIxQVVXF0NAQ5eXlhMNhuTyzuLiIXq8nEomgUChQqVSMj49z7Ngx+vv7KSoqQqVSceHCBerr69FoNHR2dqJSqZaVCv1+P4cPH5bP24mJCXp6enA6nas01Hw+H29605toaWnhve99L1lZWcv2y+/+7u/ywAMPAMkMVW9vr2x8PDQ0xO/8zu9gNps5e/asfK6MjY0tO8aWhtlsXqY/JIXU6CABKZ/PtyHpg81GRkaG3Dyw3REfNSIq/UznztPV1snu5geoL9Lz1vIoc+cSxD2e5abAjY3wJ38Cf/d38NhjcPfdwGpS+MpS3VJSuASabDbbbUnhkUiEeDyelutpqktitxtb4oTtdKTahNpsNmMymXbUXfu2aEAUxf8B/A+Amxmrj20FVAEolUqV3+8nFosRjUaJRqPy86WkwZW+XxIAWwrEVv4fiURek8T1dJdAE4nEKydb9vDD8OSTqE7+AngdsUQcvUbLs784y5l+LUrBz2LXSfQ1NQib+M5qtVo2ZJZiYmKCubk5bDYbXq+XiYkJgsEggiCsym6l4tiYnZ2VFbI1Gg0FBQUUFBSQSCSYm5tjcnKS69evyxY7WVlZ6954CIKA82YGLxAIrLLNWfobZ2dnk5mZycWLF+UJzWw2o1QqaWxsZHR0lNOnT9PU1ITFYpHBVSKRIDc3l+LiYtra2mhubsbhcDA4OEh5eTkXL17k6NGjXLt2Da1Wy+LiIiqVikgkIoMMv98vk9UzMzOZnp7G4XDIXXXHjx+nt7cXu92O0+mkv7+fhYUF9u7dSyKRoLW1FZ1OJ1vXRCIR2tvbEUWRI0eOoFQqOXnypJwtunHjBh//+Mepra3lySeflM+1pfy2733ve9TU1DAwMEB+fj5//dd/zfvf/34KCwtxuVzcd999iKJIb28vg4OD5Ofn88wzz/DUU0/d8vewWq1yKU8CUpLavGQNs9Hs5GZDrVYTi8XWFQrdSoiiiO/GIkIxeC4bCfp81NeX8dBhG8SSE2t8fh6900kwGEShUCSB0uOPk/300ygefBD3oUO46+rwNjQQLyvDYDTKwCkjI0MGUlsFmDqd7lVbEnuljp1qWxuTyYRWq91RLaQtz4iCIPwxSd5VDnBNEISfiqL4odt8Jr4RTkoikVgGulY+X1hYkJ9Lr4VCIaLRKPPz80CyVLAZYCY938qFZLuIpluJdGp3pbsEuoo4f/QoZGej/sX3YF8SWOnUWkpK87k2pyDhmUcMh9HX1d3x2FJnmsSBkkKSgpB0t27cuCGrCi8FW2az+Y6yCx6PR1YbXxoKhUL2clxqsXPu3LllnK31SvImk4n6+nqi0SjDw8OcPHmSzMxMysrK5P0dj8cJhUIcPXqUnp4euTxoMpkoLCwkIyODK1euUF5eTmFh4TJwVVxcjNfrpa+vj8rKSk6ePElubi4Wi4WZmRmcTiczMzNy5gKS1wSlUimDi+npaYqLi+nt7aW6upqenh527dqF1+tlenqalpYWRkdHmZmZ4cCBA0QiES5evEh+fr7sEuByuWQR0aXZI6k0KQgC8/PzPPfcc9TX18t8qE996lM8/fTTtLW1EY/HcTqdfPSjH0UURX77t3+b0dFR7rvvPlQqFV/60pfkctyTTz7JG9/4RuLxOI8//ji1tbXL9nsikcDj8cjCpS6Xi6ysLBwOBzU1NXdk/bTZSIVoY3guRsQdZygnQfCGmuz8QqorO7na9Rw6fwZmQWDkxg3GFhcZHx+Xu+f0ej2er30N6xe/SOa5c2T9/OfJFWZnw/HjcOxY8m99fTJzfQfxWgY3S305X01x86bPupNjbgpYiaJ4gpvyCqIofgH4wkY/KwiCorS0dENHvUKhQKvVbgowTE5O4vP5ZDJxPB6/JTCLRCIEg8FVr0l3aVIolcoNATO/3w+8zHXayQxSOBx+zZZApclWDqUS3vlOVP/2dYQ9C8TiCeb6J/nWD55DUfxuomMeFAYD2rKyOx7b7/cvA1Qvf4WkFITV+vJ5LIoi4XBY5m5NT0/Lx4wkdGqxWMjIyNiQ4N/CwsKG9LPWstiZmpqivb2dcDi8TMrhVtILUieby+XiypUraLVaysvLmZmZoaSkBJPJRHNzM3Nzc1y5cgWn08nu3buxWCwcOXKEq1ev4na7qaur4+DBg1y4cIFEIkFdXR1nz57FYrFQU1NDe3s7NTU1tLW1UVNTw9DQEFarFY8naT8kkdcDgQA5OTmysGg0mmzZ9/l81NTUcPr0afbv38/MzAzDw8McOnSIUCjEpUuXqK6uJjs7m2g0Snt7O7FYTBYvheT529fXh8vlIh6Pc/jwYYxG4yrelNfrpbCwULYzkoCkFJ/85Cf55Cc/uWp/3n///dx//8vG37FYjPn5eTkjFY1GZemDxsZGuru7N92csF1hMpnw+/1bAlZrkcJDoRCRGwo02OldUJG7N58ffv87uCM/Z3juBxQOWrHoTJTdfz9OlYq5uTlqampeXml5Obz+9SCK0NMDL70EJ0/Ciy/Cs88m32O1wpEjSZB1/Djs3QubvDamsySm0WjSNnY6qx6pjps3sa84jtV2hcFgMKQsxbGSwK1UKlEqlVvO5khO5yszY9LfxcVFebnEublw4cKqWrFKpdpUxkytVqNUKjd8oKeTtP+KLIE+/DDCl7+Mpe8F4vFdDLfe4It/+7/58GffQiw8j666GmEbunk2I4wqKSfrdLpl8gyJRIJAIIDX62V2dpaBgQFZdHRlOXEpgJyfn9+Syr9er6ekpISSkhJisZjMAbp69eq6FjsKhUJWjZ+fn6evr4+pqSkaGhrkEp3D4VjT3Lm5uZmhoSHZyHkpuNq3bx9nz55l3759KJVKfD4fOp2ORCKB1+slPz+f6elpuSwoASvJFml0dJTi4mLZ8Lm9vV3mZHV3d3P48GG8Xi/Xrl1j7969ZGRkMDU1RWdnJ7t27SI/Px9BEIhGowwMDDAxMUFZWRl33XUXU1NT9Pf3y1lByfh4fHxcNj6ura3dVNYxGo3KIMrtdpNIJGTpg9LS0lXnkiQgmY5JT/INXKvjdykpfCV4WkoKXypD4HA4EMxqRtp9FGijdHqs5O2vpMZt5fK1f2a01ANN5eTmZqMPhGSrllUhCFBVlXz83u8llw0PJ0HWSy8lHz/5SXK5Xp9sapGyWocOwW2kYdKZNVranPFajFQd6zc7x1+1wMpsNptTdtRsd/ZEEAQZnN3urm10dJRIJEL5CkK0KIrE4/E1gZlU0vT5fKuWr0zJrgfMAoEA4XAYt9u9bPlmwNlWI51lyFuOffw4ot1JRtdPiCf+mOBckgxqMNtJeBTbUgaENbJlW4ilxtNLQ8pu+Xw+hoaG8Pv9JBIJjEYjFosFv9+P0+m8owuRSqWSwZIoirjdblwuF93d3ej1etliZ+WxLwEwnU6H3+/nxRdfpKCggOLiYjQaDaWlpeTl5dHd3S373pWWlmK1Wrl48SKVlZUcPHiQixcvkkgkaGpq4tKlS+zbt4+LFy/S0NDAjRs3yMzMJBqN4rlJZg6HwyiVSsLhMF6vl8zMTLn8KAiCTFjOyMjg8uXLHDp0iOnpaQYGBjh06BAqlYq2tjbC4TCHDx9Gp9MRi8UYHBxkbGyMkpISjh8/Lv+mOTk5dHV1MTIyIss2bNb4eHFxEbfbLZf2JAAqZfVuRx+Q/ON2UidOIoVLXD2p5HunpHAA0SYyaQlQEk3QaY7z+te/iUPaMH/72LuYrcumb+oFFtp9NJS9b3Pgprg4+XjsJvV3agpOnXo5q/WXf5nMdKnVyQ5DqXR45Egyy7UkXs0lsY1EuoC8xLNKhVeh2WwmkUikRufpFrGTwMpksVhS9ovFYrG0aTndSu5AEAQ5Y7XVzjnJuXw9vlkkEmF0dHTZ8ng8vub32EjGTHp+u4M8nWXIW2bLVCrib3oblu9+G3Hh9wjMeVGqlOiMGcTDJrQ32+3vJJZqKqUitFqtzJOSQuoIkzoTw+Ewg4ODqNVqzGbzMqHTzfL9BEGQLXYgWeacmpri0qVLiKIo87KkrseRkRH27t2LXq+nsrKS0dFR2TanvLwck8nEnj178Hg8y8ydJSNnt9tNc3MzV65cIZFIsGvXLq5fv05ZWRnj4+My4JyamiIejy9rQxcEgZmZGbKzs3E6nfT09FBVVcX169fZu3cvly9fprm5mZGREdlg2ePx0NHRQUVFhUzw7+/vZ2RkhKKiomWAaqnxcSQSYWJiYsPGx0ulDzweD2q1GofDQW5uLjU1NZu+8ZM0tbYTWElK4WsJXkplKI1Gg0qlIhgMkpOTQ25u7h2TwiH521kq9URa46gfvEY0FufXc7NkfuBxcgwGMqxFtN74Fue7voAysm/rG5mdnewQfuih5P8eD5w583JW63OfS3YZCgI0NLyc0Tp2DGGN8v5Ox6sR3NwuVCoV0Wg0JWObTCYSiURqdJ5uETuascrIyEgpsEoX3ycWi6Usc7O0Q/JW4EyhUKxrgSGBs7WAWTQaJRwOr7l8ZafmSmAWDAYBGBkZuSVISxUAWQ/UxR54J7qn/pX8cxfwz3nJyLhJ+s0t3JYyYDq0u5Za3/T29tLS0iKXsaTs1ujoqJwBXSl0uhniszRORUUF4XCYqakpurq6CIVCWK3WZdlClUpFaWkpJSUlTE1Nce3aNRQKBeXl5TidTo4cOcLY2Jhs7nzgwAH6+vq4cOECjY2NdHZ2yt8zGAwSCATIy8vD5XIRDAaxWCwyR00ScA0Gg7hcLjIzM0kkEty4cYOqqiquXLlCQ0MDfX19qFQq9u7dK1sDHTp0CK1Wy9DQEENDQxQUFHDs2DH5mrGwsMDo6Ogy4+OysjI6OzvXBFVrSR9IJa+ioiIaGhru+Ni3WCz4fL41uXy3Culmay21cElGYGm2yWw2k5WVhcFgWKYUHovFZG2x7QxLlZa5i0GyPAKHK0r51vdP8WKPj3uaDBRmH8Sgc3K+858I8ium5yvIslXf+aBWK9x/f/IBEArBhQsvlw6/9jX44heTr+3eTWVFBeLwMMJddyUzYTsIctINbmKxWFrHTkUYDAYSicSOXrB3FFhZrdaU/WLpOiCksdMJ6m53R7sUnG01EonEqpLl2NiYvFzq1FwJ4JaCM0l3aKMZM+n5WhPUevwu8djriOmtlL1wCr9axJJxM5OZvT0+lenklkmTozQBSlmRpZwrSThSAlzj4+Ny+/pK7tbtMo5arVaWXIjH41y/fh2lUsmLL76IxWIhNzeXzMxM1Gq1nNnyer0MDAzQ2dkp2+bk5OTQ09PD6dOnqaurk21vamtrGR0dxWAw4PP5yM7OZnh4GJVKJTcARKNR+S5eqVTKOk+S8rrNZqO3t5fdu3fT09NDdnY2FouFM2fOUFpaSl1dHWNjYwwMDJCbm8vRo0dlSYHR0VFGR0cRRZGCgoJVxseSmKTEAZudncXtdstG0Ha7PWXSB1LWbunvKpHC1zL0BeTsuMRtyszMlIHUZq5RKpVqWdZ7O0JMJIhd/xVxZT05I5k8+vjDfPN7X+ffv3eSquK3k2fX4Mgo5+6m/86vzn+Gs+1for7iEcry7trW74HBkNTDuqmJRTQKV67IGS3nCy8g/PSnydcKCpZ3HlZXpxRopRvcRKPRtFzbUnG8SSEIAgqFYkd36I6WAjMyMlI2XjotZdIJrHZKdV2hUKDRaJZNxPPz8xgMBvLz8ze0jrVkNJb+L5FfVy5fSuiUZDSWcm5WgjEWlKgr30jJ6R/xl9d+xWjrVxmIJIiZtoe/mE5gJQlkrhcSudtoNC7zEozFYrLQ6eTkJD09PUQiEfR6/TKwZTKZ1jyXlEolkUiExsZGzGbzKosdCVhlZGTQ1NTE4uKibJuTm5tLRUUF0WiUjo4OdDodzc3NtLe343A4ZDPlsbExbDYbsVhMFmuUtmnpQ6/XYzKZZO5Sfn4+vb29lJeXMz8/z9TUFPv372d+fp6TJ0/KaupqtZq5ubllxsd79uxZ1YggSR8olUpOnz5NIpGQ7XiqqqpSIgYbj8eXASa/38/MzAynT5+Wm2LWIoXr9Xp0Ot0rurNLjEZx/8d/sNjZyWJBMTmjDsrfUALAzFAb3z59jD98YxY6jQKDzkGGcB9qWzfX+r6NP+SivvxhFEKK5ka1Gg4eTD4+9jEunjrFPr0ezblzyYzW88+DpDnmdCZlXaTOwz17YBuvvxKwShe4SRe/TKFQpFTL6tUMrIwWiyVlYk/pFMpMJ6iLx+O/MaBuKzIaK0NqBujr60OtVsuTsFTSDAaDRLwxLGV342j7NuGLl7Fm61BORhgYHueEp22VjMZGOjaXymikk7S/uLi4ZS6hSqWSbXGkkLIgUnZramoKv98vlx6XAi6JsG42m1dZ7IRCIVwuF62trcRiMbKyssjJyaGyspJdu3YxNjbG+fPnZXmFYDDI5cuXKSwsJBwOs7CwgE6nw2QyMTs7K+9r6WIrZZFWCldK5azh4WFKS0vp6+ujuLgYu93OpUuXcDgcHD58WLa7mZycxGq1rjI+Xkv6QJLNEEVxTc2wzYRECl+L2ySRwhUKhQyYJNA0NTXFgQMH0qKTJ012d3ptSywuMvfUU0SGhsh405uICCpsP9OgX7Tw+7//+zQeqMcVjPODCx5+60hS+kOt0rN31+P0jv+U/vFfE1yYYX/1B1GrUl/RUWu1RKuq0DQ3wxNPJInv/f0vk+Ffegm+//3km02mlyUejh2D/fvhDri+6QY36epKFAQhpWMrdniC3skZWalWq1O2cekEN+kEddtx4dtqpCNTJ3VqSnpRS+ULpBBFkSFzOwBzwyP857cusP8xL0ZrEXcdr1lX42xxcRG/379mWVOKcDiMSqViamrqtlIaW5XRuFVIAGS7YinnZqnhcDwel8nyMzMz9PX1ySa1169fXyZ0qlQqMRgMlJWVUVZWRjQaZXp6mv7+fnw+H3a7ndzcXI4cOcL8/Dzd3d3E43F2794tl9dyc3MZGxvDbDaj1+sJh8NyB5pEqpbOMwnkSvt0ZmYGm80md/eNjIxgtVrZu3cvbrebixcvytY9Eq9K+o4SkJKMn51OJyUlJfI+DoVCXLt27bb7MZFIsLi4uIrbtJIUvjTbtBGl8J6enrTdOG1HaSju9zP3jW8QnZ7G9tBDGPbsYcF1hQzBgq97ga985SsAnOz088urPi72aTiwy4RarSYeT1Bf/hBmQw5X+57mpbb/w6HaP8SoT63p+ypwIwhQUZF8PP54ctn4+HKJB0m3TKtNZr6k0uHhw7CBxgcpUp25WS9SDW7Wix3IWKVs3WvFTp6xCqVSmTL0ka5OCmnsdIK6dI2dzu1eL1smCAKqzKSZuatvgO/96DJV93cxq7UhCE45A7VVgNLV1UVGRgY2m21NACa5AKyU0Fh5J7oR8dmVyzdSCtyOUCqVsrioFDMzM4yPj5OdnY3P52NgYAC/348oiphMpmVCp3l5eeTn58tt+y6Xi+vXr8s+jCaTidHRUdxuN7m5ubjdbvR6PcFgUHZAkAAwJLOEEtCKx+Pye6QmC2lSmJ+fp7S0lKmpKS5fvixraSkUCubm5ujq6sLtdqNQKGQNqV27dt0yI6TX62X+4HaQwjcbko9aOrpv77QsFXO7mf3610kEAjje8x50u3YBkNCJuPN86LvV5L4+g7m5ORqLtAxNa/n5FS+FTs0ycFOSewSjPpMLnV/lxda/40DN7+G07tq27VwZG5rk8/Ph0UeTD4C5ueUSD5/+NPzN3yRFi5uaXs5oHT2aLCfeIl7N4Ga92IHtvu0JKAjCvwIPANOiKNateO1jwP8BMkVRnL3dunYUWCkUipQhn3RnjdIJ6l6L2307QKnKTgIrZ0Gy7DXVewWt9ci27C9pspEm0q3EWjIaS4GY5AywsmEgGAyiVCrp7+9f1qm5UWAmaZxtJUKhEBaLZZUURCKRIBgM4vP5cLvdDA0NsbCwgFqtlsFWfn4+VVVVLCws4HK5GBoakoVHJdBiMpmWNUFIwGql8vlSrhUgmzObzeZlnKtYLIbb7eb8+fMyyT8nJ4fq6uploFwUxTUFL6VHMBjk3LlzGAyGOyaFbzYkgJFOYLWViExOMveNbyDG4zjf/340N70XAUREpkrmcZ7O4MqpNpqPNfH000/zznc8wj/+fJrvnHZzJE+5jMycad3NXU0f51zHlznd/gUad72b4pzDd7yNa4UgCJsHGA4HvP3tyQeA3w9nz76c1frSl+Dv/z75Wm3tyxmtY8eSBPmb8SoHN+uOncrt3uA1/9+AJ4F/X/HZQuD1wMhGx3tVZazSmbl5LQKrdO/z9cbW5CTT7xZTktjr6uoif58aT8CHzXxnJPbt0LHaiIzGWnH9+nUyMzPJyspaJaOxVllzJTC7leH5RoCZz+fDYrGsArUKhUKWaFjayBCJRGTfxJGREfx+P/F4HIPBQGZmJjqdTn4PvMynkrYrHo8Tj8dXXeylrJX03aXOVMmP0e12EwqFcDgcFBYWUl1dTSQSIRQKyVpTEnhaSQqXMk52ux2DwYBOp+P8+fPs2bNnxyU2lm5rOmKr5rjhwUHmnnoKhU6H8wMfQL2Gevt0qZva0yXkxIvR6/WcO3eORx99lEda7Pz/z8/S6jJRUrR8bJM+i+NNH+di57/QeuMb+EOT1Ja+A0HY3mvQtnCNzGZ4wxuSD4DFRbh06eXS4be+BTfLoJSWymR4bU4O4hr0hp2IdGfL0q06L4riS4IglKzx0udI+iL/YKPretVkrF6rACOdpcB0Z6zWG1uTlwRWJo9AQ1Mjo/1DNAM9Yx0cqj5yR2Onu1lByjhtt4zGWh2bSzNIs7OzzM3NMTQ0tKpTcz3yv9R1KHGilroO+Hw+2a5GasQIhULyRX6ti6302ycSCfkhLddqtTidThYWFpicnGRiYgKFQrGM22S1WsnNzcVgMGzI21Mqx6ULWKUzg7HZsRc6O3E/+ywqux3H+96HKmP1TYyISNgcRZejJtQXY//+/Zw7dw6Akiwt99Rb+PU1Hx1jce5eUTXTqAwcrn+C9r5n6Rv7FYGFafZVvR+Vcnt5h9u+z3W6ZBnw6FH4sz+DWAyuXn25dPjjH8PXv84uIJ6VlZSCkLJadXV3bC69kUh3tizFY29pohIE4W3AuCiKVzcz171qMlavVYCRbkD5Sh1bU5i0iTG7Rer27+HsT55Pkton+zlY1XJH3zvdgHI7NW7WktG4VVy9epXCwkLsdvuq73QrYCYZnq+VWVsJmqRlarVatlVZKyRgK4EvCTQt7aiTsk3bsa8WFhZYXFxcZT20EyFpVGWsAVB2YuzNWMuE2tuZ/+53Uefn43jsMZRr6OuJoshCIknmz6jUMfWSnwPNB/iHJ/9B7ng9VmPiau80L/Zo2V0UIc++/NhUCEr27HoUszGX9r5neants9zV+HGUyu0pl252u7cUKhU0NycfH/1osvOwq4vhb34TZ2cnxjNn4DvfSb7Xak0Csr/6qyRfK0Wx3Y0xmx07lZ2vQ0NDTkEQFKIobhi9CYJgAD4JvGGz4+0ksHrliqz8Bke606evVO0czU2OldEr8vv/+N/43J/8OZ85Dd4F8ASGsZlL0vsFtxivxN97pYzG7bJga5UnJc0q6bO3285IJCJ3WUrcM4VCIQOu7TwufT4fbW1taeE5+Xw+gsFgWsaWNM9u3Lixofc7+vqwiyIjGRl0Xriw6vWwMk5PlpdZU5hMv44+bxdmsQCjaCEajfL0009TWloKQIGwgI8q/uU5F432cSyatYGOljp8wWucOPlTlFjXfM9mIxAI4Ha76e/v35b1bWrslhbUd92FVqNBNzVFxtWrZLS34zx9GuGuu2j73OcIrvCk3a4IBoNMTU0xNDSUkvXfbmyXy8XIyIZpTFsJBbCZtFg5UApI2aoC4IogCAdEUXSt98GdBFaJVE4KO5BKXHfs12Jt+pW8zwVj8m7Z4EngSoQwF1SgjQ8RidkYcZ29I2CVzn2e6tLQerwtdEAYMAAAIABJREFUv9/P0NCQbEq8Vd6WXq9HEATC4bDMe4pGo/LnpNfW+42lTJsoiuh0Ojk7FYvFlkk1LM1gLf27mbvjK1euUF5enpasUWtrq2xivdPR3t5OXl7eMlX/9UI8coSZr32NvL4+su67D9XNz4miyOVQP6e9bSRI8EZzI4fzKok44vS0TfPQm36Lwro83vrWt+K82THX0dHBHouRH7YlaPcV89hdDoozV3cnXh+Yp29cyd3H34JSsT0Zj6U8xp2Orq4u7Hb7y9InUtfh4CAcO8b+P/szePFFqKra9rG7u7uxWq2bslDarujp6cFsNpOXl5eS9ZeWls4ODg5uiqwoimI7IB8EgiAMAfteaV2BiVgsliCJGrc9Xsvg5rU49m33uVKJqNZi8Mdwx/y8/wMfYHxOxdve+zij0yeoK3toy6WDdALK9cjMt+s0vFXGaC3D7lsBI4nDtNFOw0QiIetheb1epqenWVxcRKPRYLFY5EzXwsKCvH3hcFj+fdfiWSkUChlg6nQ6YrGY/JtIPo4OhwOr1SobOIdCIebn5xkfH5dtaiBJWl8JulYqmafTWSFdvnHS2JvJ/AlqNfZHH2XmK19h7umnyfzd38WjjPIDzwUGw1OUaLJ4u+0ADlWS/6i6KXafY87ngx/84LJ1iaKI1ajk8fsc/Nvzs3zjxBzvOe6gNHs5uPIERrAY87YNVEljv+JoJaWl8OtfJzlX996b5GZtc+Yq3dSOVO5z8Was9x5BEJ4G7gacgiCMAf9LFMWvbWW8nbxaxOPxeMpm4XSDm1cx6e+W8Urf56JOjyYUwRMKMT09zY2uASKR/0osvsDk3FUKsvZvaexUkDxFUZRV5dfSxpKez8zMMD8/T39//6a1sYxG45rLpfLZRrZbEIRbirKGw2GZkO71egkEAoiiKCu4O51OysrK5JLDzMwMer0es9mMRqNZ5ne3dLtEUVzGoZRKfhKgkwj9wWAQvV5PVlYWSqWS8fFxPB6PLLXgdDqx2WwySJJU56UOwWAwyOzsrMypEkURjUaDz+djaGgIk8m0DIDtBODZjg7UrcZWeKsqqxXbI48w841/5/kL3+NsuQIFAm+17qfZUI5iyXGm1AsISogG4rS1taFSqairq5PHFgSBDIOSx+91JsHVi7O865iDXblJHpAoingCo+Q7927fRpN+zuwt93llJfzqV0li+733JknvS2Qs7jTSvd3pppWIoviu27xestF17WjGKpFIpGwWTje4ecVmblIYr3hQp9cjRBeJzSbYv38/zz33HO6IEq1gZth1dsvAaqVhqASKbgWG1ssYrVzvrYCR1MEWjUYxGAwUFBRsm5r7RkOv1+N2u4nH4zL/RgJRkUhEljuwWCxUVFRgNptRKBTEYjGmp6cZHx+ns7MTm81GVlYWZrOZkZERAoEABoOBUCiEVquVuVYSV0oCVoBsxLwUWEmAL5FIyL6D09PT2O12Ghoa0Ov1zM/PMzk5SWdnJwqFQjaulkRC1wpRFIlGo7z00kvY7XYWFhaYmZmRgZj0HVdmu6TndyIMKkW6Dd63Mra/yMlP3tvAhC5CWVDNg6VvIENlXPU+QRBQGRXEggkefvhhmpub+fa3vw0sB3VmfRJcff2FOZ56aY7fPmqnKl9PaHGOaCyE1Vx0Zxu6Il7R2oD19fDcc3DPPS9nrrapdPeKzNRtU+z0HLmjwCqVGav/B252PtLNNbqteKHRiCK6gH5eS/2+RhKJBOPDXVjzipgSOwktujHo7HKmaCPAKBaL4fV6GR8fX8bTWc9/UKfTYTab1/Uf3GiEw+Eda/2XhDMlAOV2u5mbm2N2dlbOQmVnZ7Nr165V6twLCwuMjIzgcrkIh8NkZmZSUlKCyWRiZGSEnp4eMjMzKS4uZmBgQBba1Gg0LCwsyOezSqWSy4GJRELeZ9IyiUcVDAZxOp0sLi7idrvZvXs3KpWKwcFB/H4/eXl57Nq1C71eTzQalbfjxo0bJBIJGWA5HA55W6TfRq/XLzOzXhrxeHxZ1svv9zM1NcXCwoJsZbNUTHZp2VGn0912IotEImkhrsPmgVVcTHAq0MUJXwcavYo3dQsUvdiG7nf2QFnZmp9RGZXEAnGKi4sZHh5+eV0rPFCNOiUfuNfJv78wyzMn3TxyxI5Vl3y/1bS9wCrdbha3vSY0N8PPfpbUyLrvPjhxYl01941GujNWKd7nOzpR7TSwShkC+H/gZudjQ+AmRaFWq4nFYrds9Y/FYmRrVCiiQTLmjIjZIQDGei8RztkFtSIvnv8WerEehUJxS/NlrVaLyWRa9poEqkpKSnZ8u/V6PT6fb9vXG4vFZAAlPaTsmJSFysnJ4fLlyxw/fnzV50VRxOfz4XK5mJqaQqlUkpOTQ319PUajkUAgwMDAAG63m6KiIpqbm+np6SEUClFSUsLAwAC5ubnMzMwgCAJarXYZZ0wCF5FIRC4FSsDP4XDg8/lQqVRMT09TXV2Ny+XC4/Gwe/du7HY7k5OTXLlyBUEQKCwsJDc3VybpLjVgHhwcJBqNYrPZcDgcCIKwrsyCUqnEaDRiNK7OyEj7RTKZllTdPR6PLKOwFByuxfWC9HXebgZYTUTcfN9zHlfUQ52+iPszmjE4BGauz+D+znfI/IM/QLUGAV9lUhALJCgpKeGnP/3pumPrNQp+5x4n3zwxx7On3RwoC6IQVJiNa4PerUY6je03DDBaWuBHP4L7708CrOefT8oy3OHYr9hM3R3GqzljtRAIBFImIfxaLQWmE9zcqRP70rb89QjXK58nEgm5a6yvr2/NLJFarSZWXYXpuecpuGEhclzPOx96GDIcDKl3U+WMMuft4+jB30Ol3JwXmlS2SkfodDqZi7SVEEVRtp+RHsFgEJVKtcx+prq6es3OOZ1OJxPEl/oAzs7OYjKZyMnJ4dChQ3LH3tzcHB0dHcRiMcrKyqipqaG/v58rV65QXV2N2+1mYmKCoqIiXC4XKpUKq9UqmxdLmUCp3Cd9J6VSKRPXZ2dnKS4uZmRkhOrqarq7u8nOzmbv3r309fXR29tLZWUlLS0thEIhxsbGOHXqFBaLhaKiIhwOxzKbnng8jtfrZXZ2lpGRERm8Sxkto9G44UlAEAS5a9Fms635nlgstsxKZ25uTv4/EAhw4sQJGWitR7Lf7tgIwIiKcU742jkd6Mag0PIu+zGq9TctWpRgf9e7mPmnf8L9zDNkfvCDCCuOKZVJyeJUlOLiYlwul6xldSsvUJ1awXvvdvDUS3Oc6y+jKufYthLX4Teo/Pq618F//mfSRufNb06WCDdh+Lwy0u2kkUpgldhhcLCTR0/A6/VGU7XydGZu7hRg/CaOLZ2EwWAQr9e7Ia2ijbTlL32u0+nWXK5QKBgZGSEajVK+XmfMH/wBfP/75LSdZGC0hf/47rP85CedXPCaOWZy4Jq7yrDrDOX5r9vUtmu1Wubn57e66+4oJGCzkYhEIquyUIlEAoPBIBssFxYWYjAYNnxRs9ls3LhxQ5ZfkPz3amtr5YtyPB5nZGSEwcFBzGYzlZWVZGRkMDU1xalTpygoKODgwYO0trZit9vJycnB5XJhs9mIx+MySDObzXIJUDq3Jd6V5ANoMBjkMlJ1dTWdnZ3U19czNzdHa2sre/bsQalU0tPTIwOsyspKdu/ejdvtZmRkhPb2dnJzcyksLMRoNKJUKrHb7djtdmZmZmhubmZxcZG5uTk6OzsJBoOYTCYZaFksljuaFFQqlWwJtDQCgQCdnZ3s27dP7mxcSrKXhCwlkv2tuF6pItkPh2f4gec8szE/TYZS3pSxF71iedlS7XRie+gh3E89hecnP8H69rcv21cSx6qoOFnOGx0dZdeuXcscBlaGVq3gPccdfPHHZ+l2tXChN8CBXaZt2671DN5THZsGdW9+M3z72/DII/DWt8JPfwprCLNudOx0daCmGtS9moGV3+PxpCxj9ZucubmTkEpim4m12vI3AoxWtuVLbe5+v39NXtFagGm7TlyNRkMwGFz/Tffei5ibS0bnd1G33Q37oNa+yK8GfHSPFGG3lNE/9jylecdRCBv/XlILfzpC+r2X3uEtlTSQHktNkDMyMiguLpZ5XpuNUCjE5OQkU1NThMNhEokE+/btWwUowuGwrHOVk5PDwYMH0el0BAIBzp8/j0aj4dChQ7KpcW1tLX6/n+npaQoLCxkbG0On01FYWMjk5CQLCwuYzWbUarUMrGKxmNxtmJWVhUqlkkFVd3c3TU1NXL16lYqKCnJycmhrayM3N5fGxkaCwSA9PT3cuHGDqqoqGRjFYjFcLhfXrl0jHo9TWFhIXl6ebJcjZZysVivl5eWIokggEGBubo6+vj58Ph8Gg0FeX0ZGxrZMEoFAQG4AWM/wWyLZL8163Y5kv/SvpB22NNbrRgwnovzKd40LwRtkKI28z3E3Fbpbl+P0VVWY77oL/4svosnPx7j/5aYRtUmJGId7jt3HL37xi2VctvXAajQ2R6n9GebCf8SPL0EsDi1V2wOu1gN1qY4tZcsefBC+8Q14z3uSz3/4Q9BuLgu/5bG3KVIJ6m7enO2o4eaOAiuv15sy1PhayRqtbMsPh8P4/X7Zg+1WwOh2HWhLAdBabflSB9bSi93ExAR+v5/Kysod2falodVqbw9uVCqE97yHjM99Hlt3mLA7xgMfeDcqtQ3H//csj931etpu/BMTM60UZO3b8Nh6vX7DWaPtDqkE2t3dLZOlRVHEZDJhsVhwOByUlpbeUYlIFEU8Hg8ul4vp6Wk0Gg05OTk0NTWh1+s5ceLEsiyXz+ejv78fr9dLaWkpx48fl290Ojs7mZ2dpa6uDpvNRl9fH1NTUxw6dIixsTHm5+eprKykra2Nmpoa+vr6EASBgoICJicn8fv92O12+Rzz+XwIgiDzo8bHx6murmZgYIDq6mquXbvGgQMHaGtrw+FwcOTIEXp7ezl9+jSNjY3s27cPn89Hd3c3iUSCqqoqrFYrBQUFFBQUsLCwwNjYGKdPn062+2dkrCpTCIIgZ5hKSkoQRVE2dx4aGsLr9aLRaGSgZbPZtjRpSKbXtwtBEGRboluJmK4k2Xu9XlwulyzOCstJ9lK3ZSgUWkay71uc5Ieei3jjQQ4Yd3OfpQHtBkpx5te9jsjEBJ6f/hR1Tg6amzIBKlNyvVmWbIrekCwhbqTy4AmMoBDivPOgjl+16/h5q5doXOSu2q2XwpZGOnltWwIY73oXLCzABz8Iv/Vb8N3vwiYtYmKxWEptZW43dqpAXSQSQRCEHb0T3tFSoM/nS1mt7jcBWElljY2UzFYuXzmeBHqkDIJ057nU8HYpMEpFW75Go1n13XYqNgSsAN73PhSf+QwZ13/A1MV87r33Xr7yz/+MPxhkwlOGSZ9F79gvyc9s3vD+2UqWcLMRj8cJBAJ4vV45CxUOh+WOtXg8Tnl5OSaTaVvu9OLxODMzM7hcLubn58nIyCAnJ4eKiopVF9v8/HzGxsYwGAz09/cjCALl5eU0NjbKfMOxsTF6e3spLS3l2LFjxGIxLly4gNFopKWlhd7eXvx+Pw0NDZw7d46mpiba2tqoq6ujo6ND7sQbHh4mFothNBrlLGtubi46nY6BgQFKS0uZm5vDarXi8/koLy+ntbWV/fv309nZSXt7Ow0NDeTk5HDlyhXy8/MpLy/nwIEDeDweuru7USgUVFVVYbFY0Ov17Nq1i4qKCk6cOEEikeDEiRNkZWVRWFi4JtARBEEmsBcVJUtaUulwYmKC69evy+VFSUtrIxOYz+fbNhXszZLsp6enicVitLe3yyR7jynKldxZzHENb07UUhrOJhxYQKHnttsjKBTYH36Y6a98hblnniHrD/8QpcmEypgEVrFAgh+d+xGZmZns3bv3tuvz+EdQCCps5jweblGiOj/Pr6/5iMVF7qk3p10T6U5iy9/98ceT4Oq//Bd473vhW9+CTVwb0lkKTCWw8vv9KBSK25Q3tjc2vCWCICiBSySdnh8QBKEUeAawA1eA94qiGFlnFX6fz5eyo30ngNWttIqkLp9IJLImMFp6B7ayLX8lp0jqQNtoW/709DQzMzPs2rUrpdu+VqSzJKbVauV29nWjvp7FhhrMPc8w0voB3vHOh/nCP/4j89ef47zzEd6+7z6u9T3FrOcGmbaNZ96kZok7LflIIpWSHpTP5yMQCMhZEYvFQlZWFhUVFbJB6sjICJFI5I4tVsLhMFNTU3Lmwul0UlhYSENDwy23SzrHrl+/TkFBAfX19cu4QV6vl46ODkwmE0eOHEGj0eDxeGhra2P37t3k5ubK2bampibOnz9PVVUVU1NT5ObmMjU1RVlZGYODg1RVVZGRkUE4HEan08klZ5vNxuTkJFarFYPBwPDwMM3NzbS2tlJXV0dubi5tbW00NzczMDDA+fPn2bdvH0ePHqWnp0fOXlmtVg4dOoTb7aajowONRkNlZSVmsxmv14vRaGTv3r3E43Gmpqbo6uoiHA7L2a31ZBB0Oh35+fnk5+cDybtmt9vNzMwM3d3dALLEg91uXyVXAclSoMm0fdyh9WIlyT4ajWI2m5dxGN1hP52zv0Cr1OBMmGSS/VIl+7UI9gaDAa1Wi0Kvx/GudzHz1a/i/va3cb7//ahMyYk8Fozz4Q9/mHvuuYcnn3xyzf2xNOZvKq4rFMkp7MGDNpQKgRev+4nFRd7QuDXeWzoFWbclnngCQiH4xCdAr4evfQ02sT2/CR2om42bwMqfkpXfIjazJR8BugDplu1/A58TRfEZQRC+AnwQ+PI6nw8EAoGUHbFS9uZWIWWKNiviuBQUrdWWLx0MgiBgtVrX5BWl8mBVq9VpyxrpdLq0Aav1rF1WRuKxx7B+4s9wjfRR94Zm7EYjIxd+SM6+dxKK7UGr/jG9Y7/cFLDS6/WEQqFNTXyxWEwW1pRAlKRJtVTSwGQyrXtxt9ls8uS82fD7/bIkAkB2djbV1dWYTKZ1j9OFhQUGBweZmpoiPz+fvLw8cnNzZVAViUTo7u7G5/NRX18vl9CGhoYYGRlh3759GI1GOjs7iUajNDU10dHRgdPpxGQy0dPTw6FDhzhz5owsfhoIBLDZbIyMjKDVakkkEphMJlQqFfPz8zQ2NtLX10d1dTU9PT00NTVx6dIljh49SjgclrNVBoOBM2fOsH//fmpqanC73Vy6dImioiJKS0ux2+20tLQwOzvLtWvX0Ov1hMNhucStVCrJy8sjLy+PcDjM2NgY586dk/lg2dnZt52MpXLqUokHSRdMUtGXJB4cDscy8dN0RDAYxG63L1tm15p5p/0wT7lfotvq5oGS5eXzRCLB4uKizPVaSbKH5PXK1tBAxuXLjH3nO6gO3wNAxBeTmxCkzsBbhSiKeAMj5Gc2y8sUCoG3HbCiUgqc7g4QS4i8eW/GMqX3jUQkErktqEtVbFvz1cc/ngRXf/EXSXD1pS/Bb0AGL1Xz5M0b1e3XqFknNgSsBEEoAN4C/A3w34TkHrgHePfNt3wd+AvWAVaiKMaLi4u3xLGSyJnrgSHpTt/r9S5ry5dCUmpeCxhJytZr8Yo2cmFzu92Mjo6mxbxywyWxFIRard5Y1ihFsdGske6x95P400+SceNZvK01vLGxkZ9cPs09mjjnbixybPfddA39EG9gjAxTwYbGNpvNt8woSJybpcrkoVAIhUIhA6i8vDyqqqq2JP5oMplkAvftLkaiKOJ2u3G5XLKFTE5ODvv379/QBDI/P8/AwADBYJDS0lKqqqrkbtArV66QmZkpdwBWVFRQX18vNzZcvXoVpVLJkSNHUCgUtLe3A7Bnzx5GR0cJh8PU1tZy7tw56uvrGRoaoqSkBJfLRX5+PrOzs5SVlTE0NCSr3WdkZBAKhTAajahUKhYWFrBYLEQiEVnSob29ncbGRq5du0ZPTw9VVVXodDrOnz9PU1MTdrudY8eO0d3dzZkzZ2hsbMRoNOJ0OnE4HAwNDdHZ2cnIyIjsJSiFVqulvLyc8vJyvF4vo6OjdHd3y9m+jIyMDU0QKpWKrKws2R4oHo/j8XiYm5tjdHQUv98vE/OdTuemOje3IwKBAMXFxauWV+nzaTFVcSbQTak2i1r9y+KcCoUCg8EgE/lXxlKSfSAWI37VxfygFzDSP9yPQqFgcHCQzs5OVCoV/f39a5LsQ4uzRGMLq4RBFYLAW5ozUCkFznQHiMVF3rrfuilwtbTcvtMRjUa3j+P0P/9nElz93d8lwdVnPvMbAa5SEX6/n0Qi4d3JMTeasfo88AlAyvk7AI8oilLtbQzIv91KEomEODc3tyGtolsZw64FfqS2fEDW35Ha8ncidoJzc6tIJ7BKN49B0nQy3Ka9WJGby8jr9pF57T+YPvzf+f23vJv3HTiAucbGL9p8aOtbUCp+Qd/Yr2iuev+GxpbAjQTqlz5isZgsaSDpQm1G++h2IQiCPP7KFn1AtpBxuVx4vV5sNhs5OTlUVVVtiEMhiiKTk5MMDAyg0WgoLy/Hbrcv+/5GoxGdTsfzzz9Pbm4uR48elc9Bv9/PlStXKC0tpaioCFEUuXr1Kmq1mpqaGubn5xkaGqKlpYWxsTGZeH/16lWOHz/OqVOnaGlpYWBgQN4+yXTZZDIxPz9PVlYWMzMzsn5VTU0NHR0dHD58mOnpaSYmJmhoaODSpUsMDAxQVlbGgQMHuHjxIpWVleTm5lJbW8vc3BwXL16kpKREBhKTk5O0tLQQDoe5dOkSVquV3bt3r8qiSJIViUSC6elpent7CYVC5OfnU1BQsG7WZWUolUo5WwXIPLNoNEpHRwehUAiz2Sy/x2xOLY8oFArd8rx6vWUPI+EZvj9/gVy1DbtqY4RxiWSviCnxKl6HlwUUiwFyDvvJfFMj85+ap7a2FpvNhlarRaVSrUmyT6hHAfC6YTQ2KoMviWT/xkYLKqXAS9f9xOMib79ZJtxIpBNYbevYggCf/nQSXP3934PRCH/1V7d8+298CXSdCAQCxONxz06OeVtgJQjCA8C0KIqXBUG4W1q8xls3ksdUTkxMLANGUmr/TtvyfT4f8/PzO8ZJWBrpBDfShJOu2C6u0VZCEuq8HbACcD36AEW//l+YRs9iPngUbXQWe7mBEx1+LvXH2J3bwuDEi1SXvA2Dzr7q81KLvQSe5ubmZKVxs9ksa0JJ8gCpDqfTKVvLQLJU53K5cLlcRCIRsrKyKC0txWq1bngCjkajjIyMMDIygtPppKmpaU2y8+LiIp2dnVK3Dbt375a3eWxsjL6+Pvbu3YvFYkEURVpbW9Hr9VRVVbG4uMjVq1c5ePAg8Xic/v5+jh49yvDwMIWFhXIXGrx8bEuZ40QigdFoZHR0lKKiIjo6OmhububkyZOyXc309DR79uzh9OnT2Gw29u7dK0s9FBQU0NLSwqVLlwiFQpSXl+NwODh69ChdXV2cO3eOnJwc9Hq9LOaZnZ3N5OQk58+fx+FwrGnfo1Ao5DJfJBJhfHycixcvolarKSwsJCcnZ9PXM7fbzeHDh1Gr1VRUVCCKIn6/n7m5OW7cuIHf70+JxAMkJ1lJL2ytUAoKHrG38OXpn/Md9xk+lHkfqg3IlYgJEXdriMlf+ogvJsg8bEA5/iuiF4bwFj9CV1cX73jHO4jFkmXBtTiE0dgiv770HEZ1Do6MYhYXw8zPzy8zzlYqldgMBupzrLQNQTi8yFv2mmS/zfVicXHx1QGsIAmu/uEfkoT2v/7rpL7Vn/7pmm9NZwk01arrfr+fSCQyl7IB1oiNZKyOAG8TBOF+QEeSY/V/uXvv6Lb2+8r3c1BIggRJgCDAToKk2ElRJEWKlKhbXe+1U67tazuxYyeeTCZZXs44dZJ5eelrUibrOWW9PMfxZBInsZM4dhw7Lvc690pUoyQ2sYgSWMDeQBSikgCB8/6AzhFAgFUsM7PXukt3gTg4KKfs3/e7v3t/DtAJgqB6UrUqBpb2e6FQKORvbGw8kS/xLKtGZ90SO0sctGp0EjiMA/r2+9/Hpvb3MM3+CzMVv8+j+SXe/IXP8o4f+w3uTwa4Wvci1sXrTC+9TVXR++IqUE9KyWRkZJCVlYVer6ekpIT+/n66u7tP+FMmR25uLg8ePCAYDMZFyJw/f37Xya/d4PP5mJ6eZn19ndLS0rjqUywikQhWq5X5+XlqamrIz89ncXGRkZERmpubGR0dJRQKceXKFdRqNZFIhIGBAdkkNBwO09fXR1NTE+np6fT391NTU4NSqWRubo7u7m6mp6cpLCzE5XKh0+nkm41CoSAcDpORkSG3AgOBgByoLEXZ3L17l+eee46mpiYGBwe5fPky7e3t9Pb2kpKSgslkorOzk6GhIYaHh2lqakKlUtHU1MTS0hL9/f3U19fLbVZBEGQ92eLiInfu3JGHCZK1cVNSUigvL6e8vByPx8P8/DwWi4WcnBxKSkrQ6/X7Xv+2trZkPacEKVonKyuL8vLyPS0ecnNz0el0R57w8ng8+9o86FVafljfyZcdN/jexhCv6tr2fH5gJcTCN13454NklKVQ9D4dmjw1kcDr2L74RXxf+xqWu3fRFBbKLcBkmJj/HptBF1ebfx5DdknS50jtRtekD1bCOD0huZoodUJ2E9n7/X50zxgNc1ScSLVMoYDPfz5Krn7lV6Lk6jOfOZ19HxAnbfPg8Xjw+XyOE9tBEuxLrERR/BXgVwCeVKx+QRTFHxUE4Z+ADxKdDPwE8I39XkuhUAQCgcCJ3ITPckLtrFtikmfQWZi7HaZqdNzQarWsr68f6Lm52fmMvXqJlm/9K2Lnb/HQJvC5b/wpL773BxHFGt4a2ECfUsrk/HVcS0ays/XyTSwzM3PXm9RpmglGIhHW19dZWVmRJ7JKSkrkCJnDQNJeTU1NEQwGqaioYK9Fj81m4+HDh+Tn53P16lX5M0vWC2+//TYVFRWUl5fLVcy+vj70ej1VVVWIosjw8DDFxcXk5ubK4/yFhYUXMSn5AAAgAElEQVTMzs5SUFCAWq1mZWWFy5cvY7Va0ev18gVfql5JCQuiKKLX63E4HJjNZsbHx7l06RImk4m5uTnMZjMGgwGLxUJNTQ0dHR3cuXNHnipsaWnBYrFw79492traZHLX1taGzWbj7t27NDc3x+X1FRcXU1hYyPz8PLdv3yY/P5/KyspdbwqZmZnU19dTV1eHzWbDarUyPDxMYWEhJSUluxp+Li8v76vXTGbxIMXhLCwsMDIygkqlkitakhfYQbCxsXGgidM6TTFdGTXc8T2mPNVEvSaR6IS3Iqy85Wb9rg9lmoKSH9ahv/BUL6bQaDB8/OPYvvAFNG+9hfEnf5JHu2iNvP5VJha+T4npEobs3RMXVCoV92fg+uMI1YVpvH4lhxSVWf77XiJ7p9NJamoq09PTSV3sT9LJ/sTIjVIJf/3XUXL1sz8b1Vz95E+ezr4PgJPet9vtDm9ubv6v1QrcA78MfEUQhN8BBoEv7reBUqn0SiXs48ZZt8Tg7EIspVbkWRKrs0BmZiYzMzP7Pk8URbLDadz84FXa/uEa2TPf4nLV66iUX+Br//AlWl/7LTwhDV11LzA0+T+payrEkH1u39fNzs5mY2MjYXrqOBEMBmW9lBQhU1BQQGNjIxaLBZVKdShSFYlEWFxcxGq1kpGRQVVV1a4ZdhDV2oyNjSGKIu3t7Qnn7urqKoFAAEEQyM3NRRAEuTKVm5srj+tbrVYEQcBsNsvGoZcuXUIURaxWK5cvX8btdqPRaFCr1bhcLgoLC3G73XEVK3haJZV0VnV1dXKVoqqqSo7Nqa6u5vbt2xiNRnJycujo6JCtF6Qq2sLCArdv30av18tDBYWFhaytrdHb28u5c+coLi5+SgQUCsrKyigpKWF2dpabN29SVFRERUXFruefIAiyUD0UCrG0tJQQCB277fLyMs3NzQf+TSVoNBrZCgKix47dbmdtbS3B4sFgMOx63LhcLkpKkleDduKd2c3MBW38i/MuBWo9elVUiiGKIhtjmyx+x8W2N4KhLZ38d2SjSk9sV6qys/mWUomrp4ePp6aSdv58wnNEUWR46p9QKtQ0VPzwru8nHBH55n0XA9N+WivSeX+7LkFftZfI/ubNm3R0dADIZqp+v18+ziUn+1g3/J1u9kedBN/a2trzXHwmqFTw5S9Hndl/6qei5OpjH4vb91EGaY4DJ71vl8u1Bfwva7eAKIrXgGtP/n8a6DjM9oIgOB0OB3l5eYfZ7H8LpKSknFmfWnICP2wL6Lj27fGc6jEbt++dDujhcBiPxxNnrBkMBklNS2W1vQG/SU/u0nVcVR/kcnklt27e5JX/kMGiM0ShsZGhSQGb6/GBiJVer8fpdB47sfL5fLJeKhwOk5eXR1VVVUKETEFBARaLRfZK2gvBYJCZmRkWFxfJy8ujvb1914oJRL/HyclJVlZWqK+vlwOKJUQiEcbHx/F4PFy5coWtrS36+/u5ePGinL1nNpuBaLVraWmJrq4uBEHAYrFQWlqKRqNhcXGR3NxcUlJS5Dag9B1kZGRgs9lITU2NCzqXhPu5ublMTExQV1cnj+rX1tZSVlbG5OQktbW1tLa2cu/ePa5cuUJ6ejptbW309fXR2dkpExG3243VauXKlSvy5zOZTOj1esbGxlhaWqK5uTlOjK5QKGRx/szMDDdu3KC0tBSz2bxnRUOtVlNWVkZZWRk+n4/5+Xlu3LhBdnY2paWlZGZmEgqFjmXxmZKSQkFBgRwTEwqFcDqdrK+vMzU1RTgcRqfTydOQ0udzuVw0NjYeaB8qQcnrOVee6K1u8SnjOwg7RBb/zYVncou0fDXmjxjIKNn7xvn//e3fotNo+BGnk4LhYcQrV+ICm5ftD1hzPqSp8oOkpSRvUwa3I/zjLQeWpS2eb8g8klHo9va2fJNPSUnZtS0YDodlouX3+9nY2JBjmGKd7JNVvWKd7GMRCATk4/9EkJoK//zP8Oqr8IlPRMnVBz4ARMnNWXQdpH2f5H3TZrMFgf9tKlaHRjgcnlteXqauru5EXv8sW2JS1egsiNVZVo3S09NlT6TThCiKsjHh+Pg4Xq8Xn8+HQqGQjTXz8/Oprq6WfxP/xgMevXieC995G66GeVfNFf6vf/srHIvjbIjlqJQadNoSbM7H1Ja9uu97yMnJYXx8fO8g6AN+FqfTKVsipKamkp+fT2tr657kJysrC5/Pt+eYtsfjYXp6GqfTidls5urVq3ueH6IosrKywuPHjykpKeHq1asJN4HNzU36+/sxGo1cunRJnvaqr6/n+vXr1NbWyqTK5/PJ03pKpZKNjQ3sdjvd3d2Iosjk5CQdHR3yfru7uwkEAnIkz9bWVoKFQUZGBl6vF6PRiEKhIBgMUlhYSE9PD9XV1ZjNZnp6ejCbzaSnp3Pu3DmGh4dpa2sjKyuL5uZm7t27R1dXF3a7HYfDQXd3N4ODg9TV1ckLP7VazYULF1hdXeXOnTtUV1cnkFilUkllZSVlZWVYrVZ6enpk4rRfyygjI4Pa2lpqamrkQOi1tTW0Wq1MLI8TarU6weLB6XRit9uZnZ0lGAzKxE7STR6EmOhVWn5If4l/XLtF73cmyerTIigFCl/JJrc9A0G592sEg0FGRkb47Gc/S/jqVdTXruH42tfI+dCHEBQKtsNBRqa+SlZGIeWFzyd9Dd9WmL+7bmfREeL9F3W0Vx3+uztMx0OpVKLVancdlpKc7KWqVyAQkEX20mJQpVLFkS6XyyWbUJ/YPUyjiWYJvvvd0Ricr38dXn2Vra2t/7O0ZTGYmZkJAcsntoMkOFUG4vF4ppaXT+7zSW7cZ0mszgJnWTWSbnIniVAoFGes6fF45FW9UqlEqVRSW1u7r8lla0Ylb7x4gdZ/uE7m+iDv6Pox/qznq3gWJ4kUlOMJhDHqa5lc+D7b4U1Uyr3H5Q/jJ7UTu0XIVFdXH/j4lXQ/8/PzVFRUyI+LoojNZmNqagqAiooKzp8/v+979Hg8jI6OkpqaSmdnZ1K7AJvNxujoKI2NjXFVrFAoJEfYLCwsUFhYiFqtpq+vjwsXLpCWlibrrKT3srKygk6nQ6PRyE7nKpUKm80mX+STXXS1Wq1M5o1GIzabjaKiIoxGIysrKxQWFlJdXc2jR4+4cOECxcXFrK2tMT8/T0lJCTk5OdTW1tLT0yN/VrVaTVdXF/fv3ycQCMjEEKKTgXq9ntHRUdnGYed7UqlUVFVVYTabmZ6epqenh4qKCkpKSvad1hMEQW7PXb9+ncLCwoRA6JMQ9yqVSnJzc8nNzQWixGJ6eppAIHBoi4fiBSPv/9cuVBsqhDqR2vflo848mBZpbGyMUChEa2srrtxc8q5eZfPGDTYyM8l+73uxzH+PwJaDtprPJg1Ld3q3+Ztrdjb823ykO4e64t0XI3tBGoo4DsQ62e8GqX0tVb2CwSBWq1UW2UuvsbPVqNFo5CrukaDVwre/DS+/HK1Y/du/saXTnanG6sRaoMDCwoLI/+HEamZhYWELOJFfUCI3Z1HSPMtg3rOqGsHTaczj0JeJoojP50sw1lSpVPJEVHFxsZyFCDA9PY1SqUzq57QTOSot4Xe+RFj1Z+SsXCNQ/kv0/ep/ZSk7i28CLn8Yo66Wifk3sG9MkZfTsOfrSbEzB5migugFRGrxBQIBjEYjJSUlNDc3H/m7Kykpobe3l/LyciKRCAsLC8zMzJCdnU1DQ8OB3lcoFMJisWC322lsbEza2hRFkYmJCWw2G11dXXE3jGAwyN27d6msrKSwsBC73U5vby+pqalUVFTIF02r1SpbA0jVqpaWFiAapixVg2Lbq7sRK4k0Go1GZmdnKSoqoqysjNHRUXmKb3p6Wg4ybmpq4tatW+Tk5JCeno7b7UahUKBQKOTKUmpqKl1dXQwODuLz+aivr5d/l5SUFFpbW1leXub27dvU1NQkbduo1WpqamooLy9namqKnp4eKisr43Rau8HpdJKeni5PFcYGQmu1WkpLSzEajSem41QoFGxublJdXY3JZJItHtbX13n8+DFer5eMjAyZaGVlZRH2iix+x8XG2CbphlSGfnASa8EKxZr3oOdg1jcDAwMAtLa2srKyQt0LL+Db3sZ35w5bWQomxTcpNrWTq0uM7Vp2BPnSdTvhiMgnXsylzHj0W4vH4zlVux7JYigrK4tIJCIPT0jYKbL3er2sra0RCATinOyTEa99RfbZ2fC978GLL8IP/ADqP/xDNEm0baeBk5bQOBwOAXCe2A6S4LRLO8szMzN+TphYnQXOsmp0lq1AeFopPMzJEQwGE4w1Yy0NJF+o/doR2dnZLCwsJHWJTobz+c3MtddQMPYG2+d/kfSXXiG153uEys7j8oYpLq1AIaiwuR7tS6zgacUkGYGRvK9iI2Ty8/Opr68/EBE8CFJTU9FoNAwODrKxsUFhYSGdnZ0H+i2ksOTJyUnKy8vjiEQsgsEgAwMDZGVl0dXVFVeBCQaD9Pb2Ul1dLU+ySSP/i4uL8vMCgQBzc3NcvXoVALvdjkajISMjA1EUWVtbo7q6GohqfKQKXDJiJYnXAXQ6HQ8ePEAURTIzM4lEInIbrb6+nocPH8oVqfPnz9Pf3y+7eL/wwgtYrVYGBwdpbW1FEASUSiVtbW2Mj49z//59eWJQQkFBAQaDgeHhYbl6tZvtQl1dHRUVFUxOTnL9+nWqqqooLCzc9XiWnOclxAZCu1wu5ubmGBsb2zMQ+llht9upra0F4i0eKioq5IWP3W5nenqaDacb/e0KhIiCrC41xS8ZyFNm8OdrK/yT4zY/YXz5QP5WS0tL6PV6KioqWFxcRK1Wk/3udxP2uBle+w5CrkBj+WsJ202tbPKVGw7SUhR88qVcTNnPVtXbzXD3NJAsxuegTvaxInu3251UZJ9M66XOyUF48014/nnqf/EXUbW3Q3v7aX1kGSftHRYKhULiseUFHQxnQaxOLNjuLInVWVeNziovEKIVBI/Hk/TkiEQiccaa0omfkpIiX7TLysrIzMw8Ugs3OzubsbGxAz+/TlNMz8ttlP/Ol1BvLOEKlvDKH/83zr20wruafxWlMoecrArWnI8P9Homk4nh4WFZZxWJROQImfX1ddLT0w8VIXMYbGxsMDU1hdfrRalU8txzzx14FFwKS87MzJTDkpPB6XTy4MEDamtrEywAtra26O3tpba2Nm4gZXl5Ga/Xy0svvcTIyAhra2uEQiHq6+vl9zcxMUFDQ4P8XiSjYEmbIt1kwuFwwnEh+UtJNw6pHZ2ZmYnZbGZmZoaGhgZycnJQKpXYbDaMRqPs/ZSamsrFi9Gcu8rKSh4+fMjIyIgcxyMIAvX19czOzsoZg7E3vZSUFC5evMjS0hK3bt2irq5uV3uE1NRUGhoa2NzcZGJigsnJSZmExhKsra0tNjY2uHDhQsJrCIKAXq9Hr9fHBUIHg0HZ5f04pqo2Nzfl0PdkkBz/tVotZWVliKLIo4erhLe3cRescOvOOGq1mva8Im5qZnjDNcQr+r39rQB+7dd+jV/+5V/G5/PJFSNBoWDr+So2Hl+nZEKLUGyHiqcWEMMzfr5+10lupoqPv5BLVvqzWyB4PJ6EIY3TwlEsayRt40FE9hL5Siay1/7e71H/0z+N8M53sv53f4eqs/NpcPYpGD+fZMUqEAggiuKpVx1OnVjFrmKPG2lpabjdp5q1KOMsq0Y7bzSnjdjcvJ3GmlIlISsrC4PBQHl5uSxMPg5IN+OD+kmpBCXqV38AfudL6G3X8C18EvO5czy++y1skx+HCzkY9bWMz/wrW0EPqSl7r2DT09MJBALMz8+ztraG2+0mJyeH/Px86urqjt3zRhJ5T09Po1KpqKyspKWlhdu3b8uamL0QDAZlsX9jY+OufkWSDcLi4iLt7e0J2pNAIMC9e/cSJgbdbjePHz/m8uXLpKSk0NbWxujoKKurqxQWFiKKIi6XS85NhPg24G75i7HvSxAE0tPT8fl8ZGZmYjKZWFtbIzMzk4KCAjkfUKlUUl9fz/3799HpdAQCAbq7u3nw4AHr6+uytqiuro4HDx7InlcSysrK0Gg09Pb20tbWlvDdFhYWxlWvmpqadtVCpaWl0dTURCAQwGKxyATLZDIhCAJTU1NUVFTse14cRyD0blhdXT3UxLYgCORdzWL+a07K02tovhANZbfb7SwH3PSKFkSLC7M2X/bS2o0ApqSksLy8LBOEcDjI6MzXydTkUxjQY//ylzF+6lOo8/O5Ne7he0NuzKYUPnrVgCbleK55+x17Jwmfz3diNkT7iexdLhdjf/zHtPzCL2D88Iexfu5zTD45ViFRZB/773HomU/SC3B5eRm1Wr1yIi++B06bWLldLteJGT1pNBpWVk79OwTOvmqUkZEh32hOGpKlgUSgJHO9paUlOR+vsrISrVZ7KuaZOp0Ol8uVtFyeDDWt78BZnEva9Buszf0IH3j9o/zcL3yWR48sBJeMGHU1jAPrGxaKjMlX3LERMpJ26ty5c4eKkDkMpLiZ+fl5cnJyaG5ujrtYVlVVMTExQWtra9LtRVFkdnYWq9VKVVXVnmL2UCgkZ/tdvnw54TcMBALcvXuXpqamuO9cahm2trbKN9BQKITNZuO5555jdnaWnp4eBEGQq1VSG1BqP0mO65CYXyaZg0qVE+l4NxqNjIyMUFlZKcfLLC8vYzKZmJ+fJxAIkJOTQ2dnJ4Ig0NraSm9vr1ypEwRBzhXc2Y4zmUykpaXR399PQ0NDQkVDqn4tLS1x8+ZN6uvr9yQnGo2G5uZmfD4fFouFiYkJKioqWF1dlb+Dg+K4AqElrKysyL/LQaFr1LDy/Q1stzxkVaeRmppKYWEhH47k8rnVb7FSLtIWMeBwOJicnCQcDqPX62Wd1uzsLJ/+9Kf5/d//fdnnDMAy/wb+LTvd5/8zuuo8bF/4ArYvfYmh7h+jd2abhpI0XuvKQb3PxOFBIS3OzmLwCZCnXE8bku9cWl0dqt5eeNe7qPz0p6n8ylfgh34ISBTZSya0xyGyP+k4m+XlZURRnD+xHeyCUz2KRFEUCwoKTox9nHXVCM7OJFRqxx0nsRJFkc3NzThPKK/XK4u2s7OzycvLo7y8nIGBAS5fvnxs+z4McnJycDgcByZWphQdY+/sovorbyK8tMW7Wl4FPkvvg9u4vuXE8KkfR6VMw+Z8LBMrURTlQNi1tTVUKhX5+fk0NzezubnJ7OzsiUy2+P1+pqensdlslJSUyHExO2E0Gnn8+HHSMX2Hw8Ho6CgGg2FfuwW3283AwIBsjLkTPp+P+/fvc/78+TiReyQSkSNqYrU/kh2FVquloaGBtbU1hoaGGBkZoaSkRA5glsib0+mUReE79VWSSahCoZAnMiG6qNjc3JT/ptPpGBkZYXJyErPZzIsvvsidO3eIRCIolUo0Gg01NTU8ePCAixcvIggCCoWCtrY2OfomVpielZVFZ2enPDEoOZ1LEASBoqIiDAYDDx48YHl5mYaGhj0n+TIyMmhpacHr9XLv3j3ZcuOgx/BOPGsg9Pb2NoFA4NAVG4VKILdTy/IbbvxLQdILo4Q6TZHCS5lNfGujD1fONvX59UC8xcPMzAzf/OY3+f73v4/D4UChUERJZ2Cdifk3KDZeJFcX1d3pfvRj/NO3Jpic2aajIpVX2nNQHDBY+SA4y2oVRNuQsZO9pwm5DVlYCD09UZ+rD3wAvvhF+OQn40T2ySCJ7KV2o8fjSRDZp6SkJNV6iaJ4qLDyw2JpaQm/3z91YjvYBadOzwVB8JzUQXzWVSNJVLuX99BJQWrHHRXb29txlgZut5tQKIRGo5HF5AUFBWRkZCRtNYTD4TMjlTk5OYyOjh5qm9RXfxD1X32TjKW7pPreS23TRYb6/p1gXSabD0bI1VWz5noku57b7XbZG2tnjIlGo+HBgwfH1oqVbrJTU1NsbW3JwvK9XlsQBGpqahgfH5f1Q7Fhya2trfuec3Nzc1it1qRtL4jefCT7hJ2ajvHxcXJycmQzSogSOq/XS1NTk/zYwsICLS0t6HQ65ufnGRoaIjU1lampKUwmE06nk/r66E04VmsFyEHMEF1I2O3RXNXt7W1ZwC9prVJTU+UgaIDi4mKmp6epqopOlknu6nNzc/Lgg1KpjIu+ia0gpKWl0dXVxcDAAD6fj9ra2oRjPS0tjY6ODhYWFrh582aCJUUyqFQquYpmsViwWCzU1tYemaQfNRB6dXVV9rc6LAwXM1i97sF2y0vZh56S7baMSu76LHxvY4hzaQWoBGWcxUNNTQ1/8Ad/IJuYzs7Ocu36NYIpvYCAOe/dUc3dtshXxlVYtRVcst2j3e9AaP0xUByfBcVBY3xOCsnE66eFQCDw9HzPyYE334TXXoMf/3FwOODnfm7P7WNF9smwm8je7/dLAcn09PQkbTVKwdlHva8sLi5uOxyO6b2eIwjC/wDeB6yJotj45LHfAH4SsD152q+Kovjtg+731ImVSqVaWV5erpEucMeJs64aSRWzsyJWB2mDSgLenZYGkmVBVlYWRUVF1NbWHkoQK1UQzmKqRvreD/O7l777Q4TSfhrN0vfYmHiR//SZX6HX4mWzOILzu98l8Fw+/sg6i8tTFBeeo7GxcVdiIwgCRqORtbW1fTPe9kIkEmFpaQmr1YpGo6GysvJQru4mk0kOU3a5XCwsLMjC8r2+l3A4zMjICOFwmCtXriStaHk8Hvr6+mhtbU24Ac3Pz+Pz+WiPmSiKRCKMjIzQ1tYm71vKZZOib8rLy5mdnaWtrY319XUePnyI2+3m7t27aLVaIpEIwWCQlZUVFAoF29vbLC8vIwgCXq+X5eVlNjY2AOSWXnd3NyqViuXlZWZnZ2VSV1FRQU9PD6WlpXIVrLGxkZs3b2IwGGTSqVar6ejooLe3N4FAqlQq2tvbGRsbY2BggAsXLiSQFCmmRgrJXlpaoqGhYdcq4aNHj6ipqUGn09HR0YHL5eLx4+jgRG1t7TPd7A8TCL24uHjoVqQEZZoCw8UMbHe8FLxjmxR99LMqBQXvzm7hb+3X6fNN0qmtidtuY2OD7373u/zMz/wMer0ehUKBSrvAmHWBQt3LWKeWuOeyMuYuxhtS8Z7zqVwIV+L86iDOr30N/RMD0ePAxsbGmQnXpUrrWWXO+ny++Pa1Vgvf/GY08ubnfz5Krn77t+GI728vkf3c3ByhUAiz2Rwnsne5XCwtLcWJ7NPS0pJqvfbS7M7OzvrY38PqfwJ/BvzNjsf/H1EU//sRPvLpE6tIJDK3vLzMSRArONuqkdSOO2o5/1kgaaxiEQqFEiwNwuEw6enpcb5QB3VY3gtSbt5ZECtBEMjOzsblch14pZ+izWK1ux3tw3/H1hmmra0Fe0YKj1IttCxMU55WyJAf8ovSMebuf8EtKipienr6SMQqGAwyOzvLwsICJpOJixcvHvn4LSgokDPuYsOSd4PX62VgYIDS0lLKysqSHgdut5v+/n7ZuTwWTqeT6elprly5Erft5OQkBQUFcVWyyclJzp07Jz9PMkbNzMwkMzMTnU4nO7j7fD5mZ2cRBAGn0ymveiWvIb1ez/LyMt3d3SiVSkKhEHfu3JEJTF5eHo8ePZKFsUqlknPnzmGxWGSypVKpuHDhAoODg1y5ckUmzmlpabS3t3Pv3j3a29vjPoMgCDQ2NmK1Wunt7aW9vT3pAkSj0XDp0iXm5ubk6pUklpfgcrnw+XxxVT6dTselS5dwOBw8fPgQlUqV0F49CvYKhM7PzycQCDzTPnI7o8TKdsdL0StPb55VqQVUpubztnuU8+lm0hVPW7vf+MY3CAaDfPjDH45aluSIDM98g4LcC7TXvcbjpU3enI3aD72rbpvUzTnuut2YamthbIxQRgbGV145liqxy+Xi3Ln9Y6xOAifhsn/Y/SdUs1NT4StfgZ/+afjd3wW7Hf7sz6KBzscIqVp2EJG95OklETCHw5HUyT6WdE1PT4fZh1iJotgjCIL5OD/XqRMrn883tbS0dGKvf9ZVo7OwXIhEIvj9frn14/F48Pv9cl88KytL9r05KXGmTqdjZWUlqS7nNCD5SR2EWEmtNu+ly+R9/zZq1wIGdwFe2xT/OHWfFp1AtlsBKgGXd56C3P0DcXU6newIf1CXbK/Xy9TUFE6nk7Kysn31T3vB7/czOjoq6332NQgkqj+wWCxJW3sSXC4Xg4ODCQQDou2LoaEhOjo64t63VE2SPKuk5zqdzri2YOw0IESJll6vJzU1ldTUVGw2G5mZmbLeKRAIUFZWJhOAqakpWTelVqtRKBSyLkuhUFBQUMDi4qKsiSouLsZqtcbpaXQ6HQUFBYyPj8cJtzMyMmhtbaWvr49Lly4lXE/Ky8vRaDTcvn2bixcvJr0hCIJAWVkZRqORoaEhpDgvaZJ1bGyMxsbGpGQ2JydHjtwZGRkhLS2NmpqaZ5ZQJAuEvn//PqIoMj8/nxAIfVCkZKvQN2lwDPjJeyFLDlsWBIH3ZLfw/659l+vuMd6rezpcYTAY+OAHP8ilS5d4+/obrGz2oEnV01z1o7w14uH6mIcCvZqPdOeg16qAUkI2G3aLhTDgWV9nvKcHtVoti+H1ev2h378oimeW8wrRhctZ+WeJorh7hI5SCZ//PBgM8Hu/B04n/M3fwDEGJvv9/gNNogqCIFerdoMkspeqXuvr68zPz6cARyUcnxYE4ceAPuDnRVE8sMnoqRMrl8s1NTs7GwROJM76LB3QtVotk5OTJ7qPra2tBEuDSCQi+wBpNBrMZjMajeZUS8s6nY7x8fFT299OGI1G+vv7ZZPJndje3pYjZKTJs9LmaIZ4ZHuCNEcFPutbfOlPfpOP/c7naF1aI7M2nw3vwQZKJEKzuLgYN1W2E6IoyiG4kUjkwHEzuyEcDjMxMcHq6qpsfRAKhbh58yZ5eXlJdRuRSISHDx/i8/l2FcNDVCM1PDxMR0dHwoo6EonQ19dHY2Nj3ClP5JIAACAASURBVN+k2Jqmpqa4SsJOOwHpe4glM7HGoBA91mOrPEqlMi7PTZoMlEihRK4lcl9WVkZfX59MrARBoK6ujvHx8bi2ZWVlJXfu3JH9riRkZ2fT1NQk5wrurEzl5+ej0WhkMf9uler09HS6urqYnZ3l5s2bnD9/no2NDVm7uBcMBgOXL1/GZrMxODiIVqulpqbmWEbzpUDoubk5ebDgxo0b6HQ6SkpKMBgMhzoujVcycT4IYL/vI+/5p0QhT62jNb2Ce74JOrRVGFTRv7366qu8+uqr+Hw+tpT9BINu2ut/nn+4GWBqZYvWinRebdOhVgmI4TDe27dxv/02glqN/rXXKGxu5pwgsLm5KXvHPXz4EIVCQU5ODrm5ueTk5Oy70DnuoZ/DYmNjI6GaeVrYqWNMgCDAf/tvUe3VL/0SbGzAV78Kx1RhO4p/125IJrJ3OBwBwH6El/tz4LcB8cm/fwT8xEE3PovZ0omRkREPcCL9svT09BPPrtsNsY7Qz4pIJBJnaeB2u9nc3CQlJUW2NCgvL5fLqAAWi0WOODhtqNXqvVc/J4y0tDS2t7fjKkabm5usrq7GRciUlZVx4cKF6A3jyerfr7CwPfMCP/OJ1/mLz/0mf21Zokm9RfbFYtZdEwd+DyUlJdy/fz8psQqHw3LcTFZWFnV1dc+knxFFkeXlZSwWS0JYslqtpqGhgQcPHtDR0RF3cwwEAvT395Ofn09DQ8OuN06pUtLR0ZFwPEnkqaCgIEGXsrCwQEZGRpw2LBgMYrPZ4sLXHQ4HOp0ujnxJ8TOx2yWbCpQg6fokYmUymZiZmZGJlUajISUlJU6YbDQamZqawuFwyO9REARaWlriLBgkGAwGqquruXfvHp2dnQnHdnZ2tjwxWFlZmRDSLEGyEpAWAH6/n5deeinpc5NtazKZZB1fX18f2dnZVFdXP3Nl3u12o1arycnJIScnJy4QemRkhIKCAkpKSg7UqtLkq8k8l8r6XS/Gy1oU6qfH1ktZTYwEZnljY4iPGq5isVhk4jM29R22xAUKTD/Kl2+m4d3c4gc7dLRVRvcZWl3F+fWvE1paIq2uDt373ocyhgilpaXJ3l4QrVzY7XbW19exWCxEIhFycnLkqtbOylTssXAW2NjYeOYg96PiwDE+v/iLUXL1H/8jvOtd8K1vwTFMQR+mwn9YhMNhtra2NkVRPHi69hOIoii3ngRB+ALwrcNsfybEanR0NLz/046G2IDW04YUiXEYciH1jndWoSSvnuzsbIxGI5WVlft6guh0urgV+2lDr9fjcrnObPVlMpmYnZ0lEomwurqKQqEgLy+PhoaG5BePJ99TWmQZMSxQmlZGRXUjN+5ew1b9UbJUJhaC9w9kFArRC3xKSkqcF9Pm5iYzMzMsLy9TUFDApUuXnnn6RwpLTktL2zUs2WQysbS0xPz8vFyxWVtbY2xsbM/qCkSDlsfGxpK2wCAavSJV22KxtbXF5OQk3d3dcY9brVbMZnMcidrZBgyFQiiVyrjn7LRb2FmxysjIiDMElvzMYocYysvLmZmZobn5aTu3vr6e4eHhOF2YRqOhtraWwcHBBDJaUFBAMBikv7+f9vb2BE2PRqOhq6uL/v5+fD4fVVVVu56nUnB4UVERt2/fprm5+cC6QEEQyMvLw2Qysby8zL1798jJyaGqqurIx9RO367YQOjt7W1WVlYOFQhtvKJl+q/tOIf9GNqekrFMpYarmfX8u3uYma01PvOZzzAzM8Ode99l0XmNLfEVvvvAjDYN/sM7jBQZUhC3t/HcuIGnpwdFWhr6119Hs8diQIJarZYnIyFarZYsHqxWK6FQCJ1OJ39Ou91+ZsRmZ9LAaeNQA0ef+lSUTH30o/D889GswRh94GEheWCdVGdlfn4etVp9JA8rQRAKRFGUtFk/DBxq7PzUiZUoio7i4uITy+2J9bc5C0jtiWTViFhLA+m/YDBIWlqa3BbIy8tDq9UeSZCZnZ3NxMTBKyzHjZycHOx2+6kSq9gImZWVFSKRCHV1dVy6dGn/qUaNBkwmSgN+JtXbzDxc50c+/AF+93d+i2uqX+IDvuj2Lu88eTn1B3o/FRUVWK1WKioq5BBgs9l8qLiZ3SCFJTscDjmyZS80NDTIwcMLCws4HA4uX768p5ZkbW2N8fHxXQnb+vo6CwsLXL58OeGCODY2Rk1NTdyNd3t7m6WlJZ577jn5MVEU5cBnCbFkNPbzxi5QYu0WIHquLS8/1aVKi5HYUGyj0cjY2FjcyjgrK0veNtavqqCggLW1NWZnZxOqjmVlZQSDQYaGhmhpaUn47NI04cjICENDQzQ3Nyc9h6emptDpdDQ0NOD1ehkaGpIrRQc9PgRBkIOmFxcX6e3txWg0UlVVdahJXqmyE6t7i4VKpaK4uJji4mI5XWC/QGhtRSpp+Wpst7zktKQjxHhNXdbW0Oeb5KvT1/j+97/Pz/3cf+bO2F8x73o/6/5GKvNT+eBlPRmpSoJLSzi//nW2V1fRNDWR/corKI/YflKpVBiNRrm6GolEcLlc2O12hoeHsdlsiKKI0WjEYDCQkZFxajKKQCBwJnpgCR6PJ2mY+K547TX4t3+Lmod2d0etGY7ov5VUNH+MsFgshMPhkf2eJwjCl4EXgFxBEBaAXwdeEAThAtFW4AzwU4fZ95nYzEYiEbfX6807iS9VqVSeqaeSFOuiVqvjjDV9Ph8KhUK2NCgoKKCmpuZYMr4kSGHIZ/XZDQYD8/Mnb3IbCoVkf6nYCJna2lpu3LhBUVHRwYlpSQnZy3bcz/vImNTwodc/wB/8we/Ta/fy6ooONLDhnTsQsZJaodKYcFVVlWwt8CyIDUuuqKjYNSx5J9RqNfX19Vy/fh2z2UxXV9ee262srGCxWHYNcfb7/YyMjNDZ2ZlAAmw2G6FQKG7CDWB2dpaSkpK459vtdnJycuJ+I0m4vhOx73dnK1DKCIyFyWSKC8XeTftWW1tLb28v+fn5ce9DIqMGgyFhJV9VVcXY2BgPHz5M6lCuUCg4f/48U1NT8sRgLMlcX19nZWVFNtLVarVcuXKFqakpbt68SXNz865DBMkgCALFxcUUFhaysLDA7du3k/qs7Yb5+XlKSkoOdCxpNBqqq6upqqraMxBaEARM3VrmvurEbdkku/YpaVALKt6R1cx//ZvfJRwOc64lmweLrxAI5fN8QyYvNmYihLfZePMtvLduocjIIOejH0UT00I+DkgaLMl2or+/n3PnzmG322XtoVarlStaWVlZJ3Y93djYONRvftw4kkXOO94Bb70F731vlFx973uwCznfb98nSawePXq0vbq62rff80RR/GiSh7/4LPs+E2KlVqstk5OTVckCR48DGo3m1CwXpBFwiUStr68TCoXQ6/VyFaqoqOjUVkFSdt1Z6Kw0Gg1bW1snklno9/vlqlQoFCIvL4/KysqE2A6panZgT5rSUoTHjzHVZBGeFhAzM5ldWOXzb7i4v76KocqIax8B+/b2NvPz87L7ujS2fRy+OC6Xi9HRUbKysvYMS04Gu93O2NgYpaWl+4aTLy0tMTU1RWdnZ9J9bG9v09fXR3Nzc8J5FQ6H5dZh7G8RDoeZm5uLmw6EaBtw5yrZ5XLFPZYs6mJnxUqpVCKKYtxCwmg0xoViA5SWlnLv3r04O4m0tDTy8/OZmZmJa2nutGDYSSDr6+sZHBxkYmIiqWWMIAicO3eO9PR0OcBZOiclUhp7bkjPz8vLY2hoCKPRSHV19aHOH4VCQWlpKcXFxbK9Q1FRERUVFbtKEiKRCLOzs1y5cuXA+5He736B0LoGDctvurHd8sYRK4AmTRmT3+rDUFbEEh9BEVbzA60pXKzJYmtuDte//Avb6+ukt7SQ/Z73oDjha7g0sKDT6dDpdFRWViKKIl6vF7vdzuTkJG63G41GIxOtndrAZ8FZGpNKbcgjTUN2dMCNG1G91XPPwbe/DV1dh3qJkx4aePDggTscDj8+sR3sgTMhVh6Pp99isbx6UsRKagceJ7ESRRGfzxfnTO73+1GpVHGWBpWVlQwPD3Pp0qVj2/dhoNPpcDgcZ0KsIKqzcjgcz9wOjI2QWV1dlXUTFy5c2POzSdWJA5OakhJ4802q6vJ49J01ph/aaHpPKY2qSYZDJl5KOYfLm7y9GggEmJ6eZm1tjeLiYjl4OBwO09PTQ2Vl5ZGF/LFhyefPnz+Ux5AoikxNTbGyskJnZ6fsSj4zM0N5eXnC8yVRfWdnZ9JKhyiKDA0NUVZWlrT9+PjxY0pLSxPOt4WFhYTxfal1e/78+bjn7vTySXbBl6rRsUhNTY3TqKSnp8vxNhIpknLMdvqcnTt3jhs3blBSUhL3uaXF0Pj4eFy7EqLE4sKFC9y/f5/Z2VnZtX0nCgsL0Wg03L17l/PnzzM+Pk5TU9Ou16TMzMyE6tVhb7gKhQKz2UxJSQmzs7PyZzObzQnH4dLSEiaT6Zkq5nsFQhsaivHeDuObD5JR8nQfDoeDidsjXH7/z6DSbNOSsUKLuQPXd76Dr7cXZVYWho9/nLQT8jncCZvNlnBOSJFdmZmZmM1mRFGUx/fn5uYYHh5GrVaTm5srWzwctc3vcDj2nCI+STyz23t9Pdy8Ce98Z7SK9bWvwbvffeDNvV5vQoX7ODE6OroNWE5sB3vgTIiV0+kcHhsb8wMncvfPzMzE4/EcuWIQDAbjCJRkaZCRkUFWVhY6nY6ysrJdLQ22trbOtB23tLR05n5SRyFW4XBYbpc4HI5dI2T2gsFgYGRk5OBVs9JS8HpJxQcmkcyZdG4vjPCbv/ajmJ/7JFX570SrvkNw20+KKnq4OhwOpqenCQQClJeXU1dXF7cvpVJJcXExs7OzhxbFiqLIzMwMMzMzVFdXH9qKIRQKMTg4iEaj4fLly/L7On/+PHfu3EGj0cSZmErBzskm3iRMTEyQmpqalES43W7sdnuCYD0SiWC1WhPyI9fX18nJyUmYVNzpnpyMWO2sWMHTdmDsDULKjow9/81mMzMzM3HESqVSUV5ezsTEhByjI6GiooK7d++yurqa4LMj5QrevXuXlJSUXW8Oer2ejo4Orl+/TkFBwb7nhEKhoKqqSq5e5eXlUVVVdejqiFKppKKigtLSUmZmZrhx4wZlZWWUlZXJVb7p6ek4y4lnxc5A6LnpeSKqLCa/u4D5dQPZ2dn4tyJ8e3ibn/7Da6TnOwm3jFI4q8f2539O2OEgo72drHe+E8UpCbmlxdt+rThBEEhPT6e0tFQeBNnc3MRut7O0tMTY2BhKpVKePDyIxYO0f0ljexY4ljak2RwlV+95D7z//fC3fwuvv36gTU+6FfjEL3PtxHawB84myhsmhoaGfJwQsdJqtSwuLu77vEgkgtfrjSNRkqWBVIUym81kZmYeqvJwmq3IndDpdDx8+PDU9ytBGmc/KILBoGyJIMWdFBUVJfggHRSCIJCbm4vNZjuQ8RxSoO7cHMaaUsSbcCcygnfTz8ztf2bq5R+hPi8dl3uOUCATq9Uq30RiI0F2wmw2c/PmTcxm84FXs1LrLjc390hmoRsbGwwODlJdXZ3QaovNwUtJSSEnJ0eeVrx06dKu+1pdXWV9fZ3Ozs6Ev0m2C8nI39LSEkajMaEikoz0JxOu70asdmaBSsMisaRF0lnFEiuDwcDo6GjCeHdpaSk9PT2y4acEqTJ1584ddDpdwnuR4m2kXMFkpEkiMKWlpbjdbiYnJ6msrNyXKGdlZdHd3c3ExAS3bt2iubn5SK7oKpWKc+fOUVZWhtVqlT+nZNlyUten7OxsmlqymV9w4hjwYxmbwLm5yZCzFG8QLtQ+5vm2dv5ua5SHoQkKRJHcH/9xUpNUU08SktXAURbAaWlpFBUVyZOtwWAQh8MhWzyIooher9/V4gHO1hgUoufdsbQh8/Lg7bejxOojH4kaif7U3lpvqYV/3JIRCVtbW2xvb/tEUTyxQbm9cFbEavLRo0cn9uJSxUqC1EuOzceTRK9arZasrCxyc3OpqKjYM3fooJDiVc6CWEmBlSfpD7IXpH0Gg8Fd2wxer1du8UUiEfLy8qipqSEzM/NYqnxFRUVYrdaDEauSkui/c3NkN9Vgu+FDMavixdfey9/8yRfwejZYy+hgYPgaxbndtLa2HqjNqlarKS4uZmZmZt+q1ebmpjy5dpCw5J0QRZHZ2Vnm5uZ2dQGHaHaclIOXl5eH2+2mo6NjV+Ln8XgYHx+Pq3zFQqoA7bw4S63Ine3wSCSC0+mMsz6AqHB9Z4txt1bgTq2YVqvFZrPFPWYwGLBY4jsAUobf/Px8nKZKoVDIpqGtra1x26Slpcmaqp36MXj6fd69e5eWlpaE72FycpLt7W0uXLiAKIo8ePAgqXlqMigUCmpqasjPz2doaIiCgoK4OKDDQK1WU11dTXl5OZOTk4yOjlJbW3siWshYGFoycNz3kx1QczcQ4d+/8Zc4pv+ZT3/qNTT/005jYzrD5w282PUyqelHC4B+Fuwk38+ClJSUBIsHh8MRZ/EQS7Q0Gg12u/1M4s8kbGxsUCJd/54VOl1UxP766/Cf/lM0X/C//Jdd8wVPehpyamoKtVp98BX+MePkzqo9IIqi3+12h0+CTIbDYTnsdWRkhFu3bnHt2jUGBwex2WykpqbKOWrPP/88bW1tcvn9uNzKpdy8s4Jer8fpPLD7/rHDZDKxtva0AiuKIg6Hg7GxMa5du8bY2BhqtZq2tjauXr1KdXX1sU7e6PV6OV5mX0gVq/l50otTUGoEyhbyyHlXDduRCEtv/Q+c/ka0vkWK5+cRx8bYsloJezzsd/yWl5czNzfH9vZ20r9HIhEmJibo7e2lqKiIzs7OQ5Oq7e1tBgcHcTqdXLlyZd/tNRoNRqMRq9VKXV3drqQqFArR399Pa2trUoIcCASYnZ2lpqYm4W+rq6vodLqEFofUIt75Ox+mYrVTY5XMXiU23iYWJSUlzM3NJfxuJpOJzc3NpOdsXl4eGRkZWK3WhL9B9Pu8ePEiAwMDcVmdk5OTOBwOmpubEQQBhULBhQsX0Gg03Lt372DHJtFrSXd3N9vb29y6dStuwXhYqNVqsrOzKS4uJhgM0tPTw8LCwr7H8WGxGdzAutTDoP3PCaXbWRuI8NW//kfe+NJvk5+ZT+dqKkt6JYGsXBDgOxtDx/4eDoJkbd7jgkqlwmQyUVdXx5UrV7h69SrFxcX4/X6GhoZ4++23mZqaYnNzE6/Xeyaf/zhdzwFIT4evfx1+5EfgV381aiq6y+c66WqdxWJhc3PzwYntYB+cVcUKpVJps9vt+UcVOUvGmrGWBl6vV7Y0kHre1dXVp54BpdPpTsV2YDdIGhOT6fRXgRCN+rBYLCiVyrgImfz8fGpqak7cmf2g8TJAtIytUsHcHCggpUTAaM0m7WoeLRcv8K/f/EsKXvhx7FlK/H19iDE3RCEtDVVuLqrcXNRP/lUZjaj0egSVCpVKRVlZGVNTUwkEZG1tjYcPH1JYWHigsORk8Hg8DAwMYDabdxVR78Tjx4/Z3Nyku7ubgYEBWltbk1acpHig3VpQIyMj1NfXJ/yWoigyOTlJS0tLwjZLS0uyRiX2+ckMEre2thLI1k6DUNg9wmpnvA0gt/gdDkdcpUAQBOrr6xkbG0tqSVFfX8/NmzfJzc1N+n1otVpaWlq4f/8+nZ2dzM3NsbGxkWAmKggC1dXVLCwscOfOHdrb2w+0apeqai6Xi4GBAYqLi+PigQ6KSCQi22mkpaVRUVHB5OQkU1NTVFVVUVBQcOTFTWDLydL6EEvrg9g3phARUWcUkl3t5wt/+Fdc7/0LLn/oHVz6rY/xd5kSURdRomDbF+T69esUFhZSUlJyatPc29vbp9ZVUCqVcrUKor/FW2+9hUqlYmxsDL/fT2ZmphzFc1zV+92wtbVFSkrK8e9DrYYvfSnq0v5HfxRtC37+89FrbAxO2mbi4cOHmzabbeDEdrAPzoxYCYIwbrFYmg5CrLa3t+NMNd1ut3xSSFqogoICMjIy5AvZ+Pg4SqXyTII1NRoNfr//TAXsu62wTxKbm5usrKywvLzM+vo66enp8REyp4i94mXioFQiFhcT/Pa3WbLb0XpTyVpQ8UNTK/xQXQmKbCObX/8c2aop8goqETaDiD4fEZ8P0e9HDAQQAwEIBiESIRyJEBFFBIUCQaGgVBAIBoOEU1JQCALi9ja+rCzm/uIvdnU2PwgWFxeZmJhI2oJKBlEUefToEX6/n7a2NgRBoL29XbZQiBV1j4+Pk52dvatx4PLyMkqlMilxt9vtaDSapNmCLpeLnZPAuwlYDypel46rnW0tk8mE1WpN0HOZzWasVmtCC0bSUa2trSVUMZRKJS0tLQwODtLd3Z2UBOt0OtkzzGAw0NbWtmubrbi4GI1GQ29vb1Jiuxt0Oh3d3d08fvyY27dvc+HChQNFzUiwWq0UFBTIJDYtLY3GxkYCgQAWi4XJyUmqq6vJy8s70Pnq27SzsD7AlGOUtZCDTXU64XQDIcNzeASBEGFu/tFf8nbvF3nPez/CK//lnRjWQhjTqwg4N+luaEenzEAhKAiVRQOhBwYG5LbtUQOhD4K1tbUzW3hCtOKr1Wo5d+4c586dQxRFPB4Pdrsdi8WCx+MhPT1dJmPZ2dnH2rZNViU+NigU8Cd/Eg1v/s3fjJKrv/97iFk8bWxsnOiA1YMHD7yc0UQgHIFYCYKQBvQAqU+2/6ooir8uCMJLwH8nGq7cD3xKFMXkPRDA6XT2jY+Pf+jy5cvyGSyKIn6/P64K5ff7USqVMoEqKiqirq5uX/2Q1I6LnYA6LUhTJH6//1AXvuNCamoq29vbJ57bJ10MJL2UQqEgPz+fpqYmpqenMZlMZ5bBJcXL7Myfi8XW1hYzMzPozGbyrl2jfHhY/pvptoqwWkClSmVTvIuoBEHzEIU6FVQqlCpVdBWmUkFKCqJGIwsyxUiESCRCJBwmsr2NoNEQVCgQFQrUq6tkbGxwsa0tmh5/SEieUVtbW3sGKMdCFEUePnwoa7ikm6ZWq6Wjo4N79+5RU1MjO3l7PB46OjqSvlYoFOLRo0cJ034SLBZLgkUBRG9kyZy6d7vAH7QVCE+922LPNZ1Ox8bGRsLiRq/XMzIykvT16+rquH//PiaTKeF9ZmVlUVpaKkcC7UQkEmFxcZHMzEw2Nzf3be0YDAaZ2NbV1R24JaVUKqmvr8fhcHD//n1KS0spLy/flwgFg8GknmIQXQg2Nzfj9/t5/PixTLBif6+tSIj1bTcL/gVmPNOsBh14FLClTgNDPhC9zmYp0zGqsqhSZaFy63B2lFHvyeM/tnyM3Df+FeOnfoLHq6sYTOXkqJ62gqRA6LKyMnw+H/Pz888UCL0fVlZWzizGBhL1XYIgyPe48vJy+V5ot9uZmZlhY2ODlJQUmWg9i8UDnEI+oiDAb/xGtHL1sz8Lr74K//Iv8KT95/P5TtQSaHR0VATOLIbkKHfdLeAlURS9giCogZuCIHwP+GvgZVEULYIg/BbwCfZwL/X5fPevXbvmefHFF7MkS4NwOEx6ejrZ2dlkZ2dTUlJCenr6kU6o7Ozs/yXacWdBrAA5A+u4NQSRSAS73c7Kygrr6+totVry8/MTImTy8/NZXl4+NnHoUVBeXo7Vak0QS7vdbqanp3G5XJSXl5P7xhvRitMTomT9ByfexS3+6aM9vE93kb/772/z91/4Pd78/p9yoe7VpPsSnvy3E5FwmGWLhdm7dymzWCj84z9G+NCHjkSq/H4//f39FBYW0tTUdKDzQhRFRkdHEUVR1vvEIj09ncuXL9PX18f6+jp2uz0uQ28nxsfH5dzKnXA6nfIiaCcWFxeTemg5nc6klbFkww/JWoHwVGcVe64li7eRHi8tLWV+fl42cpWQnp5Obm4uc3NzSVurZrOZe/fusbKyErdg29raoq+vT/ZZm52dpb+/n4sXL+5ZZdBqtVy+fJn79+/j9/uTfj+7IScnh6tXrzI+Ps6dO3f29XcbHx+nqqpqz4VWeno6LS0teL1eHj9+TP/sGItFIZx48YgxejUhQrpKjUmZQZGmkEJNPkZVFrmqLFIVagKBAH/xhb9EqPggZWVmfvBKO35/Fhnv+QSCXo9tdDTB3iIWGRkZ1NbWPlMg9F6IRCK43e4zM+aEKLFKpk+UIAgCGRkZZGRkyO3zQCCAw+FgcXFRtniIJVqHGVZyOBwJWZ8ngs98JkquPvlJePll+Pa3CWZlnUwb8gme3KO2RVE8M6HzoYnVk/FFSS2qfvJfGNgSRVEqvb0J/Ap728IP9vf3o1QqKSsrO7SlwX6QKkZnBSmf7dimLg4JSWNyHMRqZ4SMwWAgPz+f+vr6XVdNubm5jI2NnVk7FKLfgVSpUalUrK2tMTU1hSAIVFZWxhONmIuSrjEd96MtquyFDKRM03q+lj9dnuXX/+8/5hv/lJxYJYPH42FkZASNRsO52lqU3/0ugt8PH/jAoT/LysoKjx494vz58wdeaUp2CEqlksbGxl1/h5SUFFpaWrh27RoGg2FXMuBwOPB4PLtmy01MTFBdXZ3weDgcxu12J42scblcu95k93NelyARq53H+s54GwnFxcXcunUrqfVBdXW17Fy+83okWTDcvn1bFue73W4GBgbiqk5ms5mtrS2Gh4eTktlYpKSk0NnZyeDgID6fj4YDhAxLkH5Xu93OvXv3ZK1dsqqgZDR7EGi1Wtra2rhjH+fO5hAZgQ0K/U6MqizMWVVUG1rJ1CSXcHg8Ht7//vfT09PDJ369lJ8yBtCE5wio2vHMpeLULRw4cmpnIPTy8vKhAqF3w/r6+rFXwA4Dydn9sOJtjUaTYPFgt9tZW1tDmrKXvLQMBsOuU9mRSIRQKHR6MpmPfQyys6MTg889h+fLXz5RUmuxWFCr1WfWBoQjTgUKgqAUBGGIqPnWm8A9QC0IwsUnT/kgsCejEEVxw+FwGbAd+QAAIABJREFUeIqKitDr9cfeshIEgZSUlH2jPE4KOp0Ol8t1JvuGpxWro8Lv9zM9Pc3t27e5c+cOHo+HyspKXnjhBc6fP4/JZNqzFK1QKGQX+LOCJGIfGhri+vXrrKys0NTURFdXV9J2j4Ss6jQEFdTPlLEUctD+fAOXXvlJ/vWrb3L9+vV99xsKhRgdHWVoaIi6ujpaWlpIWV8n7fFjwpmZ0ZXbARGJRHj48CFWq5Wurq5DkaqhoSHUavW+N+tIJCIL2Y1GIzdv3sTtdic8Z2RkZFeiIOkek5EnSc+yc7vIk5ZpMgF8MuzWCtwteN1oNMZNp0pQq9XodLoEmwbpb6Wlpbt6saWmptLQ0MDAwABWq5XBwUFaW1sTSF11dTVKpZLx8fGkrxMLpVJJW1sbSqWS+/fv7zpFuhsMBgPd3d14PB56e3vjxPzS73bQCmcs2vRVaAQ1qsg2lZ5MitxtVGo7diVVdrudl19+mZs3b/Lap/+UF0rzKHVOYfrkj6Jr0OAaDTA7nbwauB9UKhUlJSV0dXXR1tbG1tYWt27doq+vj7W1tUNN1S0sLPz/zL13eGRpeeb9OxVVKsVSzjm11Mo5dPcASx6ThjVmwYH0GdvArvmMMfYCvsy19mdMmDUY2FkYbLDHpIGZIQwwDGqlbuWcY7VSlXKsXHW+P6pPTaulClJLrb6va66ZKZ0659QJ7/u8z3M/931pAsrwio3NgwZ2kjhtUVER165d84xrOzs7dHV10dzczODgIEtLS0eeiUux0Xn8cbccw/IyYW98I1EPMDf5Q09Pj7i/v//bCztAADhTNCOKohMoFQQhAvgxUAi8C/iSIAhq4FeA39FBqVROTExMJJ3EyTgPSDyryyApyuVyZDKZTz2ni4TibldaoLYFoiiys7ODwWBgbW3No8tSVlZ2ZoJ1UlISS0tLl6LVYjabmZ+fx2AwYLPZeOyxxwJeocmDZIRmB2GalqGokDEnm+d17/oIUz3P8cEPfoChoeETr6koiiwuLjI7O0tmZuaRgMY6O0vY9DRr9fWEORwEB/BMWCwWent7iY6Opra2NuCB2OVy0d/fT0hICLm5uX6/Nzw8TFxcnCc40Ol0R7oNBUFgdnaW+Ph4r3IO3rzzwF0GvL/sBt4HeG/vjLdS4ElmzODOWlut1iP2NhLS09OZmpo6cWzIyMigpaWFtLS0E+9zREQEJpOJxcVFGhoaTlwUCoJAUVERfX19zM7O+uXzCIJAQUEBer3e0zF4GkVuhULB1atX2djYoLOzk4yMDFJTU5mbmyMmJuZMAqMqmYLqkFxuumwcqCepyMz2NAXl5+cf2efq6iqvfe1rmZ6e5k8+/S1is5qov/MsUe99L6qkJCJLLGwPmgk9PFks8zTwZQidmprqMxPkdDrZ3d09cQHwsCDxDc8bSqWS2NhYzzPtdDrZ2dnxWPFInbZOp5OwsLCHX024ds0tJPqa1xD3xBPuQOs+7bjzQFtb2+7u7m7Hue/4FHigNgNRFHeAZuD1oijeEkWxSRTFatzkdr/Esd3d3Zd7e3svTMDjsrNGOp3uUvWkpHKgN0gmqoODgzQ3NzM3N0d4eDj19fXU1dUdU6M+y/G3trZOnAwvCjs7O/T29tLd3U1oaCg3btwgOTmZjY2NU+0nolCDY89F2U4WQ+YF0hPVvPkD/4vp6Rl+/vOfn3jc9vZ2dnd3aWxsPFKScR4eIu/uRnZ4SPB73sPg4KDfFfbGxga3bt0iNzeXvLy8UwVVvb29hIWFBfS9hYUFHA7HkYlf0k6SVr6SdYe3wMlkMmEymU5UH3c6nezv758YQN3v3SfBmzGst4yVWq32qgsVFRV1YtY0IiICq9WKxWI58Ti5ublMTh73bzUYDLS3t5Ofnw9wYkAnQRAEysrKWFtbC5jvmZaWRn5+Prdv3z6WNQwE0dHRnnvX3t7O4uKi1/sWCKq1OcgEGUvBYVhdy9TV1ZGVlcXw8DA9PT2e3z8xMcHq6ipf+tp/EpHzamo3ukn9vXegvssPCslU41I7CN06v0WWZAhdUlLCtWvXiIyMZGxsjNbWVubm5rDZbMe+4y17+jBxnsKkviBxsPLy8qivr+f69eukp6ezv7/P+vo6zc3N9PT0MD8/z97e3sPR0iovp+/JJxGCg+Gxx6Cl5dwP0dHRYQcuTWoBzhBYCYIQczdThSAIGuA1wIQgCLF3P1MDfwl83d++9vf3b7W2tl5Y5HPZQpk6ne6BynEPivj4eAwGw5HPrFYrd+7coauri9bWVtbX10lKSvKIpZ6Vt3ASJI7EaYOa00IURVZWVmhra2Nqaor09HSamppISUlBJpORlZXF7OzsqQaOsLwgBDlkLSRiEe2ExLhIK3wtP/rFM7z97W/3bGe1WhkYGPB0i129evXY9bPp9WjGxxGDgwl75zsJDg5Gr9d7/S1TU1NMTk5SW1t7qgHY6XTS3d2NTqcLaDLd3NxkcXHxRDkMhUJBaWkpGRkZ3L59+5i/372Ynp72qgouiTCe9Lft7W2vHYEnZWu8caykv51UQvNWDgS3nY23+5CQkMD+/r5HkNNsNtPV1cXS0hJ1dXUkJydTVlbGwMCAz9KdTCajqqoKvV6P0Wj0ut3951xeXk5fX5/PhZE3SNkrSatpZWXlzJNmqFxDsSaNzdB4pozuJEBUVBQNDQ2kpaXR2tpKX18f1dXVDPYNs6UqId5soOFNFajvkTrZ3dvFlWTGNO/EfnA8OH5QSIbQNTU1VFVVIYoit27doquri9XVVc9zs7y87OEoXQZsNhtOp/NS/AElegZAfX09N27c8HAip6amaG5uprOzk9nZWXZ2di5kQWy1WnFkZiK0t0Niotu0+YUXzm3/LpeL9fV1uyiKlzfxcrZSYALwr4IgyHEHZt8XRfGngiB8XhCEN9/97GuiKL4cwL76bt26dTpCwSkgEdgvi0AdHR3NzMzMQz+uhNDQUI8XokQ+F0WR+Ph4CgoKzuyTdRokJyczPz9/IeVYu93OnTt3uHPnDtHR0ZSVlZ3YMaTRaAgNDWV9fT3g85AHyQjNCsI8aSeyQstWmAHIglB3N1hfXx9BQUEYjUZyc3N9kpStc3OETk66W441GgoLCz2Ck/eW1mw2m6eEV1dXdyrdGimoiouLC6i7zGw2MzQ0RG1trU+unNVqJTExEYVCQWtrK4WFhUdKuxaLhZ2dHa/E6OXl5RMJ7YBXKQxvGStvpUB4xTPw/sxYdHT0iZkncJeqW1tbTyyX3isaGhMTw+LiIleuXDny/ISGhpKRkcHIyMgxfa57oVAoPD6NSqUyIJ5cWFgYtbW1no7B0/KSpqenSUhIICsri5GREVZWVigpKTnThN4QWsCAeYFx5w6V5k1k8kj2zU5+9XIXf/qh/8affvivKSgwsU0YdkUEv1MZjib7aOlzZmaG5Lo0jHM2dkbMxNRenPluUFDQEUPoxcVFxsfHiYqKuhx+0T24SLX3QHC/P+L9Eg+Hh4dsbm4yNzfH3t4earXaQ4aPiIh4IIkHcDfAREZGQnIytLbCG94Ab3sbfPvbbpL7A2JmZgaFQnF5k+5dnKUrcAg4JqssiuJfAH9xyn3tJiQk2E7iQJwHpJbVs3RgnAcC8c27CEgWMgaDAYvFwsDAAGlpaVRWVj70lVJkZCRDQ0Pn6l14eHjI3NwcGxsbpKam0tjY6Hff2dnZDA0NnSrACy/SsDdloXIvh19rB1ApEljZVtHa2sqNGzcQBIGKigrq6uqoqanhscce87Thu0QRlwucLhHLb1uIODzk8M1vw7rvwOkSScy4SnPnKEVXSxARcFkPWJwd9uhJnQYOh4Ouri6SkpICmoCdTic9PT0UFxf7LPVarVZmZmY81zc5OZnx8XGmp6cpKCggPDzcwx86Kah0OBwcHh6eGDzZ7XYPD/Gk4570vgiC4DXzIr3n90+avriGCoWCqKgojEbjMb07qXNrc3OToKAgGhsbT+RSpaamsra2xsrKildBVTjq01hRUREQ5ykoKIi6ujr6+vowmUzk5+cHtBDa3t5mbW2NhoYGZDIZZWVlGI1GT2n5pIyNKIqYbSL7Zif7ZicHFhd7ZicHZid7JgfqvXJWrJV8fvQQFxaG23/M81//c3TxGRwmXWdBEUuwaKVIpWdbiCD6nut9cHCAxWIhvjKGvYQ1tgdMFxpY3QtJukci8ctkMlpaWkhKSiI5Ofmhj4cGg8GnzMJFw1cZUpIoCQkJ8YwjZrOZzc1NlpaWGB4e9iwMoqKi0Ol0p24629raeoUyEB0NL78Mb30rvPe9bn/Bj370gX5fb28vBwcHzQ+0k3PApSmve05AoZicnJxM8qVr8iCQOBaX5SIeHR3NxsaGz0H3POBwODxZKYmcGR8fT3R0NAaD4UydOOeBU9nL+IAULM7OzmKz2cjMzPQpIXA/QkNDUavVp+I3hOcFsSSH5LkYhGIBdcQ+65uJtFl2+YNPfY2ZoU4Wp4f4l699gyeffJK3ffifKL72TrYMdxi+9QLJ2eUkZpbwttENopRqvuSswPbTe8tByXT9xp2xlgku/t83ezdQ9ga73U5XVxepqakBSXtI3YKS6KIvjI6OkpeX5wlaQ0NDqa6uZmtri5GREY8Aa0FBwYnf91UG9KX8bLFYTv2+3m+8fi8kruFJ1yc9PZ2xsbFXAmKXi9XVVWZmZoiOjqa+vp7h4WGvCz9BECgpKaG9vZ3IyEifgarkK9jT00NNTU1AAokKhYKqqirGxsbo7e2lrKzM5yLUbrczODh4TEMrLi6OyMhIRkZGGJ9fw6RMxWSHfbPLHUiZnThOSAYqRTta+yFamQVrgowQ6zTj3/ohP3n2aSqvlvH0P3+djIIsgqMjEWQyRDGXlZUVbt++TUxMDNnZ2UxOTnqylpGlwaz8YhfLmp2g2IdnEi+Tydjb2/NkgpeXl+nu7kapVJKSkkJ8fPyFLO7vhcvlurRFvoT19XWvciknQaPRkJyc7OmitFqtbG1tHZF4kDJaOp3ObwJha2vrKE0hNBR+9jO3v+DHPuYOrj7zGa/mzf7Q1ta2s7Oz036mL58jLj2w2tvb+21PT89jV65cuZCalE6nY2Fh4dICi5iYGJaXly8ksDKbzRiNRgwGA1arlZiYGNLT04mMjDxi9TE2NnapelIB28ucAEnRen5+Hq1WS05Ozpk7evLy8hgcHDzRCPgkyDUyQjLVmMccpKdFsRq1htKqxCETSK+vIbWxElEu4nLZWNfPEB4bgzxiEcP4SzR//x8Bd138Y3I57dE6zBHt6OIiEEQnguBAEB2EWLbY3i3DRfaZgiqpAyxQ3sjs7CwKhcLvvVhfX8dut5+YPdPpdNTX19Pf348gCHR2dpKVlXVMWX15edlD8r4f29vbXu+jzWY7deeYVqs9xieUEBsby9zc3ImBVVhYGA6Hg93dXdbX11lcXCQ2Npbq6mpPkBQREcHy8rLXFn2VSsXVq1fp6+ujvr7e57MVGhpKaWkpXV1d1NXVBfQ7BUGgsLCQ+fl5T8fgSd8TRZH+/n5yc3NPfJZUKhXl5eX8oGWZ4TkL4WoXETI78Y5Dgq27qPc3CDbtEuwwoXUcEqKRERwbjTI+DkVcLN+Imma8rYtvPfs073rXu/j2t7997DykhVRiYiJLS0u0tbXhdDo9avwRVzWs/HKXrQETia99eCW5vb09VCqVJ0OVkZFBRkYG+/v7LC4uMjU1hU6nIyUl5cj4eZ7Y2NgIeOy5CLhcrmMOBaeFWq0mISHBMy7Y7Xa2trbY3NxkZmYGp9NJZGSkJ9i6NyPodDpxOp3Hg6+gIPj+9+FDH3Jb4GxuwpNPuq1xTon29nY7bueXS8WjEFh1tLW17fz+7//+hfS/SpILlwWdTsfIyMi57EsURfb29jwWMnK53GMh4+1lkclkhIWFee3AehgIxF7mfthsNhYWFlheXiYuLi5gw1pfCA0NJTg4+FRcK1mqHfu0i/L/9J1RFYUUxBVAJvIm5fv44795OyPL/RyO/ILE7u/xt9uH/M5IIWH6CL7f8q+0Db/EGz/wHlRv08COigjt6QZbm81GZ2cn2dnZAZcO19bWMBqN1NXV+dxOss2pqanxOglIbevXr1/3lGbHxsY8q1u5XO4xlj0JOzs7Xhcb3jhWvuBNcgFeGQPuX1yIosj29jaCIHDr1i1ycnJOLCvn5eXR0dFBQkKCT0Hc9fV1ryKp9yIyMpIrV67Q1dVFbW1twCXyjIwMgoODuXXrFpWVx7Obs7OzaDQav4u4K+k6hpe3qDe0kGqYBKUKRWwsquQ4lHF5KOPiUMTFIb8vo9Z0oGXnmpPPfP0jfPqDX/bJAZT8/gwGA8HBwXR0dJCYmEhmZiZh2UHsDJlIeE0YguzhBBl37tw5ZgAO7jHhypUrFBQUsL6+zvz8PENDQxdiCL26unrhlQtf2N7ePncbG6VSeUSqxel0sr29zebmJnq9HpvNRnh4OFFRUSgUCu/+hAoFfPObR82bn376iHCzP7hcLoxGo+OyievwCARWQF9HR8eFEdhlMhlKpfJMg/V5HT8oKAiTyXQmb6T7LWRCQ0OJj4+ntrY2YN5WYmIiKysrl6rdkpaWxsLCgl/15/39febm5tje3iYtLY2mpqZzFY/Ny8ujr6/vRN+6e3F4eMjIyAhyjZzUt2QjRwkuEF0iogtEp/vfSP9/92/SNrGuMHJcKWhnfoUoV/DXXx/GFRwBLpHokHBG5vtJeS6d9DdVYhejcFq2sdujAppkrVYrnZ2d5OXlBUyEPTg4YGxsLCBS/NTUlN9JRa/Xk5KS4rGwKS0txWazsbKyQk9PD3a7neDgYOx2+4nP6eHhodfFgDeOlS8oFAqcTueJmVlBEDylQqmhY3l5GYPBQFhYGFlZWYyNjZGRkXHitVGr1SQlJTE/P3+iHpeEvLw82tvbiYmJ8fuuxcbGYrfb6e7upqamJuAyVFxcHEFBQXR3d1NcXOwp5wYaNANkxqsRBNiKLyB1bRqD5ndRLAcjGEFQCMgUAjLlHoJiH5lCYNuyyce/+Sf8xbv+hrrkAlCnc+e5dZRqNTKl4PmOoBSQKe/+t0LAbDPhNMhIL8kmLSILw/oqHS/dJiYyGfuUioN5K6FZF89xcjqdrK+v+7TREQTBowFlt5+/IbQ0jp+mDHfeuCj9rHshl8uJjo728Kgk8/XNzU2mp6dxOBz09vZ6MlpHGqgEAT7/eTf36q/+CnZ23JmsAOfNu9n4k5V9HzIuPbASRXEnISHBdpGGwZJv32lJwecFqeU70FKY3W73lPj29/c9FjKFhYVncjiPjY1lYmKCK1euXFoaOi4ujvHx8RNJ7KIosr6+7pFEyMrKori4+ELOVavV+iztOBwOpqenWVtbo7Cw8ERtpkDhslhw/cHPcZaXkfpHmTidToaHh3lz7qv5wo/+F2p5ECrTLhZ7EEkJQZ62dV+/22Kx0NnZSUFBQcBZN7vd7uHn+Ftc7O3tsbGxQWNjo9dtnE7niYa+KpWK9PR00tPTaW9vR6PR0NnZ6Zm04uLiCAsL8xDJvf1OURTP9JyrVKoTy4gOhwOVSsXAwABOpxOtVktCQsIRQrq0ePGWUcjKyqKlpYXU1FSvQZ9MJqO8vJzu7u6ADLKTkpKwWq309fVRWVkZ8PMeHh7u6RjMzMwkIiKC0dFR6uvrA7puGpWM5CgVd0zRlLpcBMvUWIMcuFKsREdGg1NAdIi47CLzy3P80T/+LobtVVaWV6jWZmG1h7KzYkYuOhEdIqIP9QQN8cx0S3IrKiLIRFIcW+wykpeefOHcpqWlJRITEwN+pi7CEFqy0TnLc31e2NjYeOjG0zKZDJ1O55mDCwsLcTqdbG5uMjEx4fH4lAKt8PBwhE9+EiIj4cMffkWOwVum6x50d3eLJpOp+eJ/lX9cemAFoFAo+gcGBpIqKyv9b3wGSJ0/lxVYxcbGMjY25jOwOjw89JT4HA4HcXFx5OTkEBYW9sABhlwuJzw8/EJSwYFCWvktLi56zD+dTidLS0ssLCwQHh5OYWHhmRSiT4vc3NxjpR1RFFldXWVyctKTKXvQQdD+y1+i3tnB/ra3cXh4SG9vLykpKaSnp2NzWFHL1MhMSkAgPTESlWWf0dFRvDkRmM1mOjs7KSoqCjjgE0WRvr4+srOz/baZS96C/oLaxcVFjwTDib/7rn6SlJ20Wq2sra0xMzPD/v4+oiiiUChYXV0lLCzsiNF6IHpL3viCISEhHi7Nzs4O29vb7O7uIggC4eHhiKLI9evXT7yvaWlpnhLQSZDL5WRlZTE1NeX1/oA7cJcENMsDUJXOzMzEZrMFdN3vhUajob6+nq6uLkZGRqitrT1VRj47Qc1vh22YlcEoFfuI6ijCHpMzPT1IYWEhsbGxdHV18bsffTMul4vf3nyZuro6DpwW/mn1WWIPd/hw7h8jCDJEp4jLIbqDMYeIaBdZN26ytrpGblYeLvs9f7e7/+2wOtkNXqelpcWj8H8RQYcoiuj1eqqrq8/0/XsNoSXdt7MYQi8vL59YinxYkKzdLsMFBNz3wWQyodVqPe9jZmbmMYmH3d1dgoKCiHrsMRKfegrthz+M8Nhj8OKL4Cc7/+KLL25vbW396iH9JJ94JAIrg8Hwo5deeuk1lZWVF5IX1ul0AXl2XRRCQkIwm81HrDUuwkLGF5KTk1laWrq0wArcrelSQLOwsODJEJx2UnhQqNVqkpOTmZubIycnh729PUZGRggODqa+vv7czkX83vcQBYHNN7yBie5uSkpKiIyMRBRFbHYrQbIgRJs72IkMlZOSnk9fXx9zc3PHnOdNJhNdXV2nMmEGtyJ2aGhoQOT2hYUFIiMjfQZgLpeLhYUF6uvrvW6zurp6RL5ArVaTkpLiIY8PDQ2hVCo9diSSj1lQUBBqtRqbzcbs7CwqlQqlUnlkwnU6nSwvL+N0OrHZbNjtdqxWK4eHhxweHrK+vo5OpyM8PJzU1FTCw8M971xzc7PXwE3iKx0cHHhtIkhJSaG1tdVnGRPc75rRaAzYky4vL4+hoSEmJye9kv1PgiAIOJ1OIiIimJubo7S0NODgJDs+iN8O72NMKyXesIz9IIKE6ESio6MZHBzkN7/5De9///uJj4/nxRdf9PDGQuRB5MjCmQp2cWd7jDRdEYJcQC4X4O5r43K5mB2dpLqhGo3G+7sUTziZ9jRmZ2e5efMmmZmZHlHf88LW1hZarfaBZRUEQfCUuCRD6MHBQVwul19DaKkc5kvr7KJx2fpZOzs7J/ojniTxYDKZ3GT4igqEz32Oos98BntTE/t3O2+9LehaWlqcuH2LLx2PRGDlcDiaX3jhhb1PfvKTFxJYndY377whCAIxMTEYjUZkMhkGg4Ht7W3Cw8OJj48nOzv73DSevCE6OprR0dFL7Q40m804HA7a29vJzc3l2rVrF14G8IbMzExaWlo4ODjg4OCAoqKi8+WgiSKKl1/Gkp2N3mqlvr7+yGrxH//+aa4Y8tiSu+UXdCEKBEGgtLSU27dvExQU5MmeHBwc0NPT4wnMAsXKygq7u7vU1NT43dZsNqPX632WAKV9xsTE+Fz5rqys+MzqHBwcUF5efuRdFEURi8XCxsYGBwcHKJVKbDYbBwcHR4IhySInKCgIjUZDeHg4KpUKrVbr6U7yxqWRjMm9lVDT09PR6/UUFhae+HdBEMjPz2d8fBxf2fV7JRh0Op1fbqUgCBQXF9PT03NiUH0SJOuilJQU0tLSmJub4/bt21RVVQU0liTplGhUAkvB6STOtAGFWIx2tGlBVFdXExMTw+OPP86nP/3pY2T8V0XVMLnxa9q2e0nTHb/PCwsLxMbGBrRAVCqV5Ofnk5mZyczMDC0tLWRlZZGcnHwu49T8/HxA1/M0kAyhU1JSMJvNLC4u0t7eTmhoKCkpKcf4mxK36TJtdAwGg1dZlIeB08jcBAcHExwc7F6IFRfjeuopZHe7fsfGxjzlRal8qFQqMRqN2O12gyiKVm/7FQThW8CbgTVRFIvu+fwjwJ/h9jf+mSiKn3iwX/uIBFaiKC4kJCQ4LpJn5UvL5iJhtVoxGAxsbW15OlNSUlIoLi5+qPV26WE8TUfceUAURQwGA3NzcygUCnJyclhZWbnUtLgoiiwvL2O329nf36epqencBz3L1BRBRiN7164d4005cZF0JZukwxTWXXJUCgGt2v0syOVyj0q3QqFAo9HQ09NDeXn5qRSjd3d3mZqaoqGhIaDfNjw8zJUrV3y+f6IoMjs76zNQs9ls2Gw2r1kfURRPtKwRBAGNRoNGoyEiIsLr87G7u0tGRsaJC6SQkBCvFjXgLsn7ev7j4+M9WSNvAX9sbCyzs7M+5SLAHTAUFxd7JBj8veuCIFBeXk5nZ6eHLO8NkhZZRESEh16QlZXl6b6rrKz0W6KSyQSy4oNYMIjU4vZStKw50KapEQSBzMxMvv3tbzM4OMjgoLs8KD0bCepo4p0Cswo4tO6gVb/Cf7Farej1+mP8O39QqVRcuXKFrKwspqenPdnkhISEM7+bJpMJs9l8oU07gRhCLy8vn3twdxo4nU5MJtOp5VzOE+vr61RUVJz+iz/7GbKZGVTPPOMh/ksSDxsbG0xPT+Nyueju7sZmsx03cT2KbwNfAf5N+kAQhMeAtwDFoihaJWu+B8XlMenug0Kh6BsYGLiw/fszJD5P7O/vMz09TVtbm3TDKS4uJigoiCtXrlwaiVHiOD0MOBwO5ubmuHnzJuvr65SUlFBTU+MxJ74sCYzt7W3a29vZ29vjscceQ61Wn7uf49raGl2zs4iCgGJtDevc3JG/63dX+c1vnmdhYxanPdKTrZKgVCqpqalhZGTEo9R9mqDKarXS399PRUVFQNmL1dVV5HK534DbaDQSERHhM+t7fxnwfvgqtUnn7qsU68svUKPRYDKZvH7Xn2+lTCYjPj6e1dVVr9sAFBYWerThfEGn0xEdHc0fQQ+vAAAgAElEQVT0tF8/esAdVFdVVTE3N+fV31AURUZGRlCr1cf8IBMSEiguLqarq+tE4+n7kZ2g5sAGu+HhCDIHZqObVr6zs8NXvvIV1tfXqampISIigra2tiPXrjHsKg6Fitb1tiP7HBsbIz8//8wLZLVaTVFRETU1NWxsbNDa2uqx4jotfLkCnDdOMoQeHR3l5s2bbG5unqkj/Lxw2fpZDocDh8NxtmrRF74AqanwxBOejySJh8LCQpqammhoaKC3t3dvY2PjZ752JYpiC3D/i/Fh4B+kTJcoiie/eKfEIxNYGY3GH7700kvHrebPCRERER4tm/OG1Eo7OjpKc3Mz4+PjqNVqqqqqaGxsJCcnx2OtsLNzYZ7TfhEZGcn+/j52u93/xmeEyWRiZGSE1tZWXC4XDQ0NFBcXH5lMc3JyHrqHomSWPD4+TnFxMUVFRSiVSoqKihgdHT0Xw1FRFJmcnGRmZobqV70KsrNRbW2x8/zzuGw2z3aTxgW++eQ/0rfYicWsQRdyPDtiNpsRRRG5XH6q+yWViAoKCgJSeLbb7UxMTPgs3Um/TTJb9oWVlRWf2RZfiuvgP7Dy5RcoLVa8veP3UgK8IS0tzWfWC/AQ7r0Jkt6L3Nxc1tfXAw7elUol1dXVjI2NHTOQl4IqURS9dvhGRkZSU1PD8PAwKysrPo+VHe+e6AzJV5GzjeVuYDU4OMhHPvIRxsfHEQSBtLQ0qqurmZqaYnh4GIfDwdXwK2gddgYdG577sbW1hdVq9RlYB4qgoCCKi4uprKzEYDDQ1tbG2tpawOO3zWZjc3PzUhqWJEPo2tpaEhMTCQ8P5/bt23R1dWEwGC7E3NgXDAbDudyTs2Jra8uvy8OJ6O2FmzfdNjc+AnWFQsHt27ctnI1flQs0CYLQKQjCTUEQqs6wj2N4ZAIru93e/Pzzz5/sSXEOkEhy3mwvTot7tU5u3rzJ4uIiUVFRNDU1UV1dTWpq6rEJIj4+PqDB+KIgCIKHxH7e2Nraoru7m76+PiIjI7l+/bpX7phOp8NsNnN4eHju53E/XC4Xc3NzdHR0EBsbS11d3ZHOQ6n1/kEDPavVyu3bt3G5XNTV1bnlBMrLUW9u4tzeZv/lVzzJVw7dK3+VXIX5ECJDjg4a29vbDAwMUFtbS11dHcPDwwFPzJJpcKBE1YmJCTIzM/0S9jc2NggODvZZYpLI5L628VdCCyRj5XR67+/XaDQeMvxJ8Je5Dg4ORi6Xs7e353UbgPz8fCYnJ/1OkpIEw/DwcMABslqtprq6moGBAc94dW9QdfXqVZ/ZB6kJY2FhgZmZGa/BSFiwnLhwBXeCElC41rEYbIii6Gn0uZeTExwcTF1dHSEhIbS1tbG9vU2FMoFDpZqB7X6PlIi/czstgoODKS0tpby8nKWlJdrb231mHSXMzc2RkZFxqbwmcAc1JSUlXL9+nby8PDY2Nrh58ybDw8MPJWsvWYFdZtPSmfWzvvQlCAmBD3zA52YGgwGbzWb0xa/yAQUQCdTi9jr+vnAOD80jE1iJoqifn5+3OxwXphX6wOVAs9nssZXo6Ojw8D1u3LhBaWmpX7+p2NhYjEbjhWTNAsV5BlYul4ulpSVaW1uZm5sjKyuLxsZGkpKS/KoyZ2VlMTt7sVpuUinBarXS1NREYmLiiQNtdna2RzPsLNja2qKjo4PMzEwKCgpeOUZ5OcLKCtrcXA5u3cK2vAzAyoH7GVQpgsDpJq7fu6/BwUGqq6vRarVoNBpPWdBbeUiCXq/HarX6zSpJ2N7eZm9vLyC+2/T09LHS0/3wZ0QMF5uxAjfPypsCO7jfQX/XUSKx+4JGoyEuLs7vduAODrKzsxkcHAz43Q8ODqaiooKenh5MJhODg4MAAQcuSqWS2tpa9vf3GRoa8nrNshOCWDKrgF2cVnAcuJiYmCA4OPhYR6MgCGRkZFBVVcX4+DjRW1EonXY6DsaZmpoiOTn5gexSfEGr1VJeXk5JSQkLCwt0dHR4LXdKXXuBdGReJO630QkPD6eoqIjr168TExPD1NQUN2/eZGZmxmcW9UEgNUldpn7W5ubm6TNWS0vwve+5gyo/NIjm5mbRYrG8cMbTWwKeFd3oAlzA2cUL7+KRCawAFApFT39//4Xt/7SBlSiK7O7uMjk5SUtLC/39/bhcLoqLi7l+/ToFBQWn8pVSKBRotVq/q+GLxL32MmeFzWZjenqamzdvsru7S0VFBZWVladaFcXHx7O9ve0zu3BWmM1menp6mJ2dpbKykoKCAp+cD5lMRnFx8akmPniFzC3ZvxzLEpWVARAWFYUsJITtn/wEl8OBweSeEFRyFXIXRN4tBW5sbDA0NHTMoFej0VBbW8vk5CTLd4Oz+7G1tYVer6e0tDSg59HlcjE8PExJSYnf7be3t1EoFH41xvwFVi6XC5fL5fNePAjHCvwHVuHh4ezt7fm8z3FxcWxsbOBvkZednc3CwkJAmajk5GRkMtmpFjVhYWFcvXqV5uZmVCrVqUzHwX2tSktL0Wg0dHV1nXie2QlqXCLsRbvvrcVoZ3x8nPz8fK+TsVarpb6+nlBNOHE7ZtYUcuZ29A+FoB0aGkplZSVFRUXMzMxw+/btY/SKhYUFjyvAZUKv15/oUStx+aqqqqirq0Mul9Pd3c3t27c9UiLnheXl5YB9RC8CFovFU4I/Fb7yFXC53GVAP/jZz362vbW19YsznuJPgFcBCIKQC6gA/ylRP3ikAiuj0fjsRfKstFotFovF54DpcrlYW1tjaGiI5uZmpqen0Wq11NXVUV9fT1ZW1gOtypKSkrxOjg8LgfBITsLBwQGDg4N0dHQgl8tpamqisLDwTMRMQRDIyckJmNgbCJxOJ1NTU3R2dpKSkkJNTU3A9yoiIgKdThdwFs1ut9PT08Ph4SENDQ0nX4O7gZVsdJSIxx/HYTSy3HkTs8UdTKoUahQu0IUqWFtbY3R0lNra2hPb1NVqNbW1tej1+mPnaDabGRwcpLKyMuABbHZ2lri4uIA6haampvxmq6xWK06n0+ezsLu765eE/6ClQH+BlWRv42thIQiCxwbKF5RKJenp6QGXka9evcrs7GzAJXC73c7U1BRJSUlsbW2dacIVBIHc3FxSUlK4devWsYVMWowapVxgOd7NRTKtWJiYmPDbmr9vWmXHeRu73P1b9sNtD5U7FBYWRnV1Nfn5+UxMTNDZ2cne3h4Oh4PFxcUzGb6fJ5xOJxsbG34bQlQqFRkZGZ6xdHd3l5aWFgYHB9na2nqg6obkaHHRNja+cCb9rIMD+MY34B3vgIwMv5u3trY6gW5/2wmC8AxwC8gTBGFJEIT3A98CMgVBGAH+E/gD8RxKSo9UYGW325tfeOGFC03nSC3X98Jms7G0tER3dzc3b970qLRfv36dyspKkpOTz01nKi4u7tLLgbGxsQGtyOGVl/P27dsMDg4SFxfH9evXyczMfGBpjISEBHZ2dnx2cgUKo9FIa2srgiBw7dq1M4nh5eXlsbKy4jebt7u7S3t7O4mJib5lM6KjITkZ+vvR5OejKSpCPz1AfFE6X/rGn1OSXIFSBMveOhMTE9TW1vrsnJHKOzs7OwwPDyOKIk6nk56eHq5evRpwgHt4eMjKyorfYAnc5QzJsd4XzqMMCO6Fja9Mg7+MlVar9Ru4nDQG3I/U1NSAFh9paWkYjcaAMq9KpZKSkhL6+vr8BiEmk4mOjg4yMjIoKSkhLS2Nnp6eMwcvSUlJFBYWHsvwKOQC6XEq5hURCBximt9ldHSUL3zhC8f2IYouVjeHaBt6khcH/pHfyA4wRiSQbguhVJVHW1vbQ2/OiYiIoLa2lpycHE/TTFxc3IXJ9gSKlZUV4uPjT1WCkwyhb9y4QUJCAvPz89y8eZOpqakzZfYfBRudMxHnn37a7RP4538e0P7tdvtqIPwqURR/TxTFBFEUlaIoJoui+E1RFG2iKL5HFMUiURTLRVF82d9+AsEjoWMlQRRF/UXrWcXHx6PX6wkLC8NgMGAwGHA6ncTFxZGbm3suFjK+8CjYy8hkMpKSklhaWvK6srvXbiY0NJSCgoJTtfwHAmk1PTU1dWZVYsksWaFQUFNT80Cq9XK5nNLSUgYGBmhoaDhxgtfr9SwsLFBRURFQ1x1lZXC3vB3+xjey2fIdlEEq8jKj0S6FoJXD7OxMwKbaEhl6cnKSzs5OFAoFycnJp7K4GRoaoqioKKABNxBuFbgnEn8WLtvb2w9cLvLHsVKr1R77Dm+IiYmhv7/fJxdNo9GgVqv9BoMymYy8vDwmJiYou5uh9IXIyEji4uKYnJz0mhXa3NxkaGiI0tJST0CbkpKCzWajv7+f8vLyM41RUVFRVFVV0dPTQ35+vmfCy0kIYnrFCrJ9LIZXlLAl2B1m9IYO5lZuYrJsYAlLZjatFqcgcHU9kidK/guCIJAUl8jAwAAxMTHk5uY+1Aldp9NRVVVFc3MzW1tb9PX1kZeXd2GcL39YWFjwKSLrC+dlCO3ND/VhweFwYDabT6ef5XTCl78MdXVQW+t387v8qp8+wGleCB6pjBWAXC7v7unpOff9St0Rq6urLC0tMTQ0hFwup7y8nGvXrpGXl3ei5P5F4FEqB96fObNY3KWAlpYWzGYzNTU1pxanPA3i4uLY398/dYegw+FgfHyc3t5esrOzqaioOBcroLCwMJKSkpiYmDh2vL6+PjY3N2loaAgsqAIoL4eJCTg8RB4Swm5+MocT8/zyx13smLaR2ZyUllefysNLUgBXqVSsr6+fyih6aWmJ4ODggMikh4eHmEwmv/u3WCyIouj3+u/t7fnkaTkcDr+8GH+lQEEQPFYv3qDRaLDZbH5La4GQ2MG9WDOZTAF3eeXk5HgEDu/HwsICY2Nj1NbWHssSZmVlodFoPN2BZ0FISAj19fXMzs4yd1dfLTveXXo1hSrpGOvjL//yL9nf32ffZGRw5nu8ePtTjMz9CLUqHFfOWxiLySBcEUbFQhRvym30jJmhoaE0NDQgk8loa2t76FzSubk5srOzaWhoIDk5mb6+PgYGBs4lI34abG9ve5wBHhSSIXRDQwMlJSUcHh7S2tpKf38/GxsbXp8Dl8vF9vb22WQOzglnKkM+/zzMzQWUrQJ44YUXth6AX3VheOQCq9XV1e88++yz3kkSp4DT6cRgMDAwMEBzc7PHCy0pKYnc3FzS09MvxJfPHyQS/WWWA9VqNaGhoZ42/r29Pfr7++ns7ESj0XDt2jXy8/Mv3AJIEATy8vIC9nKUVNNbW1sJCgqisbHx3AePzMxM9vb2MBrddjMHBwe0t7cTFRVFWVnZ6bKpZWUgijA0BMC6xsna4CRP/stPWHMYyTHKeeaFLZY2bX52dBTr6+uYTCZqa2vp7e31ywcCd8l7ZmbGq+XL/ZiZmSEnJ8fvYiOQMqDdbkcul/vMYvjjV4H/UiC4gwd/gXp0dLRfCYuYmBi2trb8ktMFQeDKlSuMjY353O7e7SUJBttdfTOn08nAwACbm5vU19d7HZcKCgpwOBwPxE1UqVTU1tayvb3NyMgIuhA5kVo5G+Eh3Jpt54tf/AID00/zm56/Rb/aTmJ0KRUl/4PppGIGXFtUBGdSuRhFSVr+sfKzTCYjNzfXk/mdmpp6KNwri8XC6uqqR4A4NjaWxsZG4uPj6enpYWho6EIaZU5CoLZEp4VkCH3jxg2P2HNzczMTExPHnndpwXXZNjqn1hH74hchPR3e+la/m4qiSHNzsxO4faYTvEA8coGVy+X61bPPPnvmN8BisaDX6+ns7KS1tZXNzU1SUlK4ceMG5eXlJCYmkpiYeKl6UjKZjKioqIemBO8NGRkZjI2N0dHRwdjYGMnJyVy7do20tLSH2lETGxuLw+E4Joh4P/b29ujo6GBjY4P6+noyMjIupNwgTXxjY2PMz8/T09NDaWmpZ9A+FaTyUH8/JpeVXZeZqDA3X+8rP/8IFnGbsikX3//pOh0TBwEF21L5s7KyksjISOrr61lcXGR4eNjnJDY6Okpubm5AfEGLxcLOzk5AXLXz4lcFElj5KwWCfwI7uIMmf7ILku5bINnlyMhIlEql331K0Gg0pKRH8KvOz9Az9l2a214gIiKC8vJyn++e5EO4s7PDwsJCQMc6CVK2XqFQ0N3dTXqsnDmFgvmNaRLiojiwrZCf9mZeW/M5QtJfw3cPhzDYd3giso7inVg0qiCfZaawsDAaGxsRRdHjdHCRmJycPFZ+FASB+Ph4mpqaiI6Opquri5GREb+l4geB1Wrl4ODgQmkekiF0WVkZTU1NaLVaBgcHaWtrQ6/XY7fbWVpautRuQFEU2dnZOZ2dUFcXtLXBf//vPgVBJfT19SGTyfpEUbw4jaYz4pELrERR3LdYLHcC7VoTRZH9/X2mpqZobW2lp6cHu93uIQEWFhYSFRV1ZEKMjo6+9KDmYdrL3A+Hw8H8/DyDg4OYTCZycnKora29VKNQacV/UmBht9sZHh5maGiIwsJCSkpK/E7ADwqlUklISAgTExPU1dWdvRSakgI6HfT3Y7C7ib3lpXH890++kY65Sd771VextDXB9UVou73Lv7dsYbJ6L1E5HA5PoCdlE1UqFdXV1QQHB9PW1naiHtf6+jo2m81vACQhUDsQs9mMIAh+M5v+hEGBEz0E74e/UiAERmCXDJn9QSKxBxLwXrlyhfHx8YAz0dpQOQ5xl6WNDvaFXzG/9Qzzqy3Y7L5LVzKZjIqKCpaXlwPKVHqDlC1WhW6wt/s9tpVy5jdmyInO5nXVnyMn9fU0m2f5980WwhXBfDj29aTaIlhcXPSr1C+dZ15eHsXFxfT39zM9PX0hWfr9/X329/e9ZkekLs9r164RERHBrVu3GBsb82QLzxMLCwukp6c/tHFUMoSur6+noqICq9VKW1ubZEp8aVWR7e1tIiIiTncdvvhFCAuD970voM1/9KMfHS4vLz99xlO8UDxygRXA7u7ud37yk594fepdLhcbGxuMjIxw8+ZNxsfHCQpyu7I3NjaSnZ3tkwMjmduelwr7WSDZy1zEy+0NZrOZ0dFRWltbcTgc1NfXU1xcfKnZOwlhYWFo7zqYSxBFEb1eT1tbG+Hh4TQ0NPjNepwHpI4snU7nMYU9MwTBQ2BfXnFnPnaTqnnsnfX83f9+C/tOE62TX0Yth9caBFbvWPjai+vo14+vqkVRpK+vj8zMzGNBiiS6KnWdzc/PewZVp9PJ6OhowOKSNpuN9fX1gIKwQLJVEHjGyh/X7LwyVoHY24C7ZK7Vav1mUwEPdy2QBZPVamV25g4AP/huGJ//u3V++bLIrdHf8otbn6Rn/Fusb08giif/Vsmse2Zm5syLRIttl86xbzC//gtk8kRsLjt3tufJDs1i12Hmm+sv0XEwQbU2hw/GvJZQl5qBgQG/WbX7ER4eTlNTEw6Hg/b2dr/35rQYGxvzavFzL6QM5LVr19BqtbS3tzMxMXFuFl9Op5OVlZVLI4xLhtBpaWkkJydjMBhobm5mdHT0oc91/jxDj0Gvhx/+ED70IQiQv/rDH/7QJIriL894ihcK+Wc/+9nLPodj+Ou//uuVzc3NP/jgBz/oaemw2+0YjUampqaYmprC4XAQFxdHQUEBKSkphIeHn4r7IpHZT0P8PU8IgoDD4eDg4OBC3dfBvXoYHR3lzp07xMfHc/XqVaKjo5HL5YSEhDA+Pk5iYuKlC+pFREQwODhISkoKu7u79PT0eLrgdDrdQ1kFGo1GBgYGuHr1KklJSeh0Ou7cuYPT6Tx71mpkBNdzz7H9hrdRklvGkGURY0gUVdkVNNSpyL2hQ2tbwagPpVSMYDVcoH32EJlMICVa5fndU1NTKBQKn91sQUFBpKSksLKywuzsLDqdjrm5OXQ6XcASFDMzM0RHRwf0XI6OjpKXl+f33ZuamiI3N9fnPTQajQQHB/tcFB0eHmI2m32+t3K5nLm5uRPFGe+F1WrFarX6va8qlQq9Xh8QX+TeZ/ikMrUoiqysrDAwMEBqWjLGnW6e+ucWRrp/Q/uvX+a3v1xgZauY4MQS9MZOVtd/jdN1SHBQFErFUd6VXC4nLi6O/v5+v+bY92N5vZe2wW8yY0xmae93Me6nopWZGPr1D3hT2RN0Na1xKNp4h66OxtACBBG6urrIyck5U5lLEARiYmIIDQ1lYGDAI+HxoO/0+vo6u7u7AbsNSOcSERFBWloaBwcHDA0NYbfbH1ihXK/Xo9VqL1U3CvAI/yYlJZGamorT6WRmZob5+XlcLhdarfZCx3pRFBkdHeXKlSuBX8/PfQ5u34b/+A+/SusAi4uLfO1rX5ve29t78gFP90LwSMktSBBFcTEhIWHfaDTGmEwmyQuI2NhYMjMzT59iPAHx8fG0t7eTl5d3Tmd9eqSkpNDZ2UlGACJop4XL5WJ1dZX5+XnUajWZmZknBieCIJCens78/PylXgtwBwVxcXG0traiUqkoLS0NvPvuASGKIhMTE+zs7FBfX+8pNQqCQFlZGR0dHYSGhp46CBZFkTtXr5LqdFL6xBMIn/wkiX/6fr5vGaBV3KSs/g+JvtPH6GE/H/3zT1Oe1Mj/9/tf5U5NJC8N7rFgtPL2ukj2t9fY2tqiNoAWZLlcTlFREVtbW3R2duJwOHj1q18d0Pk6HA5WVla4du2a321NJhNyudzvhG42m93eiX7eWYvF4ndSCqQUqFQqAxLTjImJYXZ21q+lT1RUFCMjI9hsNr8ZNZVKRUpKCnNzc+Tm5h75m9lsZmhoCJVKRUNDAwgOBhegrOFNvDXjTUSro3hu5Pvsjw9j2f4T1lVXefHXL1JYKic28gUy4lwUpFwlMaYEuczNkwsKCqKqqoquri6qqqr8trbb7Ae0j7zA8KKWLdMHcYkK7KvdvOftjxFllFH0nh/grAzijmWe96S9Dp3C/f6NjY0RHR39wGa+kZGRNDY2MjExQUdHB6WlpWeWRHC5XIyNjVFVdTbfXJlMRkZGBqmpqSwsLNDa2kpKSgoZGRmnDjxcLhd6vZ76+voznct5YXd3l6CgIM/4JRlCJyYmYrFYWF5e5tatW2g0GlJTU4mNjT13nurOzg5hYWGBX8O9PXjqKXjnOyEAey2A559/3r63t/edBzjNC8W5B1aCIAQBLYD67v5/KIriZwRBeDXwedzlxwPgD0VR9CpZLAjCT5966qmPvvvd76akpORM6t6+oFQqCQ4O9tsCfpFQq9UEBQUFpEgdKOx2O3q9nsXFRWJiYigvL/d77VJSUmhpaSErK+vShPVcLhfz8/MYDAYcDgdVVVUPTYPGYrHQ19eHTqejtrb2WACgUCioqKigq6vLY7AcCCRDW2tREalDQwh/9VfwqU8R+dWv8oHPfoZfv72MDvM0Ccm5XIss5vfeO8f/+fpLvOtLb+Sr/8/TPP67xfxidI+v/txIQYie19+oONWCQiJU63Q62traKCoq8ttBubCwQGpqakCD4nmWAcFdgjwP8jq4329/gVB4eDi7u7uIoujzukr6QYuLi2RlZfk9dkZGBi0tLaSlpaFWq3G5XMzOzrK8vMyVK1c8atyiqEBARuPr30n9VDj2cBM33vJ6gubVKOYUDMiH+bsvfAClKoi8qjdQcu2d5BYriQr5FTkJSsqzrxAdnuzx0evp6fGq5SaKIr0z47SObrJtvoZMcJEbJ/Liv36W7/zr/8U+/qe8O+kTaPOjsJQvUL2ZisG6SGRBAYuLi5jNZgoLC/3+9kAgl8spLCz0GLenpaWdiZc0NzdHfHz8A88NcrmcrKws0tLSmJ+f99y70zTxrK6uEhMTcyrZlIvAnTt3vC4UgoKCyMrKIisri93dXRYXF92ej9HRpKamntscdGobnW99yx1cffzjAX/lO9/5zs7BwcGzZzi9h4KL4FhZgVeJolgClAKvFwShFvga8N9EUSwF/gP4G187WV1d/U53d/dGZmbmuQdVEh4FPanU1FTu3LnzwPs5PDxkeHiY9vZ2BEGgsbGRoqKigK6dXC4nOTn5XM7jLJDMku12O01NTZSUlDA6OvpQjr25ucmtW7fIzs4mPz/f6+Cu1Wq5evUqXV1dASvWj4yMYLfb3f59hYVujZaWFkhORv7BD/H6pj/gg7dt7NgP+LF6nQ9++p/5yl+9iw3LMv/1n95Iz1d+wHtrQ3E4bMxZ0pErTqf+v7CwgE6no7S0lMrKSqanp+nt7fXadu50OllcXPRbQpOwuroaUHksEOI6nJ/cAgRGYBcEweMd6A9SYBUIGVgul5Obm8vExARGo5GWlhZEUaSpqemIxYkgyFAptTidFvZs+6h1SuwZK2T/WTSyOpEiRT7/9kfP8abytzE/8Gv+/e/fzZf+9LX099tomyrkn3/h4Mnnb/Pznn6sooyioqJjnoAOp0jv7A5ffG6S53vCObAlUJcrUhc9y9+8/wbf/bdv8tZ3/A5vTfwIlhArGW8P5o3Fb6CmqhpRFOno6GBhYYGysrJzL8XrdDqampo4PDzk1q1bp9KbMpvNLC0tnaoE6A8KhYKcnBwaGxux2+20tLSg1+v9Pm+SZ+jD8Er0hUBtdOC4IfTk5OS5GEJLTh2BnAMADgc8+SQ0NUGAgqr7+/vo9XqTKIoLZz7RC8a5B1Z3XaIldqLy7j/i3X+k1FA44K+dpa+rq8sZyCR2VjxK9jJn8QETRZGNjQ06OzsZGBggOjqa69evk5WVdWoLHkkM8WH6fUlmyXNzc1RWVpKfn49CoSA2NhZBEAJuXT8LRFFkenqa8fFxamtrAxoIoqOjycjI8GstIqmbAxQXFx+dkJqa4NYt+MEPwG4n5Yk/5C9+78tcHVrlJ45REj7yxzz3iT8jLjaEH7c+y/oPZmhMsbB16KJ7JnARVbPZjF6v95R3tVotNTU1JCcn09XVxdjY2DHS7uLiIomJiQFlLQ8PD1EoFAF1ZwaasQrEcSGQUiAERmCHwGQXwF3iCwsLC2AKBGEAACAASURBVKiTENzXe2lpCb1eT01NDbm5uSdmP1TKEH70fz/He558DQqnnIKCAiYXRrn6umTKP5HGf/noDT79h//Ayx8d4B/+67+Qk55PecEOhYo2tgf/g9889zNe7lPylV/s8XTrJiuuGH5xc5DdQxsto/v803NLPNd1iNVupSpTzyfemsbsrZ/whte+CrvFxMe+8Wk+UfUlNEFqSt6fSkaiO6iWsnTSNTxPY+B7IZWt8/Ly6OrqYmFhIaDxeHR0lIKCggvhCimVSvLy8mhoaMBkMtHS0uIzqF5fXyc0NPRSNBHvhcFgIC4u7lSlPckQurq6+lwMoTc3N4mMjAz8HH78Y1hYCFgQFOCXv/yl6HK5fnKqE3vIuJC6jyAIcqAXyAa+KopipyAIHwB+LgiCGdgDfJJFRFF0JSUltXZ0dDwRCN/jLFAoFISGhp5eb+McIZPJSExMZGlpKeBMgcvl8tjNaLVa8vLyHrhbTqlUkpCQwJ07dy7cwNTpdDI7O8vKysqR0si9KCoqorOzE51Od+7lSckaRKvVUl9ff6qBKCUlBZPJxPDw8PGgCXdQNTAwgEql8t6pJAjwxBPwlrfAU0+h+Nu/5S1v+Bi1b3kNz3z8DSje18QzkVE49oJQHuhYeXaCmAIdvx0WKEkPRqPyf74jIyMUFBQcuXaCIBAXF0dMTAx37tyhra2NpKQkMjMzkclkLCwsBMwRCbQMKIpiQDIKgSLQjFVISEhAnXySvU0gtj3p6enMzc35JM7v7e0xOTmJ3W6nqKgIo9Hoc8JVKbWoglRY7WZkNjf3c21tjYWFBTIyMogvDSO+NAyzwY7u9jt43dDjCEMCm7F79PZ+k45f/xrFv/095dU1XLn2O+xeeQKZIpye592dgqHqeYoSpnlN+auJDC0GoCIxgde++RqVf/c+3vBSHcEOFbnvj0MT+cpiTCqP19XVYbFYuHXrVuA2TmdAVFQUjY2NjI2NMfs//yfpBgOKujqoqoIrV47oGhmNRlwu15n8QE8DlUpFQUEBmZmZzMzMcPPmTXJyckhMTPS816IoMjk56dfO6WFgfn7+gc5DMoTOyMhgf3+fxcVFpqam0Ol0pKSkBNRscOoy4Be/CFlZ8PjjAX/lmWee2VpbW3sm8IM8fFyI3IIois67Jb9koFoQhCLgfwBvFEUxGXga+KK//aysrHz7e9/73oUqyz0K5UBv9jL3w2q1elK2h4eHVFVVUVFRcW4SBFlZWczPz1/Y6hTcq6rW1lZkMhnXrl3zminSaDSkpaUxOTl5rsff2dmho6ODlJSUgP3y7kdubi6iKDI1NXXkc5fLRV9fHxqNJqD2b5RK+JM/gZkZ+MxniHvpFh971V9S96mvcrM+nOXKYBSan/LZ732Kv/3om1hu/S0vdxv9np/BYPAEUSdBJpORnp7OtWvXkMvltLa2ejhmgXJEAi0DHhwcBOQV5nQ6A7oXcrn8XDNWGo0Gu90eUHk3MjKSw8PDEwUm9/b26O3tZXh4mIyMDOrr60lLS0MURZ9ZLpUyBGWQEovdguxuArGwsJA7d+4cKVFq4pVkvzWWq3+RSOLrw4hxhPMvtU/znT/7Ga97/ROMTYzy7X/4JC/981spjmsmIbSFgtj/w+tL1vmd2nfxlS//G+9773sZe+673Mrdp+5/f5jH2+oJPQgm690xaOJfCarsdjtdXV0UFhYSFhZGbGwsZWVl9PT0nGjDc15QKBQUFxeT2taG4pvfhA98AEpK3F1iTU3w8Y/j+O53mfv1rym++v9Td97hkZ3l2f+dGc2od2lXvddVWZVd7Upb3MA2CY4Bx6Z84EAgQEJCGoQSHEoK+YA4NBMTTLG/GEKJiYmDAZst6r333rs0Go2mz5z3+2N2ZqVVm5Fmdu37uubSaMo578yc857nfZ77ue8in43jVvj7+1NQUMD58+dZX1+nurqahYUFhBAsLy8TEhJyxzwJndBqtS7esDdwFENoWZZZW1tzv9O+ocHRCfgXfwFuZh7tdjv19fV2oMXNj3JH4FOmshBiQ5Kka8CbgNNCiKYbT/0Y+JUbm7jy0ksvmZ966ilfDZETJ064RP3ulDhmQEAAwcHBrK+v70ku3tzcZHx8nI2NjR0XRG9DpVKRkJDA1NSU1/kCW1tb9Pb2olKp3DZLTktLo76+3m2OzkEQQjA5OcnMzMyxifFO9WtnGTMjIwNZlmlrayM8PHxXN9ihCA2Fz30OPvxhpC98gbJ//3dK/+M3zBVnMHGxkE++9yKff/olnvrau5no+zDxv19KdmEBQYWFKG8hnFqtVgYGBqisrDx0t07SbkpKClevXsXPz4/+/n4yMjIOzDBtbW2hVqvdCsLcLQO6w68C9zNWQUFBbnN2oqOjWV9fP7QcLEmSixOZnZ3tCppGRx09OFlZWbsuKqdOnaKzs5OLFy/uOb/4+4WgClBjtZmRTY6FldMMvKOjg4sXL+4415WBCmKrQompDGFr3ExocwVFUcVYir/Iy5svsZylY+qElZMja3zhL5/jwft/h9rmf6a1tZXLd53hR8X3Ey4F8Uj1BezLkPJYFCHpN793m81GU1MT2dnZOzo0w8PDOX/+PC0tLaSnp5OcnOzWd3sUqC9dQtTUMPLDH6IYHCRteRm/jg741rfwM5moBPjzP3dksyoqHH/PnoVjdiwehoCAAIqKijAajTtkf9zp1PU1fGWj44khtMc2Ok8+CZGR8L73uT2ehoYGlEplrdhP4O01Al90BcYC1htBVSDwBuD/AuGSJOUIIYaBNwKHmsMJIYxJSUmDvb29se4o/R4FCoWCqKgozwh3PkB6ejrj4+OuwMq5GnIapTrFH30d/GVkZFBbW+s1Wxubzcbw8DCrq6suFXx34Qxg2trauHTp0pHbgm02G11dXSiVSi5cuOCVzyVJEuXl5TQ1NaFUKllcXCQ6Ovp4ZNq4OExPPknn+fOU9fYSV3OdxG/9Dwq7nUfUKvoiYvnpq0/zf3sy+JMPvomsX0ehTkkhsKiIwIIClDeU4g8LjG7F6uoqJ0+epKioiLm5OVpaWggMDCQ9PX1PiY65uTm3Fdw1Go1br3U3sHK3K1ChUCCEcGvBdOLECZaXl906/5OSkqitrUWlUjE1NUVISAj5+fn7dlSFhoYSFhbG/Pz8niUStSoYldpxPJqNN0nD4eHhJCcn09/fT9Ee2RlJkgjNDCA0MwCL1sZai4G3tT2CfU1getnE1dA6tkJUfPVb3yIsNJj3fvlPSH7nRU4rEylrLGBz1ETim8OJKLi5wJFlmZaWFlJSUvbMRgYGBlJVVUVbWxsGg+FQXbIjo6oKSZbJiY1l+Z57qOnrI/tTnyJAqWTu17+m2GxGammBlhb4x38E5/GQnLwz2Covd0sTyVMEBgZy+vRpJiYmGB8fp6Ojg9zc3DumX2WxWNBqtZSUlPh0P05D6NTUVPR6PTMzM9TU1BAREeFq7nA7uJuYgBdegL/5G/Bgkfv8889vvlbV1rfDFxmreODZGzwrBfATIcRLkiT9EfBfkiTJgAZwS7d+aWnpG9/73vdKnnzySZ8JGqWkpDA2NnZHA6vIyEgMBgNbW1usrq4yOTlJRESEKx1/u6BSqUhKSmJyctKt1vL94DRLHhkZIS0tjUuXLh1pEg4JCSEhIYHh4WHy8vI8fr/TXNqpV+NNOMVLf/vb3xIXF3fsDiW73U5rayu5b3oT6scfdzyo02G7fhXNb35B0pWr/OPGCiyNY/vSD9CWZaKKy0Tf3Iw2Lg5FcjIiJISE++93e59CCEZHRykvL0ehUJCcnExSUhIajYaJiQl6e3tJSkoiKSnJFfgsLi66zcXSarVumT57O2MFjgyDyWQ6NDsaFRV1qAm4EAKtVsvU1BRGo9GlKebOmHNzc2lsbCQuLm5XUK9WhZBelM87H/xrFPadC4f09HSamppYWlo6kE+kDvcj/g1hnLw7FG2/kbVmPW+avo8H33IvXe/pYvasDilF4q2RVUQ2hLPUruPEXaHEVNws0cqyTGtrKydPnjzwPPHz86OiooKenh46OjooKSnxvl+nM9taX8+Je+8lMjKS7u5ux3H38MNIkZHwoQ85XqPXQ0eHI8hqbnb8feFGF74kQW7uzmDr9GnwAt9PCMH09DRVVVXY7XaGhoZcc5S3TeEPw9TU1NF8TI8BpyF0bm4ua2trTE1NsbCwQHBwsMut4EB8/eugUMCf/qnb+7Tb7bz44otm4DfHG73vId3Jjjh3IElSQGJi4vT09HSsLwx3wXGSVFdXU1lZecd0SIxGI11dXWg0Gpemiq/98PaDzWajpqaGixcvetxdCI5gpqenx7WaP+53Kssy9fX1FBQUeFQSnJ2dZXR0lLKyMp8EpzabjebmZuLi4pifnyc9Pf3IxqdO0nt4ePiBq765mRGG//EVClsbCJqsJnjNIZEhh4ejz8hAf+EC9shIlFFRBGRnE5CVhTo9HcU+v8HKygozMzP7kl4tFguzs7PMzs7i7+/vMg93p9QoyzLV1dXcfffdh752amoKu91+6IpXCMH169fd2mZvb6+LrH8Y6uvrKS0t3RWE6fV65ubmWFhYICgoiNTUVFQqFSMjI1RUVBy6XSeGhobw8/PbtViZXmrip13LpPeVkrUlU/zEzqDGbDZTX1/vkX4agHHRymrzFpouI8IqsIWbCE0JxNgjiCoLIunhmyLLzkxVTEyMR4upsbExFhcXOXv2rPfnzcJCRwbq5ZcB6O7udrll5OTkHHyera1Ba+vNYKu5GZZucBNVKigu3hls5ee7zfFxYm5ujrW1NYqLi12PbW5uMjg4iN1uJy8v77Y0RAkhuHbtGpcuXbpjGoTgIM5brVYCAwNdHZRJSUkkJCTsvoZsbDh+27e8Bf6f+xqfr776Ko8//viP5ufn3+Xl4Xsdr0nl9e0QQpgSExPramtr3+Kr7kCnh9Ts7Oxt1yLZ2NhgbGwMvV5PamoqBoOBzMzMO2ov4+fnR1paGqOjo+Tn57v9PovFwuDgIJubmxQWFnqNVK9QKCgpKaG1tZWLFy8eOoHY7XaXhtSFCxeOFBweBifBNyUlheTkZJeKPnCk4GpiYgLgUBX+xORs1j+VyPOvPozl1Zf45n9+mIejI/k/JWmUNwwQ0t+P9d3vZjMtDUN7O/qmJlAq8U9NxT87m4DsbPy2mW2PjIzsWWpyQq1Wk5GRQUZGBpubm3R3d2MwGGhpaSEuLo6TJ0/ue1H1RPjWbDa7xXvzZFXuJLC7E1jFxsaysrJCcnIyOp2OxcVFlpaW8PPzIzExkaqqqh3Hkdlsxmg0ut1in5mZSU1NDSkpKTu2468KwWabZkm7QIp9t1WMv7+/i6d17tw5tz9/YJyK5N+LJOGN4ax3GVhtUmLssROQriDpoeMHVc7PFBQURH19vfcFfS9cgB//GGSZ5dVVDAYD586dcxmyz8/PU1xcvPfiMzoaHnjAcQMQAmZnHYGWM9j64Q/h6acdzwcHO8qG24OttDRHxmsP2O12hoeHd2Vtw8LCqKioYGNjw9V0k5eX5zXhzb2wsLBATEzMHQ2qwCHVcu7cOfz9/UlOTsZoNDIzM0NdXR2hoaEkJycT65x3nnkGtrY8klgAePrpp9cXFhZ8R7j2Il7zGSsASZLuede73vWz559/3nOTKjdhNptpampyy8rjuBBCsLCwwPj4uOvCFR0djSRJDA0N4e/v73PJg8PgzDa4QzR3psXHx8fJysoiKSnJJ2npqakpNjY2OH369L6v0ev1tLe3k5iYSHp6uk/GYbVaXVZE24MoZ7CVnJzsUdlxdXWVwcFBl47MYRBC8MyrqxjXrITW1vKJ5z7Kmn6Fe99Yyj+arVRc68aSmoTyK/+KtaQE8+goptFRbDf0mpRhYfhnZ2OLi2NClqlwI/vkxLVr16iqqsJkMrGwsMDS0hIKhYLY2FhiY2OJiIhwlYbcDRbB4W8WHx/vVkfRtWvX3MpYrayssLS0xGH8TIvFwvT0NJOTkyiVSoKDg4mPjz8waJyamsJkMnlkAzU1NcXW1tYOBXONbpK//tq3+f4T/8yPPvAyb//2A0iK3cdsb28vgYGBRy7PCyHYmNyia6KN0vJSwsPDsdvttLS0EBsbe6yy/8bGBh0dHZw+ffpIPoJ74tln4b3vxdrRQa1Gsytjt7CwwODgIHl5eW51p+6CLMPw8M5gq7MTnB2fMTG7yfE3qCKjo6PIsnxok8r6+rorU5mbm+v1rLkQgtraWsrLy30mou0OtFotQ0NDe2ZwhRBoVldZ7OjAODzMCZOJxK9+FUVODly54vY+DAYDGRkZ80tLS0nidRC0vOYzVjdw/be//a3FXR7GUeALe5lbYbVamZ6eZnp6mpiYGEpLS3et8tLT06mvr7/tNfNboVAoyMvLY3BwkNLS0n1ft76+Tl9fH1FRUUcuHbqLlJQUVyZhL87JwsICQ0NDnD592mdpeIvFQlNTE5mZmbtI2c6Ox9bWVqxWq1sXK6cmlrtBFTiyNg+WhvOdV1YoeO/9/Cjpv3nuFz/gp9ee408v5fNXP/0c93zmGU4++iiaN1zA/+tPcfLBB7FptY4ga2QEY28voq2NpMhIzAkJ+Luhoba5uUlQUJCrIzAsLIzc3FzMZjMrKytMTU3R1dWFv78/UVFRrK+vu6UPBe5zrDxBSEgIY2NjOx4TQqDX69nY2GBtbY2NjQ0UCgUxMTEIIdzuuE1MTKSmpsYjAndKSgrV1dUYDAbXhVDtF4JfoCN4M1mNCJtAUu/eXn5+PnV1dcTExBxpfpIkicj0UM7EnqGlpYWysjIXf85d/bz9EBERwblz52hpaXHpPB0bFy4AMPeTn5D3Z3+2qwwaHx9PVFSUK3tVVFTkWTlSoYC8PMftPe9xPGaxQE/PTr7Wr399kxyfmopcXg4xMWQ+9hjExzs6evdBVFQUlZWVrK2t0dPTQ0BAALm5uW7Jj7iD1dVVgoKC7mhQhRDMdXaSYTbDiy/CzAxMTzv+zswgzcwQNTdH1DaJFFmtpvtjHyN0YoLExES3frdf/OIXQpbln74egip4nWSsAOLi4v7t3/7t3z701re+1WfRxtLSEsvLyweWRo4CvV7PxMSEq9Tg5Gnsh97eXiIjI4/M1/EWnJYWhYWFuyZzk8nEwMAAJpOJwsLC22aW7OScnD9/3pVJk2WZgYEBdDodZWVlPuPJObOaOTk5B5rROvWsQkJCyM3N3ffCa7PZqK+vp6io6EiB4M/q1+mbMXA+QUupXwpDL06hs6+hqGphNkCw+KF/4a9WNKhlmaE/eTv+n/k8GVEZKCQJrUbDeHU18WNj2LVags+dI+y++1AcENwMDAwQFhZ26HHpJHd3d3cTGhqK1WolODiY0NBQQkJCCA0NJTg4eMc5UFdX5zZXx52MlRACo9FIfX09mZmZ6HQ6Njc3XWOJiIggKiqKyMhIVyDV1tZGZmam2yXsnp4eYmNjPTImXl5eZmZmhvLycgCsNhN/8e9f5lsf+Tv+7f/8kA98+zH8gvcO7JyNGLdKMHiK5eVlmpubKSws9Gpm3Gq10traSkxMDFlZWcdbGAqBPTYWbVUVUb/4xYEvnZubY3h4mPz8/GObRO/C1ha0t7uCLUtdHWqn7qEkOfhZ2zNbxcWwxznktHoZGhpyzQvHDYgaGhp839yk0+0Klrb/L2ZmkG61wFGrHRwq5y0lZef/qamY1Grm5uaYnZ11yxD68uXLKzU1NXcJIQ5VE3gt4HUTWEmSdPoNb3jDq6+88oqb6mOeQ5Zlrl+/7hWdKCfRcmxsDIvFQkZGBnFxcW510BiNRlpaWo7cSedNbGxs7NBFcpolz8zMkJubS1xc3G0f4+rqKkNDQ1RWVmI2m2lvbyc2Npbs7GyfjcVkMtHU1ER+fr5b3aPbbW2Kiop2/e5CCLe6sA7CyoaRp3+1jFX4EeyvoDhMTWKPBaGRuWp4hi/96GvI8xq+ERrMozo9G3FR1H3+A4S943GUo3pyUjKICg1l89VX0Tc1oYyIIOLhhwnYI9PmJI27w3EDx0W2sbGRS5cuIYTAYDCg0+lcN4PBgM1mQ5Ik/P39WV9fdzVs+Pn5oVKpUCqVKBQKFAoFkiS55BM6OzspLCzEZrNhs9mwWq2YzWYsFgsmk8ll1RMQEMDGxga5ubku2YODAreZmRlMJpPbWbbNzU36+/s91jFqaGhwkZuFEPzVs1/iq+/7JP/62Hf5k28/jjpi/+93cnwc5fe/T/LDD7vtrbYdW1tbtLa2kpiYyMLCApWVlV7NMsuyvMPO6agNR1qtFuub30z04iLSyMihrzebzXR1daFSqSgsLPRJ5lyv1zukX/LzkbaT41tawGmLpFY7Og+3B1u5uS5yvFNGZ2hoyKV5dxQrHK1W67LjOjLMZgf37JZgacf/Wu3O9ygUjkzdjWBJFxmJPjKSuIqKm4FTbKzjdR58lunpaVZWVoiNjd1lCL26ukpRUdHYwsKC94whfYzXU2AlxcXFTQwMDKR6ixS9FwYGBggJCTmyAJ4sy8zPzzMxMUFQUBAZGRlHykZ0dHSQmJh4RyUgnGhvbychIQGlUkl/f79LWuBOEuyHhobY2tpic3OToqIi99V+jwCj0UhTUxOFhYUe7cfpR7i+vk55efmOyX54eBiz2Xys7GhHRweR0SfQS1H0TxsZmjdhswhKVyFtDfRBGl7Ufo4Xf9FKdP8U31arKLRYGb9QwNW/eoSAC3dREJpOXkAS0vQcmhdfxL62RlB5OeEPPIBiW/lFq9UyPDzM2bNn3RrbysoKi4uLh34+WZZdWciioiLMZrMrYLLZbMiyjBACWZaRJAmFQsHMzAxpaWmoVCr8/PxcnoXOm0qlcgXYra2trsDqMJhMJtra2rhwowzlDurq6igtLfUo+6DVaunt7aWqqgpJkvibn32NLz/6F3zxrd/kL779QQJi9w8KxAsvID3yiOOfykr46EfhkUcc3W6HYH19na6uLsrKyggPD3fNU+fPn/fqueyU8FhdXeXMmTMeBzlWq5W6ujrO19YS8MQTjo4+NxczTomXgoICr8+dTgrArjlACEcg4gyympuhrc2R7QFHufAWcrxITmZhcZGRkRGioqLIzs72qOuztbWV9PT0/aUd7HZYXNw308TMzM1Oye2Iidk/05SS4giqbsk0l5SUeKVxQZZllpeXmZ6exmg0kpiYSFJSEs8884z1M5/5zN9tbGz887F3cpvweuFYIYQQUVFRz/70pz/99B/90R/5bNxpaWm0trZ6HFhZLBYmJyeZm5vj5MmTnDlz5limnFlZWfT09LwmAisn7ysmJoazZ8/e2Zo+uDIXS0tLFBcX+zSoMhgMNDc3U1RU5LE+jSRJ5OTkMDs7S0NDA2fPniUwMJDFxUVWV1ePtdpcXV3FbDaTmuzwLStIDsRqE4wumuifMdI8YOT0TCSPqb9K2V/M0bH+Q160+1MQnkrypz7F+x/5AluRoQzfX8aLbzyD9Mb7yf/Dh4hvGMZQ14BpZITIhx4i4AY521MPMHf9NxUKhStL5e6xvrKycmCJdTuCg4PR6/VuBVYBAQGugM7dLiunHZUn3bPh4eEEBgaytLREXFwcoSeieOT3/47cmAJk68ELXemrX0WkpDD60ENk/upXKN75TkhIgD/+Y4e20z4dkPPz84yMjOwooSckJGCxWGhra+Ps2bNey/ZKkkR2drarY7CiosLtuVAIQVdXF1lZWQQ4L+D19Y7WfDf2m5SURExMDF1dXczPz1NQUOCV7NXS0hJKpXLvuUaSHEFHSorDAxQcgc3Q0E5y/Ne+5uBxAdKJEyScPUv8mTOsZWbSNj5ORFYW2dnZh5bD9Vtb2BYXiVYqoa5u7+Bpfh5utWkKCbkZLJWU7A6ekpLAg7l9c3PT1ezhDTgNoePi4rBYLC6x4qefftqi1Wqf9cpObhNeNxkrAEmSUkpLS1vb29t9KnHb0tJCVlaWWxcGnU7H+Pg4Go2G1NRUkpOTvdb62tzcTFZWlvc6bTyE3W5ndHSUhYUFIiMj8ff3P5JIpzdhsVhob28nLCyM9PR0GhsbOXfunE+CPb1eT0tLi1fI8Gtra3R3d5Odnc3o6ChVVVVH5oLZ7XZqamqoqKjY93Pb7ILRcSOal7UErcrMh0BHgpnIqGUY66Xmzz/IQ0LwkJ8fITYbNn8VYxcLGb3/LNb77uHkpJbEnnlCiooJf/BBalpa3C4DguPYPXXqlFtEXZPJREdHh1vaWAA1NTVUVla6NZaZmRnMZrPb4q19fX3ExMS4bfBrt9uprq7mrrvu8qjs5cyCXr58mSf7XiSgqYJL05D5h9GEpO2TuWhrc5T//uVfWHnPexgZGqJSq0X6+tfhN79xcHve+U5HFutGw4nTJFij0eybPRoaGsJoNPrE2cGZJSstLXWLuzY+Ps7m5qZDRdxkciin//mfw5e+5NF+hRDMzMwwNjZGYWHhsVTRneebu1Zc+8JsdpDjt2e2BgYcGS/AlpzMemYm4swZou+/Hz9Z3jPTJE9Po9iL15SUtH+mKTnZ8V168fft6upySa74CuPj41y+fLlrdnZ2X1l5SZK+B7wZWBZCFN547MeAs2U3Ati44V98W/C6CqwAEhISepqamgp96VW1trbG5OSki2B6K5xExPHxcWRZJjMzkxMnTnh9UtJqtfT397t9wfEWnNmgwcFBkpKSXNpeNTU1lJeXe62rxVM4CdF5eXkukur6+rqrrOJNLRedTkdra6vbFwR3sLm5SXV1NdnZ2R616d+KgYEB1Gq1W12HQhYsN2yx+MomVj+ZlngLC4EBmHWTTDX/lCs/f45CjYb3x8TwtgA1gbPzAMyezmD0DeVs5eUQrYomNCCe3Lvuxu/ECSQ3AoirV69y9913u3VOaLVaxsbG9hUpvRWeEN01Gg1TU1Nu230sLy+ztLTkUYm2r6+PyMhIj7vh+vv7CQoK4ieGdjQvVYsUcAAAIABJREFURPPG9XDK/yiL8Px9zq/HH4ef/9zBiwkPp6+vD39/f0fQODAA3/ymQ6ZAr4eLF7F95CO0p6QQHB5+oCm4EIKenh5UKpVHmTd34VygbD9v98KesiNVVQ6+Tm3tkfZtNBrp7OwkODiYU6dOHWmOGBoaQqlUHttZYU/odA5y/I1gSzQ3I01N7XyNJLl4Tbb4eBZVKhIrK5G2B1AnTnjEazounOXau+66y6cc289+9rOGL33pS39qNBr3tbGRJOkysAU85wysbnn+XwCtEOILPhvorXCWVV4vt6CgoD/+h3/4B4PwIWRZFteuXRMmk2nH4zabTUxOTopr166J9vZ2odVqfTkMIYQQzc3NYnV11ef7cUKn04mGhgbR1tYmjEbjjudWV1dFQ0ODkGX5to1HCMfvMTY2Jqqrq4Ver9/1/OTkpGhpafHauLRarbhy5YpXf19ZlkVDQ4OYnp4WLS0toqurS9jt9iON7fr16x6/1zBvFv1fWxCdT8yK1n8YF798ckA8860Z8bl/Hxbv++snxdnzl4ROtyVET4+Y/NAHxWZJkRCOtbRYT4oRvb93QYy96y1i6SMfESvf/77YvHZNmCYmhGyx7N6XwSDq6urcHtvS0pLo7e11+/UNDQ27js39YLFYRE1Njdvbttls4urVq26/XgjHOePJ53XCYrGIK1euiH8a+KkAxIcu/6VYa9nnXJ+fF0KlEuKjH3U9ZLfbxfXr14VGo7n5Oo1GiCefFPa0NCFAWOPjhfjiF4VYWTlwLLIsi5aWFjE6Ourx53AHZrNZ1NbWirGxsT2f1+v14sqVK8JguGVq/9jHhPD3F+KWudgTyLIsJicnxdWrVz2eS7e2tsS1a9eOdK4eGUtLwvbLX4rZH/9Y1P3wh2Kkv19YrVYhhBDt7e1icXHx9o1lH4yOjvrsWHFClmWRmpq6AoSKQ+ICIA3o3eNxCZgBsg/bhjdvty/E9RIMBsMPv/Od7+iFDzNtkiSRlpbG5OQkcFNaoLq6GpPJxPnz5yktLb0tHn65ubkMDg76fD82m42+vj7a29vJycmhrKxsF5kyOjoatVrNwsKCz8fjhLOFW6fTUVVVtWfpKzU1FbVazejo6LH3p9VqaWtr48yZM179ffv7+11mpU5Bv7q6OgwGg9vbEDc6DY/SbRUYr4Z7Nwi8aCcmJ5wkUwhnFiTeMhPE+yN+n08++iP+66dafmtM4r5XrxLdN8hH3vY2xj71SfQZWaTX9ZLxw//mxFNPEfWhD6F+/HEs73oX6+9+N2tf+hLa3/wG09AQstHoNr/KCbPZ7BFx1xO/QJVKhe1WrskBUCqVqNVqjEaj2+9xZnC3trbcfo9zbKmpqchKUKkDMFmNyAbz3i/+1rccnJk/+zPXQ06vys7OzpufMSKCucceo/qZZ9h6/nn8Tp2CT33KkdX4wAfgRsferZAkibKyMpcchLehVquprKxEo9HQ09PD9vnbZrPR2trK6dOnd5faqqocJbT29iPvW5IkUlNTqaioYGhoiN7eXuzbdJX2gxCC3t5eCgoKvO+HeBBOnED5pjeR+NhjVDz6KKhU1NTUMDAwwNbW1h3n3YobZVZve6/eirq6OqxWa5MQQneMzVwCloQQh7eWehGvG/K6E0IIbWJiYvW1a9feds899/hsP4mJiVy7do2trS22trZIT0/3igyDpwgLCyMgIMDViuptiG2dNOnp6QeWDAAKCgqor68nNjbWp2Kg4Cidtbe3u9TcD0JhYSGNjY2EhYUdueav0Wjo6uri7NmzXi13zs7OotfrXR11kiS5uHNNTU1uq0dPTU0RERFxpNKk1WplcWWBy/c5jmEhR2JcsrLQO4F5aJ201XiUGyrExBaff/h7/KzrBzz7q5/wrRdeID8/n3/67vdJTA9itvaXxLePkNc5Q3hrK1JDA/zkJ9hDQ7EkJqJLTESRnU1Mdja2hQX8goIcAot2u+Pv9vs3/ipnZwksKwM31b8VCoVbF0YnlEolVqvV7eP1xIkTLC8veyScmZaWxtTUlEtV3SrsGGUzBtmMQbbcuG/BIJt33DeEmDEb7PipHIGV3WjdvXGj0WG/8tBDcEs5KiQkhPT0dHp7eykqKqK3txeLxcKFy5cdn/dd74LeXkeZ8Lnn4LvfhbvucvCWHnoItpXGFAoFZ8+epaGhAbVa7XXujDMQHBoaorm5mfLycpRKJZ2dnaSmpu7NJXXaxtTV3TRnPiKCgoKorKxkcnKSmpoaiouLD+Svzs/Po1arfdoccxj8/PzIysoiNTWV2tpabDYbU1NTpKSk3N5gbxuWl5eJjIz0+fz/la98ZX1+fv6fjrmZdwI/8sZ4PMHrjmMFIEnS2QcffPDll19+2es24kIIFhcXGR8fx2AwkJSURF5e3h3Vk9LpdHR1dXHhwgWvjsPZ9u2pWfLs7Cyrq6tu81aOgunpaSYmJigrK3NbfNRisVBfX09JSYnHwYeTv3UQIfwo2NjYoKura5fXnBMWi4WOjg6CgoI4derUvoG7yWSioaHhyGaro6OjSJK0Jy9Llu1MzNUy0dMOiykEak4TtBmIwaTj510/5n/7fs4HHvsoj7/vHczLE3z5Z98k/I3ZZCQn8eYpFdmd00iNjVBfjzQ97fHYAIRKhfQHfwCf+MSu4OFWdHR0kJGR4bYCeUdHB+np6W4fE1qtlpGREc64oRMlhGBDb6d1dpma0XEMej3CDxT+EgqVAnWwP5IfoLSDQgaFjEIh4yfZ8VPYUUs2sBn5/L1/zb0pl3nqs/9Awltu+fzf/a4j23TlCuyxmBRC0NDQ4LT92N/KaX3dsa1vftNBhk5NhY98BN7/ftgWYFgsFhoaGigqKvJZ48zMzAwTExNERkaiUCh22PzsQlaWQ3jzhRe8tn+9Xk9nZycRERHk5eXtOu+cEiAXLlzwmeCwJ9DpdHR3d3P27FnGx8dZWFggMzOTpKSk2x5g3Q5h0rW1NQoKCiaXlpYyhBtBiiRJacBLYhvHSpIkP2AOKBdCzPpssHvgdZexuoHWzs7OjaWlpWhvrapsNpvLbiYqKorTp0+jUChoa2vzyvaPg9DQUIKCglhZWfFKGthplqzT6fZUVT8MiYmJzM7O+iSLZrfb6e7uRpZlLly44FEQoVarOXv2LM3NzTvayg/D6uoqvb29x+/6uQVms5nOzk7Onj277+pOrVZTUVHB5OQktbW1lJSU7Pl79PT0HJl8a7fbmZmZ4dKlS3s+r1AoyUy+i5T4CkZmXmF07husWVWEGX+fu5Pew+/e9QHCDYL5n2j4785f8/z/PA1/DynpWfz6TWeofPu9fOCPv0GyOgaxvEz3D35AYVIS5okJTGNjyGYzUnAwAdnZ+Ofn4xce7hBMVCpBoWCwv5+MujrUzz0H3/sevP3tjvLVPgRyTzNWTjNmdwOrsLAwdDodQohdAYoQgvUtO5PLZiaWTIwtGTAYFUz86kf85D//DrN1ZwnxG//YgToqlhf+98u88vJTKBRKFH4qFAolSqWKP/taAyr/QGxWMyarCdl4S9lSCPjqVx2ik3uozQshGB8fx3KjjT8+Pn7/xVdUFHz84/CXfwn/8z/w9a/D3/wNfPazDluXj34UCgpcx2RjYyPl5eU+uYAmJyej1WqZmpri4sWLB7/4wgX41a8c34WXFpbBwcFUVVUxPj5ObW0txcXFO8rXvb295ObmviaCKnAQ6J3jycvLIyMjg5GREaqrq8nKyiIxMfG2LP43NzcBfE6D+e53v2syGo1fdyeoOgBvAAZvd1AFr9OMFUBISMiffOITn/jKE088cawrocFgYGJiguXlZZdv1vaTqa2tjdTU1DuaDoZtqr/HUGMXQjA1NcXExATZ2dnHOhmd7eKetOAfhq2tLdrb20lJSTmWV+L6+jo9PT37Zom2Y3l5mYGBAc6dO+cRz+cwyLJMQ0MD2dnZbgfDOp2Ojo4O4uPjyczMdK1EFxcXmZ2ddSuDshcmJycxm81udyIazRoGJv+H6aUmJJTERZfgpzyHbu4kuikrmtFZOjt+yfX+l+mYbkahUPKf/3KdqLxwYsPVGNFQUekwZBV2O6aREfStrZhvKGj7Z2YSfOYMAbm5SEolDQ0NlJWV4a/RwL/+q4NPtLUFv/d78OlPw7lzO8bniWEzwFJvL4ahIdJLSyE6GsLCDr1AO+1twsPDWdXZmFy2MLlsZnLZzIbOxFh3NcMNP+eRu97NfUFnGRrt5KXeH5GfkIQQaqw2CatN4tHy9xKoCqRhvJrWyQZsshU7VmxYsUs2Pv6OJ1AGq/h5/U9IMKbyO28sJvW92xqbXn0V3vhG+P734b3v3fk73eh4Cw0NJT8/H41Gw9DQkEt41C10dzsCrOefd8gb3HefI8D63d9FZzDQ2trqEzmT5eVlhoeHKSwspLOzk1OnTu1/nnz72/DhD8PoqNvlYk+wtbVFZ2cn0dHR5OTksLq6yvT0tNtiuL7Gre4X22EymRgdHWVtbY3s7OyDA2svoL29neTkZJ/QUpwQQpCenr46NTWVJYTQHvZ6SZJ+BNwNxABLwGeFEN+VJOkHQKMQ4mmfDXa/Mb1eAytJkkKTkpLGp6amYo6SCnXazZhMJjIyMoiPj98zpbq5uUlfX99tlzzYC729vYSHhx9JFX67WXJOTo5X6uOTk5NsbW1RWLirw9VjzM/PMzw8fKQy3n7bm5yc5Pz58/umypeWlhgaGuLcuXNeNwDu6uoiJCTELUmE7ZBlmeHhYVZWViguLiY4ONil23SUwM9p03SUkkZrx1Wsygk0+kEs1i38lAHERxcTHXEGnSmVmXELk53TzPR08DuZDxBmgT989hGWNhe4XHwvD9z1IPc9eC8x2RH4R/th39RiaG9H396OvLmJIiSEoLIyem02qh544OYFYX3dUa762tcc9++7zxFg3XMPSBL9/f3ExMTsfSG2Wh3BQmPjzdutTQ1+fo4Aa9tNREVhCY9CHxTOpjqYJVnFYmAsQ0nlbCkCke02ZnpfYbD5p/Q212HQ6wkLCOfTv/NPPFBaRoQ0QmDkFjq7jZDgYJSAbLUhW8BuUWG3qrHb1Njt/sj2QGSCkAnGThCCIBzNSxCcskTWB7bJTrz5zQ7No6kpuPH7OxdIk5OTFBQU7LjIDQwMoFQqycnJ8ei3ZnUVnnkGnnrKIeeQng5/+qdsvO1tdE5OUllZ6bVzRKvVunTL/P39MZvNtLS0kJSUtLd3YU+PoxT43HM3DZO9DCEEY2NjzM7OYrPZuHjxolcXWscZ135+rdthNBoZHh5Gq9WSk5PDyZMnvR5gGQwG2trauHjxok+DtytXrvCe97znhbm5uUd8thMf43UbWAEkJCQ8/53vfOedv/u7v+vWryzLMgsLC4yPjxMQEEBmZqZbHILGxkby8/OP5CrvTVgsFurq6jwi0ZtMJvr7+zGbzV43S3ZyO3Jyco6c0ZNlmb6+PgwGA2VlZV4lRI6Pj7O2tsaZM2d2TQQLCwsuJWpvp/snJydZW1ujrKzsyBPQ5uYmXV1dCCFITk4mPT39SNuZmZlhc3PzYA7LHhBCcO3aNe666y6QBKsbw8wut7Kw1onVZkTlF0RCTAkJMWdQ+KUzsWRleGqLX/2/Zxlo+y19w7WYrUbUSn/ec/6D/PnvfJKgBDVBSWoCE5QoLXNY+lowDQ+DECijo/FPSUGdmop/airKqCgkvd6RrfjKVxz2HOfPw6c/zWBWFuEREQ7C//z8ziCqtdVB9gaIi4PKSuxnzjBiMJAcHIppYRXLyhr2tQ0krRbF5iaqLS3+W1oCdRr87DvJ41aVmpX8DFYKTvCp/2qkBRXn897EvSW/w9kHSzl9Np6Q1CikG8ft4uIiy8vLFBcXH/z92u0Imw1hsyGbLFg3bejXDAxsTnHpnhtZ6eFhh8/cZz8Ln/sc4MiudHV1ER4eTl5e3q5ssSzL1NXVUVBQcDR+lM0G//3fjixWTQ0EB2N47DH677mH0+94x7HPz62tLVpaWnY1iNjtdtrb211cwx3njSxDZKRD/PRp3yYfmpub2dzcJCkpiZycnDtGEHdicXGRhYUFSm8Ivh4Gg8HgsvvKzc0lNjbWa0FQT08P0dHRHuu1eYr7779/7ZVXXnlQCNHq0x35EK/rwEqSpFOVlZXX6+vrD7yqWywWpqammJ2d5cSJE6Snp3uU2j5MMPR2YmxsDLvdfuiKVJZlxsfHmZ2d9alZsrMkeOHCBY8nXaPRSFtbG3FxcWRmZvpkfHupSs/NzTExMcG5c+e83tmytrZGf38/VVVVx+4gXV9fp62tDZVKdXCpZB8IIaiurj5SmXN1dZXZ2dldDQqybGNZM8DsShuLa93Y7CbUqhASY0pJjD1Db9cCUdmF1I7N03C1mcm6BnLjC3mo9BECNjb48DfeQmXmXVzKupfzxReISAxAuzpMmKTEpt1C2ASgBL8ApKBQpIAQFJJEaMMLRP7qG6jWZjDG52NJyCJkthPlkkMaQKjVWItK0OUXs5pxirmkXJaDY9i0KtjCH70yGKvyZsZFCIFFN49dP0tqSjT+qk2ar/+CuZ5OWFpCsbZJxJqee1Uq3hGVTNDMCJIQyEo/Nk4VEPjAfQTe+wYH/2cb38QZkB61yaCnp8cly8FHPuLIIk1PY4+JYWRkxCVeelDQ5BTkPMo5uQPt7fCNb8APfwgWCxsVFYS9//0oTp+GU6ccHngewDlXlJaW7rlIFUIwMDCAXq+nrKxs5/nz4IOOIHofuQhvYH5+nrm5OcrKyhgbG2NxcZGSkpLbIquzF2RZdp2/nnI/t7a2GBoawmQykZube2wqi7MxyNeCoDMzM1RUVAwuLCx4X6n2NuJ1HVgBJCQkdFy/fr1kL0f6ra0txsfHWV9fJyUlhZSUlCNNdkIIl9mqt3yRjgqnvcJBqfmVlZXbapY8OzvL0tKSR4Hn8vIyfX19FBcXe+zB5wmcWjTOzqOZmRmmp6epqKjwelBlNBppbGz0iDi/H2RZpra2ltLSUpRKJX19fYBDVsLdbS8sLLhKip6iu7ubuLi4A4M5u93CkqaPuZU2Ftd6sMtWJOFPdEQKIYEnCQiKZY4geteUrK34s9an4Tff/wem+uuxWs34qwKpyKzizy5/gpyTpxhY6qZ69LfIsg27bMMuW7HJNt5z8X2EhkfSPFaLXP19Hp4fJNhmZSQ4luHgGHLe+NfMF5zj19M1dPZfuTE6gUJhRylZePh97yc40EzDr1+g5VoN2nUNmjUdNqsdf38/Xq77AgHqML74uR/TUN3LyaiTnAxLJFoVx7nEy9xd+AALiWNIljrOjS8QXd+J1NLiyO4oFA77mMuXHbeLFxlaWyMgIMAjuQYnXFnpoiKUqanw2GMsfvGLDA4OujKX7mRRZmZmWFlZcVvN/kAsL8N3voPtG9/Ab7txb1oaFBY6mgwKCx233FyHtc4tMJvNNDY2utVpODk5yezsLGfPnr05x/393zsyd+vr4CUnhO1wdt1uL5lvbm7S2dnpmkdvd/ZqYmICs9l8LBuxzc1NhoaGsNls5ObmHrnLc3BwkMDAwCMd057gYx/72NZTTz31EaPR+JxPd+RjvO4DK5VK9db3v//933/66afDwXEhXV1ddWV2MjMzvVJvPs5FytuYm5tjdXWV06dP73jcYDDQ29vrMOUtKLitZsmtra3Ex8cfatQrhMO7bH19nfLycq9zm/bbZ0dHh8tgt6Kiwqv2N+DoKnVyIbzRoj46OorNZtsxqS4vL9Pf3+8itx/0GYQQ1NbWusRIPYEQwmVJ4+7FxGY3MTbdxPRCB/5BNraMy1isNwUzzapgNBFpLIlkTEshzFSPMFzfyGjnVd79N/9BRHw6bVf+g19+95MASJICSaFEoVDwwX9+hej4DFp+8wOq/+tJJIUCSZKQhIxCwDN/+RKZIoln6/6N5xq/jayQkRUyQikAwWcbvgUqJfXPvkLvK61ExkcTGR9LZFwsJ8LjuKfgAcIWQwieDSBA5zge7SqZrTg9M8krjOcsUBaVyX1hxQQobgTjej00NUF1tePW0OAgfwPyqVMsZWURX1bmMLUNDnb8vfX+Xv/7+TEyMkLEM88Q+6Uv0f3cc1hPnaKgoMDjrGNbWxsnT548VAPObcgyo6+8gt/gIKk6HVJvr0Mja2jopuGvnx/k5NwMtAoLsebm0ri8TK4HWVfnsV5eXu6gL/z2t/CGNzi6Ax94wDuf5waEEDQ1NZGRkbFrfLIsMzIywvLyMiUlJV6lUhwEq9VKbW3tkTOft0Kr1TI4OIgQgry8PI94rDabjZqaGp/rOJpMJtLT05cWFxdThBAWn+3oNuB1H1hJkuR38uTJ6aGhofiNjQ0mJycJDQ11dfR4C0IIrl+/7lUS53HGUldXR3FxMWFhYS6z5MXFRU6dOuXTjo394FxpH5StMZvNtLW1ERUVRW5u7m3VBhsfH2d4eJj09PRj+fTtBSEE7e3txMTEeGVF5yzlXLp0addEJssyExMTTE9Pk5GRQUpKyp7f48rKCjMzM0fKWKysrDA/P78rcD8MExMTAC4+mMWqZ8u47LrpjUtoDSvMKO0sh8Sg94tGrIWi1qsRSoFdYceuFEhqkJTCof10y02pkPC3g58Mav8AFEo/FJKEyuRH5FQoUZNhhE+F4GdRIitlNlMMbKbrWYlfxRZoJ9wQRvBcICHzgYTMBaEyOC5a1gAbukQDung92gQ9+hgTsiRj3jTwaOrdJKkPyaqazQ6T5BuBlq2mBj8PldgBUKsRQUHIW1voioqQX331yIG608/Nm9psTvX/gICAm+eRxeLgg/X2OojmzoBrfPzm+wICkAoKdgRcFBZCYuK+HZpOgeDCwkJiAgIcJsJ/+7fwBe9avk1MTLC1tXWgP6RTjy4xMdFntIXtcPpI7knmPwY0Gg2Dg4MolUry8vLcKnOOjY0hyzJ7VYW8iR/84Ae2j3/8419fWVn5a5/u6DbgdR9YAcTExHz+8ccff+KDH/yglJaW5rNujqMSgX0BjUZDf38/6enpDA8Pe1Qm8BVWVlYYGRmhsrJy18SztrZGd3c3BQUFt92SYWxsjNXVVcrKylzEX29OEiMjIxiNRq9kM4UQNDY2kp2dfSAvwmq1Mjw8zOrqKjk5Obs4dPX19RQVFR1phd3V1UVCQoLHAXp7ezsZGRmHroaFEJgsWib1EzRujKKVbEQEhBHiF0yoKpRgZRCBCvWNmz9BrvtqVJIfs7OzmEymfU1xZZtAP2Vmc9CEdsiEdeOG5pWfAJvjO1KFKQlOUxOS6k9wmhr/GL89L5YNDQ2UlJR4XNpdXl5mfmaGktxcMBgcGS6DYff9bf/bdTo25uYwrq0RqFCw9uij5Lz97R7t91asr6+7OH/emhuEELS2thITE3NgU4VVo6H3Jz8hXa8nYnb2ZsC13RIrImJnoOUsK94IJk0mEy0tLaSlpZH88MOOx1991SufAxzBW0dHBxcvXjw0GyPLMkNDQ6ytrVFSUuIzM3qn7MxxpHUOw9raGoODg/j7+5OXl7fvZ7Hb7VRXV3Px4kWfK62fOnVqdWBg4LQQYt6nO7oNuOOBlSRJAUA14I9DsPRnQojPSpJUAzivCieAZiHEW/bZRkxaWtrA2NjYkaQX3IUza3X+/Pk73oqr0+mor68nODiYM2fO3PHxODEwMIAkSa4SlrONeXFxkfLycq8KcLqDkZERNjY2KC8vd3nMtbe3ey24WlpaYnR0lMrKSq9cuDxVtTcYDIyMjLC5uUlOTg4nTpxAo9EwOjpKRUWFx/uXZZlr165xzz33eDypX7t2jcuXL3v0PYyNjaFSqTzyHZufn0en07mVeRRCYFq2sda9ydLUKulnkglJVaOKULr1+UZHR12efp7AOVe4QyC3Wq2Mj48zPz9Penq6KwtZU1NDWVnZsS/gQ0NDrhKQt2C322lqaiI1NXXP8r/VaqWxsZGsrKzddk2rq9DXdzPQcma6tNski+LjXcGW/dQpBpRKkl56ifDf/AZJo9lhxXNU2Gw2amtrKSsr84igrtFo6O7uJikpiYyMDK8GP86F1XH4UJ5gZWWFoaEhgoKCyM3N3cUhvl3Zqrq6Oh599NHfzM/Pe7fOe6dwOx2f97rhEHAJuXFfBTQB5295zX8Bjx+0nZMnT37/Zz/7mc8tyGdnZ0V3d7evd7MvLBaL6O3tFdevXxeLi4viypUrwmKx3LHx3ApZlkVdXZ1YXl4WFotFNDY2iu7u7tvrDn9jHIODg6K1tXXXvu12u2hpaRGDg4NCluUj70On04mrV68Kk8l03OEKIYQwm83iypUrwmw2e/zera0t0d7eLqqrq8W1a9fE+vr6kcawtLQkurq6PH6fxWIR1dXVHr+vr69PLC4uevSexcVF0d/f79F7ZFkWV69e9eg9Qgih1WpFS0uLx+8TQojh4WExPj6+7/Nms1kMDg6KK1euiLGxMWGz2XY8v7KyIpqbm4+07+2QZVnU1taK1dXVY29rOywWi7h+/bpYWlra8bjZbBbV1dVifn7ek0EKMTMjxMsvC/HlLwvxB38gRFmZEAEBQjg01103W0fHsccuy7JobW0VU1NTR3q/zWYTvb29ora2VmxtbR17PE7Mzc2J9vZ2r23PHciyLBYXF8X169dFZ2enMBgMQgghrFaruHLlirBarT4fw8WLF1eAEnGH4xFv3e64pY0QQgBOMoLqxs2VRpMkKRS4F3jfQdtZWlr67Gc+85k3v+1tb4vxZf07ISGB0dFRjEbjbc2+CCGYnZ1ldHR0h1myyWRieHj4NVGeBIfBcFlZGbW1tSgUCvLy8nyue3IrxI22bZPJtKeWlNMMtrOzk/7+/kONp/eC1WqltbWV0tJSr3Hu+vv7yc7OPpKuVnBwMKWlpSwtLdHV1UVXVxcZGRkee4nNz88fSYB2Y2PjSMKuZrPZ4+/PmXn0BM7fV5Zlj76P0NDQfe1tDkNKSgrxclEtAAAgAElEQVSNjY2kpaXteK/RaHSVp9PS0vYlBcfExDA2Nsb6+vqxsheSJFFaWupySvBWSUelUnHu3DkaGhpQqVRERkZiNBppbm4mLy/PMxNnSYKkJMftwQdvPm63O7haNzJb2tFRBlZWKLNYjqU/Nz09jUKh8ChTuh1KpZKCggLW19dpaWkhNTV11+/sKWw2m0s5/3ZCkiROnjzJiRMnWFxcpLm52WWynJyc7PVGn1vR1dXF6OjomBCi06c7uo24s+pnNyBJklKSpE5gGXhFCNG07em3Ar8VQmwetA0hxPTGxkbdK6+84tPapiRJZGdnMzw87Mvd7IBWq6W+vh6NRsOFCxd2nMApKSmsr6+7PJzuNIRwmFhLkoSfnx9xcXG3ff99fX1YrVZKS0v3negUCgWlpaUIIejs7HRmRt3eR3t7O9nZ2V5rkFhdXcVkMh3aVXkYZmdnKSsro7KyEr1ez/Xr1xkaGsJsNh/6XlmW0Wg0R7qIb2xs7PBacxdHDaw88Qp0IigoCKPRePgLt0GSJMLDw9nY2PB4f/7+/oSEhKDRaBBCuHTJWlpaiIyM5K677iItLe1Abk9+fj79/f0eHZ97ISgoiJycHJforLfg7+9PRUUFnZ2dLC0t0dTURGFhoWdB1UFQKiE7G976VnjiCcKffZa0oiLq6+vR6/VH2qRWq2VycvJAsrq7iIqK4tKlS+j1epcR9lExPDxMWlraHWuOkiSJ+Ph4Ll++TEREhCuB4M7ccRz87d/+7fri4uLHfbqT24zXRGAlhLALIUqAJKBCkqTtHinvBH7kznYWFxc/+elPf3rNF2Pcjvj4eLRa7bFOIndgsVjo6uqit7eXwsJCiouLd63SJEmisLCQ3t5er06YR4HNZqO9vR2NRsPdd9/NyZMnGRwcvG37F0LQ09ODEILi4uJDV4/bZSlaW1vdvlgPDg4SFhZ27CDICbvdTm9vr1tjPgh6vR6j0Uh0dDT+/v7k5+dz6dIlAgICaGxspK2tjfX19X2Pk5WVFWJiYo40Bo1G85rOWMFNM2ZPceLECVZWVjx+HzjMhvv6+qipqWF8fJz09HQuXbrktk9nWFgYISEhLGwnfB8RiYmJKJVKZmZmjr2t7XDyc5qbm8nPz/epLh1AXFwcJSUlNDc3s76+7tF7rVYrHR0dlJWVeS0To1QqKSwsdH0HU1NTHs/FOp3OlcG803BWQk6dOkVERAQNDQ0MDAy4jL69idHRUVpbWxeEEDVe3/gdxGsisHJCCLEBXAMeBJAkKRqoAP7XzfcPzs/P9zY1NR3+4mNAkiRycnJ8lrUSQjA5OUldXR3R0dFUVVUdmBmJjIwkODjY6xOmJ9DpdNTV1RETE+MStczJyUGn0zE/7/smDyEEXV1drknO3eBAkiRyc3OJjo6mqakJq9V64Ovn5ubY3Nz0KhF4ZGSEpKSkY7fEj46OkpWVteOz+/n5kZqayuXLl0lLS2N8fJzq6mrGxsZ2rUTn5uaOHCzq9fojiecKITwm/SuVytsaWMXGxnoUWAkh0Gg0dHV10dfXh16vp6SkhDNnzhAVFeVx4JqXl8fw8PCRPvOtKCoqYnx8/Ejfw35YXV11+XwODg765AJ8KyIiIjh//jw9PT3Mzc259R5npjknJ8cnelTR0dFcvHgRrVZLY2Oj29lRIRwSFkVFRbdVgmY/WK1W5ubmHJ2YyclcvnyZoKAg6urqGBoaOnSO9ASf+9znNlZWVj7htQ2+RnDHAytJkmIlSYq4cT8QeAPgTHM8CrwkhDC5u72FhYWPf+pTn/J51urkyZPodDqvTlDgaI+uqanBYDBw6dIlkpKS3DrZTp065TKVvt2YnZ2lra2NkpKSHd1TTr7VyMgIWu2hJuVHhrPTz9/f/0h8KYCMjAzS0tKor6/fNxOp1WoZGRk5lgfgrdDpdCwvL5ORkXGs7RiNRjY2NvYtwUiSRHR0NGfOnHHJYTQ1NdHc3Mz8/DwWiwWtVnukcp7RaMTf39/j7+SoGdajlgKPGlj5+/tjt9sPvaA4OzSdgWt8fDx333032dnZR854AQQEBBAXF8fk5OSRt+GEn58fp0+fpqOjwyuB2szMDP39/Zw/f57k5GRX1sbmFAz1IQIDA6mqqmJ6eprh4eFDjydnptmXnE8/Pz+Ki4vJysqisbGR6enpQ8c1NTVFeHj4kc49X2BsbGxHiVqhULgWZ2q1mtraWkZGRo79G8/Pz/Pqq69qZFn+pTfG/VrCHQ+sgHjgqiRJ3UALDo7VSzeeewdulgGdEEK0DgwMTDotQHwFp6TAwMCAV7ZnMploa2tjeHiYsrIyTp065VGq2ukn19PT45XxuAO73U53dzcLCwtcuHBhz6yaSqWivLycjo4On6xknUFVSEgI+fn5xwp4EhISKCoqoqmpaRenxmw209HRwZkzZ7xG/nWuVIuLi48t1TA2NrYrW7Uf1Go1GRkZXL58mby8PDY2Nrh+/TqyLLO0tORx0HJUfpXNZjtSOeZ2Z6zAkY1YW9u9XjMajYyPj1NbW0tnZydqtZrKykrOnDnDiRMnkCSJ5ORkZmZmjlWqz8rKYmpqyivZgsjISOLi4o5VphfC4aAwNzdHVVWVS+4lLi6O1NRUWltbvRK4HQYngd5oNNLV1bXvPufn572eaT4IsbGxXLx4kfX1dZqbm/dd8BqNRiYnJ2/buA6DyWRicXFxT3kRpVJJenq6S1KlpqbG5XByFHzxi1/c3Nzc/DtxpzksPsAdD6yEEN1CiFIhRLEQolAI8YVtz90thPiVp9tcXFz8+BNPPOFZ8f0IiI2NRZZlj+v82yHLMqOjozQ2NpKYmMi5c+eOrFtz8uRJFArFbSm9GQyGHTpaBwUbzqDH25OtLMu0trYSERHhNTX1qKgoFxl3cXFxx37y8/O9KgroXKkehZu0HRaLhdXV/8/eewc3lt33nt+DQBBMYALYzLGZAxgA5u6Wy2sruEZPa7u82ifJY8nWSlaNSvM0si2X1nH9nup51lp7rbLLssZ6Dhqp7LeSXdYoeWq62c0AgiRIAsxgJkEABBEJgohn/2BfDLubAcA9QPfM9KeKNRw2cO4lCNz7O7/w/doS2onn5OSgubkZeXl5uHnzJmw2G+7fv4/JyUns7OzE1LjqcDhS1rgOJN5jlZaWlnBwr1AoYLVaQSmFy+XCysoKRkZGoNPpAAA9PT0YGBhAZWXlE32QaWlpkMlkFwZmsSISiVBTU4O1tbWE1zhPXV0dnE4nbDZb3M+NRCKYnZ3F6enphfZQ5eXlkMvl0Ol0Ken7FAgEaG9vR1ZW1oXl/GRkmmNBLBZDqVSiuroa4+Pj2Nvbe+T14NoXWlpakj55FyvLy8toaGi4cqMnFApRW1uL4eHhqIDo5uZmXJ9Jh8OBf/7nf3b7fL7vsDjvZ42nHlglibvj4+NWFqnz62hubk54asdqtWJkZAThcBjDw8NPqGcnQmtrK1ZWVpLa58CN5La0tMRs71BUVAS5XA6DwcDkHMLhMCYnJ1FYWHipAneiZGZmYmBgIGqDo9froVAo2E064WxnuLm5yWSnyjVFJ/reCYfD8Hg8KC8vR2trK27fvo2mpib4/X5otVqMjIxgcXERh4eHF+5OUym1ACReCgTObgrxljBOT09xcnKCvb093L17F2tra8jMzER/fz8GBgZQU1NzrUBvVVUV71JeRUUFDg8P455svAhOgkGv18d1reDMinNycq7MtNbW1kIqlaZsqIYQgrq6OlRWVj5Szucyzd3d3UlXDr8MhUKBoaEhHB4eQqvVRjcr+/v7SE9PfyoWZBfhdrvh9XpjnuQWiUSor6/H0NAQ/H4/7t27h+3t7ZgCrD/7sz/zer3er1JKk18zfgo8deX1ZCEWi//Txz/+8b977bXX2FuhP8bc3BzkcnnMGYPzZsmtra3M9bD29/dhtVrR2dnJdN1IJILl5WW43W50dXXFrSND6ZkZskwmQ21tbcLnEQqFoNVqUVxcnNQpmkgkgomJCRwfH+N973sf0wvz1NQUysrKeMtRcGatt2/fTriceHBwALvdfqkWWjAYhM1mw+HhIex2O8RiMfLz85Gfn4+8vDyMjo7ife97X9zHjUdB/TyRSAQPHjzArVu34j7mzMzMlT6ilFJ4vV7Y7XbY7XY4nU6IxWLI5fKoe0CiTfr3799Hb28vr3F6i8WC/f39hDwgL8JkMmFvbw8qlerawNzhcGB2dhatra0xBQOclElmZibq6+uZnG8s2O12zM3Nob29HUtLS1FHgmcBs9mMpaUl1NTUYGNjIyVWMbHCKb4n2usVCARgNBphtVpRW1t7aX+w1+tFXV2d2Ww2V1FKk6vl8JR4NvKPSSAUCv3bG2+84bRYLLksMw0X0djYiPHxcdy4cePKm1s4HMba2hosFktSzZJLSkqwt7cHi8XCLMvC9YAVFhait7c3oewIIQRKpRITExPIyMh40uoiBkKhEDQaDcrLyxMW94sVp9OJUCiE+vp6jI2NoaenJ6Gb6uOYzWZQSplofG1vb6OiooJXj9b+/v6VWT+xWIzi4uLo38vv98Nut8Nms2FpaQk+nw/T09PRsmZOTk5MQbff70/IiokQknBJmeuzkslkoJTi5OQELpcLTqcTLpcLp6enyMjIQEFBASoqKtDW1hZt4hUKhbDZbAm9BwghqKiowM7ODi97EIVCgfX19YSzhI9TUlICq9WKnZ2dK217dnd3sbGxAbVaHfPvTwhBR0cHtFottre3mRiUx0J+fj5UKhXu3buH8vLyZyaoAs560PLy8nDv3j1IpdKnLpHDYbVaIRKJeDXQp6Wlobm5GbW1tVhbW8P6+jrq6+tRXFz8yP3ir//6r0/9fv/X361BFfAuzlgBQGZm5id+7dd+7f/9y7/8y9iNoBJkdXU1Wnt+HEopDg4OUmqWzKXsBwYGeAvO2Ww26PX6mHeq1xEMBjE2Nob29va4PsjBYBAajQZVVVUoKyvjfR5X4fP5MDExgd7eXmRkZER3601NTbwColAohPv376O/v5+3vyPX3zA8PJxwjwbnl3b79u2EguXd3V34fD7cuHEjGpy4XC6EQiGIxWJkZWUhKysLGRkZ0S9uh768vAyZTJZQgH337l3cuXPn2sdRSnF6egqfz4eTkxOYzWZ4PB4IBAJQSiGVSpGbmwuZTAaZTIb09PRLXwe3242VlRWoVKq4zxd4O7t4584dXiV/p9OJxcXFC83OE4F7D3R3dz8hQxAOh7GwsAC/34/Ozs6E3mfhcBgTExOorq5OmQsD13Lgcrlw48YNXhly1uzu7uLw8BDFxcVYXl5GY2NjQp8BVlBKMTIyApVKxVvy5Tw+nw9ra2twOBxRo/iH5ulWk8lURyn1MDvYM8a7OrAihAiLiopWtVptTSI2HfHA3TAHBwcf2a17PB4YDAakp6ejubk5paq6BwcH2N3djSnNfxGUUqytreHw8BBdXV1MS5YnJyfQaDQx74ADgQA0Gg1qa2uTfnEOh8MYGxtDc3PzI2KHXL9GdnY2mpqaEgqODQYDsrKymJQwNzc3EQgEeDXum0wmOJ1ONDc3J/T8+fl5lJSUoLCw8Il/CwQCOD4+hsfjiQY2Jycn0R4nv9+PrKwsZGdnIy0tDWKxGCKRCCKRCEKhEAKBAISQ6H+BszIgV2JqbW1FKBSKfgWDQQQCAfj9fvj9/mhWKz09HRkZGZBKpSCEwGazQa1Wx/33o5RGA7pEA5q5uTkUFxfzzqJMT0+jrKyMWUba6XRifn4eg4OD0Qyd1+uNHodPDx9wFlSOj4+jubn5wvcKSzY2NuBwONDV1RV9r4hEomdCJ+rk5ASTk5NRc26/3w+9Xg9CCNra2njZ9CTKzs4OPB5P0mzRTk5OsLq6Co/Hgx/96Eenf/VXf/XHdrv9vyblYM8I7+rACgDEYvEv/OIv/uLff+c730m6SMju7i4cDgfa29sRDAaxuroa7V1JhVP5RczOziI/Pz/uslkgEMDMzAyvIOI6nE4nZmdn0d/ff2XA6ff7odFoorueZMKJCBYUFFwY/HDBptVqRXd3d1zBptPphMFgwODgIO8LfCQSwb1793j3aGi1WtTX1ydszTMyMoL+/v64z4FSGg2UBQIBAoHAI0FSKBSKBlHcf4GzxnWBQIDd3V1UVVVBJBI9EpBJJBJIJBKkpaVdaBUTDocxOjqaUH8WcNajVV1dnXDJhJsoVKvVCT2f4+TkBFqtFrdu3WIWLBiNRvj9frS0tMBkMmFlZQVKpZKZvtLp6SkmJiagVCqZlDEvwmQyYXNzE/39/dFrFqUUq6urcDqd6O7ufmoTeJRSjI2NobGx8Ql1+v39fayurqK5uZnpkMx1cFnUVPR67e3tobe398hkMpXFo035TuRd22PFEQqFfnD37t29xcXFvER35bFSVlaG7e1trKyswGQyoaamJmHBSla0trbiwYMHKCgoiLk3glONbmhoSGqKOjc3F83NzZicnERfX9+FH+zT01NoNBo0NTWlpFdiY2MDIpHo0owSp7pfUFCAiYmJmNP4kUgE8/PzV/oXxsP+/j6Kiop4XQxDoRC8Xi9ychKrlEciEUQikYTOgRCCYDCI/Pz8K73yLuPw8DChiUqhUIhwOJyQqTLwtuxCosGGTCaD3+/nbeKekZGBwsLCa3uj4qG2thbj4+OYmJgAIeSJ7Dtf0tPToVKpMDk5CZVKxVS6BDjrEzIajY8EVcDb7gq7u7sYGxuDSqViPjAUC0ajEXl5eRda/pSWlqKgoADz8/MwmUxobW1NSVP7ysoKampqUnKsV1991eN2u7/8bg+qgHev3EIUSim1WCyfeemll5Kua8X1lmxtbWFwcBCVlZVPPfXMKQHHoilDKcXGxgb0ej1UKlVK6v4KhQK1tbWYnJx8YoSe63Nqbm5OSVBltVphNptjMmctKCjA4OAgdnd3odPprh3h39jYgEKhYGKlQSnF+vo6b7V2brgh0feoy+XiZUIdDocTCqr4IpFIEpYjidfe5iIqKyuxs7PDaw0AqK+vx8bGBjOVc5fLBb/fD5fLhY6OjqSUpTIzM9HV1YWpqSmmLhF2ux2Li4vo7e29NEgoLy9HS0sLNBpNUp0gLsLlcuHg4ODKzQAXeMrlcjx48ABWqzWp5+R2u+F0OpM+BAScbQS/853vHB0fH7921eMIIa8RQqyEEMO5nykJIROEkFlCyBQhhF+6NwW86wMrAKCUji0uLi6Mj48nZX3OLHlhYQFdXV0oKSmJiks+C+Tn56OwsPBKb8NgMIjp6Wl4PB4MDg4ymX6LlZKSEpSVlT0iIMr1YLW1taVE58Xr9WJhYQHd3d0xlz3T0tKgUqlQUFCABw8eXCoUy2kg8ZkGO4/ZbEZ+fj7v5nc+3oBA4vpVT5vMzMyEFdglEgkikQgvBfTS0lKYTCbeYrlisRgVFRVYX1/ntQ5XKuM2VB0dHZibm0vaxJpMJkNra2tM3pyx4Ha7MTc3B7VafW0PK2frpNPpkh64cIRCIczOzqKzs/PaawshBGVlZejv78fm5ibm5uaYevNxcIb18fiq8uG3fuu3nA6H479QSq8ToPsWHnoFn+O/A/hDSqkSwO89/P9nmvdEYAUAZrP5s5/73OeOWF4sKKXY3NyMmg8PDAwgJycHjY2NWF9fT4kZaazU19fDZrNdqLTsdrsxOjqKoqIidHR0PJUsQmVlJQoKCqDT6XB8fIzJyUm0t7dfmDZnTTAYxNTUFDo7O+MOVrgxepVKhcXFRSwuLj6SeeNsa1pbW5m8rpTSqNkyH4LBIE5OThIuAwKJK64DZzcbPq8HC8mFRCksLOSloi4UClFYWAiLxZLwGhzV1dU4ODhIOPtzfHyM0dFRRCIRDA4OIisrCzdu3IBUKmXiTXgZhYWFqK+vvzBTHQ9cg31PT0/ME21ZWVno7+/H6upqUn9HDr1ej6qqqriy1enp6VCr1VGdOL5Z0sfZ29tDdnZ2SjZGKysrePPNN/cDgcD3r3sspXQEwOM7VAqAu1DJACTfWoQn75nAilK6cHBwcP+NN95g4qlydHSE+/fvw+fzYXh4GKWlpdHIXywWo66ujpcXF2sEAgG6urqg1+sfuQhzpayuri4ke3LyOurq6iASiTAyMoKOjo6UNPxzoqW1tbW8LjKZmZkYHByERCJ5JHtlMpkgkUiYTUIdHh4iMzOT91i02WzmXep1u90JB2aJqq5zJOoXCJzdWL1eb8LHlsvlvLMdVVVV2N7e5rUGcPa5rq+vx8rKSlzPi0QiWFtbw/T0NFpaWtDY2PhINqWlpQU7Oztwu928z/EyiouLn8hUxwPXwN/Z2Rl3iV0ikaC/vx82mw0LCwtJy87t7OwgEokkVG7jNm29vb0wGo2Yn59nUvYNBoMwGo0p8yf8/Oc/b7dYLJ/l4Qn4BQB/SgjZBfAqgC+zO7vk8J4JrADAbDZ/4eWXX7bzScFzQpmc99RlZsllZWXweDxPmPk+TaRSKVpaWjAzMxNNT1utVgwODvLKXLDC7Xbj6OgIxcXF2N7eTol43srKCjIzM5noYhFCUFtbi56eHiwvL2N2dhYrKytMx5iNRiOTkqLJZOIlWxEMBqOSCInAN7BK1C8Q4J+xys/P5+UPCgDZ2dkIh8NR6xU+FBcXw+PxwOOJTRbI5XLhwYMHiEQiGB4evjDrKBQK0dnZCZ1OxyujdB2VlZXIz8+Pu/TIyRZ0dHQkvCESCoXo7u4GIQRarZb57+l2u7G5uYmOjg5e5TapVIq+vj7k5OTgwYMHvLKlwJl+XG1tbUqkHSYnJzE/P79CKb3PY5nPAniZUloO4GUA32RzdsnjPRVYUUq3XS7X9//xH/8x7qI1t8PjzJL7+vqunGrhdEn0ev0zo64LnDWLZ2Vl4c0334RMJkNXV9czYQDqcrkwPT0NlUoFpVKJtLS0pPZ5APw1nC6D85HzeDwIhUK8b8IcdrsdIpGIdwN8MBjE6ekpr3X49lexCKwSvRFmZGTwCmiEQiHS09N5B0WVlZVMSlGEkKhn6VWEQiEsLCxgfn4eSqXyWrPdnJwclJeXX7suX+rq6iAWi2M+zvmgiq8UBPfaFRUVYWxsjFlDfSgUgk6nS1hU9XEIIaiqqoJarcbKygoMBkNC739OwDcV1QlKKT73uc8dmc3mz/Bc6lcB/H8Pv/9nAM+b1581rFbrl7/yla+4OCPMGJ+DkZERUEqjZsmxkJOTg4KCAmxsbCR6usw5ODjA0dER0tPTkZWV9dSnFoGzm/TMzAxUKhWys7NBCEFTU1NSgyu3243V1dXojpU1XBA0PDyM/f19TExM8Co/AcDa2hoTz7WDgwPeemBOp5PXTe1plgK5vzef9xWLcmBxcTEsFgvvJnbgLIvGiZ8+DqUUJpMJ9+/fR2ZmJoaGhmLOUFdXV8Pr9SZ1GIcQgpaWFpyensJoNF75WJZB1XkqKyvR0NCAiYmJmDN/VzE/P4+qqirmlYCMjAz09/cjMzMT9+/fj2vTFolEoh6Kqbju//jHP6Z7e3sTlNJ5nkuZANx++P3PAFjjuV7Sec8FVpRSm8/n+8bXv/71ayMrr9cLjUaDnZ0d9Pb2or6+Pu6GW04/he9NlS+RSAQGgwE7OzsYHBxEb28vDAYDfD7fUz0vu92O2dlZqNXqRzKAyQyuOPHTZDneh8Nh6PV6tLe3QyqVoru7G3V1dZiamsLy8nJCO023241IJMKk2dRkMvGaBgTOGtffqRkr4Ky8wue9r1AoeDcUC4VCKBQKHBwc8FqHo7m5GUtLS498VjweDyYmJmC1WjEwMICqqqq4bqqEEHR2dmJpaYmpPMJlx7HZbJdKUSQrqOJQKBTo6urC9PQ0r78t1zuXLG9EQgiqq6uhUqmwtLSEhYWFmD4L6+vrKCoqSknbRyQSwRe+8IUjs9n8UjzPI4S8DmAcQAMhZI8Q8ikAvwHg/yaEzAH4rwA+zf6M2fKeC6wAwGaz/cmf/umf2i+rVYdCISwvL2NqairaM5OooJxQKERbW1vSy1pX4fP5MDY2BolEArVajbS0NKSnp6OtrQ3T09NJ7aG4iqOjI8zPz6O3t/dCeQcuuJJIJJiZmWGys49EIpiamkJjYyMTTamLWFtbQ1lZ2SO/U2FhIYaHhyEWizEyMoK9vb243g9ra2tMeqsCgQACgQBvcUav18tLkuNp9lgB/PusuOfz/UxXVVUxm0zLysqCTCbD/v4+AoEADAYDZmdn0dDQAKVSmfDrLZFI0NLSEpMWHh8EAgF6enqws7PzRIbM4/FAo9EkLajiyMnJQV9fH5aXlxPSGrPb7dje3kZ7e3sSzu5RMjMzMTAwgPT0dDx48AAOh+PSxx4fH8NkMjGTfLmOb37zmwGHw/F9SulmPM+jlH6UUlpMKRVTSssopd+klD6glHZTSjsopb2U0ulknTcr3pOBFaXU63K5XvnCF77gfOzn0ZR5WloahoeHmUxzFRQUICsri4koYLxYrdaoQvjNmzcf2a0WFhaipKQE8/PzKQ/6Dg8PYTAY0Nvbe2XQygVXubm5TBpMFxcXUVhYmDRrHI/HA6vVeqF4p0AgQG1tLQYGBmC322NuRPV6vfD5fEykJw4ODnhPA/p8PkgkEl7lhKdZCgT4B1aEEOTm5l55M4uFzMxMCAQCXudynps3b8JgMGB0dBQymQxDQ0NMpms5cdtktzWIRKJoHxH32XA6nZiamkJ3d3dSgyqO9PR09Pf3w2w2P5EBvAqfz4e5uTn09PSkrG+VG5jp7u7GwsIClpaWnvhcUEqjJcBkWJM9jsPhwO///u/brVbrF5N+sGeU92RgBQA+n+/1n/70pxtarRbAWallfHw8mjKvqalh+iZsamrCxsZGUtPp56GUYnl5OWrxcFmAyJmrbm7GtbHghcViweLiIvr6+mLOBNbW1uLGjRuYmJhIWDBvZ2cHPp8vabs2TrOqra3tyveORCJBe3s7OvNb4JIAACAASURBVDs7sb6+Do1Gc2VfB5etYtEXwXcaEODfXwU8/VIg38AKYFMOBNg0sVNKsbe3h4mJCeTk5KC0tBTl5eVMe2mampqwv7+fdNXytLQ0qNVq6PV6bG1tYXZ2Fr29vSmdXBaJRFCpVAiHw5iZmbn2vRYOhzE9PY22tjbeUiiJkJWVFTV2fvDgwSN/o62tLeTm5qYkKAWAL37xiy6Px/M7lNLkaXU847xnA6uHVjcfe/HFF+3z8/OYm5tDU1MTr5T5VYjFYjQ3N2N+nm8f3/X4/X5MTEyAUor+/v4rRS+56UWTycRchO4izGYzVlZWrjVevojKykpUV1djfHwc8QwfAGe7qK2tLWZefRexs7ODnJycmC9gWVlZUKvVqKurw/z8PKanp5+42ft8PrhcLiaWPn6/H6FQiLeqPovAKhQK8drV8y0F8lFf5ygsLGTymblx4wYODw8TChS5LPvIyAgcDgcGBgbQ29sbLQey5LwEAysbncuQSqWorKyM9io+jWCFEILW1lbk5+djYmLi0teT21CVlpYy06tLBEII6urqoFQqMT8/j5WVFRwfH2N7exsNDQ0pOQedToc33nhj+/j4+O9TcsBnlPdsYAUAlNIll8v1vR/84AehoaGhpEf0RUVFEIlE2N/fT9ox7HY7xsbGUFNTg6amppiCCKFQiJ6eHhgMBia6OpdhMpmwtraGvr6+hDVUSkpK0NjYiPHx8ZgHAk5PTzE7O5vUFP3p6Sk2NjbQ1NQU93MLCgowMDCA8vJyzM7OQqfTRX+39fV11NXVMQkGWZQBAf6N6xx8fie+pUA+foHn1+BrbwOcBYnFxcUwmWIXlKaUwmw24/79+zg8PIRarUZbWxskEgmEQiFqa2uvtLBKlOzsbFRVVWFhYYH52ufZ3t7G/v4++vr6MD8/H/dGiiXV1dWora3F2NjYhcH45uZmVA7hWSAnJweDg4MAgHv37qG6ujolpclIJIJf/dVfPbJYLB/jIQb6ruA9HVgBwP7+/st/8Rd/YWOlNXQdra2tWF1dZV4S5Ix5FxYW0Nvbi6Kiorien56eDqVSiampqaR4U+3t7WFjY4NXUMWhUCigVCoxOTl57bhxOBzG1NRU0lP0BoMBTU1NCV/ACCFQKBQYHBxESUkJZmZmMDU1BYvFwrt0x8GiDEgphd/v5+VTGIlEeAeKfEuBhBDeawBnWauLJA7ipbKyMiYl9vN9oGazGT09Pejo6HiipF5eXg673Z6UaeTKykr4/X5m04znoZRiaWkJFosF/f39kMvlUePkZFyXYuXGjRvo7OyEVqt9pC/y8PAQJpMJbW1tz4R0DYdAIIBEIkFRURG2t7exurrKZPjnKl577bWAxWL5V0qpPqkHegfwng+sKKUej8fzxZdffjkldudpaWlobW1lOmETDAah1Wrh9XoxODiYcACRl5eH2tpaTE9PM/0Qbm9vY3t7G319fczkDXJzc9Hb2wu9Xn/pTp9L0ZeUlCQ1RW+xWEApZdIQTwhBUVERhoaGQAgBISSmAPI6Tk9PEQ6HeQeXXq+X90Qh3/4qgH8pEDgrB/INPBQKBRMzX6lUCrFYfKmFTDgcxtbWFu7duwe73R4V0r3s78kNfSwtLfE+t4vWViqVWF5eZirXcr6fSaVSRaVt5HI56urqkqKOHg8ymQx9fX1YWFjA/v4+3G43FhYWHjnXZ4Xj42NsbW1BqVRiaGgIkUgEo6OjTDS6LsLhcOD3fu/3HFar9b8k5QDvMN7RgRUhJJ0QMkkImSOELBBC/vDhzwkh5E8IIauEkCVCyOevWsfr9b7+k5/8ZH1qaiol5y2Xy5GVlcWkYdzlcmF0dBSlpaVMpj5KS0tRUFDAbFJwa2sLJpMJvb29zNPRGRkZGBgYwNbWFtbX1584X+71ra6uZnrc84RCISwuLqKtrY35um63G3fu3EF9fT3W19cxOjqKg4ODhP4uBwcHTDJfLMqALAIrvqVAgE0De15eHu/JQI6LpBf8fj9WV1cxMjICv9+PgYEBtLa2xjT0IZfLEQqFmJ3feVhvEAOBACYmJpCXl4fW1tYnsj8lJSUoLi7G9PT0U3WykEql6O/vx9bWFsbGxtDd3Z2Unlw+RCIR6HQ6KJVKiEQiCAQCNDY2oq2tDTMzMzAajcxfw1deecXldrt/h1KakgTFs847OrAC4AfwM5TSDgBKAO8nhPQBeBFAOYBGSmkTgO9ctcjDRvaPv/jii0fJTpdyNDc3Y3d3N+EdBKUU29vbmJ2dRXd3N2/Bx/NwPT3XqSBfx/r6OiwWC9RqddJq/GKxGH19fXC73Zifn4/ebLkUfbJVhpeXl1FdXc2rNHYRW1tbqKiogEAgQF5eHlQqFTo6OmCz2XD37l2sra3F1SPEogwInAVWT3siEOBfCgTYNLBz9jYsSm4KhQJHR0cIhUJRN4KJiYmo9EtDQ0PcZXTO6iYZwYhcLkdubi7v68Tx8THGxsZQW1t7oUwJR3V1NWQy2VPVBATOMnbhcBh5eXkwGo1JL7HFy+rqKoqKip7YAOXm5mJoaAjBYBCjo6PMJD5mZ2fxgx/8YNvr9f4PJgu+C3hHB1b0DO7dIX74RXFm2vhHlNLIw8ddm6unlC4eHh7+yze+8Q22ozSXIBQKoVQqodPp4v5gcj5UR0dHGBwcZC50yU0KHh0dYW9vL6E11tbWcHR0lJI0uUAggFKpRGZmJsbHx+FwOGAwGNDT05PUYzudTjidTuYKy+FwGHt7e0+sm5WVhba2NgwPD0MkEmFsbAw6nQ4Oh+PKG83p6SkopQmL3J7H6XRCJpPxWuNZKQVmZWUxCYjkcjmT6cBIJIKsrCzcvXsXq6urqKiowK1bt1BVVZXwxiQnJwcZGRlJs6RpbGyE2WxOOCtmsVgwNTWFzs7OmErp9fX1EAgEWF5eTuh4fOEEhmtqaqBWq5Gdnc1LAoY1drsdNpvtUkkZoVCIpqYmtLS0YGpq6sJMfzxEIhG8+OKLzxvWH+MdHVgBACFESAiZBWAF8FNKqQZALYBfIYRMEUJ+SAiJSbjIarV+6Q/+4A/sqWpkl8lkKC4ujusicXx8jNHRURQUFCTVQFkgEKC7uxsbGxtxu6mvrKzA5XKhp6cnJYJ0wNujxjU1NRgdHUVdXR3zLNJ5IpEI5ufnk5IR29nZQWlp6aV/W5FIhOrqaty+fRtlZWXY2NjAyMgIjEbjhdNTrLJVkUgEkUiEd5/cu6kUCPDrs6KUwuFwYG5uDiMjI5BKpVGRzMLCQibvrcbGRqysrCQlsyIQCNDZ2Ym5ubm4JBgopVhbW4vq7MUarHObPq/Xi/X19URPOyEopdDr9cjPz0dZWVn0mlNVVYWxsbGkTlTHQigUwvz8fEySMnl5eRgeHsbp6SnGxsYS3mB861vfCprN5ucN64/xjg+sKKVhSqkSQBkANSGkFYAEwCmltAfANwC8FuNaHo/H88WXXnrJef2j2VBXVweHwxFT8LK/v4+pqSkolcqk+VCdRywWQ6VSQa/XX9pUex5uosfr9aK7uztlQdX54+/t7aG+vh4bGxtJlbXY3NyEXC5nLloYiUSwtbUVU18YIQRyuRzd3d3o7++HUCiERqPB5OQkTCZTtFTGKrByuVy8s1XAs1MKFIlETJqhucxXPIGLz+eD0WjEyMgI1tfXUVxcjDt37qC1tRWZmZlM+6KkUml0OiwZZGVloaamBnp9bPfWUCiE6elp+Hy+hPTsCCHo6uqC1WpNOKOeCKurq6CUPpENKikpQXt7OzQaTVL62WLFYDCgpqYmZp06oVCIlpYWNDU1QavVYnNzM67slc1mw1e+8pUji8XyvGH9Md7xgRUHpdQJ4C6A9wPYA/A/H/7T9wDEbNzk9Xpf/4//+A/Dj3/845QUzjnz0au0WrjsyP7+PgYHB5nc3GKFMxGenp6+cldDKcXi4iL8fn9SRTivYnV1FVKpFPX19RgYGMDe3h4WFhaY79RPTk6wu7uL+vp6pusCZ8FzUVFR3FmhtLQ0VFdX49atW2hoaIDT6cTIyAgmJycRDAZ5S1wAZ2VAFvpVz0opEDjbPPDVs+LsbZzOq/djfr8fm5ubePDgAWZmZiASidDf34+enh4oFIroZ6aqqop5EFRXV4etra2klazKy8sRDoev3cx4vV6MjY1BLpfzGrYRCARQqVTY3NyExWJJaI142NzchNvtRkdHx4XXtry8PPT29mJ+fj4uPTJW7O3tIRgMory8PO7n5ufnY2hoCMfHxxgfH4858/bJT37S6XK5XnresP4k7+jAihAiJ4TkPvxeCuBnASwD+D6An3n4sNsAYlbKo5RSq9X6K7/+679+lGzrBo6MjAw0NTVdOGFzcnKC0dFRZGZmQqVSMZMriIfs7OyohstF+ltcijwcDl964Uk2ZrMZdrsdzc3NAM5umGq1GmKxGOPj48zGwjkJh9bWVub9W5wWWW1tLa91ZDIZmpubcefOHUilUqSlpeHevXvQ6XQ4ODhIWDWbReM6AN46WACbUiDAthx4UZ/VyckJNjY2MDY2hsnJSUQiEXR3d2NwcBBVVVUXBryFhYVwOp1MgyCxWIyqqirejeaXQQhBR0cHVldXL70xm0wmaLVatLa2Msm4cyXTpaUl3nIkV7G3twez2Yyurq4rr23np5STMXl3GR6PB0ajEUqlMuFrr0gkQltbG+rr6zE5OYnt7e0rz/9f/uVfQpOTk+Ner/dfEj3vdzPv6MAKQDGAtwgh8wC0OOux+ncAXwXwi4QQPYD/BuDX41mUUmpyuVy//Zu/+ZspKwneuHED2dnZWFtbi/7MYrFAo9GgpaUFtbW1T1WALjc3F62trdBoNI/s8DmDT4FA8NRE8jweD5aXl58oPxJCUF9fj4aGBkxMTDDRGzKZTJBIJEnRxTo4OEB+fj6z8W1CCJxOJ3p6enDnzh1UVlZGzZ8nJiawvb0dV8DpdruZlD4DgQDvDQKLUiDARssKeLuBneuZWlpawr179zA3NxfNSg8PD6O2tvbaIQJCCMrKypiXuSorK2GxWJhqT51HLBajvb39iQ1iJBKBXq/H7u4uBgYGmJhCc0gkEqjVaszNzcXUrhAvZrMZW1tbMQ/hcFPKHo/nkSnlZBEKhTAzM4POzk4mm+7CwkIMDQ3B5XJBo9Fc+F6x2Wz4/Oc/f2SxWD7O+4DvUt7RgRWldJ5S2kkpbaeUtlJK/+jhz52U0g9RStsopf2U0rl41/Z4PN96880353/0ox+lbJa2qakJVqsVNpsNS0tL2NjYYH4h4kNhYSEaGxuh0WgQCoVAKYVOp4NEIkFLS8tTCaoCgQCmp6fR1dV1abmrsLAQ/f39MBqNF7q/x3Os1dVVtLS08DnlC+GyVXV1dczWPDk5gVAohEQiASEE+fn5aGlpifbyBINB6HQ63L17F3q9Hmaz+dIsSTAYhFAoZNY3x0J5/VnJWHm9XphMJrjdbrz11lvY3NxETk4OBgYG0N/fj+rq6rgnMsvLy7Gzs8M068HpGSVzoq6goAAFBQVROx0u4y6VSqFWq5mUpB8nIyMDPT09mJmZYdpAbrPZsLKyErdcDDelLJVKo6X4ZGEwGFBZWcm0PUQkEqG9vR21tbXQaDRPvA9ffPFFh8Ph+CylNL6ppvcQyTcQeodCKaWEkP/tN37jN2YNBoMiFX1NAoEAra2tePDgAaqrq9HX1/dM2SQAZ36HwWAQGo0GaWlpyMnJSZnB5+NQSjE9PY2GhoZrMynp6eno7+/H6uoqxsfH0dnZGbcK+eLiIm7evJmUm8Ph4SGysrKY2u5c1bSelZWFuro61NXVIRwO4+joCIeHh1hdXY1qZxUUFCA/Px9paWnM+qtYBQosS4G7u7sxP55SiuPjY9jtdhwdHcHtdiM9PR1yuRwlJSVQKBRMBgUkEgmysrLgcDiYbqyKioqwvr7ObBDhIurr6zE2NgZCCPb399HR0ZH0zWF2djba29sxOTmZUEP843CSLYlacHHZ8r29PYyPj0OlUjGROznP7u4uwuFw0gaZ5HI5BgcHsbCwgIODA3R0dODf/u3fQlNTU2M+n+97STnou4TngdUVUEoPcnJyfvszn/nM//P6668nPbKy2WzQ6/W4efNmUnsG+FJSUgKj0YjT01N0dXU9tfNYXFxEfn5+zMbChBA0NDSgsLAQGo0GN2/eRFlZWUzPPTo6gs/nYyrEep61tTW0t8c8YxETJpMJfX191z5OKBRCoVBAoVAAOMvMcZOqRqMRoVAIhBBkZ2fDbrdDJpMl3F/GonEdYFcKzMjIuDLLcXp6CpfLFdUsOzk5QVZWFvLz86OClVwWz2azYX9/n5m3Y1VVFTY3N5kGJYSQqGhof38/s3XPEw6HkZaWBqPRiNu3b8c8pcaX/Px8NDc3R4OrRKVonE4n5ubmoFKpePcClpWVQSqVYmJiAl1dXcyCWY/Hg/X19aj1VbIQi8VQKpWwWq344Q9/iJdfftlpsVg+kbQDvkt4Hlhdg8fj+R9vvfXWi2+88cbwBz/4waSUTimlMBqNsFgs6Ovrg1QqxeLiIlZXV59aNugyOFPj8vJyiEQiTE5OQq1Wp9wra29vD16vFyqVKu7nFhQUYGhoKFr+am9vv3JXGg6HodfroVKpknIRs9vtSEtLYyr06vV6IRaLE9ptp6WloaioKGrkHYlEMDY2hoyMDOzs7MDtdiMSiSA7Oxs5OTnIzs5GVlYWMjMzr319AoEAk8CKVcZKIBCAUopgMIjj42McHx/D4/HA7XbD5/NBIpEgNzcXMpkM5eXlkEqll/6O+fn5MBgMvM/p/Hp6vR6BQIBpljQvLw9isRhWqzUaTLPi6OgIer0etbW1UY2+7u5upse4CoVCgUAgAK1Wi97e3rhL106nE7Ozs1CpVMwCwoKCAqhUKkxNTaGpqSn6uUoUrq8qmTqGj6NQKPA3f/M3Trvd/huU0md31/+M8DywugauJPjpT396zmAwKFiUQ84TCASg0+mQmZmJgYGB6IWgsbERExMTMJvNTMx9WRAKhaDValFcXIyqqqroz1MdXDmdTqyvr2NgYCDhQEcsFqOrqwsmkwmjo6NobW2FXC6/8LFGoxGlpaVJ23mvra0xD6BZZk4EAgGCwSAaGhqir3ckEokGIA6HAzs7O9HMT0ZGRvRLKpVGvxeJRDg9PWWWsYonsKKU4vT0FD6fDycnJzg5OYHP54PX641KAHBBIpeNSk9Pj+v9JRAIIJVK4fV6mbxXCCGoqKjA7u4u70nRx2luboZWq4VcLmeyWYhEIlheXobD4YBarY6WtK1WK3Z3dxOSAUiUsrIyBAIBzMzMoLu7O+bfLxlBFUdWVhYGBgag1WpxcnKSsH8p19daU1PDXEPvKr773e+GdDrdA5/P9/2UHfQdDHmuQh8b2dnZn/jgBz/459/97neZRVbcB7mhoeHCclYgEIgafbK2rYmXUCiEyclJlJaWPlHT397ehslkSklwdXp6ivHxcajVamYXP5/Ph9nZWWRmZqKpqemR6RqPxwOdToehoaGkCJ66XK6klGVGRkYS7g95nNPTU8zMzGBgYODax0YikSeCF+6/wWAwOlGak5MDiUSCtLQ0iESiJ74IIRAIBCCERL+nlIJSGlWAn5+fR0tLC0Kh0BNffr8ffr8/2jhMCIFEInki2MvIyMDq6ipu3LhxaWAdDxsbGyCEMDP+5nzdbt++zTxbajAYkJOTg4qKCl7rOJ1OzM/Po7i4OOozysGdfzKCletYWlpCMBiMaVo5mUHVecLhMHQ6HdLT0xMa+FlZWUEwGERra2uSzvBJrFYrlEql+eDgoOV5tio2ngdWMUIIIQqF4s3XXnvt9oc+9CFed1hKKba2trC7u4vu7u4rP8hutxszMzMYHBx8KhpWwNnFcXJyEpWVlZf2JKUiuIpEIhgfH8fNmzeZlzAopdjZ2cHGxgaam5tRVFQESinGxsbQ3NzMRL/pIqamplBdXY2CggJmax4fH0cbb1lwcHAAp9OJpqYm3msZjUaIxWIoFIpo4HM+IAoGgwiHw4hEIo8EUtx1igu2BAIBdnd3oz563JdYLIZIJEJaWhokEgnEYvG1N6+trS1QSpkEQ8fHx1hcXIRarea9FodOp0NZWRmTwO88gUAAo6OjUe/JeAmHw1hZWYHdbkdHR8elmz+73Y7FxcVHMvKpgNOcS09PvzIjnKqg6vx5LS8vw+PxxFXOM5vN2NzcTKjEyYcPfOADjrt37/6az+f716seRwh5DcAvALBSSlsf/qwDwF8DyAKwBeA/U0rZ62I8YzwvBcbIw5LgRz/96U/Pz8/PKxK9EYZCIczNzUEoFGJwcPDaICQnJwf19fWYnp5Gb29vyqcEA4EANBoNamtrrywtcVksjUaTNCFTvV6PGzduMA+qgLOMRmVlJYqKiqIq9zKZDDk5OUkLqo6Pj3F6eso0qALOyoAsm+ydTiez18Dv9yMnJwdSqZT3lNTh4SEaGxt5n1NWVhYODg54rwO8rYsViUSY3fw4YU/WgVVaWhoqKiqwsbERt4sA10tVUVGBwcHBK69L+fn5kMvlWF1dZfL3ihVCCNrb2zE1NYXNzc0LA2fu90hlRo0QgqamJmxvb0cnBq9rkue0+lIdnP7TP/1T8GEJ8Mqg6iHfAvCXAP7+3M/+FsArlNJ7hJBPAvgSgP+T/Zk+W7yjdaxSDaXU4nK5/o9f+qVfciSS6XO73RgdHYVCoYBSqYw5s1NSUgKZTIalpaW4j8mHQCCAiYkJ1NXVxdSvU1lZiYqKCkxMTPC2CXmczc1NhMNh1NTUMF33cdLT06FWq5Gfn4/FxUXk5OQkTUHZaDRe6kLPB9Z9eQ6Hg4nUAsBuKpAlrERCgbObZl5e3rX2NvGQm5sLn893oesBX6qqqmAymS6103qcYDCI+fl5rK6uQq1Wo6amJqbNXn19PY6OjuI2dOcL5yt4cHDwhN2OxWKBwWBAb29vysuUwNn1kuulvUrcNBgMXqvVlwyMRiO++MUvmi0Wy8dieTyldATA46XCBgAjD7//KYBfZHiKzyzPA6s4OT4+/v7i4uL/fPXVV+OSL97d3Y0q5CbSyNnY2AiPx5NUY+Hz+P1+jI+PX9r/dRllZWWor69naiNjs9mwt7eXUrscm80GpVIJh8OB8fFxeDwepuv7fD643W7m2TePx4P09HRmGUNKKRMLGo5nMbBKT09nGrTI5XImKv8cXBP7zs4OszU5hEIhbt68iZWVlSsfRynF7u4uHjx4gNzcXPT19cWluXbeE5X1pus6hEIhVCoV1tfXo3+X/f19rK6uRqewnxZyuRxdXV2YmZm50BKJ0+qrr69PabO63+/HCy+8cGSxWD7Cs3RnAPDCw+9/GUDqphieIs8DqwSwWq2fe/XVV7cnJyevfWw4HMbc3BwsFgsGBwcT/nBwOy+j0ch0N3wRPp8PExMT0V6jeCkqKora3/DNBJycnECv16OnpydlU4cWiwWRSATl5eVQKpVoamrC7OwsFhYWEvbZexzOE5B1oMi6DOj1epGVlcVsPdbSASzgGuRZ2Y9w9jYsKSsrw/7+flKypyUlJXC5XJduHlwuF8bGxuBwODA0NISKioqE3rcZGRmor6/H3Nxcynz0OMRiMXp7e7G4uIjFxUVsbW2hr6/vmQjyc3Jy0NfXh+Xl5SfMtxcXFyGTyZhN+MbKSy+95LZYLP+dUjrNc6lPAvgcIWQaQDaA1EbVT4nngVUCUEoDVqv1Q7/8y79suyrI8Xq9GB0dRXZ2Nrq7u3lnEcRiMXp6eqDT6ZhaN5zH5/NBo9FcKT8QCwUFBVAqlZicnEzYwysUCmFqagodHR0p21WGQiEsLi6ira0t+rO8vDwMDQ0hMzMT9+/f532D8/v9sNlszC+WlFKYzWbeOjnnYVkGBM7OMZU9IrHCshyYlpYW1cZihUgkQn5+PtNMGMd50dDzBINB6PV66PV6tLa2or29nfc1rLS0FCKRKC61e1ZIJBIoFApsbm6itbX1qQ0DXQTnDGGxWLC0tARKKTY3N+Hz+VLalwYA3/ve90L/+q//qrPb7X/Kdy1K6TKl9Ocopd0AXgewzv8Mn32evSvcOwRK6YbD4fj8Rz/6UedFN9mDgwNotVq0tbXF3IcQC5mZmVAqldBqtcw9qLxeLzQaDdrb25k0VOfm5qKnpwfT09Ow2WxxPZdSitnZWVRWVqbUK3FlZQVVVVVPBHKEEFRVVWFgYACHh4fRHXwibGxsoLq6mnm2yuPxICMjg+kNw+FwMGtcT0aWgtWaLDwDz5OMrFVVVRW2traYrsnBfd6Pjo4QiUSwubmJBw8eQCaTYXBwkKn9TVtbGzY2Npi+3tdBKYXBYIDP58Pg4CB0Ol3SzKgTRSQSQaVSIRKJYHR0FPv7++js7EzpwNL29jY++9nPWq1W6/9KGXy4CCGKh/8VAPgKziYE3/U8D6x44Ha7X5+ZmXnj61//erRBIxKJYGFhAdvb2xgYGEjKRFleXh7q6+uh1WqZlS+Oj48xOTkJpVLJNJDJzs5GX18fFhcXsbe3F/PzjEYjJBJJ0nywLsLpdMLhcDwifvo4EokESqUSbW1tWF5extTUVFzZw2AwCLPZnBTBRNZlQABMPeWCwSDToI/TtmIBy4wVcKZUzTqwkslkCAaDSQsIuJL3yMgI/H4/hoeHEy77XYVIJEJHRwd0Oh2z69dVhMNhaLVaCIVCdHV1ITc3F21tbZicnEx5v9d1EEJQWlqKk5MTUEqZtR7EQjAYxAsvvGC32Wy/nIheFSHkdQDjABoIIXuEkE8B+CghZBXAMgATgL9je9bPJs8DK55YrdZf/+M//uP9ubk5+Hw+jI+PR+v5yewlKS4uRlFREXQ6He+bi8fjgVarjV50WCOVSjEwMIC9vT2srq5ee74WiwWHh4doaWlhfi6XwWnetLe3x3QjycnJQX9/PyoqKqDVarGwsBBTfQIzlAAAIABJREFUBnFrawuVlZXMy2GUUlgsFqZlwEgkgnA4zCwYYt24zsovEGCfscrLy4PdbmeepauoqHiiD4cFDocDer0ewNvTasm0S8nLy8ONGzewvLyctGMAbw/hFBUVoampKfrZLigoQENDAyYnJ1MavFzHyckJdDodBgcHo0NAqcrsfelLX/KYTKa/DIVCY4k8n1L6UUppMaVUTCkto5R+k1L655TS+odfv8MiC/ZO4HlgxRNKqc9qtf7CRz7yEedbb72FhoYG1NfXpyR9W1tbi7S0tGsneq7C7XZjamoK3d3dSXO7B852qWq1Gj6fD3Nzc5fuVD0eD5aWltDd3Z3SXpyNjQ3I5fK4hwsUCgVu3bqFrKwsPHjwAKurq5deqMPhMPb29ngrXV+E2+1GZmYm05uh2+1m+p5gHVix8gsE2AdWAoEAGRkZTLNgwFmP0sHBAbPf2+12Q6vVYnl5Ga2trRgaGsL29jazgPUq6urq4HQ6mWf2OI6PjzE+Po76+voLM983btxARUUFpqamUpI5u45gMAitVouOjg5kZmaiqKgInZ2d0Gq1SZep+OEPfxh5/fXXF2w22x8m9UDvEZ4HVgyglC47HI4vfeMb33CzFnu8jtbWVrhcroRGsZ1OJ6anp6FSqVIyyisQCNDe3o7MzExoNJonMjycXktnZ2dKp3VOTk6wu7sbt0giBycueuvWLQiFQty/fx9Go/GJAGtnZyfavMuaZJQBWTeuJyNjxeqGKBaLmWcuktFnJRQKIZfLYbFYeK3j8XgwPT0NvV6Pmpoa9Pf3QyaTQSKRoLi4OGm9XOfhJBgMBgPzktzR0RG0Wi06OzuvlDSpqKhAYWEhk8w/HyKRCLRaLW7evPlIK4ZMJkNfXx8WFhbiaqWIB5PJhE996lNWq9X6YUrp048w3wU8D6wY4XA4/nZ8fPzN1157LaVFe0IIuru7sbOzA7PZHPPz7HY7ZmdnoVarmY7TXwchBDdv3kRFRQXGxsaiO/rzei3JzJw9DqUUer0eLS0tvOUchEIhamtrMTw8DAC4f/8+1tfXoxYtW1tbzDzkzkMphdVqZVoGBNg2rgPPdikQOMuqshwIUSgUSZniq6ysTDjw8Xq9mJmZwdzcXFQ1/fHNYG1tLXZ2dlLSfySVStHY2IjZ2Vlmgc3Ozg4WFhbQ19cX07Wkrq4O6enpWFhYeCrBFaUUMzMzKCoqunBS+HwrxcrKCtNzDIfD+PCHP2y32Wz/O6WU/Zv1PcrzwIohFovl47/7u7+7r9PpUnpcrsy2srIS0/Td0dER5ufnmRoZx0tpaSna29sxOTkJq9WKpaWlp6LXcnBwALFYzNQuRCQSoa6uDsPDw4hEIhgZGcH09DQKCwuTMuLtcrmQnZ3NXOfL7XYzzWQ+y6VAgH0De2ZmJk5OTpiXmbKzsxGJROI6V5fLhenpaczMzKCsrAyDg4OXvudFIhFqamqwtrbG6pSvpLi4GBKJhHfvWCQSgV6vh8ViwcDAQFwSLc3NzQgGgyn7nTm43s6srCzU1tZe+jjuGu/3+5k2/b/yyiue7e3tvw0EAm8xWfA5AJ4HVkyhlHqtVuvPvfDCC4d8U/XxkpaWht7eXhgMhisFRA8PD6HX69Hb2xuXcnIyyMvLQ39/P/R6Pcxm85VGqckgGAxiZWUlaU7xIpEIN2/exNDQEOx2Ow4PD7GwsMDcmmR/f595QBoMBiEUCpn2uT3rGSvWfVacvU2ishxXUVVVdW0gQimFzWbDxMQEFhcXUVlZiaGhISgUimt7QCsqKmCz2ZKml/c4LS0t2NraStjhgLPfkkgk6OnpibvcTghBR0cHHA5HUoYDLmNpaQmEkJiufQKBAG1tbZDJZJiYmOCdXf2Hf/iHwLe//e2pw8PDL/Na6DlP8DywegghJJ0QMkkImSOELBBC/vDhz79FCNkkhMw+/FJetQ6l1Giz2f7zBz7wAXus/lusSE9Ph0qlgk6nu/ACZbVasbi4+NRtHM7j9/shFAqRm5uL2dnZlDTNciwuLqKuri7pSuCHh4coKSnBnTt3kJOTA41Gg9nZWSY3ca4MyNoax+l0Mp8QZWmNA7DtsQLYB1ZAcmQXgLMsj9lsvvD3p5Ti4OAAo6Oj2N7eRlNTE/r7+1FYWBjzUA1nFJwqf1KRSITOzk7odLq4rwFutxtjY2OoqanhNTgkEAjQ09ODvb09ZqbcV7G2tgafz4e2tra4/i61tbWorq5+pJUiXrRaLV555ZVdq9X6wvO+KvY8D6zexg/gZyilHQCUAN5PCOl7+G9fopQqH37NXreQz+f76fb29ldffPFFV6pr9pmZmeju7n5CX8lsNmN5eRl9fX1Mb2584NLaPT096OrqQl5eHsbGxlIi3Hd0dISTkxOUlZUl9TiUUqyvr6Ourg4CgQDl5eW4desWiouLMT8/j/HxcVgsloT7JhwOB3JycpiXAZMVWLEMYlmXApMRWBUWFiYlsBIIBLhx48YjAUAgEIDRaMTdu3dxeHiIzs5OXtO+CoUCgUAgKRm3i5DJZCgtLY0rmDOZTJiZmUF3dzcT43GhUAi1Wo21tbW4RY3jYWtrC3a7PWEB0OLi4mgrhd0en+SUyWTCRz7yEavVav1ZSmnqVFrfQzwPrB5Cz+DeZOKHXwlHRXa7/dW33nrrJ1/72tdSLu+bk5MTtZM5PT2FyWTC2traM+ONBZz1Q0xNTaG5uTnaPF9dXY3m5mZMTEwkpen3/LH1en3MmlV8ODw8RFZW1iMZQkIIioqKMDAwgNbWVpjNZty7dw/r6+txp/dNJhPzaUCAfeM6cPa6swwAWWeskiGPwAWSyWgE55rYXS4XZmdnMTY2BoFAgKGhoej0LV84q5tUbRBramrg8Xiu/fxHIhEYDAbs7u5icHAQ2dnZzM5BLBZDrVbDYDDA5XIxW5djf38fJpMJPT09vErteXl56O3thV6vh8lkiuk5p6eneP/732+3Wq2/QindSvjgz7mS54HVOQghQkLILAArgJ9SSjUP/+lPCCHzhJCvEUJiikwopdRisXzsq1/9qvEnP/lJylOteXl5aGlpiY7+9/X1PVPmtwaDAUVFRU+UsAoKCtDf3w+j0Rj1zGLN2toaSktLU9K4v7a2hrq6ukv/PTs7Gx0dHRgcHAQAjI6OYnZ2NiZxSUopDg8PmZcBgbPpMZavTzL+jqx7rIRCISilzM9VLpczz36EQiHY7Xa4XC4YDAaUlJTg9u3bqKmpYTogIZPJIJVKecs7xAonwbCwsIDLWilOTk4wOjqK9PR0qNXqpAyEcG0VMzMzTINts9mMjY0NqFQqJpuMjIwMDAwMYGtrC0aj8cr3LqUUH/vYx1x7e3t/FAgE7vI++HMu5XlgdQ5KaZhSqgRQBkBNCGkF8GUAjQBUAPIB/HYc6wUODw//l0984hPmVE+bAGeGyiKRCJTSZ0IAj2N7exvBYPDSKRjOkJQQgrGxMabN3h6PB2az+coJHFbY7XakpaXFtJsWi8Wora3F7du3UVpais3NTdy7dw9Go/HSG4zdbkdubi5zIdXT01NIJBKm2bxQKMRcv4t1KRA4syxi3Rspl8uZZGAppXA4HJidncX9+/fh9XrR3NwMmUwWU0N6ojQ1NWF5eTll15D09HQ0NzdfqC1lNpuh0WjQ0tKCurq6pGacMzMzowKdLK5BZrMZa2tr6O3tZRoMisVi9PX1wePxYH5+/tK/01e/+tWT+/fv/7vdbv9zZgd/zoU8D6wugFLqBHAXwPsppQcPy4R+nPkcqeNcy2KxWH7hAx/4wFEy0sqXsbW1hf39fQwPD6OpqQkajYb5DSMR7HY7tre3oVQqr7woEkLQ2NgYtXVg0ady3rYmFaruq6uruHnzZlzPIYRALpeju7sbAwMDEAqF0Gg00Gg0ODg4eCRDYzKZkiJPkYwyIOuJQIB9xgpITp8VNxmYaCbM5/PBaDRiZGQEGxsbKC0txZ07d9DY2IiKigocHh4mdehDKpVCoVAkJEKcKEVFRcjMzMTm5iaAtz1Yt7a2MDAwkDJj9tzcXLS2tmJycpLXFN75oCoZlQOBQAClUgmpVHrhuf7gBz8If+1rX1uxWq2/xvzgz3mC54HVQwghckJI7sPvpQB+FsAyIaT44c8IgP8EwBDv2pRSndVqfenDH/6wIxVTbxsbGzCbzVCr1RCJRFAoFGhsbHzqwRVnZxNPGlwul6O/vx+rq6u8d807OzvIzs5OijH243BBNJ8G8LS0NFRXV+PWrVtobGyE3W7HyMgIdDpd1E+Rpf4Wh9PpZP4aBQKBpARWrLMoyQisErG38fv92NrawujoKGZmZiAUCtHf34/u7m7I5fLopkQgEKC4uDjmHptEuXnzJjY3N5kKqF5Hc3Mzdnd3YbFYMDY2FvVgTXWfaGFhIW7evInJycmEAthkB1UchBDU19ejvLwc4+Pj0SGg5eVlfOpTnzo4PDz8OUpp6v6A72GeB1ZvUwzgLULIPAAtznqs/h3APxFC9AD0AAoB/F+JLO52u19fXFz8u1deeSUxoZYYMRqNsNlsUKvVjwQvTzu4CofDmJqaQnt7e9xSD+dLg6Ojownd+Px+PzY2NtDU1BT3cxNhbW0t7mzVVchkMrS0tODOnTtRI97T01Po9XrYbDamAQZrKxvg7fIiS5JRCmQtEsoRiwp7IBDAzs4OxsfHozfxrq4uDA4Oorq6+tKbcmVlZdK1l8RiMSorK7G+vp7U45yHCxq1Wm1KPVgvori4GGVlZXH7CqYqqDpPaWkpWlpaMDExga2tLXzwgx+0WSyWD1JKkzfm+JxHSJ59+TsMSuk8gM4Lfv4zrI5xeHj4pW9/+9udbW1tg5/85CeZf8pWVlbgdrsvnTbhmpw1Gk1Kd36UUszOzqK8vPwJ+4xYEQgEaGhogEKhwNTUFKqqqlBZWRnzhdZgMKCxsTEpja6Pc3x8DL/fn/DvehWEEBQUFGBvby9qVL2/vw+9Xg+ZTIYbN25ALpcn/HtSSpnrTQHvrFIgV35iiVwux8LCAmpqah75udfrhdlsjmpSFRUVxT3RJ5VKIRaL4XK5kmoHVVVVhZGREVRWViZdBy8QCGBubg4ikQiNjY04ODhISnY2HiorK+H3+zE3N3dtKwPwdIIqjoKCAnR0dODnf/7n/Waz+TOUUn1KT+A9zvPAKoVQSiOEkF/48pe/rCkqKmr60Ic+xGT2nFKK5eVlnJycRG+2l8EFVxMTE+jt7U2JptX6+jpEIhGqqqp4r5WXl4ehoSEsLCxgcnISSqXy2hu21WpFOBxGcXEx7+PHgtFovHISkC+UUtjtdrS1tUEgEEAul4NSCqfTGb2Yp6Wl4caNG1AoFHHdpFlPA3L4/X7mN/1klAKlUmlSdNQ4e5tQKASXy/X/s3fmcW2dZ77/vRKSQAixCMS+YzaDwQteAC/Zmja9aZukmU4z6e2SNkv33HSSaadp0txJ26RpFrdN23TSmUnippkm6TRJm9xmszFgAzbGLMbsuwQS2oV26bl/gFRsY8yic+TlfD8ffSwLcd4XkHR+51l+D2ZmZqDT6RAdHY20tDRs3bp1Xe/FvLw8jI6OoqqqKoy7PpPgxU1fXx+qq5f1SV4XOp0OPT09KCkpQUZGBogIra2tmJ6eDotX1XrYsGEDenp6cOrUKWzcuPG8z9NoNBHtxg4EAvjSl75kGR0d/bHD4XiN9w1c4QipQJ4hIodOp9v3pS99afzo0aPhOB5OnToFl8uFLVu2rKgoW61Wh/yiuB5ZodPpMDMzg8rKyrAdMyoqClVVVcjLy0Nzc/Oyw6d9Ph96enrCuv5yOJ1OWK1WTiwQgszOziIpKemMv3VwfEpZWRn27t2LTZs2gYjQ3d2NDz/8EB0dHZiamrqgnxIXhesANxErLlKBjDEwxsJ2XCKC1WrF8PAwvF4vDh48iMnJSSQkJKC+vh47d+5EXl7eui9w1Go1jEYjfD5fWPZ9PtLS0jA3Nwer1Rr2Y/v9fnR1dWF4eBi7du0KNWYwxlBdXY3e3t6wj4NaLYwxbNy4ES6XC4ODg0s+Z3x8HCMjI9i1a1dERBUR4Wtf+5rtyJEjL+j1+sd434AAWCSmeQsAjLHstLS0lg8++CB9rXU/wRNnIBBYk9llsHV727ZtYTXYC2K323Hs2DHs2rWLs7Sj2+1GZ2cnRCIRKioqzlmnp6cHcrkc+fn5nKx/Nl1dXVCpVJwOk+7o6EBWVhaSk5NX9PxAIACTyQS9Xh+qx0pKSgrdFp/UOzs7kZGRseJjr5TW1lZs3LgxrNGw2dlZaLXasIvmtrY2lJWVhYxrV0NQSBmNRhiNRlitVigUilBU0eVycVbn19/fD6lUGpbI8HIYjUb09/dj586dF37yCpmdnUV3dzdyc3ORl5e35GeZTqfD0NAQdu7cGbFaqyCBQACtra3IyMhATk5O6PGhoSHo9fo1zSsMF48++qhj//79b+t0ultJOMFHBCEVGCGIaIIxdt3111//YXNzc8pqR6sErQPEYvGaHcQTExND42+qq6vDGqnwer04fvz4ilJ160Emk6GmpgYajQbNzc3YsGEDMjMzwRiDxWKByWRCeXk5Z+svxu12w2AwcDbUGZj/QDcajatK+YhEIqhUqlDNl9frhclkgtFoxMjICDweD5RKJVQqFQwGAyfDsLmqseLCWylYwL4SYeX1emE2m0NCyuVyIS4uDiqVCkVFRVAqlaH3ptfrxZEjRzgTVjk5OWhtbeVcWCUlJUEsFoelK9Xr9eLUqVNwOBzYvn37soPhgw0AwRFRkSQ4V/Do0aOQSqVITU1FX18f7HY7tm/fzoudy1I8//zznmeeeea4Xq//R0FURQ5BWEUQIuqJior61NVXX/1GS0uLaqXCJlgMLpPJUFZWtq6rN6VSiR07dqC1tRUVFRVhiVQQEdrb21FYWBj27rLzEYyy9PT0YGpqCpWVlejs7ERVVRVvV7fDw8MoKCjgdL3Z2dlVDdNdColEArVaHUpXBgIBWK1WGAwGOJ1OHDlyBCKRCPHx8aHbeucR+v3+S8IgFPi75UJqauoZj7vdblgsFpjNZlgsFtjtdkgkEsTHxyMpKQk5OTnLFnVLJBIwxuDxeDhJEUVHRyMmJoazdO5iysvLcfz48XW9Fqenp9Hb24uioqIVXxyWlZWhqakJycnJvH22nI+oqChs374dzc3NGB8fh0wmw9atWyMWTXvrrbf83/ve9/r0ev1HiWjZnDBjLBvACwDSAAQAPEdEzzDGkgC8AiAPwCiAfyAifoZFXkYIwirC+Hy+ZoVC8eVrrrnmd01NTYkX6rYJBAI4ceIEFApF2NqP5XI5du7ciZaWFpSUlKy7QLSvrw9xcXGcDzg+G6lUis2bN0On0+Hw4cNQKpWcpDiXwuv1Ynp6Gnv37uV0nampqTNSD+FAJBKFTlLp6enYvHkzfD4frFYrzGYzRkdHYbVaQUSIiYmBQqFAXFxc6F8+Oi3Pt+9wdwUSEaKiokK+UHa7HTabDV6vF1KpFAkJCYiPj0dGRgZiY2NX/f5LSUmBXq/nZL4j8Pcidq6FVWxsLBITEzE5OYns7OxVfa/b7Q6VMOzatWtV9WVisRibN2/G8ePHUV9fH7F0W5CoqCjI5XIYjcaQJUwkaG5upjvuuGNMp9PtI6KVFM76ANxHRO2MsTgAxxlj7wL4AoD3iegnjLF/AfAvWMW0EYF5BGF1EWC32/9HpVKl3XjjjT9+5513Es73YREIBHD8+HHEx8ejuLg4rHsIekW1trbC7XYjNzd3TcfRaDQwm83YsWNHWPe3GuLi4iCVShEbG4umpiZUVlZy2oYOzDvd5+bmcpoCCAQCMJvNnHVkLfavioqKCtVgBSEiOJ3OkNiYmJiAzWaDz+cDYwwxMTGQy+WQy+Wh+zKZDGKxmJPfy1oiVj6fD263Gy6XC06nEw6HAw6HA06nM+TvJpPJYLPZkJGRgezs7LCKx6CDOVfCKhi19Xq9nAvekpISNDU1ISMjY0XRTCLC2NgYRkZGQh1/ayEuLg55eXno7u7mtDvxQvh8Phw/fhxJSUkoLy9HW1sbduzYsWw6kwtOnTqFW265RavT6fYSkXEl30NEWgDahfs2xlgvgEwAnwSwb+Fp/4X5CSSCsFolQvH6RURKSsoj11133TcPHDgQf/aVT9BgMzk5mdM5dz6fD+3t7YiLi0NpaemqrsCsViva29tRV1cXsShGsDW7oKAAKSkpsFgs6OrqglKpRFlZGSf78vv9aGhowJ49e8IyWPV8BFv0uepwbG9vR0FBwZpSLIFA4Byh4nA44PF4QvdjY2MRFRUFmUwGiUSCqKio0L+Lb8HOPJFIdMb94IDk4OxLt9uNwcFBFBcXw+fzLXnzeDxwu90hASYWiyGTySCTyUIiMHiTSqWh1/vBgwexb9++cP56Q7+nQ4cOYd++fZxFNwYHByESic7xzOKC4AzUC5nhmkwmdHd3IykpCSUlJeuONBER2trakJWVxWmjyPlwuVxoa2tDXl5eKGJnMplw8uRJTpt1zmZiYgJ1dXW6iYmJfUTUu5ZjMMbyADQAqAAwTkQJi75mIiLuR1VcZggRq4uI2dnZh957773M+++//9af/vSnoRyW3+9HW1sbUlNTOe9ui4qKQk1NDXp6etDe3o7q6uoViQWPx4P29nZs3bo1YqIKALRaLSQSSaioNj4+HnV1dZiYmEBjYyMKCwuRnZ0d1pPa2NgYMjMzORVVwHwakMvCZKvVCqVSuabvFYlEiI2NXbLrz2QyYWxsDFVVVaGIkdfrPUMAeb1euN1u+P1+BAKBMwRU8N+zxVbQzNRisYREWUxMzBmCTSqVQiqVrvpvIxaLORkcHfw92e12ztLUOTk5OHLkCPLz8zlPTRUUFKChoQE5OTlLigmPxxMqTq+urg7bzxy0YGhqakJiYiLnhqWLsVqtOH78OCorK8+oSU1MTMTGjRvR0tKCXbt2cf45aDQacfXVVxs0Gs2n1iGqFABeA/BtIrJGutvyckEQVhcRRESMsa+88MILacnJyVc98MADMT6fD62trcjMzFxzem61MMZQUVGB4eFhHD16FDU1NcsW2wYCARw7dgylpaW81TQthdfrRV9fH2pra894nDGGnJwcpKeno7e3F+Pj42FLDwYCAYyNjaG+vn7dx1oOv98Pi8XCWe2M1+vlLGUX7AhkjEEikYTthBM02ywtLQ3L8RYT7AzkIoUcrLPi6r0ilUqhUChgNBo5cf9fjFgsxoYNG9Df339GJHVx2q+4uBgZGRlhF3lSqRSVlZU4ceIEb/VNer0ePT0957WoSUlJgcfjCaUFubrYstlsuOqqq4xTU1Nf9Pl8R9ZyDMaYBPOi6gARvb7w8AxjLJ2ItAtzcpefwySwJIJB6EUGEQV0Ot2nfvaznx194oknnC0tLcjOzuZNVC2moKAABQUFOHLkyLJGoj09PUhOTo64K/KpU6dQVFR03jC8RCLBpk2bUFlZie7ubpw4cWLdLtuTk5NIS0vj/Oo02NrO1cnDbDZz1mXFhdUCwF1XIMDNMOYgarUaer2ek2MHyc/Px+joKKdrBMnMzITJZAr9vnQ6HRoaGjA3N4f6+vqQ/QkXBLsDz2fWGU7Gx8dx+vRp7Ny5c1lRnJmZifT0dLS3t4OLUhu73Y59+/YZR0ZGvu5wON5cyzHY/B/keQC9RPTkoi+9AeDzC/c/D+DP69vtlYkgrC5CiMir1+s/+tRTT3V++OGHntV23YST9PR0bNq0CS0tLTCZzu26HR8fh9vtDuvA4bVgMBgwNze3ok7E+Ph41NbWIi0tDS0tLTh9+vSaHKuJKGSxwDVTU1OcFTwDl6awCqYDuYBLYRUbGwun08mZKATm01LBmZVcwxhDeXk5Ojs7ceTIEUxMTKCmpgYbN27kpSygtLQU09PTS34+hYPgyDCtVrviLsb8/HwolUp0dnaG9TU6NzeHq666yjQ0NHSv1Wp9eR2HqgPwOQBXM8Y6Fm43APgJgOsYYwMArlv4v8AqEYTVRQoReTQazd79+/e3PfvssxGd45CYmIgdO3ags7MTk5OToceNRiNGR0dXNJCUSwKBALq7u1dllMoYQ3p6Ovbs2QOZTIbDhw9jdHR0VSc7rVYLlUrFeaGq3++H1Wrl1LeHS+8jroQVl3AprID595TRuKIGrjXBGEN2djYmJiY4WyOIy+XCxMQELBYLMjIysHXrVl4740QiETZv3oyTJ0/C6/WG9djBzj+v14vt27evquYuaIdz+vTpsOzF4XDgmmuuMQ0ODv6z2Wx+YT3HIqJGImJEtImIqhdufyUiAxFdQ0QbFv7l7kV6GSMIq4sYInLr9fprH3744Y7f/va3ERVXcrkctbW10Gg06OnpgcPhwMmTJyM6uiHIwMAA0tPT1zSCRCQSIT8/H/X19XA4HDh8+DC0Wu0FrzKJiPNhy0FmZmagVqs5Fa9cDV8GLk1hFayx4go+0oHZ2dmYnJzkLKrn9Xpx+vRpHD16FGlpaaitrcXExARn6y2HQqFAQUEBurq6wnZMh8OB5uZmqNVqVFZWrvr9xxhDZWUl5ubmMDw8vK69OJ1OXHvttab+/v5/MZlMz6/rYAKcIwirixwicun1+qu///3vdz733HPcx/WXQSKRoKamBiKRCAcPHkRZWRnvni1nY7fbMT09vW6BI5FIUF5eju3bt0On06GxsREzMzPnPUkEi4/56EbSaDScpgFdLleouJwL3G73uocM802wfosrkZCcnMy5sJJIJEhISMDs7GxYjxtsEmlsbER0dDT27NmD9PR0xMfHQ6FQQKvVhnW9lZKdnY1AIICpqal1H2t2dhYtLS2oqKhYlyEvYwxbtmzBzMzMGdH+1eB0OnHdddeZTp8+/aDRaHxuzZsR4A1BWF0CEJFTp9Pt+/73v38i0mlBYP6NnpGRgdOnT3My5X6lBOclVlZWhq2bLSb8L7H3AAAgAElEQVQmBlVVVdi6dSs0Gg2ampqg0+nOOcEODAzwUlfm8/lgt9s5NTjlegSK1+uNeFRzLUilUng8Hk6OLZFIIBKJODt+kKATezjw+XwYGBhAY2MjJBIJ9uzZg7y8vDPee6Wlpejv7+e0fux8MMZQVVWF/v7+ZZttliNYNxksUl9skLtWRCIRampqMDIyAp1udU12DocDV199tamnp+e7RqPxl+vejAAvCMKKYxhj0YyxVsbYScZYD2Psh2d9/eeMsQsWcxCRU6/XX/Xwww8f279/f8TE1fDwMEQiEaqqqrBlyxa0t7dH7Ap1YmICCoUiLB9+ZyOXy7F582ZUV1djcnISzc3NoSt/g8EQamnnGp1Ox3ka0Gw2cz4C5VL0x+G6zipou8AlCQkJcDqdcLnW/pHh9/sxNDSEw4cPQyQSYc+ePSgoKFjSSiA6Ohrp6em8dSSeTbDzt729fdXizu/3o6OjAxaLBbt27QprNDo4V/DUqVMrrq1b6P4znT59+p9NJtNvwrYZAc4RhBX3uAFcTURVAKoBfJQxthMAGGPbAKy4InkhLXjto48+2vLkk0+uzydgDej1emi12lCRuFKpRG1tLUZHR3H69GleayvcbjeGhoZQVlbG6ToKhQJbtmzBpk2bMDY2hsbGRnR1dfHWBcl1NyBw5iibcBM09uQSrl53QSNPrkhJSVl1BGMt5ObmYnx8fNXf5/F40NfXh4aGBgQCAezevRuFhYUX9GYqLCzE2NhY2AvJV4pKpUJycnLIFX4lBIePx8fHr9gUebXIZDJs374dJ0+ehM1mW/a5NpsN+/btM/b3939bqKm69BCEFcfQPMFPZ8nCjRhjYgA/BXD/Ko/n1ul0H3nssceO/OQnP+FNXM3NzaG7uxvbtm07I/QvlUqxc+dOAMCRI0fWdWW8Grq7u1FaWsqby3tcXBy2bt2KoqIieDwenDx5EuPj45ymPHw+H+bm5tbshr4Sgu7lXNVAcV24zrWXFZcF7AkJCTCbzZxfkGRmZmJqamrF6zidTnR3d6O5uRkymQx79uzBhg0bVpzOjYqKQkFBwaqETbgpLi6GXq9fUXRoZmYGR48eRVlZGQoKCji9EJDL5di6dSuOHz9+Xg89i8WCvXv3GgcGBr653u4/gcggCCseYIyJGWMdmHexfZeIWgB8HcAbC8MwVwUReXQ63UefeuqpD+677z471x/MPp8Px44dQ3V19ZInYMYYSktLUVRUhCNHjnCe3tDpdPD5fEhPT+d0naWYnJzE1q1bsXPnTszNzeHQoUMYGhpakw/WhZienkZaWtol2w0IcC+sRCLRJWkSCpw53oZLoqKioFKpLhgds9lsOHHiBNra2pCYmIi9e/ciLy9vTdGbnJwc6PX6Ndc6rReRSIQtW7Ysa8EQCATQ09OD4eFh1NbWcu5SH0SpVGLTpk1obW09p8ZOq9Vix44dhoGBgbssFssBXjYkEHYEYcUDROQnomoAWQC2M8b2ALgVwM/XcUyvTqf7xEsvvfTKbbfdZuHixL6wTmg474XqcNRqNXbu3In+/n709fVxciXu8/lw6tQpbNq0KezHvhBBw8Wgd1VZWRnq6+tBRDh8+DB6enrCGuHQaDScD5jlunDd4/FwLqz8fj8nx5bL5ZwLA7VazUs68HxF7EQUith0dXUhMzMTu3fvXrdbevBiq7d3TSPswoJcLseGDRvQ2dl5zteCqT+JRIKdO3fybgeSlJSE0tJStLS0hC7KBgYGsGvXLv3IyMgtNpvtVV43JBBWBGHFI0RkBnAQwFUAigAMMsZGAcgZY6ueybAw/uYr77///tMf+chHzFycBPr7+yGXy7FS9/eYmBjs2rULgUAAR48eDbvzc19fH3JycngduhpkqU5AiUSCoqIi7N27F4mJiejo6EBLS8uSnYSrwev1wul0cpoGBLgvXA9aOXAFlxGroLDgMiLMRwE7MB8lCb6mgPnX19DQEA4dOoTp6WmUl5ejtrY2rI0SarUabrcbZrM5LMdbC1lZWWCMnWGUqtPpcPToUZSUlIRMPCNBamoq8vPz0dbWhtbWVuzdu3d6bGzsWrfbfSgiGxIIG4Kw4hjGWApjLGHhfgyAawEcJ6I0IsojojwADiJakxETEZFOp3u4o6Pjgfr6emM43Zy1Wi2MRiPKy8tX9X0ikQhlZWUoLCw8o5tuvVgsFhiNRuTn54fleKvB6XTCZrMhJSVlya+LRCJkZGSgrq4OpaWl0Gg0OHToEIaHh9dUxBtMA3KN2Wzm1MqBjxorriJWwPyFwnrnSS5HcLwNlz9DkNzcXPT39+PkyZNoamoCANTV1aGqqooTAR8cdXPq1KmImIYGqaysxNDQEGw2G3p7ezE0NITa2lokJydHbE9BsrKy0N/fH/jUpz41rdVqdxHRueE1gUsOQVhxTzqADxljnQDaMF9j9Va4FzEajc/19/d/cceOHYa1GtEtxmq1oq+vD1u3bl2zR9Ti1GBPT8+6Th5Bz6rVjK0JJ0GX9ZWsHewsqq2tRSAQQGNjIzo6OmA0Gld8guEjDRgIBOD3+zltALiUa6wA7uusgPm0EFdz7oD59Pn4+DjGxsYwOTkJtVqNvXv3orCwkPPmj4SEBMhkMl7SnecjGFVuaGiASCSKSOrvfBw4cMBz//3392m12k1ENBrp/QiEB0FYcQwRdRLR5oWZTBVE9MgSzwmLIZLdbn9jZGTkxtraWt16ahs8Hg/a29uxZcsWSKXSde0pmBqMjo5GU1PTmg1FR0ZGoFKpOI2unA+32w2DwbDqYnmpVIqioiLs27cPmZmZGBkZwaFDhzA4OLhs96TX64XL5UJcXNx6t74sVquV89/npdwVCPAjrLiosyIiGI1GdHR04PDhw3A6ndiyZQtyc3NBRLxenJSVlfFuxxKEiDAyMoKhoaGQM/vF4qn2xBNPOO69994TOp1uOxFxnw8W4I1Lzw5ZYFl8Pt8RxthVV1999buvvfZaem1t7ao+RQKBAI4fP46SkpKwpQcYYygsLERKSgo6OjqQkZGBwsLCFX/AOZ1OjI+PY/fu3WHZz2oZHh5eVxs2YwwpKSlISUmB1+vF5OQk2traIJVKkZOTg9TU1DOiglqtlpeORy79q4JcDhGrcIxIWY7Vei4th8vlwuTkJKampqBQKJCTk4OqqqrQazc3Nxfd3d2cR0MXI5fLkZycjPHxceTm5vK2rsvlQkdHB2JjY1FfXw+RSBQqTYhkGpCIcN9999kOHDjQoNfrbyYibu33BXhHiFhdhhDRqenp6Z033XTT6FtvvbWq/Ftvby+SkpI4ObErlUrU1dXB7XbjyJEjK6pdCaYAy8vLOTHtuxBerxfT09PIysoKy/EkEgny8/Oxe/dulJWVwWAw4NChQ+jo6IBerwcRYWpqipcTH9cdgcB89HO9Uc/l4LIrEOAnYhUcb7PWRg+Px4OxsTE0Nzfj2LFjEIvFqK2txdatW5GSknLGBUFcXBwCgQCn/lxLUVxcjOHhYU5sSZZCq9XiyJEjKCgoQGVlJcRicWhuX1dXF+ejhM6Hz+fDZz/7WctLL730ik6n+4Qgqi5PBGF1mUJEEzqdbtuXvvSlU//+7/++ok/siYkJzM3Nobi4mLN9icVibNy4EcXFxTh69CgmJiaWTRFotVpERUVBrVZztqflGBkZQW5ubthmES5GqVSioqIC+/btQ1ZWFjQaDT788ENYLBZ4PB7OUydWq5XzrkOA23E2XKcCuZwXuJjVdgd6vV5MTEzg6NGjOHr0KLxeL6qrq1FfX4/8/Pxla6fCOT9wpUgkEuTk5GBoaIjTdbxeL06cOIHJyUnU1dWd87kRExODkpISnDx5kvfUpN1ux0c+8hHT+++//7Rer7+TiPgfqCjAC4KwuowhIqNer9/5r//6r4e/8Y1v2Ja7sjeZTBgeHsaWLVt4qUFITk5GfX09DAYDWlpaloxeeb1e9PX1oaKigvP9LIXP58PU1BTn6QvGGJKTk1FVVYWCggKkpqZibGwMBw8eRFdXF/R6fdjFg9frhVgs5kQwBuHjxMV1KpAxxnlUDFiZsHK73RgfH0dLSwuamprgcDhQUVGBPXv2oKioCHK5fEVrpaenQ6fT8dKJuJj8/HxotVrOpjNotVo0NjYiOTkZ27ZtO2+kNCMjAxKJZE1jftbK6Ogotm3bZmhvb/8/er3+YbrAm4Mxls0Y+5Ax1rswY/ZbC4/fuvD/wMJINIGLEKHG6jKHiByMsY+88sorPz558uSdb7zxRuLZdTXBWoTt27eveGxFOJBIJKiuroZer0dLSwtyc3ORl5cXEnanTp1CYWFhxDp4xsfHkZWVxWsKUqPRoKqqCrGxsQgEApidnYVWq0V3dzfi4uKQlpaG1NTUdXdzWSwWzuuruE4DAtynAoF5SwSuRwslJiaGoiiLL2xsNhump6cxMzMDYN77qLy8fF2NDSKRCKmpqdBqtWFLca903eLiYvT19aGqqipsx3W73ejq6gIA1NbWrujzoqKiAo2NjVCpVJwPU29oaKB//Md/nNFqtZ8kotYVfpsPwH1E1M4YiwNwnDH2LoBuADcDEIYyX8QIwuoKYOHq6F/i4uKOb9269dm33347OZju8/v9OHbsGCoqKjgdbbIcKSkpqK+vx+nTp9Hc3Iyqqip4PB7Mzc1FxGEdmC/iHxsbQ319PW9rut1u+P3+0N9BJBJBrVZDrVaDiGC1WqHVajE8PBxKj6rVasTFxa06yng5FK4D3KcCgb/XWXEprBhjUCgUoTSwTqfD7OwsYmJikJaWhpqamrD+LnNzc9HR0cGrsALmo2XDw8Ow2Wzr7nolIkxOTmJwcBClpaWrqguNiopCdXU12tvbQ4XtXPCrX/3K9dBDD43o9fpriUiz0u9bGHWmXbhvY4z1AsgkoncBbtPrAutHEFZXEDab7Y+Msb49e/b89T//8z/Tr7/+elFXVxfS09PPa3zJF1FRUaioqIDRaMTx48fhcrmwa9euiH2ATE5OIi0tjbchz8Dy3YCMMcTHxyM+Ph6lpaVwOp3Q6XTo7++HzWaDUqkMdR6uxJXeZDKt2vh1tfAhrPiIWHFZwE5EMJvN0Ov1sFqtaG1tRUZGBlJSUlBWVsZZtDQ2NhYikSgsAmc1LDYN3bFjx5qP43Q6cfLkSURHR6O+vn5N79OEhARkZGSgt7cXGzduXPNelsLr9eKee+6xvvnmm4f0ev1niGjNLrOMsTwAmwG0hGt/AtwiCKsrDCLqZIxt/vznP/+3O+64o/zTn/60tKCgINLbCpGUlIS0tDTMzs6io6MDlZWVnHeunQ0RYXh4GLt27eJ1XY1Gg82bN6/ouTExMcjNzQ35ElksFuj1epw4cQIejwdJSUlQqVRISkpaUmhxPXwZ4E9YrcXZfjXExsaGzWcqEAjAarXCaDTCYDDAbrcjPj4eKSkp2LJlC681hcEi9srKSl7WC5KUlATG2JpsDwKBAEZGRjAxMYGNGzeu+4KwsLAwNDg+XBeXBoMBN9xwg2l4ePiZ2dnZRy5UT7UcjDEFgNcAfJuI1mYCKMA7grC6AiEiPWNsxwsvvPD7wcHBa1988cX4i8WJ2G63Y3p6Grt378bc3By6urogl8tRVlbGW62VVqsNDVrmC5fLhUAgsKYZiIwxJCQkICEhARs2bIDf74fRaITRaMT4+HjIbDQotqRSKWQyGefRwMstFbgWvF4vTCZTSEh5vV4olcrQEF6FQnHG38HlcsHv9/NS15eamorTp0/ztt5iysvL0d7ejt27d6/4dWgwGNDd3Y3U1FTs3r07LHtmjGHz5s04evToiuuzlqOnpwcf//jHZ3U63RcdDse6JmwwxiSYF1UHiOj1dW1MgFcEYXWFsuCf8mmVSnXvjh07vv/OO+8k8TGb7gJ7QmdnJyorKyESiRAXF4ddu3ZBo9GgubkZ+fn5yM3N5VQQEBEGBwdRU1PD2RpLEU5TULFYHEoLAvM/k81mg8FgwODgYGi0TldXFxISEhAfHw+FQhH2OhO32815YTAfqcCoqKgVreH1emGxWEI3q9UKsViMxMREJCUlIS8vD9HR0cseIykpCUajkZfUvEgkQnp6OqamppCTk8P5eotRKBRISEjA1NTUBeu8XC4Xenp64PV6sW3btrBHWmNiYlBaWhpq4Fnr58uf//xn31133aWZmZn5KBGtffQFADa/iecB9BLRk+s5lgD/CMLqCsdgMDwllUpP1tTUvPynP/1JvW1b5Dp4JyYmEBsbi6SkpNBjjDFkZmYiNTUVfX19aGxsREVFBWfpQb1ej7i4uDVFjtaDRqPBli1bODk2YwxKpRJKpRL5+fno7e1FXFwcZDIZLBYL+vv7YbfbIRaLoVQqQ0IrLi4OUql0zScavlKBXEesgPkO1mCXYyAQgMPhgM1mg81mg9VqDf3+gnVwhYWFiIuLW7VYVavVYU1LXYjc3FwcO3aMd2EFACUlJWhubkZ6evqS0adg2m98fBylpaVIS0vj7KIqaEExOjq66iHvRIRHHnnE8eyzz3brdLqPElE4Bj/WAfgcgC7GWMfCY98DIAPwcwApAP7CGOsgouvDsJ5AGBGElQA8Hs8HjLFdH//4x//2wx/+MOuuu+6S8V007na7MTQ0dN4uvKioKGzcuBE2m43T9ODAwEBYW8FXgtPpBBHxJuZMJhPy8/MRHR19xgnc5/OFIi1arRb9/f3weDwQi8UhoaVQKCCXyyGXyy9ozXEppwKJCG63G06nE3Nzc/B6vWhrawvVc8XGxoZ+J+np6eek9NaKSqVCf3//uo+zUmJiYiCVSmGxWHifwymTyUIzNIuKis742uzsLHp6epCamoo9e/bwkqrcuHEjmpqaoFKpVtwBajab8ZnPfMbc0dHxuk6nu4uIwmItT0SNAM73gvpTONYQ4A5BWAkAAIhomDG26eGHH/7Pv/71r9e99NJLCXy4cgfp7u5GSUnJBbt7zk4PZmZmorCwMCwfvAaDATKZjPP01dloNBreZrcFBcNSKamoqCioVCqoVKozHvf5fLDb7bDZbDCZTJiamoLD4YDf7wdjDDExMSGxFR0dDZlMBplMBpfLxYuP1WqFVfB34PF44Ha74XK54HQ64XA44HQ6Q6NlZDJZ6OcKRvGKioo4TUUvHm/DV41ffn4+RkdHeb+gAOaLxxsaGpCTkwOpVAq73Y6enh4AwNatW3l9LwYtGDo6OlBXV3fBz5SWlhbceuuteqPR+A273f4KT9sUuAQQhJVACCJyAPgHpVL5+U2bNj3x+uuvJ3OVnlqMTqeDz+dbcY1RMD2YlpaGkZERNDQ0oKioCFlZWes66Q0MDKCsrGzN379WtFot+ErBrqUbMCoqKlQcfzaBQCAkSoLpsdnZWbjdbtjtdhw+fBjA/N9MJpMhKioKEokEUVFRS94YYyG388X/Bv+uRIRAIBD61263hxoefD4ffD4fvF5v6H7w5vF4QtEmxliogD94i42NRUpKCuRy+ZLpz+npaZhMJl7sP4Iu7Hx5TKWkpIRqmPi0FwHmI45FRUXo7e0FYwwWiwXl5eXniHu+iI+PR2ZmJk6dOnXebslAIIDHHnvM+fTTT4/qdLqPE9EIz9sUuMgRhNVlAGMsGkAD5vPvUQBeJaKHGGPPA9iG+ZByP4AvENEF25usVut/McaaP/axj731wAMPZN97770xXJ1QfD5fyNNmtWsEP5RzcnLQ39+PkZERlJWVrak+xWKxAADv6RCn0wnG2AWLmsNFuAcvi0QixMbGniPWiAiHDh3Cvn37AMyfjILiZrHgCf4/aI56tnAiotD9s0UXYww+nw8ulwtmszkkzmJiYs4RbFKpFBKJZM3CSKFQYGJiYr2/rhWhVqsxMjLCm7BijCErKwtTU1PIy8vjZc0gfr8fTqcTExMTKCsrQ2VlZcTNLwsKCtDS0oKZmRmkpqae8bXZ2VnccsstptOnT/9Rp9N9QxiiLLAUgrC6PHADuJqI7Astuo2MsbcB3Bv0PmGMPQng6wB+spIDEtEAY2zT448//pu33377k6+88krC4qLycNHf34+cnJx11RdJpVJUVFRgbm4Op06dwtDQEMrLy1fllN3f38/p8OnzwWcaEJivCQlX9+Fy+Hy+M6IfIpEI0dHRYReQDocDXV1dKC0tDetxz0Yul8PhcHC6RpCEhASYzeZzxttwSU5OTmisFB9rLnZNz87ORk1NDSYmJiIuqoB5oVldXY0jR44gPj4+9Jo9dOgQ/dM//ZPeaDR+2eFwvBnhbQpcxAhDmC8DaJ5gJEqycKNFoooBiAGwKqM6InJPT09/4ejRo3dWVVXpjxw5EtZ9WywWGAyGVXfhnI/Y2FjU1NSguLgYXV1dOH78+Ir8h+x2e8hUk28iIaz4iMq5XC5eaoT46goUiUSh6BnXMMYQFxcHm83G+VpBgvVkZrOZ03WICBqNBg0NDbBYLKirq0NRURFSU1Ph8/lgNBo5XX+lREdHo7y8HB0dHfD5fPjBD34wd+utt3ZNTU1tFUSVwIUQhNVlAmNMvNCWqwPwLhG1LDz+HwCmAZRivk131dhstj9OTk5u/+QnP3nq0UcfdYTjRBb0rNq0aVPYr1KTkpJQW1uLnJwcdHR04MSJE5ibmzvv8wcGBrBhw4aw7mElOBwOiMVi3oqUA4EA/H4/L3U0Ho+Hl5+LD4PQINHR0XC5XLysFbRd4JOgEzsXEBGmp6dx+PBhzM7OYvv27aioqDijuSE46oYP8boSUlNT4XQ6sWvXLvuvf/3r3+r1+q1ENBnpfQlc/AjC6jKBiPxEVA0gC8B2xljFwuNfBJABoBfAZ9Zx/FG9Xl+9f//+F/bt22da74f+yMgIkpKSOIueMMaQkpKCuro6ZGRkoL29HR0dHeekc4IF15GYlTg1NYXMzEze1rNarbzVkPHV1caHQWgQLmcGnk1KSkrYxuisFJVKBYvFEtYRQUSEmZkZNDY2Ynp6Gtu2bcOmTZuWTP0rlUrExsZieno6bOuvh3fffTdw++23z3R0dNys0+nuDZeVgsDljyCsLjOIyAzgIICPLnrMD+AVALes89jemZmZe44dO/a5qqqqmf/5n/9Z0xnN6XRifHwcJSUl69nOimCMITU1FfX19UhLS8OxY8fQ2dkJp3N+JurQ0BDnLfTnI5xu6yvBZDIt2dnHBZdbKhDgV1jJ5fJQQT9fMMaQnZ0dliJ9IoJOp0NTU1PI/La6uhpyuXzZ7ystLUVfXx9vf9OlcDgcuPvuu6233377MY1GU+31et+N2GYELkkEYXUZwBhLYYwlLNyPAXAtgD7GWNHCYwzAjQBOh2M9h8PxF61WW3H33Xe/f9NNN5lXWxfR2dmJ8vLyCxpMhhPGGNLS0rB7924kJyejra0Nx44dg06n41XcBJmbm4NEIuHc52kx4e4IXA6+IlZ8CmI+hRXw9/E2fJKdnY3x8fE1p+OCNVSNjY2YnJxEdXU1Nm/evGKLj5iYGKSlpWFsbGxN66+Xw4cPU3l5+ewrr7zyoE6n20lEF0f4TOCSQhBWlwfpAD5kjHUCaAPwLoC/APgvxlgXgK6F5zwSrgWJaHZ6evr6d999957Kykrdn//85xVdWms0GkRFRUGtVodrK6uCMYaMjAzs3r071HXV2trK+wmM7zQgMJ8K5Mv0lU+DS76IjY1dtlYv3KjVat7TgVKpFEqlctXvB7/fj9HRURw6dAgGgwHbtm3Dli1b1mTwWVRUhNHR0bCmJC+Ew+HAPffcY/30pz/dPjY2VmMymfbTxVLsJXDJIQirywAi6iSizUS0iYgqiOgRIgoQUR0RVS489k/BLsFwYrfb/6DRaCruuuuuD2+++eZlo1derxd9fX2oqKgI9zZWTdBNfN++fSguLsbQ0BCampowMzPDS/GsVqsFn0OvvV4vxGJx2Actn4/LUVjxWbwOAMnJyZidneVtvSCrKWL3er0YGBhAQ0MD3G43amtrUVlZuS77lKioKOTn52NwcHDNx1gNjY2NtHHjxtk//OEPP9DpdDVENMrLwgKXLYKwElg3RKSfnp6+7m9/+9tXKysrdW+88caS0ave3l4UFhZeFCfckZER5OXlQSQSITExETU1NaiqqoJWq0VDQwPGx8c5q2+x2+2QyWS8pgEtFgtv9VXA5SmsgqakfNX/BM1N+RRzAJCYmAi73R4a7bMUDocDPT09aGxshFgsxu7du1FSUhK213ROTg5mZmZCtZBc4HQ68bWvfc16yy23tI+OjtaYTKZnhCiVQDgQhJVA2LDb7S9rNJqKO++888NPf/rTZpPp70PejUYj7HY7srOzI7jDeXw+H6amppCTk3PG4wqFAtXV1dixYwccDgcaGhpw6tSpsH+4RyINyGfhOjBv7cDH4Fy+4TsdGBxvwyeMMeTk5JxTxE5E0Ov1aGlpQXt7OxISErB3714UFBSEvV5SJBKhtLQUp0+HpSz0HJqbm7Fx40b9yy+//JBOp9u+0igVYyybMfYhY6yXMdbDGPvWwuM/ZYydZox1Msb+FKx5FbgyEYSVQFgJRq/eeeedr1ZWVs689dZbgUAggK6uLk48q9bC+Pg4srKyznvij46ORmlpKfbu3QulUoljx46htbUVs7OzYUkTTk9P85oGBPgtXL+c4buAPRLCCgCysrIwOTkJIoLP58PIyAgOHTqEyclJlJSUoL6+HpmZmZymllNTU+FwOELjpsLBQpTKdtNNN7WPjIzsMBqNTxPRakKQPgD3EVEZgJ0AvsYYK8d8XWsFEW3C/Piw74Zt0wKXHIKwEuAEu93+8tTU1KYvf/nLBz/xiU84JBIJr5Pqz0cgEMDY2NiKZqKJRCJkZWVh9+7d2LBhA8bHx9HQ0IDR0VH4fGuztLFarYiOjuZ92O1ahi+vFZ/Px2u0ijHGm6kk3xGrhIQEWCwW3k0zJRIJYmNj0dbWhsOHD8Pn86G2thabN2/mLfLJGAcnNcsAACAASURBVAuZhoaDDz/8kDZu3Di7EKWqWcvwZCLSElH7wn0b5v0BM4nob4t8ro5i3k9Q4ApFmBUowBlEpGOMXfvBBx/ccuzYsWe++93vJn3961+PjmSKaHJyEmlpaasWNomJiUhMTITb7cbY2BgOHz6MhIQE5ObmIjExccWROI1Gw3saMOgpxVe0kO/6qqBJKB/2HQqFAgaDgfN1giweb8NHR6fP54NGo8HExESoxnDfvn0RizQnJiZCIpFAp9OtuZNYo9Hg7rvvNrW2tnbNzMx8PlzF6YyxPACbAbSc9aUvYd43UOAKRYhYCXAKEZHD4Xh1ZmZmw6OPPvqb8vJyQ3Nzc6T2guHhYRQUFKz5GDKZDMXFxdi3bx+ys7NDKZKBgYELFhkHx3pc7mnASAiry9EkNAjXLuxEBKPRiI6ODhw+fBhOpxObN2/Gnj17AGDZInY+KC8vR29v76qjdl6vF4899phzy5YtE2+//fbt09PTe8MoqhQAXgPw7cXd1oyxf8V8uvBAONYRuDQRIlYCvEBEDgDfZoz98uabb35xz549Jb/4xS8S+PSz0mq1UKlUYTnpM8aQnJyM5ORkeL1eTE1Noa2tDVKpFDk5OUhNTT2n/sRms0Eul/NqjArMD16+nDsC+ZwXKJFI1pwGXitqtRodHR0oKioK63FdLhcmJycxOTmJuLg45OTkoKqq6ozoVG5uLsbGxniZknA+5HI5kpOTMTExcU7Dyfn44IMP6M477zRYLJbfzs7OPkJEYWutZIxJMC+qDhDR64se/zyA/wXgGqG78MpGiFgJ8AoRDczMzOx6880379i0aZPm6aefdvFxoiIiDA4Ohv3kBMyfbPPy8rB7926UlZXBYDDg0KFDOHny5BkF75HoBgSujIgVn6NfoqKieDWvjImJCdt4G4/Hg7GxMTQ3N6OtrQ1isRh1dXXYunUrUlJSzkn5ZWZmQqPRRHww8oYNGzA0NHRBUTs1NYUbb7zRdNtttx0aGhqq0ev13wuzqGIAngfQS0RPLnr8owAeAPCJhYtIgSsYIWIlwDsLV3OvM8be+dGPfvTor371q9t/97vfJdfV1XG2pk6ng1KpXJdx4UpQKpWoqKgAEWF2dhaTk5Po6upCcnIyZmZmOBF2y0FEcLvdiI6O5m1Nt9uNuLg43tbjM2IFzKcD5+bmeI0CqlQqGAyGNdUZ+Xw+TE9PY2pqCi6XCxkZGaiqqlpRM0NUVBRUKhVmZmZ4T2EvJhgJHh4eRnFx8Tlf93q9eOKJJ5zPPPPMrMFguNvr9f6Vo63UAfgcgC7GWMfCY98DsB+ADMC7C+L0KBHdzdEeBC5yBGElEDEWruzuZYw9e8stt7ywe/fu0l/84hcJqampYV9rcHAQVVVVYT/u+WCMISUlBSkpKQgEAhgZGUEgEEBjYyNSU1ORkZGB+Ph4zouC+ewGDOJ2u5GcnMzbenzWWAHznYF2u51XYaVWq6HX61csrHw+H3Q6HaampjA3N4e0tDSUl5evSfDm5eXh1KlTERVWwX00NDQgNzf3jIhoMO1nNpufMxgM/zecEaqzIaJGAEu9abkScgKXIIKwEog4RDTAGKt96623PnX48OGff/Ob30y69957Y8IVXTIYDJDJZBGzexCJRHC73aioqEBqaipmZmYwODgIm82GpKQkpKenQ6VScWJREAn/qss9FahQKMLqrbQSVCrVBc0yXS4XpqenMT09DZfLBbVajeLiYiiVynUJeKVSCZ/PB4fDAblcvubjrBexWIzi4mKcPn0aVVVV6O/vx7e+9S3jiRMnOmdmZr5ARJGZ3CwgcBaCsBJYNYyxaAANmA99RwF4lYgeYowdALANgBdAK4C7iGhFxSgL6cE/McbeeeKJJ+579tlnv/Hggw8m3HHHHdL1FnsPDAygrKxsXcdYD0SEmZkZlJSUQCwWIyMjAxkZGQgEAjAYDJienkZPTw8UCgXS0tKQmpoattEgZrMZ6enpYTnWSrmci9eBeWE1NTXF23rAmeNtgmldIoLNZsP09DRmZmYgEomQmpqKioqKsF9EBIvYI/k+AoCMjAy0trbi8ccft77//vtTMzMz9xDRoYhuSkDgLARhJbAW3ACuJiL7QodMI2Psbcy3GN++8JzfA/gygF+t5sBE5ATwb4yxXzz44IOPPPbYY5/96U9/mnjzzTeL13LVbTabAQDx8fGr/t5wYTaboVQqz4lIiUSiULoweJLUarVoaWmBSCRCcnIy1Go1EhIS1hxxMJvNKC0tDcePsWJ8Ph+vnY98pwLlcjmvJqFBUlJSoNVqIZPJoNfrYTQaQ2J8x44dnM6ezMjIQENDA0pKSngb5H02ZrMZjzzyiP3ll182GwyGb3u93teF7juBixFBWAmsmoUPs6CZj2ThRkQUqjNgjLViHe7DRGQG8E3G2I+//vWv/+yhhx76yM9//nPVVVddtarjDAwMLFnsyicajQYZGRnLPocxBqVSCaVSiZKSErhcLszOzmJ0dBRmsxmxsbEhERYbG7sioRUIBOD3+3l3eQfAq6Ek36lAsVgMIgIRcf5zBgIBGI1G6PX6UIovLy8PmZmZqKio4M3hXiwWQ61WY3p6+oKv5XDjdDrx9NNPO/fv32+em5t7xGaz/fsil3MBgYsOQVgJrAnGmBjAcQBFAH5JRC2LvibBfOfMt9a7DhFpAdzGGNtw2223PVtQULD5F7/4hWrz5s0X/F6bzQaPx4OkpKT1bmPNEBF0Ot2qo0bR0dHIyspCVlYWiAh2ux16vR49PT1wOBxITEyESqVCUlIS5HL5kid4q9XKe6TO7/fzHtHgOxUIzBvFctFtGQgEYDabYTQaMTs7C5fLhcTERKSkpKCgoABNTU0oLS2NiBN6bm4uOjs7eRNWPp8Pv/vd7zyPPPKIxel0/txoND6xENEWELioEYSVwJogIj+A6oUp7n9ijFUQUffCl58F0EBEh8O43gCA6xhjW2+44Ybf1NTUFDz11FOJhYWF5/2ewcFBbNiwIVxbWBMmkwnx8fHriiwEx5rExcWhoKAgdPI1GAzo7u6Gw+GAQqFAUlISkpKSEB8fD5FIBJPJxGvnGjDvk8RnfRXAf8QK+LsD+3qFlcfjgdFoDN18Ph/i4+ORlJSETZs2nVMsrlQqIyKYAYTqtux2O6eNIESE119/PfDP//zPxrm5uZd1Ot0PFiLYAgKXBIKwElgXRGRmjB0E8FEA3YyxhwCkALiLo/WOA9gmFouvbW1t/eUNN9yQ+sMf/jA+Ozv7jOc5HA7Y7XakpKRwsY0Vw8VsQJFIFBJRAEIRLaPRiNHRUVgsFkgkEng8HmRlZWFubu68Ua1wE5xLyCd811gBfxdWq7GV8Pv9sFqtsFgsMJvNMJvNiIqKCkUfi4qKLlgnlZKSAr1eH7Gawby8PIyNjWHjxo1hPzYR4d1338V9991nmJ2dfXd6evo+ItKEfSEBAY4RhJXAqmGMpQDwLoiqGADXAniMMfZlANdjfqQDp2c6v9//HmOs7MCBAze//fbbP9qzZ0/yI488khgcvTE4OIjCwsKIDY8F5k8Uer0e5eXlnK6zOKKVm5sLYL4zr6GhAX6/PxTVkkqliI+PR3x8PBISEqBQKML++7lSIlaxsbHQ6/Xn/brX64XVaoXZbIbFYoHNZgMwH3GKj49HTk4OKisrVx3JVKvVOHHiBO9Gs0HS0tLQ19eH0tLSsNV3BQIBvP7664EHH3zQaLFYGrVa7QNE1B+WgwsIRABBWAmshXQA/7VQZyUC8N9E9BZjzAdgDMCRhRP260T0CFebWBBvrzLGXnv11VevbWhoeKKysjLzhz/8ocrtdqOyspKrpVeE0WhEQkJCRLqoRCIRoqOjz6jtcrvdsFgssFgs6Ovrg91uB2MMCoUCCoUiJM5iY2PXvOdIRKzEYjE8Hg+va8bFxWFkZARerxc2mw02mw12ux02mw1OpxNRUVFQKpVISEhAQUEB4uLiwiJEYmJi4PF44Pf7eStcX4xIJEJaWhq0Wi2ystbcmwJgXoS/+OKLvn/7t38zu1yut6anp39ARBNh2qqAQMQQhJXAqiGiTgDnVI8TUUReTwtdiu8CqGKM7ezt7d2fnp5e/Pjjj8fv3bs3YlGrSM0GBACLxXJOfZVMJoNarT7Dvdvv92Nubi4kDjQaDebm5kBEiImJgUKhgFwuh1wuR0xMzAWHSLvdbt6d3rlMBQZHAjmdTjgcjtDNZrPBZDKhtbU1JEyDBebR0dGcvubWM94mHOTm5uLEiRNrFlZzc3P49a9/7X7qqaesHo/ngF6v/xERnT/8dx4YY9kAXgCQBiAA4DkieoYx9n8BfHLhMR2ALwgpRQE+EYSVwGUFER0FsJ0xVnHbbbc9lpSUtP3RRx9NuvHGG0V8Ro6ICAaDARUVFbytuZiVFq6LxeKQzcNiiAhOpxN2ux0OhwNGozEkKvx+PxhjIaEVHR0NmUwGmUwGq9WK2NhYBAIB3iJ1a+kKJCL4/X643e5zbkERFYyCyWSyM4SlSqWCQqFAc3Mzdu3axXtEUq1WQ6fTRUxYyeVyiMViWK3Wc143y2EymfD00087nnvuOZvH43nWaDQ+TUTWdWzFB+A+ImpnjMUBOM4YexfAT4noQQBgjH0TwA8ACHP7BHhDEFYClyULHYofZ4zl33333f923333feShhx5K/OxnPyvmw7zSYDAgMTExYmaKJpNpXbVdjLFQpGopAoFASIC4XC54PB5YrVaYTCa4XC4MDg4i6N0YdA2XSCSh+0vdGGNgjEEkEp1zXyQShbyjAoHAGfetVmvIgdzn88Hn88Hr9YbuL755vd6QCIuKioJUKg2JQplMhri4OKjVasjlckil0mUjT7GxsaGOTD5ZyXgbrgkWsa8k3a7VavHjH//Y9t///d9Wh8PxmM1m+2045vktWLFoF+7bGGO9ADKJ6NSip8UCEExEBXhFEFYClzVENALgnxhjad/5znce/N73vnfrN77xjbivfOUr0VzO0ItkGhDgfviySCRCbGzsOWuYzWbU1NSEutuIaElxs/j/brcbfr//HMF09v3gumeLL7fbDYfDEeqyi4qKQkxMzDnCLSjswlWbpFAoMDc3x7uwWmq8Dd+kpqait7d3WZf9kydP4rHHHjN98MEHZovF8pDL5XqZK2NPxlge5ssTWhb+/yiA/w3AAmB1rsICAuuECRMBBK4kGGPK+Pj4r0RHR3/r2muvVTzwwAOJ4S5yDwQCOHjwIPbt2xeRiJXL5UJ7eztqa2t5X/vgwYPgu67NbDZjdHQU1dXVvK0JAOPj4/B6vVjOS40rBgYGIJPJkJOTw/vaQfr6+hATE3PGHrxeL15//fXAj3/8Y4Ner+/XaDQPAfiAy9EzjDEFgEMAHiWi18/62ncBRBPRQ1ytLyBwNpHJUwgIRAgisprN5p/NzMzkHThw4B+vv/76o5s3b5599dVXA17viuZFXxCDwQCVShXRmWpcRuMuBN/NApGwWwD+7mUVCYJ+VpEkJycHY2NjAICZmRk8+OCDc3l5ebpvfvObvzl58uT2qampeiJ6n2NRJQHwGoADZ4uqBX4P4Bau1hcQWApBWAlckRBRgIj+ptFodnV0dOz42te+9tvc3FzdAw88YB8fH1/XsSOdBoyE4zowH6mLRAdmJAxCgcgKq/j4eFitVkQy4xAdHY2uri5cd911purq6sEnn3zy/2g0mryZmZmvEtEo1+uz+Rfb8wB6iejJRY8vHrfwCQCRLUgTuOIQaqwErniIaBjA3Yyxb+/fv/8fXnzxxfsLCwtT77//ftUNN9zAVlOTEwgEYDKZUFVVxd2GL4DJZEJ+fj7v63o8ngs6h3NBJGYFAoBUKkW4opyrJTi0OxLjbWZnZ/H888+7fvWrX9l8Pl/j1NTUj4joGK+bmKcO8zNJuxhjHQuPfQ/AHYyxEszbLYxB6AgU4BlBWAlcEjDGogE0AJBh/nX7KhE9xBj7OoBvAygEkEJEs2tdY6FT6QUALzDGNg4ODt4vFos/9rnPfU7+xS9+Mba4uPiCx5idnYVKpYqYd1bQdykSRc1ut5t3c1AgcqlAYF7ULVfAzSUpKSnQ6XS8CCufz4f33nsPv/zlLw1tbW1Wh8PxjM1m+08isnC++HkgokYAS73R/sr3XgQEFiMIK4FLBTeAq4nIvlBX0cgYextAE4C3ABwM52JE1APg84wx+c9+9rNPvfDCC99WKpV5d955Z/xtt90mTU1NXfL7pqamIlpQzHU34HJEUlhFImIFzFsuzM3NRWR2X0pKCk6cOMHZoHEiwrFjx/Dcc8+Z//KXv3gAvKPVap8F0Mpl3ZSAwKWOIKwELgkWPsiDBS2ShRsR0QmAu4JpInJgvgD294wx9cMPP3z7448/fld+fn7iV7/61aSbbrpJHBQygUAAZrOZ9+60xZhMpogVrkdKWEUqFQj8vc4qEsIqJiYmZF0RzojZ0NAQ/uM//mPupZdecvh8vvapqalnALxHRJHJewoIXGIIwkrgkmFhNuFxAEUAfklELXyuT0Q6AE8CeJIxVjQwMHDnd77znc9u37495p577lFt2rQJycnJER38bDabkZ6eHpG1IyWsGGMRFVbBAcuRQKVSwWg0rtuFXa/X4/e//73nueees5jN5vHZ2dn9Ho/ndSKKTHW+gMAljCCsBC4ZiMgPoJoxlgDgT4yxigWH9UjsZRDA/YyxB958882atra2r4rF4k9ec8014q9+9atx27dvj4jAMpvNZwxe5hO3272qESfhIpJCVqFQQKvVRmz9YJ3VWoTV3Nwc/vznPweeffZZw9DQkMXhcPzGarW+SEQzHGxVQOCKQRBWApccRGRmjB0E8FEAERFWi/ZCAFoBtDLGJC+88MK177///teJaNtVV10VddtttyVdffXVvBSTBwIB+P1+SCQSztdaikhFrCJJsMYqUqhUKvT29q74+ZOTk3jjjTe8L774onl0dNTh8/lenZ2dfY6I+jncpoDAFYUgrAQuCRhjKQC8C6IqBsC1AB6L8LbOYKEG5W0AbzPGog4cOFD7/vvv305EN5SVlUlvv/32pBtvvFHM1fDc1Q7FDTdXorAK1ncRUUQiZ8FRPU6nEzExMed8nYhw4sQJvPbaa3N//OMfHXNzcxqbzfaSzWZ7bWHck4CAQJgRhJXApUI6gP9aqLMSAfhvInprYXr9/QDSAHQyxv5KRF+O5EYBYGEmWsPCDYyxko6Ojn948MEHP5uYmJj8mc98RnHLLbfElJeXh+2EHMnCdWDex+pKE1bAvJ9VJH92tVoNvV4f6kZ1uVz48MMP8Yc//MH03nvv+UQi0QmtVvsffr//HSIyh3t9xlg25m1K0jDvHfUcET2z6OvfAfBTrNMORUDgUkGYFSggwDOMsWSpVPq/1Gr1FwCUf+xjH5PceuutCXV1dZDL5Ws+7okTJ5Cfnx8R13UAofmIV9ranZ2dyMzMhEqlisj6FosFTU1NmJmZ8b/00kvGnp4ej0gk+n9arfZFAE1cd/MxxtIBpBNRO2P/v737j436LgM4/n7ujpZdWzootLRjYRUogw3oxljAsaGLgoFkcRo1Ji4ajX/MxR9TE+Pmj5loYhbnojHbkjnFLETUgE7ocG6Rn5ssWWFbkW2tLQf0p4yWckcLd/f9Pv7x/R6rpa2F9XvfHn1eyTftfe/ae5o06dPP8/k8j5ThHTD5uKoe9ZOuXwM3AistsTJTga1YGZNn/h+XzcBmESl++umnP9TQ0PBZ13XXzZ49u2Tjxo3XbNiwoXTNmjUjlndG09/fH1opcDL8gxZWOS7XciGfiVVHRwe7d+/WnTt39r7yyituJBJ59+zZs1v7+vr+BLydzz5TqtoFdPmfJ0XkLeA64CjwON6K8nP5iseYsFliZUyIVPUC8IJ/ISIVR44cuWvLli33Oo5z53gTrUwmQzQaDW3wcyaTCW3TPHgnA8NMrIIeiNzR0cGePXu0oaGh9+WXX3Ycx+kYGBjY0dfXtwtonCw9pkTkBuAW4FURuQfoUNU3wjy5aUy+WWJlzCSiqqeBP/vXJYnWnDlzSjZt2hRfv359yerVqy8mWv39/aGVAMHb1xPGGJ2c3CbyMBLLkpISEonEhH7Pzs5Odu/erQ0NDb0HDhxwXdftGBwc3NHb27sLeG2yJFJDiUgpsA1vxFQWeBhYH2pQxoTAEitjJrEREq3ZTU1Ndz377LP3Oo5zRzweL7311ltlyZIls1auXBlZuHDhZZUPJ0rYG9dz8wLDmNkXj8cZGBi44q/v7u6msbGRgwcPDuzduzfV2tqKiHQMDg7unMyJ1FD+mKltwBZV3S4iy4BaILdaNQ84JCK3q2p3iKEaEzhLrIwZhzGGQNcCW4FZwCHgPlVNBxWHvz9ru38hIsVtbW3LiouLb6+srPxoJpNZEY/HS+vr62XdunXXrlq1KrZixYr3tSl+PMJutRDmWJtcmWs8pcjOzs5cEnVu375959ra2hCRzmw2e6Cnp2cP3u9QopBm8Yn3Qz8DvKWqPwdQ1SagcshrEsBttnndTAWWWBkzPqMNgf4m8LiqbhWRp4AvAU/mKyh/j9Zr/vUEXEy2btqxY8eqqqqqjziOc0txcfGM+vp6Wbt2bfnSpUun1dXVMX/+/Alb4Tl//nzoK1ZhJVbw3qpVbm5kKpWipaWF5uZmDh8+nNq/f/9AIpHQYUlUI3CikJKoUdwB3Ac0icjr/r2HVPX5EGMyJjTWbsGYyyQiceAAcD/QAMxV1ayIrAEeUdUNoQY4AhEpAm4SkRVz5869LRaLLc9kMvOLioqumT9/vi5fvrx4+fLlZYsXL47U1dUxd+7cy9oIfvToUSoqKqiqqgruhxhDY2MjixYtyuupyHQ6zbFjx2hubmbfvn1OIpFINTc3Xzh9+rS6rtsfi8WaU6nUob6+vsN4SVT7VZBEGWP+D1uxMmachg+BBlqBM34zUIB2vGPmk45fnjzsX5tz90UkcuLEiXn79++vmz59+pLZs2ffBtyUzWarS0pKptXV1bFs2bLptbW1pTU1NVJTU0N1dTVVVVX/s9p1NZYCU6kUXV1dF6+TJ09mWlpaUk1NTZn29nYymczAtGnTjqXT6Td6enoagWagRVX7JjQQY0xBscTKmHEaPgQaWDLSy/Ib1fujqi5wwr9eGvqciBS3trbW7tq1a1EsFps3a9ashcXFxbWqOi+bzc6JRqPFRUVFscrKSq2oqChbvHhxdsGCBSU1NTWR6upqZs6cSWlpKWVlZZSWlgZ6Ym88pcB0Ok0ymSSVSpFMJjl16hSdnZ20t7dfSCQSA8ePH8+0t7dz5swZyWQyGRFJxmKxbtd1T5w7d67tzJkzbcBJ4B2gy1afjDEjsVKgMVdARH4IDADfoQBKgUHxV/Eq8UYOVYtIdUVFxaLp06fXRiKRWa7rlrmuW+o4TjwSicQikUg0Go1GIpFINB6Pa1lZmc6YMYPy8vJIeXl5pKSkJBqNRiUajRKNRiN+by6JxWKiqjiOo9lsVl3XVcdx1HVdMpmM293dXTQ4OHghlUplkskkyWRS0uk0rus6juO4rus6QDoajZ6LRCJJIOk4TmcymWxNJpPHgU68JpddwNlCSppGGykjIo8AXwZyTbZs35MxeWCJlTHjMMIQ6L/jDYH+PLBtyOb1N1X1iTBjLQT+SbI4UAqU+VcpcA0gQG4mZO6K4iUNI10OkPKvZO5jkKczJ5PRRsoAnwZSqvqzUAM0ZoqxUqAx4zPaEOijwFYR+THe/qVnwgyyUPgrQuf8qyfkcAraGCNljDEhsBUrY4y5SvgjZfYBN+O1AvkCcBavHce3bGO9McELZ7CYMeayiMj1IrJbRN4SkX+JyNf9+ytE5J8i0iQiO0QknCnMJnRDR8qo6lm8fmoLgHq8Fa3HQgzPmCnDVqyMKQBj7KP5HfBtVd0rIl8EalX1+2HGavLPb1q7E3gh1/182PM3ADtV9eY8h2bMlGMrVsYUAFXtUtVD/udJILePZjFe6QfgReCT4URowjLSSBn/fvWQl90LHMl3bMZMRZZYGVNg/NWHW4BX8f5Y3uM/9Sng+nCimnpGK8/6z31VRN7x7z8acCi5kTJ3i8jr/rUReNQvEb8JfBh4MOA4jDFYKdCYguLvo9kL/ERVt4vIjcAvgQrgr8DXVLUizBinijHKs1XAw8AmVb0gIpWq+p8wYzXG5I+tWBlTIPx9NNuALaq6HUBV31bV9aq6Evg93pidIGMYbRN9vYgc9FdLXhOR24OMYzIYozx7P/BTf0A2llQZM7VYYmVMARhjH02l/zECfA94KuBQsnjH9pcAq4EHRGQp8CjwI1WtB37gPw7MGAneH4aUwxIi8nqQcQyJ5wbeK8/WAXeKyKsisldEVuUjBmPM5GANQo0pDLl9NE1DkoWHgEUi8oD/eDvw2yCDGKMZpQK5Vg/leCNigpRL8C6W4UTkRVX9TO4FIvIY0B9wHJe0ORCRGDATL/FcBfxRRD5QSGNyjDFXzvZYGWOuyLBmlNcBL+CNo4kAH1TV43mM5TngV6r6ov9Y8AZL362qLQG+7yVtDkTkb3ilwD3+41ZgtaqeGvUbGWOuGlYKNMZcthGaUd4PPKiq1+OdPsvbaJ9hZbicO4GegJOqEcuzwF+Au/3X1AFFwLtBxWGMmVxsxcoYc1lGWaXpB65VVfUTjn5VDbwL/PBTkkPuPwn8W1UD6zYuImuB/UAT3jBo8MqzLwG/wet4nsZr4PqPoOIwxkwutsfKGDNuY6zSdALrgD14qzWBrRQNieWSU5L+/RjwCWBlkO+vqgfwSp8j+VyQ722MmbxsxcoYM25jrNKcBX6B98/aeeArqtoYYByCN86nV1W/Mey5jwHfVdV1Qb2/McaMxhIrY0zBGS3BU9XnRWQzcFBVg249YYwxl7DEyhhjjDFmgtipQGOMMcaYCWKJlTHGGGPMBLHEyhhjjDFm2g0qogAAADNJREFUglhiZYwxxhgzQSyxMsYYY4yZIJZYGWOMMcZMEEusjDHGGGMmiCVWxhhjjDET5L9jBc/SeEHovgAAAABJRU5ErkJggg==\n",
        "text/plain": [
         "<Figure size 720x720 with 1 Axes>"
        ]
        "text/plain": [
         "<Figure size 720x720 with 1 Axes>"
        ]
@@ -7444,12 +8896,14 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 138,
-   "metadata": {},
+   "execution_count": 132,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
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\n",
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\n",
        "text/plain": [
         "<Figure size 720x720 with 1 Axes>"
        ]
        "text/plain": [
         "<Figure size 720x720 with 1 Axes>"
        ]
@@ -7500,12 +8954,14 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 139,
-   "metadata": {},
+   "execution_count": 133,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
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\n",
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\n",
        "text/plain": [
         "<Figure size 720x720 with 1 Axes>"
        ]
        "text/plain": [
         "<Figure size 720x720 with 1 Axes>"
        ]
@@ -7556,12 +9012,14 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 140,
-   "metadata": {},
+   "execution_count": 134,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [
      {
       "data": {
     "outputs": [
      {
       "data": {
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G0A5vgVUrY6wjxIfA4XA45+EeK841Tw9VzzUAPgaQDuAsgDsZY03hsjHSEaqBG3yvqKio1NjY2DSpVBovEoniiCjG4/GoPR6P2u12K0QikUTkRSyRSERKpdITExMDlUoFiUQCsVhMYrEYYrEYIpGIxGIx2traohUKRZvH42Eejwdutxtut5u5XC44HA60tLTAarVSR0cH3G63x+PxuN1ut4eI2sVisVUkElmJqIUxZnG73c12u72uqampFEA1gCrhrznUcyFezQjhyP0AKhlj+eG2h8OJBLiw4lzz9FD1/M/wzgm3nIieAhDPGPttuGwMF4I3KRVAGgBDdHR0WmxsbH+JRGJyu91Gt9utkUgkUqVSKTIajSwtLU2Snp4uT01NVej1elKr1VCr1VCpVOf/RkdHQywWX7YtmzdvRl5e3mV9hjGGjo4OtLa2orW1FVar9fzfpqYmVFVVOUtLS21lZWUdFRUVzGw2k9PpdHo8HrtUKq0FcM5ut5eYzeYzwsjNKgAljLHWyz6AHyFE9ASA6wDEcGHF4XjhoUAOp3tuBZAnLL8H75D2H6WwEqZISQCQLRaLByQmJo6SSqXDnE6nyWQyRaWlpUGn08Xl5ua6U1NTFQaDAUajEQaDARqNJqIrwxMRoqKiEBUVhYSEhO52kQKI7brS4XCgpqYms7q6GtXV1aisrHQfO3bMWVVV1VFSUtKenJzsBtAkFouLmpubD7S2th4DcBJe0XVNhCKJKAXAbAB/BPBEmM3hcCIGLqw4nB+qnjMAKxljbwLQM8aqAYAxVi0U7ryqISIJvBM6D0pISMhVKBQjnE5n/5SUFJVer6chQ4ZIcnNz1Tk5OdLs7GykpaVBIvH+RGzfvh1jx46FVCoN6zGECrlcjvT0dKSnp/tWiY8dOybW6/XyxMREAEBzc3PSqVOnBp48eXLu0aNHrYcPH7adPn2aDAaDUyKRVDPGvq+vr9/X0dFxAsBhxlh9mA4nWLwK4Dfw5sZxOBwBLqw4nG6qnofboCtFmJx3sEQiuS4pKelGt9s9ymQyxQ4bNgyjR49WDR48WJGdnY3MzEwoFIpe21MoFLDb7deMsOoOm80GpVJ5/n1cXBxGjx6N0aNHA4BKeIExhpqaGuPJkydHFRcX33vw4MGWPXv2OA0Gg1sikZTYbLbNjY2N2wEcEArCXnUQUT6AOsbYASLKC7c9HE4kwYUV55qnc9VzIvJVPa8lIoPgrTLAOydbREJEMgCDZTLZaJ1ON83lco1KT0+Pyc3NxQ033BA3evRoaW5uLlQqVZ/7UCqVsNlsiImJCZzhVxl2u90vEUpEMBgMMBgMmDx5sghAHOAVXKWlpUkHDhyYsGPHjpZt27Y5jEajWywWn7Xb7VvNZvM2eMVWTZAPJRBMBPATIpoFQA4ghog+YIzdG2a7OAAOHDigk0gkbwMYgmurELgHwDGXy/XAqFGjwvabzYUV55pGqHQuYoy1dqp6vgzAegALASwX/q4Ln5UXQkRJRDTZaDTe5na7x6Snp6tHjBhBN9xwQ+yYMWOkw4cPR3R0dED79HmsrmUYYxCJ+n6PIiJkZGQgIyMD8+bNi4E34Rtnz541HDhwYPyOHTse3rZtm8NgMHjEYvHZtra2jc3NzRvhFVuugB1IAGCMPQ3gaQAQPFa/4qIqcpBIJG8nJSUNTExMbBKJRNfMCDWPx0P19fWDampq3gbwk3DZwYUV51qnp6rn+wD8k4j+C0A5gHnhMpCI9IKQmut2uyeMGDEiKj8/P3r69OnRo0aNuiA8FSyUSiXq639sKUL+43K5+jSSsTeICP369UO/fv1wxx13nBdbZWVlSdu2bRvz+eefP7pr1y6WkpJS1traur6lpeUrAN9FmtDiRBxDrjVRBQAikYglJiZaampqhoTTDi6sONc0jLESAMO7WW8GMC30Fl0spHJzcxWjR4+OW7BggWTMmDGIiooKuU3XusfK3zBgICAiX+K8aMGCBQkAUF5envjvf/975IYNG546fPiwNSUlpdxqta63WCwbARwMp9BijG2Gd9QsJ3IQXWuiyodw3GENf3JhxeGEGSJSi0Si6UajcZ7L5Zo4YsQI+ezZs5UzZsyI9gmpwsJCTJw48YpCUVeCL8fqWsXS2gZpVPA9gz2RlpaGG2+8UZSfn69MTU1VlpeX6woLC0d+8cUXi3fv3u1JSUkps1qt6ywWy1oA3/Mip5xwc/r0aen8+fP71dfXS0UiERYuXFj/7LPP1tXW1ornzJmTUVlZGZWcnNy+bt26ksTERPfBgwflixYtSj9+/Ljyqaeeqly2bFmtr63k5OSh0dHRbpFIBIlEwo4dO1YUzmPrDS6sOJwwQERp0dHRc2NjYxdkZmamzpkzR3HLLbeoxowZA7lcftH+sbGxsFgsiI+PD4O1gFgshsfjCUvf4aTd6cGuYiu2HXfB44nBqdZGjMyMRrpOBlGI63c1NDRg+HCvczUtLQ0LFy4ULVy4UAsAZWVlid9+++3If/zjH48dPnzYZTQaN1VXV/8dwLZrpa4WJ7KQSqV4+eWXKyZNmmRramoSjRgxYtCsWbNa3nrrrYS8vLzWF1988dTvfve7pCVLliS9/vrrlTqdzrVixYryNWvWdPsjt2XLlpMGg+GqCIFzYcXhhAChgvnIhISEn0okkjmjR49WzZ8/P/a2226TmUymXj+fkJAAs9kcNmEFACKRCG63Oyi5RpGG082w71Qbth1vRVu7B8kxLsSrZThZ5cCRMjviVWKMzIjGiH5KxCiDfz48Hg8cDkeP+XQmkwmLFi0SLVq0KLG9vR1btmy57+OPP77lq6++cqWmph6pra191+l0buDTMnFChclkcppMJicAxMfHezIzM+3l5eWyjRs3xm3ZsqUYAAoKCsyTJ08eAKAyOTnZlZyc7Fq3bl1cWA0PAFxYcThBgogUAKYajcb7k5KSrh8zZox4/vz52ptuuokut2yBVqvF0aNH0b9//+AY6we+PKsrKdsQ6bg9DIdKbdh8rBUWmxv99FG4cVgM6sqOIjs7G3KFCscr7Dhwpg3/OdKCb4+2IMsQhVGZ0cg2yiEWBceLZbFYEBt7UYH4bomKisKMGTMwY8aMeMYYjh49Ou2TTz4Z//HHH7clJyfXWq3WD1taWtYwxk4HxVgOpwvFxcWy48ePKydPnmw1m80Sn+AymUzOxsZGv3TItGnTsogIixYtqv/Vr37V0PsnwgcXVhxOACEilUwmuz0xMfFBk8mUnZ+fL7vzzjtjJ0yYcL6KeV9QKpWw2+1gjIVtChlfntWPUVh5GMPxcw58e6QFDa0uJGuluG1sHDKTvGHZs0U2KBQKSCSE4elKDE9XwtzqwsGSNhwstWH1tkao5CIMT1diVKYSCTGBLaRqNpuh1Wov+3NEhGHDhmHYsGHKpUuXKqurqxPXr1///IcffviEwWBweDyez+vq6t4EcITnZf04afrss1RnXV1AEwSlOp0tfs6cc/7sa7FYRHPnzs1cvnz5OY1G06d8gh07dpxIT093VlZWSqZOnZo9ePBgx80332ztS1uhgAsrTsRARGIA+wFUMsbyiWgqgP8FIANwAMB/ReIwc6HK+fTk5OTFJpNpxIIFC5Tz58+PzsnJCWQfiImJgcViQVxceDzlP8aRgYwxnK5uxzdHWlDd5ERijAQ/vV6DnGT5BQLW7XZfJIy1agluHB6LKUNjcLragQNnbNhVbMWOE1akJcowKkOJwWkKyCRXPuDAbDZjyJArH0FuMBhQUFAgKSgoSLTZbNi4cePDb7zxxp1Hjx5t02g07zU1Na1ijJVfcUchQJg8vRWAG4CLMXZdeC3idKW9vZ1mz56dOW/evMaFCxc2A4BWq3WVlZVJTSaTs6ysTKrRaHr9TU9PT3cCQHJysmv27NnNu3btiubCisPxj8UAiuCt4iyCd/LjaYyxk0S0DN5CnavCaaAPYeLiMQaD4VGDwTDjlltuiXrwwQdjR40aFTSPki/PKlzCSqlUoqnpx5OiU1bfjm8Ot6CsvgNx0WLMHRePYSYFRF3CeR6P55LXVCwiDEhWYECyAq12Nw6V2vBdiQ2f7WnGhgMWDDUpMDIzGskaaZ++G4yxi6bTCQRKpRJz586luXPnJjQ3NyesWbPmd6+//vrDRqOxzmKx/D+bzfaPqyAnawpjLKLDQuHGX89SoPF4PLj77rtN2dnZjueee+78CL+ZM2c2r1y5Uvviiy/WrFy5UnvTTTc1X6qdlpYWkdvtRnx8vKelpUVUWFgY8/vf/74q+EfQd7iw4kQERJQCYDaAPwJ4AoAWQDtj7KSwyyZ4Kz2HVVgRUVZCQsJDer3+p+PGjZM//PDD2mnTpl1RmM9ftFotvv/+e2RmZga9r+5QKBSoqoro3zO/qGly4psjFpysaodKLkL+dbEYmRENibh70XM5NazUCjGuH6TGpIEqlNV34LsSGw6ftWP/GRv0sRKMzIzG8HQFlFH+J7xbLBbExMQENQQcFxeHBx54QPLAAw8kVlRUJL7//vsvv/POO0tTUlJOVFdXv+rxeP7NGGsPmgGcHx2bNm1SrV27VpuVlWXPyckZBABLly6tXLp0afWcOXMyTSZTgtFo7Fi7du0ZACgvL5eMHj16UFtbm5iI2MqVK/VFRUXHampqJHPmzOkPAG63m26//XbzHXfc0RLOY+sN4mF1TiRARGsAvARADeBXAG4BcBbA7Yyx/US0AsBUxtjQMNimi4uLW6hUKh9KT0+PfeSRR7S33XabKNDTxvQGYwybN29GXl5eWPKsnE4n9uzZg0mTJoW8bwDnj72vmFtd+PZIC46W2yGXEiYNUmNcdnSvobr6+nrU1tb2ORTn6PDgaLkd351pQ2WjE2IRMDBFgZEZSmQkRfVatuHMmTOQSCTwZ/RooDl69ChWrVrVumbNGodYLN5TXl7+v/CWcAh77Q0iKgXQBIABWMkYezPMJkUMhw8fPjt8+PBr1pN3+PDhhOHDh6eHq3/useKEHSLKB1DHGDsgzDsGxhgjorsBvEJEUQC+BhCy/CohFDnNaDQ+k5OTM/CnP/1pXF5envSGG24IlQnd2QS1Wo2Wlha/R4gFEqlUCpcr4lLcesVic2PLsRZ8V2KDWES4YZAKEweqoZD5l/t0pVXX5TIRRvePxuj+0ahpcuK7kjYcPmvDsXI74qLFGJGhxMh+SsRGd/9z3NDQgMGDB/e5/yth6NChePXVV9XLly9Xr1y5Mn/37t0TCgsLHVqtdlVjY+P/Y4zV9t5K0JjIGKsiIh2ATUR0gjG2NYz2cDgAuLDiRAYTAfyEiGYBkMObY/WBMKnr9QBARDMAZAfbECJKjI+Pf1iv1z80ffp05RNPPBE/YsQIeDwebNmyBR6PJ2zVz4Ef8qzCIax8hHNk4uXQ1u7GtuNW7D1pBQMwOisaNwxSQ624vLpTNpstYOc7KV6KWaPiMD03Ficq7DhwxobCo63YfLQVmYYojMqIxoBk+fmwpC+/KtTe0a5UVVUhPz8fixcv1litVnz44YdPvfLKKw8nJycfqaqq+iOAwlCPKmSMVQl/64joMwBjAHBhxQk7XFhxwg5j7Gl486cgeKx+xRi7l4h0wo9mFIDfwpt/FXCERPRJRqPx2aysrNzHH388bsGCBVK1Wn1+H5FIhISEBNTV1SEpKSkYZviFVqtFUVERMjIywtK/QqGAw+EI2bx5faHd6cHOE1bsPGFFh5theLoSU4aoEa/q28+d3W4P+DWXiglDTUoMNSnRZHXhoJDw/vGORiijRMhNV2JkphJyskOtVoddyFZUVGDs2LEAAJVKhYKCAmlBQUHC/v37p7788su5hYWFbfHx8a83Nze/EYqEdyKKBiBijLUKyzMALAt2vxyOP3BhxYlkfi2ECUUAXmeMfRvIxolIGR0dfZ9er//1+PHjY5966intmDFjeryJpaWlobi4OKzCSqVSoa2tLWxeI4VCAZvNFpHCyulm2HvKim3HrbC1ezAoRY6pw2Kgi72ymlLBGJHXmXiVBFOHxiBvsBpnatrxXUkb9pyyYmexFYkqD8aYEoLWtz9YLBbI5fJuJ/++7rrrsHr1ao3FYtG8++67f1ixYsUvjUZjYXV19QuMsaNBNEsP4DPhf0AC4CPG2MYg9sfh+A0XVrhojvMAACAASURBVJyIgjG2GcBmYfnXAH4d6D6IqJ9er/+N0Wi8/YEHHoh+5JFHlHq9vtfPxcbGwuFwoL29vdubTCggIqhUKrS2tuJyq7cHAl+R0L4UqwwWvmrphcda0WJzIzPJWy09WSsLSPtOpxNSaWALfnaHSETIMsqRZZSjzeHGobM2bDnaiC2nZRiW4/E7JyzQlJeXIy0t7ZL7xMbG4vHHH4967LHHEr/55ps7X3jhhakGg6HabDa/4HQ6Pw10/TnGWAmA4YFsk8MJFOFLFuFwQgwRjTIajYXDhw/f+9e//vWhs2fPJi5dutQvUeUjJSUFFRUVQbSyd7RaLcxmc1j69lWAjwQ8jOFomQ2vbajFur3NiFGIcP/UBCyckhAwUeVLGwq1dzBaLsaEASoMia2ErYNh43eWkPbvw+PxoKGhATqdzq/9RSIRZsyYga1btybs2LFj6EMPPfSWXq8vj4uL+40QsuNwfvRwYcX5UUNephgMhv15eXlfffrpp3mHDh1KuPPOO0V98UJEgrDyJbCHA18oMJwwxnCyyoE3NtbjXzubIBYR7rlegwenJyJDH1hPosPhgFwuD2ib/mK1WmGIl2LSIDUOltpwssoRchtqamqg0+n6NGAjIyMDr732WszJkycNv/3tb58zGAwliYmJLxFR+GYS54SM06dPS8eOHZudkZExuH///oOff/55HQDU1taKJ0yYkGUymYZMmDAhq76+XgwABw8elOfm5ubIZLKRS5YsueBpt6GhQXzTTTdl9OvXb3BGRsbgb775JqJFOhdWnB8lRCSSSqW3JSUlHb/tttvWbNq0aVRhYaF23LhxV9SuTCaDUqlEc/MliwUHFbVajdbWVoR4EBaAH0KB4eJsXTtW/acBH2wxo93lwe3j4/HITTrkpCiC4lW60lILV0JDQwO0Wi3yBquhi5Vg/d4m2DtCWz7q3LlzSE1NvaI2YmJi8PTTTytKSkp0S5cufSItLa1Yr9e/QUSGAJnJiUCkUilefvnlipKSku/37dtXtGrVKt2BAwfkf/jDHwx5eXmtZWVlx/Ly8lqXLFmSBAA6nc61YsWK8oKCgotKeDz00EOpM2bMaCktLf3++PHjx3Nzc0P/lHEZcGHF+VFBRJLo6OiFer3+zL333vt/O3fuzPnss880gZhnzUdaWhrKy8M3nRoRITo6GlZr6KfKkslk6OjoCHm/u09a8W11Ft75TwOarC7ccl0cfjFLj+HpyoumoAkkwU5cvxRmsxkJCQmQiAlzxsbD6vCENCTocDjQ0dERsFw+uVyORx55RHbmzJnEv/zlLw9kZWUdMRqN/yCi8EwlwAkqJpPJOWnSJBsAxMfHezIzM+3l5eWyjRs3xhUUFJgBoKCgwPzll1/GA955ACdPnmyTSqUXPDE2NjaK9uzZo3788ccbAEAul7OEhAR3qI/ncuDCivOjgIgUsbGxj+v1+rKCgoK/HT58OP3dd9+N7devX8D7SkxMRENDA9zu8P1vhyvPyucVCrW3bMMBr6CYPjwGi/P1GJ3V8xQ0gSRcwooxhtbWVvhKfiRrZZg0UBXSkOC5c+eQkpIS8HYlEgnmz58vLi4uTnjzzTfvHD58+G6j0biRiIYFvDNORFBcXCw7fvy4cvLkyVaz2SwxmUxOwCu+GhsbLzmI7sSJE1EajcY1b9689IEDBw666667TC0tLRGtXfioQM5VDRHFaDSaJ5OSkgoefvhh9eLFi5XBLp4pEomQlJSEmpoaJCcnB7WvnkhISMDp06eRnp4e8r59XqtQjowckqZA0bk2XD9I3fvOAcRutyMhIfTlDtra2hAdHX1BeDNvSAyKKhxYv7cJj87SQx7EUYKMMVRWVmLixIlB64OIkJ+fT/n5+Qnbtm2b+fTTT48yGo2nqqurf8UY2xm0jq8xvit+P7XFVhXQp4MYpdE2csACvyZ3tlgsorlz52YuX778nEajuexYtsvloqKiIuWKFSvKp06d2rZo0aLUZ599NmnFihURO3FpRKs+DqcniEiu0WieNhqNp5YsWfLbkpIS/ZIlS4IuqnykpaXh3LmwTBoPwJu30tLScs3kWbU7PVBKQh+CDJfHypdf1RmJmDB3XDxaHR5sPBjckGBTUxPUanVIykwAwPXXX4/t27cnbNiwYfyMGTM+NxgMu7gH6+qnvb2dZs+enTlv3rzGhQsXNgOAVqt1lZWVSQGgrKxMqtFoLlmKIz09vUOv13dMnTq1DQDuuuuupsOHD4cnPu8n3GPFuaogIrFKpVqUlJS09JFHHol78sknleG48alUKrhcrrAlNxPReYET6ulOFAoF7HY74uNDN7jL6vBAJgp96DVcNcvMZjP69+9/0fpkrQyTclTYVmTF4FQFsozBGbEYiKT1vpCbm4uvvvpKs2/fvnE///nPvzUYDLtramp+wRgrDbkxPxL89SwFGo/Hg7vvvtuUnZ3teO65584npM+cObN55cqV2hdffLFm5cqV2ptuuumSI4HS0tJcSUlJHYcPH44aPnx4+9dffx0zYMCAiE5e58KKc1VARCSTyX5iMBhemzlzZsLLL78s12g0YbUpNTUV586dQ3Z20Kcw7BatVouGhoaQC6tweKysDjdUotBOAB2uGlaMMbS0tPSYNJ43NAYnKh1Yt68Zj96sC3hI0O12o7GxEcOGhc9hNHr0aOzZs0f75ZdfznriiSemJiUlfVxbW/tbxlhd2IziXBabNm1SrV27VpuVlWXPyckZBABLly6tXLp0afWcOXMyTSZTgtFo7Fi7du0ZACgvL5eMHj16UFtbm5iI2MqVK/VFRUXHNBqN529/+1v5/PnzMzo6OigtLa199erVZ8N5bL3BhRXnIohIDGA/gErGWD4RTQPwP/CGjq0A7meMnQ6hPZOSkpLemDJlSvJLL70UV1JSApVKFarue8RoNGLHjh3IysoKy/QyCQkJKCkpgclkCmm/SqUSTU1Bnw7uPB7G0ObwQBMdWo9VqCqud8UXfuzpOyUVE+aMi8dbm+rx1SELbh0TWM9hdXU1kpKSwj4/IREhIyODNmzYoNi9e/eCp59+Ol+n0/1ffX39MsZYa5hsigPwNoAhABiAnzHGdoXDlkhn5syZVsbYge627dq162TXdWlpaa7a2toj3e0/YcIE+7Fjx4oCbWOw4DlWnO5YDKDzl/h1APMZY7kAPgLwTCiMIKKhBoNh+/Tp09cVFhYO/uijj+JMJhMyMjJw+nTIdF2PSKVSqNXqkIqMzsTGxsJiCX1Fbl8oMFTY2z3wMEAWYo9VJOVXdSVFK8PEHBUOnLHhdHVgoyL+TGETCtrb21FTU4P09HTcc8894tOnTycsWbLkF0aj8VR8fPyvhcnZQ80KABsZYznwTqlz1dzsOaGDCyvOBRBRCoDZ8D6V+WAAfHGJWABBHY1BRCaDwbB+1KhRhWvXrp349ddfa3Jycs5vT01NRV1dHRyO8IfZw1nTiojCUgldLpeH9NxbHd6BRFEhzrEKl7Aym81+zcU4ZWgMEmIkWLe3GY4AFQ612WxgjIU8vNwdp06dQv/+/c9XfZdKpXj00UejTp48qV+8ePFzer3+jEqlup+IQnIfI6IYADcAWAUAjLEOxlj4KgVzIhYurDhdeRXAbwB0/qV+AMAGIqoAsADA8mB0TETRer3+b1lZWfvfeeed2fv27dOOHTv2ov1EIhGys7Nx8uRF3uSQk5CQgKamJrhcofWm+PDlWYUSkUgU0tGIVodXUMnEoTnHLubGGUcNtjtPok4R+nkRLRYL/BndKhUKh7bY3fjqUGA8l+FKWu+K3W6H2WzutpxJdHQ0nnvuOeX333+ffP/996/Q6XTFRBS8uhA/kAGgHsC7RHSQiN7m8x9yuoMLK855iCgfQF03cfFfApjFGEsB8C6AvwS4X1IqlXfp9fpTzz777INFRUUJN998s+hSOR4GgwHNzc1hn7eOiGAwGFBdXR2W/sM1b6BEIoHT6QxJX1a7V+MHc1Rgk8uKvdZT+MC8BS9Vf4L3zIU4JqnGf8QnUGyvDFq/XbHZbFAoFH7PzZeaIMOEAYEJCTLGUFVVBaPReEXtBILi4mIMGDDgknleWq0Wr732Wsz27dv7T5o0aX1SUtJaIvJ/RvXLRwJgJIDXGWMjALQBeCqI/XGuUriw4nRmIoCfENFZAP8AMJWI/g1gOGNsj7DPxwAmBKpDIsrR6XR7b7311jeOHj1qePTRR6PEYrE/n0NOTg5OnDgRKFP6TDjDgbGxsWGZtzCUIwNbfR6rAAorJ3PhlKMKG5oPYEXtF3il9nN8YdmPemcLRigzMF9zA6ZVpUEnjsXHjTtQ2n7R9GVBwZ/8qq5MHdYpJOjse0jQbDYjLi4OEkl4xzRZrVZYrVbo9f5ppKysLGzdulXz+uuv56ekpBzVaDS/JqJgHEQFgIpOv4Vr4BVaHM4FcGHFOQ9j7GnGWApjLB3A3QC+BXArgFgi8tUUmI4AJGz6wn45OTnb161bd93q1avjEhMTL6uNxMRE2O12tLS0XKk5V4QvD6etrS3kfYtEIsjl8pAmkwOhTWC3OjyQigki6ruHjDEGs6sVu63F+HvDZrxU9SneN2/B/rYziBerMCt2JBbr8/G4Ph/5cddhgCIZsLlwX0Ie4iXR+NC8FRUdwfcM+ptf1ZnOIcGvr6BwaKQkrZ84cQI5OTmXNSqRiDBnzhxxcXFx4gMPPLBEp9OdCHR4kDFWA+AcEQ0QVk0DcDyQfXB+HHBhxbkkjDEXgAcBfEJEh+HNsfp1X9vrGvY7duyYdty4cX1tK6K8VuGqxB6OPKtQeqzaHG6IqBkt4k/gdPkv5jo8LhTbK/FF8368WvsFVtR+gQ2W79DktuK66Ews0E7G08a5uC8hD+NUA6CVqC+4mTPGoJIosDBhCqJFcrzfsBm1zuB6By0WC+Li4i77c76Q4P4zNpypufyQoNPpREtLC8JdG85iscDpdPZ5GiGlUok///nPqu3bt2cGKTz4CwAfEtERALkAXgxg2z8qTp8+LR07dmx2RkbG4P79+w9+/vnndQBQW1srnjBhQpbJZBoyYcKErPr6ejEAHDx4UJ6bm5sjk8lGLlmy5Pw1O3z4cFROTs4g30ulUo1YtmyZLlzH5Q9cWHG6hTG2mTGWLyx/xhgbyhgbzhjLY4yV9KVNIsrR6/WXHfa7FFqtFh6PJ2wlD3z48qzCMcVMOPKsQumxarV7IBN7xUJZTc8lgxhjqHdasKP1BN5rKMRL1Z/gw8atOGgrQaI0Bvmx1+Fx/S1YrM/HrLhRyJIbIe0hYuRyueD7bsaIlbg/YQokJMZ7DYUwu4JTQslut0Mmk/mdX9WVqUNjoFVLsHZPM9ovMyToy60Kd+2qoqIidB4B3Fd84cE33ngjPzU1NWDhQcbYIcbYdYyxYYyx2xhj4f3hiWCkUilefvnlipKSku/37dtXtGrVKt2BAwfkf/jDHwx5eXmtZWVlx/Ly8lqXLFmSBAA6nc61YsWK8oKCggvi7sOHD28/ceLE8RMnThw/duzYcblc7rn77rsjejQmF1acoENEKp1O99rAgQO3r127tk9hv0sxcODAsHutJBIJ4uPjQ+45AoC4uLiQ51mF0mNldbihjPIK1pPnNl7gtWr3OFFkr8D6pn14pfZz/K1uA75qOYgWtw1jVVlYqJ2Cpwy3417tZIxRZUEj8a+wbNdSC/ESFRYmTIEHHrzXUAiLO/DHbjabr2jCZ6mEMGdsHFpsbnx96PLC45EwGtBsNkMkEgVsqiQiwm233SY+ceJE4oMPPugLD04KSOOcXjGZTM5JkybZACA+Pt6TmZlpLy8vl23cuDGuoKDADAAFBQXmL7/8Mh4AkpOTXZMnT7ZJpdIen07Xr18fk5aW1p6dnR36iUMvA155nRNUZDLZNL1e/94zzzyT8PDDD1+xh6o7YmNjIZVK0dDQcEU3pislLS0NpaWlCKRo9AeRSASZTAaHwwG5PDhzx3Ul1DlW8YoWEJOh3WnF/oqv4NJm47SjGuUdDXDDAxlJkBmVhOvVg5AVZUCc5MpGwXc3B6ROGov7tFPwbsN/8F5DIf4rYRqixYE73w0NDVcsbtISozA+R4WdJ6wYlCpHZlLv9lmtVojF4rDMeemDMYYTJ05g6NChAW9bqVTiT3/6k+rBBx9U3X///euSkpI21tbWFjDGrAHvjNMtxcXFsuPHjysnT55sNZvNEpPJ5AS84quxsdFvHbJ69WrNHXfcEfph0JcJF1acoEBEKr1ev3L8+PE3ffTRR5ru6tEEkpycHBw6dAgTJ04MWzgjPj4eR44cCctUKFqttse6P8FALBbD4wlMUcpL4fYw2Ns9kMR1oLL/WEg9DAdFdqDlMPSSWIxXDUCW3IBUWQIkFDjR3lNxUKNMg/nayfh7w2b83bwZ9ydMhUIkC0ifzc3NAZmfb9rQGBRXOrBubzN+frMOUdJLByYiIWm9vr4eCoWix/kRA0H//v2xbds2zapVq+545plnJstksvs6Ojq+DVqHEcJnTXtS65zNAa10q5PG2ebEj/UrqdRisYjmzp2buXz58nMajabPPxoOh4O++eab2L/85S8VfW0jVPBQICfgCF6qEy+88MIdmzdvDrqoAgCVSgWVSoXa2tAMi+8OIkJycjIqK0NX98hHuAqFut3BrYbe5vCAAWhRe2cvSY/SwVR3CrPshJ/rZ2FGbC76RekDKqqAS1ddT4/S4W7tJNQ5LfjQvAUdnisvXOpwOCCVSvucX9UZqYRw29g4WNp6DwkyxlBbW4ukpKQr7rev+LxVAwYM6H3nK4SI8MADD8j279+fPHbs2H/p9fr3iSj8E4/+SGlvb6fZs2dnzps3r3HhwoXNAKDVal1lZWVSACgrK5NqNBq//oHWrFkTO2jQIFtqamp4qjFfBtxjxQkYQi7V62PHjp21evVqTUpKSkj7HzBgAPbu3Qu9Xh82r1Vqair27duH9PT0kPYbHx+PY8eOhbRPXzgwmBNi+6quR1EzJA43FiTfiEOWOpRV70Bb8o2IVgQn9NtdKLAz2XIjbteMx78ad2J14zbM195wReLuSvOrumJKjMK4AdHYVdyGwakKZCR1P61eXV0dtFotghGi95fq6mrExcWFdBqdlJQUbN26VfP222/f+eyzz04Ri8X3ut3uzSEzIIT461kKNB6PB3fffbcpOzvb8dxzz51/4p05c2bzypUrtS+++GLNypUrtTfddJNfCaL/+Mc/NHfeeWdj8CwOHNxjxQkIYrF4iuClunPr1q0hF1WA90av1WrD4jHyIZfLIZVK0doanJFjPSEWiyGVStHe3h6yPkORwO6bJ9ClYFC1e3+uBqTNgohEKDr7edD6tdvtvc4TOESRhlvjRuNMew3WNO6Cm/U9NNqXwqC9MW1YDLRqMdbubepxlGC4w4AejwcnT55EdnZ27zsHGCLCgw8+KNu3b1/y+PHjP0lKSvo7914Fjk2bNqnWrl2r3b59u9pXKuHjjz+OXbp0aXVhYWGMyWQaUlhYGLN06dJqACgvL5fo9fphb775pv6VV14x6PX6YY2NjSIAaG1tFW3fvj3m3nvvjejRgD64x4pzRfi8VOPHj5+1evVqTbhHFmVlZWHXrl0wGo0BCav0BV8l9sGDB4e0X1+eVaimJFEqlUFPYPd5rNxyBlWrN29NERWHjOQpOHXua/RPvRFxqsB/59xut19enJHRmXAwJzZaDmJ9817cGjcWoj54S5uamjBkyJC+mNojMokIt42NxzvfNGDT4RbkX3dhfayOjg7YbDa/5iUMFhUVFdDpdCEbdNEdqamp2LZtm+att966a8mSJVPEYvGCH6v3KpTMnDnT2s30aACAXbt2XTTRa1pamqu2tvZId/ur1WpPc3PzoUDbGCy4x4rTZ8RicZ7BYDjz2GOP3b1t27awiyoAiIqKQlJSUtimmAGApKQk1NXVhSS5uzOhzrNSKBTB91gJ8wRC6oSq/Yebb1bqDEglShSVrg94n263+7JE+QRVDqaoh+CgrRQbLd9ddi2z9vZ2SKXSoITjfCHBvafaUFJ7oTezoqICKSkpYQubu91unDlzBv379w9L/50hIjz00EOyHTt2pIwaNWpjUlLSe3yCZU5f4cKKc9kQkVyv178zbty4T3bt2qW7/vrrJeGeVqYzmZmZKC0tDXpidU+IRCIkJCSgrq4upP1qNJqQFkoNTSjQDZHYBYg9ULX/EJqTSZTITp2B2qbv0dB80cPvFdFbflV35KmHYHz0AOxuO4lvW49e1mf7Mo3N5TBtWAw0KjHW7bkwJOgTVuGirKwMycnJkMkCM6rySmGMobGxEZ999lnU0qVL79Lr9UVE1LdpITjXNFxYcS4LIsrS6XSHn3rqqbu3b9+uMZlMyM3NxaFDh8ImZLoilUqRkpKC0tLSsNkQjomZxWIxxGIxOjpCUzsvFLWsrA4PRNIOSN1ORHku9OhkGPMgl8Xh+9J1Aa143xdhRUS4KXYERiozsKX1e+xo9X86zWDkV3XGFxJsbnPjm8PeByCLxQK5XI6oqO6T2oONy+VCWVkZMjIywtJ/d1RWVkIsFiM5ORkFBQVRu3fvTh02bNgXCQkJfyAifq/k+A3/snD8JiYmZqHJZNr55ZdfZv/yl79U+EIIMTExSElJCXv1885kZGTg3LlzcDr7PnHvlRAbGwuHwxHSZHLghzyrUCCVSuFyBXfks9XhBpO1Q92NaBeLZcgxzUZTaymqzYcD1uelSi1cCiLCT+JGY4giDV+1HML+ttN+fa6pqSlg1cZ7Il0XhbHZ0dhzqg2lte1hT1ovKSmByWSCRBIZab52ux2nTp26oEBpeno69u/fr73nnnue1Ol024kotJV/OVctXFhxeoWIlHq9/l95eXmvHjlyJGHkyJEX7ZORkQGLxRLyOet6QiwWIz09HWfOnAmbDSkpKaioCG0tu1DnWRFRn3LJGGNwOp2w2+1obW1FU1MT6uvrUVtbi5qaGlRVVaGyshJNre1wy5xQdbjR0dGB8vJynDt3DpWVlaiqqoKMpUMu0+Lo6U/R0FAHi8WCtrY2dHR09DnHrS8eKx8iEmFu/DhkRRnwefM+HLWV9byzw4GOI0cgt1hCIjBuHO4NCX62pwm1dWbodOGZx7ajowOVlZUwmUxh6b8rjDEcOnQIQ4YMuaiwr1QqxV//+lf1u+++O8ZgMByWSCSTw2Qm5yoiMh4XOL1CRGIA+wFUMsbyiWgbALWwWQdgL2PstiD0O1in032+bNky40MPPRTVU6IrESE3Nxd79+7FxIkTQ155vDtMJhO2bt2Kfv36hSXkkZKSgl27diEzMzNkfWo0GhQV+R+GulLkcjkcDgcUCgXa29tht9vR3t7e7aur91AikVz0EolEEIlEICIQEdo6FEC8EzFuCRhjcLlc8Hg8YIyd/6uRj0FVy5c4UboZSnF/uFyu86/O4srj8cBut8NqtaK1tRXNzc1IT0/H5MmTIRKJcM8996C+vh7V1dWYMGECfvnLX/apkr+ExLhLMwnvmzfj32e/gbrZiPSKVuDMmQtfFRWQMYYRqanALbcAQU4iPz9K8D8NOM76Ia7EjmyjHDHK0NawOn36NDIyMsJaO6szpaWlUKvVl5yKatasWeJ9+/YZbr311k8TExPfbmho+B1jLGi5D0Q0AMDHnVZlAFjCGHs1WH1yAgcXVlcPiwEUAYgBAMbY9b4NRPQJgHWB7IyIKC4uriAzM/OFtWvXav0ZCq5UKpGRkYHvv/8eubm5gTSnT4hEImRmZuLUqVMBH8ruDzKZDEqlEs3NzYiLi+v9AwHAJ06CMa1OR0cHWltbYbPZYLPZYLfbYbFYsHPnTkgkEkRFRUGhUEAul0Mmk0GlUkGj0SAqKgpRUVGQSqWXJVKcbgbXgSpA1gGTWg97VNRFOTlOpxMSyQBsPVSErVs/RYJiCurrG1BbW4u6ujoMGTIEzzzzDABvEdWuk1X/5Cc/QU5ODhwOB2pqaqBUKpGdnY1Nmzbh008/xbPPPotHHnkE0dHRiI6Ovni0oMcDVFdfJJpkZ87gZ2fOgBq71DPU64HMTCAvD8jMhLm4GNrVq4G9e4GxY/0+N30lXReFwdomnLNpsH6f91wY4qXINsqRkyyHQSPtU7kIf3E4HKirq8MNN9wQtD4uh9bWVpSXl+P666/vdd/k5GTs3r1b88wzzzzy7rvvTiOiWxhj1cGwizFWDCAXOP9QXQngs2D0FSxOnz4tnT9/fr/6+nqpSCTCwoUL65999tm62tpa8Zw5czIqKyujkpOT29etW1eSmJjoPnjwoHzRokXpx48fVz711FOVy5YtO19UdOnSpbr3338/kYiQk5Nj+/jjj88qlcrAJVYGGC6srgKIKAXAbAB/BPBEl21qAFMBLApgf2qdTrd66tSpE99+++24y6mInJqaipqaGtTU1IR1mgwfKSkpKCkpuaLwzpXgS2IPlbACfsiz6sv5Z4ydD8/5PDtWqxVOp/O8WIqOjoZarT5ff0ipVAYlX6dNqGEFaQeSZFo8/8GbePXVV1FXV3deOOXm5mLbtm0Y1O9WLJi7HOfOeh/yY2Njodfrodfrz7e3bNkySKVS6HQ66PV66HQ6GAyG85XjDx/25mkVFhZi0KBB+OCDDzBp0iQ01dbiq3/+E1XbtuHGfv2Q2tGB6NpayCsqIDl3DuRw/GC0WAyYTEBmJujOO9Hez4RvEltRmRqP/JHzYNRcGP4q+uILTFyzBrRmTUiElcPhgFHRhDunD0Z9iwvFlQ4UVzmw9XgrtnzfCpVchGyjHNlGOTKTonqdZ/By8RUDDVeNuc54PB4cOnQIubm5fnvPJBIJli9frpo+ffqI++6776BcLl/kcDi+DLKp0wCcYYxdIq4ceUilUrz88ssVkyZNsjU1NYlGjBgxaNasWS1vvfVWQl5eXuuLL7546ne/+13SkiVLkl5//fVKwINjgQAAIABJREFUnU7nWrFiRfmaNWsuSDgsLS2Vvvnmm/ri4uJjKpWKzZo1K+Ptt9/WPPbYY5GRd9INXFhdHbwK4Df4IfTXmTkA/sMYC0i9AyIaodfr1/75z3823HfffZft8iAiDB8+HDt37kR8fHzYRh11tic7OxvFxcVh8aIlJibi+PHjfhecDARarRb19fW9CivGGKxWK5qbm2GxWGCxWNDR0QGlUgmVSgW1Wo20tDSo1eoevV8+ERYMWoUaVlJRK/75wTasWrUKQ4cOhV6vx7hx46DX6zFw4EAAQGLcAPxpxc/R7q7D7dOXQ626OBn8F7/4Ra99spoapH38MfQeD548cwb429+Ac+cw0BdS3LYNDrEYdqMRjgEDYBs3Di0JCbAZDBBlZ0ORnY3YhATExsZCJpMhCsD1bhtW1X+D9xz78TNnLPRSr8h2Op1gsbGg6dOBf/0L+POfgx4O7Fy7ShcrhS5WiusHqWFrd+NUdTtOVjpw/Jwd35XYIBZ5PVwDkuUYYJQjXnVlt4u2tjY0NzdfkCAeTk6dOgWdTtenh55p06aJvvvuO/3cuXM/1Ov1H9bV1T3BGAvWSJm7AawOUttBw2QyOU0mkxMA4uPjPZmZmfby8nLZxo0b47Zs2VIMAAUFBebJkycPAFCZnJzsSk5Odq1bt+6iC+J2u6mtrU0UFRXlttvtopSUlPCMSvITLqwiHCLKB1DHGDtARHnd7PJTAG8Hoi+NRvPzAQMGLF2/fr32SqaYiIqKwsCBA3H48GGMHj06bAUIfSQlJeH06dOwWq1BndeuO0QiEXQ6HWpra0NWEV2j0aC4uPii9Xa7HWazGY2NjbBYLHC73VCpVIiNjYVOp0NWVtZlC2GFQhG0el2+qutyWLD5213IyMjAkSPdFmYGANw89SFs/u4lnKvfikGqWy+/w/37gVtvRWZVFZCY6A3ZTZrk/ZuZifqYGPzftm14+YMPUHvuHGYMHIiv/v536OH1fvhEak1NDYqLi+F0OhEdHY34+HjcFj8Sa5z78V5DIR5IvBEaiRpmsxkajQaYNw/YsMHb/+jRfTxbvcMYQ0XF/8/emYdHVZ79/3NmTzJZJzPZM9lXkpAAQXYQ16ooKHVDrctrF9/WautSW+tWfemv7Vtti75qN1FULFYExYVadgKEJSGQPSELIftM1sms5/z+CIks2TNZ2vK5Li6SzDnPeWbmzJzvue/7+d6nWbBgwUWPearlZER5khHliUuUqGmxU1JnpbTOyrYj7Ww70o7BV0FCqIbEMA3hOhVy2eg+1yUlJSQlJU359wH0rsRsamoa8LUYKUFBQezZs8f/xRdfvPf3v//9EkEQrpIkqcGN00QQBBWwAviJO8edbEpKSlSFhYWeS5Ys6WptbVX0CS6j0egwmUxD6pDo6GjHQw891BAdHZ2uVqvFRYsWdaxatWr6GCcOwCVhNf1ZAKwQBOEbgAbwEQThHUmS1giCoAOy6Y1ajRlBEJQGg+GPixcvvvG9997zdUfKLDg4mPr6empra6d0WTf0Rq2SkpIoKSlh1qxZk378yMhITp48OWnCSqlUIkkSLS0tdHR0YDKZ6OzsRKPREBAQQEhICMnJyW6pwZpIk1Czpfem1FMyUVlZRVhY2JDb+2kjCNPPpqJuR6/HlXoUrVreew/uuw8xMJCK998n4dZbL9pEDzx20008/D//w4cfftgfgbRarTz55JPcf//950VjJEmiu7sbk8mE6XQLKRYvjoabePPMF6xSzKKnpbM3VXnjjaBU9katJlBYtbW1odVqh33f5TKBaIOaaIOaazJ9ae3sTRmWnrGyv7iLvUVdeKgE4kN6RVZciAYP1dCpvY6ODnp6eoYsEJ8sXC4X+fn5zJ49e9wpSZlMxtNPP+21YMGC1DvvvPPo2bqrAdu4jJFrgaOSJDUOu+UgfHTQHNHU5hi9f8gQGPyUlpVz/UfU3Lm9vV22atWq2LVr19YGBASMeqluc3Oz/NNPP/UrLy8v0Ol0ruuuuy7m1VdfDfje9743bRsyT32i+xJDIknSTyRJCpckKYrekPA/JUlac/bh1cAnkiRZBx1gGARB0On1+v3f//73b/noo4/cIqr6mDFjBpWVlRPuzj0S9Ho9NpuN9vb2ST+2t7c3TqdzQs00JUmio6ODiooKDhw4gMVioaSkpD8VunTpUubNm0diYiJ6vd5the0qlWrCDEmbzp433mInlZWnhhVWAMlR1yNKTkpqto3sIKIIP/0p3HEHzJ5Nw5YtyIYR3yqVittvv51vfvObABw9epTXX3+d9PR0li5dyqZNm3A4HAiCgFarJTIykpkzZ3Ld/Cu5W7cUu1zkY+cxKs9UU1hYSMHp09gWLULatAncaHR6IWP1rtJ5K5ifpOVblwfy5KoQbl0QQGKYB+UNNv6238wv/17Pn79qZl9RJy0djgHNWouLi6dNtKqwsBCj0ejW6PXll18u27dvX0h8fPwXvr6+d7lt4N6MxL9cGrAPm80mXHfddbGrV6823XPPPW0AOp3OWV1drQSorq5WBgQEDGmGt3XrVp/IyEhbaGioU61WSzfddFPb/v37p3Wz7EsRq39tbgPWjnVnQRBSg4KCPnvzzTdDb7jhBrcXACmVStLS0jh27Bjz58+f8i/V5ORkiouLmTsJRcIXEh4eTm1tLeNJsV6I1WqlubmZ5uZm2tvb0Wq16PV60tLS6OzspLW1lejoaLcdbyD63lNJktz+/rb22EAhITb1+lKNRFhpPQxEBS+kqmEvseHL0XoM4dXU2Ql33glbt8IDD8C6dXRXVeE1ypuL+fPnc/r0af785z/z6quvsnr1akJDQ8nNzb0oSmn0CuIuxVLWt+ygNMHFbSFz0XRCy9KlhP3znxz785/xXLgQvV6Pn5+f24q8XS4XJpOJ9PT0cY2jUclIjfQgNdIDUZQ4bbJTerYA/ou8Dr7I6yBAKycxrLcA3qhX09nRhiiKE+ouP1Kam5vp6uqakFXCMTExHDlyRLdy5crfGQyG2c3NzY9IkjTmhqGCIHgCVwLfHs+8RhpZcjeiKHLbbbcZExISrM8++2x/xO3qq69ue/3113UvvfRSw+uvv6675ppr2oYaJyoqyn706FFtZ2enzMvLS/znP//pPWvWrKm/Wx+CS8LqXwhJknYCO8/5felYx9JqtTcZjcY3t23bFpiSkjL+yQ2CTqfDz8+PysrKSfVzGog+d2uTydRb2zKJhIWFsW/fPuLj48csQCRJ6q/haWpqQqFQoNfriY6Oxs/P77xxVSoVZWVl7pr+kKjVamw2GxqNZviNR0FHjxNULrAIxMXFjbivXaLxWmoaD1BU9Qlzku8beKPKSlixAoqL4Xe/g//+bxAELBbLmNJVOp2Oxx57jEcffZRt27bx2WefERISAsBf//pXEhMTueyyyxAEgSi1gWtlaWxXnuSPpq9I8zBy1be/Bc8/T1pxMY3XXENNTQ35+flotVqCg4MJCgoaV0+9+vp6goOD3Sp+ZTKByEA1kYFqrsjwpa3bSekZKyV1VnLLuskp6UatENCpu1i9MMltxx0rDoeDEydO9L8PE4G3tzdffvml3xNPPHHv+vXrM86mBse0ukOSJAsw9Wp0jGzfvl27efNmXXx8fE9SUlIKwHPPPVf33HPP1a9cuTLWaDQGhoaG2jdv3lwBUFNTo5gzZ05Kd3e3XBAE6fXXXw8qKio6cfnll3ffcMMN5vT09GSFQkFqaqrl0UcfbZ7aZzc0gjt7bF1i+iMIghAYGPhcXFzcf3/66af+kyEwXC4Xe/fuJTMzEx8fnwk/3lB0dHRQUFAwJRG0I0eOEB0dPSpR53K5aGlpoaGhAZPJhI+PD8HBwRgMhmHTebt27WLBggUT7uqdn59PRESE28Xqi9vKcEoWVsSfIDPhTnbu3MnSpUtHtG/hqS2U1n7O0swn8fO+IP21Ywfccktv2u2DD+CKK/ofysnJITMz020i0el0EhUVRV1dHVlZWTz00EPcfvvtnDp1Cq2/D2VeJvZ1FgMS37vndwRUNSArKwdB6E/vNjQ00NjYiFwuJzg4mODgYEZjgQKwf/9+MjIyRr3fWLE7RSobbOwvaqOqReT73zCg951a0+AjR44QFBQ0aY2n3333XccjjzxS29TUdKUkSZWTctCz5OfnV2VkZExeC4ZpRn5+fmBGRkbUVB3/Uo3VfxCCIHgYDIZPVq5c+fCePXsmRVRBb3uZvkbNY20z4i58fHzQaDQ0N0/+Dc9IGzM7nU7q6urIzc1l9+7dNDc3ExYWxpIlS5g1axZhYWEjqpEKCAjAdKFB5QQwEc2YJUnCZpOhkHWhUY2iCP0s8RFXolJ4UVh1gW/uq6/ClVf2GnUePHieqAKw2WxutQhRKBQUFxfz2muvYbPZuP/++wkPD+fvf/87IYFBLPdJ5+Gg60j1iGTv1anIKio5sX8LLklEEAR8fX1JTExk8eLFZGVlIZfLKSgoYNeuXRQXF4/I6sJisSBJ0qSJKuh1eU8M06AVezNAslGuIHQ3Z86cQZKkSRNVAHfccYdy27ZtMeHh4TkqlerySTvwJaacS8LqPwRBEML1ev3R559/fvkbb7zhM9nNT319fQkJCRnQBmCy6VshONnR2sDAQMxm84CNi0VRpKGhgSNHjrBnzx46OjpITExk6dKlzJgxg8DAwFHX2wQGBk5K78aJWBnY7uwGuxKlrIuXnv0T3/nOd0a1v1LhQULkNTSZi2g2l4DDAd/9Ljz0EFxzDeTkQHz8efv0nQ/ujmRqtVq+853vUFBQwI4dO1i2bFm/ODabzXih5uaAeVx252OIchmm9//Mq02fUWKtO+8c9fDwICoqissuu4wFCxag1WopLCxk165dlJaW0t3dPeDxa2triYiIcOtzGgmNjY2o1L2RP/kUXmmsVislJSXjri8bC7NmzSI3N9eQnJz8N51O96gw1YWml5gULgmr/wAEQZgbEhKS++GHHyZ++9vfnjLHzri4uH4fpanEy8sLHx8f6usnpBvFoAiCQEhISP9xJUmiqamJY8eOsWvXLlpaWoiJiWHp0qUkJyfj4+Mzrot8nwP7RDMREavT1nYQ5Who49CBAhobR7/aPDp0MR5qf0qPbUC68kr4v/+Dxx+Hjz8G34ujYHa7fVx1TMMhCAJLly7l1VdfZfbs2QDcd999zJ49m927dxMcGo9w+XIu++w4oiiyoXU3b7XuoMFhvmgshUJBeHg4c+fOZf78+ajVavLz89mzZw8VFRVYz7rBS5LEmTNnJs3qow9JkigpKcFg6HW+n8g2OcPNIy8vj9TU1Al9b4ciODiYQ4cOBVxxxRU/NxgMGwRBmPpGqpeYUC4Jq39ztFrtTfHx8Z8eOHAgeNGiRVN6tyQIApmZmRw/fnzAqM1kkpiYSGlp6aRHrSIjIzl16hRFRUXs3LmT+vp6IiMj+yNT/v7+bouYqFQqXC7XhL/WExGxOt3dm+JSi61UV50mLi5u1GPIZUrSLMnMvPNlOJADb78Nv/xlb9uZAbBYLHh6utXuZ0BaW1sJDAwE4M4778RsNrNkyRJuv/12zMuXo6qo4qHGML7hm0W93cxrTZ+z2XyQDtfAr7FSqcRoNDJ//nyys7ORyWTk5uZy4MABSktL8fX1nfA6uwupq6tDp9MhV/RqiKmKWFVXV+Ph4YHBMMTq0ElArVbz/vvv+/7whz+8Sa/X7xYEYVrbBVxifFxaFfhvTEBAwHcTExN/8Y9//COgb0XcVOPl5UVUVBSFhYVTEprvQ6PRoNfrJ83A1OVycebMGWpqaujq6iIsLIzFixdPeJsbf39/zGbzhBozajSa/giJu2jo7ga8sbTWYbPZxiSs2LyZkDXfwe4hI/f/7mb2nbcPeSc53n6SkigiOZ1IDgc4nf0/Sw5H789nf7cWFqKNi6PHbOa6GTO4/OOP+e2f/8yv33iD/Zs3c0omgz/9hawnniBZmM0+oZZDllMUWKqYr4hmnjIalVzVK8BlMpDJEGQyEARUMhlRkZFERUXR2dnJ4cOHcblcnDhxgsjIyElZPCKKIuXl5cybN48jp3pNXqeixqq7u5uqqioWLlw46cceCEEQ+MlPfuIRHh6e9aMf/eigIAhLJEn6jy0w/3fmkrD6N0QQBCEoKOjFtLS0hz///HPPqWg+PBRGo5GDBw/S1NQ0pXeS8fHx7Nu3j7CwsAkTOO3t7VRVVWEymQgJCSEzM5PW1la6u7snpXdgX53VRAqriSgbabH0CjVT4xmA0QkrSYIXX4Snn0aYM4e2P/2CM+bN1DTkEBUy+EXWWlaGl9lMe3X116LoHEHEBb9f+DMu14imZwA6LmjN8x0/P65/8EH+d/duLGYz6nffpVStxs/DgwxBINpbycG5BnbFVpDbXsyc3GYSStuRDRNwjdFoCHngAUwuF0VFRdjtdiIjIwkLC5uwKFZNTQ3BwcGo1WpcYq957GRHrCRJ4tixY6Snp096tG447rrrLpWvr2/Sd7/73ROCIMz9V2uufInhmV5n3CXGjSAIMoPB8Mfly5eveuihhzybmpowGo1TPa3zEASBmTNnkpOTg5+f35TVPqhUKkJDQ6muriYmJsZt44qiSH19PVVVVSgUCqKjo0lPT+8XICqVij179pCYmDjhlg86nY5Tp05N6DGgNx3lcDjc4ujulFx09vSmL7UeSpYtW0ZiYiLl5eXD72yxwL339too3HEH/PGPGDQaAvLzKa7+lAhDNnK5CkmUcPWIOHtEXBaR7qJTsK8KiVq65C4EpRJBofj6/76flUpkHh4ISiVc+NgF2134GAoFbV1dtJhMvUaxoogkiv3/B4oi6x95BNmGDSiffprnPvoIU1AQv3rySZJjYjCKIqfbuvnKq4FdS5UULYhmWVsARqvmvLGQJCRRpN1sRlFURNv77xP04IOEhIRgtVqprq5mz549GAwGoqKi3Lpa0OVycerUqf4okXhW+E12jVV5eTk6nW7S/epGgsPhwNfXV/bWW28F3X333TmCIFwtSVLBVM/L3ZSXlyvvvPPO6ObmZqVMJuOee+5pfvrpp5saGxvlK1eujKmrq1OHhYXZPv7440q9Xu86duyY5t57740qLCz0fPLJJ+uef/75/sLKF154wbB+/Xq9JEncfffdzT//+c8npkGpm7gkrP6NEARBrdfrN99zzz0Lf/nLX2pFUSQnJweNRtPbk2waodFoSExM5Pjx4/2FvFNBTEwMe/fuJTIyctx3tjabjaqqKs6cOYPBYCAzM3PAmh2FQoG/vz8tLS0T3jtNrVbjcDhwuVwTGiHz8PDAYrHgO0BR+GhpcXYgOZSAyLx5yTzxvTcABhRWkiQh2iVcFhFXeTWqe1cjK8zD8r3n6Lz5YVw7bLh6ejC030q7qYGTe08js2twWS8M9XgDV6AJk5HwQDCCfGKEgLm4GP+YGJRDRWoffBDpmWd4LCGBqw8cIHvVKr7//e/zzDPPkODnR7wkcaKnhu0d+WzU15OgCeVqn0z0yvPTfMf37iU9NZXO997D9MEH6Nas6f/cxcfH09DQQF5eXr/41+v14xb6p06dIjw8vF9gu84qq8mMWLW3t1NfXz9tUoDn4nK5OHToEAkJCYSEhLBz586QK6+88iuFQnGz0+ncM9XzcydKpZLf/OY3pxcuXGgxm82yzMzMlG984xsdb775ZuDSpUs7X3rppbKnnnoq+Oc//3nwa6+9VmcwGJyvvPJKzaZNm86rW8nNzdWsX79ef/To0SKNRiMuWbIkYeXKle1paWm2qXpuw3FJWP2bIAiCt16v/+qpp56a8cMf/tADev2jsrOz2b9/PyqViulSZ9VHaGgo9fX11NXVjahdyUSgVCqJjIyksrJyzO1m2traqKiooKuri6ioKBYtWjSsSOsrYp+MprR9dVZ9BdMTQV8BuzuEVaOjDewqlHIrGnWvWDj9SRv+h+KprGlBdJyNNllEXD0ikgs8Tx8h6oMHwNHDqW/+hU7dFbCzC5laQOEpQ+6hQemhoFt2irDEDFReKuSeMgRnF107v0DhIeO0IRnKQqj/qoPQq8b/PAZiRG2GDAaEJUvIrqqitKSEp3/+c1555RU2bNjAV199RVpaGmmeRpI8wjnQVcLuzkLWNW1jtlccy7xn4CXX0NXVhVwuxycxEfl119G2dSsdX36J7zXXAL3Ng0NDQwkNDaW9vZ1Tp05RWFhIZGTkmG8yHA4HtbW1LF68uP9voighEyYmXTwQLpeLvLw8MjMz3dYOyF30pSdDQ0P7XfkTEhLIycnRL1u27CNvb+/vdHZ2bpriaboNo9HoMBqNDgB/f38xNja2p6amRvX555/77dq1qwTg29/+duuSJUsSgbqwsDBnWFiY8+OPP/Y7d5yCggKPrKysLm9vbxFgwYIFnRs3bvRLS0sbc2PqieaSsPo3QBAEg16v3/273/0u5rbbbjsvF6NSqcjOzubgwYNkZ2dPqkngSEhPT2fv3r0EBASMq3B4PERFRbF7926io6NHnMqSJImWlhbKy8uRyWTExcUREBAw4guIv78/x48fd1v6bCj66qwmUlj1RazcQaOjHexqFLJO7r99LYsWHOHbgT8FwNHhQu4pQ61T4BkhQ+4hQ7vzPbzfeRgxOBzrn78kND0VuacMhYfsvMhTe5edHUf/hE9EJ6nRN+Hq7KT5zXdRKx3o73uQ8vx8wn09ad7bhdaowifRveejy+XC4XCMzIB09Wr43vfQNzfzf//3fzz44IO8/PLLJCYm9j6X9nZ8fX1Z5J1ClmcMOzpPcLi7nHxLFYu9U/CrFfsXZXjNmYOjsZGu/ftRBAXhlZl53qF8fX2ZOXMmdru9P00YGhpKdHT0qNL0FRUVREVFnRcZdYm99fWTRXFxMeHh4VPe4WEgTp48iaen50XCOjQ0lIMHD+quvPLK1wMCAoJNJtMfpmiKE0ZJSYmqsLDQc8mSJV2tra2KPsFlNBodJpNpSB0yc+bMnueffz6soaFB7uXlJW3fvt03IyNjYNO2acIlYfUvjiAIMUFBQTs2bNgQvnz58gG/wjw9PcnMzCQ3N5d58+a51Vl6vCiVSmbMmEFeXt6E9vAaCrlcTkxMDGVlZQzXN1GSJOrr66moqMDLy4vU1NQxfYkLgkBYWBh1dXVERUWNceYjQ6fTUV09sfWxnp6eY/KaGogGRxsKRxgKwUR5aS1XLtfgk6TBXNtO4n+fE9l0Ont9qX77W1i+HPkHH+A1RE2NrzaccMNsKut2EB04n64Nf0fs7ibwvvuQtFoUCgWh1/rRfdpBzd/NJHxXicrPPV+RdoeFipocNN72ke2walWvmenf/gapqWRlZbF+/XoAOjs7SU1NZfny5axdu5aQkBCu95vNXK94vujIY3tHPhoPOfcFfu0q73vttTibm2nbsgWFTod6gJWwKpWK+Ph4YmJiqK2tZf/+/eh0OuLi4oa96bHZbDQ0NJwXrQIQJQn5JH2mW1tbaW9vH/YzPBVUVFRgs9nIysoa8HE/Pz/27NkTcOONN75gMBjCm5ubfyK5yQum5iNzhLXJ4VYfEY1BaYlcObLmzu3t7bJVq1bFrl27tjYgIGDUrTeysrKsDz/8cMPll1+e4OnpKaakpFim24KEC5lesdJLjApBEGaGhobu27ZtW+RgoqoPPz8/UlJSyM3NnXIPqQvR6/VotVqqqqqmbA4RERE0NTUNahvgcrmoqqpi165dtLa2MmvWLLKyssZ1ZxwREUFt7cQ3ntdoNNjt9gltJ+ROL6smRxvYlVg6arBabcTHx2M3OXF5OL7eqK0Nrr++V1R9//vw2WcwgkLlZOMNiJLI8d2v4aivx/+b30QVFtZvtSBTCkTdGoAkQvUHJkTn2K9tdoeF6oYcck6s47MDT1BS9yEN3VspqtqKJA3zXgQFweLFvcLqAmQyGXfffTfvv/8+CQkJ/OpXv8Jut6NX+rJGt4QVspmgEPiraQdn7L1mvIJcTsCttyL39cX03ns429oGPbRcLicqKoolS5ag0+nIzc3l6NGjQ7bPKSsrIzY29qL022RFrBwOBwUFBcycOXNKbs6G4syZMzQ2NpKZmTnk3DQaDdu2bfO79tprv6PX698SBOFf/vpss9mE6667Lnb16tWme+65pw1Ap9M5q6urlQDV1dXKgICAYS9IjzzySEthYWHR4cOHSwICAlzx8fHu9XdxM9Nb9l1iUARBmB0REbFtx44d+tjY2BHtYzAYsFqtHDlyhDlz5kyrGoSUlBT27NnTL7ImG5lMRnx8PGVlZaSlpfX/XRRFampqOHXqFCEhIcyfP99tqxg1Gg1KpZLOzk68vb3dMuZg+Pn5YTab0el0EzK+u9zXLaKNDlcPgl1Be0MFALGxsdgPuhCDzwqrkhJYsQJOnYI33oD/+q8Rj++p0RFqDaPOq4aYb6zC42xq7VxzULVOQcRN/lRvNFG/vZ2wa/2GGvI87E4LDS3HqWs5QpO5GEly4aEOIDZsGa31cjz9zZTUfEZbVw2zEu9FpRwikLB6Nfz3f0NhIZwThfHy8uKll17ivvvu49FHH+Xxxx/nj3/8Y/9KP+l0F7fHzucj+xH+0vJP1uiWYFTrkXl6orvzTprfeAPTu+8S+MADyIY4lwVB6K8Hamlp4fjx42g0GhISEs47X3t6emhtbSU1NfWiMXprrCZe6Jw8eZKYmJhJMXgdDa2trf2eXiP5vpXL5fz1r3/1ffzxx1euX79eKwjCakmSRubjMQgjjSy5G1EUue2224wJCQnWZ599tj+cffXVV7e9/vrrupdeeqnh9ddf111zzTWDq/yz1NXVKcLCwpxlZWWqTz/91O/QoUPFEzv78TF9rqyXGDEKhWKu0Wjctnv37hGLqj4iIyPx8/OjoKBg0l3Hh0Iul5ORkcGxY8emrFFzaGgoZrMZi8XSL6h2795NT08PCxcuJCkpye3WECNtzDxeJrpvoEwV1Yr2AAAgAElEQVQmc8v51OhoB6cCSRIwNfSmL6NCYhAdEqKHA774AubOBZMJvvpqVKIKoGvPHvQHu5ALcqq8q/r/fqHrul+qB4FzvWjJ6aa9cGjBaHdaqGk4QM6JV/ks5wmOlq6no7ue2LBlLJn5OFdlv0BK1E1IDl9mJ99DRtxtNJmL2XXsl3R0nxl84FWrQBBg08D1zHFxcWzZsoXPPvuMpUuXotfrsdvttLa2EuUfyv2By9HKNaxv3UG5tbeNklKvJ2D1ahyNjZg/+qjXomEYBEFAr9ezYMECIiMjyc/P5+jRo/29CUtKSkhISBgwGuMSJ35FYENDA3a7fUr6IQ5FR0cHBQUFzJkzZ1R1lIIg8Ktf/Ur7X//1X1caDIaPBEH4lwyAbN++Xbt582bd3r17vZOSklKSkpJSNm7c6Pvcc8/V79ixw8doNM7YsWOHz3PPPVcPUFNTowgKCkp/4403gn7729+GBAUFpZtMJhnAihUrYmNjY1Ovv/76uJdffrlGr9ePS2xONMJ0urheYngUCsX8iIiIj3fv3h041i8SSZLIz8/H09NzzCvhJoq+Js19RbqTTUNDA+Xl5TidTgwGA3FxcRPqsyWKIrt27WLJkiUTGkHs6enh2LFjzJ8/f8KOsWfPHubNmzcu24oDXaVsO1MER2bTU72WpqJ2fvfz16j6qxnv2l8T8/bvYcaM3n5/o6xNsxw/jnnTJjzS0micraGk9jOWZD6Bv7eRkydPotfrzzOsFZ0S5X9qxtbqJOE7BtQBXz8vu9NCQ+tx6pqP0mQu6o9MhemzCAvMws/beJ7QMJlM1NTUMHPmTABa2ys4VPQmTqeVrMS7CNPPGnjSixeD2QwFI7M52rt3L3fccQf79+8nPDycLlcPb7XspMXZwTcDFpDsEQ5A5969dHz5Jd7LluGzbNmoXkdJkmhubqakpASNRkN3dzdLliwZUFh9mGOiutnOoyuCR3WMkWKz2di/f39/v8TpQk9PDwcPHhx3ucCzzz7b/eqrr+5ubm5eIUnSiGs48vPzqzIyMv5jXd3z8/MDMzIyoqbq+JciVm5AEAS5IAjHBEH45OzvgiAILwqCUCoIQpEgCD9wx3EUCsWiyMjIj/fu3TtmUXV2fqSnp2M2myelxmc0xMfH09TURNsQNSATQV9RenFxMRaLhbS0NFJSUibcvFQmkxEYGEhT08T63QldChT5fljqJ876xR3pwEZHG2pnb+RoVnY8b721HlenQNCuXxPz1itw442wb9+oRZWtshLzRx+hiorCf+VK4iKuQKXUUnhqMzBwn0CZQiDqmwEIQPVGEzarhZrGg+SceJXPc57kaMl6OrrPEBu2lMUzH+Oq7BeYEbMKf5+oi0RGS0vLeWlYnW8syzJ/gq82nNyiP3Gi8u+IA2V8Vq+GEyegeGSZj8rKSsxmMytXrqSnpwet3IN79ZcTovRno2kvxy1VAGgXLMBj5kw6d+yg5+TJkb+Q9H5/GAwGFi5ciM1mQxRFCgoKsNkuPrcmMmLVd4OYnJw8rUSVw+EgNzeXtLS0ca9OfPbZZ70efvjhJQaDYdtENG8+c+aMoaCgILWgoCC1rKws2uVyTa8CtX9RLgkr9/AwUHTO798CIoAkSZKSgffHewCVSrXUaDR+tG/fvkB3eD7JZDJmzZpFVVXVhF/UR4NMJmPmzJnk5+fjGmGLkPHS1tbG/v37aWhoYO7cucyaNYvKyspJOTZMbDrQZRWp+6yNknVNqOt9qf1y4tKB7hJWPq5eDynJYUOSJOwmJ21pK6m87/7etNgoa/AcTU20vv8+ioAAdLffjqBQoFR4kBh5Dc1tJTSZiwftEyh4O9Bc3kxPvYPc9V9xtOQtOrrriAlbco6YupkAn+ghC5MHsrvQqH1ZmP5DokMWUX76H+QU/AGbo+v8HW++ech04Ll0dHSQmJjIO++8w+HDh3nwwQeRJAlPmZp7ApcRqdLzoTmHw93lCIKA/w03oIqIwPz3v2Ovrx/Zi3nB8WQyGcuWLUOn05GTk0Npael5n9uJrLGqra1FqVQSHDwx0bCxIIoiubm5xMbGuq2e8ac//anno48+ukCv13/uTnFls9mUzc3NQSkpKYVpaWknAaGlpWX6WdX/C3JJWI0TQRDCgeuAP57z5+8Cz0tnl/5IkjQu5aJQKBZGRERs2rdvn67PWM4dKBQKsrOzKSwspL293W3jjhdvb28iIiIoKioafuNxYLFYOHLkCEVFRcyYMYPMzEw8PDzQ6XS4XK5Ji5r5+vrSbbNQb2nFKjrcUqskiRKtR7opfqWRlgPdBGR6Yo2soKfShb1jYlaFjndloChJNDnb8XR6I0kS9698msceewy72YkYm0jNXWtGvcTM1dFB69tvIygU6O66C9k54ikqZBEe6gAKT23GJX7tTO9w9lDbeJADJ17js5wnOGF/ne6YY3ifzmK25gmuyv7FiMRU//MSRaxW64DCTSZTkBF/O5kJd9HaXsHOo2tp6zxHZIeGwoIFA64OvJCamhoiIyO58cYbeeGFF3jnnXf43//9XwDUMiV3BS4hTh3KlrZc9nUWISiVBNx2GzIPD0zvvourq2uYI5xPcXExycnJ/dYhixYtQiaTsXv3bmpra5EkCZcE8glowGyxWKisrGTGjBluH3us9BmABgUFud3w+IknnvB87LHHLjsbuXJbzZUkSYIoijJRFBFFUaZSqRzD73WJ4fiXLIqbZrwMPE5vT4w+YoFbBUFYCTQDP5AkqWwsgysUinmRkZEf7dmzRzcRd2ZqtZrZs2eTm5vL3Llzp82qmujoaA4cOEBLS4vbjS0dDgelpaW0tLSQnJw8YCPopKQkioqKmDdvnluPPRilRgs7zF8CoECGl1yDl6z3n1auvuhn7dnHPWVq5Besyu6usVG3rZ2eMw48I1VE3+WLWVlA8+Eviaj5LqcP1BJz1TDu32PA09NzXAXyba4u7JITpdOT7rZ6enpsREVFYTO5UPuPvh2PaLPRumEDYk8Pgffdh8Lv/NV9cpmS5KjrOVqyHi9ZELWNB6lrOUaTqRBRcuKh9ic6dDFh+ln4zY+k4i8mzF8K6GOcqANHHjhob2/Hz2/olYXG4Hn4eIVw6OQb7M7/DTPjbycy6LLeB2+5BX74QygthUFqIkVRpLm5ud/D6ac//Sn5+fns3r2bRx55BJlMhlJQcLtuIR+ac/iiIw+b5GSZ9wwC7ryTlj/+EdN77xF47729fQ2HwWTqtXE4t5uDXC4nLi6OyMhISktLOXXqFD3WOGQy915mJEkiLy+PtLS0CTfXHQ1FRUWo1WpGu6BopDz22GOeDodj/iuvvLJFEIRR1VwNhFqtdhgMhoaCgoJ0QRBEb2/vDn9//w53zfc/mUvCahwIgnA90CRJ0hFBEJae85AasEqSNFsQhFXAn4FFYxh/rtFo3LJ79+7A0NBQ90x6ALRaLTNnzuw3EJ2qpsjn0teo+cCBAyxcuNAtX6CSJFFbW0tFRQUxMTGkpKQMGnHw8/NDoVBMiLC7kB7RTr28A32XhqzQJLpEK92ijW6XlS6xh0ZnG90uKy4GXsHlKVPhJdPgZ9FiPBCEb5E3olZEvMGJI1WigSbyC7egDdbS41eDdCwQ6QoJwc2RhPGmAhscvRFCwa6ko7m3pig+Ph57nhOfJM2oxpJcLkwbN+JobER3xx2oBvn8RBiyKan+km5rLkdKcvFQ+Z0VU1n4e0dxrpWQ8Zv+lL7WTNVGE/EPGpApR/b6XVhfNRj+3lEszfoJuUV/5GjJeto6a5gRczOym2/uFVabNsFTTw24b2NjI3q9vn8BhCAIrF+/HpVKdd6iCIUgZ7X/fFTCIXZ2nsAuObg6OBP/lSsxffABbVu34nfTTUNG4iRJoqio6DxbknNRqVTMmDGD7u5u8rY34BIFLBat227aKisr8fX1nTDrkLFw6tQpLBYLs2YNsgjBTTz11FOeDodj8bp16z4SBOGm8VgxOBwOeXt7u9+MGTMKFAqFq6ysLKapqSnAYDCY3Dnn/0QuCavxsQBYIQjCNwAN4CMIwjvAaeDDs9t8BPxltAMLgjDbaDRu3b17d2B4eLjbJjwY/v7+JCYmkpuby2WXXTahDXtHioeHB/Hx8RQUFAzqWDxS2tvbKSgowNfXd8RCLSkpifz8fBYsWDChpoNl1jOISCT06Eh1hQwY3ZAkCavkoNt1VnSJVrpcVrpFK912G+ojanSHfBFcAuWZpzmRWYVLKYL57AAhSQBEZnYzZ0ckplIzuiT3llOMNxXY6GhHAOxWaGvqDfBGR8TQs09E5a9gEF15EZIk0fbJJ9jKy/FbsQLNECtfBUFGbPAKahsPk5Z4+UVi6lxUvgoiV/lz6p1W6ra1EXHjyHpvtra2kp6ePqJt1Spv5qf/gJOVH1FR90/au04zJ+V+NPPn96YDBxFWNTU1JCcnn/e3vtTj6dOnefLJJ3n11Vfx8fFBJsi40W8uKkHJ/q4SbKKTG1Jn4710KZ07d6IwGPBesGDQOTY3N6PRaIYtzPby8kLr7YPd7uDQoUOEhoYSFxc3rtWvHR0dnD59elo1WK6vr+fMmTOT1jnimWee8XI6ncveeOONDwVBuHms4qq9vd1HpVLZVCqVE8Df37+tq6tLe0lYjZ9LNVbjQJKkn0iSFC5JUhRwG/BPSZLWAJuBy89utgQoHc24giCkRUREfLpz50595ACtJyaK4OBgwsLCOHr06LTxuAoLC8PlcnHmzBB+P0PgcDg4fvw4J06c6G1eO4r0gbe3N15eXm5r1TIYJdY6vGRq0oMTBi1iFwQBD5mKQKUPRrWeFI8IsrXxzKqPJ/adcAz7AvCP9SLlByHcvHIuPzXewo+Db2SNVwaxZ04w2y5wlc9M7EYLNrWDmpyxvZ5DoVAoxrXgoNHRhr9cS3ePi7bGShQKBSE+vTcV51odDEfnrl1YjhzBe/FivGbPHnZ7ueRPhO5yAnxiBhVVffgkaDAs1mI6YsGUN7yIlCSJnp6eUUVrZIKctNhbmJV0L21d1ew8upbu65dBXh6Ul1+0vdVqxW63Dyp0KioqeP/991mzZk2/R5xMEPiGbxaLtSkcsVTwofkAnksWo0lJoePLL7GWDvyVJUkSJSUlJCUljei5uETQqFUsXrwYQRDYvXv3mBfLiKJIXl4eM2fOnBY3ftCbEi0tLWXOnDmTOqcXXnjB61vf+tZyg8HwjjBGNadSqewWi0XrcrlkkiTR0dHh7eHhMa0dzf9VuCSsJoa1wM2CIBQA/wM8MNIdBUEwBgcHf/GPf/zDMNE95AYiKioKrVbLiRMnJv3YAyEIAhkZGZSUlAzabmYgJEmipqaGvXv34u/vz/z58/H19R318RMTEykpKZkwoemUXJRa60nUhBFkMNDa2joicWJtcVD5dgunNrQiyASi79IRfYeuX4AoBDneMg1nKrdgcLm4NuJGFnonc7N+AbXxDVDti6PT/XWqgiCM2eC10dlGsNKPbptE0sxUnn3+J4hnKz5UASO7aFny8uj85z/xyMjAe/nyke0zgNXCUAQv88ErSkXd1jasTUO/hn3NksdChGEOi2c+hkymYF98Xe8fByhiP336NENFtZcsWcLLL7/M1q1beeaZZ/r/LggCV/hmcIVPBgU91XzQth/tyhtRBgVh+tvfcDQ3XzRWfX09Pj4+I27mLooSMtnXnQ3mzp1LdXU1ubm5o04bl5SUEBwcPObX0910dXWRn59Pdnb2lJRPrF27VrtixYpv6PX6X49lfx8fn25fX1/zyZMnk0+cOJEKCEFBQRe/6ZcYNZeElZuQJGmnJEnXn/25TZKk6yRJSpMkaZ4kSfkjGUMQhECDwbDz448/DplK486kpCQcDgflA9wdTwUqlYqUlBTy8/NHJHC6u7vZv38/bW1tLFy4kIiIiDGH6D09PQkICBhzxGw4qm3N2CQHSZowZDIZBoNhyAiZyypy5ot2Stc10V1jJ/RqHxK+Z8An/uIapFP1e2jrqiEt5haUit60kEEbgDXkDDJRRsG+Erc/n7HWWdlFJyZnJ3qFH1a7jJSZ0Tz22JPYTL31uWr/4SNW1ooKzJs3o46Oxv/GG0f8no9WWAlyAeMtAchUAlUbTbjsgwvJkdZXDYavNpylmU+iTczClBKEZcMbuMSvxZwkScMKK4CHHnqI+++/n1/84hf87QJxttg7het8Z1FsreO9zhy0t38TQaHoLfw/J7UrSRJlZWWjMu/t9bH6+n3w8PBgzpw5GI1GDh48SGVl5Yg+0yaTidbWVuLj40d87InEarVy+PBhsrKyhm1QPVEIgsDrr7/uM3fu3Pt0Ot2PxjJGZGTkmfT09JNpaWkn4+LiTslkMrfdQZaUlKiio6NTb731VmN8fHzqihUrojdv3uydlZWVdNZ13bOjo0O2evXqqBkzZiQnJyenvPPOO359+86aNSsxJSUlOSUlJXn79u1eAJ988ol3dnZ24jXXXBMTHR2dumLFiuip6tQxFJeE1TRBEAQvvV6/66233orIzs6e6rkwc+ZMmpubqaurm9K59BEUFIRGoxnS70mSJMrLy8nNzSU5OZn09HS3FL0nJCRQVlY2Ia12iq2nUQpyYtS9Kz4H87SSRAnTsW6Kf9dI874u/DM8SXo4CP0Cb2SKiwWE1dZO4amP0fslnefqLQgCcR5htAaZsZ1Q4xLd6xU2VmHV7GxHAvxFP0QJ6itLsPW4sJtdyD0E5B5Df1U5Ghsxvf8+isBAAs56VY2UwTyshkLpIyfyFn9sLU7qPmkbVBwM5F81WlRKL+bNeAj7Td/A82QVhz/9GT223uK5trY2tFrtsOe5IAisW7eOefPm8ctf/vKic3muNoGVfnM5ZWtig/MYnrfdgqu9HdMHHyCdjaDW1tYSGBiIRjPyhQSiJCEfQN/2GYz29PSwb9++IRs8O51Ojh8/PmwT48nC6XSSm5tLamrqlEfPZDIZmzZt8ouPj/+pj4/P7VM6mQGora3V/OhHP2oqLi4+WVFRodmwYYPu8OHDxS+++OLpF198MeSpp54KWbZsWceJEyeK9uzZU/Kzn/0svKOjQxYaGurcs2dPaWFhYdHGjRsrH3nkkf6amKKiIo9169bVlpeXn6ypqVFv37598pvLDsOl4vVpgCAISr1e/+VvfvObuGuuuWZaFA/IZDJmz55NTk4OarV6wlfGjYTU1FT27t1LYGDgRamIjo4O8vPzCQwMZNGiRW6td1Cr1QQFBVFbW4vRaHTbuJIkUWytI1YdjOrsknRvb2+cTud5F3vLaTt1n7ZhqXPgGa4k+k4dnmFDpx4KKj9EFJ1kxN920cUoKDCIkqgydAdTOHKihOz0lEFGGT1jLWBvPLsi0NPljaWjmv99+Fn0+HOd7x2ohqmv6veqUql6vapGceGH3gvlWAS4d6yGoKXeNO7oxCtKjS7r/HNSkqRRR8MGQxBkBD/4DLz0F3y27WNn4FrmJD9AXY2FkdZhqtVqNm/ejEajGbCAPNMrBpVMwSZTDu96uLhlxbXYPvqE9s8/x/uaa6ioqGDBEEXtA+ESQTbI6lOFQkFqaipms5mjR48SEhIyYHF7YWEhUVFRI04/TiSiKHL48GGioqLQ6/VTPR2g93398ssv/S+77LLfq1SqJrvd/tWF22RnZ18UZly1apXpySefbO7s7JQtX778olDgmjVrWn7wgx+01tfXK2688cbzPCQOHTo0onB3WFiYLTs7uwcgISGh5/LLL++QyWRkZWVZfvGLX4Q2NDSovvjiC7/f/e53wQA2m00oLy9XGY1Gx/33328sLCz0kMlkVFdX91vrp6WldcfGxjoAUlNTLRUVFVO/jP0CLkWsphhBEGR6vf7DH//4xzPvuuuuaXWCKJVKsrOzOXHiBB0dU29volAoSE9PJy8vrz9CIIoixcXF5OXlkZ6eTnJy8oQUkcbFxVFZWelWN/hGZxvtLguJmvPNBMPDwzl9+jSOThc1H5kpe6MZe7uLiFX+xD2gH1ZUNZkKqWs+TELkNWg9LvboCgwMROsvx6Gy03LMhk10X63VWCNWjY52lIIcmV2NqeEUcNZqwewcMg0oWq20vP02otWKbs0aFKOMIIiiOK4oSNASb7Qxauo+aaOn4fzXsaOjAx8fH/dFWYxGyM4m4VAXCoUH+wpeod6cO6oLvMFgwMfHh56eHv7nf/4Hh+P8Oad6RHK7bhHNjg7eD21GXDSX7oMHqd2+ndDQ0FHXEomiNGxLG39/fxYtWoQkSezdu/c8Y96mpiYsFotbb2jGSl8LHZ1ON+0aPvv4+LBjxw5daGjo+4IgZE71fPpQqVT9oVyZTIZGo5Gg1/PM5XIJkiSxadOm8uLi4sLi4uLC+vr6gqysLOuLL74YZDAYHEVFRYUFBQWFDoej/yxSq9X9Y8rlcpxO59SHMS/gUsRqijEYDK/eeuutSx9//PHp4cx5ARqNhlmzZnH48GEuu+yyKasn6CMgIAB/f38qKiowGAzk5eUREhLCwoULJ7SJsVKpJDw8nKqqKrcZABb11CEAiZrzPZZCDKEc3VSItbYRySmhX6glaIk3cvXwz8/lspNfvhGth4H4iCsH3MbLywu7TYCoOoLLjextLGR5SIY7nhKenp5jWkXZ4GzDoPDD0i1haqwCIDY6lp6DLvxmDCyU+7yqnM3N6NasQTWGrgRWq3VUqa0LEWQCkbf4U/paE9UbTcR/R9//Po23vmpAVq9G/thjLPV7jz1tn9DRk4fd0YVa5T38vufwj3/8g6eeeoq6ujr+8Ic/nPdYgiaUuwKXsqF1F5vS1NxgikWTk0NwxujPEZfEiFrayGQyEhMTCQkJIT8/H4PBgNHY2xx73rx50yIFWFpa2m+COh0JCgriq6++Cly8ePE2p9N53h3gUBEmb29vcajHQ0JCnCONUI2WZcuWdfzmN78J+utf/1ojk8nYt2+fx4IFC3ra29vl4eHhdrlczh/+8AfdZLU3cxeXIlZTSEhIyHPz58+/4+WXXx7dt+Ik4+3tTXp6OocOHbroDncqSExMpLKykiNHjjBz5kzi4+MnVFT1ER0dTU1NjdtegxJrHeGqQLTyXrEqOiRaDnZRvq4Vz3I9qhCBxIcMhF7lOyJRBVBa+yXd1mYy4m5DLvs6vSVJUn9dzcaNG7njjjvYcnQTclFGfV4Hbc5utzynsaQCJUmi0dFGkNKXzh4npoYq5HIZIf7hIDJgKlCSJNq2bMFWUdHrVTXGi91Y6qsuRKmVY7wlAJvJyektX9dbtba2ul9Y3Xxz7zE3f4LCngKInG4+POphbrjhBn784x+zbt063nzzzYsej1Yb+Fbg5VhFB3+b70mnrxrLnj2jPs5IIlbn4uPj059u3LFjB0ajcVzC111UV1fT3t5OWlratBB5gxEbG8uWLVuC29ragu12+7QPnKxdu/aM0+kUkpKSUuLj41N/9rOfhQH88Ic/bHrvvfd0GRkZSaWlpRoPD4/pV6E+BJeE1RTh7+9/f3x8/MMPPfSQd/MAy5qnGzqdjvj4eHJzcyekiHuk9PT0cPDgwX6X6cmsu1AoFERFRbmlQXO7y8IZh4lETRiiU6Ilt7evX92n7agDFOhWKejJahxV65ROSyNltV8SbphDgE88x44d4+WXX2bVqlUYDAZ27doF9HqDqdVqXn3zT7RqyokqCmJ7+4gWrg6LUqkctfDsEq1YRBvBSj/au220NVYQGh4EXb1fTwOlAjt37sRy7BjeS5fiNQ7zWHfVQGmj1QQv96GtoIfWwxYkSaK7uxvtKBtGD0t0NMyejeuDD5Djh682gprGA2Maau3atVx11VU89NBD7Nu376LHw1U67vJbjA0nxVck03PiBI6GhlEdwyVKg9ZYDYZMJkOr1eLn50dNTQ3V1dVT6qvX2NhIbW0ts2bNmtaiCnrrBR0OBz4+PvLy8vIkp9M5Zdf4xMREe1lZ2cm+3z/88MOqe++913zuY1qtVnr33XerS0tLC8vKyk7u2LGjHCAtLc1WWlpamJ+fX7xu3bo6i8VyDOD666/v7NsGYP369TU/+MEPJq6z/Bi5JKymAE9Pz29ERET8v88++8x38eLFlJWVUV1dPdXTGpbQ0FCCg4M5duzYlHzRnT59moMHD5KQkEBmZiZhYWGUlExIhHpQjEYj9fX12O32cY1T0lOH4BKILDL0CqqtbSh95cTcoyP2vkDCMgyYzWaczpG1A7Pb7ew9+mdkMiVqZwYBAQFkZWXxyCOPkJeXx/XXX9/v6L5o0SLefvtturq62FqxEe82L86cMlNrbxnXcwL6LzyjOT/6CtcNSj/ae2wsvP52XnjxCeym3vD/hR5W3UeP0rljB56ZmXgvWzau+bpLWAEYFmrxjldzZlsbLeW9q/Um5EK8ejXyw4eJEgQig+bS3lVLR/fo7UDkcjnvv/8+RqORBx54YMD6wY6qZiIJoDRQQvLQ0LFjx6iOIYqMKmIFvTdPpaWlzJ49m4ULF9LW1sahQ4ew2WyjG8gNmM1mioqKyM7OnjampINhs9nIyckhLCwMrVZLcHCwqry8PFEUxemtBv8NuSSsJhlBEGaGhIS8tWPHjgAvLy9UKhXz5s2jsbGR4uLiaeN4PhgxMTFoNBoKCwsn7ZgOh4MjR47Q2NjIggUL+lcoxsbGYjabx9X4d7TIZDJiY2MpKxtTT20AJJdE49EOrv0gm/ZPbCi1MqLv0hH3QCDesRoEQUAQBEJCQqivrx9wDKvVyu7du3nhhRe48sor8fPz5dVX3iM1+kaSEtNYs2YNGzZsoKamhsrKSv7yl7+Qmfl1TevChQuZM2cOG7ZuoltqJ64whM/a3OO4r9FoRnUR7BNWQQo/unqcRCXGcMMNK7CZnAgKUHp/fUGzlpfTtmUL6thY/FasGLdwcUcqsA9BJhC5yh+Fl5z6zd0EeE7MSlrplluQZDJCXnuNcP0cBEE25qiVv78/W++0wpYAACAASURBVLduZcuWLRcJB6vVSlNTE9kBSXRLNkyXZ2EtKsI+Ck83lySNqMaqj74GyzNmzECpVKJQKMjIyCAqKor9+/dPeBeEc+nu7iYvL485c+ZMi/6pQ9HV1UVOTg6JiYn9hfUBAQGCv7+/prKyMna6X1f+3bgkrCYRQRAMwcHBn3z++eeB59ZeyOVy5syZg91uJy8vb0pTbSMhJSWFnp4et6TEhqO9vZ19+/YRFBTErFmzzlsWLwgCmZmZFBQUjDiy4w7Cw8NpaWkZ9eo3SZQw51so+n0jkf8IRqGREX2njrgH9fjEay4SCZGRkTScOIFotdLV1cXJk/1RdRITE1myZAnPPPMMjY0NXHldCsuWX0ZUSG8fxHXr1nHHHXcMunpJEATuv/9+oqOjafUrIrQykMbOdgp6xh859fDwGFWdVaOzHW+ZB15yNSZzF8W5X9LV4cRudqLyU/Q3i1Z1dmLauBGFXk/ArbciuCGC4M6IFYDCS47xm/6IXdC1UUXRKw3UfGSm9Ug31maHW4Rrq48PDfffj+ydd1B//DlBATOobTqEOMZ+vElJScTHxyNJElu3bu2fY2lpKfHx8SR6hqMRlJTFahE8POj46qLV/IMy2ohVVVUVWq32opWOQUFBzJ8/n8rKSgoLCyf8O9Jms5Gbm0tmZua0sHkYCpPJ1D9Xg+H8VcBBQUEypVKpPXPmzOhXdlxizFwSVpOEIAgqvV6//a233goZyD1YEATS0tLQarUcOnRoUoXCaOkTNA0NDRPmSC5JElVVVeTl5TFr1qxBnaU9PT2Jjo6e1BY8giCQkJBA6SD91C5EEiXMBRZK/tBEzYdmHAon+68+ie4BD3wSLxZUfaisVv65bh2zExLw9/NjxYoV/Y+98MILbNmyhZaWFt7+8Cnu/f5l3Lfm6WF73Z3LFVdcwXvvvcesGzKQiXKSy0LZ3pGPQxrfuTfaAva+wnWAqooy/vrLZ8g7VojN5ELl3yueeoqLMebmIsjlBI7Bq2ow7Ha726MRnhEqOmZXE3ylNxq9ko4SK6c/bqPk902c/GUDp95tpWlvJ901NkTn6IVWTU0Nquefh+xs+Pa3iRKjsdk7aDYXj2veH3/8MStWrODXv/41FouFtrY2QkNDUQpyUjwiKLLXo1k4D1tZGbYhjHr7kCQJURrcx+pCurq6qK6uJiVlYF81tVrd3yA+JydnTLYeI6HPADQ5OXnAhujTiYaGBgoKCpg7d+6gZqURERHyrq6uIJPJND16Af0HcElYTQKCIAgGg+HtJ554Iv6qq64a9DUXBIH4+HjCw8PJyckZVW+8yaYvylZWVobJ5N5m6E6nk6NHj2I2m1mwYAHe3kMvmoyMjMRms01qmiA4OJiOjg66uwdfTSeJEm0neyh9tYmav5kRZGC8LYDy22tpi+4kUj20/9Abv/0tT376KQ5J4ruXXcZL116L9WyU8O677+aGG24ARTun6vcSG7YMP+3ovHX0ej0mkwm5rzcFXbsxnvCn3Wlhf9f46tZG42XlkkSaHe0EKf1wuiQa63ov2PFxCb0eVmdXBJrefRcA3Zo1yAdpNjxa+iIz7q6D6urqQhOkJGiRD9F3/H/23js8rvpM//6c6UUzmhlpZtSbVV0kS7IsuYCNbcChJiTAlpCQvJBGID0EkhDyZgObsCkL+4Z1fgRIAgmwpBCy1BBjbEuybHXZarZ675oZTZ857x+yBssqVhkZ8wv3dfmyRjNzzvccnfM99/d57ud+othwbwxZd1tIuNGAPkuFe9hH/xs2Tj8xQsNDfZx+Ypi+NyaxNbvwOxePxPh8Pmw2GyarFZ55BjwerF95BLlEQ9dg2arGfeONN3LzzTdz77338uSTT5KVlRU6N7maZLyin568RCRaLfa///2C2wucPZSl8KqZBst5eXmLapkEQSArK4usrCzKy8tX3NB5IYiiSGVlJYmJiVit1rBuO9zo6OjgzJkzbNu2bdGo61n5grS/vz9lamrqvS+x/AfAJV+O+X8DTCbT1/bs2XP1V7/61SWJORISElAqlZSXl7Nly5bwVxaFCTMGojPjvBABWgpsNhtVVVWsW7duySZ8My14SktLMRgMKJXKC39plRAEgezsbJqamigsLJz1niiK2JrcDPzdhnvQj9IsI/kWI5Hr1QQFkZb+PrJUcUgXiS719/fztR//mN2Zmdz/2GPsiI3F9uabjD79NKr164m86iokxkhqW3+PShFJdvJ1yz4GnU6H3W7nxhtvZKR/iP/5xCFyR+M5LDlFgSYNnXRl2iONRrNk3duY346fIFa5gSlPkLHBjmmtkjWZ055xFCYZYjCIJCICVzCI4gI98ZYDj8ezJtfK+W1sBEFAZZajMsuJKpxOK/kcAZxdXqa6vEx1eRgpczB8ZPrzSrMMbZLi7D8lCpM0RHD6+vqIi4ubfp2RAT//OcJnPsPm4ngq93vx+pwo5CtLbQqCwFNPPUVTUxP3338///zP73ZISVFY0EnU1Pt6uWHnTmyvv46nowPlIo3ig2eJq3QJzKq1tRWz2YzRaFzSWKOjo9m2bRtVVVWMjo6SnZ29aoIsiiJ1dXUYDIZLwpB0IYiiSFNTEw6HIxTBuxBkMhlpaWmytra2jMzMzFNyufz9ZQz1PsMHEas1hkKh2JecnHzf008/HbmcG99sNpOfn8/x48fDHhEKJ9RqNYWFhVRWVq46wtbT00N1dTUFBQXLdjZWKpVkZ2dTV1d30QoAzGYzHo8n5EoviiK2Zhet/z1Mx+/HCPpFkj5mJOsuC4aNGgSJQJd3BJfoJUu9OEGIiYnh2U9/mqe+9S3MFgtTMTFY774b/d69eE6fZvCxxzh18JdMTvWwad3NyGXLX4gKgoBGo+Ezn/kMZ7raOdj6Csk1GgJikLdsdSs6J7C8iNWgbxKYEa4HGB/owGw1w9T0mk9hlOLr7SXocDC+yEN8JQincP1cLMUYVB4hJXK9mrj9kWR8xsLG++NY9+loYvbpURikTJ500f2nCZr+c5BTjwzQ8dwow0ft9DQNzL437rgDbriBuJ88R8TpQXqHK1c1dq1Wy/3334/D4eDHP/5x6PcSQcImTTKt7j6EwlwkERHY3npr0XstFLG6wFNmYmKCoaGhZTdYVqlUIfPQsrKyVVfqtra2IooimZmZq9rOWiIYDFJdXY3f72fLli3LqlRUq9XEx8fL29raMi6Gjvf06dPy4uLizLS0tA3p6ekbfvCDH1gABgcHpdu3b89ITk7euH379ozh4WEpwOOPP27KzMxcn5mZuT4/Pz+7rKwsdHO++OKL+pSUlI1JSUkb77///pg1H/wq8QGxWkMIgpAeExPz7Kuvvmpayco4MjKSkpIS6uvrF6wOuxSg1+vZuHHjig1ERVHk5MmT9Pb2sn37dvQrTPXExsYik8no6elZ0fdXguzsbBpPNWJrddP6y2Hanx0j4A6S+BED2V+0YszVhMTXAE2uHqRISFfOPzf09fXxyiuvEBgfp9hsJnr9+lBjZkEuR7drF9Z77kGSl0EbDRjG1UR2BRFXOFFGR0eza9cu0tLSeOr4Y0jbotgqSaPa2Ua/d2WEXqVSLZlkD/gnkCBglutxuAOMDbSTmBSHd3xa56U0yXA1NoJEwlSYzTbDLVyH6WvZbrcv+xqWyAUiUpRYL9eRdls0G74VS9YXLSRcb0C3Tomr30ff6za0ZXHI/OdowgQBnngCDEaKHjpET/fyTTzPxcTEBCkpKTz44INccZ6VRZ46mSAijYEBdJdfjrezE88iBSzB4IUjVoFAgNraWjZv3rwik9+ZyHFaWhqlpaUrbr3V3d3N2NgYubm5l6xXlc/n49ixY0RGRq7YqNRgMAh6vV7d1dWVEv4RzoZcLucnP/lJT1tb28njx483/upXv7JUVlaqvve978Xu3r3b3tnZ2bB79277Aw88EAOQnp7uOXr0aHNLS8up++67r++zn/1sMkxLQ77yla8kvfLKKy0tLS0n//CHP5gqKysv6ZTmB8RqjSAIgt5isbzx0ksvWVaTq1er1aFqmPb29jCOMLyIjo4mLS2NEydOLKtix+v1Ul5ejlQqZevWrStqhnsuNm7cyOnTp9dM2Ho+jAYj8soo2n87in8qSMKNBrLvsWLK1yJIZ098oijS7O4lTWlFKZl7nHa7nWuvvZZ/+Zd/YaBuOmKkTE3FaDRit9tDpFWq19OdOQVyKevGU5l86SWGf/lLPCvwQouKimJiYoJvfvObNLSdpLLtOIn1EtQSJa9OrsyvbDleVkO+CaJkOmSClEmnl4988b/45nfvwjs2TazkBinuxkaUKSkEV3ltnI+1iFhNTU2h0WhW/XAWJAIqi5yoIi1JHzWR85UYZFfZEYISxuvOKwwwmxGefBLd6UFif/oCDufKtYaNjY1kZ2fzwAMPsH///lnvxciNmGV6ap2daAsLker1i0atZiJW0kXORWNjI4mJiauWEcTExFBYWEhVVdWyC2qGh4fp6Ohgy5YtF6WDw0rgdrspKysjKSlp1S21YmJiJIFAwDA4OLimXaSTk5N9O3fudAIYjcbgunXrXF1dXYrXXnvN8NnPfnYU4LOf/ezoq6++agS48sorp8xmcwDgiiuumBoYGFAAvP3229rk5GTP+vXrvSqVSrzpppvGXnzxxUu6quDSvIre5xAEQWo2m//66KOPJpzrHbRSyOVySkpKGB0d5dSpU5es11VCQgJms3lWk+TFYLfbKS0tJTk5OSwaCZg+V5s2bbpoJqZDhx1IB9V40yfIvsdKVOFcQjWDYb+NsYCDbHX8nPf8fj+33nor9fX1PPfcc2jGxpBoNMjMZgRBID4+nt7eXgAGRuvpG6kmK/kaEj55F8aPfYygw8HIr37F2Asv4D+nie2FoNPr6Rt18y//ehvx8fFUjRzGUyfnioiNdHiHaHSvLPq3VAf2Ad8EMfLpOXJyyokpJpWigo14xgPI9RKCEyP4R0dRLVApthqsRcTqfH1VuCCKIkO+ftTxcsZr5qm4vOYa/J+7g/QXahn94y9XtI+RkRFkMlmoEm5ycpL7778/VP0qCAK5mhS6vMNMCl50u3bh6+nBs4Cn24zGaiGuMjIygs1mIzU1dUXjPR86nY4dO3bQ1dVFY2Pjku7/yclJTp48ydatW5HJLk3Jsd1up7y8nPXr1xMfP3fuWC4EQSAlJUU6NjYWb7PZLoqXRHNzs+LUqVOaXbt2OUZHR2XJyck+mCZfY2Njc078Y489Fn3FFVdMAnR3dyvi4+NDed6EhARvb2/vJW0sdmleSe9zWCyWn99+++35t956a9iW2FKplMLCQk6ePElVVRX5+fmX5Opq3bp1NDQ00NTURE5OzoKfGxgYoKmpiYKCghWn/hZCdHQ0AwMDtLW1ha1h8nxwdHoYOGjDsEnNSOoAI2PDc3xkzkXTWZKSpZo9OYqiyN13382rr77KgQMH2L9/PwM/+QmKlJQQ2UxISKCyspKExDjqTr+AThNDRsK+aZ1Ubi6q7GwcR47gOHoUV1MTuh07iLjsMiTzWAmIokjvmI+GThcN3S5szhSEU04aGxvpP9aB6x0T1h4nZpOeNyZryFTFIROW5xk1Y7mwmJWBO+hjIjBFoXz6b9R65gwnXn+Dfyq8GsWYH4VRhrtx2ohWnZ0NVVXLGsOF4HK5wk6sRkZG1uSaGx4exmQyYdqsofd/J3EN+FDHzJ5eZD/5T5yvv4z1q48gfujzCFFLJ3gzgui8cxotu91uHn30Udra2njuuecAyFUn85atjjpXJ5fl52M/fBjb3/+OMiNjzsIoFLGaJxXo8/mor6+npKQkrKk3uVxOcXExjY2NVFRUUFBQsGAU3Ol0UlVVRVFR0UUpeFkJRkdHqauro7CwcOXz5Je/DDU1s34lBbJEUepyOrOCguCUwPJWoRs3Onnyye6lfHRyclJy0003rfv3f//3bpPJdMF0xssvv6x75plnoktLS5tg/si3IAiXZnThLC69J/P7HJGRkbfl5eV9/OGHHw57KZ8gCGzcuBGDwUB5efkl0RD5fMyM0eFw0NHRMed9URQ5c+YMbW1tq9JTXQg5OTn09PRgt9vXZPt+Z4Cu/xlHYZCScL2B7JxsmpubF10lN7l6iZOb0EtnP8z/9re/8d///d/ce++9fOYzn8E/Pk5gchLlOSt5tVqNTCaj/vRLOD2j5KX/ExLJu+siiUKBfs8eLPfcgzonB/uhQwz+53/irKlBDAYRRZH+MS9v1Ezy85cH+eUbwxxrdRBrlGOJCFDd4Uam1JK8PYPBqR6GKkbZH5nPWMDBMcfS/LrOxVIE7ENnHddjZNMRkpoTx3j11z/A6QjgGfOjOKuvkickhM1i4Vy4XK6wN/i12WwL+gmtBl1dXSQlJWHYqEaQMn/USqPB/sv/QDE2hef/uQ2W01ZocBCtVjsrJWe1WvnKV77C888/T9VZUmuURZCoiKbO2YEgk6HbvRtfXx/uprkeWjMaq/kkVvX19WRkZKxJ8YAgCKxfv56EhARKS0vnvQ69Xi/Hjx8nLy/vkq267uvro6GhgZKSkjWZJyWCgEqlElzBoGatWIrH4xGuvfbadTfffPPYJz/5yQmAqKgof2dnpxygs7NTbjKZQsZ5x44dU3/hC19I/vOf/3w6JiYmAJCUlDQrQtXT06OIi4u79B5+5+AfLmIlCIIUOAH0iqJ4nSAITwO7gMmzH7ldFMWahb5/gW1npKSk/PTFF180rGU0ad26dajVasrKyigqKlqTyWk1EASBgoICysvLUalUxMRMC7VFUQy5pJeUlKxpxE0qlZKXl0dNTQ07duwI675EUaT7jxP4pwKk32lGqpKgRYter2dgYIDY2Lkmx/aAi17fKFfoNs15b9++fbz00ktcd920ZYLnLCE9t5RdFEX0UV5a+g+RaC0h2jB/5ZIsMhLTzTfjKS5m8tVXOfPXg3TUTHDGkM6YS0AiQFqMkt0bdWQnqFErJDR3wrOlbk6cnqKn9q/c9vPbeP7zr7L/Ji0ZylgO2U+yWZOKVrp0ErIUk9BB/9mKwLOpwJ6uzmkvt9RNdNidyDV+fH196PftW/J+l4twRkucTidqtTrs4mev18vU1BQGgwFBENBlqhivcxJ7pX5O2jn6iltovuMAOQdeg9/+Fj7xiQtuXxRFmpubKSoqmvPe17/+dX7xi19w//3389prrwGQp07hr5MnGPCNY83LC0WtVFlZCOfcZwtFrPr7+wkEAmFJay2G+Ph41Go15eXlFBQUhAhvIBDg+PHjZGVlYTKZ1nQMK0VbWxsDAwNs37591bpTfv7zBd+SAlNDQwxNTXlTU1PDIuLt6+uzjI6OmkVR5Dvf+U4gMzNz6sEHHwwJ/66++uqJAwcORD300EMDBw4ciNq/f/8EQGtrq+Lmm29e9+STT7bn5uaGemLt2rVrqqOjQ9XU1KRISUnx/fGPfzQ9++yza9/2YxX4R4xYfQloPO933xBFcfPZfyslVSqLxfK/f/jDH6LXKgpzLuLi4tiwYQPHjh1bcSXMWmLGQLS5uTnUTLiiogKlUnnR0pgGgwGr1bpkh/SlYqRsCluLm9irI9HEvZvqmnFjny9q1eLuQ4RZ+qry8nIaGhoQBIEbbrghdE68HR0hfRXAyEQrR2p/Rkv/c0hENetTblx8fDYfZTYDLyR8mP9ZdwsnFOtQjfSxV3qGr+3V8ond0eSnaVErpveXkWjEqJiivMXBFXv2oVQq+PXh/0NnaTP7I/Pxin4O2pfnbL8kYuWbQCnIiTwbwRvo6cIQbUbpOxtBmJquhF0LfZXP51v9A+s8jIyMrIm+qqenh4SEhBBhM+Vp8DuC2Nvm9mOUShW4v/QZRvPiEL/4RVhCwUtvby8mk2netGhkZCT33Xcfr7/+Om+//TYAG9RJSBCoc3YiSKXod+/GPziI67z+ofNprNxudyjleDGq70wmE0VFRVRXVzM4OIgoilRVVREfHx9a8F1KmKmQHh8fp6SkJOzX6Hwwm81CIBCIHBkZWTXLnJqaUo2OjprXr1/f2Nvb2/nyyy9rjxw5os/Ozl6fnZ29/vnnn4/8/ve/33/w4EF9cnLyxoMHD+q///3v9wN85zvfiZ2YmJDdfffdydnZ2es3btyYA6Hqwq79+/dnZmRkbPjwhz88tmXLlkvXPZt/sIiVIAgJwLXAD4GvhnPbFovlwH333ZdYUFAQzs0uiqioqJCH1KZNmy7onXOxoVAoKCoqoqysDKlUuizTz3AhPT2d0tJSxsfHl2w+uBicvV7635xEn6Miuni27lOtVhMdHU1PT8+c42xy92KQarGeTXudPn2a66+/npSUFCoqKmY9ZDzt7SiSkxl3dNLY8TLDE02oFJHkpt+KYySSyXEX6pjZ6aZxh5/6LhcNnS4GJqaj5MlmBdcWRpJtlSIcb8ZeWoq9+RDizp1E7NgR0l9JJBLWGac4Mailb0rDHXfeyf/3X7/gznc+Sc5VW9iiTefE1Gm2ajOwyJeW5looFSiKIn6/H6/XS69rBJOooa+vD7/fz3B/F+bYWFpr2oAIHB11KHQ6Grq7CXZ2hjQxgiAgkUhCzaqlUikymSz0b6Z5r0KhQKlUolAo5hD5mehSODEyMhI2Ifa56Onpobi4OPRal6lCqhYYr3Giz5gbRUyK286J+/dw5R1/QrjtNjh0CBbwOwoGg5w+fZpt27YtuP+77rqLhoaGkBO5VqpknTKWelcn+/R5qDdtwv7OO9gPHkS9fn0oanV+xEoURWpra1m/fv1FbWocERHBtm3bOH78OGfOnMFoNJISZk+0cCAQCFBdXY1Go6GgoOCi2T7MiNmbm5sTtVqtQ61Wr9gQzOVyqTUajUMqlQY/9KEPObq6uvokEkkwPj5+VqlqWVnZnNXu888/3wnMW9p86623Tt56662T8713KeIfilgBPwe+CZxf2/tDQRAeAN4CviWK4tyl4CLQ6XS3bN++/fovfelLF91bQ6fTUVxczPHjx0lPTycuLu5iD2FRBALTBr9+v39RYfdaQSKRsHnzZk6cOMHOnTtXVfkTcAfpfGEMWYSUxBuN8058GRkZlJaWEh8f/24EKujnjHuALdp1CILA6Ogo11xzDaIo8rvf/W7WdvwTE9gCIwwluBipOYxCHsHGtI+SGnsZUqmCSe0kzc3NxMTEMDnlp6HbRUOXi97RaTKVECVnf34kG5LURGrOeZju24emsBDbG29gP3gQZ1UV+iuvRH3WDyc7IYI2h8jRRgdf/drXePwXv+B3b77I5o+ncUXmJuqcHbw2Wc0noncveo58Ph9OpxOHw8H4+Dj19fU4nU7cbncokieTyVAoFQzFTJLsM+IMOBEFGWMDnaRftpUIIRIbAVQTXSi35pKWloYgCExMTJCenk7wrGZMFEWCwSCBQAC/34/f78fn8+FyufD5fHi9XjweD16vN7RvuVyOWq0OfW9kZAS1Wo1arV51FHVycjLs+iqbzYZSqZwlrpbIBAybNIxVTRFwB5GqZo/bpE9DkpJG67c+TNa3n4Uf/Qjuv3/e7Xd3d2O1WhcVb6vVap5++ulZv8vTJPPieB+d3mFSlRZ0V1zB+Asv4KqvR3NWAB84T2PV1dWFSqV6T1rFKJVKrFYr7e3tREZGIoriJeVX5fP5OH78ODExMaSlpV30/ctkMlJSUmTt7e0Z2dnZpyQSyYpkV2q12tXX1xfv8/mkEolEtNlskRqNZuG+X/+X4h+GWAmCcB0wJIpipSAIu8956z5gAFAAvwTuBf7fZWw3NTEx8b+ee+4543t1o6rVarZt28aJEydwuVxrWgm3HIyNjVFbW0tRURFut5uKigq2bdt20cuaIyIiSE5O5tSpU+Tm5q5oG6Io0v3SON7JAOmfjkammf8hrFAoiI2NpbOzMxS9OOMZwE+ALFU8brebD3/4w3R1dfHWW2/NcpuenOrl5KlnGSqeQC64WZ98I2nxu5Cd1Tb5AiKTXhXNw0pq3hikZ3Ra8xlrlHNlnp6NSWqMEQufW5nRiOnWW/F0dDD56quMv/giU8eOEXnNNURHR5GmH+BEfyRuqZl//ZeP86f/+TN3Hf44iTk57NJt5HVbNa3uPtKVsbjdbmw2Gw6HA7vdjsPhwOfzoVAoUKvVIS+n2NhYNBoNKpVqFnGZ9E/x18EzZFtSyYjIYMzh5+7/LCPHUovCq0IisyP43Rjy81GcJStSqXRVIl5RFEPEq+2ssWV/fz8ulyuUttRoNERERKDT6YiIiECv1y/J3XpGCB/uFPeMaP18GPM0jFZMMXHKRVTB7MipIAgkWUto3DHEups/gux734OrroItW2Z9LhAI0NbWxs6dO5c0ljNnznDgwAEefvhhslUJKAQZdc4OUpUW1OvXY7dasb39NuqNGxGkUs7yKqQSgampKdrb25e8r3Cjt7eXkZER9u7dS1NTE9XV1Ss2JQ03XC4XFRUVZGZmzqvPvFjQarWYTCZFV1dXUkpKyvJN8aa34bZarQPNzc2ZEokkqFarnZcSgb1Y+IchVsAO4AZBEK4BVIBeEIRnRFH8+Nn3PYIgPAV8fakbFARBYTab//rCCy+Yw5FmWg1myoxrampoaGhgw4YN7+mKbHh4mJMnT1JcXIxGo0Gv1+N2u6msrKSoqOiiT2gpKSkcO3aMoaGhFUXORk84mTzpJvZKPdqkxUuz09LSOHLkCImJichkMprcPagEOSlKCz96+N85cuQIzz//PDt27ADA7hykqfN/6R2uRBqUEt+jJ++W7+LyKWnq9dI9MkH3iJf+cd/Z9Eo0BrWXPZsi2ZSsIUq3vNtYmZKC+bOfxVldje1vf2P4wAHUeXlEaiOI1Jg40ujghw//kE8UfgJtfzKD/d0kBrVEBBT8qb+Uwg4TWrUGnU6HTqcjKSkJnU43Rw8yPDyMwWCYl0gP+KcrAmeE6w6XH4VKS0JcNJ4GP1KpE5lGjzyMEVhBFfZGPwAAIABJREFUEFAoFCgUCuRyech3bQaiKOJ0OkNEcWRkBLvdTjAYRK/XExkZicFgQK/XzznWpbSxWS6CwSDDw8Osn0djpkmQo4ySMV7jnEOsABKtW2nsfJm279xKZtlx+Nd/nbar0L772Y6ODhISEpas46mqquKRRx5h48aNfOITnyBbFc9JVxfXGgqRSaTo9+xh7Pe/x1lbi7ag4JyqQJGamhpyc3PfE6+okZGRULNiqVTKhg0baGlp4cSJExQWFi6rLUy4MdMbNTc395IQ0lutVsnp06eNo6Ojk1FRUUs3xJu9jRGr1ToC0NnZGa9QKFbXa+h9iH8YYiWK4n1MR6c4G7H6uiiKHxcEIVYUxX5hmoV8GFiyStdisTz65S9/OaWkpGRNxrxcSCQS8vPzaWxspLKykvz8/Pdk0ujr6wvpNs5NMSQlJeF2u6mvr7/orSNmGjU/1/QmGomRSLkWvVSDTqpGJ1Gjl6rRSdXz+jW5Bnz0vTqBLl2JeceFS7PlcjlJSUm0t7ezLn0dLe4+Ms42Xf7a175GXl4e1157LVOuEZq6XqF78BiCoMZk+AiOYy4aIxI59IoNm2tapCKTQpxJQUlmBInRCqx6OFl7nMs3Xr7y8yGRoC0sRL1hA/Z33sFRVkYa4N+exKFhPR2DLlTpCoQyBU1vVxFbmM1luixeldajK0pka8SF+7rNCNjnizKFegSe1Wz9/eBb/O13f2X3Ax/BO+ZH8A6j2pyzZtfIfK7rgiCg1WrRamcTlWAwiN1uZ2Jigt7eXk6dOkUwGMRgMBAVFYXJZGJkZCTsjXsHBwcxm83zLkIEQcC4WcPAWza849OeX+dCo4oiOjKTTvcpMn79a4R9++DrX4fHHwemU09dXV1cdtllSx7PRz/6UQoLC3nggQe49dZbydWkUOfqpNXdT446AVV2NvK4OOxvv40mNzekserv68VoNL4nxMFms4UsC84lkJmZmbS3t3Ps2DGKioouikj8fMwsPgsLC8PSwP58rCTdKQgCqamp0ubm5mStVjulUqmWbWvg9XplCoXC73a7FZOTk4acnJy5XhxriGAwKABr3wxxEfzDEKtF8KwgCGZAAGqAzy3lSxqN5rqioqJb7r333vA6DK4SMx4u7e3tlJeXU1RUdFGFol1dXXR1dbFt27Z5J6uMjAzq6upoaWkhKyvroo0LpnvYDZi9eNw9CB4B/zz3nkainEW0dAE1Uc8ZEVQSFNcLOEQ3WlGJRFg84paSksI777yDND6CqaCH/r+dZHRvFlFRUVyxdxulDS/S0jvAlDcBP3cz4dQR6AEiQC/1k2xWkhitmCZSBjmy88rqVSpVeDQ9CgW+ggLsBgPSQ4dIKf0jpVm30Tys4rqiTK78wtXs3LCDR2+9hgxBSuPIIH+317FJk4xasvh1NSNgn59YTWCQalGd3cbhwwcp++t/E/2T2/GO+1GJk6iys1d3bItgOe1sJBIJkZGRs851IBBgYmKC0dFRenp6GB4eJhAIYLfbsVgsYRHGd3V1LWqya8xTM/CWjfFaJ9bdc89xkrWEqpbfMFaYRNTXvgb/8R9w7bVw3XW0tbWRkpKyrAiSRCLh4Ycf5qqrruLAgQPcdfcX0UqU1Lk6yFFPVy3q9+xh9JlncFZXE4zdCMDIyDBb92xd/glYJVwuF5WVlWzZsmVev7LU1FTkcjnl5eUUFxdf1Hmyp6eHtrY2SkpKwu6lBtPzw+joKFFRUcsmVzKZjKSkJFl7e3tGVlbWqeVmF06fPr0uEAjIBEEQk5KSuuRyeWBZG1gFgsGgMDw8HMkyAiRrgX9IYiWK4tvA22d/3rPc7wuCkBAfH/+rF1980Xgp5OjnQ2pqKiqVirKyMrZu3XpRvK7OnDnD8PAwJSUlC07YgiCwadMmjh8/vqB+ZC0hlUiJd6jYr8nDFGPGHnRhCzixB1zYAi7sQVfo5wHfBFlvJRE1JvDOdbUMOyfBCRIEIs6LdOnPvp7+eToSlpqWStnAKc4creOhTz3C3z9Wyodu/xLDNiXewLaz44F4k4LsBAUWRx/agy+RcucnUcQuvrqfacy8adNcX6zFIIoiDoeDoaEhhoaG8Hg8GI1GzAkJSD7yEXy//z257jaqRjOQqIzoorX8/tBz3F3zcbIKivlQZAH/Pfwah+wN7I9cvAJ2McuFQd9EKA0I0N52Br0pFqs6hoGggFTumuXjFW4Eg8FVRXOlUilRUVFERUWFUtwZGRkMDw9TU1ODx+PBZDJhNpsxm83LToG53W68Xu+imjKFQYY2RcFYrRPLLt2cB2iceTO1p5+na/AYUf/2b/Dmm/DpT+OtrKS/v5/LL19+xHPfvn1cccUV/Nu//Ruf+tSn2KhOonKqDXfQh0oiR5mRgTwhAfuhQ/huml44edRpjDkCROsv3lzp8/moqKggNzd30WhQQkICMpnsos2TMwbJw8PDCy4+w4GEhIQQ4V8pJicnVUePHs3U6/XL7cY+OvNDZ2ensrOz82La2geBBr/ff8dF3Occ/EMSq9VAEASZxWL56zPPPGM+V59xKSI2NhalUjnHIG8t0NLSwuTkJFu3br2gfkoikVBYWEhZWRkqleqiVgtKBAGD0UhrfSvboqKxqgyzHvDnYqx6iu6WCQy7VHxkczH2wAzpcp4lZC5G/XY6PEO4xLkyAplMSs/rQV780mNEJ2STddW3GLYFMOvdZCdEsS7WQMw50ajxPx/EJReRL6FqymKx0NjYSDAYvOD5DgaDjI2NMTAwwMjICBqNBqvVSl5e3izvokAgQHVWFjlN5dRkrKO0ycH3fvAgV16zjyd//nt+9JtiYhVG8jVpHHO0UqTNIEq28ENLrVYzOjo65/d+McCI30b2Oa19ejo7MMUkIpvSAF7USQaENUpjBwKBsGr8ZvyrZqJa6enpBAIBxsbGGBoaorm5OWSUGxMTs6QIxYx31YVg2qyh+88TOHt8aBNnR1xkUhVx5nx6hyvZtO5mZM8+C4WFeP71X0k/cGBF50AQBB5++GF++9vf4vf7ydWmcGyqlUZXN/na6epN/d69jP761wi175BoyKW+G2q7hkg2Kyhcp2V9ogqFbO1IVjAY5Pjx42RkZCxJ9xYTE4NcLufYsWNs3bo17G2OZiCKIg0NDfj9foqLi9dUZyqXy1dt/REMBoWdO3f6q6qqPud2u18L09D+IfABsVomzGbzv915553pu3fvfl+UOswY5J04cYINGzawFmSwubkZu91OYWHhkicLmUzG1q1bKSsrQ6FQhBq/rjUEBASJwIYNG6ipqaG4uHjeULl72EfvXyfRpihIusKEMF9fjnPgDfpxnCVbM+Sr7GgTz37jTtQRGr75w1vYmltNfvo+tOr5TSQ9HR0ok5NnuVcvBIlEgsViYWBgYF6LjRnhc29vL5OTk5hMJmJiYsjJyVkwUiOVSvHEx2OSSMgYbqb6TDZfuXEXeel5/PblF/nGyFeJjk5irz6XBlcXb0zW8M9RC2t0NBoN3d1z24mN+G0EEWcR2oHeLrIKduFrtwNKInLWzpU73M2XR0dH55AgqVQailYBOBwOBgYGqKysJBgMEhMTQ3x8/LzjEEWR3t7eRb2lZhC5Xk3PXycYr3HOIVYASdZiugfL6R+tJXFDEd6HHkL3ta8RkZ8P+/fDzTfD9dfDMqoti4uLQ75aBlHEJI2g1tVBvnbaJkCZloYkPh79yRo+/Y0rcQZlVLc7qTozxR/Lx3mlUiA3RUNhmoZYU3jTb6IoUl1djdVqXZb1TFRUFLm5uVRUVKwJuQoEAlRWVqLX69m4ceMlZfWwECQSCX/605+M+fn5TwuCsFEUxZH3ekzvF1yaeaxLFIIg5FksljsefPDBi9IRPFyIiIigpKSEpqYmenp6wrrtGVJVUFCw7BWYUqkMuSJfyKU7XJAgICJisVjQaDR0ds6tKg76RDpfGEOQCyR/7MKkCkAhkWGS6UhRWtikSWZ7RDZPfPNHSKVSHvrZR7lt/yfYuemfFiRVgclJAmNjy0p/zaQDZyCKYigVdejQIYaHh0lJSWH37t3k5eVhtVovmP6Kjo7Gs2UL+f5O/KJAReMk9379XvonevnlIwcA0EnVXKZbT6O7hzbP4ILbWsgkdNA3uyLQ5XLh9/uxxsXg6hgHgmhz187LZzn6qqVgfHz8gguDiIgI0tPT2bFjR0jPU1NTw+HDhzlz5gxu97tG0hMTE2i12iVpfqQqCZE5aiYanAT9c62HoiMzUCtNdA+WA9C4dy8jf/kLwuc+BydOwMc/DhYL3HgjPPMMTC7dg/Hw4cMcOHCATZpk2j1D2APTf+tAIECXxYLM68V54gQ6tZTL1+u45zorn9oTTWaciqozUzz++jCPvzbE8dYp3N7waI0bGxtRqVQrspwxmUwhchXO+cjr9VJWVobFYiE7O/t9QapmYLVa+cUvfhFlsVieea/H8n7CB8RqiRAEQR4bG/vygQMHot6LkuHVQqVSsW3bNnp6emhtbV20WfBSsRpSNQOtVsvmzZupqKjA6137qlxBmCZWAOvXr6ejowOHwzHrM32vTuAe9JN0kxG5fmXpqElngA997r/48kP3c9WOO+jpGl/08zP9ARXLIFY6nQ6fz8fw8DANDQ0cPHiQvr4+EhIS2L17Nxs3bsRkMi1rIo+KimJkcpJ1H7maZHsHx5rt3PjJj/L9W/6dncar8Qem/0bbI7KIlGp4bbKKoDj/Q1Emk4UMYs/FgG8CKZJQGlGtVvPdp46z/+Zb8Ax7kMo9SFVrJ8sIZ8TK7XYjl8uXpddSKBQkJyezfft2ioqKEASBEydOcPToUbq7u+no6FiW9tC4WUPAJWJrmdvlQxAkJFqLGRpvYnS8D5vNRtR11033j+vqgqNH4fOfn7ZiuO22aZJ1/fXwm9/AxOLV9k899RRf/vKXiR6RISJS75pepJw8eZKYggKUaWk4jhwhePa+lggCqVYlH9tu4hsfieXawkiCosjLJyZ45M8D/LF8nM5hz4rnpvb2dpxO57z2FEtFOMmVKAbpG2rkaOlR0tPTL0m396Xguuuuk+Xn5+/SarW3vtdjeb/gA2K1RERHR//wjjvuiBIEgYaGhnkfGJc6ZtJvDoeD+vr6VZGrcJCqGRiNRrKzs6moqFjz8ypBIMi7DuAzjZpnzsVEg5PRE07MOyPQZy6/Wqeuro677rqLt2u70Bmt7L8smXUpBUxNTWG32xf8nqejA0GlQr7E/mU+n4+Ojg7cbjd1dXVERUWFIlPR0dErXhUbjUbGx8dRJCSwPUWGGzmVZe3cdufNRDrX0dVUB4BckHGlPo8B3wQ1zoX70QmCQDA4m3gN+iYxy/VIz1ZWiqKIx69EqwgS8KtRGtfWIiScxGqm8mqlUKlUpKWlsXPnTvLz87Hb7fT09NDX18f4+PiS7lFdmhJZhITxmvmJQJK1GBCpa3ptdsREIoHt2+FnP4POTigthbvugtpa+OQnp0nWddfBr389L8l68MEHEUWRxx76KXFyE3XOTgYHB3G73dPeZldcQXBqiqljx+Z8V62QUJwZwRf2W/jsVWbyUtU0drv41d9GeOx/hzjSaMfhXvpc0N/fT19fH/n5+auOCIWDXDndY7xT/XMqmh4jJT3ykuxLuBSMjY1x5MgRfvSjH6kiIyP/82wF/Qe4AD4gVkuAIAibrVbrpx944AHNtm3b0Gg0HDlyhIkLrOguRcy0eFEoFBw/fnxFRKalpSVspGoGMTExJCYmUllZGZZo2kIQEGZt32g0Eh0dTWtrK54xP90vTaBJkBO7d/kO33V1dezZs4eXXnqJI7X9mDTtFGVdPd0yJjubpqaF7Vw8HR0ok5IuqK8aHx+nqqqKo0eP4vP5QqaHMTExYflbzPTd83g8ZO8rIiYwTnm3iCVTzxuNf+Hzd3wzdP42qZNJkEfxN1sdnuD8djfzpQMHfRPEyN5NnT3xq6d48bEvoXTbCaBHFR9+T59zEc5U4OjoaNgaL88Y6a5bt464uDjOnDnDO++8Q3t7Oz7fwnZCglTAmKvB1uLGPzX3fo5QW4jUJmP3nUKpWWA7Egls2wY//Sl0dEBZGdx9N9TXw+23T5Osa6+Fp5+G8enoa1JSEl/4whd46qmn0HcH6PONcaK1js2bNyMIAsrkZJTp6TiOHiXomb9LmCAIxEcpuKHIyDc+EsNHig2olRLeqLHxH38e4Lkjo7T2uUNmo/NhbGyMlpYWtm7dGjbfvnPJ1Xzp7IUgiiJdA+W8deIHjDtOo9ckkhK/OSxjupgIBoOcOnWKxsZGioqKyMvL4/HHH4/+ICW4NHxArC4AQRAUFovlf1544YUomUyGIAikpaVRUFBAfX09zc3Nc1bklzpmHvRWq5WysrJlpeDa2tqYmJgIK6maQXJyMnq9ftXRtMUgnBOxgumJMC0hneEzY7T9fhhBgOSbTQjS5a16a2tr2bNnD2q1mu8/+igaQwo7cqKQy6Yf4NHR0fj9/nnJeMBmIzA6imKBKp5AIEB3dzeHDx/m9OnTJCUlsWvXLjIyMkLtV8bHF081LgdRUVGMjo4iSCRcXhSDXa6j5q1y7JoB3ig/yF/+8jwwfR19yFCAI+jmsKNx3m2db7ngDHiwB11YzhGu/+3vB+k8VY7O4UREhdK8ttXZ4YxYhau59wy6urpITk7GYrGwZcsWtm3bht/v58iRI9TX189JW8/AuFkDQZhomJ8EyLwbkMokHKr+EV0D5YsPQiKBkhL4yU+mSVZ5OdxzD5w8CZ/6FFitcM018NRTfPvzn0ej0fDCw08giNCZ6sUte5fc6ffsIeh0MlV+gX0CCpmE/DQtd15p5ovXWCjJjKBjyMtvD43ys5cH+Xu9jYkp/6zv2O12amtr2bp1a9itC0wmE5s2baKiogLPAsTwXHi8dipO/ZKqlt8QCHoQBAmF2bchXMDz7lKDzWbjyJEjyOVytm/fHjLMvfHGG6U7duzYGhER8U/v8RAveby//uLvAcxm8w/vvvvuuPPz9jqdjh07diCKIqWlpQtOeJcykpOTQ02Dp6Yu3Cezu7ubwcHBZVX/LRdZWVkEAgHOnDmzqu0EvUE8Y36mujxMnHIxUuFg4C0b6QcTSPxLDC0Hhjj1kwHq/98+Gn88SERZIt7BIPE3RM5xsb4Qamtr2bt3L2q1mv999Q8MB1PQqWxsyZh9zeTk5MwbtZrRVynPI1Yej4empibeeecdHA4HW7ZsoaioaE6q73wR+2oRHR0dsklYnxmFSRGgUkzgk/t3ER1h4eHv/zj02URFNLnqZErtTUz4515DarV6FrEaPNvKJuYcYnX6dAummBQiJqYfmkrT2moYA4FAWFqreDwepFJp2KIkTqcTURRnOb8rFAoyMjLYvXs30dHR1NXVUVZWxuDg4KzFhzpGjipGPm86cGxsDIXEzN4t38aoS6Gq5TdUtzxDILCEBZUgQHHxtLloeztUVMCXvwyNjfDpTxO9YQN1CQl83B+kYCKGMcHJ40Ov0uLumx5/QgKqzEzsR48SdM/VgC0ES6Sc/QWRfP3GGG7ZYSJaL+NQg52f/WWQ3xwc4WSXiynntAFoYWHhmvlPRUVFkZOTQ0VFxaJRw76Rat468QMGRhtQCNPViBkJVxEZcWHLjEsFoihy+vRpqqurycvLIyMjY05a9YknnjB8kBK8MKQPPvjgez2GSxaCIGxOS0v72TPPPBO5UFuJ6OhodDod1dXViKKIwWB4X1V9REREEBkZSWVlJUajcUGPnf7+ftrb2ykuLl7Tfl+CIGC1WmlpaZn2xDmnDFwMiPinpgmTq9/HVKcHW6uHyZMuxqqdjJQ7GDxsZ+AtG4MH7YyUTzFW5WSywYW9xcNUlxfFlAxBBJ1OjSpGjm6dksgNaoz5GrzrJplUjCzbV6u1tZWDBw/y+uuvc2aigY7RDezZGEGSeXb7G5VKRX9/PyqValbExHHsGP7RUSI/9CEEYbphbWNjI62trVgsFjZt2oTFYllwRa7RaGhqaiIxMTEshFepVNLS0kJKSgqCICBTyKgekpLYdQxBTOQPh//I1fv3kZgwLbCOk5s4NtWKLehigzpx1rY8Hg8OhyOULmt299Hq6eeqyM0oJdPH8+37v01MWj43pW5A5k3GcrkOecRcstLR0bFqAXAwGKSrqyssQuKhoSEkEknYLEza2tqIioqa129OEAR0Oh2JiYkYDAa6urpoaWlBJpMRERExXZThDTJW7cKwUY1M++75q66uZsOGDWg1kSRYtyICbb0HGRirx2zIQiG/cJums4OA+Hi48kr40pem9VeRkUTW1rLh2DHS91zHhoKrOe0eoGyqGa/oJ1VpRW42M1VejiCTzVk8XAgSiYAlUs7mVA2bUzUoFRJOD3ioanNyvNXO5qxYkuLC26PxfGi1WmQyGSdPniQ+Pn7WPeb1O6lpeZbGjpeRosequQqv0IZSoWdLzqeRzNMi61KE0+nk+PHjKBQKCgoKFiSqarWajIwM1cGDBwu//vWv//YiD/N9g/dfedtFwvkpwMVgNBq57LLLOHXqFOXl5WzevPmiOJ2HC0ajka1bt3L8+HFycnKwnmdQOTIyQktLC9u2bbsoTVQlEglFRUUc+2sVjtckCB4pfkcQvzMI82QIJSoBeYQUWYQETawCWYQEWYQUue7s/2dfy7QS/s/Imyglckqir5izHYOYSllZWcjw8UKYES5fdtll1NfX0z9aTUtDNApZgC0Z83epz87Opq6uju3bt4cIuLejA0VyMja7ndbWVtxuN+np6UvupygIArGxsfT395OYmHjBz18IMpkMiUSC1+tFoVCQl6rhrbpJ6iwF/Mt2PU8ejOTB736H1998GwCDTMsOXTaH7Ccp9mSSpHz33Gk0Gvr7+0OvB30TaCRKIiTTBN5utzM6MkyuNRWtNAo/oFhD8brb7Q5bC5HR0dE598pKIYoi/f397Ny584Kf1el0bN68GZfLRVtbG62trSQnJxO7IR7egPFaJ7H7psnZ0NAQSqUytECRCFLWp1xPlD6Nyqanebv638nP/Djx5sLlDVgQYMsWxMJCyq+9lpKbbqLnpz+l3O/nM7d+jFcnqjnqaKLTM8wtlh2ocnJwlJYSUVKCZIVzozFCxp5Nei7P0fLKO/W0TEbzUnUAldZNZlz428Kci/j4ePx+PydOnAg1kR8ab6S6+be4vTYipHkkRl+OV3aSvt5RduZ9Fank4vcfXC5EUaSrq4v29nY2bdq0pEKMG264QfrrX/96S0RExD87HI7fX4Rhvu/wQSpwAZjN5ofuueeeuMV6dZ0LqVTKpk2bSE9Pp7y8nN7e3jUeYXih1WrZtm0bra2ts7ydxsfHaWhouOi9tGQyGVZbCu5ePxIdROaosO7SEX+9gZR/NpF+p5mcr1jZ9N04Nt0fR/Y9VtI/bSb5FhPx1xiwXq7DlK9Fn6FCHatArpMiSIRZdgvnQxAE8vPzaWhoWDTsD1BVVUVmZiZPPfUUAIGghxPNrzLpyqYoXb+gs7ROp0Oj0TA0NDT9Pbsd/8gIgxIJjY2NpKamsnPnTmJiYpYV+UxMTJzXjHOlmNFZAcilAiVZOrpUsSiFCb687z52Z+2clYraGZGDTqI+a79wTorqPPH6oG8CqywydGyjo6MkpWVgTkhHqY5DppUgVa7dtBROfdXY2FjYGguPjo4SGRm5rIWLWq1mw4YN7Ny5E7/fT3l1KdK4AOM1TsSgiCiKNDc3kz1Pz0WraQO7C+5Dr43jeOOvqD39PIEFChAWQ3t7O3qTCeHGGzFXVPDVu+7CPm7jBmMRNxu3M+yf5PGh1+jfvRHR48Fx9Oiy93EuRFGkvr6OnEQtn9sfS7Rexu/eGaW2fe198JKTk4mKiqKyqoKa1ucorX8MiUSBnn1kJn4IS6yaM70HSYm9jOjI9DUfz2rh8XioqKhgfHycnTt3Lqu69YknnjAYDIafCYJw8dpmvI/wAbGaB4Ig5MfExNz+rW99a9kzsNlsZufOnQwMDHDixImL4s0ULiiVSkpKShgYGAjZKdTU1LB169Y1aRS6GMSAiKvbj36jip7EU0RdqSJmj57oIi2ROWq0iQoURhkS+fLSrpLzqgLPh1qtZt26dTQ0LNzDs6qqin379qHT6di9ezcAJ9v/RN9EFiCwNWPx1EpWVhbNzc1MTk5y6q23ALDm51NSUrLi0n2tVosoimEzNjxXZwVQlK5FIRNoXH85N20r5mrrJxkZPR16XymRs1efS49vlAbXu8RcLpeHSGpQFBnyT85yXE9JSeG7P3uSjUXbEaVGFGusrwoXsfJ6vUgkkrBFcFfTN1Mul5OZmclll12GNNWPzxaktayDvr4+9Hr9LM3WudCoTOzM/SrpCXtp7zvE4dqfMuWe24JoIdjtdrq7u8nJyUH42MfQBgJsmZjg29/+NgCbNMl8zrIfg0zLC8EGKq7LYbKinMAS9JwLobm5GalUSnp6OhFqKZ/aG02yWcEfyscpbVp7navRLDDkfomO/ndIslyGzLmTDdnbSUiIp7r1GVQKPRtSP7zm41gt+vv7KS0tJTk5mc2bNy/7OjYajTNVgs+u0RDf1/iAWJ2Hs70AX3j++eejVipKlcvlFBYWEhcXx9GjR0PRifcDZryupqamOHLkCJs3b16z3lmLwdXvI+gRMWZGkJeXd0Hx6FJxflXgfEhISMDv989KYc2gsrKSvXv3otfrefvtt0lNTWVk8jTt/eWMu7eSnaDGGLH4JBUMBvF6vVRVVWH2+RCUSqIyM1d1XBBeEbvJZGJs7N3eqxqlhII0DU2eSFQ6G1N2H9/50vdmRTc3a1KJlRt501aLNzgtRJ+JTImiyETAgVf0z+nNOOURUAhOfHYJStPaalLCZbWwWv+qc+H3+7HZbKuOfslkMrKuSEWiFPC2ClRVVaHRaBatWpZIpGxM+yhb138Gh3OIt6seon+07oL7CgaD1NTUkJeXNy3JUisfAAAgAElEQVTe37sXIiP5dnY2Bw4c4MSJEwBEyXTcab6SYm0m1fHw5w/F0VPxzoqOr7OzE5vNxqZNm0LXlUou4eO7o1mfqOK16knerJlck4riQNDHyfY/c7j2p8jlMozSqxjuNFGQX4TFYqG1501sU33kpf9TqBL4UoTP56O6upqenh62b9++Kn+t66+/XnrZZZdt0Wg0t4RxiP9X4ANidR6MRuNXbr/99pilpgAXQ1xcHNu2baOtrY26ujr8fv+Fv3QJIBgM4nQ6iYmJobm5+T0Zt71turw5IlWJyWQiIyMjLAaii6UCz/1Mbm4uTU1Ns8qsh4eH2bdvHwaDgbfffpuUlBQCQR+1rb/D4duKxy+neJFolcfjoa6ujurqatavX48gCAj9/SiSksLScHhGZxWOB8uMtci5ZHZ79vSxtRVuxRHs51fPvcCPfvRQ6H2JILA/soDJgJNSx7vVjyqVCrfbzYBvbkXgN776Vf7PI99FLfHiswWWXZG5XIQrYhVO/6re3l5iY2PDUvQikQsYNqgJdMtIUqXj7REp/dMJOo/1M9nkYrLRxeQpFxMnXUw0OBmvczJe60TVk0mh7JsYBko49fox6l45wnC5jeFyB8OlDoaO2hk6YmfwHTuDh+yc+lMHUc44FFMaAu4gKBRw/fUU9fcTb7HwhS98IUToZIKUaw2F/JNpJ5MmNb9NGaV+vGVZxzU4OEh3dzeFhYVzzpNcKnDLdhNb0jUcbnTwUsUEgUV8r5aLCUc3h6p+RGv3GyTHbGdD4h2IPkPISsTuHKS58xXioguIjc4L237DjZGREY4ePUp0dDRbtmxBqVy9rcnjjz9u0Ov1PxcE4X3V5m2t8YF4/RwIgmBNTEz8xve+970llslcGCqViuLiYjo7Ozly5Ai5ublh02WsBURRpKqqioSEBFJSUuju7qasrIytW7eG5UZcKhztHlQWWag6LC4uDrfbTXV19byT61IhQcC3BOKhVCrJyckJpUIFQcBsNvPII4+wb9++UFVZa/eb2KYGmHB/EkukjFTrXB1aIBCgra2Nnp4eMjIyQivuyYEB/CMjaPLzV3Qs50Mmk2E0GhkZGQlLpZrJZGJ0dDS0qjVoZWxIUlPV6+aWfDPXbfoYTz35NA8++INQJWWq0kKOKoEjjkYKtGnopRo0Gg0ul4tB2SQCYJa9W/VWfugQ9ikBoyADkTVPBbpcrrAQq7GxMbKyssIwIkKEIVww5KkZq3LCYT1+QIeWidogE4xd8LsRbCeC6RqRPhbuFABKAkDr0WEAZFoJRt0+4saf4Ve338dgXi6ufh+qKDlS1fT6fb06kWjNTl7oeZP/UVTSKdi4OjIf+QUq58bHx2lsbGT79u0LWltIJALXbzGgVUo5dNKO0xPk5u0m5LKVk9WgGKC1+w2aOv8XhTyCkg2fx23X0dE+He0BKC0rRdRWIJXKyU2/ecX7WksEAgEaGxux2WwUFxeHtbDKbDbzne98x/SDH/zgYeCesG34fY4PiNU5sFqtv3z00Uejwp36EgSBlJQUzGYz1dXVREVFkZWVtWZeUKvBqVOn0Gq1IeLw/7N35uFxluX+/7yzr0lmJslk3/ek2ZqkaZKWpYAFQYSCgoioqCgeRTxHOQheIKB40APKonhEEDkqiCCCIshSbLO0TdIszZ40SbPvezL7vL8/0oSGZp9JW/id73Vxpcy87zPvLO/zfJ/7/t7fOzw8HJVKRVlZGTk5Oeh0XuOcK8LtFJnrsmPIXvo9xMTEYLFYaGhoIDU1dVNjC6wdsVpAUFAQAwMD/O1vf8NkMlFQUMCXvvSlxedn5gZp6XoDjWYPI30yrsjVLSF8oijS19dHS0sL4eHh7N69e8nCEDQ2xhwg92IPsYiICDo6OrxCrPz9/RkZGVmSLihK0nHshIXBpAg+X/BVXq39E/99//3812OPLR5ziW8mjw++zjtTtVxlyF/0shpUT2CU6lFI3p922jo6MG+7CD/mNXxb3c7Gbrd7bCS5EMXzhiHlzMwMUqnUq4vdCP0o9joJD44AAQQJIAjMzs3Q3t6OQqkgNi4GpUo5/7wASIT3/y0IDIxVc6z9ZaQyKZkJ1xNgSAQBXG4XpWWlZGdmI3eosI06sY865y1QfC/ArdCQfayH3vCv0/arEWCedClMMpRGGUqTH584Hk2NTx9Ht7fTZR/m08aixb6RH8Ts7CzV1dXrKp4RBIE96T7oVBJer5zkd++N8JndJtSKjc+z03ODHG1+lvHpTkIDtpMe+ynaj/cwPT1Efn7+4n0cHOWi8UQnKZHXolKcbpNxtjE5OUl1dTVhYWGkpqZuiRXQ1772NeUTTzzxGUEQnhBFsdnrL/AhxLm3sp8lCIJQlJCQUHTllVdu2Wei1WopLCxEKpVSXFzM1NTUVr3UptDR0YHFYuGDadCAgACysrIoLy9forvZKsz12nE7RPTRp0fIUlJSsFqtmzYQlaxDY3Uq+vv7uf766/nqV7+6RKsiiiLVrX9EKpUzZi1CJRfIiHp/cZyenqasrIzh4WEKCgqIi4tbQqpsXV3MFRfjjI6m14sFDgaDgenpaa/o0T6oswIINiqIMSs51G0hfnsoFyZfwi9/8xQTw8OLx5hkenboEqie66DPPraYMhl0TmCWv7/4zExMMDA+jiEoGr1zftHcyojVQorU08VlbGzMa/oqT0Try8HpdNLZ2UlcbhS6aCW6KCXaCCXacAWBiUZ27N1OcHIAVe0V9E53oTBJUfrL50mPQYbCT4bCV0pE9HZ27/wGCq2CQ62P0zLwOhIFNLU2EhkdgY9Rj9osxy9FTeAuPeFXGoj9agSSKz+OqeefJNxi4uXpp/lF04/wSVQhCDB93MrAO1OMdyYQUXs+Vz5TSM5vkqj5nx5qXuxm8MA0E3UWLP12XDY3NpuN8vJysrKyNhRl3JGg45oCAz2jdp5+Z5hpy/rlA6Lo5njvfvYf/REzlmFykr7I9sQvUF/XitPpJDc3d/E+ttgmaO35O37aGPo6hXOqUMntdtPS0kJtbS3Z2dnExsZumb+iVCrlmWeeMZnN5ueED5OJ4xbi/4gVi4L13z799NPGrf5dCIJAQkICGRkZVFVVcfz48S3tjbdeDA8P09vbu2ITU19fX3bs2DHv17SMqNubmO2wgQDaqNOJ1YIlwuDgIH19fRseW7IOjdUCfvnLX3LFFVcQFRXFvffeu+Rz6Ro8xMhkC1Eh19Dc6yQ7RotCJsHpdFJfX091dTXJyclkZmaelkJ1W62Mv/QSUh8fgq+9lq6uLq8QITjZey001Ct2H3K5HFEUT7u2omQd0xY31lgTNxfcRmpcLF2vvLLkmPP0qaglSt6YrEKlUjFtmWXMOb1EuN74r38BYDRHoXUokMgFZLqtm5JsNptX0tkjIyNeIVaiKDI4OOjVBr0dHR1ERESsGE1b8DzbtWsXDoeDgwcPLqn+PBV6TRC7s75LhHkHzV2v817lfzMzO766ueq+fQiDg6jby5kWxvn1n3/JQGgbcTcHkPqdYNLuDibh1kD8o9vQSMoxxiiRS6RYjjsYeHuKE38ao+WXw9T9sJ+GR/pICE7Gz89v5ddbAdsiNdyw28T4jIun3h5mbHptneicdZSS2kc5dvxFAvwS2LP9bsyGDA4fPoyPjw9paWlLijFq2p7HLbrITbmJxIREKisrz4n2ZjMzM5SWluJ2uyksLESv39remwD5+fmcf/758Wq1+tzMh55h/B+xYlGwbo6LO3PeI76+vhQVFWG1WikrK/NamfxmMDs7S11dHTk5Oau259BoNIti/I6Oji27nul2G+ogOTLN8j/PBQPR1tbWFReFlSAgLPFZWg4ul4vbbruNW2+9lUsvvZSysjKSkpIWo2Q2+zR17S9j9ImlfzIFUYS8BC39/f0cPHgQrVZLUVHRij3kJl5/HdfEBIZ9+1DodERGRtLe3r6h97EawsLC6Onp8cpYRqPxtD6EsUFKgvzklM7YSYlL5JEv/hLdcCeWhobFY9QSBRfqt9FpH6JHNsmwcxIRlhAre3s7O7alERCeiMIqR2GQbmnXAm8J170VsRoeHsZoNHqtJY7D4aCnp2ddrvJSqZSkpCRycnJobW3l6NGjy0ZcZFIF2YmfIyH8MibnOgiOUKz+HV12GSiV8NJL3HvvvQQFBXHrrbcuFp1IFRLUQXLMn0xHQzX+mkoKbolj+mtTvPLFYo5+qhm/q5U4EieRuuVM/RNcts2RlbhgFZ+/0B+bXeSpt4fpH1s+oiSKIicGyni38odMzJwgM/4G8lNvBVFJWVkZ4eHhxMXFLXnffSNVDIzWkhx5OVp1AMHBwRiNRhpOuQfONERRpKOjg4qKClJTU0lKSjqjcpPHHnvMz9fX95H/E7L/H7FCEASzTqfzqmB9vZBKpaSmppKYmMiRI0fo6uo649GrBTfhzMzMdXlVKRQK8vPzGRkZoaGhwevX63aIzPXY0S2TBjwVcrmcvLw8amtrmZ5eTWS7FJJ1aKwkEgnDw8PcfvvtvPLKK+j1ehITE+nr62Nqaoq69pdwuqykxVxP5fE54oIUtDdV09vbS0FBwWIrmOUwd+wYlupq9OedhzIyEpj3curr6/NaKkGtViOTyTb0uawEk8nEyMjIkscEQaAwWcfwtAsS1KjHYqjViPzjZz/DdUp6e7s2lkCZL+9a6hiVzHsXLRAr0eUi2mrl7vvuJTAsEems5IwI1z3VMjmdTkRR9Iq+yttpwLa2NmJiYjZE1LRaLTt27CAoKIiSkhL6+vqWvaf7B7oRkBAamL76gHo9XHIJvPwyPno9//3f/01FRQVPPfXUksNkBgOa7Gxmjx5FnJziYt9MPhO0i0HTBL/1f5uOnUOEfsoP24iTnr9ObHqeCTMpuPlif6QSgaffGaFjcGkzZat9ksP1T1LV8hy+unAuyL6LqOBCZmZmOHToECkpKYSFLe33Z3fMUdv2J3x14cSGXbj4eEJCAhaLxatGveuF1Wrl8OHDTE9Pr7qp20oEBATwve99zxQYGPjgGX/xcwwfGmIlCIJUEIQqQRD+9oHHHxMEYdPOcGaz+VePPvqo8Wx4NS3AZDJRWFjI6Ogo5eXl6+qk7g0sVADGxMRs6EaUSqXk5OTgdrupqqryavh7ttuO6GRNYgXzBGL79u1UVlZiXWeD19XsFjo7O2lvb0cQBJ577jkefvhhJBIJTpcNu3OKuMQgDle/TPfQEeLDL6FrxJdZmxuNrZ2wsLA1S5idExNMvPYa8rAw9Oedt/i4RCIhNjaW1tbWdb2H9cBbnlanOrCfirQINb4aKTUKKaIgcs8vXuFbL77I8IsvIp78PUgFCR/zzWLcNUu7cQa5IMUgnd+/2E+cwDU3h0XjCyK4J8Utb77sjYiVt9zW7XY7s7Ozm0pzLQer1crg4OCmWhoJgkBISAiFhYUMDAxQXl6+5H7q6elhztlOoDEFhXwdwYh9+6C7G8rLue666zj//PO5++67lzjwA4v3wPTJlHC8KoS9MwkE2rUcU/bzK80bzBbNMVFnYaRs86aiAT5yvnRxAD4aKb97b4SG7vnr6B0+yrsVDzA03khazD6K0m9Dq543xq2oqCA7O3tZS4269pewO2bISvjskl6ACzKF9vb206K8W4ne3l7KysqIiYkhPT39jLQdWwm33nqr0mg0fkYQhA0b8wmC8LQgCEOCINSd8phREIS3BEFoPfn3zDPGTeBDQ6yA24DGUx8QBCEH2PTMJAhCYXx8/K4rr7zyrHfKlMvlZGVlERERQWlpKQMDA1v+mi0tLWg0mk1Pxmlpafj6+nL48GGvaYRmOmwgAW3k+trnLGgf1jIQdbkdWG2TOJ1WHC47/aO1dA0eoq3nXRo7/8ZzLz7A9pwMrrz6Iv5V9RD7jz7AP8r+k1eLv8nfSm7nzcN3caT5Z8xyBLnUj3D/3bxTNYRe4eSKC7PW1MmIbjfjL70EbjfGa645zbcqPDyc4eHh0xafzcJsNjM0NOQx6VUoFLjd7tO8zKQSgZ2JOtqmHBDq5Kbcb9A9McGfXnuNmdLSxePiVcHEK4NxyNwESH2QnIzkWRob+cwf/sB/3Xc/apcT0bm1PQLBO8TKW/qq3t5eQkNDvZb6bG1tJT4+3qPUz0ID3qioKMrKyujq6sJisdDYWopLnCUsMHd9A33iEyCTwUsvIQgCTz75JG+88cZp0UKZry/anBzmqqpwjo3R3d2NbWyWW6I+ztcC9hKtNPNGcgX90aP0vjnBaPvmndV9NVJuvsifYIOcF4rHeKn4n5Q3PoVGZeKC7XcSF7YHQZDQ19dHXV0d+fn5SxrAL2B4vImuwTLiwi/CT3f6vCmTycjJyaG6unrdm73Nwm63U1lZycDAAIWFhRtuHr8VkEqlPP300yaz2fy/mxCy/xbY+4HH/hN4RxTFeOCdk/9/zuNDYbcgCEIY8HHgh8C3Tz4mBX4CfAa4ahNjygIDA5995plntlywvhEEBQVhMBioqalhYGCA1NRUr6QdPoiBgQHGxsbYsWOHR+PExsYu2jHk5uZ6nGqZ6bChCX7f+2Y98Pf3Jyo6jH8d/i1+/nKcTgsO5xx259ziX/fJPmhDgQlYVD4cbnty8fyDb7fy2H/txz/Qh//4/pXIpErUSgNymQaFTINcrp3/K9Mgk6qpq+7irYPHmLRHc3mO77p6KM4cPIj9xAkMV1+NbJmIx0JRQ0tLCxkZnpsMSqVSTCYTw8PDHjcKXqgO/ODEvT1Ww3t1U3T7a7gg5nJiIn/ELysrueqtt1DGxqIInm9Evdc3i7bBfkzMR6tEUcTa1ET7xARhUfH4ue2A7EORChwdHcUbWszu7m6P770FzM3NMT4+TlpamlfGCwwMxGAwUFdXR0NDA/qgKawzcoJN29Y3gMEAF14IL70EP/7xEr+vDzbB1u/axWxlJUNvvklnWBg7d+5EIpEQrDBwvWkXA45xDnysAd0f1bS94KDmpg7yzQlopBsvQtAopVyWOcyfSieo6U4lI8LIroxMpNL53117ezsDAwMUFBQsO+c6XXaqW/+IVhVAUsRlK76OVqslLS2NiooKdu7c6TUN3akYGhqivr6ehIQEQkNDvT6+J9i5cyfnn39+/GuvvXYN8OJ6zxNF8YAgCFEfePhK4PyT/34WeA+4w/Or3Fp8WCJWPwO+C5y6/f434FVRFDdVoubn53fbTTfddEYF6+uFUqkkNzcXo9FISUnJhgXaa2F2dpampia2b9/uFXFjaGgoKSkpizn+zcJlc8/rq2LWP2m63U6O9+6nrudJZtxV9A/XM2cbQxAk6NSBBBpSiAk5j+SoT5ARdx3+PnEoFT6cl/Vd9uTcw9G3DTx8/9vk7yigtqqFm/Y9QmH6beSlfJmshBtIjbmKhPBLiAouItBvG72dFrQaX/qsJpQygYyotSMg9p4epvbvR52WhnoV0hQcHMzU1BSzHvRSOxVbnQ5UyiXkxWuptDoQNC5u3PV5mnp6eOfECcZffBH3Sc1YgNyXiywJZDrnFwBHfz8zIyP0jY1hNEfi55pPzW51KvCDi/pG4XQ6cbvdHjcjn5qaQqlUes1wt7m5mcTERK8K/+VyOQaDAR8fPSOTdfhpE5BJN/DZ7dsHx49D7fvtce68806KioqWdE+Q+vggT0/H3dREdkzMaWmsILmBT4UUEnWdEYVThvgXKY/0vcZbkzXMutYvmXC6rFS3/oGKpifYFrqf5FA3NV3BvFk9g8vtpr6+fnGjudJGtvnE35m1DpOZ8Bmk0tV/AwEB84L2+vr6dV/jut6H00ltbS3t7e3k5+efc6RqAY899tiCI7unGhvzwhp/8u/ZD8utA+c8sRIE4XJgSBTFylMeCwGuBR5b8cTVx/TVaDTfvffee8+4YH29EASBiIgI8vLyaGpqor6+3uN2LjBf8VZZWUlGRobHC8Sp8Pf3Jzs7m4qKik0TwdkuO7jXp68SRTc9QxW8XXEfx46/iI82lPOy7iDK73MEa66mKON2dqTeQnbijaTFXE1ixF6iQ3ajUwcgCDIM+ijkEl9ef/1NbrrpJt56661VW5SMjo5SUlJCQEAAmdm5jNr0hOnnUMpXv4XcNhtjf/4zUr0evyuuWHXxEwSBxMREmpqaVjxmI/Dz82Nubs5jUfxKxArmPYMEKUyEKrk88maio8PoDw7GOTLC1JtvLh4XqQxAYp3fF1kbGuiamG9v4xsYhd4pAQHkvluXCvSGh9X4+LhX9FXeFK1PT08zOzvr9TTQ7OwsnZ2dRMXrEQU7LksAtbW165+DPvlJkEjmo1YnkZWVRWVlJb/61a8WH5ubm6NJrUaQy7Hs37/icGGhJqKvMuE/6EvhkVSKZxp4ZPBV/jlZzaxr9ZTbyGQb71b+iM7+EuLCLuLC7Xfw6V1h7EzUcqhllmffmK/23b59+4rRpYnpLtp63iEyqJAAv/U57sfExGC1WjdlC7McxsfHKS4uxsfHx+sO6t5GQEAA//7v/240mUx3nu1rORs454kVUAh8QhCETuB54EKgHogD2k4+rhEEoW29AwYEBNx79913+51Nwfp6odFoKCgoQKVSUVxczOTkpEfj1dXVERYWtiVVIz4+PuTn51NXV7epyWSmw4YgBU3E6oRveLyZf1U9REXT08ikSnamfZ3Cbd/EoI8kLS2NmZkZOjs7lz1XQGByeJzp6WlUKhXvvvsuzzzzzIrRA1EUaWlpobGxkby8PMLDw2nps+ESBQLV0wwODq56rZP/+Aeu8XEM+/YhWcdEGBAQgNVq9Zp5rDesF5RKJS6Xa9lFVa+WkhmtoVxwI5PI+M1dP+U7D/wAXWEhs+XlWE6SxAWTUJjXV3WfXMB8A+PROSTIfaVIPGg/shYcDofHKXVv6KvcbrdX0rMLaGpqIikpyavRKlEUqaqqIiMjg/7RKmRSNUU7Poler6ekpISZmXVonQIDYdeuJcTq2muvZc+ePdx1110MDQ1ht9spLy9nW14ePuedh62lBesqxr9+aRoCCnQYanz4wsDFJKpCKJlp5JHB15YlWC63g7r2lymueQSAoozbSYu5GqlEjkQQ2JOmwaSyMDSnXtWV3O12UdXyvygUOlKj1686WRCzt7S0eBSFdrvdi5vrnJycVauOzyV84xvfUKnV6lsEQfBkNzIoCEIwwMm/Q965uq3FOU+sRFG8UxTFMFEUo4DrgHdFUTSIohgkimLUycfnRFFcV05PEIQgrVb72S9/+cveC9dsMQRBIDY2lqysLGpqamhtbd1U+XFvby92u53o6OgtuMp5qNVqCgoK6Ozs3LA7+kyHDU2oAukKLSgmZ3ooPfY4Jcd+js0xTXbi57gg+07MxvcnRUEQyM7Opre3d9kCgK6G4zx+2Xe5+eabgXkyuNIkZbPZFoX5BQUFi8Lnhm4LerWE8/OSaGhoWDEiZKmvZ+7oUXS7dqFcZ9saQRBITk6msbFx7YPXAW95WhkMhhUrnQqTdMzIwBog4jOQQc9gJb0hIciDgph45RVc09OLxMoxMoJzeJiorCy+cPON+AYmo7bNu35vJbzRI3B0dNRjYjU4OEhAQIBXUvATExM4nU6vNYNeQGtrK/7+/vj46ugfrSHEPxOZVEF0dDTp6elUVFSsz4B23z5oaICT5FoQBB5//HFmZ2e54447KC8vJzExEYPBgC4/H6mfH5NvvLFYVbocgi/2QRupYOp1O5fb8/i3wMtIUoVSMtPEw4Ov8uZkFTMuKxPTXbx39Me09bxNVHAhF2TfiVEfs7hBmJubo6ysDDtqooJW3/Ac732Hydke0mM/jUK+sd+QXC4nIyODysrKTWUcpqenKSkpQSKRUFBQcEZainkLSqWS+++/3y8wMPBHax+9Il4Fbjr575uAv3p+ZVuPc55YeRtms/mnDz30kOFslqRuFj4+PhQVFeF0OikpKdnQLmhmZobW1lYyMzO3fLcjl8vJz89nYmKC+vr6dZFAl9WNpc+xrL5qzjpGZdOz7D/6IOPTnaRGX8VFufcSYc5HEE7/CUulUnJzc2lubl7SkuX111/njr1fwuV0cccdq+sfR0dHKS0tJSoqitTU1MWF0OZw09JvJSVMjVqtJjExkdpTdCSL72dykvFXX0UeEoLPBRes+f5PxUK6yRsl20qlEpVK5XGkczk/qwX4+8hJDFXRoJUgs+l55pHfkZqeTkdCAm67nfG//AWlQoHVasV6kjAW7tvH9++/E5XWD4VFgsK49RWBnqROXC4XTqfTY12UN9OATU1Np7Wf8hSTk5MMDg6SkJDA4FgdTpeVsMCcxef9/PwoLCykr6+Pmpqa1cnC1VfP/z0lapWUlMTtt9/OkSNHCAgIICgoiIyMDAJDQki7/36SvvMdTAbD4sYH5itmfXx80Ov16H31ZHwzigf/8T06nx/F6NRzY+gefhxzE/dF3cBl/rn4KLXs+8aNzLrtpEd/gayEG1DINUilUmQyGTKZjIyMDEKjkpi2QmTAyt/pjGWIxhN/J9iUQWjA5pqlGwwGwsLCqKurW/vgkxBFkePHj3P06FHS09NJSEg4J3vLroUbb7xR7uPjs08QhDVLzwVB+CNQBiQKgtAjCMLNwI+BiwVBaAUuPvn/5zw+VOxCFMX3mK8K+ODj66LxgiDEpaSkfOyaa6456/YKm4VEIiE5OZmxsTHKy8uJjo4mIiJiVbLkcrk4evQomZmZW1JhuNJ1Zmdn09jYSGVlJVlZWatWx8x02kBcqq+yO2Zp6X6T9t73AIgL20NC+N517RoVCgW5ubkcPnyYnJwcnnnmGW6//Xai0+LZ95vb2b59+7LniaJIe3s7/f397Nix47QoR2u/FacLUiPmF+mQkBAGBgbo6elZNBIU3W7GXn4ZXC6M1157mrXCepCUlER9fT0FBQUbPveDWBCxb9u2zqquZWAymVZMrwIUJut4usdKptLFLt3l+Pr9gZ88+SS//e53mfzb37CUl0taQDwAACAASURBVCOKIpbGRuTBwYzabAxPTiJz+SCxCSi2OGLlqdXC+Pi4x+lzq9WK3W5ftox/oxgdHUUqlXrNBwvm54nq6mqys7ORSCT0DFWglOvx91tqSSSXy8nJyaGzs5OSkhJycnKW/2xDQyE/f55Y3XUXMH9/XX311ZjNZhIS5se97LLLFom/rbER0W6n4JSKyc9+9rNYrVYEQVj8LyM2G8eQi66XxvnmN7+JIAg4nLP0jDcwJpfgX5BFdeg2kLv5z+9/D6VEjiAIWCwWRkdHeeCBBxiw6IFxogKWT16Iokh1yx+QCFLS4z7t0WcbHR29GOlbS3BusVioqqpa7M6xFVWFZwpSqZSHH37Y+JWvfOVnwL7VjhVF8foVntrj/SvbWnyoiJWnCAoKevzRRx81fRjy02vBaDRSVFREfX09AwMDZGRkrFjxVF9fT1hYmFcn4fVAEARSUlJob2/n0KFD5OXlrUjsZjpsCDLQhClwuR20975HS/cbOJxWws07SI68HI1qY6l6jUZDdnY2+/fv50c/+hFXXHEFn3v8P2iULF9I6nK5qKmpQSqVUlBQsOwOsb7Lgk4lIcL//cl427ZtFBcXYzKZUKvVzJSWYu/owO+Tn0S2ydSRr68vSqWS4eFhAgICNjXGAgIDA2lsbMTtdm9616tSqXA4HLhcrmUn+sgAJWEBCrom7EQNpHPNvot4+umXuf/++wlMTGTyn/9En5GBo6cH/YUXsi0vj8RtyXxs32+Ara8ItFgsHhGa0dFRj1Nup5JvTyCKIo2NjV6x5TgVTU1NhIWFodfrcTgtDIzVERlUsMQEcwGCIBAdHb3oY5eenr58mnTfPvjOd6C9HWJiOH78OHK5nNtvv33xkAcffN+o29bVxchTT6E/pVr71OdPxcjhGXr/Psnte7/HTHwFDR1/RSbNJiP+elSGeA5M13N0rgP1LRnkaGOJnzXSf7ybvLw8VCoVh8vHUcoFzH7Lz0knBkoZmWwhM/4zqJWezZ2CIJCZmUlJSQkGg2FZIiqKIj09PRw/fpy0tDSvp3jPFi6//HKJ2Ww+TxCEFFEUz17PnzOID19scZMQBCErKioqZ8+ePR9+VnUSCyHt6OhoysrKlhWMDw0NMTc3t6W6qrUQExNDTEwMpaWlKxpgznTY0YYr6Bk9zNvl91Lf8ReM+hguyL6T7Ymf2zCpgvkIgV6vJz8/n5///Oe88MILaPRa3Ms4r1ssFkpLSzEYDGRkZCxLQOxONy19NlLC1Ugk7/+M5HI5aWlpVFdXY+vtZeqdd1ClpKDJ2lzqYAELFYKetg2SSCQEBgZ6bDprMBiYOFnNtxyKknU0a0FAwhUZe1GpVDz00EP4ffKTSNRqzNXVAAjR0XR3d2MKMqM9KU87E6lATyJWngrXRVFcV7RiPRgaGkKr1Xq1ue7IyAiTk5PExMQA0D9ai9vtICwgZ9XzjEYj+fn5NDQ0LN8/dN/JIMXLL9PT08Pw8PCqcgRlRATqtDRmSkqWtEdaDqY8LfpUCQP7pzl+pIpAQzIX5txNaEA2Jpmeqwz5fNP8cbZpIjg808KfnOWk5mUik8m44YYb+PMLfyAiQLHkXl6A1TZJfcfLmHzjiAzyPGoM8/NEeno6VVVVp93TNpuNiooKRkZGKCws/MiQKpgnlU888YQpKCjoF2f7Ws4U/r8hVuHh4c/ed999pjPdi+9MIDAwcFH3UFlZuehAbrfbqa+vPyO6qrUQHBzMtm3bOHTo0GkVb45ZF9YBB0PKQxxt+R1KuZ7C9NvYue3r+Oo2t8MfHR1lz5493HnnnQQGBlJQUEBVVRWCyGmT2tjY2GJfsNUIaGufDYdLJCX8dK2Ov9GIn9XK0B//iESrxfCJT3j8met0OvR6vVdc+L3habWazgogMVSFyiRj3FckbKqQT113Ka+//jo2QcBw1VUIbjf4+tI9O4soivgFBqM9aZZ/JsTrm9VYuVwuHA6HRx5YExMTaLVajy1ORFFc9K3yFhwOB3V1dWRlZS3+ZnuHKlArjRh9YtY8f6FgZXx8nOrq6qVu/9HRkJWF44UXaG9vJycnZ82oqc/FFyO63Uy9/faKx8w3Ti6lMfhhHLphghs/RVbIl1ApfJccZ5DqiOvRct5YJKJc4MWpMkQpvPX22xyrLCZqBX1V7fE/4XI5yIq/YVkd52ZhNBoxGo20tb1fxD4wMEBpaSlhYWFkZWWdMbnGmUROTg6xsbE5giDkn+1rORP4/4JYSaXSC9LS0sJNJhOlpaVeN9w8F6BQKMjJycFsNlNcXMzQ0BA1NTUkJSV5tCB4E0ajkZycHI4ePcrw8DAA49MnqPzXywBYjV3kJH2R87K+u26vmOXQ2dlJYWEhlZWV5OXlAfMCWKPRyPDw8JKIVW9vL3V1dezYsWPNiER9twWtUkJUgALR7cbe3890SQkjzz1H/4MP4rN/P8zMoNq7F4mXrDwSExNpaWnxOGql1+txOBwetdlYzc8KQCIIFCbpaNYJyGy+XHPJ+bS2tqLRaFDFx+MqKMCRk7NYLepnDkXvcCFVC0jVWzsViaK46TToxMSEx/oqb4nW+/r6VkwlbRZ1dXXExsYuEk+bY4ahiUbCAnPWvTmQSqVkZWWh1+s5dOjQkvZS1ssvR15RwQ6NZl2kQXaySnCupgZ7/+lpe6ttkkP1v6S69ff4+oYSf2MYgiDjxAvjuB3v3ycul4uKigpkMhkXbNvJNYYC+h1j/HX8COGRcYwNdBC5jL6qb6SavpEqkiIvQ6fxji3GqUiIiWG8uZnBf/2LYwcPcuLECQoKCgg+2angowSHw0FTUxNlZWXce++92qCgoCc30ermQ4ePvMZKEATBbDb/8tFHH/WLi4tjenqapqYmWltbSUpKOuO6o61GWFgYJpOJsrIygHOif9SpWEjNHT5SitDVwNhsAwF9l4PMze49X0Hq4W6turqaSy+9FKvVyltvvcWuXbsAmHTOMhYi0j86gyiKiKJIW1sbIyMj7Ny5c80J3+5w09xrIVU7y8SfD2Jrb8d90pdJ5u+PJjMTZUwMVoOBurY2Cj3QM50KtVqNyWSip6dnUz0dT0V4eDjd3d3Ex8dv+lrsdvuqWq2MaA37/SdxDLkxDqdidw/iduuw2+2osrMZHh6mtXLe61dvikDfz5a3snE6nR4JgD1NA7pcLsbGxkhPT9/0GDDvZ9Ta2kp+vvc2/f39/TidziXar77ho4iie8004AexYAuj0WgoLS0lNzcXQRCoyM6m0GhE+e1vw7/+BetYV/W7dzNXVcXkG2/g//nPLxK8nqEKatpewOW2sy32WmJCzkMQJEj2Wej4/Rg9f5sg/JN+OBwOysvLCQ0NJeqk1UmSOpQ9Pum8PVWL2hzKWMt7hBiXEiu7c47athfw0YYSF3bxht7/cnDNzeHo78cxMLD41zkyQqjbjRPwTU4m7brrznpGwdtwuVx0dHTQ3d1NVFQUu3fvRiKRUFRUFPHKK69cCrx+tq9xK/GRJ1YqleqavXv3Bi20rtHr9eTm5jIxMUFjYyMymYzk5OQPlT/IWlhY+MLCwjh48CCZmZnnFIFUqVSkZ8bzr+o/46NKwDiXhTJK7jGpmp6e5uKLL0atVvPWW29hSghl/9Qxmqy99DvmrQv8VXpCRjSUdJag0+nYsWPHiiTBNT2NraMDW3s7jb02HMYiQo/txyadQhkfjyo2FmV0NFLf99MPaiBwaorW1lavpWvi4+MpKysjNDTUI7IWGhpKSUkJcXFxm57I/fz8mJiYWNGBXC4VyEvS094zRcJIPI31b3PrV6/myiuv5I477sBisXDeeefx4x8/iKAOQGsXzohw3ROrhdHRUY+iTf39/QQFBXm8eHZ3d2M2m70WgbbZbDQ1NVFQULDk2nqGK9BrgvDRbk4PFhwcjEql4tChQ4iiSOauXUgeegi+9CV47jn43OfWHEOiVqO/4AIm//53rM3NSGPDqGl7gd7hSgz6KLITb0J/SjTJJ1GN+Xw9g+9NIw+EFmctiYmJpzVH36VLYdAxSakpgpnJYWZnpvA95f5t6HgFq32KHalfRSJZPxkXRRHX5OQ8eTqFSLlOsTmR+vggCwpiJiAA+9QUPt3dzJlMHylS5Xa76erqoqOjg/DwcHbv3r1kU/PTn/7UcPDgwUcFQXhDFEXPOsSfw/hIEytBEKRms/knDz74oO8Hn/Pz82Pnzp2MjIxQXV2NVqslMTHRqyH2swFRFKmuriY9PR2j0UhQUBBVVVUEBgYSHx9/znih+OlDUch1uGfl2EfcGLM892vV6LT8+NePIE8w8U9jOxPDxxCAMIU/F/tkkKwKw0/QUN5ezoxl5rTPw221YuvsxNbejq29HefQvMmvoFLRHn0paomLzC9chSIwYNXJMD4+npKSEsxms1cIrVKpJCgoiBMnTnhUhCCXy9Hr9R61ZlnQWa12fm6cll9VTZE4KsHVpiQuLobHH3+cf//3f2dubo7du3eTnBrFz17tQWUTUBjOXeG62+3Gbrd7RMy6u7s9srqA+QhAe3s7RUVFHo2zgIV5Ijk5eYk3l8U2zujkcZIiP+7Rgu/r64tcLsdqtc6nBb/wBXjqqfkKwU98AtZxX2hzcpg9fJgTZS/RMT6N3TlLctQVxIdfsmylovl8PVOdcwz+c4a0r23DFLR8s/O92hxeDmzFHBdHc38Heb6ZAIxMtNDZX0xc2B4M+sgVr0t0uXCOjODo78e+QKIGBhAXCnMEAZm/P4qICOTBwfP/BQUxe9LOIiQkBHNVFbbRUSZ0Oq9U/p5tLBRntLW1ERQURFFR0bJZgMjISK6++uqAZ5999gbguTN/pWcGH2lipVQqr923b59htdy1v78/hYWFDA4OUlFRgcFgICEhwWsNUs80Ojs78fX1XVz4dDodhYWFtLa2UlJSQlZW1jkRnRMECYF+SYz1zQuzuwe78HclbzhlY3XZufPBe3AHKjFfnoY1V4qMaWLlQZynTyVRFYJOOr8o2u12Dh0+RGRkJIGBgZSVliIbHkY2MICtvR1HXx+43QhyOYqICDQZGShjYiAwiM5XBtkWqUZpXltrI5FIyMrKoqKigl27dnnFhyY2Npbi4mIiIiI8Gm9BxL5ZYuXv70/1yeq+laBRSkhM1jLcM4tvbyY3fHGUV155lV//+tfk5eVx+PBhDAES5FYjAsKWpwI9iVhNTEwsiWhs5rXdbrfH91xnZyehoaFeEzZ3d3cvEvZT0TNcCYhLTEE3ioWWOKGhoYSFhXHkyBEcDgfhv/gF5OTA978Pj63d5tUpOujaKaXX0ovW6cfOrO/ip1s5HT48MsywphedGIRWunLFZP+om/isi9j2+VBK/LpJcyWjFCRUtf4BjcpEUuTli8e6bTYcg4NL03lDQ+B0zh8gkyE3m1GnpqI4SaBkZjOSU4oUFmQH/f39ZGZmolMqGfjjH9FkZpKRlcXhw4cpKio6rQH1hwGiKDI4OEhzczMmk4mdO3euuXbec889Pi+//PJ9giD8/qMatfrwfZPrxElt1QPf+9731jSvEQSBoKAgzGYzvb29lJWVYTabiYuL+1BVaFgsFk6cOHHarlYikZCYmIjZbKayspLw8HCio6PPegg6wJBMz2AlSECHL2VlZeTl5a1ZOTXlmqPZ2kv9TBe//M+fcOS3b5J17Xncfe1eklShxCmDUUiW/rStViuHDx9eTA+ITiepIyNY9+8HQUARFoZ+1y6UMTEowsMRTpnkGnss2J0iqctUA64EnU5HZGQkDQ0NHkcrYD7aFB4eTnt7+6Y1UjBPjOrq6nA6nZuayNVqNVardU1PrIIkHS9WzJLX64u/oODiiy/i4Ycf5plnnmHPnj3827duJj7pHmDrKwLn5uY2rZHy1L+qq6vLY22cw+Ggq6trUS/oKebm5laMfvUOVeCni0Cn3rw2s6GhAZVKtWjdkJ+fT3l5OQ6zmZhbb4Vf/GI+gpWdveIYIxMtHG1+jjnbGGHjQQQ3yfHJWfl76O7uprOzk5RtmfQ0TOGyrlzscWLIhkSA66MyeG78XV4YKyZ3ZppZyxA5xquxlBxeJFHOsTE4WTgi0WiQBwWh27FjMQolM5lWNQCenZ2lurp60XdQIpEwV1OD6HCgTk9HqVYTFRVFU1MTaWlpa3205xRGRkZoampCp9ORl5e37s2L2Wzm0ksv9fvf//3fK/iQtKjZKD6yxEoikXzswgsvNG3EN0YQBMLCwggJCaGrq4vi4mLCwsKIjo4+53cToihSU1NDamrqitfq5+dHUVERjY2NHDp0iMzMzLPaIT3QkAQSEUFvQ+X0JT4+ntLSUvLy8pakbkRRZMg5SZO1lyZLD72OMRwWO6/f9itqXy/jS9/6Gr/46aPIpcu/79nZWcrLyxdN99xzc4w+/zz2zk5keXk0q1Tk7969IqFr6LagVghEmzcWxYyKiuLQoUNeC/VHR0dz4MABoqKiNk34BUEgODiY/v7+TS/4vr6+TE5Orlop56eVYUxVYRuwIOtI4Javf4ZrPvlFnn/+edxuNwHBAYtWC1vtYeVJn8CRkZFNG3GKokh/f7/H6bv29nYiIyO9MgctRJO2bdt22ngzliEmZrpIjbl60+O3t7djsViWdDaQyWTk5eXN98v73OeI+9OfEG69FUpL4QPk3OWy09D5Ksd796NV+bMr49vo5zQMH32S6QMH8P3Yx057P62trYyPj7Nz505svfMtdlzWlQMhnUM2gn0E/vOam3BowPnzG5mZ6yOrT4nw9gGmAKnBgDwoCHVGBvKgIBTBwUhW6Sv6QYiiuKg1WpBlLGCuthapry+Kk/dfZGQkpaWljI2NbTqSfCYxPj5OU1MTcrl8PgK3iWjsPffc4/fGG2/8WBCEV8WPoAfSuc0WPEBgYOBDP/jBDzYlcJFIJERFRREeHk5nZycHDx4kKiqKyMjIc0aj9EH09PSgUqnWXMClUilpaWkMDw9z6NAh4uPjveIGvRmolQZ0ajMOzRi2US1RZjMKhYLDhw+TkZnBlMZJk7WHJksvY64ZAELlJnYpk/j+p7/OsdJDPPLII3zrW99a8TWmp6epqKggMzMTg8GAY2SE0d//HtfEBIZ9+9BkZMDgIEeOHGHnzp2npdmcLpGmXiup4WqkyxgJroYFt+VDhw6tqDnYCKRSKdHR0bS1tXnUIy48PJyamppNEyt/f39GR0fXtCAoSNVTXGElbiSOkPx2XnvtNTo6Ovjd736H0eyPdhSQglx/bvYJdLvdWK3WTZOy0dFRfH19PSJEdrud/v5+du/evekxTsXx48fx8/NbNoLXM1QBCIQFLN/uaS309fUxMDDAjh07TiMgUqmUnJwcampq6L3tNsLuugueeQZO6Qk4Pn2Co83PMj03QHTwblJjrkImVYIvaDIzmTl0CG1uLrKT5EMURWpraxFFkdzcXCQSCU71/Brtts0TK9HpxDE0tBiBmusfpFdzEdtGjzHU0sLI7Cx7hy+iJyAEZ3IS/jtSkAcFIfFgw2m1WqmpqUGlUp2W4nPNzmI7fhxdQQHCybVEEITFRs3ncgubqakpmpqacLvdpKSkeJQij4qKIj8/3/zKK6+cxzJt6j7sODdZgocQBKEwKysr1JOUCcxPBrGxsRQVFWG32zlw4ADd3d0eewp5Gzabjba2NlJTU9d9TkBAAEVFRQwNDVFRUYHdbt/CK1wZgYZk5hQ92MaciKKIwWAgLy+PZ0f28/TIOxyeacUk03OFXy7/EXQltwRewsX+WVxy4UU8//zz6yJV27dvx2AwYGtvZ/jXv0a0WPD//OfnSRXzoenw8HAqKytP+26PD1ixOTaWBjwVarWa+Ph4jh07tqnzP4iIiAgGBwex2WybHkOr1SKKInMn7SI2irWMQhcQbFDgipMjESVYGlRceFEBQycLAnz8A9A5QOojRdggYd0oXC7XpsjN5OSkR4uHN7yrWltbiYmJ8cqGbmpqir6+PpKSkk57ThRFeobKMfnGolZu3LNrdHSU1tZWcnNzVyQGEomEzMxMxj7+cWazsxHvuANGR3G7XTR2/o0DVT/B4bRSsO0bZMRfN0+qTsJnzx4EiYSpt94C5i00jhw5gkqlWuyU4LZYcA71ADBdWsngE0/Q98ADDD/5JBOvvMJcVRWDEj/cgpT49EjSzj+f9qkJ/CdbCRc0vOc/TV+I1iNS1dfXR1lZGVFRUWRkZJz2u7PU14PbvTj3LECn0xEaGkpra+umX3urMDc3x9GjRzl27BixsbHk5+d7dF8s4IEHHjAEBwf/1AuXeM7hIxmxCg4O/skPf/hDr8VU5XI5iYmJREdH09rayoEDB0hISPBKCbU3cOzYMZKTkzccEZHL5WRnZ9PX10dJSQkpKSmYzd43xFsNAYYkhtVHEB3gnHYj95Gi1Wpx6aT4z6i4TJlBnP+8VqO2thaHw8H27du57777Vh33VFLl4+PDbGUlE6+9hsxkwnTDDYu73gVERkZisVg4duwY27ZtW/xe67ssqOQbTwOeirCwMAYGBujr6yMkJGTT48D84hQXF0dra6tHmowFEftyi+xa0Gg0WCwWRFFc8/efs92HzmOj6Hty6egv4eDBgwBIlFq0dlAEbu0U5Ha7N32Pjo6Oblqb5XQ6mZqa8ii1Y7FYGB4eJiUlZdNjLMDtdlNdXU1mZuayxGdytocZyyCxoRdseOzp6Wlqa2vJz89fcw4SBIFt6em0fu97xH/609i+cxul/5bK5Ew34YF5bIv7FArZ6RFCqY8PuqIipvfvZ6atjWOdnYQqlfj19zN29CiOgQFc4+OIyICbsQ1NoI70QZWQMC8qDw5GajDQ3DCDcGya+J0pxFQlMDdnReYM57Pmvfx65G1eGDvILQEfwyDbWHrL4XBw7NgxXC4XhYWFK8oKLLW1yAIDkS8zz8bExFBSUkJISIhXGnV7CqvVSktLCxMTEyQlJREQsHo19EaRmppKYmJilCAI20VRrPTawOcAPnIRK0EQ0qOjoxOyPOzTthwUCgWpqank5eUxNDREcXHxooP42cLQ0BBut/u06p6NICQkhJ07d9LZ2UlNTQ3OhYqXMwB/3wScmvn+c7bR91/XjUikKYTR/mGam5t555132LVrF7fccsuaEcNTSZVep2PyzTeZ+OtfUUZHE/DlL59GqhaQmJiIy+VabDexkAZMDlMjk3o2oaSnp9Pc3OyR8/kCQkNDGR0dXbHv4nqwoLPaTPRVEAR8fHyYPMWjZyXEBikZD5Wismnprz/BD+67l5/85CfM2QS0DlCbzt2KwJGRkU0L13t7ewkODvZoIWppaSEhIcEri1lzczPBwcErLti9w5UIgoSQgJUF5cvBarVSWVnJ9u3b1/05C4JA3FWfpPdTF6H47e9RVDWQl/IVtid9fllStQBdYSGCTsfEc88RceAA0rfeYvrdd3EMDaEIDcXnooswffZ6EECbvxv/G2/E9+KLUaelzYvMJRJODNkx+8lRyQUk2hMAyB2pqKVKbjDtxi2K/GH0ADa3Y8Xr+CCGh4cpLi4mMDCQnJycFUmVc3wce1cXmhWMYiUSCenp6YvpzbMFu91OQ0MDhw4dwt/fn127dhEYGLglQYQHH3zQ9FGMWn3kiFVwcPBDDz744OZtktcBtVpNRkYGWVlZdHV1LQoPzzRcLpfXqs5UKhV5eXn4+flRXFx8xt6PXKZCG6gFlhIrl+hGJpGSm5tLdXU1e/fuJTw8nL/85S+r3uCnkiqdUsnY888zU1KCNi8P02c/i2QVc8UFrcPo6Cg9PT20D9qwOpbvDbhRLJDy6upqjydNQRBITEykubl502PIZDIMBsO6UnrLYUFntRYEQSChQI9dArL27UQnaNixYwfOOSVyN6i2mFht1sNKFEWPRO89PT0epQFnZ2eZmprySpuTsbExxsbGWDBJ/iDm04AVBPolo5SvP1LjcDg4cuQIaWlpG4qwzFpGKKn9OdU3hmEz6cl6uIJgv7Wjr5Ozs3THxiJPS8P34x/H/+abCb7rLoJuuw3jpz6Ffvdu1AnxSFXCslWBTpdI94idyEAF3YOH0ZtmOP/CfHz08+TZJNPzKWMhw84pXh4/hHuN+9TlclFXV0dbWxv5+fmEhYWtOjdZTsoB1KvM176+vvj4+NDT07Pm5+FtOJ1OWlpaKCkpQavVsnv3bkJCQrY0K5Ofn09wcHCaIAgbD52fw/hIEStBEGIDAgK2e6sseS3odDq2b99Oamoqra2tHD58+LQGw1uJ48ePExoa6rXKPkEQiIyMJDc3l8bGRhobG5c2VN0imEIicUuczA2/r/lx4UYqSJBIJPT19eF0OnnwwQdXXWjm5uYWSZVWFBn5zW+wNjfje9ll+F1++apl0QuQSCTk5OTQ0dFBZcs4KrlAbJB3PM0CAwNRq9UeN0OGeV3YzMwMMzMzmx7Dk8bM69VZAaTFaBjwF/AdDae7qwKHaw6ZZX4hVp6BisDN3B+Tk5P4bKAK7FTMzMwgkUg8ui+bmppITEz0eFFzOp3U1tau2oh9bKodi22M0A14V7ndbioqKoiJiVl3VE8URTr6DvJu5Q+ZnO0hPftLKH7+JJqGJgbvv3/VcwcHB6mpqWHbpZdivvZadDt2oIyMRLKMZ5JUJVm2KrB/3IHDJRJicHGs/c/ExaTz7tslFBYWLh4Tpwpmr28WjdYe9k+vrIucmJiguLgYjUZDfn7+mt+1KIrM1daiiIhAtkbRR3JyMm1tbUv6LW4lFsxnDx48iEwmY/fu3We0UOtHP/qRKTg4+MEz8mJnCB8pYhUUFPTDBx54wHSmdU++vr7s2LGD+Ph46urqqKysZHZ2dktfc25ujr6+PmJjY70+tlarpaCgAJlMRnFx8ZaTRbMxGad6nJnB91/HLbqRnvx5dnR0oNfrycjIoKysbFnhts1m48iRI2RkZKCanmbof/4H5/g4phtuQLfB3moymYyIhCxaBhzEBEo94FMJ2AAAIABJREFUTgOeitTUVDo6Ojz+fQiCQFJSEk1NTZsew2AwMD09vakJXKvVMjc3t67om1Qi4J+jRSIKTDcE42QIhXXewFFxBjysNhN18sS/qru72yPvqqmpKaxWq1csOurr64mOjkar1a54TM9wBRKJnGDT+mwlFlzbAwIC1l1RbLFNUFb3BDVtf8ToE82F2+8mwpyP5PrrES+4AP9HHqHjyJFlzz1x4gStra0UFBSs67uUqiS4l4lYdQ7NzxuzM//A5bKTlfAZBEGCy+VactwObQLZmhj+NV3PsbkTS55zu900Nzdz7NgxsrOziYmJWRf5dQ4O4hwaQr2OfpFyuZzY2FiP7u31wO12c+LECQ4cOIDT6WTXrl3ExMSc8arESy65RPDx8SkSBMEzw7dzCB8ZYiUIQrBOp9tz+eWXnzU1udFoZOfOnYSHh3P06FFqamo80sGshrq6OlJSUrZsVyEIAvHx8WRkZFBdXU1bW9uW5f399BE4tZPYRucnOFEUceFGIsy/tz179nDnnXcSERFBYmIiZWVlSyI1DoeDw4cPk5qairq/n5Gnn0aQSgn40pdQJSRs+Hq6hm38/uAUGqUMH1urV79DmUxGeno6VVVVHn+e/v7+OByOdWmdloMgCISEhNDX17epc/V6/bpJd/Z2PWMa8OnNxC5pQGmdXyC3mlhtNmK12cbLoigyMDDgUQqvsbGR5ORkj6NVg4ODWK3WVVOSbtFF3/BRgoxpyGXr60G44GG0nk2dKIp0D5XzbuUDjE62kh73aQq2/Rsa1UmdoyAgPPEEUqsV7X33LYmgiqJIU1MTg4OD7Ny5c03j4AXMpwJPj1idGLbjp3ExMlFKQsRe9Jpgvv71r59WTS0IApf75RChCOCVicP02edlETMzM5SWlgJQWFiIXr+yu/sHMVdbCxIJ6nVWboeHhzM5Obnpe3s1iKJIX18fBw4cYHZ2lsLCQhISEs6aV6MgCNx///1Gs9n8g7NyAVuAjwyxCgwM/P4999xjONtVeoIgEBgYSFFREQEBARw5coT6+nqv2hkMDQ0tvs5Ww9fXl8LCQux2O6WlpZsu0V8NEkGKwiDAtBK3y40bEREWI1ZXXnkld955JzCfTsvKyqK8vJzx8fHFsuu4uDhUjY2MvfACMrOZgK98ZdnKm7VwfMDKs/tH0SglfPmSQPK3pyy25PAWjEYjJpNpUSTvCZKSkmhsbNz0+eHh4XR3d2/q3PXqrACUcgmyZCVamwL3SBhqmwKnCiTyrb1fNxOxWrCiWC3KsxKGh4cxGo2b3vWPj883C/fUKHJBgJyRkbEqQRuZaMHmmF53C5vOzk5mZmZIS0tbk/jZHDOUNz5FZdMz6DVmLth+FzEh5yEIH1h2kpMRvv1tAv/+dyb+/nf6+/sXqxjtdvuqFg7LQaKS4LItJVZut8iJYRtKaRN6TTAJ4ZcA81Hbtra20+ZnmSDlOmMRGomSP4weoL6jmYqKioVKtg1taEW3G8uxYyhjY5Gu8zclCALbtm3j2LFjXtvQiqLI0NAQBw8eZGRkhPz8fFJSUtZNWLcSV199tUStVl8hCMLm2xycQ/hI2C0IgqANCQm55rrrrjtnnNUWogHBwcF0d3cvltHGxMR4ZBTpdrtpaGhgx44dXrza1SGVSklJSWF0dJQjR44QExNDeHi4V0WNOrMea7OMyaEhdEHz95ZUkOB2u2lvbyciImJxAlhIvR45cuT/cffe4ZGe5b3/553epVHXqndp1Ve9rLaAbTDFYAy2wUDABDDJL7ZDOyT5JedKb4dycg4/ciWchASHEkNsMAQ4gHe10qqveu+99xmNpr6/P2ZnvNpVmRlJu3K+17XX7s7M++rRO8/7Pvdz39/7+0UikZAQG4u6qYmt9nbUubkY3/MehACucf+Mhe/XrxGml/GRK2Ho1VLQhpCenk5zczPl5eUnlibPyMjwdhIdRxPGaDQikUgClgZQq9XIZDK2t7f92oGDm2fV39/vtS45CnlXghlqX0A5eQmZTYpT4y6bWa1W7x+Hw4HdbsfhcNyzoGxvb3Pt2rU9r0mlUuRyOTKZDLlcjkqlQqFQoFQqUavVWK1Wv3finmsRyPyempo6Vnm+v7/fLz26g9DV1UVGRgaqQ5o1wC0KKpOqiAw5mjy+sLDA7Ows5eXlR16b+dUuOob+DZvDzPnEx0iLe+jegOpO/MEfwEsvkfuNb1Cbns7w8DDR0dGkpqb6/T24OVZ7587SpgOrXUSlG6Ew/Rkkty2vPJ3A4+PjZGRk7DlGJ1XxPm0p39q4zq+EAT5d/SgKmf/PFdvUFM7NTQwPPeTXcXcS2Y9ri7S6usrAwABqtdrNQQ1g03CakEqlfO5znwv6wz/8w/8H+KMHPZ7j4r9EYKXX6z/6yU9+UncWbWcEQSA+Pp7Y2FgmJye9RrqJiYkBLdITExNERUU9ECua0NBQqqqq6O3t9RqKnpRZdUhsNHM4WZ6eQh3p3q1LBQnz8/OkpaXx9a9/neeee877eY1Gg9FoZGluDsnPfsbOwgL6K1fQX74c0ILYOb7DfzStcy5EzjOXwtAo31gEoqOj2d3dpb29naKiohMJKD1iie3t7cdWW87MzKS7u5vKysqAxuYhsfu7oOt0Osxm84F6Vru7u2xubmIymdje3naT7UPPEbFixCmA3WjHZnOiVCoxGAwolUpvkCSTye7JCly7do3Lly97/y+KIk6n0xuM2e12b4C2vb3N0tISFouF2tpawD1ndDoder3e+2e/6x5oGdBms2E2mwkODsjwgeXlZZRK5bHFF2dmZpBIJEdqpjldduZWOogOK0AqOTxgWF9fZ3BwcF93gjthd1joHn2ZqcUGDNoYKnN/myCdDzwsnQ6++lWEJ54g+4/+CIvR6NYJlMm8Xn2Iok//Dp22ol9zQJfa+7q4ts37NgTOGdcI+dd67+tvX1nhO4DuE5+Ac+f2nMcsisw+9RRvrc7m55IefmXq5u3B/slRgLsbUJDLUd0VuPmCzMxM76Y8kGfE5uYm/f39SCQScnNzz4Q+1kH46Ec/Kv+TP/mT3xQE4U9EUbx/mj+ngLMXifiJ22bLn/vMZz7z4EzvfIBEIiEpKYm4uDjGx8epra31Zn58TSvb7XYmJydPzIw1EHj8oRYWFrh58yaZmZkn0hJuiApjjkU251dx3n64SZEwNjYGcE9WZHR0FIfDQalajWlhAUt5OecCDKqah0281rpJUqSSD14MQSm/9/tISkrCYrHQ29t7YmapBoOB2NhYBgYGjpWlMBgMqNVqlpeXAyoPR0ZGMjg4SFZWll8lDkEQ0Ol0bG9vo1KpWFtbY319nY2NDXZ3d1GpVBgMBvR6PQkJCeh0Olai7Cz9yzpSEbSxBlJSAi95CYLgDcL2y8xYLBZ2d3cpLy/3lvc8Qd7y8jLb29uA+/p5bF70ej2rq6sBCafOzs4SExMT0Bz08ImOq79nsVgYHh72yZ9wca0Xh9NypIWNyWSio6ODsrKyQ8tGyxuD3Br8VyzWddLjHiEz4R3ezJAv2H7oIUyPPkpkUxMADqcTUaFAABAE9x8f/q3aFZFbRcR1GQIgCgIai5U4UYZRJwNh1nuM0eWiAFANDsLKCggCoihiX1tDu7RE2cc/jiwql80NGw3mQeIUYeRofJfREB0Odnp6UGVm7tvBeBQUCgVxcXGMjo6S7gdf1GQyMTAwgN1uJzMz80j7qbMAnU7He9/7Xs0//uM/vhv44YMez3Hwpg+sgJqqqqqgk+iguR+QyWSkpaWRmJjIyMgItbW1pKWl+aQX4rG3OAuZuaioKIxGI52dnSwsLJCTk3OsEqfCIEWUOrGu2LCLbj6TVNg/sJqfn3d7khUWsvS1r6FMS2MtLo729nYKCgr8Cg5q+7b5ZecWGTEqPlAVgvyQDsCsrCxu3brF6OjoiXVjJicn09DQcCyVb3DvbFtbWwNSR5ZKpYSGhrK8vOyz8r7NZmNlZYXd3V0aGxu9GcSQkBASExNRqVT7jiM6Vc6EYQPNlog69HjeiUfhTuK6IAhotVq0Wu2e39HpdLK1tcXGxgZDQ0Nsb297s05Op5OgoCCfr+f09HTAJfqFhQUMBkNAhrYeeLr1fL0XZ5dbUch1hAcfHERarVZaW1u5cOHCgVw1h9NG3/grjM1dQ6uOoKbgc4QYkvwa+9raGp2dnRR95ztIbmdV1hcXGR4ePjJLds+5bpqY+9kmOV+KRqqW0D/+Gi83p5EcqeCZy3vHJQX+/sUXefTRR3nooYdYWlqit7eXwoYGFL//+8huW888HFTArH2NVzaaiJQHES73Lau4OzqKaLEcKArqCzzm6wkJCUdWCCwWC4ODg5hMJjIzMwPubH1Q+OxnPxv06quv/iFv8sDqvpPXBUGQCoLQLgjCa7f//01BEDoFQegSBOFlQRD8erKcO3fuj770pS+dfUvwuyCXy8nKyqK8vJy1tTVu3LjB4uLigUTFnZ0dlpeXj+09dpJQKpWUlJQQFhZGfX19wGKTAIJEQBbsQmI2sL7t7gyS3M5YSSQSEhISAHdqe3BwkJKSEnaamxEtFgxXr3rT3E1NTT4RzUVR5Bcdm/yyc4u8BDVPVR8eVIF7cS4sLGRxcTGgTrqDzllQUEB3d/exCPIajYbg4GDm5+cDOv4oTStRFNnY2GBgYIDa2lqamprY3NwkISGB4OBgqquryc7OJjo6GrVafWgwElXuvsXD4k+mjHwQfCGuS6VSjEYjSUlJFBcXU1RURFhYGEqlktHRUV5//XVaW1uZmZk59PvZ2tpCqVQGVBoXRdGrsn4ceGRJfNlkOpy7LKx2ExNWiESyf9DiaQw5zHB3bWuca7f+grG5aySfu8yVC7/nd1A1Pz9Pd3c35eXle0pVkZGRxMTE+C2qK1W5555z18WWeY7u8WYcLh2Zsftnc7/yla9w5coVurq6GBsbo6KiguDJSQgJcZcHcZPZnwypQi5I+e5anc/K7JauLiQaDcoDxFl9+n2kUtLT0w8VBLZarfT09NDc3ExUVBRVVVVvuqAKIDU1leTk5BhBEHxO4QuC8H8EQVgSBKHnjtfeLwhCryAILkEQfBdoOyE8iK7A54E725heFEUxXxTFPGAK+G1fTyQIQqzRaMwpLr7v1+3EoFKpyM3Npbi42OvZt1+nVX9/P5mZmWfCm/BOCIJAXFwcZWVlDA0N0dvbe48ujK/QhKuR74SwvOXulvNkrOLi4lAoFFitVtrb2ykuLkbmdGK6eRNVZiaKmBjAfVPGx8fT0NBwqHWMSxR5rXWTun4TJalaHq8wIvXRCFgikVBSUsLIyIjPHXFHQaPRkJycTG9v77HOk56eztDQUECirsHBwezs7OzpjhJFkZWVFTo7O7l27Rqjo6Po9XoqKiq4ePEiWVlZxMXFeXlWviKxSs9W8RS6c6ebsQqkI3B1dZWIiAji4+MpKiriypUrpKWlYTabaWhooL6+nrGxsXvm13EMl2dmZggNDT0Wb3J7e5vp6WmysrJ8+vz8ShdOl52YiJJ933e5XLS1tZGQkLBvednlctA3/iNqO/4Wp8tGVe7vkJf6AWRS/zrMxsfHGRsbo7Kyct/fPykpCblczujoqM/nlKrcy5rD4qR96NtYHO7scmLE/mNbW1vjj//4j9nY2KCsrMxdVu7qgry8N8qMgEGq4f0hlaw4tnl1o/nIOe+yWtkdGECdne2TOPFhOHfuHJubm97ytQd2u52BgQEaGhoIDg6mpqbmzHjYBorf//3fD42Kivp9Pw75Z+Btd73WAzwO1J7UuPzBfQ2sBEGIBd4B/KPnNVEUt26/JwBqwOcndFhY2Auf//zn33TZqv2g0WgoLCwkPz+fsbExGhoa2Nhwe+htbGxgtVrvi7xCoFCr1VRUVKBSqairqwtIf0UVpkK+a2Rlcxxwc6yeffZZ/vIv/9Kr9Hz+/Hl0Oh2mhgbE3V30V/aaxsbExHD+/HkaGxvveQgBOF0iP2xYp2XETHWWjncWByHx8yEkl8spKSmhu7v7xMRT4+LisNlsLCwsBHwOlUpFREREwPIJsbGxTE9Ps76+Tnd3N9euXWNmZoZz585x6dIlioqKiImJ2VNm8pTY/FGAFwQBaZh4ohIk+yEQDau7hUEFQSAoKIiMjAxqamq4cMFNXm5tbeXmzZtMTk5itVr9KqPeCZfLxejoKGlpaX4fe+c5Ojo6yM/P97lkNrPciloRTKjh3o5OURTp6urCaDTuGyxumme53v7XDE3/jPjIMq4W/QHhRv84aaIo0tvby+rq6pHmzTk5OSwuLrK0tOTTuSW3A6uZ2XbWtyeQyCvRKiWE6vdSKFwuF/39/bS2tvKNb3yDJ554gpaWFnC5oKfHHVjdhWRlFG815NFjmaLRPHToOHYHBhDtdp9EQY+CIAicP3+evr4+AK+naV1dHSqVipqamiMtdd4seOSRRwS5XP5WQRB8alMWRbEWWLvrtX5RFAP3/Dom7nfG6qvAF4A9W2pBEP4JWAAygb/z5USCIMikUumHPvCBD5wZiYWTgF6vp6SkhKysLPr7+2lpaaG7u5vs7Owzf9MIgkBKSgoXLlygq6uLoaEhvzIZylAZgkvKzop7kZYKEi5fvsxTTz1FT08PkZGRRERE4NrZwdTQgOr8eRT7EOfDwsK4cOECra2te7JKdqfI9+rW6Jq08NY8Aw8X+M6fuRtqtZoLFy7Q1tZ2IgKiHp/C/v7+fZXlfUVqaipjY2N+Zw09Ugf9/f2Mjo4SERHBpUuXKCgoIDw8/FDeWmhoqN/ZO41GcyqaaHfC34yVKIpHyk6o1WqSk5Oprq6moKAAm81GbW0tLpeLtbU1vzWHJicniYqKOlZ37fDwMBERET53I9rsJpbW+4iJKN5XAmFoaMgrEHwnRNHF0PQvuH7rr9i1bVKW/WkuZHwEucy/4NXlcnHr1i1EUaSoqOjIYNBjM9XX1+dTAO8pBU5NtxJpzGZlS09ChGLPvb61tUVdXR0ymYyHHnqIGzduoNPpuHz5Mv/3H/4BTCY4wNOvWpdFliqWn2+2M2ldPnAcO11dSIOCUBxTKsEDDwezt7fX2+laU1NDYmLifbOfuR+QSCR86lOf0ul0uo8+6LEEivv2bQiC8E5gSRTFtrvfE0XxY8A53CXCJ305n0wme9fjjz+ufhCyA/cDwcHBVFRUEBoaislkYmxs7NQXopOCXq+nqqoKl8tFfX29z9kMZYh7RynfcfM57FYrr7/+Ol1dXdjtdi9h3HTzJqLViuGubNWdMBgMlJeX09PTw9zcHFa7i5eurzIwu8s7ioKoyfZPs+mgn5Gbm0tLS8uJCIgqlUqysrLo7OwMWBRQoVAQExPDxMTEkZ8VRZG1tTVaW1tpampCLpcTFhZGWloakZGRPj+s/REK9UCtVp+aK4EHVqvVr4DFbDaj1Wp9DrY1Gg1paWno9XrS09OZnp7m+vXrjI6O+jQfHA4HExMTx2qE2NjYYGlpya+M19xKB6LoIjb8XgrF1NQUGxsb5Obm7rkOJssSNzq/TN/4K0SF5nK16A+IDvU/E2O322lsbCQ4ONgnkVEPlEolhYWFtLW1HXltJUr3OSUOJYkxT7Kx4yQx3D0PRFFkdHSU9vZ28vPzSUtL85qaNzQ0kJOTw9c//Wn3iQ7INAmCwHuNZQRLtXx/rR6T89557DSbsY6Oos7LQziBoEcURaanpzGZTMzNzVFdXU1qaup9t5+5X/jkJz+p1ul0LwpnPZtwAO5nmFsFvFsQhAngu8BVQRC+7XlTFEUn8D3gfb6cLCIi4veef/754wm+vAkwPz9PZWUl586do7W1le7u7kP5Q2cFEomEzMxMsrOzaW1tZWJi4shgQRnqDqyUO+6d2fTIJFevXuUHP/iBV0HaaTZjamxEnZNzpLK6Wq2msrKSrqFZ/v4/ZxlfsvJ4uZGy9MA7r+5GWFgYKSkptLS0nIhhdVRUFHK5/Fju9snJyUxNTeFw7C8F43K5mJqa4saNG4yPj5OcnOz1CUtMTPTbmNlgMLC1teVXMHjaGSvPWPx5LgeiX2W1WrHZbMTFxVFYWOg19K2vr6ezs/PQTcX4+DhxcXEBd9M6nU46OzspLCz0K2Mxs9SKTh1BkG5vJmVpaYnJyUmKioq85xNFkbG567ze9uds78xTlPEblGR9AqXC/42JxWKhoaGBxMTEgILJoKAgkpOT6erqOnSuLZo6AYg2FLO06c5YJkQo2NnZ8fIvq6ur7yHkR0ZG8vrrr/P+jAxEQYBDJFBUEgVPhVazK9r4/tpNnOLee9/S2wsu17G6AcF9/efn56mtrWVzc5Pq6mqCg4NP3b/1QSM8PJwLFy4EAfuTAM847ltgJYril0RRjBVFMRF4Cvg18GFBEFLBy7F6F3Ck86QgCMlRUVEJdyvl/lfDnYKBkZGRXLx4kZCQEBobG+nv779v7ufHgdFopLq6mq2tLZqamg4NCmV6CRKFgM7mFhScGp0A4MqVK16JCVN9PaLdjv4Oocj94BJFhuZ2+faNTW7On2PDApXxZvITTz7DGRMTQ2Rk5In4/4GbUzI6Ohpw4CGTyUhISPBKVXjgcDgYHR3l+vXrmM1mSktLKSoqIiQkxBuAREREsLKy4leQKAiC34HSaQdWdrvd74AlEOPluw2XPR56ly5dIioqis7OTpqbm71WNXeOb2ZmhqQk/zro7kRfXx/x8fF+STRYrBusbA4TE168J+jc2Nigr6+P0tJS771msa7T0PO/6Br5HqFBqVwt+gPiIksDKp9vbW3R2NhIdnb2kcKlhyEuLg6pVMrk5OS+71tt2/ROfx8AozKZyWUrKrmAdWuB5uZmMjIyyM7OPjDTo9VqeTonB1JTQaulu7v7wMxqlNzIu4JLmLAt8cutzj3vWTo7kUVEeDd/oijidInYHSK7dhc7Vhcmi5OtHSfrJger2w6WN+0sbtiZW7Mxu2pjYXGJuro6FhcXKS0tJScnB6VSSUZGxqkbNJ8FfOELXwg9d+7clx70OALBgxZEEoBvCYJguP3vTuC5ww+BiIiIFz//+c8HLvrzJoAoigwODpKf/4bjvCAIxMTEeG1y6urqiImJOTPaVgfBYzy8tLREQ0MD6enpxNzu5LsTgiCgCJGhsoQBM7S3uN3u827v+pwmE+amJtS5ucgPIPLbnSJdEzvcHDCxvOXAoJbwcIGBC8kaxkcGaGtro7Cw8MRT6CkpKfT09NDf38/58+ePdS65XE5ubi4dHR1UVFQEtJAlJCRQW1tLYmIigiAwNjbG3Nwc8fHxXLx48cD5IpFIiIiIYGFhwa8FMDQ0lJWVFZ+tMk67FBgIv2pra8svZWpRFJmdnaWiouKe9wRBIDIyksjISNbX1xkeHsbhcJCRkeH1iUxKSgp4Hi4vL3s9+/zB7PItQCT2jm7AnZ0d2tvbKS0tRalUIooiM0vNdI58H1F0kp/6FInRFwPmI66srNDd3U1xcbHftkn7ITc3l/r6eoxG4z1Zp+6xH2AXLQhycFlh3GxFItppHd0lPKKA3gUpzvktXC63f6BLdDe0uMQ3/v+Wlg42k7L4vz8b53eeukx0XArP/8m/ojGEej/jcok4XeASNagcFdQ7HbQLM0iR4nS6cKqv4tIrEL8/6/5ZAey3Uo0mHq8uvCdwNhgMqFQqlpeXfZLWeLOipqYGhUJRLQhCsCiKGwd9ThCE7wCXgTBBEGZwW+Ks4eZrhwM/EQShQxTFR+7HuOEBBVaiKF4Drt3+b5U/xwqCII2Kinr/448//l+HrbcPlpeX0Wg0+z6IPLpOsbGxTExMcOPGDRISEs48idFDsO3u7mZhYYG8vLx7sgrKUCmWWffiPD8zTlBQkFc12FRXh+hw7Jut2rE6aR420zRkxmx1ERUs533lRrLj1chu61NlZ2czNjZGU1MTJSUlxxI03Q/Z2dm0tbUxPj5+rEwEuAOVoKAgxsbGAiqbSKVSEhMTvQbSiYmJ1NTU+LSQx8fH09vb61dgFRYWxtjYmFdv7CioVKpTLWn7G1h5Pu9P8LCxsYFWqz3SxNZoNFJaWsrW1hYDAwMMDAxgsVi4evWqzz/rTtjtdnp6enzy7Lsbs8utBOni0GvcmRSbzUZzczMFBQVotVqstm06Rr7D/EoHIYYUijI+glYd+OI9OzvL6Ogo5eXlJ2bDJZVKvXyrqqoq7328uNbLzFIzGfGPIqolbK+bMUlsWF1yuhZ1sGj2nkMAJBKQCALS239LJKCwW9BNj9Fb/V5MTg1P/tZf8a2/+W3++LfezvN/9h2i4pKRSwSkcgGJREAqQJigZ9y+wK64TZYmBtniOs7NKbQXCpGrVUgEkEgEJAJI7/z7jp8rFQSsVgvzc7O4RGhfCiU+NvrAbGRGRgYdHR2EhYWd+aamQCEIAp/+9Kf1f/qnf/phDmlqE0Xx6QPe+o/TGdnROLtpjoNxpbKyMnh9fZ2IiIj/kpPKIxhYUFBw6OekUikpKSnEx8czNja2xybnrF4XhUJBUVERs7Oz1NXVkZ2dvUdGQhkig34JgguW5udJTk52c6u2tzE1N6POz0d+R7lmddtBw6CJ9rEd7E6RtGgllZk6kiOV+16D5ORkVCoVN2/epLS09EQ9Fz0Coo2NjahUqmNb/WRmZnqNmv3Z6Xs4VOPj49jtdqqrq/0yXdXr9djtdq8tjS8ICgryS2JDIpGcSNn0IPgrtRAIv8pf7SqDwUBpaamXgH2nfIg/6O7uJi0tze+5a7Yss749QXbSewE3R6u5udlreTK/0knH8L9hd1jITnovqbFvOdw4+QiMjo6ytLRERUXFiW9i9Ho9qampdHZ2UlxcjMO5S8fwd9CpI0mKfgsDwiIMSnkqU4s+T4suRYlMJngDmQMlVlpaQBQpf6KS8ndEwjs+wccezeKxxx7jK59/Jz/60Y/2zVBuOFR8Y/lnLEvmec+tUZRKNeEVd0sr7Q+z2czAQD/G2GrVAAAgAElEQVT23V0uFmThlOpp/+kSIbqDl2edTodGownYxurNAIvFQmVlpdJoNL6Ij2oBZwVvusAqJibm+U9+8pPKxcVF+vr6iIyM9JtncNaxsrLiNYz1BXK5nIyMDJKSkhgeHvba5ERHR5/ZACsmJoaQkBCvJc758+eRyWTIjRIEl4BmW8X7P1lOWfwzAGzfuAEuF4ZLlxBFkakVGzcHTAzM7CKRQH6ihspMHRFBRz/Az507h1KppLGxkaKiohM1JpVKpZSUlNDQ0IBSqSQkJHCZNalUuseo2Zds5OLiIgMDA4SHh3Px4kWWl5cZHR31llN9RVxcHNPT0z53mwmCgFqt9itTJJPJAuJC+YKdnR2/AtvV1dV7/CgPg9PpZG1tze/rarFYMJlMXLp0idXVVW7duoXRaCQjI+PIzBfA3NwcLpeL2FgfjI3vwsxyKwAx4UWIokhbWxtxcXGEhgXRNvgvTC82EqSLoyrveQzawHlQHo0qm81GWVnZqWXRY2NjWVxcZGZmhjVrAxbrOnlJz9LY0ETCW5KRTenY7LVg6ltHppUQnKvGmK9BfZgwbXe3++87pBaqqqq4efMmb3/72/nGN76xb2AVLNPyhLGSf1m9xq/Py3mvZn+phjuxu7vL4OAgW1tbZGRkeO2oBmfdJXLjIYEVuAWBOzs7/0sFVk6nk4WFBaampnA6ncTHxxMZGakXBCFRFMWJBz0+X/GmCqwEQdDExsaWPfzww+4sxu0voaenB4fDQVxcHOfOnTuVB/X9xMjISECmvAqFguzsbCwWC0NDQ4yOju65Yc8a1Go1ZWVlTE5OUldXR35+PvPbC4AB3aaa0CQdubmJOLe2MLe2osovYNCsob5tmZlVO2qFwMVsPWVpWvRq/7gqoaGhFBcX09bWRk5OzonaPygUCkpLS2lsbKSkpORYQX9QUBBRUVFek+SDYDab6enpQSaT7cnERUdHMzIy4pUS8BUxMTHU19eTmprq89zx8Kx8zeJ4COwH2aUcB/6WAjc3N/0ax/z8fEAK14ODg2RkZCAIAmFhYVy8eJGZmRnq6+tJSkoiISHhwHN6FmJP56G/mFlqJdSQglpppLu7G4PBgMZg4ddtf8qudZOM+LeTEf92v4yT74bT6eTWrVtotVoKCwtP/bmTl5fHtbpXMUuvEaTMYWF6l9LSUvd3XwAxjwazPbzLetcOq61mVhrNKMNkGPPUBOdrUBrv+l27ukCjgbuC7PT0dBobG72Z4/30zlJV0VQtqqlPgx61lnvDLzdsNhvDw8MsLy+Tnp5OXl7enuu0bnJr0Bl1hz/TdDodCoWCtbW1Y23gHjQ8dllTU1Osra0RGRlJbm6u97n53HPPGb/whS88C/y/D3akvuPsEnL2gVwuf/fTTz+t9kxCqVRKTEwM5eXlFBUVYbVaqa+vp62tjeXl5VMtNZwWNjY2kEgkx8qiqNVq8vPzuXDhAtPT09y8eZO1tbWjD3wAEASBxMREiouL6ejoYHHH7XUnzDi48bM+egbqWL1eR48hi28JpXyvfg2z1cU7ioL47GNRvDXP4HdQ5YFer6e8vJy+vr5jyRvsB4+AaGtr67G5RGlpaayuru77HTqdTgYGBmhtbSUlJYWioqI9JSJBEMjMzDzUZ2w/yOVy9Hr9Pd1sh8FfPavTJLD7U8bc2dk50t/wbtzdDegLTCYTJpNpj0K7xxKquroas9lMXV2d13HhToiiSGdnJ9nZ2T5ltu7GpnmW7Z15YiKKGRkZwe6wYpV2Ut/9P5FKFNQUfI6sxHcdK6iy2Ww0NjYSFhbG+fPn78tmTioVcKq6wKXknLGGioqKPQG1RCYQlKUm8clQsj8fTexjwch0EhZ+vc3AVxYZ/sdlVlrMOHZuC+p2dbmzVftk2cLDw1GpVGxtbVFeXs4LL7ywR4hXdLnIe32UxBWRX1h6mbbt9U51OBwMDg5SX1+PXq/n0qVLnDt37p7rtGZyoJAJaJVHL89paWkMDw8f+L7T6aSwsJB3vvOdgFvio6ysjLS0NJ588kmv+4HVauXJJ58kNTWVsrIyn3Twjgur1crIyAi1tbWMjo4SHR3N5cuX7ymPP/HEE1KZTPaRN5Om1ZsqsAoPD3/+4x//+L7bf7VaTXp6OpcuXSIpKYnZ2VmuXbvG4ODgm0ZYE9zZquPYW9wJrVZLUVERubm5DA8P09TUdGb1TzyLRVR8JC6Ji5XeGb7+Jz/nP345yT9sZlAfWYleK+ep6hCef0ckZek6FLLjT1+VSkVFRQXT09OMjIycaDAeFBREdnY2LS0tB2pK+QIPd6urq2vPeVZXV7lx4wYymYyLFy8emHULDw/HYrH4/d0fZcx8N4KCgvYNCg7CaUouiKLocwnKX36VxWLB5XL5nYkcGBg40O9TLpeTnZ1Nfn4+vb299Pb27vmup6amvJZFgWB2qRUBCYI9irmlftYcrzE+f52UmKtcufAljIbEgM7rgUcjKjk5+diNG75CFEX6BjvYta+gkOkQcR0azEnVEkKLtKR+PJys340k6q0GnBYXsz/eoO9vFhh/aQVXexdizuFlPK1Wy8MPP8zXvvY13v/+93vnsG1qCtfmJu+RZGGQqvneWj1m5y5Op5PR0VFu3LiBXC6npqaG+Pj4A8e6bnZi1El9CkyDg4NxOp372ncBfO1rX9uT6f7iF7/Iiy++yPDwMEajkW9+85sAfPOb38RoNDIyMsKLL77IF7/4xSN/diBwuVzMz8/T1NREU1MTEomEiooKiouLD+RMGwwGCgsLNUDhqQzqFPCmCawEQQjT6/UpmZmHe1IJgkBISAgFBQVcvHgRtVpNe3s7N2/eZHp6+lgL3GnDbDazu7t74mldg8Hg3aX09PTQ1tbml7fb/UB3TzeatHAWB0DikjCy4tapsaovEm2Z52PlKn7zoXDOx6mR+GiY7CvkcjllZWVsbW3R09NzosFVeHg4iYmJtLa2HktAVKvVkpiYSF9fHw6Hg66uLgYHBykpKSE1NfXQIMKTtfJX+yYsLIz19XWf7xmJRIJKpfI5C3VaGSuHw+GXjMHq6qpfgdXU1JTfHKfNzU3sdvuRJWeDwUBlZSUajYa6ujpWVlYwm82Mj48HRA8AdwAys9yKXhPP4OQvWHf+HJfopCrvBXJTnkDqp3Hy3djc3KSpqYnc3NxjN2z4CrPZTH19PVK0FGc+i0PcYGj+JZZXffPJVATLiKzRk/HbEaQ/F05YmQ7bwAySjVXmFxOYfnUd07gVcR+dBKlUyle+8hW++tWv8sorr3D16lWWlpbY6epCkMsJTj/PUyHV7Dit/Ovcr6mtrcXpdHpFeI+am+smx6HE9buRmpq6b9ZqZmaGn/zkJ3ziE58A3PPg17/+NU888QQAH/3oR3nllVcAePXVV/noR90OMk888QS/+tWvTvQ56Hm2Xr9+ndXVVbKysqipqSE5OdmnDOxzzz0XGhUVdaQU01nBm4ZjpdPpPvSJT3zCr/qYTCYjPj6e+Ph4zGYz09PT3Lhxw2suajQazxT3aGRkhNTU1FM7f0hICJWVlSwvL9Pe3o7BYCA9Pf1EO+P8hUt00bjYS4NxgojucPK6U7CUWOj4o18RFBZLQVo7NaKGpKTqUx2HRCKhsLDQW1a7cOHCiWldxcXFsbu7S2dnJwUFBQHPuYSEBG7cuMG1a9dIS0u7x3bkMISGhjI8PMz6+rpXvuIoCIJAdHQ08/PzPpe9PDwrXz5/WhmrQPhVvvrseZSwq6v9m4/9/f0ctSn0QBAEkpKSiIyMpKOjg+3tbYqKigLWqlvfnmBndxXENRBEEqIqyUl+n98ef/theXmZ3t7eY3MJfYUoikxOTjIxMUFeXp53E6pU6Gjs+QYNvV/jctFnMWh9C/AEQUAdrUAdrUAU3Qbo0tJ8VrstrLXtIA+SYsxzk95VEXu5u88//zzx8fF88IMf5LlPf5q/KylBlZWFoFCwMDcOThcbwg4VlW9B5aO1kiiKrJucpEb5VsYG9+bNI+Fx57P8hRde4K//+q+92azV1VWCg4O98yg2NpbZ2VnALYvhuWdlMhlBQUEBCebeCY8I7szMDAqFgvj4eM6fPx9QM8Pb3vY2AXiXIAjS2y4tZxpvmoyVXq//9DPPPBOwU6lWqyUzM5PLly8TExPD+Pg4169fZ3h4+ExYxOzu7rKxsbGHf3FaCA8Pp7q6moiICJqbm+nt7T2W8W8gsItOWswj/M/Fn/AzZw8R82HkNiSjP6/EZpiju72F6nd8ApMjhWmFnunp6VPnzAmCQFZWFuHh4TQ2Nnr5BycBj6+Xv1wnD1wulzfj5Al4/A3QPMbe/sDTHegr/OFZnVbGyh+pBYvFgkKh8Plhv7a2hsFg8CvIWV1dRSKR+BzQeqDRaAgLC0Ov19Pb2+uXnMWdmJxvAkAh11Ge/RyF6c+cSFA1PT3NwMAA5eXl9yWo2t3d9dIZqqur92T2w4MzuFjwuwgCXG//G9a2xg450/4QetwdgZG/VcX5L0QR/4QRVYSMpXoTg/9ricGvL7FUv4196411/b3vfS/Xr1/nr194AdFiwRoXx49afsmPxU50cjWfin6bz0EVgGnXhd0pHklc3zNuQSAlJYXR0VHva6+99hoREREUFRV5X9vv+el5hhz2nj8QRZGlpSVaW1upr6/H6XRSUlJCWVkZ0dHRAXeIKhQKHn74YQVwsEHsGcKbImMlCEJySUlJaFRU1Emci/DwcMLDw7Hb7czOztLS0oJcLic+Pp6oqKgHIrI5OTnpVcm+H/AszlFRUczMzNDQ0EBUVBQpKSmn2lVpcdloMQ/TaBrC5NrF6FDx0Mp5gn4VjjpGRuL7Qvn3LzcQYTTyyKV8Vi1ZlD4UzdBgPwsLC+Tn5wdE3vUHiYmJqFQqGhoaKCkp8Sv7cRAEQfAaNk9OTvospAnuDMytW7eIiIjg4sWLzM/P09XVRXHxvSa6hyEoKAiFQuGXYrNWq0UURZ+zQMHBwXR1dfl0bqlUeiL+infDn4yVv7vyqakpv747URQZGBggN/fo9vu7sbm5ycLCAtXV1ZhMJjo6OoiNjSUpKcnn54TdbmdpwURUSBEXMp9EIT9+ACSKIsPDw6ytrVFRUXFfXB/m5uYYHBy8R/fuTgTr4qgp/BzX275MXdfXKM36BFGhflz3ri6IjYWQEKSAMU+DMU+D3eRko8fCRucO8z/fYv4XW+iSlBjz1QSdV1NaWsr8t7/Nv3R2oi9IYqVMg1Gm46NhVzBI/Xt2rJvcZfejpBbuxrlz5xgaGsLhcCCTyaivr+dHP/oRP/3pT9nd3WVra4sXXniBjY0N72dmZma8IsCxsbFMT08TGxuLw+Fgc3PTL0qK2WxmamqKhYUFQkJCSElJITg4+ETXs0996lPGX/7yl78D/PLETnpKeFNkrEJDQ3/zM5/5zIn3k8rlchITE7l48SLZ2dmsr69z/fp1uru7A94dBgKXy8Xc3FxA2jTHhacrqaamBqVSSV1dHSMjI3u6XU4CW84dfr7ZzpcXXuWXW11EyoN5n6KYspFoQn4VgUwrIfFDoUjkAi9++MPUfupTREWP4xIVjC65KCwsJDY2lvr6ehYXF090bPshKiqKvLw8mpqaTmwuCIJAUVER09PTPv8OCwsLNDU1cf78edLT0xEEwdtJ5Enj+wNPh6A/2b/4+Hifs1YSiQSFQuFzFlgikZz4XPMnsPKHuB7IgrO0tIRarfa7y9fpdNLR0UFBQYG3S7iqqort7W1aW1t98gn1CIDmpj1Kee6zJxZUdXV1sbOzs8dX8LRgt9tpa2tjbm6OqqqqI8n7QbooijM+g0TU09T790wuNPj+w7q79+hXeSDXSQkv15H2qQgyfyeCyEt6bOsOpv9jg96/mqf1233Mj4zwe6/9mO/deI1weRAfD3ur30EVwNptqYUQPzJW4H62eIIjgL/4i79gZmaGiYkJvvvd73L16lVeeuklrly5wssvvwzAt771LR577DEA3v3ud/Otb30LgJdffpmrV68eGRQ5HA6mpqa8huN6vZ6amhry8/NPhWZTUVGBRCIpFwTh+DvdU8aZD6wEQRBkMtmH3ve+952sudtd0Ov1ZGdnc+nSJcLDwxkcHKS2tpaxsbETLQnth/n5eSIiIk7cv84fSCQSkpKSuHjxIqIoUltby8TExLEzCsv2LV5Zb+IrCz/mpmmQdNU5ngt/hA+HXGKjax5jXwIuu0jyM6HIdVIWZmZY/+EPUUcEIVMPo1Xa6Bh383Cio6OprKxkYmKCjo6OU29EMBqNlJSU0N7eztLS0omcUyqVUlpaSn9//6FSBqIo0tfXx8TEBJWVlfcs5nl5eQwNDfldStPpdOh0Or+C0+joaObm5nwOxkJDQx9oOdCfUuDGxobPJbq5uTm/SrAev09fuVV3YmBggNjY2D0BmVQqJT8/n+joaOrr6w/t8hRFkfb2dqKjo49lenwnnE4nLS0tqFQq8vPzTz2zv7y8TF1dHVFRURQXF/ucqT4XlUi09l3o1Qm0D/0rQ1M/P3ru2u3Q1wdHCL4qw+REXTUQ86wGe9UyDqMF+XAQLy/M4HKJXHz0Kh8Lu4pWGhhrZd3kQACCtP4HrAkJCUxOTh76u/7VX/0VX/7yl0lNTWV1dZVnn30WgGeffZbV1VVSU1P58pe/zF/+5V/ue7woiqyurtLe3k5dXR0Wi4XCwkIqKyuJjY091TVMEASefvpptVQqffep/ZATwpuhFHihqKhIfRLmnb5AIpEQFRVFVFQUVqvVWybTaDTEx8cTHh5+4g+U8fFxLly4cKLnDBQymYy0tDQSExO9GiOpqanExMT4p/NjW6Fuu5+BXbcxaZE2hUpdJiEy9655ZHgU41ACtlUXyc+EooqQMzk5SVpqKn/+trfx/j//DML6FOdjBVrHrGxbnOjVUpRKJaWlpV4T6jsJrKcBnU5HRUUFzc3N7O7u+mVhchAUCgUlJSU0NzdTWlp6j3CnzWajra0No9FIWVnZge35OTk5dHR0+O0Zl5GRQXNzM5GRkT4dJ5PJMBqNrKys+FRCDAsLY2ZmZl+j7bvhIbCfJEfH18Bqd3cXuVzu8/08PT3t1306Pz9PcHCw36Xk1dVVNjY2qKys3Pf92NhYgoKCaGtrIz09fd/Aqa+vD7Va7Zea/GGwWq20tLQQFxfnVyk0EDidTvr6+jCZTAF7DOZkF1B/08S5SCN9E6+ya98iN/l9B1v0DA66g6sjAqudnR0GBwcxm81kFmUSVGmk98vz1HZMEhQezB9c+U1UksCpCusmB3qNFLnU/2yPQqEgKCjonvv08uXLXL7tr5qcnExzc/M9x6pUKv793//9wHNbLBampqaYn5/HYDAQHx9/rEacQPHxj39c99JLL/0O8N37+oP9xJkPrMLDw5/52Mc+5p+J1wlBqVSSkpJCSkqKVxm2r6+PiIgI4uPjT8SpfWNjA7lcfiI8npOEXC4nKyuL5OTkPSruhy3GoigybJ2nbrufCdsSakFBjT6bMm06OukbXS4Wi4XVX++img8m9t3B6FPd7/3Nf//viC4Xj7znPWxpdpBsyChNj6RldI2uiR2qstzXWxAE4uPjCQsLo729HaPRSGZm5qntoJVKJRUVFbS1tbG7u0taWtqxHygeZeqWlhYqKipQ3ia4bm9vH7pg3onw8HAWFhaYmJjwSztIrVYTGhrK7Oysz+Xn+Ph4xsfHfQqsPEbbvkCj0Zx4xsrpdPpUovKHX2UymZBIJD4v8i6Xi6GhIcrLy336vAd2u53u7m5KS0sPnWN6vZ6qqira2trY3Nzco481OjrK7u7uiW3WzGYzLS0tZGVlnXpzzfr6Op2dnSQkJJCTkxPwfaZUKklKTGZnJ4rkmCDGZl/HZtvmQsZH9hdB9fACDwisrFYrQ0NDrK+vk56e7r0O17d7WUrZprOjicfeehWV7Hj8zzWzE6M28KxPcnKy19LquLjbXiYuLm6P6fWDQGZmJkqlMlUQBK0oiuajj3gwOPOlQKlU+tgjjzzywDURgoODycvLo6amhuDgYHp7e6mrq2NyctInvsNBGB8fP7Fd5WlAqVSSm5tLSUkJCwsL1NfXs7KyV1HYKbro3Jng60s/49ur11lzbPO2oEJ+N+rdvMWQtyeoAuj/8QSq2WDCq3SEFruzNUuzs/yff/s3Hi8qIvuZZ1jdGsGoTyQyWE1MiJzOiXsXX41GQ2VlJQqFgrq6ulMVP5XJZJSUlGCxWOjq6joR0nVwcDBZWVleAdHl5WXa2tq4cOGCz+Wb8+fPMzk56bcuWVpaGiMjIz7/Hkajke3tbZ/mulQqRS6X+9Rp6vEXPCk4nc5TEQb1V2l9enqaiIgIn9XfPejt7SU5OdmnjZZHf83lctHW1obT6WRubo7FxcUTs5PZ2NigubmZgoKCUw2qXC4Xg4OD9PT0UFxc7BdB/yAkJiayurpKYvgjnE98jJnlVhp6vo7dsQ//r7sb5HLIyNjzst1up7+/n4aGBoxGIxcvXsTTRPWLrQ5+vd3NrH4Ah9POpfRHjzVe8F/D6m4EBQVht9sDvqdEUfQGt7W1tWxubpKbm0t1dTUJCQlnwi7uscceUwFvfdDjOAxnOrASBCEhPj5ed7/KgL7gJG10bDYbm5ubJ+pTd1rQaDQUFBSQn5/PxMQEDQ0NLK+v0mga4muLr/GD9QZcuHhvcBkvRL2LSl0mSsm9N+FM8xKSHj1B51VEP/QGf+R/fO5zWGw2vvRnf4ZLJrK5PU1oUAoABUkaFjbsLKzfu6gLgkBqaioFBQV0dHScuHr6nZBIJOTl5aFSqY6tpu5BZGQkcXFx1NXV0d/fT3l5uV9EZw/vpqOjw69gT6lUEhUV5bOyuoc0Pzc359PnfeVZnbSWlT/8Kl81vURRZGFhwWfxS6fTydjYmN+adAsLC9hsNr8COEEQyM7OJjQ0lBs3bnhFY08ie7u4uEhHRwelpaU+63wFgu3tberr6wG34fFJlYUFQSAnJ4eenh7S4h6mMP3DrGwMUd/1Vay2u5TKu7ogK8sdXOEmZg8PD1NXV4dGo6GmpobY2FgEQcAluvjxRiv1pgFKtWl8KrOChs/9kAvat+IwB96IYXeIbFtcfkkt7IekpCTGx8f9OsZXe5mzgA984AP6mJiYjz3ocRyGMx1YabXaxz/0oQ+d3h19TBxkozMwMODTYjE9PX2otcFZhF6vp7i4mKysLH64fJOfbrahQcEHQy7yWxGPUqhNRibs/2Awz1pZ+akVVbSM+MeNCLcV1M39/Xz7pz/l7eXlFDz0EGtbE4i4CA1yW/vkJKiRCNA5cfA1NRgMVFdXY7PZuHnzJmbz6WSJBUEgIyOD6OhoGhoajq3/JYoiVqsVp9OJXq/3lgT9gdFoJDw8/FDPsP2QkpLC+Pi4z115/mhaeYRCj8JJk9d9DaysVityudwnsu3y8jIhISE+E3MnJiaIiYnxSxbEarXS399Pfn5+QM+DsLAwb5PNcTLoHkxOTjI8PExFRYVf5t3+QBRFxsbGuHXrFrm5uWRkZJx4OT8kJASVSsXi4iIJURWUZX+K7Z15ajv+FrPljvnZ1QV5ebhcLsbHx7lx4wYSiYSamhoSEhK843KKLn643kjrzggXded5R1ARosmMUd6PTFCy3BC4o8WG2b1RO07GCtzNJktLS0dutO62l5FKpUfay5wFlJaW4nQ6y4UDCXMPHmd2YABBQUEffs973vPgc49H4G4bHa1We6SNjiiKzMzMPBCJhZOAQq9mQbtDrjSW3FE9O/1L7B6yQNo2HYz+6zKCSiTlmXAkCvfUc+3ssPXaa/ziv/03/u6f/xmA1c1hQCDE4OYNaZVS0s+p6JrcwbWPxYQHEomE8+fPe8trR3XIHAfx8fFkZGTQ0NAQcBDn6fwzmUxcvnwZQRD8Do48SEtLY2lpyS+vPrlcTlxcnM+7W7VajUwmO9CX7E6EhIT4ZOAsl8tPtLvTV6kFf2xspqamfG5a8LSg+1Pe9xgsZ2VlBRRY7+7u0tbWRnl5OQUFBTQ1Nfn0HR00loGBARYXF/dw/04aFouFxsZGdnZ2qK6uPtWMWFZWFgMDA7hcLqJCc6nM/R1sDjO1nX/Lhmka1tdhZoaN+Hhqa2ux2WxUV1eTkpKyJ5i2i06+t1ZHl2WStxryeSgon+HhYSqffpru2V6CspSsNJlx7gZGE/BILfirYXU3JBIJERERLCws7Pu+x17m2rVre+xlkpKSTl0j8CQglUqprq6WAaUPeiwH4cwGVoIgGDQaTexJdGHdT8hkMi/JLz8/H7PZzI0bN+jo6GBtbc270G9sbKDVat8UE3k/dFomcOLiYmgOlZWVxMTE0NraSldX1z0aRk6ri/Fvr+K0ukj6UChy/RsPq7Uf/xinyUTab/wGKbf5DaubIwTpYveoQ+cnati2uBhbPDpDFBISQnV1tZcfclrK+hERERQUFNDc3OxTEHEnPIupy+XW6JJKpeTl5bG2tuaX0rkHEomEgoICOjs7/dKFSkpKYnp62ucsh69ZK6lUilQq9UmqRBCEExMK9TVj5Su/ymazYTabfV74R0dHSUhI8EvfaWZmBrlcTiACyHa7nebmZnJycjAYDBiNRoqKimhtbfUryAZ3BqOzsxObzUZJScmptM57NpRNTU2kpaWRk5Nz6jIzarWayMhIb9k7NCiFi/mfRYKEus6vMHHzNQCs29tUVlaSkZFxD5fI6rLz7dXrDOzO8s6gYmr05wH48Y9/TNfwMBGhoURcNuCyiqw0BbbRekMc9PjXIy4ubk+Z32azeTNx/f39hIaGcvnyZe+8ebPhQx/6UGhERMQHH/Q4DsJZDqweefzxxx+cid0J4DAbnfHx8RNp3X8QEEWRNvMoMfIQouRuIbjIyEguXrxIaGgojY2N9PX1YbPZEJ0ik99fY3fJjvqyHUPcG2WFnZ4eXvrOd3j85ZfZuP1wdbkcrG1PEG3HX2AAACAASURBVBq0l5+SHqNCJRcOLQfeCZlMRn5+PomJiTQ0NDA/P39yF+AOBAcHU1ZWRmdn54E7xLshiiK3bt1CpVLt6XySSCQUFxczMTERkG6WXq8nLi7OL9saqVRKUlLSHjuMwxAVFcXi4qJPmUBfeVYqlerEgl9fM1a+8qtmZ2d9lhqx2WzMzc35rao/OjpKTk6Oz8d44HK5aG1tJSUlZQ9P02AwUFpaSkdHh88Bv8PhoLm5Ga1W65cHpT+w2Wy0traytLREVVXVfeWWpqamMj4+7t1AGLTRZMd/HJdTQr9+FOfDDxP5v/83ip///J5jLS4b31p5nQnrEo8byynVpXnfe+211zgfF0dCXByaaAX6NHc50Gnzf6OwZnKgkAlolcdflg0Gg9err7W1lYaGhhOzlzkLeOihhxAE4bEHPY6DcGavbExMzMfe//73ny3WXIDw2OgUFRVRVVWFVCplbm6O0dFR5ubmTsXW4zQxa19jybHJBW3KntcFQSAmJoaamhq0Wi319fX0fX+C7WEr5vQl0qoTvZ91bm+z9uqr/H8tLVgkEm978IZpCpfLTqhhb2AllwrkxKvpm97Favf9ekVGRlJVVcXMzAy3bt06Ef7J3fB0J46MjDA5OXnoZz1BlU6n29Mi74FMJqO0tJS+vr6AFN+TkpLY2tryid/kQXx8PAsLCz7xxaRSKaGhoT4Ffr7yrE6SwG6xWI4MrGw2G1Kp1Keskj/l+pGRkXvKR4dBFEU6OjrIzc31u9vKc2x4ePi+emFarZbS0lI6OzuPDK52d3dpaGggJibmRKRE9sPi4iL19fXExMRw4cKF+95d5nHZGBkZYW1tjZs3b7I4v0mwPgaNXov0Bz+AwkJ48kloavIeZ3Lu8k8rv2Levs6TIVUUaN6QNdnY2ODGjRs8lJOD5DbBO7JGj3PHxVqr//N5/bbUwnGvv8lkor+/3xu0p6SkUFNTQ2pqqt9dqmcVWq2WlJQUtSAIZ7Kl/kwGVoIgyFwuV9FZEc08ScjlcuRyOampqeTk5DwwG53joM08ilyQkqvef2cukUhISEigpqYG56wMa9A2ysw3MhyiKLL+yiv8qq+Pwbk5vvjFL3ofJqubIwDejsA7kZ+kwe4U6Z/xL7uhUCi8hMz95CJOAgqFgoqKChYXFxkYGNg3o3NnUJVxV1v3nVAqlRQXF3Pr1i2/Aw5BECgsLKSnp8fnIFIikZCSkuIzvys+Pt6nbsKQkBDW1taO/NxJEtjtdvuRi/bq6qpPorJbW1soFAqfFqPd3V2Wlpb84kyOjY0RFBTkM9frTgwMDHifIwdBo9EcGVyZTCYaGxvJzMz0qxvRVzgcDjo7O5mYmKCiouLEVOADgdFoZGxsjMHBQXJycigqKkIilbhFQ3U6+MlPIDoa3vlOGBlh02Hmmyu/ZNWxzQdDaziv3nt9fv7zn+N0OnlLWhrS24GVNkGJNlHB8s1tXA7/+J3rJkfA/CqHw8Hk5CR1dXV0d3ej1+u5dOkSoiieuGffWcEzzzxj1Ov173vQ49gPZzKwAiovX74sezOnKg/D1NQUcXFx+9roXL9+/b7Y6AQKq8tOt2WSHHU8qn3kFO6EVCpFE6FE6lCg1Wqpra1lamoKc1sb1uFh/r63l/j4eJ588knvMSubI+jUEagU99b948MUGLVSr8WNP/B4aZWVlTE8PExPT8+Je9RJpVJKSkqw2Wz3yB94PNY0Gs2hQZUHOp2O/Px8Wlpa/J4LarWa1NRUn0U6wa3mvbq66lOAExwczM7OzpHjkslkSCSSIwO8k8pY+dqo4KswqD+k9aGhIdLT030ur2xvbzMzMxOQ3c3ExAQmk8mn8qEnuOro6LhH521tbY2WlhYKCwtPRFDybqytrVFXV0dwcDClpaUPLFtiNptpa2ujr6+PlJQUDAaDl1ckis431NgjI+E//xNEEefbHualgZcxOXf5SOgV0lT3Sm1ERETw9NNPUxAa6s1YgTtrZd9ysd7h+5wWRZF1k9MvftXd9jIeUdiKigpiY2NRqVQYDAafNjdvRrz73e+W6fX6Zx70OPbDmYxcoqKiPvTBD37w9HxKHiA8C9edLcweG53S0lLKy8sRRZGGhgZaWlpYXFw8U6XCXss0NtHBBc29GaX9sCPZRrarICM9w20iu7nJ2k9+QqvFQkNnJ5/97Ge9GQZRdLG2NXYPv8oDQRDIT9IwvmhlcyewoEitVlNeXo5Go6Gurs5vgu9REASB3NxcdDodTU1N3o63/v5+BEHwayENCQkhIyODlpYWv4PAmJgYnE6nz9wyQRBIT09ncHDQp8/HxsYyMzNz5Od84VmdVMZqd3fXp8Xbl4yVy+VieXnZJ1FMs9nMxsaGzzpXLpeL9vZ2CgoK/CZuz8/PMzs7y4ULF3zOQmg0GoqLi2lra/N2sM7Pz9Pd3U1ZWRlBQUF+jeEouFwu+vr66O/vp6SkhISEhAeSMbFYLHR2dnLr1i3i4uKoqKggIyOD5eVlL6dPFF1I7uzaT09n7ZXv4Jqd5T0f/lM+ri4jQbl/0HnlyhW+/U//hMTh8GasAP5/9t48vPG7vvd9/bTLiyxZkvd93+2xxx57xjPZaQNJIIStLAmBblDu5QDnKWnPuRcO5bTJ6YUnfWh7SimUUNL2QIDmwGVtmMQzY3vs8dge2+N9X2VL8qp9+d0/PFLssbV4Gc+E3vfz8GSQpZ9+kn7L+/v5vD/vd1y+EnWanOVLm4i+6Mj+ltOPxydGZbXgcDiCi/Dp6WkyMzO57777KC4u3tMGP4hFylsN6enpxMXFpQqCcM9ZMt2TxEoUxXc8+OCDd3s37ggCYthQCMTo3HfffRQWFmIymXjjjTcYGBg49Aj1ceK6fRyDLJ4sReQVv8PhwCZdB5+Ae82HQqGgrKwMqc9HXmUln/3sZ3n88ceDlYYN+yIer32PvmonqnNiEIEbUYrY94MgCOTl5VFbW0tfXx/Dw8PHSl4FQaCwsJDMzExaW1sZGhrC4XAcShSckpJCeno6169fP5B1hCAIVFdXMzQ0FLXXVkpKCpubm1G5uB+EWEVqvR5XxSoa4brH40EikUTUV5lMpqhzQQNBy9H+tiMjI6SkpByY0FitVkZGRg41sRcfHx+MUBodHWViYoKmpqZjj9La2Njg8uXLKBQKzp49e8c8sMLB7XYzMDBAR0cHSUlJNDc3B32ZAudmoO0tiv5d+YHzbgtfz9vgx//zc6TemCD1I5+AfexAFhYWmJ+fx3/rXJHuMLEWBIHk++Jxr/pY649uwfDmROD+x6XP5wvm1gYGX5qbm6mtrcVgMIQ89gwGA6urq/fU4vw48Z73vCdGKpU+erf343YcG7ESBEEqCEK3IAg/ufX/XxYEYVgQhH5BEL4lCEJUakVBEAqKiooUhwnefCtgYWEh6pXtzhgdnU4XjNGZmpq6IyLsSFjxrDPjNlMbkx/VTWR0dJS0ou0Vv8u8feEQpFIEhYJMo5EvfelLrK6u0traitVq3aGvCk2s9PEyMg0KeqfsR/aoCuStAbS2th44FiYSMjIyMBqNjI+PU1BQcOhVe05ODrGxsQwMDBzodQEi29PTE9V3FaioDQ0NRXyuUqlEpVJF1AVGo7NSKBTH0vqORrgerb4q2jbgxsYGDocj6lba6uoqZrOZwsLCyE/ega2tLXp7e6mvrz+0RUtCQgJxcXGMjY0daTv7QRRFxsbG6Onpoaam5kjH+2Hh8XgYHh6mtbUVjUbDhQsXSE1N3bMfaWlpWK1WHA7HLmI16VrmH1d+jWVxhb/858t8KSlpW3f1yU8yOTHBmTNnKCws5P3vfz9f/epXycvLw3JrcfGxT32KM2fOMDU1BYCmWIUqSbZdtQrjvRfAatDD6k3CfHu8zObmJpWVlZw7dy5qSw9BEDAYDKysrET1Hb7V8NRTT8WmpqY+E81zb/GQZUEQ+nc89peCIAwJgnBDEIQfHVf16zgrVp8Gds55vwyUAJWAGvjdaDaiUqkefvLJJ4+3Nn2PwGazIZfLD2y6J5VKSUtLC8boeDyeQ8foHAVd9gkkCLsmY0LB6XSyurpKWsm2N49r5U0i6JBI+MaPfoTFYqG2tpbKykrGxsYYmbiKUq4hRhVezFudo2Z53btvxM1BIZFIKC4upry8nGvXrjE5OXls36fVamV5eZmmpiauX79+JK1DaWkpbrc7aluEAJKTk1GpVFFH1xiNxmDUUiREI2IPtHnDLQQCN76jfu92uz2ih1U0+iqXy4XL5YrK32doaIjS0tKoSERAyH3QHD+Xy8W1a9eora09dIXJ7/cHKx0HIdvRwG6309raitvt5ty5cyfui+Tz+RgfHw9Wyi5cuEBmZmbI7zgQgzU+Po5f9CMIUkacC/yT+XUSZDF8rvAp2n7Zwp/OzPCPqanwjW/Q8cQTfOYzn2F0dBSdTsfLL7/M+fPnaXvtNQD+6Qc/4DOf+Qyf//znt99DIpB0IR7nspeN4cjDNtYtLwKgjZWFjJcpLS09VLxMeno68/PzB37dWwE1NTV4vd4aIboT6tvAb9/22K+AClEUq4AR4E+OY7+OhVgJgpABvAP4h8Bjoij+VLwFoAOIalzGaDS++6GHHnprumZGQKQ2YDRQq9UUFhYeOkbnsPCKPnrtk5So0veEKu+HiYkJcnNzkcdKkcVKcJrfLKcPrKzwx9/4BjduJcoHfHdE6Rp4dXR1dYWtHlVkxSCVQM8R2oG3IxCwGpiSOqrmx2az0dvbS0NDA4mJiTQ2NtLX1xd11t7tEASBmpoalpeXD3yRLC8vZ3JyMmqH+IBTdSQkJSVhNpsjthn0en1EUqlUKo8cDxRNKzCailW0gcuBFks0FTCAmzdvBquP0SLgL1VWVnZoLZTH46G9vR2tVktFRQXZ2dloNJoDV0BvhyiKTE9P09HRQUlJyXab/w6bfe6E3+9nenqalpYW/H4/58+fJzc3N6r2bVpa2q1j18uSXME/W1owyjV8zPAwqZrt6qPH4+FrycmsvP3tvH9ggPfeuiY99NBDLC0t8fjjjzPS0wOAJC6O97znPbz22mtBwqotV6PQSTG9sRmRxFq3vMQo4fq1jmOPl9HpdKyvrx/7sM69AIlEQklJiQSIKPoVRbEFsN722C9FUQzcnNqJkqdE3K/j2AjwIvDHwJ4r7K0W4EeAn0faiCAIgtfrrTyMWd5bAYuLi1G3ASPhMDE6R8GwcwGb37XHu2o/eDweTCZTcPRcaZDhWnlzf27cElTX1dUFH3O41nB51ijM3Ra7dnd309PTsy/BiVFKKEpT0TftwBdFmT1aSKVSKisrKSgooL29/dCrPK/Xy7Vr16ipqQlWUNRqNWfPnmVycpKJiYlDbTdgIDo+Pn4gywiZTEZVVVXUVQqdbtv0NRIZihSdEcBJ6awiua4Hqmbh7BhEUYx6ATQ4OEhpaWlU+7a8vIzdbj+QeWjAADQnJ4ekpKSoX7cTDoeDtrY2srOzyc9/89wtLi7G4XAcWtjscrno6OhgbW2N5ubmQ1lGHBaB36ilpSUYiVNYWHggt3tBEMjOzmZOoeZ6jIoMhYFnDQ8SK1Xi8/moqakhKSmJR972NoRvfIPLajXSP/xD+PnPuXnzJgCPPfYYEqcTURCQ3Ip7SkhICA5rCFKBpPPxOBY8bI3vv2jY2Nigr6+fkdl14uSeOxIvEzBwNplMx7K9ew2PP/54glKpfOgYNvUx4GfHsJ2jEytBEB4DlkVR7ArxlL8FWkRRvBTF5gpLS0slv4k2CxsbG6jV6jtijBdtjM5RcN02jkaipkAZOXZjenqarKys4MpRaZTtqlj1zs6SqtXuIpmrm1MAJGpyMRqNNDc3k5ycTEdHB/39/XuqGTW5MWw5/YwvHa3KsR8C77+0tMS1a9cOpP8JeFXl5eXtcfaWy+U0NjZitVoZGBg41O8il8upr6+nr69vz/h8OCQmJqLT6aJuJZaUlDA4OBhxH6NpB0ZTsTqOyUCXyxW2zW61WiNWl6KNmlpZWUGhUERVRQqIqWtqaqKuPATsORITEw/tL7WxsUF7eztlZWV7iGLA72xiYuLAcUyLi4u0traSk5NDdXX1gQjNUSCKIiaTiUuXLmG1WmlsbKS0tPTQ19QFvZMJQwZGr5+n9fejkmz/5lKplJ6eHubm5ujo6GBwfJxPpaRAZSW85z3MvvpqcMhIp1SCWo2w45618zfW1cQg10gwtbw5eBSIl2lpaWFwcBCXNBGHT8G5iqQ71kb9TW4HPvzwwwqj0fjuo2xDEIT/AnjZljAdGcfBYM4BTwiCMAX8K/CgIAjfBRAE4QuAEfhsNBtSqVQPPf744/fc6ORxYGFh4UTM8cLF6Bw2NmTda2PMtcip2Lzdo8n7wOfzMTs7u2tlrjLI8dn9eG3bpeieqSmqbjNStG5MIBFkJMRtPy4IAqmpqVy4cAGtVktbWxtDQ0PBqkNhqgq1QqD3EJ5W0UAul1NXV0daWhpXrlyJOmJmdHSUmJiYkDdDqVQarNRdv379UNM6arU6OD5/EDJSUlLCwsJCVIRMo9GgVqsjil7j4+PxeDxhjy25XI7f7w9bRT1qxSpAAMMRl2j0VdGI1kVRDE4CRoMbN25QXFx8IB+nkZGR4ATbYWCxWOjq6qKuri7kZ5bJZJw+fZqenp6o2rAej4fu7m7m5uY4e/ZsVFYUxwWLxcKVK1dYWFjg9OnTVFZWHtoXSxRFXt/o5xebPehsa1SY11BI9pJDrVbL/fffT3t7O3MbG3hffRX0ev56cpJHb/32qVotnlvE0uv1sr6+vou8S2QCxnPx2KbczPVuL9RaW1vx+Xw0NDRw5swZpte347rKMu+cz5dGo8Fmsx17J+NeQEVFBV6vtzpKndUeCILwDPAY8CHxmISHRyZWoij+iSiKGaIo5gAfAH4tiuKHBUH4XeC3gN8RRTGqu4fBYPiN1VctLy+f6IXo9hgduVxOZ2cn7e3tB47R6bZPIgK1MZHTAxYWFkhJSdm1ilUat//tXPGytbXFxNIS1be1RFc3pkiIy0B6m+lowNjzwoULqFQqLl++zNjYGAJ+KrJiGJx34DxAxM1BkZaWRlNTExMTE9y4cSPshclsNrOyskJZWVnYbQqCQHl5OVqtlvb29kNNeMbHx1NVVUVHR8eBHNZramr2mJeGQnFxcUgX+Z2Ixisn0nTgUStWbrc7YpXJYrGEbVn5fD6sVmvECT+TyURcXFxUQuL5+XkEQTjQomp6epq1tTWqqqoOpa1ZWFhgYGCAxsbGiBWQ2NhYysrKItp5mM1mrly5gsFg4PTp0wcewDks1tbWaGtrY2Jigurqak6dOnUkiwhRFPnlRg+/3uyjRp1DiXUWh+3NCeOVlZWgt53D4eDf//3fKS0t5YEHHuCV1lb4+c/xORx8a2kJLBayjUamby0+XnnlFR588MFdv9nW1hbLvu1KkWVoI2ilE4iXcbj9DMw6qMyOQSG7c52awP3gTqRO3G1IJBJKS0sFIPQ4eQgIgvDbwOeBJ0RRPLZV+p3suf0dkAy0CYLQIwjC/x3uyYIgCD6f71RGRsaJTbmdFBwOBzKZ7MTzsQII5GSdP3+e8vLyA8Xo+EWR6/YJ8pTJ6GSRbyRTU1Pk5OTsekxl2CZWLrOXuLg4pn74Q54+dSr4O/v9Pta2ptFpQk8bSiQScnJyuHDhAgAtLS0kq9bx+uDmzPHEoYSCSqXizJkzaDQaLl++vC9BcDqd9PX1UVtbG7X7dn5+Pjk5ObS2th6KVOj1egoLC+ns7IyaKGs0GtLS0qISp8fGxpKQkBDRZDTQZgh33hoMhrBGoUetWEUSrnu9Xvx+f9hzcGlpiZSUlLBkJlCtisY93+FwMDIyQlVVVcTnBmAymZidnaWuru5QpGp8fDwYHxOtZU1ycjIJCQmMjIzs+ZvP56O/v5+RkRHOnDkTdtruOLG5uUlnZ2dw6rK+vp74HV5Rh4Ff9PPjtWtc2RqiIbaQd+kaERBRKFTBivTi4iIPPPAAVVVV1NfX88gjj/DYY4/xwgsv8NWvfhXD+fN8Ji8P7doaPP44OqkUi8NBQUEBX/3qV3n++eeD8TJXrlyhr7cPsSsWaYyEsnfkB/WLAfRN2/H6oC7/eP3E9kNKSkrUQfFvJXg8Hu6///5ElUoVVmclCMK/AG1AsSAIc4IgfBz4ayAe+NUtnvJ3x7FPx9ocF0XxdeD1W/8+6LYLi4qKZOPj42xubhITE4PBYECv15OQkPCWzjpaXFwkJSWyNukkEIjRKS0tZXl5meHhYZxOJ+np6WRmZu5Z9U+4lljz2XhEUx1x26urq6hUqj0XdHmCFEEu4LxluaBNTESiVCK63QhKJRu2eXx+D4nxkW0cpFIpBQUFZGdnMzY2jlyipnNklVN5MXf0GBEEgZycHIxGI93d3ej1eoqLi5FIJIiiSHd3N+Xl5VHfzAJIS0tDqVTS3t5OXV3dgTUWaWlpOBwOuru7o3bjzs/PD3qHRdIcFRcX097evq8fUAByuZz4+HhWV1dDbk+v14fVd6lUqkO3qiGycD2azzozM0NlZWXY58zPz6PX6yP+zoGQ5IqKiqgXVGtrawwODtLU1HRg3ZIoigwMDOByuWhsbIya3AdQUlJCW1tb8JoLsL6+Tk9PDxkZGZSXl5/INdhutzM8PIzNZqO0tPTYRPE+0c+PVtu54ZjmfFwZD2u2q4F+0UeCJoHJyUmSk5Opqqqiu7t7z+vz8vJoa2sjNTUV26lTCH/2Z4jvfS+61VUefvFFRv/qr7BYLMzMzDAzM0Nqaiq1tbWstXpYtmyS8zta5PvE1XSN20nRyknV3flFd2JiIr29vYii+Ja+n7rdbsxmMxaLBavVikQiobKyUpaUlPRetgs6+0IUxd/Z5+Fv3ol9PBnVYRRQqVQPvetd71KfPn0aURSx2WxYLBbGx8eDwu+dROutJHBfWlqipqbmbu/GLgRidFJSUnC5XEFXX7VaTVZWFklJSUgkEq7bJ1ALCkrVkadQJyYmyMvb2y4UJAJKvQyX2csLL7yAsLzMh2JjEV0uUCqxbk4C28L1aCGTyZhxpuLxb5GgcNDS0kJxcTHJycl39KIRGxvLuXPnGBsb4/Lly9TU1LCyskJ8fPyhJ7f0en1QM1VRURFVjt1O5Ofn09/fz+DgYMQ2JLwpXO7o6KC5uTnsTVylUmE0GpmdnQ2rPQqI2EORF4VCgc/nw+v17vt+R/3NIlWsIumrHA4Hfr8/bHvP7/czNjZGU1NTxP2ZmpoiLi4uauNQm81Gd3c3DQ0NB26z+Xw+uru7iYmJOVDUzU5IJBJOnTrF1atXOXv2LNPT05hMJmpra49cKYoGTqeT0dFRVldXKS4uPrLFwE54RB/ft15hyDnPw5pqLsS/eY6IoohCqcK27mdrayvs79/Z2cnKygqPPfYYPPUU4gsvoP7jP8b19a/zhlJJQkIC2dnZJCYmIggCtlk3yy1WdKdiSCjdS8QXrW4WVz28o+5kCgeCIKDVasMugO5FuFyuXURKJpOh1+tJTk6mtLQUmUyG3+/nk5/8ZLkgCMJx6aSOgnuGWO3UVwmCENQwZGdnI4oidrsdi8XC5OQk6+vrqFQq9Ho9BoMBrVZ7zxItj8eDx+M59uiI40RgwiU/P5+1tTVmZmYYHBwkITmRwYQ56mMLkAnh/WmcTidbW1shT1iVUYZ9zs03vvENKvPy+FBjI36nE6lGw+rGJEqFBrUy+pP99f5Nrgxt0VAYyzvq0nA60xkeHmZsbIzi4uI7EiobQEBUnJSUxLVr1/B6vRw1gik+Pp7GxkY6OjrIz88/sN9ZeXk5XV1dTE5OkpsbmaDGxMSQm5vLwMAA1dXhq5GFhYVcuXKF9PT0kD5FBoOB/v7+kMQJtm0cVldXQ/42crkcj8dzqJa5w+FAqw0992KxWHbZDdyOmZmZoD1IuOekpKREJD5bW1vMzMzQ3Nwcfqdvwe1209nZSU1NzYEjYDweDx0dHaSlpUX1u4dDYOji4sWL5OTkcO7cuTt+XfV4PIyNjWEymSgsLKSiouJYSYbL7+FfrJeYcJl4LOE0DXG7hwFE0YdEkJKTk8PU1FTYYOsf//jHSKVSHnnkEebm5thQqykVBBRm854Fit/tZ+aHVuQaKemP7j852jVhRyaBqpyTuzekpqaytLR0TxMrp9MZJFKrq6vI5XL0ej1paWmUl5fvew0K6KyWlpYKgNGT3+vduCeIlSAIQkpKSmV5eXmovxMbG0tsbGxw1exwODCbzUxPT3Pjxg0UCsUuonWSRnXhcNKi9aNCq9Wi1Wrx+Xz0LY3hw8/WlJkp7RTp6ekhb3ozMzPk5OSEvCgqDTJmOhcZHx/nmSefBMB/S1dk3ZgkMT436gvq5cFNLvZvcio3hrffWu2p1WpqamrY2tpiaGiI0dFRSktL91geHCfi4+ORSqVotVo6Ojqoqak5EoFWqVQ0NTVx7do1nE5nWCJwOwJVqPb2dlQqVVR+aVlZWSwtLWEymcIeowqFgrS0NKanp/etSAbePzU1lcXFxZATkQGdVShipVarsdvthzLCDFex8vl8+Hy+kOJ2URRZXFwMS4R8Ph+Tk5MRyZLf76enp4eqqqqorkE+n4+Ojo5DHasOh4OOjg6KioqO7I8niiJTU1PMzc2h0WjQaDR3lFR5vV4mJiaYn58nLy+PCxcuHPv7Ofxuvmt5gzm3hXfrGvdNjNiOtBFISUlheHg45MJAFEVeffVVqqur6evrI10up+S//3d8Gg3CX/zFntcs/GoDt8VH/kcNSFV7P5fHK3Jjyk5Zphq14uSKAkajkeHh4agq2yeFwL3cYrGwtrYWvJdnZGRQUVER9b38iSee0La2tj7M/0+sgigqLy8XDnJiqdVqMjMzgxdxh8OBxWJhbm6Ovr6+IMs1GAzodLq7RrSWlpZC3ozuZUilUqrSCvnV0iDuNCWe9e0Ynfj4eLKySeLeFwAAIABJREFUsnYFf4qiyMLCQtibjsoo4+ZCHwCnT52CoSFElwuXZwubc4Xs1HNR7VfH6Ba/7NmgIkvNOxu0SG4jY3FxcZw+fZr19XUGBwcDzrx3xB9mdHSU1NRUioqKsFgsdHR0kJeXdySBr1wu58yZM/T09NDX13egFbxUKqWhoYHW1laUSmXEVWnAzb21tRWdThd2qi4/P59Lly6RlZUVsiKVmZlJb29vSGKl1+uZnJwM+R4BAfthiJXT6Qw5fm+1WsOSFqvVikajCdsSnZycJDMzM2I1bWxsLHjNiQRRFOnq6iIzM/PAi6+NjQ26urqorq4+cvXB6XTS09NDbGwszc3N+P3+4ATgceYJwjbxnJqaCnrdXbhw4Y5cm7d8Tr5juciKZ4P3J56jTL3/MSneirSRSCT7LgycTidzc3Pbgct+P48++ij3nzuH8La3Ia6uYv3IR9Dc1mLeHHNiuWrD0BRLXN7+1c2bcw6cHpHavJMNqZbJZKhUKmw2210JyIbtRZDZbMZsNu/qPmVlZVFVVXVogv3QQw8pjEbjk8D/PN49PjjuCWKlUCjue8c73nEk/yq1Wk1GRkawnO90OrFYLMHRY6lUuotonYSpnSiKbGxshG1R3MuQCBLK1Zlcs43xnvyzFBQUsLq6yszMDP39/aSmppKVlRW8GYb7TpVGOTcXewGoa2jAMzSE3+lkY+OWvio+J+L+dE/Y+Mm1dYrTVTzVpEMiCU04EhISaGxsxGKx0NfXh1qtpri4+NguJhsbG5hMpiCZ1Ov1nDt3joGBAZaWlqiurj70SHpA7zI0NBTMiIv25iOXy2loaKC9vZ3Tp09H1McolUpKSkro7e3l9OnTIUmcTCYjKyuLiYkJioqK9n1ObGxssG2/X/VIqVTi8Xjw+Xz7fp5AxeowEEUx5AU5kr4qkneVx+NhdnY2OJEaCmtra5hMpmCwd6T97evrQ6PRHMiNHbYtAQYGBqivrz9UdtxOzM/PMzIyQnl5+S6NYHFxMf39/dTW1h5p+wGIosjs7CwTExOkpqbS3Nx8x6ak1702XrJcZN1n54P6CxSqQlfzRNGPcGs4Pisri+7ubtLT0zGZTMzMzOB2u8nIyKCpqYm+vr7t4/Yzn4E33sD7la/gWVuDHdc9r8PP7L+tojTISH049AKha9yGLk5KTvLJuwslJSWxvLx85NZxNNiplzabzUG9tF6vJzc391j10uXl5Xi93vDTJyeEe4JYGY3GhxsbG4/1CFOpVKSnpwe1Ki6XC4vFwtLSEjdv3kQikQSJVmJi4h0hWpubm8THx7+lJzAq1Nm020YYcs5TE5NLYmIiiYmJeL1eFhcX6e7uZnNzk+zs7LD6GmWiDKfHQUVBJfqUFJYAv9OJddOEgARtfPibS/+Mg3/rWCMvWcn7ziUiDUOqdkKv13P27FlWVlbo6upCq9VSVFR0aHNBeNMV+/bVlVwup6amhqWlJVpbWyktLT30NKggCJSWljI1NUV7ezv19fVRVw/UajV1dXV0dXXR2NgY8bMGdBdzc3NhXb5zcnJoaWkhJycn5L4EPK1C2REEdFb7EZ2YmJhDxW54PJ6w56/FYgl5EwmYOoYbLhkfHyc3NzcsufX5fPT29kZttzE2NobP54vKtmEn5ubmmJycjOp3DQe3201f33YFeT+Sk5qaytzcXMQ2cSQE2qyjo6MYDAbOnj177FWwnbB4N3nJfBGH383T+gfIVobWWoqiiIgf4ZbpsdfrxWazcfHixaAwek+l+7vfhRdfhE9/Gt873wkvvYSw47iY/3/X8Gz5Kfw9PRL5/tco66aXqWU3D1Vp9lTcTwJGo5HBwcE7QqxEUWRraytIpHZO+Ofn59/RCX+JREJ6erpEEIRkURTvan7PPUGsfD5fbSQB7VGhVCpJS0sLGvW53W4sFgvLy8tBT5+dROs4VlPLy8t3VER9EshU6NFKY+mzz+zSKARidFJSUrh0aTut6NKlS+h0OrKysvb4tUjkAv/pyed4Lu3/QnKrkiM6naxuTKKJS0cmDV3dGZ538EqrlUy9gg9eSEQuPdiJKQgCSUlJGI1GFhcXaW9vJykpiYKCgkNd5Kenp4NatP2QkpKCTqejt7eXpaUlysvLD3085eTkoFKpaGtro76+PmoNl0ajoby8nI6ODs6ePRtx4VBRURFs/4SyEpBKpeTl5TE2NhZSo5GWlsalS5coKira9wIa0FmFIlaHqViFs1rw+Xx4PJ6Q1cOFhYWwVhIul4ulpaWI1arBwUEyMzOjmqCbm5vDYrHQ0NBwoIibsbExLBbLoewYdmJ5eZmBgQGKiopCDkkIgkBlZSVXr17FYDAcuF0niiIrKysMDw8HQ9YPakVyUJg8a7xkvogfP88aHiRNEb5FKt6Ktl1fW6elpSV4j5BIJPsf393deD/2MS4DKR//ODm3Qo0DxGqt38HaDQfJD8QTkx76unJ9woYgwKncuzPQFBcXh81mOxbbBVEU2dzc3EWk4uLiMBgMFBYWotFoTrSwcP78eWVXV1cd8NMTe9N9cNeJlSAIitzc3PiTnppTKBSkpqYGRZ8ejwer1YrZbGZkZARRFElMTESv16PX6w91A15ZWYk4cXWvQxAEKtRZtG4NYfe5iLmNAM3Pz5OZmUlhYSElJSWYzWYmJye5ceMG6enpZGRkBC+oSqMMt9mLIJeDTIbP6WB1c4rMpPqQ7z++5OR/XbaSopPz4fv0R3InDjhgp6SkMDc3x5UrV0hLSyM/Pz/qG1Ug5yuSiFmpVFJfX8/s7CxXrlyhsrLy0J48KSkpKBQKrl69Sm1tbdQaJKPRiMvl4tq1azQ0NIStpMjlcioqKuju7qapqSnkxTAzM5OWlhby8vL2rZjIZDK0Wm1I8qTX65ment5324d1Xw8nXF9bWwurd5qdnQ3b7hodHaWgoCDsdxdocYQavtmJlZUVJicnaWpqiroFEmgbBmJQDts68Xq93Lx5E7vdTlNTU8SKV0BeEZi0jRZWq5XBwUFUKhW1tbUnouWZd1v4jvl1ZIKUjxkeJkke+hwJkL7p6WkEUcGaY5QL9U8Qo47H5/PR0tJCaWnp7nPAbIYnn0QwGnnGYuG3vvY1/uozn9n+m0yGZ9PH3E/WUKfJSb4Qmlz7/CLdk3YKU5VoYu6O7lcQBBISEiKeG/shIG8JiM1tNluQSBUXF9/1Ds25c+cSvvOd7zTzH51YAeU1NTV3vVcml8tJTk4Olr09Hg+rq6uYzWbGxsbw+/27iFYk/YzP58Plct3TNgvRolKdxeWtQW46Zzkduzs1YH5+PnhjCsQmGI1GPB4P8/PzdHV1IZPJmJqa4s//2/N8+dGvUeRPQqJSseU241U5QzquT6+4+OcWK4nxMp6+X4/qmKZnJBIJWVlZpKenMz09HRRl5+TkRFyZ37x5k6KioqgqUIIgBIX+3d3daLVaSkpKDiXWTUxMpL6+nmvXrlFWVha1Z1ZGRgYOh4Pe3t6IIcAGg4GlpSUmJydDDlxIJBIKCwvDOopnZWUxPT29L7FSqVS43W78fv8eghAwWw1AFEW8Xm8wssfv92O325FIJMjl8uD3GI5Ymc3mkITWZrMFJ0r3Q2AgJhxh8ng89Pf3c+bMmYg3lPX19WDUTLRE3ufz0dXVhUajobi4+NA3rdXVVXp7e8nJyaGysjLq7eTl5XHp0iUyMjIiEqSNjQ0GBwcBqKysvGOBwrdjyrXMy5Y3iJEoecbwIIkhEiICNhgmk4nExEQKCgrI8H2Mqzf/jsHpH1Jb/DRSqRSdTrd7YeD1wgc+AEtLSC9d4tFvfpNvf/vb/MkHP4gCQCJh9tVV/G4/WU8ZEMJU1McWnWw6/Lyj7u4IxwNISkpiZWUlIrESRZH19fUgkbLb7Wg0GvR6PaWlpcTFxd1TUpe6ujpiYmLuu9v7cdeJlUwmO33hwoV7Tt0tl8tJSkoK3sC8Xm+QaE1MTOD1encRrdtXf6urq3d01P8kkSLXoZfG0+eY2UWsAtWF/W5MgRidnJwcVlZW+KNPfoqR6SH0aiPW+TUkSiVWcTtjaz/H9QWrm+++YUETI+WZBwzEKI9/dRdobQVE2YFKTGZm5r5VgfX1dWw224GrkDExMZw9e5aJiYmgqehhJt/i4uJoamqio6MDl8sVVg+1EwUFBfT19UUVHFxaWsrly5cxGo0h21ppaWmMj4+HJDSJiYn09fWF9KQKmBTq9Xrcbjdra2tsbm5is9mw2+1cvHgxeLGWy+VBEuJwOOjr68Pv9+PxeIIxPk6nk/j4eBwORzCGJ7BytlgsIcXhkUTrw8PDIVuaAfT19VFQUBCxzWW327l+/Tr19fVRa6PcbjcdHR1kZmYeWOAegN/vZ2RkBLPZzOnTpw8sdpdIJJSXlzMwMEBDQ8O+z9na2mJ4eBiXy0VJScmJeiSNOBf4V8tldLJYnjE8gEa6+3j0er3Mz88zNzeHRCIhMzOT4uLiHYsbHSXZjzE0/RN08dnkpd8fjGgKEqs//VN47TX41regvp7PabX8/d//PV9/+WX+j9RU1odgc8RF2tsTUBnDL7i6xu3EKiUUp9+5wOVoYDAY6Orq2jOI4vf7dxEph8OBRqPBYDBQUVFBTMydTbg4KnJycvD5fHdelR8Bd51YJScnP1xfX393QvQOAJlMFqzGwPZKMkC0pqam8Hg86HS6INFaXl4+tBP3vQZBEKiIyaJl8yabPgfx0u2byMLCQsRwWfeWh4+/9w+43t3F8+/+GwxVGibH+zBubWHGjlwWQ6x69/dkWvPw0kUzaoWEjz6gJ159Z0vmMpmMoqIicnJyGBsbo6WlhcLCQtLS0nZZSgwMDBw62kMQBPLz8zEajfT09JCamkpBQcGBt6VUKoNeVw6Hg8LCwojbCOhlOjs7mZ6eDnuTlkqlVFdX09PTE9IgUhCEYEDzfm20QMt1YWFhz3s5HI6g+F8QhGDrMD4+nvT0dBwOx/6iYeD111/nzJkzex7v6OggKysrKJw1mUxsbW0hk8nY2tpic3MThUKx67OIosjS0lLICcfA68KR6MXFRXw+X0Qz14ABaHV1ddTExmaz0dnZSWlp6aHF45ubm/T09JCcnMy5c+cOfUM0GAyMj4/vCbEOZCFubGxQUlJy4nrSfscMP7C2kSRP4Gn9A8TekimIohiMl9nY2AjGy4Qiv8VZv83a1gx9E6+gicvAYNhOMvD7/UheeQX+8i/hE5+AZ58Ftg1z3/Wud/GDX/6SP3z6k1hbvMTlKjE0hK9CbTp8jCw4aSqOi3r45k5BpVLh9Xpxu91sbW0FiZTL5SIhIQG9Xk9VVdVbruNyy5NMKghCkiiKy3drP+46sfL5fHX3WtxLNJBKpRgMhuCqxufzsba2htlsZmZmBqvVSmpqKl6vN6wg+K2CSnU2b2wOcNMxy5m47ZvRwsJCyFWs1+HH3LrFc1/8PD++/CP+5MNf5NNf/T1Ym8Lyo1am8ldZTbCj9ObR2dkZjNFZtfl56aIZmVTgow8YSIg9uUNUoVBQVlZGXl4eIyMjjI+PB+M1lpeXUSqVR7bO0Gg0NDc3Mzw8zJUrVzh16tSBNSgymYyGhgZu3LgRnE6MhlzV1dXR1taGSqUKe7PWarUkJyczMjISssKVlJTE2NhYcPL1dmRmZtLV1UVWVhbr6+vMz89jNpuRy+UkJiayublJc3PzHuK2tLSE0+k8UBvJ6XRiNBr3tFhNJhPj4+MsLCzQ399PbGwsKSkppKamBmM9QrVlh4aGKCkpCStqHxoaikhYfD4fnZ2dFBUVRV3JWVtbo7u7m5qamkNVvUVRZGJigrm5uUNXR29HWVkZPT09NDc343a7GR0dxWKxUFRUFNXxd9y4bpvg1bUOMhUGPqy/gEqiwOFwMDMzw+Li4p54mXAQBAl1xc/wRvcLdN78BvfX/gkGg4HVlhb0zz4LZ89uTwLuwNe+9jWko2NYfh0LAmQ+qUWIQJZ6Ju34xZMJXA6Fnfcpl8tFS0tLMCqupqbmLX+fAmhublZ2d3fXAT+7W/twV4mVIAjy7Oxszd0yKjtOBHyy9Ho9Pp+PS5cukZubi8VioaenB6fTSUJCQvAgvtdLqrcjSZ5AsiyBPsc0Z+KKsNlsyGSyPVozn9PPStsWK21buO0eZu2T/MHHPsGXv/5f2Hz9dSwdFxmvdWCLcVKY+TZKcx5nc2Nb+9DVN0bfejaiIOV3HzaSGH93Dk+VSkVVVRV2uz3o4u5yuTh79uyxbP9W/AJWq5XOzk5ycnLIzs4+0PEgkUiorq5mZGSEjo4O6urqIup2dhqIKhSKsDftgoICWltbQ7a0BUGgpKSEwcHBkOTa5XJx8eJF4uPjycjIoLi4OLiPS0tL+77mMJOBfr9/X4K0vr4eNBEOVLMWFha4cuUKbreb/Pz8fSej1tfXcbvdISswgYDlsrKysEMtgXDutLS0qJ3Rl5eXuXnzJg0NDYcSfQcCuRMSEmhubj428834+Hji4uK4du0aNpuN/Pz8YPV2dnaWp59+mqWlJSQSCb//+7/Ppz/9aaxWK+9///uZmpoiJyeH733ve+h0OkRR5NOf/jQ//elPiYmJ4dvf/vaB/LLatob52fp18pUpvF97FvPCMjMzM4iiSGZmZsT8y/0gl6lpKPsDWnr+Bx03/56K+HcR9+EPQ0ICvPIK3PY7p6enM/f6Km4xgfSHVCi04d9PFEWuT9jJMiowaE6uQePz+bBarVgsFiwWy67OSlFRES6X68CWH/c6mpubE15++eVz/EclVkDZW31qbj+sr6+j1WqDnk+FhYXB3nXAsHJn71qv1xMbG3vPE62KmGxe27jBmteGeXFxVxvQ5/Jjbrex0rqJzyGiKVGS8qCRX3zxJ/g3N7G89BIrm6NMnHWAXEpD8e+TZtiuVCYkJGBIL+anoxb8+DltWGToxji2zMywMTp3GoFQ29HRUaanp+nt7aW0tPRYKgCwrUVqbm7m5s2bdHR0UF1dfSBvokBLbnp6Ouh1FWmoQqFQ0NDQwNWrV8PevCUSCTU1NVy7do3z58/ve4PW6/XB4NwA+VpdXWV8fByHw4Fer0cqlVJZudezLzCVdHsVJyYmBovFEu1XgM/nC2sMGqiGC4JAfHw8xcXF5OTkcPnyZba2tnjjjTfIysra5Sg/ODhIaWlpyPecmZmJWPUDGBgYCGYyRoOZmRlmZmZoamo6sLmsKIrMzc0xPj5+qCDvcAjE+VitVnw+Hw899NCu40Emk/GVr3yF2tpaNjc3qaur45FHHuHb3/42Dz30EM899xzPP/88zz//PC+88AI/+9nPGB0dZXR0lKtXr/KJT3yCq1evRvUZ39gc4NebfRRIk6mY19LW10pKSgrV1dVHnj7UxKZSW/w0HX1fR/af3ofcZML/+utI9iHFDpOHvo4tPvndt/N86fO8v+mDYbc9veLGsunlQtmdlRN7vd5dRMrn86HT6TAYDOTm5u46rgIk/DcNtwTs99/NfbirxEomk52+77777jnh+lFhsVj23DAkEgk6nQ6dTkdBQUFw2sJisTAwMIDdbic+Pj5ItO61aQvYng58beMG/Y4ZWLJQX1+Pz+XH0mFj+coWPrsfTbGKqfgBPvnCn/DKA6+gm7Jh/cErzKeuMl+7iSY2jYay3yduh65qatnFyy0WVHIJH384CYMmHafTGbQq2C9G56QgiiLz8/M0NzfjcDi4efMmcrmckpKSI7tew/ZNqaqqiuXlZdra2iguLo6oW7sd2dnZqNXqoNdVpBtMTEwMp06dorOzM+xNPBCCfvPmzX3JERCsWuXn5zM6OopcLqegoACdToff76elpWXfqpBer9/3PDmo5UIoDyu/34/T6dz3bwHtV0FBAR6PJzgZmpycjF6vD56r+8Fut0dltzE+Po7L5YqqEiOKIiMjI6ytrR1oYjAAl8vFjRs3kMlknDt37tgWIn6/n5mZGSYnJ8nIyOC+++5jaGiIxcXFXYHVO21r4uPjKS0tZX5+nldffZXXX38dgGeeeYb777+fF154gVdffZWnn34aQRBobGxkbW2NxcXFiFW9X6xep9UxgsIrIWbdjy1ZSlJhPlKJjGVhC5nbgVyQIkO6/d9b/5MLUiRCdBPFaYZTnPuBlYSWXsae+zgJRUXcXrf0e0VmfrBKamISYOcrL77I+37nd8Jem66P21DKBMqzjrfVFrAJChCpndPreXl5YQm6Wq3G5XIdi5/VvYS8vDy8Xu9dzZG7q8QqJSXl4YaGhnteuH5QWK3WsCnpsL2CDphMBloSGxsbWCwWBgcHg/4gAdPSu+0PApAoiydNnkiffYpKn4b1a25WLlvx2vzEFypJeVDDnG2K9559NzqdDseVK7gHe5k85WJNs0VmUgPVhR9EJn2zrD407+B7V6xoY2U8c78+qKlSqVQUFhaGjNE5KVHl3NwcRqMRlUoVDEk2m8309PQQFxdHcXHxsegSkpKS0Gq13Lhxg8XFRaqqqg50g0xKSkKhUATDoCNpc7RaLWVlZXR0dIQ1nMzJyeHq1ashhzECC4SxsbE94uxAe3y/IHKDwcCNGzcoLCzc9fhBW4GhJhMDVeP9MDc3R339tndagAjm5eUxOztLZ2dnyBSBQGuvqqoqLPmZn5/HZDLR2NgY8Zz1+/1BIf9BDEMDWFpaYnBwkJKSkiMHMQcQWEyMjY2RnJy8y5m9sLCQtrY20tPT993Xqakpuru7OXPmDCaTKbhPqampLC9va4kD3ncBZGRkMD8/v+/++/1+TCYT0zPT9CTNggLcMj83ElbAtwKr0X0mKZJbREuCXJAFCVeQfN0iY1k/uUTT33yf4fed598/WESCtZVsVWHwuXJBitAiR1wSkJ5a4AOPnOP5//W/+fHFn3PhwoVd25XeInNOt5+BWSfVOeoj+fDBNpEKkKhAZTcxMRGDwXAow2ONRsPGxsaxVeHvBewQsBtEUTTfjX24q8TqrSpcD4dwWWnhEDBtS0hIIC8vb5ej7cjICJubm8TGxgaJ1kk72gZQKctivGOZuOtZLDo3iMvfJlSxmQqWl5d59NFHEYDvPvss3snrDDc78cg8VOd/gJzU87v2uWfSzr9dXSVFJ+cj9+uJ3cdSQRCEPTE6PT09iKJIVlYWqampdyz3URRFxsfHaWpq2vW4wWDg3LlzmEwmOjo6SExMpKio6NDZgAEoFApOnz4dNC8tLy8/0KSVVquloaEh6mmypKQknE4nXV1d1NfXh5wArKmpoa2tDZ1OF7zBOp1O+vv78Xq9VFdXMz4+vm+lLCsri9HR0T37EhMTE5wQ3HlMyGQyfLccraNBqIpVKP+qjY0NFArFnparRCJBrVaTmppKTExM0D1+52To+Pg4Op0urAjdYrEEj5lIRp5er5dr164F5QIHOZ+9Xi/9/f1B7d9Rjz3YPt5NJhPDw8Po9fp9q5lKpRKDwcDCwsKeacitrS2eeuopXnzxxbDDBzu9ygK4/bNvbGwwMzPDysoKRqORstIyGuLP4BG9eEUfXtGHR/ThZfu/nluPeXf8e/d/vbufw+6/O0U38UOT1P3Rl1ioLeRHz/8hDrmISbAzstEb3K9EUzz3t9UwXbxEV8MsVD5JzK8u8p+f/698oPg/7/oMEgRkghQWUvH4chnVdfO3y64dFTXZrf+GIHuClBhRgXFTGaxKSSSSIJGK1k8vHBITE7FYLL9RxAq2Bew9PT11wC/uxvvfNWIlCII0KytLexztlHsJW1tbx6KXEgQBjUaDRqMhNzc3GGYZMCzd2NggJiYmSLTuZAYTbJe/rV02EloSqN7U4MpwUfZb6cRlb194bTYbjz/+OIsLC3zvY8+iNG4yWLyJSpnA+dL/E50mZ9f22oa3+Nn1dXKTlXzwfCJKeeSVXCBGJzMzE7vdzszMTNgYnaNiaWmJxMTEfW9at1ZFJCcnMz8/T1tbG8nJyRQUFBz5YpeRkYFer6enp4elpSXKysqiFiHHxsbS1NREZ2cnTqczov9RVlZW0B8q1HSXSqWiqKiIGzduUFtby/T0NFNTU5SUlASzEJeWljCZTHuyERMSErDb7bjd7j2r6YSEhH0rS4Ig7Gsguh/sdvu+1TmLxbKvgWko7ypRFBkeHg46hWdmZnLz5k1mZmaoqqrC5/OxsLAQtgW4sbFBX18fZ86ciXgMuFwuOjo6yMnJidqPbOdn6+vrC3quHccxbzabGRoaIi4uLmL8TH5+Pp2dnbtIp8fj4amnnuJDH/oQ7373uwFITk4OtvgWFxeDFc+MjAxmZ2eD25ubmyMtLQ232838/Dyzs7MolUqysrIoKyvbdRwoBTlK7kCTY30dfu/TEKsh7dVf81xGButbc1y8/gJxcVmcqfokXg8sfH8Dv0bk1BNZ5F2fxza5xMYffpy//fMXqTbpySjK2UPsek06JHFuMhKVeJEFyaHL7wz+e+drfLeidgJ4fKOU7KQ0SkpKjn0RmZiYyOjoaEhD4Lcqzp07l/Dyyy+f5T8asQIyc3Nz9y5d3uIIjHEfNwRBIC4ujri4OHJycoKVsYBh6fr6ejA1XK/Xo9VqjyU13O8VsXbbWX5jE8+Gj5hsOS1NPTgKvTQkv3kyrlos2FZW+Nq7nkD3iJapxDWSdKXUlTyLUv4meRZFkV/3bfLGwCalGSrec/bg2X+wXfEoKSmhuLg4bIzOYRGoVp06dSrs8wRBICMjg7S0NGZmZrh8+TIZGRnk5uYe6SKoVqtpbGxkamqKy5cvU11dHbXVQ8DrqqurC4fDEdGxu6ioiN7eXkZHR0P6OqWnpzM3NxcMqL198qqkpITOzk6Sk5N3vVfg+5mbm9tz8dbr9ZjN5j2fK6CzikaMbLfb91RORFHE4XDsqRr7/X5WVlb2zYELjOgH3lOhUFBTU4PFYqGzsxO3282ZM2dCnlMOh4Ouri7q6uoiHntbW1sHdtCHbRH58PAwq6urNDQ0HEs7fG1tjcHBQeTTL6MpAAAgAElEQVRyOdXV1VFlHarVauLj41lZWSEpKQlRFPn4xz9OaWkpn/3sZ4PPe+KJJ3jppZd47rnneOmll3jnO98ZfPyv//qv+cAHPkB7ezsxMTHMz88zMjJCRkYGZ86cOZYKXNTw++EjH4GJiW0j0Fv6sYS4DHKN72By5X8zMfUT9EO/hdfqJ/9ZA3HxStY2BBwmN1/8T3/K/TVneWfVg3vO+aVVD20byzxam0CTfu8Qg9PpDObsra6ubtuR6BPZ1In8xNvL6ZgC6tPvXFdHo9Gwubl5x7Z/t1BSUkJ8fHzd3Xr/u0msiqqqqk7w7DkZrK2tHVh8fBgIgkBsbCyxsbHBqkSAaAUm2FQqVbCidVCiJfpErD12TG9s4lnzEZOpIPNJLY74DXRrcqa9FpY96xhlGrzr6yh/9St+8LH3M3PWz4psjeKst1OS/fZgcjyAXxT5adc6HaM2avNieLxee2SjvNtjdBYWFoIxOllZWSQnJx9q5NxqtaJSqaKeNJJIJMHqw+TkJJcuXQraKByW4AqCQG5uLkajke7ubpKSkigsLIxqe1KplPr6evr6+ujp6aG6ujrk6wRBoKqqis7OzpAVnfn5eWw2Gz6fb99sRbVajU6nY35+fpewGbYrFFevXt1DrAwGA/39/RQU7I5JOgix2q8VuL6+vm9rw2QyYTQa93wPAfF4Y2PjntcEzp/V1VWGhoaoqanZc9P3eDx0dHREFeNitVrp7e09UOYjbFfDenp6SEtL4+zZs0euUm1ubjI4OIjf76esrOzAraCAm39SUhJXrlzhn/7pn6isrAxOYf75n/85zz33HO973/v45je/SVZWFt///vcBePvb386rr75KdnY2MpmML3/5y+Tn56PVau+OjvTP/gx+/GP42tfgtrDtkrwHWFwZYalvBrptGJpiicu9ZUTq9SJIpRiNRt773vfuu+muCRtSCVTnbB+jgZgks9nM2toacrkcg8FAeno6FRUVSKVSbD4Xf7v8MwwyDb+dEH5hd1QIgoBcLt+3ovxWxq3BlP1XiSeAu0as1Gp1WVVV1cmESZ0g1tfXw45q30nExMQER8dh+yQOGJbeuHEjeBLr9Xp0Ot2+hEP0iazesGN6fRP3qo+YDDmZT2iJy1due9bcnKBam0uvaKLPMU37l7/L1V/8gi99/FHmLjgRZDIaSz5JSuJu8b7XJ/Kj9lX6ZhycK4njbTXHrxGTy+VkZ2eTnZ3N5uYmMzMzQb1IVlbWgcw9w+XlhYNUKqWgoIDs7GzGx8dpaWkhPz+fjIyMQ3/euLg4zp07x+joKFeuXKGmpiaqykLAcX1sbIyOjg5Onz4dsoomkUh2GYgGKik+n4++vj68Xi/nz59ndXWVnp6efbPxioqKaGtrIy0tbXf7RqlEpVLtITwBofrtOquDCNi9Xu+etlsofdXMzMy+5+bs7GxwQOF2WK1W1tfXaW5uxmQy0draSlVVVXD7fr+fzs5OCgoKIlocLC0tMTQ0xJkzZ6KuNomiyNjYGIuLi9TU1Bw5fy/gzeZwOCgpKTl0MHhgmCZg9LqfbgrgtddeC/47MIE5OzvLs88+yxe+8AVSUlKOzWvrUPjJT+CLX4Snn4Y/+qM9f1Yqlajd1WgG03HHmlGf8QHb1xHR54Nb55MoivzFX/wFSqWSz33ucwB4fCK9k3ayE/0M37zB+vo6CoUCg8FAZmYmVVVV+5L8V9euYve7+LD+PhSSO3+LDrTkT9o5/04iLi4OiURy1/jFXSNWer3+dHFx8W/OjCdvhsbeLd+l26FWq4OaJHiz7Dw/P09/fz9yuTzYOtRpdWzedLN0cQO31Yc6TU7uO7TEFyp33fTMZjNNhU3krhn5x2/9Ay//5dd429lyJqrW0cVl0VD6e8Sqd99g3F4//3rZytiii0eqNZwvi0wKjor4+HjKy8spLS1lZWWF0dFR7HY7GRkZZGRkhG01OBwOHA7HkVq6AUuG3NxcRkdHmZiYoKioiJSUlEMRLIlEQnFxMcnJyVy/fp3MzExyc3OjclwvLCxEpVIF7RhCeWUFHN3b2tqCZCigpQm8V1JSEktLS0xPT5OTk7Pr9UqlkuTkZGZmZvb8LSsri5mZmV22DQEd4e1TSWq1Oqr2hN/v3/fzWyyWPVO5LpcLt9u9h5j4fD4mJib2NX/1er3cuHEjOK2XkpJCQkIC165dIzs7m8zMTLq7u0lOTo4YazM1NcX8/Dxnz56NujJgs9no6ekJ+p0dpbXvdDqDlg6BNIGjLmxyc3OZnJwMGcYNe+Nl0tLSomqXnghGRuBDH4LaWvi7v4MQ34duKgvRLWfj7E/oHDVz/6nPo1TEI/p8CLdIoSAIdHV1cfHiRR599NFtuxizE6cnmwyNh+zs7Ki6Btfs4ww55/nthFOkKk4ma1ar1bK2tvYbRawADAaDIAhCoiiK1pN+77vZCiwLped4q2Jra+tYvI3uFFQqFenp6cGbgMvlwmKxsLi4yOhrs8TeTEZI8KF7h4LUWt0eguh2u5FIJEgcDlb/8Vf8y3/9Wypqcvjd/3aO3LRmqgreh1Sy+zV2l5+XWyzMWdy8s0FLXf7JuuxLJBKSk5NJTk7G7XYzNzfH1atXUalUwRid2y92kfL0DgKlUklFRUUwV21sbOxIuWparZbm5mYGBwdpb2+POoYiMzMTlUpFe3t72DBepVLJ6dOnaW9vRyKRUFFRsUcHVFZWFgxqvr1dV1BQwOXLl8nMzNxViUhKSgq2nnZ+3wGd1e2VLJPJFPEzOZ3OPSQx1FTu3NzcnhYlbP/Wqamp+5KdgYEBcnNzd21LrVbT1NREd3c3U1NT6HQ68vPzQ+6jKIoMDQ2xtbVFY2NjVNUZURSD/lFVVVVHIvhut5uxsTGWl5cpLCyksrLy2CrFycnJDA4O7hu2fdh4mRPD5ia8613bjuo//CGEOIfW+u2IMwqEcjt1Te+mpef/oXPoW5yt/BR4vfgFgampqaAZ7Q9/+EP6+/t55JFHMGaq6fp3CxkZqSQmRj5Hlz3r/PyWo3xj7Mm5oSckJER1vr3VUFFRIe3t7S0EIrvPHjOOrm4+JHw+X/JvSkhxAKG0HfcqlEolaWlpVFVVUfdbVSABZZqU9ZgVWltbuXTpEgMDA5hMJjweD2azmWSPh5YvfIEvfPFF9LkpPP03H6Oh4qOcKvrQHlK1YffxrddWWLC6ed+5xBMnVbdDoVCQl5fHhQsXKC4uZmVlhTfeeIOBgYFghUQURRYXFyNWIA4KtVpNdXU1p06dYmZmhtbWVqzWwy2kpFIpFRUVFBYWcvXqVebm5qJ6ndFoDBqDhntvt9sNbH8X+7VPZTIZ1dXVdHd372kByeVyMjIymJyc3PW4RCIJVrt2wmAw7HFaj7YVuJ++amNjY48VScCV/Pbf1Ov1Mj09vS8xMplMOJ3OffVmMpkMvV6Px+PB5XLh9/v3PAe2K2rd3d14vV5Onz4dFalyOp10dHSwtrZGc3PzoUmV1+tlZGSEK1euEBsby4ULF0J6Tx0WgcGE+fl5YLv6Nzc3R2trK9evX0etVtPc3MypU6fQ6/X3DqkSRfjoR7crVt/7HoRYRHk2fcz9eA11mpzVpAUS4jIpznwS89owr7f/I8urq3hWV/E5HBQUFAQHP8rLy9HpdG8uIKIY0fKKPl5ZbUUhyHi3rhHJCX5XcXFxbG1tndj7nRSqq6vjBUG4K9Wbu1KxEgRBWVBQIL9nTrRjwlu5T63UyTA0xGLusFH8SAmqSnnQjM5sNjM8PIx0bo7soSGmYzfRpcTyzD98CnKKyEreK/q1bHr5zkUzNpefD9+nJz8l+qiWk0BCQgKVlZX4/X6WlpYYGBjA4/GQkJAQUn92HIiLi+P/Y+/No9tazOve38E8EAMJcCbAmQQHURQpUiIp6crX19d26qFOGieOXfsmThqnvatezmvSeGW9+OW1Te2kbtP4rbiDY8d1HDtu7MSuh9i+voMkipJISpzEeRDnESRBEgMxnfcHdI4AEhQpiaQotXstLJDAwXRwcM4+37e/vevr6/F4PAwODgJQUVHxWNoZyU+rt7eXhYUFampq9m0zWSwWzp07JwcD7zRlXFlZoa+vj5aWFjweD+3t7UkrLVJMRrJJwsLCQq5evUp+fn5CJcPpdHL37t2E4Q6j0YjX603QWanVsW1vPySrTCXTV62vr2M0Gnetm/Hx8YQoGwnBYJD+/v49ReLz8/PMz89z+fJlxsfH5WnA+EpcKBSio6OD9PT0XeL8vTA3N8fQ0BCVlZX7epDthUgkwuTkJJOTkzidTi5dunSkGqa8vDxu3LiBx+NhdXX10OJljhSf/WysSvX5z8Pb3pZ0EVEUmf77NaIhEaHRi2/Rx+uvv44uZRuAjPQsiv5xLSv/7b9hmZ3Fcj/7E5DJsLTpHGT0/aeebhZC63w47RIm5fG2SRUKBUqlMmnl8VlGRUWFJjMzsx742nG/9iNXrARBUAqCcEcQhO/f//9VQRBGBUEQBUE4aEBV8fMW/AixHfizVLHaiYxLJhQqgYXXNoDYAS4rK4uqqiouXbpE+vIygslExruy+LMv/wYVxio2xW2654flKgfERoz/4rVltkMiv/qi/cSRqngoFApycnI4f/48DQ0NrKys4Ha76ezsZHl5eU9R7pNCIjilpaX09vbS2dmJ1+t95OdRq9XU1dWRk5NDa2vrgUr6BoOBpqYmxsfHEypLy8vL3L17l/Pnz6PX68nKyiI3N5fbt28nXQ9lZWUsLi7i8XgSblepVBQUFDA+Pp5wu8lkIhQKEQgE5NukDL94TZVEZvZb98mIldvt3kWskk06Sp5JO7VgoijS3d2Ny+VKqsNbXV1leHiYhoYGlEolpaWlpKWl0d7eLleuAoEAbW1tOJ3OA5GqUCjE7du3mZ2dpaWl5bFIldQ+vHLlCqFQiIsXL1JcXHxkpCoQCDA6OsrNmzcJBoNYLBYuX75MRUXFySZV//AP8Pu/Dx/6EHzqUwl3iaLI+vo6Y2NjtL/RyebINuE8L6pUyMnJoaKiAqVxErXKiKvwJbR5eehrati6fp2wx4PJZHqs1u1IYI427xDnjKWU6w+3Un5QSFrH5wn3DVQPFEYsCMKXBUFYEgShL+62fyMIQo8gCF2CIPxEEIQDj/s/Tivwk8BA3P+twEvA5CM8R9np06ePJ5PkGBEMBo/Xf+WQoU5Rkt6Sgqc/gG82mHDf9uYmhtVVZiwWlpd8ZNgdXKyIOZIveVe5desWb731Fj9pHeBLP11CEODjL9nJtT07I7wKhQKVSsWLL75IYWEhs7OzvPnmmwwODj4W6TkI0tLSaG5uxuFwcPv2bbq7uxOIx0GRk5NDU1MT9+7do7u7m3A4/NDlNRoN58+fx+1209/fz9ramkyq4nVLBQUFpKSk0NfXt4voSEHNXV1du9zS8/PzmZ+fZ3t7O+F2h8ORYA4JD3RW8dDpdLseuxM7W4GSiW68fiwSibC6urqrkjw6OkpRUdEu4jEzM4NKpUoar7K1tUV3dzeNjY0J1a/i4mLsdjt37txhY2ODGzduUFlZeaB28vLyMteuXSMjI4OGhoZHHnkXRZG5uTneeustNjc3aWlpoby8/EjSCKLRKPPz89y8eZP29naUSiUtLS3U1NSwtbV1clp9e2FsLEaoamrgS18iKoqsra3JBPHNN99kbGwMlUpFRUM5xkINmiUTjsx8srKyWFgeZmG1l5LcF1EpY78R80svAbDx2mt85CMfobu7Wz4GSGvjYecHW5EAf7d2kwyVhZctTy+F5HkkVoWFhYRCoYMloMNfAu/acdufiKJYI4piLfB94A8O+tqPRKwEQcgD/hHwJek2URTviKJ471Gex2q11lRXV5/g05pHx/PiA5LenILKqGD+JxsJB9K1O3cQRJE/+s53+IN/9XUikSAaVaxsnJ2bQ+P5Zjz6U1ybMqNXRziTOsndO610d3czOzv7WGThuDE3Nye7SaelpVFbW8vFixcxGo10d3fT2trK9PT0vqTlUSFN2124cIH09HRu3rzJ3bt3E6qAB4FOp6OxsRGr1cq1a9f21XAplUrq6+vlCsvZs2eTnhi4XC5CoRBjY2O77jOZTOTl5cltTQkKhYLi4mJGR0cTbs/NzWV2djZh25ICmeOh1+v31VntrFhtbm7uCi9fWFjYZVoaCARYWlra5Xju9/sZGxtLmvMZCATo6Oigrq4u6bCApNNqbW2lrq5uX+uFSCRCX18fo6OjnD9/Pqmw/mEQRZGlpSWuXr3KysoK58+fp6qq6kj2QRsbG/T19fHWW2/hdrupqKjg4sWLFBYWolaryczMPNLq7qHA60X8wAeIAhOf/zxt3d289dZbTExMoFarqa6u5vLly9TX15Ofn4/JZCL33VYi/iiLb2yQlpbGgqcNlVJHYe4L8tOqrFZSmprwd3cTnJtLfM19eKYoivzd2k0C0SC/mNaMWnh6s2Qmk+m501mp1WrUarVBOADjF0XxCrC647Z4pmnkYF1d4NE1Vn8K/C7wRPPyJpOp7v9MBJ5MKLUKMl4wMfdDD1tj25hKYmdmgYEB1CkpDE5MUFiUTTgaRHF/z7GyBq/fWca9Gaa5PIW3nzajVjqJRCKsra3hdruZnJwkGAxitVpl08UTMXIdh9nZWerq6hJuO84YHUEQyMnJITs7m+npaa5fv052djZFRUUH1j4IgkB+fj52u52uri5SU1NxuVx7jnkHg0E2NjZwOp309PTQ0NCw67WkvEBpmnInCSgqKqKtrY2VlZUEQpGXl8eVK1cSKktqtRqTyZSQUCC1AuN1VpKA/WFtlZ0nM263exeh2WnxADA8PLzLaFUKWK6urt71+cPhMLdu3aKqqmrPVv/c3Bybm5vYbDaWl5cfqplbX1+nu7sbh8NBVVXVI28/q6urDAwMoNfrqa+vP5LWmzRBOzMzs2e8jASFQoHVamV1dfWxfbGOAtFoVN7/8PWvU9bby+xv/zaqsjJO22z7eonps9TYzhpZafeirfIRFKcpzX4nGlXi40wXL+Lr7OQ3P/xhok4nX/3qVwEQ7u8f9zoa3/KOMLI9x89Z6slUH9xj7yiQkpLyXDqwOxwOcXp6OgeYfZzHC4Lw74CPAh4guSAvCQ5csRIE4T3AkiiKnY/+9hIRiURcO1Ptn3Vsbm4eyLTxWYDtrBGNVcn8TzcQoyLRQADV/Dzcr0AUl+YRiQQRRAEmnbx5VUkoIvLK2+y8q84iR9QolUrsdjvl5eU0Nzdz6dIlOZuuq6uLN954gzt37jA1NXVgQ8ijQiAQQBTFh5I9KUbn8uXL5ObmMjExwVtvvcXw8DB+v//Q3osgCLLwWK1Wc+3aNcbGxh4pnNhoNMqeSdeuXUta5hdFkc7OTioqKqiuriY/P5+2trakn0WhUHD27FnGx8d3te0EQeDMmTP09fUliM4FQaCsrIzh4eGE5Xe2AyWdVfwZs+S+vhek6shOj7X4A7vf7ycSiSSc8Ph8vqTpCBMTE5jN5l3ELBqN0tHRITvgJ8PY2Bj37t2jpaWFs2fPsrCwwPLy8q7lotEoQ0ND9Pb2Ul9fT1FR0SORKo/Hw40bNxgdHeXUqVNyruFhQaqCtbe309bWhiiKnDt3jnPnzpGdnf1QDyYp8uhpIhKJyIM2ra2tXLlyhenpaQwGA45XX4WyMvL+5m9wGI0HNmjNetGEUiMw/cMVBFTYjLud0BU6HaYXX6RvdJSpHdv6XlgMrfNjzx1KtTmcMz79Y6FWq9239f4s4tSpUxrgsas4oij+viiKDuDrwKsHfdyjVKxagPcJgvBzgA4wC4LwV6IofuTR3ioIgpB6GDlXJwlbW1vP7ETgTihUApkvmpn+zhrrd/1oxFGEaJR5o5FoNEpxiYOtgJ5vveGF1QJycyP80/MZ6DUP5+lSMrtUhYhGo6yvr+N2u+np6cHv92OxWOSKlsFgODbdhhQWexAcVYzOTigUCoqKinA6nYyPj3PlyhU5ePcgZpGCIFBSUkJGRoYch1JcXCyv04GBAdLS0mSxdG5urux1VV9fv6vqolaraWxs5MaNG9TV1SXcr9frKS4upq+vLyFfMSsri9HR0YSKbnp6Onfv3iUSicjrSdJZSScnBoNhV3swHtvb2wltS1EU2draSji5mZ6e3tXuGxwc3JWduLm5yfT09K6AZUnIbrPZkgYli6JIf38/gUCA8+fPy9+J5GAvDQFAbP/Q1dVFeno6LS0tj2T2ubW1xeDgIMFgkIqKiqSh00+Cra0tpqamWFxcxGazUVpa+sih7lI80U4X/aNEOBxmbW1NHjgJh8PytGp+fv5uI9y//mtoaoLf+A3427/d0xA0HiqjktQLClZes5FV8E68WyFIMltgrK/HEwqRHQjIxqHy0+8oWYXEMP9z9To6hYYPpO5OMHgaEAQBlUpFOBw+En3e04AoilRUVJjVarULeOMJn+6vgR8AnznIwgdeg6Iofhr4NIAgCJeBf/WYpEpdUlKib2trIxKJIAgCer0eg8EgX0t/q9XqE7HRHQSbm5vPVUJ4ao2e5dZNFn62QZqtl4hWy8h9zY4+o4E7My+iUUfBNUBtaf6+pCoZ4olWaWkpoiji8XjkkX+fz4fZbJaJltFoPLLtYWFhgdOnDzRAkoCdMTrT09OPHaOzF1QqFWVlZRQWFjI6OsqVK1coLS2V9WD7wWw209LSwtDQENevX+fMmTNsbGywsbHBuXPnEpa12WzU19fT2dnJqVOndlVwdDod9fX1dHR0JBAHiLX+FhYWEkiqIAi4XC6Ghoaor6+Xb8vOzmZ+fl5uK9rtdoaHhyksjGlN96tY7RSub21tJWwfkqi7paVFXmZzcxO/359geBqNRuUsxZ1keGhoSI4o2olIJMKdO3fQ6/XU1dUlfA86nY6amho6OztpampiamqKyclJamtrH2l78Pv9DA0Nsbm5+USmsskgnRBMT0+jVCpxOp2Ul5c/9gmB1A48qhB6iBGp1dVVVlZWWF1dJRKJkJaWhs1mo6ioaP/Bofp6+KM/gt/5HfjSl2IE6wBYynidsLEK48Bp1u2LkMQPVlAqWQ+FsCgUeDs6SIn7Xe1sBf7E08VS2MM/tb1AivLkTExLflaHsc86DkSjUTklw+fzydc+n0+unIdCIUVGRsbu1PUDQBCEUlEUR+7/+z5g8GHLx+OJqakgCP+SmO4qC+gRBOGHoij++kMekpmVleW/ePGiCR6sHGnFeDwe5ufn8fv98srR6XS7SJfBYECr1Z4Y4uX3+/eMCnkWISgEsl+yMPF1N5trapRlBZy/8CKf+qO/YllsIk0zy0fecYY/31gmym4Txcd6TUHAarVitVopKSlBFEU2NjZYWVmhv78fr9eLyWSSY3ikvLInRSgUIhgMHrg9sBdMJhOVlZW4XK5HjtE5CNRqNRUVFXJMztjY2IHjSZRKJZWVlbjdbm7cuEEoFOKFF15I+jiz2cz58+dpb2+nuLh413SbNFZ+69YtmpubZU2SFOZ8/fp10tLS5M+bnp7OyMiIbN4JsXZgd3e3TKx26qx0Ot1DBx52Ctd36qtWV1cxm80JeqmBgQFcLlfCZx4eHiYzM3PXwWRycpKNjQ0aGhp2rSMpdFnSvyWDlMf5xhtvkJmZycWLFw9MWra3txkZGcHtdlNeXs7p06cPZTs/6niZrKwsFhYWDo1YhUKhBCIliqJMpEpKSh5PqP/bvw0//jF88pNw4QLsk+vqC6wytdxGQZONyGt2ggMqaNy9nCiKrHo82LOz2XzjDQw1NQiyGP0BtRryz3LTO0KTsZxS3YGn948Fks7qpBCrcDicQJziyVN8UUbiAyaTiczMTAwGg1yUMZlMfOELX9h3MkQQhG8AlwG7IAgzxCpTPycIQjkQJeZ68ImDvvfHIlaiKL4JvHn/7z8D/uwRHp7jcDjkPYxCocBoNO6pFRBFkUAgIK9Qr9fLysoKPp9P7glrNJqkVS+dTvdE+VoHRSQSQaFQnBiSd1gwlWnR2UP4VmrZyglxpV3EWnyZ045posG/xmI4CxsQEZM7Tz8pBEHAYrFgsVgoLi5GFEU2NzdlHYVUpZCCpXc6bh8Uy8vLu2JbngSPE6PzKNDpdJw6dQqfz8fQ0BAjIyNUVFQcSDhss9lISUkhHA7T3d1NbW1tUsInRbe0t7cTCAR2uZNLLaP29nbOnTsnkwatVktFRQXd3d0JpMTlcjEwMCBXyIxGY0L8jCAIGAwG2S4hvvKU7DvdWbFaWVkhXre507tqbW2NaDSasI6kNtLOnMDFxUWmp6dpamra9dp+v59bt27JFcO9MDMzw+LiIgqFAqfTmZRU/dqv/Rrf//73ycjIkPVpnZ2dvPrqq7jdbkpKSvjWt76FIAiIosgnP/lJfvjDH2IwGPjLv/zLXYMWe8Hn8zE9PX3k8TIZGRmMjIzsv+AeiDckXl1dladzbTab5En05G9SoYD/8T9ilgsf+hDcvAkPOeEZmfkpAKWNDSzOiIgjafjXttGnJj5me3ubd7zjHZx597uJLi2xefUqnItpnaVhyc2In79bv0mW2so7LI9eHT9qSEMlx4VQKCQTpnjS5Pf7EUURpVKZQJxsNpv890HbldnZ2USj0X2JlSiKH0py81886meS8DSaqdmFhYUHPnWPZ6XJzoREUSQYDCZ8KfPz8/h8PlmQrFQqd1W7pOvD0ML4/f4nrnacRAiCgD5lkMDKKSb6YODe3/LKB5rIzdugf0JEjMbE1FGOhlglez9msxmz2UxRUZGsq3G73YyMjLC5uYnBYJCJ1kF1IktLS0mjSw4DUoxOUVERHo+HqakpBgYGyMjIwOl0PtHAg8Fg4MyZM2xubjI4OMjIyAgul+uhZ5yzs7MolUoaGxtZWFjg+vXruFyupPoytVrN+fPnuXPnDn19fbsm2HJycggEAty5c4f6+nr5PqlyMT09La9X6be7uroq/y2J2CgGTjAAACAASURBVCWzYCneRtJiSQ7sySoTPp9P1hpJhFuqhoXDYTweD7W1D3yBBgcHqYirTkQiEbq7uzl79mwCyV1bW2NgYIDm5uZd+4aNjQ06Ozs5ffr0nlWZYDBIT08PCoWCixcvyoMayUKUX3nlFV599VU++tGPMjo6yvT0NN/85jf5hV/4BT796U/z2c9+ls9+9rN87nOf40c/+hEjIyOMjIxw8+ZNfuu3foubN/eOQItEIszPzzM1NYUoijgcDi5cuHCk+hmVSoVarU4aNZQMwWBQ1ketrq6iUCiw2WxkZGRQXl5+dC7g2dnwla/Ae98Ln/40/Mf/mHSxwLaHyflWnJnnMejSyHlnGM+Qn5kfr1H6y1kJy+p0On70ox8BsPad77DV1oaiol6+PyqKfGftBiExzD9JbUYlHJ0b/uPCYDDI8URPClEU2d7e3kWYpOMyxH7f8cdjqdqk1+sPrSCSkZFBOBw+dvHzsRMrlUqV43Q6D22URRAEtFotWq12zwNKKBRK+HKXl5fl/6VQ2HhmHE+8DvLjTuYA/TxgYm6Lv1UVUJ0iUrIc5GP/+VM4DZ/mlU+8GFtAjPk5RQ9u73GokEq9JpOJgoIC2SDS7XYzNjbGxsYGer0+gWjt/MGK900Ca2pqjvz97hWj43A4yM3NfewDiclkoqGhgfX1dQYGBlCpVLhcrl2kTcqPk3RHWVlZpKam0tPTw8LCQlKrAYVCQV1dHQMDA3R2dnLmzJkEwlFUVITf76e/v5+qqir59urqaq5duyYPIUAsuqe3t1eOisnJyeHq1auUlZUhCAI2m42xsTE5AFuyXEhGrOJPZrxeb8Kgw9zcHNnZ2fL/KysrqNXqhP1Df38/+fn5CRODXq+Xrq6uXQag8MCV/uzZs3uS4aWlJe7evUt5eblczZJ8niYmJnZV/S5cuMD169dl89lLly7xiU98gjfffBOAj33sY1y+fJnPfe5zfPe73+WjH/0ogiBw/vx51tfXdw1cSM7hU1NTTy1eJj09neXl5aQnKtvb2wlESspczMzMpKKi4nhF0+95D7z6Kvyn/wQvvwzv2ukNCaOzrxEVI5Q5XgZAa1OhrYri64vgmw1iyE3eijS//e34797F29YGnEEU4YZ3iLHtBd5rPUuG+mSmcxzEO05CNBolEAgkJU6S/55Wq004lqalpcmdpOPq7qhUKpRK5bG7dh87sbLZbGU5OTnH2jO7bxS2p7dMJBJJ6OWur68zNzeHz+eTzSDjiVf8tVarPfAZ2rOCcETk9d4Nrg1sYhajaPMmmL6yTSQSobKyEtX97VSMxH5A0SNqBT4qBEEgJSWFlJQU8vPz5VaT2+1mYmICj8eDTqeTiZbVapVJ8XG0jCVIMTpSxWd6eprW1lZMJhNOpxO73f5YOx6r1UpTUxMrKyt0d3djNBopLy+XCcjIyAgFBQUJpEGr1XL27FlmZmZobW2lurp6l2BdEAQqKyuZmJjgxo0buxzCKysr6ezsZHx8XNYcqVQqTp06xZ07d2QiZTab0el0cutVpVJhtVplfZTFYmFjY0Nu/0kC9mQnTPGaxp36qunpablNJooig4ODCdWrpaUlvF5vghHo9vY27e3tnDlzZhcRmZmZYXx8fJcrvYRwOMzdu3cJBAI0NTXtWqakpIQrV67IOjtRFJmdnWV0dJRIJILBYJAF8ouLizJZys7OZmlpCYhVGuMnE6Xw4+zsbAKBgOw5lZKSgtPppKam5qlIE9LT0xkbG8PpdBIIBGQitba2hlqtxmazkZOTQ1VV1ZFmGB4If/zH8Oab8LGPQU8PxEUJbYe2mJi7Sl5GA0b9g4KHrUXP/EiA2R+sU/Ib6fI6fuONN3jllVf4+7//e86cOUNKczNrbV1QfIa18BZverpx6XI5azhYbuTTgFqtli1dpGPiTlG43+8nHA7LOkjpOGgymcjIyMBgMKDRaE6ULEar1SoFQVCJoni4zs4PwbETK41GU3DQsfbjglKplA/IySDpvKSNy+v1ylWv7e1tAoEAWq1WrpDEV72OS+d1WFhcD/HttjUW1kNUC4s0zr+O550v0d8xBECZsxylIkakItEQAsJTq1jtB0EQZP2edAbt9/tZWVlhcnKSnp4e+cDmdruxWq3HvrPX6XSUlpZSUlLC2toaU1NT9PX1kZ2djcPheKxqgxTOvLS0REdHB6mpqeTl5bG0tMSlS5d2LS8IAg6HQ45lWVxcxOVy7VoXhYWF6HQ62traaGxslE8mJB+rGzduoNPp5GqNRF7Hx8flao3L5eL27dukp6fLfl2Tk5MymZTOmo33vYYedgYdX5GSnt/r9crPAzGiYjQa5d92KBSSo3ukx4fDYdrb26moqEggcaIoMjY2xvLyMk1NTUkriqurq/T09FBYWIjT6Ux6QFEqlZSVlTEwMEBmZibDw8PYbDaampqYn58/0EEomav5ysqKnNWXl5dHS0vLUw3R9fv9bGxssLi4yBtvvIFWq8Vms5GXl0d1dfXTJ1I7odfDN74BDQ3wq78K3/9+TIMFjM28TiQaoszxzoSHmG0m7pXOQZ+d9R4/qfeT2RYXF5mampJJdcqFCyi6Y55WN72jGIxa3m89GdYK8EDftJM8bW1t8cYbb8j6JulYlpqaSm5urjyt/ywhMzNTHB8fzwDm9l34kHDsxEoUxdyTRqz2Q7zOK5lAuLOzk/z8fJRKpbyBrq2t4ff7ZZ2XSqVK2mrU6/UnYocTFUVuDHl5rduDVq3gQ80WLF/7CpHCQkwWC/OqeygEBebZbJSumPlh5L77+lGJ148Cer1edlIHuHXrFlarlZmZGXp7e+WzarvdTmpq6rF9N5JQNy0tjXA4zPz8PN3d3YiiiNPpJDs7+5FaJYIgkJmZSUZGBnNzc7S1tUl6gz13jJJgfXx8nGvXrlFbW7vLaTw7OxutVit7WUn3S7qt69evywdUiBGp1tZW0tPTMZvNGI1GzGYz8/Pz5OTkkJaWRm9vL6FQCLVaLeusJGK1sLCw631KywLy5Kj0PuJF66IoMjQ0RGPjgzGunp4eysrKZOIlmaQ6HI6E8GNRFOnr6yMcDnPu3LldJ0eS2efq6ioNDQ37EmC1Ws3s7CyhUCiBlO5EZmam3OKbn5+Xhyry8vKYnp5mY2ODqakphoeH0el0VFRUPNTl/Sjh8/lYWVlhZWVFrgZL07q1tbXPhmFydTV8/vPwL/4FfOEL8MlPEgz7GJ97kxx7LWZj4rFKq9Xita9izclm7icezC4dSq1Cjo+StHcKrZaU8+dhErYifj6Weh7jMXWkJN1xsmpT/PEo/jiUnp6OwWAgGo1y6tSp50ra4nA4FG1tbdk8z8QqHA5nPE56+0mGZGypVqv3NO+L13n5fD6Wl5fljT1e57WXn9dRYt0b5u9urDGxFMSVq+N9jVaU90ZYDQbxZWWRmpLC4NgABTlF+O5GMdbFzsoikW2UguLEVqwOAq/XmzC9FggEcLvdzM3N0dfXJ+tAJKJ1HDqQnTE609PTjx2jI01Wmkwm7HY7165dIy8vj8LCwqSfRRAEiouLZVPRzMxMSktLE14vLS2NhoYGOjo6qKqqkv2V4g1EJS2SUqmUg5olAXdZWZlsVyBprebm5sjPz8dmszExMYHT6dxT8+Hz+WRiIv0tTc4tLCwgxWXNzs6SlpYmLzt3P8tNso8QRZGenh6sVqus64JYG6SzsxOz2Ux1dfWudb2xsUFXVxfZ2dlym3MvSGJ4jUZDdXU1brf7obKB973vfXz1q1/l937v9/jqV7/K+9//foLBII2Njfzpn/4pRUVFrKyskJ2dzeXLl/d8nsNGvH5xZWVFrs7bbDYKCwsT9IuCILC+vv5sECuA3/ot+Id/gN/9Xbh8mQnrHOFIgHLnu3ctKggCKrWKrHemMPGVNZaubpH9klkmVvH7/7kSG0yCc26bopqHZ0c+CnZ2UOKPK5K+SaPRJBxLUlNTD9RBkarEzxOxKigo0AI5wBOnxhwUx06slEql9nlxdpXwsCqAhIPqvKQfytraGrOzs3v2tOOvH7enLYoiPZN+ftCxTlSE9zdaqSuKiYBX795F0OtZ0+txmkx87WtfY2Z8lu3vCmy16SE/1gpUIJwYjdWjQmrh7jR3zM3NlQ++29vbuN1uFhYW6O/vlyeX7HY7aWlpR060DAYD5eXllJWVyVqxnp4ecnJycDgcB9L2jYyMUFZWRmZmJg6Hg3v37nH16lUKCgrIz89PuqM1mUy0tLQwPDxMa2srtbW1Ca3ylJQU2etqe3tb9qOS8us6OztlTZLZbCY7O5uhoSEqKirkgQJpatDhcMhVX4vFgsfjkZ8rmUlo/I4/Xl+1vLxMWloaSqWSaDTK6OgoTU1NQOy7HhoaSjAMHRkZQRRF4nNLg8Egt27dIi8vj4KCgoTXFUWR8fFxZmZmklbz4rGxscHg4CDRaFTOGBRFkampKbxeL0ajkQ996EO8+eabrKyskJeXxx/+4R/ye7/3e3zwgx/kL/7iL8jKyuIzn/kMbW1tvPDCC7S3t/Mrv/IrGAwGvvKVrzz0O39SxE/crqysJEzcFhcXP3Ti1mazJXW9P7EQBPjyl6GmBvFDv8z4//dOsjJOYUlJPqWfkpJCNDWItUbP8vVN0uoNrK6ukpKSImsPNyI+XtvsAc5QOOzGm3aLlB22Hnshmb5Juk6m+U1JSZErTk+qb9qv/f4sIj8/36hQKI7VNOxYGY4gCKrCwsLnilUdVqL7fjqvnVMYm5ubLC0t7ZrCSNZuTDaF4duO8v2Odfqm/DjsGn7hfCpppthXI4bDBIaG0FdUEAgG5ceXVZeyuLLBwuubaK05hCPbKJ7hilX86P9e0Gq1stAcYgdet9vN0tISg4MxI954onVU1UVBELDb7djt9l0xOg6Hg6ysrKRtS2lbkVpKSqWS4uLihJic4uJi8vLydm0jCoUCl8vF2toaHR0dMhGTltPpdDQ1NdHR0YHf76ekpEQWqVdXV3Pr1i1Zm1RSUsL169fldV5aWkprayt5eXlyO1yKvdHpdDJ5Svb7ih8WWVlZkd3ap6amZK3V1NQUmZmZsli8q6uLqqoq+cA3PT3N6uoqjY2N8ufx+XzcunULl8tFVlbiOL3P56OrqwuLxcKFCxf2bBF7vV6Ghobw+/1UVFQkbF+CIFBaWsro6CinT5/mG9/4xq7Hb21t8YUvfEGOl3E6nTKJ+S//5b8kfc3DgGRZIRGpeI+40tLSR/KIs1gs9Pb2Htl7PRLY7TF/q5dfxvWfFVi+9sk9F5UcyrPfkc3GQID5H3uoqqril3/5l4GYrOLbazeIEBOCa9Iz2XjrLQy1tSgMhl1T6vHXyboXqamp5OTkHHhK/Umg1+ufuzDmnJwchd1uP9apgeMmORmZmZnPZnljD8TrPY4SCoVCJkzJIPmGxJeFV1dXk/qGRJVGXhs1EggJXHLpeOGUFbXqwYFie3wcMRBAV1kJ8/Pcu3ePL37xi3ziE58gv6mA5RubpI68SPjss6exiofH43lkl2GNRkN2drY8uRXvDj08PJzgDm2z2R7PHXofJIvRkQTRO2N07t27R2Fh4a6Dolqtpry8XHZxl2Jy4m0KJKSmpnLhwgX6+/u5efMmtbW1skhXpVLR2NhId3c3vb29nDp1SiaBRUVFdHR0yBql2tpa2tvbuXDhAhqNhpycHCYnJ2Xh99TUFJWVlbLOSvKZ25lf5vP5ZD2Ux+PBYrEQCoXwer1YrVYikQgTExNy9t/k5CQGg0Eml0tLS9y7d4+mpia5Wre+vs6dO3eora1NaOeIosj09DTj4+OcOnVqTxPWQCDA8PAw6+vrcvxMMiKSmZnJ4OBgwn7jsONlDoL4VAO32y0bs0qh6U+SaiC97/gsyGcBkbddYvJXGij6+i34WRd8oDDpclIlVZOnJONiCguvb/JLr3yEj3/844iiyJX1Pia2FzkbqaAD8G9vI/r99Hz726w7HAl6W71eT3p6+qH6Kj4JtFrtQzM6n0Xc14Um/zKPCMdNrLIdDsezMyJ3AGxvb5+IKBupVajT6R6q8/L5fLQOevEFRd5evIEhPEfb9ZjOS5oESevrQ6NWs6LVolQqaWtr40/+5E/48Ic/jFKrwHZRQ+TH+QQn51AUKI7NIPSw4fF4drV7HhWST5F0oA+FQrKj9+joKNFoNIFoPWmszU48LEYnJyeHhYWFpJOAEjQaDVVVVfj9foaHhxNicuKhUqmoqalhaWmJtrY2ysrK5HapRJqGhoZob2+nvr4epVJJXl4egUCArq4u2cagsLCQu3fvcvr0aYqKirh27ZpccRseHpYd5CcnJ3E4HHJrIr6FLlWsJMsFhULB5OQkubm5CILAxMQEeXl5qNVqvF4v9+7dk0mWx+Ohv7+fpqYmmawtLS3R399PY2Njggh9e3ub7u5uNBrNnhN3wWCQ0dFRlpaWKCsrk4nlXhAEgdzcXKanpzGbzUcWL7MTUg6nVJGKz+GsqKhIcLs/DJjN5hMVj3IQ3Ftope9Xa3Hc9aH+9V+PTQvmJbYDJcPp1dVVZmZm8Gb4CCgFvvvFH5H7j2Kf9XrBIpkbAjO3RVTqELkr42hOn6bq7W9HfcLXh1arlRNNnhfk5OQgiuK+7uuHieMmVmmZmZnP1qzmPtje3j6SqsRRQK1Wx7yCgmFSU0K80JiYkyVlM23NzxMdH2d1fJztaJTXX38diI0U37p1C41BQVivw3vdgpA3S1gVOdZU+8PCUeQ7qtVqMjIyZGISDodlojUxMUE4HCY1NVUmWof1+slidFpbW4EHkT0PE63q9XpOnz6N1+tlcHCQ0dFRXC7XrlZpRkYGVquV3t5eFhYWOHXqlKzrcLlcTE5OynYMGo2G4uJi+vr6ZOdzp9PJwsICS0tLsvv8xMQEpaWl2Gw2lpaWSE9Pp6enR35ffr8/KbGam5uTK0gzMzM0NDQQCoWYnp7m4sWLiKLInTt3OH36NCqVCp/Px+3bt2loaJAJrhSQ3NTUlEB6FxYWGBgYoKKiYldbEGLf69jYGHNzcxQXF+NyuQ5kqyK17icmJsjJyTmyeJloNCoHmrvdbnkd2u12qqurEwxVjwIWi4X19fVnhlhFoiFGp39Kqq2M0Fd+C1VLC8F3vYu1D3yAtaoqVnNyCEVjJ5ASYU9LS0OvMPL73/vX/K+e/0nfe3+KaXGO10tFzIM5LGozeG+2h4p/8gkUh3xCdVR4HomVzWYjEokkrzYcEY6bWKVYrdbnSmO1vb196FWIo8a0O0hhxu73rFKpMJlMGF96iYW+Pmyjo+guX8ZgMGCxWHjppZcIBAIMTv6AtZIFMnp/nvS+VDada7zV9xaw22033s/rJBGvYDB4LEZ2KpWK9PR0eXIuEonIROvevXuEQqEEonUYFQspRmd5eRmHw8Hy8vKBY3SMRiP19fVsbGwwMDAAsGukX6PRUF9fz+zsLK2trVRVVclEMj8/H51Ox/Xr12Ubgurqajo6Orh37x4FBQWcPn2atrY2rFYrBQUFXLlyhYKCApxOJyMjI2RmZqLRaGR39Z1iWqm66na7cTqdbGxsoNFo0Ol0DA0NUVBQgEqlYnh4WJ7mDAaDtLe3c/r0aVJSUhBFUW7dxVevQqGQnNvX3Ny867cdiUS4d+8eU1NT5Ofnc+nSpX3bN8niZTIyMigqKjo04hGNRllfX5eJ1Pb2NhaLBZvNRk1NzbFPeUmWGicN4XA4qbZpwzeFn3WE7RL69EGy/s2/IeeP/5isf/tvyQJEsxnOn0e4cAGxuZmrkQilpaX8+f/13/n27a/zz9/2MobXXmMp1wILZ1iKlNDsSqHhTO6+7+kkQaVSEQqFnvbbOFTo9Xqi0eixtpWOm+SYUlNTn43yzgHxrBErjy/Cpj9Knm3vr0Gh12O6dImNH/8Yw30SYLfbUSgURPAws3IVW1UtKx4PVbcKKWtMx1SpT5oPJZ0tx+u8kk02HmY+1EGwubn5VMbBlUqlLEKH2EFXOiBOTU0RDAaxWCzyMo9LtEKhEIFAQBbeP2qMjtls5ty5c6yurtLX14dWq8XlciW0ynJzc7HZbHR1dbGwsBBz5VepZGJ069Ytzpw5g9Vqpa6uTjYQzcrKory8nJ6eHs6ePUtRUZFcIZMqOjabTbYmiNd8SIHnENNF1dTU0N/fj9PpZHt7m/n5eS5duoTH42FxcZGWlhYikQjt7e2Ul5eTlpZGNBqVxdUNDQ3y87ndbnp7e5OK+aPRqKy1ys3N5eLFiw+dCN0vXkalUjE/P//YxCp+u3G73QSDQaxWKzabjdra2qeeBGEymRgeHj7W1xRFcZfxpfR3fLBv/H7HZrPhcDjQaKt443YHet0aDacbEBob4VOfgqkpuHYNobUVrl2Dz3wGQRS5qFCwlZOHOD/Pb6fl8Ls/9w5M73wno6kmuKYkN13BO04/HX+xJ8FJOvk9LAiCgEKhOFauc6wvplarLWaz+blrBe6laTqJmFmJTRDm2R/Ob1POnWPt6lVU7e1sbW5it9sRxShdw3+NQqnhXnohsxeGeOf/bGTlhz5SPqxL0HklQ7Id38bGxq5E872I12FaG0gTaE8bSqVSrlZBYuWhq6uLQCAgEy2bzXbgFs7i4mKC4eXjxuikpaXR3NzM8vIyt2/fxmw2Jxhs6nQ6zp07x+TkJNeuXeP06dOkpqaSmppKY2Oj7GiemZlJQ0ODbCAq6b9mZmZwOBxcuXKFwsJC8vLymJmZwW63MzMzQ1FREdPT0/L7kaYFA4GA3IJfXl6msrKSgYEBiouL5SnAuro6BEGgs7OT3NxcsrKyCIfDdHZ2YrVa5YzCSCTC4OAgHo+HxsbGhOqOKIrMzc0xMjJCRkYGLS0tD239x8fLmEwmHA5H0niZjIwMWVN2EEQiEVZXV3G73bjd7oRKp1QlPEnQaDTytPJhQfJvSjZRt/PETdpnZGdny9YE+524lTnfSc/o37C8PkRGqitmw5CfH7t8+MOEVlbwvfUWkR/8AMXQECMdd/jVSAjD6hz8zu8Q/fMvkuqs5azrDG/7Z+9BSSbw7BEVQRDk6cTnBUql8lg/zLESq5SUlLRnxjTugAgGg89UxWrGHUSpgCzrw/mtoFKxWV6O9c4dvvlHf4Ta5eLefCvujTF0Je9nKLjAy7m15LxoZu7HG3j6A1irHn6WLAgCGo0GjUaz55m6pPOSzjbdbjfT09P4/X4ikYjsgr+XkepBz7jiLQhOEhQKhezADg+0MlI1JV4rY7PZMBqNST/z/Pw85eXlSV9jZ4zO9PT0vjE66enp2O12FhYWuHXrljyGL7VTCwoKsNvtdHV1YbfbKSsrw2g00tTURHt7O4FAgPz8fBobG7l58yYNDQ2cOnWK1tZWbDYbpaWlst/WzZs3yc/Pp7e3d5eXlaSvWllZwWazsbi4SHp6uhzwW1lZSX9/P3l5eZhMJnp7ezEajRQUFLC9vc2tW7fIz8+X3dk9Hg9dXV3k5eVRWVkpr0tRFFlaWmJoaAir1bpnTqD0HS0sLDA9PU0wGMThcOwbLyM5X29sbCT1tguHwwlEKhKJkJqait1up7Cw8MTvcwRBQKlUPtLUdDQaTchsjd8PSO0pnU6X8PuX2ueHITXIz2pmZOrHDE7+L9Kt5TGCEQwS6O/H29lJcHISFAp073gH4//o5/nLP3+LmlPl/Oav1BC9do2pv3udwq6r1Lz1Hfiv/zekpkJzM7S0xC4NDbEYnRMOiRSfNLL+JFAcM0s8VmKl1WptzxuxOi67hcPCtDtIdqoalXL/ndB6ejq2jAw2fvYzzMU53J34O7RpldwS1ynRZtGc4kI4D2s9fmZ/sE5KkRaV/sm2X0nntdd2Iu18pR2vx+Nhfn4ev9+fdOcbT8DizUClPLqTDoVCIVeASkpKEqa77t69i8/nk13VbTabXIXb2trat9X5sBgdh8NBTk5OQpVQEASys7PJyspiZmaG69evk52dTVFREWq1mpSUFFpaWhgZGZFNRU0mE+fPn6ezs5NAIEBZWRl1dXV0dHTQ1NREVVUVXV1dnDt3jrGxMSKRCDqdjq2tLdRqNeFwWA6GhQcVK7fbTV5eHqOjo1RUVDA8PCybqHo8HiorKxkbGyMUClFdXY3X66W9vZ3KykoyMjIQRZGRkREWFhaoq6tLWFdut5vBwUH0ej1nz57dU5/k8XiYmppiZWWFjIyMR46XyczMZHl5GbPZLNt2SEQqfpq0qKjoxBOpZDAYDPj9fnn/KJ007WzT+Xy+hJMm6fdqMpnIzMyU/ZuOuk2lVKgpc76L7tFvMjfWinFwHV9PD2IggDItDfM73oGhthbBaGTmW2P8s5YzlP2LDMhU8w/KMm5k/xLWiikKgmP8/EAEpPbhD34QewG1Gurr4cKFB2QrPf3hb+opQK1WEwqFnitipVarFccZxHy8fUeVynIS2i+HiZ0eOycZkajI/GqI+uKDCVlD4TCWl1/mlQ9+kFpfJ65LNsZsDnRE+fnUJhSCAErIe7+Vkf+6zPxPPTjed7RtUYVCIQcrJ8POdoHX65XHy6VpF41Gg8fjYXp6WiZfkpHqSS9/C4KA1WrFarXKba+NjQ3cbjcDAwN4vV60Wi0KhULWkR3kgLRXjI7VasXpdCZMrkmhzbm5uXIL0Ol0UlBQIAcOZ2Zmcvv2bfLy8igqKqKxsZGenh66u7upqamhsrJSNhA1mUxMTk5SXl7O0NCQ7Gkl+VlJrQmIVazS0tKYnJyktLSU7e1tFAoFGxsbVFZW0trayrlz55ibm2NpaYlz586xvr4uWz5YrVa8Xi937tzBZrPJMTsQI0oDAwMoFApqamqSElNp4nJmZgadTofT6aSqquqRt5tQKIQoikxMTDA7OwvE2q52u52SkpJnZtI4HlKbPz6svqurC1EU5TZ/PHGSqk0Gg+FE7EOjfj+2aTWaoJr+gW9RcceGoaoaY10dmoICBEFgfn6el5ua9V8PgwAAIABJREFU+dT5z9DU3IQ+U03XhI8bw17Olxm5kzGD1uCCxrPwsY/FntjthuvXY0SrtRX+7M/gP/yH2H1lZTGCJZGtsrJYC/IpQqVSyQ7vzwuMRmMUMAKe43i943Zetz6PFauTsFM4CBbXQ4QiIo599FXxEPPy+FZ3N5pGHTkfeT+rUR8ftb2NFOWDsxlDjob0phSWr2+RWmMgpeDpnV3Hn/Umc1WXAkqvXbuG2WzG7/czPz8vG6nG67ySab2etoHfTkhZgBaLhaKiIkRRpL+/Xzas3NzcxGg0yu7wB3HQ3hmjMzk5SW9v764YHYVCQWFhIQ6Hg4mJCa5cuUJRUREOh0N2KB8cHKStrY0zZ85QU1PDyMgIt27d4uzZs+Tn59PZ2UldXR3Xr1+nrq4Or9crt/qqqqqYn59PaAf6fD7S09NRq9XMz8+Tl5fH0NAQLpeLvr4+iouL8Xq9jI2N0dTUJDvknzt3Dr1ez71797h37x41NTXy9rG1tSWbdrpcrl2aSaktODU1JXuEnTt37pGqSJJjv3SRKpGiKHL+/PkTT6SSDaZI1zsNiKXfixT5VFZWdmJPWERRJDg5iff2bQJ37yKGQuRVpDOeO4fyN95LWnadvGwkEuEjH/kIY6NjWC/aUFeHmFsN8r32NQoyNDTXaLixFMam2lG1tNngve+NXQC2t6GzM1bNam2F730PpIgiu/1BNevCBairg2OuVj6PxOp+JdnEc0qszM9bxepZcheecd8Xrj9kIlCCFCWyuBQ7m9akpjOmDHExpZJi3W5fn8wXTaz3+5n53jpl/zwDhepkijYl7Yfk/J0MUuSEdOBYXl5OGjmRTOv1tNvCgiDg9XqprKyUbQWkqt3o6CgbGxtytcButz808+2gMToqlYrS0lIKCgoYHR3lypUrlJSUkJubS1VVFSsrK9y8eZPi4mJKS0uZmZmRva4CgQB3796lpqaGrq4uXC4Xw8PDZGRkEAwGWVtbw263y5YL0gE9LS2NmZkZqqqqWFhYIBwOEw6HMZvN3L59m6amJmZnZ5mZmaG5uZloNMrNmzcxGAxcuHABlUqF3+9naGiIra0tXC6XPKkpYWtri6mpKTleprS09KHrKx5SxuTKygpra2solUrS0tLIyMjA5XLJJ2NSWsLTJlY7I7Pir+Mjs+K397S0tD0jsyBmvLq8vHwiSVVkawtfVxe+zk7CbjeCVouhthZDfT1ZmenMd/whQ/M/ISvrjPzZPve5z/H666/z//6Tz+OqLcNr2OK7V1cxapV8sCWN5WhsetWu2qd4oNXGtFdSdqAowtDQg9Zhayt897sPlm1oeFDRam6GfWK4nhTPKbESgGMjH8dKrKLRqOl5q1jBszOiOrMSxKhVYDXuTwSlFuet7m8D4CsqIXMpwAvm5MkASo2CvPdamfiam6Wrm2S97eSOGu/nln/QwGzpwJNM55WMeOn1+l2hz0cBKeQXYtumlEFZUFCAKIr4fD5WVlYYHx/H4/HIImCbzYbVak16INwvRsdisaBWq6moqKCoqIjh4WHGx8fltmBLSwt9fX0sLCxw+vRptFotbW1t1NfXMz4+LhuGrq6uEg6HsVqtzMzMoFKpUKvVMrGSfMDMZjNGo5GxsTGKiooYGBigrq6O27dvU19fz8TEBJubmzQ1NbG4uMjQ0JDst7W9vc3AwACrq6uUl5eTmZkpfyePGy8TCAQSiJRarcZms5GdnS3bUCSDxWJhY2PjoYHOh4H4YN+d5ClZyLukb9Lr9Y/t96bT6eRq1kmAGI2yPToaq04NDkI0isbpxHrpEvqqKhRx5Lbc+W66Rr7O4mofWbbYkMUf/MEf8PMv/yLvdX2QlAYl3xvX4g1E+PhL6aTolAx6NwCw76xY7QdBAJcrdvn4x2O3LS4+aB9euwaf/zx89rOx+yorE9uHRUWH2j6UtI3PEywWi0CsYnUsOFZiFYlEUp5HYvWsYMYdwmE/2E4yHA4TVawyMNYGgNFu5e0/m8U3ewXNe96T9DHmUh3WGj1LVzaxVuvRpZ9MUf+TuuXvF5gt6bzitSZS1Ste57WXkeqTnOFLremHVaEkjVp+fj6ATLQmJyfp7u5Gp9PJFa1kREuK0amoqGBpaSkhRicvLw+tVsupU6fw+XwMDQ3JHlVnzpxhfn6e1tZWKisrOXPmDB0dHdTU1DA6OkpWVhZTU1MUFBQwNTUlEyxJ9CyKIgqFgrW1NaLRKKmpqSwvLzM1NUVpaSldXV1UV1czOjqKWq2mtraWrq4uAFpaWhAEgYGBARYXFykpKaG6uhpBEBBFUfYRO2i8jN/vl4nU+vo6arUau91Obm4u1dXVB65im81mlpeXD7Tsw7DTxiT+emewr8FgIDU1ldzcXHma9iig1WoP3XLhcRBeW8N35w6+27eJbGygMBpJaWrCUFeHeg/xuDPzPMPTP2Zg8vtkplXzjW98g/z8fP71pX+HMUPL7UCEJa+anz+fSu79DsBKeBMVSszKQzBjzcyED3wgdgHw+6G9/UFF61vfgv/+32P3ZWUltg9ra2NC+cfE81ixum9M/nwSq2g0qj9uB+D/gxj8wSgrm2FOFx5s/QeDATYiN1jWZ6G3pvC+whayNH68HR2kNDWh2iOMNuddFjZHAsx8d53iX7MjKE5eNe+oTV3jdV7JQnslnVf8AXBtbU324xFFMSGodWfV62EH7c3NzUeaTIOYpsrpdMoWBH6/XyYaPT09Mmmw2WykpqbKry8Iwq4YnZs3b8qi7oyMDM6cOcPm5iaDg4OMjIxQUVFBc3OznMF39uxZbt++TXFxMRMTEzidTsbHx+WqSTgclgXqoiii0WhkKwKv1yu3CaempmSj0fT0dMxmM9evX6e0tJTMzEwmJiaYmZmhsLCQS5cuoVAoZJH+/Pw8FovlofEyEvl0u92sr6+j1Wqx2+2yT9XjkmGz2czY2NhDl0m2vcQbX8ID+wZpO0lPTz/Q9nKUOAovq4NCDIcJDA7i7exke3wcAG1xMZZ3vxtdeTnCPrpYhUJJufPd3Bn+GgvuHr7whS8w9NoE21e1+Fwabk9uUWjxUlv4wFl9JbyBTZUSG+o5bOj1cOlS7AIQjUJ/f2L78Nux7gIGA5w794BsNTXBI1REpfin5wkWi0XF89oKVCgUymelbXYQRKPRZ6cNeF9f5TiAvgpgfP51VnVge99lvvnLv877UhuIlG7i6+5m42c/I+2DH0z6OHWKkpx3Wpj++3VWb/uwnT15lgZP23tMEAS0Wi1arfahgdnxB9Hl5eU9KxDxBGx9ff2JjU/1er08IQgP2lyzs7P09fXJbS6bzUZaWpqsWSsqKqKoqEi2IYiP0WloaGB9fZ3BwUGUSiUul4v19XU6OzupqKiQK1YTExOkp6cTCARYXV2VrRY0Go38e9Nqtej1eiKRCHNzc6SkpJCWlsbExAQFBQV4PB6Wl5dpaGhgaWmJq1ev4nA45DDqubm5hHgZSXMlIb5dKtk36HQ67HY7+fn5nD59+tB0Q1qtNmGKdWerTiImOyucqampD9U3nQRI1cDjRGhpCd/t2/i6uoj6fCgtFkwvvIChrg7VI7rcOzIb+dJX/iNba/+DX3nPn0C/EVUGfGduC4dNRblpNWF5d3iTTNUxZSMqFFBdHbv85m/GbpubezB5eO0a/Pt/D5FIrE146lRi+9Dp3LN9qFQqn7uK1f3El+ezYnXcJl1HDak18SxgZiWIAOTY9i8Rb/rmGVttZTKvjgyVhXdbzwCgNJlIaW5m8803Cba0oMlNnoOVesbAapePuZ94MJfrUJtOlrg/FAqdeF+gg+q8pIPw2toas7Ozsj2BZAeQbLLxUTUzOp2O3Nxccu9/35Iwe35+nv7+/gT3+LS0NCwWC6dOnUoaoyPlEErmn6dOnWJwcBCLxcLa2hpWq5XFxUU0Gg1qtRqFQkEwGCQYDBKNRmWRulTVM5vNKBQKFhYWyM/PZ3x8XNZ8tbe3k5WVRUtLC1tbW/T19SWNlxFFka2tLZlIxQv8CwsLsVgsT/Q73/ldxV+Hw2G2trbo7u6WybHJZCIjI+Oxvqv/HRENBvH39eHr7CQ4PR0z8XS5MNbXoy0uRnjM766nu5c//n++S+OFfJrTf51tt5neIgV6nZJfbLbS1/WAfETEKGvhLap0jsP6WI+OnBz4xV+MXQC2tuDmzQdk66/+Cr74xdh9eXmJRKumBu5XNhUKhWxv8rwgJSVFDRxbu+y4pwKP8+WOHM9axSrdokKnfvhORhSj3Bn+a+5llBFVqNj4Rh+/2fO3fPnLXwYgpbkZb3s7np/8BPsrryT9/IIg4HiflaE/X2L2hx4Kfulop1geFeFw+JkwB30Y9tJ5dXd343A4sFqtCVNem5ubLC0t7ZryStZu3K8KIkXSSFOVkpXA4uKi7AMleTKlp6cnjdGRzE7v3r2LxWKRp/QkryOpMid9Vsko1OfzoVQqZdIVCATY3t7GZrMxMzNDfn6+7IFVV1fH4uIi169fT4iXgdjE38TEBG63O8GSoqSk5ECWFPGIry7uvE5WXUxNTSUnJ0eeIm1ra6O2tva5MmSMhyiKh76fFEWR0Nwc3s5O/L29iNvbqOx2zC+/jKG2FuUTVm23trb4pV/6Jez2dP7l7/5j1q6HCRtgXBfl4xfSsRgTBd5r4S2iiNjVJ2hoJyUF3v722AVi1ave3getw2vX4G/+5sGyTU3Q0oKmqgrhvizgeYFKpRIEQTi2KsiBiZUgCEqgA5gVRfE9giAUAt8E0oDbwD8VRXG/hvqzwUIOiKPYYRwFRFFkxh2kIm//OIV78630K7bZ0OdwLuDg67e+R0dHh3y/QqfD9MILeH74Q7ZHR9GVliZ9Hq1dTeYLZhZ+toFn0I/FdXKiHJ4lU9dHhRT5olAoZMKUDJIvUTwRWF1dfagvkXS9U7ej0WjIzs4mOzsbiBENSdg9NDQEIFe0mpub2draYnp6mtXVVTIzM9HpdExNTckTcjsnJwOBAEqlUm4LRqPRhCwzlUol3+fxeMjPz2dxcVEmmc3NzQQCAVmgL+VE2mw2ysrKHmqiKumbksWsJNPD6fV60tPTH8n3TJqeex6JlfTdHNbvLerz4evpwdvZSXhxEUGtRl9VhaG+Ho3TeWj741dffZXR0VF+9rOf4dCnsrWRxp1seE+jVRarx2MlvAmAbT+rhacJpTImbK+thVdfjd02NZWo0/rDP8QqiliUSjh9OtElfo8OxbMAhUKB8gA/RkEQvgy8B1gSRbF6x33/CvgTIF0UxZWHPc+jbO2fBAYAiZJ/DvhPoih+U/j/2Xvz6DYS88r3V9hBEARIgOAO7jtFUTspqdWL2+1Op922x05sTyZtT5KXOJnJOMnLcpKc9zzOTOY9x/PiLI4TJ7GT9tiJE7udtO14abvbstYWSYniIu6kSHAnAWIj9qXeH1RVAyRIkRJFUTpzz9EhRAKoQlWh6tb33e9eQfgr4OeBv7zLSu9icQcfj0orcHUtQSh6d2PQUMTDtfnXWShspEq0UpvMlzPZUmE4fpy1q1fxvv76tqX2/DPZePqDzP2bl+xKLUrtwdhWj5L32G4RjUZ3NPGYGpi9nc4rVfOztLQkC6aTyeQmJ+1UAlZYWEhhYaH8PqurqzidTsbGxuS4lrq6OtneQLrwJhKJ9YnUZJJEIrHpp2TgKhEaQRAQBIFIJILBYMDtdqNSqSgtLSUcDrO0tMTt27cxGo1YLBYaGhrIzs5OywTcyr8pdYIz9TOaTKY9deo/KNNzDwJStfF+iJWYTBKdmiJw4wahwUGIx1EXF2N+97vRHzqEYo8J6auvvsorr7zCJz7xCZ588kn6PrtEQJ0gUTbEkcpnMr7GGV+3WjjQxCoT7Pb1fx/+8Pr/vV78P/gBgR/8gMKxMfjbv113igeoqEhvHzY3r2u9HgEoFAoUCsVOTvp/D3wW+FLqLwVBKAPeCTh2srwdHe2CIJQCPwn8IfAbwvpZ6Rng3995yivAf+UuxIrHrGL1qLQCZ5w7Mwa9PvHPjFuryFHqORuvASGB0+mUtTUSBJWKnGefxf21rxHq7yfr8OGM76dQCZS+ZGb8C04W3/BR8sI+CTvvgsctuT0Ve/nZ1Gq17OqeCRuz31wu16bsN0nnlTrir9Fo8Pv9cjZeIpEgOztbJk6JREKOfJH0VKmfD5CnBKULt0KhkKcxV1ZWiEQiWK1WGhsbUSgU8nrNzc3J5Ck1W1IihQaDAavVuilb8kEitRr3uOF+BOwJv59gTw+BGzdIrK4i6HQYjh5dr07dqY4+CDz//PN86lOf4jd+4zeY6QvCSoLFihj5xn9lbsVMqe34pte44n6yFFqyFAdbu3lXmEzE3/EOFmtqKGxrg1gMenvfrmi98QZ85Svyc+WQ6bNn141MD+jU/52K1V35jiiKFwRBqMjwp88Avw28tpPl7fQ24k/uvKlExy2AJyXQcBa4a53wUSAhu8GjUrGadUXRqATyc7be3XMrPXQqw8RURj5ieQJxMUhMSOJ0OjmcgTjpm5tZu3QJ3xtvoG9u3nJ82WDXYjlhwHktQG5rFlmlDz+641HZb/eK/fqe7SQwO9XPy+/3s7S0RDAYlEmNVquV9W6xWEwWqyuVSlmwnul9BUEgkUjIBEvKE9Tr9fK4+O3bt5mamkpr05lMJoqKimT/poNwTlIoFI8tsZL2z04hJhKEx8cJXr9OeHR03cSzooKcp59G39SE8ACTDSKRCLFYjOzsbH77t3+bYCTJxOsestTwzAeKuT5qY8TxHUryj7JRruOM++7uuP6IIG2fqdVw/Pj6v1/7tXWX+Nu33yZaly/Dd7+7/lyVaj2CJ7V9WFDw8D5ICu5UrO6pbCoIwkusS6B6d3q+uOuCBEGQ+o3XBUF4Svp1hqfe9dsjiuLDP4vtIR4VjdWcK0pRrhrFFp5SyWScNxdex2Ox86zxEGUaK9PiNAqFgqKiIqqrqze9RlAoyHnuOVyvvELg+nWyT53acvlFz+bgHQox+y0Pdb9s27PPda94VPbbo46d6rxS229arVY2Vb1zMsxIrqRoIrVaTXZ2dkYt2KOio5MGCkpLSx/2quw5nE4n0Wh0y2MgFZHpaVb/+Z9J+v0osrPJPn163cRzQ9TQg8InPvEJXnvtNbq7uzEYDLz+QxeVftCfycKco6He/gLdw19k3nmTkvyjeL3rsXOhZJSVuJcG3eOx/+LxOMvLy5n/KAjrTu9VVfDyy+u/W12Fq1ff1mr9xV/AH//x+t9qatYDp9/znv1Z+S0wOTlJLBZr2+3rBEHIAn4feG43r9vJmecM8JIgCC8AOtY1Vn8CmAVBUN2pWpUC83d7I4VCoT9//vxu1u9AI5FIEIlEOOifKR4sYD5s5F9ffwuzZnPEhEiChHGdF49M95N0rZ8MRVHkU5/6FMCWn7FKqWS6t5eVO0aFmaD0azEGSgkrApz/0eBDbwgHg0E8Hs9jqbPy+/0H/nhMhSiKshg907+tINkuRCIRmYQJgiCTMen/jwIkk8+9cGA/aIjH41y/fn1nIn6Ph+JwGCXgV6uZCoeJDAw8+JW8g/HxcUZHR3n11Vex2+0E3EVANtdm3Ez88BZa1RoooP9WF2Osa6q+e+mH9BW7CWniJMY8nA+e37f1fVCQvle7Oo8YDPDcc/DccwjRKMaxMUwDA1R+4QssfPGLjD3gyKa7YXp6+l7tnqqBSkCqVpUCNwRBOCmK4uJWLxJ2U6a9U7H6zTtTgV8DXk0Rr/eJovi57V5fXl6+OD09fTBqg3uAYDDIwMAAJ0+efNirsi1C0SSf//4ysYTIx95lw6jffJKLRP383fQ/Mp9l5J2qYsojlcRiMaqrq2Xdy8YKgBiPM/8Hf4DxmWfIeeqpjMuO+ROMfX79glH7S/kHwtPqxo0b8lj944bz58/z1Bb7Yr+RTCbTNFiplalUfZPkKSa5i8diMQRBIBqNyrqrjVAoFHKOICDHAUmaq1AoJOu8MlWzJKuDg0C+xsbG0Ov1j2XFqrOzk5aWlh1VrACSkQiBa9dYu3KFZDCItraWnKefRrMP22Z5eZmamhqefvppXnvtNZKJJH2fWmReK3LDLvBEY5RV1x/R0fLLFFoO8drV1xmuWCMhJvmQ5QmqtI/Hpc3r9TI5OcmRI0fu/82ys+FjH1uvWj1EfOlLX+JXfuVXfnttbe3Td3vuHY3VtzdOBd752xRwfC+nAjfid4CvCoLw34Ee4At3e8F+u/A+aEi6joMOvUbBh5+w8Nevr/DPl1f56DNWlBvaglqNkZcrPsxfzn2DN5IzPBP0UqxqYm5ujo6ODv7gD/6Aj370o2mvSd6JPdjKMyYZE7n9Dy4S4SQ1P289EKQKHp39dq/Yr1anRGAyTdSlkhqJyJhMJgoLC2XxusvlYnV1lUgkgtFolNt+Op2OUCgkT/xtPG9IbUClUpn2HEEQZBfznJwc2bBUEq+HQiG8Xi+Li4ubyF2mycb9Eq9LE5aPI3Y74KPQajGeO4fh1CmZYK389V/vC8Gy2Wz83u/9Hr/7u78r36BYmvUo+kMsm9W80S+So/0g7UI+t0IOekpdmIRs/oP1SfIPkn/VfWLPhrJEEYLBAyFov1MBv6udvCAI/wg8BVgFQZgFPiGK4l25zUbsiliJongeOH/n8SSw21LNY8WsdivMfJgoMKt5z0kzX7/q5vs9Xl44tnlCL0tt5OeK38NfLH2bi1on53w3OFv9UygUCr72ta9tIlaJQAAARYYvjiiKOP7FTWg+RsWH8tAXPXzRuoTH0VlYgvTZ7vdCLYriplgd6XE4HE6zW5DIiMVikf+fWt1MtVtYXV1FFEXy8vIwm83o9XoWFhYIhUJkZWXJ7Tzp9ZJIXRRFeeggtdUn2S5InzcUCpGfn09eXh6hUIjh4WECgYBst1BcXJzmWyXZLUifLRAI4HQ60+wW1Gr1JtK1l3YLj7P9x72S/IdFsD7+8Y/zuc99jldeeYWnnnoKc7Oe1etB3luazfnsm/RMlfO3b8aI1Yxgylbzi8XvxKB8vPzH9uzGLBRaJ1cHwIz5jl3LXYmVKIofvsvfK3ayvH1Vdz4qJGSneNQqH60VWcy6orw1GqDUoqG1YjMhytWY+Zn8d/D3zh9xTb+MbeZ7/NRP/RR/+qd/isfjwZySt5WUiFWGL87Sj/x4B0IUvTMHU+PBMQeFx3u8XQq+1eu33+aZhOPS460MQgsKCuTH2xGKWCzG4uKiTKTgbYPQ2tpa1tbWcDgcjI2NyX5XDocjjVTFYjG5KgXr+0z6nVSlktZBFEW0Wi1ra2uYzWaMRiMzMzOyILytrU02CB0ZGWFtbU22VbBYLOTk5KDX68nL25wQIBHM1O2zsLCQZhCqVCo3ka7dGIRGIpEdeY89irhfc9D9Jlh6vZ4LFy7IgeTZlVqUegHfUIiixls4msdxOo7DUBNavQ+hTAOPGSfes6lpKcj5gBCrZDK5byf9/R6beayY1cMIGb1fvOuIiQV3jNc6PRSY1RSYN48vV+qKOCPUcMkwwRurvRw7k0/sf8Z47bXX+MhHPiI/byti5e4PsnTeT+6RLPLP7lug+I6hUqkeu5BRCVIcjBTuu7HaFAqF0iJtUkmAVHHabbBvNBqVc/ZWV1dRKBRYLBby8/Opr69HrVbLkTbDw8NyvExhYSGjo6OYzWYKCwtZXl7GaDTKgxPS90ur1cpVnTt+NGg0GtkoNBKJyITLbDYzNTWFxWKhsbGR5eVlrly5QnZ2Nna7ncrKSmA9ssTlcjE2Nobf7ycrK0smWiaTSf78giCg0WjQaDRpNxWpiMfjadt4ZWVFbj1KLdFMGi9J5/W4uq7D+rbZi2rcfhKsiooKAFwuF1lZWeTU6/EOh7h6SMlqjoon7DGUM9n8eEDkL767xHtP5VJb9Pjsvz1rBd65PhyUVmBiH++m/3fF6j7wKLUCJSgVAj99Jo+/+v4y/3jRxS+9y4Zes/nupE1dweyai6k80IcHKCqx8rWv/XNGYqVMIVaBmSgz/+LGUK6h9N3mAyEO3ojHgVhJuXkbtU0ul4vl5WU0Gk2aOafRaKSgoAC9Xn/fwb5SCLNUkVKpVFgsFgoKCmhsbJQrFFIIs8PhkEOYz5w5g8/nY2hoCIPBQHNzM8PDw5jNZnQ6HSqVCq/XKxMnySxUpVIhiiJ6vV4OYxZFUf58breb8vJypqensdvtqFQqbty4QWFhIadPnyYQCOBwOLh16xaFhYXY7XYqKiqoqKhAFEUCgQAul4uJiQl8Ph96vT6NaG13By+FQd8tMFvaR16vV25/xmIx/H4/PT09GAyGTQRsv3ReDxJ7uf77RbAWFxdpbGzkd37nd3j5pV8ieVNE4yzkeKGXd5a0Es+OE14ZYSJUzv867+JEjYF3HclBo3r0/fH2rBUoEasDULGKx+OiKIr71l7aV2KVfJT6ZjvAo9YKlGDUK/npM3n83RtOvvGWmw8/kYdiwxdJrVZz2FdAtFjBTFELH/jFk9QUNZAUEyiE9TvQRCAASiXCnbvtqCfO1D+6UBuVVHwoD4XqYF4Q1Gr1gSdWUvspkzhccldPvQhLrua5ubmIopjRe+xeIbXRXC4XbrcbtVot65Wam5s3VSS8Xi8OhwOn04nNZqO5uRmj0YjH46G7uxuVSkVraytut5v+/n4aGxsZHx/HZrMxNzdHYWEh4XCYQCAg7yeNRkMikZDDlyUtmdTWKyoqYmZmhqqqKrxeL2tra5w8eZKlpSUuX75MWVkZLS3rQz4LCwv09vYiiiJlZWUUFxfLgdbl5eWIoiiT1Nu3b+P1etHpdDLRMpvNu2qVbBWYDesXsfPnz9PW1ibv30AgIFe9UmN1MlW99krn9ajhQROswsJCnnzySf7wf/whwecLeEn9DA0DSirsb8c05WUleeeTNt7o83F1eI2JxTD/rj0Xe/6j7b6+Z+kNB6gVuLa2FgOC+7W8/SZWicdgUMvXAAAgAElEQVTJnPFRrFhJKM/X8vxRE9+57uXCLT9PtaTfbatUKsR4kg/nneWvVr6P/edepuT2JbqHvsjxhv+IQqEiGQiguCM4TkSS3P6HVZIxkeqPWlEZDq7wQKPRyOZ+DwNSsG+mNp3kaaRSqdIuoDabLWMA8kbE43FmZmbua/1CoZBMpDweDxqNBovFQmlpKS0tLRmXH41GmZ2dZXZ2Fp1Oh91up7m5GYVCgd/vp6uri3g8TmNjI3q9nps3b6LT6Th69Cg9PT3U1NQwOTlJZWWl7Jaem5sr+1UpFAoikYjc+ovH46jVaoqKimQSVFFRwdzcHFarlYKCAjo7O6mtreXcuXPcvn2bCxcuUFlZid1up7S0lGAwyMzMDJcuXcJkMmG328nLy0MQBAwGAwaDQdbaSMuYnp6mr69P3iZWqxWz2XzP7a5IJCJPJW6li0s9XqRjxePxbBkEvZGAPSxh/H6c6x8kwfqFT36cb337W7z5p1/np599EsVkBVnadaIv5R+qlQLPHzFRX6LjX95y84U3nJxtyObpQzmolI/mdW7PQrMPUCvQ7XZHAf9+LW9fiZVCoQgFg0E5wuJ/4+HiVK2BWWeUH/X7KcnTUFv8tk5AapeZVAZ+Ou8srzjf5Fa8hov/8E/EPxjhZNMvkgwEUBoMiEkRx6tuwksxKv+DBZ3twcVO7AW0Wq1cCXgQEEVxS/8mSd8kVSCki19ubq5cgbifi5HRaMTn8+3qNcFgMI1I6XQ6LBYLdrud1tbWLe9ek8kkKysrOBwOgsEgpaWlnDp1SvalCgaDjIyMEAgEaGhowGq1srCwQE9PD01NTeh0Oq5fv05rayvj4+PY7XYcDgdVVVXMzs7idrsxm82o1WqUSiU+n0/efrm5uRiNRpxOJ4IgYLfbmZiYoKmpidnZWUKhEKdPn2ZgYICFhQVaW1spLy9nYmKCCxcuUFNTQ0lJCfX19dTV1cmkqb+/n+LiYsrKytKIjrSvysrKgHXy6XK5mJ2dpb+/X67iWa1WcnNzd0xmfD7fXf3UBEFAq9Wi1Wq3DcxOPd5WVlY2VTgzabykaJ8HgZ0Ggu8F9pJgiaLIpbUhOq2LnPvIi1x85d+YebaH4lg7yhU1WNkULF1p0/KffsLG93q8XBxaY3QhzPvb8yjMPdjnwky439BsGQeoYuX1euPA2n4tb1+JlVKpXPP7/f+bWB0QCILASyfNLHljfP3qKh97l43c7PVDIlWHVKm18S7TEX79H3+d66/8mBOnK0gkP0t1SI/GYGDhBz58w2GKXzCRU3vwRZxarVa+QN8LJM1MplZdPB6Xw4elC5jRaMRms5GVlXXf+qa7QWpzblUtSNUTOZ1OWU9ksVioqKi4q54I1t3dHQ4Hy8vL8qRfqrA7EokwOjqK2+2mvr4em81GPB6np6eHeDzOmTNn8Hg89PT0cPz4cSYnJzGbzYTDYWw2G7Ozs9jtdmZnZ/F6veTn58vibsmqIScnB6dz3aOvvLycwcFBjh49yo0bNzh27Bjz8/PcvHmTY8eOye3A5uZmGhoaqKysZGxsjImJCerr6ykoKMBqtWK1WonFYszPz8tu4Xa7ncLCwk1ESTL0lEw9w+EwLpeLubk5BgYGZN2ZRLS2ulDthFjtBGq1GrVafVedl3Ssut1u5ubmCIVCGY/ZVAJ2r8fsw5h2vF+ClRCTfMvTxY3gJC16Ox/7fz5P49freb3nm7ycfZTIeBY0ZiYfWrWC95zMpaFEx2udHj7/+jJPH8rhbEP2lnFiBxHxeHxv9tsBqlh5PJ44j3HFyu/3+yksLNzPxT5wPMrtTY1KwYfPWvir7y/z1Uur/MKz+ahVwiaBd7uhjpfe/16u/c13GZkoINs4SbhETc3su/FdXsNywoD11KNBmKWJua2Qeve/seqU6e5f0jc9yLv/3cBgMBAIBMjOzkYURXkCzul0pk3AVVdXp03AbQeJcMzMzKBSqbDb7TQ0NKQRjlgsxvj4OEtLS9TW1tLS0oIgCDidTgYGBqiurqa0tJTZ2Vmmpqbo6OhgenoaURSx2WwMDAzQ0NCAz+fD4/FQUlLC+Pj4up7ljhWCUqnEbDbLnlPNzc2Mjo7S2NjIyMgIR48e5fr167S3t7O0tMTVq1c5efIkeXl53Lx5k8XFRZqammhpaSEUCjEyMsL4+LhcUVOr1ZSXl1NeXi7bQoyOjsoVvK22l06no6SkhJKS9Sx6SeC/uLjI4OCgPClptVrJy8uTL8per5eampq92O3bYjudF7wdmC0d736/n+Xl5bQqq1arzVj12qrK+jCnHe+FYIWSUf5p9RKTkSXOGZt5xngIhSAwMjLCtOs1Yhfm8A7pKPnJdQuOrb7r9SV6/tMLGr7d5eGHvT5G5ta1Vxbjo5FdGYvFduyUvy0OkHjd6/WKPK7EShRF39ravlXj9gXS5NKjEviaCXlGFe/vyOUrF1b5dreH957aPM0nCAK/8Y6P8uni3+dr3/o+H/7QXzJ96Q28szUYKpWUvLCzC/TDhhTPE4lEmJ+f32R8mUmvkp+f/9D1KjuFKIoYDAZGRkbSxN1Wq5Xa2lpycnJ2vJ9EUcTpdOJwOPD7/ZSUlHDs2LFNWqB4PM7t27eZnZ2lqqqKc+fOoVAoSCQSDA0N4fP5OHXqFDqdjrGxMVZXV+no6GB+fh63283Ro0e5cuUKR48epbe3l0OHDnHjxg3y8/PJzc0lGAzKJ3ppn8zMzFBaWorP50Or1cqBzD6fj0OHDtHV1UVHRwc6nY4rV65w8uRJTp06xfT0NJcuXaK1tZW8vDza2tpYW1tjeHiYsbExGhoa5HZbdnY2TU1NNDY2srKywvj4OIFAQK5USS3PTNBqtRQXF1NcXAyst8Wkic3h4WEA8vLyWF1dvavn2H4gNTDbYrFs+rukbdtY9UrVBW70PfP7/fL58WF9b3ZKsNzxNb7s+jGr8TXeZz7FEUOV/B6FhYUMzq7gUQ9Q6S8nMBMlKm7f5jRo1weE+qdDfLvbw+e+u8zzR0wcr8k68OfJx7EV6PP5RB7XVqAoih6/f99I475Aar08ysQK1u+ynmoxcn7AT6lFw4na9S9DajVOp9LwoQ98kL/5q8/zg+k5nrz5AWJ6D9N136Ik9jGylJtPyPsNyUk7U5sudcIqFovh8/kwGAyYzeZHdsJKFEV8Pp+skQoEAmi1WmKxGEeOHElzGd8pgsEgDoeDhYUFcnNzqaysJDc3d9P7JJNJpqenmZqawm63c+7cOfkC6vF46O3tpaysjObmZgD6+voQRZGTJ0/idDqZnp6mo6OD4eFh7HY7kv4yFAphtVpxu91YrVbGx8dl8pGVlSVbMBQXF9PV1SUL4E+dOsWVK1c4deoU1dXVdHd3y5qva9euceTIESoqKsjPz6enpweLxUJ9fT3Z2dkcP34cr9fL0NAQCoWChoYGua0mCAI2mw2bzSaL9K9du4ZWq8Vut1NQUHDX40aj0VBUVERRURGwXhWYm5tDEASuXbsmtzglI9WDZhgqtQp1Ot22Oq/U6u7q6iqCILCyspJxkjX18YM+f24kWP7Ll2WC5X/6GP+sHCYhJvlZ61ObMv9EMUnPzQF+52Nf45PvifDRwY8QqVqPYdoOgiDQWpFFuU3Lv15z861uD0OzId57KpecrIN7g7Zn17MD1Aq8ozt9PCtW8Xjc+7hVrB4HTyQJT7UYmXNF+c4ND4W565qNWCyWdpL/2Q/+e774+b+FL/qJFynJP7XEIqtc7P1jzhz6L2RnPdggUinYN9NEXWr2m3TSlqo1G7PfOjs7KSsre+T0fqIo4vV65dZeMBiUc/EaGxvlVs/58+d3Rari8TgLCwvMzMwgiiJ2u50nnngi4wlWFEVmZ2eZmJigqKiIs2fPym2RZDIptwOPHj2K0WgkHo9z/fp1zGYzdXV1eL1eBgcH6ejowO124/f7aWpq4tKlSxw/fpyBgQHq6+sZGBigvLycsbExmbjo9XqCwaBcydJqtSSTSXJycnC5XBw6dIienh46OjoIh8PcvHmTI0eOcPLkSbq6umhqasJms3HmzBnGx8e5dOkSbW1t5OTkYDKZaG9vx+Vy0d/fj16vp6GhIa0totFoqKqqoqqqCp/Ph8PhYHh4mPz8fOx2+471UlIAdGVlJdXV1cRiMdxuN06nk/HxcZLJZBrR2q46dlCgVqsxmUyYTCYA3G63XCWFzd5rq6ur8vdYMlJN9V5LrX7tlTZxI8G6OdPDm4keDGGBn9UdpzhDkHIo4qGyJpemljr+4vwf8RMnXkJZHMFqte5omaYsJS8/ZaFrPMD3e3x89jtLvHjczKFy/YGsXj2OxCoQCCiAwH4tb1+JVSQScT2OFSvpgv6oQyEIvL8jj89/f5l/uuSivVC/SYB66sQpOv9kGHFRxYXn+2jJy+Jswa9xpf/Pudj7x5w+9KuYsu99xHmji3WqDUFqsK908jWZTBQVFcku1jtFVlYWgUDgwBOrZDKJ1+uVK1JSwLDVaqWlpUXO19uI7Oxs/H7/thd6URRxu904HA7cbjdFRUUcPnx4y20iiiILCwuMjY1htVo5ffp02rGxtrbGzZs3sVqtnDlzRrZI6OrqoqysjPLycoLBID09PZw4cQKFQsGtW7c4deqUXB1TKpWEw2Gys7NlY9DUNlJWVhYrKytYLBacTqc8SVhXV0dnZyfnzp3DZDIxOTlJdXU1/f39DA0N0dTUREdHB52dnYTDYex2O7W1tdhsNnp6eigtLaWqqgpBELBYLJw+fZqVlRW6u7tlQrhRL5STk0NLSwvJZJKlpSWGhobkGJ3S0tK7Ho9LS0s0NDQA6+cRqSoG698DiWhNTk6SSCTIzc2Vidaj4NQeDAbT2pxKpRKj0bhlpUfSeUnfe7/fz9LS0rZpAdLj3U7TChoNN49Y+UG1jeKQhnd+cxzRM4wzgwYrEFpGoRD4b//993jvu1/m717/PB85+iG01Tsnu4IgcLI2m+pCHa9eXeXrV90Mz4V58biJLO3Bql5tpx/bFYJB0OngAMgnYrFYUhTFfauA7CuxWltbW33ciJVGo3mgo/v7jSytgg+dzeNvfrhCz3IedVXhtBPhwut+mFdT2B4mJzDNj4vM2FX1PHH4N7jc92dc6vsMHS3/mbycyk3vnSl3LZU4Zcpdy8/Plz1+9rJdYDQaWVtbky9kBwXJZBKPxyMTqUgkgslkwmKx0NraumNRaVFREfPz8xmJlRQvMzc3h9FoxG63c/jw4W0vTMvLy4yMjJCTk8PJkyfTLpiiKDI1NcX09DSHDx+WW0WBQCCtShSNRuns7KStrY3s7Gxu3LhBTU0NWq2WsbEx2tvbmZ2dpbS0FI/HQ25uLqFQKG1ZUmRPdXU1DoeD2tpahoeHaWpqwmq1Mjs7S0NDA5cuXcJms9HS0kJ3dze3b9+msrKSjo4Orl+/TigUoq6uDpPJxNmzZxkeHubq1au0tbXJZNVms5Gfn8/CwgJvvfUWNpuNmpqaTW06hUIht/nC4TCzs7NcuXJF9sHKz8/ftG2lG4itiK9KpSI/P5/8/HxgvdojEa2pqSlisVga0ToIOq1UiKIoe43tFKk6r63ec2O+pXSzkSnfcmPVS6p6bpz8e19xO8r/FN/UIpQI1lpoGYDn3vkiL734El98/bO8cOsnOPz07quIFqOKn382n8tDa/xowMfUcoT3nMylvuTgEOU9s8kIBA5EtQr235x8X4lVLBbz+ny+GPDwR6f2CA/aE+lhoChPw0sncvnGW24uDEf4wB3u4excw3UtgNgQ4Cd/63283FhP/p/9R762eoVfsr2Ls4d/nct9f8blvj+ltvDDKMU8mURJ20itVqed9IqKimTitJ/6puzsbObm5vZteVshkUikEaloNIrZbMZisdDW1nbPF8yCggImJibkishW8TJ3u/Ctrq4yPDyMVqvl6NGjm6pZUrvNYDDwxBNPyNUlt9stt+HMZjOJRIKuri5ZHD4/P08ymaS0tJTp6WkKCgrQarXMzs7S0dHB7du3sVgsacJ1WK9YBYNBdDqdXMXIz89naWmJmpoarl69SklJCW1tbfT09HD27FmOHj3KW2+9hU6no6ioiBMnTtDf309vby+tra0olUqam5txuVx0dnZSVVVFWVmZHPZcXFxMYWEhMzMzXL58mZKSEqqqqjISfZ1OR01NDdXV1Xg8nk0xOtL2W15epqBg521zpVIpW0JA+nHjcDiIRCIy0bJarQ+daEWj0T1vX6bqvDJBunFLrXb7fD6ZiImiSFIlMFDsxqkN0Zoo4Wy0mpA/sG6LsoUGy9uaQKlQo9OY+PT/92naDh1hoPsW71I+cU+fQ6kQONdspLZYy6tX3Xzlgotj1Vk8f8SEVv3wNZ57GsJ8QDoCiUTi8SVWgP+OA+pjRawCgX1r3e4b2iqzGJ520zcn0OAIUR4VmPs3L1nVKnKeMTH3q4t8OxbjE/O5vFkwyz+M/4CWxVyytU/jEr/N/OoV6op/CovFsknfdBBgNBp5GNXTRCLB6uoqLpcLl8uVVnmw2+17dkFUq9XodDrm5+dlPVZqvMzdIOX5AbS0tGSsrMzNzTE6Okpzc3Na5U9qi508eRKDwYAoily/fp2SkhI5rmZkZIQzZ86QSCSYnJzk7NmzeL1e2TfJ5XJht9tZWlra1E6Sbj7NZjMejwe73c7Q0JBcNZqenqayslIOeW5oaODEiRNcvXoVrVZLXl4era2tjI2N0dXVxbFjx2TfqTNnznDr1i0WFxc5fPiwTA4UCgXl5eUyEbx48aJsy5Bp4k0QBHJzc8nNzSWRSGyK0VlcXKSurm53OzUFSqVSrlZBeqXz5s2bhMNhTCaTHMOzVcv4QcHv9+/oONtLpAZmSzqvVHjiAf6X8zyriTDPKBqpiJlZXV1lbm4uTeel1+vJev55sqen4dYt3FnLaE1qYkvL1NXV0ffdYQLnFUSWE+gL752AFOVq+Ni7bLzZ7+Py0BqTixHe155Lhe3h6en2NEnkgFSsRFEkmUzuqxB6v4nV2h2jrscGWq2W1dXVh70ae4J4PJ7WnqsxrjK7YuRrl0XeMZMgByWr1Q4iTj0ffOEF/uzLX+bXhm6TXWKiwGbhqYYzANwYmWPBdZPikiI5V/CgQaPREI1GH7gHWTweTyNSklbGarVSWVn5QETJ0uSa3+9ncHCQlpYWOV7mbggEAgwPDxOJRGhoaJD9oza+f39/P0CacB1genqamZkZWX8liiIDAwMYjUY58Li3t5fm5mY0Gg0TExOyHsnhcGC320kmk0SjUVmovnH8X7JykHRWdXV1RKNRwuEwVVVVXLp0ibKyMmpra7l8+TJut5vc3FxOnDjBtWvXOHHiBNnZ2dTV1eFwOGSvK61Wi1qtpq2tjcXFRa5cuUJjY2Oa755SqaSqqgq73c7k5CQXLlyQK1xbbV+lUinrroLBILdv32Z5eRmVSkV5ebkco3M/UCgU5OXlyftL0uZJQvxUbZ7FYsFgMDzQ497n8+07sdoO89FVvuz6MXExwc9anqJal9lLMXU4JmSx4K+uJrTy92S5kyz8zd8w3d6OUpXN0koY5YUouWc0crvxXm4eVUqB59rWI3G+8Zabv3vDyemGbJ5pzUH9ECJxdtu+3RaBwIGoWIVCIRQKxdbGhQ8A+02sVpeWlh4Ppfcd3K+L934hU5k8lURJ+qZUTUKBLZ8jfgchQyNjwRDH12BhuJSSJ3P4vz/9Gb7+zW/yu5/8JO9/6r9jzHpb7GnLbcSxdBWPf5q8nKpt1urhQq/XEw6H97RtEovF0ohU6nRXVVXVA5vuSo2XCYVClJSUcObMGd566y3y8/PvSqpCoRCjo6P4fD4aGhpkbc9GLC8vc+vWLerr62WPJlg/vkZGRvD5fHR0dMhVnImJCWKxmByA7HA40Ol02Gw2YrEYDoeDJ554gkQiIU/1ud1uueKwUWMFb+usrFYrN2/eBJCNR2tqaigrK+P27dvU1tZy5MgRurq6OHv2LFlZWRw9epTu7m7a29vlTEOdTsfVq1c5ceKE3KorLCwkNzeX3t5eFhcXaW5uTrvgqFQq6urqqKioYHx8nAsXLlBXV0dRUdG2F1epItfU1EROTs62MTr3A4VCIVfMampq0qZJb926RTAYxGg0ykQrOzt7T4mW1+ulsnKzzvJhYDg0x9fclzEodHzU+gw29eZqlgSFQiHnRAIkk3FGLkWw1HWg6hulNRrFUWDgmb99ip9z/Aq/3vbL8nTuVnKHVCPVrb6H5flafuV5G9+/6eXy8BpjC2He355LUd7+2m5EIpG9O0cdkFagy+VCqVS693OZ+02sFmZmZva11/mgcTcX7/1CJmGn9DiTsFOv11NQULBJ2LnxPScmJnjxRB7RI0lu/d0K9tk4r1/x8HqWwAdf/i0+89n/i+p/vcizHz0sv86W2wAILK0OHmhiZTKZ8Hg893Uxi8ViMolyuVzAuvGj1WrNKHTea9wtXqawsJD5+Xk5424jotEoY2NjcuWntbU14wU2Ho8zODhIMBiUjTclJJNJent7USqVnDhxQn797OwsKysrnDp1CkEQCAQC3L59m7NnzwIwOTlJRUUFKpWKubk5CgoKEAQBl8sla4k2aqzgbWKVn59POByWtVpXrlyhurqayspKLly4QEVFBQaDgYqKCgYHB2ltbcVkMtHU1CQbiKpUKmw2G1qtVhbWS+J7rVbLiRMnZG3VoUOHNlXPJJJUVVXF6Oio7OKeSbAO69+pubk5Wd+2mxid+4EgCJjNZsxmM9XV1bL/mcvlYmhoSHbqlzRa9+J/loqDUrF6a22U73pvUKTO5Wcs5zAqd/ddD4SdiCQx2WownDAR6OzkC6+9RiwR4yfq3kdtTS1CSlxNpgGdhYWFbQd0Uh+/dCKXhhI9r3W6+fzrK+uROI3ZKPcpEmdPiVUgAFt4nu0n5ufnEQRhdj+Xud/Eanlpaenhq/P2EPtlt7BxFDm12rTVKLI0LXSvwb7Sa0RRRKNS0PzTVkb+fIl3x1QMlyjp7/gI71fm01DRjmcxi3iWiEopoFFnk2ssZ9k9SGPFi3u6HfYSJpMJr9crmzbuBJKDtsvlkg0QJSJVV1e3L5E2krnk7OzslvEyEioqKujq6qK0tDTtGIjFYkxOTrKwsEB1dTVNTU1bHiNut5ve3l4qKio4dOhQ2vPi8Tjd3d1YLBZqamrkv0k2AR0dHSgUCkRR5ObNm7S2tqJSqYhGoywsLHDu3DlgvZJ16NAh+bWHD68T9UypBpKAHd7eh7m5uRgMBnmasLKykvHxcRobGykvL+fatWssLy/LlgaRSITu7m5OnjyJQqHAZDJx6tQpurq6qK+vl9t/UsCzVB0zmUwZt7VOp6O1tZVAIMDIyIjs4r6RiC0tLZGbm5t2nGwVo5OXl4fdbsds3pyEcL8QBEH2nKqqqkIURfx+Py6Xi9HRUaRMV4lo7caxP5FIADzUlIKkmOT73ptcDYzQoCvhA7mn0Sh2f7nzBxcBMOoLyHlHK87r13nlK1/h2dPvotxYTdSdQGt5+31TdV6pNzip2Ggps7KykmYpo1AoOF2YRZ/Twht9PgamfPx0uwFzjuGBn1/2NN8xEIBdhF8/KCwsLBCJRG7v5zL323k9Xlpa+lhprPbqhLfRPC/1Z2pIqnSHYzQaKSgo2FPzvEzQ6XRyu0xjUlL0zhzm/s3LMyezefYdAv8WKWY4ls3lqwluDSxyrNrA8RoDttwmRhzfJRoLoFE//HJwJuTl5TE1NbXtc6TMN6fTidvtRqlUkpeXh81mo6GhYd8c93caL7MRer0eo9EoT6ElEgmmpqZwOBxUVFTI8TOZkEwmGR0dxel0prXJJITDYbq6uqisrJTDiGG9WjEwMEB7e7t8IRgfH0/TAI2NjVFVVYVCoZAvKNnZ2fINRFZWFslkMuNxrdfr8Xq9AFitVlwuF7m5ubKnlfRY0j9ptVra2tq4evUqZrMZjUZDWVkZoVCIvr4+2WoiKyuLjo4Ourq6CIfDVFRUyMuU/jY5OSmbimYSSBsMBo4ePYrP55NjchobGzGZTIiiyNjYGEePHt1yf22M0ZmYmCAQCFBSUkJZWdkDayULgkBOTg45OTlUVlbKYd2SYanP55Nv1qxW67YZk16vd0tSsR+IJuO86r7KUHiWDkM97zK1oRDu7X5eslrIzipAodLzDb8fbzDIr77/p8ANwbloGrHaCVQqlbytNyIQSTDoCDIwHWRpLX7nd0nGJ26TjAU3mSBvtJS43yGhTK33e8YBaQXOz88nnU7n+H4uc99zWBKJRORxiIBJhUqluqupmlQezkScMsU9HJRgX2l6TvqyWU4YcPcGmf+ul/pfLaA0b5EfiDf41m/+Jb/+//4TF27VcHHQT6WtFSE+yLJ7mFLbsYe2/ttBp9MRiUTSBOzhcDiNSKnVaiwWC0VFRTQ1Ne37cbvTeJntUFtbS09PD8FgkKmpKUpLS7d0VZfg9/u5efMmBQUFnDlzZtPy1tbW6O7uprm5OU2PFQqFuH79OsePH5fbhV6vl4WFBbkFGAqFcDqdNDU1ATAzMyO3Kr1e77b6KlgnOQsLCwBYLBb6+/upqakhPz+fW7duydl0NTU1jI6OcujQIXQ6HfX19fT393Ps2DF5u/T19TE6Okp9fT2w3tprb2+Xva4aGhrkzy4IAtXV1eTn53Pz5k2KiorSqnSpkPy+3G43g4ODqNVq8vPz0/Q722FjjM7c3NyuY3TuB4IgyKHN0tBBMBiUK5Ferxe9Xp9GtKT1cblcGYce9gNriRBfcV1gPrbKC6ajtGfX39/7BZfQanJQq9aPw9euXuVEZSXHIk6cKgjNx8htvc91DiUYmgtzyxFiajlCUoTcbCWnG7JpLtNTnKdGEN5u5W+M7QoEAnLVKzW2ayPp2klsVzAY3FUFf1sckKnA6enpQDKZnN/PZe47u1GpVMtLS0vlUgr848+ym5QAACAASURBVADpDlqpVGY0voR18pV6gNtsNtm/6SAH+2ZnZ6cZaQoKgdKXchn9q2UWXvcSLS/AqgYSMX7wpU/w6rd+wPWJINcnAoSiP8PipQBnm9Y4UpWFXnPwusAGg4GxsTGCwSAej0fWvZSUlNDS0vJQ9s1u4mXuBlEU8Xg8cptn4xRfpudPTk4yOzu7ZVVmdXWV3t5ejh49mvb3WCxGZ2cnra2tsr4mkUjQ29tLW1ubfEIfHR2ltrYWQRAQRZH5+XnOnFmfKE3VV4VCoYxmkVlZWfL3SnoskePCwkIWFhYoLS2lpKSEiYkJWadVXFzMwsICc3NzlJSUrGe5tbbS2dnJ9PQ05eXlALJWbGBggJ6enrR1h3XSdPbsWUZGRrh8+TJHjhzZkizl5ubS0dHBysoKnZ2d2Gy2XVcFNBoNlZWVVFZW3leMzv1AEASZFErbSSJaU1NTeDwedDodFouFpaUl2traHvg6bcRyzMuXXT8mkAzz4bwnaNDffxtqLbSIUf+239ibb77Jd778ZUSHA7UhQHDu3tpm/lCCwZkQt2ZCTK9EEcV189CzTUaay3QUmtVb3jxJlhBbHUOiKBKNRtOuRR6PZ9ugeelxJk3jPeOAVKympqYiwONNrARBmFtYWDjxKBErURRlkrRR4ySNefv9fjnMV6/Xk5ubK98hHCT/pt3CaDQyMzOT9jt9oZr809msXFpDLCnEmOvnE7/8y/yXP/xDfvidb/DBD36Qpw/l8K2r32F8uZDv9Xh5o8/HoXI9J2sNFO/zpEsqJLdmp9OJx+MhmUySTCapra2ltbX1oYUw7zZeZifvt7S0xOjoqHxx7+vr25YohkIhenp6ZDfyTM9dWFhgdHSU9vb2tBN7IpGgs7OT2traNF3R8PAwJSUl8sU/EAjg8/lobV2/zV9dXSUnJ0cme06nU9ZabYxEkZCqa5RaWFL7yW6309vbK2vK6uvrGRkZ4ciRIwC0trZy6dIl8vLy0OvXs9qOHTsmG4hKpp2CINDS0sLExATXrl3j+PHjaYRUoVDQ2NjI6uoqXV1dVFRUUF5evuV3PRqNyj5enZ2d8qDBblt79xujs5fIysrCbrdjt9uB9eNnZWUFv99Pd3c3Go1GnjqU4ooeFCYji3zVdQmVoOTnrO+gRHP/gfCiKOIPLlGSf1QWpYuiSEFjIwabjbWuKUIRA2JSTBOwbwVvIM7gbJhbMyFmVqKIQH6OiiebjTSX6bGZVHtyrRAEAa1Wi1ar3TYwO/V6trKyIv+8du3apgnxVAK2o2NMFA9MxerOwNzCfi5z34lVNBqdksr4BwWJRCJjiy4YDKbpm6QDzGg0YrPZ5NFph8NBIpGgqurgTsDdK6SK1UYUPmXEeyuE+WI+xudG+WBzM3935Ai/+Zu/yYsvvriuNak2o0h+gebq32dwTk/fVIgbk0FKLWpO1mbTbNc/UK+W1PaFy+XC6/Wi0+mwWq2Ul5dz+PBhgsEgt27d2iQy3i/cS7zM3eB0OhkeHsZgMHD8+HH5DtRms8nmmalIDVVuaWnZMlz29u3bzM/Pc/r06bSTqyiK9PT0UFRUlGbB4HK58Hg8nD59Wv7d8PAw9fX18ueTvKuk90mtUgWDwYwVs9TlCoIg66zMZrNsSCrdeRcUFDA+Pi4bVqrValpaWujt7ZWnFVUqVZqBqKQPEgSBmpoa2Y7h5MmTm1y/8/LyOHv2LIODg1y7do22trZNz0kkEoyOjnL69Gm0Wi0FBQXMzc1x9epVCgsLqa6u3jUhupcYnQcNvV5PTk4OBQUFHDt2TG6rz83NMTAwILfVLRYLeXl5e0a0egKTvObpxKrK4T9YnsSs2psqSTS2RiweJFtfyOuvv84v/MIv8NWvfnVdH9XWxmrvtwlHIeyMobdlvll0r8XlytSsa/1moMCs4ulDRprK9NhMD0fmoVarUavVm6qd58+f56mnntp0TXS73czNzW3S/Gaqemk0GoRweJ1cHYCK1dLSkgAs7+cy951YuVyu0fn5eRHYt2/9dv5Nkr4plZ3vVt+k1+tZWVnZh0+y/5CMNDdCoVFQ+m4zk19KUDdYTXziDf7sM5/hiaee4tVXX+Xll1+mIG9dQ4M4xHtOPstzbSZu3g7SORbgG2+5+d4NL0eqsjhRayAv+/4PxVTBrcvlShPcVlZWpulAJBgMBoLBoHwc7AdS42Xi8TilpaU7ipe5GzweD0NDQ6hUKg4fPrxp3L22tpaLFy9SUlIiT/5EIhH6+vpQqVRbroMoigwNDREMBmlvb990QRwcHESv16fdWMRiMfr7+zl58qR8gff5fITDYVmTFY/H8Xg8ctvI6/WmTZ+FQqE0c85UpHqQWSwWbt26RXV1NQBlZWXMzMzIBK6hoYGRkRGOHz8OrEfgLC4uMjU1JZNMyVqhs7NTdoyXUFpaik6n46233uLYsWObtqtKpaK1tZXl5WWuXr26yeNrfHwcu90uV6cEQaC0tJTi4mIcDgeXLl2SQ6DvhWzsNEZnP7CysiLvX51OR0lJCVJ3QhoEWVhYYHBwMM09Pi8vb9etblEU+ZF/gPP+Aaq0BXww7yx6xd5Vw9dCSwAYswr4oz/6LySTSaxWKxqNBkVWFuYz9fh/BN63JtG/1CC/btUf59YdMjW/uk6minLVPNuaQ1OZDmvOwQweicVi8vGnVCpljV0mSEMm0rXU7/ezvLwsd3G0y8t0ALMeD8HR0U1+XvtJ+iORSGI/A5jhIRCreDw+73A4AkDmPbZLZOonSz+36ifn5+fLJGov7ppSx78fR0iTgRvvxI01OhbrXJQMlhJLGjheXCxrUgD02lyMWUUsrw5SW/oseo2Cjvps2usMTC5F6BoLcHVkjSvDa9QUaTlZm01tkRbFDj1bRFFkbW1NJlKpI+I1NTU7GhGXokc8Hs8DF9x6vV4cDseu42XuBr/fz9DQEMlkksbGxi0nsiRTS0nAvbi4yNDQEA0NDVsKVpPJJD09PWi1Wo4dO7Zpe05OThIOhzdNut26dYuqqqo0vcbQ0BCNjY3ye8zPz1NcXCz/P1VfBZk9rCRIrux6vV4mx1IFq7i4mEuXLlFXVydXtMbGxvB4PPK2aWpq4tKlS+Tn58sXD4PBQFtbm+xxldqms1qtsrloa2trxgqnzWbDbDbT19fHwsICra2thEIhlpaWZOF+KhQKBRUVFbKhqeS9VV5efk8kP1OMTl9fH8lkkrKyMoqLix/48MXKyorcdt0IrVZLcXGxTDol6xKppSm5x1utVvLy8ra90YiLCV5zd9IbmuJIViXvNp9AtccpD/7gOrEaHVzgzTff5NOf/rTsnwZgfqKF2fOz+HrnUHSUMbSc5JYjxKJnnUyVWNQ815ZDU5l+T24cHzS20jRmQmpgdqbvgvg//gcAxve9D8FgkKteqbrjjb6K0s+91B3H43ESicS+h/nueG8LgqADLgDaO6/7uiiKnxAE4RngfwIa4Drw83dhhwu3b9+OsENitXECIvXnVhMQktbpbhMQewXpJP+4QvIK2kisRFHkZsc4zzlOsBZ5kpyhYdpeejewrsUpKirCltvI7fkLxBNRVMr1u0lBEKgu1FFdqMMbTHB9IkD3eICvXHBhNig5XmPgWFUWBp1y0/L8fr9MpNbW1mRTw7q6uns2NbTZbCwtLT0QYhWNRuVWn+T0vdN4mbshGAwyPDwsT6/tpJ1ZUlLC3NwcV65cQaVSye2pTIjFYnR1dVFQUCBXg1IxPz/P4uKi3FKTsLi4SDQaTTMllWKfUrfxzMxM2kXY6XTS3NyctvytLq7SzYzFYkEQBIxGIz6fD5PJhEqlwmQypRG1xsZGhoeHaW9vB9bvyFtbW7l58yanT5+W90dubi6NjY0yuUo9wefk5NDe3i5ryVKrUhI0Gg3Hjx9nbm6OixcvAnDs2LFt97c0wVheXs7ExAQXLlygurp6k/fYbrAxRmdmZoZLly5hMpmw2+17EqOzEfF4nFgstmNhvkajkduZ8LbZrtPpZGRkBECuaFksFvlYCCWj/KPrIlPRZd6R08q57K092O4Ha6ElFIKKz/75X5OTk8Mv/uIvyl5mAM5AkohZhSdYzZd/6AGgzKrh+SMmmsp0mA0Hn0ylYs+E64kEwl//NTz9NKZTp9iqmb/RSHVpaUkmXpkm5VMf7/QG4U501F3bSYIgfBF4EVgWRbHlzu/+K/B/ANLrf08Uxe/sZLm72fMR4BlRFNcEQVADlwRB+D7wCvAOURRHBUH4A+AjwBe2eZ/5mZmZhPSf1GymjeRpo2eHdHdqtVoPVLCvFAz7oHPnHhYkh3JJ2CshIsYJ6CJEno6g+G4B7oFpzO8WuXjxIu985zv55je/yZETTUzMvYnLO0ZBXvPm985S8syhHJ5sNjI0G6ZzbI0f9vr4Ub+P5jI9x8ohGXbLsRFGoxGLxUJDQ8OexXDk5+fLfkN7gWQyyfLyMg6Hg3A4TElJCadOndozD6JwOMzo6Cgej4f6+npsNtuOt4NESGOxGE8++eSW6xQKhejq6qK6uppMgyYul4uxsTFOnz6dRj4ikQhDQ0OcPn06bZ2Gh4flWBtYF7FL3lHwth5OaltJYbBbfS69Xp8Wfi7prKSLnt1uZ3p6WiZWZrMZhUKBy+WSCaiU2Tg+Pp4WiFxQUEA4HOb69etpTvLSck+fPk1nZ6ecTZgJJSUleDweFhYWcDgcNDU13fUuXK1W09DQQGVlJWNjY0xOTlJXV0dhYeF9HedZWVnU19dTV1eHy+WSY3SKior2NPh7eXl5yyiknUCtVlNYWCi3f6V4KKfTydjYGMlkEmOeifN50/gJ84HcDlqzKvZk3TPBH1xkzaPm619/ld/6rd/CYDDgi6g4fyvA4EyIFV+cVgGqoyrOLF7h+L97Akv5vX/+hw2/379l629X+N73YHoaPv3pbZ+mVqtlk9pM2OjtuLq6KvMEKTB7Kz8vydtxYWEBhUKxE9f1vwc+C3xpw+8/I4ri/9zB69OwY2Ilrp/pJBWz+s6/BBARRXH0zu9/APwu2xOrpcXFRf3FixfT08TvbByTyURRURFZWVkP1b9pt3gQuXMHBWazmbm5uU2/9yfWS7r6VhX67ihrK4cJjs9z6tQp7HY7H//4x+np6UahULPkHsxIrCQoFQJNpVpKjGEmZn10TyXomwafJ8g7mjU0Nzc/sOBYtVqNRqO57zu21HgZq9VKfX39tuLr3SIajTI+Ps7y8jK1tbWbXNC3QyKRYHh4GI/HQ3t7Oz6fj5s3b26qNsG6Fur69etbtrz8fj99fX1pBqCAHLDc2NiYRthWVlbQarVpQtmZmRlZtC69Z2rFMVPrORVZWVlpukaLxcLQ0JBMdPLy8ujv70+rejU2NtLX15dG+urq6rh8+bLcxpNQXl5OKBSiv79/03ZWq9W0t7fT09NDKBTK6Frvcrlwu908/fTTOBwOLl68yOHDh7ec0kqFVqulpaWFUCjEyMhIWkzO/UBqi1qtVuLxOHNzc9y4cQOFQrEnMTqLi4tppqr3C7VaTUFBgXxDF4/HcbgWCMRGUCRhqm8Msnzy5OFem6euhZapqqznS1/9V5S5dfzZt5dwB8sRXH4q8jWcqjNR5oXlb3ppDDpJ/vDfEH/u5x7Zm+u1tbX7PsYA+Mu/hMJCeO977+ttlEolRqNxS7nExjQSv98vV70kXXB3dzeJROKuxEoUxQuCIFTc1wqnYFe1SkEQlKy3+2qAvwA6AbUgCMdFUewGPgBkDiW7A1EUY6WlpaGOjg7j42QSutFI83HCVhoyf3KdWBlVOgrfm8XY37iZ/56f2l8t4U/+5E948cUX+dznPk/Hc7Usrw7Chm5SMpnE4/HI5f9wOIzJZCLfYsGYY0QVjPHS2Yp9EXtK/keZWl7bYTfxMveKeDzO5OQkc3NzVFVVbeuWngkSiSopKZFJRVZWFqurq4yMjNDQ8Lbw1ul0yhqsTP5IUiUnk+v77OysXHWQIIoiw8PDaS0/URTT4myk5aaSuLt5PUl5gRKys7MJBAJy1VjSWs3Pz8u+S0ajEb1eL7vQw7pWpK2tjRs3bmyymKivr6e3t5fx8XFqa2vTlq9UKjl27BiDg4PcuHGDtrY2+bXhcFgmnkqlksrKStlUND8/n9ra2h3tP71eT1tbG2tra3JMTmNj447I2d2gUqnSYnRmZmbuK0ZH+i7vxbptt85VBWV8LPYTfNn1Y3rKVrEoC9F4fNy+fZtYLCZXIS0Wy7bEfDuIosiMM8zo4iHWYkcIxLUonFBkStJgi/PEkTKy78gUIs4Yy4C68RzRm/9EqK+PrMOHt1/AAYUkrbgvTE3Bd74Dv//78IALI6k6r0y4c6OXXF5eHryPxfxnQRBeBrqB/1MUxR2FOe+K2YiimADaBEEwA/8CNAMfAj4jCIIWeB24q/peFEV3MBi07Yex3X5ho5Hm4wRBEFCr1ZuqCFLFyqjIIqssB6OpG/9KPd7hED/5kz/JCy+8wCc/+Um+//QXWQsNshZ0EgkJMpGKRqOYTCasViuHDx+WvyDDcyFG5ld5R2vOvk3QFBUV0d3dvSNida/xMrtFMplkamqK6elp7HY7586d2xVhE0WR8fFxFhYWaGtr20SUGhsbuXr1KktLS7IFwMTExCaPKgmSAWhLS8um9wqFQkxMTMhGnxIWFxfJyclJO2GvrKxsGrd3uVxpBO9u1UOtVitrLOFtp3C/3y+vW1lZGdevX5eJFUBDQwPd3d1p7VOj0UhZWRlDQ0Np7cpUA1GdTrcpyFoQBJqbm5mcnOTatWucOHECpVLJ9evXOXTo0P/P3nuHt5Wfd76fg0oQLCDA3ptYRLFIFCk2STPjsT1je1zj6zu205ysEydxbpzirc/dG69j5+6N17nZTSaxk43jdGfjTDwe2zPj8UgUm0hKYu8dJMUCgAABEB3n/gEdDCkCJFgkyn7u93n4iAIPTj/n9/7e9/t+v3vOYUJCAi0tLUxPT9PZ2UldXV3MjQsJCQnU19djs9mYmJgIdzqe1vszISGByspKKioqjm2jIwXGjyNbk6ZM4tNp7+IfLLd4zTvC09nVPFXeQjAYZGtrK1zu9Hq96HS6cKB10PMZFEWWTV5GjS7GjG5sOwG6XrmDMvgGX/ziH1CZp2F6YoTc3NxwUAWg0iuQqQUCimxU2dnYXnuNuPJyZMcM6s4KoihyKo4oX/saCAJ8+tOns2MngCAIjI+Pb/t8voljruIl4L8A4oN/vwJ8KpYvHussiqJoFQThBvDcg/rjVQBBEN4FlB30XQC5XD4xPT1dLllL/CQgkpDmTxL0ej0Wi2UPYTccWMlDL5HUBhU7P7Sw8opAQpGar3zlK1y6dIm3Xh/kfAt09b5Kuq6W1NRULl68GPFF5/EF+W6/jfRkBa0Vp9I4GhOkFuCDMiWnYS8TC0RRxGg0Mjc3R1ZW1rFU151OJwMDA2GdpUgZEkkcs7u7m83NTba3t2lubo5Ygg8Gg/T391NcXLxP50rSsaqurt5XGpyamqKxsXHP8kajcY+WltSUsDv4OixjtdsgXPpd4llJAYfUXbR7Ji41t6yuru7hjhUVFdHT04PJZNpzfDKZjMuXL9Pd3U1cXFzEUklxcTFxcXF0dnYSHx9PZmZmRC0wmUxGeXk5GRkZ3L17l7y8PIqKimK+fySjaIvFwvDwMHFxcVRUVJyanMJJbHRWVlb2lHYfNbRyNT+b+jTfsfbxln0Ys3+bD6RcCZc64e0smjQJkiZykg1PnEbD0qYUTLmwu4LIZVCaFUdlxgpfffWrXL92jfrS0L1jtVr3BN4QcqKIz1ays+oj/YUX2Pza17DfuEHyc889tnNxGvB4PCcvpXo88Od/Di+8AHkHFq4eG4aHh73A1KELRoAoiuvS74IgfB34bqzfjbmeIAhC2oNMFYIgaIBngQlBENIffKYG/i3wp4ety263352aOtaxPrGIJqT5kwKDwRDu7JJgD7hQCnLUQmgwVZWfI4F2fHaRO/84ytraGt/73vd43wdDreaN9U9TV1dHbm5u1EHzh0Pb2HcCfKAxBcUjFA+NBKljbjf8fj9Go5HOzk4GBgbQarVcvXqVurq6U++skuxdbt68id1up6WlhfLy8iMFVaIosri4SF9fH5WVlVRWVh5YdlKpVCQnJ7O0tERNTU1UHSupjJUbwa1+bm4uPGDtxvLyMqmpqXuutc/nw2637ykZPcyvgtg6lB7WWDMYDJhMpj3LSMbMu1FWVhYmQ0sQBIG6ujpGRkbCTTMSJAHR0dHRsPnzw8jOziYxMRGz2XwoT0Wn09HW1sbOzg49PT17SpqxQK/X09LSQl5eHnfv3mVwcBC3232kdRwGyUbn2rVrVFZWYjabuXnzJiMjI2xvb+9ZVgpgHrc/oEKQ8yHdFZ5NqmXItcg3TD/CEXj7XEryDWVlZbS0tHDt2jUKCgrC2m1/8Z0R/uebJvqnHWQmy/lIk45/++EsPnHNQNdrf45j283nf+ffAaH7ViaTRcwYa7JVuNd9KDKyib90CUdPD7719X3LPclwOBwnl3759rdhcxM+85nT2alTgNFoFDimnY0gCLs1aD4EjMT63aP0fGcBbwmCMAT0AW+Iovhd4HcEQRgHhoBXRFH80WErslqtQyMjI87DlvtxQjQhzZ8UpKSksLW1t7y87d9BIyoZHx+no6ODkVu3kBG6rLkFuTz11FM89dRT+LiPSplAcsLB3l1Gk5feKSeN57TkpT5+2xuJkyOKIhaLhYGBAW7duoXT6eTixYvhwey0uYGiKLKxscGtW7fY3NykqamJqqqqsIhnrHC73fT29mK1Wmlrazt0oAsEAvT396NWq2lubqa/v39PeU3CxMQESqUyYpnUbrezvLy8p4wHocF2dnaW0tLSPZ/v9umTsLtTT0IsmjoPc/8SExNxOBzhjkIIcefW19f3fBYXF0d6evp+qyaNhpKSEkZG9r8/4+LiuHz5Mnfv3o3IN5ydnQWgtbWVu3fv7gvwHoZcLufChQucO3eO27dvs7y8vGcfD4OUXWprayMtLY2enh5GR0cfyTtIstG5fv16uEng1q1bzM/P4/V6WV9fPxOldwidh2uJ5/mYvo013xZf23yDdZ814rJSoHXu3DmuXLmCTUylMFXO/3bRTVn8PJaFXkaH7jE9Pc1ffO2fOF+Ty7VrTwMhuZBoz1N8jhIxAO4NH0nPPougVmN99dUjXc+zxql0BL70EpSUwDvfeTo7dUL4fD58Pt+OGMOFEATh74FuoFwQhGVBEH4B+K+CIAw/iHmeBj4X67ZjDqxEURwSRfGiKIo1oiheEEXxCw8+/x1RFCtFUSwXRfEPY1zd1ODg4E+c8JNKpYo4MP0kQKlUhkUHR0dHuXXrFtvrFrZxcy95jZq6C+QuLeFPCHX+6asSuHnzJjU1NfTf7SBdV4EgRL/dAkGR7/RukRgv59nas+HeBQIB/H4/P/rRj5ifnycnJ4ennnqKioqK0zMmfQgWi4Wuri6MRiP19fXU1tYei3S7urpKd3c3RUVF1NbWHhr8eb1eenp6SE1N5fz586SkpFBVVUVPT8+e7MfCwgIOh4MLFy7sGziDwSADAwN7iNsSFhcXycrK2ldeMBqN+7hKDwuDQihIPKw08TCBXTIK3p05lsvl6PX6fc4IpaWlzM3NEQgE9nyem5sbNsF+GAkJCdTW1tLX17cngJmdncVkMnHx4sWw1tXY2BjLy4d3eaemptLa2srGxgb9/f1HDowkkv7169dJTEyks7OTyclJ/P7TF5qWbHSuXLlCQ0MDgUCA7u5uhoaGSEhIONNAokqTx6dS30FADPLnm28w5T44SbHlCLDtCnKhMIHK8lKuXLnCU089RWlpKRMTE6ytmnn3+0KCsPPz8+HyfyRoskMTINeKD7lWS/Kzz+JdWMA1PHzqx/mosL29fTLO3sgI3LoFv/RLcEZ+qw9jfn4epVI5H8uyoii+KIpiliiKSlEUc0VR/AtRFH9aFMXqBzHP+0VRjNmL76zOwKwkAPeTBJ1OF7VU8OMIn8/H2toaIyMjtLe343a7WVlZwWAw0NTUxKfOv4+nEi8wxQZf23yN5TgPweQaVAY5calKOjo6GB4eRpsskp5y/sBtdYw7WLf5ed/lZNTKx3dbBgIBVldX6enp4c6dO2Gia319/SOdhdtsNm7fvs3MzAzV1dXU19cfiyvj8/m4e/cuq6urtLa2xtQ8sbOzQ3d3N8XFxXu4TmlpaeHgyuVysba2xsrKCpcuXYp4HqampsjIyNgnKeH3+1lYWNin8WS321EqlXsCR4lftbsMcZiGlYRI3aoGgwGz2bzns0jlQJVKRU5ODgsLC3s+FwSB2tpaJiYmIk6SpNJSX19f2APQYrHQ0NAQLrnGxcXR3NyM0WhkZmbm0IBDqVRy6dIlcnJy6OzsZP0YZSRBEMINDkqlklu3bjE7O7svcDwtSDY6jY2NqFQqbDYbN27cYHx8/MwoETkqA59OfxcpigT+1txOjyM63WRhI3RtC9PfDt4FQSA5OZkLFy7wsU8+Te2lYsrKysJdrOPj4/T29jI3N4fNZgtfV1WKHLlGYGc1FBTH19ejfEBkD/6YTLRPHFj96Z+CWg0///Ont1MnxNTUFD6fb/Astn0megeiKHqys7N9P2mCmpKQ5o9rZ6DX6w2rmlssFmQyGQaDgbS0NMrLy8ME593t9M8kVVPk0fLP27f4/nMlvPDXAqlXQi+r7u5uSkrzSUhUk5ZSEW2zmO1+bo5sU5UXR0XO45GriGYvI4oiN27cIBAInKpkggSHw8HExARer/fErfObm5uMjo5SWloakfsUCTabjbt371JbWxuxtJGamkpNTQ2dnZ0IgsDVq1cjnoetrZBo68NdgBCaKebl5e3ja+02XJbgdDr36ZMdpLi+G/Hx8fvK05Lg5249JZ1Oh9PpxOv17imvFhcXc+vWLQoKCvZk+FQqNzMG3QAAIABJREFUFefPn2dgYGCP16GErKwsXC4XN27cIDk5OaKyulKp5MqVKwwMDDAyMhIx4/cwsrOz0ev1DA4Osra2RlVV1ZHLznK5nOLiYvLz85mbm6O9vZ3i4mLy8vIeiQvF8vIyRUVFFBYWhjPaw8PDBINBcnNzycnJeeQ2OruRLI/nF1Kf5Z+3uvme7Q4m/zbPJ19C/lC2fH7Dg1YtIy1p/74VFRXxW//h49gcKyQlJaHVajEajVy7dg2HwxEWx7Xb7cTHx5OamooyLZ6dlVBgJchk6N77Xja//nXsb731xBPZg8EggUDg+LqRDgd885vw0Y9CFAP3s8D4+Lh3fX39zlls+8yEpORy+frGxkb2w2reP85ITk6OWEJ4UiGZoppMJiwWCwqFAoPBQEZGBpWVlfteiKmpqczNze1bT+JrXfzU8jKT155HCAi0Z4zwrLeGnp4emq6WkqTNRqOO7F8niqESoEIu8J76yMucFjweD8vLy6ysrKDRaCLaywiCQFZW1ql3OUlij3a7/cRij4FAgPHxcex2O1euXIlZ5kEKxBoaGg7kU0jBhyAIEScKfr+fwcHBfarkEAqKlpeX92hUwdtq9A+r2z+sXwWxW2s8XAqEEB9oe3t7T7egZHq8srKyJ0MnaTnNzs5SXl6+Zz0ZGRlho+zdcg3S8ZvNZpRKJWq1OmrAIpPJuHjxIhMTE/T393Pp0qVDg/W4uDgaGxvD5sw1NTXHIoVLvpCFhYXMzMzQ3t4etuE5rcmsKIosLy+HfRB32+i4XK7wMTxKG51IUMuU/O/6q/xwe5AOxzhmv52P6VuJe2DQLIoiCxteCtNVEfdnZ2cHr0fE/8Bizmw2h/ddEqwsLCwk6A+yMWjD/EMHvpUAotoTLq8bDAY0D4js8ZcuoXyCJ9sn1q/6278Fux1+5VdOb6dOAYODg/Zd4uWPFWdZDB37/zsDHy/cbjfLy8sMDg5y48YN+vv72d7eDrf0t7W1UVlZSXp6esRZpkqlIhgM7umack1M4JmawnD1KSrXiiBOxJi+we/d/kvMZjOFZVrSU6Jbxdyb22F+w8u76pJJ1Jx+higYDLK2tkZvby+3b98GCHNEorWPFxQUsLi4eCrb93g8jIyM0NvbS0ZGRphsfFxYrVY6OjrQarVR9aYiwWg0hr3yDnqJejwe+vv7aWhooLW1lampKebm5vaUs8bGxigsLIxYupyZmaGoqGhfACGp0T98viPxq2INrCRz8N2QxE8fLhHm5uZG5DwVFBRw//79iNymqqoq5ufn96zL5XLR1dVFRkYGV69exev1honrkSAIApWVlWGCeSwcKkEQKCgooKGhgfHxccbGxvZ0MB4FUvatqakJi8XCrVu39pH5j4v19fU9Hn67odFoKC8v5/r16+FS7M2bN5mcnDxyF+RxIBME3pVcxwd0jcx71vn65htY/KF3s9UZwLYT2FMG3I2vfvWrtF38NG53aD83Nzf3TC48Zj+rr9sY/8o66/+6g2BXkvlUEud/NZfq6mpUKhXz8/MMazQEBYHVl1/GYrEc+xo+athstuM7RIhiiLReWwsPfDifFIyMjASA6bPY9pllrMxmc//k5OTHr169+hNTCxQEAYVCEXMp41HD5XKFS3tWqxWVSoXBYCA3N5cLFy4cq9SVmpqKyWQiKysL0efD9v3vo0hLQ9t4hcWvbKIri+dXMt/DHy99iwsfbEH7TCsJunMR1+VwBXhtwEZBmopLJadLDj+JvYzksH5QJ9Bh8Pl8zM7Osra2RklJCVVVVSearQeDQaanp9nY2KC+vj7mGaYoikxPT2OxWGhubj6wLOP3++nt7eX8+fPhc9Xc3Mzw8DB37tyhtraWra0tdnZ2qK6u3vd9j8fD+vr6vmwVhMqAD2eFRFGMyO04TMNKgkwmixggSLILuwM/tVqNSqXatz2pdDY9Pb3HABpCWZ+amhru3btHS0sL6+vrjI+P77H6uXjxIj09PcTFxUX0VJRQWFhIXFwcXV1dNDY2xhQ4arVaWlpamJ2dpaOjI6LIa6yIi4ujuro6bNwt2eTEYtwdDfPz8/t0nR6GIAhhE+WHbXTy8vLIysp6JCV3CfXaEvSKBP7B3MHXNl/nRf1VLBuhcx8tsDKbzWji45DJQ/w0k8nEuZIytoZ3sPTv4Jj3gAySyuIw1GtJPKdGkIWebTUKtFot+fn5eObmMHV2IhgMLC4uMjQ0FH4Hp6amotPpHumxxwqr1bqH3nEk9PTA4GCIY/WE0XpMJpMoiqLl8CVPH2cWWLlcrrGhoaFtiGp+/WOJ5ORkbDZbRIHAR42dnZ09gVRcXBwGg4H8/HxqampOhWORlpbG/fv3ycrKwt7RQWBri9Sf+zlcqwECO0GSyuNIlGv4t00/Q9lX4xiU+/kHzwwfdOmp0OzlAX3/rg2vX+T9jTpkp/BQSvYyRqMRpVJ5InuZoqIi5ubmjhxYBQIB5ufnMRqNFBYWHtl+JhIcDgf37t0jPT2d1tbWmNcniiJDQ0MEg0EaGxsP/J4kAFpQULBndi6Xy6mrq2NlZQXJ3/Pq1atRyeylpaX7tuPxeMJ2RbshZaYeXtfOzg5ZWVnEgkgTGalk/XAJT8qcPBwM5OXlcfPmzYj+hHq9nuTkZDo6OlCpVLS0tOzpVpTJZDQ0NNDd3Y1arT7wuc/MzEStVnP79m0uXboUU6AvCAKlpaWkp6czMDBAdnY2JSUlxw7S4+PjuXTpEna7nYmJCaanp6moqNjjkxgL7HY7oigeSfsoko3O9PT0sW10YkWROoNPp7+LvzHd5BumH5G72ky8WklacuThz2KxoEtJJCj62V5xED+TxlS3icBOEKVOTuY7ktBfjEeZFP29EvR62frXf0Wu15P+wgvkPiivu1wuzGYzy8vLDA8Po1Qqw4FWSkrKmQRaNptt36QnZrz0EiQmwic+cbo7dUI4HA6CweD24Us+GpylWd/U0NDQj0fLxBGg0+mwWq2PPLASRRGn0xnmSG1vb6PRaDAYDBQWFpKcnPxIyKp6vZ7R0VF8Fgv2W7fQXLiAurgY8+u20CzuXGhgWltbI3FjnFZtBjNpev7Ocov6+BKeS76IWqZkatXN8JKLZ6oTSTuBbU0ke5mGhoZj+4TtPs7x8fEwufowBINBlpaWwsTto9rPRIIoiiwsLLC0tERtbe2RBj9Joyo5OZny8vIDBywpAJMGuEjIyclheXkZp9MZ5iTtzn7t7OywtbUVMYOxvLwckVwfiV8FsWes4G2e1e7ASprcPIyMjAwmJiYIBoP7eHVlZWVMTU1RU1Oz5zu77ZdqamoiSkAolUoaGhro6emJ6rEoISUlhYaGBvr7+zl//nzMjS5JSUm0trYyOTlJV1cXFy9ePJEESGJiIg0NDVitVsbHx1EoFFRUVMQcKM3MzOzTKDsKTsNG5ygwKBL5N+nv5B/NHcxv+EhNiS5HYdo0k6xJIbP/k8z/0IZKSCKhUoXhspaE4rezUwdh+803Q5POT30K2a6GCY1GE+ahQYieYTabWVlZYWRkJMxzlQKtR038F0URn893ZM08AEwm+Na34Bd+AU6qgXXKmJmZQalUnhnX6CwDK+P8/PyTlTs8BaSkpDA+Pn7q6xVFMdyRYjKZ9nSklJSUkJyc/FiIoXK5PGTg+93vIshkJL/73QBsT7pJKFAjj5Nht9vJzc3lE/+mkf/zP32RZ9Ke4kfbw3Q6xpn3rPP+pCZe6QuQlqSgrfJ4ar+P2l5GEARKSkqYnZ3dN9juhiiKrKysMDMzQ2ZmJm1tbadSBna5XAwMDJCQkLDPHPgweDwe+vr6yMvL25e1iYSpqSkEQdhnNLwbKysrKBQKnn76aRYXF+no6KCioiJcQpicnKSsrGzf+ZcIzs3NzfvWaTab90kywNECK4lPtTuYEQQBjUazj6slk8lIS0tjfX19X0YsKysrPLhrtVq8Xi9jY2O43e6wZtPAwEBUeyCNRkN9fT137949tKEgISGB5uZment7cbvdMTdJyOVyzp8/j9lspre3l6KiIvLz8090z+t0OpqbmzGZTAwODqLVaikvLz8waHO5XNjt9hNxBSVEstHp7e1FpVIdaqNzVMTL1LwQ18YfeUyYtDP809YqH9I1oZKFhkH3hg9zv5OVkTWS5ekoPIn4KkyUPF1ASlbskxqv0YizpwdtQwPqXd2pkSCVkKUystRQtLa2xtjYWLgzOzU1Fb1ef+qB1vb29vEV1//yL0M2Nk+Q0rqEiYkJtre3+89q+2cWWImiGMjOzrY6HI60Eyu+PkFISEjA6XRyUikJSd9HCqQcDgdarZbU1FTOnTtHUlLSmUlVZPp8+GdmSHrnO5EnJ+Ox+PFs+jHUhzI7vb29BINBikoNpKdUohDkvCu5jrK4bP55q5tv9M/DTjafejb1SLY1knDj0tISgiCQl5d3LB+9mI8zM5PJycmIPlqiKLK+vs7k5CQGg4Hm5uZTm2UvLy8zMzNDVVXVkQcvp9MZtrOJpeN2aWkJq9UaUVZAgsvlYmpqira2NgRBoLCwkMzMTEZGRlhYWCA/Px+n0xlxezabjfj4+Igz4mikWVEUYx5MIxHV4W2e1cNBS35+PuPj4/sCK0EQKC8vZ2JiguTkZIxGI2VlZXu66LKzs5mYmOD8+ciabElJSVRXV9PX1xfVc1GCpHZ/584d3G43586di/l5NhgMtLW1MToaso2qq6s78b0nCZWur6/T399PSkoKZWVlEdc7Ozt7onJkNEg2OkVFRWxvb7O0tMTExARpaWnk5+efium0cTOUqWrJyaTbdZdt1w7vXWvEedfHjtGLIIePv+dnkOfYWW55iYTg8+gyo0+sHobo97P18svIk5JIOoYCuVqtJjs7O+zJ6vV6MZvNbGxsMDER8hLeHWiddBJ3bB5pMAh/9mdw9SocwrM7C3R2dtqsVmv3WW3/LDNWyOXyOwMDA+ekdt2fBOzuSjqK4KNE5JU4Uk6nk4SEhDDx+mEvtbOC6POh7O3FHR9PwoMsxPZEqDMrqSJUfuvuDt3P1bVlJMa/PYAVqtP5kPxZvrGyBVn3eV0c4yP+ZgyK6DMmURTZ2tpiaWmJra0tsrKyTlwGiRVS1koKciSYTCYmJiZISEigsbEx5uzKYfB6vQwNDSGTyWhtbT3yS9NqtXLv3j3q6upi0sfa2NhgcXGR5ubmqPeWKIoMDg5y4cKFPfsjWbxsbW1x+/ZtEhMTw/fsbkTSroJQxlGj0ezbrt/vP1J2TqPR7FNVh1CgIAV9u5GUlITX693HpwoGg7hcLu7fv49KpYoYsJeUlNDV1XXgYGQwGCgtLaWvr4+mpqYDA0TJg3BoaIihoSFqampifsYVCgW1tbWsr6/T1dVFRUVFzLy0aBAEgczMTDIyMlhZWaG7u5uMjAxKS0vD197tdmMymfYR/U8bko1OMBgMNw14PB7y8vLIyck5XukKWNjwolEJXJUVkXNbi2ckwKbXiVwvkPXuJPR18dRoP8vK5j36xr+OTpdwpPeu/eZN/JubGD75SWQnpCNAKNjMysoKX1ufzxeebE9NTSGKInq9PtwgcNTzYrFYjlfSfeMNmJ2F//Jfjv7dx4COjg4PcCYaVnDGgdXa2toPe3t7P9zW1vb4jeEeIfR6PWaz+cDAShRFbDZb+CGRyhkGg4HKykoSEo72QD8u2Ds7CW5tYa6vJzsQQK1QsD3pRp2mQK0P3U7d3V3kFxoozr+45xgCQZHv9ztI1Mh5x8V0fuBc5KWNH/B88iUuxRfvWdblcoU1pxITE8nPz6e2tvaxn5Pc3NwwsdnlcjE+Po5KpaKuru7k3lq7sLGxwejoKOXl5eHZ6lEgDT6NjY0xBfRWq5WxsbFDOwUXFhbQarVRM2eSWnVpaSmDg4NhT0G9Xk8wGMRsNkfsIIzGr4pVakFCtIyVJNYbCZL0QmlpKT6fj8XFRYxGIxkZGTQ0NLC4uBjxnAiCwMWLF+nt7aWtrS3qecvOzsblcnHv3r2oqvUSZDIZtbW1TE1N0dvbS319/ZEysBkZGeh0OoaGhlhbW9sXAB8Hku5XdnY2RqORjo4OcnNzKSoqCnOrHtdzKNnoZGVl4fF4MBqNdHd3hzvvjuKOEPAE8Yy6eHoLZgY3ERQCCRVqOkpGWMvc4qf0LaTFJTA7O4ugCmW2UvSx91b51tZCvNPaWuLKyo51vIdBqVSSmZkZLsH7fL6wWO/MzAzBYHBPoHVYJvPYiusvvQRpafDhDx/nMB4pRFFkbW0tIIriwYadjxBnGlj5/f7+mzdv2n7zN3/z5MX6JwgGg2HfTD0YDGKz2cIZKZfLRVJSEqmpqVRVVe1Tn34S4bdacdy6Rdz58+iqqlhbWyM3PQ/Hooe0llCQIYoi3d3d1Ldk7dOv6ppwsG718+JVPZXJGkq0qXzbept/tfYy5V7lvUmXcGyGFNH9fj95eXnHytycJgRBICcnh46ODhISEqiqqjq+5ksE+P1+RkdHcbvdNDc3H4t0LwUGsZYjd3Z2uHfvHo2NjQcu73A4WFxc5OrVq1GXmZiYoLKyEp1OR1paGltbW8zNzTE2NkZiYiKpqakR72uz2RyR/3UUfhVEFgmF0IAcFxcXcX3Z2dl0dHTgdDrZ2toiPz9/T4Zqfn6era2tiFm/+Ph4ioqKGB0dpba2Nup+SWbO4+PjUUuHEqQy5NLSEj09PTQ0NByptKdWq7l8+TLLy8t0dnZy4cKFU2mekclkFBQUkJuby8LCAjdv3iQQCOwTeX1cUKvVlJaWUlJSgtVqZWlpidHRUTIzM8nLy4s60dlZ9WLud7I15KLSKxJMlpH9fBIptfEo4mVkB5L4O/Mt/t7STotYynOljXzhi/+O6quQkBjb8ygGAmy9/DIyjYbk558/zcM+EEqlMsxRg9D7RAq0JC/MlJSUcKC1+/3icrlQq9VHH3eMRnjlFfj850M2Nk8Y5ubmUCgU+5WsHyPONLACxgYHz8TK55FCmi1bLJZwIOXxeEhOTsZgMFBTU/NYSlmnDdsPfgBA8nPPEadUMjQ0RNJ2GgQhuTz0wAYCAf7j734av2KG9F02Nma7n7dGtjmfG0dlbmigS1Zo+VnD07xlGuCWa5L7lg3e7a0I28ucNSTNn52dHQRBOPXrZrFYGBoaOjYJWRRFpqamsFqtNDU1xZTp8Hq99Pb2UldXd2BmSzJYrq2tjVqaM5vNyGSyPd2KKSkp1NfXh4U0BUGgr6+P3Nxc0tLSwvtos9kidjkeNWMll8ujCi9KPKu8vLxw88fq6ir3798nEAiQkJAQsfxWWVnJ6OgoLS0tEdebn5/P2toa6+vrB/LYqqqquHPnDvPz83sU36MhPz+fuLg4uru7aWhoOBKVQOIcpqamcu/ePdbW1qisrDyV9n25XE5JSQnb29v4/X5u3bpFSUkJubm5ZzIZFASBlJQUUlJSotroCH4ZW8MuLP1OXPd9CEqBYIGSGz4vH/uQgTT920WSJHk8n0p9B/+y1cN3JzsBiIvXAjaCQV+UvdgLR1cXvtVV9B/7GPIzfLcrFArS0tLCGeZAIBAOtBYWFvD5fOFAy+fzHU/H7OtfDwmD/tIvnfLenw7u3LnDzs7OjbPchzMNrERR9GVlZW07nc604xjQPkkIBAJYrdZwIOVwOJifnyc9PZ26urpT4+GcFdwzM7jHxkh6xztQ6HQoCM2OrGM7yONlxOeFXlQKhYKGq2kERT0q5dtZrFf6rMhlb9vWSPYyy8vLJMXHU56TiTFhi6qsR8vdiAVutzscsEj2MxsbG4yPj1NfX3/i9QeDQSYnJ8Pmvce594PBIENDQwiCcCDxfDcCgQC9vb0xeRTOzMyEW74jQRRFJiYmDuyYVKvVtLa2YrPZWFlZYWpqCqVSiV6vj8o92tnZOTJhXyaTRfR2TEpKYm5uDovFgsViQavVkpmZSWtrK1tbW9y/fz/ieUtOTkalUrG5uRlxXwRBoK6ujq6uLlJSUqLyWqTSoSQgGgsHKj09HZVKFQ5+j+olqdFoaG5uZm5uLiwqehoZVrvdjsPhoK2tDZ/Px/T0NO3t7ZSVlZGZmXlm2fZINjqdP+whubcAwS8jLkNBznuTSamJ55UhG65lHxkp+zPgKpmCj+pbMXmNAEwnOimSKfAHD1fK95lMbL/1FnHnz6N5xNyzo0Iul5OamhrOYO4epxYXFxEEAZfLFSbEHzpO+XyhwOo974FDOh7PCh0dHTaLxdJ5lvtw1hkricBeEsnM9UlGIBDAYrFgNpsxm817ZgL5+fnMz8+TkpJyYkLpkwDR78f26qvIDQYSdl2nrMxstm+6STmvDWu7vP7D7zO21M+7nv54eLmB+R3m1j28tz6Jne1NJkaWcLvd5Obm0tzcjEqlwmK7x5Rj/cTdlCeB1+tlZmaGjY0NysrKqK6uDu9Leno6s7OzWK3WI4sp7sb29jYDAwNkZWXR0tJyrGP1+/309/eHidKxrEMURe7cuUNeXt6h3YJWq5X19fWIBssSNjY20Gg0UTOLRqORvLw8BEFAp9OFz5nL5WJiYoJAIEB7ezsKhQKdTkdiYiJarRaHw0FeXt6hx7MbarWazc3NcFbKZrNht9tRKpU4HI7wtdwdzKWlpTE6OhrVbLuiooJ79+5FLWWq1WoqKioYHBzk8uXLUa+BXC6nsbGRrq4u1Gp1TB1YOp2OK1euhIPgo/qpSk0XkqioREA/iWzB2NgY58+fRxAEVCoVVVVV4W5RScX9NOQXTgLJRqe0sJSJiXV8tiDrBbOgM6Aln4UNDwVp6qhixDJB4Jw3lMHxGdRM5pRyzu/goLtRDAaxvvwyglKJ7r3vfQRHdbqQy+XhsuDa2hrNzc04HA5MJhMDAwNhIV/J73CfgO/LL8Pa2hMpsSDhrInr8AQEVuvr6z/s6+v7UGtr69l7wBwAv9+/J5CSatepqakUFRXt40Skp6ezsrLyExFYObq68JvNGH76pxF2lZtSgmk4vXaSyt+u2/8fv/7raBI9fPIjXwTA6Q7w/bs2UuP9OIx9bKanRbSXiZepCRDEJwZQCY/3tvT7/czNzbGyskJJSQkVFRX7BiFBEKiqqmJkZORYAZEoiuFt1NbWHjuL4PF46O3tpbCwMOYARBRFhoeHSUpKOlTXKhAIMDg4yKVLl6IOxKIoMjk5yeXLl6P+fXV1NWJgJnUCSrYwXq8Xq9WKw+Hg/v37mM1m7ty5Ez6/SqUyXD50Op3cvn077FcplQA9Hg9+vx+DwYBWqyUjIyPcRdvV1UVCQkLE65mZmcn9+/cjipcmJCSQmJjI2tpa1Gc4KyuL+/fvs7KyEnEdEpRKJY2NjWH+VCxND/Hx8bS0tIS1rmLRI3sYiYmJYb/Hrq6uYzdcbG5uhq1pdkOj0VBbW4vD4WBycjKs4n5cG6jTglwt59zPpTP99U0M40Woi3109w1iceRRlu6PGkxDqLwN0CovYkUu8EpwnSTPBkXqyEKuzr4+vEtL6D70IeRPAH0hVrjdbhQKBSqVCr1eH75mEhfYbDYzPDy8hwtsMBjQvvQSQkEBPPfcGR9BZIiiyP3794OiKG6c5X6ceWDl9/v729vbrb/xG7/xRBHYfT7fnkBqd7dFcXHxoeTSlJQURkZGHtPePjr4bTbsN28SV1lJ3EMCkp55EVEQUeaE/NpsNhuTE7O8+KkmEuNChNeBaRNuXxaJcQpqLreRlhy5bBIvC53PnaAnLNj3qBEIBMLK5gUFBYeqpScnJ6PValldXT3QF+5hSGRxnU5Ha2vrsXkvDoeD/v7+I+tbzczMEAgEYrKtGB8fJy8v70CO2+rqKjqdLioXymKxkJSUFLXpwGq1hkuIKpVqD/nWbDbz1FNPAaGXpN/vD5t+9/T0hDNPSqUyfB7n5uaQy+URgw+JZxUp8MnPz2dwcDBqUFReXk5vb++Bpa7q6mo6OzsxGAwHllE0Gg2XLl2iv7+fpqammJoUVCpVWOvK5XIdqqAfCTKZjIqKCra2tsKWRYWFhTGvJxgMMjY2FjWIhlAQWl9fz/b2dlgcubKy8lR0p44LlU5B8U+nMvMXm3h+pKbghVpYsRAv7NDe3h7VRufSpUt8/vOf55kLrfQt/wnG/Ct80/QWL+gauKTdK2br39pi+403UJeWEl9X97gP8UQwmUwR3yEymSzMXystLd3TvT5+5w4Nb73F+osv4jIaMRgMT1z3+sLCwpkT1wFO3/Pk6BgdGBg4udX6CeHz+VhbW2N0dJT29na6u7vZ3NxEr9dz5coVrl+/TnV1NdnZ2TF17MjlctRqdcRW8B8nbP/gB4iiSHKEGYpt0oUyW2R1cwWA27dvI4oimRlZdHf34PP5eO7qBT7akoLdLfCnr5nom3FGNM7VyB54aQUfvctRMBhkcXGR9vb2sPddcXFxTAHP+fPnmZqaCg/2B0EURZaWlujt7aWiIkTKP25QZbFY6Ovr4+LFi0cKqpaXlzGbzTFJVUjWSAcRrSUz6LID2smjaVdBaKasUqkiZsOCweCefRQEAaVSSXx8PPHx8chkMuLj44mLi9tzHqNJLkBIz0rKQjwMrVaLKIpRvytZRK2srEQ9VqVSyYULF7h3717E+3o3kpOTqaqqoq+vD78/uqXKbsjlchoaGvB6vQwMDEQl6h+GlJQU2tracDgc3L59G7fbHdP35ubmyMzMjIkHmJSUxJUrVzh37hwjIyPcuXMHp9N5rP09DWgylRS+aMBj9rP9XRuyIFysKuapp54KK+23t7czMzMTPh+lpaU899xzFBYWE+f38qxPTaE6nZett3ndNkDwwTUWRRHrd74DgO7973+igotYsLGxEdN7RCrll5SU0HD9OmJTE6m3bxP0+xkfH+fGjRv09fUxNzfH9vb2oc/Ao8YD4vrNM90JnoCMlSiK3qysLPvOzk764+yUkxRtzWYzFosFQRDQ6/WkpqZSVlZ2Ki3+aWlpbG5uHiuN/yTAPTuYJmnJAAAgAElEQVSLa3SUxKefRvEQidZt8uE1B8h8LolR4zR+v5/h4WFkMoH/9qVvU15WxbVr/xlBkFFdIFCQpuZfbm/xSp+ViRUXH2xMIVHz9uCoCWesDieLHhcP0sRMTU2FDY2PKqgnqUNPTk5G9MWT4PF4GBwcRKVSnVgyQtrnK1euHKljbnNzk7m5OVpaWg7l1/h8PkZGRrhy5cqBg4TRaCQ9PT1qxsXv92O1WqmLMoM3m81RO5GOKrUgIT4+Pmrwo9PpGB4ejvrdvLw8jEZj1GzeuXPn6O7uJjs7O+o5TE1NZW1tjfn5+YgWPbuRlpaGx+Ohv7//UGNsCYIgUF1dzczMDL29vVy+fPlYbgMKhYLq6mo2Njbo7u6mrKzswMyrpCV3kNxGJOj1epqbm9nc3OTu3bskJSVRVlZ2Jg08icVq8j6UwtL/2qLRBQlxsog2On19fSGup8VCIBBAJpMhl6uQBbx80nCd79nu0OEYx+y385GUZnyDw3hmZ0l+73tRnIBzeRaQslDH4YoKn/0s8k98guLpaYqff36PQ8jU1BTb29skJCSEyfCP2yGks7PTZrFYOh7bBqPgzAMrALlcfndwcLAkkp/YaUHyYDKZTGxtbSGXy9Hr9aSnp1NRUfFIbFHS09OZmpr6sQyswoT1lBQSIyjjW8dCs/yliRXkci3BgIJf/MBn+OA7PsSf/d3voc80c2vgv/Hmv1q41d7Dxz/+cT704Q8zk5PM6wM2/vh7G7y/Ucf5vNDLNj6csTr9wEoURTY3N5mYmECn08VciomGgoICOjs7oxLZ19bWGB8fp7KyMizkd1zMz8+zuroaJvnHCpvNxujoaMwyDCMjI5SUlBw4+AUCAebm5g4kta+uru6xgXkYJpMp6mB+VKkFCdG0rCCU8VEqlRFtieBtTatIPocQIqlnZmaytLRE4QFdUJWVlXR0dJCWlnaoVIjUwTY4OEhdXV1MA4/k5ajRaOjq6qKxsfHY93B6ejopKSlhUdHq6up995bEyzuuZIMUvKSlpbG2tkZvb2/Yjuu4qunHRUpNPL2DdnKm/ay9vk3O828/sw/b6DQ1NbGzs0NufjoCMgJBH3JBxvuSL5OmSOL7tnv8+fprPHtzhJSCArQNDY/1WE4Dkj3asQKen/op+K3fgv/+3+H55xEEgaSkJJKSkigqKtrjaTszM8P29jbx8fHhQOtRe9reunXrzInr8IQEVpubmz/s6en5QHNz86k9cZJruBRIKZVKDAYDWVlZnD9//pG7hkOIPGq328+00+24cPT04DeZ0H/iEwgPsi277WV2FkW0QhqqhWRUJOOfhYVbW4CaT8R9ATpBFPwEB7/JwtgSn/70p/nVz/wqT116B+9/+mMUlr6bvu9YWM5UcalSiyxeRoJTw47Cg6gWEWLwEBSDQUSvF9HrJejxhH73eMK/Bz0edvx+pkURjUbD5cuXT0WHShAEamtruXfv3h5TXinr4/P5aGlpOZF/myiKjI+P43Q6aWpqOtLg5nK5uHv3LpcvX45p8L1//z5+v/9AAjaE+AuH2YkYjUYuXrwY9e9bW1tRM32Szc1RoVQqDyytGQwGzGZzREV7hUJBcnIyZrM5qqhmSUkJHR0d5OXlRb0Ocrmc2tpaBgYGaG1tPTQTVVpayvDwMJOTk1RUVBy47G7k5uaiVqvp6emhvr7+2HpvSqWS+vp6VlZW6OzspKqqKsxzg9A9oVAojtyR+DAEQSArK4vMzEyWl5fp6uoiKyuL4uLixyr8O5UiosyXQ7cTVZKctNa3z5vbY8PqWOIHr7/C+Pg4n/nNd7Jg/QYAa2sbzCvnycnJoSmhnBR5At/aaOfb78nm47pWhFMyiH6ciCYjEhNUqpB+1e/+LkxPw0O8W0EQSExMJDExkcLCwnCpXRIstdls4RK7FGidlsl2MBhkZWUlKIri+qms8AR4IgIrr9d789VXX7V+7nOfi9x6EQNcLlc4kLJarSiVSlJTU8nJyeHChQunIpR3VEjRvNVqPbIezVkisL2N/cYN4srK0JSX43K5MBqNrK6uhu1lUmtTQYSgV8S/E6C3s5/q8hrwygi4g/h3grgdDl7Iv8rz72jCuGrj9b43ebXvZfx2ka9+9J3kAff6O9HfrUMpV/JuQrO/IVYRZAFkCj8ymR+ZzIuAFwE3sqAbgjsIARdCwImABxkehPCPl4dDsgu/9mskpx/71oqIxMREMjIymJmZoaysLNxFcxrCiZI4p0qlOrCVPxJ8Ph+9vb3U1tbGNOh6PB4mJiZobW09cDt+v5+lpaUDy0JOpzPslRltW7tJ5w/D5XIdu1tSEASCwWDEl7TBYOD+/ftRrYLy8/NZXFyMGlgplUry8vKYn58/0FdNp9ORkZHB1NTUocGSVN7r6+tjcXHxSFnttLS0MBG+trb2RF14OTk5GAwGBgYGWFtb4/z582GdtdOUwJEETHNyclhcXKSjo4P8/HwKCwsf+bs5KIpsOQP4LsWToPWw+to2655B7OlD2BxG3F4bAP/jj14lWRfPxz/xYTLTz5GckEeCOoeVlfthG51cr5cP9M7x+gfP8Vf+fj7iUnJeczR5kLPGxsZGRJupmPFLvwS/93vwx38Mf/iHBy4qCAJarRatVhu+x6VAa2FhAavVSlxcXDjQ0ul0xw60RkdHUSgU0ev+jxFPRGAFTI2NjQWjvRgjYWdnZ08gpVarSU1NJS8vj5qamlOLgk+KzMxM1tfXf6wCK9trryEGArjr6+np7ibodpOTns6VsjLkgQDB7W3cm5tvZ4o8HnJ37mO/u0iCSgVeL3KPB43HQ77PzULmKnG127zYouTfD/4cHqsPHV9nccvBz3/jKyQkpHCx/gVann6a6zlplC75CIoaCGoIihqCATUi8QSDOoJBJYgHXFtBRFT6CaZvk5lsRBzrJek46sIx4Ny5c9y6dQuHw4Hb7aaxsfHEGTGfz0d/fz/p6emUlJQc6buSAGhZWVlMg60oigwMDHD+/PlDyzOzs7MUFBQcmOmVtKui4SB+FYSe6ePKk8TFxeF2uyOef71ez9jYWNTv6vV6hoeH8fv9UY+vqKiI9vZ2CgoKDsy0lJaW0tXVFdUSZzcEQaC+vp7u7m7i4uKOlB1KSkqiqakpfL1PIusSFxfHlStXwgGPSqWivLz8kZTsZDIZRUVF4UC1vb2d4uJi8vLyTvWdLYoiLo8Fq2OJFdMa/mANq6bv4M7sJ+P+i8TdzMPXPE5aYTm6xHyM8w7u9LzEF77wBdou/fKede220bH+3d+RuCPwjPMct+PW+AdLB+9MqqUtofLHoirh9/txu93HEiUOIysLPvpR+Mu/hC9+EY4o4REfH09+fn64wcXlcmEymVhaWmJoaCicFDEYDKSkpMQceL/55pvezc3Nfzny8TwCPBGBlSiKYl5e3sjo6GhmpEh6dzrRbDZjs9mIi4sjNTWVgoICamtrn5hA6mGkp6eHBfR+HGCZnsY1PIwoCPCtb5EXCLz9twO+pxIEAnI5Hq0WQaVCUKuRqVTIExMpl+dicFmYTBpi8pqLKkUbKZoSEgWBf7pwjn/47qu88sa3uHXzm/xZeg5/89d/x3vfdS3qtoI+kYAriN8VJPDgx7XtYW1pHa/TR7JgwD1nYHNZj1qegnPZjzZfduovPrvdTiAQwGQy8cwzz5y4vOxyuejr66OkpORIcg4Qekbu3btHdnZ2zIPs0tJSTAO61+tldXWVa9eiXxOpMeCgjJbJZDpw31wu17EDU6kzMNL35XI5crkcr9cbMViQylUrKytRM0dyuZyioiJmZ2cPfJZlMhl1dXX09/dz9erVQweF3QKiKpXqSBMwjUazR+sqFtucaBAEgcLCQvx+f5gbk5mZ+cjeqwqFgnPnzlFYWMjMzAzt7e2cO3fuQH5eNIiiyI7bhNVhxOpYwmpfwuYw4vWHOhLt7mKghmy9nnNZHyGpKhPTP6qR33kvpRfT0GQo+ce/+hKJiYl89rOfjbgNyUYnkJSETy5Hp9NzzmhnR7/DGwyy4bXyAf0VFMLjr4wcBZubm3tKvsfGr/86/P3fwze/Cb/yKydalUajIS8vLzwpk2g8KysrjIyMhGk8BoMBvV4f9Zn6zne+Y/V4PD880c6cEoSzbo+UoNFoPvPlL3/5D3/jN35DJYoiTqczHEjtJsAZDIZTrcs+DkjifE+qP+Bue5kEuZys5WU0Gg0ytRpBrUZQqcK/yx4ETYJaHfrswd9QKLh79y6FhYVRsxIO1wZ943+BzWGkNPcdnC/8IDJZ6CGx2+388p/8V/q+1ckHf/n/5YXWQtbHXmd6eooXX3wxKnHY4/EwPT2N2WymvLycjIwMBEHAa/Vj/Kt+nJYMRFGFJktJanMCugsaZIqTBViiKDI9Pc3a2hoXL15kY2MDl8t1YJfgYbDb7fT391NdXX0sA92RkRFkMtmhhr8SdnZ26O3tpa2t7dCAcHR0NFwCjobNzU1WVlaidgMC3Lx5k9bW1qjbu3HjRljD6qh/n5mZQa1WR82YjY+Po9PpogZ2Ei/toPJXMBikvb09JrPr+fl5HA5HzCUXp9NJb28vjY2NR84mBAIB7t27h0ajCaujHwc7Ozvcvn2b1tZWFhYWWF9fp66u7rH4drrdbqanp9na2qK8vJz09PSIxyGKQZyuzVAA5TBitYf+9QdCzQuCICdJm40uIR9dQh66hHwm7+v43l0nn3mfDpUmiDfow2XzYf+GH0QR3097mDRNo0nQEK9PwhP04RV9eIJ+PKIPr+h/8Jkft8+NP0rs1LSVQ2PmeQwGwxObvZLe0ScWcRVFaGwEhwPGxuARHm+kxrPdgZZCoSAYDJKTk7O+traWJT4BQc2JAytBEOKAdkBNKAP2v0RR/M+CILwD+H8IaWU5gJ8TRXHmgPWUXb9+vfcP/uAPku12O1qt9sxaNk8bc3MhvbLDWrEfJ4LBIBsbGywtvW0vk5ube6L0/9bWFjMzMzQc0CkTCPoYmfs286s3SUksoqHyU8THhQKxb5h+hMstkrJQx5jRTee3/i9+9PKfA9DS0sLHP/5xPvrRj5Keno7P52N2dpa1tTVKS0tDxqsP3SObX/86okyNrOYjmHoceDb9KBJkGBq0GBq0KBOOPrt0Op1hq5OysjJkMhmiKNLT0xO2ETkqzGYzQ0ND1NfXH0tUUbLauXTpUsz2Nl1dXVRWVh76gnW73fT09HD9+vUD133nzh2Kioqirk8yf26L0GEq7dPNmzePHVitrq5it9ujyiZsbGywvr5+YKDT3d1NdXX1gerky8vLWK3WQ4No6Z4oLS2NmShstVoZGBiIKXCLtL3R0VE8Hg8XL1488sQzGAzS3d1NRUVFeGJks9kYGBggNzeX4uLix/IO3tnZYXJyEqfTSWVlJV61kw3HIls797G6N9j2bOEjQEBQIMqVKNTJyFVJyJRaUMQRkCnwioFQYCT68QZ9uGfy4H4WtHaym4CZZI7nqe/UsRJcYeiTK/jUfpSCHLWgRCUoUMse/CsoUcsUqAQl4vQccpsDfVMrapkytKxMgUZQEW8XMBqN2Gw2srKyyM/Pf6I8YkVR5K233uLpp58+nWv5zW/Cz/4svP46vPOdJ19fjJCkkqRASxAENjc3+dznPvejxcXFd0T7niAI/xN4H7AhiuKFXZ9/Fvg1wA+8Kori50+6j6dRCvQAz4ii6BAEQQl0CILwfeAl4AOiKI4LgvArwH8Cfu6A9UxPTU35S0tLH3lL5uNGVlYW9+7deyICK7vdztLSEhsbG6Smpka0lzkuUlJScLvdB+oRyWVKaks/RmryOe5N/Q1v3f0yl8p/hixDDfEyNTbFFh9r1TO44EKt/F3qnv0FPAuvceP7/8Sv/dqv8bd/+7f81V/9FcvLyxQVFXHt2rWog0jA4UCVq0PfoMVwOR7HrIfNbgfrb9nZaLejq44ntVlLfNbhwaQoiiwuLrKwsEBtbe2eko0gCFy6dImuri4SExOP9DJdXV1lenqapqamY72EV1dXWV9fp6mpKeZnZnZ2lpSUlJhmrZOTk1GlCCT4fD7sdvuBZazD+FVut/tEEhgajYaNjeguFnq9PqwKHg35+fkYjUYqKyujLpOTk8Ps7OyhmluSUXNPTw9tbW0xdcDpdDoqKyvp6+uLWSZj9/YuXLjA7Oxs2DrnKF13ExMTYV6LhOTkZNra2piYmKC7u5uLFy8+8kAhPj6eixcvYrfbeWP2NQbSHgjxqgG1Adh7D8mRPQiCBFQEUCMjTqYkWYgPB0PTvhS8Wriuq387GBIUqNOUbDo3+Ni1Z/jN0f/IF/76P6BQHTzZshiNeBe3yXxnhHtEHdI08/v9rK6ucvfuXQRBID8/n6ysrDNpoNoNi8WCXq8/vbH1Yx+D3/7tkPTCYwysVCoVWVlZ4eyzz+fjy1/+sn9jY+OfDvnqN4D/AXxT+kAQhKeBDwA1oih6BEE4lS6nEwdWD9Jujgf/VT74ER/8SNPvZGD1sPXk5eXdMxqNz57E5PZJhEajCVtzPM4WYwk+n4+VlRWMRiNKpZL8/HwqKysfSTm1sLCQhYWFAwcngJy0SyQn5NI3/hfcHv1TSnOfRZOSi0v0hAalongK01V8u0fJgv4X+fcv/CpaWx/GhZlwIDMwMHCgtlDQ6UT2IPsgCAKJpXEklsbhNvkw9TjZGthha2AHbYGK1OYEkiviwmbSu+F2uxkYGCA+Pj5q6UytVlNdXc3du3dpbm6O6dzOzs6yvr5OS0vLse4LSSsm1u1ByAR6dXU1auZoN5xOJzabLWw/Ew0rKysRM4a7YTKZDuRyHVfDSsJB6usQ4vTIZLKoPCsINZpIHX3RjkUQBMrLy5mcnDyw7Amh576srCycjYwFGRkZeDwe7ty5Q2Nj45EHQUmLrLu7m4aGhpgCofX1dWw2G01NTfv+JpfLqaqqwmQycfv27VPpeo0FiYmJNJ5rYsB6ixSng3OuUkryi0lJSHoQGIWySLFwmv7IvU5esoIrCftL2X/0L/83voCP5rSnWf4XKwUf1Ud8B0gQFArEQ1TzFQpFmJztdDpZWlpieno6qo3O48La2tqJdfX2QK2GT38avvQlmJuDM0ocKJVKbty4YXG73W8etJwoiu2CIBQ+9PFngN8XRdHzYJlT8Rg8lZFVEAS5IAgDwAbwhiiKt4FfBL4nCMIy8NPA7x+2HpPJ9O0333zz0UlvnyHS09NZX3988hqSKOadO3fo7OzE5/PR0NBAU1PTgSrSJ0V2djZra2sxWXYkaNK5VvfbFGVfZ2b5h2xu3sMV9IZtI3RaBT/7tIErRUGmVlyMuS/wzPt/ntLSUr70pS/xzDPP8Pu///sRbRSCD/St5BH4KnGpSnLfp+P8b2WS9e4kfLYAi/9gYfwP19nosBNwvW0bsrq6Snd3N8XFxdTU1ByYRUhNTSUtLe3ADjQIXZuRkRGsVitNTU3HCqrsdjvDw8NHykxIMg51dXUxXX9JY+mwQeCwbkB4e7YcDcdVXZegUqnweg9+dRgMBiyW6C0Ykmjw5ubmgevJyMjA4XDgcDgOXA5CGS7JlDpWSIPv0NDQsSxCsrOzqaqqoqenh+3t7QOXdTqdjI2NHVpGTk1NpbW1FZPJRH9/Px7Po7eeytXmkhqUsaOUUWXQYx41cn9kAbVXhlaujimoCgZFthx+DIn7n1ubzcZLL73E8+95nqYXa7GNuln9ge3Acy7I5Yi7GnoOg1arpbKyco+Nzs2bN/fY6DwOSOPBcfibB+KXfxlkMviTPznd9R4BwWCQ8fFxEYhKNToAZcBVQRBuC4JwUxCEU1F8PZXRVRTFgCiKdUAu0CgIwgXgc8B7RFHMBf4S+G+Hrcftdr/5yiuvWE9jn540ZGdnH+nlelw4nU4mJia4ceMGKysrFBUVcf36dc6dO3eiUkuskMvl5OXlsbi4GNvyD0qDDZW/SNBjRQQWzffCXWYd/x93bx7eZlrfe38e7ZI3ed/3fY/jJfGWzMIw8NLTQim0HChQoFyFUgotlKXtoT2c83JR2kPhPZyBmTJsM8wwDAMMFGZhIHGcOLHjLd73fZVly5Jl7XrePxQpceLlkS0nnvO9rlyxpUfPc0u+9dzf+7d8v5cukRm+yYcejkEfruZHVzb52bUNPvO5f+Cd73wnn/vc53j7299+1wLivelRJtunXkaulZHQGEHRJxLJ+pMYVHo5S6+YGfy3ZWZfXKfzShdLS0s0NjZKrp3Kz88P6H7tBo/HQ2dnJzKZjNOnTx+K4NpsNq5fv87p06eDIiPDw8OkpKRIquMym83YbLYD64MsFgtKpXLfueVyuZDJZPuS0qNGrPykYL9F0W/IvB8yMjKYnZ098FpFRUUMDw9LGltFRQUjIyNBLaQFBQWBJonDIDY2lpqaGjo7O/d8z263m+vXr3Pq1ClJNV1KpZKqqirS0tK4cuUKy8vLhxpbMGjQn8Kh0tG/eYmGhgZSUlK4fv06fX19kj7PzW0PHi+7EqtvfOMbbG1t8YUvfIH4xgji6sNYu2rFcHlvwiwoFBAEsQq87qYSfU1NDQ0NDcjlcjo6Orh27RpLS0uH9oCUCrPZTFhYWOiFsdPS4A//EL79bbhPvpD9/f0oFIreQxatK4Bo4CzwaeA5IQThxJCGLURRNAEXgDcDlTcjVwA/AhoknGJsaGjIe9yT7H4gMjISm80mybw3WPjFGy9fvkxvby9hYWE0Nzdz6tSp0ObUJSIzM5PZ2dmgbhap8acpT/cZPV8be4qXL/1vlpeXqauro6ysjPSEMD78xniaS8Lpntrmey1WvvS17/DVr36VF198kbq6OkZGRgLn896MJsglaKwIMoGoEi15H4in4CPxqNJh47qNqM1EqqurgyroFwSBqqoqJicn2djY2PGcy+Xi6tWrxMTEHLp7y+Vy0dHRQXl5eVCF7uvr62xsbEjWxhoeHqa4+GBtnv0Ml/0wGo0H1nMdNWIFvnTsfpGUmJiYfSNW4KtzslqtB0a/4uLicDqdbG5uHjgulUpFaWkpPT09kiNQgiBQUVHB+vr6niT9IERERHD27FkGBwfv8lL0y3Pk5OQErbGXnJxMQ0MDMzMz9PT0SDaUPgwqwnJRIjAhc7NqGiQxMZHm5mZiYmK4evUqQ0ND+95TjRbf2GLCdxIKr9fL448/TmNjY6DZJuXRKKLKtCy9Ymbjxh5pZbn8wFTgQfDb6DQ3N1NcXIzRaOTixYv09/cfGGE8LPzp+mPBX/0VmEzw9NPHc/4D8Jvf/MZpMBheOOTL54EXRB/aAS9w5LDekYmVIAjxgiDob/6sBd4ADAFRgiAU3DzskZuP7QtRFEWFQtHX399/1GGdSCQnJ7O0tBSSc4miiNFopLu7m0uXLmGz2aiqqqKhoYH09PR7YtmzF5RKJYmJiczPzwf1OpXbt7BOJlcxlOBlKKKHOXGNbY9vsVTIBR6pjOIDD8eBAN95zUjJA3/GK6/8BoVCsSNq4rlJrGRBtK57PB7G10Ywy3yEKP3M4ew8FAoFNTU19PT0BDzsbDYbV65cIScn59BNDF6vl+vXr5ObmxtUSN/tdnPjxg2qqqokkbmNjQ1EUTyQDPk7Sw+q29jPLsaPo0asYH/PQCCQMt1vIRYEgdTU1D1NnW9HcXHxgQXxfiQkJKDT6SRHcsGniVVTU8P09PS+hfn7QavVUl9fz+zsLBMTE4HHR0ZGAvpBh4Faraauro6YmBhaW1tZWF5jxeTCvO3B5Qldt7tKpqBCl40pPJ7eqZ8jit7A3+jcuXPodDpaW1sZHR3dleCtb/keuzNiJQgCX//613niiSduPSYTyHhbNGFZKuZ+uoFl8m6SLigU4PUihmjzHxkZSVlZGefPnyc2NpahoSFaWlqYnJw8kNxLhSiKrKysHNmeaE80NUFlpa+I/T4oHfziF7/YdDgc+9ZX7YOfAQ+BT5kAUAH7h7UlIBSrbzLwPUEQ5PiI2nOiKP5SEIQ/B34iCIIX2AA+IOVkBoPhhddee+18RUXFvXXqvAdITU3lxo0bB+7w98Od9jKZmZmSjVzvJXJycrh27Rrp6ekHjs1sNjM0NIQHL405BaxprMwrVQzjZXjDZ1QeJdeRrIwmSRlNcng0735ET1uvi9ahLRL1xbza0klyjBqv18t3v/td3n5Tz2m/VODt2NjYoLe3l4yMTOQGLeocBeqYw389wsLCqKyspL29nfLycnp7e49kP+JXSU9ISAh65zkwMEB2drZk4jI0NERpaemBx/k7Sw9KZxqNRgoKCvY9Zi+T5GDgL2DfLwLjr7Pab5FJT0/n2rVrBwpuRkdHI5PJDux49KOkpCRg1CxVq0qhUFBXV0dbWxtqtfpQHbxKpZIzZ87Q09NDX18fkZGRmM3mfWVRpMDf8RYXF8djv15i03mLiCjlAlq1DJ1KdvN/3+9ale8x3c2fterbflbJkO9SOF4Tlkfn9iSzcg+zK1fJTPIlP2QyGZmZmaSlpTE9Pc2lS5fIzMwkKysrMCeNFjdKuUCE9tYc9Xq9LC4ukpOTc1eTjUwpkP2uWMa/bWD6GSN5H4xHm3SrhlHwd/Z5PL7aohBBJpMFOt38uoJtbW3odDoyMzOJj48/9D1+Y2ODqKio4+tKFARf1OpDH4KLF2EfyZRQw+v1Mjw87AUmDjpWEIRngAeAuJu1318AngSeFAShH3AC7wuFDlYougJvAHe5roqi+FMgaHl5u93+m5/+9Kebn/zkJw/pEnlyERYWhsvlCnoR8Xg8LC8vMzc3h9vtJj09ncbGxvvSYSgVGo2G6OjofT3a/PVgdrt9V02lKWMPV6Z/hl0TiSaunDW3hRH7Av5Zr8tQkRiZxvpgMt961UB9qQbX9FU++MEP8t1Tp/j/HnqIlAMWMK/Xy+joKGtra9TU1CAuK5g0GUl+JHg9qTsRExNDQkICbW1tNDU1HUnWYmhoCJVKFbTNzcrKCna7XYylxP8AACAASURBVDKZNxgMqFQqSWOdnZ3dUzfKD390aL+56r+PHXVzoNPp9o1Ywa06q/2IlVqtRq1WYzabD0y3FhUV0dfXR0NDw4HjVygUAfPug7wZ7xxPTU0NHR0dnDlz5lCRPZlMRlVVFZ2dnQwODvLwww+HbDOm0+lIS9RjXbCRF7lGXGIqXkGFzeFl2+nF5vCysunB5vBic3rx7rNsaZTCLcJ183+tSk6Yq5BVEmnpH6HGXU6EVh14Xq2UkZubS0ZGBpOTkztscowWDzHh8h3v9dlnn+Wf//mf+fWvf73rGORaGdl/Gsv4EwYmf7BG/p/Ho9LfXCpvkhPR4wmY04caarWa3NxccnJyMJlMzM7OMjAwQGJiIhkZGfvqrO2GY00D+vFf/yv83d/5olb3kFj19PSgUCh6pJAhURTftcdT7wnxsE6Gpc3tEEVxPCkpyRmKmouTiJSUFJaWlvaVCQDfYrO5ucns7CxGo5HExERKS0vviQpyqJCfn097ezvJyck7bmx2u52RkRHMZjOFhYV77sayY08Ro4nnav9jODf+kweL3k9c/KMsu0wsuzZYcm2wFLuB5/Q83rE8LvfFIUTl8N7/9Vme/dy/8cjcNE++7VHe1Pjwrh1EFouFnp4eEhMTaWhoQCaTMd25jlwrEFV89Lk3Pz+PwWAgNzeX8fFxyQKed2Jqagqr1UpNTU1Qr3M6nQwODkpa9ME354aHh6mqumufdBccDgd2u/1AAnZQN6B/nKHwpdNqtQfWUMXGxkoqCPcXsR8kBBoZGYlWq5VsFRIdHU1cXBxjY2MHRvFuR3h4OJWVlXR0dFBfX3+oz8tkMrG1tUVeXh4dHR3U1taGzA8wK0HNwJyd5qospkZvkJycTN6pvLvmnSiKOFwiNqeX7duIl//3HY87vaxvubE5vdiciUAiYxQyZthZhyQIBCJeOnUMGkUMk4NbeHoGWXPqyUrU7Lj+//gf/wO3273vPVgVpSD7T+MY/7aByR/4IlcKncyXCoQj11lJgd9GJzo6OrC57uvrw+PxkJ6eTkpKyoGba383oJQI9JGg1foiVv/6rzA7C0fIygSDn/zkJ9alpaXv3ZOLBYETR6wABEH4z9/+9rcffstb3nK/hxJypKamBmwFdsPt9jJ+s8qysrLXlYWPH1qtltjYWBYWFkhLS8PpdDI2NobBYKCgoICKiooDF/yosFTOV/0d1wa+Rfvg45Rkv5X8tEfIUN+q2fGIXlZTTVybMNPbF0FW6kf4syey+NHf/yNvffgt/Jd/+TBv+JPfI1kVTbIymmSFHvfiFgtz81RWVuLXTXNbPZiHbcTWhR3J9kYURcbHxzEajTQ0NKBQKBgcHKSvr4/y8vKgyNXS0hKLi4tBCYD6x9Db20tRUZHk6Ojy8jIRERGSdsTz8/OkpaUdeNy9qq+Cg7WswBc583q9+xoug09SYXh4GCnG8IWFhXR2dkpO1xQUFNDa2kpiYmJQUcyYmBgKCwsDAqLBpHb8mwh/xCs8PDygdRWKzz4z3jfHjDYVTU1NjIyMBKy8bk97CoKARiWgUcmIDiLwsuW282/z/0mi1UPUygzluR/E7dXsSs62HF62HVq2HSpcHvBY5lld9RAfH8+vfvUrhoaGeOKJJw78u2oTlWS/K5bJ768x/UMjOe+Lu0WsDtEZeBTI5XJSU1NJTU0NlINcvnyZyMhIMjIy9rTRWVtbIyYm5t6sHx/9qI9YPfYYfOlLx3894Pnnn9/2eDy7hx7vI+T/9E//dL/HcBc+/elPm4E/ePvb3/5/XchKqVQyNzdHbGxsYLfo9XpZWVlhcHCQmZkZoqKiKC0tDYR9T1r9VDCIjIykt7cXh8PB4OAgSUlJVFRUBGVTpJCrSU+oxWpfY3Lht9gcGyTGlCIIvpuFTBCIkGspitdzKiuMpXU3Llsub6p/CKt9jje++Y1Epycw6zQwaJ+j2zaF4PTyxsrmHYuKscOKZcxB+lujUYQdrh5BFEX6+vpwOBxUV1cHFr+4uDhWVlbY2NiQbHGyvr7O0NAQZ86cCTrtu7CwgM1mkxwVEUWRrq4uKisrJV2rr6+P0tLSAxf34eFhCgoK9j1uY2MDr9d7IAGbnp7eN8qgUCiYmJg4MBq8tbWFTCbbt85JEASsViter/fAKLFKpWJzc1PSsf5zx8TE0N3dTXp6elCLXnh4OF6vl4mJCcmGxdvb23R0dFBdXR0gzREREURGRtLZ2UlMTMyRpVh0GhlXR7ZQKQWK03TEx8cTHh5Od3c3giAc2U1DJVNg8JqYV1pI3uxDr3NxKreK9DgVOYlqClM1lGZoOZWtozYvjIaicM6XRnKuNIL81AgmJycZGRnhs5/9LADf/e53JRFTVbQCVayCtTYrjjUXYfEW7MNDhNfVIbtP3q9+U+LMzEzUajVzc3MMDw/jdDrR6XQ7vr8jIyNkZGTcG59avR56euCnP/XVXB1zqcrCwgLf+MY3Jsxm878f64UOgZMaBrly4cIF9/+NsgtwyzrDYrEwMDDAxYsXMRgMFBYWcu7cOXJyckIWor+f8Hg8LCwsYLfbsVqtnDt3joyMjEPdYOVyFTVFf0ZR5luYXWnjct/Xcbru1pvRhyl4/0NxNG7dwByex1v+/Pv8PxXv4k9jz+P93ginhn0LX2JS0o4bqyiKGDu30aWr0CQc7obg8Xjo6OhApVLdJcLpb5/3e6EdhK2tLXp7ew+VrrHZbIyPj0s2AAZfBCo2NlZS+t1kMqHT6Q4cl9vtxuv1HkjUQhWxkjqvpOhZgTRNKz8KCgoYHR2VLDESERFBWlqaZC2s25GVlUV4eDhSuqf9ZtunTp26q14sJiaG2tpauru7DxRFPQgyQSAjXs306q1OtpiYGJqamjCZTLS3tx9ZEPO0LgeH6EaRWs/00iW2bAd3SsplAmFhYVRXVzMwMEB3dzfvfe97gxpLdLmOlDdFsTlox9AX4bMVuccRq90gCAKxsbFUVVXR3NyMVqulu7ubK1euMD8/j91ux2w2H91wORj81V+B0QjPPnvsl3rxxRfdFovlqWO/0CFwIomVKIpumUzW2dXVdb+HEnK4XC5cLhfj4+P09/cTHR3N+fPnKS8vD5ln3/2G1+tlZmaGlpYWPB4P58+fD4k+iyAIFGW+hZqiP2PDPM3F7q9g2b5bzV4mCJQbunm3boQIrZxnLq3z+S9/j8997nMo8ZEprWwnKdiedeJYcxNTfbgF3ul00tbWRmJi4p5q5X4rnq2trX3Jld1uDwiABks4/PpEZWVlQSmyT0xMkJ+fL+l4KdpVIK2+CkKjYeWHUqk8UCvuIAV2PyIjI3E6nZIWYY1GQ0JCQlASIzk5OWxubkoieXeiqKgocB/ZC35Sdae35e0IDw/n7NmzDA8PH1ovy4+sBBVGi5st2y3S4S/Yz8rKoq2t7UgiydnqRKLlYayGxyITlAxO/Xzf471eL88//zw//rHPQu6RRx7hySef5DOf+Qz9/f10dnZKUs8HiG8IJ74hnM1xDTYqTwSxuh1+G53GxkYqKyuxWCxcvHgRQRAwmUyHUvA/FB58EEpL4etfP3bphaeeemrDYrH85FgvckicSGIFsLCw8J0f//jH0mb9CYcoiqyurgbsZTweDykpKeTm5h6rvcy9hiiKLCws0NLSgtVqpbGxkYKCAl/XUFoak5OTIblOWkItTZWfwO2x09LzLxg2du76Rbcb0W4nIUrBW0950Su3Wdzw3QjVEb4F/E5iZezaRqYW0JcGv8Bvb29z5coV8vPzyczM3PfY28nV8PDwXTc8t9tNR0cHpaWlhyLaU1NTREZGBqVzNTs7S1JSkqRaLI/Hg9FolFSoLaW+CkIXsQJfXd9BdVYqlQqPxyNJ2DItLU0yWcrLy2NiYgKPxEXXb9Tc398ftHCw/7UGg2FXzS2r1XogqfJDo9FQX1/PwsICo6Ojh16E/XVWM4a79ZcSExNpbGxkYWGBrq4uHFtbiEG+Z5kgUKXLYcZlJCn9IRbXulk3331PEUWRl156idraWt7xjnfw+OOP43K5WFxc5D3veQ8xMTE0NDSQkZFBd3c3vb29B3aTAiS/MZKITDfbnGVz+PiL1w8Lv42OTqcjNzf33troCAJ87GO+lODly8d2GavVysTEhE0UxdAsKiHGiV3RRVF8+YUXXjh4tp9gWK1WhoaGuHDhAktLSzvsZbKzsyWnGU46/AJ0ly5dYn19nbNnz1JSUrIjVZSTk8P8/HzIPMZiInM4V/V3aFXRXOn/30wvtQae89vZLG5sMDc7Q1xsFHh8NxR5mO/mfzux8ti9mPpt6Mu1yNXBfSVMJhPXrl2jsrJSsgCfn1zZ7Xb6+/sDC5lfADQrK0tyHdbtsFgszM3NHWiAfTs8Hg9TU1OSZRyWl5dJTEyUlHaTqu9kt9tDZrckpYAdfN15dyrj7wa/WKgUsqFSqUhJSQlKBNS/+B1GFNkvIDoxMbEj6mU2mwPpP6mq6n69rO3t7UN7FCZHK1HKBWYMu3/HVSoVtbW1JOj1GL7yFRa/+EWWvvxlVr/5TYzPPovp179mq60N2+AgzsVFPFbrXeOoCstBQGAjKhW1MpL+yZ/uOOb69eucP3+eN7/5zWxsbPD973+fl156ifHxcbKzs3dEcePj42lqaiIhIYH29nb6+/v3vT8JMoHkcx6ULLB4UcAyce+8/oKF2WxGqVSSlpZGTU0NjY2NO2x0FhcXj89G50//FKKifNILx4RXX30VURT3D1neR5zIrkAAURTNqamp87Ozs/FHEdS813C73SwuLjI3N4cgCKSnp9Pc3HxXB9Lt1hmv53oqo9HI8PAwOp2OmpqaPSMPcrmc/Px8RkdHg6r92Q9hmliaT/0t14eepGfsh2zZVijNfhsbN9M8YWtr5L/pTfS1biG6fYutXOe7sd5OrDb6bIgukdhq6Srt4BPIHBwcpK6uTrLgox+CIFBZWcng4CDd3d1UVlbS19dHTEzModSw/QbLlZWVQXWLTU1NkZ6eLjltODc3d6AEAfgIm8fjkTS3RVEMWdT2IPV1P+Li4jAajQcSWJVKRVhYGCaTSRJJyc3N5dKlS2RkZEh2P0hLS2NpaYmlpSWSk5MlvcYPpVJJXV0dV69e5fTp07jdbnp7e6mpqQlamkUmk1FZWcno6Gig2D2YuaSQC6THqXbUWe2G1MxMFpVKnCoVYkICEYKAe3UVx9jYXVEsQalErtcjj4pCrtejiIoiJyOMHnGStyU8wMDCiywZe0mOrUQQBFZXVxkbG+Mb3/gGH/rQh1CpVNhsNlZWVjh37txdYxEEgeTkZJKSkgKinElJSeTm5u76nZCp5ETwCluR72P62XXyPhCHNvnk3b/n5uZ2pOuVSiXZ2dlkZ2djNpuZnZ1leHiYhIQEMjIygrLHOhBhYfDBD8LXvgYLC3AMGlpPP/20cXV19YchP3GIcGKJFcDm5uYPfvazn5V9/OMfP7lKmPgWhvX1dWZnZzGZTKSkpFBVVbVvekMQhECa4bAWJ/cTJpOJ4eFh5HI5FRUVkm7iqampTE5OsrW1FbTI3V5QKrScKfsL+id+wvj8a6yszqLx1FH84IPYLl7E8PjjbGf9ER7HTe/AMBW4dhKr9U4rmiQl2hTp02x2dpbZ2Vnq6+sPrRguCAKlpaWMjY1x4cIFYmJiJNc53YmxsTESEhIC0hFS4HK5mJub23XB2Q02mw232y3pb7e+vi6JiLhcrpDaL+l0OlZW7q67uxOxsbFMTU1JOqe/iF3K+/HXukxOTkruyPST7CtXrhATExP0fNJoNFRXV9PW1hZQWT9salUQBAoLC5mZmQnIMQQznsx4FRf6LdidXjSq3cmyIJejzsxEYTJhPXeOwbk5KisriYqKwru9jWdzE4/JhMdkwr25GfjdtbSE12olNyuCiUfTMPyulzXRzLv+8Z2cCsvjCx/4AA2RkfQ99xzhiYkIJhPeqCiGhoYoKiral7z7N8GpqanMzMzQ2tpKeno62dnZO8iloFAgw0nqA9vM/zaKyaeMOwVETwD8VlN7Ra79Njr+bvShoSEcDgdpaWmkpaWFZqP/l38JX/0qfPOb8MUvHv18t8Hj8dDa2uoG2kN64hDi5MyGXWC1Wl94+umnP/fxj3/8RKqw324v49cTCcZeJj09nStXrpCdnf26kVSwWCwMDw/jdrspLi4OaiH3E4n+/n7Onj0bsjHJBDlZCW9ifnGKLecEDzZ9HJlMjiM7m/Uf/xireZvmMw/x3rc24NXIdxCr7SUntkUXqW+R1g4uiiKjo6OYTCbOnj0bElKgUqmQy+VYLBYcDkfQabGNjQ0MBgMNDVJ8zm9hYmLiroVjP8zNzUmOpkmtrwq1ELDUiJVarcblcuHxeA58//Hx8QwMDEg6Fnxdey0tLWRlZUlepNRqNcXFxYFO0GDvB2tra6hUKkRRDIkjQ2ZmJhqNJkCupEZkMxPUiFiYXXNSkLL3PFZnZWF+9VUyExKIj48P2DXl5+ejCguDPdwavE4nsZsmfjHxPJ99+VUuv/BbVGo5p96Wg3NuDs/mJni93J7Qi1MqEWJjMd4R+fJHwmRhYQg3SZdMJiM7O5v09HSmpqZoaWkhOzubjIwMZLJbAqFKtZuc98Yy9h8GJr9vJO9DPgHRk4ClpSUSEhIOjALvZ6OTkZFBQkLC4delnBx4y1vg8cfhH/4BjmhXdTva29uRy+VXRVE8sbIBJ5pYiaI4k5ycvGWxWOJPiuK4XwF3dnY2oIB7WHsZv3XI2traoWpq7iX8MgFWq5WioqKgiqNvR2xsLNPT0ywvLx9o3isFoigyMTFxk9yG4XAnIpP5Fj91Vhbxf/EXOH5hIsFkoU7vpt1jR4EMpeCb+uud2wgK0FccvMP3er3cuHEDQRCora0NSfpqZWWFubk5mpub2djYCKR0pIbmPR5PIPUTzHgcDgfLy8uSo1WiKLK4uEhjY6Ok441G44FeexDawnWQTqzgVp3VQXNZEASSkpJYWlqSJIoql8vJyclhfHyckpuelVKQlJQUsK6SWv4giiKDg4PYbDaam5tZWVkJCIgedX4mJiaiVqtpb2+nqqpK0iYqLVaJXAbTq44DiRWAc3qaiLIyGhsbGRsb4/Lly1RVVe0ZFZWpVPzwF7/kqx/5BF4BPvJXf8kbfz8OpXab2NqPoJCp8G5t4TaZcJtMTPT0kBQejmx7G/f6Oo6pKcQ766gUCuSRkShuI17yqCgy9HrSSkqYNhhoaWkhLy+PxJsEQfR40CbcEhCd+qGR3PfFIVPe/w3y1NQUp0+fDuo1t9vo+B0/BgcHD22jA/ikFx59FJ57zld3FSI899xzloWFhe+E7ITHgBNNrADcbvfPXn755U/80R/90X2bsbvZy5SVlYXEXiY7O5uRkZETS6wcDgejo6Osr69TWFgouXB5P5SWlnL16lXi4+OPZAy6vb1Nd3c30dHRNDU18Vrnb4kK25nP92jC8Apm5m1r/PK5V1DGvxFNlo+0eJ1eNm5soy/VotDuvwi53W46OzuJjo4mPz8/JBFGk8nE0NAQ9fX1yOVy4uLiqK6uprOzk4KCgj09Fm/H4OAgmZmZQd/4xsbGyMvLk7z4bmxsEBERIWkD4fF4cLlcklJINpstpMRKLpdLLsr111lJ2SSkp6fT19cniVj5j/d71gUTgSwtLeXy5cvExcUd+Lm4XC46OzvR6/VUV1cjCAIpKSnYbDa6u7sPbaF0O/R6PXV1dXR0dFBcXHxgg4ZKISMlRrVrZ+DtUKakIKhUOKan0d50ligsLCQhIYHr168HzJT949/Y2MBut5OcnExtbS1//J53EfMXtfxR0UOUilpaer7C+PxvKM76PeSRkcgjI1n0eFDU1JBwB7n12mx4Njdxm0y30o43f3eNj+O1WHYcHwnow8Nx9vQwJQiEccvSJjxbTcbbo5n58QazP1kn850xCLsYSd8rbG5uolQqj5QK1uv16PX6Q9voBPCGN0Bhoa+IPYTE6uc//7kd+E3ITngMOBmxy32wtrb29He+8x3j/bi2w+FgYmKClpYWxsbGSExM5IEHHqCkpCRknn16vR6XyyWpk+lewuVyMTQ0RFtbG9HR0Zw7d46kpKSQEAqNRkN6erokz7bdIIoiMzMztLe3U1xcTElJCSIerDYDEbqdUTCb07fI/rLll/z3tjZsghvlhgXb4CCmQTteu0jM6f3THA6Hg7a2NlJSUigoKAjJZ2C1Wunu7r6rhiUiIoLGxsZAcel+3VkGg4Gtra0DlcbvhM1mw2g0BmXMKlW7CpBc6A0+chxqT1C5XC5JSkGqUCjcUjyXGg2TyWQB0dBgoFQqKS8vp7u7e9+/vcVi4fLly2RkZNylm5abm4tGo2FwcDCoa++FsLAw6uvrGRsbk9TxmBmvYnHdicu99/gFuRxVRgaO6ekdj0dHR9Pc3MzW1hZXr15lbW2NL33pS+Tk5PC3f/u3AJSXl/ODb3+P8qwiurYniY7IIiXuNOPzv8Hu2AR839np6eld69xkWi3KpCS0RUWEnzlD1KOPEvPOd5Lw4Q+T/OlPk/Lf/huJn/gEce9/P/q3vY2IBx9EU1BAmF5PhNeLV6lkaH4+MHf0ZbcERBd+tXnvNKN2weTkZMhqdv02OvX19VRXV+NwOLh8+TJdXV2sra0d/D5lMp/0QkcHXLsWkjENDw/jcDjGRVG0huSEx4QTT6yArs7OTpvljl3EccHr9bK8vEx7ezvXrl1DEATq6+upra0NSbRmN2RnZ0supD1uuN1uxsbGaG1tRafTce7cOdLS0kL+vrOzs1lZWZEs0OeHw+Ggvb0dk8lEU1NTQIDSajMA4p7EymmzEhkTg5idjsYrY/3ZZ1l9dQ5VjJywrL3rYLa2tmhra6OwsPBQ3Xp7vYeOjg6qqqp2rV3xFyB7vV6uXbu2awu4y+Wiv78/qJo+P0ZGRigsLJT8OrfbLSll5sfa2prkY0OdCgTp6UCNRoPL5ZIc4UpPTw9KIiU5ORmTyRT0pik2Nha9Xr+n7tv8/DydnZ2cPn16z6hmSUkJNpstZNpxarWa+vp6VlZWDiT8mfFqPF6YN+4ftVJnZeFeXcVj3blGyuVyysvLycvL4/z583z+85+nqamJz3zmMzuOq9blYHRbmHEaKMn+fbyih+GZ/wR8kdzCwsJD1UAKCgWKmBjUOTmEVVUR+eCDRL/1rcS9//0kf/KTpP/jP1L44INMT0/T1taGyWQivt4nIGpst2JovT/yi06nk83NzUOXaewHrVZLQUEB58+fJzMzk7m5OS5cuMDIyMj+8/t974OIiJBJLzz55JNbKysrXw/JyY4RJ55YiaIout3up3/yk58cq9St2Wy+b/YyycnJrK6uShYWPA54vV6mpqa4dOkSMpmMc+fOkZmZeWzipTKZjPLy8qA0c5aWlrhy5QpZWVlUVlbuuGlatpcAiNDtbFe3OXznttutREREYJd7iUzJQFVxDoclHLVnAO8eqvAbGxsBAiRFEFMK/AKgBxX+C4JASUkJWVlZXLlyBaNxZ9D2xo0bFBQUBB3t2draYmtrS7LmFvg+d6m+dCBdvwpCX7wOwdVZ6fV6SXpWACkpKSwtLUmer/4Ou8PY1hQVFTE/P7/DscBfT7e0tERjY+O+dXiCIFBVVcXy8vKR1M5vh1wup7a2FqfTSW9v756ENCNehQBM76Fn5Yfqtjqr3eD3F/3IRz7CF77whbu63Eq1GagFBV3WCcK1CWQnNzO9fJnZhaFA2vC4EBERQU1NDSUlJQwPD9Pe3k54g4C+XMvSq2bWe+59BmJmZobMzMxjbYQ6yEbnrjUsIgLe/35fndXy8pGuLYoizzzzjM3j8bx4pBPdA5x4YgVgNBqf+D//5/8c7EERJFwuF9PT01y6dInBwcH7Zi8jk8lISUkJyg4jVBBFkbm5OVpaWnA6nTQ1NZGbm3uk2iepiImJITw8/MAogMvloquri/n5eRobG3clBZbtZUAgXLuTAPkjVjarT+LB5nWilatxRdSCIKLa7mH1scew32ENsry8zI0bNzhz5kzI5oIoinR2dpKeni6Z2CQlJXHmzBmGhoYCqtiLi4uIohhUKs+P4eHhPS139sLs7KzkaJ3X68XpdEquK/J6vSGfa1JFQuFWnZUUKBQKoqKiJNnh+JGQkIDNZgva0kkul3Pq1Cl6enrwer2YzWYuX74cWNCl1Ln4idDY2FhQY94PgiBQXl5OWFgY7e3tu6ZctSoZiXolMwfoWalSUxGUyrvSgX5cvHgRgD//8z8nJSWFy5cvs7K4gn3VhcPoBotApZjDsHkRm9NBQfqbUMjV3Bj/CZWVlfek0zoqKoqzZ8+Sm5tLX18fxqxptBkK5n62gWX83gmIiqLI/Px8yKLqUrCbjU5LSwu9vb1sbGzc2oB87GPgcvk6BI+AtrY2vF7vVVEUT1bdzC448cXrAKIoTqakpBiXl5fjj9pJJooiBoMhYIKcmppKbW1tyJSfD4vMzEyuXbt2aJPiYCGKIsvLy4yOjhIXF0dDQ8N9ESotKSmhtbWVhISEXSMXa2tr9Pf3k5eXR2pq6p6fjWV7iTBNHHL5zvfgJ1bb276Ilc3rROtVsdGzTVSRlsRH3sf6s89i/MEPiDh/nogHHmBmdpaFhQXq6+tD9pmIokhfXx9RUVEH2t7cCZ1OR0NDA6Ojo1y6dAmXy0Vzc3PQY9jc3MTpdAaVKrBarQiCIDldZzKZJEtweDyeY4mI6nQ6yWQpNjaW2dlZyZpTGRkZzMzMSI7ICYJAUVERw8PD1NXVSXqNH1FRUSQlJXH16lVcLhenTp0KmuTfLiB6GNHQ3SAIAvn5+TvkGO68f2YmqOia2MbjFZHvUcy9V52VH+985zvJycmhoqICuVxOTEwMg9+dY3nxFplLJ4l0khhlDQRIEz6BV+Ziom0dudKMTCEgKEBQCMjkAsLN332PCwhyIXCMlNJwKQAAIABJREFU7ObvgkLY+brAcdx6jXLnY5FqPWeqzrK2YWDUPEbUZjpTzxrJ+2A8unsgILq4uEh8fHxINeGCgd9Gp6ioCIPBwMTEBFtbWz5trIwMNI8+6tO0+uxn4ZD31G9961sbi4uLJz4NCK8TYgVgsVi++dRTT335U5/61KEEMaxWK7OzsywvLxMTE0N2djbR0dEnRj9Ko9Gg1+tZWVkJiQzBfjAYDAwPDxMZGUldXV3IUzHBQKFQUFJSwo0bN6irqwv8PTweD0NDQ5jNZs6cOXPgGC3by4Tr7o4Cbd8kVs899zxanYofil1EToXhtnqJqQ5DGach/sMfxvSLX2C5cIGNwUEs6enUveENKENINMfHx/F6vRQWFh7q9f6uqdXVVURRZGlpKWgSPjQ0FJTdDQSnXQU+Inw/04AQXCpQq9XidDrxer2SSF5MTAx9fX243W7Ji1hsbCxjY2NsbGxILuoHX/3Z2toaFouF6urqQ0dOtVptoNv07NmzIdtEpqeno9FoAqTt9s7UzHg110atLG24SIvd+3ukzsrC/NpreKxW5HfUGyqVSurr6wO/azQaElLjMC5ZsRatkJaSjlat47JpCLlXTpmYytrKBi5mcaMjSV+B6AavR0R0iYgeEa9LRLTd/Nkt+p53+34X3SJiCKoxosgGwedBPPbdFYo+mYBaEzodpzvhl5ypra09tmtIhSAIJCQkkJCQgMvlYn5+no6ODhIefpjCl1/G++MfI3v3u4M+r9Pp5JVXXnECvwv9qEOP1w2x2traevo//uM//v5Tn/qUZF2CO+1lMjIyKCgouCdprsMgLy+P7u7uYyNW6+vrDA8Po1ar99WKuddISEhgfn6excVFUlNTMZlM9Pb2kp6eTmlp6YHkwSt62NpeJSH6bs0gm8OLQg5Vp8rZ8thhuQttnwZlpJyIPN/NTqZSEfXWt7IiCIQPDhKzuspqdzeqzEw0BQVoCgtRHqEgdG5uDqPRuIM4HgYzMzPo9XpKSkoCHZuVlZWSxBuNRiMymSyohd1P4IKJjhmNRk6dOiXp2OMoXIfgUoHgiwyZTKZAI8R+8FugLCwsBBV5LC4uZnBwcAdR2AuiKDI1NcXs7CxlZWVotVo6Ojpoamo6dEQiMjKS0tJS2tvbqa+vD4mIKPjEU6uqqujo6KCysjLwGWbG+8jU9KpjX2IVqLOamUF7myzC4uIiX/nKV/jLv/xL8vLyAo9rk1UgblNyPp/+yRvERsWSUBrBS+ZuhNl1zp87w7rVQvfoD0gtjiA1vjqo9yN6feRKdIs7CJfXzS1idvtjbtFH3G4naTdf53GJWD1mrrRdITU1lZycnGOJKBkMBsLDw+/rBnk3KJVKstPTyf7tb/HeLF6fuHIFe0UFGRkZQW0UXnrpJRH4hSiGgvoeP143xEoUxbXU1NSJ4eHh+KKiov2OC9pe5qQgLCwMjUYTVPGvFJjNZoaGhgAoKysLrS9UiFBeXk5raysbGxtsbGxw+vRpyWmLbbsRr+i+q3AdwO7yolEKfPOb36SwphxduBr5lJyYB3QBvRmXy8X169eJr6gg7Q/+AOf8PPbRUewjI5hffhnzyy8jj4lBU1iIpqAAdWZmQIH5IBgMBqanp6mvrz9S2stqtTI9PR1YXMvLyzEajXR0dJCWlkZOTs6e5xdFkeHh4aA9GtfW1oiOjpa8GHi9Xux2u+Qb/JrJhkwZ+sVAoVAE1QgSGxuL0WiURKzAlw7s6uoKilhFRUWhVCoP7Jg0m8309fWh1+t3EKns7GwGBgaorKyUfM07ER8fj8Ph4Pr165w5cyZkadioqCjOnDlDR0cHBQUFJCcnE6GVExshZ9bghH2CpLfXWd1OrF577TX+/d//nfe///07jtck+gihYFbS2NjI+Pg4tt4FZFkCmykCERERhIefYWLhNQamfk5ybCUymfRlTpAJCDJAKRCa7beePE9qoJY3MzOTzMzMkG7ux8fHQ+a/GjJ4vfDss/BP/wRjY8hqa+Hb3yb3oYdYNRgYGRnBbrdLttF57LHHjMvLy4/dm8EfHa+L4nU/DAbD15588slde1ltNhujo6NcvHiRmZkZ0tPTeeCBBygsLHxdkCo/8vLyGL+jkPqwsFqtdHZ20t/fT35+PmfOnDmRpAoISAosLS3R0NAQVC2IxervCLw70mdzeJF77XzkIx/h1VdfIXMkCRCIOe2bE3a7nba2NjIyMsjLywv4mEU98giJH/sYiX/zN0T93u+hiI3F2tGB8XvfY+nLX8b47LNYu7rw7CMDsrm5ycDAALW1tUfaqYqiGDBqvv08sbGxNDc343a7uXTp0p6aTAaDAa1WG/TfPhjtKvC9X6n1VW6PyM9vyLg+fzy1jYIgBC0UKhVarRaZTBa0VIi/1mq3rkK/fEZvby+lpaWUlpbu+FtnZGRgt9tZXV0N6pp3Ii0tjbi4OHp7e0Oqt6TT6XxaVxO9/K7j3+kde4Zo3RpTK9tsWOZwuXdPzQoKBar0dBx3yM1cuHCB6OjouwiDJsH3mdiXXYFar7z0bKJNcqbkRjxeD4IgozT7bWzb15hauhSy93hYyOVycnNzA9/VlpYWZmdnQ/L5m0wm5HJ5yHQVjwxRhJ/+FCor4d3vBq0Wfv5zn47VI48gk8tJSkqirq6OM2fOIIoibW1tdHR0sLKysutnYjab6e7u3ga67/0bOhxeNxErAJfL9eIzzzzz9S9/+cvhgiCE1F7mpMCveGs2mw9Ngvwk02w2B9SMTypEUWR6epqZmRlOnTrFwsIC09PT5ObmSj6HryNwd2K17fQieHxpIaVOQ9ZIIsocAZVegcViobOzk7Kysj2jCAq9nvC6OsLr6vA6nTgmJ33RrNFR7DcFGJWpqbdShklJCDIZ29vbdHV1haQxYmxsjNjY2F3TeHK5nKKiItLT0+nv72dmZoaSkpJA1MgfraquDi4l4nK5sFgsQaUOg6mvGpyzYXPJWNoMaliSodFosNvtkjZVOp0Om82GKIpB+XzOzc0FVbMWHh5OeHj4jjpKfzfX+Pg4OTk5e6a+/UbNbW1t6PX6IzVV5OXl0dfXx8jICPtF/4OFSqUiPs3DyOwoFvsMLocJh/v3ean9cbRKA0qFjjBNHDpN7M3/4wjTxOLNisV1YRLv9jaym3+v3/3ud5w/f/6uqJpcLUMVI8e24gJ883RycpLYknisTgNXr16l6lQVCdElxOsLGZn5FRmJZ1Eq7n+aTKFQUFBQQFZWFuPj41y8eDEQ4TtsicDY2NihjdtDClGEl1+Gf/xHuH4dCgp8Eat3vMMnFLoLpNroPP/88x632/198X4qrwaJ1xWxEkVxOy0t7dorr7zye8nJyQF7mfLy8hNTLxQK5OfnMz4+HrTfk9PpZGxsjLW1NQoKCqioqDgxxfm7wWaz0dvbS1hYGM3NzcjlciIjI2ltbSU+Pl4ysbRsL6FR6Xe9edqcXnD7iJVqW4POpiHiTb50a19fX1C+fDKVCm1REdqiIkRRxLW8jGN0FNvICJYLF7D87nfIwsNR5eUxqlZTWV9/5Hm5ubnJ8vIyTU1N+x4XFhbGmTNnWFlZob29nfj4ePLz8zEYDOj1eskmun4sLCzs24W5G4xGIxUVFZKOvTrqi/Zs2UU2tz1E6Y5HckFqtDoqKiqoiFtycjJjY2NBS1cUFhbS3t5OYmIiRqMxIPPS2Nh4IFnSaDQUFhZy48YNampqJF/zTvglEzo6Opieng5auX8/mLZmCNcmkaT9Q6IU28yYIDb6XWTHz7FtX8NqN2K2LrBs7MMr3uzukwEPwkDXPxMekcSm0ed3974Pvo118yQ6TSxqZWTgc9YmKbEv+15748YNMvOzueRupzoih6LCbNrb28nJyaEk+61c7P4yo3MvU5r91pC9x6NCpVJRUlJCTk4Oo6OjjI+PU1RURHx8fFBzaWtrC6fTKTmFfWxoaYG//3tobYWsLPjOd+A97wGJUfqDbHQee+yxDaPR+O3jfROhxeuKWAEsLCx87Vvf+tYjjz32mLq8vPxEE4fDIi4ujpGREba2tiQtzP5d29LSErm5uZSUlJz4z2VhYYHR0VHKysp2+CT69Xu6u7tpamqSVItg2V7eNVoFYHOKCC5fGkKzEoY9wYlD72ayf1pSt+FeEAQBVXIyquRkIs6fx2O14hgbwzYywnZfHxlhYUQ/+uihzu2Hx+Ohp6eH06dPS66HSUxMJD4+ntnZ2YA0w0GkbDfMzc0F1WUkiqJk378Fo5N5o4tErZkVWyTzRidRutBGFIItYPfb20glVv72f4PBEFREWKvVEh4ezsWLFwkLC+P06dNBke+UlBSWl5eZn5+X7Fu4GwRBoLq6mra2NjQaTcgM0Tcs0yTFlFFWWMb4+ATqOTfr1jjeeLrojmO92Bwmtu1GrNurrPzmZ3jSInGJXgaGO4nUa4hKmael518BkMtU6DSxvn/KKjCm0zfwO5weF5v6SNybHsq0mcSqY2lsbGRgYIDlZScpsdVMLPyO7ORz6DT3mYDcAY1GQ0VFBVarlZGREcbGxiguLpZMlEZHR+9vtKq9Hf7hH+DVVyE5Gb7xDfjQhw4tpwC3bHRSU1Ox2Wxcv36dlZUViyiK06Eb+PHjnhErQRA0QAugvnnd50VR/IIgCJcAf4I4AWgXRXG/7cXv2traTNHR0YknnTwcFoIgBHzG9otaeTwepqenmZ2dJSsri3Pnzh2bUnqo4HQ6uXHjBoIg0NTUtGvaNioqioyMDPr7+w8s1hVFEcv2CplJu3db2RxeNC6fZUb4eiSzTSu45j00NDSENGUsDwtDW1nJgMtFfEoKsldfxdrVRXiQ2kW3Y3h4mLS0tKDrJ2QyGVlZWYiiyMLCAu3t7UEVzVosFpRKZVApzM3NTcldPldHt1ApBAoi11hzRDK/5qQ0PfTq68HYYMXFxQX00qQiIyODiYkJycTKbDYzPDyMy+XC7XZTXV19qO+rv9EjNjb2SJ1gcrmcuro6rly5glqtDirtuxu27Uacri2iI7IAUESm4RHXMKwZsdnCdoxVEGToNDHoNDHE6fMJ84ziHbaR8NGPcu4U/M2HHWw7jGzbff+s9rVb/wtdxJHB3ORlnFGLTCyWoFJHMDX4HQw3U436xDgcNhmzM+GIcg/DM7/kdOF7j/T+jgt+gu2fH16vl+Li4n2/T1tbW2xvb+/YlN4z3LjhS/m9+CLExcG//it89KO+eqoQQqvVcuXKFfvGxsZX9ztOEIQngd8DVkVRLLv52I8Av7aNHjCJoiitXTkEuJcRKwfwkCiKW4IgKIFWQRB+LYpioJdbEISfAD/f7ySiKHoSExN//MILL3z0T/7kT042izgC4uPjGRsbw2Kx3LWwer1e5ubmmJycJC0tjebm5vsmDBcMVldXGRgYoLCwcE+PMz+ysrLo7Ow8cGduc2zg8Tp2jVi5PCIuj8iZqhpan7qOvC+SS0UDqFNSQBF6Uj4wMEBYWBiZNTWsjY5iuXAB3alTyA6xgzMajWxublJScreEhBT4SXdjYyOCIDA5OUlLSwvp6elkZmbuSyqDLVoH6fVVW3YP/bM2KjPVRAoqkt3KAz3lDgOdTsfKykpQx29vbwdVZ6XX67FarTidzn3TeOvr64yPj+N2uyksLCQ2NpahoaHAhihYKJVKysrK6Onp4ezZs0eKTqtUKurq6rh27Rp1dXVBp4xvx4bFV4AeHZnN9KqDpy4a0Ycr+P1TMVy9epXq6uo90+6qrCwsFy7gtdmQabUoFGoiFSlEht19n9jOsDPWYyRf905khRv0uCbJcYso5WrWLVMsGLoQudm4cHMfMbtylZyUR9BHHJ/NzVHh1xXc2NhgYGAAlUpFUVHRrhHNYP0+Q4KREfjCF+BHP4KoKPjiF+Gv/9pnW3MMEEWRb37zm1tbW1s/OODQ7wL/G/j+ba/9Y//PgiD8G3BM1Zy7454RE9EHfxuN8ua/QDGaIAgRwEPAzw461+rq6le/8pWvSG/jeR3C7zM2MjISeMwfgWhpaWF7e5umpiby8/NPPKlyu93cuHGDyclJ6uvrDyRVcKtYd3x8fN/Iw63C9V2kFm6Kg0aFa9GZ9EyaRyhPyeS6bYLHV1/B4Ardd21iYgKHw0FxcTGCIBD5yCN4t7awXr0a9LlcLhd9fX2HMlj2Y2ZmhtTUVFQqFUqlksLCQpqbmxEEgdbWVoaGfH5qd8Lr9bK6uhp0ashoNEpSdL8+bsXjhbIUEa1WS3qcisV1Fx5vaOtSg00FCoJAZGRkUNYzgiCQmprKwsLCXc+JosjKygqXL19mYmKC/Px8GhoaAuQzLy+PqampQ/uDxsfHEx4ezvQequXBQKfTBbSodjP8lop18xRymYoNaxxPXTQSqZPzZw/FkZkaHxAo3av7Up2dDaLI6JUr5Obm8tprr+15ndH5YVCI6OwJbIbH4xXg4ZRHaaz4a95Y90X+S/PXeKT2v9NY/tecyn83+emPEhd+iq7OG0F1f94vREdH09DQQGZmJt3d3fT09OwQvDWbzdjt9nsXrZqehg98AEpK4Je/hM9/HqamfGnAY+xGvGmz1iqKomm/40RRbAF29WwSfDfQdwLPHMMQ98Q9jfgIgiAXBKEHWAVeFUXx2m1Pvw14TRTFA+9soihOLi8vz9xOOv5vRFxcHA6HI1DAfOnSJdbX1zl79izFxcWvi+7H9fV1WltbiYyM5MyZM0Gll5RKJVVVVXR1de3qSQa3my/vIrVwk1jNz4wz4LzOux/7L3zpzX/DqZlotrx2vml4mU7rxJHbnhcWFlhZWaGqqipAhNQZGWiKirC0tuINYoEH6O/vJzc399AyIW63m5mZGXJycnY8rlAoyM3N5fz58wGvt+vXr7O+vh74DFZXV4mLiwsqRSWKoqRCcY9XpGPcSm6SGrXg69hLi1Xh8oismFzBv9F9oFQqcbmCO6e/zioY+LsD/XC5XExMTHDx4kWWl5eprKyktrb2rjSbUqkkLS2NqTtkBoJBSUkJs7OzQcs+7Aa/8Oxe/n9SsGGZRpSd5umWjQCpitD6QkaRkZGcPXuWgYGBXU2hVampoFDw21/9isnJyT29NOfm5vB4PeiSVdiWXfTZZoiWh5OivFWXJBPkhGnjiI8uJCu5kdLsP6Dp9Ic5W9fMyMgIAwMD99XwXiri4+NpamoiKSmJ9vZ2+vv7cTgcIe/m3BOLi74UX0EB/PCHvujU5CT8z/8JR0wbS8G//Mu/GBcXF790xNM0AyuiKI6FYkxScU+JlSiKnpt5zjSgThCEstuefhdBsMrV1dX/92tf+9o9De/dDyQnJ3PlyhWWlpaoqamhvLz8vvsaSoHX62VoaIjBwUFqa2vJyso6VPQlKiqKrKysPXV3LNvLqJThqFV375wsVl9EJlyfwB995A/4/Du+yI3+Xt7e+GbaP/EM6gUnPze18/zGFezew6Wj1tbWAnYSd5KRyIcfRnQ4sLS2Sj7f0tISLpfrSIXJk5OTZGRk7BnJlMlkZGRk0NzcTE5OTiBNODk5yfT0dNBpQL80yEF/38E5Gxabl7MF4QEi5lflDnU60D+WYEhzsHpW4GsZV6lUzM7O0t3dzeXLlwECxrT7FaZnZ2czNzcXNAH0Qy6XU1lZSXd3t2TNrv2QkJBAZmYmnZ2dQZ/P43Uxb4SeuQfuIlV+aLVa6uvrmZ6eZmJiYsdzglKJKi2Ni5cvExcXt2sKfHNzk8nJSSoqKtAmqbCtuJiyr1CmlWbt5Nfa0mg0tLa2srl58pcPQRBISkri3Llz6PV6WltbMZlMx6tHaDDApz4FubnwxBPwwQ/CxAT8r/8F90i6Z3V1la6urk2g44inCopXhAr3pUbpZmjvAvAmAEEQYoE64D+lnsPtdv/ihRdesEn1BHu9wWQy0dbWhtFoJDw8nJycnNeN0KnFYuHy5cvI5XIaGxuPVLcBBGqC7rwZw82OQO3d0Sqz2cz08HXSomVcm4LVLYHPffnT/PJjV/jk+z7NS7/8FV/9/U9zXlPMgG2Ox1ZfYt4Z3KLqV8mura3dNXqoTExEW1HB1tWreCSkmBwOB8PDw1RWVh46Beh0OllYWJBUuyMIAjExMdTU1HD27FlcLhdra2uMjY2xsrIieXGVWl91bdRKTLic/BR1wCdQHyYnXCNjfi30dVZqtTqo1FZYWBhWq1UyGdve3g7UQY6NjZGens758+fJzc2VFE1WKBRkZWXtOq+lQq/Xk5CQwNhYaDbkGRkZ6PV6+vr6giKlg7MLjK29g3CtuCup8kOpVHL27FlMJhP9/f07rqHKzOTy8DDnmpru2qQ4HA66u7uprq72NVYkKvDaRdRWFeU66RsBQRDIzc2lqqqK3t5eRkdHQyqUelwQBIG0tDTCw8NJSUmhtbWV8fHx0EbeTCZfUXpODnz1q/DHfwyjo/DYY5CaGrrrSMATTzxh29ra+upRtKsEQVAAfwj8KHQjk4Z7RqwEQYgXBEF/82ct8AZg+ObT7wB+KYri3UUfe0AURbfH43n6ueeeO/kx3SBgsVjo6OhgeHiY4uJiamtrKS8vZ2Bg4MTfAPxmoF1dXVRUVFBQUBCy4sqysjJWVlZ2KE/7OgKXiAjbSazW1tbo6uqirraG9zyYQKROzjMt67gT5CSXxfGBgk8wfGOUp556iodjT/G+6Ae4+B+/4BtTL9JqGcIr4XO22Wx0dXVRXV29b2dW5EMPgShivnBh3/OJokhvby/FxcWo1Yc3bPULTQZrmaFWq1EoFBQXF5Obm4vBYODixYv09PRgMBj2JVlSLJiW1p3Mrjmpyw9HJgiBiJUgCKTFqpgzhjYVCIers4qIiNi3ps9mszExMcGlS5fo6elBpVIFunFjYmKCnu+ZmZksLy8fqbYpPz+f1dVVTKZ9S1Eko6CgAFEUJZO16VUHP70mRyk386fnIvYkVX7IZLKAhEhnZ2eAHCwplfz/7L13fFuFvf7/PpI1bVnee8Z7JXaG40XYhFHo7S2jhd4CHbRwW2hpbyltuYyWDihd9NJFF22BFigtUHYZieOZ4RnHew9ZtmxLtrZ0vn8oEnFiO7akDPj9ntdLrziydM7x0dE5z/l8ns/zjC8sUHOc27rb7Wb//v0UFhb6KoCqo9E2qfOxxIeszyLjWISHh1NTU4PL5WLfvn2YW1rg4EEYHoalJY/h5VkGbzW1qKiIXbt2AR4d0tDQUGAVy8VF+O53ITMTvvMduPxy6OyEP/zB89xphtvt5le/+tXi4uLiHwNc1EXAEVEUx4KxXRvB6VQ9JwJ/FARBiofQ/U0UxZeO/u5jwPc3usCZmZmfPPzww5+88cYbz8DMaXBhNpvp7u5maWmJgoKCZReqiIgIFAoF09PTq2oPzjTMZjMtLS1otdp1+09tBBKJhO3bt1NfX49arSYsLAybw4TDaV6mrxobG2NgYICKigpfy/SGc6P5zet6/vLuLJ84PwLTb2aQ9oVx4e4LARhq7OKf9zzO2z99lpY7Psw1n7qea+N3ESZdueXqcDhobm6mpKTkpCX5kMhIQrdvZ6m5GU11NSGrEJDR0VHkcnlAfkLeyBPvSXejGBsbo7KyErlcTmRkJKIoMjs7y/j4OB0dHYSHh5OQkEBcXJyvIiOKIktLSyf1YmroWUImFSjb5Km6HjtJlxIt58i4FbPNjVoRvHs9lUrFRivaXp2V93MVRRGj0cjU1BQ6nY6QkBASEhJOcNSPjY1Fp9ORmLixqTOJREJWVha9vb0UFxef/A2rLKOsrIwDBw4E5bsnCAKbN2+mubn5pBOi3uk/pcxMftyLxEZ8a93rKCwsZHBwkIaGBsrLywmJi+NjW7dyznHr6+joID4+fpmthTPWQ8ayFhL8vnmTSCQUFBRgmJhAlZKynEwpFBAdvf5HTAxERECQz3teiKLI4cOHfQHnUqmU7Oxs0tPT6e/vZ8+ePWRnZ2/M1NdigV/+Er73PU/778orPZN+AeRRBgOvvfaa6HA43hRFcV1+KYIgPAWcB8QIgjAG3CuK4m/x8IrT3gaE00isRFFsA8pW+d15fi5zLDk5uWP//v3nB+JEfCZhtVrp7e1lbm7OFz+z0hejoKCA5uZmYmNjzyqvKm8kR39/PyUlJUENjz4eCoWCsrIy9u/fT1VV1XsTgaoEX7VMr9dTWVm5rBUTGy7j2uoo/vzuLC/2L7Jri4qZxkVidoYijwjh/PPPp7GxkbvuuotX7/kjjY+/wpt3fYL7b/wKOeqko3+nG7tjCavdSEfrINnZ2ev+WzXnnov50CGM//43Uddee8LvzWYzAwMDVFdXB7R/enp6yM3N9ev4mJ+fR61WL7MNEASBmJgYYmJiEEXRN0QxMDAAeDRJoaGhhIaGrnkyX7K5aB82U7YpFJVc4qu8et+TEuNZ5/isnZyk4OkHN1qxAg+x6uzsRCqVMjMzw8LCgo9QHn9cHYu0tDS6uro2TKzAk983MDDga4/6g7CwMFJTU+nq6vKboB0LiUSyzEB0Ja8uL6kKV0vZFPk8cREbv+nLzMxEqVRSV1dHeXk5P7vtNsRjNGeDg4M4HI4TIq663KO4NVKiDYFrjaKSkhAzM7EC49ddR1poKDKjEWZnYWbG8+/hw55/Z2dhtfabIHhE3eslYt6f16GZnZiYQKvVnmC9I5PJyM/PJzMzk97eXvr7+8nNzSUhYQ3CabfD737nqU6Nj8NFF3kIVUXFBvfcqcGDDz44OzU19eB6Xy+K4sdXef6moG3UBnF2z+mvAxMTE/d/73vf2/Lcc8+dXba6J4HD4aC3t5fp6WlycnIoLi5e8+KkVquJjY1ldHSU9PT007ilq8Nms9Ha2opMJjttGY1arZa8vDyam5tJyPCcgMPUCXR0dOBwONi5c+eKxCI7Ucnl27S8tH+B+DQ18R0w9ZaRpA+HYrMbycqL5k9/fYTXX3+T737nMf79o6fZdFkpmbYlEudGcDiMiKKn3B6mSCfSy1AeAAAgAElEQVQxsWrd2ywNCyO0soKZhlps4304YrSY3TbMbhtLLhu6gTHOL9kW0P4zm83Mz8/7nXJ/ssrEsbET+fn52O12n3DfYrFQW1tLZGQkUVFRREREoFQqfcfzgT4zTjfszPVo7Y73fUqOkiEIMHoKiNXJxOjeXM65uTkMBgMmk4mlpSViYmLIzs5elygfPK0lm82GzWbbcCv3WEPgkxniroXMzEwaGhrQ6/VBGcUPCQmhvLyc+vp65HL5Mlf6Y0nV9TVKaltHiNRsLI/Si8TERObn53nooYe4rbwcR0MDbqsV/cIC4+PjVFZWnvAZtFtGyIpJRgwsk9oHYfdulH/6E5rbbqO2t3d1rz1RBC/pOv7hJWHex8QEtLd7fl5aWn3lavWaJMwdGcnM5CQFNTUeEXl0tMdH6ph9olAoKC4uxmKx0N3dTX9/P3l5ecuPA5cL/vxnuP9+j11CVZXn/+edF5ydGAT09fUxMDAwLopi55nelkDwvidWwJ59+/Yt6PX6qDPiQrtBOJ1OBgYGGB8fZ9OmTRtyS8/JyaG2tpbk5OQz7l01NTVFV1cX+fn5ft2lB4LExETMZjODw68QIlXQ0daHRqPxkVO36MJuX8RqX8DqMGKzG7HajSgFI+nRKewdSeechBHcLal0KH6GXfPe2TkqDX7wi8swmaRYnBZ6kPN/332bO2+5mszEJByuReash+iZeIe4+HIfQTK7bSy5bZhdx/3f+8i3I+bnAc1w3ES/EAMfDTDv68iRIxvOrfPC5XIxOzu7oUqHXC4nXqPB0tZG1MUXE5qR4SMnw8PDWCwWlEolYZpw6ru1pEZJiTw6e3G8NYNCJiEuPCToAvZjW4FeSwiTycTi4iJGo9GnpQoPDycyMpLc3Fw0Gg379+8nISFhw473XuuFjbi3e5GQkEBfX9+6Y6xWgiAIlJaW0tDQsGqqwUahUCjYsWMHTU1N7Ny5E7VavYxU3XxBDEtmTxh5ZLh/epyZmRmuueYahoeH2fmzn1EiihgOH6bLaKSqquqE1ua8c4lR+wybEzZhG3LidohIZAFqOXfvhl/8gri+PiKqq2lra2NycpLNmzcv34+C4CE1Wq1H5L1e2GwnJ2Lex+io51+DAUQRCXAC3ZZKISrqBBKmio6mNDoaa2goY/X16EJDSS0tRTs25jH3PHIEtm71xM9ceukycnY24JFHHlnQ6/UPnOntCBTve2IliqIYFhb28GOPPfbIvffee+YjzFeB2+1maGiI4eFh0tLS2LVr14a1EDKZjPT0dF9o55mAw+Ggs7MTu91OVVVVQELrQJCVlUXv1AJOpxuLshmn083bB/+OzW7E5ljkGO9ZH2QhKtIijrBovYJGdwpXyFykjn8M7VXzKOXhKOThKOVa5LJQBMFDdv/89t95dG8H//ViAyWXVnD+l64msqiGQ+hA9+IJ65AgoJYofI/YEK3nZ6kC6fA4tHQSf86FaJPScJsdvDHazFDUIm5EpPh3kjMajVgsFr+rFDqdjri4uI15VzkczD71FEqdDrG1FXluLvHx8cs0gFarlYN98yzZXZSo52hs7MfpdOJ0OpFIJHR0dKBUKlEoFESHShnQO1laWkImkxESEnLS7RFFEZfL5YuIcTgcvqqRzWbDbDYzOzvLO0cHB9RqNRqNxjdlGx4evuI6vDqrjRKr5ORk6uvrycrK2jDBFQSB/Px8uru72bbNv8oPeMhkTk6OL2A8GAgNDaW0tJTm5maSc7bx9D7jMkuF0alBBCREhG3MpgNgbm6OSy65hP7+fl58/nlKrVZsg4OMHDrEjo99bEVH+w7LCADJKVHMimasegfqJP/z6QA4/3xPaPBrryE/7zy2b9/O+Pg4tbW1J+SZ+gWFApKSPI/1wu3GPj3NwTfeYMemTUjn5lYmYrOzHhPPAwc8P1utKIHj6b0rPx/pc8/BRz5y1hEq8MT0PP/882an0/nCmd6WQPG+J1YAS0tLT/z617++/5vf/KbqTFdyjocoioyOjtLf309SUlLAd5IZGRns2bOH9PT0gHLC/MHs7Czt7e1s2rSJ1NTUMxr0bDabcTkBwcWidZQwSRRqZTRR4ZkoZOHLiJLn33CkEs9+r7G7+c0berpjnBSMaYhcykCTsHIL6hPn/yd59Vn8788eZM9fXqb91QbKzivnUw9dRVSYlrL0DxMqVREq9RAphSBDssp+EfML0L3WieT1ZqI/vZl9bftIK0hhyH4Ep+hCKvinnQukWgWeNmBRUdG6Xy+KInMvvohjbAyHRoPQ3Y3bbj8hukepVHJEJyUiFC6tLkAi8WxfT08PgiCg1Wp9JChUImJ1qGk81I1SYsXpdJ4w6WQymXwkyYuQkBDfQy6Xo1AoUCgUaDQa4uLimJub23CGZkxMDD09PWRucCJKLpcTGhrK/Py8X7l73hirjeQuroSUlBSmJqcYahwntSwRqdy/48otihhMTibnHEwYJAxbsnl7zxxRYbJllgpzpiHCw5IJkW6M3BiNRi677DI6Ozv56yOPUNTaim1piYXkZMyZmUxMTJCdnX3Ccd1hGSFZFkVskoZZzFimgkCswsM9rbHXXvOIufEQ5aioKFpaWpiamqKwsDDoQzlrQiLhyPQ0yeedhzQ1df3vM5tPqIiZ3G7akpNRhYWRZzYHbIFzKvDHP/7R4XA4fiOKon8OtWcRzi4W4idEUVyKj49/9umnn77lE5/4xGk88leHKIpMTk7S09NDbGws1dXVa+aJrRcSiYTCwkI6OjrYsWNHELb05HC5XBw5coT5+XnKy8vPuJ/WwsICBw8epHLLrWg0GpqamtiUsGndLUmVXMINu6J5/FUdmbMw/toCeZ9XIEhOJCYGgwGzbp4XfvoXzN8z88tf/pLW1lY+knEZzV2Pc2RQ5MOX/ve6LtyCTIbm/POZ/+c/GXjrLRIzMjCoRLCDU3ShYOOEe25uDrfb7ffQgMViwel0bqg6s1hXh6WlBVdZGWJcHOJrr2Hr6UF1XCtxas7B0LSdS0rDfaQKPJWs5OTkZdscHuugeWyayKQ8yjatfNJ/5513OG+DehCFQoHT6dzQd89rubCR3EAv0tLSGBkZ8TvQuKCggCNHjrBz506/3u9FhjyP8eeMmN6aImZHKDHlYcjCVz81ut0iMyYnkwYHE3N2JgwOpuYc2Jyeyq9UAvERMnLjrKQoxwhTeiqTouhmzjREStzGz0XPPfccBw4c4Le33MKO6WmkycmMlZSQUlZGfnw8ra2ttLe3U1JS4vscZp0mJhwGdoeXIg+VIpEJWKeCZNWxezd885ug08HRyqtKpaKiooKhoSH27t3Lli1bAg6rXi8WFhYwGo0b102q1Z7HMWRMA1SJInq9ngMHDvi0qmeL2bTL5eKHP/zhgsFgePRMb0swcPaMlwWI6enpb99///1zZ9rrSRRFpqenqa2tRa/Xs3PnToqKioJCqryIi4vzredUY2FhgdraWpRKJVVVVWecVE1PT3Po0CF27NhBVFQUMpmM8vJyent70ev1615OtCaEa3fF0BEDtiknhvYTp8cWFxdpbW2lvLwcmUyGVqvlrrvu4sknnyQ5dityMZtrP/wlCovyeeKJJ9bloK0uLUWIjETa2kp2djYhgudi5xT9s2Pz+p35i9HRUVI3cDds7enB+PrrKIuKmE5JIbKwEElYGOaOjhNe29i7iEwqsPU4omSxWE44jmLCQ1DIBMaC7Gflz2SgIAio1WqW1hIcr4LY2FgMBoPfxo3ei7bBsGL02bphn3SDFBzaJab3LtL14ylGnjNgnrTjcotMzTk4OLDEv/bP85s39Dz47CQ/f3ma5xrm2N9nxuUW2ZKp5j/KI7j10li+eXUSn98dx/UXpBEbGeoz9zSZdThdVqI0G6vuuS0WPhIby5u33MLFaWloP/xhBjZvJr64mMTERCQSCaWlpcjlcpqbm33709sGLFalIUgElPEhWHVBJFYAb7yx7GlBEMjMzGT79u10dnbS3d0dFKf7tSCK4gmkMlAIgkBcXBznnHMOsbGxNDQ0+GQdZxp///vf3RaL5UVRFDeWKXWW4gNDrERRnFxcXPz3Sy+9dGqP+DVgMBioq6tjdHSUrVu3smXLllPWrisuLubw4cOn7AvuNQhsbW2lrKzML91IsDEyMkJ3dzeVlZXLBL4ymYydO3fS2dm5oQtSZryC0gu1zCtg6JUF3M73SLnVamX//v1rGoCeV/4Z7vzWh7A7F7jxxhvJycnh5z//+ZreSS5RxBAWhuLoa0KOtv+cbPxznJmZ8RE+fyCKIhMTE+sKxQZw6PUYnnkGWXw8Ef/xH5gWF9FGRKAqKsLa04P7mFBns81N25CFzRmqE7ypvML2YyERBJKj5EGPtvHHywr8i7eB9yJIJicnN/xeLwoKCujq6grIENg8ZkedJEdabYYPOXHmyJntsND7Cz1vPzzB889M84+GeQ4NmhEE2Jal5j8rIvnvy+L4xtWJ3HJJHB/aHsHWrFASI+WESN/77ufn5/syEedMQwBEhmesa7usFgsfu/xy3vja11hqbmbL5ZcT98Uv0uV2ExsXt2wy1as7i4+Pp76+HrvdTod5mDR5DNoQD1lXxsuwTDmCY55cVgaxsZ524AoICwujqsozDbxv3741jWQDxejoKFqtNqCW8GoQBIGkpCR27dqFRqNh3759dHd3+50RGShEUeSee+4x6HS6e8/IBpwCfGCIFcDU1NQ3v/WtbxlOd9VqYWGBxsZGent7KSkpYdu2bae8h61Wq0lKSgooDmM1LC0tUVdXh9PppKam5tTmUq0DoijS09PD5OQklZWVKwrmFQoF5eXltLa2YlxHfIwX23LCcG9TEmIWOfSyh5Q5nU6am5spKipa829Xq8L5yu3f55HH/5Of/foukpOTueOOO9a8qHZ2dhKemAgOB6LN5nfFShRFn7bKX8zNzaHRaNal+XNbLMw++SRCSAhR11+PxeHwOaerSkrA6cR65Ijv9QcHlnC4RCpyV55wW4mkp8bI0c07sDuDd7PgT8UK/Atk9uL4YOaNIjw8HKVSuaEK7LEQXSLmSQfqZBlxqXn8vU/KPwQ7b+TD2CYpUW6BqjG4Tiflc2nh3Lwrmsu3RVCaqSY+QoZ0hZb4sfBOH+r1ekYn2wmRqghTnTxDbmloiI9UVvLXV16he3GRuFtvRXv55bT39KDRaE7wqvIiPT2dnJwc3tj/LjrnAiWq9+xmVAkyXBYRpykIx4xEAhdfDK+/DqvcsEokEvLy8igpKeHgwYMMDAwEPRHDS1pP9YCSNzN0165dyGQy9u7dS39//2kPqH799ddFo9FYK4qi/1+aswwfKGIlimK/Xq8/sHfv3tOyvsXFRQ4cOEBnZye5ubns3LnztJKQ7OxsxsfH/bojXwmiKDI8PExzczMFBQUUFBSccTNSt9tNW1sbFouFHTt2rGkzoVar2b59OwcOHNgQudp1cSSLkRJch6z0DC6xf/9+MjMz1zUJFBdZwKbk80jNM/L8i4/T2dnJpqNj2Ndffz1f//rXmZryGJlOT09jtVqJPnpX7jIaCcE/YqXT6QgLC/N7NB9O7l3lhehyYfjb33DNzxP1sY8REhHB7OwsMTExAMhTUpBqtZjb2wGPXqepd4mMODnxEctJm8PhWPUzTImW4RZhwhC8dqC/FSutVovRaPTrohkWFobb7Q7oe+mdEPRn/Va9E9Ehok6Rc3DQikQQ2JI6xH/9h4orbkqg7GuJpF0TiUwlYeJfC3Q9MsXkmws4jOs/BiUSCSWbczGYeghTJvmmaFeCy2xG//zzfPyKK3i1tZVH7rqLL/7ud4TEx9Pe3k5ISAh5eXlrri8+Ph5blhpBhBT7e1Uc5dFoG0swdVbT09DauubLIiIiqKmpwWw2U19fH7RzMEBXVxfZ2dmnxRcQPC7umzZt4pxzzsHlcrFnzx6Gh4dPebvTi2984xuzk5OTXz8tKztN+EARK4DJycmv3X333Ruv4W8AFouFlpYWDh06RFpaGlVVVadN0HgsvEL29qMXtEBgtVppampifn6empoaogL0VQoGvJUjpVLJ5s2b10XyNBrNhsmVVCqh+KNRKFzQ9Y85pmYTQBG7rsxAgKLMjxCmiuNQz5/YlO0hKg6HA7fbzUMPPURGRgaf+9zn2LNnD1u2bCHkKPl2GY2+ipVjA8RKFEW6u7tPejFaC06nk7m5OR85WgsLr7+Orb+fiCuvRHHUnPbY4GVBIkFVXIytvx+X2Uz3hJX5JRc7V6hWHe9hdSxSoj06xNEg+ln5W7ESBAGVSuXXe8EzmTcyMuLXe8FjcRAeHu5XS9E87tl/soQQWgfNFKapOJI+zi9mXuOP/f+kv/8godHzbLpeSdbN0YRlKk7QYZ0MVvsCjV3/hyBx4jSlrfhdE91ulpqbmfzxj7n1vvt48fBhHvrud7nz+570svb2dgRBoKio6KQyA6PLTIdzjBJFGr1tXT59qTczMGg6q0su8fy7SjvwWEilUoqLi8nNzaWhoYHR0dGAq1cLCwuYTCZSUlICWo4/CAkJITc3l+rqapaWltizZw/j4+OnNKO2oaGBycnJDlEUu0/ZSs4APnDEShTFtsHBwZ5Dhw4Ffdk2m42Ojg6ampqIj4+npqYmKA7HgcDrPxSIpmNiYoL6+noyMzM9F/6zwLLCZrNRX19PYmIieXl5G9J3+UOutGkK3OkOMuYEMhtlTP98hn3fn2Dfr6boeMnAbKcZ25wT0X3iSSZEKmdb3k1Y7Uba+/4GeHRfTz/9NN3d3Xzyk5/k97//PQ8//DAKhQKpl1iZTH61AsfHx4mOjg5Ivzc5OUliYuJJ9+vSwYMs1dcTWlFB6FFfJG9+3rH6D1VJCbjdWLu6aOhZQquWkp984sTRWrEtoUopUWFSxoOos/K3YgUenZW/7cDk5GQmJycDuijl5eXR09Oz4WWYx+xIVQK9JjtWh0hepgSbxEXK6CLv1NZxztVXU3PzR/jCDR/lz1/7LwaaHkQb9Tqh4ePMty/S+ws9PT8bZOadQezT07it1mXbYLUtUNv6E8xWA5XFt7Fz26UcOHBg2X62j46i//WvmX/xRYiJwRIXxwMPPMD/3H23T5gtCMJJEye82Gvqwo3IhZFbqKyspKenh5GREaQqCTKtNHgVq4QET1beOoiVFzExMdTU1KDX69m/f7/fYnBvdT6YgnV/IJfLKSwspKKigtnZWfbu3YtOpzslBOvuu++enZyc/GrQF3yGceavoKcAk5OTX/3mN7/54ssvvxyUsou35z01NUVWVta67rBOJ0pKSqirqyMmJmZD5WOHw0FbWxuiKAbNDiIYWFpaorm5mcLCwhUzytYDL7nyCtBP1qIdHh7GUTxN0e4tmCYd6AatSCYdSKdduMYtjDUddfAOAWWsDHWCDGVcCMo4Gap4GRGadHLTLqV75GUSoreQHOuJxczJyeF///d/iYqK4p133vF4FB21NnAbje+J18X1ld3dbjd9fX1UVlb6tV+8GBkZoaxsxehOH2zDw8y/+CKKrCy03okpPFUnlUq17DsgS0xEGh3NWMcAg/IELtoSvqJWZ62KFXiqVoPTNr+sDlaCRCLx+4IQHR3N4OCgXxFSISEhhIeHYzAY/LbCUCqVvhir9bRsvTCPO1AlyanrNxMbHoIQboR52Nk4DVPQERlH7+FBmsfe03DtefBBcjWL1A228Fa3jtToHaQfKCIrOpbk0AnU8mGk4SqcEQo6U/uwS22UhlxA6JgdicZASUYGTQ0NVJSVYX7nHcwHDyKEhSG74gpiy8v556c/jVQq9YtUGV1mDiz1UabeRGRIGIRARUWFj8wpE6KDV7ECTzvwxz+GxUVYZ6tdJpOxdetWJiYm2LdvH4WFhcvMcteDgYEBYmNjz7im1Qtvp8BsNnPkyBGfMXWw8mA7Ojro7u4eEkXxQFAWeBbhA0msRFGsS0xMHO/t7Y3Kycnxezkul4vBwUFGR0fJyMjYsNHg6YJCoSA7O5vOzk5f+vnJoNfr6ejoICcn54yUnVfD3NwcLS0tlJWVLcsm8wfHkqvS0tJV27U6nY7R0VEqKyuRSqWEpihI2OE5oTpdIoOjFoZ6LcyO2JAZRcIXHETMOJAfcy6XKAWUseUkSUPpG+9EtS0NTVIETqmd3t5e7rvvPhQKhe9CIqhUy1qBTtZXsRoZGSE+Pj4gx/ulpSWfpcBqcM7PY3j6aaQREURdey3CMcaIx+qrvBAEAXVxMe90u5EqPVNmK+FkDvEpMXLahi0YzS60ocE5PUmlUpxO54YrsVqtloWFBb/X6/W0CuRClJOTQ11dHSkpKes697jtbqzTDkJ3qBmbtXFpmZYJ5wSH/vRvnv/Zy/zlwQep/sQnyS3MY990By+0v81QzwCHriwmOqaMSYuFvz7zFBbLv3zLDFOE8+ZXG4iSGnhh6lfMjuipsaTjEvZjkL7XGcgG9O+8gyAIhFZV8eAbb/Dm5z/Pnj170Gg0uN1uX7boRm5Oa49Wq3ZpCn3PeXMM29rasGBA0IfidopIQoJww7t7Nzz0ELz9Nlx55YbempSURFRUFK2trUxNTVFUVLSu425xcZHx8XFqamr83epTBrVazdatWzGZTHR1ddHb20t+fn7A5+d77rnH8EGsVsEHlFgBTE9Pf+3ee+996sknn9zwp+92uxkZGWFwcJCUlBTOOeecs6I9thZSUlIYHx8/aQCry+Xi8OHDLC4uUlFRcdrd29fC1NSUzxwxWH5ZGo2GnTt30tTURHFx8QmEYG5ujq6urhUzyQBCpAI5GWpyMtQe77AFJ0fGrRwatzCtcxBug3hRIEUqBZuISp+LwprLaJcVmMKtcJJ9SaHPXmB6eprp6Wliw8NxmUzINtAK9BL9QE++J/OuctvtGJ58EtHpJOb665Ecd4zMzMys6Eou5BfTM2WhUL1EqGJlM8qTVaxSj+qsxmYdQSNWarUai8Wy4YgaiUSCUqk86TavhujoaDo6OvwidV7I5XISExMZGhryDUWsBcukA9wwJLoIkUBpppq/Gg1M1PdgsFhIUirpnp/HaFjgvPhSauJKaKscYo/pME8baom7sZi62zrQzkro7e6hq6uLoa4RYgoiMXVrePXZWd7sehU4KnrOyGBrYSG/vfdeXCYTLa2tuNPTeauujh/+6EfcdttthIWF4XK5fMaUubm56yZVRpeZ/Ut9lKozPdWqoxBFEduMkyTzJiZn5hBFME/bCAtGiHd1tcdg87XXNkyswFPpKS8vZ2RkhNraWjZv3rymZlUURVpbWykpKTm9zu4bhEajoby83HfOlMlk5Ofn+zVAMzg4SENDgw54N/hbeuZxdrOFAOB2u1976623ZsfHxyOSk5PX9R5RFBkfH6evr8+noTpdkxmBQhAEtmzZQmNjIzU1NSueyOfn52ltbSUtLW3dZfjTheHhYUZHR6mqqgp6S1KtVlNRUUFjYyN5eXkkJCQAnspNS0sL5eXl61qnIAjER8iIj5BxbpEGk8VFz4SV7nErb03ZcKhE5NGQFrqIytROujQVxUgCcy870agsaIuUXHjhhSgUCl754hdxGY0oN0CsvEQ/kGPSmwhwzjnnrPr7ueefx6HTEX3DDchWIOmrRa60m0JxSpwU6ZuA3BWXv5bGCjzu3iESGJ21U5QWHNLvFaFvlFjBe35W/hArQRBITExkYmJiQ62847Fp0yZqa2tJS0s7KUEzj3vKqC0mG0UZKpRygXG7gYH6Ti4qKMC9sEBZWRlNTU1UV1d7WlihWWxRZ9JpGWGP6TB/X2gkShHGrupC/vviC7HbFtjX9lOccRIezv8BR/Z+gYHJXsZdQ4w7hhDUCkKP5hvedffdNDQ0APCpT32KRx99FJfLRXNzMwkJCRuOCXqvWlWE0+xmccCGqc+Kqd+GY8HznZFHyxGKnRzq2U959I7A80sVCk924AZ0VsdDEATS09OJiYmhpaWFyMhI8vPzV6w6Dg8Po9Vqz4qBofUgMjKSyspKZmZmaGlpISwsjLy8vA3dpD/wwAPzMzMzd4tn2tH7FOEDS6xEURSVSuW3HnzwwV899thjazatRVFEp9PR3d1NdHT0ql5JZztUKhXp6ekcOXKE4mPiRdxuN729vUxPT7Nt27aARvSDDe+Em9Fo9LXiTgWUSiWVlZU0NTXhcDiIi4ujubmZsrIyvz3HNCop27JC2ZYVisMpMqDzkKzucQkmsZJOl43ync2kt29n+BkDqfYI7rzzTj71qU/x+pEjXBAZeYzdwtoaK4fDwejoKLt27fJrW72YmZkhMjJy1Qu06Z13sHZ2Er57N8rcE8mR19zz+AuE2y3S2LtIstyCtqsD58JuQlYgX263e83POEQqkBglZ+wsmAwET9VpeHh4Q+70xyItLY2DBw8GRKxkMhlpaWkMDAyQu8JncizM43bEUAEjItuzQzE4TUz0DTOvN1B97Vacc3Oo1Wo2bdq0TDogFSRsVmdQrErniHWMd02d/GO+ibeMbcQYhohyLlKz8wtEhWdS8pFCZg/UMNO4hGPBhSI6hJmmRSJL1Xz729+mtbUVnU7HZz/7WZxOJ01NTaSnp294Hy7Ylxjom+Y83RZmx8yMTiyA6Gm7azYp0JyrISxLgSLScyxHTcupr69n+/btgZ/jdu+Gf/0LBgZgHZXC1RAaGkpVVRX9/f3U1tZSWlq6TENlsVgYGho6K1uAJ0NMTAzV1dXodDqampqIiooiNzf3pNdOnU7HK6+8Mu90Ok9Msf+A4OwTDAURNpvtmeeee25+rYm5mZkZ9u3bx9TUFOXl5RQXF78vSZUXGRkZLCws+BzIFxcX2bdvHwDV1dVnFalyu920tLTgcDjYsWPHKS+Dy+VyKioqGBsbY8+ePRQUFASsE/BCFiKQl6ziqvJIvnxVHNtjB1HLXTSNbeNQ5rNYo4cZ/cc856WdT3Z2Nj945hmci4tIj/Kpk1Ws+p9fQZ0AACAASURBVPv7ycjICHgfreVdZTl8GNPbb6MqLSXsqMP08TjWZuFY9E5amVt0UZHvuWhYVoi4cblc69IJpUTLmJjzRK8EA4FMBkZERASks1KpVEgkEhYXF/1eBni+1+Pj4yeNTTKP2zEoIU4bQlqMnAmHgZEGj3HrrqoqRIsFt9VKamoqdrvd57HmhUQQKFSl8vnY3VyjKUO0GBiISOBwRiWHBSs2twOpSkJcjYaCL8WTdk0kEqXA+EseP6widnD7Z7/E97//faampnj33XfJzs5eF6kSRRHbrJOZxkUGn5xl4CED57ywmcimcJAIxJ+nIfszMRTflUjGx6KJ3h7qI1XgmZAuKyujubk54EggX7xNAFUrLwRBIDs7m9LSUlpaWujr60MURV8LcL06rLMR3qSBXbt2ERkZSX19PV1dXWsep/fdd5/RZDL9ryiuc2LnfYgPNLESRdFlNBq/evfdd88f/7u5uTnq6+sZGhqitLSU0tLSs0pv5C8EQaCsrIy2tjZ6e3s5cOAAJSUl5OXlnVXCe6fTSWNjIxqN5rS2JaVSqU+4PTk5eUpM8Pr7+shLjeXWyzYRpVExsPAxZndMsRTXjfFdGddffBXt/f281HMYYclTSVmLWNlsNqampvyaTjsWDocDk8m0oojfMTXF3HPPIUtJIfLKK1f9PFYSrgM09CwRrpJQXBCLLCkJywreauvVKqXGyHG6QDcfnEmvQCpWEokEuVwekAFkoE7s8J6JY19f36qvcZpd2A0uJiSeapUgeNqA0Wnx3HTTTeQdDfN1zc/7pANdXV3YbLYTlmW2GZjs+gv5k4e5Wl1IgjyK140t/GjqBd4xdmBx2xGkApElanJuiSX70zHL/LD6/zqN2yBBIpGs2bp2WdzMH7Yw+sIcR36s48hPdYz/awHzlJ3hbB26K2co/noiOZ+NJeH8cELTFAjS1c8VWq2WnTt30t7efgJp3BByciAjIyjEyovw8HCqq6ux2+3U1dXR09NDaGjoGbfsCQYEQSAlJYVdu3ahUqmora2lt7f3hJic4eFhnn/+eb3ZbP7LGdrU04Kz50p7imC1Wp999dVXdd4Tkslkoqmpie7ubgoLC4NTNj7LIAgCbreb0dFRampqglaVCRasVit1dXWkpqaSnZ192kiVKIq0tbURGRlJVVUVoaGhNDY2ris8eb2Yn59nenqanJwcNCopn7oglsgwGQdGK4j6cBkhuUY+HHUHGYkp/FsywIG+J5AADvfqOV29vb1kZWUFTIzHx8dJTk4+YX+7FheZ/ctfEFQqoj/+cYQ1LoTz8/MnHE8zRgf9Uza2Z4cilXgibhwTEziPy9o7mb7Ki2AbhQZSsQJPO9Cf3EAvEhMTmZqaCtgHKDU1FZ1Oh/WYTMZj4dVXGUNhS4aHwE44DNRcdB6///3vkR3V8Djn5gDPNHF+fj6tra3Ltm3JMkNt649xuMzUbL6dzZFbuCnmAj4bezGpihjeMrXzo6kXeHOhlSWX1TMFmK4g42PR5N8Rj7IQlnocRBzIIHWomK63+n1+cqJLZGnExtRbRnp/o6fj+5MMP21gvt2CMkFG8oe05H8pnuFPTdByTh/by7KQqjZ23KvVaiorK+nv72doaGhD7/VBEDxVq7fegiCeH6RSKYWFhaSlpdHb20tYWNgpNeA83ZBIJL4JekEQ2Lt3L4ODg74b2K9+9atzs7Ozt3+Qq1Xw/wFiJYqiqNfrb7399tvnDx48SFtbG1lZWVRUVJySgMszjbGxMRoaGiguLkaj0fgcis8WmEwmGhoaKCgoOO02D729vYii6JtKysnJIS0tjfr6er8rGsfC5XL5Qqu9JChMJeXmC2OIDJPyt3ozigsziKsM56kb3+burQ8yZx4Ft5O+yXfpGHgO49LEsmVaLBZmZ2eDsq9WmgYUnU4Mf/0rrqUloq+/HukaAm+LxYJcLj+B4DX2LCGVwPZsj1ZNdVTfd3w7cL0VK61aSphSErRA5pCQkIDyz/wNZPZCKpUSFRXld/afFxKJhJycHHp7e1f8vWnEhggk5ahQySW4RTeDs+Mo9B7SLj1KiF1HiRV4SJ9MJmNsbAw4SqrafoLTZaW65A4iNe9VSVPlMXwi+lxujb2UbGUCexcP8yPdC7y6cBCjy4woiowahphJHib/zjgSLwnHOS+iaU+m77FZ+v88TccPJul7fAbduyYQReJ3acj6dAzFX08k8/poYsrDsGsd7F/qp1SdSVSIfze93ra/Xq/3P9B6924wmaC+3q9tWA1ut5uhoSEqKysxGo00NTWtWDV8P0MqlZKdnU1NTQ02m409e/bw5ptvUltbO+J0Ol8509t3qvH+bOxuEC6X6+20tLTRmZmZiIsvvvismoYLFux2O21tbUgkEt80Y0REBPv27SMyMtI37n8mYTAYaG1tXZdhZ7AxOjrK3NwcO3bsWPb5Jycno1KpaGxspKSkZF0RL6uhq6uL1NTUEyqgYUopN18Qwx/emuHJvQY+XhNFmiQCff1mpP8G2U1G5IoI+sffpm/s30SEpZGWUElK7Ha6u3s3NJ6+GkwmEzKZbNlxIIoi8//6F/bhYSKvuQZ5UtKayzAMDRF9XBvR6nBzaNBMSZqKMKVH/xWi1SJPS8Pc3o7m3HMBD+n87W9/ywUXXHDSyTBBEEiNkQeNWHmX6Xa7/ar6RUREBBwblZaWRn9/v9+Gt154g9dXIqnT/VYW5bCtwHP8zThNtL60jwf/5zdUdHeTk5ODoFD4KlZeFBcXs2/fPtRhsL/nlzhddqo330FE2Mq6qER5JNdF1aB3LLDHdJiGxR4aF3tJM4eTZ42hoqLCY1VRoyC2Moz5wxam9s5jHDUTVaBBm6smLFNBiHrlz8IzCehml6YooH0llUrZvn07HR0dHDp0iNLS0o19/hdcAFKppx0Y4NDIseju7iYhIYHo6Giio6PR6XTU1dWRn59PYmJi0NZzNsBryZCZmcmFF164NDU19fkP6iTgsfjAV6y8GB0dvfHee++d/SCSKp1Ox759+0hKSmLr1q0+TYNcLqeoqIiWlpYzXm6emJigvb2dioqK006qpqenGRoaYtu2bSueWKOioqioqKCrq4vBwUG/1qHX6zGZTKuShlCllJsujCFGI+OpvQaWtoTSO/4nLnvgCkwPDhKjyefSnd+jJOtqRNFNW99feaXh6+iM+3z2EIFgJdH6UmMj5gMH0Ozahfqo/mZVNDWRsGMH6d/+9rKnWwbM2J3iCbmAqpISnNPTOI5WTH/2s5/xne98h1tuuWVdkR/J0XJmTS7MNv8rTcu2J4B2oFQqRSaTrdqCWw8iIiJYWlryO+7EC0EQyMvLo7t7ebSa2+3GqXNi0QqkRHu+/xMOAyONR4iJjfGQKkFAGhGxrGIlim5MljE0cTr2tf/kKKm6fVVSdSxiZVo+GlXJLdqLSDCqGFYt8HpUP/9caGLG4Wn9eXVYBbclEfdJGRMJPYQXrE6qTC4LzUt9bFFn+F2tOhaCIFBSUoJWq91421+rhcrKoOqsDAYDBoOB7Oxs33Px8fFUVVUxNjbGwYMHgypNOFvQ3NxMf3//flEUG870tpwOvC+IlSAISkEQmgRBaBUEoVMQhPuPPi8IgvCgIAg9giB0CYJw+2rLEEXx0NDQ0P4333zzA8OWnU4nra2tvrJy0goVh7i4ONRqtd+EIRgYGBhgcHCQqqqq0z4gsLCwwOHDhykvL19z8kalUlFVVeVzft+IqN3hcNDR0UFpaemalaVQhZSbLogmJtxDrpJLUyhIyeLJ539F1DMRhLhDyUq+gPO3fYPztt6NQpKEhS5sjvXlHa4Gt9vN9PT0MoJm7e9n4dVXUebno7nggrUX0NoKu3cj2O0on3oK3vV4+rlFj8VCSrSM5OjlPmCqwkIQBMxtbQBcd8NlXH1DJX19ffzkJz856TYfaxQaDAQiYIfA24GCIJCcnMz4+Ljfy/AiLi6OpaUlTCaT77mxYRtyB0RlvufuP273TAR69S4AIZGRWE2zjE3v58CRP/BKw9fZ0/IwozN7kIdEkB710XWRKi8MBgPdze1cHVfNlxOvojw0h3bzCI9Ov8wzhn3oHO/NDSUnJxMbG7vmjZ63WnVugNWq45GVleVr+2+IIO/eDQcPQoBtXHgvQqysrOyE84RCoWD79u3Exsayb98+vzMqz0aIosgXvvCF2ampqVvXep0gCL8TBGFaEISOY54rFQShQRCEFkEQ9guCUH7qtzhwvC+IFWADLhBFcQtQClwqCEIFcBOQCuSLolgAPL3WQqampr5wxx13zJ7p6k0wYDAYqK2tJSIigvLy8jVbfUVFRYyNjTE/f8Jw5CmFKIp0dnZiMBioqKg47WarZrOZgwcPsn379nVZaEilUsrKytBoNNTV1a37Qtze3k5OTs66SKNaIeWmC2KI1cp4LfpcbvrItYwahnjrtZfo/8MMTrOnQiO4wlFTBrgZ1TWtaztWw/T0NDExMb5qnXN2FsPf/kZITAyRH/0owlrtke5uuPhixNBQWn7/e0hPh9tuA4eD/kkbsyYXFbknVhakGg37Fhe54DOfoX/4AAd7f8UNt5RStSuPBx544KQEIylKhiCcXQL2QC92KSkpPi1TIBAEgYKCAo4cOeJ77kirx84hq/g9T7b2gS7mx/Scu+tcFpbG6Rl5jbbEwzQXdrP/yO/QGTqJiyxge/7NXF75Ay7e+Q1mdbZlhG01iKLIwMAAnZ2d7Ny5k+joaLRSNZdHbOPOhCupDsun2zrB/02/wpOzexi3e0hpVlYWMpls2bZ7sbxatXEz15MhOTmZwsJCGhoa1vU3Ah5iJYrwxhsBrVsURVpaWsjJyVlVZygIAqmpqezcuZOenh46OjoC0gaeLXjppZfcOp3uXVEUu07y0j8Alx733EPA/aIolgL/e/T/Zz3eF8RK9MBrBCM7+hCBW4EHvBMGoiiuqdQWRbFvdnb2tWefffZ9e7S63W66urro6upix44dpKenn1R/I5VK2bp1q88z6nRt58GDBwHYtm3baY9qsNvtNDc3s2XLlg1NfQqCQFZWFoWFhTQ2Np50ZHtiYgK3270hcblaIfGQK2GJxZ2fI6Uwj8eaH8E0aabvtzM4jC6OHDlCSeFOosI3MaKrD6iVe2wb0G21MvvkkwiCQPQNNyBZi3AODsKFF4JEwvRTT6Hetg0efRQOH4af/ISG3kXClBIKU5cTSlEU+dGPfsTHf/ITluxm3m3+P5TyCNTiNj5523akIYLPnXs1KGQS4rWyoOmsAq1YRUZGMnecNmmjUCqVyOVy34RcIIiOjsblcjE/P4/V7sY4YkeUgDbF83nanRYa99YBIItq5+0DD3J46J+4QkQSh1RU5/43l1X+gO35N5MStwO5LAypVOrzWlqrYutwONi/fz8mk4mqqqoTiEKYVMUl2lLuTLiK8zXFDNv0/Er/Ok/MvM2wXU9xcTGLi4snTOydqmrVsYiJiWHr1q3s379/fRXIrVshOjrgduDg4CByuZz1pICoVCoqKytRq9XU1tae9hviYMLlcnHnnXcapqamvnSy14qiuAc43oBMBLzaES0wwfsA7wtiBSAIglQQhBZgGnhDFMVGIAu47miJ8BVBEE6auKzT6b76ta99be54f433A4xGI7W1tYSEhPjsAtaLsLAwcnJyToveyuFw0NDQQERExIbCVoMFb4RGXl6e3zERUVFRVFVVMTQ0RGdn54oXGqvVSnd3N5s3b97w8lVyCR8NHybGbqDmQ99gzmBgYfMIzlkLU7f+krCGPiK0EaTFV2IyTzFnGvLr77DZbFitVrRaLaLbjeHZZ3HOzhJ13XWErBJKDcD4OFx0EZjN8MYb6LRaj7D/yivhqqsQ77sPXfsgO7JDCTnGV8hqtXLzzTfzla98hcsuO5/7Hv8wqTGxbMv9POGKIooKdvC7Zz/FlVdddtJtT4mWMT5rxx2E49WbF+gvpFIpISEhAU9veYOZg4H8/Hy6urpoGzajNYM0BgZ171DX/nP+fuB+MneVcMt3Pkrplq2U5tzA7p3fpTr2v0jpD0XrCEcQTjz9a7Va4uPj6enpWXGd8/PzPj3nli1b1rxhUksUnB9ewpcTruLi8C1MOub43cy/+d3Mv9EWJTE2Pua7cTnV1apjER4eTkVFBR0dHUxMnOQ6LZXCxRfD6697Kld+YG5ujrGxsWVpGCeDIAhs2rSJrVu30t7eTk9Pzynx3DvV+NOf/uQwGo3PiaLor5Hbl4CHBUEYBX4I3B28rTt1eN8QK1EUXUfLgSlAuSAIxYACsIqiuB34DfC7dSxnamlp6c+/+c1vgjdydIohiiJ9fX0cOnSILVu2+ISoG0VycjJyufyU6q0sFgt1dXVkZGSQlZV1ytazGkRR5ODBgyQnJwcs+lYoFOzcuROZTHZCa9DrmlxYWOh3tmFoRBhXDL9E0TmVfPGnDSSU7yDzhkgSn/8mSb/+G4d/OIXQmEfobB4jE/5pPsfGxnzVNOObb2Lr6SHiiitQrDWZp9d7SJVe77lTLylhbm7uPWPRn/4Ut0vk8j/d57NY8OLOO+/kj3/8I1/52q185n8KiJZryW+NxmmXEBoaSvGm/0Qqd9I98jKvv/76CQaCxyIlRo7VITJrDPwmyJsXGAgC9bMCj1BZr9cH5SIZEREBEhvvto8RZXUzJ99Pe/8zmK0zqOO3EhYXwbf/59dUltxKRmI1KkWEj0w716iC5OTkMDMzs6xCJ4oig4ODtLW1sX379nVVXrxQSmScoynky/FXcbl2K3PORf48t4eOTUb6n/wV5q9/ne7nH0dmXAx4EnC98Goqh4aGGBgYWPvFu3fD1BQc1QtuBA6HwzcJ7U/VXqPRUF1djdvtpq6uLmAH/9MJm83GPffcMz89Pf2NABZzK/BlURRTgS8Dvw3O1p1avG+IlReiKM4D7+DpxY4Bzx391fPAukoHer3+3u985zvzwfAuOtUwm83U1dVhs9moqakJ2HuruLiYsbGxgNsaK8FoNPo8tFYS0p8OdHR0EBYWRkZGRlCWJwgCubm5FBQU0NTUxOjoKKIoMjIyglKpJD4+3u9lS8PDUbjtpGweISJVzV9rZ3lzdJDZq64goucVNFEmjJ124g5djfjXCgaf1jPXasZpWf9F2UuszK2tLNbWElpeTuiOHau/YX4eLrkEhofhpZdgxw5sNhtSqdR3YbAlp7HnP2+nsOllNO96tCfeKui3vvUtHv/DI5zzIQkR4SmUR1+DZHYRy9AQarWaiLBU0hMqeenVp9i9ezePPfbYqpviFbCPBqEdKJPJAm6Dh6iMdA4/hdnqP7mSSCTExsai0+kC2haAhSUHbbNuMGoIcUuIy0nmoh33cdGO+1hwaGl94i3cc8v/5pW8rI6HN72htbUVp9OJ1WqlsbERk8kUUCyWXBJCRVgeX4q+lJv/Nco1532e6q/ch/oHP2D7Nbfz9eLPEr1jF9x+OzzzjIfMnELIZDIqKiqYm5ujs7Nz9Ur+JZd4/t1gO1AURQ4dOkRubq7feaTgOWby8/MpKipi//79DA4OnvEp7/Xg0UcftVosll+JohhIvtCNwN+P/vwM8P+L14MFQRBiBUGIOPqzCrgIOAL8A/CONJ0LrFy/Pg6iKBrNZvND991331lL/70X76amJt+XKhg6JalUyrZt22htbQ149PtYzMzM+ITiK2XJnQ709fXhcDjIz88P+rKjo6Oprq5Gr9fT2NjIwMAARUUB+uwcNeOU4yB8Sz+1f7ufT3x0N29vvxTB6SBt/gWK7kok6iMWFhM6MA1ZGHlujs4fTNL/hxn0DYvY51ev5szPz3v0Lzodc//8J/LMTLSXrdGCW1yEyy7zaKief97n3TM7O7vsM20dMrPn0ltwZOXAF77A3554gquvvhqXy4UrZJyYzAEiNRlUl9yOpmALhITg6unxifsL0q+kaHMqFdVF3HPPPauSjOjwEJQyISg6K2+F198LkstlZ0D3IkuOft4++H2mDCdmIa4XgbYD5xadvNA8x49f1DG+kE2O06PZyijeQpjK45P17r/f5oVvPM74cWJ5iUKBJDT0BC+r4xEaGkpGRgbNzc3U19ezadMmNm/eHNg5aGkJfvpTQrJzyfzcXUTJtQw//iMe63qSPz71TRbv/qpHz/Tb38K110JiIuTmwqc/DX/4A/T3+92OWw0SiYStW7cCcODAgZXF4klJUFKyYWI1MDCAUqkM2k1mZGQkNTU1LC4u0tjYGFBr+1RDr9fzyCOPGGZnZ78X4KIm8FzbwXOtX9kd9yzD+4JYAYnA24IgtAHNeDRWLwHfBz4qCEI78D3gM+td4Pz8/E+feOKJqbWyt84UbDabL0i0uro66EQlNDSU/Px8Dhw4EJSWxPj4OIcPH6aiogLNGs7dpxLj4+Po9fqTWh4EAplMRllZGWazGZfLFXDQq/Son5fU7sItdfLFmz+M22nj+q/dRGtkHJaf/wJBIpJSuglLaROmy54n+7OxxFWH4TC5mHh5ga4f6ej5xTRTbxuxTDmWEYeRkRFSo6KYffpppBoNUdddh7DahdFigauuguZmePrp90JoWU6sRFGkoWeJ+PgwJP/3KPT303njjej1eg73v8WBI38gWptFVckXkIWokCiVKHNzkQ4NoTo6uapUaMlL280nPl+CxWLh7rtXlk1IBIHkaDljM8EZuFAqlX57UfWNv4XFZiCUcpRyLQ0dj3F48J+4TxKevRLCw8Ox2Wwb1mvNmpw83zDHT1/ScWjATJqklysM02SOhONS25FHeT5bp+iiZd8B1OFhlJaWnrCc472sVoLD4WBubo6FhQVyc3MDMzadmYF774W0NPjSlzwZfP/6F0JbG+mf/jKfz7uO886/lZbdH8L56queqmlDAzz8MBQUwD/+ATffDNnZkJwM110HP/+5pzUXhPOXIAgUFRURFRW1utfV7t1QW+shh+uAXq9ncnJyQ7qq9SAkJISSkhI2bdpEQ0NDUOw7TgW++MUvzs/Pz98hiuK620KCIDwF1AN5giCMCYLwaeCzwCOCILQC3wVuOTVbHFy8L4iVKIptoiiWiaK4WRTFYlEUHzj6/LwoileIolgiimKlKIqtG1imU6fT3XTzzTcbzqay6uTkJHV1daSlpVFaWnrKLAoSEhKIiori8OHDAS2nv7+fkZERKisrz5i7+8zMDP39/Wzfvv2UB0339fWRmJhITU0NAwMDAU1aeitWErsDp+giIjyMniOd/NfNn+PH83pUwwP88rYHMCy6SUuoQL/QgxBrIvFiLflfjCf/dk9siPD/2Dvv8LjKM2/fZ5pmNOq9W5Zsy2pWteVegAALJIEADjUsLYSEALtJNiFssiQkIXWz8AEh2QUChCQQSgxZE4NNXNW71XuXRmVGI2n6zHm/P8aSbSzbki3JZuG+rrlkT3nPO+ecOed5n/J7VBKG/ZO0PDtM068N9L83zkS7DaNhGMUHHyAcDkJvvRXl6drJOJ1www2wfz+89BJcd91JLxuNxpkigPYhB6MTbjKiZa575hn+DPy7UslLP/oy7UNvEx6UwvqMr6FSHj8XdBnpTGoFGAZnnkuOu5QVK5Zzwy0befHFF09bJRgXqsFgduFwnf8N9FwlF+wOMy09e4gOyyY2bB2ro7/EsqhNtPTuobD2KexO87zHnE9j5mGzi78UGnnqfw0c7bGyIVrHNVMj5NatRDceRdSlAaiumGJwyLt/h11muoobyNuwdlYPkyo4+Iw5VgaDgcOHDxMaGsq2bdtoaWk5N+92d7c3rJeQAD/8IWzeDEeOwMGDcNVV3n58gEJSsCwylsTERO9iT6mEggL45jdh1y5vrl9dHTz7LGzfDoWF8PWvQ1aW18N1zTXws595nz8PL3xSUhKJiYkUFhaeep5ccYV37P37zzqOxWKhrq5uUa9HERERbN68maGhISoqKhY0+nC+FBUVsX///ha73f7m2d99HCHEzUKIaCGEWggRJ4R4XghxWAiRJ4TIEkIUCCEqFmveC8nHwrBaLIQQR1pbWw/t2rXrgssvuFwuqqqq6O3tZePGjQuitn02Vq1ahc1mm/MF/kSEEBw9ehSz2TyT4H0hmJiYoK6ujnXr1i36HMxmM4ODg6SkpKDVamf0ew4fPnxWWYbZkNRqFL6+KB1unB4X4eHhxMbG8tLzz/KNklImVSoKKot5ereBxr5UPLKKHkPJzOd9wtREbPZn5b3hpH0rirjPB+EToWKszELnS0ZCi+KxDTgJvuEG1KfzOLjdcNttsHs3PPcc3HrrSS87nU4UCsWMuGpJqwW9j4IffONL7N69G9uPfoRS54Pvt75LZHAa6zPuR6U8nsxvl138LcrMazcl86y2mr8ai+l0GFAo1KQt/zyfvWklGWtSTqsRFReqQQgYMJ2/1+pcJRcaunYhhIeM5dcRFhaGyTRBzqpbyV31JUyTXfyj8glGx+eUhTDDtFjomRZ1g0Ynfz40xtO7h2nut7NlmS+3q3VE/cOKojcIKaOftH+JIXKbPylpq2htbUWWZY72tTDWNsCl23fMOq4yOBiP2Yz4iLfH6XRSWVlJd3c3GzZsICEhAZ1OR0pKyvxa+hw9CrffDsnJ8JvfeD1M9fVeI2njxtN+LD4+nuDgYGpra0/eLwoFpKfD/ffDH/8IPT1eKZCXX4Ybb4S2NvjOd2DTJq9a+o4d8P3ve7Wn5pnsHRMTQ2ZmJsXFxSfLYmzeDDrdWcOBbreb8vJysrOzF32hqVarycvLIzo6miNHjlwUfWE9Hg933XXXmMFguP2T0LrmdHwiegWeCYPBcN+DDz549PLLLw+fS4PYxWB0dJS6ujqSk5OJi4tbMnmC6STVI0eO4Ofnd7zq6yx4PB4qKyvx8/MjIyPjgvVetNlsVFRUkJ+fv+gXsekGyyf2G5sW9IuIiODo0aP09fWRmZk5JzHSaRT+/ijsDpxCQVjShuOlFwAAIABJREFU8T5hmWvz4StfIed3v6MvwMpD992JVqvh3gejWHXbFSgUJ3si1H5KQvP0hObp8ThkGl7YB4PLGJe+gO9YIFpZICk+cpxkGe65x5so/J//CV8+1ct+YhjQOOWmpd/O1nR/LvnJj5mYmCBhlUz9YDaZzxQS3hyJIvO4cTvgNPL62BF8ujRsak1kJKaOoyldVNo6CVT6kqFLwD8mlZ8/F8Zn1l0+6/6JC/OO17cAQqG+vr5Y5hjKmWZ8soceQzEr4z6DXheOj9o9I26ZELWeQP94yhr+m8O1T5KW+DlWxn9mVhmDj6LRaAiy2xmtqCA8P/+k13pHnRyon6BlwIFWLbF9hZ7kYYH5AyuTAhyJLZgSD7Nj8zdRqbzb8vHxITIykt7eXgorvMb3Fds/M+u2VcHB4PHgmZhAFRSEEILBwUGam5tJSUk5JScoJiaGwcFB+vv7z1wNePgw/PSn8L//C3q916v0r/8K8XNXcl+5ciW1tbW0tLSQkpIy+5skyRtOTEz0GnAAw8Pe7R865H38+Mfe81uphJwc2LLF+9i8GcLDzziHkJAQ8vPzqaioID09nfDwcNBqvd6yMxhW08nqSUlJc76WLgQxMTGEhIRQXV3N0NAQaWlpZ+wysZg8++yzjrGxsT8KIea30vg/hvQJNipnCAkJ+da99977/Z/97Gfn35xqHng8XiFIs9lMdnb2aRV5FxuLxUJpaemcwnnTwpuxsbELVnl3LrhcLgoLC8nIyFiSZPmGhgY0Gs1JPb4+yuDgIE1NTSQmJpKYmDgng3P0lVeo11n4x/oghASp2jg2+q0mwSfMu/JfswbPL37Bv5vt/PpXP8PldHDZ5+/g//37v7IsxBfhcp3ycJhM2IqK8EnNYUpsZaLJjl+yDwlfCEbtf8wgEwIeeMAbXvnhD+F735t1fnV1dURERBAeHs5Xv/MLjjZ1s/tPTxHgq6S5+z0au98lNjib/NueQTKZoKEBoddTMtVCTW0PqZXLCBzxVkRpdCZ0/I3xL3+eOjFMm2MQGYHWYWEFgXT/rZe7br3jlOP5X+8OERmkJtpzlO3bt8/tgM2C0Wikt7eXrKysOb1fCMHhmv9kyjbMZWsfQ63yJt8fOnTopE4CLred6tY/0D9SSWRIBnkpd6BRn7kKzNHVxehLL4HHg29uLkFXX023SWZ/3SQdBgc6jcTGJD+SRgXjJRZklyA42xd3WjO1hpfJTbmDhMiCk8Z0uVwcPnyYxjQ7YsLJfcuvnvUGa29rY+zllwm7805c4eHU1dWh0WjIyMg4rXTI9Njr168/ucOALHurR6dDcWFh3vDf174G56ghJ4SgtLSU6OjoU/pbzpnJSSgq8oYdDx2CkhKYzmlLTT1uaG3Z4u0mMAt2u53S0lKSkpK8kiVPPunNEevs9Bp1H6G5uRmXy7XgeVVzRQhBd3c3XV1dZGVlLalxB968sjVr1gwMDQ2tEkLMbwXzf4xPDStAkiRVRERE05EjR5LPdONcSMxmM9XV1cTFxZGUlHTBvD7TjIyM0NzczIYNG05b+WO1WmeEN5ciVHk6ZFmmuLiYxMTEJZF1GBsbo6mpiY0bN571OLndblpaWhgdHSUzM/OsFzfj229jqanBtWoZR+MU1MWrcGgURI44yKo3s/Y7v0RhtzP8la8wYLPwL7VlFO49gq9/KN+/9xF26qdQi1MrA+WoKOLuvRdUKowVVvrfM6NQSyRcF0TAKq03dPLzn8O//ZvXy3Ca73Xw4EHy8vJ48MGHeOGF58nffCWFH75Da//fael5j/iIdeSk3I6isBg2b8b5zX/l/etvxb9ET9CYH+pgBX55SkzjRqjwR80AEandhN10AxaPg3pbD0fGSmjpHOK3l32bbbdfzc+f/k/SdfH4KryevzeLjLQPOVgb1MyOHdvndtBmwW63U1VVxYYNG+b0/v6RSsoa/4fslbeQGL0Zh0umodfG4bpRHB4Vvlo1GpWERi2hUUk4nQbMllZ8VBLLorIJ0occe12Bj8r7Hh+1Aml8jMk/v4rW14cxnQ82o0xl9HoG1WH4aRVsXKEnyQjGwik8NkFguo6oS/yRghzsLfsBAfpoNq/5l1nPxabWZv6kq2KLfyqXBc5uQLrHxjA8+SS2ggL6j3md57I4GR4epqOjg4KCAiSXC/70J+851NDgNU6++U246y5YgAWi2+2muLj4/BPnp3E4oLz8uEfr8GGYDvXFx3srYKcNrdTUmd/DtMp8eHg4yS4XUlqaN2R+330nDT84OEhXVxcFBQWLnud5NqampqiuriYsLIxVq1Yt2Xxuuumm8Xfeeec+q9X6+pJs8CLmU8PqGJIkbd6yZcuuAwcOhCymkSOEoLW1laGhoZm+dBcLXV1djI6OkpeXd8pF22w2U1lZSVZW1jmrmS8E0wKgwcHBJCUlLfr2XC4XR44cYd26dfPyKE5OTnL06FF8fX1JTU09bXiw/cMP0dTWotXrkdRqXFoNjbFKKmMEE1rBplcPcsW3n8P8zFMo89bR6CnhH0erePOVIXbc/SRhgb5sjLKQvzIEpUYDKhWHi4vZsGXLSd4H+4iL7r+YsA+5SOz8DYF/+LG359/TT5/WqHK5XOzevZtf/vKXHD58mM3XPsjLv3kCi/XvtPXtZVnURrJX3oIkKRCyYPK6W/D72xu0fPl9bKtWsGx7CMFrfBkYGsBisRBui6PnTSNqBki8JQTf1d5FjMU2wu7qn/PC746y56X3uXv3j4jLTGalNpo1ukQmeoP4e+UkGyM6ufLSzfM4eicju2UK3yln42fXolCf+TfukV3sLfsBKqUvyQn/SnWnjboeG063IMgXAjROfPUBOFwyTrfA4Rbev043DrdgrumrEgKBhN5tIdtUR3p8BuY2f9yTMv4rfYi6NADfGO9xrGp5lZ6hInbkfZcA/fEFxdTUlDdh+OAB3t77N8atE/z8V7/ktsu+cMr2hBAM9vcj/+53eLKyiL/uurnfeIWg6d13CS8pIfSVV6C31ytD8O1ve+URFjjH0eFwUFRURHZ2tlcMdSHxeLwe4WlD69Ch47pZoaHekOGWLbB1K3JWFjX19aiUSjI++1mkvDx4662ZoUwmE7W1tWzYsOGcxYIXmqW+zxQXF3PttdeWGgyG9Z/k3KppPjWsTiAqKmrXc889d/W11167KI3tLtRKYj7U19cjSRJpaWkzzw0PD9PQ0EB+fv45iwMuFPX19QDnrSE1V6qrqwkJCTmnkIQQgoGBAVpaWmY8kyd6A6fDK1u3bj3FSygLmUZ7HyVD1dySdROtl69l6PmnWC20VNQ+SfbKW0GZz66iYR6/fwfJKRn89ulfkRAdTGdnJ3l5eafMR3YLJr/2BIG/exTzuhvRvP0KuhifmblarVYsFgsWi4WEhAQGBwfZunUrg4OD3PTgf7Fux3VsTN5P5+B+lkdvZc2KnSBLGI9a6d4/hqZ3nJTfbMWdlo625BCS0nt+t7a2otPpiIuLw1gxSe8uM2rVCCnfykCp896M6zreoqZxN/9y5y4Skpfzw92/od7ey6RsQz0ViKsyi+Xhvdx52fp5HwcAt8VD919MTHU40EaqSLg+BF3U6Q2B6ta9FLcMYnVvZ9yqQKOSyEjQkZPkS3SgRElJCVu2bJn1sw7nJGVNf2BwrJ3w4DxWxH0Wj1Bjn7IxumcvDqcHn41b8ej8mLI6mDIOsE0fzci+cTweX3z8p4j7Qjx+yccNeeNEJwerf0ly7CXEBu9Ap9Oh0+l46aWXuPvuu/F4PEgKBVGZieStzeeRux5i44aTE8XHx8dpaGhAq9US/eGH+CxfTsj1159+p3k8UFNzsvFxLEHas2kTyu9+16t7togL0ek0hYKCgsVNlRDCq5N16NDx8GF7u/c1vR6xYQOjq1fjc/gw/h0dSKOjoFZjtVopKSlZ/PmdI0sRGfF4PGRkZIw1NTVt/KTnVk3zqWF1ApIkRcbHx9c1NTWFLeSP5ELHvueDEGLG9Z2YmEhvby9dXV2sW7duXknZi0FHRwdGo3FWj9piMDQ0RE9PD2vXrj2v7Xk8Hjo6Oujr62PlypXExsYiSRINDQ3o9XqWnSbHY5rJ++5E9/If+UX50ziDAgizmlhud3BV5kNYrDYe/s6Peem3v0IIwRXX3sa6zGV85b77iIiI4ODBg7z88stYLBY2NTTwQG0tewODUXzlPcJ843jX9Co/+d0PTqmWMxgMjIyMUFRURHhCOhVjCeQmNoHrTZJjLyF92RcYr7UxdHACl1FmPGQKywYrl1UcQfO1r8Mf/jBTYVhbW0tcXNyMp9PwfidDh1Vog+ysfCAZhUaB021lb9ljHP6gjyf+40+89NJL3Hb7bXQ5h6ma6qJmbyxED3BFTgCb/FPntf+tA066/mTEbfHgSDCjGw5GtslEXRpA+Ea/maR+t0fQ3G+nvM1Mu8EFKFgWriE3yZe0eB0+aq+h6BYeXmz4X1bHJZPvvxKd4lQvhRAyLb3v09j1Ln66CPJX3IHztb/jGh4m7I478Dl2zJ3jbur+uwflpA/aKBUBQS14mj5AExtLyM6dqIKD6e/v47evfIuqshY6mx3U19fz9ttvc+2111JXV8eTrzyHKzuI5fmp3BK/g2RNFAcPHmTjxo1oNBpsNhuNjY3Y7XbS0tIICgpi5PnnQQjC7zlB+s9uh9LS40ZUYaE3Vwm8OUXHQmXmrCyOOp1s3LhxSRaHJpOJmpqame+zZAwMnJwQX1s7I1DqKi1FZGVRVFTEmjVrLupr+mLn8j799NOOxx9//HcGg+HBBR34Y8ynhtVHWOhEdrvdTnV1Nb6+vhe0WmM+eDweioqK8PX1xel0kp+ff8HnPTAwMJPDsBAK9GfD4XBQWFjIxo0bF8ygdDgcNDc3YzabSU5OpqWlha1bt5795lRdDTk5WH79c/7xzzuomGrFI0GiKoStgWtI9omiqa2be7/2DY584A1RHDhcyNZNG3j11Vf59re/zRc9Hn4xNERJcDA/zs/nySd/i1Thz4fvf0jxyH4is0IICPZHr9ej1+vZuXMnlZWVrF+/njeKzbQPTpIW+WtSYi8j0nQJI4emcI57mAiz0JjbTU72cvL1yUiy7C2p7+6GpiYICqK4uJisrKyTkp57f/shxv6V6ONUJP1zJAqNgo6BA1S3/JnXfjfAA/d/8ySP0O/eH2bIZsKdW8UG/1VcEZiDYg7GrrHKQt+746j0ShJvDqHZUE9CVCKTB2TMDXb0yzToLvWnZsxObZcNq1NGq7YTpK3gcwXbiQs/Ob/HI2ReNx6h0e5VNFdLSjJ1yyjQryRac2qIfGS8mfLGF3A5LCxr0rNqx13ojlW7WfucdL46htvlQb3WQepnkkCChj17MO3ZQ1J4OMa8PDKvvBIAvd6XTZs2s3XrVnbu3Mmy5OXsNldQae1gmSacG0M2EqD03jR7e3sxmUyo1WqGh4dZvXo1ERERMwsE01tv4aivJyov77jhUFZ2XAcqPX0mFMaWLXCs3+Q0TU1NKBQKVq1addZjsBAYDAZaW1vPmAO66IyPw5EjTNTUUJWXh8LXlxUrVhAdHX32z14ELEb1+cjICJmZmYMGg2HlJz1h/UQ+Naw+wrFE9sb9+/evSE2d38r4owwMDNDc3Ex6evrCJGAuEdNlwwaDgfXr11/w1ZjRaOTo0aNs3LhxSfSyhBCUlZURHx+/KBfNqakpiouLUSqVc89ZW7vW61GorcVkH+W11ucxhizDLkGkKpCNfqsJNiopqRuhsl9HfFQId1wagb9O6VWuvuEG7w1y926vHs+x7zlWamFgjxmlj4L4LwQTsNJbFep2u71Vl7nr+a93h4nyLWKbJgGpYRkuswdXtJuyrCZcSW52hm4kSn3COVJR4Z3vAw/AU0+xf/9+tm3bdtKF3DMxQfev/8akZyv65T4k3RoKasE/Kn6MLGQuzft3FIrjxvyeKjNHmo5pEqmd+PhAjN4Pf60SP50SP60CP633r79OiV4tYfpwEmOZFb8kH5bdGIxKr6S5uRl/f38CQyJp2G9GUWJDCKiNBr90LSujLXT1/ZyV8ZeQkXRyjpIsBG+Ziqi1dZNviyXUrWc00sOrf34VY/8IQUo9CZowItVBREdF86UvfQkhyzz90Fepm6rDoZMJ8V9OVNgawqQY8q2XoPZXsl/sorq5komJCQ4ePMjAwAB33HILP9+8GctIHz8dO8LaglzuuPFnM+f/iGuC14yHGXGb2eKfzg7/DJTHZB5cLhcdHR20tLSwevVqkpOTvcb74OCMEeV57z0U7e1IACoV5OUdT97etMmbZ3QGZFnmyJEjZGZmLnz+02no7u7GYDCctwf5fBFCzOhcFRQULNn3XwhcLhd1dXW43W7WrFlz3ovGG264YXz37t2fJqx/hE8Nq1mQJCknMzPzg6qqqtBzWR25XC5qj3VCz8zMvGgSGueC2+2moqKCoKAgYmJiKC8vv6D5A5OTk5SXl59a5r2I9Pb2Mjo6Sk5OzqKMb7VaKS8vJysri+bmZjweD6tXrz6zAfvf/+3VmSoshA0bKKp7FtNUP1GZd1I41cKw24zGrSBbv5xQayL7Stz4+ii4211B4M1fgNxceP99mCWJ1WZw0fMXI/ZhN2Eb9ERfFsioaQSDYZCqgQloS2TNhIxkU+ETr+RobidHI7vI1i/n6sA8fBSzGLsPPAC/+Q2itJQDk5OzyiRMHjnC8J4OpqQd+CX6sPzWUIanGiiue5bEiKt46bf7uPvuu8nIyMDq8PD23hqi45NpmzTSZ5nAx61H69Zjscu4T5D41bpgfT+E2qAzEgaTVOh1Svy1SmTnFGaboHdciUeGRJ2KnD6BYthDQKqW/qQ/MSH38Jm1P5iRVwDvzfTd8XL+VraXlt/sp6uqmRdeeIFLLrmErdu3cejAwZO+28rsNErLSmDPAbbecw9HPyIgm7dsPX969B0Sbw4hPTeV1tZWoqOj2b59O1u2bOGSSy5hVVISxft/zrC6n+yeVOKuvQNlQADV1k7+Nl6OWlJyffAGVmi9xr/b7aazo4OhxkaW+/igNRqxNTUR39t7cs6Qry+ejAwsWi2+Dz+M6vLLvbpT82RycpLKyko2b968ZF6kpqYmnE4nmZmZF8y4amhowOPxkJSURFlZGWlpaR+rhTMcl4ZJTU095wrvd955x3Pvvff+w2AwzC6Y9gnmU8PqNERERPzyoYceuv/RRx+dl0UxPDxMfX09q1atOrOY3kXIdI/C+Pj4mbyf6fyG9evXL3nLGrvdTnFxMbm5uQQc66u32NhsNkpKSti0adOieceqqqqIiYkhMjIS8CYVNzc3I4Rg5cqVs5e+T056m8HeeCO88AL9I1WUNf43GzK+RkRwGnXmLvaP1GD0deBBJsASQfhrJm750e2IVSloDv4DzmC4yS7B4PtmRkssaCNVODPHmBzoRtmcidYjoU/U4N7o5K8BJbjxcE1QPtm+y0//JcfHISUFOTGRol/+kk2zJHoLj4fh557DOhHJhH0DfokaEm8Jobj5GXr6m3ngtj+TlZXFvn37kCSJ/fv3zxhoNdYu/moqIUzlz22h2/AROqZsHsbbHVjem0C4BRN5WoxhCqbsHqbsMlM271+VQiY32d+biB6sQciCkcIpBveacassBFw2xcr1x5P/hRA8+eErPPvT/6J1bxUBAQE8+OCDbNq0icsuuwyXy4Usy8hC0OkwUGZpo905iFrrw7KuCdJtoaQWXI4kJNr+2om9UYs9qpVVN8USG5XN1NQUo6OjGI3GmYbAAGPmdg7V/IpEn2wiPhjGg6BhYywDox0sH5NZP6FHOzSK3NuLo7MTBgfxGRtD8ZH2JiIkBOlE3aacHBz9/Yy+8AKht9+OduXK0x/Hs9DR0YHVal0y7SYhBNXV1fj5+bHyPOZ9rrS1tWE2m8nNzUWSJBwOB6WlpSxbtuzcNbcuEA6Hg+rqanx8fMjIyJhXuofJZCIzM9PQ39+/Rghx4SXfLzI+NaxOgyRJmoiIiPq5hgTdbjcNDQ1YLBays7OXzLuyUFgsltOuvkZHR6mvr1/ScmKXy0VRURGpqale5eMlQAhBUVERq1atIiwsbFG2MTk5SW1t7ayaWGazmdbWVux2O8nJyURFRZ38nvvug1degcFBZH89fy9+hLCgFNal3UNTUxN6vZ7Q2AgabX0MFO7hM9d9k8mgaF74/hsk7/Blx/IYQlWnL7sWQjBWb2TwXRuyzbtdgx4SL/enK6mDw1ONRKqC2BmyiXD1HAzdV16BL32JnkceIeEnP5n1LY7ubkaffx5WXc1oaxx+iRpCrnNyoPYnVBxw8aPv/zevvfYaO3fuPMmwAmi3D/Fn4yG0Cg23hWxDUaFiYI8Zn2AViTeHoI041TC2WCwcPVrH+vUni2t6ZBcH9j1NYM1lqCZCCF2rJ/qKAJQaBf/v/Zd58Io78A8O5Fv/8g2+/vWvExQUxNGjR4mMjJzVWzFQVURxfzlNGWHY1RDpCWbDB2kou5UEb1TSEf57xi09rIi7lLTEa5EEVLz4Ijl6PUqDAdHfh6HuAzTD4wRP+SD6B1DMohrv0elwhIUhxcbis3w5irg4rwF+7DHq40M3kLd27cmfM5sZ+tWvCPrsZ9F/5LX5sBS/mY8iyzKlpaXExcV5hTuXiO7uboaGhli7du1JeZEnevlXrVp1wTUJ54MQgt7eXjo6OsjMzJyz2PL1118/vmfPnq9OTU39aZGn+LHkU8PqDEiSlJ2RkbGvqqoq5EzW/LRXZ9myZXNW3L6YMJlMVFdXk5OTc9p8gaGhIdra2li/fv2iJ7LLskxJSQnx8fFLeuFsb2/HbrcvqpRDWVkZSUlJZ7yAWSwW2traMJlMLF++nLi4OG+opbzcm7v0zDPw1a9S2/Y6XYOHuaLgJxQeKWPLli3eY1NbC9u3IwcFUvrOy+ztjsY5oYWVrcQkOEnTxpCIFoXdzJRtmCmrgSmbgSnbMG6PHaVDj19/Np2aTUwF+eCTd5R+9xhr9Su4MjAHtTTH4y8Ejs2b8Sks9DbKffRRWH+qXILp7bex1tSgufQrDOz14JeoYaJgL53Dh/nhw4cYGzPR2NhIeXn5KSHFQaeJV4cOkrZ/GbFt4QSs1pLwhWCU2tkLAmRZ5tChQ2zbtu2k51t69tDQtYuNqQ/hqojk3T+8x5hs4JL/uIrd+nLG3jjKE3c9QuAJntOBgQHMZjMfXXjZGhowvvYaPitWEHDzF2kY7sf2uox2XEPN1nZCc/Xk+yxj4v0XcO59l+g6M6E1/Uim442RZR81thAtqvhkrHExtAQLLNFhJLmD0febcCQk0Lt2LfF5ecTExJyxAGK6Q8GJXl8hyww8/jh+GzYQePns7YTmylJ4eT/KdA7gUi28+vv76erqYv369bOGPWVZnumnmJmZeVFK6ZwJq9VKVVUVQUFBrF69+oyh3WMhwA8NBsP5nTj/h1E+9thjF3oOFy2PPfbY0GOPPRbucrmyt27desoVQ5Zlmpub6e7uJjc3l8jIyI+dUWUwGGaaGJ8p3Obn54ckSTQ1NZ31Qn4+CCGoqakhODh4SVvmTE5O0tzcTG5u7qJ9t/HxcUZGRs5aSaXRaIiKiiI6OpqRkRHq6+ux2Wz4rVyJ+r33vAbWfffh4xNI5+BBZJcarSrSq0Lf0gI7diC0Wux/fxvfaH+SggcZNCuwDsbhcJpp9e2g0jlAk6WT4Yl2sJvw9wkkPGg18RHrCA1cg9EnilpzAM5lbdj1Rq4P2cAW/7SZBOk5IUn05OUh+fmhffddrxjp4cOQkOBV6j72W9EkJGCpqEDpGCToknxGiy3oJ5Mwh5WTmr6SV1/6OwDJycmnnBMas5qwN4Px7dXRuLabkKt8idSdPplYkiS6urpOGsfuNFPW+D+EB6fRWufiaz/8Mr/7+1N0j3Ryk+YuolTBfPWWnad4oTUaDW1tbSeFgBydnYz9+c+oY2IIve02HEMw+aoLjV1BWHYbgZW7iPjVc0T+y/eIfuk9Ikt7kV1OhgsS8Hz9IZpuuoPgZ3/Nns/KGO+5gZr7v8xfP5OA64rPsCb3eoYiEnBGR+NrNBI8MUFYairqsxSX6PV6mpubT1qkSJKEtaYGhUqF7jzDeGq1GqVSSVdX15JVyCkUCiIjI6mqqiIkJGRRpWAMBgNtbW0UFBScdlEpSRKRkZFMTEzQ3t5OVFTUx8q4UqvVxMfHMzExQX19PcHBwbOmfhiNRq6++urRoaGhyx577LH5dzT/hPCpYXUW/u3f/u1AfX39l66++uqQE1dGk5OTlJWV4e/vT1ZW1gXXeDoXuru76ezsnHNieGBgIC6Xi/b2dqKjoxfFiGxubgZg9erVS2akyrJMWVnZKZIAC01VVRWpqalzzlVTqVSEhYWxbNkynE4nDQ0NyLJM8JtvIq66Ct3yNAZHaxgb7yAsLAJT/T78rroJ2WXn4K+upEHdQN9wGaPjDYT4NiJEOObRFSxz6FkZLrBodAz5+jHoH44ctJyw4FSWB6czarBwZEyLwykRkW7gzogdLPM5N69A/+gouiuuQP+tb3krzXbt8nrc9u6F6GhYsQKFRoNCp8NSUoJ/WhR+qbGMFlsJsmXgTCoiY/Vl3HbLnUxOTp5kEE202Ol8eRThhOgvBlCzooNiSzO+Ch/iNKf3CPb29hIbGztz46tt+wtFRaU88ch7PPnkU6jVah54/Ftk/eDzxLjDCK0JZLLNgT5Rg8r3+EpepVLR2dlJfHw8CoUC5+AgYy+/jCooiLAvfQnL7lomfvB7Ig4/Q9yefyfg978l6sMSQtBi/MwWDt1zJbt+cCul37iVwa0pDAT2IgcHYhKdjLjNtMVm0ukcZo0rmugW0EgqVq9eTXxODrrVq7E1NmIpLkZSKtHEx5/296LT6ejv78fX1/ek89ve3IxnchL9R5pAnwsBAQH09fWhUCiWrJvE9O+jvLycqKioRfGWjY3/KJr5AAAgAElEQVSN0dDQQEFBwVnTICRJIjQ0FFmWqaurIyoq6oLL1MwHSZIICQkhJCSEmpoanE4nISEhJ51Xt95663hDQ8MDTqez9AJO9aLn01DgHJAkKTs9PX1vdXV1qFKpnBF7zMrK+liV2k4jhKC5uZmJiQny8vLmXdHT0tLCxMTEgnt3urq6GB4eXvJy6qXQ5BkdHaWzs5O155HPAmDq7iZg9WoMl16K5de/xq3soLlvF9pRC5sf3IXPhIOmF7+JIicXP99I/HSR+Oki0Ki9smz7aic42DDF6lgtN2wMZlxMctTWTZ21hzHPJAok1BYtjop8YpKs3LMuGZV07hVfpaWlpKeno5+uOrPb4YUXvE17e3q81YqPPor43OcYef55POPjRD74IOYWQc9bJhwh/Vg27Gf72m/yX//1JA6Hg9CQUDTDfoh2HZEJEWx/MB9dqAan7OYNUyFN9n62+KVxWcCaWc+jiooKVq5cia+vL/2DjVR1PofDlMh/fPt5vvvd75J17WbenixlmSac28K2YWlw0feOCdkNMVcEELpWPzNubW0tMTExBAGmH/0In85O/DweOHgExaQ3tCeWJyHt2A7bt8O2bV6PHV51/Vb7ICWWVtocg0hCEGgZxdcxhSFkOUpZSfpQENnhK4mPjz/lJi3b7Zh27cJeX4921SqCv/AFFKep3p2YmKCuro6NG4+rsZveeQd7QwPR3/nOOR/fE3E6nRw5cmRBtd/mwmLJsRiNRmpraykoKJj3gmu6W8XatWuPn/sfI6ajMUajkezsbPR6Pbt27fJ8+ctf3mcwGK640PO72PnUsJoj4eHhP7///vu/duWVV/oGBASQmpp64YTqzgNZlqmpqUGpVJ5XyXJzczOTk5MLZlxN53AttQCgyWSivr6eTZs2LZoxJ4TgyJEjZGVlLcxq/u67Ea+9Rk9REc1DA6imutn87Z+jHjQg7d0LBQVn/HhJyxS7K8zEhWm4dWsIvj5Kbw85l4laaxcVVW6cQ7E8/NlIgv3Ob8V94MABtmzZcuo54nR61dmfeALa2iAtDff992MwGNAXFBB0zTWYaqz0vGXEFtRN9A0qvvudp/jjH/94yjZsNhtarZbvfe97vPnmmyiCtXgCVSRExpIfm86PHn8cSZJobGzEZrPN3IifeeYZVqWH8MB3tvOZtT9AqfChw2ng1bGDRKuDuSNsx4yUhGvSQ+/bJibbHPiv8CH+2mDUrnFML76Iavdu9CUlKI6p17sjEzFHFyA2byPk4atQJJ9ZWR9gzD3JkfEGqm0duBUQ5tRxXWABccFRZzwvhRBYSkow79mD0t+fkJ070ZwmL7GiooKEhISZnKTJQ4eY+OADoh99FMUCGUIGg2GmU8NSLo4GBwfp6Og4bQ7UfJk2qubbI/REpvurZmdnX3AtwHNlej8EBwfzT//0T4bBwcFMIcTIhZ7Xxc6nhtUckSRJHRMT0/7aa6/Fb9587o1gLyRut5vy8nJCQ0NZsWLFeV/4Fsq4ulAtK9xuN4cPH170VeXQ0BCDg4MLp4tVUuJNAn/uOQrj41n7ne+gbGmh+oknUF5yCbGxsYSGhp7x+Nb32niz0EiQXsXt20NnDKghwwj/c8BOUpQvt2ydW4XQmfhoJd8puN3wl7/Aj38M9fV4oqOZyM9H/9RTaBITMVZb6HnLiDN0APtyF37NMQwPjKLOduKKnMJkMnHzzTcD8MILL7B7925GRkboHu5nZGQElULJ8JABH4WaG2+8kTfeeGNm02uyUrn6i8u4947vsjxmC12OYV4Z20+oyp87wy49pVWNEALj3h6sz7xBUMO7+HUcRvJ4cAUH40pMRHnT7QwpdjA+EU7kNn8iL/E/62/MbrczMDDAwMAACoWC6PgYOsYHSI9IJuqYHMdccPb1YXz9dTyTkwRecQX6goJTtm2xWGZ0pyRJwlpXh+n114n46ldRn6OW0WzU1NQQFBR01lZNC01nZydjY2Pn3fJqIYyqaaxWK2VlZaSkpJyzXtSFxu12c80119gOHTp0p8Viee1Cz+fjwKeG1TyQJCkrLS1tX01NTejHKXYO3gt4WVnZTJXZQnG+xtWSNVmdhdraWgICAhY1SV4IwcGDB1m7du3CfT8hIDsbjxBYAf+mJti1C3HllYyOjtLf34/JZCIsLIzY2FiCg4NnvdF0DTv448Ex1CqJ27eFERWs5r3Cdoq6tdyxI5TkqPPTLXO73RQVFZ22WfFJyDK88w7i8ceRKivxBAej+MEPkO65h57qIYzvqZBQoPSTSNwZgl/i2edWaWlnl6mUaE0It4VupauxnfZ278PfX0/Cml7UKi3bcx9h0DXO70c/xF/py91hl6JXnjD+2Bi8/bbXANy3DzwenGHLGF91NZa0NSiiRwj63I0MFgXhNLqJ+3wwIdmnP9ZOp5PBwUH6+/uRZZmYmBhiYmJmcu9MJhPt7e3kzzP3SbZaMb31FvaWFnTp6QR9/vMoPpLPV1NTQ0REBNHR0Tj7+xn57W8JuflmdOfZZeJEphcsC2GYzJeGhgaEEOdc2buQRtU0TqeTsrIyYmNjl7QgZ6H461//6r7vvvv2GQyGKy/0XD4ufGpYzZPw8PAn7rvvvq//6Ec/+tgEzqempigvLyc9PX1RSpPP1bhyOBwUFRWRnZ295Llqw8PDdHR0UDDLyn4h6e/vx2g0kpmZubADP/00fP3rCKUS6fXX4Qsfab8iy4yMjNDf34/ZbCY4OJioqCjCw8NPCpUMm128vH8Mh0vm5s2hvHW4H43Wl69fff4VrtOVlvMyEITA/txzSE88gU9vL0RGwje+QdWKRKwDgRhX7UX2saJR++Gj9vP+1fihUfsf/7/af+b1XtnKW5OV+Cm0fClsB6Eqf2/hSd1fmHCVsynzQWS/KF4Y2YdWoebu8Mu8/fZmMaZISkK+7josiYmYR43YRDZWkQtaDwpJhYRE4k2h+C0/Naw2NTXF0NAQBoMBWZaJiooiNjZ21pv3tDF+LrpxQpaZOnKEiX37UAYFEXrTTSd5o2w2G6WlpWzduhXZZmPopz8l8Mor8Tsh92ohMBqNNDY2zqrXtpgIIaisrCQoKIjk5OR5fXYxjKppPB4PFRUV+Pv7L2lhzvliMBjIyckxDA4OZgghRi/0fD4ufGpYzRNJklTh4eFlr7/+etb27dsv+l+H0WikpqaG3NxcAgMDF207LS0tmM1m8vLy5mRcTXszUlJSlrwdxHSS7YYNGxZVTV6W5Zkb5EIn88pGI+ZLLyXwG99AcdttZ3yvEAKj0cjQ0BAjIyPodLoZYUtfX1/MFjevHBhjZMKNEPDZ/CDWrjz/dYPBYGBsbIy0tLR5fU4Iwejvf49UWEhoRwfShx8iQkLovmwdvrmp2MP1WMJ8sYZqsPgKnO4pHK4pXO7Zq78tPv60R6cjIZEzMU6YpGForJ6o0DRWptzK8yN7kZC4V5FD0LsfnGJMsXMn8mc/y5TFwlRJCcLlwjc7G//t23Fa9LS/NoyQBavujEIb5s3J8ng8GI1GhoeHZ/Z5VFQUkZGRczrn2traUCqVLF9+BnX7M+Do6sL4l78g22wEXX01vseUwgHq6+sJCAggLi6OwZ/8BN+cHIKuuuqctnMmGhoa0Gg0rFixYsHHPhOyLFNcXExiYqJXgmQOTDcoXkwvmxCCuro6XC4X2dnZF70cgyzLbNq0yVhRUXGz0+l8/0LP5+PEJ8awkiRJCxwEfAAV8IYQ4j8kSfo9sA0wH3vrPwshqs8yVmxsbGxlVVVVxFKpgp8Lg4ODtLS0sG7duiVRgm9vb2dkZIT8/PwzlhlPyxtER0dfkDYQFRUVMx6DxaS7uxur1XqKgORCMG0kzdcTJoRgampq5oZvt9sJDg4mICiMPQ1gnJL5xrWx+KjP/6Lf1dWFEOKcjAPXyAjDzz6Lb2YmwXFx8OMfI/72NyRZPvmNWi3ExUFsLCI2Fk9MBK7IEJyRwdgj/LGH6bEGqTEKK4c0MnYFpJmG0BqHyc/7Gm/3HGD57iIue78ZzYcHvMZUcrK3ddCNNyKnpWEpKWHyyBGE3Y4uIwP/Sy5BfYLKuM1qo7Kikow1GTP7dbpUPTw8nPDw8HmX3U+H7ucURj0NnqkpTG+8gaOjA112NkHXXINCo8HpdFJYWMjWrVsZ+c1vUAUFEXrrree8ndMhyzKHDx8mOzt7yVpSTTPduSE9Pf2sauJDQ0M0NzcvyXVSCHHSdXKpBFXPhccee8zy7LPPPj88PPzQmd4nSdILwDXAsBAi49hzWcBzgB/QBdwqhJhY5ClfNHySDCsJ0AshpiRJUgOHgYeArwB/E0K8ccYBPoJWq71m3bp1L+/fvz/4Ylx5dHZ2MjAwwLp165b0x9vT00NPTw8FBQWzblcIQW1tLVqtlpSUlCWb1zT9/f0MDQ2Rl5d39jefBx6Ph4MHD7J58+ZF2f+lpaWkpKSctxdSlmVMJhPDw8P09PQiJAXRkeGEhIQQGhqKTqc757BFQ0MDoaGhMz0R54v5gw+YOnSIsLvuwicxkQN797ItJQX6+6Gv7/jjxP/394PLdfJASiXExOCJjaErXM1wpD9anzBC6uqIP1yDwiOfZEyRk4Nwu5kqLWXq0CFkqxXt6tUEXHLJTFjN4/FgMpkwGo0YjUZGRkaIjo4mIiKC8PDwBblBl5SUkJqael5GiZBlJvfvZ/LAAVTh4YR88Yuow8Npbm5Go9EQUFSE22gk8oEHznu+szExMUF1dTWbN29ecg/NtCJ8Xl7eaatx+/r66OzsnJNO1ULS19dHR0cH69atW/IerHPh0KFD4vrrr68bGRnJFUK4z/ReSZK2AlPAyycYVmXAN4UQByRJugtYLoT43uLP/OLgE2NYnYgkSb54Dav7jz3mbVgBREZGPvfwww/f/sgjjyxthuYZEELQ2NiI1WolJyfngkhCDA4O0traSkFBwSkhsJaWFmw2G2vWzK4xtJjYbDaKi4sXzdg5kfb2dmRZXpRGsQ6Hg5KSErZu3bqg4xYWFrJmzRocDseMwWC1WtHr9QQGBhIUFERgYOCcbwTTelHnahjITifDTz+NpNEQcf/9HDh06MwVhuBNgh8dnd3o6utD7u/D09uD2mrHuCwS5Y1fJPDmOyAnByQJ4XZjrapiYv9+5MlJfJKT8duxA3tAAGazeeYhyzJBQUGEhoYSEhJCS0sLCQkJhISEnNN3nY3BwUHGxsYWpMGxva0N05tvIlwugj73OdSpqV5vktWKraqK6EcfXbTfY1tbG06nc94h4YVgYmKCysrKWbWoOjs7GRwcZN26dRdEyHM6/Hgmw+9CMDY2RnZ29nBfX1++EKJ3Lp+RJCkR73102rCaAAKFEEKSpHhgjxBi6U+AC8THq7TtPJEkSQlUACuAZ4QQJZIk3Q/8WJKk7wP7gO8IIRxzGW94ePjBX//611t27NiRtn6WHmhLjSzLVFVV4ePjc94lx+dDdHQ0KpWKoqKik3IWenp6MJlMSy4ACsdb5aSnpy+6UeVyuejp6TmvMM6Z6OvrW/AwpizLOJ1O/Pz88PPzmwmfCCGwWCyYzWbGxsZob2/H4XCg0+nw9/fHz88Pf39//P39T9mvVqv1vPJVFBoNgVddhfGPf2SqqGiOH1JARIT3kZt76suAkD28VfseK6JWsSbKKworPB6stbWYP/wQYTbjCQ9nIjubMY0G0dFBQEAAgYGBxMbGkpqaesp3DQ0NZXR0dEENq8jISJqampBl+by9PdoVK4i4/36Mr7+O6Y030K9dS0JKCuNNTWicTmSrFeUiSY4kJydTWFiI0Whc0P0zFwICAsjIyKCsrIwNGzbMHLeWlhbGx8cpKCi4YHqEYWFh5ObmUlFRwZo1a5Z838yGEIIbbrjBNDo6+uW5GlWnoQ74HLALuBGIX5AJfkz4RBlWQggPkC1JUhDwtiRJGcAjwBCgAX4HfBv44RzHc0qSdPXOnTtLa2pqwi+kCJzL5aK8vJyIiIh5V8MsBuHh4axZs4bS0lJyc3Ox2+10d3ezYcOGC5K02dXVha+v75Ikynd0dJCYmLhoq+D+/n4KziICOl/Gx8dnDStKkjRjbE0bc0II7HY7k5OTTE5O0tvby+TkJC6XC7Vaja+vL76+vthsNkwm00wrlXM57rrVq9GmpDC5fz+q82y9IoTA5XJhtVpZLmJx9Jo5OlyLaG/Hv7kZjdWKMzAQ17Zt6FauJC4ggFR//zndeMPCwqiuPmNq5rxRKBSEh4djMBgWpAefMiCAsDvvZGLfPqYOH8avt5cBPz8iAI/JtGiGlSRJZGdnU1ZWxubNm5fcOxQWFkZycjLl5eWsW7eOpqYmHA4H+fn5FzyBPCAggIKCAkpLS1m5cuWck+0Xi1/84hfWhoaGN202267zHOou4KljDot3AOf5z+7jwyfKsJpGCDEuSdJ+4EohxC+PPe2QJOlF4JvzHKvL39//gS9+8Yu/3bNnT9CF8BLZbDbKyspYsWLFBf9hnkhISAh5eXmUlpYihGDLli0XxOU+NTVFd3c3SyHsOq1RtNBhumnMZjNarXbBqwzHxsYIOyEh+0xIkoROp0On051iqE4bLhaLBfBWBlqtVmw2G9NpByqVCo1Gg4+PD2q1GpVKhUqlOunfCoUCSZKQJAnFli2I9nYi6+oYUSgQkuQN2ykUoFAgSxKyEHgAjxC4hcAjBC6PB6fbjdPtRhz7nEqjQavXI2QZjdFIaFcXYnQUVXg4AZ/7HNrU1HPypup0Oux2+4J4l04kISGBxsbGBWtuLCmVBF5+OZqEBExvvUW4wQCA22Q6rWL7QqDX61m+fDn19fVkZWUt2nZOR2xsLFarlX379hEXF0dOTs5FI3mg0+nYuHEjZWVl2O12kpKSLsg8SktL+dWvftUzPDz8tfMdSwjRBFwOIEnSKuDq8x3z48QnxrCSJCkccB0zqnTAZcDPJEmKFkIMHktuvxavC3NeTE5Ovh4ZGXn1k08+ufPhhx9e0kzE6RyCzMzMs1a/XAimV/sqlQqDwbDkVYCyLFNdXU1WVtaSGHWtra0kJycv2kq4p6dnUfbh6Ojogtzw1Go1gYGBqFQqgoKCTskPEkLg8XhwOBw4HA5cLhdutxu3243T6cRqteJ2u5FlGSHEzF9tWhr+tbU4Dx8+7baVxx7zSUFWhIQQcMMN6DIykM7zmAUGBs5ohi0UAQEBM/tqIY1p3erVqO+/H+Nrr+EaGMAxNsZiJ4omJCTMaHmda0HDueJwODAYDPj5+c0Y7BcTarWagoICqqqqsNlspKWlLekcx8fHufHGG0eHh4evFkKct3dJkqQIIcSwJEkK4N/xVgh+YvjEGFZANPDSsTwrBfC6EOJvkiR9eMzokoBqvFWC82Z4ePi+J554Yv3WrVtX5c6S27EYjI2NcfTo0Ysu+XGaacXh3Nxc/P39qaiowGazsWrVqiW7aLS1tREWFrYkvbpsNhujo6OLlqTr8XgYHR09Z1Xp0yHLMna7fUH1e2w226yVcZIkzXil5tVGKCeH/aGhbNuyBSHL4PEgPJ6Zv7M+5/GALM/6nNvppGNggOxrr0VaoBybsLAwxsbGFvxci4uLo6+vb8FD/KrgYMLvuYf+999nQKNhsX8hkiSRlZVFUVERwcHBS1aFNy2QnJaWRnh4OOXl5XR1dV10KuhKpZK8vDwaGhqorKwkJydnSUKVQghuvvnmcZPJ9KAQomO+n5ck6U/AdiBMkqQ+4D8AP0mSpj1fbwEvLtiEPwZ8YgwrIUQtcEqzNiHEJQs0vl2SpGuuv/76wpqamrDF1m0ZGBigra3tnDqvLwUej2emR9b0jWbdunXU1dVRVVW1JAJ54+PjGAwGNm3atKjbmaalpWVRjUaDwUBERMSC7zez2bzg4rHnm7g+K5KEpFKxUHvXvH//ghlV4DWsamtrF1wQMy4ujqKiIpKSkhb83JJUKmL/6Z/oOHRocY7ZR9BqtaxevZqamhry8/MXfYE1m0Bybm4uxcXF+Pj4LFiIdaGQJIn09HQ6OjooLi5m7dq1i15s8/TTT9srKyt3T0xM/OlcPi+EuPk0Lz15HtP6WHPxCTB9jBFCtBqNxn+9/vrrx+WPChkuIO3t7XR1dbFhw4aL0qgSQlBRUUFsbOxJjUclSSIzM5PAwECKi4txOhcvn9Hj8VBTU7NkCscWi4WJiYlFbbS6WGHA+eRXzZWluEkvBAspNzOdsL/QEjYajQa9Xs/4+PiCjjuNJEmsWrWK5ubmRRn/o0RHR6NUKunv71/U7fT19VFXV8f69etPWjgolUrWrl1LS0sLRqNxUedwriQlJZGYmEhhYSE2m23RtlNYWCgef/zxnuHh4XsWbSOfQD41rBYYs9n8Sm1t7R8eeeSRqYUee7olwvj4OOvXr78oVXun5+jv739aV3tycjJJSUkUFhYyMbE4YryNjY3ExcUtWYi0qamJlJSURVuB22w23G73onyf0dHRBc/PO10o8GJiOuF8IQk4pne10CQkJNDT07Pg404TGRmJxWJhcnJy0bZxIpmZmbS2ti6K0SCEoL6+nv7+/tMuPjUaDWvXrqWmpoapqQW/VC8IMTExZGRkUFxcvCjXyb6+Pm688cbhkZGRzwghFs96+wTyqWG1CAwPDz/84osvVv35z392nf3dc2O6iadCoZh3s+OlpL29HbfbzerVq8/4vqioKPLy8qisrGRgYGBB5zA6OsrExMSSVddMTEzgcDgWVcqhr6+PuEWo2hJCYLPZFty79HHwWOl0OqzW2fsLnivTeVYLTXh4OEajEY/Hs+Bjg9drtXr1apqamhZl/I+iVqvJzMykqqpqQT18LpeLkpISlErlWbtO+Pr6kpubS3l5OQ7HnKQLl5zQ0FDy8/OprKxkdHTheiBbrVauuOIKo8FguF4IsXgW+yeUi/Pu/DFHCOEZGRm55qGHHuqrqqo67/GcTifFxcWEhoYuebXIfOjr62NkZISsrKw5zdHf359NmzbR09NDU1PTglxgXS4XR48eXdJy6sbGxrMakueDEIL+/v5F6W1oNpsJCAhY8H01rWl1MePr+//Ze/P4tsor//9zJHmTN9mO9zh24njL6izOQhwHaKEpS0PKTH9QKHSmLZ2BDqUFOvMtLWunHYalUNoSlraUQoG20KbQQAcK2Zw4ixPHTuLd8a7NmyzZ1n5+f0gyJtiOF9175fh5v1562Zbk+5wosu7nnvN5ztEGXVgFGoUGGyJCamoqDAZD0I8dYMGCBXC73ZKVHMdbLy4uDufOnQvK8axWK8rLy7Fo0SIUFhZO6T0dHx+P5cuX4+jRo3C7J53cohixsbHYtGkTzp49G5TyKTPjhhtuGOju7r7P7XaXByFEwXkIYSURzDxoMpmu3LFjh8no7xUzE0ZGRkaNqzOddC8HPT09aGlpQUlJybSyaYFtxh6PB0ePHoXr/Dlv0+T06dNYunSpbGWogEdDyq7J/f3943Y2DwZS+KsCAjlULwACREVFBb0UFR0djeHh4aD7rADpy4EAUFRUJFvWKrBeoMHsbDAYDKisrMTatWun3csvOTkZOTk5OH78OKT0xs6GyMhIbN68Ge3t7WhqaprVsR5++OGhioqKt/r7++dVCwQ5EcJKQpi5yWAw3LR9+/a+maSaLRYLKioqsHLlypDbvTKWwcFBnD59esYztwI7YTIzM1FeXj5jP4Fer4fb7ZakZDYRdXV1KCoqknQNqUzrgDT+KrvdHpKDZc9HiowVESE2NlYST0xMTAw8Ho+kZmadTge1Wi1JOXM81Go1Vq9ejaqqqhmJGmZGXV0dWlpacMkll8x4LmVWVhYSExNRXV0tiSgOBoGL0MHBQdTU1Mwozt27d7t/+ctfnjGbzd+UIESBHyGsJMbpdH7Q3t7+k69+9auW6fwhmM1mnDx5EiUlJSExQ2oiRkZGUFlZiXXr1s36ZLpw4UKsXbsWJ06cmPaVucPhQF1d3ZTLkMHAbDYjIiJixh/mU8HtdqO/vz/oWSXAd1IKDFkOJnPBuA5Ik7ECpPNZAT4B0NExmxFuFybgtZJLYOh0OqSkpKCxsXFav2e323HYP0Ny8+bNs+6LlZeXByJCQ0PDrI4jJSqVCmvWrIFGo8Hx48en5bk7ffo0brvttm6TybSdmUOz7nmRIISVDPT19T3x4Ycf/v3JJ5+c0qd4Z2cn6urqsGnTJsTExEgd3oxxuVw4evQoVq9eHbTdanFxcSgtLR0VllPxPTAzqqqqsGzZMtmaDgaulKX0VgG+LFx6erokYtFqtSI2Njbox54LxnUAiIiIkMS0LJXPCvDtFOvu7pZU9MTGxkKr1cJkMkm2xvnk5eXBbDajv79/Ss/v6enB4cOHsXTp0in7qS4EEWHVqlWwWCxoa2ub9fGkgohQVFSE5OTkKbet6e3txTXXXNPjF1VTe5EFM0YIKxlgZjaZTF959NFHG/7+979PmO9mZjQ2NqKzsxObN28O6XJKoAFoXl5e0DNqGo0Ga9euRUJCAsrLyy/ov2hvb0dERISsYzIMBgPi4uKCnu05n46ODmRlSTMYXooyIDB3MlaBk3GwRUpMTAyGhoYkET9hYWGIi4uTvP9SQUEB6uvrZctaqVQqFBcX49SpU5NmYZgZ9fX1qK+vx6ZNm4K+E5eIsG7dOnR0dGA23lg5yMnJQW5uLg4fPjxpSdvlcuGqq67qN5lM/8LMtTKGOG8RwkommNlpNpuv/OpXv6ofL+XNzKipqYHNZpuxV0kumBknT55EWlqaZEOfiQg5OTkoLi5GZWUlOjs7x33e8PAwzp0796mZdFLCzKNd1qUkYIKWSrxJYVwH5k7GCvD1Mwp2o1oiQkxMjGQ9oeQwsWu1Wuh0uqC3QpmMmJgYZGdn4+zZs+M+7nA4UFFRAY/HI2lz5EAD0draWtl2SM6UtLQ0rFq1CkeOHJmwf9q//du/Dba0tDw9PDz8jszhzVuEsJIRZjYZDBRbLYgAACAASURBVIZrtm/f3jO2VBDI/oSHh8vWKXw2nD17FlFRUbL0iYqPj8eWLVtgNBpRWVn5iV2DAYG3cuVKWYVoZ2cnFixYIHlWRkrTOjPDarVKUmqWoi+WVEhhYAek9VklJSVhYGBA8vYA+fn5aGxslHWnXE5ODmw2G8xm8yfuNxgMOHToEJYsWYJly5ZJ/hkZERGBkpISnDx5EkNDQ5KuNVsSEhJGYz2/fPvUU0+NvPPOO/t6enoeVii8eUlon8EvQpi5Sq/X33r55Zf3DQ0Nwel04vDhw0hNTQ2aV0BKWlpaYLfbJRs0PB5hYWFYt24d0tLSUF5ePupfaW5uRkJCgiTlrInwer1obm5GXl6epOsw86i/Sgqk8lcBPlNxRERE0I8rBVIZ2KX0WRHRqNdKSiIjI5GSkiK5WX4sRITi4mKcPn0aLpcLbrcbp06dQltbGy655BJZy/3R0dFYs2YNjh07FrINRAPExMRg8+bNqK+vH/3/ev31110//vGPT5tMpn/mUN3qeJEihJUCDA8P72lra7t3+/btlv379yMvLw/Z2dlKh3VBuru7YTAYZG2+OZbMzExs3LgRDQ0NOHnyJLq6uiQ3j59PW1sb0tPTJTfJ9/T0ICEhQbJMXG9vrySCdK70sAogVcYqNjYWNptNMo/SokWLZBE8S5cuRUtLi2Qd38cjKioK+fn5OH78OA4ePAidTocNGzYoItZ1Oh2Kiopw7NgxWV+DmRAREYHNmzeju7sbL730Et95550tZrP5s8wc2qrwIkQIK4WwWCy/bmpqeurnP/+5NTk5WelwLkhvby+ampqm3QA02ERFRWHjxo0wm83wer2yzvlyu91obW2VpQQqZRkQkM5fNRc6ro9FKmFFRIiOjpbs/RkVFQUikrxMFR4ejszMTLS2tkq6zlgCf9cDAwNYtGgRsrOzFRXqqampyMrKQmVlZcj2uAqg0WigVqvx/e9/32Q2m7cxszTDWAWTIoSVguj1+gcPHz78+7vuukueyaczxGq1orq6GiUlJSFx0qyvr8eSJUuwbt06VFVVyeYDOXfuHBYtWiT5a+ByuWC1WpGQkCDJ8QP+KikGOs8l4zogXSkQ8JUDpWy0KYeJHQCWLFmC9vZ2WUa+DA4OorzcN2XlsssuQ1tbW9AHZc+E7OxsxMfHz7gxp1w0Nzdjx44dBr1ev4WZQ3tb40WMEFYKYzKZbn/jjTc+evTRR4N/2RwE7Hb7aAPQUNhC39fXh/7+fuTm5o72vPJ6vTh48OCEu2KCgcvlQmdnJ3JyciRbI0BgLqBUV+lDQ0OIjo6W5PhzTVhFRkZKduKW0sAOAOnp6TAYDJKf6DUaDbKzs9Hc3CzZGl6vF/X19aiqqsKqVatQUFCAyMhILF++HFVVVSEhZvLz8+H1emc9UkYqjEYjPvOZz/R0d3dfxczS/WcJLogQVgrDzF6TyfRPTzzxRNXLL78cUrXwQAPQFStWSNpdfKq43W5UV1ejuLh4VBSoVCoUFBSguLgY1dXVqK2tlcQL0dTUhCVLlkCtVgf92OfT2dkp6VgeqfpXAXOnh1UAlUol2Uk7Li4Og4ODkh1frVYjMTHxUzvopCAnJwfd3d1Bb00B+GZhHjhwACqVCqWlpYiPjx99LCUlBVqtNiQadgYaiPb29spq6J8Kg4ODuOyyy3q7u7tvYOaTSscz3xHCKgRgZpfZbL7ynnvuaX7vvfdCwiHp9Xpx/Phx5ObmSuLFmQlnzpzB4sWLx+3rFMhehYeH48CBA0FtoOhwOGA0GiVr1DkWq9UKjUYjqTiRyl8FzL2MFeDLyMx2+Pd4EJFkHq4AcpUDVSoVcnNzpz12ZjLcbjfOnDmDM2fOYO3atcjLyxvXv7ls2TK0traGRNsDlUqF9evXo7W1VRZBOxUcDgeuvPLK/s7Ozv9wOp3/UDoegRBWs4aIIonoKBGdIqIzRPTQeY8/Q0QXdLAy85DZbN526623dhw9elS6gKdAYERMcnIyMjMzFY0lgNFohN1un9TQTUTIzc1FSUkJ6urqUF1dHZQTZkNDw4Qf+sFGatM6M2NwcFCyDORcy1gB0vuspGq7APh2rdlsNkmE4flkZWWhp6cnKKVTk8mEgwcPQqvVYsuWLZP6/TQaDVatWoWTJ0+GRElQo9Fgw4YNOHPmjKT2g6ng9XrxxS9+caCxsfFHg4ODr13o+USURUQfEVGt/3z1bf/9iUT0PhE1+r9KY/CcJwhhNXscAC5n5tUAigFsJ6JNAEBE6wHopnogZu4xmUyX7tixQ19fXy9NtFOgrq4OYWFhWLp0qWIxjMXpdOLs2bNTHrAcHR2NzZs3IyEhAQcPHkR7e/uMP5CHh4fR398vWYf5sXi9XphMJkl79QQySlL5t+aisJIyqyS1z4qIsHDhwgknEwR7rby8PMzms2l4eBhHjx5FW1sbNm7ciMWLF0/pvZiYmIikpKSgZsxmQ0REBNavX48TJ05ImpGcDGbGbbfdNnjs2LFf9/b2PjnFX3MDuJuZiwBsAnAHES0D8F8A/sHMeQD+4f9ZMEOEsJol7COQkQrz35iI1AAeA/C9aR6vzWAwXHnFFVeY5NziHKC1tRU2m03WETGTwcw4derUqJl1qhARsrKyUFpaCovFgvLy8hldXdbX1yM/P1+W7d5msxlJSUmS+rik9FcBvv+vUJ8ccD5SCqv4+HjJsxpyCSvAZ5gfHBycdlnO6/WioaEBR48eRU5ODkpKSqYtwAsKCmAwGBTPEgWIiYnB6tWrcezYMUm8Zxfiv/7rv2xvv/32HrPZfM9Uf4eZ9cx8wv+9FUAtgEwAOwD81v+03wK4Ltjxzifm1idgiEJEaiKqAmAC8D4zHwHwLQB/ZWb9dI/HzKc7OjquvvTSS81y+CcCGAwGdHV1Ye3atSHT4LGrqwtqtXrGGaOwsDCsXLkSK1euRE1NDWpqaqZcNrFarRgaGpKt23NbW5ukZUBAWn+V2+2WxdwfbKQsBRIRoqKiJM1qREZGIjw8HIOD0rcsIiIUFBSgrq5uyr9jMpmwf/9+EBHKyspmPDg5MKi5qqoqZJp1JiYmIj8/X/YGoj/4wQ9sL7300gcmk+mmmXZVJ6IcAGsAHAGQGjhX+b8Gd7r1PEMIqyDAzB5mLgawEMAGIioD8M8AnpnFMY+3tbVdU1ZW1iPH1Wh/fz/q6+tRUlISMifHkZERNDY2YuXKlbM+VmDmYHx8PA4ePIi2trYLlgfr6upkGzPkcDgwMjICnW7KleMZYbFYPrHrKpjMReM6IG3GCpDeZwXIZ2IHgOTkZNjt9gsKOZvN9omyXzB8inFxcVi4cOG0hJ3UpKenIyMjQzYP2IMPPjj0/PPP7zWZTP/EzDNq4EdEMQDeBHCXaCIafISwCiLMPABgL4DLACwF0ERErQC0RDTt5ifMfLSzs/MLZWVlPVLOBbPZbKiqqkJJSYnko1qmSsBAv3LlyqA15CQiLFq0CKWlpRgaGsL+/fthNI7fQy8w5FauHZFSt1gAfMIn0LFbCuaivwqQNmMFSO+zAnzdwQPTCKSGiFBUVITa2tpxH3c6naipqcGJEyewZMmSGZX9JmPJkiWwWCySv6bTYfHixdBqtThz5oyk6/z4xz8efvbZZ/ebzeadzDyjFBkRhcEnql5l5rf8dxuJKN3/eDp81RfBDBHCapYQUTIR6fzfRwH4LIBKZk5j5hxmzgEwzMwzcoK73e7D7e3tO7du3dprMBiCF7gfh8OB48ePY+3atSGVbTh37hxiY2MlETZhYWFYtmwZSkpK0NnZicOHD3/Kt1FXV4eioqKgrz0RXV1dkgsrqf1VczVjpVarJRUk8fHxGBgYkOz4gK9MlpycPOGFQrBJTEwE4Mt0B/B4PGhqakJ5eTl0Oh22bt0qyd9vYFDzdMr6clBUVASHwyFZI9X//d//HX766afLTSbTF5h5Rm3wyXdV9SsAtcw81vD+VwC3+r+/FcDu2UU7vxHCavakA/iIiKoBHIPPY/VOMBdwu90HOzo6/mnLli29wcxcud1uHD16FMuWLZOsPDQTrFYrOjo6JBc2Wq0W69atQ1FREU6fPo2TJ09iZGQEvb29UKvVkpflAlgsFkRGRko+ZFaqwcsB5qqwAnzCRCqPjEqlQmRkpKRZMUDeciAAFBYWora2FsyMzs5OHDhwAMyMsrIyZGVlSVpC12q1WLJkCU6fPi3ZGtOFiLBmzRoYjUZ0dXUF9diPPvro8OOPP15hMpmunqmo8rMFwFcAXE5EVf7bVQD+B8AVRNQI4Ar/z4IZolE6gLkOM1fDZwCc7Dkxs13H6XTu1Wg0O0tLS986cODAgtn2l/J6vaisrEROTs6MzaRS4PV6UVVVhdWrV8vm9dLpdLjkkktgNBpx5MgROBwOrF+/Xpa1Ael7VwWwWCySisW5WgoEPi4HxsTM+k91XAI+KymbzMbFxcHhcMDhcEgu0gPreb1efPTRR1iwYAE2b94sy7oBsrKyYDAYoNfrkZ6eLtu6k6FSqVBSUoLDhw8jIiIiKBm7//7v/x56+umny81m8zXMPKsUHTMfBDCR4v3MbI4t+BiRsZpDuN3uA+3t7TtKS0t7ZnNlysyorq5GQkKCLN3Ep0NjYyNSUlJkyxYFICKkpaWhsLAQ0dHRqKmpwZkzZyTfRu31etHT0yO5uB0ZGUF4eLikrRDmsrCS2sAuh88KkKf1AjOPNviMiIiASqXCypUrZRVVgO9vdvXq1airq4PDETrTwMLCwlBSUoLTp0/PeqfmAw88MPSzn/1sn9lsvnq2okogH0JYzTHcbveh1tbWa8rKyswz7XPV0NAw2uwvlOjv74fZbFYsLmZGQ0MD1q5di7KyMsTGxuLQoUOora2VTGAZDAakpKRI3vtJyjYLATweDzSauZkEl9rArtPpJPdZAR8LK6l2p5nNZpSXl6OzsxNr165FSUkJdDodpPB/ToWIiAgUFRXh1KlTIdGVPUBUVBTWrVuHEydOzPh9dd9999l27dr1oclk2jHL8p9AZoSwmoMw85G2trarysrKzNOdtN7e3o6BgQGsWrUqZHpVAb6T8qlTp1BcXKxYg8nu7m4kJCRAq9VCpVJh0aJFKCsrg1arRXl5Oerq6oIusOQqA0ptXPd6vSH1fpouUmesVCoVwsPDgzIOZjLCw8Oh1WqD2kSTmUcFVXt7O4qLi7F27drRmZ0FBQVoaGhQTNikpaUhPDw85AYjx8bGYuXKlTh27Ni0TPbMjHvvvdf24osvvm8ymXYKUTX3EMJqjsLMxzs6Oq4sKysznDhxYkq/YzKZ0N7ejnXr1oXcSfDs2bPIzs6WzONyIbxeLxobGz+VLVOpVMjOzsa2bdsQFRWFQ4cOoaamJignYbvdDpfLNemctGAxMDCAhATpxn/N5TIgIL2wAuTpZwUEz8TOzOjq6sKBAwfQ0dGBVatWYd26dZ/6G42KikJSUpJs3d/HY/ny5WhpaVFsvMxEJCUlYenSpTh27NiUdp56PB7ceuutg7/97W//7O9TFRqdUAXTQgirOQwzV+n1+i2f//zn2z/44INJ/2oHBgZw9uxZlJSUhFy5xmw2w2azIScnR7EYOjo6kJKSMuHYnLECKykpCZWVlaisrJyVh6Kjo0MWj5vdbpfcXzWXdwQC0pcCAfl8VikpKejt7Z3xLkePx4PW1lbs27cP/f39KCkpwdq1aye9AMjLy0Nzc7MsfbTGIzBhIVQGNY8lIyMDqampF4zNbrfjqquuGnjvvfd+aTabb51p80+B8ghhNcdh5haTyVTy5S9/ufH1118fN988PDyMkydPoqSkRHaD6YVwuVw4ffo0iouLFcuieTwetLS0TMnbRUTIyMhAaWkpFi1ahDNnzuDIkSPo6emZ1gd6IBsw292dU0HqNgvAx81H5yphYWFwu6WtuOh0uk/0fZIKIkJqauq0fU9OpxMNDQ3Yv38/HA4HLrnkEqxYsWJK/68RERFIS0tDW1vbTMOeNUlJSdDpdGhpaVEshonIzc1FRETEhE1VBwYGUFpa2n/s2LEfmkym/zfTMTWC0EAIq4sAZjaZzeaSO++8s+qnP/3pJy67nU4njh49iuLi4lFPRChRXV2N/Px8RU/Kra2tyMzMnFaHdyJCcnIyNm/ejIKCArS1tWH//v1oa2ub0gm6v78fsbGxQesqPxlS+6sAXylwLmesAN//qZQZF7VajbCwMFl2sE2nHGixWFBVVYVDhw4hLCwMW7duRUFBwbSnMOTm5qK1tVXROX6FhYXo7OyUZW7idFm+fDmGh4dx7ty5T9zf3d2NjRs39tbX19/W19f3c4XCEwQRIawuEpjZajabS3/yk5/svffee23MDI/Hg6NHj6KoqEhSf81M6e7uBjPLkrWZCJfLhfb2dixZsmTGx9DpdFi3bh02bdoEu92OAwcO4MyZMxgaGprwd+QyrQM+ESf1//9cLwUCvmHGUpvLk5KSZCkHxsTEwOPxTFje9Hq96OrqGt2UkZGRgW3btmHx4sUztgqEhYUhKytL0YyRWq0eHdSsVFlyIgINRLu7u6HX6wH4dmhv3rzZ3NzcvNNqtf5J4RAFQUIIq4sIZnaazeZrXn755T/edNNNliNHjiArKwupqalKh/Yp7HY76uvrsWrVKkXjaGlpQXZ2dlB8ZxERESgoKMC2bduQkJCAqqoqHDlyBCaT6RNlQrfbjf7+flnmEDocDoSFhUnebPViyFhdTAZ2wNdA8/ydcoG/u3379mFgYADFxcXYuHEjUlJSglKKX7x4MTo7OxUdNRMfH4/09HTU19crFsNEqNVqbNiwAQ0NDXj//fdx6aWX6tvb2z/jdrsPKB2bIHiElotZMGuY2UtEX/voo4/0XV1dd7333nshd7YLDFhevny5okOfnU4nuru7sW3btqAeV6VSISMjAxkZGbBYLGhtbcWZM2eQnp6OrKws9PX1IT09XRZPmRz+KsCX+ZOjrCklchjYExMTcfbsWUnXCJCRkYHy8nLk5ubCaDSivb0dLpcLixYtwtatWyXZxKJWq7F48WI0NzejsLAw6MefKkuXLkV5eTn6+vpG5xqGCmFhYRgYGPDefvvtZr1ev5mZlTOmCSRBZKwuQpiZ9Xr9fdXV1XeXlpb2yWGYnQ5tbW3QarWKj9JpbGxEbm6upLvl4uPjsXr1apSVlSE6OhpVVVWoqalBWFiYLF4UOfxVF4vPVo6MlVqthlqtlryjP+DLInq9Xnz44Yfo7+/HsmXLsHXr1qBlaCdi0aJFMBgMinZDD5TdqqurJd+UMF1+97vfOb/xjW/UdXd3rxCi6uJECKuLmP7+/l319fVf27hxY6+Su3XGMjQ0hNbWVixbtkzROEZGRmA2m2Ub6aNWq5GVlYU1a9YgJiYGTqcT+/fvx6lTp6a9o3A6yOGvstvtE7apmEvIkbECpPVZORwOnDt3DgcOHEBtbS0yMzORlJSE5cuXIy4uTpI1z0elUmHp0qVobGyUZb2JiI6ORk5ODs6cOaNoHAGYGT/5yU+G77777uNms3kDM8tTExbIjigFXuTYbLa/EJF+8+bNf3njjTdSt27dqlhnUGbGyZMnsWrVKsV7aTU0NCA/P1/2Fg/t7e1YvHgxsrKyUFhYCLPZjM7OTtTU1CA5ORmZmZnQ6XRBicvpdEKtVkv+Wl8MxnVAnowV4BNWRqMxaIODnU4n9Ho9urq64PF4kJGRgZKSEkRGRoKZsW/fPrjdbln/5jIzM9Hc3Kx449js7GwcPXoUJpNJ0Qy53W7HLbfcYtm3b98ef48qMffvIkZkrOYBzHxEr9evv/766+ufe+45xfLzTU1NSEpKUtzzMDQ0hMHBwaCd2KYKM0Ov14+uS0RISUlBcXExtm3bhgULFqClpQV79+7F2bNnYbFYZpXJkstfpfTJM1iEh4fLUqJLTExEX1/frI7hdrvR2dmJI0eO4PDhw3A6nVi9ejW2bt2K3Nzc0QwiESE9PR3d3d3BCH3KEBEKCgoUN5AHBjXLMVB9IvR6PTZu3Nj3j3/84yGj0fhlIaoufkTGap7AzF1EtPb+++//4/Hjx7c+++yzcXJewVosFuj1epSWlsq25kTU1dWhoKBA9mxVT08PEhISxs0cqFQqpKWlIS0tDW63GyaTCQ0NDbDZbFiwYAHS09ORmJg4LT9YT0+PLDtCh4eHQ7JH2nQJvB+YWdL3hkajgUqlgtPpnNbmjZGRERgMBhgMBjidTqSmpmLZsmUXHImUlZWFkydPytbeI0Bqaiqamppgs9kUG1UF+NpoFBQUoLq6GuvXr5d17ePHj2Pnzp0mo9F4o9Pp/FDWxQWKITJWIQ4RRRLRUSI6RURniOgh//2/8t9XTUR/IqILfnIx84jJZLp29+7dT23durV/tlfNU8Xj8aCqqkrRAcsBBgcHYbfbkZycLPvaU+1dpdFoRss5ZWVlSElJQVdXF/bt24fKykp0dXVNaTu7XDuiLpaMFeBrmSGH6TopKemCWStmhsViQX19Pfbv348TJ07A6/Vi1apV2LZtGwoLC6c0Z1Kr1YKIJu2rJgVEhMLCQtTV1cm67nhkZGSAiGSdZ/j73//edfXVV7d0dnZunoqoIqIsIvqIiGr9n/Xf9t//z/6fvUQkrzIUzAiRsQp9HAAuZ2YbEYUBOEhE7wL4DjMPAgARPQngWwD+50IH849KeCAmJubE2rVrX9yzZ88CqY3kdXV1WLhwoWzm2cmora1FUVGR7Nkql8sFq9U6bSO5Wq1GamoqUlNTR0+0BoMBTU1N0Gg0SE5ORnJy8qd8WS6XCyqVShZfzcXisQI+NrBLbcZPSkqC2WxGWlraJ+53OBzo6emByWTCwMAAYmNjkZaWhk2bNs2qNUmgE3tRUdFsQ58WCxYsQGNjIywWC+Lj42Vd+3xWrVqFgwcPIikpSdILAa/Xi+9973u2l19+udJsNl/LzNYp/qobwN3MfIKIYgFUEtH7AE4D+CKA56SKWRBchLAKcfxCyOb/Mcx/4zGiigBEAZiWGcdms+0mosbLL7/8vRdeeCHj2muvlaSDZG9vLywWi+K7AAGMzmlTwuPV1dU1etU8U4gIOp0OOp0OhYWFsNvtMJvNOHfuHCwWC6Kjo5GSkoLk5GRYrVbZ/p0OhyPkZlDOlICBXeqdlImJiaivr4fH40Fvby/MZjN6enqgVquRnJyM7OxsrF69OmgZ3vT0dDQ2NqKwsFD2i4rCwkLU1tZi06ZNsq57PmFhYVixYgWqqqqwadMmSV6HwcFB7Ny5c+D06dO/NZvN353OIGVm1gPQ+7+3ElEtgExmfh+A7P9vgpkjhNUcgIjUACoBLAXwC2Y+4r//NwCuAnAWwN3TPS4znyWi4q997Wt/v/POO5fdd9992mD+8bpcLtTU1GDDhg0h8aFQW1uL5cuXK7J2Z2cn1q1bF9RjRkZGIisrC1lZWWBm2Gw2mEwm1NTUoL+/H3FxcTh37hwSExMRFxcnyf9BwFwfCv+/wUDqlgtOpxN9fX3o6+uD1WrF/v37sWDBAiQnJyM/P1+yJqtqtRqJiYkwm82y745LSEiASqWSbTPFZCQnJ8NgMKC1tRWLFy8O6rGbm5vx+c9/vtdoNN5lsVhemc2xiCgHwBoAR4IRm0BehLCaAzCzB0AxEekA/JmIVjDzaWb+F7/oegbA/wfgNzM4dh8RXfLMM8+8cPz48R2vvfaaLlhp8tOnT2PJkiUhUSYym82IiIhQpBxhtVqh0WgkLT8QEWJjYxEbG4vc3Fzs27cPhYWFsFgsaGxshNVqRWRkJBITE5GYmAidTheUk/h0DdihjlarRbAa6jIzhoaGRoXUwMAANBoNEhISkJSUBLfbPVrmlYNFixahublZkbYDhYWFqKmpwSWXXKK4CF+2bBkOHDiA5OTkoJnq//GPf3hvvvlmo8FguJaZK2dzLL9f9k0AdwUqE4K5hRBWcwhmHiCivQC2w1d3BzN7iOgNAPdiBsLKfwwXgK8mJibesWbNmod2796dVFBQMKtYDQYDXC6XbA04J4OZUVdXhzVr1iiyvpwDlwFfppCIkJSUhKSkpNEB0yMjI+jr64Ner0ddXR3cbjdiYmKg0+kQHx+P+Pj4aZf0LiZ/FTDzXlZerxc2mw0DAwOwWCywWCxwuVyIjo5GYmIiFi1ahJUrV35qZqNcOzcB37Bwm82myPihuLg4REVFKZIxO5/AoOaTJ09iy5Ytsyq3er1e/OhHPxr6+c9/3mI2m69kZsNsYvP7aN8E8CozvzWbYwmUQwirEIeIkgG4/KIqCsBnAfwvES1l5ia/x+paALPeetPX1/cLIiovKyvb/dhjj6XdcsstM0pFOBwO1NbWhsTVKeATebGxsYps+fZ6vTCZTLLOTZtoN2BUVBQyMzORmZkJAKPlQ4vFApPJhMbGRjidTkRFRY2+XoEs2EQn4otpRyDgK6/a7fYJHw9koWw2G6xW6+hXr9eL2NhYxMfHIy0tDQUFBRfM5CUlJcnanZyIsHDhQnR2dga9DDYVCgsLcfz4cSQnJyv+uaDT6ZCSkoLGxkbM9CLSaDTii1/8Yn9TU9MrZrP57tn2p/J/lv8KQC0zPzmbYwmURQir0CcdwG/9JT8VgD8A+BuAA0QUB4AAnALw78FYjJmriGjFvffe+/s9e/aU/upXv9JNp0cRM+PUqVMoKioKCUMzM6OhoQEbNmxQZH2z2YykpKRPZSqkpLe3FwsWLLjg88aWDxcuXAjA93qNjIyMCoaOjg5YrVa4XC6Eh4cjJiYG0dHR0Gq1iIqKwuDg4EWVsSKiUcE5PDyMkZERDA8Pw2azjbYr0Gq1o8IzUE6aye7LsLAweL1eWbuiL1y4EMeOHVNEWGm1Wuh0Ouj1emRkZMi+/vnk5eWhvLwcqamp0Ol00/rdDz74wHvrrbeae3t7v2q3298LUkhbAHwFQA0RVfnv+z6ACPjsHskA/kZEVcz8uSCtuqIQ/AAAIABJREFUKZAAIaxCHGauhs/EeD5bJFzTSkRfeO+9925bvXr1j/7yl78sWLFixZR+t6OjA+Hh4Z/aRq4UnZ2dkm+vnoz29nbk5eXJumZvb++M1yQiaLXacYdkO53OUYFhtVphMplgMpmgUqnQ0tKCiIgIREVFISIiYtxbWFiYopkKj8cDp9MJu93+ia8OhwN2ux3Dw8Pwer0YHh7GmTNnEBMTg6ioKCQkJCArKwtarTbofdgC/azkKo9FRkYiPDwcg4ODirQ/yc/PR0VFBdLS0hTvaadSqVBcXIzKykps3bp1Shc/brcb9913n+2ll16qN5lM1/p38gUFZj4I34XyePw5WOsIpEcIK8G4+Ns8PEdEBz7zmc+8/dBDD2V+85vfjJjsxDg8PIyWlhZs2SKZ5psWXq8Xzc3N2Lx5syLrO51ODA8PT/tqeDa43W54vV5JPDTh4eGj5vcAR44cwcqVKxEVFQWHw4GRkRE4HA44HA4MDQ2hv79/9OfzR4poNJpP3VQqFYho9OvY7x0OB5qbm8HMYGZ4vd5PfPV4PHC73aM3l8v1iZFAKpXqU2JPq9UiISFh9Hu1Wo0TJ04gNzdXlo0OSUlJ6OnpkdV3lJWVhY6ODkV2yEZGRiIlJQUdHR3Izs6Wff3ziY2NxaJFi1BbW4sLXTx2dXVhx44dfe3t7S+Yzeb7/JuKBIJPIYSVYFL8LRlWPvjggy/t2bPnildeeUU33pVuYMDyypUrZTfGTkRbWxvS0tIUK0l2dnaOltjkQq5u6wHsdjsiIyNBRIiMjJxyY82xQsjlco2KobFC6XzxRESjWa/xBJharUZYWNinhNp0CRjY5RJWzc3Nkq8zlrS0NNTX16OoqEiRrNHSpUtRXl6OhQsXyloin4jFixejoqICZrN5wokMf/vb3zzf+MY3TCaT6Ua3271P5hAFcwwhrAQXhJmHAXwpLi7u1lWrVj3+1ltvLVi7du0nntPS0gKdTqd4n5oAHo8Hra2tis4m7OzsxMaNG2Vdc6r+qmDBzDM6ORPRqPiZqhg7d+6cLLsrpe5lNZbw8PBRgSmXz0qlUmHBggUwmUyKlOzDw8ORmZmJtra20R2rSkJEKC4uRkVFBUpLSz9xYehyufDd737X+sYbb9SYzebrmNmsYKiCOYKYFSiYMoODg79ta2u7ZPv27Q1PPvnkSKDMMjg4iM7OTll3vl2IlpYWZGVlKZY9s1gsiIyMlD1bJmcTRpfLJZsYkJOZtlyYKQkJCUHrnTVVAiNulGLJkiVoa2uD2+1WLIaxREVFIS8vDzU1NaP3tba2Yt26dX2vvfba42azeasQVYKpIoSVYFowc6PZbF716KOPvl5aWtrX2to6OmA5FNL6gO+Er9SW8gBy964CfFk6j8cjW8POi63VQgA5M1aAb55eb2+vbOsBQHx8POx2uywDp8dDo9EgOzsbLS0tiqw/HpmZmfB4POjq6sKuXbscGzdu7Kypqbm6p6fn4emMphEIhLASTBtmdhiNxn+tqKi4/pJLLjHt37/fHQoDlgM0Nzdj8eLFigk9r9cruyEZ8PmrpJ5xN5aLrTloALmFVVJSkuzCCsBoTyulyM7ORldX16c2NSgFESEhIQE7d+50PPjgg2+YTKZCZq5QOi7B3EMIK8GM8Xg8e/V6fe4zzzzzWmlpaX9HR4fSIcHhcMBgMMieLRqLwWBASkqK7MZguf1VIyMjF6WwUqvV8HrlS1BERETA5XLB45F3k1lAWI3dOSknarUaubm5aGpqUmT9sTAznnvuOUdpaWlnZWXldoPBcCszDykdl2BuIoSVYFYws81oNN5SUVFxfUlJSefzzz/vVOqDGgAaGxuxdOlSRXvkKFEGBOT1VwG+jNXFWAoEfCd9OYWOEj6r8PBwaLVaWCwWWdcdy8KFC2EymSbtdi81HR0d2Lp1a9/999//htFoLPJ4PHsVC0ZwUSCElSAoeDyej4xGY9H999//RllZWb8SJYaRkRH09vaOjmxRArvdDpfLhdjYWFnX9Xg8cLlcsprlL9ZSIOArB8ppYFfCZwUob2JXqVTIz89HQ0OD7GszM55//nlnSUlJ5+HDh683Go23MrNN9kAEFx1CWAmCBjPbDAbDLYcOHbp+/fr1XS+88IKs2av6+noUFBQo2t27o6NDkcHT/f39svqrgIvXvA4o47Pq6emRbb0AKSkp6O3tlb0MOZb09HQMDAyMjgySg87OTpSVlfWLLJVACoSwEgQdf/aq8Ic//OEft23bJkv2ymazwWazITU1VfK1JoKZ0dXVpUjGTG5/FeAz6YfKTtBgI3fLhcjISLhcLlm9XYDPsJ2amgqDwSDruufHUFhYiPr6esnXYma88MILzvXr13cdOnToeoPBcIvIUgmCjRBWAknwZ69urqio+Of169d3/fznP3dIeVVcV1eHwsJCRbNV/f39iI2NVaR3ltz+Ko/Ho/isNymRW1gBgE6nk91nBShfDgSA5ORkjIyMYHBwULI1mpqaUFpa2vfDH/7wj0ajsdDj8Xwk2WKCec3F+8komDZEFElER4noFBGdIaKH/Pe/SkT1RHSaiH5NRFNWDk6n8x9Go7HgkUceeWHFihW9FRXB371ssVjgcrlkz9icj1Kmda/XC6fTOeUO5sHgYi4DAvKXAgHlfFYxMTHweDyy/3vHEsha1dXVBf3Yw8PD+N73vmfbsmVL86FDh75gMBhunmqWioiyiOgjIqr1fyZ+23//Y0RUR0TVRPRnIpJvIKgg5BHCSjAWB4DLmXk1gGIA24loE4BXARQCWAkgCsDXp3NQZh4yGo3/UVdXt+W66647duONNw6YzcFrYlxbW6t413e3243+/n5FxN3AwICsg56Bi9u4DiiTsVLKZwV8PJhZSZKSkuD1eoOWtWNm/PnPf/YUFBSYX3jhhQf9fanKp3kYN4C7mbkIwCYAdxDRMgDvA1jBzKsANAD4f0EJWnBRIISVYBT2EbiSC/PfmJn3+B9jAEcBzGiyMDPXG43Gjbt37/7mypUr9c8888ysy4O9vb1QqVSyG7fPR6/XIz09XZFSZE9Pj+wzGi/2jJVGo5Hd0B0VFQWn0ym7zwoAMjIy0N3drVhPqwBFRUVByVo1NjZi69atfbfffvvbnZ2dK/v7+59g5mnPz2FmPTOf8H9vBVALIJOZ/2/M8Soww89EwcWJEFaCT0BEaiKqAmAC8D4zHxnzWBiArwB4b6bHZ2YeHh7+g9FozPvRj370/GzKg8w86q1Smvb2dkV2AwLKGNcv9owV4CtPyS1y4uPjMTAwIOuaABAWFoa4uDj09fXJvvZY4uPjERYWhplmtIeHh3HvvffaSktLm8vLy7+g1+t3MrMxGLERUQ6ANQCOnPfQvwJ4NxhrCC4OhLASfAJm9jBzMXxXYBuIaMWYh38JYD8zHwjCOkNGo/HOurq6LTt27Dh+ww03TLs8aDabERUVBaXH6QRKRtHR0bKv7fV6YbfbZc8eXewZK8C3U0/uxpVKjbcBQsPEDmB0h+B0smfMjLfeestTUFBgfvHFF2da9psQIooB8CaAu5h5cMz998FXLnw1WGsJ5j5CWAnGhZkHAOwFsB0AiOgBAMkAvhvkdepNJtOGv/71r9MqD4ZatkqpEToWi0V2fxUwPzJWSvislDKwAz5RNzAwALd72hWzoBITE4OYmBgYjVNLNAWr7DcR/kz9mwBeZea3xtx/K4BrANzEStdQBSGFEFaCUYgoObC7hYiiAHwWQB0RfR3A5wDcKMWU97HlwUceeeT5oqKinj179ngn+6zS6/XQ6XSKn9yZedRfpQRK+KsAn1lfibYScqKEsNJqtRgZGVHEZ0VEo14rpSkoKLhg1qqnpwd33HHH4NatWxvLy8uvNRgMQSv7BSCfafJXAGqZ+ckx928H8J8AvsDM8r5JBCGPEFaCsaQD+IiIqgEcg89j9Q6AXQBSARwmoioiul+KxZl5yGQy3dnY2Lj+a1/72jvr168f13/l9XrR0NCA/Px8KcKYFj09PUhISIBGo1FkfaUagyrZL0wulGi5APh8RkrN7wuF3YGA77VPSkpCV1fXpx4bGhrCAw88MLxixYqul1566T+MRmMhMx+SKJQt8PlKL/d/9lUR0VUAfg4gFsD7/vt2SbS+YA6izNlAEJIwczV85szz75f1fcLMbQB2ENGKnTt3PrtixYplP/vZzxKLiooA+MbGpKSkyNq3aSLa29uxePFiRdZmZoyMjMietbPb7SHx2kuNVqudcjkqmAR8VkrsdNVqtSAiDA0NKeIZHEteXh4OHz6MjIwMqFQquFwu7Nq1y/GTn/xkYGRk5PGBgYGfMbNTyhiY+SCA8a4i9ki5rmBuIzJWgpCFmU/r9fqtH3zwwY7LLrvs9I033jjQ2tqKlpYWLF26VOnw4HK5YLVaFWv1YLFYEB8fL/u688G4DihTCgSU9VkBoWNij4iIQFpaGlpbW/Hqq696li5d2vPwww//TK/X5/X39z8utagSCGaKyFgJQh5mPkhEq956661r9+3b94vPfe5zC1avXh2ZmJioaFzd3d3IyMhQrCymlL9qPhjXAV8LApfLJfu6AUHHzIq8t9LT09HY2Kj4iChmRnNzM9999932gYGB141G438yc/A6CwsEEiEyVoI5ATOzw+H4q16vz/nTn/70rWXLlnU//PDDw0pkFAJ0dHQo1rsKUMZfBcwfYRUQFXJv+CIixMXFSTo3bzLUajUSExNn3EsqGBw9ehQbNmzo/frXv/63+vr6ZQaD4V+FqBLMFYSwEswpmNljtVp/ZTQalzz11FOP5OXlmZ5++mmH3ALLarVCo9EoVhJjZsUEznwpBQK+cpTD4ZB9XSXH2wDKmdhPnjyJz33uc307duw4dPz48cv1ev21zNwqeyACwSwQwkowJ2FmR19f3/90d3fnPfLII/+Tm5trfOihh4bl6lqtdLZqcHAQcXFxipRq5kvGCpi/PquEhARYrVZZSqHMjP3792PLli09V1999aH/+7//u1av12/xb6YRCOYcQlgJ5jTMPNjT0/OgwWBY/OSTT36/sLCw+zvf+Y7VYDBItqbX64XBYEBaWppka1wIpfxVAOB0OhEeHq7I2nKjVMuF6OhoDA0NKTa7j4iQmZmJzs5OydZgZrz99ttcXFzcc8MNN7x36NChz3R3d2+RsHWCQCALQlgJLgqYecRisTxtNBqzn3/++W8VFxe3fvWrX7WcO3cu6GuZzWYsWLAAarU66MeeKr29vYoIq8CJfj70sQKUy1gREWJjY2G1WmVfO0BWVpYkwsrtduOVV17x5Ofn99x2221vVFdXb+zu7v68yFAJLhaEsBJcVDCze2ho6GWj0Zj76quv3rp58+a66667rv/06dNBW0PJETaAT9wMDQ0hJiZG9rXnU7YKUE5YAcr7rCIjIxEeHh40E73dbscvfvELZ25urvmee+55oampaZVer7+RmVuCsoBAECIIYSW4KGFmr8vl2m00Gpft3r37i1dcccXxSy+9tPfw4cOzOq7T6cTw8LAi8/kCWK1WxMbGCn+VDChVCgSU91kBwTGxDw4O4sc//vHIkiVLTA888MAT7e3tBQaD4d+ZWR+kMAWCkEIIK4HiEFEkER0lolNEdIaIHvLf/y0iaiIiJqIZ9RVgH3v1en3Jvn37Pnf99dd/uHr16p433njDOxNjbmdnJxYuXDiTUIKGkv4qJTq9K0lkZCTsdrsia8fExMBmsynmswKAtLQ0mEymGc0ubGlpwR133DGYn5+vf+yxxx7Q6/VLenp6vs/M/TOJhYiyiOgjIqr1f05823//I0RU7R8t839ElDGT4wsEwUIIK0Eo4ABwOTOvBlAMYDsRbQJQDt8g6LZgLMLMld3d3Z+prq4uufPOO5/Lyckx33///cPTGVsSCsJKKX8V4MtYzZdWC4ByvawCawfElVKoVCosWLAAJpNpSs/3er34+9//jrKysp7S0tLq559//mtGo3FRf3//Y8w8NMtw3ADuZuYiAJsA3EFEywA8xsyrmLkYwDsAJJllKhBMFSGsBIrjzyoFzh5h/hsz80kpetgwc6vRaLy9u7s754knnvju6tWrW6677rq+ioqKSU+gFosFkZGRiIiICHZIU4aZYbPZEBsbq8j6860UCCjXgR1Q3mcFTG3EjcViwVNPPeXIzc01/8u//MsbBw4cuLy7u3u1y+X6EzO7gxEHM+uZ+YT/eyuAWgCZzDzWBBYNQLkUn0AAMdJGECIQkRpAJYClAH7BzEekXpOZhwE8R0TP7969e8uxY8d+oNVq19511126W265Jex88aK0aR0AbDYboqOjFduVN99KgcDHBnYlTPsLFixAQ0ODYoO+ASA+Ph52ux0Oh+MTFxXMjOPHj+OJJ57o37t3r83hcDw7MDCwa6alvulARDnwDYw/4v/5vwHcAsAC4DKp1xcIJkNkrAQhATN7/Kn8hQA2ENEKGddmZj7Y1dW1vampafkPf/jDR/Ly8rpuvvnm/hMnTgDwlTh6enqQkpIiV1jjotQYmwAjIyOIjIxUbH0lUNLAHmi5oKTPCgAWLlw42nrBZrNh165drsLCQvN11133jzfeeON6o9GY3d/f/xOZRFUMgDcB3BXIVjHzfcycBeBVAN+SOgaBYDJExkoQUjDzABHtBbAdQPB6JEx9fTOAR4jov1999dXLP/roox/ExcUtu+GGG3SXXXZZmEql7LVIT08P8vLyFI1hvvSwCqBkywUiglarVay9RoCMjAzs2rULFRUV/Xv37h1xuVwv9vX1/ZKZp25QDAJEFAafqHqVmd8a5ym/B/A3AA/IGZdAMBYhrASKQ0TJAFx+URUFn2H9USVjYmYvgA8AfEBEKU899dQtzz333DdzcnLib7/99qSdO3eqoqOj5Y4JVqsVcXFxsq4bwOVyQaOZfx8ZUVFRig1EBj5uu6CEsKqpqcGLL75offPNN+1qtfpwe3v7EwAO+v8+ZIV8iv5XAGqZ+ckx9+cxc6P/xy8AqJM7NoFgLPPvU1IQiqQD+K3fZ6UC8AdmfoeI7gTwPQBpAKqJaA8zf13u4JjZBOBxAI8TUV5jY+M37rnnni9v2LAh8vbbb0/67Gc/K4vgGBoaglarVSxjNB+N64CyGSvAZ2Bvbm5Gdna2LOt1dHTgd7/73civf/1rm91ur9Xr9U95vd49zCz/NOpPsgXAVwDUEFGV/77vA/gaERUA8MK3g/jfFIpPIAAghJUgBPCPslgzzv0/A/Az+SOaGP+V8feI6D/ffvvtkuPHj98BYPvVV18dftttt+nWr18vmfAJBX/VfGq1EEBJjxXgM48PDg6CmSV7bw0MDOCPf/yj+9lnn+03GAxGi8Xyi+Hh4Tfk8ExNFWY+CGC8F2CP3LEIBJMhhJVAMAPY5yY+CuAoEYW9+OKLn3333Xe/rdFo1t58883am2++ObqwsDCoa/b09CA3Nzeox5wO8zVjpVKpFDWPB3xWw8PDCGb5eWhoCO+99x7v2rWrt6amxuZ0Ol/q7+//DTNP3ltBIBBMihBWAsEsYWYXgHcBvEtEMY899tgXX3rppW+o1eqCa665JvxLX/pS/JYtW2ZVLmRmDA4OIj4+PmhxT5eRkREkJycrtr6SqNVquN1uxTxmgX5WsxVW3d3d+Otf/+p+5ZVX+pubm0e8Xu/bJpPpeTEAWSAIHkJYCQRBxN/o9GUALxNR5C9/+cvL//KXv9zq9XrLSkpKNDfddFPS9u3baboCKdDxXMkdefM1YwX4fFYjIyOKNWZNSkrCuXPnpu2zYmZUV1fjzTffHP7DH/4wZLVaDTab7dXBwcE3mblJonAFgnmNEFYCgUQwsx0+/8ceIqK333577eHDh2/UaDQ7Fy5cGHvTTTfFX3fddeE5OTkXPJbS/ipg/nqsAJ/Panh4WDFhFR8fD4vFMqXnOhwO7N27F6+//nr/+++/7yaiU3q9/jcej+fdUPJMCQQXK0JYCQQy4PdkVfpv9xBR1tmzZ3c+/vjjt0RERCzauXNn1LXXXhuzcePGcRtw9vT0KNp9G/A1SVWr1YrGoBRK7wxUqVSIjIycMGvY1taGDz/80Pvaa6/1VldXu1Qq1ft6vf5lAAf8pWqBQCATQlgJ5jVEFAlgP4AI+P4e/sTMDxDRYgCvA0gEcALAV5jZGax1mbkDvh2PPyOi2CeeeOKK119//Z88Hs+WtLS0qKuvvlp75ZVXRm/cuBERERGwWCyK+qs8Hg+Ubo6qJFFRUejt7VU0hkA/K61Wi/b2dnz44Yfed955p6+iooKJqNVqtf7VYrH8GcBZlsBtT0RZ8JW50+BrbfA8Mz895vF7ADwGIJmZlR1wKBAoiBBWgvmOA8DlzGzzd3U+SETvAvgugJ8y8+tEtAvA1wA8K0UA/oGyb/lvIKKUqqqqbS+99NJOj8ezJTU1VVtSUqJTq9WagNCSm/nsrwJ8GauOjg7F1m9vb8f777/v3bNnj/3UqVNDzNxqs9n+arFY3gNQFaxBxxfADeBuZj5BRLEAKonofWY+6xddVwAQOwoF8x4hrATzGv+Vvc3/Y5j/xgAuB/Bl//2/BfAgJBJW48RkAvBH/w1ElFpdXV327rvv7vRntCKvueaa6CuuuCJ6/fr1sgie+eyvAuTtZcXMaGtrw/79+71vv/12X0VFBY8RUn8HcFImIXV+XHoAev/3ViKqBZAJ4CyAn8LXzHe33HEJBKGGEFaCeY+/43slgKUAfgGgGcDAmJNXJ3wnEEXwz2P7hNA6derUtt/85jc7PR5PSWRkZFxxcTHKysp0GzZsCCsuLg5qvyNAZKw0Gg08Hk/Qj8vMOHfuHCorK1FeXj544MABe3d3t1ej0ZyzWq3v+oXUCSWE1GQQUQ58TX2PENEXAHQx86n5NkdSIBgPIawE8x5m9gAoJiIdgD8DKBrvafJGNTF+ofUH/w1EFN7a2rrsnXfeWZ+WlvZZj8ezLiIiIm7VqlW0bds2XUlJSdiaNWtmNWtuZGQECQkJQfoXzE2ICF6vd8ZeM2ZGS0sLKisrcfDgQcvBgwcdBoPBo1arz42MjOzv7e09AKBS7sHG04WIYuAbhHwXfOXB+wBcqWhQAkEIIYSVQODHPwR6L4BNAHREpPFnChYC6FY0uEnwm+qr/LcXAYCIwlpbW5ft2bNnVGyFh4frVq5ciZKSkpjly5dH5efnY+nSpVMq8Q0PDyMzU7GkXUgQKAdeKBvIzNDr9WhoaEB9fb2nqqrKWlFR4TIYDG6NRtMyPDy8t6+v7yB8mSiTPNEHB78P8U0ArzLzW0S0EsBiAIFs1UIAJ4hoAzMbFAxVIFAMIawE8xoiSgbg8ouqKACfBfAogI8A/BN8OwNvxRzzjvi32J/y334FAESkaWtrK3rnnXeKkpKSirVa7RqXy5WnVqtjU1NTsWLFCk1xcXFsYWFhWH5+PrKzs0c7jc93jxWAT42V6e/vR2NjIxoaGlBTU2M9derUSFNTEw0NDbk0Gk03M58xm83HnE5nHYBTc32nHPmU068A1DLzkwDAzDUAUsY8pxXA+rn+bxUIZgMpOQNLIFAaIloFnzldDUAF4A/M/DARLcHH7RZOAriZmR3KRSod/hNmEoB8IspPS0tbr9FoVrlcruzw8PCo7OxsTk5O1q1evdqzaNGiqPT0dGRkZCA9PR1JSUmydYPfu3cvLr30UlnWstvt0Ov1o7euri7P6dOnnXq93tnc3Oy0WCxuAP1qtbp2YGCg0mq1ngbQAOBcMNtyhBJEVArgAIAa+NotAMD3mXnPmOe0QggrwTxHCCuBQDAhRKSCr7yzCEC6VqvN0ul0eRqNJtvj8WR4PJ5EjUYTHhUVpcrIyOBFixapc3JyorKysqJSU1MpNjYWsbGxiImJGf0aExMzo0ajMxFWzAyHwwGr1Qqr1QqbzTb6dWBgAF1dXa5z584Nt7W1OTs7O7mvr49cLpeLmYc1Go2RmdtHRkbO9fX1NTNzN3y74pr9o4sEAoHgUwhhJRAIZo2/0WoagHQA6eHh4Qt1Ol12WFhYgkql0hFRnNfrjfV6vbEejyeKiMLUarVKpVKp1Wq1SqvVcmxsLMfGxkKj0UCtVpNarYZarYZKpYJKpaLh4eHYqKgoq9frZY/HA6/XC7fbzV6vFyMjIxgcHITNZiOn0wmv1+vxer0ej8fDKpXKrlKpbCqVykZEg8xscbvdAyMjI6aBgYFz8ImlgGjqk6K5pkAgmD8IYSUQCBTFnxWLAhALIAYfl2XHu3ngK0Odf7MDsAKwiREuAoFASYSwEggUZqJRIUS0GsAu+MRGK4CbmHlQsUAFijHJe+RBAN8AYPY/9ROeJ4FAID9CWAkECkNE6QDSx44KAXAdfKb6e5h5HxH9K4DFzPxDJWMVKMMk75EvwZele1zRAAUCwSjzd6qqQBAiMLOemU/4v7cCCIwKKYBvQDQAvA/gemUiFCjNJO8RgUAQYghhJRCEEGNHhQA4DeAL/of+GUCWMlEJQonz3iMA8C0iqiaiXxPR/G6PLxCEAEJYCQQhwthRIX4v1b8CuIOIKuEzdl+U/ZEEU2ec98izAHIBFMO3q/EJBcMTCAQQHiuBICTwjwp5B8DfA12tz3s8H8ArzLxB9uAEIcEU3iM5AN5h5hUyhyYQCMYgMlYCgcKMNyrEf3+K/6sKwA/g2yEoZRxZRPQREdUS0Rki+rb//mIiqiCiKiI6TkTzRtxN9Jr4H/sPIqr33/+/Escx0XskfczTdsJXPhYIBAoiMlYCgcJMNCoEQB6AO/w/vwXg/0nZvHKSnWdPAfgpM79LRFcB+B4zXypVHKHEJK9JKoD7AFzNzA4iSpFyoPIk75Eb4SsDMnwtOb7JzHqp4hAIBBdGDGEWCBSGmQ8CmGjg3tMyxqGHz6cDZrYSUWDnGQOI8z8tHr4u5ZIySd+mN+DbLQkAOgADzFwsVRyTvCbfAPA/gfnqgJ7cAAABxklEQVSRUooq//Eneo+InlUCQYghMlYCgeBT+P06+wGsgE9I/B2+E7sKwCXM3Cbx+uNmipj57JjnPAHAwswPSxnLmPVy8PFrsh/AbgDb4ev6fg8zH5MjDoFAENoIj5VAIPgE4+w8+3cA32HmLADfgc/rIykX6tvk9xx9CcBrUsfiX+/810QDIAHAJgD3AviDPyaBQDDPEcJKIBCM4t959iaAV5n5Lf/dt8Ln8QKAPwKQ1bw+Tt8mANgKwMjMjTKsP95r0gngLfZxFL5y5QKpYxEIBKGPEFYCgQDAxDvP4PNUbfN/fzkAycXMmJjOzxQFuBEyZKsmeU3+At9rEWiFEQ6gR+p4BAJB6CM8VgKBAMCkO88G4TPRa+DzE93OzJUyxDNu3yYi0gDoArCOmTsljmGi1+QDAL+Gb0eeEz6P1YdSxiIQCOYGQlgJBIKQw58p+i2APma+67zHtsPXemLbuL8sEAgECiJKgQKBIBTZAuArwP/fzh2cAAgEQRCc2IzCsA3JzyUgNL6qomiWZXadYdLnbGht272fntYBvnKxAgCIuFgBAESEFQBARFgBAESEFQBARFgBAESEFQBARFgBAESEFQBA5AUKE3x5LVfx2QAAAABJRU5ErkJggg==\n",
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\n",
        "text/plain": [
         "<Figure size 720x720 with 1 Axes>"
        ]
        "text/plain": [
         "<Figure size 720x720 with 1 Axes>"
        ]
@@ -7612,8 +9070,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 141,
-   "metadata": {},
+   "execution_count": 135,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "# list(raw_data_2020.columns)"
     "outputs": [],
     "source": [
      "# list(raw_data_2020.columns)"
@@ -7621,8 +9081,10 @@
    },
    {
     "cell_type": "code",
    },
    {
     "cell_type": "code",
-   "execution_count": 142,
-   "metadata": {},
+   "execution_count": 136,
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": [
      "# deaths_headlines_e = raw_data_2020.iloc[:, [1]].copy()\n",
     "outputs": [],
     "source": [
      "# deaths_headlines_e = raw_data_2020.iloc[:, [1]].copy()\n",
@@ -7638,14 +9100,18 @@
    {
     "cell_type": "code",
     "execution_count": null,
    {
     "cell_type": "code",
     "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": []
    },
    {
     "cell_type": "code",
     "execution_count": null,
     "outputs": [],
     "source": []
    },
    {
     "cell_type": "code",
     "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "Collapsed": "false"
+   },
     "outputs": [],
     "source": []
    }
     "outputs": [],
     "source": []
    }
@@ -7669,7 +9135,7 @@
     "name": "python",
     "nbconvert_exporter": "python",
     "pygments_lexer": "ipython3",
     "name": "python",
     "nbconvert_exporter": "python",
     "pygments_lexer": "ipython3",
-   "version": "3.7.4"
+   "version": "3.8.5"
    }
   },
   "nbformat": 4,
    }
   },
   "nbformat": 4,
diff --git a/uk_deaths.md b/uk_deaths.md

index 4dc06c22db6369527160e729d9b6c92ed59f6e2d..a6baf23c12a5fdb5e4eea1a860401393245e5de0 100644 (file)
--- a/uk_deaths.md
+++ b/uk_deaths.md
@@ -6,21 +6,23 @@ jupyter:
        extension: .md
        format_name: markdown
        format_version: '1.2'
        extension: .md
        format_name: markdown
        format_version: '1.2'
-      jupytext_version: 1.3.4
+      jupytext_version: 1.9.1
    kernelspec:
      display_name: Python 3
      language: python
      name: python3
  ---
  
    kernelspec:
      display_name: Python 3
      language: python
      name: python3
  ---
  
+<!-- #region Collapsed="false" -->
  Data from:
  
  * [Office of National Statistics](https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/weeklyprovisionalfiguresondeathsregisteredinenglandandwales) (Endland and Wales) Weeks start on a Saturday.
  * [Northern Ireland Statistics and Research Agency](https://www.nisra.gov.uk/publications/weekly-deaths) (Northern Ireland). Weeks start on a Saturday. Note that the week numbers don't match the England and Wales data.
  * [National Records of Scotland](https://www.nrscotland.gov.uk/statistics-and-data/statistics/statistics-by-theme/vital-events/general-publications/weekly-and-monthly-data-on-births-and-deaths/weekly-data-on-births-and-deaths) (Scotland). Note that Scotland uses ISO8601 week numbers, which start on a Monday.
  
  Data from:
  
  * [Office of National Statistics](https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/weeklyprovisionalfiguresondeathsregisteredinenglandandwales) (Endland and Wales) Weeks start on a Saturday.
  * [Northern Ireland Statistics and Research Agency](https://www.nisra.gov.uk/publications/weekly-deaths) (Northern Ireland). Weeks start on a Saturday. Note that the week numbers don't match the England and Wales data.
  * [National Records of Scotland](https://www.nrscotland.gov.uk/statistics-and-data/statistics/statistics-by-theme/vital-events/general-publications/weekly-and-monthly-data-on-births-and-deaths/weekly-data-on-births-and-deaths) (Scotland). Note that Scotland uses ISO8601 week numbers, which start on a Monday.
  
+<!-- #endregion -->
  
  
-```python
+```python Collapsed="false"
  import itertools
  import collections
  import json
  import itertools
  import collections
  import json
@@ -33,11 +35,11 @@ import matplotlib.pyplot as plt
  %matplotlib inline
  ```
  
  %matplotlib inline
  ```
  
-```python
-!ls uk-deaths-data
+```python Collapsed="false"
+england_wales_filename = 'uk-deaths-data/publishedweek532020.xlsx'
  ```
  
  ```
  
-```python
+```python Collapsed="false"
  raw_data_2015 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2015.csv', 
                         parse_dates=[1, 2], dayfirst=True,
                        index_col=0,
  raw_data_2015 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2015.csv', 
                         parse_dates=[1, 2], dayfirst=True,
                        index_col=0,
@@ -48,7 +50,7 @@ dh15i.columns = ['total_2015']
  # dh15i.head()
  ```
  
  # dh15i.head()
  ```
  
-```python
+```python Collapsed="false"
  raw_data_2016 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2016.csv', 
                          parse_dates=[1, 2], dayfirst=True,
                        index_col=0,
  raw_data_2016 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2016.csv', 
                          parse_dates=[1, 2], dayfirst=True,
                        index_col=0,
@@ -59,7 +61,7 @@ dh16i.columns = ['total_2016']
  # dh16i.head()
  ```
  
  # dh16i.head()
  ```
  
-```python
+```python Collapsed="false"
  raw_data_2017 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2017.csv', 
                          parse_dates=[1, 2], dayfirst=True,
                        index_col=0,
  raw_data_2017 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2017.csv', 
                          parse_dates=[1, 2], dayfirst=True,
                        index_col=0,
@@ -70,7 +72,7 @@ dh17i.columns = ['total_2017']
  # dh17i.head()
  ```
  
  # dh17i.head()
  ```
  
-```python
+```python Collapsed="false"
  raw_data_2018 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2018.csv', 
                          parse_dates=[1, 2], dayfirst=True,
                        index_col=0,
  raw_data_2018 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2018.csv', 
                          parse_dates=[1, 2], dayfirst=True,
                        index_col=0,
@@ -81,7 +83,7 @@ dh18i.columns = ['total_2018']
  # dh18i.head()
  ```
  
  # dh18i.head()
  ```
  
-```python
+```python Collapsed="false"
  raw_data_2019 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2019.csv', 
                          parse_dates=[1, 2], dayfirst=True,
                        index_col=0,
  raw_data_2019 = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2019.csv', 
                          parse_dates=[1, 2], dayfirst=True,
                        index_col=0,
@@ -92,7 +94,7 @@ dh19i.columns = ['total_2019']
  # dh19i.head()
  ```
  
  # dh19i.head()
  ```
  
-```python
+```python Collapsed="false"
  raw_data_2020_i = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2020.csv', 
                          parse_dates=[1], dayfirst=True,
                        index_col=0,
  raw_data_2020_i = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2020.csv', 
                          parse_dates=[1], dayfirst=True,
                        index_col=0,
@@ -100,19 +102,19 @@ raw_data_2020_i = pd.read_csv('uk-deaths-data/Weekly_Deaths_NI_2020.csv',
                             )
  deaths_headlines_i = raw_data_2020_i.iloc[:, [1]]
  deaths_headlines_i.columns = ['total_2020']
                             )
  deaths_headlines_i = raw_data_2020_i.iloc[:, [1]]
  deaths_headlines_i.columns = ['total_2020']
-deaths_headlines_i.head()
+deaths_headlines_i.tail()
  ```
  
  ```
  
-```python
-
+```python Collapsed="false"
+raw_data_2019
  ```
  
  ```
  
-```python
+```python Collapsed="false"
  
  ```
  
  
  ```
  
-```python
-raw_data_s = pd.read_csv('uk-deaths-data/weekly-deaths-april-20-scotland.csv', 
+```python Collapsed="false"
+raw_data_s = pd.read_csv('uk-deaths-data/weekly-deaths-scotland.csv', 
                        index_col=0,
                        header=0,
                          skiprows=2
                        index_col=0,
                        header=0,
                          skiprows=2
@@ -120,7 +122,7 @@ raw_data_s = pd.read_csv('uk-deaths-data/weekly-deaths-april-20-scotland.csv',
  # raw_data_s
  ```
  
  # raw_data_s
  ```
  
-```python
+```python Collapsed="false"
  deaths_headlines_s = raw_data_s[reversed('2015 2016 2017 2018 2019 2020'.split())]
  deaths_headlines_s.columns = ['total_' + c for c in deaths_headlines_s.columns]
  deaths_headlines_s.reset_index(drop=True, inplace=True)
  deaths_headlines_s = raw_data_s[reversed('2015 2016 2017 2018 2019 2020'.split())]
  deaths_headlines_s.columns = ['total_' + c for c in deaths_headlines_s.columns]
  deaths_headlines_s.reset_index(drop=True, inplace=True)
@@ -128,12 +130,12 @@ deaths_headlines_s.index = deaths_headlines_s.index + 1
  deaths_headlines_s
  ```
  
  deaths_headlines_s
  ```
  
-```python
+```python Collapsed="false"
  
  ```
  
  
  ```
  
-```python
-eng_xls = pd.read_excel('uk-deaths-data/publishedweek312020.xlsx', 
+```python Collapsed="false"
+eng_xls = pd.read_excel(england_wales_filename, 
                          sheet_name="Weekly figures 2020",
                          skiprows=[0, 1, 2, 3],
                          header=0,
                          sheet_name="Weekly figures 2020",
                          skiprows=[0, 1, 2, 3],
                          header=0,
@@ -142,11 +144,11 @@ eng_xls = pd.read_excel('uk-deaths-data/publishedweek312020.xlsx',
  eng_xls
  ```
  
  eng_xls
  ```
  
-```python
+```python Collapsed="false"
  # eng_xls_columns
  ```
  
  # eng_xls_columns
  ```
  
-```python
+```python Collapsed="false"
  eng_xls_columns = list(eng_xls.columns)
  
  for i, c in enumerate(eng_xls_columns):
  eng_xls_columns = list(eng_xls.columns)
  
  for i, c in enumerate(eng_xls_columns):
@@ -162,34 +164,34 @@ eng_xls.columns = eng_xls_columns
  # eng_xls.columns
  ```
  
  # eng_xls.columns
  ```
  
-```python
+```python Collapsed="false"
  eng_xls['Total deaths, all ages']
  ```
  
  eng_xls['Total deaths, all ages']
  ```
  
-```python
+```python Collapsed="false"
  eng_xls['Wales'].iloc[1:]
  ```
  
  eng_xls['Wales'].iloc[1:]
  ```
  
-```python
+```python Collapsed="false"
  # raw_data_2020 = pd.read_csv('uk-deaths-data/publishedweek272020.csv', 
  #                        parse_dates=[1], dayfirst=True,
  #                       index_col=0,
  #                       header=[0, 1])
  ```
  
  # raw_data_2020 = pd.read_csv('uk-deaths-data/publishedweek272020.csv', 
  #                        parse_dates=[1], dayfirst=True,
  #                       index_col=0,
  #                       header=[0, 1])
  ```
  
-```python
+```python Collapsed="false"
  
  ```
  
  
  ```
  
-```python
+```python Collapsed="false"
  # raw_data_2020.head()
  ```
  
  # raw_data_2020.head()
  ```
  
-```python
+```python Collapsed="false"
  # raw_data_2020['W92000004', 'Wales']
  ```
  
  # raw_data_2020['W92000004', 'Wales']
  ```
  
-```python
+```python Collapsed="false"
  raw_data_2019 = pd.read_csv('uk-deaths-data/publishedweek522019.csv', 
                         parse_dates=[1], dayfirst=True,
                        index_col=0,
  raw_data_2019 = pd.read_csv('uk-deaths-data/publishedweek522019.csv', 
                         parse_dates=[1], dayfirst=True,
                        index_col=0,
@@ -197,7 +199,7 @@ raw_data_2019 = pd.read_csv('uk-deaths-data/publishedweek522019.csv',
  # raw_data_2019.head()
  ```
  
  # raw_data_2019.head()
  ```
  
-```python
+```python Collapsed="false"
  raw_data_2018 = pd.read_csv('uk-deaths-data/publishedweek522018.csv', 
                         parse_dates=[1], dayfirst=True,
                        index_col=0,
  raw_data_2018 = pd.read_csv('uk-deaths-data/publishedweek522018.csv', 
                         parse_dates=[1], dayfirst=True,
                        index_col=0,
@@ -205,7 +207,7 @@ raw_data_2018 = pd.read_csv('uk-deaths-data/publishedweek522018.csv',
  # raw_data_2018.head()
  ```
  
  # raw_data_2018.head()
  ```
  
-```python
+```python Collapsed="false"
  raw_data_2017 = pd.read_csv('uk-deaths-data/publishedweek522017.csv', 
                         parse_dates=[1], dayfirst=True,
                        index_col=0,
  raw_data_2017 = pd.read_csv('uk-deaths-data/publishedweek522017.csv', 
                         parse_dates=[1], dayfirst=True,
                        index_col=0,
@@ -213,7 +215,7 @@ raw_data_2017 = pd.read_csv('uk-deaths-data/publishedweek522017.csv',
  # raw_data_2017.head()
  ```
  
  # raw_data_2017.head()
  ```
  
-```python
+```python Collapsed="false"
  raw_data_2016 = pd.read_csv('uk-deaths-data/publishedweek522016.csv', 
                         parse_dates=[1], dayfirst=True,
                        index_col=0,
  raw_data_2016 = pd.read_csv('uk-deaths-data/publishedweek522016.csv', 
                         parse_dates=[1], dayfirst=True,
                        index_col=0,
@@ -221,7 +223,7 @@ raw_data_2016 = pd.read_csv('uk-deaths-data/publishedweek522016.csv',
  # raw_data_2016.head()
  ```
  
  # raw_data_2016.head()
  ```
  
-```python
+```python Collapsed="false"
  raw_data_2015 = pd.read_csv('uk-deaths-data/publishedweek2015.csv', 
                         parse_dates=[1], dayfirst=True,
                        index_col=0,
  raw_data_2015 = pd.read_csv('uk-deaths-data/publishedweek2015.csv', 
                         parse_dates=[1], dayfirst=True,
                        index_col=0,
@@ -229,14 +231,14 @@ raw_data_2015 = pd.read_csv('uk-deaths-data/publishedweek2015.csv',
  # raw_data_2015.head()
  ```
  
  # raw_data_2015.head()
  ```
  
-```python
+```python Collapsed="false"
  dhw = eng_xls['Wales'].iloc[1:]
  dhe = eng_xls['Total deaths, all ages'].iloc[1:] - dhw
  deaths_headlines_e = pd.DataFrame({'total_2020': dhe.dropna()})
  deaths_headlines_w = pd.DataFrame({'total_2020': dhw.dropna()})
  ```
  
  dhw = eng_xls['Wales'].iloc[1:]
  dhe = eng_xls['Total deaths, all ages'].iloc[1:] - dhw
  deaths_headlines_e = pd.DataFrame({'total_2020': dhe.dropna()})
  deaths_headlines_w = pd.DataFrame({'total_2020': dhw.dropna()})
  ```
  
-```python
+```python Collapsed="false"
  # deaths_headlines_e = raw_data_2020.iloc[:, [1]].copy()
  # deaths_headlines_e.columns = ['total_2020']
  # deaths_headlines_w = raw_data_2020['W92000004'].copy()
  # deaths_headlines_e = raw_data_2020.iloc[:, [1]].copy()
  # deaths_headlines_e.columns = ['total_2020']
  # deaths_headlines_w = raw_data_2020['W92000004'].copy()
@@ -247,7 +249,7 @@ deaths_headlines_w = pd.DataFrame({'total_2020': dhw.dropna()})
  # deaths_headlines_e
  ```
  
  # deaths_headlines_e
  ```
  
-```python
+```python Collapsed="false"
  dh19e = raw_data_2019.iloc[:, [1]]
  dh19w = raw_data_2019['W92000004']
  dh19e.columns = ['total_2019']
  dh19e = raw_data_2019.iloc[:, [1]]
  dh19w = raw_data_2019['W92000004']
  dh19e.columns = ['total_2019']
@@ -256,11 +258,11 @@ dh19e.total_2019 -= dh19w.total_2019
  dh19e.tail()
  ```
  
  dh19e.tail()
  ```
  
-```python
+```python Collapsed="false"
  dh19w.head()
  ```
  
  dh19w.head()
  ```
  
-```python
+```python Collapsed="false"
  dh18e = raw_data_2018.iloc[:, [1]]
  dh18w = raw_data_2018['W92000004']
  dh18e.columns = ['total_2018']
  dh18e = raw_data_2018.iloc[:, [1]]
  dh18w = raw_data_2018['W92000004']
  dh18e.columns = ['total_2018']
@@ -269,7 +271,7 @@ dh18e.total_2018 -= dh18w.total_2018
  # dh18e.head()
  ```
  
  # dh18e.head()
  ```
  
-```python
+```python Collapsed="false"
  dh17e = raw_data_2017.iloc[:, [1]]
  dh17w = raw_data_2017['W92000004']
  dh17e.columns = ['total_2017']
  dh17e = raw_data_2017.iloc[:, [1]]
  dh17w = raw_data_2017['W92000004']
  dh17e.columns = ['total_2017']
@@ -278,7 +280,7 @@ dh17e.total_2017 -= dh17w.total_2017
  # dh17e.head()
  ```
  
  # dh17e.head()
  ```
  
-```python
+```python Collapsed="false"
  dh16e = raw_data_2016.iloc[:, [1]]
  dh16w = raw_data_2016['W92000004']
  dh16e.columns = ['total_2016']
  dh16e = raw_data_2016.iloc[:, [1]]
  dh16w = raw_data_2016['W92000004']
  dh16e.columns = ['total_2016']
@@ -287,7 +289,7 @@ dh16e.total_2016 -= dh16w.total_2016
  # dh16e.head()
  ```
  
  # dh16e.head()
  ```
  
-```python
+```python Collapsed="false"
  dh15e = raw_data_2015.iloc[:, [1]]
  dh15w = raw_data_2015['W92000004']
  dh15e.columns = ['total_2015']
  dh15e = raw_data_2015.iloc[:, [1]]
  dh15w = raw_data_2015['W92000004']
  dh15e.columns = ['total_2015']
@@ -296,13 +298,13 @@ dh15e.total_2015 -= dh15w.total_2015
  # dh15e.head()
  ```
  
  # dh15e.head()
  ```
  
-```python
+```python Collapsed="false"
  # dh18 = raw_data_2018.iloc[:, [1, 2]]
  # dh18.columns = ['total_2018', 'total_previous']
  # # dh18.head()
  ```
  
  # dh18 = raw_data_2018.iloc[:, [1, 2]]
  # dh18.columns = ['total_2018', 'total_previous']
  # # dh18.head()
  ```
  
-```python
+```python Collapsed="false"
  deaths_headlines_e = deaths_headlines_e.merge(dh19e['total_2019'], how='outer', left_index=True, right_index=True)
  deaths_headlines_e = deaths_headlines_e.merge(dh18e['total_2018'], how='outer', left_index=True, right_index=True)
  deaths_headlines_e = deaths_headlines_e.merge(dh17e['total_2017'], how='outer', left_index=True, right_index=True)
  deaths_headlines_e = deaths_headlines_e.merge(dh19e['total_2019'], how='outer', left_index=True, right_index=True)
  deaths_headlines_e = deaths_headlines_e.merge(dh18e['total_2018'], how='outer', left_index=True, right_index=True)
  deaths_headlines_e = deaths_headlines_e.merge(dh17e['total_2017'], how='outer', left_index=True, right_index=True)
@@ -312,7 +314,7 @@ deaths_headlines_e = deaths_headlines_e.merge(dh15e['total_2015'], how='left', l
  deaths_headlines_e
  ```
  
  deaths_headlines_e
  ```
  
-```python
+```python Collapsed="false"
  deaths_headlines_s = raw_data_s[reversed('2015 2016 2017 2018 2019 2020'.split())]
  deaths_headlines_s.columns = ['total_' + c for c in deaths_headlines_s.columns]
  deaths_headlines_s.reset_index(drop=True, inplace=True)
  deaths_headlines_s = raw_data_s[reversed('2015 2016 2017 2018 2019 2020'.split())]
  deaths_headlines_s.columns = ['total_' + c for c in deaths_headlines_s.columns]
  deaths_headlines_s.reset_index(drop=True, inplace=True)
@@ -321,14 +323,16 @@ deaths_headlines_s = deaths_headlines_s.loc[1:52]
  deaths_headlines_s
  ```
  
  deaths_headlines_s
  ```
  
+<!-- #region Collapsed="false" -->
  # Correction for missing data
  # Correction for missing data
+<!-- #endregion -->
  
  
-```python
+```python Collapsed="false"
  # deaths_headlines_s.loc[20, 'total_2020'] = 1000
  # deaths_headlines_s
  ```
  
  # deaths_headlines_s.loc[20, 'total_2020'] = 1000
  # deaths_headlines_s
  ```
  
-```python
+```python Collapsed="false"
  deaths_headlines_w = deaths_headlines_w.merge(dh19w['total_2019'], how='outer', left_index=True, right_index=True)
  deaths_headlines_w = deaths_headlines_w.merge(dh18w['total_2018'], how='outer', left_index=True, right_index=True)
  deaths_headlines_w = deaths_headlines_w.merge(dh17w['total_2017'], how='outer', left_index=True, right_index=True)
  deaths_headlines_w = deaths_headlines_w.merge(dh19w['total_2019'], how='outer', left_index=True, right_index=True)
  deaths_headlines_w = deaths_headlines_w.merge(dh18w['total_2018'], how='outer', left_index=True, right_index=True)
  deaths_headlines_w = deaths_headlines_w.merge(dh17w['total_2017'], how='outer', left_index=True, right_index=True)
@@ -338,7 +342,7 @@ deaths_headlines_w = deaths_headlines_w.merge(dh15w['total_2015'], how='left', l
  deaths_headlines_w
  ```
  
  deaths_headlines_w
  ```
  
-```python
+```python Collapsed="false"
  deaths_headlines_i = deaths_headlines_i.merge(dh19i['total_2019'], how='outer', left_index=True, right_index=True)
  deaths_headlines_i = deaths_headlines_i.merge(dh18i['total_2018'], how='outer', left_index=True, right_index=True)
  deaths_headlines_i = deaths_headlines_i.merge(dh17i['total_2017'], how='outer', left_index=True, right_index=True)
  deaths_headlines_i = deaths_headlines_i.merge(dh19i['total_2019'], how='outer', left_index=True, right_index=True)
  deaths_headlines_i = deaths_headlines_i.merge(dh18i['total_2018'], how='outer', left_index=True, right_index=True)
  deaths_headlines_i = deaths_headlines_i.merge(dh17i['total_2017'], how='outer', left_index=True, right_index=True)
@@ -347,12 +351,16 @@ deaths_headlines_i = deaths_headlines_i.merge(dh15i['total_2015'], how='left', l
  deaths_headlines_i
  ```
  
  deaths_headlines_i
  ```
  
-```python
+```python Collapsed="false"
+deaths_headlines_s
+```
+
+```python Collapsed="false"
  deaths_headlines = deaths_headlines_e + deaths_headlines_w + deaths_headlines_i + deaths_headlines_s
  deaths_headlines
  ```
  
  deaths_headlines = deaths_headlines_e + deaths_headlines_w + deaths_headlines_i + deaths_headlines_s
  deaths_headlines
  ```
  
-```python
+```python Collapsed="false"
  deaths_headlines_e['previous_mean'] = deaths_headlines_e['total_2019 total_2018 total_2017 total_2016 total_2015'.split()].apply(np.mean, axis=1)
  deaths_headlines_w['previous_mean'] = deaths_headlines_w['total_2019 total_2018 total_2017 total_2016 total_2015'.split()].apply(np.mean, axis=1)
  deaths_headlines_s['previous_mean'] = deaths_headlines_s['total_2019 total_2018 total_2017 total_2016 total_2015'.split()].apply(np.mean, axis=1)
  deaths_headlines_e['previous_mean'] = deaths_headlines_e['total_2019 total_2018 total_2017 total_2016 total_2015'.split()].apply(np.mean, axis=1)
  deaths_headlines_w['previous_mean'] = deaths_headlines_w['total_2019 total_2018 total_2017 total_2016 total_2015'.split()].apply(np.mean, axis=1)
  deaths_headlines_s['previous_mean'] = deaths_headlines_s['total_2019 total_2018 total_2017 total_2016 total_2015'.split()].apply(np.mean, axis=1)
@@ -361,42 +369,44 @@ deaths_headlines['previous_mean'] = deaths_headlines['total_2019 total_2018 tota
  deaths_headlines
  ```
  
  deaths_headlines
  ```
  
-```python
+```python Collapsed="false"
  deaths_headlines['total_2020 total_2019 total_2018 total_2017 total_2016 total_2015'.split()].plot(figsize=(14, 8))
  ```
  
  deaths_headlines['total_2020 total_2019 total_2018 total_2017 total_2016 total_2015'.split()].plot(figsize=(14, 8))
  ```
  
-```python
+```python Collapsed="false"
  deaths_headlines[['total_2020', 'previous_mean']].plot(figsize=(10, 8))
  ```
  
  deaths_headlines[['total_2020', 'previous_mean']].plot(figsize=(10, 8))
  ```
  
-```python
+```python Collapsed="false"
  deaths_headlines_i.plot()
  ```
  
  deaths_headlines_i.plot()
  ```
  
-```python
+```python Collapsed="false"
  # Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#
  
  # Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#
  
+dhna = deaths_headlines.dropna()
+
  fig = plt.figure(figsize=(10, 10))
  ax = fig.add_subplot(111, projection="polar")
  
  theta = np.roll(
      np.flip(
  fig = plt.figure(figsize=(10, 10))
  ax = fig.add_subplot(111, projection="polar")
  
  theta = np.roll(
      np.flip(
-        np.arange(len(deaths_headlines))/float(len(deaths_headlines))*2.*np.pi),
+        np.arange(len(dhna))/float(len(dhna))*2.*np.pi),
      14)
  # l15, = ax.plot(theta, deaths_headlines['total_2015'], color="#b56363", label="2015") # 0
  # l16, = ax.plot(theta, deaths_headlines['total_2016'], color="#a4b563", label="2016") # 72
  # l17, = ax.plot(theta, deaths_headlines['total_2017'], color="#63b584", label="2017") # 144
  # l18, = ax.plot(theta, deaths_headlines['total_2018'], color="#6384b5", label="2018") # 216
  # l19, = ax.plot(theta, deaths_headlines['total_2019'], color="#a4635b", label="2019") # 288
      14)
  # l15, = ax.plot(theta, deaths_headlines['total_2015'], color="#b56363", label="2015") # 0
  # l16, = ax.plot(theta, deaths_headlines['total_2016'], color="#a4b563", label="2016") # 72
  # l17, = ax.plot(theta, deaths_headlines['total_2017'], color="#63b584", label="2017") # 144
  # l18, = ax.plot(theta, deaths_headlines['total_2018'], color="#6384b5", label="2018") # 216
  # l19, = ax.plot(theta, deaths_headlines['total_2019'], color="#a4635b", label="2019") # 288
-l15, = ax.plot(theta, deaths_headlines['total_2015'], color="#e47d7d", label="2015") # 0
-l16, = ax.plot(theta, deaths_headlines['total_2016'], color="#afc169", label="2016") # 72 , d0e47d
-l17, = ax.plot(theta, deaths_headlines['total_2017'], color="#7de4a6", label="2017") # 144
-l18, = ax.plot(theta, deaths_headlines['total_2018'], color="#7da6e4", label="2018") # 216
-l19, = ax.plot(theta, deaths_headlines['total_2019'], color="#d07de4", label="2019") # 288
+l15, = ax.plot(theta, dhna['total_2015'], color="#e47d7d", label="2015") # 0
+l16, = ax.plot(theta, dhna['total_2016'], color="#afc169", label="2016") # 72 , d0e47d
+l17, = ax.plot(theta, dhna['total_2017'], color="#7de4a6", label="2017") # 144
+l18, = ax.plot(theta, dhna['total_2018'], color="#7da6e4", label="2018") # 216
+l19, = ax.plot(theta, dhna['total_2019'], color="#d07de4", label="2019") # 288
  
  
-lmean, = ax.plot(theta, deaths_headlines['previous_mean'], color="black", linestyle='dashed', label="mean")
+lmean, = ax.plot(theta, dhna['previous_mean'], color="black", linestyle='dashed', label="mean")
  
  
-l20, = ax.plot(theta, deaths_headlines['total_2020'], color="red", label="2020")
+l20, = ax.plot(theta, dhna['total_2020'], color="red", label="2020")
  
  # deaths_headlines.total_2019.plot(ax=ax)
  
  
  # deaths_headlines.total_2019.plot(ax=ax)
  
@@ -410,60 +420,62 @@ def _closeline(line):
  
  
  ax.set_xticks(theta)
  
  
  ax.set_xticks(theta)
-ax.set_xticklabels(deaths_headlines.index)
+ax.set_xticklabels(dhna.index)
  plt.legend()
  plt.title("Deaths by week over years, all UK")
  plt.savefig('deaths-radar.png')
  plt.show()
  ```
  
  plt.legend()
  plt.title("Deaths by week over years, all UK")
  plt.savefig('deaths-radar.png')
  plt.show()
  ```
  
+<!-- #region Collapsed="false" -->
  # Excess deaths calculation
  # Excess deaths calculation
+<!-- #endregion -->
  
  
-```python
+```python Collapsed="false"
  # raw_data_2020.loc[12, 'Week ended']
  ```
  
  # raw_data_2020.loc[12, 'Week ended']
  ```
  
-```python
+```python Collapsed="false"
  eng_xls.loc[12, 'Week ended']
  ```
  
  eng_xls.loc[12, 'Week ended']
  ```
  
-```python
+```python Collapsed="false"
  # raw_data_2020.iloc[-1]['Week ended']
  ```
  
  # raw_data_2020.iloc[-1]['Week ended']
  ```
  
-```python
+```python Collapsed="false"
  deaths_headlines_e.total_2020.dropna().last_valid_index()
  ```
  
  deaths_headlines_e.total_2020.dropna().last_valid_index()
  ```
  
-```python
+```python Collapsed="false"
  eng_xls.loc[deaths_headlines_e.total_2020.dropna().last_valid_index(), 'Week ended']
  ```
  
  eng_xls.loc[deaths_headlines_e.total_2020.dropna().last_valid_index(), 'Week ended']
  ```
  
-```python
+```python Collapsed="false"
  eng_xls.loc[27, 'Week ended']
  ```
  
  eng_xls.loc[27, 'Week ended']
  ```
  
-```python
+```python Collapsed="false"
  # raw_data_2020.loc[12].droplevel(1)['Week ended']
  ```
  
  # raw_data_2020.loc[12].droplevel(1)['Week ended']
  ```
  
-```python
+```python Collapsed="false"
  # raw_data_2020.iloc[-1].droplevel(1)['Week ended']
  ```
  
  # raw_data_2020.iloc[-1].droplevel(1)['Week ended']
  ```
  
-```python
+```python Collapsed="false"
  (deaths_headlines.loc[12:].total_2020 - deaths_headlines.loc[12:].previous_mean).sum()
  ```
  
  (deaths_headlines.loc[12:].total_2020 - deaths_headlines.loc[12:].previous_mean).sum()
  ```
  
-```python
+```python Collapsed="false"
  (deaths_headlines.loc[12:27].total_2020 - deaths_headlines.loc[12:27].previous_mean).sum()
  ```
  
  (deaths_headlines.loc[12:27].total_2020 - deaths_headlines.loc[12:27].previous_mean).sum()
  ```
  
-```python
+```python Collapsed="false"
  deaths_headlines.previous_mean.sum()
  ```
  
  deaths_headlines.previous_mean.sum()
  ```
  
-```python
+```python Collapsed="false"
  # excess_death_data = {
  #     'start_date': str(eng_xls.loc[12, 'Week ended']),
  #     'end_date': str(eng_xls.loc[deaths_headlines_e.total_2020.dropna().last_valid_index(), 'Week ended']),
  # excess_death_data = {
  #     'start_date': str(eng_xls.loc[12, 'Week ended']),
  #     'end_date': str(eng_xls.loc[deaths_headlines_e.total_2020.dropna().last_valid_index(), 'Week ended']),
@@ -474,18 +486,18 @@ deaths_headlines.previous_mean.sum()
  #     json.dump(excess_death_data, f)
  ```
  
  #     json.dump(excess_death_data, f)
  ```
  
-```python
-excess_death_data = {
-    'start_date': str(eng_xls.loc[12, 'Week ended']),
-    'end_date': str(eng_xls.loc[27, 'Week ended']),
-    'excess_deaths': (deaths_headlines.loc[12:27].total_2020 - deaths_headlines.loc[12:27].previous_mean).sum()
-}
+```python Collapsed="false"
+# excess_death_data = {
+#     'start_date': str(eng_xls.loc[12, 'Week ended']),
+#     'end_date': str(eng_xls.loc[27, 'Week ended']),
+#     'excess_deaths': (deaths_headlines.loc[12:27].total_2020 - deaths_headlines.loc[12:27].previous_mean).sum()
+# }
  
  
-with open('excess_deaths.json', 'w') as f:
-    json.dump(excess_death_data, f)
+# with open('excess_deaths.json', 'w') as f:
+#     json.dump(excess_death_data, f)
  ```
  
  ```
  
-```python
+```python Collapsed="false"
  # excess_death_data = {
  #     'start_date': str(raw_data_2020.loc[12].droplevel(1)['Week ended']),
  #     'end_date': str(raw_data_2020.iloc[-1].droplevel(1)['Week ended']),
  # excess_death_data = {
  #     'start_date': str(raw_data_2020.loc[12].droplevel(1)['Week ended']),
  #     'end_date': str(raw_data_2020.iloc[-1].droplevel(1)['Week ended']),
@@ -496,29 +508,31 @@ with open('excess_deaths.json', 'w') as f:
  #     json.dump(excess_death_data, f)
  ```
  
  #     json.dump(excess_death_data, f)
  ```
  
-```python
+```python Collapsed="false"
  eng_xls['Week ended']
  ```
  
  eng_xls['Week ended']
  ```
  
-```python
+```python Collapsed="false"
  # raw_data_2020.droplevel(1, axis='columns')['Week ended']
  ```
  
  # raw_data_2020.droplevel(1, axis='columns')['Week ended']
  ```
  
-```python
+```python Collapsed="false"
  deaths_by_week = deaths_headlines.merge(eng_xls['Week ended'], left_index=True, right_index=True)
  deaths_by_week.rename(columns={'Week ended': 'week_ended'}, inplace=True)
  deaths_by_week.to_csv('deaths_by_week.csv', header=True, index=False)
  ```
  
  deaths_by_week = deaths_headlines.merge(eng_xls['Week ended'], left_index=True, right_index=True)
  deaths_by_week.rename(columns={'Week ended': 'week_ended'}, inplace=True)
  deaths_by_week.to_csv('deaths_by_week.csv', header=True, index=False)
  ```
  
-```python
+```python Collapsed="false"
  # deaths_by_week = deaths_headlines.merge(raw_data_2020.droplevel(1, axis='columns')['Week ended'], left_index=True, right_index=True)
  # deaths_by_week.rename(columns={'Week ended': 'week_ended'}, inplace=True)
  # deaths_by_week.to_csv('deaths_by_week.csv', header=True, index=False)
  ```
  
  # deaths_by_week = deaths_headlines.merge(raw_data_2020.droplevel(1, axis='columns')['Week ended'], left_index=True, right_index=True)
  # deaths_by_week.rename(columns={'Week ended': 'week_ended'}, inplace=True)
  # deaths_by_week.to_csv('deaths_by_week.csv', header=True, index=False)
  ```
  
+<!-- #region Collapsed="false" -->
  # Plots for UK nations
  # Plots for UK nations
+<!-- #endregion -->
  
  
-```python
+```python Collapsed="false"
  # Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#
  
  fig = plt.figure(figsize=(10, 10))
  # Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#
  
  fig = plt.figure(figsize=(10, 10))
@@ -557,7 +571,7 @@ plt.savefig('deaths-radar_england.png')
  plt.show()
  ```
  
  plt.show()
  ```
  
-```python
+```python Collapsed="false"
  # Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#
  
  fig = plt.figure(figsize=(10, 10))
  # Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#
  
  fig = plt.figure(figsize=(10, 10))
@@ -595,7 +609,7 @@ plt.savefig('deaths-radar_wales.png')
  plt.show()
  ```
  
  plt.show()
  ```
  
-```python
+```python Collapsed="false"
  # Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#
  
  fig = plt.figure(figsize=(10, 10))
  # Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#
  
  fig = plt.figure(figsize=(10, 10))
@@ -633,7 +647,7 @@ plt.savefig('deaths-radar_scotland.png')
  plt.show()
  ```
  
  plt.show()
  ```
  
-```python
+```python Collapsed="false"
  # Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#
  
  fig = plt.figure(figsize=(10, 10))
  # Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#
  
  fig = plt.figure(figsize=(10, 10))
@@ -671,11 +685,11 @@ plt.savefig('deaths-radar_northern_ireland.png')
  plt.show()
  ```
  
  plt.show()
  ```
  
-```python
+```python Collapsed="false"
  # list(raw_data_2020.columns)
  ```
  
  # list(raw_data_2020.columns)
  ```
  
-```python
+```python Collapsed="false"
  # deaths_headlines_e = raw_data_2020.iloc[:, [1]].copy()
  # deaths_headlines_e.columns = ['total_2020']
  # deaths_headlines_w = raw_data_2020['W92000004'].copy()
  # deaths_headlines_e = raw_data_2020.iloc[:, [1]].copy()
  # deaths_headlines_e.columns = ['total_2020']
  # deaths_headlines_w = raw_data_2020['W92000004'].copy()
@@ -686,10 +700,10 @@ plt.show()
  # deaths_headlines_e
  ```
  
  # deaths_headlines_e
  ```
  
-```python
+```python Collapsed="false"
  
  ```
  
  
  ```
  
-```python
+```python Collapsed="false"
  
  ```
  
  ```
diff --git a/uk_deaths_import.ipynb b/uk_deaths_import.ipynb

new file mode 100644 (file)

index 0000000..7df5f34
--- /dev/null
+++ b/uk_deaths_import.ipynb
@@ -0,0 +1,6213 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "source": [
+    "Data from:\n",
+    "\n",
+    "* [Office of National Statistics](https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/weeklyprovisionalfiguresondeathsregisteredinenglandandwales) (Endland and Wales) Weeks start on a Saturday.\n",
+    "* [Northern Ireland Statistics and Research Agency](https://www.nisra.gov.uk/publications/weekly-deaths) (Northern Ireland). Weeks start on a Saturday. Note that the week numbers don't match the England and Wales data.\n",
+    "* [National Records of Scotland](https://www.nrscotland.gov.uk/statistics-and-data/statistics/statistics-by-theme/vital-events/general-publications/weekly-and-monthly-data-on-births-and-deaths/weekly-data-on-births-and-deaths) (Scotland). Note that Scotland uses ISO8601 week numbers, which start on a Monday.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The sql extension is already loaded. To reload it, use:\n",
+      "  %reload_ext sql\n"
+     ]
+    }
+   ],
+   "source": [
+    "import itertools\n",
+    "import collections\n",
+    "import json\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "from scipy.stats import gmean\n",
+    "import datetime\n",
+    "\n",
+    "import matplotlib as mpl\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline\n",
+    "\n",
+    "from sqlalchemy.types import Integer, Text, String, DateTime, Float\n",
+    "from sqlalchemy import create_engine\n",
+    "%load_ext sql"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Connected: covid@covid'"
+      ]
+     },
+     "execution_count": 57,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql $connection_string"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "engine = create_engine(connection_string)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "england_wales_filename = 'uk-deaths-data/copyofpublishedweek042021.xlsx'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "scotland_filename = 'uk-deaths-data/Scottish Government COVID-19 data (10 February 2021).xlsx'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "n_ireland_filename = 'uk-deaths-data/Weekly_Deaths_0.xlsx'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {
+    "Collapsed": "false",
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>...</th>\n",
+       "      <th>North East</th>\n",
+       "      <th>North West</th>\n",
+       "      <th>Yorkshire and The Humber</th>\n",
+       "      <th>East Midlands</th>\n",
+       "      <th>West Midlands</th>\n",
+       "      <th>East</th>\n",
+       "      <th>London</th>\n",
+       "      <th>South East</th>\n",
+       "      <th>South West</th>\n",
+       "      <th>Wales</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Week number</th>\n",
+       "      <td>Week ended</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Total deaths, all ages (2021)</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Total deaths, all ages (2020)</td>\n",
+       "      <td>Total deaths: average of corresponding week in...</td>\n",
+       "      <td>Total deaths: average of corresponding week in...</td>\n",
+       "      <td>Total deaths: average of corresponding week in...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>E12000001</td>\n",
+       "      <td>E12000002</td>\n",
+       "      <td>E12000003</td>\n",
+       "      <td>E12000004</td>\n",
+       "      <td>E12000005</td>\n",
+       "      <td>E12000006</td>\n",
+       "      <td>E12000007</td>\n",
+       "      <td>E12000008</td>\n",
+       "      <td>E12000009</td>\n",
+       "      <td>W92000004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2021-01-08 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>17751</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12254</td>\n",
+       "      <td>12175</td>\n",
+       "      <td>11412</td>\n",
+       "      <td>756</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>858</td>\n",
+       "      <td>2090</td>\n",
+       "      <td>1640</td>\n",
+       "      <td>1414</td>\n",
+       "      <td>1785</td>\n",
+       "      <td>2082</td>\n",
+       "      <td>2138</td>\n",
+       "      <td>2950</td>\n",
+       "      <td>1570</td>\n",
+       "      <td>1198</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2021-01-15 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>18042</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14058</td>\n",
+       "      <td>13822</td>\n",
+       "      <td>12933</td>\n",
+       "      <td>856</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>797</td>\n",
+       "      <td>2112</td>\n",
+       "      <td>1408</td>\n",
+       "      <td>1402</td>\n",
+       "      <td>1820</td>\n",
+       "      <td>2240</td>\n",
+       "      <td>2346</td>\n",
+       "      <td>3127</td>\n",
+       "      <td>1593</td>\n",
+       "      <td>1170</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2021-01-22 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>18676</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12990</td>\n",
+       "      <td>13216</td>\n",
+       "      <td>12370</td>\n",
+       "      <td>812</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>836</td>\n",
+       "      <td>2202</td>\n",
+       "      <td>1426</td>\n",
+       "      <td>1496</td>\n",
+       "      <td>1925</td>\n",
+       "      <td>2267</td>\n",
+       "      <td>2417</td>\n",
+       "      <td>3328</td>\n",
+       "      <td>1670</td>\n",
+       "      <td>1077</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2021-01-29 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>18448</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11856</td>\n",
+       "      <td>12760</td>\n",
+       "      <td>11933</td>\n",
+       "      <td>802</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>752</td>\n",
+       "      <td>2191</td>\n",
+       "      <td>1485</td>\n",
+       "      <td>1403</td>\n",
+       "      <td>1926</td>\n",
+       "      <td>2350</td>\n",
+       "      <td>2302</td>\n",
+       "      <td>3271</td>\n",
+       "      <td>1775</td>\n",
+       "      <td>974</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2021-02-05 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11612</td>\n",
+       "      <td>12206</td>\n",
+       "      <td>11419</td>\n",
+       "      <td>760</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2021-02-12 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10986</td>\n",
+       "      <td>11925</td>\n",
+       "      <td>11154</td>\n",
+       "      <td>729</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2021-02-19 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10944</td>\n",
+       "      <td>11627</td>\n",
+       "      <td>10876</td>\n",
+       "      <td>722</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2021-02-26 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10841</td>\n",
+       "      <td>11548</td>\n",
+       "      <td>10790</td>\n",
+       "      <td>724</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2021-03-05 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10816</td>\n",
+       "      <td>11183</td>\n",
+       "      <td>10448</td>\n",
+       "      <td>698</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>2021-03-12 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10895</td>\n",
+       "      <td>11498</td>\n",
+       "      <td>10745</td>\n",
+       "      <td>720</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>2021-03-19 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11019</td>\n",
+       "      <td>11205</td>\n",
+       "      <td>10447</td>\n",
+       "      <td>727</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>2021-03-26 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10645</td>\n",
+       "      <td>10573</td>\n",
+       "      <td>9841</td>\n",
+       "      <td>677</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>2021-04-02 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11141</td>\n",
+       "      <td>10130</td>\n",
+       "      <td>9414</td>\n",
+       "      <td>665</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>2021-04-09 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>16387</td>\n",
+       "      <td>10305</td>\n",
+       "      <td>9601</td>\n",
+       "      <td>667</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>2021-04-16 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>18516</td>\n",
+       "      <td>10520</td>\n",
+       "      <td>9807</td>\n",
+       "      <td>671</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>2021-04-23 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>22351</td>\n",
+       "      <td>10497</td>\n",
+       "      <td>9787</td>\n",
+       "      <td>661</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>2021-04-30 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>21997</td>\n",
+       "      <td>10458</td>\n",
+       "      <td>9768</td>\n",
+       "      <td>662</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>2021-05-07 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>17953</td>\n",
+       "      <td>9941</td>\n",
+       "      <td>9289</td>\n",
+       "      <td>624</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>2021-05-14 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12657</td>\n",
+       "      <td>9576</td>\n",
+       "      <td>8937</td>\n",
+       "      <td>612</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>2021-05-21 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14573</td>\n",
+       "      <td>10188</td>\n",
+       "      <td>9526</td>\n",
+       "      <td>635</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>2021-05-28 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12288</td>\n",
+       "      <td>9940</td>\n",
+       "      <td>9299</td>\n",
+       "      <td>614</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>2021-06-04 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9824</td>\n",
+       "      <td>8171</td>\n",
+       "      <td>7607</td>\n",
+       "      <td>546</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>2021-06-11 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10709</td>\n",
+       "      <td>9977</td>\n",
+       "      <td>9346</td>\n",
+       "      <td>610</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>2021-06-18 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9976</td>\n",
+       "      <td>9417</td>\n",
+       "      <td>8803</td>\n",
+       "      <td>588</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>2021-06-25 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9339</td>\n",
+       "      <td>9404</td>\n",
+       "      <td>8810</td>\n",
+       "      <td>573</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>2021-07-02 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8979</td>\n",
+       "      <td>9293</td>\n",
+       "      <td>8695</td>\n",
+       "      <td>571</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>2021-07-09 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9140</td>\n",
+       "      <td>9183</td>\n",
+       "      <td>8606</td>\n",
+       "      <td>555</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>2021-07-16 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8690</td>\n",
+       "      <td>9250</td>\n",
+       "      <td>8648</td>\n",
+       "      <td>578</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>2021-07-23 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8823</td>\n",
+       "      <td>9093</td>\n",
+       "      <td>8502</td>\n",
+       "      <td>557</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>2021-07-30 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8891</td>\n",
+       "      <td>9052</td>\n",
+       "      <td>8452</td>\n",
+       "      <td>566</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>2021-08-06 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8946</td>\n",
+       "      <td>9036</td>\n",
+       "      <td>8436</td>\n",
+       "      <td>572</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>2021-08-13 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8945</td>\n",
+       "      <td>9102</td>\n",
+       "      <td>8502</td>\n",
+       "      <td>571</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>2021-08-20 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9392</td>\n",
+       "      <td>9085</td>\n",
+       "      <td>8494</td>\n",
+       "      <td>564</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>2021-08-27 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9631</td>\n",
+       "      <td>9157</td>\n",
+       "      <td>8560</td>\n",
+       "      <td>573</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>2021-09-03 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9032</td>\n",
+       "      <td>8241</td>\n",
+       "      <td>7674</td>\n",
+       "      <td>539</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>2021-09-10 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7739</td>\n",
+       "      <td>9182</td>\n",
+       "      <td>8604</td>\n",
+       "      <td>552</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>2021-09-17 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9811</td>\n",
+       "      <td>9306</td>\n",
+       "      <td>8708</td>\n",
+       "      <td>577</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>2021-09-24 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9523</td>\n",
+       "      <td>9264</td>\n",
+       "      <td>8663</td>\n",
+       "      <td>575</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>2021-10-01 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9634</td>\n",
+       "      <td>9377</td>\n",
+       "      <td>8744</td>\n",
+       "      <td>604</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>2021-10-08 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9945</td>\n",
+       "      <td>9555</td>\n",
+       "      <td>8942</td>\n",
+       "      <td>587</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>2021-10-15 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9954</td>\n",
+       "      <td>9811</td>\n",
+       "      <td>9168</td>\n",
+       "      <td>615</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>2021-10-22 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10534</td>\n",
+       "      <td>9865</td>\n",
+       "      <td>9215</td>\n",
+       "      <td>630</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>2021-10-29 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10739</td>\n",
+       "      <td>9759</td>\n",
+       "      <td>9104</td>\n",
+       "      <td>628</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>2021-11-05 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10887</td>\n",
+       "      <td>9891</td>\n",
+       "      <td>9248</td>\n",
+       "      <td>616</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>2021-11-12 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11812</td>\n",
+       "      <td>10331</td>\n",
+       "      <td>9675</td>\n",
+       "      <td>625</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>2021-11-19 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12254</td>\n",
+       "      <td>10350</td>\n",
+       "      <td>9662</td>\n",
+       "      <td>658</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>2021-11-26 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12535</td>\n",
+       "      <td>10380</td>\n",
+       "      <td>9701</td>\n",
+       "      <td>653</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>2021-12-03 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12456</td>\n",
+       "      <td>10357</td>\n",
+       "      <td>9690</td>\n",
+       "      <td>646</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>2021-12-10 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12303</td>\n",
+       "      <td>10695</td>\n",
+       "      <td>9995</td>\n",
+       "      <td>679</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>2021-12-17 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12292</td>\n",
+       "      <td>10750</td>\n",
+       "      <td>10034</td>\n",
+       "      <td>693</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>2021-12-24 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13011</td>\n",
+       "      <td>11548</td>\n",
+       "      <td>10804</td>\n",
+       "      <td>718</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>2021-12-31 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11520</td>\n",
+       "      <td>7954</td>\n",
+       "      <td>7421</td>\n",
+       "      <td>518</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53 7</th>\n",
+       "      <td>2020</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>:</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10069</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>54 rows × 87 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                             NaN  NaN  NaN                            NaN  \\\n",
+       "Week number           Week ended  NaN  NaN  Total deaths, all ages (2021)   \n",
+       "1            2021-01-08 00:00:00  NaN  NaN                          17751   \n",
+       "2            2021-01-15 00:00:00  NaN  NaN                          18042   \n",
+       "3            2021-01-22 00:00:00  NaN  NaN                          18676   \n",
+       "4            2021-01-29 00:00:00  NaN  NaN                          18448   \n",
+       "5            2021-02-05 00:00:00  NaN  NaN                            NaN   \n",
+       "6            2021-02-12 00:00:00  NaN  NaN                            NaN   \n",
+       "7            2021-02-19 00:00:00  NaN  NaN                            NaN   \n",
+       "8            2021-02-26 00:00:00  NaN  NaN                            NaN   \n",
+       "9            2021-03-05 00:00:00  NaN  NaN                            NaN   \n",
+       "10           2021-03-12 00:00:00  NaN  NaN                            NaN   \n",
+       "11           2021-03-19 00:00:00  NaN  NaN                            NaN   \n",
+       "12           2021-03-26 00:00:00  NaN  NaN                            NaN   \n",
+       "13           2021-04-02 00:00:00  NaN  NaN                            NaN   \n",
+       "14           2021-04-09 00:00:00  NaN  NaN                            NaN   \n",
+       "15           2021-04-16 00:00:00  NaN  NaN                            NaN   \n",
+       "16           2021-04-23 00:00:00  NaN  NaN                            NaN   \n",
+       "17           2021-04-30 00:00:00  NaN  NaN                            NaN   \n",
+       "18           2021-05-07 00:00:00  NaN  NaN                            NaN   \n",
+       "19           2021-05-14 00:00:00  NaN  NaN                            NaN   \n",
+       "20           2021-05-21 00:00:00  NaN  NaN                            NaN   \n",
+       "21           2021-05-28 00:00:00  NaN  NaN                            NaN   \n",
+       "22           2021-06-04 00:00:00  NaN  NaN                            NaN   \n",
+       "23           2021-06-11 00:00:00  NaN  NaN                            NaN   \n",
+       "24           2021-06-18 00:00:00  NaN  NaN                            NaN   \n",
+       "25           2021-06-25 00:00:00  NaN  NaN                            NaN   \n",
+       "26           2021-07-02 00:00:00  NaN  NaN                            NaN   \n",
+       "27           2021-07-09 00:00:00  NaN  NaN                            NaN   \n",
+       "28           2021-07-16 00:00:00  NaN  NaN                            NaN   \n",
+       "29           2021-07-23 00:00:00  NaN  NaN                            NaN   \n",
+       "30           2021-07-30 00:00:00  NaN  NaN                            NaN   \n",
+       "31           2021-08-06 00:00:00  NaN  NaN                            NaN   \n",
+       "32           2021-08-13 00:00:00  NaN  NaN                            NaN   \n",
+       "33           2021-08-20 00:00:00  NaN  NaN                            NaN   \n",
+       "34           2021-08-27 00:00:00  NaN  NaN                            NaN   \n",
+       "35           2021-09-03 00:00:00  NaN  NaN                            NaN   \n",
+       "36           2021-09-10 00:00:00  NaN  NaN                            NaN   \n",
+       "37           2021-09-17 00:00:00  NaN  NaN                            NaN   \n",
+       "38           2021-09-24 00:00:00  NaN  NaN                            NaN   \n",
+       "39           2021-10-01 00:00:00  NaN  NaN                            NaN   \n",
+       "40           2021-10-08 00:00:00  NaN  NaN                            NaN   \n",
+       "41           2021-10-15 00:00:00  NaN  NaN                            NaN   \n",
+       "42           2021-10-22 00:00:00  NaN  NaN                            NaN   \n",
+       "43           2021-10-29 00:00:00  NaN  NaN                            NaN   \n",
+       "44           2021-11-05 00:00:00  NaN  NaN                            NaN   \n",
+       "45           2021-11-12 00:00:00  NaN  NaN                            NaN   \n",
+       "46           2021-11-19 00:00:00  NaN  NaN                            NaN   \n",
+       "47           2021-11-26 00:00:00  NaN  NaN                            NaN   \n",
+       "48           2021-12-03 00:00:00  NaN  NaN                            NaN   \n",
+       "49           2021-12-10 00:00:00  NaN  NaN                            NaN   \n",
+       "50           2021-12-17 00:00:00  NaN  NaN                            NaN   \n",
+       "51           2021-12-24 00:00:00  NaN  NaN                            NaN   \n",
+       "52           2021-12-31 00:00:00  NaN  NaN                            NaN   \n",
+       "53 7                        2020  NaN  NaN                              :   \n",
+       "\n",
+       "             NaN                            NaN  \\\n",
+       "Week number  NaN  Total deaths, all ages (2020)   \n",
+       "1            NaN                          12254   \n",
+       "2            NaN                          14058   \n",
+       "3            NaN                          12990   \n",
+       "4            NaN                          11856   \n",
+       "5            NaN                          11612   \n",
+       "6            NaN                          10986   \n",
+       "7            NaN                          10944   \n",
+       "8            NaN                          10841   \n",
+       "9            NaN                          10816   \n",
+       "10           NaN                          10895   \n",
+       "11           NaN                          11019   \n",
+       "12           NaN                          10645   \n",
+       "13           NaN                          11141   \n",
+       "14           NaN                          16387   \n",
+       "15           NaN                          18516   \n",
+       "16           NaN                          22351   \n",
+       "17           NaN                          21997   \n",
+       "18           NaN                          17953   \n",
+       "19           NaN                          12657   \n",
+       "20           NaN                          14573   \n",
+       "21           NaN                          12288   \n",
+       "22           NaN                           9824   \n",
+       "23           NaN                          10709   \n",
+       "24           NaN                           9976   \n",
+       "25           NaN                           9339   \n",
+       "26           NaN                           8979   \n",
+       "27           NaN                           9140   \n",
+       "28           NaN                           8690   \n",
+       "29           NaN                           8823   \n",
+       "30           NaN                           8891   \n",
+       "31           NaN                           8946   \n",
+       "32           NaN                           8945   \n",
+       "33           NaN                           9392   \n",
+       "34           NaN                           9631   \n",
+       "35           NaN                           9032   \n",
+       "36           NaN                           7739   \n",
+       "37           NaN                           9811   \n",
+       "38           NaN                           9523   \n",
+       "39           NaN                           9634   \n",
+       "40           NaN                           9945   \n",
+       "41           NaN                           9954   \n",
+       "42           NaN                          10534   \n",
+       "43           NaN                          10739   \n",
+       "44           NaN                          10887   \n",
+       "45           NaN                          11812   \n",
+       "46           NaN                          12254   \n",
+       "47           NaN                          12535   \n",
+       "48           NaN                          12456   \n",
+       "49           NaN                          12303   \n",
+       "50           NaN                          12292   \n",
+       "51           NaN                          13011   \n",
+       "52           NaN                          11520   \n",
+       "53 7         NaN                          10069   \n",
+       "\n",
+       "                                                           NaN  \\\n",
+       "Week number  Total deaths: average of corresponding week in...   \n",
+       "1                                                        12175   \n",
+       "2                                                        13822   \n",
+       "3                                                        13216   \n",
+       "4                                                        12760   \n",
+       "5                                                        12206   \n",
+       "6                                                        11925   \n",
+       "7                                                        11627   \n",
+       "8                                                        11548   \n",
+       "9                                                        11183   \n",
+       "10                                                       11498   \n",
+       "11                                                       11205   \n",
+       "12                                                       10573   \n",
+       "13                                                       10130   \n",
+       "14                                                       10305   \n",
+       "15                                                       10520   \n",
+       "16                                                       10497   \n",
+       "17                                                       10458   \n",
+       "18                                                        9941   \n",
+       "19                                                        9576   \n",
+       "20                                                       10188   \n",
+       "21                                                        9940   \n",
+       "22                                                        8171   \n",
+       "23                                                        9977   \n",
+       "24                                                        9417   \n",
+       "25                                                        9404   \n",
+       "26                                                        9293   \n",
+       "27                                                        9183   \n",
+       "28                                                        9250   \n",
+       "29                                                        9093   \n",
+       "30                                                        9052   \n",
+       "31                                                        9036   \n",
+       "32                                                        9102   \n",
+       "33                                                        9085   \n",
+       "34                                                        9157   \n",
+       "35                                                        8241   \n",
+       "36                                                        9182   \n",
+       "37                                                        9306   \n",
+       "38                                                        9264   \n",
+       "39                                                        9377   \n",
+       "40                                                        9555   \n",
+       "41                                                        9811   \n",
+       "42                                                        9865   \n",
+       "43                                                        9759   \n",
+       "44                                                        9891   \n",
+       "45                                                       10331   \n",
+       "46                                                       10350   \n",
+       "47                                                       10380   \n",
+       "48                                                       10357   \n",
+       "49                                                       10695   \n",
+       "50                                                       10750   \n",
+       "51                                                       11548   \n",
+       "52                                                        7954   \n",
+       "53 7                                                         :   \n",
+       "\n",
+       "                                                           NaN  \\\n",
+       "Week number  Total deaths: average of corresponding week in...   \n",
+       "1                                                        11412   \n",
+       "2                                                        12933   \n",
+       "3                                                        12370   \n",
+       "4                                                        11933   \n",
+       "5                                                        11419   \n",
+       "6                                                        11154   \n",
+       "7                                                        10876   \n",
+       "8                                                        10790   \n",
+       "9                                                        10448   \n",
+       "10                                                       10745   \n",
+       "11                                                       10447   \n",
+       "12                                                        9841   \n",
+       "13                                                        9414   \n",
+       "14                                                        9601   \n",
+       "15                                                        9807   \n",
+       "16                                                        9787   \n",
+       "17                                                        9768   \n",
+       "18                                                        9289   \n",
+       "19                                                        8937   \n",
+       "20                                                        9526   \n",
+       "21                                                        9299   \n",
+       "22                                                        7607   \n",
+       "23                                                        9346   \n",
+       "24                                                        8803   \n",
+       "25                                                        8810   \n",
+       "26                                                        8695   \n",
+       "27                                                        8606   \n",
+       "28                                                        8648   \n",
+       "29                                                        8502   \n",
+       "30                                                        8452   \n",
+       "31                                                        8436   \n",
+       "32                                                        8502   \n",
+       "33                                                        8494   \n",
+       "34                                                        8560   \n",
+       "35                                                        7674   \n",
+       "36                                                        8604   \n",
+       "37                                                        8708   \n",
+       "38                                                        8663   \n",
+       "39                                                        8744   \n",
+       "40                                                        8942   \n",
+       "41                                                        9168   \n",
+       "42                                                        9215   \n",
+       "43                                                        9104   \n",
+       "44                                                        9248   \n",
+       "45                                                        9675   \n",
+       "46                                                        9662   \n",
+       "47                                                        9701   \n",
+       "48                                                        9690   \n",
+       "49                                                        9995   \n",
+       "50                                                       10034   \n",
+       "51                                                       10804   \n",
+       "52                                                        7421   \n",
+       "53 7                                                         :   \n",
+       "\n",
+       "                                                           NaN  NaN  ...  \\\n",
+       "Week number  Total deaths: average of corresponding week in...  NaN  ...   \n",
+       "1                                                          756  NaN  ...   \n",
+       "2                                                          856  NaN  ...   \n",
+       "3                                                          812  NaN  ...   \n",
+       "4                                                          802  NaN  ...   \n",
+       "5                                                          760  NaN  ...   \n",
+       "6                                                          729  NaN  ...   \n",
+       "7                                                          722  NaN  ...   \n",
+       "8                                                          724  NaN  ...   \n",
+       "9                                                          698  NaN  ...   \n",
+       "10                                                         720  NaN  ...   \n",
+       "11                                                         727  NaN  ...   \n",
+       "12                                                         677  NaN  ...   \n",
+       "13                                                         665  NaN  ...   \n",
+       "14                                                         667  NaN  ...   \n",
+       "15                                                         671  NaN  ...   \n",
+       "16                                                         661  NaN  ...   \n",
+       "17                                                         662  NaN  ...   \n",
+       "18                                                         624  NaN  ...   \n",
+       "19                                                         612  NaN  ...   \n",
+       "20                                                         635  NaN  ...   \n",
+       "21                                                         614  NaN  ...   \n",
+       "22                                                         546  NaN  ...   \n",
+       "23                                                         610  NaN  ...   \n",
+       "24                                                         588  NaN  ...   \n",
+       "25                                                         573  NaN  ...   \n",
+       "26                                                         571  NaN  ...   \n",
+       "27                                                         555  NaN  ...   \n",
+       "28                                                         578  NaN  ...   \n",
+       "29                                                         557  NaN  ...   \n",
+       "30                                                         566  NaN  ...   \n",
+       "31                                                         572  NaN  ...   \n",
+       "32                                                         571  NaN  ...   \n",
+       "33                                                         564  NaN  ...   \n",
+       "34                                                         573  NaN  ...   \n",
+       "35                                                         539  NaN  ...   \n",
+       "36                                                         552  NaN  ...   \n",
+       "37                                                         577  NaN  ...   \n",
+       "38                                                         575  NaN  ...   \n",
+       "39                                                         604  NaN  ...   \n",
+       "40                                                         587  NaN  ...   \n",
+       "41                                                         615  NaN  ...   \n",
+       "42                                                         630  NaN  ...   \n",
+       "43                                                         628  NaN  ...   \n",
+       "44                                                         616  NaN  ...   \n",
+       "45                                                         625  NaN  ...   \n",
+       "46                                                         658  NaN  ...   \n",
+       "47                                                         653  NaN  ...   \n",
+       "48                                                         646  NaN  ...   \n",
+       "49                                                         679  NaN  ...   \n",
+       "50                                                         693  NaN  ...   \n",
+       "51                                                         718  NaN  ...   \n",
+       "52                                                         518  NaN  ...   \n",
+       "53 7                                                         :  NaN  ...   \n",
+       "\n",
+       "            North East North West Yorkshire and The Humber East Midlands  \\\n",
+       "Week number  E12000001  E12000002                E12000003     E12000004   \n",
+       "1                  858       2090                     1640          1414   \n",
+       "2                  797       2112                     1408          1402   \n",
+       "3                  836       2202                     1426          1496   \n",
+       "4                  752       2191                     1485          1403   \n",
+       "5                  NaN        NaN                      NaN           NaN   \n",
+       "6                  NaN        NaN                      NaN           NaN   \n",
+       "7                  NaN        NaN                      NaN           NaN   \n",
+       "8                  NaN        NaN                      NaN           NaN   \n",
+       "9                  NaN        NaN                      NaN           NaN   \n",
+       "10                 NaN        NaN                      NaN           NaN   \n",
+       "11                 NaN        NaN                      NaN           NaN   \n",
+       "12                 NaN        NaN                      NaN           NaN   \n",
+       "13                 NaN        NaN                      NaN           NaN   \n",
+       "14                 NaN        NaN                      NaN           NaN   \n",
+       "15                 NaN        NaN                      NaN           NaN   \n",
+       "16                 NaN        NaN                      NaN           NaN   \n",
+       "17                 NaN        NaN                      NaN           NaN   \n",
+       "18                 NaN        NaN                      NaN           NaN   \n",
+       "19                 NaN        NaN                      NaN           NaN   \n",
+       "20                 NaN        NaN                      NaN           NaN   \n",
+       "21                 NaN        NaN                      NaN           NaN   \n",
+       "22                 NaN        NaN                      NaN           NaN   \n",
+       "23                 NaN        NaN                      NaN           NaN   \n",
+       "24                 NaN        NaN                      NaN           NaN   \n",
+       "25                 NaN        NaN                      NaN           NaN   \n",
+       "26                 NaN        NaN                      NaN           NaN   \n",
+       "27                 NaN        NaN                      NaN           NaN   \n",
+       "28                 NaN        NaN                      NaN           NaN   \n",
+       "29                 NaN        NaN                      NaN           NaN   \n",
+       "30                 NaN        NaN                      NaN           NaN   \n",
+       "31                 NaN        NaN                      NaN           NaN   \n",
+       "32                 NaN        NaN                      NaN           NaN   \n",
+       "33                 NaN        NaN                      NaN           NaN   \n",
+       "34                 NaN        NaN                      NaN           NaN   \n",
+       "35                 NaN        NaN                      NaN           NaN   \n",
+       "36                 NaN        NaN                      NaN           NaN   \n",
+       "37                 NaN        NaN                      NaN           NaN   \n",
+       "38                 NaN        NaN                      NaN           NaN   \n",
+       "39                 NaN        NaN                      NaN           NaN   \n",
+       "40                 NaN        NaN                      NaN           NaN   \n",
+       "41                 NaN        NaN                      NaN           NaN   \n",
+       "42                 NaN        NaN                      NaN           NaN   \n",
+       "43                 NaN        NaN                      NaN           NaN   \n",
+       "44                 NaN        NaN                      NaN           NaN   \n",
+       "45                 NaN        NaN                      NaN           NaN   \n",
+       "46                 NaN        NaN                      NaN           NaN   \n",
+       "47                 NaN        NaN                      NaN           NaN   \n",
+       "48                 NaN        NaN                      NaN           NaN   \n",
+       "49                 NaN        NaN                      NaN           NaN   \n",
+       "50                 NaN        NaN                      NaN           NaN   \n",
+       "51                 NaN        NaN                      NaN           NaN   \n",
+       "52                 NaN        NaN                      NaN           NaN   \n",
+       "53 7               NaN        NaN                      NaN           NaN   \n",
+       "\n",
+       "            West Midlands       East     London South East South West  \\\n",
+       "Week number     E12000005  E12000006  E12000007  E12000008  E12000009   \n",
+       "1                    1785       2082       2138       2950       1570   \n",
+       "2                    1820       2240       2346       3127       1593   \n",
+       "3                    1925       2267       2417       3328       1670   \n",
+       "4                    1926       2350       2302       3271       1775   \n",
+       "5                     NaN        NaN        NaN        NaN        NaN   \n",
+       "6                     NaN        NaN        NaN        NaN        NaN   \n",
+       "7                     NaN        NaN        NaN        NaN        NaN   \n",
+       "8                     NaN        NaN        NaN        NaN        NaN   \n",
+       "9                     NaN        NaN        NaN        NaN        NaN   \n",
+       "10                    NaN        NaN        NaN        NaN        NaN   \n",
+       "11                    NaN        NaN        NaN        NaN        NaN   \n",
+       "12                    NaN        NaN        NaN        NaN        NaN   \n",
+       "13                    NaN        NaN        NaN        NaN        NaN   \n",
+       "14                    NaN        NaN        NaN        NaN        NaN   \n",
+       "15                    NaN        NaN        NaN        NaN        NaN   \n",
+       "16                    NaN        NaN        NaN        NaN        NaN   \n",
+       "17                    NaN        NaN        NaN        NaN        NaN   \n",
+       "18                    NaN        NaN        NaN        NaN        NaN   \n",
+       "19                    NaN        NaN        NaN        NaN        NaN   \n",
+       "20                    NaN        NaN        NaN        NaN        NaN   \n",
+       "21                    NaN        NaN        NaN        NaN        NaN   \n",
+       "22                    NaN        NaN        NaN        NaN        NaN   \n",
+       "23                    NaN        NaN        NaN        NaN        NaN   \n",
+       "24                    NaN        NaN        NaN        NaN        NaN   \n",
+       "25                    NaN        NaN        NaN        NaN        NaN   \n",
+       "26                    NaN        NaN        NaN        NaN        NaN   \n",
+       "27                    NaN        NaN        NaN        NaN        NaN   \n",
+       "28                    NaN        NaN        NaN        NaN        NaN   \n",
+       "29                    NaN        NaN        NaN        NaN        NaN   \n",
+       "30                    NaN        NaN        NaN        NaN        NaN   \n",
+       "31                    NaN        NaN        NaN        NaN        NaN   \n",
+       "32                    NaN        NaN        NaN        NaN        NaN   \n",
+       "33                    NaN        NaN        NaN        NaN        NaN   \n",
+       "34                    NaN        NaN        NaN        NaN        NaN   \n",
+       "35                    NaN        NaN        NaN        NaN        NaN   \n",
+       "36                    NaN        NaN        NaN        NaN        NaN   \n",
+       "37                    NaN        NaN        NaN        NaN        NaN   \n",
+       "38                    NaN        NaN        NaN        NaN        NaN   \n",
+       "39                    NaN        NaN        NaN        NaN        NaN   \n",
+       "40                    NaN        NaN        NaN        NaN        NaN   \n",
+       "41                    NaN        NaN        NaN        NaN        NaN   \n",
+       "42                    NaN        NaN        NaN        NaN        NaN   \n",
+       "43                    NaN        NaN        NaN        NaN        NaN   \n",
+       "44                    NaN        NaN        NaN        NaN        NaN   \n",
+       "45                    NaN        NaN        NaN        NaN        NaN   \n",
+       "46                    NaN        NaN        NaN        NaN        NaN   \n",
+       "47                    NaN        NaN        NaN        NaN        NaN   \n",
+       "48                    NaN        NaN        NaN        NaN        NaN   \n",
+       "49                    NaN        NaN        NaN        NaN        NaN   \n",
+       "50                    NaN        NaN        NaN        NaN        NaN   \n",
+       "51                    NaN        NaN        NaN        NaN        NaN   \n",
+       "52                    NaN        NaN        NaN        NaN        NaN   \n",
+       "53 7                  NaN        NaN        NaN        NaN        NaN   \n",
+       "\n",
+       "                 Wales  \n",
+       "Week number  W92000004  \n",
+       "1                 1198  \n",
+       "2                 1170  \n",
+       "3                 1077  \n",
+       "4                  974  \n",
+       "5                  NaN  \n",
+       "6                  NaN  \n",
+       "7                  NaN  \n",
+       "8                  NaN  \n",
+       "9                  NaN  \n",
+       "10                 NaN  \n",
+       "11                 NaN  \n",
+       "12                 NaN  \n",
+       "13                 NaN  \n",
+       "14                 NaN  \n",
+       "15                 NaN  \n",
+       "16                 NaN  \n",
+       "17                 NaN  \n",
+       "18                 NaN  \n",
+       "19                 NaN  \n",
+       "20                 NaN  \n",
+       "21                 NaN  \n",
+       "22                 NaN  \n",
+       "23                 NaN  \n",
+       "24                 NaN  \n",
+       "25                 NaN  \n",
+       "26                 NaN  \n",
+       "27                 NaN  \n",
+       "28                 NaN  \n",
+       "29                 NaN  \n",
+       "30                 NaN  \n",
+       "31                 NaN  \n",
+       "32                 NaN  \n",
+       "33                 NaN  \n",
+       "34                 NaN  \n",
+       "35                 NaN  \n",
+       "36                 NaN  \n",
+       "37                 NaN  \n",
+       "38                 NaN  \n",
+       "39                 NaN  \n",
+       "40                 NaN  \n",
+       "41                 NaN  \n",
+       "42                 NaN  \n",
+       "43                 NaN  \n",
+       "44                 NaN  \n",
+       "45                 NaN  \n",
+       "46                 NaN  \n",
+       "47                 NaN  \n",
+       "48                 NaN  \n",
+       "49                 NaN  \n",
+       "50                 NaN  \n",
+       "51                 NaN  \n",
+       "52                 NaN  \n",
+       "53 7               NaN  \n",
+       "\n",
+       "[54 rows x 87 columns]"
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "eng_xls = pd.read_excel(england_wales_filename, \n",
+    "                        sheet_name=\"Weekly figures 2021\",\n",
+    "                        skiprows=[0, 1, 2, 3],\n",
+    "                        skipfooter=11,\n",
+    "                        header=0,\n",
+    "                        index_col=[1]\n",
+    "                       ).iloc[:91].T\n",
+    "eng_xls"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "eng_xls_columns = list(eng_xls.columns)\n",
+    "\n",
+    "for i, c in enumerate(eng_xls_columns):\n",
+    "#     print(i, c, type(c), isinstance(c, float))\n",
+    "    if isinstance(c, float) and np.isnan(c):\n",
+    "        if eng_xls.iloc[0].iloc[i] is not pd.NaT:\n",
+    "            eng_xls_columns[i] = eng_xls.iloc[0].iloc[i]\n",
+    "\n",
+    "# np.isnan(eng_xls_columns[0])\n",
+    "# eng_xls_columns\n",
+    "\n",
+    "eng_xls.columns = eng_xls_columns\n",
+    "# eng_xls.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Week ended</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>Total deaths, all ages (2021)</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>Total deaths, all ages (2020)</th>\n",
+       "      <th>Total deaths: average of corresponding week in 2015-2019 (England and Wales) 1</th>\n",
+       "      <th>Total deaths: average of corresponding week in 2015-2019 (England) 1</th>\n",
+       "      <th>Total deaths: average of corresponding week in 2015-2019 (Wales) 1</th>\n",
+       "      <th>NaN</th>\n",
+       "      <th>...</th>\n",
+       "      <th>North East</th>\n",
+       "      <th>North West</th>\n",
+       "      <th>Yorkshire and The Humber</th>\n",
+       "      <th>East Midlands</th>\n",
+       "      <th>West Midlands</th>\n",
+       "      <th>East</th>\n",
+       "      <th>London</th>\n",
+       "      <th>South East</th>\n",
+       "      <th>South West</th>\n",
+       "      <th>Wales</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Week number</th>\n",
+       "      <td>Week ended</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Total deaths, all ages (2021)</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Total deaths, all ages (2020)</td>\n",
+       "      <td>Total deaths: average of corresponding week in...</td>\n",
+       "      <td>Total deaths: average of corresponding week in...</td>\n",
+       "      <td>Total deaths: average of corresponding week in...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>E12000001</td>\n",
+       "      <td>E12000002</td>\n",
+       "      <td>E12000003</td>\n",
+       "      <td>E12000004</td>\n",
+       "      <td>E12000005</td>\n",
+       "      <td>E12000006</td>\n",
+       "      <td>E12000007</td>\n",
+       "      <td>E12000008</td>\n",
+       "      <td>E12000009</td>\n",
+       "      <td>W92000004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2021-01-08 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>17751</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12254</td>\n",
+       "      <td>12175</td>\n",
+       "      <td>11412</td>\n",
+       "      <td>756</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>858</td>\n",
+       "      <td>2090</td>\n",
+       "      <td>1640</td>\n",
+       "      <td>1414</td>\n",
+       "      <td>1785</td>\n",
+       "      <td>2082</td>\n",
+       "      <td>2138</td>\n",
+       "      <td>2950</td>\n",
+       "      <td>1570</td>\n",
+       "      <td>1198</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2021-01-15 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>18042</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14058</td>\n",
+       "      <td>13822</td>\n",
+       "      <td>12933</td>\n",
+       "      <td>856</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>797</td>\n",
+       "      <td>2112</td>\n",
+       "      <td>1408</td>\n",
+       "      <td>1402</td>\n",
+       "      <td>1820</td>\n",
+       "      <td>2240</td>\n",
+       "      <td>2346</td>\n",
+       "      <td>3127</td>\n",
+       "      <td>1593</td>\n",
+       "      <td>1170</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2021-01-22 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>18676</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12990</td>\n",
+       "      <td>13216</td>\n",
+       "      <td>12370</td>\n",
+       "      <td>812</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>836</td>\n",
+       "      <td>2202</td>\n",
+       "      <td>1426</td>\n",
+       "      <td>1496</td>\n",
+       "      <td>1925</td>\n",
+       "      <td>2267</td>\n",
+       "      <td>2417</td>\n",
+       "      <td>3328</td>\n",
+       "      <td>1670</td>\n",
+       "      <td>1077</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2021-01-29 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>18448</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11856</td>\n",
+       "      <td>12760</td>\n",
+       "      <td>11933</td>\n",
+       "      <td>802</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>752</td>\n",
+       "      <td>2191</td>\n",
+       "      <td>1485</td>\n",
+       "      <td>1403</td>\n",
+       "      <td>1926</td>\n",
+       "      <td>2350</td>\n",
+       "      <td>2302</td>\n",
+       "      <td>3271</td>\n",
+       "      <td>1775</td>\n",
+       "      <td>974</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2021-02-05 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11612</td>\n",
+       "      <td>12206</td>\n",
+       "      <td>11419</td>\n",
+       "      <td>760</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2021-02-12 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10986</td>\n",
+       "      <td>11925</td>\n",
+       "      <td>11154</td>\n",
+       "      <td>729</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2021-02-19 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10944</td>\n",
+       "      <td>11627</td>\n",
+       "      <td>10876</td>\n",
+       "      <td>722</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2021-02-26 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10841</td>\n",
+       "      <td>11548</td>\n",
+       "      <td>10790</td>\n",
+       "      <td>724</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2021-03-05 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10816</td>\n",
+       "      <td>11183</td>\n",
+       "      <td>10448</td>\n",
+       "      <td>698</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>2021-03-12 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10895</td>\n",
+       "      <td>11498</td>\n",
+       "      <td>10745</td>\n",
+       "      <td>720</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>2021-03-19 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11019</td>\n",
+       "      <td>11205</td>\n",
+       "      <td>10447</td>\n",
+       "      <td>727</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>2021-03-26 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10645</td>\n",
+       "      <td>10573</td>\n",
+       "      <td>9841</td>\n",
+       "      <td>677</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>2021-04-02 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11141</td>\n",
+       "      <td>10130</td>\n",
+       "      <td>9414</td>\n",
+       "      <td>665</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>2021-04-09 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>16387</td>\n",
+       "      <td>10305</td>\n",
+       "      <td>9601</td>\n",
+       "      <td>667</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>2021-04-16 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>18516</td>\n",
+       "      <td>10520</td>\n",
+       "      <td>9807</td>\n",
+       "      <td>671</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>2021-04-23 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>22351</td>\n",
+       "      <td>10497</td>\n",
+       "      <td>9787</td>\n",
+       "      <td>661</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>2021-04-30 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>21997</td>\n",
+       "      <td>10458</td>\n",
+       "      <td>9768</td>\n",
+       "      <td>662</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>2021-05-07 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>17953</td>\n",
+       "      <td>9941</td>\n",
+       "      <td>9289</td>\n",
+       "      <td>624</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>2021-05-14 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12657</td>\n",
+       "      <td>9576</td>\n",
+       "      <td>8937</td>\n",
+       "      <td>612</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>2021-05-21 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14573</td>\n",
+       "      <td>10188</td>\n",
+       "      <td>9526</td>\n",
+       "      <td>635</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>2021-05-28 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12288</td>\n",
+       "      <td>9940</td>\n",
+       "      <td>9299</td>\n",
+       "      <td>614</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>2021-06-04 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9824</td>\n",
+       "      <td>8171</td>\n",
+       "      <td>7607</td>\n",
+       "      <td>546</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>2021-06-11 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10709</td>\n",
+       "      <td>9977</td>\n",
+       "      <td>9346</td>\n",
+       "      <td>610</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>2021-06-18 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9976</td>\n",
+       "      <td>9417</td>\n",
+       "      <td>8803</td>\n",
+       "      <td>588</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>2021-06-25 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9339</td>\n",
+       "      <td>9404</td>\n",
+       "      <td>8810</td>\n",
+       "      <td>573</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>2021-07-02 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8979</td>\n",
+       "      <td>9293</td>\n",
+       "      <td>8695</td>\n",
+       "      <td>571</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>2021-07-09 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9140</td>\n",
+       "      <td>9183</td>\n",
+       "      <td>8606</td>\n",
+       "      <td>555</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>2021-07-16 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8690</td>\n",
+       "      <td>9250</td>\n",
+       "      <td>8648</td>\n",
+       "      <td>578</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>2021-07-23 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8823</td>\n",
+       "      <td>9093</td>\n",
+       "      <td>8502</td>\n",
+       "      <td>557</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>2021-07-30 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8891</td>\n",
+       "      <td>9052</td>\n",
+       "      <td>8452</td>\n",
+       "      <td>566</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>2021-08-06 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8946</td>\n",
+       "      <td>9036</td>\n",
+       "      <td>8436</td>\n",
+       "      <td>572</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>2021-08-13 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8945</td>\n",
+       "      <td>9102</td>\n",
+       "      <td>8502</td>\n",
+       "      <td>571</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>2021-08-20 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9392</td>\n",
+       "      <td>9085</td>\n",
+       "      <td>8494</td>\n",
+       "      <td>564</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>2021-08-27 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9631</td>\n",
+       "      <td>9157</td>\n",
+       "      <td>8560</td>\n",
+       "      <td>573</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>2021-09-03 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9032</td>\n",
+       "      <td>8241</td>\n",
+       "      <td>7674</td>\n",
+       "      <td>539</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>2021-09-10 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7739</td>\n",
+       "      <td>9182</td>\n",
+       "      <td>8604</td>\n",
+       "      <td>552</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>2021-09-17 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9811</td>\n",
+       "      <td>9306</td>\n",
+       "      <td>8708</td>\n",
+       "      <td>577</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>2021-09-24 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9523</td>\n",
+       "      <td>9264</td>\n",
+       "      <td>8663</td>\n",
+       "      <td>575</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>2021-10-01 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9634</td>\n",
+       "      <td>9377</td>\n",
+       "      <td>8744</td>\n",
+       "      <td>604</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>2021-10-08 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9945</td>\n",
+       "      <td>9555</td>\n",
+       "      <td>8942</td>\n",
+       "      <td>587</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>2021-10-15 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>9954</td>\n",
+       "      <td>9811</td>\n",
+       "      <td>9168</td>\n",
+       "      <td>615</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>2021-10-22 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10534</td>\n",
+       "      <td>9865</td>\n",
+       "      <td>9215</td>\n",
+       "      <td>630</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>2021-10-29 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10739</td>\n",
+       "      <td>9759</td>\n",
+       "      <td>9104</td>\n",
+       "      <td>628</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>2021-11-05 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10887</td>\n",
+       "      <td>9891</td>\n",
+       "      <td>9248</td>\n",
+       "      <td>616</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>2021-11-12 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11812</td>\n",
+       "      <td>10331</td>\n",
+       "      <td>9675</td>\n",
+       "      <td>625</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>2021-11-19 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12254</td>\n",
+       "      <td>10350</td>\n",
+       "      <td>9662</td>\n",
+       "      <td>658</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>2021-11-26 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12535</td>\n",
+       "      <td>10380</td>\n",
+       "      <td>9701</td>\n",
+       "      <td>653</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>2021-12-03 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12456</td>\n",
+       "      <td>10357</td>\n",
+       "      <td>9690</td>\n",
+       "      <td>646</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>2021-12-10 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12303</td>\n",
+       "      <td>10695</td>\n",
+       "      <td>9995</td>\n",
+       "      <td>679</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>2021-12-17 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12292</td>\n",
+       "      <td>10750</td>\n",
+       "      <td>10034</td>\n",
+       "      <td>693</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>2021-12-24 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13011</td>\n",
+       "      <td>11548</td>\n",
+       "      <td>10804</td>\n",
+       "      <td>718</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>2021-12-31 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11520</td>\n",
+       "      <td>7954</td>\n",
+       "      <td>7421</td>\n",
+       "      <td>518</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53 7</th>\n",
+       "      <td>2020</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>:</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10069</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>54 rows × 87 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                      Week ended  NaN  NaN  Total deaths, all ages (2021)  \\\n",
+       "Week number           Week ended  NaN  NaN  Total deaths, all ages (2021)   \n",
+       "1            2021-01-08 00:00:00  NaN  NaN                          17751   \n",
+       "2            2021-01-15 00:00:00  NaN  NaN                          18042   \n",
+       "3            2021-01-22 00:00:00  NaN  NaN                          18676   \n",
+       "4            2021-01-29 00:00:00  NaN  NaN                          18448   \n",
+       "5            2021-02-05 00:00:00  NaN  NaN                            NaN   \n",
+       "6            2021-02-12 00:00:00  NaN  NaN                            NaN   \n",
+       "7            2021-02-19 00:00:00  NaN  NaN                            NaN   \n",
+       "8            2021-02-26 00:00:00  NaN  NaN                            NaN   \n",
+       "9            2021-03-05 00:00:00  NaN  NaN                            NaN   \n",
+       "10           2021-03-12 00:00:00  NaN  NaN                            NaN   \n",
+       "11           2021-03-19 00:00:00  NaN  NaN                            NaN   \n",
+       "12           2021-03-26 00:00:00  NaN  NaN                            NaN   \n",
+       "13           2021-04-02 00:00:00  NaN  NaN                            NaN   \n",
+       "14           2021-04-09 00:00:00  NaN  NaN                            NaN   \n",
+       "15           2021-04-16 00:00:00  NaN  NaN                            NaN   \n",
+       "16           2021-04-23 00:00:00  NaN  NaN                            NaN   \n",
+       "17           2021-04-30 00:00:00  NaN  NaN                            NaN   \n",
+       "18           2021-05-07 00:00:00  NaN  NaN                            NaN   \n",
+       "19           2021-05-14 00:00:00  NaN  NaN                            NaN   \n",
+       "20           2021-05-21 00:00:00  NaN  NaN                            NaN   \n",
+       "21           2021-05-28 00:00:00  NaN  NaN                            NaN   \n",
+       "22           2021-06-04 00:00:00  NaN  NaN                            NaN   \n",
+       "23           2021-06-11 00:00:00  NaN  NaN                            NaN   \n",
+       "24           2021-06-18 00:00:00  NaN  NaN                            NaN   \n",
+       "25           2021-06-25 00:00:00  NaN  NaN                            NaN   \n",
+       "26           2021-07-02 00:00:00  NaN  NaN                            NaN   \n",
+       "27           2021-07-09 00:00:00  NaN  NaN                            NaN   \n",
+       "28           2021-07-16 00:00:00  NaN  NaN                            NaN   \n",
+       "29           2021-07-23 00:00:00  NaN  NaN                            NaN   \n",
+       "30           2021-07-30 00:00:00  NaN  NaN                            NaN   \n",
+       "31           2021-08-06 00:00:00  NaN  NaN                            NaN   \n",
+       "32           2021-08-13 00:00:00  NaN  NaN                            NaN   \n",
+       "33           2021-08-20 00:00:00  NaN  NaN                            NaN   \n",
+       "34           2021-08-27 00:00:00  NaN  NaN                            NaN   \n",
+       "35           2021-09-03 00:00:00  NaN  NaN                            NaN   \n",
+       "36           2021-09-10 00:00:00  NaN  NaN                            NaN   \n",
+       "37           2021-09-17 00:00:00  NaN  NaN                            NaN   \n",
+       "38           2021-09-24 00:00:00  NaN  NaN                            NaN   \n",
+       "39           2021-10-01 00:00:00  NaN  NaN                            NaN   \n",
+       "40           2021-10-08 00:00:00  NaN  NaN                            NaN   \n",
+       "41           2021-10-15 00:00:00  NaN  NaN                            NaN   \n",
+       "42           2021-10-22 00:00:00  NaN  NaN                            NaN   \n",
+       "43           2021-10-29 00:00:00  NaN  NaN                            NaN   \n",
+       "44           2021-11-05 00:00:00  NaN  NaN                            NaN   \n",
+       "45           2021-11-12 00:00:00  NaN  NaN                            NaN   \n",
+       "46           2021-11-19 00:00:00  NaN  NaN                            NaN   \n",
+       "47           2021-11-26 00:00:00  NaN  NaN                            NaN   \n",
+       "48           2021-12-03 00:00:00  NaN  NaN                            NaN   \n",
+       "49           2021-12-10 00:00:00  NaN  NaN                            NaN   \n",
+       "50           2021-12-17 00:00:00  NaN  NaN                            NaN   \n",
+       "51           2021-12-24 00:00:00  NaN  NaN                            NaN   \n",
+       "52           2021-12-31 00:00:00  NaN  NaN                            NaN   \n",
+       "53 7                        2020  NaN  NaN                              :   \n",
+       "\n",
+       "             NaN  Total deaths, all ages (2020)  \\\n",
+       "Week number  NaN  Total deaths, all ages (2020)   \n",
+       "1            NaN                          12254   \n",
+       "2            NaN                          14058   \n",
+       "3            NaN                          12990   \n",
+       "4            NaN                          11856   \n",
+       "5            NaN                          11612   \n",
+       "6            NaN                          10986   \n",
+       "7            NaN                          10944   \n",
+       "8            NaN                          10841   \n",
+       "9            NaN                          10816   \n",
+       "10           NaN                          10895   \n",
+       "11           NaN                          11019   \n",
+       "12           NaN                          10645   \n",
+       "13           NaN                          11141   \n",
+       "14           NaN                          16387   \n",
+       "15           NaN                          18516   \n",
+       "16           NaN                          22351   \n",
+       "17           NaN                          21997   \n",
+       "18           NaN                          17953   \n",
+       "19           NaN                          12657   \n",
+       "20           NaN                          14573   \n",
+       "21           NaN                          12288   \n",
+       "22           NaN                           9824   \n",
+       "23           NaN                          10709   \n",
+       "24           NaN                           9976   \n",
+       "25           NaN                           9339   \n",
+       "26           NaN                           8979   \n",
+       "27           NaN                           9140   \n",
+       "28           NaN                           8690   \n",
+       "29           NaN                           8823   \n",
+       "30           NaN                           8891   \n",
+       "31           NaN                           8946   \n",
+       "32           NaN                           8945   \n",
+       "33           NaN                           9392   \n",
+       "34           NaN                           9631   \n",
+       "35           NaN                           9032   \n",
+       "36           NaN                           7739   \n",
+       "37           NaN                           9811   \n",
+       "38           NaN                           9523   \n",
+       "39           NaN                           9634   \n",
+       "40           NaN                           9945   \n",
+       "41           NaN                           9954   \n",
+       "42           NaN                          10534   \n",
+       "43           NaN                          10739   \n",
+       "44           NaN                          10887   \n",
+       "45           NaN                          11812   \n",
+       "46           NaN                          12254   \n",
+       "47           NaN                          12535   \n",
+       "48           NaN                          12456   \n",
+       "49           NaN                          12303   \n",
+       "50           NaN                          12292   \n",
+       "51           NaN                          13011   \n",
+       "52           NaN                          11520   \n",
+       "53 7         NaN                          10069   \n",
+       "\n",
+       "            Total deaths: average of corresponding week in 2015-2019 (England and Wales) 1  \\\n",
+       "Week number  Total deaths: average of corresponding week in...                               \n",
+       "1                                                        12175                               \n",
+       "2                                                        13822                               \n",
+       "3                                                        13216                               \n",
+       "4                                                        12760                               \n",
+       "5                                                        12206                               \n",
+       "6                                                        11925                               \n",
+       "7                                                        11627                               \n",
+       "8                                                        11548                               \n",
+       "9                                                        11183                               \n",
+       "10                                                       11498                               \n",
+       "11                                                       11205                               \n",
+       "12                                                       10573                               \n",
+       "13                                                       10130                               \n",
+       "14                                                       10305                               \n",
+       "15                                                       10520                               \n",
+       "16                                                       10497                               \n",
+       "17                                                       10458                               \n",
+       "18                                                        9941                               \n",
+       "19                                                        9576                               \n",
+       "20                                                       10188                               \n",
+       "21                                                        9940                               \n",
+       "22                                                        8171                               \n",
+       "23                                                        9977                               \n",
+       "24                                                        9417                               \n",
+       "25                                                        9404                               \n",
+       "26                                                        9293                               \n",
+       "27                                                        9183                               \n",
+       "28                                                        9250                               \n",
+       "29                                                        9093                               \n",
+       "30                                                        9052                               \n",
+       "31                                                        9036                               \n",
+       "32                                                        9102                               \n",
+       "33                                                        9085                               \n",
+       "34                                                        9157                               \n",
+       "35                                                        8241                               \n",
+       "36                                                        9182                               \n",
+       "37                                                        9306                               \n",
+       "38                                                        9264                               \n",
+       "39                                                        9377                               \n",
+       "40                                                        9555                               \n",
+       "41                                                        9811                               \n",
+       "42                                                        9865                               \n",
+       "43                                                        9759                               \n",
+       "44                                                        9891                               \n",
+       "45                                                       10331                               \n",
+       "46                                                       10350                               \n",
+       "47                                                       10380                               \n",
+       "48                                                       10357                               \n",
+       "49                                                       10695                               \n",
+       "50                                                       10750                               \n",
+       "51                                                       11548                               \n",
+       "52                                                        7954                               \n",
+       "53 7                                                         :                               \n",
+       "\n",
+       "            Total deaths: average of corresponding week in 2015-2019 (England) 1  \\\n",
+       "Week number  Total deaths: average of corresponding week in...                     \n",
+       "1                                                        11412                     \n",
+       "2                                                        12933                     \n",
+       "3                                                        12370                     \n",
+       "4                                                        11933                     \n",
+       "5                                                        11419                     \n",
+       "6                                                        11154                     \n",
+       "7                                                        10876                     \n",
+       "8                                                        10790                     \n",
+       "9                                                        10448                     \n",
+       "10                                                       10745                     \n",
+       "11                                                       10447                     \n",
+       "12                                                        9841                     \n",
+       "13                                                        9414                     \n",
+       "14                                                        9601                     \n",
+       "15                                                        9807                     \n",
+       "16                                                        9787                     \n",
+       "17                                                        9768                     \n",
+       "18                                                        9289                     \n",
+       "19                                                        8937                     \n",
+       "20                                                        9526                     \n",
+       "21                                                        9299                     \n",
+       "22                                                        7607                     \n",
+       "23                                                        9346                     \n",
+       "24                                                        8803                     \n",
+       "25                                                        8810                     \n",
+       "26                                                        8695                     \n",
+       "27                                                        8606                     \n",
+       "28                                                        8648                     \n",
+       "29                                                        8502                     \n",
+       "30                                                        8452                     \n",
+       "31                                                        8436                     \n",
+       "32                                                        8502                     \n",
+       "33                                                        8494                     \n",
+       "34                                                        8560                     \n",
+       "35                                                        7674                     \n",
+       "36                                                        8604                     \n",
+       "37                                                        8708                     \n",
+       "38                                                        8663                     \n",
+       "39                                                        8744                     \n",
+       "40                                                        8942                     \n",
+       "41                                                        9168                     \n",
+       "42                                                        9215                     \n",
+       "43                                                        9104                     \n",
+       "44                                                        9248                     \n",
+       "45                                                        9675                     \n",
+       "46                                                        9662                     \n",
+       "47                                                        9701                     \n",
+       "48                                                        9690                     \n",
+       "49                                                        9995                     \n",
+       "50                                                       10034                     \n",
+       "51                                                       10804                     \n",
+       "52                                                        7421                     \n",
+       "53 7                                                         :                     \n",
+       "\n",
+       "            Total deaths: average of corresponding week in 2015-2019 (Wales) 1  \\\n",
+       "Week number  Total deaths: average of corresponding week in...                   \n",
+       "1                                                          756                   \n",
+       "2                                                          856                   \n",
+       "3                                                          812                   \n",
+       "4                                                          802                   \n",
+       "5                                                          760                   \n",
+       "6                                                          729                   \n",
+       "7                                                          722                   \n",
+       "8                                                          724                   \n",
+       "9                                                          698                   \n",
+       "10                                                         720                   \n",
+       "11                                                         727                   \n",
+       "12                                                         677                   \n",
+       "13                                                         665                   \n",
+       "14                                                         667                   \n",
+       "15                                                         671                   \n",
+       "16                                                         661                   \n",
+       "17                                                         662                   \n",
+       "18                                                         624                   \n",
+       "19                                                         612                   \n",
+       "20                                                         635                   \n",
+       "21                                                         614                   \n",
+       "22                                                         546                   \n",
+       "23                                                         610                   \n",
+       "24                                                         588                   \n",
+       "25                                                         573                   \n",
+       "26                                                         571                   \n",
+       "27                                                         555                   \n",
+       "28                                                         578                   \n",
+       "29                                                         557                   \n",
+       "30                                                         566                   \n",
+       "31                                                         572                   \n",
+       "32                                                         571                   \n",
+       "33                                                         564                   \n",
+       "34                                                         573                   \n",
+       "35                                                         539                   \n",
+       "36                                                         552                   \n",
+       "37                                                         577                   \n",
+       "38                                                         575                   \n",
+       "39                                                         604                   \n",
+       "40                                                         587                   \n",
+       "41                                                         615                   \n",
+       "42                                                         630                   \n",
+       "43                                                         628                   \n",
+       "44                                                         616                   \n",
+       "45                                                         625                   \n",
+       "46                                                         658                   \n",
+       "47                                                         653                   \n",
+       "48                                                         646                   \n",
+       "49                                                         679                   \n",
+       "50                                                         693                   \n",
+       "51                                                         718                   \n",
+       "52                                                         518                   \n",
+       "53 7                                                         :                   \n",
+       "\n",
+       "             NaN  ... North East North West Yorkshire and The Humber  \\\n",
+       "Week number  NaN  ...  E12000001  E12000002                E12000003   \n",
+       "1            NaN  ...        858       2090                     1640   \n",
+       "2            NaN  ...        797       2112                     1408   \n",
+       "3            NaN  ...        836       2202                     1426   \n",
+       "4            NaN  ...        752       2191                     1485   \n",
+       "5            NaN  ...        NaN        NaN                      NaN   \n",
+       "6            NaN  ...        NaN        NaN                      NaN   \n",
+       "7            NaN  ...        NaN        NaN                      NaN   \n",
+       "8            NaN  ...        NaN        NaN                      NaN   \n",
+       "9            NaN  ...        NaN        NaN                      NaN   \n",
+       "10           NaN  ...        NaN        NaN                      NaN   \n",
+       "11           NaN  ...        NaN        NaN                      NaN   \n",
+       "12           NaN  ...        NaN        NaN                      NaN   \n",
+       "13           NaN  ...        NaN        NaN                      NaN   \n",
+       "14           NaN  ...        NaN        NaN                      NaN   \n",
+       "15           NaN  ...        NaN        NaN                      NaN   \n",
+       "16           NaN  ...        NaN        NaN                      NaN   \n",
+       "17           NaN  ...        NaN        NaN                      NaN   \n",
+       "18           NaN  ...        NaN        NaN                      NaN   \n",
+       "19           NaN  ...        NaN        NaN                      NaN   \n",
+       "20           NaN  ...        NaN        NaN                      NaN   \n",
+       "21           NaN  ...        NaN        NaN                      NaN   \n",
+       "22           NaN  ...        NaN        NaN                      NaN   \n",
+       "23           NaN  ...        NaN        NaN                      NaN   \n",
+       "24           NaN  ...        NaN        NaN                      NaN   \n",
+       "25           NaN  ...        NaN        NaN                      NaN   \n",
+       "26           NaN  ...        NaN        NaN                      NaN   \n",
+       "27           NaN  ...        NaN        NaN                      NaN   \n",
+       "28           NaN  ...        NaN        NaN                      NaN   \n",
+       "29           NaN  ...        NaN        NaN                      NaN   \n",
+       "30           NaN  ...        NaN        NaN                      NaN   \n",
+       "31           NaN  ...        NaN        NaN                      NaN   \n",
+       "32           NaN  ...        NaN        NaN                      NaN   \n",
+       "33           NaN  ...        NaN        NaN                      NaN   \n",
+       "34           NaN  ...        NaN        NaN                      NaN   \n",
+       "35           NaN  ...        NaN        NaN                      NaN   \n",
+       "36           NaN  ...        NaN        NaN                      NaN   \n",
+       "37           NaN  ...        NaN        NaN                      NaN   \n",
+       "38           NaN  ...        NaN        NaN                      NaN   \n",
+       "39           NaN  ...        NaN        NaN                      NaN   \n",
+       "40           NaN  ...        NaN        NaN                      NaN   \n",
+       "41           NaN  ...        NaN        NaN                      NaN   \n",
+       "42           NaN  ...        NaN        NaN                      NaN   \n",
+       "43           NaN  ...        NaN        NaN                      NaN   \n",
+       "44           NaN  ...        NaN        NaN                      NaN   \n",
+       "45           NaN  ...        NaN        NaN                      NaN   \n",
+       "46           NaN  ...        NaN        NaN                      NaN   \n",
+       "47           NaN  ...        NaN        NaN                      NaN   \n",
+       "48           NaN  ...        NaN        NaN                      NaN   \n",
+       "49           NaN  ...        NaN        NaN                      NaN   \n",
+       "50           NaN  ...        NaN        NaN                      NaN   \n",
+       "51           NaN  ...        NaN        NaN                      NaN   \n",
+       "52           NaN  ...        NaN        NaN                      NaN   \n",
+       "53 7         NaN  ...        NaN        NaN                      NaN   \n",
+       "\n",
+       "            East Midlands West Midlands       East     London South East  \\\n",
+       "Week number     E12000004     E12000005  E12000006  E12000007  E12000008   \n",
+       "1                    1414          1785       2082       2138       2950   \n",
+       "2                    1402          1820       2240       2346       3127   \n",
+       "3                    1496          1925       2267       2417       3328   \n",
+       "4                    1403          1926       2350       2302       3271   \n",
+       "5                     NaN           NaN        NaN        NaN        NaN   \n",
+       "6                     NaN           NaN        NaN        NaN        NaN   \n",
+       "7                     NaN           NaN        NaN        NaN        NaN   \n",
+       "8                     NaN           NaN        NaN        NaN        NaN   \n",
+       "9                     NaN           NaN        NaN        NaN        NaN   \n",
+       "10                    NaN           NaN        NaN        NaN        NaN   \n",
+       "11                    NaN           NaN        NaN        NaN        NaN   \n",
+       "12                    NaN           NaN        NaN        NaN        NaN   \n",
+       "13                    NaN           NaN        NaN        NaN        NaN   \n",
+       "14                    NaN           NaN        NaN        NaN        NaN   \n",
+       "15                    NaN           NaN        NaN        NaN        NaN   \n",
+       "16                    NaN           NaN        NaN        NaN        NaN   \n",
+       "17                    NaN           NaN        NaN        NaN        NaN   \n",
+       "18                    NaN           NaN        NaN        NaN        NaN   \n",
+       "19                    NaN           NaN        NaN        NaN        NaN   \n",
+       "20                    NaN           NaN        NaN        NaN        NaN   \n",
+       "21                    NaN           NaN        NaN        NaN        NaN   \n",
+       "22                    NaN           NaN        NaN        NaN        NaN   \n",
+       "23                    NaN           NaN        NaN        NaN        NaN   \n",
+       "24                    NaN           NaN        NaN        NaN        NaN   \n",
+       "25                    NaN           NaN        NaN        NaN        NaN   \n",
+       "26                    NaN           NaN        NaN        NaN        NaN   \n",
+       "27                    NaN           NaN        NaN        NaN        NaN   \n",
+       "28                    NaN           NaN        NaN        NaN        NaN   \n",
+       "29                    NaN           NaN        NaN        NaN        NaN   \n",
+       "30                    NaN           NaN        NaN        NaN        NaN   \n",
+       "31                    NaN           NaN        NaN        NaN        NaN   \n",
+       "32                    NaN           NaN        NaN        NaN        NaN   \n",
+       "33                    NaN           NaN        NaN        NaN        NaN   \n",
+       "34                    NaN           NaN        NaN        NaN        NaN   \n",
+       "35                    NaN           NaN        NaN        NaN        NaN   \n",
+       "36                    NaN           NaN        NaN        NaN        NaN   \n",
+       "37                    NaN           NaN        NaN        NaN        NaN   \n",
+       "38                    NaN           NaN        NaN        NaN        NaN   \n",
+       "39                    NaN           NaN        NaN        NaN        NaN   \n",
+       "40                    NaN           NaN        NaN        NaN        NaN   \n",
+       "41                    NaN           NaN        NaN        NaN        NaN   \n",
+       "42                    NaN           NaN        NaN        NaN        NaN   \n",
+       "43                    NaN           NaN        NaN        NaN        NaN   \n",
+       "44                    NaN           NaN        NaN        NaN        NaN   \n",
+       "45                    NaN           NaN        NaN        NaN        NaN   \n",
+       "46                    NaN           NaN        NaN        NaN        NaN   \n",
+       "47                    NaN           NaN        NaN        NaN        NaN   \n",
+       "48                    NaN           NaN        NaN        NaN        NaN   \n",
+       "49                    NaN           NaN        NaN        NaN        NaN   \n",
+       "50                    NaN           NaN        NaN        NaN        NaN   \n",
+       "51                    NaN           NaN        NaN        NaN        NaN   \n",
+       "52                    NaN           NaN        NaN        NaN        NaN   \n",
+       "53 7                  NaN           NaN        NaN        NaN        NaN   \n",
+       "\n",
+       "            South West      Wales  \n",
+       "Week number  E12000009  W92000004  \n",
+       "1                 1570       1198  \n",
+       "2                 1593       1170  \n",
+       "3                 1670       1077  \n",
+       "4                 1775        974  \n",
+       "5                  NaN        NaN  \n",
+       "6                  NaN        NaN  \n",
+       "7                  NaN        NaN  \n",
+       "8                  NaN        NaN  \n",
+       "9                  NaN        NaN  \n",
+       "10                 NaN        NaN  \n",
+       "11                 NaN        NaN  \n",
+       "12                 NaN        NaN  \n",
+       "13                 NaN        NaN  \n",
+       "14                 NaN        NaN  \n",
+       "15                 NaN        NaN  \n",
+       "16                 NaN        NaN  \n",
+       "17                 NaN        NaN  \n",
+       "18                 NaN        NaN  \n",
+       "19                 NaN        NaN  \n",
+       "20                 NaN        NaN  \n",
+       "21                 NaN        NaN  \n",
+       "22                 NaN        NaN  \n",
+       "23                 NaN        NaN  \n",
+       "24                 NaN        NaN  \n",
+       "25                 NaN        NaN  \n",
+       "26                 NaN        NaN  \n",
+       "27                 NaN        NaN  \n",
+       "28                 NaN        NaN  \n",
+       "29                 NaN        NaN  \n",
+       "30                 NaN        NaN  \n",
+       "31                 NaN        NaN  \n",
+       "32                 NaN        NaN  \n",
+       "33                 NaN        NaN  \n",
+       "34                 NaN        NaN  \n",
+       "35                 NaN        NaN  \n",
+       "36                 NaN        NaN  \n",
+       "37                 NaN        NaN  \n",
+       "38                 NaN        NaN  \n",
+       "39                 NaN        NaN  \n",
+       "40                 NaN        NaN  \n",
+       "41                 NaN        NaN  \n",
+       "42                 NaN        NaN  \n",
+       "43                 NaN        NaN  \n",
+       "44                 NaN        NaN  \n",
+       "45                 NaN        NaN  \n",
+       "46                 NaN        NaN  \n",
+       "47                 NaN        NaN  \n",
+       "48                 NaN        NaN  \n",
+       "49                 NaN        NaN  \n",
+       "50                 NaN        NaN  \n",
+       "51                 NaN        NaN  \n",
+       "52                 NaN        NaN  \n",
+       "53 7               NaN        NaN  \n",
+       "\n",
+       "[54 rows x 87 columns]"
+      ]
+     },
+     "execution_count": 64,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "eng_xls"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2021-01-08 00:00:00</td>\n",
+       "      <td>1198</td>\n",
+       "      <td>2021</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2021-01-15 00:00:00</td>\n",
+       "      <td>1170</td>\n",
+       "      <td>2021</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2021-01-22 00:00:00</td>\n",
+       "      <td>1077</td>\n",
+       "      <td>2021</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2021-01-29 00:00:00</td>\n",
+       "      <td>974</td>\n",
+       "      <td>2021</td>\n",
+       "      <td>Wales</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  week           date_up_to deaths  year nation\n",
+       "0    1  2021-01-08 00:00:00   1198  2021  Wales\n",
+       "1    2  2021-01-15 00:00:00   1170  2021  Wales\n",
+       "2    3  2021-01-22 00:00:00   1077  2021  Wales\n",
+       "3    4  2021-01-29 00:00:00    974  2021  Wales"
+      ]
+     },
+     "execution_count": 65,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = eng_xls.iloc[1:][['Week ended', 'Wales']].reset_index(level=0).rename(\n",
+    "    columns={'Week ended': 'date_up_to', 'Wales': 'deaths',\n",
+    "            'index': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2021\n",
+    "rd['nation'] = 'Wales'\n",
+    "rd.dropna(inplace=True)\n",
+    "rd.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "query_string = '''\n",
+    "delete from all_causes_deaths\n",
+    "where nation = 'Wales'\n",
+    "  and year = 2021;\n",
+    "'''\n",
+    "with engine.connect() as connection:\n",
+    "    connection.execute(query_string)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    engine,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "10 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>week</th>\n",
+       "            <th>year</th>\n",
+       "            <th>date_up_to</th>\n",
+       "            <th>nation</th>\n",
+       "            <th>deaths</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>1</td>\n",
+       "            <td>2021</td>\n",
+       "            <td>2021-01-08</td>\n",
+       "            <td>England</td>\n",
+       "            <td>16553</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>1</td>\n",
+       "            <td>2021</td>\n",
+       "            <td>2021-01-08</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>568</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>1</td>\n",
+       "            <td>2021</td>\n",
+       "            <td>2021-01-04</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>1720</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>1</td>\n",
+       "            <td>2021</td>\n",
+       "            <td>2021-01-08</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>1198</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2</td>\n",
+       "            <td>2021</td>\n",
+       "            <td>2021-01-15</td>\n",
+       "            <td>England</td>\n",
+       "            <td>16872</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2</td>\n",
+       "            <td>2021</td>\n",
+       "            <td>2021-01-15</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>443</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2</td>\n",
+       "            <td>2021</td>\n",
+       "            <td>2021-01-11</td>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>1550</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>2</td>\n",
+       "            <td>2021</td>\n",
+       "            <td>2021-01-15</td>\n",
+       "            <td>Wales</td>\n",
+       "            <td>1170</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>3</td>\n",
+       "            <td>2021</td>\n",
+       "            <td>2021-01-22</td>\n",
+       "            <td>England</td>\n",
+       "            <td>17599</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>3</td>\n",
+       "            <td>2021</td>\n",
+       "            <td>2021-01-22</td>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>474</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[(1, 2021, datetime.date(2021, 1, 8), 'England', 16553),\n",
+       " (1, 2021, datetime.date(2021, 1, 8), 'Northern Ireland', 568),\n",
+       " (1, 2021, datetime.date(2021, 1, 4), 'Scotland', 1720),\n",
+       " (1, 2021, datetime.date(2021, 1, 8), 'Wales', 1198),\n",
+       " (2, 2021, datetime.date(2021, 1, 15), 'England', 16872),\n",
+       " (2, 2021, datetime.date(2021, 1, 15), 'Northern Ireland', 443),\n",
+       " (2, 2021, datetime.date(2021, 1, 11), 'Scotland', 1550),\n",
+       " (2, 2021, datetime.date(2021, 1, 15), 'Wales', 1170),\n",
+       " (3, 2021, datetime.date(2021, 1, 22), 'England', 17599),\n",
+       " (3, 2021, datetime.date(2021, 1, 22), 'Northern Ireland', 474)]"
+      ]
+     },
+     "execution_count": 68,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select * from all_causes_deaths where year = 2021 limit 10"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "      <th>deaths</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2021-01-08 00:00:00</td>\n",
+       "      <td>2021</td>\n",
+       "      <td>England</td>\n",
+       "      <td>16553</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2021-01-15 00:00:00</td>\n",
+       "      <td>2021</td>\n",
+       "      <td>England</td>\n",
+       "      <td>16872</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2021-01-22 00:00:00</td>\n",
+       "      <td>2021</td>\n",
+       "      <td>England</td>\n",
+       "      <td>17599</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2021-01-29 00:00:00</td>\n",
+       "      <td>2021</td>\n",
+       "      <td>England</td>\n",
+       "      <td>17474</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  week           date_up_to  year   nation deaths\n",
+       "0    1  2021-01-08 00:00:00  2021  England  16553\n",
+       "1    2  2021-01-15 00:00:00  2021  England  16872\n",
+       "2    3  2021-01-22 00:00:00  2021  England  17599\n",
+       "3    4  2021-01-29 00:00:00  2021  England  17474"
+      ]
+     },
+     "execution_count": 69,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rd = eng_xls.iloc[1:][['Week ended', 'Total deaths, all ages (2021)', 'Wales']].reset_index(level=0).rename(\n",
+    "    columns={'Week ended': 'date_up_to', \n",
+    "             'Total deaths, all ages (2021)': 'ew_deaths',\n",
+    "             'Wales': 'w_deaths',\n",
+    "            'index': 'week'}\n",
+    "    )\n",
+    "rd['year'] = 2021\n",
+    "rd['nation'] = 'England'\n",
+    "rd['deaths'] = rd['ew_deaths'] - rd['w_deaths']\n",
+    "rd.drop(labels=['ew_deaths', 'w_deaths'], axis='columns', inplace=True)\n",
+    "rd.dropna(inplace=True)\n",
+    "rd.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "query_string = '''\n",
+    "delete from all_causes_deaths\n",
+    "where nation = 'England'\n",
+    "  and year = 2021;\n",
+    "'''\n",
+    "with engine.connect() as connection:\n",
+    "    connection.execute(query_string)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    engine,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "4 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>nation</th>\n",
+       "            <th>sum</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>England</td>\n",
+       "            <td>68498</td>\n",
+       "            <td>4</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>1922</td>\n",
+       "            <td>4</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>7928</td>\n",
+       "            <td>5</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>Wales</td>\n",
+       "            <td>4419</td>\n",
+       "            <td>4</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[('England', 68498, 4),\n",
+       " ('Northern Ireland', 1922, 4),\n",
+       " ('Scotland', 7928, 5),\n",
+       " ('Wales', 4419, 4)]"
+      ]
+     },
+     "execution_count": 72,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select nation, sum(deaths), count(*) from all_causes_deaths where year = 2021 group by nation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2021-01-08</td>\n",
+       "      <td>568.0</td>\n",
+       "      <td>2021</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2021-01-15</td>\n",
+       "      <td>443.0</td>\n",
+       "      <td>2021</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2021-01-22</td>\n",
+       "      <td>474.0</td>\n",
+       "      <td>2021</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2021-01-29</td>\n",
+       "      <td>437.0</td>\n",
+       "      <td>2021</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2021-02-05</td>\n",
+       "      <td>462.0</td>\n",
+       "      <td>2021</td>\n",
+       "      <td>Northern Ireland</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  week date_up_to  deaths  year            nation\n",
+       "0    1 2021-01-08   568.0  2021  Northern Ireland\n",
+       "1    2 2021-01-15   443.0  2021  Northern Ireland\n",
+       "2    3 2021-01-22   474.0  2021  Northern Ireland\n",
+       "3    4 2021-01-29   437.0  2021  Northern Ireland\n",
+       "4    5 2021-02-05   462.0  2021  Northern Ireland"
+      ]
+     },
+     "execution_count": 73,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ni_xls = pd.read_excel(n_ireland_filename, \n",
+    "                        sheet_name='Table 1',\n",
+    "                        skiprows=[0, 1, 2, 3],\n",
+    "                        header=0,\n",
+    "                      ).rename(\n",
+    "    columns={'Week Ending (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2021P)': 'deaths',\n",
+    "            'Registration Week': 'week'})\n",
+    "rd = ni_xls[ni_xls['deaths'].notna()][['week', 'date_up_to', 'deaths']]\n",
+    "rd['year'] = 2021\n",
+    "rd['nation'] = 'Northern Ireland'\n",
+    "rd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "query_string = '''\n",
+    "delete from all_causes_deaths\n",
+    "where nation = 'Northern Ireland'\n",
+    "  and year = 2021;\n",
+    "'''\n",
+    "with engine.connect() as connection:\n",
+    "    connection.execute(query_string)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    engine,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "4 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>nation</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>England</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>Wales</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>Scotland</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>Northern Ireland</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[('England',), ('Wales',), ('Scotland',), ('Northern Ireland',)]"
+      ]
+     },
+     "execution_count": 76,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select nation from all_causes_deaths group by nation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# sco_xls = pd.read_excel(scotland_filename, \n",
+    "#                         sheet_name=\"2.2_excess\",\n",
+    "#                         skiprows=[0, 1, 2, 3],\n",
+    "#                         skipfooter=3,\n",
+    "#                         header=0,\n",
+    "#                         index_col=[1]\n",
+    "#                        ).iloc[:91].T"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import openpyxl"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<openpyxl.worksheet._read_only.ReadOnlyWorksheet at 0x7f872dd50cd0>"
+      ]
+     },
+     "execution_count": 79,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "wb = openpyxl.load_workbook(scotland_filename, read_only=True)#, data_only=True, keep_links=False)\n",
+    "sheet = wb.worksheets[7]\n",
+    "sheet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sheet.reset_dimensions()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>date_up_to</th>\n",
+       "      <th>deaths</th>\n",
+       "      <th>year</th>\n",
+       "      <th>nation</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2021-01-04</td>\n",
+       "      <td>1720.0</td>\n",
+       "      <td>2021</td>\n",
+       "      <td>Scotland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>54</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2021-01-11</td>\n",
+       "      <td>1550.0</td>\n",
+       "      <td>2021</td>\n",
+       "      <td>Scotland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>55</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2021-01-18</td>\n",
+       "      <td>1559.0</td>\n",
+       "      <td>2021</td>\n",
+       "      <td>Scotland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>56</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2021-01-25</td>\n",
+       "      <td>1604.0</td>\n",
+       "      <td>2021</td>\n",
+       "      <td>Scotland</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2021-02-01</td>\n",
+       "      <td>1495.0</td>\n",
+       "      <td>2021</td>\n",
+       "      <td>Scotland</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   week date_up_to  deaths  year    nation\n",
+       "53    1 2021-01-04  1720.0  2021  Scotland\n",
+       "54    2 2021-01-11  1550.0  2021  Scotland\n",
+       "55    3 2021-01-18  1559.0  2021  Scotland\n",
+       "56    4 2021-01-25  1604.0  2021  Scotland\n",
+       "57    5 2021-02-01  1495.0  2021  Scotland"
+      ]
+     },
+     "execution_count": 81,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "scot_elems = [[value for value in row] for row in sheet.values]\n",
+    "scot_cols = scot_elems[3]\n",
+    "scot_dicts = [{k: v for k, v in zip(scot_cols, row)} for row in scot_elems[4:]]\n",
+    "scot_data = pd.DataFrame(scot_dicts)\n",
+    "rd = scot_data[scot_data.date >= '2021'].rename(\n",
+    "    columns={'week_number': 'week', 'date': 'date_up_to', 'total_deaths': 'deaths'})[['week', 'date_up_to', 'deaths']]\n",
+    "rd['year'] = 2021\n",
+    "rd['nation'] = 'Scotland'\n",
+    "rd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "query_string = '''\n",
+    "delete from all_causes_deaths\n",
+    "where nation = 'Scotland'\n",
+    "  and year = 2021;\n",
+    "'''\n",
+    "with engine.connect() as connection:\n",
+    "    connection.execute(query_string)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 83,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rd.to_sql(\n",
+    "    'all_causes_deaths',\n",
+    "    engine,\n",
+    "    if_exists='append',\n",
+    "    index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "4 rows affected.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <thead>\n",
+       "        <tr>\n",
+       "            <th>nation</th>\n",
+       "            <th>sum</th>\n",
+       "            <th>count</th>\n",
+       "        </tr>\n",
+       "    </thead>\n",
+       "    <tbody>\n",
+       "        <tr>\n",
+       "            <td>England</td>\n",
+       "            <td>68498</td>\n",
+       "            <td>4</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>Northern Ireland</td>\n",
+       "            <td>2384</td>\n",
+       "            <td>5</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>Scotland</td>\n",
+       "            <td>7928</td>\n",
+       "            <td>5</td>\n",
+       "        </tr>\n",
+       "        <tr>\n",
+       "            <td>Wales</td>\n",
+       "            <td>4419</td>\n",
+       "            <td>4</td>\n",
+       "        </tr>\n",
+       "    </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "[('England', 68498, 4),\n",
+       " ('Northern Ireland', 2384, 5),\n",
+       " ('Scotland', 7928, 5),\n",
+       " ('Wales', 4419, 4)]"
+      ]
+     },
+     "execution_count": 84,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%sql select nation, sum(deaths), count(*) from all_causes_deaths where year = 2021 group by nation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Create graphs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>year</th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>2017</th>\n",
+       "      <th>2018</th>\n",
+       "      <th>2019</th>\n",
+       "      <th>2020</th>\n",
+       "      <th>2021</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>week</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>11561.0</td>\n",
+       "      <td>12236.0</td>\n",
+       "      <td>11247.0</td>\n",
+       "      <td>11940.0</td>\n",
+       "      <td>10237.0</td>\n",
+       "      <td>11467.0</td>\n",
+       "      <td>16553.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>15206.0</td>\n",
+       "      <td>10790.0</td>\n",
+       "      <td>12890.0</td>\n",
+       "      <td>14146.0</td>\n",
+       "      <td>11800.0</td>\n",
+       "      <td>13119.0</td>\n",
+       "      <td>16872.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>13930.0</td>\n",
+       "      <td>10753.0</td>\n",
+       "      <td>12775.0</td>\n",
+       "      <td>13371.0</td>\n",
+       "      <td>11177.0</td>\n",
+       "      <td>12223.0</td>\n",
+       "      <td>17599.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>13106.0</td>\n",
+       "      <td>10600.0</td>\n",
+       "      <td>11996.0</td>\n",
+       "      <td>13085.0</td>\n",
+       "      <td>11006.0</td>\n",
+       "      <td>11133.0</td>\n",
+       "      <td>17474.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>12099.0</td>\n",
+       "      <td>10362.0</td>\n",
+       "      <td>11736.0</td>\n",
+       "      <td>12470.0</td>\n",
+       "      <td>10552.0</td>\n",
+       "      <td>10885.0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "year     2015     2016     2017     2018     2019     2020     2021\n",
+       "week                                                               \n",
+       "1     11561.0  12236.0  11247.0  11940.0  10237.0  11467.0  16553.0\n",
+       "2     15206.0  10790.0  12890.0  14146.0  11800.0  13119.0  16872.0\n",
+       "3     13930.0  10753.0  12775.0  13371.0  11177.0  12223.0  17599.0\n",
+       "4     13106.0  10600.0  11996.0  13085.0  11006.0  11133.0  17474.0\n",
+       "5     12099.0  10362.0  11736.0  12470.0  10552.0  10885.0      NaN"
+      ]
+     },
+     "execution_count": 85,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "qstr = '''select week, year, deaths\n",
+    "from all_causes_deaths\n",
+    "where nation = 'England' '''\n",
+    "deaths_e = pd.read_sql_query(qstr, engine).pivot(index='week', columns='year', values='deaths')\n",
+    "deaths_e.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>year</th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>2017</th>\n",
+       "      <th>2018</th>\n",
+       "      <th>2019</th>\n",
+       "      <th>2020</th>\n",
+       "      <th>2021</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>week</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>725.0</td>\n",
+       "      <td>809.0</td>\n",
+       "      <td>744.0</td>\n",
+       "      <td>783.0</td>\n",
+       "      <td>718.0</td>\n",
+       "      <td>787.0</td>\n",
+       "      <td>1198.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1031.0</td>\n",
+       "      <td>711.0</td>\n",
+       "      <td>825.0</td>\n",
+       "      <td>904.0</td>\n",
+       "      <td>809.0</td>\n",
+       "      <td>939.0</td>\n",
+       "      <td>1170.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>936.0</td>\n",
+       "      <td>720.0</td>\n",
+       "      <td>835.0</td>\n",
+       "      <td>885.0</td>\n",
+       "      <td>683.0</td>\n",
+       "      <td>767.0</td>\n",
+       "      <td>1077.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>828.0</td>\n",
+       "      <td>717.0</td>\n",
+       "      <td>881.0</td>\n",
+       "      <td>850.0</td>\n",
+       "      <td>734.0</td>\n",
+       "      <td>723.0</td>\n",
+       "      <td>974.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>801.0</td>\n",
+       "      <td>690.0</td>\n",
+       "      <td>749.0</td>\n",
+       "      <td>815.0</td>\n",
+       "      <td>745.0</td>\n",
+       "      <td>727.0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "year    2015   2016   2017   2018   2019   2020    2021\n",
+       "week                                                   \n",
+       "1      725.0  809.0  744.0  783.0  718.0  787.0  1198.0\n",
+       "2     1031.0  711.0  825.0  904.0  809.0  939.0  1170.0\n",
+       "3      936.0  720.0  835.0  885.0  683.0  767.0  1077.0\n",
+       "4      828.0  717.0  881.0  850.0  734.0  723.0   974.0\n",
+       "5      801.0  690.0  749.0  815.0  745.0  727.0     NaN"
+      ]
+     },
+     "execution_count": 86,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "qstr = '''select week, year, deaths\n",
+    "from all_causes_deaths\n",
+    "where nation = 'Wales' '''\n",
+    "deaths_w = pd.read_sql_query(qstr, engine).pivot(index='week', columns='year', values='deaths')\n",
+    "deaths_w.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>year</th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>2017</th>\n",
+       "      <th>2018</th>\n",
+       "      <th>2019</th>\n",
+       "      <th>2020</th>\n",
+       "      <th>2021</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>week</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1146.0</td>\n",
+       "      <td>1394.0</td>\n",
+       "      <td>1205.0</td>\n",
+       "      <td>1531.0</td>\n",
+       "      <td>1104.0</td>\n",
+       "      <td>1161.0</td>\n",
+       "      <td>1720.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1708.0</td>\n",
+       "      <td>1305.0</td>\n",
+       "      <td>1379.0</td>\n",
+       "      <td>1899.0</td>\n",
+       "      <td>1507.0</td>\n",
+       "      <td>1567.0</td>\n",
+       "      <td>1550.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1489.0</td>\n",
+       "      <td>1215.0</td>\n",
+       "      <td>1224.0</td>\n",
+       "      <td>1629.0</td>\n",
+       "      <td>1353.0</td>\n",
+       "      <td>1322.0</td>\n",
+       "      <td>1559.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1381.0</td>\n",
+       "      <td>1187.0</td>\n",
+       "      <td>1197.0</td>\n",
+       "      <td>1610.0</td>\n",
+       "      <td>1208.0</td>\n",
+       "      <td>1226.0</td>\n",
+       "      <td>1604.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>1286.0</td>\n",
+       "      <td>1205.0</td>\n",
+       "      <td>1332.0</td>\n",
+       "      <td>1369.0</td>\n",
+       "      <td>1206.0</td>\n",
+       "      <td>1188.0</td>\n",
+       "      <td>1495.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "year    2015    2016    2017    2018    2019    2020    2021\n",
+       "week                                                        \n",
+       "1     1146.0  1394.0  1205.0  1531.0  1104.0  1161.0  1720.0\n",
+       "2     1708.0  1305.0  1379.0  1899.0  1507.0  1567.0  1550.0\n",
+       "3     1489.0  1215.0  1224.0  1629.0  1353.0  1322.0  1559.0\n",
+       "4     1381.0  1187.0  1197.0  1610.0  1208.0  1226.0  1604.0\n",
+       "5     1286.0  1205.0  1332.0  1369.0  1206.0  1188.0  1495.0"
+      ]
+     },
+     "execution_count": 87,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "qstr = '''select week, year, deaths\n",
+    "from all_causes_deaths\n",
+    "where nation = 'Scotland' '''\n",
+    "deaths_s = pd.read_sql_query(qstr, engine).pivot(index='week', columns='year', values='deaths')\n",
+    "deaths_s.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>year</th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>2017</th>\n",
+       "      <th>2018</th>\n",
+       "      <th>2019</th>\n",
+       "      <th>2020</th>\n",
+       "      <th>2021</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>week</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>319.0</td>\n",
+       "      <td>424.0</td>\n",
+       "      <td>416.0</td>\n",
+       "      <td>447.0</td>\n",
+       "      <td>365.0</td>\n",
+       "      <td>353.0</td>\n",
+       "      <td>568.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>373.0</td>\n",
+       "      <td>348.0</td>\n",
+       "      <td>434.0</td>\n",
+       "      <td>481.0</td>\n",
+       "      <td>371.0</td>\n",
+       "      <td>395.0</td>\n",
+       "      <td>443.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>383.0</td>\n",
+       "      <td>372.0</td>\n",
+       "      <td>397.0</td>\n",
+       "      <td>470.0</td>\n",
+       "      <td>332.0</td>\n",
+       "      <td>411.0</td>\n",
+       "      <td>474.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>397.0</td>\n",
+       "      <td>355.0</td>\n",
+       "      <td>387.0</td>\n",
+       "      <td>426.0</td>\n",
+       "      <td>335.0</td>\n",
+       "      <td>347.0</td>\n",
+       "      <td>437.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>374.0</td>\n",
+       "      <td>314.0</td>\n",
+       "      <td>371.0</td>\n",
+       "      <td>433.0</td>\n",
+       "      <td>296.0</td>\n",
+       "      <td>323.0</td>\n",
+       "      <td>462.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "year   2015   2016   2017   2018   2019   2020   2021\n",
+       "week                                                 \n",
+       "1     319.0  424.0  416.0  447.0  365.0  353.0  568.0\n",
+       "2     373.0  348.0  434.0  481.0  371.0  395.0  443.0\n",
+       "3     383.0  372.0  397.0  470.0  332.0  411.0  474.0\n",
+       "4     397.0  355.0  387.0  426.0  335.0  347.0  437.0\n",
+       "5     374.0  314.0  371.0  433.0  296.0  323.0  462.0"
+      ]
+     },
+     "execution_count": 88,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "qstr = '''select week, year, deaths\n",
+    "from all_causes_deaths\n",
+    "where nation = 'Northern Ireland' '''\n",
+    "deaths_i = pd.read_sql_query(qstr, engine).pivot(index='week', columns='year', values='deaths')\n",
+    "deaths_i.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>2017</th>\n",
+       "      <th>2018</th>\n",
+       "      <th>2019</th>\n",
+       "      <th>2020</th>\n",
+       "      <th>2021</th>\n",
+       "      <th>prev_mean</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>week</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>11561.0</td>\n",
+       "      <td>12236.0</td>\n",
+       "      <td>11247.0</td>\n",
+       "      <td>11940.0</td>\n",
+       "      <td>10237.0</td>\n",
+       "      <td>11467.0</td>\n",
+       "      <td>16553.0</td>\n",
+       "      <td>11444.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>15206.0</td>\n",
+       "      <td>10790.0</td>\n",
+       "      <td>12890.0</td>\n",
+       "      <td>14146.0</td>\n",
+       "      <td>11800.0</td>\n",
+       "      <td>13119.0</td>\n",
+       "      <td>16872.0</td>\n",
+       "      <td>12966.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>13930.0</td>\n",
+       "      <td>10753.0</td>\n",
+       "      <td>12775.0</td>\n",
+       "      <td>13371.0</td>\n",
+       "      <td>11177.0</td>\n",
+       "      <td>12223.0</td>\n",
+       "      <td>17599.0</td>\n",
+       "      <td>12401.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>13106.0</td>\n",
+       "      <td>10600.0</td>\n",
+       "      <td>11996.0</td>\n",
+       "      <td>13085.0</td>\n",
+       "      <td>11006.0</td>\n",
+       "      <td>11133.0</td>\n",
+       "      <td>17474.0</td>\n",
+       "      <td>11958.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>12099.0</td>\n",
+       "      <td>10362.0</td>\n",
+       "      <td>11736.0</td>\n",
+       "      <td>12470.0</td>\n",
+       "      <td>10552.0</td>\n",
+       "      <td>10885.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11443.8</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         2015     2016     2017     2018     2019     2020     2021  prev_mean\n",
+       "week                                                                          \n",
+       "1     11561.0  12236.0  11247.0  11940.0  10237.0  11467.0  16553.0    11444.2\n",
+       "2     15206.0  10790.0  12890.0  14146.0  11800.0  13119.0  16872.0    12966.4\n",
+       "3     13930.0  10753.0  12775.0  13371.0  11177.0  12223.0  17599.0    12401.2\n",
+       "4     13106.0  10600.0  11996.0  13085.0  11006.0  11133.0  17474.0    11958.6\n",
+       "5     12099.0  10362.0  11736.0  12470.0  10552.0  10885.0      NaN    11443.8"
+      ]
+     },
+     "execution_count": 89,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "qstr = '''select week, avg(deaths) as prev_mean\n",
+    "from all_causes_deaths\n",
+    "where year <= 2019 and nation='England' \n",
+    "group by week\n",
+    "order by week'''\n",
+    "deaths_prev = pd.read_sql_query(qstr, engine, index_col='week')\n",
+    "deaths_prev.head()\n",
+    "deaths_e = deaths_e.merge(deaths_prev, on='week')\n",
+    "deaths_e.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 90,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>2017</th>\n",
+       "      <th>2018</th>\n",
+       "      <th>2019</th>\n",
+       "      <th>2020</th>\n",
+       "      <th>2021</th>\n",
+       "      <th>prev_mean</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>week</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>725.0</td>\n",
+       "      <td>809.0</td>\n",
+       "      <td>744.0</td>\n",
+       "      <td>783.0</td>\n",
+       "      <td>718.0</td>\n",
+       "      <td>787.0</td>\n",
+       "      <td>1198.0</td>\n",
+       "      <td>755.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1031.0</td>\n",
+       "      <td>711.0</td>\n",
+       "      <td>825.0</td>\n",
+       "      <td>904.0</td>\n",
+       "      <td>809.0</td>\n",
+       "      <td>939.0</td>\n",
+       "      <td>1170.0</td>\n",
+       "      <td>856.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>936.0</td>\n",
+       "      <td>720.0</td>\n",
+       "      <td>835.0</td>\n",
+       "      <td>885.0</td>\n",
+       "      <td>683.0</td>\n",
+       "      <td>767.0</td>\n",
+       "      <td>1077.0</td>\n",
+       "      <td>811.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>828.0</td>\n",
+       "      <td>717.0</td>\n",
+       "      <td>881.0</td>\n",
+       "      <td>850.0</td>\n",
+       "      <td>734.0</td>\n",
+       "      <td>723.0</td>\n",
+       "      <td>974.0</td>\n",
+       "      <td>802.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>801.0</td>\n",
+       "      <td>690.0</td>\n",
+       "      <td>749.0</td>\n",
+       "      <td>815.0</td>\n",
+       "      <td>745.0</td>\n",
+       "      <td>727.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>760.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        2015   2016   2017   2018   2019   2020    2021  prev_mean\n",
+       "week                                                              \n",
+       "1      725.0  809.0  744.0  783.0  718.0  787.0  1198.0      755.8\n",
+       "2     1031.0  711.0  825.0  904.0  809.0  939.0  1170.0      856.0\n",
+       "3      936.0  720.0  835.0  885.0  683.0  767.0  1077.0      811.8\n",
+       "4      828.0  717.0  881.0  850.0  734.0  723.0   974.0      802.0\n",
+       "5      801.0  690.0  749.0  815.0  745.0  727.0     NaN      760.0"
+      ]
+     },
+     "execution_count": 90,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "qstr = '''select week, avg(deaths) as prev_mean\n",
+    "from all_causes_deaths\n",
+    "where year <= 2019 and nation='Wales' \n",
+    "group by week\n",
+    "order by week'''\n",
+    "deaths_prev = pd.read_sql_query(qstr, engine, index_col='week')\n",
+    "deaths_prev.head()\n",
+    "deaths_w = deaths_w.merge(deaths_prev, on='week')\n",
+    "deaths_w.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>2017</th>\n",
+       "      <th>2018</th>\n",
+       "      <th>2019</th>\n",
+       "      <th>2020</th>\n",
+       "      <th>2021</th>\n",
+       "      <th>prev_mean</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>week</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1146.0</td>\n",
+       "      <td>1394.0</td>\n",
+       "      <td>1205.0</td>\n",
+       "      <td>1531.0</td>\n",
+       "      <td>1104.0</td>\n",
+       "      <td>1161.0</td>\n",
+       "      <td>1720.0</td>\n",
+       "      <td>1276.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1708.0</td>\n",
+       "      <td>1305.0</td>\n",
+       "      <td>1379.0</td>\n",
+       "      <td>1899.0</td>\n",
+       "      <td>1507.0</td>\n",
+       "      <td>1567.0</td>\n",
+       "      <td>1550.0</td>\n",
+       "      <td>1559.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1489.0</td>\n",
+       "      <td>1215.0</td>\n",
+       "      <td>1224.0</td>\n",
+       "      <td>1629.0</td>\n",
+       "      <td>1353.0</td>\n",
+       "      <td>1322.0</td>\n",
+       "      <td>1559.0</td>\n",
+       "      <td>1382.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1381.0</td>\n",
+       "      <td>1187.0</td>\n",
+       "      <td>1197.0</td>\n",
+       "      <td>1610.0</td>\n",
+       "      <td>1208.0</td>\n",
+       "      <td>1226.0</td>\n",
+       "      <td>1604.0</td>\n",
+       "      <td>1316.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>1286.0</td>\n",
+       "      <td>1205.0</td>\n",
+       "      <td>1332.0</td>\n",
+       "      <td>1369.0</td>\n",
+       "      <td>1206.0</td>\n",
+       "      <td>1188.0</td>\n",
+       "      <td>1495.0</td>\n",
+       "      <td>1279.6</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        2015    2016    2017    2018    2019    2020    2021  prev_mean\n",
+       "week                                                                   \n",
+       "1     1146.0  1394.0  1205.0  1531.0  1104.0  1161.0  1720.0     1276.0\n",
+       "2     1708.0  1305.0  1379.0  1899.0  1507.0  1567.0  1550.0     1559.6\n",
+       "3     1489.0  1215.0  1224.0  1629.0  1353.0  1322.0  1559.0     1382.0\n",
+       "4     1381.0  1187.0  1197.0  1610.0  1208.0  1226.0  1604.0     1316.6\n",
+       "5     1286.0  1205.0  1332.0  1369.0  1206.0  1188.0  1495.0     1279.6"
+      ]
+     },
+     "execution_count": 91,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "qstr = '''select week, avg(deaths) as prev_mean\n",
+    "from all_causes_deaths\n",
+    "where year <= 2019 and nation='Scotland' \n",
+    "group by week\n",
+    "order by week'''\n",
+    "deaths_prev = pd.read_sql_query(qstr, engine, index_col='week')\n",
+    "deaths_prev.head()\n",
+    "deaths_s = deaths_s.merge(deaths_prev, on='week')\n",
+    "deaths_s.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 92,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>2017</th>\n",
+       "      <th>2018</th>\n",
+       "      <th>2019</th>\n",
+       "      <th>2020</th>\n",
+       "      <th>2021</th>\n",
+       "      <th>prev_mean</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>week</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>319.0</td>\n",
+       "      <td>424.0</td>\n",
+       "      <td>416.0</td>\n",
+       "      <td>447.0</td>\n",
+       "      <td>365.0</td>\n",
+       "      <td>353.0</td>\n",
+       "      <td>568.0</td>\n",
+       "      <td>394.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>373.0</td>\n",
+       "      <td>348.0</td>\n",
+       "      <td>434.0</td>\n",
+       "      <td>481.0</td>\n",
+       "      <td>371.0</td>\n",
+       "      <td>395.0</td>\n",
+       "      <td>443.0</td>\n",
+       "      <td>401.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>383.0</td>\n",
+       "      <td>372.0</td>\n",
+       "      <td>397.0</td>\n",
+       "      <td>470.0</td>\n",
+       "      <td>332.0</td>\n",
+       "      <td>411.0</td>\n",
+       "      <td>474.0</td>\n",
+       "      <td>390.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>397.0</td>\n",
+       "      <td>355.0</td>\n",
+       "      <td>387.0</td>\n",
+       "      <td>426.0</td>\n",
+       "      <td>335.0</td>\n",
+       "      <td>347.0</td>\n",
+       "      <td>437.0</td>\n",
+       "      <td>380.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>374.0</td>\n",
+       "      <td>314.0</td>\n",
+       "      <td>371.0</td>\n",
+       "      <td>433.0</td>\n",
+       "      <td>296.0</td>\n",
+       "      <td>323.0</td>\n",
+       "      <td>462.0</td>\n",
+       "      <td>357.6</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       2015   2016   2017   2018   2019   2020   2021  prev_mean\n",
+       "week                                                            \n",
+       "1     319.0  424.0  416.0  447.0  365.0  353.0  568.0      394.2\n",
+       "2     373.0  348.0  434.0  481.0  371.0  395.0  443.0      401.4\n",
+       "3     383.0  372.0  397.0  470.0  332.0  411.0  474.0      390.8\n",
+       "4     397.0  355.0  387.0  426.0  335.0  347.0  437.0      380.0\n",
+       "5     374.0  314.0  371.0  433.0  296.0  323.0  462.0      357.6"
+      ]
+     },
+     "execution_count": 92,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "qstr = '''select week, avg(deaths) as prev_mean\n",
+    "from all_causes_deaths\n",
+    "where year <= 2019 and nation='Northern Ireland' \n",
+    "group by week\n",
+    "order by week'''\n",
+    "deaths_prev = pd.read_sql_query(qstr, engine, index_col='week')\n",
+    "deaths_prev.head()\n",
+    "deaths_i = deaths_i.merge(deaths_prev, on='week')\n",
+    "deaths_i.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 93,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>2017</th>\n",
+       "      <th>2018</th>\n",
+       "      <th>2019</th>\n",
+       "      <th>2020</th>\n",
+       "      <th>2021</th>\n",
+       "      <th>prev_mean</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>week</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>13751.0</td>\n",
+       "      <td>14863.0</td>\n",
+       "      <td>13612.0</td>\n",
+       "      <td>14701.0</td>\n",
+       "      <td>12424.0</td>\n",
+       "      <td>13768.0</td>\n",
+       "      <td>20039.0</td>\n",
+       "      <td>13870.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>18318.0</td>\n",
+       "      <td>13154.0</td>\n",
+       "      <td>15528.0</td>\n",
+       "      <td>17430.0</td>\n",
+       "      <td>14487.0</td>\n",
+       "      <td>16020.0</td>\n",
+       "      <td>20035.0</td>\n",
+       "      <td>15783.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>16738.0</td>\n",
+       "      <td>13060.0</td>\n",
+       "      <td>15231.0</td>\n",
+       "      <td>16355.0</td>\n",
+       "      <td>13545.0</td>\n",
+       "      <td>14723.0</td>\n",
+       "      <td>20709.0</td>\n",
+       "      <td>14985.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>15712.0</td>\n",
+       "      <td>12859.0</td>\n",
+       "      <td>14461.0</td>\n",
+       "      <td>15971.0</td>\n",
+       "      <td>13283.0</td>\n",
+       "      <td>13429.0</td>\n",
+       "      <td>20489.0</td>\n",
+       "      <td>14457.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>14560.0</td>\n",
+       "      <td>12571.0</td>\n",
+       "      <td>14188.0</td>\n",
+       "      <td>15087.0</td>\n",
+       "      <td>12799.0</td>\n",
+       "      <td>13123.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13841.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         2015     2016     2017     2018     2019     2020     2021  prev_mean\n",
+       "week                                                                          \n",
+       "1     13751.0  14863.0  13612.0  14701.0  12424.0  13768.0  20039.0    13870.2\n",
+       "2     18318.0  13154.0  15528.0  17430.0  14487.0  16020.0  20035.0    15783.4\n",
+       "3     16738.0  13060.0  15231.0  16355.0  13545.0  14723.0  20709.0    14985.8\n",
+       "4     15712.0  12859.0  14461.0  15971.0  13283.0  13429.0  20489.0    14457.2\n",
+       "5     14560.0  12571.0  14188.0  15087.0  12799.0  13123.0      NaN    13841.0"
+      ]
+     },
+     "execution_count": 93,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths = deaths_e + deaths_w + deaths_i + deaths_s\n",
+    "deaths.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 94,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='week'>"
+      ]
+     },
+     "execution_count": 94,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 1008x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "deaths[[2021, 2020, 2019, 2018, 2017, 2016, 2015]].plot(figsize=(14, 8))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='week'>"
+      ]
+     },
+     "execution_count": 95,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "deaths[[2021, 2020, 'prev_mean']].plot(figsize=(10, 8))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 96,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='week'>"
+      ]
+     },
+     "execution_count": 96,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "deaths_i.plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 97,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "83207.6000000001"
+      ]
+     },
+     "execution_count": 97,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths[2020].sum() - deaths.prev_mean.sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 98,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def _closeline(line):\n",
+    "    x, y = line.get_data()\n",
+    "    x = np.concatenate((x, [x[0]]))\n",
+    "    y = np.concatenate((y, [y[0]]))\n",
+    "    line.set_data(x, y)\n",
+    "\n",
+    "def _closeline_connect(lines):\n",
+    "    for line0, line1 in zip(lines, lines[1:]):\n",
+    "        x0, y0 = line0.get_data()\n",
+    "        x1, y1 = line1.get_data()\n",
+    "\n",
+    "        x0 = np.concatenate((x0, [x1[0]]))\n",
+    "        y0 = np.concatenate((y0, [y1[0]]))\n",
+    "        line0.set_data(x0, y0) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 99,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#\n",
+    "\n",
+    "def create_and_save_radar_plot(dataset, title_string, filename_suffix):\n",
+    "\n",
+    "    fig = plt.figure(figsize=(10, 10))\n",
+    "    ax = fig.add_subplot(111, projection=\"polar\")\n",
+    "\n",
+    "    theta = np.roll(\n",
+    "        np.flip(\n",
+    "            np.arange(len(dataset))/float(len(dataset))*2.*np.pi),\n",
+    "        14)\n",
+    "    l15, = ax.plot(theta, dataset[2015], color=\"#e47d7d\", label=\"2015\") # 0\n",
+    "    l16, = ax.plot(theta, dataset[2016], color=\"#afc169\", label=\"2016\") # 72 , d0e47d\n",
+    "    l17, = ax.plot(theta, dataset[2017], color=\"#7de4a6\", label=\"2017\") # 144\n",
+    "    l18, = ax.plot(theta, dataset[2018], color=\"#7da6e4\", label=\"2018\") # 216\n",
+    "    l19, = ax.plot(theta, dataset[2019], color=\"#d07de4\", label=\"2019\") # 288\n",
+    "\n",
+    "    lmean, = ax.plot(theta, dataset['prev_mean'], color=\"black\", linestyle='dashed', label=\"mean, 15–19\")\n",
+    "\n",
+    "    l20, = ax.plot(theta, dataset[2020], color=\"#bb0000\", label=\"2020\")\n",
+    "    l21, = ax.plot(theta, dataset[2021], color=\"#ff0000\", label=\"2021\")\n",
+    "\n",
+    "    # deaths_headlines.total_2019.plot(ax=ax)\n",
+    "\n",
+    "    _closeline(lmean)\n",
+    "    _closeline_connect([l15, l16, l17, l18, l19, l20, l21])\n",
+    "\n",
+    "    ax.set_xticks(theta)\n",
+    "    ax.set_xticklabels(dataset.index)\n",
+    "    plt.legend()\n",
+    "    plt.title(f\"Deaths by week over years, {title_string}\")\n",
+    "    plt.savefig(f'deaths-radar-2021{filename_suffix}.png')\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 100,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "create_and_save_radar_plot(deaths, 'all UK', '')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 101,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "# # Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#\n",
+    "\n",
+    "# dhna = deaths# .dropna()\n",
+    "\n",
+    "# fig = plt.figure(figsize=(10, 10))\n",
+    "# ax = fig.add_subplot(111, projection=\"polar\")\n",
+    "\n",
+    "# theta = np.roll(\n",
+    "#     np.flip(\n",
+    "#         np.arange(len(dhna))/float(len(dhna))*2.*np.pi),\n",
+    "#     14)\n",
+    "# # l15, = ax.plot(theta, deaths_headlines['total_2015'], color=\"#b56363\", label=\"2015\") # 0\n",
+    "# # l16, = ax.plot(theta, deaths_headlines['total_2016'], color=\"#a4b563\", label=\"2016\") # 72\n",
+    "# # l17, = ax.plot(theta, deaths_headlines['total_2017'], color=\"#63b584\", label=\"2017\") # 144\n",
+    "# # l18, = ax.plot(theta, deaths_headlines['total_2018'], color=\"#6384b5\", label=\"2018\") # 216\n",
+    "# # l19, = ax.plot(theta, deaths_headlines['total_2019'], color=\"#a4635b\", label=\"2019\") # 288\n",
+    "# l15, = ax.plot(theta, dhna[2015], color=\"#e47d7d\", label=\"2015\") # 0\n",
+    "# l16, = ax.plot(theta, dhna[2016], color=\"#afc169\", label=\"2016\") # 72 , d0e47d\n",
+    "# l17, = ax.plot(theta, dhna[2017], color=\"#7de4a6\", label=\"2017\") # 144\n",
+    "# l18, = ax.plot(theta, dhna[2018], color=\"#7da6e4\", label=\"2018\") # 216\n",
+    "# l19, = ax.plot(theta, dhna[2019], color=\"#d07de4\", label=\"2019\") # 288\n",
+    "\n",
+    "# lmean, = ax.plot(theta, dhna['prev_mean'], color=\"black\", linestyle='dashed', label=\"mean, 15–19\")\n",
+    "\n",
+    "# l20, = ax.plot(theta, dhna[2020], color=\"#bb0000\", label=\"2020\")\n",
+    "# l21, = ax.plot(theta, dhna[2021], color=\"#ff0000\", label=\"2021\")\n",
+    "\n",
+    "# # deaths_headlines.total_2019.plot(ax=ax)\n",
+    "\n",
+    "# _closeline(lmean)\n",
+    "# _closeline_connect([l15, l16, l17, l18, l19, l20, l21])\n",
+    "\n",
+    "# ax.set_xticks(theta)\n",
+    "# ax.set_xticklabels(dhna.index)\n",
+    "# plt.legend()\n",
+    "# plt.title(\"Deaths by week over years, all UK\")\n",
+    "# plt.savefig('deaths-radar-2021.png')\n",
+    "# plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "source": [
+    "# Plots for UK nations"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 102,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "create_and_save_radar_plot(deaths_e, 'England', '-england')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 103,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 720x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "create_and_save_radar_plot(deaths_w, 'Wales', '-wales')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 104,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "create_and_save_radar_plot(deaths_s, 'Scotland', '-scotland')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 105,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 720x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "create_and_save_radar_plot(deaths_i, 'Northern Ireland', '-northern-ireland')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "jupytext": {
+   "formats": "ipynb,md"
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/uk_deaths_import.md b/uk_deaths_import.md

new file mode 100644 (file)

index 0000000..e775661
--- /dev/null
+++ b/uk_deaths_import.md
@@ -0,0 +1,489 @@
+---
+jupyter:
+  jupytext:
+    formats: ipynb,md
+    text_representation:
+      extension: .md
+      format_name: markdown
+      format_version: '1.2'
+      jupytext_version: 1.9.1
+  kernelspec:
+    display_name: Python 3
+    language: python
+    name: python3
+---
+
+<!-- #region Collapsed="false" -->
+Data from:
+
+* [Office of National Statistics](https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/weeklyprovisionalfiguresondeathsregisteredinenglandandwales) (Endland and Wales) Weeks start on a Saturday.
+* [Northern Ireland Statistics and Research Agency](https://www.nisra.gov.uk/publications/weekly-deaths) (Northern Ireland). Weeks start on a Saturday. Note that the week numbers don't match the England and Wales data.
+* [National Records of Scotland](https://www.nrscotland.gov.uk/statistics-and-data/statistics/statistics-by-theme/vital-events/general-publications/weekly-and-monthly-data-on-births-and-deaths/weekly-data-on-births-and-deaths) (Scotland). Note that Scotland uses ISO8601 week numbers, which start on a Monday.
+
+<!-- #endregion -->
+
+```python Collapsed="false"
+import itertools
+import collections
+import json
+import pandas as pd
+import numpy as np
+from scipy.stats import gmean
+import datetime
+
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+%matplotlib inline
+
+from sqlalchemy.types import Integer, Text, String, DateTime, Float
+from sqlalchemy import create_engine
+%load_ext sql
+```
+
+```python Collapsed="false"
+connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'
+```
+
+```python Collapsed="false"
+%sql $connection_string
+```
+
+```python Collapsed="false"
+engine = create_engine(connection_string)
+```
+
+```python Collapsed="false"
+england_wales_filename = 'uk-deaths-data/copyofpublishedweek042021.xlsx'
+```
+
+```python Collapsed="false"
+scotland_filename = 'uk-deaths-data/Scottish Government COVID-19 data (10 February 2021).xlsx'
+```
+
+```python
+n_ireland_filename = 'uk-deaths-data/Weekly_Deaths_0.xlsx'
+```
+
+```python Collapsed="false"
+eng_xls = pd.read_excel(england_wales_filename, 
+                        sheet_name="Weekly figures 2021",
+                        skiprows=[0, 1, 2, 3],
+                        skipfooter=11,
+                        header=0,
+                        index_col=[1]
+                       ).iloc[:91].T
+eng_xls
+```
+
+```python Collapsed="false"
+eng_xls_columns = list(eng_xls.columns)
+
+for i, c in enumerate(eng_xls_columns):
+#     print(i, c, type(c), isinstance(c, float))
+    if isinstance(c, float) and np.isnan(c):
+        if eng_xls.iloc[0].iloc[i] is not pd.NaT:
+            eng_xls_columns[i] = eng_xls.iloc[0].iloc[i]
+
+# np.isnan(eng_xls_columns[0])
+# eng_xls_columns
+
+eng_xls.columns = eng_xls_columns
+# eng_xls.columns
+```
+
+```python
+eng_xls
+```
+
+```python
+rd = eng_xls.iloc[1:][['Week ended', 'Wales']].reset_index(level=0).rename(
+    columns={'Week ended': 'date_up_to', 'Wales': 'deaths',
+            'index': 'week'}
+    )
+rd['year'] = 2021
+rd['nation'] = 'Wales'
+rd.dropna(inplace=True)
+rd.head()
+```
+
+```python
+query_string = '''
+delete from all_causes_deaths
+where nation = 'Wales'
+  and year = 2021;
+'''
+with engine.connect() as connection:
+    connection.execute(query_string)
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    engine,
+    if_exists='append',
+    index=False)
+```
+
+```python
+%sql select * from all_causes_deaths where year = 2021 limit 10
+```
+
+```python
+rd = eng_xls.iloc[1:][['Week ended', 'Total deaths, all ages (2021)', 'Wales']].reset_index(level=0).rename(
+    columns={'Week ended': 'date_up_to', 
+             'Total deaths, all ages (2021)': 'ew_deaths',
+             'Wales': 'w_deaths',
+            'index': 'week'}
+    )
+rd['year'] = 2021
+rd['nation'] = 'England'
+rd['deaths'] = rd['ew_deaths'] - rd['w_deaths']
+rd.drop(labels=['ew_deaths', 'w_deaths'], axis='columns', inplace=True)
+rd.dropna(inplace=True)
+rd.tail()
+```
+
+```python
+query_string = '''
+delete from all_causes_deaths
+where nation = 'England'
+  and year = 2021;
+'''
+with engine.connect() as connection:
+    connection.execute(query_string)
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    engine,
+    if_exists='append',
+    index=False)
+```
+
+```python
+%sql select nation, sum(deaths), count(*) from all_causes_deaths where year = 2021 group by nation
+```
+
+```python
+ni_xls = pd.read_excel(n_ireland_filename, 
+                        sheet_name='Table 1',
+                        skiprows=[0, 1, 2, 3],
+                        header=0,
+                      ).rename(
+    columns={'Week Ending (Friday)': 'date_up_to', 'Total Number of Deaths Registered in Week (2021P)': 'deaths',
+            'Registration Week': 'week'})
+rd = ni_xls[ni_xls['deaths'].notna()][['week', 'date_up_to', 'deaths']]
+rd['year'] = 2021
+rd['nation'] = 'Northern Ireland'
+rd
+```
+
+```python
+query_string = '''
+delete from all_causes_deaths
+where nation = 'Northern Ireland'
+  and year = 2021;
+'''
+with engine.connect() as connection:
+    connection.execute(query_string)
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    engine,
+    if_exists='append',
+    index=False)
+```
+
+```python
+%sql select nation from all_causes_deaths group by nation
+```
+
+```python
+# sco_xls = pd.read_excel(scotland_filename, 
+#                         sheet_name="2.2_excess",
+#                         skiprows=[0, 1, 2, 3],
+#                         skipfooter=3,
+#                         header=0,
+#                         index_col=[1]
+#                        ).iloc[:91].T
+```
+
+```python
+import openpyxl
+```
+
+```python
+wb = openpyxl.load_workbook(scotland_filename, read_only=True)#, data_only=True, keep_links=False)
+sheet = wb.worksheets[7]
+sheet
+```
+
+```python
+sheet.reset_dimensions()
+```
+
+```python
+scot_elems = [[value for value in row] for row in sheet.values]
+scot_cols = scot_elems[3]
+scot_dicts = [{k: v for k, v in zip(scot_cols, row)} for row in scot_elems[4:]]
+scot_data = pd.DataFrame(scot_dicts)
+rd = scot_data[scot_data.date >= '2021'].rename(
+    columns={'week_number': 'week', 'date': 'date_up_to', 'total_deaths': 'deaths'})[['week', 'date_up_to', 'deaths']]
+rd['year'] = 2021
+rd['nation'] = 'Scotland'
+rd
+```
+
+```python
+query_string = '''
+delete from all_causes_deaths
+where nation = 'Scotland'
+  and year = 2021;
+'''
+with engine.connect() as connection:
+    connection.execute(query_string)
+```
+
+```python
+rd.to_sql(
+    'all_causes_deaths',
+    engine,
+    if_exists='append',
+    index=False)
+```
+
+```python
+%sql select nation, sum(deaths), count(*) from all_causes_deaths where year = 2021 group by nation
+```
+
+```python
+
+```
+
+# Create graphs
+
+```python
+qstr = '''select week, year, deaths
+from all_causes_deaths
+where nation = 'England' '''
+deaths_e = pd.read_sql_query(qstr, engine).pivot(index='week', columns='year', values='deaths')
+deaths_e.head()
+```
+
+```python
+qstr = '''select week, year, deaths
+from all_causes_deaths
+where nation = 'Wales' '''
+deaths_w = pd.read_sql_query(qstr, engine).pivot(index='week', columns='year', values='deaths')
+deaths_w.head()
+```
+
+```python
+qstr = '''select week, year, deaths
+from all_causes_deaths
+where nation = 'Scotland' '''
+deaths_s = pd.read_sql_query(qstr, engine).pivot(index='week', columns='year', values='deaths')
+deaths_s.head()
+```
+
+```python
+qstr = '''select week, year, deaths
+from all_causes_deaths
+where nation = 'Northern Ireland' '''
+deaths_i = pd.read_sql_query(qstr, engine).pivot(index='week', columns='year', values='deaths')
+deaths_i.head()
+```
+
+```python
+qstr = '''select week, avg(deaths) as prev_mean
+from all_causes_deaths
+where year <= 2019 and nation='England' 
+group by week
+order by week'''
+deaths_prev = pd.read_sql_query(qstr, engine, index_col='week')
+deaths_prev.head()
+deaths_e = deaths_e.merge(deaths_prev, on='week')
+deaths_e.head()
+```
+
+```python
+qstr = '''select week, avg(deaths) as prev_mean
+from all_causes_deaths
+where year <= 2019 and nation='Wales' 
+group by week
+order by week'''
+deaths_prev = pd.read_sql_query(qstr, engine, index_col='week')
+deaths_prev.head()
+deaths_w = deaths_w.merge(deaths_prev, on='week')
+deaths_w.head()
+```
+
+```python
+qstr = '''select week, avg(deaths) as prev_mean
+from all_causes_deaths
+where year <= 2019 and nation='Scotland' 
+group by week
+order by week'''
+deaths_prev = pd.read_sql_query(qstr, engine, index_col='week')
+deaths_prev.head()
+deaths_s = deaths_s.merge(deaths_prev, on='week')
+deaths_s.head()
+```
+
+```python
+qstr = '''select week, avg(deaths) as prev_mean
+from all_causes_deaths
+where year <= 2019 and nation='Northern Ireland' 
+group by week
+order by week'''
+deaths_prev = pd.read_sql_query(qstr, engine, index_col='week')
+deaths_prev.head()
+deaths_i = deaths_i.merge(deaths_prev, on='week')
+deaths_i.head()
+```
+
+```python Collapsed="false"
+deaths = deaths_e + deaths_w + deaths_i + deaths_s
+deaths.head()
+```
+
+```python Collapsed="false"
+deaths[[2021, 2020, 2019, 2018, 2017, 2016, 2015]].plot(figsize=(14, 8))
+```
+
+```python Collapsed="false"
+deaths[[2021, 2020, 'prev_mean']].plot(figsize=(10, 8))
+```
+
+```python Collapsed="false"
+deaths_i.plot()
+```
+
+```python
+deaths[2020].sum() - deaths.prev_mean.sum()
+```
+
+```python
+def _closeline(line):
+    x, y = line.get_data()
+    x = np.concatenate((x, [x[0]]))
+    y = np.concatenate((y, [y[0]]))
+    line.set_data(x, y)
+
+def _closeline_connect(lines):
+    for line0, line1 in zip(lines, lines[1:]):
+        x0, y0 = line0.get_data()
+        x1, y1 = line1.get_data()
+
+        x0 = np.concatenate((x0, [x1[0]]))
+        y0 = np.concatenate((y0, [y1[0]]))
+        line0.set_data(x0, y0) 
+```
+
+```python Collapsed="false"
+# Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#
+
+def create_and_save_radar_plot(dataset, title_string, filename_suffix):
+
+    fig = plt.figure(figsize=(10, 10))
+    ax = fig.add_subplot(111, projection="polar")
+
+    theta = np.roll(
+        np.flip(
+            np.arange(len(dataset))/float(len(dataset))*2.*np.pi),
+        14)
+    l15, = ax.plot(theta, dataset[2015], color="#e47d7d", label="2015") # 0
+    l16, = ax.plot(theta, dataset[2016], color="#afc169", label="2016") # 72 , d0e47d
+    l17, = ax.plot(theta, dataset[2017], color="#7de4a6", label="2017") # 144
+    l18, = ax.plot(theta, dataset[2018], color="#7da6e4", label="2018") # 216
+    l19, = ax.plot(theta, dataset[2019], color="#d07de4", label="2019") # 288
+
+    lmean, = ax.plot(theta, dataset['prev_mean'], color="black", linestyle='dashed', label="mean, 15–19")
+
+    l20, = ax.plot(theta, dataset[2020], color="#bb0000", label="2020")
+    l21, = ax.plot(theta, dataset[2021], color="#ff0000", label="2021")
+
+    # deaths_headlines.total_2019.plot(ax=ax)
+
+    _closeline(lmean)
+    _closeline_connect([l15, l16, l17, l18, l19, l20, l21])
+
+    ax.set_xticks(theta)
+    ax.set_xticklabels(dataset.index)
+    plt.legend()
+    plt.title(f"Deaths by week over years, {title_string}")
+    plt.savefig(f'deaths-radar-2021{filename_suffix}.png')
+    plt.show()
+```
+
+```python
+create_and_save_radar_plot(deaths, 'all UK', '')
+```
+
+```python Collapsed="false"
+# # Radar plot code taken from example at https://stackoverflow.com/questions/42878485/getting-matplotlib-radar-plot-with-pandas#
+
+# dhna = deaths# .dropna()
+
+# fig = plt.figure(figsize=(10, 10))
+# ax = fig.add_subplot(111, projection="polar")
+
+# theta = np.roll(
+#     np.flip(
+#         np.arange(len(dhna))/float(len(dhna))*2.*np.pi),
+#     14)
+# # l15, = ax.plot(theta, deaths_headlines['total_2015'], color="#b56363", label="2015") # 0
+# # l16, = ax.plot(theta, deaths_headlines['total_2016'], color="#a4b563", label="2016") # 72
+# # l17, = ax.plot(theta, deaths_headlines['total_2017'], color="#63b584", label="2017") # 144
+# # l18, = ax.plot(theta, deaths_headlines['total_2018'], color="#6384b5", label="2018") # 216
+# # l19, = ax.plot(theta, deaths_headlines['total_2019'], color="#a4635b", label="2019") # 288
+# l15, = ax.plot(theta, dhna[2015], color="#e47d7d", label="2015") # 0
+# l16, = ax.plot(theta, dhna[2016], color="#afc169", label="2016") # 72 , d0e47d
+# l17, = ax.plot(theta, dhna[2017], color="#7de4a6", label="2017") # 144
+# l18, = ax.plot(theta, dhna[2018], color="#7da6e4", label="2018") # 216
+# l19, = ax.plot(theta, dhna[2019], color="#d07de4", label="2019") # 288
+
+# lmean, = ax.plot(theta, dhna['prev_mean'], color="black", linestyle='dashed', label="mean, 15–19")
+
+# l20, = ax.plot(theta, dhna[2020], color="#bb0000", label="2020")
+# l21, = ax.plot(theta, dhna[2021], color="#ff0000", label="2021")
+
+# # deaths_headlines.total_2019.plot(ax=ax)
+
+# _closeline(lmean)
+# _closeline_connect([l15, l16, l17, l18, l19, l20, l21])
+
+# ax.set_xticks(theta)
+# ax.set_xticklabels(dhna.index)
+# plt.legend()
+# plt.title("Deaths by week over years, all UK")
+# plt.savefig('deaths-radar-2021.png')
+# plt.show()
+```
+
+<!-- #region Collapsed="false" -->
+# Plots for UK nations
+<!-- #endregion -->
+
+```python
+create_and_save_radar_plot(deaths_e, 'England', '-england')
+```
+
+```python
+create_and_save_radar_plot(deaths_w, 'Wales', '-wales')
+```
+
+```python
+create_and_save_radar_plot(deaths_s, 'Scotland', '-scotland')
+```
+
+```python
+create_and_save_radar_plot(deaths_i, 'Northern Ireland', '-northern-ireland')
+```
+
+```python Collapsed="false"
+
+```
diff --git a/uk_end.js b/uk_end.js

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-document.write('183');
-\ No newline at end of file
author	Neil Smith <neil.git@njae.me.uk>
	Mon, 15 Feb 2021 09:28:17 +0000 (09:28 +0000)
committer	Neil Smith <neil.git@njae.me.uk>
	Mon, 15 Feb 2021 09:28:17 +0000 (09:28 +0000)
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