Obitos_BR_por_data.ipynb

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  "metadata": {
    "colab": {
      "name": "Obitos-BR-por-data.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "X1kljADrORcH",
        "colab_type": "text"
      },
      "source": [
        "# Óbitos por data do óbito. \n",
        "\n",
        "Esse script replica gráficos de duas fontes:\n",
        "\n",
        "* Reportes de óbitos nos boletins semanais do MS <br>\n",
        "https://twitter.com/canalpeixebabel/status/1262387751787339780?s=20\n",
        "* Plot animado de reportes diários <br>\n",
        "https://twitter.com/obscovid19br/status/1262166415160807424?s=20\n",
        " "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "D7atOAaIMJX7",
        "colab_type": "code",
        "outputId": "0c9b4a0d-b353-4518-9bdf-a9f434e3c7a9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 226
        }
      },
      "source": [
        "!wget https://raw.githubusercontent.com/covid19br/covid19br.github.io/master/SRAGs-tabela-last-updated_revised2.csv"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "--2020-05-19 22:16:37--  https://raw.githubusercontent.com/covid19br/covid19br.github.io/master/SRAGs-tabela-last-updated_revised2.csv\n",
            "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 151.101.0.133, 151.101.64.133, 151.101.128.133, ...\n",
            "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|151.101.0.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 3920 (3.8K) [text/plain]\n",
            "Saving to: ‘SRAGs-tabela-last-updated_revised2.csv’\n",
            "\n",
            "\r          SRAGs-tab   0%[                    ]       0  --.-KB/s               \rSRAGs-tabela-last-u 100%[===================>]   3.83K  --.-KB/s    in 0s      \n",
            "\n",
            "2020-05-19 22:16:38 (53.9 MB/s) - ‘SRAGs-tabela-last-updated_revised2.csv’ saved [3920/3920]\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7OrlygdiMLNo",
        "colab_type": "code",
        "outputId": "0dfeabd1-0be3-4190-d01f-3f18ccf10612",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 75
        }
      },
      "source": [
        "import numpy as np\n",
        "import seaborn as sns\n",
        "import pandas as pd\n",
        "import matplotlib\n",
        "import matplotlib.pyplot as plt\n",
        "import matplotlib.animation as animation\n",
        "from IPython.display import HTML"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
            "  import pandas.util.testing as tm\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "H7lvX75yMNPG",
        "colab_type": "code",
        "outputId": "d28d1ca3-fcac-4238-bd00-7527d299c756",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "obitos_df = pd.read_csv('SRAGs-tabela-last-updated_revised2.csv')\n",
        "datas = obitos_df['Data']\n",
        "datas = ['/'.join(d.split('/')[::-1]) for d in datas]\n",
        "obitos_df['Data'] = np.asarray(datas)\n",
        "obitos_df.drop(0, inplace=True)\n",
        "display(obitos_df)"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Data</th>\n",
              "      <th>08/05/20</th>\n",
              "      <th>07/05/20</th>\n",
              "      <th>03/05/20</th>\n",
              "      <th>02/05/20</th>\n",
              "      <th>29/04/20</th>\n",
              "      <th>27/04/20</th>\n",
              "      <th>23/04/20</th>\n",
              "      <th>22/04/20</th>\n",
              "      <th>20/04/20</th>\n",
              "      <th>19/04/20</th>\n",
              "      <th>17/04/20</th>\n",
              "      <th>16/04/20</th>\n",
              "      <th>15/04/20</th>\n",
              "      <th>14/04/20</th>\n",
              "      <th>13/04/20</th>\n",
              "      <th>11/04/20</th>\n",
              "      <th>10/04/20</th>\n",
              "      <th>08/04/20</th>\n",
              "      <th>07/04/20</th>\n",
              "      <th>06/04/20</th>\n",
              "      <th>05/04/20</th>\n",
              "      <th>04/04/20</th>\n",
              "      <th>02/04/20</th>\n",
              "      <th>30/03/20</th>\n",
              "      <th>29/03/20</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020/03/16</td>\n",
              "      <td>3</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020/03/17</td>\n",
              "      <td>3</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020/03/18</td>\n",
              "      <td>6</td>\n",
              "      <td>6.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020/03/19</td>\n",
              "      <td>7</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2020/03/20</td>\n",
              "      <td>15</td>\n",
              "      <td>14.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2020/03/21</td>\n",
              "      <td>13</td>\n",
              "      <td>13.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>9.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2020/03/22</td>\n",
              "      <td>17</td>\n",
              "      <td>17.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>16.0</td>\n",
              "      <td>16.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>2020/03/23</td>\n",
              "      <td>37</td>\n",
              "      <td>37.0</td>\n",
              "      <td>37.0</td>\n",
              "      <td>37.0</td>\n",
              "      <td>37.0</td>\n",
              "      <td>34.0</td>\n",
              "      <td>31.0</td>\n",
              "      <td>30.0</td>\n",
              "      <td>29.0</td>\n",
              "      <td>29.0</td>\n",
              "      <td>29.0</td>\n",
              "      <td>28.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>24.0</td>\n",
              "      <td>20.0</td>\n",
              "      <td>20.0</td>\n",
              "      <td>20.0</td>\n",
              "      <td>18.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>12.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>2020/03/24</td>\n",
              "      <td>34</td>\n",
              "      <td>34.0</td>\n",
              "      <td>31.0</td>\n",
              "      <td>31.0</td>\n",
              "      <td>31.0</td>\n",
              "      <td>29.0</td>\n",
              "      <td>29.0</td>\n",
              "      <td>29.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>26.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>23.0</td>\n",
              "      <td>23.0</td>\n",
              "      <td>23.0</td>\n",
              "      <td>22.0</td>\n",
              "      <td>20.0</td>\n",
              "      <td>18.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>12.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>2020/03/25</td>\n",
              "      <td>33</td>\n",
              "      <td>33.0</td>\n",
              "      <td>32.0</td>\n",
              "      <td>32.0</td>\n",
              "      <td>32.0</td>\n",
              "      <td>29.0</td>\n",
              "      <td>29.0</td>\n",
              "      <td>28.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>26.0</td>\n",
              "      <td>26.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>24.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>20.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>13.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>2020/03/26</td>\n",
              "      <td>47</td>\n",
              "      <td>47.0</td>\n",
              "      <td>43.0</td>\n",
              "      <td>43.0</td>\n",
              "      <td>41.0</td>\n",
              "      <td>37.0</td>\n",
              "      <td>36.0</td>\n",
              "      <td>36.0</td>\n",
              "      <td>33.0</td>\n",
              "      <td>32.0</td>\n",
              "      <td>32.0</td>\n",
              "      <td>32.0</td>\n",
              "      <td>31.0</td>\n",
              "      <td>31.0</td>\n",
              "      <td>30.0</td>\n",
              "      <td>29.0</td>\n",
              "      <td>29.0</td>\n",
              "      <td>28.0</td>\n",
              "      <td>28.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>26.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>20.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>14.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>2020/03/27</td>\n",
              "      <td>55</td>\n",
              "      <td>55.0</td>\n",
              "      <td>52.0</td>\n",
              "      <td>52.0</td>\n",
              "      <td>52.0</td>\n",
              "      <td>48.0</td>\n",
              "      <td>43.0</td>\n",
              "      <td>40.0</td>\n",
              "      <td>36.0</td>\n",
              "      <td>35.0</td>\n",
              "      <td>35.0</td>\n",
              "      <td>35.0</td>\n",
              "      <td>33.0</td>\n",
              "      <td>30.0</td>\n",
              "      <td>30.0</td>\n",
              "      <td>29.0</td>\n",
              "      <td>29.0</td>\n",
              "      <td>28.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>23.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>11.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>2020/03/28</td>\n",
              "      <td>66</td>\n",
              "      <td>66.0</td>\n",
              "      <td>64.0</td>\n",
              "      <td>64.0</td>\n",
              "      <td>64.0</td>\n",
              "      <td>56.0</td>\n",
              "      <td>54.0</td>\n",
              "      <td>52.0</td>\n",
              "      <td>51.0</td>\n",
              "      <td>51.0</td>\n",
              "      <td>51.0</td>\n",
              "      <td>49.0</td>\n",
              "      <td>44.0</td>\n",
              "      <td>41.0</td>\n",
              "      <td>41.0</td>\n",
              "      <td>39.0</td>\n",
              "      <td>36.0</td>\n",
              "      <td>34.0</td>\n",
              "      <td>33.0</td>\n",
              "      <td>33.0</td>\n",
              "      <td>33.0</td>\n",
              "      <td>31.0</td>\n",
              "      <td>28.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>13.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>2020/03/29</td>\n",
              "      <td>64</td>\n",
              "      <td>64.0</td>\n",
              "      <td>62.0</td>\n",
              "      <td>62.0</td>\n",
              "      <td>62.0</td>\n",
              "      <td>61.0</td>\n",
              "      <td>54.0</td>\n",
              "      <td>52.0</td>\n",
              "      <td>49.0</td>\n",
              "      <td>48.0</td>\n",
              "      <td>48.0</td>\n",
              "      <td>48.0</td>\n",
              "      <td>48.0</td>\n",
              "      <td>46.0</td>\n",
              "      <td>45.0</td>\n",
              "      <td>45.0</td>\n",
              "      <td>45.0</td>\n",
              "      <td>45.0</td>\n",
              "      <td>43.0</td>\n",
              "      <td>43.0</td>\n",
              "      <td>41.0</td>\n",
              "      <td>37.0</td>\n",
              "      <td>30.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>2020/03/30</td>\n",
              "      <td>82</td>\n",
              "      <td>82.0</td>\n",
              "      <td>82.0</td>\n",
              "      <td>82.0</td>\n",
              "      <td>82.0</td>\n",
              "      <td>73.0</td>\n",
              "      <td>71.0</td>\n",
              "      <td>66.0</td>\n",
              "      <td>59.0</td>\n",
              "      <td>57.0</td>\n",
              "      <td>57.0</td>\n",
              "      <td>55.0</td>\n",
              "      <td>52.0</td>\n",
              "      <td>51.0</td>\n",
              "      <td>47.0</td>\n",
              "      <td>46.0</td>\n",
              "      <td>43.0</td>\n",
              "      <td>42.0</td>\n",
              "      <td>36.0</td>\n",
              "      <td>33.0</td>\n",
              "      <td>33.0</td>\n",
              "      <td>33.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>2020/03/31</td>\n",
              "      <td>93</td>\n",
              "      <td>90.0</td>\n",
              "      <td>88.0</td>\n",
              "      <td>87.0</td>\n",
              "      <td>87.0</td>\n",
              "      <td>84.0</td>\n",
              "      <td>81.0</td>\n",
              "      <td>75.0</td>\n",
              "      <td>73.0</td>\n",
              "      <td>72.0</td>\n",
              "      <td>70.0</td>\n",
              "      <td>67.0</td>\n",
              "      <td>64.0</td>\n",
              "      <td>59.0</td>\n",
              "      <td>55.0</td>\n",
              "      <td>54.0</td>\n",
              "      <td>52.0</td>\n",
              "      <td>46.0</td>\n",
              "      <td>39.0</td>\n",
              "      <td>32.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>26.0</td>\n",
              "      <td>20.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>2020/04/01</td>\n",
              "      <td>103</td>\n",
              "      <td>100.0</td>\n",
              "      <td>98.0</td>\n",
              "      <td>97.0</td>\n",
              "      <td>96.0</td>\n",
              "      <td>86.0</td>\n",
              "      <td>82.0</td>\n",
              "      <td>81.0</td>\n",
              "      <td>73.0</td>\n",
              "      <td>70.0</td>\n",
              "      <td>68.0</td>\n",
              "      <td>65.0</td>\n",
              "      <td>61.0</td>\n",
              "      <td>57.0</td>\n",
              "      <td>53.0</td>\n",
              "      <td>53.0</td>\n",
              "      <td>52.0</td>\n",
              "      <td>45.0</td>\n",
              "      <td>36.0</td>\n",
              "      <td>35.0</td>\n",
              "      <td>32.0</td>\n",
              "      <td>29.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>2020/04/02</td>\n",
              "      <td>115</td>\n",
              "      <td>110.0</td>\n",
              "      <td>107.0</td>\n",
              "      <td>107.0</td>\n",
              "      <td>107.0</td>\n",
              "      <td>102.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>95.0</td>\n",
              "      <td>82.0</td>\n",
              "      <td>82.0</td>\n",
              "      <td>79.0</td>\n",
              "      <td>75.0</td>\n",
              "      <td>71.0</td>\n",
              "      <td>67.0</td>\n",
              "      <td>56.0</td>\n",
              "      <td>54.0</td>\n",
              "      <td>51.0</td>\n",
              "      <td>48.0</td>\n",
              "      <td>36.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>26.0</td>\n",
              "      <td>26.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>2020/04/03</td>\n",
              "      <td>131</td>\n",
              "      <td>131.0</td>\n",
              "      <td>126.0</td>\n",
              "      <td>126.0</td>\n",
              "      <td>122.0</td>\n",
              "      <td>117.0</td>\n",
              "      <td>110.0</td>\n",
              "      <td>105.0</td>\n",
              "      <td>94.0</td>\n",
              "      <td>91.0</td>\n",
              "      <td>87.0</td>\n",
              "      <td>84.0</td>\n",
              "      <td>77.0</td>\n",
              "      <td>71.0</td>\n",
              "      <td>64.0</td>\n",
              "      <td>63.0</td>\n",
              "      <td>58.0</td>\n",
              "      <td>41.0</td>\n",
              "      <td>35.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>2020/04/04</td>\n",
              "      <td>148</td>\n",
              "      <td>146.0</td>\n",
              "      <td>141.0</td>\n",
              "      <td>140.0</td>\n",
              "      <td>138.0</td>\n",
              "      <td>136.0</td>\n",
              "      <td>119.0</td>\n",
              "      <td>111.0</td>\n",
              "      <td>103.0</td>\n",
              "      <td>102.0</td>\n",
              "      <td>98.0</td>\n",
              "      <td>92.0</td>\n",
              "      <td>85.0</td>\n",
              "      <td>80.0</td>\n",
              "      <td>75.0</td>\n",
              "      <td>71.0</td>\n",
              "      <td>65.0</td>\n",
              "      <td>49.0</td>\n",
              "      <td>44.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>2020/04/05</td>\n",
              "      <td>149</td>\n",
              "      <td>149.0</td>\n",
              "      <td>145.0</td>\n",
              "      <td>144.0</td>\n",
              "      <td>141.0</td>\n",
              "      <td>133.0</td>\n",
              "      <td>128.0</td>\n",
              "      <td>122.0</td>\n",
              "      <td>111.0</td>\n",
              "      <td>107.0</td>\n",
              "      <td>104.0</td>\n",
              "      <td>98.0</td>\n",
              "      <td>90.0</td>\n",
              "      <td>86.0</td>\n",
              "      <td>78.0</td>\n",
              "      <td>71.0</td>\n",
              "      <td>69.0</td>\n",
              "      <td>51.0</td>\n",
              "      <td>42.0</td>\n",
              "      <td>20.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>2020/04/06</td>\n",
              "      <td>154</td>\n",
              "      <td>154.0</td>\n",
              "      <td>154.0</td>\n",
              "      <td>154.0</td>\n",
              "      <td>145.0</td>\n",
              "      <td>129.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>115.0</td>\n",
              "      <td>104.0</td>\n",
              "      <td>102.0</td>\n",
              "      <td>93.0</td>\n",
              "      <td>86.0</td>\n",
              "      <td>80.0</td>\n",
              "      <td>73.0</td>\n",
              "      <td>71.0</td>\n",
              "      <td>70.0</td>\n",
              "      <td>64.0</td>\n",
              "      <td>46.0</td>\n",
              "      <td>31.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>2020/04/07</td>\n",
              "      <td>168</td>\n",
              "      <td>166.0</td>\n",
              "      <td>163.0</td>\n",
              "      <td>163.0</td>\n",
              "      <td>153.0</td>\n",
              "      <td>140.0</td>\n",
              "      <td>135.0</td>\n",
              "      <td>123.0</td>\n",
              "      <td>106.0</td>\n",
              "      <td>102.0</td>\n",
              "      <td>99.0</td>\n",
              "      <td>90.0</td>\n",
              "      <td>81.0</td>\n",
              "      <td>71.0</td>\n",
              "      <td>61.0</td>\n",
              "      <td>53.0</td>\n",
              "      <td>50.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>2020/04/08</td>\n",
              "      <td>171</td>\n",
              "      <td>171.0</td>\n",
              "      <td>164.0</td>\n",
              "      <td>164.0</td>\n",
              "      <td>155.0</td>\n",
              "      <td>146.0</td>\n",
              "      <td>130.0</td>\n",
              "      <td>118.0</td>\n",
              "      <td>105.0</td>\n",
              "      <td>105.0</td>\n",
              "      <td>101.0</td>\n",
              "      <td>93.0</td>\n",
              "      <td>79.0</td>\n",
              "      <td>70.0</td>\n",
              "      <td>57.0</td>\n",
              "      <td>53.0</td>\n",
              "      <td>45.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>2020/04/09</td>\n",
              "      <td>150</td>\n",
              "      <td>143.0</td>\n",
              "      <td>134.0</td>\n",
              "      <td>134.0</td>\n",
              "      <td>127.0</td>\n",
              "      <td>121.0</td>\n",
              "      <td>110.0</td>\n",
              "      <td>97.0</td>\n",
              "      <td>90.0</td>\n",
              "      <td>86.0</td>\n",
              "      <td>79.0</td>\n",
              "      <td>70.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>50.0</td>\n",
              "      <td>44.0</td>\n",
              "      <td>32.0</td>\n",
              "      <td>22.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>2020/04/10</td>\n",
              "      <td>193</td>\n",
              "      <td>191.0</td>\n",
              "      <td>181.0</td>\n",
              "      <td>179.0</td>\n",
              "      <td>163.0</td>\n",
              "      <td>150.0</td>\n",
              "      <td>139.0</td>\n",
              "      <td>122.0</td>\n",
              "      <td>103.0</td>\n",
              "      <td>99.0</td>\n",
              "      <td>87.0</td>\n",
              "      <td>81.0</td>\n",
              "      <td>67.0</td>\n",
              "      <td>58.0</td>\n",
              "      <td>47.0</td>\n",
              "      <td>31.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>2020/04/11</td>\n",
              "      <td>171</td>\n",
              "      <td>168.0</td>\n",
              "      <td>161.0</td>\n",
              "      <td>160.0</td>\n",
              "      <td>156.0</td>\n",
              "      <td>139.0</td>\n",
              "      <td>124.0</td>\n",
              "      <td>111.0</td>\n",
              "      <td>98.0</td>\n",
              "      <td>96.0</td>\n",
              "      <td>86.0</td>\n",
              "      <td>78.0</td>\n",
              "      <td>69.0</td>\n",
              "      <td>54.0</td>\n",
              "      <td>39.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>2020/04/12</td>\n",
              "      <td>212</td>\n",
              "      <td>209.0</td>\n",
              "      <td>200.0</td>\n",
              "      <td>198.0</td>\n",
              "      <td>186.0</td>\n",
              "      <td>171.0</td>\n",
              "      <td>151.0</td>\n",
              "      <td>132.0</td>\n",
              "      <td>114.0</td>\n",
              "      <td>109.0</td>\n",
              "      <td>101.0</td>\n",
              "      <td>93.0</td>\n",
              "      <td>78.0</td>\n",
              "      <td>57.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>2020/04/13</td>\n",
              "      <td>203</td>\n",
              "      <td>203.0</td>\n",
              "      <td>203.0</td>\n",
              "      <td>203.0</td>\n",
              "      <td>193.0</td>\n",
              "      <td>178.0</td>\n",
              "      <td>155.0</td>\n",
              "      <td>140.0</td>\n",
              "      <td>113.0</td>\n",
              "      <td>108.0</td>\n",
              "      <td>96.0</td>\n",
              "      <td>84.0</td>\n",
              "      <td>67.0</td>\n",
              "      <td>37.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>2020/04/14</td>\n",
              "      <td>194</td>\n",
              "      <td>195.0</td>\n",
              "      <td>188.0</td>\n",
              "      <td>187.0</td>\n",
              "      <td>168.0</td>\n",
              "      <td>145.0</td>\n",
              "      <td>129.0</td>\n",
              "      <td>109.0</td>\n",
              "      <td>93.0</td>\n",
              "      <td>89.0</td>\n",
              "      <td>70.0</td>\n",
              "      <td>52.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>2020/04/15</td>\n",
              "      <td>210</td>\n",
              "      <td>210.0</td>\n",
              "      <td>200.0</td>\n",
              "      <td>197.0</td>\n",
              "      <td>182.0</td>\n",
              "      <td>150.0</td>\n",
              "      <td>132.0</td>\n",
              "      <td>113.0</td>\n",
              "      <td>87.0</td>\n",
              "      <td>83.0</td>\n",
              "      <td>62.0</td>\n",
              "      <td>41.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>2020/04/16</td>\n",
              "      <td>224</td>\n",
              "      <td>218.0</td>\n",
              "      <td>197.0</td>\n",
              "      <td>193.0</td>\n",
              "      <td>157.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>93.0</td>\n",
              "      <td>73.0</td>\n",
              "      <td>51.0</td>\n",
              "      <td>45.0</td>\n",
              "      <td>33.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>2020/04/17</td>\n",
              "      <td>222</td>\n",
              "      <td>212.0</td>\n",
              "      <td>192.0</td>\n",
              "      <td>190.0</td>\n",
              "      <td>164.0</td>\n",
              "      <td>137.0</td>\n",
              "      <td>101.0</td>\n",
              "      <td>75.0</td>\n",
              "      <td>44.0</td>\n",
              "      <td>35.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>2020/04/18</td>\n",
              "      <td>239</td>\n",
              "      <td>231.0</td>\n",
              "      <td>208.0</td>\n",
              "      <td>205.0</td>\n",
              "      <td>179.0</td>\n",
              "      <td>151.0</td>\n",
              "      <td>98.0</td>\n",
              "      <td>69.0</td>\n",
              "      <td>28.0</td>\n",
              "      <td>19.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>2020/04/19</td>\n",
              "      <td>220</td>\n",
              "      <td>214.0</td>\n",
              "      <td>189.0</td>\n",
              "      <td>183.0</td>\n",
              "      <td>158.0</td>\n",
              "      <td>118.0</td>\n",
              "      <td>72.0</td>\n",
              "      <td>50.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>2020/04/20</td>\n",
              "      <td>268</td>\n",
              "      <td>255.0</td>\n",
              "      <td>225.0</td>\n",
              "      <td>220.0</td>\n",
              "      <td>176.0</td>\n",
              "      <td>121.0</td>\n",
              "      <td>79.0</td>\n",
              "      <td>52.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>2020/04/21</td>\n",
              "      <td>240</td>\n",
              "      <td>226.0</td>\n",
              "      <td>200.0</td>\n",
              "      <td>199.0</td>\n",
              "      <td>161.0</td>\n",
              "      <td>106.0</td>\n",
              "      <td>56.0</td>\n",
              "      <td>34.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>2020/04/22</td>\n",
              "      <td>266</td>\n",
              "      <td>239.0</td>\n",
              "      <td>202.0</td>\n",
              "      <td>200.0</td>\n",
              "      <td>151.0</td>\n",
              "      <td>108.0</td>\n",
              "      <td>46.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>2020/04/23</td>\n",
              "      <td>290</td>\n",
              "      <td>247.0</td>\n",
              "      <td>198.0</td>\n",
              "      <td>188.0</td>\n",
              "      <td>145.0</td>\n",
              "      <td>94.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>2020/04/24</td>\n",
              "      <td>260</td>\n",
              "      <td>225.0</td>\n",
              "      <td>177.0</td>\n",
              "      <td>173.0</td>\n",
              "      <td>132.0</td>\n",
              "      <td>55.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>2020/04/25</td>\n",
              "      <td>251</td>\n",
              "      <td>221.0</td>\n",
              "      <td>169.0</td>\n",
              "      <td>162.0</td>\n",
              "      <td>107.0</td>\n",
              "      <td>23.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>2020/04/26</td>\n",
              "      <td>268</td>\n",
              "      <td>237.0</td>\n",
              "      <td>194.0</td>\n",
              "      <td>184.0</td>\n",
              "      <td>121.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>2020/04/27</td>\n",
              "      <td>259</td>\n",
              "      <td>214.0</td>\n",
              "      <td>156.0</td>\n",
              "      <td>147.0</td>\n",
              "      <td>72.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>2020/04/28</td>\n",
              "      <td>283</td>\n",
              "      <td>228.0</td>\n",
              "      <td>168.0</td>\n",
              "      <td>157.0</td>\n",
              "      <td>49.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>2020/04/29</td>\n",
              "      <td>274</td>\n",
              "      <td>221.0</td>\n",
              "      <td>129.0</td>\n",
              "      <td>111.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>2020/04/30</td>\n",
              "      <td>217</td>\n",
              "      <td>161.0</td>\n",
              "      <td>83.0</td>\n",
              "      <td>66.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>2020/05/01</td>\n",
              "      <td>227</td>\n",
              "      <td>164.0</td>\n",
              "      <td>63.0</td>\n",
              "      <td>51.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>2020/05/02</td>\n",
              "      <td>217</td>\n",
              "      <td>143.0</td>\n",
              "      <td>31.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>2020/05/03</td>\n",
              "      <td>216</td>\n",
              "      <td>139.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50</th>\n",
              "      <td>2020/05/04</td>\n",
              "      <td>202</td>\n",
              "      <td>123.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>51</th>\n",
              "      <td>2020/05/05</td>\n",
              "      <td>204</td>\n",
              "      <td>95.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>52</th>\n",
              "      <td>2020/05/06</td>\n",
              "      <td>123</td>\n",
              "      <td>11.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53</th>\n",
              "      <td>2020/05/07</td>\n",
              "      <td>106</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>54</th>\n",
              "      <td>2020/05/08</td>\n",
              "      <td>31</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Data  08/05/20  07/05/20  ...  02/04/20  30/03/20  29/03/20\n",
              "1   2020/03/16         3       3.0  ...       2.0       2.0       2.0\n",
              "2   2020/03/17         3       3.0  ...       2.0       2.0       2.0\n",
              "3   2020/03/18         6       6.0  ...       4.0       4.0       4.0\n",
              "4   2020/03/19         7       7.0  ...       7.0       6.0       6.0\n",
              "5   2020/03/20        15      14.0  ...       7.0       6.0       6.0\n",
              "6   2020/03/21        13      13.0  ...      10.0       9.0       9.0\n",
              "7   2020/03/22        17      17.0  ...      10.0       8.0       8.0\n",
              "8   2020/03/23        37      37.0  ...      17.0      15.0      12.0\n",
              "9   2020/03/24        34      34.0  ...      17.0      12.0      12.0\n",
              "10  2020/03/25        33      33.0  ...      17.0      14.0      13.0\n",
              "11  2020/03/26        47      47.0  ...      20.0      14.0      14.0\n",
              "12  2020/03/27        55      55.0  ...      15.0      11.0      11.0\n",
              "13  2020/03/28        66      66.0  ...      28.0      15.0      13.0\n",
              "14  2020/03/29        64      64.0  ...      30.0      14.0       7.0\n",
              "15  2020/03/30        82      82.0  ...      27.0       2.0       NaN\n",
              "16  2020/03/31        93      90.0  ...      20.0       NaN       NaN\n",
              "17  2020/04/01       103     100.0  ...      15.0       NaN       NaN\n",
              "18  2020/04/02       115     110.0  ...       5.0       NaN       NaN\n",
              "19  2020/04/03       131     131.0  ...       NaN       NaN       NaN\n",
              "20  2020/04/04       148     146.0  ...       NaN       NaN       NaN\n",
              "21  2020/04/05       149     149.0  ...       NaN       NaN       NaN\n",
              "22  2020/04/06       154     154.0  ...       NaN       NaN       NaN\n",
              "23  2020/04/07       168     166.0  ...       NaN       NaN       NaN\n",
              "24  2020/04/08       171     171.0  ...       NaN       NaN       NaN\n",
              "25  2020/04/09       150     143.0  ...       NaN       NaN       NaN\n",
              "26  2020/04/10       193     191.0  ...       NaN       NaN       NaN\n",
              "27  2020/04/11       171     168.0  ...       NaN       NaN       NaN\n",
              "28  2020/04/12       212     209.0  ...       NaN       NaN       NaN\n",
              "29  2020/04/13       203     203.0  ...       NaN       NaN       NaN\n",
              "30  2020/04/14       194     195.0  ...       NaN       NaN       NaN\n",
              "31  2020/04/15       210     210.0  ...       NaN       NaN       NaN\n",
              "32  2020/04/16       224     218.0  ...       NaN       NaN       NaN\n",
              "33  2020/04/17       222     212.0  ...       NaN       NaN       NaN\n",
              "34  2020/04/18       239     231.0  ...       NaN       NaN       NaN\n",
              "35  2020/04/19       220     214.0  ...       NaN       NaN       NaN\n",
              "36  2020/04/20       268     255.0  ...       NaN       NaN       NaN\n",
              "37  2020/04/21       240     226.0  ...       NaN       NaN       NaN\n",
              "38  2020/04/22       266     239.0  ...       NaN       NaN       NaN\n",
              "39  2020/04/23       290     247.0  ...       NaN       NaN       NaN\n",
              "40  2020/04/24       260     225.0  ...       NaN       NaN       NaN\n",
              "41  2020/04/25       251     221.0  ...       NaN       NaN       NaN\n",
              "42  2020/04/26       268     237.0  ...       NaN       NaN       NaN\n",
              "43  2020/04/27       259     214.0  ...       NaN       NaN       NaN\n",
              "44  2020/04/28       283     228.0  ...       NaN       NaN       NaN\n",
              "45  2020/04/29       274     221.0  ...       NaN       NaN       NaN\n",
              "46  2020/04/30       217     161.0  ...       NaN       NaN       NaN\n",
              "47  2020/05/01       227     164.0  ...       NaN       NaN       NaN\n",
              "48  2020/05/02       217     143.0  ...       NaN       NaN       NaN\n",
              "49  2020/05/03       216     139.0  ...       NaN       NaN       NaN\n",
              "50  2020/05/04       202     123.0  ...       NaN       NaN       NaN\n",
              "51  2020/05/05       204      95.0  ...       NaN       NaN       NaN\n",
              "52  2020/05/06       123      11.0  ...       NaN       NaN       NaN\n",
              "53  2020/05/07       106       NaN  ...       NaN       NaN       NaN\n",
              "54  2020/05/08        31       NaN  ...       NaN       NaN       NaN\n",
              "\n",
              "[54 rows x 26 columns]"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7qIOaALvQTCy",
        "colab_type": "code",
        "outputId": "b3af15ab-afef-41a3-8284-8781b07f256c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        }
      },
      "source": [
        "dados = obitos_df[['Data', '08/05/20', '27/04/20', '20/04/20']]\n",
        "dados = dados.melt('Data', var_name='Reporte', value_name='Óbitos')\n",
        "display(dados)"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "display_data",
          "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>Data</th>\n",
              "      <th>Reporte</th>\n",
              "      <th>Óbitos</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020/03/16</td>\n",
              "      <td>08/05/20</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020/03/17</td>\n",
              "      <td>08/05/20</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020/03/18</td>\n",
              "      <td>08/05/20</td>\n",
              "      <td>6.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020/03/19</td>\n",
              "      <td>08/05/20</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020/03/20</td>\n",
              "      <td>08/05/20</td>\n",
              "      <td>15.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>157</th>\n",
              "      <td>2020/05/04</td>\n",
              "      <td>20/04/20</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>158</th>\n",
              "      <td>2020/05/05</td>\n",
              "      <td>20/04/20</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>159</th>\n",
              "      <td>2020/05/06</td>\n",
              "      <td>20/04/20</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>160</th>\n",
              "      <td>2020/05/07</td>\n",
              "      <td>20/04/20</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>161</th>\n",
              "      <td>2020/05/08</td>\n",
              "      <td>20/04/20</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>162 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "           Data   Reporte  Óbitos\n",
              "0    2020/03/16  08/05/20     3.0\n",
              "1    2020/03/17  08/05/20     3.0\n",
              "2    2020/03/18  08/05/20     6.0\n",
              "3    2020/03/19  08/05/20     7.0\n",
              "4    2020/03/20  08/05/20    15.0\n",
              "..          ...       ...     ...\n",
              "157  2020/05/04  20/04/20     NaN\n",
              "158  2020/05/05  20/04/20     NaN\n",
              "159  2020/05/06  20/04/20     NaN\n",
              "160  2020/05/07  20/04/20     NaN\n",
              "161  2020/05/08  20/04/20     NaN\n",
              "\n",
              "[162 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TGATv06nPkiT",
        "colab_type": "code",
        "outputId": "c5994309-b545-455d-d784-2d7550ad55c4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 457
        }
      },
      "source": [
        "plt.figure(figsize=(15, 5))\n",
        "\n",
        "sns.barplot(data=dados, x='Data', y='Óbitos', hue='Reporte', dodge=False, palette='husl')\n",
        "plt.xticks(rotation=90)"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,\n",
              "        17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,\n",
              "        34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50,\n",
              "        51, 52, 53]), <a list of 54 Text major ticklabel objects>)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5XRaO9uKR7BY",
        "colab_type": "code",
        "outputId": "ea6782e1-0648-4be8-e051-401f0b219785",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 587
        }
      },
      "source": [
        "plt.close('all')\n",
        "fig, ax = plt.subplots(figsize=(14, 8))\n",
        "plt.ylim(0, 300)\n",
        "plt.xlim(0, 54)\n",
        "plt.xticks(rotation=90, fontsize=14)\n",
        "plt.yticks(fontsize=14)\n",
        "\n",
        "def plot_obitos(idx):\n",
        "\n",
        "  colunas = obitos_df.columns[::-1]\n",
        "  dados   = pd.DataFrame(obitos_df[colunas[:idx]])  \n",
        "  dados['Data'] = obitos_df['Data']\n",
        "\n",
        "  # Plot do passado\n",
        "  dados = dados.melt('Data', var_name='Reporte', value_name='Óbitos')\n",
        "  sns.lineplot(data=dados, x='Data', y='Óbitos', hue='Reporte', ax=ax, palette='Greys', legend=False)\n",
        "  \n",
        "  # Plot do presente\n",
        "  sns.lineplot(data=obitos_df, x='Data', y=obitos_df[colunas[idx]], ax=ax, color='red', legend=False)\n",
        "\n",
        "  ax.set_title('Reporte de {0}'.format(colunas[idx]), fontsize=18)\n",
        "  ax.set_ylabel('Óbitos por data do óbito', fontsize=14)\n",
        "  \n",
        "\n",
        "anim = animation.FuncAnimation(fig, plot_obitos, frames=25, interval=1000, blit=False)\n",
        "HTML(anim.to_html5_video())"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1008x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}