--- /dev/null
+{
+ "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": {
+ "image/png": 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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",
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+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
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+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
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+ "<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",
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+ " <th>doubling_time</th>\n",
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+ " </tr>\n",
+ " <tr>\n",
+ " <th>dateRep</th>\n",
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+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <td>2019-12-31</td>\n",
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+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>2020-01-03</td>\n",
+ " <td>0</td>\n",
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+ " <td>NaN</td>\n",
+ " </tr>\n",
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+ " <td>2020-01-04</td>\n",
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+ " <td>0.000000</td>\n",
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+ " </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",
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+ " <td>343.603005</td>\n",
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+ " <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",
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+ " <td>124.672307</td>\n",
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+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
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+ "</div>"
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+ "\n",
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+ "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"
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+ "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",
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+ "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",
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+ "... ... ... ... ... ... \n",
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+ "[350 rows x 12 columns]"
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+ "execution_count": 479,
+ "metadata": {},
+ "output_type": "execute_result"
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+ "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": [
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+ " <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": {
+ "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['2020-04-01':, ['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": {
+ "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['2020-03-01':'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": {
+ "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['2020-03-01':'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": {
+ "image/png": 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3rF+/HoCYmBiWLVtGr169uHmc5rhx4zh79mzJ9UOHDkVRFPz9/XFzc8Pf3x9Qi5BFR0cTEPDfxjt/f/+76roXFhZiYWHBs88+y+DBgxkyZMht8WRkZJCenl5SIOypp55i7NixJc/fWrs9OjoagM6dO/Ppp58SGxvLqFGjSu213+Tj43NbzH369Cn5fm62d9PmzZvp2rXrbUMyPj4+Jd/jrTFok+y5G5PYG4muvnZPO8rIyyA2K5aWLi2h/VPq5qhLB7V6j6ro4N6B6GvRJGYnsi16GyM3jWROyBx9h1Xr7N69m3/++YdDhw4RFhZG27Ztadas2V013m9V0drrQKl13U1NTTl69CijR49mw4YNDBhQuaG50mq3P/roo2zatAlLS0v69+/Pzp07y339nd9DafGvWrXqrhLDt75eV/XjZXI3JrFBYGat1oTRosjUSABaOLWAliPB3KZGDM10rNcRgHmh85i2bxpCCP659A/FoljPkdUuGRkZODo6YmVlRWRkJIcPHyYnJ4fdu3eTkpJSciZpVZVW1z0rK4uMjAwGDRrE3Llz7xrKsbe3x9HRkX379gGwbNmycsv8XrhwAV9fX1577TWGDRvGiRMnqhzzTRkZGezZs4fhw4dXu63KksMyxiTmKHi2U9e4a9GpFHW8tLlzczC3hmZD4NQmGDQbzCy0eq/K8HP0w76OPRvPb6SZUzNGNRnFZ0c+4+TVk7R2rXphM6lyBgwYwE8//UTr1q1p2rQpnTp1ol69ekyfPp3OnTtTr1492rVrR1FRUfmNlSI8PPyuuu6ZmZkMHz6c3NxchBDMmXP3O7YlS5aUTKj6+vqyaNGiMu/z+++/s3z5cszMzHB3d+fDDz+sUry3Wr9+Pf369cPa2rrabVWWopYHvv8CAwNFcHCwXu5tlPKvwxf11VK9far/Q3mrqXumEpYcxvYx29UHov6B5aNh3HJ1Pb0efXLoE0KTQ/n1oV8x1ZjS6/dePNXyKV5v/7pe47qfTp8+TfPmzfUdhqQDpf3bKooSIoQILO+1cljGWMSHQnEheGl3vB3gdOppWjjfMtTj00utW3NC/3XX3+v0HmuHrsXZ0hn7OvYEugfy7+V/9R2WJOmdTO7G4uZkqpZXymTmZ3Lp2iWaO93SezAxhZaj1DX1uRlavV9laRTNbRN3DzZ4kOhr0bIevFRtKSkpd9WODwgIKDkrtqaTyd1YxAaBUyOtby4qmUx1vmOStvXDUJQHpzdr9X7V1bt+bwB2Xr73SgdJqghnZ+e7ascfP34cZ2fD2BEtk7sxEEKdTNXB+vbbJlNv5dle3QlbA4ZmbuVu7U4r51bsurxL36FIkl7J5G4M0i9BdhLU101yr2tVFxdLl9ufUBTwHwsX90Lm/as3UxEPNniQE1dPcD79vL5DkSS9kcndGMTeWHWkg577XZOpt/IfAwg4tVHr962OQb6DsDW35fE/H2dbtDxfU6qdZHI3BleOg0kdrW9eyi7IJjoj+t7J3bWpes+T67R63+rytPFkzdA1+Nr7MmXPFGYHlV58TJKMmUzuxiD+uFq5z8RMq81GpkYiEOrO1HtpOQpiDkNGrFbvXV2eNp4sHrCYEY1HsOTUEi5mXNR3SLXG9OnTmT278r9Qd+/ezcGD/5W1ePrpp/njD90flL5ixYrbVsNoNJq7drwaIpncDV1xsZrcPbRz9N2tTqecBkpZKXOrVmoBppo2NANgZmLGa21fQ6No2HJhi77DkcpxZ3K/Xx577LGSlTDLli3D29v7tsJlhkqWHzB0qechP1Mnyf1Y0jHcrd1xtXK990XOjcC9tTo00/llrcdQXa5WrnSq14mtF7bycsDLaBTj7s98efTLkuWr2tLMqRnvdHinzGs+/fRTli5dSv369XF1daV9+/acP3+el19+meTkZKysrPj1119p1qwZmzdvZubMmeTn5+Ps7MyKFSvIycnhp59+wsTEhOXLlzNv3jwA9u7dyzfffENCQgKzZs1izJgxXLlyhXHjxnHt2jUKCwv58ccf6d69e6lx2djY8PLLL/PPP//g6OjIZ599xttvv83ly5eZO3cuw4YNu+36W+uu33z95MmT2bJlC5aWlmzcuBE3N7dq/o3eH8b9k14bxIeqnz2029MoFsUEJwSXHIpRppYjIS4Y0i5pNQZtGeI7hLisOEKTQvUdilEKCQlh1apVhIaGsm7dOoKC1A11kyZNYt68eYSEhDB79mxeeuklgJJDLkJDQ3nkkUeYNWsW3t7evPDCC7zxxhscP368JFlfuXKF/fv3s2XLFqZNmwbAypUr6d+/P8ePHycsLKzMXnZ2dja9evUiJCQEW1tb3n//fXbs2MH69etLrR3z+++/35bcs7Oz6dSpE2FhYfTo0YNff/1Va39vulahnruiKAOAbwETYIEQ4os7nm8ALAEcblwzTQhR+TOypMqLDwVTS3BpqtVmo9KjSMtL4wH3CqzAaTkS/v0YTm1Qa9vUMH0a9MHS1JLN5zfT3q29vsPRqfJ62Lqwb98+Ro4ciZWVFQDDhg0jNzeXgwcP3lZDPS8vD4DY2FjGjRvHlStXyM/Px8fH555tjxgxAo1GQ4sWLUhMTATggQceYMKECRQUFDBixIgyk7u5uXlJOWB/f3/q1KmDmZlZqXXXjxw5gpWVFa1atbrt9Tdrxbdv354dO3ZU4m9Gv8rtuSuKYgLMBwYCLYDxiqLcOQj7PrBaCNEWeAT4QduBSvcQHwr1WqslAbTo5iEYFeq5O/mARzuIWK/VGLTFysyKvg36sj16O3lFefoOxyjdWbu9uLgYBweH23Z2nj6tzuG8+uqrvPLKK4SHh/Pzzz+Tm5t7z3ZvrXt+s8hhjx492Lt3L56enjzxxBNlHohtZmZWEltV6q7f+npd1V3XlYoMy3QAooQQF4QQ+cAq4M7ixAKwu/FneyBeeyFK91RcBFfCdDLefvTKUTxtPPGw8ajYC5oNVn/RZCZqPRZtGNJoCJkFmeyJ2aPvUIxOjx49WL9+PTk5OWRmZrJ582asrKzw8fEpqeMuhCAsLAxQa5x7enoCalnem2xtbcnMzCz3fpcuXaJu3bo899xzTJw4kWPHjlX7eyguLmbNmjU88sgj1W6rpqhIcvcEYm75OvbGY7eaDjyuKEos8CfwamkNKYoySVGUYEVRgpOTk6sQrnSbq2eh4LrWk3uxKCY4sYLj7Tc1eUj9fL5m1nTp6N6RupZ12XyhZtXCMQbt2rVj3LhxBAQEMHr06JLx8hUrVvDbb7/Rpk0bWrZsycaN6oqq6dOnM3bsWLp3746Ly387n4cOHcr69esJCAgoOWSjNLt37yYgIIC2bduydu1aJk+u/lDg3r178fLywtfXt9pt1RhCiDI/gLGo4+w3v34CmHfHNW8Cb934c2fgFKApq9327dsLqZpCVwjxkZ0QSZFabfbU1VOi1eJWYlPUpoq/qKhIiFmNhVjzjFZj0aavjn4lApYGiPTcdH2HolWnTp3SdwiSjpT2bwsEi3LythCiQj33WKD+LV97cfewy0Rg9Y1fFocAC+COYiSS1sWHqkfeOTfWarNHE44CFRxvv0mjgcZ91J57cdVO3NG1wb6DKSwulCUJpFqhIsk9CGiiKIqPoijmqBOmm+645jLQB0BRlOaoyV2Ou+hafKi6xlzLx+oFJQTR0K4hbtaVXM/buC/kpP23PLOGaebUDF97X7Ze2KrvUCQt69ix411118PDw/Udll6Vu8RCCFGoKMorwDbUZY4LhRARiqLMQH17sAl4C/hVUZQ3UCdXn77x9kHSlcJ8SAiHwAnabba4kJDEEAb4VO40eQAaPQiKBs7tAK9yTwG77xRFYYjvEL4L/Y74rPiKTxYbACHEXStWapMjR47oOwStq24KrdAmJiHEn0IIPyFEIyHEpzce+/BGYkcIcUoI0VUI0UYIESCE2F6tqKTyxQZBYS407KLVZs+mnSWrIKtyQzI3WTmpdd6j/tFqTNo0yHcQAH9eNJ5tGBYWFqSkpFQ7GUg1hxCClJQULCyqfgC9LD9gqC7sUnvJ3qVvu66q6IxoAPwc/arWQOO+sPsLuJ6qJvsaxtPGk7Z127L1wlYmtppoFL1dLy8vYmNjkSvQjIuFhQVeXl5Vfr1M7obq/C61l2zpoNVm47LiAKo+ZNG4L+z+XJ1Y9R+jxci0Z7DPYGYemVl2rXoDYmZmVuYuT6l2krVlDFFOGsQfU8e4tSw2KxZnC2csTS2r1oBHW7B0qtFDM/29+2NjZsNrO1/jTOoZfYcjSTohk7shurgPRDH49tZ603GZcXja3rlHrRI0JtCot9pzr6FjwA4WDiwesBiB4Mm/nmRv7F59hyRJWieTuyG6sAvMbXWyIiU2KxZPm2okd1DfUWQlQmKEdoLSgaZOTVk5aCUN7Rryyr+vMG3fNGIyY8p/oSQZCJncDdH5XeDdTesnLxUWF5KQnYCXTdUncYD/hovO/1v9oHTIzdqNxQMWM6HVBP699C/D1g/jlxO/6DssSdIKmdwNTVo0pF1Uhz60LPF6IkWiqPo9dzsP9WzVqJqd3EGtGPl6+9f5c9SfdPLoxI9hP5JdkK3vsCSp2mRyNzTnd6mfdTTeDlRvzP2mRg/C5UOQf736bd0HrlauTGg1gcLiQg7HH9Z3OJJUbTK5G5oLu8HOE1yaaL3pm8sgq91zBzW5F+XDpQPVb+s+CagbgI2ZDfvi7l2RUJIMhUzuhiYhXF3froPNN7FZsZgoJrhbu1e/sYZdwNTCIIZmbjLTmNHZozP7YvfJ3Z6SwZPJ3ZAU5qlj7q7aPVLvptjMWNyt3THTaGGi1swSGnatsfXd76WHVw+ScpI4kybXv0uGTSZ3Q5J6EUQRuFSxNEA54rLitDMkc1PjPnD1DGTEaq9NHevm2Q1Arn2XDJ5M7obk6ln1sw7G20EHyb1JP/Xz8ZXaa1PHXCxdaOnckn2xctxdMmwyuRuSm8ndWfvJPbcwl6s5V7Wb3F2agN8AOPwD5JV/NmZN0d2rOyeuniA9N13foUhSlcnkbkiunlNXytSx0XrT8Vnq4VpaWQZ5qx5T1Vo4wQu1264O9fDsQbEo5kC84az0kaQ7yeRuSK6e1dmQTGyWOi5e7d2pd/IKVNfkH5xnMGveW7q0xMnCiR2Xdug7FEmqMpncDYUQas9dh5OpoKU17nfq+TZkJ8OxpdpvWwc0ioahvkPZE7OHqzlX9R2OJFWJTO6GIjMB8jN1l9wz46hjUgcXSx2ca96wi7os8sBcg+m9j/IbRaEoZNP5O48LliTDIJO7odDxSpmb1SB1djLRg+9D5hXYN1s37WuZr70v7eq2Y925dXJDk2SQZHI3FCXJXTcbmLS+DPJODbtA60fgwHfq8JIBGO03mkvXLhGcGKzvUCSp0mRyNxRXz6k13G21UBrgDvlF+cRkxug2uQP0+wTMrGDrWzX2II9bPdTwIWzNbFl7bq2+Q5GkSpPJ3VDcXCmjg2GTLRe2kF2QTe/62q80eRubutDnA7i4ByLW6fZeWmBpaslg38HsiN5BRl6GvsORpEqRyd1Q6GilTFFxEYtOLqK5U3M6e3TWevt3CZwA9drAtvcNYnJ1bNOxFBQX8MnhT+TYu2RQZHI3BHlZcC1WJ5Op/17+l+hr0Uz0n6i7ydRbaUxgwBeQGQ+H5uv+ftXk5+jH6+1fZ1v0Nn4N/1Xf4UhShcnkbghSotTPWu65CyH47eRvNLRrSN8GfbXadpkadoHmQ2H/HHWJZw33TMtnGOw7mHmh89h52bCqXEq1l0zuhuDm6hItJ/dDVw5xKuUUz7R8BhONiVbbLlffj9XDPHbOvL/3rQJFUZjeeTqtnFsxdc9UZgfNJi03Td9hSVKZZHI3BNfiQGMKTj5abXb1mdW4WLowtNFQrbZbIc6NoOPzELocrpy4//evJAtTC77v8z0DfQay7PQyBq4bKDc4STWaTO6GoNvrMC0GTOtorcliUUxIYgjdPbtjbmKutXYrpccUsHaBDS9CQY5+YqgEZ0tnZnabybph6/C192VW0Czyi/L1HZYklUomd0NhbqXV5i5mXCQ9L522ddtqtd1KsXSEET9B4knY/r7+4qikRg6NeDngZTLyMtgTu0ff4UhSqWRyr8IhhaYAACAASURBVKWOJR0DoJ1bO/0G0qQvdHkVghbA6c36jaUSOtXrRF3LumyM2qjvUCSpVBVK7oqiDFAU5YyiKFGKoky7xzUPK4pySlGUCEVRDOfonVoqNDEUJwsnGtg20Hco8OCH4NEONr5sMEfymWhMGNJoCPvj9svKkVKNVG5yVxTFBJgPDARaAOMVRWlxxzVNgHeBrkKIlsDrOohV0qJjScdoV7fd/VnbXh5TcxjzGxQXwbrn1c8GYHij4RSJIrZe2KrvUCTpLhXpuXcAooQQF4QQ+cAqYPgd1zwHzBdCpAEIIZK0G6akTYnZicRlxel3vP1OTr4wcBZc2g8Hv9N3NBXi6+BLa5fWbIjaIHevSjVORZK7JxBzy9exNx67lR/gpyjKAUVRDiuKMkBbAUraF5ocCkB7t/Z6juQOAY9Ci+Hq2vf4UH1HUyHDGg0jKj2K06mn9R2KJN2mIsm9tPftd3ZTTIEmQC9gPLBAURSHuxpSlEmKogQrihKcnJxc2VglLQlNDMXS1JKmTropH1xligJD5oJ1XfhjIuTW/GJdA3wGYGlqydfBX1NkIMNJUu1QkeQeC9S/5WsvIL6UazYKIQqEEBeBM6jJ/jZCiF+EEIFCiEBXV9eqxixVU2hSKK1dW2OqMdV3KHezcoLRCyAt+sb4e7G+IyqTfR173u3wLkcTjvJL+C/6DkeSSlQkuQcBTRRF8VEUxRx4BLhza94GoDeAoiguqMM0F7QZqKQdWflZnEk7Q7u6el4CWRbvrjDgczj7F+ydpe9oyjWi8QiG+g7lp7CfCEoI0nc4kgRUILkLIQqBV4BtwGlgtRAiQlGUGYqiDLtx2TYgRVGUU8AuYKoQIkVXQUtVF5YcRrEorlmTqaXpMAnaPAq7P4fImr0aRVEU3u/0Pg1sG/D23rdl7XepRqjQOnchxJ9CCD8hRCMhxKc3HvtQCLHpxp+FEOJNIUQLIYS/EGKVLoOWqu7E1RMoKLR2ba3vUMqmKDBkjrr+fe1zcCVM3xGVycrMilk9ZpGSk8Kik4v0HY4kyR2qtc3plNM0tGuItZm1vkMpn5kFjP8/tUzBynFw7c6pnpqluXNzBvoMZGXkSrmxSdI7mdxrmdOpp2nu3FzfYVScrTs8tlo9sGTlw+rnGuzFNi+SX5TPb+G/6TsUqZaTyb0WSc1NJSE7gRZOLcq/uCZxawljF0PCSdj5ib6jKZO3vTfDGg3j9zO/k5Bd8w8ikYyXTO61SGRKJAAtnA0suYNaYOyBiXD0F0gI13c0ZXq+zfMIBD+f+FnfoUi1mEzutcip1FMANHNupudIqujB98HSCbZOqdHr3z1tPHnY72HWnl3LwfiD+g5HqqVkcq9FTqecxsvGCztzO32HUjWWjvDQDIg5DGH/p+9oyjS53WQaOTRi2t5pcnhG0guZ3GsRg5tMLU2b8VC/I+z4ELJr7lYKKzMrvu71NXlFeUzdM5WC4gJ9hyTVMjK51xLX8q8RkxljmOPtt9Jo1PXvuRnw5xR9R1MmX3tfpneZzvHk4ywIX6DvcKRaRib3WuLmZGpzJwPvuYO6eqbXNIhYByfX6juaMg30GUgXjy5sOb9F36FItYxM7rXEzZK0Bj8sc1PX18GzPWx9CzIT9R1NmXrV78XlzMtEZ0TrOxSpFpHJvZY4lXIKd2t3nCyc9B2KdpiYqodrF+Sox/PV4NUzPbx6ALA3dq+eI5FqE5nca4nTqaeNY0jmVq5+0P9TiNoBe77QdzT35GnjSWOHxjK5S/eVTO61wPWC60RnRBvPkMytAidCwOOw50s4vVnf0dxTd6/uhCSGkJVfs8snSMZDJvdaIDI1EoEwvLIDFaEoMPhrtXrk+hcgqWYed9fDsweFopBDVw7pOxSplpDJvRaISIkAoKVLSz1HoiNmFjBuOZhZwdIRcPWcviO6S0DdAGzNbeXQjHTfyOReC0SkROBm5YaLpYu+Q9Ede094ahMUF8LiITUuwZtqTOnq0ZV9sfsoFjV38lcyHjK51wIRVyMMf/NSRdRtDk9v+S/BXz6s74hu08OrBym5Kaw7t07uWJV0TiZ3I5eVn0X0tWhaOhvpkMydbiZ4E3NYOAD+mgb52fqOCoCe9XvibefNx4c+pu+avswLnUdBkUzykm7I5G7kbm5eMtrx9tLUbQ4vHYIHnoUjP8KPXeDCHn1HhZ25HRuGb2B+n/m0dm3NLyd+YfKuyeQU5ug7NMkIyeRu5CKuqpOptWJY5lZ1bGDwbHh6KygaWDoMNr0KGbEghN7CMtGY0MOrB/MenMeHnT9kf9x+XvznRblEUtI6U30HIOlWREoEHtYexrMztbK8u8ELB2D353Doezi2VF1V4+QLHgFQv5N6jZPPfQ9trN9YbMxs+N++//H8P8+zsP9C6pjUue9xSMZJJncjdyrlVO0akimNuRX0+0QtF3zpAKReUFfTRG6F0OWAAgO+gE4v3PfQBvoMxEQx4a09bzHj0Axmdp2Joij3PQ7J+MjkbsQy8jK4nHmZkU1G6juUmsGthfpxU3ExpJyDf2fA3+9A+iXoNxM0Jvc1rH7e/Xgx/UV+DPuR5k7NebzF4/f1/pJxksndiN2cTK114+0VpdGAa1N4eClsew8O/wBxx6DpQHWoxqPtfUv0L7R5gTOpZ5gdPJumTk15wP2B+3JfyXjJCVUjdnMytdYsg6wqjQkM/EItY3A9Bf75CBb0UVfZnN1+XyZgNYqGz7p/hru1O98e+1bn95OMn0zuRiwiJQIvGy/s69jrOxTD8MCz8GowTDkHI3+GonxYORaWjYRr8Tq/vbWZNU+2eJKw5DBCk0J1fj/JuMnkbsROpZySQzJVYVMX2jwCLx1RJ1pjg2HRQEi7pPNbj2g8Avs69iw+uVjn95KMm0zuRiojL4O4rDjjLPN7v5iaQ6cX4amNkJMOiwZBynmd3tLKzIpxTcexK2aXPLlJqhaZ3I3UmdQzgJGcmapvnu3VkgaFOWqCz4jT6e3GNxuPmcaMZaeW6fQ+knGTyd1IRaaqB2I3dWqq50iMhLs/PLVFrVPz++NQkKuzW7lYujC00VA2nt9I0vUknd1HMm4yuRupyNRIXC1djbvM7/3m1gJG/Qzxx2DLGzpdRfNMq2fQKBom75S1Z6SqqVByVxRlgKIoZxRFiVIUZVoZ141RFEUoihKovRClqjideppmTs30HYbxaTYYer0LYSvh4Dyd3aahXUO+6P4FESkRvLf/PVkDXqq0cpO7oigmwHxgINACGK8oyl1LMBRFsQVeA45oO0ipcnILc7mYcVEmd13p8Ta0GA47PoB93+jsNg82eJApgVPYcWmHXPsuVVpFeu4dgCghxAUhRD6wChheynWfALMA3Q1GShUSlR5FkSiSK2V0RaOB0b+B/1j492PY8ZHOhmieaPEEo5uMZtHJRcRl6XYiVzIuFUnunkDMLV/H3nishKIobYH6QogtZTWkKMokRVGCFUUJTk5OrnSwUsXcLDsge+46ZGIGI3+BwAlwYC5seR2Ki7R+G0VReL718wCsP7de6+1Lxqsiyb20EnUl3RRFUTTAHOCt8hoSQvwihAgUQgS6urpWPEqpUiJTIrE1s8XLxkvfoRg3jQYGfwPd3oSQxfDHBCjM0/pt6tnUo5tnN9afW09hcSEA+UX5zAmZw4X0C1q/n2QcKpLcY4H6t3ztBdy6F9sWaAXsVhQlGugEbJKTqvoTmRZJU6emsnTs/aAo0PcjtZrkqQ2wchwUaH91y2i/0STlJLEvdh8APxz/gYUnF/Lu/ncp0sE7BsnwVSS5BwFNFEXxURTFHHgE2HTzSSFEhhDCRQjhLYTwBg4Dw4QQwTqJWCpTUXER59LOySGZ+63LqzB8PlzYDRteVMsJa1EPrx64Wrqy9txawpPDWRSxiCaOTTiVcoo/zv6h1XtJxqHc5C6EKAReAbYBp4HVQogIRVFmKIoyTNcBSpVz6dolcgpz5GSqPrR9HB76GCLWw+7PtNq0mcaMEY1HsC9uH+/sewdXS1eWDFhCB/cOfBv6Lam5qVq9n2T4KrTOXQjxpxDCTwjRSAjx6Y3HPhRCbCrl2l6y164/NydTmzrKnal60eU1aPsE7P0Kjv+fVpse1WQUxaKYmMwYPu7yMbbmtrzX8T1yCnOYEzJHq/eSDJ88rMPIRKZGYqYxw9fBV9+h1E6Kok6ypl9Sh2cy49UJVy3Mf3jZevGw38PYmNvQ1bMrAL4OvjzZ4kkWnlzI5WuXebrl0/Ss3xONIjef13aK0NNJ8IGBgSI4WHbwte257c9xLf8avw/5Xd+h1G752bDpNTj5BzQbAiN+BAs7ndyqoLiAVZGrWH5qOfHZ8QS4BvBrv1+xMLXQyf0k/VIUJUQIUe6CFfnr3YgIITiTekZWgqwJzK1h9ALo/zmc+QsWDoBrV3RyKzONGU+0eIKto7byUeePOJ58nE8Of4K+Om5SzSCTuxFJvJ5IWl6arARZUygKdH4JHl+rDtP89hAkn9XZ7Uw1pozxG8NLAS+x6fwmVkau1Nm9pJpPJncjcrOGu1wGWcM06g1Pb4XCXFjYHy7u1entnm/9PL3q9+KroK8ISgjS6b2kmksmdyMSmRqJgoKfo5++Q5Hu5BEAE7eDtQssGQY7Z0JRoU5upVE0fN7tc+rb1mfqnqlczbmqk/tINZtM7kYkMjWSBnYNsDaz1ncoUmmcfGHSbgh4TF0quWggxOvmIGwbcxu+6fUN2QXZvL337ZKyBVLtIZO7EYlMjZTr22s6c2sYMV+tKpl6Hn7pBX9MhLRord+qiWMTPuj8AUEJQcw/Pl/r7Us1m0zuRiIzP5PYrFi5M9VQ+I+B145D9ykQuRV+7AaRf2r9NsMaDWN0k9EsCF/AmrNryr0+vyifDVEb5FCOEZDJ3UjcnEyVPXcDYmEHfT6AV4LAuRGsGg+7v9B6XZppHabR3bM7Mw7NYG7I3DJPddoQtYEPDnxA/z/6M+PQDGIzY7Uai3T/yORuJM6kyZUyBsuhPkz4G9qMh92fw5qnIP+61pq3MLXguwe/Y6zfWH47+RtT90zlWv61Uq/dF7sPd2t3hjUexsaojTyz7Rl5xJ+BksndSESmRuJs4YyrlayTb5DMLNVdrP1mwunNsGQIZCZqrXlTjSkfdPqAN9u/yb+X/2XEhhHsvLzztmvyivI4knCE3vV781Hnj3i/0/skZCdwPv281uKQ7h+Z3I1EZGqk7LUbOkVRSwePWw5Jp+HX3moJg33fwLl/qn3Sk6IoPNPqGVYMXoGThROTd03mm+D/zoANTggmpzCH7p7dAQh0V3e4ByfKMiGGSCZ3I1BQVEBUepTcmWosmg+BZ/4ER291svXfj2HFaJjXDg7Nh9yMajXf0rkl/zfk/xjqO5Slp5aWjKvvjd2LhYkFD7g/AICXjRduVm4EJ8jkbohkcjcCFzIuUFhcKGvKGBOPtmqCf/s8TIuBsUvAth5s+x983Uzt0V8Jq3LzZhozJrebjKIoLI5YjBCCvbF76VCvQ0nBMUVRCHQPJDgxWNapMUAyuRuB/XH7AWjt2lrPkUg6YWEHLUeok66T9kCr0XBiNfzcA1Y9BumXq9Ssm7UbwxsNZ/259QQnBhObFUsPzx63XRPoFkhqbioXr10stQ25OarmksndCGy9uJUA1wA8bDz0HYqkax4BMPx7eOs0PPg+nN8J33eAPbMgK6nSzU1oNYFCUci0vdMA6O7V/bbnA91ujLvfMTSTU5jDe/vfo/3y9gxcO5A3dr3BxqiNsodfg8jkbuDOpJ7hXNo5BvsO1nco0v1k6Qg9psLLR6FJX9j1KXzdVK1bc2wp5GVWqJkGdg3o37A/STlJNHZofFcHoaFdQ1wsXW6bVL107RKP/fkYm89vZkTjEbRwbsHp1NO8f+B93tj9Bhl51ZsTkLRDnsRk4LZe3IqpYkp/7/76DkXSB4f6/62uObkOTq6FTa/CX+9Ay5HQdBDU7wA2de/ZxET/ifwV/Rc9vHrc9ZyiKAS6BRKSEIIQghNXT/DCjhcw0ZjwY98fS06EKhbFLDu1jLnH5jJ602h+6PuDLGCnZ/IkJgNWLIrp90c/mjo1ZX4fWTtEAoSA2GAIXaYm+/wbPXhHb3WTVPtnwNbtrpcdSzxGE8cm2Jrb3vXc75G/M/PITL7q+RUzDs7AwcKBBf0WlDoMGJESwaTtk+jm2Y0ve3yp7e9OQp7EVCuEJIaQeD2RwT5ySEa6QVGg/gMw7DuYGgUTtqsbo5x81d2vc1rC+hfvmoRt59au1MQO/613n7pnKrbmtvzW77d7zu+0dG5JT6+eHIw/SFE11+VL1SOTuwHbemErVqZW9G7QW9+hSDWRmQU06KhujHpiPbwSAoETIGIdfP8A/DujQmPzvva+1LWsS12ruizot4B6NvXKvL6bZzfS89KJSInQ1nciVYFM7gaqoKiA7Ze206dBHyxNLfUdjmQIXBrDoFnwagg0Hwb7vob5neDC7jJfpigKiwYsYvWQ1dS3q1/ubbp4dEGjaEqW6Er6IZO7gQpKDCIzP5OHGj6k71AkQ2PvBaN/hYk71Jo2S4fD1illFitrYNcAZ0vnCjXvYOFAK5dWMrnrmUzuBmp3zG4sTCzo5NFJ36FIhqp+B3h+L3R8EYJ+Vc93TY/RStPdPLtx8upJUnNT73pOCCHXw98HMrkbICEEu2N208mjkxySkarH3AoGfgGPrlFPg/q1N1w6VO1mu3t2RyA4GH/wtsfzivKYuH0iMw7PqPY9pLLJ5G6Azqad5Ur2FXrXlxOpkpb49YNn/4U6drBkqDrZWo2a8i2cW+BYx/GuoZnPj3xOUEIQf5z9g/Dk8OpGLZVBJncDtCtmFwpKqZtOJKnKXP3guX/VIwD3fQ3zO8KpTVU6GUqjaOji2YWDcQdLDvvYGLWRtefW8ljzx3CycGLOsTlyeEaHZHI3QLtjduPv6o+LpYu+Q5GMjaUjjPwJnv5TPcx79RPwY2cIXQGF+ZVqqrtnd9Ly0hi+YThv732bTw5/Qgf3DkwJnMLzrZ8nKCFITrrqkEzuBiYxO5GIlAg5JCPplndXeGEfjPoVFBPY+BJ82wYOzqtw3Zq+DfvyWtvX8Lb3JiQxBBdLF77s8SWmGlPG+o2lvm195hybIzc76UiFassoijIA+BYwARYIIb644/k3gWeBQiAZmCCEuKTlWCVgT+weAHp59dJvIJLxMzGD1g+D/1iI+gcOfAvb34e9X0HbJ9QNUc6N7vnyOiZ1eK71cyVfCyFQFAUAMxMzXmv7GlP3TuXv6L9l4TsdKLfnriiKCTAfGAi0AMYritLijstCgUAhRGvgD2CWtgOVVNuit+Fp40kjh3v/p5IkrVIUaPIQPL0Fnt0JjfrAkZ/Uk6EWD4H9c9R6NkUF5TSj3PZ1P+9+eNt5s/zUcl1GX2tVpOfeAYgSQlwAUBRlFTAcOHXzAiHErluuPww8rs0gJVVIYghHE47yRvs37vqPIkn3hVd7GLtIPbz72FI4+Qf8M119ztQC3FqCe2uwdABRDChg7QI27mrxMo8A9R0B6qTr+Gbj+fzo55xIPiEPm9GyiiR3T+DWnQ2xQMcyrp8I/FWdoKS7CSGYFzoPF0sXxjcbr+9wpNrO1g16TlU/spIheh/EhahH/0WsU5dRKhoQRXDraU3mNtCwi1r+oPXDDG88nO9Cv2Nl5EqZ3LWsIsm9tC5iqeuXFEV5HAgEet7j+UnAJIAGDRpUMEQJ4PCVw4QkhvBuh3flxqUbCoqKib6aTUZOATYWptjUMcVEoyAEmJlocLWto+8QawcbV2g1Sv24kxDqgd5ZSZB8Gi7uhfO7YNMrsPMTrDu+wAjvgfx+fgNTAqfIFWBaVJHkHgvcWi3IC4i/8yJFUfoC7wE9hRB5pTUkhPgF+AXUeu6VjraWEkLwfej3uFu7M8ZvzH27b/r1fEIvp5OcmUdyVh55hcUogIlGwc/Nlg4+TjhZm9+XWLLzCgmKTuXUlWtEXsnkbGIm55OzKCi6949R2wYOjH+gAUPa1MPKXJ5LoxeKog7RWDqo6+hbDFcT/oXd6gTtvx/ziJU9K9zsWXNiIS92fFvfERuNivzEBwFNFEXxAeKAR4BHb71AUZS2wM/AACFE5Q9ylMq0L24fJ66eYHrn6Zib6DaZFhcLDpy/yurgWLZFJJBfWPYGlsZ1bWjpYUfzenY0dLLC0twE6zqmNHO3xdbCrEoxFBQVcyYhkwtXszmflMXRi6kEX0otSeSeDpY0dbeld7O6NHWzxdHanOy8QrJyCykSAo0CqdkFrD0Wy9trT/Du+nAaOlnh62pDPXsL7CxNsbUww8xEg4kCJiYaTDUKphoFK3NTHK3NcLI2x8WmDk5W5mg0cn5DqxQFGvVWP66E4X3gW7om72NVxGIc4o7TpP1z+Lq1wbGOo5xbqoYKncSkKMogYC7qUsiFQohPFUWZAQQLITYpivIP4A9cufGSy0KIYWW1KU9iqrgX/3mRs2ln+Xv035hpqpYwy5OWnc+akBhWHLnMpZTrOFiZMSLAk4Gt3PFwsMTFpg6W5iYA5BUWER6bwZGLqYRcSiPyyjXiM3Jva8+2jinjOzbg6S7eeDhUbBjpen4hq47GsGDfhZL2FAWautnS08+Vbk1caO3lgL1lxf4OhBAERaex52wSF5KziUrKIjkrj8zcQoqKK/bG0USj4GpThxYedrTxcqBNfXv8Pe1xtpFDPtoUdv4vXjvwHqnivxU3liYWuNvUw8nCCTtzO5wsnOjn3Y/O9TrX6qRf0ZOY5DF7NVxCdgL9/ujHpNaTeKXtK1pt+0pGDltPXOHf00kERadSWCzo4O3EY50aMKCVO3VMTSrcVvr1fK5k5HI9v4hrOQWsD41ja/gVFGBoGw8m9fCleT27214jhCA2LYdDF1I4GHWV3WeTSb9eQAcfJx7r2IBm7nY0dLbCwqzicVSEEIKcgiIKCgVFQlBYXExRsaCwSJCdX0hadgGp2fmkZOeRdC2P+IwcwmMziErO4uZ/F08HSx5sVpdXH2xMXTsLrcZXWwkhSLp8gLP7PudSUhjxZmZccfAkzc6da0oxCdkJZOZn4mPvwxMtnmBk45GYamrfcJtM7kbip7CfmH98Pn+N+gsvWy+ttBmTep0fdp/nj5AYCooETd1sebB5XYYHeNDM3a78BiooNu06C/dHsyroMtfziwio74CjlRnmphpSsvI5k5BJZp66ksLFxpxujV14onND2jd00loM2pSZW0B4XAYn4zIIi8lg+6kETDUaJnbz4dnuPjhY3Z/5h1oh5TyELILQ5eqEbKeXyO8xhW3x+1lxegURKRE0cWzC/zr8r+QYwNpCJncjUCyKGbRuEF62Xizot6Da7eUXFvPtv2f5ec8FNIrCww948Ww3X7xdrLUQ7b1lXC9g2eFo9pxNJregmPzCYuwtzWjqbktTd1se8HbCz83G4N5qX0rJ5uvtZ9kUFo+FmYaRbb14uos3Td1LP4tUqoKcdPjnIwhZDA4NYeAshF9/dl7eyaygWcRnxzOu6Tje7fAuJhrtvsOrqWRyNwKH4g8xacckZvWYxUCfgdVqKyopizd+P054XAaj23kxtX9T3O3lcII2RCZcY/GBaNaHxpFXWMyTnRvyzoBmWNepfUMGOhN9ALa8DlfPQpN+MOALcuw9+D70e5aeWsqwRsOY0WVGrUjwMrkbgbf3vM2B+APsfHgndUyqNoEnhGBVUAwfb47A0syEz0f5M6BV2QccS1WTlp3PdzvPsfhgNJ4Olnw20p8efq76Dst4FObD0Z9h95dQkA1+AyBwAj9lRzE/7AeG+A5hZteZRp/gZXI3cBl5GfRe3ZuxfmN5t+O7VWsjp4D/rQtna/gVujV24euH2+AmJ/90Ljg6lal/nODi1Ww6eDvxWp8mdG3sbHDDTjVWZqJa2yZ0GWQng0MDfvEJYF76cVq7tOZ/Hf9HS5eW+o5SZ2RyN3Crz6zmk8OfsHrIapo7N6/06y+nXOfJhUeITcvhrX5Neb6Hr1yvfR/lFhSx6uhlftxznsRreXRv4sKsMa2pZy93F2tNYT5EblHH4y/uYYuNDbNdXEhVihnj0Ytp7d/A3LquWpfeiH6xyuRu4J766yky8jJYP3x9pXt8EfEZPLUwiMLiYhY8GUigd81cfVIb5BYUsfLIZb7adgZTE4VPhrdieICH7MVrW+oFOL6SzLN/80N+DMvt7Xg6/RpvpaWDmRU4+YKTj3ptVhJcTwErZ7Cvrz7n3RXqdwKzmv/OViZ3AxafFU//tf15te2rTGo9qVKvPXj+Ks8vDcHWwpSlEzvQuK5cuVETRF/N5q01YYRcSsPf054J3bwZ7O+Buak8L0frspL4ZN//WJ10hF/qDaBzkQmkXVR/ASgmai0cSyc1wadfhoxYtcCZSR2o10atUe/UCOo2A7dW6iodTc35d5LJ3YAtCF/At8e+rfTa9o3H45iyJgxvZ2uWTOhQ4Z2h0v1RVCxYHRzDb/svEpWUhZO1Od2buNCtsQsNnKxIu55P2vUCrOuY4mFvgaejJe52FrKXXwU5hTk8suURMvMzWTtsLY4Wjve+OC8TLh2EC3sg4YS6xj7zlvJZFvbQehx0mAQuTXQffDlkcjdgIzeOxMbMhmWDllXoeiEEP+w+z1fbztDJ14mfHw/E3ko3ZQqk6isuFuyLusq6Y7EciLrK1ax7n03qYmNOGy8HOvk68/AD9StcekGCyNRIHt36KP4u/rze/nUCXAMq/osyPxuSIiExXF2GeWoDFOWDd3e1Jo5PT7WXb3L//z1kcjdQZ1LPMGbzGN7r+B6PNHuk3Otz8ot4b30460LjGB7gwawxrStVNkDSr+JiwZnETK5m5eFkbY6jlTlZeYXEpecQk3qdsJgMjsekcT45G5s6pjzWsQFjA+vj62ItJ8grYP259XwZ9CXZBdn42vsyxHcIPbx64OfoV7l3RFlJH3v2cQAAExhJREFUELJErVWfdOOcIo0pOPqAix/49oSmg8ChftntaIFM7gZqTsgclkYsZefDO8t+K4laRuD5ZSGcTrjG6338ePXBxvI/vJGKiM/g5z0X2HIinmIB9pZmtPayx9WmDnXMNNjUMaV5PTv8Pe3xdbXBRP4clLhecJ1t0dtYe24tYclhALhbuxPgGkAL5xa0d2tfuYNCbh5OkhihbqpKjIDU8+pzbv7QoCN4BkL9DupkrZaH1WRyN0CZ+ZkM2zCMFs4tmN9n/j2vKyoWrDx6ma/+jkQA3z3Slt7N6t6/QCW9iU27zsGoFEJj0giLySAzr4C8gmIycgrIu1Ge2cWmDuMe8GJ8hwZ4OVrpOeKaJfl6Mvvi9rE/bj8RVyOIz1bH1ie0msBrbV+r+gaoq1FwZiuc2wHxoZCfpT5u5wU+PcCunlrHvrhQncjNTFAncRt0UXv9noFgUrEdzTK5G6CPDn7EhqgNLBu47J49ifDYDN7bEM6J2Aw6+zrz+Sh/ndeGkWq+omLB+eQsTsRm8PfJK+yMVI9VaFzXBm9na3xcrWlb35EHvB1lueJbpOWmMS90HmvOrqGnV0++6P4FNuY21Wu0uEjt0V86qJ48Fb0fctPV5xSTG2fKukFxASScBIR6vmy/T6HZ/7d359FVlncCx7+/u2UjOyGEBAQEWWRX6KjVYh1bLAy21AXsVJ2xdno67YznjKd6tBtdHJ32tNM57WnHsY7rQGutQi1atdoW0BZQHA0gixDIAiGEm/Umd3t/88f7kgkIIcSb7eb3Oeee+973ffPc5z5588tz32dbetaavgX3YWZjzUa++Psvctus27jjojvedzyaSPKjl/fyn3/aT1FOiK8uncHyudZf2pxebVMHT22rprK2harGdg41Rogl3Zp9eUEWmUFf11KEM8flceG4fOaPL6CiMGvEXVOqytrda3lgywOMGzWOuxfdzRUVVwzMm0eOw/5X4Y/fc5chnLwYFtwMFQvdPvin+V1YcB9GmqPNrFi3gryMPH6x7BfvW21pR10zd6x9i71H27jh4gruXTrTek2YcxJNJKmsdRdY2XOklXhSiSUd6po62FPf2rXK1ehRGSyYUMCcinwuHJfvTtM8QEspDrZtR7ax+vXVVLVUsbhiMddMuoaS7BLKcspSNt32GSUTsO1h+MN90BF29+WWwbRrYMbfuL10vJ45FtyHkW+89g3W7VvHk0uf5MLik+fEeHZ7LXf/+m3ys4Lc/+k5XDnN7q2b1IolHPbUt7K9uontB8O8eShMVWMEgIBP+OsZpaxcNJ7Lp5akfUNtPBnniV1P8NP//SkdiY6u/ZeVX8aX5325/+esScbdBtqarW6j7d6X3UnSsopg1qdh7kpk/EIL7sPBjmM7WPXbVdw882buXHhn1/5E0uG+De/y8OYDLJpUxE9uWkBJrt0rNQOjtTPOzroWfv/uUX71Rg3H22NMH5vLvUtncPnU9J/pMhKPcLj9MA0dDVQeq+SRHY/QHG1mccVibpx+I5eUXTIws0/GO2Df76HyV/DuBkhGkdUtFtyHOlXl5udv5lDrIZ771HPkhtypApojcf7xf95k075j3HrpRO5dOoOgf+gMfzYjSzSR5IXKI3z/xd1UH+/gymkl3H75ZP5qcvGI6XrbFmvj8Z2Ps+bdNYSjYcpyyphRNIOORAfRZJTSnFLOzz+fCwov4OKxF3f9LadUZzPsXIdcdIsF96Fuw/4N3LXxLlZfupoVU1cAsL+hjc89uo3qcITvfnI2Nyzs/0ERxvRGNJHkkc1V/PjVfbR2JijLz2T5vHEsmz2OWeV5I6IhNpaM8Ur1Kzy791mOdhwlO5BNyB+irq2O2rZaAAISYN6YeVxWfhkLxy5kZvFMaltref7A82yq20SGP4OCjALG5YzjqvOuYm7JXHzS+8qb3XMf4iLxCMufXU5RZhFrlq7BJz6efrOW1et3EAz4+NnfXsSiSTaboxl6OmJJXt5VzzPba/njngaSjjKhKJurZoxhwYRC5k8ooLxg5PW6icQj7Gzcyea6zWys2cju8G4AMvwZRJNRBGFOyRz84qcp2kRNaw0xJ0ZpdikXFl+IiOCoQ1u8jaZoEwknwbLJy7jhghsoyCzoeh8L7kPcA1se4IldT/DokkeZOGoW9/z6HV7YcYRFE4v4wY1zbfCJGRbC7TFe3HmE375zhC0HGumMu90t8zIDTC3NZUrJKCoKsxhXkMXY/EwKsoNd0yxkBtN7mozGjka21W9j+9HtlOWU8fGJH2dsztiu4+3xdl6tfpXfVf2uq9YPkBvMpSCjgLZ4G1uObCErkMW8knkc7zxOfaSeTas2WXAfqv58+M/c/uLtrJq+irlZf8fX11XS0hnnzo9N43OXT077HgkmPcWTDruPtLL9UJjd9a3srW/jvYa2M06MlhX0U5QTYsqYUcwuz2dWeR5zxxfYTJjd7A3v5bGdj7H7+G5Ks0spzSnla5d8zYL7UNQSa2HFuhWEfJlURO7hxR3u/N7fu34O08fmDXb2jEm5zniSw82dHGnupMmb1jgciRFuj3GsLcq7R1rZe7SNpOPGojG5Gcwuz2dqaS4XlI5i0ugcxhdlU5wTsqBP72/L2PLsAyjpJPnO69+hIdKAv/6f2NfSzF1LpnP75ZMIWG8Yk6Yyg34mjc5hUg/TZHTGk+w63MLbNc28Vd3EzroW/rS3oWtwFUBOyM95xTldaZ1XnM3E0TmcV5RNSW6GBf5TWHAfIG8dfYtvbP42+1v2EG24msmhqaz50nymjbWVkozJDPqZP6GQ+RMKucXbF086HGxs52BjhEPHIxxsjFDV2E5lXTMv7DjSVdN3f97H+MJsikeFyM8Kkp8VZPSoDEpyMyjIDhLy+wkFfCQdJZpI0hlPEokl6YgniSUcgn4fQb94zz5Cfh+5mQEKst30fD533i8RCPl9hAI+cjOC5GUFhuw/FQvu/cRRh12Nu9hUs4UX3tvIvratOPF8Ykdv4rOzl/OVJdPTvkHJmA8i6PcxZUzuaZeKjCcdasMdVDW2U+0F/upwhHB7nIONEcKRGI1tMRJO/952DviEwpwQRdkhCrKDFGaHyMsKkJsZpCAryOjcDIpzQpTkZjAmL5OSURkDtrSiBfcUa4m1sHbn0zy5aw3HY4cBcGLF5MQ/xk3TbmXl9VMZmz/0F+E1ZigL+n1MHJ3T44yojqM0d8Rp6ogTSzjEEg4+n9uQmxn0kxX0kxXyE/L7SDhKPOl4D3fenZaOOOH2GM0dcRQQQKErrZbOOMfb3X8i4UiMpkic9xraaO1M0NoZpz2WPG2+xuRmUFGYRUVhNuOLshhfmE1hToiATwj4feRlBijKCVGQHSI3I9DngWIW3FOgpbODtZUv8/yBF9jf/hcciZKITCS78zMsOf/D3DB/FnMq8ofs1zdj0pHPq1X3ZuKzkE/eV6Mu/4BrEEcTSRrb3Ebjhlb3Ud8SpbYpQk24g+3VYX77zuGTbi+97zOIuzBLYU6IsvxMxub1Pk8W3PvgWFuUt2uaeP1ADS/XPkODvIwE2tFENtmJi/hI2XJuuvJS5lYUjJjh2caYk2UE/IwryOpxofpE0uFwcyfNHXEcVeJJpaXD/UYQjrjfGpoicRrboxxp7uS19471+v0tuPcgkXSoCXew92gbuw63sKOumcraFg5HqggWvEGwYAsS7KQ8tIBl513HytkfpSTXFs4wxvROwO9jfFE25zLJiNzTy7R7lZjIEuBHgB94SFXvP+V4BvAYcBHQCNyoqlW9z+7gUVXqmjvZW9/KvqNtHDjWTk24g9qmDneBA23Hn1WNP6OBgtwW/OMOkaMH8IufK8oX84V5n2dm8czB/hjGGHOSswZ3EfEDPwGuBmqArSKyXlV3djvtNiCsqlNEZCXwAHBjf2S4L6KJJOH2OMfaotQ1uS3sB45F2FPfyp4jrbRGE4AiwTB5ecfIzwsTLD7GmDFVNCdrcJtRQALZTC6YwpJJX+ETkz5BcVbxoH4uY4w5k97U3BcB+1R1P4CIrAWuBboH92uBb3rbvwJ+LCKiPQx/PdhUzz+s+yHg9h9VwFF115BVxVEl6SiOoyRVcRxIqIPjON5zkoSTJOE4OOqQdCCp7rajDqpJ4holoVEc4t3e2QFJEgwoORl+Si8IMCGUpDFWRXuiBQcIA8WZxcwqms68McuZN2YeUwqmUJxZbI2ixphhoTfBvRyo7va6BvjQmc5R1YSINAPFwEl3/0Xk88DnATInZvJa08N9zDbg8x6nJQg+AmSS6csgKCH8PsHvEwI+P9nBEBmBECJJIEnAF2Bh+dXMLJ7JtKJpTMqfRF7IpgIwxgxfvQnup6uqnloj7805qOqDwIMA8xbM15euewUAnwh+EXct2LNUjH3iwy/+k56716YFsdq1MWbE601wr4GTGnMrgLoznFMjIgEgHzje4xv7/JTkFJ5DVo0xxvRWb8bBbgWmisgkEQkBK4H1p5yzHrqmhLgOeKWn++3GGGP611lr7t499C8Bv8PtCvmwqu4QkW8B21R1PfBz4HER2YdbY1/Zn5k2xhjTs171c1fVDcCGU/Z9vdt2J3B9arNmjDGmr2wScWOMSUMW3I0xJg1ZcDfGmDRkwd0YY9LQoC2QLSKtwG7vZT7QnKKkR2paozllRPAHSKuv0iGts5VjOnzGgUyrr9flmQzVzzmQf9/TVPXs63Oq6qA8cLtRnth+MIXpjsi0upfnUMrXcEvrbOWYDp9xgNPq03U5DD/ngP1997ZMh8ptmd9YWpaWpZWWaaXaUP2cQy6twbwts01VLx6UN09DVp6pYeWYWlaeqdG9HHtbpoNZc39wEN87HVl5poaVY2pZeabGg2fYPqNBq7kbY4zpP0PlnrsxxpgUsuBujDFpqN+Cu4ioiDze7XVARBpE5Ln+es+RQEQ+5ZXt9MHOy3Bj12T/EZG2wc5DOjlbeYrIH0Skx0bV/qy5twOzRCTLe301UHsuCXgLf5iTrQI2cY7TKnsLnY90H/iaNGa46O/bMs8DS73tVcCaEwdEZJGIvCYi273nad7+W0XkKRH5DfBiP+dvWBGRUcBlwG14wV1EFovIn0TkGRHZKSI/ExGfd6xNRL4lIn8BLhm8nA8pfbkmN4rIvG7nbRaROQOa62HAuxaf6/b6xyJyq7ddJSKrReRNEXnHvnmeXU/l2Rv9HdzXAitFJBOYA/yl27F3gStUdT7wdeC+bscuAW5R1Y/2c/6Gm08CL6jqHuC4iCzw9i8C/gWYDZwPrPD25wCVqvohVd004LkdmvpyTT4E3AogIhcAGar69oDlOH0cU9UFwE+BOwc7M+muX4O79wcwEbeGtOGUw/nAUyJSCfwQuLDbsZdUtcc1WEeoVbjBCe95lbe9RVX3q2oStyb6YW9/Enh6YLM4tPXxmnwKWCYiQeDvgUcGJLPp59fe8xu4vwPTjwbinvZ64PvAYqC42/5vA6+q6qdEZCLwh27H2gcgX8OKiBQDH8W9Z6y4Sx4qboA6dbDCidedXsA3Jzuna1JVIyLyEnAtcANgIy5PL8HJFcbMU45HveckAxN7hruzlWePBqIr5MPAt1T1nVP25/P/jVm3DkA+hrvrgMdU9TxVnaiq44EDuLX0Rd4C5j7gRtwGV3NmfbkmHwL+A9hq3yrP6CAwU0QyRCQfuGqwMzTMfaDy7Pfgrqo1qvqj0xz6N+BfRWQzbi3U9GwV8Mwp+54GbgJeB+4HKnED/qnnmW76ck2q6htAC/DfA5DFYcXr1RZV1Wrgl8DbwJPA9kHN2DCVqvK06QeGORFZDNypqssGOy/pTETG4d6mma6qziBnZ0gRkbnAf6nqosHOSzpIVXnaCFVjzkJEbsbtVXOvBfaTicgXcBvxvzrYeUkHqSxPq7kbY0waSlnNXUTGi8irIrJLRHaIyD97+4tE5CUR2es9F3r7PyMib3uP17yvIifSWiIiu0Vkn4jcnao8GmPMSJGymruIlAFlqvqmiOTi9mX9JG6vg+Oqer8XqAtV9S4RuRTYpaphEbkG+KaqfsgbJr8Hd2h4DbAVWKWqO1OSUWOMGQFSVnNX1cOq+qa33QrsAspx+wY/6p32KG7AR1VfU9Wwt//PQIW3vQjY5w3KieEO1rk2Vfk0xpiRoF8aVL0BIPNxG6FKVfUwuP8AgDGn+ZHbcOf8APcfQnW3YzXePmOMMb2U8lFi3uRWTwN3qGqLiJzt/Ctxg/uJIfOn+wFr9TXGmHOQ0pq7N/fG08CTqnpiHol67378ifvyR7udPwd35N+1qtro7a4BxndLtgKoS2U+jTEm3aWyt4wAP8dtJP1Bt0PrgVu87VuAdd75E3AnEvqsN8vhCVuBqd5w+hDu1LbrU5VPY4wZCVLZW+bDwEbgHeDEQI97cO+7/xKYABwCrlfV4yLyEPBp3PkTABKqerGX1ieAf8cdAv6wqn43JZk0xpgRwgYxGWNMGrLpB4wxJg1ZcDfGmDRkwd0YY9KQBXdjjElDFtyNMSYNWXA3xpg0ZMHdGGPSkAV3Y4xJQ/8HgZGZdWXbCwEAAAAASUVORK5CYII=\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",
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+ " </tr>\n",
+ " <tr>\n",
+ " <td>2020-01-01</td>\n",
+ " <td>0</td>\n",
+ " <td>0</td>\n",
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+ " <td>0</td>\n",
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+ " <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",
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+ " <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": {
+ "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['2020-10-01':, ['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",
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+ " <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",
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+ " <td>2019-12-31</td>\n",
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+ " cases deaths cases_culm deaths_culm cases_diff deaths_diff \\\n",
+ "2019-12-31 0 0 0 0 NaN NaN \n",
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+ "\n",
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+ "2020-12-14 18023.000000 417.857143 357.762938 372.146458 ... \n",
+ "\n",
+ " admissions_m7 cases_m7n deaths_m7n admissions_m7n cases_m7nd \\\n",
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+ "2020-12-14 NaN 0.711496 0.443383 NaN 31.398955 \n",
+ "\n",
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+ "\n",
+ "[350 rows x 24 columns]"
+ ]
+ },
+ "execution_count": 494,
+ "metadata": {},
+ "output_type": "execute_result"
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+ "source": [
+ "data_by_day"
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+ {
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+ "metadata": {
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+ ],
+ "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": {
+ "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':, ['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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xYzDrqqu+uFOBnx1TX6Cqfgugqk+q6iic7vWBwKxq9w7B6ZI2xrQDlvgZ0/4s4ocuwOpuAv7rto7V5U2cyQRxIhIE/P6Y86FAtqoWichYnJasKm6iVwH8lfpb+xpjHnCHiMSKSAhOi9d8t+sSnPfdB3jQPV7RhDoWAsNEZLrbhfxLoHsd14cCeUCBiAwGfl79pKp+D2QALwKfqGply1kikCcis0UkUES8RWSoiIxpYl31xT0XuFdE4gFEJFxErnR/H+O24vridLUX4YwnrHQW8FEdcRlj2hBL/Ixpf14BLhSRwMoDIhKAM3bv5VrvcqnqRziTLL7Emfjw5TGX/AJ4UETygd/hJIo1xTAMeLUpb6AW/8JJJJcCSTgJStUMYreb+R2ciSGvN6UCVc0ErgT+hDPBIQ5YBdQ2VvBunMQ3H2eM3vwarpl3bEyqWg5cjDO2MAnIxEkOw+sIr9a66otbVd8FHsOZWJIHbMSZ/Q0Q5pZ3CKf7PAv4C1St4xcHvFdHXMaYNsQWcDamHRKRR4CDqvp3D9V/I/BTVZ3oifqbiztOcS8wQ1Wb0nXsEc0Vt4j8Fdilqs82W3DGGI/yyKKgxpiWpapzPFW32z38C6BNJgvukiorcCaWzMIZR/edR4NqgJaIW1XvaobQjDEnEevqNcY0Gzf5yMCZcNGk7taTwGnALpzu14uB6ZW7oJzk2mrcxphWZF29xhhjjDEdhLX4GWOMMcZ0EG1ijF9ERITGxMR4OgxjjDGm2RUUl5GZX1y1cKMqiECgnzdBvt4E+fng4y11lmFOLqtXr85U1UhPx1GTNpH4xcTEsGrVKk+HYYwxxjS7Hz33LTsO5DOgWyheAiJCQVEZ2w/kU1KhlAB9I4J56X/GckrXIE+HaxpARFLqv8oz2kTiZ4wxxrRHOw/mszrlEPdeMJifndXvqHNFpeVsSsvl+z05/OXTbfz98+387eqEWkoypmFsjJ8xxhjjIW+t2ou3l3D5yON3Bgzw9WZUny7cfEZfbjwthvfW7mNXRkENpRjTcJb4GWOMMR5QWl7Bf9fsY/LgKCJD/eu89qdn9sXfx5snv9jRStGZ9qrNdvWWlpayd+9eioqKPB1KhxAQEECvXr3w9fX1dCjGGNMuLN56kMyCYq4e3bveayNC/Lnp9Bj+sXQXv5rcn/5Roa0QoWmP2mzit3fvXkJDQ4mJiUHEZju1JFUlKyuLvXv3Ehsb6+lwjDGmXXhz1V4iQ/2ZNKhhkz9/emZf/rM8mSe+2MlT157assGZdqvNdvUWFRXRtWtXS/pagYjQtWtXa101xphmcjC/iMXbDnL5yJ74eDfsT3GXYD9uOj2GD9ensf1AfgtHaNqrNpv4AZb0tSJ71sYY03zeWbOP8grlqgZ081b3kzP6EuznwxOf21g/0zRtOvEzxhhj2hpV5c1VqYzu05l+kSGNurdzsB//MyGGhRvS2bbfWv1M41nidwL279/PNddcQ79+/YiLi+PCCy9k+/btng7LGGPMSWzNnkPszijkqjGNa+2rdONpMQB8vSOjGaMyHYUlfk2kqlx22WVMmjSJXbt2sXnzZh555BEOHDjg6dCMMcacpCoqlGcX7yLYz5tpw3o0qYzIUH+6BPux86Ct6WcazxK/Jlq8eDG+vr7ccsstVccSEhI49dRTOeeccxg5ciTDhg1jwYIFABQWFjJt2jRGjBjB0KFDmT9/PgCrV6/mrLPOYtSoUUydOpX09HQAnnzySeLi4hg+fDjXXHNN679BY4wxze4PC7fwxdaD3DllEMH+TV9Yo39kiCV+pkna7HIu1T3wwSY2p+U1a5lx0WH8/uL4Ws9v3LiRUaNGHXc8ICCAd999l7CwMDIzMxk/fjyXXHIJH3/8MdHR0SxcuBCA3NxcSktL+dWvfsWCBQuIjIxk/vz53HffffzrX//i0UcfJSkpCX9/f3Jycpr1vRljjGl9L369m38tS+J/JsTw4wkxJ1RWv6gQPt6Y3jyBmQ6lXSR+JxNVZc6cOSxduhQvLy/27dvHgQMHGDZsGHfffTezZ8/moosu4owzzmDjxo1s3LiR8847D4Dy8nJ69HCa/ocPH86MGTOYPn0606dP9+RbMsYYc4I+WJfGHxZu4cJh3fnttLgTXimhf1QIhw6XklVQTNeQunf9MKa6dpH41dUy11Li4+N5++23jzv+2muvkZGRwerVq/H19SUmJoaioiIGDhzI6tWrWbRoEffeey9TpkzhsssuIz4+nuXLlx9XzsKFC1m6dCnvv/8+Dz30EJs2bcLHp118XMYY06F8tzuLu95cx9iYLvztqgS8vE58eaz+Uc5s4J0HCyzxM41iY/yaaPLkyRQXF/PCCy9UHVu5ciUpKSlERUXh6+vL4sWLSUlJASAtLY2goCCuv/567r77btasWcOgQYPIyMioSvxKS0vZtGkTFRUVpKamcvbZZ/OnP/2JnJwcCgpsLIcxxrQ1ZeUV3PXmOnp3CeT5G0cR4OvdLOVWJX4Z9rfBNI41ITWRiPDuu+9y++238+ijjxIQEEBMTAz3338/t912G6NHjyYhIYHBgwcDsGHDBmbNmoWXlxe+vr4899xz+Pn58fbbb3PbbbeRm5tLWVkZt99+OwMHDuT6668nNzcXVeWOO+6gU6dOHn7HxhhjGuuLrQfZl3OEudePolOQX7OVGx0eQJCft03wMI1mid8JiI6O5s033zzueE1dtzExMUydOvW44wkJCSxduvS44998803zBGmMMcZj/rM8hejwAM4dEtWs5YoI/Wxmr2kC6+o1xhhjWsDOg/l8szOTGeP7NHg/3sboHxXCLkv8TCNZ4meMMca0gP8sT8HP24urm7hDR336R4WQlltEYXFZi5Rv2idL/IwxxphmVlBcxn/X7GPa8B5EtNCs28p9fnfZBA/TCJb4GWOMMc3s3TV7KSgu48bT+rRYHdWXdDGmoSzxM8YYY5qRqvLy8hSG9wonoXfLrcjQp2sQPl5iiZ9pFEv8jDHGmGa0fHcWOw8WcONpMSe8Q0ddfL29iIkItsTPNIolfifo3XffRUTYunVrjednzpxZ4w4ftUlLS+OKK65odBw333wzmzdvbvR9xhhjmtcr36bQOciXi4b3aPG6+keG2CLOplEs8TtB8+bNY+LEibzxxhvNUl50dHSjEsVKL774InFxcc0SgzHGmKYpLa/gy60HuTShZ7Pt0lGX/lEhpGQdpqSsosXrMu2DJX4noKCggGXLlvHPf/6zKvFTVW699Vbi4uKYNm0aBw8erLo+JiaGOXPmcNpppzF69GjWrFnD1KlT6devH3PnzgUgOTmZoUOHArBp0ybGjh1LQkICw4cPZ8eOHRQWFjJt2jRGjBjB0KFDmT9/PgCTJk1i1apVgJOMDhs2jKFDhzJ79uyq+kNCQrjvvvsYMWIE48eP58CBAwC89dZbDB06lBEjRnDmmWe2/IMzxph2andGISXlFS06tq+6/lEhlFcoKVmFrVKfafvax84dH90D+zc0b5ndh8EFj9Z5yXvvvcf555/PwIED6dKlC2vWrCE5OZlt27axYcMGDhw4QFxcHD/+8Y+r7unduzfLly/njjvuYObMmSxbtoyioiLi4+O55ZZbjip/7ty5/PrXv2bGjBmUlJRQXl7OokWLiI6OZuHChQDk5uYedU9aWhqzZ89m9erVdO7cmSlTpvDee+8xffp0CgsLGT9+PA8//DD/93//xwsvvMBvfvMbHnzwQT755BN69uxJTk5OMz1AY4zpeLbuzwNgSI+wVqmvckmXnQcLGNAttFXqNG2btfidgHnz5nHNNdcAcM011zBv3jyWLl3Ktddei7e3N9HR0UyePPmoey655BIAhg0bxrhx4wgNDSUyMpKAgIDjkq7TTjuNRx55hMcee4yUlBQCAwMZNmwYn3/+ObNnz+brr78mPDz8qHtWrlzJpEmTiIyMxMfHhxkzZlRtCefn58dFF10EwKhRo0hOTgZgwoQJzJw5kxdeeIHy8vJmf07GGNNRbEnPx9db6BsZ3Cr19Yty6rG1/ExDtY8Wv3pa5lpCVlYWX375JRs3bkREKC8vR0S47LLL6pzF5e/vLOTp5eVV9Xvl67Kyo1dfv+666xg3bhwLFy5k6tSpvPjii0yePJnVq1ezaNEi7r33XqZMmcLvfve7qntUtda6fX19q2Lz9vauqm/u3LmsWLGChQsXkpCQwNq1a+natWvjH4oxxnRwW9Lz6B8Vim8LbNFWkyA/H3p2CrSZvabBrMWvid5++21uvPFGUlJSSE5OJjU1ldjYWLp06cIbb7xBeXk56enpLF68uMl17N69m759+3LbbbdxySWXsH79etLS0ggKCuL666/n7rvvZs2aNUfdM27cOL766isyMzMpLy9n3rx5nHXWWXXWs2vXLsaNG8eDDz5IREQEqampTY7ZGGM6sq378xjSo3W7XPtF2cxe03Dto8XPA+bNm8c999xz1LEf/ehHbNmyhQEDBjBs2DAGDhxYb9JVl/nz5/Pqq6/i6+tL9+7d+d3vfsfKlSuZNWsWXl5e+Pr68txzzx11T48ePfjjH//I2Wefjapy4YUXcumll9ZZz6xZs9ixYweqyjnnnMOIESOaHLMxxnRU2YUlHMgrZkj31hnfV6l/ZAjzkrKpqFC8vFpu3UDTPkhdXYMni9GjR2vljNVKW7ZsYciQIR6KqGOyZ26MMbX7dlcm172wgv/871jOGBDZavW+vmIPc97dwDezz6ZX56BWq9fUTkRWq+poT8dRE+vqNcYYY5rBlvR8AAa3douf7dlrGsESP2OMMaYZbE3PIyLEn8hQ//ovbkaW+JnGsMTPGGOMaQZb9+e3+sQOgC7BfkSHB/B9qq3DaupniZ8xxhhzgsrKK9h2IJ/B3T2ziPLY2C4kJmXXuaSXMWCJnzHGGHPCkrMKKSmraLUdO441NrYrGfnFpGQd9kj9pu1o8cRPRLxF5HsR+dB9HSsiK0Rkh4jMFxG/lo7BGGNM21Re0TZasDw1saPS2NjOACQmZXukftN2tEaL36+BLdVePwY8rqoDgEPA/7ZCDC3C29ubhIQE4uPjGTFiBH/729+oqKhoUlk5OTk8++yzVa+XLFlStb2aMcZ0RAvW7mPUHz5jdcohT4dSr6378/Dxkqot1Fpbv8gQugT7kZhsiZ+pW4smfiLSC5gGvOi+FmAy8LZ7ycvA9JaMoSUFBgaydu1aNm3axGeffcaiRYt44IEHmlTWsYmfMcZ0ZKXlFfz5k23kHC7lJ6+sIjmz0NMh1WlLej79IkPw9/H2SP0iwpiYztbiZ+rV0i1+fwf+D6hsBusK5Khq5aa0e4GeNd0oIj8VkVUisiojI6OFwzxxUVFRPP/88zz99NOoKuXl5cyaNYsxY8YwfPhw/vGPfwBQUFDAOeecw8iRIxk2bBgLFiwA4J577mHXrl0kJCQwa9asqmuvuOIKBg8ezIwZM6oG7d5zzz3ExcUxfPhw7r77bs+8YWOMaUHvfb+PvYeO8NuL4lBVZv47kezCEk+HBUBRaflxx7amt/5WbccaG9uVPdmH2Z9b5NE4zMmtxbZsE5GLgIOqulpEJlUeruHSGgdwqOrzwPPg7NxRV12PJT7G1uytJxDt8QZ3GczssbMbdU/fvn2pqKjg4MGDLFiwgPDwcFauXElxcTETJkxgypQp9O7dm3fffZewsDAyMzMZP348l1xyCY8++igbN25k7dq1gNPV+/3337Np0yaio6OZMGECy5YtIy4ujnfffZetW7ciIuTk2PR9Y0z7Ul6hPLtkF/HRYfx4QgwJvcO59oUV/OSVVbx28zgCfJuvVe2DdWmsTM7m/ovja93ubHdGASuSslmVfIhVKdnsyT7M364awWWn9gIg93ApablFDPbQxI5KY2O6AJCYnM0lI6I9Gos5ebVki98E4BIRSQbewOni/TvQSUQqE85eQFoLxtDqKlvlPv30U1555RUSEhIYN24cWVlZVfvhzpkzh+HDh3Puueeyb98+Dhw4UGNZY8eOpVevXnh5eZGQkEBycjJhYWEEBARw880388477xAUZNvzGGPalw/Xp5GUWcivJvdHRBjVpwuPX5XA6pRD3PXmOiqaacJHVkExc97ZwCvLUy5Oyu8AACAASURBVHhrdWqN18xL3MPkv37Fve9sYMm2gwzuHsrQ6HDmvLOR7QecCR1b9ucBeGwpl0pDeoQS4u9DYlKWR+MwJ7cWa/FT1XuBewHcFr+7VXWGiLwFXIGTDN4ELDjRuhrbMtdSdu/ejbe3N1FRUagqTz31FFOnTj3qmpdeeomMjAxWr16Nr68vMTExFBXV3Czv7//D6u/e3t6UlZXh4+NDYmIiX3zxBW+88QZPP/00X375ZYu+L2OMaQm5h0spLCkjulNg1bGKCuWZxTsZ2C2EKXHdq45PG96DvYcG88ePtjJxQATXjj3lhOt/8osdHC4tZ3D3UB5ZtJVzhnQjIuSHf3d3ZRTwwAebmNg/ggcvjSc2IhgR4WBeERc++TW/eG0NC345ga3pTuIX5+EWPx9vL0b16czKpJN/MozxHE+s4zcbuFNEduKM+funB2JodhkZGdxyyy3ceuutiAhTp07lueeeo7S0FIDt27dTWFhIbm4uUVFR+Pr6snjxYlJSUgAIDQ0lPz+/3noKCgrIzc3lwgsv5O9//3tV17AxxrQ1P39tNWf9eTGPf7adkjJnKPgnm/az/UABvzy7/3Fdrz89sy9jY7rw50+2kXu49ITq3pVRwGsr9nDt2N48fd1IjpSU89CHm6vOl5RVcPsbawn09eavV42gb2QIzvxEiAoL4MlrTmVXRgH3vbuBLen5dAn2a/Wt2moyNrYL2w7kc+gkGQ9pTj4t1uJXnaouAZa4v+8GxrZGvS3tyJEjJCQkUFpaio+PDzfccAN33nknADfffDPJycmMHDkSVSUyMpL33nuPGTNmcPHFFzN69GgSEhIYPHgwAF27dmXChAkMHTqUCy64gGnTptVYZ35+PpdeeilFRUWoKo8//nirvV9jjGkum9Jy+XZXFgOiQnjiix18tDGdx340nKe+3EnfiGAuGn78GDUR4feXxHHxU9/w+Ofbuf+S+HrrKS4rx9fL67gk8rGPthLg683t5w4kIsSfn0/qxxNf7ODykb04a2AkT3yxnQ37cpl7/Ui6hQUcV+7p/SO449yB/O2z7QT6enPqKZ2qEkNPGhvrjPNblXKI8+K6eTgaczKStrC9y+jRo3XVqlVHHduyZQtDhgzxUEQdkz1zY0xzufutdSxcn853957D6j3Z3PfuRtLd2ah/uXIEV4zqVeu9v3lvA/MSU1l428RaF0xWVd5bu4+HPtxCVKg/f7lyBEN7hgOwYncWVz//HbOmDuKXZ/cHnATxgie+prS8goenD+Omfydy5ahe/OmKEbXGUVGh3PTvRL7ekcmPJ8Tyu4vjmvo4mk1xWTnD7v+Um07rw33TPB9PRyUiq1V1tKfjqIlt2WaMMaZVZRYU8/7aNK4Y1YvwIF8mD+7Gp3ecyQ3j+3DGgAguTah7Rupd5w0iNMCH3y/YVOPetKnZh7nxX4ncMX8dvTsHkl1YwqXPLOOvn26jqLScRxZtoUd4AD+eEFt1j7+PN49cNozU7CP8z0sr6d05iN9dXHeLopeX8PerEzitb1emxJ8crWv+Pt4k9O5k6/mZWrVKV68xxhhT6bXv9lBSXsHMCTFVx0IDfHlo+tAG3d852I+7pwziN+9t5MP16Vw8IhpVJSmzkIXr03lmyU58vLx48NJ4ZozrQ0FRGQ8t3MxTX+7kzVWpHMgr5q9XjiDQ7+hlYcb37crVo3vz9pq9PH51AiH+9f+J7Briz7yfjm/U+29pY2O68NxXuygsLiO4Ae/BdCxt+huhqifFmIqOoC0MCTDGnPyKy8p5dUUKkwZF0i8ypMnlXDv2FF5fsYdHFm0hMSmbr7ZnsCf7MADnDunGQ9Pj6RHuzBYOD/LlL1eOYNqwHtz7zgZG9O7EZafWuHcAj1w+jNvOHUDPajON25qxsV14evFO1uw5xBkDIj0djjnJtNnELyAggKysLLp27WrJXwtTVbKysggIOH6AszHGNMbC9elk5Bcf1c3aFN5ewgOXxnP1P5bz3zV7Ob1fV35yRixnDYzilK41r2969uAolv7f2VSo1rpYs7eXtOmkD2Bkn854ewkrk7It8TPHabOJX69evdi7dy9tYTu39iAgIIBevWofbG2MMfVRVf61LIn+USGcMSDihMsbE9OFr2dPJiLEr8F75Pr5tP+h7SH+PsRHh7HCxvmZGrTZxM/X15fY2BP7P0ZjjDHNJ7uwhM5BvrX2wqxKOcTGfXk8fNnQZuupaeutcy1lbEwXXvkuheKy8gYnxaZjaP//62OMMabF/Xf1XsY8/Dn3vrOhxjHBFRXK01/uJDzQl8tPtd6DljYmtgslZRVs2Jvr6VDMScYSP2OMMSfkxa93c9db6+gW6s8bK1N5funuo86rKg98sImvtmdw2zkDjptNa5rfmBhnIWfr7jXHssTPGGNMk6gqf/5kK39YuIULh3Xny7snMW14Dx79eCsfb9xfdd0TX+zg5eUp/OSMWH5cbQkX03K6BPsxICqElcmW+JmjtdkxfsYYYzynokK5772NzEvcw3XjTuGhS4fi7SX89coR7Dt0hNvnf89bnU5nzZ5D/P3zHVwxqhdzLhxiqzC0orGxXXh/bRrlFYp3LbOYTcdjLX7GGGMa7W+fbWde4h5+eXY/Hp4+tCqxCPD15oUbR9M12J8b/rWC37+/ifPiuvHo5cMs6WtlY2O7kF9cxpb0PE+HYk4ilvgZY4xplEUb0nl68U6uGdObu6cMOi6hiwz1518zx1Berozv24Wnrj0VH2/7c9PaKsf52fZtpjrr6jXGGNNgW9LzuOvNdYw8pRMPXBpfayveoO6hfDN7MiEBPtbN6CHRnQLp3SWQxKRsfjzRlj8zDvtfMGOMMQ2SXVjCT15ZRVigD3OvH1Xv+nDhQb6W9HnYmJgurEzOtm03TRVL/IwxxtSrrLyCW19fw8H8Yv5xw2iiwmwLx7ZgXGwXsgpL2JVR6OlQzEnCEj9jjDH1ev7r3Xy7K4tHLhtGQu9Ong7HNFDlOD9b1sVUssTPGGNMnfblHOGpL3YyNb4bV4yyXTfaktiIYCJC/G2Ch6liiZ8xxpg6PbxwM4ry24viPB2KaSQRYWxsZ0v8TBVL/IwxxtRq6fYMFm3Yz61n96dX5yBPh2OaYGxMF/blHGHvocOeDsWcBCzxM8YYU6PisnLuf38TMV2D+MmZfT0djmmisbFdARvnZxyW+BljjKnRi18nsTuzkPsvia936RZz8hrUPZTQAB8Skw55OhRzErDEzxhjzHH25RzhqS93cH58dyYNivJ0OOYEeHsJY2O68N3uLE+HYk4ClvgZY4w5zmvfpVBWrvzmoiGeDsU0g9P7R5CUWWjj/IwlfsYYY4733e4shvUKtwkd7cQZAyIAWLYz08ORGE+zxM8YY8xRDpeUsX5vLuP7dvV0KKaZDIgKISrUn693WOLX0VniZ4wx5ihrUnIoq1DGxXbxdCimmYgIE/tH8O2uLCoqbN/ejswSP2OMMUdZkZSFt5cwOsYSv/Zk4oAIsgtL2Jye5+lQjAdZ4meMMeYoK3ZnMzQ6jBB/H0+HYprRhP42zs9Y4meMMaaaotJy1qbmMM7G97U73cICGNgthG8s8evQLPEzxhhTZc2eQ5SUV9j4vnZqYv9IEpOyKSot93QoxkMs8TPGGFNlxe5sRLDxfe3UxAFdKS6rYHWK7eLRUVniZ4wxpsqKpCzio8MID/T1dCimBYyL7YqPl9iyLh2YJX7GGGMAKC4r5/s9OYyLtfF97VWwvw8jT+lsEzw6MEv8jDHGALAuNZfiMhvf195NHBDBxrRcDhWWeDoU4wGW+BljjAGcbdpEYKwlfu3ahP4RqMK3u7I8HYrxAEv8jDHGAM74vkHdQukU5OfpUEwLGtErnNAAH77ZmeHpUIwHWOJnjDGGEnemp+3P2/75eHtxWt+uLN2eiapt39bRWOJnjDGGDftyKCqtYHxf6+btCM4cGMm+nCPsyij0dCimlVniZ4wxhu92ZwMw1mb0dgiTBkUCsGTbQQ9HYlpbiyV+IhIgIokisk5ENonIA+7xl0QkSUTWuj8JLRWDMcaYhvl8ywHieoTRJdjG93UEvToH0T8qhK+22zi/jqYlW/yKgcmqOgJIAM4XkfHuuVmqmuD+rG3BGIwxxtQjNfsw3+/J4eIR0Z4OxbSiSQMjWbE7m8MlZZ4OxbSiFkv81FHgvvR1f2wUqTHGnGQ+XJ8OwEXDe3g4EtOaJg2KoqS8guW2rEuH0qJj/ETEW0TWAgeBz1R1hXvqYRFZLyKPi4h/Lff+VERWiciqjAxrijbGmJby/ro0Tj2lE727BHk6FNOKxsR2JsjPmyXb7G9sR9KiiZ+qlqtqAtALGCsiQ4F7gcHAGKALMLuWe59X1dGqOjoyMrIlwzTGmA5r58F8tqTncfFw6+btaPx9vDm9XwRLth+0ZV06kFaZ1auqOcAS4HxVTXe7gYuBfwNjWyMGY4wxx/tgXToi1s3bUU0aFElq9hF2Z9qyLh1FS87qjRSRTu7vgcC5wFYR6eEeE2A6sLGlYjDGGFM7VeWD9WmMj+1KVFiAp8MxHvDDsi4t39373LrneGD5Ay1ej6lbS7b49QAWi8h6YCXOGL8PgddEZAOwAYgA/tCCMRhjjKnFprQ8dmcU2mzeDqxyWZeWXs8v80gmL65/kY+SPrJuZQ/zaamCVXU9cGoNxye3VJ3GGGMa7oP1afh4CRcM7e7pUIwHTRoYySvLUzhcUkaQX8ukBa9sfoWSihJKKkrIPJJJZJCN3fcU27nDGGM6IFXlw3XpnDEggs62aHOH1tLLuuSV5PHmtjfpEeyMI03OS26RekzDWOJnjDEd0Jo9OezLOWLdvKbFl3WZv3U+haWFzBk3B4Ck3KQWqcc0jCV+xhjTAb33/T78fLw4L66bp0MxHtaSy7ocKTvCq1teZWLPiZzZ60wCfQIt8fMwS/yMMaaDWZmczeuJe5ieEE1ogK+nwzEngYn9u5KafYT9eUXNWu57O98juyibm4fdjJd40Sesj3X1epglfsYY04FkF5bwq9e/p3fnQH57UZynwzEniWG9wgHYtC+v2cosrSjlpY0vkRCZwMiokQDEhsVai5+HWeJnjDEdREWFcteba8kuLOHp60Zaa5+pMrh7GCLOEj/N5eOkj0krTOPmYTfjLN0LMeExpBWkUVxe3Gz1mMaxxM8YYzqIF77ezeJtGfz2oiEM7Rnu6XDMSSTY34fYiGA2peU2W5mvbnmV/p36c0avM6qOxYTFoCh78vY0Wz2mcSzxM8aYDmB1SjZ/+mQbFw7rzvXj+3g6HHMSGhod3mwtfvsL97M5azOX9LsEL/kh1YgNjwVsZq8nWeJnjDEdwL3vbKBnp0Ae/dHwqm43Y6qLjw5jX84RDhWWnHBZS1KXADCp96SjjvcJc/6nwyZ4eI4lfsYY084dyCti+4ECbjytD2E2rs/UIj7a6f7fnH7irX6LUxcTExZT1cJXKcg3iO7B3a3Fz4Ms8TPGmHYuMSkbgHGxXT0ciTmZxUeHAbBx34mN8ysoKSBxf+JxrX2VYsJiSM5NPqE6TNNZ4meMMe1cYlI2If4+DOkR6ulQzEmsc7AfPTsFnvA4v2VpyyirKKs78ctLbvbFok3DWOJnjDHtXGJSNqP6dMbH2/7JN3WLiw5j4wnO7F2SuoRO/p0YETmixvOx4bEUlBaQeSTzhOoxTWP/ChhjTDt2qLCEbQfyGRvbxdOhmDZgaHQ4SZmFFBaXNen+sooylu5dypm9zsTHy6fGa2LCYwCb4OEplvgZY0w7tjK5cnyfJX6mfvHRYajC1v1N6+79/uD35JXkcXbvs2u9JjbMlnTxJEv8jDGmHUtMysbfx6tqSy5j6lK5sPfGJm7dtjh1Mb5evpwefXqt13QL7kagT6Alfh5iiZ8xxrRjicnZnHpKJ/x9vD0dimkDuoX50zXYr0k7eKgqS1KXMK7HOIJ8g2q9zku86BPWx7p6PcQSP2OMaafyi0rZuC+XsbaMi2kgEXEmeDShxW937m5S81Pr7OatFBsWa0u6eEiTEj8R+V1zB2KMMaZ5rU45RIXa+D7TOEN7hrPjYD4lZRWNum9x6mIAzux1Zr3XxoTHsK9gH8XlxU2K0TRdU1v8bm7WKIwxxjS7xKRsfLyEU0/p5OlQTBsSHx1Gabmy/UD+Uccr9PhEUFVJzUtl0e5FLNi5gLiucXQP7l5vHTFhMSjKnrw9zRa3aZia51oDIlJbO68AgS0TjjHGmOaSmJTNsF7hBPnV+k+9Mcep3LptU1pu1WSP1PxUfvT+j1BVwvzDCPcPJ9gnmOS8ZHKKcwAI8A7gwQkPNqiOyq3cknKTGNB5QAu8C1Obuv41yAHGqOqBY0+ISGrLhWSMMeZEFZWWs25vDj+eGFv/xcZU06dLECH+Pkft4LF071KOlB3h2sHXUlRWRG5xLvml+Uw+ZTJDI4YyPGI4/Tr1q3XtvuPqCOsD2Fp+nlDXJ/QK0Ac4LvEDXm+ZcIwxxjSH7/fkUFquNr7PNJqXlxDXI+yoxG/l/pX0DOnJnHFzmqWOIN8gugV161ATPEQkAFgK+OPkX2+r6u9F5FbgdqAfEKmqtW5pIiJhwBbgXVW91T02CngJpzd2EfBrrWM/vFrH+Knqb1Q1sZZzs+t+e8YYYzwpMSkbERjVxxI/03hx0WFsTsujvEKp0ApW7l/J2O5jm7WO2PDYjraWXzEwWVVHAAnA+SIyHlgGnAukNKCMh4Cvjjn2HPBTYID7c35dBdTZJisi4W4BPQEF0oBPVDWnAcEZY4zxkMTkLIZ0DyM80NfToZg2aETvcF76Npm5X+3i7GEl5JXkMab7mGato294X17f+jrnvHUO0cHR9AjuwcAuA7kp/iZ8vdrf99ZthStwX/q6P6qq34OzlE5d3Ja9bsDHwGj3WA8gTFWXu69fAaYDH9VWTq0tfiJyI7AGmAQEAcHA2cBq95wxxpiTUGFxGatTDtn+vKbJLhzWg4uG9+DPn2zjN5+8B9DsLX43xd/Ez4b/jPE9xuPn7ceGzA08seYJ7v/2furoqWzTRMRbRNYCB4HPVHVFA+/zAv4KzDrmVE9gb7XXe91jtaqrxe8+YNSxrXsi0hlYgTMG0BhjzElmwdo0ikoruHhED0+HYtoofx9vnrr2VAZ1C+XZLS8RGNwNKW/ebf+iQ6K59dRbjzr23NrneHbds0QGRnL7qNubtb6TgaqWAwki0gl4V0SGqurGBtz6C2CRqqYe0zJYUzNhnVlzXev4SS03V9RSkTHGGA9TVV79LoXB3UMZeUpnT4dj2jAR4ednxxIcvofi/FgueXoZaTlHWrTOW0bcwpUDr+SfG//Ja1tea9G6PMltVFtCPePxqjkNuFVEkoG/ADeKyKM4LXy9ql3XC2dYXq3qSvweBtaIyHMiMsf9mYvT/ftwAwM1xhjTitbsyWFzeh43nNan3jFDxtRnc9ZmiisOc/vEC9ifV8R/V++t/6YTICLcN+4+zjnlHB5LfIyPkmodqnbSWrg+vcbjIhLptvQhIoE4Ezq2NqRMVZ2hqqeoagxwN/CKqt6jqulAvoiMF+c/+BuBBXWVVdes3pdxBg9+hTMTpQQnOx2tqi81JFBjjDGt67XvUgjx92F6Qp3DfIxpkMT9zuIelw85i1NP6cSnm2ta4a15eXt589iZjzGy20jmfDOHbdnbWrzO5pB7pJQ75q/ll6+vqe2SHsBiEVkPrMQZ4/ehiNwmIpUtd+tF5EUAERld+Xs9fg68COwEdlHHxA6oZ8s2VT2kqm+o6l9V9S9AgaoeakAQxhhjWll2YQkfrk/n8pE9Cfa33TrMiUtMT6R/p/50DezK1PjubNiXy74W7u4F8Pf254mznyDQO5Bn1z7b4vWdqG93ZXLB35fy/ro0bj+35p1IVHW9qp6qqsNVdaiqPugef1JVe6mqj6pGq+rN7vFVlb8fU85LlWv4VbtuqKr2U9Vb61rDDxq/V2/D9mIxxhjT6t5alUpJeQXXj+/j6VBMO1BaXsr3B7+vms07Nd7Zg/fTTftbpf5w/3BuiL+BL1O/ZHPW5lapsyke/2w7172wAn9fb/7789O5/dyBng6pTo1N/GzAiDHGnIQqKpTXVuxhbGwXBnYL9XQ4ph1Yn7meovIixvZwEr/YiGAGRIXw6aaW7+6tdP2Q6wn1C+W5tc+1Wp2NkV1YwpNf7uCCod1ZeNtEEnp38nRI9Wps4vezFonCGGPMCVm6I4M92Yettc80m8T9iQjC6G6jq45Nje9OYnI2hwpLWiWGUL9Qboq7iSV7l7Apc1Or1NkYX+/IQBV+dlY/gvzaxvCKuhZw9hORG0XkXPf1dTjTh38pIu1vSW1jjGnDXv0uhYgQP853u+OMOVGJ6YkM7jKYcP8f1u+bGt+d8grli60HWy2OGUNmEO4fzjNrn2m1Ohvqq20ZdA7yZVjP5l3jsCXV1eL3b2Aa8GsR+Q9wJc7CzWNwZo8YY4w5CaTnHuHLrQe5ekxv/Hwa25FjzPGKyopYl7HuuN06hvYMIzo8gE9aaZwfQIhfCDPjZ/L1vq9Zn7G+1eqtT0WFsnRHBmcOjMTbq+2MhKurXXKYqg4XER9gHxCtquUi8iqwrnXCM8YYU58P1qVRoXDlqN6eDsW0YeUV5Ww/tJ01B9fwbdq3lFaUVo3vqyQiTInvzrzEPRwuKWu17s1rB1/Ly5te5tm1zzL3vLmtUmd9NqXlkVlQwlkDIz0dSqPU9b+GXiLiB4Ti7NVb2Y7pj7OxsDHGmJPA++vSGNErnJiIYE+HYtqor/d+zcQ3JnLVh1fxaOKj7Di0g+n9pzOux7jjrp0S143isgqWbs9stfiCfYOZGT+TZWnLeGLNE6Tmp7Za3bX5arvT3X1mG0v86krV/4mzorQ3zr69b4nIbmA88EYrxGaMMaYeuzIK2Lgvj99eFOfpUEwb9tXer6jQCh4941FGRo2kR0jt+zyPje1CpyBfPt20n/OHtt6Y0msHX8vajLX8c8M/eXHDi4zuNppL+1/KtNhp+Hq3fnvUkm0ZDOsZTkSIf6vXfSJqTfxU9XERme/+niYir+BsL/KCqia2VoDGGGNq9/7aNETgouG1/6E2pj7Jucn079SfaX2n1Xutj7cX5wzuxudbDlBaXoGvd+uMKw3yDeKpyU+xv3A/H+z6gPd2vsdvl/2WzVmbmTNuTqvEUCn3cClr9hzil2f3b9V6m0N9n1Y60FtELgfOBlJxthmpl4gEiEiiiKwTkU0i8oB7PFZEVojIDhGZ73YnG2OMaSRV5f11aYyP7Uq3sABPh2PasN25u4kJj2nw9VPiu5F7pJTEpOyWC6oW3YO785PhP+HDyz7k8gGX89b2t9hXsK9VY/hmZyYVSpsb3wd1L+cyBdgB3A9ciDPD9wFgh3uuPsXAZFUdASQA54vIeOAx4HFVHQAcAv73hN6BMcZ0UBv35ZGUWcilCdGeDsW0Yfkl+WQcyaBveN8G33PmgEgCfL34rBX27q2NiPDzET/HCy/mrmvdCR9fbT9IWIBPm1iw+Vh1tfg9AZyrqheo6s3uz/nAee65OqmjwH3p6/4oMBl42z3+MjC9ydEbY0wHtmDtPny9hQuGWjevabrdubsBGpX4Bfp5M7F/JJ9tPkA9W8O2qO7B3blq0FW8v+t9knOTW6VOVeWr7RmcMSASn1bq5m5OdUXsA+yt4fg+GjirV0S8RWQtcBD4DNgF5KhqmXvJXqBnLff+VERWiciqjIyMhlRnjDEdRkWF8uH6dM4aGEV4kC20YJpud46b+HVqeOIHcF5cFPtyjrAlPb8lwmqwm4fdjL+3P8+ue7ZV6tu6P58DecVtspsX6k78/gWsFJHZInKd+3MPziLO/2xI4aparqoJQC9gLDCkpstqufd5VR2tqqMjI9vmwzXGmJaSmJzN/rwiLrFuXnOCkvKS8PXypWdIje0wtZo8uBsi8PkWz3X3AnQN7MqMITP4OOljth/a3uL1LdnmNEadNSgSVWXmxzN5edPLLV5vc6k18VPVPwLXAQKcBpzunprhnmswVc0BluAsBdPJXRQanIQwrZExG2NMh7dgbRpBft6cOyTK06GYNi4pJ4k+YX3w8WrcYsyRof6c2ruTR8f5VZoZP5MQ3xCe+d7Z1q28opxl+5Yxe+ls7lxyJ4t2L6KwtLBZ6vpq+0EGdw+lW1gA6zLWsfrAauaum0teSV6zlN/S6vyUVXULsKXytYiMVNXNDSlYRCKBUlXNEZFAnKVgHgMWA1fgrAV4E7CgibEbY0yHVFJWwUcb0zkvrlub2RjenLx25+5mUJdBTbr33Lhu/OnjbaTnHqFHeGAzR9Zw4f7h3Bh/I8+sfYaHlj/Ekr1LOHj4IOH+4fh5+fFZymf4efkxoecETo8+naigKCICI4gIjCAyMLLB6wDmF5WyKvkQ/3tGLAAfJX2Ej5cPBaUFvL7ldW4ZcUut94pIb+AVoDtQATyvqk+ISAIwFwgAyoBf1LRsnog8hjPRFuAhVZ3vHhfgDzhb65YDz6nqk7XF0dh/MV4ERjbw2h7AyyLijdOy+Kaqfigim4E3ROQPwPc0sNvYGGOMY/G2g+QcLuWSEdbN2xGUV5SzIXMDwyOH4yUNm0xw00c3MSJyBHeOvrPO64rLi9lbsJcLYi9oUmxT3MTv8y0HuWF8nyaV0VxuiLuBeVvn8faOt5nYcyKzx8xmUu9J+Hj5sPbgWj5L+YxPUz5lcerio+7rEtCFRZcvIti3/p1vFm/LoKxCOW9IN8oryvkk+RMm9ZpEWUUZr255lRvibqirnDLgLlVdIyKhwGoR+Qz4E/CAqn4kIhe6rydVv1FEpuHkXwk4O6h9JSIfqWoeMBPoDQxW1QoRqbMboLGJX4N3IVbV9cCpNRzfjTPezxhjTBO8tmIP3cMC2uzgctM4L254kafXPs3do+/mpvib6r1+d+5u1hxcw86cnfzq1F/VLBpeQAAAIABJREFU2ZqVkpdChVY0akZvdf0iQ4jpGsTnmw94PPEL9g1m/kXz8fHyISIw4qhzI7uNZGS3kcwaM4uMwxlkFmWSdSSLbdnbePL7J/ks5TOm9z9+kZFDRYd4cPmD3DnqTnqH9ebTTfuJCPHj1FM6s+pAIllFWVzw/+zdd3iUZdbH8e9J74FAEiAh9N57VQHBgl3Xgr2grKtrW3tZ27r6WhZ3111dV0UU14JYEUSaIKD03iHUEFJISK8z9/vHM2CQlAlk8kwm53NdcyV58szMD4R4uMu5251Py/CWXDvrWj7d/im39ry10nzGmFSs/sgYY/JEZCvWBlcDRLlui6byJXDdgUWuzbHlIrIeOA/4DLgTuNYY43S9dnp1v0+13Yf8bC3vV0opVYf2HSlg8Y4MJgxOapCtJFTtJOck858N/yHIL4g31r7h1hm1C/YvACC3NJelh5bW+PpQ+x29x4gIY7vF8/PuI+SXlNf8BA9rEd7ipKKvIj/xIz48nh7NenBm4plM7DWRpMgkvt39baX3T98xnXn75zF5zWRKyh38uD2Dsd3i8fcTZu+ZTVhAGGcmnkmv2F4MbzWcqZunUlReVGNOEWmLNTi2HLgPeEVEDgCvAo9V8pT1wPkiEiYizbEO1Wjt+l4H4GpXJ5TZItKpuveu9qeGiESLyNUi8oCI3A8Ei0jD61aolFI+4qPl+/H3E64Z3Lrmm1WD5jROnl32LKEBoXww/gP8/fx57ufnauybt3D/QrrGdCU6OJpZe2ZVe++enD0IQtuotqecc1z3eEodThbvaHit10SEizpcxIrDKziUf+JAW7mznM+2f3Z8jeDH65eSX1LOuT1aUOYoY+6+uYxJGkNIgHVqzqTek8gqzuLzHZ9X9lYV3zMCmAHc55qqvRO43xjTGrifSpbAGWN+AGYBy4CPgZ+xpo7BmvotNsYMBP6L1ZWlStWd3HEjsAZrnjkMCMeqMFe7vqeUUqoeFZc5mL7qAOd0j9cj2hqB6dunsyZ9DQ8NeogezXpwf//7+SX1F77Z/U2Vz0krSGND5gbOaXMO49qM48cDP1JYVljl/XuO7qFVRKvjxcupGNCmKU3CApnnBbt7T8VFHS4CYGbyzBOuLzqwiLTCNJ4Z/gwxITFM3fpvwoP8GdahGT+n/kxuae4JayP7x/dnUItBTNk0pcr3EpFArKLvI2PMF67LNwHHPp9OFcvhjDEvGGP6GmPGYS292+n61kHXawJ8CfSu7tdb3YjfE8AAY8ydxpi/uB6/BwYCT1b3okoppererI2pZBeWcb3Na6mU5x0uOMzkNZMZ2nIol3S4BIAru1xJ/7j+vLzyZTKLMit93o8HfgTg7KSzGd9uPEXlRSw6uKjK90nOST7l9X3HBPj7MaZLHAu2p1PucJ7Wa9khISKBgfED+Xb3tyeMpn6y/RNahLfg/HbnM7HnRDIdm+nTOYOQQH9m7ZlFVFAUw1oOO+G1JvWeREZR5SOfrt237wJbjTF/q/CtQ8BZrs/H8GtBV/G5/iLSzPV5b6zi7gfXt79yPQ/X61TbzLC6wk+ovLmyk1ps8lBKKVU3pv2yj/bNwxneoZndUZQHGWP4yy9/wWmc/HnYn7HqBWt92tPDn6aovIiXVrxU6XPn759P26i2tItuR/+4/sSFxlU53etwOtibu5d20e1OO/O47vEcLSxj1b7s034tO1zc4WL25u5lQ+YGwJoC/yX1F67sfCUBfgF0ChuHs6wJR4K+pLCskIX7FzKuzbiTNs4MbjGYvrF9q3qbEcANwBgRWed6jAduB15zbdj4K3AHgIgMFJF3XM8NBH5ydUZ5G7i+wiloLwFXiMhG4EVgYnW/1uoKvxeANSLypog87nq8hTX9+0J1L6qUUqpubTmUy5r9R7l2SNLxQkD5nu1Z23l8yeMsOriIu/reRevIE9dyto9uz6Tek5izdw7z988/4Xu5pbmsPLySMUljEBH8/fw5t925LElZQk5JzknvdajgECWOktMe8QM4o3MsQf5+zN6YetqvZYdxbcYR4h9yfJPHZ9s/I8AvgMs7XQ7Awq3ZlB85h0NFO3lm2TMUlhdW2gJHRHh99OuVvocxZokxRowxvV1Ttn2NMbNc1wcYY/oYY4YYY1a77l9ljJno+rzYGNPd9RhqjFlX4XWPGmMuMMb0MsYMM8asr+7XWt3JHVOxpnUXASVAKdbpGwONMe9X96JKKaXq1rTl+wgO8ON3AxLtjqLqmNM4WZKyhDt+uIPfffs75u+fz43db+S6btdVev+tPW+lW0w3nvv5ObKKs45fX3xwMeWmnDFJY45fu6DdBZQ7y08qEsEa1YJT39FbUURwAOf3asEXa1Io8ILdvbUVERTBmKQxzN4zm5ySHL7e9TXj2oyjeWhzjDHM2XyYwbHj6BDdgdl7Z9M8tDkD4wdW+lrNQr17RL7aXb3GmGxjzCfGmNeMMa+6Pm+Y47hKKdVA5RWX8dXaFC7u04omYUF2x1F14GjxUWbvmc0TS57g7Olnc+e8O9l9dDf39r+Xub+by0ODHqryCLVA/0BeGPkCeaV5PP/z88fXpS3Yv4DY0Fh6Ne91/N7uzbqTFJlU6XTv8cKvDkb8AG4c1pa8knK+XJtSJ69X3y7pcAm5pbk8+tOj5JXlMaHrBAB2puez90gh53ZvyR/7/xGAc9uei7+fv51xT1mVDZxdR4u8gtVccDbwijGmzPW9r4wxJ3c6VEopVae2H87jqa82UVjq0E0dPsAYw4srXuTT7Z/iNE6ig6MZ3nI4o1qPqnTNWFU6Ne3E3f3uZvLqycxMnsm4NuNYkrKEi9pfdMLpHiLC+e3O578b/0tmUeYJPe6Sc5KJCYkhOji6Tn5t/ZOa0DMhig9+3st1DXBJwpCWQ4gLjWNJyhI6N+18fK3eD5sPA9YpJbGRSTw7/FnOTDzTzqinpboRv/ewpnb/iHX82qJjO0oA/emjlFIelFtcxrPfbmb8P35iR3oeL1/Rmz6ttY1qQ/f2hrf5eNvHXNrxUqaNn8aiqxbx8lkvM779eLeLvmNu6n4T/eL68eLyF/lm9zcUlRedMM17zPh243EaJ3P2zjnhevLR09/RW5GIcOOwtuxIy+eX5Kyan+Bl/P38uaCDdRTuNV2vOV64ztmcRr+kJsRFhSAiXN7p8mqbRHu76gq/WGPMW8aYdcaYPwL/BhaLSAcq3+2rlFKqDizakcGYVxfx/rK9XDOoNQv/NIqrBmnD5oZuZvJM3lj3Bhe1v4hnhj1Dn9g+pzVd6O/nzwsjXqDclPPC8heICIxgcIuTW8C1b9KerjFdmbp5KocLrNErYwzJOcl1sqO3Ims5QiAf/Ly3Tl+3vlzf7Xpu6H4DF7a/EIBDR4vYmJLDOd1b2Jys7lRX+AWKyPGOjsaYacC9wBysEUCllFJ1bNmuTG7/YBXNI4L45q6RvHBZL5qG67q+hm7l4ZX8eemfGdRiEM8Of7bOpkFbR7XmwYEP4jROzkg8o8pRw2eGPUN+aT63zrmVwwWHOVJ8hNzS3Dod8QMICfTn6kGt+WFLGoeO1nx0mbeJC4vj4UEPExoQClj/CAMY2y3Ozlh1qrrC7x1gSMULxph5wJXAJk+GUkqpxmj1viwmfrCKds3C+fj2ofRKrJu1V8peyTnJ3LfwPhIjE5k8anKtp3RrcmXnK3lgwAPc0euOKu/p0bwHb417i6ziLCb+MJEVqSuAutvYUdH1Q9rgNIb/Ld9f569d3xbvyKBldAgd4yLsjlJnqmvnMtkYc1K7b2PMWtdxIUopperIppQcbp6ykvioED6cOFhH+XxATkkO/1z7T6777joC/AL499n/rrONFBWJCLf0vIWOTTtWe1/v2N68NfYtMgozeGLJE0DdtHL5rdYxYZzdNZ6PV+ynpNxR569fX8odTpbsyuTMTrENbqNKdao7qzdARCaJyPciskFE1ovIbBH5veusOaWUUnVgR1oeN7y7nKiQQD6aOIS4SD2HtyE7WnyUf6z5B+fOOJe3N7zNsFbDeP+890mMtL8HY9+4vrw59k0C/QMJCwgjPizeI+9z0/A2HCkoZfbGwx55/fqw/uBR8orLObNzrN1R6lSV7VyAD4GjwDNYBwADJGIdJjwNuNqjyZRSqhH4efcRfj9tNcEBfnw0cQitmoTaHUmdBmMMN8y+gX25+zin7TlM6j2JTk072R3rBP3j+zPlvCkcyj/ksZGsER2a0655OJ+vPsil/RI88h6etmhHJn4CIzs23B28lamu8OtvjOnym2sHgV9EpNoDgJVSStVs+qoDPP7lRpJiwphy82CSmoXZHUmdpn25+9ibu5fHBj/Gtd2utTtOlXo060GPZj089vp+fsLoLnF8tHwfxWUOQgIbXrPjxTsy6NO6CdFhvjXJWd3mjmwRuVLk106QIuInIlcDenqHUqpRWrQjg3MmLyKroPSUX8PpNLwyZxsPfb6Bwe1i+OIPI7To8xFr09cCVjPgxm5Ex2aUlDtZs7/hlQxHC0vZcPAoZ3byrWleqL7wuwb4HZAmIjtco3yHgctd31NKqUblcE4x93+6jh1p+aw7cOr/M3vm2838a+FurhnUmvdvGUx0qG+NKDRm6zLWERUUVef98Rqiwe1i8PcTft59xO4otbZkVyZOg8+t74NqpnqNMXtxreNzndghxpjMesqllFJexeE03PfpWgpLrQPod6blM6Zr7RfGF5aW88nKA1zRP5EXL+/lU7sFFaxLX0ffuL4nHJvWWEWGBNIrIZplu4/wJ7vD1NLiHRlEhQTQxwdbKlX7J1NEokSkgzHmSMWiT0R6ez6aUkp5jzcW7OKX5Cz+cmkv4iKD2ZGWf0qv89POTErLnVzeP0GLPh+TU5JDck7y8TNelTXdu/7AUfJLyu2O4jZjDIt3ZDKyU3MC/H2vgK+unctVwDZghohsFpFBFb79vqeDKaWUt1iefIS/z9/BZf0SuKJ/Ap3jI9mZnndKrzVvSxqRIQEMbhdTxymV3dalrwOslinKMrxDc8qdhpV7Gs7ZvTvT8zmcW+yT6/ug+hG/x4EBxpi+wC3AhyJyuet7+s9UpVSjkF1Qyr2frKNNs3Cev7QnIkLHuAh2puXjdNbu2HKH07BgWzqjusQR6IMjCY3duox1BEgAPZv3tDuK1xjQpilBAX4s3dVwVootdh3T5ovr+6D6ws/fGJMKYIxZAYwGnhCRe4Da/bRTSqkG6v1le0nPK+afE/oREWwti+4cH0lRmYOUWp5Fuu7AUY4UlPrUuZ/qV2vT19I1puvxc16VdXbvgKSmLPOSDR7frj/EY19s5Eh+SZX3LNqRQce4CJ/tqVld4ZcnIh2OfeEqAkcBlwCea/6jlFJe5OfkI/RMiKZnwq+LvDvHW+d27kir3XTv/K1p+PsJozpr4edryhxlbMrcpNO8lRjeoRlbUnPJPo0WSHVhZ1oeD05fz8cr9nPO5MXM2XzyqSLFZQ5W7Mny2WleqL7wu5PfTOkaY/KA84BbPRlKKaW8QXGZg3UHjjK47Ynr8TrFRwLWWqDamLc1jcFtY3yuIayCrVlbKXGU0C+un91RvM5w18kXPyfbN+pXUu7g3k/WEREcwEcTh9AiOoRJH67mgU/XcTinmKW7Mvnb3B1c985ySsqdnNnZt07rqKi6di7rq7heBnzksURKKeUl1h84Smm5kyHtm51wPTo0kPio4FqN+O0/UsiOtHyeujCprmMqL6AbO6rWOzGa8CB/lu3OZHyvlrZkeO2HHWxJzeWdGwcyomNzvvzDCN5YuIt/LdzFF2tTAPAT6N4qinvO7sQZPjziV92RbUop1agt35OFCCeN+IG1zm9nLVq6zNuaBqDr+3zUuox1JEQkEBem/31/K9Dfj8HtYli2y54Rv2W7MvnvT8lcOySJsd2t3ptBAX48MK4z47rF8+P2dHomRjOgTVOiQnx/NF4LP6WUqsKKPVl0iY+sdGq2Y1wEn6w4gNNp8POrudHBvK1pdIqLoE2zcE9EVTYyxrA2fa0e01aNER2bs3D7VlJzimgZXX+bJo4WlvLAZ+tp1yycJy/odtL3eyVG08sHmzRXR/sJKKVUJcocTlbvy2bob6Z5jzm2s/dgds07e3OKylixJ+v4aIPyLQfzD5JZlEm/WF3fV5VhHay/R/V9fNtfZ20lM7+Ev1/Tj7AgHesCNwo/EblQRNaKSJaI5IpInojk1kc4pZSyy4aDORSVORhSRaPl2uzsXbQjg3Kn0WleH6Xr+2rWrUUUTcMCWVqP071FpQ6+XZ/KlQMTG92oXnXcGfF7HbgJaGaMiTLGRBpjojycSymlbLXCddLAoCoKv45x1s7eHW6c4DFvSxrNwoPo27pp3QVUXmNd+joiAiPo2KSj3VG8lp+fMLJTLHO3HCansKxe3nPRjnSKyhxc2LtVvbxfQ+FO4XcA2GSM0abNSqlGY/meI3SMi6B5RHCl348ODaRFVAi7atjgkZ5bzPytaYzpGoe/G2sBVcOzNmMtvWN74+/nb3cUr3bnWR3IKynnzUW76+X9vtt4mJjwoCpH7Rsrdwq/h4FZIvKYiDxw7OHpYEopZZdyh5NVe7Nr/B9Gp/iIGkf8np25hTKn4Q+jdTTIFx0pOsKu7F06zeuG7q2iuKxvAlOW7uFQJafezNxwiAv/+RP7jhSc9nsVlzlYsDWNc3vEE6DHI57And+NF4BCIASIrPBQSimftDU1j/yScgbXVPjFRbIrveozexduS+e7Dan8cXRH2jXX3by+6MtdX2IwnNv2XLujNAj3j+uMMfD6vB0nXN+UksOfPlvPppRcbpu6irzi05sOXrQjg4JSh219A72ZO4VfjDHmcmPM08aYZ489PJ5MKaVssnyPtQC9qh29x3SOj6C4zMmB7MKTvldYWs6TX22iY1wEk87qUMmzVUPncDqYvn06g1sMpn10e7vjNAitY8K4cVgbPl998PjGqOyCUn4/bTVNw4L454R+7M0s4J6P1+Ko4h9U7pi9MZUmYYE1/h1ujNwp/OaJyDkeT6KUUl7il+Qs2jYLIz4qpNr7jh3dtqOSdX6T5+4g5WgRL17ei6AAnWryRUsPLeVQwSGu7nK13VEalLtGdyQ8OICXv9+Gw2m455O1pOeW8NYNA7ioTyuevrgHC7dn8PL3207p9YvLHMzbms653VsQqNO8J3Hnd+Qu4HsRKXa1ctF2Lkopn+V0GlbuzapxmhesNX5wckuXTSk5vLd0LxMGt2ZQJad+KN/wybZPiA2NZXTSaLujNChNw4O4c1QH5m1NZ9KHq/hpZybPXdKDvq2bAHDD0DbcMLQN/1mczIzVB2v9+kt2ZpJfUs75vVrUdXSfUGPh52rf4meMCXF9ru1clFI+a3taHjlFZQxpV/MUUVRIIC2jQ9iV/uuIX0FJOY99sZGmYYE8et7JJwUo33Aw7yBLUpZwRecrCPTz/WO+6tqtI9rRIiqEeVvTmTA4iWsGn3iG9Z8v6s6w9s147IuNbDlUu7GmWRtTiQ4NZETH5nUZ2We4NQYqIheLyKuux4WeDqWUUnZZnmyt73NnxA+so9uOjfgdyCrkijeXsflQDn+5tGelR70p3/D5js/xEz+u6HSF3VEapJBAf166ohfXDGrNMxd3P+n7gf5+/Pu6/kSFBvDYFxvcXu9XUu5g7tY0xnWP12neKrhzcsdLwL3AFtfjXte1mp7XWkQWishWEdksIve6rj8jIikiss71GH+6vwillKor6w4cpUVUCK1jwty6v3O8tbN32e5MLvnXUg4dLWLKLYM5r6fuJvRVpY5Svtj5BWclnkWLcJ1OPFWjusTx0hW9CQ6ovP9h0/AgnrqwO+sP5vDhz3srvSe7oJScol93AC/dlUlecTkX6G7eKrlzcN14oK8xxgkgIlOBtcCjNTyvHPiTMWaNiEQCq0Vkrut7k40xr55qaKWU8pRdGfnH1+65o3N8BCXlTq57Zzntm4fzzk2DtHWLj5u7by7ZJdlc3VU3dXjaxX1aMWNNCq/M2c45PVrQqkno8e/N3pjKvZ+so9ThJCkmjJ4JURw6WkxkSIBO81bD3XHQJhU+d+vAO2NMqjFmjevzPGArkFC7eEopVX+cTsPu9AI6xrlf+PVKsH48ju4Sx5d3jdCirxH4dPunJEUmMbTlULuj+DwR4YVLe+Iwhqe/2Xz8+scr9nPX/9bQMyGKh8/rQs+EKDal5LLuwFEu6tNKd9JXw50RvxeBtSKyEBDgTOCx2ryJiLQF+gHLgRHA3SJyI7AKa1Qwu5Ln3AHcAZCUlPTbbyulVJ1LzS2mqMxBh1j3C7/uraJY9NAoEpuG6ZFsjcDuo7tZm76WBwc+iJ9ocVEfWseEcf/Yzrw4exvfbzrMnswC/u/7bZzVOZY3r+9PWNCvpUxecdkJX6uTVfunVkQEWAIMBb5wPYYZYz5x9w1EJAKYAdxnjMkF3gQ6AH2BVOC1yp5njHnbGDPQGDMwNjbW3bdTSqlTdmx3bm1G/ADaNAvXoq+RmLtvLoJwQfsL7I7SqNw6sh3dWkZx36dr+b/vt3Fxn1b898aBJxV5kSGB+nexBtUWfsYYA3zlmrb9xhjztTHmsLsvLiKBWEXfR8aYL1yvmWaMcbjWDP4XGHwa+ZVSqs7sPsXCTzUeC/YvoHdsb5qH6hqy+hTo78dLl/fCGLhxWBtev7qvTueeInfGQ38RkUHGmJW1eWHXaOG7wFZjzN8qXG9pjEl1fXkZsKk2r6uUUp6yKyOf6NBAmoUH2R1FeaHU/FS2Zm3lgQEP2B2lUerTugnrnz6HkMDKdwEr97hT+I0GJonIPqAAa52fMcb0ruF5I4AbgI0iss517XFggoj0BQywF5h0KsGVUqqu7UrPp2NcBNa/W5U60YIDCwAYkzTG5iSNlxZ9p6/Kwk9E2hlj9gDnn8oLG2OWYBWJvzXrVF5PKaU8LTkjn7O7xtsdQ3mpBfsX0LFJR9pEtbE7ilKnrLoJ8s9dH98zxuz77aM+wimlVH05WlhKZn4pHeK0HYs62dHio6xOW83o1nour2rYqpvq9RORp4HOInLSgoaK6/aUUqqhO9UdvapxWHRwEQ7j4Oyks+2OotRpqW7E7xqgGKs4jKzkoZRSPmN3hqvwi9Ufb+pk8/fPJz4snu7NTj5XVqmGpMoRP2PMduD/RGSDMWZ2PWZSSql6tys9n6AAPxKahtZ8s2pUisqL+PnQz1zW6TLd+KMavBqb4GjRp5RqDHal59O+uTZiVidblrKMYkexTvMqn6DdD5VSCtidUbszelXjseDAAqKCougf39/uKEqdNi38lFKNXnGZgwPZhbU6o1c1DuXOcn488CNnJZ5FoF+g3XGUOm3V9fG7vLonHjuCTSmlGrrkjAKM0R296mQ/HfyJ3NJcneZVPqO6di4XuT7GAcOBBa6vRwM/Alr4KaV8wvEdvVr4qQqyirN4/pfnaRvVlpGJI+2Oo1SdqG5X7y0AIjIT6H7sfF0RaQn8q37iKaWU5+1Kz0cE2jXX5s3K4jROnlzyJDklObw59k2C/YPtjqRUnXBnjV/bY0WfSxrQ2UN5lFKq3u3KyKd10zA9B1QdN23LNH5K+YkHBz1Il5gudsdRqs5UN9V7zI8iMgf4GDBYjZ0XejSVUkrVo93p+TrNq47bfGQzk9dMZkzrMVzT5Rq74yhVp2os/Iwxd4vIZcCZrktvG2O+9GwspZSqHw6nITmzgDM6Nbc7irLBV7u+YsaOGSRGJpIUmURiZCJvrX+L5qHNeW7Ec9qwWfkcd0b8ANYAecaYeSISJiKRxpg8TwZTSqn6cDC7kNJyp474NUKFZYW8tuo1gvyCSCtM47vk7zAY/MWfd899l+jgaLsjKlXnaiz8ROR24A4gBugAJABvAbq3XSnV4OmO3sbrs+2fcbTkKNPGT6NPbB9KHCWk5KUQHBBMQkSC3fGU8gh3RvzuAgYDywGMMTtFJM6jqZRSqp7sSrcKP23e3LgUlxfz/ub3GdpyKH1i+wAQ7B9M+ybtbU6mlGe5s6u3xBhTeuwLEQnA2uShlFIN3q70fJpHBNEkLMjuKKoezdg5gyPFR7ij9x12R1GqXrlT+C0SkceBUBEZB0wHvvVsLKWUqh9bU/PoFBdpdwxVj0odpby36T36x/VnUItBdsdRql65U/g9CmQAG4FJwCzgSU+GUkqp+pBfUs7mQzkMbNvU7iiqHn216yvSC9OZ1GeS3VGUqnfutHNxAv91PZRSymes2ZeN08CgtjF2R1H1pMxZxnub3qN3894MaznM7jhK1bsqCz8R2Ug1a/mMMb09kkgpperJyr1Z+PsJ/dvoiF9jMXP3TFLyU3h8yOPao081StWN+F1YbymUUsoGy/dk0aNVFBHB7rY0VQ1ZmaOMtze8TbeYbpyRcIbdcZSyRZU/7Ywx++oziFJK1aeScgfrDhzlhqFt7I6i6smXu77kYP5B/nX2v3S0TzVaNW7uEJGhIrJSRPJFpFREHCKSWx/hlFLKUzYezKG03Mngdrq+rzEoLi/mrfVv0S+un472qUbNnV29bwATgJ1AKDAR+KcnQymllKct35MF6MaOxuKTbZ+QUZTBPf3u0dE+1ai5tbDFGLNLRPyNMQ5giogs83AupZTyqJV7s+gYF0FMuDZu9nX5pfm8s+kdRrQawcAWA+2Oo5St3Cn8CkUkCFgnIi8DqUC4Z2MppZTnOJyG1XuzubBPK7ujqHrwwZYPyCnJ4Y/9/2h3FKVs585U7w2u++4GCoDWwBWeDKWUUp607XAueSXlDNH1fT4vuzibqZunMq7NOHo062F3HKVs586IXyZQaowpBp4VEX8g2LOxlFLKc1YcW9+nhZ/Pe3fjuxQ7irmr7112R1HKK7gz4jcfCKvwdSgwzzNxlFLK81buzSKhSSgJTULtjqI8KKckh0+3f8oF7S6gQ5MOdsdRyiu4U/iFGGPyj33h+jysmvuVUsprGWO0DW5IAAAgAElEQVRYsSdb27g0Al/s/IJiRzE39bjJ7ihKeQ13Cr8CEel/7AsRGQAUeS6SUkp5zp7MAjLzS7SNi48rd5bz8baPGRg/kC4xXeyOo5TXcGeN333AdBE55Pq6JXC15yIppZTnrNxrre8b3E7P5/VlCw8sJLUglUcGPWJ3FKW8So2FnzFmpYh0BboAAmwzxpR5PJlSSnnAij3ZxIQH0SE2wu4oyoOmbZlGQkQCo1qPsjuKUl7FnSPbrsRa57cJuAT4tOLUr1JKNSQr92YxsE1TPb3Bh209spU16WuY0HUC/n7+dsdRyqu4s8bvKWNMnoiMBM4FpgJvejaWUkrVvfS8YvZnFer6Ph/30daPCA0I5bJOl9kdRSmv407h53B9vAB40xjzNaBnHCmlGpw1+7IB6N9G1/f5qiNFR5i1ZxYXd7iYqKAou+Mo5XXcKfxSROQ/wFXALBEJdvN5SinlVVbvyyYowI+eCVoQ+KrpO6ZT5izjum7X2R1FKa/kTgF3FTAHOM8YcxSIAR7yaCqllPKAVfuy6Z0QTXCArvvyRU7j5LPtnzEiYQTtotvZHUcpr1Rj4WeMKTTGfGGM2en6OtUY84PnoymlVN0pLnOwKSWHAW11mtdX7Tq6i4yiDMa3G293FKW8lsembEWktYgsFJGtIrJZRO51XY8RkbkistP1UX8KK6U8bmNKDmUOw4Ak/ZHjq9amrQWgX1w/m5Mo5b08uVavHPiTMaYbMBS4S0S6A48C840xnbDOAX7UgxmUUgqw1veBbuzwZWsz1hIbGktiRKLdUZTyWh4r/FxTwmtcn+cBW4EErF6AU123TQUu9VQGpZQ6ZvW+bNo1D6d5RLDdUZSHrE1bS7+4ftqjUalq1LrwE5F5IjJbRC6sxXPaAv2A5UC8MSYVrOIQiKviOXeIyCoRWZWRkVHbmEopdZwxhjX7sumv07w+63DBYQ4VHNJpXqVqcCojfjcCTwJt3LlZRCKAGcB9xphcd9/EGPO2MWagMWZgbGzsKcRUSinL3iOFHCkoZaBu7PBZa9Nd6/vitfBTqjo1ntVbkWsjRnNjzGpgtRv3B2IVfR8ZY75wXU4TkZbGmFQRaQmk1za0UkrVxqq9WQAM0PV9Pmtt+lpCA0Lp0rSL3VGU8mrunNX7o4hEiUgMsB6YIiJ/c+N5ArwLbDXGVLz/G+Am1+c3AV/XPrZSSrlvzf5sokIC6BgbYXcU5SFr09fSO7Y3AX61Gs9QqtFxZ6o32jVFezkwxRgzABjrxvNGADcAY0RknesxHngJGCciO4Fxrq+VUspjVu/Lpn+bpvj56aJ/X5Rfms+O7B30j+tvdxSlvJ47/zQKcE3JXgU84e4LG2OWAFX9lD3b3ddRSqnTkVNYxo60fC7q3cruKMpDNmRswGmcurFDKTe4M+L3LNaRbbuMMStFpD2w07OxlFKqbqw5YPXv0xM7fNea9DX4iR+9Y3vbHUUpr+fOiF+qMeb43yZjTLI7a/yUUsobrN6bjb+f0Cexid1RlIesTV9Ll6ZdCA8MtzuKUl7PnRG/f7p5TSmlvM7qfdl0axlJeLAu+vdFZc4yNmRsoH+8ru9Tyh1V/iQUkWHAcCBWRB6o8K0owN/TwZRS6nSVO5ysO3CUqwbqEV6+anvWdoodxfSN62t3FKUahOr+CRwERLjuiaxwPRf4nSdDKaVUXdidUUBRmYM+rXWa11etSVsDQL9Y3dihlDuqLPyMMYuARSLyvjFmXz1mUkqpOrEpJQeAXgnRNidRnrI2fS0JEQnEh8fbHUWpBqG6qd7XjTH3AW+IiPnt940xF3s0mVJKnaaNKTmEBvrTXhs3+yRjDGvT1zKs1TC7oyjVYFQ31fuh6+Or9RFEKaXq2uZDOXRvFYW/Nm72OSWOEiavnsyR4iMMjB9odxylGozqpnpXuz4uqr84SilVNxxOw+ZDuVw5QDd2+JrtWdt59KdH2XV0F9d2vZaLO+gElFLuqrG/gYiMAJ4B2rjuF8AYY9p7NppSSp26PZkFFJY66Knr+3yG0ziZtmUar695naigKP599r85I/EMu2Mp1aC409jqXeB+YDXg8GwcpZSqG8c3diRq4ecLCsoKeGLJE8zfP59RrUfx7PBniQmJsTuWUg2OO4VfjjFmtseTKKVUHdqUkkNwgB8ddWNHg7cvdx/3LriXvbl7eWjgQ9zQ/QZEdN2mUqfCncJvoYi8AnwBlBy7aIxZ47FUSil1mjam5NCtZRQB/u4cUKS81eKDi3l08aP4+/nzn3H/YUjLIXZHUqpBc6fwO/a3rOK2KQOMqfs4Sil1+pxOw5ZDuVzSr5XdUVQtlTnK2HRkE7+k/sKK1BWsTltNl5guvD76dRIiEuyOp1SDV2PhZ4wZXR9BlFKqruzLKiSvpFwbNzcwC/cv5JGfHqGovAhB6BrTlYm9JnJ779sJDQi1O55SPsGdXb1/ruy6Mea5uo+jlFKn79jGjh6ttPBrSD7a+hExITE8OPBBBrUYRHSw/vdTqq65s/iloMLDAZwPtPVgJqWUOi2bUnII8vejc3xkzTcrr1BYVsia9DWMazOOsW3GatGnlIe4M9X7WsWvReRV4BuPJVJKqdO06VAOXVpEEhSgGzsaipWHV1LmLGNEwgi7oyjl007lp2IYoM2blVJeyRjDppRcbdzcwCw9tJTQgFD6x/W3O4pSPs2dNX4bsXbxAvgDsYCu71NKeaWD2UXkFJXpxo4GZmnKUga1GESQf5DdUZTyae60c7mwwuflQJoxptxDeZRS6rRsdG3s6JkQZXMS5a4DuQfYn7efa7tda3cUpXyeO2v89tVHEKWUqgubUnII8BO6tNCNHQ3F0kNLARiZMNLmJEr5Pl35rJTyKRtTcugcH0lwgL/dUZSblh5aSkJEAkmRSXZHUcrnaeGnlPIZxhg2H8rV9X0NSJmjjBWpKxiZMFLP31WqHmjhp5TyGWm5JWQVlNJD1/c1GOsy1lFYXsjwVsPtjqJUo1DlGj8RyePX3bwnMcboT1allFdJOVoEQOumYTYnUe5amrKUAAlgSMshNd+slDptVRZ+xphIABF5DjgMfAgIcB2gq6aVUl4nI68YgNjIYJuTKHctPbSUvnF9CQ8MtzuKUo2CO1O95xpj/m2MyTPG5Bpj3gSu8HQwpZSqrfS8EgDiorTwawgyizLZlrVNT+tQqh65U/g5ROQ6EfEXET8RuQ7rzF6llPIq6bkl+Ak0C9fCryFYdmgZACNaaeGnVH1xp/C7FrgKSHM9rnRdU0opr5KeV0zziGD8/XR3qLcrc5YxY8cMmoU0o0tMF7vjKNVouNPAeS9wieejKKXU6UnPK9Fp3gbAGMOLy19kTfoanh/xPH6iDSaUqi81/m0Tkc4iMl9ENrm+7i0iT3o+mlJK1U56bglxkSF2x1A1+GDLB0zfMZ3bet7GpR0vtTuOUo2KO//M+i/wGFAGYIzZAFzjyVBKKXUq0vNKiNMdvV5t4f6FvLbqNca1Gcc9/e+xO45SjY47hV+YMWbFb66VeyKMUkqdqnKHkyMFWvh5s21Z23jkp0fo3qw7L4x8Qad4lbKBO3/rMkWkA65mziLyOyDVo6mUUqqWjhSUYgzERulUrzdyOB08vPhhooKi+OeYfxIaEGp3JKUapRo3dwB3AW8DXUUkBdgDXO/RVEopVUvpua4efjri55UWHljInpw9vHLWK8SGxdodR6lGy51dvcnAWBEJB/yMMXmej6WUUrWT7jq1Qws/72OM4d2N79I6sjXjksbZHUepRs2dXb33ikgUUAhMFpE1InKO56MppZT7fj21Q6d6vc3KwyvZdGQTN/e4GX8/f7vjKNWoubPG71ZjTC5wDhAH3AK85NFUSilVS8ememMjdMTP27y36T2ahTTjko7aElYpu7lT+B1rgT8emGKMWV/hmlJKeYX0vGKahgUSFKA7Rb3J1iNbWXpoKdd3v55gfy3KlbKbOz8hV4vID1iF3xwRiQScNT1JRN4TkfRjjZ9d154RkRQRWed6jD/16Eop9Surh59O83qbKZumEB4YzlVdrrI7ilIK9wq/24BHgUHGmEIgCGu6tybvA+dVcn2yMaav6zHL7aRKKVUNPa7N+xzIO8CcfXO4qvNVRAVF2R1HKUU1hZ+IdHV92tf1sb2I9Afa4N5u4MVA1mknVEopN2TkFhOrO3q9ytTNU/EXf67vrh3AlPIW1RVwfwJuB16r5HsGGHOK73m3iNwIrAL+ZIzJPsXXUUopwGoXkpGvU73epKCsgK93fc2F7S8kLizO7jhKKZcqCz9jzO2uj6Pr8P3eBJ7HKhyfxyoqb63sRhG5A7gDICkpqQ4jKKV8TXZhGWUOoz38vMj8/fMpdhRzeafL7Y6ilKqgysJPRKr922qM+aK2b2aMSavw+v8FZlZz79tYJ4YwcOBAU9v3Uko1HsebN+saP68xc/dMEiIS6BPbx+4oSqkKqpvqvaia7xmg1oWfiLQ0xhw75/cyYFN19yullDuO9fCL1+bNXiGzKJPlh5dzW8/bENHuX0p5k+qmet3ZuVslEfkYGAU0F5GDwNPAKBHpi1U47gUmnc57KKUUVDi1Q6d6vcLsPbNxGicXtr/Q7ihKqd+ocXcugIhcAPQAjv9z2hjzXHXPMcZMqOTyu7VKp5RSbvj1nF4d8fMG3yV/R7eYbrRv0t7uKPZwlENWMmRuh4ztkLkDyoshOBKCo6yP/oHgKHM9SiG0CfS8AmIa6e+Zqjc1Fn4i8hYQBowG3gF+B6zwcC6llHJbem4JkcEBhAbpObB225Ozh81HNvPgwAftjmKPLd/ArAchP+3Xa1GJEBwBJXm/PnAtXfcLBP8gKCuEBX+BpOHQ91rocalVICpVx9wZ8RtujOktIhuMMc+KyGucwvo+pZTylIy8EmJ1Y4dX+C75O/zEj/PbnW93lPqVnw6zHoItX0GL3jD2GYjtAs07n1zAOZ3gLLdG/Y6tgcxJgQ2fwrr/wTd3w/ePwtA7Ydjd1migUnXEncKvyPWxUERaAUeAdp6LpJRStZOeV6zr+7yAMYbvkr9jcIvBjat334bpMPshKC2As/8Mw++xirqq+PmBX9CJ16IT4IwHYOT9cHAV/PwGLH4FVvwXRtwLQyZBULhnfx2qUXDnyLaZItIEeAVYg7Up4xNPhlJKqdrQc3q9w4bMDRzMP8gF7S+wO0r9MAbmPg1fTIRmneD3S+CMP1Vf9NVEBFoPgqumwqTF0HoIzH8W/t4XNn5uvadSp6HGws8Y87wx5qgxZgbWcW1djTFPeT6aUkrVzBhDem6Jjvh5ge+SvyPYP5ixSWPtjuJ55aXw5e9h6esw4Ba4ZbY1tVuXWvaB6z6DW+dAdCLMuA0+vsaaFlbqFLmzucMfuABoe+x+EcEY8zfPRlNKqZrllZRTVObQ5s02K3eWM2fvHEa1HkVEUITdcTyrJA8+uxF2L4DRT8KZD/66Vs8TkobCxHnwy5vWBpB/DYFxz0L/G09vdFE1Su6s8fsWKAY2Ak7PxlFKqdo51rxZp3rttSJ1BVnFWb6/qSP3kDXqdngTXPIv6Hd9/byvnz8Mvxu6XgDf3gPfPWBNAXc6B7qMh45jISSqfrKoBs2dwi/RGNPb40mUUuoU/NrDT0f87DRn3xwiAiMYmTDS7iies28ZfHaT1XplwifQ+Zz6zxDTDm78BnbMga3fwI7vYeN0qy1M1wtg8O3QZoRnRyAVALfeeiszZ84kLi6OTZusg8ieeuopvv76a4DuIvIDcLMx5tBvnysiNwFPur78izFmqohEAj9VuC0RmGaMua8uc7uzuWO2iNjwp1sppWqWcezUDp3qtU2Zs4x5++YxuvVogv198L+DMdbu2qkXWa1ZJs63p+g7RgS6nAeX/hse3GmtLxw0EZJ/hPcvgDeHw8p3rV3GymNuvvlmvv/++xOuPfTQQ2zYsAFgCzAT+PNvnyciMVinmQ0BBgNPi0hTY0yeMabvsQewDw+0z3On8PsF+FJEikQkV0TyRCS3roMopdSpODbVG6tTvbZZnrqc3NJczm17rt1R6l5ZMXz1B6spc8excPsCiOtqd6pf+flDm+Fw/kvwwFa4+A1r3d93D8DrvWDJ61CSb3dKn3TmmWcSExNzwrWoqBOm28M53qn7BOcCc40xWcaYbGAucF7FG0SkExDHiSOAdcKdqd7XgGHARmN0H7lSyruk5xUTHOBHVIhbJ1AqD5izdw6RgZEMazXM7ih1qyQPPp4Ae3+Csx6Fsx6xevB5q6Aw6H+Dte7wwHKrD+C8p2HZP6xegIMmai/AevDEE08A9MY65nZ0JbckAAcqfH3Qda2iCcCnnqi73PkTvBPYpEWfUsobpeeVEBcVjOiaJluUOcqYv38+o5NGE+QfVPMTGoqCI9bU7r5lcNnbMPox7y76KhKxdgJfPwNumwet+sHcP8PrvWHp33UK2MNeeOEFgA3AR8DdldxS2Q+r39ZY1wAf120yizt/ilOBH0XkMRF54NjDE2GUUqq2rB5+Os1rl59TfyavNM+3pnlzUmDK+ZC+Fa75CPpcbXeiU9d6kKsAnGv1BdQCsPYObzzVxtn/A66o5PpBoHWFrxOB4xtARKQPEGCMWX0qb1oTdwq/PcB8IAiIrPBQSinb6XFt9pqzdw6RQZEMa+kj07yH1sF751ltW66fAV18pD1N68FwwxcnFoD/6A+bv9TTQKpSnAsz74e3Rlq/T27YuXNnxS8vBrZVctsc4BwRaSoiTYFzXNeOmYCHRvughjV+rubNEcaYhzwVQCmlTkd6XgkjOza3O0ajVOooZcH+BYxtM5bAht5IOHuv1Rx543QIj4WbZ0KrvnanqnvHCsD9y63zhaffbPUCHP8qNG1jdzrvsf17a4NMXioMuxs6nzyiPWHCBH788UcyMzNJTEzk2WefZdasWWzfvh2gO1ZB93sAERkI/N4YM9EYkyUizwMrXS/1nDEmq8JLXwWM99QvrdrCzxjjEJH+nnpzpZQ6HcVlDvKKy4mL0qleOyxNWUp+WT7ntT2v5pu9VcER+OlVWPkOiD+MfABG3gch0XYn86ykITBxAaz876+ngZz1MAz5vbVJpLEqyITZj8CmzyGuO1z1ISQOqPTWjz8+eVDutttuA0BEthhjLjp23RizCphY4ev3gPcqe11jTPvT+jXUwJ1tcOtE5BtgOnB8QYAxps57yyilVG382spFp3rtMGffHKKDoxnccrDdUWqvtBCWv2m1OynNh77XwejHIaqV3cnqj38ADL0Tul1kFTvzn4Vf/m2NcA2aCME+fvReRcbAphkw+2FrinfU4zDyfgjwoQ1LLu4UfjHAEWBMhWsGDzQVVEqp2tBTO+yTXZzNjwd+5Ly25xHo14CmeR3lsO4j+PFFaxqv8/kw9mmI62Z3MvtEJ1qbWPb/AotetlrALP27dUTcsD/6ZPFzgrzDMPMB2P4dtOpvNcb24T8PNRZ+xphb6iOIUkrV1saUHAA6xjWikQmb5Zfm8+GWD/lgywcUlRdxacdL7Y5Us+y9kLwI9iyCPYuhIAMSB8Hv3rOaHytL0lBr/d/BVVYBOP8562i4K9/3zZFQY2Dd/2DOY1BeAuOeh6F/sEZCfViNvzoRSQT+CYzAGulbAtxrjDno4WxKKVWt5clZJDYNJbFpI16TVE/KneV8sOUD3tv0HjklOYxNGstdfe+iY9OO9oXKz4C1H1iNliu2RivKgtxUa0QvL9Uq9AAi4qH9aOh+iXWurfZ+rFziQLjuM2sn69d3w1tnWEVy+7PsTlZ3jh6Ab++F3fMhaThc/E9obuOf5XrkTlk7BasXzZWur693XRvnqVBKKVUTYwwr9mYxukuc3VEahQ+2fMDk1ZMZmTCSu/vdTY9mPewLU5wLP/8Lfn7DWp/nH+RqSeJqSxLaFCJbQGQrq3lxfA9odxbEdtFirzZ6XGZtcPj0BvjwUhjzFIy4r+E0sq6M0wmrp1jtbIyxdjMPvK1h/5pqyZ3CL9YYM6XC1++LyH2eCqSUUu7YmZ5PVkEpQ9rH1HyzOi0FZQVM2TSFEQkjeHPsm/X3xk4HFGZBcQ6U5FgfD2+Cpa9D4RHofimMeRKad6q/TI1NbBfrfOJv77E2fxxcCZe+CaFN7E5We/np8OUk2L0A2o+Ci/7RKFvYuFP4ZYrI9fzaTHAC1mYPpZSyzS/J1o+hoe2a2ZzE93287WOOlhzlrj531f2Ll+RDxjZI22w9snZDfpr1P+mCDDDOk5/TfhSc/WdIqLzNhqpjwRFwxbvQegjMeRzeHgVXfQAte9udzH27F8AXk6AkFy74Gwy8tdGO/rpT+N0KvAFMxhpHX+a6ppRStlmenEWr6BBax4TaHcWn5Zfm8/7m9zkj4Qx6xfaquxc+vBF+eAqSF/56LSgCmnWEqERrd2VEvNVMObQJBEdZvfXCYxvNWiyvIgJDJkHLvlbT53fHWQVUv+vsTlY9RxksfMFq2xPbBW78GuK7253KVu7s6t2PdeyIUkp5BWMMy/cc4YxOsUgj/Vd7fflo60fklORwV986Gu3LO2w1DF47zSroznzYOiEjvgdEJzWqtVYNUtIQmLQYZtwKX/8B9v4E578MIVF2JztZ+jYrY8pq6H8TnPdS425O7VJl4Scif67mecYY87wH8iilVI12Z+STmV/KkHa6vs+T8krzmLplKqMSR9Gj+Wls5ijMggPLrVYqq6eCoxSG3QVnPmhtxFANS0Qs3PAVLPo/WPwK7FsGl79ttYPxBo4yqw/hov+zRpGvfN/aqKKA6kf8Ciq5Fg7cBjQDtPBTStnil2TrWMuh7XV9nydN2zqNvNI87ux7Z+2f7CizesFt+w7SN1vX/AKhy/kw9hlo1qEuo6r65udvnXTS4Wz44naYcj6c8SdrBNeuhs+OMmt0b/bDkLre2vwz/lWrUFXHVVn4GWNeO/a5iEQC9wK3AJ8Ar1X1PKWU8rTle7KIjwqmTTOdtvGU3NJcPtz8IaNbj6Z7s1quiSrKhs9ushomtx8FPZ6ENsOszRiBuibTpyQNgd8vge8fs0b/VrwNnc6BzudBx7Ge3f3rKLMaTO9bBimrrGKvvNhaB3rVB1a/RnWSatf4iUgM8ABwHTAV6G+Mya6PYEopVRljDMuTjzC0fTNd3+chqw6v4uWVL5NXlscf+v6hdk/OSob/XQ1Ze+DSt6DvBM+EVN4jJAou/Rf0ugI2fm4VYxung18AdBlvtdyJ7VJ375d3GFa/D6umQP5hCAixNp0MvA0SB0CHMbqEoBrVrfF7BbgceBvoZYzJr7dUSilVhT2ZBaTnlWj/Pg84kHuAv63+G/P2z6NFeAteO+s1usZ0df8F9v8Cn1xrtWC58WtoO8JzYZX36TDGejgd1rFv276FVe/DtpnQ9zoY9ah1LvCpMMZaJ7ribdjyNTjLrRHFQX+HjmeDfwM6L9pm1Y34/QkoAZ4EnqjwL2vB2tzhhVt4lFK+bvkeXd/nCd/s/oZnlj1DgF8Af+z3R27sfiMhASHuPbmsCBa/ai2ob5IE103XNXyNmZ+/NQWcNMQ66eOn12DlO7DhM+hynjUaFxwJQZFWIdj1gqqnhEsLYdPnVsF3eCMER8PgO2DQRP0zdoqqW+One+qVUl5nefIRmkcE0755uN1RfEZReRGvrXqN7s26M3nUZGLDarEYfvcCmPkAZO+B3tfAeS9CmI7GKpfw5tafiaF3Wrts9y2zmnaX5EF5kXXPzGDoOh76XAttR0L6Ftj/szWCvPcn68SWuO5w4WTodZXVUFqdMncaOCullFew+vdlMaR9jK7vq0MzdswgqzirdkVfcS589yfY+BnEdIAbv4H2Z3k2qGq4miTBJf868ZqjHA6vh/WfWGsDN3954vebtoOuF0Lfa6HNiEZ70kZd08JPKdVg7MksIDWnmKHav6/OlDpKmbJ5CgPiB9A/vr97T8reZ23gOLITznoERj4AgW5OCyt1jH+AtdM7YQCc8wLsmmu1Y2nZB1oPhch4uxP6JC38lFJeo7jMwYaDOexMz2NnWj470vJIOVpEXnE5+cXllDqsc1t1fV/d+Xr316QXpvP8CDdbsx5YCZ9MgPJSuH6G1a5FqdMVEGSt9et6gd1JfJ4Wfkop25U7nExffZC/zd1BRl4JAOFB/nSMj6RPYhOiQgOICA4kMiSApJgwOsVH2pzYN5Q7y3lv43v0bNaTYS2H1fyEjZ/DV3+AqJZw8yyI7ez5kEqpOqWFn1LKNsYYFm5P56XZ29iRls+ANk3562W96N4qilbRIbqOz8Nm75nNwfyDPDzo4Zp/r9f9D766E5KGwdUfQbiOuirVEGnhp5SyhdNpuOeTtczckErbZmG8dX1/zu3RQou9euI0Tt7Z+A6dmnbirNY1bMo4sAK+vRfanWW1agkIrp+QSqk6p4WfUsoWby7azcwNqdxzdifuHt2RoADtIFWf5u+fT3JOMi+f+TJ+Us3vfU4KfHIdRCVYh91r0adUg6aFn1Kq3i3bnclrP2znoj6tuH9sJx3lq2fZxdm8tuo12ka15Zw251R9Y1mRdRJHWRHc9I3251PKB2jhp5SqV+m5xdzz8TraNg/nxct7adFXz8ocZdz/4/1kFGYw5bwp+Pv5V36jMfD13dbB9xM+hrhu9RtUKeURHptbEZH3RCRdRDZVuBYjInNFZKfro56irJQPO5hdSFpuMcYYwNq9+8eP15JfUsab1w0gIlj/7VmfjDG8sPwFVqet5rkRz9E7tndVN8Lcp6yjss5+CrqcX79BlVIe48mfuu8DbwAfVLj2KDDfGPOSiDzq+voRD2ZQStnk63Up3PfpOoyB5hFBdG8VTYCfsHxPFq9e2YcuLbQlS32btnUaM3bO4PZet3NB+yr6pTkdMPM+WPMBDLzNas6slPIZHiv8jDGLRaTtby5fAoxyfT4V+BEt/JTyOXO3pPHAZ+sZ3DaG83q2YPOhXDYfymVnWk0Kv8MAACAASURBVB7XDknidwMS7Y7Y6Px08CdeXfUqZyedzd397q78pvISmHEbbP0WznwIRj+hx2Qp5WPqe54l3hiTCmCMSRWRuKpuFJE7gDsAkpKS6imeUup0Ld2VyV3/W0PPhGjevXnQCdO5DqfBT+uIercvdx+PLH6Ezk0789eRf618F29JnrV7d88iOPdFGPaH+g+qlPI4r+2fYIx52xgz0BgzMDbWzUPDlVK2WrM/m9s/WEW7ZuFMvWXQSWv4/P1EN3PUs8KyQu5beB/+fv78ffTfCQsMO/mm5EXwnzNh7xK49C0t+pTyYfU94pcmIi1do30tgfR6fn+llIdsPJjDLVNWEhsZzIe3DaZJWJDdkRo9YwzPLHuG5Jxk3hz7Jq0iWp14Q2GWtYlj7TRo2g5u/BranWFPWKVUvajvwu8b4CbgJdfHr+v5/ZVSHrB6XxY3v7eSqNBApt02hLioELsjKazNHLP3zube/vcyvNXwE7+5/Xv45m6r+Bt5P/x/e/cdX1V9P3789b4jO7khg5CEBAKyp4ggw4F+VdyjThS3re2vu2qt/bba1t1q1dqvo9aFe1uLipQiIijIlshMGBlkkZ17c+fn98e5QTYiyb0Z7+fjcR53nHPPeR+OHt58Pufz/pz4a3DGRydQpVTEdFjiJyKvYA3kyBCRUuAOrITvdRG5HtgOXNxRx1dKRcbizTXc8MIyslLieOmGieSkavLQGSyrWMaDyx7k5LyTuX7k9XuuXD8bXpsJWSPgyrch+wBlXZRS3U5Hjuq9/ACrTumoYyqlImv+hipumrWcfukJvHjDRHona0tfZ+AJeLj101vJS87j7ql37/lc5eZ58MY1kDPW6tqN1bI6SvUkWj1VKfWdLCneyfdfWMaQPsm8cN1E0hL1mb7OYnbxbKo91dx/wv0kxSR9s2LrImvkbsYQuPItTfqU6oE08VNKHTa3L8Atb64hJzWel244Dle8M9ohqTBjDC+te4mhaUMZnzX+mxWly+HlSyE1D2a+A/E6cZJSPVGnLeeilOq8HvhoA9tr3TzwvdGa9HUySyuWsrl+M1cMu8Lq4g0GYNGj8NxZkJhude8maYkspXoqbfFTSh2WJcU7eW7xVq6Z3J+JA9KjHY7ay4vrXiQtLo0zCs6AirXWyN3ylTDkLDj7IUjuE+0QlVJRpImfUupb8/iC3PrWGvLS4rl1+pBoh6P2UtJYwoKSBdw48npiF/wFPnvI6tK9+DkYfr5Ov6aU0sRPKfXt/eXjDWzb6eblGyeSEKO3j87m5fUvYxcbl675ALZ9AWMuh9PvgYS0aIemlOok9M6tlPpWlm+r45lFW7jyuHwmD8yIdjhqLy3+Ft7d+CaneXz0rl4NFzwJYy6LdlhKqU5GEz+l1CEZY7jng3X0To7ltjOGRTsctbegn3fn/ormYCtXBmLgxnlWcWallNqLJn5KqUOav6GK5dvquPuCkSTF6m2j0/DUw4rn8S15kldSQoyOcTHq+o8hzhXtyJRSnZTewZVSBxUKGf4yZyP5aQlcMj4v2uEogKZKa+DGilkU4eW2vv3Zho+HT7xbkz6l1EFp4qeUOqgP11bw9Y5GHrpkDE67lv6MqoAPljwBCx7ABDy8OmQqD/pKSHAm8ujkvzAtf1q0I1RKdXKa+CmlDigQDPHg3A0M6p3EeWNzox1Oj+UP+fl06aPUr5qF212DO28wK9JyWVyziim5U7hryl1kxOuAG6XUoWnip5Q6oHdWllFc3cITV47DbtMacFHhbeL+ty7gNX8lxGPV5QtVk9Tg4TcTfsPlQy+3ZuhQSqlvQRM/pdR+eQNBHv7PJkblujh9hM72EBXlq/jqnWt4PTHAJcmDuPF/HiE+zkWCIwGnXafKU0odPk38lFL79dIX2ymr93DPhaO0RSnSjIElTxKY+zv+lJNFZmwqvzhnFkkxSdGOTCnVxWnip5Tax9qyBu7/aD0nDM7khEH67FhE+T3w7g+h8B1eGziBdaEK/jzpfzXpU0q1Cx2ip5TaQ4PHz49eWkFaYgx/vWSMtvZFUnMVPHc2FL5L1Um38jd7E1NypnB6v9OjHZlSqpvQxE8ptUsoZPjV66sor/fw2IxxpCfFRjuknqPya/jHKVBZCJfO4gGpwx/0c/vE2zX5Vkq1G038lFK7PPFpEf9ZV8X/njWMY/r1inY4PYMxsO59eOZ0CPrg2g9YmJzKnK1zuHH0jeSn5Ec7QqVUN6LP+CmlAFi8uYa/zNnAOWNyuHpy/2iH0zNUrYc5v4Gi/0KfUXD5qxQbH7/+8McclXoU1428LtoRKqW6GU38lFKsr2jkpheXMyAzift0FG/Hc9fCJ/fBl09DbBJMvw+OvYEaXwM/+uAGYmwxPHbKY8TYY6IdqVKqm9HET6kebvtONzP/uZSEGAfPXnMsibF6W+hQNZth1vnQWAbHXAvTfguJ6XgCHn4y7yfs9Ozk2enPkpukM6Uopdqf3uGV6sGqGlu58p9L8AdDvPyDSeSlJUQ7pO5tx2qYdaH1/vr/QN9jAAiGgvxm4W8o3FnIw9MeZmTGyCgGqZTqzjTxU6qHanD7ueqZpdQ0e3n5xuMYlJUc7ZC6t22fw8uXQGwKXPUeZBy1a9XfVv6NedvncduE2zg5/+QoBqmU6u50VK9SPVCLN8C1zy2luLqFp2aOZ2xearRD6t42zYVZF0BSFlw/Z4+k78uKL3lm7TNcNPgirhh2RRSDVEr1BJr4KdXDeHxBrn/+S1aXNvDIZWOZqjNzdKyl/4CXL4WMQXDth+Dqu2tVk6+J2z+7nfyUfG4Zf0sUg1RK9RTa1atUD9LqD/L9WctYsqWWhy8dyxmjsqMdUvcV9MOHv4Zl/4TB0+HCf0Bcyh6b3LvkXqrd1bxwxgskOPX5SqVUx9PET6kewhcI8eOXV7BwUw0PfG80543VUaMdxl0Lb1wNWz6FKT+DU+4Am32PTeZsncP7xe/zwzE/ZHTm6CgFqpTqaTTxU6qbC4UMy7fX8X/zNzN/QzV/Om8ElxybF+2wuq/qDfDKZdBQCuc/DmNn7LNJlbuKP33xJ0amj+TG0TdGIUilVE+liZ9S3dSqknreW1XGB1/toLLRS6zDxh3nDGfmpP7RDq372vQfePNacMTC1f+G/In7bGKM4Y7Fd+ANeLn3+Htx2pxRCFQp1VNp4qdUN7O+opF7P1jPgo3VxNhtnDgkk7NHZ3PKsCyStDhzxzAGvngcPv4t9B4Bl78MqfufY/eDLR/wWdln3DbhNvq7+kc2TqVUj6d/CyjVTexo8PDQxxt5c0UpybEObj9zKJdNyCclTluUOpS/FT68BVa8AEPPhguetKZh24/61noe+PIBRmWM4rIhl0U4UKWU0sRPqS6vpNbN0wuLefXLEoyBG48fwI9OGkhqgs7z2uEqC+GtG6GqEI6/2Zp+zXbgKlkPLn+QRm8jT536FPa9BnsopVQkaOKnVBdVWN7AkwuKmf3VDmwCFxydy09OHqTTrkVCKARLHof/3AlxqTDjDRh82kF/smTHEt7d/C7Xj7yeIWlDIhOnUkrtRRM/pboIbyDIl1vqWLCxigUbq9lY2UxSrIMbphZw3dQCslLioh1iz7CzCGb/Eoo/gSFnwbmPQuLBi2C3Blr54+d/JC85j5vG3BSZOJVSaj808VOqkwuGDI/M28Q/Pi3G4w8SY7dxbEEvLj02n4uO6YsrXp/hi4iGUljwAKx8ERxxcM4jMO5qEDnkT59a8xTbm7bz1KlPEefQBF0pFT2a+CnVidW7ffz01VV8urGas0Znc+HRuRw3IJ1EHZ0bOS01sPAh+PJpwMCEG+H4X0FS72/18011m3h27bOcO/BcJuVM6thYlVLqEPRvD6U6qcLyBm56cTkVDa3cc8EoLp+Qh3yL1iXVTlob4PO/W4vfDWNmwEm/PmCZlv0JmRB3fn4nyTHJ3Dz+5g4MVimlvh1N/JTqZGqavby5vJS/zt1Ir4QYXvvBJMbl94p2WD2H3wNLn4LP/gqeOhh+vjVaN3PwYe/q9Q2vs6Z6DfdMvYdecXoNlVLRp4mfUhHgD4bYVNnM2rIG1pTVU1jeSHKckxE5KYzMcTE8J4WiqmZeX1bCf9dXEQgZjh+UwUOXjCUzOTba4fcMfg8sexYWPQzNlXDUqXDy/0LO2O+0u8qWSh5e8TCTsidx9oCz2zlYpZT6bqKS+InIVqAJCAIBY8z4aMShVCR8VdrAtc8tpabZB0ByrIPhOSnUNHn5x6fFBEJm17YZSTFcO6U/F4/PY3BWcrRC7ln8Hlj+nNXC11wJBSfAxc9Bv8lHtNt7l95LMBTkd5N+p130SqlOI5otftOMMTVRPL5SHe6r0gauePoLUuKdPHLZWEbluuifnojNZiUC3kCQjRXNfL2jgbTEWE4akonTfuACwKod+Vt3S/gqoP/xcNGz0H/KEe963rZ5zNs+j18c8wvykvOOPFallGon2tWrVAdZU1rPlU8vISXeySs3HrffwsqxDjuj+roY1dcVhQh7KH8rrHjeSviadkC/qXDRP6H/1HbZ/YbaDdy95G6G9BrCzOEz22WfSinVXqKV+BngYxExwJPGmKf23kBEvg98HyA//9uPolOqM9g96Xv1+8fRt5fOptEpbJoL//4lNGyHflPgwn9AwfHtsmtjDG9sfIP7l96PK9bF3VPvxmnTGotKqc4lWonfFGNMuYj0BuaKyHpjzKe7bxBOBp8CGD9+vNnfTpTqjFZur+PqZ5Zq0teZtNTAR7fBV29AxhC46j0oOPFbFV/+Npp9zfzh8z/w0daPmJwzmXum3kN6fHq77FsppdpTVBI/Y0x5+LVKRN4BJgCfHvxXSnV+i4tquOH5ZWQmx/LSDRM16Ys2Y2DN61bS522Ck34DU38BjvYbKb1u5zpuXnAzZc1l/Gzcz7hu5HXYRJ/TVEp1ThFP/EQkEbAZY5rC708D/hjpOJRqb/9dX8lNL66gf3oCL14/kd46d250+T3wwc3WFGt9J8C5f4PeQ9tt98YYXt3wKn/+8s+kxaXxzOnPMC5rXLvtXymlOkI0WvyygHfC5Q0cwMvGmI+iEIdS7eb91eX84rVVDMtO4fnrJpCWGBPtkHq2uq3w2kyoWAMn3GK19Nns7bb7Jl8Tdyy+g7nb5nJC3xO4a8pdWqBZKdUlRDzxM8YUA2MifVylOkIgGOLv84t4eN5GxvfrxT+vOZaUOH2gP6o2zYW3brC6eS9/FYac0a67L6wp5FcLfkVlSyW/OuZXXDXiKu3aVUp1GVrORanvqLi6mV+8vprVJfWcNzaH+y4cTXxM+7UqqcO0Yw18ci9s+ACyRsGlL0DagHbbvTGGl9a9xIPLHyQzPpNnpz/L2N7fbVYPpZSKFk38lDpMxhhmfbGNez5YR6zDzmMzjubs0TnRDqvnqiy0Er5170OsC066HSb/BGLab2BNg7eB3y/6Pf8t+S8n5Z3EXVPuwhWrtReVUl2PJn5KHYaKhlZueXM1CzfVcMLgTP580WiydBBHdIRCsPAvMP8eiE2GE2+D434I8antdghjDAvLFnL3F3dT5anilvG3MHP4TJ2CTSnVZWnip9S39K/V5fzu3bX4AiH+dP5IrpyYrwlAtLQ2wjs3wYbZMPpSmH4fJKS12+6NMSwoXcATq5+gcGchecl5vDD9BUZljmq3YyilVDRo4qfUIdS7ffzuvULeX13O2LxU/nrpWAoyEqMdVs9VvRFeuwJ2FsH0+2HiD9qtELM/5Gfe9nk889UzrKtdR25SLn+Y/AfOGXAOTrsO2lFKdX2a+Cl1EAs2VnPrm6vZ2ezj5tMGc9OJA3HYdQRnVLTNsTvvT1YB5qv/1W7z69Z4anhz45u8seENqjxV5CXn8cfJf+TsgWfrtGtKqW5FEz+l9sPjC3Lvh+t44fNtDOqdxD+vPpaRufowf1QEvLByFnz6IDSVQ//j4fzHITXvgD8xxtDoa6S0uZSypjLKmq2l7bMv6MNpd+K0OXHYHBTVF+EP+ZmcM5nfT/o9U3OnYm/Hun9KKdVZaOKn1F7WlNbz81dXUVzTwvVTC7jl9CHEOTUJiDh3Lax+Bb54HBpKIG8iXPAEFJyw367dGk8Ns4tnM2frHLY2bKXJ37TH+pSYFHKTchnUaxDxjnj8QT/+kLWMzxrPJUMuocBVEKmzU0qpqNDET6ndzF9fxQ9fWk5aQgwv3ziRyQMzoh1Sz2IMbFsEy5+Dr9+DoM9K+M55BAaevE/C5w16WVi6kPc2v8fCsoUETZCR6SM5a8BZ9E3uS9+kvuQm55KblEtyTHJ0zkkppToRTfyUCnt7RSm3vLmG4dkpPHvtsWQkxUY7pJ7BXQvF82Hzf6Hov1Z3bqwLjrkGxl0NfUbusXlroJVFZYv4eNvHLChdQIu/hYz4DK4acRXnDzyfAantV7RZKaW6G038lAKeXljMXbPXMeWodJ6cOZ6kWP1fo10FfFC+wmrNq98OLTXg3gkt1dboXAzEuWDASTDkTBh27j4FmI0xzPp6Fn9f9XfcATeuWBen9z+d0/qdxsTsiThses2UUupQ9E6perRAMMQDczbw1KfFnDmqD3+9dCyxDn2e74i5a6F8JZStgG2fwfYlEPBY6xIyIDETEjMgaySMvAiOOgVyxoF9/7ekBm8Dv1v0O+aXzOeEvidw5bArGd9nvI64VUqpw6SJn+qxqhpb+ckrK1mypZaZx/XjznNHYLdpQebD0lIDOzdDbbG11GyCHaugbus322SNhGOutkqv5E+GxPTDOsTamrXcvOBmKlsqufXYW7ly2JVaOFsppb4jTfxUj7Rocw0/e3UlLd4gD148hu8d0zfaIXUNDaWw9TPYutB63T3BEzuk5kP2GDjmWsg5GnLGWl2430FlSyUvrX+JWV/PIjM+k+fPeJ7RmaPb5zyUUqqH0sRP9Si1LT6eXljM4wuKGJiZxCs3jmNQlo72PKidRVD4DhS+C5VfWd/FpVoteMfeAJlDIW2AlfS1w+wW62vX83zh83y05SNChJjefzq3T7wdV6zWUVRKqSOliZ/q9owxfLm1jpeWbOPDryrwBUNcOC6Xu84fSUKM/i+wX95mq4beylmwY7X1Xd8JcNpd1gCM3iPA1r4zmLj9bu5cfCcfbv2QeEc8lw69lCuGXUFe8oELNSullDo8+ree6rYaPH7eXlHKy0u2s6mqmeQ4BzMm5nPFxHxt5TuQ+hJY+pQ1NVprA2SPtZK94ecfdKaMI1XSWMJP5/+U4oZibhpzEzOHzyQlJqXDjqeUUj2VJn6qW2n1Byksb+TVpdt5f005rf4QY/JSeeCi0ZwzOof4GB2xu4+gHzbPg1UvwvoPrO+GnwvH/T/IO7bDD7+obBG3fHoLNrHx+P88zuScyR1+TKWU6qk08VNdkjGGLTUtfLa5huXb6iipdVNS56G6yQtAQoydC8f1ZcaEfJ1jd3+CfqhYA2vfhjWvQ0uVVWZl0o9gwg86tHWvjTGGZ9Y+w6MrH+Wo1KN4ZNoj9E3WQTZKKdWRNPFTnVplYytFVc00tvpp8FjLlpoWPt1YQ1m9VRcu2xVHQUYi04Zk0rdXAv3SEzh5aG+S47TG2y6+Fij+BLZ/AaVfWjX2Aq1gc8Lg02HsFTDo1HYZnPFtuP1ufr/498zZOofp/afzh8l/IMGZcOgfKqWUOiKa+KlOpcHtZ1FRDYuLalhctJPi6pZ9tkmOdTBpYDo3nTSQEwZl0C89MQqRdgEtNbDxI1g/25oKLdAK9hjrub3x10Pf8VBw4mHX1TtSJU0l/Gz+zyiqL+KXx/ySa0Zco3X5lFIqQjTxU1FnjGHpllpeWbqdD9ZW4AuESIyxM6EgjcuPzWdEbgqp8TG4EpykxDlIinVootAmFLK6aetLrJp6VV9DZaH12lBibePKs+a9HXIm5B8Hjo6Zg9jtd1PSZB3TaXPitDlx2Bz4Qj7cfjfugJuy5jLuX3o/AI+f8jiTc/V5PqWUiiRN/FSHCIYMW2qaKSxvpKi6hW07W9ha00JJnYeEGDvZrjiyUuLISIpl4aZqiqpbSI5zcPmxeZw7NofRfVNx2tu3XEiXE/BaBZPrt1tL0w5rbtuWaqs1r6nCWh/0fvMbmwMyBlsJXu/rYODJVkHldkyUg6EgJU0lbKrfxMa6jWyq28Smuk2UNJVgMIf8/aBeg3hk2iNapkUppaJAE79OxhhDdZOXwh2NNLj92GyCwybYRIh12EiIsZMY67CW8Pt4px1blKYaC4YM5fUetu10s622haKqFtaWNbC2vAG3LwiATSAnNZ6CjESm57pwewNUNLaytqyBqiYvQ/sk8+eLRnN2Tx51awzUb4Nti79Zaov23S4+LTzPbSZkj4ahZ1mFk1151mv6UeCIaffwGrwNvLnxTeZum0tRfRGtwVYAbGIjPzmfIWlDOHvA2RSkFuAQB/6QH3/ITyAUIMYeQ4IjgQRnAgmOBIamDSXG3v4xKqWUOjRN/KLMGMP6iiY+XFvByu11rNvRSE2z77D3kxBjJznOQbYrntzUeHJS4+idHEfQGLz+EN5AkEDIMCQrmQkFafTtFb9Pd6nHF8TjD+4RW22Lj6LqFoqqmymubqGi0UNTa4Dm1gBN3gD1bh/+4DetPHFOG8OzU7hkfB6jcl2MzHXRPyOBWEcPTegOJBSCmg2wbRFs+9xK9JrKrXVxqZA/CUZfaiVzqXlWYpeSE7HBF21KGkt4cd2LvLP5HTwBD0f3PpqLh1zMoNRBDE4bzEDXQOIccRGNSSml1HeniV+EGWNo9ATYXutm7rpKZq8pp6i6BZvAsOwUTh7am+HZKQzPcZGRFEPIGIIhCIRCeAMhPL4gzd4Abl+AFm8Qty9AszeI2xugweNnR0Mr63Y08p91lXgDoV3HbWs19AWt73JccRzTP42QMZTWeSircx8y4cxKiSU3NZ60xBjy0xJIjnOSmuCkX1oC/dIT6ZeeQJ+UuKi1PnZ6AR9s+RTW/Qs2fGB12QIkZ1uJXr/J1pI5rN1nxTgcwVCQReWLeGPDGywoXYDdZufMgjO5avhVDEkbErW4lFJKHTlN/NpZIBhiVUk9y7fVUev20eD2U+/2U+f2UdnYSkVjK61+K/kSgeMK0rl2SgHTR/YhI6n9Hro3xtDYGsBpF2LsNhx2G6GQYUNlE0u31LJ0ay3LttYS57TTt1c8w4dnkZsav08JFFe8kwGZiRRkJGp5lMPV1qq3/XPY+hls+g94GyAmCQadBkedYiV6vQra9Rm878IYQ2lTKbO3zObtTW+zo2UHaXFp3DDqBi4behm9E3pHNT6llFLtQ4w59MPY0TZ+/HizbNmyaIdBbYuPr8sb+XpHAzubfaTEO0mJd+KKd+LxBfh0Yw0LN1XT2BoAIMZho1eCtT41PobeKbH0SYmjj8taJhSk0TtZu8m6jYDPmtd2+2KrXt72z8FTZ61LyrLq5A071yqh4oz8dfcGvTR4G3aNsG3xt7CxbiMrKlewsmol1R6rBXJS9iQuGnwR0/Km4Yxw17JSSnUHIrLcGDM+2nHsT7dv8Wv1B1mxvY7aFh/17m+KANe7feFX63PIGARBBEQEm1iNMDYRBKhq8rKjoXXXfmPstl3dpm2yUmKZPrIPJw7uzZSj0klN0AfYu622wRjlK6F8FZQth9JlELCKSpM20Bp4kT/ZGmGbNiAqrXoVLRV8UvIJn5R8wtKKpfhD/n22yUnMYUL2BMb1HseknEk62lYppbqxbpn4+QIhFm2u4f3V5Xz8dSXN3sAe6+OcNqsuXLwTV4KTvr0ScNoFYyBkDCEDYL2a8OeCjESG56QwIsfFsOwU0hJjaPUHaQwnkiLCwMxErS/XHRkDjWXhJG+3pa01z+aEPiOtWnn9JlnP6yVFr2vUE/DwQfEHvLHxDQp3FgLQL6UfM4bOoJ+rnzXCNjzKNj85n+yk7KjFqpRSKrK6TeIXDBm+KN7J+6vL+XBtBQ0ePylxDs4c1YfpI/uQ1ysBV7hrNs7ZPiNM45x24px2eqdod22XZ4w12KK2GHYWWa+1ba9bwNtobSd2yBoOw86BnKOtpffwDiuKfDhKm0p5bcNrvL3pbRp9jQzuNZifj/s50/KnUZBSoP8oUUop1XUTPxMejfr1jkYWb65h9lcV1DR7SYyxc+rwLM4Zk8PxgzKJcfTwIsBqT556qF4fTu6Kdkv0toCv6ZvtxB6uizcQ8iZaRZFzjoasEeCMj178+1FUX8STa55kztY5CMIp+acwY9gMxvUep8meUkqpPXSJxK+ytoQHXr6NQDARbyiR6pY4NtfYqfQk4jGJiCOWU4dmcPbI3pw4MJV4ewhCQXBXQChgtebEp0Jsyrd/ziroB78b/K3Wq80B8b0gJjHqIzB7BGOsaxgKQMhvXYdAeAn6reths1sLgK8FvE17Lr5m69VTDzs3QdU6q8u2jdihVz/rebz8SdZzeOkDrdfU/IjXzDtcm+o28eSaJ/l468fEOeK4esTVXDH0CrISs6IdmlJKqU6qS4zqjS+IN0fdedR+1zmMISkUIjEUfjUhkkIGVzCEKxTEFQqREQxyaosHlzggIQMS0q3kzVgJYgl+4gM+MnyebxI9E9zv8XYlgLEpVsuPI46QM446Zzy9knOxpeRAch9ISANPPaalhvqWcspbqgjanYgzHpszAWISsCVkIMnZSHIfJD4dm82OiFgLgk1s4QEn1ue0uDQSnAn7xhT0g99jxRzril4NuFAImiuguRKaq3Z73e19S7U1FZlpS+oC4QQv/LntexM69PG+LWcipA+wumR7D7Pq5GUM6hLJHVit29sat7GyaiXFDcUU1RdRVF9EeUs5CY4EZgybwVXDr6JXXK9oh6qUUorOPaq3SyR+I0YOMa+8cT9ebz3N4aXF20izv5lmXxPNwVZaTJBmE6DFBGgK+WkMeWkIemkJWUWJE8TJxQn9ucqeRu/WFvyhEPNME6+EallhWgBI9AITrgAAD6ZJREFUlxiGOl0MiU1jVHwfjk7sR3p8mpXghQJWy5Gnzlq8jdT4mng3UM1boXpKJYjDGLICQbIDAVyhEDscdkocTpraac7ZGAMnBmyc1RpiqsdDrN/zTcLXxhZObpMyrQTXhKzEMOizziE2xUpcE9Ks6b+c8dZv7M5wK5rj4J9NCLzNVreotxncO60u07bn4gKt+8QdinNRkZTJ1kQXpbFxJDsSyLUnkOtIJM0ej+w6js16Fftux7ZZgyfCSTaOOLA79kwWAWKTrPp4sSnW+9hk63NMkrX9Efiy4ksWly8m3hFPojORBEcCTruTQChgTU0W9GMwuGJdpMWm0SuuF73iepEWl3bAqclaA62Ut5SzvXG7tTRtRxCyk7LJScyhT2IfGrwNLCxbyKKyRZQ2l1r/DdhiKHAVMCB1AMPShnHhoAtxxbqO6PyUUkq1L038jtCR1PHzh/xsrtvMc4XP8dHWj7CLnWl501hVvYoqdxW5SblcMuQSYmwxrK9dz/ra9RTVFxEwVkLRP6U/47LGkZech1XYxVK4s5D52+cTMAHGZ43npLyTqPfWs6OpjB2N26n31pGd2Id81wDyUweQk5SL0+bEYDBBP8bvJuSuxbhrMM1VGPdOQt5GjLcZ42/GeJsJGYNxODG2GEIOJ+tsIT4KNVJLgGRxMCEmg3h7DDG2GJz2GGJtDtJDhgy/jwyvh6xWNwW2GGz2GCt5stmtrk93rZWweeoO3LJ5qD9XoNZup8ERY00lFp4v1puSxTYbbA162OqrY6u7gm1NJbvmdt1bvCOe3KRc+ib1JTc5l9ykXNLj0q0EKzy3a3ZSNmlxad8pziPhCXj46/K/8sr6VxAEw+H/v5LoTKRXbC9SY1Pxhqw6eo3exn3+PJKdySDQtPtzhlh/PhP7TGRK7hQmZk8kPzkfu02nv1NKqc5ME78j1F4FnEuaSni+8Hn+XfxvxmSOYcbQGUzNnbrPX6S+oI+vd37NyqqVVnHb6pU0eBv22MYV6+K8gedx0eCLKHAVHHFs31YgFGDJjiXMLp7NVzVfWS1OIT+BUABPwIOnrY5cWFpcGpNzJjM1dyqTcybv2R246zk6P1vqi5izbS4VLRX4gz58IR/+oA9/0I8/5AsfJ0BLoJWd/kbqfI0HjdMmNnKTcumf0p/+rv70T+lPgauAvOQ8mnxNlDWXUdZcRmlTKaXNpdbnpjLcAfc++xKEUZmjmJY3jWl50xjgGtDhgxZWV6/mt5/9lm2N27hy2JX8dNxPcYgDd8CN2+/GG/TitDtx2qwFoMHbQJ23jlpPLbXeWupa66hrraO2tZYGbwOx9lhcsa5dS1ZCFv1S+pGfnI8r1oWI0OxrpqKlgvKWcmLtsRzd++gDthoqpZTqnDTxO0LRnrnDGIM36N3jO6fN2SlbXtx+NzWeGmo8NZQ0lfD5js9ZXLaYOm8dglDgKmBkxkhGZYxiaNpQ1lSvYfaW2Xy982sEISM+gxh7DE6bE4fNYSU2uyU48Y54MuMzyYjPID0+HVesC5t805XtEAd5yXnkp+QfdsJijKHeW0+dtw6P37Nrdon1tev5pOSTXTXpshKy6O/qT35yPvnJ+fRJ7EPIhAiYAIHQXsve3+1nm6AJ7kqeA6EA3qCXL3Z8QVZCFndNuYsJ2RPa9RoppZTq3jTxO0LRTvy6umAoyLradSwuX8ya6jV8VfMVta21u9YPTx/OWQVnMb1geqeek7WypZIFpQtYUbWCksYStjdtp95b/61/bxc7Dptj19L2uS3Jdcg360ZmjOTn435OUkxSB56RUkqp7kgTvyOkiV/7Msawo2UH62rXMcA1IKJd1e2twdtAtbsau82+R+K2xxL+XmvaKaWUioTOnPhFpY6fiEwHHgHswNPGmPuiEUdPJSLkJOWQk5QT7VCOWNvzckoppZQ6tIgXfBMRO/B34AxgOHC5iAyPdBxKKaWUUj1NNCr9TgA2G2OKjTE+4FXgvCjEoZRSSinVo0SjqzcXKNntcykwce+NROT7wPfDH70isvYg+3QBDQdZ3xH0mJE7ZgZQE+FjRoIec//a43p3hfPsaseL1DH3vv7d9Tz1mJbuen8fEuHjfXvGmIguwMVYz/W1fZ4J/O0Qv1l2iPVPReE89JgROuahrn93OU89Zvtd765wnl3teJE65t7Xv7uepx5z/9e7G51nh5/Xd12i0dVbCuTt9rkvUH6E+3z/CH+vx9Rj6jH1mF3tmD3hHPWYesyuesxOK+LlXETEAWwETgHKgC+BGcaYwoP8ZpnppMOiVcfT69+z6PXu2fT69yzd9Xp35vOK+DN+xpiAiPwYmINVzuWZgyV9YU91fGSqE9Pr37Po9e7Z9Pr3LN31enfa8+oSBZyVUkoppdSRi8YzfkoppZRSKgo08VNKKaWU6iE6ReInIheIiBGRodGORUWeiPxWRApFZI2IrBKRfeo6qu5FRPqKyHsisklEikTkERGJOcj2PxeRhEjGqDpG+F7/4G6fbxaRO6MYkupAIhIM39cLRWS1iPxSRDpF7tFTdZY//MuBz4DLoh2IiiwRmQScDYwzxowG/oc9C3yrbkZEBHgbeNcYMwgYDCQBdx/kZz8HNPHrHrzAhSKSEe1AVER4jDFjjTEjgFOBM4E7ohxTjxb1xE9EkoApwPWEEz8ROUlE/r3bNo+JyDXh92eKyHoR+UxEHt19O9UlZQM1xhgvgDGmxhhTLiLHiMgCEVkuInNEJBtARD4RkYdFZLGIrBWRCVGNXn0XJwOtxphnAYwxQeAXwHUikigifxGRr8ItwD8RkZ8COcB8EZkfxbhV+whgjXj8xd4rRKSfiMwLX/t5IpIvIi4R2drWSiQiCSJSIiLOSAeujowxpgprRq4fi8UuIn8WkS/D1/wHbduKyK3h+8BqEbkvelF3P1FP/IDzgY+MMRuBWhEZd6ANRSQOeBI4wxgzFciMUIyq43wM5InIRhH5PxE5MXxD/xtwkTHmGOAZ9mwNSjTGTAZ+FF6nupYRwPLdvzDGNALbgRuAAuDocAvwS8aYR7GKvE8zxkyLdLCqQ/wduEJEXHt9/xjwQtu1Bx41xjQAq4ETw9ucA8wxxvgjFq1qN8aYYqzcozdWg0+DMeZY4FjgRhEpEJEzsHKDicaYMcADUQu4G+oMid/lwKvh96+GPx/IUKDYGLMl/PmVjgxMdTxjTDNwDNa/AquB14AfACOBuSKyCvhfrBle2rwS/u2nQIqIpEY0aHWkBNhfHSkBTgCeMMYEAIwxtZEMTEVGONF/AfjpXqsmAS+H388CpobfvwZcGn5/Wfiz6rok/HoacFX4Pr8ESAcGYT3y86wxxg16H2hvES/gvDsRScfq9hkpIgaroLMB/sWeSWlc208iG6GKhHBX3yfAJyLyFfD/gEJjzKQD/eQQn1XnVgh8b/cvRCQFayrHYvR69hQPAyuAZw+yTdt/C/8C7hWRNKx/KP63g2NTHUREBgBBoArr7/SfGGPm7LXNdPQ+0GGi3eJ3EVazfj9jTH9jTB7Q1po3XERiw10Bp4S/Ww8MEJH+4c+Xoro0ERkiIoN2+2ossA7IDA/8QEScIjJit20uDX8/FauboCFiAav2MA9IEJGrAETEDjwIPIfV9X9TeGpHwn/RAzQByZEPVXWUcCvO61jdfW0W880gvyuwBv219QwsBR4B/h3+x6LqYkQkE3gCeMxYs0fMAX7Y9rymiAwWkUSs+8B1bSP5d7sPqHYQ1RY/rG7dvR/afAuYgXVDWANsAlYCGGM8IvIj4CMRqcG6EaiuLQn4W7i7NgBsxur2fQp4NJz4O7BaB9qm9qsTkcVACnBd5ENWR8IYY0TkAuD/ROR3WP8A/QC4HaslYDCwRkT8wD+wnvt6CvhQRHboc37dyoPAj3f7/FPgGRG5BevRj2t3W/ca8AZwUsSiU+0hPtyV68S6x88CHgqvexroD6wIj/avBs43xnwkImOBZSLi45v7g2oHXW7KNhFJMsY0h/8j+TuwyRjz12jHpSJDRD4BbjbGLIt2LEoppVRXE+2u3u/ixvC/HgoBF9YoX6WUUkopdQhdrsVPKaWUUkp9N12xxU8ppZRSSn0HUUn8RCRPROaLyLrw/H0/C3+fJiJzxZq/c66I9Ap/f0W4qvea8IwNY3bb13QR2SAim0Xktmicj1JKKaVUVxCVrt7w9FvZxpgVIpKMVcX/fOAaoNYYc184ietljPm1iEwG1hlj6sIVve80xkwMl4HYiDX/XynwJXC5MebriJ+UUkoppVQnF5UWP2PMDmPMivD7Jqy6bbnAecDz4c2ex0oGMcYsNsbUhb//gm9mcZgAbDbGFBtjfFgzf5wXmbNQSimllOpaov6MX7gY89FY07VkGWN2gJUcYs3lt7frgQ/D73OBkt3WlYa/U0oppZRSe4n2lG1JWAWbf26MabRK8x10+2lYiV/b/I37+4EOU1ZKKaWU2o+otfiFp2h5C3jJGPN2+OvK8PN/bc8BVu22/WisKt/nGWN2hr8uxZrfs01foLyjY1dKKaWU6oqiNapXgH9iDdh4aLdV/wKuDr+/GngvvH0+8DYw0xizcbftvwQGiUiBiMRgzfH4r46OXymllFKqK4rWqN6pwELgKyAU/vp2rOf8Xgfyge3AxcaYWhF5GvgesC28bcAYMz68rzOx5nG1A88YY+6O2IkopZRSSnUhOnOHUkoppVQPEfVRvUoppZRSKjI08VNKKaWU6iE08VNKKaWU6iE08VNKKaWU6iE08VNKKaWU6iE08VNKdSsiEhSRVSJSKCKrReSXInLQe52I9BeRGZGKUSmlokUTP6VUd+Mxxow1xowATgXOBO44xG/6A5r4KaW6Pa3jp5TqVkSk2RiTtNvnAViz/GQA/YBZQGJ49Y+NMYtF5AtgGLAFeB54FLgPOAmIBf5ujHkyYiehlFIdRBM/pVS3snfiF/6uDhgKNAEhY0yriAwCXjHGjBeRk4CbjTFnh7f/PtDbGHOXiMQCi7BmEtoS0ZNRSql25oh2AEopFQESfnUCj4nIWCAIDD7A9qcBo0XkovBnFzAIq0VQKaW6LE38lFLdWrirNwhUYT3rVwmMwXrGufVAPwN+YoyZE5EglVIqQnRwh1Kq2xKRTOAJ4DFjPdfiAnYYY0LATMAe3rQJSN7tp3OAH4qIM7yfwSKSiFJKdXHa4qeU6m7iRWQVVrduAGswx0Phdf8HvCUiFwPzgZbw92uAgIisBp4DHsEa6btCRASoBs6P1AkopVRH0cEdSimllFI9hHb1KqWUUkr1EJr4KaWUUkr1EJr4KaWUUkr1EJr4KaWUUkr1EJr4KaWUUkr1EJr4KaWUUkr1EJr4KaWUUkr1EP8f166Q8mlsAtEAAAAASUVORK5CYII=\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",
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+ "<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",
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+ " <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",
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+ " <tr>\n",
+ " <td>2020-12-10</td>\n",
+ " <td>16578</td>\n",
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+ " <td>36.940594</td>\n",
+ " <td>13.926573</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>2020-12-11</td>\n",
+ " <td>20964</td>\n",
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+ " <td>392.657665</td>\n",
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+ " <td>0.514053</td>\n",
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+ " <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",
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+ " <td>-92.0</td>\n",
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+ " <td>412.714286</td>\n",
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+ " <td>NaN</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>2020-12-13</td>\n",
+ " <td>21501</td>\n",
+ " <td>520</td>\n",
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+ " <td>64026</td>\n",
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+ " <td>31.106272</td>\n",
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+ " <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",
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+ " <td>64170</td>\n",
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+ " <td>-376.0</td>\n",
+ " <td>18023.000000</td>\n",
+ " <td>417.857143</td>\n",
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+ " <td>31.398955</td>\n",
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+ " <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": {
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+ "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",
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+ " <th></th>\n",
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+ " </tr>\n",
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+ " <td>456</td>\n",
+ " </tr>\n",
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+ " <tr>\n",
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+ " </tr>\n",
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+ " </tr>\n",
+ " <tr>\n",
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+ " </tr>\n",
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+ " </tr>\n",
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+ " <td>544.0</td>\n",
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+ " </tr>\n",
+ " </tbody>\n",
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+ "<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",
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+ "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",
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+ "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": {
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+ " <th>cases_diff</th>\n",
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+ " <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
+}
projects / covid19.git / blobdiff