covid-19.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "sns.set(style='white')\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\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>Province/State</th>\n",
       "      <th>Country/Region</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long</th>\n",
       "      <th>Date</th>\n",
       "      <th>Total Confirmed</th>\n",
       "      <th>Total Deaths</th>\n",
       "      <th>Total Recovered</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Japan</td>\n",
       "      <td>36.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>2020-01-22</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Japan</td>\n",
       "      <td>36.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>2020-01-23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Japan</td>\n",
       "      <td>36.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>2020-01-24</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Japan</td>\n",
       "      <td>36.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>2020-01-25</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Japan</td>\n",
       "      <td>36.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>2020-01-26</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</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>28138</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>-20.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28139</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>-20.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>2020-03-17</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28140</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>-20.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>2020-03-18</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28141</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>-20.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>2020-03-19</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28142</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>-20.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>2020-03-20</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>28143 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Province/State Country/Region   Lat   Long        Date  Total Confirmed  \\\n",
       "0                NaN          Japan  36.0  138.0  2020-01-22                2   \n",
       "1                NaN          Japan  36.0  138.0  2020-01-23                1   \n",
       "2                NaN          Japan  36.0  138.0  2020-01-24                2   \n",
       "3                NaN          Japan  36.0  138.0  2020-01-25                2   \n",
       "4                NaN          Japan  36.0  138.0  2020-01-26                4   \n",
       "...              ...            ...   ...    ...         ...              ...   \n",
       "28138            NaN       Zimbabwe -20.0   30.0  2020-03-16                0   \n",
       "28139            NaN       Zimbabwe -20.0   30.0  2020-03-17                0   \n",
       "28140            NaN       Zimbabwe -20.0   30.0  2020-03-18                0   \n",
       "28141            NaN       Zimbabwe -20.0   30.0  2020-03-19                0   \n",
       "28142            NaN       Zimbabwe -20.0   30.0  2020-03-20                1   \n",
       "\n",
       "       Total Deaths  Total Recovered  \n",
       "0                 0                0  \n",
       "1                 0                0  \n",
       "2                 0                0  \n",
       "3                 0                0  \n",
       "4                 0                1  \n",
       "...             ...              ...  \n",
       "28138             0                0  \n",
       "28139             0                0  \n",
       "28140             0                0  \n",
       "28141             0                0  \n",
       "28142             0                0  \n",
       "\n",
       "[28143 rows x 8 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('data.csv', index_col=0)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "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></th>\n",
       "      <th>Total Confirmed</th>\n",
       "      <th>Total Deaths</th>\n",
       "      <th>Total Recovered</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country/Region</th>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">Afghanistan</th>\n",
       "      <th>2020-01-22</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-23</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-24</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-25</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-26</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">Zimbabwe</th>\n",
       "      <th>2020-03-16</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-17</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-18</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-19</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-20</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9558 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Total Confirmed  Total Deaths  Total Recovered\n",
       "Country/Region Date                                                      \n",
       "Afghanistan    2020-01-22                0             0                0\n",
       "               2020-01-23                0             0                0\n",
       "               2020-01-24                0             0                0\n",
       "               2020-01-25                0             0                0\n",
       "               2020-01-26                0             0                0\n",
       "...                                    ...           ...              ...\n",
       "Zimbabwe       2020-03-16                0             0                0\n",
       "               2020-03-17                0             0                0\n",
       "               2020-03-18                0             0                0\n",
       "               2020-03-19                0             0                0\n",
       "               2020-03-20                1             0                0\n",
       "\n",
       "[9558 rows x 3 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_by_country = (df\n",
    "    .set_index(['Lat', 'Long'])\n",
    "    .groupby(['Country/Region', 'Date'])\n",
    "    .sum()\n",
    ")\n",
    "\n",
    "df_by_country"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "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>Total Confirmed</th>\n",
       "      <th>Total Deaths</th>\n",
       "      <th>Total Recovered</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-03-02</th>\n",
       "      <td>2036</td>\n",
       "      <td>52</td>\n",
       "      <td>149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-03</th>\n",
       "      <td>2502</td>\n",
       "      <td>79</td>\n",
       "      <td>160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-04</th>\n",
       "      <td>3089</td>\n",
       "      <td>107</td>\n",
       "      <td>276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-05</th>\n",
       "      <td>3858</td>\n",
       "      <td>148</td>\n",
       "      <td>414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-06</th>\n",
       "      <td>4636</td>\n",
       "      <td>197</td>\n",
       "      <td>523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-07</th>\n",
       "      <td>5883</td>\n",
       "      <td>233</td>\n",
       "      <td>589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-08</th>\n",
       "      <td>7375</td>\n",
       "      <td>366</td>\n",
       "      <td>622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-09</th>\n",
       "      <td>9172</td>\n",
       "      <td>463</td>\n",
       "      <td>724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-10</th>\n",
       "      <td>10149</td>\n",
       "      <td>631</td>\n",
       "      <td>724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-11</th>\n",
       "      <td>12462</td>\n",
       "      <td>827</td>\n",
       "      <td>1045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-12</th>\n",
       "      <td>12462</td>\n",
       "      <td>827</td>\n",
       "      <td>1045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-13</th>\n",
       "      <td>17660</td>\n",
       "      <td>1266</td>\n",
       "      <td>1439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-14</th>\n",
       "      <td>21157</td>\n",
       "      <td>1441</td>\n",
       "      <td>1966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-15</th>\n",
       "      <td>24747</td>\n",
       "      <td>1809</td>\n",
       "      <td>2335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-16</th>\n",
       "      <td>27980</td>\n",
       "      <td>2158</td>\n",
       "      <td>2749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-17</th>\n",
       "      <td>31506</td>\n",
       "      <td>2503</td>\n",
       "      <td>2941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-18</th>\n",
       "      <td>35713</td>\n",
       "      <td>2978</td>\n",
       "      <td>4025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-19</th>\n",
       "      <td>41035</td>\n",
       "      <td>3405</td>\n",
       "      <td>4440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-20</th>\n",
       "      <td>47021</td>\n",
       "      <td>4032</td>\n",
       "      <td>4440</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Total Confirmed  Total Deaths  Total Recovered\n",
       "Date                                                      \n",
       "2020-03-02             2036            52              149\n",
       "2020-03-03             2502            79              160\n",
       "2020-03-04             3089           107              276\n",
       "2020-03-05             3858           148              414\n",
       "2020-03-06             4636           197              523\n",
       "2020-03-07             5883           233              589\n",
       "2020-03-08             7375           366              622\n",
       "2020-03-09             9172           463              724\n",
       "2020-03-10            10149           631              724\n",
       "2020-03-11            12462           827             1045\n",
       "2020-03-12            12462           827             1045\n",
       "2020-03-13            17660          1266             1439\n",
       "2020-03-14            21157          1441             1966\n",
       "2020-03-15            24747          1809             2335\n",
       "2020-03-16            27980          2158             2749\n",
       "2020-03-17            31506          2503             2941\n",
       "2020-03-18            35713          2978             4025\n",
       "2020-03-19            41035          3405             4440\n",
       "2020-03-20            47021          4032             4440"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "country = 'Italy'\n",
    "min_date = \"2020-03-01\"\n",
    "\n",
    "data = df_by_country.loc[country].query('Date > @min_date')\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 6))\n",
    "\n",
    "sns.lineplot(\n",
    "    ax=ax,\n",
    "    data=data,\n",
    ")\n",
    "\n",
    "fig.autofmt_xdate()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Total Confirmed</th>\n",
       "      <th>Total Deaths</th>\n",
       "      <th>Total Recovered</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country/Region</th>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">Afghanistan</th>\n",
       "      <th>2020-01-22</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-23</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-24</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-25</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-26</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">Zimbabwe</th>\n",
       "      <th>2020-03-16</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-17</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-18</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-19</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-20</th>\n",
       "      <td>0.693147</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9558 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Total Confirmed  Total Deaths  Total Recovered\n",
       "Country/Region Date                                                      \n",
       "Afghanistan    2020-01-22         0.000000           0.0              0.0\n",
       "               2020-01-23         0.000000           0.0              0.0\n",
       "               2020-01-24         0.000000           0.0              0.0\n",
       "               2020-01-25         0.000000           0.0              0.0\n",
       "               2020-01-26         0.000000           0.0              0.0\n",
       "...                                    ...           ...              ...\n",
       "Zimbabwe       2020-03-16         0.000000           0.0              0.0\n",
       "               2020-03-17         0.000000           0.0              0.0\n",
       "               2020-03-18         0.000000           0.0              0.0\n",
       "               2020-03-19         0.000000           0.0              0.0\n",
       "               2020-03-20         0.693147           0.0              0.0\n",
       "\n",
       "[9558 rows x 3 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_log_by_country = df_by_country.add(1).apply(np.log)\n",
    "df_log_by_country"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>Country/Region</th>\n",
       "      <th>Date</th>\n",
       "      <th>Total Confirmed</th>\n",
       "      <th>Total Deaths</th>\n",
       "      <th>Total Recovered</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>2020-03-11</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>2020-03-12</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>2020-03-13</td>\n",
       "      <td>31</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>2020-03-14</td>\n",
       "      <td>34</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>2020-03-15</td>\n",
       "      <td>45</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>56</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>2020-03-17</td>\n",
       "      <td>68</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>2020-03-18</td>\n",
       "      <td>79</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>2020-03-19</td>\n",
       "      <td>97</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>2020-03-20</td>\n",
       "      <td>128</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>2020-03-11</td>\n",
       "      <td>38</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>2020-03-12</td>\n",
       "      <td>52</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>2020-03-13</td>\n",
       "      <td>151</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>2020-03-14</td>\n",
       "      <td>151</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>2020-03-15</td>\n",
       "      <td>162</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>200</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>2020-03-17</td>\n",
       "      <td>321</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>2020-03-18</td>\n",
       "      <td>372</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>2020-03-19</td>\n",
       "      <td>621</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>2020-03-20</td>\n",
       "      <td>793</td>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Chile</td>\n",
       "      <td>2020-03-11</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Chile</td>\n",
       "      <td>2020-03-12</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Chile</td>\n",
       "      <td>2020-03-13</td>\n",
       "      <td>43</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Chile</td>\n",
       "      <td>2020-03-14</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Chile</td>\n",
       "      <td>2020-03-15</td>\n",
       "      <td>74</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Chile</td>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>155</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Chile</td>\n",
       "      <td>2020-03-17</td>\n",
       "      <td>201</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Chile</td>\n",
       "      <td>2020-03-18</td>\n",
       "      <td>238</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Chile</td>\n",
       "      <td>2020-03-19</td>\n",
       "      <td>238</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Chile</td>\n",
       "      <td>2020-03-20</td>\n",
       "      <td>434</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Country/Region        Date  Total Confirmed  Total Deaths  Total Recovered\n",
       "0       Argentina  2020-03-11               19             1                0\n",
       "1       Argentina  2020-03-12               19             1                0\n",
       "2       Argentina  2020-03-13               31             2                0\n",
       "3       Argentina  2020-03-14               34             2                1\n",
       "4       Argentina  2020-03-15               45             2                1\n",
       "5       Argentina  2020-03-16               56             2                1\n",
       "6       Argentina  2020-03-17               68             2                3\n",
       "7       Argentina  2020-03-18               79             2                3\n",
       "8       Argentina  2020-03-19               97             3                3\n",
       "9       Argentina  2020-03-20              128             3                3\n",
       "10         Brazil  2020-03-11               38             0                0\n",
       "11         Brazil  2020-03-12               52             0                0\n",
       "12         Brazil  2020-03-13              151             0                0\n",
       "13         Brazil  2020-03-14              151             0                0\n",
       "14         Brazil  2020-03-15              162             0                0\n",
       "15         Brazil  2020-03-16              200             0                1\n",
       "16         Brazil  2020-03-17              321             1                2\n",
       "17         Brazil  2020-03-18              372             3                2\n",
       "18         Brazil  2020-03-19              621             6                2\n",
       "19         Brazil  2020-03-20              793            11                2\n",
       "20          Chile  2020-03-11               23             0                0\n",
       "21          Chile  2020-03-12               23             0                0\n",
       "22          Chile  2020-03-13               43             0                0\n",
       "23          Chile  2020-03-14               61             0                0\n",
       "24          Chile  2020-03-15               74             0                0\n",
       "25          Chile  2020-03-16              155             0                0\n",
       "26          Chile  2020-03-17              201             0                0\n",
       "27          Chile  2020-03-18              238             0                0\n",
       "28          Chile  2020-03-19              238             0                0\n",
       "29          Chile  2020-03-20              434             0                6"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "countries = ['Argentina', 'Brazil', 'Chile']\n",
    "min_date = '2020-03-10'\n",
    "\n",
    "data = (df_by_country\n",
    "    .loc[countries]\n",
    "    .query('Date > @min_date')\n",
    "    .reset_index())\n",
    "\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(style='whitegrid')\n",
    "fig, (ax1) = plt.subplots(figsize=(18, 6))\n",
    "\n",
    "sns.lineplot(\n",
    "    ax=ax1,\n",
    "    data=data,\n",
    "    x='Date',\n",
    "    y='Total Confirmed',\n",
    "    hue='Country/Region',\n",
    ")\n",
    "\n",
    "fig.autofmt_xdate()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x864 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(style='white')\n",
    "\n",
    "fig, (ax1, ax2) = plt.subplots(figsize=(16, 12), nrows=2)\n",
    "\n",
    "data = df_by_country.loc['Italy'].query('`Total Confirmed` > 100').reset_index()\n",
    "\n",
    "sns.barplot(\n",
    "    ax=ax1,\n",
    "    data=data,\n",
    "    x='Date',\n",
    "    y='Total Confirmed',\n",
    "    color='b'\n",
    ")\n",
    "\n",
    "sns.barplot(\n",
    "    ax=ax2,\n",
    "    data=data,\n",
    "    x='Date',\n",
    "    y='Total Deaths',\n",
    "    color='b'\n",
    ")\n",
    "\n",
    "fig.autofmt_xdate()\n",
    "\n",
    "for index, row in data.iterrows():\n",
    "    ax1.text(index - 0.5, row['Total Confirmed'] + 1000, row['Total Confirmed'])\n",
    "    ax2.text(index - 0.5, row['Total Deaths'] + 100, row['Total Deaths'])\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
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