Covid19_ITLAY.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "96535480",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f10a62b1",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('covid-nationality.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d041a48e",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>date</th>\n",
       "      <th>state</th>\n",
       "      <th>hospitalized_with_symptoms</th>\n",
       "      <th>intensive_care</th>\n",
       "      <th>total_hospitalized</th>\n",
       "      <th>home_quarantine</th>\n",
       "      <th>total_confirmed_cases</th>\n",
       "      <th>variation_total_confirmed</th>\n",
       "      <th>new_confirmed_cases</th>\n",
       "      <th>recovered</th>\n",
       "      <th>deaths</th>\n",
       "      <th>total_cases</th>\n",
       "      <th>swabs_made</th>\n",
       "      <th>casi_testati</th>\n",
       "      <th>note_it</th>\n",
       "      <th>note_en</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2020-02-24T18:00:00</td>\n",
       "      <td>ITA</td>\n",
       "      <td>101</td>\n",
       "      <td>26</td>\n",
       "      <td>127</td>\n",
       "      <td>94</td>\n",
       "      <td>221</td>\n",
       "      <td>0</td>\n",
       "      <td>221</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>229</td>\n",
       "      <td>4324</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2020-02-25T18:00:00</td>\n",
       "      <td>ITA</td>\n",
       "      <td>114</td>\n",
       "      <td>35</td>\n",
       "      <td>150</td>\n",
       "      <td>162</td>\n",
       "      <td>311</td>\n",
       "      <td>90</td>\n",
       "      <td>93</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>322</td>\n",
       "      <td>8623</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2020-02-26T18:00:00</td>\n",
       "      <td>ITA</td>\n",
       "      <td>128</td>\n",
       "      <td>36</td>\n",
       "      <td>164</td>\n",
       "      <td>221</td>\n",
       "      <td>385</td>\n",
       "      <td>74</td>\n",
       "      <td>78</td>\n",
       "      <td>3</td>\n",
       "      <td>12</td>\n",
       "      <td>400</td>\n",
       "      <td>9587</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>2020-02-27T18:00:00</td>\n",
       "      <td>ITA</td>\n",
       "      <td>248</td>\n",
       "      <td>56</td>\n",
       "      <td>304</td>\n",
       "      <td>284</td>\n",
       "      <td>588</td>\n",
       "      <td>203</td>\n",
       "      <td>250</td>\n",
       "      <td>45</td>\n",
       "      <td>17</td>\n",
       "      <td>650</td>\n",
       "      <td>12014</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>2020-02-28T18:00:00</td>\n",
       "      <td>ITA</td>\n",
       "      <td>345</td>\n",
       "      <td>64</td>\n",
       "      <td>409</td>\n",
       "      <td>412</td>\n",
       "      <td>821</td>\n",
       "      <td>233</td>\n",
       "      <td>238</td>\n",
       "      <td>46</td>\n",
       "      <td>21</td>\n",
       "      <td>888</td>\n",
       "      <td>15695</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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      ],
      "text/plain": [
       "   Unnamed: 0                 date state  hospitalized_with_symptoms  \\\n",
       "0           0  2020-02-24T18:00:00   ITA                         101   \n",
       "1           1  2020-02-25T18:00:00   ITA                         114   \n",
       "2           2  2020-02-26T18:00:00   ITA                         128   \n",
       "3           3  2020-02-27T18:00:00   ITA                         248   \n",
       "4           4  2020-02-28T18:00:00   ITA                         345   \n",
       "\n",
       "   intensive_care  total_hospitalized  home_quarantine  total_confirmed_cases  \\\n",
       "0              26                 127               94                    221   \n",
       "1              35                 150              162                    311   \n",
       "2              36                 164              221                    385   \n",
       "3              56                 304              284                    588   \n",
       "4              64                 409              412                    821   \n",
       "\n",
       "   variation_total_confirmed  new_confirmed_cases  recovered  deaths  \\\n",
       "0                          0                  221          1       7   \n",
       "1                         90                   93          1      10   \n",
       "2                         74                   78          3      12   \n",
       "3                        203                  250         45      17   \n",
       "4                        233                  238         46      21   \n",
       "\n",
       "   total_cases  swabs_made  casi_testati note_it note_en  \n",
       "0          229        4324           NaN     NaN     NaN  \n",
       "1          322        8623           NaN     NaN     NaN  \n",
       "2          400        9587           NaN     NaN     NaN  \n",
       "3          650       12014           NaN     NaN     NaN  \n",
       "4          888       15695           NaN     NaN     NaN  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "82f9d34a",
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = df.drop(['casi_testati','note_it','note_en'],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a0274a11",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>hospitalized_with_symptoms</th>\n",
       "      <th>intensive_care</th>\n",
       "      <th>total_hospitalized</th>\n",
       "      <th>home_quarantine</th>\n",
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       "      <th>new_confirmed_cases</th>\n",
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       "      <th>deaths</th>\n",
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       "      <th>swabs_made</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>70.000000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>7.000000e+01</td>\n",
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       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>34.500000</td>\n",
       "      <td>17373.142857</td>\n",
       "      <td>2225.128571</td>\n",
       "      <td>19598.285714</td>\n",
       "      <td>41387.885714</td>\n",
       "      <td>60986.157143</td>\n",
       "      <td>1427.971429</td>\n",
       "      <td>3010.128571</td>\n",
       "      <td>23623.457143</td>\n",
       "      <td>12095.185714</td>\n",
       "      <td>96704.800000</td>\n",
       "      <td>6.873203e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>20.351085</td>\n",
       "      <td>10475.956363</td>\n",
       "      <td>1330.399743</td>\n",
       "      <td>11743.460668</td>\n",
       "      <td>32774.474616</td>\n",
       "      <td>42510.504183</td>\n",
       "      <td>1642.323857</td>\n",
       "      <td>1750.317768</td>\n",
       "      <td>25315.758084</td>\n",
       "      <td>10460.388291</td>\n",
       "      <td>75590.446898</td>\n",
       "      <td>6.689012e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>101.000000</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>127.000000</td>\n",
       "      <td>94.000000</td>\n",
       "      <td>221.000000</td>\n",
       "      <td>-3106.000000</td>\n",
       "      <td>78.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>229.000000</td>\n",
       "      <td>4.324000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>17.250000</td>\n",
       "      <td>6844.000000</td>\n",
       "      <td>1196.750000</td>\n",
       "      <td>8040.750000</td>\n",
       "      <td>5327.250000</td>\n",
       "      <td>13368.000000</td>\n",
       "      <td>229.250000</td>\n",
       "      <td>1815.750000</td>\n",
       "      <td>1303.250000</td>\n",
       "      <td>1078.500000</td>\n",
       "      <td>15749.750000</td>\n",
       "      <td>8.888025e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>34.500000</td>\n",
       "      <td>20522.500000</td>\n",
       "      <td>2325.500000</td>\n",
       "      <td>23118.000000</td>\n",
       "      <td>43170.000000</td>\n",
       "      <td>74704.000000</td>\n",
       "      <td>1192.000000</td>\n",
       "      <td>3043.000000</td>\n",
       "      <td>13825.000000</td>\n",
       "      <td>11185.000000</td>\n",
       "      <td>99714.000000</td>\n",
       "      <td>4.656945e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>51.750000</td>\n",
       "      <td>27262.750000</td>\n",
       "      <td>3392.250000</td>\n",
       "      <td>30674.500000</td>\n",
       "      <td>76257.500000</td>\n",
       "      <td>102077.500000</td>\n",
       "      <td>2605.250000</td>\n",
       "      <td>4206.250000</td>\n",
       "      <td>39646.000000</td>\n",
       "      <td>22038.750000</td>\n",
       "      <td>167994.500000</td>\n",
       "      <td>1.163153e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>69.000000</td>\n",
       "      <td>29010.000000</td>\n",
       "      <td>4068.000000</td>\n",
       "      <td>33004.000000</td>\n",
       "      <td>83652.000000</td>\n",
       "      <td>108257.000000</td>\n",
       "      <td>4821.000000</td>\n",
       "      <td>6557.000000</td>\n",
       "      <td>81654.000000</td>\n",
       "      <td>28884.000000</td>\n",
       "      <td>210717.000000</td>\n",
       "      <td>2.153772e+06</td>\n",
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       "  </tbody>\n",
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      "text/plain": [
       "       Unnamed: 0  hospitalized_with_symptoms  intensive_care  \\\n",
       "count   70.000000                   70.000000       70.000000   \n",
       "mean    34.500000                17373.142857     2225.128571   \n",
       "std     20.351085                10475.956363     1330.399743   \n",
       "min      0.000000                  101.000000       26.000000   \n",
       "25%     17.250000                 6844.000000     1196.750000   \n",
       "50%     34.500000                20522.500000     2325.500000   \n",
       "75%     51.750000                27262.750000     3392.250000   \n",
       "max     69.000000                29010.000000     4068.000000   \n",
       "\n",
       "       total_hospitalized  home_quarantine  total_confirmed_cases  \\\n",
       "count           70.000000        70.000000              70.000000   \n",
       "mean         19598.285714     41387.885714           60986.157143   \n",
       "std          11743.460668     32774.474616           42510.504183   \n",
       "min            127.000000        94.000000             221.000000   \n",
       "25%           8040.750000      5327.250000           13368.000000   \n",
       "50%          23118.000000     43170.000000           74704.000000   \n",
       "75%          30674.500000     76257.500000          102077.500000   \n",
       "max          33004.000000     83652.000000          108257.000000   \n",
       "\n",
       "       variation_total_confirmed  new_confirmed_cases     recovered  \\\n",
       "count                  70.000000            70.000000     70.000000   \n",
       "mean                 1427.971429          3010.128571  23623.457143   \n",
       "std                  1642.323857          1750.317768  25315.758084   \n",
       "min                 -3106.000000            78.000000      1.000000   \n",
       "25%                   229.250000          1815.750000   1303.250000   \n",
       "50%                  1192.000000          3043.000000  13825.000000   \n",
       "75%                  2605.250000          4206.250000  39646.000000   \n",
       "max                  4821.000000          6557.000000  81654.000000   \n",
       "\n",
       "             deaths    total_cases    swabs_made  \n",
       "count     70.000000      70.000000  7.000000e+01  \n",
       "mean   12095.185714   96704.800000  6.873203e+05  \n",
       "std    10460.388291   75590.446898  6.689012e+05  \n",
       "min        7.000000     229.000000  4.324000e+03  \n",
       "25%     1078.500000   15749.750000  8.888025e+04  \n",
       "50%    11185.000000   99714.000000  4.656945e+05  \n",
       "75%    22038.750000  167994.500000  1.163153e+06  \n",
       "max    28884.000000  210717.000000  2.153772e+06  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "5b27630b",
   "metadata": {},
   "outputs": [
    {
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       "      <th>hospitalized_with_symptoms</th>\n",
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       "      <th>Unnamed: 0</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.759971</td>\n",
       "      <td>0.536125</td>\n",
       "      <td>0.738680</td>\n",
       "      <td>0.977207</td>\n",
       "      <td>0.957461</td>\n",
       "      <td>-0.305721</td>\n",
       "      <td>0.289439</td>\n",
       "      <td>0.937960</td>\n",
       "      <td>0.981392</td>\n",
       "      <td>0.988393</td>\n",
       "      <td>0.955030</td>\n",
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       "    <tr>\n",
       "      <th>hospitalized_with_symptoms</th>\n",
       "      <td>0.759971</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.946883</td>\n",
       "      <td>0.999336</td>\n",
       "      <td>0.795108</td>\n",
       "      <td>0.889073</td>\n",
       "      <td>0.227592</td>\n",
       "      <td>0.722996</td>\n",
       "      <td>0.509869</td>\n",
       "      <td>0.718915</td>\n",
       "      <td>0.770240</td>\n",
       "      <td>0.555912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>intensive_care</th>\n",
       "      <td>0.536125</td>\n",
       "      <td>0.946883</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.957970</td>\n",
       "      <td>0.562762</td>\n",
       "      <td>0.698513</td>\n",
       "      <td>0.494737</td>\n",
       "      <td>0.860763</td>\n",
       "      <td>0.230481</td>\n",
       "      <td>0.466470</td>\n",
       "      <td>0.534570</td>\n",
       "      <td>0.280654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_hospitalized</th>\n",
       "      <td>0.738680</td>\n",
       "      <td>0.999336</td>\n",
       "      <td>0.957970</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.773043</td>\n",
       "      <td>0.872244</td>\n",
       "      <td>0.259074</td>\n",
       "      <td>0.742474</td>\n",
       "      <td>0.480947</td>\n",
       "      <td>0.694164</td>\n",
       "      <td>0.747665</td>\n",
       "      <td>0.527704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>home_quarantine</th>\n",
       "      <td>0.977207</td>\n",
       "      <td>0.795108</td>\n",
       "      <td>0.562762</td>\n",
       "      <td>0.773043</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.984526</td>\n",
       "      <td>-0.338854</td>\n",
       "      <td>0.260811</td>\n",
       "      <td>0.912032</td>\n",
       "      <td>0.991391</td>\n",
       "      <td>0.996314</td>\n",
       "      <td>0.933754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_confirmed_cases</th>\n",
       "      <td>0.957461</td>\n",
       "      <td>0.889073</td>\n",
       "      <td>0.698513</td>\n",
       "      <td>0.872244</td>\n",
       "      <td>0.984526</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.189679</td>\n",
       "      <td>0.406186</td>\n",
       "      <td>0.836014</td>\n",
       "      <td>0.956099</td>\n",
       "      <td>0.974673</td>\n",
       "      <td>0.865677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>variation_total_confirmed</th>\n",
       "      <td>-0.305721</td>\n",
       "      <td>0.227592</td>\n",
       "      <td>0.494737</td>\n",
       "      <td>0.259074</td>\n",
       "      <td>-0.338854</td>\n",
       "      <td>-0.189679</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.780004</td>\n",
       "      <td>-0.563938</td>\n",
       "      <td>-0.426503</td>\n",
       "      <td>-0.354558</td>\n",
       "      <td>-0.532430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>new_confirmed_cases</th>\n",
       "      <td>0.289439</td>\n",
       "      <td>0.722996</td>\n",
       "      <td>0.860763</td>\n",
       "      <td>0.742474</td>\n",
       "      <td>0.260811</td>\n",
       "      <td>0.406186</td>\n",
       "      <td>0.780004</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.016260</td>\n",
       "      <td>0.167342</td>\n",
       "      <td>0.246142</td>\n",
       "      <td>0.027119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>recovered</th>\n",
       "      <td>0.937960</td>\n",
       "      <td>0.509869</td>\n",
       "      <td>0.230481</td>\n",
       "      <td>0.480947</td>\n",
       "      <td>0.912032</td>\n",
       "      <td>0.836014</td>\n",
       "      <td>-0.563938</td>\n",
       "      <td>-0.016260</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.956797</td>\n",
       "      <td>0.937468</td>\n",
       "      <td>0.998237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>deaths</th>\n",
       "      <td>0.981392</td>\n",
       "      <td>0.718915</td>\n",
       "      <td>0.466470</td>\n",
       "      <td>0.694164</td>\n",
       "      <td>0.991391</td>\n",
       "      <td>0.956099</td>\n",
       "      <td>-0.426503</td>\n",
       "      <td>0.167342</td>\n",
       "      <td>0.956797</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.996510</td>\n",
       "      <td>0.971369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_cases</th>\n",
       "      <td>0.988393</td>\n",
       "      <td>0.770240</td>\n",
       "      <td>0.534570</td>\n",
       "      <td>0.747665</td>\n",
       "      <td>0.996314</td>\n",
       "      <td>0.974673</td>\n",
       "      <td>-0.354558</td>\n",
       "      <td>0.246142</td>\n",
       "      <td>0.937468</td>\n",
       "      <td>0.996510</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.955576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>swabs_made</th>\n",
       "      <td>0.955030</td>\n",
       "      <td>0.555912</td>\n",
       "      <td>0.280654</td>\n",
       "      <td>0.527704</td>\n",
       "      <td>0.933754</td>\n",
       "      <td>0.865677</td>\n",
       "      <td>-0.532430</td>\n",
       "      <td>0.027119</td>\n",
       "      <td>0.998237</td>\n",
       "      <td>0.971369</td>\n",
       "      <td>0.955576</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Unnamed: 0  hospitalized_with_symptoms  \\\n",
       "Unnamed: 0                    1.000000                    0.759971   \n",
       "hospitalized_with_symptoms    0.759971                    1.000000   \n",
       "intensive_care                0.536125                    0.946883   \n",
       "total_hospitalized            0.738680                    0.999336   \n",
       "home_quarantine               0.977207                    0.795108   \n",
       "total_confirmed_cases         0.957461                    0.889073   \n",
       "variation_total_confirmed    -0.305721                    0.227592   \n",
       "new_confirmed_cases           0.289439                    0.722996   \n",
       "recovered                     0.937960                    0.509869   \n",
       "deaths                        0.981392                    0.718915   \n",
       "total_cases                   0.988393                    0.770240   \n",
       "swabs_made                    0.955030                    0.555912   \n",
       "\n",
       "                            intensive_care  total_hospitalized  \\\n",
       "Unnamed: 0                        0.536125            0.738680   \n",
       "hospitalized_with_symptoms        0.946883            0.999336   \n",
       "intensive_care                    1.000000            0.957970   \n",
       "total_hospitalized                0.957970            1.000000   \n",
       "home_quarantine                   0.562762            0.773043   \n",
       "total_confirmed_cases             0.698513            0.872244   \n",
       "variation_total_confirmed         0.494737            0.259074   \n",
       "new_confirmed_cases               0.860763            0.742474   \n",
       "recovered                         0.230481            0.480947   \n",
       "deaths                            0.466470            0.694164   \n",
       "total_cases                       0.534570            0.747665   \n",
       "swabs_made                        0.280654            0.527704   \n",
       "\n",
       "                            home_quarantine  total_confirmed_cases  \\\n",
       "Unnamed: 0                         0.977207               0.957461   \n",
       "hospitalized_with_symptoms         0.795108               0.889073   \n",
       "intensive_care                     0.562762               0.698513   \n",
       "total_hospitalized                 0.773043               0.872244   \n",
       "home_quarantine                    1.000000               0.984526   \n",
       "total_confirmed_cases              0.984526               1.000000   \n",
       "variation_total_confirmed         -0.338854              -0.189679   \n",
       "new_confirmed_cases                0.260811               0.406186   \n",
       "recovered                          0.912032               0.836014   \n",
       "deaths                             0.991391               0.956099   \n",
       "total_cases                        0.996314               0.974673   \n",
       "swabs_made                         0.933754               0.865677   \n",
       "\n",
       "                            variation_total_confirmed  new_confirmed_cases  \\\n",
       "Unnamed: 0                                  -0.305721             0.289439   \n",
       "hospitalized_with_symptoms                   0.227592             0.722996   \n",
       "intensive_care                               0.494737             0.860763   \n",
       "total_hospitalized                           0.259074             0.742474   \n",
       "home_quarantine                             -0.338854             0.260811   \n",
       "total_confirmed_cases                       -0.189679             0.406186   \n",
       "variation_total_confirmed                    1.000000             0.780004   \n",
       "new_confirmed_cases                          0.780004             1.000000   \n",
       "recovered                                   -0.563938            -0.016260   \n",
       "deaths                                      -0.426503             0.167342   \n",
       "total_cases                                 -0.354558             0.246142   \n",
       "swabs_made                                  -0.532430             0.027119   \n",
       "\n",
       "                            recovered    deaths  total_cases  swabs_made  \n",
       "Unnamed: 0                   0.937960  0.981392     0.988393    0.955030  \n",
       "hospitalized_with_symptoms   0.509869  0.718915     0.770240    0.555912  \n",
       "intensive_care               0.230481  0.466470     0.534570    0.280654  \n",
       "total_hospitalized           0.480947  0.694164     0.747665    0.527704  \n",
       "home_quarantine              0.912032  0.991391     0.996314    0.933754  \n",
       "total_confirmed_cases        0.836014  0.956099     0.974673    0.865677  \n",
       "variation_total_confirmed   -0.563938 -0.426503    -0.354558   -0.532430  \n",
       "new_confirmed_cases         -0.016260  0.167342     0.246142    0.027119  \n",
       "recovered                    1.000000  0.956797     0.937468    0.998237  \n",
       "deaths                       0.956797  1.000000     0.996510    0.971369  \n",
       "total_cases                  0.937468  0.996510     1.000000    0.955576  \n",
       "swabs_made                   0.998237  0.971369     0.955576    1.000000  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d6606c71",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(df1.corr())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "e78f3e50",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Unnamed: 0                    0\n",
       "date                          0\n",
       "state                         0\n",
       "hospitalized_with_symptoms    0\n",
       "intensive_care                0\n",
       "total_hospitalized            0\n",
       "home_quarantine               0\n",
       "total_confirmed_cases         0\n",
       "variation_total_confirmed     0\n",
       "new_confirmed_cases           0\n",
       "recovered                     0\n",
       "deaths                        0\n",
       "total_cases                   0\n",
       "swabs_made                    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "42ddecd6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(df1.isnull())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "cfd2fc0a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Unnamed: 0', 'date', 'state', 'hospitalized_with_symptoms',\n",
       "       'intensive_care', 'total_hospitalized', 'home_quarantine',\n",
       "       'total_confirmed_cases', 'variation_total_confirmed',\n",
       "       'new_confirmed_cases', 'recovered', 'deaths', 'total_cases',\n",
       "       'swabs_made'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76a96dc6",
   "metadata": {},
   "source": [
    "# Relation plot with scatter plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "1a57a9a7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x26bf920a6d0>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.relplot(x='total_cases',y='recovered',data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "d8d523f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='total_cases', ylabel='deaths'>"
      ]
     },
     "execution_count": 28,
     "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.scatterplot(x='total_cases',y='deaths',data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "292fe3bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "case_morethan_20k = df.loc[df['total_cases']>20000,['total_cases','deaths','recovered']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "c769f983",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_cases</th>\n",
       "      <th>deaths</th>\n",
       "      <th>recovered</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>21157</td>\n",
       "      <td>1441</td>\n",
       "      <td>1966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>24747</td>\n",
       "      <td>1809</td>\n",
       "      <td>2335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>27980</td>\n",
       "      <td>2158</td>\n",
       "      <td>2749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>31506</td>\n",
       "      <td>2503</td>\n",
       "      <td>2941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>35713</td>\n",
       "      <td>2978</td>\n",
       "      <td>4025</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    total_cases  deaths  recovered\n",
       "19        21157    1441       1966\n",
       "20        24747    1809       2335\n",
       "21        27980    2158       2749\n",
       "22        31506    2503       2941\n",
       "23        35713    2978       4025"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "case_morethan_20k.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "8b755bf7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x26bfb0633a0>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.relplot(x='deaths',y='total_cases',data=case_morethan_20k)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "aa4cb9cc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='total_hospitalized', ylabel='hospitalized_with_symptoms'>"
      ]
     },
     "execution_count": 45,
     "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.scatterplot(x='total_hospitalized',y='hospitalized_with_symptoms',hue = 'dea',data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "429cdf8c",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
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