{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check Corona Vaccinations \n",
    "* [this Notebook](https://github.com/salgo60/open-data-examples/blob/master/Check%20Corona%20Vaccination.ipynb) \n",
    "\n",
    "* read the data on [github.com/owid/covid-19-data...vaccinations/country_data](https://github.com/owid/covid-19-data/tree/master/public/data/vaccinations/country_data)\n",
    "  * Data is reported cummulated for United Kingdom but also subnational data England, Scotland, Northern Ireland, Wales see [issue 228](https://github.com/owid/covid-19-data/issues/228)\n",
    "     * although subnational data have been published quite irregularly so far ==> we filter them out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Last run:  2020-12-25 09:44:52.466671\n"
     ]
    }
   ],
   "source": [
    "from datetime import datetime\n",
    "start_time  = datetime.now()\n",
    "print(\"Last run: \", start_time)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "GITHUB_directory = \"https://api.github.com/repos/owid/covid-19-data/contents/public/data/vaccinations/country_data\"  \n",
    "countries = pd.read_json(GITHUB_directory)  \n",
    "listcountries = []\n",
    "for index,row in countries.iterrows():\n",
    "    df = pd.read_csv(row[\"download_url\"])\n",
    "    listcountries.append(df)\n",
    "    \n",
    "allCountries = pd.concat(listcountries, axis=0, ignore_index=True)    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>location</th>\n",
       "      <th>date</th>\n",
       "      <th>vaccine</th>\n",
       "      <th>total_vaccinations</th>\n",
       "      <th>source_url</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>2020-12-24</td>\n",
       "      <td>Pfizer/BioNTech</td>\n",
       "      <td>800000</td>\n",
       "      <td>https://www.gov.uk/government/speeches/prime-m...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Bahrain</td>\n",
       "      <td>2020-12-24</td>\n",
       "      <td>Sinopharm</td>\n",
       "      <td>50071</td>\n",
       "      <td>https://twitter.com/MOH_Bahrain/status/1342189...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Bahrain</td>\n",
       "      <td>2020-12-23</td>\n",
       "      <td>Sinopharm</td>\n",
       "      <td>38965</td>\n",
       "      <td>https://twitter.com/MOH_Bahrain/status/1341855...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>United States</td>\n",
       "      <td>2020-12-23</td>\n",
       "      <td>Moderna, Pfizer/BioNTech</td>\n",
       "      <td>1008025</td>\n",
       "      <td>https://covid.cdc.gov/covid-data-tracker/#vacc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Israel</td>\n",
       "      <td>2020-12-23</td>\n",
       "      <td>Pfizer/BioNTech</td>\n",
       "      <td>140000</td>\n",
       "      <td>https://twitter.com/YuliEdelstein/status/13418...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Canada</td>\n",
       "      <td>2020-12-23</td>\n",
       "      <td>Pfizer/BioNTech</td>\n",
       "      <td>31736</td>\n",
       "      <td>https://github.com/ishaberry/Covid19Canada/blo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Canada</td>\n",
       "      <td>2020-12-22</td>\n",
       "      <td>Pfizer/BioNTech</td>\n",
       "      <td>26287</td>\n",
       "      <td>https://github.com/ishaberry/Covid19Canada/blo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Israel</td>\n",
       "      <td>2020-12-22</td>\n",
       "      <td>Pfizer/BioNTech</td>\n",
       "      <td>71876</td>\n",
       "      <td>https://www.gov.il/en/departments/news/2212202...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>United States</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>Moderna, Pfizer/BioNTech</td>\n",
       "      <td>614117</td>\n",
       "      <td>https://covid.cdc.gov/covid-data-tracker/#vacc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Canada</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>Pfizer/BioNTech</td>\n",
       "      <td>20866</td>\n",
       "      <td>https://github.com/ishaberry/Covid19Canada/blo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Israel</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>Pfizer/BioNTech</td>\n",
       "      <td>30000</td>\n",
       "      <td>https://www.gov.il/en/departments/news/2212202...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Canada</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>Pfizer/BioNTech</td>\n",
       "      <td>14492</td>\n",
       "      <td>https://github.com/ishaberry/Covid19Canada/blo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>Pfizer/BioNTech</td>\n",
       "      <td>616933</td>\n",
       "      <td>https://coronavirus.data.gov.uk/</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>United States</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>Moderna, Pfizer/BioNTech</td>\n",
       "      <td>556208</td>\n",
       "      <td>https://www.cdc.gov/coronavirus/2019-ncov/vacc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Scotland</td>\n",
       "      <td>2020-12-20</td>\n",
       "      <td>Pfizer/BioNTech</td>\n",
       "      <td>56676</td>\n",
       "      <td>https://coronavirus.data.gov.uk/</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          location        date  ... total_vaccinations                                         source_url\n",
       "26  United Kingdom  2020-12-24  ...             800000  https://www.gov.uk/government/speeches/prime-m...\n",
       "1          Bahrain  2020-12-24  ...              50071  https://twitter.com/MOH_Bahrain/status/1342189...\n",
       "0          Bahrain  2020-12-23  ...              38965  https://twitter.com/MOH_Bahrain/status/1341855...\n",
       "27   United States  2020-12-23  ...            1008025  https://covid.cdc.gov/covid-data-tracker/#vacc...\n",
       "17          Israel  2020-12-23  ...             140000  https://twitter.com/YuliEdelstein/status/13418...\n",
       "11          Canada  2020-12-23  ...              31736  https://github.com/ishaberry/Covid19Canada/blo...\n",
       "10          Canada  2020-12-22  ...              26287  https://github.com/ishaberry/Covid19Canada/blo...\n",
       "16          Israel  2020-12-22  ...              71876  https://www.gov.il/en/departments/news/2212202...\n",
       "28   United States  2020-12-21  ...             614117  https://covid.cdc.gov/covid-data-tracker/#vacc...\n",
       "9           Canada  2020-12-21  ...              20866  https://github.com/ishaberry/Covid19Canada/blo...\n",
       "15          Israel  2020-12-21  ...              30000  https://www.gov.il/en/departments/news/2212202...\n",
       "8           Canada  2020-12-20  ...              14492  https://github.com/ishaberry/Covid19Canada/blo...\n",
       "25  United Kingdom  2020-12-20  ...             616933                   https://coronavirus.data.gov.uk/\n",
       "29   United States  2020-12-20  ...             556208  https://www.cdc.gov/coronavirus/2019-ncov/vacc...\n",
       "23        Scotland  2020-12-20  ...              56676                   https://coronavirus.data.gov.uk/\n",
       "\n",
       "[15 rows x 5 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Show 15 latest sorted by dates\n",
    "allCountries.sort_values(by=['date'],ascending=False)[0:15]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Canada              10\n",
       "United States        4\n",
       "Israel               4\n",
       "Russia               3\n",
       "Scotland             2\n",
       "United Kingdom       2\n",
       "Bahrain              2\n",
       "Wales                2\n",
       "Northern Ireland     2\n",
       "England              1\n",
       "China                1\n",
       "Name: location, dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Countries in list\n",
    "allCountries[\"location\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "location          vaccine                 \n",
       "Bahrain           Sinopharm                    2\n",
       "Canada            Pfizer/BioNTech             10\n",
       "China             CNBG, Sinovac                1\n",
       "England           Pfizer/BioNTech              1\n",
       "Israel            Pfizer/BioNTech              4\n",
       "Northern Ireland  Pfizer/BioNTech              2\n",
       "Russia            Sputnik V                    3\n",
       "Scotland          Pfizer/BioNTech              2\n",
       "United Kingdom    Pfizer/BioNTech              2\n",
       "United States     Moderna, Pfizer/BioNTech     4\n",
       "Wales             Pfizer/BioNTech              2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "allCountries.groupby([\"location\", \"vaccine\"]).size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 26 entries, 0 to 30\n",
      "Data columns (total 5 columns):\n",
      " #   Column              Non-Null Count  Dtype         \n",
      "---  ------              --------------  -----         \n",
      " 0   location            26 non-null     object        \n",
      " 1   date                26 non-null     datetime64[ns]\n",
      " 2   vaccine             26 non-null     object        \n",
      " 3   total_vaccinations  26 non-null     int64         \n",
      " 4   source_url          26 non-null     object        \n",
      "dtypes: datetime64[ns](1), int64(1), object(3)\n",
      "memory usage: 1.2+ KB\n"
     ]
    }
   ],
   "source": [
    "allCountries['date'] = allCountries['date'].astype('datetime64[ns]')   \n",
    "\n",
    "# Filter away Wales , England, Scotland see above and [issue 228](https://github.com/owid/covid-19-data/issues/228)\n",
    "list_of_countries_to_delete = [\"England\",\"Northern Ireland\",\"Scotland\",\"Wales\"]\n",
    "\n",
    "allCountriesFiltered = allCountries[~allCountries[\"location\"].isin(list_of_countries_to_delete)]\n",
    "allCountriesFiltered.info()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Countries\n",
    "%matplotlib inline    \n",
    "import matplotlib.pyplot as plt   \n",
    "\n",
    "#Reported numbers are accumulated --> get latest\n",
    "plotCountries = allCountriesFiltered.sort_values(by=['date'],ascending=False) \\\n",
    "    [['total_vaccinations','location','vaccine']].groupby('location').apply(lambda x: x.head(1))\n",
    "plotCountries = plotCountries.set_index('location')\n",
    "plotCountries[\"total_vaccinations\"].plot( y='location',kind = 'pie') \n",
    "plt.title(\"Vaccination per countries - \" + start_time.strftime('%Y %m %d'))\n",
    "plt.savefig('Corona_VaccinationperCountry.png')  \n",
    "plt.show() \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>total_vaccinations</th>\n",
       "      <th>vaccine</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>location</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>31736</td>\n",
       "      <td>Pfizer/BioNTech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bahrain</th>\n",
       "      <td>50071</td>\n",
       "      <td>Sinopharm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Israel</th>\n",
       "      <td>140000</td>\n",
       "      <td>Pfizer/BioNTech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Russia</th>\n",
       "      <td>200000</td>\n",
       "      <td>Sputnik V</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United Kingdom</th>\n",
       "      <td>800000</td>\n",
       "      <td>Pfizer/BioNTech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>China</th>\n",
       "      <td>1000000</td>\n",
       "      <td>CNBG, Sinovac</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United States</th>\n",
       "      <td>1008025</td>\n",
       "      <td>Moderna, Pfizer/BioNTech</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                total_vaccinations                   vaccine\n",
       "location                                                    \n",
       "Canada                       31736           Pfizer/BioNTech\n",
       "Bahrain                      50071                 Sinopharm\n",
       "Israel                      140000           Pfizer/BioNTech\n",
       "Russia                      200000                 Sputnik V\n",
       "United Kingdom              800000           Pfizer/BioNTech\n",
       "China                      1000000             CNBG, Sinovac\n",
       "United States              1008025  Moderna, Pfizer/BioNTech"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plotCountries.sort_values(by='total_vaccinations',ascending=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "total_vaccinations                                              3229832\n",
       "vaccine               SinopharmPfizer/BioNTechCNBG, SinovacPfizer/Bi...\n",
       "dtype: object"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plotCountries.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Vaccine numbers\n",
    "plotVaccine = plotCountries.groupby('vaccine')['total_vaccinations'].sum()\n",
    "plotVaccine.plot( kind = 'pie') \n",
    "plt.title(\"Vaccination per Vaccine - \" + start_time.strftime('%Y %m %d'))\n",
    "plt.savefig('Corona_VaccinationperVaccine.png')  \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "vaccine\n",
       "Sinopharm                     50071\n",
       "Sputnik V                    200000\n",
       "Pfizer/BioNTech              971736\n",
       "CNBG, Sinovac               1000000\n",
       "Moderna, Pfizer/BioNTech    1008025\n",
       "Name: total_vaccinations, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plotVaccine.sort_values(ascending=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Sweden have 10 000 doses...."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ended:  2020-12-25 09:44:53.930888\n",
      "Time elapsed (hh:mm:ss.ms) 0:00:01.464611\n"
     ]
    }
   ],
   "source": [
    "end = datetime.now()\n",
    "print(\"Ended: \", end) \n",
    "print('Time elapsed (hh:mm:ss.ms) {}'.format(datetime.now() - start_time))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Whole dataset\n",
    "see \n",
    "* [COVID-19 Data Processing Pipelines and datasets](https://github.com/covid19-data/covid19-data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "ourworldindata = \"https://covid.ourworldindata.org/data/owid-covid-data.json\"\n",
    "#df_ourworldindata = pd.read_json(ourworldindata) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "#df_ourworldindata.info()"
   ]
  }
 ],
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