painel_covid_goiania_v2 (2).ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "painel_covid_goiania-v2.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LB1NIW36rgzF",
        "colab_type": "text"
      },
      "source": [
        "#PAINEL COVID GYN\n",
        "\n",
        "\n",
        "```\n",
        "painel-covid-goiania.herokuapp.com\n",
        "github.com/wendelmarques/painel-covid-goiania\n",
        "```\n",
        "\n",
        "\n",
        "\n",
        "### Objetivo: Criar vizualizações com os dados sobre os casos confirmados da COVID-19 em Goiânia.\n",
        "\n",
        "##### Os dados utilizados para geração do mapa e dos gráficos, foram retirados dos Informes Epidemiológicos publicados (em PDFs) pela Prefeitura de Goiânia, por meio de uma técnica chamada Data Scraping (algoritmos que realizam a tarefa de extração). São divulgadas apenas informações sobre alguns bairros - os que possuem mais casos confirmados acumulados, por isso, foram extraídos dados de 111 bairros.\n",
        "\n",
        "#####Para mais informações, acesse: saude.goiania.go.gov.br\n",
        "\n",
        "\n",
        "<br>\n",
        "<br>\n",
        "\n",
        "#### Fontes/ créditos\n",
        "\n",
        "*    [Brasil.IO - O Brasil em dados libertos](https://brasil.io/dataset/covid19/caso/?search=&date=&state=&city=&place_type=&is_last=&city_ibge_code=5208707&order_for_place=)\n",
        "*    [Plotly - Repositório](https://github.com/plotly/dash-sample-apps/tree/master/apps)\n",
        "*   [How to create outstanding animated scatter maps with Plotly and Dash (Medium) - Lamothe Thibaud ](https://towardsdatascience.com/how-to-create-animated-scatter-maps-with-plotly-and-dash-f10bb82d357a)\n",
        "*    [Deploying Dash or Flask web application on Heroku. Easy CI/CD (Medium) - Lamothe Thibaud](https://towardsdatascience.com/deploying-dash-or-flask-web-application-on-heroku-easy-ci-cd-4111da3170b8)\n",
        "*    [Official Release of bar_chart_race (Medium) - Ted Petrou\n",
        "dexplo.org/bar_chart_race](https://medium.com/dunder-data/bar-chart-race-python-package-official-release-78a420e182a2)\n",
        "*    [Gráfico de Corrida de Barras | Dica Pandas #7 - Programação Dinâmica (YouTube)](https://www.youtube.com/watch?v=rIwxjCnvdcY)\n",
        "*    [Como utilizar a Google Geocoding API para obter endereços](https://www.devmedia.com.br/como-utilizar-a-google-geocoding-api-para-obter-enderecos/36751)\n",
        "*    [Python Client for Google Maps Services](https://github.com/googlemaps/google-maps-services-python)\n",
        "* [Como fazer um Web Scraping com Python](https://goomore.com/blog/web-scraping-python/)\n",
        "\n",
        "* [Official Release of bar_chart_race](https://medium.com/dunder-data/bar-chart-race-python-package-official-release-78a420e182a2)\n",
        "\n",
        "* [Corrida de CASOS de COVID no Brasil | Gráfico de Corrida de Barras (Bar Chart Race) | Dica Pandas #7](https://www.youtube.com/watch?v=rIwxjCnvdcY)\n",
        "\n",
        "* [ACESSANDO RECURSOS NA WEB COM PYTHON](https://pythonhelp.wordpress.com/2013/03/12/acessando-recursos-na-web-com-python/)\n",
        "\n",
        "* [Como usar o R para escolher um lugar para morar (3) - Converter CEP em coordenadas geográficas](https://sillasgonzaga.github.io/2016-11-18-olx3/#:~:text=Obter%20endere%C3%A7o%20a%20partir%20do%20CEP&text=Sabemos%20que%20quanto%20mais%20dados,%2C%20bairro%2C%20cidade%20e%20estado.&text=%C3%89%20necess%C3%A1rio%20juntar%20todas%20as,de%20endere%C3%A7os%20em%20uma%20s%C3%B3)\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "\n",
        "Criado por Wendel Marques\n",
        "\n",
        "*   [GitHub](https://www.github.com/WendelMarques)\n",
        "*   [LinkedIn](https://www.linkedin.com/in/wendelmarques/)\n",
        "*   [Medium](https://medium.com/@WendelMarques)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "n-Yt0lg1p4VP"
      },
      "source": [
        "# Drive"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cWI9iaRNEA8V",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        },
        "outputId": "8871c180-7caa-4a3a-9a88-d8886ed78fe7"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Kzt_F8ixhftF",
        "colab_type": "text"
      },
      "source": [
        "# Biblioteca e pacotes"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GUAdKb_5GXFn",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "outputId": "ecc8bf53-5379-44da-e2fe-04eba0446b35"
      },
      "source": [
        "import pandas as pd\n",
        "import time\n",
        "import bs4\n",
        "import requests\n",
        "from datetime import datetime\n",
        "!pip install tika\n",
        "from tika import parser\n",
        "import numpy as np\n",
        "import urllib.request #biblioteca usada para consultar uma URL\n",
        "from bs4 import BeautifulSoup #funções BeautifulSoup para analisar os dados retornados do site\n",
        "!pip install googlemaps\n",
        "import googlemaps\n",
        "import math\n",
        "import numpy as np\n",
        "!pip install bar_chart_race\n",
        "!pip install ffmpeg\n",
        "import bar_chart_race as bcr\n",
        "import plotly.offline as py\n",
        "import plotly.graph_objs as go\n",
        "import plotly.express as px\n",
        "\n",
        "# #https://medium.com/dunder-data/bar-chart-race-python-package-official-release-78a420e182a2"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting tika\n",
            "  Downloading https://files.pythonhosted.org/packages/96/07/244fbb9c74c0de8a3745cc9f3f496077a29f6418c7cbd90d68fd799574cb/tika-1.24.tar.gz\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.6/dist-packages (from tika) (50.3.0)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.6/dist-packages (from tika) (2.23.0)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests->tika) (1.24.3)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests->tika) (3.0.4)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests->tika) (2020.6.20)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests->tika) (2.10)\n",
            "Building wheels for collected packages: tika\n",
            "  Building wheel for tika (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for tika: filename=tika-1.24-cp36-none-any.whl size=32884 sha256=b1d04e91625f5c37bf75a1010fa8a838c6e7be367187054e416bb6ae4a8d9547\n",
            "  Stored in directory: /root/.cache/pip/wheels/73/9c/f5/0b1b738442fc2a2862bef95b908b374f8e80215550fb2a8975\n",
            "Successfully built tika\n",
            "Installing collected packages: tika\n",
            "Successfully installed tika-1.24\n",
            "Collecting googlemaps\n",
            "  Downloading https://files.pythonhosted.org/packages/00/fa/508909813a3f0ff969d341695ee0b90cb0e954b4b536f17f15cc19b5c304/googlemaps-4.4.2.tar.gz\n",
            "Requirement already satisfied: requests<3.0,>=2.20.0 in /usr/local/lib/python3.6/dist-packages (from googlemaps) (2.23.0)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests<3.0,>=2.20.0->googlemaps) (2020.6.20)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests<3.0,>=2.20.0->googlemaps) (2.10)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests<3.0,>=2.20.0->googlemaps) (1.24.3)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests<3.0,>=2.20.0->googlemaps) (3.0.4)\n",
            "Building wheels for collected packages: googlemaps\n",
            "  Building wheel for googlemaps (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for googlemaps: filename=googlemaps-4.4.2-cp36-none-any.whl size=37858 sha256=0a202a189b978f40756194544bdb8daacff40da5f17f205c9fabfc1acb2cf0d0\n",
            "  Stored in directory: /root/.cache/pip/wheels/f4/21/41/0c84572e21d52bb322f6c299f38ac7cd8ad6d4d6ce23dc3631\n",
            "Successfully built googlemaps\n",
            "Installing collected packages: googlemaps\n",
            "Successfully installed googlemaps-4.4.2\n",
            "Collecting bar_chart_race\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/09/01/f6d1a1a0978b39560843c54be7349804d7d2faef0a869acd7c8a6fc920b0/bar_chart_race-0.1.0-py3-none-any.whl (156kB)\n",
            "\u001b[K     |████████████████████████████████| 163kB 2.9MB/s \n",
            "\u001b[?25hRequirement already satisfied: matplotlib>=3.1 in /usr/local/lib/python3.6/dist-packages (from bar_chart_race) (3.2.2)\n",
            "Requirement already satisfied: pandas>=0.24 in /usr/local/lib/python3.6/dist-packages (from bar_chart_race) (1.0.5)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=3.1->bar_chart_race) (0.10.0)\n",
            "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=3.1->bar_chart_race) (2.4.7)\n",
            "Requirement already satisfied: python-dateutil>=2.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=3.1->bar_chart_race) (2.8.1)\n",
            "Requirement already satisfied: numpy>=1.11 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=3.1->bar_chart_race) (1.18.5)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=3.1->bar_chart_race) (1.2.0)\n",
            "Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.6/dist-packages (from pandas>=0.24->bar_chart_race) (2018.9)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.6/dist-packages (from cycler>=0.10->matplotlib>=3.1->bar_chart_race) (1.15.0)\n",
            "Installing collected packages: bar-chart-race\n",
            "Successfully installed bar-chart-race-0.1.0\n",
            "Collecting ffmpeg\n",
            "  Downloading https://files.pythonhosted.org/packages/f0/cc/3b7408b8ecf7c1d20ad480c3eaed7619857bf1054b690226e906fdf14258/ffmpeg-1.4.tar.gz\n",
            "Building wheels for collected packages: ffmpeg\n",
            "  Building wheel for ffmpeg (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for ffmpeg: filename=ffmpeg-1.4-cp36-none-any.whl size=6083 sha256=5fa56ad8c3c9de2f416ac11de74c52410744d65458f2be14224aa19c59abba7c\n",
            "  Stored in directory: /root/.cache/pip/wheels/b6/68/c3/a05a35f647ba871e5572b9bbfc0b95fd1c6637a2219f959e7a\n",
            "Successfully built ffmpeg\n",
            "Installing collected packages: ffmpeg\n",
            "Successfully installed ffmpeg-1.4\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sXKqjcaOMv9b",
        "colab_type": "text"
      },
      "source": [
        "# Etapas a partir da extração do Informe Epidemiológico\n",
        "`Extração de dados dos Informes Epidemiológicos (PDFs) publicados no site da Prefeitura de Goiânia`\n",
        "\n",
        "\n",
        "\n",
        "*   Bar race (por bairro e por região)\n",
        "*   Mapa\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZB4TSK7k5XZt",
        "colab_type": "text"
      },
      "source": [
        "## Data scraping - total de casos por bairro"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "j-D1Rjb0hvVN",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#acessa a pagina de informes\n",
        "siteInformes = \"https://saude.goiania.go.gov.br/goiania-contra-o-coronavirus/informe-epidemiologico-covid-19/#antigos\"\n",
        "#Consulta o site e retorne o html para a variável 'page'\n",
        "page = urllib.request.urlopen(siteInformes)\n",
        "#Parse o html na variável 'page' e armazene-o no formato BeautifulSoup\n",
        "soup = BeautifulSoup(page, 'html5lib')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ciyB7B3du5cT",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "b48dc10e-ce8c-46e5-dfcd-6c9d2a654e6d"
      },
      "source": [
        "#pecorre cada linha do html de siteInformes e pegar os links dos pdfs\n",
        "all_links = soup.find_all('a')\n",
        "urls_pdfs = []\n",
        "for link in all_links:\n",
        "    if link.get('href'):\n",
        "        if link.get('href')[-3:] == 'pdf':\n",
        "            urls_pdfs.append(link.get('href'))\n",
        "            \n",
        "urls_pdfs"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-17-19.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-17-19.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-16-18.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-16-18.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-15-17.04.2020_2.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-15-17.04.2020_2.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-14-16.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-14-16.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-13-15.04.2020-2.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-13-15.04.2020-2.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-12-14.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-12-14.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-11-13.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-11-13.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-10-12.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-10-12.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-9-11.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-9-11.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-8-10.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-8-10.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-7-09.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-7-09.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-6-08.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-6-08.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-5-07.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-5-07.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-4-06.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-4-06.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-3-05.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-3-05.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-2-04.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-2-04.04.2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-1-03-04-2020.pdf',\n",
              " 'https://saude.goiania.go.gov.br/wp-uploads/sites/3/2020/04/Informe-COVID-19-nº-1-03-04-2020.pdf']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oY5lXdzTC5Bk",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "e9245503-037b-449e-89d8-3391af86e6d5"
      },
      "source": [
        "len(urls_pdfs)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "218"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "h5kxzuttCuqi",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "02fe520c-3374-44b5-bdbf-db1debe7a80a"
      },
      "source": [
        "len(np.unique(urls_pdfs)) #deve ser igual ao numero de informes publicados - 2"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "167"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "_RCshshlTkd4",
        "colab": {}
      },
      "source": [
        "#remove link duplicados\n",
        "urls_pdfs = np.unique(urls_pdfs)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "cMHytwAVTkd0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "4c8e3a36-5a37-4e43-bfe3-034092e289a1"
      },
      "source": [
        "len(urls_pdfs)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "167"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VtXCNU-pxOLA",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "bab062ab-4f36-489f-caba-4d835094effc"
      },
      "source": [
        "#substitui alguns caracteres para evitar erros\n",
        "urls_pdfs_modificadas = []\n",
        "for url in urls_pdfs:\n",
        "    new_link = url.replace('º', '%C2%BA')\n",
        "    new_link1 = new_link.replace('padrão', 'padra%CC%83o')\n",
        "    urls_pdfs_modificadas.append(new_link1)\n",
        "\n",
        "\n",
        "i = 0\n",
        "for i in range(len(urls_pdfs_modificadas)):\n",
        "    print(i)\n",
        "    print(urls_pdfs_modificadas[i])  "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
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          "name": "stdout"
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      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "3Jlot5e1uGU5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "007c0e96-94ef-4918-a24d-271ad337ce20"
      },
      "source": [
        "###############################################################\n",
        "######### OBJETIVO: LER O HTML E EXTRAIR OS DADOS #############\n",
        "###############################################################\n",
        "\n",
        "num_informes = len(urls_pdfs) #quantidades de informes publicados\n",
        "i = 0\n",
        "j = 0\n",
        "conteudos = []\n",
        "dataset = {}\n",
        "\n",
        "def pega_data(url):\n",
        "    indice = 0\n",
        "    while indice < len(url):\n",
        "        if url[indice] == '2':\n",
        "            if url[indice+1] == '0':\n",
        "                if url[indice+2] == '2':\n",
        "                    if url[indice+3] == '0':\n",
        "                        if url[indice+4] != '/':\n",
        "                            data = url[indice] + url[indice+1]+url[indice+2]+url[indice+3]+'-'+url[indice-3]+url[indice-2]+'-'+url[indice-6]+url[indice-5]\n",
        "                            # print(data)\n",
        "                            return data\n",
        "                \n",
        "        \n",
        "        indice+=1\n",
        "\n",
        "    return '0000-00-00'        \n",
        "\n",
        "\n",
        "\n",
        "def cria_lista_bairros_e_casos(bairro_casos):\n",
        "    try:\n",
        "        num_casos = bairro_casos.split(' ')[-1]\n",
        "        num_casos = int(num_casos)\n",
        "        qdt_dig_casos = int (math.log10 (num_casos))+2\n",
        "        bairro = bairro_casos[:len(bairro_casos)-qdt_dig_casos]\n",
        "        return [bairro, num_casos]\n",
        "\n",
        "    except ValueError as e:\n",
        "        return [0, 0]\n",
        "\n",
        "\n",
        "for url in urls_pdfs_modificadas:\n",
        "\n",
        "    if i <= num_informes:\n",
        "        print(i)\n",
        "        i+=1\n",
        "        conteudos.clear()\n",
        "        conteudos.append(parser.from_file(url))\n",
        "        time.sleep(8)\n",
        "\n",
        "        #armazena o conteudo do pdf em conteudos_pdfs.txt (um pdf por vez)\n",
        "        #repare no conteudos.clear() linhas acima\n",
        "        arquivo = open('conteudos-pdfs.txt', 'w')\n",
        "        for linha in conteudos:\n",
        "            arquivo.write(linha['content']) \n",
        "        arquivo.close()\n",
        "\n",
        "        #pega a data do informe\n",
        "        data = pega_data(url)\n",
        "        data = data[:10]\n",
        "        print(data)\n",
        "\n",
        "        #abre o arquivo e captura a data em que foi criado\n",
        "        arquivo = open('conteudos-pdfs.txt', 'r')\n",
        "        lista = arquivo.readlines()\n",
        "        arquivo.close()\n",
        "\n",
        "        df = pd.DataFrame(lista)\n",
        "        delete_row = df[df[0]=='\\n'].index\n",
        "        df = df.drop(delete_row)\n",
        "        df.reset_index(inplace=True)\n",
        "        df.drop(columns=['index'], axis=1, inplace=True)\n",
        "\n",
        "        row_iterator = df.iterrows()\n",
        "\n",
        "        while 1:\n",
        "            try:\n",
        "                for aux in range(len(df)):\n",
        "                    linha_atual = next(row_iterator)\n",
        "                    \n",
        "                    if 'Setor Bueno' in linha_atual[1][0]:\n",
        "                        while 1:\n",
        "                            #cria um dicionario no formato bairro: num_casos\n",
        "                            ret = cria_lista_bairros_e_casos(linha_atual[1][0])\n",
        "                            if (ret[0] != 0 and ret[0] != 0):\n",
        "                                dataset[j] = {'data': data, 'bairro': ret[0], 'num_casos': ret[1]}\n",
        "                                j+=1\n",
        "                            #\"outros\" é a flag usada para parar o loop\n",
        "                            if 'Outros' in linha_atual[1][0]:                        \n",
        "                                break  \n",
        "                            linha_atual = next(row_iterator)            \n",
        "\n",
        "            except StopIteration as e:\n",
        "                    print(e)\n",
        "                    break\n",
        "    else:\n",
        "        i+=1\n",
        "\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
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      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VpXK166YC-aI",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "dataset"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fKQw0ezOBTcS",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "b5dc7af4-5568-44f0-a00f-97ecc61d787a"
      },
      "source": [
        "covid_goiania_por_bairro = pd.DataFrame(dataset)\n",
        "covid_goiania_por_bairro = covid_goiania_por_bairro.T\n",
        "bairros_e_num_casos.to_csv('covid_goiania_por_bairro.csv', index=False)\n",
        "covid_goiania_por_bairro"
      ],
      "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>bairro</th>\n",
              "      <th>num_casos</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-05-02</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>48</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-05-02</td>\n",
              "      <td>Setor Oeste</td>\n",
              "      <td>39</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-05-02</td>\n",
              "      <td>Jd. Goiás</td>\n",
              "      <td>18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-05-02</td>\n",
              "      <td>Setor Marista</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-05-02</td>\n",
              "      <td>Parque Amazônia</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8549</th>\n",
              "      <td>2020-09-18</td>\n",
              "      <td>Res. Granville</td>\n",
              "      <td>132</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8550</th>\n",
              "      <td>2020-09-18</td>\n",
              "      <td>Vila Mutirão I</td>\n",
              "      <td>132</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8551</th>\n",
              "      <td>2020-09-18</td>\n",
              "      <td>Conjunto Habitacional Madre Germana 2</td>\n",
              "      <td>128</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8552</th>\n",
              "      <td>2020-09-18</td>\n",
              "      <td>Vila Jardim Pompéia</td>\n",
              "      <td>128</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8553</th>\n",
              "      <td>2020-09-18</td>\n",
              "      <td>Setor Rio Formoso</td>\n",
              "      <td>125</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>8554 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            data                                  bairro num_casos\n",
              "0     2020-05-02                            Setor Bueno         48\n",
              "1     2020-05-02                            Setor Oeste         39\n",
              "2     2020-05-02                              Jd. Goiás         18\n",
              "3     2020-05-02                          Setor Marista         14\n",
              "4     2020-05-02                        Parque Amazônia         14\n",
              "...          ...                                     ...       ...\n",
              "8549  2020-09-18                         Res. Granville        132\n",
              "8550  2020-09-18                         Vila Mutirão I        132\n",
              "8551  2020-09-18  Conjunto Habitacional Madre Germana 2        128\n",
              "8552  2020-09-18                    Vila Jardim Pompéia        128\n",
              "8553  2020-09-18                      Setor Rio Formoso        125\n",
              "\n",
              "[8554 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 310
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SPSDLGCQDSvB",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "bbf2ba1e-9209-412f-e2fc-48a96abaed2f"
      },
      "source": [
        "#quantidade de bairros\n",
        "# 2 = \"outros \" e \"outros bairros\"\n",
        "\n",
        "print(len(np.unique(covid_goiania_por_bairro['bairro'])) - 2)\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "114\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3MvgEvVNDe9m",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "covid_goiania_por_bairro.to_csv('covid_goiania_por_bairro.csv', index=False)\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kOv4KXjSMz1B",
        "colab_type": "text"
      },
      "source": [
        "## Web scraping (CEPs) e obtenção de coordenadas\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vTDuhnTWNO27",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# extrair coordenadas"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iOybCtsWMzF-",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "83871693-8357-45e7-eeb4-5f49c3845a07"
      },
      "source": [
        "# bairros_e_localizacao = pd.read_csv('bairros_e_localizacao.csv', sep=',')\n",
        "# bairros_e_localizacao.to_csv('bairros_e_localizacao.csv', index=False)\n",
        "bairros_e_localizacao"
      ],
      "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>bairro</th>\n",
              "      <th>cep</th>\n",
              "      <th>localizacao</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Alphaville Flamboyant</td>\n",
              "      <td>74884-534</td>\n",
              "      <td>[-16.7070932, -49.2122502]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Alto da Glória</td>\n",
              "      <td>74815-610</td>\n",
              "      <td>[-16.7206511, -49.2250865]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Capuava</td>\n",
              "      <td>74450-410</td>\n",
              "      <td>[-16.6645242, -49.316575]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Cidade Jardim</td>\n",
              "      <td>74425-250</td>\n",
              "      <td>[-16.6761304, -49.3121233]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Conjunto Primavera</td>\n",
              "      <td>74477-207</td>\n",
              "      <td>[-16.5878046, -49.37404129999999]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>106</th>\n",
              "      <td>Vila São José - Extensão</td>\n",
              "      <td>70000-000</td>\n",
              "      <td>[-16.6551261,-49.3078991]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>107</th>\n",
              "      <td>Setor Rio Formoso</td>\n",
              "      <td>74370-020</td>\n",
              "      <td>[-16.7211142,-49.3337986]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>108</th>\n",
              "      <td>Residencial Jardim Florença</td>\n",
              "      <td>74351-008</td>\n",
              "      <td>[-16.725215,-49.3151065]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>109</th>\n",
              "      <td>Setor Perim</td>\n",
              "      <td>74580-240</td>\n",
              "      <td>[-16.6448258,-49.2994181]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>110</th>\n",
              "      <td>Residencial Orlando de Morais</td>\n",
              "      <td>74693-114</td>\n",
              "      <td>[-16.5497495,-49.2728893]</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>111 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                             bairro  ...                        localizacao\n",
              "0            Alphaville Flamboyant   ...         [-16.7070932, -49.2122502]\n",
              "1                   Alto da Glória   ...         [-16.7206511, -49.2250865]\n",
              "2                          Capuava   ...          [-16.6645242, -49.316575]\n",
              "3                    Cidade Jardim   ...         [-16.6761304, -49.3121233]\n",
              "4               Conjunto Primavera   ...  [-16.5878046, -49.37404129999999]\n",
              "..                              ...  ...                                ...\n",
              "106       Vila São José - Extensão   ...          [-16.6551261,-49.3078991]\n",
              "107              Setor Rio Formoso   ...          [-16.7211142,-49.3337986]\n",
              "108    Residencial Jardim Florença   ...           [-16.725215,-49.3151065]\n",
              "109                    Setor Perim   ...          [-16.6448258,-49.2994181]\n",
              "110  Residencial Orlando de Morais   ...          [-16.5497495,-49.2728893]\n",
              "\n",
              "[111 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 308
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "e7RBm9YQOPtD",
        "colab_type": "text"
      },
      "source": [
        "## Merge covid_goiania_por_bairro e bairros_e_localizacao"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "N4k6tPNiO9XG",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "48659748-22fe-4cec-ce4d-f5a7411027e3"
      },
      "source": [
        "covid_goiania_por_bairro = pd.merge(covid_goiania_por_bairro, bairros_e_localizacao, on='bairro')\n",
        "covid_goiania_por_bairro"
      ],
      "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>bairro</th>\n",
              "      <th>num_casos</th>\n",
              "      <th>cep</th>\n",
              "      <th>localizacao</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-05-02</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>48</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>[-16.6956937, -49.2640252]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-04-29</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>45</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>[-16.6956937, -49.2640252]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-04-30</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>48</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>[-16.6956937, -49.2640252]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-05-03</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>52</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>[-16.6956937, -49.2640252]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-05-11</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>73</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>[-16.6956937, -49.2640252]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8251</th>\n",
              "      <td>2020-09-17</td>\n",
              "      <td>Conjunto Habitacional Madre Germana 2</td>\n",
              "      <td>128</td>\n",
              "      <td>74354-830</td>\n",
              "      <td>[-16.8154446,-49.3747038]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8252</th>\n",
              "      <td>2020-09-18</td>\n",
              "      <td>Conjunto Habitacional Madre Germana 2</td>\n",
              "      <td>128</td>\n",
              "      <td>74354-830</td>\n",
              "      <td>[-16.8154446,-49.3747038]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8253</th>\n",
              "      <td>2020-09-16</td>\n",
              "      <td>Setor Rio Formoso</td>\n",
              "      <td>125</td>\n",
              "      <td>74370-020</td>\n",
              "      <td>[-16.7211142,-49.3337986]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8254</th>\n",
              "      <td>2020-09-17</td>\n",
              "      <td>Setor Rio Formoso</td>\n",
              "      <td>125</td>\n",
              "      <td>74370-020</td>\n",
              "      <td>[-16.7211142,-49.3337986]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8255</th>\n",
              "      <td>2020-09-18</td>\n",
              "      <td>Setor Rio Formoso</td>\n",
              "      <td>125</td>\n",
              "      <td>74370-020</td>\n",
              "      <td>[-16.7211142,-49.3337986]</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>8256 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            data  ...                 localizacao\n",
              "0     2020-05-02  ...  [-16.6956937, -49.2640252]\n",
              "1     2020-04-29  ...  [-16.6956937, -49.2640252]\n",
              "2     2020-04-30  ...  [-16.6956937, -49.2640252]\n",
              "3     2020-05-03  ...  [-16.6956937, -49.2640252]\n",
              "4     2020-05-11  ...  [-16.6956937, -49.2640252]\n",
              "...          ...  ...                         ...\n",
              "8251  2020-09-17  ...   [-16.8154446,-49.3747038]\n",
              "8252  2020-09-18  ...   [-16.8154446,-49.3747038]\n",
              "8253  2020-09-16  ...   [-16.7211142,-49.3337986]\n",
              "8254  2020-09-17  ...   [-16.7211142,-49.3337986]\n",
              "8255  2020-09-18  ...   [-16.7211142,-49.3337986]\n",
              "\n",
              "[8256 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 452
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cAaN7-76P7nx",
        "colab_type": "text"
      },
      "source": [
        "## Acrescentar regiao em covid_goiania_por_bairro"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "w3w7LKPzP6ar",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#web scraping de http://www.sgc.goias.gov.br/upload/arquivos/2017-02/bairros-por-regiao-2017.pdf\n",
        "# ou do wikipedia (code disponivel na v1)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Glnd-p76Q4FM",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "bairros_por_regiao = pd.read_csv('bairros_por_regiao.csv', encoding = 'utf-8', sep=',')\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "A__au2VZvbZ4",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "0c30f300-5e06-4247-f03c-fc56f25e1d76"
      },
      "source": [
        "bairros_por_regiao"
      ],
      "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>bairro</th>\n",
              "      <th>regiao</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Alice Barbosa</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Antônio Barbosa</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Antônio Carlos Pires</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Asa Branca</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Atalaia</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>488</th>\n",
              "      <td>Vila São José - Extensão</td>\n",
              "      <td>Centro Oeste</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>489</th>\n",
              "      <td>Setor Rio Formoso</td>\n",
              "      <td>Sudoeste</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>490</th>\n",
              "      <td>Residencial Jardim Florença</td>\n",
              "      <td>Sudoeste</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>491</th>\n",
              "      <td>Setor Perim</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>492</th>\n",
              "      <td>Residencial Orlando de Morais</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>493 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                            bairro        regiao\n",
              "0                    Alice Barbosa         Norte\n",
              "1                  Antônio Barbosa         Norte\n",
              "2             Antônio Carlos Pires         Norte\n",
              "3                       Asa Branca         Norte\n",
              "4                          Atalaia         Norte\n",
              "..                             ...           ...\n",
              "488       Vila São José - Extensão  Centro Oeste\n",
              "489              Setor Rio Formoso      Sudoeste\n",
              "490    Residencial Jardim Florença      Sudoeste\n",
              "491                    Setor Perim         Norte\n",
              "492  Residencial Orlando de Morais         Norte\n",
              "\n",
              "[493 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 448
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CEoE6nJ3RR0i",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "bbc61306-5ed9-4ee0-b05c-e20e3d8c5b08"
      },
      "source": [
        "def normaliza_nomes_bairros(bairro):\n",
        "\n",
        "    if 'Res.' in bairro:\n",
        "        bairro = bairro.replace('Res.', 'Residencial')\n",
        "        # bairro = bairro.strip(' ')\n",
        "\n",
        "        return bairro\n",
        "    \n",
        "    if 'Jd.' in bairro:\n",
        "        bairro = bairro.replace('Jd.', 'Jardim')\n",
        "        # bairro = bairro.strip(' ')\n",
        "        return bairro\n",
        "    else:\n",
        "        return bairro \n",
        "\n",
        "covid_goiania_por_bairro['bairro'] = covid_goiania_por_bairro['bairro'].apply(lambda x: normaliza_nomes_bairros(x))\n",
        "covid_goiania_por_bairro['bairro'] = covid_goiania_por_bairro['bairro'].apply(lambda x: x.strip(' '))\n",
        "df_completo_com_regiao = pd.merge(covid_goiania_por_bairro,  bairros_por_regiao, on='bairro')\n",
        "df_completo_com_regiao = df_completo_com_regiao.drop_duplicates()\n",
        "df_completo_com_regiao\n"
      ],
      "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>bairro</th>\n",
              "      <th>num_casos</th>\n",
              "      <th>cep</th>\n",
              "      <th>localizacao</th>\n",
              "      <th>regiao</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-05-02</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>48</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>[-16.6956937, -49.2640252]</td>\n",
              "      <td>Sul</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-04-29</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>45</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>[-16.6956937, -49.2640252]</td>\n",
              "      <td>Sul</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-04-30</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>48</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>[-16.6956937, -49.2640252]</td>\n",
              "      <td>Sul</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-05-03</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>52</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>[-16.6956937, -49.2640252]</td>\n",
              "      <td>Sul</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-05-11</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>73</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>[-16.6956937, -49.2640252]</td>\n",
              "      <td>Sul</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11399</th>\n",
              "      <td>2020-09-17</td>\n",
              "      <td>Conjunto Habitacional Madre Germana 2</td>\n",
              "      <td>128</td>\n",
              "      <td>74354-830</td>\n",
              "      <td>[-16.8154446,-49.3747038]</td>\n",
              "      <td>Noroeste</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11400</th>\n",
              "      <td>2020-09-18</td>\n",
              "      <td>Conjunto Habitacional Madre Germana 2</td>\n",
              "      <td>128</td>\n",
              "      <td>74354-830</td>\n",
              "      <td>[-16.8154446,-49.3747038]</td>\n",
              "      <td>Noroeste</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11401</th>\n",
              "      <td>2020-09-16</td>\n",
              "      <td>Setor Rio Formoso</td>\n",
              "      <td>125</td>\n",
              "      <td>74370-020</td>\n",
              "      <td>[-16.7211142,-49.3337986]</td>\n",
              "      <td>Sudoeste</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11402</th>\n",
              "      <td>2020-09-17</td>\n",
              "      <td>Setor Rio Formoso</td>\n",
              "      <td>125</td>\n",
              "      <td>74370-020</td>\n",
              "      <td>[-16.7211142,-49.3337986]</td>\n",
              "      <td>Sudoeste</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11403</th>\n",
              "      <td>2020-09-18</td>\n",
              "      <td>Setor Rio Formoso</td>\n",
              "      <td>125</td>\n",
              "      <td>74370-020</td>\n",
              "      <td>[-16.7211142,-49.3337986]</td>\n",
              "      <td>Sudoeste</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>8364 rows × 6 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             data  ...    regiao\n",
              "0      2020-05-02  ...       Sul\n",
              "1      2020-04-29  ...       Sul\n",
              "2      2020-04-30  ...       Sul\n",
              "3      2020-05-03  ...       Sul\n",
              "4      2020-05-11  ...       Sul\n",
              "...           ...  ...       ...\n",
              "11399  2020-09-17  ...  Noroeste\n",
              "11400  2020-09-18  ...  Noroeste\n",
              "11401  2020-09-16  ...  Sudoeste\n",
              "11402  2020-09-17  ...  Sudoeste\n",
              "11403  2020-09-18  ...  Sudoeste\n",
              "\n",
              "[8364 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 454
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6rWGuq0zTp4G",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "6e55d794-8a93-41bb-b72c-399df1b9c66e"
      },
      "source": [
        "bairros_c_regiao = np.unique(df_completo_com_regiao['bairro'])\n",
        "bairros_covid = np.unique(covid_goiania_por_bairro['bairro'])\n",
        "\n",
        "faltantes = list(set(bairros_covid).difference(bairros_c_regiao))\n",
        "faltantes"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 455
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "D9QlOoRwTc3J",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "fb3ee8c2-3699-48cd-e366-6baac444ad0d"
      },
      "source": [
        "len(np.unique(df_completo_com_regiao['bairro']))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "109"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 456
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "E6yNiPdjaoye",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df_completo_com_regiao.to_csv('covid_goiania_por_bairro.csv', index=False)\n",
        "covid_goiania_por_bairro = df_completo_com_regiao"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ReHWSJ6SbNNw",
        "colab_type": "text"
      },
      "source": [
        "## Bar race - região"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DD5Sf5XLbUzx",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "61a64fd6-ad9d-4fb0-95ca-7c76b36811a0"
      },
      "source": [
        " df_bar_race = covid_goiania_por_bairro\n",
        " regioes = np.unique(df_bar_race['regiao'])\n",
        " lista_regioes = list(regioes)\n",
        " lista_regioes"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['Centro Oeste', 'Leste', 'Noroeste', 'Norte', 'Oeste', 'Sudoeste', 'Sul']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 458
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ampLncVJc10p",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "0c3d5b43-86aa-4fef-f622-807fb4835cab"
      },
      "source": [
        "indices = []\n",
        "for i, linha in df_bar_race.iterrows():\n",
        "    if linha[1] in lista_regioes:\n",
        "        indices.append(i)\n",
        "\n",
        "df_bar_race = df_bar_race.drop(indices)\n",
        "df_bar_race"
      ],
      "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>bairro</th>\n",
              "      <th>num_casos</th>\n",
              "      <th>cep</th>\n",
              "      <th>localizacao</th>\n",
              "      <th>regiao</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-05-02</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>48</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>[-16.6956937, -49.2640252]</td>\n",
              "      <td>Sul</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-04-29</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>45</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>[-16.6956937, -49.2640252]</td>\n",
              "      <td>Sul</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-04-30</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>48</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>[-16.6956937, -49.2640252]</td>\n",
              "      <td>Sul</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-05-03</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>52</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>[-16.6956937, -49.2640252]</td>\n",
              "      <td>Sul</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-05-11</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>73</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>[-16.6956937, -49.2640252]</td>\n",
              "      <td>Sul</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11399</th>\n",
              "      <td>2020-09-17</td>\n",
              "      <td>Conjunto Habitacional Madre Germana 2</td>\n",
              "      <td>128</td>\n",
              "      <td>74354-830</td>\n",
              "      <td>[-16.8154446,-49.3747038]</td>\n",
              "      <td>Noroeste</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11400</th>\n",
              "      <td>2020-09-18</td>\n",
              "      <td>Conjunto Habitacional Madre Germana 2</td>\n",
              "      <td>128</td>\n",
              "      <td>74354-830</td>\n",
              "      <td>[-16.8154446,-49.3747038]</td>\n",
              "      <td>Noroeste</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11401</th>\n",
              "      <td>2020-09-16</td>\n",
              "      <td>Setor Rio Formoso</td>\n",
              "      <td>125</td>\n",
              "      <td>74370-020</td>\n",
              "      <td>[-16.7211142,-49.3337986]</td>\n",
              "      <td>Sudoeste</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11402</th>\n",
              "      <td>2020-09-17</td>\n",
              "      <td>Setor Rio Formoso</td>\n",
              "      <td>125</td>\n",
              "      <td>74370-020</td>\n",
              "      <td>[-16.7211142,-49.3337986]</td>\n",
              "      <td>Sudoeste</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11403</th>\n",
              "      <td>2020-09-18</td>\n",
              "      <td>Setor Rio Formoso</td>\n",
              "      <td>125</td>\n",
              "      <td>74370-020</td>\n",
              "      <td>[-16.7211142,-49.3337986]</td>\n",
              "      <td>Sudoeste</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>8364 rows × 6 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             data  ...    regiao\n",
              "0      2020-05-02  ...       Sul\n",
              "1      2020-04-29  ...       Sul\n",
              "2      2020-04-30  ...       Sul\n",
              "3      2020-05-03  ...       Sul\n",
              "4      2020-05-11  ...       Sul\n",
              "...           ...  ...       ...\n",
              "11399  2020-09-17  ...  Noroeste\n",
              "11400  2020-09-18  ...  Noroeste\n",
              "11401  2020-09-16  ...  Sudoeste\n",
              "11402  2020-09-17  ...  Sudoeste\n",
              "11403  2020-09-18  ...  Sudoeste\n",
              "\n",
              "[8364 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 459
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "K_J5-AGBc8-e",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "outputId": "35e2776f-cf27-4752-ef24-f4f7fd3ec2ca"
      },
      "source": [
        "df_bar_race.groupby(['regiao', 'data']).sum()['num_casos']"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "regiao        data      \n",
              "Centro Oeste  2020-04-29      44\n",
              "              2020-04-30      45\n",
              "              2020-05-01      45\n",
              "              2020-05-02      50\n",
              "              2020-05-03      47\n",
              "                            ... \n",
              "Sul           2020-09-14    7596\n",
              "              2020-09-15    7596\n",
              "              2020-09-16    8152\n",
              "              2020-09-17    8152\n",
              "              2020-09-18    8152\n",
              "Name: num_casos, Length: 914, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 460
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q9Hpk0srdFwg",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df_bar_race = pd.DataFrame(df_bar_race.groupby(['regiao', 'data']).sum()['num_casos']).unstack().T.droplevel(level=0)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "N6DLQYGndJOe",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df_bar_race.columns = ['Centro', 'Leste', 'Noroeste', 'Norte', 'Oeste', 'Sudoeste', 'Sul']\n",
        "bcr.bar_chart_race(df_bar_race, filename='bar_race_regiao.mp4')\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "C7wSisDElxFn"
      },
      "source": [
        "## Bar race - bairro"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AoqwChEjmElf",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df_bar_race = pd.read_csv('covid_goiania_por_bairro.csv', encoding = 'utf-8', sep=',')\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "45Iw8XBAlxFp",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "05b20732-19d6-4aa3-ddfe-6cb5040c8450"
      },
      "source": [
        " bairros = np.unique(df_bar_race['bairro'])\n",
        " lista_bairros = list(bairros)\n",
        "lista_bairros\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['Alphaville Flamboyant',\n",
              " 'Alto da Glória',\n",
              " 'Capuava',\n",
              " 'Cidade Jardim',\n",
              " 'Conjunto Habitacional Madre Germana 2',\n",
              " 'Conjunto Primavera',\n",
              " 'Conjunto Vera Cruz',\n",
              " 'Faicalville',\n",
              " 'Floresta',\n",
              " 'Goiá',\n",
              " 'Goiânia 2',\n",
              " 'Jardim América',\n",
              " 'Jardim Atlântico',\n",
              " 'Jardim Balneário Meia Ponte',\n",
              " 'Jardim Bela Vista',\n",
              " 'Jardim Curitiba',\n",
              " 'Jardim Europa',\n",
              " 'Jardim Goiás',\n",
              " 'Jardim Guanabara',\n",
              " 'Jardim Guanabara II',\n",
              " 'Jardim Guanabara III',\n",
              " 'Jardim Itaipu',\n",
              " 'Jardim Liberdade',\n",
              " 'Jardim Mariliza',\n",
              " 'Jardim Nova Esperanca',\n",
              " 'Jardim Novo Mundo',\n",
              " 'Jardim Petrópolis',\n",
              " 'Jardim Planalto',\n",
              " 'Jardim Presidente',\n",
              " 'Jardim Vila Boa',\n",
              " 'Jardim das Esmeraldas',\n",
              " 'Nova Suiça',\n",
              " 'Parque Amazônia',\n",
              " 'Parque Anhanguera',\n",
              " 'Parque Atheneu',\n",
              " 'Parque Industrial de Goiânia',\n",
              " 'Parque Oeste Industrial',\n",
              " 'Parque Santa Rita',\n",
              " 'Parque das Amendoeiras',\n",
              " 'Parque das Laranjeiras',\n",
              " 'Portal do Sol II',\n",
              " 'Residencial Aldeia do Vale',\n",
              " 'Residencial Brisas da Mata',\n",
              " 'Residencial Eldorado',\n",
              " 'Residencial Goiânia Viva',\n",
              " 'Residencial Granville',\n",
              " 'Residencial Itaipú',\n",
              " 'Residencial Petropolis',\n",
              " 'Residencial Recanto das Garças',\n",
              " 'Residencial Recanto do Bosque',\n",
              " 'Residencial Vale dos Sonhos I',\n",
              " 'Rodoviário',\n",
              " 'Santa Genoveva',\n",
              " 'Santo Hilário',\n",
              " 'Setor Aeroporto',\n",
              " 'Setor Bela Vista',\n",
              " 'Setor Bueno',\n",
              " 'Setor Campinas',\n",
              " 'Setor Candida de Morais',\n",
              " 'Setor Central',\n",
              " 'Setor Centro Oeste',\n",
              " 'Setor Coimbra',\n",
              " 'Setor Criméia Leste',\n",
              " 'Setor Criméia Oeste',\n",
              " 'Setor Estrela Dalva',\n",
              " 'Setor Garavelo',\n",
              " 'Setor Jaó',\n",
              " 'Setor Leste Universitário',\n",
              " 'Setor Leste Vila Nova',\n",
              " 'Setor Marechal Rondon',\n",
              " 'Setor Marista',\n",
              " 'Setor Morada do Sol',\n",
              " 'Setor Negrão de Lima',\n",
              " 'Setor Norte Ferroviário',\n",
              " 'Setor Novo Horizonte',\n",
              " 'Setor Novo Planalto',\n",
              " 'Setor Oeste',\n",
              " 'Setor Parque Tremendão',\n",
              " 'Setor Pedro Ludovico',\n",
              " 'Setor Perim',\n",
              " 'Setor Recanto das Minas Gerais',\n",
              " 'Setor Rio Formoso',\n",
              " 'Setor Santos Dumont',\n",
              " 'Setor Sudoeste',\n",
              " 'Setor Sul',\n",
              " 'Setor São Jose',\n",
              " 'Setor União',\n",
              " 'Setor Urias Magalhaes',\n",
              " 'Setor dos Funcionários',\n",
              " 'Solange Parque I',\n",
              " 'São Carlos',\n",
              " 'São Francisco',\n",
              " 'Vila Alpes',\n",
              " 'Vila Canaa',\n",
              " 'Vila Concórdia',\n",
              " 'Vila Finsocial',\n",
              " 'Vila Itatiaia',\n",
              " 'Vila Jardim Pompéia',\n",
              " 'Vila Jardim São Judas Tadeu',\n",
              " 'Vila João Vaz',\n",
              " 'Vila Maria José',\n",
              " 'Vila Mutirão I',\n",
              " 'Vila Pedroso',\n",
              " 'Vila Redenção',\n",
              " 'Vila Regina',\n",
              " 'Vila Rosa',\n",
              " 'Vila Santa Helena',\n",
              " 'Vila São José - Extensão',\n",
              " 'da Vitória']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 472
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Gt0bo9nEmW8q",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#lista de bairros que não irão aparecer no bar race \n",
        "#bairros removidos da lista:\n",
        "\n",
        "lista_bairros = ['Alphaville Flamboyant',\n",
        " 'Alto da Glória',\n",
        " 'Capuava',\n",
        " 'Cidade Jardim',\n",
        " 'Conjunto Habitacional Madre Germana 2',\n",
        " 'Conjunto Primavera',\n",
        " 'Conjunto Vera Cruz',\n",
        " 'Faicalville',\n",
        " 'Floresta',\n",
        " 'Goiá',\n",
        " 'Jardim América',\n",
        " 'Jardim Atlântico',\n",
        " 'Jardim Balneário Meia Ponte',\n",
        " 'Jardim Bela Vista',\n",
        " 'Jardim Curitiba',\n",
        " 'Jardim Europa',\n",
        " 'Jardim Guanabara II',\n",
        " 'Jardim Guanabara III',\n",
        " 'Jardim Itaipu',\n",
        " 'Jardim Liberdade',\n",
        " 'Jardim Mariliza',\n",
        " 'Jardim Nova Esperanca',\n",
        " 'Jardim Novo Mundo',\n",
        " 'Jardim Petrópolis',\n",
        " 'Jardim Planalto',\n",
        " 'Jardim Presidente',\n",
        " 'Jardim São José',\n",
        " 'Jardim Valência',\n",
        " 'Jardim Vila Boa',\n",
        " 'Jardim das Esmeraldas',\n",
        " 'Nova Suiça',\n",
        " 'Parque Anhanguera',\n",
        " 'Parque Atheneu',\n",
        " 'Parque Industrial João Braz',\n",
        " 'Parque Industrial de Goiânia',\n",
        " 'Parque Oeste Industrial',\n",
        " 'Parque Santa Rita',\n",
        " 'Parque das Amendoeiras',\n",
        " 'Parque das Laranjeiras',\n",
        " 'Portal do Sol II',\n",
        " 'Residencial Aldeia do Vale',\n",
        " 'Residencial Brisas da Mata',\n",
        " 'Residencial Eldorado',\n",
        " 'Residencial Goiânia Viva',\n",
        " 'Residencial Granville',\n",
        " 'Residencial Itaipú',\n",
        " 'Residencial Jardim Florença',\n",
        " 'Residencial Orlando de Morais',\n",
        " 'Residencial Petropolis',\n",
        " 'Residencial Recanto das Garças',\n",
        " 'Residencial Vale dos Sonhos I',\n",
        " 'Rodoviário',\n",
        " 'Santa Genoveva',\n",
        " 'Santo Hilário',\n",
        " 'Setor Aeroporto',\n",
        " 'Setor Bela Vista',\n",
        " 'Setor Candida de Morais',\n",
        " 'Setor Centro Oeste',\n",
        " 'Setor Criméia Leste',\n",
        " 'Setor Criméia Oeste',\n",
        " 'Setor Estrela Dalva',\n",
        " 'Setor Garavelo',\n",
        " 'Setor Jaó',\n",
        " 'Setor Marechal Rondon',\n",
        " 'Setor Marista',\n",
        " 'Setor Morada do Sol',\n",
        " 'Setor Novo Horizonte',\n",
        " 'Setor Novo Planalto',\n",
        " 'Setor Parque Tremendão',\n",
        " 'Setor Perim',\n",
        " 'Setor Recanto das Minas Gerais',\n",
        " 'Setor Rio Formoso',\n",
        " 'Setor Santos Dumont',\n",
        " 'Setor Sudoeste',\n",
        " 'Setor Sul',\n",
        " 'Setor São Jose',\n",
        " 'Setor União',\n",
        " 'Setor Urias Magalhaes',\n",
        " 'Setor dos Funcionários',\n",
        " 'Solange Parque I',\n",
        " 'São Carlos',\n",
        " 'São Francisco',\n",
        " 'Vila Alpes',\n",
        " 'Vila Canaa',\n",
        " 'Vila Concórdia',\n",
        " 'Vila Finsocial',\n",
        " 'Vila Jardim São Judas Tadeu',\n",
        " 'Vila João Vaz',\n",
        " 'Vila Maria José',\n",
        " 'Vila Mutirão I',\n",
        " 'Vila Pedroso',\n",
        " 'Vila Redenção',\n",
        " 'Vila Regina',\n",
        " 'Vila Rosa',\n",
        " 'Vila Santa Helena',\n",
        " 'Vila São José - Extensão',\n",
        " 'da Vitória']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "D6o_Ee22mewA",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "65db72c6-36b4-49da-de01-8555a8f35e29"
      },
      "source": [
        "len(lista_bairros)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "97"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 474
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "x-WHArwjlxFu",
        "colab": {}
      },
      "source": [
        "#remove os bairros\n",
        "indices = []\n",
        "for i, linha in df_bar_race.iterrows():\n",
        "    if linha['bairro'] in lista_bairros:\n",
        "        indices.append(i)\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mp0Aq9Amnr37",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "5e8a65f2-804e-44a6-8024-daef19371617"
      },
      "source": [
        "df_bar_race = df_bar_race.drop(indices)\n",
        "df_bar_race"
      ],
      "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>bairro</th>\n",
              "      <th>num_casos</th>\n",
              "      <th>cep</th>\n",
              "      <th>localizacao</th>\n",
              "      <th>regiao</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-05-02</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>48</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>[-16.6956937, -49.2640252]</td>\n",
              "      <td>Sul</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-04-29</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>45</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>[-16.6956937, -49.2640252]</td>\n",
              "      <td>Sul</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-04-30</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>48</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>[-16.6956937, -49.2640252]</td>\n",
              "      <td>Sul</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-05-03</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>52</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>[-16.6956937, -49.2640252]</td>\n",
              "      <td>Sul</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-05-11</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>73</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>[-16.6956937, -49.2640252]</td>\n",
              "      <td>Sul</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7975</th>\n",
              "      <td>2020-09-14</td>\n",
              "      <td>Vila Itatiaia</td>\n",
              "      <td>119</td>\n",
              "      <td>74690-505</td>\n",
              "      <td>[-16.5957572, -49.258295]</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7976</th>\n",
              "      <td>2020-09-15</td>\n",
              "      <td>Vila Itatiaia</td>\n",
              "      <td>119</td>\n",
              "      <td>74690-505</td>\n",
              "      <td>[-16.5957572, -49.258295]</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7977</th>\n",
              "      <td>2020-09-16</td>\n",
              "      <td>Vila Itatiaia</td>\n",
              "      <td>138</td>\n",
              "      <td>74690-505</td>\n",
              "      <td>[-16.5957572, -49.258295]</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7978</th>\n",
              "      <td>2020-09-17</td>\n",
              "      <td>Vila Itatiaia</td>\n",
              "      <td>138</td>\n",
              "      <td>74690-505</td>\n",
              "      <td>[-16.5957572, -49.258295]</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7979</th>\n",
              "      <td>2020-09-18</td>\n",
              "      <td>Vila Itatiaia</td>\n",
              "      <td>138</td>\n",
              "      <td>74690-505</td>\n",
              "      <td>[-16.5957572, -49.258295]</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1888 rows × 6 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            data         bairro  ...                 localizacao regiao\n",
              "0     2020-05-02    Setor Bueno  ...  [-16.6956937, -49.2640252]    Sul\n",
              "1     2020-04-29    Setor Bueno  ...  [-16.6956937, -49.2640252]    Sul\n",
              "2     2020-04-30    Setor Bueno  ...  [-16.6956937, -49.2640252]    Sul\n",
              "3     2020-05-03    Setor Bueno  ...  [-16.6956937, -49.2640252]    Sul\n",
              "4     2020-05-11    Setor Bueno  ...  [-16.6956937, -49.2640252]    Sul\n",
              "...          ...            ...  ...                         ...    ...\n",
              "7975  2020-09-14  Vila Itatiaia  ...   [-16.5957572, -49.258295]  Norte\n",
              "7976  2020-09-15  Vila Itatiaia  ...   [-16.5957572, -49.258295]  Norte\n",
              "7977  2020-09-16  Vila Itatiaia  ...   [-16.5957572, -49.258295]  Norte\n",
              "7978  2020-09-17  Vila Itatiaia  ...   [-16.5957572, -49.258295]  Norte\n",
              "7979  2020-09-18  Vila Itatiaia  ...   [-16.5957572, -49.258295]  Norte\n",
              "\n",
              "[1888 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 476
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "IYyLc-MflxFx",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "outputId": "a3156933-71b6-427c-afd4-a7a26e0bce8a"
      },
      "source": [
        "df_bar_race.groupby(['bairro', 'data']).sum()['num_casos']"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "bairro               data      \n",
              "Goiânia 2            2020-05-11      5\n",
              "                     2020-05-12      5\n",
              "                     2020-05-14      6\n",
              "                     2020-05-15      7\n",
              "                     2020-05-16      7\n",
              "                                  ... \n",
              "Vila Jardim Pompéia  2020-09-14    118\n",
              "                     2020-09-15    118\n",
              "                     2020-09-16    128\n",
              "                     2020-09-17    128\n",
              "                     2020-09-18    128\n",
              "Name: num_casos, Length: 1888, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 477
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "uuYklXNFlxF7",
        "colab": {}
      },
      "source": [
        "df_bar_race = pd.DataFrame(df_bar_race.groupby(['bairro', 'data']).sum()['num_casos']).unstack().T.droplevel(level=0)\n",
        "bcr.bar_chart_race(df_bar_race, filename='bar_race_bairro.mp4')\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "99ibYXOtRuzh",
        "colab_type": "text"
      },
      "source": [
        "## Dataframe para plotagem do mapa"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SU9hyqMxQJtf",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "c2b49f99-3e7f-4486-9fe4-22a48a29559d"
      },
      "source": [
        "covid_goiania_por_bairro.columns = ['Date', 'Zone', 'Count', 'CEP', 'Location', 'Region']\n",
        "covid_goiania_por_bairro['Category'] = 'Confirmed'\n",
        "covid_goiania_por_bairro[\"Count\"] = pd.to_numeric(covid_goiania_por_bairro[\"Count\"])\n",
        "\n",
        "covid_goiania_por_bairro['Location'] = covid_goiania_por_bairro['Location'].apply(lambda x: x[1:])\n",
        "covid_goiania_por_bairro['Location'] = covid_goiania_por_bairro['Location'].apply(lambda x: x[:-1])\n",
        "covid_goiania_por_bairro['Location'] = covid_goiania_por_bairro['Location'].apply(lambda x: x.replace(\" \", \"\"))\n",
        "\n",
        "# df_completo.to_csv('/content/drive/My Drive/Colab Notebooks/covid/covid-19-goiania-por-bairro-final.csv', index=False)\n",
        "covid_goiania_por_bairro.to_csv('covid-19-goiania-por-bairro-final.csv', index=False)\n",
        "covid_goiania_por_bairro"
      ],
      "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>Date</th>\n",
              "      <th>Zone</th>\n",
              "      <th>Count</th>\n",
              "      <th>CEP</th>\n",
              "      <th>Location</th>\n",
              "      <th>Region</th>\n",
              "      <th>Category</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-05-02</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>48</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>-16.6956937,-49.2640252</td>\n",
              "      <td>Sul</td>\n",
              "      <td>Confirmed</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-04-29</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>45</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>-16.6956937,-49.2640252</td>\n",
              "      <td>Sul</td>\n",
              "      <td>Confirmed</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-04-30</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>48</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>-16.6956937,-49.2640252</td>\n",
              "      <td>Sul</td>\n",
              "      <td>Confirmed</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-05-03</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>52</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>-16.6956937,-49.2640252</td>\n",
              "      <td>Sul</td>\n",
              "      <td>Confirmed</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-05-11</td>\n",
              "      <td>Setor Bueno</td>\n",
              "      <td>73</td>\n",
              "      <td>74223-010</td>\n",
              "      <td>-16.6956937,-49.2640252</td>\n",
              "      <td>Sul</td>\n",
              "      <td>Confirmed</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11399</th>\n",
              "      <td>2020-09-17</td>\n",
              "      <td>Conjunto Habitacional Madre Germana 2</td>\n",
              "      <td>128</td>\n",
              "      <td>74354-830</td>\n",
              "      <td>-16.8154446,-49.3747038</td>\n",
              "      <td>Noroeste</td>\n",
              "      <td>Confirmed</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11400</th>\n",
              "      <td>2020-09-18</td>\n",
              "      <td>Conjunto Habitacional Madre Germana 2</td>\n",
              "      <td>128</td>\n",
              "      <td>74354-830</td>\n",
              "      <td>-16.8154446,-49.3747038</td>\n",
              "      <td>Noroeste</td>\n",
              "      <td>Confirmed</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11401</th>\n",
              "      <td>2020-09-16</td>\n",
              "      <td>Setor Rio Formoso</td>\n",
              "      <td>125</td>\n",
              "      <td>74370-020</td>\n",
              "      <td>-16.7211142,-49.3337986</td>\n",
              "      <td>Sudoeste</td>\n",
              "      <td>Confirmed</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11402</th>\n",
              "      <td>2020-09-17</td>\n",
              "      <td>Setor Rio Formoso</td>\n",
              "      <td>125</td>\n",
              "      <td>74370-020</td>\n",
              "      <td>-16.7211142,-49.3337986</td>\n",
              "      <td>Sudoeste</td>\n",
              "      <td>Confirmed</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11403</th>\n",
              "      <td>2020-09-18</td>\n",
              "      <td>Setor Rio Formoso</td>\n",
              "      <td>125</td>\n",
              "      <td>74370-020</td>\n",
              "      <td>-16.7211142,-49.3337986</td>\n",
              "      <td>Sudoeste</td>\n",
              "      <td>Confirmed</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>8364 rows × 7 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             Date                                   Zone  ...    Region   Category\n",
              "0      2020-05-02                            Setor Bueno  ...       Sul  Confirmed\n",
              "1      2020-04-29                            Setor Bueno  ...       Sul  Confirmed\n",
              "2      2020-04-30                            Setor Bueno  ...       Sul  Confirmed\n",
              "3      2020-05-03                            Setor Bueno  ...       Sul  Confirmed\n",
              "4      2020-05-11                            Setor Bueno  ...       Sul  Confirmed\n",
              "...           ...                                    ...  ...       ...        ...\n",
              "11399  2020-09-17  Conjunto Habitacional Madre Germana 2  ...  Noroeste  Confirmed\n",
              "11400  2020-09-18  Conjunto Habitacional Madre Germana 2  ...  Noroeste  Confirmed\n",
              "11401  2020-09-16                      Setor Rio Formoso  ...  Sudoeste  Confirmed\n",
              "11402  2020-09-17                      Setor Rio Formoso  ...  Sudoeste  Confirmed\n",
              "11403  2020-09-18                      Setor Rio Formoso  ...  Sudoeste  Confirmed\n",
              "\n",
              "[8364 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 481
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bQISirNgDyM3",
        "colab_type": "text"
      },
      "source": [
        "## Gráfico de barras\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mJfZSzpSR0Ib",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#fonte dos dados: https://brasil.io/dataset/covid19/caso/?search=Goi%C3%A2nia&date=&state=GO&city=&place_type=&is_last=&city_ibge_code=5208707&order_for_place=\n",
        "\n",
        "\n",
        "\n",
        "bar_graph_dados = pd.read_csv('covid19-335f39aca2a64a1a99ef2e3e5eedbbc0.csv', sep=',')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nRpSSq3kSFAq",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4cfc1070-268b-47d8-f175-88bed8453378"
      },
      "source": [
        "bar_graph_dados.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>date</th>\n",
              "      <th>state</th>\n",
              "      <th>city</th>\n",
              "      <th>place_type</th>\n",
              "      <th>confirmed</th>\n",
              "      <th>deaths</th>\n",
              "      <th>is_last</th>\n",
              "      <th>estimated_population_2019</th>\n",
              "      <th>city_ibge_code</th>\n",
              "      <th>confirmed_per_100k_inhabitants</th>\n",
              "      <th>death_rate</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-09-17</td>\n",
              "      <td>GO</td>\n",
              "      <td>Goiânia</td>\n",
              "      <td>city</td>\n",
              "      <td>45662</td>\n",
              "      <td>1168</td>\n",
              "      <td>True</td>\n",
              "      <td>1516113</td>\n",
              "      <td>5208707</td>\n",
              "      <td>3011.78078</td>\n",
              "      <td>0.0256</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-09-16</td>\n",
              "      <td>GO</td>\n",
              "      <td>Goiânia</td>\n",
              "      <td>city</td>\n",
              "      <td>44324</td>\n",
              "      <td>1135</td>\n",
              "      <td>False</td>\n",
              "      <td>1516113</td>\n",
              "      <td>5208707</td>\n",
              "      <td>2923.52879</td>\n",
              "      <td>0.0256</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-09-15</td>\n",
              "      <td>GO</td>\n",
              "      <td>Goiânia</td>\n",
              "      <td>city</td>\n",
              "      <td>42978</td>\n",
              "      <td>1116</td>\n",
              "      <td>False</td>\n",
              "      <td>1516113</td>\n",
              "      <td>5208707</td>\n",
              "      <td>2834.74912</td>\n",
              "      <td>0.0260</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-09-14</td>\n",
              "      <td>GO</td>\n",
              "      <td>Goiânia</td>\n",
              "      <td>city</td>\n",
              "      <td>41698</td>\n",
              "      <td>1098</td>\n",
              "      <td>False</td>\n",
              "      <td>1516113</td>\n",
              "      <td>5208707</td>\n",
              "      <td>2750.32270</td>\n",
              "      <td>0.0263</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-09-13</td>\n",
              "      <td>GO</td>\n",
              "      <td>Goiânia</td>\n",
              "      <td>city</td>\n",
              "      <td>39797</td>\n",
              "      <td>1074</td>\n",
              "      <td>False</td>\n",
              "      <td>1516113</td>\n",
              "      <td>5208707</td>\n",
              "      <td>2624.93627</td>\n",
              "      <td>0.0270</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         date state  ... confirmed_per_100k_inhabitants death_rate\n",
              "0  2020-09-17    GO  ...                     3011.78078     0.0256\n",
              "1  2020-09-16    GO  ...                     2923.52879     0.0256\n",
              "2  2020-09-15    GO  ...                     2834.74912     0.0260\n",
              "3  2020-09-14    GO  ...                     2750.32270     0.0263\n",
              "4  2020-09-13    GO  ...                     2624.93627     0.0270\n",
              "\n",
              "[5 rows x 11 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 486
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9QUb4s6SSshe",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4bf1d362-b6b9-4c09-db27-e762072eba14"
      },
      "source": [
        "bar_graph_dados.columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['date', 'state', 'city', 'place_type', 'confirmed', 'deaths', 'is_last',\n",
              "       'estimated_population_2019', 'city_ibge_code',\n",
              "       'confirmed_per_100k_inhabitants', 'death_rate'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 487
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "f-3VF21NSJay",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9973cad1-18d1-4b09-b2ec-5e6d414a55e2"
      },
      "source": [
        "bar_graph_dados.drop(columns=['is_last', 'estimated_population_2019', 'city_ibge_code', 'state',\n",
        "                                'confirmed_per_100k_inhabitants', 'death_rate','place_type'\n",
        "                            ], inplace=True)\n",
        "                     \n",
        "\n",
        "bar_graph_dados.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>date</th>\n",
              "      <th>city</th>\n",
              "      <th>confirmed</th>\n",
              "      <th>deaths</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-09-17</td>\n",
              "      <td>Goiânia</td>\n",
              "      <td>45662</td>\n",
              "      <td>1168</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-09-16</td>\n",
              "      <td>Goiânia</td>\n",
              "      <td>44324</td>\n",
              "      <td>1135</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-09-15</td>\n",
              "      <td>Goiânia</td>\n",
              "      <td>42978</td>\n",
              "      <td>1116</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-09-14</td>\n",
              "      <td>Goiânia</td>\n",
              "      <td>41698</td>\n",
              "      <td>1098</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-09-13</td>\n",
              "      <td>Goiânia</td>\n",
              "      <td>39797</td>\n",
              "      <td>1074</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         date     city  confirmed  deaths\n",
              "0  2020-09-17  Goiânia      45662    1168\n",
              "1  2020-09-16  Goiânia      44324    1135\n",
              "2  2020-09-15  Goiânia      42978    1116\n",
              "3  2020-09-14  Goiânia      41698    1098\n",
              "4  2020-09-13  Goiânia      39797    1074"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 488
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "r1vonxfwTPiS",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "52239a56-c79b-44b3-9356-6f861b441fde"
      },
      "source": [
        "bar_graph_dados.rename(columns={'date': 'Data', 'city': 'Cidade', 'confirmed': 'Casos confirmados', 'deaths': 'Óbitos'}, inplace=True)\n",
        "bar_graph_dados.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>Cidade</th>\n",
              "      <th>Casos confirmados</th>\n",
              "      <th>Óbitos</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-09-17</td>\n",
              "      <td>Goiânia</td>\n",
              "      <td>45662</td>\n",
              "      <td>1168</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-09-16</td>\n",
              "      <td>Goiânia</td>\n",
              "      <td>44324</td>\n",
              "      <td>1135</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-09-15</td>\n",
              "      <td>Goiânia</td>\n",
              "      <td>42978</td>\n",
              "      <td>1116</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-09-14</td>\n",
              "      <td>Goiânia</td>\n",
              "      <td>41698</td>\n",
              "      <td>1098</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-09-13</td>\n",
              "      <td>Goiânia</td>\n",
              "      <td>39797</td>\n",
              "      <td>1074</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         Data   Cidade  Casos confirmados  Óbitos\n",
              "0  2020-09-17  Goiânia              45662    1168\n",
              "1  2020-09-16  Goiânia              44324    1135\n",
              "2  2020-09-15  Goiânia              42978    1116\n",
              "3  2020-09-14  Goiânia              41698    1098\n",
              "4  2020-09-13  Goiânia              39797    1074"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 489
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bJE1S_swWgBH",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "cf28e238-68ec-4359-dd0f-a2339f9d93e1"
      },
      "source": [
        "fig = px.bar(bar_graph_dados, x='Data', y='Casos confirmados')\n",
        "fig.update_traces()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
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              "        <script src=\"https://cdn.plot.ly/plotly-latest.min.js\"></script>    \n",
              "            <div id=\"119b29c0-e32d-46a8-ad5e-8b8307b5e159\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
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      "execution_count": null,
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      "cell_type": "code",
      "metadata": {
        "id": "adbwCX5aaoXq",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# bar_graph_dados.to_csv('/content/drive/My Drive/Colab Notebooks/covid/brasil_io-goiania.csv', index=False)\n",
        "bar_graph_dados.to_csv('brasil_io-goiania.csv', index=False)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eY8A5xtw4wzk",
        "colab_type": "text"
      },
      "source": [
        "# Etapas a partir dos dados da Secretária de Saúde do Estado de Goiás\n",
        "\n",
        "*   Gráfico de barras - casos ativos por data de notificação\n",
        "*   Gráfico de barras - casos confirmados por data de notificação\n",
        "*   Gráfico de barras - óbitos por data de notificação\n",
        "*   Média móvel em todos os gráficos\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vCLAoTTSBL8V",
        "colab_type": "text"
      },
      "source": [
        "## Dataset - casos\n",
        "\n",
        "```\n",
        "# casos_goiania_cidade\n",
        "```\n",
        "\n"
      ]
    },
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          "height": 524
        },
        "outputId": "9d91ceb5-3be8-4150-f003-47b788388f45"
      },
      "source": [
        "casos_goiania_cidade = pd.read_csv('http://datasets.saude.go.gov.br/coronavirus/casos_confirmados.csv', sep=';')\n",
        "casos_goiania_cidade"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>data_notificacao</th>\n",
              "      <th>data_inicio_sintomas</th>\n",
              "      <th>ano_epi</th>\n",
              "      <th>semana_epi</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>20200806</td>\n",
              "      <td>20200717</td>\n",
              "      <td>2020</td>\n",
              "      <td>29</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>BRANCA</td>\n",
              "      <td>20 a 29 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>SIM</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>20200918</td>\n",
              "      <td>20200914</td>\n",
              "      <td>2020</td>\n",
              "      <td>38</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>BRANCA</td>\n",
              "      <td>20 a 29 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>521930</td>\n",
              "      <td>SANTA HELENA DE GOIAS</td>\n",
              "      <td>SUDOESTE I</td>\n",
              "      <td>NAO</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>20200811</td>\n",
              "      <td>20200811</td>\n",
              "      <td>2020</td>\n",
              "      <td>33</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>AMARELA</td>\n",
              "      <td>20 a 29 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>SIM</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>20200812</td>\n",
              "      <td>20200805</td>\n",
              "      <td>2020</td>\n",
              "      <td>32</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>PARDA</td>\n",
              "      <td>30 a 39 anos</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>520510</td>\n",
              "      <td>CATALAO</td>\n",
              "      <td>ESTRADA DE FERRO</td>\n",
              "      <td>SIM</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>20200810</td>\n",
              "      <td>20200806</td>\n",
              "      <td>2020</td>\n",
              "      <td>32</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>AMARELA</td>\n",
              "      <td>20 a 29 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520140</td>\n",
              "      <td>APARECIDA DE GOIANIA</td>\n",
              "      <td>CENTRO SUL</td>\n",
              "      <td>SIM</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>183537</th>\n",
              "      <td>20200722</td>\n",
              "      <td>20200715</td>\n",
              "      <td>2020</td>\n",
              "      <td>29</td>\n",
              "      <td>FEMININO</td>\n",
              "      <td>PARDA</td>\n",
              "      <td>40 a 49 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>SIM</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>183538</th>\n",
              "      <td>20200613</td>\n",
              "      <td>20200612</td>\n",
              "      <td>2020</td>\n",
              "      <td>24</td>\n",
              "      <td>FEMININO</td>\n",
              "      <td>BRANCA</td>\n",
              "      <td>70 a 79  anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>SIM</td>\n",
              "      <td>SIM</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>SIM</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>183539</th>\n",
              "      <td>20200811</td>\n",
              "      <td>20200811</td>\n",
              "      <td>2020</td>\n",
              "      <td>33</td>\n",
              "      <td>FEMININO</td>\n",
              "      <td>PARDA</td>\n",
              "      <td>60 a 69 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>521880</td>\n",
              "      <td>RIO VERDE</td>\n",
              "      <td>SUDOESTE I</td>\n",
              "      <td>SIM</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>183540</th>\n",
              "      <td>20200824</td>\n",
              "      <td>20200817</td>\n",
              "      <td>2020</td>\n",
              "      <td>34</td>\n",
              "      <td>FEMININO</td>\n",
              "      <td>AMARELA</td>\n",
              "      <td>50 a 59 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>522145</td>\n",
              "      <td>TROMBAS</td>\n",
              "      <td>NORTE</td>\n",
              "      <td>SIM</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>183541</th>\n",
              "      <td>20200727</td>\n",
              "      <td>20200720</td>\n",
              "      <td>2020</td>\n",
              "      <td>30</td>\n",
              "      <td>FEMININO</td>\n",
              "      <td>PARDA</td>\n",
              "      <td>50 a 59 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>522185</td>\n",
              "      <td>VALPARAISO DE GOIAS</td>\n",
              "      <td>ENTORNO SUL</td>\n",
              "      <td>SIM</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>183542 rows × 15 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "        data_notificacao  data_inicio_sintomas  ...      regiao_saude  recuperado\n",
              "0               20200806              20200717  ...           CENTRAL         SIM\n",
              "1               20200918              20200914  ...        SUDOESTE I         NAO\n",
              "2               20200811              20200811  ...           CENTRAL         SIM\n",
              "3               20200812              20200805  ...  ESTRADA DE FERRO         SIM\n",
              "4               20200810              20200806  ...        CENTRO SUL         SIM\n",
              "...                  ...                   ...  ...               ...         ...\n",
              "183537          20200722              20200715  ...           CENTRAL         SIM\n",
              "183538          20200613              20200612  ...           CENTRAL         SIM\n",
              "183539          20200811              20200811  ...        SUDOESTE I         SIM\n",
              "183540          20200824              20200817  ...             NORTE         SIM\n",
              "183541          20200727              20200720  ...       ENTORNO SUL         SIM\n",
              "\n",
              "[183542 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "BmZ7Emi4eKBx"
      },
      "source": [
        "## Óbitos por dia\n",
        "\n",
        "*   Gráfico de barras com média móvel\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "```\n",
        "dataframe: obitos_por_dia\n",
        "gera: obitos_por_dia_goiania.csv\n",
        "```\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "_Cy3DpjzeKBz",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 439
        },
        "outputId": "372c5094-b96e-43d5-b55a-ffdaa6af4378"
      },
      "source": [
        "obitos_por_dia = pd.read_csv('http://datasets.saude.go.gov.br/coronavirus/obitos_confirmados.csv', sep=';')\n",
        "obitos_por_dia_remove = obitos_por_dia.loc[((obitos_por_dia['municipio'] != 'GOIANIA'))]\n",
        "\n",
        "obitos_por_dia = obitos_por_dia.drop(obitos_por_dia_remove.index)\n",
        "obitos_por_dia"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "    }\n",
              "\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>data_notificacao</th>\n",
              "      <th>data_inicio_sintomas</th>\n",
              "      <th>ano_epi</th>\n",
              "      <th>semana_epi</th>\n",
              "      <th>sexo</th>\n",
              "      <th>raca_cor</th>\n",
              "      <th>faixa_etaria</th>\n",
              "      <th>diabetes</th>\n",
              "      <th>doenca_cardiovascular</th>\n",
              "      <th>doenca_respiratoria</th>\n",
              "      <th>imunossupressao</th>\n",
              "      <th>codigo_ibge</th>\n",
              "      <th>municipio</th>\n",
              "      <th>regiao_saude</th>\n",
              "      <th>data_obito</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>20200901</td>\n",
              "      <td>20200801</td>\n",
              "      <td>2020</td>\n",
              "      <td>31</td>\n",
              "      <td>FEMININO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>60 a 69 anos</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>20200905</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>20200629</td>\n",
              "      <td>20200618</td>\n",
              "      <td>2020</td>\n",
              "      <td>25</td>\n",
              "      <td>FEMININO</td>\n",
              "      <td>BRANCA</td>\n",
              "      <td>&gt;= 80 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>SIM</td>\n",
              "      <td>SIM</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>20200702</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>20200806</td>\n",
              "      <td>20200802</td>\n",
              "      <td>2020</td>\n",
              "      <td>32</td>\n",
              "      <td>FEMININO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>60 a 69 anos</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>20200809</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>20200715</td>\n",
              "      <td>20200627</td>\n",
              "      <td>2020</td>\n",
              "      <td>26</td>\n",
              "      <td>FEMININO</td>\n",
              "      <td>PARDA</td>\n",
              "      <td>50 a 59 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>SIM</td>\n",
              "      <td>SIM</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>20200709</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>20200803</td>\n",
              "      <td>20200731</td>\n",
              "      <td>2020</td>\n",
              "      <td>31</td>\n",
              "      <td>FEMININO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>60 a 69 anos</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>20200813</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4130</th>\n",
              "      <td>20200727</td>\n",
              "      <td>20200716</td>\n",
              "      <td>2020</td>\n",
              "      <td>29</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>&gt;= 80 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>20200805</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4131</th>\n",
              "      <td>20200703</td>\n",
              "      <td>20200624</td>\n",
              "      <td>2020</td>\n",
              "      <td>26</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>PARDA</td>\n",
              "      <td>60 a 69 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>20200715</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4137</th>\n",
              "      <td>20200708</td>\n",
              "      <td>20200705</td>\n",
              "      <td>2020</td>\n",
              "      <td>28</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>PARDA</td>\n",
              "      <td>&gt;= 80 anos</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>SIM</td>\n",
              "      <td>SIM</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>20200719</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4140</th>\n",
              "      <td>20200824</td>\n",
              "      <td>20200814</td>\n",
              "      <td>2020</td>\n",
              "      <td>33</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>PARDA</td>\n",
              "      <td>70 a 79  anos</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>SIM</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>20200831</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4141</th>\n",
              "      <td>20200617</td>\n",
              "      <td>20200613</td>\n",
              "      <td>2020</td>\n",
              "      <td>24</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>PRETA</td>\n",
              "      <td>50 a 59 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>SIM</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>20200619</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1196 rows × 15 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      data_notificacao  data_inicio_sintomas  ...  regiao_saude  data_obito\n",
              "7             20200901              20200801  ...       CENTRAL    20200905\n",
              "27            20200629              20200618  ...       CENTRAL    20200702\n",
              "28            20200806              20200802  ...       CENTRAL    20200809\n",
              "29            20200715              20200627  ...       CENTRAL    20200709\n",
              "32            20200803              20200731  ...       CENTRAL    20200813\n",
              "...                ...                   ...  ...           ...         ...\n",
              "4130          20200727              20200716  ...       CENTRAL    20200805\n",
              "4131          20200703              20200624  ...       CENTRAL    20200715\n",
              "4137          20200708              20200705  ...       CENTRAL    20200719\n",
              "4140          20200824              20200814  ...       CENTRAL    20200831\n",
              "4141          20200617              20200613  ...       CENTRAL    20200619\n",
              "\n",
              "[1196 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 732
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "SnyDVWSkeKB2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "23d85fe7-eb95-4fa0-a438-81d69b75e717"
      },
      "source": [
        "obitos_por_dia = obitos_por_dia['data_notificacao'].value_counts() \n",
        "obitos_por_dia = obitos_por_dia.to_frame(name='num_casos')\n",
        "obitos_por_dia.reset_index(level=0, inplace=True)\n",
        "obitos_por_dia.rename(columns={'index': 'data_notificacao'}, inplace = True)\n",
        "obitos_por_dia"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>20200731</td>\n",
              "      <td>33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>20200805</td>\n",
              "      <td>25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>20200803</td>\n",
              "      <td>24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>20200901</td>\n",
              "      <td>22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>20200826</td>\n",
              "      <td>21</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>141</th>\n",
              "      <td>20200512</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>142</th>\n",
              "      <td>20200514</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>143</th>\n",
              "      <td>20200516</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>144</th>\n",
              "      <td>20200609</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>145</th>\n",
              "      <td>20200401</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>146 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     data_notificacao  num_casos\n",
              "0            20200731         33\n",
              "1            20200805         25\n",
              "2            20200803         24\n",
              "3            20200901         22\n",
              "4            20200826         21\n",
              "..                ...        ...\n",
              "141          20200512          1\n",
              "142          20200514          1\n",
              "143          20200516          1\n",
              "144          20200609          1\n",
              "145          20200401          1\n",
              "\n",
              "[146 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 733
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "hsb5pMYieKB7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "c4aa27a3-c72d-4433-a400-6c7630f279a5"
      },
      "source": [
        "obitos_por_dia['data_notificacao'] = obitos_por_dia['data_notificacao'].apply(lambda x: datetime.strptime(str(x), '%Y%m%d').date())\n",
        "\n",
        "obitos_por_dia\n"
      ],
      "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_notificacao</th>\n",
              "      <th>num_casos</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-07-31</td>\n",
              "      <td>33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-08-05</td>\n",
              "      <td>25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-08-03</td>\n",
              "      <td>24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-09-01</td>\n",
              "      <td>22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-08-26</td>\n",
              "      <td>21</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>141</th>\n",
              "      <td>2020-05-12</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>142</th>\n",
              "      <td>2020-05-14</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>143</th>\n",
              "      <td>2020-05-16</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>144</th>\n",
              "      <td>2020-06-09</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>145</th>\n",
              "      <td>2020-04-01</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>146 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    data_notificacao  num_casos\n",
              "0         2020-07-31         33\n",
              "1         2020-08-05         25\n",
              "2         2020-08-03         24\n",
              "3         2020-09-01         22\n",
              "4         2020-08-26         21\n",
              "..               ...        ...\n",
              "141       2020-05-12          1\n",
              "142       2020-05-14          1\n",
              "143       2020-05-16          1\n",
              "144       2020-06-09          1\n",
              "145       2020-04-01          1\n",
              "\n",
              "[146 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 734
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "qZ2s8BozeKB9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "ded3d76f-eaa0-4297-e8aa-04f881e7c75d"
      },
      "source": [
        "obitos_por_dia['data_notificacao'] = pd.to_datetime(obitos_por_dia['data_notificacao'])\n",
        "\n",
        "# Ordena pela data e salva em um novo DataFrame\n",
        "obitos_por_dia = obitos_por_dia.sort_values(by='data_notificacao')\n",
        "obitos_por_dia"
      ],
      "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_notificacao</th>\n",
              "      <th>num_casos</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>145</th>\n",
              "      <td>2020-04-01</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>132</th>\n",
              "      <td>2020-04-03</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>120</th>\n",
              "      <td>2020-04-04</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>116</th>\n",
              "      <td>2020-04-05</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>133</th>\n",
              "      <td>2020-04-10</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>118</th>\n",
              "      <td>2020-09-12</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>107</th>\n",
              "      <td>2020-09-14</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>113</th>\n",
              "      <td>2020-09-15</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>123</th>\n",
              "      <td>2020-09-16</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>134</th>\n",
              "      <td>2020-09-18</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>146 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    data_notificacao  num_casos\n",
              "145       2020-04-01          1\n",
              "132       2020-04-03          1\n",
              "120       2020-04-04          2\n",
              "116       2020-04-05          2\n",
              "133       2020-04-10          1\n",
              "..               ...        ...\n",
              "118       2020-09-12          2\n",
              "107       2020-09-14          3\n",
              "113       2020-09-15          3\n",
              "123       2020-09-16          2\n",
              "134       2020-09-18          1\n",
              "\n",
              "[146 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 735
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "giT8Q_q_eKB_",
        "colab": {}
      },
      "source": [
        "obitos_por_dia.to_csv('obitos_por_dia_goiania.csv', index=False)\n",
        "obitos_por_dia"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "55g4TmjJeKCB"
      },
      "source": [
        "### Média móvel - casos confirmados por dia"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "2Tv4W3xieKCC",
        "colab": {}
      },
      "source": [
        "# casos_ativos_goiania = pd.read_csv('casos_ativos_goiania.csv', sep=',')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "qJbePZCBeKCE",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "outputId": "198bc860-839f-482a-c101-2da9b9f9d809"
      },
      "source": [
        "df = obitos_por_dia\n",
        "for i in range(0,df.shape[0]-6):\n",
        "    df.loc[df.index[i+6],'MM_casos'] = np.round(((df.iloc[i,1]+\n",
        "                                                  df.iloc[i+1,1]+\n",
        "                                                  df.iloc[i+2,1]+\n",
        "                                                  df.iloc[i+3,1]+\n",
        "                                                  df.iloc[i+4,1]+\n",
        "                                                  df.iloc[i+5,1]+\n",
        "                                                  df.iloc[i+6,1])/7),1)           \n",
        "\n",
        "df.head(8)"
      ],
      "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_notificacao</th>\n",
              "      <th>num_casos</th>\n",
              "      <th>MM_casos</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>145</th>\n",
              "      <td>2020-04-01</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>132</th>\n",
              "      <td>2020-04-03</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>120</th>\n",
              "      <td>2020-04-04</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>116</th>\n",
              "      <td>2020-04-05</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>133</th>\n",
              "      <td>2020-04-10</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>131</th>\n",
              "      <td>2020-04-14</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>130</th>\n",
              "      <td>2020-04-15</td>\n",
              "      <td>1</td>\n",
              "      <td>1.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>129</th>\n",
              "      <td>2020-04-16</td>\n",
              "      <td>1</td>\n",
              "      <td>1.3</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    data_notificacao  num_casos  MM_casos\n",
              "145       2020-04-01          1       NaN\n",
              "132       2020-04-03          1       NaN\n",
              "120       2020-04-04          2       NaN\n",
              "116       2020-04-05          2       NaN\n",
              "133       2020-04-10          1       NaN\n",
              "131       2020-04-14          1       NaN\n",
              "130       2020-04-15          1       1.3\n",
              "129       2020-04-16          1       1.3"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 737
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "TL8K99YSeKCG",
        "colab": {}
      },
      "source": [
        "obitos_por_dia.to_csv('obitos_por_dia_goiania.csv', index=False)"
      ],
      "execution_count": 750,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "Zu8g7QiKeKCJ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "outputId": "2dc3e48e-eb10-490f-fa20-a69280da4b6b"
      },
      "source": [
        "fig = px.bar(obitos_por_dia, x='data_notificacao', y='num_casos', labels={'num_casos':'N° de óbitos', \n",
        "                                                                         'data_notificacao': 'Data de notificação',})\n",
        "\n",
        "fig.add_trace(\n",
        "    go.Scatter(\n",
        "        x=obitos_por_dia['data_notificacao'],\n",
        "        y=obitos_por_dia['MM_casos'],\n",
        "        name='Média Móvel<br>(7 dias)',        \n",
        "        hovertemplate= \"Média Móvel: %{x}<br>Data: %{y}<extra></extra>\",\n",
        "\n",
        "    ))\n",
        "\n",
        "fig.update_traces()"
      ],
      "execution_count": 758,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<html>\n",
              "<head><meta charset=\"utf-8\" /></head>\n",
              "<body>\n",
              "    <div>\n",
              "            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>\n",
              "                <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
              "        <script src=\"https://cdn.plot.ly/plotly-latest.min.js\"></script>    \n",
              "            <div id=\"d070167b-bf50-404a-8666-fdc3dd77de0d\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
              "            <script type=\"text/javascript\">\n",
              "                \n",
              "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
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              "                        [{\"alignmentgroup\": \"True\", \"hoverlabel\": {\"namelength\": 0}, \"hovertemplate\": \"Data de notifica\\u00e7\\u00e3o=%{x}<br>N\\u00b0 de \\u00f3bitos=%{y}\", \"legendgroup\": \"\", \"marker\": {\"color\": \"#636efa\"}, \"name\": \"\", \"offsetgroup\": \"\", \"orientation\": \"v\", \"showlegend\": false, \"textposition\": \"auto\", \"type\": \"bar\", \"x\": [\"2020-04-01T00:00:00\", \"2020-04-03T00:00:00\", \"2020-04-04T00:00:00\", \"2020-04-05T00:00:00\", \"2020-04-10T00:00:00\", \"2020-04-14T00:00:00\", \"2020-04-15T00:00:00\", \"2020-04-16T00:00:00\", \"2020-04-20T00:00:00\", \"2020-04-21T00:00:00\", \"2020-04-22T00:00:00\", \"2020-04-25T00:00:00\", \"2020-04-26T00:00:00\", \"2020-04-28T00:00:00\", \"2020-04-30T00:00:00\", \"2020-05-01T00:00:00\", \"2020-05-02T00:00:00\", \"2020-05-05T00:00:00\", \"2020-05-06T00:00:00\", \"2020-05-07T00:00:00\", \"2020-05-08T00:00:00\", \"2020-05-10T00:00:00\", \"2020-05-11T00:00:00\", 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              "}});\n",
              "\n",
              "// Listen for the removal of the full notebook cells\n",
              "var notebookContainer = gd.closest('#notebook-container');\n",
              "if (notebookContainer) {{\n",
              "    x.observe(notebookContainer, {childList: true});\n",
              "}}\n",
              "\n",
              "// Listen for the clearing of the current output cell\n",
              "var outputEl = gd.closest('.output');\n",
              "if (outputEl) {{\n",
              "    x.observe(outputEl, {childList: true});\n",
              "}}\n",
              "\n",
              "                        })\n",
              "                };\n",
              "                \n",
              "            </script>\n",
              "        </div>\n",
              "</body>\n",
              "</html>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "E1pQtwQFBWUg",
        "colab_type": "text"
      },
      "source": [
        "## Casos ativos\n",
        "\n",
        "*   Gráfico de barras com média móvel\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "```\n",
        "dataframe = classificacdos como \"nao recuperado\" - obtos_por_dia\n",
        "gera: casos_ativos_goiania.csv\n",
        "```\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dH9QM7O-8u7B",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 439
        },
        "outputId": "f4677be5-1daf-4c8e-8541-7d7aa60412d1"
      },
      "source": [
        "nao_recuperados = casos_goiania_cidade\n",
        "nao_recuperados_remove = nao_recuperados.loc[((nao_recuperados['recuperado'] != 'NAO') | (nao_recuperados['municipio'] != 'GOIANIA'))]\n",
        "# df_remove = df.loc[(df['recuperado'] != 'NAO')]\n",
        "\n",
        "nao_recuperados = nao_recuperados.drop(nao_recuperados_remove.index)\n",
        "nao_recuperados.reset_index(level=0, inplace=True)\n",
        "nao_recuperados = nao_recuperados.drop(columns=['index'])\n",
        "nao_recuperados"
      ],
      "execution_count": 162,
      "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_notificacao</th>\n",
              "      <th>data_inicio_sintomas</th>\n",
              "      <th>ano_epi</th>\n",
              "      <th>semana_epi</th>\n",
              "      <th>sexo</th>\n",
              "      <th>raca_cor</th>\n",
              "      <th>faixa_etaria</th>\n",
              "      <th>diabetes</th>\n",
              "      <th>doenca_cardiovascular</th>\n",
              "      <th>doenca_respiratoria</th>\n",
              "      <th>imunossupressao</th>\n",
              "      <th>codigo_ibge</th>\n",
              "      <th>municipio</th>\n",
              "      <th>regiao_saude</th>\n",
              "      <th>recuperado</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>20200909</td>\n",
              "      <td>20200907</td>\n",
              "      <td>2020</td>\n",
              "      <td>37</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>AMARELA</td>\n",
              "      <td>20 a 29 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>NAO</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>20200915</td>\n",
              "      <td>20200914</td>\n",
              "      <td>2020</td>\n",
              "      <td>38</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>PARDA</td>\n",
              "      <td>10 a 14 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>NAO</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>20200909</td>\n",
              "      <td>20200907</td>\n",
              "      <td>2020</td>\n",
              "      <td>37</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>20 a 29 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>NAO</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>20200910</td>\n",
              "      <td>20200908</td>\n",
              "      <td>2020</td>\n",
              "      <td>37</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>15 a 19 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>NAO</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>20200911</td>\n",
              "      <td>20200908</td>\n",
              "      <td>2020</td>\n",
              "      <td>37</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>30 a 39 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>NAO</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2912</th>\n",
              "      <td>20200915</td>\n",
              "      <td>20200912</td>\n",
              "      <td>2020</td>\n",
              "      <td>37</td>\n",
              "      <td>FEMININO</td>\n",
              "      <td>PARDA</td>\n",
              "      <td>40 a 49 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>NAO</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2913</th>\n",
              "      <td>20200914</td>\n",
              "      <td>20200913</td>\n",
              "      <td>2020</td>\n",
              "      <td>38</td>\n",
              "      <td>FEMININO</td>\n",
              "      <td>AMARELA</td>\n",
              "      <td>40 a 49 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>NAO</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2914</th>\n",
              "      <td>20200815</td>\n",
              "      <td>20200802</td>\n",
              "      <td>2020</td>\n",
              "      <td>32</td>\n",
              "      <td>FEMININO</td>\n",
              "      <td>BRANCA</td>\n",
              "      <td>&gt;= 80 anos</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>NAO</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2915</th>\n",
              "      <td>20200812</td>\n",
              "      <td>20200726</td>\n",
              "      <td>2020</td>\n",
              "      <td>31</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>40 a 49 anos</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>NAO</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2916</th>\n",
              "      <td>20200805</td>\n",
              "      <td>20200728</td>\n",
              "      <td>2020</td>\n",
              "      <td>31</td>\n",
              "      <td>FEMININO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>&gt;= 80 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>SIM</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>NAO</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2917 rows × 15 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      data_notificacao  data_inicio_sintomas  ...  regiao_saude  recuperado\n",
              "0             20200909              20200907  ...       CENTRAL         NAO\n",
              "1             20200915              20200914  ...       CENTRAL         NAO\n",
              "2             20200909              20200907  ...       CENTRAL         NAO\n",
              "3             20200910              20200908  ...       CENTRAL         NAO\n",
              "4             20200911              20200908  ...       CENTRAL         NAO\n",
              "...                ...                   ...  ...           ...         ...\n",
              "2912          20200915              20200912  ...       CENTRAL         NAO\n",
              "2913          20200914              20200913  ...       CENTRAL         NAO\n",
              "2914          20200815              20200802  ...       CENTRAL         NAO\n",
              "2915          20200812              20200726  ...       CENTRAL         NAO\n",
              "2916          20200805              20200728  ...       CENTRAL         NAO\n",
              "\n",
              "[2917 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 162
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "tFsZFsuDU5L5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "866a0ba0-76f3-434e-db76-606ca17331dd"
      },
      "source": [
        "nao_recuperados = nao_recuperados['data_notificacao'].value_counts() \n",
        "nao_recuperados = nao_recuperados.to_frame(name='num_casos')\n",
        "nao_recuperados.reset_index(level=0, inplace=True)\n",
        "nao_recuperados.rename(columns={'index': 'data_notificacao'}, inplace = True)\n",
        "nao_recuperados"
      ],
      "execution_count": 163,
      "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",
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              "      <th></th>\n",
              "      <th>data_notificacao</th>\n",
              "      <th>num_casos</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>20200915</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>20200914</td>\n",
              "      <td>198</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>20200909</td>\n",
              "      <td>129</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>20200916</td>\n",
              "      <td>124</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>20200910</td>\n",
              "      <td>123</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>145</th>\n",
              "      <td>20200422</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>146</th>\n",
              "      <td>20200420</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>147</th>\n",
              "      <td>20200416</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>148</th>\n",
              "      <td>20200414</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>149</th>\n",
              "      <td>20200401</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>150 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     data_notificacao  num_casos\n",
              "0            20200915        245\n",
              "1            20200914        198\n",
              "2            20200909        129\n",
              "3            20200916        124\n",
              "4            20200910        123\n",
              "..                ...        ...\n",
              "145          20200422          1\n",
              "146          20200420          1\n",
              "147          20200416          1\n",
              "148          20200414          1\n",
              "149          20200401          1\n",
              "\n",
              "[150 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 163
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "VqV3Zf-DU5MB",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "d08fadc8-b2f1-44cb-eac5-ac3395fd3e34"
      },
      "source": [
        "nao_recuperados['data_notificacao'] = nao_recuperados['data_notificacao'].apply(lambda x: datetime.strptime(str(x), '%Y%m%d').date())\n",
        "\n",
        "nao_recuperados\n"
      ],
      "execution_count": 164,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "        vertical-align: top;\n",
              "    }\n",
              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>data_notificacao</th>\n",
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              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-09-15</td>\n",
              "      <td>245</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-09-14</td>\n",
              "      <td>198</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-09-09</td>\n",
              "      <td>129</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-09-16</td>\n",
              "      <td>124</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-09-10</td>\n",
              "      <td>123</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>145</th>\n",
              "      <td>2020-04-22</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>146</th>\n",
              "      <td>2020-04-20</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>147</th>\n",
              "      <td>2020-04-16</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>148</th>\n",
              "      <td>2020-04-14</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>149</th>\n",
              "      <td>2020-04-01</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>150 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    data_notificacao  num_casos\n",
              "0         2020-09-15        245\n",
              "1         2020-09-14        198\n",
              "2         2020-09-09        129\n",
              "3         2020-09-16        124\n",
              "4         2020-09-10        123\n",
              "..               ...        ...\n",
              "145       2020-04-22          1\n",
              "146       2020-04-20          1\n",
              "147       2020-04-16          1\n",
              "148       2020-04-14          1\n",
              "149       2020-04-01          1\n",
              "\n",
              "[150 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 164
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6W-acXaAD09T",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 439
        },
        "outputId": "588e3677-8976-4db3-8591-059c95e84551"
      },
      "source": [
        "obitos_por_dia = pd.read_csv('http://datasets.saude.go.gov.br/coronavirus/obitos_confirmados.csv', sep=';')\n",
        "obitos_por_dia_remove = obitos_por_dia.loc[((obitos_por_dia['municipio'] != 'GOIANIA'))]\n",
        "\n",
        "obitos_por_dia = obitos_por_dia.drop(obitos_por_dia_remove.index)\n",
        "obitos_por_dia.reset_index(level=0, inplace=True)\n",
        "obitos_por_dia = obitos_por_dia.drop(columns=['index'])\n",
        "\n",
        "obitos_por_dia"
      ],
      "execution_count": 6,
      "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_notificacao</th>\n",
              "      <th>data_inicio_sintomas</th>\n",
              "      <th>ano_epi</th>\n",
              "      <th>semana_epi</th>\n",
              "      <th>sexo</th>\n",
              "      <th>raca_cor</th>\n",
              "      <th>faixa_etaria</th>\n",
              "      <th>diabetes</th>\n",
              "      <th>doenca_cardiovascular</th>\n",
              "      <th>doenca_respiratoria</th>\n",
              "      <th>imunossupressao</th>\n",
              "      <th>codigo_ibge</th>\n",
              "      <th>municipio</th>\n",
              "      <th>regiao_saude</th>\n",
              "      <th>data_obito</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>20200901</td>\n",
              "      <td>20200801</td>\n",
              "      <td>2020</td>\n",
              "      <td>31</td>\n",
              "      <td>FEMININO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>60 a 69 anos</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>20200905</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>20200629</td>\n",
              "      <td>20200618</td>\n",
              "      <td>2020</td>\n",
              "      <td>25</td>\n",
              "      <td>FEMININO</td>\n",
              "      <td>BRANCA</td>\n",
              "      <td>&gt;= 80 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>SIM</td>\n",
              "      <td>SIM</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>20200702</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>20200806</td>\n",
              "      <td>20200802</td>\n",
              "      <td>2020</td>\n",
              "      <td>32</td>\n",
              "      <td>FEMININO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>60 a 69 anos</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>20200809</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>20200715</td>\n",
              "      <td>20200627</td>\n",
              "      <td>2020</td>\n",
              "      <td>26</td>\n",
              "      <td>FEMININO</td>\n",
              "      <td>PARDA</td>\n",
              "      <td>50 a 59 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>SIM</td>\n",
              "      <td>SIM</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>20200709</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>20200803</td>\n",
              "      <td>20200731</td>\n",
              "      <td>2020</td>\n",
              "      <td>31</td>\n",
              "      <td>FEMININO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>60 a 69 anos</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>20200813</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1191</th>\n",
              "      <td>20200811</td>\n",
              "      <td>20200801</td>\n",
              "      <td>2020</td>\n",
              "      <td>31</td>\n",
              "      <td>FEMININO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>70 a 79  anos</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>SIM</td>\n",
              "      <td>SIM</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>20200822</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1192</th>\n",
              "      <td>20200613</td>\n",
              "      <td>20200606</td>\n",
              "      <td>2020</td>\n",
              "      <td>23</td>\n",
              "      <td>FEMININO</td>\n",
              "      <td>PRETA</td>\n",
              "      <td>50 a 59 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>SIM</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>20200629</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1193</th>\n",
              "      <td>20200812</td>\n",
              "      <td>20200625</td>\n",
              "      <td>2020</td>\n",
              "      <td>26</td>\n",
              "      <td>FEMININO</td>\n",
              "      <td>PRETA</td>\n",
              "      <td>70 a 79  anos</td>\n",
              "      <td>SIM</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>20200708</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1194</th>\n",
              "      <td>20200715</td>\n",
              "      <td>20200710</td>\n",
              "      <td>2020</td>\n",
              "      <td>28</td>\n",
              "      <td>FEMININO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>70 a 79  anos</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>20200714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1195</th>\n",
              "      <td>20200810</td>\n",
              "      <td>20200804</td>\n",
              "      <td>2020</td>\n",
              "      <td>32</td>\n",
              "      <td>FEMININO</td>\n",
              "      <td>PARDA</td>\n",
              "      <td>50 a 59 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>SIM</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>20200824</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1196 rows × 15 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      data_notificacao  data_inicio_sintomas  ...  regiao_saude  data_obito\n",
              "0             20200901              20200801  ...       CENTRAL    20200905\n",
              "1             20200629              20200618  ...       CENTRAL    20200702\n",
              "2             20200806              20200802  ...       CENTRAL    20200809\n",
              "3             20200715              20200627  ...       CENTRAL    20200709\n",
              "4             20200803              20200731  ...       CENTRAL    20200813\n",
              "...                ...                   ...  ...           ...         ...\n",
              "1191          20200811              20200801  ...       CENTRAL    20200822\n",
              "1192          20200613              20200606  ...       CENTRAL    20200629\n",
              "1193          20200812              20200625  ...       CENTRAL    20200708\n",
              "1194          20200715              20200710  ...       CENTRAL    20200714\n",
              "1195          20200810              20200804  ...       CENTRAL    20200824\n",
              "\n",
              "[1196 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "5u-wz5WAUMmv",
        "colab": {}
      },
      "source": [
        "obitos_por_dia = obitos_por_dia['data_notificacao'].value_counts() \n",
        "obitos_por_dia = obitos_por_dia.to_frame(name='num_casos')\n",
        "obitos_por_dia.reset_index(level=0, inplace=True)\n",
        "obitos_por_dia.rename(columns={'index': 'data_notificacao'}, inplace = True)\n",
        "obitos_por_dia"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "EShsPmhsUMmz",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "49effa56-d4f1-47b6-8b89-2fcdccdc5fb9"
      },
      "source": [
        "obitos_por_dia['data_notificacao'] = obitos_por_dia['data_notificacao'].apply(lambda x: datetime.strptime(str(x), '%Y%m%d').date())\n",
        "\n",
        "obitos_por_dia\n"
      ],
      "execution_count": 8,
      "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",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>data_notificacao</th>\n",
              "      <th>num_casos</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-07-31</td>\n",
              "      <td>33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-08-05</td>\n",
              "      <td>25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-08-03</td>\n",
              "      <td>24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-09-01</td>\n",
              "      <td>22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-08-26</td>\n",
              "      <td>21</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>141</th>\n",
              "      <td>2020-05-12</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>142</th>\n",
              "      <td>2020-05-14</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>143</th>\n",
              "      <td>2020-05-16</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>144</th>\n",
              "      <td>2020-06-09</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>145</th>\n",
              "      <td>2020-04-01</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>146 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    data_notificacao  num_casos\n",
              "0         2020-07-31         33\n",
              "1         2020-08-05         25\n",
              "2         2020-08-03         24\n",
              "3         2020-09-01         22\n",
              "4         2020-08-26         21\n",
              "..               ...        ...\n",
              "141       2020-05-12          1\n",
              "142       2020-05-14          1\n",
              "143       2020-05-16          1\n",
              "144       2020-06-09          1\n",
              "145       2020-04-01          1\n",
              "\n",
              "[146 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "zdNG1O1aVJRT",
        "colab": {}
      },
      "source": [
        "faltantes = []\n",
        "casos_ativos = {}\n",
        "\n",
        "k = 0\n",
        "for i, linha_ob in obitos_por_dia.iterrows():\n",
        "    # print(linha_ob['data_notificacao'])\n",
        "    for j, linha_nao_rec in nao_recuperados.iterrows():\n",
        "        if linha_ob['data_notificacao'] == linha_nao_rec['data_notificacao']:\n",
        "            num= linha_nao_rec['num_casos'] - linha_ob['num_casos']\n",
        "            casos_ativos[k] = {'data': linha_nao_rec['data_notificacao'], 'num_casos': num}\n",
        "            faltantes.append(j)\n",
        "            k+=1\n",
        "            break\n"
      ],
      "execution_count": 165,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "OyrvJ49xVJRW",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 111
        },
        "outputId": "248d65e3-35da-45e4-f39e-89bd87ba8359"
      },
      "source": [
        "casos_ativos=pd.DataFrame(data=casos_ativos)\n",
        "casos_ativos= casos_ativos.T\n",
        "casos_ativos.reset_index(level=0, inplace=True)\n",
        "casos_ativos.drop(columns=['index'], inplace = True)\n",
        "casos_ativos.head(2)"
      ],
      "execution_count": 166,
      "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>num_casos</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-07-31</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-08-05</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         data num_casos\n",
              "0  2020-07-31         5\n",
              "1  2020-08-05         3"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 166
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Kp4GCqVJVDZB",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 173
        },
        "outputId": "a743174d-0fd1-481e-8a74-68cae847fad6"
      },
      "source": [
        "nao_recuperados =nao_recuperados.drop(indices)\n",
        "nao_recuperados.reset_index(level=0, inplace=True)\n",
        "nao_recuperados.drop(columns=['index'], inplace = True)\n",
        "nao_recuperados"
      ],
      "execution_count": 167,
      "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_notificacao</th>\n",
              "      <th>num_casos</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-09-17</td>\n",
              "      <td>93</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-09-13</td>\n",
              "      <td>56</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-09-07</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-04-24</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  data_notificacao  num_casos\n",
              "0       2020-09-17         93\n",
              "1       2020-09-13         56\n",
              "2       2020-09-07         13\n",
              "3       2020-04-24          1"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 167
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tSCBtPwSVDP0",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "casos_ativos = casos_ativos.to_dict('dict')\n",
        "nao_recuperados = nao_recuperados.to_dict('dict')"
      ],
      "execution_count": 168,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YzjvEzSvbsPN",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "ativos = {}\n",
        "\n",
        "j= 0\n",
        "for i in range(len(casos_ativos['num_casos'])):\n",
        "    ativos[j] = {'data_notificacao': casos_ativosT['data'][i], 'num_casos': casos_ativosT['num_casos'][i]}\n",
        "    j+=1\n",
        "\n",
        "for i in range(len(nao_recuperados['num_casos'])):\n",
        "    ativos[j] = {'data_notificacao': nao_recuperados['data_notificacao'][i], 'num_casos': nao_recuperados['num_casos'][i]}\n",
        "    j+=1\n",
        "\n"
      ],
      "execution_count": 169,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vN87y_5Og8qO",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "f94b2c47-9507-4372-b222-ad4faa546e8d"
      },
      "source": [
        "casos_ativos_goiania = pd.DataFrame(ativos)\n",
        "casos_ativos_goiania = casos_ativos_goiania.T\n",
        "casos_ativos_goiania"
      ],
      "execution_count": 172,
      "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_notificacao</th>\n",
              "      <th>num_casos</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-07-31</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-08-05</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-08-03</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-09-01</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-08-26</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>145</th>\n",
              "      <td>2020-04-01</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>146</th>\n",
              "      <td>2020-09-17</td>\n",
              "      <td>93</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>147</th>\n",
              "      <td>2020-09-13</td>\n",
              "      <td>56</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>148</th>\n",
              "      <td>2020-09-07</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>149</th>\n",
              "      <td>2020-04-24</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>150 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    data_notificacao num_casos\n",
              "0         2020-07-31         5\n",
              "1         2020-08-05         3\n",
              "2         2020-08-03         9\n",
              "3         2020-09-01        13\n",
              "4         2020-08-26        15\n",
              "..               ...       ...\n",
              "145       2020-04-01         0\n",
              "146       2020-09-17        93\n",
              "147       2020-09-13        56\n",
              "148       2020-09-07        13\n",
              "149       2020-04-24         1\n",
              "\n",
              "[150 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 172
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lAV3OK_Kby2W",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "4d18d25b-d802-4d5e-9fe3-a71d942b2afd"
      },
      "source": [
        "sum(casos_ativos_goiania['num_casos'])"
      ],
      "execution_count": 175,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1721"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 175
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "gbOmA1IoUMm2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "6e0ef6a0-14ab-485f-8867-ebc5f927143c"
      },
      "source": [
        "casos_ativos_goiania['data_notificacao'] = pd.to_datetime(casos_ativos_goiania['data_notificacao'])\n",
        "\n",
        "# Ordena pela data e salva em um novo DataFrame\n",
        "casos_ativos_goiania = casos_ativos_goiania.sort_values(by='data_notificacao')\n",
        "casos_ativos_goiania"
      ],
      "execution_count": 176,
      "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",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>data_notificacao</th>\n",
              "      <th>num_casos</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>145</th>\n",
              "      <td>2020-04-01</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>132</th>\n",
              "      <td>2020-04-03</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>120</th>\n",
              "      <td>2020-04-04</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>116</th>\n",
              "      <td>2020-04-05</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>133</th>\n",
              "      <td>2020-04-10</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>107</th>\n",
              "      <td>2020-09-14</td>\n",
              "      <td>195</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>113</th>\n",
              "      <td>2020-09-15</td>\n",
              "      <td>242</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>123</th>\n",
              "      <td>2020-09-16</td>\n",
              "      <td>122</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>146</th>\n",
              "      <td>2020-09-17</td>\n",
              "      <td>93</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>134</th>\n",
              "      <td>2020-09-18</td>\n",
              "      <td>104</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>150 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    data_notificacao num_casos\n",
              "145       2020-04-01         0\n",
              "132       2020-04-03         0\n",
              "120       2020-04-04         0\n",
              "116       2020-04-05         0\n",
              "133       2020-04-10         0\n",
              "..               ...       ...\n",
              "107       2020-09-14       195\n",
              "113       2020-09-15       242\n",
              "123       2020-09-16       122\n",
              "146       2020-09-17        93\n",
              "134       2020-09-18       104\n",
              "\n",
              "[150 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 176
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cBnLjx7PKyE_",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "af3e84b8-87ec-4720-d5b8-6ca708b0de7b"
      },
      "source": [
        "casos_ativos_goiania.to_csv('casos_ativos_goiania.csv', index=False)\n",
        "casos_ativos_goiania\n"
      ],
      "execution_count": 177,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>data_notificacao</th>\n",
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              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>145</th>\n",
              "      <td>2020-04-01</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>132</th>\n",
              "      <td>2020-04-03</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>120</th>\n",
              "      <td>2020-04-04</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>116</th>\n",
              "      <td>2020-04-05</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>133</th>\n",
              "      <td>2020-04-10</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>107</th>\n",
              "      <td>2020-09-14</td>\n",
              "      <td>195</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>113</th>\n",
              "      <td>2020-09-15</td>\n",
              "      <td>242</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>123</th>\n",
              "      <td>2020-09-16</td>\n",
              "      <td>122</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>146</th>\n",
              "      <td>2020-09-17</td>\n",
              "      <td>93</td>\n",
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              "    <tr>\n",
              "      <th>134</th>\n",
              "      <td>2020-09-18</td>\n",
              "      <td>104</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>150 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    data_notificacao num_casos\n",
              "145       2020-04-01         0\n",
              "132       2020-04-03         0\n",
              "120       2020-04-04         0\n",
              "116       2020-04-05         0\n",
              "133       2020-04-10         0\n",
              "..               ...       ...\n",
              "107       2020-09-14       195\n",
              "113       2020-09-15       242\n",
              "123       2020-09-16       122\n",
              "146       2020-09-17        93\n",
              "134       2020-09-18       104\n",
              "\n",
              "[150 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 177
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nfdlBVpgLF-w",
        "colab_type": "text"
      },
      "source": [
        "### Média móvel - ativos"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "idWtiR-sLTvJ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "casos_ativos_goiania = pd.read_csv('casos_ativos_goiania.csv', sep=',')"
      ],
      "execution_count": 178,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MOUIInoiLIXm",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "outputId": "9160fc13-fbc3-4c74-b928-97ef832cc055"
      },
      "source": [
        "df = casos_ativos_goiania\n",
        "for i in range(0,df.shape[0]-6):\n",
        "    df.loc[df.index[i+6],'MM_casos'] = np.round(((df.iloc[i,1]+\n",
        "                                                  df.iloc[i+1,1]+\n",
        "                                                  df.iloc[i+2,1]+\n",
        "                                                  df.iloc[i+3,1]+\n",
        "                                                  df.iloc[i+4,1]+\n",
        "                                                  df.iloc[i+5,1]+\n",
        "                                                  df.iloc[i+6,1])/7),1)           \n",
        "\n",
        "df.head"
      ],
      "execution_count": 179,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>data_notificacao</th>\n",
              "      <th>num_casos</th>\n",
              "      <th>MM_casos</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-04-01</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-04-03</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-04-04</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-04-05</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-04-10</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2020-04-14</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2020-04-15</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2020-04-16</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  data_notificacao  num_casos  MM_casos\n",
              "0       2020-04-01          0       NaN\n",
              "1       2020-04-03          0       NaN\n",
              "2       2020-04-04          0       NaN\n",
              "3       2020-04-05          0       NaN\n",
              "4       2020-04-10          0       NaN\n",
              "5       2020-04-14          0       NaN\n",
              "6       2020-04-15          0       0.0\n",
              "7       2020-04-16          0       0.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 179
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6kVJnZDgTq9r",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "casos_ativos_goiania.to_csv('casos_ativos_goiania.csv', index=False)"
      ],
      "execution_count": 180,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GJYBK1N7Tn8u",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "outputId": "2d73fc9a-a177-4f30-cd0c-4a858e6687e6"
      },
      "source": [
        "fig = px.bar(casos_ativos_goiania, x='data_notificacao', y='num_casos', labels={'num_casos':'N° de casos ativos', 'data_notificacao': 'Data de notificação'})\n",
        "\n",
        "fig.add_trace(\n",
        "    go.Scatter(\n",
        "        x=casos_ativos_goiania['data_notificacao'],\n",
        "        y=casos_ativos_goiania['MM_casos'],\n",
        "        name='Média Móvel<br>(7 dias)',        \n",
        "        hovertemplate= \"Média Móvel: %{x}<br>Data: %{y}<extra></extra>\",\n",
        "\n",
        "    ))\n",
        "\n",
        "fig.update()"
      ],
      "execution_count": 181,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
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              "                \n",
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      "cell_type": "markdown",
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      "source": [
        "## Casos por dia\n",
        "\n",
        "*   Gráfico de barras com média móvel\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "```\n",
        "dataframe: casos_por_dia\n",
        "gera: casos_por_dia_goiania.csv\n",
        "```\n"
      ]
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        "casos_por_dia = casos_goiania_cidade\n",
        "casos_por_dia_remove = casos_por_dia.loc[((casos_por_dia['municipio'] != 'GOIANIA'))]\n",
        "# df_remove = df.loc[(df['recuperado'] != 'NAO')]\n",
        "\n",
        "casos_por_dia = casos_por_dia.drop(casos_por_dia_remove.index)\n",
        "casos_por_dia"
      ],
      "execution_count": null,
      "outputs": [
        {
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              "      <th>raca_cor</th>\n",
              "      <th>faixa_etaria</th>\n",
              "      <th>diabetes</th>\n",
              "      <th>doenca_cardiovascular</th>\n",
              "      <th>doenca_respiratoria</th>\n",
              "      <th>imunossupressao</th>\n",
              "      <th>codigo_ibge</th>\n",
              "      <th>municipio</th>\n",
              "      <th>regiao_saude</th>\n",
              "      <th>recuperado</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>20200722</td>\n",
              "      <td>20200722</td>\n",
              "      <td>2020</td>\n",
              "      <td>30</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>PARDA</td>\n",
              "      <td>70 a 79  anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>SIM</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>20200824</td>\n",
              "      <td>20200818</td>\n",
              "      <td>2020</td>\n",
              "      <td>34</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>PRETA</td>\n",
              "      <td>50 a 59 anos</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>SIM</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>20200623</td>\n",
              "      <td>20200607</td>\n",
              "      <td>2020</td>\n",
              "      <td>24</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>BRANCA</td>\n",
              "      <td>30 a 39 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>SIM</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>20200622</td>\n",
              "      <td>20200607</td>\n",
              "      <td>2020</td>\n",
              "      <td>24</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>BRANCA</td>\n",
              "      <td>20 a 29 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>SIM</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>20200910</td>\n",
              "      <td>20200906</td>\n",
              "      <td>2020</td>\n",
              "      <td>37</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>BRANCA</td>\n",
              "      <td>60 a 69 anos</td>\n",
              "      <td>SIM</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>NAO</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>183327</th>\n",
              "      <td>20200805</td>\n",
              "      <td>20200729</td>\n",
              "      <td>2020</td>\n",
              "      <td>31</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>BRANCA</td>\n",
              "      <td>60 a 69 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>SIM</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>SIM</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>183332</th>\n",
              "      <td>20200825</td>\n",
              "      <td>20200820</td>\n",
              "      <td>2020</td>\n",
              "      <td>34</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>BRANCA</td>\n",
              "      <td>30 a 39 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>SIM</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>183334</th>\n",
              "      <td>20200804</td>\n",
              "      <td>20200729</td>\n",
              "      <td>2020</td>\n",
              "      <td>31</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>AMARELA</td>\n",
              "      <td>70 a 79  anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>SIM</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>183336</th>\n",
              "      <td>20200514</td>\n",
              "      <td>20200512</td>\n",
              "      <td>2020</td>\n",
              "      <td>20</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>PARDA</td>\n",
              "      <td>&gt;= 80 anos</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>SIM</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>SIM</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>183347</th>\n",
              "      <td>20200613</td>\n",
              "      <td>20200601</td>\n",
              "      <td>2020</td>\n",
              "      <td>23</td>\n",
              "      <td>MASCULINO</td>\n",
              "      <td>IGNORADO</td>\n",
              "      <td>60 a 69 anos</td>\n",
              "      <td>SIM</td>\n",
              "      <td>SIM</td>\n",
              "      <td>NAO</td>\n",
              "      <td>NAO</td>\n",
              "      <td>520870</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>CENTRAL</td>\n",
              "      <td>SIM</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>47468 rows × 15 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "        data_notificacao  data_inicio_sintomas  ...  regiao_saude  recuperado\n",
              "0               20200722              20200722  ...       CENTRAL         SIM\n",
              "5               20200824              20200818  ...       CENTRAL         SIM\n",
              "6               20200623              20200607  ...       CENTRAL         SIM\n",
              "7               20200622              20200607  ...       CENTRAL         SIM\n",
              "19              20200910              20200906  ...       CENTRAL         NAO\n",
              "...                  ...                   ...  ...           ...         ...\n",
              "183327          20200805              20200729  ...       CENTRAL         SIM\n",
              "183332          20200825              20200820  ...       CENTRAL         SIM\n",
              "183334          20200804              20200729  ...       CENTRAL         SIM\n",
              "183336          20200514              20200512  ...       CENTRAL         SIM\n",
              "183347          20200613              20200601  ...       CENTRAL         SIM\n",
              "\n",
              "[47468 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 715
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hA6oGq4CWORK",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "d4f2b777-1849-4c47-8bdd-43b6cd56df98"
      },
      "source": [
        "casos_por_dia = casos_por_dia['data_notificacao'].value_counts() \n",
        "casos_por_dia = casos_por_dia.to_frame(name='num_casos')\n",
        "casos_por_dia.reset_index(level=0, inplace=True)\n",
        "casos_por_dia.rename(columns={'index': 'data_notificacao'}, inplace = True)\n",
        "casos_por_dia"
      ],
      "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",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>data_notificacao</th>\n",
              "      <th>num_casos</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>20200812</td>\n",
              "      <td>1195</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>20200811</td>\n",
              "      <td>1072</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>20200817</td>\n",
              "      <td>1042</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>20200813</td>\n",
              "      <td>996</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>20200804</td>\n",
              "      <td>977</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>186</th>\n",
              "      <td>20200314</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>187</th>\n",
              "      <td>20200310</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>188</th>\n",
              "      <td>20200313</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>189</th>\n",
              "      <td>20200311</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>190</th>\n",
              "      <td>20200301</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>191 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     data_notificacao  num_casos\n",
              "0            20200812       1195\n",
              "1            20200811       1072\n",
              "2            20200817       1042\n",
              "3            20200813        996\n",
              "4            20200804        977\n",
              "..                ...        ...\n",
              "186          20200314          1\n",
              "187          20200310          1\n",
              "188          20200313          1\n",
              "189          20200311          1\n",
              "190          20200301          1\n",
              "\n",
              "[191 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 716
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Vu0m24XpWc-x",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "24a6273d-0325-4030-da86-ba9b2fce79b4"
      },
      "source": [
        "casos_por_dia['data_notificacao'] = casos_por_dia['data_notificacao'].apply(lambda x: datetime.strptime(str(x), '%Y%m%d').date())\n",
        "\n",
        "casos_por_dia\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>data_notificacao</th>\n",
              "      <th>num_casos</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-08-12</td>\n",
              "      <td>1195</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-08-11</td>\n",
              "      <td>1072</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-08-17</td>\n",
              "      <td>1042</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-08-13</td>\n",
              "      <td>996</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-08-04</td>\n",
              "      <td>977</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>186</th>\n",
              "      <td>2020-03-14</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>187</th>\n",
              "      <td>2020-03-10</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>188</th>\n",
              "      <td>2020-03-13</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>189</th>\n",
              "      <td>2020-03-11</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>190</th>\n",
              "      <td>2020-03-01</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>191 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    data_notificacao  num_casos\n",
              "0         2020-08-12       1195\n",
              "1         2020-08-11       1072\n",
              "2         2020-08-17       1042\n",
              "3         2020-08-13        996\n",
              "4         2020-08-04        977\n",
              "..               ...        ...\n",
              "186       2020-03-14          1\n",
              "187       2020-03-10          1\n",
              "188       2020-03-13          1\n",
              "189       2020-03-11          1\n",
              "190       2020-03-01          1\n",
              "\n",
              "[191 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 717
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "q5wGx2adXsCt",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "46d38e23-32b6-4948-d834-63ade1d4090c"
      },
      "source": [
        "casos_por_dia['data_notificacao'] = pd.to_datetime(casos_por_dia['data_notificacao'])\n",
        "\n",
        "# Ordena pela data e salva em um novo DataFrame\n",
        "casos_por_dia = casos_por_dia.sort_values(by='data_notificacao')\n",
        "casos_por_dia"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>data_notificacao</th>\n",
              "      <th>num_casos</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>190</th>\n",
              "      <td>2020-03-01</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>187</th>\n",
              "      <td>2020-03-10</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>189</th>\n",
              "      <td>2020-03-11</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>188</th>\n",
              "      <td>2020-03-13</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>186</th>\n",
              "      <td>2020-03-14</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2020-09-14</td>\n",
              "      <td>947</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2020-09-15</td>\n",
              "      <td>942</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>2020-09-16</td>\n",
              "      <td>467</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53</th>\n",
              "      <td>2020-09-17</td>\n",
              "      <td>358</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>107</th>\n",
              "      <td>2020-09-18</td>\n",
              "      <td>113</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>191 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    data_notificacao  num_casos\n",
              "190       2020-03-01          1\n",
              "187       2020-03-10          1\n",
              "189       2020-03-11          1\n",
              "188       2020-03-13          1\n",
              "186       2020-03-14          1\n",
              "..               ...        ...\n",
              "5         2020-09-14        947\n",
              "6         2020-09-15        942\n",
              "42        2020-09-16        467\n",
              "53        2020-09-17        358\n",
              "107       2020-09-18        113\n",
              "\n",
              "[191 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 718
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bCfAO8klZrQx",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "b243cee7-3bc5-4934-e322-cb753d6090a2"
      },
      "source": [
        "casos_por_dia.to_csv('casos_por_dia_goiania.csv', index=False)\n",
        "casos_por_dia"
      ],
      "execution_count": 759,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>data_notificacao</th>\n",
              "      <th>num_casos</th>\n",
              "      <th>MM_casos</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
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              "      <th>190</th>\n",
              "      <td>2020-03-01</td>\n",
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              "      <th>5</th>\n",
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              "      <td>947</td>\n",
              "      <td>539.1</td>\n",
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              "      <th>6</th>\n",
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              "      <td>942</td>\n",
              "      <td>600.6</td>\n",
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              "      <th>42</th>\n",
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              "      <td>573.7</td>\n",
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              "    <tr>\n",
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              "      <td>113</td>\n",
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              "<p>191 rows × 3 columns</p>\n",
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            ],
            "text/plain": [
              "    data_notificacao  num_casos  MM_casos\n",
              "190       2020-03-01          1       NaN\n",
              "187       2020-03-10          1       NaN\n",
              "189       2020-03-11          1       NaN\n",
              "188       2020-03-13          1       NaN\n",
              "186       2020-03-14          1       NaN\n",
              "..               ...        ...       ...\n",
              "5         2020-09-14        947     539.1\n",
              "6         2020-09-15        942     600.6\n",
              "42        2020-09-16        467     595.4\n",
              "53        2020-09-17        358     573.7\n",
              "107       2020-09-18        113     515.0\n",
              "\n",
              "[191 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 759
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "YZtIdV6TZlR5"
      },
      "source": [
        "### Média móvel - casos confirmados por dia"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "E6U-adpYZlR6",
        "colab": {}
      },
      "source": [
        "# casos_ativos_goiania = pd.read_csv('casos_ativos_goiania.csv', sep=',')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "Q4jJ6OwuZlR9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "outputId": "cef086df-227f-4ac0-c283-0eb6d882a183"
      },
      "source": [
        "df = casos_por_dia\n",
        "for i in range(0,df.shape[0]-6):\n",
        "    df.loc[df.index[i+6],'MM_casos'] = np.round(((df.iloc[i,1]+\n",
        "                                                  df.iloc[i+1,1]+\n",
        "                                                  df.iloc[i+2,1]+\n",
        "                                                  df.iloc[i+3,1]+\n",
        "                                                  df.iloc[i+4,1]+\n",
        "                                                  df.iloc[i+5,1]+\n",
        "                                                  df.iloc[i+6,1])/7),1)           \n",
        "\n",
        "df.head(8)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>data_notificacao</th>\n",
              "      <th>num_casos</th>\n",
              "      <th>MM_casos</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>190</th>\n",
              "      <td>2020-03-01</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>187</th>\n",
              "      <td>2020-03-10</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>189</th>\n",
              "      <td>2020-03-11</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>188</th>\n",
              "      <td>2020-03-13</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>186</th>\n",
              "      <td>2020-03-14</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>178</th>\n",
              "      <td>2020-03-15</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>176</th>\n",
              "      <td>2020-03-16</td>\n",
              "      <td>4</td>\n",
              "      <td>1.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>184</th>\n",
              "      <td>2020-03-17</td>\n",
              "      <td>1</td>\n",
              "      <td>1.6</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    data_notificacao  num_casos  MM_casos\n",
              "190       2020-03-01          1       NaN\n",
              "187       2020-03-10          1       NaN\n",
              "189       2020-03-11          1       NaN\n",
              "188       2020-03-13          1       NaN\n",
              "186       2020-03-14          1       NaN\n",
              "178       2020-03-15          2       NaN\n",
              "176       2020-03-16          4       1.6\n",
              "184       2020-03-17          1       1.6"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 720
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "vYOSe4W1ZlSC",
        "colab": {}
      },
      "source": [
        "casos_por_dia.to_csv('casos_ativos_goiania.csv', index=False)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "yJTfvmiqZlSH",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "outputId": "12acde19-d541-4834-a247-f3e93db9f1bf"
      },
      "source": [
        "fig = px.bar(casos_por_dia, x='data_notificacao', y='num_casos', labels={'num_casos':'N° de casos confirmados', \n",
        "                                                                         'data_notificacao': 'Data de notificação',})\n",
        "\n",
        "fig.add_trace(\n",
        "    go.Scatter(\n",
        "        x=casos_por_dia['data_notificacao'],\n",
        "        y=casos_por_dia['MM_casos'],\n",
        "        name='Média Móvel<br>(7 dias)',        \n",
        "        hovertemplate= \"Média Móvel: %{x}<br>Data: %{y}<extra></extra>\",\n",
        "\n",
        "    ))\n",
        "\n",
        "fig.update_traces()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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              "                        })\n",
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              "        </div>\n",
              "</body>\n",
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          },
          "metadata": {
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    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "RGXRmikKuuxr"
      },
      "source": [
        "## Casos acumulados por dia\n",
        "\n",
        "*   Gráfico de barras com média móvel\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "```\n",
        "dataframe: casos_goiania_cidade\n",
        "gera: casos_acumulados_por_dia_goiania.csv\n",
        "```\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "NMVVnOIauuxs",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "0333fb6e-60df-4ae6-dbf3-feb44b50e7d6"
      },
      "source": [
        "casos_acumulados = pd.read_csv('casos_por_dia_goiania.csv', sep=',')\n",
        "casos_acumulados = casos_acumulados.drop(columns=['MM_casos'])\n",
        "casos_acumulados"
      ],
      "execution_count": 819,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>data_notificacao</th>\n",
              "      <th>num_casos</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-03-01</td>\n",
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              "      <td>2020-03-10</td>\n",
              "      <td>1</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-03-11</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-03-13</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-03-14</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>186</th>\n",
              "      <td>2020-09-14</td>\n",
              "      <td>947</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>187</th>\n",
              "      <td>2020-09-15</td>\n",
              "      <td>942</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>188</th>\n",
              "      <td>2020-09-16</td>\n",
              "      <td>467</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>189</th>\n",
              "      <td>2020-09-17</td>\n",
              "      <td>358</td>\n",
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              "    <tr>\n",
              "      <th>190</th>\n",
              "      <td>2020-09-18</td>\n",
              "      <td>113</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>191 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    data_notificacao  num_casos\n",
              "0         2020-03-01          1\n",
              "1         2020-03-10          1\n",
              "2         2020-03-11          1\n",
              "3         2020-03-13          1\n",
              "4         2020-03-14          1\n",
              "..               ...        ...\n",
              "186       2020-09-14        947\n",
              "187       2020-09-15        942\n",
              "188       2020-09-16        467\n",
              "189       2020-09-17        358\n",
              "190       2020-09-18        113\n",
              "\n",
              "[191 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 819
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XuLO9LgSyQaf",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "e3030f5f-51c2-4cb3-817b-b0ba8c24d604"
      },
      "source": [
        "casos_acumulados['acumulado'] = casos_acumulados['num_casos'].cumsum()\n",
        "casos_acumulados"
      ],
      "execution_count": 820,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>data_notificacao</th>\n",
              "      <th>num_casos</th>\n",
              "      <th>acumulado</th>\n",
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              "      <th>2</th>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-03-13</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-03-14</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>186</th>\n",
              "      <td>2020-09-14</td>\n",
              "      <td>947</td>\n",
              "      <td>45588</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>187</th>\n",
              "      <td>2020-09-15</td>\n",
              "      <td>942</td>\n",
              "      <td>46530</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>188</th>\n",
              "      <td>2020-09-16</td>\n",
              "      <td>467</td>\n",
              "      <td>46997</td>\n",
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              "    <tr>\n",
              "      <th>189</th>\n",
              "      <td>2020-09-17</td>\n",
              "      <td>358</td>\n",
              "      <td>47355</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>190</th>\n",
              "      <td>2020-09-18</td>\n",
              "      <td>113</td>\n",
              "      <td>47468</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>191 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    data_notificacao  num_casos  acumulado\n",
              "0         2020-03-01          1          1\n",
              "1         2020-03-10          1          2\n",
              "2         2020-03-11          1          3\n",
              "3         2020-03-13          1          4\n",
              "4         2020-03-14          1          5\n",
              "..               ...        ...        ...\n",
              "186       2020-09-14        947      45588\n",
              "187       2020-09-15        942      46530\n",
              "188       2020-09-16        467      46997\n",
              "189       2020-09-17        358      47355\n",
              "190       2020-09-18        113      47468\n",
              "\n",
              "[191 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 820
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "VvmF6Ij2uux3",
        "colab": {}
      },
      "source": [
        "casos_acumulados.to_csv('casos_acumulados_por_dia_goiania.csv', index=False)\n"
      ],
      "execution_count": 821,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "BQMK3wqmuux6"
      },
      "source": [
        "### Média móvel - casos confirmados por dia"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "B_L0Bpckuux6",
        "colab": {}
      },
      "source": [
        "# casos_ativos_goiania = pd.read_csv('casos_ativos_goiania.csv', sep=',')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "e4Mas1YvuuyJ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "outputId": "351d61fb-545a-4e7a-ee63-bbd25176a9ae"
      },
      "source": [
        "fig = px.bar(casos_acumulados, x='data_notificacao', y='acumulado', labels={'acumulado':'N° de casos confirmados', \n",
        "                                                                         'data_notificacao': 'Data de notificação',})\n",
        "\n",
        "\n",
        "fig.update_traces()"
      ],
      "execution_count": 823,
      "outputs": [
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          "metadata": {
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    {
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      "source": [
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      "execution_count": null,
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}