Resolvido_Lista_de_Exercícios.ipynb

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        "<img alt=\"Colaboratory logo\" width=\"15%\" src=\"https://raw.githubusercontent.com/carlosfab/escola-data-science/master/img/novo_logo_bg_claro.png\">\n",
        "\n",
        "#### **Data Science na Prática 3.0**\n",
        "*by [sigmoidal.ai](https://sigmoidal.ai)*\n",
        "\n",
        "---"
      ]
    },
    {
      "cell_type": "markdown",
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        "id": "vvplGyW2N3rX"
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      "source": [
        "# Lista de Exercícios\n",
        "\n",
        "A lista de exercícios tem por objetivo colocar a mão na massa e relembrar os conceitos que foram passados nas aulas anteriores.\n",
        "\n",
        "<center><img src=\"https://images.unsplash.com/photo-1542903660-eedba2cda473?ixid=MnwxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8&ixlib=rb-1.2.1&auto=format&fit=crop&w=1050&q=80\" height=\"400px\"></center>\n",
        "\n",
        "Optei por não necessariamente seguir a sequencia das aulas, colocando os exercícios "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9GQoXiddIpr9"
      },
      "source": [
        "## Exercício 1\n",
        "\n",
        "* Importar o pacote Pandas\n",
        "* importar os dados de ocorrências da aviação civil neste link\n",
        "* Ver qual o tamanho (linhas x colunas) do *DataFrame*\n",
        "* Verificar as 5 primeiras "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hdRXuNktKw9p"
      },
      "source": [
        "**Importe o Pandas e importe os dados de ocorrências da aviação civil que se encontram em `csv` [neste link](https://raw.githubusercontent.com/carlosfab/dsnp2/master/datasets/ocorrencias_aviacao.csv).**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8TpD5o8MLMaV"
      },
      "source": [
        "import pandas as pd\n",
        "df=pd.read_csv('https://raw.githubusercontent.com/carlosfab/dsnp2/master/datasets/ocorrencias_aviacao.csv')\n"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Tf8ScLP9LRjq"
      },
      "source": [
        "**Veja qual o tamanho (linhas e colunas) do conjunto de dados importado.**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vGsqOw52LnKZ",
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          "base_uri": "https://localhost:8080/"
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        "outputId": "111162c8-0c2e-40eb-b534-133ebb6ff5aa"
      },
      "source": [
        "df.shape"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(5208, 22)"
            ]
          },
          "metadata": {},
          "execution_count": 12
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      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OvvxJlZXL-BH"
      },
      "source": [
        "**Identifique o tipo de cada coluna (inteiro, float, object).**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MjAmdNplMOMJ",
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        "outputId": "22712c57-4c2a-474a-c4c2-42855dacddb3"
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      "source": [
        "df.dtypes"
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      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "codigo_ocorrencia                   int64\n",
              "ocorrencia_classificacao           object\n",
              "ocorrencia_tipo                    object\n",
              "ocorrencia_tipo_categoria          object\n",
              "ocorrencia_tipo_icao               object\n",
              "ocorrencia_latitude               float64\n",
              "ocorrencia_longitude              float64\n",
              "ocorrencia_cidade                  object\n",
              "ocorrencia_uf                      object\n",
              "ocorrencia_pais                    object\n",
              "ocorrencia_aerodromo               object\n",
              "ocorrencia_dia                     object\n",
              "ocorrencia_horario                 object\n",
              "investigacao_aeronave_liberada     object\n",
              "investigacao_status                object\n",
              "divulgacao_relatorio_numero        object\n",
              "divulgacao_relatorio_publicado     object\n",
              "divulgacao_dia_publicacao          object\n",
              "total_recomendacoes                 int64\n",
              "total_aeronaves_envolvidas          int64\n",
              "ocorrencia_saida_pista             object\n",
              "ocorrencia_dia_extracao            object\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ew5bo-eZMTCZ"
      },
      "source": [
        "**Veja as 3 primeiras entradas do conjunto de dados.**"
      ]
    },
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      "source": [
        "df.head(3)"
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      "execution_count": 30,
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              "   codigo_ocorrencia ocorrencia_classificacao  \\\n",
              "0    201305055424986                 ACIDENTE   \n",
              "1    201605160250139          INCIDENTE GRAVE   \n",
              "2    201805021421302                INCIDENTE   \n",
              "\n",
              "                                     ocorrencia_tipo  \\\n",
              "0                              FALHA DO MOTOR EM VOO   \n",
              "1  COLISÃO COM OBSTÁCULO DURANTE A DECOLAGEM E POUSO   \n",
              "2                                          AERÓDROMO   \n",
              "\n",
              "                           ocorrencia_tipo_categoria ocorrencia_tipo_icao  \\\n",
              "0                FALHA OU MAU FUNCIONAMENTO DO MOTOR               SCF-PP   \n",
              "1  COLISÃO COM OBSTÁCULO DURANTE A DECOLAGEM E POUSO                 CTOL   \n",
              "2                                          AERÓDROMO                 ADRM   \n",
              "\n",
              "   ocorrencia_latitude  ocorrencia_longitude ocorrencia_cidade ocorrencia_uf  \\\n",
              "0              -9.9085              -63.0333         ARIQUEMES            RO   \n",
              "1             -11.2644              -61.2589            CACOAL            RO   \n",
              "2             -11.4956              -61.4508            CACOAL            RO   \n",
              "\n",
              "  ocorrencia_pais  ... ocorrencia_horario investigacao_aeronave_liberada  \\\n",
              "0          BRASIL  ...           11:00:00                            NaN   \n",
              "1          BRASIL  ...           19:19:00                            SIM   \n",
              "2          BRASIL  ...           22:40:00                            SIM   \n",
              "\n",
              "  investigacao_status divulgacao_relatorio_numero  \\\n",
              "0          FINALIZADA                         ***   \n",
              "1               ATIVA          IG-084/CENIPA/2016   \n",
              "2          FINALIZADA                         ***   \n",
              "\n",
              "  divulgacao_relatorio_publicado divulgacao_dia_publicacao  \\\n",
              "0                            NÃO                       NaN   \n",
              "1                            NÃO                       NaN   \n",
              "2                            NÃO                       NaN   \n",
              "\n",
              "  total_recomendacoes total_aeronaves_envolvidas  ocorrencia_saida_pista  \\\n",
              "0                   0                          1                     NÃO   \n",
              "1                   0                          1                     NÃO   \n",
              "2                   0                          1                     NÃO   \n",
              "\n",
              "   ocorrencia_dia_extracao  \n",
              "0               2018-08-28  \n",
              "1               2018-08-28  \n",
              "2               2018-08-28  \n",
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              "      <th>0</th>\n",
              "      <td>201305055424986</td>\n",
              "      <td>ACIDENTE</td>\n",
              "      <td>FALHA DO MOTOR EM VOO</td>\n",
              "      <td>FALHA OU MAU FUNCIONAMENTO DO MOTOR</td>\n",
              "      <td>SCF-PP</td>\n",
              "      <td>-9.9085</td>\n",
              "      <td>-63.0333</td>\n",
              "      <td>ARIQUEMES</td>\n",
              "      <td>RO</td>\n",
              "      <td>BRASIL</td>\n",
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              "      <td>11:00:00</td>\n",
              "      <td>NaN</td>\n",
              "      <td>FINALIZADA</td>\n",
              "      <td>***</td>\n",
              "      <td>NÃO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>NÃO</td>\n",
              "      <td>2018-08-28</td>\n",
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              "      <th>1</th>\n",
              "      <td>201605160250139</td>\n",
              "      <td>INCIDENTE GRAVE</td>\n",
              "      <td>COLISÃO COM OBSTÁCULO DURANTE A DECOLAGEM E POUSO</td>\n",
              "      <td>COLISÃO COM OBSTÁCULO DURANTE A DECOLAGEM E POUSO</td>\n",
              "      <td>CTOL</td>\n",
              "      <td>-11.2644</td>\n",
              "      <td>-61.2589</td>\n",
              "      <td>CACOAL</td>\n",
              "      <td>RO</td>\n",
              "      <td>BRASIL</td>\n",
              "      <td>...</td>\n",
              "      <td>19:19:00</td>\n",
              "      <td>SIM</td>\n",
              "      <td>ATIVA</td>\n",
              "      <td>IG-084/CENIPA/2016</td>\n",
              "      <td>NÃO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>NÃO</td>\n",
              "      <td>2018-08-28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>201805021421302</td>\n",
              "      <td>INCIDENTE</td>\n",
              "      <td>AERÓDROMO</td>\n",
              "      <td>AERÓDROMO</td>\n",
              "      <td>ADRM</td>\n",
              "      <td>-11.4956</td>\n",
              "      <td>-61.4508</td>\n",
              "      <td>CACOAL</td>\n",
              "      <td>RO</td>\n",
              "      <td>BRASIL</td>\n",
              "      <td>...</td>\n",
              "      <td>22:40:00</td>\n",
              "      <td>SIM</td>\n",
              "      <td>FINALIZADA</td>\n",
              "      <td>***</td>\n",
              "      <td>NÃO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>NÃO</td>\n",
              "      <td>2018-08-28</td>\n",
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          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "p_2rj-KqMbtA"
      },
      "source": [
        "**Veja quantos valores únicos existem para a coluna `ocorrencia_classificacao`**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DVtxiIREMnnV",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "73636ccf-f489-4e21-98a9-536697de99dc"
      },
      "source": [
        "df['ocorrencia_classificacao'].unique()"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['ACIDENTE', 'INCIDENTE GRAVE', 'INCIDENTE'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZoUq8qxPMqPj"
      },
      "source": [
        "**Descubra qual Estado possui o maior número de ocorrências com aeronaves civis.**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Fdin50sWM29y",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "72e8e9d5-9847-408a-cda4-26d676a50894"
      },
      "source": [
        "df['ocorrencia_uf'].value_counts()\n",
        "#maior ocorrencia no estado de São Paulo com 1207."
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "SP     1207\n",
              "RJ      498\n",
              "MG      476\n",
              "PR      437\n",
              "RS      350\n",
              "GO      268\n",
              "PA      255\n",
              "MT      244\n",
              "AM      219\n",
              "BA      208\n",
              "SC      160\n",
              "DF      151\n",
              "MS      132\n",
              "PE       88\n",
              "CE       75\n",
              "ES       66\n",
              "MA       63\n",
              "TO       54\n",
              "AC       53\n",
              "RR       50\n",
              "PI       39\n",
              "RO       30\n",
              "PB       20\n",
              "SE       18\n",
              "AL       16\n",
              "RN       15\n",
              "AP       13\n",
              "***       3\n",
              "Name: ocorrencia_uf, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jaE4lKoMNDNG"
      },
      "source": [
        "**Quantos por cento das ocorrências são do tipo `FALHA DO MOTOR EM VOO`?**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MZNDxepbNqFr",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "67f120f4-b1f9-425c-888d-b01984ce5bbe"
      },
      "source": [
        "df.loc[df.ocorrencia_tipo=='FALHA DO MOTOR EM VOO'].shape[0]/df.shape[0]*100\n",
        "#13% das ocorrencias são do tipo falha do motor em voo."
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "13.095238095238097"
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BZCNVc1NOVeb"
      },
      "source": [
        "## Exercício 2\n",
        "\n",
        "Você irá trabalhar agora com os dados da ação BBAS3, do Banco do Brasil na BOVESPA.\n",
        "\n",
        "Na variável `df_bbas3`, foi importado [este arquivo `csv`](https://raw.githubusercontent.com/carlosfab/dsnp2/master/datasets/BBAS3.SA.csv), onde o *index* do *DataFrame* representa os valores da ação para determinado dia. Responda as perguntas abaixo."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4XZI_FjDPFsR"
      },
      "source": [
        "# importar pandas\n",
        "import pandas as pd\n",
        "\n",
        "# importar o csv com dados da BB\n",
        "df_bb = pd.read_csv(\"https://raw.githubusercontent.com/carlosfab/dsnp2/master/datasets/BBAS3.SA.csv\",\n",
        "                       index_col=\"Date\")"
      ],
      "execution_count": 42,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "j5gGguY3P67Q"
      },
      "source": [
        "**Veja as 5 primeiras entradas da variável `df_bb`.**"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_bb.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "fFrS4TmQIpdt",
        "outputId": "4289df52-ea64-4281-bbf6-fd68f636875d"
      },
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                 Open       High        Low      Close  Adj Close      Volume\n",
              "Date                                                                         \n",
              "2019-05-06  49.470001  49.669998  49.180000  49.369999  46.886795   6314800.0\n",
              "2019-05-07  49.080002  49.680000  48.220001  49.490002  47.000763  10846100.0\n",
              "2019-05-08  49.500000  50.840000  49.500000  50.590000  48.045422  14459600.0\n",
              "2019-05-09  50.910000  51.259998  50.119999  51.029999  48.463291  15377500.0\n",
              "2019-05-10  51.099998  51.189999  49.860001  50.160000  47.637051   8975300.0"
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              "      <td>49.470001</td>\n",
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    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "O3tTLDfTQTGZ"
      },
      "source": [
        "**Quais são os valores da ação para o dia 04 de outubro de 2019?**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kPSOenAuQj81",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ae3ce240-dfbd-413a-ffdb-0dc1755b46f7"
      },
      "source": [
        "df_bb.loc['2019-10-04']"
      ],
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Open         4.537000e+01\n",
              "High         4.560000e+01\n",
              "Low          4.462000e+01\n",
              "Close        4.560000e+01\n",
              "Adj Close    4.444867e+01\n",
              "Volume       7.228200e+06\n",
              "Name: 2019-10-04, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PRZtV761Qr0-"
      },
      "source": [
        "**Qual a média do Volume financeiro movimentado em todo o período?**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "n-vZleQPEGey",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "60e371e3-7975-4084-ed64-61bf58fbcd7d"
      },
      "source": [
        "df_bb.Volume.mean()"
      ],
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "14052947.368421054"
            ]
          },
          "metadata": {},
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_pO0tCV1EdD0"
      },
      "source": [
        "## Exercício 3\n",
        "\n",
        "Você irá trabalhar agora com os dados do projeto +BIKE, usado em aulas passadas.\n",
        "\n",
        "Na variável df_bike, foi importado [este arquivo csv](http://dl.dropboxusercontent.com/s/yyfeoxqw61o3iel/df_rides.csv).\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YFvJfTuVE0da",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "7f9add05-e840-479b-a9b9-e6bfbed370fe"
      },
      "source": [
        "# importar pandas\n",
        "import pandas as pd\n",
        "\n",
        "# importar o csv com dados da BBAS3\n",
        "df_bike = pd.read_csv(\"http://dl.dropboxusercontent.com/s/yyfeoxqw61o3iel/df_rides.csv\")\n",
        "\n",
        "# ver as primeiras entradas\n",
        "df_bike.head()"
      ],
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  user_gender user_birthdate user_residence   ride_date time_start  time_end  \\\n",
              "0           M     1971-06-08            NaN  2018-01-01   06:05:18  06:21:33   \n",
              "1           M     1989-02-11             DF  2018-01-01   06:27:01  06:32:17   \n",
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              "4           M     1969-03-03             DF  2018-01-01   06:58:56  17:40:04   \n",
              "\n",
              "                     station_start  \\\n",
              "0                11 - Rodoviária 2   \n",
              "1         26 - Ministério da Saude   \n",
              "2                11 - Rodoviária 2   \n",
              "3  10 - Ministério dos Transportes   \n",
              "4                   15 - Brasil 21   \n",
              "\n",
              "                                         station_end  ride_duration  ride_late  \n",
              "0                            41 - Instituto de Artes      16.250000        0.0  \n",
              "1  28 - CNMP - Conselho Nacional do Ministério Pú...       5.266667        0.0  \n",
              "2                            43 - Biblioteca Central      15.400000        0.0  \n",
              "3                                     6 - Rodoviária       5.866667        0.0  \n",
              "4                                  11 - Rodoviária 2     641.133333        1.0  "
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              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-47f17ce8-6435-4f66-8849-7debdfae7292 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-47f17ce8-6435-4f66-8849-7debdfae7292');\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": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sj3lwZctE7KP"
      },
      "source": [
        "**Qual a porcentagem de valores ausentes para a coluna `user_gender`?**\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g8GJ7kgLFEbr",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "154110f3-d2a7-4482-c616-bdc965aa0b25"
      },
      "source": [
        "df_bike.user_gender.isnull().sum()/df_bike.shape[0]"
      ],
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.0013782446175371187"
            ]
          },
          "metadata": {},
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oDVOu-XpFZYI"
      },
      "source": [
        "**Preencha a coluna `user_gender` com o valor mais frequente.**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7f9WWlD6FZnJ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e5877a96-d6da-41a6-be35-064da0b6ad42"
      },
      "source": [
        "df_bike.user_gender.value_counts()"
      ],
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "M    212608\n",
              "F     74318\n",
              "Name: user_gender, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_bike=df_bike.fillna({'user_gender':'M'})"
      ],
      "metadata": {
        "id": "kM6rjQ7_TvmN"
      },
      "execution_count": 60,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_bike.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qW_k7fa6T66U",
        "outputId": "1497ccf2-ee07-4c50-99cd-001223bc911f"
      },
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "user_gender            0\n",
              "user_birthdate         1\n",
              "user_residence    179905\n",
              "ride_date              0\n",
              "time_start             0\n",
              "time_end           43285\n",
              "station_start          0\n",
              "station_end            0\n",
              "ride_duration      73174\n",
              "ride_late          73174\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ckDXwzIzF7XT"
      },
      "source": [
        "**Plote u boxplot para a coluna `ride_duration`.**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xIluDO2wGGE6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        },
        "outputId": "2941ffb3-1cbb-4b10-d90d-aed0d1db0ba1"
      },
      "source": [
        "df_bike.ride_duration.plot(kind='box');"
      ],
      "execution_count": 62,
      "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"
          }
        }
      ]
    }
  ]
}