Florest_TDCSPv2.ipynb

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    "colab": {
      "name": "Florest_TDCSP.ipynb",
      "version": "0.3.2",
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      "include_colab_link": true
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        "version": 3
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      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.7.2"
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    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/triatebr/aprenda-python/blob/master/Florest_TDCSPv2.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9al4UdJTdo2l",
        "colab_type": "text"
      },
      "source": [
        "![logos](https://img.freepik.com/free-vector/telemarketing-background-design_1212-238.jpg?size=338&ext=jpg)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-JsLybLYdo2s",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#importando bibliotecas\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import datetime \n",
        "%matplotlib inline"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qa470cr5do20",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import warnings\n",
        "warnings.filterwarnings('ignore')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Pu_Qyks1epmz",
        "colab_type": "code",
        "outputId": "df8e0478-3ac5-4b30-f37f-544675250389",
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
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              "ok": true,
              "headers": [
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                  "content-type",
                  "application/javascript"
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              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 74
        }
      },
      "source": [
        "\n",
        "from google.colab import files\n",
        "uploaded = files.upload()"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-ca431331-f71d-4572-b8bc-48f58ec75b75\" name=\"files[]\" multiple disabled />\n",
              "     <output id=\"result-ca431331-f71d-4572-b8bc-48f58ec75b75\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Saving bank-full_.csv to bank-full_.csv\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fwZVwJgMdo25",
        "colab_type": "text"
      },
      "source": [
        "**Dados utilizados**\n",
        "\n",
        "Para o exempçlo de árvore de descisão iremo utilizar um [dataset de Marketing](https://archive.ics.uci.edu/ml/datasets/Bank+Marketing). Ele demonstra valores de campanha de telemarketing de banco portugues. O objetivo e prever de cliente assinará um termo de deposito."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7fm4xI4sdo26",
        "colab_type": "code",
        "outputId": "9b6856f3-dd2b-407c-9440-5ca434b638c3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "dados = pd.read_csv('bank-full_.csv', delimiter=';')\n",
        "dados.head()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>job</th>\n",
              "      <th>marital</th>\n",
              "      <th>education</th>\n",
              "      <th>default</th>\n",
              "      <th>balance</th>\n",
              "      <th>housing</th>\n",
              "      <th>loan</th>\n",
              "      <th>contact</th>\n",
              "      <th>day</th>\n",
              "      <th>month</th>\n",
              "      <th>duration</th>\n",
              "      <th>campaign</th>\n",
              "      <th>pdays</th>\n",
              "      <th>previous</th>\n",
              "      <th>poutcome</th>\n",
              "      <th>y</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>58</td>\n",
              "      <td>management</td>\n",
              "      <td>married</td>\n",
              "      <td>tertiary</td>\n",
              "      <td>no</td>\n",
              "      <td>2143</td>\n",
              "      <td>yes</td>\n",
              "      <td>no</td>\n",
              "      <td>unknown</td>\n",
              "      <td>5</td>\n",
              "      <td>may</td>\n",
              "      <td>261</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>no</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>44</td>\n",
              "      <td>technician</td>\n",
              "      <td>single</td>\n",
              "      <td>secondary</td>\n",
              "      <td>no</td>\n",
              "      <td>29</td>\n",
              "      <td>yes</td>\n",
              "      <td>no</td>\n",
              "      <td>unknown</td>\n",
              "      <td>5</td>\n",
              "      <td>may</td>\n",
              "      <td>151</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>no</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>33</td>\n",
              "      <td>entrepreneur</td>\n",
              "      <td>married</td>\n",
              "      <td>secondary</td>\n",
              "      <td>no</td>\n",
              "      <td>2</td>\n",
              "      <td>yes</td>\n",
              "      <td>yes</td>\n",
              "      <td>unknown</td>\n",
              "      <td>5</td>\n",
              "      <td>may</td>\n",
              "      <td>76</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>no</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>47</td>\n",
              "      <td>blue-collar</td>\n",
              "      <td>married</td>\n",
              "      <td>unknown</td>\n",
              "      <td>no</td>\n",
              "      <td>1506</td>\n",
              "      <td>yes</td>\n",
              "      <td>no</td>\n",
              "      <td>unknown</td>\n",
              "      <td>5</td>\n",
              "      <td>may</td>\n",
              "      <td>92</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>no</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>33</td>\n",
              "      <td>unknown</td>\n",
              "      <td>single</td>\n",
              "      <td>unknown</td>\n",
              "      <td>no</td>\n",
              "      <td>1</td>\n",
              "      <td>no</td>\n",
              "      <td>no</td>\n",
              "      <td>unknown</td>\n",
              "      <td>5</td>\n",
              "      <td>may</td>\n",
              "      <td>198</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>no</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   age           job  marital  education  ... pdays  previous poutcome   y\n",
              "0   58    management  married   tertiary  ...    -1         0  unknown  no\n",
              "1   44    technician   single  secondary  ...    -1         0  unknown  no\n",
              "2   33  entrepreneur  married  secondary  ...    -1         0  unknown  no\n",
              "3   47   blue-collar  married    unknown  ...    -1         0  unknown  no\n",
              "4   33       unknown   single    unknown  ...    -1         0  unknown  no\n",
              "\n",
              "[5 rows x 17 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zLu8KgCVdo3E",
        "colab_type": "code",
        "outputId": "995b3bb7-192d-4ecc-9b8d-79e0ec8638ed",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 391
        }
      },
      "source": [
        "#verificar as colunas utlizadas\n",
        "dados.info()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 45211 entries, 0 to 45210\n",
            "Data columns (total 17 columns):\n",
            "age          45211 non-null int64\n",
            "job          45211 non-null object\n",
            "marital      45211 non-null object\n",
            "education    45211 non-null object\n",
            "default      45211 non-null object\n",
            "balance      45211 non-null int64\n",
            "housing      45211 non-null object\n",
            "loan         45211 non-null object\n",
            "contact      45211 non-null object\n",
            "day          45211 non-null int64\n",
            "month        45211 non-null object\n",
            "duration     45211 non-null int64\n",
            "campaign     45211 non-null int64\n",
            "pdays        45211 non-null int64\n",
            "previous     45211 non-null int64\n",
            "poutcome     45211 non-null object\n",
            "y            45211 non-null object\n",
            "dtypes: int64(7), object(10)\n",
            "memory usage: 5.9+ MB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uEctmVI4do3J",
        "colab_type": "code",
        "outputId": "902f286e-59c9-4034-f31e-7637527475d3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "#Nº de linhas e colunas\n",
        "dados.shape"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(45211, 17)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6LMxWOcqdo3N",
        "colab_type": "text"
      },
      "source": [
        "![logos](https://psucd8.files.wordpress.com/2011/10/outlierscatterplot_10001.gif)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BTJOybFhdo3P",
        "colab_type": "text"
      },
      "source": [
        "**Processo de detecção de OUTLIERS**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1kOrP3Pvdo3Q",
        "colab_type": "text"
      },
      "source": [
        "Em estatística, **outlier** , valor aberrante ou valor atípico, é uma observação que apresenta <p> um grande afastamento das demais da série (que está \"fora\" dela), ou que é inconsistente. <p>A existência de outliers implica, tipicamente, em prejuízos a interpretação dos resultados dos **testes estatísticos** aplicados às amostras."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IJGccQfZdo3R",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#Lista com as colunas numéricas que não são necessariamente contínus\n",
        "numerical_columns = [col for col in dados.columns if (dados[col].dtype=='int64' or dados[col].dtype=='float64')]"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jwH9s3Ardo3U",
        "colab_type": "code",
        "outputId": "39fc7bb9-05ac-4100-f631-caa1f63bf999",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "numerical_columns"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['age', 'balance', 'day', 'duration', 'campaign', 'pdays', 'previous']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eRDI9J6bdo3Y",
        "colab_type": "code",
        "outputId": "dad88a01-3e4e-4921-ecd7-e33424f7a6ec",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 173
        }
      },
      "source": [
        "dados[numerical_columns].describe().loc[['min', 'max', 'mean', '50%'],:]"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>balance</th>\n",
              "      <th>day</th>\n",
              "      <th>duration</th>\n",
              "      <th>campaign</th>\n",
              "      <th>pdays</th>\n",
              "      <th>previous</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>18.00000</td>\n",
              "      <td>-8019.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>95.00000</td>\n",
              "      <td>102127.000000</td>\n",
              "      <td>31.000000</td>\n",
              "      <td>4918.00000</td>\n",
              "      <td>63.000000</td>\n",
              "      <td>871.000000</td>\n",
              "      <td>275.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>40.93621</td>\n",
              "      <td>1362.272058</td>\n",
              "      <td>15.806419</td>\n",
              "      <td>258.16308</td>\n",
              "      <td>2.763841</td>\n",
              "      <td>40.197828</td>\n",
              "      <td>0.580323</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>39.00000</td>\n",
              "      <td>448.000000</td>\n",
              "      <td>16.000000</td>\n",
              "      <td>180.00000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           age        balance        day  ...   campaign       pdays    previous\n",
              "min   18.00000   -8019.000000   1.000000  ...   1.000000   -1.000000    0.000000\n",
              "max   95.00000  102127.000000  31.000000  ...  63.000000  871.000000  275.000000\n",
              "mean  40.93621    1362.272058  15.806419  ...   2.763841   40.197828    0.580323\n",
              "50%   39.00000     448.000000  16.000000  ...   2.000000   -1.000000    0.000000\n",
              "\n",
              "[4 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Qmm4gur2do3c",
        "colab_type": "text"
      },
      "source": [
        "Repara-se que há no **Balance** um valor de '-8019' ! Estranho neh<p>\n",
        "    Esses valor pode atrapalhar todo o processo de **aprendizado de máquina**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rU-q7hEmdo3d",
        "colab_type": "code",
        "outputId": "cc4502de-33c5-4abe-ea1b-ecccf22856d2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 80
        }
      },
      "source": [
        "dados[dados['balance'] == dados['balance'].min ()]"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>job</th>\n",
              "      <th>marital</th>\n",
              "      <th>education</th>\n",
              "      <th>default</th>\n",
              "      <th>balance</th>\n",
              "      <th>housing</th>\n",
              "      <th>loan</th>\n",
              "      <th>contact</th>\n",
              "      <th>day</th>\n",
              "      <th>month</th>\n",
              "      <th>duration</th>\n",
              "      <th>campaign</th>\n",
              "      <th>pdays</th>\n",
              "      <th>previous</th>\n",
              "      <th>poutcome</th>\n",
              "      <th>y</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>12909</th>\n",
              "      <td>26</td>\n",
              "      <td>blue-collar</td>\n",
              "      <td>single</td>\n",
              "      <td>secondary</td>\n",
              "      <td>yes</td>\n",
              "      <td>-8019</td>\n",
              "      <td>no</td>\n",
              "      <td>yes</td>\n",
              "      <td>cellular</td>\n",
              "      <td>7</td>\n",
              "      <td>jul</td>\n",
              "      <td>299</td>\n",
              "      <td>3</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>no</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       age          job marital  education  ... pdays  previous poutcome   y\n",
              "12909   26  blue-collar  single  secondary  ...    -1         0  unknown  no\n",
              "\n",
              "[1 rows x 17 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pbGDwYOAdo3h",
        "colab_type": "text"
      },
      "source": [
        "Vamos apagar o registro '12909' do conjunto de dados."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aTBVDvvbdo3i",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "dados.drop(dados.index[12909], inplace=True)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aM0peZ39do3k",
        "colab_type": "text"
      },
      "source": [
        "![logos](https://mktes.files.wordpress.com/2014/09/curso-de-web-design-e28093-microcamp-curitiba-centro-aponta-as-vantagens-da-segmentac3a7c3a3o-de-mercado.jpg?)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "biKxEMGado3l",
        "colab_type": "text"
      },
      "source": [
        "Após a importação dos dados (.csv), iremos dividir o arquivo em 2 partes.<p>\n",
        "    Pois assim, deixaremos um montante de registros para ser utilizado no modelo de **IA** após o término.<p>\n",
        "        Ao todo temos 45211 registros, para o desenvolvimento da IA, usaremos 30000 e deixaremos o restante para a 2ª fase do processo\n",
        "        "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "adaQIDJHdo3m",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#vamos começar embaralhando o conjunto de dados, pois ele pode estar ordenado de alguma forma\n",
        "dados = dados.sample(frac=1)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eix2nPR6do3o",
        "colab_type": "code",
        "outputId": "c1cb6c2f-baa9-4da1-f6e7-01510066c446",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "#1ª segmentação \n",
        "dados = dados.head(30000)\n",
        "dados.shape"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(30000, 17)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YkgiWktHdo3s",
        "colab_type": "code",
        "outputId": "078842f5-2dbb-4c16-dc1e-13ca1f6d9059",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "#2ª segmentação\n",
        "df = dados.tail(25211)\n",
        "df.shape"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(25211, 17)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rNHTx_Dddo3x",
        "colab_type": "text"
      },
      "source": [
        "Usaremos para o desenvolvimento do modelo de **IA** o conjunto 'dados'<p>\n",
        "    O dataframe 'df' será utilizado em 2º momento"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "g-lL-4aVdo30",
        "colab_type": "text"
      },
      "source": [
        "Como podemos perceber os dados estão distribuidos de varias maneiras, temos variaveis categoricas, representadas como objetos e variaveis numericas. Varios dados são desconhecidos, porém estão salvos como 'unknown'."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zgY4edcado31",
        "colab_type": "text"
      },
      "source": [
        "**análise exploratoria**\n",
        "\n",
        "Antes de prevemos os valores vamos fazer uma análise exploratoria, vamos verificar qual idade e qual escolaridade tem maior chance de fechar o deposito."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "paleS3Bbdo32",
        "colab_type": "code",
        "outputId": "2b86ba9b-dec5-4fcb-d579-2b4b2e3185db",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 225
        }
      },
      "source": [
        "idade= sns.FacetGrid(dados, hue=\"y\", aspect=3);\n",
        "idade.map(sns.kdeplot, \"age\").add_legend();\n",
        "idade.set(xlim=(0, 85));"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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VsG9ZIZ7GcEnjqky8pwtf3dWZFjER/HfaJrq9OIOXpm7k8ImMQjuXiJQcnsll\nnYDR3spBBa5IcXNlw/KxUL83VKyTb/jSncnsST7Fte1iij438S3+ARB/G4xYCX2eg/0r4MNLYNxf\n4ODaQj1Vh7hKfHJbByY/0I0ejaJ5f/Y2ur44g4cnrGTF7qOUtOFyInJ+jDFNga3AdGvtFq/lUdJ+\nqGgMrpR5676Hr2+FIeOdBv35ePTrVUxde5Clf+ut8YtStDJOwKL3YcFbkHHcWXzkoicLpYfu2bYf\nTmXsgp1MXLaXk5kuWtSMYEiHWPo1r0alckGFfj4RH+aTrUwKVOAaY/oBbwD+wEfW2hfP2h8MfAq0\nA5KAGzxtIvoALwJBQCbwmLV2Rl7nUoErZd6Y/nB8H4xYAX55F6wnM7Jp/8JvDGpVgxevaVlMCYrP\nS0uGhW87xW72KWg5GHo8ClH1Cv1UqRnZfLd8L58u3MWWQ6n4+xk6143ishbV6dWkClUrhBT6OUV8\njArcHAOM8Qc2A32AvcBSYIi1dv0ZMfcCLa21dxtjBgNXWWtv8PRAS7TW7jfGNAemWWvznCWjAlfK\ntAOr4YPucOnzTi/SfExctpdHv17FxLs7E1+nUjEkKHKG1MMw/3VY+hG4MqH5NdD90QL1bT5X1lrW\nHzjOlDUHmLLmIDuOnASgTlQYHeIq0TEuira1K1InKkyLSIicG598wxSkwO0MPGOt7et5/iSAtfbf\nZ8RM88QsNMYEAAeBaHvGwY3zEykJqG6tzXVmgQpcKdN+uA/Wfuu0BgutmG/44FELSTyewYxHeupD\nXbwn9ZAzbGHpaGdVtCaXQ4/HoHrR/FXBWsvGgyeYv/UIi7Yns3Rn8unOCxVCAmgRE0HLmEha1oyg\nZa1IakSE6P0hkjuffHMUZCWzmsCeM57vBTrmFmOtzTbGpABRwJEzYq4BludU3BpjhgPDAWJjYwuc\nvEipcjIJ1kyEVkMKVNzuTkpj0fZkHuvbSB/e4l3hVeDS56DrSFj0LiwZBRsmQcP+zmppNdsV6umM\nMTSpXoEm1StwR/e6uN2WzYdOsHL3MVbvS2H13mN8OGc72W7nHkpUuSBaxETQvUE0/ZpXo2ZkaKHm\nIyKlT7Es1WuMaQa8BFya035r7ShgFDh3cIsjJ5Fit3wsZKdDx7sKFD5x+V6MgavaqPetlBDloqDX\n087wmiWjYOE7TteFOt2dbfX7gF/hN+fx8zM0rlaBxtUqMNizLT3LxcaDJ1iz9xir96awfPdRnpu8\nnucmr6dVTAT9mldnSIdaRIZpwpqILypIgbsPqHXG8xjPtpxi9nqGKETgDEfAGBMDfAfcYq3ddsEZ\ni5RGrmznz7txPaBKk3zD0zLthVdlAAAgAElEQVSz+XzRLi5qGE0N3Y2SkiY0Eno+Dp3ugYQxzmS0\nL6+Hyg2h073QajAEFu3/25BAf1rXiqR1rcjT27YfTmXquoNMXXuQl6Zu5L1ZWxnRqwG3dK5DUIC6\nYor4koK845cCDYwxcZ6l1wYDk86KmQTc6nl8LTDDWmuNMZHAT8AT1tr5hZW0SKmz6Sc4vhc63l2g\n8HFL9pB8MpN7L65fxImJXIDg8tD1QRi5Gq7+EAJCYPJIeK0ZzPyXM0mtGNWNDufei+oz6f5uTB3Z\nndaxFXn+pw30eW02P685oF67IiWEMaaOMWaDMeZDY8w6Y8wvxphQY0xrY8wiY8xqY8x3xpj8x/Pl\ndo4Ctgm7DHgdp03YGGvtC8aYZ4EEa+0kY0wI8BnQBkgGBltrtxtjngKeBM5s9HuptfZQbufSJDMp\nkz4eACm7nYb6+bQGy8h20eM/M6kTVY4Jd3UupgRFCoG1sHOeM3Rh88/gHwwtroP426FmW2cFtWI2\na9Mh/jVlA5sTU7mjWxx/G9BEY9rF1+T6H77OEz+9DrQu5POt3PnigJF5JmRMHZzFIOKttSuNMV/h\n3Cx9HHjAWjvbU2dWsNbmeazcFGgMrrV2CjDlrG1/P+NxOnBdDq97Hnj+fBITKTMOroVd85yVovIp\nbgG+WbaPxOMZvHxdq2JITqQQGQNx3Z2vI1ucQnf1V7Dyc6ja3FmausW1BZpkWVgualSFbvUr89zk\n9Xw0bwfZbss/Lm+qIlfE+3ZYa1d6Hi8D6gGR1trZnm1jga/P9+DFMslMxKct+QACQqHNTfmGZrvc\nvDd7K61qRdKtfuViSE6kiFRuAJe/Dn2ehbUTIeFjmPIoTPsrNLjUubPbsB8EFv1CDgH+fjwzqBkB\n/n6MnreDbLebZwc1x89PRa74tvzutBaxM7tquYDI3ALPhwpckaKUluzcwWp5A4Tlv1DDpFX72ZN8\nir8PbKY7TFI2hFRwhijE3w77Vzjvh7XfwMbJEFwBGvSBRpc5/4ZEFFkaxhieGtCEAH/DB7O3k+2y\n/OuqFipyRUqOFOCoMaa7tXYucDMwO5/X5EoFrkhRWv5pgVuDud2Wd2dto3G18vRqXKUYkhMpZjXa\nOF+XPg875zp9oTdPdQpevwCo3RXq9oS4nlC9NfgX7keUMYYn+jUm0M+Pt2dupXnNCG7qVLtQzyEi\nF+RW4H1jTBiwHbjtfA+kAlekqLiynSVO63SHqs3yDZ+27iBbD6Xy1pA2uqskZZufP9S9yPlyu2Bv\nAmyaAlt+henPOjFB5aFOV6e1XlwPqNKsUHrsGmN45NKGLN99lJd+3kifplWpWqHoh0mIyP9Ya3cC\nzc94/vIZuzsVxjkK1EWhOKmLgpQZG36ECTfBDZ87S5vmIcvlpu9rczAGfnmoJ/4qcMVXpR527u7u\nnAs75kDSVmd7aCWo081T8PZ0xvhewDCeHUdO0vf1OfRuUoV3byzcldhEShif/EDRHVyRorL4A4io\n5Sxnmo/PFu5i+5GTjBkar+JWfFt4NDS/2vkCSNnnFLvbZzsF7wZPG/by1aFhX2g0wCl6z3GyWlzl\ncoy4pD4v/7KZ39Yn0rtp1UL+RkTEm1TgihSFxHXOh3Lvf+Y7jjD5ZCav/7aZ7g0qc3Ejjb0V+YOI\nms7KaK0GO312j+5wCt1tM50xvMs+gaBwpzND/G3OkKAC3tkd3qMek1bt5+8/rKVzvSjKBesjUaSs\n0NqFIkVh8fvOqk5tb8k39PXfNnMy08XTA9WbUyRPxkCluk4/3evHwuPb4cZvnJZj22fC2MvhnQ7O\n0sHpKfkeLijAj39f3YL9Kem88svmos9fRIqNClyRwpZ6CFZNgNZ/ybc12ObEE3yxeDc3doylYdXy\nxZSgSBkREAwNejv9dh/eAFe+77Qem/p/8EZrWDwKXFl5HqJd7Urc2DGWTxbsYNvh1GJKXESKmgpc\nkcK25ENwZUKn+/IMs9by3OT1lAvyZ2TvhsWUnEgZFRgKrYfAndPhzplQrTn8/Bi82xk2TnGGN+Ri\nZO+GBPj58fH8HcWYsIgUJRW4IoUpM81pDdboMqhcP8/QmZsOMXfLER7s3ZBK5YKKKUERH1CzLdwy\nCYZMcIY1jB8CXw/NddhCdPlgrmhdg2+W7eNYWmbx5ioiRUIFrkhhWvUlnEqGLvfnGZblcvP85A3U\nrVyOm9VoXqTwGQON+sE9C6DXP5y2fR/0cFZTy8Gw7nGcynLx5ZLdxZyoiBQFFbgihcXtgoXvQM12\nENs5z9Df24I9NbAJQQF6G4oUGf9A6P4w3DbFGY87+lKnhd9ZQxYaV6tAt/qVGbtgJ5nZbi8lK+Ib\njDHPGmNGnvH8BWPMg8aYx4wxS40xq40x//TsK2eM+ckYs8oYs9YYc0NBzqGeKCKFZdPPkLwdrvsk\nzzZFR9UWTKT4xXaCu+fBd3fDz4/D0V3Q94U/vFeHdYvjtk+WMmXNAa5sU9OLyYoUk2ciXgdaF/JR\nV/JMysh8YsYA3wKvG2P8gMHAX4FeQAecxSkmGWN6ANHAfmvtAABjTERBktCtI5HCsuAtiIyFxnmv\nWvbab5tJzchWWzCR4hZWCYaMh453w6J3YPJI5y8vHj0bRlMvuhwfzdtOSVvlU6Qs8SzVm2SMaQNc\nCqwA2p/xeDnQGGgArAH6GGNeMsZ0t9bm3wMQ3cEVKRx7lsKeRdDvpTwXdvhfW7Daagsm4g1+ftDv\nRQgqB3NfcSaGXvke+Afg52e4vVscf/tuLUt2JNOxbpS3sxUpWvnfaS1KHwFDgWo4d3R7Af+21n5w\ndqAxpi1wGfC8MWa6tfbZ/A6uO7gihWHeqxBaEdrclGvI723BwoL8eaiP2oKJeI0x0Ovvztear2Di\nbafv5F7dJobIsEBGz1PLMJEi9h3QD+fO7TTP1+3GmHAAY0xNY0wVY0wNIM1a+znwX6BtQQ6uO7gi\nFypxPWyaAhc9CcHhuYbN2nyYuVuO8NSAJmoLJlISdH/EWXFw2l+dr/4vERrkz40dY3l31jYOpJyi\nekSot7MUKZOstZnGmJnAMWutC/jFGNMEWOgZvpcK3ATUB/5rjHEDWcA9BTm+7uCKXKh5r0FgOegw\nPNcQt9vyn6mbiK0Uxi2d6xRfbiKSt873Qef7neW1F74LwHXtamEt/LByv5eTEym7PJPLOgGjf99m\nrX3DWtvC89XZWrvNWjvNWtvSWtvaWtveWptQkOOrwBW5EMk7YO1EaH97nsvyTl5zgA0HjvNwn4Zq\nCyZS0vR5Dppc7tzF3fAjdSqXo21sJN8t36fJZiJFwBjTFNgKTLfWbimKc+iTVuRCzH8D/ALyXJY3\ny+Xm1V820bhaeQa1qlGMyYlIgfj5wVWjnB7W39wBexO4qm0MmxJPsP7AcW9nJ1LmWGvXW2vrWmsf\nKapzqMAVOV8nDsLKL6D1jVCheq5hXyfsZWdSGo9e2gg/P7UFEymRgsKcFmLhVWHCzVxeL5BAf8N3\ny/d5OzMROQ8qcEXO18K3wZ0NXUfkGpKe5eKN6ZtpGxtJryZa1EGkRAuPhus/hbQkIqfex8UNK/PD\nqv243BqmIFLaqMAVOR8nk2DpGGh2NVSqm2vYZwt3kXg8g8f6NtaiDiKlQY3W0P9F2DaDR0Mnc/hE\nBvO3HvF2ViJyjlTgipyPBW9AVhr0eCzXkBPpWbw7ayvdG1Smcz01jBcpNdrdBi2up8GGt+gdspHv\nVmiYgkhpowJX5FylHoIlH0KL66BK41zDPpy7g6NpWTzeN/cYESmBjIGBr2GiGvBawFssW7uBkxnZ\n3s5KRM6BClyRczXvdchOh57/l2tIUmoGo+dup3/zarSIiSjG5ESkUASHw/VjCbOneI53+WWdeuKK\nlCYFKnCNMf2MMZuMMVuNMU/ksD/YGDPBs3+xMaaOZ3uUMWamMSbVGPN24aYu4gXHD0DCaGg1BCrX\nzzXs3VnbOJXl4pFLtSSvSKlVpQmm7wv09F/NiTnveTsbETkH+Ra4xhh/4B2gP9AUGOJp0HumYcBR\na2194DXgJc/2dOBp4NFCy1jEm+a96nROyGPs7f5jp/hs0S6uaRtD/SrlizE5ESlsfu2Hsa1iV244\n+iFJO1Z6Ox0RKaCC3MHtAGy11m631mYC44Erzoq5AhjreTwR6GWMMdbak9baeTiFrkjplrIXln3i\n9L2tFJdr2JvTt4CFB3s3KL7cRKRoGIMZ9DYnCIVv7oTsDG9nJCIFUJACtyaw54znez3bcoyx1mYD\nKUCBp40bY4YbYxKMMQmHDx8u6MtEitecl8HaPO/ebj+cytfL9vKXjrHEVAwrxuREpKjUjavLW+Ej\niUrdDDOe83Y6IlIAJWKSmbV2lLU23lobHx0d7e10RP7s0EZY/inE3w6RtXINe+XXzQQH+HHfxbmP\nzxWR0qda+yv5PLsXdsHbsH22t9MRkXwUpMDdB5z5iR7j2ZZjjDEmAIgAkgojQZES4denISg8z84J\na/el8NPqA9zeNY7o8sHFmJyIFLXLW1XnhewbORYaC9/fA6eOejslEclDQQrcpUADY0ycMSYIGAxM\nOitmEnCr5/G1wAxrrdY2lLJh20zY8gv0eBTK5T7y5uVfNhERGsidPXJf2UxESqeYimE0q12dp/0e\nhNREmPyQM2RJREqkfAtcz5ja+4FpwAbgK2vtOmPMs8aYQZ6w0UCUMWYr8DBwupWYMWYn8Cow1Biz\nN4cODCIll9sFvzwFkbWh4125hi3ZkcysTYe556J6RIQGFmOCIlJcBrWuweSkahyOfxjWfQerJ3g7\nJRHJRUBBgqy1U4ApZ237+xmP04HrcnltnQvIT8S7Vn4BiWvh2o8hIOdhB9Za/jN1I1XKB3Nr5zrF\nm5+IFJvLWlTnnz+u5xNzJY/FzoWfHoXYTlCxjrdTE5GzlIhJZiIlUkYqzHgeYjpAs6tyDZu16TAJ\nu47yQK8GhAb5F2OCIlKcKocH07V+ZX5YnYi96n1nSd9v73L+0iMiJYoKXJHczH3FGWvX91/OB1kO\n3G7Lf6ZtIrZSGDfE595dQUTKhita1WDv0VMsPx4Bl70MexY5C8CISImiAlckJ4nrYMGbzqIOtdrn\nGjZ5zQE2HDjOw30aEhSgt5NIWXdps6oEB/jx46r90PJ6aHY1zHoR9i3zdmoicgZ9Ioucze2GH0dC\nSARc+nyuYVkuN6/9uplGVctzeasaxZigiHhL+ZBAejWpwqRV+8l0WRj4KoRXhW+HQ+ZJb6cnIh4q\ncEXOtmwM7F3iDE0Iq5Rr2KcLd7HjyEke69sIf7+chzCISNlzXXwtkk9m8uv6RAitCFe9D0nbYNrf\nvJ2aiHiowBU50/ED8Ns/Ia4ntLwh17BDJ9J5/dfN9GwYTa8mVYoxQRHxth4NoqkZGcr4pbudDXE9\noMsDsOxj2Dgl7xeLSLFQgStypp8fB1cmDHwt14llAC/9vIn0bBf/uLwpJo84ESl7/P0M18fXYu6W\nI+xOSnM2XvIUVGsBk+6HE4neTVBEVOCKnLb2W9gwCXo8BlH1cg1btiuZb5bv5Y7udakbHV6MCYpI\nSXF9+xj8DExI8NzFDQiGqz9yxuFOul+rnIl4mQpcEYCjO+HHByGmPXR9MNcwl9vy9x/WUT0ihPsv\nrl98+YlIiVI9IpSLG1Xhq4S9ZLnczsYqjaHPs87S3ks/8m6CIj5OBa6IKwsmDgMMXDMa/HNfanfc\nkt2s23+cvw1oQrngAi0EKCJl1JAOsRw+kcGMjYf+t7HDcKjf21ni+/Am7yUn4uNU4IrMfAH2JcCg\nN6Bi7VzDEo+n899pm+hcN4oBLaoXY4IiUhJd1CiaqhWCGbdk9/82GgNXvANB5eCbOyA7w3sJivgw\nFbji27bNhHmvQ9tb81yO1+W2PDh+BZnZbp6/qrkmlokIAf5+3BBfi9mbD7Pv2Kn/7ShfDQa9BQdX\nw+SHNB5XxAtU4IrvOroTvr0TohtBvxfzDH1rxhYWbU/muSubU08Ty0TE4/r2zhLdE5bu+eOOxgOg\n5xOw8guY95oXMhPxbSpwxTedOgpfXOeMv73+MwgKyzV0wbYjvDF9C1e3rcm17WKKMUkRKeliKobR\ns2E0XyzaRWpG9h93XvQENL8Wpv8T1v/gnQRFfJQKXPE92Rkw/kbnDu7gLyG6Ya6hR1IzGDl+JXGV\ny/HcFc2LL0cRKTUe7NWApJOZjJ674487fh+PG9MBvr0L9i33ToIiPkgFrvgWtxu+vxd2zYcr34M6\nXXMNzXK5eWjCSo6dyuLtIW3VNUFEctQmtiJ9m1Xlw7nbST6Z+cedgSHOL9Lh0fDlDXB4s3eSFPEx\nKnDFd1jrtO5ZOxF6/R1aXJtraJbLzYhxK5i75QjPDmpG0xoVijFRESltHr20EWmZ2bw7c+ufd4ZH\nw43fOI8/GaD2YSLFQAWu+Aa3CyY9AIvegQ53QbeHcw3NdrkZOX4lP689yNMDmzK4Q2wxJioipVGD\nquW5pm0Mny7a9ceOCr+LbghDf3KGLXwyAA5tLP4kRXyIClwp+7IzYOJtsOIz6P4o9H/J+ZDJKdTl\nZuSElfy05gBPDWjCsG5xxZysiJRWI/s0BAtv/JbLMITTRa6/U+Qmri/eBEV8iApcKdsyUmHcYGcG\n86XPQ6+ncy1uUzOyGTF+BZNXH+BvlzXhju51izlZESnNakaGcnPn2kxctpeth07kHFS5gVPk+gfC\nmL6wcUrxJiniI1TgStl1YBWM6gnbZ8Ggt6HLA7mGrtpzjIFvzmXq2oM8NaAJd/ZQcSsi5+7ei+oR\nFhTA339YR7bLnXNQ5fow7FeoVBfGD4GZ/3ImwIpIoVGBK2WPtbDoPfioN2Smwa0/Qtubcwx1uy3v\nz97GNe8tIDPbzfjhnXXnVkTOW1R4MH8f2JQF25J4bnIeQxAia8HtU6H1jTD7JafQTUsuvkRFyjj1\nPZKy5ehO+Pn/YPNUaNjf6UFZLirH0KU7k/nP1I0s3XmUy1pU499XtSQiLLB48xWRMuf69rXYnHiC\nj+btoH6VcG7uXCfnwMBQ52dUjTYw9Ql4Ox76PAut/gJ+uv8kciGMLWFrZMfHx9uEhARvpyGlzamj\nMPcVWPyBM4Gj9z+g4905jrddvfcYr/yymdmbD1M5PJjH+zbiuvgYTC5jc0VEzpXLbRn+aQKzNh/m\nk9va071BdN4vOLgWfnoE9iyCWh1hwCtQrUXxJCtlnU9+uKnAldItLdnpjjDvNTh1zPlz3yV/gwo1\n/hCWnuXi1/WJfJWwh7lbjlAxLJB7LqrHzZ3qEBrk76XkRaQsS83I5tr3FrDv2Cm+uacLDauWz/sF\nbjesGge/Pu38bGt0GXS6B+p0y3VyrEgB+OR/HhW4UvpYC3sTIGE0rP0WXBlQ9yLo8xxUb3k6LCPb\nxbKdR5m85gA/rtrPifRsakaGMqRDLYZ2jSNcK5OJSBHbezSNK99ZQGpGFg/3acjtXeMI8M9n+EFa\nMix8BxLGwKlkqNoC2g9zCt7yVYsncSlLVOCWBCpwJUdZ6bBzHmz5xfk6ugOCwqHlDRB/O1RrTrbL\nzebEVJbsSGLOliMs2p5EWqaLkEA/LmtenWvbxdCpbhR+fj75XhcRLzmQcoqnv1/HbxsSaV6zAi9e\n3ZLmNSPyf2HWKVj9lTNp9vAGZ1uNttCov3NXt2pzCNEqi5Ivn/zQK1CBa4zpB7wB+AMfWWtfPGt/\nMPAp0A5IAm6w1u707HsSGAa4gBHW2ml5nUsFrpCR6hSwB9fA/pVwYCUcWA3ZpyAgFBvXgxN1+rCp\n8qVsTTFsOniC1XuPsf7AcdKznFY7daLC6N4gmh4No+lcL0p3a0XEq6y1/Lz2IP+YtI6k1Ax6NanK\nRY2i6dkwmpiKYfm9GBLXweafYfM05y9YeD67K9V1xupWrAMVYiCiJpSvDqGREBzhFMD+mjzr41Tg\n5hhgjD+wGegD7AWWAkOstevPiLkXaGmtvdsYMxi4ylp7gzGmKTAO6ADUAH4DGlprXbmdTwVuKWIt\nWLezDK51nfXYOo+z0yErDZuZhisjFZt1Cpt5EpuRhs04ASePQNoRbOohzIn9BKTsJiA96fQpsvxD\nSQxryPagRiz2a82cjIbsTHFzIiP7dExooD/Na1agZUwkLWMiaFOrIrFR+XxgiIh4QUpaFm/N2MLP\naw+eXtK3fpVwGlYNp0r5EKpFhFC1QjAhAf4E+PsR4G8I8DME+PkR6G8I8PcjOCOZ0MOrCE1aR2jS\nOkKS1hOQuh8/d2aO57T+wVi/AKx/EPgFYv0CwD8I6x8IfoHg5+9MzvXzd/Z5Hv9vewDm98f+/mfs\n/317gOe5H8Yv0Pn3zNf5+Xv+DfjDuf7w2Pg744yNH+D59/dxx78//tM+k8M+k8e+nF6XQ6zxd/71\n8z9j+9nbfo8zZ2w7Y9+Zr71A5/qX9hwmTKvAzTHAmM7AM9bavp7nTwJYa/99Rsw0T8xCY0wAcBCI\nBp44M/bMuNzOpwK3BDu6y2lj83shy4UPb3FbwzHKkWQjSLSR7LZV2GOrssdGs8HGssNWB+NHdPlg\nqlYIoWqFEGpEhBBXuRxx0eHUrVyOmpGhGnYgIqWKtZZth1OZtekwc7ccYc/RNBJT0jmZmev9nzwZ\n3ERxghrmCFXMMSpwkgomjfKkUc5kEEA2gWQTiItAsgkwzr9BZOOHmwDc+OHGHzcBxnX68f++XGc9\nd+Nn3ATgOv16/zOOcTrelKxhkMXNbQ1uDBbzh09Me7rmNGdsc5wkhHYZHxTK+Y2BHf8e4JMfkAX5\nu21NYM8Zz/cCHXOLsdZmG2NSgCjP9kVnvbbm2ScwxgwHhnueZhhj1hYoe99TGTji7SQKXwqwP8+I\nHXkfoIxelwum65I7XZuc6brkrFRcl53AsuI/bam4Nl5wgddlYKElYl5kqrW2X6EdsJQoEQMTrbWj\ngFEAxpgEa228l1MqkXRtcqbrkjNdl9zp2uRM1yVnui6507XJma6L9xVkqZR9QK0znsd4tuUY4xmi\nEIEz2awgrxURERERKTQFKXCXAg2MMXHGmCBgMDDprJhJwK2ex9cCM6wzuHcSMNgYE2yMiQMaAEsK\nJ3URERERkT/Ld4iCZ0zt/cA0nDZhY6y164wxzwIJ1tpJwGjgM2PMViAZpwjGE/cVsB7IBu7Lq4OC\nx6jz/3bKPF2bnOm65EzXJXe6NjnTdcmZrkvudG1ypuviZSVuoQcRERERkQtRkCEKIiIiIiKlhgpc\nERERESlTSlSBa4zpZ4zZZIzZaox5wtv5eIsxZowx5tCZ/YCNMZWMMb8aY7Z4/q3ozRy9wRhTyxgz\n0xiz3hizzhjzoGe7ro0xIcaYJcaYVZ5r80/P9jhjzGLPe2qCZ6KozzHG+BtjVhhjJnue+/x1Mcbs\nNMasMcasNMYkeLb5/HsJwBgTaYyZaIzZaIzZYIzp7OvXxhjTyPN/5fev48aYkb5+XQCMMQ95fu6u\nNcaM8/w89vmfMd5WYgpcz5LA7wD9gabAEM9Sv77oE+DspsxPANOttQ2A6Z7nviYbeMRa2xToBNzn\n+T+iawMZwCXW2lZAa6CfMaYT8BLwmrW2PnAUGObFHL3pQWDDGc91XRwXW2tbn9GvU+8lxxvAVGtt\nY6AVzv8dn7421tpNnv8rrYF2QBrwHT5+XYwxNYERQLy1tjnOZPzB6GeM15WYAhfoAGy11m631mYC\n44ErvJyTV1hr5+B0ozjTFcBYz+OxwJXFmlQJYK09YK1d7nl8AudDpya6NlhHqudpoOfLApcAEz3b\nffLaGGNigAHAR57nBl2X3Pj8e8kYEwH0wOkOhLU201p7DF2bM/UCtllrd6HrAk5HqlDPOgBhwAH0\nM8brSlKBm9OSwH9a1teHVbXWHvA8PghU9WYy3maMqQO0ARajawOc/jP8SuAQ8CuwDThmrc32hPjq\ne+p14HHA7Xkeha4LOL8A/WKMWeZZLh30XgKIAw4DH3uGtXxkjCmHrs2ZBgPjPI99+rpYa/cBLwO7\ncQrbFJwVk/UzxstKUoErBeRZRMNn+7sZY/6/vfsL/WuO4zj+fPGj2DBjFzRLu2BcaJa0tcViiNYk\nRUISSWG5cMMNqcmVK3Eh7kxt9scdLjZCsTXzZ/7kwmYom6L5F0lvF+fzs18/m6zVzrfveT7q1+97\nzvlevH/vvp/ze5/PeZ/vZyawAXiwqn6aemzIuamqv9rtw7l0d0QW9BxS75KsBPZX1Y6+YxlBy6pq\nEV1b2H1JLpt6cMBjaQJYBDxbVRcDvzLttvuAc0PrJV0FrJ9+bIh5aT3H19NdGJ0NzODfLYbqwSgV\nuC7r+9/2JTkLoP3e33M8vUhyAl1x+2JVbWy7zc0U7XbqVmAJMKvdNoNhjqmlwKoke+janq6g668c\nel4mZ56oqv10vZSX4liCbrbtm6p6r22/TFfwmpvOtcD7VbWvbQ89LyuA3VX1fVX9CWykO+8M/hzT\nt1EqcP/PksBDNnU55DuAV3qMpRetd/J54LOqemrKIXOTzEkyq70+CbiKrkd5K93y2TDA3FTVw1U1\nt6rOpTunbKmqWxl4XpLMSHLK5GvgamAXjiWq6jvg6yTnt11X0q3GOfjcNLdwsD0BzMteYHGSk9v/\nqMnPy6DPMaNgpFYyS3IdXb/c5JLAa3oOqRdJXgKWA2cC+4BHgc3AOmAe8BVwU1VNfxBtrCVZBrwF\nfMzBfspH6Ppwh56bi+geZDie7sJ1XVU9nmQ+3czlbGAncFtV/dFfpP1Jshx4qKpWDj0v7e/f1DYn\ngLVVtSbJGQx8LAEkWUj3UOKJwJfAnbRxxYBz0y6G9gLzq+pA2zf4z0z7Wsab6b7pZydwN13P7WDP\nMaNgpApcSZIk6WiNUouCJEmSdNQscCVJkjRWLHAlSZI0VixwJUmSNFYscCVJkjRWLHAlSZI0Vixw\nJUmSNFYscCXpMJJsTrIjySdJ7mn77kryRZJtSZ5L8nTbPyfJhiTb28/SfqOXpOFyoQdJOowks6vq\nh7b88XbgGuAdYBHwM16R0PgAAAEYSURBVLAF+LCq7k+yFnimqt5OMg94raou6C14SRqwib4DkKQR\ntjrJDe31OcDtwJuTS5EmWQ+c146vAC7slqMH4NQkM6vql2MZsCTJAleSDinJcrqidUlV/ZbkDeBz\n4HCzsscBi6vq92MToSTpcOzBlaRDOw34sRW3C4DFwAzg8iSnJ5kAbpzy/teBByY3kiw8ptFKkv5h\ngStJh/YqMJHkM+BJ4F3gW+AJYBtdL+4e4EB7/2rgkiQfJfkUuPeYRyxJAnzITJKOyGRfbZvB3QS8\nUFWb+o5LknSQM7iSdGQeS/IBsAvYDWzuOR5J0jTO4EqSJGmsOIMrSZKksWKBK0mSpLFigStJkqSx\nYoErSZKksWKBK0mSpLHyN8XaR4Wm5F4XAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 701.25x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Bxg3K0undo39",
        "colab_type": "code",
        "outputId": "6e47aac2-52a1-4778-b5d8-5495ee190883",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 225
        }
      },
      "source": [
        "idade= sns.FacetGrid(dados, hue=\"y\", aspect=3);\n",
        "idade.map(plt.hist, \"age\").add_legend();\n",
        "idade.set(xlim=(0, 85));"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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SdUluTnJTkuta27i/juYmuSjJD5KsSXKofZLntufIxM9Pk5wy7v0CkOTv2vvt95N8rr0P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\nSZLUKwZcSZIk9YoBV5IkSb3y//VMbxu1ZUtQAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 701.25x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UKI2lhrido4C",
        "colab_type": "code",
        "outputId": "6ceda380-3ee9-46e4-d99c-e2aa45fb99cd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        }
      },
      "source": [
        "sns.countplot(dados['y'])"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f1a497fff98>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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9gEvn2dcWYEvvPkqSnp7jaUixJGmRM1QkSd0YKpKkbgwVSVI3hookqRtDRZLUjaEiSerG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\nSUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ySvXo0QKdo4F",
        "colab_type": "code",
        "outputId": "046254cd-7fd2-44ea-853e-6b01c8fec679",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        }
      },
      "source": [
        "sns.countplot(dados['marital'])"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f1a46de2860>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZcxIDqaWdo4I",
        "colab_type": "code",
        "outputId": "73e387e0-37f4-4121-9127-896baeeb93cc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        }
      },
      "source": [
        "sns.countplot(dados['education'])"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f1a46d359e8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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XCiVNltQmqW3lypW5FmtmZp1UESodQEdE3JnGr6YImefSZS3SzxVp+nJgSGn+wamsu/J3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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LmwCpuUIpHOa",
        "colab_type": "text"
      },
      "source": [
        "![logos](https://d1jnx9ba8s6j9r.cloudfront.net/blog/wp-content/uploads/2019/01/Classification-Random-Forest-Random-Forest-In-R-Edureka-2-381x300.png)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DPK0NgL4do4M",
        "colab_type": "text"
      },
      "source": [
        "**Tratamento dos dados**\n",
        "\n",
        "Porém para podermos utilizar os dados em algum algoritmo de aprendizado  precisamos que todos os valores sejam numericos, assim precisamos converter as colunas que são object.\n",
        "\n",
        "Existem maneiras de fazermos isto com o sklearn ou com o pandas.\n",
        "Vamos mostrar as duas:\n",
        "\n",
        "- **Pandas:** Com o pandas convertemos a coluna para category, apos isto podemos fazer a função cat.codes. \n",
        "- **Sklearn:** Temos que utilizar a classe LabelEnconder, ela funciona como a classe de normalização."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3i_9avsVdo4O",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "education = dados['education']"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0tnsuyY2do4R",
        "colab_type": "code",
        "outputId": "37af1d8e-d7ac-49bb-8163-3239af810fa7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 119
        }
      },
      "source": [
        "education.head()"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2627      tertiary\n",
              "13193    secondary\n",
              "7477     secondary\n",
              "22500     tertiary\n",
              "28587      primary\n",
              "Name: education, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vfDQ9t5_do4V",
        "colab_type": "code",
        "outputId": "146cf575-a8c5-4ea3-8e0e-664d6798532f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 119
        }
      },
      "source": [
        "#Pandas\n",
        "#Convertendo os dados para categorico\n",
        "educationConv = education.astype('category')\n",
        "\n",
        "# pegando o valores de cada categoria\n",
        "educationConv = educationConv.cat.codes\n",
        "educationConv[:5]"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2627     2\n",
              "13193    1\n",
              "7477     1\n",
              "22500    2\n",
              "28587    0\n",
              "dtype: int8"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vLLBrW_Ddo4Y",
        "colab_type": "code",
        "outputId": "13369ff9-bc6d-4aab-e3ce-d22a7fe9a295",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 119
        }
      },
      "source": [
        "education.head()"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2627      tertiary\n",
              "13193    secondary\n",
              "7477     secondary\n",
              "22500     tertiary\n",
              "28587      primary\n",
              "Name: education, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0NxejzYRdo4c",
        "colab_type": "code",
        "outputId": "17e8172c-16c2-4025-e367-6f631c0b2a0d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "#Sklearn\n",
        "from sklearn.preprocessing import LabelEncoder\n",
        "\n",
        "label = LabelEncoder()\n",
        "educationConv2 = label.fit_transform(education)\n",
        "educationConv2[:5]"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([2, 1, 1, 2, 0])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nq1njk4Ado4f",
        "colab_type": "text"
      },
      "source": [
        "Agora vamos usar um loop para podermos fazer a conversão de todos os dados do dataframe "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hR7E_zmldo4g",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "for coluna in dados:\n",
        "    if dados[coluna].dtype == object:\n",
        "        dados[coluna] = dados[coluna].astype('category').cat.codes"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RiCsCG44do4n",
        "colab_type": "text"
      },
      "source": [
        "Nota-se como o dataframe ficou após a conversão dos **dados** !"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LWkartgZdo4n",
        "colab_type": "code",
        "outputId": "91c079a1-55b8-45c2-9590-efd496a31916",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "dados.head()"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>job</th>\n",
              "      <th>marital</th>\n",
              "      <th>education</th>\n",
              "      <th>default</th>\n",
              "      <th>balance</th>\n",
              "      <th>housing</th>\n",
              "      <th>loan</th>\n",
              "      <th>contact</th>\n",
              "      <th>day</th>\n",
              "      <th>month</th>\n",
              "      <th>duration</th>\n",
              "      <th>campaign</th>\n",
              "      <th>pdays</th>\n",
              "      <th>previous</th>\n",
              "      <th>poutcome</th>\n",
              "      <th>y</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2627</th>\n",
              "      <td>48</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>489</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>13</td>\n",
              "      <td>6</td>\n",
              "      <td>60</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13193</th>\n",
              "      <td>49</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>13229</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>8</td>\n",
              "      <td>4</td>\n",
              "      <td>77</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7477</th>\n",
              "      <td>34</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>88</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>29</td>\n",
              "      <td>6</td>\n",
              "      <td>82</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22500</th>\n",
              "      <td>34</td>\n",
              "      <td>10</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>22</td>\n",
              "      <td>0</td>\n",
              "      <td>71</td>\n",
              "      <td>5</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28587</th>\n",
              "      <td>45</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>999</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>29</td>\n",
              "      <td>3</td>\n",
              "      <td>182</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       age  job  marital  education  ...  pdays  previous  poutcome  y\n",
              "2627    48    4        1          2  ...     -1         0         3  0\n",
              "13193   49    0        1          1  ...     -1         0         3  0\n",
              "7477    34    7        1          1  ...     -1         0         3  0\n",
              "22500   34   10        1          2  ...     -1         0         3  0\n",
              "28587   45    1        2          0  ...     -1         0         3  0\n",
              "\n",
              "[5 rows x 17 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4sWlF3L3do4q",
        "colab_type": "text"
      },
      "source": [
        "**Separando dados**\n",
        "\n",
        "Com os dados convertidos vamos separa X e y, e em treino e teste."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jtRpFYkXdo4r",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "dadosY1 = dados[dados['y']== 1]\n",
        "dadosY2 = dados[dados['y']== 0]"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Nztxp6nudo4s",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "dadosY2 = dadosY2.sample(len(dadosY1))"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "f6pcXUpvdo4u",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "dados2 = pd.concat([dadosY1,dadosY2])"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0LCk1R_bdo4w",
        "colab_type": "text"
      },
      "source": [
        "Apaga-se a coluna **y** (coluna alvo)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Hf2ZAEekdo4x",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "y = dados.y\n",
        "x = dados.drop('y',axis=1) "
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DjA522rVdo4y",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from sklearn.model_selection import train_test_split"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4q_Wwa1pdo40",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#Optamos por destinar 30% dos dados para treino\n",
        "np.random.seed(100)\n",
        "xTreino,xTeste,yTreino,yTeste = train_test_split(x,y, test_size=0.3)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BkG_6t_1do42",
        "colab_type": "text"
      },
      "source": [
        ""
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3RnOHvqOdo43",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from sklearn.ensemble import RandomForestClassifier"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xdxWLpDJdo45",
        "colab_type": "code",
        "outputId": "f7641635-b4de-4c83-a1bb-947c9774f3b7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        }
      },
      "source": [
        "rf = RandomForestClassifier(max_depth=4)\n",
        "rf.fit(xTreino,yTreino)"
      ],
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',\n",
              "                       max_depth=4, max_features='auto', max_leaf_nodes=None,\n",
              "                       min_impurity_decrease=0.0, min_impurity_split=None,\n",
              "                       min_samples_leaf=1, min_samples_split=2,\n",
              "                       min_weight_fraction_leaf=0.0, n_estimators=10,\n",
              "                       n_jobs=None, oob_score=False, random_state=None,\n",
              "                       verbose=0, warm_start=False)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jyTmO0jQdo48",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#NÃO RODAR\n",
        "#Predizendo dados \n",
        "preditos = rf.predict(xTeste)\n",
        "#Verificando modelo\n",
        "from sklearn.metrics import classification_report\n",
        "print(classification_report(preditos,yTeste))"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MChO9Ugcdo5A",
        "colab_type": "code",
        "outputId": "dd46b6bf-d4ea-4af1-9031-5b28a227fa22",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        }
      },
      "source": [
        "import sklearn.metrics as metrics\n",
        "# calculate the fpr and tpr for all thresholds of the classification\n",
        "probs = rf.predict_proba(xTeste)\n",
        "preds = probs[:,1]\n",
        "fpr, tpr, threshold = metrics.roc_curve(yTeste, preds)\n",
        "roc_auc = metrics.auc(fpr, tpr)\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "plt.title('Receiver Operating Characteristic')\n",
        "plt.plot(fpr, tpr, 'b', label = 'AUC = %0.2f' % roc_auc)\n",
        "plt.legend(loc = 'lower right')\n",
        "plt.plot([0, 1], [0, 1],'r--')\n",
        "plt.xlim([0, 1])\n",
        "plt.ylim([0, 1])\n",
        "plt.ylabel('True Positive Rate')\n",
        "plt.xlabel('False Positive Rate')\n",
        "plt.show()"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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OSjtbtthAkD/8IexInKug2bOt/Pfs2XD66fDoo7DnnmFH5aqoeBLF5VjzU3Pg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\nnHPOxfT/dZhGZeu6uhkAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tCVHgIPsdo5G",
        "colab_type": "code",
        "outputId": "bc5e0251-1930-43c3-f048-c0c87737a10d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        }
      },
      "source": [
        "print (\"\\nAcurácia de classificação = \"+str(100*roc_auc)+\"%\\n\")"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\n",
            "Acurácia de classificação = 93.89410406795561%\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JZiDrRMJdo5M",
        "colab_type": "text"
      },
      "source": [
        "![logos](https://cdn4.iconfinder.com/data/icons/robotics-and-artificial-intelligence/512/2-512.png)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "s8eIs6e9do5N",
        "colab_type": "text"
      },
      "source": [
        "Agora abordaremos a 2ª parte do conjunto de dados separada lá no começo<p>\n",
        "    Chamamos de \"**df**\"<p>\n",
        "        Realizaremos todo o tratamento de dados novamente para os mesmos<p>\n",
        "            Porém antes realizaremos uma análise dos dados"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1IgCv9PAdo5O",
        "colab_type": "code",
        "outputId": "1fa1a9ba-507e-405d-9075-a0e2dec6fbca",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "df.shape"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(25211, 17)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hPmNlWjbdo5U",
        "colab_type": "code",
        "outputId": "f020ab68-c8d5-4cf3-8bcf-c0aceb8e7beb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "df.head()"
      ],
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>job</th>\n",
              "      <th>marital</th>\n",
              "      <th>education</th>\n",
              "      <th>default</th>\n",
              "      <th>balance</th>\n",
              "      <th>housing</th>\n",
              "      <th>loan</th>\n",
              "      <th>contact</th>\n",
              "      <th>day</th>\n",
              "      <th>month</th>\n",
              "      <th>duration</th>\n",
              "      <th>campaign</th>\n",
              "      <th>pdays</th>\n",
              "      <th>previous</th>\n",
              "      <th>poutcome</th>\n",
              "      <th>y</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>12860</th>\n",
              "      <td>29</td>\n",
              "      <td>blue-collar</td>\n",
              "      <td>married</td>\n",
              "      <td>primary</td>\n",
              "      <td>no</td>\n",
              "      <td>707</td>\n",
              "      <td>no</td>\n",
              "      <td>no</td>\n",
              "      <td>cellular</td>\n",
              "      <td>7</td>\n",
              "      <td>jul</td>\n",
              "      <td>210</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>no</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6858</th>\n",
              "      <td>53</td>\n",
              "      <td>blue-collar</td>\n",
              "      <td>married</td>\n",
              "      <td>secondary</td>\n",
              "      <td>no</td>\n",
              "      <td>314</td>\n",
              "      <td>yes</td>\n",
              "      <td>no</td>\n",
              "      <td>unknown</td>\n",
              "      <td>28</td>\n",
              "      <td>may</td>\n",
              "      <td>184</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>no</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>360</th>\n",
              "      <td>48</td>\n",
              "      <td>management</td>\n",
              "      <td>married</td>\n",
              "      <td>tertiary</td>\n",
              "      <td>no</td>\n",
              "      <td>263</td>\n",
              "      <td>yes</td>\n",
              "      <td>no</td>\n",
              "      <td>unknown</td>\n",
              "      <td>5</td>\n",
              "      <td>may</td>\n",
              "      <td>350</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>no</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21115</th>\n",
              "      <td>60</td>\n",
              "      <td>management</td>\n",
              "      <td>married</td>\n",
              "      <td>tertiary</td>\n",
              "      <td>no</td>\n",
              "      <td>759</td>\n",
              "      <td>no</td>\n",
              "      <td>no</td>\n",
              "      <td>cellular</td>\n",
              "      <td>14</td>\n",
              "      <td>aug</td>\n",
              "      <td>136</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>no</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7748</th>\n",
              "      <td>45</td>\n",
              "      <td>technician</td>\n",
              "      <td>single</td>\n",
              "      <td>unknown</td>\n",
              "      <td>no</td>\n",
              "      <td>7108</td>\n",
              "      <td>yes</td>\n",
              "      <td>yes</td>\n",
              "      <td>unknown</td>\n",
              "      <td>30</td>\n",
              "      <td>may</td>\n",
              "      <td>1212</td>\n",
              "      <td>3</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>unknown</td>\n",
              "      <td>no</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       age          job  marital  education  ... pdays  previous poutcome   y\n",
              "12860   29  blue-collar  married    primary  ...    -1         0  unknown  no\n",
              "6858    53  blue-collar  married  secondary  ...    -1         0  unknown  no\n",
              "360     48   management  married   tertiary  ...    -1         0  unknown  no\n",
              "21115   60   management  married   tertiary  ...    -1         0  unknown  no\n",
              "7748    45   technician   single    unknown  ...    -1         0  unknown  no\n",
              "\n",
              "[5 rows x 17 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FzaUp0m2do5a",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "education = df['education']"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q4hTuXa7do5c",
        "colab_type": "code",
        "outputId": "83ee54cd-527c-447b-8378-0f3a9179df51",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 119
        }
      },
      "source": [
        "education.head()"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2627      tertiary\n",
              "13193    secondary\n",
              "7477     secondary\n",
              "22500     tertiary\n",
              "28587      primary\n",
              "Name: education, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "O76rtTJgdo5g",
        "colab_type": "code",
        "outputId": "49f9d11f-9b8d-4069-ed79-003fec22d55d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "#dessa vez usaremos somente o Sklearn\n",
        "from sklearn.preprocessing import LabelEncoder\n",
        "\n",
        "label = LabelEncoder()\n",
        "educationConv2 = label.fit_transform(education)\n",
        "educationConv2[:5]"
      ],
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([2, 1, 1, 2, 0])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ikSu7qlNdo5l",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "for coluna in df:\n",
        "    if df[coluna].dtype == object:\n",
        "        df[coluna] = df[coluna].astype('category').cat.codes"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "epolsRf1do5p",
        "colab_type": "code",
        "outputId": "6917feda-6990-43c5-bb3f-8018a526a7b6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "df.head()"
      ],
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>job</th>\n",
              "      <th>marital</th>\n",
              "      <th>education</th>\n",
              "      <th>default</th>\n",
              "      <th>balance</th>\n",
              "      <th>housing</th>\n",
              "      <th>loan</th>\n",
              "      <th>contact</th>\n",
              "      <th>day</th>\n",
              "      <th>month</th>\n",
              "      <th>duration</th>\n",
              "      <th>campaign</th>\n",
              "      <th>pdays</th>\n",
              "      <th>previous</th>\n",
              "      <th>poutcome</th>\n",
              "      <th>y</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>12860</th>\n",
              "      <td>29</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>707</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>4</td>\n",
              "      <td>210</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6858</th>\n",
              "      <td>53</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>314</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>28</td>\n",
              "      <td>6</td>\n",
              "      <td>184</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>360</th>\n",
              "      <td>48</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>263</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>6</td>\n",
              "      <td>350</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21115</th>\n",
              "      <td>60</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>759</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>14</td>\n",
              "      <td>0</td>\n",
              "      <td>136</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7748</th>\n",
              "      <td>45</td>\n",
              "      <td>9</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>7108</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>30</td>\n",
              "      <td>6</td>\n",
              "      <td>1212</td>\n",
              "      <td>3</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       age  job  marital  education  ...  pdays  previous  poutcome  y\n",
              "12860   29    1        1          0  ...     -1         0         3  0\n",
              "6858    53    1        1          1  ...     -1         0         3  0\n",
              "360     48    4        1          2  ...     -1         0         3  0\n",
              "21115   60    4        1          2  ...     -1         0         3  0\n",
              "7748    45    9        2          3  ...     -1         0         3  0\n",
              "\n",
              "[5 rows x 17 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "y59GvPVsdo5u",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "novo = df.drop('y',axis=1)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bM8UArofdo5w",
        "colab_type": "code",
        "outputId": "9340ac4a-2e00-4634-8c5f-5aa1cf8ababe",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "novo.head()"
      ],
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>job</th>\n",
              "      <th>marital</th>\n",
              "      <th>education</th>\n",
              "      <th>default</th>\n",
              "      <th>balance</th>\n",
              "      <th>housing</th>\n",
              "      <th>loan</th>\n",
              "      <th>contact</th>\n",
              "      <th>day</th>\n",
              "      <th>month</th>\n",
              "      <th>duration</th>\n",
              "      <th>campaign</th>\n",
              "      <th>pdays</th>\n",
              "      <th>previous</th>\n",
              "      <th>poutcome</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>12860</th>\n",
              "      <td>29</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>707</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>4</td>\n",
              "      <td>210</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6858</th>\n",
              "      <td>53</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>314</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>28</td>\n",
              "      <td>6</td>\n",
              "      <td>184</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>360</th>\n",
              "      <td>48</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>263</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>6</td>\n",
              "      <td>350</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21115</th>\n",
              "      <td>60</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>759</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>14</td>\n",
              "      <td>0</td>\n",
              "      <td>136</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7748</th>\n",
              "      <td>45</td>\n",
              "      <td>9</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>7108</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>30</td>\n",
              "      <td>6</td>\n",
              "      <td>1212</td>\n",
              "      <td>3</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       age  job  marital  education  ...  campaign  pdays  previous  poutcome\n",
              "12860   29    1        1          0  ...         1     -1         0         3\n",
              "6858    53    1        1          1  ...         2     -1         0         3\n",
              "360     48    4        1          2  ...         2     -1         0         3\n",
              "21115   60    4        1          2  ...         2     -1         0         3\n",
              "7748    45    9        2          3  ...         3     -1         0         3\n",
              "\n",
              "[5 rows x 16 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SHb23yv8do5y",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#Predizendo dados \n",
        "preditos = rf.predict(novo)\n",
        "perc_resp = rf.predict_proba(novo)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "A4zrNN6Bdo51",
        "colab_type": "code",
        "outputId": "96b97813-7c59-4ceb-a5b6-ff3241e0216c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "preditos"
      ],
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0, 0, 0, ..., 0, 0, 0], dtype=int8)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "838fz_Cpdo53",
        "colab_type": "code",
        "outputId": "3d2e5d3c-87f1-4e15-8382-6602b1272430",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        }
      },
      "source": [
        "perc_resp[:,0] #todas as linhas da 1ª coluna"
      ],
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0.97812055, 0.98783235, 0.98783235, ..., 0.98015447, 0.97325937,\n",
              "       0.98728167])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 51
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8oHE4UNGdo56",
        "colab_type": "code",
        "outputId": "643c8542-6043-4cb4-aa18-ae7c89472a11",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        }
      },
      "source": [
        "perc_resp[:,1] #todas as linhas da 2ª coluna"
      ],
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0.02187945, 0.01216765, 0.01216765, ..., 0.01984553, 0.02674063,\n",
              "       0.01271833])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tBzkOx7ddo59",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "novo['resp']=preditos"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ja20rGJ7do5_",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "novo['perc_resp1'] =perc_resp[:,0]"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KteitdOfdo6A",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "novo['perc_resp2'] = perc_resp[:,1] "
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0wyDNs06ZGwJ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "7b626f4b-a5d3-4c4d-eba0-c25a7d120a0a"
      },
      "source": [
        "novo.sort_values(by=['perc_resp2'],ascending=False)"
      ],
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>job</th>\n",
              "      <th>marital</th>\n",
              "      <th>education</th>\n",
              "      <th>default</th>\n",
              "      <th>balance</th>\n",
              "      <th>housing</th>\n",
              "      <th>loan</th>\n",
              "      <th>contact</th>\n",
              "      <th>day</th>\n",
              "      <th>month</th>\n",
              "      <th>duration</th>\n",
              "      <th>campaign</th>\n",
              "      <th>pdays</th>\n",
              "      <th>previous</th>\n",
              "      <th>poutcome</th>\n",
              "      <th>resp</th>\n",
              "      <th>perc_resp1</th>\n",
              "      <th>perc_resp2</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>24059</th>\n",
              "      <td>30</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1664</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>20</td>\n",
              "      <td>8</td>\n",
              "      <td>2016</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>0.364113</td>\n",
              "      <td>0.635887</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24095</th>\n",
              "      <td>30</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1310</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>27</td>\n",
              "      <td>8</td>\n",
              "      <td>3284</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>0.386929</td>\n",
              "      <td>0.613071</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>446</th>\n",
              "      <td>39</td>\n",
              "      <td>9</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>45248</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>1623</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>0.391965</td>\n",
              "      <td>0.608035</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24058</th>\n",
              "      <td>44</td>\n",
              "      <td>9</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1679</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>20</td>\n",
              "      <td>8</td>\n",
              "      <td>718</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>0.463547</td>\n",
              "      <td>0.536453</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8696</th>\n",
              "      <td>30</td>\n",
              "      <td>9</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>3107</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>1516</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>0.486674</td>\n",
              "      <td>0.513326</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8832</th>\n",
              "      <td>30</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>543</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>1449</td>\n",
              "      <td>6</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>0.486674</td>\n",
              "      <td>0.513326</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7732</th>\n",
              "      <td>34</td>\n",
              "      <td>9</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1451</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>30</td>\n",
              "      <td>6</td>\n",
              "      <td>1097</td>\n",
              "      <td>15</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>0.490452</td>\n",
              "      <td>0.509548</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17473</th>\n",
              "      <td>27</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>192</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>28</td>\n",
              "      <td>4</td>\n",
              "      <td>1076</td>\n",
              "      <td>17</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>0.490943</td>\n",
              "      <td>0.509057</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26366</th>\n",
              "      <td>30</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>501</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>20</td>\n",
              "      <td>7</td>\n",
              "      <td>994</td>\n",
              "      <td>1</td>\n",
              "      <td>177</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.500498</td>\n",
              "      <td>0.499502</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7953</th>\n",
              "      <td>27</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>416</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>30</td>\n",
              "      <td>6</td>\n",
              "      <td>1193</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.502392</td>\n",
              "      <td>0.497608</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12650</th>\n",
              "      <td>29</td>\n",
              "      <td>7</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>339</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>1576</td>\n",
              "      <td>3</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.502475</td>\n",
              "      <td>0.497525</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29895</th>\n",
              "      <td>32</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>678</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>1579</td>\n",
              "      <td>1</td>\n",
              "      <td>246</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.502814</td>\n",
              "      <td>0.497186</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8628</th>\n",
              "      <td>45</td>\n",
              "      <td>7</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1893</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>1259</td>\n",
              "      <td>6</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.507343</td>\n",
              "      <td>0.492657</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7674</th>\n",
              "      <td>46</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>14481</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>30</td>\n",
              "      <td>6</td>\n",
              "      <td>1269</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.508090</td>\n",
              "      <td>0.491910</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29747</th>\n",
              "      <td>30</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>1028</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>1294</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.513279</td>\n",
              "      <td>0.486721</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6626</th>\n",
              "      <td>26</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>6840</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>28</td>\n",
              "      <td>6</td>\n",
              "      <td>1560</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.513697</td>\n",
              "      <td>0.486303</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11838</th>\n",
              "      <td>29</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>908</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>20</td>\n",
              "      <td>5</td>\n",
              "      <td>1663</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.513861</td>\n",
              "      <td>0.486139</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9392</th>\n",
              "      <td>29</td>\n",
              "      <td>9</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>778</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>5</td>\n",
              "      <td>1994</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.513861</td>\n",
              "      <td>0.486139</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6741</th>\n",
              "      <td>29</td>\n",
              "      <td>6</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>3672</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>28</td>\n",
              "      <td>6</td>\n",
              "      <td>1210</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.515010</td>\n",
              "      <td>0.484990</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>569</th>\n",
              "      <td>28</td>\n",
              "      <td>7</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>5090</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>1297</td>\n",
              "      <td>3</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.515010</td>\n",
              "      <td>0.484990</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4377</th>\n",
              "      <td>30</td>\n",
              "      <td>9</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>3291</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>19</td>\n",
              "      <td>6</td>\n",
              "      <td>1218</td>\n",
              "      <td>3</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.515010</td>\n",
              "      <td>0.484990</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3500</th>\n",
              "      <td>29</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>10576</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>15</td>\n",
              "      <td>6</td>\n",
              "      <td>1224</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.515010</td>\n",
              "      <td>0.484990</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9381</th>\n",
              "      <td>26</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>710</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>5</td>\n",
              "      <td>1276</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.515174</td>\n",
              "      <td>0.484826</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7748</th>\n",
              "      <td>45</td>\n",
              "      <td>9</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>7108</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>30</td>\n",
              "      <td>6</td>\n",
              "      <td>1212</td>\n",
              "      <td>3</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.517447</td>\n",
              "      <td>0.482553</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29934</th>\n",
              "      <td>41</td>\n",
              "      <td>6</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>-94</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>1164</td>\n",
              "      <td>1</td>\n",
              "      <td>203</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.518081</td>\n",
              "      <td>0.481919</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16470</th>\n",
              "      <td>28</td>\n",
              "      <td>8</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>153</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>23</td>\n",
              "      <td>4</td>\n",
              "      <td>1124</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.518645</td>\n",
              "      <td>0.481355</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15597</th>\n",
              "      <td>25</td>\n",
              "      <td>7</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2311</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>21</td>\n",
              "      <td>4</td>\n",
              "      <td>1105</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.518645</td>\n",
              "      <td>0.481355</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15149</th>\n",
              "      <td>27</td>\n",
              "      <td>7</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1820</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>17</td>\n",
              "      <td>4</td>\n",
              "      <td>1027</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.518645</td>\n",
              "      <td>0.481355</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21117</th>\n",
              "      <td>30</td>\n",
              "      <td>9</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>289</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>14</td>\n",
              "      <td>0</td>\n",
              "      <td>1184</td>\n",
              "      <td>4</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.518645</td>\n",
              "      <td>0.481355</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13302</th>\n",
              "      <td>26</td>\n",
              "      <td>9</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>370</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>8</td>\n",
              "      <td>4</td>\n",
              "      <td>1061</td>\n",
              "      <td>4</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.518645</td>\n",
              "      <td>0.481355</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>29601</th>\n",
              "      <td>34</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>261</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>88</td>\n",
              "      <td>5</td>\n",
              "      <td>251</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.991847</td>\n",
              "      <td>0.008153</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29420</th>\n",
              "      <td>33</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>644</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>124</td>\n",
              "      <td>2</td>\n",
              "      <td>271</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.991847</td>\n",
              "      <td>0.008153</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29470</th>\n",
              "      <td>47</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>152</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>193</td>\n",
              "      <td>3</td>\n",
              "      <td>271</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.991847</td>\n",
              "      <td>0.008153</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29711</th>\n",
              "      <td>55</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>781</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>112</td>\n",
              "      <td>3</td>\n",
              "      <td>270</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.991847</td>\n",
              "      <td>0.008153</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29304</th>\n",
              "      <td>38</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>569</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>164</td>\n",
              "      <td>2</td>\n",
              "      <td>272</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.991847</td>\n",
              "      <td>0.008153</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29181</th>\n",
              "      <td>60</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>174</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>157</td>\n",
              "      <td>2</td>\n",
              "      <td>252</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.991847</td>\n",
              "      <td>0.008153</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29236</th>\n",
              "      <td>43</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1109</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>115</td>\n",
              "      <td>3</td>\n",
              "      <td>264</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.991847</td>\n",
              "      <td>0.008153</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29258</th>\n",
              "      <td>31</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>783</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>221</td>\n",
              "      <td>2</td>\n",
              "      <td>272</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.991847</td>\n",
              "      <td>0.008153</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29180</th>\n",
              "      <td>45</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>474</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>190</td>\n",
              "      <td>4</td>\n",
              "      <td>264</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.991847</td>\n",
              "      <td>0.008153</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29969</th>\n",
              "      <td>51</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>362</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>108</td>\n",
              "      <td>4</td>\n",
              "      <td>272</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.991847</td>\n",
              "      <td>0.008153</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29774</th>\n",
              "      <td>38</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>221</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>93</td>\n",
              "      <td>2</td>\n",
              "      <td>274</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.991847</td>\n",
              "      <td>0.008153</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29981</th>\n",
              "      <td>32</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>557</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>210</td>\n",
              "      <td>2</td>\n",
              "      <td>253</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.991847</td>\n",
              "      <td>0.008153</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29537</th>\n",
              "      <td>35</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>1891</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>188</td>\n",
              "      <td>3</td>\n",
              "      <td>270</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.991847</td>\n",
              "      <td>0.008153</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29445</th>\n",
              "      <td>50</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1158</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>116</td>\n",
              "      <td>3</td>\n",
              "      <td>265</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.991847</td>\n",
              "      <td>0.008153</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29275</th>\n",
              "      <td>37</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>230</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>120</td>\n",
              "      <td>2</td>\n",
              "      <td>272</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.991847</td>\n",
              "      <td>0.008153</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29409</th>\n",
              "      <td>36</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>806</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>106</td>\n",
              "      <td>2</td>\n",
              "      <td>259</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.991847</td>\n",
              "      <td>0.008153</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29476</th>\n",
              "      <td>35</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>273</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.992263</td>\n",
              "      <td>0.007737</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29169</th>\n",
              "      <td>34</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>50</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>173</td>\n",
              "      <td>1</td>\n",
              "      <td>258</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.992263</td>\n",
              "      <td>0.007737</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29065</th>\n",
              "      <td>34</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>-271</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>90</td>\n",
              "      <td>1</td>\n",
              "      <td>252</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.992263</td>\n",
              "      <td>0.007737</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29989</th>\n",
              "      <td>33</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>-241</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>117</td>\n",
              "      <td>1</td>\n",
              "      <td>253</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.992263</td>\n",
              "      <td>0.007737</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29545</th>\n",
              "      <td>31</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>124</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>343</td>\n",
              "      <td>1</td>\n",
              "      <td>264</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.992263</td>\n",
              "      <td>0.007737</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29564</th>\n",
              "      <td>46</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>-319</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>256</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.992263</td>\n",
              "      <td>0.007737</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29879</th>\n",
              "      <td>42</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>30</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>98</td>\n",
              "      <td>1</td>\n",
              "      <td>266</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.992263</td>\n",
              "      <td>0.007737</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29395</th>\n",
              "      <td>31</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>112</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>159</td>\n",
              "      <td>2</td>\n",
              "      <td>271</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.992263</td>\n",
              "      <td>0.007737</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29705</th>\n",
              "      <td>53</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>-211</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>195</td>\n",
              "      <td>6</td>\n",
              "      <td>251</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.992263</td>\n",
              "      <td>0.007737</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29519</th>\n",
              "      <td>48</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>69</td>\n",
              "      <td>1</td>\n",
              "      <td>252</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.992263</td>\n",
              "      <td>0.007737</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29643</th>\n",
              "      <td>42</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>-97</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>216</td>\n",
              "      <td>4</td>\n",
              "      <td>271</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.992263</td>\n",
              "      <td>0.007737</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29845</th>\n",
              "      <td>58</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1640</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>72</td>\n",
              "      <td>6</td>\n",
              "      <td>274</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.992378</td>\n",
              "      <td>0.007622</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29143</th>\n",
              "      <td>37</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>164</td>\n",
              "      <td>1</td>\n",
              "      <td>250</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.992794</td>\n",
              "      <td>0.007206</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29184</th>\n",
              "      <td>57</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>11</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>261</td>\n",
              "      <td>1</td>\n",
              "      <td>265</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.992794</td>\n",
              "      <td>0.007206</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>25211 rows × 19 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       age  job  marital  education  ...  poutcome  resp  perc_resp1  perc_resp2\n",
              "24059   30    1        1          1  ...         3     1    0.364113    0.635887\n",
              "24095   30    0        1          1  ...         3     1    0.386929    0.613071\n",
              "446     39    9        2          3  ...         3     1    0.391965    0.608035\n",
              "24058   44    9        2          1  ...         3     1    0.463547    0.536453\n",
              "8696    30    9        2          1  ...         3     1    0.486674    0.513326\n",
              "8832    30    6        1          2  ...         3     1    0.486674    0.513326\n",
              "7732    34    9        0          1  ...         3     1    0.490452    0.509548\n",
              "17473   27    0        2          1  ...         3     1    0.490943    0.509057\n",
              "26366   30    1        1          1  ...         0     0    0.500498    0.499502\n",
              "7953    27    1        1          0  ...         3     0    0.502392    0.497608\n",
              "12650   29    7        2          0  ...         3     0    0.502475    0.497525\n",
              "29895   32    0        2          1  ...         0     0    0.502814    0.497186\n",
              "8628    45    7        2          0  ...         3     0    0.507343    0.492657\n",
              "7674    46    4        0          2  ...         3     0    0.508090    0.491910\n",
              "29747   30    4        2          2  ...         3     0    0.513279    0.486721\n",
              "6626    26    4        2          2  ...         3     0    0.513697    0.486303\n",
              "11838   29    1        2          1  ...         3     0    0.513861    0.486139\n",
              "9392    29    9        2          1  ...         3     0    0.513861    0.486139\n",
              "6741    29    6        2          1  ...         3     0    0.515010    0.484990\n",
              "569     28    7        2          1  ...         3     0    0.515010    0.484990\n",
              "4377    30    9        2          2  ...         3     0    0.515010    0.484990\n",
              "3500    29    4        1          2  ...         3     0    0.515010    0.484990\n",
              "9381    26    0        1          1  ...         3     0    0.515174    0.484826\n",
              "7748    45    9        2          3  ...         3     0    0.517447    0.482553\n",
              "29934   41    6        2          2  ...         0     0    0.518081    0.481919\n",
              "16470   28    8        2          1  ...         3     0    0.518645    0.481355\n",
              "15597   25    7        2          1  ...         3     0    0.518645    0.481355\n",
              "15149   27    7        2          1  ...         3     0    0.518645    0.481355\n",
              "21117   30    9        1          1  ...         3     0    0.518645    0.481355\n",
              "13302   26    9        1          1  ...         3     0    0.518645    0.481355\n",
              "...    ...  ...      ...        ...  ...       ...   ...         ...         ...\n",
              "29601   34    1        1          1  ...         0     0    0.991847    0.008153\n",
              "29420   33    4        1          2  ...         0     0    0.991847    0.008153\n",
              "29470   47    1        2          1  ...         0     0    0.991847    0.008153\n",
              "29711   55    1        1          0  ...         0     0    0.991847    0.008153\n",
              "29304   38    0        2          1  ...         0     0    0.991847    0.008153\n",
              "29181   60    5        1          0  ...         0     0    0.991847    0.008153\n",
              "29236   43    1        1          1  ...         0     0    0.991847    0.008153\n",
              "29258   31    4        2          1  ...         0     0    0.991847    0.008153\n",
              "29180   45    4        1          2  ...         0     0    0.991847    0.008153\n",
              "29969   51    1        1          0  ...         0     0    0.991847    0.008153\n",
              "29774   38    0        2          1  ...         0     0    0.991847    0.008153\n",
              "29981   32    1        1          1  ...         0     0    0.991847    0.008153\n",
              "29537   35    4        2          2  ...         0     0    0.991847    0.008153\n",
              "29445   50    3        2          0  ...         0     0    0.991847    0.008153\n",
              "29275   37    4        2          2  ...         0     0    0.991847    0.008153\n",
              "29409   36    4        1          2  ...         0     0    0.991847    0.008153\n",
              "29476   35    0        2          1  ...         0     0    0.992263    0.007737\n",
              "29169   34    0        1          1  ...         0     0    0.992263    0.007737\n",
              "29065   34    1        1          1  ...         0     0    0.992263    0.007737\n",
              "29989   33    1        1          1  ...         0     0    0.992263    0.007737\n",
              "29545   31    1        1          0  ...         0     0    0.992263    0.007737\n",
              "29564   46    4        1          2  ...         0     0    0.992263    0.007737\n",
              "29879   42    0        2          1  ...         0     0    0.992263    0.007737\n",
              "29395   31    4        2          2  ...         0     0    0.992263    0.007737\n",
              "29705   53    1        1          0  ...         0     0    0.992263    0.007737\n",
              "29519   48    0        1          0  ...         0     0    0.992263    0.007737\n",
              "29643   42    1        1          0  ...         0     0    0.992263    0.007737\n",
              "29845   58    5        2          1  ...         0     0    0.992378    0.007622\n",
              "29143   37    4        1          1  ...         0     0    0.992794    0.007206\n",
              "29184   57    0        1          1  ...         0     0    0.992794    0.007206\n",
              "\n",
              "[25211 rows x 19 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8d6eDEJ3do6B",
        "colab_type": "code",
        "outputId": "97add3f3-613c-4067-c839-9cf4cbf41e6a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 689
        }
      },
      "source": [
        "novo.head(20)"
      ],
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>job</th>\n",
              "      <th>marital</th>\n",
              "      <th>education</th>\n",
              "      <th>default</th>\n",
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              "      <th>day</th>\n",
              "      <th>month</th>\n",
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              "      <th>campaign</th>\n",
              "      <th>pdays</th>\n",
              "      <th>previous</th>\n",
              "      <th>poutcome</th>\n",
              "      <th>resp</th>\n",
              "      <th>perc_resp1</th>\n",
              "      <th>perc_resp2</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>12860</th>\n",
              "      <td>29</td>\n",
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              "      <td>210</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.978121</td>\n",
              "      <td>0.021879</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6858</th>\n",
              "      <td>53</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>314</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>28</td>\n",
              "      <td>6</td>\n",
              "      <td>184</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.987832</td>\n",
              "      <td>0.012168</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>360</th>\n",
              "      <td>48</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>263</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>6</td>\n",
              "      <td>350</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.987832</td>\n",
              "      <td>0.012168</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21115</th>\n",
              "      <td>60</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>759</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>14</td>\n",
              "      <td>0</td>\n",
              "      <td>136</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.979851</td>\n",
              "      <td>0.020149</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7748</th>\n",
              "      <td>45</td>\n",
              "      <td>9</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>7108</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>30</td>\n",
              "      <td>6</td>\n",
              "      <td>1212</td>\n",
              "      <td>3</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.517447</td>\n",
              "      <td>0.482553</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22840</th>\n",
              "      <td>53</td>\n",
              "      <td>9</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>925</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>25</td>\n",
              "      <td>0</td>\n",
              "      <td>930</td>\n",
              "      <td>3</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.561418</td>\n",
              "      <td>0.438582</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20685</th>\n",
              "      <td>44</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>781</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>12</td>\n",
              "      <td>0</td>\n",
              "      <td>112</td>\n",
              "      <td>5</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.980428</td>\n",
              "      <td>0.019572</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13452</th>\n",
              "      <td>35</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>9</td>\n",
              "      <td>4</td>\n",
              "      <td>112</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.980312</td>\n",
              "      <td>0.019688</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>501</th>\n",
              "      <td>32</td>\n",
              "      <td>9</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>-170</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>46</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.987583</td>\n",
              "      <td>0.012417</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3252</th>\n",
              "      <td>49</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1530</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>15</td>\n",
              "      <td>6</td>\n",
              "      <td>173</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.986601</td>\n",
              "      <td>0.013399</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20440</th>\n",
              "      <td>54</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>212</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>12</td>\n",
              "      <td>0</td>\n",
              "      <td>81</td>\n",
              "      <td>4</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.979851</td>\n",
              "      <td>0.020149</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16408</th>\n",
              "      <td>57</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>246</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>23</td>\n",
              "      <td>4</td>\n",
              "      <td>322</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.980428</td>\n",
              "      <td>0.019572</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27163</th>\n",
              "      <td>52</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2594</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>21</td>\n",
              "      <td>7</td>\n",
              "      <td>425</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.973122</td>\n",
              "      <td>0.026878</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14202</th>\n",
              "      <td>27</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>3638</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>11</td>\n",
              "      <td>4</td>\n",
              "      <td>271</td>\n",
              "      <td>5</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.979379</td>\n",
              "      <td>0.020621</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3523</th>\n",
              "      <td>48</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>559</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>15</td>\n",
              "      <td>6</td>\n",
              "      <td>1231</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.573946</td>\n",
              "      <td>0.426054</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26279</th>\n",
              "      <td>35</td>\n",
              "      <td>7</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>5551</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>20</td>\n",
              "      <td>7</td>\n",
              "      <td>258</td>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.976859</td>\n",
              "      <td>0.023141</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3518</th>\n",
              "      <td>59</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1423</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>15</td>\n",
              "      <td>6</td>\n",
              "      <td>584</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.913412</td>\n",
              "      <td>0.086588</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18020</th>\n",
              "      <td>52</td>\n",
              "      <td>10</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>959</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>30</td>\n",
              "      <td>4</td>\n",
              "      <td>694</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.624885</td>\n",
              "      <td>0.375115</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3654</th>\n",
              "      <td>43</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>-228</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>16</td>\n",
              "      <td>6</td>\n",
              "      <td>122</td>\n",
              "      <td>2</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.988160</td>\n",
              "      <td>0.011840</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25798</th>\n",
              "      <td>32</td>\n",
              "      <td>9</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>432</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>19</td>\n",
              "      <td>7</td>\n",
              "      <td>164</td>\n",
              "      <td>2</td>\n",
              "      <td>195</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0.979162</td>\n",
              "      <td>0.020838</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       age  job  marital  education  ...  poutcome  resp  perc_resp1  perc_resp2\n",
              "12860   29    1        1          0  ...         3     0    0.978121    0.021879\n",
              "6858    53    1        1          1  ...         3     0    0.987832    0.012168\n",
              "360     48    4        1          2  ...         3     0    0.987832    0.012168\n",
              "21115   60    4        1          2  ...         3     0    0.979851    0.020149\n",
              "7748    45    9        2          3  ...         3     0    0.517447    0.482553\n",
              "22840   53    9        2          1  ...         3     0    0.561418    0.438582\n",
              "20685   44    4        1          1  ...         3     0    0.980428    0.019572\n",
              "13452   35    0        1          1  ...         3     0    0.980312    0.019688\n",
              "501     32    9        2          3  ...         3     0    0.987583    0.012417\n",
              "3252    49    0        1          1  ...         3     0    0.986601    0.013399\n",
              "20440   54    3        1          0  ...         3     0    0.979851    0.020149\n",
              "16408   57    4        1          2  ...         3     0    0.980428    0.019572\n",
              "27163   52    2        1          0  ...         3     0    0.973122    0.026878\n",
              "14202   27    0        2          1  ...         3     0    0.979379    0.020621\n",
              "3523    48    1        1          0  ...         3     0    0.573946    0.426054\n",
              "26279   35    7        2          1  ...         3     0    0.976859    0.023141\n",
              "3518    59    5        1          0  ...         3     0    0.913412    0.086588\n",
              "18020   52   10        1          0  ...         3     0    0.624885    0.375115\n",
              "3654    43    4        2          1  ...         3     0    0.988160    0.011840\n",
              "25798   32    9        1          2  ...         1     0    0.979162    0.020838\n",
              "\n",
              "[20 rows x 19 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_mBuDYBUdo6E",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}