{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The sql extension is already loaded. To reload it, use:\n",
      "  %reload_ext sql\n"
     ]
    }
   ],
   "source": [
    "import itertools\n",
    "import collections\n",
    "import json\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from scipy.stats import gmean\n",
    "import datetime\n",
    "\n",
    "import sqlalchemy\n",
    "\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "%load_ext sql"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [],
   "source": [
    "connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Connected: covid@covid'"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql $connection_string"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "conn = sqlalchemy.create_engine(connection_string)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [],
   "source": [
    "normalisation_date = '2020-08-01' # '2020-05-15'\n",
    "\n",
    "hospital_normalisation_date = {\n",
    "    'hospital_normalisation_date': normalisation_date\n",
    "}\n",
    "\n",
    "with open('hospital_normalisation_date.json', 'w') as f:\n",
    "    json.dump(hospital_normalisation_date, f)\n",
    "    \n",
    "hnd = pd.to_datetime(normalisation_date).strftime(\"%d %B %Y\")\n",
    "with open('hospital_normalisation_date.js', 'w') as f:\n",
    "    f.write(f\"document.write('{hnd}');\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>new_admissions</th>\n",
       "      <th>new_admissions_7</th>\n",
       "      <th>new_cases</th>\n",
       "      <th>new_cases_7</th>\n",
       "      <th>new_deaths</th>\n",
       "      <th>new_deaths_7</th>\n",
       "      <th>hospital_cases</th>\n",
       "      <th>hospital_cases_7</th>\n",
       "      <th>ventilator_beds</th>\n",
       "      <th>ventilator_beds_7</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-01-22</th>\n",
       "      <td>3341.0</td>\n",
       "      <td>3771.7500</td>\n",
       "      <td>29094.0</td>\n",
       "      <td>24870.428</td>\n",
       "      <td>1401</td>\n",
       "      <td>1238.7142</td>\n",
       "      <td>38144.0</td>\n",
       "      <td>38057.168</td>\n",
       "      <td>4076.0</td>\n",
       "      <td>4015.8572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-23</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3651.6667</td>\n",
       "      <td>20495.0</td>\n",
       "      <td>22463.666</td>\n",
       "      <td>1348</td>\n",
       "      <td>1241.7142</td>\n",
       "      <td>37266.0</td>\n",
       "      <td>37915.600</td>\n",
       "      <td>4066.0</td>\n",
       "      <td>4027.3333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-24</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14266.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>610</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37561.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4077.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-25</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4482.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>592</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4032.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-26</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1631</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            new_admissions  new_admissions_7  new_cases  new_cases_7  \\\n",
       "date                                                                   \n",
       "2021-01-22          3341.0         3771.7500    29094.0    24870.428   \n",
       "2021-01-23             NaN         3651.6667    20495.0    22463.666   \n",
       "2021-01-24             NaN               NaN    14266.0          NaN   \n",
       "2021-01-25             NaN               NaN     4482.0          NaN   \n",
       "2021-01-26             NaN               NaN        NaN          NaN   \n",
       "\n",
       "            new_deaths  new_deaths_7  hospital_cases  hospital_cases_7  \\\n",
       "date                                                                     \n",
       "2021-01-22        1401     1238.7142         38144.0         38057.168   \n",
       "2021-01-23        1348     1241.7142         37266.0         37915.600   \n",
       "2021-01-24         610           NaN         37561.0               NaN   \n",
       "2021-01-25         592           NaN             NaN               NaN   \n",
       "2021-01-26        1631           NaN             NaN               NaN   \n",
       "\n",
       "            ventilator_beds  ventilator_beds_7  \n",
       "date                                            \n",
       "2021-01-22           4076.0          4015.8572  \n",
       "2021-01-23           4066.0          4027.3333  \n",
       "2021-01-24           4077.0                NaN  \n",
       "2021-01-25           4032.0                NaN  \n",
       "2021-01-26              NaN                NaN  "
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qstr = '''select uk_data.date\n",
    "    , uk_data.new_admissions, uk_data_7.new_admissions as new_admissions_7\n",
    "    , uk_data.new_cases, uk_data_7.new_cases as new_cases_7\n",
    "    , uk_data.new_deaths, uk_data_7.new_deaths as new_deaths_7\n",
    "    , uk_data.hospital_cases, uk_data_7.hospital_cases as hospital_cases_7\n",
    "    , uk_data.ventilator_beds, uk_data_7.ventilator_beds as ventilator_beds_7\n",
    "    from uk_data left outer join uk_data_7 using (date)\n",
    "    order by uk_data.date'''\n",
    "hd2 = pd.read_sql_query(qstr, conn)\n",
    "hd2['date'] = hd2.date.astype('datetime64[ns]')\n",
    "hd2.set_index('date', inplace=True)\n",
    "hd2.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * postgresql://covid:***@localhost/covid\n",
      "390 rows affected.\n",
      "Returning data to local variable res\n"
     ]
    }
   ],
   "source": [
    "%%sql res << select uk_data.date\n",
    "    , uk_data.new_admissions, uk_data_7.new_admissions as new_admissions_7\n",
    "    , uk_data.new_cases, uk_data_7.new_cases as new_cases_7\n",
    "    , uk_data.new_deaths, uk_data_7.new_deaths as new_deaths_7\n",
    "    , uk_data.hospital_cases, uk_data_7.hospital_cases as hospital_cases_7\n",
    "    , uk_data.ventilator_beds, uk_data_7.ventilator_beds as ventilator_beds_7\n",
    "    from uk_data left outer join uk_data_7 using (date)\n",
    "    order by uk_data.date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>new_admissions</th>\n",
       "      <th>new_admissions_7</th>\n",
       "      <th>new_cases</th>\n",
       "      <th>new_cases_7</th>\n",
       "      <th>new_deaths</th>\n",
       "      <th>new_deaths_7</th>\n",
       "      <th>hospital_cases</th>\n",
       "      <th>hospital_cases_7</th>\n",
       "      <th>ventilator_beds</th>\n",
       "      <th>ventilator_beds_7</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-01-17</th>\n",
       "      <td>3725.0</td>\n",
       "      <td>3939.0000</td>\n",
       "      <td>28875.0</td>\n",
       "      <td>37337.855</td>\n",
       "      <td>671</td>\n",
       "      <td>1217.5714</td>\n",
       "      <td>38095.0</td>\n",
       "      <td>38292.285</td>\n",
       "      <td>3871.0</td>\n",
       "      <td>3857.4285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-18</th>\n",
       "      <td>4054.0</td>\n",
       "      <td>3872.8572</td>\n",
       "      <td>44732.0</td>\n",
       "      <td>35766.570</td>\n",
       "      <td>599</td>\n",
       "      <td>1223.5714</td>\n",
       "      <td>39181.0</td>\n",
       "      <td>38338.145</td>\n",
       "      <td>3916.0</td>\n",
       "      <td>3898.5715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-19</th>\n",
       "      <td>4132.0</td>\n",
       "      <td>3825.8572</td>\n",
       "      <td>39311.0</td>\n",
       "      <td>34143.285</td>\n",
       "      <td>1610</td>\n",
       "      <td>1240.8572</td>\n",
       "      <td>38765.0</td>\n",
       "      <td>38348.430</td>\n",
       "      <td>3947.0</td>\n",
       "      <td>3939.5715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-20</th>\n",
       "      <td>4016.0</td>\n",
       "      <td>3811.0000</td>\n",
       "      <td>35015.0</td>\n",
       "      <td>32707.428</td>\n",
       "      <td>1820</td>\n",
       "      <td>1248.4286</td>\n",
       "      <td>38650.0</td>\n",
       "      <td>38294.000</td>\n",
       "      <td>3953.0</td>\n",
       "      <td>3969.8572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-21</th>\n",
       "      <td>3598.0</td>\n",
       "      <td>3828.2000</td>\n",
       "      <td>31430.0</td>\n",
       "      <td>30620.428</td>\n",
       "      <td>1290</td>\n",
       "      <td>1239.7142</td>\n",
       "      <td>37957.0</td>\n",
       "      <td>38217.715</td>\n",
       "      <td>3960.0</td>\n",
       "      <td>3999.2856</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-22</th>\n",
       "      <td>3341.0</td>\n",
       "      <td>3771.7500</td>\n",
       "      <td>29094.0</td>\n",
       "      <td>24870.428</td>\n",
       "      <td>1401</td>\n",
       "      <td>1238.7142</td>\n",
       "      <td>38144.0</td>\n",
       "      <td>38057.168</td>\n",
       "      <td>4076.0</td>\n",
       "      <td>4015.8572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-23</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3651.6667</td>\n",
       "      <td>20495.0</td>\n",
       "      <td>22463.666</td>\n",
       "      <td>1348</td>\n",
       "      <td>1241.7142</td>\n",
       "      <td>37266.0</td>\n",
       "      <td>37915.600</td>\n",
       "      <td>4066.0</td>\n",
       "      <td>4027.3333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-24</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14266.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>610</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37561.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4077.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-25</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4482.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>592</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4032.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-26</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1631</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            new_admissions  new_admissions_7  new_cases  new_cases_7  \\\n",
       "date                                                                   \n",
       "2021-01-17          3725.0         3939.0000    28875.0    37337.855   \n",
       "2021-01-18          4054.0         3872.8572    44732.0    35766.570   \n",
       "2021-01-19          4132.0         3825.8572    39311.0    34143.285   \n",
       "2021-01-20          4016.0         3811.0000    35015.0    32707.428   \n",
       "2021-01-21          3598.0         3828.2000    31430.0    30620.428   \n",
       "2021-01-22          3341.0         3771.7500    29094.0    24870.428   \n",
       "2021-01-23             NaN         3651.6667    20495.0    22463.666   \n",
       "2021-01-24             NaN               NaN    14266.0          NaN   \n",
       "2021-01-25             NaN               NaN     4482.0          NaN   \n",
       "2021-01-26             NaN               NaN        NaN          NaN   \n",
       "\n",
       "            new_deaths  new_deaths_7  hospital_cases  hospital_cases_7  \\\n",
       "date                                                                     \n",
       "2021-01-17         671     1217.5714         38095.0         38292.285   \n",
       "2021-01-18         599     1223.5714         39181.0         38338.145   \n",
       "2021-01-19        1610     1240.8572         38765.0         38348.430   \n",
       "2021-01-20        1820     1248.4286         38650.0         38294.000   \n",
       "2021-01-21        1290     1239.7142         37957.0         38217.715   \n",
       "2021-01-22        1401     1238.7142         38144.0         38057.168   \n",
       "2021-01-23        1348     1241.7142         37266.0         37915.600   \n",
       "2021-01-24         610           NaN         37561.0               NaN   \n",
       "2021-01-25         592           NaN             NaN               NaN   \n",
       "2021-01-26        1631           NaN             NaN               NaN   \n",
       "\n",
       "            ventilator_beds  ventilator_beds_7  \n",
       "date                                            \n",
       "2021-01-17           3871.0          3857.4285  \n",
       "2021-01-18           3916.0          3898.5715  \n",
       "2021-01-19           3947.0          3939.5715  \n",
       "2021-01-20           3953.0          3969.8572  \n",
       "2021-01-21           3960.0          3999.2856  \n",
       "2021-01-22           4076.0          4015.8572  \n",
       "2021-01-23           4066.0          4027.3333  \n",
       "2021-01-24           4077.0                NaN  \n",
       "2021-01-25           4032.0                NaN  \n",
       "2021-01-26              NaN                NaN  "
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hospital_data = res.DataFrame()\n",
    "hospital_data['date'] = hospital_data.date.astype('datetime64[ns]')\n",
    "hospital_data.set_index('date', inplace=True)\n",
    "hospital_data.tail(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>new_admissions</th>\n",
       "      <th>new_admissions_7</th>\n",
       "      <th>new_cases</th>\n",
       "      <th>new_cases_7</th>\n",
       "      <th>new_deaths</th>\n",
       "      <th>new_deaths_7</th>\n",
       "      <th>hospital_cases</th>\n",
       "      <th>hospital_cases_7</th>\n",
       "      <th>ventilator_beds</th>\n",
       "      <th>ventilator_beds_7</th>\n",
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       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-01-03</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-04</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-05</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-06</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-07</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-22</th>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-23</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-24</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-25</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-26</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>390 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            new_admissions  new_admissions_7  new_cases  new_cases_7  \\\n",
       "date                                                                   \n",
       "2020-01-03           False             False      False        False   \n",
       "2020-01-04           False             False      False        False   \n",
       "2020-01-05           False             False      False        False   \n",
       "2020-01-06           False             False      False        False   \n",
       "2020-01-07           False             False      False        False   \n",
       "...                    ...               ...        ...          ...   \n",
       "2021-01-22            True              True       True         True   \n",
       "2021-01-23           False              True       True         True   \n",
       "2021-01-24           False             False       True        False   \n",
       "2021-01-25           False             False       True        False   \n",
       "2021-01-26           False             False      False        False   \n",
       "\n",
       "            new_deaths  new_deaths_7  hospital_cases  hospital_cases_7  \\\n",
       "date                                                                     \n",
       "2020-01-03        True         False           False             False   \n",
       "2020-01-04        True         False           False             False   \n",
       "2020-01-05        True         False           False             False   \n",
       "2020-01-06        True          True           False             False   \n",
       "2020-01-07        True          True           False             False   \n",
       "...                ...           ...             ...               ...   \n",
       "2021-01-22        True          True            True              True   \n",
       "2021-01-23        True          True            True              True   \n",
       "2021-01-24        True         False            True             False   \n",
       "2021-01-25        True         False           False             False   \n",
       "2021-01-26        True         False           False             False   \n",
       "\n",
       "            ventilator_beds  ventilator_beds_7  \n",
       "date                                            \n",
       "2020-01-03            False              False  \n",
       "2020-01-04            False              False  \n",
       "2020-01-05            False              False  \n",
       "2020-01-06            False              False  \n",
       "2020-01-07            False              False  \n",
       "...                     ...                ...  \n",
       "2021-01-22             True               True  \n",
       "2021-01-23             True               True  \n",
       "2021-01-24             True              False  \n",
       "2021-01-25             True              False  \n",
       "2021-01-26            False              False  \n",
       "\n",
       "[390 rows x 10 columns]"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hospital_data == hd2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "new_admissions       float64\n",
       "new_admissions_7     float64\n",
       "new_cases            float64\n",
       "new_cases_7          float64\n",
       "new_deaths             int64\n",
       "new_deaths_7         float64\n",
       "hospital_cases       float64\n",
       "hospital_cases_7     float64\n",
       "ventilator_beds      float64\n",
       "ventilator_beds_7    float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hospital_data.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "new_admissions       float64\n",
       "new_admissions_7     float64\n",
       "new_cases            float64\n",
       "new_cases_7          float64\n",
       "new_deaths             int64\n",
       "new_deaths_7         float64\n",
       "hospital_cases       float64\n",
       "hospital_cases_7     float64\n",
       "ventilator_beds      float64\n",
       "ventilator_beds_7    float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hd2.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='date'>"
      ]
     },
     "execution_count": 116,
     "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[['new_admissions', 'new_admissions_7']].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='date'>"
      ]
     },
     "execution_count": 117,
     "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[['hospital_cases', 'hospital_cases_7']].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='date'>"
      ]
     },
     "execution_count": 118,
     "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[['ventilator_beds', 'ventilator_beds_7']].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 720x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(10, 8))\n",
    "ax = hospital_data.loc['2020-03-20':, ['hospital_cases', 'ventilator_beds']].plot(\n",
    "    secondary_y='ventilator_beds',\n",
    "    figsize=(10, 8),\n",
    "    title=\"People in hospital, and on mechanical ventilation\")\n",
    "# axl.legend(['Number in hospital', 'Number on ventilator'])\n",
    "plt.savefig('people_in_hospital.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [],
   "source": [
    "hospital_data['cases_m7nd'] = hospital_data.new_cases_7 / hospital_data.new_cases_7.loc[normalisation_date]\n",
    "hospital_data['deaths_m7nd'] = hospital_data.new_deaths_7 / hospital_data.new_deaths_7.loc[normalisation_date]\n",
    "hospital_data['admissions_m7nd'] = hospital_data.new_admissions_7 / hospital_data.new_admissions_7.loc[normalisation_date]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "96.1"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(int(hospital_data.loc[normalisation_date:, ['cases_m7nd', 'admissions_m7nd', 'deaths_m7nd']].max().max() * 10) + 1) / 10.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ymax = (int(hospital_data.loc[normalisation_date:, ['cases_m7nd', 'admissions_m7nd', 'deaths_m7nd']].max().max() * 10) + 1) / 10.0\n",
    "ax = hospital_data.loc[normalisation_date:, ['cases_m7nd', 'admissions_m7nd', 'deaths_m7nd']].plot(\n",
    "    ylim=(0, ymax), \n",
    "    figsize=(10, 8),\n",
    "    title=\"Cases, hospital admissions, and deaths\\n(7-day moving averages)\")\n",
    "\n",
    "lvi = hospital_data.cases_m7nd.last_valid_index()\n",
    "ax.text(x = lvi + pd.Timedelta(days=1), y = hospital_data.cases_m7nd[lvi], s = f'{hospital_data.cases_m7nd[lvi]:.2f}')\n",
    "\n",
    "lvi = hospital_data.admissions_m7nd.last_valid_index()\n",
    "ax.text(x = lvi + pd.Timedelta(days=1), y = hospital_data.admissions_m7nd[lvi], s = f'{hospital_data.admissions_m7nd[lvi]:.2f}')\n",
    "\n",
    "lvi = hospital_data.deaths_m7nd.last_valid_index()\n",
    "ax.text(x = lvi + pd.Timedelta(days=1), y = hospital_data.deaths_m7nd[lvi], s = f'{hospital_data.deaths_m7nd[lvi]:.2f}')\n",
    "\n",
    "\n",
    "ax.set_xlabel(\"Date\")\n",
    "ax.set_ylabel(f'Normalised units, scaled from {normalisation_date}')\n",
    "ax.legend(['Cases', 'Admissions', 'Deaths'])\n",
    "\n",
    "plt.savefig('cases_admissions_deaths.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}