notebook.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "f0dfe134-af1d-4716-85ff-29ac996a6710",
   "metadata": {},
   "source": [
    "# WHO COVID-19 Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ef00bfb-537c-4640-b4d9-c0947a576a75",
   "metadata": {
    "tags": []
   },
   "source": [
    "From the 31 December 2019 to the 21 March 2020, WHO collected the numbers of confirmed COVID-19 cases and deaths through official communications under the International Health Regulations (IHR, 2005), complemented by monitoring the official ministries of health websites and social media accounts. You can access the dataset by this link: \n",
    "\n",
    "[WHO Coronavirus (COVID-19) Dashboard](https://covid19.who.int/data)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e5249eb2-a4c1-4fbd-aa1e-e769ee472156",
   "metadata": {},
   "source": [
    "### Get Data and Overview"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "id": "1b257681-62b1-4da4-909d-8fb7ebc5d9b9",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "id": "6a061626-bdfc-4bfc-bb0c-d99dac3f9931",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "pd.options.display.max_rows = 200"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "id": "936e54f1-27ae-40fa-8abf-4d8227dc288d",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "covid_df = pd.read_csv('/Users/xumengying/Desktop/WHO/WHO-COVID-19-global-data.csv', delimiter=\",\", encoding='utf-8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "id": "411bff65-4266-4188-abc2-603f7385783a",
   "metadata": {
    "tags": []
   },
   "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_reported</th>\n",
       "      <th>Country_code</th>\n",
       "      <th>Country</th>\n",
       "      <th>WHO_region</th>\n",
       "      <th>New_cases</th>\n",
       "      <th>Cumulative_cases</th>\n",
       "      <th>New_deaths</th>\n",
       "      <th>Cumulative_deaths</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>195899</th>\n",
       "      <td>2020-09-22</td>\n",
       "      <td>MN</td>\n",
       "      <td>Mongolia</td>\n",
       "      <td>WPRO</td>\n",
       "      <td>0</td>\n",
       "      <td>312</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25317</th>\n",
       "      <td>2022-11-09</td>\n",
       "      <td>BB</td>\n",
       "      <td>Barbados</td>\n",
       "      <td>AMRO</td>\n",
       "      <td>0</td>\n",
       "      <td>103424</td>\n",
       "      <td>0</td>\n",
       "      <td>560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194154</th>\n",
       "      <td>2023-10-08</td>\n",
       "      <td>FM</td>\n",
       "      <td>Micronesia (Federated States of)</td>\n",
       "      <td>WPRO</td>\n",
       "      <td>0</td>\n",
       "      <td>26547</td>\n",
       "      <td>0</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100168</th>\n",
       "      <td>2020-07-29</td>\n",
       "      <td>FJ</td>\n",
       "      <td>Fiji</td>\n",
       "      <td>WPRO</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>316662</th>\n",
       "      <td>2022-12-12</td>\n",
       "      <td>TV</td>\n",
       "      <td>Tuvalu</td>\n",
       "      <td>WPRO</td>\n",
       "      <td>0</td>\n",
       "      <td>2779</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12704</th>\n",
       "      <td>2023-07-06</td>\n",
       "      <td>AR</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>AMRO</td>\n",
       "      <td>0</td>\n",
       "      <td>10048581</td>\n",
       "      <td>0</td>\n",
       "      <td>130472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>313897</th>\n",
       "      <td>2023-03-13</td>\n",
       "      <td>TM</td>\n",
       "      <td>Turkmenistan</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134950</th>\n",
       "      <td>2021-12-21</td>\n",
       "      <td>HU</td>\n",
       "      <td>Hungary</td>\n",
       "      <td>EURO</td>\n",
       "      <td>1985</td>\n",
       "      <td>1230385</td>\n",
       "      <td>132</td>\n",
       "      <td>38028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>312376</th>\n",
       "      <td>2022-12-10</td>\n",
       "      <td>TR</td>\n",
       "      <td>Türkiye</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>17004677</td>\n",
       "      <td>0</td>\n",
       "      <td>101419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74439</th>\n",
       "      <td>2020-07-04</td>\n",
       "      <td>CY</td>\n",
       "      <td>Cyprus</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Date_reported Country_code                           Country  \\\n",
       "195899    2020-09-22           MN                          Mongolia   \n",
       "25317     2022-11-09           BB                          Barbados   \n",
       "194154    2023-10-08           FM  Micronesia (Federated States of)   \n",
       "100168    2020-07-29           FJ                              Fiji   \n",
       "316662    2022-12-12           TV                            Tuvalu   \n",
       "12704     2023-07-06           AR                         Argentina   \n",
       "313897    2023-03-13           TM                      Turkmenistan   \n",
       "134950    2021-12-21           HU                           Hungary   \n",
       "312376    2022-12-10           TR                           Türkiye   \n",
       "74439     2020-07-04           CY                            Cyprus   \n",
       "\n",
       "       WHO_region  New_cases  Cumulative_cases  New_deaths  Cumulative_deaths  \n",
       "195899       WPRO          0               312           0                  0  \n",
       "25317        AMRO          0            103424           0                560  \n",
       "194154       WPRO          0             26547           0                 65  \n",
       "100168       WPRO          0                27           0                  0  \n",
       "316662       WPRO          0              2779           0                  0  \n",
       "12704        AMRO          0          10048581           0             130472  \n",
       "313897       EURO          0                 0           0                  0  \n",
       "134950       EURO       1985           1230385         132              38028  \n",
       "312376       EURO          0          17004677           0             101419  \n",
       "74439        EURO          0               999           0                 19  "
      ]
     },
     "execution_count": 194,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covid_df.sample(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "id": "e5ebcdd6-6a6f-4e99-9e00-c705f415ade8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 338436 entries, 0 to 338435\n",
      "Data columns (total 8 columns):\n",
      " #   Column             Non-Null Count   Dtype \n",
      "---  ------             --------------   ----- \n",
      " 0   Date_reported      338436 non-null  object\n",
      " 1   Country_code       337008 non-null  object\n",
      " 2   Country            338436 non-null  object\n",
      " 3   WHO_region         338436 non-null  object\n",
      " 4   New_cases          338436 non-null  int64 \n",
      " 5   Cumulative_cases   338436 non-null  int64 \n",
      " 6   New_deaths         338436 non-null  int64 \n",
      " 7   Cumulative_deaths  338436 non-null  int64 \n",
      "dtypes: int64(4), object(4)\n",
      "memory usage: 20.7+ MB\n"
     ]
    }
   ],
   "source": [
    "covid_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "id": "4a3bb26a-f541-40cc-93bd-11d9bec3e538",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<Axes: title={'center': 'New_cases'}>,\n",
       "        <Axes: title={'center': 'Cumulative_cases'}>],\n",
       "       [<Axes: title={'center': 'New_deaths'}>,\n",
       "        <Axes: title={'center': 'Cumulative_deaths'}>]], dtype=object)"
      ]
     },
     "execution_count": 196,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "covid_df.hist(figsize=(10,10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "id": "9e38b5ce-41a6-4cc4-a7db-0ab32de55113",
   "metadata": {
    "tags": []
   },
   "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_reported</th>\n",
       "      <th>Country_code</th>\n",
       "      <th>Country</th>\n",
       "      <th>WHO_region</th>\n",
       "      <th>New_cases</th>\n",
       "      <th>Cumulative_cases</th>\n",
       "      <th>New_deaths</th>\n",
       "      <th>Cumulative_deaths</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>338436</td>\n",
       "      <td>337008</td>\n",
       "      <td>338436</td>\n",
       "      <td>338436</td>\n",
       "      <td>3.384360e+05</td>\n",
       "      <td>3.384360e+05</td>\n",
       "      <td>338436.000000</td>\n",
       "      <td>3.384360e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>1428</td>\n",
       "      <td>236</td>\n",
       "      <td>237</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>AF</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>EURO</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>237</td>\n",
       "      <td>1428</td>\n",
       "      <td>1428</td>\n",
       "      <td>88536</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.281237e+03</td>\n",
       "      <td>1.552443e+06</td>\n",
       "      <td>20.639879</td>\n",
       "      <td>1.856271e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.832306e+04</td>\n",
       "      <td>7.000750e+06</td>\n",
       "      <td>164.174396</td>\n",
       "      <td>7.722976e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-6.507900e+04</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>-3520.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.886000e+03</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.100000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>3.810300e+04</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.130000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.370000e+02</td>\n",
       "      <td>4.542655e+05</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.019000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.966046e+06</td>\n",
       "      <td>1.034368e+08</td>\n",
       "      <td>44047.000000</td>\n",
       "      <td>1.144877e+06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Date_reported Country_code      Country WHO_region     New_cases  \\\n",
       "count         338436       337008       338436     338436  3.384360e+05   \n",
       "unique          1428          236          237          7           NaN   \n",
       "top       2020-01-03           AF  Afghanistan       EURO           NaN   \n",
       "freq             237         1428         1428      88536           NaN   \n",
       "mean             NaN          NaN          NaN        NaN  2.281237e+03   \n",
       "std              NaN          NaN          NaN        NaN  3.832306e+04   \n",
       "min              NaN          NaN          NaN        NaN -6.507900e+04   \n",
       "25%              NaN          NaN          NaN        NaN  0.000000e+00   \n",
       "50%              NaN          NaN          NaN        NaN  0.000000e+00   \n",
       "75%              NaN          NaN          NaN        NaN  1.370000e+02   \n",
       "max              NaN          NaN          NaN        NaN  6.966046e+06   \n",
       "\n",
       "        Cumulative_cases     New_deaths  Cumulative_deaths  \n",
       "count       3.384360e+05  338436.000000       3.384360e+05  \n",
       "unique               NaN            NaN                NaN  \n",
       "top                  NaN            NaN                NaN  \n",
       "freq                 NaN            NaN                NaN  \n",
       "mean        1.552443e+06      20.639879       1.856271e+04  \n",
       "std         7.000750e+06     164.174396       7.722976e+04  \n",
       "min         0.000000e+00   -3520.000000       0.000000e+00  \n",
       "25%         2.886000e+03       0.000000       2.100000e+01  \n",
       "50%         3.810300e+04       0.000000       4.130000e+02  \n",
       "75%         4.542655e+05       1.000000       6.019000e+03  \n",
       "max         1.034368e+08   44047.000000       1.144877e+06  "
      ]
     },
     "execution_count": 197,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covid_df.describe(include='all')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "716808a6-a744-43e0-bdbe-70465ca29531",
   "metadata": {},
   "source": [
    "### Drop Rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "id": "6c0bf12d-28b9-4a9f-9c13-81a66fa29dd3",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date_reported</th>\n",
       "      <th>Country_code</th>\n",
       "      <th>Country</th>\n",
       "      <th>WHO_region</th>\n",
       "      <th>New_cases</th>\n",
       "      <th>Cumulative_cases</th>\n",
       "      <th>New_deaths</th>\n",
       "      <th>Cumulative_deaths</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>AF</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>EMRO</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-01-04</td>\n",
       "      <td>AF</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>EMRO</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-05</td>\n",
       "      <td>AF</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>EMRO</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-01-06</td>\n",
       "      <td>AF</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>EMRO</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-01-07</td>\n",
       "      <td>AF</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>EMRO</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338431</th>\n",
       "      <td>2023-11-26</td>\n",
       "      <td>ZW</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>AFRO</td>\n",
       "      <td>0</td>\n",
       "      <td>265927</td>\n",
       "      <td>0</td>\n",
       "      <td>5727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338432</th>\n",
       "      <td>2023-11-27</td>\n",
       "      <td>ZW</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>AFRO</td>\n",
       "      <td>0</td>\n",
       "      <td>265927</td>\n",
       "      <td>0</td>\n",
       "      <td>5727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338433</th>\n",
       "      <td>2023-11-28</td>\n",
       "      <td>ZW</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>AFRO</td>\n",
       "      <td>0</td>\n",
       "      <td>265927</td>\n",
       "      <td>0</td>\n",
       "      <td>5727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338434</th>\n",
       "      <td>2023-11-29</td>\n",
       "      <td>ZW</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>AFRO</td>\n",
       "      <td>0</td>\n",
       "      <td>265927</td>\n",
       "      <td>0</td>\n",
       "      <td>5727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338435</th>\n",
       "      <td>2023-11-30</td>\n",
       "      <td>ZW</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>AFRO</td>\n",
       "      <td>0</td>\n",
       "      <td>265927</td>\n",
       "      <td>0</td>\n",
       "      <td>5727</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>249900 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Date_reported Country_code      Country WHO_region  New_cases  \\\n",
       "0         2020-01-03           AF  Afghanistan       EMRO          0   \n",
       "1         2020-01-04           AF  Afghanistan       EMRO          0   \n",
       "2         2020-01-05           AF  Afghanistan       EMRO          0   \n",
       "3         2020-01-06           AF  Afghanistan       EMRO          0   \n",
       "4         2020-01-07           AF  Afghanistan       EMRO          0   \n",
       "...              ...          ...          ...        ...        ...   \n",
       "338431    2023-11-26           ZW     Zimbabwe       AFRO          0   \n",
       "338432    2023-11-27           ZW     Zimbabwe       AFRO          0   \n",
       "338433    2023-11-28           ZW     Zimbabwe       AFRO          0   \n",
       "338434    2023-11-29           ZW     Zimbabwe       AFRO          0   \n",
       "338435    2023-11-30           ZW     Zimbabwe       AFRO          0   \n",
       "\n",
       "        Cumulative_cases  New_deaths  Cumulative_deaths  \n",
       "0                      0           0                  0  \n",
       "1                      0           0                  0  \n",
       "2                      0           0                  0  \n",
       "3                      0           0                  0  \n",
       "4                      0           0                  0  \n",
       "...                  ...         ...                ...  \n",
       "338431            265927           0               5727  \n",
       "338432            265927           0               5727  \n",
       "338433            265927           0               5727  \n",
       "338434            265927           0               5727  \n",
       "338435            265927           0               5727  \n",
       "\n",
       "[249900 rows x 8 columns]"
      ]
     },
     "execution_count": 198,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covid_df[covid_df['WHO_region'] != 'EURO']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "id": "2b512a6e-404c-4b19-8c0e-2408082820d1",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "EU_covid_df = covid_df.drop(covid_df[covid_df['WHO_region'] != 'EURO'].index) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "id": "3d90ebb3-5bd0-4e6e-8a93-cfa58a683df0",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
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       "      <th>1428</th>\n",
       "      <td>2020-01-03</td>\n",
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       "      <td>0</td>\n",
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       "      <td>2020-01-04</td>\n",
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       "      <th>1430</th>\n",
       "      <td>2020-01-05</td>\n",
       "      <td>AL</td>\n",
       "      <td>Albania</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1431</th>\n",
       "      <td>2020-01-06</td>\n",
       "      <td>AL</td>\n",
       "      <td>Albania</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1432</th>\n",
       "      <td>2020-01-07</td>\n",
       "      <td>AL</td>\n",
       "      <td>Albania</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <th>328435</th>\n",
       "      <td>2023-11-26</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>328436</th>\n",
       "      <td>2023-11-27</td>\n",
       "      <td>UZ</td>\n",
       "      <td>Uzbekistan</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>174575</td>\n",
       "      <td>0</td>\n",
       "      <td>1016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>328437</th>\n",
       "      <td>2023-11-28</td>\n",
       "      <td>UZ</td>\n",
       "      <td>Uzbekistan</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>174575</td>\n",
       "      <td>0</td>\n",
       "      <td>1016</td>\n",
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       "    <tr>\n",
       "      <th>328438</th>\n",
       "      <td>2023-11-29</td>\n",
       "      <td>UZ</td>\n",
       "      <td>Uzbekistan</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>174575</td>\n",
       "      <td>0</td>\n",
       "      <td>1016</td>\n",
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       "    <tr>\n",
       "      <th>328439</th>\n",
       "      <td>2023-11-30</td>\n",
       "      <td>UZ</td>\n",
       "      <td>Uzbekistan</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>174575</td>\n",
       "      <td>0</td>\n",
       "      <td>1016</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>88536 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Date_reported Country_code     Country WHO_region  New_cases  \\\n",
       "1428      2020-01-03           AL     Albania       EURO          0   \n",
       "1429      2020-01-04           AL     Albania       EURO          0   \n",
       "1430      2020-01-05           AL     Albania       EURO          0   \n",
       "1431      2020-01-06           AL     Albania       EURO          0   \n",
       "1432      2020-01-07           AL     Albania       EURO          0   \n",
       "...              ...          ...         ...        ...        ...   \n",
       "328435    2023-11-26           UZ  Uzbekistan       EURO          0   \n",
       "328436    2023-11-27           UZ  Uzbekistan       EURO          0   \n",
       "328437    2023-11-28           UZ  Uzbekistan       EURO          0   \n",
       "328438    2023-11-29           UZ  Uzbekistan       EURO          0   \n",
       "328439    2023-11-30           UZ  Uzbekistan       EURO          0   \n",
       "\n",
       "        Cumulative_cases  New_deaths  Cumulative_deaths  \n",
       "1428                   0           0                  0  \n",
       "1429                   0           0                  0  \n",
       "1430                   0           0                  0  \n",
       "1431                   0           0                  0  \n",
       "1432                   0           0                  0  \n",
       "...                  ...         ...                ...  \n",
       "328435            174575           0               1016  \n",
       "328436            174575           0               1016  \n",
       "328437            174575           0               1016  \n",
       "328438            174575           0               1016  \n",
       "328439            174575           0               1016  \n",
       "\n",
       "[88536 rows x 8 columns]"
      ]
     },
     "execution_count": 200,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "EU_covid_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad10f8bb-da9f-4cf9-ba15-79d7cf0ff93d",
   "metadata": {},
   "source": [
    "### Question 1\n",
    "When was the first COVID case reported in the Netherlands, and how long did it take for more than 10,000 cases to be reported?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "id": "7b55cbe5-8650-41d3-9cd5-b7fa5c67e8b2",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "NL_filter = 'Netherlands'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "id": "d754a972-094a-4f94-bb4d-986f2e3f7790",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "Netherlands_table = covid_df[covid_df['Country'] == NL_filter]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "id": "5383a471-c6d2-4f0f-8397-2b5d08f0c752",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>208547</th>\n",
       "      <td>2020-03-02</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208548</th>\n",
       "      <td>2020-03-03</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208549</th>\n",
       "      <td>2020-03-04</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208550</th>\n",
       "      <td>2020-03-05</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208551</th>\n",
       "      <td>2020-03-06</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208552</th>\n",
       "      <td>2020-03-07</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208553</th>\n",
       "      <td>2020-03-08</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>311</td>\n",
       "      <td>330</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208554</th>\n",
       "      <td>2020-03-09</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>330</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208555</th>\n",
       "      <td>2020-03-10</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>330</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208556</th>\n",
       "      <td>2020-03-11</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>330</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208557</th>\n",
       "      <td>2020-03-12</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>330</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208558</th>\n",
       "      <td>2020-03-13</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>330</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208559</th>\n",
       "      <td>2020-03-14</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>330</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208560</th>\n",
       "      <td>2020-03-15</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>1276</td>\n",
       "      <td>1606</td>\n",
       "      <td>36</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208561</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>1606</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208562</th>\n",
       "      <td>2020-03-17</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>1606</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208563</th>\n",
       "      <td>2020-03-18</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>1606</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208564</th>\n",
       "      <td>2020-03-19</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>1606</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208565</th>\n",
       "      <td>2020-03-20</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>1606</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208566</th>\n",
       "      <td>2020-03-21</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>1606</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208567</th>\n",
       "      <td>2020-03-22</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>3775</td>\n",
       "      <td>5381</td>\n",
       "      <td>295</td>\n",
       "      <td>335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208568</th>\n",
       "      <td>2020-03-23</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>5381</td>\n",
       "      <td>0</td>\n",
       "      <td>335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208569</th>\n",
       "      <td>2020-03-24</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>5381</td>\n",
       "      <td>0</td>\n",
       "      <td>335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208570</th>\n",
       "      <td>2020-03-25</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>5381</td>\n",
       "      <td>0</td>\n",
       "      <td>335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208571</th>\n",
       "      <td>2020-03-26</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>5381</td>\n",
       "      <td>0</td>\n",
       "      <td>335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208572</th>\n",
       "      <td>2020-03-27</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>5381</td>\n",
       "      <td>0</td>\n",
       "      <td>335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208573</th>\n",
       "      <td>2020-03-28</td>\n",
       "      <td>NL</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EURO</td>\n",
       "      <td>0</td>\n",
       "      <td>5381</td>\n",
       "      <td>0</td>\n",
       "      <td>335</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Date_reported Country_code      Country WHO_region  New_cases  \\\n",
       "208546    2020-03-01           NL  Netherlands       EURO         19   \n",
       "208547    2020-03-02           NL  Netherlands       EURO          0   \n",
       "208548    2020-03-03           NL  Netherlands       EURO          0   \n",
       "208549    2020-03-04           NL  Netherlands       EURO          0   \n",
       "208550    2020-03-05           NL  Netherlands       EURO          0   \n",
       "208551    2020-03-06           NL  Netherlands       EURO          0   \n",
       "208552    2020-03-07           NL  Netherlands       EURO          0   \n",
       "208553    2020-03-08           NL  Netherlands       EURO        311   \n",
       "208554    2020-03-09           NL  Netherlands       EURO          0   \n",
       "208555    2020-03-10           NL  Netherlands       EURO          0   \n",
       "208556    2020-03-11           NL  Netherlands       EURO          0   \n",
       "208557    2020-03-12           NL  Netherlands       EURO          0   \n",
       "208558    2020-03-13           NL  Netherlands       EURO          0   \n",
       "208559    2020-03-14           NL  Netherlands       EURO          0   \n",
       "208560    2020-03-15           NL  Netherlands       EURO       1276   \n",
       "208561    2020-03-16           NL  Netherlands       EURO          0   \n",
       "208562    2020-03-17           NL  Netherlands       EURO          0   \n",
       "208563    2020-03-18           NL  Netherlands       EURO          0   \n",
       "208564    2020-03-19           NL  Netherlands       EURO          0   \n",
       "208565    2020-03-20           NL  Netherlands       EURO          0   \n",
       "208566    2020-03-21           NL  Netherlands       EURO          0   \n",
       "208567    2020-03-22           NL  Netherlands       EURO       3775   \n",
       "208568    2020-03-23           NL  Netherlands       EURO          0   \n",
       "208569    2020-03-24           NL  Netherlands       EURO          0   \n",
       "208570    2020-03-25           NL  Netherlands       EURO          0   \n",
       "208571    2020-03-26           NL  Netherlands       EURO          0   \n",
       "208572    2020-03-27           NL  Netherlands       EURO          0   \n",
       "208573    2020-03-28           NL  Netherlands       EURO          0   \n",
       "\n",
       "        Cumulative_cases  New_deaths  Cumulative_deaths  \n",
       "208546                19           0                  0  \n",
       "208547                19           0                  0  \n",
       "208548                19           0                  0  \n",
       "208549                19           0                  0  \n",
       "208550                19           0                  0  \n",
       "208551                19           0                  0  \n",
       "208552                19           0                  0  \n",
       "208553               330           4                  4  \n",
       "208554               330           0                  4  \n",
       "208555               330           0                  4  \n",
       "208556               330           0                  4  \n",
       "208557               330           0                  4  \n",
       "208558               330           0                  4  \n",
       "208559               330           0                  4  \n",
       "208560              1606          36                 40  \n",
       "208561              1606           0                 40  \n",
       "208562              1606           0                 40  \n",
       "208563              1606           0                 40  \n",
       "208564              1606           0                 40  \n",
       "208565              1606           0                 40  \n",
       "208566              1606           0                 40  \n",
       "208567              5381         295                335  \n",
       "208568              5381           0                335  \n",
       "208569              5381           0                335  \n",
       "208570              5381           0                335  \n",
       "208571              5381           0                335  \n",
       "208572              5381           0                335  \n",
       "208573              5381           0                335  "
      ]
     },
     "execution_count": 203,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Netherlands_table[(Netherlands_table['Cumulative_cases'] > 0) & (Netherlands_table['Cumulative_cases'] < 10000)]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "977a88ba-f50f-4e6e-91cc-43d0b7659dbe",
   "metadata": {},
   "source": [
    "The first COVID case in the Netherlands was reported on March 1, 2020, and it took 28 days for over 10,000 cases to be reported, which occurred on March 29, 2020."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1885d6fe-1d37-4bf2-afd8-492bdbbfff29",
   "metadata": {},
   "source": [
    "### Question 2\n",
    "When did Belgium report its first COVID-related death, and how much time passed before more than 1,000 cases were reported?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "id": "f00552c5-57b3-4d89-9868-cd15e892bddc",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "BE_filter = 'Belgium'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "id": "c03dc390-37e7-4738-a35f-cd575bf9b6a6",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "Belgium_table = covid_df[covid_df['Country'] == BE_filter]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "id": "7da5e95f-5c32-4e24-afc5-4453cc7d9804",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date_reported</th>\n",
       "      <th>Country_code</th>\n",
       "      <th>Country</th>\n",
       "      <th>WHO_region</th>\n",
       "      <th>New_cases</th>\n",
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       "      <th>New_deaths</th>\n",
       "      <th>Cumulative_deaths</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>27198</th>\n",
       "      <td>2020-03-09</td>\n",
       "      <td>BE</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>EURO</td>\n",
       "      <td>27</td>\n",
       "      <td>343</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27199</th>\n",
       "      <td>2020-03-10</td>\n",
       "      <td>BE</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>EURO</td>\n",
       "      <td>64</td>\n",
       "      <td>407</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27200</th>\n",
       "      <td>2020-03-11</td>\n",
       "      <td>BE</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>EURO</td>\n",
       "      <td>94</td>\n",
       "      <td>501</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27201</th>\n",
       "      <td>2020-03-12</td>\n",
       "      <td>BE</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>EURO</td>\n",
       "      <td>99</td>\n",
       "      <td>600</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27202</th>\n",
       "      <td>2020-03-13</td>\n",
       "      <td>BE</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>EURO</td>\n",
       "      <td>174</td>\n",
       "      <td>774</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27203</th>\n",
       "      <td>2020-03-14</td>\n",
       "      <td>BE</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>EURO</td>\n",
       "      <td>250</td>\n",
       "      <td>1024</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27204</th>\n",
       "      <td>2020-03-15</td>\n",
       "      <td>BE</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>EURO</td>\n",
       "      <td>338</td>\n",
       "      <td>1362</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27205</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>BE</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>EURO</td>\n",
       "      <td>179</td>\n",
       "      <td>1541</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27206</th>\n",
       "      <td>2020-03-17</td>\n",
       "      <td>BE</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>EURO</td>\n",
       "      <td>214</td>\n",
       "      <td>1755</td>\n",
       "      <td>7</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27207</th>\n",
       "      <td>2020-03-18</td>\n",
       "      <td>BE</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>EURO</td>\n",
       "      <td>387</td>\n",
       "      <td>2142</td>\n",
       "      <td>11</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27208</th>\n",
       "      <td>2020-03-19</td>\n",
       "      <td>BE</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>EURO</td>\n",
       "      <td>422</td>\n",
       "      <td>2564</td>\n",
       "      <td>15</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27209</th>\n",
       "      <td>2020-03-20</td>\n",
       "      <td>BE</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>EURO</td>\n",
       "      <td>534</td>\n",
       "      <td>3098</td>\n",
       "      <td>25</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27210</th>\n",
       "      <td>2020-03-21</td>\n",
       "      <td>BE</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>EURO</td>\n",
       "      <td>713</td>\n",
       "      <td>3811</td>\n",
       "      <td>35</td>\n",
       "      <td>109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27211</th>\n",
       "      <td>2020-03-22</td>\n",
       "      <td>BE</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>EURO</td>\n",
       "      <td>662</td>\n",
       "      <td>4473</td>\n",
       "      <td>40</td>\n",
       "      <td>149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27212</th>\n",
       "      <td>2020-03-23</td>\n",
       "      <td>BE</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>EURO</td>\n",
       "      <td>469</td>\n",
       "      <td>4942</td>\n",
       "      <td>41</td>\n",
       "      <td>190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27213</th>\n",
       "      <td>2020-03-24</td>\n",
       "      <td>BE</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>EURO</td>\n",
       "      <td>486</td>\n",
       "      <td>5428</td>\n",
       "      <td>55</td>\n",
       "      <td>245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27214</th>\n",
       "      <td>2020-03-25</td>\n",
       "      <td>BE</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>EURO</td>\n",
       "      <td>1328</td>\n",
       "      <td>6756</td>\n",
       "      <td>81</td>\n",
       "      <td>326</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27215</th>\n",
       "      <td>2020-03-26</td>\n",
       "      <td>BE</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>EURO</td>\n",
       "      <td>1195</td>\n",
       "      <td>7951</td>\n",
       "      <td>76</td>\n",
       "      <td>402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27216</th>\n",
       "      <td>2020-03-27</td>\n",
       "      <td>BE</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>EURO</td>\n",
       "      <td>1199</td>\n",
       "      <td>9150</td>\n",
       "      <td>111</td>\n",
       "      <td>513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27217</th>\n",
       "      <td>2020-03-28</td>\n",
       "      <td>BE</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>EURO</td>\n",
       "      <td>1363</td>\n",
       "      <td>10513</td>\n",
       "      <td>102</td>\n",
       "      <td>615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27218</th>\n",
       "      <td>2020-03-29</td>\n",
       "      <td>BE</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>EURO</td>\n",
       "      <td>1518</td>\n",
       "      <td>12031</td>\n",
       "      <td>136</td>\n",
       "      <td>751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27219</th>\n",
       "      <td>2020-03-30</td>\n",
       "      <td>BE</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>EURO</td>\n",
       "      <td>844</td>\n",
       "      <td>12875</td>\n",
       "      <td>144</td>\n",
       "      <td>895</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Date_reported Country_code  Country WHO_region  New_cases  \\\n",
       "27198    2020-03-09           BE  Belgium       EURO         27   \n",
       "27199    2020-03-10           BE  Belgium       EURO         64   \n",
       "27200    2020-03-11           BE  Belgium       EURO         94   \n",
       "27201    2020-03-12           BE  Belgium       EURO         99   \n",
       "27202    2020-03-13           BE  Belgium       EURO        174   \n",
       "27203    2020-03-14           BE  Belgium       EURO        250   \n",
       "27204    2020-03-15           BE  Belgium       EURO        338   \n",
       "27205    2020-03-16           BE  Belgium       EURO        179   \n",
       "27206    2020-03-17           BE  Belgium       EURO        214   \n",
       "27207    2020-03-18           BE  Belgium       EURO        387   \n",
       "27208    2020-03-19           BE  Belgium       EURO        422   \n",
       "27209    2020-03-20           BE  Belgium       EURO        534   \n",
       "27210    2020-03-21           BE  Belgium       EURO        713   \n",
       "27211    2020-03-22           BE  Belgium       EURO        662   \n",
       "27212    2020-03-23           BE  Belgium       EURO        469   \n",
       "27213    2020-03-24           BE  Belgium       EURO        486   \n",
       "27214    2020-03-25           BE  Belgium       EURO       1328   \n",
       "27215    2020-03-26           BE  Belgium       EURO       1195   \n",
       "27216    2020-03-27           BE  Belgium       EURO       1199   \n",
       "27217    2020-03-28           BE  Belgium       EURO       1363   \n",
       "27218    2020-03-29           BE  Belgium       EURO       1518   \n",
       "27219    2020-03-30           BE  Belgium       EURO        844   \n",
       "\n",
       "       Cumulative_cases  New_deaths  Cumulative_deaths  \n",
       "27198               343           1                  1  \n",
       "27199               407           0                  1  \n",
       "27200               501           0                  1  \n",
       "27201               600           1                  2  \n",
       "27202               774           3                  5  \n",
       "27203              1024           0                  5  \n",
       "27204              1362           4                  9  \n",
       "27205              1541           7                 16  \n",
       "27206              1755           7                 23  \n",
       "27207              2142          11                 34  \n",
       "27208              2564          15                 49  \n",
       "27209              3098          25                 74  \n",
       "27210              3811          35                109  \n",
       "27211              4473          40                149  \n",
       "27212              4942          41                190  \n",
       "27213              5428          55                245  \n",
       "27214              6756          81                326  \n",
       "27215              7951          76                402  \n",
       "27216              9150         111                513  \n",
       "27217             10513         102                615  \n",
       "27218             12031         136                751  \n",
       "27219             12875         144                895  "
      ]
     },
     "execution_count": 206,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Belgium_table[(Belgium_table['Cumulative_deaths'] > 0) & (Belgium_table['Cumulative_deaths'] < 1000)]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea7c3d9f-a4cd-4cc5-ad76-b26f52dbe487",
   "metadata": {},
   "source": [
    "Belgium reported its first COVID-related death on March 9, 2020, and it took 21 days until more than 1,000 cases were reported on March 30, 2020."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2986ee60-7cd0-49f6-9a12-ad558a281de0",
   "metadata": {},
   "source": [
    "### Question 3\n",
    "In the first year of the COVID-19 pandemic, which was in 2020, how did the cumulative cases vary across European Union countries?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "id": "9175d170-769a-40fb-9ef8-7d86b98bedc0",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "cases_2020 = EU_covid_df[EU_covid_df['Date_reported'] == '2020-12-31']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "id": "9190354e-8011-44c6-a1ed-2907e3d001dc",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "cases_2020 = cases_2020.sort_values(by='Cumulative_cases', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "id": "cfacfbf6-baa3-4bfa-8ce1-86faddd9bbdb",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#cases_2020.drop(['Country_code','WHO_region','New_cases','New_deaths','Cumulative_deaths','Date_reported'], axis=1, inplace=True)\n",
    "#cases_2020"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "718b4e23-3220-4f1a-bb2a-05345293a008",
   "metadata": {},
   "source": [
    "I attempted to remove columns, but discovered that the first column containing numbers like '27215' and '316662' couldn't be dropped. Instead of eliminating columns, I opted to choose the 'X-axis' and 'Y-axis' values with x='Country' and y='Cumulative_cases'.\n",
    "\n",
    "Additionally, figsize function can help to adjust the bar chart and make it more readable. However, I think if I can turn around the bar chart, and make the countries on the left side, it could be better. But I cannot figured out to call which function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "id": "40e7f599-ef4c-4c00-ac65-3ebf12292373",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = cases_2020.plot(figsize=(12,3), x='Country',y= 'Cumulative_cases', kind='bar',color='green',title= 'COVID-19 Cumulative Cases in EU Countries (2020)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "id": "f22a2819-8142-4a5e-b536-7a90dc2a997b",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "ax.figure.savefig('COVID-19 Cumulative Cases in EU Countries (2020).png')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}