RefazerPython3.ipynb

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        "<a href=\"https://colab.research.google.com/github/VitorPio7/AnimaCursoDeExtensaoPythonPanda2023/blob/main/RefazerPython3.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "source": [
        "# Importando biblioteca pandas no Python\n",
        "import pandas as pd"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "combustiveis_df = pd.read_excel(\"ca-2021-02.xlsx\")\n",
        "display(combustiveis_df.head())"
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              "  Regiao - Sigla Estado - Sigla  Municipio               Revenda  \\\n",
              "0             NE             AL  ARAPIRACA  POSTO ARAPIRACA LTDA   \n",
              "1             NE             AL  ARAPIRACA  POSTO ARAPIRACA LTDA   \n",
              "2             NE             AL  ARAPIRACA  POSTO ARAPIRACA LTDA   \n",
              "3             NE             AL  ARAPIRACA  POSTO ARAPIRACA LTDA   \n",
              "4             NE             AL  ARAPIRACA  POSTO ARAPIRACA LTDA   \n",
              "\n",
              "       CNPJ da Revenda     Nome da Rua Numero Rua Complemento       Bairro  \\\n",
              "0   12.451.076/0004-65  RODOVIA AL 220        105       KM 68  CANAFISTULA   \n",
              "1   12.451.076/0004-65  RODOVIA AL 220        105       KM 68  CANAFISTULA   \n",
              "2   12.451.076/0004-65  RODOVIA AL 220        105       KM 68  CANAFISTULA   \n",
              "3   12.451.076/0004-65  RODOVIA AL 220        105       KM 68  CANAFISTULA   \n",
              "4   12.451.076/0004-65  RODOVIA AL 220        105       KM 68  CANAFISTULA   \n",
              "\n",
              "         Cep             Produto Data da Coleta  Valor de Venda  \\\n",
              "0  57302-605            GASOLINA     2021-11-01           6.799   \n",
              "1  57302-605              ETANOL     2021-11-01           5.299   \n",
              "2  57302-605              DIESEL     2021-11-01           5.549   \n",
              "3  57302-605  GASOLINA ADITIVADA     2021-11-01           6.899   \n",
              "4  57302-605          DIESEL S10     2021-11-01           5.649   \n",
              "\n",
              "   Valor de Compra Unidade de Medida       Bandeira  \n",
              "0              NaN        R$ / litro  VIBRA ENERGIA  \n",
              "1              NaN        R$ / litro  VIBRA ENERGIA  \n",
              "2              NaN        R$ / litro  VIBRA ENERGIA  \n",
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              "      <td>VIBRA ENERGIA</td>\n",
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              "      <td>NE</td>\n",
              "      <td>AL</td>\n",
              "      <td>ARAPIRACA</td>\n",
              "      <td>POSTO ARAPIRACA LTDA</td>\n",
              "      <td>12.451.076/0004-65</td>\n",
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              "      <td>GASOLINA ADITIVADA</td>\n",
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              "      <td>6.899</td>\n",
              "      <td>NaN</td>\n",
              "      <td>R$ / litro</td>\n",
              "      <td>VIBRA ENERGIA</td>\n",
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              "      <td>AL</td>\n",
              "      <td>ARAPIRACA</td>\n",
              "      <td>POSTO ARAPIRACA LTDA</td>\n",
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              "      <td>2021-11-01</td>\n",
              "      <td>5.649</td>\n",
              "      <td>NaN</td>\n",
              "      <td>R$ / litro</td>\n",
              "      <td>VIBRA ENERGIA</td>\n",
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      "source": [
        "#Inserção simples de dado\n",
        "combustiveis_df['Ativo'] = True\n",
        "\n",
        "display(combustiveis_df.head())"
      ],
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            "text/plain": [
              "  Regiao - Sigla Estado - Sigla  Municipio               Revenda  \\\n",
              "0             NE             AL  ARAPIRACA  POSTO ARAPIRACA LTDA   \n",
              "1             NE             AL  ARAPIRACA  POSTO ARAPIRACA LTDA   \n",
              "2             NE             AL  ARAPIRACA  POSTO ARAPIRACA LTDA   \n",
              "3             NE             AL  ARAPIRACA  POSTO ARAPIRACA LTDA   \n",
              "4             NE             AL  ARAPIRACA  POSTO ARAPIRACA LTDA   \n",
              "\n",
              "       CNPJ da Revenda     Nome da Rua Numero Rua Complemento       Bairro  \\\n",
              "0   12.451.076/0004-65  RODOVIA AL 220        105       KM 68  CANAFISTULA   \n",
              "1   12.451.076/0004-65  RODOVIA AL 220        105       KM 68  CANAFISTULA   \n",
              "2   12.451.076/0004-65  RODOVIA AL 220        105       KM 68  CANAFISTULA   \n",
              "3   12.451.076/0004-65  RODOVIA AL 220        105       KM 68  CANAFISTULA   \n",
              "4   12.451.076/0004-65  RODOVIA AL 220        105       KM 68  CANAFISTULA   \n",
              "\n",
              "         Cep             Produto Data da Coleta  Valor de Venda  \\\n",
              "0  57302-605            GASOLINA     2021-11-01           6.799   \n",
              "1  57302-605              ETANOL     2021-11-01           5.299   \n",
              "2  57302-605              DIESEL     2021-11-01           5.549   \n",
              "3  57302-605  GASOLINA ADITIVADA     2021-11-01           6.899   \n",
              "4  57302-605          DIESEL S10     2021-11-01           5.649   \n",
              "\n",
              "   Valor de Compra Unidade de Medida       Bandeira  Ativo  \n",
              "0              NaN        R$ / litro  VIBRA ENERGIA   True  \n",
              "1              NaN        R$ / litro  VIBRA ENERGIA   True  \n",
              "2              NaN        R$ / litro  VIBRA ENERGIA   True  \n",
              "3              NaN        R$ / litro  VIBRA ENERGIA   True  \n",
              "4              NaN        R$ / litro  VIBRA ENERGIA   True  "
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              "      <td>57302-605</td>\n",
              "      <td>DIESEL</td>\n",
              "      <td>2021-11-01</td>\n",
              "      <td>5.549</td>\n",
              "      <td>NaN</td>\n",
              "      <td>R$ / litro</td>\n",
              "      <td>VIBRA ENERGIA</td>\n",
              "      <td>True</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>NE</td>\n",
              "      <td>AL</td>\n",
              "      <td>ARAPIRACA</td>\n",
              "      <td>POSTO ARAPIRACA LTDA</td>\n",
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              "      <td>GASOLINA ADITIVADA</td>\n",
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              "      <td>VIBRA ENERGIA</td>\n",
              "      <td>True</td>\n",
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              "      <td>AL</td>\n",
              "      <td>ARAPIRACA</td>\n",
              "      <td>POSTO ARAPIRACA LTDA</td>\n",
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              "      <td>RODOVIA AL 220</td>\n",
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              "      <td>KM 68</td>\n",
              "      <td>CANAFISTULA</td>\n",
              "      <td>57302-605</td>\n",
              "      <td>DIESEL S10</td>\n",
              "      <td>2021-11-01</td>\n",
              "      <td>5.649</td>\n",
              "      <td>NaN</td>\n",
              "      <td>R$ / litro</td>\n",
              "      <td>VIBRA ENERGIA</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-cd98e920-7be7-4f32-971e-8a69da4a3cdf')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-cd98e920-7be7-4f32-971e-8a69da4a3cdf button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-cd98e920-7be7-4f32-971e-8a69da4a3cdf');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# (por Leandro Rodrigues)\n",
        "# como preencher uma coluna 'Valor de Venda - Status' que verifica o seguinte:\n",
        "# se o valor de venda for maior que 6,5 reais, ele fala que tá Caro..caso contrário, está barato\n",
        "import numpy as np\n",
        "\n",
        "combustiveis_df['Status do Valor de Venda'] = np.where(combustiveis_df['Valor de Venda'] > 6.5, 'Caro', 'Barato')\n",
        "display(combustiveis_df[['Revenda', 'Valor de Venda', 'Status do Valor de Venda']])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 502
        },
        "id": "-0HTMyP8vwst",
        "outputId": "b83f3e90-4814-47b4-a525-8be4dcc4062d"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "                                           Revenda  Valor de Venda  \\\n",
              "0                             POSTO ARAPIRACA LTDA           6.799   \n",
              "1                             POSTO ARAPIRACA LTDA           5.299   \n",
              "2                             POSTO ARAPIRACA LTDA           5.549   \n",
              "3                             POSTO ARAPIRACA LTDA           6.899   \n",
              "4                             POSTO ARAPIRACA LTDA           5.649   \n",
              "...                                            ...             ...   \n",
              "168404  COMERCIAL DE COMBUSTIVEL CACHOEIRINHA LTDA           5.859   \n",
              "168405           ABC DISTRIBUICAO DE PETROLEO LTDA           6.580   \n",
              "168406           ABC DISTRIBUICAO DE PETROLEO LTDA           4.740   \n",
              "168407           ABC DISTRIBUICAO DE PETROLEO LTDA           5.448   \n",
              "168408           ABC DISTRIBUICAO DE PETROLEO LTDA           6.580   \n",
              "\n",
              "       Status do Valor de Venda  \n",
              "0                          Caro  \n",
              "1                        Barato  \n",
              "2                        Barato  \n",
              "3                          Caro  \n",
              "4                        Barato  \n",
              "...                         ...  \n",
              "168404                   Barato  \n",
              "168405                     Caro  \n",
              "168406                   Barato  \n",
              "168407                   Barato  \n",
              "168408                     Caro  \n",
              "\n",
              "[168409 rows x 3 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-420b9203-16d0-49b5-af76-43b9c51783c5\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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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              "        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>Revenda</th>\n",
              "      <th>Valor de Venda</th>\n",
              "      <th>Status do Valor de Venda</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>POSTO ARAPIRACA LTDA</td>\n",
              "      <td>6.799</td>\n",
              "      <td>Caro</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>POSTO ARAPIRACA LTDA</td>\n",
              "      <td>5.299</td>\n",
              "      <td>Barato</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>POSTO ARAPIRACA LTDA</td>\n",
              "      <td>5.549</td>\n",
              "      <td>Barato</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>POSTO ARAPIRACA LTDA</td>\n",
              "      <td>6.899</td>\n",
              "      <td>Caro</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>POSTO ARAPIRACA LTDA</td>\n",
              "      <td>5.649</td>\n",
              "      <td>Barato</td>\n",
              "    </tr>\n",
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              "      <th>...</th>\n",
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              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>168404</th>\n",
              "      <td>COMERCIAL DE COMBUSTIVEL CACHOEIRINHA LTDA</td>\n",
              "      <td>5.859</td>\n",
              "      <td>Barato</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>168405</th>\n",
              "      <td>ABC DISTRIBUICAO DE PETROLEO LTDA</td>\n",
              "      <td>6.580</td>\n",
              "      <td>Caro</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>168406</th>\n",
              "      <td>ABC DISTRIBUICAO DE PETROLEO LTDA</td>\n",
              "      <td>4.740</td>\n",
              "      <td>Barato</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>168407</th>\n",
              "      <td>ABC DISTRIBUICAO DE PETROLEO LTDA</td>\n",
              "      <td>5.448</td>\n",
              "      <td>Barato</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>168408</th>\n",
              "      <td>ABC DISTRIBUICAO DE PETROLEO LTDA</td>\n",
              "      <td>6.580</td>\n",
              "      <td>Caro</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>168409 rows × 3 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-420b9203-16d0-49b5-af76-43b9c51783c5')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
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              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-420b9203-16d0-49b5-af76-43b9c51783c5 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-420b9203-16d0-49b5-af76-43b9c51783c5');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Calcular postos de gasolina por habitante temos na amostragem de \n",
        "# combustiveis nov/2021\n",
        "\n",
        "num_habitantes_df = pd.read_csv(\"ibge_num_habitantes_estimado.csv\", sep=\";\")\n",
        "display(num_habitantes_df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 614
        },
        "id": "frLUd2vpvzyM",
        "outputId": "fd45103b-9c9f-4fe8-86ed-da6a09d0a602"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "         Municipio Estado  NumHabitantes2021\n",
              "0   BELO HORIZONTE     MG            2530701\n",
              "1         CAMPINAS     SP            1223237\n",
              "2     CAMPO GRANDE     MS             916001\n",
              "3         CURITIBA     PR            1963726\n",
              "4          GOIANIA     GO            1555626\n",
              "5       INDAIATUBA     SP             260690\n",
              "6            NATAL     RN             803739\n",
              "7           PALMAS     TO             313349\n",
              "8        PENAPOLIS     SP              64098\n",
              "9     PORTO ALEGRE     RS            1492530\n",
              "10     PORTO VELHO     RO             548952\n",
              "11      RIO BRANCO     AC             419452\n",
              "12  RIO DE JANEIRO     RJ            6775561\n",
              "13    SALTO GRANDE     SP               9396\n",
              "14          SANTOS     SP             433991\n",
              "15       SAO PAULO     SP           12396372\n",
              "16     SAO VICENTE     SP             370839\n",
              "17     SERRA NEGRA     SP              29669"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-cc42b0f2-068b-4a35-8389-cdffa007a9a8\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
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              "        vertical-align: top;\n",
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              "\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>Municipio</th>\n",
              "      <th>Estado</th>\n",
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              "    </tr>\n",
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              "  <tbody>\n",
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              "      <th>0</th>\n",
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              "      <td>MG</td>\n",
              "      <td>2530701</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CAMPINAS</td>\n",
              "      <td>SP</td>\n",
              "      <td>1223237</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>CAMPO GRANDE</td>\n",
              "      <td>MS</td>\n",
              "      <td>916001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>CURITIBA</td>\n",
              "      <td>PR</td>\n",
              "      <td>1963726</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>GO</td>\n",
              "      <td>1555626</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>INDAIATUBA</td>\n",
              "      <td>SP</td>\n",
              "      <td>260690</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>NATAL</td>\n",
              "      <td>RN</td>\n",
              "      <td>803739</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>PALMAS</td>\n",
              "      <td>TO</td>\n",
              "      <td>313349</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>PENAPOLIS</td>\n",
              "      <td>SP</td>\n",
              "      <td>64098</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>PORTO ALEGRE</td>\n",
              "      <td>RS</td>\n",
              "      <td>1492530</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>PORTO VELHO</td>\n",
              "      <td>RO</td>\n",
              "      <td>548952</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>RIO BRANCO</td>\n",
              "      <td>AC</td>\n",
              "      <td>419452</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>RIO DE JANEIRO</td>\n",
              "      <td>RJ</td>\n",
              "      <td>6775561</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>SALTO GRANDE</td>\n",
              "      <td>SP</td>\n",
              "      <td>9396</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>SANTOS</td>\n",
              "      <td>SP</td>\n",
              "      <td>433991</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>SAO PAULO</td>\n",
              "      <td>SP</td>\n",
              "      <td>12396372</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>SAO VICENTE</td>\n",
              "      <td>SP</td>\n",
              "      <td>370839</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>SERRA NEGRA</td>\n",
              "      <td>SP</td>\n",
              "      <td>29669</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-cc42b0f2-068b-4a35-8389-cdffa007a9a8')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "\n",
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              "    }\n",
              "\n",
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              "      background-color: #434B5C;\n",
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              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-cc42b0f2-068b-4a35-8389-cdffa007a9a8 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-cc42b0f2-068b-4a35-8389-cdffa007a9a8');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Calcular postos de gasolina por habitante temos na amostragem de \n",
        "# combustiveis nov/2021\n",
        "\n",
        "num_habitantes_df = pd.read_csv(\"ibge_num_habitantes_estimado.csv\", sep=\";\")\n",
        "num_habitantes_df.rename(columns={\"Estado\":\"Estado - Sigla\"}, inplace=True)\n",
        "display(num_habitantes_df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 614
        },
        "id": "GoMCPBTuv3GD",
        "outputId": "1c9fa81e-e019-4cc1-e18f-2295e8bd26c6"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "         Municipio Estado - Sigla  NumHabitantes2021\n",
              "0   BELO HORIZONTE             MG            2530701\n",
              "1         CAMPINAS             SP            1223237\n",
              "2     CAMPO GRANDE             MS             916001\n",
              "3         CURITIBA             PR            1963726\n",
              "4          GOIANIA             GO            1555626\n",
              "5       INDAIATUBA             SP             260690\n",
              "6            NATAL             RN             803739\n",
              "7           PALMAS             TO             313349\n",
              "8        PENAPOLIS             SP              64098\n",
              "9     PORTO ALEGRE             RS            1492530\n",
              "10     PORTO VELHO             RO             548952\n",
              "11      RIO BRANCO             AC             419452\n",
              "12  RIO DE JANEIRO             RJ            6775561\n",
              "13    SALTO GRANDE             SP               9396\n",
              "14          SANTOS             SP             433991\n",
              "15       SAO PAULO             SP           12396372\n",
              "16     SAO VICENTE             SP             370839\n",
              "17     SERRA NEGRA             SP              29669"
            ],
            "text/html": [
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              "      <th></th>\n",
              "      <th>Municipio</th>\n",
              "      <th>Estado - Sigla</th>\n",
              "      <th>NumHabitantes2021</th>\n",
              "    </tr>\n",
              "  </thead>\n",
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              "      <th>0</th>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CAMPINAS</td>\n",
              "      <td>SP</td>\n",
              "      <td>1223237</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>CAMPO GRANDE</td>\n",
              "      <td>MS</td>\n",
              "      <td>916001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>CURITIBA</td>\n",
              "      <td>PR</td>\n",
              "      <td>1963726</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>GO</td>\n",
              "      <td>1555626</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>INDAIATUBA</td>\n",
              "      <td>SP</td>\n",
              "      <td>260690</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>NATAL</td>\n",
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              "      <td>803739</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>PALMAS</td>\n",
              "      <td>TO</td>\n",
              "      <td>313349</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>PENAPOLIS</td>\n",
              "      <td>SP</td>\n",
              "      <td>64098</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>PORTO ALEGRE</td>\n",
              "      <td>RS</td>\n",
              "      <td>1492530</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>PORTO VELHO</td>\n",
              "      <td>RO</td>\n",
              "      <td>548952</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>RIO BRANCO</td>\n",
              "      <td>AC</td>\n",
              "      <td>419452</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>RIO DE JANEIRO</td>\n",
              "      <td>RJ</td>\n",
              "      <td>6775561</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>SALTO GRANDE</td>\n",
              "      <td>SP</td>\n",
              "      <td>9396</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>SANTOS</td>\n",
              "      <td>SP</td>\n",
              "      <td>433991</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>SAO PAULO</td>\n",
              "      <td>SP</td>\n",
              "      <td>12396372</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>SAO VICENTE</td>\n",
              "      <td>SP</td>\n",
              "      <td>370839</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>SERRA NEGRA</td>\n",
              "      <td>SP</td>\n",
              "      <td>29669</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "\n",
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              "\n",
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              "          document.querySelector('#df-c7f83bae-9f84-4b14-82e5-222ddb3df61b button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-c7f83bae-9f84-4b14-82e5-222ddb3df61b');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
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              "  "
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Faz um MERGE dos dois dataframes\n",
        "colunas = ['Municipio', 'Estado - Sigla']\n",
        "merge_df = combustiveis_df.merge(num_habitantes_df, how=\"inner\", on=colunas)\n",
        "display(merge_df)\n",
        "print(merge_df.info())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "_8Yuwz3sv9VK",
        "outputId": "65132814-0eb3-493a-de98-b53c979f2477"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "      Regiao - Sigla Estado - Sigla   Municipio  \\\n",
              "0                 CO             GO     GOIANIA   \n",
              "1                 CO             GO     GOIANIA   \n",
              "2                 CO             GO     GOIANIA   \n",
              "3                 CO             GO     GOIANIA   \n",
              "4                 CO             GO     GOIANIA   \n",
              "...              ...            ...         ...   \n",
              "20629             SE             SP  INDAIATUBA   \n",
              "20630             SE             SP  INDAIATUBA   \n",
              "20631             SE             SP  INDAIATUBA   \n",
              "20632             SE             SP  INDAIATUBA   \n",
              "20633             SE             SP  INDAIATUBA   \n",
              "\n",
              "                                         Revenda      CNPJ da Revenda  \\\n",
              "0                      AERO SETE AUTO POSTO LTDA   37.831.484/0001-20   \n",
              "1                      AERO SETE AUTO POSTO LTDA   37.831.484/0001-20   \n",
              "2                      AERO SETE AUTO POSTO LTDA   37.831.484/0001-20   \n",
              "3                              POSTO DO BOI LTDA   06.880.293/0001-25   \n",
              "4                              POSTO DO BOI LTDA   06.880.293/0001-25   \n",
              "...                                          ...                  ...   \n",
              "20629                     POSTO DOS ESTEVES LTDA   20.763.169/0001-00   \n",
              "20630  ABDELNOR VI COMERCIO DE COMBUSTIVEIS LTDA   30.253.289/0001-11   \n",
              "20631  ABDELNOR VI COMERCIO DE COMBUSTIVEIS LTDA   30.253.289/0001-11   \n",
              "20632  ABDELNOR VI COMERCIO DE COMBUSTIVEIS LTDA   30.253.289/0001-11   \n",
              "20633  ABDELNOR VI COMERCIO DE COMBUSTIVEIS LTDA   30.253.289/0001-11   \n",
              "\n",
              "                          Nome da Rua Numero Rua  \\\n",
              "0      AVENIDA VEREADOR JOSE MONTEIRO       1854   \n",
              "1      AVENIDA VEREADOR JOSE MONTEIRO       1854   \n",
              "2      AVENIDA VEREADOR JOSE MONTEIRO       1854   \n",
              "3               AVENIDA INDEPENDENCIA      2.908   \n",
              "4               AVENIDA INDEPENDENCIA      2.908   \n",
              "...                               ...        ...   \n",
              "20629                 AVENIDA ITORORO        160   \n",
              "20630      AVENIDA PRESIDENTE KENNEDY        496   \n",
              "20631      AVENIDA PRESIDENTE KENNEDY        496   \n",
              "20632      AVENIDA PRESIDENTE KENNEDY        496   \n",
              "20633      AVENIDA PRESIDENTE KENNEDY        496   \n",
              "\n",
              "                               Complemento                Bairro        Cep  \\\n",
              "0      QUADRA08                  LOTE  11E  SETOR NEGRAO DE LIMA  74650-300   \n",
              "1      QUADRA08                  LOTE  11E  SETOR NEGRAO DE LIMA  74650-300   \n",
              "2      QUADRA08                  LOTE  11E  SETOR NEGRAO DE LIMA  74650-300   \n",
              "3                                      NaN             VILA NOVA  74645-010   \n",
              "4                                      NaN             VILA NOVA  74645-010   \n",
              "...                                    ...                   ...        ...   \n",
              "20629                                  NaN                CENTRO  13330-055   \n",
              "20630                                  NaN         CIDADE NOVA I  13334-170   \n",
              "20631                                  NaN         CIDADE NOVA I  13334-170   \n",
              "20632                                  NaN         CIDADE NOVA I  13334-170   \n",
              "20633                                  NaN         CIDADE NOVA I  13334-170   \n",
              "\n",
              "                  Produto Data da Coleta  Valor de Venda  Valor de Compra  \\\n",
              "0                GASOLINA     2021-11-01           6.999              NaN   \n",
              "1                  ETANOL     2021-11-01           4.990              NaN   \n",
              "2      GASOLINA ADITIVADA     2021-11-01           7.130              NaN   \n",
              "3                GASOLINA     2021-11-01           6.990              NaN   \n",
              "4                  ETANOL     2021-11-01           4.990              NaN   \n",
              "...                   ...            ...             ...              ...   \n",
              "20629            GASOLINA     2021-12-28           6.499              NaN   \n",
              "20630          DIESEL S10     2021-12-28           5.499              NaN   \n",
              "20631  GASOLINA ADITIVADA     2021-12-28           6.699              NaN   \n",
              "20632              ETANOL     2021-12-28           4.899              NaN   \n",
              "20633            GASOLINA     2021-12-28           6.299              NaN   \n",
              "\n",
              "      Unidade de Medida  Bandeira  Ativo Status do Valor de Venda  \\\n",
              "0            R$ / litro    RAIZEN   True                     Caro   \n",
              "1            R$ / litro    RAIZEN   True                   Barato   \n",
              "2            R$ / litro    RAIZEN   True                     Caro   \n",
              "3            R$ / litro    BRANCA   True                     Caro   \n",
              "4            R$ / litro    BRANCA   True                   Barato   \n",
              "...                 ...       ...    ...                      ...   \n",
              "20629        R$ / litro  IPIRANGA   True                   Barato   \n",
              "20630        R$ / litro    RAIZEN   True                   Barato   \n",
              "20631        R$ / litro    RAIZEN   True                     Caro   \n",
              "20632        R$ / litro    RAIZEN   True                   Barato   \n",
              "20633        R$ / litro    RAIZEN   True                   Barato   \n",
              "\n",
              "       NumHabitantes2021  \n",
              "0                1555626  \n",
              "1                1555626  \n",
              "2                1555626  \n",
              "3                1555626  \n",
              "4                1555626  \n",
              "...                  ...  \n",
              "20629             260690  \n",
              "20630             260690  \n",
              "20631             260690  \n",
              "20632             260690  \n",
              "20633             260690  \n",
              "\n",
              "[20634 rows x 19 columns]"
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Regiao - Sigla</th>\n",
              "      <th>Estado - Sigla</th>\n",
              "      <th>Municipio</th>\n",
              "      <th>Revenda</th>\n",
              "      <th>CNPJ da Revenda</th>\n",
              "      <th>Nome da Rua</th>\n",
              "      <th>Numero Rua</th>\n",
              "      <th>Complemento</th>\n",
              "      <th>Bairro</th>\n",
              "      <th>Cep</th>\n",
              "      <th>Produto</th>\n",
              "      <th>Data da Coleta</th>\n",
              "      <th>Valor de Venda</th>\n",
              "      <th>Valor de Compra</th>\n",
              "      <th>Unidade de Medida</th>\n",
              "      <th>Bandeira</th>\n",
              "      <th>Ativo</th>\n",
              "      <th>Status do Valor de Venda</th>\n",
              "      <th>NumHabitantes2021</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>CO</td>\n",
              "      <td>GO</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>AERO SETE AUTO POSTO LTDA</td>\n",
              "      <td>37.831.484/0001-20</td>\n",
              "      <td>AVENIDA VEREADOR JOSE MONTEIRO</td>\n",
              "      <td>1854</td>\n",
              "      <td>QUADRA08                  LOTE  11E</td>\n",
              "      <td>SETOR NEGRAO DE LIMA</td>\n",
              "      <td>74650-300</td>\n",
              "      <td>GASOLINA</td>\n",
              "      <td>2021-11-01</td>\n",
              "      <td>6.999</td>\n",
              "      <td>NaN</td>\n",
              "      <td>R$ / litro</td>\n",
              "      <td>RAIZEN</td>\n",
              "      <td>True</td>\n",
              "      <td>Caro</td>\n",
              "      <td>1555626</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CO</td>\n",
              "      <td>GO</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>AERO SETE AUTO POSTO LTDA</td>\n",
              "      <td>37.831.484/0001-20</td>\n",
              "      <td>AVENIDA VEREADOR JOSE MONTEIRO</td>\n",
              "      <td>1854</td>\n",
              "      <td>QUADRA08                  LOTE  11E</td>\n",
              "      <td>SETOR NEGRAO DE LIMA</td>\n",
              "      <td>74650-300</td>\n",
              "      <td>ETANOL</td>\n",
              "      <td>2021-11-01</td>\n",
              "      <td>4.990</td>\n",
              "      <td>NaN</td>\n",
              "      <td>R$ / litro</td>\n",
              "      <td>RAIZEN</td>\n",
              "      <td>True</td>\n",
              "      <td>Barato</td>\n",
              "      <td>1555626</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>CO</td>\n",
              "      <td>GO</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>AERO SETE AUTO POSTO LTDA</td>\n",
              "      <td>37.831.484/0001-20</td>\n",
              "      <td>AVENIDA VEREADOR JOSE MONTEIRO</td>\n",
              "      <td>1854</td>\n",
              "      <td>QUADRA08                  LOTE  11E</td>\n",
              "      <td>SETOR NEGRAO DE LIMA</td>\n",
              "      <td>74650-300</td>\n",
              "      <td>GASOLINA ADITIVADA</td>\n",
              "      <td>2021-11-01</td>\n",
              "      <td>7.130</td>\n",
              "      <td>NaN</td>\n",
              "      <td>R$ / litro</td>\n",
              "      <td>RAIZEN</td>\n",
              "      <td>True</td>\n",
              "      <td>Caro</td>\n",
              "      <td>1555626</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>CO</td>\n",
              "      <td>GO</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>POSTO DO BOI LTDA</td>\n",
              "      <td>06.880.293/0001-25</td>\n",
              "      <td>AVENIDA INDEPENDENCIA</td>\n",
              "      <td>2.908</td>\n",
              "      <td>NaN</td>\n",
              "      <td>VILA NOVA</td>\n",
              "      <td>74645-010</td>\n",
              "      <td>GASOLINA</td>\n",
              "      <td>2021-11-01</td>\n",
              "      <td>6.990</td>\n",
              "      <td>NaN</td>\n",
              "      <td>R$ / litro</td>\n",
              "      <td>BRANCA</td>\n",
              "      <td>True</td>\n",
              "      <td>Caro</td>\n",
              "      <td>1555626</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>CO</td>\n",
              "      <td>GO</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>POSTO DO BOI LTDA</td>\n",
              "      <td>06.880.293/0001-25</td>\n",
              "      <td>AVENIDA INDEPENDENCIA</td>\n",
              "      <td>2.908</td>\n",
              "      <td>NaN</td>\n",
              "      <td>VILA NOVA</td>\n",
              "      <td>74645-010</td>\n",
              "      <td>ETANOL</td>\n",
              "      <td>2021-11-01</td>\n",
              "      <td>4.990</td>\n",
              "      <td>NaN</td>\n",
              "      <td>R$ / litro</td>\n",
              "      <td>BRANCA</td>\n",
              "      <td>True</td>\n",
              "      <td>Barato</td>\n",
              "      <td>1555626</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20629</th>\n",
              "      <td>SE</td>\n",
              "      <td>SP</td>\n",
              "      <td>INDAIATUBA</td>\n",
              "      <td>POSTO DOS ESTEVES LTDA</td>\n",
              "      <td>20.763.169/0001-00</td>\n",
              "      <td>AVENIDA ITORORO</td>\n",
              "      <td>160</td>\n",
              "      <td>NaN</td>\n",
              "      <td>CENTRO</td>\n",
              "      <td>13330-055</td>\n",
              "      <td>GASOLINA</td>\n",
              "      <td>2021-12-28</td>\n",
              "      <td>6.499</td>\n",
              "      <td>NaN</td>\n",
              "      <td>R$ / litro</td>\n",
              "      <td>IPIRANGA</td>\n",
              "      <td>True</td>\n",
              "      <td>Barato</td>\n",
              "      <td>260690</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20630</th>\n",
              "      <td>SE</td>\n",
              "      <td>SP</td>\n",
              "      <td>INDAIATUBA</td>\n",
              "      <td>ABDELNOR VI COMERCIO DE COMBUSTIVEIS LTDA</td>\n",
              "      <td>30.253.289/0001-11</td>\n",
              "      <td>AVENIDA PRESIDENTE KENNEDY</td>\n",
              "      <td>496</td>\n",
              "      <td>NaN</td>\n",
              "      <td>CIDADE NOVA I</td>\n",
              "      <td>13334-170</td>\n",
              "      <td>DIESEL S10</td>\n",
              "      <td>2021-12-28</td>\n",
              "      <td>5.499</td>\n",
              "      <td>NaN</td>\n",
              "      <td>R$ / litro</td>\n",
              "      <td>RAIZEN</td>\n",
              "      <td>True</td>\n",
              "      <td>Barato</td>\n",
              "      <td>260690</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20631</th>\n",
              "      <td>SE</td>\n",
              "      <td>SP</td>\n",
              "      <td>INDAIATUBA</td>\n",
              "      <td>ABDELNOR VI COMERCIO DE COMBUSTIVEIS LTDA</td>\n",
              "      <td>30.253.289/0001-11</td>\n",
              "      <td>AVENIDA PRESIDENTE KENNEDY</td>\n",
              "      <td>496</td>\n",
              "      <td>NaN</td>\n",
              "      <td>CIDADE NOVA I</td>\n",
              "      <td>13334-170</td>\n",
              "      <td>GASOLINA ADITIVADA</td>\n",
              "      <td>2021-12-28</td>\n",
              "      <td>6.699</td>\n",
              "      <td>NaN</td>\n",
              "      <td>R$ / litro</td>\n",
              "      <td>RAIZEN</td>\n",
              "      <td>True</td>\n",
              "      <td>Caro</td>\n",
              "      <td>260690</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20632</th>\n",
              "      <td>SE</td>\n",
              "      <td>SP</td>\n",
              "      <td>INDAIATUBA</td>\n",
              "      <td>ABDELNOR VI COMERCIO DE COMBUSTIVEIS LTDA</td>\n",
              "      <td>30.253.289/0001-11</td>\n",
              "      <td>AVENIDA PRESIDENTE KENNEDY</td>\n",
              "      <td>496</td>\n",
              "      <td>NaN</td>\n",
              "      <td>CIDADE NOVA I</td>\n",
              "      <td>13334-170</td>\n",
              "      <td>ETANOL</td>\n",
              "      <td>2021-12-28</td>\n",
              "      <td>4.899</td>\n",
              "      <td>NaN</td>\n",
              "      <td>R$ / litro</td>\n",
              "      <td>RAIZEN</td>\n",
              "      <td>True</td>\n",
              "      <td>Barato</td>\n",
              "      <td>260690</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20633</th>\n",
              "      <td>SE</td>\n",
              "      <td>SP</td>\n",
              "      <td>INDAIATUBA</td>\n",
              "      <td>ABDELNOR VI COMERCIO DE COMBUSTIVEIS LTDA</td>\n",
              "      <td>30.253.289/0001-11</td>\n",
              "      <td>AVENIDA PRESIDENTE KENNEDY</td>\n",
              "      <td>496</td>\n",
              "      <td>NaN</td>\n",
              "      <td>CIDADE NOVA I</td>\n",
              "      <td>13334-170</td>\n",
              "      <td>GASOLINA</td>\n",
              "      <td>2021-12-28</td>\n",
              "      <td>6.299</td>\n",
              "      <td>NaN</td>\n",
              "      <td>R$ / litro</td>\n",
              "      <td>RAIZEN</td>\n",
              "      <td>True</td>\n",
              "      <td>Barato</td>\n",
              "      <td>260690</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>20634 rows × 19 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-99295425-42c5-48cb-8dca-729289c84d2d')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-99295425-42c5-48cb-8dca-729289c84d2d button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-99295425-42c5-48cb-8dca-729289c84d2d');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 20634 entries, 0 to 20633\n",
            "Data columns (total 19 columns):\n",
            " #   Column                    Non-Null Count  Dtype         \n",
            "---  ------                    --------------  -----         \n",
            " 0   Regiao - Sigla            20634 non-null  object        \n",
            " 1   Estado - Sigla            20634 non-null  object        \n",
            " 2   Municipio                 20634 non-null  object        \n",
            " 3   Revenda                   20634 non-null  object        \n",
            " 4   CNPJ da Revenda           20634 non-null  object        \n",
            " 5   Nome da Rua               20634 non-null  object        \n",
            " 6   Numero Rua                20634 non-null  object        \n",
            " 7   Complemento               3837 non-null   object        \n",
            " 8   Bairro                    20634 non-null  object        \n",
            " 9   Cep                       20634 non-null  object        \n",
            " 10  Produto                   20634 non-null  object        \n",
            " 11  Data da Coleta            20634 non-null  datetime64[ns]\n",
            " 12  Valor de Venda            20634 non-null  float64       \n",
            " 13  Valor de Compra           0 non-null      float64       \n",
            " 14  Unidade de Medida         20634 non-null  object        \n",
            " 15  Bandeira                  20634 non-null  object        \n",
            " 16  Ativo                     20634 non-null  bool          \n",
            " 17  Status do Valor de Venda  20634 non-null  object        \n",
            " 18  NumHabitantes2021         20634 non-null  int64         \n",
            "dtypes: bool(1), datetime64[ns](1), float64(2), int64(1), object(14)\n",
            "memory usage: 3.0+ MB\n",
            "None\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Destruir coluna completamente vazia (todas as linhas são nulas)\n",
        "merge_df.dropna(axis='columns', inplace=True)\n",
        "print(merge_df.info())\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OrxFPlzowAjE",
        "outputId": "25093453-83fa-44e5-8e32-2b640715a0d2"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 20634 entries, 0 to 20633\n",
            "Data columns (total 17 columns):\n",
            " #   Column                    Non-Null Count  Dtype         \n",
            "---  ------                    --------------  -----         \n",
            " 0   Regiao - Sigla            20634 non-null  object        \n",
            " 1   Estado - Sigla            20634 non-null  object        \n",
            " 2   Municipio                 20634 non-null  object        \n",
            " 3   Revenda                   20634 non-null  object        \n",
            " 4   CNPJ da Revenda           20634 non-null  object        \n",
            " 5   Nome da Rua               20634 non-null  object        \n",
            " 6   Numero Rua                20634 non-null  object        \n",
            " 7   Bairro                    20634 non-null  object        \n",
            " 8   Cep                       20634 non-null  object        \n",
            " 9   Produto                   20634 non-null  object        \n",
            " 10  Data da Coleta            20634 non-null  datetime64[ns]\n",
            " 11  Valor de Venda            20634 non-null  float64       \n",
            " 12  Unidade de Medida         20634 non-null  object        \n",
            " 13  Bandeira                  20634 non-null  object        \n",
            " 14  Ativo                     20634 non-null  bool          \n",
            " 15  Status do Valor de Venda  20634 non-null  object        \n",
            " 16  NumHabitantes2021         20634 non-null  int64         \n",
            "dtypes: bool(1), datetime64[ns](1), float64(1), int64(1), object(13)\n",
            "memory usage: 2.7+ MB\n",
            "None\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "colunas=['Regiao - Sigla', 'Nome da Rua', 'Numero Rua', \n",
        "         'Bairro', 'Cep', 'Produto', 'Data da Coleta', 'Valor de Venda',\n",
        "         'Unidade de Medida', 'Bandeira', 'Ativo', 'Status do Valor de Venda']\n",
        "merge_df.drop(labels=colunas, axis=1, inplace=True)\n",
        "print(merge_df.info())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Y3dfVRuTwDiZ",
        "outputId": "9ab66fd5-365c-48da-eafd-6395739ecb38"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 20634 entries, 0 to 20633\n",
            "Data columns (total 5 columns):\n",
            " #   Column             Non-Null Count  Dtype \n",
            "---  ------             --------------  ----- \n",
            " 0   Estado - Sigla     20634 non-null  object\n",
            " 1   Municipio          20634 non-null  object\n",
            " 2   Revenda            20634 non-null  object\n",
            " 3   CNPJ da Revenda    20634 non-null  object\n",
            " 4   NumHabitantes2021  20634 non-null  int64 \n",
            "dtypes: int64(1), object(4)\n",
            "memory usage: 967.2+ KB\n",
            "None\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Remover a linhas duplicadas\n",
        "merge_df.drop_duplicates(inplace=True)\n",
        "display(merge_df.head(100))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 711
        },
        "id": "f-zH7FwLwE6p",
        "outputId": "712bd816-82ef-4e90-c0e5-edaa4b44a693"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "     Estado - Sigla       Municipio                                   Revenda  \\\n",
              "0                GO         GOIANIA                 AERO SETE AUTO POSTO LTDA   \n",
              "3                GO         GOIANIA                         POSTO DO BOI LTDA   \n",
              "7                GO         GOIANIA                             POSTO DN LTDA   \n",
              "11               GO         GOIANIA                         POSTO ALDEIA LTDA   \n",
              "15               GO         GOIANIA               AUTO POSTO SANTA LUZIA LTDA   \n",
              "...             ...             ...                                       ...   \n",
              "1677             RJ  RIO DE JANEIRO       POSTO SANTA CLARA DA PAVUNA II LTDA   \n",
              "1682             RJ  RIO DE JANEIRO          POSTO SANTA CLARA DA PAVUNA LTDA   \n",
              "1688             RJ  RIO DE JANEIRO            NOVA PARADINHA AUTO POSTO LTDA   \n",
              "1694             RJ  RIO DE JANEIRO            AUTO POSTO LUAR DA PENHA LTDA.   \n",
              "1699             RJ  RIO DE JANEIRO  AUTO POSTO FUTURO GNV DE BONSUCESSO LTDA   \n",
              "\n",
              "          CNPJ da Revenda  NumHabitantes2021  \n",
              "0      37.831.484/0001-20            1555626  \n",
              "3      06.880.293/0001-25            1555626  \n",
              "7      05.413.136/0001-47            1555626  \n",
              "11     04.896.662/0001-42            1555626  \n",
              "15     04.142.631/0001-04            1555626  \n",
              "...                   ...                ...  \n",
              "1677   06.955.648/0001-06            6775561  \n",
              "1682   03.246.347/0001-07            6775561  \n",
              "1688   07.594.094/0001-13            6775561  \n",
              "1694   07.035.006/0001-43            6775561  \n",
              "1699   05.037.349/0001-11            6775561  \n",
              "\n",
              "[100 rows x 5 columns]"
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              "      <th>0</th>\n",
              "      <td>GO</td>\n",
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              "      <td>AERO SETE AUTO POSTO LTDA</td>\n",
              "      <td>37.831.484/0001-20</td>\n",
              "      <td>1555626</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>GO</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>POSTO DO BOI LTDA</td>\n",
              "      <td>06.880.293/0001-25</td>\n",
              "      <td>1555626</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>GO</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>POSTO DN LTDA</td>\n",
              "      <td>05.413.136/0001-47</td>\n",
              "      <td>1555626</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>GO</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>POSTO ALDEIA LTDA</td>\n",
              "      <td>04.896.662/0001-42</td>\n",
              "      <td>1555626</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>GO</td>\n",
              "      <td>GOIANIA</td>\n",
              "      <td>AUTO POSTO SANTA LUZIA LTDA</td>\n",
              "      <td>04.142.631/0001-04</td>\n",
              "      <td>1555626</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>1677</th>\n",
              "      <td>RJ</td>\n",
              "      <td>RIO DE JANEIRO</td>\n",
              "      <td>POSTO SANTA CLARA DA PAVUNA II LTDA</td>\n",
              "      <td>06.955.648/0001-06</td>\n",
              "      <td>6775561</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1682</th>\n",
              "      <td>RJ</td>\n",
              "      <td>RIO DE JANEIRO</td>\n",
              "      <td>POSTO SANTA CLARA DA PAVUNA LTDA</td>\n",
              "      <td>03.246.347/0001-07</td>\n",
              "      <td>6775561</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1688</th>\n",
              "      <td>RJ</td>\n",
              "      <td>RIO DE JANEIRO</td>\n",
              "      <td>NOVA PARADINHA AUTO POSTO LTDA</td>\n",
              "      <td>07.594.094/0001-13</td>\n",
              "      <td>6775561</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1694</th>\n",
              "      <td>RJ</td>\n",
              "      <td>RIO DE JANEIRO</td>\n",
              "      <td>AUTO POSTO LUAR DA PENHA LTDA.</td>\n",
              "      <td>07.035.006/0001-43</td>\n",
              "      <td>6775561</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1699</th>\n",
              "      <td>RJ</td>\n",
              "      <td>RIO DE JANEIRO</td>\n",
              "      <td>AUTO POSTO FUTURO GNV DE BONSUCESSO LTDA</td>\n",
              "      <td>05.037.349/0001-11</td>\n",
              "      <td>6775561</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "<p>100 rows × 5 columns</p>\n",
              "</div>\n",
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              "                                                     [key], {});\n",
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    {
      "cell_type": "code",
      "source": [
        "#Agrupar e contar quantos postos tem na cidade..\n",
        "postos_por_municipio_df = merge_df.groupby(by=['Estado - Sigla', 'Municipio', 'NumHabitantes2021']).count()\n",
        "postos_por_municipio_df.drop('CNPJ da Revenda', axis=1, inplace=True)\n",
        "postos_por_municipio_df.rename(columns={\"Revenda\": \"Número de Postos\"}, inplace=True)\n",
        "display(postos_por_municipio_df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 551
        },
        "id": "llj4PcDazauy",
        "outputId": "d9069f4f-2ea8-4123-881a-891db4a18ed8"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "                                                 Número de Postos\n",
              "Estado - Sigla Municipio      NumHabitantes2021                  \n",
              "AC             RIO BRANCO     419452                           44\n",
              "GO             GOIANIA        1555626                          93\n",
              "MG             BELO HORIZONTE 2530701                          54\n",
              "MS             CAMPO GRANDE   916001                          104\n",
              "PR             CURITIBA       1963726                         110\n",
              "RJ             RIO DE JANEIRO 6775561                         379\n",
              "RN             NATAL          803739                           37\n",
              "RO             PORTO VELHO    548952                           40\n",
              "RS             PORTO ALEGRE   1492530                          73\n",
              "SP             CAMPINAS       1223237                          51\n",
              "               INDAIATUBA     260690                           36\n",
              "               SANTOS         433991                           36\n",
              "               SAO PAULO      12396372                        429\n",
              "               SAO VICENTE    370839                           20\n",
              "TO             PALMAS         313349                           26"
            ],
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              "      <th></th>\n",
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              "      <th>AC</th>\n",
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              "      <th>PR</th>\n",
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              "      <th>RO</th>\n",
              "      <th>PORTO VELHO</th>\n",
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              "      <th>RS</th>\n",
              "      <th>PORTO ALEGRE</th>\n",
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              "      <td>73</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">SP</th>\n",
              "      <th>CAMPINAS</th>\n",
              "      <th>1223237</th>\n",
              "      <td>51</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>INDAIATUBA</th>\n",
              "      <th>260690</th>\n",
              "      <td>36</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SANTOS</th>\n",
              "      <th>433991</th>\n",
              "      <td>36</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SAO PAULO</th>\n",
              "      <th>12396372</th>\n",
              "      <td>429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SAO VICENTE</th>\n",
              "      <th>370839</th>\n",
              "      <td>20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>TO</th>\n",
              "      <th>PALMAS</th>\n",
              "      <th>313349</th>\n",
              "      <td>26</td>\n",
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              "  </tbody>\n",
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              "                                                     [key], {});\n",
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              "\n",
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              "            + ' to learn more about interactive tables.';\n",
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              "  "
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          "metadata": {}
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#AQUI O FINAL ESTÁ COM PROBLEMA\n",
        "\n",
        "#Agrupar e contar quantos postos tem na cidade..\n",
        "postos_por_municipio_df = merge_df.groupby(by=['Estado - Sigla', 'Municipio', 'NumHabitantes2021']).count()\n",
        "display(postos_por_municipio_df.info())\n",
        "postos_por_municipio_df.drop('CNPJ da Revenda', axis=1, inplace=True)\n",
        "postos_por_municipio_df.rename(columns={\"Revenda\": \"NumPostos\"}, inplace=True)\n",
        "\n",
        "#postos_por_municipio_df['PostosPorHabitante'] = postos_por_municipio_df['NumPostos'] / postos_por_municipio_df['NumHabitantes2021']\n",
        "display(postos_por_municipio_df)"
      ],
      "metadata": {
        "id": "JSWFWczg2HZt",
        "outputId": "1c235fbe-3780-4e18-e357-1aa9a73f25da",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 725
        }
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "MultiIndex: 15 entries, ('AC', 'RIO BRANCO', 419452) to ('TO', 'PALMAS', 313349)\n",
            "Data columns (total 2 columns):\n",
            " #   Column           Non-Null Count  Dtype\n",
            "---  ------           --------------  -----\n",
            " 0   Revenda          15 non-null     int64\n",
            " 1   CNPJ da Revenda  15 non-null     int64\n",
            "dtypes: int64(2)\n",
            "memory usage: 800.0+ bytes\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "None"
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          "data": {
            "text/plain": [
              "                                                 NumPostos\n",
              "Estado - Sigla Municipio      NumHabitantes2021           \n",
              "AC             RIO BRANCO     419452                    44\n",
              "GO             GOIANIA        1555626                   93\n",
              "MG             BELO HORIZONTE 2530701                   54\n",
              "MS             CAMPO GRANDE   916001                   104\n",
              "PR             CURITIBA       1963726                  110\n",
              "RJ             RIO DE JANEIRO 6775561                  379\n",
              "RN             NATAL          803739                    37\n",
              "RO             PORTO VELHO    548952                    40\n",
              "RS             PORTO ALEGRE   1492530                   73\n",
              "SP             CAMPINAS       1223237                   51\n",
              "               INDAIATUBA     260690                    36\n",
              "               SANTOS         433991                    36\n",
              "               SAO PAULO      12396372                 429\n",
              "               SAO VICENTE    370839                    20\n",
              "TO             PALMAS         313349                    26"
            ],
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              "\n",
              "  <div id=\"df-1654c363-f898-478e-971b-d898932b998d\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
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              "        vertical-align: middle;\n",
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              "      <td>44</td>\n",
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              "      <td>93</td>\n",
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              "      <th>CURITIBA</th>\n",
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              "      <th>RS</th>\n",
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              "      <td>73</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">SP</th>\n",
              "      <th>CAMPINAS</th>\n",
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              "      <td>51</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>INDAIATUBA</th>\n",
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              "      <td>36</td>\n",
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              "      <th>12396372</th>\n",
              "      <td>429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SAO VICENTE</th>\n",
              "      <th>370839</th>\n",
              "      <td>20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>TO</th>\n",
              "      <th>PALMAS</th>\n",
              "      <th>313349</th>\n",
              "      <td>26</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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            ]
          },
          "metadata": {}
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "plt.hist(combustiveis_df['Valor de Venda'])\n",
        "#vamos colocar um título no gráfico\n",
        "plt.title(\"Valor médio dos combustíveis Nov/2021\")\n",
        "#Rótulo horizontal \n",
        "plt.xlabel(\"Preço (em reais)\")\n",
        "plt.ylabel(\"Quantidade de Coletas\")\n",
        "\n",
        "#Traça a linha vermelha tracejada com o preço médio\n",
        "plt.axvline(combustiveis_df['Valor de Venda'].mean(), color = 'red', linestyle ='dashed',linewidth=5)\n",
        "\n",
        "#\"Plota\" o gráfico\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "OIQlItRWgCxo",
        "outputId": "b15df168-1beb-45cb-eadd-df137ba0a3a7"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Segundo gráfico\n",
        "c_mean = combustiveis_df['Valor de Venda'].groupby(by=combustiveis_df['Produto']).mean()\n",
        "display(c_mean)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 156
        },
        "id": "F5XoN1FzooTE",
        "outputId": "3691c113-1e97-4ca1-966e-4ef58f045a1b"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Produto\n",
              "DIESEL                5.375682\n",
              "DIESEL S10            5.454901\n",
              "ETANOL                5.456115\n",
              "GASOLINA              6.708741\n",
              "GASOLINA ADITIVADA    6.860422\n",
              "GNV                   4.392935\n",
              "Name: Valor de Venda, dtype: float64"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import seaborn as sn\n",
        "#Vou definir a área do gráfico \n",
        "plt.figure(figsize=(7,5))\n",
        "\n",
        "#Plotar o gráfico\n",
        "c_mean.plot(\n",
        "    kind=\"barh\",\n",
        "    xlabel=\"Tipo de Combustível\",\n",
        "    ylabel=\"Preço reais/litro\",\n",
        "    color=\"red\",\n",
        "    alpha = 0.8\n",
        "   \n",
        ")\n",
        "\n",
        "#Grid\n",
        "plt.grid()\n",
        "\n",
        "#Exibe\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 320
        },
        "id": "IG5dcONPpS2q",
        "outputId": "661e8c48-b3a6-45db-ddfe-7cfe8474bb84"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 504x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Vamor personalizar a planilha Excel...\n",
        "from openpyxl import load_workbook\n",
        "from openpyxl.styles import PatternFill, Font, Color, Alignment\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "bX_71kXXx6zL"
      },
      "execution_count": 36,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#c_mean.reset_index(inplace=True)\n",
        "display(c_mean)\n",
        "\n",
        "excel = \"por_litro.xlsx\"\n",
        "c_mean.to_excel(excel, \"Sumário\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 156
        },
        "id": "DTOSCSx40epJ",
        "outputId": "44ba7574-f60a-4c39-828c-45223d96e767"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Produto\n",
              "DIESEL                5.375682\n",
              "DIESEL S10            5.454901\n",
              "ETANOL                5.456115\n",
              "GASOLINA              6.708741\n",
              "GASOLINA ADITIVADA    6.860422\n",
              "GNV                   4.392935\n",
              "Name: Valor de Venda, dtype: float64"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from openpyxl import load_workbook\n",
        "from openpyxl.styles import PatternFill, Font, Color, Alignment\n",
        "\n",
        "wb = load_workbook(excel)\n",
        "\n",
        "ws = wb['Sumário']\n",
        "\n",
        "cinzinha = PatternFill(\"solid\", fgColor = \"808080\")\n",
        "coords = ['A1','B1']\n",
        "for coord in coords:\n",
        " ws[coord].fill = cinzinha\n",
        "\n",
        "wb.save(excel)"
      ],
      "metadata": {
        "id": "d5MuRH8N2aLX"
      },
      "execution_count": 43,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Vamor personalizar a planilha Excel...\n",
        "from openpyxl import load_workbook\n",
        "from openpyxl.styles import PatternFill, Font, Color, Alignment\n",
        "\n",
        "#Vai abrir o Excel no openpyxl\n",
        "wb = load_workbook(excel) # wb = Workbook\n",
        "\n",
        "#Pegar a planilha certa... usando o Sheet Name (nome da planilha)\n",
        "ws = wb['Sumário'] # Work Sheet -> planilha atual, ativa, de trabalho\n",
        "\n",
        "#Vamos pintar o cabeçalho da tabela de \"cinzinha\"\n",
        "cinzinha = PatternFill(\"solid\", fgColor=\"CCCCCC\")\n",
        "coords = ['A1', 'B1']\n",
        "for coord in coords:\n",
        "  ws[coord].fill = cinzinha\n",
        "\n",
        "#Onde o preço do combustível for maior ou igual a 6,5 reais (6.5) pinta a fonte\n",
        "#de vermelho e deixa negrito...\n",
        "MAX_ROW = ws.max_row\n",
        "num_linha = 2\n",
        "while (num_linha <= MAX_ROW):\n",
        "  coord = 'B'+str(num_linha) #coord=\"B{0}\".format(num_linha)\n",
        "  if ws[coord].value >= 6.5:\n",
        "    ws[coord].font = Font(bold=True, color=\"FF0000\")\n",
        "  num_linha = num_linha + 1\n",
        "#Salvar o Excel\n",
        "wb.save(excel)\n"
      ],
      "metadata": {
        "id": "NB5q3XP4AcXM"
      },
      "execution_count": 44,
      "outputs": []
    }
  ]
}