E01_Notebook_02_CSV_Projeto_Final_csv.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Projeto_Final_csv",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8VoQNtzqJGhw"
      },
      "source": [
        "# Base de dados usada para a realização desse projeto\n",
        "\n",
        "[COVID-19 Vaccinations in the United States, County](https://catalog.data.gov/dataset/covid-19-vaccinations-in-the-united-statescounty-8204e/resource/5c3af69e-46fc-494e-888b-63cc36845ede)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JbJu3LZSJ3e_",
        "outputId": "6610b753-f066-4175-aec9-d8ee6e047e72"
      },
      "source": [
        "#Instalando a Biblioteca Pandera (no Colab toda vez em que se inicia o notebook tem que fazer a instalação da bibliotera para ser utilizada)\n",
        "\n",
        "!pip install pandera"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: pandera in /usr/local/lib/python3.7/dist-packages (0.8.0)\n",
            "Requirement already satisfied: pyarrow in /usr/local/lib/python3.7/dist-packages (from pandera) (3.0.0)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.7/dist-packages (from pandera) (21.3)\n",
            "Requirement already satisfied: typing-inspect>=0.6.0 in /usr/local/lib/python3.7/dist-packages (from pandera) (0.7.1)\n",
            "Requirement already satisfied: pandas-stubs in /usr/local/lib/python3.7/dist-packages (from pandera) (1.2.0.38)\n",
            "Requirement already satisfied: numpy>=1.9.0 in /usr/local/lib/python3.7/dist-packages (from pandera) (1.19.5)\n",
            "Requirement already satisfied: pandas>=1.0 in /usr/local/lib/python3.7/dist-packages (from pandera) (1.1.5)\n",
            "Requirement already satisfied: wrapt in /usr/local/lib/python3.7/dist-packages (from pandera) (1.13.3)\n",
            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.7/dist-packages (from pandera) (3.10.0.2)\n",
            "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from packaging>=20.0->pandera) (3.0.6)\n",
            "Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.7/dist-packages (from pandas>=1.0->pandera) (2018.9)\n",
            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=1.0->pandera) (2.8.2)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas>=1.0->pandera) (1.15.0)\n",
            "Requirement already satisfied: mypy-extensions>=0.3.0 in /usr/local/lib/python3.7/dist-packages (from typing-inspect>=0.6.0->pandera) (0.4.3)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "n5Qva7Z13g2a"
      },
      "source": [
        "# Importando Bibliotecas para a utlização do pandas e para acessar o bucket do GCP"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iQqdQ9iS3LXo"
      },
      "source": [
        "from google.cloud import storage\n",
        "import pandas as pd\n",
        "import pandera as pa\n",
        "import io\n",
        "from io import BytesIO"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0EVFSl3T4Bgd"
      },
      "source": [
        "# Criando o client object\n",
        "\n",
        "storage_client = storage.Client.from_service_account_json(\"/content/chave_projeto-finalsc01-b94741ddd471.json\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8LHg0ELW4JS5"
      },
      "source": [
        "# Acessando o Bucket do Projeto"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ueN6j1XR4G-g"
      },
      "source": [
        "BUCKET_NAME = 'projeto-finalsc01'\n",
        "\n",
        "bucket = storage_client.get_bucket(BUCKET_NAME)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gWpjs-eX4Q7x"
      },
      "source": [
        "# Listando os arquivos contidos no Bucket"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XuCIhwby4M2g",
        "outputId": "c89fbcd7-0785-43db-faad-7cc35ad89f94"
      },
      "source": [
        "filename  = list(bucket.list_blobs(prefix=''))\n",
        "for name in filename:\n",
        "  print(name.name)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "chave/\n",
            "chave/projeto-finalsc01-b94741ddd471.json\n",
            "dados-brutos/\n",
            "dados-brutos/COVID-19_Vaccinations_in_the_United_States_County.csv\n",
            "dados-brutos/COVID_US_HOSPITALIZATION.json\n",
            "dados-tratados/\n",
            "dados-tratados/Casos_Hospitalizacoes_Obitos_Cidade.csv\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SDM7wq9Y4flw"
      },
      "source": [
        "# Carregando o dataset .csv"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1ggOtbFJ4cI_"
      },
      "source": [
        "blop = bucket.blob(\"dados-brutos/COVID-19_Vaccinations_in_the_United_States_County.csv\")\n",
        "data = blop.download_as_string()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wZvyrRAi4isA"
      },
      "source": [
        "# Criando um DataFrame utilizando pandas"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 652
        },
        "id": "yQP0s3ke4hY6",
        "outputId": "333139b9-c1b2-45c0-8f48-31593123f2fa"
      },
      "source": [
        "df = pd.read_csv(io.BytesIO(data), encoding='utf-8', sep=',', parse_dates = [\"Date\"], dayfirst = True)\n",
        "\n",
        "df"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py:2718: DtypeWarning: Columns (1) have mixed types.Specify dtype option on import or set low_memory=False.\n",
            "  interactivity=interactivity, compiler=compiler, result=result)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>FIPS</th>\n",
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              "      <th>Recip_County</th>\n",
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              "      <th>Series_Complete_18PlusPop_Pct_SVI</th>\n",
              "      <th>Series_Complete_65PlusPop_Pct_SVI</th>\n",
              "      <th>Metro_status</th>\n",
              "      <th>Series_Complete_Pop_Pct_UR_Equity</th>\n",
              "      <th>Series_Complete_12PlusPop_Pct_UR_Equity</th>\n",
              "      <th>Series_Complete_18PlusPop_Pct_UR_Equity</th>\n",
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              "  <tbody>\n",
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              "      <th>0</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>19149</td>\n",
              "      <td>46</td>\n",
              "      <td>Plymouth County</td>\n",
              "      <td>IA</td>\n",
              "      <td>48.3</td>\n",
              "      <td>12168</td>\n",
              "      <td>12168.0</td>\n",
              "      <td>57.6</td>\n",
              "      <td>11528</td>\n",
              "      <td>61.1</td>\n",
              "      <td>3917</td>\n",
              "      <td>83.9</td>\n",
              "      <td>97.4</td>\n",
              "      <td>12921.0</td>\n",
              "      <td>51.3</td>\n",
              "      <td>12857.0</td>\n",
              "      <td>60.9</td>\n",
              "      <td>12175.0</td>\n",
              "      <td>64.5</td>\n",
              "      <td>4077.0</td>\n",
              "      <td>87.4</td>\n",
              "      <td>A</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>Metro</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>01021</td>\n",
              "      <td>46</td>\n",
              "      <td>Chilton County</td>\n",
              "      <td>AL</td>\n",
              "      <td>31.9</td>\n",
              "      <td>14178</td>\n",
              "      <td>14177.0</td>\n",
              "      <td>37.8</td>\n",
              "      <td>13447</td>\n",
              "      <td>39.7</td>\n",
              "      <td>4688</td>\n",
              "      <td>61.7</td>\n",
              "      <td>92.6</td>\n",
              "      <td>17431.0</td>\n",
              "      <td>39.2</td>\n",
              "      <td>17413.0</td>\n",
              "      <td>46.5</td>\n",
              "      <td>16523.0</td>\n",
              "      <td>48.8</td>\n",
              "      <td>5480.0</td>\n",
              "      <td>72.1</td>\n",
              "      <td>D</td>\n",
              "      <td>14.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>Metro</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>20167</td>\n",
              "      <td>46</td>\n",
              "      <td>Russell County</td>\n",
              "      <td>KS</td>\n",
              "      <td>39.8</td>\n",
              "      <td>2727</td>\n",
              "      <td>2727.0</td>\n",
              "      <td>46.8</td>\n",
              "      <td>2636</td>\n",
              "      <td>49.1</td>\n",
              "      <td>1112</td>\n",
              "      <td>65.6</td>\n",
              "      <td>93.6</td>\n",
              "      <td>3013.0</td>\n",
              "      <td>43.9</td>\n",
              "      <td>3002.0</td>\n",
              "      <td>51.6</td>\n",
              "      <td>2894.0</td>\n",
              "      <td>53.9</td>\n",
              "      <td>1197.0</td>\n",
              "      <td>70.7</td>\n",
              "      <td>A</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Non-metro</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>36031</td>\n",
              "      <td>46</td>\n",
              "      <td>Essex County</td>\n",
              "      <td>NY</td>\n",
              "      <td>65.8</td>\n",
              "      <td>24262</td>\n",
              "      <td>24262.0</td>\n",
              "      <td>73.1</td>\n",
              "      <td>22876</td>\n",
              "      <td>73.8</td>\n",
              "      <td>7418</td>\n",
              "      <td>82.9</td>\n",
              "      <td>97.6</td>\n",
              "      <td>25992.0</td>\n",
              "      <td>70.5</td>\n",
              "      <td>25723.0</td>\n",
              "      <td>77.5</td>\n",
              "      <td>24189.0</td>\n",
              "      <td>78.1</td>\n",
              "      <td>7853.0</td>\n",
              "      <td>87.8</td>\n",
              "      <td>B</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>Non-metro</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>16017</td>\n",
              "      <td>46</td>\n",
              "      <td>Bonner County</td>\n",
              "      <td>ID</td>\n",
              "      <td>37.8</td>\n",
              "      <td>17308</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>17267</td>\n",
              "      <td>47.0</td>\n",
              "      <td>7946</td>\n",
              "      <td>68.4</td>\n",
              "      <td>97.6</td>\n",
              "      <td>19484.0</td>\n",
              "      <td>42.6</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>19428.0</td>\n",
              "      <td>52.9</td>\n",
              "      <td>8714.0</td>\n",
              "      <td>75.0</td>\n",
              "      <td>A</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Non-metro</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
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              "      <th>1119189</th>\n",
              "      <td>2020-12-13</td>\n",
              "      <td>22123</td>\n",
              "      <td>51</td>\n",
              "      <td>West Carroll Parish</td>\n",
              "      <td>LA</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>C</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Non-metro</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1119190</th>\n",
              "      <td>2020-12-13</td>\n",
              "      <td>13293</td>\n",
              "      <td>51</td>\n",
              "      <td>Upson County</td>\n",
              "      <td>GA</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>D</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Non-metro</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1119191</th>\n",
              "      <td>2020-12-13</td>\n",
              "      <td>48137</td>\n",
              "      <td>51</td>\n",
              "      <td>Edwards County</td>\n",
              "      <td>TX</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>B</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Non-metro</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1119192</th>\n",
              "      <td>2020-12-13</td>\n",
              "      <td>13143</td>\n",
              "      <td>51</td>\n",
              "      <td>Haralson County</td>\n",
              "      <td>GA</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>C</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Metro</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1119193</th>\n",
              "      <td>2020-12-13</td>\n",
              "      <td>39077</td>\n",
              "      <td>51</td>\n",
              "      <td>Huron County</td>\n",
              "      <td>OH</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>B</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Non-metro</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1119194 rows × 32 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "              Date  ... Series_Complete_65PlusPop_Pct_UR_Equity\n",
              "0       2021-11-17  ...                                     4.0\n",
              "1       2021-11-17  ...                                     3.0\n",
              "2       2021-11-17  ...                                     7.0\n",
              "3       2021-11-17  ...                                     8.0\n",
              "4       2021-11-17  ...                                     7.0\n",
              "...            ...  ...                                     ...\n",
              "1119189 2020-12-13  ...                                     NaN\n",
              "1119190 2020-12-13  ...                                     NaN\n",
              "1119191 2020-12-13  ...                                     NaN\n",
              "1119192 2020-12-13  ...                                     NaN\n",
              "1119193 2020-12-13  ...                                     NaN\n",
              "\n",
              "[1119194 rows x 32 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "a4w_qSe15B94"
      },
      "source": [
        "# Analisando a base de dados"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZGaf6JMW42uo",
        "outputId": "4f9e2679-315b-445c-ceb8-1108ee1bf56c"
      },
      "source": [
        "print(df.info())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 1119194 entries, 0 to 1119193\n",
            "Data columns (total 32 columns):\n",
            " #   Column                                   Non-Null Count    Dtype         \n",
            "---  ------                                   --------------    -----         \n",
            " 0   Date                                     1119194 non-null  datetime64[ns]\n",
            " 1   FIPS                                     1119194 non-null  object        \n",
            " 2   MMWR_week                                1119194 non-null  int64         \n",
            " 3   Recip_County                             1119194 non-null  object        \n",
            " 4   Recip_State                              1119194 non-null  object        \n",
            " 5   Series_Complete_Pop_Pct                  1119194 non-null  float64       \n",
            " 6   Series_Complete_Yes                      1119194 non-null  int64         \n",
            " 7   Series_Complete_12Plus                   1103848 non-null  float64       \n",
            " 8   Series_Complete_12PlusPop_Pct            1103848 non-null  float64       \n",
            " 9   Series_Complete_18Plus                   1119194 non-null  int64         \n",
            " 10  Series_Complete_18PlusPop_Pct            1119194 non-null  float64       \n",
            " 11  Series_Complete_65Plus                   1119194 non-null  int64         \n",
            " 12  Series_Complete_65PlusPop_Pct            1119194 non-null  float64       \n",
            " 13  Completeness_pct                         1119194 non-null  float64       \n",
            " 14  Administered_Dose1_Recip                 1084005 non-null  float64       \n",
            " 15  Administered_Dose1_Pop_Pct               1119194 non-null  float64       \n",
            " 16  Administered_Dose1_Recip_12Plus          1042424 non-null  float64       \n",
            " 17  Administered_Dose1_Recip_12PlusPop_Pct   1103848 non-null  float64       \n",
            " 18  Administered_Dose1_Recip_18Plus          1057571 non-null  float64       \n",
            " 19  Administered_Dose1_Recip_18PlusPop_Pct   1119194 non-null  float64       \n",
            " 20  Administered_Dose1_Recip_65Plus          1057571 non-null  float64       \n",
            " 21  Administered_Dose1_Recip_65PlusPop_Pct   1119194 non-null  float64       \n",
            " 22  SVI_CTGY                                 1097890 non-null  object        \n",
            " 23  Series_Complete_Pop_Pct_SVI              894828 non-null   float64       \n",
            " 24  Series_Complete_12PlusPop_Pct_SVI        881487 non-null   float64       \n",
            " 25  Series_Complete_18PlusPop_Pct_SVI        894828 non-null   float64       \n",
            " 26  Series_Complete_65PlusPop_Pct_SVI        894828 non-null   float64       \n",
            " 27  Metro_status                             1097890 non-null  object        \n",
            " 28  Series_Complete_Pop_Pct_UR_Equity        893959 non-null   float64       \n",
            " 29  Series_Complete_12PlusPop_Pct_UR_Equity  880752 non-null   float64       \n",
            " 30  Series_Complete_18PlusPop_Pct_UR_Equity  894171 non-null   float64       \n",
            " 31  Series_Complete_65PlusPop_Pct_UR_Equity  893453 non-null   float64       \n",
            "dtypes: datetime64[ns](1), float64(22), int64(4), object(5)\n",
            "memory usage: 273.2+ MB\n",
            "None\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YEyOdgwSFsZC"
      },
      "source": [
        "Podemos verificar que a base de dados contém 1 coluna do tipo datetime, 22 colunas do tipo float, 4 colunas do tipo int e 5 colunas do tipo string\n",
        "\n",
        "Podemos verificar também que algumas colunas contém dados faltantes"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yi-W4L6f5M-p"
      },
      "source": [
        "# Traduzindo o Schema para Português-BR"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZSzsSxsi5Du6"
      },
      "source": [
        "df.rename(columns={'Date': 'Data',\n",
        "                   'FIPS': 'CEPPIF', #Código Estadual Padrão de Processamento de Informações Federais\n",
        "                   'MMWR_week': 'Relatorio_semanal_morbidade_mortalidade', #controle e prevenção de doenças\n",
        "                   'Recip_County': 'Condado', #região em que reside o paciente\n",
        "                   'Recip_State': 'Estado', #estado em que reside o paciente\n",
        "                   'Series_Complete_Pop_Pct': 'Porcentagem_populacao_vacinada', #Porcentagem de pessoas que estão totalmente vacinadas (têm segunda dose de uma vacina de duas doses ou uma dose de uma vacina de dose única) com base na jurisdição e no condado onde vive o paciente\n",
        "                   'Series_Complete_Yes': 'Numero_total_vacinados', #Número total de pessoas que estão totalmente vacinadas (têm segunda dose de uma vacina de duas doses ou uma dose de uma vacina de dose única) com base na jurisdição e no condado onde vive o paciente\n",
        "                   'Series_Complete_12Plus': 'Numero_total_12+', #Número total de pessoas com mais de 12 anos que estão totalmente vacinadas (têm uma segunda dose de uma vacina de duas doses ou uma dose de uma vacina de dose única) com base na jurisdição onde vive o paciente\n",
        "                   'Series_Complete_12PlusPop_Pct': 'Porcentagem_total_12+', #Porcentagem de pessoas com mais de 12 anos que estão totalmente vacinadas (têm uma segunda dose de uma vacina de duas doses ou uma dose de uma vacina de dose única) com base na jurisdição onde vive o paciente\n",
        "                   'Series_Complete_18Plus': 'Numero_total_18+', #Número total de pessoas com mais de 18 anos que estão totalmente vacinadas (têm uma segunda dose de uma vacina de duas doses ou uma dose de uma vacina de dose única) com base na jurisdição e no condado onde vive o paciente\n",
        "                   'Series_Complete_18PlusPop_Pct': 'Porcentagem_total_18+', #Porcentagem de pessoas com mais de 18 anos que estão totalmente vacinadas (têm uma segunda dose de uma vacina de duas doses ou uma dose de uma vacina de dose única) com base na jurisdição e no condado onde vive o paciente\n",
        "                   'Series_Complete_65Plus': 'Numero_total_65+', #Número total de pessoas com mais de 65 anos que estão totalmente vacinadas (têm uma segunda dose de uma vacina de duas doses ou uma dose de uma vacina de dose única) com base na jurisdição onde vive o paciente\n",
        "                   'Series_Complete_65PlusPop_Pct': 'Porcentagem_total_65+', #Porcentagem de pessoas com mais de 65 anos que estão totalmente vacinadas (têm uma segunda dose de uma vacina de duas doses ou uma dose de uma vacina de dose única) com base na jurisdição onde vive o paciente\n",
        "                   'Completeness_pct': 'Porcentagem_total_pessoas_vacinadas', #Representa a proporção de pessoas totalmente vacinadas cujo código Federal Information Processing Standards (FIPS) é relatado e corresponde a um código FIPS de condado válido na jurisdição.\n",
        "                   'Administered_Dose1_Recip': 'Primeira_dose', #Pessoas com pelo menos uma dose por estado de residência\n",
        "                   'Administered_Dose1_Pop_Pct': 'Porcentagem_primeira_dose', #Porcentagem da População total com pelo menos uma dose por estado de residência\n",
        "                   'Administered_Dose1_Recip_12Plus': 'Primeira_dose_12+', #Pessoas com mais de 12 anos com pelo menos uma dose por estado de residência\n",
        "                   'Administered_Dose1_Recip_12PlusPop_Pct': 'Porcentagem_primeira_dose_12+', #Porcentagem de 12+ Pop com pelo menos uma dose por estado de residência\n",
        "                   'Administered_Dose1_Recip_18Plus': 'Primeira_dose_18+', #Pessoas com mais de 18 anos com pelo menos uma dose por estado de residência\n",
        "                   'Administered_Dose1_Recip_18PlusPop_Pct': 'Porcentagem_primeira_dose_18+', #Porcentagem de Pop 18+ com pelo menos uma dose por estado de residência\n",
        "                   'Administered_Dose1_Recip_65Plus': 'Primeira_dose_65+', #Pessoas com mais de 65 anos com pelo menos uma dose por estado de residência\n",
        "                   'Administered_Dose1_Recip_65PlusPop_Pct': 'Porcentagem_primeira_dose_65+', #Porcentagem de Pop com mais de 65 anos com pelo menos uma dose por estado de residência\n",
        "                   'SVI_CTGY': 'IVS_Categoria', #Índice de Vulnerabilidade Social por Categoria\n",
        "                   'Series_Complete_Pop_Pct_SVI': 'Porcentagem_total_pop_vacinada', #Porcentagem da população totalmente vacinada / IVS\n",
        "                   'Series_Complete_12PlusPop_Pct_SVI': 'Porcentagem_total_12+_IVS', #Porcentagem da população com 12+ totalmente vacinadas / IVS\n",
        "                   'Series_Complete_18PlusPop_Pct_SVI': 'Porcentagem_total_18+_IVS', #Porcentagem da população com 18+ totalmente vacinadas / IVS\n",
        "                   'Series_Complete_65PlusPop_Pct_SVI': 'Porcentagem_total_65+_IVS', #Porcentagem da população com 65+ totalmente vacinadas / IVS\n",
        "                   'Metro_status': 'Status_metropolitano', #Status da área metropolitana (se é uma área metropolitana ou não metropolitana)\n",
        "                   'Series_Complete_Pop_Pct_UR_Equity': 'Porcentagem_total_metropolitana/NaoMetropolitana', #Porcentagem da população totalmente vacinada - Metropolitana / Não Metropolitana\n",
        "                   'Series_Complete_12PlusPop_Pct_UR_Equity': 'Porcentagem_total_12+_metropolitana/NaoMetropolitana',  #Porcentagem da população com 12+ totalmente vacinada - Metropolitana / Não Metropolitana\n",
        "                   'Series_Complete_18PlusPop_Pct_UR_Equity': 'Porcentagem_total_18+_metropolitana/NaoMetropolitana', #Porcentagem da população com 18+ totalmente vacinada - Metropolitana / Não Metropolitana\n",
        "                   'Series_Complete_65PlusPop_Pct_UR_Equity': 'Porcentagem_total_65+_metropolitana/NaoMetropolitana' #Porcentagem da população com 65+ totalmente vacinada - Metropolitana / Não Metropolitana\n",
        "\n",
        "                   }, inplace = True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 313
        },
        "id": "Tx9JiDe8J1g7",
        "outputId": "4bc0e331-8eba-414a-d38d-fef7505c6cbd"
      },
      "source": [
        "df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>CEPPIF</th>\n",
              "      <th>Relatorio_semanal_morbidade_mortalidade</th>\n",
              "      <th>Condado</th>\n",
              "      <th>Estado</th>\n",
              "      <th>Porcentagem_populacao_vacinada</th>\n",
              "      <th>Numero_total_vacinados</th>\n",
              "      <th>Numero_total_12+</th>\n",
              "      <th>Porcentagem_total_12+</th>\n",
              "      <th>Numero_total_18+</th>\n",
              "      <th>Porcentagem_total_18+</th>\n",
              "      <th>Numero_total_65+</th>\n",
              "      <th>Porcentagem_total_65+</th>\n",
              "      <th>Porcentagem_total_pessoas_vacinadas</th>\n",
              "      <th>Primeira_dose</th>\n",
              "      <th>Porcentagem_primeira_dose</th>\n",
              "      <th>Primeira_dose_12+</th>\n",
              "      <th>Porcentagem_primeira_dose_12+</th>\n",
              "      <th>Primeira_dose_18+</th>\n",
              "      <th>Porcentagem_primeira_dose_18+</th>\n",
              "      <th>Primeira_dose_65+</th>\n",
              "      <th>Porcentagem_primeira_dose_65+</th>\n",
              "      <th>IVS_Categoria</th>\n",
              "      <th>Porcentagem_total_pop_vacinada</th>\n",
              "      <th>Porcentagem_total_12+_IVS</th>\n",
              "      <th>Porcentagem_total_18+_IVS</th>\n",
              "      <th>Porcentagem_total_65+_IVS</th>\n",
              "      <th>Status_metropolitano</th>\n",
              "      <th>Porcentagem_total_metropolitana/NaoMetropolitana</th>\n",
              "      <th>Porcentagem_total_12+_metropolitana/NaoMetropolitana</th>\n",
              "      <th>Porcentagem_total_18+_metropolitana/NaoMetropolitana</th>\n",
              "      <th>Porcentagem_total_65+_metropolitana/NaoMetropolitana</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>19149</td>\n",
              "      <td>46</td>\n",
              "      <td>Plymouth County</td>\n",
              "      <td>IA</td>\n",
              "      <td>48.3</td>\n",
              "      <td>12168</td>\n",
              "      <td>12168.0</td>\n",
              "      <td>57.6</td>\n",
              "      <td>11528</td>\n",
              "      <td>61.1</td>\n",
              "      <td>3917</td>\n",
              "      <td>83.9</td>\n",
              "      <td>97.4</td>\n",
              "      <td>12921.0</td>\n",
              "      <td>51.3</td>\n",
              "      <td>12857.0</td>\n",
              "      <td>60.9</td>\n",
              "      <td>12175.0</td>\n",
              "      <td>64.5</td>\n",
              "      <td>4077.0</td>\n",
              "      <td>87.4</td>\n",
              "      <td>A</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>Metro</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>01021</td>\n",
              "      <td>46</td>\n",
              "      <td>Chilton County</td>\n",
              "      <td>AL</td>\n",
              "      <td>31.9</td>\n",
              "      <td>14178</td>\n",
              "      <td>14177.0</td>\n",
              "      <td>37.8</td>\n",
              "      <td>13447</td>\n",
              "      <td>39.7</td>\n",
              "      <td>4688</td>\n",
              "      <td>61.7</td>\n",
              "      <td>92.6</td>\n",
              "      <td>17431.0</td>\n",
              "      <td>39.2</td>\n",
              "      <td>17413.0</td>\n",
              "      <td>46.5</td>\n",
              "      <td>16523.0</td>\n",
              "      <td>48.8</td>\n",
              "      <td>5480.0</td>\n",
              "      <td>72.1</td>\n",
              "      <td>D</td>\n",
              "      <td>14.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>Metro</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>20167</td>\n",
              "      <td>46</td>\n",
              "      <td>Russell County</td>\n",
              "      <td>KS</td>\n",
              "      <td>39.8</td>\n",
              "      <td>2727</td>\n",
              "      <td>2727.0</td>\n",
              "      <td>46.8</td>\n",
              "      <td>2636</td>\n",
              "      <td>49.1</td>\n",
              "      <td>1112</td>\n",
              "      <td>65.6</td>\n",
              "      <td>93.6</td>\n",
              "      <td>3013.0</td>\n",
              "      <td>43.9</td>\n",
              "      <td>3002.0</td>\n",
              "      <td>51.6</td>\n",
              "      <td>2894.0</td>\n",
              "      <td>53.9</td>\n",
              "      <td>1197.0</td>\n",
              "      <td>70.7</td>\n",
              "      <td>A</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Non-metro</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>36031</td>\n",
              "      <td>46</td>\n",
              "      <td>Essex County</td>\n",
              "      <td>NY</td>\n",
              "      <td>65.8</td>\n",
              "      <td>24262</td>\n",
              "      <td>24262.0</td>\n",
              "      <td>73.1</td>\n",
              "      <td>22876</td>\n",
              "      <td>73.8</td>\n",
              "      <td>7418</td>\n",
              "      <td>82.9</td>\n",
              "      <td>97.6</td>\n",
              "      <td>25992.0</td>\n",
              "      <td>70.5</td>\n",
              "      <td>25723.0</td>\n",
              "      <td>77.5</td>\n",
              "      <td>24189.0</td>\n",
              "      <td>78.1</td>\n",
              "      <td>7853.0</td>\n",
              "      <td>87.8</td>\n",
              "      <td>B</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>Non-metro</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>16017</td>\n",
              "      <td>46</td>\n",
              "      <td>Bonner County</td>\n",
              "      <td>ID</td>\n",
              "      <td>37.8</td>\n",
              "      <td>17308</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>17267</td>\n",
              "      <td>47.0</td>\n",
              "      <td>7946</td>\n",
              "      <td>68.4</td>\n",
              "      <td>97.6</td>\n",
              "      <td>19484.0</td>\n",
              "      <td>42.6</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>19428.0</td>\n",
              "      <td>52.9</td>\n",
              "      <td>8714.0</td>\n",
              "      <td>75.0</td>\n",
              "      <td>A</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Non-metro</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        Data  ... Porcentagem_total_65+_metropolitana/NaoMetropolitana\n",
              "0 2021-11-17  ...                                                4.0  \n",
              "1 2021-11-17  ...                                                3.0  \n",
              "2 2021-11-17  ...                                                7.0  \n",
              "3 2021-11-17  ...                                                8.0  \n",
              "4 2021-11-17  ...                                                7.0  \n",
              "\n",
              "[5 rows x 32 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sUAbGGzgRCu9"
      },
      "source": [
        "# Verificando se a coluna **Relatorio_semanal_morbidade_mortalidade** contém valores únicos"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5uPK_TCIJ6_q",
        "outputId": "1f61b355-3176-40d5-8cd6-3ad5d4c20590"
      },
      "source": [
        "#Verificação realizada para saber o que cada código significava\n",
        "pd.unique(df['Relatorio_semanal_morbidade_mortalidade'])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([46, 45, 44, 43, 42, 41, 40, 39, 38, 37, 36, 35, 34, 33, 32, 31, 30,\n",
              "       29, 28, 27, 26, 25, 24, 23, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13,\n",
              "       12, 11, 10,  9,  8,  7,  6,  5,  4,  3,  2,  1, 53, 52, 51])"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HHspJPo9Rl1W"
      },
      "source": [
        "# Deletando colunas que não fazem sentido para a análise de dados"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BS6SZFX3MVYZ"
      },
      "source": [
        "df.drop(['CEPPIF', 'Relatorio_semanal_morbidade_mortalidade', 'Porcentagem_populacao_vacinada'], axis = 1, inplace = True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Pr1SzLJmNK2e"
      },
      "source": [
        "\n",
        "\n",
        "1.   A coluna **CEPPIF** representa o código da região federal, como já temos o condado e o estado, não será necessária na base de dados.\n",
        "\n",
        "2.   Como não foi encontrado o que representa cada código da coluna **Relatorio_semanal_morbidade_mortalidade**, resolvemos dropar para não atrapalhar a análise de dados.\n",
        "\n",
        "3.   A coluna **Porcentagem_populacao_vacinada** faz referência a coluna **Relatorio_semanal_morbidade_mortalidade**, então não faz sentido deixar se não sabemos o que representa cada código da coluna de relatório."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 313
        },
        "id": "Rjz1m-mHRbv8",
        "outputId": "91ac9c3c-3deb-413c-f20f-6d35f8b6a2c0"
      },
      "source": [
        "df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Condado</th>\n",
              "      <th>Estado</th>\n",
              "      <th>Numero_total_vacinados</th>\n",
              "      <th>Numero_total_12+</th>\n",
              "      <th>Porcentagem_total_12+</th>\n",
              "      <th>Numero_total_18+</th>\n",
              "      <th>Porcentagem_total_18+</th>\n",
              "      <th>Numero_total_65+</th>\n",
              "      <th>Porcentagem_total_65+</th>\n",
              "      <th>Porcentagem_total_pessoas_vacinadas</th>\n",
              "      <th>Primeira_dose</th>\n",
              "      <th>Porcentagem_primeira_dose</th>\n",
              "      <th>Primeira_dose_12+</th>\n",
              "      <th>Porcentagem_primeira_dose_12+</th>\n",
              "      <th>Primeira_dose_18+</th>\n",
              "      <th>Porcentagem_primeira_dose_18+</th>\n",
              "      <th>Primeira_dose_65+</th>\n",
              "      <th>Porcentagem_primeira_dose_65+</th>\n",
              "      <th>IVS_Categoria</th>\n",
              "      <th>Porcentagem_total_pop_vacinada</th>\n",
              "      <th>Porcentagem_total_12+_IVS</th>\n",
              "      <th>Porcentagem_total_18+_IVS</th>\n",
              "      <th>Porcentagem_total_65+_IVS</th>\n",
              "      <th>Status_metropolitano</th>\n",
              "      <th>Porcentagem_total_metropolitana/NaoMetropolitana</th>\n",
              "      <th>Porcentagem_total_12+_metropolitana/NaoMetropolitana</th>\n",
              "      <th>Porcentagem_total_18+_metropolitana/NaoMetropolitana</th>\n",
              "      <th>Porcentagem_total_65+_metropolitana/NaoMetropolitana</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>Plymouth County</td>\n",
              "      <td>IA</td>\n",
              "      <td>12168</td>\n",
              "      <td>12168.0</td>\n",
              "      <td>57.6</td>\n",
              "      <td>11528</td>\n",
              "      <td>61.1</td>\n",
              "      <td>3917</td>\n",
              "      <td>83.9</td>\n",
              "      <td>97.4</td>\n",
              "      <td>12921.0</td>\n",
              "      <td>51.3</td>\n",
              "      <td>12857.0</td>\n",
              "      <td>60.9</td>\n",
              "      <td>12175.0</td>\n",
              "      <td>64.5</td>\n",
              "      <td>4077.0</td>\n",
              "      <td>87.4</td>\n",
              "      <td>A</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>Metro</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>Chilton County</td>\n",
              "      <td>AL</td>\n",
              "      <td>14178</td>\n",
              "      <td>14177.0</td>\n",
              "      <td>37.8</td>\n",
              "      <td>13447</td>\n",
              "      <td>39.7</td>\n",
              "      <td>4688</td>\n",
              "      <td>61.7</td>\n",
              "      <td>92.6</td>\n",
              "      <td>17431.0</td>\n",
              "      <td>39.2</td>\n",
              "      <td>17413.0</td>\n",
              "      <td>46.5</td>\n",
              "      <td>16523.0</td>\n",
              "      <td>48.8</td>\n",
              "      <td>5480.0</td>\n",
              "      <td>72.1</td>\n",
              "      <td>D</td>\n",
              "      <td>14.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>Metro</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>Russell County</td>\n",
              "      <td>KS</td>\n",
              "      <td>2727</td>\n",
              "      <td>2727.0</td>\n",
              "      <td>46.8</td>\n",
              "      <td>2636</td>\n",
              "      <td>49.1</td>\n",
              "      <td>1112</td>\n",
              "      <td>65.6</td>\n",
              "      <td>93.6</td>\n",
              "      <td>3013.0</td>\n",
              "      <td>43.9</td>\n",
              "      <td>3002.0</td>\n",
              "      <td>51.6</td>\n",
              "      <td>2894.0</td>\n",
              "      <td>53.9</td>\n",
              "      <td>1197.0</td>\n",
              "      <td>70.7</td>\n",
              "      <td>A</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Non-metro</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>Essex County</td>\n",
              "      <td>NY</td>\n",
              "      <td>24262</td>\n",
              "      <td>24262.0</td>\n",
              "      <td>73.1</td>\n",
              "      <td>22876</td>\n",
              "      <td>73.8</td>\n",
              "      <td>7418</td>\n",
              "      <td>82.9</td>\n",
              "      <td>97.6</td>\n",
              "      <td>25992.0</td>\n",
              "      <td>70.5</td>\n",
              "      <td>25723.0</td>\n",
              "      <td>77.5</td>\n",
              "      <td>24189.0</td>\n",
              "      <td>78.1</td>\n",
              "      <td>7853.0</td>\n",
              "      <td>87.8</td>\n",
              "      <td>B</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>Non-metro</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>Bonner County</td>\n",
              "      <td>ID</td>\n",
              "      <td>17308</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>17267</td>\n",
              "      <td>47.0</td>\n",
              "      <td>7946</td>\n",
              "      <td>68.4</td>\n",
              "      <td>97.6</td>\n",
              "      <td>19484.0</td>\n",
              "      <td>42.6</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>19428.0</td>\n",
              "      <td>52.9</td>\n",
              "      <td>8714.0</td>\n",
              "      <td>75.0</td>\n",
              "      <td>A</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Non-metro</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        Data  ... Porcentagem_total_65+_metropolitana/NaoMetropolitana\n",
              "0 2021-11-17  ...                                                4.0  \n",
              "1 2021-11-17  ...                                                3.0  \n",
              "2 2021-11-17  ...                                                7.0  \n",
              "3 2021-11-17  ...                                                8.0  \n",
              "4 2021-11-17  ...                                                7.0  \n",
              "\n",
              "[5 rows x 29 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ELjE7khgRvo8"
      },
      "source": [
        "# Verificando os valores nulos"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-u2qIkqGRhvs",
        "outputId": "b3d8485d-a4b9-4316-a128-c6ef32a837c6"
      },
      "source": [
        "df.isna().sum()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Data                                                         0\n",
              "Condado                                                      0\n",
              "Estado                                                       0\n",
              "Numero_total_vacinados                                       0\n",
              "Numero_total_12+                                         15346\n",
              "Porcentagem_total_12+                                    15346\n",
              "Numero_total_18+                                             0\n",
              "Porcentagem_total_18+                                        0\n",
              "Numero_total_65+                                             0\n",
              "Porcentagem_total_65+                                        0\n",
              "Porcentagem_total_pessoas_vacinadas                          0\n",
              "Primeira_dose                                            35189\n",
              "Porcentagem_primeira_dose                                    0\n",
              "Primeira_dose_12+                                        76770\n",
              "Porcentagem_primeira_dose_12+                            15346\n",
              "Primeira_dose_18+                                        61623\n",
              "Porcentagem_primeira_dose_18+                                0\n",
              "Primeira_dose_65+                                        61623\n",
              "Porcentagem_primeira_dose_65+                                0\n",
              "IVS_Categoria                                            21304\n",
              "Porcentagem_total_pop_vacinada                          224366\n",
              "Porcentagem_total_12+_IVS                               237707\n",
              "Porcentagem_total_18+_IVS                               224366\n",
              "Porcentagem_total_65+_IVS                               224366\n",
              "Status_metropolitano                                     21304\n",
              "Porcentagem_total_metropolitana/NaoMetropolitana        225235\n",
              "Porcentagem_total_12+_metropolitana/NaoMetropolitana    238442\n",
              "Porcentagem_total_18+_metropolitana/NaoMetropolitana    225023\n",
              "Porcentagem_total_65+_metropolitana/NaoMetropolitana    225741\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "J7ldsn5STfBT"
      },
      "source": [
        "# Deletando linhas com dados faltantes"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0GhBxGLv6uYI",
        "outputId": "ad66945e-5a20-443b-feaf-49453337b476"
      },
      "source": [
        "#Verificando os valores conditos na coluna 'Status_metropolitano'\n",
        "pd.unique(df['Status_metropolitano'])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Metro', 'Non-metro', nan], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nxwavRanfRLQ"
      },
      "source": [
        "#Deletando valores nulos da coluna 'Status_metropolitano'\n",
        "df.dropna(subset = ['Status_metropolitano'], inplace = True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 313
        },
        "id": "9mxA3gDKKvDf",
        "outputId": "92dc8f4f-ee81-4697-b33e-b0b72fa222e2"
      },
      "source": [
        "#Traduzindo os valores conditos na coluna 'Status_metropolitano'\n",
        "\n",
        "df.loc[df.Status_metropolitano == 'Metro', ['Status_metropolitano']] = 'Metropolitano'\n",
        "df.loc[df.Status_metropolitano == 'Non-metro', ['Status_metropolitano']] = 'Não Metropolitano'\n",
        "\n",
        "df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Condado</th>\n",
              "      <th>Estado</th>\n",
              "      <th>Numero_total_vacinados</th>\n",
              "      <th>Numero_total_12+</th>\n",
              "      <th>Porcentagem_total_12+</th>\n",
              "      <th>Numero_total_18+</th>\n",
              "      <th>Porcentagem_total_18+</th>\n",
              "      <th>Numero_total_65+</th>\n",
              "      <th>Porcentagem_total_65+</th>\n",
              "      <th>Porcentagem_total_pessoas_vacinadas</th>\n",
              "      <th>Primeira_dose</th>\n",
              "      <th>Porcentagem_primeira_dose</th>\n",
              "      <th>Primeira_dose_12+</th>\n",
              "      <th>Porcentagem_primeira_dose_12+</th>\n",
              "      <th>Primeira_dose_18+</th>\n",
              "      <th>Porcentagem_primeira_dose_18+</th>\n",
              "      <th>Primeira_dose_65+</th>\n",
              "      <th>Porcentagem_primeira_dose_65+</th>\n",
              "      <th>IVS_Categoria</th>\n",
              "      <th>Porcentagem_total_pop_vacinada</th>\n",
              "      <th>Porcentagem_total_12+_IVS</th>\n",
              "      <th>Porcentagem_total_18+_IVS</th>\n",
              "      <th>Porcentagem_total_65+_IVS</th>\n",
              "      <th>Status_metropolitano</th>\n",
              "      <th>Porcentagem_total_metropolitana/NaoMetropolitana</th>\n",
              "      <th>Porcentagem_total_12+_metropolitana/NaoMetropolitana</th>\n",
              "      <th>Porcentagem_total_18+_metropolitana/NaoMetropolitana</th>\n",
              "      <th>Porcentagem_total_65+_metropolitana/NaoMetropolitana</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>Plymouth County</td>\n",
              "      <td>IA</td>\n",
              "      <td>12168</td>\n",
              "      <td>12168.0</td>\n",
              "      <td>57.6</td>\n",
              "      <td>11528</td>\n",
              "      <td>61.1</td>\n",
              "      <td>3917</td>\n",
              "      <td>83.9</td>\n",
              "      <td>97.4</td>\n",
              "      <td>12921.0</td>\n",
              "      <td>51.3</td>\n",
              "      <td>12857.0</td>\n",
              "      <td>60.9</td>\n",
              "      <td>12175.0</td>\n",
              "      <td>64.5</td>\n",
              "      <td>4077.0</td>\n",
              "      <td>87.4</td>\n",
              "      <td>A</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>Metropolitano</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>Chilton County</td>\n",
              "      <td>AL</td>\n",
              "      <td>14178</td>\n",
              "      <td>14177.0</td>\n",
              "      <td>37.8</td>\n",
              "      <td>13447</td>\n",
              "      <td>39.7</td>\n",
              "      <td>4688</td>\n",
              "      <td>61.7</td>\n",
              "      <td>92.6</td>\n",
              "      <td>17431.0</td>\n",
              "      <td>39.2</td>\n",
              "      <td>17413.0</td>\n",
              "      <td>46.5</td>\n",
              "      <td>16523.0</td>\n",
              "      <td>48.8</td>\n",
              "      <td>5480.0</td>\n",
              "      <td>72.1</td>\n",
              "      <td>D</td>\n",
              "      <td>14.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>Metropolitano</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>Russell County</td>\n",
              "      <td>KS</td>\n",
              "      <td>2727</td>\n",
              "      <td>2727.0</td>\n",
              "      <td>46.8</td>\n",
              "      <td>2636</td>\n",
              "      <td>49.1</td>\n",
              "      <td>1112</td>\n",
              "      <td>65.6</td>\n",
              "      <td>93.6</td>\n",
              "      <td>3013.0</td>\n",
              "      <td>43.9</td>\n",
              "      <td>3002.0</td>\n",
              "      <td>51.6</td>\n",
              "      <td>2894.0</td>\n",
              "      <td>53.9</td>\n",
              "      <td>1197.0</td>\n",
              "      <td>70.7</td>\n",
              "      <td>A</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Não Metropolitano</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>Essex County</td>\n",
              "      <td>NY</td>\n",
              "      <td>24262</td>\n",
              "      <td>24262.0</td>\n",
              "      <td>73.1</td>\n",
              "      <td>22876</td>\n",
              "      <td>73.8</td>\n",
              "      <td>7418</td>\n",
              "      <td>82.9</td>\n",
              "      <td>97.6</td>\n",
              "      <td>25992.0</td>\n",
              "      <td>70.5</td>\n",
              "      <td>25723.0</td>\n",
              "      <td>77.5</td>\n",
              "      <td>24189.0</td>\n",
              "      <td>78.1</td>\n",
              "      <td>7853.0</td>\n",
              "      <td>87.8</td>\n",
              "      <td>B</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>Não Metropolitano</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>Bonner County</td>\n",
              "      <td>ID</td>\n",
              "      <td>17308</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>17267</td>\n",
              "      <td>47.0</td>\n",
              "      <td>7946</td>\n",
              "      <td>68.4</td>\n",
              "      <td>97.6</td>\n",
              "      <td>19484.0</td>\n",
              "      <td>42.6</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>19428.0</td>\n",
              "      <td>52.9</td>\n",
              "      <td>8714.0</td>\n",
              "      <td>75.0</td>\n",
              "      <td>A</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Não Metropolitano</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        Data  ... Porcentagem_total_65+_metropolitana/NaoMetropolitana\n",
              "0 2021-11-17  ...                                                4.0  \n",
              "1 2021-11-17  ...                                                3.0  \n",
              "2 2021-11-17  ...                                                7.0  \n",
              "3 2021-11-17  ...                                                8.0  \n",
              "4 2021-11-17  ...                                                7.0  \n",
              "\n",
              "[5 rows x 29 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "scYKa0GIDiqb",
        "outputId": "aefbecfc-f552-4d0b-b9d9-1932a291f666"
      },
      "source": [
        "#Verificando os valores conditos na coluna 'IVS_Categoria'\n",
        "pd.unique(df['IVS_Categoria'])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['A', 'D', 'B', 'C', nan], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9OTpgPI-eyb5"
      },
      "source": [
        "#Deletando valores nulos da coluna 'IVS_Categoria'\n",
        "df.dropna(subset = ['IVS_Categoria'], inplace = True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2DAbDNiEEcoa",
        "outputId": "646cadbc-fc47-44a0-a86f-c2622f4c6d7a"
      },
      "source": [
        "#Conferindo se os valores nulos das colunas 'Status_metropolitano' e 'IVS_Categoria' foram deletados\n",
        "df.isna().sum()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Data                                                         0\n",
              "Condado                                                      0\n",
              "Estado                                                       0\n",
              "Numero_total_vacinados                                       0\n",
              "Numero_total_12+                                         15007\n",
              "Porcentagem_total_12+                                    15007\n",
              "Numero_total_18+                                             0\n",
              "Porcentagem_total_18+                                        0\n",
              "Numero_total_65+                                             0\n",
              "Porcentagem_total_65+                                        0\n",
              "Porcentagem_total_pessoas_vacinadas                          0\n",
              "Primeira_dose                                            34260\n",
              "Porcentagem_primeira_dose                                    0\n",
              "Primeira_dose_12+                                        73867\n",
              "Porcentagem_primeira_dose_12+                            15007\n",
              "Primeira_dose_18+                                        58860\n",
              "Porcentagem_primeira_dose_18+                                0\n",
              "Primeira_dose_65+                                        58860\n",
              "Porcentagem_primeira_dose_65+                                0\n",
              "IVS_Categoria                                                0\n",
              "Porcentagem_total_pop_vacinada                          203028\n",
              "Porcentagem_total_12+_IVS                               216369\n",
              "Porcentagem_total_18+_IVS                               203028\n",
              "Porcentagem_total_65+_IVS                               203028\n",
              "Status_metropolitano                                         0\n",
              "Porcentagem_total_metropolitana/NaoMetropolitana        203892\n",
              "Porcentagem_total_12+_metropolitana/NaoMetropolitana    217099\n",
              "Porcentagem_total_18+_metropolitana/NaoMetropolitana    203680\n",
              "Porcentagem_total_65+_metropolitana/NaoMetropolitana    204398\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MEdDuMUCXJPA"
      },
      "source": [
        "# Substituindo valores nulos por 0"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gQx1kfsIUEjT"
      },
      "source": [
        "#Substituindo os valores nulos das colunas restantes por 0 para facilitar a análise estatística do DataFrame\n",
        "df.fillna(0, inplace = True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 313
        },
        "id": "RaEwBTkzXtzH",
        "outputId": "3f9aeea8-6026-46d3-f876-4d7869134d30"
      },
      "source": [
        "df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Condado</th>\n",
              "      <th>Estado</th>\n",
              "      <th>Numero_total_vacinados</th>\n",
              "      <th>Numero_total_12+</th>\n",
              "      <th>Porcentagem_total_12+</th>\n",
              "      <th>Numero_total_18+</th>\n",
              "      <th>Porcentagem_total_18+</th>\n",
              "      <th>Numero_total_65+</th>\n",
              "      <th>Porcentagem_total_65+</th>\n",
              "      <th>Porcentagem_total_pessoas_vacinadas</th>\n",
              "      <th>Primeira_dose</th>\n",
              "      <th>Porcentagem_primeira_dose</th>\n",
              "      <th>Primeira_dose_12+</th>\n",
              "      <th>Porcentagem_primeira_dose_12+</th>\n",
              "      <th>Primeira_dose_18+</th>\n",
              "      <th>Porcentagem_primeira_dose_18+</th>\n",
              "      <th>Primeira_dose_65+</th>\n",
              "      <th>Porcentagem_primeira_dose_65+</th>\n",
              "      <th>IVS_Categoria</th>\n",
              "      <th>Porcentagem_total_pop_vacinada</th>\n",
              "      <th>Porcentagem_total_12+_IVS</th>\n",
              "      <th>Porcentagem_total_18+_IVS</th>\n",
              "      <th>Porcentagem_total_65+_IVS</th>\n",
              "      <th>Status_metropolitano</th>\n",
              "      <th>Porcentagem_total_metropolitana/NaoMetropolitana</th>\n",
              "      <th>Porcentagem_total_12+_metropolitana/NaoMetropolitana</th>\n",
              "      <th>Porcentagem_total_18+_metropolitana/NaoMetropolitana</th>\n",
              "      <th>Porcentagem_total_65+_metropolitana/NaoMetropolitana</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>Plymouth County</td>\n",
              "      <td>IA</td>\n",
              "      <td>12168</td>\n",
              "      <td>12168.0</td>\n",
              "      <td>57.6</td>\n",
              "      <td>11528</td>\n",
              "      <td>61.1</td>\n",
              "      <td>3917</td>\n",
              "      <td>83.9</td>\n",
              "      <td>97.4</td>\n",
              "      <td>12921.0</td>\n",
              "      <td>51.3</td>\n",
              "      <td>12857.0</td>\n",
              "      <td>60.9</td>\n",
              "      <td>12175.0</td>\n",
              "      <td>64.5</td>\n",
              "      <td>4077.0</td>\n",
              "      <td>87.4</td>\n",
              "      <td>A</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>Metropolitano</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>Chilton County</td>\n",
              "      <td>AL</td>\n",
              "      <td>14178</td>\n",
              "      <td>14177.0</td>\n",
              "      <td>37.8</td>\n",
              "      <td>13447</td>\n",
              "      <td>39.7</td>\n",
              "      <td>4688</td>\n",
              "      <td>61.7</td>\n",
              "      <td>92.6</td>\n",
              "      <td>17431.0</td>\n",
              "      <td>39.2</td>\n",
              "      <td>17413.0</td>\n",
              "      <td>46.5</td>\n",
              "      <td>16523.0</td>\n",
              "      <td>48.8</td>\n",
              "      <td>5480.0</td>\n",
              "      <td>72.1</td>\n",
              "      <td>D</td>\n",
              "      <td>14.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>Metropolitano</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>Russell County</td>\n",
              "      <td>KS</td>\n",
              "      <td>2727</td>\n",
              "      <td>2727.0</td>\n",
              "      <td>46.8</td>\n",
              "      <td>2636</td>\n",
              "      <td>49.1</td>\n",
              "      <td>1112</td>\n",
              "      <td>65.6</td>\n",
              "      <td>93.6</td>\n",
              "      <td>3013.0</td>\n",
              "      <td>43.9</td>\n",
              "      <td>3002.0</td>\n",
              "      <td>51.6</td>\n",
              "      <td>2894.0</td>\n",
              "      <td>53.9</td>\n",
              "      <td>1197.0</td>\n",
              "      <td>70.7</td>\n",
              "      <td>A</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Não Metropolitano</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>Essex County</td>\n",
              "      <td>NY</td>\n",
              "      <td>24262</td>\n",
              "      <td>24262.0</td>\n",
              "      <td>73.1</td>\n",
              "      <td>22876</td>\n",
              "      <td>73.8</td>\n",
              "      <td>7418</td>\n",
              "      <td>82.9</td>\n",
              "      <td>97.6</td>\n",
              "      <td>25992.0</td>\n",
              "      <td>70.5</td>\n",
              "      <td>25723.0</td>\n",
              "      <td>77.5</td>\n",
              "      <td>24189.0</td>\n",
              "      <td>78.1</td>\n",
              "      <td>7853.0</td>\n",
              "      <td>87.8</td>\n",
              "      <td>B</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>Não Metropolitano</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>Bonner County</td>\n",
              "      <td>ID</td>\n",
              "      <td>17308</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>17267</td>\n",
              "      <td>47.0</td>\n",
              "      <td>7946</td>\n",
              "      <td>68.4</td>\n",
              "      <td>97.6</td>\n",
              "      <td>19484.0</td>\n",
              "      <td>42.6</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>19428.0</td>\n",
              "      <td>52.9</td>\n",
              "      <td>8714.0</td>\n",
              "      <td>75.0</td>\n",
              "      <td>A</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Não Metropolitano</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        Data  ... Porcentagem_total_65+_metropolitana/NaoMetropolitana\n",
              "0 2021-11-17  ...                                                4.0  \n",
              "1 2021-11-17  ...                                                3.0  \n",
              "2 2021-11-17  ...                                                7.0  \n",
              "3 2021-11-17  ...                                                8.0  \n",
              "4 2021-11-17  ...                                                7.0  \n",
              "\n",
              "[5 rows x 29 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uOar-GKzXRgY",
        "outputId": "1950a95d-b8fb-4bc2-8e6d-723cb4143bd2"
      },
      "source": [
        "#Verificando se os valores nulos foram substituídos\n",
        "df.isna().sum()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Data                                                    0\n",
              "Condado                                                 0\n",
              "Estado                                                  0\n",
              "Numero_total_vacinados                                  0\n",
              "Numero_total_12+                                        0\n",
              "Porcentagem_total_12+                                   0\n",
              "Numero_total_18+                                        0\n",
              "Porcentagem_total_18+                                   0\n",
              "Numero_total_65+                                        0\n",
              "Porcentagem_total_65+                                   0\n",
              "Porcentagem_total_pessoas_vacinadas                     0\n",
              "Primeira_dose                                           0\n",
              "Porcentagem_primeira_dose                               0\n",
              "Primeira_dose_12+                                       0\n",
              "Porcentagem_primeira_dose_12+                           0\n",
              "Primeira_dose_18+                                       0\n",
              "Porcentagem_primeira_dose_18+                           0\n",
              "Primeira_dose_65+                                       0\n",
              "Porcentagem_primeira_dose_65+                           0\n",
              "IVS_Categoria                                           0\n",
              "Porcentagem_total_pop_vacinada                          0\n",
              "Porcentagem_total_12+_IVS                               0\n",
              "Porcentagem_total_18+_IVS                               0\n",
              "Porcentagem_total_65+_IVS                               0\n",
              "Status_metropolitano                                    0\n",
              "Porcentagem_total_metropolitana/NaoMetropolitana        0\n",
              "Porcentagem_total_12+_metropolitana/NaoMetropolitana    0\n",
              "Porcentagem_total_18+_metropolitana/NaoMetropolitana    0\n",
              "Porcentagem_total_65+_metropolitana/NaoMetropolitana    0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VvDkWF86tdr5"
      },
      "source": [
        "# Modificando o tipo de dado de algumas colunas para fazer a validação"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xBfNQw8ceenJ",
        "outputId": "6da9a680-a889-438c-fc39-98f971c6bcbb"
      },
      "source": [
        "print(df.info())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 1097549 entries, 0 to 1119193\n",
            "Data columns (total 29 columns):\n",
            " #   Column                                                Non-Null Count    Dtype         \n",
            "---  ------                                                --------------    -----         \n",
            " 0   Data                                                  1097549 non-null  datetime64[ns]\n",
            " 1   Condado                                               1097549 non-null  object        \n",
            " 2   Estado                                                1097549 non-null  object        \n",
            " 3   Numero_total_vacinados                                1097549 non-null  int64         \n",
            " 4   Numero_total_12+                                      1097549 non-null  float64       \n",
            " 5   Porcentagem_total_12+                                 1097549 non-null  float64       \n",
            " 6   Numero_total_18+                                      1097549 non-null  int64         \n",
            " 7   Porcentagem_total_18+                                 1097549 non-null  float64       \n",
            " 8   Numero_total_65+                                      1097549 non-null  int64         \n",
            " 9   Porcentagem_total_65+                                 1097549 non-null  float64       \n",
            " 10  Porcentagem_total_pessoas_vacinadas                   1097549 non-null  float64       \n",
            " 11  Primeira_dose                                         1097549 non-null  float64       \n",
            " 12  Porcentagem_primeira_dose                             1097549 non-null  float64       \n",
            " 13  Primeira_dose_12+                                     1097549 non-null  float64       \n",
            " 14  Porcentagem_primeira_dose_12+                         1097549 non-null  float64       \n",
            " 15  Primeira_dose_18+                                     1097549 non-null  float64       \n",
            " 16  Porcentagem_primeira_dose_18+                         1097549 non-null  float64       \n",
            " 17  Primeira_dose_65+                                     1097549 non-null  float64       \n",
            " 18  Porcentagem_primeira_dose_65+                         1097549 non-null  float64       \n",
            " 19  IVS_Categoria                                         1097549 non-null  object        \n",
            " 20  Porcentagem_total_pop_vacinada                        1097549 non-null  float64       \n",
            " 21  Porcentagem_total_12+_IVS                             1097549 non-null  float64       \n",
            " 22  Porcentagem_total_18+_IVS                             1097549 non-null  float64       \n",
            " 23  Porcentagem_total_65+_IVS                             1097549 non-null  float64       \n",
            " 24  Status_metropolitano                                  1097549 non-null  object        \n",
            " 25  Porcentagem_total_metropolitana/NaoMetropolitana      1097549 non-null  float64       \n",
            " 26  Porcentagem_total_12+_metropolitana/NaoMetropolitana  1097549 non-null  float64       \n",
            " 27  Porcentagem_total_18+_metropolitana/NaoMetropolitana  1097549 non-null  float64       \n",
            " 28  Porcentagem_total_65+_metropolitana/NaoMetropolitana  1097549 non-null  float64       \n",
            "dtypes: datetime64[ns](1), float64(21), int64(3), object(4)\n",
            "memory usage: 251.2+ MB\n",
            "None\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Mzqtx5ULtzvz"
      },
      "source": [
        "#Modificando a coluna 'Numero_total_12+' de float para int\n",
        "df[['Numero_total_12+']] = df[['Numero_total_12+']].astype(int)\n",
        "\n",
        "#Modificando a coluna 'Primeira_dose' de float para int\n",
        "df[['Primeira_dose']] = df[['Primeira_dose']].astype(int)\n",
        "\n",
        "#Modificando a coluna 'Primeira_dose_12+' de float para int\n",
        "df[['Primeira_dose_12+']] = df[['Primeira_dose_12+']].astype(int)\n",
        "\n",
        "#Modificando a coluna 'Primeira_dose_18+' de float para int\n",
        "df[['Primeira_dose_18+']] = df[['Primeira_dose_18+']].astype(int)\n",
        "\n",
        "#Modificando a coluna 'Primeira_dose_65+' de float para int\n",
        "df[['Primeira_dose_65+']] = df[['Primeira_dose_65+']].astype(int)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2HDT6hgoMFCr"
      },
      "source": [
        "# Validando os dados do DataFrame usando a biblioteca panderas"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 635
        },
        "id": "N8zHsE7MMEvr",
        "outputId": "79270531-d416-4f87-da50-a8e7553f1d65"
      },
      "source": [
        "schema = pa.DataFrameSchema(\n",
        "    columns = {\n",
        "        \"Data\":pa.Column(pa.DateTime),\n",
        "        \"Condado\":pa.Column(pa.String),\n",
        "        \"Estado\":pa.Column(pa.String),\n",
        "        \"Numero_total_vacinados\":pa.Column(pa.Int),\n",
        "        \"Numero_total_12+\":pa.Column(pa.Int),\n",
        "        \"Porcentagem_total_12+\":pa.Column(pa.Float),\n",
        "        \"Numero_total_18+\":pa.Column(pa.Int),\n",
        "        \"Porcentagem_total_18+\":pa.Column(pa.Float),\n",
        "        \"Numero_total_65+\":pa.Column(pa.Int),\n",
        "        \"Porcentagem_total_65+\":pa.Column(pa.Float),\n",
        "        \"Porcentagem_total_pessoas_vacinadas\":pa.Column(pa.Float),\n",
        "        \"Primeira_dose\":pa.Column(pa.Int),\n",
        "        \"Porcentagem_primeira_dose\":pa.Column(pa.Float),\n",
        "        \"Primeira_dose_12+\":pa.Column(pa.Int),\n",
        "        \"Porcentagem_primeira_dose_12+\":pa.Column(pa.Float),\n",
        "        \"Primeira_dose_18+\":pa.Column(pa.Int),\n",
        "        \"Porcentagem_primeira_dose_18+\":pa.Column(pa.Float),\n",
        "        \"Primeira_dose_65+\":pa.Column(pa.Int),\n",
        "        \"Porcentagem_primeira_dose_65+\":pa.Column(pa.Float),\n",
        "        \"IVS_Categoria\":pa.Column(pa.String),\n",
        "        \"Porcentagem_total_pop_vacinada\":pa.Column(pa.Float),\n",
        "        \"Porcentagem_total_12+_IVS\":pa.Column(pa.Float),\n",
        "        \"Porcentagem_total_18+_IVS\":pa.Column(pa.Float),\n",
        "        \"Porcentagem_total_65+_IVS\":pa.Column(pa.Float),\n",
        "        \"Status_metropolitano\":pa.Column(pa.String),\n",
        "        \"Porcentagem_total_metropolitana/NaoMetropolitana\":pa.Column(pa.Float),\n",
        "        \"Porcentagem_total_12+_metropolitana/NaoMetropolitana\":pa.Column(pa.Float),\n",
        "        \"Porcentagem_total_18+_metropolitana/NaoMetropolitana\":pa.Column(pa.Float),\n",
        "        \"Porcentagem_total_65+_metropolitana/NaoMetropolitana\":pa.Column(pa.Float)\n",
        "\n",
        "    }\n",
        ")\n",
        "\n",
        "schema.validate(df)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Condado</th>\n",
              "      <th>Estado</th>\n",
              "      <th>Numero_total_vacinados</th>\n",
              "      <th>Numero_total_12+</th>\n",
              "      <th>Porcentagem_total_12+</th>\n",
              "      <th>Numero_total_18+</th>\n",
              "      <th>Porcentagem_total_18+</th>\n",
              "      <th>Numero_total_65+</th>\n",
              "      <th>Porcentagem_total_65+</th>\n",
              "      <th>Porcentagem_total_pessoas_vacinadas</th>\n",
              "      <th>Primeira_dose</th>\n",
              "      <th>Porcentagem_primeira_dose</th>\n",
              "      <th>Primeira_dose_12+</th>\n",
              "      <th>Porcentagem_primeira_dose_12+</th>\n",
              "      <th>Primeira_dose_18+</th>\n",
              "      <th>Porcentagem_primeira_dose_18+</th>\n",
              "      <th>Primeira_dose_65+</th>\n",
              "      <th>Porcentagem_primeira_dose_65+</th>\n",
              "      <th>IVS_Categoria</th>\n",
              "      <th>Porcentagem_total_pop_vacinada</th>\n",
              "      <th>Porcentagem_total_12+_IVS</th>\n",
              "      <th>Porcentagem_total_18+_IVS</th>\n",
              "      <th>Porcentagem_total_65+_IVS</th>\n",
              "      <th>Status_metropolitano</th>\n",
              "      <th>Porcentagem_total_metropolitana/NaoMetropolitana</th>\n",
              "      <th>Porcentagem_total_12+_metropolitana/NaoMetropolitana</th>\n",
              "      <th>Porcentagem_total_18+_metropolitana/NaoMetropolitana</th>\n",
              "      <th>Porcentagem_total_65+_metropolitana/NaoMetropolitana</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>Plymouth County</td>\n",
              "      <td>IA</td>\n",
              "      <td>12168</td>\n",
              "      <td>12168</td>\n",
              "      <td>57.6</td>\n",
              "      <td>11528</td>\n",
              "      <td>61.1</td>\n",
              "      <td>3917</td>\n",
              "      <td>83.9</td>\n",
              "      <td>97.4</td>\n",
              "      <td>12921</td>\n",
              "      <td>51.3</td>\n",
              "      <td>12857</td>\n",
              "      <td>60.9</td>\n",
              "      <td>12175</td>\n",
              "      <td>64.5</td>\n",
              "      <td>4077</td>\n",
              "      <td>87.4</td>\n",
              "      <td>A</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>Metropolitano</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>Chilton County</td>\n",
              "      <td>AL</td>\n",
              "      <td>14178</td>\n",
              "      <td>14177</td>\n",
              "      <td>37.8</td>\n",
              "      <td>13447</td>\n",
              "      <td>39.7</td>\n",
              "      <td>4688</td>\n",
              "      <td>61.7</td>\n",
              "      <td>92.6</td>\n",
              "      <td>17431</td>\n",
              "      <td>39.2</td>\n",
              "      <td>17413</td>\n",
              "      <td>46.5</td>\n",
              "      <td>16523</td>\n",
              "      <td>48.8</td>\n",
              "      <td>5480</td>\n",
              "      <td>72.1</td>\n",
              "      <td>D</td>\n",
              "      <td>14.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>Metropolitano</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>Russell County</td>\n",
              "      <td>KS</td>\n",
              "      <td>2727</td>\n",
              "      <td>2727</td>\n",
              "      <td>46.8</td>\n",
              "      <td>2636</td>\n",
              "      <td>49.1</td>\n",
              "      <td>1112</td>\n",
              "      <td>65.6</td>\n",
              "      <td>93.6</td>\n",
              "      <td>3013</td>\n",
              "      <td>43.9</td>\n",
              "      <td>3002</td>\n",
              "      <td>51.6</td>\n",
              "      <td>2894</td>\n",
              "      <td>53.9</td>\n",
              "      <td>1197</td>\n",
              "      <td>70.7</td>\n",
              "      <td>A</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Não Metropolitano</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>Essex County</td>\n",
              "      <td>NY</td>\n",
              "      <td>24262</td>\n",
              "      <td>24262</td>\n",
              "      <td>73.1</td>\n",
              "      <td>22876</td>\n",
              "      <td>73.8</td>\n",
              "      <td>7418</td>\n",
              "      <td>82.9</td>\n",
              "      <td>97.6</td>\n",
              "      <td>25992</td>\n",
              "      <td>70.5</td>\n",
              "      <td>25723</td>\n",
              "      <td>77.5</td>\n",
              "      <td>24189</td>\n",
              "      <td>78.1</td>\n",
              "      <td>7853</td>\n",
              "      <td>87.8</td>\n",
              "      <td>B</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>Não Metropolitano</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2021-11-17</td>\n",
              "      <td>Bonner County</td>\n",
              "      <td>ID</td>\n",
              "      <td>17308</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>17267</td>\n",
              "      <td>47.0</td>\n",
              "      <td>7946</td>\n",
              "      <td>68.4</td>\n",
              "      <td>97.6</td>\n",
              "      <td>19484</td>\n",
              "      <td>42.6</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>19428</td>\n",
              "      <td>52.9</td>\n",
              "      <td>8714</td>\n",
              "      <td>75.0</td>\n",
              "      <td>A</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Não Metropolitano</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1119189</th>\n",
              "      <td>2020-12-13</td>\n",
              "      <td>West Carroll Parish</td>\n",
              "      <td>LA</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>C</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Não Metropolitano</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1119190</th>\n",
              "      <td>2020-12-13</td>\n",
              "      <td>Upson County</td>\n",
              "      <td>GA</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>D</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Não Metropolitano</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1119191</th>\n",
              "      <td>2020-12-13</td>\n",
              "      <td>Edwards County</td>\n",
              "      <td>TX</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>B</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Não Metropolitano</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1119192</th>\n",
              "      <td>2020-12-13</td>\n",
              "      <td>Haralson County</td>\n",
              "      <td>GA</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>C</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Metropolitano</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1119193</th>\n",
              "      <td>2020-12-13</td>\n",
              "      <td>Huron County</td>\n",
              "      <td>OH</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>B</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Não Metropolitano</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1097549 rows × 29 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "              Data  ... Porcentagem_total_65+_metropolitana/NaoMetropolitana\n",
              "0       2021-11-17  ...                                                4.0  \n",
              "1       2021-11-17  ...                                                3.0  \n",
              "2       2021-11-17  ...                                                7.0  \n",
              "3       2021-11-17  ...                                                8.0  \n",
              "4       2021-11-17  ...                                                7.0  \n",
              "...            ...  ...                                                ...  \n",
              "1119189 2020-12-13  ...                                                0.0  \n",
              "1119190 2020-12-13  ...                                                0.0  \n",
              "1119191 2020-12-13  ...                                                0.0  \n",
              "1119192 2020-12-13  ...                                                0.0  \n",
              "1119193 2020-12-13  ...                                                0.0  \n",
              "\n",
              "[1097549 rows x 29 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SaGhGqHaL4RK"
      },
      "source": [
        "# Salvando as transformações realizadas no DataFrame para o Bucket do GCP"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vp6vEwt1qPcW"
      },
      "source": [
        "bucket = storage_client.get_bucket('projeto-finalsc01')\n",
        "bucket.blob('dados-tratados/Vacinacoes_nos_EUA.csv').upload_from_string(df.to_csv(index=False),'Vacinacoes_nos_EUA.csv' )"
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}