COVID PROJECTS.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "canada_data= pd.read_csv(\"canada-testing-data.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>id</th>\n",
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       "      <th>age</th>\n",
       "      <th>case_id</th>\n",
       "      <th>country</th>\n",
       "      <th>province</th>\n",
       "      <th>region</th>\n",
       "      <th>sex</th>\n",
       "      <th>travel</th>\n",
       "      <th>travelh</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>3904</td>\n",
       "      <td>2020-03-26</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>3904</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Saskatchewan</td>\n",
       "      <td>Saskatoon</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
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       "      <td>1</td>\n",
       "      <td>1516</td>\n",
       "      <td>2020-03-23</td>\n",
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       "      <td>1516</td>\n",
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       "      <td>Ontario</td>\n",
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       "      <td>Male</td>\n",
       "      <td>1</td>\n",
       "      <td>Costa Rica</td>\n",
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       "      <td>2</td>\n",
       "      <td>18454</td>\n",
       "      <td>2020-04-07</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>18451</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <td>3</td>\n",
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       "      <td>2020-04-07</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>18452</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>5658</td>\n",
       "      <td>2020-03-29</td>\n",
       "      <td>60-69</td>\n",
       "      <td>5657</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Algoma</td>\n",
       "      <td>Female</td>\n",
       "      <td>1</td>\n",
       "      <td>United States</td>\n",
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       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>642</td>\n",
       "      <td>2020-03-18</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>642</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Nova Scotia</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>1</td>\n",
       "      <td>Not Reported</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>3560</td>\n",
       "      <td>2020-03-26</td>\n",
       "      <td>60-69</td>\n",
       "      <td>3560</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Simcoe Muskoka</td>\n",
       "      <td>Male</td>\n",
       "      <td>1</td>\n",
       "      <td>India, United Arab Emirates</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>725</td>\n",
       "      <td>2020-03-18</td>\n",
       "      <td>80-89</td>\n",
       "      <td>725</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Chatham-Kent</td>\n",
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       "      <td>1</td>\n",
       "      <td>United States</td>\n",
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       "      <td>8</td>\n",
       "      <td>21943</td>\n",
       "      <td>2020-04-10</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>21940</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Quebec</td>\n",
       "      <td>Montréal</td>\n",
       "      <td>Not Reported</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>Not Reported</td>\n",
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       "      <td>Toronto</td>\n",
       "      <td>Not Reported</td>\n",
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       "      <td>NaN</td>\n",
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      "text/plain": [
       "      id        date           age  case_id country      province  \\\n",
       "0   3904  2020-03-26  Not Reported     3904  Canada  Saskatchewan   \n",
       "1   1516  2020-03-23         40-49     1516  Canada       Ontario   \n",
       "2  18454  2020-04-07  Not Reported    18451  Canada       Ontario   \n",
       "3  18455  2020-04-07  Not Reported    18452  Canada       Ontario   \n",
       "4   5658  2020-03-29         60-69     5657  Canada       Ontario   \n",
       "5    642  2020-03-18  Not Reported      642  Canada   Nova Scotia   \n",
       "6   3560  2020-03-26         60-69     3560  Canada       Ontario   \n",
       "7    725  2020-03-18         80-89      725  Canada       Ontario   \n",
       "8  21943  2020-04-10  Not Reported    21940  Canada        Quebec   \n",
       "9  18457  2020-04-07  Not Reported    18454  Canada       Ontario   \n",
       "\n",
       "           region           sex  travel                      travelh  \n",
       "0       Saskatoon  Not Reported       0                          NaN  \n",
       "1            York          Male       1                   Costa Rica  \n",
       "2         Toronto  Not Reported       0                          NaN  \n",
       "3         Toronto  Not Reported       0                          NaN  \n",
       "4          Algoma        Female       1                United States  \n",
       "5    Not Reported  Not Reported       1                 Not Reported  \n",
       "6  Simcoe Muskoka          Male       1  India, United Arab Emirates  \n",
       "7    Chatham-Kent        Female       1                United States  \n",
       "8        Montréal  Not Reported       0                          NaN  \n",
       "9         Toronto  Not Reported       0                          NaN  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_data.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(50984, 10)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 50984 entries, 0 to 50983\n",
      "Data columns (total 10 columns):\n",
      "id          50984 non-null int64\n",
      "date        50984 non-null object\n",
      "age         50984 non-null object\n",
      "case_id     50984 non-null int64\n",
      "country     50984 non-null object\n",
      "province    50984 non-null object\n",
      "region      50984 non-null object\n",
      "sex         50984 non-null object\n",
      "travel      50984 non-null int64\n",
      "travelh     592 non-null object\n",
      "dtypes: int64(3), object(7)\n",
      "memory usage: 3.9+ MB\n"
     ]
    }
   ],
   "source": [
    "canada_data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
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       "      <td>50984.000000</td>\n",
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       "    <tr>\n",
       "      <td>mean</td>\n",
       "      <td>25493.418622</td>\n",
       "      <td>25491.191943</td>\n",
       "      <td>0.011611</td>\n",
       "    </tr>\n",
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       "      <td>std</td>\n",
       "      <td>14718.086883</td>\n",
       "      <td>14717.173561</td>\n",
       "      <td>0.107130</td>\n",
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       "      <td>min</td>\n",
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       "      <td>1.000000</td>\n",
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       "      <td>25%</td>\n",
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       "      <td>12746.750000</td>\n",
       "      <td>0.000000</td>\n",
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       "    <tr>\n",
       "      <td>50%</td>\n",
       "      <td>25493.500000</td>\n",
       "      <td>25490.500000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>75%</td>\n",
       "      <td>38239.250000</td>\n",
       "      <td>38236.250000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>max</td>\n",
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       "      <td>50982.000000</td>\n",
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       "                 id       case_id        travel\n",
       "count  50984.000000  50984.000000  50984.000000\n",
       "mean   25493.418622  25491.191943      0.011611\n",
       "std    14718.086883  14717.173561      0.107130\n",
       "min        1.000000      1.000000      0.000000\n",
       "25%    12747.750000  12746.750000      0.000000\n",
       "50%    25493.500000  25490.500000      0.000000\n",
       "75%    38239.250000  38236.250000      0.000000\n",
       "max    50985.000000  50982.000000      1.000000"
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     "execution_count": 6,
     "metadata": {},
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   "source": [
    "canada_data.describe()"
   ]
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       "              date           age country province    region           sex  \\\n",
       "count        50984         50984   50984    50984     50984         50984   \n",
       "unique          72            17       1       13        86             3   \n",
       "top     2020-04-22  Not Reported  Canada   Quebec  Montréal  Not Reported   \n",
       "freq          1970         49523   50984    25759     12489         49660   \n",
       "\n",
       "             travelh  \n",
       "count            592  \n",
       "unique            75  \n",
       "top     Not Reported  \n",
       "freq             165  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "canada_data.describe(include=object)"
   ]
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  {
   "cell_type": "code",
   "execution_count": 13,
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50%</td>\n",
       "      <td>25493.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25490.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75%</td>\n",
       "      <td>38239.250000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38236.250000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>max</td>\n",
       "      <td>50985.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50982.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  id        date           age       case_id country province  \\\n",
       "count   50984.000000       50984         50984  50984.000000   50984    50984   \n",
       "unique           NaN          72            17           NaN       1       13   \n",
       "top              NaN  2020-04-22  Not Reported           NaN  Canada   Quebec   \n",
       "freq             NaN        1970         49523           NaN   50984    25759   \n",
       "mean    25493.418622         NaN           NaN  25491.191943     NaN      NaN   \n",
       "std     14718.086883         NaN           NaN  14717.173561     NaN      NaN   \n",
       "min         1.000000         NaN           NaN      1.000000     NaN      NaN   \n",
       "25%     12747.750000         NaN           NaN  12746.750000     NaN      NaN   \n",
       "50%     25493.500000         NaN           NaN  25490.500000     NaN      NaN   \n",
       "75%     38239.250000         NaN           NaN  38236.250000     NaN      NaN   \n",
       "max     50985.000000         NaN           NaN  50982.000000     NaN      NaN   \n",
       "\n",
       "          region           sex        travel       travelh  \n",
       "count      50984         50984  50984.000000           592  \n",
       "unique        86             3           NaN            75  \n",
       "top     Montréal  Not Reported           NaN  Not Reported  \n",
       "freq       12489         49660           NaN           165  \n",
       "mean         NaN           NaN      0.011611           NaN  \n",
       "std          NaN           NaN      0.107130           NaN  \n",
       "min          NaN           NaN      0.000000           NaN  \n",
       "25%          NaN           NaN      0.000000           NaN  \n",
       "50%          NaN           NaN      0.000000           NaN  \n",
       "75%          NaN           NaN      0.000000           NaN  \n",
       "max          NaN           NaN      1.000000           NaN  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_data.describe(include=\"all\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>id</th>\n",
       "      <th>date</th>\n",
       "      <th>age</th>\n",
       "      <th>case_id</th>\n",
       "      <th>country</th>\n",
       "      <th>province</th>\n",
       "      <th>region</th>\n",
       "      <th>sex</th>\n",
       "      <th>travel</th>\n",
       "      <th>travelh</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>3904</td>\n",
       "      <td>2020-03-26</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>3904</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Saskatchewan</td>\n",
       "      <td>Saskatoon</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1516</td>\n",
       "      <td>2020-03-23</td>\n",
       "      <td>40-49</td>\n",
       "      <td>1516</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>York</td>\n",
       "      <td>Male</td>\n",
       "      <td>1</td>\n",
       "      <td>Costa Rica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>18454</td>\n",
       "      <td>2020-04-07</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>18451</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>18455</td>\n",
       "      <td>2020-04-07</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>18452</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>5658</td>\n",
       "      <td>2020-03-29</td>\n",
       "      <td>60-69</td>\n",
       "      <td>5657</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Algoma</td>\n",
       "      <td>Female</td>\n",
       "      <td>1</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50979</td>\n",
       "      <td>10865</td>\n",
       "      <td>2020-04-02</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>10864</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Quebec</td>\n",
       "      <td>Montréal</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50980</td>\n",
       "      <td>10867</td>\n",
       "      <td>2020-04-02</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>10866</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Quebec</td>\n",
       "      <td>Montréal</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50981</td>\n",
       "      <td>10869</td>\n",
       "      <td>2020-04-02</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>10868</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Quebec</td>\n",
       "      <td>Montréal</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50982</td>\n",
       "      <td>10873</td>\n",
       "      <td>2020-04-02</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>10872</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Quebec</td>\n",
       "      <td>Montréal</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50983</td>\n",
       "      <td>10879</td>\n",
       "      <td>2020-04-02</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>10878</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Quebec</td>\n",
       "      <td>Montréal</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>50984 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id        date           age  case_id country      province  \\\n",
       "0       3904  2020-03-26  Not Reported     3904  Canada  Saskatchewan   \n",
       "1       1516  2020-03-23         40-49     1516  Canada       Ontario   \n",
       "2      18454  2020-04-07  Not Reported    18451  Canada       Ontario   \n",
       "3      18455  2020-04-07  Not Reported    18452  Canada       Ontario   \n",
       "4       5658  2020-03-29         60-69     5657  Canada       Ontario   \n",
       "...      ...         ...           ...      ...     ...           ...   \n",
       "50979  10865  2020-04-02  Not Reported    10864  Canada        Quebec   \n",
       "50980  10867  2020-04-02  Not Reported    10866  Canada        Quebec   \n",
       "50981  10869  2020-04-02  Not Reported    10868  Canada        Quebec   \n",
       "50982  10873  2020-04-02  Not Reported    10872  Canada        Quebec   \n",
       "50983  10879  2020-04-02  Not Reported    10878  Canada        Quebec   \n",
       "\n",
       "          region           sex  travel        travelh  \n",
       "0      Saskatoon  Not Reported       0            NaN  \n",
       "1           York          Male       1     Costa Rica  \n",
       "2        Toronto  Not Reported       0            NaN  \n",
       "3        Toronto  Not Reported       0            NaN  \n",
       "4         Algoma        Female       1  United States  \n",
       "...          ...           ...     ...            ...  \n",
       "50979   Montréal  Not Reported       0            NaN  \n",
       "50980   Montréal  Not Reported       0            NaN  \n",
       "50981   Montréal  Not Reported       0            NaN  \n",
       "50982   Montréal  Not Reported       0            NaN  \n",
       "50983   Montréal  Not Reported       0            NaN  \n",
       "\n",
       "[50984 rows x 10 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_data.groupby(\"id\").head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "17638    2\n",
       "17639    2\n",
       "2047     1\n",
       "35460    1\n",
       "661      1\n",
       "        ..\n",
       "46396    1\n",
       "36155    1\n",
       "34106    1\n",
       "40249    1\n",
       "2049     1\n",
       "Name: case_id, Length: 50982, dtype: int64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_data[\"case_id\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "case_ids= set(canada_data[\"case_id\"].values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>date</th>\n",
       "      <th>age</th>\n",
       "      <th>case_id</th>\n",
       "      <th>country</th>\n",
       "      <th>province</th>\n",
       "      <th>region</th>\n",
       "      <th>sex</th>\n",
       "      <th>travel</th>\n",
       "      <th>travelh</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>19109</td>\n",
       "      <td>17642</td>\n",
       "      <td>2020-04-07</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>17639</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Quebec</td>\n",
       "      <td>Montréal</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50594</td>\n",
       "      <td>17641</td>\n",
       "      <td>2020-04-07</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>17639</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Quebec</td>\n",
       "      <td>Montréal</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          id        date           age  case_id country province    region  \\\n",
       "19109  17642  2020-04-07  Not Reported    17639  Canada   Quebec  Montréal   \n",
       "50594  17641  2020-04-07  Not Reported    17639  Canada   Quebec  Montréal   \n",
       "\n",
       "                sex  travel travelh  \n",
       "19109  Not Reported       0     NaN  \n",
       "50594  Not Reported       0     NaN  "
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_data.loc[canada_data[\"case_id\"]==17639]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         3904\n",
       "1         1516\n",
       "2        18451\n",
       "3        18452\n",
       "4         5657\n",
       "         ...  \n",
       "50979    10864\n",
       "50980    10866\n",
       "50981    10868\n",
       "50982    10872\n",
       "50983    10878\n",
       "Name: case_id, Length: 50984, dtype: int64"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_data['case_id']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'date', 'age', 'case_id', 'country', 'province', 'region', 'sex',\n",
       "       'travel', 'travelh'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>date</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>2020-01-25</td>\n",
       "      <td>50-59</td>\n",
       "      <td>1</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>Male</td>\n",
       "      <td>1</td>\n",
       "      <td>China</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2789</td>\n",
       "      <td>2</td>\n",
       "      <td>2020-01-27</td>\n",
       "      <td>50-59</td>\n",
       "      <td>2</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>Female</td>\n",
       "      <td>1</td>\n",
       "      <td>China</td>\n",
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       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>3</td>\n",
       "      <td>2020-01-28</td>\n",
       "      <td>40-49</td>\n",
       "      <td>3</td>\n",
       "      <td>Canada</td>\n",
       "      <td>BC</td>\n",
       "      <td>Vancouver Coastal</td>\n",
       "      <td>Male</td>\n",
       "      <td>1</td>\n",
       "      <td>China</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2822</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>20-29</td>\n",
       "      <td>4</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Middlesex-London</td>\n",
       "      <td>Female</td>\n",
       "      <td>1</td>\n",
       "      <td>China</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16001</td>\n",
       "      <td>5</td>\n",
       "      <td>2020-02-04</td>\n",
       "      <td>50-59</td>\n",
       "      <td>5</td>\n",
       "      <td>Canada</td>\n",
       "      <td>BC</td>\n",
       "      <td>Vancouver Coastal</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16637</td>\n",
       "      <td>50981</td>\n",
       "      <td>2020-04-28</td>\n",
       "      <td>40-49</td>\n",
       "      <td>50978</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Thunder Bay</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16638</td>\n",
       "      <td>50982</td>\n",
       "      <td>2020-04-28</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>50979</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Peterborough</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16639</td>\n",
       "      <td>50983</td>\n",
       "      <td>2020-04-28</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>50980</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Peterborough</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16640</td>\n",
       "      <td>50984</td>\n",
       "      <td>2020-04-28</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>50981</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Peterborough</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16641</td>\n",
       "      <td>50985</td>\n",
       "      <td>2020-04-28</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>50982</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Sudbury</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>50984 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id        date           age  case_id country province  \\\n",
       "10         1  2020-01-25         50-59        1  Canada  Ontario   \n",
       "2789       2  2020-01-27         50-59        2  Canada  Ontario   \n",
       "11         3  2020-01-28         40-49        3  Canada       BC   \n",
       "2822       4  2020-01-31         20-29        4  Canada  Ontario   \n",
       "16001      5  2020-02-04         50-59        5  Canada       BC   \n",
       "...      ...         ...           ...      ...     ...      ...   \n",
       "16637  50981  2020-04-28         40-49    50978  Canada  Ontario   \n",
       "16638  50982  2020-04-28  Not Reported    50979  Canada  Ontario   \n",
       "16639  50983  2020-04-28  Not Reported    50980  Canada  Ontario   \n",
       "16640  50984  2020-04-28  Not Reported    50981  Canada  Ontario   \n",
       "16641  50985  2020-04-28  Not Reported    50982  Canada  Ontario   \n",
       "\n",
       "                  region           sex  travel travelh  \n",
       "10               Toronto          Male       1   China  \n",
       "2789             Toronto        Female       1   China  \n",
       "11     Vancouver Coastal          Male       1   China  \n",
       "2822    Middlesex-London        Female       1   China  \n",
       "16001  Vancouver Coastal        Female       0     NaN  \n",
       "...                  ...           ...     ...     ...  \n",
       "16637        Thunder Bay          Male       0     NaN  \n",
       "16638       Peterborough  Not Reported       0     NaN  \n",
       "16639       Peterborough  Not Reported       0     NaN  \n",
       "16640       Peterborough  Not Reported       0     NaN  \n",
       "16641            Sudbury  Not Reported       0     NaN  \n",
       "\n",
       "[50984 rows x 10 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_data.sort_values(\"case_id\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <td>Canada</td>\n",
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       "      <td>1</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
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       "      <td>India, United Arab Emirates</td>\n",
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       "    <tr>\n",
       "      <td>8715</td>\n",
       "      <td>26358</td>\n",
       "      <td>2020-04-13</td>\n",
       "      <td>50-59</td>\n",
       "      <td>26355</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>North Bay Parry Sound</td>\n",
       "      <td>Female</td>\n",
       "      <td>1</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10968</td>\n",
       "      <td>17168</td>\n",
       "      <td>2020-04-06</td>\n",
       "      <td>40-49</td>\n",
       "      <td>17167</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Algoma</td>\n",
       "      <td>Female</td>\n",
       "      <td>1</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15019</td>\n",
       "      <td>24856</td>\n",
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       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Timiskaming</td>\n",
       "      <td>Female</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>15020</td>\n",
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       "      <td>2020-04-12</td>\n",
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       "      <td>0</td>\n",
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       "      <td>Ontario</td>\n",
       "      <td>Timiskaming</td>\n",
       "      <td>Male</td>\n",
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       "      <td>NaN</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>170 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id        date           age  case_id country province  \\\n",
       "1       1516  2020-03-23         40-49     1516  Canada  Ontario   \n",
       "2      18454  2020-04-07  Not Reported    18451  Canada  Ontario   \n",
       "3      18455  2020-04-07  Not Reported    18452  Canada  Ontario   \n",
       "4       5658  2020-03-29         60-69     5657  Canada  Ontario   \n",
       "6       3560  2020-03-26         60-69     3560  Canada  Ontario   \n",
       "...      ...         ...           ...      ...     ...      ...   \n",
       "8715   26358  2020-04-13         50-59    26355  Canada  Ontario   \n",
       "10968  17168  2020-04-06         40-49    17167  Canada  Ontario   \n",
       "15019  24856  2020-04-12         70-79    24853  Canada  Ontario   \n",
       "15020  24857  2020-04-12         20-29    24854  Canada  Ontario   \n",
       "15998  14326  2020-04-04         50-59    14325  Canada  Ontario   \n",
       "\n",
       "                      region           sex  travel  \\\n",
       "1                       York          Male       1   \n",
       "2                    Toronto  Not Reported       0   \n",
       "3                    Toronto  Not Reported       0   \n",
       "4                     Algoma        Female       1   \n",
       "6             Simcoe Muskoka          Male       1   \n",
       "...                      ...           ...     ...   \n",
       "8715   North Bay Parry Sound        Female       1   \n",
       "10968                 Algoma        Female       1   \n",
       "15019            Timiskaming        Female       0   \n",
       "15020            Timiskaming          Male       0   \n",
       "15998            Timiskaming          Male       0   \n",
       "\n",
       "                           travelh  \n",
       "1                       Costa Rica  \n",
       "2                              NaN  \n",
       "3                              NaN  \n",
       "4                    United States  \n",
       "6      India, United Arab Emirates  \n",
       "...                            ...  \n",
       "8715                        Canada  \n",
       "10968               United Kingdom  \n",
       "15019                          NaN  \n",
       "15020                          NaN  \n",
       "15998                          NaN  \n",
       "\n",
       "[170 rows x 10 columns]"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_data[canada_data['province']==\"Ontario\"].groupby(\"region\").head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>Female</td>\n",
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       "      <td>Not Reported</td>\n",
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       "      <td>3440</td>\n",
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       "      <td>2020-03-20</td>\n",
       "      <td>60-69</td>\n",
       "      <td>956</td>\n",
       "      <td>Canada</td>\n",
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       "      <td>Middlesex-London</td>\n",
       "      <td>Female</td>\n",
       "      <td>1</td>\n",
       "      <td>Not Reported</td>\n",
       "    </tr>\n",
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       "      <td>3316</td>\n",
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       "      <td>2020-03-17</td>\n",
       "      <td>50-59</td>\n",
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       "      <td>Canada</td>\n",
       "      <td>Saskatchewan</td>\n",
       "      <td>Regina</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <td>1650</td>\n",
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       "      <td>30-39</td>\n",
       "      <td>107</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>Calgary</td>\n",
       "      <td>Female</td>\n",
       "      <td>1</td>\n",
       "      <td>Not Reported</td>\n",
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       "    <tr>\n",
       "      <td>14632</td>\n",
       "      <td>4592</td>\n",
       "      <td>2020-03-27</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>4591</td>\n",
       "      <td>Canada</td>\n",
       "      <td>NL</td>\n",
       "      <td>Labrador-Grenfell</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>1</td>\n",
       "      <td>Not Reported</td>\n",
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       "    <tr>\n",
       "      <td>3601</td>\n",
       "      <td>482</td>\n",
       "      <td>2020-03-17</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>482</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Nova Scotia</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>Not Reported</td>\n",
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       "      <td>Not Reported</td>\n",
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       "      <td>Canada</td>\n",
       "      <td>PEI</td>\n",
       "      <td>Prince Edward Island</td>\n",
       "      <td>Male</td>\n",
       "      <td>1</td>\n",
       "      <td>Not Reported</td>\n",
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       "      <td>Ontario</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>Male</td>\n",
       "      <td>1</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13033</td>\n",
       "      <td>11373</td>\n",
       "      <td>2020-04-02</td>\n",
       "      <td>60-69</td>\n",
       "      <td>11372</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Sudbury</td>\n",
       "      <td>Male</td>\n",
       "      <td>1</td>\n",
       "      <td>Not Reported</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4351</td>\n",
       "      <td>1508</td>\n",
       "      <td>2020-03-23</td>\n",
       "      <td>30-39</td>\n",
       "      <td>1508</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>York</td>\n",
       "      <td>Male</td>\n",
       "      <td>1</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8020</td>\n",
       "      <td>1471</td>\n",
       "      <td>2020-03-22</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>1471</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Yukon</td>\n",
       "      <td>Yukon</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>1</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2588</td>\n",
       "      <td>293</td>\n",
       "      <td>2020-03-15</td>\n",
       "      <td>70-79</td>\n",
       "      <td>293</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Manitoba</td>\n",
       "      <td>Winnipeg</td>\n",
       "      <td>Male</td>\n",
       "      <td>1</td>\n",
       "      <td>Not Reported</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8976</td>\n",
       "      <td>2023</td>\n",
       "      <td>2020-03-23</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>2023</td>\n",
       "      <td>Canada</td>\n",
       "      <td>NL</td>\n",
       "      <td>Eastern</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>1</td>\n",
       "      <td>Not Reported</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8768</td>\n",
       "      <td>2022</td>\n",
       "      <td>2020-03-23</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>2022</td>\n",
       "      <td>Canada</td>\n",
       "      <td>NL</td>\n",
       "      <td>Eastern</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>1</td>\n",
       "      <td>Not Reported</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          id        date           age  case_id country      province  \\\n",
       "8994    9743  2020-04-01         60-69     9742  Canada       Ontario   \n",
       "1470     654  2020-03-18  Not Reported      654  Canada  Saskatchewan   \n",
       "6150   11374  2020-04-02         50-59    11373  Canada       Ontario   \n",
       "7033    2872  2020-03-25         50-59     2872  Canada       Ontario   \n",
       "133      608  2020-03-18         40-49      608  Canada       Ontario   \n",
       "400     4046  2020-03-27         60-69     4046  Canada       Ontario   \n",
       "3440     956  2020-03-20         60-69      956  Canada       Ontario   \n",
       "3316     478  2020-03-17         50-59      478  Canada  Saskatchewan   \n",
       "1650     107  2020-03-11         30-39      107  Canada       Alberta   \n",
       "14632   4592  2020-03-27  Not Reported     4591  Canada            NL   \n",
       "3601     482  2020-03-17  Not Reported      482  Canada   Nova Scotia   \n",
       "5354    7287  2020-03-30  Not Reported     7286  Canada           PEI   \n",
       "2476     122  2020-03-12         40-49      122  Canada       Ontario   \n",
       "651     2128  2020-03-24         50-59     2128  Canada       Ontario   \n",
       "13033  11373  2020-04-02         60-69    11372  Canada       Ontario   \n",
       "4351    1508  2020-03-23         30-39     1508  Canada       Ontario   \n",
       "8020    1471  2020-03-22  Not Reported     1471  Canada         Yukon   \n",
       "2588     293  2020-03-15         70-79      293  Canada      Manitoba   \n",
       "8976    2023  2020-03-23  Not Reported     2023  Canada            NL   \n",
       "8768    2022  2020-03-23  Not Reported     2022  Canada            NL   \n",
       "\n",
       "                     region           sex  travel           travelh  \n",
       "8994                Sudbury        Female       1            Canada  \n",
       "1470                 Regina  Not Reported       1            Mexico  \n",
       "6150                Sudbury          Male       1      Not Reported  \n",
       "7033         Simcoe Muskoka        Female       1           Austria  \n",
       "133                Waterloo        Female       1  Pakistan, Turkey  \n",
       "400              Grey Bruce        Female       1      Not Reported  \n",
       "3440       Middlesex-London        Female       1      Not Reported  \n",
       "3316                 Regina  Not Reported       1            Canada  \n",
       "1650                Calgary        Female       1      Not Reported  \n",
       "14632     Labrador-Grenfell  Not Reported       1      Not Reported  \n",
       "3601           Not Reported  Not Reported       1      Not Reported  \n",
       "5354   Prince Edward Island          Male       1      Not Reported  \n",
       "2476                 Ottawa        Female       1             Italy  \n",
       "651                 Toronto          Male       1     United States  \n",
       "13033               Sudbury          Male       1      Not Reported  \n",
       "4351                   York          Male       1     United States  \n",
       "8020                  Yukon  Not Reported       1     United States  \n",
       "2588               Winnipeg          Male       1      Not Reported  \n",
       "8976                Eastern  Not Reported       1      Not Reported  \n",
       "8768                Eastern  Not Reported       1      Not Reported  "
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_data[canada_data[\"travel\"]!=0].sample(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>date</th>\n",
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       "      <th>travelh</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <td>27476</td>\n",
       "      <td>23483</td>\n",
       "      <td>2020-04-11</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>23480</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Waterloo</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>29809</td>\n",
       "      <td>30886</td>\n",
       "      <td>2020-04-16</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>30883</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>302</td>\n",
       "      <td>25505</td>\n",
       "      <td>2020-04-13</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>25502</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Quebec</td>\n",
       "      <td>Montréal</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>36008</td>\n",
       "      <td>48393</td>\n",
       "      <td>2020-04-27</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>48390</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Quebec</td>\n",
       "      <td>Laval</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>30575</td>\n",
       "      <td>31117</td>\n",
       "      <td>2020-04-17</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>31114</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Quebec</td>\n",
       "      <td>Laurentides</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>29434</td>\n",
       "      <td>13380</td>\n",
       "      <td>2020-04-04</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>13379</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Quebec</td>\n",
       "      <td>Montérégie</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>45423</td>\n",
       "      <td>35399</td>\n",
       "      <td>2020-04-19</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>35396</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>Calgary</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1251</td>\n",
       "      <td>33695</td>\n",
       "      <td>2020-04-18</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>33692</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>Calgary</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>30063</td>\n",
       "      <td>13991</td>\n",
       "      <td>2020-04-04</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>13990</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>Calgary</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>49725</td>\n",
       "      <td>7851</td>\n",
       "      <td>2020-03-31</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>7850</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Quebec</td>\n",
       "      <td>Gaspésie-Îles-de-la-Madeleine</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          id        date           age  case_id country province  \\\n",
       "27476  23483  2020-04-11  Not Reported    23480  Canada  Ontario   \n",
       "29809  30886  2020-04-16  Not Reported    30883  Canada  Ontario   \n",
       "302    25505  2020-04-13  Not Reported    25502  Canada   Quebec   \n",
       "36008  48393  2020-04-27  Not Reported    48390  Canada   Quebec   \n",
       "30575  31117  2020-04-17  Not Reported    31114  Canada   Quebec   \n",
       "29434  13380  2020-04-04  Not Reported    13379  Canada   Quebec   \n",
       "45423  35399  2020-04-19  Not Reported    35396  Canada  Alberta   \n",
       "1251   33695  2020-04-18  Not Reported    33692  Canada  Alberta   \n",
       "30063  13991  2020-04-04  Not Reported    13990  Canada  Alberta   \n",
       "49725   7851  2020-03-31  Not Reported     7850  Canada   Quebec   \n",
       "\n",
       "                              region           sex  travel travelh  \n",
       "27476                       Waterloo  Not Reported       0     NaN  \n",
       "29809                        Toronto  Not Reported       0     NaN  \n",
       "302                         Montréal  Not Reported       0     NaN  \n",
       "36008                          Laval  Not Reported       0     NaN  \n",
       "30575                    Laurentides  Not Reported       0     NaN  \n",
       "29434                     Montérégie  Not Reported       0     NaN  \n",
       "45423                        Calgary  Not Reported       0     NaN  \n",
       "1251                         Calgary  Not Reported       0     NaN  \n",
       "30063                        Calgary  Not Reported       0     NaN  \n",
       "49725  Gaspésie-Îles-de-la-Madeleine  Not Reported       0     NaN  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_data.sample(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "canada_data.drop([\"id\",\"case_id\",\"country\"], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <th>province</th>\n",
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       "      <th>travelh</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>12267</td>\n",
       "      <td>2020-04-21</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>South</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17134</td>\n",
       "      <td>2020-04-20</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>Central</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5876</td>\n",
       "      <td>2020-03-31</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>Quebec</td>\n",
       "      <td>Montréal</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21351</td>\n",
       "      <td>2020-03-18</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>BC</td>\n",
       "      <td>Fraser</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50942</td>\n",
       "      <td>2020-04-02</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>Quebec</td>\n",
       "      <td>Montréal</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8808</td>\n",
       "      <td>2020-04-28</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>Quebec</td>\n",
       "      <td>Lanaudière</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26462</td>\n",
       "      <td>2020-04-16</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>Quebec</td>\n",
       "      <td>Montréal</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24401</td>\n",
       "      <td>2020-04-26</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>Quebec</td>\n",
       "      <td>Montréal</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15003</td>\n",
       "      <td>2020-04-12</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Peel</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23481</td>\n",
       "      <td>2020-04-26</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>Quebec</td>\n",
       "      <td>Montréal</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             date           age province      region           sex  travel  \\\n",
       "12267  2020-04-21  Not Reported  Alberta       South  Not Reported       0   \n",
       "17134  2020-04-20  Not Reported  Alberta     Central  Not Reported       0   \n",
       "5876   2020-03-31  Not Reported   Quebec    Montréal  Not Reported       0   \n",
       "21351  2020-03-18  Not Reported       BC      Fraser  Not Reported       0   \n",
       "50942  2020-04-02  Not Reported   Quebec    Montréal  Not Reported       0   \n",
       "8808   2020-04-28  Not Reported   Quebec  Lanaudière  Not Reported       0   \n",
       "26462  2020-04-16  Not Reported   Quebec    Montréal  Not Reported       0   \n",
       "24401  2020-04-26  Not Reported   Quebec    Montréal  Not Reported       0   \n",
       "15003  2020-04-12  Not Reported  Ontario        Peel  Not Reported       0   \n",
       "23481  2020-04-26  Not Reported   Quebec    Montréal  Not Reported       0   \n",
       "\n",
       "      travelh  \n",
       "12267     NaN  \n",
       "17134     NaN  \n",
       "5876      NaN  \n",
       "21351     NaN  \n",
       "50942     NaN  \n",
       "8808      NaN  \n",
       "26462     NaN  \n",
       "24401     NaN  \n",
       "15003     NaN  \n",
       "23481     NaN  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_data.sample(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id         25493.418622\n",
       "case_id    25491.191943\n",
       "travel         0.011611\n",
       "dtype: float64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_data.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\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>id</th>\n",
       "      <th>date</th>\n",
       "      <th>age</th>\n",
       "      <th>case_id</th>\n",
       "      <th>country</th>\n",
       "      <th>province</th>\n",
       "      <th>region</th>\n",
       "      <th>sex</th>\n",
       "      <th>travel</th>\n",
       "      <th>travelh</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>34996</td>\n",
       "      <td>46989</td>\n",
       "      <td>2020-04-26</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>46986</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Quebec</td>\n",
       "      <td>Montréal</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25482</td>\n",
       "      <td>47561</td>\n",
       "      <td>2020-04-26</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>47558</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Peel</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20490</td>\n",
       "      <td>46347</td>\n",
       "      <td>2020-04-26</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>46344</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>South</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21070</td>\n",
       "      <td>46812</td>\n",
       "      <td>2020-04-26</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>46809</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Quebec</td>\n",
       "      <td>Laval</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24861</td>\n",
       "      <td>47478</td>\n",
       "      <td>2020-04-26</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>47475</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Peel</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20819</td>\n",
       "      <td>46608</td>\n",
       "      <td>2020-04-26</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>46605</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Quebec</td>\n",
       "      <td>Laurentides</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24769</td>\n",
       "      <td>47447</td>\n",
       "      <td>2020-04-26</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>47444</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Hamilton</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24593</td>\n",
       "      <td>47413</td>\n",
       "      <td>2020-04-26</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>47410</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Durham</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25258</td>\n",
       "      <td>47541</td>\n",
       "      <td>2020-04-26</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>47538</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Peel</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>34993</td>\n",
       "      <td>46971</td>\n",
       "      <td>2020-04-26</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>46968</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Quebec</td>\n",
       "      <td>Montréal</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          id        date           age  case_id country province       region  \\\n",
       "34996  46989  2020-04-26  Not Reported    46986  Canada   Quebec     Montréal   \n",
       "25482  47561  2020-04-26  Not Reported    47558  Canada  Ontario         Peel   \n",
       "20490  46347  2020-04-26  Not Reported    46344  Canada  Alberta        South   \n",
       "21070  46812  2020-04-26  Not Reported    46809  Canada   Quebec        Laval   \n",
       "24861  47478  2020-04-26  Not Reported    47475  Canada  Ontario         Peel   \n",
       "20819  46608  2020-04-26  Not Reported    46605  Canada   Quebec  Laurentides   \n",
       "24769  47447  2020-04-26  Not Reported    47444  Canada  Ontario     Hamilton   \n",
       "24593  47413  2020-04-26  Not Reported    47410  Canada  Ontario       Durham   \n",
       "25258  47541  2020-04-26  Not Reported    47538  Canada  Ontario         Peel   \n",
       "34993  46971  2020-04-26  Not Reported    46968  Canada   Quebec     Montréal   \n",
       "\n",
       "                sex  travel travelh  \n",
       "34996  Not Reported   False     NaN  \n",
       "25482  Not Reported   False     NaN  \n",
       "20490  Not Reported   False     NaN  \n",
       "21070  Not Reported   False     NaN  \n",
       "24861  Not Reported   False     NaN  \n",
       "20819  Not Reported   False     NaN  \n",
       "24769  Not Reported   False     NaN  \n",
       "24593  Not Reported   False     NaN  \n",
       "25258  Not Reported   False     NaN  \n",
       "34993  Not Reported   False     NaN  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_data[canada_data[\"date\"].apply(lambda date: date==\"2020-04-26\")].sample(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    50392\n",
       "1      592\n",
       "Name: travel, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_data[\"travel\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "canada_data[\"travel\"]=canada_data[\"travel\"].map(bool)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "mean    2.549119e+04\n",
       "sum     1.299643e+09\n",
       "amax    5.098200e+04\n",
       "amin    1.000000e+00\n",
       "Name: case_id, dtype: float64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_data[\"case_id\"].agg([np.mean, np.sum, np.max, np.min])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>travel</th>\n",
       "      <th>False</th>\n",
       "      <th>True</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>province</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>Alberta</td>\n",
       "      <td>4826</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>BC</td>\n",
       "      <td>2019</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Manitoba</td>\n",
       "      <td>258</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>NL</td>\n",
       "      <td>249</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>NWT</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>New Brunswick</td>\n",
       "      <td>95</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Nova Scotia</td>\n",
       "      <td>897</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Ontario</td>\n",
       "      <td>15952</td>\n",
       "      <td>385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>PEI</td>\n",
       "      <td>1</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Quebec</td>\n",
       "      <td>25742</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Repatriated</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Saskatchewan</td>\n",
       "      <td>345</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Yukon</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "travel         False  True \n",
       "province                   \n",
       "Alberta         4826     24\n",
       "BC              2019     34\n",
       "Manitoba         258     14\n",
       "NL               249      9\n",
       "NWT                2      3\n",
       "New Brunswick     95     23\n",
       "Nova Scotia      897     18\n",
       "Ontario        15952    385\n",
       "PEI                1     26\n",
       "Quebec         25742     17\n",
       "Repatriated        0     13\n",
       "Saskatchewan     345     21\n",
       "Yukon              6      5"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(canada_data[\"province\"], canada_data[\"travel\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20cfd739c48>"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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miEiSuhkikqRuhogkqZshIknqZohIkroZIpKkboaIJKmbISJJ6maISJK6GSKSpG6GiCSpmyEiSepmiEiSuhkikqRuhogkqZshIknqZohIkroZIpKkboaIJKmbISJJ6maISJK6GSKSpG6GiCSpmyEiSepmiEiSuq1c7AEcqySbgLcBK4A/qaq3LPKQpEXzqTd952IPQSegb/mN+wbb95I+E0myAngHcBGwHrg8yfrFHZUkLR9LOkSA84HZqnqkqr4A3ARcvMhjkqRlY6lfzloNPDq2Pge85OBOSbYAW9rqfyZ5eApjWw7OBD692IM4EeT3Ny/2EHQo/z7nXZNj3cPzD9ew1ENk0r9MHVKouh64fvjhLC9JZqpqw2KPQ5rEv8/pWOqXs+aAs8fW1wCPLdJYJGnZWeohshtYl+ScJCcDlwE7FnlMkrRsLOnLWVV1IMkbgJ2MbvHdWlUPLPKwlhMvEepE5t/nFKTqkCkESZIWZKlfzpIkLSJDRJLUzRBRlySbkjycZDbJ1Ys9Hmlekq1J9ia5f7HHshwYInrGfNyMTnA3ApsWexDLhSGiHj5uRiesqvo7YP9ij2O5METUY9LjZlYv0lgkLSJDRD0W9LgZSV/9DBH18HEzkgBDRH183IwkwBBRh6o6AMw/buYh4GYfN6MTRZK/AO4Avi3JXJIrF3tMX8187IkkqZtnIpKkboaIJKmbISJJ6maISJK6GSKSpG6GiHScJTktyc9O4XM+meTMoT9HOhJDRDr+TgMOCZH29GPpq4ohIh1/bwG+Nck9SXYn+WiSPwfuA0jygSR3J3kgyZZWe32S353fQZKfTPL2tvzaJHe1/f2xYaQTiV82lI6zJGuBD1bVuUleBvw1cG5VfaK1n1FV+5OcwugRMt/P6D90d1TVC1qfDwHXAp8Bfhd4VVX9b5J3AndW1fYknwQ2VNWnp3qA0piViz0AaRm4az5Amp9P8mNt+WxgXVXdmeSRJBuBPcC3Af8AXAWcB+xOAnAKsHd6Q5eOzBCRhvdf8wvtzOQHge+tqs8luR14Vmt+D/Aa4F+A91dVZZQc26rqjdMdsrQwzolIx9/TwLMP0/Yc4MkWIN8ObBxrex9wCXA5o0ABuA14dZKzYHQpLMnzhxm29Mx5JiIdZ1X1mST/kOR+4L+BJ8aa/wb4mST3Ag8Dd45t92SSB4H1VXVXqz2Y5NeBDyc5CfhfRpe4/m1KhyMdkRPrkqRuXs6SJHUzRCRJ3QwRSVI3Q0SS1M0QkSR1M0QkSd0MEUlSt/8HdqfTas0G/qsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x= \"travel\", data= canada_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20c82c297c8>"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, axes = plt.subplots(nrows=1, ncols=2, figsize=(12, 4))\n",
    "sns.countplot(x=\"province\", data= canada_data, ax= axes[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>date</th>\n",
       "      <th>age</th>\n",
       "      <th>province</th>\n",
       "      <th>region</th>\n",
       "      <th>sex</th>\n",
       "      <th>travel</th>\n",
       "      <th>travelh</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>2020-03-26</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>Saskatchewan</td>\n",
       "      <td>Saskatoon</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2020-03-23</td>\n",
       "      <td>40-49</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>York</td>\n",
       "      <td>Male</td>\n",
       "      <td>1</td>\n",
       "      <td>Costa Rica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>2020-04-07</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>2020-04-07</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>2020-03-29</td>\n",
       "      <td>60-69</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Algoma</td>\n",
       "      <td>Female</td>\n",
       "      <td>1</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>40255</td>\n",
       "      <td>2020-04-13</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>NL</td>\n",
       "      <td>Western</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>40265</td>\n",
       "      <td>2020-04-13</td>\n",
       "      <td>50-59</td>\n",
       "      <td>New Brunswick</td>\n",
       "      <td>Zone 5 (Campbellton area)</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>47949</td>\n",
       "      <td>2020-03-27</td>\n",
       "      <td>20-29</td>\n",
       "      <td>New Brunswick</td>\n",
       "      <td>Zone 4 (Edmundston area)</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>47950</td>\n",
       "      <td>2020-03-27</td>\n",
       "      <td>30-39</td>\n",
       "      <td>New Brunswick</td>\n",
       "      <td>Zone 4 (Edmundston area)</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>47964</td>\n",
       "      <td>2020-03-27</td>\n",
       "      <td>20-29</td>\n",
       "      <td>New Brunswick</td>\n",
       "      <td>Zone 5 (Campbellton area)</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>421 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             date           age       province                     region  \\\n",
       "0      2020-03-26  Not Reported   Saskatchewan                  Saskatoon   \n",
       "1      2020-03-23         40-49        Ontario                       York   \n",
       "2      2020-04-07  Not Reported        Ontario                    Toronto   \n",
       "3      2020-04-07  Not Reported        Ontario                    Toronto   \n",
       "4      2020-03-29         60-69        Ontario                     Algoma   \n",
       "...           ...           ...            ...                        ...   \n",
       "40255  2020-04-13  Not Reported             NL                    Western   \n",
       "40265  2020-04-13         50-59  New Brunswick  Zone 5 (Campbellton area)   \n",
       "47949  2020-03-27         20-29  New Brunswick   Zone 4 (Edmundston area)   \n",
       "47950  2020-03-27         30-39  New Brunswick   Zone 4 (Edmundston area)   \n",
       "47964  2020-03-27         20-29  New Brunswick  Zone 5 (Campbellton area)   \n",
       "\n",
       "                sex  travel        travelh  \n",
       "0      Not Reported       0            NaN  \n",
       "1              Male       1     Costa Rica  \n",
       "2      Not Reported       0            NaN  \n",
       "3      Not Reported       0            NaN  \n",
       "4            Female       1  United States  \n",
       "...             ...     ...            ...  \n",
       "40255  Not Reported       0            NaN  \n",
       "40265  Not Reported       0            NaN  \n",
       "47949  Not Reported       0            NaN  \n",
       "47950  Not Reported       0            NaN  \n",
       "47964  Not Reported       0            NaN  \n",
       "\n",
       "[421 rows x 7 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_data.groupby(\"region\").head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>age</th>\n",
       "      <th>province</th>\n",
       "      <th>region</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>48606</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>Calgary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18266</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>Calgary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22844</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>Calgary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18265</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>Calgary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6237</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>Calgary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3012</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>Yukon</td>\n",
       "      <td>Yukon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17186</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>Yukon</td>\n",
       "      <td>Yukon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1845</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>Yukon</td>\n",
       "      <td>Yukon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16824</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>Yukon</td>\n",
       "      <td>Yukon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24586</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>Yukon</td>\n",
       "      <td>Yukon</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>50984 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                age province   region\n",
       "48606  Not Reported  Alberta  Calgary\n",
       "18266  Not Reported  Alberta  Calgary\n",
       "22844  Not Reported  Alberta  Calgary\n",
       "18265  Not Reported  Alberta  Calgary\n",
       "6237   Not Reported  Alberta  Calgary\n",
       "...             ...      ...      ...\n",
       "3012   Not Reported    Yukon    Yukon\n",
       "17186  Not Reported    Yukon    Yukon\n",
       "1845   Not Reported    Yukon    Yukon\n",
       "16824  Not Reported    Yukon    Yukon\n",
       "24586  Not Reported    Yukon    Yukon\n",
       "\n",
       "[50984 rows x 3 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_data[[\"age\",\"province\",\"region\"]].sort_values(by=\"province\", ascending=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Quebec           25759\n",
       "Ontario          16337\n",
       "Alberta           4850\n",
       "BC                2053\n",
       "Nova Scotia        915\n",
       "Saskatchewan       366\n",
       "Manitoba           272\n",
       "NL                 258\n",
       "New Brunswick      118\n",
       "PEI                 27\n",
       "Repatriated         13\n",
       "Yukon               11\n",
       "NWT                  5\n",
       "Name: province, dtype: int64"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_data['province'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "canada_case_count= pd.read_csv('Documents/programming/data/covid19-analysis/canada-cumulative-case-count-by-new-hybrid-regional-health-boundaries.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(6624, 36)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_case_count.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['objectid', 'hr_uid', 'province', 'engname', 'frename', 'casecount',\n",
       "       'deaths', 'recovered', 'tests', 'totalpop2019', 'pop0to4_2019',\n",
       "       'pop5to9_2019', 'pop10to14_2019', 'pop15to19_2019', 'pop20to24_2019',\n",
       "       'pop25to29_2019', 'pop30to34_2019', 'pop35to39_2019', 'pop40to44_2019',\n",
       "       'pop45to49_2019', 'pop50to54_2019', 'pop55to59_2019', 'pop60to64_2019',\n",
       "       'pop65to69_2019', 'pop70to74_2019', 'pop75to79_2019', 'pop80to84_2019',\n",
       "       'pop85older', 'averageage_2019', 'medianage_2019', 'shape_area',\n",
       "       'shape_length', 'last_updated', 'sourceurl', 'globalid',\n",
       "       'retrieved_at'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_case_count.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFC0E3B48>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFBE73C48>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFC2CAD48>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFC303E08>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFC66CF08>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFC6AA088>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFC6E1108>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFC719208>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFC720DC8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFC757FC8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFC7C4548>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFC7FD608>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFC834748>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFC86E848>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFC8A8948>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFC8E2A88>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFC91AB88>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFC952C08>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFC989D48>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFC9C3F08>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "coll= ['pop0to4_2019',\n",
    "       'pop5to9_2019', 'pop10to14_2019', 'pop15to19_2019', 'pop20to24_2019',\n",
    "       'pop25to29_2019', 'pop30to34_2019', 'pop35to39_2019', 'pop40to44_2019',\n",
    "       'pop45to49_2019', 'pop50to54_2019', 'pop55to59_2019', 'pop60to64_2019',\n",
    "       'pop65to69_2019', 'pop70to74_2019', 'pop75to79_2019', 'pop80to84_2019',\n",
    "       'pop85older']\n",
    "canada_case_count[coll].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 6624 entries, 0 to 6623\n",
      "Data columns (total 36 columns):\n",
      "objectid           6624 non-null int64\n",
      "hr_uid             6624 non-null int64\n",
      "province           6624 non-null object\n",
      "engname            6624 non-null object\n",
      "frename            6624 non-null object\n",
      "casecount          6624 non-null int64\n",
      "deaths             4845 non-null float64\n",
      "recovered          3487 non-null float64\n",
      "tests              3531 non-null float64\n",
      "totalpop2019       6624 non-null int64\n",
      "pop0to4_2019       6624 non-null int64\n",
      "pop5to9_2019       6624 non-null int64\n",
      "pop10to14_2019     6624 non-null int64\n",
      "pop15to19_2019     6624 non-null int64\n",
      "pop20to24_2019     6624 non-null int64\n",
      "pop25to29_2019     6624 non-null int64\n",
      "pop30to34_2019     6624 non-null int64\n",
      "pop35to39_2019     6624 non-null int64\n",
      "pop40to44_2019     6624 non-null int64\n",
      "pop45to49_2019     6624 non-null int64\n",
      "pop50to54_2019     6624 non-null int64\n",
      "pop55to59_2019     6624 non-null int64\n",
      "pop60to64_2019     6624 non-null int64\n",
      "pop65to69_2019     6624 non-null int64\n",
      "pop70to74_2019     6624 non-null int64\n",
      "pop75to79_2019     6624 non-null int64\n",
      "pop80to84_2019     6624 non-null int64\n",
      "pop85older         6624 non-null int64\n",
      "averageage_2019    6624 non-null float64\n",
      "medianage_2019     6624 non-null float64\n",
      "shape_area         6624 non-null float64\n",
      "shape_length       6624 non-null float64\n",
      "last_updated       6624 non-null int64\n",
      "sourceurl          6624 non-null object\n",
      "globalid           6624 non-null object\n",
      "retrieved_at       6624 non-null object\n",
      "dtypes: float64(7), int64(23), object(6)\n",
      "memory usage: 1.8+ MB\n"
     ]
    }
   ],
   "source": [
    "canada_case_count.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>objectid</th>\n",
       "      <th>hr_uid</th>\n",
       "      <th>casecount</th>\n",
       "      <th>deaths</th>\n",
       "      <th>recovered</th>\n",
       "      <th>tests</th>\n",
       "      <th>totalpop2019</th>\n",
       "      <th>pop0to4_2019</th>\n",
       "      <th>pop5to9_2019</th>\n",
       "      <th>pop10to14_2019</th>\n",
       "      <th>...</th>\n",
       "      <th>pop65to69_2019</th>\n",
       "      <th>pop70to74_2019</th>\n",
       "      <th>pop75to79_2019</th>\n",
       "      <th>pop80to84_2019</th>\n",
       "      <th>pop85older</th>\n",
       "      <th>averageage_2019</th>\n",
       "      <th>medianage_2019</th>\n",
       "      <th>shape_area</th>\n",
       "      <th>shape_length</th>\n",
       "      <th>last_updated</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>6624.000000</td>\n",
       "      <td>6624.000000</td>\n",
       "      <td>6624.000000</td>\n",
       "      <td>4845.000000</td>\n",
       "      <td>3487.000000</td>\n",
       "      <td>3531.000000</td>\n",
       "      <td>6.624000e+03</td>\n",
       "      <td>6624.000000</td>\n",
       "      <td>6624.000000</td>\n",
       "      <td>6624.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>6624.000000</td>\n",
       "      <td>6624.000000</td>\n",
       "      <td>6624.000000</td>\n",
       "      <td>6624.000000</td>\n",
       "      <td>6624.000000</td>\n",
       "      <td>6624.000000</td>\n",
       "      <td>6624.000000</td>\n",
       "      <td>6.624000e+03</td>\n",
       "      <td>6.624000e+03</td>\n",
       "      <td>6.624000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mean</td>\n",
       "      <td>56.445652</td>\n",
       "      <td>2765.760870</td>\n",
       "      <td>356.983696</td>\n",
       "      <td>20.708772</td>\n",
       "      <td>93.818469</td>\n",
       "      <td>3933.708298</td>\n",
       "      <td>3.979893e+05</td>\n",
       "      <td>20992.684783</td>\n",
       "      <td>21398.760870</td>\n",
       "      <td>21356.695652</td>\n",
       "      <td>...</td>\n",
       "      <td>22512.891304</td>\n",
       "      <td>18593.956522</td>\n",
       "      <td>13194.663043</td>\n",
       "      <td>8988.826087</td>\n",
       "      <td>8967.445652</td>\n",
       "      <td>41.836413</td>\n",
       "      <td>42.539674</td>\n",
       "      <td>5.485916e+11</td>\n",
       "      <td>7.058358e+06</td>\n",
       "      <td>1.587116e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>std</td>\n",
       "      <td>32.876869</td>\n",
       "      <td>1436.352351</td>\n",
       "      <td>998.996080</td>\n",
       "      <td>71.020167</td>\n",
       "      <td>178.322680</td>\n",
       "      <td>7345.926522</td>\n",
       "      <td>4.996018e+05</td>\n",
       "      <td>26367.640560</td>\n",
       "      <td>25833.459478</td>\n",
       "      <td>25417.825171</td>\n",
       "      <td>...</td>\n",
       "      <td>25453.931861</td>\n",
       "      <td>20955.087035</td>\n",
       "      <td>15628.343134</td>\n",
       "      <td>11151.400786</td>\n",
       "      <td>11326.500798</td>\n",
       "      <td>4.026469</td>\n",
       "      <td>5.851991</td>\n",
       "      <td>2.519062e+12</td>\n",
       "      <td>3.300618e+07</td>\n",
       "      <td>5.973174e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>min</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>471.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>178.000000</td>\n",
       "      <td>1.384900e+04</td>\n",
       "      <td>800.000000</td>\n",
       "      <td>790.000000</td>\n",
       "      <td>800.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>302.000000</td>\n",
       "      <td>182.000000</td>\n",
       "      <td>85.000000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>28.100000</td>\n",
       "      <td>25.100000</td>\n",
       "      <td>5.064297e+08</td>\n",
       "      <td>1.320794e+05</td>\n",
       "      <td>1.586030e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25%</td>\n",
       "      <td>29.750000</td>\n",
       "      <td>1303.750000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>697.000000</td>\n",
       "      <td>1.099395e+05</td>\n",
       "      <td>5745.500000</td>\n",
       "      <td>5823.000000</td>\n",
       "      <td>6013.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>7789.750000</td>\n",
       "      <td>6452.500000</td>\n",
       "      <td>4559.750000</td>\n",
       "      <td>3021.250000</td>\n",
       "      <td>3171.000000</td>\n",
       "      <td>40.075000</td>\n",
       "      <td>39.275000</td>\n",
       "      <td>1.071701e+10</td>\n",
       "      <td>5.952193e+05</td>\n",
       "      <td>1.586627e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50%</td>\n",
       "      <td>53.500000</td>\n",
       "      <td>3526.500000</td>\n",
       "      <td>63.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>36.000000</td>\n",
       "      <td>1571.000000</td>\n",
       "      <td>1.909105e+05</td>\n",
       "      <td>9649.000000</td>\n",
       "      <td>9646.000000</td>\n",
       "      <td>9817.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>12056.500000</td>\n",
       "      <td>10168.500000</td>\n",
       "      <td>7109.500000</td>\n",
       "      <td>4915.000000</td>\n",
       "      <td>4943.000000</td>\n",
       "      <td>42.200000</td>\n",
       "      <td>43.100000</td>\n",
       "      <td>3.422650e+10</td>\n",
       "      <td>1.392877e+06</td>\n",
       "      <td>1.587144e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75%</td>\n",
       "      <td>83.250000</td>\n",
       "      <td>3558.500000</td>\n",
       "      <td>270.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>101.000000</td>\n",
       "      <td>3475.500000</td>\n",
       "      <td>4.824042e+05</td>\n",
       "      <td>25531.500000</td>\n",
       "      <td>26679.750000</td>\n",
       "      <td>26261.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>27561.250000</td>\n",
       "      <td>22861.250000</td>\n",
       "      <td>15946.750000</td>\n",
       "      <td>10626.000000</td>\n",
       "      <td>11421.000000</td>\n",
       "      <td>44.425000</td>\n",
       "      <td>46.375000</td>\n",
       "      <td>1.479078e+11</td>\n",
       "      <td>3.551779e+06</td>\n",
       "      <td>1.587602e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>max</td>\n",
       "      <td>122.000000</td>\n",
       "      <td>6201.000000</td>\n",
       "      <td>12487.000000</td>\n",
       "      <td>1039.000000</td>\n",
       "      <td>2930.000000</td>\n",
       "      <td>59003.000000</td>\n",
       "      <td>2.987513e+06</td>\n",
       "      <td>150465.000000</td>\n",
       "      <td>134471.000000</td>\n",
       "      <td>128262.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>142429.000000</td>\n",
       "      <td>113681.000000</td>\n",
       "      <td>79425.000000</td>\n",
       "      <td>63322.000000</td>\n",
       "      <td>76806.000000</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>53.800000</td>\n",
       "      <td>2.272713e+13</td>\n",
       "      <td>3.117239e+08</td>\n",
       "      <td>1.588169e+12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          objectid       hr_uid     casecount       deaths    recovered  \\\n",
       "count  6624.000000  6624.000000   6624.000000  4845.000000  3487.000000   \n",
       "mean     56.445652  2765.760870    356.983696    20.708772    93.818469   \n",
       "std      32.876869  1436.352351    998.996080    71.020167   178.322680   \n",
       "min       1.000000   471.000000      0.000000     0.000000     1.000000   \n",
       "25%      29.750000  1303.750000     16.000000     0.000000    10.000000   \n",
       "50%      53.500000  3526.500000     63.000000     3.000000    36.000000   \n",
       "75%      83.250000  3558.500000    270.000000    17.000000   101.000000   \n",
       "max     122.000000  6201.000000  12487.000000  1039.000000  2930.000000   \n",
       "\n",
       "              tests  totalpop2019   pop0to4_2019   pop5to9_2019  \\\n",
       "count   3531.000000  6.624000e+03    6624.000000    6624.000000   \n",
       "mean    3933.708298  3.979893e+05   20992.684783   21398.760870   \n",
       "std     7345.926522  4.996018e+05   26367.640560   25833.459478   \n",
       "min      178.000000  1.384900e+04     800.000000     790.000000   \n",
       "25%      697.000000  1.099395e+05    5745.500000    5823.000000   \n",
       "50%     1571.000000  1.909105e+05    9649.000000    9646.000000   \n",
       "75%     3475.500000  4.824042e+05   25531.500000   26679.750000   \n",
       "max    59003.000000  2.987513e+06  150465.000000  134471.000000   \n",
       "\n",
       "       pop10to14_2019  ...  pop65to69_2019  pop70to74_2019  pop75to79_2019  \\\n",
       "count     6624.000000  ...     6624.000000     6624.000000     6624.000000   \n",
       "mean     21356.695652  ...    22512.891304    18593.956522    13194.663043   \n",
       "std      25417.825171  ...    25453.931861    20955.087035    15628.343134   \n",
       "min        800.000000  ...      302.000000      182.000000       85.000000   \n",
       "25%       6013.000000  ...     7789.750000     6452.500000     4559.750000   \n",
       "50%       9817.000000  ...    12056.500000    10168.500000     7109.500000   \n",
       "75%      26261.000000  ...    27561.250000    22861.250000    15946.750000   \n",
       "max     128262.000000  ...   142429.000000   113681.000000    79425.000000   \n",
       "\n",
       "       pop80to84_2019    pop85older  averageage_2019  medianage_2019  \\\n",
       "count     6624.000000   6624.000000      6624.000000     6624.000000   \n",
       "mean      8988.826087   8967.445652        41.836413       42.539674   \n",
       "std      11151.400786  11326.500798         4.026469        5.851991   \n",
       "min         52.000000     28.000000        28.100000       25.100000   \n",
       "25%       3021.250000   3171.000000        40.075000       39.275000   \n",
       "50%       4915.000000   4943.000000        42.200000       43.100000   \n",
       "75%      10626.000000  11421.000000        44.425000       46.375000   \n",
       "max      63322.000000  76806.000000        49.000000       53.800000   \n",
       "\n",
       "         shape_area  shape_length  last_updated  \n",
       "count  6.624000e+03  6.624000e+03  6.624000e+03  \n",
       "mean   5.485916e+11  7.058358e+06  1.587116e+12  \n",
       "std    2.519062e+12  3.300618e+07  5.973174e+08  \n",
       "min    5.064297e+08  1.320794e+05  1.586030e+12  \n",
       "25%    1.071701e+10  5.952193e+05  1.586627e+12  \n",
       "50%    3.422650e+10  1.392877e+06  1.587144e+12  \n",
       "75%    1.479078e+11  3.551779e+06  1.587602e+12  \n",
       "max    2.272713e+13  3.117239e+08  1.588169e+12  \n",
       "\n",
       "[8 rows x 30 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_case_count.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>province</th>\n",
       "      <th>engname</th>\n",
       "      <th>frename</th>\n",
       "      <th>sourceurl</th>\n",
       "      <th>globalid</th>\n",
       "      <th>retrieved_at</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>6624</td>\n",
       "      <td>6624</td>\n",
       "      <td>6624</td>\n",
       "      <td>6624</td>\n",
       "      <td>6624</td>\n",
       "      <td>6624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>unique</td>\n",
       "      <td>13</td>\n",
       "      <td>93</td>\n",
       "      <td>93</td>\n",
       "      <td>47</td>\n",
       "      <td>92</td>\n",
       "      <td>72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>top</td>\n",
       "      <td>ON</td>\n",
       "      <td>Chatham-Kent Health Unit</td>\n",
       "      <td>Zone 1 (région de Moncton)</td>\n",
       "      <td>https://www.quebec.ca/en/health/health-issues/...</td>\n",
       "      <td>b8332908-ad89-44e0-bbd0-86c9e03f369d</td>\n",
       "      <td>2020-04-19 07:15:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>freq</td>\n",
       "      <td>2448</td>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>1296</td>\n",
       "      <td>72</td>\n",
       "      <td>92</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       province                   engname                     frename  \\\n",
       "count      6624                      6624                        6624   \n",
       "unique       13                        93                          93   \n",
       "top          ON  Chatham-Kent Health Unit  Zone 1 (région de Moncton)   \n",
       "freq       2448                        72                          72   \n",
       "\n",
       "                                                sourceurl  \\\n",
       "count                                                6624   \n",
       "unique                                                 47   \n",
       "top     https://www.quebec.ca/en/health/health-issues/...   \n",
       "freq                                                 1296   \n",
       "\n",
       "                                    globalid         retrieved_at  \n",
       "count                                   6624                 6624  \n",
       "unique                                    92                   72  \n",
       "top     b8332908-ad89-44e0-bbd0-86c9e03f369d  2020-04-19 07:15:00  \n",
       "freq                                      72                   92  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_case_count.describe(include=object)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>objectid</th>\n",
       "      <th>hr_uid</th>\n",
       "      <th>province</th>\n",
       "      <th>engname</th>\n",
       "      <th>frename</th>\n",
       "      <th>casecount</th>\n",
       "      <th>deaths</th>\n",
       "      <th>recovered</th>\n",
       "      <th>tests</th>\n",
       "      <th>totalpop2019</th>\n",
       "      <th>...</th>\n",
       "      <th>pop80to84_2019</th>\n",
       "      <th>pop85older</th>\n",
       "      <th>averageage_2019</th>\n",
       "      <th>medianage_2019</th>\n",
       "      <th>shape_area</th>\n",
       "      <th>shape_length</th>\n",
       "      <th>last_updated</th>\n",
       "      <th>sourceurl</th>\n",
       "      <th>globalid</th>\n",
       "      <th>retrieved_at</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>110</td>\n",
       "      <td>25</td>\n",
       "      <td>2402</td>\n",
       "      <td>QC</td>\n",
       "      <td>Région du Saguenay—Lac-Saint-Jean</td>\n",
       "      <td>Région du Saguenay—Lac-Saint-Jean</td>\n",
       "      <td>273</td>\n",
       "      <td>20.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>276281</td>\n",
       "      <td>...</td>\n",
       "      <td>7706</td>\n",
       "      <td>8104</td>\n",
       "      <td>45.1</td>\n",
       "      <td>47.2</td>\n",
       "      <td>2.540617e+11</td>\n",
       "      <td>3.000150e+06</td>\n",
       "      <td>1588100400000</td>\n",
       "      <td>https://www.quebec.ca/en/health/health-issues/...</td>\n",
       "      <td>eac3fc7e-71a2-4c8b-8ef7-adaedd272237</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>111</td>\n",
       "      <td>26</td>\n",
       "      <td>2403</td>\n",
       "      <td>QC</td>\n",
       "      <td>Région de la Capitale-Nationale</td>\n",
       "      <td>Région de la Capitale-Nationale</td>\n",
       "      <td>789</td>\n",
       "      <td>45.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>700684</td>\n",
       "      <td>...</td>\n",
       "      <td>17227</td>\n",
       "      <td>19379</td>\n",
       "      <td>43.3</td>\n",
       "      <td>43.1</td>\n",
       "      <td>4.239543e+10</td>\n",
       "      <td>1.345502e+06</td>\n",
       "      <td>1588100460000</td>\n",
       "      <td>https://www.quebec.ca/en/health/health-issues/...</td>\n",
       "      <td>86c78678-676c-4e27-ba98-e40183335f49</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>112</td>\n",
       "      <td>27</td>\n",
       "      <td>2404</td>\n",
       "      <td>QC</td>\n",
       "      <td>Région de la Mauricie et du Centre-du-Québec</td>\n",
       "      <td>Région de la Mauricie et du Centre-du-Québec</td>\n",
       "      <td>1176</td>\n",
       "      <td>93.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>518043</td>\n",
       "      <td>...</td>\n",
       "      <td>14468</td>\n",
       "      <td>16673</td>\n",
       "      <td>45.2</td>\n",
       "      <td>47.1</td>\n",
       "      <td>1.034139e+11</td>\n",
       "      <td>2.210870e+06</td>\n",
       "      <td>1588100460000</td>\n",
       "      <td>https://www.quebec.ca/en/health/health-issues/...</td>\n",
       "      <td>e4efb474-f888-4d6e-89fa-6983b1854141</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>113</td>\n",
       "      <td>28</td>\n",
       "      <td>2405</td>\n",
       "      <td>QC</td>\n",
       "      <td>Région de l'Estrie</td>\n",
       "      <td>Région de l'Estrie</td>\n",
       "      <td>826</td>\n",
       "      <td>25.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>513429</td>\n",
       "      <td>...</td>\n",
       "      <td>12873</td>\n",
       "      <td>13748</td>\n",
       "      <td>43.8</td>\n",
       "      <td>44.9</td>\n",
       "      <td>2.608167e+10</td>\n",
       "      <td>1.099065e+06</td>\n",
       "      <td>1588100520000</td>\n",
       "      <td>https://www.quebec.ca/en/health/health-issues/...</td>\n",
       "      <td>200a9a1f-cb75-41d6-ac40-2e77ebde21ea</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>114</td>\n",
       "      <td>29</td>\n",
       "      <td>2406</td>\n",
       "      <td>QC</td>\n",
       "      <td>Région de Montréal</td>\n",
       "      <td>Région de Montréal</td>\n",
       "      <td>12487</td>\n",
       "      <td>1039.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1856818</td>\n",
       "      <td>...</td>\n",
       "      <td>40649</td>\n",
       "      <td>50237</td>\n",
       "      <td>40.6</td>\n",
       "      <td>39.0</td>\n",
       "      <td>9.562571e+08</td>\n",
       "      <td>2.478708e+05</td>\n",
       "      <td>1588100520000</td>\n",
       "      <td>https://www.quebec.ca/en/health/health-issues/...</td>\n",
       "      <td>8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>115</td>\n",
       "      <td>30</td>\n",
       "      <td>2407</td>\n",
       "      <td>QC</td>\n",
       "      <td>Région de l'Outaouais</td>\n",
       "      <td>Région de l'Outaouais</td>\n",
       "      <td>270</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>409421</td>\n",
       "      <td>...</td>\n",
       "      <td>7501</td>\n",
       "      <td>7160</td>\n",
       "      <td>41.4</td>\n",
       "      <td>42.0</td>\n",
       "      <td>7.192139e+10</td>\n",
       "      <td>2.091063e+06</td>\n",
       "      <td>1588100580000</td>\n",
       "      <td>https://www.quebec.ca/en/health/health-issues/...</td>\n",
       "      <td>889faae9-4e01-437d-a948-5e32d396b03b</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>116</td>\n",
       "      <td>31</td>\n",
       "      <td>2408</td>\n",
       "      <td>QC</td>\n",
       "      <td>Région de l'Abitibi-Témiscamingue</td>\n",
       "      <td>Région de l'Abitibi-Témiscamingue</td>\n",
       "      <td>149</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>148529</td>\n",
       "      <td>...</td>\n",
       "      <td>3257</td>\n",
       "      <td>3363</td>\n",
       "      <td>42.6</td>\n",
       "      <td>43.6</td>\n",
       "      <td>1.440284e+11</td>\n",
       "      <td>2.022227e+06</td>\n",
       "      <td>1588105680000</td>\n",
       "      <td>https://www.quebec.ca/en/health/health-issues/...</td>\n",
       "      <td>cef3a9ff-5524-452d-bca9-43627fdf0611</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>117</td>\n",
       "      <td>32</td>\n",
       "      <td>2409</td>\n",
       "      <td>QC</td>\n",
       "      <td>Région de la Côte-Nord</td>\n",
       "      <td>Région de la Côte-Nord</td>\n",
       "      <td>114</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>87447</td>\n",
       "      <td>...</td>\n",
       "      <td>2162</td>\n",
       "      <td>2027</td>\n",
       "      <td>43.7</td>\n",
       "      <td>45.7</td>\n",
       "      <td>6.943192e+11</td>\n",
       "      <td>1.066786e+07</td>\n",
       "      <td>1588105680000</td>\n",
       "      <td>https://www.quebec.ca/en/health/health-issues/...</td>\n",
       "      <td>6f999911-9627-40ef-92aa-cd7fc9106c7a</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>118</td>\n",
       "      <td>33</td>\n",
       "      <td>2410</td>\n",
       "      <td>QC</td>\n",
       "      <td>Région du Nord-du-Québec</td>\n",
       "      <td>Région du Nord-du-Québec</td>\n",
       "      <td>7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14642</td>\n",
       "      <td>...</td>\n",
       "      <td>273</td>\n",
       "      <td>171</td>\n",
       "      <td>41.5</td>\n",
       "      <td>42.6</td>\n",
       "      <td>9.118141e+11</td>\n",
       "      <td>7.393913e+06</td>\n",
       "      <td>1588102560000</td>\n",
       "      <td>https://www.quebec.ca/en/health/health-issues/...</td>\n",
       "      <td>17f34b76-8177-4eb1-a35b-e93ec778afc1</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>119</td>\n",
       "      <td>34</td>\n",
       "      <td>3546</td>\n",
       "      <td>ON</td>\n",
       "      <td>Niagara Regional Area Health Unit</td>\n",
       "      <td>Circonscription sanitaire régionale de Niagara</td>\n",
       "      <td>472</td>\n",
       "      <td>42.0</td>\n",
       "      <td>204.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>450816</td>\n",
       "      <td>...</td>\n",
       "      <td>12668</td>\n",
       "      <td>14601</td>\n",
       "      <td>44.2</td>\n",
       "      <td>45.7</td>\n",
       "      <td>3.545058e+09</td>\n",
       "      <td>3.189421e+05</td>\n",
       "      <td>1588109280000</td>\n",
       "      <td>https://www.niagararegion.ca/health/covid-19/d...</td>\n",
       "      <td>85032ec9-5a18-4a1a-8ca6-d21acefcd298</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>120</td>\n",
       "      <td>35</td>\n",
       "      <td>3547</td>\n",
       "      <td>ON</td>\n",
       "      <td>North Bay Parry Sound District Health Unit</td>\n",
       "      <td>Circonscription sanitaire du district de North...</td>\n",
       "      <td>16</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>1636.0</td>\n",
       "      <td>128804</td>\n",
       "      <td>...</td>\n",
       "      <td>3881</td>\n",
       "      <td>3671</td>\n",
       "      <td>45.4</td>\n",
       "      <td>48.1</td>\n",
       "      <td>3.951683e+10</td>\n",
       "      <td>1.806803e+06</td>\n",
       "      <td>1588109340000</td>\n",
       "      <td>https://www.myhealthunit.ca/en/health-topics/c...</td>\n",
       "      <td>d8c2dedb-a9a7-4b62-9969-a6faaa1980a6</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>121</td>\n",
       "      <td>36</td>\n",
       "      <td>3549</td>\n",
       "      <td>ON</td>\n",
       "      <td>Northwestern Health Unit</td>\n",
       "      <td>Circonscription sanitaire du Nord-Ouest</td>\n",
       "      <td>16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.0</td>\n",
       "      <td>1349.0</td>\n",
       "      <td>74771</td>\n",
       "      <td>...</td>\n",
       "      <td>1521</td>\n",
       "      <td>1509</td>\n",
       "      <td>39.5</td>\n",
       "      <td>38.7</td>\n",
       "      <td>5.261314e+11</td>\n",
       "      <td>3.773241e+06</td>\n",
       "      <td>1588083060000</td>\n",
       "      <td>https://www.nwhu.on.ca/covid19/Pages/home.aspx</td>\n",
       "      <td>abd0444e-e2a1-497c-8a75-e5b5762f0baa</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>122</td>\n",
       "      <td>37</td>\n",
       "      <td>3551</td>\n",
       "      <td>ON</td>\n",
       "      <td>City of Ottawa Health Unit</td>\n",
       "      <td>Circonscription sanitaire de la ville d'Ottawa</td>\n",
       "      <td>1221</td>\n",
       "      <td>71.0</td>\n",
       "      <td>529.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1019693</td>\n",
       "      <td>...</td>\n",
       "      <td>19340</td>\n",
       "      <td>20805</td>\n",
       "      <td>40.4</td>\n",
       "      <td>39.2</td>\n",
       "      <td>5.843672e+09</td>\n",
       "      <td>3.882171e+05</td>\n",
       "      <td>1588109460000</td>\n",
       "      <td>https://www.ottawapublichealth.ca/en/public-he...</td>\n",
       "      <td>f46b61ab-19e1-4051-946e-32002768ddd0</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>123</td>\n",
       "      <td>38</td>\n",
       "      <td>3553</td>\n",
       "      <td>ON</td>\n",
       "      <td>Peel Regional Health Unit</td>\n",
       "      <td>Circonscription sanitaire régionale de Peel</td>\n",
       "      <td>2358</td>\n",
       "      <td>89.0</td>\n",
       "      <td>242.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1553076</td>\n",
       "      <td>...</td>\n",
       "      <td>24940</td>\n",
       "      <td>21848</td>\n",
       "      <td>39.0</td>\n",
       "      <td>38.2</td>\n",
       "      <td>2.424380e+09</td>\n",
       "      <td>2.362829e+05</td>\n",
       "      <td>1588109460000</td>\n",
       "      <td>http://www.peelregion.ca/coronavirus/#cases</td>\n",
       "      <td>58190c56-92ca-4e4e-ad24-fe885c550a82</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>124</td>\n",
       "      <td>40</td>\n",
       "      <td>3555</td>\n",
       "      <td>ON</td>\n",
       "      <td>Peterborough County–City Health Unit</td>\n",
       "      <td>Circonscription sanitaire du comté et de la ci...</td>\n",
       "      <td>86</td>\n",
       "      <td>2.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>3713.0</td>\n",
       "      <td>144237</td>\n",
       "      <td>...</td>\n",
       "      <td>4272</td>\n",
       "      <td>4900</td>\n",
       "      <td>44.8</td>\n",
       "      <td>46.2</td>\n",
       "      <td>8.292255e+09</td>\n",
       "      <td>4.135967e+05</td>\n",
       "      <td>1588109520000</td>\n",
       "      <td>https://www.peterboroughpublichealth.ca/your-h...</td>\n",
       "      <td>aa3f708b-2039-4eb3-992f-4df701806483</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>125</td>\n",
       "      <td>41</td>\n",
       "      <td>3556</td>\n",
       "      <td>ON</td>\n",
       "      <td>Porcupine Health Unit</td>\n",
       "      <td>Circonscription sanitaire de Porcupine</td>\n",
       "      <td>59</td>\n",
       "      <td>3.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>1789.0</td>\n",
       "      <td>90540</td>\n",
       "      <td>...</td>\n",
       "      <td>2061</td>\n",
       "      <td>1902</td>\n",
       "      <td>42.2</td>\n",
       "      <td>43.5</td>\n",
       "      <td>7.305916e+11</td>\n",
       "      <td>5.377468e+06</td>\n",
       "      <td>1588083000000</td>\n",
       "      <td>http://www.porcupinehu.on.ca/en/your-health/in...</td>\n",
       "      <td>f8661a8f-4d7c-48ac-9007-56b58ef0ac0c</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>126</td>\n",
       "      <td>42</td>\n",
       "      <td>3557</td>\n",
       "      <td>ON</td>\n",
       "      <td>Renfrew County and District Health Unit</td>\n",
       "      <td>Circonscription sanitaire du comté et du distr...</td>\n",
       "      <td>15</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1477.0</td>\n",
       "      <td>106578</td>\n",
       "      <td>...</td>\n",
       "      <td>3063</td>\n",
       "      <td>3129</td>\n",
       "      <td>43.8</td>\n",
       "      <td>45.1</td>\n",
       "      <td>3.377381e+10</td>\n",
       "      <td>1.077930e+06</td>\n",
       "      <td>1588109520000</td>\n",
       "      <td>https://www.rcdhu.com/novel-coronavirus-covid-...</td>\n",
       "      <td>b8332908-ad89-44e0-bbd0-86c9e03f369d</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>127</td>\n",
       "      <td>43</td>\n",
       "      <td>3558</td>\n",
       "      <td>ON</td>\n",
       "      <td>The Eastern Ontario Health Unit</td>\n",
       "      <td>Circonscription sanitaire de l'Est de l'Ontario</td>\n",
       "      <td>91</td>\n",
       "      <td>0.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>1930.0</td>\n",
       "      <td>179454</td>\n",
       "      <td>...</td>\n",
       "      <td>4417</td>\n",
       "      <td>4136</td>\n",
       "      <td>43.5</td>\n",
       "      <td>46.0</td>\n",
       "      <td>1.072138e+10</td>\n",
       "      <td>5.044397e+05</td>\n",
       "      <td>1588109580000</td>\n",
       "      <td>https://eohu.ca/en/my-health/covid-19-status-u...</td>\n",
       "      <td>07381039-5aa9-436c-ad92-e6da548431c8</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>128</td>\n",
       "      <td>44</td>\n",
       "      <td>3560</td>\n",
       "      <td>ON</td>\n",
       "      <td>Simcoe Muskoka District Health Unit</td>\n",
       "      <td>Circonscription sanitaire du district de Simco...</td>\n",
       "      <td>261</td>\n",
       "      <td>15.0</td>\n",
       "      <td>144.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>562142</td>\n",
       "      <td>...</td>\n",
       "      <td>13391</td>\n",
       "      <td>13148</td>\n",
       "      <td>42.6</td>\n",
       "      <td>43.4</td>\n",
       "      <td>1.946062e+10</td>\n",
       "      <td>1.259109e+06</td>\n",
       "      <td>1588109580000</td>\n",
       "      <td>http://www.simcoemuskokahealthstats.org/topics...</td>\n",
       "      <td>124d22ca-7518-421f-a811-e2f0b39fc737</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>129</td>\n",
       "      <td>45</td>\n",
       "      <td>3561</td>\n",
       "      <td>ON</td>\n",
       "      <td>Sudbury and District Health Unit</td>\n",
       "      <td>Circonscription sanitaire de Sudbury et son di...</td>\n",
       "      <td>57</td>\n",
       "      <td>1.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>3466.0</td>\n",
       "      <td>202681</td>\n",
       "      <td>...</td>\n",
       "      <td>5045</td>\n",
       "      <td>4895</td>\n",
       "      <td>43.3</td>\n",
       "      <td>44.4</td>\n",
       "      <td>1.108435e+11</td>\n",
       "      <td>3.609397e+06</td>\n",
       "      <td>1588109640000</td>\n",
       "      <td>https://www.phsd.ca/health-topics-programs/dis...</td>\n",
       "      <td>673afa7b-0155-4739-bf21-d9238048fe08</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>130</td>\n",
       "      <td>46</td>\n",
       "      <td>3562</td>\n",
       "      <td>ON</td>\n",
       "      <td>Thunder Bay District Health Unit</td>\n",
       "      <td>Circonscription sanitaire du district de Thund...</td>\n",
       "      <td>69</td>\n",
       "      <td>1.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>2922.0</td>\n",
       "      <td>154444</td>\n",
       "      <td>...</td>\n",
       "      <td>3865</td>\n",
       "      <td>4158</td>\n",
       "      <td>43.0</td>\n",
       "      <td>43.9</td>\n",
       "      <td>6.682825e+11</td>\n",
       "      <td>8.036945e+06</td>\n",
       "      <td>1588112040000</td>\n",
       "      <td>https://www.tbdhu.com/coronavirus</td>\n",
       "      <td>1be2ba7e-a6da-46fc-92f1-42cc6c0e5824</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>131</td>\n",
       "      <td>47</td>\n",
       "      <td>3563</td>\n",
       "      <td>ON</td>\n",
       "      <td>Timiskaming Health Unit</td>\n",
       "      <td>Circonscription sanitaire de Timiskaming</td>\n",
       "      <td>12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.0</td>\n",
       "      <td>596.0</td>\n",
       "      <td>33389</td>\n",
       "      <td>...</td>\n",
       "      <td>1017</td>\n",
       "      <td>996</td>\n",
       "      <td>45.0</td>\n",
       "      <td>48.1</td>\n",
       "      <td>3.436522e+10</td>\n",
       "      <td>8.894735e+05</td>\n",
       "      <td>1588109640000</td>\n",
       "      <td>https://www.timiskaminghu.com/90484/covid-19#C...</td>\n",
       "      <td>de7e4ccb-d405-4f71-97f4-404bd2aeb305</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>132</td>\n",
       "      <td>48</td>\n",
       "      <td>3565</td>\n",
       "      <td>ON</td>\n",
       "      <td>Waterloo Health Unit</td>\n",
       "      <td>Circonscription sanitaire de Waterloo</td>\n",
       "      <td>709</td>\n",
       "      <td>66.0</td>\n",
       "      <td>269.0</td>\n",
       "      <td>5770.0</td>\n",
       "      <td>571232</td>\n",
       "      <td>...</td>\n",
       "      <td>10527</td>\n",
       "      <td>10697</td>\n",
       "      <td>39.7</td>\n",
       "      <td>38.7</td>\n",
       "      <td>2.630614e+09</td>\n",
       "      <td>2.520853e+05</td>\n",
       "      <td>1588109700000</td>\n",
       "      <td>https://www.regionofwaterloo.ca/en/health-and-...</td>\n",
       "      <td>1657926a-de14-4ec2-a97b-7a8b54622ba4</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>133</td>\n",
       "      <td>49</td>\n",
       "      <td>3566</td>\n",
       "      <td>ON</td>\n",
       "      <td>Wellington-Dufferin-Guelph Health Unit</td>\n",
       "      <td>Circonscription sanitaire de Wellington-Duffer...</td>\n",
       "      <td>270</td>\n",
       "      <td>19.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>304193</td>\n",
       "      <td>...</td>\n",
       "      <td>5986</td>\n",
       "      <td>5987</td>\n",
       "      <td>40.4</td>\n",
       "      <td>40.0</td>\n",
       "      <td>8.073621e+09</td>\n",
       "      <td>5.489423e+05</td>\n",
       "      <td>1588109700000</td>\n",
       "      <td>https://app.powerbi.com/view?r=eyJrIjoiMDE0OGV...</td>\n",
       "      <td>a86fca32-95a4-4234-bfb6-622b12f32c4b</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>134</td>\n",
       "      <td>50</td>\n",
       "      <td>3568</td>\n",
       "      <td>ON</td>\n",
       "      <td>Windsor-Essex County Health Unit</td>\n",
       "      <td>Circonscription sanitaire de Windsor-comté d'E...</td>\n",
       "      <td>581</td>\n",
       "      <td>43.0</td>\n",
       "      <td>159.0</td>\n",
       "      <td>6199.0</td>\n",
       "      <td>348836</td>\n",
       "      <td>...</td>\n",
       "      <td>7744</td>\n",
       "      <td>8152</td>\n",
       "      <td>41.4</td>\n",
       "      <td>42.0</td>\n",
       "      <td>3.389723e+09</td>\n",
       "      <td>3.737460e+05</td>\n",
       "      <td>1588109760000</td>\n",
       "      <td>https://www.wechu.org/cv/local-updates</td>\n",
       "      <td>00a44660-f775-4f73-aac1-d1ec56aaca88</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>135</td>\n",
       "      <td>51</td>\n",
       "      <td>1203</td>\n",
       "      <td>NS</td>\n",
       "      <td>Zone 3 - Eastern</td>\n",
       "      <td>Zone 3 - Eastern</td>\n",
       "      <td>50</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>138177</td>\n",
       "      <td>...</td>\n",
       "      <td>4102</td>\n",
       "      <td>3846</td>\n",
       "      <td>45.8</td>\n",
       "      <td>49.5</td>\n",
       "      <td>3.408778e+10</td>\n",
       "      <td>2.794639e+06</td>\n",
       "      <td>1588098060000</td>\n",
       "      <td>https://novascotia.ca/coronavirus/data/</td>\n",
       "      <td>72b5482f-3f2e-4ae6-a368-a8608b642cac</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>136</td>\n",
       "      <td>52</td>\n",
       "      <td>1204</td>\n",
       "      <td>NS</td>\n",
       "      <td>Zone 4 - Central</td>\n",
       "      <td>Zone 4 - Central</td>\n",
       "      <td>772</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>444740</td>\n",
       "      <td>...</td>\n",
       "      <td>7900</td>\n",
       "      <td>7852</td>\n",
       "      <td>41.2</td>\n",
       "      <td>40.2</td>\n",
       "      <td>1.472536e+10</td>\n",
       "      <td>1.205836e+06</td>\n",
       "      <td>1588098060000</td>\n",
       "      <td>https://novascotia.ca/coronavirus/data/</td>\n",
       "      <td>00786a76-f6cd-403e-8d85-36bf269d87e3</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>137</td>\n",
       "      <td>53</td>\n",
       "      <td>1301</td>\n",
       "      <td>NB</td>\n",
       "      <td>Zone 1 (Moncton area)</td>\n",
       "      <td>Zone 1 (région de Moncton)</td>\n",
       "      <td>23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4305.0</td>\n",
       "      <td>217155</td>\n",
       "      <td>...</td>\n",
       "      <td>4830</td>\n",
       "      <td>5412</td>\n",
       "      <td>43.2</td>\n",
       "      <td>43.9</td>\n",
       "      <td>2.122780e+10</td>\n",
       "      <td>1.103411e+06</td>\n",
       "      <td>1588099440000</td>\n",
       "      <td>https://www2.gnb.ca/content/gnb/en/departments...</td>\n",
       "      <td>3e89b814-c25f-4ffe-b991-3310a3712942</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>138</td>\n",
       "      <td>54</td>\n",
       "      <td>1302</td>\n",
       "      <td>NB</td>\n",
       "      <td>Zone 2 (Saint John area)</td>\n",
       "      <td>Zone 2 (région de Saint John)</td>\n",
       "      <td>26</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2889.0</td>\n",
       "      <td>149412</td>\n",
       "      <td>...</td>\n",
       "      <td>3501</td>\n",
       "      <td>3512</td>\n",
       "      <td>43.1</td>\n",
       "      <td>45.0</td>\n",
       "      <td>2.140013e+10</td>\n",
       "      <td>1.320296e+06</td>\n",
       "      <td>1588099500000</td>\n",
       "      <td>https://www2.gnb.ca/content/gnb/en/departments...</td>\n",
       "      <td>e7557c80-9a79-4846-b929-d76c38bfc046</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>139</td>\n",
       "      <td>55</td>\n",
       "      <td>1303</td>\n",
       "      <td>NB</td>\n",
       "      <td>Zone 3 (Fredericton area)</td>\n",
       "      <td>Zone 3 (région de Fredericton)</td>\n",
       "      <td>47</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3063.0</td>\n",
       "      <td>179137</td>\n",
       "      <td>...</td>\n",
       "      <td>3960</td>\n",
       "      <td>3763</td>\n",
       "      <td>41.9</td>\n",
       "      <td>42.1</td>\n",
       "      <td>5.003797e+10</td>\n",
       "      <td>1.071391e+06</td>\n",
       "      <td>1588099500000</td>\n",
       "      <td>https://www2.gnb.ca/content/gnb/en/departments...</td>\n",
       "      <td>fcfb3f6f-3194-4a02-b131-75718a603c2a</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>140</td>\n",
       "      <td>56</td>\n",
       "      <td>1304</td>\n",
       "      <td>NB</td>\n",
       "      <td>Zone 4 (Edmundston area)</td>\n",
       "      <td>Zone 4 (région d'Edmundston)</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>937.0</td>\n",
       "      <td>45390</td>\n",
       "      <td>...</td>\n",
       "      <td>1235</td>\n",
       "      <td>1169</td>\n",
       "      <td>46.4</td>\n",
       "      <td>50.3</td>\n",
       "      <td>1.709937e+10</td>\n",
       "      <td>7.765637e+05</td>\n",
       "      <td>1588099500000</td>\n",
       "      <td>https://www2.gnb.ca/content/gnb/en/departments...</td>\n",
       "      <td>25d24683-b924-47b0-ab7b-18954554eee9</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>141</td>\n",
       "      <td>57</td>\n",
       "      <td>1305</td>\n",
       "      <td>NB</td>\n",
       "      <td>Zone 5 (Campbellton area)</td>\n",
       "      <td>Zone 5 (région de Campbellton)</td>\n",
       "      <td>12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>553.0</td>\n",
       "      <td>23126</td>\n",
       "      <td>...</td>\n",
       "      <td>780</td>\n",
       "      <td>916</td>\n",
       "      <td>49.0</td>\n",
       "      <td>53.8</td>\n",
       "      <td>1.217174e+10</td>\n",
       "      <td>5.263302e+05</td>\n",
       "      <td>1588100040000</td>\n",
       "      <td>https://www2.gnb.ca/content/gnb/en/departments...</td>\n",
       "      <td>fa760c11-19ce-41e4-8d1c-c2dd92f86bad</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>142</td>\n",
       "      <td>58</td>\n",
       "      <td>1306</td>\n",
       "      <td>NB</td>\n",
       "      <td>Zone 6 (Bathurst area)</td>\n",
       "      <td>Zone 6 (région de Bathurst)</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1163.0</td>\n",
       "      <td>70761</td>\n",
       "      <td>...</td>\n",
       "      <td>2219</td>\n",
       "      <td>2138</td>\n",
       "      <td>48.3</td>\n",
       "      <td>52.7</td>\n",
       "      <td>1.051998e+10</td>\n",
       "      <td>7.731629e+05</td>\n",
       "      <td>1588100160000</td>\n",
       "      <td>https://www2.gnb.ca/content/gnb/en/departments...</td>\n",
       "      <td>9fb436e5-fe1a-4579-8a06-b37ffae3690b</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>143</td>\n",
       "      <td>59</td>\n",
       "      <td>4604</td>\n",
       "      <td>MB</td>\n",
       "      <td>Northern Regional Health Authority</td>\n",
       "      <td>Office régional de la santé du Nord</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>77380</td>\n",
       "      <td>...</td>\n",
       "      <td>544</td>\n",
       "      <td>396</td>\n",
       "      <td>30.7</td>\n",
       "      <td>26.9</td>\n",
       "      <td>1.434341e+12</td>\n",
       "      <td>8.392579e+06</td>\n",
       "      <td>1588103220000</td>\n",
       "      <td>https://www.gov.mb.ca/covid19/updates/data.html</td>\n",
       "      <td>17401c93-4065-4490-bcab-32b920729479</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>144</td>\n",
       "      <td>60</td>\n",
       "      <td>4605</td>\n",
       "      <td>MB</td>\n",
       "      <td>Southern Health—Santé Sud</td>\n",
       "      <td>Southern Health—Santé Sud</td>\n",
       "      <td>31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>205885</td>\n",
       "      <td>...</td>\n",
       "      <td>3518</td>\n",
       "      <td>3626</td>\n",
       "      <td>36.6</td>\n",
       "      <td>34.4</td>\n",
       "      <td>6.524804e+10</td>\n",
       "      <td>1.910979e+06</td>\n",
       "      <td>1588103220000</td>\n",
       "      <td>https://www.gov.mb.ca/covid19/updates/data.html</td>\n",
       "      <td>3eecfb30-34b7-414a-8cff-f5632e9b5448</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>145</td>\n",
       "      <td>68</td>\n",
       "      <td>3570</td>\n",
       "      <td>ON</td>\n",
       "      <td>York Regional Health Unit</td>\n",
       "      <td>Circonscription sanitaire régionale de York</td>\n",
       "      <td>1457</td>\n",
       "      <td>90.0</td>\n",
       "      <td>579.0</td>\n",
       "      <td>4426.0</td>\n",
       "      <td>1200761</td>\n",
       "      <td>...</td>\n",
       "      <td>23393</td>\n",
       "      <td>21585</td>\n",
       "      <td>40.6</td>\n",
       "      <td>40.8</td>\n",
       "      <td>4.064797e+09</td>\n",
       "      <td>3.332101e+05</td>\n",
       "      <td>1588122420000</td>\n",
       "      <td>https://www.york.ca/covid19</td>\n",
       "      <td>c8fff00e-9d45-48b5-b365-e0899d3611df</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>146</td>\n",
       "      <td>69</td>\n",
       "      <td>3575</td>\n",
       "      <td>ON</td>\n",
       "      <td>Southwestern Public Health Unit</td>\n",
       "      <td>Circonscription sanitaire du sud-ouest</td>\n",
       "      <td>59</td>\n",
       "      <td>4.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>2233.0</td>\n",
       "      <td>209238</td>\n",
       "      <td>...</td>\n",
       "      <td>5230</td>\n",
       "      <td>5376</td>\n",
       "      <td>41.7</td>\n",
       "      <td>42.2</td>\n",
       "      <td>7.414612e+09</td>\n",
       "      <td>6.237560e+05</td>\n",
       "      <td>1588109880000</td>\n",
       "      <td>https://www.swpublichealth.ca/partners-and-pro...</td>\n",
       "      <td>e9ea1347-81aa-47a2-850d-a41726e3793c</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>147</td>\n",
       "      <td>70</td>\n",
       "      <td>3595</td>\n",
       "      <td>ON</td>\n",
       "      <td>City of Toronto Health Unit</td>\n",
       "      <td>Circonscription sanitaire de la cité de Toronto</td>\n",
       "      <td>5128</td>\n",
       "      <td>305.0</td>\n",
       "      <td>2930.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2987513</td>\n",
       "      <td>...</td>\n",
       "      <td>63322</td>\n",
       "      <td>76806</td>\n",
       "      <td>40.9</td>\n",
       "      <td>39.3</td>\n",
       "      <td>1.237670e+09</td>\n",
       "      <td>1.966657e+05</td>\n",
       "      <td>1588109940000</td>\n",
       "      <td>https://www.toronto.ca/home/covid-19/media-roo...</td>\n",
       "      <td>8aa96e82-b87b-4239-802e-c687222bebf7</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>148</td>\n",
       "      <td>71</td>\n",
       "      <td>4601</td>\n",
       "      <td>MB</td>\n",
       "      <td>Winnipeg Regional Health Authority</td>\n",
       "      <td>Office régional de la santé de Winnipeg</td>\n",
       "      <td>206</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>787724</td>\n",
       "      <td>...</td>\n",
       "      <td>14603</td>\n",
       "      <td>17524</td>\n",
       "      <td>39.7</td>\n",
       "      <td>38.2</td>\n",
       "      <td>1.637336e+09</td>\n",
       "      <td>2.917499e+05</td>\n",
       "      <td>1588102980000</td>\n",
       "      <td>https://www.gov.mb.ca/covid19/updates/data.html</td>\n",
       "      <td>7ddc61eb-dc45-4cb7-b1f4-1da8abacb4d5</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>149</td>\n",
       "      <td>72</td>\n",
       "      <td>4602</td>\n",
       "      <td>MB</td>\n",
       "      <td>Prairie Mountain Health</td>\n",
       "      <td>Santé de Prairie Mountain</td>\n",
       "      <td>15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>142031</td>\n",
       "      <td>...</td>\n",
       "      <td>3419</td>\n",
       "      <td>3740</td>\n",
       "      <td>40.0</td>\n",
       "      <td>38.5</td>\n",
       "      <td>1.719848e+11</td>\n",
       "      <td>4.055103e+06</td>\n",
       "      <td>1588103040000</td>\n",
       "      <td>https://www.gov.mb.ca/covid19/index.html</td>\n",
       "      <td>361db834-f0ef-4fd3-bd6a-39d5d82bd180</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>40 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     objectid  hr_uid province                                       engname  \\\n",
       "110        25    2402       QC             Région du Saguenay—Lac-Saint-Jean   \n",
       "111        26    2403       QC               Région de la Capitale-Nationale   \n",
       "112        27    2404       QC  Région de la Mauricie et du Centre-du-Québec   \n",
       "113        28    2405       QC                            Région de l'Estrie   \n",
       "114        29    2406       QC                            Région de Montréal   \n",
       "115        30    2407       QC                         Région de l'Outaouais   \n",
       "116        31    2408       QC             Région de l'Abitibi-Témiscamingue   \n",
       "117        32    2409       QC                        Région de la Côte-Nord   \n",
       "118        33    2410       QC                      Région du Nord-du-Québec   \n",
       "119        34    3546       ON             Niagara Regional Area Health Unit   \n",
       "120        35    3547       ON    North Bay Parry Sound District Health Unit   \n",
       "121        36    3549       ON                      Northwestern Health Unit   \n",
       "122        37    3551       ON                    City of Ottawa Health Unit   \n",
       "123        38    3553       ON                     Peel Regional Health Unit   \n",
       "124        40    3555       ON          Peterborough County–City Health Unit   \n",
       "125        41    3556       ON                         Porcupine Health Unit   \n",
       "126        42    3557       ON       Renfrew County and District Health Unit   \n",
       "127        43    3558       ON               The Eastern Ontario Health Unit   \n",
       "128        44    3560       ON           Simcoe Muskoka District Health Unit   \n",
       "129        45    3561       ON              Sudbury and District Health Unit   \n",
       "130        46    3562       ON              Thunder Bay District Health Unit   \n",
       "131        47    3563       ON                       Timiskaming Health Unit   \n",
       "132        48    3565       ON                          Waterloo Health Unit   \n",
       "133        49    3566       ON        Wellington-Dufferin-Guelph Health Unit   \n",
       "134        50    3568       ON              Windsor-Essex County Health Unit   \n",
       "135        51    1203       NS                              Zone 3 - Eastern   \n",
       "136        52    1204       NS                              Zone 4 - Central   \n",
       "137        53    1301       NB                         Zone 1 (Moncton area)   \n",
       "138        54    1302       NB                      Zone 2 (Saint John area)   \n",
       "139        55    1303       NB                     Zone 3 (Fredericton area)   \n",
       "140        56    1304       NB                      Zone 4 (Edmundston area)   \n",
       "141        57    1305       NB                     Zone 5 (Campbellton area)   \n",
       "142        58    1306       NB                        Zone 6 (Bathurst area)   \n",
       "143        59    4604       MB            Northern Regional Health Authority   \n",
       "144        60    4605       MB                     Southern Health—Santé Sud   \n",
       "145        68    3570       ON                     York Regional Health Unit   \n",
       "146        69    3575       ON               Southwestern Public Health Unit   \n",
       "147        70    3595       ON                   City of Toronto Health Unit   \n",
       "148        71    4601       MB            Winnipeg Regional Health Authority   \n",
       "149        72    4602       MB                       Prairie Mountain Health   \n",
       "\n",
       "                                               frename  casecount  deaths  \\\n",
       "110                  Région du Saguenay—Lac-Saint-Jean        273    20.0   \n",
       "111                    Région de la Capitale-Nationale        789    45.0   \n",
       "112       Région de la Mauricie et du Centre-du-Québec       1176    93.0   \n",
       "113                                 Région de l'Estrie        826    25.0   \n",
       "114                                 Région de Montréal      12487  1039.0   \n",
       "115                              Région de l'Outaouais        270     2.0   \n",
       "116                  Région de l'Abitibi-Témiscamingue        149     3.0   \n",
       "117                             Région de la Côte-Nord        114     0.0   \n",
       "118                           Région du Nord-du-Québec          7     0.0   \n",
       "119     Circonscription sanitaire régionale de Niagara        472    42.0   \n",
       "120  Circonscription sanitaire du district de North...         16     0.0   \n",
       "121            Circonscription sanitaire du Nord-Ouest         16     NaN   \n",
       "122     Circonscription sanitaire de la ville d'Ottawa       1221    71.0   \n",
       "123        Circonscription sanitaire régionale de Peel       2358    89.0   \n",
       "124  Circonscription sanitaire du comté et de la ci...         86     2.0   \n",
       "125             Circonscription sanitaire de Porcupine         59     3.0   \n",
       "126  Circonscription sanitaire du comté et du distr...         15     1.0   \n",
       "127    Circonscription sanitaire de l'Est de l'Ontario         91     0.0   \n",
       "128  Circonscription sanitaire du district de Simco...        261    15.0   \n",
       "129  Circonscription sanitaire de Sudbury et son di...         57     1.0   \n",
       "130  Circonscription sanitaire du district de Thund...         69     1.0   \n",
       "131           Circonscription sanitaire de Timiskaming         12     NaN   \n",
       "132              Circonscription sanitaire de Waterloo        709    66.0   \n",
       "133  Circonscription sanitaire de Wellington-Duffer...        270    19.0   \n",
       "134  Circonscription sanitaire de Windsor-comté d'E...        581    43.0   \n",
       "135                                   Zone 3 - Eastern         50     NaN   \n",
       "136                                   Zone 4 - Central        772     NaN   \n",
       "137                         Zone 1 (région de Moncton)         23     NaN   \n",
       "138                      Zone 2 (région de Saint John)         26     NaN   \n",
       "139                     Zone 3 (région de Fredericton)         47     NaN   \n",
       "140                       Zone 4 (région d'Edmundston)          7     NaN   \n",
       "141                     Zone 5 (région de Campbellton)         12     NaN   \n",
       "142                        Zone 6 (région de Bathurst)          1     NaN   \n",
       "143                Office régional de la santé du Nord          3     NaN   \n",
       "144                          Southern Health—Santé Sud         31     NaN   \n",
       "145        Circonscription sanitaire régionale de York       1457    90.0   \n",
       "146             Circonscription sanitaire du sud-ouest         59     4.0   \n",
       "147    Circonscription sanitaire de la cité de Toronto       5128   305.0   \n",
       "148            Office régional de la santé de Winnipeg        206     NaN   \n",
       "149                          Santé de Prairie Mountain         15     NaN   \n",
       "\n",
       "     recovered   tests  totalpop2019  ...  pop80to84_2019  pop85older  \\\n",
       "110        NaN     NaN        276281  ...            7706        8104   \n",
       "111        NaN     NaN        700684  ...           17227       19379   \n",
       "112        NaN     NaN        518043  ...           14468       16673   \n",
       "113        NaN     NaN        513429  ...           12873       13748   \n",
       "114        NaN     NaN       1856818  ...           40649       50237   \n",
       "115        NaN     NaN        409421  ...            7501        7160   \n",
       "116        NaN     NaN        148529  ...            3257        3363   \n",
       "117        NaN     NaN         87447  ...            2162        2027   \n",
       "118        NaN     NaN         14642  ...             273         171   \n",
       "119      204.0     NaN        450816  ...           12668       14601   \n",
       "120       15.0  1636.0        128804  ...            3881        3671   \n",
       "121       15.0  1349.0         74771  ...            1521        1509   \n",
       "122      529.0     NaN       1019693  ...           19340       20805   \n",
       "123      242.0     NaN       1553076  ...           24940       21848   \n",
       "124       42.0  3713.0        144237  ...            4272        4900   \n",
       "125       43.0  1789.0         90540  ...            2061        1902   \n",
       "126       10.0  1477.0        106578  ...            3063        3129   \n",
       "127       45.0  1930.0        179454  ...            4417        4136   \n",
       "128      144.0     NaN        562142  ...           13391       13148   \n",
       "129       45.0  3466.0        202681  ...            5045        4895   \n",
       "130       51.0  2922.0        154444  ...            3865        4158   \n",
       "131       11.0   596.0         33389  ...            1017         996   \n",
       "132      269.0  5770.0        571232  ...           10527       10697   \n",
       "133       89.0     NaN        304193  ...            5986        5987   \n",
       "134      159.0  6199.0        348836  ...            7744        8152   \n",
       "135        NaN     NaN        138177  ...            4102        3846   \n",
       "136        NaN     NaN        444740  ...            7900        7852   \n",
       "137        NaN  4305.0        217155  ...            4830        5412   \n",
       "138        NaN  2889.0        149412  ...            3501        3512   \n",
       "139        NaN  3063.0        179137  ...            3960        3763   \n",
       "140        NaN   937.0         45390  ...            1235        1169   \n",
       "141        NaN   553.0         23126  ...             780         916   \n",
       "142        NaN  1163.0         70761  ...            2219        2138   \n",
       "143        NaN     NaN         77380  ...             544         396   \n",
       "144        NaN     NaN        205885  ...            3518        3626   \n",
       "145      579.0  4426.0       1200761  ...           23393       21585   \n",
       "146       28.0  2233.0        209238  ...            5230        5376   \n",
       "147     2930.0     NaN       2987513  ...           63322       76806   \n",
       "148        NaN     NaN        787724  ...           14603       17524   \n",
       "149        NaN     NaN        142031  ...            3419        3740   \n",
       "\n",
       "     averageage_2019  medianage_2019    shape_area  shape_length  \\\n",
       "110             45.1            47.2  2.540617e+11  3.000150e+06   \n",
       "111             43.3            43.1  4.239543e+10  1.345502e+06   \n",
       "112             45.2            47.1  1.034139e+11  2.210870e+06   \n",
       "113             43.8            44.9  2.608167e+10  1.099065e+06   \n",
       "114             40.6            39.0  9.562571e+08  2.478708e+05   \n",
       "115             41.4            42.0  7.192139e+10  2.091063e+06   \n",
       "116             42.6            43.6  1.440284e+11  2.022227e+06   \n",
       "117             43.7            45.7  6.943192e+11  1.066786e+07   \n",
       "118             41.5            42.6  9.118141e+11  7.393913e+06   \n",
       "119             44.2            45.7  3.545058e+09  3.189421e+05   \n",
       "120             45.4            48.1  3.951683e+10  1.806803e+06   \n",
       "121             39.5            38.7  5.261314e+11  3.773241e+06   \n",
       "122             40.4            39.2  5.843672e+09  3.882171e+05   \n",
       "123             39.0            38.2  2.424380e+09  2.362829e+05   \n",
       "124             44.8            46.2  8.292255e+09  4.135967e+05   \n",
       "125             42.2            43.5  7.305916e+11  5.377468e+06   \n",
       "126             43.8            45.1  3.377381e+10  1.077930e+06   \n",
       "127             43.5            46.0  1.072138e+10  5.044397e+05   \n",
       "128             42.6            43.4  1.946062e+10  1.259109e+06   \n",
       "129             43.3            44.4  1.108435e+11  3.609397e+06   \n",
       "130             43.0            43.9  6.682825e+11  8.036945e+06   \n",
       "131             45.0            48.1  3.436522e+10  8.894735e+05   \n",
       "132             39.7            38.7  2.630614e+09  2.520853e+05   \n",
       "133             40.4            40.0  8.073621e+09  5.489423e+05   \n",
       "134             41.4            42.0  3.389723e+09  3.737460e+05   \n",
       "135             45.8            49.5  3.408778e+10  2.794639e+06   \n",
       "136             41.2            40.2  1.472536e+10  1.205836e+06   \n",
       "137             43.2            43.9  2.122780e+10  1.103411e+06   \n",
       "138             43.1            45.0  2.140013e+10  1.320296e+06   \n",
       "139             41.9            42.1  5.003797e+10  1.071391e+06   \n",
       "140             46.4            50.3  1.709937e+10  7.765637e+05   \n",
       "141             49.0            53.8  1.217174e+10  5.263302e+05   \n",
       "142             48.3            52.7  1.051998e+10  7.731629e+05   \n",
       "143             30.7            26.9  1.434341e+12  8.392579e+06   \n",
       "144             36.6            34.4  6.524804e+10  1.910979e+06   \n",
       "145             40.6            40.8  4.064797e+09  3.332101e+05   \n",
       "146             41.7            42.2  7.414612e+09  6.237560e+05   \n",
       "147             40.9            39.3  1.237670e+09  1.966657e+05   \n",
       "148             39.7            38.2  1.637336e+09  2.917499e+05   \n",
       "149             40.0            38.5  1.719848e+11  4.055103e+06   \n",
       "\n",
       "      last_updated                                          sourceurl  \\\n",
       "110  1588100400000  https://www.quebec.ca/en/health/health-issues/...   \n",
       "111  1588100460000  https://www.quebec.ca/en/health/health-issues/...   \n",
       "112  1588100460000  https://www.quebec.ca/en/health/health-issues/...   \n",
       "113  1588100520000  https://www.quebec.ca/en/health/health-issues/...   \n",
       "114  1588100520000  https://www.quebec.ca/en/health/health-issues/...   \n",
       "115  1588100580000  https://www.quebec.ca/en/health/health-issues/...   \n",
       "116  1588105680000  https://www.quebec.ca/en/health/health-issues/...   \n",
       "117  1588105680000  https://www.quebec.ca/en/health/health-issues/...   \n",
       "118  1588102560000  https://www.quebec.ca/en/health/health-issues/...   \n",
       "119  1588109280000  https://www.niagararegion.ca/health/covid-19/d...   \n",
       "120  1588109340000  https://www.myhealthunit.ca/en/health-topics/c...   \n",
       "121  1588083060000     https://www.nwhu.on.ca/covid19/Pages/home.aspx   \n",
       "122  1588109460000  https://www.ottawapublichealth.ca/en/public-he...   \n",
       "123  1588109460000        http://www.peelregion.ca/coronavirus/#cases   \n",
       "124  1588109520000  https://www.peterboroughpublichealth.ca/your-h...   \n",
       "125  1588083000000  http://www.porcupinehu.on.ca/en/your-health/in...   \n",
       "126  1588109520000  https://www.rcdhu.com/novel-coronavirus-covid-...   \n",
       "127  1588109580000  https://eohu.ca/en/my-health/covid-19-status-u...   \n",
       "128  1588109580000  http://www.simcoemuskokahealthstats.org/topics...   \n",
       "129  1588109640000  https://www.phsd.ca/health-topics-programs/dis...   \n",
       "130  1588112040000                  https://www.tbdhu.com/coronavirus   \n",
       "131  1588109640000  https://www.timiskaminghu.com/90484/covid-19#C...   \n",
       "132  1588109700000  https://www.regionofwaterloo.ca/en/health-and-...   \n",
       "133  1588109700000  https://app.powerbi.com/view?r=eyJrIjoiMDE0OGV...   \n",
       "134  1588109760000             https://www.wechu.org/cv/local-updates   \n",
       "135  1588098060000            https://novascotia.ca/coronavirus/data/   \n",
       "136  1588098060000            https://novascotia.ca/coronavirus/data/   \n",
       "137  1588099440000  https://www2.gnb.ca/content/gnb/en/departments...   \n",
       "138  1588099500000  https://www2.gnb.ca/content/gnb/en/departments...   \n",
       "139  1588099500000  https://www2.gnb.ca/content/gnb/en/departments...   \n",
       "140  1588099500000  https://www2.gnb.ca/content/gnb/en/departments...   \n",
       "141  1588100040000  https://www2.gnb.ca/content/gnb/en/departments...   \n",
       "142  1588100160000  https://www2.gnb.ca/content/gnb/en/departments...   \n",
       "143  1588103220000    https://www.gov.mb.ca/covid19/updates/data.html   \n",
       "144  1588103220000    https://www.gov.mb.ca/covid19/updates/data.html   \n",
       "145  1588122420000                        https://www.york.ca/covid19   \n",
       "146  1588109880000  https://www.swpublichealth.ca/partners-and-pro...   \n",
       "147  1588109940000  https://www.toronto.ca/home/covid-19/media-roo...   \n",
       "148  1588102980000    https://www.gov.mb.ca/covid19/updates/data.html   \n",
       "149  1588103040000           https://www.gov.mb.ca/covid19/index.html   \n",
       "\n",
       "                                 globalid         retrieved_at  \n",
       "110  eac3fc7e-71a2-4c8b-8ef7-adaedd272237  2020-04-29 07:15:57  \n",
       "111  86c78678-676c-4e27-ba98-e40183335f49  2020-04-29 07:15:57  \n",
       "112  e4efb474-f888-4d6e-89fa-6983b1854141  2020-04-29 07:15:57  \n",
       "113  200a9a1f-cb75-41d6-ac40-2e77ebde21ea  2020-04-29 07:15:57  \n",
       "114  8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4  2020-04-29 07:15:57  \n",
       "115  889faae9-4e01-437d-a948-5e32d396b03b  2020-04-29 07:15:57  \n",
       "116  cef3a9ff-5524-452d-bca9-43627fdf0611  2020-04-29 07:15:57  \n",
       "117  6f999911-9627-40ef-92aa-cd7fc9106c7a  2020-04-29 07:15:57  \n",
       "118  17f34b76-8177-4eb1-a35b-e93ec778afc1  2020-04-29 07:15:57  \n",
       "119  85032ec9-5a18-4a1a-8ca6-d21acefcd298  2020-04-29 07:15:57  \n",
       "120  d8c2dedb-a9a7-4b62-9969-a6faaa1980a6  2020-04-29 07:15:57  \n",
       "121  abd0444e-e2a1-497c-8a75-e5b5762f0baa  2020-04-29 07:15:57  \n",
       "122  f46b61ab-19e1-4051-946e-32002768ddd0  2020-04-29 07:15:57  \n",
       "123  58190c56-92ca-4e4e-ad24-fe885c550a82  2020-04-29 07:15:57  \n",
       "124  aa3f708b-2039-4eb3-992f-4df701806483  2020-04-29 07:15:57  \n",
       "125  f8661a8f-4d7c-48ac-9007-56b58ef0ac0c  2020-04-29 07:15:57  \n",
       "126  b8332908-ad89-44e0-bbd0-86c9e03f369d  2020-04-29 07:15:57  \n",
       "127  07381039-5aa9-436c-ad92-e6da548431c8  2020-04-29 07:15:57  \n",
       "128  124d22ca-7518-421f-a811-e2f0b39fc737  2020-04-29 07:15:57  \n",
       "129  673afa7b-0155-4739-bf21-d9238048fe08  2020-04-29 07:15:57  \n",
       "130  1be2ba7e-a6da-46fc-92f1-42cc6c0e5824  2020-04-29 07:15:57  \n",
       "131  de7e4ccb-d405-4f71-97f4-404bd2aeb305  2020-04-29 07:15:57  \n",
       "132  1657926a-de14-4ec2-a97b-7a8b54622ba4  2020-04-29 07:15:57  \n",
       "133  a86fca32-95a4-4234-bfb6-622b12f32c4b  2020-04-29 07:15:57  \n",
       "134  00a44660-f775-4f73-aac1-d1ec56aaca88  2020-04-29 07:15:57  \n",
       "135  72b5482f-3f2e-4ae6-a368-a8608b642cac  2020-04-29 07:15:57  \n",
       "136  00786a76-f6cd-403e-8d85-36bf269d87e3  2020-04-29 07:15:57  \n",
       "137  3e89b814-c25f-4ffe-b991-3310a3712942  2020-04-29 07:15:57  \n",
       "138  e7557c80-9a79-4846-b929-d76c38bfc046  2020-04-29 07:15:57  \n",
       "139  fcfb3f6f-3194-4a02-b131-75718a603c2a  2020-04-29 07:15:57  \n",
       "140  25d24683-b924-47b0-ab7b-18954554eee9  2020-04-29 07:15:57  \n",
       "141  fa760c11-19ce-41e4-8d1c-c2dd92f86bad  2020-04-29 07:15:57  \n",
       "142  9fb436e5-fe1a-4579-8a06-b37ffae3690b  2020-04-29 07:15:57  \n",
       "143  17401c93-4065-4490-bcab-32b920729479  2020-04-29 07:15:57  \n",
       "144  3eecfb30-34b7-414a-8cff-f5632e9b5448  2020-04-29 07:15:57  \n",
       "145  c8fff00e-9d45-48b5-b365-e0899d3611df  2020-04-29 07:15:57  \n",
       "146  e9ea1347-81aa-47a2-850d-a41726e3793c  2020-04-29 07:15:57  \n",
       "147  8aa96e82-b87b-4239-802e-c687222bebf7  2020-04-29 07:15:57  \n",
       "148  7ddc61eb-dc45-4cb7-b1f4-1da8abacb4d5  2020-04-29 07:15:57  \n",
       "149  361db834-f0ef-4fd3-bd6a-39d5d82bd180  2020-04-29 07:15:57  \n",
       "\n",
       "[40 rows x 36 columns]"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_case_count.iloc[110:150, :37]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>objectid</th>\n",
       "      <th>hr_uid</th>\n",
       "      <th>casecount</th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>AB</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>4833.000000</td>\n",
       "      <td>513.080556</td>\n",
       "      <td>10.255556</td>\n",
       "      <td>231.863158</td>\n",
       "      <td>19079.550877</td>\n",
       "      <td>892508.200000</td>\n",
       "      <td>56946.600000</td>\n",
       "      <td>55310.400000</td>\n",
       "      <td>53035.200000</td>\n",
       "      <td>...</td>\n",
       "      <td>40320.400000</td>\n",
       "      <td>30025.400000</td>\n",
       "      <td>19518.400000</td>\n",
       "      <td>13128.000000</td>\n",
       "      <td>13717.800000</td>\n",
       "      <td>38.320000</td>\n",
       "      <td>37.320000</td>\n",
       "      <td>4.071358e+11</td>\n",
       "      <td>3.108612e+06</td>\n",
       "      <td>1.587120e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>BC</td>\n",
       "      <td>98.000000</td>\n",
       "      <td>593.000000</td>\n",
       "      <td>321.333333</td>\n",
       "      <td>14.433333</td>\n",
       "      <td>193.091667</td>\n",
       "      <td>13240.300000</td>\n",
       "      <td>954864.000000</td>\n",
       "      <td>45310.800000</td>\n",
       "      <td>44755.200000</td>\n",
       "      <td>47032.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>64975.000000</td>\n",
       "      <td>56209.200000</td>\n",
       "      <td>46703.200000</td>\n",
       "      <td>32251.200000</td>\n",
       "      <td>23733.200000</td>\n",
       "      <td>42.620000</td>\n",
       "      <td>42.920000</td>\n",
       "      <td>5.724977e+11</td>\n",
       "      <td>8.258738e+06</td>\n",
       "      <td>1.587125e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>MB</td>\n",
       "      <td>67.000000</td>\n",
       "      <td>4603.000000</td>\n",
       "      <td>48.677778</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>277208.200000</td>\n",
       "      <td>17795.400000</td>\n",
       "      <td>17325.800000</td>\n",
       "      <td>16844.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>13882.600000</td>\n",
       "      <td>11165.800000</td>\n",
       "      <td>7515.800000</td>\n",
       "      <td>5201.000000</td>\n",
       "      <td>5820.200000</td>\n",
       "      <td>37.720000</td>\n",
       "      <td>36.020000</td>\n",
       "      <td>3.746536e+11</td>\n",
       "      <td>4.038372e+06</td>\n",
       "      <td>1.587111e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>NB</td>\n",
       "      <td>50.857143</td>\n",
       "      <td>1304.000000</td>\n",
       "      <td>16.353175</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1374.428571</td>\n",
       "      <td>103917.285714</td>\n",
       "      <td>4668.857143</td>\n",
       "      <td>5138.428571</td>\n",
       "      <td>5334.571429</td>\n",
       "      <td>...</td>\n",
       "      <td>7013.285714</td>\n",
       "      <td>5946.142857</td>\n",
       "      <td>3935.571429</td>\n",
       "      <td>2546.428571</td>\n",
       "      <td>2610.142857</td>\n",
       "      <td>45.514286</td>\n",
       "      <td>48.300000</td>\n",
       "      <td>2.200759e+10</td>\n",
       "      <td>9.349297e+05</td>\n",
       "      <td>1.587112e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>NL</td>\n",
       "      <td>75.500000</td>\n",
       "      <td>1012.500000</td>\n",
       "      <td>61.840278</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>52.909091</td>\n",
       "      <td>1443.061594</td>\n",
       "      <td>126133.750000</td>\n",
       "      <td>5254.250000</td>\n",
       "      <td>5946.750000</td>\n",
       "      <td>6426.250000</td>\n",
       "      <td>...</td>\n",
       "      <td>9144.250000</td>\n",
       "      <td>7434.500000</td>\n",
       "      <td>4673.500000</td>\n",
       "      <td>2942.000000</td>\n",
       "      <td>2385.250000</td>\n",
       "      <td>44.425000</td>\n",
       "      <td>46.950000</td>\n",
       "      <td>2.766625e+11</td>\n",
       "      <td>1.073486e+07</td>\n",
       "      <td>1.587111e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>NS</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>1202.500000</td>\n",
       "      <td>150.743056</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>228629.250000</td>\n",
       "      <td>10219.500000</td>\n",
       "      <td>10827.000000</td>\n",
       "      <td>10973.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>15021.000000</td>\n",
       "      <td>12891.500000</td>\n",
       "      <td>8534.250000</td>\n",
       "      <td>5379.250000</td>\n",
       "      <td>5335.250000</td>\n",
       "      <td>44.650000</td>\n",
       "      <td>46.975000</td>\n",
       "      <td>2.776942e+10</td>\n",
       "      <td>1.875473e+06</td>\n",
       "      <td>1.587116e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>NT</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>6101.000000</td>\n",
       "      <td>4.972222</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.916667</td>\n",
       "      <td>2124.000000</td>\n",
       "      <td>44078.000000</td>\n",
       "      <td>3013.000000</td>\n",
       "      <td>3162.000000</td>\n",
       "      <td>3289.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1579.000000</td>\n",
       "      <td>838.000000</td>\n",
       "      <td>568.000000</td>\n",
       "      <td>339.000000</td>\n",
       "      <td>259.000000</td>\n",
       "      <td>35.400000</td>\n",
       "      <td>34.600000</td>\n",
       "      <td>8.483916e+12</td>\n",
       "      <td>7.197691e+07</td>\n",
       "      <td>1.587111e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>NU</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>6201.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>432.305556</td>\n",
       "      <td>37226.000000</td>\n",
       "      <td>4145.000000</td>\n",
       "      <td>3770.000000</td>\n",
       "      <td>3399.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>770.000000</td>\n",
       "      <td>478.000000</td>\n",
       "      <td>234.000000</td>\n",
       "      <td>86.000000</td>\n",
       "      <td>66.000000</td>\n",
       "      <td>29.300000</td>\n",
       "      <td>27.200000</td>\n",
       "      <td>2.272713e+13</td>\n",
       "      <td>3.117239e+08</td>\n",
       "      <td>1.587117e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>ON</td>\n",
       "      <td>45.764706</td>\n",
       "      <td>3550.058824</td>\n",
       "      <td>308.261029</td>\n",
       "      <td>19.065402</td>\n",
       "      <td>80.844729</td>\n",
       "      <td>1706.697917</td>\n",
       "      <td>419893.647059</td>\n",
       "      <td>21451.735294</td>\n",
       "      <td>21794.264706</td>\n",
       "      <td>22353.676471</td>\n",
       "      <td>...</td>\n",
       "      <td>22638.558824</td>\n",
       "      <td>18745.029412</td>\n",
       "      <td>12920.088235</td>\n",
       "      <td>9070.117647</td>\n",
       "      <td>9603.470588</td>\n",
       "      <td>42.695588</td>\n",
       "      <td>43.677941</td>\n",
       "      <td>7.180465e+10</td>\n",
       "      <td>1.214599e+06</td>\n",
       "      <td>1.587117e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>PE</td>\n",
       "      <td>90.000000</td>\n",
       "      <td>1100.000000</td>\n",
       "      <td>25.208333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.097222</td>\n",
       "      <td>2117.208333</td>\n",
       "      <td>135849.000000</td>\n",
       "      <td>6906.000000</td>\n",
       "      <td>7549.000000</td>\n",
       "      <td>7885.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>8517.000000</td>\n",
       "      <td>7605.000000</td>\n",
       "      <td>4737.000000</td>\n",
       "      <td>3026.000000</td>\n",
       "      <td>2789.000000</td>\n",
       "      <td>42.300000</td>\n",
       "      <td>43.400000</td>\n",
       "      <td>1.218400e+10</td>\n",
       "      <td>1.489017e+06</td>\n",
       "      <td>1.587109e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>QC</td>\n",
       "      <td>53.166667</td>\n",
       "      <td>2409.500000</td>\n",
       "      <td>924.037037</td>\n",
       "      <td>44.542088</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>449547.000000</td>\n",
       "      <td>22781.722222</td>\n",
       "      <td>24503.333333</td>\n",
       "      <td>23330.888889</td>\n",
       "      <td>...</td>\n",
       "      <td>26991.388889</td>\n",
       "      <td>22645.833333</td>\n",
       "      <td>15975.500000</td>\n",
       "      <td>10387.777778</td>\n",
       "      <td>11240.722222</td>\n",
       "      <td>41.833333</td>\n",
       "      <td>42.638889</td>\n",
       "      <td>2.386474e+11</td>\n",
       "      <td>3.198632e+06</td>\n",
       "      <td>1.587114e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>SK</td>\n",
       "      <td>119.500000</td>\n",
       "      <td>473.500000</td>\n",
       "      <td>51.571759</td>\n",
       "      <td>0.638889</td>\n",
       "      <td>33.625000</td>\n",
       "      <td>3615.680556</td>\n",
       "      <td>203465.500000</td>\n",
       "      <td>13488.166667</td>\n",
       "      <td>13300.333333</td>\n",
       "      <td>12790.666667</td>\n",
       "      <td>...</td>\n",
       "      <td>10130.666667</td>\n",
       "      <td>7566.833333</td>\n",
       "      <td>5261.166667</td>\n",
       "      <td>3951.333333</td>\n",
       "      <td>4530.500000</td>\n",
       "      <td>38.216667</td>\n",
       "      <td>36.816667</td>\n",
       "      <td>3.164268e+11</td>\n",
       "      <td>3.566404e+06</td>\n",
       "      <td>1.587113e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>YT</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>6001.000000</td>\n",
       "      <td>9.083333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.291667</td>\n",
       "      <td>844.958333</td>\n",
       "      <td>39469.000000</td>\n",
       "      <td>2063.000000</td>\n",
       "      <td>2317.000000</td>\n",
       "      <td>2023.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2336.000000</td>\n",
       "      <td>1437.000000</td>\n",
       "      <td>894.000000</td>\n",
       "      <td>438.000000</td>\n",
       "      <td>348.000000</td>\n",
       "      <td>39.800000</td>\n",
       "      <td>39.900000</td>\n",
       "      <td>2.468406e+12</td>\n",
       "      <td>9.894476e+06</td>\n",
       "      <td>1.587122e+12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>13 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            objectid       hr_uid   casecount     deaths   recovered  \\\n",
       "province                                                               \n",
       "AB         20.000000  4833.000000  513.080556  10.255556  231.863158   \n",
       "BC         98.000000   593.000000  321.333333  14.433333  193.091667   \n",
       "MB         67.000000  4603.000000   48.677778   0.000000         NaN   \n",
       "NB         50.857143  1304.000000   16.353175        NaN         NaN   \n",
       "NL         75.500000  1012.500000   61.840278   0.750000   52.909091   \n",
       "NS         65.000000  1202.500000  150.743056        NaN         NaN   \n",
       "NT         10.000000  6101.000000    4.972222        NaN    2.916667   \n",
       "NU         11.000000  6201.000000    0.000000   0.000000         NaN   \n",
       "ON         45.764706  3550.058824  308.261029  19.065402   80.844729   \n",
       "PE         90.000000  1100.000000   25.208333        NaN   20.097222   \n",
       "QC         53.166667  2409.500000  924.037037  44.542088         NaN   \n",
       "SK        119.500000   473.500000   51.571759   0.638889   33.625000   \n",
       "YT          9.000000  6001.000000    9.083333   0.000000    6.291667   \n",
       "\n",
       "                 tests   totalpop2019  pop0to4_2019  pop5to9_2019  \\\n",
       "province                                                            \n",
       "AB        19079.550877  892508.200000  56946.600000  55310.400000   \n",
       "BC        13240.300000  954864.000000  45310.800000  44755.200000   \n",
       "MB                 NaN  277208.200000  17795.400000  17325.800000   \n",
       "NB         1374.428571  103917.285714   4668.857143   5138.428571   \n",
       "NL         1443.061594  126133.750000   5254.250000   5946.750000   \n",
       "NS                 NaN  228629.250000  10219.500000  10827.000000   \n",
       "NT         2124.000000   44078.000000   3013.000000   3162.000000   \n",
       "NU          432.305556   37226.000000   4145.000000   3770.000000   \n",
       "ON         1706.697917  419893.647059  21451.735294  21794.264706   \n",
       "PE         2117.208333  135849.000000   6906.000000   7549.000000   \n",
       "QC                 NaN  449547.000000  22781.722222  24503.333333   \n",
       "SK         3615.680556  203465.500000  13488.166667  13300.333333   \n",
       "YT          844.958333   39469.000000   2063.000000   2317.000000   \n",
       "\n",
       "          pop10to14_2019  ...  pop65to69_2019  pop70to74_2019  pop75to79_2019  \\\n",
       "province                  ...                                                   \n",
       "AB          53035.200000  ...    40320.400000    30025.400000    19518.400000   \n",
       "BC          47032.000000  ...    64975.000000    56209.200000    46703.200000   \n",
       "MB          16844.000000  ...    13882.600000    11165.800000     7515.800000   \n",
       "NB           5334.571429  ...     7013.285714     5946.142857     3935.571429   \n",
       "NL           6426.250000  ...     9144.250000     7434.500000     4673.500000   \n",
       "NS          10973.000000  ...    15021.000000    12891.500000     8534.250000   \n",
       "NT           3289.000000  ...     1579.000000      838.000000      568.000000   \n",
       "NU           3399.000000  ...      770.000000      478.000000      234.000000   \n",
       "ON          22353.676471  ...    22638.558824    18745.029412    12920.088235   \n",
       "PE           7885.000000  ...     8517.000000     7605.000000     4737.000000   \n",
       "QC          23330.888889  ...    26991.388889    22645.833333    15975.500000   \n",
       "SK          12790.666667  ...    10130.666667     7566.833333     5261.166667   \n",
       "YT           2023.000000  ...     2336.000000     1437.000000      894.000000   \n",
       "\n",
       "          pop80to84_2019    pop85older  averageage_2019  medianage_2019  \\\n",
       "province                                                                  \n",
       "AB          13128.000000  13717.800000        38.320000       37.320000   \n",
       "BC          32251.200000  23733.200000        42.620000       42.920000   \n",
       "MB           5201.000000   5820.200000        37.720000       36.020000   \n",
       "NB           2546.428571   2610.142857        45.514286       48.300000   \n",
       "NL           2942.000000   2385.250000        44.425000       46.950000   \n",
       "NS           5379.250000   5335.250000        44.650000       46.975000   \n",
       "NT            339.000000    259.000000        35.400000       34.600000   \n",
       "NU             86.000000     66.000000        29.300000       27.200000   \n",
       "ON           9070.117647   9603.470588        42.695588       43.677941   \n",
       "PE           3026.000000   2789.000000        42.300000       43.400000   \n",
       "QC          10387.777778  11240.722222        41.833333       42.638889   \n",
       "SK           3951.333333   4530.500000        38.216667       36.816667   \n",
       "YT            438.000000    348.000000        39.800000       39.900000   \n",
       "\n",
       "            shape_area  shape_length  last_updated  \n",
       "province                                            \n",
       "AB        4.071358e+11  3.108612e+06  1.587120e+12  \n",
       "BC        5.724977e+11  8.258738e+06  1.587125e+12  \n",
       "MB        3.746536e+11  4.038372e+06  1.587111e+12  \n",
       "NB        2.200759e+10  9.349297e+05  1.587112e+12  \n",
       "NL        2.766625e+11  1.073486e+07  1.587111e+12  \n",
       "NS        2.776942e+10  1.875473e+06  1.587116e+12  \n",
       "NT        8.483916e+12  7.197691e+07  1.587111e+12  \n",
       "NU        2.272713e+13  3.117239e+08  1.587117e+12  \n",
       "ON        7.180465e+10  1.214599e+06  1.587117e+12  \n",
       "PE        1.218400e+10  1.489017e+06  1.587109e+12  \n",
       "QC        2.386474e+11  3.198632e+06  1.587114e+12  \n",
       "SK        3.164268e+11  3.566404e+06  1.587113e+12  \n",
       "YT        2.468406e+12  9.894476e+06  1.587122e+12  \n",
       "\n",
       "[13 rows x 30 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "province_mean=canada_case_count.groupby('province').mean()\n",
    "province_mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "province_view['median age']= province_mean['medianage_2019']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "province_view=canada_case_count.groupby('province').sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "    .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>objectid</th>\n",
       "      <th>hr_uid</th>\n",
       "      <th>casecount</th>\n",
       "      <th>deaths</th>\n",
       "      <th>recovered</th>\n",
       "      <th>tests</th>\n",
       "      <th>totalpop2019</th>\n",
       "      <th>pop0to4_2019</th>\n",
       "      <th>pop5to9_2019</th>\n",
       "      <th>pop10to14_2019</th>\n",
       "      <th>...</th>\n",
       "      <th>pop85older</th>\n",
       "      <th>averageage_2019</th>\n",
       "      <th>medianage_2019</th>\n",
       "      <th>shape_area</th>\n",
       "      <th>shape_length</th>\n",
       "      <th>last_updated</th>\n",
       "      <th>median age</th>\n",
       "      <th>teens</th>\n",
       "      <th>young adults</th>\n",
       "      <th>adults</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>province</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>AB</td>\n",
       "      <td>7200</td>\n",
       "      <td>1739880</td>\n",
       "      <td>184709</td>\n",
       "      <td>3692.0</td>\n",
       "      <td>66081.0</td>\n",
       "      <td>5437672.0</td>\n",
       "      <td>321302952</td>\n",
       "      <td>20500776</td>\n",
       "      <td>19911744</td>\n",
       "      <td>19092672</td>\n",
       "      <td>...</td>\n",
       "      <td>4938408</td>\n",
       "      <td>13795.2</td>\n",
       "      <td>13435.2</td>\n",
       "      <td>1.465689e+14</td>\n",
       "      <td>1.119100e+09</td>\n",
       "      <td>571363375320000</td>\n",
       "      <td>37.320000</td>\n",
       "      <td>38210112</td>\n",
       "      <td>40815864</td>\n",
       "      <td>24727104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>BC</td>\n",
       "      <td>35280</td>\n",
       "      <td>213480</td>\n",
       "      <td>115680</td>\n",
       "      <td>5196.0</td>\n",
       "      <td>69513.0</td>\n",
       "      <td>2780463.0</td>\n",
       "      <td>343751040</td>\n",
       "      <td>16311888</td>\n",
       "      <td>16111872</td>\n",
       "      <td>16931520</td>\n",
       "      <td>...</td>\n",
       "      <td>8543952</td>\n",
       "      <td>15343.2</td>\n",
       "      <td>15451.2</td>\n",
       "      <td>2.060992e+14</td>\n",
       "      <td>2.973146e+09</td>\n",
       "      <td>571364919180000</td>\n",
       "      <td>42.920000</td>\n",
       "      <td>34281576</td>\n",
       "      <td>45465120</td>\n",
       "      <td>25170912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>MB</td>\n",
       "      <td>24120</td>\n",
       "      <td>1657080</td>\n",
       "      <td>17524</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>99794952</td>\n",
       "      <td>6406344</td>\n",
       "      <td>6237288</td>\n",
       "      <td>6063840</td>\n",
       "      <td>...</td>\n",
       "      <td>2095272</td>\n",
       "      <td>13579.2</td>\n",
       "      <td>12967.2</td>\n",
       "      <td>1.348753e+14</td>\n",
       "      <td>1.453814e+09</td>\n",
       "      <td>571359924540000</td>\n",
       "      <td>36.020000</td>\n",
       "      <td>12579192</td>\n",
       "      <td>13007448</td>\n",
       "      <td>8098704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>NB</td>\n",
       "      <td>25632</td>\n",
       "      <td>657216</td>\n",
       "      <td>8242</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>692712.0</td>\n",
       "      <td>52374312</td>\n",
       "      <td>2353104</td>\n",
       "      <td>2589768</td>\n",
       "      <td>2688624</td>\n",
       "      <td>...</td>\n",
       "      <td>1315512</td>\n",
       "      <td>22939.2</td>\n",
       "      <td>24343.2</td>\n",
       "      <td>1.109182e+13</td>\n",
       "      <td>4.712046e+08</td>\n",
       "      <td>799904653080000</td>\n",
       "      <td>48.300000</td>\n",
       "      <td>5124960</td>\n",
       "      <td>6423480</td>\n",
       "      <td>5076432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>NL</td>\n",
       "      <td>21744</td>\n",
       "      <td>291600</td>\n",
       "      <td>17810</td>\n",
       "      <td>66.0</td>\n",
       "      <td>4656.0</td>\n",
       "      <td>398285.0</td>\n",
       "      <td>36326520</td>\n",
       "      <td>1513224</td>\n",
       "      <td>1712664</td>\n",
       "      <td>1850760</td>\n",
       "      <td>...</td>\n",
       "      <td>686952</td>\n",
       "      <td>12794.4</td>\n",
       "      <td>13521.6</td>\n",
       "      <td>7.967880e+13</td>\n",
       "      <td>3.091640e+09</td>\n",
       "      <td>457088025060000</td>\n",
       "      <td>46.950000</td>\n",
       "      <td>3357072</td>\n",
       "      <td>4439376</td>\n",
       "      <td>3509064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>NS</td>\n",
       "      <td>18720</td>\n",
       "      <td>346320</td>\n",
       "      <td>43414</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>65845224</td>\n",
       "      <td>2943216</td>\n",
       "      <td>3118176</td>\n",
       "      <td>3160224</td>\n",
       "      <td>...</td>\n",
       "      <td>1536552</td>\n",
       "      <td>12859.2</td>\n",
       "      <td>13528.8</td>\n",
       "      <td>7.997594e+12</td>\n",
       "      <td>5.401363e+08</td>\n",
       "      <td>457089510840000</td>\n",
       "      <td>46.975000</td>\n",
       "      <td>6314112</td>\n",
       "      <td>8277624</td>\n",
       "      <td>6078456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>NT</td>\n",
       "      <td>720</td>\n",
       "      <td>439272</td>\n",
       "      <td>358</td>\n",
       "      <td>0.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>152928.0</td>\n",
       "      <td>3173616</td>\n",
       "      <td>216936</td>\n",
       "      <td>227664</td>\n",
       "      <td>236808</td>\n",
       "      <td>...</td>\n",
       "      <td>18648</td>\n",
       "      <td>2548.8</td>\n",
       "      <td>2491.2</td>\n",
       "      <td>6.108419e+14</td>\n",
       "      <td>5.182338e+09</td>\n",
       "      <td>114272000220000</td>\n",
       "      <td>34.600000</td>\n",
       "      <td>390672</td>\n",
       "      <td>419184</td>\n",
       "      <td>224280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>NU</td>\n",
       "      <td>792</td>\n",
       "      <td>446472</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>31126.0</td>\n",
       "      <td>2680272</td>\n",
       "      <td>298440</td>\n",
       "      <td>271440</td>\n",
       "      <td>244728</td>\n",
       "      <td>...</td>\n",
       "      <td>4752</td>\n",
       "      <td>2109.6</td>\n",
       "      <td>1958.4</td>\n",
       "      <td>1.636354e+15</td>\n",
       "      <td>2.244412e+10</td>\n",
       "      <td>114272449080000</td>\n",
       "      <td>27.200000</td>\n",
       "      <td>508608</td>\n",
       "      <td>361008</td>\n",
       "      <td>141192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>ON</td>\n",
       "      <td>112032</td>\n",
       "      <td>8690544</td>\n",
       "      <td>754623</td>\n",
       "      <td>38188.0</td>\n",
       "      <td>170259.0</td>\n",
       "      <td>2621488.0</td>\n",
       "      <td>1027899648</td>\n",
       "      <td>52513848</td>\n",
       "      <td>53352360</td>\n",
       "      <td>54721800</td>\n",
       "      <td>...</td>\n",
       "      <td>23509296</td>\n",
       "      <td>104518.8</td>\n",
       "      <td>106923.6</td>\n",
       "      <td>1.757778e+14</td>\n",
       "      <td>2.973338e+09</td>\n",
       "      <td>3885262889880000</td>\n",
       "      <td>43.677941</td>\n",
       "      <td>109143864</td>\n",
       "      <td>136315944</td>\n",
       "      <td>94066632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>PE</td>\n",
       "      <td>6480</td>\n",
       "      <td>79200</td>\n",
       "      <td>1815</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1447.0</td>\n",
       "      <td>152439.0</td>\n",
       "      <td>9781128</td>\n",
       "      <td>497232</td>\n",
       "      <td>543528</td>\n",
       "      <td>567720</td>\n",
       "      <td>...</td>\n",
       "      <td>200808</td>\n",
       "      <td>3045.6</td>\n",
       "      <td>3124.8</td>\n",
       "      <td>8.772481e+11</td>\n",
       "      <td>1.072092e+08</td>\n",
       "      <td>114271819560000</td>\n",
       "      <td>43.400000</td>\n",
       "      <td>1045368</td>\n",
       "      <td>1254600</td>\n",
       "      <td>897696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>QC</td>\n",
       "      <td>68904</td>\n",
       "      <td>3122712</td>\n",
       "      <td>1197552</td>\n",
       "      <td>52916.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>582612912</td>\n",
       "      <td>29525112</td>\n",
       "      <td>31756320</td>\n",
       "      <td>30236832</td>\n",
       "      <td>...</td>\n",
       "      <td>14567976</td>\n",
       "      <td>54216.0</td>\n",
       "      <td>55260.0</td>\n",
       "      <td>3.092870e+14</td>\n",
       "      <td>4.145427e+09</td>\n",
       "      <td>2056899823200000</td>\n",
       "      <td>42.638889</td>\n",
       "      <td>57714192</td>\n",
       "      <td>69322824</td>\n",
       "      <td>53073360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>SK</td>\n",
       "      <td>51624</td>\n",
       "      <td>204552</td>\n",
       "      <td>22279</td>\n",
       "      <td>276.0</td>\n",
       "      <td>14526.0</td>\n",
       "      <td>1561974.0</td>\n",
       "      <td>87897096</td>\n",
       "      <td>5826888</td>\n",
       "      <td>5745744</td>\n",
       "      <td>5525568</td>\n",
       "      <td>...</td>\n",
       "      <td>1957176</td>\n",
       "      <td>16509.6</td>\n",
       "      <td>15904.8</td>\n",
       "      <td>1.366964e+14</td>\n",
       "      <td>1.540687e+09</td>\n",
       "      <td>685632870000000</td>\n",
       "      <td>36.816667</td>\n",
       "      <td>11136672</td>\n",
       "      <td>10673352</td>\n",
       "      <td>6970752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>YT</td>\n",
       "      <td>648</td>\n",
       "      <td>432072</td>\n",
       "      <td>654</td>\n",
       "      <td>0.0</td>\n",
       "      <td>453.0</td>\n",
       "      <td>60837.0</td>\n",
       "      <td>2841768</td>\n",
       "      <td>148536</td>\n",
       "      <td>166824</td>\n",
       "      <td>145656</td>\n",
       "      <td>...</td>\n",
       "      <td>25056</td>\n",
       "      <td>2865.6</td>\n",
       "      <td>2872.8</td>\n",
       "      <td>1.777252e+14</td>\n",
       "      <td>7.124022e+08</td>\n",
       "      <td>114272783280000</td>\n",
       "      <td>39.900000</td>\n",
       "      <td>298368</td>\n",
       "      <td>378936</td>\n",
       "      <td>206352</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>13 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          objectid   hr_uid  casecount   deaths  recovered      tests  \\\n",
       "province                                                                \n",
       "AB            7200  1739880     184709   3692.0    66081.0  5437672.0   \n",
       "BC           35280   213480     115680   5196.0    69513.0  2780463.0   \n",
       "MB           24120  1657080      17524      0.0        0.0        0.0   \n",
       "NB           25632   657216       8242      0.0        0.0   692712.0   \n",
       "NL           21744   291600      17810     66.0     4656.0   398285.0   \n",
       "NS           18720   346320      43414      0.0        0.0        0.0   \n",
       "NT             720   439272        358      0.0      210.0   152928.0   \n",
       "NU             792   446472          0      0.0        0.0    31126.0   \n",
       "ON          112032  8690544     754623  38188.0   170259.0  2621488.0   \n",
       "PE            6480    79200       1815      0.0     1447.0   152439.0   \n",
       "QC           68904  3122712    1197552  52916.0        0.0        0.0   \n",
       "SK           51624   204552      22279    276.0    14526.0  1561974.0   \n",
       "YT             648   432072        654      0.0      453.0    60837.0   \n",
       "\n",
       "          totalpop2019  pop0to4_2019  pop5to9_2019  pop10to14_2019  ...  \\\n",
       "province                                                            ...   \n",
       "AB           321302952      20500776      19911744        19092672  ...   \n",
       "BC           343751040      16311888      16111872        16931520  ...   \n",
       "MB            99794952       6406344       6237288         6063840  ...   \n",
       "NB            52374312       2353104       2589768         2688624  ...   \n",
       "NL            36326520       1513224       1712664         1850760  ...   \n",
       "NS            65845224       2943216       3118176         3160224  ...   \n",
       "NT             3173616        216936        227664          236808  ...   \n",
       "NU             2680272        298440        271440          244728  ...   \n",
       "ON          1027899648      52513848      53352360        54721800  ...   \n",
       "PE             9781128        497232        543528          567720  ...   \n",
       "QC           582612912      29525112      31756320        30236832  ...   \n",
       "SK            87897096       5826888       5745744         5525568  ...   \n",
       "YT             2841768        148536        166824          145656  ...   \n",
       "\n",
       "          pop85older  averageage_2019  medianage_2019    shape_area  \\\n",
       "province                                                              \n",
       "AB           4938408          13795.2         13435.2  1.465689e+14   \n",
       "BC           8543952          15343.2         15451.2  2.060992e+14   \n",
       "MB           2095272          13579.2         12967.2  1.348753e+14   \n",
       "NB           1315512          22939.2         24343.2  1.109182e+13   \n",
       "NL            686952          12794.4         13521.6  7.967880e+13   \n",
       "NS           1536552          12859.2         13528.8  7.997594e+12   \n",
       "NT             18648           2548.8          2491.2  6.108419e+14   \n",
       "NU              4752           2109.6          1958.4  1.636354e+15   \n",
       "ON          23509296         104518.8        106923.6  1.757778e+14   \n",
       "PE            200808           3045.6          3124.8  8.772481e+11   \n",
       "QC          14567976          54216.0         55260.0  3.092870e+14   \n",
       "SK           1957176          16509.6         15904.8  1.366964e+14   \n",
       "YT             25056           2865.6          2872.8  1.777252e+14   \n",
       "\n",
       "          shape_length      last_updated  median age      teens  young adults  \\\n",
       "province                                                                        \n",
       "AB        1.119100e+09   571363375320000   37.320000   38210112      40815864   \n",
       "BC        2.973146e+09   571364919180000   42.920000   34281576      45465120   \n",
       "MB        1.453814e+09   571359924540000   36.020000   12579192      13007448   \n",
       "NB        4.712046e+08   799904653080000   48.300000    5124960       6423480   \n",
       "NL        3.091640e+09   457088025060000   46.950000    3357072       4439376   \n",
       "NS        5.401363e+08   457089510840000   46.975000    6314112       8277624   \n",
       "NT        5.182338e+09   114272000220000   34.600000     390672        419184   \n",
       "NU        2.244412e+10   114272449080000   27.200000     508608        361008   \n",
       "ON        2.973338e+09  3885262889880000   43.677941  109143864     136315944   \n",
       "PE        1.072092e+08   114271819560000   43.400000    1045368       1254600   \n",
       "QC        4.145427e+09  2056899823200000   42.638889   57714192      69322824   \n",
       "SK        1.540687e+09   685632870000000   36.816667   11136672      10673352   \n",
       "YT        7.124022e+08   114272783280000   39.900000     298368        378936   \n",
       "\n",
       "            adults  \n",
       "province            \n",
       "AB        24727104  \n",
       "BC        25170912  \n",
       "MB         8098704  \n",
       "NB         5076432  \n",
       "NL         3509064  \n",
       "NS         6078456  \n",
       "NT          224280  \n",
       "NU          141192  \n",
       "ON        94066632  \n",
       "PE          897696  \n",
       "QC        53073360  \n",
       "SK         6970752  \n",
       "YT          206352  \n",
       "\n",
       "[13 rows x 34 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q=[\"pop5to9_2019\",\"pop10to14_2019\",\"pop15to19_2019\"]\n",
    "w=[\"pop25to29_2019\",\"pop30to34_2019\",\"pop35to39_2019\",\"pop40to44_2019\",\"pop45to49_2019\"]\n",
    "e=[\"pop55to59_2019\",\"pop60to64_2019\",\"pop65to69_2019\",\"pop70to74_2019\",\"pop75to79_2019\",\"pop80to84_2019\",\"pop85older\"]\n",
    "for i in q:\n",
    "    province_view[\"teens\"]= np.add(province_view[\"pop0to4_2019\"],province_view[i])\n",
    "for i in w:\n",
    "    province_view[\"young adults\"]= np.add(province_view[\"pop20to24_2019\"],province_view[i])\n",
    "for i in e:\n",
    "    province_view[\"adults\"]= np.add(province_view[\"pop50to54_2019\"],province_view[i])    \n",
    "province_view"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {
    "scrolled": true
   },
   "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>casecount</th>\n",
       "      <th>deaths</th>\n",
       "      <th>recovered</th>\n",
       "      <th>median age</th>\n",
       "      <th>teens</th>\n",
       "      <th>young adults</th>\n",
       "      <th>adults</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>province</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>QC</td>\n",
       "      <td>1197552</td>\n",
       "      <td>52916.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>42.638889</td>\n",
       "      <td>57714192</td>\n",
       "      <td>69322824</td>\n",
       "      <td>53073360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>ON</td>\n",
       "      <td>754623</td>\n",
       "      <td>38188.0</td>\n",
       "      <td>170259.0</td>\n",
       "      <td>43.677941</td>\n",
       "      <td>109143864</td>\n",
       "      <td>136315944</td>\n",
       "      <td>94066632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AB</td>\n",
       "      <td>184709</td>\n",
       "      <td>3692.0</td>\n",
       "      <td>66081.0</td>\n",
       "      <td>37.320000</td>\n",
       "      <td>38210112</td>\n",
       "      <td>40815864</td>\n",
       "      <td>24727104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>BC</td>\n",
       "      <td>115680</td>\n",
       "      <td>5196.0</td>\n",
       "      <td>69513.0</td>\n",
       "      <td>42.920000</td>\n",
       "      <td>34281576</td>\n",
       "      <td>45465120</td>\n",
       "      <td>25170912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>NS</td>\n",
       "      <td>43414</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>46.975000</td>\n",
       "      <td>6314112</td>\n",
       "      <td>8277624</td>\n",
       "      <td>6078456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>SK</td>\n",
       "      <td>22279</td>\n",
       "      <td>276.0</td>\n",
       "      <td>14526.0</td>\n",
       "      <td>36.816667</td>\n",
       "      <td>11136672</td>\n",
       "      <td>10673352</td>\n",
       "      <td>6970752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>NL</td>\n",
       "      <td>17810</td>\n",
       "      <td>66.0</td>\n",
       "      <td>4656.0</td>\n",
       "      <td>46.950000</td>\n",
       "      <td>3357072</td>\n",
       "      <td>4439376</td>\n",
       "      <td>3509064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>MB</td>\n",
       "      <td>17524</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>36.020000</td>\n",
       "      <td>12579192</td>\n",
       "      <td>13007448</td>\n",
       "      <td>8098704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>NB</td>\n",
       "      <td>8242</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>48.300000</td>\n",
       "      <td>5124960</td>\n",
       "      <td>6423480</td>\n",
       "      <td>5076432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>PE</td>\n",
       "      <td>1815</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1447.0</td>\n",
       "      <td>43.400000</td>\n",
       "      <td>1045368</td>\n",
       "      <td>1254600</td>\n",
       "      <td>897696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>YT</td>\n",
       "      <td>654</td>\n",
       "      <td>0.0</td>\n",
       "      <td>453.0</td>\n",
       "      <td>39.900000</td>\n",
       "      <td>298368</td>\n",
       "      <td>378936</td>\n",
       "      <td>206352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>NT</td>\n",
       "      <td>358</td>\n",
       "      <td>0.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>34.600000</td>\n",
       "      <td>390672</td>\n",
       "      <td>419184</td>\n",
       "      <td>224280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>NU</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>27.200000</td>\n",
       "      <td>508608</td>\n",
       "      <td>361008</td>\n",
       "      <td>141192</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          casecount   deaths  recovered  median age      teens  young adults  \\\n",
       "province                                                                       \n",
       "QC          1197552  52916.0        0.0   42.638889   57714192      69322824   \n",
       "ON           754623  38188.0   170259.0   43.677941  109143864     136315944   \n",
       "AB           184709   3692.0    66081.0   37.320000   38210112      40815864   \n",
       "BC           115680   5196.0    69513.0   42.920000   34281576      45465120   \n",
       "NS            43414      0.0        0.0   46.975000    6314112       8277624   \n",
       "SK            22279    276.0    14526.0   36.816667   11136672      10673352   \n",
       "NL            17810     66.0     4656.0   46.950000    3357072       4439376   \n",
       "MB            17524      0.0        0.0   36.020000   12579192      13007448   \n",
       "NB             8242      0.0        0.0   48.300000    5124960       6423480   \n",
       "PE             1815      0.0     1447.0   43.400000    1045368       1254600   \n",
       "YT              654      0.0      453.0   39.900000     298368        378936   \n",
       "NT              358      0.0      210.0   34.600000     390672        419184   \n",
       "NU                0      0.0        0.0   27.200000     508608        361008   \n",
       "\n",
       "            adults  \n",
       "province            \n",
       "QC        53073360  \n",
       "ON        94066632  \n",
       "AB        24727104  \n",
       "BC        25170912  \n",
       "NS         6078456  \n",
       "SK         6970752  \n",
       "NL         3509064  \n",
       "MB         8098704  \n",
       "NB         5076432  \n",
       "PE          897696  \n",
       "YT          206352  \n",
       "NT          224280  \n",
       "NU          141192  "
      ]
     },
     "execution_count": 159,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "province_view[['casecount','deaths','recovered','median age','teens','young adults','adults']].sort_values('casecount', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFBFD0CC8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFC0F0448>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFC124B48>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFC15E508>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "col = [\"teens\",'young adults', \"adults\"]\n",
    "province_view[col].hist(figsize=(10,4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20cfd547ac8>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(province_view[\"young adults\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "module 'seaborn' has no attribute 'hist'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-46-503384da3878>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0msns\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mhist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mprovince_view\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mcol\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m: module 'seaborn' has no attribute 'hist'"
     ]
    }
   ],
   "source": [
    "sns.hist(province_view[col])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20cff911208>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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/5phSyqUT3HTIP1srpTwK/PZ01+FZ1NQx9ZsQ3wXePhvHSCPiRcBofarJs4EbJzg2J80Z7gmrIyLiFOCLwO2z+CbV8cBtdeyfo/qCUGlOc09YkhL5xpwkJTLCkpTICEtSIiMsSYmMsCQl+n83N1uy5fpu4QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(province_view[\"young adults\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20c81276b88>"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(x=\"young adults\", data= province_view)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFEFE9488>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x0000020CFF2D0748>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x2520 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "province_view[[\"teens\",\"young adults\"]].plot(kind=\"density\", subplots=True, layout=(2,1), sharex= False, figsize=(10,35))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "province\n",
      "AB    103753080\n",
      "BC    104917608\n",
      "MB     33685344\n",
      "NB     16624872\n",
      "NL     11305512\n",
      "NS     20670192\n",
      "NT      1034136\n",
      "NU      1010808\n",
      "ON    339526440\n",
      "PE      3197664\n",
      "QC    180110376\n",
      "SK     28780776\n",
      "YT       883656\n",
      "dtype: int64\n",
      "province\n",
      "AB    103753080\n",
      "BC    104917608\n",
      "MB     33685344\n",
      "NB     16624872\n",
      "NL     11305512\n",
      "NS     20670192\n",
      "NT      1034136\n",
      "NU      1010808\n",
      "ON    339526440\n",
      "PE      3197664\n",
      "QC    180110376\n",
      "SK     28780776\n",
      "YT       883656\n",
      "dtype: int64\n",
      "province\n",
      "AB    103753080\n",
      "BC    104917608\n",
      "MB     33685344\n",
      "NB     16624872\n",
      "NL     11305512\n",
      "NS     20670192\n",
      "NT      1034136\n",
      "NU      1010808\n",
      "ON    339526440\n",
      "PE      3197664\n",
      "QC    180110376\n",
      "SK     28780776\n",
      "YT       883656\n",
      "dtype: int64\n",
      "province\n",
      "AB    103753080\n",
      "BC    104917608\n",
      "MB     33685344\n",
      "NB     16624872\n",
      "NL     11305512\n",
      "NS     20670192\n",
      "NT      1034136\n",
      "NU      1010808\n",
      "ON    339526440\n",
      "PE      3197664\n",
      "QC    180110376\n",
      "SK     28780776\n",
      "YT       883656\n",
      "dtype: int64\n",
      "province\n",
      "AB    103753080\n",
      "BC    104917608\n",
      "MB     33685344\n",
      "NB     16624872\n",
      "NL     11305512\n",
      "NS     20670192\n",
      "NT      1034136\n",
      "NU      1010808\n",
      "ON    339526440\n",
      "PE      3197664\n",
      "QC    180110376\n",
      "SK     28780776\n",
      "YT       883656\n",
      "dtype: int64\n",
      "province\n",
      "AB    103753080\n",
      "BC    104917608\n",
      "MB     33685344\n",
      "NB     16624872\n",
      "NL     11305512\n",
      "NS     20670192\n",
      "NT      1034136\n",
      "NU      1010808\n",
      "ON    339526440\n",
      "PE      3197664\n",
      "QC    180110376\n",
      "SK     28780776\n",
      "YT       883656\n",
      "dtype: int64\n",
      "province\n",
      "AB    103753080\n",
      "BC    104917608\n",
      "MB     33685344\n",
      "NB     16624872\n",
      "NL     11305512\n",
      "NS     20670192\n",
      "NT      1034136\n",
      "NU      1010808\n",
      "ON    339526440\n",
      "PE      3197664\n",
      "QC    180110376\n",
      "SK     28780776\n",
      "YT       883656\n",
      "dtype: int64\n",
      "province\n",
      "AB    103753080\n",
      "BC    104917608\n",
      "MB     33685344\n",
      "NB     16624872\n",
      "NL     11305512\n",
      "NS     20670192\n",
      "NT      1034136\n",
      "NU      1010808\n",
      "ON    339526440\n",
      "PE      3197664\n",
      "QC    180110376\n",
      "SK     28780776\n",
      "YT       883656\n",
      "dtype: int64\n",
      "province\n",
      "AB    103753080\n",
      "BC    104917608\n",
      "MB     33685344\n",
      "NB     16624872\n",
      "NL     11305512\n",
      "NS     20670192\n",
      "NT      1034136\n",
      "NU      1010808\n",
      "ON    339526440\n",
      "PE      3197664\n",
      "QC    180110376\n",
      "SK     28780776\n",
      "YT       883656\n",
      "dtype: int64\n",
      "province\n",
      "AB    103753080\n",
      "BC    104917608\n",
      "MB     33685344\n",
      "NB     16624872\n",
      "NL     11305512\n",
      "NS     20670192\n",
      "NT      1034136\n",
      "NU      1010808\n",
      "ON    339526440\n",
      "PE      3197664\n",
      "QC    180110376\n",
      "SK     28780776\n",
      "YT       883656\n",
      "dtype: int64\n",
      "province\n",
      "AB    103753080\n",
      "BC    104917608\n",
      "MB     33685344\n",
      "NB     16624872\n",
      "NL     11305512\n",
      "NS     20670192\n",
      "NT      1034136\n",
      "NU      1010808\n",
      "ON    339526440\n",
      "PE      3197664\n",
      "QC    180110376\n",
      "SK     28780776\n",
      "YT       883656\n",
      "dtype: int64\n",
      "province\n",
      "AB    103753080\n",
      "BC    104917608\n",
      "MB     33685344\n",
      "NB     16624872\n",
      "NL     11305512\n",
      "NS     20670192\n",
      "NT      1034136\n",
      "NU      1010808\n",
      "ON    339526440\n",
      "PE      3197664\n",
      "QC    180110376\n",
      "SK     28780776\n",
      "YT       883656\n",
      "dtype: int64\n",
      "province\n",
      "AB    103753080\n",
      "BC    104917608\n",
      "MB     33685344\n",
      "NB     16624872\n",
      "NL     11305512\n",
      "NS     20670192\n",
      "NT      1034136\n",
      "NU      1010808\n",
      "ON    339526440\n",
      "PE      3197664\n",
      "QC    180110376\n",
      "SK     28780776\n",
      "YT       883656\n",
      "dtype: int64\n",
      "this is the end\n"
     ]
    }
   ],
   "source": [
    "for x in province_view.iterrows():\n",
    "    cols =[\"teens\",\"young adults\",\"adults\"]\n",
    "    totals = sum(province_view[x] for x in cols)\n",
    "    print(totals)\n",
    "print(\"this is the end\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "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>objectid</th>\n",
       "      <th>hr_uid</th>\n",
       "      <th>province</th>\n",
       "      <th>engname</th>\n",
       "      <th>frename</th>\n",
       "      <th>casecount</th>\n",
       "      <th>deaths</th>\n",
       "      <th>recovered</th>\n",
       "      <th>tests</th>\n",
       "      <th>totalpop2019</th>\n",
       "      <th>...</th>\n",
       "      <th>pop80to84_2019</th>\n",
       "      <th>pop85older</th>\n",
       "      <th>averageage_2019</th>\n",
       "      <th>medianage_2019</th>\n",
       "      <th>shape_area</th>\n",
       "      <th>shape_length</th>\n",
       "      <th>last_updated</th>\n",
       "      <th>sourceurl</th>\n",
       "      <th>globalid</th>\n",
       "      <th>retrieved_at</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>29</td>\n",
       "      <td>2406</td>\n",
       "      <td>QC</td>\n",
       "      <td>Région de Montréal</td>\n",
       "      <td>Région de Montréal</td>\n",
       "      <td>12487</td>\n",
       "      <td>1039.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1856818</td>\n",
       "      <td>...</td>\n",
       "      <td>40649</td>\n",
       "      <td>50237</td>\n",
       "      <td>40.6</td>\n",
       "      <td>39.0</td>\n",
       "      <td>9.562571e+08</td>\n",
       "      <td>247870.831035</td>\n",
       "      <td>1588100520000</td>\n",
       "      <td>https://www.quebec.ca/en/health/health-issues/...</td>\n",
       "      <td>8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4</td>\n",
       "      <td>2020-04-29 14:16:03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>114</td>\n",
       "      <td>29</td>\n",
       "      <td>2406</td>\n",
       "      <td>QC</td>\n",
       "      <td>Région de Montréal</td>\n",
       "      <td>Région de Montréal</td>\n",
       "      <td>12487</td>\n",
       "      <td>1039.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1856818</td>\n",
       "      <td>...</td>\n",
       "      <td>40649</td>\n",
       "      <td>50237</td>\n",
       "      <td>40.6</td>\n",
       "      <td>39.0</td>\n",
       "      <td>9.562571e+08</td>\n",
       "      <td>247870.831035</td>\n",
       "      <td>1588100520000</td>\n",
       "      <td>https://www.quebec.ca/en/health/health-issues/...</td>\n",
       "      <td>8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4</td>\n",
       "      <td>2020-04-29 07:15:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>206</td>\n",
       "      <td>29</td>\n",
       "      <td>2406</td>\n",
       "      <td>QC</td>\n",
       "      <td>Région de Montréal</td>\n",
       "      <td>Région de Montréal</td>\n",
       "      <td>12487</td>\n",
       "      <td>1039.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1856818</td>\n",
       "      <td>...</td>\n",
       "      <td>40649</td>\n",
       "      <td>50237</td>\n",
       "      <td>40.6</td>\n",
       "      <td>39.0</td>\n",
       "      <td>9.562571e+08</td>\n",
       "      <td>247870.831035</td>\n",
       "      <td>1588100520000</td>\n",
       "      <td>https://www.quebec.ca/en/health/health-issues/...</td>\n",
       "      <td>8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4</td>\n",
       "      <td>2020-04-28 21:15:55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>390</td>\n",
       "      <td>29</td>\n",
       "      <td>2406</td>\n",
       "      <td>QC</td>\n",
       "      <td>Région de Montréal</td>\n",
       "      <td>Région de Montréal</td>\n",
       "      <td>12034</td>\n",
       "      <td>983.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1856818</td>\n",
       "      <td>...</td>\n",
       "      <td>40649</td>\n",
       "      <td>50237</td>\n",
       "      <td>40.6</td>\n",
       "      <td>39.0</td>\n",
       "      <td>9.562571e+08</td>\n",
       "      <td>247870.831035</td>\n",
       "      <td>1588011840000</td>\n",
       "      <td>https://www.quebec.ca/en/health/health-issues/...</td>\n",
       "      <td>8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4</td>\n",
       "      <td>2020-04-28 07:16:04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>482</td>\n",
       "      <td>29</td>\n",
       "      <td>2406</td>\n",
       "      <td>QC</td>\n",
       "      <td>Région de Montréal</td>\n",
       "      <td>Région de Montréal</td>\n",
       "      <td>12034</td>\n",
       "      <td>983.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1856818</td>\n",
       "      <td>...</td>\n",
       "      <td>40649</td>\n",
       "      <td>50237</td>\n",
       "      <td>40.6</td>\n",
       "      <td>39.0</td>\n",
       "      <td>9.562571e+08</td>\n",
       "      <td>247870.831035</td>\n",
       "      <td>1588011840000</td>\n",
       "      <td>https://www.quebec.ca/en/health/health-issues/...</td>\n",
       "      <td>8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4</td>\n",
       "      <td>2020-04-27 21:16:06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>298</td>\n",
       "      <td>29</td>\n",
       "      <td>2406</td>\n",
       "      <td>QC</td>\n",
       "      <td>Région de Montréal</td>\n",
       "      <td>Région de Montréal</td>\n",
       "      <td>12034</td>\n",
       "      <td>983.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1856818</td>\n",
       "      <td>...</td>\n",
       "      <td>40649</td>\n",
       "      <td>50237</td>\n",
       "      <td>40.6</td>\n",
       "      <td>39.0</td>\n",
       "      <td>9.562571e+08</td>\n",
       "      <td>247870.831035</td>\n",
       "      <td>1588011840000</td>\n",
       "      <td>https://www.quebec.ca/en/health/health-issues/...</td>\n",
       "      <td>8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4</td>\n",
       "      <td>2020-04-28 14:16:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>574</td>\n",
       "      <td>29</td>\n",
       "      <td>2406</td>\n",
       "      <td>QC</td>\n",
       "      <td>Région de Montréal</td>\n",
       "      <td>Région de Montréal</td>\n",
       "      <td>11621</td>\n",
       "      <td>938.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1856818</td>\n",
       "      <td>...</td>\n",
       "      <td>40649</td>\n",
       "      <td>50237</td>\n",
       "      <td>40.6</td>\n",
       "      <td>39.0</td>\n",
       "      <td>9.562571e+08</td>\n",
       "      <td>247870.831035</td>\n",
       "      <td>1587925560000</td>\n",
       "      <td>https://www.quebec.ca/en/health/health-issues/...</td>\n",
       "      <td>8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4</td>\n",
       "      <td>2020-04-27 14:15:59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>758</td>\n",
       "      <td>29</td>\n",
       "      <td>2406</td>\n",
       "      <td>QC</td>\n",
       "      <td>Région de Montréal</td>\n",
       "      <td>Région de Montréal</td>\n",
       "      <td>11621</td>\n",
       "      <td>938.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1856818</td>\n",
       "      <td>...</td>\n",
       "      <td>40649</td>\n",
       "      <td>50237</td>\n",
       "      <td>40.6</td>\n",
       "      <td>39.0</td>\n",
       "      <td>9.562571e+08</td>\n",
       "      <td>247870.831035</td>\n",
       "      <td>1587925560000</td>\n",
       "      <td>https://www.quebec.ca/en/health/health-issues/...</td>\n",
       "      <td>8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4</td>\n",
       "      <td>2020-04-26 21:15:58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>666</td>\n",
       "      <td>29</td>\n",
       "      <td>2406</td>\n",
       "      <td>QC</td>\n",
       "      <td>Région de Montréal</td>\n",
       "      <td>Région de Montréal</td>\n",
       "      <td>11621</td>\n",
       "      <td>938.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1856818</td>\n",
       "      <td>...</td>\n",
       "      <td>40649</td>\n",
       "      <td>50237</td>\n",
       "      <td>40.6</td>\n",
       "      <td>39.0</td>\n",
       "      <td>9.562571e+08</td>\n",
       "      <td>247870.831035</td>\n",
       "      <td>1587925560000</td>\n",
       "      <td>https://www.quebec.ca/en/health/health-issues/...</td>\n",
       "      <td>8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4</td>\n",
       "      <td>2020-04-27 07:16:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1034</td>\n",
       "      <td>29</td>\n",
       "      <td>2406</td>\n",
       "      <td>QC</td>\n",
       "      <td>Région de Montréal</td>\n",
       "      <td>Région de Montréal</td>\n",
       "      <td>11161</td>\n",
       "      <td>895.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1856818</td>\n",
       "      <td>...</td>\n",
       "      <td>40649</td>\n",
       "      <td>50237</td>\n",
       "      <td>40.6</td>\n",
       "      <td>39.0</td>\n",
       "      <td>9.562571e+08</td>\n",
       "      <td>247870.831035</td>\n",
       "      <td>1587839820000</td>\n",
       "      <td>https://www.quebec.ca/en/health/health-issues/...</td>\n",
       "      <td>8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4</td>\n",
       "      <td>2020-04-25 21:16:12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      objectid  hr_uid province             engname             frename  \\\n",
       "22          29    2406       QC  Région de Montréal  Région de Montréal   \n",
       "114         29    2406       QC  Région de Montréal  Région de Montréal   \n",
       "206         29    2406       QC  Région de Montréal  Région de Montréal   \n",
       "390         29    2406       QC  Région de Montréal  Région de Montréal   \n",
       "482         29    2406       QC  Région de Montréal  Région de Montréal   \n",
       "298         29    2406       QC  Région de Montréal  Région de Montréal   \n",
       "574         29    2406       QC  Région de Montréal  Région de Montréal   \n",
       "758         29    2406       QC  Région de Montréal  Région de Montréal   \n",
       "666         29    2406       QC  Région de Montréal  Région de Montréal   \n",
       "1034        29    2406       QC  Région de Montréal  Région de Montréal   \n",
       "\n",
       "      casecount  deaths  recovered  tests  totalpop2019  ...  pop80to84_2019  \\\n",
       "22        12487  1039.0        NaN    NaN       1856818  ...           40649   \n",
       "114       12487  1039.0        NaN    NaN       1856818  ...           40649   \n",
       "206       12487  1039.0        NaN    NaN       1856818  ...           40649   \n",
       "390       12034   983.0        NaN    NaN       1856818  ...           40649   \n",
       "482       12034   983.0        NaN    NaN       1856818  ...           40649   \n",
       "298       12034   983.0        NaN    NaN       1856818  ...           40649   \n",
       "574       11621   938.0        NaN    NaN       1856818  ...           40649   \n",
       "758       11621   938.0        NaN    NaN       1856818  ...           40649   \n",
       "666       11621   938.0        NaN    NaN       1856818  ...           40649   \n",
       "1034      11161   895.0        NaN    NaN       1856818  ...           40649   \n",
       "\n",
       "      pop85older  averageage_2019  medianage_2019    shape_area  \\\n",
       "22         50237             40.6            39.0  9.562571e+08   \n",
       "114        50237             40.6            39.0  9.562571e+08   \n",
       "206        50237             40.6            39.0  9.562571e+08   \n",
       "390        50237             40.6            39.0  9.562571e+08   \n",
       "482        50237             40.6            39.0  9.562571e+08   \n",
       "298        50237             40.6            39.0  9.562571e+08   \n",
       "574        50237             40.6            39.0  9.562571e+08   \n",
       "758        50237             40.6            39.0  9.562571e+08   \n",
       "666        50237             40.6            39.0  9.562571e+08   \n",
       "1034       50237             40.6            39.0  9.562571e+08   \n",
       "\n",
       "       shape_length   last_updated  \\\n",
       "22    247870.831035  1588100520000   \n",
       "114   247870.831035  1588100520000   \n",
       "206   247870.831035  1588100520000   \n",
       "390   247870.831035  1588011840000   \n",
       "482   247870.831035  1588011840000   \n",
       "298   247870.831035  1588011840000   \n",
       "574   247870.831035  1587925560000   \n",
       "758   247870.831035  1587925560000   \n",
       "666   247870.831035  1587925560000   \n",
       "1034  247870.831035  1587839820000   \n",
       "\n",
       "                                              sourceurl  \\\n",
       "22    https://www.quebec.ca/en/health/health-issues/...   \n",
       "114   https://www.quebec.ca/en/health/health-issues/...   \n",
       "206   https://www.quebec.ca/en/health/health-issues/...   \n",
       "390   https://www.quebec.ca/en/health/health-issues/...   \n",
       "482   https://www.quebec.ca/en/health/health-issues/...   \n",
       "298   https://www.quebec.ca/en/health/health-issues/...   \n",
       "574   https://www.quebec.ca/en/health/health-issues/...   \n",
       "758   https://www.quebec.ca/en/health/health-issues/...   \n",
       "666   https://www.quebec.ca/en/health/health-issues/...   \n",
       "1034  https://www.quebec.ca/en/health/health-issues/...   \n",
       "\n",
       "                                  globalid         retrieved_at  \n",
       "22    8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4  2020-04-29 14:16:03  \n",
       "114   8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4  2020-04-29 07:15:57  \n",
       "206   8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4  2020-04-28 21:15:55  \n",
       "390   8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4  2020-04-28 07:16:04  \n",
       "482   8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4  2020-04-27 21:16:06  \n",
       "298   8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4  2020-04-28 14:16:15  \n",
       "574   8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4  2020-04-27 14:15:59  \n",
       "758   8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4  2020-04-26 21:15:58  \n",
       "666   8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4  2020-04-27 07:16:00  \n",
       "1034  8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4  2020-04-25 21:16:12  \n",
       "\n",
       "[10 rows x 36 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_case_count.sort_values(\"casecount\", ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2020-04-19 07:15:00    92\n",
       "2020-04-11 21:15:00    92\n",
       "2020-04-18 07:15:00    92\n",
       "2020-04-24 21:15:58    92\n",
       "2020-04-20 21:16:08    92\n",
       "                       ..\n",
       "2020-04-22 14:15:57    92\n",
       "2020-04-06 04:15:00    92\n",
       "2020-04-13 21:15:00    92\n",
       "2020-04-14 14:15:00    92\n",
       "2020-04-25 21:16:12    92\n",
       "Name: retrieved_at, Length: 72, dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_case_count['retrieved_at'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'canada_case_count' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-1-0d7289b62632>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mcanada_case_count\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0miloc\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;36m3\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m:\u001b[0m\u001b[1;36m15\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m: name 'canada_case_count' is not defined"
     ]
    }
   ],
   "source": [
    "canada_case_count.iloc[:3, :15]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "x= ['pop0to4_2019',\n",
    "       'pop5to9_2019', 'pop10to14_2019', 'pop15to19_2019', 'pop20to24_2019',\n",
    "       'pop25to29_2019', 'pop30to34_2019', 'pop35to39_2019', 'pop40to44_2019',\n",
    "       'pop45to49_2019', 'pop50to54_2019', 'pop55to59_2019', 'pop60to64_2019',\n",
    "       'pop65to69_2019', 'pop70to74_2019', 'pop75to79_2019', 'pop80to84_2019',\n",
    "       'pop85older']\n",
    "y= canada_case_count[\"totalpop2019\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in x:\n",
    "    canada_case_count[i] = np.divide(canada_case_count[i],y) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>pop0to4_2019</th>\n",
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       "      <th>pop10to14_2019</th>\n",
       "      <th>pop15to19_2019</th>\n",
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       "      <td>0.052139</td>\n",
       "      <td>0.054440</td>\n",
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       "      <td>0.051071</td>\n",
       "      <td>0.055719</td>\n",
       "      <td>0.057315</td>\n",
       "      <td>0.052107</td>\n",
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       "      <td>0.051893</td>\n",
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       "      <td>4.162376e-07</td>\n",
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       "      <td>0.056589</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   pop0to4_2019  pop5to9_2019  pop10to14_2019  pop15to19_2019  pop20to24_2019  \\\n",
       "0  8.766314e-08  8.930426e-08        0.052139        0.054440        0.068289   \n",
       "1  3.139646e-07  3.241741e-07        0.050201        0.051071        0.055719   \n",
       "2  4.087962e-07  4.162376e-07        0.059134        0.059251        0.064300   \n",
       "3  4.743558e-07  4.990656e-07        0.056589        0.058165        0.059903   \n",
       "4  2.186747e-07  2.189554e-07        0.047251        0.047541        0.062403   \n",
       "\n",
       "   pop25to29_2019  pop30to34_2019  pop35to39_2019  pop40to44_2019  \\\n",
       "0        0.077958        0.072230        0.066757        0.061344   \n",
       "1        0.057315        0.052107        0.051838        0.051893   \n",
       "2        0.062076        0.052483        0.052344        0.052593   \n",
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       "4        0.079654        0.072100        0.064444        0.058786   \n",
       "\n",
       "   pop45to49_2019  \n",
       "0        0.061431  \n",
       "1        0.057522  \n",
       "2        0.055359  \n",
       "3        0.057206  \n",
       "4        0.058762  "
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_case_count.iloc[:5, 10:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>objectid</th>\n",
       "      <th>hr_uid</th>\n",
       "      <th>province</th>\n",
       "      <th>engname</th>\n",
       "      <th>frename</th>\n",
       "      <th>casecount</th>\n",
       "      <th>deaths</th>\n",
       "      <th>recovered</th>\n",
       "      <th>tests</th>\n",
       "      <th>totalpop2019</th>\n",
       "      <th>...</th>\n",
       "      <th>pop80to84_2019</th>\n",
       "      <th>pop85older</th>\n",
       "      <th>averageage_2019</th>\n",
       "      <th>medianage_2019</th>\n",
       "      <th>shape_area</th>\n",
       "      <th>shape_length</th>\n",
       "      <th>last_updated</th>\n",
       "      <th>sourceurl</th>\n",
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       "      <td>2020-04-29 07:15:57</td>\n",
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       "      <td>Région de Montréal</td>\n",
       "      <td>12487</td>\n",
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       "      <td>1856818</td>\n",
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       "      <td>40.6</td>\n",
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       "      <td>8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4</td>\n",
       "      <td>2020-04-28 21:15:55</td>\n",
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       "      <td>https://www.quebec.ca/en/health/health-issues/...</td>\n",
       "      <td>8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4</td>\n",
       "      <td>2020-04-28 14:16:15</td>\n",
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       "      <td>Région de Montréal</td>\n",
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       "      <td>8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4</td>\n",
       "      <td>2020-04-28 07:16:04</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     objectid  hr_uid province             engname             frename  \\\n",
       "22         29    2406       QC  Région de Montréal  Région de Montréal   \n",
       "114        29    2406       QC  Région de Montréal  Région de Montréal   \n",
       "206        29    2406       QC  Région de Montréal  Région de Montréal   \n",
       "298        29    2406       QC  Région de Montréal  Région de Montréal   \n",
       "390        29    2406       QC  Région de Montréal  Région de Montréal   \n",
       "\n",
       "     casecount  deaths  recovered  tests  totalpop2019  ...  pop80to84_2019  \\\n",
       "22       12487  1039.0        NaN    NaN       1856818  ...        0.021892   \n",
       "114      12487  1039.0        NaN    NaN       1856818  ...        0.021892   \n",
       "206      12487  1039.0        NaN    NaN       1856818  ...        0.021892   \n",
       "298      12034   983.0        NaN    NaN       1856818  ...        0.021892   \n",
       "390      12034   983.0        NaN    NaN       1856818  ...        0.021892   \n",
       "\n",
       "     pop85older  averageage_2019  medianage_2019    shape_area   shape_length  \\\n",
       "22     0.027055             40.6            39.0  9.562571e+08  247870.831035   \n",
       "114    0.027055             40.6            39.0  9.562571e+08  247870.831035   \n",
       "206    0.027055             40.6            39.0  9.562571e+08  247870.831035   \n",
       "298    0.027055             40.6            39.0  9.562571e+08  247870.831035   \n",
       "390    0.027055             40.6            39.0  9.562571e+08  247870.831035   \n",
       "\n",
       "      last_updated                                          sourceurl  \\\n",
       "22   1588100520000  https://www.quebec.ca/en/health/health-issues/...   \n",
       "114  1588100520000  https://www.quebec.ca/en/health/health-issues/...   \n",
       "206  1588100520000  https://www.quebec.ca/en/health/health-issues/...   \n",
       "298  1588011840000  https://www.quebec.ca/en/health/health-issues/...   \n",
       "390  1588011840000  https://www.quebec.ca/en/health/health-issues/...   \n",
       "\n",
       "                                 globalid         retrieved_at  \n",
       "22   8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4  2020-04-29 14:16:03  \n",
       "114  8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4  2020-04-29 07:15:57  \n",
       "206  8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4  2020-04-28 21:15:55  \n",
       "298  8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4  2020-04-28 14:16:15  \n",
       "390  8826f734-d4c3-4ec2-ac2f-5abd6c6ab2d4  2020-04-28 07:16:04  \n",
       "\n",
       "[5 rows x 36 columns]"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_case_count.sort_values(by=['casecount',\"tests\"], ascending=[False,False]).head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>objectid</th>\n",
       "      <th>hr_uid</th>\n",
       "      <th>province</th>\n",
       "      <th>engname</th>\n",
       "      <th>frename</th>\n",
       "      <th>casecount</th>\n",
       "      <th>deaths</th>\n",
       "      <th>recovered</th>\n",
       "      <th>tests</th>\n",
       "      <th>totalpop2019</th>\n",
       "      <th>pop0to4_2019</th>\n",
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       "      <th>pop10to14_2019</th>\n",
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       "      <th>pop25to29_2019</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3537</td>\n",
       "      <td>ON</td>\n",
       "      <td>City of Hamilton Health Unit</td>\n",
       "      <td>Circonscription sanitaire de la cité de Hamilton</td>\n",
       "      <td>421</td>\n",
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       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3538</td>\n",
       "      <td>ON</td>\n",
       "      <td>Hastings and Prince Edward Counties Health Unit</td>\n",
       "      <td>Circonscription sanitaire des comtés de Hastin...</td>\n",
       "      <td>39</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>144779</td>\n",
       "      <td>0.045455</td>\n",
       "      <td>0.046934</td>\n",
       "      <td>7268</td>\n",
       "      <td>7394</td>\n",
       "      <td>8067</td>\n",
       "      <td>8298</td>\n",
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       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3539</td>\n",
       "      <td>ON</td>\n",
       "      <td>Huron Perth Public Health Unit</td>\n",
       "      <td>Circonscription sanitaire du comté de Huron Perth</td>\n",
       "      <td>44</td>\n",
       "      <td>4.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1413.0</td>\n",
       "      <td>136672</td>\n",
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       "      <td>0.056888</td>\n",
       "      <td>8082</td>\n",
       "      <td>8098</td>\n",
       "      <td>8788</td>\n",
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      ],
      "text/plain": [
       "   objectid  hr_uid province                                          engname  \\\n",
       "0         1    3537       ON                     City of Hamilton Health Unit   \n",
       "1         2    3538       ON  Hastings and Prince Edward Counties Health Unit   \n",
       "2         3    3539       ON                   Huron Perth Public Health Unit   \n",
       "\n",
       "                                             frename  casecount  deaths  \\\n",
       "0   Circonscription sanitaire de la cité de Hamilton        421    19.0   \n",
       "1  Circonscription sanitaire des comtés de Hastin...         39     2.0   \n",
       "2  Circonscription sanitaire du comté de Huron Perth         44     4.0   \n",
       "\n",
       "   recovered   tests  totalpop2019  pop0to4_2019  pop5to9_2019  \\\n",
       "0      237.0  3758.0        576272      0.050518      0.051464   \n",
       "1       19.0     NaN        144779      0.045455      0.046934   \n",
       "2       31.0  1413.0        136672      0.055871      0.056888   \n",
       "\n",
       "   pop10to14_2019  pop15to19_2019  pop20to24_2019  pop25to29_2019  \n",
       "0           30046           31372           39353           44925  \n",
       "1            7268            7394            8067            8298  \n",
       "2            8082            8098            8788            8484  "
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_case_count.iloc[:3, :16]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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